Split pandas data frame columns by row value

Question

I have a data frame like this:

>df = pd.DataFrame({'A':['M',2,3],'B':['M',2,3],'AA':['N',20,30],'BB':['N',20,30]})
>df = df.rename(columns={df.columns[2]: 'A'})
>df = df.rename(columns={df.columns[3]: 'B'})
>df

  A  B  A  B
0 M  M  N  N
1 2  2  20 20
2 3  3  30 30

and I have to split the data frame vertically by row index 0 = 'M' and 'N':

The data in the data frame comes from an Excel sheet and the column names are not unique. Thanks for help!

you need to split data into 2 separate data frames?

Zaraki Kenpachi
– Zaraki Kenpachi

2019-06-18 09:51:06 +00:00
Commented Jun 18, 2019 at 9:51 — Zaraki Kenpachi
– Zaraki Kenpachi, Commented Jun 18, 2019 at 9:51
Have you tried iloc?

Noob Programmer
– Noob Programmer

2019-06-18 09:53:49 +00:00
Commented Jun 18, 2019 at 9:53 — Noob Programmer
– Noob Programmer, Commented Jun 18, 2019 at 9:53

quest · Accepted Answer · 2019-06-18 09:57:34Z

2

This should get the job done:

df.loc[:,df.iloc[0, :] == "M"]
df.loc[:,df.iloc[0, :] == "N"]

answered Jun 18, 2019 at 9:57

quest

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Comments

Zaraki Kenpachi · Accepted Answer · 2019-06-18 09:55:45Z

1

Use pandas iloc for selecting columns:

=^..^=

import pandas as pd

df = pd.DataFrame({'A':['M',2,3],'B':['M',2,3],'AA':['N',20,30],'BB':['N',20,30]})
df = df.rename(columns={df.columns[2]: 'A'})
df = df.rename(columns={df.columns[3]: 'B'})

df1 = df.iloc[:, :2]
df2 = df.iloc[:, 2:]

Output:

answered Jun 18, 2019 at 9:55

Zaraki Kenpachi

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Comments

Space Impact · Accepted Answer · 2019-06-18 09:56:50Z

1

Use list comprehension with loc as:

dfs = [df.loc[:, df.loc[0,:].eq(s)] for s in ['M','N']]

This gives seperate dataframes in list.

answered Jun 18, 2019 at 9:56

Space Impact

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