Hands-On Exploratory Data Analysis with Python

Number of emails per day

Let's find the busiest day of the week in terms of emails:

counts = dfs.dayofweek.value_counts(sort=False)counts.plot(kind='bar')

The output of the preceding code is as follows:

The preceding output shows that my busiest day is Thursday. I receive most of my emails on Thursdays. Let's go one step further and see the most active days for receiving and sending emails separately:

sdw = sent.groupby('dayofweek').size() / len(sent)rdw = received.groupby('dayofweek').size() / len(received)df_tmp = pd.DataFrame(data={'Outgoing Email': sdw, 'Incoming Email':rdw})df_tmp.plot(kind='bar', rot=45, figsize=(8,5), alpha=0.5) ...