Article Outline
Python matplotlib example 'boston'
Modules used in program:
import seaborn as sns
import statsmodels.api as sm
import sklearn
import matplotlib.pyplot as plt
import scipy.stats as stats
import pandas as pd
import numpy as np
python boston
Python matplotlib example: boston
%matplotlib inline
import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
import sklearn
import statsmodels.api as sm
import seaborn as sns
sns.set_style("whitegrid")
sns.set_context("poster")
# special matplotlib argument for improved plots
from matplotlib import rcParams
from sklearn.datasets import load_boston
boston = load_boston()
bos = pd.DataFrame(boston.data)
bos.columns = boston.feature_names
bos['PRICE'] = boston.target
X = bos.drop('PRICE', axis = 1)
Y = bos['PRICE']
X_train, X_test, Y_train, Y_test =\
sklearn.cross_validation.train_test_split(X, Y, test_size = 0.33, random_state = 5)
from sklearn.linear_model import LinearRegression
lm = LinearRegression()
lm.fit(X_train, Y_train)
Y_pred = lm.predict(X_test)
plt.scatter(Y_test, Y_pred)
plt.xlabel("Prices: $Y_i$")
plt.ylabel("Predicted prices: $\hat{Y}_i$")
plt.title("Prices vs Predicted prices: $Y_i$ vs $\hat{Y}_i$")
Python links
- Learn Python: https://pythonbasics.org/
- Python Tutorial: https://pythonprogramminglanguage.com