Applied Data Science with Python and Jupyter, Alex Galea, 2018 – Chapter 1

Basic system for Jupyter is a web front end to little pockets of code that execute on the backend; setup means getting the server running.

Assume this means that each notebook has its own kernel running on the server? Or not running, something more like a session.

Notebooks can be saved out as Python or HTML files.

DataFrames: created by Pandas constructor. Have a describe() method that gives summaries of individual variables. corr() gives a correlation matrix.

Seaborn pairplot: exactly what I wanted when working on reports at VCS – pairwise plots of variables against each other.

ndarray.reshape: reshapes the x-y sizes of an array; param values of -1 for a dimension mean that the correct value is inferred from other values.

sklearn.preprocessing.PolynomialFeatures: returns an object capable of transforming data frames, e.g. with degree of 2, and one-dimensional input the output frame would contain a frame for each input value, containing the value to the powers zero, one and two (i.e. the number one, the input value, and the input value squared).

sklearn.linear_model.LinearRegression: gives an object which can perform linear regression (multi-linear in the example)

There’s a bug in the last section, about categorical features. The cell that starts, “# Color-segmented pair plot” contains this:

sns.pairplot(df[cols], hue='AGE_category',
hue_order=['Relatively New', 'Relatively Old',
'Very Old'], plot_kws={'alpha': 0.5},
diag_kws={'bins': 30})

But this throws an AttributeError – ‘Line2D’ has no property ‘bins’. Removing the parameter diag_kws={‘bins’: 30} leaves the call running properly.

Leave a Reply

Your email address will not be published. Required fields are marked *

I accept that my given data and my IP address is sent to a server in the USA only for the purpose of spam prevention through the Akismet program.More information on Akismet and GDPR.

This site uses Akismet to reduce spam. Learn how your comment data is processed.