geoplot | High-level geospatial data visualization library for Python | Data Visualization library

I'm trying to use geoplot to draw a heatmap of crime distribution in San Francisco county. The problem is when I used the dataset from geoplot to draw the map of SF, the x,y axes do not appear. I'm using this map for my final presentation, so I figured it would be more readable for my audiences with axes displayed for them(longitude&latitude as axes). I've searched as many documents as I could, and I tried to use ax.axis('on') but didn't work. I would be much appreciate for any advice given. Thanks (BTW I'm doing this on jupyter) df is the data frame I used which contained 500k crime records with locations containing longitude & latitude.

In my very simple case I would like to display the heatmap of the points in the points GeoJSON file but not on the geographic density (lat, long). In the points file each point has a confidence property (a value from 0 to 1), how to display the heatmap on this parameter? weight=points.confidence don't seem to work.

for exemple:

I got a dataframe with the following columns Name (string), size (num), latitude (num), longitude (num), geometry (shapely.geometry.point.Point).

When i'm plotting my points on a map and are trying to annotate each point the annotation is not shown at all. My guess is that this is due to the projection im using.

Here are the lines of codes im running:

I would like to plot something that resembles a kdeplot using geoviews without actually plotting the contour lines. The geoplot library supports something like this:

How can I make such a plot in geoviews?

Here is a very basic example of the kind of kdeplot I am managing to generate via geoviews, which by default plots the black lines that separates different intensities:

I recently posted a question on how to plot a heatmap using geopandas. I was recommended to use geoplot.kdeplot(), but passing a projection crashes my session.

Suppose I have the following data stored in df_points and df_map respectively:

I have trouble making a interactive map with PySAL. I want to visualize the dutch 'gemeente' (Municipalities). You can download shape files from the dutch bureau of statistics: https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/wijk-en-buurtkaart-2019

I have a file of store locations that I am trying to plot onto a NYC map. I have been using the below two links as my guide so far, but I have been unable to get the code to work.

• https://residentmario.github.io/geoplot/quickstart/quickstart.html

• https://towardsdatascience.com/geopandas-101-plot-any-data-with-a-latitude-and-longitude-on-a-map-98e01944b972

I would like to figure out how to plot a geoplot onto subplots in matplotlib. i.e. I have plotted a GeoDataFrame with geometries, and a column of counts, but I would like multiple maps on a grid of subplots

Also if you know a way to use facetgrid with geoplots, that would be helpful.

I am using geoplot which uses matplotlib to create plots.

One such functionality is geoplot.pointplot, that creates an AxesSubplot every time you call it. This allows you to call it multiple times and overlay a bunch of pointplots. The underlying code simply creates a matplotlib scatter.

My problem is that for each of these pointplots, geoplot assigns them an individually unique cmap, and so if one plot is yellow at a value of 40, another might be blue. This is an issue, as I don't want to have multiple legends for 1 plot. Ideally, all the plots follow a single legend and the values are consistent among the plots.

Below is an example:

Any help in solving this would be much appreciated. I tried feeding vmin and vmax to geoplot.pointplot but they each had no affect.

EDIT:

I have found a "solution". By adding a point to each subplot at the south pole, it falls outside the bounds of the graph and as such artificially increases the range of the colorbar. I'm not answering with this, because this is a vry hacky way of getting what I want done, and not ideal. This is done through the following code: