Coverage for /var/srv/projects/api.amasfac.comuna18.com/tmp/venv/lib/python3.9/site-packages/pandas/__init__.py: 51%
65 statements
« prev ^ index » next coverage.py v6.4.4, created at 2023-07-17 14:22 -0600
1from __future__ import annotations
3__docformat__ = "restructuredtext"
5# Let users know if they're missing any of our hard dependencies
6_hard_dependencies = ("numpy", "pytz", "dateutil")
7_missing_dependencies = []
9for _dependency in _hard_dependencies:
10 try:
11 __import__(_dependency)
12 except ImportError as _e:
13 _missing_dependencies.append(f"{_dependency}: {_e}")
15if _missing_dependencies: 15 ↛ 16line 15 didn't jump to line 16, because the condition on line 15 was never true
16 raise ImportError(
17 "Unable to import required dependencies:\n" + "\n".join(_missing_dependencies)
18 )
19del _hard_dependencies, _dependency, _missing_dependencies
21# numpy compat
22from pandas.compat import is_numpy_dev as _is_numpy_dev # pyright: ignore # noqa:F401
24try:
25 from pandas._libs import hashtable as _hashtable, lib as _lib, tslib as _tslib
26except ImportError as _err: # pragma: no cover
27 _module = _err.name
28 raise ImportError(
29 f"C extension: {_module} not built. If you want to import "
30 "pandas from the source directory, you may need to run "
31 "'python setup.py build_ext --force' to build the C extensions first."
32 ) from _err
33else:
34 del _tslib, _lib, _hashtable
36from pandas._config import (
37 get_option,
38 set_option,
39 reset_option,
40 describe_option,
41 option_context,
42 options,
43)
45# let init-time option registration happen
46import pandas.core.config_init # pyright: ignore # noqa:F401
48from pandas.core.api import (
49 # dtype
50 ArrowDtype,
51 Int8Dtype,
52 Int16Dtype,
53 Int32Dtype,
54 Int64Dtype,
55 UInt8Dtype,
56 UInt16Dtype,
57 UInt32Dtype,
58 UInt64Dtype,
59 Float32Dtype,
60 Float64Dtype,
61 CategoricalDtype,
62 PeriodDtype,
63 IntervalDtype,
64 DatetimeTZDtype,
65 StringDtype,
66 BooleanDtype,
67 # missing
68 NA,
69 isna,
70 isnull,
71 notna,
72 notnull,
73 # indexes
74 Index,
75 CategoricalIndex,
76 RangeIndex,
77 MultiIndex,
78 IntervalIndex,
79 TimedeltaIndex,
80 DatetimeIndex,
81 PeriodIndex,
82 IndexSlice,
83 # tseries
84 NaT,
85 Period,
86 period_range,
87 Timedelta,
88 timedelta_range,
89 Timestamp,
90 date_range,
91 bdate_range,
92 Interval,
93 interval_range,
94 DateOffset,
95 # conversion
96 to_numeric,
97 to_datetime,
98 to_timedelta,
99 # misc
100 Flags,
101 Grouper,
102 factorize,
103 unique,
104 value_counts,
105 NamedAgg,
106 array,
107 Categorical,
108 set_eng_float_format,
109 Series,
110 DataFrame,
111)
113from pandas.core.arrays.sparse import SparseDtype
115from pandas.tseries.api import infer_freq
116from pandas.tseries import offsets
118from pandas.core.computation.api import eval
120from pandas.core.reshape.api import (
121 concat,
122 lreshape,
123 melt,
124 wide_to_long,
125 merge,
126 merge_asof,
127 merge_ordered,
128 crosstab,
129 pivot,
130 pivot_table,
131 get_dummies,
132 from_dummies,
133 cut,
134 qcut,
135)
137from pandas import api, arrays, errors, io, plotting, tseries
138from pandas import testing # noqa:PDF015
139from pandas.util._print_versions import show_versions
141from pandas.io.api import (
142 # excel
143 ExcelFile,
144 ExcelWriter,
145 read_excel,
146 # parsers
147 read_csv,
148 read_fwf,
149 read_table,
150 # pickle
151 read_pickle,
152 to_pickle,
153 # pytables
154 HDFStore,
155 read_hdf,
156 # sql
157 read_sql,
158 read_sql_query,
159 read_sql_table,
160 # misc
161 read_clipboard,
162 read_parquet,
163 read_orc,
164 read_feather,
165 read_gbq,
166 read_html,
167 read_xml,
168 read_json,
169 read_stata,
170 read_sas,
171 read_spss,
172)
174from pandas.io.json import _json_normalize as json_normalize
176from pandas.util._tester import test
178# use the closest tagged version if possible
179from pandas._version import get_versions
181v = get_versions()
182__version__ = v.get("closest-tag", v["version"])
183__git_version__ = v.get("full-revisionid")
184del get_versions, v
186# GH 27101
187__deprecated_num_index_names = ["Float64Index", "Int64Index", "UInt64Index"]
190def __dir__() -> list[str]:
191 # GH43028
192 # Int64Index etc. are deprecated, but we still want them to be available in the dir.
193 # Remove in Pandas 2.0, when we remove Int64Index etc. from the code base.
194 return list(globals().keys()) + __deprecated_num_index_names
197def __getattr__(name):
198 import warnings
200 if name in __deprecated_num_index_names:
201 warnings.warn(
202 f"pandas.{name} is deprecated "
203 "and will be removed from pandas in a future version. "
204 "Use pandas.Index with the appropriate dtype instead.",
205 FutureWarning,
206 stacklevel=2,
207 )
208 from pandas.core.api import Float64Index, Int64Index, UInt64Index
210 return {
211 "Float64Index": Float64Index,
212 "Int64Index": Int64Index,
213 "UInt64Index": UInt64Index,
214 }[name]
215 elif name == "datetime":
216 warnings.warn(
217 "The pandas.datetime class is deprecated "
218 "and will be removed from pandas in a future version. "
219 "Import from datetime module instead.",
220 FutureWarning,
221 stacklevel=2,
222 )
224 from datetime import datetime as dt
226 return dt
228 elif name == "np":
230 warnings.warn(
231 "The pandas.np module is deprecated "
232 "and will be removed from pandas in a future version. "
233 "Import numpy directly instead.",
234 FutureWarning,
235 stacklevel=2,
236 )
237 import numpy as np
239 return np
241 elif name in {"SparseSeries", "SparseDataFrame"}:
242 warnings.warn(
243 f"The {name} class is removed from pandas. Accessing it from "
244 "the top-level namespace will also be removed in the next version.",
245 FutureWarning,
246 stacklevel=2,
247 )
249 return type(name, (), {})
251 elif name == "SparseArray":
253 warnings.warn(
254 "The pandas.SparseArray class is deprecated "
255 "and will be removed from pandas in a future version. "
256 "Use pandas.arrays.SparseArray instead.",
257 FutureWarning,
258 stacklevel=2,
259 )
260 from pandas.core.arrays.sparse import SparseArray as _SparseArray
262 return _SparseArray
264 raise AttributeError(f"module 'pandas' has no attribute '{name}'")
267# module level doc-string
268__doc__ = """
269pandas - a powerful data analysis and manipulation library for Python
270=====================================================================
272**pandas** is a Python package providing fast, flexible, and expressive data
273structures designed to make working with "relational" or "labeled" data both
274easy and intuitive. It aims to be the fundamental high-level building block for
275doing practical, **real world** data analysis in Python. Additionally, it has
276the broader goal of becoming **the most powerful and flexible open source data
277analysis / manipulation tool available in any language**. It is already well on
278its way toward this goal.
280Main Features
281-------------
282Here are just a few of the things that pandas does well:
284 - Easy handling of missing data in floating point as well as non-floating
285 point data.
286 - Size mutability: columns can be inserted and deleted from DataFrame and
287 higher dimensional objects
288 - Automatic and explicit data alignment: objects can be explicitly aligned
289 to a set of labels, or the user can simply ignore the labels and let
290 `Series`, `DataFrame`, etc. automatically align the data for you in
291 computations.
292 - Powerful, flexible group by functionality to perform split-apply-combine
293 operations on data sets, for both aggregating and transforming data.
294 - Make it easy to convert ragged, differently-indexed data in other Python
295 and NumPy data structures into DataFrame objects.
296 - Intelligent label-based slicing, fancy indexing, and subsetting of large
297 data sets.
298 - Intuitive merging and joining data sets.
299 - Flexible reshaping and pivoting of data sets.
300 - Hierarchical labeling of axes (possible to have multiple labels per tick).
301 - Robust IO tools for loading data from flat files (CSV and delimited),
302 Excel files, databases, and saving/loading data from the ultrafast HDF5
303 format.
304 - Time series-specific functionality: date range generation and frequency
305 conversion, moving window statistics, date shifting and lagging.
306"""
308# Use __all__ to let type checkers know what is part of the public API.
309# Pandas is not (yet) a py.typed library: the public API is determined
310# based on the documentation.
311__all__ = [
312 "ArrowDtype",
313 "BooleanDtype",
314 "Categorical",
315 "CategoricalDtype",
316 "CategoricalIndex",
317 "DataFrame",
318 "DateOffset",
319 "DatetimeIndex",
320 "DatetimeTZDtype",
321 "ExcelFile",
322 "ExcelWriter",
323 "Flags",
324 "Float32Dtype",
325 "Float64Dtype",
326 "Grouper",
327 "HDFStore",
328 "Index",
329 "IndexSlice",
330 "Int16Dtype",
331 "Int32Dtype",
332 "Int64Dtype",
333 "Int8Dtype",
334 "Interval",
335 "IntervalDtype",
336 "IntervalIndex",
337 "MultiIndex",
338 "NA",
339 "NaT",
340 "NamedAgg",
341 "Period",
342 "PeriodDtype",
343 "PeriodIndex",
344 "RangeIndex",
345 "Series",
346 "SparseDtype",
347 "StringDtype",
348 "Timedelta",
349 "TimedeltaIndex",
350 "Timestamp",
351 "UInt16Dtype",
352 "UInt32Dtype",
353 "UInt64Dtype",
354 "UInt8Dtype",
355 "api",
356 "array",
357 "arrays",
358 "bdate_range",
359 "concat",
360 "crosstab",
361 "cut",
362 "date_range",
363 "describe_option",
364 "errors",
365 "eval",
366 "factorize",
367 "get_dummies",
368 "from_dummies",
369 "get_option",
370 "infer_freq",
371 "interval_range",
372 "io",
373 "isna",
374 "isnull",
375 "json_normalize",
376 "lreshape",
377 "melt",
378 "merge",
379 "merge_asof",
380 "merge_ordered",
381 "notna",
382 "notnull",
383 "offsets",
384 "option_context",
385 "options",
386 "period_range",
387 "pivot",
388 "pivot_table",
389 "plotting",
390 "qcut",
391 "read_clipboard",
392 "read_csv",
393 "read_excel",
394 "read_feather",
395 "read_fwf",
396 "read_gbq",
397 "read_hdf",
398 "read_html",
399 "read_json",
400 "read_orc",
401 "read_parquet",
402 "read_pickle",
403 "read_sas",
404 "read_spss",
405 "read_sql",
406 "read_sql_query",
407 "read_sql_table",
408 "read_stata",
409 "read_table",
410 "read_xml",
411 "reset_option",
412 "set_eng_float_format",
413 "set_option",
414 "show_versions",
415 "test",
416 "testing",
417 "timedelta_range",
418 "to_datetime",
419 "to_numeric",
420 "to_pickle",
421 "to_timedelta",
422 "tseries",
423 "unique",
424 "value_counts",
425 "wide_to_long",
426]