Data Analysis Fundamentals:
Numpy + Pandas
A Hackerschool X SDS Collaboration
NUS Hackers x NUS Statistics & Data Science Society
Workshop | Date |
Introduction to Python | 22 Aug |
Automation with Python | 28 Aug |
Data Analysis Fundamentals: Numpy + Pandas | 11 Sep |
Data Visualisation with Python + Tableau | 18 Sep |
Bharath Shankar
Javier Tham
Keith Lim
About us
Y2 Data Science & Analytics
Y2 Business Analytics
Y2 Data Science & Analytics
OBJECTIVES
Numpy
Pandas
01
02
What’s Next
03
And its applications
And its applications
Keeping in touch with us
Slides and solutions
will be shared!
Colab
Do make a copy!
Q&A
Ask your questions at slido here!
https://www.sli.do/
# 271247
Numpy
01
And its applications
Numpy
An alternative for lists and arrays in Python�Consists of functions like copies, view, and indexing that helps in saving a lot of memory
Use multi-dimensional arrays�Create vectors and matrices with ndarray
Use mathematical operations�Linear algebra, bitwise operations, Fourier transform, arithmetic operations, string operations
Speed improvements�All operations implemented using arrays exploit broadcasting, and thus, benefit from the speed gains
An invaluable tool for scientific computing�Serves as foundation for many other packages, such as pandas, scipy, sklearn, and many, many others
Pandas
02
And its applications
Pandas
What’s Next
03
Keeping in touch with us
PYTHON FOR DATA SCIENCE
Data Visualisation with Python and Tableau (18 Sep)
Links for workshop materials
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