DataFrame的基本操作
1，选择
(1),Select column
In [11]: df[‘a‘] Out[11]: 0 -1.355263 1 0.010888 2 1.599583 3 0.004565 4 0.460270 Name: a, dtype: float64
In [15]: df.loc[1] Out[15]: a 0.010888 b -0.900427 c -0.397198 Name: 1, dtype: float64
(3) Select row by integer location
In [19]: df.iloc[1] Out[19]: a 0.010888 b -0.900427 c -0.397198 Name: 1, dtype: float64
In [24]: df[1:3] Out[24]: a b c 1 0.010888 -0.900427 -0.397198 2 1.599583 0.662713 0.943103
(5) Select rows by boolean vector
In [27]: df[df[‘a‘]>0.5] Out[27]: a b c 2 1.599583 0.662713 0.943103
2,删除
In [28]: del df[‘a‘] In [29]: df Out[29]: b c 0 1.451534 -0.497793 1 -0.900427 -0.397198 2 0.662713 0.943103 3 -0.505622 1.156941 4 0.333584 -1.260798
In [32]: df.pop(‘b‘) Out[32]: 0 1.451534 1 -0.900427 2 0.662713 3 -0.505622 4 0.333584 Name: b, dtype: float64 In [33]: df Out[33]: c 0 -0.497793 1 -0.397198 2 0.943103 3 1.156941 4 -1.260798
In [35]: df[‘e‘]=[‘e‘,‘w‘,‘t‘,‘e‘,‘d‘] In [36]: df Out[36]: c e 0 -0.497793 e 1 -0.397198 w 2 0.943103 t 3 1.156941 e 4 -1.260798 d
原文：http://www.cnblogs.com/sklww/p/3813006.html