Added an introduction to the reshaping documentation #7623

nishtha981 · 2023-03-14T15:55:15Z

Closes Reshaping doc intro looks incomplete #7091

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headtr1ck

Thanks for this PR and welcome to xarray.

I think this intro can still be improved, I have left a few hints. Maybe collectively we can come up with a more general motivation.

headtr1ck · 2023-03-15T20:35:36Z

doc/user-guide/reshaping.rst

@@ -6,6 +6,16 @@ Reshaping and reorganizing data

 These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.

+Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks.


I think this sentence should be the first one of this intro.

Okay!
Will change that and put it as the beginning

headtr1ck · 2023-03-15T20:36:48Z

doc/user-guide/reshaping.rst

@@ -6,6 +6,16 @@ Reshaping and reorganizing data

 These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.

+Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks.
+
+To reorder dimensions on a DataArray or across all variables on a Dataset, use the transpose() method. An ellipsis (...) can be used to represent all other dimensions. To expand a DataArray or all variables on a Dataset along a new dimension, use the expand_dims() method. This method attaches a new dimension with size 1 to all data variables. To remove such a size-1 dimension from the DataArray or Dataset, use the squeeze() method.


I don't think having this short summary which repeats parts from below is very useful to have here.

Got it
Will remove it!

doc/user-guide/reshaping.rst

headtr1ck

Almost :)

headtr1ck · 2023-03-27T17:51:10Z

doc/user-guide/reshaping.rst

@@ -4,7 +4,9 @@
 Reshaping and reorganizing data
 ###############################

-These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.
+Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks. To convert from a Dataset to a DataArray, use the to_array() method. Unlike pandas, xarray's stack() method does not automatically drop missing values.


Suggested change

Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks. To convert from a Dataset to a DataArray, use the to_array() method. Unlike pandas, xarray's stack() method does not automatically drop missing values.

Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks.

No need to mention specific method and their peculiarities in the introduction already.
I didn't check below, so make sure that the section about these methods contain the sentences you have added here.

headtr1ck · 2023-03-27T17:52:23Z

doc/user-guide/reshaping.rst

-These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.
+Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks. To convert from a Dataset to a DataArray, use the to_array() method. Unlike pandas, xarray's stack() method does not automatically drop missing values.
+
+These methods are particularly useful for reshaping xarray objects for use in machine learning packages, such as scikit-learn, that usually require two-dimensional numpy arrays as inputs. It can also be used in working with geospatial data where we need to analyze and visualize geospatial data, such as satellite imagery or geospatial datasets. Xarray can also be used for time series analysis, including forecasting and anomaly detection.


Suggested change

These methods are particularly useful for reshaping xarray objects for use in machine learning packages, such as scikit-learn, that usually require two-dimensional numpy arrays as inputs. It can also be used in working with geospatial data where we need to analyze and visualize geospatial data, such as satellite imagery or geospatial datasets. Xarray can also be used for time series analysis, including forecasting and anomaly detection.

These methods are particularly useful for reshaping xarray objects for use in machine learning packages, such as scikit-learn, that usually require two-dimensional numpy arrays as inputs. It can also be used in working with geospatial data where we need to analyze and visualize geospatial data, such as satellite imagery or geospatial datasets.

I think the last sentence does not really apply to reshaping. You can just drop it completely or check if you can add it somewhere else in a more general introduction.

…e bot

nishtha981 · 2023-03-30T05:58:33Z

@headtr1ck @TomNicholas
Please do review the pr!
Thanks!

.github/config.yml

TomNicholas · 2023-03-30T15:48:14Z

doc/user-guide/reshaping.rst

-These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.
+Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks. Unlike pandas, xarray's stack() method does not automatically drop missing values.
+
+These methods are particularly useful for reshaping xarray objects for use in machine learning packages, such as scikit-learn, that usually require two-dimensional numpy arrays as inputs. It can also be used in working with geospatial data where we need to analyze and visualize geospatial data, such as satellite imagery or geospatial datasets.


No need to say "geospatial data" three times in the same sentence.

Instead I might say

"Reshaping can also be required before passing data to external visualization tools, for example geospatial data might expect input organized into a particular format corresponding to stacks of satellite images."

doc/user-guide/reshaping.rst

TomNicholas · 2023-03-30T17:43:55Z

I've made a final edit to remove the mention of a specific method in the intro, and remove some blanks lines. This looks good to me now so I'll merge it! Thanks @nishtha981 !

nishtha981 · 2023-03-30T17:50:31Z

Hey!
@TomNicholas the documentation tests are failing
Would you be able to merge the pr despite the issue or can you guide me on how to solve it?

nishtha981 · 2023-03-31T04:34:34Z

Hey @TomNicholas
I've found that the issue executablebooks/sphinx-book-theme#711 was causing an issue with the test cases of my pr.
It has been merged now so I'll be making an empty push so that the test cases can run again.

TomNicholas · 2023-03-31T04:40:23Z

Hi @nishtha981 - that's great that you identified what was causing the docs ci builds to fail! I was wondering why that was!

Fixing this for xarray may require more than just re-running the ci. For example it might require us to pin a particular version of a library (here sphinx_book_theme) in order to guarantee the CI works again. If it doesn't work immediately now, what we normally do is to open a new github issue on xarray's issue tracker to track the problem. That way if the problem comes up in multiple PRs we can just refer all of them back to the one issue, until it gets resolved completely.

TomNicholas · 2023-03-31T04:40:58Z

I've also just told the readthedocs to rebuild just now

nishtha981 · 2023-03-31T05:12:06Z

@TomNicholas
Do I pin the sphinx-book-theme version 0.3.0

nishtha981 · 2023-03-31T06:04:02Z

I am not sure if pinning works as pydata-sphinx-theme had some private function which sphinx-book-theme was using but now it cannot.
Will probably have to wait for a new release of sphinx-book-theme.

headtr1ck · 2023-03-31T06:22:28Z

I am not sure if pinning works as pydata-sphinx-theme had some private function which sphinx-book-theme was using but now it cannot.
Will probably have to wait for a new release of sphinx-book-theme.

See #7703

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nishtha981 · 2023-03-31T15:21:20Z

Hey! @TomNicholas
All the checks have passed.
Can you please merge the pr?

TomNicholas · 2023-03-31T15:26:10Z

Thanks @nishtha981 !

I just realised after merging that this PR should in theory have had a corresponding entry in the what's new page, as all PRs are supposed to have.

We won't worry about that this time, but try and remember to add it next time! That way you will also be listed as a contributor on the what's new page.

nishtha981 · 2023-03-31T15:39:07Z

Sure!
I'll keep that in mind next time!
Thank you

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Added an introduction to the reshaping documentation #7623

Added an introduction to the reshaping documentation #7623

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		@@ -6,6 +6,16 @@ Reshaping and reorganizing data

		These methods allow you to reorganize your data by changing dimensions, array shape, order of values, or indexes.

		Reshaping and reorganizing data refers to the process of changing the structure or organization of data by modifying dimensions, array shapes, order of values, or indexes. Xarray provides several methods to accomplish these tasks.

Added an introduction to the reshaping documentation #7623

Added an introduction to the reshaping documentation #7623

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