Data import and array transposition
(framme,dtype='dataType',delimmiter='delimiter',
skiprows=''(number of rows skipped'),
usecols=''Number of lines to be used',''
unpack='Ture/Flase(transpose or not)':Load text file data
Meaning of loadtxt parameter
- The numpy array transpose is done in 4 ways
- The value of the parameter unpack is set to TRUE.
- Transpose using the .T property of the array
- Transpose using the transpose() method of an array
- Using the swapaxes method with numpy arrays
Examples are as follows:
import numpy as np filepath = './' t1 = (filepath,usecols=(1,2,3),delimiter=',',dtype='float') print(t1) # Four ways to transpose # first method:Set the value of parameter "unpack" —— True t2 = (filepath,usecols=(1,2,3),delimiter=',',dtype='float',unpack=True) # second method: use the '.T' attributions of array's t3 = print(t3) # third method: use the method of 'transpose' t4 = () print(t4) # forth method: swapaxes(arguments：axes needed swapped) t5 = (0,1) print(t5)
Run results:
numpy array indexing and slicing
import numpy as np filename = './' t1 = (filename,delimiter=',',dtype='float',usecols=(1,2,3)) # print(t1) # Fetch line operations print(t1[0]) print(t1[0,:]) # Take multiple consecutive lines print(t1[3:]) print(t1[3:,:]) # Fetch discrete multiple lines print(t1[[1,3,13,19]]) print(t1[[1,2,4,6],:]) # Fetch column print(t1[:,0]) # Take consecutive columns print(t1[:,2:]) # Take discontinuous columns print(t1[:,[1,2]]) # Take rows 2-5, columns 2-3 # Fetch cross data from multiple locations print(t1[1:5,1:3]) # Fetch data information from non-adjacent locations print(t1[[1,4,6],[0,1,2]])
import numpy as np filepath = './' t1 = (filepath,delimiter=',',usecols=(1,2,3)) print(t1<9.5) t1[t1 < 9.5] = 0 print(t1[:,1]) # if-else operations (t1>=9.6,10,0) print(t1) # clip(m,n)Putting an array with less thanm's replacement withm,more thann's replacement withn
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