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pandas-dev/pandas | doc/make.py | DocBuilder._run_os | def _run_os(*args):
"""
Execute a command as a OS terminal.
Parameters
----------
*args : list of str
Command and parameters to be executed
Examples
--------
>>> DocBuilder()._run_os('python', '--version')
"""
subprocess.check... | python | def _run_os(*args):
"""
Execute a command as a OS terminal.
Parameters
----------
*args : list of str
Command and parameters to be executed
Examples
--------
>>> DocBuilder()._run_os('python', '--version')
"""
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pandas-dev/pandas | doc/make.py | DocBuilder._sphinx_build | def _sphinx_build(self, kind):
"""
Call sphinx to build documentation.
Attribute `num_jobs` from the class is used.
Parameters
----------
kind : {'html', 'latex'}
Examples
--------
>>> DocBuilder(num_jobs=4)._sphinx_build('html')
"""
... | python | def _sphinx_build(self, kind):
"""
Call sphinx to build documentation.
Attribute `num_jobs` from the class is used.
Parameters
----------
kind : {'html', 'latex'}
Examples
--------
>>> DocBuilder(num_jobs=4)._sphinx_build('html')
"""
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pandas-dev/pandas | doc/make.py | DocBuilder._open_browser | def _open_browser(self, single_doc_html):
"""
Open a browser tab showing single
"""
url = os.path.join('file://', DOC_PATH, 'build', 'html',
single_doc_html)
webbrowser.open(url, new=2) | python | def _open_browser(self, single_doc_html):
"""
Open a browser tab showing single
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url = os.path.join('file://', DOC_PATH, 'build', 'html',
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pandas-dev/pandas | doc/make.py | DocBuilder._get_page_title | def _get_page_title(self, page):
"""
Open the rst file `page` and extract its title.
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fname = os.path.join(SOURCE_PATH, '{}.rst'.format(page))
option_parser = docutils.frontend.OptionParser(
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doc = docutils.utils.ne... | python | def _get_page_title(self, page):
"""
Open the rst file `page` and extract its title.
"""
fname = os.path.join(SOURCE_PATH, '{}.rst'.format(page))
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pandas-dev/pandas | doc/make.py | DocBuilder._add_redirects | def _add_redirects(self):
"""
Create in the build directory an html file with a redirect,
for every row in REDIRECTS_FILE.
"""
html = '''
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<head>
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</head>
<body>
... | python | def _add_redirects(self):
"""
Create in the build directory an html file with a redirect,
for every row in REDIRECTS_FILE.
"""
html = '''
<html>
<head>
<meta http-equiv="refresh" content="0;URL={url}"/>
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<body>
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pandas-dev/pandas | doc/make.py | DocBuilder.html | def html(self):
"""
Build HTML documentation.
"""
ret_code = self._sphinx_build('html')
zip_fname = os.path.join(BUILD_PATH, 'html', 'pandas.zip')
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self... | python | def html(self):
"""
Build HTML documentation.
"""
ret_code = self._sphinx_build('html')
zip_fname = os.path.join(BUILD_PATH, 'html', 'pandas.zip')
if os.path.exists(zip_fname):
os.remove(zip_fname)
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pandas-dev/pandas | doc/make.py | DocBuilder.latex | def latex(self, force=False):
"""
Build PDF documentation.
"""
if sys.platform == 'win32':
sys.stderr.write('latex build has not been tested on windows\n')
else:
ret_code = self._sphinx_build('latex')
os.chdir(os.path.join(BUILD_PATH, 'latex'))... | python | def latex(self, force=False):
"""
Build PDF documentation.
"""
if sys.platform == 'win32':
sys.stderr.write('latex build has not been tested on windows\n')
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pandas-dev/pandas | doc/make.py | DocBuilder.clean | def clean():
"""
Clean documentation generated files.
"""
shutil.rmtree(BUILD_PATH, ignore_errors=True)
shutil.rmtree(os.path.join(SOURCE_PATH, 'reference', 'api'),
ignore_errors=True) | python | def clean():
"""
Clean documentation generated files.
"""
shutil.rmtree(BUILD_PATH, ignore_errors=True)
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pandas-dev/pandas | doc/make.py | DocBuilder.zip_html | def zip_html(self):
"""
Compress HTML documentation into a zip file.
"""
zip_fname = os.path.join(BUILD_PATH, 'html', 'pandas.zip')
if os.path.exists(zip_fname):
os.remove(zip_fname)
dirname = os.path.join(BUILD_PATH, 'html')
fnames = os.listdir(dirnam... | python | def zip_html(self):
"""
Compress HTML documentation into a zip file.
"""
zip_fname = os.path.join(BUILD_PATH, 'html', 'pandas.zip')
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os.remove(zip_fname)
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pandas-dev/pandas | pandas/io/formats/latex.py | LatexFormatter.write_result | def write_result(self, buf):
"""
Render a DataFrame to a LaTeX tabular/longtable environment output.
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# string representation of the columns
if len(self.frame.columns) == 0 or len(self.frame.index) == 0:
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"""
Render a DataFrame to a LaTeX tabular/longtable environment output.
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# string representation of the columns
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pandas-dev/pandas | pandas/io/formats/latex.py | LatexFormatter._format_multicolumn | def _format_multicolumn(self, row, ilevels):
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Combine columns belonging to a group to a single multicolumn entry
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"""
row... | python | def _format_multicolumn(self, row, ilevels):
r"""
Combine columns belonging to a group to a single multicolumn entry
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pandas-dev/pandas | pandas/io/formats/latex.py | LatexFormatter._format_multirow | def _format_multirow(self, row, ilevels, i, rows):
r"""
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"""
for j in range(ileve... | python | def _format_multirow(self, row, ilevels, i, rows):
r"""
Check following rows, whether row should be a multirow
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pandas-dev/pandas | pandas/io/formats/latex.py | LatexFormatter._print_cline | def _print_cline(self, buf, i, icol):
"""
Print clines after multirow-blocks are finished
"""
for cl in self.clinebuf:
if cl[0] == i:
buf.write('\\cline{{{cl:d}-{icol:d}}}\n'
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# remove entries that... | python | def _print_cline(self, buf, i, icol):
"""
Print clines after multirow-blocks are finished
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for cl in self.clinebuf:
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buf.write('\\cline{{{cl:d}-{icol:d}}}\n'
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pandas-dev/pandas | pandas/io/parsers.py | _validate_integer | def _validate_integer(name, val, min_val=0):
"""
Checks whether the 'name' parameter for parsing is either
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without losing accuracy. Raises a ValueError if that is
not the case.
Parameters
----------
name : string
Paramete... | python | def _validate_integer(name, val, min_val=0):
"""
Checks whether the 'name' parameter for parsing is either
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pandas-dev/pandas | pandas/io/parsers.py | _validate_names | def _validate_names(names):
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Check if the `names` parameter contains duplicates.
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names : array-like or None
An array containing a list of the names used for the output DataFrame.
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"""
Check if the `names` parameter contains duplicates.
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pandas-dev/pandas | pandas/io/parsers.py | _read | def _read(filepath_or_buffer: FilePathOrBuffer, kwds):
"""Generic reader of line files."""
encoding = kwds.get('encoding', None)
if encoding is not None:
encoding = re.sub('_', '-', encoding).lower()
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compress... | python | def _read(filepath_or_buffer: FilePathOrBuffer, kwds):
"""Generic reader of line files."""
encoding = kwds.get('encoding', None)
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pandas-dev/pandas | pandas/io/parsers.py | _is_potential_multi_index | def _is_potential_multi_index(columns):
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Check whether or not the `columns` parameter
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Parameters
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columns : array-like
Object which may or may not be convertible into a MultiIndex
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"""
Check whether or not the `columns` parameter
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pandas-dev/pandas | pandas/io/parsers.py | _evaluate_usecols | def _evaluate_usecols(usecols, names):
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"""
Check whether or not the 'usecols' parameter
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pandas-dev/pandas | pandas/io/parsers.py | _validate_usecols_names | def _validate_usecols_names(usecols, names):
"""
Validates that all usecols are present in a given
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pandas-dev/pandas | pandas/io/parsers.py | _validate_usecols_arg | def _validate_usecols_arg(usecols):
"""
Validate the 'usecols' parameter.
Checks whether or not the 'usecols' parameter contains all integers
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Raises a ValueError if that is not the case.
Parameters
----------
useco... | python | def _validate_usecols_arg(usecols):
"""
Validate the 'usecols' parameter.
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pandas-dev/pandas | pandas/io/parsers.py | _validate_parse_dates_arg | def _validate_parse_dates_arg(parse_dates):
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"""
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pandas-dev/pandas | pandas/io/parsers.py | _stringify_na_values | def _stringify_na_values(na_values):
""" return a stringified and numeric for these values """
result = []
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result.append(str(x))
result.append(x)
try:
v = float(x)
# we are like 999 here
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v = int(... | python | def _stringify_na_values(na_values):
""" return a stringified and numeric for these values """
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pandas-dev/pandas | pandas/io/parsers.py | _get_na_values | def _get_na_values(col, na_values, na_fvalues, keep_default_na):
"""
Get the NaN values for a given column.
Parameters
----------
col : str
The name of the column.
na_values : array-like, dict
The object listing the NaN values as strings.
na_fvalues : array-like, dict
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"""
Get the NaN values for a given column.
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col : str
The name of the column.
na_values : array-like, dict
The object listing the NaN values as strings.
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pandas-dev/pandas | pandas/io/parsers.py | ParserBase._extract_multi_indexer_columns | def _extract_multi_indexer_columns(self, header, index_names, col_names,
passed_names=False):
""" extract and return the names, index_names, col_names
header is a list-of-lists returned from the parsers """
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return header[... | python | def _extract_multi_indexer_columns(self, header, index_names, col_names,
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pandas-dev/pandas | pandas/io/parsers.py | ParserBase._infer_types | def _infer_types(self, values, na_values, try_num_bool=True):
"""
Infer types of values, possibly casting
Parameters
----------
values : ndarray
na_values : set
try_num_bool : bool, default try
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pandas-dev/pandas | pandas/io/parsers.py | ParserBase._cast_types | def _cast_types(self, values, cast_type, column):
"""
Cast values to specified type
Parameters
----------
values : ndarray
cast_type : string or np.dtype
dtype to cast values to
column : string
column name - used only for error reporting
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"""
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dtype to cast values to
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column name - used only for error reporting
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pandas-dev/pandas | pandas/io/parsers.py | CParserWrapper._set_noconvert_columns | def _set_noconvert_columns(self):
"""
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Currently, any column that is involved with date parsing will not
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"""
names = self.orig_names
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pandas-dev/pandas | pandas/io/parsers.py | PythonParser._handle_usecols | def _handle_usecols(self, columns, usecols_key):
"""
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"""
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pandas-dev/pandas | pandas/io/parsers.py | PythonParser._check_for_bom | def _check_for_bom(self, first_row):
"""
Checks whether the file begins with the BOM character.
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in the field subsequent to the BOM, remove it as well
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the name, n... | python | def _check_for_bom(self, first_row):
"""
Checks whether the file begins with the BOM character.
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lines : array-like
The array of lines that we are to filter.
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lines : array-like
The array of lines that we are to filter.
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pandas-dev/pandas | pandas/io/parsers.py | FixedWidthReader.get_rows | def get_rows(self, infer_nrows, skiprows=None):
"""
Read rows from self.f, skipping as specified.
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because it's simpler to leave the other locations
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Read rows from self.f, skipping as specified.
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pandas-dev/pandas | doc/source/conf.py | linkcode_resolve | def linkcode_resolve(domain, info):
"""
Determine the URL corresponding to Python object
"""
if domain != 'py':
return None
modname = info['module']
fullname = info['fullname']
submod = sys.modules.get(modname)
if submod is None:
return None
obj = submod
for pa... | python | def linkcode_resolve(domain, info):
"""
Determine the URL corresponding to Python object
"""
if domain != 'py':
return None
modname = info['module']
fullname = info['fullname']
submod = sys.modules.get(modname)
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pandas-dev/pandas | doc/source/conf.py | process_class_docstrings | def process_class_docstrings(app, what, name, obj, options, lines):
"""
For those classes for which we use ::
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pandas-dev/pandas | pandas/io/msgpack/__init__.py | pack | def pack(o, stream, **kwargs):
"""
Pack object `o` and write it to `stream`
See :class:`Packer` for options.
"""
packer = Packer(**kwargs)
stream.write(packer.pack(o)) | python | def pack(o, stream, **kwargs):
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Pack object `o` and write it to `stream`
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pandas-dev/pandas | pandas/core/internals/concat.py | get_mgr_concatenation_plan | def get_mgr_concatenation_plan(mgr, indexers):
"""
Construct concatenation plan for given block manager and indexers.
Parameters
----------
mgr : BlockManager
indexers : dict of {axis: indexer}
Returns
-------
plan : list of (BlockPlacement, JoinUnit) tuples
"""
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"""
Construct concatenation plan for given block manager and indexers.
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----------
mgr : BlockManager
indexers : dict of {axis: indexer}
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plan : list of (BlockPlacement, JoinUnit) tuples
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pandas-dev/pandas | pandas/core/internals/concat.py | concatenate_join_units | def concatenate_join_units(join_units, concat_axis, copy):
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"""
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pandas-dev/pandas | pandas/core/internals/concat.py | get_empty_dtype_and_na | def get_empty_dtype_and_na(join_units):
"""
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Returned N/A value may be None which means there was no casting involved.
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dtype
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dtype
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pandas-dev/pandas | pandas/core/internals/concat.py | is_uniform_join_units | def is_uniform_join_units(join_units):
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"""
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pandas-dev/pandas | pandas/core/internals/concat.py | trim_join_unit | def trim_join_unit(join_unit, length):
"""
Reduce join_unit's shape along item axis to length.
Extra items that didn't fit are returned as a separate block.
"""
if 0 not in join_unit.indexers:
extra_indexers = join_unit.indexers
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extra_block ... | python | def trim_join_unit(join_unit, length):
"""
Reduce join_unit's shape along item axis to length.
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pandas-dev/pandas | pandas/core/internals/concat.py | combine_concat_plans | def combine_concat_plans(plans, concat_axis):
"""
Combine multiple concatenation plans into one.
existing_plan is updated in-place.
"""
if len(plans) == 1:
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pandas-dev/pandas | pandas/io/stata.py | _cast_to_stata_types | def _cast_to_stata_types(data):
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pandas-dev/pandas | pandas/io/stata.py | _pad_bytes_new | def _pad_bytes_new(name, length):
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pandas-dev/pandas | pandas/io/stata.py | StataReader._setup_dtype | def _setup_dtype(self):
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pandas-dev/pandas | pandas/io/stata.py | StataReader._do_convert_categoricals | def _do_convert_categoricals(self, data, value_label_dict, lbllist,
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pandas-dev/pandas | pandas/io/stata.py | StataWriter._write | def _write(self, to_write):
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pandas-dev/pandas | pandas/io/stata.py | StataWriter._prepare_categoricals | def _prepare_categoricals(self, data):
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pandas-dev/pandas | pandas/io/stata.py | StataWriter._check_column_names | def _check_column_names(self, data):
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"""
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pandas-dev/pandas | pandas/io/stata.py | StataWriter._close | def _close(self):
"""
Close the file if it was created by the writer.
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then leave this file open for the caller to close. In either case,
attempt to flush the file contents to ensure they are written to disk
... | python | def _close(self):
"""
Close the file if it was created by the writer.
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then leave this file open for the caller to close. In either case,
attempt to flush the file contents to ensure they are written to disk
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pandas-dev/pandas | pandas/io/stata.py | StataStrLWriter.generate_table | def generate_table(self):
"""
Generates the GSO lookup table for the DataFRame
Returns
-------
gso_table : OrderedDict
Ordered dictionary using the string found as keys
and their lookup position (v,o) as values
gso_df : DataFrame
DataF... | python | def generate_table(self):
"""
Generates the GSO lookup table for the DataFRame
Returns
-------
gso_table : OrderedDict
Ordered dictionary using the string found as keys
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pandas-dev/pandas | pandas/io/stata.py | StataStrLWriter.generate_blob | def generate_blob(self, gso_table):
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gso_table : OrderedDict
Ordered dictionary (str, vo)
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Generates the binary blob of GSOs that is written to the dta file.
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gso_table : OrderedDict
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pandas-dev/pandas | pandas/io/stata.py | StataWriter117._tag | def _tag(val, tag):
"""Surround val with <tag></tag>"""
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pandas-dev/pandas | pandas/io/stata.py | StataWriter117._write_header | def _write_header(self, data_label=None, time_stamp=None):
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pandas-dev/pandas | pandas/io/stata.py | StataWriter117._write_map | def _write_map(self):
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pandas-dev/pandas | pandas/io/stata.py | StataWriter117._update_strl_names | def _update_strl_names(self):
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pandas-dev/pandas | pandas/io/stata.py | StataWriter117._convert_strls | def _convert_strls(self, data):
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pandas-dev/pandas | pandas/plotting/_converter.py | register | def register(explicit=True):
"""
Register Pandas Formatters and Converters with matplotlib
This function modifies the global ``matplotlib.units.registry``
dictionary. Pandas adds custom converters for
* pd.Timestamp
* pd.Period
* np.datetime64
* datetime.datetime
* datetime.date
... | python | def register(explicit=True):
"""
Register Pandas Formatters and Converters with matplotlib
This function modifies the global ``matplotlib.units.registry``
dictionary. Pandas adds custom converters for
* pd.Timestamp
* pd.Period
* np.datetime64
* datetime.datetime
* datetime.date
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pandas-dev/pandas | pandas/plotting/_converter.py | deregister | def deregister():
"""
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"""
Remove pandas' formatters and converters
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pandas-dev/pandas | pandas/plotting/_converter.py | _dt_to_float_ordinal | def _dt_to_float_ordinal(dt):
"""
Convert :mod:`datetime` to the Gregorian date as UTC float days,
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"""
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... | python | def _dt_to_float_ordinal(dt):
"""
Convert :mod:`datetime` to the Gregorian date as UTC float days,
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"""
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pandas-dev/pandas | pandas/plotting/_converter.py | _get_default_annual_spacing | def _get_default_annual_spacing(nyears):
"""
Returns a default spacing between consecutive ticks for annual data.
"""
if nyears < 11:
(min_spacing, maj_spacing) = (1, 1)
elif nyears < 20:
(min_spacing, maj_spacing) = (1, 2)
elif nyears < 50:
(min_spacing, maj_spacing) = (... | python | def _get_default_annual_spacing(nyears):
"""
Returns a default spacing between consecutive ticks for annual data.
"""
if nyears < 11:
(min_spacing, maj_spacing) = (1, 1)
elif nyears < 20:
(min_spacing, maj_spacing) = (1, 2)
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pandas-dev/pandas | pandas/plotting/_converter.py | period_break | def period_break(dates, period):
"""
Returns the indices where the given period changes.
Parameters
----------
dates : PeriodIndex
Array of intervals to monitor.
period : string
Name of the period to monitor.
"""
current = getattr(dates, period)
previous = getattr(da... | python | def period_break(dates, period):
"""
Returns the indices where the given period changes.
Parameters
----------
dates : PeriodIndex
Array of intervals to monitor.
period : string
Name of the period to monitor.
"""
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pandas-dev/pandas | pandas/plotting/_converter.py | has_level_label | def has_level_label(label_flags, vmin):
"""
Returns true if the ``label_flags`` indicate there is at least one label
for this level.
if the minimum view limit is not an exact integer, then the first tick
label won't be shown, so we must adjust for that.
"""
if label_flags.size == 0 or (labe... | python | def has_level_label(label_flags, vmin):
"""
Returns true if the ``label_flags`` indicate there is at least one label
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if the minimum view limit is not an exact integer, then the first tick
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pandas-dev/pandas | pandas/plotting/_converter.py | DatetimeConverter.axisinfo | def axisinfo(unit, axis):
"""
Return the :class:`~matplotlib.units.AxisInfo` for *unit*.
*unit* is a tzinfo instance or None.
The *axis* argument is required but not used.
"""
tz = unit
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majfmt = PandasAutoDateFormatt... | python | def axisinfo(unit, axis):
"""
Return the :class:`~matplotlib.units.AxisInfo` for *unit*.
*unit* is a tzinfo instance or None.
The *axis* argument is required but not used.
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'Pick the best locator based on a distance.'
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delta = relativedelta(dmax, dmin)
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num_sec = (delta.hours * 60.0 + delta.minutes) * 60.0 + delta.secon... | python | def get_locator(self, dmin, dmax):
'Pick the best locator based on a distance.'
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delta = relativedelta(dmax, dmin)
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"""
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# TODO(wesm): unused?
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"""
Set the view limits to include the data range.
"""
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pandas-dev/pandas | pandas/plotting/_converter.py | TimeSeries_DateLocator._get_default_locs | def _get_default_locs(self, vmin, vmax):
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if self.plot_obj.date_axis_info is None:
self.plot_obj.date_axis_info = self.finder(vmin, vmax, self.freq)
locator = self.plot_obj.date_axis_info
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"Returns the default locations of ticks."
if self.plot_obj.date_axis_info is None:
self.plot_obj.date_axis_info = self.finder(vmin, vmax, self.freq)
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pandas-dev/pandas | pandas/plotting/_converter.py | TimeSeries_DateLocator.autoscale | def autoscale(self):
"""
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pandas-dev/pandas | pandas/plotting/_converter.py | TimeSeries_DateFormatter._set_default_format | def _set_default_format(self, vmin, vmax):
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pandas-dev/pandas | pandas/plotting/_converter.py | TimeSeries_DateFormatter.set_locs | def set_locs(self, locs):
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self.locs = locs
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pandas-dev/pandas | pandas/io/json/table_schema.py | set_default_names | def set_default_names(data):
"""Sets index names to 'index' for regular, or 'level_x' for Multi"""
if com._all_not_none(*data.index.names):
nms = data.index.names
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"""Sets index names to 'index' for regular, or 'level_x' for Multi"""
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pandas-dev/pandas | pandas/io/json/table_schema.py | convert_json_field_to_pandas_type | def convert_json_field_to_pandas_type(field):
"""
Converts a JSON field descriptor into its corresponding NumPy / pandas type
Parameters
----------
field
A JSON field descriptor
Returns
-------
dtype
Raises
-----
ValueError
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"""
Converts a JSON field descriptor into its corresponding NumPy / pandas type
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field
A JSON field descriptor
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dtype
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pandas-dev/pandas | pandas/io/json/table_schema.py | build_table_schema | def build_table_schema(data, index=True, primary_key=None, version=True):
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Create a Table schema from ``data``.
Parameters
----------
data : Series, DataFrame
index : bool, default True
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"""
Create a Table schema from ``data``.
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data : Series, DataFrame
index : bool, default True
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pandas-dev/pandas | pandas/io/json/table_schema.py | parse_table_schema | def parse_table_schema(json, precise_float):
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json :
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Flag controlling precision when decoding string to double values, as
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... | python | def parse_table_schema(json, precise_float):
"""
Builds a DataFrame from a given schema
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json :
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pandas-dev/pandas | pandas/core/ops.py | get_op_result_name | def get_op_result_name(left, right):
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left : {Series, Index}
right : object
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Find the appropriate name to pin to an operation result. This result
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pandas-dev/pandas | pandas/core/ops.py | _maybe_match_name | def _maybe_match_name(a, b):
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pandas-dev/pandas | pandas/core/ops.py | maybe_upcast_for_op | def maybe_upcast_for_op(obj):
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Cast non-pandas objects to pandas types to unify behavior of arithmetic
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obj: object
Returns
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out : object
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"""
Cast non-pandas objects to pandas types to unify behavior of arithmetic
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obj: object
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pandas-dev/pandas | pandas/core/ops.py | make_invalid_op | def make_invalid_op(name):
"""
Return a binary method that always raises a TypeError.
Parameters
----------
name : str
Returns
-------
invalid_op : function
"""
def invalid_op(self, other=None):
raise TypeError("cannot perform {name} with this index type: "
... | python | def make_invalid_op(name):
"""
Return a binary method that always raises a TypeError.
Parameters
----------
name : str
Returns
-------
invalid_op : function
"""
def invalid_op(self, other=None):
raise TypeError("cannot perform {name} with this index type: "
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pandas-dev/pandas | pandas/core/ops.py | _gen_eval_kwargs | def _gen_eval_kwargs(name):
"""
Find the keyword arguments to pass to numexpr for the given operation.
Parameters
----------
name : str
Returns
-------
eval_kwargs : dict
Examples
--------
>>> _gen_eval_kwargs("__add__")
{}
>>> _gen_eval_kwargs("rtruediv")
{'r... | python | def _gen_eval_kwargs(name):
"""
Find the keyword arguments to pass to numexpr for the given operation.
Parameters
----------
name : str
Returns
-------
eval_kwargs : dict
Examples
--------
>>> _gen_eval_kwargs("__add__")
{}
>>> _gen_eval_kwargs("rtruediv")
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pandas-dev/pandas | pandas/core/ops.py | _gen_fill_zeros | def _gen_fill_zeros(name):
"""
Find the appropriate fill value to use when filling in undefined values
in the results of the given operation caused by operating on
(generally dividing by) zero.
Parameters
----------
name : str
Returns
-------
fill_value : {None, np.nan, np.inf}... | python | def _gen_fill_zeros(name):
"""
Find the appropriate fill value to use when filling in undefined values
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Parameters
----------
name : str
Returns
-------
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pandas-dev/pandas | pandas/core/ops.py | _get_opstr | def _get_opstr(op, cls):
"""
Find the operation string, if any, to pass to numexpr for this
operation.
Parameters
----------
op : binary operator
cls : class
Returns
-------
op_str : string or None
"""
# numexpr is available for non-sparse classes
subtyp = getattr(c... | python | def _get_opstr(op, cls):
"""
Find the operation string, if any, to pass to numexpr for this
operation.
Parameters
----------
op : binary operator
cls : class
Returns
-------
op_str : string or None
"""
# numexpr is available for non-sparse classes
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pandas-dev/pandas | pandas/core/ops.py | _get_op_name | def _get_op_name(op, special):
"""
Find the name to attach to this method according to conventions
for special and non-special methods.
Parameters
----------
op : binary operator
special : bool
Returns
-------
op_name : str
"""
opname = op.__name__.strip('_')
if spe... | python | def _get_op_name(op, special):
"""
Find the name to attach to this method according to conventions
for special and non-special methods.
Parameters
----------
op : binary operator
special : bool
Returns
-------
op_name : str
"""
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pandas-dev/pandas | pandas/core/ops.py | _make_flex_doc | def _make_flex_doc(op_name, typ):
"""
Make the appropriate substitutions for the given operation and class-typ
into either _flex_doc_SERIES or _flex_doc_FRAME to return the docstring
to attach to a generated method.
Parameters
----------
op_name : str {'__add__', '__sub__', ... '__eq__', '_... | python | def _make_flex_doc(op_name, typ):
"""
Make the appropriate substitutions for the given operation and class-typ
into either _flex_doc_SERIES or _flex_doc_FRAME to return the docstring
to attach to a generated method.
Parameters
----------
op_name : str {'__add__', '__sub__', ... '__eq__', '_... | [
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pandas-dev/pandas | pandas/core/ops.py | fill_binop | def fill_binop(left, right, fill_value):
"""
If a non-None fill_value is given, replace null entries in left and right
with this value, but only in positions where _one_ of left/right is null,
not both.
Parameters
----------
left : array-like
right : array-like
fill_value : object
... | python | def fill_binop(left, right, fill_value):
"""
If a non-None fill_value is given, replace null entries in left and right
with this value, but only in positions where _one_ of left/right is null,
not both.
Parameters
----------
left : array-like
right : array-like
fill_value : object
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pandas-dev/pandas | pandas/core/ops.py | mask_cmp_op | def mask_cmp_op(x, y, op, allowed_types):
"""
Apply the function `op` to only non-null points in x and y.
Parameters
----------
x : array-like
y : array-like
op : binary operation
allowed_types : class or tuple of classes
Returns
-------
result : ndarray[bool]
"""
#... | python | def mask_cmp_op(x, y, op, allowed_types):
"""
Apply the function `op` to only non-null points in x and y.
Parameters
----------
x : array-like
y : array-like
op : binary operation
allowed_types : class or tuple of classes
Returns
-------
result : ndarray[bool]
"""
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pandas-dev/pandas | pandas/core/ops.py | masked_arith_op | def masked_arith_op(x, y, op):
"""
If the given arithmetic operation fails, attempt it again on
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Parameters
----------
x : np.ndarray
y : np.ndarray, Series, Index
op : binary operator
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# For Series `x` is 1D so ravel() is a no... | python | def masked_arith_op(x, y, op):
"""
If the given arithmetic operation fails, attempt it again on
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x : np.ndarray
y : np.ndarray, Series, Index
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pandas-dev/pandas | pandas/core/ops.py | invalid_comparison | def invalid_comparison(left, right, op):
"""
If a comparison has mismatched types and is not necessarily meaningful,
follow python3 conventions by:
- returning all-False for equality
- returning all-True for inequality
- raising TypeError otherwise
Parameters
----------
... | python | def invalid_comparison(left, right, op):
"""
If a comparison has mismatched types and is not necessarily meaningful,
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- returning all-False for equality
- returning all-True for inequality
- raising TypeError otherwise
Parameters
----------
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pandas-dev/pandas | pandas/core/ops.py | should_series_dispatch | def should_series_dispatch(left, right, op):
"""
Identify cases where a DataFrame operation should dispatch to its
Series counterpart.
Parameters
----------
left : DataFrame
right : DataFrame
op : binary operator
Returns
-------
override : bool
"""
if left._is_mixed... | python | def should_series_dispatch(left, right, op):
"""
Identify cases where a DataFrame operation should dispatch to its
Series counterpart.
Parameters
----------
left : DataFrame
right : DataFrame
op : binary operator
Returns
-------
override : bool
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pandas-dev/pandas | pandas/core/ops.py | dispatch_to_series | def dispatch_to_series(left, right, func, str_rep=None, axis=None):
"""
Evaluate the frame operation func(left, right) by evaluating
column-by-column, dispatching to the Series implementation.
Parameters
----------
left : DataFrame
right : scalar or DataFrame
func : arithmetic or compar... | python | def dispatch_to_series(left, right, func, str_rep=None, axis=None):
"""
Evaluate the frame operation func(left, right) by evaluating
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pandas-dev/pandas | pandas/core/ops.py | dispatch_to_index_op | def dispatch_to_index_op(op, left, right, index_class):
"""
Wrap Series left in the given index_class to delegate the operation op
to the index implementation. DatetimeIndex and TimedeltaIndex perform
type checking, timezone handling, overflow checks, etc.
Parameters
----------
op : binary... | python | def dispatch_to_index_op(op, left, right, index_class):
"""
Wrap Series left in the given index_class to delegate the operation op
to the index implementation. DatetimeIndex and TimedeltaIndex perform
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type checking, timezone handling, overflow checks, etc.
Parameters
----------
op : binary operator (operator.add, operator.sub, ...)
left : Series
ri... | [
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"ch... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/ops.py#L1349-L1380 | train |
pandas-dev/pandas | pandas/core/ops.py | dispatch_to_extension_op | def dispatch_to_extension_op(op, left, right):
"""
Assume that left or right is a Series backed by an ExtensionArray,
apply the operator defined by op.
"""
# The op calls will raise TypeError if the op is not defined
# on the ExtensionArray
# unbox Series and Index to arrays
if isinsta... | python | def dispatch_to_extension_op(op, left, right):
"""
Assume that left or right is a Series backed by an ExtensionArray,
apply the operator defined by op.
"""
# The op calls will raise TypeError if the op is not defined
# on the ExtensionArray
# unbox Series and Index to arrays
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] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/ops.py#L1383-L1410 | train |
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