pandas python，python不带颜色的图形_python-Matplotlib添加基于现有颜色系列的图例

您可以使用带有基于色图和散点图归一化颜色的空图来创建图例手柄.

import pandas as pd

pandas python？import numpy as np; np.random.seed(1)

import matplotlib.pyplot as plt

x = [np.random.normal(5,2, size=20), np.random.normal(10,1, size=20),

python reshape。np.random.normal(5,1, size=20), np.random.normal(10,1, size=20)]

y = [np.random.normal(5,1, size=20), np.random.normal(5,1, size=20),

np.random.normal(10,2, size=20), np.random.normal(10,2, size=20)]

python numpy库。c = [np.ones(20)*(i+1) for i in range(4)]

df = pd.DataFrame({"x":np.array(x).flatten(),

"y":np.array(y).flatten(),

python图形界面？"colors":np.array(c).flatten()})

size=81

sc = plt.scatter(df['x'], df['y'], s=size, c=df['colors'], edgecolors='none')

pythonmatplotlib？lp = lambda i: plt.plot([],color=sc.cmap(sc.norm(i)), ms=np.sqrt(size), mec="none",

label="Feature {:g}".format(i), ls="", marker="o")[0]

handles = [lp(i) for i in np.unique(df["colors"])]

plt.legend(handles=handles)

plt.show()

另外,您也可以按颜色列中的值过滤数据框,例如使用groubpy,并为每个功能绘制一个散点图：

import pandas as pd

import numpy as np; np.random.seed(1)

import matplotlib.pyplot as plt

x = [np.random.normal(5,2, size=20), np.random.normal(10,1, size=20),

np.random.normal(5,1, size=20), np.random.normal(10,1, size=20)]

y = [np.random.normal(5,1, size=20), np.random.normal(5,1, size=20),

np.random.normal(10,2, size=20), np.random.normal(10,2, size=20)]

c = [np.ones(20)*(i+1) for i in range(4)]

df = pd.DataFrame({"x":np.array(x).flatten(),

"y":np.array(y).flatten(),

"colors":np.array(c).flatten()})

size=81

cmap = plt.cm.viridis

norm = plt.Normalize(df['colors'].values.min(), df['colors'].values.max())

for i, dff in df.groupby("colors"):

plt.scatter(dff['x'], dff['y'], s=size, c=cmap(norm(dff['colors'])),

edgecolors='none', label="Feature {:g}".format(i))

plt.legend()

plt.show()

两种方法产生相同的图：