Plot stacked bar chart from pandas data frame

Question

I have dataframe:

payout_df.head(10)

What would be the easiest, smartest and fastest way to replicate the following excel plot?

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Answer 1

Besides the lack of data, I think the following code will produce the desired graph

import pandas as pd
import matplotlib.pyplot as plt

df.payout = pd.to_datetime(df.payout)

grouped = df.groupby(pd.Grouper(key='payout', freq='M')).sum()
grouped.plot(x=grouped.index.year, kind='bar', stacked=True)

plt.show()

I don't know how to reproduce this fancy x-axis style. Also, your payout column must be a datetime, otherwise pd.Grouper won't work (available frequencies).

Answer 2

If you just want a stacked bar chart, then one way is to use a loop to plot each column in the dataframe and just keep track of the cumulative sum, which you then pass as the bottom argument of pyplot.bar

import pandas as pd
import matplotlib.pyplot as plt

# If it's not already a datetime
payout_df['payout'] = pd.to_datetime(payout_df.payout)

cumval=0
fig = plt.figure(figsize=(12,8))
for col in payout_df.columns[~payout_df.columns.isin(['payout'])]:
    plt.bar(payout_df.payout, payout_df[col], bottom=cumval, label=col)
    cumval = cumval+payout_df[col]

_ = plt.xticks(rotation=30)
_ = plt.legend(fontsize=18)