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import numpy as np
import pandas as pd
import seaborn as sns

df = pd.read_csv("Advertising.csv")

df.head()

df.shape

import matplotlib.pyplot as plt

sns.pairplot(df, kind = "reg")
plt.show()

sns.jointplot(x = "TV", y = "sales", data=df, kind="reg")

import statsmodels.api as sm

X = df[["TV"]]
X[:5]

# matris oluşturma
X = sm.add_constant(X)
X[:5]

# bağımlı değişken oluşturma
y = df[["sales"]]
y[:5]

lm = sm.OLS(y, X)
model = lm.fit()

model.summary()

# üstteki modeli aşağıdaki gibi de kurgulayabiliriz
import statsmodels.formula.api as smf

lm = smf.ols("sales ~ TV", df)
model = lm.fit()
model.summary()

# model parametreleri
model.params

model.summary().tables[1]