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()

實驗總結：

　　資料分析初始階段，通常要進行視覺化處理。資料視覺化旨在直觀展示資訊的分析結果和構思，令某些抽象資料具象化，這些抽象資料包括資料測量單位的性質或數量。資料視覺化是資料分析中很重要的一部分，它能夠幫助使用者從繁雜的資料中更直觀有效地獲取資訊。

　　turtle庫可以繪製多種圖形，對於資料視覺化分析非常重要，其中語法知識較為簡單，難點在於和之前的知識相結合，繪製出一些複雜的圖形。