如何从Pandas数据框中输入Plotly条形图的x和y值

Question

我有以下玩具数据集：

df = pd.DataFrame({'Make':['Ford', 'Ford', 'Ford', 'BMW', 'BMW', 'BMW', Mercedes', 'Mercedes', 'Mercedes'],
                          'Score':['88.6', '76.6', '100', '79.1', '86.8', '96.4', '97.3', '98.7', '98.5'],
                          'Dimension':['Speed', 'MPG', 'Styling', 'Speed', 'MPG', 'Styling', 'Speed', 'MPG', 'Styling'],
                          'Month':['Apr-19', 'Apr-19', 'Apr-19', 'Apr-19', 'Apr-19', 'Apr-19', 'Apr-19', 'Apr-19', 'Apr-19']})

我正在使用Plotly和Dash框架来构建基于Web的交互式仪表板。代码如下：

import base64
import datetime
import io
import dash
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objects as go
import dash_table
import pandas as pd


app = dash.Dash()

app.layout = html.Div([
dcc.Upload(
        id='upload-data',
        children=html.Div([
        'Drag and Drop or ',
        html.A('Select Files')
        ]),
        style={
        'width': '100%',
        'height': '60px',
        'lineHeight': '60px',
        'borderWidth': '1px',
        'borderStyle': 'dashed',
        'borderRadius': '5px',
        'textAlign': 'center',
        'margin': '10px'
         },
        # Allow multiple files to be uploaded
        multiple=True
),

html.Div(id='output-data-upload'),
])

def parse_contents(contents, filename, date):
    content_type, content_string = contents.split(',')

    decoded = base64.b64decode(content_string)
    try:
        if 'csv' in filename:
        # Assume that the user uploaded a CSV file
            df = pd.read_csv(
                io.StringIO(decoded.decode('utf-8')))
        elif 'xls' in filename:
        # Assume that the user uploaded an excel file
            df = pd.read_excel(io.BytesIO(decoded))
    except Exception as e:
        print(e)
        return html.Div([
            'There was an error processing this file.'
        ])

    return html.Div([
        html.H5(filename),
        html.H6(datetime.datetime.fromtimestamp(date)),

        dash_table.DataTable(
            data=df.to_dict('records'),
            columns=[{'name': i, 'id': i} for i in df.columns]
        ),

        html.Hr(),  # horizontal line

        #### How to get the x and y values DYNAMICALLY from the data frame to pass into the Bar() function? ####

        dcc.Graph(
            figure = go.Figure(data=[
            go.Bar(name=df.columns.values[0], x=pd.unique(df['Make']), y=[88.6, 76.6, 100], text=[88.6, 76.6, 100], textposition='auto'),
            go.Bar(name=df.columns.values[1], x=pd.unique(df['Make']), y=[92.5, 93.6, 93.4], text=[92.5, 93.6, 93.4], textposition='auto'),
            go.Bar(name=df.columns.values[2], x=pd.unique(df['Make']), y=[99.1, 99.2, 95.9], text=[99.1, 99.2, 95.9], textposition='auto'),
            ])
            ),        


        html.Hr(),

        # For debugging, display the raw contents provided by the web browser
        html.Div('Raw Content'),
        html.Pre(contents[0:200] + '...', style={
            'whiteSpace': 'pre-wrap',
            'wordBreak': 'break-all'
        })
    ])

@app.callback(Output('output-data-upload', 'children'),
              [Input('upload-data', 'contents')],
              [State('upload-data', 'filename'),
               State('upload-data', 'last_modified')])
def update_output(list_of_contents, list_of_names, list_of_dates):
    if list_of_contents is not None:
        children = [
            parse_contents(c, n, d) for c, n, d in
            zip(list_of_contents, list_of_names, list_of_dates)]
        return children

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

总而言之，用户上传一个.csv文件，并创建一个Pandas data frame。然后根据数据框中的数据绘制条形图。

如您所见，go.Bar()函数的x和y值来自df数据帧。 x值的数量可能会波动（在这种情况下为3，但可能为2或10，或介于两者之间的任意值）。我以一种非常微妙的方式将x值硬编码为列名中的索引值。

问题：

1]最动态地读取x值的Python方法是什么，以使代码接受可变数量的x值？

2）从y数据帧动态读取关联的df值的最佳方法是什么？ （出于本示例的目的，我将它们完全硬编码在其中）

提前感谢？

Answer 1

您是否以此方式尝试过？

    dcc.Graph(
        figure = go.Figure(data=[
        go.Bar(name=df.columns.values[0], x=pd.unique(df['Make']), y=df['Score'], text=df['Score'], textposition='auto'),
        go.Bar(name=df.columns.values[1], x=pd.unique(df['Make']), y=df['Score'], text=df['Score'], textposition='auto'),
        go.Bar(name=df.columns.values[2], x=pd.unique(df['Make']), y=df['Score'], text=df['Score'], textposition='auto'),
        ])
        ),