Exploding Dataframes based on cell values

Question

I have a data frame that looks something like:

import pandas as pd
import numpy as np

f = {'business':['#','FX','IR'],
 'AL':['A','L','#'],
 'Company':['207','#','1']}
filterr = pd.DataFrame(data=f)
filterr

Whenever there is a '#' present in the dataframe, I need the rows to repeat based on every combination from a list.The set of list that I have looks something like:

business=['FX','IR']
AL=['A','L']
Company=['1','207']

So, The end result I am looking for looks something like:

f1 = {'business':['FX','IR','FX','FX','IR','IR'],
 'AL':['A','A','L','L','A','L'],
 'Company':['207','207','1','207','1','1']
 }

filter_output=pd.DataFrame(data=f1)
display(filter_output)

Any ideas on the most efficient way to do this ?

Thanks !!

updated code accordingly

Number Logic
– Number Logic

2019-06-24 17:31:30 +00:00
Commented Jun 24, 2019 at 17:31 — Number Logic
– Number Logic, Commented Jun 24, 2019 at 17:31
yes. you are right. Modified the code accordingly

Number Logic
– Number Logic

2019-06-24 17:33:39 +00:00
Commented Jun 24, 2019 at 17:33 — Number Logic
– Number Logic, Commented Jun 24, 2019 at 17:33

BENY · Accepted Answer · 2019-06-24 17:37:31Z

3

Here is one method , I am not sure about the efficient part

filterr.mask(filterr.eq('#')).fillna(d).stack().str.split(',').apply(pd.Series).stack().unstack(1).ffill()
Out[804]: 
    business AL Company
0 0       FX  A     207
  1       IR  A     207
  2       CR  A     207
1 0       FX  L       1
  1       FX  L     207
2 0       IR  A       1
  1       IR  L       1

d={'business':'FX,IR,CR',
'AL':'A,L',
'Company':'1,207'}

answered Jun 24, 2019 at 17:37

BENY

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1 Comment

BENY Over a year ago

@anky_91 Yep that could be a way too

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