How to use argmin with groupby in pandas

argmin() is not an agg function, you can use apply to get the closest index of every group:

txt = """  cat  val
0   a    1
1   a    6
2   a   12
3   b    2
4   b    5
5   b   11
6   c    4
7   c   22"""

import io

df = pd.read_csv(io.BytesIO(txt), delim_whitespace=True, index_col=0)
df["val_delt"] = (df.val - 5.5).abs()
idx = df.groupby("cat").apply(lambda df:df.val_delt.argmin())
df.ix[idx, :]

output:

cat  val  val_delt
1   a    6       0.5
4   b    5       0.5
6   c    4       1.5

All answers here are somewhat correct, but none of them does it in a concise, beautiful and pythonic way. I leave here a clear way to do this.

>>> indx = df.groupby('cat')['val_delt'].idxmin()
>>> df.loc[indx]

  cat  val  val_delt
1   a    6       0.5
4   b    5       0.5
6   c    4       1.5