from platform import python_version\n\nprint(python_version())\n------\n3.8.10<\/code><\/pre><\/div>\n\n\n\n- numpy 1.21.4<\/li><\/ul>\n\n\n\n
from platform import python_version\n\nprint(python_version())\n------\n1.21.4<\/code><\/pre><\/div>\n\n\n\n<\/p>\n\n\n\n
<\/span>\u691c\u8a3c\u7528\u30ea\u30b9\u30c8<\/span><\/h2>\n\n\n\nTrue\u3068False\u3067\u69cb\u6210\u3055\u308c\u305f\u30ea\u30b9\u30c8\u3001True\u3068False\u30681,0\u3067\u69cb\u6210\u3055\u308c\u305f\u30ea\u30b9\u30c8\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002<\/p>\n\n\n\n
import numpy as np\nbl_lst = np.array([True, True, False, True, False])\nbl_int_lst = np.array([True, 1, False, 1, 0])<\/code><\/pre><\/div>\n\n\n\n<\/span>\u683c\u7d0d\u3057\u305f\u969b\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\n\u307e\u305a\u3001\u683c\u7d0d\u76f4\u5f8c\u306b\u5024\u304c\u3069\u3046\u306a\u308b\u304b\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002bool\u578b\u306e\u307f\u306e\u5834\u5408\u306fbool\u578b\u306e\u307e\u307e\u3067\u3059\u304c\u3001bool\u3068\u6574\u6570\u304c\u6df7\u5728\u3057\u3066\u3044\u308b\u5834\u5408\u306fTrue : 1\u3001False : 0\u3068\u81ea\u52d5\u7684\u306b\u7f6e\u63db\u3055\u308c\u307e\u3059\u3002<\/strong>\u3053\u306e\u524d\u63d0\u6761\u4ef6\u3092\u7406\u89e3\u3059\u308b\u3068\u305d\u306e\u5f8c\u306e\u6319\u52d5\u3082\u3059\u3093\u306a\u308a\u3068\u8179\u843d\u3061\u3057\u307e\u3057\u305f\u3002<\/p>\n\n\n\nprint("bool list: {}".format(bl_lst))\nprint("bool&int_list: {}".format(bl_int_lst))\n-----\nbool list: [ True True False True False]\nbool&int_list: [1 1 0 1 0]<\/code><\/pre><\/div>\n\n\n\n<\/span>\u5e73\u5747(mean)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nTrue\u304c1\u3001False\u304c0\u3068\u307f\u306a\u3055\u308c\u3066\u5e73\u5747\u5024\u304c\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
print("mean of bool: {}".format(np.mean(bl_lst)))\nprint("mean of bool&int: {}".format(np.mean(bl_int_lst)))\n-----\nmean of bool: 0.6\nmean of bool&int: 0.6<\/code><\/pre><\/div>\n\n\n\n<\/span>\u4e2d\u592e\u5024(median)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nmedian\u306b\u3064\u3044\u3066\u3082mean\u3068\u540c\u69d8\u306bTrue : 1 \u3001False : 0\u306e\u63db\u7b97\u5f0f\u3067\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
print("median of bool: {}".format(np.median(bl_lst)))\nprint("median of bool&int: {}".format(np.median(bl_int_lst)))\n-----\nmedian of bool: 1.0\nmedian of bool&int: 1.0<\/code><\/pre><\/div>\n\n\n\n<\/span>\u5206\u6563(var)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nvar\u3082True : 1 \u3001False : 0\u306e\u63db\u7b97\u5f0f\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
print("var of bool: {}".format(np.var(bl_lst)))\nprint("var of bool&int: {}".format(np.var(bl_int_lst)))\n-----\nvar of bool: 0.24000000000000005\nvar of bool&int: 0.24000000000000005<\/code><\/pre><\/div>\n\n\n\n<\/p>\n\n\n\n
<\/span>\u5408\u8a08(sum)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nsum\u306e\u5834\u5408\u3082\u540c\u69d8\u306bTrue : 1\u3001False : 0\u3067\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
print("sum of bool: {}".format(np.sum(bl_lst)))\nprint("sum of bool&int: {}".format(np.sum(bl_int_lst)))\n-----\nsum of bool: 3\nsum of bool&int: 3<\/code><\/pre><\/div>\n\n\n\n<\/span>\u6700\u5927(max)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nbool\u578b\u306e\u307f\u306e\u30ea\u30b9\u30c8\u306e\u5834\u5408\u306fTrue\u304cmax\u3068\u3057\u3066\u62bd\u51fa\u3055\u308c\u307e\u3059\u3002bool\u578b\u3068int\u304c\u6df7\u5728\u3057\u305f\u30ea\u30b9\u30c8\u306f\u3059\u3079\u3066int\u306b\u7f6e\u63db\u3055\u308c\u3066\u3044\u308b\u305f\u3081\u3001max\u3068\u3057\u3066\u306f1\u304c\u9078\u3070\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
print("max of bool: {}".format(np.max(bl_lst)))\nprint("max of bool&int: {}".format(np.max(bl_int_lst)))\n-----\nmax of bool: True\nmax of bool&int: 1<\/code><\/pre><\/div>\n\n\n\n<\/span>\u6700\u5c0f(min)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\n bool\u578b\u306e\u307f\u306e\u30ea\u30b9\u30c8\u306e\u5834\u5408\u306fFalse\u304cmin\u3068\u3057\u3066\u62bd\u51fa\u3055\u308c\u307e\u3059\u3002bool\u578b\u3068int\u304c\u6df7\u5728\u3057\u305f\u30ea\u30b9\u30c8\u306f\u3059\u3079\u3066int\u306b\u7f6e\u63db\u3055\u308c\u3066\u3044\u308b\u305f\u3081\u3001min\u3068\u3057\u3066\u306f0\u304c\u9078\u3070\u308c\u307e\u3059\u3002<\/p>\n\n\n\n
print("min of bool: {}".format(np.min(bl_lst)))\nprint("min of bool&int: {}".format(np.min(bl_int_lst)))\n-----\nmin of bool: False\nmin of bool&int: 0<\/code><\/pre><\/div>\n\n\n\n<\/span>\u30bd\u30fc\u30c8(sort)\u306e\u6319\u52d5<\/span><\/h2>\n\n\n\nsort\u306e\u30c7\u30d5\u30a9\u30eb\u30c8\u306f\u964d\u9806\u30bd\u30fc\u30c8\u306b\u306a\u308a\u307e\u3059\u304c\u3001bool\u578b\u306e\u307f\u306e\u5834\u5408\u306fFalse\u2192True\u306e\u9806\u306b\u4e26\u3073\u307e\u3059\u3002bool\u578b\u3068int\u578b\u306e\u6df7\u5728\u306b\u3064\u3044\u3066\u306fTrue : 1\u3001False\uff1a0\u306b\u7f6e\u63db\u3055\u308c\u3066\u3044\u308b\u306e\u30670\u21921\u306e\u9806\u306b\u4e26\u3073\u307e\u3059\u3002<\/p>\n\n\n\n
print("sort of bool: {}".format(np.sort(bl_lst)))\nprint("sort of bool&int: {}".format(np.sort(bl_int_lst)))\n-----\nsort of bool: [False False True True True]\nsort of bool&int: [0 0 1 1 1]<\/code><\/pre><\/div>\n\n\n\n<\/p>\n\n\n\n
<\/p>\n\n\n\n
<\/span>\u307e\u3068\u3081<\/span><\/h2>\n\n\n\nTrue\u3001False\u306e\u6f14\u7b97\u306e\u6319\u52d5\u306b\u3064\u3044\u3066\u306f\u5fd8\u308c\u304c\u3061\u3067\u3059\u304c\u3001\u57fa\u672c\u7684\u306bTrue : 1 \u3001False : 0\u3068\u8003\u3048\u3066\u304a\u3051\u3070\u554f\u984c\u306a\u3044\u3067\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u6982\u8981 Numpy\u306f\u6570\u5024\u578b\u306e\u5024\u306b\u5bfe\u3057\u3066\u8c4a\u5bcc\u306a\u30e1\u30bd\u30c3\u30c9\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u304c\u3001...<\/p>\n","protected":false},"author":1,"featured_media":1218,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_locale":"ja","_original_post":"https:\/\/obenkyolab.com\/?p=3791","footnotes":""},"categories":[7],"tags":[95],"class_list":["post-3791","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","tag-numpy","ja"],"_links":{"self":[{"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/posts\/3791","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3791"}],"version-history":[{"count":6,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/posts\/3791\/revisions"}],"predecessor-version":[{"id":4581,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/posts\/3791\/revisions\/4581"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=\/wp\/v2\/media\/1218"}],"wp:attachment":[{"href":"https:\/\/obenkyolab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/obenkyolab.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}