CODEWITHSUNDEEP
pythonpandasdataframecsvdictionary
user14551647
user14551647

Reputation:

pandas for python creates multiple index columns when saving df in csv

When I iterate this code over, pandas keeps creating new index columns in my csv.

import pandas as pd

credentials = pd.read_csv("credentials.csv")

email = "[email protected]"
nick = "jarda"
passw = "heslo"
csfd_conf_link = "test.link"

dict_to_append = {"nick": nick, "pass": passw, "email": email, "conf_link": csfd_conf_link}

credentials_updated = credentials.append(dict_to_append, ignore_index=True)
credentials_updated.to_csv("credentials.csv")

So it ends up looking like this this (better visible in the screenshot):

   Unnamed: 0  Unnamed: 0.1  ...                         email                                          conf_link
0           0           0.0  ...                [email protected]                                               test
1           1           1.0  ...                 [email protected]                                               test
2           2           2.0  ...  [email protected]  https://www.csfd.cz/potvrzeni/registration/?co...
3           3           3.0  ...                [email protected]                                          test.link
4           4           4.0  ...                [email protected]                                          test.link
5           5           5.0  ...                [email protected]                                          test.link
6           6           NaN  ...                [email protected]                                          test.link

I know that indexing can be turned of with credentials_updated.to_csv("credentials.csv", index=False). However, what if I wanted to have the columns indexed? Any help would be appreciated. Thanks.

Upvotes: 0

Views: 541

Answers (1)

Cameron Riddell
Cameron Riddell

Reputation: 13417

If you want to keep the Index roundtrip, you can specify index_col in your call to pd.read_csv, and keep index=True in your call to to_csv:

import pandas as pd

try:
    credentials = pd.read_csv("credentials.csv", index_col=0)
except FileNotFoundError:
    credentials = pd.DataFrame()
...

credentials_updated.to_csv("credentials.csv")

The try/except will help you out if you delete your "credentials.csv" for whatever reason.

Upvotes: 1

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