更新菜单后不可见打印痕迹
我正在美国地图上绘制散布图（51个州的51条迹线，包括DC和4个不同年份的4条迹线）。我有2个按钮的updatemenus，它们可以在一个带有图例的散点图（51条迹线）和一个底部带有滑块的散点图（4条迹线）之间切换。我最初设置4条迹线（年）visible = False是因为我只希望最初显示51条迹线，但是当我单击按钮切换到带有滑块的散点图并设置前51条迹线visible = False和最后4条迹线时visible = [True, False, False, False]我的踪迹在地图上都不可见。
不确定为什么会这样。当我在第一次创建散点图时设置cities_year visible = True时（即它们最初可见）时，会出现迹线，但我不希望这样，因为那样我便将所有散点图绘制在每个散点图的顶部两次其他。
以下是一些用于创建数据集的代码：
data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')
data = data.iloc[:400] # Keep only first 400 samples
data.loc[:100, 'year'] = '1990'
data.loc[100:200, 'year'] = '1991'
data.loc[200:300, 'year'] = '1992'
data.loc[300:, 'year'] = '1993'
我正在使用plotly 2.7.0版和离线绘图 这是我的密谋代码：
cities = []
for state in data['name'].value_counts().index:
data_sub = data.loc[data['name'] == state]
city = dict(
type = 'scattergeo',
visible = True,
locationmode = 'USA-states',
lon = data_sub['lon'],
lat = data_sub['lat'],
mode = 'markers',
marker = dict(
size = 8,
color = "rgb(255, 102, 102)",
opacity = 0.4,
line = dict(
width=0.5,
color='rgb(255, 102, 102)'
)
),
name = state
)
cities.append(city)
cities_year = []
for year in sorted(data.year.value_counts().index):
data_sub = data.loc[data['year'] == year]
city = dict(
type = 'scattergeo',
visible = False,
locationmode = 'USA-states',
lon = data_sub['lon'],
lat = data_sub['lat'],
mode = 'markers',
marker = dict(
size = 8,
color = "rgb(255, 102, 102)",
opacity = 0.4,
line = dict(
width=0.5,
color='rgb(255, 102, 102)'
)
),
name = str(year)
)
cities_year.append(city)
slider = [dict(active = 0,
pad = dict(t = 1),
steps = [dict(args = ["visible", ([False] * len(cities)) + [True, False, False, False]],
label = "1990",
method = "restyle"
),
dict(args = ["visible", ([False] * len(cities)) + [False, True, False, False]],
label = "1991",
method = "restyle"
),
dict(args = ["visible", ([False] * len(cities)) + [False, False, True, False]],
label = "1992",
method = "restyle"
),
dict(args = ["visible", ([False] * len(cities)) + [False, False, False, True]],
label = "1993",
method = "restyle"
)
]
)
]
updatemenus = list([
dict(type="buttons",
active=0,
buttons=list([
dict(label = 'states',
method = 'update',
args = [dict(visible = ([True] * len(cities)) + ([False] * len(cities_year))),
dict(sliders = [],
showlegend = True)]),
dict(label = 'years',
method = 'update',
args = [dict(visible = ([False] * len(cities)) + [True, False, False, False]),
dict(sliders = slider,
showlegend = False)])
]),
)
])
layout = dict(
title = 'myplot',
geo = dict(
scope='usa',
projection=dict(type='albers usa'),
showland=True,
showlakes = True,
landcolor = 'rgb(217, 217, 217)',
subunitwidth=1,
countrywidth=1,
subunitcolor="rgb(255, 255, 255)",
countrycolor="rgb(255, 255, 255)"
),
updatemenus=updatemenus
)
trace_data = cities + cities_year
fig = dict(data=trace_data, layout=layout)
iplot(fig, validate=False)
1 个答案:
答案 0 :(得分：0)
问题：如果我理解正确，则运行以上code时：iplot()创建带有两个标记为“ scattergeo()”的两个buttons的states图和'years'。在这两个按钮中，“ states”按钮处于活动状态并显示其图形（带有“红点”和legend）。 “ years”按钮对应于带有slider选项（years 1990至1993）的图。现在，单击此“ years”按钮时，期望在“ maps”上出现“红色点”（对于year 1990）。但是，这不会发生。
运行以上代码时的绘图
单击“年”按钮时，没有数据点的问题图
尝试的解决方案：
当visible的{{1}} True的{{1}} city中的dictionary设置为cities_year（在下面）时，则问题已经解决了。也就是说，运行list后，该图将显示两个按钮。现在，当'traces'code为years时，它将在button clicked处显示带有slider的'红色点'。设置year可能很重要，因为它可能是在加载或显示1990的第一时间。 （visible=True; plot）
Jupyter Notebook 5.0.0运行Python 3.6.6之后的图：
现在，单击“年”按钮时，图为：
编辑-1 ---------------
cities_year = []
for year in sorted(data.year.value_counts().index):
data_sub = data.loc[data['year'] == year]
city = dict(
type = 'scattergeo',
visible = True,
仍然无法正常工作。但是找到了一种解决方法，可以仅使用code来选择slider。
legends 
编辑-2 ---------------
问题仍然没有解决，但是下面的代码可能有助于缩小发现错误的范围。在下面的year中，有两个样本数据集：（1） dict(label = 'years',
method = 'restyle',
args = [dict(visible = ([False] * len(cities)) + [True, True, True, True]),
dict(sliders = slider,
showlegend = False)])
和（2）code。为了简单起见，每个go.Scatter()中总共只有go.Scattergeo() 5个。请注意，尽管用于生成示例数据集的rows不同，但以下代码可绘制上述两个数据集。它表明dataframe正常工作，并且code存在问题中提到的问题。
导入库
go.Scatter() 为go.Scattergeo()创建数据
import datetime
from datetime import date
import pandas as pd
import numpy as np
from plotly import __version__
%matplotlib inline
import cufflinks as cf
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
init_notebook_mode(connected=True)
cf.go_offline()
import plotly.offline as pyo
import plotly.graph_objs as go
from plotly.tools import FigureFactory as FF
import json
为go.Scatter()创建数据
# Create random numbers
x = np.random.randn(100)
y = 10 + np.random.randn(100)
z = np.linspace(-3,2,100)
df = pd.DataFrame({'x':x, 'y':y, 'z':z})
df.head(2)
# Create traces
trace1 = go.Scatter(visible = True, x=df.x, y=df.y, mode='markers', name='trace1', marker=dict(color='red'))
trace2 = go.Scatter(visible = True, x=df.x, y=df.z, mode='markers', name='trace2', marker=dict(color='black'))
trace3 = go.Scatter(visible = False, x=df.x, y=df.y*df.y, mode='markers', name='trace3', marker=dict(color='blue'))
trace4 = go.Scatter(visible = False, x=df.x, y=df.z*0.5, mode='markers', name='trace4', marker=dict(color='orange'))
trace5 = go.Scatter(visible = False, x=df.x, y=df.z*df.z, mode='markers', name='trace5', marker=dict(color='purple'))
# Create list of traces
data = [trace1, trace2, trace3, trace4, trace5]
go.Scattergeo()是以上两个数据集的共同点
# Create dataframe for cities
df = pd.DataFrame({'name': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Philadelphia'],
'pop': [8287238, 3826423, 2705627, 2129784, 1539313],
'lat': [40.730599, 34.053717, 41.875555, 29.758938, 39.952335],
'lon': [-73.986581, -118.242727, -87.624421, -95.367697, -75.163789],
'year': [1990, 1991, 1992, 1993, 1991]
})
# Create city traces manually without for-loop
trace1 = go.Scattergeo(visible=True,name = 'trace1',locationmode = 'USA-states',
lon = df[df['name']=='New York']['lon'], lat = df[df['name']=='New York']['lat'],
mode = 'markers',marker = dict(size=10, symbol='circle-open', color = "red"))
trace2 = go.Scattergeo(visible=True,name = 'trace2',locationmode = 'USA-states',
lon = df[df['name']=='Los Angeles']['lon'], lat = df[df['name']=='Los Angeles']['lat'],
mode = 'markers',marker = dict(size=10, symbol='circle-open', color = "red"))
trace3 = go.Scattergeo(visible=False, name = 'trace3', locationmode = 'USA-states',
lon = df[df['year']==1990]['lon'], lat = df[df['year']==1990]['lat'],
mode = 'markers',marker = dict(size=20, symbol='circle-open', color = "blue")
)
trace4 = go.Scattergeo(visible=False, name = 'trace4', locationmode = 'USA-states',
lon = df[df['year']==1991]['lon'], lat = df[df['year']==1991]['lat'],
mode = 'markers',marker = dict(size=20, symbol='circle-open', color = "blue")
)
trace5 = go.Scattergeo(visible=False, name = 'trace5', locationmode = 'USA-states',
lon = df[df['year']==1992]['lon'], lat = df[df['year']==1992]['lat'],
mode = 'markers',marker = dict(size=20, symbol='circle-open', color = "blue")
)
# Create list of traces
data = [trace1, trace2, trace3, trace4, trace5]
具有Code
（左：# Create slider
sliders = [dict(active=-1,
pad = {"t": 1},
currentvalue = {"prefix": "Plot Number: "},
execute=True,
steps = [
dict(args = ["visible", [False, False, True, False, False]],
label = "trace3",
method = "restyle"
),
dict(args = ["visible", [False, False, False,True, False]],
label = "trace4",
method = "restyle"
),
dict(args = ["visible", [False, False, False, False, True]],
label = "trace5",
method = "restyle"
)
],
transition = 0
)
]
# Create updatemenus
updatemenus = list([
dict(
buttons= list([
dict(
args = [
{'visible': (True, False, False, False, False)},
{'sliders':[], 'showlegend': True, 'title': 'Plots only'}
],
label = 'single_plot',
method = 'update'
),
dict(
args = [
{'visible': (False, False, True, False, False)},
{'sliders':sliders, 'showlegend': True, 'title': 'Plots with slider'}
],
label = 'multi_plots',
method = 'update'
)
]),
direction = 'left',
pad = {'r': 10, 't': 10},
showactive = True,
type = 'buttons',
x = 0.1,
xanchor = 'left',
y = 1,
yanchor = 'top'
)])
# Create layout
layout = go.Layout(title='Chart') #, geo=dict(scope='usa')) #<--uncomment for Scattergeo() ... optional
layout['updatemenus'] = updatemenus
# Plot data
fig = go.Figure(data=data, layout=layout)
pyo.offline.plot(fig)
'go.Scatter()'的图；右：button'single_plot'的图）
请注意，此处按“ multi_points” button后，正确显示了右侧数据点上的图。
具有multi_plots
（左：button'go.Scattergeo()'的图；右：button'single_plot'的图）
请注意，按“ button”按钮后，右侧图中的数据点丢失了。
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