In [2]: import numpy as np import pandas as pd In [3]: ser = pd.Series([5,0,3,8,4],index=['red','blue','yellow','white','green']) ser.index In [21]: ser Out[21]: red 5 blue 0 yellow 3 white 8 green 4 dtype: int64 In [20]: # 更换索引时可调整标签顺序，删除或增加 ser.reindex(['white','blue','glod','red','yellow']) Out[20]: white 8.0 blue 0.0 glod NaN red 5.0 yellow 3.0 dtype: float64 In [23]: ser3 = pd.Series([1,5,6,3],index=[0,3,5,6]) ser3 Out[23]: 0 1 3 5 5 6 6 3 dtype: int64 In [24]: ser3.reindex(range(6),method='ffill') Out[24]: 0 1 1 1 2 1 3 5 4 5 5 6 dtype: int64 In [25]: ser3.reindex(range(7),method='bfill') Out[25]: 0 1 1 5 2 5 3 5 4 6 5 6 6 3 dtype: int64 In [29]: ser.drop(['red','white']) Out[29]: blue 0 yellow 3 green 4 dtype: int64 In [33]: frame = pd.DataFrame(np.arange(16).reshape((4,4)),index=['red','blue','yellow','white'],columns=['ball','pen','pencil','paper']) frame Out[33]: ball pen pencil paper red 0 1 2 3 blue 4 5 6 7 yellow 8 9 10 11 white 12 13 14 15 In [34]: ser = pd.Series(np.arange(4),index=['ball','pen','pencil','paper']) ser Out[34]: ball 0 pen 1 pencil 2 paper 3 dtype: int32 In [35]: frame - ser Out[35]: ball pen pencil paper red 0 0 0 0 blue 4 4 4 4 yellow 8 8 8 8 white 12 12 12 12 In [37]: ser['boll'] = 9 ser Out[37]: ball 0 pen 1 pencil 2 paper 3 boll 9 dtype: int64 In [38]: frame - ser Out[38]: ball boll paper pen pencil red 0 NaN 0 0 0 blue 4 NaN 4 4 4 yellow 8 NaN 8 8 8 white 12 NaN 12 12 12 In [39]: np.sqrt(frame) Out[39]: ball pen pencil paper red 0.000000 1.000000 1.414214 1.732051 blue 2.000000 2.236068 2.449490 2.645751 yellow 2.828427 3.000000 3.162278 3.316625 white 3.464102 3.605551 3.741657 3.872983 In [40]: f = lambda x : x.max() - x.min() # 调用函数 frame.apply(f) Out[40]: ball 12 pen 12 pencil 12 paper 12 dtype: int64 In [43]: frame.apply(f,axis=1) Out[43]: red 3 blue 3 yellow 3 white 3 dtype: int64 In [44]: # 也可以返回Series对象 def f(x): return pd.Series([x.min(),x.max()],index=['min','max']) frame.apply(f) Out[44]: ball pen pencil paper min 0 1 2 3 max 12 13 14 15 In [46]: frame.sum(axis=1) Out[46]: red 6 blue 22 yellow 38 white 54 dtype: int64 In [47]: frame.mean() Out[47]: ball 6.0 pen 7.0 pencil 8.0 paper 9.0 dtype: float64 In [50]: frame.describe() Out[50]: ball pen pencil paper count 4.000000 4.000000 4.000000 4.000000 mean 6.000000 7.000000 8.000000 9.000000 std 5.163978 5.163978 5.163978 5.163978 min 0.000000 1.000000 2.000000 3.000000 25% 3.000000 4.000000 5.000000 6.000000 50% 6.000000 7.000000 8.000000 9.000000 75% 9.000000 10.000000 11.000000 12.000000 max 12.000000 13.000000 14.000000 15.000000 In [52]: ser = pd.Series([5,0,3,8,4],index=['red','blue','yellow','whiite','green']) ser Out[52]: red 5 blue 0 yellow 3 whiite 8 green 4 dtype: int64 In [53]: # 按照首字母升序 ser.sort_index() Out[53]: blue 0 green 4 red 5 whiite 8 yellow 3 dtype: int64 In [54]: ser.sort_index(ascending=False) Out[54]: yellow 3 whiite 8 red 5 green 4 blue 0 dtype: int64 In [55]: frame = pd.DataFrame(np.arange(16).reshape((4,4)),index=['red','blue','yellow','white'],columns=['ball','pen','pencil','paper']) frame Out[55]: ball pen pencil paper red 0 1 2 3 blue 4 5 6 7 yellow 8 9 10 11 white 12 13 14 15 In [56]: frame.sort_index(axis=1) Out[56]: ball paper pen pencil red 0 3 1 2 blue 4 7 5 6 yellow 8 11 9 10 white 12 15 13 14 In [66]: frame.sort_index(by=['pen','paper']) D:ProgramDataAnaconda3libsite-packagesipykernel_launcher.py:1: FutureWarning: by argument to sort_index is deprecated, pls use .sort_values(by=...) """Entry point for launching an IPython kernel. Out[66]: ball pen pencil paper red 0 1 2 3 blue 4 5 6 7 yellow 8 9 10 11 white 12 13 14 15 In [67]: ser.rank() Out[67]: red 4.0 blue 1.0 yellow 2.0 whiite 5.0 green 3.0 dtype: float64 In [68]: ser.rank(method='first') Out[68]: red 4.0 blue 1.0 yellow 2.0 whiite 5.0 green 3.0 dtype: float64 In [69]: ser.rank(ascending=False) Out[69]: red 2.0 blue 5.0 yellow 4.0 whiite 1.0 green 3.0 dtype: float64