PyCafe - Dash - Toronto Communicable Diseases Analysis

app.py
requirements.txt
app.py
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# check out https://dash.plotly.com/ for documentation
# And check out https://py.cafe/maartenbreddels for more examples
from dash import Dash, Input, Output, callback, dcc, html
import plotly
import pandas as pd
import plotly.express as px

## Pandas Intake ##
external_link = 'https://raw.githubusercontent.com/jragh/plotlymeetup/refs/heads/main/October%202025/Toronto_Communicable_Diseases_2022_2024.csv'

raw_df = pd.read_csv(external_link, thousands = ',')

raw_df['Cases'] = pd.to_numeric(raw_df['Cases'])

print(raw_df.head(400))



## Assuming Toronto Population of 3,025,650, Across all three Years
toronto_pop = 3025647

## Create a Months Mapping Dictionary for ordering later on ##
months_mapping = {
    'January': 1,
    'February': 2,
    'March': 3,
    'April': 4,
    'May': 5,
    'June': 6,
    'July': 7,
    'August': 8,
    'September': 9,
    'October': 10,
    'November': 11,
    'December': 12
}

## Map the Month mapping dictionary into a new column
raw_df['Month Mapping'] = raw_df['Month'].map(months_mapping)

## New Column for Data ##
raw_df['Cases Per 100k'] = (raw_df['Cases'] / toronto_pop) * 100000

print(raw_df.columns)


## Basic Example Group By for Figure ##
disease_grouping_annual = raw_df.loc[(raw_df['Disease Category'] == 'Sexually Transmitted and Bloodborne')].groupby(['Disease', 'Year'])['Cases'].sum().reset_index()
print(disease_grouping_annual.head(25))

## Basic Figure for Displaying our Group By Data ##
disease_grouping_annual['Year'] = disease_grouping_annual['Year'].astype(str)

# basic_fig = px.bar(
#     disease_grouping_annual,
#     y='Disease',
#     x='Cases',
#     orientation='h',
#     color='Year',
#     barmode='group',
#     category_orders = {'Year': ['2022', '2023', '2024']}
# )


## Basic Fig Enhanced ##
## Figure Set Up ##
basic_fig = px.bar(
    disease_grouping_annual,
    y='Disease',
    x='Cases',
    orientation='h',
    color='Year',
    barmode='group',
    category_orders = {'Year': ['2022', '2023', '2024']},
    color_discrete_map = {'2022': '#71bdff', '2023': '#4281c0', '2024': '#0e4984'},
    text='Cases'
)

basic_fig.update_xaxes(showgrid=True, zeroline=False, showline=False, showticklabels=True, tickwidth=2, gridcolor="rgba(30, 63, 102, 0.15)", type="-")

basic_fig.update_yaxes(linewidth=2.5, showgrid=False, linecolor='rgb(180, 180, 180)')

basic_fig.update_layout(legend={
            'orientation':'h',
            'yanchor':"bottom",
            'y':1.02,
            'xanchor': 'center',
            'x': 0.5,
            'font': {'size': 12}}, 
            legend_title = {'text': 'Year', 'font': {'weight': 'bold', 'size': 12}},
            xaxis_title={'text':"Reported Cases", 'font': {'size': 12}},
            yaxis_title={'text':"Disease Listed", 'font': {'size': 12}},
            yaxis_tickfont={'size': 10},
            xaxis_tickfont={'size': 10},
            margin={'l':10, 'r': 10, 't': 10, 'b': 10},
            plot_bgcolor='#fff', paper_bgcolor="#fff",
            hovermode='y unified')

basic_fig.update_traces(textfont_size=8.5, textposition='outside', marker={"cornerradius":3})

app = Dash(__name__)

app.layout = (
    html.Div([
        dcc.Graph(figure=basic_fig)
    ])
)

app.layout = html.Div(

    html.Div([
        html.H3('Sexually Transmitted Diseases Report', style={'marginBottom': '0.25rem', 'marginTop': '0.5rem', 'font-family': "sans-serif", 'marginLeft': "0.4rem"}),
        html.Small('Cases, Toronto, 2022 - 2024', style={'color': 'grey', 'font-family': "sans-serif", "marginLeft": "0.4rem"}),
        dcc.Graph(figure=basic_fig, style={
            'height': 'calc(100% - 3rem)',
            'marginBottom': '0.35rem',
        })
    ], style={
        'width': '90vw', 
        'height': '80vh', 
        'borderRadius': '15px', 
        'borderColor': 'lightgrey', 
        'borderWidth': '1.35px',
        'padding': '0.5rem',
        'backgroundColor': '#fff',
        'borderStyle': 'solid',
        'boxShadow': '0 2px 12px rgba(0, 0, 0, 0.12)'})
    
, style={'height': '100vh', 'width': '100vw', 'background-color': '#fafafa', 'display': 'flex', 'justifyContent': 'center'})
Py.Cafe

dash-toronto-communicable-diseases-analysis

Toronto Communicable Diseases Analysis
