오징어게임

선생님 이번 오징어 게임 미션을 하면서 작업형 2를 풀고 있습니다

import pandas as pd

train = pd.read_csv("../input/big-data-analytics-certification/t2-1-train.csv")

test = pd.read_csv("../input/big-data-analytics-certification/t2-1-test.csv")

train.head() #pop: 'TravelInsurance' drop:'id'

test.head() #pop:'id'

train.info() #'Employment Type','GraduateOrNot','FrequentFlyer','EverTravelledAbroad'

train.isnull().sum() #'AnnualIncome' 결측값

test.isnull().sum() #'AnnualIncome' 결측값

target = train.pop('TravelInsurance')

test_id = test.pop('id')

me = train['AnnualIncome'].mean()

train = train.fillna(me)

me = test['AnnualIncome'].mean()

test = test.fillna(me)

from sklearn.preprocessing import LabelEncoder

encoder = LabelEncoder()

train['Employment Type'] = encoder.fit_transform(train['Employment Type'])

train['GraduateOrNot'] = encoder.fit_transform(train['GraduateOrNot'])

train['FrequentFlyer'] = encoder.fit_transform(train['FrequentFlyer'])

train['EverTravelledAbroad'] = encoder.fit_transform(train['EverTravelledAbroad'])

test['Employment Type'] = encoder.fit_transform(test['Employment Type'])

test['GraduateOrNot'] = encoder.fit_transform(test['GraduateOrNot'])

test['FrequentFlyer'] = encoder.fit_transform(test['FrequentFlyer'])

test['EverTravelledAbroad'] = encoder.fit_transform(test['EverTravelledAbroad'])

from sklearn.model_selection import train_test_split

X_tr, X_val, y_tr, y_val = train_test_split(train, target, test_size=0.2, random_state=0)

from sklearn.ensemble import RandomForestClassifier

model = RandomForestClassifier(random_state=2022)

model.fit(X_tr, y_tr)

pred = model.predict_proba(X_val)

from sklearn.metrics import roc_auc_score

roc_auc_score(y_val, pred[:,1])

이렇게 코드를 작성했는데 예측하는 단계에서

pred = model.predict_proba(test) 이걸 썼더니

X has 8 features, but RandomForestClassifier is expecting 9 features as input.

이렇게 에러가 뜨는데 뭐가 잘못됐을까요?