text_plain_output_1.png
import pandas as pd

import warnings

import gc
import warnings
warnings.filterwarnings('ignore')
import scipy as sp
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)
from tqdm.auto import tqdm
import itertools
from sklearn.preprocessing import StandardScaler, OrdinalEncoder, MinMaxScaler
from sklearn.metrics import roc_auc_score, roc_curve
import matplotlib.pyplot as plt

df_train = pd.read_csv('../input/amazon-train/delivery time.csv')
df_test = pd.read_csv('../input/amazon-train/delivery time Test.csv')
test_id = df_test['ID']
df_train = df_train.set_index('Source.Name.1')
df_test = df_test.set_index('Source.Name.1')
target = df_train['Time_taken (min)']

x_train = cdata3.iloc[:df_train.shape[0], :]
x_test = cdata3.iloc[df_train.shape[0]:, :]