{"id":2870,"date":"2023-07-20T08:04:01","date_gmt":"2023-07-20T08:04:01","guid":{"rendered":"https:\/\/statorials.org\/my\/matplotlib-aline\/"},"modified":"2023-07-20T08:04:01","modified_gmt":"2023-07-20T08:04:01","slug":"matplotlib-aline","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/matplotlib-aline\/","title":{"rendered":"Matplotlib \u1010\u103d\u1004\u103a abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

\n

R \u101b\u103e\u102d abline<\/a> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u101c\u1019\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u101e\u102d\u102f\u1037 \u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1031\u102c\u1004\u1037\u103a\u1011\u100a\u1037\u103a\u101b\u1014\u103a \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1000\u1036\u1019\u1000\u1031\u102c\u1004\u103a\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a \u1024\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u101e\u100a\u103a Matplotlib \u1010\u103d\u1004\u103a\u1019\u101b\u103e\u102d\u1015\u102b\u104a \u101e\u102d\u102f\u1037\u101e\u1031\u102c\u103a Python \u1010\u103d\u1004\u103a abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1011\u1015\u103a\u1010\u1030\u1015\u103d\u102c\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037 \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nimport<\/span> numpy as<\/span> np\n\ndef<\/span> abline<\/span> (slope, intercept):\n    axes = plt. gca<\/span> ()\n    x_vals = np. array<\/span> ( axes.get_xlim<\/span> ())\n    y_vals = intercept + slope * x_vals\n    plt. plot<\/span> (x_vals, y_vals, '--')\n<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1014\u1019\u1030\u1014\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b pandas DataFrame \u1014\u103e\u1004\u1037\u103a \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \u1024 syntax \u1000\u102d\u102f\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\u101e\u100a\u103a \u104b<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' x<\/span> ': [1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11],\n                   ' y<\/span> ': [13, 14, 17, 12, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40]})\n\n#view first five rows of DataFrame\n<\/span>df. head<\/span> ()\n\n\tx y\n0 1 13\n1 1 14\n2 2 17\n3 3 12\n4 4 23<\/strong><\/pre>\n
 \u1025\u1015\u1019\u102c 1- \u1021\u101c\u103b\u102c\u1038\u101c\u102d\u102f\u1000\u103a\u1019\u103b\u1009\u103a\u1038\u1006\u103d\u1032\u101b\u1014\u103a Abline \u1000\u102d\u102f\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1001\u103c\u1004\u103a\u1038\u104b<\/strong><\/span><\/h3>\n
 \u101a\u1001\u1004\u103a\u1000 \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1011\u102c\u1038\u101e\u1031\u102c abline<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1016\u103c\u1004\u1037\u103a \u1021\u101c\u103b\u102c\u1038\u101c\u102d\u102f\u1000\u103a\u1019\u103b\u1009\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1006\u103d\u1032\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1015\u102b\u101e\u100a\u103a\u104b<\/span> <\/p>\n
 #create scatterplot\n<\/span>plt. scatter<\/span> (df. x<\/span> , df. y<\/span> )\n\n#add horizontal line at y=30\n<\/span>abline( 0,30<\/span> )<\/span><\/strong> <\/pre>\n
\"\"<\/p>\n
 \u101b\u101c\u1012\u103a\u101e\u100a\u103a y=30 \u1010\u103d\u1004\u103a \u1021\u101c\u103b\u102c\u1038\u101c\u102d\u102f\u1000\u103a\u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 2- \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1011\u102c\u1038\u101e\u1031\u102c \u101c\u103b\u103e\u1031\u102c\u1005\u1031\u102c\u1000\u103a\u1014\u103e\u1004\u1037\u103a \u101c\u1019\u103a\u1038\u1006\u102f\u1036\u1019\u103b\u1009\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u1006\u103d\u1032\u101b\u1014\u103a \u1019\u103b\u1009\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 3<\/strong> \u104f slope \u1014\u103e\u1004\u1037\u103a 15<\/strong> \u104f y-intercept \u1015\u102b\u101e\u1031\u102c\u1019\u103b\u1009\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1006\u103d\u1032\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span> <\/p>\n
 #create scatterplot\n<\/span>plt. scatter<\/span> (df. x<\/span> , df. y<\/span> )\n\n#add straight line with slope=3 and intercept=15\n<\/span>abline( 3,15<\/span> )<\/span><\/strong> <\/pre>\n
\"\"<\/p>\n
 \u101b\u101c\u1012\u103a\u1019\u103e\u102c \u101c\u103b\u103e\u1031\u102c\u1005\u1031\u102c\u1000\u103a 3 \u104f \u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1031\u102c\u1004\u1037\u103a\u1016\u103c\u1005\u103a\u1015\u103c\u102e\u1038 15 \u101c\u1019\u103a\u1038\u1006\u102f\u1036\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1025\u1015\u1019\u102c 3- regression line \u1000\u102d\u102f\u1006\u103d\u1032\u101b\u1014\u103a abline \u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 \u101a\u1001\u1004\u103a\u1000 \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1011\u102c\u1038\u101e\u1031\u102c abline<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1016\u103c\u1004\u1037\u103a \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1019\u103b\u1009\u103a\u1038\u1000\u102d\u102f \u101b\u1031\u1038\u1006\u103d\u1032\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span> <\/p>\n
 #calculate slope and intercept of regression line\nslope = np. polyfit<\/span> (df. x<\/span> , df. y<\/span> , 1)[ 0<\/span> ]<\/span>\nintercept = np. polyfit<\/span> (df. x<\/span> , df. y<\/span> , 1)[ 1<\/span> ]<\/span>\n\n#create scatterplot\n<\/span>plt. scatter<\/span> (df. x<\/span> , df. y<\/span> )\n\n#add regression line\n<\/span>abline(slope, intercept)<\/span><\/strong> <\/pre>\n
\"\"<\/p>\n
 \u101b\u101c\u1012\u103a\u101e\u100a\u103a \u1000\u103d\u1000\u103a\u1000\u103d\u1000\u103a\u1021\u1019\u103e\u1010\u103a\u1019\u103b\u102c\u1038\u1019\u103e\u1010\u1006\u1004\u1037\u103a \u1010\u102d\u102f\u1000\u103a\u101b\u102d\u102f\u1000\u103a\u1016\u103c\u1010\u103a\u101e\u1014\u103a\u1038\u101e\u100a\u1037\u103a \u1010\u1015\u103a\u1006\u1004\u103a\u1011\u102c\u1038\u101e\u1031\u102c \u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a\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 \u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u1010\u103d\u1004\u103a \u1021\u1001\u103c\u102c\u1038\u1018\u102f\u1036\u1021\u101c\u102f\u1015\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u101e\u100a\u103a-<\/span><\/p>\n
 Pandas \u1010\u103d\u1004\u103a \u101e\u102e\u1038\u1001\u103c\u102c\u1038\u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u1031\u102b\u1004\u103a\u1038\u1014\u100a\u103a\u1038<\/a>
 Pandas \u101b\u103e\u102d \u1021\u1001\u103c\u1031\u1021\u1014\u1031\u1010\u1005\u103a\u1001\u102f\u1021\u1015\u1031\u102b\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u104d \u1000\u1031\u102c\u103a\u101c\u1036\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u1031\u102b\u1004\u103a\u1038\u1014\u100a\u103a\u1038<\/a>
 \u1015\u1014\u103a\u1012\u102b\u1019\u103b\u102c\u1038\u1010\u103d\u1004\u103a \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u103c\u1014\u103a\u1005\u102f\u1015\u102f\u1036\u1004\u103d\u1031\u1000\u102d\u102f \u1010\u103d\u1000\u103a\u1001\u103b\u1000\u103a\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
R \u101b\u103e\u102d abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u101c\u1019\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1010\u1005\u103a\u1001\u102f\u101e\u102d\u102f\u1037 \u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1031\u102c\u1004\u1037\u103a\u1011\u100a\u1037\u103a\u101b\u1014\u103a \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b \u1000\u1036\u1019\u1000\u1031\u102c\u1004\u103a\u1038\u1005\u103d\u102c\u1016\u103c\u1004\u1037\u103a \u1024\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u101e\u100a\u103a Matplotlib \u1010\u103d\u1004\u103a\u1019\u101b\u103e\u102d\u1015\u102b\u104a \u101e\u102d\u102f\u1037\u101e\u1031\u102c\u103a Python \u1010\u103d\u1004\u103a abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1011\u1015\u103a\u1010\u1030\u1015\u103d\u102c\u1038\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037 \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a- import matplotlib. pyplot as plt import numpy as np def abline (slope, intercept): axes = plt. gca () x_vals = np. array ( axes.get_xlim ()) y_vals = intercept + slope * x_vals plt. plot (x_vals, […]<\/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":"\nMatplotlib - Statology \u1010\u103d\u1004\u103a abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u100a\u103a\u1038<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a Matplotlib \u1010\u103d\u1004\u103a abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f R \u1010\u103d\u1004\u103a\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101e\u100a\u1037\u103a\u1021\u101b\u102c\u1014\u103e\u1004\u1037\u103a \u1006\u1004\u103a\u1010\u1030\u101e\u1031\u102c abline \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u1025\u1015\u1019\u102c\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1004\u1037\u103a \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, 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 \u1019\u103e\u1010\u103a\u1001\u103b\u1000\u103a<\/strong> – NumPy \u1010\u103d\u1004\u103a polyfit<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u104f \u1005\u102c\u101b\u103d\u1000\u103a\u1005\u102c\u1010\u1019\u103a\u1038\u1021\u1015\u103c\u100a\u1037\u103a\u1021\u1005\u102f\u1036\u1000\u102d\u102f \u1024\u1014\u1031\u101b\u102c\u1010\u103d\u1004\u103a<\/a> \u101b\u103e\u102c\u1010\u103d\u1031\u1037\u1014\u102d\u102f\u1004\u103a\u1015\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n