{"id":245,"date":"2021-09-02T13:08:53","date_gmt":"2021-09-02T13:08:53","guid":{"rendered":"https:\/\/www.jibsheet.net\/linux\/?p=245"},"modified":"2021-09-02T13:14:35","modified_gmt":"2021-09-02T13:14:35","slug":"pandas-python-how-to-drop-a-row-with-nan","status":"publish","type":"post","link":"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/","title":{"rendered":"Pandas\/Python – how to drop a row with ‘NaN’"},"content":{"rendered":"

So, you want to get rid of any row that has ‘NaN’ ( null or not a number ) values, because it doesn’t work with some functions ( or can’t ignore )<\/p>\n

obs1.dropna(how = 'all', subset = ['wind_mph'], inplace = True)\r\nobs1 = obs1.reset_index(drop=True)<\/pre>\n
Another important point – is that with Pandas – you have to convert any value you load to NaN.\u00a0 Or somehow change it to the cannonical ‘NaN’.\u00a0 \u00a0here is a way to convert text to ‘NaN’.\u00a0 \u00a0 This might also clean up any automated conversion for columns – so if 99.9% of your column data is float, but one value text or something – it will though an internal exception and keep the column as a object.\u00a0 The data my program generates puts a “<no_value_provided>”, the parm to use is na_values ( and it can be a list if your data has more than one notation.<\/p>\n
def date_utc(x): return dateutil.parser.parse(x[:20], ignoretz=True)\r\nobs1 = pd.read_csv(target_csv, parse_dates=[9], date_parser=date_utc,\r\n                    dtype = { 'wind_mph': 'float64'},\r\n                    na_values = \"<no_value_provided>\")<\/pre>\n
 <\/p>\n","protected":false},"excerpt":{"rendered":"
So, you want to get rid of any row that has ‘NaN’ ( null or not a number ) values, because it doesn’t work with some functions ( or can’t ignore ) obs1.dropna(how = ‘all’, subset = [‘wind_mph’], inplace = True) obs1 = obs1.reset_index(drop=True) Another important point – is that with Pandas – you have to convert any value you […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[14,7,1],"tags":[],"yoast_head":"\nPandas\/Python - how to drop a row with 'NaN' - Jon Allen's Linux Stuff<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas\/Python - how to drop a row with 'NaN' - Jon Allen's Linux Stuff\" \/>\n<meta property=\"og:description\" content=\"So, you want to get rid of any row that has ‘NaN’ ( null or not a number ) values, because it doesn’t work with some functions ( or can’t ignore ) obs1.dropna(how = 'all', subset = ['wind_mph'], inplace = True) obs1 = obs1.reset_index(drop=True) Another important point – is that with Pandas – you have to convert any value you […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\" \/>\n<meta property=\"og:site_name\" content=\"Jon Allen's Linux Stuff\" \/>\n<meta property=\"article:published_time\" content=\"2021-09-02T13:08:53+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-09-02T13:14:35+00:00\" \/>\n<meta name=\"author\" content=\"jonallen\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"jonallen\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\"},\"author\":{\"name\":\"jonallen\",\"@id\":\"https:\/\/www.jibsheet.net\/linux\/#\/schema\/person\/295a80d0b2aa929b648c4fdddee83993\"},\"headline\":\"Pandas\/Python – how to drop a row with ‘NaN’\",\"datePublished\":\"2021-09-02T13:08:53+00:00\",\"dateModified\":\"2021-09-02T13:14:35+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\"},\"wordCount\":147,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.jibsheet.net\/linux\/#\/schema\/person\/295a80d0b2aa929b648c4fdddee83993\"},\"articleSection\":[\"Pandas\",\"Python\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\",\"url\":\"https:\/\/www.jibsheet.net\/linux\/index.php\/2021\/09\/02\/pandas-python-how-to-drop-a-row-with-nan\/\",\"name\":\"Pandas\/Python - 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