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`

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')
``````

## 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()
``````