拆分＆amp;在熊猫中移动细胞

Question

我的pandas DataFrame有点问题。

如图所示，第一行的released_date为“已发布的2006”，而同一列的所有其他值的格式为“已发布的MMM DD”。

我想将released_date下的第一个单元格拆分为“已发布”和“2006”，将“2006”复制到年级列，然后将所有内容移动一列。有任何想法吗？

当前格式：

...|**released_date**| **year** | **genre**  | ...
...| Released   2006 | Arcade   |    Comic   |...

所需的输出格式：

...|**released_date**| **year** | **genre**  | ...
...|    Released     |     2006 |     Arcade |...

提前致谢!!

以下是用于读取文件的代码：

import pandas as pd
df = pd.read_csv("IndieGameCSV/page_1.csv", \
    names=["Windows","Mac","Linux","engine","release_date","year","genre1",\
           "theme","players","score_final","rating", "link" ], index_col=False)

以下是图片中显示的数据：

True, False, True,Custom Built,Released 2006,Arcade,Comic,Single Player,                     10,1 v, http://indiedb.com/games/tux-climber,
True, True, True,Custom Built,Released Oct 20, 2014,Role Playing,Fantasy,MMO,                     7.3,45 , http://indiedb.com/games/pokemon-planet,
True, True, True,Ren'py,Released May 16, 2015,Turn Based Strategy,Noire,Single Player,                     9,1 v, http://indiedb.com/games/black-closet,
True, True, False,ShiVa3D,Released Jan 2, 2015,First Person Shooter,Sci-Fi,Single Player,                     7.8,4 v, http://indiedb.com/games/kumoon,

Answer 1

您可以使用str.extract方法提取年份：

In [11]: df["release_date"].str.extract("(\d{4})")
Out[11]:
0    2006
1    2014
2    2015
3    2015
Name: "release_date", dtype: object

如果您想要拆分DataFrame，还可以查看.str.match，以检查列是否与正则表达式匹配：

In [12]: df["release_date"].str.match("Released \d{4}")
Out[12]:
0     True
1    False
2    False
3    False
Name: "release_date", dtype: bool

用这个和〜这个索引df。