Python Pandas：如果字符串值列表 == [none]，则从数据框中删除行

Question

我的数据框中有一列包含值列表。

 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这个 [none] 列表。我试过了，

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

但这只有在我将列转换为字符串时才有效。如何实现？

Answer 1

首先让我们编写一个函数来删除列表中的 'none':

print(df)

    tags
0   [marvel, comics, comic, books, nerdy]
1   [new, snapchat, version, snap, inc]
2   [none]
3   [new, york, times, ny, times, nyt, times]
4   [today, show, today, show, today, none]


def delete_none(element):
    new = []
    for val in element:
        if val != 'none':
            new.append(val)
    if len(new) == 0:
        return np.nan
    else:
        return new

现在我们将这个函数应用于 tags 列：

df.tags.apply(delete_none)

输出：

0         [marvel, comics, comic, books, nerdy]
1           [new, snapchat, version, snap, inc]
2                                           NaN
3    [new, york, times, ny, times, nyt,  times]
4             [today, show, today, show, today]

Answer 2

新答案

OP 想从子列表中删除 'none' 并删除只有 'none'

的行

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

更像 pythonic 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

理解中有赋值表达式

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

旧答案

`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]

Python Pandas：如果字符串值列表 == [none]，则从数据框中删除行

Python Pandas: Drop rows from data frame if list of string value == [none]

python

pandas

data-preprocessing

新答案

旧答案

`explode`

`list.ne`

Python Pandas：如果字符串值列表 == [none]，则从数据框中删除行

Python Pandas: Drop rows from data frame if list of string value == [none]

python

pandas

data-preprocessing

新答案

旧答案

explode

list.__ne__

`explode`

`list.ne`