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()

  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()

  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()

  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)