Py.Cafe

import numpy as np
import pandas as pd
import plotly.express as px
import dash
import dash_bootstrap_components as dbc
from dash import Dash, html,  dcc, Input, Output, State

df = pd.read_csv("all_outlays_2025-02-14.csv", parse_dates=['Date'])

df['pct_change'] = df['Daily'].pct_change()
df['pct_change'] = df['pct_change'].replace([np.inf, -np.inf], np.nan)
df['pct_change'] = df['pct_change'].fillna(0)

pivot_df = (
    df.pivot_table(
        index=["Date"],
        columns="transaction_catg_renamed",
        values="Daily",
        aggfunc="sum"
    )
    .fillna(0)
)

pivot_pct_df = (
    df.pivot_table(
        index=["Date"],
        columns="transaction_catg_renamed",
        values="pct_change",
    )
    .fillna(0)
)

categories = df['transaction_catg_renamed'].unique()

app = dash.Dash(__name__, external_stylesheets=[dbc.themes.UNITED])

app.title = "US federal government’s expenditure"

sidebar = dbc.Col([
    html.Hr(),
    html.H6("Selecting Time Frequency"),
    dbc.RadioItems(
        id="period-filter",
        options=[
            {'label': 'Days', 'value': 'D'},
            {'label': 'Weeks', 'value': 'W'},
            {'label': 'Months', 'value': 'ME'},
            {'label': 'Quarters', 'value': 'QE'}
        ],
        value='ME',
        inline=False, 
        class_name="btn btn-info",
    ),
    html.Hr(),
    html.H6("Transaction Categories"),
    html.Hr(),
    dbc.Button("Select Categories", id="open-modal", n_clicks=0, className="btn btn-info"),
    dbc.Modal([
        dbc.ModalHeader("Select Categories"),
        dbc.ModalBody(dbc.Checklist(
            id='category-checklist',
            options=[{'label': cat, 'value': cat} for cat in categories],
            value=  ['IAP - USAID',
                     'Dept of Education (ED)', 
                     'Dept of Commerce (DOC)', 
                     'Dept of Energy (DOE)', 
                     'Dept of Justice (DOJ)'],
            inline=False,  
            switch=True,
            style={"backgroundColor": "#f0f0f0", "padding": "8px", "fontSize": "16px"}
        )),
        dbc.ModalFooter(
            dbc.Button("Close", id="close-modal", className="btn btn-info"
                      )
        )
    ], id="modal", is_open=False),
    html.Div(id="selected-categories", style={"marginTop": "10px"})
  
], width=3, style={'background-color': '#f8f9fa', 'padding': '20px', 'text-align': 'center', 'position': 'fixed',
    'height': '100vh',
    'overflow': 'auto'}) 


content = dbc.Col([
    html.H4("The Hamilton Project: Tracking US federal expenditure since 2022",
            style={"text-align": "center"}),
    html.Hr(),
    dbc.Row([
        html.H5("Total US Federal Spending Trends by Category",
                style={"backgroundColor": "#f0f0f0", "padding": "8px", "text-align": "center"}),
        dbc.Col(dcc.Graph(id="area-chart"), width=12),
    ]),
    dbc.Row([
        html.H5("Percentage Change in US Federal Expenditure by Category",
                style={"backgroundColor": "#f0f0f0", "padding": "8px", "text-align": "center"}),
        dbc.Col(dcc.Graph(id="line-chart"), width=12),
    ]),
], width={"size": 9, "offset": 3})

app.layout = dbc.Container([
    dbc.Row([
        sidebar,
        content
    ])
], fluid=True)

@app.callback(
    Output("modal", "is_open"),
    [Input("open-modal", "n_clicks"), Input("close-modal", "n_clicks")],
    [State("modal", "is_open")],
)
def toggle_modal(n1, n2, is_open):
    if n1 or n2:
        return not is_open
    return is_open

@app.callback(
    Output("selected-categories", "children"),
    Input('category-checklist', 'value')
)
def display_selected_categories(selected_categories):
    return f"Selected Categories: {', '.join(selected_categories)}" if selected_categories else "No categories selected"

@app.callback(
    Output("area-chart", "figure"),
    Output("line-chart", "figure"),
    Input("period-filter", "value"),
    Input('category-checklist', 'value')
)
def update_charts(selected_period, selected_categories):

    resample_str = selected_period

    filtered_pivot_df = pivot_df[selected_categories]
    filtered_pivot_pct_df = pivot_pct_df[selected_categories]

    resampled_pivot_df = filtered_pivot_df.resample(resample_str).sum()
    resampled_pivot_pct_df = filtered_pivot_pct_df.resample(resample_str).mean()

    fig_area = px.area(resampled_pivot_df, template='presentation', color_discrete_sequence=px.colors.qualitative.Prism,
                       labels={'transaction_catg_renamed': 'Transaction Categories', 'Date': '', 'value': 'US$ in Billions'},
                       markers=True)
    fig_area.update_layout(legend=dict(title=None, orientation="h", y=1, yanchor="bottom", x=0.5, xanchor="center",
                                        font=dict(size=16)))

    fig_line = px.line(resampled_pivot_pct_df, template='presentation', color_discrete_sequence=px.colors.qualitative.Prism,
                        labels={'transaction_catg_renamed': 'Transaction Categories', 'Date': '', 'value': 'Percentage Change %'},
                        markers=True)
    fig_line.update_layout(showlegend=False)

    return fig_area, fig_line