Pandas Dataframe: split multiple columns into multiple columns

Question

I've a panda dataframe in this format.

   Var1                  Var2                        Var2
    A   [2016-09-26, 2016-08-25, 2016-08-06] [u'1', u'5', u'4']
    B   [2016-09-26, 2016-08-25, 2016-08-06] [u'1', u'5', u'4']

I want to convert it into the following format.

Var1     Var2      Var3
 A    2016-09-26    1
 A    2016-08-25    5
 A    2016-08-06    4
 B    2016-09-26    1
 B    2016-08-25    5
 B    2016-08-06    4

Can anyone please tell me how to do it?

Thanks a lot!

jezrael · Accepted Answer · 2017-03-14 14:02:32Z

1

If values in columns Var2 and Var3 are in lists, you can use numpy.repeat for repeat values by legths by str.len and flat values of nested lists by chain:

print (type(df.Var2.iat[0]))
<class 'list'>

print (type(df.Var3.iat[0]))
<class 'list'>

from  itertools import chain

df1 = pd.DataFrame({
        "Var1": np.repeat(df.Var1.values, df.Var2.str.len()),
        "Var2": list(chain.from_iterable(df.Var2)),
        "Var3": list(chain.from_iterable(df.Var3))})

print (df1)
  Var1        Var2 Var3
0    A  2016-09-26    1
1    A  2016-08-25    5
2    A  2016-08-06    4
3    B  2016-09-26    1
4    B  2016-08-25    5
5    B  2016-08-06    4

answered Mar 14, 2017 at 14:02

jezrael

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2 Comments

Beta Over a year ago

@jazrael: Thanks a lot! This answer perfectly solved my problem.

jezrael Over a year ago

Super, glad can help you. And nice day!

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