nwbot

import os
import glob
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

def convert_date(ser):
    return ser[:10]
    
path = 'C:\\Users\\hello\\Documents\\twitch\\nw\\data\\'
extension = 'csv'
os.chdir(path)
result = [i for i in glob.glob('*.{}'.format(extension))]

df = pd.DataFrame()
for data in result:
    data_in = pd.read_csv(data)
    df = df.append(data_in, ignore_index=True)

df.drop(['promoted impressions', 'promoted engagements',
       'promoted engagement rate', 'promoted retweets', 'promoted replies',
       'promoted likes', 'promoted user profile clicks', 'promoted url clicks',
       'promoted hashtag clicks', 'promoted detail expands',
       'promoted permalink clicks', 'promoted app opens',
       'promoted app installs', 'promoted follows', 'promoted email tweet',
       'promoted dial phone', 'promoted media views',
       'promoted media engagements'], axis=1, inplace=True)
df['date'] = df['time'].apply(convert_date)
df['date'] = pd.to_datetime(df['date'])
df['time'] = pd.to_datetime(df['time'])
df['daycode'] = df['time'].dt.weekday
df['day'] = df['time'].dt.weekday_name
int_cols = ['impressions', 'engagements', 'engagement rate', 'retweets', 'replies', 'likes',
            'user profile clicks', 'url clicks', 'hashtag clicks', 'detail expands',
            'permalink clicks', 'app opens', 'app installs', 'follows',
            'email tweet', 'dial phone', 'media engagements']

for c in int_cols:
    df[c] = df[c].astype(int)

df['week'] = df['date'].dt.week + (52 * (df['date'].dt.year - df['date'].dt.year.min()))
df['week'] = df['week'] - df['week'].min()
df.sort_values(['date', 'time'], inplace=True)
df = df.reset_index(drop=1)