Python Train Test Split - Machine Learning
In this Short, I demonstrate my preferred method for splitting a dataframe into training and test dataframes using pandas and sklearn.
Source code:
Libraries
import pandas as pd
import sqlalchemy
from sqlalchemy import create_engine
import sklearn
from sklearn.model_selection import train_test_split
Creating SQL Alchemy engine object
engine = create_engine('postgresql://postgres:youtube@localhost:5432/eSports.val')
Initiailizing connection to database
conn = engine.connect()
SQL query as a string to pass into pd.read_sql function
sql = 'SELECT * FROM players'
creating a dataframe
df = pd.read_sql_query(sql,conn)
dropping columns that aren't being analyzed
df = df.drop(['player_name','team', 'country'], axis=1)
Independent variables
X = df.drop('kd', axis=1)
Dependent (outcome) variable
y = df['kd']
train-test split
X_train, X_test, y_train, y_test = train_test_split(
X
, y
, test_size=0.3
, random_state=2)
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