我一直在嘗試用Plotly創(chuàng)建Geoscatter Plot，其中標(biāo)記大小應(yīng)指示一個城市（zip_city）中的客戶（行項目）數(shù)量。我的代碼基于Plotly文檔中的兩個模板：United States Bubble Map和Aggregation part with Aggregates映射。除了一個缺點，我設(shè)法編寫了符合我想要的代碼：當(dāng)我將鼠標(biāo)懸停在氣泡上時，我想查看城市名稱加上客戶數(shù)量（匯總結(jié)果），因此阿瓜迪亞：2。您能幫我怎么做嗎？這是我的代碼（作為plotly的初學(xué)者，我也愿意進行代碼改進）：import plotly.offline as pyoimport pandas as pddf = pd.DataFrame.from_dict({'Customer': [111, 222, 555, 666], 'zip_city': ['Aguadilla', 'Aguadilla', 'Arecibo', 'Wrangell'], 'zip_latitude':[18.498987, 18.498987, 18.449732,56.409507], 'zip_longitude':[-67.13699,-67.13699,-66.69879,-132.33822]})data = [dict( type = 'scattergeo', locationmode = 'USA-states', lon = df['zip_longitude'], lat = df['zip_latitude'], text = df['Customer'], marker = dict( size = df['Customer'], line = dict(width=0.5, color='rgb(40,40,40)'), sizemode = 'area' ), transforms = [dict( type = 'aggregate', groups = df['zip_city'], aggregations = [dict(target = df['Customer'], func = 'count', enabled = True)] )] )]layout = dict(title = 'Customers per US City')fig = dict( data=data, layout=layout )pyo.plot( fig, validate=False)我可以transforms直接在data參數(shù)中訪問參數(shù)結(jié)果以顯示每個城市的客戶數(shù)量嗎？
1 回答
Cats萌萌
TA貢獻1805條經(jīng)驗 獲得超9個贊
您可以創(chuàng)建一個列表，其中將包含您想要的內(nèi)容，然后text=list在中進行設(shè)置data。也不要忘記指定hoverinfo='text'。
我已經(jīng)更新了您的代碼，因此請嘗試以下操作：
import pandas as pd
import plotly.offline as pyo
df = pd.DataFrame.from_dict({'Customer': [111, 222, 555, 666],
'zip_city': ['Aguadilla', 'Aguadilla', 'Arecibo', 'Wrangell'],
'zip_latitude':[18.498987, 18.498987, 18.449732,56.409507],
'zip_longitude':[-67.13699,-67.13699,-66.69879,-132.33822]})
customer = df['Customer'].tolist()
zipcity = df['zip_city'].tolist()
list = []
for i in range(len(customer)):
k = str(zipcity[i]) + ':' + str(customer[i])
list.append(k)
data = [dict(
type = 'scattergeo',
locationmode = 'USA-states',
lon = df['zip_longitude'],
lat = df['zip_latitude'],
text = list,
hoverinfo = 'text',
marker = dict(
size = df['Customer'],
line = dict(width=0.5, color='rgb(40,40,40)'),
sizemode = 'area'
),
transforms = [dict(
type = 'aggregate',
groups = df['zip_city'],
aggregations = [dict(target = df['Customer'], func = 'count', enabled = True)]
)]
)]
layout = dict(title = 'Customers per US City')
fig = dict(data=data, layout=layout)
pyo.plot(fig, validate=False)
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