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Data Analysis Fundamentals:

Numpy + Pandas

A Hackerschool X SDS Collaboration

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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

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Bharath Shankar

Javier Tham

Keith Lim

About us

Y2 Data Science & Analytics

Y2 Business Analytics

Y2 Data Science & Analytics

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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!

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Colab

Do make a copy!

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Q&A

Ask your questions at slido here!

https://www.sli.do/

# 271247

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Numpy

01

And its applications

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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

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Pandas

02

And its applications

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Pandas

  • Economics
  • Recommendation Systems
  • Stock Prediction
  • Neuroscience
  • Statistics
  • Advertising
  • Analytics
  • Natural Language Processing
  • Big Data
  • Data Science

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What’s Next

03

Keeping in touch with us

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PYTHON FOR DATA SCIENCE

Data Visualisation with Python and Tableau (18 Sep)

>> Sign up here

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Links for workshop materials

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Feedback

Submit your feedback here!

https://forms.gle/nnZxLHHXDJDbrfUe7

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Stay updated with the latest workshops and events!

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References