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 npimport matplotlib.pyplot as pltimport matplotlib as mpldef 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 namelabels   = ['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)