根据下拉列表和日期选择器为某个唯一值在虚线图中创建图表

Question

我有一个简单的数据库，如下图所示：

和查询看起来像：

SELECT 
       [Date]
      ,[eNodeBName]
      ,[Downlinkbandwidth]
      ,[DownlinkEARFCN]
      ,[CellName]
      ,[LocalCellId]
      ,[PhysicalcellID]
      ,[LRRCConnReqAtt]
      ,[RRCSetupSuccessRate]
      ,[InterFreqSuccessRate4G]
      ,[IntraRATHOSucccessRate]
      ,[IntraFreqSuccessRate4G]
      ,[CellDLMaxThroughputMbps]
      ,[CellDownlinkAverageThroughputMbps]
  FROM [myDB].[dbo].[input]

现在我需要创建一个交互式图表，该图表取决于日期选择器和下拉列表等输入。

由于这是我创建的示例 GUI，用于绘制图表抛出此输入，如下图所示：

现在我正在根据以下列名称创建图表，如下图所示：

因为这是相关的查询，如下所示：

SELECT 
       [Date]
      ,[CellName]
      ,[LRRCConnReqAtt]
      ,[RRCSetupSuccessRate]
      ,[InterFreqSuccessRate4G]
      ,[IntraRATHOSucccessRate]
      ,[IntraFreqSuccessRate4G]
      ,[CellDLMaxThroughputMbps]
      ,[CellDownlinkAverageThroughputMbps]
  FROM [myDB].[dbo].[input]

所以现在 X 轴应该是Date列，与下面的列相关的 y 轴是KPI列：

SELECT 
       [LRRCConnReqAtt]
      ,[RRCSetupSuccessRate]
      ,[InterFreqSuccessRate4G]
      ,[IntraRATHOSucccessRate]
      ,[IntraFreqSuccessRate4G]
      ,[CellDLMaxThroughputMbps]
      ,[CellDownlinkAverageThroughputMbps]
  FROM [myDB].[dbo].[input]

所以现在我们有一个包含唯一值的唯一列被称为CellName，这个单元格名称我想根据日期列和 KPI 列为这个唯一值创建一个简单的图表。

例如，我想根据 12 月 27 日至 1 月 9 日的数据显示CellNameKPI的某个= 2002334的折线图LRRCConnReqAtt。所以我需要一个如下图所示的图表，这是一个在 Excel 中创建的示例图表。

这是我的代码：

import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
from sqlalchemy import create_engine
import datetime
from datetime import datetime as dt
from dash.dependencies import Input, Output

# connect db
engine = create_engine('mssql+pyodbc://xxxxxx\SMxxxxxARTRNO_EXPRESS/myDB?driver=SQL+Server+Native+Client+11.0')
cursor = engine.raw_connection().cursor()

start = datetime.datetime(2019, 12, 2)
end = datetime.datetime(2019, 12, 15)

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

lte_kpis = pd.read_sql('SELECT * FROM [myDB].[dbo].[input]',
                       engine)

lte_kpis_raw = pd.read_sql('SELECT LRRCConnReqAtt, RRCSetupSuccessRate, InterFreqSuccessRate4G, IntraRATHOSucccessRate, IntraFreqSuccessRate4G,CellDLMaxThroughputMbps, CellDownlinkAverageThroughputMbps FROM [myDB].[dbo].[input]',
                           engine)

scale_1 = ['LRRCConnReqAtt']
scale_2 = ['RRCSetupSuccessRate', 'InterFreqSuccessRate4G', 'IntraRATHOSucccessRate', 'IntraFreqSuccessRate4G']
scale_3 = ['CellDLMaxThroughputMbps', 'CellDownlinkAverageThroughputMbps']

pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)

availble_cell = lte_kpis['CellName'].unique()

# availble_cell = lte_kpis.unique(lte_kpis[['Date', 'Site Name', 'Cell CI', 'Cell LAC']].values.ravel('K'))

app.layout = html.Div([
    dcc.Dropdown(
        id='cell-name-xaxis-column',
        options=[{'label': i, 'value': i} for i in availble_cell],
        value='2205516'
    ),

    dcc.Dropdown(
        id='myColumns',
        options=[{'label': col, 'value': col} for col in lte_kpis_raw.columns],
        multi=True,
        value='LRRCConnReqAtt'
    ),

    dcc.DatePickerRange(
        id='my-date-picker-range',
        min_date_allowed=dt(1995, 8, 5),
        max_date_allowed=dt(2030, 9, 19),
        initial_visible_month=dt(2019, 10, 5),
        start_date=dt(2019, 10, 1),
        end_date=dt(2020, 1, 1)
    ),
    html.Div(id='output-container-date-picker-range'),

    dcc.Graph(
        style={'height': 300},
        id='my-graph'
    )

])


@app.callback(
    Output('my-graph', 'figure'),
    [Input('cell-name-xaxis-column', 'value'),
     Input('myColumns', 'value')])
def update_graph(xaxis_column_name, yaxis_column_name, date_value):
    dff = lte_kpis[lte_kpis['Date'] == date_value]

    return {
        'data': [dict(
            x=dff[dff['Date'] == xaxis_column_name]['Value'],
            y=dff[dff['Date'] == yaxis_column_name]['Value'],
            text=dff[dff['Date'] == yaxis_column_name]['CellName'],
            mode='line',
            line={
                'size': 15,
                'opacity': 0.5
            }
        )],
    }


if __name__ == '__main__':
    app.run_server(debug=True)

请注意，我想将多个 KPI 放在一张具有不同图表的图表中....

由于这些 KPI 中的比例值略有不同，因此我尝试创建三种类型的对象，其列名比例值如下代码所示

scale_1 = ['LRRCConnReqAtt']
scale_2 = ['RRCSetupSuccessRate', 'InterFreqSuccessRate4G', 'IntraRATHOSucccessRate', 'IntraFreqSuccessRate4G']
scale_3 = ['CellDLMaxThroughputMbps', 'CellDownlinkAverageThroughputMbps']

这是我发现的错误：

TypeError: update_graph() missing 1 required positional argument: 'date_value'

Traceback (most recent call last)
File "C:\Users\mwx825326\PycharmProjects\MyReference\venv\Lib\site-packages\dash\dash.py", line 1337, in add_context
output_value = func(*args, **kwargs)  # %% callback invoked %%
TypeError: update_graph() missing 1 required positional argument: 'date_value'
Traceback (most recent call last):
  File "C:\Users\mwx825326\PycharmProjects\MyReference\venv\Lib\site-packages\dash\dash.py", line 1337, in add_context
    output_value = func(*args, **kwargs)  # %% callback invoked %%
TypeError: update_graph() missing 1 required positional argument: 'date_value'

任何帮助表示赞赏.!!!