交互式Plotly Int滑块

Question

交互式Plotly Int滑块

3

大家好，我是一个Python、Plotly和Jupyter Notebook的新手。我想使用一个滑动条来选择天数范围，以此为查询条件创建一张图表。我的问题在于，我希望图表能够在与滑动条交互时自动更新，而不必重新运行查询和图表创建代码。我的代码如下：

slider = widgets.IntSlider()
display(slider)
sliderVal = slider.value

df = pd.read_sql(f"""
SELECT CASE WHEN SiteID LIKE 3 THEN 'BLAH' 
        WHEN SiteID LIKE 4 THEN 'BLAHBLAH' 
        END AS Website, 
        COUNT(1) AS Count
FROM            viewName
WHERE        (TimeStamp > DATEADD(DAY, -{sliderVal}, GETDATE()))
GROUP BY SiteId
ORDER BY Count DESC
           """, conn)

data = [go.Bar(x=df.Website, y=df.Count)]
layout = go.Layout(
    xaxis=dict(
        title='Website'),
    yaxis=dict(
        title='Exception count'),
    title=f'Number of exceptions per user in the last {sliderVal} days')
chart = go.Figure(data=data, layout=layout, )
py.iplot(chart, filename='WebExceptions')

提前感谢!

- gcpreston

下次请尝试提供一个可重现的示例，包括最小的数据集，以便人们可以在需要时运行您的示例。这样做可以更快地获得更精确的答案。 - byouness

1个回答

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- byouness · Accepted Answer

如果您不想重新运行查询，那么您的数据框 df 必须包含您希望 intslider 小部件采用的所有值的结果，然后与小部件链接的函数将仅过滤数据并使用新过滤的数据重新绘制图表。

以下是一个带有虚假数据的示例：

import ipywidgets as widgets
import plotly.offline as py
import plotly.graph_objs as go
import pandas as pd
py.init_notebook_mode(connected = True)

# Dummy data, to be replaced with your query result for the range of sliderVal
df = pd.DataFrame({'Days': [1] * 3 + [2] * 4 + [3] * 5,
                  'Website': [1,2,3, 4,5,6,7, 8,9,10,11,12],
                  'Count': [10,5,30, 15,20,25,12, 18,17,30,23,27]})

def update_plot(sliderVal):
    filtered_df = df.query('Days== ' + str(sliderVal))
    data = [go.Bar(x = filtered_df.Website,
                   y = filtered_df.Count)]
    layout = go.Layout(
        xaxis = dict(title = 'Website'),
        yaxis = dict(title = 'Exception count'),
        title = f'Number of exceptions per user in the last {sliderVal} days')
    chart = go.Figure(data = data, layout = layout, )
    py.iplot(chart, filename = 'WebExceptions')

# links an IntSlider taking values between 1 and 3 to the update_plot function
widgets.interact(update_plot, sliderVal = (1, 3))

下面是 sliderVal = 2 时的结果：