import pandas as pd import numpy as np df = pd.DataFrame(np.arange(50).reshape(10, 5), columns=list('abcde')) print(df) print(df.describe()) print(df.sem()) df1 = pd.Series(['a', 'b', 'c', 'd', 'a', 'a', 'f', 'd']) print(df1.value_counts()) print(df1.describe()) 输出结果: a b c d e 0 0 1 2 3 4 1 5 6 7 8 9 2 10 11 12 13 14 3 15 16 17 18 19 4 20 21 22 23 24 5 25 26 27 28 29 6 30 31 32 33 34 7 35 36 37 38 39 8 40 41 42 43 44 9 45 46 47 48 49 a b c d e count 10.000000 10.000000 10.000000 10.000000 10.000000 mean 22.500000 23.500000 24.500000 25.500000 26.500000 std 15.138252 15.138252 15.138252 15.138252 15.138252 min 0.000000 1.000000 2.000000 3.000000 4.000000 25% 11.250000 12.250000 13.250000 14.250000 15.250000 50% 22.500000 23.500000 24.500000 25.500000 26.500000 75% 33.750000 34.750000 35.750000 36.750000 37.750000 max 45.000000 46.000000 47.000000 48.000000 49.000000 a 4.787136 b 4.787136 c 4.787136 d 4.787136 e 4.787136 dtype: float64 a 3 d 2 b 1 c 1 f 1 dtype: int64 count 8 unique 5 top a freq 3 dtype: object
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