实验六 Python库应用编程与体验

import turtle
turtle.setup(800,600)
turtle.pencolor('pink')
for i in range(4):
    for i in range(2):
        turtle.circle(80,90)
        turtle.left(90)
    turtle.right(90)
turtle.left(30)
for i in range(4):
    for i in range(2):
        turtle.circle(80,90)
        turtle.left(90)
    turtle.right(90)
turtle.left(30)
for i in range(4):
    for i in range(2):
        turtle.circle(80,90)
        turtle.left(90)
    turtle.right(90)
turtle.hideturtle()
turtle.done()

import turtle
turtle.speed(0)
turtle.setup(800,600)
turtle.bgcolor('black')
turtle.pencolor('white')
angle = 0
size = 2
for i in range(10):
    for j in range(4):
        turtle.forward(size)
        angle = angle + 72
        turtle.seth(angle)
        size = size + 5
turtle.hideturtle()
turtle.done()

import  turtle
import  random
turtle.setup(800,600)
turtle.penup()
turtle.backward(100)
turtle.pendown()
i = 0
while i < 20:
    rgb = tuple(random.random() for i in range(3))
    turtle.color(rgb)
    turtle.begin_fill()
    turtle.forward(10)
    turtle.left(90)
    turtle.forward(30)
    turtle.left(90)
    turtle.forward(10)
    turtle.left(90)
    turtle.forward(30)
    turtle.left(90)
    turtle.forward(10)
    i = i + 1
    turtle.end_fill()
turtle.hideturtle()
turtle.done()

import turtle
def square(size=50,rgb='orange'):
    turtle.pencolor(rgb)
    for i in range(4):
        turtle.forward(size)
        turtle.left(90)

def main():
    turtle.setup(800,600)
    turtle.speed(0)

    for i in range(10):
        square(80)
        turtle.left(36)

    turtle.hideturtle()
    turtle.done()

if __name__ == '__main__':
    main()

 

实验总结：

　　数据分析初始阶段，通常要进行可视化处理。数据可视化旨在直观展示信息的分析结果和构思，令某些抽象数据具象化，这些抽象数据包括数据测量单位的性质或数量。数据可视化是数据分析中很重要的一部分，它能够帮助用户从繁杂的数据中更直观有效地获取信息。

　　turtle库可以绘制多种图形，对于数据可视化分析非常重要，其中语法知识较为简单，难点在于和之前的知识相结合，绘制出一些复杂的图形。