In [1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter
import matplotlib.dates as mdates
name = "GME"
filename = "%s.csv" % name
file = filename
df = pd.read_csv(filename, delimiter='\t', parse_dates=['Submission_Date'])
df['Submission_Date'] = pd.to_datetime(df['Submission_Date'], format='%Y-%m-%d %H:%M:%S')
df = df.groupby(pd.Grouper(key='Submission_Date',freq='H')).count()
df = df.rename(columns={"Post ID": "Number_of_Submissions"})
df = df.drop(columns=['Title', 'Url', 'Author', 'Score', 'Total_Num_of_Comments', 'Permalink', 'Flair', 'Selftext', 'TitleAndText', 'Word Count'])
df.to_csv('GME_Number_of_Submissions_per_hour.csv')
df.head()
# reindex to fill dates with no posts
df.index = pd.to_datetime(df.index, format='%d.%m.%Y %H')
df = df.reindex(pd.date_range(df.index.min(), df.index.max()))
df.index = df.index.strftime('%Y-%m-%d %H')
df = df['Number_of_Submissions']
df.index = pd.to_datetime(df.index, format='%Y-%m-%d %H')
df = df.reindex(pd.date_range(df.index.min(), df.index.max()))
df.index = df.index.strftime('%Y-%m-%d')
ax = df.plot.bar(figsize=(20,6))
plt.xlabel('Submission date')
plt.ylabel('Number of submissions')
plt.title('Number of submissions over time')
every_nth = 7
for n, label in enumerate(ax.xaxis.get_ticklabels()):
if n % every_nth != 0:
label.set_visible(False)
