(Python Example for Beginners)
Write a Pandas program to compare the elements of the two Pandas Series.
Sample Series: [2, 4, 6, 8, 10], [1, 3, 5, 7, 10]
Python Code :
import pandas as pd ds1 = pd.Series([2, 4, 6, 8, 10]) ds2 = pd.Series([1, 3, 5, 7, 10]) print("Series1:") print(ds1) print("Series2:") print(ds2) print("Compare the elements of the said Series:") print("Equals:") print(ds1 == ds2) print("Greater than:") print(ds1 > ds2) print("Less than:") print(ds1 < ds2)
Series1: 0 2 1 4 2 6 3 8 4 10 dtype: int64 Series2: 0 1 1 3 2 5 3 7 4 10 dtype: int64 Compare the elements of the said Series: Equals: 0 False 1 False 2 False 3 False 4 True dtype: bool Greater than: 0 True 1 True 2 True 3 True 4 False dtype: bool Less than: 0 False 1 False 2 False 3 False 4 False dtype: bool
Pandas Example – Write a Pandas program to compare the elements of the two Pandas Series
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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