I have this two data frames df and df1 where
B2B_1 = {'Month': ['10/2018','11/2018','12/2018','01/2019','02/2019','03/2019'],
'B2B': [200,400, 250,
100,120,200]]
}
B2C_1 = {'Month': ['10/2018','11/2018','12/2018','01/2019','02/2019','03/2019'],
'B2C': [200,400, 250,
100,120,200]
}
df=pd.DataFrame(B2B_1)
df1=pd.DataFrame(B2C_1)
And I didn't know how to plot these two data frames in one plot where axis is based on "Month"
pandas plotting functions have the ax parameter in them; if you pass an e.g. matplotlib axis instance to it, it will do its plotting on that axis. So
# make a figure and an axis
fig, ax = plt.subplots(figsize=(14, 7))
# plot desired quantities; note the `ax=ax` in both
df.plot(x="Month", y="B2B", ax=ax)
df1.plot(x="Month", y="B2C", ax=ax)
Two DataFrame something like this code
B2B_1 = {'Month': ['10/2018','11/2018','12/2018','01/2019','02/2019','03/2019'],
'B2B': [200,400, 250,
100,120,200]
}
B2C_1 = {'Month': ['10/2018','11/2018','12/2018','01/2019','02/2019','03/2019'],
'B2C': [200,400, 250,
100,120,200]
}
df=pd.DataFrame(B2B_1)
df1=pd.DataFrame(B2C_1)
x=df['Month']
x1=df["B2B"]
y=df1['Month']
y1=df1["B2C"]
plt.figure(figsize=(15,8))
plt.bar(x,x1,label="Month")
plt.bar(y,y1,label="Month")
plt.title("Data")
plt.legend(title="Data")
plt.show()
Using that code help to plot the two dataframe easy
pd.concat([df,df1], axis=1).plot(kind='bar')