Introduction to Python Pandas for Data Analytics

115 Pages·2016·1.31 MB·English

by  Srijith Rajamohan

Introduction
toPython
Pandasfor
Data
Analytics
Srijith Introduction to Python Pandas for Data
Rajamohan
Analytics
Introduction
toPython
Python
programming
Srijith Rajamohan
NumPy
Matplotlib
AdvancedResearchComputing,VirginiaTech
Introduction
toPandas
Casestudy Tuesday 19th July, 2016
Conclusion
1/115
Course Contents
Introduction
toPython
Pandasfor
Data
Analytics This week:
Srijith
Rajamohan Introduction to Python
•
Python Programming
Introduction
toPython •
NumPy
Python •
programming
Plotting with Matplotlib
NumPy •
Introduction to Python Pandas
Matplotlib •
Introduction Case study
toPandas •
Conclusion
Casestudy
•
Conclusion
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Section 1
Introduction
toPython
PanDdaatsafor 1 Introduction to Python
Analytics
Srijith 2 Python programming
Rajamohan
Introduction 3 NumPy
toPython
Python
programming 4 Matplotlib
NumPy
Matplotlib 5 Introduction to Pandas
Introduction
toPandas
6 Case study
Casestudy
Conclusion
7 Conclusion
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Python Features
Introduction
toPython
Pandasfor
Data
Analytics
Srijith Why Python ?
Rajamohan
Interpreted
Introduction •
toPython Intuitive and minimalistic code
Python •
programming Expressive language
•
NumPy
Dynamically typed
Matplotlib •
Automatic memory management
Introduction
•
toPandas
Casestudy
Conclusion
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Python Features
Introduction
toPython
Pandasfor
Data Advantages
Analytics
Ease of programming
Srijith
Rajamohan •
Minimizes the time to develop and maintain code
•
Introduction
toPython Modular and object-oriented
•
Python Large community of users
programming •
NumPy A large standard and user-contributed library
•
Matplotlib
Disadvantages
Introduction
toPandas
Interpreted and therefore slower than compiled languages
Casestudy •
Decentralized with packages
Conclusion
•
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Code Performance vs Development Time
Introduction
toPython
Pandasfor
Data
Analytics
Srijith
Rajamohan
Introduction
toPython
Python
programming
NumPy
Matplotlib
Introduction
toPandas
Casestudy
Conclusion
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Versions of Python
Introduction
toPython
Pandasfor
Data
Analytics
Two versions of Python in use - Python 2 and Python 3
Srijith •
Rajamohan
Python 3 not backward-compatible with Python 2
•
Introduction A lot of packages are available for Python 2
toPython •
Python Check version using the following command
programming •
NumPy
Example
Matplotlib
Introduction
toPandas $ python --version
Casestudy
Conclusion
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Section 2
Introduction
toPython
PanDdaatsafor 1 Introduction to Python
Analytics
Srijith 2 Python programming
Rajamohan
Introduction 3 NumPy
toPython
Python
programming 4 Matplotlib
NumPy
Matplotlib 5 Introduction to Pandas
Introduction
toPandas
6 Case study
Casestudy
Conclusion
7 Conclusion
8/115
Variables
Introduction
toPython
Pandasfor
Data
Analytics Variable names can contain alphanumerical characters and
•
Srijith some special characters
Rajamohan
It is common to have variable names start with a
•
Introduction lower-case letter and class names start with a capital letter
toPython
Python Some keywords are reserved such as ‘and’, ‘assert’,
programming •
‘break’, ‘lambda’. A list of keywords are located at
NumPy
https://docs.python.org/2.5/ref/keywords.html
Matplotlib
Introduction Python is dynamically typed, the type of the variable is
toPandas •
derived from the value it is assigned.
Casestudy
A variable is assigned using the ‘=’ operator
Conclusion
•
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Variable types
Introduction
toPython
Pandasfor
Data
Analytics Variable types
•
Srijith • Integer (int)
Rajamohan
• Float (float)
Introduction • Boolean (bool)
toPython
• Complex (complex)
Python • String (str)
programming
• ...
NumPy
• User Defined! (classes)
Matplotlib
Documentation
Introduction
toPandas •
• https://docs.python.org/2/library/types.html
Casestudy
• https://docs.python.org/2/library/datatypes.html
Conclusion
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