{"id":2130,"date":"2023-07-23T13:49:44","date_gmt":"2023-07-23T13:49:44","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%8f%e1%80%b9%e1%80%8f%e1%80%9d%e1%80%ab%e1%80%a7%e1%80%9b%e1%80%ad%e1%80%9a%e1%80%ac%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6\/"},"modified":"2023-07-23T13:49:44","modified_gmt":"2023-07-23T13:49:44","slug":"%e1%80%a1%e1%80%8f%e1%80%b9%e1%80%8f%e1%80%9d%e1%80%ab%e1%80%a7%e1%80%9b%e1%80%ad%e1%80%9a%e1%80%ac%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%8f%e1%80%b9%e1%80%8f%e1%80%9d%e1%80%ab%e1%80%a7%e1%80%9b%e1%80%ad%e1%80%9a%e1%80%ac%e1%80%99%e1%80%bc%e1%80%b1%e1%80%95%e1%80%af%e1%80%b6\/","title":{"rendered":"Seaborn \u1010\u103d\u1004\u103a area chart \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038 (\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a\u1021\u1010\u1030)"},"content":{"rendered":"

<\/p>\n

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seaborn<\/a> \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1021\u1001\u103c\u1031\u1001\u1036\u1021\u1011\u102c\u1038\u1021\u101e\u102d\u102f\u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nimport<\/span> seaborn as<\/span> sns\n\n#set seaborn style\n<\/span>sns. set_theme<\/span> ()\n\n#create seaborn area chart<\/span>\nplt. stackplot<\/span> ( df.x<\/span> , df.y1<\/span> , df.y2<\/span> , df.y3<\/span> )\n<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f\u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f\u1015\u103c\u101e\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 1- Seaborn \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a Seaborn \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a-<\/span> <\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nimport<\/span> seaborn as<\/span> sns\n\n#set seaborn style\n<\/span>sns. set_theme<\/span> ()\n \n#define DataFrame\n<\/span>df = pd. DataFrame<\/span> ({' period<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8],\n                   ' team_A<\/span> ': [20, 12, 15, 14, 19, 23, 25, 29],\n                   ' team_B<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' team_C<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#create area chart\n<\/span>plt. stackplot<\/span> (df. period<\/span> , df. team_A<\/span> , df. team_B<\/span> , df. team_C<\/span> )\n<\/strong><\/pre>\n
\"\"<\/p>\n
 x-axis \u101e\u100a\u103a period variable \u1000\u102d\u102f\u1015\u103c\u101e\u1015\u103c\u102e\u1038 y-axis \u101e\u100a\u103a \u1021\u1001\u103b\u102d\u1014\u103a\u1014\u103e\u1004\u1037\u103a\u1021\u1019\u103b\u103e \u1021\u1016\u103d\u1032\u1037\u101e\u102f\u1036\u1038\u1016\u103d\u1032\u1037\u1005\u102e\u1021\u1010\u103d\u1000\u103a \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 2- Seaborn \u1010\u103d\u1004\u103a \u1005\u102d\u1010\u103a\u1000\u103c\u102d\u102f\u1000\u103a\u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u104f\u1021\u101b\u1031\u102c\u1004\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u101b\u1019\u100a\u103a\u1000\u102d\u102f\u1015\u103c\u101e\u1015\u103c\u102e\u1038 \u1010\u102d\u1000\u103b\u101e\u1031\u102c\u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a \u1012\u100f\u1039\u100d\u102c\u101b\u102e\u1010\u1005\u103a\u1001\u102f\u1011\u100a\u1037\u103a\u101e\u100a\u103a-<\/span> <\/p>\n
 import<\/span> pandas as<\/span> pd\nimport<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nimport<\/span> seaborn as<\/span> sns\n\n#set seaborn style\n<\/span>sns. set_theme<\/span> ()\n \n#define DataFrame\n<\/span>df = pd. DataFrame<\/span> ({' period<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8],\n                   ' team_A<\/span> ': [20, 12, 15, 14, 19, 23, 25, 29],\n                   ' team_B<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' team_C<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n#define colors to use in chart\n<\/span>color_map = [' red<\/span> ', ' steelblue<\/span> ', ' pink<\/span> ']\n    \n#create area chart\n<\/span>plt. stackplot<\/span> (df. period<\/span> , df. team_A<\/span> , df. team_B<\/span> , df. team_C<\/span> ,\n              labels=[' Team A<\/span> ', ' Team B<\/span> ', ' Team C<\/span> '],\n              colors=color_map)\n\n#add legend\n<\/span>plt. legend<\/span> (loc=' upper left<\/span> ')\n\n#add axis labels\n<\/span>plt. xlabel<\/span> (' Period<\/span> ')\nplt. ylabel<\/span> (' Points Scored<\/span> ')\n\n#display area chart\n<\/span>plt. show<\/span> ()<\/strong> <\/pre>\n
\"\"<\/p>\n
 \u1021\u101b\u1031\u102c\u1004\u103a<\/strong> \u1021\u1004\u103c\u1004\u103a\u1038\u1021\u1001\u102f\u1036\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u101b\u1031\u102c\u1004\u103a\u1021\u1019\u100a\u103a\u1019\u103b\u102c\u1038\u1021\u1015\u103c\u1004\u103a \u1006\u101a\u103a\u1002\u100f\u1014\u103a\u1038\u1002\u100f\u1014\u103a\u1038\u101b\u1031\u102c\u1004\u103a\u1000\u102f\u1012\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u101c\u1000\u103a\u1001\u1036\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u101e\u1010\u102d\u1015\u103c\u102f\u1015\u102b\u104b<\/span><\/p>\n
 \u1011\u1015\u103a\u101c\u1031\u102c\u1004\u103a\u1038\u1021\u101b\u1004\u103a\u1038\u1021\u1019\u103c\u1005\u103a\u1019\u103b\u102c\u1038<\/strong><\/span><\/h3>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a Seaborn \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u102c\u1038\u1018\u102f\u1036\u1000\u103d\u1000\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u101e\u100a\u103a-<\/span><\/p>\n
 Seaborn \u1010\u103d\u1004\u103a Time Series Plot \u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/a>
 Seaborn \u1010\u103d\u1004\u103a Pie Chart \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/a>
 Seaborn \u1010\u103d\u1004\u103a barplot \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
seaborn \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1021\u1001\u103c\u1031\u1001\u1036\u1021\u1011\u102c\u1038\u1021\u101e\u102d\u102f\u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b import matplotlib. pyplot as plt import seaborn as sns #set seaborn style sns. set_theme () #create seaborn area chart plt. stackplot ( df.x , df.y1 , df.y2 , df.y3 ) \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f\u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f\u1015\u103c\u101e\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c 1- Seaborn \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1015\u102b\u104b \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a Seaborn \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a- import pandas as pd import […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"\nSeaborn \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038 (\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a\u1021\u1010\u1030) - Statorials<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a Seaborn \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b\" \/>\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\/my\/\u1021\u100f\u1039\u100f\u101d\u102b\u1027\u101b\u102d\u101a\u102c\u1019\u103c\u1031\u1015\u102f\u1036\/\" \/>\n<meta property=\"og:locale\" content=\"my_MM\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Seaborn \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1007\u101a\u102c\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038 (\u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a\u1021\u1010\u1030) - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1025\u1015\u1019\u102c\u1019\u103b\u102c\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a Seaborn \u1010\u103d\u1004\u103a \u1027\u101b\u102d\u101a\u102c\u1019\u103c\u1031\u1015\u102f\u1036\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b\" \/>\n<meta property=\"og:url\" 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