Bar plot type chart with unique values compounding the bars

Question

I’m trying to create a graph using python that show each value that count, stacked, in a form of column.

df = pd.DataFrame()
df['hour']=['00:00', '00:00','01:00', '01:00','01:00','02:00','02:00','03:00','03:00','03:00','03:00','03:00','04:00','05:00','05:00','05:00']
df['event']=['abc','def','abc','def','ghj','def','klm','mno','klm','ghj','pqr','stu','def', 'abc','pqr','mno' ]

I’m expecting something like this:

A solution or any insight will be very welcome!

Asked By: mainburnerone

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Source

Answer 1

I am using Plotly for this you can use matplotlib either.

Answered By: Nitiz

Answer 2

Try to pivot your dataframe then draw your graph:

import matplotlib.pyplot as plt

# Pivot your dataframe and create a dummy column
df1 = df.assign(value=1).pivot_table(index='hour', columns='event', 
                                     values='value', fill_value=0)

# Use Pandas to draw your graph
ax = df1.plot.bar(stacked=True, rot=0, legend=False, width=1, color='blue')

# Fill each rectangle
labels = df1.mul(df1.columns).to_dict('list').values()
for c, l in zip(ax.containers, labels):
    ax.bar_label(c, l, label_type='center', color='white')

# Customize your graph
ax.yaxis.set_major_locator(plt.NullLocator())
plt.show()

Output:

Details:

>>> df1
event  abc  def  ghj  klm  mno  pqr  stu
hour                                    
00:00    1    1    0    0    0    0    0
01:00    1    1    1    0    0    0    0
02:00    0    1    0    1    0    0    0
03:00    0    0    1    1    1    1    1
04:00    0    1    0    0    0    0    0
05:00    1    0    0    0    1    1    0

Answered By: Corralien

Bar plot type chart with unique values compounding the bars

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