Matplotlib Dataframe 2 Column [dates, Non-numerical-data] Stacked Bar Chart Defining Attributes

Background: I have managed to create the following graph, but I have difficulty with some of the elements Disclaimer: This graph below is what I want to achieve, however I would li

Solution 1:

As for the date format, I couldn't do what I wanted because of the different locales. Also, the only way to make the width of the bar thicker is to thin out the number of data, so unnecessary lines are removed.

import pandas as pd
import numpy as np
import io

data = '''
date Operation
2020-05-07 A
2020-05-08 B
2020-05-08 A
2020-05-12 A
2020-05-12 A
2020-05-12 B
2020-05-13 C
2020-05-13 A
2020-05-13 B
2020-05-14 A
2020-05-19 B
2020-05-21 A
2020-05-25 A
2020-05-26 B
2020-05-26 C
2020-05-26 A
2020-05-26 A
2020-05-29 A
'''

df = pd.read_csv(io.StringIO(data), sep='\s+')
df['date'] = pd.to_datetime(df['date'])
all_dates = pd.date_range('2020-05-01','2020-05-31', freq='D').date
df2 = pd.crosstab(df.date,df.Operation).reindex(all_dates)

import matplotlib.pyplot as plt

fig = plt.figure(figsize=(4,8),dpi=100) # Define the chart size (400 by 800)

df2.dropna(inplace=True) # Make the bars more wide

ax = df2.plot.bar(stacked=True)

ax.set_title('this is my chart') # Add a this is my chart title to the chart

ax.set_xlabel('this is x-axis') # Add labels (this is x axis, this is y-axis) to the x & y axis ?
ax.set_ylabel('this is y-axis')

start, end = ax.get_ylim()
ax.yaxis.set_ticks(np.arange(start, end, 1)) # Make the y-axis integers