尝试以下代码：

使用以下代码读取给定的数据集

import pandas as pd
df=pd.read_csv('assets/NISPUF17.csv',index_col=0)
df

主代码

def chickenpox_by_sex():
    # YOUR CODE HERE
    male_df=df[df['SEX']==1]           
    vac_m=male_df[male_df['P_NUMVRC']>=1]  
    cp_m=vac_m[vac_m['HAD_CPOX']==1]       
    counts_cp_m=cp_m['SEX'].count()
    ncp_m=vac_m[vac_m['HAD_CPOX']==2]
    counts_ncp_m=ncp_m['SEX'].count()
    male=counts_cp_m/counts_ncp_m
    female_df=df[df['SEX']==2]               
    vac_f=female_df[female_df['P_NUMVRC']>=1]  
    cp_f=vac_f[vac_f['HAD_CPOX']==1]       
    counts_cp_f=cp_f['SEX'].count()
    ncp_f=vac_f[vac_f['HAD_CPOX']==2]
    counts_ncp_f=ncp_f['SEX'].count()
    female=counts_cp_f/counts_ncp_f
    ratio_dict={"male":male,"female":female}
    return ratio_dict
    raise NotImplementedError()

使用以下代码进行检查

chickenpox_by_sex()['female']

完成此操作的最终代码

assert len(chickenpox_by_sex())==2, "Return a dictionary with two items, the first for males and the second for females."

=〉[性别]-〉性别= 1（雄性）;性别= 2（雌性）
=〉[HAD_COP]-〉感染水痘= 1;未感染水痘= 2
=〉[P_NUMVRC]〉= 1-〉给予一剂或多剂

• 比率（男性）=（已接种及感染水痘）/（已接种及未感染水痘）
• 比率（女性）=（已接种及感染水痘）/（已接种及未感染水痘）

变量名称：
公-公 Dataframe
vac_m-接种雄性
cp_m-接种和感染水痘（雄性）
counts_cp_m-接种和感染水痘的计数
ncp_m-接种疫苗但未感染水痘（男性）
counts_ncp_m-接种疫苗且未感染水痘
女性也是如此。

正确的解决方案。

def chickenpox_by_sex():
    import pandas as pd

    df = pd.read_csv("NISPUF17.csv")

    maleDf = df[df["SEX"] ==1]
    doses1 = maleDf[maleDf["P_NUMVRC"] >= 1]
    chichkenPox1_1 = doses1[doses1["HAD_CPOX"] == 1]
    count1_1 = chichkenPox1_1["SEX"].count()
    chichkenPox1_2 = doses1[doses1["HAD_CPOX"] == 2]
    count1_2 = chichkenPox1_2["SEX"].count()
    resultMale = count1_1/count1_2

    femaleDf = df[df["SEX"] == 2]
    doses2 = femaleDf[femaleDf["P_NUMVRC"] >= 1]
    chichkenPox2_1 = doses2[doses2["HAD_CPOX"] == 1]
    count2_1 = chichkenPox2_1["SEX"].count()
    chichkenPox2_2 = doses2[doses2["HAD_CPOX"] == 2]
    count2_2 = chichkenPox2_2["SEX"].count()
    resultFemale = count2_1/count2_2

    dict = {"male":resultMale,
            "female":resultFemale
        }   

    return dict

下面的代码同样适用：

import pandas as pd
import numpy as np
import math
def chickenpox_by_sex():
 df=pd.read_csv('assets/NISPUF17.csv')
 c_vaccinated=df[df['P_NUMVRC']>0] 
 menstats=c_vaccinated[c_vaccinated['SEX']==1]
 mnocpox=len(menstats[menstats['HAD_CPOX']==2])
 menratio=len(menstats[menstats['HAD_CPOX']==1])/mnocpox
 
 
 wstats=c_vaccinated[c_vaccinated['SEX']==2]
 wnocpox=len(wstats[wstats['HAD_CPOX']==2])  
 wratio=len(wstats[wstats['HAD_CPOX']==1])/wnocpox
 ratios={'male':menratio,'female':wratio}

 return ratios
chickenpox_by_sex()

import pandas as pd

def chickenpox_by_sex():
    df = pd.read_csv('assets/NISPUF17.csv')
    df = df.drop(df[df.HAD_CPOX == 77].index)
    df = df.drop(df[df.HAD_CPOX == 99].index)
    df = df.dropna(subset=['P_NUMVRC'])

    df.loc[df['HAD_CPOX'] == 1, 'HAD_CPOX'] = 'YES'
    df.loc[df['HAD_CPOX'] == 2, 'HAD_CPOX'] = 'NO'

    df.loc[df['SEX'] == 1, 'SEX'] = 'male'
    df.loc[df['SEX'] == 2, 'SEX'] = 'female'

    df.loc[df['P_NUMVRC'] == 2.0, 'P_NUMVRC'] = 1
    df.loc[df['P_NUMVRC'] == 3.0, 'P_NUMVRC'] = 1

    df = df[['SEX', 'P_NUMVRC', 'HAD_CPOX']].round(decimals=0)

    dfm = df[df['SEX'] == 'male']
    dfmVac = dfm[dfm['P_NUMVRC'] == 1.0]
    mPoxVacYes = len(dfmVac[dfmVac['HAD_CPOX'] == 'YES'])
    mPoxVacNo = len(dfmVac[dfmVac['HAD_CPOX'] == 'NO'])

    dff = df[df['SEX'] == 'female']
    dffVac = dff[dff['P_NUMVRC'] == 1.0]
    fPoxVacYes = len(dffVac[dffVac['HAD_CPOX'] == 'YES'])
    fPoxVacNo = len(dffVac[dffVac['HAD_CPOX'] == 'NO'])

    ratioM = mPoxVacYes/float(mPoxVacNo)
    ratioF = fPoxVacYes/float(fPoxVacNo)

    result = {'male': ratioM * 100, 'female': ratioF * 100}

    return result

import pandas as pd
import numpy as np
df = pd.read_csv('assets/NISPUF17.csv', usecols = ['HAD_CPOX', 'SEX', 'P_NUMVRC']).dropna().reset_index()
    
    def chickenpox_by_sex():
        girls = df[df.SEX == 2]
        girls_had = girls[(girls.HAD_CPOX == 1) & (girls.P_NUMVRC > 0.0)]
        girls_not_had = girls[(girls.HAD_CPOX == 2) &(girls.P_NUMVRC > 0.0)]        
        girls_ratio = len(girls_had)/len(girls_not_had)
    
        boys = df[df.SEX == 1]
        boys_had = boys[(boys.HAD_CPOX == 1) & (boys.P_NUMVRC > 0.0)]
        boys_not_had = boys[(boys.HAD_CPOX == 2) &(boys.P_NUMVRC > 0.0)]
        boys_ratio = len(boys_had)/len(boys_not_had)
    
        result = {"male": round(boys_ratio, ndigits=4),
                  "female":round(girls_ratio, ndigits = 4)}
        return result
        
    chickenpox_by_sex()