从pandas DataFrame中的文本中提取子字符串作为新列 [英] Extract substring from text in a pandas DataFrame as new column
问题描述
我下面有一个要计算的单词"列表
I have a list of 'words' I want to count below
word_list = ['one','three']
我在pandas数据框中有一列,下面是文本.
And I have a column within pandas dataframe with text below.
TEXT |
-------------------------------------------|
"Perhaps she'll be the one for me." |
"Is it two or one?" |
"Mayhaps it be three afterall..." |
"Three times and it's a charm." |
"One fish, two fish, red fish, blue fish." |
"There's only one cat in the hat." |
"One does not simply code into pandas." |
"Two nights later..." |
"Quoth the Raven... nevermore." |
所需的输出如下所示,其中保留了原始文本列,但仅将word_list中的单词提取到了新列中
The desired output is the following below, where it keeps the original text column, but only extracted the words in word_list to a new column
TEXT | EXTRACT
-------------------------------------------|---------------
"Perhaps she'll be the one for me." | one
"Is it two or one?" | one
"Mayhaps it be three afterall..." | three
"Three times and it's a charm." | three
"One fish, two fish, red fish, blue fish." | one
"There's only one cat in the hat." | one
"One does not simply code into pandas." | one
"Two nights later..." |
"Quoth the Raven... nevermore." |
在python 2.7中有没有办法做到这一点?
Is there a way to do this in Python 2.7?
推荐答案
使用str.extract
:
df['EXTRACT'] = df.TEXT.str.extract('({})'.format('|'.join(word_list)),
flags=re.IGNORECASE, expand=False).str.lower().fillna('')
df['EXTRACT']
0 one
1 one
2 three
3 three
4 one
5 one
6 one
7
8
Name: EXTRACT, dtype: object
word_list
中的每个单词都由正则表达式分隔符|
连接,然后传递给str.extract
以进行正则表达式模式匹配.
Each word in word_list
is joined by the regex separator |
and then passed to str.extract
for regex pattern matching.
re.IGNORECASE
开关已打开,以进行不区分大小写的比较,并且将结果匹配项转换为小写形式以与您的预期输出匹配.
The re.IGNORECASE
switch is turned on for case-insensitive comparisons, and the resultant matches are lowercased to match with your expected output.
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