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Plotly：如何使用下拉菜单按年、月和日对数据进行子集化？

[英]Plotly: How to subset data by year, month and day using dropdown menus?

 原文  2020-06-21 16:33:27  2   2    python/ drop-down-menu/ plotly

问题描述

I am trying to plot three graphs (day, month, year) and give the user the option to pick which graph they want to see with a dropdown menu.我正在尝试 plot 三个图表（日、月、年），并让用户可以通过下拉菜单选择他们想要查看的图表。 When I do it for (day, month) it works perfectly (with month showing as the default graph), but when I add (year), then (day, month) don't show up (in this scenario, I want year to be the default graph).当我为（日，月）执行此操作时，它工作得很好（月份显示为默认图表），但是当我添加（年）时，（日，月）不显示（在这种情况下，我想要年作为默认图表）。

This is the working code:这是工作代码： 

 # Plot Day temp_day = pd.DataFrame(df.day.value_counts()) temp_day.reset_index(inplace=True) temp_day.columns = ['day', 'tweet_count'] temp_day.sort_values(by=['day'], inplace=True) temp_day.reset_index(inplace=True, drop=True) trace_day = go.Scatter( x=temp_day.day.values, y=temp_day.tweet_count.values, text = [f"{humanize.naturaldate(day)}: {count} tweets" for day,count in zip(temp_day.day.values,temp_day.tweet_count.values)], hoverinfo='text', mode='lines', line = { 'color': my_color, 'width': 1.2 }, visible=False, name="Day" ) # Plot Month temp_month = pd.DataFrame(df.YYYYMM.value_counts()) temp_month.reset_index(inplace=True) temp_month.columns = ['YYYYMM', 'tweet_count'] temp_month['YYYYMM'] = temp_month['YYYYMM'].dt.strftime('%Y-%m') temp_month.sort_values(by=['YYYYMM'], inplace=True) temp_month.reset_index(inplace=True, drop=True) trace_month = go.Scatter( x=temp_month.YYYYMM.values, y=temp_month.tweet_count.values, mode='lines', line = { 'color': my_color, 'width': 1.2 }, visible=True, name="Month" ) # Menus updatemenus = list([ dict( active=0, buttons=list([ dict(label = 'Month', method = 'update', args = [{'visible': [True, False]}, {'title': 'Number of Tweets per Month'}]), dict(label = 'Day', method = 'update', args = [{'visible': [False, True]}, {'title': 'Number of Tweets per Day'}]), ]), ) ]) # Layout layout = go.Layout(title="Number of Tweets -- Pick a scale", updatemenus=updatemenus, ) fig = go.Figure(data=[trace_month, trace_day], layout=layout) iplot(fig)

This is the code that doesn't work and I can't figure out why:这是不起作用的代码，我不知道为什么： 

 # Plot Day temp_day = pd.DataFrame(df.day.value_counts()) temp_day.reset_index(inplace=True) temp_day.columns = ['day', 'tweet_count'] temp_day.sort_values(by=['day'], inplace=True) temp_day.reset_index(inplace=True, drop=True) trace_day = go.Scatter( x=temp_day.day.values, y=temp_day.tweet_count.values, text = [f"{humanize.naturaldate(day)}: {count} tweets" for day,count in zip(temp_day.day.values,temp_day.tweet_count.values)], hoverinfo='text', mode='lines', line = { 'color': my_color, 'width': 1.2 }, visible=False, name="Day" ) # Plot Month temp_month = pd.DataFrame(df.YYYYMM.value_counts()) temp_month.reset_index(inplace=True) temp_month.columns = ['YYYYMM', 'tweet_count'] temp_month['YYYYMM'] = temp_month['YYYYMM'].dt.strftime('%Y-%m') temp_month.sort_values(by=['YYYYMM'], inplace=True) temp_month.reset_index(inplace=True, drop=True) trace_month = go.Scatter( x=temp_month.YYYYMM.values, y=temp_month.tweet_count.values, mode='lines', line = { 'color': my_color, 'width': 1.2 }, visible=False, name="Month" ) # Plot year temp_year = pd.DataFrame(df.year.value_counts()) temp_year.reset_index(inplace=True) temp_year.columns = ['year', 'tweet_count'] temp_year.sort_values(by=['year'], inplace=True) temp_year.reset_index(inplace=True, drop=True) trace_year = go.Scatter( x=temp_year.year.values, y=temp_year.tweet_count.values, text = [f"Year {year}: {count:,.0f} tweets" for year,count in zip(temp_year.year.values,temp_year.tweet_count.values)], hoverinfo='text', mode='lines+markers', line = { 'color': my_color, 'width': 1.2 }, visible=True, name="Year" ) # Menus updatemenus = list([ dict( active=0, buttons=list([ dict(label = 'Year', method = 'update', args = [{'visible': [True, False, False]}, {'title': 'Number of Tweets per Month'}]), dict(label = 'Month', method = 'update', args = [{'visible': [False, True, False]}, {'title': 'Number of Tweets per Month'}]), dict(label = 'Day', method = 'update', args = [{'visible': [False, False, True]}, {'title': 'Number of Tweets per Day'}]), ]), ) ]) # Layout layout = go.Layout(title="Number of Tweets -- Pick a scale", updatemenus=updatemenus, ) fig = go.Figure(data=[trace_year, trace_month, trace_day], layout=layout) iplot(fig)

Here's the data:这是数据： 

 # Year Scatter({ 'hoverinfo': 'text', 'line': {'color': '#ff00a7', 'width': 1.2}, 'mode': 'lines+markers', 'name': 'Year', 'text': [Year 2011: 73 tweets, Year 2012: 562 tweets, Year 2013: 1,153 tweets, Year 2014: 700 tweets, Year 2015: 2,104 tweets, Year 2016: 1,816 tweets, Year 2017: 1,691 tweets, Year 2018: 1,082 tweets, Year 2019: 914 tweets, Year 2020: 482 tweets], 'visible': False, 'x': array([2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]), 'y': array([ 73, 562, 1153, 700, 2104, 1816, 1691, 1082, 914, 482]) }) # Month Scatter({ 'line': {'color': '#ff00a7', 'width': 1.2}, 'mode': 'lines', 'name': 'Month', 'visible': False, 'x': array(['2011-06', '2011-07', '2011-08', '2011-09', '2011-10', '2011-11', '2011-12', '2012-01', '2012-02', '2012-03', '2012-04', '2012-05', '2012-06', '2012-07', '2012-08', '2012-09', '2012-10', '2012-11', '2012-12', '2013-01', '2013-02', '2013-03', '2013-04', '2013-05', '2013-06', '2013-07', '2013-08', '2013-09', '2013-10', '2013-11', '2013-12', '2014-01', '2014-02', '2014-03', '2014-04', '2014-05', '2014-06', '2014-07', '2014-08', '2014-09', '2014-10', '2014-11', '2014-12', '2015-01', '2015-02', '2015-03', '2015-04', '2015-05', '2015-06', '2015-07', '2015-08', '2015-09', '2015-10', '2015-11', '2015-12', '2016-01', '2016-02', '2016-03', '2016-04', '2016-05', '2016-06', '2016-07', '2016-08', '2016-09', '2016-10', '2016-11', '2016-12', '2017-01', '2017-02', '2017-03', '2017-04', '2017-05', '2017-06', '2017-07', '2017-08', '2017-09', '2017-10', '2017-11', '2017-12', '2018-01', '2018-02', '2018-03', '2018-04', '2018-05', '2018-06', '2018-07', '2018-08', '2018-09', '2018-10', '2018-11', '2018-12', '2019-01', '2019-02', '2019-03', '2019-04', '2019-05', '2019-06', '2019-08', '2019-09', '2019-10', '2019-11', '2019-12', '2020-01', '2020-02', '2020-03', '2020-04', '2020-05', '2020-06'], dtype=object), 'y': array([ 1, 1, 2, 8, 4, 20, 37, 79, 16, 13, 8, 12, 2, 5, 68, 139, 57, 64, 99, 182, 63, 60, 74, 128, 59, 109, 126, 86, 77, 112, 77, 78, 44, 32, 22, 33, 46, 61, 66, 109, 81, 78, 50, 140, 151, 297, 173, 225, 69, 119, 213, 177, 134, 217, 189, 255, 149, 114, 127, 154, 116, 110, 150, 184, 179, 117, 161, 48, 115, 147, 153, 199, 174, 195, 154, 162, 114, 140, 90, 156, 81, 107, 62, 64, 49, 128, 127, 60, 89, 115, 44, 58, 86, 65, 102, 93, 82, 78, 158, 65, 50, 77, 55, 71, 70, 105, 124, 57]) }) # Day Scatter({ 'hoverinfo': 'text', 'line': {'color': '#ff00a7', 'width': 1.2}, 'mode': 'lines', 'name': 'Day', 'text': [Jun 04 2011: 1 tweets, Jul 17 2011: 1 tweets, Aug 11 2011: 1 tweets, ..., Jun 17: 4 tweets, Jun 18: 1 tweets, Jun 19: 3 tweets], 'visible': False, 'x': array([datetime.date(2011, 6, 4), datetime.date(2011, 7, 17), datetime.date(2011, 8, 11), ..., datetime.date(2020, 6, 17), datetime.date(2020, 6, 18), datetime.date(2020, 6, 19)], dtype=object), 'y': array([1, 1, 1, ..., 4, 1, 3]) })

2 个解决方案

解决方案1
 4  2020-06-25 11:06:26

It's hard to tell what works and what doesn't in your code snippets since you've provided a datasample that just does not work.由于您提供了一个不起作用的数据样本，因此很难分辨代码片段中哪些有效，哪些无效。 However, I do have a suggestion for you that answers your question directly regarding:但是，我确实有一个建议可以直接回答您的问题：

I am trying to plot three graphs (day, month, year) and give the user the option to pick which graph they want to see with a dropdown menu我正在尝试 plot 三个图表（日、月、年），并让用户可以通过下拉菜单选择他们想要查看的图表

The snippet below will let you chose between two datasets: year and month .下面的代码片段将让您在两个数据集之间进行选择： year和month 。 And those are the exact datasets that you've provided.这些是您提供的确切数据集。 When you've got a working sample for days , that dataset can be easily included.当您有days的工作样本时，可以轻松地包含该数据集。 And I'll happily do that for you when you're ready.当你准备好时，我很乐意为你做这件事。

Anyway, the following plot will let you chose year and month using a dropdown menu.无论如何，下面的 plot 将让您使用下拉菜单选择year和month 。 And don't worry if the design wrt line and marker style are not to your liking.如果设计 wrt 线条和标记样式不符合您的喜好，请不要担心。 That is simply included in the code as placeholders for you to change as you see fit.这只是作为占位符包含在代码中，供您根据需要进行更改。

Year年

在此处输入图像描述

Month月

在此处输入图像描述

DAY天

(tba...) （待定……）

Complete code完整代码

import plotly.graph_objects as go
import pandas as pd

df_y=pd.DataFrame({'x':[2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020],
                   'y':[  73,  562, 1153,  700, 2104, 1816, 1691, 1082,  914,  482]})

df_m=pd.DataFrame({'x':['2011-06', '2011-07', '2011-08', '2011-09', '2011-10', '2011-11',
                        '2011-12', '2012-01', '2012-02', '2012-03', '2012-04', '2012-05',
                        '2012-06', '2012-07', '2012-08', '2012-09', '2012-10', '2012-11',
                        '2012-12', '2013-01', '2013-02', '2013-03', '2013-04', '2013-05',
                        '2013-06', '2013-07', '2013-08', '2013-09', '2013-10', '2013-11',
                        '2013-12', '2014-01', '2014-02', '2014-03', '2014-04', '2014-05',
                        '2014-06', '2014-07', '2014-08', '2014-09', '2014-10', '2014-11',
                        '2014-12', '2015-01', '2015-02', '2015-03', '2015-04', '2015-05',
                        '2015-06', '2015-07', '2015-08', '2015-09', '2015-10', '2015-11',
                        '2015-12', '2016-01', '2016-02', '2016-03', '2016-04', '2016-05',
                        '2016-06', '2016-07', '2016-08', '2016-09', '2016-10', '2016-11',
                        '2016-12', '2017-01', '2017-02', '2017-03', '2017-04', '2017-05',
                        '2017-06', '2017-07', '2017-08', '2017-09', '2017-10', '2017-11',
                        '2017-12', '2018-01', '2018-02', '2018-03', '2018-04', '2018-05',
                        '2018-06', '2018-07', '2018-08', '2018-09', '2018-10', '2018-11',
                        '2018-12', '2019-01', '2019-02', '2019-03', '2019-04', '2019-05',
                        '2019-06', '2019-08', '2019-09', '2019-10', '2019-11', '2019-12',
                        '2020-01', '2020-02', '2020-03', '2020-04', '2020-05', '2020-06'],
                    'y':[  1,   1,   2,   8,   4,  20,  37,  79,  16,  13,   8,  12,   2,   5,
                         68, 139,  57,  64,  99, 182,  63,  60,  74, 128,  59, 109, 126,  86,
                         77, 112,  77,  78,  44,  32,  22,  33,  46,  61,  66, 109,  81,  78,
                         50, 140, 151, 297, 173, 225,  69, 119, 213, 177, 134, 217, 189, 255,
                        149, 114, 127, 154, 116, 110, 150, 184, 179, 117, 161,  48, 115, 147,
                        153, 199, 174, 195, 154, 162, 114, 140,  90, 156,  81, 107,  62,  64,
                         49, 128, 127,  60,  89, 115,  44,  58,  86,  65, 102,  93,  82,  78,
                        158,  65,  50,  77,  55,  71,  70, 105, 124,  57]})

# IMPROVEMENT 1
# INSERT ANOTHER DATAFRAME FOR DAYS HERE WITH THE SAME STRUCTURE AS ABOVE

# IMPROVEMENT 1
# INCLUDE THE DATAFRAME AS VALUE AND THE NAME df_d as key
# in the dict below:

dfc = {'year':df_y, 'month':df_m}

# set index
for df in dfc.keys():
    dfc[df].set_index('x', inplace=True)


# plotly start 
fig = go.Figure()
# menu setup    
updatemenu= []

# buttons for menu 1, names
buttons=[]

# plotly start 
fig = go.Figure()
# one trace for each column per dataframe: AI and RANDOM
for df in dfc.keys():
    fig.add_trace(go.Scatter(x=dfc[df].index,
                             y=dfc[df]['y'],
                             visible=True,
                             #marker=dict(size=12, line=dict(width=2)),
                             #marker_symbol = 'diamond',
                             name=df
                  )
             )


# some line settings for fun
lines = [dict(color='royalblue', width=2, dash='dot'), dict(color='firebrick', width=1, dash='dash')]
markers = [dict(size=12, line=dict(width=2)), dict(size=12, line=dict(width=2))]

# create traces for each color: 
# build argVals for buttons and create buttons
for i, df in enumerate(dfc.keys()):
    args_y = []
    args_x = []
    for col in dfc[df]:
        args_y.append(dfc[df][col].values)
        args_x.append(dfc[df].index)
    argVals = [ {'y':args_y, 'x':args_x,
                 'marker':markers[i], 'line': lines[i]}]

    buttons.append(dict(method='update',
                        label=df,
                        visible=True,
                        args=argVals))

updatemenu=[]
your_menu=dict()
updatemenu.append(your_menu)
updatemenu[0]['buttons']=buttons
updatemenu[0]['direction']='down'
updatemenu[0]['showactive']=True


fig.update_layout(showlegend=False, updatemenus=updatemenu)
fig.show()

解决方案2
 -1 已采纳  2020-07-02 11:20:21

Turns out, all axis need to be in the same format.事实证明，所有轴都需要采用相同的格式。 This was solved by setting year inside the plot year to:通过将 plot 年份中的年份设置为： 

 x=temp_year.day.astype('datetime64[Y]').astype(str).values y=temp_year.tweet_count.values

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