Matplotlib数据可视化实例分析

#coding=utf-8

import matplotlib as mpl

import matplotlib.pyplot as plt

import 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()

#coding=utf-8

import matplotlib as mpl

import matplotlib.pyplot as plt

import 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()

#coding=utf-8

import matplotlib as mpl

import matplotlib.pyplot as plt

import 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()

from random import choice

class 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)

#-*- coding: utf-8 -*-

#coding=utf-8

import matplotlib as mpl

import matplotlib.pyplot as plt

import pylab

from 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,

# 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()

import random

class 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)

#coding=utf-8

from die import Die

import pygal

import 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_sides

for 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()

#conding=utf-8

from die import Die

import pygal

import 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_sides

for 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')

AKDT,Max TemperatureF,Mean TemperatureF,

Min TemperatureF,Max Dew PointF,MeanDew

PointF,Min DewpointF,Max Humidity, Mean Humidity,

Min Humidity, Max Sea Level PressureIn,

Mean Sea Level PressureIn, Min Sea Level PressureIn,

Max VisibilityMiles, Mean VisibilityMiles, Min VisibilityMiles,

Max Wind SpeedMPH, Mean Wind SpeedMPH, Max Gust

SpeedMPH,PrecipitationIn, CloudCover, Events, WindDirDegrees

2014-7-1,64,56,50,53,51,48,96,83,58,30.19,30.00,29.79,

10,10,10,7,4,,0.00,7,,337

2014-7-2,71,62,55,55,52,46,96,80,51,29.81,29.75,29.66,

10,9,2,13,5,,0.14,7,Rain,327

2014-7-3,64,58,53,55,53,51,97,85,72,29.88,29.86,29.81,

10,10,8,15,4,,0.01,6,,258

2014-7-4,59,56,52,52,51,50,96,88,75,29.91,29.89,29.87,

10,9,2,9,2,,0.07,7,Rain,255

2014-7-5,69,59,50,52,50,46,96,72,49,29.88,29.82,29.79,

10,10,10,13,5,,0.00,6,,110

2014-7-6,62,58,55,51,50,46,80,71,58,30.13,30.07,29.89,

10,10,10,20,10,29,0.00,6,Rain,213

2014-7-7,61,57,55,56,53,51,96,87,75,30.10,30.07,30.05,

10,9,4,16,4,25,0.14,8,Rain,211

2014-7-8,55,54,53,54,53,51,100,94,86,30.10,30.06,30.04,

10,6,2,12,5,23,0.84,8,Rain,159

2014-7-9,57,55,53,56,54,52,100,96,83,30.24,30.18,30.11,

10,7,2,9,5,,0.13,8,Rain,201

2014-7-10,61,56,53,53,52,51,100,90,75,30.23,30.17,30.03,

10,8,2,8,3,,0.03,8,Rain,215

2014-7-11,57,56,54,56,54,51,100,94,84,30.02,30.00,29.98,

10,5,2,12,5,,1.28,8,Rain,250

2014-7-12,59,56,55,58,56,55,100,97,93,30.18,30.06,29.99,

10,6,2,15,7,26,0.32,8,Rain,275

2014-7-13,57,56,55,58,56,55,100,98,94,30.25,30.22,30.18,

10,5,1,8,4,,0.29,8,Rain,291

2014-7-14,61,58,55,58,56,51,100,94,83,30.24,30.23,30.22,

10,7,0,16,4,,0.01,8,Fog,307

2014-7-15,64,58,55,53,51,48,93,78,64,30.27,30.25,30.24,

10,10,10,17,12,,0.00,6,,318

2014-7-16,61,56,52,51,49,47,89,76,64,30.27,30.23,30.16,

10,10,10,15,6,,0.00,6,,294

2014-7-17,59,55,51,52,50,48,93,84,75,30.16,30.04,29.82,

10,10,6,9,3,,0.11,7,Rain,232

2014-7-18,63,56,51,54,52,50,100,84,67,29.79,29.69,29.65

,10,10,7,10,5,,0.05,6,Rain,299

2014-7-19,60,57,54,55,53,51,97,88,75,29.91,29.82,29.68,

10,9,2,9,2,,0.00,8,,292

2014-7-20,57,55,52,54,52,50,94,89,77,29.92,29.87,29.78,

10,8,2,13,4,,0.31,8,Rain,155

2014-7-21,69,60,52,53,51,50,97,77,52,29.99,29.88,29.78,

10,10,10,13,4,,0.00,5,,297

2014-7-22,63,59,55,56,54,52,90,84,77,30.11,30.04,29.99,

10,10,10,9,3,,0.00,6,Rain,240

2014-7-23,62,58,55,54,52,50,87,80,72,30.10,30.03,29.96,

10,10,10,8,3,,0.00,7,,230

2014-7-24,59,57,54,54,52,51,94,84,78,29.95,29.91,29.89,

10,9,3,17,4,28,0.06,8,Rain,207

2014-7-25,57,55,53,55,53,51,100,92,81,29.91,29.87,29.83,

10,8,2,13,3,,0.53,8,Rain,141

2014-7-26,57,55,53,57,55,54,100,96,93,29.96,29.91,29.87,

10,8,1,15,5,24,0.57,8,Rain,216

2014-7-27,61,58,55,55,54,53,100,92,78,30.10,30.05,29.97,

10,9,2,13,5,,0.30,8,Rain,213

2014-7-28,59,56,53,57,54,51,97,94,90,30.06,30.00,29.96,

10,8,2,9,3,,0.61,8,Rain,261

2014-7-29,61,56,51,54,52,49,96,89,75,30.13,30.02,29.95,

10,9,3,14,4,,0.25,6,Rain,153

2014-7-30,61,57,54,55,53,52,97,88,78,30.31,30.23,30.14,

10,10,8,8,4,,0.08,7,Rain,160

2014-7-31,66,58,50,55,52,49,100,86,65,30.31,30.29,30.26,

10,9,3,10,4,,0.00,3,,217

import csv

from datetime import datetime

from matplotlib import pyplot as plt

import 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()

from pygal.maps.world import COUNTRIES

for country_code in sorted(COUNTRIES.keys()):

print(country_code, COUNTRIES[country_code])

from pygal.maps.world import COUNTRIES

def 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.

return

print(get_country_code('Thailand'))

# print(get_country_code('Andorra'))

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')

#conding = utf-8

import json

from matplotlib import pyplot as plt

import matplotlib as mpl

from country_codes import get_country_code

import pygal

from pygal.style import RotateStyle

from 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:

cc_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')

# coding=utf-8

import requests

import pygal

from 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 = 14

my_config.major_label_font_size = 18

my_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')