Page 537 - Python Data Science Handbook
P. 537
colon (:), 44 as dictionary, 110-112
color compression, 473-476 as generalized NumPy array, 102
colorbars as specialized dictionary, 103
colormap selection, 256-259 as two-dimensional array, 112-114
customizing, 255-262 constructing, 104
discrete, 260 data selection in, 110
handwritten digit example, 261-262 defined, 97
colormap, 256-259 index alignment in, 117
column(s) masking, 114
accessing single, 45 multiply indexed, 136
indexing, 163 operations between Series object and, 118
MultiIndex for, 133 slicing, 114
sorting arrays along, 87 DataFrame.eval() method, 211-213
suffixes keyword and overlapping names, assignment in, 212
153 local variables in, 213
column-wise operations, 211-213 DataFrame.query() method, 213
command history shortcuts, 9 datasets
comparison operators, 71-73 appending, 146
concatenation combining (Panda), 141-158
datasets, 141-146 concatenation, 141-146
of arrays, 48, 142 merging/joining, 146-158
with pd.concat(), 142-146 datetime module, 189
confusion matrix, 357 datetime64 dtype, 189
conic projections, 303 dateutil module, 189
contour plots, 241-245 debugging, 22-24
density and, 241-245 decision trees, 421-426
three-dimensional function, 241-245 (see also random forests)
three-dimensional plot, 292 creating, 422-425
Conway, Drew, xi overfitting, 425
cross-validation, 361-370 deep learning, 513
cubehelix colormap, 258 density estimator
cylindrical projections, 301 GMM, 484-488
histogram as, 492
D KDE (see kernel density estimation (KDE))
data describe() method, 164
as arrays, 33 development, IPython
missing (see missing data) profiling and timing code, 25-30
data representation (Scikit-Learn package), profiling full scripts, 27
343-346 timing of code snippets, 25-27
data as table, 343 dictionary(-ies)
features matrix, 344 DataFrame as specialization of, 103
target array, 344-345 DataFrame object constructed from list of,
data science, defining, xi 104
data types, 34 Pandas Series object vs., 100
fixed-type arrays, 38 digits, recognition of (see optical character rec‐
integers, 35 ognition)
lists in, 37-41 dimensionality reduction, 261
NumPy, 41 machine learning, 340-342
DataFrame object (Pandas), 102-105 PCA and, 433
Index | 519
