在Choropleth映射中添加下拉菜单以选择每种状态并生成新的图形类型 [英] Adding drop down menu to Choropleth map to select each state and generate new graph type
问题描述
我已经创建了一个Choropleth映射，我想知道是否可以为每个州添加一个下拉菜单.当您选择下拉菜单时，该图将变为该状态下随时间获得的学士学位数的折线图.
I've created a Choropleth map and I want to know if it's possible to add a drop down with each state. When you select the drop down the graph changes to a line graph of the number of Bachelor degrees earned over time in that state.
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
这是我到目前为止尝试过的:
This is what I've tried so far:
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)
我得到与创建的功能相关的AttributeError，但是以前我设法通过存在的菜单来生成图形，但是图形生成了50个菜单按钮，而不是带有50个选项的下拉菜单.
I'm getting an AttributeError related to the function I've created but previously I managed to generate the graph with the menus present but the graph generated 50 menu buttons rather than a drop down with 50 options.
我认为这些问题可以解决，但问题的症结在于是否可以将图形类型组合在一起?理想情况下，如果我单击阿拉斯加以显示观察到的时间段内完成的学士学位数，则希望显示一个折线图. 这可能吗?
I think these issues can be resolved but the crux of my problems are whether or not it's possible to combine graph types together? Ideally I'd want to show a line graph if I click on Alaska showing the number of bachelor's degrees completed over the time period observed. Is this possible?
编辑代码
I managed to get the drop down menu to work but it doesn't mesh well with the slider and the map. I don't know how to get slider to disappear when you click an item in the drop down menu or how to prevent the map from being overlayed on top of the line graph.
推荐答案
您可以通过Plotly在线获得所需的功能，但是在渲染第一个图形时需要加载所有数据.也许看看启用了动态数据加载的Plotly的Dash.
You can get the desired functionality with Plotly online but all the data needs to be loaded when the first graph is rendered. Perhaps have a look at Plotly's Dash which enabled dynamic loading of data.
为了获得显示痕迹的下拉菜单，您可以执行以下操作:
In order to get the dropmenu which shows traces you could do the following:
- 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. - 创建一个下拉菜单，其中显示了所选国家/地区的散点图(通过将布尔数组传递给
visible) - 添加菜单项以再次显示地图
- First create map, then add a scatter plot for each country but only show the map by setting the
visibleattribute. - Create a drop down menu which shows the scatter plot for the selected country (by passing an array of Booleans to
visible) - Add a menu entry to show the map again
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)
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