{"id":1326,"date":"2023-07-26T20:52:11","date_gmt":"2023-07-26T20:52:11","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%b1%d8%b3%d9%85-%d8%ae%d8%b7%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%d8%af%d8%a9-matplotlib\/"},"modified":"2023-07-26T20:52:11","modified_gmt":"2023-07-26T20:52:11","slug":"%d8%b1%d8%b3%d9%85-%d8%ae%d8%b7%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%d8%af%d8%a9-matplotlib","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%b1%d8%b3%d9%85-%d8%ae%d8%b7%d9%88%d8%b7-%d9%85%d8%aa%d8%b9%d8%af%d8%af%d8%a9-matplotlib\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0631\u0633\u0645 \u062e\u0637\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a matplotlib"},"content":{"rendered":"

<\/p>\n

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\u064a\u0645\u0643\u0646\u0643 \u0639\u0631\u0636 \u0623\u0633\u0637\u0631 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a \u0645\u062e\u0637\u0637 Matplotlib \u0648\u0627\u062d\u062f \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a:<\/span><\/p>\n

 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\n\nplt. plot<\/span> (df[' column1<\/span> '])\nplt. plot<\/span> (df[' column2<\/span> '])\nplt. plot<\/span> (df[' column3<\/span> '])\n\n...\nplt. show<\/span> ()\n<\/strong><\/pre>\n
 \u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0639\u062f\u0629 \u0623\u0645\u062b\u0644\u0629 \u062d\u0648\u0644 \u0643\u064a\u0641\u064a\u0629 \u0631\u0633\u0645 \u062e\u0637\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a \u0645\u062e\u0637\u0637 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0628\u0627\u0646\u062f\u0627 DataFrame \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/span><\/p>\n
 import numpy<\/span> as np<\/span> \nimport<\/span> pandas as<\/span> pd\n\n#make this example reproducible\n<\/span>n.p. random<\/span> . seeds<\/span> (0)\n\n#create dataset\n<\/span>period = np. arange<\/span> (1, 101, 1)\nleads = np. random<\/span> . uniform<\/span> (1, 50, 100)\nprospects = np. random<\/span> . uniform<\/span> (40, 80, 100)\nsales = 60 + 2*period + np. random<\/span> . normal<\/span> (loc=0, scale=.5*period, size=100)\ndf = pd. DataFrame<\/span> ({' period<\/span> ': period, \n                   ' leads<\/span> ': leads,\n                   ' prospects<\/span> ': prospects,\n                   ' sales<\/span> ': sales})\n\n#view first 10 rows\n<\/span>df. head<\/span> (10)\n\n\n        period leads sales prospects\n0 1 27.891862 67.112661 62.563318\n1 2 36.044279 50.800319 62.920068\n2 3 30.535405 69.407761 64.278797\n3 4 27.699276 78.487542 67.124360\n4 5 21.759085 49.950126 68.754919\n5 6 32.648812 63.046293 77.788596\n6 7 22.441773 63.681677 77.322973\n7 8 44.696877 62.890076 76.350205\n8 9 48.219475 48.923265 72.485540\n9 10 19.788634 78.109960 84.221815\n<\/strong><\/pre>\n
 \u0631\u0633\u0645 \u062e\u0637\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a Matplotlib<\/strong><\/span><\/h3>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u0629 \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u0631\u0633\u0645 \u062b\u0644\u0627\u062b\u0629 \u0623\u0633\u0637\u0631 \u0641\u0631\u062f\u064a\u0629 \u0641\u064a \u0642\u0637\u0639\u0629 \u0623\u0631\u0636 \u0648\u0627\u062d\u062f\u0629 \u0641\u064a matplotlib:<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt<\/span>\n\n#plot individual lines<\/span>\nplt. plot<\/span> (df[' leads<\/span> '])<\/span>\nplt. plot<\/span> (df[' prospects<\/span> '])<\/span>\nplt. plot<\/span> (df[' sales<\/span> '])\n\n<\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span>\n<\/span><\/strong><\/pre>\n
\"\u062e\u0637\u0648\u0637<\/p>\n
 \u062a\u062e\u0635\u064a\u0635 \u0627\u0644\u062e\u0637\u0648\u0637 \u0641\u064a Matplotlib<\/strong><\/span><\/h3>\n
 \u064a\u0645\u0643\u0646\u0643 \u0623\u064a\u0636\u064b\u0627 \u062a\u062e\u0635\u064a\u0635 \u0627\u0644\u0644\u0648\u0646 \u0648\u0627\u0644\u0646\u0645\u0637 \u0648\u0627\u0644\u0639\u0631\u0636 \u0644\u0643\u0644 \u0633\u0637\u0631:<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n<\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"\u062a\u062e\u0635\u064a\u0635<\/p>\n
 \u0625\u0636\u0627\u0641\u0629 \u0648\u0633\u064a\u0644\u0629 \u0625\u064a\u0636\u0627\u062d \u0641\u064a Matplotlib<\/strong><\/span><\/h3>\n
 \u064a\u0645\u0643\u0646\u0643 \u0623\u064a\u0636\u064b\u0627 \u0625\u0636\u0627\u0641\u0629 \u062a\u0633\u0645\u064a\u0629 \u062a\u0648\u0636\u064a\u062d\u064a\u0629 \u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u0633\u0637\u0648\u0631:<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], label=' Leads<\/span> ', color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], label=' Prospects<\/span> ', color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], label=' Sales<\/span> ', color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n#add legend\nplt. legend<\/span> ()<\/span>\n\n<\/span><\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"\u0625\u0636\u0627\u0641\u0629<\/p>\n
 \u0623\u0636\u0641 \u062a\u0633\u0645\u064a\u0627\u062a \u0648\u0639\u0646\u0627\u0648\u064a\u0646 \u0627\u0644\u0645\u062d\u0627\u0648\u0631 \u0641\u064a Matplotlib<\/strong><\/span><\/h3>\n
 \u0648\u0623\u062e\u064a\u0631\u064b\u0627\u060c \u064a\u0645\u0643\u0646\u0643 \u0625\u0636\u0627\u0641\u0629 \u062a\u0633\u0645\u064a\u0627\u062a \u0627\u0644\u0645\u062d\u0627\u0648\u0631 \u0648\u0639\u0646\u0648\u0627\u0646\u064b\u0627 \u0644\u0625\u0643\u0645\u0627\u0644 \u0627\u0644\u0645\u062e\u0637\u0637:<\/span> <\/p>\n
 #plot individual lines with custom colors, styles, and widths<\/span>\nplt. plot<\/span> (df[' leads<\/span> '], label=' Leads<\/span> ', color=' green<\/span> ')\nplt. plot<\/span> (df[' prospects<\/span> '], label=' Prospects<\/span> ', color=' steelblue<\/span> ', linewidth= 4<\/span> )\nplt. plot<\/span> (df[' sales<\/span> '], label=' Sales<\/span> ', color=' purple<\/span> ', linestyle=' dashed<\/span> ')\n\n#add legend\nplt.<\/span> legend<\/span> ()<\/span>\n\n#add axis labels and a title\nplt. ylabel<\/span> (' Sales<\/span> ', fontsize= 14<\/span> )<\/span>\nplt. xlabel<\/span> (' Period<\/span> ', fontsize= 14<\/span> )<\/span>\nplt. title<\/span> (' Company Metrics<\/span> ', fontsize= 16<\/span> )<\/span>\n\n<\/span><\/span>#displayplot<\/span>\nplt. show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n
\"\"<\/p>\n
 \u064a\u0645\u0643\u0646\u0643 \u0627\u0644\u0639\u062b\u0648\u0631 \u0639\u0644\u0649 \u0627\u0644\u0645\u0632\u064a\u062f \u0645\u0646 \u062f\u0631\u0648\u0633 Matplotlib \u0647\u0646\u0627 .<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u064a\u0645\u0643\u0646\u0643 \u0639\u0631\u0636 \u0623\u0633\u0637\u0631 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a \u0645\u062e\u0637\u0637 Matplotlib \u0648\u0627\u062d\u062f \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a: import matplotlib. pyplot as plt plt. plot (df[‘ column1 ‘]) plt. plot (df[‘ column2 ‘]) plt. plot (df[‘ column3 ‘]) … plt. show () \u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0639\u062f\u0629 \u0623\u0645\u062b\u0644\u0629 \u062d\u0648\u0644 \u0643\u064a\u0641\u064a\u0629 \u0631\u0633\u0645 \u062e\u0637\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a \u0645\u062e\u0637\u0637 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0628\u0627\u0646\u062f\u0627 DataFrame \u0627\u0644\u062a\u0627\u0644\u064a\u0629: 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":[11],"tags":[],"yoast_head":"\n\u0643\u064a\u0641\u064a\u0629 \u0631\u0633\u0645 \u062e\u0637\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629 \u0641\u064a Matplotlib - 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