CollectUSSenatorTweets/createGraphs.py
2023-07-07 18:18:51 +02:00

145 lines
4.0 KiB
Python

#%%
#!/usr/bin/env python3
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from funs.CleanTweets import remove_URL, remove_emoji, remove_html, remove_punct
import string
#%%
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 26 20:36:43 2023
@author: michael
"""
import pandas as pd
# import pyreadstat
# import numpy as np
###################
# Setup directories
# WD Michael
wd = "/home/michael/Documents/PS/Data/collectTweets/"
# WD Server
# wd = '/home/yunohost.multimedia/polsoc/Politics & Society/TweetCollection/'
# datafile input directory
di = "data/IN/"
# Tweet-datafile output directory
ud = "data/OUT/"
# Name of file that all senator data will be written to
senCSV = "SenatorsTweets-OnlyCov.csv" # SenatorsTweets-Final.csv SenatorsTweets-OnlyCov.csv
# Name of file that all senator data will be written to
senDataset = "senators-raw.csv"
# Name of new datafile generated
senCSVc = "SenatorsTweets-Final.csv"
senCSVcCov = "SenatorsTweets-OnlyCov.csv"
# Outfiles
wcAllTweetsF = "graphs/Wordcloud-All.png"
wcCovTweetsF = "graphs/Wordcloud-Cov.png"
TwCovTimeline = "graphs/Timeline.png"
# don't change this one
senCSVcPath = wd + ud + senCSVc
senCSVcCovPath = wd + ud + senCSVcCov
wcAllTweetsFPath = wd + ud + wcAllTweetsF
wcCovTweetsFPath = wd + ud + wcCovTweetsF
TwCovTimelinePath = wd + ud + TwCovTimeline
#%%
df = pd.read_csv(senCSVcPath, dtype=(object))
dfCov = pd.read_csv(senCSVcCovPath, dtype=(object))
#%%
df['cleanContent'] = df['rawContent'].apply(remove_URL)
df['cleanContent'] = df['cleanContent'].apply(remove_emoji)
df['cleanContent'] = df['cleanContent'].apply(remove_html)
df['cleanContent'] = df['cleanContent'].apply(remove_punct)
# create string with all cleaned tweets as text
str_alltweets = df['cleanContent'].astype(str).str.cat(sep=' ').casefold()
#%%
dfCov['cleanContent'] = dfCov['rawContent'].apply(remove_URL)
dfCov['cleanContent'] = dfCov['cleanContent'].apply(remove_emoji)
dfCov['cleanContent'] = dfCov['cleanContent'].apply(remove_html)
dfCov['cleanContent'] = dfCov['cleanContent'].apply(remove_punct)
# create string with all cleaned tweets as text
str_covtweets = dfCov['cleanContent'].astype(str).str.cat(sep=' ').casefold()
#%%
# replace single U and S characters
str_covtweets = str_covtweets.replace(' u ', ' ')
str_covtweets = str_covtweets.replace(' s ', ' ')
str_alltweets = str_alltweets.replace(' u ', ' ')
str_alltweets = str_alltweets.replace(' s ', ' ')
# %%
# create wordcloud alltweets
wcA = WordCloud(background_color="white", width=1000, height=1000, repeat=True)
wcA.generate(str_alltweets)
#%%
# draw
plt.figure( figsize=(20,20))
plt.axis("off")
plt.imshow(wcA, interpolation="bilinear")
fig1 = plt.gcf()
plt.show()
fig1.savefig(wcAllTweetsFPath)
# %%
# create wordcloud covtweets
wcC = WordCloud(background_color="white", width=1000, height=1000, repeat=True)
wcC.generate(str_covtweets)
#%%
# draw
plt.figure( figsize=(20,20))
plt.axis("off")
plt.imshow(wcC, interpolation="bilinear")
fig2 = plt.gcf()
plt.show()
fig2.savefig(wcCovTweetsFPath)
# %%
# with open('test.txt', 'w') as f:
# f.write(str_covtweets)
# %%
dfT = pd.DataFrame()
dfT['date'] = df['date'].copy()
dfT['count'] = 1
dfCovT = pd.DataFrame()
dfCovT['date'] = dfCov['date'].copy()
dfCovT['count'] = 1
#%%
dfT['date'] = pd.to_datetime(dfT['date']).dt.strftime('%Y-%m-%d')
dfCovT['date'] = pd.to_datetime(dfCovT['date']).dt.strftime('%Y-%m-%d')
#%%
dfT = dfT.groupby('date').count().reset_index()
dfCovT = dfCovT.groupby('date').count().reset_index()
#%%
import matplotlib.dates as mdates
# n of tweets overall
my_dpi=300
plt.figure(figsize=(1000/my_dpi, 1500/my_dpi), dpi=my_dpi)
plt.style.use('seaborn-darkgrid')
fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(dfCovT['date'], dfCovT['count'], marker='', color='tab:blue', linewidth=1, alpha=0.4)
ax.plot(dfT['date'], dfT['count'], marker='', color='tab:blue', linewidth=1, alpha=1)
ax.xaxis.set_major_locator(mdates.MonthLocator(interval=3))
ax.xaxis.set_minor_locator(mdates.MonthLocator())
fig.autofmt_xdate()
fig.savefig(TwCovTimelinePath)
# %%