我正在尝试使用列表推导来创建Plotly data
的{{1}}属性。
这是df:
Scattermapbox
这是我要遍历的元组:
import plotly.plotly as py
import plotly.graph_objs as go
import pandas as pd
df = pd.DataFrame(
{"BOROUGH": ['MANHATTAN','MANHATTAN','MANHATTAN','QUEENS', 'QUEENS', 'QUEENS'],
"CALL_QTY":[100, 10, 5, 15, 30, 45],
"lat":[40.75, 40.72, 40.73, 40.72, 70.71, 40.721],
"lng":[-73.99, -73.98, -70.97, -73.74, -73.73, -73.72]})
这是我创建的使用列表推导的函数:
u_sel = [list(a) for a in zip(['MANHATTAN', 'QUEENS'], # names
['blue', 'orange'], # colors
[0.6, 0.7])] # opacity
问题:当我尝试运行以下命令时:
def scattermap_data(df, u_sel):
return([go.Scattermapbox(
lat = df.loc[df['BOROUGH']==b].lat.astype('object'),
lon = df.loc[df['BOROUGH']==b].lng.astype('object'),
mode = 'markers',
marker = dict(
size=df.loc[df['BOROUGH']==b].CALL_QTY,
sizeref=0.9,
sizemode='area',
color=color,
opacity=opacity
)
)] for b, color, opacity in u_sel
)
data = scattermap_data(df, u_sel)
layout = go.Layout(autosize=False,
mapbox= dict(
accesstoken=mapbox_access_token,
zoom=10,
style = 'dark',
center= dict(
lat=40.721319,
lon=-73.987130)
),
title = "O God, Why?")
fig = dict(data=data, layout=layout)
py.iplot(fig, filename='tmapbox')
我的问题:我的印象是,单个df将分解为scattermapbox跟踪元素的两个实例-ValueError:
Invalid value of type 'builtins.generator' received for the 'data' property of
Received value: <generator object scattermap_data.<locals>.<genexpr> at 0x000000000A72AF68>
的结构,上面类似于:
data
(这在格式上看起来与许多绘图示例类似,在这些示例中,轨迹列表构成了data = [trace1, trace2]
中data
的{{1}}参数。
如果我对dict
进行了两条独立的跟踪,则此示例可以工作,但是我有多个需要该多重跟踪属性的图,并且我不想为每个图重复代码(即,使两个不同的{每个情节都有{1}}个实例。我觉得我已经很接近让它起作用了,但是我只需要进行一些调整。
辅助信息:Plotly v.3.0.3,python 3.6,我是新列出列出理解和plotly的人,任何帮助将不胜感激。
edit:添加fig
语句以防万一。
edit2:改进的问题陈述,标题
答案 0 :(得分:1)
我发现了我的问题:在返回函数时,我应该使用list()
而不是方括号。
def scattermap_data(df, u_sel):
return(list(go.Scattermapbox(
lat = df.loc[df['BOROUGH']==b].lat.astype('object'),
lon = df.loc[df['BOROUGH']==b].lng.astype('object'),
mode = 'markers',
marker = dict(
size=df.loc[df['BOROUGH']==b].CALL_QTY,
sizeref=0.9,
sizemode='area',
color=color,
opacity=opacity
)
) for b, color, opacity in u_sel)
)