Scategory_scatter: 创建一个散点图，不同颜色表示不同类别

一个快速生成由类别着色的散点图的函数，可以从 pandas DataFrame 或 NumPy ndarray 对象中获取数据。

> 来自 mlxtend.general 的 category_scatter

概述

参考文献

• -

示例 1 - 来自 Pandas DataFrames 的类别散点图

import pandas as pd
from io import StringIO

csvfile = """标签,x,y
类别1,10.0,8.04
类别1,10.5,7.30
类别2,8.3,5.5
类别2,8.1,5.9
类别3,3.5,3.5
类别3,3.8,5.1"""

df = pd.read_csv(StringIO(csvfile))
df

绘制数据，其中类别由 label_col 列中的唯一值决定。x 和 y 值只是我们想要绘制的 DataFrame 的列名。

import matplotlib.pyplot as plt
from mlxtend.plotting import category_scatter

fig = category_scatter(x='x', y='y', label_col='label', 
                       data=df, legend_loc='upper left')

示例 2 - 来自 NumPy 数组的类别散点图

import numpy as np
from io import BytesIO

csvfile = """1,10.0,8.04
1,10.5,7.30
2,8.3,5.5
2,8.1,5.9
3,3.5,3.5
3,3.8,5.1"""

ary = np.genfromtxt(BytesIO(csvfile.encode()), delimiter=',')
ary

array([[  1.  ,  10.  ,   8.04],
       [  1.  ,  10.5 ,   7.3 ],
       [  2.  ,   8.3 ,   5.5 ],
       [  2.  ,   8.1 ,   5.9 ],
       [  3.  ,   3.5 ,   3.5 ],
       [  3.  ,   3.8 ,   5.1 ]])

现在，假设第一列代表标签，第二列和第三列分别代表 x 和 y 值。

import matplotlib.pyplot as plt
from mlxtend.plotting import category_scatter

fix = category_scatter(x=1, y=2, label_col=0, 
                       data=ary, legend_loc='upper left')

API

category_scatter(x, y, label_col, data, markers='sxo^v', colors=('blue', 'green', 'red', 'purple', 'gray', 'cyan'), alpha=0.7, markersize=20.0, legend_loc='best')

Scatter plot to plot categories in different colors/markerstyles.

Parameters

• x : str or int

  DataFrame column name of the x-axis values or integer for the numpy ndarray column index.

• y : str

  DataFrame column name of the y-axis values or integer for the numpy ndarray column index

• data : Pandas DataFrame object or NumPy ndarray.

• markers : str

  Markers that are cycled through the label category.

• colors : tuple

  Colors that are cycled through the label category.

• alpha : float (default: 0.7)

  Parameter to control the transparency.

• markersize : float (default` : 20.0)

  Parameter to control the marker size.

• legend_loc : str (default: 'best')

  Location of the plot legend {best, upper left, upper right, lower left, lower right} No legend if legend_loc=False

Returns

• fig : matplotlig.pyplot figure object

Examples

For usage examples, please see https://rasbt.github.io/mlxtend/user_guide/plotting/category_scatter/