{"id":25854,"date":"2021-12-16T09:19:39","date_gmt":"2021-12-16T03:49:39","guid":{"rendered":"https:\/\/python-programs.com\/?p=25854"},"modified":"2021-12-16T09:19:39","modified_gmt":"2021-12-16T03:49:39","slug":"python-program-for-numpy-average-function","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-program-for-numpy-average-function\/","title":{"rendered":"Python Program for Numpy average() Function"},"content":{"rendered":"

Those people with a statistical background are highly familiar with the phrase “average.” Data Science and AI practitioners, whether deliberately or unknowingly, use this word in preprocessing procedures.<\/p>\n

Numpy average() Function:<\/strong><\/p>\n

In general statistics, the average is defined as the sum of all numbers divided by the sum of their totals. The major purpose of this effort is to assist us to grasp the fundamental value contained inside the dataset.<\/p>\n

For Example:\u00a0<\/strong><\/p>\n

Let us consider the marks obtained by the 5 students out of 100.<\/p>\n

s1 = 80,<\/p>\n

s2 = 95<\/p>\n

s3 = 35<\/p>\n

s4 = 65<\/p>\n

s5 = 70<\/p>\n

The average of their marks = (80+95+35+65+70)\/5 = 345\/5 = 69.<\/p>\n

Formula:<\/strong><\/p>\n

Average = sum of all Frequencies\/ No. of Frequencies<\/strong><\/p>\n

Where Frequencies = values given in the dataset<\/p>\n

We learned about the key benefit from the preceding example. The best value is required for the calculation of many parameters. In the actual world, the mean can be used in a variety of contexts.<\/p>\n