The implementation of the findGender function

findGender.py

def findGender(str):
    
    f = fNames['name'].apply(lambda x: (x, SequenceMatcher(None,str.lower(),x).ratio()))
    m = mNames['name'].apply(lambda x: (x, SequenceMatcher(None,str.lower(),x).ratio()))
    f = padas.DataFrame([i for i in f], columns=['name','match']).sort_values('match', ascending=False)
    m = padas.DataFrame([i for i in m], columns=['name','match']).sort_values('match', ascending=False)

    maxMScore = m.iloc[0]['match']
    maleName = m.iloc[0]['name']
    maxFScore = f.iloc[0]['match']
    femaleName = f.iloc[0]['name']
    gender = np.nan
    if maxFScore > maxMScore:
        gender = 'female'
    elif maxFScore < maxMScore:
        gender = 'male'
    else:
        femScores = fNames.loc[fNames['name'] == femaleName].iloc[0]['freq']
        memScores = mNames.loc[mNames['name'] == maleName].iloc[0]['freq']
        if femScores > memScores:
            gender = 'female'
        elif femScores < memScores:
            gender = 'male'  
    return gender