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from urllib.request import urlretrieve
import pandas as pd
import jovian
import plotly.express as px
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from sklearn.linear_model import LinearRegression
from sklearn import metrics
from math import sqrt
from sklearn import preprocessing
matplotlib.rcParams['font.size'] = 14
matplotlib.rcParams['figure.figsize'] = (10, 6)
matplotlib.rcParams['figure.facecolor'] = '#00000000'
medical_charges_url = 'https://raw.githubusercontent.com/JovianML/opendatasets/master/data/medical-charges.csv'
urlretrieve(medical_charges_url, 'medical.csv')
('medical.csv', <http.client.HTTPMessage at 0x286f6a86188>)
medical_df = pd.read_csv('medical.csv')
medical_df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 1338 entries, 0 to 1337 Data columns (total 7 columns): age 1338 non-null int64 sex 1338 non-null object bmi 1338 non-null float64 children 1338 non-null int64 smoker 1338 non-null object region 1338 non-null object charges 1338 non-null float64 dtypes: float64(2), int64(2), object(3) memory usage: 73.3+ KB