Need to transpose a pandas dataframe

问题:

I have a Series that look like this:

      col1          id
 0      a           10
 1      b           20
 2      c           30
 3      b           10
 4      d           10
 5      a           30
 6      e           40

My desired output is this:

    a   b   c   d   e
10  1   1   0   1   0
20  0   1   0   0   0
30  1   0   1   0   0
40  0   0   0   0   1

I got this code:

import pandas as pd

df['dummies'] = 1
df_ind.pivot(index='id', columns='col1', values='dummies') 

I get an error:

    137 
    138         if mask.sum() < len(self.index):
--> 139             raise ValueError('Index contains duplicate entries, '
    140                              'cannot reshape')
    141 

ValueError: Index contains duplicate entries, cannot reshape

There are duplicate id's because multiple values in col1 can be attributed to a single id.

How can I achieve the desired output?

Thanks!

回答1:

You could use pd.crosstab

In [329]: pd.crosstab(df.id, df.col1)
Out[329]:
col1  a  b  c  d  e
id
10    1  1  0  1  0
20    0  1  0  0  0
30    1  0  1  0  0
40    0  0  0  0  1

Or, use pd.pivot_table

In [336]: df.pivot_table(index='id', columns='col1', aggfunc=len, fill_value=0)
Out[336]:
col1  a  b  c  d  e
id
10    1  1  0  1  0
20    0  1  0  0  0
30    1  0  1  0  0
40    0  0  0  0  1

Or, use groupby and unstack

In [339]: df.groupby(['id', 'col1']).size().unstack(fill_value=0)
Out[339]:
col1  a  b  c  d  e
id
10    1  1  0  1  0
20    0  1  0  0  0
30    1  0  1  0  0
40    0  0  0  0  1