Select a range of column base on value of another column in pandas

Question

My dataset looks like this(first row is header)

0    1    2    3    4    5
1    3    4    6    2    3
3    8    9    3    2    4
2    2    3    2    1    2

I want to select a range of columns of the dataset based on the column [5], e.g:

1    3    4
3    8    9    3
2    2

I have tried the following, but it did not work:

df.iloc[:,0:df['5'].values]

What kind of output you want? If it s a dataframe, do you want to replace missing values with nans? — hanego
– hanego, Commented Dec 7, 2017 at 3:04

Scott Boston · Accepted Answer · 2017-12-07 03:19:44Z

2

Let's try:

df.apply(lambda x: x[:x.iloc[5]], 1)

Output:

     0    1    2    3
0  1.0  3.0  4.0  NaN
1  3.0  8.0  9.0  3.0
2  2.0  2.0  NaN  NaN

answered Dec 7, 2017 at 3:19

Scott Boston

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2 Comments

Nice one :-) I like the usage of apply

apply is neater :-)

BENY · Accepted Answer · 2017-12-07 03:36:58Z

2

Recreate your dataframe

df=pd.DataFrame([x[:x[5]] for x in df.values]).fillna(0)
df
Out[184]: 
   0  1    2    3
0  1  3  4.0  0.0
1  3  8  9.0  3.0
2  2  2  0.0  0.0

answered Dec 7, 2017 at 3:36

BENY

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