Pandas2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.25 0.5  0.75 1.  ]\n",
      "Index(['a', 'b', 'c', 'd'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "data = pd.Series([0.25,0.5,0.75,1.0],index=['a','b','c','d'])\n",
    "print(data.values)\n",
    "print(data.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    0.25\n",
       "b    0.50\n",
       "c    0.75\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['a':'c']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dictionaries in pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades_dict={'A':4,'A+':3.5,'B':3,'B+':2.5,'C':5}\n",
    "marks_dict={'A':85,'A+':80,'B':75,'B+':70,'C':60}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades=pd.Series(grades_dict)\n",
    "marks=pd.Series(marks_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A     4.0\n",
      "A+    3.5\n",
      "B     3.0\n",
      "B+    2.5\n",
      "C     5.0\n",
      "dtype: float64\n",
      "A     85\n",
      "A+    80\n",
      "B     75\n",
      "B+    70\n",
      "C     60\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(grades)\n",
    "print(marks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4. , 3.5, 3. , 2.5, 5. ])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grades.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([85, 80, 75, 70, 60], dtype=int64)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "85"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A+    80\n",
       "B     75\n",
       "B+    70\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "marks[1:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "D = pd.DataFrame({'Marks': marks,'Grades':grades})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>60</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades\n",
       "A      85     4.0\n",
       "A+     80     3.5\n",
       "B      75     3.0\n",
       "B+     70     2.5\n",
       "C      60     5.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[85. ,  4. ],\n",
       "       [80. ,  3.5],\n",
       "       [75. ,  3. ],\n",
       "       [70. ,  2.5],\n",
       "       [60. ,  5. ]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.values[2,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Marks', 'Grades'], dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "D['ScaleMarks'] = 100*(D['Marks']/90) # adding columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "      <th>ScaleMarks</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "      <td>94.444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "      <td>88.888889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "      <td>83.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "      <td>77.777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>60</td>\n",
       "      <td>5.0</td>\n",
       "      <td>66.666667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades  ScaleMarks\n",
       "A      85     4.0   94.444444\n",
       "A+     80     3.5   88.888889\n",
       "B      75     3.0   83.333333\n",
       "B+     70     2.5   77.777778\n",
       "C      60     5.0   66.666667"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Deleting Columns\n",
    "del D['ScaleMarks']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>60</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades\n",
       "A      85     4.0\n",
       "A+     80     3.5\n",
       "B      75     3.0\n",
       "B+     70     2.5\n",
       "C      60     5.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = D[D['Marks']>60]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades\n",
       "A      85     4.0\n",
       "A+     80     3.5\n",
       "B      75     3.0\n",
       "B+     70     2.5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to remove NaN vlaues "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = pd.DataFrame([{'a':1,'b':4},{'b':-3,'c':9}])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-3</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     a  b    c\n",
       "0  1.0  4  NaN\n",
       "1  NaN -3  9.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-3</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     a  b    c\n",
       "0  1.0  4  0.0\n",
       "1  0.0 -3  9.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filling NaN with some value\n",
    "A.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# It drops all the NaN values, but sometime Data can be lost due to this\n",
    "A.dropna?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## explicit index: use loc, implicit index use iloc\n",
    "data[1]: explicit index, data[1:3] implicit index "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "Dta = pd.Series(['a','b','c'],index=[1,3,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'a'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Dta[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    b\n",
       "5    c\n",
       "dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Dta[1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    a\n",
       "3    b\n",
       "dtype: object"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Dta.loc[1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    b\n",
       "5    c\n",
       "dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Dta.iloc[1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Marks     75.0\n",
       "Grades     3.0\n",
       "Name: B, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.iloc[2,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>60</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades\n",
       "A      85     4.0\n",
       "A+     80     3.5\n",
       "B      75     3.0\n",
       "B+     70     2.5\n",
       "C      60     5.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Marks</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>60</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B+</th>\n",
       "      <td>70</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>75</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A+</th>\n",
       "      <td>80</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>85</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Marks  Grades\n",
       "C      60     5.0\n",
       "B+     70     2.5\n",
       "B      75     3.0\n",
       "A+     80     3.5\n",
       "A      85     4.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D.iloc[::-1,:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## handling missing data from sklearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.impute import SimpleImputer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('covid19Vaccination.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>DATE_</th>\n",
       "      <th>SEQID</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>_1DOSE</th>\n",
       "      <th>_2DOSE</th>\n",
       "      <th>_TOTAL</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>438178</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Uşak</td>\n",
       "      <td>Usak</td>\n",
       "      <td>169159</td>\n",
       "      <td>81055</td>\n",
       "      <td>250214</td>\n",
       "      <td>369433</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>438097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>438179</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Van</td>\n",
       "      <td>Van</td>\n",
       "      <td>236641</td>\n",
       "      <td>91208</td>\n",
       "      <td>327849</td>\n",
       "      <td>1149342</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>438098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>438180</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Yalova</td>\n",
       "      <td>Yalova</td>\n",
       "      <td>129888</td>\n",
       "      <td>65920</td>\n",
       "      <td>195808</td>\n",
       "      <td>276050</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>438181</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Yozgat</td>\n",
       "      <td>Yozgat</td>\n",
       "      <td>151825</td>\n",
       "      <td>81924</td>\n",
       "      <td>233749</td>\n",
       "      <td>419095</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>438100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>438182</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Zonguldak</td>\n",
       "      <td>Zonguldak</td>\n",
       "      <td>275433</td>\n",
       "      <td>139382</td>\n",
       "      <td>414815</td>\n",
       "      <td>591204</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>438101</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID               DATE_  SEQID            CITY      CITY2  _1DOSE  \\\n",
       "0   438102 2021-06-26 22:41:31   5412           Adana      Adana  784464   \n",
       "1   438103 2021-06-26 22:41:31   5412        Adıyaman   Adiyaman  170847   \n",
       "2   438104 2021-06-26 22:41:31   5412  Afyonkarahisar      Afyon  292611   \n",
       "3   438105 2021-06-26 22:41:31   5412            Ağrı       Agri   94807   \n",
       "4   438106 2021-06-26 22:41:31   5412         Aksaray    Aksaray  131889   \n",
       "..     ...                 ...    ...             ...        ...     ...   \n",
       "76  438178 2021-06-26 22:41:31   5412            Uşak       Usak  169159   \n",
       "77  438179 2021-06-26 22:41:31   5412             Van        Van  236641   \n",
       "78  438180 2021-06-26 22:41:31   5412          Yalova     Yalova  129888   \n",
       "79  438181 2021-06-26 22:41:31   5412          Yozgat     Yozgat  151825   \n",
       "80  438182 2021-06-26 22:41:31   5412       Zonguldak  Zonguldak  275433   \n",
       "\n",
       "    _2DOSE   _TOTAL  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0   355404  1139868     2258718          15           0          15  438021  \n",
       "1    77955   248802      632459           2           0           2  438022  \n",
       "2   138934   431545      736912           8           0           8  438023  \n",
       "3    41146   135953      535435           0           0           0  438024  \n",
       "4    62603   194492      423011           3           0           3  438025  \n",
       "..     ...      ...         ...         ...         ...         ...     ...  \n",
       "76   81055   250214      369433           6           0           6  438097  \n",
       "77   91208   327849     1149342           5           0           5  438098  \n",
       "78   65920   195808      276050           2           0           2  438099  \n",
       "79   81924   233749      419095           1           0           1  438100  \n",
       "80  139382   414815      591204           6           0           6  438101  \n",
       "\n",
       "[81 rows x 13 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>DATE_</th>\n",
       "      <th>SEQID</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>_1DOSE</th>\n",
       "      <th>_2DOSE</th>\n",
       "      <th>_TOTAL</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>438107</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Amasya</td>\n",
       "      <td>Amasya</td>\n",
       "      <td>169285</td>\n",
       "      <td>87322</td>\n",
       "      <td>256607</td>\n",
       "      <td>335494</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>438026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>438108</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Ankara</td>\n",
       "      <td>Ankara</td>\n",
       "      <td>2652085</td>\n",
       "      <td>1241906</td>\n",
       "      <td>3893991</td>\n",
       "      <td>5663322</td>\n",
       "      <td>91</td>\n",
       "      <td>6</td>\n",
       "      <td>97</td>\n",
       "      <td>438027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>438109</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Antalya</td>\n",
       "      <td>Antalya</td>\n",
       "      <td>1055350</td>\n",
       "      <td>530415</td>\n",
       "      <td>1585765</td>\n",
       "      <td>2548308</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>33</td>\n",
       "      <td>438028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>438110</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Ardahan</td>\n",
       "      <td>Ardahan</td>\n",
       "      <td>34629</td>\n",
       "      <td>18642</td>\n",
       "      <td>53271</td>\n",
       "      <td>96161</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>438111</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Artvin</td>\n",
       "      <td>Artvin</td>\n",
       "      <td>80554</td>\n",
       "      <td>43132</td>\n",
       "      <td>123686</td>\n",
       "      <td>169501</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>438112</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Aydın</td>\n",
       "      <td>Aydin</td>\n",
       "      <td>555807</td>\n",
       "      <td>293208</td>\n",
       "      <td>849015</td>\n",
       "      <td>1119084</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>438031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>438113</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Balıkesir</td>\n",
       "      <td>Balikesir</td>\n",
       "      <td>661424</td>\n",
       "      <td>359073</td>\n",
       "      <td>1020497</td>\n",
       "      <td>1240285</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>438032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>438114</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bartın</td>\n",
       "      <td>Bartin</td>\n",
       "      <td>96816</td>\n",
       "      <td>49086</td>\n",
       "      <td>145902</td>\n",
       "      <td>198979</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>438115</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Batman</td>\n",
       "      <td>Batman</td>\n",
       "      <td>108989</td>\n",
       "      <td>48556</td>\n",
       "      <td>157545</td>\n",
       "      <td>620278</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>438034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>438116</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bayburt</td>\n",
       "      <td>Bayburt</td>\n",
       "      <td>24128</td>\n",
       "      <td>13155</td>\n",
       "      <td>37283</td>\n",
       "      <td>81910</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>438117</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bilecik</td>\n",
       "      <td>Bilecik</td>\n",
       "      <td>108385</td>\n",
       "      <td>49145</td>\n",
       "      <td>157530</td>\n",
       "      <td>218717</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>438118</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bingöl</td>\n",
       "      <td>Bingol</td>\n",
       "      <td>57366</td>\n",
       "      <td>30771</td>\n",
       "      <td>88137</td>\n",
       "      <td>281768</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>438037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>438119</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bitlis</td>\n",
       "      <td>Bitlis</td>\n",
       "      <td>51093</td>\n",
       "      <td>23726</td>\n",
       "      <td>74819</td>\n",
       "      <td>350994</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>438120</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Bolu</td>\n",
       "      <td>Bolu</td>\n",
       "      <td>151636</td>\n",
       "      <td>75911</td>\n",
       "      <td>227547</td>\n",
       "      <td>314802</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>438039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>438121</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>5412</td>\n",
       "      <td>Burdur</td>\n",
       "      <td>Burdur</td>\n",
       "      <td>128036</td>\n",
       "      <td>66955</td>\n",
       "      <td>194991</td>\n",
       "      <td>267092</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438040</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID               DATE_  SEQID            CITY      CITY2   _1DOSE  \\\n",
       "0   438102 2021-06-26 22:41:31   5412           Adana      Adana   784464   \n",
       "1   438103 2021-06-26 22:41:31   5412        Adıyaman   Adiyaman   170847   \n",
       "2   438104 2021-06-26 22:41:31   5412  Afyonkarahisar      Afyon   292611   \n",
       "3   438105 2021-06-26 22:41:31   5412            Ağrı       Agri    94807   \n",
       "4   438106 2021-06-26 22:41:31   5412         Aksaray    Aksaray   131889   \n",
       "5   438107 2021-06-26 22:41:31   5412          Amasya     Amasya   169285   \n",
       "6   438108 2021-06-26 22:41:31   5412          Ankara     Ankara  2652085   \n",
       "7   438109 2021-06-26 22:41:31   5412         Antalya    Antalya  1055350   \n",
       "8   438110 2021-06-26 22:41:31   5412         Ardahan    Ardahan    34629   \n",
       "9   438111 2021-06-26 22:41:31   5412          Artvin     Artvin    80554   \n",
       "10  438112 2021-06-26 22:41:31   5412           Aydın      Aydin   555807   \n",
       "11  438113 2021-06-26 22:41:31   5412       Balıkesir  Balikesir   661424   \n",
       "12  438114 2021-06-26 22:41:31   5412          Bartın     Bartin    96816   \n",
       "13  438115 2021-06-26 22:41:31   5412          Batman     Batman   108989   \n",
       "14  438116 2021-06-26 22:41:31   5412         Bayburt    Bayburt    24128   \n",
       "15  438117 2021-06-26 22:41:31   5412         Bilecik    Bilecik   108385   \n",
       "16  438118 2021-06-26 22:41:31   5412          Bingöl     Bingol    57366   \n",
       "17  438119 2021-06-26 22:41:31   5412          Bitlis     Bitlis    51093   \n",
       "18  438120 2021-06-26 22:41:31   5412            Bolu       Bolu   151636   \n",
       "19  438121 2021-06-26 22:41:31   5412          Burdur     Burdur   128036   \n",
       "\n",
       "     _2DOSE   _TOTAL  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0    355404  1139868     2258718          15           0          15  438021  \n",
       "1     77955   248802      632459           2           0           2  438022  \n",
       "2    138934   431545      736912           8           0           8  438023  \n",
       "3     41146   135953      535435           0           0           0  438024  \n",
       "4     62603   194492      423011           3           0           3  438025  \n",
       "5     87322   256607      335494           1           0           1  438026  \n",
       "6   1241906  3893991     5663322          91           6          97  438027  \n",
       "7    530415  1585765     2548308          29           4          33  438028  \n",
       "8     18642    53271       96161           0           0           0  438029  \n",
       "9     43132   123686      169501           0           0           0  438030  \n",
       "10   293208   849015     1119084          10           0          10  438031  \n",
       "11   359073  1020497     1240285          18           1          19  438032  \n",
       "12    49086   145902      198979           0           0           0  438033  \n",
       "13    48556   157545      620278           1           0           1  438034  \n",
       "14    13155    37283       81910           0           0           0  438035  \n",
       "15    49145   157530      218717           2           0           2  438036  \n",
       "16    30771    88137      281768           1           0           1  438037  \n",
       "17    23726    74819      350994           0           0           0  438038  \n",
       "18    75911   227547      314802           4           0           4  438039  \n",
       "19    66955   194991      267092           2           0           2  438040  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['SEQID'],axis=1,inplace=True) # axis = 1 column or vertical wise, inplace true means reflect changes in original df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>DATE_</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>_1DOSE</th>\n",
       "      <th>_2DOSE</th>\n",
       "      <th>_TOTAL</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID               DATE_            CITY     CITY2  _1DOSE  _2DOSE  \\\n",
       "0  438102 2021-06-26 22:41:31           Adana     Adana  784464  355404   \n",
       "1  438103 2021-06-26 22:41:31        Adıyaman  Adiyaman  170847   77955   \n",
       "2  438104 2021-06-26 22:41:31  Afyonkarahisar     Afyon  292611  138934   \n",
       "3  438105 2021-06-26 22:41:31            Ağrı      Agri   94807   41146   \n",
       "4  438106 2021-06-26 22:41:31         Aksaray   Aksaray  131889   62603   \n",
       "\n",
       "    _TOTAL  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0  1139868     2258718          15           0          15  438021  \n",
       "1   248802      632459           2           0           2  438022  \n",
       "2   431545      736912           8           0           8  438023  \n",
       "3   135953      535435           0           0           0  438024  \n",
       "4   194492      423011           3           0           3  438025  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# renaming columns\n",
    "df.rename(columns={'DATE_':'Date','_1DOSE':'Dose1','_2DOSE':'Dose2','_TOTAL':'Total'},inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID                Date            CITY     CITY2   Dose1   Dose2  \\\n",
       "0  438102 2021-06-26 22:41:31           Adana     Adana  784464  355404   \n",
       "1  438103 2021-06-26 22:41:31        Adıyaman  Adiyaman  170847   77955   \n",
       "2  438104 2021-06-26 22:41:31  Afyonkarahisar     Afyon  292611  138934   \n",
       "3  438105 2021-06-26 22:41:31            Ağrı      Agri   94807   41146   \n",
       "4  438106 2021-06-26 22:41:31         Aksaray   Aksaray  131889   62603   \n",
       "\n",
       "     Total  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0  1139868     2258718          15           0          15  438021  \n",
       "1   248802      632459           2           0           2  438022  \n",
       "2   431545      736912           8           0           8  438023  \n",
       "3   135953      535435           0           0           0  438024  \n",
       "4   194492      423011           3           0           3  438025  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID                Date            CITY     CITY2   Dose1   Dose2  \\\n",
       "0  438102 2021-06-26 22:41:31           Adana     Adana  784464  355404   \n",
       "1  438103 2021-06-26 22:41:31        Adıyaman  Adiyaman  170847   77955   \n",
       "2  438104 2021-06-26 22:41:31  Afyonkarahisar     Afyon  292611  138934   \n",
       "3  438105 2021-06-26 22:41:31            Ağrı      Agri   94807   41146   \n",
       "4  438106 2021-06-26 22:41:31         Aksaray   Aksaray  131889   62603   \n",
       "\n",
       "     Total  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0  1139868     2258718          15           0          15  438021  \n",
       "1   248802      632459           2           0           2  438022  \n",
       "2   431545      736912           8           0           8  438023  \n",
       "3   135953      535435           0           0           0  438024  \n",
       "4   194492      423011           3           0           3  438025  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'] = pd.to_datetime(df['Date']) # its same according to data\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>81.000000</td>\n",
       "      <td>8.100000e+01</td>\n",
       "      <td>8.100000e+01</td>\n",
       "      <td>8.100000e+01</td>\n",
       "      <td>8.100000e+01</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>438142.000000</td>\n",
       "      <td>3.965429e+05</td>\n",
       "      <td>1.828914e+05</td>\n",
       "      <td>5.794343e+05</td>\n",
       "      <td>1.032276e+06</td>\n",
       "      <td>8.407407</td>\n",
       "      <td>0.493827</td>\n",
       "      <td>8.901235</td>\n",
       "      <td>438061.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>23.526581</td>\n",
       "      <td>7.727379e+05</td>\n",
       "      <td>3.171276e+05</td>\n",
       "      <td>1.088717e+06</td>\n",
       "      <td>1.872576e+06</td>\n",
       "      <td>24.283110</td>\n",
       "      <td>1.574194</td>\n",
       "      <td>25.764610</td>\n",
       "      <td>23.526581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>438102.000000</td>\n",
       "      <td>2.412800e+04</td>\n",
       "      <td>1.315500e+04</td>\n",
       "      <td>3.728300e+04</td>\n",
       "      <td>8.191000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>438021.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>438122.000000</td>\n",
       "      <td>1.069900e+05</td>\n",
       "      <td>4.914500e+04</td>\n",
       "      <td>1.575450e+05</td>\n",
       "      <td>2.849230e+05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>438041.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>438142.000000</td>\n",
       "      <td>1.976310e+05</td>\n",
       "      <td>9.889600e+04</td>\n",
       "      <td>2.940100e+05</td>\n",
       "      <td>5.377620e+05</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>438061.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>438162.000000</td>\n",
       "      <td>3.955820e+05</td>\n",
       "      <td>1.871380e+05</td>\n",
       "      <td>5.805240e+05</td>\n",
       "      <td>1.081065e+06</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>438081.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>438182.000000</td>\n",
       "      <td>6.197550e+06</td>\n",
       "      <td>2.419591e+06</td>\n",
       "      <td>8.617141e+06</td>\n",
       "      <td>1.546245e+07</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>204.000000</td>\n",
       "      <td>438101.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  ID         Dose1         Dose2         Total    POPULATION  \\\n",
       "count      81.000000  8.100000e+01  8.100000e+01  8.100000e+01  8.100000e+01   \n",
       "mean   438142.000000  3.965429e+05  1.828914e+05  5.794343e+05  1.032276e+06   \n",
       "std        23.526581  7.727379e+05  3.171276e+05  1.088717e+06  1.872576e+06   \n",
       "min    438102.000000  2.412800e+04  1.315500e+04  3.728300e+04  8.191000e+04   \n",
       "25%    438122.000000  1.069900e+05  4.914500e+04  1.575450e+05  2.849230e+05   \n",
       "50%    438142.000000  1.976310e+05  9.889600e+04  2.940100e+05  5.377620e+05   \n",
       "75%    438162.000000  3.955820e+05  1.871380e+05  5.805240e+05  1.081065e+06   \n",
       "max    438182.000000  6.197550e+06  2.419591e+06  8.617141e+06  1.546245e+07   \n",
       "\n",
       "       DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL         PREVID  \n",
       "count   81.000000   81.000000   81.000000      81.000000  \n",
       "mean     8.407407    0.493827    8.901235  438061.000000  \n",
       "std     24.283110    1.574194   25.764610      23.526581  \n",
       "min      0.000000    0.000000    0.000000  438021.000000  \n",
       "25%      0.000000    0.000000    0.000000  438041.000000  \n",
       "50%      1.000000    0.000000    1.000000  438061.000000  \n",
       "75%      6.000000    0.000000    6.000000  438081.000000  \n",
       "max    193.000000   11.000000  204.000000  438101.000000  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 81 entries, 0 to 80\n",
      "Data columns (total 12 columns):\n",
      " #   Column      Non-Null Count  Dtype         \n",
      "---  ------      --------------  -----         \n",
      " 0   ID          81 non-null     int64         \n",
      " 1   Date        81 non-null     datetime64[ns]\n",
      " 2   CITY        81 non-null     object        \n",
      " 3   CITY2       81 non-null     object        \n",
      " 4   Dose1       81 non-null     int64         \n",
      " 5   Dose2       81 non-null     int64         \n",
      " 6   Total       81 non-null     int64         \n",
      " 7   POPULATION  81 non-null     int64         \n",
      " 8   DIFF_1DOSE  81 non-null     int64         \n",
      " 9   DIFF_2DOSE  81 non-null     int64         \n",
      " 10  DIFF_TOTAL  81 non-null     int64         \n",
      " 11  PREVID      81 non-null     int64         \n",
      "dtypes: datetime64[ns](1), int64(9), object(2)\n",
      "memory usage: 7.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info() # 81 by 81 all entries are filled "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "invalid type promotion",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-65-1816eca44690>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mimputer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSimpleImputer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstrategy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'constant'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mdf2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimputer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36mfit_transform\u001b[1;34m(self, X, y, **fit_params)\u001b[0m\n\u001b[0;32m    688\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0my\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    689\u001b[0m             \u001b[1;31m# fit method of arity 1 (unsupervised transformation)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 690\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    691\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    692\u001b[0m             \u001b[1;31m# fit method of arity 2 (supervised transformation)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\impute\\_base.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, X, y)\u001b[0m\n\u001b[0;32m    275\u001b[0m         \u001b[0mself\u001b[0m \u001b[1;33m:\u001b[0m \u001b[0mSimpleImputer\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    276\u001b[0m         \"\"\"\n\u001b[1;32m--> 277\u001b[1;33m         \u001b[0mX\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_input\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0min_fit\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    278\u001b[0m         \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fit_indicator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    279\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\impute\\_base.py\u001b[0m in \u001b[0;36m_validate_input\u001b[1;34m(self, X, in_fit)\u001b[0m\n\u001b[0;32m    239\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    240\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 241\u001b[1;33m             X = self._validate_data(X, reset=in_fit,\n\u001b[0m\u001b[0;32m    242\u001b[0m                                     \u001b[0maccept_sparse\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'csc'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    243\u001b[0m                                     \u001b[0mforce_all_finite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mforce_all_finite\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\base.py\u001b[0m in \u001b[0;36m_validate_data\u001b[1;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[0;32m    418\u001b[0m                     \u001b[1;34mf\"requires y to be passed, but the target y is None.\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    419\u001b[0m                 )\n\u001b[1;32m--> 420\u001b[1;33m             \u001b[0mX\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mcheck_params\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    421\u001b[0m             \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mX\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    422\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36minner_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     71\u001b[0m                           FutureWarning)\n\u001b[0;32m     72\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 73\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     74\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[1;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)\u001b[0m\n\u001b[0;32m    532\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    533\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mdtype\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdtypes_orig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 534\u001b[1;33m             \u001b[0mdtype_orig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresult_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mdtypes_orig\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    535\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    536\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mdtype_numeric\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36mresult_type\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: invalid type promotion"
     ]
    }
   ],
   "source": [
    "# if not entries are fully filled:\n",
    "# use .fillna( ) function or \n",
    "\n",
    "imputer = SimpleImputer(strategy='constant')\n",
    "df2 = pd.DataFrame(imputer.fit_transform(df),columns=df.columns) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Date</th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "      <th>DIFF_1DOSE</th>\n",
       "      <th>DIFF_2DOSE</th>\n",
       "      <th>DIFF_TOTAL</th>\n",
       "      <th>PREVID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>438102</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>438021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438103</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>438022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>438104</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>438023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>438105</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Ağrı</td>\n",
       "      <td>Agri</td>\n",
       "      <td>94807</td>\n",
       "      <td>41146</td>\n",
       "      <td>135953</td>\n",
       "      <td>535435</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>438024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>438106</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>438025</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ID                Date            CITY     CITY2   Dose1   Dose2  \\\n",
       "0  438102 2021-06-26 22:41:31           Adana     Adana  784464  355404   \n",
       "1  438103 2021-06-26 22:41:31        Adıyaman  Adiyaman  170847   77955   \n",
       "2  438104 2021-06-26 22:41:31  Afyonkarahisar     Afyon  292611  138934   \n",
       "3  438105 2021-06-26 22:41:31            Ağrı      Agri   94807   41146   \n",
       "4  438106 2021-06-26 22:41:31         Aksaray   Aksaray  131889   62603   \n",
       "\n",
       "     Total  POPULATION  DIFF_1DOSE  DIFF_2DOSE  DIFF_TOTAL  PREVID  \n",
       "0  1139868     2258718          15           0          15  438021  \n",
       "1   248802      632459           2           0           2  438022  \n",
       "2   431545      736912           8           0           8  438023  \n",
       "3   135953      535435           0           0           0  438024  \n",
       "4   194492      423011           3           0           3  438025  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df.groupby('CITY')[['Dose1','Dose2','Total','POPULATION']].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CITY</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adana</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aksaray</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Amasya</td>\n",
       "      <td>169285</td>\n",
       "      <td>87322</td>\n",
       "      <td>256607</td>\n",
       "      <td>335494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Çorum</td>\n",
       "      <td>238440</td>\n",
       "      <td>121891</td>\n",
       "      <td>360331</td>\n",
       "      <td>530126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>İstanbul</td>\n",
       "      <td>6197550</td>\n",
       "      <td>2419591</td>\n",
       "      <td>8617141</td>\n",
       "      <td>15462452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>İzmir</td>\n",
       "      <td>2136705</td>\n",
       "      <td>1006223</td>\n",
       "      <td>3142928</td>\n",
       "      <td>4394694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Şanlıurfa</td>\n",
       "      <td>266534</td>\n",
       "      <td>109394</td>\n",
       "      <td>375928</td>\n",
       "      <td>2115256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Şırnak</td>\n",
       "      <td>70624</td>\n",
       "      <td>25473</td>\n",
       "      <td>96097</td>\n",
       "      <td>537762</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              CITY    Dose1    Dose2    Total  POPULATION\n",
       "0            Adana   784464   355404  1139868     2258718\n",
       "1         Adıyaman   170847    77955   248802      632459\n",
       "2   Afyonkarahisar   292611   138934   431545      736912\n",
       "3          Aksaray   131889    62603   194492      423011\n",
       "4           Amasya   169285    87322   256607      335494\n",
       "..             ...      ...      ...      ...         ...\n",
       "76           Çorum   238440   121891   360331      530126\n",
       "77        İstanbul  6197550  2419591  8617141    15462452\n",
       "78           İzmir  2136705  1006223  3142928     4394694\n",
       "79       Şanlıurfa   266534   109394   375928     2115256\n",
       "80          Şırnak    70624    25473    96097      537762\n",
       "\n",
       "[81 rows x 5 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df.groupby(['CITY','CITY2','Date'])[['Date','Dose1','Dose2','Total','POPULATION']].sum().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>Date</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adıyaman</td>\n",
       "      <td>Adiyaman</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>170847</td>\n",
       "      <td>77955</td>\n",
       "      <td>248802</td>\n",
       "      <td>632459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aksaray</td>\n",
       "      <td>Aksaray</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>131889</td>\n",
       "      <td>62603</td>\n",
       "      <td>194492</td>\n",
       "      <td>423011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Amasya</td>\n",
       "      <td>Amasya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>169285</td>\n",
       "      <td>87322</td>\n",
       "      <td>256607</td>\n",
       "      <td>335494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Çorum</td>\n",
       "      <td>Corum</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>238440</td>\n",
       "      <td>121891</td>\n",
       "      <td>360331</td>\n",
       "      <td>530126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>İstanbul</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>6197550</td>\n",
       "      <td>2419591</td>\n",
       "      <td>8617141</td>\n",
       "      <td>15462452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>İzmir</td>\n",
       "      <td>Izmir</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>2136705</td>\n",
       "      <td>1006223</td>\n",
       "      <td>3142928</td>\n",
       "      <td>4394694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Şanlıurfa</td>\n",
       "      <td>Sanliurfa</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>266534</td>\n",
       "      <td>109394</td>\n",
       "      <td>375928</td>\n",
       "      <td>2115256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Şırnak</td>\n",
       "      <td>Sirnak</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>70624</td>\n",
       "      <td>25473</td>\n",
       "      <td>96097</td>\n",
       "      <td>537762</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              CITY      CITY2                Date    Dose1    Dose2    Total  \\\n",
       "0            Adana      Adana 2021-06-26 22:41:31   784464   355404  1139868   \n",
       "1         Adıyaman   Adiyaman 2021-06-26 22:41:31   170847    77955   248802   \n",
       "2   Afyonkarahisar      Afyon 2021-06-26 22:41:31   292611   138934   431545   \n",
       "3          Aksaray    Aksaray 2021-06-26 22:41:31   131889    62603   194492   \n",
       "4           Amasya     Amasya 2021-06-26 22:41:31   169285    87322   256607   \n",
       "..             ...        ...                 ...      ...      ...      ...   \n",
       "76           Çorum      Corum 2021-06-26 22:41:31   238440   121891   360331   \n",
       "77        İstanbul   Istanbul 2021-06-26 22:41:31  6197550  2419591  8617141   \n",
       "78           İzmir      Izmir 2021-06-26 22:41:31  2136705  1006223  3142928   \n",
       "79       Şanlıurfa  Sanliurfa 2021-06-26 22:41:31   266534   109394   375928   \n",
       "80          Şırnak     Sirnak 2021-06-26 22:41:31    70624    25473    96097   \n",
       "\n",
       "    POPULATION  \n",
       "0      2258718  \n",
       "1       632459  \n",
       "2       736912  \n",
       "3       423011  \n",
       "4       335494  \n",
       "..         ...  \n",
       "76      530126  \n",
       "77    15462452  \n",
       "78     4394694  \n",
       "79     2115256  \n",
       "80      537762  \n",
       "\n",
       "[81 rows x 7 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = df2[df2['Total']>256607]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CITY</th>\n",
       "      <th>CITY2</th>\n",
       "      <th>Date</th>\n",
       "      <th>Dose1</th>\n",
       "      <th>Dose2</th>\n",
       "      <th>Total</th>\n",
       "      <th>POPULATION</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adana</td>\n",
       "      <td>Adana</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>784464</td>\n",
       "      <td>355404</td>\n",
       "      <td>1139868</td>\n",
       "      <td>2258718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afyonkarahisar</td>\n",
       "      <td>Afyon</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>292611</td>\n",
       "      <td>138934</td>\n",
       "      <td>431545</td>\n",
       "      <td>736912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Ankara</td>\n",
       "      <td>Ankara</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>2652085</td>\n",
       "      <td>1241906</td>\n",
       "      <td>3893991</td>\n",
       "      <td>5663322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Antalya</td>\n",
       "      <td>Antalya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>1055350</td>\n",
       "      <td>530415</td>\n",
       "      <td>1585765</td>\n",
       "      <td>2548308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Aydın</td>\n",
       "      <td>Aydin</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>555807</td>\n",
       "      <td>293208</td>\n",
       "      <td>849015</td>\n",
       "      <td>1119084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Balıkesir</td>\n",
       "      <td>Balikesir</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>661424</td>\n",
       "      <td>359073</td>\n",
       "      <td>1020497</td>\n",
       "      <td>1240285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Bursa</td>\n",
       "      <td>Bursa</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>1272038</td>\n",
       "      <td>550539</td>\n",
       "      <td>1822577</td>\n",
       "      <td>3101833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Denizli</td>\n",
       "      <td>Denizli</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>475605</td>\n",
       "      <td>212478</td>\n",
       "      <td>688083</td>\n",
       "      <td>1040915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Diyarbakır</td>\n",
       "      <td>Diyarbakir</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>307868</td>\n",
       "      <td>134167</td>\n",
       "      <td>442035</td>\n",
       "      <td>1783431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Edirne</td>\n",
       "      <td>Edirne</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>226150</td>\n",
       "      <td>123707</td>\n",
       "      <td>349857</td>\n",
       "      <td>407763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Elazığ</td>\n",
       "      <td>Elazig</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>191848</td>\n",
       "      <td>101103</td>\n",
       "      <td>292951</td>\n",
       "      <td>587960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Erzurum</td>\n",
       "      <td>Erzurum</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>212225</td>\n",
       "      <td>106493</td>\n",
       "      <td>318718</td>\n",
       "      <td>758279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Eskişehir</td>\n",
       "      <td>Eskisehir</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>457620</td>\n",
       "      <td>215045</td>\n",
       "      <td>672665</td>\n",
       "      <td>888828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Gaziantep</td>\n",
       "      <td>Gaziantep</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>570536</td>\n",
       "      <td>207651</td>\n",
       "      <td>778187</td>\n",
       "      <td>2101157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Giresun</td>\n",
       "      <td>Giresun</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>210905</td>\n",
       "      <td>123826</td>\n",
       "      <td>334731</td>\n",
       "      <td>448721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Hatay</td>\n",
       "      <td>Hatay</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>512074</td>\n",
       "      <td>223365</td>\n",
       "      <td>735439</td>\n",
       "      <td>1659320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Isparta</td>\n",
       "      <td>Isparta</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>205991</td>\n",
       "      <td>107865</td>\n",
       "      <td>313856</td>\n",
       "      <td>440304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Kahramanmaraş</td>\n",
       "      <td>Kahramanmaras</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>336185</td>\n",
       "      <td>149207</td>\n",
       "      <td>485392</td>\n",
       "      <td>1168163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Kastamonu</td>\n",
       "      <td>Kastamonu</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>175799</td>\n",
       "      <td>99604</td>\n",
       "      <td>275403</td>\n",
       "      <td>376377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Kayseri</td>\n",
       "      <td>Kayseri</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>534876</td>\n",
       "      <td>250399</td>\n",
       "      <td>785275</td>\n",
       "      <td>1421455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Kocaeli</td>\n",
       "      <td>Kocaeli</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>793994</td>\n",
       "      <td>321371</td>\n",
       "      <td>1115365</td>\n",
       "      <td>1997258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Konya</td>\n",
       "      <td>Konya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>757561</td>\n",
       "      <td>374716</td>\n",
       "      <td>1132277</td>\n",
       "      <td>2250020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Kütahya</td>\n",
       "      <td>Kutahya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>254612</td>\n",
       "      <td>125308</td>\n",
       "      <td>379920</td>\n",
       "      <td>576688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Kırklareli</td>\n",
       "      <td>Kirklareli</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>197631</td>\n",
       "      <td>98896</td>\n",
       "      <td>296527</td>\n",
       "      <td>361737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Malatya</td>\n",
       "      <td>Malatya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>290096</td>\n",
       "      <td>147223</td>\n",
       "      <td>437319</td>\n",
       "      <td>806156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Manisa</td>\n",
       "      <td>Manisa</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>637609</td>\n",
       "      <td>284045</td>\n",
       "      <td>921654</td>\n",
       "      <td>1450616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Mersin</td>\n",
       "      <td>Mersin</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>730833</td>\n",
       "      <td>349594</td>\n",
       "      <td>1080427</td>\n",
       "      <td>1868757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Muğla</td>\n",
       "      <td>Mugla</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>578641</td>\n",
       "      <td>286979</td>\n",
       "      <td>865620</td>\n",
       "      <td>1000773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Ordu</td>\n",
       "      <td>Ordu</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>352377</td>\n",
       "      <td>187138</td>\n",
       "      <td>539515</td>\n",
       "      <td>761400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Osmaniye</td>\n",
       "      <td>Osmaniye</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>198547</td>\n",
       "      <td>95463</td>\n",
       "      <td>294010</td>\n",
       "      <td>548556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Sakarya</td>\n",
       "      <td>Sakarya</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>395582</td>\n",
       "      <td>184942</td>\n",
       "      <td>580524</td>\n",
       "      <td>1042649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Samsun</td>\n",
       "      <td>Samsun</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>562448</td>\n",
       "      <td>292951</td>\n",
       "      <td>855399</td>\n",
       "      <td>1356079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Sivas</td>\n",
       "      <td>Sivas</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>245140</td>\n",
       "      <td>126038</td>\n",
       "      <td>371178</td>\n",
       "      <td>635889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Tekirdağ</td>\n",
       "      <td>Tekirdag</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>477726</td>\n",
       "      <td>208146</td>\n",
       "      <td>685872</td>\n",
       "      <td>1081065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Tokat</td>\n",
       "      <td>Tokat</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>250396</td>\n",
       "      <td>137312</td>\n",
       "      <td>387708</td>\n",
       "      <td>597861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Trabzon</td>\n",
       "      <td>Trabzon</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>341832</td>\n",
       "      <td>186529</td>\n",
       "      <td>528361</td>\n",
       "      <td>811901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Van</td>\n",
       "      <td>Van</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>236641</td>\n",
       "      <td>91208</td>\n",
       "      <td>327849</td>\n",
       "      <td>1149342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Zonguldak</td>\n",
       "      <td>Zonguldak</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>275433</td>\n",
       "      <td>139382</td>\n",
       "      <td>414815</td>\n",
       "      <td>591204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Çanakkale</td>\n",
       "      <td>Canakkale</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>298662</td>\n",
       "      <td>161433</td>\n",
       "      <td>460095</td>\n",
       "      <td>541548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Çorum</td>\n",
       "      <td>Corum</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>238440</td>\n",
       "      <td>121891</td>\n",
       "      <td>360331</td>\n",
       "      <td>530126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>İstanbul</td>\n",
       "      <td>Istanbul</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>6197550</td>\n",
       "      <td>2419591</td>\n",
       "      <td>8617141</td>\n",
       "      <td>15462452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>İzmir</td>\n",
       "      <td>Izmir</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>2136705</td>\n",
       "      <td>1006223</td>\n",
       "      <td>3142928</td>\n",
       "      <td>4394694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Şanlıurfa</td>\n",
       "      <td>Sanliurfa</td>\n",
       "      <td>2021-06-26 22:41:31</td>\n",
       "      <td>266534</td>\n",
       "      <td>109394</td>\n",
       "      <td>375928</td>\n",
       "      <td>2115256</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              CITY          CITY2                Date    Dose1    Dose2  \\\n",
       "0            Adana          Adana 2021-06-26 22:41:31   784464   355404   \n",
       "2   Afyonkarahisar          Afyon 2021-06-26 22:41:31   292611   138934   \n",
       "5           Ankara         Ankara 2021-06-26 22:41:31  2652085  1241906   \n",
       "6          Antalya        Antalya 2021-06-26 22:41:31  1055350   530415   \n",
       "9            Aydın          Aydin 2021-06-26 22:41:31   555807   293208   \n",
       "11       Balıkesir      Balikesir 2021-06-26 22:41:31   661424   359073   \n",
       "20           Bursa          Bursa 2021-06-26 22:41:31  1272038   550539   \n",
       "21         Denizli        Denizli 2021-06-26 22:41:31   475605   212478   \n",
       "22      Diyarbakır     Diyarbakir 2021-06-26 22:41:31   307868   134167   \n",
       "24          Edirne         Edirne 2021-06-26 22:41:31   226150   123707   \n",
       "25          Elazığ         Elazig 2021-06-26 22:41:31   191848   101103   \n",
       "27         Erzurum        Erzurum 2021-06-26 22:41:31   212225   106493   \n",
       "28       Eskişehir      Eskisehir 2021-06-26 22:41:31   457620   215045   \n",
       "29       Gaziantep      Gaziantep 2021-06-26 22:41:31   570536   207651   \n",
       "30         Giresun        Giresun 2021-06-26 22:41:31   210905   123826   \n",
       "33           Hatay          Hatay 2021-06-26 22:41:31   512074   223365   \n",
       "34         Isparta        Isparta 2021-06-26 22:41:31   205991   107865   \n",
       "36   Kahramanmaraş  Kahramanmaras 2021-06-26 22:41:31   336185   149207   \n",
       "40       Kastamonu      Kastamonu 2021-06-26 22:41:31   175799    99604   \n",
       "41         Kayseri        Kayseri 2021-06-26 22:41:31   534876   250399   \n",
       "43         Kocaeli        Kocaeli 2021-06-26 22:41:31   793994   321371   \n",
       "44           Konya          Konya 2021-06-26 22:41:31   757561   374716   \n",
       "45         Kütahya        Kutahya 2021-06-26 22:41:31   254612   125308   \n",
       "46      Kırklareli     Kirklareli 2021-06-26 22:41:31   197631    98896   \n",
       "49         Malatya        Malatya 2021-06-26 22:41:31   290096   147223   \n",
       "50          Manisa         Manisa 2021-06-26 22:41:31   637609   284045   \n",
       "52          Mersin         Mersin 2021-06-26 22:41:31   730833   349594   \n",
       "53           Muğla          Mugla 2021-06-26 22:41:31   578641   286979   \n",
       "57            Ordu           Ordu 2021-06-26 22:41:31   352377   187138   \n",
       "58        Osmaniye       Osmaniye 2021-06-26 22:41:31   198547    95463   \n",
       "60         Sakarya        Sakarya 2021-06-26 22:41:31   395582   184942   \n",
       "61          Samsun         Samsun 2021-06-26 22:41:31   562448   292951   \n",
       "64           Sivas          Sivas 2021-06-26 22:41:31   245140   126038   \n",
       "65        Tekirdağ       Tekirdag 2021-06-26 22:41:31   477726   208146   \n",
       "66           Tokat          Tokat 2021-06-26 22:41:31   250396   137312   \n",
       "67         Trabzon        Trabzon 2021-06-26 22:41:31   341832   186529   \n",
       "70             Van            Van 2021-06-26 22:41:31   236641    91208   \n",
       "73       Zonguldak      Zonguldak 2021-06-26 22:41:31   275433   139382   \n",
       "74       Çanakkale      Canakkale 2021-06-26 22:41:31   298662   161433   \n",
       "76           Çorum          Corum 2021-06-26 22:41:31   238440   121891   \n",
       "77        İstanbul       Istanbul 2021-06-26 22:41:31  6197550  2419591   \n",
       "78           İzmir          Izmir 2021-06-26 22:41:31  2136705  1006223   \n",
       "79       Şanlıurfa      Sanliurfa 2021-06-26 22:41:31   266534   109394   \n",
       "\n",
       "      Total  POPULATION  \n",
       "0   1139868     2258718  \n",
       "2    431545      736912  \n",
       "5   3893991     5663322  \n",
       "6   1585765     2548308  \n",
       "9    849015     1119084  \n",
       "11  1020497     1240285  \n",
       "20  1822577     3101833  \n",
       "21   688083     1040915  \n",
       "22   442035     1783431  \n",
       "24   349857      407763  \n",
       "25   292951      587960  \n",
       "27   318718      758279  \n",
       "28   672665      888828  \n",
       "29   778187     2101157  \n",
       "30   334731      448721  \n",
       "33   735439     1659320  \n",
       "34   313856      440304  \n",
       "36   485392     1168163  \n",
       "40   275403      376377  \n",
       "41   785275     1421455  \n",
       "43  1115365     1997258  \n",
       "44  1132277     2250020  \n",
       "45   379920      576688  \n",
       "46   296527      361737  \n",
       "49   437319      806156  \n",
       "50   921654     1450616  \n",
       "52  1080427     1868757  \n",
       "53   865620     1000773  \n",
       "57   539515      761400  \n",
       "58   294010      548556  \n",
       "60   580524     1042649  \n",
       "61   855399     1356079  \n",
       "64   371178      635889  \n",
       "65   685872     1081065  \n",
       "66   387708      597861  \n",
       "67   528361      811901  \n",
       "70   327849     1149342  \n",
       "73   414815      591204  \n",
       "74   460095      541548  \n",
       "76   360331      530126  \n",
       "77  8617141    15462452  \n",
       "78  3142928     4394694  \n",
       "79   375928     2115256  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1e8695e9820>]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,10,1000) # start from zero go to 10\n",
    "y = np.sin(x)\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1e865761580>"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD4CAYAAADhNOGaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAdxElEQVR4nO3df4wc533f8feHlIWKiluZ0lmmRPFOLlg3jFvL0kFVIsC1Y8uV1KaUixiQIDFEYoAQKrWOEbRlSyA1GhAwgiJJnbpJGUUNI7ISBFeuCEe2LDNp3TS1o5OiH5RZRjQtUjRZ8fTDdhoaUGV++8fMmsvl7N3u7ez8ej4vYHG7szO7z97O7GeeeZ5nRhGBmZmla1XdBTAzs3o5CMzMEucgMDNLnIPAzCxxDgIzs8RdUHcBVuKyyy6Lubm5uothZtYqTz311KsRMTM4vZVBMDc3x8LCQt3FMDNrFUlHi6b70JCZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeJKCQJJ90s6JenAkOcl6bOSDkt6TtK1fc/dLOlQ/tz2MsrTKXv3wtwcrFoFl12W3Vatyqbt3Vt36cyq4e1gqsqqEfwecPMSz98CbMxv24DfApC0Gvhc/vwm4A5Jm0oqU/vt3QvbtsHRoxABr72W3SKyaVu2gOSNwbqp9+MvZeu6t4OpKSUIIuJrwOtLzLIZ+P3IfB24RNI64HrgcEQciYg3gYfyedPW2wDuugtOnx4+X+8U4kePZoHhjcC6on8nCM6u60W8HUysqjaCK4GX+x4fz6cNm34eSdskLUhaWFxcnFpBaze4AYzq9GnYutXVZWu3UXeChjl9OlvW28BYqgoCFUyLJaafPzFiV0TMR8T8zMx5I6Tbb9INAOCHPzxbXfaekbXNSneCingbGEtVQXAcuKrv8XrgxBLT01LmBtBz+jTs2FHe65lN244dK98JKuJtYGRVBcE+4Ofy3kM3AN+LiJPAk8BGSVdLuhC4PZ83LaNuAJdemt0gaxxbztGjriJb8/Vqw8vtCPXW+XG2A28DIymr++iDwP8C3iPpuKRPSLpb0t35LI8BR4DDwO8A/xggIt4C7gUeBw4CD0fEC2WUqRVG3QDWrIE9e+DVV7NbBDzwAMzOZhvC6tXDl3UV2Zps1Nrw7Gy2zkcUbwdL8TawvIho3e26666L1tuzJ2LNmohsdR5+m53N5p30tWZnq/hUZuOZnV16vV2zZvn1P8LbwIiAhSj4TfXI4rosdzioVwt46SW4886lX+vOO2HXrqX3jFxFtiY6dmz4c7Oz2Xq93PoPo20DS71X4hwEdSlrA+i5884sNJYLA1eRrQl6h0WHjQ+YnR1tJ6jfcttAhHeGhnAQVG0aG0C/nTuz2sQw7klhdVuuXWDNmmw9XqmltgHvDBVyEFRp2hsAuIpszbfUYdGV1IYHLbcNeGfoPIqlhm431Pz8fLTyUpVL9RCanc1CYJINYNT369U6zOqwalVxjViCM2fa+14tIOmpiJgfnO4aQZWG7YlLkx0OGqaoiiy54djqtWHDeNPb8l4t5iCoUtUr5WAVWfIJuqw+/eNmBgeClXFYtIh3hkbiIKhCHRtAT39PisEqso+VWlWKziba2xbKaBcYxjtDI3EbwbT1NoD+xrHeyjiNdoFhfKzU6tSE9qomlKFmw9oILqijMEkp6iHRC4EqV74NG4o3Ah8rtSoMax+rsgdbE8rQUD40NG1NWfl8rNTq1IRG2yaUoaEcBNPWlJXPx0qtDnW2jw0q2hmqugwN5SCYtiatfG44tirV1UA8TP/OkJSdyvqii7JrHideK3Zj8bTs3Zv9sB47BmvXZtNefz2rCVTVQDyMG46tCk1unC3qxLFmTfXhVDEPKKtS/55QBLz2GvzgB9m506cxcGxcTTlcZd3WlPaxIkWdOBKuFTsIpqHpK1mTDldZdzV5h6PJIVWDsq5QdrOkQ5IOS9pe8Pw/k/RMfjsg6YeS1ubPvSTp+fy5hh/vGVHTVzIfK7UqNHmHo8khVYeiq9WMcwNWA98C3g1cCDwLbFpi/p8B/rDv8UvAZeO8Z+OvUDbsqktNvEJS0ZWdRr0qlNly9uzJ1ntptKvtVSXR9Z4pXqHseuBwRByJiDeBh4DNS8x/B/BgCe/bXE3eExrU9MNY1i697qKrVmV/IWsXO3OmGe1jPYO14tlZ2Lo1W+97ZU+pZlyUDuPcgJ8F7ut7vAX490PmXQO8Dqztm/Zt4GngKWDbEu+zDVgAFjZs2DDN0Fy5/r2fSy/Nbk3bExokFddepLpLZm3T5r3sNpd9DEyxRqCCacP6pP4M8D8j4vW+aTdGxLXALcA9kj5QtGBE7IqI+YiYn5mZmazE09D0nkLD+FiplaXNtcs2l70EZQTBceCqvsfrgRND5r2dgcNCEXEi/3sK+ALZoab2aeuK1KbDWNZsTe8ksZQ2l70EZQTBk8BGSVdLupDsx37f4EyS/hrwd4FH+6ZdLOntvfvAR4EDJZSpem1dkYqOlXZ8UI1NSZtrl20uewkmDoKIeAu4F3gcOAg8HBEvSLpb0t19s34M+EpE/GXftMuBP5b0LPCnwB9ExJcnLVMt2rwi9U49ceZMVhNItcHMJtPm2mWby16GooaDpt8a2X20C41NXfgMVq+mdhcdRZvLPiKGNBbX/qO+klsjgyCi/StSm8Y/WHO0fb0v0sXPFMODwBemmVT/yeWacEK5SbS1ncPqM3jytt4pzaG920EXP9MyfPbRSXTtDIZNPlukNVMX15kufqaczz46DW3tMjpM6g1mNr4u1iK7+JmW4SCYRNdWGHcltXG1ubfcMF38TMtwEEyiiytMf1fSJo+ItmboYi2yi59pGQ6CSXR9hRk8gZjHFNigLtYiu/iZllPUlajpt0Z1H+1oNzOPKbAldXW97zimeNK5tHX1UErXGsKtPIMnWOx1r+xqjTGBmrGDYCUSWDE61xBu5UlpJyGR0HMQjCuRFaOTDeFWjpR2EhIJPQfBuBJZMTrfEG4rl9JOQiKh5yAYVyIrRpI9J2w0Ke0kJBJ6DoJxJbJiAN1tCLfJpLSTkEjoOQjGlciKcZ4UGshtdKnsJCQSeqUEgaSbJR2SdFjS9oLnPyjpe5KeyW+/POqyjZPIinGOVBrIzYokEHoTB4Gk1cDnyC4+vwm4Q9Kmgln/R0Rck9/+zZjLNksCK8Y5Umkgt6W5VtjZ/0EZ1yO4HjgcEUcAJD0EbAa+OeVlrSqpNJDbcAmeo/88Hf4flHFo6Erg5b7Hx/Npg35S0rOSviTpJ8Zctn4d3RMYSUoN5FbMtcJO/w/KCAIVTBu82s3TwGxEvA/4TeC/jrFsNqO0TdKCpIXFxcUVF3ZFUj9GnmoDuZ3lWmGn/wdlBMFx4Kq+x+uBE/0zRMT3I+L/5vcfA94m6bJRlu17jV0RMR8R8zMzMyUUewwd3hMYSYoN5HYu1wo7/T8oIwieBDZKulrShcDtwL7+GSS9S5Ly+9fn7/vaKMs2Qof3BEaWWgO5ncu1wk7/DyYOgoh4C7gXeBw4CDwcES9IulvS3flsPwsckPQs8Fng9vysqIXLTlqm0nV4T8BsJK4Vdvp/4IvXj6JrF6mf1N692WGxY8eyMNy5M83/g1nL+OL1k+jwnsDYUm84T03KveUS4iAYlY+RZ1JvOE+JQ39pHQpJHxqy8axalf0oDJKykLTumJvLfvwHzc5mO0Mpa+nhYh8aGleH0r5UbjhPh3vLDdexmrGDoIirxMN1uAudDXDoD9exkHQQFOlY2pfKDefpcOgP17GQdBAU6Vjal84N52lw6A/XsZB0EBTpWNqbrZhDv1jHQtJBUKRjaT9VblS3VHUoJB0ERTqW9lPjRnWzTnAQDNOhtJ8aN6p3k2t542v5/6yMK5RZqtyo3j0dvgrX1HTgf+YaQb+Wp3rl3KjePa7lja8D/zMHQY+Pd4/Pjerd41re+DrwP3MQ9HQg1SvnRvXucS1vfB34nzkIejqQ6rVwo3q3uJY3vg78z0oJAkk3Szok6bCk7QXP3ynpufz2J5Le1/fcS5Kel/SMpPpOKdqBVDebmGt54+vA/2zi01BLWg38OXAT2cXonwTuiIhv9s3zU8DBiHhD0i3ApyPi7+TPvQTMR8Sro77nVE5D3dLTypqZjWqap6G+HjgcEUci4k3gIWBz/wwR8ScR8Ub+8OvA+hLet1wdSPXaudeVWSuVEQRXAi/3PT6eTxvmE8CX+h4H8BVJT0naNmwhSdskLUhaWFxcnKjAQ/l498q511W7OcSTVkYQqGBa4fEmSR8iC4J/0Tf5xoi4FrgFuEfSB4qWjYhdETEfEfMzMzOTltnK5l5X7eUQL1cLQ7WMIDgOXNX3eD1wYnAmSX8buA/YHBGv9aZHxIn87yngC2SHmqrTwi+tkdzrqr0c4uVpaaiWEQRPAhslXS3pQuB2YF//DJI2AI8AWyLiz/umXyzp7b37wEeBAyWUaTQt/dIayb2u2sshXp6WhurEQRARbwH3Ao8DB4GHI+IFSXdLujuf7ZeBS4H/MNBN9HLgjyU9C/wp8AcR8eVJyzSyln5pjdSBvtTJcoiXp6WhOnH30TqU1n101aqsJjBIyhqMbTx792YheuxY9iOyc6cb3NvAXafLMzeXHVkYNDubdUCp2TS7j7aX94TK5V5X7eSu0+Vpac047SBo6ZdmVjqHeDlaGqppB0FLv7RWcG8sS1ULQ9UXprnzzlZ8Ua3SgQt1mKUk7RqBTYd7Y7WDa22WcxBY+VrahS4pHkNTjZaEbZpB0JIvp7XcG6v5XGubvhaFbXpB0KIvp7XcG6v5XGubvhaFbXpB0KIvp7XcG6v5XGubvhaFbXpB0KIvp9Va2IUuKa61TV+Lwja9IGjRl2M2Na61TV+Lwja9IGjRl2M2Va61TVeLwja9IGjRl9MZ7qVlqWpJ2KY5stijiavjUcZmjZdejcCq5V5azeLamRVwENh0uZdWc3gMTb0aHMKlBIGkmyUdknRY0vaC5yXps/nzz0m6dtRlS9PgL6HT3EurOVw7q0/TQzgiJroBq4FvAe8GLgSeBTYNzHMr8CVAwA3AN0Zdtuh23XXXxVj27IlYsyYi+wqy25o12XSbLv/vm0M693vo3aS6S9Z9s7PF//vZ2UqLASxEwW9qGTWC64HDEXEkIt4EHgI2D8yzGfj9vCxfBy6RtG7EZSfnPaH6uJdWc7h2Vp+GHyItIwiuBF7ue3w8nzbKPKMsC4CkbZIWJC0sLi6OV8KGfwmd15IudJ3nMTT1aXgIlxEEKpg2eEX4YfOMsmw2MWJXRMxHxPzMzMx4JWz4l2BWCdfO6tPwEC4jCI4DV/U9Xg+cGHGeUZadXMO/BLPKuHZWj4aHcBlB8CSwUdLVki4Ebgf2DcyzD/i5vPfQDcD3IuLkiMtOruFfQnLcg8tS1OAQnnhkcUS8Jele4HGyXkD3R8QLku7On/9t4DGynkOHgdPAzy+17KRlKuTRxM3gkcZmjVPKOIKIeCwi/kZE/PWI2JlP++08BMh7C92TP/+3ImJhqWWtw9yDq3qugTVPw76TNM81ZPVxD65quQbWPA38TpSNMWiX+fn5WFhYWH5Ga565uWzFHzQ7mx03tXL5/908NX4nkp6KiPnB6T7XkFXLPbiq5RpY8zTwO3EQWLXcg6taHkPTPA38ThwEVr0Gd6PrHNfAmqeB34mDwKzLXANrngZ+J24sNjNLhBuLrZka1p/aLEUOAqtP0y/W0WYOWBuDg8Dq41HG0+GAbZcGhLbbCKw+q1ZlP1SDpKxHka2MB5G1x+AoY8h6EE2p8dhtBNY8DexP3QkNHLBkQzSkVuwgsPo0sD91Jzhg26Mhoe0gsPo0sD91Jzhg26Mhoe0gsHp5lHH5HLDt0ZDQ9mmozbrIF2Jqh953tGNHdjhow4YsBCr+7iaqEUhaK+kJSS/mf99RMM9Vkv5I0kFJL0j6ZN9zn5b0HUnP5LdbJymPmVnrNKBWPOmhoe3A/ojYCOzPHw96C/iliPhx4AbgHkmb+p7/9Yi4Jr89NmF5rM0a0J/aLEWTBsFmYHd+fzdw2+AMEXEyIp7O7/8FcBC4csL3ta7xIKjJOUhthSYNgssj4iRkP/jAO5eaWdIc8H7gG32T75X0nKT7iw4t9S27TdKCpIXFxcUJi22N05D+1K3lIO2GmsJ82ZHFkr4KvKvgqR3A7oi4pG/eNyKi8Mdc0o8B/x3YGRGP5NMuB14FAvgVYF1E/MJyhfbI4g7yKOPJeDRx+1UwynjYyOKJTjEh6RDwwYg4KWkd8N8i4j0F870N+CLweET82pDXmgO+GBHvXe59HQQd5B+yyThI26+CbWBap5jYB2zN728FHi14YwG/CxwcDIE8PHo+BhyYsDzWVg3pT91aDRmYZBOocZTxpEHwGeAmSS8CN+WPkXSFpF4PoBuBLcBPF3QT/VVJz0t6DvgQ8KkJy2Nt5UFQk3GQtl+NYe6zj5p1xd69tQ9MsgnU2EbgkcVmXeHRxO1W4yhjn2vImsl94i1FNY0ydhBY87hP/OgcmFYCB4E1jweXjcaB2W0Vhrwbi6153Cd+NB570V1Tajj2pSqtPdwnfjQNubqVTUHFtWIHgTWP+8SPxoHZXRWHvIPAmseDy0bjwOyuikPeQWDN1ICLdTSeA7O7Kg55DygzazMPIuumigeXuUZgzee+8paiCmvFDgJrNveVP5dD0abAQWDN5sFlZzkU0zbFnQAPKLNm8+CyszyALF0lDTDzgDJrJ/eVP8sDyNI15ZrxREEgaa2kJyS9mP8ddr3il/IL0DwjaWHc5S1h7it/lkMxXVPeCZi0RrAd2B8RG4H9+eNhPhQR1wxUS8ZZ3lLkvvJnORTTNeWdgEmDYDOwO7+/G7it4uUtBR5clnEopmvKOwETNRZL+m5EXNL3+I2IOO/wjqRvA28AAfzHiNg1zvL5c9uAbQAbNmy47mhRo5mZWVeVcCnSFTcWS/qqpAMFt81jvP+NEXEtcAtwj6QPjLEsABGxKyLmI2J+ZmZm3MWtK9yP3lI1xZrxskEQER+JiPcW3B4FXpG0DiD/e2rIa5zI/54CvgBcnz810vJmQLr96B1+NmWTthHsA7bm97cCjw7OIOliSW/v3Qc+ChwYdXmzH0lxcFmq4WeVmrSN4FLgYWADcAz4eES8LukK4L6IuFXSu8lqAZCd5O4/R8TOpZZf7n09oCxRKQ4u8yAyK9GwNoKJzj4aEa8BHy6YfgK4Nb9/BHjfOMubFdqwofhHscv96D2IzCrgkcXWHin2o/cgMquAg8DaI8V+9CmGn1XOF6axdkntQiwVX6DE0uQagbVXKt0qPbLapsxBYO3U9W6VqYScNYKDwNqpy2MKuh5y1jgOAmunLner7HLIWSM5CKydutytssshZ43kILB26nK3yi6HnDWSg8DaqctjCrocctZIDgJrr/5ulTt3ZsfQu9DLpsshZ43kAWXWfr1eNr0G1l4vG2jXj2cJFx4xWwnXCKz9utDLxl1GrUYOAmu/LvSy6UKYWWs5CKz9utDLpgthZq3lILD260Ivmy6EmbXWREEgaa2kJyS9mP99R8E875H0TN/t+5J+MX/u05K+0/fcrZOUxxLVhV42XQgza61JawTbgf0RsRHYnz8+R0QciohrIuIa4DrgNGcvXQnw673nI+KxCctjqWp7V9IuhJm11qRBsBnYnd/fDdy2zPwfBr4VEQXXGzQrQdt63/SfZXTHjizEfLppq9ikQXB5RJwEyP++c5n5bwceHJh2r6TnJN1fdGipR9I2SQuSFhYXFycrtXVXm3rftC20rLMUEUvPIH0VeFfBUzuA3RFxSd+8b0RE4Y+5pAuBE8BPRMQr+bTLgVeBAH4FWBcRv7Bcoefn52NhYWG52SxFq1ZlP6qDpGxPu0nm5rIf/0Gzs1mNwKxkkp6KiPnB6cuOLI6Ijyzxoq9IWhcRJyWtA04t8VK3AE/3QiB/7R/dl/Q7wBeXK4/ZkjZsKP5xbWLvG3cZtYaY9NDQPmBrfn8r8OgS897BwGGhPDx6PgYcmLA8lro29b5xl1FriEmD4DPATZJeBG7KHyPpCkk/6gEkaU3+/CMDy/+qpOclPQd8CPjUhOWx1A32vrn0UrjoItiypXk9iNoUWtZpy7YRNJHbCGwkgyejg+yHtu5umf0nl1u7Npv2+us+0ZxN3bA2Ao8stu5qYg+iwZ5Cr70GP/gBPPCAu4xabRwE1l1NbIxtYjhZ8hwE1l1NbIxtYjhZ8hwE1l1FjbFSdlimrobjJoaTJc9BYN3V34MIshDodY6oehRv71QSR49m5ejnnkJWMweBdVvvZHSzs+ePOK7q2Hx/AzFk5eiFgU8uZw3gaxZbGuo8Nl/UQBzhU0lYY7hGYGmo89i8G4it4RwEloY6Go577QLDBm26gdgawkFgaai64XiwXWCQG4itQRwElo4qG46L2gV63EBsDeMgsPQMOzZf5mGiYe8h+VQS1jgOAkvPUsfmJz1M5HYBayEHgaWnqOG430oPE7ldwFrKQWDpGWw4LnL0aHbZy1EOFfVqAXfd5XYBayVfj8DSNuy6wf16PYxmZ89eL6B3TYHeKSOW2o6aeL1kS9JUrkcg6eOSXpB0RtJ5L943382SDkk6LGl73/S1kp6Q9GL+t/DC92ZTs9xhIji3m+mWLdkP+5Yt554yYiluF7CGm/TQ0AHgHwFfGzaDpNXA58guXr8JuEPSpvzp7cD+iNgI7M8fm1Vn8NKWy+n96I9ak3a7gLXAREEQEQcj4tAys10PHI6IIxHxJvAQsDl/bjOwO7+/G7htkvKYrUhvfMGZM0u3G4zL7QLWElU0Fl8JvNz3+Hg+DeDyiDgJkP9957AXkbRN0oKkhcXFxakV1hI3yqGi5axZA3v2eLyAtcayQSDpq5IOFNw2L7ds7yUKpo3dQh0RuyJiPiLmZ2Zmxl3cbDRFp6IYhU8rbS22bBBExEci4r0Ft0dHfI/jwFV9j9cDJ/L7r0haB5D/PTVO4c2moneoKCK7qPywUOj/8X/ggWx+1wKshao4NPQksFHS1ZIuBG4H9uXP7QO25ve3AqOGi1k1ikJB8o+/dcpE4wgkfQz4TWAG+C7wTET8PUlXAPdFxK35fLcCvwGsBu6PiJ359EuBh4ENwDHg4xHx+nLv63EEZmbjGzaOwAPKzMwSMZUBZWZm1n4OAjOzxDkIzMwS5yAwM0tcKxuLJS0Cy5wycqjLgFdLLE5bpPi5/ZnTkeLnXslnno2I80bktjIIJiFpoajVvOtS/Nz+zOlI8XOX+Zl9aMjMLHEOAjOzxKUYBLvqLkBNUvzc/szpSPFzl/aZk2sjMDOzc6VYIzAzsz4OAjOzxCUVBJJulnRI0mFJnb8+sqSrJP2RpIOSXpD0ybrLVBVJqyX9maQv1l2Wqki6RNLnJf3v/Dv/ybrLNG2SPpWv2wckPSjpr9RdpmmQdL+kU5IO9E1bK+kJSS/mf9+x0tdPJggkrQY+B9wCbALukLSp3lJN3VvAL0XEjwM3APck8Jl7PgkcrLsQFft3wJcj4m8C76Pjn1/SlcA/BeYj4r1kp7m/vd5STc3vATcPTNsO7I+IjcD+/PGKJBMEwPXA4Yg4EhFvAg8Bo15us5Ui4mREPJ3f/wuyH4Yrl16q/SStB/4+cF/dZamKpL8KfAD4XYCIeDMivltvqSpxAXCRpAuANZy9+mGnRMTXgMFrtWwGduf3dwO3rfT1UwqCK4GX+x4fJ4EfxR5Jc8D7gW/UW5JK/Abwz4EzdRekQu8GFoH/lB8Su0/SxXUXapoi4jvAvyW7qNVJ4HsR8ZV6S1WpyyPiJGQ7fcA7V/pCKQVB0VXIk+g7K+nHgP8C/GJEfL/u8kyTpH8AnIqIp+ouS8UuAK4Ffisi3g/8JRMcKmiD/Jj4ZuBq4ArgYkl31VuqdkopCI4DV/U9Xk9Hq5H9JL2NLAT2RsQjdZenAjcC/1DSS2SH/35a0p56i1SJ48DxiOjV+D5PFgxd9hHg2xGxGBH/D3gE+Kmay1SlVyStA8j/nlrpC6UUBE8CGyVdLelCskalfTWXaaokieyY8cGI+LW6y1OFiPiXEbE+IubIvuM/jIjO7yVGxP8BXpb0nnzSh4Fv1likKhwDbpC0Jl/XP0zHG8gH7AO25ve3Ao+u9IUuKKU4LRARb0m6F3icrHfB/RHxQs3FmrYbgS3A85Keyaf9q4h4rMYy2fT8E2BvvqNzBPj5msszVRHxDUmfB54m6yH3Z3T0VBOSHgQ+CFwm6Tjwr4HPAA9L+gRZKH58xa/vU0yYmaUtpUNDZmZWwEFgZpY4B4GZWeIcBGZmiXMQmJklzkFgZpY4B4GZWeL+P35pEMf9CUuVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x[::10],y[::10],color='red') # scatter plot "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1e869741e50>]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y,color='b')\n",
    "plt.plot(x,np.cos(x),color='g')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "43"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "city = df3['CITY'].unique()\n",
    "len(city)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZgAAAEWCAYAAABbgYH9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3dfZBX5X338feHh7KsKEGEiKywaEwjiCyyEjNmGi0GjGmjZvQOukZMvGfVaEzapk0smeJDSJqmUertQ0qbxKdtxGqcaKbeSsHWScaiS24EARGigqtUCCgxhSUC3/uPcy3+WHeXfbr2AT+vmTO/8/uec529zu7oh3Ou63d+igjMzMy624De7oCZmR2aHDBmZpaFA8bMzLJwwJiZWRYOGDMzy8IBY2ZmWThgzMwsCweMWUaSLpZUL+l3kjZLekzSx3u7X2Y9wQFjlomkPwcWAN8GPgiMA+4Azu3gcQZ1f+/M8nPAmGUgaThwI3B1RPw0Iv4nIt6JiEcj4i8lDZG0QNLraVkgaUhqe4akBklfl/TfwI8lXSbpF81+Rkj6UFq/S9Id6Qrpd5J+KenodNw3Jb0gaWqP/yLsfc0BY5bHx4Ay4OFWts8FTgOqgCnAdOCbJduPBo4ExgO17fyZ/ysd4yhgN/A08Kv0/kHg5g6dgVkXOWDM8hgJ/CYi9rSyvQa4MSK2RMRW4Abg8yXb9wHzImJ3ROxq5898OCKWR0QjRbA1RsQ9EbEXWAT4CsZ6lAPGLI9twFFtjJ8cA2wseb8x1ZpsTUHREW+UrO9q4f2wDh7PrEscMGZ5PA00Aue1sv11ittfTcalWpPmjzn/H6C86Y2ko7uhj2ZZeXaKWQYRsUPS3wC3S9oDPAG8A5wFnAn8BPimpGcpwuRvgPvaOORzwCRJVcALwPUZu2/WLRwwZplExM2S3qAYeH8YeIviyubbQD1wBLAy7f6vwLfaONaLkm4E/p3idtd1wBX5em/WdfIXjpnlJ+kUoCYi/qK3+2LWUzwGY5aZpGHAKxS3x8zeNxwwZvn9JdAA/N/e7ohZT/ItMjMzy8JXMGZmloVnkSVHHXVUVFZW9nY3zMz6leXLl/8mIka1tM0Bk1RWVlJfX9/b3TAz61ckbWxtm2+RmZlZFg4YMzPLwgFjZmZZeAzGzKzEO++8Q0NDA42NHX2Y9aGtrKyMiooKBg8e3O42DhgzsxINDQ0cfvjhVFZWIqm3u9MnRATbtm2joaGBCRMmtLudb5GZ9WV1dVBZCQMGFK91db3do0NeY2MjI0eOdLiUkMTIkSM7fFXnKxizvqquDmprYefO4v3GjcV7gJqa3uvX+4DD5b068zvxFYxZXzV37rvh0mTnzqJu1g84YMz6qk2bOla3Q8bAgQOpqqpi0qRJTJkyhZtvvpl9+/Zl+3nbtm3jzDPPZNiwYVxzzTXddlzfIjPrq8aNK26LtVS3Q9rQoUNZsWIFAFu2bOHiiy9mx44d3HDDDVl+XllZGTfddBPPP/88zz//fLcd11cwZn3V/PlQXn5grby8qFufkXsexujRo1m4cCG33XYbEUFjYyNf+MIXmDx5MlOnTuXJJ58EYPXq1UyfPp2qqipOPvlk1q9fD8B99923v37FFVewd+/e9/yMww47jI9//OOUlZV1a98dMGZ9VU0NLFwI48eDVLwuXOgB/j6kaR7Gxo0Q8e48jO4OmeOOO459+/axZcsWbr/9dgBWrVrFT37yE+bMmUNjYyM/+MEP+MpXvsKKFSuor6+noqKCtWvXsmjRIn75y1+yYsUKBg4cSF0PzkT0LTKzvqymxoHSh7U1D6O7/2xN3931i1/8gi9/+csAfOQjH2H8+PG8+OKLfOxjH2P+/Pk0NDTw2c9+lhNOOIElS5awfPlyTj31VAB27drF6NGju7djbfAVjJlZJ/XUPIyXXnqJgQMHMnr0aFr7ksiLL76YRx55hKFDhzJr1iyWLl1KRDBnzhxWrFjBihUrWLduHddffz0PP/wwVVVVVFVVZX2KfLaAkVQm6RlJz0laLemGVL9e0muSVqTlnJI210naIGmdpFkl9WmSVqVttypNyJY0RNKiVF8mqbKkzRxJ69MyJ9d5mtn7V2vzLbpzHsbWrVu58sorueaaa5DEH/3RH+2/zfXiiy+yadMm/vAP/5CXXnqJ4447jmuvvZbPfOYzrFy5khkzZvDggw+yZcsWALZv387GjRs5//zz94dOdXV193W2uYjIsgAChqX1wcAy4DTgeuBrLew/EXgOGAJMAH4NDEzbngE+lo75GPCpVP8S8IO0PhtYlNaPBF5KryPS+oi2+jtt2rQwM1uzZk27973vvojy8ohiBKZYysuLelcMGDAgpkyZEhMnToyTTz45vve978XevXsjImLXrl0xZ86cOOmkk6KqqiqWLl0aERHf/va3Y+LEiTFlypSYNWtWbNu2LSIi7r///pgyZUpMnjw5TjnllHj66adb/Jnjx4+PESNGxGGHHRZjx46N1atXv2efln43QH20lgOtbejOBSgHfgV8tI2AuQ64ruT94ylUxgAvlNQvAv6xdJ+0Pgj4TQqh/fukbf8IXNRWHx0wZhbRsYCJKMJk/PgIqXjtarj0ZR0NmKxjMJIGSloBbAEWR8SytOkaSSsl/UjSiFQbC7xa0rwh1cam9eb1A9pExB5gBzCyjWM171+tpHpJ9Vu3bu3CmZrZ+1VNDbzyCuzbV7x6Tsa7sgZMROyNiCqgApgu6STgTuB4oArYDHw/7d7Sg26ijXpn25T2b2FEVEdE9ahRLX6ltJmZdVKPzCKLiLeA/wDOjog3UvDsA/4JmJ52awCOLWlWAbye6hUt1A9oI2kQMBzY3saxzMysh+ScRTZK0gfS+lDgLOAFSWNKdjsfaHouwSPA7DQzbAJwAvBMRGwG3pZ0Wpo9dinws5I2TTPELgCWpnuCjwMzJY1It+BmppqZmfWQnB+0HAPcLWkgRZA9EBE/l3SvpCqKW1avAFcARMRqSQ8Aa4A9wNUR0fRMg6uAu4ChFLPIHkv1HwL3StpAceUyOx1ru6SbgGfTfjdGxPaM52pmZs1kC5iIWAlMbaH++TbazAfe86CliKgHTmqh3ghc2MqxfgT8qANdNjOzbuRP8puZ9TE9/bj+xYsXM23aNCZPnsy0adNYunRptxzXzyIzM+tjevpx/UcddRSPPvooxxxzDM8//zyzZs3itdde6/JxfQVjZtYFdavqqFxQyYAbBlC5oJK6Vd37tOKeeFz/1KlTOeaYYwCYNGkSjY2N7N69u8t9d8CYmXVS3ao6ah+tZeOOjQTBxh0bqX20tttDpicf1//QQw8xdepUhgwZ0uV++xaZmVknzV0yl53vHPi8/p3v7GTukrnUTO7ej/RHDzyuf/Xq1Xz961/niSee6JY++wrGzKyTNu1o+bn8rdU7qyce19/Q0MD555/PPffcw/HHH98t/XbAmJl10rjhLT+Xv7V6Z/TE4/rfeustPv3pT/Od73yH008/vdv67oAxM+uk+TPmUz64/IBa+eBy5s94z8f5OmTXrl37pymfddZZzJw5k3nz5gHwpS99ib179zJ58mQ+97nPcddddzFkyBAWLVrESSedRFVVFS+88AKXXnopEydO5Fvf+hYzZ87k5JNP5pOf/CSbN29+z8+77bbb2LBhAzfddNP+K5umUOoKtXa59X5TXV0dOb/Zzcz6h7Vr13LiiSe2e/+6VXXMXTKXTTs2MW74OObPmN/t4y99RUu/G0nLI6LFby3zIL+ZWRfUTK45ZAOlq3yLzMzMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZWR+ybdu2/Z9FOfrooxk7duz+97///e8P2HfBggXs3LmzlSO964wzzqA3PobhacpmZn3IyJEj9z+q//rrr2fYsGF87Wtfa3HfBQsWcMkll1BeXt7i9t7mKxgzs66oq4PKShgwoHg9yNOKO2PJkiVMnTqVyZMn88UvfpHdu3dz66238vrrr3PmmWdy5plnAnDVVVdRXV3NpEmT9n/yvzc5YMzMOquuDmprYeNGiChea2u7NWQaGxu57LLLWLRoEatWrWLPnj3ceeedXHvttRxzzDE8+eST+78TZv78+dTX17Ny5Ur+8z//k5UrV3ZbPzrDAWNm1llz50LzMZCdO4t6N9m7dy8TJkzgwx/+MABz5szhqaeeanHfBx54gFNOOYWpU6eyevVq1qxZ02396AyPwZiZddamVh7L31q9Ew477LB27ffyyy/z93//9zz77LOMGDGCyy67jMbGxm7rR2f4CsbMrLPGtfJY/tbqndDY2Mgrr7zChg0bALj33nv5xCc+AcDhhx/O22+/DcBvf/tbDjvsMIYPH84bb7zBY4891m196CxfwZiZddb8+cWYS+ltsvLyot5NysrK+PGPf8yFF17Inj17OPXUU7nyyisBqK2t5VOf+hRjxozhySefZOrUqUyaNInjjjuuW7/XpbP8uP7Ej+s3M+j44/qpqyvGXDZtKq5c5s+HmkPz6cp+XL+ZWU+qqTlkA6WrPAZjZmZZOGDMzJrx0MF7deZ34oAxMytRVlbGtm3bHDIlIoJt27ZRVlbWoXYegzEzK1FRUUFDQwNbt27t7a70KWVlZVRUVHSojQPGzKzE4MGDmTBhQm9345DgW2RmZpaFA8bMzLLIFjCSyiQ9I+k5Sasl3ZDqR0paLGl9eh1R0uY6SRskrZM0q6Q+TdKqtO1WSUr1IZIWpfoySZUlbeakn7Fe0pxc52lmZi3LeQWzG/jjiJgCVAFnSzoN+AawJCJOAJak90iaCMwGJgFnA3dIGpiOdSdQC5yQlrNT/XLgzYj4EHAL8N10rCOBecBHgenAvNIgMzOz/LIFTBR+l94OTksA5wJ3p/rdwHlp/Vzg/ojYHREvAxuA6ZLGAEdExNNRzBu8p1mbpmM9CMxIVzezgMURsT0i3gQW824omZlZD8g6BiNpoKQVwBaK/+EvAz4YEZsB0uvotPtY4NWS5g2pNjatN68f0CYi9gA7gJFtHKt5/2ol1Uuq95REM7PulTVgImJvRFQBFRRXIye1sbtaOkQb9c62Ke3fwoiojojqUaNGtdE1MzPrqB6ZRRYRbwH/QXGb6o1024v0uiXt1gAcW9KsAng91StaqB/QRtIgYDiwvY1jmZlZD8k5i2yUpA+k9aHAWcALwCNA06yuOcDP0vojwOw0M2wCxWD+M+k22tuSTkvjK5c2a9N0rAuApWmc5nFgpqQRaXB/ZqqZmVkPyflJ/jHA3Wkm2ADggYj4uaSngQckXQ5sAi4EiIjVkh4A1gB7gKsjYm861lXAXcBQ4LG0APwQuFfSBoorl9npWNsl3QQ8m/a7MSK2ZzxXMzNrxl84lvgLx8zMOq6tLxzzJ/nNzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPL4qABI2mWpMslVTarfzFXp8zMrP9rM2AkfRuYC0wGlkj6csnma3J2zMzM+reDXcH8KfDHEfFVYBrwKUm3pG1qq6GkYyU9KWmtpNWSvpLq10t6TdKKtJxT0uY6SRskrZM0q6Q+TdKqtO1WSUr1IZIWpfqy0qssSXMkrU/LnA78TszMrBscLGAGRcQegIh4iyJwjpD0r8AfHKTtHuAvIuJE4DTgakkT07ZbIqIqLf8GkLbNBiYBZwN3SBqY9r8TqAVOSMvZqX458GZEfAi4BfhuOtaRwDzgo8B0YJ6kEQfpr5mZdaODBcyvJX2i6U1E7I2Iy4F1wIltNYyIzRHxq7T+NrAWGNtGk3OB+yNid0S8DGwApksaAxwREU9HRAD3AOeVtLk7rT8IzEhXN7OAxRGxPSLeBBbzbiiZmVkPOFjAXAg807wYEd8Ejm3vD0m3rqYCy1LpGkkrJf2o5MpiLPBqSbOGVBub1pvXD2iTrrR2ACPbOFbzftVKqpdUv3Xr1vaejpmZtUObARMRuyJilwqXSPobAEnjaPtqZD9Jw4CHgK9GxG8pbncdD1QBm4HvN+3aUhfaqHe2zbuFiIURUR0R1aNGjWrzPMzMrGPa+zmYO4CPARel928Dtx+skaTBFOFSFxE/BYiIN9Kttn3AP1GMkUBxlVF6VVQBvJ7qFS3UD2gjaRAwHNjexrHMzKyHtDdgPhoRVwONAGlco81B/jQW8kNgbUTcXFIfU7Lb+cDzaf0RYHaaGTaBYjD/mYjYDLwt6bR0zEuBn5W0aZohdgGwNI3TPA7MlDQi3YKbmWpmZtZDBrVzv3fSjK4AkDQK2HeQNqcDnwdWSVqRan8NXCSpKh3rFeAKgIhYLekBYA3FDLSrI2JvancVcBcwFHgsLVAE2L2SNlBcucxOx9ou6Sbg2bTfjRGxvZ3namZm3UDFP/gPspNUA3wOOIVi1tYFwDcj4l/zdq/nVFdXR319fW93w8ysX5G0PCKqW9rWrltkEVEH/BXwHYqB+fMOpXAx66vq6qCyEgYMKF7r6nq7R2bt166AkXQ88HJE3E4xZvJJSR/I2jOz97m6OqithY0bIaJ4ra11yFj/0d5B/oeAvZI+BPwzMAH4l2y9MjPmzoWdOw+s7dxZ1M36g/YGzL70QcbPAv8QEX8GjDlIGzPrgk2bOlY362vaGzDvSLqIYorwz1NtcJ4umRnAuHEdq5v1Ne0NmC9QfNByfkS8nD6ncl++bpnZ/PlQXn5grby8qJv1B+2dRbYG+BrFZ1pOAhoi4m+z9szsfa6mBhYuhPHjQSpeFy4s6mb9Qbs+aCnpDIrPv7xC8ZyvYyXNiYin8nXNzGpqHCjWf7X3k/zfB2ZGxDoASR8GfkLxJWRmZmbv0d4xmMFN4QIQES/iQX4zM2tDe69g6iX9ELg3va8BlufpkpmZHQraGzBXAVcD11KMwTxF8Qh/MzOzFrUrYCJit6R7gXsjwl/9aGZmB9XmGEz6JsvrJf0GeAFYJ2lr0zdbmpmZteZgg/xfpfhel1MjYmREHAl8FDhd0p9l752ZmfVbBwuYS4GLIuLlpkJEvARckraZmZm16GABMzgiftO8mMZhPE3ZzMxadbCA+X0nt5mZ2fvcwWaRTZH02xbqAsoy9MfMzA4RbQZMRAzsqY6Ymdmhpb2PijEzM+sQB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmlkW2gJF0rKQnJa2VtFrSV1L9SEmLJa1PryNK2lwnaYOkdZJmldSnSVqVtt0qSak+RNKiVF8mqbKkzZz0M9ZLmpPrPM3MrGU5r2D2AH8REScCpwFXS5oIfANYEhEnAEvSe9K22cAk4GzgDklNT3O+E6gFTkjL2al+OfBmRHwIuAX4bjrWkcA8iq93ng7MKw0yMzPLL1vARMTmiPhVWn8bWAuMBc4F7k673Q2cl9bPBe6PiN3pK5o3ANMljQGOiIinIyKAe5q1aTrWg8CMdHUzC1gcEdsj4k1gMe+GkpmZ9YAeGYNJt66mAsuAD0bEZihCCBiddhsLvFrSrCHVxqb15vUD2kTEHmAHMLKNYzXvV62kekn1W7du7fwJmpnZe2QPGEnDgIeAr0ZES9+OuX/XFmrRRr2zbd4tRCyMiOqIqB41alQbXTMzs47KGjCSBlOES11E/DSV30i3vUivW1K9ATi2pHkF8HqqV7RQP6CNpEHAcGB7G8cyM7MeknMWmYAfAmsj4uaSTY8ATbO65gA/K6nPTjPDJlAM5j+TbqO9Lem0dMxLm7VpOtYFwNI0TvM4MFPSiDS4PzPVzMyshwzKeOzTgc8DqyStSLW/Bv4WeEDS5cAm4EKAiFgt6QFgDcUMtKsjYm9qdxVwFzAUeCwtUATYvZI2UFy5zE7H2i7pJuDZtN+NEbE914mamdl7qfgHv1VXV0d9fX1vd8PMrF+RtDwiqlva5k/ym5lZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmJlZFg4YMzPLwgFjZmZZOGDMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMssgWMJJ+JGmLpOdLatdLek3SirScU7LtOkkbJK2TNKukPk3SqrTtVklK9SGSFqX6MkmVJW3mSFqfljm5ztHMzFqX8wrmLuDsFuq3RERVWv4NQNJEYDYwKbW5Q9LAtP+dQC1wQlqajnk58GZEfAi4BfhuOtaRwDzgo8B0YJ6kEd1/emZm1pZsARMRTwHb27n7ucD9EbE7Il4GNgDTJY0BjoiIpyMigHuA80ra3J3WHwRmpKubWcDiiNgeEW8Ci2k56MzMLKPeGIO5RtLKdAut6cpiLPBqyT4NqTY2rTevH9AmIvYAO4CRbRzLzMx6UE8HzJ3A8UAVsBn4fqqrhX2jjXpn2xxAUq2kekn1W7dubavfZmbWQT0aMBHxRkTsjYh9wD9RjJFAcZVxbMmuFcDrqV7RQv2ANpIGAcMpbsm1dqyW+rMwIqojonrUqFFdOTUzM2umRwMmjak0OR9ommH2CDA7zQybQDGY/0xEbAbelnRaGl+5FPhZSZumGWIXAEvTOM3jwExJI9ItuJmpZmZmPWhQrgNL+glwBnCUpAaKmV1nSKqiuGX1CnAFQESslvQAsAbYA1wdEXvToa6imJE2FHgsLQA/BO6VtIHiymV2OtZ2STcBz6b9boyI9k42MDOzbqLiH/1WXV0d9fX1vd0NM7N+RdLyiKhuaZs/yW9mZlk4YMzMLAsHjJmZZeGAMTOzLBwwZmaWhQPGzMyycMCYmVkWDhgzM8vCAWNmZlk4YMzMLAsHjJmZZeGAMTOzLBwwZmaWhQPGzMyycMCYmVkWDhizPqxuVR2VCyoZcMMAKhdUUreqrre7ZNZu2b7R0sy6pm5VHbWP1rLznZ0AbNyxkdpHawGomVzTm10zaxdfwZj1UXOXzN0fLk12vrOTuUvm9lKPzDrGAWPWR23asalDdbO+xgFj1keNGz6uQ3WzvsYBY9ZHzZ8xn/LB5QfUygeXM3/G/F7qkVnHOGDM+qiayTUs/NOFjB8+HiHGDx/Pwj9d6AF+6zcUEb3dhz6huro66uvre7sbZmb9iqTlEVHd0jZfwZiZWRYOGDMzy8IBY2ZmWThgzMwsCweMmZll4VlkiaStwMbe7kcnHAX8prc70cN8zu8PPuf+YXxEjGppgwOmn5NU39oUwUOVz/n9wefc//kWmZmZZeGAMTOzLBww/d/C3u5AL/A5vz/4nPs5j8GYmVkWvoIxM7MsHDBmZpaFA6YfkHSkpMWS1qfXEa3sd7akdZI2SPpGC9u/JikkHZW/113T1XOW9D1JL0haKelhSR/oud63Xzv+ZpJ0a9q+UtIp7W3bV3X2nCUdK+lJSWslrZb0lZ7vfed05e+ctg+U9P8k/bznet0NIsJLH1+AvwO+kda/AXy3hX0GAr8GjgP+AHgOmFiy/VjgcYoPkx7V2+eU+5yBmcCgtP7dltr39nKwv1na5xzgMUDAacCy9rbti0sXz3kMcEpaPxx48VA/55Ltfw78C/Dz3j6fjiy+gukfzgXuTut3A+e1sM90YENEvBQRvwfuT+2a3AL8FdBfZnV06Zwj4omI2JP2+y+gInN/O+NgfzPS+3ui8F/ABySNaWfbvqjT5xwRmyPiVwAR8TawFhjbk53vpK78nZFUAXwa+Oee7HR3cMD0Dx+MiM0A6XV0C/uMBV4ted+Qakj6DPBaRDyXu6PdqEvn3MwXKf512Ne0p/+t7dPec+9runLO+0mqBKYCy7q9h92vq+e8gOIfh/tydTCXQb3dAStI+nfg6BY2zW3vIVqohaTydIyZne1bLrnOudnPmAvsAeo61rsecdD+t7FPe9r2RV0552KjNAx4CPhqRPy2G/uWS6fPWdKfAFsiYrmkM7q9Z5k5YPqIiDirtW2S3mi6RZAum7e0sFsDxThLkwrgdeB4YALwnKSm+q8kTY+I/+62E+iEjOfcdIw5wJ8AMyLdyO5j2uz/Qfb5g3a07Yu6cs5IGkwRLnUR8dOM/exOXTnnC4DPSDoHKAOOkHRfRFySsb/dp7cHgbwcfAG+x4ED3n/Xwj6DgJcowqRpIHFSC/u9Qv8Y5O/SOQNnA2uAUb19Lm2c40H/ZhT33ksHf5/pyN+7ry1dPGcB9wALevs8euqcm+1zBv1skL/XO+ClHX8kGAksAdan1yNT/Rjg30r2O4diZs2vgbmtHKu/BEyXzhnYQHFPe0VaftDb59TKeb6n/8CVwJVpXcDtafsqoLojf+++uHT2nIGPU9xaWlnydz2nt88n99+55Bj9LmD8qBgzM8vCs8jMzCwLB4yZmWXhgDEzsywcMGZmloUDxszMsnDAmPUQSXslrUhPAn5O0p9L6tb/BiXNl/SqpN9153HNOsPTlM16iKTfRcSwtD6a4um4v4yIed34M06jeGL2+qafZdZbfAVj1gsiYgtQC1yTvgukTNKPJa1K3/txJoCkSZKeSVc+KyWdkOqXlNT/UdLAdNz/ivSQULPe5oAx6yUR8RLFf4OjgatTbTJwEXC3pDKKT3v/Q0RUAdVAg6QTgc8Bp6f6XqCmF07BrE1+2KVZ72p6iu7Hgf8DEBEvSNoIfBh4GpibvhPkpxGxXtIMYBrwbHqA6VBafhioWa9ywJj1EknHUVx9bKHlx7UTEf8iaRnFwxAfl/S/0753R8R1PdZZs07wLTKzXiBpFPAD4LYoZto8RbrNJenDwDhgXQqhlyLiVuAR4GSKh39ekCYKIOlISeN74TTM2uSAMes5Q5umKQP/DjwB3JC23QEMlLQKWARcFhG7KUJSjZgAAABdSURBVMZanpe0AvgIxdfqrgG+CTwhaSWwmOL76pH0d5IagHJJDZKu78HzMzuApymbmVkWvoIxM7MsHDBmZpaFA8bMzLJwwJiZWRYOGDMzy8IBY2ZmWThgzMwsi/8PPqrw8IwdiGIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for idx in range(0,len(city)):    \n",
    "    C = df3[df3['CITY']==city[idx]].reset_index()        \n",
    "    plt.scatter(np.arange(0,len(C)),C['Dose1'],color='blue',label='Dose-1')\n",
    "    plt.scatter(np.arange(0,len(C)),C['Dose2'],color='green',label='Dose-2')\n",
    "    plt.scatter(np.arange(0,len(C)),C['Total'],color='red',label='Total')\n",
    "    plt.title(city[idx])\n",
    "    plt.xlabel('Dose1')\n",
    "    plt.ylabel('Dose2')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}