Plotly：如何 plot 氣泡 Map 上的特定行？

Question

如何使用 Plotly 對 ZA7F5F35426B5628741 使用 Map plot 某個狀態的大小？ （即：plot 僅限西海岸和東海岸州）

我看過 Plotly 的例子，但沒有給出太多解釋如何重現相同的 plot （https://plotly.com/python/bubble-maps/#united-states-bubble-map ）

樣本數據：

             state  latitude   longitude  mag
0          Alabama   34.7360  -85.629000  4.8
1           Alaska   71.1404 -131.232000  7.9
2          Arizona   36.9940 -109.058700  5.3
3         Arkansas   36.4400  -89.920000  5.0
4       California   41.9780 -115.366000  7.3

我的代碼：

every_earthquake = pd.read_csv('earthquake_states.csv')

fifty_state_quakes = every_earthquake[['state', 'latitude', 'longitude', 'mag']].dropna()
state_mag_max = pd.DataFrame(fifty_state_quakes, columns=['state', 
                        'latitude', 'longitude', 'mag']).dropna()
state_max_mag_df = state_mag_max.groupby(['state'])['latitude', 'longitude','mag'].max().reset_index()

state_max_mag_df['text'] = state_max_mag_df['state'] + '<br>Magnitude ' + (state_max_mag_df['mag']).astype(str)
magnitude = [(0,1), (2,3), (4,5), (5,6), (7,8), (9, 10)]
colors = ['royalblue','crimson','lightseagreen','orange','lightgrey']
scale = 0.45

fig = go.Figure()

for i in range(len(magnitude)):
    magn = magnitude[i]
    state_max_mag_df1 = state_max_mag_df[(state_max_mag_df['mag'] >= magn[0]) & (state_max_mag_df['mag'] < magn[1])]
    fig.add_trace(go.Scattergeo(
    locationmode = 'USA-states',
    lon = state_max_mag_df['latitude'],
    lat = state_max_mag_df['latitude'],
    text = state_max_mag_df['text'],
    marker = dict(
        size = state_max_mag_df['mag']/scale,
        color = colors,
        line_color = 'rgb(40,40,40)',
        line_width = 0.5,
        sizemode = 'area'),
    name = '{0} - {1}'.format(magn[0], magn[1])))

      fig.update_layout(
      showlegend = True,
      geo = dict(scope = 'usa',
              landcolor = 'rgb(217, 217, 217)',
              ))
    fig.show()

Output 我得到：

Output 我想實現西和東 State 幅度：

Answer 1

import pandas as pd
import plotly.graph_objects as go

every_earthquake = pd.read_csv('earthquake_states.csv')
fifty_state_quakes = every_earthquake[['state', 'latitude', 'longitude', 'mag']].dropna()
state_mag_max = pd.DataFrame(fifty_state_quakes, columns=['state', 'latitude', 'longitude', 'mag']).dropna()
state_max_mag_df = state_mag_max.groupby(['state'])['latitude', 'longitude','mag'].max().reset_index()
state_max_mag_df['text'] = state_max_mag_df['state'] + '<br>Magnitude ' + (state_max_mag_df['mag']).astype(str)
magnitude = [(0,1), (2,3), (4,5), (5,6), (7,8), (9, 10)]
colors = ['#E58606', '#5D69B1', '#52BCA3', '#99C945', '#CC61B0', '#24796C']
scale = 5

fig = go.Figure()

for i in range(len(magnitude)):

    magn = magnitude[i]

    state_max_mag_df1 = state_max_mag_df[(state_max_mag_df['mag'] >= magn[0]) & (state_max_mag_df['mag'] < magn[1])]

    fig.add_trace(go.Scattergeo(
    locationmode = 'USA-states',
    lon = state_max_mag_df1['longitude'],
    lat = state_max_mag_df1['latitude'],
    text = state_max_mag_df1['text'],
    marker = dict(
        size = state_max_mag_df1['mag'] * scale,
        color = colors[i],
        line_color = 'rgb(40,40,40)',
        line_width = 0.5,
        sizemode = 'diameter'),
    name = '{0} - {1}'.format(magn[0], magn[1])))

fig.update_layout(
  showlegend = True,
  geo = dict(scope = 'usa', landcolor = 'rgb(217, 217, 217)')
)

fig.show()