making groupby plot using matplotlib and pandas-CodePudding

i have a code that plot the figure as fllows

code is

import matplotlib.pyplot as plt
import pandas as pd

years=["ASD","MNG","KQR","MND","QST", "MNR"]
dataavail={
    "Jan":[20,20,30,19,10,21],
    "Feb":[20,13,10,18,15,30],
    "Mar":[20,20,10,15,18,30],
    "Apr":[20,20,10,15,18,0],
    "May":[20,20,10,15,18,0],
    "Jun":[20,20,10,15,18,0],
    "Jul":[20,20,10,15,18,0],
    "Aug":[20,20,10,15,18,45],
    "Sep":[20,20,10,15,18,0],
    "Oct":[20,20,10,15,18,0],
    "Nov":[20,20,10,15,18,0],
    "Dec":[20,20,0,0,0,0],
}


df_month = pd.DataFrame(dataavail, index=years)
fig, ax1 = plt.subplots(1, figsize=(8, 5))
df_month.plot(kind='bar', stacked=True, colormap=plt.cm.tab20, ax=ax1)
plt.legend(loc="upper right", ncol = 3,handlelength=1.5, borderpad=0.2, labelspacing=0.2) 
plt.xticks(rotation=0)
plt.show()

However, instead of stack plot i need the groupby plot something like as figure attached where the x-axis should be same as the first plot.can anybody help me on this.

CodePudding user response：

IIUC you want an unstacked bar plot?

df_month.plot.bar()

output:

using your code:

You should remove stacked=True (or use stacked=False):

df_month = pd.DataFrame(dataavail, index=years)
fig, ax1 = plt.subplots(1, figsize=(8, 5))
df_month.plot(kind='bar', stacked=False, colormap=plt.cm.tab20, ax=ax1)
plt.legend(loc="upper right", ncol = 3,handlelength=1.5, borderpad=0.2, labelspacing=0.2) 
plt.xticks(rotation=0)
plt.show()