compile tweets

[HendrickxBrent]

import pandas as pd import glob import os

setting the path for joining multiple files

files = os.path.join("C:\Users\Brent\Documents\Psychology\KUL\thesisstatisticsdata", "all*.csv")

list of merged files returned

files = glob.glob(files) print("Resultant CSV after joining all CSV files at a particular location...");

joining files with concat and read_csv

df = pd.concat(map(pd.read_csv, files), ignore_index=True) print(df)

os.chdir("C:\Users\Brent\Documents\Psychology\KUL\thesisstatisticsdata")

aaa = df.head(1000)

clean data

df2 = pd.DataFrame(df[['author.id', 'text','created_at']])

df.to_csv('data.csv')

import os import glob import pandas as pd

Setting the path for joining multiple files

os.chdir("C:\Users\Brent\Documents\Psychology\KUL\thesisstatisticsdata") files = os.path.join("C:\Users\Brent\Documents\Psychology\KUL\thesisstatisticsdata", "all*.csv")

List of merged files returned

files = glob.glob(files) print("Resultant CSV after joining all CSV files at a particular location...")

Joining files with concat and read_csv

df = pd.concat(map(pd.read_csv, files), ignore_index=True) print(df)

Clean data

df2 = pd.DataFrame(df[['id','conversation_id','author.id', 'text','created_at','lang','public_metrics.like_count', 'public_metrics.reply_count' ,'public_metrics.retweet_count','author.public_metrics.tweet_count','author.public_metrics.followers_count' ,'author.public_metrics.following_count','author.verified','Tweet']])

Create new columns for emotions

emotion_mapping = { 'anger': 'anger', 'anticipation': 'anticipation', 'disgust': 'disgust', 'fear': 'fear', 'joy': 'joy', 'love': 'love', 'optimism': 'optimism', 'pessimism': 'pessimism', 'sadness': 'sadness', 'surprise': 'surprise', 'trust': 'trust' }

for emotion in emotion_mapping.keys(): columns = [col for col in df.columns if emotion in col] df2[emotion_mapping[emotion]] = df[columns].sum(axis=1)

df2.to_csv('data.csv')