Python3 Data Analysis 3rd day

Getting started with NumPy

1 sum can be used to count ture of Boolean values

2 Any to test whether the presence of true all in the array is true

3 sort

NumPy arrays can be sorted by sort

4 unique can find a value that does not duplicate

5 np.in1d is used to test the membership of a value in one array in another array, and returns a Boolean array

6 7 NumPy can read or write text data or binary data on a disk

8 Np.save and Np.load are the two main functions for reading and writing disk array data

9 Np.savez can save multiple arrays to a sub-lasso file and pass the array in as a keyword parameter

Also, when loading, the various arrays are deferred loading
Accessing text files

1 mainly for pandas read_csv read_table or Np.loadtxt or np.genfromtxt

CSV file comma split file
2 linear algebra

dot function for matrix multiplication

3 Numpy.linalg has a set of standard matrix decomposition operations and so on, such as reverse-column

Common functions

Random number

1 Numpy.random Module

2 normal function Generation standard is too distributed

Note xrange usage is exactly the same as range, but instead of generating a list object, it is a generator.

1 Argmax Returns the index of the first maximum value of a Boolean array