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import faicons as fa
import plotly.express as px
from shinywidgets import render_plotly
from shiny import reactive, render
from shiny.express import input, ui
from shared import app_dir, tips # فرض بر این است که tips دیتافریم شماست
# محدودهی سنی موجود در داده
bill_rng = (min(tips.سن), max(tips.سن))
# تنظیمات صفحه
ui.page_opts(title="تحلیل احساسات کاربران", fillable=True)
# ------------------ Sidebar ------------------
with ui.sidebar(open="desktop"):
ui.input_slider(
"سن",
"رنج سنی",
min=bill_rng[0],
max=bill_rng[1],
value=bill_rng,
pre="سال",
)
ui.input_checkbox_group(
"شبکه_اجتماعی",
"انتخاب شبکه اجتماعی",
tips["شبکه اجتماعی"].unique().tolist(),
selected=tips["شبکه اجتماعی"].unique().tolist(),
inline=True,
)
ui.input_action_button("reset", "بازنشانی فیلتر")
# ------------------ آیکونها ------------------
ICONS = {
"user": fa.icon_svg("user", "regular"),
"wallet": fa.icon_svg("wallet"),
"currency-dollar": fa.icon_svg("dollar-sign"),
"ellipsis": fa.icon_svg("ellipsis"),
}
# ------------------ Value Boxes ------------------
with ui.layout_columns(fill=False):
with ui.value_box(showcase=ICONS["user"]):
"تعداد کاربران"
@render.express
def total_tippers():
data = tips_data()
print(data.shape[0])
with ui.value_box(showcase=ICONS["wallet"]):
"میانگین احساس"
@render.express
def average_tip():
data = tips_data()
if data.shape[0] > 0:
print(data["احساس"].mean())
with ui.value_box(showcase=ICONS["currency-dollar"]):
"میانگین سن"
@render.express
def average_bill():
data = tips_data()
if data.shape[0] > 0:
print(f"{data['سن'].mean():.1f} سال")
# ------------------ جدول و نمودار ------------------
with ui.layout_columns(col_widths=[6, 6, 12]):
with ui.card(full_screen=True):
ui.card_header("جدول دادهها")
@render.data_frame
def table():
return tips_data()
@render_plotly
def scatterplot():
data = tips_data()
if data.shape[0] == 0:
return {}
return px.scatter(
data,
x="سن",
y="احساس",
color="جنسیت",
trendline="lowess",
)
with ui.card(full_screen=True):
with ui.card_header(class_="d-flex justify-content-between align-items-center"):
"توزیع احساس بر اساس ویژگیها"
with ui.popover(title="انتخاب ویژگی برای مقایسه"):
ICONS["ellipsis"]
ui.input_radio_buttons(
"tip_perc_y",
"تفکیک بر اساس:",
["جنسیت", "موضوع", "سطح تأثیر"],
selected="جنسیت",
inline=True,
)
@render_plotly
def tip_perc():
from ridgeplot import ridgeplot
dat = tips_data()
if dat.shape[0] == 0:
return {}
dat["percent"] = dat["احساس"]
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
# ------------------ CSS ------------------
ui.include_css(app_dir / "styles.css")
# ------------------ Reactive ------------------
@reactive.calc
def tips_data():
رنج_سنی = input.سن()
شبکهها = input.شبکه_اجتماعی()
idx1 = tips["سن"].between(رنج_سنی[0], رنج_سنی[1])
idx2 = tips["شبکه اجتماعی"].isin(شبکهها)
return tips[idx1 & idx2]
@reactive.effect
@reactive.event(input.reset)
def _():
ui.update_slider("سن", value=bill_rng)
ui.update_checkbox_group("شبکه_اجتماعی", selected=tips["شبکه اجتماعی"].unique().tolist())
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