Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

docs: Resolve geopandas.read_file(...) warnings #3795

Merged
merged 1 commit into from
Feb 6, 2025
Merged

docs: Resolve geopandas.read_file(...) warnings #3795

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 5 additions & 5 deletions doc/user_guide/marks/geoshape.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -254,7 +254,7 @@ Here we lookup the field ``rate`` from the ``df_us_unemp`` DataFrame, where the
from vega_datasets import data
import geopandas as gpd

gdf_us_counties = gpd.read_file(data.us_10m.url, driver='TopoJSON', layer='counties')
gdf_us_counties = gpd.read_file(data.us_10m.url, layer="counties")
df_us_unemp = data.unemployment()

alt.Chart(gdf_us_counties).mark_geoshape().transform_lookup(
Expand Down Expand Up @@ -470,7 +470,7 @@ regular faceting will not work for geographic visualization:
.. altair-plot::

source = data.population_engineers_hurricanes().melt(id_vars=['state', 'id'])
us_states = gpd.read_file(data.us_10m.url, driver='TopoJSON', layer='states')
us_states = gpd.read_file(data.us_10m.url, layer="states")
gdf_comb = gpd.GeoDataFrame(source.join(us_states, on='id', rsuffix='_y'))

alt.Chart(gdf_comb).mark_geoshape().encode(
Expand Down Expand Up @@ -524,7 +524,7 @@ populous states. Using an ``alt.selection_point()`` we define a selection parame
import geopandas as gpd

# load the data
us_states = gpd.read_file(data.us_10m.url, driver="TopoJSON", layer="states")
us_states = gpd.read_file(data.us_10m.url, layer="states")
us_population = data.population_engineers_hurricanes()[["state", "id", "population"]]

# define a pointer selection
Expand Down Expand Up @@ -583,8 +583,8 @@ We use here an elegant way to access the nested point coordinates from the geome
import geopandas as gpd

# load data
gdf_quakies = gpd.read_file(data.earthquakes.url, driver="GeoJSON")
gdf_world = gpd.read_file(data.world_110m.url, driver="TopoJSON")
gdf_quakies = gpd.read_file(data.earthquakes.url)
gdf_world = gpd.read_file(data.world_110m.url, layer="countries")

# define parameters
range0 = alt.binding_range(min=-180, max=180, step=5, name='rotate longitude ')
Expand Down
4 changes: 2 additions & 2 deletions tests/examples_arguments_syntax/interval_selection_map_quakes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,8 @@
import geopandas as gpd

# load data
gdf_quakies = gpd.read_file(data.earthquakes.url, driver="GeoJSON")
gdf_world = gpd.read_file(data.world_110m.url, driver="TopoJSON")
gdf_quakies = gpd.read_file(data.earthquakes.url)
gdf_world = gpd.read_file(data.world_110m.url, layer="countries")

# defintion for interactive brush
brush = alt.selection_interval(
Expand Down
4 changes: 2 additions & 2 deletions tests/examples_methods_syntax/interval_selection_map_quakes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,8 @@
import geopandas as gpd

# load data
gdf_quakies = gpd.read_file(data.earthquakes.url, driver="GeoJSON")
gdf_world = gpd.read_file(data.world_110m.url, driver="TopoJSON")
gdf_quakies = gpd.read_file(data.earthquakes.url)
gdf_world = gpd.read_file(data.world_110m.url, layer="countries")

# defintion for interactive brush
brush = alt.selection_interval(
Expand Down