PyCafe - Vizro - Book Reading Insights

app.py
filtered_books.csv
requirements.txt
app.py
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from vizro import Vizro
import vizro.models as vm
from vizro.models.types import capture
import pandas as pd
import plotly.graph_objects as go
from vizro.models.types import capture

####### Function definitions ######
@capture("graph")
def sequence_reading(data_frame):
    fig = go.Figure()
    fig.add_trace(
        go.Scatter(
            x=data_frame["Date Read"],
            y=[1] * len(data_frame),
            mode="markers",
            marker=dict(size=10, color="blue"),
        )
    )
    fig.update_layout(
        title="Sequence of reading",
        xaxis_title="Date Read",
        yaxis_title="Sequence",
        yaxis=dict(showticklabels=False, showgrid=False),
        xaxis=dict(tickangle=-45),
    )
    return fig


@capture("graph")
def pages_books_totals(data_frame):
    # Prepare data
    data_frame["Date Read"] = pd.to_datetime(data_frame["Date Read"])
    data_frame.sort_values("Date Read", inplace=True)
    data_frame["Cumulative Pages"] = data_frame["Number of Pages"].cumsum()

    # Aggregate data by year for total books read
    yearly_books = data_frame.groupby(data_frame["Date Read"].dt.year).size()

    # Create figure with secondary y-axis
    fig = go.Figure()

    # Add line for cumulative pages
    fig.add_trace(
        go.Scatter(
            x=data_frame["Date Read"],
            y=data_frame["Cumulative Pages"],
            mode="lines",
            name="Cumulative Pages Read",
        )
    )

    # Add bars for books read per year
    fig.add_trace(
        go.Bar(
            x=yearly_books.index, y=yearly_books, name="Books Read per Year", yaxis="y2"
        )
    )

    # Set up the layout
    fig.update_layout(
        title="Cumulative Pages Read and Books Read per Year",
        xaxis_title="Date",
        yaxis=dict(title="Number of Pages"),
        yaxis2=dict(title="Total Books", overlaying="y", side="right"),
    )

    return fig


@capture("graph")
def rating_comparison(data_frame):
    # Filter out rows where 'My Rating' is 0
    df = data_frame[data_frame["My Rating"] != 0]

    # Create a figure
    fig = go.Figure()

    # Add dumbbell traces
    for index, row in df.iterrows():
        fig.add_trace(
            go.Scatter(
                x=[row["My Rating"], row["Average Rating"]],
                y=[row["Title"], row["Title"]],
                mode="markers+lines",
                name=row["Title"],
                marker=dict(size=10),
                line=dict(width=2),
            )
        )

    # Update layout
    fig.update_layout(
        title="Comparison of My Rating vs Average Rating",
        xaxis_title="Rating",
        yaxis_title="Book Title",
        showlegend=False,
    )

    return fig

########### Read data ############
df = pd.read_csv("filtered_books.csv")
df["Date Read"] = pd.to_datetime(df['Date Read'],dayfirst=True)


        ########### Model code ############
model = vm.Dashboard(
    pages=[
        vm.Page(
            components=[
                vm.Graph(
                    id="sequence_reading",
                    figure=sequence_reading(df),
                )
            ],
            title="Sequence of Reading",
            layout=vm.Layout(grid=[[0]]),
            controls=[
                vm.Filter(
                    type="filter",
                    column="Date Read",
                    targets=["sequence_reading"],
                    selector=vm.DatePicker(type="date_picker", range=True),
                )
            ],
        ),
        vm.Page(
            components=[
                vm.Graph(
                    id="pages_books_totals",
                    figure=pages_books_totals(df),
                )
            ],
            title="Pages and Book Totals",
            layout=vm.Layout(grid=[[0]]),
            controls=[],
        ),
        vm.Page(
            components=[
                vm.Graph(
                    id="rating_comparison",
                    figure=rating_comparison(df),
                )
            ],
            title="Rating Comparison",
            layout=vm.Layout(grid=[[0]]),
            controls=[],
        ),
    ],
    title="Book Reading Analysis Dashboard",
)

Vizro().build(model).run()
Py.Cafe

goodreads-reading-insights

Book Reading Insights
