dailylog 4-30-20

Delay last frame -delay 300

Plotly Colorscales

PREP THE DATA

import pandas as pd
import plotly.express as px

from urllib.request import urlopen
import json
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
    counties = json.load(response)

fips = pd.read_csv('county_fips.csv')
fips_ga = fips[fips['State'] == 'GA']
fips_ga_dict = dict(zip(fips_ga.Name,fips_ga.FIPS)) 
fips_ga_dict

df = pd.read_csv('all_georgia.csv')

def get_fips(county):
    try:
        return fips_ga_dict[county]
    except:
        return 'na'
    
df['fips'] = df.apply(lambda x: get_fips(x['name']), axis=1)

MAKE THE PLOT

def make_plot(df):
    date = df.columns[0]
    fig = px.choropleth(df, geojson=counties, locations='fips', color=date,
                               color_continuous_scale="Viridis",
                               range_color=(0, 1000),
                               scope="usa",

                               labels={'2020-04-25':'infected'}
                              )
    fig.update_geos(fitbounds="locations", visible=False)
    fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
    fig.update_layout(
        title={
            'text': date,
            'y':0.9,
            'x':0.5,
            'xanchor': 'center',
            'yanchor': 'top'},
    coloraxis_colorbar=dict(
    title="Number of infections",
            titleside="top",
        tickmode="array",
        tickvals=[0, 100, 500, 1000, 2000],
        ticktext=["0", "100", "500", "1000", ">2000"],
        ticks="outside"
    )
    )
    filename = 'georgia_v4' + date + '.png'
    fig.write_image(filename)
    fig.show()

DO THE THING

for col in df.columns[1:-1]:
    sm_df = df[[col, 'fips']]
    make_plot(sm_df)