CODEWITHSUNDEEP
pythonpandasdataframemerge
mongotop
mongotop

Reputation: 5774

Merge two Pandas DataFrames based on approximate or exact matches

Below is the DataFrames example I want to merge.

#!/usr/bin/env python

import pandas as pd

countries   = ['Germany', 'France', 'Indonesia']
rank_one    = [1, 5, 7]
capitals    = ['Berlin', 'Paris', 'Jakarta']
df1         = pd.DataFrame({'country': countries,
                            'rank_one': rank_one,
                            'capital': capitals})

df1 = df1[['country', 'capital', 'rank_one']]    

population = ['8M', '82M', '66M', '255M']
rank_two   = [0, 1, 6, 9]
df2        = pd.DataFrame({'population': population,
                           'rank_two': rank_two})

df2        = df2[['rank_two', 'population']]

I want to merge the both DataFrames based on an exact or approximate match.

if rank_two is equal to rank_one

OR

rank_two is the closest and next bigger number from rank_one.

Example :

df1 :

     country  capital  rank_one
0    Germany   Berlin         1
1     France    Paris         5
2  Indonesia  Jakarta         7

df2 :

   rank_two population
0         0         8M
1         1        82M
2         6        66M
3         9       255M

df3_result :

     country  capital  rank_one  rank_two population
0    Germany   Berlin         1         1        82M
1     France    Paris         5         6        66M
2  Indonesia  Jakarta         7         9       255M

Upvotes: 3

Views: 1598

Answers (2)

Sven Harris
Sven Harris

Reputation: 2939

You can use the pandas 'merge_asof' function

pd.merge_asof(df1, df2, left_on="rank_one", right_on="rank_two", direction='forward')

alternatively if you want to merge by closest and you don't mind if it's higher or lower you can use:

direction="nearest"

Upvotes: 2

BENY
BENY

Reputation: 323366

By using merge_asof

pd.merge_asof(df1,df2,left_on='rank_one',right_on='rank_two',direction='forward')
Out[1206]: 
     country  capital  rank_one  rank_two population
0    Germany   Berlin         1         1        82M
1     France    Paris         5         6        66M
2  Indonesia  Jakarta         7         9       255M

Upvotes: 6

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