Introduction to Python for statistics,analysis Note 3

First, generating arrays and matrices

1, Linspace (start,end,number), generates number between start and end number

>>> x = Linspace (0)>>>01  23456789.])

2, Logspace (start,end,number) produces numbers, between 10**start,10**end, the equivalent of an exponential function, the x-axis is divided into number of numbers, to calculate the exponent.

Same as 10**linspace (start,end,number) effect

3, Arange (l,u, s)

4,Meshgrid ()

>>> x = Arange (5)>>> y = arange (3)>>> x, y =Meshgrid (x, y)>>>Xarray ([[0,1,2,3,4],[0,1,2,3,4],[0,1,2,3,4]])>>>Yarray ([[0,0,0,0,0],[1,1,1,1,1],[2,2,2,2,2]])

5, Ix_ (a,b) Irregular selection of elements, where a, a can be a list or a tuple

>>> x = Reshape (Arange (25.0),(5,5))>>>Xarray ([[0.,1.,2.,3.,4.],[ 5.,6.,7.,8.,9.],[ Ten., One., A., -., -.],[  the., -., -., -., +.],[  -., +., A., at., -.]])>>> X[ix_ ([2,3],[0,1,2])] # Rows2&3, cols0,1and2Array ([[Ten., One., A.],[  the., -., -.]])>>> x[2:4,:3] # Same, Standard Slicearray ([[Ten., One., A.],[  the., -., -.]])>>> X[ix_ ([0,3],[0,1,4])] # No Slice equiv

Second, approximate

1,around, round

x=NP.  Random. Randn (3)   

X

Np. Around (x) 

Np. Around (x,2) #近似精度为2位小数 

[0.23073931  1.08865135-0.95564268][0.  1.-1.] [0.23  1.09-0.96]

2, floor (x), Ceil (x),

III. Statistical characteristics

1/sum, calculation and

A=np.reshape (Np.arange (Ten),(2,5));p rint A,'\ n'print Np.sum (a),'\ n'Print Np.sum (A,0),'\ n'Print Np.sum (A,1)[[0 1 2 3 4] [5 6 7 8 9]]  $ [ 5  7  9  One  -] [Ten  *]

2/prod the same characteristics as SUM, he is the product of the calculation

A=np.reshape (Np.arange (1,5),(2,2));p rint A,'\ n'? Print Np.prod (a),'\ n'Print Np.prod (A,0),'\ n'Print Np.prod (A,1),'\ n'[[1 2] [3 4]]  - [3 8] [ 2  A]

3,exp,log--equivalent to ln (),log10,sqrt,Square,absolute, ABS, Sign is the manipulation of elements

A=NP.RANDOM.RANDN (2,3);p rint A,'\ n'print Np.abs (a) print np.sign (a)
[[-0.35632202-0.56913468-0.5054189 ] [-0.13182024  1.62914028  1.57704769]] [[ 0.35632202  0.56913468  0.5054189 ] [ 0.13182024  1.62914028  1.57704769]][[-1. -1. -1.] [-1.1.1.]]

4, for the operation of complex numbers, the following operations are also the operation of the elements

• Real (a) or a.real, the real part of the plural
• Imag (A) or a.imag, imaginary part of a complex number
• Conj (A) , conjugate, conjugate plural

5,Unique (A) is the operation of all elements, equivalent to the Python set (), the effect of the redo

6, in1d (A, B)

>>> x = arange (10.0)>>> y = arange (5.0,15.0) >>> in1d (x, y) array ([False, False, False, False, False, True, True, True, true, True], Dtype =
   
    bool)
   

7,union1d (A, B), returns the unique set of elements in 2 arrays. Equivalent set merge

8,intersect1d (A, B) is equivalent to the collection of the pickup

9,setdiff1d (b), in set A, not in set B

10,setxor1d (A, B), equivalent to take a set XOR, only in a set of elements

11. Sort

A=NP.RANDOM.RANDN (2,3);p rint aprint Np.sort (A,1) Print Np.sort (A,0) Print Np.sort (A,none) [[2.33262004-2.17579511  1.02508041] [-0.11651321  1.02673882  1.25183328]][[-2.17579511  1.02508041  2.33262004] [-0.11651321  1.02673882  1.25183328]][[-0.11651321-2.17579511  1.02508041] [ 2.33262004  1.02673882  1.25183328]][-2.17579511-0.11651321  1.02508041  1.02673882  1.25183328  2.33262004]

Note: The difference between a.sort () and sort (a), one will change the data structure, one will not.

>>> x = Randn (3)>>>Xarray ([2.70362768, -0.80380223, -0.10376901])>>>sort (x) array ([-0.80380223, -0.10376901,2.70362768])>>>Xarray ([2.70362768, -0.80380223, -0.10376901])>>> X.sort () # in-Place , changes x>>>Xarray ([-0.80380223, -0.10376901,2.70362768])

12,Max, amax, argmax , min, Amin , Argmin

Max is the method of the array, Amax is the function, Argtmax returns

A=NP.RANDOM.RANDN (3,5);p rint aprint Np.amax (A,1) Print Np.amax (A,0) Print Np.amax (A,none) [[-1.20363617e-01   6.09840964e-01-2.42821192e-01-1.87136859e+00-9.24036132e-01] [ -2.12137767e-04-4.49847000e-01   6.05104140e-02   5.00253683e-01    1.63359279e+00] [ -3.41458128e-01-9.52592527e-01   8.66845911e-01-1.26919405e+00    1.67080515e+00]][ 0.60984096  1.63359279  1.67080515][ -2.12137767e-04   6.09840964e-01   8.66845911e-01   5.00253683e-01   1.67080515e+00]1.67080515388

13,minimum (a , b), maximum (A, B) compares two arrays, returns the smallest or largest number in the corresponding position of two arrays

Introduction to Python for statistics,analysis Note 3