Spatial inequality dynamics across US counties

# Load libraries import numpy as np import pandas as pd pd.set_option('display.max_columns', None) import matplotlib.pyplot as plt plt.style.use('ggplot') from matplotlib.ticker import FormatStrFormatter from matplotlib_scalebar.scalebar import ScaleBar from pylab import rcParams import matplotlib as mpl mpl.rcParams['figure.dpi'] = 72 import seaborn as sns #sns.set_style("darkgrid") #sns.set_context(context="paper", font_scale=1.5, rc=None) #sns.set(font="serif") import plotly.express as px import plotly.graph_objects as go import geopandas as gpd import libpysal from libpysal import weights from libpysal.weights import Queen import inequality from inequality.gini import Gini_Spatial import esda from esda.moran import Moran, Moran_Local import splot from splot.esda import moran_scatterplot, plot_moran, lisa_cluster, plot_local_autocorrelation from splot.libpysal import plot_spatial_weights from giddy.directional import Rose import statsmodels.api as sm import statsmodels.formula.api as smf from spreg import OLS from spreg import MoranRes from spreg import ML_Lag from spreg import ML_Error from mgwr.gwr import GWR, MGWR from mgwr.sel_bw import Sel_BW from mgwr.utils import shift_colormap, truncate_colormap import warnings warnings.filterwarnings('ignore')

gdf = gpd.read_file("https://github.com/gdsbook/book/raw/master/data/us_county_income/uscountypcincome.gpkg") #gdf = gpd.read_file("/work/uscountypcincome.gpkg") gdf.head()

gdf.columns

gdf.shape

gdf.query('NAME == "Jackson" & STATEFP == "28"').loc[:, '1969':'1979']

years = np.arange(1969, 2018).astype(str)

sns.histplot(x=gdf['1969'], kde=True);

px.histogram(gdf, x = '1969', hover_name= 'NAME', marginal='rug')

g69 = inequality.gini.Gini(gdf['1969'].values) g69.g

def gini_by_col(column): return inequality.gini.Gini(column.values).g

inequalities = gdf[years].apply(gini_by_col, axis=0).to_frame('gini')

inequalities.plot();

px.line(inequalities, x=inequalities.index, y='gini')

def theil(column): return inequality.theil.Theil(column.values).T

inequalities['theil'] = gdf[years].apply(theil, axis=0)

inequalities['theil'].plot();

px.line(inequalities, x=inequalities.index, y='theil')

ax = gdf.plot( column='1969', scheme='NaturalBreaks', legend=True, edgecolor='none', legend_kwds={'loc': 'lower left'}, figsize=(12, 12) ) ax.set_axis_off() plt.show()