I have tried the code below
import pandas as pd
from sklearn.linear_model import LinearRegression
import numpy as np
# Assign the dataframe to this variable.
# TODO: Load the data
bmi_life_data = pd.read_csv("bmi_and_life_expectancy.csv")
X= bmi_life_data['BMI'].values.reshape(-1,1)
y = bmi_life_data['Life expectancy'].values.reshape(-1,1)
# Make and fit the linear regression model
#TODO: Fit the model and Assign it to bmi_life_model
bmi_life_model = LinearRegression()
bmi_life_model.fit(X,y)
# Mak a prediction using the model
# TODO: Predict life expectancy for a BMI value of 21.07931
laos_life_exp = bmi_life_model.predict(21.07931)
but it gives me the error
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.
Even after reshaping it. I have tried to not reshape it but it still gives me the same error.
CodePudding user response:
The error was in the prediction line
laos_life_exp = bmi_life_model.predict(21.07931)
should be
laos_life_exp = bmi_life_model.predict([[21.07931]])
to be of appropriate dimension
Thanks to @onyambu