choropleth

I am using folium to create a choropleth map of a set of countries. I am following the documentation . However. for some reason the map doesn't show any shades. I am using the world geojson from natural earth (see the gist ). My dataframe looks like: >>> spatial_scores.head() Out[1]: id Country Score PER Peru 2.810300 HND Honduras 2.734521 GUF French Guiana 2.730886 SLV El Salvador 2.473134 CRI Costa Rica 2.454963 The world geojson looks like: >>> world_json['features'][0]['id'] Out [2]: u'AFG' The relevant portions of the choropleth codes are as below: map1 = folium.Map(location=[-15., -60],

I'm recreating the example choropleth and trying to add a slider that, when dragged, would change from year to year. Another user asked a similar question but they didn't receive a reply. I did some more searching and found an example where the user generated random values for the additional years and created a slider but it's in JavaScript and I'm not sure how to translate it into Python. Here's the code in JavaScript: Plotly.d3.csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv', function(err, rows){ function unpack(rows, key) { return rows.map(function(row)

I have been trying to build a Choropleth / Bubble map of UK for my own shiny dashboard project. My dashboard is a student information management system and the map is supposed to show students come from which regions (zip codes or cities is also fine). Unfortunately, most packages, such as plotly and ggmap, only cover information about states of USA. So, could someone please tell me how to create a map for UK? Here is an example of what I am trying to accomplish: Choropleth Map for UK This is a step-by-step implementation of what I meant by my comment. I did not use the External Post that I

I am not getting any color variation in my output map even after the choropleth is linked with the geo_data and the data frame is linked with data parameter in the choropleth method. I have provided the "key_on" parameter rightly and the "columns" parameter rightly. I have removed all the NULL values from the Dataframe. import pandas as pd from pandas import read_csv import folium import os import webbrowser crimes = read_csv('Dataframe.csv',error_bad_lines=False) vis = os.path.join('Community_Areas.geojson') m = folium.Map(location = [41.878113, -87.629799], zoom_start = 10, tiles =

Example: I want to plot two tmap plots side by side, which are generated by this code. library(tmap) library(gridExtra) data(World) plot1= tm_shape(World, projection = "merc") + tm_layout("", inner.margins=c(-1.72, -2.05, -0.75, -1.56)) + tm_borders(alpha = 0.3, lwd=2) plot2= tm_shape(World, projection = "merc") + tm_layout("", inner.margins=c(-1.72, -2.05, -0.75, -1.56)) + tm_borders(alpha = 0.3, lwd=2) plot1 and plot2 work fine as single stand-alone plots: Problem: I have problems to put both plots side-by-side. I tried: grid.arrange(plot1, plot2) throughs an error Error in arrangeGrob(...,

I'm trying to make a choropleth map, but how can I set the size of the map? Now I've this map: I would like expand the map to all the space, I read the documentations but I didn't find a solution. This is my code: var data = [{ type: 'choropleth', locationmode: 'country names', locations: unpack(output, 'label'), z: unpack(output, 'nres'), text: unpack(output, 'nres') }]; var layout = { geo: { projection: { type: 'equirectangular' } } }; Plotly.plot(mapChoropleth, data, layout, { showLink: false }); Plotly tries to take all the available space without changing the image ratio. If you have a

I'd like to generate a choropleth map using the following data points: Longitude Latitude Price Here is the dataset - https://www.dropbox.com/s/0s05cl34bko7ggm/sample_data.csv?dl=0 . I would like the map to show the areas where the price is higher and the where price is lower. It should most probably look like this (sample image): Here is my code: library(ggmap) map <- get_map(location = "austin", zoom = 9) data <- read.csv(file.choose(), stringsAsFactors = FALSE) data$average_rate_per_night <- as.numeric(gsub("[\\$,]", "", data$average_rate_per_night)) ggmap(map, extent = "device") + stat