Python is a popular programming language for data science. The document discusses how Python and its tools like Pandas, Scikit-learn, and MLflow can be used for data analysis, machine learning, and big data processing. It also provides an overview of data science concepts and the Python tools and libraries commonly used by data scientists in their work.

1. PYTHON IN DATA SCIENCE WORK
RICK BAHAGUE, DATA SCIENTIST
RBAHAGUEJR@GMAIL.COM

2. Our Agenda
What is Data Science?
Introduction to Python
Python Tools for Data Science
A bit of Python for Big Data Processing
Questions

3. Data Science
Source: Python Data Analytics

4. Data Scientist asks relevant
real world questions
Source: http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
And hopefully,
discovers
actionable
recommendations
from data

5. TOOLS

6. WHAT IS
PYTHON?
“THE NAME PYTHON COMES
FROM THE SURREAL BRITISH
COMEDY GROUP MONTY PYTHON,
NOT FROM THE SNAKE. PYTHON
PROGRAMMERS ARE
AFFECTIONATELY CALLED
PYTHONISTAS, AND BOTH MONTY
PYTHON AND SERPENTINE
REFERENCES USUALLY PEPPER
PYTHON TUTORIALS AND
DOCUMENTATION.”
Automate the Boring Stuff with Python

7. import antigravity

8. Installing Python
https://www.continuum.io/downloads

9. Launching Anaconda Python
Distribution

10. When is data ready and
prepared for analysis ?
Image source: http://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/

11. Github: https://github.com/RickBahague/dspop

12. Sample Data Set:
Github: https://github.com/veekun/
pokedex

13. Pandas: Python Data Analysis
Library
Import pandas library
Reading/Writing Data
Series
DataFrame
Selecting Internal Elements
Assigning Values to Elements

14. Pandas: Python Data Analysis
Library
Evaluating Values (unique, isin, value_counts,
NaN)
Filtering Values
Transpose
Operations between DataFrame and Series
Statistics Functions, Correlation/Covariance

15. Scikit-learn & ML Basics
... learning from experience either
with or without supervision of
humans
Mastering Machine Learning with scikit-learn

16. ML Flow
Image source: http://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/

17. Machine Learning with
Scikit-learn
Source: http://scikit-learn.org/stable/

18. A bit of Big Data Processing
Source: Python Data Analytics

19. Creative Commons License
Python in Data Science Work by Rick
Bahague is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike 4.0
International License.
Based on a work at https://medium.com/
@rbahaguejr.
Permissions beyond the scope of this license
may be available at https://medium.com/
@rbahaguejr.