Check if a string in a Pandas DataFrame column is in a list of strings
pandas, python, python-2.7
Solution
frame = pd.DataFrame({'a' : ['the cat is blue', 'the sky is green', 'the dog is black']})
frame
a
0 the cat is blue
1 the sky is green
2 the dog is black
The `str.contains` method accepts a regular expression pattern:
mylist = ['dog', 'cat', 'fish']
pattern = '|'.join(mylist)
pattern
'dog|cat|fish'
frame.a.str.contains(pattern)
0 True
1 False
2 True
Name: a, dtype: bool
Because regex patterns are supported, you can also embed flags:
frame = pd.DataFrame({'a' : ['Cat Mr. Nibbles is blue', 'the sky is green', 'the dog is black']})
frame
a
0 Cat Mr. Nibbles is blue
1 the sky is green
2 the dog is black
pattern = '|'.join([f'(?i){animal}' for animal in mylist]) # python 3.6+
pattern
'(?i)dog|(?i)cat|(?i)fish'
frame.a.str.contains(pattern)
0 True # Because of the (?i) flag, 'Cat' is also matched to 'cat'
1 False
2 True
Problem
If I have a frame like this ``` frame = pd.DataFrame({ "a": ["the cat is blue", "the sky is green", "the dog is black"] }) ``` and I want to check if any of those rows contain a certain word I just have to do this. ``` frame["b"] = ( frame.a.str.contains("dog") | frame.a.str.contains("cat") | frame.a.str.contains("fish") ) ``` `frame["b"]` outputs: ``` 0 True 1 False 2 True Name: b, dtype: bool ``` If I decide to make a list: ``` mylist = ["dog", "cat", "fish"] ``` How would I check that the rows contain a certain word in the list?