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!
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:
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:
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()
import matplotlib.pyplot as plt x_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,ymax plt.show()
import matplotlib.pyplot as ply from random import choice class 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()
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 pygal from random import randint class 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')
这个可以直接在Pycharm中安装插件,非常方便。
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: 200 dict_keys(['total_count', 'incomplete_results', 'items'])
# 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: 2061622 repositories returned:30 Keys: 71 Name: awesome-python Owner: vinta Starts: 40294 Repository: https://github.com/vinta/awesome-python Created: 2014-06-27T21:00:06Z Updated: 2017-10-29T00:50:49Z Description: A curated list of awesome Python frameworks, libraries, software and resources
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