问题
I have a problem with the type of one of my column in a pandas dataframe. Basically the column is saved in a csv file as a string, and I wanna use it as a tuple to be able to convert it in a list of numbers. Following there is a very simple csv:
ID,LABELS
1,"(1.0,2.0,2.0,3.0,3.0,1.0,4.0)"
2,"(1.0,2.0,2.0,3.0,3.0,1.0,4.0)"
If a load it with the function "read_csv" I get a list of strings. I have tried to convert to a list, but I get the list version of a string:
df.LABELS.apply(lambda x: list(x))
returns:
['(','1','.','0',.,.,.,.,.,'4','.','0',')']
Any idea on how to be able to do it?
Thank you.
回答1:
You can use ast.literal_eval
, which will give you a tuple:
import ast
df.LABELS = df.LABELS.apply(ast.literal_eval)
If you do want a list, use:
df.LABELS.apply(lambda s: list(ast.literal_eval(s)))
回答2:
Use str.strip and str.split:
df['LABELS'] = df['LABELS'].str.strip('()').str.split(',')
But if no NaN
s here, list comprehension
working nice too:
df['LABELS'] = [x.strip('()').split(',') for x in df['LABELS']]
回答3:
You can try this (assuming your csv
is called filename.csv
):
df = pd.read_csv('filename.csv')
df['LABELS'] = df.LABELS.apply(lambda x: x.strip('()').split(','))
>>> df
ID LABELS
0 1 [1.0, 2.0, 2.0, 3.0, 3.0, 1.0, 4.0]
1 2 [1.0, 2.0, 2.0, 3.0, 3.0, 1.0, 4.0]
来源:https://stackoverflow.com/questions/50278300/convert-a-columns-of-string-to-list-in-pandas