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I have a problem converting a Xarray dataset into a Pandas dataframe. The thing is that when I convert into a pd dataframe, pandas don't see the right amount of columns. During the conversion I switch from 5 columns (lat, lon, time, sst, time_bnds) to only 2 columns.

Here is my code

PATH = os.path.join (DIR, 'sst.mnmean.nc')
data=xr.open_dataset(PATH)

I'm not able to copy paste the result so here is a screenshot

data_pd = data.to_dataframe(dim_order=None)

Here is the result in pandas dataframe

As you can see pandas sees only 2 columns even though there are 6 variables.

I was expecting to see the 5 exact same columns in my pandas dataframe, which is not the case. To be clear, I just want to work with sst variable (sea surface temperature) and time bnds which is the timestamp

(I know that coordinates are considered as index, I tried reset_index() but it doesn't work)

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  • This is a bit hard for us to debug without more info. Ideally, you could post a full minimal reproducible example but at least could you copy and paste the results of print(data) and print(data_pd) into your question as a text block? Commented Nov 7, 2022 at 1:25
  • Sorry, i just edited the post. I hope it's clearer Commented Nov 7, 2022 at 8:48
  • You can copy the result of print(ds) - it’s a string. Please fully upload images of data/code/logs/etc Commented Nov 7, 2022 at 15:35
  • reset_index does work, but it's not an inplace operation, so try data_pd = data_pd.reset_index(). the other variables are just in the index - they're not columns. Commented Nov 8, 2022 at 6:42
  • Does this answer your question? Pandas reset index is not taking effect Commented Nov 8, 2022 at 6:43
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