Machine Learning | Apply Built-in functions on the pandas Dataframe | Sum | Max | Min | Count - P4

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Machine Learning | Apply Built-in functions on the pandas Dataframe | Sum | Max | Min | Count - P4
Topics to be covered :
1. How to find the Sum, Count, Max, Min and Average.
2. How to find the unique values and its count.

import pandas as pd
import numpy as np

Get the Maximum value of the column Age
print('Maximum value of column Age: ', dataset['Age'].max())

Get the Minimum value of the column Age
print('Minimum value of column Age: ', dataset['Age'].min())

Find the sum of the rows in the columns Age
print('Sum of the rows in the column Age:', dataset['Age'].sum())

Get the count of the number of rows in column Age
print('Count of the no of vlaues in the column Age :', dataset['Age'].count())

Get the Average/mean of the column Age
print('The Average age is :', dataset['Age'].mean())

NaN - No a Number

How to find the unique values and its count
dataset['Age'].count()

dataset['Sex'].count()

dataset['Sex'].unique()

dataset['Sex'].value_counts()

All Playlist of this youtube channel
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1. Data Preprocessing in Machine Learning

2. Confusion Matrix in Machine Learning, ML, AI

3. Anaconda, Python Installation, Spyder, Jupyter Notebook, PyCharm, Graphviz

4. Cross Validation, Sampling, train test split in Machine Learning

5. Drop and Delete Operations in Python Pandas

6. Matrices and Vectors with python

7. Detect Outliers in Machine Learning

8. TimeSeries preprocessing in Machine Learning

9. Handling Missing Values in Machine Learning

10. Dummy Encoding Encoding in Machine Learning

11. Data Visualisation with Python, Seaborn, Matplotlib

12. Feature Scaling in Machine Learning

13. Python 3 basics for Beginner

14. Statistics with Python

15. Sklearn Scikit Learn Machine Learning

16. Python Pandas Dataframe Operations

17. Linear Regression, Supervised Machine Learning

18 Interiew Questions

19. Jupyter Notebook Operations