When analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. This adjustment can be done by normalizing to values between 0 and 1, or throwing away outliers. For this program, read in a list of floats and adjust their values by dividing all values by the largest value. Output each value with two digits after the decimal point. Follow each number output by a space. Ex: If the input is: 30.0 50.0 10.0 100.0 65.0 the output is: 0.30 0.50 0.10 1.00 0.65 python please: also input is a list of numbers not individual inputs for the assignment
When analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. This adjustment can be done by normalizing to values between 0 and 1, or throwing away outliers. For this program, read in a list of floats and adjust their values by dividing all values by the largest value. Output each value with two digits after the decimal point. Follow each number output by a space. Ex: If the input is: 30.0 50.0 10.0 100.0 65.0 the output is: 0.30 0.50 0.10 1.00 0.65 python please: also input is a list of numbers not individual inputs for the assignment
C++ Programming: From Problem Analysis to Program Design
8th Edition
ISBN:9781337102087
Author:D. S. Malik
Publisher:D. S. Malik
Chapter8: Arrays And Strings
Section: Chapter Questions
Problem 20PE
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When analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. This adjustment can be done by normalizing to values between 0 and 1, or throwing away outliers.
For this program, read in a list of floats and adjust their values by dividing all values by the largest value. Output each value with two digits after the decimal point. Follow each number output by a space.
Ex: If the input is:
30.0 50.0 10.0 100.0 65.0
the output is:
0.30 0.50 0.10 1.00 0.65
python please: also input is a list of numbers not individual inputs for the assignment
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