1 折线图的制作
1.1 需求描述
使用matplotlib绘制一个简单的折线图，在对其进行定制，以实现信息更加丰富的数据可视化，绘制（1,2,3,4,5）的平方折线图。
1.2 源码
#coding=utf-8import matplotlib as mplimport matplotlib.pyplot as pltimport pylab# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# squares = [1,35,43,3,56,7]input_values = [1,2,3,4,5]
squares = [1,4,9,16,25]# 设置折线粗细plt.plot(input_values,squares,linewidth=5)# 设置标题和坐标轴plt.title('平方数图',fontsize=24)
plt.xlabel('值',fontsize=14)
plt.ylabel('平方值',fontsize=14)# 设置刻度大小plt.tick_params(axis='both',labelsize=14)
plt.show()
1.3 生成结果
2 scatter()绘制散点图
2.1 需求描述
使用matplotlib绘制一个简单的散列点图，在对其进行定制，以实现信息更加丰富的数据可视化，绘制（1,2,3,4,5）的散点图。
2.2 源码
#coding=utf-8import matplotlib as mplimport matplotlib.pyplot as pltimport pylab# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# 设置散列点纵横坐标值x_values = [1,2,3,4,5]
y_values = [1,4,9,16,25]# s设置散列点的大小，edgecolor='none'为删除数据点的轮廓plt.scatter(x_values,y_values,c='red',edgecolor='none',s=40)# 设置标题和坐标轴plt.title('平方数图',fontsize=24)
plt.xlabel('值',fontsize=14)
plt.ylabel('平方值',fontsize=14)# 设置刻度大小plt.tick_params(axis='both',which='major',labelsize=14)# 自动保存图表，参数2是剪裁掉多余空白区域plt.savefig('squares_plot.png',bbox_inches='tight')
plt.show()
2.3 生成结果
2.4 需求改进
使用matplotlib绘制一个简单的散列点图，在对其进行定制，以实现信息更加丰富的数据可视化，绘制1000个数的散点图。并自动统计数据的平方，自定义坐标轴
2.5 源码改进
#coding=utf-8import matplotlib as mplimport matplotlib.pyplot as pltimport pylab# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# 设置散列点纵横坐标值# x_values = [1,2,3,4,5]# y_values = [1,4,9,16,25]# 自动计算数据x_values = list(range(1,1001))
y_values = [x**2 for x in x_values]# s设置散列点的大小，edgecolor='none'为删除数据点的轮廓# plt.scatter(x_values,y_values,c='red',edgecolor='none',s=40)# 自定义颜色c=(0,0.8,0.8)红绿蓝# plt.scatter(x_values,y_values,c=(0,0.8,0.8),edgecolor='none',s=40)# 设置颜色随y值变化而渐变plt.scatter(x_values,y_values,c=y_values,cmap=plt.cm.Reds,edgecolor='none',s=40)# 设置标题和坐标轴plt.title('平方数图',fontsize=24)
plt.xlabel('值',fontsize=14)
plt.ylabel('平方值',fontsize=14)#设置坐标轴的取值范围plt.axis([0,1100,0,1100000])# 设置刻度大小plt.tick_params(axis='both',which='major',labelsize=14)# 自动保存图表，参数2是剪裁掉多余空白区域plt.savefig('squares_plot.png',bbox_inches='tight')
plt.show()
2.6 改进结果
3 随机漫步图
3.1 需求描述
随机漫步是每次步行方向和步长都是随机的，没有明确的方向，结果由一系列随机决策决定的。本实例中random_walk决策步行的左右上下方向和步长的随机性，rw_visual是图形化展示。
3.2 源码
random_walk.py
from random import choiceclass RandomWalk(): '''一个生成随机漫步数据的类''' def __init__(self,num_points=5000): '''初始化随机漫步属性''' self.num_points = num_points self.x_values = [0] self.y_values = [0] def fill_walk(self): '''计算随机漫步包含的所有点''' while len(self.x_values)<self.num_points: # 决定前进方向及沿着该方向前进的距离 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 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_visual.py
#-*- coding: utf-8 -*-#coding=utf-8import matplotlib as mplimport matplotlib.pyplot as pltimport pylabfrom random_walk import RandomWalk# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# 创建RandomWalk实例rw = RandomWalk()
rw.fill_walk()
plt.figure(figsize=(10,6))
point_numbers = list(range(rw.num_points))# 随着点数的增加渐变深红色plt.scatter(rw.x_values,rw.y_values,c=point_numbers,cmap=plt.cm.Reds,edgecolors='none',s=1)# 设置起始点和终点颜色plt.scatter(0,0,c='green',edgecolors='none',s=100)
plt.scatter(rw.x_values[-1],rw.y_values[-1],c='blue',edgecolors='none',s=100)# 设置标题和纵横坐标plt.title('随机漫步图',fontsize=24)
plt.xlabel('左右步数',fontsize=14)
plt.ylabel('上下步数',fontsize=14)# 隐藏坐标轴plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
3.3 生成结果
4 Pygal模拟掷骰子
4.1 需求描述
对掷骰子的结果进行分析，生成一个掷筛子的结果数据集并根据结果绘制出一个图形。
4.2 源码
Die类
import randomclass Die: """ 一个骰子类 """ def __init__(self, num_sides=6): self.num_sides = num_sides def roll(self): # 返回一个1和筛子面数之间的随机数 return random.randint(1, self.num_sides)
die_visual.py
#coding=utf-8from die import Dieimport pygalimport matplotlib as mpl# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False
die1 = Die()
die2 = Die()
results = []for roll_num in range(1000):
result =die1.roll()+die2.roll()
results.append(result)# print(results)# 分析结果frequencies = []
max_result = die1.num_sides+die2.num_sidesfor value in range(2,max_result+1):
frequency = results.count(value)
frequencies.append(frequency)print(frequencies)# 直方图hist = pygal.Bar()
hist.title = '骰子投掷1000次各面结果统计图'hist.x_labels =[x for x in range(2,max_result+1)]
hist.x_title ='结果'hist.y_title = '结果分布'hist.add('D6+D6',frequencies)
hist.render_to_file('die_visual.svg')# hist.show()
4.3 生成结果
5 同时掷两个骰子
5.1 需求描述
对同时掷两个骰子的结果进行分析，生成一个掷筛子的结果数据集并根据结果绘制出一个图形。
5.2 源码
#conding=utf-8from die import Dieimport pygalimport matplotlib as mpl# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False
die1 = Die()
die2 = Die(10)
results = []for roll_num in range(5000):
result = die1.roll() + die2.roll()
results.append(result)# print(results)# 分析结果frequencies = []
max_result = die1.num_sides+die2.num_sidesfor value in range(2,max_result+1):
frequency = results.count(value)
frequencies.append(frequency)# print(frequencies)hist = pygal.Bar()
hist.title = 'D6 和 D10 骰子5000次投掷的结果直方图'# hist.x_labels=['2','3','4','5','6','7','8','9','10','11','12','13','14','15','16']hist.x_labels=[x for x in range(2,max_result+1)]
hist.x_title = 'Result'hist.y_title ='Frequency of Result'hist.add('D6 + D10',frequencies)
hist.render_to_file('dice_visual.svg')
5. 生成结果
6 绘制气温图表
6.1 需求描述
对csv文件进行处理，提取并读取天气数据，绘制气温表，在图表中添加日期并绘制最高气温和最低气温的折线图，并对气温区域进行着色。
6.2 源码
csv文件中2014年7月部分数据信息
View Code
highs_lows.py文件信息
import csvfrom datetime import datetimefrom matplotlib import pyplot as pltimport matplotlib as mpl# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# Get dates, high, and low temperatures from file.filename = 'death_valley_2014.csv'with open(filename) as f:
reader = csv.reader(f)
header_row = next(reader) # print(header_row)
# for index,column_header in enumerate(header_row):
# print(index,column_header)
dates, highs,lows = [],[], [] for row in reader: try:
current_date = datetime.strptime(row[0], "%Y-%m-%d")
high = int(row[1])
low = int(row[3]) except ValueError: # 处理
print(current_date, 'missing data') else:
dates.append(current_date)
highs.append(high)
lows.append(low)# 汇制数据图形fig = plt.figure(dpi=120,figsize=(10,6))
plt.plot(dates,highs,c='red',alpha=0.5)# alpha指定透明度plt.plot(dates,lows,c='blue',alpha=0.5)
plt.fill_between(dates,highs,lows,facecolor='orange',alpha=0.1)#接收一个x值系列和y值系列，给图表区域着色#设置图形格式plt.title('2014年加利福尼亚死亡谷日气温最高最低图',fontsize=24)
plt.xlabel('日（D）',fontsize=16)
fig.autofmt_xdate() # 绘制斜体日期标签plt.ylabel('温度（F）',fontsize=16)
plt.tick_params(axis='both',which='major',labelsize=16)# plt.axis([0,31,54,72]) # 自定义数轴起始刻度plt.savefig('highs_lows.png',bbox_inches='tight')
plt.show()
6.3 生成结果
7 制作世界人口地图：JSON格式
7.1 需求描述
下载json格式的人口数据，并使用json模块来处理。
7.2 源码
json数据population_data.json部分信息
countries.py
from pygal.maps.world import COUNTRIESfor country_code in sorted(COUNTRIES.keys()): print(country_code, COUNTRIES[country_code])
countries_codes.py
from pygal.maps.world import COUNTRIESdef get_country_code(country_name): """Return the Pygal 2-digit country code for the given country."""
for code, name in COUNTRIES.items(): if name == country_name: return code # If the country wasn't found, return None.
returnprint(get_country_code('Thailand'))# print(get_country_code('Andorra'))
americas.py
import pygal
wm =pygal.maps.world.World()
wm.title = 'North, Central, and South America'wm.add('North America', ['ca', 'mx', 'us'])
wm.add('Central America', ['bz', 'cr', 'gt', 'hn', 'ni', 'pa', 'sv'])
wm.add('South America', ['ar', 'bo', 'br', 'cl', 'co', 'ec', 'gf', 'gy', 'pe', 'py', 'sr', 'uy', 've'])
wm.add('Asia', ['cn', 'jp', 'th'])
wm.render_to_file('americas.svg')
world_population.py
#conding = utf-8import jsonfrom matplotlib import pyplot as pltimport matplotlib as mplfrom country_codes import get_country_codeimport pygalfrom pygal.style import RotateStylefrom pygal.style import LightColorizedStyle# 解决中文乱码问题mpl.rcParams['font.sans-serif']=['SimHei']
mpl.rcParams['axes.unicode_minus']=False# 加载json数据filename='population_data.json'with open(filename) as f:
pop_data = json.load(f) # print(pop_data[1])# 创建一个包含人口的字典cc_populations={}# cc1_populations={}# 打印每个国家2010年的人口数量for pop_dict in pop_data: if pop_dict['Year'] == '2010':
country_name = pop_dict['Country Name']
population = int(float(pop_dict['Value'])) # 字符串数值转化为整数
# print(country_name + ":" + str(population))
code = get_country_code(country_name) if code:
cc_populations[code] = population # elif pop_dict['Year'] == '2009':
# country_name = pop_dict['Country Name']
# population = int(float(pop_dict['Value'])) # 字符串数值转化为整数
# # print(country_name + ":" + str(population))
# code = get_country_code(country_name)
# if code:
# cc1_populations[code] = populationcc_pops_1,cc_pops_2,cc_pops_3={},{},{}for cc,pop in cc_populations.items(): if pop <10000000:
cc_pops_1[cc]=pop elif pop<1000000000:
cc_pops_2[cc]=pop else:
cc_pops_3[cc]=pop# print(len(cc_pops_1),len(cc_pops_2),len(cc_pops_3))wm_style = RotateStyle('#336699',base_style=LightColorizedStyle)
wm =pygal.maps.world.World(style=wm_style)
wm.title = '2010年世界各国人口统计图'wm.add('0-10m', cc_pops_1)
wm.add('10m-1bm',cc_pops_2)
wm.add('>1bm',cc_pops_3)# wm.add('2009', cc1_populations)wm.render_to_file('world_populations.svg')
7.3 生成结果
countries.py
world_population.py
8 Pygal可视化github仓库
8.1 需求描述
调用web API对GitHub数据仓库进行可视化展示:https://api.github.com/search/repositories?q=language:python&sort=stars
8.2 源码
python_repos.py
# coding=utf-8import requestsimport pygalfrom pygal.style import LightColorizedStyle as LCS, LightenStyle as LS# Make an API call, and store the response.url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'r = requests.get(url)print("Status code:", r.status_code) # 查看请求是否成功，200表示成功response_dict = r.json()# print(response_dict.keys())print("Total repositories:", response_dict['total_count'])# Explore information about the repositories.repo_dicts = response_dict['items']print("Repositories returned:",len(repo_dicts))# 查看项目信息# repo_dict =repo_dicts[0]# print('\n\neach repository:')# for repo_dict in repo_dicts:# print("\nName:",repo_dict['name'])# print("Owner:",repo_dict['owner']['login'])# print("Stars:",repo_dict['stargazers_count'])# print("Repository:",repo_dict['html_url'])# print("Description:",repo_dict['description'])# 查看每个项目的键# print('\nKeys:',len(repo_dict))# for key in sorted(repo_dict.keys()):# print(key)names, plot_dicts = [], []for repo_dict in repo_dicts:
names.append(repo_dict['name'])
plot_dicts.append(repo_dict['stargazers_count'])# 可视化my_style = LS('#333366', base_style=LCS)
my_config = pygal.Config() # Pygal类Config实例化my_config.x_label_rotation = 45 # x轴标签旋转45度my_config.show_legend = False # show_legend隐藏图例my_config.title_font_size = 24 # 设置图标标题主标签副标签的字体大小my_config.label_font_size = 14my_config.major_label_font_size = 18my_config.truncate_label = 15 # 较长的项目名称缩短15字符my_config.show_y_guides = False # 隐藏图表中的水平线my_config.width = 1000 # 自定义图表的宽度chart = pygal.Bar(my_config, style=my_style)
chart.title = 'Most-Starred Python Projects on GitHub'chart.x_labels = names
chart.add('', plot_dicts)
chart.render_to_file('python_repos.svg')
8.3 生成结果
本文转自 zddnd 51CTO博客，原文链接:
http://blog.51cto.com/13013666/1949246
