CODEWITHSUNDEEP
pythonpandasmatplotlib
min
min

Reputation: 65

Multiple plots in 1 figure using for loop

I've got data in the below format, and what I'm trying to do is to:

1) loop over each value in Region
2) For each region, plot a time series of the aggregated (across Category) sales number.

Date |Region |Category | Sales
01/01/2016| USA| Furniture|1
01/01/2016| USA| Clothes |0
01/01/2016| Europe| Furniture|2
01/01/2016| Europe| Clothes |0
01/02/2016| USA| Furniture|3
01/02/2016| USA|Clothes|0
01/02/2016| Europe| Furniture|4
01/02/2016| Europe| Clothes|0 ...

The plot should look like the attached (done in excel).

enter image description here

However, if I try to do it in Python using the below, I get multiple charts when I really want all the lines to show up in one figure.

Python code: 

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv(r'C:\Users\wusm\Desktop\Book7.csv')


plt.legend()
for index, group in df.groupby(["Region"]):
    group.plot(x='Date',y='Sales',title=str(index))

plt.show()

Short of reformatting the data, could anyone advise on how to get the graphs in one figure please?

Upvotes: 3

Views: 741

Answers (1)

jezrael
jezrael

Reputation: 862431

You can use pivot_table:

df = df.pivot_table(index='Date', columns='Region', values='Sales', aggfunc='sum')
print (df)
Region      Europe  USA
Date                   
01/01/2016       2    1
01/02/2016       4    3

or groupby + sum + unstack:

df = df.groupby(['Date', 'Region'])['Sales'].sum().unstack(fill_value=0)
print (df)
Region      Europe  USA
Date                   
01/01/2016       2    1
01/02/2016       4    3

and then DataFrame.plot

df.plot()

Upvotes: 3

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