{"id":4302,"date":"2023-07-12T03:55:48","date_gmt":"2023-07-12T03:55:48","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%87%e1%85%a9%e1%84%83%e1%85%a1-%e1%84%8f%e1%85%b3%e1%86%ab-numpy-%e1%84%80%e1%85%a2%e1%84%89%e1%85%ae-%e1%84%80%e1%85%a1%e1%86%b9\/"},"modified":"2023-07-12T03:55:48","modified_gmt":"2023-07-12T03:55:48","slug":"%e1%84%83%e1%85%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%87%e1%85%a9%e1%84%83%e1%85%a1-%e1%84%8f%e1%85%b3%e1%86%ab-numpy-%e1%84%80%e1%85%a2%e1%84%89%e1%85%ae-%e1%84%80%e1%85%a1%e1%86%b9","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%83%e1%85%a1%e1%84%8b%e1%85%b3%e1%86%b7%e1%84%87%e1%85%a9%e1%84%83%e1%85%a1-%e1%84%8f%e1%85%b3%e1%86%ab-numpy-%e1%84%80%e1%85%a2%e1%84%89%e1%85%ae-%e1%84%80%e1%85%a1%e1%86%b9\/","title":{"rendered":"Numpy: \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218 \uacc4\uc0b0"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec NumPy \ubc30\uc5f4\uc758 \ud2b9\uc815 \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 import<\/span> numpy as<\/span> np\n\nvals_greater_10 = (data ><\/span> 10<\/span> ). sum<\/span> ()\n<\/strong><\/pre>\n
 \uc774 \ud2b9\uc815 \uc608\ub294 data<\/strong> \ub77c\ub294 NumPy \ubc30\uc5f4\uc5d0\uc11c 10\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218\ub97c \ubc18\ud658\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: NumPy \ubc30\uc5f4\uc758 \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218 \uacc4\uc0b0<\/strong><\/span><\/h2>\n
 \ucd1d 15\uac1c\uc758 \uc694\uc18c\uac00 \uc788\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 2D NumPy \ubc30\uc5f4\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\n\n#create 2D NumPy array with 3 columns and 5 rows\n<\/span>data = np. matrix<\/span> (np. arange<\/span> (15). reshape<\/span> ((5, 3)))\n\n#view NumPy array\n<\/span>print<\/span> (data)\n\n[[ 0 1 2]\n [3 4 5]\n [6 7 8]\n [9 10 11]\n [12 13 14]]\n<\/span><\/span><\/strong><\/pre>\n
 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec 10\ubcf4\ub2e4 \ud070 \uac12\uc744 \uac00\uc9c4 \ubc30\uc5f4\uc758 \ucd1d \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #count number of values greater than 10 in NumPy matrix\n<\/span>vals_greater_10 = (data ><\/span> 10<\/span> ). sum<\/span> ()\n\n#view results\n<\/span>print<\/span> (vals_greater_10)\n\n4<\/span><\/span><\/strong><\/pre>\n
 \uacb0\uacfc\ub97c \ubcf4\uba74 NumPy \ubc30\uc5f4\uc758 4\uac1c<\/strong> \uac12\uc774 10\ubcf4\ub2e4 \ud070 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 NumPy \ubc30\uc5f4\uc744 \uc218\ub3d9\uc73c\ub85c \uac80\uc0ac\ud558\uba74 4\uac1c\uc758 \uc694\uc18c(11, 12, 13, 14)\uac00 \uc2e4\uc81c\ub85c 10\ubcf4\ub2e4 \ud070 \uac83\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 10\ubcf4\ub2e4 \uc791\uc740 \uc694\uc18c \uc218\ub97c \ucc3e\uc73c\ub824\uba74 \ubcf4\ub2e4 \uc791\uc74c \uc5f0\uc0b0\uc790( <<\/strong> )\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #count number of values less than 10 in NumPy matrix\n<\/span>vals_less_10 = (data <<\/span> 10<\/span> ). sum<\/span> ()\n\n#view results\n<\/span>print<\/span> (vals_less_10)\n\n10<\/span><\/span><\/strong><\/pre>\n
 \uacb0\uacfc\ub97c \ubcf4\uba74 NumPy \ubc30\uc5f4\uc758 10\uac1c<\/b> \uac12\uc774 10\ubcf4\ub2e4 \uc791\uc740 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 NumPy\uc5d0\uc11c NaN\uacfc \ub3d9\uc77c\ud55c \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a>
 NumPy\uc5d0\uc11c 0\uacfc \uac19\uc740 \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a>
 NumPy\uc5d0\uc11c True\uc640 \ub3d9\uc77c\ud55c \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \uae30\ubcf8 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec NumPy \ubc30\uc5f4\uc758 \ud2b9\uc815 \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. import numpy as np vals_greater_10 = (data > 10 ). sum () \uc774 \ud2b9\uc815 \uc608\ub294 data \ub77c\ub294 NumPy \ubc30\uc5f4\uc5d0\uc11c 10\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218\ub97c \ubc18\ud658\ud569\ub2c8\ub2e4. \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc2e4\uc81c\ub85c \uc774 \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608: NumPy \ubc30\uc5f4\uc758 \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218 \uacc4\uc0b0 \ucd1d […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-4302","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nNumPy: \uac12\ubcf4\ub2e4 \ud070 \uc694\uc18c \uc218 \uacc4\uc0b0 - 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