計算ライブラリのSciPyを利用して、グラフ表示

# ライブラリ読み込み
import pandas
from pandas.plotting import scatter_matrix
import matplotlib.pyplot as plt
from sklearn import model_selection
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.naive_bayes import GaussianNB
from sklearn.svm import SVC

# データセット読み込み
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"
names = ['sepal-length', 'sepal-width', 'petal-length', 'petal-width', 'class']
dataset = pandas.read_csv(url, names=names)

# データ内容
print(dataset.shape)

# 上位データの表示
print(dataset.head(20))

# データ要約
print(dataset.describe())

# classごとの分類
print(dataset.groupby('class').size())

# 箱ひげ図
dataset.plot(kind='box', subplots=True, layout=(2,2), sharex=False, sharey=False)
plt.show()

# 分布図
dataset.hist()
plt.show()

# 相関図？
scatter_matrix(dataset)
plt.show()