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Artificial Intelligence for Idiot
  • Introduction
  • What is Machine Learning
  • Python Basics
    • Random Number
  • Data Manipulation
    • Numpy
    • Pandas
  • Data Visualization
    • Matplotlib
      • Simple drawing
      • Simple line and point
      • Any line and label
      • Annotation in reality
  • Dataset Searching
  • Keras
    • Data preparation
    • Build the simplest model
  • Robot
    • Speech to Text
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  1. Data Manipulation

Numpy

Numpy is a short name of number of python

numpy is a python library for number processing.

import numpy as np

py_list to np_array np.array(a_list)

np_array to py_list np_array.tolist()

creat a numpy array

>>> np.arange(3)
array([0, 1, 2])
>>> np.arange(3, step=0.1)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2,
       1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. , 2.1, 2.2, 2.3, 2.4, 2.5,
       2.6, 2.7, 2.8, 2.9])
>>> np.arange(1,3, step=0.5)
array([1. , 1.5, 2. , 2.5])

use np_array as list

for i in np_array:
   print(i)

get np_array index by value

index_list = np.where(np_array == some_value)[0]
print(index_list)

get np_array values by index_list

value_list = np_array[index_list]
print(value_list)

Just remember, any list you put in numpy function, it will automatically converted to np_array.

Don't put different size sub-list into one single numpy array, for example, np.array([1, [20, 30]]) is bad, but np.array([1, 20, 30]) is good. np.array([[1,2], [3,4]]) is also ok.

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Last updated 2 years ago

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