Create a nested dictionary from pd dataframe Python

Question

I have the following data frame like (in reality with hundreds of rows)

    Location Date       Court    Winner 
0   Paris    10/2/2018  Outdoor  Flavio
1   Paris    10/2/2018  Indoor   Luca
2   Paris    10/2/2018  Indoor   Giovanni
3   Paris    10/2/2018  Indoor   Luca

What I want to do is to get a nested dictionary that look like that:

{ 'Flavio' : { 'Outdoor' : 1 , 'Indoor' : 0 } , 'Luca' : {'Outdoor' : 0 , 'Indoor' : 2} }

and so on. So in other words I want to determine the number of times winners won in the Outdoor and in the Indoor court.

Thank you in advance!

jezrael · Accepted Answer · 2020-02-20 11:43:05Z

5

Use crosstab with DataFrame.to_dict:

d = pd.crosstab(df['Court'],df['Winner']).to_dict()
print (d)
{'Flavio': {'Indoor': 0, 'Outdoor': 1},
 'Giovanni': {'Indoor': 1, 'Outdoor': 0}, 
 'Luca': {'Indoor': 2, 'Outdoor': 0}}

edited Feb 20, 2020 at 11:43

answered Feb 20, 2020 at 11:38

jezrael

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2 Comments

filbranden Over a year ago

Also possible pd.crosstab(df['Court'], df['Winner']).to_dict() rather than using .T

Celius Stingher Over a year ago

You are always first!

Celius Stingher · Accepted Answer · 2020-02-20 11:41:40Z

3

You can do it with a pivot_table and to_dict:

import pandas as pd
import numpy as np
df = pd.DataFrame({'Location':['France','France','France','France'],
                   'Court':['Outdoor','Indoor','Indoor','Indoor'],
                   'Winner':['Flavio','Luca','Giovanni','Luca']})
df = pd.pivot_table(df,values='Location',columns='Winner',index='Court',aggfunc='count',fill_value=0)
a = df.to_dict()
print(a)

Output:

{'Flavio': {'Indoor': 0, 'Outdoor': 1}, 'Giovanni': {'Indoor': 1, 'Outdoor': 0}, 'Luca': {'Indoor': 2, 'Outdoor': 0}}

answered Feb 20, 2020 at 11:41

Celius Stingher

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