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Migrate to dashboard-tips example
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import faicons as fa
import plotly.express as px
# Load data and compute static values
from shared import app_dir, tips
from shinywidgets import render_plotly
from shiny import reactive, render
from shiny.express import input, ui
bill_rng = (min(tips.total_bill), max(tips.total_bill))
# Add page title and sidebar
ui.page_opts(title="Restaurant tipping", fillable=True)
with ui.sidebar(open="desktop"):
ui.input_slider(
"total_bill",
"Bill amount",
min=bill_rng[0],
max=bill_rng[1],
value=bill_rng,
pre="$",
)
ui.input_checkbox_group(
"time",
"Food service",
["Lunch", "Dinner"],
selected=["Lunch", "Dinner"],
inline=True,
)
ui.input_action_button("reset", "Reset filter")
# Add main content
ICONS = {
"user": fa.icon_svg("user", "regular"),
"wallet": fa.icon_svg("wallet"),
"currency-dollar": fa.icon_svg("dollar-sign"),
"ellipsis": fa.icon_svg("ellipsis"),
}
with ui.layout_columns(fill=False):
with ui.value_box(showcase=ICONS["user"]):
"Total tippers"
@render.express
def total_tippers():
tips_data().shape[0]
with ui.value_box(showcase=ICONS["wallet"]):
"Average tip"
@render.express
def average_tip():
d = tips_data()
if d.shape[0] > 0:
perc = d.tip / d.total_bill
f"{perc.mean():.1%}"
with ui.value_box(showcase=ICONS["currency-dollar"]):
"Average bill"
@render.express
def average_bill():
d = tips_data()
if d.shape[0] > 0:
bill = d.total_bill.mean()
f"${bill:.2f}"
with ui.layout_columns(col_widths=[6, 6, 12]):
with ui.card(full_screen=True):
ui.card_header("Tips data")
@render.data_frame
def table():
return render.DataGrid(tips_data())
with ui.card(full_screen=True):
with ui.card_header(class_="d-flex justify-content-between align-items-center"):
"Total bill vs tip"
with ui.popover(title="Add a color variable", placement="top"):
ICONS["ellipsis"]
ui.input_radio_buttons(
"scatter_color",
None,
["none", "sex", "smoker", "day", "time"],
inline=True,
)
@render_plotly
def scatterplot():
color = input.scatter_color()
return px.scatter(
tips_data(),
x="total_bill",
y="tip",
color=None if color == "none" else color,
trendline="lowess",
)
with ui.card(full_screen=True):
with ui.card_header(class_="d-flex justify-content-between align-items-center"):
"Tip percentages"
with ui.popover(title="Add a color variable"):
ICONS["ellipsis"]
ui.input_radio_buttons(
"tip_perc_y",
"Split by:",
["sex", "smoker", "day", "time"],
selected="day",
inline=True,
)
@render_plotly
def tip_perc():
from ridgeplot import ridgeplot
dat = tips_data()
dat["percent"] = dat.tip / dat.total_bill
yvar = input.tip_perc_y()
uvals = dat[yvar].unique()
samples = [[dat.percent[dat[yvar] == val]] for val in uvals]
plt = ridgeplot(
samples=samples,
labels=uvals,
bandwidth=0.01,
colorscale="viridis",
colormode="row-index",
)
plt.update_layout(
legend=dict(
orientation="h", yanchor="bottom", y=1.02, xanchor="center", x=0.5
)
)
return plt
ui.include_css(app_dir / "styles.css")
# --------------------------------------------------------
# Reactive calculations and effects
# --------------------------------------------------------
@reactive.calc
def tips_data():
bill = input.total_bill()
idx1 = tips.total_bill.between(bill[0], bill[1])
idx2 = tips.time.isin(input.time())
return tips[idx1 & idx2]
@reactive.effect
@reactive.event(input.reset)
def _():
ui.update_slider("total_bill", value=bill_rng)
ui.update_checkbox_group("time", selected=["Lunch", "Dinner"])