2025-02-17 (v1.1.0):

• New HTML theme (includes the light and dark mode).
• Not using seaborn where it can easily be replaced by a few calls to the lower-level matplotlib, especially in the numpy chapters. This way, we can learn how to create some popular charts from scratch. In particular, we are now using own functions to display a heat map and a pairs plot.
• Use numpy.genfromtxt more eagerly.
• A few more examples of using f-strings for results' pretty-printing.
• Bug fixes and loads of other minor extensions.
• Updated to Python 3.11, numpy 2.2, pandas 2.2, matplotlib 3.10 (amongst others).

2023-02-06 (v1.0.3):

• Numeric reference style; updated bibliography.
• Reduce the file size of the screen-optimised PDF at the cost of a slight decrease of the quality of some figures.
• The print-optimised PDF now uses selective rasterisation of parts of figures, not whole pages containing them. This should result in a much better quality of the printed version.
• Bug fixes.
• Minor extensions, including: {command}pandas.Series.dt.strftime, more details how to avoid pitfalls in data frame indexing, etc.

2022-08-24 (v1.0.2):

• First printed (softcover) version.
• Fix page margins and headers.
• Minor typesetting and other fixes.

2022-08-12 (v1.0.1):

• Cover.
• Print version ready; ISBN 978-0-6455719-1-2 assigned.

2022-07-16 (v1.0.0):

• Preface complete.
• Handling tied observations.
• Plots look better when printed in black and white.
• Exception handling.
• File connections.
• Other minor extensions and material reordering: more aggregation functions, pandas.unique, pandas.factorize, probability vectors representing binary categorical variables, etc.
• Final proof-reading.

2022-06-13 (v0.5.1):

• The Kolmogorov–Smirnov Test (one and two sample).
• The Pearson Chi-Squared Test (one and two sample and for independence).
• Dealing with round-off and measurement errors.
• Adding white noise (jitter).
• Lambda expressions.
• Matrices are iterable.

2022-05-31 (v0.4.1):

• The Rules.
• Matrix multiplication, dot products.
• Euclidean distance, few-nearest-neighbour and fixed-radius search.
• Aggregation of multidimensional data.
• Regression with k-nearest neighbours.
• Least squares fitting of linear regression models.
• Geometric transforms; orthonormal matrices.
• SVD and dimensionality reduction/PCA.
• Classification with k-nearest neighbours.
• Clustering with k-means.
• Text Processing and Regular Expression chapters were merged.
• Unidimensional Data Aggregation and Transformation chapters were merged.
• pandas.GroupBy objects are iterable.
• Semitransparent histograms.
• Contour plots.
• Argument unpacking and variadic arguments (*args, **kwargs).

2022-05-23 (v0.3.1):

• More lightweight mathematical notation.
• Some equalities related to the mathematical functions we rely on (the natural logarithm, cosine, etc.).
• A way to compute the most correlated pair of variables.
• A note on modifying elements in an array and on adding new rows and columns.
• An example seasonal plot in the time series chapter.
• Solutions to the SQL exercises added; using {command}pd.testing.assert_frame_equal instead of {command}DataFrame.equals to ignore small round-off errors.
• More details on file paths.

2022-04-12 (v0.2.1):

• Many chapters merged or relocated.
• Added captions to all figures.
• Improved formatting of elements (information boxes such as note, important, exercise, example).