将下拉菜单添加到Choropleth地图以选择每个状态并生成新的图表类型

时间:2017-10-18 20:07:47

标签: python plotly choropleth

我已经创建了一个Choropleth地图,我想知道是否可以为每个州添加一个下拉列表。当您选择下拉列表时,图表会更改为该州内一段时间内获得的学士学位数的折线图。

我的数据样本:

        year state statetotal ba_total
0     1984.0    AK      221.0    108.0
1     1985.0    AK      242.0    141.0
2     1984.0    NC      229.0    117.0
3     1985.0    NC      257.0    138.0
4     1984.0    MA      272.0    165.0
5     1985.0    MA      280.0    176.0
6     1984.0    NY      375.0    249.0
7     1985.0    NY      309.0    208.0

这是我迄今为止所尝试过的:

for col in df.columns:
    df[col] = df[col].astype(str)

scl = [[0.0, 'rgb(242,240,247)'],[0.2, 'rgb(218,218,235)'],[0.4, 'rgb(188,189,220)'],\
            [0.6, 'rgb(158,154,200)'],[0.8, 'rgb(117,107,177)'],[1.0, 'rgb(84,39,143)']]

df['text'] = df['statename'] + '<br>' + \
    'Bachelor '+df['ba_total']+'<br>'+ \
    'Master '+df['ma_total']+'<br>'+ \
    'PhD '+df['phd_total']

# Years
years = list(df['year'].astype(float).astype(int).unique())

# make data
data = []

# Append data
for year in years:
    dataset_by_year = df[df['year'].astype(float).astype(int) == int(year)]

    data_dict = [ dict(
        type='choropleth',
        visible=True,
        colorscale = scl,
        autocolorscale = False,
        locations = dataset_by_year['state'],
        z = dataset_by_year['statetotal'].astype(float),
        locationmode = 'USA-states',
        text = dataset_by_year['text'],
        marker = dict(
            line = dict (
                color = 'rgb(255,255,255)',
                width = 2
            ) ),
        colorbar = dict(
            title = "Educ. Grads")
        ) ]
    data.append(data_dict[0])

# let's create the steps for the slider
steps = []
for i in range(len(data)):
    step = dict(method='restyle',
                args=['visible', [False] * len(data)],
                label='{}'.format(i + 1984))
    step['args'][1][i] = True
    steps.append(step)

sliders = [dict(active=0,
                pad={"t": 1},
                steps=steps)]    

# create the empty dropdown menu
updatemenus = list([dict(buttons=list()), 
                    dict(direction='down',
                         showactive=True)])

total_codes = len(df.state.unique()) + 1

for s, state in enumerate(df.state.unique()):
    # add a trace for each state
    data.append(dict(type='scatter',
                     x=[i for i in range(1984, 2016)],
                     y=[i for i in df.statetotal],
                     visible=False))

    # add each state to the dropdown    
    visible_traces = [False] * total_codes
    visible_traces[s + 1] = True
    updatemenus[0]['buttons'].append(dict(args=[{'visible': visible_traces}],
                                          label=state,
                                          method='update'))

# add a dropdown entry to reset the map    
updatemenus[0]['buttons'].append(dict(args=[{'visible': [True] + [False] *  (total_codes - 1)}],
                                      label='Map',
                                      method='update'))

layout = dict(title='Aggregated Number of Graduates in Education by State',
              updatemenus=updatemenus,
              geo=dict(scope='usa',
                       projection={'type': 'albers usa'}),
              sliders=sliders)

fig = dict(data=data, 
           layout=layout)

我得到的AttributeError与我创建的功能有关,但之前我设法生成带有菜单的图表,但图表生成了50个菜单按钮,而不是下拉菜单50个选项。

我认为这些问题可以解决,但问题的关键在于是否可以将图表类型组合在一起?理想情况下,如果我点击阿拉斯加州,显示在所观察的时间段内完成的单身汉学位数,我想要显示折线图。 这可能吗?

编辑代码

我设法让下拉菜单工作,但它与slider和地图没有很好地融合。当您点击下拉菜单中的项目或如何防止地图重叠在折线图顶部时,我不知道如何让滑块消失。

1 个答案:

答案 0 :(得分:3)

您可以使用Plotly在线获得所需的功能,但在渲染第一个图形时需要加载所有数据。也许看看Plotly的Dash,它可以动态加载数据。

为了获得显示痕迹的dropmenu,您可以执行以下操作:

  • 首先创建地图,然后为每个国家/地区添加散点图,但只能通过设置visible属性来显示地图。
  • 创建一个drop down menu,显示所选国家/地区的散点图(通过将布尔数组传递给visible
  • 添加菜单条目以再次显示地图

enter image description here

enter image description here

import pandas as pd
import plotly

plotly.offline.init_notebook_mode()
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')

# create the initial map
data = [dict(type='choropleth',
             locations = df['code'].astype(str),
             z=df['total exports'].astype(float),
             locationmode='USA-states', 
             visible=True)]

layout = dict(geo=dict(scope='usa',
                       projection={'type': 'albers usa'}))

# create the empty dropdown menu
updatemenus = list([dict(buttons=list()), 
                    dict(direction='down',
                         showactive=True)])

total_codes = len(df.code.unique()) + 1

for s, state in enumerate(df.code.unique()):
    # add a trace for each state
    data.append(dict(type='scatter',
                     x=[i for i in range(1980, 2016)],
                     y=[i + random.random() * 100 for i in range(1980, 2016)],
                     visible=False))

    # add each state to the dropdown    
    visible_traces = [False] * total_codes
    visible_traces[s + 1] = True
    updatemenus[0]['buttons'].append(dict(args=[{'visible': visible_traces}],
                                          label=state,
                                          method='update'))

# add a dropdown entry to reset the map    
updatemenus[0]['buttons'].append(dict(args=[{'visible': [True] + [False] *  (total_codes - 1)}],
                                      label='Map',
                                      method='update'))
layout['updatemenus'] = updatemenus

fig = dict(data=data, 
           layout=layout)
plotly.offline.iplot(fig)