Question

有没有办法在任何列中查询包含某个字符串的行的DataFrame？像Series.str这样的东西除了DataFrame？这是我到目前为止所做的：

In [2]: s = "Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est"

In [3]: df = pd.DataFrame(np.array(s.split(' ')).reshape((-1, 4)), columns=['one', 'two', 'three', 'four'])

In [4]: df
Out[4]: 
           one            two         three        four
0        Lorem          ipsum         dolor         sit
1        amet,    consectetur   adipisicing       elit,
2          sed             do       eiusmod      tempor
3   incididunt             ut        labore          et
4       dolore          magna       aliqua.          Ut
5         enim             ad         minim     veniam,
6         quis        nostrud  exercitation     ullamco
7      laboris           nisi            ut     aliquip
8           ex             ea       commodo  consequat.
9         Duis           aute         irure       dolor
10          in  reprehenderit            in   voluptate
11       velit           esse        cillum      dolore
12          eu         fugiat         nulla   pariatur.
13   Excepteur           sint      occaecat   cupidatat
14         non      proident,          sunt          in
15       culpa            qui       officia    deserunt
16      mollit           anim            id         est

[17 rows x 4 columns]

In [5]: mask = df['one'].str.contains('dolor') | df['two'].str.contains('dolor') | df['three'].str.contains('dolor') | df['four'].str.contains('dolor')

In [6]: df[mask]
Out[6]: 
       one    two    three    four
0    Lorem  ipsum    dolor     sit
4   dolore  magna  aliqua.      Ut
9     Duis   aute    irure   dolor
11   velit   esse   cillum  dolore

[4 rows x 4 columns]

理想情况下，我想用类似的东西替换最后两行：

df[df.ix[:, 'one':'four'].str.contains('dolor')]

这可能吗？

Answer 1

您可以使用pd.np.char.array()：

的矢量化操作

a = pd.np.char.array(df.values)
mask = a.find('dolor')!=-1
df2 = df.iloc[np.any(mask, axis=1)]

，df2的内容将是：

       one    two    three    four
0    Lorem  ipsum    dolor     sit
4   dolore  magna  aliqua.      Ut
9     Duis   aute    irure   dolor
11   velit   esse   cillum  dolore

Answer 2

Pandas没有DataFrame.str方法（至少目前还没有）。但是，您可以使用

import numpy as np
mask = np.logical_or.reduce(
    [df[col].str.contains('dolor') 
     for col in df.loc[:, 'one':'four'].columns])

这比写作少一点，比

快一点

mask = df['one'].str.contains('dolor') | df['two'].str.contains('dolor') | df['three'].str.contains('dolor') | df['four'].str.contains('dolor')

In [29]: %timeit mask = np.logical_or.reduce([df[col].str.contains('dolor') for col in df.loc[:, 'one':'four'].columns]); df[mask]
1000 loops, best of 3: 761 µs per loop

In [30]: %timeit mask = df['one'].str.contains('dolor') | df['two'].str.contains('dolor') | df['three'].str.contains('dolor') | df['four'].str.contains('dolor'); df[mask]
1000 loops, best of 3: 1.13 ms per loop

Answer 3

如果theres＆＃39; dolor＆＃39;这将为您提供信息。在任何一栏中：

df.ix[:, 'one':'four'].apply(lambda x: x.str.contains('dolor'), axis=1)

将为任何列的每一行提供true / false值

如果您将此项与另一项申请相结合，您将获得总列数的信息

df.ix[:, 'one':'four'].apply(lambda x: x.str.contains('dolor'), axis=1).apply(lambda x: True in x.values, axis=1)

并使用它作为列掩码将给出结果：

df[df.ix[:, 'one':'four'].apply(lambda x: x.str.contains('dolor'), axis=1).apply(lambda x: True in x.values, axis=1)]

然而，这大约慢了3-4倍:(那是unutbu解决方案。

多列pandas矢量化字符串函数？

3 个答案: