panel_test.py

import panel
import pandas as pd
from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvas

returns_opts = [
    ("0/100", 0.013),
    ("20/80", 0.017),
    ("30/70", 0.019),
    ("40/60", 0.022),
    ("50/50", 0.024),
    ("60/40", 0.026),
    ("70/30", 0.028),
    ("80/20", 0.030),
    ("100/0", 0.035),
]

savings_opts = [0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50]


def get_return_series(deposit, rate, period):
    deposit = [deposit] * period
    rate = [rate] * period

    df = pd.DataFrame({"deposit": deposit, "rate": rate})
    df["interest"] = df.deposit * df.rate
    # does not account for initial balance
    # initial balance always 0
    df["total"] = (
        df["deposit"] * df["rate"].shift().add(1).cumprod().fillna(1)
    ).cumsum()
    return df


def mpl_plot(df_a, df_b):
    fig = Figure()
    FigureCanvas(fig)  # not needed in mpl >= 3.1
    ax = fig.add_subplot()

    df_a.plot(ax=ax, label="alice")
    df_b.plot(ax=ax, label="bob")

    fig.legend(loc="upper right")

    return fig


def calculate_data(
    view_fn=mpl_plot,
    savings_alice=0.15,
    returns_alice=0.04,
    savings_bob=0.05,
    returns_bob=0.04,
    period=20,
):
    df_one = pd.DataFrame(get_return_series(savings_alice, returns_alice, period))
    df_two = pd.DataFrame(get_return_series(savings_bob, returns_bob, period))

    return view_fn(df_one["total"], df_two["total"])


savings_alice = panel.widgets.FloatSlider(name="savings")

w_alice_deposit = panel.widgets.FloatSlider(
    name="Savings", start=0.05, end=3, step=0.05, value=0.25
)
w_alice_rate = panel.widgets.DiscreteSlider(
    name="Return", options=dict(returns_opts), value=0.035
)

box_alice = panel.WidgetBox("# Alice", w_alice_deposit, w_alice_rate)


w_bob_deposit = panel.widgets.FloatSlider(
    name="Savings", start=0.05, end=3, step=0.05, value=0.15
)
w_bob_rate = panel.widgets.DiscreteSlider(
    name="Return", options=dict(returns_opts), value=0.035
)

box_bob = panel.WidgetBox("# Bob", w_bob_deposit, w_bob_rate)

w_period = panel.widgets.IntSlider(name="Period", start=5, end=100, step=1, value=25)


def mpl_plot_mod(df_a, df_b):
    fig = Figure()
    FigureCanvas(fig)  # not needed in mpl >= 3.1
    ax = fig.add_subplot()

    df_a.plot(ax=ax, label="alice")
    df_b.plot(ax=ax, label="bob")

    ax.axhline(y=25, color="red", label="25x savings")

    fig.legend(loc="upper right")

    return fig


@panel.depends(
    w_alice_deposit.param.value,
    w_alice_rate.param.value,
    w_bob_deposit.param.value,
    w_bob_rate.param.value,
    w_period.param.value,
)
def calculate_data_mod(
    savings_alice, returns_alice, savings_bob, returns_bob, period, view_fn=mpl_plot_mod
):
    df_one = pd.DataFrame(get_return_series(savings_alice, returns_alice, period))
    df_two = pd.DataFrame(get_return_series(savings_bob, returns_bob, period))

    return view_fn(df_one["total"], df_two["total"])


dashboard = panel.Row(
    panel.Column(
        panel.Row(box_alice),
        panel.Row(box_bob),
        panel.Row(w_period),
    ),
    panel.Column(
        calculate_data_mod,
    ),
)

panel.serve(dashboard)