From ba2c4264738e056cee553d81d4a457ebe47ddfe1 Mon Sep 17 00:00:00 2001 From: andersy005 Date: Tue, 3 Oct 2023 05:44:24 +0000 Subject: [PATCH] deploy: deef167af129339e5270b70657e1a421341dc016 --- _sources/intermediate/01-high-level-computation-patterns.ipynb | 2 +- intermediate/01-high-level-computation-patterns.html | 2 +- searchindex.js | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/_sources/intermediate/01-high-level-computation-patterns.ipynb b/_sources/intermediate/01-high-level-computation-patterns.ipynb index 338c7e03..43a7dd5a 100644 --- a/_sources/intermediate/01-high-level-computation-patterns.ipynb +++ b/_sources/intermediate/01-high-level-computation-patterns.ipynb @@ -928,7 +928,7 @@ "For instance, grouping data by month (which have varying numbers of days) or the results of an image classification.\n", "The GroupBy functions are essentially a generalization of `coarsen`: \n", "\n", - "- `groupby`: divide data into distinct groups, e.g. climatologies, composites. Works best when the \"group indentifiers\" or \"labels\" are exact and can be determined using equality (`==`), e.g. characters or integers. Remember that floats are not exact values.\n", + "- `groupby`: divide data into distinct groups, e.g. climatologies, composites. Works best when the \"group identifiers\" or \"labels\" are exact and can be determined using equality (`==`), e.g. characters or integers. Remember that floats are not exact values.\n", "- `groupby_bins`: Use binning operations, e.g. histograms, to group your data.\n", "- `resample`: Specialized implementation of GroupBy specifically for time grouping (so far), allows you to change sampling frequency of dataset.\n", "\n", diff --git a/intermediate/01-high-level-computation-patterns.html b/intermediate/01-high-level-computation-patterns.html index 0fb0f21a..6e8c17f8 100644 --- a/intermediate/01-high-level-computation-patterns.html +++ b/intermediate/01-high-level-computation-patterns.html @@ -7458,7 +7458,7 @@

Label space “windows” or bins : GroupBycoarsen:

    -

  • groupby: divide data into distinct groups, e.g. climatologies, composites. Works best when the “group indentifiers” or “labels” are exact and can be determined using equality (==), e.g. characters or integers. Remember that floats are not exact values.

    • +

  • groupby: divide data into distinct groups, e.g. climatologies, composites. Works best when the “group identifiers” or “labels” are exact and can be determined using equality (==), e.g. characters or integers. Remember that floats are not exact values.

  • groupby_bins: Use binning operations, e.g. histograms, to group your data.

  • resample: Specialized implementation of GroupBy specifically for time grouping (so far), allows you to change sampling frequency of dataset.

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Guide","Creating custom accessors","<no title>","apply_ufunc","Automatic Vectorization","Handling complex output","Core dimensions","Handling dask arrays","np.interp : An end-to-end example","Fast vectorization with Numba","A gentle introduction","Binary data without lazy loading","Binary data with lazy loading","Creating new backends","map_blocks","A gentle introduction","Parallelizing custom functions","Data Tidying","Re-organize InSAR ice velocity data","Creating Data Structures","Reading and writing files","Data Structures","Xarray\u2019s Data structures","Indexing and Selecting Data","Manipulating Dimensions (Data Resolution)","Computing with Multiple Objects","Labeled data","Basic Computation","Grouped Computations","Windowed Computations","Weighted Reductions","Computation","Plotting and Visualization","Basic Visualization","Faceting","Geography with Cartopy","Computational Patterns","Accessing remote data stored on the cloud","Interactive plots using hvplot","Advanced Indexing","Boolean Indexing & Masking","Indexing","Parallel computing with Dask","A Tour of Xarray Customizations","Welcome to the Xarray Tutorial!","Fundamental Path","Get Started","Intermediate Path","Learning Paths","Xarray in 45 minutes","Glossary","Keep Exploring!","Oceanhackweek 2020","Xarray Fundamentals","Indexing and Selecting Data","Computation","Xarray Online Tutorial","SciPy 2023","Thinking like 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