Question

我正在使用数据框中的Twitter数据。我想根据在文本中找到的某个关键字过滤保存每个推文文本的列。

我已经尝试过str.contains，但是那行不通，因为该列是Series。我想为所有包含关键字“ remoaners”的推文过滤“文本”列。

remoaners_only = time_plus_text[time_plus_text["text"].str.contains("remoaners", case=False, na=False)]

这将产生一个空的数据框或许多NaN。

熊猫版本为0.24.1。

以下是输入数据：time_plus_text [“ text”]。head（10）


0    [ #bbcqt Remoaners on about post Brexit racial...
1    [@sarahwollaston Shut up, you like all remoane...
2    [ what have the Brextremists ever done for us ...
3                     [ Remoaner in bizarre outburst ]
4    [ Anyone who disagrees with brexit is called n...
5    [ @SkyNewsBreak They forecasted if the vote wa...
6    [ but we ARE LEAVING THE #EU, even the #TORIES...
7    [ Can unelected Remoaner peers not see how abs...
8    [@sizjam68 @LeaveEUOfficial @johnredwood It wo...
9    [ Hey @BBC have you explained why when award w...
Name: text, dtype: object

Answer 1

您的代码有效。因此，您需要检查输入数据或熊猫错误修复版本0.24.1与0.24.2。

0.24.2
   index                                               text
0      0     [ #bbcqt Remoaners on about post Brexit rac...

import pandas as pd
import sys
if sys.version_info[0] < 3: 
    from StringIO import StringIO
else:
    from io import StringIO

print(pd.__version__)

csvdata = StringIO("""0,   [ #bbcqt Remoaners on about post Brexit racial...
1,   [@sarahwollaston Shut up, you like all remoane...
2,   [ what have the Brextremists ever done for us ...
3,                    [ Remoaner in bizarre outburst ]
4,   [ Anyone who disagrees with brexit is called n...
5,   [ @SkyNewsBreak They forecasted if the vote wa...
6,   [ but we ARE LEAVING THE #EU, even the #TORIES...
7,   [ Can unelected Remoaner peers not see how abs...
8,   [@sizjam68 @LeaveEUOfficial @johnredwood It wo...
9,   [ Hey @BBC have you explained why when award w...""")

df = pd.read_csv(csvdata, names=["index", "text"], sep=",")

result = df[df["text"].str.contains("remoaners", case=False, na=False)]

# results
print(result)

Answer 2

问题是，您要在其中查找子字符串remoaners的字符串包含在每个单元格的list中。您需要先执行str[0]来访问此字符串，然后再执行str.contains，例如：

# input
time_plus_text = pd.DataFrame({'text':[['#bbcqt Remoaners on about post Brexit racial...'], 
                                       ['@sarahwollaston Shut up, you like all remoaners...'],
                                       ['what have the Brextremists ever done for us ...']]})
print (time_plus_text["text"].str[0].str.contains("remoaners", case=False, na=False))
0     True
1     True
2    False
Name: text, dtype: bool

所以您应该这样做：

remoaners_only = time_plus_text[time_plus_text["text"].str[0]\
                                             .str.contains("remoaners", case=False, na=False)]

通过在文本块中查找关键字来过滤数据框

2 个答案: