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"numpy.lib._npyio_impl._loadtxt_with_like" ], "example_section_data": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Code", "__tag": 4050, "value": "import numpy as np\nfrom io import StringIO # StringIO behaves like a file object\nc = StringIO(\"0 1\\n2 3\")\nnp.loadtxt(c)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "d = StringIO(\"M 21 72\\nF 35 58\")\nnp.loadtxt(d, dtype={'names': ('gender', 'age', 'weight'),\n 'formats': ('S1', 'i4', 'f4')})\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\n" }, { "__type": "Code", "__tag": 4050, "value": "c = StringIO(\"1,0,2\\n3,0,4\")\nx, y = np.loadtxt(c, delimiter=',', usecols=(0, 2), unpack=True)\nx\ny\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nThe `converters` argument is used to specify functions to preprocess the\ntext prior to parsing. `converters` can be a dictionary that maps\npreprocessing functions to each column:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO(\"1.618, 2.296\\n3.141, 4.669\\n\")\nconv = {\n 0: lambda x: np.floor(float(x)), # conversion fn for column 0\n 1: lambda x: np.ceil(float(x)), # conversion fn for column 1\n}\nnp.loadtxt(s, delimiter=\",\", converters=conv)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\n`converters` can be a callable instead of a dictionary, in which case it\nis applied to all columns:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO(\"0xDE 0xAD\\n0xC0 0xDE\")\nimport functools\nconv = functools.partial(int, base=16)\nnp.loadtxt(s, converters=conv)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nThis example shows how `converters` can be used to convert a field\nwith a trailing minus sign into a negative number.\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO(\"10.01 31.25-\\n19.22 64.31\\n17.57- 63.94\")\ndef conv(fld):\n return -float(fld[:-1]) if fld.endswith(\"-\") else float(fld)\nnp.loadtxt(s, converters=conv)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nUsing a callable as the converter can be particularly useful for handling\nvalues with different formatting, e.g. floats with underscores:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO(\"1 2.7 100_000\")\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "np.loadtxt(s, converters=float)\n", "execution_status": "failure" }, { "__type": "Text", "__tag": 4046, "value": "\nThis idea can be extended to automatically handle values specified in\nmany different formats, such as hex values:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "def conv(val):\n try:\n return float(val)\n except ValueError:\n return float.fromhex(val)\ns = StringIO(\"1, 2.5, 3_000, 0b4, 0x1.4000000000000p+2\")\nnp.loadtxt(s, delimiter=\",\", converters=conv)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nOr a format where the ``-`` sign comes after the number:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO(\"10.01 31.25-\\n19.22 64.31\\n17.57- 63.94\")\nconv = lambda x: -float(x[:-1]) if x.endswith(\"-\") else float(x)\nnp.loadtxt(s, converters=conv)\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nSupport for quoted fields is enabled with the `quotechar` parameter.\nComment and delimiter characters are ignored when they appear within a\nquoted item delineated by `quotechar`:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "s = StringIO('\"alpha, #42\", 10.0\\n\"beta, #64\", 2.0\\n')\ndtype = np.dtype([(\"label\", \"U12\"), (\"value\", float)])\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "np.loadtxt(s, dtype=dtype, delimiter=\",\", quotechar='\"')\n", "execution_status": 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