Python Pandas：如果字符串值列表== [无]，则从数据框中删除行

Amal Nasir 发表于 Dev

阿玛尔·纳西尔（Amal Nasir）|

我的数据框中有一个包含值列表的列。

 Tags
 [marvel, comics, comic, books, nerdy]
 [new, snapchat, version, snap, inc]
 [none]
 [new, york, times, ny, times, nyt, times]
 [today, show, today, show, today]
 [none]
 [mark, wahlberg, marky, mark]

我不知道如何从数据框中删除此[none]列表。我试过了，

 us_videos = us_videos.drop(us_videos.index[us_videos.tags == 'none'])

但这仅在将列转换为字符串时有效。如何实现呢？

海盗

新答案

OP希望'none'从子列表中删除并仅删除行'none'

us_videos.tags.explode().pipe(lambda s: s[s != 'none']).groupby(level=0).agg(list)

0        [marvel, comics, comic, books, nerdy]
1          [new, snapchat, version, snap, inc]
3    [new, york, times, ny, times, nyt, times]
4            [today, show, today, show, today]
6                [mark, wahlberg, marky, mark]
Name: tags, dtype: object

更加Python化的方式

dat = {}
for k, v in us_videos.tags.iteritems():
    for x in v:
        if x != 'none':
            dat.setdefault(k, []).append(x)

pd.Series(dat, name='tags')

0        [marvel, comics, comic, books, nerdy]
1          [new, snapchat, version, snap, inc]
3    [new, york, times, ny, times, nyt, times]
4            [today, show, today, show, today]
6                [mark, wahlberg, marky, mark]
Name: tags, dtype: object

具有赋值表达式的理解

pd.Series({
    k: X for k, v in us_videos.tags.iteritems()
    if (X:=[*filter('none'.__ne__, v)])
}, name='tags')

0        [marvel, comics, comic, books, nerdy]
1          [new, snapchat, version, snap, inc]
3    [new, york, times, ny, times, nyt, times]
4            [today, show, today, show, today]
6                [mark, wahlberg, marky, mark]
Name: tags, dtype: object

老答案

`explode`

us_videos[us_videos.tags.explode().ne('none').any(level=0)]

                                        tags
0      [marvel, comics, comic, books, nerdy]
1        [new, snapchat, version, snap, inc]
3  [new, york, times, ny, times, nyt, times]
4          [today, show, today, show, today]
6              [mark, wahlberg, marky, mark]

`list.ne`

us_videos[us_videos.tags.map(['none'].__ne__)]

                                        tags
0      [marvel, comics, comic, books, nerdy]
1        [new, snapchat, version, snap, inc]
3  [new, york, times, ny, times, nyt, times]
4          [today, show, today, show, today]
6              [mark, wahlberg, marky, mark]

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