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DATA2001: Data Science, Big Data and Data Diversity Data

Added on - 21 Jan 2022

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DATA2001: Data Science,
Big Data and Data Diversity
Data Cleaning and Exploration
with Python
Presented by Alan Fekete
Material prepared by UweRoehm
School of Computer Science
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The Python Environment in DATA2001
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JupyterNotebooks support interactive Data Science
with Python
IPythoninteractive command shell offers:
Tab completion
Command history
Jupyterruns in a browser and supports:
Sharing and documenting of live code
Data cleaning,visualisation, machine learning,...
Jupyter’sgallery of interesting notebooks:
We provideJupyterservers which run Python 3 you need to be using VPN, if off campus)
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1.Click here for file
open dialogue
2.Click upload
next to file name
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Installing Python andJupyterusing Anaconda
You can use ourJupyter
but it can be slow
If you wish, you
caninstall Python and
Anaconda Distribution,
which includes Python,
and other commonly used
packages for scientific
computing and data
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Python and Data Science Libraries
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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
Students who learned Python elsewhere (eginfi1110): you
need to learn how to use particular libraries (Pandas,
matplotlib etc) from the examples here, and online resources
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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
print(),len(), lower(), upper(),...
nesting of functions; example:print(len(str.upper() ) )
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