{"id":13773,"date":"2024-03-15T07:50:57","date_gmt":"2024-03-15T07:50:57","guid":{"rendered":"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/"},"modified":"2025-08-05T23:15:46","modified_gmt":"2025-08-05T23:15:46","slug":"what-is-the-usage-of-the-numpy-sum-function","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/","title":{"rendered":"NumPy Sum Function Usage Guide"},"content":{"rendered":"

The sum function in the numpy library is used to calculate the sum of elements in an array.<\/p>\n

Usage:
\nnumpy.sum(a, axis=None, dtype=None, out=None, keepdims=)<\/p>\n

Parameter description:<\/p>\n

    \n
  1. Array<\/li>\n
  2. Axis: Specifies the axis along which the calculations are performed. The default is None, which means all elements are summed. If axis=0 is specified, the sum is taken along the columns; if axis=1 is specified, the sum is taken along the rows.<\/li>\n
  3. dtype: specifies the data type of the returned value, by default is None, which means it will retain the original data type of the array.<\/li>\n
  4. Output: Specify the output array to store the computed results.<\/li>\n
  5. “keepdims: maintain the dimensions of the output array. If set to True, the result will have the same dimensions as the input array, but if set to False, the result will be a simplified array.”<\/li>\n<\/ol>\n

    Return value:
    \nReturn an array or a scalar indicating the sum of the elements in the array.<\/p>\n

    Original: \u6211\u5f88\u9ad8\u5174\u80fd\u5e2e\u52a9\u4f60\u3002<\/p>\n

    Paraphrased: I’m glad I could help you.<\/p>\n

    import numpy as np\r\n\r\na = np.array([1, 2, 3, 4, 5])\r\nprint(np.sum(a))  # \u8f93\u51fa15\r\n\r\nb = np.array([[1, 2, 3], [4, 5, 6]])\r\nprint(np.sum(b))  # \u8f93\u51fa21\r\n\r\nc = np.array([[1, 2, 3], [4, 5, 6]])\r\nprint(np.sum(c, axis=0))  # \u8f93\u51fa[5 7 9]\r\n\r\nd = np.array([[1, 2, 3], [4, 5, 6]])\r\nprint(np.sum(d, axis=1))  # \u8f93\u51fa[ 6 15]\r\n\r\ne = np.array([[1, 2, 3], [4, 5, 6]])\r\nprint(np.sum(e, axis=1, keepdims=True))  # \u8f93\u51fa[[ 6] [15]]\r\n<\/code><\/pre>\n
    In the above code, the sum of elements in arrays a, b, c, d, and e is calculated separately.<\/p>\n","protected":false},"excerpt":{"rendered":"
    The sum function in the numpy library is used to calculate the sum of elements in an array. Usage: numpy.sum(a, axis=None, dtype=None, out=None, keepdims=) Parameter description: Array Axis: Specifies the axis along which the calculations are performed. The default is None, which means all elements are summed. If axis=0 is specified, the sum is taken […]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","footnotes":""},"categories":[1],"tags":[3719,71,73,299,72],"class_list":["post-13773","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-array","tag-data-science","tag-numpy","tag-programming","tag-python"],"yoast_head":"\nNumPy Sum Function Usage Guide - Blog - Silicon Cloud<\/title>\n<meta name=\"description\" content=\"Learn how to use NumPy sum for array calculations. 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Explains axis, dtype parameters with examples for efficient data operations.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - Silicon Cloud\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/SiliCloudGlobal\/\" \/>\n<meta property=\"article:published_time\" content=\"2024-03-15T07:50:57+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-08-05T23:15:46+00:00\" \/>\n<meta name=\"author\" content=\"William Carter\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@SiliCloudGlobal\" \/>\n<meta name=\"twitter:site\" content=\"@SiliCloudGlobal\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"William Carter\" \/>\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.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/\"},\"author\":{\"name\":\"William Carter\",\"@id\":\"https:\/\/www.silicloud.com\/blog\/#\/schema\/person\/f697031891aacefc4b681d139781d3c0\"},\"headline\":\"NumPy Sum Function Usage Guide\",\"datePublished\":\"2024-03-15T07:50:57+00:00\",\"dateModified\":\"2025-08-05T23:15:46+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/\"},\"wordCount\":194,\"publisher\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/#organization\"},\"keywords\":[\"array\",\"data science\",\"NumPy\",\"programming\",\"Python\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/\",\"url\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-the-numpy-sum-function\/\",\"name\":\"NumPy Sum Function Usage Guide - Blog - Silicon Cloud\",\"isPartOf\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/#website\"},\"datePublished\":\"2024-03-15T07:50:57+00:00\",\"dateModified\":\"2025-08-05T23:15:46+00:00\",\"description\":\"Learn how to use NumPy sum for array calculations. 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