Python/Pandas 返回找到的字符串的列和行索引
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/45042005/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Python/Pandas return column and row index of found string
提问by codeninja
I've searched previous answers relating to this but those answers seem to utilize numpy because the array contains numbers. I am trying to search for a keyword in a sentence in a dataframe ('Timeframe') where the full sentence is 'Timeframe for wave in ____' and would like to return the column and row index. For example:
我已经搜索了与此相关的先前答案，但这些答案似乎使用了 numpy，因为数组包含数字。我正在尝试在数据帧（“时间帧”）中的句子中搜索关键字，其中完整的句子是“____中的波浪时间帧”，并希望返回列和行索引。例如：
df.iloc[34,0]
returns the string I am looking for but I am avoiding a hard code for dynamic reasons. Is there a way to return the [34,0] when I search the dataframe for the keyword 'Timeframe'
返回我正在寻找的字符串，但由于动态原因我避免使用硬代码。当我在数据帧中搜索关键字“Timeframe”时，有没有办法返回 [34,0]
回答by jezrael
EDIT:
编辑：
For check index need containswith boolean indexing, but then there are possible 3 values:
对于检查索引需要contains使用boolean indexing，但可能有 3 个值：
df = pd.DataFrame({'A':['Timeframe for wave in ____', 'a', 'c']})
print (df)
A
0 Timeframe for wave in ____
1 a
2 c
def check(val):
a = df.index[df['A'].str.contains(val)]
if a.empty:
return 'not found'
elif len(a) > 1:
return a.tolist()
else:
#only one value - return scalar
return a.item()
print (check('Timeframe'))
0
print (check('a'))
[0, 1]
print (check('rr'))
not found
Old solution:
旧解决方案：
It seems you need if need numpy.wherefor check value Timeframe:
如果需要numpy.where检查值，您似乎需要Timeframe：
df = pd.DataFrame({'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,'Timeframe'],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')})
print (df)
A B C D E F
0 a 4 7 1 5 a
1 b 5 8 3 3 a
2 c 4 9 5 6 a
3 d 5 4 7 9 b
4 e 5 2 1 2 b
5 f 4 Timeframe 0 4 b
a = np.where(df.values == 'Timeframe')
print (a)
(array([5], dtype=int64), array([2], dtype=int64))
b = [x[0] for x in a]
print (b)
[5, 2]
回答by Cedric Zoppolo
In case you have multiple columns where to look into you can use following code example:
如果您有多个要查看的列，可以使用以下代码示例：
import numpy as np
import pandas as pd
df = pd.DataFrame([[1,2,3,4],["a","b","Timeframe for wave in____","d"],[5,6,7,8]])
mask = np.column_stack([df[col].str.contains("Timeframe", na=False) for col in df])
find_result = np.where(mask==True)
result = [find_result[0][0], find_result[1][0]]
Then output for dfand resultwould be:
然后输出dfandresult将是：
>>> df
0 1 2 3
0 1 2 3 4
1 a b Timeframe for wave in____ d
2 5 6 7 8
>>> result
[1, 2]
