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87 | 87 | e.g. [0,1,3]. Intervening rows that are not specified will be
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88 | 88 | skipped (e.g. 2 in this example is skipped). Note that this
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89 | 89 | parameter ignores commented lines and empty lines if
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90 |
| - ``skip_blank_lines=True``, so header=0 denotes the first line of |
| 90 | + ``skip_blank_lines=True``, so ``header=0`` denotes the first line of |
91 | 91 | data rather than the first line of the file.
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92 | 92 | names : array-like, default None
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93 | 93 | List of column names to use. If file contains no header row, then you
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94 |
| - should explicitly pass header=None. Duplicates in this list will cause |
| 94 | + should explicitly pass ``header=None``. Duplicates in this list will cause |
95 | 95 | a ``UserWarning`` to be issued.
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96 | 96 | index_col : int or sequence or False, default None
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97 | 97 | Column to use as the row labels of the DataFrame. If a sequence is given, a
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98 | 98 | MultiIndex is used. If you have a malformed file with delimiters at the end
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99 |
| - of each line, you might consider index_col=False to force pandas to _not_ |
100 |
| - use the first column as the index (row names). |
| 99 | + of each line, you might consider ``index_col=False`` to force pandas to |
| 100 | + not use the first column as the index (row names). |
101 | 101 | usecols : list-like or callable, default None
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102 | 102 | Return a subset of the columns. If list-like, all elements must either
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103 | 103 | be positional (i.e. integer indices into the document columns) or strings
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104 | 104 | that correspond to column names provided either by the user in `names` or
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105 | 105 | inferred from the document header row(s). For example, a valid list-like
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106 |
| - `usecols` parameter would be [0, 1, 2] or ['foo', 'bar', 'baz']. Element |
107 |
| - order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``. |
| 106 | + `usecols` parameter would be ``[0, 1, 2]`` or ``['foo', 'bar', 'baz']``. |
| 107 | + Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``. |
108 | 108 | To instantiate a DataFrame from ``data`` with element order preserved use
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109 | 109 | ``pd.read_csv(data, usecols=['foo', 'bar'])[['foo', 'bar']]`` for columns
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110 | 110 | in ``['foo', 'bar']`` order or
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357 | 357 | Characters to consider as filler characters in the fixed-width file.
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358 | 358 | Can be used to specify the filler character of the fields
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359 | 359 | if it is not spaces (e.g., '~').
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| 360 | +**kwds : optional |
| 361 | + All the following keyword arguments can be passed. |
360 | 362 | """
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361 | 363 |
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362 | 364 |
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