Python – Getting keyError(key) when using groupBy.agg()

import pandas as pd

dict1 = {
  "brand": "Ford",
  "model": "Mustang",
  "year": 1964
}

dict2 = {
  "brand": "Ford",
  "model": "F150",
  "year": 1999
}

dict3 = {
  "brand": "Chevy",
  "model": "Malibu",
  "year": 1972
}

d = {
        "col0": ["GM", "GM", "Dodge"],
        "col1": [dict1, dict3, dict2],
        "col2": [dict3, dict2, dict2],
        "col3": [dict1, dict2, dict3]
    }

df = pd.DataFrame(d)

grouped = df.groupby(['col0'], as_index=False)
first = lambda a : a[0]
df = grouped.agg({'col1':first,'col2':first, 'col3':first})

When I try to use the agg function, I’m getting raise KeyError(key) from err.

What I”m trying to do is combine these based on the columns I’m grouping by and I want to take the first dict after grouping.

I want the output to be what you see below and I don’t really care which “GM” is kept. I arbitrarily chose the first, which is fine.

d = {
        "col0": ["GM", "Dodge"],
        "col1": [dict1, dict2],
        "col2": [dict3, dict2],
        "col3": [dict1, dict3]
    }

Answer

Use .iloc:

grouped = df.groupby('col0')
first = lambda a : a.iloc[0]
df = grouped.agg({'col1':first, 'col2': first, 'col3': first})