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ocefpafConengmo
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Remove Stamen (#1811)
* remove Stamen * address comments on docs * Update test_minimap.py --------- Co-authored-by: Conengmo <[email protected]>
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docs/advanced_guide/custom_panes.md

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@@ -30,7 +30,7 @@ We'll make an example to show how the GeoJson we add hides any labels
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underneath.
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```{code-cell} ipython3
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m = folium.Map([43, -100], zoom_start=4, tiles="stamentoner")
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m = folium.Map([43, -100], zoom_start=4)
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folium.GeoJson(geo_json_data, style_function=style_function).add_to(m)
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@@ -43,14 +43,14 @@ Now we'll create a custom pane and add a tile layer that contains only labels.
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The labels will show on top off the geojson.
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```{code-cell} ipython3
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m = folium.Map([43, -100], zoom_start=4, tiles="stamentonerbackground")
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m = folium.Map([43, -100], zoom_start=4, tiles="cartodbpositronnolabels")
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folium.GeoJson(geo_json_data, style_function=style_function).add_to(m)
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folium.map.CustomPane("labels").add_to(m)
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# Final layer associated to custom pane via the appropriate kwarg
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folium.TileLayer("stamentonerlabels", pane="labels").add_to(m)
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folium.TileLayer("cartodbpositrononlylabels", pane="labels").add_to(m)
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m
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```

docs/advanced_guide/subplots.md

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@@ -20,7 +20,7 @@ subplot1 = fig.add_subplot(1, 2, 1)
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subplot2 = fig.add_subplot(1, 2, 2)
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subplot1.add_child(
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folium.Map([0, 0], tiles="stamenwatercolor", zoom_start=1)
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folium.Map([0, 0], zoom_start=1)
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)
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subplot2.add_child(
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folium.Map([46, 3], tiles="OpenStreetMap", zoom_start=5)
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# Create two maps.
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m = folium.Map(
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location=[0, 0],
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tiles="stamenwatercolor",
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zoom_start=1,
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position="absolute",
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left="0%",

docs/getting_started.md

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@@ -58,7 +58,7 @@ m.save("index.html")
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Choosing a tileset
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------------------
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The default tiles are set to `OpenStreetMap`, but a selection of tilesets from Stamen and CartoDB are also built in.
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The default tiles are set to `OpenStreetMap`, but a selection of tilesets are also built in.
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```{code-cell} ipython3
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folium.Map((45.5236, -122.6750), tiles="cartodb positron")
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tooltip. You can also pick colors and icons.
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```{code-cell} ipython3
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m = folium.Map([45.35, -121.6972], zoom_start=12, tiles="Stamen Terrain")
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m = folium.Map([45.35, -121.6972], zoom_start=12)
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folium.Marker(
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location=[45.3288, -121.6625],

docs/index.rst

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@@ -22,7 +22,7 @@ It enables both the binding of data to a map for choropleth visualizations
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as well as passing rich vector/raster/HTML visualizations as markers on the map.
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The library has a number of built-in tilesets from OpenStreetMap,
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Mapbox, and Stamen, and supports custom tilesets.
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Mapbox, etc, and supports custom tilesets.
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Folium supports both Image, Video, GeoJSON and TopoJSON overlays and has a
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number of vector layers built-in.
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docs/user_guide/plugins/heatmap.md

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@@ -12,7 +12,7 @@ data = (
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import folium
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from folium.plugins import HeatMap
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m = folium.Map([48.0, 5.0], tiles="stamentoner", zoom_start=6)
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m = folium.Map([48.0, 5.0], zoom_start=6)
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HeatMap(data).add_to(m)
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docs/user_guide/plugins/heatmap_with_time.md

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@@ -44,7 +44,7 @@ for time_entry in data:
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```
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```{code-cell} ipython3
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m = folium.Map([48.0, 5.0], tiles="stamentoner", zoom_start=6)
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m = folium.Map([48.0, 5.0], zoom_start=6)
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hm = folium.plugins.HeatMapWithTime(data)
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### Options
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Now we show that the time index can be specified, allowing a more meaningful representation of what the time steps mean. We also enable the 'auto_play' option and change the maximum opacity. See the docmentation for a full list of options that can be used.
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Now we show that the time index can be specified, allowing a more meaningful representation of what the time steps mean. We also enable the 'auto_play' option and change the maximum opacity. See the documentation for a full list of options that can be used.
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```{code-cell} ipython3
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from datetime import datetime, timedelta
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```
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```{code-cell} ipython3
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m = folium.Map([48.0, 5.0], tiles="stamentoner", zoom_start=6)
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m = folium.Map([48.0, 5.0], zoom_start=6)
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hm = folium.plugins.HeatMapWithTime(data, index=time_index, auto_play=True, max_opacity=0.3)
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docs/user_guide/plugins/mini_map.md

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@@ -23,7 +23,7 @@ m
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```{code-cell} ipython3
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m = folium.Map(location=(30, 20), zoom_start=4)
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MiniMap(tile_layer="Stamen Toner").add_to(m)
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MiniMap().add_to(m)
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m
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```
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docs/user_guide/plugins/tag_filter_button.md

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@@ -25,7 +25,7 @@ Then, create the `TagFilterButton` object and let it know which tags you want to
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from folium.plugins import TagFilterButton
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# Create map and add the data with additional parameter tags as the segmentation
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m = folium.Map([48., 5.], tiles='stamentoner', zoom_start=7)
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m = folium.Map([48., 5.], zoom_start=7)
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for i, latlng in enumerate(data):
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category = category_column[i]
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folium.Marker(

docs/user_guide/plugins/timeslider_choropleth.md

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@@ -155,7 +155,7 @@ import folium
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from folium.plugins import TimeSliderChoropleth
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m = folium.Map([0, 0], tiles="Stamen Toner", zoom_start=2)
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m = folium.Map([0, 0], zoom_start=2)
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TimeSliderChoropleth(
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gdf.to_json(),
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By default the timeslider starts at the beginning. You can also select another timestamp to begin with using the `init_timestamp` parameter. Note that it expects an index to the list of timestamps. In this example we use `-1` to select the last timestamp.
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```{code-cell} ipython3
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m = folium.Map([0, 0], tiles="Stamen Toner", zoom_start=2)
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m = folium.Map([0, 0], zoom_start=2)
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TimeSliderChoropleth(
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gdf.to_json(),

docs/user_guide/raster_layers/image_overlay.md

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@@ -11,7 +11,7 @@ If you have a static image file on your disk, you can simply draw it on the map.
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import os
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import folium
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m = folium.Map([37, 0], zoom_start=1, tiles="stamentoner")
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m = folium.Map([37, 0], zoom_start=1)
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merc = os.path.join("data", "Mercator_projection_SW.png")
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@@ -46,7 +46,7 @@ A few remarks:
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You can also provide simply URL. In this case, the image will not be embedded in folium's output.
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```{code-cell} ipython3
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m = folium.Map([37, 0], zoom_start=1, tiles="stamentoner")
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m = folium.Map([37, 0], zoom_start=1)
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folium.raster_layers.ImageOverlay(
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image="https://upload.wikimedia.org/wikipedia/commons/f/f4/Mercator_projection_SW.jpg",

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