Page 539 - Python Data Science Handbook

iteration over groups, 164 immutable array, Index object as, 106
transform() method, 167 importing, tab completion for, 7
groupby() operation (Pandas), 161-170 In objects, IPython, 13
GroupBy object and, 163-165 index alignment
grouping example, 169 in DataFrame, 117
pivot tables vs., 171 in Series, 116
split key specification, 168 Index object (Pandas), 105-107
split-apply-combine example, 161-163 as immutable array, 106
as ordered set, 106
H indexing
handwritten digits, recognition of (see optical fancy, 78-85
character recognition) (see also fancy indexing)
hard negative mining, 513 hierarchical (see hierarchical indexing)
help NumPy arrays: accessing single elements, 43
IPython, 3-8 Pandas, 107
magic functions, 13 IndexSlice object, 137
help() function, 4 indicator variables, 183
hexagonal binnings, 248 inner join, 153
hierarchical indexing input/output history, IPython, 13-16
in one-dimensional Series, 128-141 In and Out objects, 13
MultiIndex, 128-141, 129-131 related magic commands, 16
(see also MultiIndex type) suppressing output, 15
rearranging multi-indices, 137-140 underscore shortcuts and previous outputs,
unstack() method, 130 15
with Python tuples as keys, 128 installation, Python, xiv
Histogram of Oriented Gradients (HOG) integers, Python, 35
caveats and improvements, 512-514 IPython, 1
features, 506 accessing documentation with ?, 3
for face detection pipeline, 506-514 accessing source code with ??, 5
simple face detector, 507-512 command-line commands in shell, 18
histograms, 245-249 controlling exceptions, 20-22
binning data to create, 83 debugging, 22-24
faceted, 318 documentation, 3-8, 34
KDE and, 248, 491-496 errors handling, 20-24
manual customization, 282-284 exploring modules with tab completion, 6-7
plt.hexbin() function, 248 help and documentation, 3-8
plt.hist2d() function, 247 input/output history, 13-16
Seaborn, 314-317 keyboard shortcuts in shell, 8
simple, 245-246 launching Jupyter notebook, 2
two-dimensional, 247-249 launching shell, 2
holdout sets, 360 magic commands, 10-13
Hunter, John, 217 notebook (see Jupyter notebook)
hyperparameters, 349 plotting from shell, 219
(see also model validation) profiling and timing code, 25-30
shell commands, 16-19
I shell-related magic commands, 19
web resources, 30
iloc attribute (Pandas), 110 wildcard matching, 7
images, encoding for machine learning analy‐ Iris dataset
sis, 378

Index | 521