diff --git a/business_idea/business_idea_stats.ipynb b/business_idea/business_idea_stats.ipynb index 4d4bcc3..e69de29 100644 --- a/business_idea/business_idea_stats.ipynb +++ b/business_idea/business_idea_stats.ipynb @@ -1,1278 +0,0 @@ -<<<<<<< HEAD -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Statistics for the business idea" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Business idea\n", - "\n", - "This file contains all the plots we made related to our business idea. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Business idea statistics \n", - "\n", - "- [The timeframe](#The-timeframe)\n", - "- [The normal topics dataframe](#Dataframe-for-all-the-tweets-in-a-conversation)\n", - "- [The dataframes per airline](#Dataframes-per-Airline)\n", - "- [Number of tweets per topic (in presentation)](#Number-of-tweets-per-topic)\n", - "- [Number of tweets per airline](#Number-of-tweets-per-airline-that-have-a-topic)\n", - "- [Number of tweets per topic for all airlines separately](#Number-of-tweets-per-topic-per-Airline)\n", - "- [Percentage of tweets per airline for all topics separately](#Percentage-of-tweets-per-topic-for-all-airlines)\n", - "- [Stacked bar chart with airlines and topics (in presentation)](#Stacked-bar-chart-topics-and-airlines)\n", - "- [Coocurring topics](#Number-of_coocurring-topics)" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "metadata": {}, - "outputs": [ - { - "ename": "ProgrammingError", - "evalue": "1045 (28000): Access denied for user 'root'@'localhost' (using password: NO)", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mProgrammingError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[105], line 9\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mseaborn\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01msns\u001b[39;00m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m----> 9\u001b[0m connection \u001b[38;5;241m=\u001b[39m \u001b[43mmysql\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mhost\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlocalhost\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43muser\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mroot\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43mpassword\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[43mdatabase\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mjbg030\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\n\u001b[0;32m 14\u001b[0m \u001b[43m)\u001b[49m\n\u001b[0;32m 16\u001b[0m cursor \u001b[38;5;241m=\u001b[39m connection\u001b[38;5;241m.\u001b[39mcursor()\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\pooling.py:294\u001b[0m, in \u001b[0;36mconnect\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 292\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m CMySQLConnection \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m use_pure:\n\u001b[0;32m 293\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m CMySQLConnection(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m--> 294\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mMySQLConnection\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\connection.py:164\u001b[0m, in \u001b[0;36mMySQLConnection.__init__\u001b[1;34m(self, **kwargs)\u001b[0m\n\u001b[0;32m 162\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m kwargs:\n\u001b[0;32m 163\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 164\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 165\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[0;32m 166\u001b[0m \u001b[38;5;66;03m# Tidy-up underlying socket on failure\u001b[39;00m\n\u001b[0;32m 167\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclose()\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\abstracts.py:1181\u001b[0m, in \u001b[0;36mMySQLConnectionAbstract.connect\u001b[1;34m(self, **kwargs)\u001b[0m\n\u001b[0;32m 1178\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 1180\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdisconnect()\n\u001b[1;32m-> 1181\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_open_connection\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1182\u001b[0m \u001b[38;5;66;03m# Server does not allow to run any other statement different from ALTER\u001b[39;00m\n\u001b[0;32m 1183\u001b[0m \u001b[38;5;66;03m# when user's password has been expired.\u001b[39;00m\n\u001b[0;32m 1184\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_client_flags \u001b[38;5;241m&\u001b[39m ClientFlag\u001b[38;5;241m.\u001b[39mCAN_HANDLE_EXPIRED_PASSWORDS:\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\connection.py:572\u001b[0m, in \u001b[0;36mMySQLConnection._open_connection\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 570\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_socket\u001b[38;5;241m.\u001b[39mopen_connection()\n\u001b[0;32m 571\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_do_handshake()\n\u001b[1;32m--> 572\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_do_auth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 573\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_user\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_password\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 575\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_database\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 576\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client_flags\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 577\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_charset_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 578\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_ssl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 579\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_conn_attrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 580\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 581\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mset_converter_class(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_converter_class)\n\u001b[0;32m 582\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_client_flags \u001b[38;5;241m&\u001b[39m ClientFlag\u001b[38;5;241m.\u001b[39mCOMPRESS:\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\connection.py:309\u001b[0m, in \u001b[0;36mMySQLConnection._do_auth\u001b[1;34m(self, username, password, database, client_flags, charset, ssl_options, conn_attrs)\u001b[0m\n\u001b[0;32m 296\u001b[0m packet \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_protocol\u001b[38;5;241m.\u001b[39mmake_auth(\n\u001b[0;32m 297\u001b[0m handshake\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handshake,\n\u001b[0;32m 298\u001b[0m username\u001b[38;5;241m=\u001b[39musername,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 306\u001b[0m auth_plugin_class\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_auth_plugin_class,\n\u001b[0;32m 307\u001b[0m )\n\u001b[0;32m 308\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_socket\u001b[38;5;241m.\u001b[39msend(packet)\n\u001b[1;32m--> 309\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_auth_switch_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43musername\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpassword\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 311\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (client_flags \u001b[38;5;241m&\u001b[39m ClientFlag\u001b[38;5;241m.\u001b[39mCONNECT_WITH_DB) \u001b[38;5;129;01mand\u001b[39;00m database:\n\u001b[0;32m 312\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcmd_init_db(database)\n", - "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\mysql\\connector\\connection.py:366\u001b[0m, in \u001b[0;36mMySQLConnection._auth_switch_request\u001b[1;34m(self, username, password)\u001b[0m\n\u001b[0;32m 364\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_mfa(packet)\n\u001b[0;32m 365\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m packet[\u001b[38;5;241m4\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m255\u001b[39m:\n\u001b[1;32m--> 366\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m get_exception(packet)\n\u001b[0;32m 367\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n", - "\u001b[1;31mProgrammingError\u001b[0m: 1045 (28000): Access denied for user 'root'@'localhost' (using password: NO)" - ] - } - ], - "source": [ - "# Imports and setting up MySQL\n", - "\n", - "\n", - "import mysql.connector\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "import numpy as np\n", - "\n", - "connection = mysql.connector.connect(\n", - " host='localhost',\n", - " user='root',\n", - " password='',\n", - " database='jbg030'\n", - ")\n", - "\n", - "cursor = connection.cursor()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### The timeframe" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [ - "# Input for now is year-month-day\n", - "timeframe = {'start': ['2019', '06', '10'], 'end':['2020', '01', '12']}\n", - "timeframe_start = f'{timeframe['start'][2]}/{timeframe['start'][1]}/{timeframe['start'][0]}'\n", - "timeframe_end = f'{timeframe['end'][2]}/{timeframe['end'][1]}/{timeframe['end'][0]}'\n", - "\n", - "start_date = pd.to_datetime(timeframe_start)\n", - "end_date = pd.to_datetime(timeframe_end)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dataframe for all the tweets in a conversation" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\3038341243.py:17: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_topics1 = pd.read_sql(conv_topics1, connection)\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\3038341243.py:18: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_topics2 = pd.read_sql(conv_topics2, connection)\n" - ] - } - ], - "source": [ - "conv_topics1 = \"\"\"\n", - " SELECT text, id, staff, baggage, delay_and_cancellation, money, timestamp_ms\n", - " FROM tweets \n", - " WHERE TRIM(language) = 'en' AND (mentioned_airlines LIKE '%Lufthansa%' OR mentioned_airlines LIKE '%British_Airways%' OR mentioned_airlines LIKE '%KLM%' OR mentioned_airlines LIKE '%AirFrance%')\n", - "\"\"\"\n", - "conv_topics2 = \"\"\"\n", - " SELECT tweets.text, tweets.id, tweets.staff, tweets.baggage, tweets.delay_and_cancellation, tweets.money, tweets.timestamp_ms\n", - " FROM tweets \n", - " JOIN hasher ON tweets.id = hasher.id\n", - " JOIN conversations ON hasher.conversation_id = conversations.conversation_id\n", - " WHERE TRIM(language) = 'en' AND conversations.conversation_id IN (\n", - " SELECT conv.conversation_id\n", - " FROM conversations AS conv\n", - " WHERE conv.airline LIKE '%Lufthansa%' OR conv.airline LIKE '%British_Airways%' OR conv.airline LIKE '%KLM%' OR conv.airline LIKE '%AirFrance%'\n", - " )\n", - "\"\"\"\n", - "df_topics1 = pd.read_sql(conv_topics1, connection)\n", - "df_topics2 = pd.read_sql(conv_topics2, connection)\n", - "\n", - "df_topics = pd.concat([df_topics1, df_topics2], ignore_index=True, axis=0)\n", - "df_topics = df_topics.drop_duplicates()\n", - "\n", - "df_topics['time'] = pd.to_datetime(df_topics['timestamp_ms'], unit='ms')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Creates a new dataframe with all the tweets in a certain time period" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [], - "source": [ - "mask = (df_topics['time'] >= start_date) & (df_topics['time'] <= end_date)\n", - "df_topics_time = df_topics.loc[mask].copy()" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [], - "source": [ - "# Drops all the columns that we do not need anymore\n", - "\n", - "columns_drop = ['text', 'id', 'timestamp_ms', 'time']\n", - "df_topics_time = df_topics_time.drop(columns=columns_drop)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dataframes per Airline" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\3362364312.py:18: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_ba1 = pd.read_sql(conv_ba1, connection)\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\3362364312.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_ba2 = pd.read_sql(conv_ba2, connection)\n" - ] - } - ], - "source": [ - "# Creates the Dataframe for British Airways\n", - "\n", - "conv_ba1 = \"\"\"\n", - " SELECT text, id, staff, baggage, delay_and_cancellation, money, timestamp_ms\n", - " FROM tweets \n", - " WHERE TRIM(language) = 'en' AND mentioned_airlines LIKE '%British_Airways%'\n", - "\"\"\"\n", - "conv_ba2 = \"\"\"\n", - " SELECT tweets.text, tweets.id, tweets.staff, tweets.baggage, tweets.delay_and_cancellation, tweets.money, tweets.timestamp_ms\n", - " FROM tweets \n", - " JOIN hasher ON tweets.id = hasher.id\n", - " JOIN conversations ON hasher.conversation_id = conversations.conversation_id\n", - " WHERE TRIM(language) = 'en' AND conversations.conversation_id IN (\n", - " SELECT conv.conversation_id\n", - " FROM conversations AS conv\n", - " WHERE conv.airline LIKE '%British_Airways%'\n", - " )\n", - "\"\"\"\n", - "\n", - "df_ba1 = pd.read_sql(conv_ba1, connection)\n", - "df_ba2 = pd.read_sql(conv_ba2, connection)\n", - "\n", - "df_ba = pd.concat([df_ba1, df_ba2], ignore_index=True, axis=0)\n", - "df_ba = df_ba.drop_duplicates()\n", - "\n", - "df_ba['time'] = pd.to_datetime(df_ba['timestamp_ms'], unit='ms')" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2474775066.py:18: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_af1 = pd.read_sql(conv_af1, connection)\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2474775066.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_af2 = pd.read_sql(conv_af2, connection)\n" - ] - } - ], - "source": [ - "# Creates the dataframe for AirFrance\n", - "\n", - "conv_af1 = \"\"\"\n", - " SELECT text, id, staff, baggage, delay_and_cancellation, money, timestamp_ms\n", - " FROM tweets \n", - " WHERE TRIM(language) = 'en' AND mentioned_airlines LIKE '%AirFrance%'\n", - "\"\"\"\n", - "conv_af2 = \"\"\"\n", - " SELECT tweets.text, tweets.id, tweets.staff, tweets.baggage, tweets.delay_and_cancellation, tweets.money, tweets.timestamp_ms\n", - " FROM tweets \n", - " JOIN hasher ON tweets.id = hasher.id\n", - " JOIN conversations ON hasher.conversation_id = conversations.conversation_id\n", - " WHERE TRIM(language) = 'en' AND conversations.conversation_id IN (\n", - " SELECT conv.conversation_id\n", - " FROM conversations AS conv\n", - " WHERE conv.airline LIKE '%AirFrance%'\n", - " )\n", - "\"\"\"\n", - "\n", - "df_af1 = pd.read_sql(conv_af1, connection)\n", - "df_af2 = pd.read_sql(conv_af2, connection)\n", - "\n", - "df_af = pd.concat([df_af1, df_af2], ignore_index=True, axis=0)\n", - "df_af = df_af.drop_duplicates()\n", - "\n", - "df_af['time'] = pd.to_datetime(df_af['timestamp_ms'], unit='ms')" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2117588957.py:18: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_klm1 = pd.read_sql(conv_klm1, connection)\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2117588957.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_klm2 = pd.read_sql(conv_klm2, connection)\n" - ] - } - ], - "source": [ - "# Creates the dataframe for KLM\n", - "\n", - "conv_klm1 = \"\"\"\n", - " SELECT text, id, staff, baggage, delay_and_cancellation, money, timestamp_ms\n", - " FROM tweets \n", - " WHERE TRIM(language) = 'en' AND mentioned_airlines LIKE '%KLM%'\n", - "\"\"\"\n", - "conv_klm2 = \"\"\"\n", - " SELECT tweets.text, tweets.id, tweets.staff, tweets.baggage, tweets.delay_and_cancellation, tweets.money, tweets.timestamp_ms\n", - " FROM tweets \n", - " JOIN hasher ON tweets.id = hasher.id\n", - " JOIN conversations ON hasher.conversation_id = conversations.conversation_id\n", - " WHERE TRIM(language) = 'en' AND conversations.conversation_id IN (\n", - " SELECT conv.conversation_id\n", - " FROM conversations AS conv\n", - " WHERE conv.airline LIKE '%KLM%'\n", - " )\n", - "\"\"\"\n", - "\n", - "df_klm1 = pd.read_sql(conv_klm1, connection)\n", - "df_klm2 = pd.read_sql(conv_klm2, connection)\n", - "\n", - "df_klm = pd.concat([df_klm1, df_klm2], ignore_index=True, axis=0)\n", - "df_klm = df_klm.drop_duplicates()\n", - "\n", - "df_klm['time'] = pd.to_datetime(df_klm['timestamp_ms'], unit='ms')" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\269955520.py:18: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_lh1 = pd.read_sql(conv_lh1, connection)\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\269955520.py:19: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n", - " df_lh2 = pd.read_sql(conv_lh2, connection)\n" - ] - } - ], - "source": [ - "# Creates the dataframe for Lufthansa\n", - "\n", - "conv_lh1 = \"\"\"\n", - " SELECT text, id, staff, baggage, delay_and_cancellation, money, timestamp_ms\n", - " FROM tweets \n", - " WHERE TRIM(language) = 'en' AND mentioned_airlines LIKE '%Lufthansa%'\n", - "\"\"\"\n", - "conv_lh2 = \"\"\"\n", - " SELECT tweets.text, tweets.id, tweets.staff, tweets.baggage, tweets.delay_and_cancellation, tweets.money, tweets.timestamp_ms\n", - " FROM tweets \n", - " JOIN hasher ON tweets.id = hasher.id\n", - " JOIN conversations ON hasher.conversation_id = conversations.conversation_id\n", - " WHERE TRIM(language) = 'en' AND conversations.conversation_id IN (\n", - " SELECT conv.conversation_id\n", - " FROM conversations AS conv\n", - " WHERE conv.airline LIKE '%Lufthansa%'\n", - " )\n", - "\"\"\"\n", - "\n", - "df_lh1 = pd.read_sql(conv_lh1, connection)\n", - "df_lh2 = pd.read_sql(conv_lh2, connection)\n", - "\n", - "df_lh = pd.concat([df_lh1, df_lh2], ignore_index=True, axis=0)\n", - "df_lh = df_lh.drop_duplicates()\n", - "\n", - "df_lh['time'] = pd.to_datetime(df_lh['timestamp_ms'], unit='ms')" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [], - "source": [ - "# Create the masks for the right timeframe\n", - "\n", - "mask_ba = (df_ba['time'] >= start_date) & (df_ba['time'] <= end_date)\n", - "mask_af = (df_af['time'] >= start_date) & (df_af['time'] <= end_date)\n", - "mask_klm = (df_klm['time'] >= start_date) & (df_klm['time'] <= end_date)\n", - "mask_lh = (df_lh['time'] >= start_date) & (df_lh['time'] <= end_date)" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [], - "source": [ - "# Gives dataframes with entries that are in the right timeframe\n", - "\n", - "df_ba_time = df_ba.loc[mask_ba]\n", - "df_af_time = df_af.loc[mask_af]\n", - "df_klm_time = df_klm.loc[mask_klm]\n", - "df_lh_time = df_lh.loc[mask_lh]" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "metadata": {}, - "outputs": [], - "source": [ - "# Drops all the columns we do not need anymore\n", - "\n", - "df_topics_ba = df_ba_time.drop(columns=columns_drop)\n", - "df_topics_af = df_af_time.drop(columns=columns_drop)\n", - "df_topics_klm = df_klm_time.drop(columns=columns_drop)\n", - "df_topics_lh = df_lh_time.drop(columns=columns_drop)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Plots" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets per topic" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "staff 29117\n", - "baggage 10811\n", - "delay_and_cancellation 66103\n", - "money 65012\n", - "dtype: int64\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "counts_topics = df_topics_time.apply(lambda col: col.value_counts().get(1, 0))\n", - "print(counts_topics)\n", - "\n", - "plt.figure(figsize=(10,6))\n", - "counts_topics.plot(kind='bar', color=sns.color_palette('colorblind'))\n", - "plt.xlabel('topics')\n", - "plt.ylabel('number of tweets')\n", - "plt.title('Number of tweets per topic', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets per airline that have a topic" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " staff baggage delay_and_cancellation money\n", - "47308 0 0 0 0\n", - "47309 0 0 0 0\n", - "47310 0 0 0 0\n", - "47311 0 0 0 0\n", - "47312 0 0 0 0\n", - "... ... ... ... ...\n", - "117204 0 0 0 0\n", - "117205 0 0 0 0\n", - "117209 0 0 0 0\n", - "117211 0 0 0 0\n", - "117212 0 0 0 0\n", - "\n", - "[61023 rows x 4 columns]\n" - ] - } - ], - "source": [ - "# Get the number of tweets per airline that have a topic\n", - "\n", - "counts_ba = df_topics_ba.apply(lambda col: col.value_counts().get(1, 0))\n", - "counts_af = df_topics_af.apply(lambda col: col.value_counts().get(1, 0))\n", - "counts_klm = df_topics_klm.apply(lambda col: col.value_counts().get(1, 0))\n", - "counts_lh = df_topics_lh.apply(lambda col: col.value_counts().get(1, 0))\n", - "\n", - "counts_ba_sum = counts_ba.sum()\n", - "counts_af_sum = counts_af.sum()\n", - "counts_klm_sum = counts_klm.sum()\n", - "counts_lh_sum = counts_lh.sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "combined_counts = pd.DataFrame({\n", - " 'Airline': ['British_Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Count': [counts_ba_sum, counts_af_sum, counts_klm_sum, counts_lh_sum]\n", - "})\n", - "\n", - "colors = ['skyblue', 'red', 'orange', 'pink']\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "combined_counts.plot(kind='bar', x='Airline', y='Count', color=colors, legend=False)\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Number of tweets')\n", - "plt.title('Number of tweets per airline belonging to a topic', weight = 'bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets per topic per Airline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### British Airways" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [], - "source": [ - "colors = ['blue', 'green', 'purple', 'orange']" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,6))\n", - "counts_ba.plot(kind='bar', color=colors)\n", - "plt.xlabel('topics')\n", - "plt.ylabel('number of tweets')\n", - "plt.title('Number of tweets per topic for British Airways', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### AirFrance" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,6))\n", - "counts_af.plot(kind='bar', color=colors)\n", - "plt.xlabel('topics')\n", - "plt.ylabel('number of tweets')\n", - "plt.title('Number of tweets per topic for AirFrance', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### KLM" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,6))\n", - "counts_klm.plot(kind='bar', color=colors)\n", - "plt.xlabel('topics')\n", - "plt.ylabel('number of tweets')\n", - "plt.title('Number of tweets per topic for KLM', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Lufthansa" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10,6))\n", - "counts_lh.plot(kind='bar', color=colors)\n", - "plt.xlabel('topics')\n", - "plt.ylabel('number of tweets')\n", - "plt.title('Number of tweets per topic for Lufthansa', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Percentage of tweets per topic for all airlines" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "metadata": {}, - "outputs": [], - "source": [ - "# Get a series object with the percentages for each topic for each airline\n", - "\n", - "percentages_ba = round((counts_ba/counts_ba_sum)*100, 2)\n", - "percentages_af = round((counts_af/counts_af_sum)*100, 2)\n", - "percentages_klm = round((counts_klm/counts_klm_sum)*100, 2)\n", - "percentages_lh = round((counts_lh/counts_lh_sum)*100, 2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Staff" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2961402507.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_staff_ba = percentages_ba[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2961402507.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_staff_af = percentages_af[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2961402507.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_staff_klm = percentages_klm[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2961402507.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_staff_lh = percentages_lh[0]\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "per_staff_ba = percentages_ba[0]\n", - "per_staff_af = percentages_af[0]\n", - "per_staff_klm = percentages_klm[0]\n", - "per_staff_lh = percentages_lh[0]\n", - "\n", - "percentages_staff = pd.DataFrame({\n", - " 'Airline': ['British Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Percent_staff': [per_staff_ba, per_staff_af, per_staff_klm, per_staff_lh]\n", - "})\n", - "\n", - "colors_airlines = ['skyblue', 'red', 'orange', 'pink']\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "percentages_staff.plot(kind='bar', x='Airline', y='Percent_staff', color=colors_airlines, legend=False)\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Percentage of staff tweets (%)')\n", - "plt.title('Percentage of tweets about staff per airline', weight = 'bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Baggage" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\967707322.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_bagg_ba = percentages_ba[1]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\967707322.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_bagg_af = percentages_af[1]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\967707322.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_bagg_klm = percentages_klm[1]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\967707322.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_bagg_lh = percentages_lh[1]\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "per_bagg_ba = percentages_ba[1]\n", - "per_bagg_af = percentages_af[1]\n", - "per_bagg_klm = percentages_klm[1]\n", - "per_bagg_lh = percentages_lh[1]\n", - "\n", - "percentages_bagg = pd.DataFrame({\n", - " 'Airline': ['British Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Percent_bagg': [per_bagg_ba, per_bagg_af, per_bagg_klm, per_bagg_lh]\n", - "})\n", - "\n", - "colors_airlines = ['skyblue', 'red', 'orange', 'pink']\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "percentages_bagg.plot(kind='bar', x='Airline', y='Percent_bagg', color=colors_airlines, legend=False)\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Percentage of baggage tweets (%)')\n", - "plt.title('Percentage of tweets about baggage per airline', weight = 'bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Delay and Cancellation" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\685534939.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_delay_ba = percentages_ba[2]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\685534939.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_delay_af = percentages_af[2]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\685534939.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_delay_klm = percentages_klm[2]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\685534939.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_delay_lh = percentages_lh[2]\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "per_delay_ba = percentages_ba[2]\n", - "per_delay_af = percentages_af[2]\n", - "per_delay_klm = percentages_klm[2]\n", - "per_delay_lh = percentages_lh[2]\n", - "\n", - "percentages_delay = pd.DataFrame({\n", - " 'Airline': ['British Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Percent_delay': [per_delay_ba, per_delay_af, per_delay_klm, per_delay_lh]\n", - "})\n", - "\n", - "colors_airlines = ['skyblue', 'red', 'orange', 'pink']\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "percentages_delay.plot(kind='bar', x='Airline', y='Percent_delay', color=colors_airlines, legend=False)\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Percentage of delay and cancellation tweets (%)')\n", - "plt.title('Percentage of tweets about delay and cancellations per airline', weight = 'bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### Money" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\1615527902.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_money_ba = percentages_ba[3]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\1615527902.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_money_af = percentages_af[3]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\1615527902.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_money_klm = percentages_klm[3]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\1615527902.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " per_money_lh = percentages_lh[3]\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "per_money_ba = percentages_ba[3]\n", - "per_money_af = percentages_af[3]\n", - "per_money_klm = percentages_klm[3]\n", - "per_money_lh = percentages_lh[3]\n", - "\n", - "percentages_money = pd.DataFrame({\n", - " 'Airline': ['British Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Percent_money': [per_money_ba, per_money_af, per_money_klm, per_money_lh]\n", - "})\n", - "\n", - "colors_airlines = ['skyblue', 'red', 'orange', 'pink']\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "percentages_money.plot(kind='bar', x='Airline', y='Percent_money', color=colors_airlines, legend=False)\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Percentage of money tweets (%)')\n", - "plt.title('Percentage of tweets about money per airline', weight = 'bold')\n", - "plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Stacked bar chart topics and airlines" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\259348465.py:8: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " 'Staff': [percentages_ba[0], percentages_af[0], percentages_klm[0], percentages_lh[0]],\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\259348465.py:9: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " 'Baggage': [percentages_ba[1], percentages_af[1], percentages_klm[1], percentages_lh[1]],\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\259348465.py:10: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " 'Delay and Cancellation': [percentages_ba[2], percentages_af[2], percentages_klm[2], percentages_lh[2]],\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\259348465.py:11: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " 'Money': [percentages_ba[3], percentages_af[3], percentages_klm[3], percentages_lh[3]]\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "percentages_ba = round((counts_ba / counts_ba_sum) * 100, 2)\n", - "percentages_af = round((counts_af / counts_af_sum) * 100, 2)\n", - "percentages_klm = round((counts_klm / counts_klm_sum) * 100, 2)\n", - "percentages_lh = round((counts_lh / counts_lh_sum) * 100, 2)\n", - "\n", - "percentages = pd.DataFrame({\n", - " 'Airline': ['British Airways', 'AirFrance', 'KLM', 'Lufthansa'],\n", - " 'Staff': [percentages_ba[0], percentages_af[0], percentages_klm[0], percentages_lh[0]],\n", - " 'Baggage': [percentages_ba[1], percentages_af[1], percentages_klm[1], percentages_lh[1]],\n", - " 'Delay and Cancellation': [percentages_ba[2], percentages_af[2], percentages_klm[2], percentages_lh[2]],\n", - " 'Money': [percentages_ba[3], percentages_af[3], percentages_klm[3], percentages_lh[3]]\n", - "})\n", - "\n", - "\n", - "percentages.set_index('Airline').plot(kind='bar', stacked=True, figsize=(10, 6), color=sns.color_palette('colorblind'))\n", - "\n", - "\n", - "plt.xlabel('Airline')\n", - "plt.ylabel('Percentage of Tweets')\n", - "plt.title('Percentage of Tweets per Topic by Airline', weight='bold')\n", - "plt.xticks(rotation=0)\n", - "plt.legend(title='Topics', bbox_to_anchor=(1.05, 1), loc='upper left')\n", - "plt.tight_layout()\n", - "\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Number of cooccuring topics" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets that contain two topics" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bdc = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['staff'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 0) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bs = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_mdc = df_topics_time[(df_topics_time['money'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:5: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_ms = df_topics_time[(df_topics_time['money'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['delay_and_cancellation'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\2442011583.py:6: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_sdc = df_topics_time[(df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]\n" - ] - } - ], - "source": [ - "count_bdc = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['staff'] == 0)].count()[0]\n", - "count_bm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 0) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "count_bs = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "count_mdc = df_topics_time[(df_topics_time['money'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]\n", - "count_ms = df_topics_time[(df_topics_time['money'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['delay_and_cancellation'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]\n", - "count_sdc = df_topics_time[(df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0) & (df_topics_time['baggage'] == 0)].count()[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "counts_two_topics = pd.DataFrame({\n", - " 'Topics': ['baggage - delay and cancellation','baggage - money', 'baggage - staff', 'money - delay and cancellation', 'money - staff', 'staff - delay and cancellation'],\n", - " 'Counts': [count_bdc, count_bm, count_bs, count_mdc, count_ms, count_sdc]\n", - "})\n", - "\n", - "plt.figure(figsize=(20, 6))\n", - "counts_two_topics.plot(kind='bar', x='Topics', y='Counts', color=sns.color_palette('colorblind'), legend=False)\n", - "plt.xlabel('Combination of topics')\n", - "plt.ylabel('Number of tweets')\n", - "plt.title('Number of tweets per pair of topics', weight = 'bold')\n", - "#plt.xticks(rotation=0)\n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets about three topics" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\996657003.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bdcs = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\996657003.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bdcm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1)& (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\996657003.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_bsm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\996657003.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_dcsm = df_topics_time[(df_topics_time['baggage'] == 0) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 1)].count()[0]\n" - ] - } - ], - "source": [ - "count_bdcs = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 0)].count()[0]\n", - "count_bdcm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1)& (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 0)].count()[0]\n", - "count_bsm = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['delay_and_cancellation'] == 0)].count()[0]\n", - "count_dcsm = df_topics_time[(df_topics_time['baggage'] == 0) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['staff'] == 1) & (df_topics_time['money'] == 1)].count()[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 102, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "counts_three_topics = pd.DataFrame({\n", - " 'Topics': ['baggage - delay and cancellation - money','baggage - money - staff', 'baggage - staff - delay and cancellation', 'money - delay and cancellation - staff'],\n", - " 'Counts': [count_bdcm, count_bsm, count_bdcs, count_dcsm]\n", - "})\n", - "\n", - "plt.figure(figsize=(20, 6))\n", - "counts_three_topics.plot(kind='bar', x='Topics', y='Counts', color=sns.color_palette('colorblind'), legend=False)\n", - "plt.xlabel('Combination of topics')\n", - "plt.ylabel('Number of tweets')\n", - "plt.title('Number of tweets per triplet of topics', weight = 'bold')\n", - "#plt.xticks(rotation=0)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Number of tweets about all four topics" - ] - }, - { - "cell_type": "code", - "execution_count": 103, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\20233498\\AppData\\Local\\Temp\\ipykernel_26700\\1606429020.py:1: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", - " count_all = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 1)].count()[0]\n" - ] - } - ], - "source": [ - "count_all = df_topics_time[(df_topics_time['baggage'] == 1) & (df_topics_time['delay_and_cancellation'] == 1) & (df_topics_time['money'] == 1) & (df_topics_time['staff'] == 1)].count()[0]\n", - "print(count_all)" - ] - } - ], - "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": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} -======= ->>>>>>> 40f842827415714eadbbf19fe3f36b42e913acc3