I'm trying to convert a netCDF file to either a CSV or text file using Python. I have read this post but I am still missing a step (I'm new to Python). It's a dataset including latitude, longitude, time and precipitation data.
This is my code so far:
import netCDF4
import pandas as pd
precip_nc_file = 'file_path'
nc = netCDF4.Dataset(precip_nc_file, mode='r')
nc.variables.keys()
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
time_var = nc.variables['time']
dtime = netCDF4.num2date(time_var[:],time_var.units)
precip = nc.variables['precip'][:]
I am not sure how to proceed from here, though I understand it's a matter of creating a dataframe with pandas.
I think pandas.Series
should work for you to create a CSV with time, lat,lon,precip.
import netCDF4
import pandas as pd
precip_nc_file = 'file_path'
nc = netCDF4.Dataset(precip_nc_file, mode='r')
nc.variables.keys()
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
time_var = nc.variables['time']
dtime = netCDF4.num2date(time_var[:],time_var.units)
precip = nc.variables['precip'][:]
# a pandas.Series designed for time series of a 2D lat,lon grid
precip_ts = pd.Series(precip, index=dtime)
precip_ts.to_csv('precip.csv',index=True, header=True)
Depending on your requirements, you may be able to use Numpy's savetxt
method:
import numpy as np
np.savetxt('lat.csv', lat, delimiter=',')
np.savetxt('lon.csv', lon, delimiter=',')
np.savetxt('precip.csv', precip, delimiter=',')
This will output the data without any headings or index column, however.
If you do need those features, you can construct a DataFrame and save it as CSV as follows:
df_lat = pd.DataFrame(data=lat, index=dtime)
df_lat.to_csv('lat.csv')
# and the same for `lon` and `precip`.
Note: here, I assume that the date/time index runs along the first dimension of the data.
import xarray as xr
nc = xr.open_dataset('file_path')
nc.precip.to_dataframe().to_csv('precip.csv')