Merge branch 'master' of github.com:plotly/plotly.py into pass-b64

Author: marthacryan

CHANGELOG.md

@@ -2,9 +2,17 @@
 All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
-## UNRELEASED
+## [5.24.0] - 2024-08-29
+
+### Added
+- New `px` functions for maps: `scatter_map`, `line_map`, `choropleth_map`, and `density_map`.
 
 ### Updated
+
+- Updated Plotly.js from version 2.34.0 to version 2.35.0. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2350----2024-08-29) for more information. These changes are reflected in the auto-generated `plotly.graph_objects` module. Notable changes include:
+  - Add new traces: scattermap, choroplethmap and densitymap and map subplots which use maplibre to render maps [[#7015](https://github.com/plotly/plotly.js/pull/7015), [#7060](https://github.com/plotly/plotly.js/pull/7060), [#7085](https://github.com/plotly/plotly.js/pull/7085), [#7088](https://github.com/plotly/plotly.js/pull/7088), [#7090](https://github.com/plotly/plotly.js/pull/7090), [#7092](https://github.com/plotly/plotly.js/pull/7092), [#7094](https://github.com/plotly/plotly.js/pull/7094), [#7134](https://github.com/plotly/plotly.js/pull/7134)]
+  - Deprecate mapbox traces and mapbox subplot [[#7087](https://github.com/plotly/plotly.js/pull/7087)]
+
 - Fixed a bug in integer validation of arrays that threw an error when an array contained a mix of strings and integers.
 
 ## [5.23.0] - 2024-07-23

README.md

@@ -40,7 +40,7 @@
 
 ## Quickstart
 
-`pip install plotly==5.23.0`
+`pip install plotly==5.24.0`
 
 Inside [Jupyter](https://jupyter.org/install) (installable with `pip install "jupyterlab>=3" "ipywidgets>=7.6"`):
 
@@ -85,13 +85,13 @@ Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is
 plotly.py may be installed using pip...
 
 ```
-pip install plotly==5.23.0
+pip install plotly==5.24.0
 ```
 
 or conda.
 
 ```
-conda install -c plotly plotly=5.23.0
+conda install -c plotly plotly=5.24.0
 ```
 
 ### JupyterLab Support
@@ -113,7 +113,7 @@ The instructions above apply to JupyterLab 3.x. **For JupyterLab 2 or earlier**,
 
 ```
 # JupyterLab 2.x renderer support
-jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager
+jupyter labextension install jupyterlab-plotly@5.24.0 @jupyter-widgets/jupyterlab-manager
 ```
 
 Please check out our [Troubleshooting guide](https://plotly.com/python/troubleshooting/) if you run into any problems with JupyterLab.

binder/requirements.txt

@@ -1,5 +1,5 @@
 jupytext
-plotly==5.23.0
+plotly==5.24.0
 jupyter
 notebook
 pandas==2.2.2

doc/apidoc/conf.py

@@ -26,7 +26,7 @@
 # The short X.Y version
 version = ""
 # The full version, including alpha/beta/rc tags
-release = "5.23.0"
+release = "5.24.0"
 
 
 # -- General configuration ---------------------------------------------------

doc/apidoc/plotly.express.rst

@@ -18,12 +18,14 @@ plotly's high-level API for rapid figure generation. ::
     scatter_3d
     scatter_polar
     scatter_ternary
+    scatter_map
     scatter_mapbox
     scatter_geo
     line
     line_3d
     line_polar
     line_ternary
+    line_map
     line_mapbox
     line_geo
     area
@@ -45,9 +47,11 @@ plotly's high-level API for rapid figure generation. ::
     parallel_coordinates
     parallel_categories
     choropleth
+    choropleth_map
     choropleth_mapbox
     density_contour
     density_heatmap
+    density_map
     density_mapbox
     imshow
     set_mapbox_access_token

doc/python/axes.md

@@ -41,7 +41,7 @@ Other kinds of subplots and axes are described in other tutorials:
 - [Polar axes](/python/polar-chart/). The axis object is [`go.layout.Polar`](/python/reference/layout/polar/)
 - [Ternary axes](/python/ternary-plots). The axis object is [`go.layout.Ternary`](/python/reference/layout/ternary/)
 - [Geo axes](/python/map-configuration/). The axis object is [`go.layout.Geo`](/python/reference/layout/geo/)
-- [Mapbox axes](/python/mapbox-layers/). The axis object is [`go.layout.Mapbox`](/python/reference/layout/mapbox/)
+- [Map axes](/python/tile-map-layers/). The axis object is [`go.layout.Map`](/python/reference/layout/map/)
 - [Color axes](/python/colorscales/). The axis object is [`go.layout.Coloraxis`](/python/reference/layout/coloraxis/).
 
 **See also** the tutorials on [facet plots](/python/facet-plots/), [subplots](/python/subplots) and [multiple axes](/python/multiple-axes/).

doc/python/bubble-maps.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.1'
-      jupytext_version: 1.1.1
+      format_version: '1.3'
+      jupytext_version: 1.16.3
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,14 +20,14 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.6.7
+    version: 3.10.0
   plotly:
     description: How to make bubble maps in Python with Plotly.
     display_as: maps
     language: python
     layout: base
     name: Bubble Maps
-    order: 4
+    order: 5
     page_type: example_index
     permalink: python/bubble-maps/
     thumbnail: thumbnail/bubble-map.jpg

doc/python/choropleth-maps.md

@@ -6,9 +6,9 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.3'
-      jupytext_version: 1.14.1
+      jupytext_version: 1.16.3
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,20 +20,20 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.8.8
+    version: 3.10.0
   plotly:
     description: How to make choropleth maps in Python with Plotly.
     display_as: maps
     language: python
     layout: base
     name: Choropleth Maps
-    order: 7
+    order: 8
     page_type: u-guide
     permalink: python/choropleth-maps/
     thumbnail: thumbnail/choropleth.jpg
 ---
 
-A [Choropleth Map](https://en.wikipedia.org/wiki/Choropleth_map) is a map composed of colored polygons. It is used to represent spatial variations of a quantity. This page documents how to build **outline** choropleth maps, but you can also build [choropleth **tile maps** using our Mapbox trace types](/python/mapbox-county-choropleth).
+A [Choropleth Map](https://en.wikipedia.org/wiki/Choropleth_map) is a map composed of colored polygons. It is used to represent spatial variations of a quantity. This page documents how to build **outline** choropleth maps, but you can also build [choropleth **tile maps**](/python/tile-county-choropleth).
 
 Below we show how to create Choropleth Maps using either Plotly Express' `px.choropleth` function or the lower-level `go.Choropleth` graph object.
 

doc/python/county-choropleth.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.3.1
+      format_version: '1.3'
+      jupytext_version: 1.16.3
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,15 +20,15 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.6.8
+    version: 3.10.0
   plotly:
     description: How to create colormaped representations of USA counties by FIPS
       values in Python.
     display_as: maps
     language: python
     layout: base
     name: USA County Choropleth Maps
-    order: 10
+    order: 11
     page_type: u-guide
     permalink: python/county-choropleth/
     thumbnail: thumbnail/county-choropleth-usa-greybkgd.jpg
@@ -37,7 +37,7 @@ jupyter:
 ### Deprecation warning
 
 
-This page describes a [legacy "figure factory" method](/python/figure-factories/) for creating map-like figures using [self-filled scatter traces](/python/shapes). **This is no longer the recommended way to make county-level choropleth maps**, instead we recommend using a [GeoJSON-based approach to making outline choropleth maps](/python/choropleth-maps/) or the alternative [Mapbox tile-based choropleth maps](/python/mapbox-county-choropleth).
+This page describes a [legacy "figure factory" method](/python/figure-factories/) for creating map-like figures using [self-filled scatter traces](/python/shapes). **This is no longer the recommended way to make county-level choropleth maps**, instead we recommend using a [GeoJSON-based approach to making outline choropleth maps](/python/choropleth-maps/) or the alternative [tile-based choropleth maps](/python/tile-county-choropleth).
 
 
 #### Required Packages
@@ -274,7 +274,7 @@ fig.layout.template = None
 fig.show()
 ```
 
-Also see Mapbox county choropleths made in Python: [https://plotly.com/python/mapbox-county-choropleth/](https://plotly.com/python/mapbox-county-choropleth/)
+Also see tile county choropleths made in Python: [https://plotly.com/python/tile-county-choropleth/](https://plotly.com/python/tile-county-choropleth/)
 
 ### Reference
 

doc/python/datashader.md

@@ -5,10 +5,10 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.2'
-      jupytext_version: 1.3.0
+      format_version: '1.3'
+      jupytext_version: 1.16.3
   kernelspec:
-    display_name: Python 3
+    display_name: Python 3 (ipykernel)
     language: python
     name: python3
   language_info:
@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.7.3
+    version: 3.10.0
   plotly:
     description: How to use datashader to rasterize large datasets, and visualize
       the generated raster data with plotly.
@@ -36,10 +36,10 @@ jupyter:
 
 [datashader](https://datashader.org/) creates rasterized representations of large datasets for easier visualization, with a pipeline approach consisting of several steps: projecting the data on a regular grid, creating a color representation of the grid, etc.
 
-### Passing datashader rasters as a mapbox image layer
+### Passing datashader rasters as a tile map image layer
 
 We visualize here the spatial distribution of taxi rides in New York City. A higher density
-is observed on major avenues. For more details about mapbox charts, see [the mapbox layers tutorial](/python/mapbox-layers). No mapbox token is needed here.
+is observed on major avenues. For more details about tile-based maps, see [the tile map layers tutorial](/python/tile-map-layers).
 
 ```python
 import pandas as pd
@@ -51,7 +51,7 @@ cvs = ds.Canvas(plot_width=1000, plot_height=1000)
 agg = cvs.points(dff, x='Lon', y='Lat')
 # agg is an xarray object, see http://xarray.pydata.org/en/stable/ for more details
 coords_lat, coords_lon = agg.coords['Lat'].values, agg.coords['Lon'].values
-# Corners of the image, which need to be passed to mapbox
+# Corners of the image
 coordinates = [[coords_lon[0], coords_lat[0]],
                [coords_lon[-1], coords_lat[0]],
                [coords_lon[-1], coords_lat[-1]],
@@ -62,16 +62,12 @@ import datashader.transfer_functions as tf
 img = tf.shade(agg, cmap=fire)[::-1].to_pil()
 
 import plotly.express as px
-# Trick to create rapidly a figure with mapbox axes
-fig = px.scatter_mapbox(dff[:1], lat='Lat', lon='Lon', zoom=12)
-# Add the datashader image as a mapbox layer image
-fig.update_layout(mapbox_style="carto-darkmatter",
-                 mapbox_layers = [
-                {
-                    "sourcetype": "image",
-                    "source": img,
-                    "coordinates": coordinates
-                }]
+# Trick to create rapidly a figure with map axes
+fig = px.scatter_map(dff[:1], lat='Lat', lon='Lon', zoom=12)
+# Add the datashader image as a tile map layer image
+fig.update_layout(
+    map_style="carto-darkmatter",
+    map_layers=[{"sourcetype": "image", "source": img, "coordinates": coordinates}],
 )
 fig.show()
 ```
@@ -113,7 +109,3 @@ fig.update_traces(hoverongaps=False)
 fig.update_layout(coloraxis_colorbar=dict(title='Count', tickprefix='1.e'))
 fig.show()
 ```
-
-```python
-
-```