如何修复 Plotly Dash 中的“下拉菜单读取”错误

我尝试重新创建网络上显示的以下示例走向数据科学示例

我编写了以下代码并对其进行了修改：

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output

import pandas as pd
import plotly.graph_objs as go

# Step 1. Launch the application
app = dash.Dash()

# Step 2. Import the dataset
filepath = 'https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv'
st = pd.read_csv(filepath)


# range slider options
st['Date'] = pd.to_datetime(st.Date)
dates = ['2015-02-17', '2015-05-17', '2015-08-17', '2015-11-17',
         '2016-02-17', '2016-05-17', '2016-08-17', '2016-11-17', '2017-02-17']

features = st.columns[1:-1]
opts = [{'label' : i, 'value' : i} for i in features]

# Step 3. Create a plotly figure
trace_1 = go.Scatter(x = st.Date, y = st['AAPL.High'],
                    name = 'AAPL HIGH',
                    line = dict(width = 2,
                                color = 'rgb(229, 151, 50)'))
layout = go.Layout(title = 'Time Series Plot',
                   hovermode = 'closest')
fig = go.Figure(data = [trace_1], layout = layout)


# Step 4. Create a Dash layout
app.layout = html.Div([
                # a header and a paragraph
                html.Div([
                    html.H1("This is my first dashboard"),
                    html.P("Dash is so interesting!!")
                         ],
                     style = {'padding' : '50px' ,
                              'backgroundColor' : '#3aaab2'}),
                # adding a plot
                dcc.Graph(id = 'plot', figure = fig),
                # dropdown
                html.P([
                    html.Label("Choose a feature"),
                        dcc.Dropdown(
                                id='opt',                              
                                options=opts,
                                value=features[0],
                                multi=True

                                ),
                # range slider
                html.P([
                    html.Label("Time Period"),
                    dcc.RangeSlider(id = 'slider',
                                    marks = {i : dates[i] for i in range(0, 9)},
                                    min = 0,
                                    max = 8,
                                    value = [1, 7])
                        ], style = {'width' : '80%',
                                    'fontSize' : '20px',
                                    'padding-left' : '100px',
                                    'display': 'inline-block'})
                      ])
                        ])


# Step 5. Add callback functions
@app.callback(Output('plot', 'figure'),
             [Input('opt', 'value'),
             Input('slider', 'value')])
def update_figure(input1, input2):
    # filtering the data
    st2 = st[(st.Date > dates[input2[0]]) & (st.Date < dates[input2[1]])]
    # updating the plot
    trace_1 = go.Scatter(x = st2.Date, y = st2['AAPL.High'],
                        name = 'AAPL HIGH',
                        line = dict(width = 2,
                                    color = 'rgb(229, 151, 50)'))
    trace_2 = go.Scatter(x = st2.Date, y = st2[input1],
                        name = str(input1),
                        line = dict(width = 2,
                                    color = 'rgb(106, 181, 135)'))
    fig = go.Figure(data = [trace_1, trace_2], layout = layout)
    return fig

# Step 6. Add the server clause
if __name__ == '__main__':
    app.run_server(debug = True)

当我更改特征输入时，它不会正确更新绘图，并且不会在图中显示所选特征。

要么是回调函数有问题，要么是第二条跟踪图的初始化有问题。但我无法弄清楚问题出在哪里。

因为您只在回调中提供两个分散跟踪。两者中，一个是静态的'AAPL.High'。所以你需要将下拉值限制为Multi=False.

仅在选择选项时生成有效的绘图，例如'AAPL.LOW'和其他人喜欢dic不会显示第二条轨迹。如果您保留，回调将不会终止multi=True如果始终只选择一个选项，回调仍然有效。当您选择两个或多个选项时，脚本将失败，因为它会尝试在此处查找数据返回块的错误数据：

trace_2 = go.Scatter(x = st2.Date, y = st2[**MULTIINPUT**],
                        name = str(input1),
                        line = dict(width = 2,
                                    color = 'rgb(106, 181, 135)'))

只允许传递一个列 id多输入。如果您想引入更多跟踪，请使用 for 循环。

将代码更改为以下内容：

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output

import pandas as pd
import plotly.graph_objs as go

# Step 1. Launch the application
app = dash.Dash()

# Step 2. Import the dataset
filepath = 'https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv'
st = pd.read_csv(filepath)


# range slider options
st['Date'] = pd.to_datetime(st.Date)
dates = ['2015-02-17', '2015-05-17', '2015-08-17', '2015-11-17',
         '2016-02-17', '2016-05-17', '2016-08-17', '2016-11-17', '2017-02-17']

features = st.columns

opts = [{'label' : i, 'value' : i} for i in features]

# Step 3. Create a plotly figure
trace_1 = go.Scatter(x = st.Date, y = st['AAPL.High'],
                    name = 'AAPL HIGH',
                    line = dict(width = 2,
                                color = 'rgb(229, 151, 50)'))
layout = go.Layout(title = 'Time Series Plot',
                   hovermode = 'closest')
fig = go.Figure(data = [trace_1], layout = layout)


# Step 4. Create a Dash layout
app.layout = html.Div([
                # a header and a paragraph
                html.Div([
                    html.H1("This is a Test Dashboard"),
                    html.P("Dash is great!!")
                         ],
                     style = {'padding' : '50px' ,
                              'backgroundColor' : '#3aaab2'}),
                # adding a plot
                dcc.Graph(id = 'plot', figure = fig),
                # dropdown
                html.P([
                    html.Label("Choose a feature"),
                        dcc.Dropdown(
                                id='opt',
                                options=opts,
                                value=features[0],
                                multi=False

                                ),
                # range slider
                html.P([
                    html.Label("Time Period"),
                    dcc.RangeSlider(id = 'slider',
                                    marks = {i : dates[i] for i in range(0, 9)},
                                    min = 0,
                                    max = 8,
                                    value = [1, 7])
                        ], style = {'width' : '80%',
                                    'fontSize' : '20px',
                                    'padding-left' : '100px',
                                    'display': 'inline-block'})
                      ])
                        ])


# Step 5. Add callback functions
@app.callback(Output('plot', 'figure'),
             [Input('opt', 'value'),
             Input('slider', 'value')])
def update_figure(input1, input2):
    # filtering the data
    st2 = st#[(st.Date > dates[input2[0]]) & (st.Date < dates[input2[1]])]
    # updating the plot
    trace_1 = go.Scatter(x = st2.Date, y = st2['AAPL.High'],
                        name = 'AAPL HIGH',
                        line = dict(width = 2,
                                    color = 'rgb(229, 151, 50)'))
    trace_2 = go.Scatter(x = st2.Date, y = st2[input1],
                        name = str(input1),
                        line = dict(width = 2,
                                    color = 'rgb(106, 181, 135)'))
    fig = go.Figure(data = [trace_1, trace_2], layout = layout)
    return fig

# Step 6. Add the server clause
if __name__ == '__main__':
    app.run_server(debug = True)

我希望这能澄清事情并解决您的问题。 :)