**http://www.ceda.ac.uk/static/media/uploads/ncas-reading-2015/10_read_netcdf_python.pdf

**https://www.youtube.com/watch?v=xu7FAYnwGTc

You need to show some code for us to be able to help you. How are you calling the functions using netcdf4? Show a snippet of your code.

• My code is below :

import numpy as np

from netCDF4 import Dataset

nc = Dataset('F:\\Research\\Data\\World wide monthly rainfall data\\precip.mon.total.2.5x2.5.v6.nc','r')

for i in nc.variables:

print(i, nc.variables[i].units, nc.variables[i].shape)

d = np.array(nc.variables['precip'], dtype=type(nc.variables))

print(d[:,23.75,91.25])

• Output :

lat degrees_north (72,)

lon degrees_east (144,)

time days since 1800-1-1 00:00:00 (1320,)

precip mm (1320, 72, 144)

[-9.96921e+36 -9.96921e+36 -9.96921e+36 ..., -9.96921e+36 -9.96921e+36 -9.96921e+36]

"print(d[:,23.75,91.25])"

From my experience you can not specify the longitude and latitude values directly in the array. You need integer values that represent these values. You can get the integer values from your lat and lon variables. (Maybe this is a poor man's solutions and there is a more elegant way to solve it, but at least this works for me.)

Thanks, Daniel Kunkel. I have already try integer values like below :

print(d[:,71,143])

But, the result is same :

[-9.96921e+36 -9.96921e+36 -9.96921e+36 ..., -9.96921e+36 -9.96921e+36 -9.96921e+36]

Did you build the package with OPeNDAP?:

"Remote OPeNDAP-hosted datasets can be accessed for reading over http if a URL is provided to the Dataset constructor instead of a filename. However, this requires that the netCDF library be built with OPenDAP support, via the --enable-dap configure option (added in version 4.0.1)."

may be that is the issue. Also make sure that the format is correct or try different formats in the Dataset constructor.

Also check this http://schubert.atmos.colostate.edu/~cslocum/netcdf_example.html#code code to see if it helps.

Cheers

I once had problems with a netcdf4/hdf5 file which I could only access properly with the h5py package for hdf files. Usually, I use scipy for netcdf files. 

Thanks, everyone. I have solved it.

Could you share how did you resolve it?

My main problem was in the data calling system. I was always calling by lat, lon value (Example: d[:,23.75,91.25]). But, calling by index is the main calling format for this  (Daniel Kunkel mention it previous comment). Funny to say, when I called by index, result remained the same since all my index had null values coincidentally. Therefore, the result showed -9.96921e+36, which means 0.

I need precipitation values for 23.75, 91.25 (lat, lon). of which having index 26, 36 respectively. So, when I call by index like d[:,26,36]). The result is fine and similar to ArcGIS result.

My ultimate code is below :

import numpy as np

from netCDF4 import Dataset

nc = Dataset('F:\\Research\\Data\\World wide monthly rainfall data\\precip.mon.total.2.5x2.5.v6.nc','r')

for i in nc.variables:

print(i, nc.variables[i].units, nc.variables[i].shape)

d = np.array(nc.variables['precip'], dtype=type(nc.variables))

print(d[:, 26, 36])

Hi

You can easily extract your time series and save to excel text csv and json file

Http:\\www.AgriMetSoft.com

Thanks Topper. But, I already solve this problem.

Hi

By Netcdf-Extractor you can merge many nc files and extract from all times in all files once

https://agrimetsoft.com/Netcdf-Extractor.aspx

http://netcdf-extractor.com/

Thanks. But, "This site can’t be reached"

Hi

I've corrected it again

www.agrimetsoft.com

Please try it again.

Regards,

Nasrin

I used this for netcdf that comes from WRF

import numpy as np

from netCDF4 import Dataset # http://code.google.com/p/netcdf4-python/

import pandas as pd

import os

f = Dataset('wrfout_d01_2007-01-01_10_00_00', 'r') # Read es para leer

latbounds = [ 4.691417 ]# Punctual values

lonbounds = [ -74.209 ] # degrees east ? # Valores límites

cor_lat = pd.DataFrame(f.variables['XLAT'][0][:])

cor_lat2 = pd.DataFrame({'a':cor_lat.iloc[:,0], 'b':abs(cor_lat.iloc[:,0] - latbounds)})

a = cor_lat2[cor_lat2.b == min(cor_lat2.b)].index.get_values()[0]

cor_lon = pd.DataFrame(f.variables['XLONG'][0][:])

cor_lon2 = pd.DataFrame({'a':cor_lon.iloc[0,:], 'b':abs(cor_lon.iloc[0,:] - lonbounds)})

b = cor_lon2[cor_lon2.b == min(cor_lon2.b)].index.get_values()[0]

vlr = (f.variables['T2'][ : , a , b ] - 273.15)[0]

vlr#This is the result

**http://www.ceda.ac.uk/static/media/uploads/ncas-reading-2015/10_read_netcdf_python.pdf

**https://www.youtube.com/watch?v=xu7FAYnwGTc

http://www.ceda.ac.uk/static/media/uploads/ncas-reading-2015/10_read_netcdf_python.pdf

https://stackoverflow.com/questions/45582344/extracting-data-from-netcdf-by-python

https://www.youtube.com/watch?v=d6diNBEDPfM

https://geosci.uchicago.edu/~rtp1/itr/PythonLectures/ReadWriteNC.html

Nasrin Salehnia is it free software?

You use this link

https://stackoverflow.com/questions/45582344/extracting-data-from-netcdf-by-python

Ismail Mondal, thanks.

Hi I use this code in order to read nc files and extract information about some locations and specific period of time:

##################################################

from netCDF4 import Dataset

import numpy as np

from netCDF4 import num2date

import os

import conda

###############################################################

# Import libraries

conda_file_dir = conda.__file__

conda_dir = conda_file_dir.split('lib')[0]

proj_lib = os.path.join(os.path.join(conda_dir, 'share'), 'proj')

os.environ["PROJ_LIB"] = proj_lib

import os

os.environ['PROJ_LIB'] = r'C:\Users\USER\Anaconda3\pkgs\proj4-5.2.0-ha925a31_1\Library\share'

from mpl_toolkits.basemap import Basemap

import matplotlib.pyplot as plt

import matplotlib.dates as mdates

from matplotlib.dates import MonthLocator,WeekdayLocator,DateFormatter

import pandas as pd

# Read the nc file#

ncfile='psl_day_ACCESS1-0_historical_r1i1p1_18500101-18741231.nc'

file = Dataset(ncfile,mode='r') # abrir el archivo en modo lectura

print(file.variables)

lon=file.variables["lon"][:]

lat=file.variables["lat"][:]

nc_time= file.variables["time"][:]

t_unit= file.variables["time"].units

psl= file.variables["psl"][:]

###########################################

try :

t_cal= file.variables['time'].calendar

except AttributeError:

t_cal=u"gregorian"

try :

t_cal=file.variables['time'].calendar

except AttributeError:

t_cal=u"gregorian"

################################################

# Convert numbers to actual dates

datevar=num2date(nc_time[:],units=t_unit,calendar=t_cal)

print(datevar)

# algun filtro de tiempo por ejemplo

# Filter by years

years=np.array([idx.year for idx in datevar])

idx_time=(years>=1850)*(years=1)*(meses=5)*(lat=85)*(lon

I had same problem before and I found the solution in YouTube

you can use this link: https://www.youtube.com/watch?v=hrm5RmsVXo0

It may help you.

Hi, this depends on the dimensions of your variable.

For example, the T2 from WRF output is function of (Time, south_north, west_east)

so you need to import the Dataset from netcdf4 and read the netcdf file

df = Dataset('path_to_your_file', mode='r')

after this, you need to specify the time range, the row number and the column number, like this:

T2 = df.variables['T2'][0, 30,30]

in the commad above I am extracting the T2 from the netcdf file at the first hour of the data (0), at row 30 and column 30.

you also can extract the entire matrix for one hour using this:

T2 = df.variables['T2'][0, :,:]

in this case you will the 2D array with the data at time 0 of the netcdf file.

Thus, it depends on the dimensions of you variables. There variables which are in function of Times, vertical level, row, col... in this case, you also need to specify which vertical level you want to get the information.

Regards

Dear Manjurul,

Please follow the link below for extracting data from netcdf files for a particular location as well as multiple locations, using PYTHON.

https://www.youtube.com/watch?v=M1rXwFZyzC4&t=2271s&ab_channel=GeoDeltaLabs

https://www.youtube.com/watch?v=FzMQs8oTS3Q&t=3s&ab_channel=GeoDeltaLabs

Meanwhile use this to make your data extraction easy using pandas library and xarray module.

THIS WORKS 100%. TRY THIS.

****

import xarray as xr

import pandas as pd

df = xr.open_dataset('< paste the link to the file and its name>')[''][:].to_dataframe()

print(df)

******

Once the data from netcdf file is converted to pandas dataframe, you can extract the data as you want.

Hope this will be highly helpful for anyone who wants to extract the data from netcdf files from any source.

Use CDO or NCO or you can find prewritten codes for Matlab and python in Github

Hi everyone, if someone is interested to extract netcdf files using Google Colab here is my solution using 5 steps:

1) Mount virtual machine

from google.colab import drive

import os

drive.mount('/content/gdrive')

2) Connecting to the drive

import os

print(os.getcwd())

os.chdir("/content/gdrive/My Drive")

print(os.getcwd())

3) Install the following libraries

!apt-get install -q libgeos-3.5.0

!apt-get install -q libgeos-dev

!pip install -q https://github.com/matplotlib/basemap/archive/master.zip !pip install -q pyproj==1.9.6 !pip install netcdf4

4) Import packages

from netCDF4 import Dataset

import numpy as np

from netCDF4 import num2date

import os

#import conda

from mpl_toolkits.basemap import Basemap

import matplotlib.pyplot as plt

import matplotlib.dates as mdates

from matplotlib.dates import MonthLocator,WeekdayLocator,DateFormatter

import pandas as pd

5) Load your netcdf file and extract the dimensions:

# Read the netcdf file###

ncfile='/content/gdrive/My Drive/TAS/HISTORICAL/tas_Amon_ACCESS1-0_historical_r1i1p1_185001-200512.nc'

file = Dataset(ncfile,mode='r') # read the file

print(file.variables)

lon=file.variables["lon"][:] # extract longitude

lat=file.variables["lat"][:] # extract latitude

nc_time= file.variables["time"][:] # Extract time

t_unit= file.variables["time"].units # extract time units

tas= file.variables["tas"][:] # extract the variable of interest

###########################################

try :

    t_cal= file.variables['time'].calendar

except AttributeError:

    t_cal=u"gregorian"

try :

    t_cal=file.variables['time'].calendar

except AttributeError:

    t_cal=u"gregorian"

################################################  

My nc file has 8 variables (longitude, latitude, time, u10, v10, swh, mwd, mwp) and the logic I'm trying is "If I input longitude and latitude, my program outputs other variables (u10, v10, swh, mwd, mwp) ordered by time." Then I would put the extracted data in another database.

I tested my nc file as below:

import netCDF4 from netCDF4 import Dataset jan = Dataset('2016_01.nc') print jan.variables.keys() lon = jan.variables['longitude'] lat = jan.variables['latitude'] time = jan.variables['time'] for d in jan.dimensions.items(): print d lon_array = lon[:] lat_array = lat[:] time_array = time[:] print lon_array print lat_array print time_array

and some of the result is below

[u'longitude', u'latitude', u'time', u'u10', u'v10', u'swh', u'mwd', u'mwp'] (u'longitude', : name = 'longitude', size = 1440) (u'latitude', : name = 'latitude', size = 721) (u'time', (unlimited): name = 'time', size = 186)

Kamal Asghar could you please add your NC file, so that I can send the required code.

Dear Kamal Asghar

Please have look to this channel in youtube , it helped me to extract rainfall from netcdf files

https://www.youtube.com/watch?v=ue55Mxe4yVQ&list=PLLxyyob7YmEE8S3QDs1PZQkiBxA4zn_Gx

please follow all the parts

good lucks

Mohammed