Trying to open a series of netCDF files with using OpenDAPError while accessing NOAA CO-OPS ocean model nowcast on IDVImporting and decoding dataset in xarray to avoid conflicting _FillValue and missing_valueViewing specific dates in a time-series of netCDF mapsPython xarray.concat then xarray.to_netcdf generates huge new file sizeHow to open multiple NetCDF files with xarray via OpenDAP?Why are NaNs introduced into dimension variable when loading a netcdf file into xarray datasetxarray automatically applying _FillValue to coordinates on netCDF output[Errno -101] NetCDF: HDF error when opening netcdf fileProblems reopening netcdf file written with xarray/dasktrouble looping xarray dataframe through subdirectories
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Trying to open a series of netCDF files with using OpenDAP
Error while accessing NOAA CO-OPS ocean model nowcast on IDVImporting and decoding dataset in xarray to avoid conflicting _FillValue and missing_valueViewing specific dates in a time-series of netCDF mapsPython xarray.concat then xarray.to_netcdf generates huge new file sizeHow to open multiple NetCDF files with xarray via OpenDAP?Why are NaNs introduced into dimension variable when loading a netcdf file into xarray datasetxarray automatically applying _FillValue to coordinates on netCDF output[Errno -101] NetCDF: HDF error when opening netcdf fileProblems reopening netcdf file written with xarray/dasktrouble looping xarray dataframe through subdirectories
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;
I want to open all the data from 1950-2005 using xarray and open_mfdataset.
https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/catalog.html
This is what I have done so far:
source=https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.years.nc
files = [source for years in range(1950,2005,1)]
ds=xr.open_mfdataset(files)
print(ds)
However, I cannot seem to get my list interpreted to be read into the variable years within source.
Any ideas?
Thank you in advance.
EDIT:
path = 'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
print(files)
nc = netCDF4.MFDataset(files)
This is the code I am using. When I try to open up these files I get an error:
OSError: [Errno -90] NetCDF: file not found: b'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.1948.nc'
Did I not enter the path correctly?
dask netcdf python-xarray noaa
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
add a comment |
I want to open all the data from 1950-2005 using xarray and open_mfdataset.
https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/catalog.html
This is what I have done so far:
source=https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.years.nc
files = [source for years in range(1950,2005,1)]
ds=xr.open_mfdataset(files)
print(ds)
However, I cannot seem to get my list interpreted to be read into the variable years within source.
Any ideas?
Thank you in advance.
EDIT:
path = 'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
print(files)
nc = netCDF4.MFDataset(files)
This is the code I am using. When I try to open up these files I get an error:
OSError: [Errno -90] NetCDF: file not found: b'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.1948.nc'
Did I not enter the path correctly?
dask netcdf python-xarray noaa
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
add a comment |
I want to open all the data from 1950-2005 using xarray and open_mfdataset.
https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/catalog.html
This is what I have done so far:
source=https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.years.nc
files = [source for years in range(1950,2005,1)]
ds=xr.open_mfdataset(files)
print(ds)
However, I cannot seem to get my list interpreted to be read into the variable years within source.
Any ideas?
Thank you in advance.
EDIT:
path = 'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
print(files)
nc = netCDF4.MFDataset(files)
This is the code I am using. When I try to open up these files I get an error:
OSError: [Errno -90] NetCDF: file not found: b'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.1948.nc'
Did I not enter the path correctly?
dask netcdf python-xarray noaa
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
I want to open all the data from 1950-2005 using xarray and open_mfdataset.
https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/catalog.html
This is what I have done so far:
source=https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.years.nc
files = [source for years in range(1950,2005,1)]
ds=xr.open_mfdataset(files)
print(ds)
However, I cannot seem to get my list interpreted to be read into the variable years within source.
Any ideas?
Thank you in advance.
EDIT:
path = 'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
print(files)
nc = netCDF4.MFDataset(files)
This is the code I am using. When I try to open up these files I get an error:
OSError: [Errno -90] NetCDF: file not found: b'https://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/ncep.reanalysis/surface/air.sig995.1948.nc'
Did I not enter the path correctly?
dask netcdf python-xarray noaa
dask netcdf python-xarray noaa
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
edited Mar 25 at 20:37
Jeff Coldplume
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
asked Mar 25 at 0:14
Jeff ColdplumeJeff Coldplume
175
175
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
All files are named air.sig995.YYYY.nc, so you need something like:
files = ['air.sig995.0:04d.nc'.format(years) for years in range(1950,2005,1)]
Which produces:
In [2]: files
Out[2]:
['air.sig995.1950.nc',
'air.sig995.1951.nc',
'air.sig995.1952.nc',
'air.sig995.1953.nc',
.....
You can also easily include a (remote) path here (if required):
path = '/some/file/path'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
See https://pyformat.info/ for more information on string formatting in Python.
answered Mar 25 at 13:02
BartBart
5,04842244
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could usexr.auto_combine.
– mdurant
Mar 25 at 20:36
add a comment |
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1 Answer
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oldest
votes
All files are named air.sig995.YYYY.nc, so you need something like:
files = ['air.sig995.0:04d.nc'.format(years) for years in range(1950,2005,1)]
Which produces:
In [2]: files
Out[2]:
['air.sig995.1950.nc',
'air.sig995.1951.nc',
'air.sig995.1952.nc',
'air.sig995.1953.nc',
.....
You can also easily include a (remote) path here (if required):
path = '/some/file/path'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
See https://pyformat.info/ for more information on string formatting in Python.
answered Mar 25 at 13:02
BartBart
5,04842244
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could usexr.auto_combine.
– mdurant
Mar 25 at 20:36
add a comment |
All files are named air.sig995.YYYY.nc, so you need something like:
files = ['air.sig995.0:04d.nc'.format(years) for years in range(1950,2005,1)]
Which produces:
In [2]: files
Out[2]:
['air.sig995.1950.nc',
'air.sig995.1951.nc',
'air.sig995.1952.nc',
'air.sig995.1953.nc',
.....
You can also easily include a (remote) path here (if required):
path = '/some/file/path'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
See https://pyformat.info/ for more information on string formatting in Python.
answered Mar 25 at 13:02
BartBart
5,04842244
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could usexr.auto_combine.
– mdurant
Mar 25 at 20:36
add a comment |
All files are named air.sig995.YYYY.nc, so you need something like:
files = ['air.sig995.0:04d.nc'.format(years) for years in range(1950,2005,1)]
Which produces:
In [2]: files
Out[2]:
['air.sig995.1950.nc',
'air.sig995.1951.nc',
'air.sig995.1952.nc',
'air.sig995.1953.nc',
.....
You can also easily include a (remote) path here (if required):
path = '/some/file/path'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
See https://pyformat.info/ for more information on string formatting in Python.
answered Mar 25 at 13:02
BartBart
5,04842244
All files are named air.sig995.YYYY.nc, so you need something like:
files = ['air.sig995.0:04d.nc'.format(years) for years in range(1950,2005,1)]
Which produces:
In [2]: files
Out[2]:
['air.sig995.1950.nc',
'air.sig995.1951.nc',
'air.sig995.1952.nc',
'air.sig995.1953.nc',
.....
You can also easily include a (remote) path here (if required):
path = '/some/file/path'
files = ['0/air.sig995.1:04d.nc'.format(path, years) for years in range(1950,2005,1)]
See https://pyformat.info/ for more information on string formatting in Python.
answered Mar 25 at 13:02
BartBart
5,04842244
answered Mar 25 at 13:02
BartBart
5,04842244
answered Mar 25 at 13:02
BartBart
5,04842244
answered Mar 25 at 13:02
BartBart
5,04842244
5,04842244
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could usexr.auto_combine.
– mdurant
Mar 25 at 20:36
add a comment |
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could usexr.auto_combine.
– mdurant
Mar 25 at 20:36
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
This is what I was looking for. I was unsure how to reference the dates as a variable within the remote path. What would be the best way to combine these into one continuous time series? Maybe xarray?
– Jeff Coldplume
Mar 25 at 20:00
Exactly xarray. You could use
xr.auto_combine.– mdurant
Mar 25 at 20:36
Exactly xarray. You could use
xr.auto_combine.– mdurant
Mar 25 at 20:36
add a comment |
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