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dfZt ddgZuddhZvy)z
|
Module contains tools for processing files into DataFrames or other objects
|
|
GH#48849 provides a convenient way of deprecating keyword arguments
|
é )Ú annotations)ÚabcÚ defaultdictN)Úfill)ÚIOÚ TYPE_CHECKINGÚAnyÚCallableÚLiteralÚ
|
NamedTupleÚ TypedDictÚoverload)Úusing_copy_on_write)Úlib)Ú STR_NA_VALUES)ÚAbstractMethodErrorÚ ParserWarning)ÚAppender)Úfind_stack_level)Úcheck_dtype_backend)Ú is_file_likeÚis_floatÚ is_hashableÚ
|
is_integerÚ is_list_likeÚ pandas_dtype)ÚSeries)Ú DataFrame)Ú
|
RangeIndex)Ú _shared_docs)Ú IOHandlesÚ
|
get_handleÚstringify_pathÚvalidate_header_arg)ÚArrowParserWrapper)Ú
|
ParserBaseÚ is_index_colÚparser_defaults)ÚCParserWrapper)ÚFixedWidthFieldParserÚ PythonParser)ÚHashableÚIterableÚMappingÚSequence)Ú TracebackType)
|
ÚCompressionOptionsÚ CSVEngineÚDtypeArgÚ DtypeBackendÚFilePathÚ
|
IndexLabelÚ ReadCsvBufferÚSelfÚStorageOptionsÚUsecolsArgTypea¯
|
{summary}
|
|
Also supports optionally iterating or breaking of the file
|
into chunks.
|
|
Additional help can be found in the online docs for
|
`IO Tools <https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html>`_.
|
|
Parameters
|
----------
|
filepath_or_buffer : str, path object or file-like object
|
Any valid string path is acceptable. The string could be a URL. Valid
|
URL schemes include http, ftp, s3, gs, and file. For file URLs, a host is
|
expected. A local file could be: file://localhost/path/to/table.csv.
|
|
If you want to pass in a path object, pandas accepts any ``os.PathLike``.
|
|
By file-like object, we refer to objects with a ``read()`` method, such as
|
a file handle (e.g. via builtin ``open`` function) or ``StringIO``.
|
sep : str, default {_default_sep}
|
Character or regex pattern to treat as the delimiter. If ``sep=None``, the
|
C engine cannot automatically detect
|
the separator, but the Python parsing engine can, meaning the latter will
|
be used and automatically detect the separator from only the first valid
|
row of the file by Python's builtin sniffer tool, ``csv.Sniffer``.
|
In addition, separators longer than 1 character and different from
|
``'\s+'`` will be interpreted as regular expressions and will also force
|
the use of the Python parsing engine. Note that regex delimiters are prone
|
to ignoring quoted data. Regex example: ``'\r\t'``.
|
delimiter : str, optional
|
Alias for ``sep``.
|
header : int, Sequence of int, 'infer' or None, default 'infer'
|
Row number(s) containing column labels and marking the start of the
|
data (zero-indexed). Default behavior is to infer the column names: if no ``names``
|
are passed the behavior is identical to ``header=0`` and column
|
names are inferred from the first line of the file, if column
|
names are passed explicitly to ``names`` then the behavior is identical to
|
``header=None``. Explicitly pass ``header=0`` to be able to
|
replace existing names. The header can be a list of integers that
|
specify row locations for a :class:`~pandas.MultiIndex` on the columns
|
e.g. ``[0, 1, 3]``. Intervening rows that are not specified will be
|
skipped (e.g. 2 in this example is skipped). Note that this
|
parameter ignores commented lines and empty lines if
|
``skip_blank_lines=True``, so ``header=0`` denotes the first line of
|
data rather than the first line of the file.
|
names : Sequence of Hashable, optional
|
Sequence of column labels to apply. If the file contains a header row,
|
then you should explicitly pass ``header=0`` to override the column names.
|
Duplicates in this list are not allowed.
|
index_col : Hashable, Sequence of Hashable or False, optional
|
Column(s) to use as row label(s), denoted either by column labels or column
|
indices. If a sequence of labels or indices is given, :class:`~pandas.MultiIndex`
|
will be formed for the row labels.
|
|
Note: ``index_col=False`` can be used to force pandas to *not* use the first
|
column as the index, e.g., when you have a malformed file with delimiters at
|
the end of each line.
|
usecols : Sequence of Hashable or Callable, optional
|
Subset of columns to select, denoted either by column labels or column indices.
|
If list-like, all elements must either
|
be positional (i.e. integer indices into the document columns) or strings
|
that correspond to column names provided either by the user in ``names`` or
|
inferred from the document header row(s). If ``names`` are given, the document
|
header row(s) are not taken into account. For example, a valid list-like
|
``usecols`` parameter would be ``[0, 1, 2]`` or ``['foo', 'bar', 'baz']``.
|
Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``.
|
To instantiate a :class:`~pandas.DataFrame` from ``data`` with element order
|
preserved use ``pd.read_csv(data, usecols=['foo', 'bar'])[['foo', 'bar']]``
|
for columns in ``['foo', 'bar']`` order or
|
``pd.read_csv(data, usecols=['foo', 'bar'])[['bar', 'foo']]``
|
for ``['bar', 'foo']`` order.
|
|
If callable, the callable function will be evaluated against the column
|
names, returning names where the callable function evaluates to ``True``. An
|
example of a valid callable argument would be ``lambda x: x.upper() in
|
['AAA', 'BBB', 'DDD']``. Using this parameter results in much faster
|
parsing time and lower memory usage.
|
dtype : dtype or dict of {{Hashable : dtype}}, optional
|
Data type(s) to apply to either the whole dataset or individual columns.
|
E.g., ``{{'a': np.float64, 'b': np.int32, 'c': 'Int64'}}``
|
Use ``str`` or ``object`` together with suitable ``na_values`` settings
|
to preserve and not interpret ``dtype``.
|
If ``converters`` are specified, they will be applied INSTEAD
|
of ``dtype`` conversion.
|
|
.. versionadded:: 1.5.0
|
|
Support for ``defaultdict`` was added. Specify a ``defaultdict`` as input where
|
the default determines the ``dtype`` of the columns which are not explicitly
|
listed.
|
engine : {{'c', 'python', 'pyarrow'}}, optional
|
Parser engine to use. The C and pyarrow engines are faster, while the python engine
|
is currently more feature-complete. Multithreading is currently only supported by
|
the pyarrow engine.
|
|
.. versionadded:: 1.4.0
|
|
The 'pyarrow' engine was added as an *experimental* engine, and some features
|
are unsupported, or may not work correctly, with this engine.
|
converters : dict of {{Hashable : Callable}}, optional
|
Functions for converting values in specified columns. Keys can either
|
be column labels or column indices.
|
true_values : list, optional
|
Values to consider as ``True`` in addition to case-insensitive variants of 'True'.
|
false_values : list, optional
|
Values to consider as ``False`` in addition to case-insensitive variants of 'False'.
|
skipinitialspace : bool, default False
|
Skip spaces after delimiter.
|
skiprows : int, list of int or Callable, optional
|
Line numbers to skip (0-indexed) or number of lines to skip (``int``)
|
at the start of the file.
|
|
If callable, the callable function will be evaluated against the row
|
indices, returning ``True`` if the row should be skipped and ``False`` otherwise.
|
An example of a valid callable argument would be ``lambda x: x in [0, 2]``.
|
skipfooter : int, default 0
|
Number of lines at bottom of file to skip (Unsupported with ``engine='c'``).
|
nrows : int, optional
|
Number of rows of file to read. Useful for reading pieces of large files.
|
na_values : Hashable, Iterable of Hashable or dict of {{Hashable : Iterable}}, optional
|
Additional strings to recognize as ``NA``/``NaN``. If ``dict`` passed, specific
|
per-column ``NA`` values. By default the following values are interpreted as
|
``NaN``: " z", "éF z )Úsubsequent_indentaÚ- ".
|
|
keep_default_na : bool, default True
|
Whether or not to include the default ``NaN`` values when parsing the data.
|
Depending on whether ``na_values`` is passed in, the behavior is as follows:
|
|
* If ``keep_default_na`` is ``True``, and ``na_values`` are specified, ``na_values``
|
is appended to the default ``NaN`` values used for parsing.
|
* If ``keep_default_na`` is ``True``, and ``na_values`` are not specified, only
|
the default ``NaN`` values are used for parsing.
|
* If ``keep_default_na`` is ``False``, and ``na_values`` are specified, only
|
the ``NaN`` values specified ``na_values`` are used for parsing.
|
* If ``keep_default_na`` is ``False``, and ``na_values`` are not specified, no
|
strings will be parsed as ``NaN``.
|
|
Note that if ``na_filter`` is passed in as ``False``, the ``keep_default_na`` and
|
``na_values`` parameters will be ignored.
|
na_filter : bool, default True
|
Detect missing value markers (empty strings and the value of ``na_values``). In
|
data without any ``NA`` values, passing ``na_filter=False`` can improve the
|
performance of reading a large file.
|
verbose : bool, default False
|
Indicate number of ``NA`` values placed in non-numeric columns.
|
|
.. deprecated:: 2.2.0
|
skip_blank_lines : bool, default True
|
If ``True``, skip over blank lines rather than interpreting as ``NaN`` values.
|
parse_dates : bool, list of Hashable, list of lists or dict of {{Hashable : list}}, default False
|
The behavior is as follows:
|
|
* ``bool``. If ``True`` -> try parsing the index. Note: Automatically set to
|
``True`` if ``date_format`` or ``date_parser`` arguments have been passed.
|
* ``list`` of ``int`` or names. e.g. If ``[1, 2, 3]`` -> try parsing columns 1, 2, 3
|
each as a separate date column.
|
* ``list`` of ``list``. e.g. If ``[[1, 3]]`` -> combine columns 1 and 3 and parse
|
as a single date column. Values are joined with a space before parsing.
|
* ``dict``, e.g. ``{{'foo' : [1, 3]}}`` -> parse columns 1, 3 as date and call
|
result 'foo'. Values are joined with a space before parsing.
|
|
If a column or index cannot be represented as an array of ``datetime``,
|
say because of an unparsable value or a mixture of timezones, the column
|
or index will be returned unaltered as an ``object`` data type. For
|
non-standard ``datetime`` parsing, use :func:`~pandas.to_datetime` after
|
:func:`~pandas.read_csv`.
|
|
Note: A fast-path exists for iso8601-formatted dates.
|
infer_datetime_format : bool, default False
|
If ``True`` and ``parse_dates`` is enabled, pandas will attempt to infer the
|
format of the ``datetime`` strings in the columns, and if it can be inferred,
|
switch to a faster method of parsing them. In some cases this can increase
|
the parsing speed by 5-10x.
|
|
.. deprecated:: 2.0.0
|
A strict version of this argument is now the default, passing it has no effect.
|
|
keep_date_col : bool, default False
|
If ``True`` and ``parse_dates`` specifies combining multiple columns then
|
keep the original columns.
|
date_parser : Callable, optional
|
Function to use for converting a sequence of string columns to an array of
|
``datetime`` instances. The default uses ``dateutil.parser.parser`` to do the
|
conversion. pandas will try to call ``date_parser`` in three different ways,
|
advancing to the next if an exception occurs: 1) Pass one or more arrays
|
(as defined by ``parse_dates``) as arguments; 2) concatenate (row-wise) the
|
string values from the columns defined by ``parse_dates`` into a single array
|
and pass that; and 3) call ``date_parser`` once for each row using one or
|
more strings (corresponding to the columns defined by ``parse_dates``) as
|
arguments.
|
|
.. deprecated:: 2.0.0
|
Use ``date_format`` instead, or read in as ``object`` and then apply
|
:func:`~pandas.to_datetime` as-needed.
|
date_format : str or dict of column -> format, optional
|
Format to use for parsing dates when used in conjunction with ``parse_dates``.
|
The strftime to parse time, e.g. :const:`"%d/%m/%Y"`. See
|
`strftime documentation
|
<https://docs.python.org/3/library/datetime.html
|
#strftime-and-strptime-behavior>`_ for more information on choices, though
|
note that :const:`"%f"` will parse all the way up to nanoseconds.
|
You can also pass:
|
|
- "ISO8601", to parse any `ISO8601 <https://en.wikipedia.org/wiki/ISO_8601>`_
|
time string (not necessarily in exactly the same format);
|
- "mixed", to infer the format for each element individually. This is risky,
|
and you should probably use it along with `dayfirst`.
|
|
.. versionadded:: 2.0.0
|
dayfirst : bool, default False
|
DD/MM format dates, international and European format.
|
cache_dates : bool, default True
|
If ``True``, use a cache of unique, converted dates to apply the ``datetime``
|
conversion. May produce significant speed-up when parsing duplicate
|
date strings, especially ones with timezone offsets.
|
|
iterator : bool, default False
|
Return ``TextFileReader`` object for iteration or getting chunks with
|
``get_chunk()``.
|
chunksize : int, optional
|
Number of lines to read from the file per chunk. Passing a value will cause the
|
function to return a ``TextFileReader`` object for iteration.
|
See the `IO Tools docs
|
<https://pandas.pydata.org/pandas-docs/stable/io.html#io-chunking>`_
|
for more information on ``iterator`` and ``chunksize``.
|
|
{decompression_options}
|
|
.. versionchanged:: 1.4.0 Zstandard support.
|
|
thousands : str (length 1), optional
|
Character acting as the thousands separator in numerical values.
|
decimal : str (length 1), default '.'
|
Character to recognize as decimal point (e.g., use ',' for European data).
|
lineterminator : str (length 1), optional
|
Character used to denote a line break. Only valid with C parser.
|
quotechar : str (length 1), optional
|
Character used to denote the start and end of a quoted item. Quoted
|
items can include the ``delimiter`` and it will be ignored.
|
quoting : {{0 or csv.QUOTE_MINIMAL, 1 or csv.QUOTE_ALL, 2 or csv.QUOTE_NONNUMERIC, 3 or csv.QUOTE_NONE}}, default csv.QUOTE_MINIMAL
|
Control field quoting behavior per ``csv.QUOTE_*`` constants. Default is
|
``csv.QUOTE_MINIMAL`` (i.e., 0) which implies that only fields containing special
|
characters are quoted (e.g., characters defined in ``quotechar``, ``delimiter``,
|
or ``lineterminator``.
|
doublequote : bool, default True
|
When ``quotechar`` is specified and ``quoting`` is not ``QUOTE_NONE``, indicate
|
whether or not to interpret two consecutive ``quotechar`` elements INSIDE a
|
field as a single ``quotechar`` element.
|
escapechar : str (length 1), optional
|
Character used to escape other characters.
|
comment : str (length 1), optional
|
Character indicating that the remainder of line should not be parsed.
|
If found at the beginning
|
of a line, the line will be ignored altogether. This parameter must be a
|
single character. Like empty lines (as long as ``skip_blank_lines=True``),
|
fully commented lines are ignored by the parameter ``header`` but not by
|
``skiprows``. For example, if ``comment='#'``, parsing
|
``#empty\na,b,c\n1,2,3`` with ``header=0`` will result in ``'a,b,c'`` being
|
treated as the header.
|
encoding : str, optional, default 'utf-8'
|
Encoding to use for UTF when reading/writing (ex. ``'utf-8'``). `List of Python
|
standard encodings
|
<https://docs.python.org/3/library/codecs.html#standard-encodings>`_ .
|
|
encoding_errors : str, optional, default 'strict'
|
How encoding errors are treated. `List of possible values
|
<https://docs.python.org/3/library/codecs.html#error-handlers>`_ .
|
|
.. versionadded:: 1.3.0
|
|
dialect : str or csv.Dialect, optional
|
If provided, this parameter will override values (default or not) for the
|
following parameters: ``delimiter``, ``doublequote``, ``escapechar``,
|
``skipinitialspace``, ``quotechar``, and ``quoting``. If it is necessary to
|
override values, a ``ParserWarning`` will be issued. See ``csv.Dialect``
|
documentation for more details.
|
on_bad_lines : {{'error', 'warn', 'skip'}} or Callable, default 'error'
|
Specifies what to do upon encountering a bad line (a line with too many fields).
|
Allowed values are :
|
|
- ``'error'``, raise an Exception when a bad line is encountered.
|
- ``'warn'``, raise a warning when a bad line is encountered and skip that line.
|
- ``'skip'``, skip bad lines without raising or warning when they are encountered.
|
|
.. versionadded:: 1.3.0
|
|
.. versionadded:: 1.4.0
|
|
- Callable, function with signature
|
``(bad_line: list[str]) -> list[str] | None`` that will process a single
|
bad line. ``bad_line`` is a list of strings split by the ``sep``.
|
If the function returns ``None``, the bad line will be ignored.
|
If the function returns a new ``list`` of strings with more elements than
|
expected, a ``ParserWarning`` will be emitted while dropping extra elements.
|
Only supported when ``engine='python'``
|
|
.. versionchanged:: 2.2.0
|
|
- Callable, function with signature
|
as described in `pyarrow documentation
|
<https://arrow.apache.org/docs/python/generated/pyarrow.csv.ParseOptions.html
|
#pyarrow.csv.ParseOptions.invalid_row_handler>`_ when ``engine='pyarrow'``
|
|
delim_whitespace : bool, default False
|
Specifies whether or not whitespace (e.g. ``' '`` or ``'\t'``) will be
|
used as the ``sep`` delimiter. Equivalent to setting ``sep='\s+'``. If this option
|
is set to ``True``, nothing should be passed in for the ``delimiter``
|
parameter.
|
|
.. deprecated:: 2.2.0
|
Use ``sep="\s+"`` instead.
|
low_memory : bool, default True
|
Internally process the file in chunks, resulting in lower memory use
|
while parsing, but possibly mixed type inference. To ensure no mixed
|
types either set ``False``, or specify the type with the ``dtype`` parameter.
|
Note that the entire file is read into a single :class:`~pandas.DataFrame`
|
regardless, use the ``chunksize`` or ``iterator`` parameter to return the data in
|
chunks. (Only valid with C parser).
|
memory_map : bool, default False
|
If a filepath is provided for ``filepath_or_buffer``, map the file object
|
directly onto memory and access the data directly from there. Using this
|
option can improve performance because there is no longer any I/O overhead.
|
float_precision : {{'high', 'legacy', 'round_trip'}}, optional
|
Specifies which converter the C engine should use for floating-point
|
values. The options are ``None`` or ``'high'`` for the ordinary converter,
|
``'legacy'`` for the original lower precision pandas converter, and
|
``'round_trip'`` for the round-trip converter.
|
|
{storage_options}
|
|
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
Returns
|
-------
|
DataFrame or TextFileReader
|
A comma-separated values (csv) file is returned as two-dimensional
|
data structure with labeled axes.
|
|
See Also
|
--------
|
DataFrame.to_csv : Write DataFrame to a comma-separated values (csv) file.
|
{see_also_func_name} : {see_also_func_summary}
|
read_fwf : Read a table of fixed-width formatted lines into DataFrame.
|
|
Examples
|
--------
|
>>> pd.{func_name}('data.csv') # doctest: +SKIP
|
c ó@ e Zd ZU ded< ded< ded< ded< ded< y )
|
Ú_C_Parser_DefaultsúLiteral[False]Údelim_whitespaceú Literal[True]Ú na_filterÚ
|
low_memoryÚ
|
memory_mapÚNoneÚfloat_precisionN©Ú__name__Ú
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Ø$Ó$Ø Ó Ø Ó Ø Ó ØÔrM r> FT)r@ rB rC rD rF Ú_c_parser_defaultsc ó, e Zd ZU ded< ded< ded< y)Ú _Fwf_DefaultszLiteral['infer']Úcolspecsz Literal[100]Ú infer_nrowsrE ÚwidthsNrG rL rM rN rQ rQ Ý s
Ø Ó Ø Ó Ø LrM rQ Úinferéd )rR rS rT Ú _fwf_defaultsÚ
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skipfooterrC rF > ÚnrowsÚcommentÚdialectÚquotingÚverboseÚdayfirstÚiteratorÚ chunksizeÚ thousandsÚ
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convertersrC rD rX ÚlineterminatorrF r@ Úskipinitialspacec ó" e Zd ZU ded< ded< y)Ú_DeprecationConfigr Ú default_valueú
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ØÓØ OrM rf .c ó y ©NrL ©ÚnameÚvalÚmin_vals rN Úvalidate_integerrp ó àrM c ó y rk rL rl s rN rp rp rq rM c ó y rk rL rl s rN rp rp
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rq rM c óÞ ||S d| dd|d}t |« r/t |« |k7 r t |« t |« }t |« S t |« r||k\ s t |« t |« S )a½
|
Checks whether the 'name' parameter for parsing is either
|
an integer OR float that can SAFELY be cast to an integer
|
without losing accuracy. Raises a ValueError if that is
|
not the case.
|
|
Parameters
|
----------
|
name : str
|
Parameter name (used for error reporting)
|
val : int or float
|
The value to check
|
min_val : int
|
Minimum allowed value (val < min_val will result in a ValueError)
|
ú'Úsz' must be an integer >=Úd)r ÚintÚ
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ValueErrorr )rm rn ro ri s rN rp rp sw ð$ {Ø
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à d1XÐ,¨W°Q¨KÐ
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|
j « s t d« yyy)aZ
|
Raise ValueError if the `names` parameter contains duplicates or has an
|
invalid data type.
|
|
Parameters
|
----------
|
names : array-like or None
|
An array containing a list of the names used for the output DataFrame.
|
|
Raises
|
------
|
ValueError
|
If names are not unique or are not ordered (e.g. set).
|
Nz Duplicate names are not allowed.F)Ú
|
allow_setsz&Names should be an ordered collection.)ÚlenÚsetry r Ú
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isinstancer ÚKeysView)Únamess rN Ú_validate_namesr / s[ ð ÐÜ u:S Z Ò (Ü Ð ?Ó@Ð @ä ¨5Õ 1´ZÀÄsÇ|Á|Ô5Tä Ð EÓFÐ Fð 6UÐ 1ð rM Úfilepath_or_bufferc óN |j dd« M|j dt j « t j u r|j dd« d|d< nd|d< |j dd« }|j dd« }|j d « d
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k( r|r t d « |t d « t d|d « }|j dd« }t |j dd« « t | fi |¤}|s|r|S |5 |j |« cddd« S # 1 sw Y yxY w)z Generic reader of line files.Ú parse_datesNÚ date_parserÚ date_formatFTr_ r` ÚengineÚpyarrowz@The 'iterator' option is not supported with the 'pyarrow' enginezAThe 'chunksize' option is not supported with the 'pyarrow' engineé rY r )Úgetr Ú
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r r^ r r_ r` r ra r rc r¡ r\ r¢ r£ rZ r¤ r¥ r[ r¦ r@ rC rD rF r§ r¨ s1 rN rª rª ± ó ðp rM )0r r r r r r r r rb r r rd r rX rY r r« rB r] r r r r r
r r^ r r_ r` r ra r rc r¡ r\ r¢ r£ rZ r¤ r¥ r[ r¦ r@ rC rD rF r§ r¨ c 0 ó y rk rL r s1 rN rª rª í r® rM c 0 ó y rk rL r s1 rN rª rª ) r® rM rª z8Read a comma-separated values (csv) file into DataFrame.Ú
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t t « ¬« nd}t « j « }2|2d = |2d = t |)||+|||*|d di|0¬« }3|2j |3« t! | |2« S )NzThe 'keep_date_col' keyword in pd.read_csv is deprecated and will be removed in a future version. Explicitly remove unwanted columns after parsing instead.©Ú
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= t |)||+|||*|d d i|0¬ « }2|1j |2« t | |1« S )NzThe 'keep_date_col' keyword in pd.read_table is deprecated and will be removed in a future version. Explicitly remove unwanted columns after parsing instead.r½ Fc 3 ó2 K | ] }t |« y wrk rÀ rÁ s rN rÄ z read_table.<locals>.<genexpr>@ s è ø Ò0UÀA´¸Q· Ñ0UùrÅ zSupport for nested sequences for 'parse_dates' in pd.read_table is deprecated. Combine the desired columns with pd.to_datetime after parsing instead.rÇ zThe 'delim_whitespace' keyword in pd.read_table is deprecated and will be removed in a future version. Use ``sep='\s+'`` insteadz]The 'verbose' keyword in pd.read_table is deprecated and will be removed in a future version.r r r ú rÉ ) r r rË rÌ rÍ r r rÎ rÒ rÓ rÔ rÕ r )3r r r r r r r r r rb r r rd r rX rY r r« rB r] r r r r r
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Mð KK Ô ä Ð# TÓ *Ð*rM )rR rT rS r¨ r` c ó y rk rL ©r rR rT rS r¨ r_ r` r s rN Úread_fwfrâ ó ð rM )rR rT rS r¨ r_ c ó y rk rL rá s rN râ râ rã rM )rR rT rS r¨ r_ r` c ó y rk rL rá s rN râ râ rã rM c óP | | t d« |dvr | t d« |&g d}}|D ] } |j ||| z f« || z } |J |j d« }
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Read a table of fixed-width formatted lines into DataFrame.
|
|
Also supports optionally iterating or breaking of the file
|
into chunks.
|
|
Additional help can be found in the `online docs for IO Tools
|
<https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html>`_.
|
|
Parameters
|
----------
|
filepath_or_buffer : str, path object, or file-like object
|
String, path object (implementing ``os.PathLike[str]``), or file-like
|
object implementing a text ``read()`` function.The string could be a URL.
|
Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is
|
expected. A local file could be:
|
``file://localhost/path/to/table.csv``.
|
colspecs : list of tuple (int, int) or 'infer'. optional
|
A list of tuples giving the extents of the fixed-width
|
fields of each line as half-open intervals (i.e., [from, to[ ).
|
String value 'infer' can be used to instruct the parser to try
|
detecting the column specifications from the first 100 rows of
|
the data which are not being skipped via skiprows (default='infer').
|
widths : list of int, optional
|
A list of field widths which can be used instead of 'colspecs' if
|
the intervals are contiguous.
|
infer_nrows : int, default 100
|
The number of rows to consider when letting the parser determine the
|
`colspecs`.
|
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
|
Back-end data type applied to the resultant :class:`DataFrame`
|
(still experimental). Behaviour is as follows:
|
|
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
|
(default).
|
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
|
DataFrame.
|
|
.. versionadded:: 2.0
|
|
**kwds : optional
|
Optional keyword arguments can be passed to ``TextFileReader``.
|
|
Returns
|
-------
|
DataFrame or TextFileReader
|
A comma-separated values (csv) file is returned as two-dimensional
|
data structure with labeled axes.
|
|
See Also
|
--------
|
DataFrame.to_csv : Write DataFrame to a comma-separated values (csv) file.
|
read_csv : Read a comma-separated values (csv) file into DataFrame.
|
|
Examples
|
--------
|
>>> pd.read_fwf('data.csv') # doctest: +SKIP
|
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k( rC| j j d d « d k( r$t t |« t « r d}d |vr|d z }t ||| j j d d « | j j dd « | j j dd« || j j dd« | j j dd « ¬« | _ | j J | j j }n |dk7 rdt |« }t |« || |fi | j ¤S # t $ r( | j | j j# « w xY w)N)r rî r rç zUnknown engine: z (valid options are ú)TÚrr FÚrbr r¤ r Úbr rD r¥ rº r§ )r¤ r rD Úis_textÚerrorsr§ rî z)Invalid file path or buffer object type: )r) r+ r% r* ry Úkeysr~ r rû r r# r r" rü Úhandler$ Ú Exceptionr )rÿ r r Úmappingr5 Úmoderi s rN rý zTextFileReader._make_engine8 s¿ ô Ü"Ü)Ü/ñ 0
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Converts lists of lists/tuples into DataFrames with proper type inference
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and optional (e.g. string to datetime) conversion. Also enables iterating
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lazily over chunks of large files
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|
Parameters
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----------
|
data : file-like object or list
|
delimiter : separator character to use
|
dialect : str or csv.Dialect instance, optional
|
Ignored if delimiter is longer than 1 character
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names : sequence, default
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header : int, default 0
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Row to use to parse column labels. Defaults to the first row. Prior
|
rows will be discarded
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index_col : int or list, optional
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Column or columns to use as the (possibly hierarchical) index
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has_index_names: bool, default False
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True if the cols defined in index_col have an index name and are
|
not in the header.
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na_values : scalar, str, list-like, or dict, optional
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Additional strings to recognize as NA/NaN.
|
keep_default_na : bool, default True
|
thousands : str, optional
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Thousands separator
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comment : str, optional
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Comment out remainder of line
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parse_dates : bool, default False
|
keep_date_col : bool, default False
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date_parser : function, optional
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|
.. deprecated:: 2.0.0
|
date_format : str or dict of column -> format, default ``None``
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|
.. versionadded:: 2.0.0
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skiprows : list of integers
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Row numbers to skip
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skipfooter : int
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Number of line at bottom of file to skip
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converters : dict, optional
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Dict of functions for converting values in certain columns. Keys can
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encoding : str, optional
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Encoding to use for UTF when reading/writing (ex. 'utf-8')
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float_precision : str, optional
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Specifies which converter the C engine should use for floating-point
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delimiter : str or object
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Alias for sep.
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:ð 6ð 5ð 6ð 2ð6ð ð6ð ð6ð ð6ð 3ð6ð ð6ð ð6ð ð 6ð Bð 6ð ð!6ð" ð#6ð$ ð%6ð, ð-6ð. "ð/6ð0 ð16ð2 2ð36ð4 0ð56ð6 (ð76ð8 *ð96ð: 2ð;6ð< ð=6ð> ð?6ð@ ðA6ðB ðC6ðD $ðE6ðF ðG6ðH ðI6ðJ ðK6ðL ðM6ðN ðO6ðP ðQ6ðR ðS6ðT ðU6ðV ðW6ðX ðY6ðZ &ð[6ð^ +ð_6ð` ða6ðb ðc6ðd 6ðe6ðf $ðg6ðh 0ði6ðj òk6ó
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ð6ðt
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØð Ø ØØ$'Ø Ø47Ø25Ø*-Ø,/Ø47ØØØà&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ-0ØØØ8;Ø&)Ø25ñk7ØLð7ð
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$ð7ð *ð 7ð
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:ð 7ð 5ð 7ð 2ð7ð ð7ð ð7ð ð7ð 3ð7ð ð7ð ð7ð ð 7ð Bð 7ð ð!7ð" ð#7ð$ ð%7ð, ð-7ð. ð/7ð0 "ð17ð2 ð37ð4 2ð57ð6 0ð77ð8 (ð97ð: *ð;7ð< 2ð=7ð> ð?7ð@ ðA7ðB ðC7ðD ðE7ðF $ðG7ðH ðI7ðJ ðK7ðL ðM7ðN ðO7ðP ðQ7ðR ðS7ðT ðU7ðV ðW7ðX ðY7ðZ ð[7ð\ &ð]7ð` +ða7ðb ðc7ðd ðe7ðf 6ðg7ðh $ði7ðj 0ðk7ðl òm7ó
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ð7ðv
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØð Ø ØØ$'Ø Ø47Ø25Ø*-Ø,/Ø47ØØØ "ØØ&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ-0ØØØ8;Ø&)Ø25ñk7ØLð7ð
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$ð7ð *ð 7ð
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:ð 7ð 5ð 7ð 2ð7ð ð7ð ð7ð ð7ð 3ð7ð ð7ð ð7ð ð 7ð Bð 7ð ð!7ð" ð#7ð$ ð%7ð, ð-7ð. ð/7ð0 "ð17ð2 ð37ð4 2ð57ð6 0ð77ð8 (ð97ð: *ð;7ð< 2ð=7ð> ð?7ð@ ðA7ðB ðC7ðD ðE7ðF $ðG7ðH ðI7ðJ ðK7ðL ðM7ðN ðO7ðP ðQ7ðR ðS7ðT ðU7ðV ðW7ðX ðY7ðZ ð[7ð\ &ð]7ð` +ða7ðb ðc7ðd ðe7ðf 6ðg7ðh $ði7ðj 0ðk7ðl òm7ó
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ð7ðv
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØð Ø ØØ$'Ø Ø47Ø25Ø*-Ø,/Ø47ØØØØ Ø&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ-0ØØØ8;Ø&)Ø25ñk7ØLð7ð
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$ð7ð *ð 7ð
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:ð 7ð 5ð 7ð 2ð7ð ð7ð ð7ð ð7ð 3ð7ð ð7ð ð7ð ð 7ð Bð 7ð ð!7ð" ð#7ð$ ð%7ð, ð-7ð. ð/7ð0 "ð17ð2 ð37ð4 2ð57ð6 0ð77ð8 (ð97ð: *ð;7ð< 2ð=7ð> ð?7ð@ ðA7ðB ðC7ðD ðE7ðF $ðG7ðH ðI7ðJ ðK7ðL ðM7ðN ðO7ðP ðQ7ðR ðS7ðT ðU7ðV ðW7ðX ðY7ðZ ð[7ð\ &ð]7ð` +ða7ðb ðc7ðd ðe7ðf 6ðg7ðh $ði7ðj 0ðk7ðl òm7ó
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ð7ñt
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Ø×"Ñ"Ø ØJØ'Ø KØØ$Ð%6Ñ7Ø *Ð+BÑ CØ
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ñ ð #ó ó ð '*§n¡nØ,0à<CØ7:·~±~Ø48Ø "à !Ø #Ø59Ø #Ø $Ø "ØDHØØ ð
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Ø ØØ$'§N¡NØ !à48Ø25·.±.Ø*-¯.©.Ø,/¯N©NØ48ØØ àØ à&-Ø ØØ!%ØØ×$Ñ$Ø Ø !Ø Ø Ø"*Ø(,à à-0¯^©^Ø)¨,Ñ7Ø Ø8<Ø-1Ø25·.±.ñ{R+ØLðR+ð
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØØDGØ ØØ$'Ø Ø-0Ø25Ø*-Ø,/Ø47ØØà Ø&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ ØØØ"%Ø&)Ø25ñe4ØLð4ð
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$ð4ð *ð 4ð
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:ð 4ð 5ð 4ð 2ð4ð ð4ð ð4ð ð4ð 3ð4ð ð4ð ð4ð ð 4ð Bð 4ð ð!4ð" ð#4ð$ Bð%4ð& ð'4ð( ð)4ð* "ð+4ð, ð-4ð. +ð/4ð0 0ð14ð2 (ð34ð4 *ð54ð6 2ð74ð8 ð94ð: ð;4ð< ð=4ð> ð?4ð@ $ðA4ðB ðC4ðD ðE4ðF ðG4ðH ðI4ðJ ðK4ðL ðM4ðN ðO4ðP ðQ4ðR ðS4ðT ðU4ðV &ðW4ðZ ð[4ð\ ð]4ð^ ð_4ð` ða4ðb $ðc4ðd 0ðe4ðf òg4ó
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ð4ðp
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØØDGØ ØØ$'Ø Ø-0Ø25Ø*-Ø,/Ø47ØØØà&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ ØØØ"%Ø&)Ø25ñe4ØLð4ð
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$ð4ð *ð 4ð
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ð4ðp
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØØDGØ ØØ$'Ø Ø-0Ø25Ø*-Ø,/Ø47ØØØ "ØØ&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ ØØØ"%Ø&)Ø25ñe4ØLð4ð
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$ð4ð *ð 4ð
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ð4ðp
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ð '*Ø,/Ø<?Ø7:Ø47Ø !Ø Ø "Ø58Ø "Ø #Ø ØDGØØØDGØ ØØ$'Ø Ø-0Ø25Ø*-Ø,/Ø47ØØØØ Ø&)Ø ØØ!$ØØØØ Ø Ø Ø"%Ø(+ØØ ØØØ"%Ø&)Ø25ñe4ØLð4ð
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ð4ñn
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ñ ð #ó ó ð" '*§n¡nØ,0à<CØ7:·~±~Ø48Ø "à !Ø #Ø59Ø #Ø $Ø "ØDHØØ àDHØ ØØ$'§N¡NØ !à-2Ø25·.±.Ø*-¯.©.Ø,/¯N©NØ48ØØ àØ à&-Ø ØØ!%ØØ×$Ñ$Ø Ø !Ø Ø Ø"*Ø(,à à-0¯^©^Ø)¨,Ñ7Ø Ø"&Ø-1Ø25·.±.ñuF+ØLðF+ð
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ð 8;Ø#&ØØ25à ñ ØLð ð 5ð ð !ð ð
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ð ð 0ð ð ð ð ð ð ò ó
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ð ð
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ð 8;Ø#&ØØ25Øñ ØLð ð 5ð ð !ð ð
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ð ð 0ð ð ð ð ð ð ò ó
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ð ð
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ð 8;Ø#&ØØ25Ø "Øñ ØLð ð 5ð ð !ð ð
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ð ð 0ð ð ð ð ð ð ò ó
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ð ð" 8?Ø#'ØØ25·.±.ØØ ñp+ØLðp+ð 5ðp+ð !ð p+ð
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