This document provides an overview of a Python for Data Science course taught by Dr. Nisha Arora. The course covers Python basics, data structures, libraries for data science like NumPy, Pandas, Matplotlib and Scikit-learn. It includes lessons on data analysis and processing in Pandas, data visualization, coding best practices, and tips/tricks. The course materials will include presentations, code files, data files, use cases, recommended readings and bonus introductory videos on installing Python and getting started with Jupyter notebooks.

1. Help me understand your requirement
✓ Your Background
✓ Objective
✓ Expectation from the course
✓ Anything Else?

2. PYTHON FOR
DATA SCIENCE
- Dr Nisha Arora

3. Dr. Nisha Arora is a proficient educator, passionate
trainer, You Tuber, occasional writer, and a learner
forever.
✓ PhD in Mathematics.
✓ Works in the area of Data Science, Statistical
Research, Data Visualization & Storytelling
✓ Creator of various courses
✓ Contributor to various research communities and
Q/A forums
✓ Mentor for women in Tech Global
4
About Me
An educator by heart & a
trainer by profession.

4. ✓ In-depth Technical Answers
✓ Coding Queries
✓ Layman’s Term Explanation
✓ Research Queries
✓ Blog Posts
✓ Slide Decks
✓ Publications
✓ Tutorials /My Talks
✓ Mentoring
✓ Articles & Much More
My Contribution to the Community

5. Data Science Job Roles
✓ Product Owner
✓ Data Engineer
✓ Data Analysts
✓ Data Scientist/ ML Engineer
✓ Visualization Expert/ Storyteller
✓ Software Engineer
✓ Domain Expert
✓ Operations Team

6. Required Technical Skills
Data Analysts Data Scientists Data Engineer
Excel
Statistical Analysis Python/ R
Databases Data Viz & Storytelling
SQL/ Databases
R/Python/SAS EDA/Data Wrangling/Data Prep Data Warehousing/Data Architecture
Tableau/PowerBI Machine Learning/Deep Learning
Distributed Computing (Hadoop/Map
Reduce)
Statistical Analysis SQL Data Management & Data Security
Data Viz & Storytelling R, Python, SAS (sometimes)
Docker, Kubernaties, Kafka, Spark, Git
GitHub
EDA/Data Wrangling/Data Prep Tensorflow, Keras Cloud Tech (AWS/Azure/GCP)
Dashboards & Reporting Git/ GitHub Big Data Services
11
Soft Skills
Domain Knowledge

7. Top companies using Python
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8. Python is used for
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❑ Web development
❑ Desktop Application
❑ IOT Programming
❑ Data Science & Analytics
❑ Game development

9. Popularity of Python
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https://insights.stackoverflow.com/trends?tags=python

10. Python for Data Science
15
Coding Best
Practices
Tips & Tricks
✓ Programming Basics
✓ Data Science/ML Concepts
✓ Libraries for Data Science/ML
✓ Projects

11. Agenda
1. Getting started with Google Colab for
Python
2. Python Basics
3. Data Structure in Python
4. Numpy, Pandas, Matplotlib, Seaborn, Scikit-
learn
5. Data Analysis & Processing in Pandas
6. Data Visualization & Storytelling with Python
Bonus for Python Beginners
1. Downloading & Installing Python
2. Selecting the IDE
3. Python files (.py files) Vs ipython
notebooks (.ipynb files)
4. Getting started with Jupyter &
Jupyter Labs
5. Setting-up start-up folder in Jupyter
6. Getting started with Spyder
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12. What will you get?
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✓ Presentations
✓ Quick Summary of each lesson
✓ Code Files
✓ Data Files
✓ Use-cases
✓ Web-resources
✓ Recommended Readings
✓ Tips & Tricks
✓ Bonus Videos

14. Data Types in Python
Numbers – int, float, complex
Strings
Boolean
Object
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15. Data Types in Python
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16. Operators in Python
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17. Mathematical Operators
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18. Comparison Operators
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19. Boolean/Logical Operators
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20. Strings in Python
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21. Strings
Strings in Python are immutable, iterable and ordered.
which means
- we can not updates or delete values from a string
- we can iterate over elements of a string
- we can perform indexing & slicing over a string
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22. Escape Sequence
Escape character ``
Escaping allows the normal interpretation of the character to be suspended and that string to be
defined as normal.
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23. String Methods
Check with dir(str)
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24. String Slicing
1. Indexing/counting starts with 0. First character gets counted as zero
2. `[a:b]` means starting at ath position and extracting until (b-1)th position
3. `[a:]` means starting at ath position till end
4. `[:a]` means starting at the beginning until (a-1)th position
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25. String Slicing
5. negative sign with indices mean counting from right instead of natural left.
6. `[:-a]` means starting at the beginning and going up til ath position from end. Counting from end also starts
with 0.
7. `[-a:]` means starting at (a+1)th character from the end and going up till last character.
8. `[a:-b]` means starting at ath character at the beginning and going till bth position from end
9. `[-a:-b]` means starting at (a+1)th character from the end and going up till bth position from end
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26. String Slicing _ stride
The optional, third number in a slice specifies the stride.
If omitted, the default is 1: return every character in the requested range
To return every kth letter, set the stride to k.
Negative values of k reverse the string.
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