However, the preferred way is to use conda since it provides pre-built binaries for all platforms (Windows, Mac, Linux). Geopandas can be installed with conda, pipOr directly from the source. Shapley is a Python package for manipulation and analyzing geometric objects in the Cartesian plane. In a way, GeoPandas combines the power of pandas with Shapley.
It extends the functionalities of a pandas’ DataFrame, thereby making it possible to handle spatial data within pandas →hence the name.
Import streamlit as st import geopandas as gpd import pandas as pd import matplotlib.pyplot as plt import leafmap.foliumap as leafmap st.set_page_config(page_title = 'Dashboard', layout = 'wide') st.title( 'Highway Dashboard') st.sidebar.title( 'About') st.( 'Explore the Highway Statistics') data_url = '' gpkg_file = 'karnataka.gpkg' csv_file = 'highway_lengths_by_district.csv' def read_gdf(url, layer): gdf = gpd.read_file(url, layer =layer) return gdf def read_csv(url): df = pd.read_csv(url) return df gpkg_url = data_url + gpkg_file csv_url = data_url + csv_file districts_gdf = read_gdf(gpkg_url, 'karnataka_districts') roads_gdf = read_gdf(gpkg_url, 'karnataka_highways') lengths_df = read_csv(csv_url) # Create the chart districts = districts_ district = st.lectbox( 'Select a District', districts) overlay = st.sidebar.checkbox( 'Overlay roads') district_lengths = lengths_df = district] fig, ax = plt.subplots( 1, 1) district_ot(kind = 'bar', ax =ax, color =, ylabel = 'Kilometers', xlabel = 'Category') ax.get_xaxis().set_ticklabels() stats = st.sidebar.GeoPandas is a widely used open-source library for working and manipulating geospatial data in Python. Let’s add a checkbox that allows the user to overlay the roads on the map. We can selectively load certain layers on the map using a user-input widget.Import folium import requests # Replace Variables Below # origin = ( 37.7749, - 122.4194) origin_name = 'San Francisco' destination = ( 40.661, - 73.944) destination_name = 'New York' map_center = ( 39.83, - 98.58) ORS_API_KEY = '' # parameters = ) m_streamlit = m.to_streamlit( 600, 600)
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