How to create a dataframe of one index of a dataset?

Question

I have a dataset NearGrid with dimensions (index:225, time:25933) that contains daily temperature data for 225 locations. How can I create a dataframe for the first location (index=0) where the columns are date and tmax and each row represents one day of data (i.e. 25933 rows x 2 columns)?

Here's what I'm trying:

#import libraries
import os
import matplotlib.pyplot as plt
from netCDF4 import Dataset as netcdf_dataset
import numpy as np
from cartopy import config
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import xarray as xr
import pandas as pd

#open netcdf files
df=xr.open_mfdataset('/glacier1/mmartin/data/NOAATmax/Tmax****.nc')

#open cm stations csv and create new dataset with only points closest to stations in CMStations
CMStations=pd.read_csv('Slope95.csv')
Lat=CMStations.lat
Lon=CMStations.lon
NearGrid=df.sel(lat=Lat.to_xarray(), lon=Lon.to_xarray(), method='nearest')

#create dataframe of first location in NearGrid
NearGrid.isel(index=0).to_dataframe()

but when I do this the code runs indefinitely and nothing happens.

Answer 1

The problem was the way the data was chunked. When I saved the subsetted data as a new netcdf file and then opened it in a new notebook, it worked. I did that through this:

#import libraries
import os
import matplotlib.pyplot as plt
from netCDF4 import Dataset as netcdf_dataset
import numpy as np
from cartopy import config
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import xarray as xr
import pandas as pd

#open netcdf files
df=xr.open_mfdataset('/glacier1/mmartin/data/NOAATmax/Tmax****.nc')

#open cm stations csv and create new dataset with only points closest to stations in CMStations
CMStations=pd.read_csv('Slope95.csv')
Lat=CMStations.lat
Lon=CMStations.lon
NearGrid=df.sel(lat=Lat.to_xarray(), lon=Lon.to_xarray(), method='nearest')

#save as new netcdf file
NearGrid.to_netcdf('/glacier1/mmartin/data/NOAATmax/Tmax_CMStations_19510101-20211231.nc')

I then opened this file in a new notebook and manipulated the data there