Introduction to Python Pandas for Data Analytics
Introduction to Python Pandas for
Data Analytics
Srijith Rajamohan
Introduction to Python
Python programming
NumPy
Matplotlib
Introduction to Pandas
Case study
Conclusion
Introduction to Python Pandas for Data Analytics
Srijith Rajamohan
Advanced Research Computing, Virginia Tech
Tuesday 19th July, 2016
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Course Contents
Introduction to Python Pandas for
Data Analytics
Srijith Rajamohan
Introduction to Python
Python programming
NumPy
Matplotlib
Introduction to Pandas
Case study
Conclusion
This week: ? Introduction to Python ? Python Programming ? NumPy ? Plotting with Matplotlib ? Introduction to Python Pandas ? Case study ? Conclusion
2 / 115
Section 1
Introduction to Python Pandas for
Data Analytics
Srijith Rajamohan
Introduction to Python
Python programming
NumPy
Matplotlib
Introduction to Pandas
Case study
Conclusion
1 Introduction to Python 2 Python programming 3 NumPy 4 Matplotlib 5 Introduction to Pandas 6 Case study 7 Conclusion
3 / 115
Python Features
Introduction to Python Pandas for
Data Analytics
Srijith Rajamohan
Introduction to Python
Python programming
NumPy
Matplotlib
Introduction to Pandas
Case study
Conclusion
Why Python ?
? Interpreted ? Intuitive and minimalistic code ? Expressive language ? Dynamically typed ? Automatic memory management
4 / 115
Python Features
Introduction to Python Pandas for
Data Analytics
Srijith Rajamohan
Introduction to Python
Python programming
NumPy
Matplotlib
Introduction to Pandas
Case study
Conclusion
Advantages ? Ease of programming ? Minimizes the time to develop and maintain code ? Modular and object-oriented ? Large community of users ? A large standard and user-contributed library
Disadvantages ? Interpreted and therefore slower than compiled languages ? Decentralized with packages
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