Write a Python function which accepts DataFrame Age, Salary columns second, third and fourth rows as input and find the mean, product of values

PythonPandasServer Side ProgrammingProgramming

Input

Assume, sample DataFrame is,

 Id Age  salary
0 1 27   40000
1 2 22   25000
2 3 25   40000
3 4 23   35000
4 5 24   30000
5 6 32   30000
6 7 30   50000
7 8 28   20000
8 9 29   32000
9 10 27  23000

Output

Result for mean and product of given slicing rows are,

mean is
Age          23.333333
salary    33333.333333
product is
Age                12650
salary    35000000000000

Solution

To solve this, we will follow the below approaches.

  • Define a DataFrame

  • Create a function, slice second, third, and fourth rows of age and salary columns using iloc function and store it in result DataFrame.

df.iloc[1:4,1:]
  • Calculate the mean and product from the result DataFrame.

Example

Let us see the following implementation to get a better understanding.

import pandas as pd
def find_mean_prod():
   data = [[1,27,40000],[2,22,25000],[3,25,40000],[4,23,35000],[5,24,30000], [6,32,30000],[7,30,50000],[8,28,20000],[9,29,32000],[10,27,23000]]
   df = pd.DataFrame(data,columns=('Id','Age','salary'))
   print(df)
   print("slicing second,third and fourth rows of age and salary columns\n")
   result = df.iloc[1:4,1:]
   print("mean is\n", result.mean())
   print("product is\n", result.prod())
find_mean_prod()

Output

 Id Age  salary
0 1 27   40000
1 2 22   25000
2 3 25   40000
3 4 23   35000
4 5 24   30000
5 6 32   30000
6 7 30   50000
7 8 28   20000
8 9 29   32000
9 10 27  23000
slicing second,third and fourth rows of age and salary columns
mean is
Age          23.333333
salary    33333.333333
product is
Age                12650
salary    35000000000000
raja
Updated on 24-Feb-2021 07:19:56

Advertisements