དཔལ་ལྡན་འབྲུག་གཞུང་། ཤེས་རིག་དང་རིག་རྩལ་གོང་འཕེལ་ལྷན་ཁག།

Department of School Education

Ministry of Education & Skills Development

Online Training for ICT Teachers

28 February 2023

Classes XI & XII ICT Curriculum

Data Science SESSION II

Data Science Part II

Presentation Outline

ICT Curriculum

Objectives

• Import Pandas lib
• Explain structure of a DataFrame
• Clean the dataset
• Filter the dataset
• Generate statistical analysis

Content Scope

• Introduction to Pandas
• Series & DataFrame
• Data Analysing Methods
• Data Referencing & Cleaning Methods
• Statistical Data Analysing Methods

Career Opportunities

• Data Analyst/freelance
• Data Engineer/Scientist
• In Bhutan too, people with data analysis skills are hired by large companies (consultant).

Introduction to Pandas

Why?

• Read external data

• Data Cleaning

• Data Extraction

• Data Preparation for ML

Python Data Analysis Library

NumPy Vs Pandas

Getting Started with Pandas

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Video Link

Pandas can be installed using the Python package manager pip

Pandas Series

Sample

Output

Problem

Write a python program to display at least 4 names of your family members or friends.

Python Code

Pandas DataFrame

Python� Code

Problem

Write a python program to display the population data of any five Dzongkhags. Include following information:

• Dzongkhag
• Population
• Area

Sample Output

Series and DataFrame

Datasets of Pandas are either stored as Series or DataFrame

Data Analysing Methods

info() → Displays a summary of the DataFrame

max() → Returns the maximum value

min() → Returns the minimum value

sort() → Returns the sorted DataFrame

describe() → Returns basic statistics for the numerical columns in the DataFrame

head() → Returns the first five rows of the DataFrame

head(N) → Returns the first N rows of the DataFrame

tail() → Returns the last five rows of the DataFrame

tail(N) → Returns the last N rows of the DataFrame

Data Analysing Methods (Activity 1)

Problem Statement

Write a python program to:

• sort the data in descending order based on the Total column.
• display data of top 10 countries.
• display data of the bottom 5 countries.

Link to csv file

Sample Output

Data Analysing Methods (Activity 1)

Python Code

Data Referencing & Cleaning Methods

shape() → Returns the number of rows and columns

notna() → Select non-null values

dropna() → Removes rows or columns with missing data

fillna() → Fills missing values with a specified value

isin() → Filter data based on elements

loc() → Access a group of rows and columns by labels

iloc() → Access a group of rows and columns by integer position

Data Referencing & Cleaning Methods (Activity 2)

Problem Statement

Write a python program using Pandas to collect all data with non-empty values under the ‘Calories’ column.

• List the information of maximum calories burnt (consider 350 & above).
• Display the dates only, when maximum calories were burnt.

Link to csv file

Sample Output

Statistical Data Analysing Methods

sum() → Returns the sum of the values in a column or row

mean() → Returns the average of the values in a column or row

median() → Returns the median value of the values in a column or row

mode() → Returns the mode (most common value) of the values in a column or row

std() → Returns the standard deviation of the values in a column or row

corr() → Returns the correlation coefficients between values in a column or row

Statistical Data Analysing Methods (Activity 3)

Problem Statement

Write a python program to:

• Find the total number of students in a column called ‘Total_Appeared’ to calculate how many appeared in each subject by adding ‘Female’ and ‘Male’ columns.
• Find the total number of papers written by students.
• Find the average of all the numeric data ('CA Pass' till 'Total_Appeared' column).

Link to csv file.

Sample Output

Pandas in Summary

Wes McKinney

(Twitter Photo)

Powerful and open-source library for data manipulation and data analysis in Python

Pandas Resources

GitHub Repository

YouTube Video

Pandas Official Site

Pandas Activity Book →