expand表示是否把series类型转化为DataFrame类型

下面代码中的ｎ表示去掉下划线"_"的数量

代码如下：

import numpy as npimport pandas as pds2 = pd.Series(['a_b_c_f_j', 'c_d_e_f_h', np.nan, 'f_g_h_x_g'])print("-----------------------------------")print(s2.str.split('_'))print("-----------------------------------")print(s2.str.split('_').str.get(1))print("-----------------------------------")print(s2.str.split('_').str[1])print("---------------expand=True--------------------")expand1=s2.str.split('_', expand=True)print(expand1)print(type(expand1))print("---------------expand=False--------------------")expand2=s2.str.split('_', expand=False)print(expand2)print(type(expand２))print("##########################################################")print("---------------expand=True,n=1--------------------")expand1=s2.str.rsplit('_', expand=True,n=1)print(expand1)print("---------------expand=False,n=1--------------------")expand2=s2.str.rsplit('_', expand=False,n=1)print(expand2)

运行结果如下：

-----------------------------------0 [a, b, c, f, j]1 [c, d, e, f, h]2 NaN3 [f, g, h, x, g]dtype: object-----------------------------------0 b1 d2 NaN3 gdtype: object-----------------------------------0 b1 d2 NaN3 gdtype: object---------------expand=True-------------------- 0 1 2 3 40 a b c f j1 c d e f h2 NaN NaN NaN NaN NaN3 f g h x g<class 'pandas.core.frame.DataFrame'>---------------expand=False--------------------0 [a, b, c, f, j]1 [c, d, e, f, h]2 NaN3 [f, g, h, x, g]dtype: object<class 'pandas.core.series.Series'>##########################################################---------------expand=True,n=1-------------------- 0 10 a_b_c_f j1 c_d_e_f h2 NaN NaN3 f_g_h_x g---------------expand=False,n=1--------------------0 [a_b_c_f, j]1 [c_d_e_f, h]2 NaN3 [f_g_h_x, g]dtype: object[Finished in 0.4s]

以上这篇基于pandas中expand的作用详解就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。