{"id":996,"date":"2023-07-28T01:23:17","date_gmt":"2023-07-28T01:23:17","guid":{"rendered":"https:\/\/statorials.org\/ko\/matplotlib-%e1%84%82%e1%85%ae%e1%84%8c%e1%85%a5%e1%86%a8-%e1%84%86%e1%85%a1%e1%86%a8%e1%84%83%e1%85%a2-%e1%84%8e%e1%85%a1%e1%84%90%e1%85%b3\/"},"modified":"2023-07-28T01:23:17","modified_gmt":"2023-07-28T01:23:17","slug":"matplotlib-%e1%84%82%e1%85%ae%e1%84%8c%e1%85%a5%e1%86%a8-%e1%84%86%e1%85%a1%e1%86%a8%e1%84%83%e1%85%a2-%e1%84%8e%e1%85%a1%e1%84%90%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/matplotlib-%e1%84%82%e1%85%ae%e1%84%8c%e1%85%a5%e1%86%a8-%e1%84%86%e1%85%a1%e1%86%a8%e1%84%83%e1%85%a2-%e1%84%8e%e1%85%a1%e1%84%90%e1%85%b3\/","title":{"rendered":"Matplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

\ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub294<\/strong> \ub9c9\ub300\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ubc94\uc8fc\uc758 \ube48\ub3c4\ub97c \ud45c\uc2dc\ud558\ub294 \ucc28\ud2b8 \uc720\ud615\uc785\ub2c8\ub2e4.<\/span><\/p>\n

matplotlib.pyplot.bar()<\/a> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Matplotlib\uc5d0\uc11c \uc774\ub7ec\ud55c \uc720\ud615\uc758 \ucc28\ud2b8\ub97c \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n

\uae30\ubcf8 \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8 \ub9cc\ub4e4\uae30<\/strong><\/span><\/h2>\n

\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub204\uc801 \ub9c9\ub300\ud615 \ucc28\ud2b8\ub97c \ub9cc\ub4e4\uc5b4 \uc11c\ub85c \ub2e4\ub978 4\uac1c \ud310\ub9e4 \ubd84\uae30\uc5d0 \uac78\uccd0 \ub450 \uc81c\ud488\uc758 \ucd1d \ud310\ub9e4\ub7c9\uc744 \ud45c\uc2dc\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n

 import<\/span> numpy as<\/span> np\nimport<\/span> matplotlib.pyplot as<\/span> plt\n\n#createdata<\/span>\nquarter = ['Q1', 'Q2', 'Q3', 'Q4']\nproduct_A = [14, 17, 12, 9]\nproduct_B = [7, 15, 24, 18]\n\n#define chart parameters\n<\/span>N = 4 \nbarWidth = .5\nxloc = np. orange<\/span> (N)\n\n#display stacked bar chart\n<\/span>p1 = plt. bar<\/span> (xloc, product_A, width=barWidth)\np2 = plt. bar<\/span> (xloc, product_B, bottom=product_A, width=barWidth)\nplt. show<\/span> ()\n<\/strong><\/pre>\n
\"Matplotlib\uc758<\/p>\n
 \uc81c\ubaa9, \ub77c\ubca8, \ucea1\uc158 \ucd94\uac00<\/strong><\/span><\/h2>\n
 \ucc28\ud2b8\ub97c \ub354 \uc27d\uac8c \uc77d\uc744 \uc218 \uc788\ub3c4\ub85d \uc81c\ubaa9, \ub808\uc774\ube14, \ub208\uae08 \ud45c\uc2dc \ubc0f \ubc94\ub840\ub97c \ucd94\uac00\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 import<\/span> numpy as<\/span> np\nimport<\/span> matplotlib.pyplot as<\/span> plt\n\n#create data for two teams<\/span>\nquarter = ['Q1', 'Q2', 'Q3', 'Q4']\nproduct_A = [14, 17, 12, 9]\nproduct_B = [7, 15, 24, 18]\n\n#define chart parameters\n<\/span>N = 4 \nbarWidth = .5\nxloc = np. orange<\/span> (N)\n\n#create stacked bar chart\n<\/span>p1 = plt. bar<\/span> (xloc, product_A, width=barWidth)\np2 = plt. bar<\/span> (xloc, product_B, bottom=product_A, width=barWidth)\n\n#add labels, title, tick marks, and legend\n<\/span>plt. ylabel<\/span> ('Sales')\nplt. xlabel<\/span> ('Quarter')\nplt. title<\/span> ('Sales by Product & Quarter')\nplt. xticks<\/span> (xloc, ('Q1', 'Q2', 'Q3', 'Q4'))\nplt. yticks<\/span> (np. arange<\/span> (0, 41, 5))\nplt. legend<\/span> ((p1[0], p2[0]), ('A', 'B'))\n\n#displaychart\n<\/span>plt. show<\/span> ()<\/strong> <\/pre>\n
\"Matplotlib\uc758<\/p>\n
 \ucc28\ud2b8 \uc0c9\uc0c1 \uc0ac\uc6a9\uc790 \uc815\uc758<\/strong><\/span><\/h2>\n
 \ub9c8\uc9c0\ub9c9\uc73c\ub85c plt.bar()<\/strong> \uc758 colors()<\/strong> \uc778\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ucc28\ud2b8\uc5d0 \uc0ac\uc6a9\ub418\ub294 \uc0c9\uc0c1\uc744 \uc0ac\uc6a9\uc790 \uc815\uc758\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 import<\/span> numpy as<\/span> np\nimport<\/span> matplotlib.pyplot as<\/span> plt\n\n#create data for two teams<\/span>\nquarter = ['Q1', 'Q2', 'Q3', 'Q4']\nproduct_A = [14, 17, 12, 9]\nproduct_B = [7, 15, 24, 18]\n\n#define chart parameters\n<\/span>N = 4 \nbarWidth = .5\nxloc = np. orange<\/span> (N)\n\n#create stacked bar chart\n<\/span>p1 = plt. bar<\/span> (xloc, product_A, width=barWidth, color=' springgreen<\/span> ')\np2 = plt. bar<\/span> (xloc, product_B, bottom=product_A, width=barWidth, color=' coral<\/span> ')\n\n#add labels, title, tick marks, and legend\n<\/span>plt. ylabel<\/span> ('Sales')\nplt. xlabel<\/span> ('Quarter')\nplt. title<\/span> ('Sales by Product & Quarter')\nplt. xticks<\/span> (xloc, ('Q1', 'Q2', 'Q3', 'Q4'))\nplt. yticks<\/span> (np. arange<\/span> (0, 41, 5))\nplt. legend<\/span> ((p1[0], p2[0]), ('A', 'B'))\n\n#displaychart\n<\/span>plt. show<\/span> ()<\/strong> <\/pre>\n
\"\uc0ac\uc6a9\uc790<\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Matplotlib\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
 Matplotlib \ud50c\ub86f\uc5d0\uc11c \uae00\uaf34 \ud06c\uae30\ub97c \ubcc0\uacbd\ud558\ub294 \ubc29\ubc95<\/a>
 Matplotlib \ud50c\ub86f\uc5d0\uc11c \uc9c4\ub4dc\uae30\ub97c \uc81c\uac70\ud558\ub294 \ubc29\ubc95<\/a>
 Matplotlib \ud50c\ub86f\uc5d0 \ub208\uae08\uc120\uc744 \ud45c\uc2dc\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub294 \ub9c9\ub300\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ubc94\uc8fc\uc758 \ube48\ub3c4\ub97c \ud45c\uc2dc\ud558\ub294 \ucc28\ud2b8 \uc720\ud615\uc785\ub2c8\ub2e4. matplotlib.pyplot.bar() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Matplotlib\uc5d0\uc11c \uc774\ub7ec\ud55c \uc720\ud615\uc758 \ucc28\ud2b8\ub97c \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc774 \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uae30\ubcf8 \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8 \ub9cc\ub4e4\uae30 \ub2e4\uc74c \ucf54\ub4dc\ub294 \ub204\uc801 \ub9c9\ub300\ud615 \ucc28\ud2b8\ub97c \ub9cc\ub4e4\uc5b4 \uc11c\ub85c \ub2e4\ub978 4\uac1c \ud310\ub9e4 \ubd84\uae30\uc5d0 \uac78\uccd0 \ub450 \uc81c\ud488\uc758 \ucd1d \ud310\ub9e4\ub7c9\uc744 \ud45c\uc2dc\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. import numpy […]<\/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-996","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nMatplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Matplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/matplotlib-\u1102\u116e\u110c\u1165\u11a8-\u1106\u1161\u11a8\u1103\u1162-\u110e\u1161\u1110\u1173\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Matplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - Statorials\" \/>\n<meta property=\"og:description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Matplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ko\/matplotlib-\u1102\u116e\u110c\u1165\u11a8-\u1106\u1161\u11a8\u1103\u1162-\u110e\u1161\u1110\u1173\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T01:23:17+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/stackedbar1.png\" \/>\n<meta name=\"author\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ko\/matplotlib-%e1%84%82%e1%85%ae%e1%84%8c%e1%85%a5%e1%86%a8-%e1%84%86%e1%85%a1%e1%86%a8%e1%84%83%e1%85%a2-%e1%84%8e%e1%85%a1%e1%84%90%e1%85%b3\/\",\"url\":\"https:\/\/statorials.org\/ko\/matplotlib-%e1%84%82%e1%85%ae%e1%84%8c%e1%85%a5%e1%86%a8-%e1%84%86%e1%85%a1%e1%86%a8%e1%84%83%e1%85%a2-%e1%84%8e%e1%85%a1%e1%84%90%e1%85%b3\/\",\"name\":\"Matplotlib\uc5d0\uc11c \ub204\uc801 \ub9c9\ub300 \ucc28\ud2b8\ub97c \ub9cc\ub4dc\ub294 \ubc29\ubc95(\uc608\uc81c \ud3ec\ud568) - 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