Add a gradient colorband legend in plotly - colors

Question

I'm using plotly, plotly express and plotly figure factory to plot U.S data. But I have an issue with color band.
1- Can I add a different color band from the original one? like a new type which is not based on the graph?
2- I want a gradient one but it shows a discrete one.
I would appreciate if anyone can help me.
=========================
import plotly.figure_factory as ff
import numpy as np
import pandas as pd
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv')
df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply(lambda x: str(x).zfill(2))
df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply(lambda x: str(x).zfill(3))
df_sample['FIPS'] = df_sample['State FIPS Code'] + df_sample['County FIPS Code']
colorscale = ["#f7fbff","#ebf3fb","#deebf7","#d2e3f3","#c6dbef","#b3d2e9","#9ecae1",
"#85bcdb","#6baed6","#57a0ce","#4292c6","#3082be","#2171b5","#1361a9",
"#08519c","#0b4083","#08306b"]
endpts = list(np.linspace(1, 12, len(colorscale) - 1))
fips = df_sample['FIPS'].tolist()
values = df_sample['Unemployment Rate (%)'].tolist()
fig = ff.create_choropleth(
fips=fips, values=values,
binning_endpoints=endpts,
colorscale=colorscale,
show_state_data=False,
show_hover=True, centroid_marker={'opacity': 0},
asp=2.9, title='USA by Unemployment %',
legend_title='% unemployed'
)
fig.layout.template = None
fig.write_image("fig1.png", scale=20)
fig.show()
=====================================enter image description here

Answer 1

I recommend moving to https://plotly.com/python/mapbox-county-choropleth/
figure generation is quicker
uses a continuous color scale as you require
provides much more flexible zoom and pan
data prep
import requests
import urllib
from pathlib import Path
from zipfile import ZipFile
import geopandas as gpd
import pandas as pd
import plotly.express as px
# get geometry data as a geopandas dataframe
# fmt: off
src = [{"name": "counties", "suffix": ".shp", "url": "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_20m.zip",},]
data = {}
for s in src:
f = Path.cwd().joinpath(urllib.parse.urlparse(s["url"]).path.split("/")[-1])
if not f.exists():
r = requests.get(s["url"],stream=True,)
with open(f, "wb") as fd:
for chunk in r.iter_content(chunk_size=128): fd.write(chunk)
fz = ZipFile(f)
fz.extractall(f.parent.joinpath(f.stem))
data[s["name"]] = gpd.read_file(f.parent.joinpath(f.stem).joinpath([f.filename for f in fz.infolist() if Path(f.filename).suffix == s["suffix"]][0])).assign(source_name=s["name"])
gdf = pd.concat(data.values()).to_crs("EPSG:4326")
df_sample = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv')
df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply(lambda x: str(x).zfill(2))
df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply(lambda x: str(x).zfill(3))
df_sample['FIPS'] = df_sample['State FIPS Code'] + df_sample['County FIPS Code']
gdf2 = pd.merge(gdf, df_sample, left_on=["STATEFP","COUNTYFP"], right_on=["State FIPS Code","County FIPS Code"])
plot
colorscale = ["#f7fbff","#ebf3fb","#deebf7","#d2e3f3","#c6dbef","#b3d2e9","#9ecae1",
"#85bcdb","#6baed6","#57a0ce","#4292c6","#3082be","#2171b5","#1361a9",
"#08519c","#0b4083","#08306b"]
# build choropleth
fig = px.choropleth_mapbox(
gdf2,
geojson=gdf2.geometry,
locations=gdf2.index,
color="Unemployment Rate (%)",
color_continuous_scale=colorscale,
hover_data=["NAME", "FIPS"]
).update_layout(
mapbox={"style": "white-bg", "zoom": 1.5, "center": {"lat": 50, "lon": -120}},
margin={"l":0,"r":0,"t":30,"b":0},
title='USA by Unemployment %',
coloraxis_colorbar_title="Rate"
)
fig