NumPy

Einführung in Python

Hugo Bowne-Anderson

Data Scientist at DataCamp

Listen-Zusammenfassung

Leistungsstark
Sammlung von Werten
Kann verschiedene Typen beinhalten
Ändern, Hinzufügen, Löschen
Notwendig für Data Science
- Mathematische Operationen auf Sammlungen
- Geschwindigkeit

height = [1.73, 1.68, 1.71, 1.89, 1.79]
height

[1.73, 1.68, 1.71, 1.89, 1.79]

weight = [65.4, 59.2, 63.6, 88.4, 68.7]
weight

[65.4, 59.2, 63.6, 88.4, 68.7]

weight / height ** 2

TypeError: unsupported operand type(s) for ** or pow(): 'list' and 'int'

import numpy as np

np_height = np.array(height)
np_height

array([1.73, 1.68, 1.71, 1.89, 1.79])

np_weight = np.array(weight)
np_weight

array([65.4, 59.2, 63.6, 88.4, 68.7])

bmi = np_weight / np_height ** 2
bmi

array([21.85171573, 20.97505669, 21.75028214, 24.7473475 , 21.44127836])

height = [1.73, 1.68, 1.71, 1.89, 1.79]
weight = [65.4, 59.2, 63.6, 88.4, 68.7]
weight / height ** 2

TypeError: unsupported operand type(s) for ** or pow(): 'list' and 'int'

np_height = np.array(height)
np_weight = np.array(weight)
np_weight / np_height ** 2

array([21.85171573, 20.97505669, 21.75028214, 24.7473475 , 21.44127836])

np.array([1.0, "is", True])

array(['1.0', 'is', 'True'], dtype='<U32')

python_list = [1, 2, 3]
numpy_array = np.array([1, 2, 3])

python_list + python_list

[1, 2, 3, 1, 2, 3]

numpy_array + numpy_array

array([2, 4, 6])

bmi

array([21.85171573, 20.97505669, 21.75028214, 24.7473475 , 21.44127836])

bmi[1]

20.975

bmi > 23

array([False, False, False,  True, False])

bmi[bmi > 23]

array([24.7473475])

Einführung in Python