CODEWITHSUNDEEP
pythonpandasmatplotlibcontextily
Natalie Shahsavarian
Natalie Shahsavarian

Reputation: 31

HTTPError: Tile URL resulted in a 404 error

I have data on NY State Hospitals with georeferences and want to create a choropleth map with base map. I also tried layering with .plot() with no success. When I run my code for layered plot no image is shown, and when I run contextily I get this error message:

HTTPError: Tile URL resulted in a 404 error. Double-check your tile url: https://stamen-tiles-a.a.ssl.fastly.net/terrain/24/8388574/8388589.png

The conda environement:

*conda config --add channels conda-forge*
*conda config --add channels anaconda*
*conda create -n geo python=3.7.0 geopandas=0.4.0 spyder contextily*
*conda activate geo*

This is what I am running, beginning to end:

import pandas as pd
import geopandas as gp
import contextily as ctx
import matplotlib.pyplot as plt
from shapely.geometry import Point
%matplotlib inline


usa = gp.read_file("https://alicia.data.socrata.com/resource/cap4-bs3u.geojson")
NY_state = usa.loc[usa['state_abbr'] == 'NY']

ax = NY_state.to_crs(epsg=3857).plot(figsize=(10,10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ax)
ax

The steps above work well and create a nice map. Below is how I manipulated the NY State Hospital data to create make GeoDataFrame and value for choropleth map (Infections Observed/Infections Predicted)

polpro_new = pd.read_csv('https://health.data.ny.gov/api/views/utrt-
zdsi/rows.csv?accessType=DOWNLOAD&api_foundry=true' )

polpro_new.rename(columns = {'New Georeferenced Column':'Georef'}, inplace = True)

Geo_df = polpro_new.Georef.str.split(expand=True)
Geo_df = Geo_df.dropna()
Geo_df = polpro_new.Georef.str.split(expand=True)

Geo_df.rename(columns = {0:'Latitude', 1:'Longitude'}, inplace = True)
Geo_df['Latitude'] = Geo_df['Latitude'].str.replace(r'(', '')
Geo_df['Latitude'] = Geo_df['Latitude'].str.replace(r',', '')
Geo_df['Longitude'] = Geo_df['Longitude'].str.replace(r')', '')

New_df = pd.concat([polpro_new, Geo_df], axis=1, join='inner', sort=False)

clabsi1 = New_df[(New_df['Indicator Name']==
                         'CLABSI Overall Standardized Infection Ratio')]

clabsi_2008 = clabsi1[(clabsi1['Year']== 2008)]

df08 = pd.DataFrame([Point(xy) for xy in zip(clabsi_2008.loc[:,
'Longitude'].astype(float), clabsi_2008.loc[:,'Latitude'].astype(float))])

df08.rename(columns = {0:'geometry'}, inplace = True)


clabsi_08 = clabsi_2008.reset_index()
df08.reset_index()
New_df_08 = pd.concat([clabsi_08, df08], axis=1, sort=False)


New_df_08['IO_to_IP'] = New_df_08['Infections Observed']/New_df_08
['Infections Predicted']

I used the 'coords' DataFrame to create a GeoDataFrame

coords = New_df_08[['IO_to_IP', 'geometry']]
geo_df = gp.GeoDataFrame(coords, crs = 3857, geometry = New_df_08['geometry'])

Below are the two ways I tried to plot the georefrence data over a base map

y_plot = geo_df.plot(column='IO_to_IP', figsize=(10,10), alpha=0.5, edgecolor='k')
ctx.add_basemap(ny_plot)
ny_plot

and

geo_df.plot('IO_to_IP', ax=ax)
plt.show()
plt.savefig("my_plot")

I am able to create the ny_plot but no base plot, get this error:

HTTPError: Tile URL resulted in a 404 error. Double-check your tile url: https://stamen-tiles-a.a.ssl.fastly.net/terrain/24/8388574/8388589.png

What might be the problem here? How do I go about fixing it?

Again the output I am looking for is a choropleth map of infection ratio (observed/predicted) on a base map of NY State

Upvotes: 3

Views: 2716

Answers (1)

juka19
juka19

Reputation: 11

Apparently there is a bug when the points in your data are too close to each other, see here: https://github.com/geopandas/contextily/issues/199

The fix that is suggested is to add a parameter to the zoom level, e.g.:

ctx.add_basemap(ax, zoom=1)

Upvotes: 1

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