交互式 Plotly Int 滑块

Question

您好，我对 Python、Plotly 和 Jupyter Notebook 还很陌生。我想使用滑块 select 天数作为查询中的范围，从中创建图表。我唯一的问题是我希望图形在与滑块交互时自动更新，而不必重新运行查询和图形创建。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')

提前致谢！

Answer 1

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，然后链接到小部件的函数将简单地过滤数据并使用新的过滤数据重新绘制图形。

这是一个包含一些虚拟数据的示例：

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))

这是 sliderVal = 2 的结果：

交互式 Plotly Int 滑块

Interactive Plotly Int Slider

python

plotly

jupyter

ipywidgets