pythonmatplotlibgeojson
Population All Scrambled - -Python - Matplotlib - Mapping
Language: Python
I have this data stored as a Datraframe in a variable called: grouped_fips_pop
FIPS County County Pop 2022 Formated_FIPS
0 53001 Adams 20961.0 0500000US53001
1 53003 Asotin 22508.0 0500000US53003
2 53005 Benton 212791.0 0500000US53005
3 53007 Chelan 79926.0 0500000US53007
4 53009 Clallam 77805.0 0500000US53009
5 53011 Clark 516779.0 0500000US53011
6 53013 Columbia 4026.0 0500000US53013
7 53015 Cowlitz 111956.0 0500000US53015
8 53017 Douglas 44192.0 0500000US53017
9 53019 Ferry 7448.0 0500000US53019
10 53021 Franklin 98678.0 0500000US53021
11 53023 Garfield 2363.0 0500000US53023
12 53025 Grant 101311.0 0500000US53025
13 53027 Grays Harbor 77038.0 0500000US53027
14 53029 Island 86625.0 0500000US53029
15 53031 Jefferson 33589.0 0500000US53031
16 53033 King 2266789.0 0500000US53033
17 53035 Kitsap 277673.0 0500000US53035
18 53037 Kittitas 45189.0 0500000US53037
19 53039 Klickitat 23271.0 0500000US53039
20 53041 Lewis 85370.0 0500000US53041
21 53043 Lincoln 11601.0 0500000US53043
22 53045 Mason 68166.0 0500000US53045
23 53047 Okanogan 43127.0 0500000US53047
24 53049 Pacific 24113.0 0500000US53049
25 53051 Pend Oreille 14179.0 0500000US53051
26 53053 Pierce 927380.0 0500000US53053
27 53055 San Juan 18662.0 0500000US53055
28 53057 Skagit 131179.0 0500000US53057
29 53059 Skamania 12460.0 0500000US53059
30 53061 Snohomish 840079.0 0500000US53061
31 53063 Spokane 549690.0 0500000US53063
32 53065 Stevens 48229.0 0500000US53065
33 53067 Thurston 298758.0 0500000US53067
34 53069 Wahkiakum 4688.0 0500000US53069
35 53071 Walla Walla 61890.0 0500000US53071
36 53073 Whatcom 230677.0 0500000US53073
37 53075 Whitman 47619.0 0500000US53075
38 53077 Yakima 257001.0 0500000US53077
I ran this below:
import plotly.express as px
import requests
import json
import pandas as pd
# Load county GeoJSON data
r = requests.get('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json')
counties = json.loads(r.text)
# Filter counties GeoJSON data to include only Washington state
target_states = ['53']
counties['features'] = [f for f in counties['features'] if f['properties']['STATE'] in target_states]
grouped_fips_pop['County Pop 2022'] = grouped_fips_pop['County Pop 2022'].astype(int)
# Create choropleth map for Washington state
fig = px.choropleth(grouped_fips_pop,
geojson=counties,
locations='FIPS',
color='County Pop 2022',
color_continuous_scale='Viridis',
range_color=(grouped_fips_pop['County Pop 2022'].min(), grouped_fips_pop['County Pop 2022'].max()),
scope='usa',
labels={'County Pop 2022': 'Population'},
hover_name= 'County'
)
less_50K = grouped_fips_pop[grouped_fips_pop['County Pop 2022'] < 50000]
b50K_100K = grouped_fips_pop[(grouped_fips_pop['County Pop 2022'] >= 50000) & (grouped_fips_pop['County Pop 2022'] < 100000)]
high_100K = grouped_fips_pop[grouped_fips_pop['County Pop 2022'] >= 100000]
less_50K['County Pop 2022'] = less_50K['County Pop 2022'].astype(int)
b50K_100K['County Pop 2022'] = b50K_100K['County Pop 2022'].astype(int)
high_100K['County Pop 2022'] = high_100K['County Pop 2022'].astype(int)
# Update layout and display the map
fig.update_layout(title_text='2022 Population in Washington State',
title_x=0.5, # Center the title horizontally
title_y=0.9, # Position the title closer to the top
geo=dict(projection_scale=5, center={'lat': 47.5, 'lon': -120}, projection_type='albers usa'), # Use Albers USA projection
margin={'r': 0, 't': 20, 'l': 0, 'b': 0}, # Reduce top margin to move title closer to the map
updatemenus=[
dict(
buttons=list([
dict(
args=[{"z": [grouped_fips_pop['County Pop 2022']]}],
label="All",
method="restyle"
),
dict(
args=[{"z": [less_50K['County Pop 2022']]}],
label="Less than 50,000",
method="restyle"
),
dict(
args=[{"z": [b50K_100K['County Pop 2022']]}],
label="50,000 - 100,000",
method="restyle"
),
dict(
args=[{"z": [high_100K['County Pop 2022']]}],
label="More than 100,000",
method="restyle"
)
]),
direction="down",
pad={"r": 10, "t": 10},
showactive=True,
x=0.1,
xanchor="left",
y=1.1,
yanchor="top"
)
]
)
fig.show()
And it plots the map with the county areas filled with population. When I select the dropdown options it scrambles all info. For example: On all option the county 'King' gives me 2M in population, when i select the option less then 50K Population, it shows me the county 'King' highlighted, which it shouldn't because its higher then 50K and not lesser then 50k, and it shows with a population of 4688.
My question is what can i do to resolve this? I tried a little of dash but without luck.
Solution
The reason the map does not display correctly is that the county geometry is not in a one-to-one relationship with the county population, so the display is incorrect. So I think the geometry needs to be adjusted to that group to match the population data given in the dropdown. The easiest way to do this is to give the data that matches the criteria to the current data frame, give that value None otherwise, and hide the map.
less_50K = grouped_fips_pop.copy()
less_50K['County Pop 2022'] = less_50K['County Pop 2022'].apply(lambda x: x if x < 50000 else None)
b50K_100K = grouped_fips_pop.copy()
b50K_100K['County Pop 2022'] = b50K_100K['County Pop 2022'].apply(lambda x: x if x >= 50000 and x < 100000 else None)
high_100K = grouped_fips_pop.copy()
high_100K['County Pop 2022'] = high_100K['County Pop 2022'].apply(lambda x: x if x >= 100000 else None)
# Create choropleth map for Washington state
fig = px.choropleth(grouped_fips_pop,
geojson=counties,
locations='FIPS',
color='County Pop 2022',
color_continuous_scale='Viridis',
range_color=(grouped_fips_pop['County Pop 2022'].min(), grouped_fips_pop['County Pop 2022'].max()),
scope='usa',
labels={'County Pop 2022': 'Population'},
hover_name= 'County'
)
# Update layout and display the map
fig.update_layout(title_text='2022 Population in Washington State',
title_x=0.5, # Center the title horizontally
title_y=0.9, # Position the title closer to the top
geo=dict(projection_scale=5, center={'lat': 47.5, 'lon': -120}, projection_type='albers usa'), # Use Albers USA projection
margin={'r': 0, 't': 20, 'l': 0, 'b': 0}, # Reduce top margin to move title closer to the map
updatemenus=[
dict(
buttons=list([
dict(
args=[{"z": [grouped_fips_pop['County Pop 2022']]}],
label="All",
method="restyle"
),
dict(
args=[{"z": [less_50K['County Pop 2022']]}],
label="Less than 50,000",
method="restyle"
),
dict(
args=[{"z": [b50K_100K['County Pop 2022']]}],
label="50,000 - 100,000",
method="restyle"
),
dict(
args=[{"z": [high_100K['County Pop 2022']]}],
label="More than 100,000",
method="restyle"
)
]),
direction="down",
pad={"r": 10, "t": 10},
showactive=True,
x=0.1,
xanchor="left",
y=1.1,
yanchor="top"
)
]
)
fig.show()
- Is it possible to call setter as a method?
- Accessing a Python traceback from the C API
- Scraping hierarchical website in a specific category
- How to offset a marker in matplotlib?
- How to access current user in Django class based view
- Is there a way to define list(obj) method on a user defined class in python?
- Deserializing Json list into class objects not able to extract attrributes
- What is the pythonic way to detect the last element in a 'for' loop?
- How to get integer values from a string in Python?
- Optimize this Python code that involves matrix inversion
- how to read a file with dictionary?
- How to extract only audio from downloading video? Python yt-dlp
- How to solve Invalid element(s) received for the 'color' property?
- Plotly Value error - Invalid property for colour
- no module named distutils....but distutils installed?
- how can i change the venv of my current shell from within a python script
- What is the difference between "cast(...)" and "... # type: ..."?
- getting the file size with pycurl
- export conda environment without prefix variable which shows local path to executable
- How can I fix datetime error when trying to use the now syntax?
- Python 3 asyncio with aioboto3 seems sequential
- How can I set OpenCV to use origin as bottom-left corner of image?
- Can I use sleep in the main thread without blocking other threads?
- Getting number of elements in an iterator in Python
- Merging tuples if they have one common element
- How to specify the response_model in FastAPI on a non-default return?
- PyCharm doesn’t see files in project
- How to tune PID controller on non-linear model (here: diving of a body)
- Create list of factorials using list comprehension
- Rewriting URL request function to satisfy GitHub CodeQL server side request forgery (SSRF) warning