python之类型错误: 'DataFrame' 对象不是可调用的 python 函数

我有两个函数，一个从 csv 创建数据框，另一个操作该数据框。我第一次通过 lsc_age(import_data()) 函数传递原始数据没有问题。但是，我在第二次以上尝试时收到上述错误 (TypeError: 'DataFrame' object is not callable) 。关于如何解决问题的任何想法？

def import_data(csv,date1,date2): 
    global data 
    data = pd.read_csv(csv,header=1) 
    data = data.iloc[:,[0,1,4,6,7,8,9,11]] 
    data = data.dropna(how='all') 
    data = data.rename(columns={"National: For Dates 9//1//"+date1+" - 8//31//"+date2:'event','Unnamed: 1':'time','Unnamed: 4':'points',\ 
              'Unnamed: 6':'name','Unnamed: 7':'age','Unnamed: 8':'lsc','Unnamed: 9':'club','Unnamed: 11':'date'}) 
    data = data.reset_index().drop('index',axis=1) 
    data = data[data.time!='Time'] 
    data = data[data.points!='Power '] 
    data = data[data['event']!="National: For Dates 9//1//"+date1+" - 8//31//"+date2] 
    data = data[data['event']!='USA Swimming, Inc.'] 
    data = data.reset_index().drop('index',axis=1) 
    for i in range(len(data)): 
        if len(str(data['event'][i])) <= 3: 
            data['event'][i] = data['event'][i-1] 
        else: 
            data['event'][i] = data['event'][i] 
    data = data.dropna() 
    age = [] 
    event = [] 
    gender = [] 
    for row in data.event: 
        gender.append(row.split(' ')[0]) 
        if row[:9]=='Female 10': 
            n = 4 
            groups = row.split(' ') 
            age.append(' '.join(groups[1:n])) 
            event.append(' '.join(groups[n:])) 
        elif row[:7]=='Male 10': 
            n = 4 
            groups = row.split(' ') 
            age.append(' '.join(groups[1:n])) 
            event.append(' '.join(groups[n:])) 
        else: 
            n = 2 
            groups = row.split(' ') 
            event.append(' '.join(groups[n:])) 
            groups = row.split(' ') 
            age.append(groups[1]) 
    data['age_group'] = age 
    data['event_simp'] = event 
    data['gender'] = gender 
    data['year'] = date2 
    return data 
 
def lsc_age(data_two): 
    global lsc, lsc_age, top, all_performers 
    lsc = pd.DataFrame(data_two['event'].groupby(data_two['lsc']).count()).reset_index().sort_values(by='event',ascending=False) 
    lsc_age = data_two.groupby(['year','age_group','lsc'])['event'].count().reset_index().sort_values(by=['age_group','event'],ascending=False) 
    top = pd.concat([lsc_age[lsc_age.age_group=='10 & under'].head(),lsc_age[lsc_age.age_group=='11-12'].head(),\ 
                 lsc_age[lsc_age.age_group=='13-14'].head(),lsc_age[lsc_age.age_group=='15-16'].head(),\ 
                 lsc_age[lsc_age.age_group=='17-18'].head()],ignore_index=True) 
    all_performers = pd.concat([lsc_age[lsc_age.age_group=='10 & under'],lsc_age[lsc_age.age_group=='11-12'],\ 
                            lsc_age[lsc_age.age_group=='13-14'],lsc_age[lsc_age.age_group=='15-16'],\ 
                            lsc_age[lsc_age.age_group=='17-18']],ignore_index=True) 
    all_performers = all_performers.rename(columns={'event':'no. top 100'}) 
    all_performers['age_year_lsc'] = all_performers.age_group+' '+all_performers.year.astype(str)+' '+all_performers.lsc 
    return all_performers 
 
years = [i for i in range(2008,2018)] 
for i in range(len(years)-1): 
    lsc_age(import_data(str(years[i+1])+"national100.csv",\ 
    str(years[i]),str(years[i+1]))) 

请您参考如下方法:

在第一次调用函数 lsc_age() 时

lsc_age = data_two.groupby(['year','age_group','lsc'])['event'].count().reset_index().sort_values(by=['age_group','event'],ascending=False) 

您正在用数据框覆盖您的函数对象。发生这种情况是因为您使用

global lsc, lsc_age, top, all_performers 

Python 中的函数是对象。请查看有关此的更多信息 here .

要解决您的问题，请尽量避免全局导入。它们似乎没有必要。尝试通过函数的参数传递数据。