Question5.ipynb

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    "Library import"
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   "execution_count": 5,
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from numpy import median"
   ]
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   "metadata": {},
   "source": [
    "Reading csv file"
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   "cell_type": "code",
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   "source": [
    "data = pd.read_csv('impute_country_vaccination_stats.csv') "
   ]
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   "source": [
    "Medians are found for each country and added to the countries and medians lists. Then, a DataFrame is created from these two lists (with the median at the top) and the first 3 rows are returned with the head() method. The USA, China and India came out as the countries with the highest daily vaccination amount."
   ]
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   "metadata": {},
   "outputs": [],
   "source": [
    "country = data['country'].unique()\n",
    "countries = []\n",
    "medians = []\n",
    "\n",
    "for i in country:\n",
    "    a = pd.DataFrame(data[data['country'] == i])\n",
    "    #b = median(a['daily_vaccinations'])\n",
    "    countries.append(i)\n",
    "    medians.append(median(a['daily_vaccinations']))\n",
    "    #print(i,\"ülksinin medyani:\",b,\"\\n\")\n"
   ]
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   "cell_type": "code",
   "execution_count": 8,
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   "outputs": [],
   "source": [
    "mediantable = pd.DataFrame(list(zip(ulkeler, medyanlar)),columns =['ulke', 'medyan']).sort_values(by=['medyan'],ascending=False).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "        vertical-align: top;\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ulke</th>\n",
       "      <th>medyan</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>378253.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>China</td>\n",
       "      <td>276786.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>India</td>\n",
       "      <td>173922.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "            ulke    medyan\n",
       "0  United States  378253.0\n",
       "1          China  276786.0\n",
       "2          India  173922.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mediantable.head(3)"
   ]
  }
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