2회 기출유형(작업형2)

import pandas as pd

import numpy as np

from sklearn.model_selection import train_test_split

def exam_data_load(df, target, id_name="", null_name=""):

    if id_name == "":

        df = df.reset_index().rename(columns={"index": "id"})

        id_name = 'id'

    else:

        id_name = id_name

    if null_name != "":

        df[df == null_name] = np.nan

    X_train, X_test = train_test_split(df, test_size=0.2, random_state=2022)

    y_train = X_train[[id_name, target]]

    X_train = X_train.drop(columns=[target])

    y_test = X_test[[id_name, target]]

    X_test = X_test.drop(columns=[target])

    return X_train, X_test, y_train, y_test

df = pd.read_csv("Train.csv") # 파일명이 다를 경우 파일명을 수정해주세요

X_train, X_test, y_train, y_test = exam_data_load(df, target='Reached.on.Time_Y.N', id_name='ID')

X_train.to_csv("X_train.csv", index=False)

y_train.to_csv("y_train.csv", index=False)

X_test.to_csv("X_test.csv", index=False)

import pandas as pd
X_test = pd.read_csv("X_test.csv")
X_train = pd.read_csv("X_train.csv")
y_train = pd.read_csv("y_train.csv")

# X_train.shape, y_train.shape, X_test.shape
#print(X_train.info())
print(X_test.info())
#print(y_train.info())

y_train = y_train.drop(columns = ['ID'])

#print(X_train.shape, X_test.shape)
X_train = X_train.drop(columns = ['ID'])
X_train = X_train.drop(columns = ['Warehouse_block'])
X_train = X_train.drop(columns = ['Mode_of_Shipment'])
X_train = X_train.drop(columns = ['Product_importance'])
X_train = X_train.drop(columns = ['Gender'])

X_test = X_test.pop('ID')
X_test = X_test.drop(columns = ['Warehouse_block'])
X_test = X_test.drop(columns = ['Mode_of_Shipment'])
X_test = X_test.drop(columns = ['Product_importance'])
X_test = X_test.drop(columns = ['Gender'])
#print(X_train.shape, X_test.shape)

from sklearn.ensemble import RandomForestClassifier
model = RandomForestClassifier()
model.fit(X_train,y_train)
model_pred = model.predict_proba(X_test)

강사님 안녕하세요. 위와 같이 인코딩을 하지 않고 object 컬럼을 지우는 방향으로 해서 모델학습을 진행하였어요. 그런데 이런 애러가 났어요. 어떻게 해야 할까요?

None

<ipython-input-36-25befb274901>:30: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  model.fit(X_train,y_train)
/usr/local/lib/python3.10/dist-packages/sklearn/base.py:439: UserWarning: X does not have valid feature names, but RandomForestClassifier was fitted with feature names
  warnings.warn(

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-36-25befb274901> in <cell line: 31>()
     29 model = RandomForestClassifier()
     30 model.fit(X_train,y_train)
---> 31 model_pred = model.predict_proba(X_test)
     32 

3 frames

/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
    900             # If input is 1D raise error
    901             if array.ndim == 1:
--> 902                 raise ValueError(
    903                     "Expected 2D array, got 1D array instead:\narray={}.\n"
    904                     "Reshape your data either using array.reshape(-1, 1) if "

ValueError: Expected 2D array, got 1D array instead:
array=[ 8285. 10192.  8675. ...  7390.  9977.  5696.].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.