import pandas as pdimport numpy as npimport mathdf=pd.Dataframe({'Class': ['A1','A1','A1','A2','A3','A3'], 'Force': [50,150,100,120,140,160] }, columns=['Class', 'Force'])print(df)print('-'*30)stats = df.groupby(['Class'])['Force'].agg(['mean', 'count', 'std'])print(stats)print('-'*30)ci95_hi = []ci95_lo = []for i in stats.index: m, c, s = stats.loc[i] ci95_hi.append(m + 1.96*s/math.sqrt(c)) ci95_lo.append(m - 1.96*s/math.sqrt(c))stats['ci95_hi'] = ci95_histats['ci95_lo'] = ci95_loprint(stats)输出是
Class Force0 A1 501 A1 1502 A1 1003 A2 1204 A3 1405 A3 160------------------------------ mean count stdClass A1 100 3 50.000000A2 120 1 NaNA3 150 2 14.142136------------------------------ mean count std ci95_hi ci95_loClass A1 100 3 50.000000 156.580326 43.419674A2 120 1 NaN NaN NaNA3 150 2 14.142136 169.600000 130.400000
