In [114]: df Out[114]: A B C D 2018-06-30 0.318501 0.613145 0.485612 0.918663 2018-07-31 0.614796 0.711491 0.503203 0.170298 2018-08-31 0.530939 0.173830 0.264867 0.181273 2018-09-30 0.009428 0.622133 0.933908 0.813617 2018-10-31 0.126368 0.981736 0.358643 0.904409 2018-11-30 0.747830 0.294678 0.427755 0.803732 2018-12-31 0.549106 0.225865 0.530107 0.590769 2019-01-31 0.371511 0.191638 0.267706 0.279762 In [115]: df.ix[[2,5],[‘B‘,‘C‘]] Out[115]: B C 2018-08-31 0.173830 0.264867 2018-11-30 0.294678 0.427755
loc:通过行标签索引数据
In [116]: df.loc[‘2018-06-30‘] Out[116]: A 0.318501 B 0.613145 C 0.485612 D 0.918663 Name: 2018-06-30 00:00:00, dtype: float64
iloc:通过行号索引行数据
In [118]: df.iloc[0] Out[118]: A 0.318501 B 0.613145 C 0.485612 D 0.918663 Name: 2018-06-30 00:00:00, dtype: float64
ix:通过行标签或行号索引数据(基于loc和iloc的混合)
原文地址:https://www.cnblogs.com/jycjy/p/9134741.html
时间: 2024-11-15 06:50:42