#!/usr/bin/env python
# coding: utf-8

import pandas as pd
import geopandas as gpd
import numpy as np
import censusdata as cd

# census table
cdcol='B19013_001E'

# census geography
cdf = cd.download('acs5', 2019,
           cd.censusgeo([('state', '36'),
                         ('county','083'),
                        ('county subdivision','*')]),
          [cdcol])

geoid=[]
geoname=[]

# convert geoname into more useful parts
for index in cdf.index.tolist():
    geopart=''
    for part in index.geo:
        geopart = geopart + part[1]
    geoid.append(geopart)
    geoname.append(index.name)

cdf['geoid']=geoid
cdf['geoname']=geoname

geosplit = cdf['geoname'].str.split(', ', expand = True)
cdf['muni']=geosplit[0]
cdf['county']=geosplit[1]

# load graphiing libraries
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.ticker as mtick

# sort by town name
cdf = cdf.sort_values(by='geoname')

# x axis value, we are using the census data
# we obtained above
xAxVal = cdcol;

# 10 inch by 10 inch figure
plt.rcParams['figure.figsize'] = [10, 10]

# conservative but nice style
sns.set_style('whitegrid')

# call the Seaborn Wrapper, with basic information about the bar graph
# switch the x and y if you want a more traditional vertical graph
gx=sns.barplot(x = xAxVal, y = "muni", data = cdf, palette='Paired')

# set font settings
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = 'Overpass Mono'
plt.rcParams['font.size'] = '18'

# nicer labels
plt.ylabel('Municipality', fontweight=700)
plt.xlabel('Median Household Income', fontweight=700)

# dollar formatting for x-axis
fmt = '${x:,.0f}'
tick = mtick.StrMethodFormatter(fmt)
gx.xaxis.set_major_formatter(tick) 

# add the labels on the individual bars -- change the +1.5 and horizonal alignment to on or before that bars
for i in range(len(cdf[xAxVal])):
    plt.annotate("${:,}".format(cdf[xAxVal][i]), xy=(cdf[xAxVal][i]+1.5,i), ha='left', va='center',  fontweight=1000)

# Include a title, shown in the center (50% from left), and near the top (91% from bottom)
plt.figtext(0.5, .91, 'Median Household Income in Renselaer County', wrap=True,  ha='center', va='center', fontweight=1000, fontsize=26)

# Include footer text, 90% from the left, text-aligned left, 3% from the bottom of the image
plt.figtext(0.9, 0.03, '2019 American Community Survey, 5 yr.', wrap=True, horizontalalignment='right', fontstyle='italic', fontsize=14, color='#00000088')
plt.figtext(-0.2, 0.03, 'Andy Arthur, 9/14/2021', wrap=True, horizontalalignment='left', fontstyle='italic', fontsize=14, color='#00000088')

# Save as a SVG or PNG for posting at 175 DPI. The BBOX inches tight setting avoids long
# y axis from getting cut off
plt.savefig('/tmp/ren.svg',dpi=175, bbox_inches='tight')