# License: BSD 3 clause import numpy as np import matplotlib.pyplot from mpl_toolkits.mplot3d from sklearn import decomposition from sklearn import datasets import pandas as pd as plt import Axes 3D np.random.seed (5) centers = [[1, 1], [-1, -1], [1, -1]] iris = datasets.load_iris() iris_df = pd. DataFrame (data = iris['data'], columns = iris['feature_names'])
# License: BSD 3 clause import numpy as np import matplotlib.pyplot from mpl_toolkits.mplot3d from sklearn import decomposition from sklearn import datasets import pandas as pd as plt import Axes 3D np.random.seed (5) centers = [[1, 1], [-1, -1], [1, -1]] iris = datasets.load_iris() iris_df = pd. DataFrame (data = iris['data'], columns = iris['feature_names'])
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
Explain what this python code is doing:
![# License: BSD 3 clause
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2 import numpy as np
3 import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d
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from sklearn import decomposition
from sklearn import datasets
import pandas as pd
np.random.seed (5)
import Axes 3D
centers = [[1, 1], [-1, -1], [1, -1]]
iris datasets.load_iris ()
iris_df =
pd. DataFrame (data = iris['data'], columns
iris['feature_names'])](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa2a845e9-e168-41e4-bfa5-307beadca896%2Fd7548c1e-6a7b-4a43-8866-8382fa03691e%2Foyzbn4e_processed.png&w=3840&q=75)
Transcribed Image Text:# License: BSD 3 clause
1
2 import numpy as np
3 import matplotlib.pyplot as plt
4
from mpl_toolkits.mplot3d
5
6
7
8
9
10
11
12
13
14
15
16
17
from sklearn import decomposition
from sklearn import datasets
import pandas as pd
np.random.seed (5)
import Axes 3D
centers = [[1, 1], [-1, -1], [1, -1]]
iris datasets.load_iris ()
iris_df =
pd. DataFrame (data = iris['data'], columns
iris['feature_names'])
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