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numpy.arange() in Python
  • Difficulty Level : Medium
  • Last Updated : 19 Apr, 2020

About :
arange([start,] stop[, step,][, dtype]) : Returns an array with evenly spaced elements as per the interval. The interval mentioned is half opened i.e. [Start, Stop)
Parameters :

start : [optional] start of interval range. By default start = 0
stop  : end of interval range
step  : [optional] step size of interval. By default step size = 1,  
For any output out, this is the distance between two adjacent values, out[i+1] - out[i]. 
dtype : type of output array

Return:

Array of evenly spaced values.
Length of array being generated  = Ceil((Stop - Start) / Step)




# Python Programming illustrating
# numpy.arange method
  
import numpy as geek
  
print("A\n", geek.arange(4).reshape(2, 2), "\n")
  
print("A\n", geek.arange(4, 10), "\n")
  
print("A\n", geek.arange(4, 20, 3), "\n")


Output :

A
 [[0 1]
 [2 3]]

A
 [4 5 6 7 8 9]

A
 [ 4  7 10 13 16 19]

Note 1:
These NumPy-Python programs won’t run on onlineID, so run them on your systems to explore them.

Note 2:
The advantage of numpy.arange() over the normal in-built range() function is that it allows us to generate sequences of numbers that are not integers. For example






# Python Programming illustrating
# numpy.arange method
  
import numpy as np
  
# Printing all numbers from 1 to 2 in steps of 0.1
print(np.arange(1, 2, 0.1))


Output:

[1.  1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9]

If you try it with the range() function, you get a TypeError.

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