List of examples

Description	Type	Chap	Link
Quantitative data	✍️	1	Example 1.1
Floating-point numbers	💻	1	Example 1.2
Infinity and NaN	💻	1	Example 1.3
Dates and times in NumPy	💻	1	Example 1.4
Vectors in Python	💻	1	Example 1.5
Accessing vector elements	💻	1	Example 1.6
Slicing vectors	💻	1	Example 1.7
Arrays in Python	💻	1	Example 1.8
Indexing arrays	💻	1	Example 1.9
Array reductions	💻	1	Example 1.10
Ordinal data	✍️	1	Example 1.11
Dummy variables	✍️	1	Example 1.12
Series	✍️	1	Example 1.13
Series in pandas	💻	1	Example 1.14
Operations on series	💻	1	Example 1.15
Series and frames in pandas	💻	1	Example 1.16
Operations on data frames	💻	1	Example 1.17
Importing CSV data	💻	1	Example 1.18
iloc for rows in a frame	💻	1	Example 1.19
loc for rows in a frame	💻	1	Example 1.20
Selecting rows in a frame	💻	1	Example 1.21
Concatenating data in pandas	💻	1	Example 1.22
Merging data in pandas	💻	1	Example 1.23
Merging data	💻	1	Example 1.24
Handling missing values in pandas	💻	1	Example 1.25
Cleaning a data frame	💻	1	Example 1.26
Encoding qualitative data	💻	1	Example 1.27
Dummy variables in pandas	💻	1	Example 1.28
Summary statistics in pandas	💻	2	Example 2.1
Standard deviation by hand	✍️	2	Example 2.2
Sample variance	✍️	2	Example 2.3
Mean, variance, STD in pandas	💻	2	Example 2.4
Z scores	✍️, 💻	2	Example 2.5
Z scores in Python	💻	2	Example 2.6
Median	✍️	2	Example 2.7
Quantiles	💻	2	Example 2.8
Quartiles and IQR	💻	2	Example 2.9
ECDF of penguins	💻	2	Example 2.12
ECDF of a simple distribution	✍️	2	Example 2.11
ECDF of penguins	💻	2	Example 2.12
CDF of a uniform distribution	✍️	2	Example 2.13
ECDF of temperatures	💻	2	Example 2.14
PDF of temperature distribution	✍️	2	Example 2.15
PDF of a uniform distribution	✍️	2	Example 2.16
Uniform random numbers in NumPy	💻	2	Example 2.17
Normal distribution in NumPy	💻	2	Example 2.18
Grouping data	💻	2	Example 2.19
Facet plots	💻	2	Example 2.20
Box and violin plots	💻	2	Example 2.21
Aggregating data in groups	💻	2	Example 2.22
Grouping data by cuts	💻	2	Example 2.24
Outliers for mean and median	✍️	2	Example 2.25
Interquartile range	💻	2	Example 2.26
Outliers	💻	2	Example 2.27
Outliers and the Pearson coefficient	💻	2	Example 2.30
Spearman correlation coefficient	💻	2	Example 2.31
Categorical correlation	💻	2	Example 2.32
The Datasaurus	💻	2	Example 2.33
Correlation vs. dependence	💻	2	Example 2.34
Simpson’s paradox	💻	2	Example 2.35
Digit classification	💻	3	Example 3.1
Feature matrix	✍️	3	Example 3.2
Train–test split	💻	3	Example 3.3
Testing accuracy	💻	3	Example 3.4
Combined metrics	✍️	3	Example 3.7
Multiclass one-vs-rest	✍️	3	Example 3.8
Multiclass metrics	💻	3	Example 3.9
Decision tree	✍️	3	Example 3.10
Gini impurity	✍️	3	Example 3.11
Gini impurity	✍️	3	Example 3.12
Tree partitioning	✍️	3	Example 3.13
Inspecting a decision tree	💻	3	Example 3.14
Tree classifier for the penguins dataset	💻	3	Example 3.15
Interpreting a decision tree	💻	3	Example 3.16
Calculating distance	✍️	3	Example 3.17
kNN classifier	✍️	3	Example 3.18
kNN classifier for the penguins dataset	💻	3	Example 3.19
kNN sensitivity to scaling	✍️	3	Example 3.20
Pipeline for standardizing columns	💻	3	Example 3.21
Probabilistic classifier	✍️, 💻	3	Example 3.22
Probabilistic classifier for the penguins dataset	💻	3	Example 3.23
Varying decision threshold	💻	3	Example 3.24
ROC curve	💻	3	Example 3.25
Area under ROC curve	💻	3	Example 3.26
Hyperparameters	✍️	4	Example 4.1
Learning curves	💻	4	Example 4.2
Overfitting	💻	4	Example 4.3
Bagging ensemble classifier	💻	4	Example 4.4
Bagging ensemble (better)	💻	4	Example 4.5
Folds for validation	✍️	4	Example 4.7
Cross-validation grid search	💻	4	Example 4.10
Linear regression	✍️	5	Example 5.13
Inner product	✍️	5	Example 5.2
Mean squared and mean absolute error	✍️	5	Example 5.3
Coefficient of determination	✍️	5	Example 5.4
Linear regression for sea ice dataset	💻	5	Example 5.5
Matrix times vector	✍️	5	Example 5.6
Multilinear regression for MPG dataset	💻	5	Example 5.7
Multilinear regression for sales dataset	💻	5	Example 5.8
Polynomial regression for the MPG dataset	💻	5	Example 5.9
Overfitting in polynomial regression	💻	5	Example 5.10
Ridge regression for diabetes dataset	💻	5	Example 5.11
LASSO regression for diabetes dataset	💻	5	Example 5.12
Random forest for regression	💻	5	Example 5.19
Cross-entropy	✍️	5	Example 5.20
Logistic regression as a spam filter	💻	5	Example 5.21
Distance matrix	✍️	6	Example 6.1
Usage of `pairwise_distances`	💻	6	Example 6.2
Angular distance	💻	6	Example 6.3
Rand index by hand	✍️	6	Example 6.4
Adjusted Rand index	💻	6	Example 6.5
Silhouette values	✍️	6	Example 6.6
Silhouette values calculation	💻	6	Example 6.7
Silhouettes as performance metric	💻	6	Example 6.8
Limitation of silhouettes	💻	6	Example 6.9
Inertia	✍️	6	Example 6.10
k-means on blobs dataset	💻	6	Example 6.11
k-means on stripes dataset	💻	6	Example 6.12
k-means on digits dataset	💻	6	Example 6.13
Comparing linkages on simple datasets	💻	6	Example 6.16
Agglomerative for penguins dataset	💻	6	Example 6.17
Constructing networks/graphs	💻	7	Example 7.1
Importing networks	💻	7	Example 7.2
Neighbors of a node	💻	7	Example 7.3
Ego graph	💻	7	Example 7.4
Node degrees	💻	7	Example 7.6
Average degree	💻	7	Example 7.7
ER graphs	💻	7	Example 7.8
Clustering coefficient	✍️	7	Example 7.10
Clustering in the Twitch network	💻	7	Example 7.11
Clustering in ER graphs	💻	7	Example 7.12
Distances in a complete graph	✍️	7	Example 7.14
Distances in a wheel graph	💻	7	Example 7.15
Connectedness	✍️	7	Example 7.16
Distances in ER graphs	💻	7	Example 7.17
Degree distribution in the Twitch network	💻	7	Example 7.18
Degree distribution in the Twitch network	💻	7	Example 7.19
Barabási–Albert graphs	💻	7	Example 7.20
Power-law degrees in the Twitch network	💻	7	Example 7.21
Betweenness centrality in the Twitch network	💻	7	Example 7.25
Eigenvectors	✍️	7	Example 7.26
Eigenvector centrality	✍️	7	Example 7.27
Comparison of centrality metrics	💻	7	Example 7.28