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solara-geospatialDashboard / pages /Servicios_apoyo.py

FranciscoGS

Update pages/Servicios_apoyo.py

4e22767 verified 4 months ago

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	#Libraries
	import solara
	from ipyleaflet import Map, GeoJSON, GeoData, LayersControl, Marker, MarkerCluster, basemaps, Choropleth
	from branca.colormap import linear
	import plotly.express as px
	import matplotlib
	import geopandas as gpd
	import pandas as pd
	import numpy as np
	from shapely import wkt
	import json
	import re

	#Read Pois Data Set
	df = pd.read_csv('./data/pois_final_control.csv')
	df = df[(df['EnEstudio'] == True)]
	df = df[df['Geometry'].notnull()]
	df['geometry'] = df['Geometry'].apply(wkt.loads)
	pois = gpd.GeoDataFrame(df, geometry='geometry')
	pois = pois.set_crs(epsg=4326, inplace=True)
	pois = pois.drop('EnEstudio', axis=1)
	pois = pois.drop('Geometry', axis=1)

	#Read H3 Data Set
	df1 = pd.read_csv('./data/poiscount_r8hex_large.csv', index_col=0)
	df1 = df1[df1['Conteo'] > 0]
	df1 = df1.drop('EnEstudio', axis=1)
	df1['geometry'] = df1['geometry'].apply(wkt.loads)
	h3 = gpd.GeoDataFrame(df1, geometry='geometry')
	h3 = h3.set_crs(epsg=4326, inplace=True)

	#Set controls values
	cantones = [str(k) for k in pois['Canton'].unique().tolist()]
	categorias = [str(k) for k in pois['Categoria'].unique().tolist()]
	canton = solara.reactive('QUITO')
	categoria = solara.reactive('salud')
	limit = solara.reactive(2500)

	#Filter function
	def data_filter(df, city, category):
	df_filtered = df.loc[df['Canton']==city]
	df_filtered = df_filtered[df_filtered['Categoria']==category]
	return df_filtered

	#Map function
	def ipyleaflet_map(geo_df, h3_df, h3_geojson):
	# Define map center and initial zoom level
	center = (geo_df.geometry.y.mean(), geo_df.geometry.x.mean())
	zoom = 11
	# Create the map
	m = Map(center=center, zoom=zoom)

	# Create GeoData from the GeoDataFrame
	services = GeoData(
	geo_dataframe=geo_df,
	style={
	'color': 'black',
	'radius': 7,
	'fillColor': '#3366cc',
	'opacity': 0.5,
	'weight': 1.9,
	'dashArray': '2',
	'fillOpacity': 0.6
	},
	hover_style={
	'fillColor': 'red',
	'fillOpacity': 0.2
	},
	point_style={
	'radius': 7,
	'color': 'red',
	'fillOpacity': 0.8,
	'fillColor': 'blue',
	'weight': 3
	},
	name='Servicios de Apoyo'
	)

	#h3 Density
	colormap = linear.YlOrRd_04.scale(min(h3_df['Conteo']), max(h3_df['Conteo']))
	choro_data = dict(zip(h3_df.index.astype(str), h3_df['Conteo']))
	h3_choropleth = Choropleth(
	geo_data=h3_geojson,
	choro_data=choro_data,
	colormap=colormap,
	border_color='black',
	style={'fillOpacity': 0.8, 'dashArray': '5, 5'},
	name='Densidad'
	)

	# Add GeoData to the map
	m.add_layer(services)
	m.add_layer(h3_choropleth)

	# Add Cluster Markers
	markers = [Marker(location=(point.y, point.x)) for point in geo_df.geometry]

	# Create and add MarkerCluster to the map
	marker_cluster = MarkerCluster(markers=markers, name='Cluster Markers')
	m.add_layer(marker_cluster)

	# Add layer control
	m.add_control(LayersControl())

	# Display the map
	display(m)

	#Interactive bar chart function
	def type_chart_plotly(df):
	tipo_counts = df['Tipo'].value_counts().sort_values(ascending=True)

	fig = px.bar(tipo_counts, orientation='h',
	x=tipo_counts.values, y=tipo_counts.index,
	labels={'x': 'Conteo', 'y': 'Tipo'},
	title='Servicios')
	solara.FigurePlotly(fig)

	#Main panel layout
	@solara.component
	def View():
	dff = data_filter(pois, canton.value, categoria.value)
	h3f = data_filter(h3, canton.value, categoria.value)
	geo_json_H3 = json.loads(h3f.to_json())
	row_count = len(dff)
	if row_count > limit.value:
	solara.Warning(f"Only showing the first {limit.value} of {row_count:,} services on map")
	ipyleaflet_map(dff.iloc[:limit.value], h3f, geo_json_H3)
	if row_count > 0:
	with solara.Card(''):
	type_chart_plotly(dff)
	else:
	solara.Warning("You filtered out all the data, no charts shown")

	#Controls
	@solara.component
	def Controls():
	solara.Select('Cantón', values=cantones, value=canton)
	solara.Select('Categoría', values=categorias, value=categoria)
	#solara.SelectMultiple('Fuente', all_values=fuentes, values=fuente)
	solara.Text("Maximum number of pois to show on map")
	solara.SliderInt('', value=limit, min=1, max=5000)

	#Dashboard Layout
	@solara.component
	def Page():
	with solara.Column():
	solara.Title('Servicios de Apoyo para Migrantes')
	with solara.Sidebar():
	with solara.Card('Filtros'):
	with solara.Column():
	Controls()
	View()
	Page()