105 vector time slider

Visualizing vector data with time attributes

Uncomment the following line to install leafmap if needed.

In [1]:

# %pip install -U leafmap

# %pip install -U leafmap

In [2]:

from leafmap import leafmap
import geopandas as gpd

from leafmap import leafmap import geopandas as gpd

In [3]:

url = "https://github.com/opengeos/datasets/releases/download/us/zillow_home_value_index_by_county_ca.geojson"

url = "https://github.com/opengeos/datasets/releases/download/us/zillow_home_value_index_by_county_ca.geojson"

In [4]:

data = gpd.read_file(url)
data.head(2)

data = gpd.read_file(url) data.head(2)

Out[4]:

	place	RegionID	SizeRank	RegionName	RegionType	StateName	State	Metro	StateCodeFIPS	MunicipalCodeFIPS	...	2024-06-30	2024-07-31	2024-08-31	2024-09-30	2024-10-31	2024-11-30	2024-12-31	2025-01-31	index	geometry
0	geoId/06037	3101	0	Los Angeles County	county	CA	CA	Los Angeles-Long Beach-Anaheim, CA	06	037	...	853328	856958	862129	868712	873819	877921	881313	880547	218.0	MULTIPOLYGON (((-118.67855 33.02634, -118.6748...
1	geoId/06073	2841	4	San Diego County	county	CA	CA	San Diego-Chula Vista-Carlsbad, CA	06	073	...	931835	933267	932833	932389	931683	931874	932380	932486	212.0	POLYGON ((-117.61109 33.33401, -117.57155 33.3...

2 rows × 313 columns

In [5]:

legend_dict = {
    "[ 0,  200000]": "#e6f3ff",  # Very light blue
    "( 200000,  400000]": "#deebf7",  # Light blue
    "( 400000,  600000]": "#9ecae1",  # Medium blue
    "( 600000,  800000]": "#4292c6",  # Medium-dark blue
    "( 800000, 1000000]": "#2171b5",  # Dark blue
    "( 1000000, 2000000]": "#084594",  # Very dark blue
    "Nodata": "#f0f0f0",  # Light gray
}

legend_dict = { "[ 0, 200000]": "#e6f3ff", # Very light blue "( 200000, 400000]": "#deebf7", # Light blue "( 400000, 600000]": "#9ecae1", # Medium blue "( 600000, 800000]": "#4292c6", # Medium-dark blue "( 800000, 1000000]": "#2171b5", # Dark blue "( 1000000, 2000000]": "#084594", # Very dark blue "Nodata": "#f0f0f0", # Light gray }

In [6]:

gdf = leafmap.color_code_dataframe(data, legend_dict=legend_dict)
gdf.head(2)

gdf = leafmap.color_code_dataframe(data, legend_dict=legend_dict) gdf.head(2)

Out[6]:

	place	RegionID	SizeRank	RegionName	RegionType	StateName	State	Metro	StateCodeFIPS	MunicipalCodeFIPS	...	2024-06-30	2024-07-31	2024-08-31	2024-09-30	2024-10-31	2024-11-30	2024-12-31	2025-01-31	index	geometry
0	geoId/06037	3101	#e6f3ff	Los Angeles County	county	CA	CA	Los Angeles-Long Beach-Anaheim, CA	06	037	...	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#e6f3ff	MULTIPOLYGON (((-118.67855 33.02634, -118.6748...
1	geoId/06073	2841	#e6f3ff	San Diego County	county	CA	CA	San Diego-Chula Vista-Carlsbad, CA	06	073	...	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#2171b5	#e6f3ff	POLYGON ((-117.61109 33.33401, -117.57155 33.3...

2 rows × 313 columns

In [7]:

m = leafmap.Map()
m

m = leafmap.Map() m

In [8]:

m.add_gdf_time_slider(gdf, time_interval=0.05, zoom_to_layer=True)
m.add_legend(title="Median Home Value", legend_dict=legend_dict)

m.add_gdf_time_slider(gdf, time_interval=0.05, zoom_to_layer=True) m.add_legend(title="Median Home Value", legend_dict=legend_dict)