Expand row values in pandas into multiple columns

Question

I have a dataframe with two columns:id and vendor_name as given below:

 id   vendor_name
  1   vendor1
  1   vendor2
  2   vendor1

I want to transform it as follows:

 id   vendor_name1 vendor_name2
  1    vendor1        vendor2  
  2    vendor1        nan

Is there a way i can acheive this in pandas?

What have you tried so far?

Sociopath
– Sociopath

2019-11-18 10:06:06 +00:00
Commented Nov 18, 2019 at 10:06 — Sociopath
– Sociopath, Commented Nov 18, 2019 at 10:06

jezrael · Accepted Answer · 2019-11-18 10:06:14Z

1

Use Series.unstack for reshape with new columns names created by GroupBy.cumcount:

df1 = (df.set_index(['id', df.groupby('id').cumcount().add(1)])['vendor_name']
        .unstack()
        .add_prefix('vendor_name')
        .reset_index())
print (df1)
   id vendor_name1 vendor_name2
0   1      vendor1      vendor2
1   2      vendor1          NaN

answered Nov 18, 2019 at 10:06

jezrael

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