{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analyzing Twitter Users' Reflections using NLP\n", "_This is a notebook by Jessica Uwoghiren._" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a Sentiment Analysis Project using Natural Language Processing (NLP) Techniques. In December 2020, I felt it would be a good idea to obtain insights into how Twitter users felt about the year. Twitter receives over 500 million tweets per day from its users across the globe, so I only had to find a way to retrieve the data. This Notebook makes use of several Python libraries like Pandas (for Data Cleaning/Manipulation), Tweepy (for Tweets Mining), NLTK (Natural Language Toolkit), TextBlob (for Sentiment Analysis), MatPlotlib & WordCloud (for Data Exploration), Emot (for Emojis identification), Plotly (for some Data Visualisation)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Contents\n", "\n", "[1. Import Libraries](#1.-Import-Libraries)\n", "\n", "[2. Tweets Mining](#2.-Tweets-Mining)\n", "\n", "[3. Data Cleaning](#3.-Data-Cleaning) \n", "\n", "[4. Location Geocoding](#4.-Location-Geocoding)\n", "\n", "[5. Tweets Processing](#5.-Tweets-Processing)\n", "\n", "[6. Data Exploration](#6.-Data-Exploration)\n", "\n", "[7. Sentiment Analysis](#7.-Sentiment-Analysis)\n", "\n", "[8. Closing Remarks and Links](#THANK-YOU-FOR-TAKING-TIME-TO-STUDY-MY-NOTEBOOK.-I-HOPE-YOU-GOT-SOME-INSIGHTS.)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Import Libraries\n", "\n", "Import all the libraries to be used in this notebook. I prefer to do this at the initial stage and added more libraries as I went along on the project" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T16:41:06.939789Z", "start_time": "2021-01-06T16:41:05.011622Z" } }, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import tweepy # for tweet mining\n", "import pandas as pd # for data manipulation and analysis\n", "import numpy as np # for working with arrays and carrying out mathematical operations. Pandas is built on Numpy\n", "import csv # to read and write csv files\n", "import re # In-built regular expressions library\n", "import string # Inbuilt string library\n", "import glob # to retrieve files/pathnames matching a specified pattern. \n", "import random # generating random numbers\n", "import requests # to send HTTP requests\n", "from PIL import Image # for opening, manipulating, and saving many different image file f\n", "import matplotlib.pyplot as plt # for plotting\n", "\n", "# Set the limits for Pandas Dataframe display to avoid potential system freeze\n", "pd.set_option(\"display.max_rows\", 15)\n", "pd.set_option(\"display.max_columns\", 15)\n", "pd.set_option('display.max_colwidth', 40)\n", "\n", "# Natural Language Processing Toolkit\n", "from nltk.corpus import stopwords, words # get stopwords from NLTK library & get all words in english language\n", "from nltk.tokenize import word_tokenize # to create word tokens\n", "# from nltk.stem import PorterStemmer (I played around with Stemmer and decided to use Lemmatizer instead)\n", "from nltk.stem import WordNetLemmatizer # to reduce words to orginal form\n", "from nltk import pos_tag # For Parts of Speech tagging\n", "\n", "from textblob import TextBlob # TextBlob - Python library for processing textual data\n", "\n", "import plotly.express as px # To make express plots in Plotly\n", "import chart_studio.tools as cst # For exporting to Chart studio\n", "import chart_studio.plotly as py # for exporting Plotly visualizations to Chart Studio\n", "import plotly.offline as pyo # Set notebook mode to work in offline\n", "pyo.init_notebook_mode()\n", "import plotly.io as pio # Plotly renderer\n", "import plotly.graph_objects as go # For plotting plotly graph objects\n", "from plotly.subplots import make_subplots #to make more than one plot in Plotly\n", "\n", "\n", "# WordCloud - Python linrary for creating image wordclouds\n", "from wordcloud import WordCloud\n", "\n", "from emot.emo_unicode import UNICODE_EMO, EMOTICONS # For emojis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Tweets Mining\n", "\n", "I used the Tweepy library for Python to scrape tweets. You need a developer account with Twitter to get the keys used below for this task." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T22:07:27.073043Z", "start_time": "2020-12-25T22:07:27.064100Z" } }, "outputs": [], "source": [ "consumer_key = 'XXXXXXXXXXXXXXXXXX'\n", "consumer_secret = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXX'\n", "access_key= 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX\n", "access_secret = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T22:07:27.388199Z", "start_time": "2020-12-25T22:07:27.381216Z" } }, "outputs": [], "source": [ "auth = tweepy.OAuthHandler(consumer_key, consumer_secret) # Pass in Consumer key and secret for authentication by API\n", "auth.set_access_token(access_key, access_secret) # Pass in Access key and secret for authentication by API\n", "api = tweepy.API(auth,wait_on_rate_limit=True,wait_on_rate_limit_notify=True) # Sleeps when API limit is reached" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Creating User-defined Functions for Tweets Mining\n", "I created 4 different functions for the different search queries I had and stored them in a csv file. This is because I ran the program for 3 consecutive days 22nd to 25th of December. For the 1st run, I did not have to specify the __\"since_id\"__ but I had to for the following days so that Twitter API does not return Tweets I already had. Another thing to note is you don't have to specify a sleep time for your function. Tweepy has a built-in attribute \"wait_on_rate_limit\" which I specified above." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T19:46:09.113988Z", "start_time": "2020-12-25T19:46:09.005279Z" } }, "outputs": [], "source": [ "def get_tweets2(search_query2, num_tweets2, since_id_num2):\n", " # Collect tweets using the Cursor object\n", " # Each item in the iterator has various attributes that you can access to get information about each tweet\n", " tweet_list2 = [tweets for tweets in tweepy.Cursor(api.search,\n", " q=search_query2,\n", " lang=\"en\",\n", " since_id=since_id_num2,\n", " tweet_mode='extended').items(num_tweets2)]\n", " # Begin scraping the tweets individually:\n", " for tweet in tweet_list2[::-1]:\n", " tweet_id = tweet.id # get Tweet ID result\n", " created_at = tweet.created_at # get time tweet was created\n", " text = tweet.full_text # retrieve full tweet text\n", " location = tweet.user.location # retrieve user location\n", " retweet = tweet.retweet_count # retrieve number of retweets\n", " favorite = tweet.favorite_count # retrieve number of likes\n", " with open('tweets_2020_has_been.csv','a', newline='', encoding='utf-8') as csvFile2:\n", " csv_writer2 = csv.writer(csvFile2, delimiter=',') # create an instance of csv object\n", " csv_writer2.writerow([tweet_id, created_at, text, location, retweet, favorite]) # write each row" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:01:27.308746Z", "start_time": "2020-12-25T19:46:09.116983Z" }, "code_folding": [] }, "outputs": [], "source": [ "search_words2 = \"\\\"2020 has been\\\"\" # Specifying exact phrase to search\n", "# Exclude Links, retweets, replies\n", "search_query2 = search_words2 + \" -filter:links AND -filter:retweets AND -filter:replies\" \n", "with open('tweets_2020_has_been.csv', encoding='utf-8') as data:\n", " latest_tweet = int(list(csv.reader(data))[-1][0]) # Return the most recent tweet ID\n", "get_tweets2(search_query2, 10000, latest_tweet)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:01:27.316629Z", "start_time": "2020-12-25T20:01:27.310643Z" } }, "outputs": [], "source": [ "# Same as above\n", "def get_tweets3(search_query3, num_tweets3, since_id_num3):\n", " # Collect tweets using the Cursor object\n", " # Each item in the iterator has various attributes that you can access to get information about each tweet\n", " tweet_list3 = [tweets for tweets in tweepy.Cursor(api.search,\n", " q=search_query3,\n", " since_id=since_id_num3,\n", " lang=\"en\",\n", " tweet_mode='extended').items(num_tweets3)]\n", "\n", " # Begin scraping the tweets individually:\n", " for tweet in tweet_list3[::-1]:\n", " tweet_id = tweet.id\n", " created_at = tweet.created_at\n", " text = tweet.full_text\n", " location = tweet.user.location\n", " retweet = tweet.retweet_count\n", " favorite = tweet.favorite_count\n", " with open('tweets_2020_was_a.csv', 'a', newline='', encoding='utf-8') as csvFile3:\n", " csv_writer3 = csv.writer(csvFile3, delimiter=',')\n", " csv_writer3.writerow([tweet_id, created_at, text, location, retweet, favorite])" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:02:01.367665Z", "start_time": "2020-12-25T20:01:27.317624Z" } }, "outputs": [], "source": [ "search_words3 = \"\\\"2020 was a\\\"\" # Specifying exact phrase to search\n", "# Exclude Links, retweets, replies\n", "search_query3 = search_words3 + \" -filter:links AND -filter:retweets AND -filter:replies\"\n", "with open('tweets_2020_was_a.csv', encoding='utf-8') as data:\n", " latest_tweet = int(list(csv.reader(data))[-1][0]) # Return the most recent tweet ID\n", "get_tweets3(search_query3, 10000, latest_tweet)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:02:01.375592Z", "start_time": "2020-12-25T20:02:01.369564Z" } }, "outputs": [], "source": [ "# Same as above\n", "def get_tweets4(search_query4, num_tweets4, since_id_num4):\n", " # Collect tweets using the Cursor object\n", " # Each item in the iterator has various attributes that you can access to get information about each tweet\n", " tweet_list4 = [tweets for tweets in tweepy.Cursor(api.search,\n", " q=search_query4,\n", " lang=\"en\",\n", " since_id=since_id_num4,\n", " tweet_mode='extended').items(num_tweets4)]\n", "\n", " # Begin scraping the tweets individually:\n", " for tweet in tweet_list4[::-1]:\n", " tweet_id = tweet.id\n", " created_at = tweet.created_at\n", " text = tweet.full_text\n", " location = tweet.user.location\n", " retweet = tweet.retweet_count\n", " favorite = tweet.favorite_count\n", " with open('tweets_this_year_has_been.csv','a', newline='', encoding='utf-8') as csvFile4:\n", " csv_writer4 = csv.writer(csvFile4, delimiter=',')\n", " csv_writer4.writerow([tweet_id, created_at, text, location, retweet, favorite])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:31:56.617723Z", "start_time": "2020-12-25T20:02:01.377543Z" } }, "outputs": [], "source": [ "search_words4 = \"\\\"this year has been\\\"\" # Specifying exact phrase to search\n", "# Exclude Links, retweets, replies\n", "search_query4 = search_words4 + \" -filter:links AND -filter:retweets AND -filter:replies\"\n", "with open('tweets_this_year_has_been.csv',encoding='utf-8') as data:\n", " latest_tweet=int(list(csv.reader(data))[-1][0]) # Return the most recent tweet ID\n", "get_tweets4(search_query4,10000,latest_tweet)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:31:56.625654Z", "start_time": "2020-12-25T20:31:56.618679Z" } }, "outputs": [], "source": [ "def get_tweets5(search_query5, num_tweets5, since_id_num5):\n", " # Collect tweets using the Cursor object\n", " # Each item in the iterator has various attributes that you can access to get information about each tweet\n", " tweet_list5 = [tweets for tweets in tweepy.Cursor(api.search,\n", " q=search_query5,\n", " lang=\"en\",\n", " since_id=since_id_num5,\n", " tweet_mode='extended').items(num_tweets5)]\n", "\n", " # Begin scraping the tweets individually:\n", " for tweet in tweet_list5[::-1]:\n", " tweet_id = tweet.id\n", " created_at = tweet.created_at\n", " text = tweet.full_text\n", " location = tweet.user.location\n", " retweet = tweet.retweet_count\n", " favorite = tweet.favorite_count\n", " with open('tweets_this_year_was_a.csv','a',newline='', encoding='utf-8') as csvFile5:\n", " csv_writer5 = csv.writer(csvFile5, delimiter=',')\n", " csv_writer5.writerow([tweet_id, created_at, text, location, retweet, favorite])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:32:14.209536Z", "start_time": "2020-12-25T20:31:56.627618Z" } }, "outputs": [], "source": [ "search_words5 = \"\\\"this year was a\\\"\" # Specifying exact phrase to search\n", "search_query5 = search_words5 + \" -filter:links AND -filter:retweets AND -filter:replies\"\n", "with open('tweets_this_year_was_a.csv', encoding='utf-8') as data:\n", " latest_tweet = int(list(csv.reader(data))[-1][0]) # Return the most recent tweet ID\n", "get_tweets5(search_query5, 10000, latest_tweet)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Combining all Tweets into single Pandas Dataframe" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:41.272638Z", "start_time": "2020-12-30T00:19:41.049231Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " tweet_id created_at \\\n", "0 1340701494316830727 2020-12-20 16:51:59 \n", "1 1340701340511723525 2020-12-20 16:51:23 \n", "2 1340701052287541248 2020-12-20 16:50:14 \n", "3 1340701023367692288 2020-12-20 16:50:07 \n", "4 1340700570433310726 2020-12-20 16:48:19 \n", "\n", " text location retweet \\\n", "0 When you think 2020 has been bad and... Newcastle Upon Tyne 0 \n", "1 every single boy i hooked up with tu... NaN 0 \n", "2 if you can reply to this, you made m... north carolina 0 \n", "3 2020 has been such a cruel year but ... @retailthrpy_PH 0 \n", "4 It’s official then Amsterdam is canc... Birmingham 0 \n", "\n", " favorite \n", "0 0 \n", "1 0 \n", "2 0 \n", "3 0 \n", "4 0 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "path = r'C:\\Users\\Osas\\Twitter data' # use your path\n", "all_files = glob.glob(path + \"/*.csv\")\n", "\n", "tweets = []\n", "\n", "for filename in all_files:\n", " df = pd.read_csv(filename, index_col=None, header=0) # Convert each csv to a dataframe\n", " tweets.append(df)\n", "\n", "tweets_df = pd.concat(tweets, axis=0, ignore_index=True) # Merge all dataframes\n", "\n", "tweets_df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Data Cleaning\n", "The dataframe in Section 2 were cleaned in this section. Duplicate values were checked and removed. It is also important to mention that the Tweet ID was considered as the Primary key for all the dataframe. I also replaced \"NaN\" values in Location column because if used for Location Geocoding, \"NaN\" values return Coordinates which should not be." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:42.042538Z", "start_time": "2020-12-30T00:19:42.037553Z" } }, "outputs": [ { "data": { "text/plain": [ "(50868, 6)" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.shape #Get number of rows and columns" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:45.733707Z", "start_time": "2020-12-30T00:19:45.718748Z" } }, "outputs": [ { "data": { "text/plain": [ "88" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.duplicated(subset='tweet_id').sum() # Check for duplicate values" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:53.105960Z", "start_time": "2020-12-30T00:19:53.074045Z" } }, "outputs": [], "source": [ "tweets_df=tweets_df.drop_duplicates(subset=['tweet_id']) # drop duplicate values" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:53.971644Z", "start_time": "2020-12-30T00:19:53.965660Z" } }, "outputs": [ { "data": { "text/plain": [ "(50780, 6)" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.shape # Check the shape after dropping duplicates" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:19:57.285010Z", "start_time": "2020-12-30T00:19:57.269017Z" } }, "outputs": [ { "data": { "text/plain": [ "tweet_id False\n", "created_at False\n", "text False\n", "location True\n", "retweet False\n", "favorite False\n", "dtype: bool" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.isna().any() # Check for \"NaN\" values" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:20:19.135151Z", "start_time": "2020-12-30T00:20:19.126175Z" } }, "outputs": [], "source": [ "tweets_df['location']=tweets_df['location'].fillna('No location') # Replace \"NaN\" values with \"No Location\"" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:20:20.448691Z", "start_time": "2020-12-30T00:20:20.429727Z" } }, "outputs": [ { "data": { "text/plain": [ "tweet_id False\n", "created_at False\n", "text False\n", "location False\n", "retweet False\n", "favorite False\n", "dtype: bool" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.isna().any() # Check for \"NaN\" values again" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Location Geocoding\n", "For my final dashboard, I wanted to add a map that shows the number of tweets per country. To do that, Tableau needs basic geographic information that it can recognize. After several trials and errors, I ended up using the HERE Developer API to return Longitude, Latitude & Country names for each tweet. One key thing is if you send a request with a \"NaN\" or Null value to the API, it will return an actual location. This is why I had to replace \"NaN\" values with \"No Location\" in the step on Data Cleaning. __It is also important to study your dataframe to ensure you are getting the expected results. This is how I caught this discrepancy__" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T20:44:25.612956Z", "start_time": "2020-12-25T20:44:25.607970Z" } }, "outputs": [], "source": [ "URL = \"https://geocode.search.hereapi.com/v1/geocode\" # Deevloper Here API link\n", "api_key = '#######################' # Acquire api key from developer.here.com\n", "\n", "def getCoordinates(location):\n", " PARAMS = {'apikey': api_key, 'q': location} # required parameters\n", " r = requests.get(url=URL, params=PARAMS) # pass in required parameters\n", " # get raw json file. I did this because when I combined this step with my \"getLocation\" function, \n", " # it gave me error for countries with no country_code or country_name. Hence, I needed to use try - except block\n", " data = r.json() # Raw json file \n", " return data" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T21:19:05.996035Z", "start_time": "2020-12-25T20:44:29.696620Z" } }, "outputs": [], "source": [ "tweets_df['Location_data']=tweets_df['location'].apply(getCoordinates) # Apply getCoordinates Function" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:20:36.664879Z", "start_time": "2020-12-30T00:20:36.655903Z" } }, "outputs": [], "source": [ "# a function to extract required coordinates information to the tweets_df dataframe\n", "\n", "def getLocation(location):\n", " for data in location:\n", " if len(location['items'])>0:\n", " latitude = location['items'][0]['position']['lat']\n", " longitude = location['items'][0]['position']['lng']\n", " try: \n", " country_code = location['items'][0]['address']['countryCode']\n", " country_name = location['items'][0]['address']['countryName']\n", " country_name = location['items'][0]['address']['countryName']\n", " except KeyError:\n", " country_code = float('Nan')\n", " country_name = float('Nan')\n", " else: \n", " latitude = float('Nan')\n", " longitude = float('Nan')\n", " country_code = float('Nan') \n", " country_name = float('Nan')\n", " result = (latitude, longitude, country_code, country_name)\n", " return result" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:20:46.000863Z", "start_time": "2020-12-30T00:20:45.935039Z" }, "scrolled": true }, "outputs": [], "source": [ "tweets_df['location']=tweets_df['location_data'].apply(getLocation) #apply getLocation function" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T21:19:06.254238Z", "start_time": "2020-12-25T21:19:06.168506Z" } }, "outputs": [ { "data": { "text/html": [ "
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013421213738634362882020-12-24 14:54:052020 has been an absolute shit year for all of...No location012{'items': []}(nan, nan, nan, nan)
113421214194721382402020-12-24 14:54:16Kid this morning: It felt like it’s been 10 ye...No location06{'items': []}(nan, nan, nan, nan)
213421214268207390842020-12-24 14:54:18Just wanted to take this opportunity to wish y...Scotland, United Kingdom07{'items': [{'title': 'Scotland, MD, United Sta...(38.09434, -76.36635, USA, United States)
313421216185507553302020-12-24 14:55:03Reflecting on this year and I feel like I have...Johannesburg, South Africa914{'items': [{'title': 'Johannesburg, Gauteng, S...(-26.20491, 28.04006, ZAF, South Africa)
413421219501440573442020-12-24 14:56:22One good thing about 2020 has been the number ...Toronto04{'items': [{'title': 'Toronto, ON, Canada', 'i...(43.64869, -79.38544, CAN, Canada)
\n", "
" ], "text/plain": [ " tweet_id created_at \\\n", "0 1342121373863436288 2020-12-24 14:54:05 \n", "1 1342121419472138240 2020-12-24 14:54:16 \n", "2 1342121426820739084 2020-12-24 14:54:18 \n", "3 1342121618550755330 2020-12-24 14:55:03 \n", "4 1342121950144057344 2020-12-24 14:56:22 \n", "\n", " text \\\n", "0 2020 has been an absolute shit year for all of... \n", "1 Kid this morning: It felt like it’s been 10 ye... \n", "2 Just wanted to take this opportunity to wish y... \n", "3 Reflecting on this year and I feel like I have... \n", "4 One good thing about 2020 has been the number ... \n", "\n", " location retweet favorite \\\n", "0 No location 0 12 \n", "1 No location 0 6 \n", "2 Scotland, United Kingdom 0 7 \n", "3 Johannesburg, South Africa 9 14 \n", "4 Toronto 0 4 \n", "\n", " Location_data \\\n", "0 {'items': []} \n", "1 {'items': []} \n", "2 {'items': [{'title': 'Scotland, MD, United Sta... \n", "3 {'items': [{'title': 'Johannesburg, Gauteng, S... \n", "4 {'items': [{'title': 'Toronto, ON, Canada', 'i... \n", "\n", " Location \n", "0 (nan, nan, nan, nan) \n", "1 (nan, nan, nan, nan) \n", "2 (38.09434, -76.36635, USA, United States) \n", "3 (-26.20491, 28.04006, ZAF, South Africa) \n", "4 (43.64869, -79.38544, CAN, Canada) " ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T21:19:06.356076Z", "start_time": "2020-12-25T21:19:06.255268Z" } }, "outputs": [], "source": [ "# Extraction of Location Coordinates and Country names to different columns\n", "tweets_df[['Latitude', 'Longitude', 'Country_Code',\n", " 'Country_Name']] = pd.DataFrame(tweets_df['Location'].tolist(),\n", " index=tweets_df.index)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2020-12-25T21:19:06.513573Z", "start_time": "2020-12-25T21:19:06.357958Z" } }, "outputs": [ { "data": { "text/html": [ "
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013421213738634362882020-12-24 14:54:052020 has been an absolute shit year for all of...No location012{'items': []}(nan, nan, nan, nan)NaNNaNNaNNaN
113421214194721382402020-12-24 14:54:16Kid this morning: It felt like it’s been 10 ye...No location06{'items': []}(nan, nan, nan, nan)NaNNaNNaNNaN
213421214268207390842020-12-24 14:54:18Just wanted to take this opportunity to wish y...Scotland, United Kingdom07{'items': [{'title': 'Scotland, MD, United Sta...(38.09434, -76.36635, USA, United States)38.09434-76.36635USAUnited States
313421216185507553302020-12-24 14:55:03Reflecting on this year and I feel like I have...Johannesburg, South Africa914{'items': [{'title': 'Johannesburg, Gauteng, S...(-26.20491, 28.04006, ZAF, South Africa)-26.2049128.04006ZAFSouth Africa
413421219501440573442020-12-24 14:56:22One good thing about 2020 has been the number ...Toronto04{'items': [{'title': 'Toronto, ON, Canada', 'i...(43.64869, -79.38544, CAN, Canada)43.64869-79.38544CANCanada
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" ], "text/plain": [ " tweet_id created_at \\\n", "0 1342121373863436288 2020-12-24 14:54:05 \n", "1 1342121419472138240 2020-12-24 14:54:16 \n", "2 1342121426820739084 2020-12-24 14:54:18 \n", "3 1342121618550755330 2020-12-24 14:55:03 \n", "4 1342121950144057344 2020-12-24 14:56:22 \n", "\n", " text \\\n", "0 2020 has been an absolute shit year for all of... \n", "1 Kid this morning: It felt like it’s been 10 ye... \n", "2 Just wanted to take this opportunity to wish y... \n", "3 Reflecting on this year and I feel like I have... \n", "4 One good thing about 2020 has been the number ... \n", "\n", " location retweet favorite \\\n", "0 No location 0 12 \n", "1 No location 0 6 \n", "2 Scotland, United Kingdom 0 7 \n", "3 Johannesburg, South Africa 9 14 \n", "4 Toronto 0 4 \n", "\n", " Location_data \\\n", "0 {'items': []} \n", "1 {'items': []} \n", "2 {'items': [{'title': 'Scotland, MD, United Sta... \n", "3 {'items': [{'title': 'Johannesburg, Gauteng, S... \n", "4 {'items': [{'title': 'Toronto, ON, Canada', 'i... \n", "\n", " Location Latitude Longitude \\\n", "0 (nan, nan, nan, nan) NaN NaN \n", "1 (nan, nan, nan, nan) NaN NaN \n", "2 (38.09434, -76.36635, USA, United States) 38.09434 -76.36635 \n", "3 (-26.20491, 28.04006, ZAF, South Africa) -26.20491 28.04006 \n", "4 (43.64869, -79.38544, CAN, Canada) 43.64869 -79.38544 \n", "\n", " Country_Code Country_Name \n", "0 NaN NaN \n", "1 NaN NaN \n", "2 USA United States \n", "3 ZAF South Africa \n", "4 CAN Canada " ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:22:24.231251Z", "start_time": "2020-12-30T00:22:24.186341Z" } }, "outputs": [], "source": [ "# Drop unnecessary columns\n", "tweets_df.drop(['Location_data','location','Location'], axis=1, inplace=True)\n", "# Rename columns\n", "tweets_df.columns=['Tweet_ID','Time_Created','Tweet','Retweet_Count','Favorite_Count',\n", " 'Latitude','Longitude','Country_Code','Country_Name']" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T00:22:36.603176Z", "start_time": "2020-12-30T00:22:36.590211Z" } }, "outputs": [ { "data": { "text/html": [ "
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Tweet_IDTime_CreatedTweetRetweet_CountFavorite_CountLatitudeLongitudeCountry_CodeCountry_Name
013407014943168307272020-12-20 16:51:59When you think 2020 has been bad and...0054.97789-1.61162GBREngland
113407013405117235252020-12-20 16:51:23every single boy i hooked up with tu...00NaNNaNNaNNaN
213407010522875412482020-12-20 16:50:14if you can reply to this, you made m...0035.78547-78.64270USAUnited States
313407010233676922882020-12-20 16:50:072020 has been such a cruel year but ...00NaNNaNNaNNaN
413407005704333107262020-12-20 16:48:19It’s official then Amsterdam is canc...0052.47891-1.90592GBREngland
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" ], "text/plain": [ " Tweet_ID Time_Created \\\n", "0 1340701494316830727 2020-12-20 16:51:59 \n", "1 1340701340511723525 2020-12-20 16:51:23 \n", "2 1340701052287541248 2020-12-20 16:50:14 \n", "3 1340701023367692288 2020-12-20 16:50:07 \n", "4 1340700570433310726 2020-12-20 16:48:19 \n", "\n", " Tweet Retweet_Count Favorite_Count \\\n", "0 When you think 2020 has been bad and... 0 0 \n", "1 every single boy i hooked up with tu... 0 0 \n", "2 if you can reply to this, you made m... 0 0 \n", "3 2020 has been such a cruel year but ... 0 0 \n", "4 It’s official then Amsterdam is canc... 0 0 \n", "\n", " Latitude Longitude Country_Code Country_Name \n", "0 54.97789 -1.61162 GBR England \n", "1 NaN NaN NaN NaN \n", "2 35.78547 -78.64270 USA United States \n", "3 NaN NaN NaN NaN \n", "4 52.47891 -1.90592 GBR England " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5. Tweets Processing\n", "To reach the ultimate goal, there was a need to clean up the individual tweets. To make this easy, I created several functions in my Python code which I further applied to the \"Tweets\" column in my Pandas data frame to produce the desired results. \n", "Also, for my Word Cloud, I wanted to only show the words used to describe 2020, so I created a function to extract only the adjectives to a new column." ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:04:20.722394Z", "start_time": "2021-01-06T17:04:20.712420Z" } }, "outputs": [], "source": [ "# Function to remove punctuations, links, emojis, and stop words\n", "def preprocessTweets(tweet):\n", " tweet = tweet.lower() #has to be in place\n", " # Remove urls\n", " tweet = re.sub(r\"http\\S+|www\\S+|https\\S+\", '', tweet, flags=re.MULTILINE)\n", " # Remove user @ references and '#' from tweet\n", " tweet = re.sub(r'\\@\\w+|\\#|\\d+', '', tweet)\n", " # Remove stopwords\n", " tweet_tokens = word_tokenize(tweet) # convert string to tokens\n", " filtered_words = [w for w in tweet_tokens if w not in stop_words]\n", " filtered_words = [w for w in filtered_words if w not in emojis]\n", " filtered_words = [w for w in filtered_words if w in word_list]\n", "\n", " # Remove punctuations\n", " unpunctuated_words = [char for char in filtered_words if char not in string.punctuation]\n", " unpunctuated_words = ' '.join(unpunctuated_words)\n", "\n", " return \"\".join(unpunctuated_words) # join words with a space in between them\n", "\n", "\n", "# function to obtain adjectives from tweets\n", "def getAdjectives(tweet):\n", " tweet = word_tokenize(tweet) # convert string to tokens\n", " tweet = [word for (word, tag) in pos_tag(tweet)\n", " if tag == \"JJ\"] # pos_tag module in NLTK library\n", " return \" \".join(tweet) # join words with a space in between them" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:04:21.715915Z", "start_time": "2021-01-06T17:04:21.299850Z" } }, "outputs": [], "source": [ "# Defining my NLTK stop words and my user-defined stop words\n", "stop_words = list(stopwords.words('english'))\n", "user_stop_words = ['2020', 'year', 'many', 'much', 'amp', 'next', 'cant', 'wont', 'hadnt',\n", " 'havent', 'hasnt', 'isnt', 'shouldnt', 'couldnt', 'wasnt', 'werent',\n", " 'mustnt', '’', '...', '..', '.', '.....', '....', 'been…', 'one', 'two',\n", " 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine', 'ten', 'aht',\n", " 've', 'next']\n", "alphabets = list(string.ascii_lowercase)\n", "stop_words = stop_words + user_stop_words + alphabets\n", "word_list = words.words() # all words in English language\n", "emojis = list(UNICODE_EMO.keys()) # full list of emojis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### An example of how the above function works is shown below" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:48:54.743648Z", "start_time": "2021-01-06T17:48:54.719714Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "difficulty sad happy worked\n" ] } ], "source": [ "print(preprocessTweets(\"2020 was a year of difficulty. It was sad, but I am happy with how things worked out for me\"))" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:27:28.361069Z", "start_time": "2021-01-06T17:04:29.995842Z" } }, "outputs": [], "source": [ "# Apply preProcessTweets function to the 'Tweet' column to generate a new column called 'Processed Tweets'.\n", "# This took 23 mins to run for 50,780 rows\n", "tweets_df['Processed_Tweets'] = tweets_df['Tweet'].apply(preprocessTweets)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:28:32.078274Z", "start_time": "2021-01-06T17:27:28.362029Z" } }, "outputs": [], "source": [ "# Apply getAdjectives function to the new 'Processed Tweets' column to generate a new column called 'Tweets_Adjectives'\n", "tweets_df['Tweets_Adjectives'] = tweets_df['Processed_Tweets'].apply(getAdjectives)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:28:32.095126Z", "start_time": "2021-01-06T17:28:32.080203Z" } }, "outputs": [ { "data": { "text/html": [ "
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Tweet_IDTime_CreatedTweetRetweet_CountFavorite_CountLatitudeLongitudeCountry_CodeCountry_NameProcessed_TweetsTweets_Adjectives
013407014943168307272020-12-20 16:51:59When you think 2020 has been bad and...0054.97789-1.61162GBREnglandthink bad see phrase mutationbad phrase
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213407010522875412482020-12-20 16:50:14if you can reply to this, you made m...0035.78547-78.64270USAUnited Statesreply made yes really rough made bet...rough worth
313407010233676922882020-12-20 16:50:072020 has been such a cruel year but ...00NaNNaNNaNNaNcruel thank goodness met people made...bearable
413407005704333107262020-12-20 16:48:19It’s official then Amsterdam is canc...0052.47891-1.90592GBREnglandofficial catofficial
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" ], "text/plain": [ " Tweet_ID Time_Created \\\n", "0 1340701494316830727 2020-12-20 16:51:59 \n", "1 1340701340511723525 2020-12-20 16:51:23 \n", "2 1340701052287541248 2020-12-20 16:50:14 \n", "3 1340701023367692288 2020-12-20 16:50:07 \n", "4 1340700570433310726 2020-12-20 16:48:19 \n", "\n", " Tweet Retweet_Count Favorite_Count \\\n", "0 When you think 2020 has been bad and... 0 0 \n", "1 every single boy i hooked up with tu... 0 0 \n", "2 if you can reply to this, you made m... 0 0 \n", "3 2020 has been such a cruel year but ... 0 0 \n", "4 It’s official then Amsterdam is canc... 0 0 \n", "\n", " Latitude Longitude Country_Code Country_Name \\\n", "0 54.97789 -1.61162 GBR England \n", "1 NaN NaN NaN NaN \n", "2 35.78547 -78.64270 USA United States \n", "3 NaN NaN NaN NaN \n", "4 52.47891 -1.90592 GBR England \n", "\n", " Processed_Tweets Tweets_Adjectives \n", "0 think bad see phrase mutation bad phrase \n", "1 every single boy hooked turned awful single turned awful \n", "2 reply made yes really rough made bet... rough worth \n", "3 cruel thank goodness met people made... bearable \n", "4 official cat official " ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:29:19.157843Z", "start_time": "2021-01-06T17:29:19.153854Z" } }, "outputs": [], "source": [ "# function to return words to their base form using Lemmatizer\n", "def preprocessTweetsSentiments(tweet):\n", " tweet_tokens = word_tokenize(tweet)\n", " lemmatizer = WordNetLemmatizer() # instatiate an object WordNetLemmatizer Class\n", " lemma_words = [lemmatizer.lemmatize(w) for w in tweet_tokens]\n", " return \" \".join(lemma_words)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:29:28.586569Z", "start_time": "2021-01-06T17:29:21.955360Z" } }, "outputs": [], "source": [ "# Apply preprocessTweetsSentiments function to the 'Processed Tweets' column to generate a new column\n", "# called 'Processed_Tweets'\n", "tweets_df['Tweets_Sentiments'] = tweets_df['Processed_Tweets'].apply(preprocessTweetsSentiments)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:29:28.607515Z", "start_time": "2021-01-06T17:29:28.587566Z" } }, "outputs": [ { "data": { "text/html": [ "
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Tweet_IDTime_CreatedTweetRetweet_CountFavorite_CountLatitudeLongitudeCountry_CodeCountry_NameProcessed_TweetsTweets_AdjectivesTweets_Sentiments
013407014943168307272020-12-20 16:51:59When you think 2020 has been bad and...0054.97789-1.61162GBREnglandthink bad see phrase mutationbad phrasethink bad see phrase mutation
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313407010233676922882020-12-20 16:50:072020 has been such a cruel year but ...00NaNNaNNaNNaNcruel thank goodness met people made...bearablecruel thank goodness met people made...
413407005704333107262020-12-20 16:48:19It’s official then Amsterdam is canc...0052.47891-1.90592GBREnglandofficial catofficialofficial cat
\n", "
" ], "text/plain": [ " Tweet_ID Time_Created \\\n", "0 1340701494316830727 2020-12-20 16:51:59 \n", "1 1340701340511723525 2020-12-20 16:51:23 \n", "2 1340701052287541248 2020-12-20 16:50:14 \n", "3 1340701023367692288 2020-12-20 16:50:07 \n", "4 1340700570433310726 2020-12-20 16:48:19 \n", "\n", " Tweet Retweet_Count Favorite_Count \\\n", "0 When you think 2020 has been bad and... 0 0 \n", "1 every single boy i hooked up with tu... 0 0 \n", "2 if you can reply to this, you made m... 0 0 \n", "3 2020 has been such a cruel year but ... 0 0 \n", "4 It’s official then Amsterdam is canc... 0 0 \n", "\n", " Latitude Longitude Country_Code Country_Name \\\n", "0 54.97789 -1.61162 GBR England \n", "1 NaN NaN NaN NaN \n", "2 35.78547 -78.64270 USA United States \n", "3 NaN NaN NaN NaN \n", "4 52.47891 -1.90592 GBR England \n", "\n", " Processed_Tweets Tweets_Adjectives \\\n", "0 think bad see phrase mutation bad phrase \n", "1 every single boy hooked turned awful single turned awful \n", "2 reply made yes really rough made bet... rough worth \n", "3 cruel thank goodness met people made... bearable \n", "4 official cat official \n", "\n", " Tweets_Sentiments \n", "0 think bad see phrase mutation \n", "1 every single boy hooked turned awful \n", "2 reply made yes really rough made bet... \n", "3 cruel thank goodness met people made... \n", "4 official cat " ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:32:02.209959Z", "start_time": "2021-01-06T17:32:01.603856Z" } }, "outputs": [], "source": [ "# I had to write my results to a csv file at every instance due to the amount of time it took for the preprocessTweets\n", "# function to run\n", "tweets_df.to_csv('Tweets_Processed.csv',encoding='utf-8-sig', index=False) \n", "# Also, encoding is important when writing text to csv file" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 6. Data Exploration\n", "In this section, the aim was to show the most common words used by Twitter Users to describe 2020. This was made possible by the \"getAdjectives\" function in Section 5. I also made use of WordCloud and MatPlotlib for this task." ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:32:43.453309Z", "start_time": "2021-01-06T17:32:43.446330Z" } }, "outputs": [], "source": [ "# Extract all tweets into one long string with each word separate with a \"space\"\n", "tweets_long_string = tweets_df['Tweets_Adjectives'].tolist()\n", "tweets_long_string = \" \".join(tweets_long_string)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T02:00:21.015230Z", "start_time": "2020-12-30T02:00:19.627904Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Import Twitter Logo\n", "image = np.array(Image.open('twitter.png'))\n", " \n", "fig = plt.figure() # Instantiate the figure object\n", "fig.set_figwidth(14) # set width\n", "fig.set_figheight(18) # set height\n", "\n", "plt.imshow(image, cmap=plt.cm.gray, interpolation='bilinear') # Display data as an image\n", "plt.axis('off') # Remove axis\n", "plt.show() # Display image" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T02:00:21.428091Z", "start_time": "2020-12-30T02:00:21.423103Z" } }, "outputs": [], "source": [ "# Create function to generate the blue colour for the Word CLoud\n", "\n", "def blue_color_func(word, font_size, position, orientation, random_state=None,**kwargs):\n", " return \"hsl(210, 100%%, %d%%)\" % random.randint(50, 70)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T02:00:29.329373Z", "start_time": "2020-12-30T02:00:22.543108Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Instantiate the Twitter word cloud object\n", "twitter_wc = WordCloud(background_color='white', max_words=1500, mask=image)\n", "\n", "# generate the word cloud\n", "twitter_wc.generate(tweets_long_string)\n", "\n", "# display the word cloud\n", "fig = plt.figure()\n", "fig.set_figwidth(14) # set width\n", "fig.set_figheight(18) # set height\n", "\n", "plt.imshow(twitter_wc.recolor(color_func=blue_color_func, random_state=3),\n", " interpolation=\"bilinear\")\n", "plt.axis('off')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T04:04:41.363535Z", "start_time": "2020-12-30T04:04:40.441964Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "twitter_wc.to_file(\"wordcloud.png\") #save to a png file" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Analyzing Top Words in the Word Cloud" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:32:51.622608Z", "start_time": "2021-01-06T17:32:51.587600Z" } }, "outputs": [], "source": [ "# Combine all words into a list\n", "tweets_long_string = tweets_df['Tweets_Adjectives'].tolist()\n", "tweets_list=[]\n", "for item in tweets_long_string:\n", " item = item.split()\n", " for i in item:\n", " tweets_list.append(i)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:32:51.907890Z", "start_time": "2021-01-06T17:32:51.775099Z" } }, "outputs": [], "source": [ "# Use the Built-in Python Collections module to determine Word frequency\n", "from collections import Counter\n", "counts = Counter(tweets_list)\n", "df = pd.DataFrame.from_dict(counts, orient='index').reset_index()\n", "df.columns = ['Words', 'Count']\n", "df.sort_values(by='Count', ascending=False, inplace=True)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:32:52.599999Z", "start_time": "2021-01-06T17:32:52.591986Z" } }, "outputs": [ { "data": { "text/html": [ "
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WordsCount
24good4205
51tough2871
78new2807
159happy2689
48hard2668
0bad2329
28great2185
116last1504
10grateful1432
65difficult1232
\n", "
" ], "text/plain": [ " Words Count\n", "24 good 4205\n", "51 tough 2871\n", "78 new 2807\n", "159 happy 2689\n", "48 hard 2668\n", "0 bad 2329\n", "28 great 2185\n", "116 last 1504\n", "10 grateful 1432\n", "65 difficult 1232" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head(10) # Check dataframe first 10 rows" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Top 10 Words in Twitter Users' 2020 Reflections" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:39:40.522663Z", "start_time": "2021-01-06T17:39:40.383039Z" }, "scrolled": false }, "outputs": [ { "data": { "image/png": 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}, "metadata": {}, "output_type": "display_data" } ], "source": [ "# print(px.colors.sequential.Blues_r) to get the colour list used here. Please note, I swatched some colours\n", "\n", "# Define my colours for the Plotly Plot\n", "colors = ['rgb(8,48,107)', 'rgb(8,81,156)', 'rgb(33,113,181)', 'rgb(66,146,198)',\n", " 'rgb(107,174,214)', 'rgb(158,202,225)', 'rgb(198,219,239)',\n", " 'rgb(222,235,247)', 'rgb(247,251,255)', 'rgb(247,253,255)']\n", "\n", "# Set layout for Plotly Subplots\n", "fig = make_subplots(rows=1, cols=2, specs=[[{\"type\": \"xy\"}, { \"type\": \"domain\"}]],\n", " vertical_spacing=0.001)\n", "\n", "# Add First Plot\n", "fig.add_trace(go.Bar(x = df['Count'].head(10), y=df['Words'].head(10),marker=dict(color='rgba(66,146,198, 1)',\n", " line=dict(color='Black'),),name='Bar Chart',orientation='h'), 1, 1)\n", "\n", "# Add Second Plot\n", "fig.add_trace(go.Pie(labels=df['Words'].head(10),values=df['Count'].head(15),textinfo='label+percent',\n", " insidetextorientation='radial', marker=dict(colors=colors, line=dict(color='DarkSlateGrey')),\n", " name='Pie Chart'), 1, 2)\n", "# customize layout\n", "fig.update_layout(shapes=[dict(type=\"line\",xref=\"paper\", yref=\"paper\", x0=0.5, y0=0, x1=0.5, y1=1.0,\n", " line_color='DarkSlateGrey', line_width=1)])\n", "\n", "# customize plot title\n", "fig.update_layout(showlegend=False, title=dict(text=\"Twitter Users' 2020 Refelections (10 Most Common Words)\",\n", " font=dict(size=18, )))\n", "\n", "# Customize backgroound, margins, axis, title\n", "fig.update_layout(yaxis=dict(showgrid=False,\n", " showline=False,\n", " showticklabels=True,\n", " domain=[0, 1],\n", " categoryorder='total ascending',\n", " title=dict(text='Common Words', font_size=14)),\n", " xaxis=dict(zeroline=False,\n", " showline=False,\n", " showticklabels=True,\n", " showgrid=True,\n", " domain=[0, 0.42],\n", " title=dict(text='Word Count', font_size=14)),\n", " margin=dict(l=100, r=20, t=70, b=70),\n", " paper_bgcolor='rgba(0,0,0,0)',\n", " plot_bgcolor='rgba(0,0,0,0)')\n", "\n", "# Specify X and Y values for Annotations\n", "x = df['Count'].head(10).to_list()\n", "y = df['Words'].head(10).to_list()\n", "\n", "# Show annotations on plot\n", "annotations = [dict(xref='x1', yref='y1', x=xa + 350, y=ya, text=str(xa), showarrow=False) for xa, ya in zip(x, y)]\n", "\n", "fig.update_layout(annotations=annotations)\n", "fig.show(renderer = 'png')" ] }, { "cell_type": "code", "execution_count": 331, "metadata": { "ExecuteTime": { "end_time": "2020-12-26T06:11:28.848646Z", "start_time": "2020-12-26T06:11:25.900532Z" } }, "outputs": [ { "data": { "text/plain": [ "'https://plotly.com/~jess-data/63/'" ] }, "execution_count": 331, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Export to Plot to Chart Studio using my Chart Studio Credentials\n", "py.plot(fig, filename = 'Twitter Users 2020 Refelections (10 Most Common Words)', auto_open=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 7. Sentiment Analysis\n", "In this section, the aim was to show the most common words used by Twitter Users to describe 2020. This was made possible byt the getAdjectives function. I also made use of WordCloud and MatPlotlib for this task." ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:39:46.275906Z", "start_time": "2021-01-06T17:39:46.270922Z" } }, "outputs": [], "source": [ "# Create function to obtain Subjectivity Score\n", "def getSubjectivity(tweet):\n", " return TextBlob(tweet).sentiment.subjectivity\n", "\n", "# Create function to obtain Polarity Score\n", "def getPolarity(tweet):\n", " return TextBlob(tweet).sentiment.polarity\n", "\n", "# Create function to obtain Sentiment category\n", "def getSentimentTextBlob(polarity):\n", " if polarity < 0:\n", " return \"Negative\"\n", " elif polarity == 0:\n", " return \"Neutral\"\n", " else:\n", " return \"Positive\"" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:40:08.346203Z", "start_time": "2021-01-06T17:39:51.590413Z" } }, "outputs": [], "source": [ "# Apply all functions above to respective columns\n", "tweets_df['Subjectivity']=tweets_df['Tweets_Sentiments'].apply(getSubjectivity)\n", "tweets_df['Polarity']=tweets_df['Tweets_Sentiments'].apply(getPolarity)\n", "tweets_df['Sentiment']=tweets_df['Polarity'].apply(getSentimentTextBlob)" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T04:08:13.571962Z", "start_time": "2020-12-30T04:08:13.505146Z" } }, "outputs": [ { "data": { "text/plain": [ "Positive 25225\n", "Negative 15963\n", "Neutral 9592\n", "Name: Sentiment, dtype: int64" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# See quick results of the Sentiment Analysis\n", "tweets_df['Sentiment'].value_counts()" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T04:08:13.702634Z", "start_time": "2020-12-30T04:08:13.573921Z" } }, "outputs": [], "source": [ "# Create dataframe for Count of Sentiment Categories\n", "bar_chart = tweets_df['Sentiment'].value_counts().rename_axis('Sentiment').to_frame('Total Tweets').reset_index()" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T04:08:13.855204Z", "start_time": "2020-12-30T04:08:13.703572Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Sentiment Total Tweets\n", "0 Positive 25225\n", "1 Negative 15963\n", "2 Neutral 9592" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bar_chart # Display dataframe" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "ExecuteTime": { "end_time": "2021-01-06T17:48:10.253192Z", "start_time": "2021-01-06T17:47:52.035464Z" } }, "outputs": [ { "data": { "image/png": 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}, "metadata": {}, "output_type": "display_data" } ], "source": [ "sentiments_barchart = px.bar(bar_chart, x = 'Sentiment', y='Total Tweets', color='Sentiment')\n", "\n", "sentiments_barchart.update_layout(title='Distribution of Sentiments Results',\n", " margin={\"r\": 0, \"t\": 30, \"l\": 0, \"b\": 0})\n", "\n", "sentiments_barchart.show(renderer = 'png') #Display plot. \n", "\n", "# I used renderer so that the plots show on the web when people view my notebook. \n", "# For interactive plots, exclude the \"renderer\" argument\n", "# Note, I further customized the plot on Chart Studio for my Medium post" ] }, { "cell_type": "code", "execution_count": 121, "metadata": { "ExecuteTime": { "end_time": "2020-12-26T02:02:15.821462Z", "start_time": "2020-12-26T02:02:12.555199Z" } }, "outputs": [ { "data": { "text/plain": [ "'https://plotly.com/~jess-data/59/'" ] }, "execution_count": 121, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Export to Plot to Chart Studio using my Chart Studio Credentials. \n", "py.plot(sentiments_barchart, filename = 'Distribution of Sentiments Results', auto_open=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## WE MADE IT!! \n", "### Preview the resulting dataframe in preparation for export to Tableau" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "ExecuteTime": { "end_time": "2020-12-30T04:09:38.264615Z", "start_time": "2020-12-30T04:09:38.246654Z" } }, "outputs": [ { "data": { "text/html": [ "
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Tweet_IDTime_CreatedTweetRetweet_CountFavorite_CountLatitudeLongitudeCountry_CodeCountry_NameProcessed_TweetsTweets_AdjectivesTweets_SentimentsSubjectivityPolaritySentiment
013407014943168307272020-12-20 16:51:59When you think 2020 has been bad and...0054.97789-1.61162GBREnglandthink bad see phrase mutationbad phrasethink bad see phrase mutation0.666667-0.700000Negative
113407013405117235252020-12-20 16:51:23every single boy i hooked up with tu...00NaNNaNNaNNaNevery single boy hooked turned awfulsingle turned awfulevery single boy hooked turned awful0.607143-0.535714Negative
213407010522875412482020-12-20 16:50:14if you can reply to this, you made m...0035.78547-78.64270USAUnited Statesreply made yes really rough made bet...rough worthreply made yes really rough made bet...0.4000000.300000Positive
313407010233676922882020-12-20 16:50:072020 has been such a cruel year but ...00NaNNaNNaNNaNcruel thank goodness met people made...bearablecruel thank goodness met people made...1.000000-1.000000Negative
413407005704333107262020-12-20 16:48:19It’s official then Amsterdam is canc...0052.47891-1.90592GBREnglandofficial catofficialofficial cat0.0000000.000000Neutral
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" ], "text/plain": [ " Tweet_ID Time_Created \\\n", "0 1340701494316830727 2020-12-20 16:51:59 \n", "1 1340701340511723525 2020-12-20 16:51:23 \n", "2 1340701052287541248 2020-12-20 16:50:14 \n", "3 1340701023367692288 2020-12-20 16:50:07 \n", "4 1340700570433310726 2020-12-20 16:48:19 \n", "\n", " Tweet Retweet_Count Favorite_Count \\\n", "0 When you think 2020 has been bad and... 0 0 \n", "1 every single boy i hooked up with tu... 0 0 \n", "2 if you can reply to this, you made m... 0 0 \n", "3 2020 has been such a cruel year but ... 0 0 \n", "4 It’s official then Amsterdam is canc... 0 0 \n", "\n", " Latitude Longitude Country_Code Country_Name \\\n", "0 54.97789 -1.61162 GBR England \n", "1 NaN NaN NaN NaN \n", "2 35.78547 -78.64270 USA United States \n", "3 NaN NaN NaN NaN \n", "4 52.47891 -1.90592 GBR England \n", "\n", " Processed_Tweets Tweets_Adjectives \\\n", "0 think bad see phrase mutation bad phrase \n", "1 every single boy hooked turned awful single turned awful \n", "2 reply made yes really rough made bet... rough worth \n", "3 cruel thank goodness met people made... bearable \n", "4 official cat official \n", "\n", " Tweets_Sentiments Subjectivity Polarity Sentiment \n", "0 think bad see phrase mutation 0.666667 -0.700000 Negative \n", "1 every single boy hooked turned awful 0.607143 -0.535714 Negative \n", "2 reply made yes really rough made bet... 0.400000 0.300000 Positive \n", "3 cruel thank goodness met people made... 1.000000 -1.000000 Negative \n", "4 official cat 0.000000 0.000000 Neutral " ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tweets_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "ExecuteTime": { "end_time": "2020-12-26T00:26:14.885934Z", "start_time": "2020-12-26T00:26:14.841061Z" } }, "outputs": [], "source": [ "# Remove Unnecessary columns. I used copy here because I wanted a datframe that does not impact my original dataframe\n", "tableau_df = tweets_df.drop((['Processed_Tweets','Tweets_Sentiments','Subjectivity','Polarity']), axis=1).copy(deep=True)" ] }, { "cell_type": "code", "execution_count": 333, "metadata": { "ExecuteTime": { "end_time": "2020-12-27T01:56:47.723738Z", "start_time": "2020-12-27T01:56:47.322811Z" } }, "outputs": [ { "data": { "text/html": [ "
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Tweet_IDTime_CreatedTweetRetweet_CountFavorite_CountLatitudeLongitudeCountry_CodeCountry_NameTweets_AdjectivesSentiment
013407014943168309762020-12-20 16:51:59When you think 2020 has been bad and...0054.97789-1.61162GBREnglandbad phraseNegative
113407013405117240322020-12-20 16:51:23every single boy i hooked up with tu...00NaNNaNNaNNaNsingle turned awfulNegative
213407010522875409922020-12-20 16:50:14if you can reply to this, you made m...0035.78547-78.64270USAUnited Statesrough worthPositive
313407010233676920322020-12-20 16:50:072020 has been such a cruel year but ...00NaNNaNNaNNaNbearableNegative
413407005704333109762020-12-20 16:48:19It’s official then Amsterdam is canc...0052.47891-1.90592GBREnglandofficialNeutral
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" ], "text/plain": [ " Tweet_ID Time_Created \\\n", "0 1340701494316830976 2020-12-20 16:51:59 \n", "1 1340701340511724032 2020-12-20 16:51:23 \n", "2 1340701052287540992 2020-12-20 16:50:14 \n", "3 1340701023367692032 2020-12-20 16:50:07 \n", "4 1340700570433310976 2020-12-20 16:48:19 \n", "\n", " Tweet Retweet_Count Favorite_Count \\\n", "0 When you think 2020 has been bad and... 0 0 \n", "1 every single boy i hooked up with tu... 0 0 \n", "2 if you can reply to this, you made m... 0 0 \n", "3 2020 has been such a cruel year but ... 0 0 \n", "4 It’s official then Amsterdam is canc... 0 0 \n", "\n", " Latitude Longitude Country_Code Country_Name Tweets_Adjectives \\\n", "0 54.97789 -1.61162 GBR England bad phrase \n", "1 NaN NaN NaN NaN single turned awful \n", "2 35.78547 -78.64270 USA United States rough worth \n", "3 NaN NaN NaN NaN bearable \n", "4 52.47891 -1.90592 GBR England official \n", "\n", " Sentiment \n", "0 Negative \n", "1 Negative \n", "2 Positive \n", "3 Negative \n", "4 Neutral " ] }, "execution_count": 333, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tableau_df.head() # Check dataframe first 5 rows" ] }, { "cell_type": "code", "execution_count": 339, "metadata": { "ExecuteTime": { "end_time": "2020-12-27T02:37:52.492769Z", "start_time": "2020-12-27T02:37:35.349879Z" } }, "outputs": [], "source": [ "# Export to Excel file. You can link Python to Tableau by the way but I Ihaven't learned that yet\n", "tableau_df.to_excel('Tweets_Tableau_Final_File.xlsx', encoding='utf-8-sig', index=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## THANK YOU FOR TAKING TIME TO STUDY MY NOTEBOOK. I HOPE YOU GOT SOME INSIGHTS.\n", "## You can use the links below to view my other pages\n", "\n", "[Medium Page](https://jess-analytics.medium.com/)\n", "\n", "[Tableau Dashboard](https://public.tableau.com/views/TwitterUsers2020ReflectionsDashboard/FinalDashboard?:language=en-GB&:display_count=y&publish=yes&:origin=viz_share_link)\n", "\n", "[LinkedIn Page](https://www.linkedin.com/in/jessicauwoghiren/)\n", "\n", "[Twitter Page](https://twitter.com/jessica_xls)\n", "\n", "[My Data Community Placeholder Website](https://linktr.ee/DataTechSpace)\n", "\n" ] } ], "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 }