I have dataframe (df3) with 266 rows which looks like below. The label columns list items are of type int.
| Id | label |
|---|---|
| 4cfab | [0,0,1,1] |
| 924cf | [0,0,1,1] |
| 916b8 | [316.0,318.0] |
| 0f549 | [0,0,1,1] |
| db696 | [345.0,39.0,9] |
I want the result like below:
| Id | label |
|---|---|
| 4cfab | ['0', '0', '1','1'] |
| 924cf | ['0', '0', '1','1'] |
| 916b8 | ['316.0','318.0'] |
| 0f549 | ['0', '0', '1','1'] |
| db696 | ['45.0','39.0','9'] |
I've tried the following but it didn't work:
df3['label'] = [str(i) for x in df3['label'] for i in x]
CodePudding user response：
You can use the pandas.Series.map method to broadcast a function over each element of the series. In this case, each element is a list. So for each list, we want to map the function str over each element of the list.
df3['label'] = df3.label.map(lambda x: list(map(str, x)))
CodePudding user response：
You can try as a list comprehension within a map():
df3['label'] = df3['label'].map(lambda x: [str(y) for y in x])
CodePudding user response：
You can try using apply() to add the quotation marks. The for loop in the lambda function loops through all the values within the lists in the df3['label'] column.
df3['label'] = df3['label'].apply(lambda x: ["'" str(i) "'" for i in range(len(x))])