def build_map():
logger.info("Preparing data")
data = get_data()
logger.info("Initializing map")
m = folium.Map(location=INITIAL_ZOOM, zoom_start=6, tiles="cartodbpositron")
logger.info("Creating GeoJSON")
events_map = folium.GeoJson(
data,
name="Events documented",
style_function=None,
tooltip=folium.GeoJsonTooltip(
aliases=["Name", "Last Name", "Occupation", "Violence Type"],
fields=["first_name", "last_name", "occupation", "method"],
localize=True,
),
).add_to(m)
# add a search by first names
logger.info("Creating search box for names")
namesearch = Search(
layer=events_map,
geom_type="Point",
placeholder="Escribe un nombre",
collapsed=False,
search_label="first_name",
search_zoom=12,
# weight=3
).add_to(m)
# add a search by last name
logger.info("Creating search box for last names")
lastnamesearch = Search(
layer=events_map,
geom_type="Point",
placeholder="Escribe un apellido",
collapsed=False,
search_label="last_name",
search_zoom=12,
).add_to(m)
logger.info("Saving to index.html")
m.save("./index.html")
def draw_map(connection):
# https://georgetsilva.github.io/posts/mapping-points-with-folium/
# https://geoffboeing.com/2015/10/exporting-python-data-geojson/
# https: // stackoverflow.com / questions / 60585689 / how - to - display - information - in -geojson - popup - python
# https://stackoverflow.com/questions/50998176/6-millions-of-markers-in-folium-leaflet-map
start_time = time.time()
df = mapper.retrieve_points(connection)
cols = df.columns
raw_json = mapper.df_to_geojson(df, cols)
locations = df[['latitude', 'longitude']]
location_list = locations.values.tolist()
print(df.head())
with open('searchdata.json', 'w') as fp:
json.dump(raw_json, fp)
print("--- %s seconds ---" % (time.time() - start_time))
print('Drawing Map...')
start_time = time.time()
m = folium.Map(location=[54.968220, -1.868530],
zoom_start=7,
prefer_canvas=True) # lat/long
with open('searchdata.json') as access_json:
read_content = json.load(access_json)
geojson_obj = folium.GeoJson(
'searchdata.json',
popup=folium.GeoJsonPopup(fields=cols.tolist())).add_to(m)
Search(layer=geojson_obj,
search_zoom=12,
search_label='name',
collapsed=False).add_to(m)
folium.LayerControl().add_to(m)
folium.plugins.LocateControl().add_to(m)
m.save('map.html')
# mapper.minify()
print("--- %s seconds ---" % (time.time() - start_time))
print('\nOpen \'map.html\' in a browser to view generated map')
def update_map():
area = pd.read_csv(
"https://data.nsw.gov.au/data/dataset/97ea2424-abaf-4f3e-a9f2-b5c883f42b6a/resource/2776dbb8-f807-4fb2-b1ed-184a6fc2c8aa/download/covid-19-cases-by-notification-date-location-and-likely-source-of-infection.csv"
)
postcodes = pd.read_csv("australian_postcodes.csv")
testing = pd.read_csv(
"https://data.nsw.gov.au/data/dataset/5424aa3b-550d-4637-ae50-7f458ce327f4/resource/227f6b65-025c-482c-9f22-a25cf1b8594f/download/covid-19-tests-by-date-and-location-and-result.csv"
)
area = area.rename(columns={"likely_source_of_infection": "Source"})
testing = testing.rename(columns={"result": "Test Result"})
testing['Test Result'] = testing['Test Result'].replace({
'Tested & excluded':
'Negative Test',
'Case - Confirmed':
'Positive Test'
})
area['Source'] = area['Source'].replace({
'Locally acquired - contact of a confirmed case and/or in a known cluster':
'Local (Known Source)',
'Locally acquired - source not identified':
'Local (Unknown Source)',
'Under investigation':
'Under Investigation'
})
area = area.dropna()
area = area.merge(postcodes, on='postcode', how='inner')
source_area = area.copy()
source_area = source_area.groupby(
['notification_date', 'postcode', 'Source']).count()
source_area = source_area.reset_index()
testing_area = testing.dropna()
testing_area = testing_area.groupby(
['test_date', 'postcode', 'Test Result']).count()
testing_area = testing_area.reset_index()
chart_area = area.copy()
chart_area = chart_area.groupby(['notification_date', 'postcode']).count()
chart_area = chart_area.reset_index()
area['Cases'] = area['postcode'].map(area['postcode'].value_counts())
area = area.sort_values('notification_date').drop_duplicates('postcode',
keep='last')
geometry = [Point(xy) for xy in zip(area.long, area.lat)]
a = area.drop(['long', 'lat'], axis=1)
crs = {'init': 'epsg:4326'}
gdf = geopandas.GeoDataFrame(a, crs=crs, geometry=geometry)
#FOLIUM START
start_coords = (-33.86051951, 151.2015802)
m = folium.Map(location=start_coords,
zoom_start=14,
min_zoom=8,
width='100%',
height='100%')
for index, row in area.iterrows():
source_subset = source_area[source_area['postcode'] == row['postcode']]
test_subset = testing_area[testing_area['postcode'] == row['postcode']]
subset = chart_area[chart_area['postcode'] == row['postcode']]
subset['cumul'] = subset['long'].cumsum()
chart = alt.Chart(source_subset).mark_bar(
cornerRadiusTopLeft=3, cornerRadiusTopRight=3).encode(
x=alt.X('notification_date', axis=alt.Axis(title='Date')),
y=alt.Y('long', axis=alt.Axis(title='New Cases')),
color=alt.Color('Source', legend=alt.Legend(orient="left")),
tooltip=[
alt.Tooltip('notification_date', title="Date"),
alt.Tooltip('Source', title="Source"),
alt.Tooltip('long', title="New Cases")
]).properties(title="New Cases in Postcode " +
str(int(row['postcode'])) + " (Latest Case: " +
row['notification_date'] + ")",
width=500,
height=200)
cum_chart = alt.Chart(subset).mark_line(point=True).encode(
x=alt.X('notification_date', axis=alt.Axis(title='Date')),
y=alt.Y('cumul', axis=alt.Axis(title='Total Cases (Cumulative)')),
tooltip=[
alt.Tooltip('notification_date', title="Date"),
alt.Tooltip('cumul', title="Total Cases")
]).properties(title="Total Cases in Postcode " +
str(int(row['postcode'])) + " (Current Total: " +
str(int(row['Cases'])) + ")",
width=500,
height=200)
#test_chart = alt.Chart(test_subset).mark_bar(cornerRadiusTopLeft=3,
#cornerRadiusTopRight=3).encode(
#x=alt.X('test_date', axis=alt.Axis(title='Date')),
#y=alt.Y('lga_code19', axis=alt.Axis(title='Tests Conducted')),
#color = alt.Color('Test Result', legend = alt.Legend(orient="left")),
#tooltip = [alt.Tooltip('test_date', title = "Date"), alt.Tooltip('Test Result', title = "Test Result"), alt.Tooltip('lga_code19', title = "Number")]
#).properties(
# title = "Number of Tests in Postcode "+str(int(row['postcode']))+" (Total Tested: "+str(int(test_subset['lga_code19'].sum()))+")"+" - Testing data decomissioned as of 8th June",
# width = 1000,
# height = 200
#)
#chart = alt.hconcat(test_chart, chart, cum_chart).resolve_scale(color='independent')
chart = alt.hconcat(chart,
cum_chart).resolve_scale(color='independent')
chart.save('chart.html', embed_options={'renderer': 'svg'})
with open('chart.html', 'r') as f:
html = f.read()
iframe = IFrame(html, height=330, width=600)
popup = folium.Popup(iframe, max_width=2650)
#day
if row['notification_date'] >= '2020-09-04':
marker_color = 'red'
fill_color = 'red'
#week
elif row['notification_date'] >= '2020-08-28':
marker_color = 'blue'
fill_color = 'blue'
else:
marker_color = 'green'
fill_color = 'green'
folium.Circle(location=[row['lat'], row['long']],
tooltip=row['name'],
radius=row['Cases'] * 10,
color=marker_color,
fill=True,
fill_color=fill_color,
popup=popup).add_to(m)
print(row['postcode'], 'done')
citygeo = folium.GeoJson(gdf, show=False, name='Marker').add_to(m)
pcsearch = Search(layer=citygeo,
geom_type='Point',
placeholder='Search for an NSW postcode',
collapsed=True,
search_label='postcode',
position='topleft',
search_zoom=14).add_to(m)
subsearch = Search(layer=citygeo,
geom_type='Point',
placeholder='Search for an NSW suburb',
collapsed=True,
search_label='name',
position='topright',
search_zoom=14).add_to(m)
folium.LayerControl().add_to(m)
m.save('templates/index.html')
print('done')
folium.Marker([lat, lon],
tooltip=r['Name'],
icon=folium.Icon(color='red', icon='cutlery')).add_to(groupA)
for i, r in df2.iterrows():
lon, lat = coordTransform.bd09_to_gcj02(r['lon'], r['lat'])
folium.Marker(
[lat, lon],
tooltip=r['Name'],
icon=folium.DivIcon(
icon_size=(100, 72),
icon_anchor=(0, 0),
html=
'<div style="font-size: 12px;color: organe; background: white;">' +
f"{r['Name']}" + '</div>')
).add_to(
groupB
) #,icon=folium.Icon(color='red', icon='cutlery')icon=folium.Icon(color='red', icon='cutlery'),icon=DivIcon(icon_size=(150,36),icon_anchor=(0,0),html='<div style="font-size: 24pt">Test</div>')
folium.Marker([lat, lon],
tooltip=r['Name'],
icon=folium.Icon(color='gray',
icon='cutlery')).add_to(groupB)
map_f.add_child(groupA)
map_f.add_child(groupB)
map_f.add_child(bankgroup)
folium.LayerControl().add_to(map_f)
Search(bankgroup, geom_type='Points', search_zoom=None,
position='topleft').add_to(map_f)
map_f.save('bank_g5_all.html')
"name": "two"
},
"geometry": {
"type": "Point",
"coordinates": [19.0402, 47.4979]
}
}, {
"type": "Feature",
"properties": {
"name": "three"
},
"geometry": {
"type": "Point",
"coordinates": [25.4858, 42.7339]
}
}]
}
geojson_obj = folium.GeoJson(points).add_to(m)
statesearch = Search(layer=geojson_obj,
geom_type='Point',
placeholder="Search",
collapsed=False,
search_label='name',
search_zoom=4,
position='topright').add_to(m)
m.save('example.html')
webbrowser.open("example.html", m)
def make_map():
SEATTLE_COORDINATES = (47.6062, -122.3321)
zoom_start = 12
# create empty map zoomed in on San Francisco
map = folium.Map(location=SEATTLE_COORDINATES, zoom_start=zoom_start, control_scale=True)
# add neighborhoods on top of this. This is an experiment to be replaced with a polygon geojson
geo_json_data = json.load(open('neighborhoods.geojson'))
# parcel_data = json.load(open('Zoned_Parcels_forJSON.json'))
# parcel2_data = json.load(open('Zoned_Parcels_forJSON_Featur.json'))
# regular style of polygons
def style_function(feature):
return {
'weight': 2,
'dashArray': '5, 5',
'fillOpacity': 0,
'lineOpacity': 1,
}
def highlight_function(feature):
return {
'fillColor': 'blue',
'weight': 2,
'lineColor': 'black',
'lineWeight': 2,
'dashArray': '5, 5',
'fillOpacity': 0.5,
'lineOpacity': 1,
}
# apply the neighborhood outlines to the map
neighborhoods = folium.features.GeoJson(geo_json_data,
style_function=style_function,
highlight_function=highlight_function,
)
# parcels = folium.features.GeoJson(parcel_data,
# style_function=style_function,
# highlight_function=highlight_function,
# )
neighborhoods2 = folium.map.FeatureGroup(name="neighborhoods2", overlay=True, control=True, show=True,)
with open("neighborhoods.geojson") as f:
geo_json_data_test = json.load(f)
for i in range(0,len(geo_json_data_test["features"])):
c = folium.features.GeoJson(geo_json_data_test["features"][i]["geometry"],
name=(geo_json_data_test["features"][i]["properties"]["name"]),
style_function=style_function,
highlight_function=highlight_function,)
folium.Popup(geo_json_data_test["features"][i]["properties"]["name"], geo_json_data_test["features"][i]["properties"]["nhood"]).add_to(c)
neighborhoods2.add_child(c)
import pdb; pdb.set_trace()
neighborhoods2.add_to(map)
print(neighborhoods)
print(neighborhoods2)
neighborhoodsearch = Search(
layer=neighborhoods2,
geom_type='Polygon',
placeholder='Search for a neighborhood name',
collapsed=False,
search_label='name',
weight=3,
fillColor="black",
fillOpacity = 0.6
).add_to(map)
# We need to fix kwargs and popups of polygons iterating through geojson
# print(geo_json_data[1,:])
# geo_json_data_df = pd.DataFrame.from_dict(geo_json_data)
# geo_json_data_df.to_csv(r'/Users/Anaavu/Documents/GitHub/ADUniverse/app/geo_json_data_df.csv')
# add a marker for every record in the filtered data, use a clustered view
for _, row in data[0:MAX_RECORDS].iterrows():
popup = folium.Popup("Feasibility: " + str(row['Random Number']) +
"<br> Address: " + str(row['Address']), max_width=300)
# html_str = """
# <a href="https://www.ibm.com/" target="_blank"> Details.</a>
# """
# iframe = folium.IFrame(html=html_str, width=100, height=50)
# popup = folium.Popup(iframe, max_width=2650)
folium.Marker([row['Latitude'], row['Longitude']], popup=popup).add_to(map)
# popup = folium.Popup(i['name'])
# c.add_to(map)
map.save("map.html")
lon, lat = coordTransform.bd09_to_gcj02(r['lon'], r['lat'])
folium.Marker(
[lat, lon],
tooltip=r['Name'],
icon=folium.DivIcon(
icon_size=(100, 72),
icon_anchor=(0, 0),
html=
'<div style="font-size: 12px;color: organe; background: white;">' +
f"{r['Name']}" + '</div>')
).add_to(
groupB
) #,icon=folium.Icon(color='red', icon='cutlery')icon=folium.Icon(color='red', icon='cutlery'),icon=DivIcon(icon_size=(150,36),icon_anchor=(0,0),html='<div style="font-size: 24pt">Test</div>')
folium.Marker([lat, lon],
tooltip=r['Name'],
icon=folium.Icon(color='gray',
icon='cutlery')).add_to(groupB)
citysearch = Search(layer=geo,
geom_type='Point',
placeholder='Search',
search_zoom=16,
collapsed=True,
search_label='name').add_to(map_f)
#
map_f.add_child(groupA)
map_f.add_child(groupB)
map_f.add_child(bankgroup)
# map_f.add_child(all)
folium.LayerControl().add_to(map_f)
map_f.save('bank_g5_with_search.html')
zoom_start=16.5
)
geojson_obj = folium.GeoJson(points, name="마커 보기").add_to(m)
for i in points["features"]:
lati = i["geometry"]["coordinates"][1]
longti = i["geometry"]["coordinates"][0]
name = i["properties"]["name"]
html = Template("""
{{name}}<br>
</p>
""").render(name=name) # html 형태로 마커 클릭 시 팝업 추가
popup = folium.Popup(html, max_width=200)
folium.Marker(location=[lati, longti], popup=popup).add_to(
m) # html 형태로 마커 클릭 시 팝업 추가
Search(layer=geojson_obj,
geom_type='Point',
placeholder="장소 검색",
search_label='name',
search_zoom=17,
collapsed=False,
position='topright').add_to(m) # 장소 검색 기능 추가
plugins.LocateControl().add_to(m) # gps 기능 추가
def make_html():
m.save('spot_search.html')