CODEWITHSUNDEEP
pythonpandasdataframe
pepe
pepe

Reputation: 9919

How to concatenate Pandas dataframes with different N rows?

Assume the following dataframe df1:

     A
1    123
2    456
3    765
4    987
5    456
6    234
7    111
8    222
9    677
10   55

and dataframe df2:

     B
1    333344
2    665577
3    889900
4    111111

I've tried doing this with pd.append(ignore_index=True) and pd.concat(axis=1, ignore_index=True) however the result is:

     A      B
1    123    333344
2    456    665577
3    765    889900
4    987    111111
5    456    NaN
6    234    NaN
7    111    NaN
8    222    NaN
9    677    NaN
10   55     NaN

However, my desired result would be:

     A      B
1    123    NaN
2    456    NaN
3    765    NaN
4    987    NaN
5    456    NaN
6    234    NaN
7    111    333344
8    222    665577
9    677    889900
10   55     111111

Do you have any suggestions on how to accomplish this?

Upvotes: 1

Views: 53

Answers (2)

Andy L.
Andy L.

Reputation: 25259

You may use reindex and shift

n = len(df1) - len(df2)
df_final = pd.concat([df1, df2.reindex(df1.index).shift(n)], axis=1)

Out[135]:
      A         B
1   123       NaN
2   456       NaN
3   765       NaN
4   987       NaN
5   456       NaN
6   234       NaN
7   111  333344.0
8   222  665577.0
9   677  889900.0
10   55  111111.0

Upvotes: 1

BENY
BENY

Reputation: 323326

Let us do

df2.index = df1.index[-len(df2):]
df = pd.concat([df1,df2],axis=1)
df
      A         B
1   123       NaN
2   456       NaN
3   765       NaN
4   987       NaN
5   456       NaN
6   234       NaN
7   111  333344.0
8   222  665577.0
9   677  889900.0
10   55  111111.0

Upvotes: 3

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