Plotly，为什么我的泡泡都是一样的颜色？

Question

我的数据中有一个名为 Pizza Shops 的列，其中包含各州的数字，范围从 1 万到超过一百万（数字是编造的）。由于某种原因，每个气泡虽然看起来大小合适，但都显示为相同的颜色（红色）。

我的代码

import plotly.graph_objects as go
import pandas as pd
import os

xl_path = "path to XLSX file"

df = pd.read_excel(open(xl_path, 'rb'), sheet_name='Data')
df.head()
scale = 5000
limits = [(0,15000),(15000,50000),(50000,100000),(100000,500000),(500000,2000000)]
colors = ["red","orange","yellow","green","blue"]
df['Text'] = df['State'] + '<br>Number of Pizza Shops ' + (df['Pizza Shops']).astype(str)

fig = go.Figure()

for i in range(len(limits)):
    lim = limits[i]
    df_sub = df[lim[0]:lim[1]]
    fig.add_trace(go.Scattergeo(
        locationmode = 'USA-states',
        locations=df['State Code'],
        text = df_sub['Text'],
        marker = dict(
            size = df_sub['Pizza Shops']/scale,
            color = colors[i],
            line_color='rgb(40,40,40)',
            line_width=0.5,
            sizemode = 'area'
        ),
        name = '{0} - {1}'.format(lim[0],lim[1])))

fig.update_layout(
        title_text = '2019 US Number of Pizza Shops<br>(Click legend to toggle traces)',
        showlegend = True,
        geo = dict(
            scope = 'usa',
            landcolor = 'rgb(217, 217, 217)',
        )
    )

fig.show()

示例数据：

| State     | State Code | Pizza Shops |
----------------------------------------
  Texas           TX         13256
  California      CA         500235
  Idaho           ID         4000
  ....           ....        .... and so on

Answer 1

问题在于，df_sub = df[lim[0]:lim[1]] 您是根据行索引而不是根据商店数量对数据框进行子集化。如果您的数据框少于 15,000 行，则所有数据点都将落在第一个桶中并显示为红色。

如果您想根据商店数量对数据框进行子集化，则应将 df_sub = df[lim[0]:lim[1]] 替换为 df_sub = df[(df["Pizza Shops"] >= lim[0]) & (df["Pizza Shops"] < lim[1])]。

import plotly.graph_objects as go
import pandas as pd

df = pd.DataFrame({"State": ["Texas", "California", "Idaho", "Alabama", "Arizona", "Georgia", "Washington"],
                   "State Code": ["TX", "CA", "ID", "AL", "AZ", "GA", "WA"],
                   "Pizza Shops": [12500, 25000, 75000, 250000, 1000000, 15000, 100000]})

df["Text"] = df["State"] + "<br>Number of Pizza Shops " + (df["Pizza Shops"]).astype(str)

scale = 2000

limits = [(0,15000),(15000,50000),(50000,100000),(100000,500000),(500000,2000000)]

colors = ["red", "orange", "yellow", "green", "blue"]

fig = go.Figure()

for i in range(len(limits)):

    lim = limits[i]

    df_sub = df[(df["Pizza Shops"] >= lim[0]) & (df["Pizza Shops"] < lim[1])]

    fig.add_trace(go.Scattergeo(
        locationmode="USA-states",
        locations=df_sub["State Code"],
        text=df_sub["Text"],
        marker=dict(
            size=df_sub["Pizza Shops"]/scale,
            color=colors[i],
            line_color="rgb(40,40,40)",
            line_width=0.5,
            sizemode="area"),
        name="{0} - {1}".format(lim[0],lim[1])))

fig.update_layout(
    title_text="2019 US Number of Pizza Shops<br>(Click legend to toggle traces)",
    showlegend=True,
    geo=dict(scope="usa", landcolor="rgb(217, 217, 217)")
)

fig.show()

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