python 散佈圖，如何做LABLE 顏色對應

python lable

noway 2025-01-23 19:59:35 ‧ 2062 瀏覽

分享至

您好：
程式碼如下：
想請問一下，該如何有LABLE對照表，與顏色對應
比如台積電 blue
鴻海 green 顏色顯示於LABLE

謝謝

from bokeh.plotting import figure, output_file, show
from bokeh.plotting import ColumnDataSource
from bokeh.models import CategoricalColorMapper,  Legend, LegendItem
import pandas as pd

# 匯入CSV格式的檔案
df = pd.read_csv("tech_stocks_2017.csv", encoding="utf8")

output_file("Ch16_4_3d.html")

tech_stocks = ["台積電", "鴻海", "廣達", "聯發科", "和碩"]

c_map = CategoricalColorMapper(
           factors=tech_stocks, 
           palette=["blue","green","red","yellow","gray"])

data = ColumnDataSource(data={
        "close": df["Close"],
        "volume": df["Volume"],
        "name": df["Name"]
        })

p = figure(title="蘋概科技股的收盤價與成交量", 
           height=400, width=700, 
           x_range=(min(df.Close), max(df.Close)),
           y_range=(min(df.Volume), max(df.Volume))
           )

p.diamond(x="close", y="volume", source=data,
          color={"field": "name", "transform": c_map  }  )

p.xaxis.axis_label = "2017年收盤價"
p.yaxis.axis_label = "2017年成交量"



show(p)

登入發表討論

熱門推薦

{{ item.channelVendor }} | {{ item.webinarstarted }} |

直播中

1 個回答

zivzhong

iT邦研究生 2 級 ‧ 2025-01-24 01:50:41

最佳解答

試試:

from bokeh.plotting import figure, output_file, show
from bokeh.plotting import ColumnDataSource
from bokeh.models import CategoricalColorMapper, Legend, LegendItem
import pandas as pd

# 匯入CSV格式的檔案
df = pd.read_csv("tech_stocks_2017.csv", encoding="utf8")

output_file("Ch16_4_3d.html")

tech_stocks = ["台積電", "鴻海", "廣達", "聯發科", "和碩"]

c_map = CategoricalColorMapper(
           factors=tech_stocks, 
           palette=["blue","green","red","yellow","gray"])

data = ColumnDataSource(data={
        "close": df["Close"],
        "volume": df["Volume"],
        "name": df["Name"]
        })

p = figure(title="蘋概科技股的收盤價與成交量", 
           height=400, width=700, 
           x_range=(min(df.Close), max(df.Close)),
           y_range=(min(df.Volume), max(df.Volume)),
           tools="pan,wheel_zoom,box_zoom,reset,save")

# 添加 diamond glyph，並使用 legend_field 自動生成 Legend
p.diamond(x="close", y="volume", source=data,
          color={"field": "name", "transform": c_map},
          legend_field="name",  # 設置 legend_field
          size=10, alpha=0.6)

p.xaxis.axis_label = "2017年收盤價"
p.yaxis.axis_label = "2017年成交量"

# 設置 Legend 的位置和樣式
p.legend.title = "科技股"
p.legend.location = "top_left"
p.legend.background_fill_alpha = 0.6

show(p)