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Hello

I have to datasets that I want to join. The first dataset as a DATE column, but the second dataset as a BEGIN_DATE and END_DATE column.

I want to join rows from dataset2 into dataset1 analysis.

Is there a way to join the 2 datasets directly or a way to enrich dataset2 and add rows matching BEGIN_DATE en END_DATE?

Best regards

Geoff.
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1 Answer

+1 vote

I succeeded in doing the "join" (actually it is not, but for my data it is). The goal is to tag each record from DATASET1 for being/not being in a specific time period. Time periods are defined in DATASET2.

I did it using Python.

For those interested, here is the script (As i'm not a Python expert, more elegant code can be proposed):

# -*- coding: utf-8 -*-
import dataiku
import pandas as pd, numpy as np
from dataiku import pandasutils as pdu

# Input datasets
DATASET1 = dataiku.Dataset("DATASET1")
DATASET1_df = histo_MAG_JF_ZV.get_dataframe()
DATASET2 = dataiku.Dataset("DATASET2")
DATASET2_df = soldes_prepared.get_dataframe()

# Output datasets
DATASET1_outuput = dataiku.Dataset("DATASET1_outuput")

# Pour chaque ligne du tableau de Soldes
for d in DATASET2.iter_rows():
    # FOR DEBUG
    #print d
    
    begin_date = d['begin']
    end_date = d['end']
                      
    cond1 = (DATASET1_df['Date'] >= begin_date)
    cond2 = (DATASET1_df['Date'] <= end_date)
    
    matching_records = DATASET1_df[cond1][cond2]
    
    # Add begin/end date to output dataset
    matching_records['begin_date'] = begin_date
    matching_records['end_date'] = end_date
    
    DATASET1_outuput.write_with_schema(matching_records)

 

Next I left join DATASET1 with DATASET1_output to recover non mathing records, as the following analysis needs both matching and non matching records.

Geoff

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