怎么用Python绘制简单的折丝图

本篇内容介绍了"怎么用Python绘制简单的折丝图"的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！

安装环境matplotlib

个人前面也说了强烈建议使用Pycharm作为Python初学者的首选IDE，主要还是因为其强大的插件功能，很多环境都能一键安装完成，像本文的matplotlib，numpy,requests等。
下面直接上效果图：

绘制简单的折丝图

使用plot来绘制折线

import matplotlib.pyplot as plt# 绘制折线图squares = [1, 4, 9, 16, 25]# plt.plot(squares, linewidth=5)  # 指定折线粗细，# #plt.show();## #修改标签文字和线条粗细# plt.title("squre number", fontsize=24)# plt.xlabel("Value", fontsize=14)# plt.ylabel("square of value", fontsize=14)# plt.tick_params(axis='both', labelsize=14)# plt.show()# 校正图形input_values = [1, 2, 3, 4, 5]plt.plot(input_values, squares, linewidth=5)plt.show()

生成的效果图：

使用scatter绘制散点图并设置样式

import matplotlib.pyplot as plt# 简单的点# plt.scatter(2, 4)# plt.show()## # 修改标签文字和线条粗细plt.title("squre number", fontsize=24)plt.xlabel("Value", fontsize=14)plt.ylabel("square of value", fontsize=14)#设置刻度标记大小plt.tick_params(axis='both', which='major', labelsize=14)# 绘制散点x_values = [1, 2, 3, 4, 5]y_values = [1, 4, 9, 16, 25]plt.scatter(x_values, y_values, s=100)plt.show()

自动计算数据

import matplotlib.pyplot as pltx_values = list(range(1, 1001))y_values = [x ** 2 for x in x_values]# y_values = [x * x for x in x_values]# y_values = [x ^ 2 for x in x_values]plt.scatter(x_values, y_values, s=40)# 坐标轴的取值范围# plt.axis(0, 1100, 0, 1100000)  # 依次是xmin xmax,ymin,ymaxplt.show()

随机漫步

import matplotlib.pyplot as plyfrom random import choiceclass RandomWalk():    def __init__(self, num_points=5000):        self.num_points = num_points        self.x_values = [0]        self.y_values = [0]    def fill_walk(self):        # 不断走，直到达到指定步数        while len(self.x_values) < self.num_points:            # 决定前进方向以及沿这个方向前进的距离            x_direction = choice([1, -1])            x_distance = choice([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])            x_step = x_direction * x_distance            y_direction = choice([1, -1])            y_distance = choice([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])            y_step = y_direction * y_distance            # 不能原地踏步            if x_step == 0 and y_step == 0:                continue            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)rw = RandomWalk()rw.fill_walk()ply.scatter(rw.x_values, rw.y_values, s=15)ply.show()

效果图

使用Pygal模拟掷骰子

pygal能够绘制的图形可以访问pygal介绍

环境安装，直接在Pycharm上安装插件。

import pygalfrom random import randintclass Die():    def __init__(self, num_sides=6):        self.num_sides = num_sides;    def roll(self):        # 返回一个位于1和骰子面数之间的随机值        return randint(1, self.num_sides)die = Die()results = []# 掷100次骰子，并将结果放在列表中。for roll_num in range(10):    result = die.roll()    results.append(str(result))print(results)# 分析结果frequencies = []for value in range(1, die.num_sides + 1):    frequency = results.count(value)    frequencies.append(frequency)print(frequencies)# 对结果进行可视化hist = pygal.Box()hist.title = "result of rolling one D6 1000 times"hist.x_labels = ['1', '2', '3', '4', '5', '6']hist.x_title = "Result"hist.y_title = "frequency of result"hist.add('D6', frequencies)hist.render_to_file('die_visual.svg')

使用Web API

1.1安装requests

这个可以直接在Pycharm中安装插件，非常方便。

1.2处理API响应

import requests# 执行api调用并存储响应url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'r = requests.get(url)print("Status code:", r.status_code)# 将api响应存储在一个变量中response_dic = r.json()# 处理结果print(response_dic.keys())得到结果：Status code: 200dict_keys(['total_count', 'incomplete_results', 'items'])

1.3处理响应字典

# 将api响应存储在一个变量中response_dic = r.json()# 处理结果print(response_dic.keys())print("Total repositories:", response_dic['total_count'])repo_dics = response_dic['items']print("repositories returned:" + str(len(repo_dics)))# 研究一个仓库repo_dic = repo_dics[0]print("\nKeys:", str(len(repo_dic)))# for key in sorted(repo_dic.keys()):#     print(key)print("Name:", repo_dic['name'])print("Owner:", repo_dic['owner']['login'])print("Starts:", repo_dic['stargazers_count'])print("Repository:", repo_dic['html_url'])print("Created:", repo_dic['created_at'])print("Updated:", repo_dic['updated_at'])print("Description:", repo_dic['description'])得到结果：Total repositories: 2061622repositories returned:30Keys: 71Name: awesome-pythonOwner: vintaStarts: 40294Repository: https://github.com/vinta/awesome-pythonCreated: 2014-06-27T21:00:06ZUpdated: 2017-10-29T00:50:49ZDescription: A curated list of awesome Python frameworks, libraries, software and resources

"怎么用Python绘制简单的折丝图"的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注网站，小编将为大家输出更多高质量的实用文章！