Problem with missing values in Altair or Plotly choropleth map

Question

I have data for a few states in the US and others are Null. While creating the maps, I would like to shade in the states with the missing value in the text but I am struggling to find the correct method. With my current code, I am unable to get the entire US map including the states with the Null value, and only the states with a certain assigned value pop up. I have also looked at previous questions posted and tried layering the maps but that gives me an error. here's how cc_df looks like

Here's my code:

# import the required library
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt# import seaborn library
%matplotlib inline
import altair as alt
from vega_datasets import data

# State database
states_df = pd.read_csv(
    'https://www2.census.gov/geo/docs/reference/state.txt',
# pipe seperated file
sep="|",
# FIPS are best as strings
dtype='str',
# rename columns
header=0, names=['state_fips', 'state', 'state_name', 'StateENS'],
# drop last column
usecols=['state_fips', 'state_name', 'state']
).set_index('state')
states_df['id'] = states_df['state_fips'].astype(int)

# The data to map
cc_df = pd.read_csv('hv_cwad.csv',
                    usecols=['state', 'CWAD'])
cc_df = cc_df.groupby('state').mean()

# Combine state database and our own data
#cc_state_df = pd.merge(cc_df, states_df)
cc_state_df = states_df.join(cc_df).reset_index()

# %%
# Create the map
states = alt.topo_feature(data.us_10m.url, 'states')
variable_list = ['CWAD']

alt.Chart(states).mark_geoshape(stroke='lightgrey',
                                strokeWidth=.5).encode(
    alt.Color(alt.repeat('row'), type='quantitative')
).transform_lookup(
    lookup='id',
    from_=alt.LookupData(cc_state_df, 'id', variable_list)
).properties(
    width=300,
    height=300
).project(
    type='albersUsa'
).repeat(
    row=variable_list
).resolve_scale(
    color='independent'
)

The output looks like this:

Answer 1

I was aware that the points you pointed out were issues, so I did some research against NaN values and found the following answers. However, the conditional judgment of the null value did not work, so I replaced the missing value with -1 to get the desired output.

import pandas as pd
import matplotlib.pyplot as plt
import altair as alt
from vega_datasets import data

# State database
states_df = pd.read_csv('https://www2.census.gov/geo/docs/reference/state.txt', 
                        sep="|", 
                        dtype='str', 
                        header=0, 
                        names=['state_fips', 'state', 'state_name', 'StateENS'],
                        usecols=['state_fips', 'state_name', 'state']).set_index('state')

states_df['id'] = states_df['state_fips'].astype(int)

import io

data = '''
state CWAD
AR 377.715148
FL 6560.929494
GA 1958.122132
IA 0.409179
KS 63.706671 
'''

cc_df = pd.read_csv(io.StringIO(data), delim_whitespace=True)
# The data to map
#cc_df = pd.read_csv('hv_cwad.csv', usecols=['state', 'CWAD'])
cc_df = cc_df.groupby('state').mean()

# Combine state database and our own data
#cc_state_df = pd.merge(cc_df, states_df)
cc_state_df = states_df.join(cc_df).reset_index()
cc_state_df.fillna(-1, inplace=True)

# Create the map
states = alt.topo_feature(data.us_10m.url, 'states')

variable_list = ['CWAD']

alt.Chart(states).mark_geoshape(
    stroke='lightgrey',
    strokeWidth=.5
).encode(
        color=alt.condition('datum.CWAD !== -1', 'CWAD:Q', alt.value('lightgray'))
).transform_lookup(
    lookup='id',
    from_=alt.LookupData(
        cc_state_df,
        'id',
        variable_list)
).properties(
    width=300,
    height=300
).project(
    type='albersUsa'
).repeat(
    row=variable_list
).resolve_scale(
    color='independent'
)