import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
from sklearn import set_config
from sklearn.metrics import mean_squared_error
[docs]
def split_xy_columns(dataset):
"""
Split a dataset into X (explanatory variables) and Y (target variables).
Parameters
----------
dataset : pandas dataframe
Returns
-------
dataset.x
Pandas dataframe containing explanatory variables
dataset.y
Pandas dataframe containing target variable
Examples
--------
>>> split_xy_columns(imported_df)
"""
#splitting the x and y columns of the data
dataset_x = dataset
dataset_x = dataset_x.drop('Renewable electricity output (% of total electricity output)', axis=1)
dataset_x = dataset_x.drop('Country Name', axis=1)
dataset_y = dataset[["Renewable electricity output (% of total electricity output)"]]
return dataset_x, dataset_y