I tried executing this code in windows and it ran flawlessly but in Ubuntu as soon as I run this code, Ubuntu freezes for 3-4 mins and then the result come and then Ubuntu behaves laggy until I restart it.
import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn import preprocessing
from xgboost import XGBClassifier
import xgboost as xgb
from sklearn.metrics import accuracy_score
dataset_len = 40000000
dlen = int(dataset_len/2)
X_11 = pd.Series(np.random.normal(2,2,dlen))
X_12 = pd.Series(np.random.normal(9,2,dlen))
X_1 = pd.concat([X_11, X_12]).reset_index(drop=True)
X_21 = pd.Series(np.random.normal(1,3,dlen))
X_22 = pd.Series(np.random.normal(7,3,dlen))
X_2 = pd.concat([X_21, X_22]).reset_index(drop=True)
X_31 = pd.Series(np.random.normal(3,1,dlen))
X_32 = pd.Series(np.random.normal(3,4,dlen))
X_3 = pd.concat([X_31, X_32]).reset_index(drop=True)
X_41 = pd.Series(np.random.normal(1,1,dlen))
X_42 = pd.Series(np.random.normal(5,2,dlen))
X_4 = pd.concat([X_41, X_42]).reset_index(drop=True)
Y = pd.Series(np.repeat([0,1],dlen))
df = pd.concat([X_1, X_2, X_3, X_4, Y], axis=1)
df.columns = ['X1', 'X2', 'X3', 'X_4', 'Y']
df.head()