🔒 reading csv in jupyter gets rid of datetimeindex

[vestal edge]

i used thios short python script to concatonate and save a new csv with the idnex beeing a datetime dtype:

df['ts']= pd.to_datetime(df['ts'])
df=df.set_index(df['ts'])
df=df.drop(columns=['ts'])
df.index = df.index.tz_convert('Europe/Berlin')

df.to_csv('C:\\Privat\\Python_VSC\\Spotify\\MyData_2025\\Data_concat.csv')

in the json's the ts column was given in UTC. (i concatonated the Json's into a csv.

Now i tried opening the new File in a jupyter notebook only to get that response:

df.index.dtype

[clever hatch]

@vestal edge

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[vestal edge]

but trying to run ```
df.index= pd.to_datetime(df.index)

 returns the following
ValueError: Array must be all same time zone

and that makes sense, cause wehn looking at the value_counts of teh idnex we see different conversions,. which i dont understanmd what they mean...

[vestal edge]

i am referring to the +01:00 and +02:00 here

2021-01-06T19:04:34Z Time Stamps in the originall .json ahve been looking like that

[cedar gazelle]

that difference (+01, +02) looks like daylight savings?

I'd just save as UTC instead

[cedar gazelle]

try using df.index= pd.to_datetime(df.index, utc=True), if you need to keep it in Berlin then maybe use .tz_convert('Europe/Berlin') again afterwards

[clever hatch]

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