How to Plot Stacked with Logarithmic Scale Bar Chart in Pandas?

DataPlotPlus -

To plot stacked bar plot with logarithmic scale in Pandas we can use parameters:

  • stacked=True
  • log=True

Steps to plot bar chart - stacked and log

  • Import matplotlib library
  • Create DataFrame with correlated data
  • Create the bar plot
  • add parameters: stacked=True, log=True

More information can be found: DataFrame.plot

Data

amount price
A 4 400
B 8 500
C 15 1000
D 7 600
E 3 120

Example

import matplotlib.pyplot as plt
import pandas as pd

data = {"amount":{"A":4,"B":8,"C":15,"D":7,"E":3},
        "price":{"A":400,"B":500,"C":1000,"D":600,"E":120}}
df = pd.DataFrame(data)

df.plot.bar(secondary_y= 'amount', stacked=True, log=True)

ax1, ax2 = plt.gcf().get_axes() 
ax1.set_ylabel('price')

ax2.set_ylabel('amount')

Output

Example 2 - non logarithmic

Create a figure and two axes:

import matplotlib.pyplot as plt
import pandas as pd

data = {"amount":{"A":4,"B":8,"C":15,"D":7,"E":3},
        "price":{"A":400,"B":500,"C":1000,"D":600,"E":120}}
df = pd.DataFrame(data)

_ = df.plot( kind= 'bar' , secondary_y= 'amount' , rot= 0 , stacked=True, log=False)
plt.show()

Output

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