• python 实现九型人格测试小程序


    用python实现九型人格测试,并把测试结果绘制成饼图,实现代码如下:

    # @Description: 九型人格
    import xlrd, matplotlib.pyplot as plt
    data = xlrd.open_workbook(r'E:python_script
    ine.xlsx')
    table = data.sheets()[0]
    
    checkout = []#存储题号
    labs = [] #存储九种性格
    sizes = [] #存储大小
    explode=[0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05,0.05]#每块之间的间隙
    with open('ninp.txt', encoding='utf-8') as f:
        f.seek(0)
        rule = eval(f.read())
        f.close()
    for i in range(table.nrows):
        if table.row_values(i)[2] == 1:  # 如果选中的是1 则把题号存入checkout
            checkout.append(int(table.row_values(i)[0]))
    for i in checkout:
        for j in rule:
            if i in rule[j]['QNO']:  # 如果题号在规则中,则size +1
                rule[j]['size'] += 1
    for x in rule:
        labs.append(x)
        sizes.append(rule[x]['size'])
    plt.figure(figsize=(12,6))
    plt.title("My Test Result 
    ")
    colors=['lightgreen','gold','lightskyblue','lightcoral','red','blue','yellow','darkgreen','purple']
    plt.pie(sizes,explode=explode,labels=labs,colors=colors,
                                    labeldistance=1.1,autopct='%3.1f%%',shadow = False,
                                    startangle=90,pctdistance=0.6)
    plt.axis('equal')
    plt.legend()
    plt.show()

    运行结果如下:

    
    

    ninp.txt里存储的规则字典格式如下:

    {
    "Perfect":{'QNO':[2,14,55,57,60,63,73,81,87,91,97,102,104,106],'size':0},
    "Helping":{'QNO':[6,8,22,30,69,71,79,82,85,86,89,90],'size':0},
    "Achievement":{'QNO':[20,33,38,59,65,67,70,72,74,77,80,93],'size':0},
    "Ego":{'QNO':[7,13,17,52,53,54,56,58,61,64,100,105],'size':0},
    "Observation":{'QNO':[3,19,23,32,42,43,47,48,51,83,88,99,101],'size':0},
    "Loyal":{'QNO':[9,10,26,29,31,35,37,45,46,68,75],'size':0},
    "Hedonism":{'QNO':[4,16,18,21,28,49,78,92,103],'size':0},
    "Leading":{'QNO':[5,11,24,27,40,44,50,66,76,84,95,96],'size':0},
    "Peace":{'QNO':[1,12,15,25,34,36,39,41,62,94,98,107,108],'size':0}
    }
    nine.xlsx文件题目及测试结果内容如下:

    
    
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  • 原文地址:https://www.cnblogs.com/wolfshining/p/7685505.html
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