Page 543 - Python Data Science Handbook

GMMs, 488-491 vectorized string operations, 178-188
k-means clustering, 470-473 pandas.eval() function, 210-211
loading/visualizing digits data, 354 Panel data, 141
Matplotlib, 261-262 partial slicing, 135
PCA as noise filtering, 440-442 partitioning (partial sorts), 88
PCA for visualization, 437 pasting code blocks, magic commands for, 11
random forests for classifying digits, pd.concat() function
430-432 catching repeats as error, 144
Scikit-Learn application, 354-358 concatenation with, 142-146
visualizing structure in digits, 460-462 concatenation with joins, 145
or keyword, 77 duplicate indices, 143
ordered set, Index object as, 106 ignoring the index, 144
orthographic projection, 302 MultiIndex keys, 144
Out objects, IPython, 13 pd.date_range() function, 193
outer join, 153 pd.eval() function, 210-211
outer products, 58 pd.merge() function, 146-158
outliers, PCA and, 445 categories of joins, 147-149
output, suppressing, 15 keywords, 149-152
overfitting, 371, 425 left_index/right_index keywords, 151-152
merge key specification, 149-152
P relational algebra and, 146
pair plots, 317 specifying set arithmetic for joins, 152
Pandas, 97 pdb (Python debugger), 22
aggregation and grouping, 158-170 Perez, Fernando, 1, 217
and compound expressions, 209 Period type, 193
appending datasets, 146 perspective projections, 302
built-in documentation, 98 pipelines, 366, 381
combining datasets, 141-158 pivot tables, 170-178
concatenation of datasets, 141-146 groupby() operation vs., 171
data indexing and selection, 107 multi-level, 172
data selection in DataFrame, 110-215 syntax, 171-173
data selection in Series, 107-110 Titanic passengers example, 170
DataFrame object, 102-105 US birthrate data example, 174-178
eval() and query(), 208-209 Planets dataset
handling missing data, 119-120 aggregation and grouping, 159
hierarchical indexing, 128-141 bar plots, 321
Index object, 105-107 plot legends
installation, 97 choosing elements for, 251
merging/joining datasets, 146-158 customizing, 249-255
NaN and None in, 123 multiple legends on same axes, 254
null values, 124-127 points size, 252
objects, 98-107 Plotly, 330
operating on data in, 115-127 plotting
(see also universal functions) axes limits for simple line plots, 228-230
pandas.eval(), 210-211 bar plots, 321
Panel data, 141 changing defaults via rcParams, 284
pivot tables, 170-178 colorbars, 255-262
Series object, 99-102 data on maps, 307-329
time series, 188-214 density and contour plots, 241-245

Index | 525