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.
To install with anaconda (conda) simply type conda install netCDF4 . Alternatively, you can install with pip . To be sure your netCDF4 module is properly installed start an interactive session in the terminal (type python and press 'Enter'). Then import netCDF4 as nc .
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)
import xarray as xr
nc = xr.open_dataset('file_path')
nc.precip.to_dataframe().to_csv('precip.csv')
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