5.Python数据可视化-美国大学各专业的性别差距

Visualizing The Gender Gap in College degrees：

读取数据：

import pandas as pd
data=pd.read_csv('./data/percent-bachelors-degrees-women-usa.csv')
print(data.columns)
#print(data[:2])
print(data.describe)

可视化：

def decorateAxes(axes):
    for key,spine in axes.spines.items():
        spine.set_visible(False)
    axes.set_ylim(0, 100)
    axes.set_yticks([0,100])
    axes.axhline(y=50,c=(171/255, 171/255, 171/255),alpha=0.3)
    axes.tick_params(left='off',right='off',top='off',bottom='off',labelbottom='off')
    
def plotCharts(axes,sub_cats,index):
    axes.plot(data['Year'],data[sub_cats[index]],c=cb_dark_blue,label='Women',linewidth=3)
    axes.plot(data['Year'],100-data[sub_cats[index]],c=cb_orange,label='Men',linewidth=3)
    for key,spine in axes.spines.items():
        spine.set_visible(False)
    axes.set_title(sub_cats[index])
    decorateAxes(axes)
    if index==(len(sub_cats)-1):
        axes.tick_params(labelbottom='on')

        
import matplotlib.pyplot as plt
%matplotlib inline

#Group degrees into three category.
sc_cats = ['Psychology', 'Biology', 'Math and Statistics', 'Physical Sciences', 'Computer Science', 'Engineering']
lib_arts_cats = ['Foreign Languages', 'English', 'Communications and Journalism', 'Art and Performance', 'Social Sciences and History']
other_cats = ['Health Professions', 'Public Administration', 'Education', 'Agriculture','Business', 'Architecture']

fig=plt.figure(figsize=(16,16))
cb_dark_blue = (0/255,107/255,164/255)
cb_orange = (255/255, 128/255, 14/255)


for i in range(1,17,3):
    
    #Generate first column in line charts.Science degrees.
    sc_cats_index=int(i/3)
    ax=fig.add_subplot(6,3,i)
    plotCharts(ax,sc_cats,sc_cats_index)
    if i==1:
        ax.text(2003, 85, 'Women')
        ax.text(2005, 10, 'Men')
    if i==16:
        ax.text(2005, 87, 'Men')
        ax.text(2003, 7, 'Women')

    #Generate second column in line charts.Liberal arts degrees.
    t=i+1
    if t<15:
        lib_arts_cats_index=int(t/3)
        ax2=fig.add_subplot(6,3,t)
        plotCharts(ax2,lib_arts_cats,lib_arts_cats_index)
        if t==2:
            ax2.text(2003, 85, 'Women')
            ax2.text(2005, 10, 'Men')
    #Generate third column in line charts.Other degrees.   
    r=i+2
    other_cats_index=int((r-1)/3)
    ax3=fig.add_subplot(6,3,r)
    plotCharts(ax3,other_cats,other_cats_index)
    if r==3:
        ax3.text(2003, 90, 'Women')
        ax3.text(2005, 5, 'Men')
    if r==18:
        ax3.text(2005, 62, 'Men')
        ax3.text(2003, 30, 'Women') 

结果如下：

生成图片并保存：

plt.savefig("./data/genders of degrees.png")