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1. Shard Calculation

Query:

Response:

Calculated Shard: 169 (from laksa017)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa169.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://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array\')), getAhrefsUnparsedNoserviceFromURL(\'https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array","crawl_time":1761780142,"first_indexed_time":1659219181,"http_code":200,"src_unparsed":"com,stackoverflow!\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array s443","src_root_hash":"714406497480128969","history_drop_reason":null,"meta_title":"python - How do I remove NaN values from a NumPy array? - Stack Overflow","meta_descriptions":[],"attrs_boilerpipe_text":"To remove NaN values from a NumPy array  x : x = x[~numpy.isnan(x)]\n Explanation The inner function  numpy.isnan  returns a boolean\/logical array which has the value  True  everywhere that  x  is not-a-number. Since we want the opposite, we use the logical-not operator  ~  to get an array with  True s everywhere that  x is  a valid number. Lastly, we use this logical array to index into the original array  x , in order to retrieve just the non-NaN values.","attrs_markdown":"# ![site logo](https:\/\/stackoverflow.com\/Content\/Img\/SE-logo75.png)\nBy clicking “Sign up”, you agree to our [terms of service](https:\/\/stackoverflow.com\/legal\/terms-of-service\/public) and acknowledge you have read our [privacy policy](https:\/\/stackoverflow.com\/legal\/privacy-policy).\n\n# OR\n\nAlready have an account? [Log in](https:\/\/stackoverflow.com\/users\/login)\n\n[Skip to main content](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#content)\n\n[Stack Overflow](https:\/\/stackoverflow.com\/)\n\n1. [About](https:\/\/stackoverflow.co\/)\n2. Products\n3. [For Teams](https:\/\/stackoverflow.co\/teams\/)\n\n1. 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To gain full voting privileges, [earn reputation](https:\/\/stackoverflow.com\/help\/whats-reputation).\n\nGot it\\!\n\nGo to help center to learn more\n\n# [How do I remove NaN values from a NumPy array?](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array)\n[Ask Question](https:\/\/stackoverflow.com\/questions\/ask)\n\nAsked\n\n13 years, 2 months ago\n\nModified [3 years, 2 months ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array?lastactivity \"2022-07-30 05:52:24Z\")\n\nViewed 879k times\n\nThis question shows research effort; it is useful and clear\n\n392\n\nSave this question.\n\nShow activity on this post.\n\nHow do I remove NaN values from a NumPy array?\n```\n[1, 2, NaN, 4, NaN, 8]   ⟶   [1, 2, 4, 8]\n```\n\n- [python](https:\/\/stackoverflow.com\/questions\/tagged\/python \"show questions tagged 'python'\")\n- [numpy](https:\/\/stackoverflow.com\/questions\/tagged\/numpy \"show questions tagged 'numpy'\")\n- [nan](https:\/\/stackoverflow.com\/questions\/tagged\/nan \"show questions tagged 'nan'\")\n\n[Share](https:\/\/stackoverflow.com\/q\/11620914 \"Short permalink to this question\")\n\nShare a link to this question\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this question](https:\/\/stackoverflow.com\/posts\/11620914\/edit)\n\nFollow\n\nFollow this question to receive notifications\n\n[edited Jul 30, 2022 at 5:36](https:\/\/stackoverflow.com\/posts\/11620914\/revisions \"show all edits to this post\")\n\n[![Mateen Ulhaq's user avatar](https:\/\/i.sstatic.net\/4cFxJ9Lj.jpg?s=64)](https:\/\/stackoverflow.com\/users\/365102\/mateen-ulhaq)\n\n[Mateen Ulhaq](https:\/\/stackoverflow.com\/users\/365102\/mateen-ulhaq)\n\n27\\.7k2121 gold badges120120 silver badges155155 bronze badges\n\nasked Jul 23, 2012 at 21:36\n\n[![Dax Feliz's user avatar](https:\/\/www.gravatar.com\/avatar\/543c6d262d8dc2818e8d3e86f35f65d1?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/1464677\/dax-feliz)\n\n[Dax Feliz](https:\/\/stackoverflow.com\/users\/1464677\/dax-feliz)Dax Feliz\n\n13k88 gold badges3333 silver badges3434 bronze badges\n\n0\n\n[Add a comment](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array \"Use comments to ask for more information or suggest improvements. Avoid answering questions in comments.\")   \\|\n\n## 13 Answers 13\nSorted by:\n\n[Reset to default](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array?answertab=scoredesc#tab-top)\n\nThis answer is useful\n\n630\n\nSave this answer.\n\nShow activity on this post.\n\nTo remove NaN values from a NumPy array `x`:\n```\nx = x[~numpy.isnan(x)]\n```\n##### Explanation\nThe inner function `numpy.isnan` returns a boolean\/logical array which has the value `True` everywhere that `x` is not-a-number. Since we want the opposite, we use the logical-not operator `~` to get an array with `True`s everywhere that `x` **is** a valid number.\n\nLastly, we use this logical array to index into the original array `x`, in order to retrieve just the non-NaN values.\n\n[Share](https:\/\/stackoverflow.com\/a\/11620982 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/11620982\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\n[edited Jul 30, 2022 at 5:52](https:\/\/stackoverflow.com\/posts\/11620982\/revisions \"show all edits to this post\")\n\n[![Mateen Ulhaq's user avatar](https:\/\/i.sstatic.net\/4cFxJ9Lj.jpg?s=64)](https:\/\/stackoverflow.com\/users\/365102\/mateen-ulhaq)\n\n[Mateen Ulhaq](https:\/\/stackoverflow.com\/users\/365102\/mateen-ulhaq)\n\n27\\.7k2121 gold badges120120 silver badges155155 bronze badges\n\nanswered Jul 23, 2012 at 21:42\n\n[![jmetz's user avatar](https:\/\/www.gravatar.com\/avatar\/4c794978de2f7a314b349f68bf0aad91?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\n[jmetz](https:\/\/stackoverflow.com\/users\/537098\/jmetz)jmetz\n\n12\\.9k33 gold badges3232 silver badges4141 bronze badges\n\nSign up to request clarification or add additional context in comments.\n\n## 10 Comments\nAdd a comment\n\n[![](https:\/\/www.gravatar.com\/avatar\/052338b3d753f00bb7724f2d2ca060a4?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/7650\/miki-tebeka)\n\nMiki Tebeka\n\n[Miki Tebeka](https:\/\/stackoverflow.com\/users\/7650\/miki-tebeka)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment15389511_11620982)\n\nOr `x = x[numpy.isfinite(x)]`\n\n2012-07-23T22:29:06.803Z+00:00\n\n53\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/da347a842b3231aad6e506c93ab95564?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/424651\/chbrown)\n\nchbrown\n\n[chbrown](https:\/\/stackoverflow.com\/users\/424651\/chbrown)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment29913880_11620982)\n\nOr `x = x[~numpy.isnan(x)]`, which is equivalent to mutzmatron's original answer, but shorter. In case you want to keep your infinities around, know that `numpy.isfinite(numpy.inf) == False`, of course, but `~numpy.isnan(numpy.inf) == True`.\n\n2013-11-19T19:02:34.14Z+00:00\n\n23\n\nReply\n\n- Copy link\n\n[![](https:\/\/i.sstatic.net\/xkm1p.png?s=64)](https:\/\/stackoverflow.com\/users\/3765905\/boltzmannbrain)\n\nBoltzmannBrain\n\n[BoltzmannBrain](https:\/\/stackoverflow.com\/users\/3765905\/boltzmannbrain)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment79136181_11620982)\n\nFor people looking to solve this with an ndarray and maintain the dimensions, use [numpy where](https:\/\/docs.scipy.org\/doc\/numpy\/reference\/generated\/numpy.where.html): `np.where(np.isfinite(x), x, 0)`\n\n2017-09-07T02:51:07.263Z+00:00\n\n17\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/639520c5cc3265d60692c09ba796beb2?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/796919\/towry)\n\ntowry\n\n[towry](https:\/\/stackoverflow.com\/users\/796919\/towry)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment89217800_11620982)\n\nTypeError: only integer scalar arrays can be converted to a scalar index\n\n2018-06-30T14:29:37.237Z+00:00\n\n1\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\njmetz\n\n[jmetz](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment89254484_11620982)\n\n@towry: this is happening because your input, `x` is not a numpy array. If you want to use logical indexing, it must be an array - e.g. `x = np.array(x)`\n\n2018-07-02T11:32:48.91Z+00:00\n\n1\n\nReply\n\n- Copy link\n\nAdd a comment\n\n\\|\n\nShow 5 more comments\n\nThis answer is useful\n\n77\n\nSave this answer.\n\nShow activity on this post.\n\n```\nfilter(lambda v: v==v, x)\n```\nworks both for lists and numpy array since v!=v only for NaN\n\n[Share](https:\/\/stackoverflow.com\/a\/29679784 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/29679784\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Apr 16, 2015 at 15:46\n\n[![udibr's user avatar](https:\/\/i.sstatic.net\/fbqjx.jpg?s=64)](https:\/\/stackoverflow.com\/users\/209852\/udibr)\n\n[udibr](https:\/\/stackoverflow.com\/users\/209852\/udibr)udibr\n\n1,08977 silver badges55 bronze badges\n\n## 8 Comments\nAdd a comment\n\n[![](https:\/\/www.gravatar.com\/avatar\/7fd359ed56b0d634d5c16dacbcf5f042?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/157441\/austin-richardson)\n\nAustin Richardson\n\n[Austin Richardson](https:\/\/stackoverflow.com\/users\/157441\/austin-richardson)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment50249119_29679784)\n\nA hack but an especially useful one in the case where you are filtering nans from an array of objects with mixed types, such as a strings and nans.\n\n2015-06-29T14:15:01.693Z+00:00\n\n12\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/9bf6decd8e2acafb6d371c2a1a6f7e1b?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/6260170\/chris-rands)\n\nChris\\_Rands\n\n[Chris\\_Rands](https:\/\/stackoverflow.com\/users\/6260170\/chris-rands)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment90198356_29679784)\n\nThis might seem clever, but if obscures the logic and theoretically other objects (such as custom classes) can also have this property\n\n2018-07-31T15:02:58.11Z+00:00\n\n5\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/acb61aa42806f4679c1f1e35aea857ed?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/1825043\/christian-oreilly)\n\nChristian O'Reilly\n\n[Christian O'Reilly](https:\/\/stackoverflow.com\/users\/1825043\/christian-oreilly)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment110324628_29679784)\n\nAlso useful because it only needs `x` to be specified once as opposed to solutions of the type `x[~numpy.isnan(x)]`. This is convenient when `x` is defined by a long expression and you don't want to clutter the code by creating a temporary variable to store the result of this long expression.\n\n2020-06-15T01:09:11.307Z+00:00\n\n1\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/568ffd089d5715f39acc4de2bf72c261?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/1795641\/smm)\n\nsmm\n\n[smm](https:\/\/stackoverflow.com\/users\/1795641\/smm)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment112340733_29679784)\n\nIt might be slow compere to `x[~numpy.isnan(x)]`\n\n2020-08-21T21:23:10.413Z+00:00\n\n1\n\nReply\n\n- Copy link\n\n[![](https:\/\/i.sstatic.net\/PyUIB.png?s=64)](https:\/\/stackoverflow.com\/users\/7362806\/m-idk392845)\n\nM\\_Idk392845\n\n[M\\_Idk392845](https:\/\/stackoverflow.com\/users\/7362806\/m-idk392845)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment131554252_29679784)\n\nwhat is v and what is x?\n\n2022-11-21T21:12:32.293Z+00:00\n\n1\n\nReply\n\n- Copy link\n\nAdd a comment\n\n\\|\n\nShow 3 more comments\n\nThis answer is useful\n\n47\n\nSave this answer.\n\nShow activity on this post.\n\nFor me the answer by @jmetz didn't work, however using pandas isnull() did.\n```\nx = x[~pd.isnull(x)]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/43475189 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/43475189\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Apr 18, 2017 at 14:37\n\n[![Daniel Kislyuk's user avatar](https:\/\/www.gravatar.com\/avatar\/c1296de0d5ade6f7d7c1020fc83ea526?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/1772802\/daniel-kislyuk)\n\n[Daniel Kislyuk](https:\/\/stackoverflow.com\/users\/1772802\/daniel-kislyuk)Daniel Kislyuk\n\n1,0061111 silver badges1212 bronze badges\n\n## 3 Comments\nAdd a comment\n\n[![](https:\/\/www.gravatar.com\/avatar\/4bb4ac5216b835cd31e9e913334e2e63?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/4379906\/kbridge4096)\n\nkbridge4096\n\n[kbridge4096](https:\/\/stackoverflow.com\/users\/4379906\/kbridge4096)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment128088483_43475189)\n\nor: `x = x[x.notnull()]`\n\n2022-06-05T17:18:56.973Z+00:00\n\n2\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/7f44b790df9ee198c42dcfd0ef2399af?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/20156987\/llohann)\n\nLlohann\n\n[Llohann](https:\/\/stackoverflow.com\/users\/20156987\/llohann)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment134949105_43475189)\n\nI am not found of including pandas on the pipe but the accepted solution got me `TypeError: ufunc 'isnan' not supported for the input types`. It does not work with strings or object types. This solution did.\n\n2023-06-23T07:32:03.87Z+00:00\n\n1\n\nReply\n\n- Copy link\n\n[![](https:\/\/i.sstatic.net\/0y5dS.png?s=64)](https:\/\/stackoverflow.com\/users\/3429115\/rafs)\n\nRafs\n\n[Rafs](https:\/\/stackoverflow.com\/users\/3429115\/rafs)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment137524880_43475189)\n\nAdded benefit for this one is it removes `NaT`s out of the box\n\n2024-02-16T15:53:31.297Z+00:00\n\n0\n\nReply\n\n- Copy link\n\nAdd a comment\n\nThis answer is useful\n\n36\n\nSave this answer.\n\nShow activity on this post.\n\nTry this:\n```\nimport math\nprint [value for value in x if not math.isnan(value)]\n```\nFor more, read on [List Comprehensions](http:\/\/docs.python.org\/tutorial\/datastructures.html#list-comprehensions).\n\n[Share](https:\/\/stackoverflow.com\/a\/11620945 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/11620945\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Jul 23, 2012 at 21:39\n\n[![liori's user avatar](https:\/\/www.gravatar.com\/avatar\/5ea9e348dc045d53f5659eadf3e695b2?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/42610\/liori)\n\n[liori](https:\/\/stackoverflow.com\/users\/42610\/liori)liori\n\n42\\.6k1313 gold badges8080 silver badges111111 bronze badges\n\n## 3 Comments\nAdd a comment\n\n[![](https:\/\/www.gravatar.com\/avatar\/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\njmetz\n\n[jmetz](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment15406044_11620945)\n\nIf you're using numpy both my answer and that by @lazy1 are almost an order of magnitude faster than the list comprehension - lazy1's solution is slightly faster (though technically will also not return any infinity values).\n\n2012-07-24T13:54:16.493Z+00:00\n\n6\n\nReply\n\n- Copy link\n\n[![](https:\/\/www.gravatar.com\/avatar\/b22fa97d3e76a2d9b907aba23b415fc6?s=48&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/4684507\/hypers)\n\nhypers\n\n[hypers](https:\/\/stackoverflow.com\/users\/4684507\/hypers)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment81833136_11620945)\n\nDon't forget the brackets :) `print ([value for value in x if not math.isnan(value)])`\n\n2017-11-22T16:09:35.39Z+00:00\n\n0\n\nReply\n\n- Copy link\n\n[![](https:\/\/i.sstatic.net\/AfU4T.jpg?s=64)](https:\/\/stackoverflow.com\/users\/2523501\/yeliabsalohcin)\n\nyeliabsalohcin\n\n[yeliabsalohcin](https:\/\/stackoverflow.com\/users\/2523501\/yeliabsalohcin)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment93769176_11620945)\n\nIf you're using numpy like the top answer then you can use this list comprehension answer with the `np` package: So returns your list without the nans: `[value for value in x if not np.isnan(value)]`\n\n2018-11-23T14:09:28.98Z+00:00\n\n0\n\nReply\n\n- Copy link\n\nAdd a comment\n\nThis answer is useful\n\n28\n\nSave this answer.\n\nShow activity on this post.\n\n[@jmetz's answer](https:\/\/stackoverflow.com\/a\/11620982\/3645374) is probably the one most people need; however it yields a one-dimensional array, e.g. making it unusable to remove entire rows or columns in matrices.\n\nTo do so, one should reduce the logical array to one dimension, then index the target array. For instance, the following will remove rows which have at least one NaN value:\n```\nx = x[~numpy.isnan(x).any(axis=1)]\n```\nSee more detail [here](https:\/\/www.w3resource.com\/python-exercises\/numpy\/python-numpy-exercise-91.php).\n\n[Share](https:\/\/stackoverflow.com\/a\/61589266 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/61589266\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered May 4, 2020 at 9:43\n\n[![M4urice's user avatar](https:\/\/www.gravatar.com\/avatar\/ed25178db3eb0df549cd6689a8112f0f?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/3645374\/m4urice)\n\n[M4urice](https:\/\/stackoverflow.com\/users\/3645374\/m4urice)M4urice\n\n66111 gold badge99 silver badges1616 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n10\n\nSave this answer.\n\nShow activity on this post.\n\nAs shown by others\n```\nx[~numpy.isnan(x)]\n```\nworks. But it will throw an error if the numpy dtype is not a native data type, for example if it is object. In that case you can use pandas.\n```\nx[~pandas.isna(x)] or x[~pandas.isnull(x)]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/47486199 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/47486199\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\n[edited Jan 9, 2020 at 13:55](https:\/\/stackoverflow.com\/posts\/47486199\/revisions \"show all edits to this post\")\n\n[![Shashank Srivastava's user avatar](https:\/\/i.sstatic.net\/kLskH.jpg?s=64)](https:\/\/stackoverflow.com\/users\/1688792\/shashank-srivastava)\n\n[Shashank Srivastava](https:\/\/stackoverflow.com\/users\/1688792\/shashank-srivastava)\n\n19522 silver badges1313 bronze badges\n\nanswered Nov 25, 2017 at 12:55\n\n[![koliyat9811's user avatar](https:\/\/www.gravatar.com\/avatar\/97ec570ce35cf05e4a260e85e6079357?s=64&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/6248016\/koliyat9811)\n\n[koliyat9811](https:\/\/stackoverflow.com\/users\/6248016\/koliyat9811)koliyat9811\n\n92511 gold badge1010 silver badges1212 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n8\n\nSave this answer.\n\nShow activity on this post.\n\nIf you're using `numpy`\n```\n# first get the indices where the values are finite\nii = np.isfinite(x)\n\n# second get the values\nx = x[ii]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/48823495 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/48823495\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Feb 16, 2018 at 9:19\n\n[![aloha's user avatar](https:\/\/www.gravatar.com\/avatar\/bac2f103216583f9fed5705038434020?s=64&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/3097391\/aloha)\n\n[aloha](https:\/\/stackoverflow.com\/users\/3097391\/aloha)aloha\n\n4,83466 gold badges3636 silver badges4343 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n7\n\nSave this answer.\n\nShow activity on this post.\n\nThe [accepted answer](https:\/\/stackoverflow.com\/a\/11620982\/7128154) changes shape for 2d arrays. I present a solution here, using the Pandas [dropna()](https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.dropna.html) functionality. It works for 1D and 2D arrays. In the 2D case you can choose weather to **drop the row or column** containing `np.nan`.\n```\nimport pandas as pd\nimport numpy as np\n\ndef dropna(arr, *args, **kwarg):\n    assert isinstance(arr, np.ndarray)\n    dropped=pd.DataFrame(arr).dropna(*args, **kwarg).values\n    if arr.ndim==1:\n        dropped=dropped.flatten()\n    return dropped\n\nx = np.array([1400, 1500, 1600, np.nan, np.nan, np.nan ,1700])\ny = np.array([[1400, 1500, 1600], [np.nan, 0, np.nan] ,[1700,1800,np.nan]] )\n\n\nprint('='*20+' 1D Case: ' +'='*20+'\\nInput:\\n',x,sep='')\nprint('\\ndropna:\\n',dropna(x),sep='')\n\nprint('\\n\\n'+'='*20+' 2D Case: ' +'='*20+'\\nInput:\\n',y,sep='')\nprint('\\ndropna (rows):\\n',dropna(y),sep='')\nprint('\\ndropna (columns):\\n',dropna(y,axis=1),sep='')\n\nprint('\\n\\n'+'='*20+' x[np.logical_not(np.isnan(x))] for 2D: ' +'='*20+'\\nInput:\\n',y,sep='')\nprint('\\ndropna:\\n',x[np.logical_not(np.isnan(x))],sep='')\n```\n**Result:**\n```\n==================== 1D Case: ====================\nInput:\n[1400. 1500. 1600.   nan   nan   nan 1700.]\n\ndropna:\n[1400. 1500. 1600. 1700.]\n\n\n==================== 2D Case: ====================\nInput:\n[[1400. 1500. 1600.]\n [  nan    0.   nan]\n [1700. 1800.   nan]]\n\ndropna (rows):\n[[1400. 1500. 1600.]]\n\ndropna (columns):\n[[1500.]\n [   0.]\n [1800.]]\n\n\n==================== x[np.logical_not(np.isnan(x))] for 2D: ====================\nInput:\n[[1400. 1500. 1600.]\n [  nan    0.   nan]\n [1700. 1800.   nan]]\n\ndropna:\n[1400. 1500. 1600. 1700.]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/55194127 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/55194127\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Mar 16, 2019 at 6:37\n\n[![Markus Dutschke's user avatar](https:\/\/i.sstatic.net\/E3sBH.png?s=64)](https:\/\/stackoverflow.com\/users\/7128154\/markus-dutschke)\n\n[Markus Dutschke](https:\/\/stackoverflow.com\/users\/7128154\/markus-dutschke)Markus Dutschke\n\n10\\.7k44 gold badges7272 silver badges6767 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n7\n\nSave this answer.\n\nShow activity on this post.\n\nIn case it helps, for simple 1d arrays:\n```\nx = np.array([np.nan, 1, 2, 3, 4])\n\nx[~np.isnan(x)]\n>>> array([1., 2., 3., 4.])\n```\nbut if you wish to expand to matrices and preserve the shape:\n```\nx = np.array([\n    [np.nan, np.nan],\n    [np.nan, 0],\n    [1, 2],\n    [3, 4]\n])\n\nx[~np.isnan(x).any(axis=1)]\n>>> array([[1., 2.],\n           [3., 4.]])\n```\nI encountered this issue when dealing with pandas `.shift()` functionality, and I wanted to avoid using `.apply(..., axis=1)` at all cost due to its inefficiency.\n\n[Share](https:\/\/stackoverflow.com\/a\/66643691 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/66643691\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Mar 15, 2021 at 18:36\n\n[![Robin Teuwens's user avatar](https:\/\/www.gravatar.com\/avatar\/d48c49b3ba564556f14fbf8f0ba873f8?s=64&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/10905753\/robin-teuwens)\n\n[Robin Teuwens](https:\/\/stackoverflow.com\/users\/10905753\/robin-teuwens)Robin Teuwens\n\n15111 silver badge66 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n6\n\nSave this answer.\n\nShow activity on this post.\n\nDoing the above :\n```\nx = x[~numpy.isnan(x)]\n```\nor\n```\nx = x[numpy.logical_not(numpy.isnan(x))]\n```\nI found that resetting to the same variable (x) did not remove the actual nan values and had to use a different variable. Setting it to a different variable removed the nans. e.g.\n```\ny = x[~numpy.isnan(x)]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/38001353 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/38001353\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Jun 23, 2016 at 20:35\n\n[![melissaOu's user avatar](https:\/\/www.gravatar.com\/avatar\/3b688306f3155459264145b9ca5dbfb5?s=64&d=identicon&r=PG&f=y&so-version=2)](https:\/\/stackoverflow.com\/users\/6506193\/melissaou)\n\n[melissaOu](https:\/\/stackoverflow.com\/users\/6506193\/melissaou)melissaOu\n\n6111 silver badge22 bronze badges\n\n## 1 Comment\nAdd a comment\n\n[![](https:\/\/www.gravatar.com\/avatar\/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\njmetz\n\n[jmetz](https:\/\/stackoverflow.com\/users\/537098\/jmetz)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment73084197_38001353)\n\nThis is strange; according to [the docs](https:\/\/docs.scipy.org\/doc\/numpy\/reference\/arrays.indexing.html#advanced-indexing), boolean array indexing (which this is), is under **advanced indexing** which apparently \"always returns a copy of the data\", so you should be over-writing `x` with the new value (i.e. without the NaNs...). Can you provide any more info as to why this could be happening?\n\n2017-03-24T10:35:03.27Z+00:00\n\n0\n\nReply\n\n- Copy link\n\nThis answer is useful\n\n2\n\nSave this answer.\n\nShow activity on this post.\n\nSimply fill with\n```\n x = numpy.array([\n [0.99929941, 0.84724713, -0.1500044],\n [-0.79709026, numpy.NaN, -0.4406645],\n [-0.3599013, -0.63565744, -0.70251352]])\n\nx[numpy.isnan(x)] = .555\n\nprint(x)\n\n# [[ 0.99929941  0.84724713 -0.1500044 ]\n#  [-0.79709026  0.555      -0.4406645 ]\n#  [-0.3599013  -0.63565744 -0.70251352]]\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/65355087 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/65355087\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\n[edited Dec 18, 2020 at 10:59](https:\/\/stackoverflow.com\/posts\/65355087\/revisions \"show all edits to this post\")\n\nanswered Dec 18, 2020 at 10:08\n\n[![bitbang's user avatar](https:\/\/i.sstatic.net\/0As0j.jpg?s=64)](https:\/\/stackoverflow.com\/users\/13740191\/bitbang)\n\n[bitbang](https:\/\/stackoverflow.com\/users\/13740191\/bitbang)bitbang\n\n2,2721818 silver badges2020 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n1\n\nSave this answer.\n\nShow activity on this post.\n\npandas introduces an option to convert all data types to missing values.\n\n- <https:\/\/pandas.pydata.org\/docs\/user_guide\/missing_data.html>\n\nThe `np.isnan()` function is not compatible with all data types, e.g.\n```\n>>> import numpy as np\n>>> values = [np.nan, \"x\", \"y\"]\n>>> np.isnan(values)\nTraceback (most recent call last):\n  File \"<stdin>\", line 1, in <module>\nTypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''\n```\nThe `pd.isna()` and `pd.notna()` functions are compatible with many data types and pandas introduces a `pd.NA` value:\n```\n>>> import numpy as np\n>>> import pandas as pd\n\n>>> values = pd.Series([np.nan, \"x\", \"y\"])\n>>> values\n0    NaN\n1      x\n2      y\ndtype: object\n>>> values.loc[pd.isna(values)]\n0    NaN\ndtype: object\n>>> values.loc[pd.isna(values)] = pd.NA\n>>> values.loc[pd.isna(values)]\n0    <NA>\ndtype: object\n>>> values\n0    <NA>\n1       x\n2       y\ndtype: object\n\n#\n# using map with lambda, or a list comprehension\n#\n\n>>> values = [np.nan, \"x\", \"y\"]\n>>> list(map(lambda x: pd.NA if pd.isna(x) else x, values))\n[<NA>, 'x', 'y']\n>>> [pd.NA if pd.isna(x) else x for x in values]\n[<NA>, 'x', 'y']\n```\n\n[Share](https:\/\/stackoverflow.com\/a\/72293751 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 4.0](https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/ \"The current license for this post: CC BY-SA 4.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/72293751\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\n[edited May 19, 2022 at 16:50](https:\/\/stackoverflow.com\/posts\/72293751\/revisions \"show all edits to this post\")\n\nanswered May 18, 2022 at 17:43\n\n[![Darren Weber's user avatar](https:\/\/www.gravatar.com\/avatar\/b01bc87327d1c6c00446b2f583365ce8?s=64&d=identicon&r=PG)](https:\/\/stackoverflow.com\/users\/1172685\/darren-weber)\n\n[Darren Weber](https:\/\/stackoverflow.com\/users\/1172685\/darren-weber)Darren Weber\n\n1,71411 gold badge2121 silver badges2222 bronze badges\n\n## Comments\nAdd a comment\n\nThis answer is useful\n\n\\-2\n\nSave this answer.\n\nShow activity on this post.\n\nA simplest way is:\n```\nnumpy.nan_to_num(x)\n```\nDocumentation: <https:\/\/docs.scipy.org\/doc\/numpy\/reference\/generated\/numpy.nan_to_num.html>\n\n[Share](https:\/\/stackoverflow.com\/a\/44683212 \"Short permalink to this answer\")\n\nShare a link to this answer\n\nCopy link\n\n[CC BY-SA 3.0](https:\/\/creativecommons.org\/licenses\/by-sa\/3.0\/ \"The current license for this post: CC BY-SA 3.0\")\n\n[Improve this answer](https:\/\/stackoverflow.com\/posts\/44683212\/edit)\n\nFollow\n\nFollow this answer to receive notifications\n\nanswered Jun 21, 2017 at 18:03\n\n[![Bruno Rodrigues de Oliveira's user avatar](https:\/\/graph.facebook.com\/401667373377025\/picture?type=large)](https:\/\/stackoverflow.com\/users\/8195855\/bruno-rodrigues-de-oliveira)\n\n[Bruno Rodrigues de Oliveira](https:\/\/stackoverflow.com\/users\/8195855\/bruno-rodrigues-de-oliveira)Bruno Rodrigues de Oliveira\n\n4522 bronze badges\n\n## 1 Comment\nAdd a comment\n\n[![](https:\/\/i.sstatic.net\/X1eYb.png?s=64)](https:\/\/stackoverflow.com\/users\/4211279\/pier-paolo)\n\nPier Paolo\n\n[Pier Paolo](https:\/\/stackoverflow.com\/users\/4211279\/pier-paolo)\n\n[Over a year ago](https:\/\/stackoverflow.com\/questions\/11620914\/how-do-i-remove-nan-values-from-a-numpy-array#comment76352149_44683212)\n\nWelcome to SO! The solution you propose does not answer the problem: your solution substitutes `NaN`s with a large number, while the OP asked to entirely remove the elements.\n\n2017-06-21T18:49:31.223Z+00:00\n\n6\n\nReply\n\n- Copy link\n\n**[Protected question](https:\/\/stackoverflow.com\/help\/privileges\/protect-questions)**. To answer this question, you need to have at least 10 reputation on this site (not counting the [association bonus](https:\/\/meta.stackexchange.com\/questions\/141648\/what-is-the-association-bonus-and-how-does-it-work)). 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Boilerpipe Text	To remove NaN values from a NumPy array x : x = x[~numpy.isnan(x)] Explanation The inner function numpy.isnan returns a boolean/logical array which has the value True everywhere that x is not-a-number. Since we want the opposite, we use the logical-not operator ~ to get an array with True s everywhere that x is a valid number. Lastly, we use this logical array to index into the original array x , in order to retrieve just the non-NaN values.
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To gain full voting privileges, [earn reputation](https://stackoverflow.com/help/whats-reputation). Got it\! Go to help center to learn more # [How do I remove NaN values from a NumPy array?](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array) [Ask Question](https://stackoverflow.com/questions/ask) Asked 13 years, 2 months ago Modified [3 years, 2 months ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array?lastactivity "2022-07-30 05:52:24Z") Viewed 879k times This question shows research effort; it is useful and clear 392 Save this question. Show activity on this post. How do I remove NaN values from a NumPy array? ``` [1, 2, NaN, 4, NaN, 8] ⟶ [1, 2, 4, 8] ``` - [python](https://stackoverflow.com/questions/tagged/python "show questions tagged 'python'") - [numpy](https://stackoverflow.com/questions/tagged/numpy "show questions tagged 'numpy'") - [nan](https://stackoverflow.com/questions/tagged/nan "show questions tagged 'nan'") [Share](https://stackoverflow.com/q/11620914 "Short permalink to this question") Share a link to this question Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this question](https://stackoverflow.com/posts/11620914/edit) Follow Follow this question to receive notifications [edited Jul 30, 2022 at 5:36](https://stackoverflow.com/posts/11620914/revisions "show all edits to this post") [![Mateen Ulhaq's user avatar](https://i.sstatic.net/4cFxJ9Lj.jpg?s=64)](https://stackoverflow.com/users/365102/mateen-ulhaq) [Mateen Ulhaq](https://stackoverflow.com/users/365102/mateen-ulhaq) 27\.7k2121 gold badges120120 silver badges155155 bronze badges asked Jul 23, 2012 at 21:36 [![Dax Feliz's user avatar](https://www.gravatar.com/avatar/543c6d262d8dc2818e8d3e86f35f65d1?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/1464677/dax-feliz) [Dax Feliz](https://stackoverflow.com/users/1464677/dax-feliz)Dax Feliz 13k88 gold badges3333 silver badges3434 bronze badges 0 [Add a comment](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array "Use comments to ask for more information or suggest improvements. Avoid answering questions in comments.") \\| ## 13 Answers 13 Sorted by: [Reset to default](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array?answertab=scoredesc#tab-top) This answer is useful 630 Save this answer. Show activity on this post. To remove NaN values from a NumPy array `x`: ``` x = x[~numpy.isnan(x)] ``` ##### Explanation The inner function `numpy.isnan` returns a boolean/logical array which has the value `True` everywhere that `x` is not-a-number. Since we want the opposite, we use the logical-not operator `~` to get an array with `True`s everywhere that `x` is a valid number. Lastly, we use this logical array to index into the original array `x`, in order to retrieve just the non-NaN values. [Share](https://stackoverflow.com/a/11620982 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/11620982/edit) Follow Follow this answer to receive notifications [edited Jul 30, 2022 at 5:52](https://stackoverflow.com/posts/11620982/revisions "show all edits to this post") [![Mateen Ulhaq's user avatar](https://i.sstatic.net/4cFxJ9Lj.jpg?s=64)](https://stackoverflow.com/users/365102/mateen-ulhaq) [Mateen Ulhaq](https://stackoverflow.com/users/365102/mateen-ulhaq) 27\.7k2121 gold badges120120 silver badges155155 bronze badges answered Jul 23, 2012 at 21:42 [![jmetz's user avatar](https://www.gravatar.com/avatar/4c794978de2f7a314b349f68bf0aad91?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/537098/jmetz) [jmetz](https://stackoverflow.com/users/537098/jmetz)jmetz 12\.9k33 gold badges3232 silver badges4141 bronze badges Sign up to request clarification or add additional context in comments. ## 10 Comments Add a comment [![](https://www.gravatar.com/avatar/052338b3d753f00bb7724f2d2ca060a4?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/7650/miki-tebeka) Miki Tebeka [Miki Tebeka](https://stackoverflow.com/users/7650/miki-tebeka) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment15389511_11620982) Or `x = x[numpy.isfinite(x)]` 2012-07-23T22:29:06.803Z+00:00 53 Reply - Copy link [![](https://www.gravatar.com/avatar/da347a842b3231aad6e506c93ab95564?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/424651/chbrown) chbrown [chbrown](https://stackoverflow.com/users/424651/chbrown) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment29913880_11620982) Or `x = x[~numpy.isnan(x)]`, which is equivalent to mutzmatron's original answer, but shorter. In case you want to keep your infinities around, know that `numpy.isfinite(numpy.inf) == False`, of course, but `~numpy.isnan(numpy.inf) == True`. 2013-11-19T19:02:34.14Z+00:00 23 Reply - Copy link [![](https://i.sstatic.net/xkm1p.png?s=64)](https://stackoverflow.com/users/3765905/boltzmannbrain) BoltzmannBrain [BoltzmannBrain](https://stackoverflow.com/users/3765905/boltzmannbrain) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment79136181_11620982) For people looking to solve this with an ndarray and maintain the dimensions, use [numpy where](https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html): `np.where(np.isfinite(x), x, 0)` 2017-09-07T02:51:07.263Z+00:00 17 Reply - Copy link [![](https://www.gravatar.com/avatar/639520c5cc3265d60692c09ba796beb2?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/796919/towry) towry [towry](https://stackoverflow.com/users/796919/towry) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment89217800_11620982) TypeError: only integer scalar arrays can be converted to a scalar index 2018-06-30T14:29:37.237Z+00:00 1 Reply - Copy link [![](https://www.gravatar.com/avatar/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/537098/jmetz) jmetz [jmetz](https://stackoverflow.com/users/537098/jmetz) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment89254484_11620982) @towry: this is happening because your input, `x` is not a numpy array. If you want to use logical indexing, it must be an array - e.g. `x = np.array(x)` 2018-07-02T11:32:48.91Z+00:00 1 Reply - Copy link Add a comment \\| Show 5 more comments This answer is useful 77 Save this answer. Show activity on this post. ``` filter(lambda v: v==v, x) ``` works both for lists and numpy array since v!=v only for NaN [Share](https://stackoverflow.com/a/29679784 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/29679784/edit) Follow Follow this answer to receive notifications answered Apr 16, 2015 at 15:46 [![udibr's user avatar](https://i.sstatic.net/fbqjx.jpg?s=64)](https://stackoverflow.com/users/209852/udibr) [udibr](https://stackoverflow.com/users/209852/udibr)udibr 1,08977 silver badges55 bronze badges ## 8 Comments Add a comment [![](https://www.gravatar.com/avatar/7fd359ed56b0d634d5c16dacbcf5f042?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/157441/austin-richardson) Austin Richardson [Austin Richardson](https://stackoverflow.com/users/157441/austin-richardson) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment50249119_29679784) A hack but an especially useful one in the case where you are filtering nans from an array of objects with mixed types, such as a strings and nans. 2015-06-29T14:15:01.693Z+00:00 12 Reply - Copy link [![](https://www.gravatar.com/avatar/9bf6decd8e2acafb6d371c2a1a6f7e1b?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/6260170/chris-rands) Chris\_Rands [Chris\_Rands](https://stackoverflow.com/users/6260170/chris-rands) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment90198356_29679784) This might seem clever, but if obscures the logic and theoretically other objects (such as custom classes) can also have this property 2018-07-31T15:02:58.11Z+00:00 5 Reply - Copy link [![](https://www.gravatar.com/avatar/acb61aa42806f4679c1f1e35aea857ed?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/1825043/christian-oreilly) Christian O'Reilly [Christian O'Reilly](https://stackoverflow.com/users/1825043/christian-oreilly) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment110324628_29679784) Also useful because it only needs `x` to be specified once as opposed to solutions of the type `x[~numpy.isnan(x)]`. This is convenient when `x` is defined by a long expression and you don't want to clutter the code by creating a temporary variable to store the result of this long expression. 2020-06-15T01:09:11.307Z+00:00 1 Reply - Copy link [![](https://www.gravatar.com/avatar/568ffd089d5715f39acc4de2bf72c261?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/1795641/smm) smm [smm](https://stackoverflow.com/users/1795641/smm) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment112340733_29679784) It might be slow compere to `x[~numpy.isnan(x)]` 2020-08-21T21:23:10.413Z+00:00 1 Reply - Copy link [![](https://i.sstatic.net/PyUIB.png?s=64)](https://stackoverflow.com/users/7362806/m-idk392845) M\_Idk392845 [M\_Idk392845](https://stackoverflow.com/users/7362806/m-idk392845) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment131554252_29679784) what is v and what is x? 2022-11-21T21:12:32.293Z+00:00 1 Reply - Copy link Add a comment \\| Show 3 more comments This answer is useful 47 Save this answer. Show activity on this post. For me the answer by @jmetz didn't work, however using pandas isnull() did. ``` x = x[~pd.isnull(x)] ``` [Share](https://stackoverflow.com/a/43475189 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/43475189/edit) Follow Follow this answer to receive notifications answered Apr 18, 2017 at 14:37 [![Daniel Kislyuk's user avatar](https://www.gravatar.com/avatar/c1296de0d5ade6f7d7c1020fc83ea526?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/1772802/daniel-kislyuk) [Daniel Kislyuk](https://stackoverflow.com/users/1772802/daniel-kislyuk)Daniel Kislyuk 1,0061111 silver badges1212 bronze badges ## 3 Comments Add a comment [![](https://www.gravatar.com/avatar/4bb4ac5216b835cd31e9e913334e2e63?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/4379906/kbridge4096) kbridge4096 [kbridge4096](https://stackoverflow.com/users/4379906/kbridge4096) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment128088483_43475189) or: `x = x[x.notnull()]` 2022-06-05T17:18:56.973Z+00:00 2 Reply - Copy link [![](https://www.gravatar.com/avatar/7f44b790df9ee198c42dcfd0ef2399af?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/20156987/llohann) Llohann [Llohann](https://stackoverflow.com/users/20156987/llohann) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment134949105_43475189) I am not found of including pandas on the pipe but the accepted solution got me `TypeError: ufunc 'isnan' not supported for the input types`. It does not work with strings or object types. This solution did. 2023-06-23T07:32:03.87Z+00:00 1 Reply - Copy link [![](https://i.sstatic.net/0y5dS.png?s=64)](https://stackoverflow.com/users/3429115/rafs) Rafs [Rafs](https://stackoverflow.com/users/3429115/rafs) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment137524880_43475189) Added benefit for this one is it removes `NaT`s out of the box 2024-02-16T15:53:31.297Z+00:00 0 Reply - Copy link Add a comment This answer is useful 36 Save this answer. Show activity on this post. Try this: ``` import math print [value for value in x if not math.isnan(value)] ``` For more, read on [List Comprehensions](http://docs.python.org/tutorial/datastructures.html#list-comprehensions). [Share](https://stackoverflow.com/a/11620945 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/11620945/edit) Follow Follow this answer to receive notifications answered Jul 23, 2012 at 21:39 [![liori's user avatar](https://www.gravatar.com/avatar/5ea9e348dc045d53f5659eadf3e695b2?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/42610/liori) [liori](https://stackoverflow.com/users/42610/liori)liori 42\.6k1313 gold badges8080 silver badges111111 bronze badges ## 3 Comments Add a comment [![](https://www.gravatar.com/avatar/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/537098/jmetz) jmetz [jmetz](https://stackoverflow.com/users/537098/jmetz) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment15406044_11620945) If you're using numpy both my answer and that by @lazy1 are almost an order of magnitude faster than the list comprehension - lazy1's solution is slightly faster (though technically will also not return any infinity values). 2012-07-24T13:54:16.493Z+00:00 6 Reply - Copy link [![](https://www.gravatar.com/avatar/b22fa97d3e76a2d9b907aba23b415fc6?s=48&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/4684507/hypers) hypers [hypers](https://stackoverflow.com/users/4684507/hypers) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment81833136_11620945) Don't forget the brackets :) `print ([value for value in x if not math.isnan(value)])` 2017-11-22T16:09:35.39Z+00:00 0 Reply - Copy link [![](https://i.sstatic.net/AfU4T.jpg?s=64)](https://stackoverflow.com/users/2523501/yeliabsalohcin) yeliabsalohcin [yeliabsalohcin](https://stackoverflow.com/users/2523501/yeliabsalohcin) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment93769176_11620945) If you're using numpy like the top answer then you can use this list comprehension answer with the `np` package: So returns your list without the nans: `[value for value in x if not np.isnan(value)]` 2018-11-23T14:09:28.98Z+00:00 0 Reply - Copy link Add a comment This answer is useful 28 Save this answer. Show activity on this post. [@jmetz's answer](https://stackoverflow.com/a/11620982/3645374) is probably the one most people need; however it yields a one-dimensional array, e.g. making it unusable to remove entire rows or columns in matrices. To do so, one should reduce the logical array to one dimension, then index the target array. For instance, the following will remove rows which have at least one NaN value: ``` x = x[~numpy.isnan(x).any(axis=1)] ``` See more detail [here](https://www.w3resource.com/python-exercises/numpy/python-numpy-exercise-91.php). [Share](https://stackoverflow.com/a/61589266 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/61589266/edit) Follow Follow this answer to receive notifications answered May 4, 2020 at 9:43 [![M4urice's user avatar](https://www.gravatar.com/avatar/ed25178db3eb0df549cd6689a8112f0f?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/3645374/m4urice) [M4urice](https://stackoverflow.com/users/3645374/m4urice)M4urice 66111 gold badge99 silver badges1616 bronze badges ## Comments Add a comment This answer is useful 10 Save this answer. Show activity on this post. As shown by others ``` x[~numpy.isnan(x)] ``` works. But it will throw an error if the numpy dtype is not a native data type, for example if it is object. In that case you can use pandas. ``` x[~pandas.isna(x)] or x[~pandas.isnull(x)] ``` [Share](https://stackoverflow.com/a/47486199 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/47486199/edit) Follow Follow this answer to receive notifications [edited Jan 9, 2020 at 13:55](https://stackoverflow.com/posts/47486199/revisions "show all edits to this post") [![Shashank Srivastava's user avatar](https://i.sstatic.net/kLskH.jpg?s=64)](https://stackoverflow.com/users/1688792/shashank-srivastava) [Shashank Srivastava](https://stackoverflow.com/users/1688792/shashank-srivastava) 19522 silver badges1313 bronze badges answered Nov 25, 2017 at 12:55 [![koliyat9811's user avatar](https://www.gravatar.com/avatar/97ec570ce35cf05e4a260e85e6079357?s=64&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/6248016/koliyat9811) [koliyat9811](https://stackoverflow.com/users/6248016/koliyat9811)koliyat9811 92511 gold badge1010 silver badges1212 bronze badges ## Comments Add a comment This answer is useful 8 Save this answer. Show activity on this post. If you're using `numpy` ``` # first get the indices where the values are finite ii = np.isfinite(x) # second get the values x = x[ii] ``` [Share](https://stackoverflow.com/a/48823495 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/48823495/edit) Follow Follow this answer to receive notifications answered Feb 16, 2018 at 9:19 [![aloha's user avatar](https://www.gravatar.com/avatar/bac2f103216583f9fed5705038434020?s=64&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/3097391/aloha) [aloha](https://stackoverflow.com/users/3097391/aloha)aloha 4,83466 gold badges3636 silver badges4343 bronze badges ## Comments Add a comment This answer is useful 7 Save this answer. Show activity on this post. The [accepted answer](https://stackoverflow.com/a/11620982/7128154) changes shape for 2d arrays. I present a solution here, using the Pandas [dropna()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html) functionality. It works for 1D and 2D arrays. In the 2D case you can choose weather to drop the row or column containing `np.nan`. ``` import pandas as pd import numpy as np def dropna(arr, args, kwarg): assert isinstance(arr, np.ndarray) dropped=pd.DataFrame(arr).dropna(args, *kwarg).values if arr.ndim==1: dropped=dropped.flatten() return dropped x = np.array([1400, 1500, 1600, np.nan, np.nan, np.nan ,1700]) y = np.array([[1400, 1500, 1600], [np.nan, 0, np.nan] ,[1700,1800,np.nan]] ) print('='20+' 1D Case: ' +'='20+'\nInput:\n',x,sep='') print('\ndropna:\n',dropna(x),sep='') print('\n\n'+'='20+' 2D Case: ' +'='20+'\nInput:\n',y,sep='') print('\ndropna (rows):\n',dropna(y),sep='') print('\ndropna (columns):\n',dropna(y,axis=1),sep='') print('\n\n'+'='20+' x[np.logical_not(np.isnan(x))] for 2D: ' +'='20+'\nInput:\n',y,sep='') print('\ndropna:\n',x[np.logical_not(np.isnan(x))],sep='') ``` Result:* ``` ==================== 1D Case: ==================== Input: [1400. 1500. 1600. nan nan nan 1700.] dropna: [1400. 1500. 1600. 1700.] ==================== 2D Case: ==================== Input: [[1400. 1500. 1600.] [ nan 0. nan] [1700. 1800. nan]] dropna (rows): [[1400. 1500. 1600.]] dropna (columns): [[1500.] [ 0.] [1800.]] ==================== x[np.logical_not(np.isnan(x))] for 2D: ==================== Input: [[1400. 1500. 1600.] [ nan 0. nan] [1700. 1800. nan]] dropna: [1400. 1500. 1600. 1700.] ``` [Share](https://stackoverflow.com/a/55194127 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/55194127/edit) Follow Follow this answer to receive notifications answered Mar 16, 2019 at 6:37 [![Markus Dutschke's user avatar](https://i.sstatic.net/E3sBH.png?s=64)](https://stackoverflow.com/users/7128154/markus-dutschke) [Markus Dutschke](https://stackoverflow.com/users/7128154/markus-dutschke)Markus Dutschke 10\.7k44 gold badges7272 silver badges6767 bronze badges ## Comments Add a comment This answer is useful 7 Save this answer. Show activity on this post. In case it helps, for simple 1d arrays: ``` x = np.array([np.nan, 1, 2, 3, 4]) x[~np.isnan(x)] >>> array([1., 2., 3., 4.]) ``` but if you wish to expand to matrices and preserve the shape: ``` x = np.array([ [np.nan, np.nan], [np.nan, 0], [1, 2], [3, 4] ]) x[~np.isnan(x).any(axis=1)] >>> array([[1., 2.], [3., 4.]]) ``` I encountered this issue when dealing with pandas `.shift()` functionality, and I wanted to avoid using `.apply(..., axis=1)` at all cost due to its inefficiency. [Share](https://stackoverflow.com/a/66643691 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/66643691/edit) Follow Follow this answer to receive notifications answered Mar 15, 2021 at 18:36 [![Robin Teuwens's user avatar](https://www.gravatar.com/avatar/d48c49b3ba564556f14fbf8f0ba873f8?s=64&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/10905753/robin-teuwens) [Robin Teuwens](https://stackoverflow.com/users/10905753/robin-teuwens)Robin Teuwens 15111 silver badge66 bronze badges ## Comments Add a comment This answer is useful 6 Save this answer. Show activity on this post. Doing the above : ``` x = x[~numpy.isnan(x)] ``` or ``` x = x[numpy.logical_not(numpy.isnan(x))] ``` I found that resetting to the same variable (x) did not remove the actual nan values and had to use a different variable. Setting it to a different variable removed the nans. e.g. ``` y = x[~numpy.isnan(x)] ``` [Share](https://stackoverflow.com/a/38001353 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/38001353/edit) Follow Follow this answer to receive notifications answered Jun 23, 2016 at 20:35 [![melissaOu's user avatar](https://www.gravatar.com/avatar/3b688306f3155459264145b9ca5dbfb5?s=64&d=identicon&r=PG&f=y&so-version=2)](https://stackoverflow.com/users/6506193/melissaou) [melissaOu](https://stackoverflow.com/users/6506193/melissaou)melissaOu 6111 silver badge22 bronze badges ## 1 Comment Add a comment [![](https://www.gravatar.com/avatar/4c794978de2f7a314b349f68bf0aad91?s=48&d=identicon&r=PG)](https://stackoverflow.com/users/537098/jmetz) jmetz [jmetz](https://stackoverflow.com/users/537098/jmetz) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment73084197_38001353) This is strange; according to [the docs](https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing), boolean array indexing (which this is), is under advanced indexing which apparently "always returns a copy of the data", so you should be over-writing `x` with the new value (i.e. without the NaNs...). Can you provide any more info as to why this could be happening? 2017-03-24T10:35:03.27Z+00:00 0 Reply - Copy link This answer is useful 2 Save this answer. Show activity on this post. Simply fill with ``` x = numpy.array([ [0.99929941, 0.84724713, -0.1500044], [-0.79709026, numpy.NaN, -0.4406645], [-0.3599013, -0.63565744, -0.70251352]]) x[numpy.isnan(x)] = .555 print(x) # [[ 0.99929941 0.84724713 -0.1500044 ] # [-0.79709026 0.555 -0.4406645 ] # [-0.3599013 -0.63565744 -0.70251352]] ``` [Share](https://stackoverflow.com/a/65355087 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/65355087/edit) Follow Follow this answer to receive notifications [edited Dec 18, 2020 at 10:59](https://stackoverflow.com/posts/65355087/revisions "show all edits to this post") answered Dec 18, 2020 at 10:08 [![bitbang's user avatar](https://i.sstatic.net/0As0j.jpg?s=64)](https://stackoverflow.com/users/13740191/bitbang) [bitbang](https://stackoverflow.com/users/13740191/bitbang)bitbang 2,2721818 silver badges2020 bronze badges ## Comments Add a comment This answer is useful 1 Save this answer. Show activity on this post. pandas introduces an option to convert all data types to missing values. - <https://pandas.pydata.org/docs/user_guide/missing_data.html> The `np.isnan()` function is not compatible with all data types, e.g. ``` >>> import numpy as np >>> values = [np.nan, "x", "y"] >>> np.isnan(values) Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'' ``` The `pd.isna()` and `pd.notna()` functions are compatible with many data types and pandas introduces a `pd.NA` value: ``` >>> import numpy as np >>> import pandas as pd >>> values = pd.Series([np.nan, "x", "y"]) >>> values 0 NaN 1 x 2 y dtype: object >>> values.loc[pd.isna(values)] 0 NaN dtype: object >>> values.loc[pd.isna(values)] = pd.NA >>> values.loc[pd.isna(values)] 0 <NA> dtype: object >>> values 0 <NA> 1 x 2 y dtype: object # # using map with lambda, or a list comprehension # >>> values = [np.nan, "x", "y"] >>> list(map(lambda x: pd.NA if pd.isna(x) else x, values)) [<NA>, 'x', 'y'] >>> [pd.NA if pd.isna(x) else x for x in values] [<NA>, 'x', 'y'] ``` [Share](https://stackoverflow.com/a/72293751 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/ "The current license for this post: CC BY-SA 4.0") [Improve this answer](https://stackoverflow.com/posts/72293751/edit) Follow Follow this answer to receive notifications [edited May 19, 2022 at 16:50](https://stackoverflow.com/posts/72293751/revisions "show all edits to this post") answered May 18, 2022 at 17:43 [![Darren Weber's user avatar](https://www.gravatar.com/avatar/b01bc87327d1c6c00446b2f583365ce8?s=64&d=identicon&r=PG)](https://stackoverflow.com/users/1172685/darren-weber) [Darren Weber](https://stackoverflow.com/users/1172685/darren-weber)Darren Weber 1,71411 gold badge2121 silver badges2222 bronze badges ## Comments Add a comment This answer is useful \-2 Save this answer. Show activity on this post. A simplest way is: ``` numpy.nan_to_num(x) ``` Documentation: <https://docs.scipy.org/doc/numpy/reference/generated/numpy.nan_to_num.html> [Share](https://stackoverflow.com/a/44683212 "Short permalink to this answer") Share a link to this answer Copy link [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/ "The current license for this post: CC BY-SA 3.0") [Improve this answer](https://stackoverflow.com/posts/44683212/edit) Follow Follow this answer to receive notifications answered Jun 21, 2017 at 18:03 [![Bruno Rodrigues de Oliveira's user avatar](https://graph.facebook.com/401667373377025/picture?type=large)](https://stackoverflow.com/users/8195855/bruno-rodrigues-de-oliveira) [Bruno Rodrigues de Oliveira](https://stackoverflow.com/users/8195855/bruno-rodrigues-de-oliveira)Bruno Rodrigues de Oliveira 4522 bronze badges ## 1 Comment Add a comment [![](https://i.sstatic.net/X1eYb.png?s=64)](https://stackoverflow.com/users/4211279/pier-paolo) Pier Paolo [Pier Paolo](https://stackoverflow.com/users/4211279/pier-paolo) [Over a year ago](https://stackoverflow.com/questions/11620914/how-do-i-remove-nan-values-from-a-numpy-array#comment76352149_44683212) Welcome to SO! The solution you propose does not answer the problem: your solution substitutes `NaN`s with a large number, while the OP asked to entirely remove the elements. 2017-06-21T18:49:31.223Z+00:00 6 Reply - Copy link [Protected question](https://stackoverflow.com/help/privileges/protect-questions). To answer this question, you need to have at least 10 reputation on this site (not counting the [association bonus](https://meta.stackexchange.com/questions/141648/what-is-the-association-bonus-and-how-does-it-work)). The reputation requirement helps protect this question from spam and non-answer activity. Start asking to get answers Find the answer to your question by asking. 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