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The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001

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Data Science, Big Data and Data Diversity Data (DATA2001)

   

Added on  2022-01-21

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DATA2001: Data Science, Big Data and Data Diversity Data Preparation and Exploration with Python Presented by Alan Fekete Material prepared by Uwe Roehm School of Computer Science The University of Sydney Page 1 Jupyter Notebooks: The Python Environment in DATA2001 The University of Sydney Page 2 Jupyter Notebooks support interactive Data Science with Python IPython interactive command shell offers: Introspection Tab completion Command history Jupyter runs in a browser and supports: Sharing and documenting of live

The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001

   

Data Science, Big Data and Data Diversity Data (DATA2001)

   Added on 2022-01-21

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The University of Sydney Page 1
DATA2001: Data Science,
Big Data and Data Diversity
Data Cleaning and Exploration
with Python
Presented by Alan Fekete
Material prepared by Uwe Roehm
School of Computer Science
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_1
The University of Sydney Page 2
Jupyter Notebooks:
The Python Environment in DATA2001
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_2
The University of Sydney Page 3
Jupyter Notebooks support interactive Data Science
with Python
IPython interactive command shell offers:
Introspection
Tab completion
Command history
Jupyter runs in a browser and supports:
Sharing and documenting of live code
Data cleaning, visualisation, machine learning, ...
Jupyter’s gallery of interesting notebooks:
https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks
We provide Jupyter servers which run Python 3
https://ucpu0.ug.it.usyd.edu.au/ (remember you need to be using VPN, if off campus)
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_3
The University of Sydney Page 4
1. Click here for file
open dialogue
2. Click upload
next to file name
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_4
The University of Sydney Page 5
Installing Python and Jupyter using Anaconda
You can use our Jupyter
server
but it can be slow
If you wish, you
can install Python and
Jupyter privately, eg
using
Anaconda Distribution,
which includes Python,
the Jupyter Notebook,
and other commonly used
packages for scientific
computing and data
science.
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_5
The University of Sydney Page 6
Python and Data Science Libraries
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_6
The University of Sydney Page 7
Python background
Students who did data1002: this should mostly be revision
If you didn’t really master pandas, matplotlib before, do so now!
Also note the following key differences
More sophisticated ways to consider the kinds of data (not just
numerical/castegorical)
Students who learned Python elsewhere (eg infi1110): you
need to learn how to use particular libraries (Pandas,
matplotlib etc) from the examples here, and online resources
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_7
The University of Sydney Page 8
Python general concepts
general program syntax
variables and types
integer and float numbers, string types, type conversion
list, dictionary, tuple and set
condition statements (if/elif/else)
for loops, ranges
functions
print(), len(), lower(), upper(), ...
nesting of functions; example: print( len( str.upper() ) )
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001_8

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