Using Python data to analyze-numpy and pands articles

The book "Data analysis using Python"

numpy--arrays and matrices, vector computing

　　1, Ndarray multidimensional arrays, matrix matrices

2, for the whole set of data for fast operation of the standard mathematical (statistical) function, (and list difference: no need to loop to write programs)

3. Tools for reading and writing disk data tools and operating memory mapping files

4. Linear algebra, random number generation and Fourier transform

5, based on the C language API, has a good operating rate

create function

Array	input data converted to Ndarray (dtype optional)
arrange	built-in range returns Ndarray
zeros/zeros_like	Returns a full 0 array, or a reference to other arrays of shape and Dtype, based on the specified shape and dtype
Eye	create n*n unit matrix
ones/ones_like	Returns a full 1 array, or a reference to other arrays of shape and Dtype, based on the specified shape and dtype
empty/empty_like	allocates only space but does not populate any values

basic functions

dtype	Data type Dtype (customizable type) Note: Complex complex must not be converted to integers
shape
reshape
Ravel
transpose/t	array transpose
stack/hstack/vstack/dstack/concatenate/
ix_	Select an indexer for a square area, a fancy index x[ix_ ([0,1],[0,1])]=x[[0,1]][:,[0,1]]

statistics function

Sqrt/square/lo G/sign
min/max/ptp/sum
mean/va R/STD
argmin/argmax	min Max index
any/all	Whether there is one or more true/arrays in the array that are all true
average
m Edian
sort
in1d	test If the value in one array is in the membership of another array, returns the bool array
unique/intersect1d/union1d/setdiff1d/setxor1d

file input and OUTPUT functions

Loadtxt/savetxt
Save/load	Saves the array as a binary format disk or read (NPY)
Savez	Save multiple arrays to a compressed file

Linear algebraic functions (LINALG)

Dot	Matrix Inner Product XTX
Qr	QR decomposition
Inv	Inverse matrix
Svd	Singular decomposition SVD
Eig	Eigenvalues and eigenvectors
Det	Matrix determinant

Random number function (randomness)

Normal (SHAPE)	Normal distribution array with shape specification
Randint/rand/randn
Seed

Note: Operations between different shape arrays are called broadcasts

pands--builds on NumPy, providing advanced data structures and operational tools

Using Python data to analyze-numpy and pands articles