NumPy: Create an array with 10^3 elements

Last update on March 24 2025 13:39:30 (UTC/GMT +8 hours)

Create Array with 10^3 Elements

Write a NumPy program to create an array with 10^3 elements.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating an array 'x' using NumPy's arange function to generate numbers from 0 to 999 (inclusive)
x = np.arange(1e3)

# Printing the array 'x' containing numbers from 0 to 999
print(x) 

Sample Output:

[   0.    1.    2.    3.    4.    5.    6.    7.    8.    9.   10.   11
.                                                                      
   12.   13.   14.   15.   16.   17.   18.   19.   20.   21.   22.   23
.                                                                      
   24.   25.   26.   27.   28.   29.   30.   31.   32.   33.   34.   35
.                                                                      
   36.   37.   38.   39.   40.   41.   42.   43.   44.   45.   46.   47
.                                                                      
   48.   49.   50.   51.   52.   53.   54.   55.   56.   57.   58.   59
.                                                                      
   60.   61.   62.   63.   64.   65.   66.   67.   68.   69.   70.   71
.                                                                      
   72.   73.   74.   75.   76.   77.   78.   79.   80.   81.   82.   83
.                                                                      
   84.   85.   86.   87.   88.   89.   90.   91.   92.   93.   94.   95                                                                      
..............................

  900.  901.  902.  903.  904.  905.  906.  907.  908.  909.  910.  911
.                                                                      
  912.  913.  914.  915.  916.  917.  918.  919.  920.  921.  922.  923
.                                                                      
  924.  925.  926.  927.  928.  929.  930.  931.  932.  933.  934.  935
.                                                                      
  936.  937.  938.  939.  940.  941.  942.  943.  944.  945.  946.  947
.                                                                      
  948.  949.  950.  951.  952.  953.  954.  955.  956.  957.  958.  959
.                                                                      
  960.  961.  962.  963.  964.  965.  966.  967.  968.  969.  970.  971
.                                                                      
  972.  973.  974.  975.  976.  977.  978.  979.  980.  981.  982.  983
.                                                                      
  984.  985.  986.  987.  988.  989.  990.  991.  992.  993.  994.  995
.                                                                      
  996.  997.  998.  999.]   

Explanation:

The above code creates and prints a NumPy array with 1000 elements, ranging from 0 to 999.

x = np.arange(1e3): This line creates a 1D NumPy array with elements from 0 to 999 (1e3 is scientific notation for 1000). The np.arange() function generates an array of evenly spaced values within the specified range.

print(x): This line prints the created NumPy array ‘x’ containing the values from 0 to 999.

For more Practice: Solve these Related Problems:

• Write a NumPy program to generate an array with 10³ sequential elements using np.arange and validate its length.
• Create an array with 1000 elements and verify the first and last values using indexing.
• Implement a function that dynamically creates large arrays and measures the time taken for creation.
• Test array generation with different powers of ten and compare their memory usage using the nbytes attribute.

Python-Numpy Code Editor: