CODEWITHSUNDEEP
pythonpandasdataframe
Grégoire de Kermel
Grégoire de Kermel

Reputation: 452

Automating pandas dataframe join from list

I have a list of 4 dataframes each containing only 1 column ('CustomerID'). I would like to merge (inner join) them within a loop.

This is what I've try for the moment:

for i in all_df:
    merged = all_df[0].merge(all_df[1], on='CustomerID')
    del df[0]

What I'm trying to do here is to merge the first dataframe (index 0) with the second (index 1), then delete the first dataframe in order that the dataframe of index 1 becomes the dataframe of index 0 and thus, I could iterate.

I know this doesn't work as what I should merge from the second iteration should be the datframe from the new variable "merged" with the daframe of index 1.

The 4 dataframes are a client database at diferent time (march 2019, april 2019, may 2019 etc.). The point is to analyse the client lifetime (how long did they stay client?, after how many days did they left? etc.)

Could you please help me with that?

Upvotes: 2

Views: 473

Answers (2)

Andy L.
Andy L.

Reputation: 25239

If you want to merge multiple dataframes, you may use functools.reduce as follows

from functools import reduce
df_merge = reduce(lambda df_x, df_y: pd.merge(df_x, df_y, on='CustomerID'), all_df)

Upvotes: 2

FBruzzesi
FBruzzesi

Reputation: 6485

Following your step this should accomplish what you are trying to do:

#Initialize the final dataframe
result_df = all_df[0]

# Cycle over the list, from the second dataframe onwards
for df in all_df[1:]:
    result_df = result_df.merge(df, on='CustomerID')

Upvotes: 0

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