Python进阶(三十八)-数据可视化の利用matplotlib 进行折线图，直方图和饼图的绘制

#Python进阶(三十八)-数据可视化の利用matplotlib 进行折线图，直方图和饼图的绘制
  我用10个国家某年的GDP来绘图，数据如下：
labels = [‘USA’, ‘China’, ‘India’, ‘Japan’, ‘Germany’, ‘Russia’, ‘Brazil’, ‘UK’, ‘France’, ‘Italy’]
quants = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0, 1846950.0]
##折线图绘制
  首先绘制折线图，代码如下：

def draw_line(labels,quants): ind = np.linspace(0,9,10) fig = plt.figure(1) ax  = fig.add_subplot(111) ax.plot(ind,quants) ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) ax.set_xticklabels(labels) plt.grid(True)

plt.show()

  

 

  
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  效果图如下图：

##柱状图绘制
  再画柱状图，代码如下：

def draw_bar(labels,quants): width = 0.4 ind = np.linspace(0.5,9.5,10) # make a square figure fig = plt.figure(1) ax  = fig.add_subplot(111) # Bar Plot ax.bar(ind-width/2,quants,width,color='green') # Set the ticks on x-axis ax.set_xticks(ind) ax.set_xticklabels(labels) # labels ax.set_xlabel('Country') ax.set_ylabel('GDP (Billion US dollar)') # title ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.grid(True)

plt.show()

  

 

  
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  效果图如下图：

##饼图绘制
  最后画饼图，代码如下：

def draw_pie(labels,quants): plt.figure(1, figsize=(6,6)) # For China, make the piece explode a bit expl = [0,0.1,0,0,0,0,0,0,0,0] # Colors used. Recycle if not enough. colors  = ["blue","red","coral","green","yellow","orange"] # autopct: format of "percent" string; plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True) plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5})

plt.show()

  

 

  
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  效果图如下图：

##附录：完整代码：

# -*- coding: gbk -*-

import numpy as np

import matplotlib.pyplot as plt

import matplotlib as mpl def draw_pie(labels,quants): # make a square figure plt.figure(1, figsize=(6,6)) # For China, make the piece explode a bit expl = [0,0.1,0,0,0,0,0,0,0,0] # Colors used. Recycle if not enough. colors  = ["blue","red","coral","green","yellow","orange"] # Pie Plot # autopct: format of "percent" string; plt.pie(quants, explode=expl, colors=colors, labels=labels, autopct='%1.1f%%',pctdistance=0.8, shadow=True) plt.title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.show()

def draw_bar(labels,quants): width = 0.4 ind = np.linspace(0.5,9.5,10) # make a square figure fig = plt.figure(1) ax  = fig.add_subplot(111) # Bar Plot ax.bar(ind-width/2,quants,width,color='green') # Set the ticks on x-axis ax.set_xticks(ind) ax.set_xticklabels(labels) # labels ax.set_xlabel('Country') ax.set_ylabel('GDP (Billion US dollar)') # title ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) plt.grid(True) plt.show()

def draw_line(labels,quants): ind = np.linspace(0,9,10) fig = plt.figure(1) ax  = fig.add_subplot(111) ax.plot(ind,quants) ax.set_title('Top 10 GDP Countries', bbox={'facecolor':'0.8', 'pad':5}) ax.set_xticklabels(labels) plt.grid(True) plt.show()

# quants: GDP

# labels: country name

labels   = ['USA', 'China', 'India', 'Japan', 'Germany', 'Russia', 'Brazil', 'UK', 'France', 'Italy']

quants   = [15094025.0, 11299967.0, 4457784.0, 4440376.0, 3099080.0, 2383402.0, 2293954.0, 2260803.0, 2217900.0, 1846950.0]

draw_pie(labels,quants)

#draw_bar(labels,quants)

#draw_line(labels,quants)

  

 

  
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文章来源: shq5785.blog.csdn.net，作者：No Silver Bullet，版权归原作者所有，如需转载，请联系作者。

原文链接：shq5785.blog.csdn.net/article/details/70187450