如何让我的 Dash 应用程序图表使用提供的下拉项目进行更新？

Question

我正在使用一个 csv 文件，其中包含一家精酿啤酒厂的啤酒销售情况。这些物品按“次要”和“主要”类型分类，因为有一些非酒精产品出售。但我不确定如何让条形图仅使用主要类别类型进行更新...

理想情况下，我尝试按次要类别显示每个选定主要类别的销售数据。代码在这里提供：

# Import required libraries
import pandas as pd
import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output, State
from jupyter_dash import JupyterDash
import plotly.express as px
import plotly.graph_objects as go 

file_loc = "https://raw.githubusercontent.com/Barbj379/Two_Ton/main/Item%20Sales%20Report.csv"

df = pd.read_csv(file_loc)

# Create a dash application
app = JupyterDash(__name__)


app.layout= html.Div(children=[
 # New Div for all elements in the new 'row' of the page
    html.Div([ 
        html.H1(children='Two Ton Dash'),
           html.Div(children='''
            Sales report of last fiscal quarter.
            
        '''),
    html.Div([dcc.Graph(id='graph0'),
       html.Label(["Category",
                dcc.Dropdown(
                id='category-dropdown', clearable=False,
                value='ALCOHOL', options=[
                    {'label': c, 'value': c}
                    for c in df['Major Category'].unique()])
                ]),
        ]),
    ])
])


# Callback function that automatically updates the tip-graph based on chosen colorscale
@app.callback(
    Output('graph0', 'figure'),
    [Input("category-dropdown", "value")]
)
def update_figure(Category):
    new_df = df.groupby(['Minor Category', 'Item Name'])['Net Sales'].sum().reset_index()
    new_df.reset_index()
    fig=px.bar(
        new_df, x="Minor Category", y="Net Sales",  color="Item Name",
        color_continuous_scale=Category,
        title="Items")
    return fig
    


if __name__ == '__main__':
    app.run_server(debug=True)
# Create an app layout

当我运行提供的代码时，会出现一个条形图，显示商品名称销售额的总和，按次要类别类型分组；但下拉菜单不会过滤掉任何内容。为这样的菜鸟道歉！

Answer 1

You should filter your data with

Category

value before groupby it.您可以按以下方式更新您的回调：

@app.callback(
    Output('graph0', 'figure'),
    [Input("category-dropdown", "value")]
)
def update_figure(Category):
    new_df = df[df['Major Category']==Category]
    new_df = new_df.groupby(['Minor Category', 'Item Name'])['Net Sales'].sum().reset_index()
    new_df.reset_index()
    fig=px.bar(
        new_df, x="Minor Category", y="Net Sales",  color="Item Name",
        color_continuous_scale=Category,
        title="Items")
    return fig