Question

我最近开始学习Dash。昨天，我能够为图表成功添加一个下拉选项，其中每个下拉列表都是数据框中的一列，而图表则是一条简单的线。现在，我想通过添加第二个下拉列表来使下拉列表更加复杂。对于第二个下拉菜单，我希望它指向数据源，而不是实际绘制变量。

这是我正在使用的：具有3个键的字典，其中每个键都是一个具有相似结构的数据框。

df_vals.keys()
['corn', 'soybeans', 'winterwheat']

for i in df_vals.keys():
    print(df_vals[i].to_dict())

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{'time': {0: Timestamp('2020-09-20 00:00:00'), 1: Timestamp('2020-09-20 06:00:00'), 2: Timestamp('2020-09-20 12:00:00'), 3: Timestamp('2020-09-20 18:00:00'), 4: Timestamp('2020-09-21 00:00:00'), 5: Timestamp('2020-09-21 06:00:00'), 6: Timestamp('2020-09-21 12:00:00'), 7: Timestamp('2020-09-21 18:00:00'), 8: Timestamp('2020-09-22 00:00:00'), 9: Timestamp('2020-09-22 06:00:00'), 10: Timestamp('2020-09-22 12:00:00'), 11: Timestamp('2020-09-22 18:00:00'), 12: Timestamp('2020-09-23 00:00:00'), 13: Timestamp('2020-09-23 06:00:00'), 14: Timestamp('2020-09-23 12:00:00'), 15: Timestamp('2020-09-23 18:00:00'), 16: Timestamp('2020-09-24 00:00:00'), 17: Timestamp('2020-09-24 06:00:00'), 18: Timestamp('2020-09-24 12:00:00'), 19: Timestamp('2020-09-24 18:00:00'), 20: Timestamp('2020-09-25 00:00:00'), 21: Timestamp('2020-09-25 06:00:00'), 22: Timestamp('2020-09-25 12:00:00'), 23: Timestamp('2020-09-25 18:00:00'), 24: Timestamp('2020-09-26 00:00:00'), 25: Timestamp('2020-09-26 06:00:00'), 26: 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0.16362961699883719, 51: 0.17188725894346107, 52: 0.2501026608797193, 53: 0.1612095137501214, 54: 0.216608892160778, 55: 0.20807770071949833, 56: 0.3094857791278423, 57: 0.1860693560615717, 58: 0.24028375345500808, 59: 0.2553237949612771, 60: 0.2942185214842173}}

现在，我尝试进行绘图。

from jupyter_dash import JupyterDash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State, ClientsideFunction
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.graph_objs as go
from dash.dependencies import Input, Output
import numpy as np
from plotly.subplots import make_subplots
import plotly.express as px

app = JupyterDash(__name__)
cols=df_vals['corn'].columns[1:]
app.layout = html.Div([
    html.Div([

        html.Div([
            dcc.Dropdown(
                id='variables',
                options=[{'label': i, 'value': i} for i in cols],
                value='2m_temp_prod'
            )
        ]),
        html.Div([
            dcc.Dropdown(
                id='crop_dropdown',
                options=[{'label': i, 'value': i} for i in df_vals.keys()],
                value='corn'
            )
        ]),
    dcc.Graph(id='plot')])
])

@app.callback(
    Output('crop-dropdown', 'options'),
    [Input('variables', 'value')])
def update_crop_dropdown(crop):
    return [{'label': i, 'value': i} for i in df_vals[crop]]


@app.callback(
    Output('plot', 'figure'),
    [Input('crop-dropdown', 'value')],
    [Input('variables', 'value')])


def update_graph(crops, variable_name):
    if crops:
        return go.Figure(data=[go.Scatter(x=df_vals['corn']['time'], y=df_vals['corn'][i][variable_name], mode='lines') for i in crops])
    
    else:
        return go.Figure(data=[])

app.run_server(mode='inline')

似乎我在这里很近。正如我所期望的，我都可以使用两个下拉菜单。但是，没有数据被绘制。我要去哪里错了？ ]

Answer 1

假设我正确理解您要第二个下拉列表选择df，第一个下拉列表指定列，则我修改了update_graph函数：

编辑：使两个下拉列表都更新。

@app.callback(
    Output('plot', 'figure'),
    [Input('crop_dropdown', 'value'),
    Input('variables', 'value')])
def update_graph(crops, variable_name):
    if crops:
        return go.Figure(data=go.Scatter(x=df_vals[crops]['time'], y=df_vals[crops][variable_name], mode='lines'))
    else:
        return go.Figure(data=[])

结果：

下拉菜单可更改字典中的数据源

1 个答案: