Replicate rows in a pandas dataframe based on the column values of another dataframe

Question

import pandas as pd
data = [10]
booklines = pd.DataFrame(data,columns=['Nums'])
matches = {'Fullname':['Sasel - Dassendorf'],'HomeTeam':['Sasel'],'AwayTeam':['Dassendorf']}
matches_df = pd.DataFrame(matches)

Is there a way I can replicate the number of rows in matches_df based on the row value 10 which is present in booklines.

The end result is the matches df replicated ten times like this. I am looking for a programatic way of doing this instead of manually adding in the ten like so.

matches_df.append([matches_df]*10,ignore_index=True)

so i want to times the value in booklines by the matches[[Fullname,HomeTeam,AwayTeam]] columns — Paul Corcoran
– Paul Corcoran, Commented Oct 12, 2022 at 7:30
I ask because not sure if need replicate multiple rows like in edited answer, last part. — jezrael
– jezrael, Commented Oct 12, 2022 at 7:34

jezrael · Accepted Answer · 2022-10-12 07:46:18Z

1

Use:

val = booklines['Nums'].iat[0]

matches = {'Fullname':['Sasel - Dassendorf']*val,
           'HomeTeam':['Sasel']*val,
           'AwayTeam':['Dassendorf']*val}
matches_df = pd.DataFrame(matches)

Or:

matches = {'Fullname':['Sasel - Dassendorf'],'HomeTeam':['Sasel'],'AwayTeam':['Dassendorf']}
matches_df = pd.DataFrame(matches).reindex(range(val), method='ffill')
print (matches_df)
             Fullname HomeTeam    AwayTeam
0  Sasel - Dassendorf    Sasel  Dassendorf
1  Sasel - Dassendorf    Sasel  Dassendorf
2  Sasel - Dassendorf    Sasel  Dassendorf
3  Sasel - Dassendorf    Sasel  Dassendorf
4  Sasel - Dassendorf    Sasel  Dassendorf
5  Sasel - Dassendorf    Sasel  Dassendorf
6  Sasel - Dassendorf    Sasel  Dassendorf
7  Sasel - Dassendorf    Sasel  Dassendorf
8  Sasel - Dassendorf    Sasel  Dassendorf
9  Sasel - Dassendorf    Sasel  Dassendorf

If same number of rows in both DataFrames and need use Nums column for replicate use Index.repeat with DataFrame.loc:

data = [10, 7]
booklines = pd.DataFrame(data,columns=['Nums'])
print (booklines)
   Nums
0    10
1     7

matches = {'Fullname':['Sasel - Dassendorf', 'Sasel - Dassendorf'],
           'HomeTeam':['Sasel', 'Dassendorf'],
           'AwayTeam':['Dassendorf', 'Sasel']}
matches_df = pd.DataFrame(matches)
print (matches_df)
             Fullname    HomeTeam    AwayTeam
0  Sasel - Dassendorf       Sasel  Dassendorf
1  Sasel - Dassendorf  Dassendorf       Sasel

df = matches_df.loc[matches_df.index.repeat(booklines['Nums'])]
print (df)
             Fullname    HomeTeam    AwayTeam
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
0  Sasel - Dassendorf       Sasel  Dassendorf
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel
1  Sasel - Dassendorf  Dassendorf       Sasel

Last for default index use:

df = df.reset_index(drop=True)

edited Oct 12, 2022 at 7:46

answered Oct 12, 2022 at 7:26

jezrael

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4 Comments

Paul Corcoran Over a year ago

thanks is there a way to look up the booklines dataframe which contains the value 10 to do this?

jezrael Over a year ago

@PaulCorcoran - Do you need extract it by booklines['Nums'].iat[0] ?

Paul Corcoran Over a year ago

thank you df = matches_df.loc[matches_df.index.repeat(booklines['Nums'])] this is the line i want

jezrael Over a year ago

@PaulCorcoran - super!

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