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#: ../../source/reference/dataframe/api/mars.dataframe.read_csv.rst:2
msgid "mars.dataframe.read\\_csv"
msgstr ""

#: mars.dataframe.read_csv:1 of
msgid ""
"Read a comma-separated values (csv) file into DataFrame. Also supports "
"optionally iterating or breaking of the file into chunks."
msgstr ""

#: mars.dataframe.read_csv of
msgid "Parameters"
msgstr ""

#: mars.dataframe.read_csv:5 of
msgid ""
"Any valid string path is acceptable. 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. 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 handler (e.g. via builtin ``open`` function) or ``StringIO``."
msgstr ""

#: mars.dataframe.read_csv:12 of
msgid ""
"Delimiter to use. If sep is 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 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'``."
msgstr ""

#: mars.dataframe.read_csv:20 of
msgid "Alias for sep."
msgstr ""

#: mars.dataframe.read_csv:22 of
msgid ""
"Row number(s) to use as the column names, and the start of the data.  "
"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 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 multi-index 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."
msgstr ""

#: mars.dataframe.read_csv:36 of
msgid ""
"List of column names to use. 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."
msgstr ""

#: mars.dataframe.read_csv:40 of
msgid ""
"Column(s) to use as the row labels of the ``DataFrame``, either given as "
"string name or column index. If a sequence of int / str is given, a "
"MultiIndex is used. 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."
msgstr ""

#: mars.dataframe.read_csv:47 of
msgid ""
"Return a subset of the columns. 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). 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 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."
msgstr ""

#: mars.dataframe.read_csv:64 of
msgid "If the parsed data only contains one column then return a Series."
msgstr ""

#: mars.dataframe.read_csv:66 of
msgid "Prefix to add to column numbers when no header, e.g. 'X' for X0, X1, ..."
msgstr ""

#: mars.dataframe.read_csv:68 of
msgid ""
"Duplicate columns will be specified as 'X', 'X.1', ...'X.N', rather than "
"'X'...'X'. Passing in False will cause data to be overwritten if there "
"are duplicate names in the columns."
msgstr ""

#: mars.dataframe.read_csv:72 of
msgid ""
"Data type for data or 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."
msgstr ""

#: mars.dataframe.read_csv:79 of
msgid ""
"Parser engine to use. The C engine is faster while the python engine is "
"currently more feature-complete."
msgstr ""

#: mars.dataframe.read_csv:82 of
msgid ""
"Dict of functions for converting values in certain columns. Keys can "
"either be integers or column labels."
msgstr ""

#: mars.dataframe.read_csv:85 of
msgid "Values to consider as True."
msgstr ""

#: mars.dataframe.read_csv:87 of
msgid "Values to consider as False."
msgstr ""

#: mars.dataframe.read_csv:89 of
msgid "Skip spaces after delimiter."
msgstr ""

#: mars.dataframe.read_csv:91 of
msgid ""
"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]``."
msgstr ""

#: mars.dataframe.read_csv:97 of
msgid "Number of lines at bottom of file to skip (Unsupported with engine='c')."
msgstr ""

#: mars.dataframe.read_csv:99 of
msgid "Number of rows of file to read. Useful for reading pieces of large files."
msgstr ""

#: mars.dataframe.read_csv:101 of
msgid ""
"Additional strings to recognize as NA/NaN. If dict passed, specific per-"
"column NA values.  By default the following values are interpreted as "
"NaN: '', '#N/A', '#N/A N/A', '#NA', '-1.#IND', '-1.#QNAN', '-NaN', "
"'-nan', '1.#IND', '1.#QNAN', '<NA>', 'N/A', 'NA', 'NULL', 'NaN', 'n/a', "
"'nan', 'null'."
msgstr ""

#: mars.dataframe.read_csv:107 of
msgid ""
"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."
msgstr ""

#: mars.dataframe.read_csv:107 of
msgid ""
"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`"
msgstr ""

#: mars.dataframe.read_csv:110 of
msgid "is appended to the default NaN values used for parsing."
msgstr ""

#: mars.dataframe.read_csv:111 of
msgid ""
"If `keep_default_na` is True, and `na_values` are not specified, only the"
" default NaN values are used for parsing."
msgstr ""

#: mars.dataframe.read_csv:113 of
msgid ""
"If `keep_default_na` is False, and `na_values` are specified, only the "
"NaN values specified `na_values` are used for parsing."
msgstr ""

#: mars.dataframe.read_csv:115 of
msgid ""
"If `keep_default_na` is False, and `na_values` are not specified, no "
"strings will be parsed as NaN."
msgstr ""

#: mars.dataframe.read_csv:117 of
msgid ""
"Note that if `na_filter` is passed in as False, the `keep_default_na` and"
" `na_values` parameters will be ignored."
msgstr ""

#: mars.dataframe.read_csv:120 of
msgid ""
"Detect missing value markers (empty strings and the value of na_values). "
"In data without any NAs, passing na_filter=False can improve the "
"performance of reading a large file."
msgstr ""

#: mars.dataframe.read_csv:124 of
msgid "Indicate number of NA values placed in non-numeric columns."
msgstr ""

#: mars.dataframe.read_csv:126 of
msgid "If True, skip over blank lines rather than interpreting as NaN values."
msgstr ""

#: mars.dataframe.read_csv:128 of
msgid ""
"The behavior is as follows: * boolean. If True -> try parsing the index. "
"* 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 lists. e.g.  If [[1, 3]] -> "
"combine columns 1 and 3 and parse as   a single date column. * dict, e.g."
" {'foo' : [1, 3]} -> parse columns 1, 3 as date and call   result 'foo' "
"If a column or index cannot be represented as an array of datetimes, say "
"because of an unparseable 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 ``pd.to_datetime`` after ``pd.read_csv``. To parse"
" an index or column with a mixture of timezones, specify ``date_parser`` "
"to be a partially-applied :func:`pandas.to_datetime` with ``utc=True``. "
"See :ref:`io.csv.mixed_timezones` for more. Note: A fast-path exists for "
"iso8601-formatted dates."
msgstr ""

#: mars.dataframe.read_csv:128 of
msgid ""
"The behavior is as follows: * boolean. If True -> try parsing the index. "
"* list of int or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3"
msgstr ""

#: mars.dataframe.read_csv:131 of
msgid "each as a separate date column."
msgstr ""

#: mars.dataframe.read_csv:132 of
msgid ""
"list of lists. e.g.  If [[1, 3]] -> combine columns 1 and 3 and parse as "
"a single date column."
msgstr ""

#: mars.dataframe.read_csv:134 of
msgid ""
"dict, e.g. {'foo' : [1, 3]} -> parse columns 1, 3 as date and call result"
" 'foo'"
msgstr ""

#: mars.dataframe.read_csv:136 of
msgid ""
"If a column or index cannot be represented as an array of datetimes, say "
"because of an unparseable 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 ``pd.to_datetime`` after ``pd.read_csv``. To parse"
" an index or column with a mixture of timezones, specify ``date_parser`` "
"to be a partially-applied :func:`pandas.to_datetime` with ``utc=True``. "
"See :ref:`io.csv.mixed_timezones` for more. Note: A fast-path exists for "
"iso8601-formatted dates."
msgstr ""

#: mars.dataframe.read_csv:146 of
msgid ""
"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."
msgstr ""

#: mars.dataframe.read_csv:151 of
msgid ""
"If True and `parse_dates` specifies combining multiple columns then keep "
"the original columns."
msgstr ""

#: mars.dataframe.read_csv:154 of
msgid ""
"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."
msgstr ""

#: mars.dataframe.read_csv:164 of
msgid "DD/MM format dates, international and European format."
msgstr ""

#: mars.dataframe.read_csv:166 of
msgid ""
"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. .. versionadded:: 0.25.0"
msgstr ""

#: mars.dataframe.read_csv:171 of
msgid ""
"Return TextFileReader object for iteration or getting chunks with "
"``get_chunk()``."
msgstr ""

#: mars.dataframe.read_csv:174 of
msgid ""
"Return 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``."
msgstr ""

#: mars.dataframe.read_csv:179 of
msgid ""
"For on-the-fly decompression of on-disk data. If 'infer' and "
"`filepath_or_buffer` is path-like, then detect compression from the "
"following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no "
"decompression). If using 'zip', the ZIP file must contain only one data "
"file to be read in. Set to None for no decompression."
msgstr ""

#: mars.dataframe.read_csv:185 of
msgid "Thousands separator."
msgstr ""

#: mars.dataframe.read_csv:187 of
msgid "Character to recognize as decimal point (e.g. use ',' for European data)."
msgstr ""

#: mars.dataframe.read_csv:189 of
msgid "Character to break file into lines. Only valid with C parser."
msgstr ""

#: mars.dataframe.read_csv:191 of
msgid ""
"The character used to denote the start and end of a quoted item. Quoted "
"items can include the delimiter and it will be ignored."
msgstr ""

#: mars.dataframe.read_csv:194 of
msgid ""
"Control field quoting behavior per ``csv.QUOTE_*`` constants. Use one of "
"QUOTE_MINIMAL (0), QUOTE_ALL (1), QUOTE_NONNUMERIC (2) or QUOTE_NONE (3)."
msgstr ""

#: mars.dataframe.read_csv:197 of
msgid ""
"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."
msgstr ""

#: mars.dataframe.read_csv:201 of
msgid "One-character string used to escape other characters."
msgstr ""

#: mars.dataframe.read_csv:203 of
msgid ""
"Indicates 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."
msgstr ""

#: mars.dataframe.read_csv:211 of
msgid ""
"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>`_ ."
msgstr ""

#: mars.dataframe.read_csv:215 of
msgid ""
"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."
msgstr ""

#: mars.dataframe.read_csv:221 of
msgid ""
"Lines with too many fields (e.g. a csv line with too many commas) will by"
" default cause an exception to be raised, and no DataFrame will be "
"returned. If False, then these \"bad lines\" will dropped from the "
"DataFrame that is returned."
msgstr ""

#: mars.dataframe.read_csv:226 of
msgid ""
"If error_bad_lines is False, and warn_bad_lines is True, a warning for "
"each \"bad line\" will be output."
msgstr ""

#: mars.dataframe.read_csv:229 of
msgid ""
"Specifies whether or not whitespace (e.g. ``' '`` or ``'    '``) will be "
"used as the sep. Equivalent to setting ``sep='\\s+'``. If this option is "
"set to True, nothing should be passed in for the ``delimiter`` parameter."
msgstr ""

#: mars.dataframe.read_csv:234 of
msgid ""
"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 DataFrame regardless, use"
" the `chunksize` or `iterator` parameter to return the data in chunks. "
"(Only valid with C parser)."
msgstr ""

#: mars.dataframe.read_csv:241 of
msgid ""
"Specifies which converter the C engine should use for floating-point "
"values. The options are `None` for the ordinary converter, `high` for the"
" high-precision converter, and `round_trip` for the round-trip converter."
msgstr ""

#: mars.dataframe.read_csv:246 of
msgid "Number of chunk bytes."
msgstr ""

#: mars.dataframe.read_csv:248 of
msgid "If read into cudf DataFrame."
msgstr ""

#: mars.dataframe.read_csv:250 of
msgid "Number of bytes to use in the head of file, mainly for data inference."
msgstr ""

#: mars.dataframe.read_csv:252 of
msgid "Number of lines to use in the head of file, mainly for data inference."
msgstr ""

#: mars.dataframe.read_csv:254 of
msgid "Create a new RangeIndex if csv doesn't contain index columns."
msgstr ""

#: mars.dataframe.read_csv:256 of
msgid "Options for storage connection."
msgstr ""

#: mars.dataframe.read_csv of
msgid "Returns"
msgstr ""

#: mars.dataframe.read_csv:259 of
msgid ""
"A comma-separated values (csv) file is returned as two-dimensional data "
"structure with labeled axes."
msgstr ""

#: mars.dataframe.read_csv of
msgid "Return type"
msgstr ""

#: mars.dataframe.read_csv:265 of
msgid ":func:`to_csv`"
msgstr ""

#: mars.dataframe.read_csv:266 of
msgid "Write DataFrame to a comma-separated values (csv) file."
msgstr ""

#: mars.dataframe.read_csv:269 of
msgid "Examples"
msgstr ""

