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DOC: fix formatting read_csv comment kwarg explanation
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pandas/io/parsers.py

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@@ -33,8 +33,9 @@ class ParserWarning(Warning):
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Parameters
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----------
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filepath_or_buffer : string or file handle / StringIO. The string could be
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a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a
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filepath_or_buffer : string or file handle / StringIO
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The string could be a URL. Valid URL schemes include
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http, ftp, s3, and file. For file URLs, a
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host is expected. For instance, a local file could be
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file ://localhost/path/to/table.csv
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%s
@@ -59,7 +60,8 @@ class ParserWarning(Warning):
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dialect : string or csv.Dialect instance, default None
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If None defaults to Excel dialect. Ignored if sep longer than 1 char
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See csv.Dialect documentation for more details
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header : int row number(s) to use as the column names, and the start of the
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header : int, list of ints
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Row number(s) to use as the column names, and the start of the
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data. Defaults to 0 if no ``names`` passed, otherwise ``None``. Explicitly
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pass ``header=0`` to be able to replace existing names. The header can be
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a list of integers that specify row locations for a multi-index on the
@@ -78,7 +80,7 @@ class ParserWarning(Warning):
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names : array-like
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List of column names to use. If file contains no header row, then you
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should explicitly pass header=None
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prefix : string or None (default)
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prefix : string, default None
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Prefix to add to column numbers when no header, e.g 'X' for X0, X1, ...
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na_values : list-like or dict, default None
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Additional strings to recognize as NA/NaN. If dict passed, specific
@@ -113,7 +115,7 @@ class ParserWarning(Warning):
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must be a single character. Like empty lines (as long as ``skip_blank_lines=True``),
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fully commented lines are ignored by the parameter `header`
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but not by `skiprows`. For example, if comment='#', parsing
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'#empty\n1,2,3\na,b,c' with `header=0` will result in '1,2,3' being
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'#empty\\na,b,c\\n1,2,3' with `header=0` will result in 'a,b,c' being
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treated as the header.
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decimal : str, default '.'
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Character to recognize as decimal point. E.g. use ',' for European data

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