PyCafe - Vizro - Vizro for Interactive Iris Dataset Exploration

data/
app.py
requirements.txt
app.py
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import plotly.express as px
import pandas as pd
from dash import Dash, dcc, Input, Output, callback, html

df = pd.read_csv("data/contestants.csv")

app = Dash()

@callback(
    Output("strip-graph", "figure"),
    Input("country","value")
)

def update_graph(country_slctd):
    dff = df.copy()
    dff['color'] = dff['to_country'].apply(lambda x: country_slctd if x == country_slctd else 'other')
    fig = px.strip(dff, x="points_final", y="year", hover_data="to_country", color="color", height=750,
                   color_discrete_map={country_slctd: 'red', 'other': 'blue'})
    return fig

# Count the number of first placements for each country
first_place_counts = df[df['place_final'] == 1].groupby('to_country').size().reset_index(name='first_place_count')

def create_choropleth():
    # Debug: Check the first place counts
    print(first_place_counts.head())

    # Debug: Check the first place counts
    print("First Place Counts:")
    print(first_place_counts)

    fig = px.choropleth(
        data_frame=first_place_counts,
        locations='to_country',
        locationmode='country names',
        color='first_place_count',
        hover_name='to_country',
        color_continuous_scale=px.colors.sequential.Plasma_r,
        range_color=(0, first_place_counts['first_place_count'].max()),  # Set range dynamically
        title='Number of Times Countries Placed First in Eurovision Throughout the Years'
    )
    return fig

def create_line_chart():
    avg_points_by_year = df.groupby('year')['points_final'].mean().reset_index()
    fig = px.line(avg_points_by_year, x='year', y='points_final', title='Average Points Over Time', color_discrete_sequence=px.colors.qualitative.Set1)
    return fig

def create_bar_chart():
    wins_by_country = df[df['place_final'] == 1].groupby('to_country').size().reset_index(name='wins')
    return px.bar(wins_by_country, x='to_country', y='wins', title='Number of Wins by Country', color_discrete_sequence=px.colors.qualitative.Pastel)

def create_scatter_plot():
    return px.scatter(df, x='running_final', y='points_final', color='to_country', title='Points vs. Running Order',
                      color_continuous_scale=px.colors.sequential.Viridis)

app.layout = html.Div([
    html.H1("Eurovision Data Visualization"),
    dcc.Tabs([
        dcc.Tab(label='Countries Placed First Map 📍', children=[
            dcc.Graph(figure=create_choropleth(), id="choropleth-map"),
            html.Div(
                "Eurovision song contest country placed 1st over the years.",
                style={"marginBottom": "20px"}
            ),
            html.Div(
                "*Data source:* Eurovision official data.",
                style={"fontSize": "12px", "color": "grey"}
            )
        ]),
        dcc.Tab(label='Final Points Based on the Year', children=[
            dcc.Dropdown(
                options=[{'label': country, 'value': country} for country in sorted(df['to_country'].unique())],
                value="Netherlands",
                clearable=False,
                id="country"
            ),
            dcc.Graph(id="strip-graph")
        ]),
        dcc.Tab(label='Avg. Final Points Over Time', children=[
            dcc.Graph(figure=create_line_chart(), id="line-chart")
        ]),
        dcc.Tab(label='Number of Wins By Country', children=[
            dcc.Graph(figure=create_bar_chart(), id="bar-chart")
        ]),
        dcc.Tab(label='Running Order vs. Points', children=[
            dcc.Graph(figure=create_scatter_plot(), id="scatter-plot")
        ])
    ])
])

# # Define content for each page
# choropleth_content = html.Div([
#     html.H2("Countries Placed First Map 📍"),
#     dcc.Graph(figure=create_choropleth(), id="choropleth-map"),
#     html.Div(
#         "Eurovision song contest country placed 1st over the years.",
#         style={"marginBottom": "20px"}
#     ),
#     html.Div(
#         "*Data source:* Eurovision official data.",
#         style={"fontSize": "12px", "color": "grey"}
#     )
# ])

# strip_chart_content = html.Div([
#     html.H2("Final Points Based on the Year"),
#     dcc.Dropdown(
#         options=[{'label': country, 'value': country} for country in sorted(df['to_country'].unique())],
#         value="Netherlands",
#         clearable=False,
#         id="country"
#     ),
#     dcc.Graph(id="strip-graph")
# ])

# line_chart_content = html.Div([
#     html.H2("Avg. Final Points Over Time"),
#     dcc.Graph(figure=create_line_chart(), id="line-chart")
# ])

# bar_chart_content = html.Div([
#     html.H2("Number of Wins By Country"),
#     dcc.Graph(figure=create_bar_chart(), id="bar-chart")
# ])

# scatter_plot_content = html.Div([
#     html.H2("Running Order vs. Points"),
#     dcc.Graph(figure=create_scatter_plot(), id="scatter-plot")
# ])

# app.layout = html.Div([
#     html.H1("Eurovision Data Visualization"),
#     dcc.Tabs([
#         dcc.Tab(label='Countries Placed First Map 📍', children=[choropleth_content]),
#         dcc.Tab(label='Final Points Based on the Year', children=[strip_chart_content]),
#         dcc.Tab(label='Avg. Final Points Over Time', children=[line_chart_content]),
#         dcc.Tab(label='Number of Wins By Country', children=[bar_chart_content]),
#         dcc.Tab(label='Running Order vs. Points', children=[scatter_plot_content])
#     ])
# ])

if __name__ == '__main__':
    app.run(debug=True)
Py.Cafe

Figure Friday 2024 - week 40

Vizro for Interactive Iris Dataset Exploration
