在Python中Plotly - 改变标记颜色

Question

我想根据数值来改变标记的颜色，所以我试了这个代码。

import plotly.express as px
import pandas as pd

rows=[['501-600','15','122.58333','45.36667'],
      ['till 500','4','12.5','27.5'],
      ['more 1001','41','-115.53333','38.08'],
      ]

colmns=['bins','data','longitude','latitude']
df=pd.DataFrame(data=rows, columns=colmns)
df = df.astype({"data": int})

def SetColor(x):
        if(x == '501-600'):
            return "steelblue"
        elif(x == 'till 500'):
            return "mintcream"
        elif(x == 'more 1001'):
            return "palegoldenrod"

fig=px.scatter_geo(df,lon='longitude', lat='latitude',color='bins',
                      opacity=0.5,size='data',
                      projection="natural earth")

fig.update_traces(marker=dict(symbol='octagon',
                                color=list(map(SetColor, df['bins'])),
                                line=dict(width=0)))

fig.show()

但在这种情况下，所有的标记都是钢蓝色的，从第一个选项开始。这里有什么地方不对？

Answer 1

#!/usr/bin/python3
import plotly.express as px
import pandas as pd

rows=[['501-600','15','122.58333','45.36667'],
      ['till 500','4','12.5','27.5'],
      ['more 1001','41','-115.53333','38.08'],
      ]

colmns=['bins','data','longitude','latitude']
df=pd.DataFrame(data=rows, columns=colmns)
df = df.astype({"data": int})

def SetColor(x):
        if(x == '501-600'):
            return "steelblue"
        elif(x == 'till 500'):
            return "mintcream"
        elif(x == 'more 1001'):
            return "palegoldenrod"

fig=px.scatter_geo(df,lon='longitude', lat='latitude',color=list(map(SetColor, df['bins'])),
                      opacity=0.5,size='data',
                      projection="natural earth")

fig.update_traces(marker=dict(symbol='octagon',
                                line=dict(width=0)))

fig.show()

这段代码应该可以用。不要更新已经绘制的图形，而是在绘制时更新颜色。

Answer 2

只要添加新的参数 color_discrete_sequence 直插 fig=px.scatter_geo 并指定你想要的颜色。

import plotly.express as px
import pandas as pd

rows = [['501-600', '15', '122.58333', '45.36667'],
        ['till 500', '4', '12.5', '27.5'],
        ['more 1001', '41', '-115.53333', '38.08'],
        ]

colmns = ['bins', 'data', 'longitude', 'latitude']
df = pd.DataFrame(data=rows, columns=colmns)
df = df.astype({"data": int})

fig = px.scatter_geo(df, lon='longitude', lat='latitude', color='bins',
                     color_discrete_sequence=['green', 'steelblue', 'thistle', 'lime'],
                     opacity=0.5, size='data',
                     projection="natural earth")

fig.update_traces(marker=dict(symbol='octagon',
                              color=list(map(SetColor, df['bins'])),
                              line=dict(width=0)))

fig.show()