Tech with tim

import pandas as pd
import numpy as np
import sklearn
from sklearn import linear_model
from sklearn.utils import shuffle

data = pd.read_csv("student-mat.csv", sep=";")

data = data[["G1", "G2", "G3", "studytime", "failures", "absences"]]

predict = "G3"

X = np.array(data.drop([predict], 1))
y = np.array(data[predict])

x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(X, y, test_size = 0.1)

Source: techwithtim.net

Similar codes

0 vote154 views1 answer
How to call any function with it name as a string
Python
0 vote206 views1 answer
Tuto date and time python
Python
0 vote163 views1 answer
Python - extract min and max values per each column name
Python
0 vote159 views2 answers
Generator expression
Python
0 vote267 views1 answer
From numpy to list python
Python
1 vote156 views1 answer
Transparancy argument pyplot
Python
0 vote155 views1 answer
Pyspark groupby sum
Python
-1 vote159 views1 answer
Show dataframe pandas python
Python
4 votes149 views2 answers
Pandas normalize df
Python
1 vote167 views1 answer
Ls.ProgrammingError: permission denied for table django_migrations
Python