python data visualization (matplotlib, scatter)

data visualization

1.matplotlib

Matplotlib probably Python 2D- drawing areas most widely used suite. It allows users to easily graphic data, and provides a variety of output formats. Here we will explore the common usage of matplotlib.

Installation matplotib

pip install -i https://pypi.douban.com/simple/ matplotlib

Test matplotib

$python
>>>import matplotlib
>>>
#没有错误信息输出，则表示matplotlib安装成功。

This may not identify pyCharm, perform the following operations

Examples of a (line)

import matplotlib.pyplot as plt
squares = [1,4,9,16,25]
plt.plot(squares)
plt.show()

Examples of di (Line)

import matplotlib.pyplot as plt
squares = [1,4,9,16,25]

#修改线条的宽度: linewidth
plt.plot(squares,linewidth=5)

#设置图标的标题，并且给坐标轴加上标签
plt.title('queares number',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('quares value',fontsize=24)

# 设置刻度标记的大小
plt.tick_params(axis="both",labelsize=14)

plt.show()

Three examples (lines)

import matplotlib.pyplot as plt

#捕入值
input_values = [1,2,3,4,5]
#输出值
squares = [1,4,9,16,25]

#修改线条的宽度: linewidth
plt.plot(input_values,squares,linewidth=5)

#设置图标的标题，并且给坐标轴加上标签
plt.title('queares number',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('quares value',fontsize=24)

# 设置刻度标记的大小
plt.tick_params(axis="both",labelsize=14)

plt.show()

Four examples (single point)

import matplotlib.pyplot as plt

plt.scatter(2,4)
plt.show()

Examples of five (single point)

import matplotlib.pyplot as plt

plt.scatter(2,4)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

plt.show()

Examples of six (multi-point)

import matplotlib.pyplot as plt

x_values = [1,2,3,4,5]
y_values = [1,4,9,16,25]
plt.scatter(x_values,y_values,s=100)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

plt.show()

Examples of seven (multi-point connection)

import matplotlib.pyplot as plt

x_values = list(range(1,1001))
y_values = [x ** 2 for x in x_values]
plt.scatter(x_values,y_values,s=100)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

#设置每个坐标轴的取值范围
plt.axis([0,1100,0,1100000])

plt.show()

Analyze

Examples of eight (multi-point connection, custom color)

# 自定义颜色
import matplotlib.pyplot as plt

x_values = list(range(1,1001))
y_values = [x ** 2 for x in x_values]
plt.scatter(x_values,y_values,c='red',s=100)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

#设置每个坐标轴的取值范围
plt.axis([0,1100,0,1100000])

plt.show()

Example IX (multiple points, custom color)

# 自定义颜色
import matplotlib.pyplot as plt

x_values = list(range(1,1001))
y_values = [x ** 2 for x in x_values]

#参数c表示紅绿蓝3种颜色的分量
plt.scatter(x_values,y_values,c=(0,0.5,0.2),s=100)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

#设置每个坐标轴的取值范围
plt.axis([0,1100,0,1100000])

plt.show()

Examples ten (multi-point connection, custom colors, gradient, save picture)

# 自定义颜色
import matplotlib.pyplot as plt

x_values = list(range(1,1001))
y_values = [x ** 2 for x in x_values]

# 将参数c设置为一个y值的列表，使用参数cmap告诉plot使用哪个颜色映射
plt.scatter(x_values,y_values,c=y_values,cmap=plt.cm.Blues,s=100)

#设置图标标题,并且给坐标轴加上标签
plt.title('squares numbers',fontsize=24)
plt.xlabel('value',fontsize=24)
plt.ylabel('squares of value',fontsize=14)

# 设置刻度标记的大小
plt.tick_params(axis="both",which='major',labelsize=14)

#设置每个坐标轴的取值范围
plt.axis([0,1100,0,1100000])

# plt.show()

# bbox_inches='tight' -->将图表多余的空白区域哉减掉
# 保存图片为squares1.png
plt.savefig('squares1.png',bbox_inches='tight') 

Examples of eleven (multiple points, custom colors, gradients, images saved)

import matplotlib.pyplot as plt

# plt.scatter(2,4)
x_values = list(range(1, 1001))
y_values = [x ** 2 for x in x_values]
# plt.scatter(x_values, y_values,c='red', s=50)
## 参数c表示红绿蓝3种颜色的分量
# plt.scatter(x_values, y_values,c=(0,0.5,0.2), s=50)
## 将参数c设置为一个y值的列表，使用参数cmap告诉plot使用哪个颜色映射
plt.scatter(x_values, y_values,c=y_values,cmap=plt.cm.Reds, s=50)

# 设置图标标题，并且 给坐标轴加上标签
plt.title('squares numbers', fontsize=24)
plt.xlabel('value', fontsize=24)
plt.ylabel('square of value', fontsize=14)

# 设置刻度的标记大小
plt.tick_params(axis='both', which='major', labelsize=14)

# 设置每个坐标轴的取值范围
plt.axis([0,1100,0,1100000])

# plt.show()
# 保存图片为squares22.png
plt.savefig('squares22.png',bbox_inches='tight')

2, Random Walk

# 随机漫步
from random import choice

class RandomWalk():
    """-个生成随机漫步数据的类"""

    def __init__(self,num_points=5000):
        """初始化随机漫步的属性"""
        self.num_points = num_points

        # 所有随机漫步都始于(0,0)
        self.x_values = [0]
        self.y_values = [0]

    def fill_walk(self):
        """计算随机漫步包含的所有点"""

        # 不断漫步,直到列表达到指定的长度
        while len(self.x_values) < self.num_points:
            # 决定前进方向以及沿着这个方向前进的距离
            x_direction = choice([1,-1])
            x_distance = choice([0,1,2,3,4])
            x_step = x_direction * x_distance

            y_direction = choice([1,-1])
            y_distance = choice([0,1,2,3,4])
            y_step = y_direction * y_distance

            # 拒绝原地踏步
            if x_step == 0 and y_step ==0:
                continue

            # 计算下一个点的x和y的值
            next_x =self.x_values[-1] + x_step
            next_y =self.y_values[-1] + y_step

            #
            # 不断漫步，直到列表达到指定的长度
        while len(self.x_values) < self.num_points:
            # 决定前进方向以及沿着这个方向前进的距离
            x_direction = choice([1, -1])
            x_distance = choice([0, 1, 2, 3, 4])
            x_step = x_direction * x_distance

            y_direction = choice([1, -1])
            y_distance = choice([0, 1, 2, 3, 4])
            y_step = y_direction * y_distance

            # 决绝原地踏步
            if x_step == 0 and y_step == 0:
                continue

            # 计算下一个点的x和y的值
            next_x = self.x_values[-1] + x_step
            next_y = self.y_values[-1] + y_step

            #
            self.x_values.append(next_x)
            self.y_values.append(next_y)

Examples of a (random walk, custom color)

import matplotlib.pyplot as plt
from 示例.mpl_squares import RandomWalk

# 创建RandomWalk实例，并且将包含的点都绘制出来
rw = RandomWalk()
rw.fill_walk()

# 给点着色
point_numbers = list(range(rw.num_points))
plt.scatter(rw.x_values, rw.y_values, c=point_numbers,cmap=plt.cm.Greens,s=15)

# 隐藏边框
# plt.axes().get_xaxis().set_visible(False)
# plt.axes().get_yaxis().set_visible(False)
plt.show()

Examples of bis (random walk, whether to continue generating)

import matplotlib.pyplot as plt
from 示例.mpl_squares import RandomWalk

while True:
    # 创建RandomWalk实例，并且将包含的点都绘制出来
    rw = RandomWalk()
    rw.fill_walk()
    plt.scatter(rw.x_values, rw.y_values, s=15)

    # 隐藏边框
    # plt.axes().get_xaxis().set_visible(False)
    # plt.axes().get_yaxis().set_visible(False)

    plt.show()

    keep_running = input('继续漫步吗？(y/n)')
    if keep_running == 'n':
        break

Output:

继续漫步吗？(y/n) y

Examples of tris (random walk, control points, the distance between multiple points)

import matplotlib.pyplot as plt
from 示例.mpl_squares import RandomWalk

# 创建RandomWalk实例，并且将包含的点都绘制出来
rw = RandomWalk()
rw.fill_walk()

# 给点着色
point_numbers = list(range(rw.num_points))

plt.scatter(0,0,c='green',s=100)
plt.scatter(rw.x_values[-1],rw.y_values[-1],c='red',s=100)

# plt.scatter(rw.x_values, rw.y_values, c=point_numbers,cmap=plt.cm.Greens,s=15)

# 隐藏边框
# plt.axes().get_xaxis().set_visible(False)
# plt.axes().get_yaxis().set_visible(False)
plt.show()

Example IV (random walk, the control points (the distance between the multi-point control) + Custom points)

import matplotlib.pyplot as plt
from 示例.mpl_squares import RandomWalk

# 创建RandomWalk实例，并且将包含的点都绘制出来
rw = RandomWalk(500000)
rw.fill_walk()

# 给点着色
point_numbers = list(range(rw.num_points))

plt.scatter(0,0,c='green',s=100)
plt.scatter(rw.x_values[-1],rw.y_values[-1],c='red',s=100)
plt.scatter(rw.x_values, rw.y_values, c=point_numbers,cmap=plt.cm.Blues,s=1)

# 隐藏边框
# plt.axes().get_xaxis().set_visible(False)
# plt.axes().get_yaxis().set_visible(False)

plt.figure(dpi=128, figsize=(10,6))
plt.show()