numpy.arange() in Python
The 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)
Example:
Python3
# 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:
- These NumPy-Python programs won’t run on onlineID, so run them on your systems to explore them.
- 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.
Example:
Python3
# 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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