Interaktive Tabellentools im Sales-Dashboard
Das übergreifende Sales-Dashboard hat seit deinem Start einen weiten Weg zurückgelegt.
Das Dashboard wurde im ganzen Unternehmen verteilt und hat sehr positives Feedback erhalten. Es gibt jedoch Wünsche, die tabellarische Komponente interaktiver zu machen. Konkret soll es möglich sein, eine bestimmte Spalte auszuwählen und damit die Achse im untenstehenden Scatterplot zu ändern.
Diese Übung ist Teil des Kurses
<Kurs>Dashboards mit Dash und Plotly erstellen</Kurs>Übungsanweisungen
- Aktiviere die Auswahl einer einzelnen Zeile im
grid, indem du den ParameterrowSelectionunterhalb von Zeile25setzt. - Erstelle unterhalb von Zeile
63einen Callback, der dieselectedRowsvonmy_gridnutzt, um die Figurscatter_comparezu aktualisieren – mit dem ausgewählten Land als großem roten Punkt hervorgehoben.
Interaktive praktische Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
from dash import Dash, dcc, html, Input, Output, callback
import plotly.express as px
import pandas as pd
from dash_ag_grid import AgGrid
ecom_sales = pd.read_csv('/usr/local/share/datasets/ecom_sales.csv')
logo_link = 'https://assets.datacamp.com/production/repositories/5893/datasets/fdbe0accd2581a0c505dab4b29ebb66cf72a1803/e-comlogo.png'
major_categories = list(ecom_sales['Major Category'].unique())
large_tb = ecom_sales.groupby(['Country'])['OrderValue'].agg(['sum', 'count', 'mean', 'median']).reset_index().rename(columns={'count':'Sales Volume', 'sum':'Total Sales ($)', 'mean':'Average Order Value ($)', 'median':'Median Order Value ($)'})
ecom_country = ecom_sales.groupby('Country')['OrderValue'].agg('sum').reset_index(name='Total Sales ($)')
bar_fig_country = px.bar(ecom_country, x='Total Sales ($)', y='Country', width=500, height=450, title='Total Sales by Country (Hover to filter the Minor Category bar chart!)', custom_data=['Country'], color='Country', color_discrete_map={'United Kingdom':'lightblue', 'Germany':'orange', 'France':'darkblue', 'Australia':'green', 'Hong Kong':'pink'})
money_fmt = {"function": ("params.value.toLocaleString('en-US', {style: 'currency', currency: 'USD'})")}
column_defs = [
{"field": "Country"},
{"field": "Total Sales ($)", "valueFormatter": money_fmt},
{"field": "Average Order Value ($)", "valueFormatter": money_fmt},
{"field": "Median Order Value ($)", "valueFormatter": money_fmt},
{"field": "Sales Volume"},
]
grid = AgGrid(
id="my_grid",
columnDefs=column_defs,
rowData=large_tb.to_dict("records"),
# Enable single-row selection
dashGridOptions={"____": "____"},
defaultColDef={
"cellStyle": {
"textAlign": "left",
"backgroundColor": "black",
"color": "white"}}
)
app = Dash()
app.layout = [
html.Img(src=logo_link,
style={'margin':'30px 0px 0px 0px' }),
html.H1('Sales breakdowns'),
html.Div([
html.H2('Controls'),
html.Br(),
html.H3('Major Category Select'),
dcc.Dropdown(id='major_cat_dd',
options=[{'label':category, 'value':category} for category in major_categories],
style={'width':'200px', 'margin':'0 auto'}),
html.Br(),
html.H3('Minor Category Select'),
dcc.Dropdown(id='minor_cat_dd', style={'width':'200px', 'margin':'0 auto'})],
style={'width':'350px', 'height':'360px', 'display':'inline-block', 'vertical-align':'top', 'border':'1px solid black', 'padding':'20px'}),
html.Div([
html.H3(id='chosen_major_cat_title'),
dcc.Graph(id='sales_line')],
style={'width':'700px', 'height':'380px','display':'inline-block', 'margin-bottom':'5px'}),
grid,
html.Br(),
html.Div([
dcc.Graph(id='scatter_compare'),
dcc.Graph(id='major_cat', figure=bar_fig_country, style={'display':'inline-block'}),
dcc.Graph(id='minor_cat', style={'display':'inline-block'})],
style={'width':'1000px', 'height':'650px','display':'inline-block'})
]
# Create a callback with the right input
@callback(
Output('scatter_compare', 'figure'),
Input('my_grid', '____')
)
def update_scatter(selected_rows):
fig = px.scatter(
large_tb,
x='Sales Volume',
y='Total Sales ($)',
color='Country',
title='Sales Volume vs Total Sales ($) — click a row to highlight')
if selected_rows:
sel_df = pd.DataFrame(selected_rows)
highlight = px.scatter(
sel_df,
x='Sales Volume',
y='Total Sales ($)',
color_discrete_sequence=['#ff0000'],
size=[15] * len(sel_df))
fig.add_trace(highlight.data[0])
return fig
@callback(
Output('minor_cat_dd', 'options'),
Output('chosen_major_cat_title', 'children'),
Input('major_cat_dd', 'value'))
def update_dd(major_cat_dd):
major_minor = ecom_sales[['Major Category', 'Minor Category']].drop_duplicates()
relevant_minor = major_minor[major_minor['Major Category'] == major_cat_dd]['Minor Category'].values.tolist()
minor_options = [dict(label=x, value=x) for x in relevant_minor]
if not major_cat_dd:
major_cat_dd = 'ALL'
major_cat_title = f'This is in the Major Category of : {major_cat_dd}'
return minor_options, major_cat_title
@callback(
Output('sales_line', 'figure'),
Input('minor_cat_dd', 'value'))
def update_line(minor_cat):
minor_cat_title = 'All'
ecom_line = ecom_sales.copy()
if minor_cat:
minor_cat_title = minor_cat
ecom_line = ecom_line[ecom_line['Minor Category'] == minor_cat]
ecom_line = ecom_line.groupby('Year-Month')['OrderValue'].agg('sum').reset_index(name='Total Sales ($)')
line_graph = px.line(ecom_line, x='Year-Month', y='Total Sales ($)', title=f'Total Sales by Month for Minor Category: {minor_cat_title}', height=350)
return line_graph
@callback(
Output('minor_cat', 'figure'),
Input('major_cat', 'hoverData'))
def update_min_cat_hover(hoverData):
hover_country = 'Australia'
if hoverData:
hover_country = hoverData['points'][0]['customdata'][0]
minor_cat_df = ecom_sales[ecom_sales['Country'] == hover_country]
minor_cat_agg = minor_cat_df.groupby('Minor Category')['OrderValue'].agg('sum').reset_index(name='Total Sales ($)')
ecom_bar_minor_cat = px.bar(minor_cat_agg, x='Total Sales ($)', y='Minor Category', orientation='h', height=450, width=480,title=f'Sales by Minor Category for: {hover_country}')
ecom_bar_minor_cat.update_layout({'yaxis':{'dtick':1, 'categoryorder':'total ascending'}, 'title':{'x':0.5}})
return ecom_bar_minor_cat
if __name__ == '__main__':
app.run(debug=True)