How Do I Change Data-type Of Pandas Data Frame To String With A Defined Format?

I'm starting to tear my hair out with this - so I hope someone can help. I have a pandas DataFrame that was created from an Excel spreadsheet using openpyxl. The resulting DataFram

Solution 1:

I'm unable to reproduce your problem but have you tried converting it to an integer first?

image_name_data['id'] = image_name_data['id'].astype(int).astype('str')

Then, regarding your more general question you could use map (as in this answer). In your case:

image_name_data['id'] = image_name_data['id'].map('{:.0f}'.format)

Solution 2:

If you could reload this, you might be able to use dtypes argument.

pd.read_csv(..., dtype={'COL_NAME':'str'})

Solution 3:

I'm putting this in a new answer because no linebreaks / codeblocks in comments. I assume you want those nans to turn into a blank string? I couldn't find a nice way to do this, only do the ugly method:

s = pd.Series([1001.,1002.,None])
a = s.loc[s.isnull()].fillna('')
b = s.loc[s.notnull()].astype(int).astype(str)
result = pd.concat([a,b])