Use groupby.first;它需要 第一个非 NA 值:

df.groupby('hostname')[['period', 'Teff']].first().reset_index()
#  hostname   period  Teff
#0      Cnc  44.3787  5234
#1      Peg   4.2293  5773
#2      Vir  38.0210  5577

或者使用自定义聚合函数手动执行此操作:

Or manually do this with a custom aggregation function:

df.groupby('hostname')[['period', 'Teff']].agg(lambda x: x.dropna().iat[0]).reset_index()

这要求每组至少有一个非 NA 值.

This requires each group has at least one non NA value.

编写自己的函数来处理边缘情况:

Write your own function to handle the edge case:

def first_(g):
    non_na = g.dropna()
    return non_na.iat[0] if len(non_na) > 0 else pd.np.nan

df.groupby('hostname')[['period', 'Teff']].agg(first_).reset_index()

#  hostname   period  Teff
#0      Cnc  44.3787  5234
#1      Peg   4.2293  5773
#2      Vir  38.0210  5577