From 6163f32d94aecc5875f6320d39c3f00b9fa2564a Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Thu, 16 Mar 2023 22:36:40 +0530 Subject: [PATCH 01/18] @TomNicholas please look into the changes. --- doc/getting-started-guide/faq.rst | 93 +++++++++++++++++++++++++++++++ 1 file changed, 93 insertions(+) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 0eeb09c432c..dd349e4cb0f 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -185,6 +185,99 @@ What other projects leverage xarray? ------------------------------------ See section :ref:`ecosystem`. + +How do I open format X file as an xarray.Dataset? +------------------------------------------------- + +To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides links to the functions for different file formats in xarray, as well as links to other packages that can be used: + +.. csv-table:: + :header: "File Format", "xarray Backend", " Other Packages" + :widths: 15, 35, 15 + + "NetCDF (.nc, .nc4, .cdf)","xarray.open_dataset() OR xarray.open_mfdataset()", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" + "HDF5 (.h5, .hdf5)","xarray.open_dataset() OR xarray.open_mfdataset()", "`h5py `_, `pytables `_ " + "GRIB (.grb, .grib)", "xarray.open_dataset()", "`cfgrib `_, `pygrib `_" + "CSV (.csv)","xarray.open_dataset()
xarray.open_mfdataset()","`_pandas `_ , `dask `_ " + "JSON (.json)","xarray.open_dataset()","`json `_, `.pandas `_" + +To use these backend functions in xarray, you can simply call them with the path to the file(s) you want to read as an argument. + +NetCDF +------ +Use xarray.open_dataset() to open a NetCDF file and return an xarray Dataset object. + + .. code:: python + + import xarray as xr + + # Use forward slashes(/), while mentioning the file location + # use xarray to open the file and return an xarray.Dataset object + ds = xr.open_dataset('/path/to/my/file.nc', engine='netcdf4') + + # Print Dataset object + print(ds) + +HDF5 +---- +Use xarray.open_dataset() to open an HDF5 file and return an xarray.Dataset object. + +.. code:: python + + import h5netcdf + import xarray as xr + + # Open HDF5 file as an xarray Dataset + ds = xr.open_dataset('path/to/hdf5/file.hdf5', engine='h5netcdf') + + # Print Dataset object + print(ds) + + +We recommend you to install h5netcdf library using + +.. code:: python + + pip install h5netcdf + +GRIB +----------- +use the xarray.open_dataset() function from the cfgrib package to open a GRIB file as an xarray Dataset. + +.. code:: python + + import xarray as xr + + # define the path to your GRIB file and the engine you want to use to open the file + # use xr.open_dataset to open the file with the specified engine and return an xarray.Dataset object + ds = xr.open_dataset('path/to/your/file.grib', engine='cfgrib') + + # Print Dataset object + print(ds) + +We recommend installing cfgrib via conda: +.. code:: python + + conda install -c conda-forge cfgrib + +CSV +--- +.. code:: python + + import xarray as xr + import + as pd + + # Load CSV file into pandas DataFrame using the "c" engine + df = pd.read_csv('your_file.csv', engine='c') + + # Convert pandas DataFrame to xarray.Dataset + ds = xr.Dataset.from_dataframe(df) + + #Prints the resulting xarray dataset + print(ds) + +Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. How should I cite xarray? ------------------------- From 0d18d56e763154eb1e1dcd0934309446fe40aa11 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Mon, 20 Mar 2023 22:59:52 +0530 Subject: [PATCH 02/18] commit 1 --- doc/getting-started-guide/faq.rst | 115 ++++++++++++++++++++++++++++++ 1 file changed, 115 insertions(+) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 0eeb09c432c..7fa071cb8fe 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -186,6 +186,121 @@ What other projects leverage xarray? See section :ref:`ecosystem`. +How do I open format X file as an xarray dataset? +------------------------------------------------- + +To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides functions used for different file formats in xarray, as well as links to other packages that can be used: + +.. csv-table:: + :header: "File Format", "xarray Backend", " Other Packages" + :widths: 15, 45, 15 + + "NetCDF (.nc, .nc4, .cdf)","``open_dataset()`` OR ``open_mfdataset()``", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" + "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " + "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" + "CSV (.csv)","``open_dataset()``", "`_pandas `_ , `dask `_" + +To use these backend functions in xarray, you can call them with the path to the file(s) you want to read as an argument. + +Xarray provides a default engine to read files, which is usually determined by the file extension or type. If you don't specify the engine, xarray will try to guess it based on the file extension or type, and may fall back to a different engine if it cannot determine the correct one. + +Therefore, it's good practice to always specify the engine explicitly, especially when working with complex data formats or non-standard file extensions. So, specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. + +For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: + +NetCDF +------ +If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. + +Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. + +.. code:: python + + import xarray as xr + + # Use forward slashes(/), while mentioning the file location + # use xarray to open the file and return an xarray.Dataset object + ds = xr.open_dataset('/path/to/my/file.nc', engine='netcdf4') + + # Print Dataset object + print(ds) + +HDF5 +---- +Use ``open_dataset()`` to open an HDF5 file and return an xarray.Dataset object. +You should specify the `engine` keyword argument when reading HDF5 files with xarray, as there are multiple backends that can be used to read HDF5 files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. + +To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: + +.. code:: python + + import h5netcdf + import xarray as xr + + # Open HDF5 file as an xarray Dataset + ds = xr.open_dataset('path/to/hdf5/file.hdf5', engine='h5netcdf') + + # Print Dataset object + print(ds) + +We recommend you to install `h5netcdf` library using + +.. code:: python + + pip install h5netcdf + +If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: + +.. code:: python + + ds = xr.open_dataset('path/to/file.h5', engine='netcdf4') + +GRIB +----------- +You should specify the `engine` keyword argument when reading GRIB files with xarray, as there are multiple backends that can be used to read GRIB files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. + +Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. + +.. code:: python + + import xarray as xr + + # define the path to your GRIB file and the engine you want to use to open the file + # use ``open_dataset()`` to open the file with the specified engine and return an xarray.Dataset object + ds = xr.open_dataset('path/to/your/file.grib', engine='cfgrib') + + # Print Dataset object + print(ds) + +We recommend installing `cfgrib` via conda: + +.. code:: python + + conda install -c conda-forge cfgrib + +CSV +--- +By default, xarray uses the built-in `pandas` library to read CSV files. In general, you don't need to specify the engine keyword argument when reading CSV files with xarray, as the default `pandas` engine is usually sufficient for most use cases. If you are working with very large CSV files or if you need to perform certain types of data processing that are not supported by the default `pandas` engine, you may want to use a different backend. +In such cases, you can specify the engine argument when reading the CSV file with xarray. + +To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: + +.. code:: python + + import xarray as xr + import pandas as pd + + # Load CSV file into `:py:func:pandas` DataFrame using the "c" engine + df = pd.read_csv('your_file.csv', engine='c') + + # Convert `:py:func:pandas` DataFrame to xarray.Dataset + ds = xr.Dataset.from_dataframe(df) + + #Prints the resulting xarray dataset + print(ds) + +Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. + How should I cite xarray? ------------------------- From ae572bb65e782980edfae689a1ddfe5fbc3634b5 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Mon, 20 Mar 2023 23:09:03 +0530 Subject: [PATCH 03/18] @TomNicholas please review --- doc/getting-started-guide/faq.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 7fa071cb8fe..68f460be40c 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -194,7 +194,7 @@ To open format X file in xarray, you need to know the `format of the data `_, `netcdf `_ , `cdms2 `_" "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" From 035b55d0d9a6f1fd1046656d29a9af34e2d67514 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Mon, 20 Mar 2023 23:15:00 +0530 Subject: [PATCH 04/18] @TomNicholas please review --- doc/getting-started-guide/faq.rst | 66 ++++++++++++++++++++----------- 1 file changed, 44 insertions(+), 22 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 519f79f2e67..b1ff54e2362 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -186,28 +186,35 @@ What other projects leverage xarray? See section :ref:`ecosystem`. -How do I open format X file as an xarray.Dataset? +How do I open format X file as an xarray dataset? ------------------------------------------------- -To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides links to the functions for different file formats in xarray, as well as links to other packages that can be used: +To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides functions used for different file formats in xarray, as well as links to other packages that can be used: .. csv-table:: :header: "File Format", "xarray Backend", " Other Packages" - :widths: 15, 35, 15 + :widths: 15, 45, 15 + + "NetCDF (.nc, .nc4, .cdf)","``open_dataset()`` OR ``open_mfdataset()``", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" + "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " + "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" + "CSV (.csv)","``open_dataset()``", "`_pandas `_ , `dask `_" + +To use these backend functions in xarray, you can call them with the path to the file(s) you want to read as an argument. - "NetCDF (.nc, .nc4, .cdf)","xarray.open_dataset() OR xarray.open_mfdataset()", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" - "HDF5 (.h5, .hdf5)","xarray.open_dataset() OR xarray.open_mfdataset()", "`h5py `_, `pytables `_ " - "GRIB (.grb, .grib)", "xarray.open_dataset()", "`cfgrib `_, `pygrib `_" - "CSV (.csv)","xarray.open_dataset()
xarray.open_mfdataset()","`_pandas `_ , `dask `_ " - "JSON (.json)","xarray.open_dataset()","`json `_, `.pandas `_" +Xarray provides a default engine to read files, which is usually determined by the file extension or type. If you don't specify the engine, xarray will try to guess it based on the file extension or type, and may fall back to a different engine if it cannot determine the correct one. -To use these backend functions in xarray, you can simply call them with the path to the file(s) you want to read as an argument. +Therefore, it's good practice to always specify the engine explicitly, especially when working with complex data formats or non-standard file extensions. So, specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. + +For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: NetCDF ------ -Use xarray.open_dataset() to open a NetCDF file and return an xarray Dataset object. +If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. - .. code:: python +Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. + +.. code:: python import xarray as xr @@ -220,7 +227,10 @@ Use xarray.open_dataset() to open a NetCDF file and return an xarray Dataset obj HDF5 ---- -Use xarray.open_dataset() to open an HDF5 file and return an xarray.Dataset object. +Use ``open_dataset()`` to open an HDF5 file and return an xarray.Dataset object. +You should specify the `engine` keyword argument when reading HDF5 files with xarray, as there are multiple backends that can be used to read HDF5 files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. + +To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: .. code:: python @@ -233,45 +243,57 @@ Use xarray.open_dataset() to open an HDF5 file and return an xarray.Dataset obje # Print Dataset object print(ds) - -We recommend you to install h5netcdf library using +We recommend you to install `h5netcdf` library using .. code:: python pip install h5netcdf +If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: + +.. code:: python + + ds = xr.open_dataset('path/to/file.h5', engine='netcdf4') + GRIB ----------- -use the xarray.open_dataset() function from the cfgrib package to open a GRIB file as an xarray Dataset. +You should specify the `engine` keyword argument when reading GRIB files with xarray, as there are multiple backends that can be used to read GRIB files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. + +Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. .. code:: python import xarray as xr # define the path to your GRIB file and the engine you want to use to open the file - # use xr.open_dataset to open the file with the specified engine and return an xarray.Dataset object + # use ``open_dataset()`` to open the file with the specified engine and return an xarray.Dataset object ds = xr.open_dataset('path/to/your/file.grib', engine='cfgrib') # Print Dataset object print(ds) -We recommend installing cfgrib via conda: +We recommend installing `cfgrib` via conda: + .. code:: python conda install -c conda-forge cfgrib CSV --- +By default, xarray uses the built-in `pandas` library to read CSV files. In general, you don't need to specify the engine keyword argument when reading CSV files with xarray, as the default `pandas` engine is usually sufficient for most use cases. If you are working with very large CSV files or if you need to perform certain types of data processing that are not supported by the default `pandas` engine, you may want to use a different backend. +In such cases, you can specify the engine argument when reading the CSV file with xarray. + +To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: + .. code:: python import xarray as xr - import - as pd - - # Load CSV file into pandas DataFrame using the "c" engine + import pandas as pd + + # Load CSV file into `:py:func:pandas` DataFrame using the "c" engine df = pd.read_csv('your_file.csv', engine='c') - # Convert pandas DataFrame to xarray.Dataset + # Convert `:py:func:pandas` DataFrame to xarray.Dataset ds = xr.Dataset.from_dataframe(df) #Prints the resulting xarray dataset From a436bdaab648acdcd871e597f79b85429dc49d3f Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Tue, 21 Mar 2023 06:21:21 +0530 Subject: [PATCH 05/18] latest commit --- doc/getting-started-guide/faq.rst | 115 ------------------------------ 1 file changed, 115 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index b1ff54e2362..3218a91d88b 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -301,121 +301,6 @@ To read CSV files with xarray, use the `open_dataset()` function and specify the Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. -How do I open format X file as an xarray dataset? -------------------------------------------------- - -To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides functions used for different file formats in xarray, as well as links to other packages that can be used: - -.. csv-table:: - :header: "File Format", "xarray Backend", " Other Packages" - :widths: 15, 45, 15 -=== - "NetCDF (.nc, .nc4, .cdf)","``open_dataset()`` OR ``open_mfdataset()``", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" - "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " - "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" - "CSV (.csv)","``open_dataset()``", "`_pandas `_ , `dask `_" - -To use these backend functions in xarray, you can call them with the path to the file(s) you want to read as an argument. - -Xarray provides a default engine to read files, which is usually determined by the file extension or type. If you don't specify the engine, xarray will try to guess it based on the file extension or type, and may fall back to a different engine if it cannot determine the correct one. - -Therefore, it's good practice to always specify the engine explicitly, especially when working with complex data formats or non-standard file extensions. So, specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. - -For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: - -NetCDF ------- -If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. - -Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. - -.. code:: python - - import xarray as xr - - # Use forward slashes(/), while mentioning the file location - # use xarray to open the file and return an xarray.Dataset object - ds = xr.open_dataset('/path/to/my/file.nc', engine='netcdf4') - - # Print Dataset object - print(ds) - -HDF5 ----- -Use ``open_dataset()`` to open an HDF5 file and return an xarray.Dataset object. -You should specify the `engine` keyword argument when reading HDF5 files with xarray, as there are multiple backends that can be used to read HDF5 files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. - -To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: - -.. code:: python - - import h5netcdf - import xarray as xr - - # Open HDF5 file as an xarray Dataset - ds = xr.open_dataset('path/to/hdf5/file.hdf5', engine='h5netcdf') - - # Print Dataset object - print(ds) - -We recommend you to install `h5netcdf` library using - -.. code:: python - - pip install h5netcdf - -If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: - -.. code:: python - - ds = xr.open_dataset('path/to/file.h5', engine='netcdf4') - -GRIB ------------ -You should specify the `engine` keyword argument when reading GRIB files with xarray, as there are multiple backends that can be used to read GRIB files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. - -Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. - -.. code:: python - - import xarray as xr - - # define the path to your GRIB file and the engine you want to use to open the file - # use ``open_dataset()`` to open the file with the specified engine and return an xarray.Dataset object - ds = xr.open_dataset('path/to/your/file.grib', engine='cfgrib') - - # Print Dataset object - print(ds) - -We recommend installing `cfgrib` via conda: - -.. code:: python - - conda install -c conda-forge cfgrib - -CSV ---- -By default, xarray uses the built-in `pandas` library to read CSV files. In general, you don't need to specify the engine keyword argument when reading CSV files with xarray, as the default `pandas` engine is usually sufficient for most use cases. If you are working with very large CSV files or if you need to perform certain types of data processing that are not supported by the default `pandas` engine, you may want to use a different backend. -In such cases, you can specify the engine argument when reading the CSV file with xarray. - -To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: - -.. code:: python - - import xarray as xr - import pandas as pd - - # Load CSV file into `:py:func:pandas` DataFrame using the "c" engine - df = pd.read_csv('your_file.csv', engine='c') - - # Convert `:py:func:pandas` DataFrame to xarray.Dataset - ds = xr.Dataset.from_dataframe(df) - - #Prints the resulting xarray dataset - print(ds) - -Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. - How should I cite xarray? ------------------------- From b7bbceae0bd78f1a5def5b5d92c6a16e345dd9b1 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Tue, 21 Mar 2023 07:49:34 +0530 Subject: [PATCH 06/18] Changes done on formatting the code --- doc/getting-started-guide/faq.rst | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 3218a91d88b..f9b2cedc161 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -218,11 +218,12 @@ Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object import xarray as xr - # Use forward slashes(/), while mentioning the file location # use xarray to open the file and return an xarray.Dataset object + ds = xr.open_dataset('/path/to/my/file.nc', engine='netcdf4') # Print Dataset object + print(ds) HDF5 @@ -238,14 +239,16 @@ To read HDF5 files with xarray, you can use the ``open_dataset()`` function from import xarray as xr # Open HDF5 file as an xarray Dataset + ds = xr.open_dataset('path/to/hdf5/file.hdf5', engine='h5netcdf') # Print Dataset object + print(ds) We recommend you to install `h5netcdf` library using -.. code:: python +.. code:: pip install h5netcdf @@ -267,9 +270,11 @@ Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB fil # define the path to your GRIB file and the engine you want to use to open the file # use ``open_dataset()`` to open the file with the specified engine and return an xarray.Dataset object + ds = xr.open_dataset('path/to/your/file.grib', engine='cfgrib') # Print Dataset object + print(ds) We recommend installing `cfgrib` via conda: @@ -291,12 +296,15 @@ To read CSV files with xarray, use the `open_dataset()` function and specify the import pandas as pd # Load CSV file into `:py:func:pandas` DataFrame using the "c" engine + df = pd.read_csv('your_file.csv', engine='c') # Convert `:py:func:pandas` DataFrame to xarray.Dataset + ds = xr.Dataset.from_dataframe(df) #Prints the resulting xarray dataset + print(ds) Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. From 6d2573e112bb76892ced2f3c5a5e6da8c564ef7d Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Tue, 21 Mar 2023 07:54:09 +0530 Subject: [PATCH 07/18] pre-commit bot changes --- doc/getting-started-guide/faq.rst | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index f9b2cedc161..8c9e5a1c437 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -214,7 +214,7 @@ If you are reading a netCDF file with a ".nc" extension, the default engine is ` Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. -.. code:: python +.. code:: import xarray as xr @@ -233,7 +233,7 @@ You should specify the `engine` keyword argument when reading HDF5 files with xa To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: -.. code:: python +.. code:: import h5netcdf import xarray as xr @@ -254,7 +254,7 @@ We recommend you to install `h5netcdf` library using If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: -.. code:: python +.. code:: ds = xr.open_dataset('path/to/file.h5', engine='netcdf4') @@ -264,7 +264,7 @@ You should specify the `engine` keyword argument when reading GRIB files with xa Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. -.. code:: python +.. code:: import xarray as xr @@ -279,7 +279,7 @@ Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB fil We recommend installing `cfgrib` via conda: -.. code:: python +.. code:: conda install -c conda-forge cfgrib @@ -290,7 +290,7 @@ In such cases, you can specify the engine argument when reading the CSV file wit To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: -.. code:: python +.. code:: import xarray as xr import pandas as pd From 0e3e23f5c8f8c43c8baa9de6cceb6fbd3d936f43 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Tue, 21 Mar 2023 08:23:01 +0530 Subject: [PATCH 08/18] code changes --- doc/getting-started-guide/faq.rst | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 8c9e5a1c437..38dbf005f65 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -214,7 +214,7 @@ If you are reading a netCDF file with a ".nc" extension, the default engine is ` Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. -.. code:: +.. code:: python import xarray as xr @@ -233,7 +233,7 @@ You should specify the `engine` keyword argument when reading HDF5 files with xa To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: -.. code:: +.. code:: python import h5netcdf import xarray as xr @@ -250,11 +250,11 @@ We recommend you to install `h5netcdf` library using .. code:: - pip install h5netcdf + conda install -c conda-forge h5netcdf If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: -.. code:: +.. code:: python ds = xr.open_dataset('path/to/file.h5', engine='netcdf4') @@ -264,7 +264,7 @@ You should specify the `engine` keyword argument when reading GRIB files with xa Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. -.. code:: +.. code:: python import xarray as xr @@ -290,12 +290,12 @@ In such cases, you can specify the engine argument when reading the CSV file wit To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: -.. code:: +.. code:: python import xarray as xr import pandas as pd - # Load CSV file into `:py:func:pandas` DataFrame using the "c" engine + # Load CSV file into pandas DataFrame using the "c" engine df = pd.read_csv('your_file.csv', engine='c') From 40f37a627c0584be25d692031cc61ba6e9130007 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Tue, 21 Mar 2023 22:38:33 +0530 Subject: [PATCH 09/18] commit_check --- doc/getting-started-guide/faq.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 38dbf005f65..056d007d7e6 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -247,6 +247,7 @@ To read HDF5 files with xarray, you can use the ``open_dataset()`` function from print(ds) We recommend you to install `h5netcdf` library using +To install the `h5netcdf` package in Conda using the Conda Forge channel, run the following command: .. code:: From 791fe93523207534b28f0792ab958f71c9be8e5a Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Wed, 22 Mar 2023 00:29:18 +0530 Subject: [PATCH 10/18] formatted function names --- doc/getting-started-guide/faq.rst | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 056d007d7e6..44fb5d93584 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -212,7 +212,7 @@ NetCDF ------ If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. -Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object. +Use :py:func:`~xarray.open_dataset` to open a NetCDF file and return an xarray Dataset object. .. code:: python @@ -228,10 +228,10 @@ Use ``open_dataset()`` to open a NetCDF file and return an xarray Dataset object HDF5 ---- -Use ``open_dataset()`` to open an HDF5 file and return an xarray.Dataset object. +Use :py:func:`~xarray.open_dataset` to open an HDF5 file and return an xarray Dataset object. You should specify the `engine` keyword argument when reading HDF5 files with xarray, as there are multiple backends that can be used to read HDF5 files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. -To read HDF5 files with xarray, you can use the ``open_dataset()`` function from the `h5netcdf` backend, as follows: +To read HDF5 files with xarray, you can use the :py:func:`~xarray.open_dataset` function from the `h5netcdf` backend, as follows: .. code:: python @@ -247,11 +247,10 @@ To read HDF5 files with xarray, you can use the ``open_dataset()`` function from print(ds) We recommend you to install `h5netcdf` library using -To install the `h5netcdf` package in Conda using the Conda Forge channel, run the following command: -.. code:: +.. code:: - conda install -c conda-forge h5netcdf + pip install h5netcdf If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: @@ -263,7 +262,7 @@ GRIB ----------- You should specify the `engine` keyword argument when reading GRIB files with xarray, as there are multiple backends that can be used to read GRIB files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. -Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. +Use the :py:func:`~xarray.open_dataset` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. .. code:: python @@ -280,7 +279,7 @@ Use the ``open_dataset()`` function from the `cfgrib` package to open a GRIB fil We recommend installing `cfgrib` via conda: -.. code:: +.. code:: conda install -c conda-forge cfgrib @@ -289,7 +288,7 @@ CSV By default, xarray uses the built-in `pandas` library to read CSV files. In general, you don't need to specify the engine keyword argument when reading CSV files with xarray, as the default `pandas` engine is usually sufficient for most use cases. If you are working with very large CSV files or if you need to perform certain types of data processing that are not supported by the default `pandas` engine, you may want to use a different backend. In such cases, you can specify the engine argument when reading the CSV file with xarray. -To read CSV files with xarray, use the `open_dataset()` function and specify the path to the CSV file as follows: +To read CSV files with xarray, use the :py:func:`~xarray.open_dataset` function and specify the path to the CSV file as follows: .. code:: python From 59cfb7dabc7168e8063232e8e9dea772cc56c86d Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Wed, 22 Mar 2023 01:08:35 +0530 Subject: [PATCH 11/18] passed all checks --- doc/getting-started-guide/faq.rst | 64 +++++++++++++++---------------- 1 file changed, 30 insertions(+), 34 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 44fb5d93584..400dc62b0e9 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -185,7 +185,7 @@ What other projects leverage xarray? ------------------------------------ See section :ref:`ecosystem`. - + How do I open format X file as an xarray dataset? ------------------------------------------------- @@ -202,9 +202,9 @@ To open format X file in xarray, you need to know the `format of the data Date: Wed, 22 Mar 2023 19:43:04 +0530 Subject: [PATCH 12/18] checks_commit --- doc/getting-started-guide/faq.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 400dc62b0e9..4599749fc00 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -250,7 +250,7 @@ We recommend you to install `h5netcdf` library using the below given code: conda install -c conda-forge h5netcdf -If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with the HDF5 file format), you can specify the engine argument as follows: +If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with HDF5 file format), you can specify the engine argument as follows: .. code:: python From e9aa0326c5ab6a48abb6d418a2c8d82d09fa2a72 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Thu, 23 Mar 2023 04:46:32 +0530 Subject: [PATCH 13/18] changes done_added zarr --- doc/getting-started-guide/faq.rst | 47 +++++++++++++++++++++++++++++-- 1 file changed, 45 insertions(+), 2 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 4599749fc00..d3692c117e2 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -199,6 +199,7 @@ To open format X file in xarray, you need to know the `format of the data `_, `pytables `_ " "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" "CSV (.csv)","``open_dataset()``", "`_pandas `_ , `dask `_" + "Zarr (.zarr)","``open_dataset()``", "`zarr `_ , `_dask `_ " To use these backend functions in xarray, you can call them with the path to the file(s) you want to read as an argument. @@ -206,6 +207,8 @@ Xarray provides a default engine to read files, which is usually determined by t Therefore, it's good practice to always specify the engine explicitly, especially when working with complex data formats or non-standard file extensions. So, specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. +:py:func:`xarray.backends.list_engines` is a function in xarray that returns a dictionary of available engines and their BackendEntrypoint objects. + For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: NetCDF @@ -218,7 +221,7 @@ Use :py:func:`~xarray.open_dataset` to open a NetCDF file and return an xarray D import xarray as xr - # use xarray to open the file and return an xarray.Dataset object + # use xarray to open the file and return an xarray.Dataset object using netcdf4 engine ds = xr.open_dataset("/path/to/my/file.nc", engine="netcdf4") @@ -226,6 +229,17 @@ Use :py:func:`~xarray.open_dataset` to open a NetCDF file and return an xarray D print(ds) + # use xarray to open the file and return an xarray.Dataset object using scipy engine + + ds = xr.open_dataset("/path/to/my/file.nc", engine="scipy") + +We recommend installing `scipy` via conda using the below given code: + +:: + + conda install scipy + + HDF5 ---- Use :py:func:`~xarray.open_dataset` to open an HDF5 file and return an xarray Dataset object. @@ -235,7 +249,6 @@ To read HDF5 files with xarray, you can use the :py:func:`~xarray.open_dataset` .. code:: python - import h5netcdf import xarray as xr # Open HDF5 file as an xarray Dataset @@ -248,6 +261,8 @@ To read HDF5 files with xarray, you can use the :py:func:`~xarray.open_dataset` We recommend you to install `h5netcdf` library using the below given code: +:: + conda install -c conda-forge h5netcdf If you want to use the `netCDF4` backend to read a file with a ".h5" extension (which is typically associated with HDF5 file format), you can specify the engine argument as follows: @@ -277,6 +292,8 @@ Use the :py:func:`~xarray.open_dataset` function from the `cfgrib` package to op We recommend installing `cfgrib` via conda using the below given code: +:: + conda install -c conda-forge cfgrib CSV @@ -303,6 +320,32 @@ To read CSV files with xarray, use the :py:func:`~xarray.open_dataset` function print(ds) +Zarr +---- +When opening a Zarr dataset with xarray, the `engine` is automatically detected based on the file extension or the type of input provided. If the dataset is stored in a directory with a ".zarr" extension, xarray will automatically use the "zarr" engine. + +To read zarr files with xarray, use the :py:func:`~xarray.open_dataset` function and specify the path to the zarr file as follows: + +.. code:: python + + import xarray as xr + + # use xarray to open the file and return an xarray.Dataset object using zarr engine + + ds = xr.open_dataset("path/to/your/file.zarr", engine="zarr") + + # Print Dataset object + + print(ds) + +We recommend installing `zarr` via conda using the below given code: + +:: + + conda install -c conda-forge zarr + +However, there may be situations where you need to specify the engine manually using the `engine` keyword argument. For example, if you have a Zarr dataset stored in a file with a different extension (e.g., ".npy"), you will need to specify the engine as "zarr" explicitly when opening the dataset. + Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. How should I cite xarray? From 48f2ab888501072026d6b85e0eda2f5312f70502 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Fri, 24 Mar 2023 00:05:49 +0530 Subject: [PATCH 14/18] minor changes --- doc/getting-started-guide/faq.rst | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index d3692c117e2..dddece1171f 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -205,15 +205,15 @@ To use these backend functions in xarray, you can call them with the path to the Xarray provides a default engine to read files, which is usually determined by the file extension or type. If you don't specify the engine, xarray will try to guess it based on the file extension or type, and may fall back to a different engine if it cannot determine the correct one. -Therefore, it's good practice to always specify the engine explicitly, especially when working with complex data formats or non-standard file extensions. So, specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. +Therefore, it's good practice to always specify the engine explicitly, to ensure that the correct backend is used and especially when working with complex data formats or non-standard file extensions. :py:func:`xarray.backends.list_engines` is a function in xarray that returns a dictionary of available engines and their BackendEntrypoint objects. For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: NetCDF ------- -If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly when reading files with xarray, to ensure that the correct backend is used. +~~~~~~ +If you are reading a netCDF file with a ".nc" extension, the default engine is `netcdf4`. However if you have files with non-standard extensions or if the file format is ambiguous. Specify the engine explicitly, to ensure that the correct backend is used. Use :py:func:`~xarray.open_dataset` to open a NetCDF file and return an xarray Dataset object. @@ -239,10 +239,10 @@ We recommend installing `scipy` via conda using the below given code: conda install scipy - HDF5 ----- +~~~~ Use :py:func:`~xarray.open_dataset` to open an HDF5 file and return an xarray Dataset object. + You should specify the `engine` keyword argument when reading HDF5 files with xarray, as there are multiple backends that can be used to read HDF5 files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. To read HDF5 files with xarray, you can use the :py:func:`~xarray.open_dataset` function from the `h5netcdf` backend, as follows: @@ -272,7 +272,7 @@ If you want to use the `netCDF4` backend to read a file with a ".h5" extension ( ds = xr.open_dataset("path/to/file.h5", engine="netcdf4") GRIB ------------ +~~~~ You should specify the `engine` keyword argument when reading GRIB files with xarray, as there are multiple backends that can be used to read GRIB files, and xarray may not always be able to automatically detect the correct one based on the file extension or file format. Use the :py:func:`~xarray.open_dataset` function from the `cfgrib` package to open a GRIB file as an xarray Dataset. @@ -297,7 +297,7 @@ We recommend installing `cfgrib` via conda using the below given code: conda install -c conda-forge cfgrib CSV ---- +~~~ By default, xarray uses the built-in `pandas` library to read CSV files. In general, you don't need to specify the engine keyword argument when reading CSV files with xarray, as the default `pandas` engine is usually sufficient for most use cases. If you are working with very large CSV files or if you need to perform certain types of data processing that are not supported by the default `pandas` engine, you may want to use a different backend. In such cases, you can specify the engine argument when reading the CSV file with xarray. @@ -321,7 +321,7 @@ To read CSV files with xarray, use the :py:func:`~xarray.open_dataset` function print(ds) Zarr ----- +~~~~ When opening a Zarr dataset with xarray, the `engine` is automatically detected based on the file extension or the type of input provided. If the dataset is stored in a directory with a ".zarr" extension, xarray will automatically use the "zarr" engine. To read zarr files with xarray, use the :py:func:`~xarray.open_dataset` function and specify the path to the zarr file as follows: @@ -344,7 +344,7 @@ We recommend installing `zarr` via conda using the below given code: conda install -c conda-forge zarr -However, there may be situations where you need to specify the engine manually using the `engine` keyword argument. For example, if you have a Zarr dataset stored in a file with a different extension (e.g., ".npy"), you will need to specify the engine as "zarr" explicitly when opening the dataset. +There may be situations where you need to specify the engine manually using the `engine` keyword argument. For example, if you have a Zarr dataset stored in a file with a different extension (e.g., ".npy"), you will need to specify the engine as "zarr" explicitly when opening the dataset. Some packages may have additional functionality beyond what is shown here. You can refer to the documentation for each package for more information. From 6e052a41e2a80696ed71a7488f3876df40144a46 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Fri, 24 Mar 2023 15:51:50 +0530 Subject: [PATCH 15/18] documentation changes --- doc/getting-started-guide/faq.rst | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index dddece1171f..67c6484ba88 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -192,16 +192,24 @@ How do I open format X file as an xarray dataset? To open format X file in xarray, you need to know the `format of the data `_ you want to read. If the format is supported, you can use the appropriate function provided by xarray. The following table provides functions used for different file formats in xarray, as well as links to other packages that can be used: .. csv-table:: - :header: "File Format", "xarray Backend", " Other Packages" + :header: "File Format", "Open via", " Related Packages" :widths: 15, 45, 15 "NetCDF (.nc, .nc4, .cdf)","``open_dataset()`` OR ``open_mfdataset()``", "`netCDF4 `_, `netcdf `_ , `cdms2 `_" "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" - "CSV (.csv)","``open_dataset()``", "`_pandas `_ , `dask `_" - "Zarr (.zarr)","``open_dataset()``", "`zarr `_ , `_dask `_ " + "CSV (.csv)","``open_dataset()``", "pandas_ , `dask `_" + "Zarr (.zarr)","``open_dataset()`` OR ``open_mfdataset()``", "`zarr `_ , `dask `_ " -To use these backend functions in xarray, you can call them with the path to the file(s) you want to read as an argument. +.. _pandas: https://pandas.pydata.org + +If you are unable to open a file in xarray: + +- You should check that you are having all necessary dependencies installed, including any optional dependencies (like scipy, h5netcdf, cfgrib etc as mentioned below) that may be required for the specific use case. + +- If all necessary dependencies are installed but the file still cannot be opened, you must check if there are any specialized backends available for the specific file format you are working with. You can consult the xarray documentation or the documentation for the file format to determine if a specialized backend is required, and if so, how to install and use it with xarray. + +- If the file format is not supported by xarray or any of its available backends, the user may need to use a different library or tool to work with the file. You can consult the documentation for the file format to determine which tools are recommended for working with it. Xarray provides a default engine to read files, which is usually determined by the file extension or type. If you don't specify the engine, xarray will try to guess it based on the file extension or type, and may fall back to a different engine if it cannot determine the correct one. @@ -209,7 +217,7 @@ Therefore, it's good practice to always specify the engine explicitly, to ensure :py:func:`xarray.backends.list_engines` is a function in xarray that returns a dictionary of available engines and their BackendEntrypoint objects. -For example, you can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: +You can use the `engine` argument to specify the backend when calling ``open_dataset()`` or other reading functions in xarray, as shown below: NetCDF ~~~~~~ From 9c35aa8af6a4ccf7e4c0fda30dc9eae92289e08e Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Fri, 24 Mar 2023 23:56:00 +0530 Subject: [PATCH 16/18] ready for review --- doc/getting-started-guide/faq.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/getting-started-guide/faq.rst b/doc/getting-started-guide/faq.rst index 67c6484ba88..08cb9646f94 100644 --- a/doc/getting-started-guide/faq.rst +++ b/doc/getting-started-guide/faq.rst @@ -198,7 +198,7 @@ To open format X file in xarray, you need to know the `format of the data `_, `netcdf `_ , `cdms2 `_" "HDF5 (.h5, .hdf5)","``open_dataset()`` OR ``open_mfdataset()``", "`h5py `_, `pytables `_ " "GRIB (.grb, .grib)", "``open_dataset()``", "`cfgrib `_, `pygrib `_" - "CSV (.csv)","``open_dataset()``", "pandas_ , `dask `_" + "CSV (.csv)","``open_dataset()``", "`pandas`_ , `dask `_" "Zarr (.zarr)","``open_dataset()`` OR ``open_mfdataset()``", "`zarr `_ , `dask `_ " .. _pandas: https://pandas.pydata.org From 509ae802668c2c8da4e2bf0a294ad91908633355 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Mon, 27 Mar 2023 00:00:38 +0530 Subject: [PATCH 17/18] added what I have done to whats-new.rst --- doc/whats-new.rst | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/doc/whats-new.rst b/doc/whats-new.rst index 6bfdf0b6f0a..64fe04569a4 100644 --- a/doc/whats-new.rst +++ b/doc/whats-new.rst @@ -41,6 +41,9 @@ Bug fixes Documentation ~~~~~~~~~~~~~ +- Update FAQ page on how do I open format X file as an xarray dataset? (:issue:`1285`, :pull:`7638`) using :py:func:`~xarray.open_dataset` + By `Harshitha `_ , `Tom Nicholas `_ and + `Michael Niklas `_. Internal Changes ~~~~~~~~~~~~~~~~ @@ -51,8 +54,8 @@ v2023.03.0 (March 22, 2023) --------------------------- This release brings many bug fixes, and some new features. The maximum pandas version is pinned to ``<2`` until we can support the new pandas datetime types. -Thanks to our 19 contributors: -Abel Aoun, Alex Goodman, Deepak Cherian, Illviljan, Jody Klymak, Joe Hamman, Justus Magin, Mary Gathoni, Mathias Hauser, Mattia Almansi, Mick, Oriol Abril-Pla, Patrick Hoefler, Paul Ockenfuß, Pierre, Shreyal Gupta, Spencer Clark, Tom Nicholas, Tom Vo +Thanks to our 20 contributors: +Abel Aoun, Alex Goodman, Deepak Cherian, Harshitha, Illviljan, Jody Klymak, Joe Hamman, Justus Magin, Mary Gathoni, Mathias Hauser, Mattia Almansi, Mick, Oriol Abril-Pla, Patrick Hoefler, Paul Ockenfuß, Pierre, Shreyal Gupta, Spencer Clark, Tom Nicholas, Tom Vo New Features ~~~~~~~~~~~~ From ae43b0424e78b788c2d2b9f541007cba30ac4f15 Mon Sep 17 00:00:00 2001 From: harshitha1201 Date: Mon, 27 Mar 2023 00:12:06 +0530 Subject: [PATCH 18/18] updated --- doc/whats-new.rst | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/doc/whats-new.rst b/doc/whats-new.rst index 64fe04569a4..c271a69e946 100644 --- a/doc/whats-new.rst +++ b/doc/whats-new.rst @@ -42,8 +42,7 @@ Documentation ~~~~~~~~~~~~~ - Update FAQ page on how do I open format X file as an xarray dataset? (:issue:`1285`, :pull:`7638`) using :py:func:`~xarray.open_dataset` - By `Harshitha `_ , `Tom Nicholas `_ and - `Michael Niklas `_. + By `Harshitha `_ , `Tom Nicholas `_. Internal Changes ~~~~~~~~~~~~~~~~ @@ -54,8 +53,8 @@ v2023.03.0 (March 22, 2023) --------------------------- This release brings many bug fixes, and some new features. The maximum pandas version is pinned to ``<2`` until we can support the new pandas datetime types. -Thanks to our 20 contributors: -Abel Aoun, Alex Goodman, Deepak Cherian, Harshitha, Illviljan, Jody Klymak, Joe Hamman, Justus Magin, Mary Gathoni, Mathias Hauser, Mattia Almansi, Mick, Oriol Abril-Pla, Patrick Hoefler, Paul Ockenfuß, Pierre, Shreyal Gupta, Spencer Clark, Tom Nicholas, Tom Vo +Thanks to our 19 contributors: +Abel Aoun, Alex Goodman, Deepak Cherian, Illviljan, Jody Klymak, Joe Hamman, Justus Magin, Mary Gathoni, Mathias Hauser, Mattia Almansi, Mick, Oriol Abril-Pla, Patrick Hoefler, Paul Ockenfuß, Pierre, Shreyal Gupta, Spencer Clark, Tom Nicholas, Tom Vo New Features ~~~~~~~~~~~~