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1. Shard Calculation

Query:

Response:

Calculated Shard: 185 (from laksa190)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa185.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://numpy.org/doc/2.2/reference/generated/numpy.nan_to_num.html\')), getAhrefsUnparsedNoserviceFromURL(\'https://numpy.org/doc/2.2/reference/generated/numpy.nan_to_num.html\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.nan_to_num.html","crawl_time":1772110740,"first_indexed_time":1734253248,"http_code":200,"src_unparsed":"org,numpy!\/doc\/2.2\/reference\/generated\/numpy.nan_to_num.html s443","src_root_hash":"448416686592400585","history_drop_reason":null,"meta_title":"numpy.nan_to_num — NumPy v2.2 Manual","meta_descriptions":[],"attrs_boilerpipe_text":"numpy.\nnan_to_num\n(\nx\n,\ncopy\n=\nTrue\n,\nnan\n=\n0.0\n,\nposinf\n=\nNone\n,\nneginf\n=\nNone\n)\n[source]\n#\nReplace NaN with zero and infinity with large finite numbers (default\nbehaviour) or with the numbers defined by the user using the\nnan\n,\nposinf\nand\/or\nneginf\nkeywords.\nIf\nx\nis inexact, NaN is replaced by zero or by the user defined value in\nnan\nkeyword, infinity is replaced by the largest finite floating point\nvalues representable by\nx.dtype\nor by the user defined value in\nposinf\nkeyword and -infinity is replaced by the most negative finite\nfloating point values representable by\nx.dtype\nor by the user defined\nvalue in\nneginf\nkeyword.\nFor complex dtypes, the above is applied to each of the real and\nimaginary components of\nx\nseparately.\nIf\nx\nis not inexact, then no replacements are made.\nParameters\n:\nx\nscalar or array_like\nInput data.\ncopy\nbool, optional\nWhether to create a copy of\nx\n(True) or to replace values\nin-place (False). The in-place operation only occurs if\ncasting to an array does not require a copy.\nDefault is True.\nnan\nint, float, optional\nValue to be used to fill NaN values. If no value is passed\nthen NaN values will be replaced with 0.0.\nposinf\nint, float, optional\nValue to be used to fill positive infinity values. If no value is\npassed then positive infinity values will be replaced with a very\nlarge number.\nneginf\nint, float, optional\nValue to be used to fill negative infinity values. If no value is\npassed then negative infinity values will be replaced with a very\nsmall (or negative) number.\nReturns\n:\nout\nndarray\nx\n, with the non-finite values replaced. If\ncopy\nis False, this may\nbe\nx\nitself.\nSee also\nisinf\nShows which elements are positive or negative infinity.\nisneginf\nShows which elements are negative infinity.\nisposinf\nShows which elements are positive infinity.\nisnan\nShows which elements are Not a Number (NaN).\nisfinite\nShows which elements are finite (not NaN, not infinity)\nNotes\nNumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic\n(IEEE 754). This means that Not a Number is not equivalent to infinity.\nExamples\n>>>\nimport\nnumpy\nas\nnp\n>>>\nnp\n.\nnan_to_num\n(\nnp\n.\ninf\n)\n1.7976931348623157e+308\n>>>\nnp\n.\nnan_to_num\n(\n-\nnp\n.\ninf\n)\n-1.7976931348623157e+308\n>>>\nnp\n.\nnan_to_num\n(\nnp\n.\nnan\n)\n0.0\n>>>\nx\n=\nnp\n.\narray\n([\nnp\n.\ninf\n,\n-\nnp\n.\ninf\n,\nnp\n.\nnan\n,\n-\n128\n,\n128\n])\n>>>\nnp\n.\nnan_to_num\n(\nx\n)\narray([ 1.79769313e+308, -1.79769313e+308,  0.00000000e+000, # may vary\n-1.28000000e+002,  1.28000000e+002])\n>>>\nnp\n.\nnan_to_num\n(\nx\n,\nnan\n=-\n9999\n,\nposinf\n=\n33333333\n,\nneginf\n=\n33333333\n)\narray([ 3.3333333e+07,  3.3333333e+07, -9.9990000e+03,\n-1.2800000e+02,  1.2800000e+02])\n>>>\ny\n=\nnp\n.\narray\n([\ncomplex\n(\nnp\n.\ninf\n,\nnp\n.\nnan\n),\nnp\n.\nnan\n,\ncomplex\n(\nnp\n.\nnan\n,\nnp\n.\ninf\n)])\narray([  1.79769313e+308,  -1.79769313e+308,   0.00000000e+000, # may vary\n-1.28000000e+002,   1.28000000e+002])\n>>>\nnp\n.\nnan_to_num\n(\ny\n)\narray([  1.79769313e+308 +0.00000000e+000j, # may vary\n0.00000000e+000 +0.00000000e+000j,\n0.00000000e+000 +1.79769313e+308j])\n>>>\nnp\n.\nnan_to_num\n(\ny\n,\nnan\n=\n111111\n,\nposinf\n=\n222222\n)\narray([222222.+111111.j, 111111.     +0.j, 111111.+222222.j])","attrs_markdown":"[Skip to main content](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.nan_to_num.html#main-content)\n\nBack to top\n\nThis is documentation for **an old version (2.2.0)**.[Switch to stable version](https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.nan_to_num.html)\n\n[![NumPy v2.2 Manual - 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The in-place operation only occurs if casting to an array does not require a copy. Default is True.\n\n**nan**int, float, optional\n\nValue to be used to fill NaN values. If no value is passed then NaN values will be replaced with 0.0.\n\n**posinf**int, float, optional\n\nValue to be used to fill positive infinity values. If no value is passed then positive infinity values will be replaced with a very large number.\n\n**neginf**int, float, optional\n\nValue to be used to fill negative infinity values. If no value is passed then negative infinity values will be replaced with a very small (or negative) number.\n\nReturns:\n\n**out**ndarray\n\n*x*, with the non-finite values replaced. If [`copy`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.copy.html#numpy.copy \"numpy.copy\") is False, this may be *x* itself.\n\nSee also\n\n[`isinf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isinf.html#numpy.isinf \"numpy.isinf\")\n\nShows which elements are positive or negative infinity.\n\n[`isneginf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isneginf.html#numpy.isneginf \"numpy.isneginf\")\n\nShows which elements are negative infinity.\n\n[`isposinf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isposinf.html#numpy.isposinf \"numpy.isposinf\")\n\nShows which elements are positive infinity.\n\n[`isnan`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isnan.html#numpy.isnan \"numpy.isnan\")\n\nShows which elements are Not a Number (NaN).\n\n[`isfinite`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isfinite.html#numpy.isfinite \"numpy.isfinite\")\n\nShows which elements are finite (not NaN, not infinity)\n\nNotes\n\nNumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.\n\nExamples\n```\n>>> import numpy as np\n>>> np.nan_to_num(np.inf)\n1.7976931348623157e+308\n>>> np.nan_to_num(-np.inf)\n-1.7976931348623157e+308\n>>> np.nan_to_num(np.nan)\n0.0\n>>> x = np.array([np.inf, -np.inf, np.nan, -128, 128])\n>>> np.nan_to_num(x)\narray([ 1.79769313e+308, -1.79769313e+308,  0.00000000e+000, # may vary\n       -1.28000000e+002,  1.28000000e+002])\n>>> np.nan_to_num(x, nan=-9999, posinf=33333333, neginf=33333333)\narray([ 3.3333333e+07,  3.3333333e+07, -9.9990000e+03,\n       -1.2800000e+02,  1.2800000e+02])\n>>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)])\narray([  1.79769313e+308,  -1.79769313e+308,   0.00000000e+000, # may vary\n     -1.28000000e+002,   1.28000000e+002])\n>>> np.nan_to_num(y)\narray([  1.79769313e+308 +0.00000000e+000j, # may vary\n         0.00000000e+000 +0.00000000e+000j,\n         0.00000000e+000 +1.79769313e+308j])\n>>> np.nan_to_num(y, nan=111111, posinf=222222)\narray([222222.+111111.j, 111111.     +0.j, 111111.+222222.j])\n```\n\n[previous numpy.heaviside](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.heaviside.html \"previous page\")\n\n[next numpy.real\\_if\\_close](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.real_if_close.html \"next page\")\n\nOn this page\n\n- [`nan_to_num`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.nan_to_num.html#numpy.nan_to_num)\n\n© Copyright 2008-2024, NumPy Developers.\n\nCreated using [Sphinx](https:\/\/www.sphinx-doc.org\/) 7.2.6.\n\nBuilt with the [PyData Sphinx Theme](https:\/\/pydata-sphinx-theme.readthedocs.io\/en\/stable\/index.html) 0.16.0.","attrs_readable_markdown":"numpy.nan\\_to\\_num(*x*, *copy\\=True*, *nan\\=0\\.0*, *posinf\\=None*, *neginf\\=None*)[\\[source\\]](https:\/\/github.com\/numpy\/numpy\/blob\/v2.2.0\/numpy\/lib\/_type_check_impl.py#L373-L481)[\\#](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.nan_to_num.html#numpy.nan_to_num \"Link to this definition\")\n\nReplace NaN with zero and infinity with large finite numbers (default behaviour) or with the numbers defined by the user using the [`nan`](https:\/\/numpy.org\/doc\/2.2\/reference\/constants.html#numpy.nan \"numpy.nan\"), *posinf* and\/or *neginf* keywords.\n\nIf *x* is inexact, NaN is replaced by zero or by the user defined value in [`nan`](https:\/\/numpy.org\/doc\/2.2\/reference\/constants.html#numpy.nan \"numpy.nan\") keyword, infinity is replaced by the largest finite floating point values representable by `x.dtype` or by the user defined value in *posinf* keyword and -infinity is replaced by the most negative finite floating point values representable by `x.dtype` or by the user defined value in *neginf* keyword.\n\nFor complex dtypes, the above is applied to each of the real and imaginary components of *x* separately.\n\nIf *x* is not inexact, then no replacements are made.\n\nParameters:\n\n**x**scalar or array\\_like\n\nInput data.\n\n**copy**bool, optional\n\nWhether to create a copy of *x* (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True.\n\n**nan**int, float, optional\n\nValue to be used to fill NaN values. If no value is passed then NaN values will be replaced with 0.0.\n\n**posinf**int, float, optional\n\nValue to be used to fill positive infinity values. If no value is passed then positive infinity values will be replaced with a very large number.\n\n**neginf**int, float, optional\n\nValue to be used to fill negative infinity values. If no value is passed then negative infinity values will be replaced with a very small (or negative) number.\n\nReturns:\n\n**out**ndarray\n\n*x*, with the non-finite values replaced. If [`copy`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.copy.html#numpy.copy \"numpy.copy\") is False, this may be *x* itself.\n\nSee also\n\n[`isinf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isinf.html#numpy.isinf \"numpy.isinf\")\n\nShows which elements are positive or negative infinity.\n\n[`isneginf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isneginf.html#numpy.isneginf \"numpy.isneginf\")\n\nShows which elements are negative infinity.\n\n[`isposinf`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isposinf.html#numpy.isposinf \"numpy.isposinf\")\n\nShows which elements are positive infinity.\n\n[`isnan`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isnan.html#numpy.isnan \"numpy.isnan\")\n\nShows which elements are Not a Number (NaN).\n\n[`isfinite`](https:\/\/numpy.org\/doc\/2.2\/reference\/generated\/numpy.isfinite.html#numpy.isfinite \"numpy.isfinite\")\n\nShows which elements are finite (not NaN, not infinity)\n\nNotes\n\nNumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.\n\nExamples\n```\n>>> import numpy as np\n>>> np.nan_to_num(np.inf)\n1.7976931348623157e+308\n>>> np.nan_to_num(-np.inf)\n-1.7976931348623157e+308\n>>> np.nan_to_num(np.nan)\n0.0\n>>> x = np.array([np.inf, -np.inf, np.nan, -128, 128])\n>>> np.nan_to_num(x)\narray([ 1.79769313e+308, -1.79769313e+308,  0.00000000e+000, # may vary\n       -1.28000000e+002,  1.28000000e+002])\n>>> np.nan_to_num(x, nan=-9999, posinf=33333333, neginf=33333333)\narray([ 3.3333333e+07,  3.3333333e+07, -9.9990000e+03,\n       -1.2800000e+02,  1.2800000e+02])\n>>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)])\narray([  1.79769313e+308,  -1.79769313e+308,   0.00000000e+000, # may vary\n     -1.28000000e+002,   1.28000000e+002])\n>>> np.nan_to_num(y)\narray([  1.79769313e+308 +0.00000000e+000j, # may vary\n         0.00000000e+000 +0.00000000e+000j,\n         0.00000000e+000 +1.79769313e+308j])\n>>> np.nan_to_num(y, nan=111111, posinf=222222)\narray([222222.+111111.j, 111111.     +0.j, 111111.+222222.j])\n```","meta_canonical":null}

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Boilerpipe Text	numpy. nan_to_num ( x , copy = True , nan = 0.0 , posinf = None , neginf = None ) [source] # Replace NaN with zero and infinity with large finite numbers (default behaviour) or with the numbers defined by the user using the nan , posinf and/or neginf keywords. If x is inexact, NaN is replaced by zero or by the user defined value in nan keyword, infinity is replaced by the largest finite floating point values representable by x.dtype or by the user defined value in posinf keyword and -infinity is replaced by the most negative finite floating point values representable by x.dtype or by the user defined value in neginf keyword. For complex dtypes, the above is applied to each of the real and imaginary components of x separately. If x is not inexact, then no replacements are made. Parameters : x scalar or array_like Input data. copy bool, optional Whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True. nan int, float, optional Value to be used to fill NaN values. If no value is passed then NaN values will be replaced with 0.0. posinf int, float, optional Value to be used to fill positive infinity values. If no value is passed then positive infinity values will be replaced with a very large number. neginf int, float, optional Value to be used to fill negative infinity values. If no value is passed then negative infinity values will be replaced with a very small (or negative) number. Returns : out ndarray x , with the non-finite values replaced. If copy is False, this may be x itself. See also isinf Shows which elements are positive or negative infinity. isneginf Shows which elements are negative infinity. isposinf Shows which elements are positive infinity. isnan Shows which elements are Not a Number (NaN). isfinite Shows which elements are finite (not NaN, not infinity) Notes NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Examples >>> import numpy as np >>> np . nan_to_num ( np . inf ) 1.7976931348623157e+308 >>> np . nan_to_num ( - np . inf ) -1.7976931348623157e+308 >>> np . nan_to_num ( np . nan ) 0.0 >>> x = np . array ([ np . inf , - np . inf , np . nan , - 128 , 128 ]) >>> np . nan_to_num ( x ) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np . nan_to_num ( x , nan =- 9999 , posinf = 33333333 , neginf = 33333333 ) array([ 3.3333333e+07, 3.3333333e+07, -9.9990000e+03, -1.2800000e+02, 1.2800000e+02]) >>> y = np . array ([ complex ( np . inf , np . nan ), np . nan , complex ( np . nan , np . inf )]) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np . nan_to_num ( y ) array([ 1.79769313e+308 +0.00000000e+000j, # may vary 0.00000000e+000 +0.00000000e+000j, 0.00000000e+000 +1.79769313e+308j]) >>> np . nan_to_num ( y , nan = 111111 , posinf = 222222 ) array([222222.+111111.j, 111111. +0.j, 111111.+222222.j])
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If x is inexact, NaN is replaced by zero or by the user defined value in [`nan`](https://numpy.org/doc/2.2/reference/constants.html#numpy.nan "numpy.nan") keyword, infinity is replaced by the largest finite floating point values representable by `x.dtype` or by the user defined value in posinf keyword and -infinity is replaced by the most negative finite floating point values representable by `x.dtype` or by the user defined value in neginf keyword. For complex dtypes, the above is applied to each of the real and imaginary components of x separately. If x is not inexact, then no replacements are made. Parameters: xscalar or array\_like Input data. copybool, optional Whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True. nanint, float, optional Value to be used to fill NaN values. If no value is passed then NaN values will be replaced with 0.0. posinfint, float, optional Value to be used to fill positive infinity values. If no value is passed then positive infinity values will be replaced with a very large number. neginfint, float, optional Value to be used to fill negative infinity values. If no value is passed then negative infinity values will be replaced with a very small (or negative) number. Returns: outndarray x, with the non-finite values replaced. If [`copy`](https://numpy.org/doc/2.2/reference/generated/numpy.copy.html#numpy.copy "numpy.copy") is False, this may be x itself. See also [`isinf`](https://numpy.org/doc/2.2/reference/generated/numpy.isinf.html#numpy.isinf "numpy.isinf") Shows which elements are positive or negative infinity. [`isneginf`](https://numpy.org/doc/2.2/reference/generated/numpy.isneginf.html#numpy.isneginf "numpy.isneginf") Shows which elements are negative infinity. [`isposinf`](https://numpy.org/doc/2.2/reference/generated/numpy.isposinf.html#numpy.isposinf "numpy.isposinf") Shows which elements are positive infinity. [`isnan`](https://numpy.org/doc/2.2/reference/generated/numpy.isnan.html#numpy.isnan "numpy.isnan") Shows which elements are Not a Number (NaN). [`isfinite`](https://numpy.org/doc/2.2/reference/generated/numpy.isfinite.html#numpy.isfinite "numpy.isfinite") Shows which elements are finite (not NaN, not infinity) Notes NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Examples ``` >>> import numpy as np >>> np.nan_to_num(np.inf) 1.7976931348623157e+308 >>> np.nan_to_num(-np.inf) -1.7976931348623157e+308 >>> np.nan_to_num(np.nan) 0.0 >>> x = np.array([np.inf, -np.inf, np.nan, -128, 128]) >>> np.nan_to_num(x) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np.nan_to_num(x, nan=-9999, posinf=33333333, neginf=33333333) array([ 3.3333333e+07, 3.3333333e+07, -9.9990000e+03, -1.2800000e+02, 1.2800000e+02]) >>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)]) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np.nan_to_num(y) array([ 1.79769313e+308 +0.00000000e+000j, # may vary 0.00000000e+000 +0.00000000e+000j, 0.00000000e+000 +1.79769313e+308j]) >>> np.nan_to_num(y, nan=111111, posinf=222222) array([222222.+111111.j, 111111. +0.j, 111111.+222222.j]) ``` [previous numpy.heaviside](https://numpy.org/doc/2.2/reference/generated/numpy.heaviside.html "previous page") [next numpy.real\_if\_close](https://numpy.org/doc/2.2/reference/generated/numpy.real_if_close.html "next page") On this page - [`nan_to_num`](https://numpy.org/doc/2.2/reference/generated/numpy.nan_to_num.html#numpy.nan_to_num) © Copyright 2008-2024, NumPy Developers. 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Readable Markdown	numpy.nan\_to\_num(x, copy\=True, nan\=0\.0, posinf\=None, neginf\=None)[\[source\]](https://github.com/numpy/numpy/blob/v2.2.0/numpy/lib/_type_check_impl.py#L373-L481)[\#](https://numpy.org/doc/2.2/reference/generated/numpy.nan_to_num.html#numpy.nan_to_num "Link to this definition") Replace NaN with zero and infinity with large finite numbers (default behaviour) or with the numbers defined by the user using the [`nan`](https://numpy.org/doc/2.2/reference/constants.html#numpy.nan "numpy.nan"), posinf and/or neginf keywords. If x is inexact, NaN is replaced by zero or by the user defined value in [`nan`](https://numpy.org/doc/2.2/reference/constants.html#numpy.nan "numpy.nan") keyword, infinity is replaced by the largest finite floating point values representable by `x.dtype` or by the user defined value in posinf keyword and -infinity is replaced by the most negative finite floating point values representable by `x.dtype` or by the user defined value in neginf keyword. For complex dtypes, the above is applied to each of the real and imaginary components of x separately. If x is not inexact, then no replacements are made. Parameters: xscalar or array\_like Input data. copybool, optional Whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True. nanint, float, optional Value to be used to fill NaN values. If no value is passed then NaN values will be replaced with 0.0. posinfint, float, optional Value to be used to fill positive infinity values. If no value is passed then positive infinity values will be replaced with a very large number. neginfint, float, optional Value to be used to fill negative infinity values. If no value is passed then negative infinity values will be replaced with a very small (or negative) number. Returns: outndarray x, with the non-finite values replaced. If [`copy`](https://numpy.org/doc/2.2/reference/generated/numpy.copy.html#numpy.copy "numpy.copy") is False, this may be x itself. See also [`isinf`](https://numpy.org/doc/2.2/reference/generated/numpy.isinf.html#numpy.isinf "numpy.isinf") Shows which elements are positive or negative infinity. [`isneginf`](https://numpy.org/doc/2.2/reference/generated/numpy.isneginf.html#numpy.isneginf "numpy.isneginf") Shows which elements are negative infinity. [`isposinf`](https://numpy.org/doc/2.2/reference/generated/numpy.isposinf.html#numpy.isposinf "numpy.isposinf") Shows which elements are positive infinity. [`isnan`](https://numpy.org/doc/2.2/reference/generated/numpy.isnan.html#numpy.isnan "numpy.isnan") Shows which elements are Not a Number (NaN). [`isfinite`](https://numpy.org/doc/2.2/reference/generated/numpy.isfinite.html#numpy.isfinite "numpy.isfinite") Shows which elements are finite (not NaN, not infinity) Notes NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Examples ``` >>> import numpy as np >>> np.nan_to_num(np.inf) 1.7976931348623157e+308 >>> np.nan_to_num(-np.inf) -1.7976931348623157e+308 >>> np.nan_to_num(np.nan) 0.0 >>> x = np.array([np.inf, -np.inf, np.nan, -128, 128]) >>> np.nan_to_num(x) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np.nan_to_num(x, nan=-9999, posinf=33333333, neginf=33333333) array([ 3.3333333e+07, 3.3333333e+07, -9.9990000e+03, -1.2800000e+02, 1.2800000e+02]) >>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)]) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, # may vary -1.28000000e+002, 1.28000000e+002]) >>> np.nan_to_num(y) array([ 1.79769313e+308 +0.00000000e+000j, # may vary 0.00000000e+000 +0.00000000e+000j, 0.00000000e+000 +1.79769313e+308j]) >>> np.nan_to_num(y, nan=111111, posinf=222222) array([222222.+111111.j, 111111. +0.j, 111111.+222222.j]) ```
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