ipyleaflet | A Jupyter - Leaflet.js bridge | Data Visualization library
kandi X-RAY | ipyleaflet Summary
kandi X-RAY | ipyleaflet Summary
A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook.
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Top functions reviewed by kandi - BETA
- Deprecated
- Create TileLayer from basemap
- Substitute new layers
- Update the data
- Applies a style to a feature
- Get the data
- Fit the model to the given bounds
- Fit bounds
- Block until a value has changed
- Convert Dataset to JSON format
- Convert dataset to json
- Add a new length unit
- Add a unit
- Add a new area unit
- Observe zoom control
- Observe attribution control
- Default layers
ipyleaflet Key Features
ipyleaflet Examples and Code Snippets
Lines of Code : 4License : Strong Copyleft (CC BY-SA 4.0)
Copy# ugly fix to remove shadow from map custom widgets
from IPython.display import display, HTML
display(HTML(""))
df = dft.groupby('bin').agg(latitude_mean=('latitude','mean'),
longitude_mean=('longitude','mean'),
count=('latitude','count'))
#https://stackoverflow.com/a/50028155/2901002
a, b = 1import sys
import json
from PyQt5.QtWidgets import QApplication, QVBoxLayout, QWidget, QLabel
from PyQt5 import QtWebEngineWidgets
from ipyleaflet import Map, Marker, LayersControl, basemaps
from ipywidgets import HTML, IntSlider
from ipydef get_callback(marker, html):
def callback(*args, **kwargs):
html.value = '''
Glider Mission:
{}
'''.format(marker.name)
return callback
marker.on_mouseover(get_callback(markermap_df = gpd.read_file(fp)
map_df.crs = 4326 # this line
map_df = map_df.to_crs(epsg=3857)
ax = map_df.plot(figsize=(10, 10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax, zoom=12, source=ctx.providers.Stamen.TonerLite)
ax.set_axis_off()button0 = widgets.Checkbox(
description="Click to display",
value=True,
indent=False
)
button1 = widgets.Checkbox(
description="",
value=True,
indent=False
)
button2 = widgets.Checkbox(
description="Select",
from ipyleaflet import Map, Polygon
poligons = [[(38.844185,-4.804621),(39.241299,-1.899833),(40.74308,-2.205491),(40.34742,-5.17429),(38.844185,-4.804621)],
[(39.365192,-1.941078),(40.867912,-1.567062),(41.276688,-4.670904),(geom_str = []
for i in test2: # same for multipolygon.geoms
print(type(i), i) # <- What happens here ? Is i a list ? a tuple ?
test = str(i)
geom_str.append(test)
geom_str
{"PLANET_API_KEY":""}
from ipyleaflet import WMSLayer
from traitlets import Bool
class WMSLayerCustom (WMSLayer):
# Additional options
logscale = Bool(True).tag(sync=True, o=True)
wms = WMSLayerCustom(url=wms_url, layers=wms_laCommunity Discussions
Trending Discussions on ipyleaflet
QUESTION
Using the following code from ipyleaflet documentation I get a nice display with 2 extra custom widgets. These widgets have a small dark shadow that I would like to remove.
ANSWER
Answered 2022-Jan-21 at 19:20QUESTION
I have a large number of latitude and longitude values that I would like to bin together in order to display them on a heatmap (ipyleaflet only seems to allow 2000 or so points in the heatmap and this would also be much more efficient when using big data).
I am actually using vaex, but a answer in terms of pandas is also fine.
The pandas pd.cut function seems to be helpful in terms of binning, however it produces a categorical column (category dtype) which looks like a list of all the values in the bin. Is there some way of changing this to just be an incremental number identifying each bin (thanks jezreal for that part of the answer)? I just need a bin number in order to then groupby the bin number and average (mean) on the latitude and longitude columns. I also need a count for the intensity of the heatmap entry.
For example:
...ANSWER
Answered 2021-Mar-24 at 09:39The pandas pd.cut function seems to be helpful in terms of binning, however it produces a categorical column (category dtype) which looks like a list of all the values in the bin. Is there some way of changing this to just be an incremental number identifying each bin
Yes, use label=False parameter in cut:
labels array or False, default None
Specifies the labels for the returned bins. Must be the same length as the resulting bins. If False, returns only integer indicators of the bins.
Last use GroupBy.agg for aggregation and last normalize count column:
QUESTION
I've created an app using PyQt5 that (amongst others) displays a map.
For the map widget, I've used pyqtlet, but I'm starting to realize that this package is really limited (I want to show different layers, to use a draggable marker, etc.), so I want to transition to ipyleaflet instead.
Except that I cannot get my map to show in the app!
The original code was like so:
...ANSWER
Answered 2021-Jan-17 at 15:02The problem is that you're trying to add self.map to the layout but since it isn't derived from a QWidget, it doesn't work and hence the error. I can see that you've imported QtWebEngineWidgets but it isn't being used. To embed a Jupyter widget, you could generate HTML that contains the ipyleaflet widget and then add the HTML to QtWebEngineWidgets.QWebEngineView. Below is a simple implementation of adding Jupyter widgets to HTML from the documentation:
QUESTION
I just learned ipyleaflet from the scipy 2020 tutorials. In the tutorial example, I have seen the possibilities of having the hover event on ipyleaflet through the GeoJSON. Could anyone tell me how to have a hover event on Marker?
Below is my test try.
...ANSWER
Answered 2020-Jul-20 at 06:50The marker.on_mouseover method takes a callback function as argument. Here you are calling update_html(marker) which returns None, which means you are calling marker.on_mouseover(None), hence the error message.
What you want to do is this:
QUESTION
I have a geojson file which consists of New York City covered with hexagon polygons, which I read into a geopandas dataframe. I wish to add the Stamen TonerLite basemap to the plot of the dataframe. However, I am unable to replicate the same results as the working example here - https://geopandas.org/gallery/plotting_basemap_background.html
I give a small example below of the code and crs of the associated dataframe:
...ANSWER
Answered 2020-Jun-18 at 10:04Your file is corrupted. The GeoJSON is loaded with CRS 3857, while the geometry itself is in 4326. Just assign the correct CRS before reprojecting to Web Mercator.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install ipyleaflet
For a development installation (requires yarn, you can install it with conda install -c conda-forge yarn):.
the -e pip option allows one to modify the Python code in-place. Restart the kernel in order to see the changes.
the --symlink argument on Linux or OS X allows one to modify the JavaScript code in-place. This feature is not available with Windows.
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