Pandas read_csv dtype=object column contains numbers

Question

I have a DataFrame column with alphanumeric IDs - some numbers, some letters, some both. I am using read_csv to read the data and want to read all the values of this column as strings. I can't change the values in the underlying data.

I have tried to set the dtype for the column as an object

df = pd.read_csv(filename, dtype = {col: object})

I have also tried to use a converter to change all the values in the columns to strings.

df = pd.read_csv(filename, converters = {i: str for i in col})

However, I still end up with some non-string numbers (12345) and some string numbers ('12345') which mess up my aggregations.

Any suggestions? Thanks!

Answer 1

您也可以尝试：

df['column'] = df['column'].apply(lambda x: str(x))

Answer 2

Use:

df = pd.read_csv(filename, dtype = {i: str for i in col})

The only difference from this and the first one is I do dtype not converter , it's basically a merge of the two.