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!
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
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