{"id":4236,"date":"2023-07-12T15:27:26","date_gmt":"2023-07-12T15:27:26","guid":{"rendered":"https:\/\/statorials.org\/hi\/%e0%a4%b8%e0%a5%80%e0%a4%ac%e0%a5%89%e0%a4%b0%e0%a5%8d%e0%a4%a8-%e0%a4%b0%e0%a5%87%e0%a4%97%e0%a4%aa%e0%a5%8d%e0%a4%b2%e0%a5%89%e0%a4%9f-%e0%a4%b8%e0%a4%ae%e0%a5%80%e0%a4%95%e0%a4%b0%e0%a4%a3\/"},"modified":"2023-07-12T15:27:26","modified_gmt":"2023-07-12T15:27:26","slug":"%e0%a4%b8%e0%a5%80%e0%a4%ac%e0%a5%89%e0%a4%b0%e0%a5%8d%e0%a4%a8-%e0%a4%b0%e0%a5%87%e0%a4%97%e0%a4%aa%e0%a5%8d%e0%a4%b2%e0%a5%89%e0%a4%9f-%e0%a4%b8%e0%a4%ae%e0%a5%80%e0%a4%95%e0%a4%b0%e0%a4%a3","status":"publish","type":"post","link":"https:\/\/statorials.org\/hi\/%e0%a4%b8%e0%a5%80%e0%a4%ac%e0%a5%89%e0%a4%b0%e0%a5%8d%e0%a4%a8-%e0%a4%b0%e0%a5%87%e0%a4%97%e0%a4%aa%e0%a5%8d%e0%a4%b2%e0%a5%89%e0%a4%9f-%e0%a4%b8%e0%a4%ae%e0%a5%80%e0%a4%95%e0%a4%b0%e0%a4%a3\/","title":{"rendered":"\u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f \u092e\u0947\u0902 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u0915\u0948\u0938\u0947 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0915\u0930\u0947\u0902"},"content":{"rendered":"

<\/p>\n

\n

\u0906\u092a \u0921\u0947\u091f\u093e \u0938\u0947\u091f \u092e\u0947\u0902 \u092b\u093f\u091f \u0939\u094b\u0928\u0947 \u0935\u093e\u0932\u0947 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u0915\u094b \u092a\u094d\u0932\u0949\u091f \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964<\/span><\/span><\/p>\n

\u0926\u0941\u0930\u094d\u092d\u093e\u0917\u094d\u092f \u0938\u0947, \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0915\u0947 \u092a\u093e\u0938 \u0932\u093e\u0907\u0928 \u0938\u0947 \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u0928\u093f\u0915\u093e\u0932\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0915\u094b\u0908 \u0905\u0902\u0924\u0930\u094d\u0928\u093f\u0939\u093f\u0924 \u0938\u0941\u0935\u093f\u0927\u093e \u0928\u0939\u0940\u0902 \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u0906\u092a \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0917\u0941\u0923\u093e\u0902\u0915 \u0915\u094b \u0924\u0941\u0930\u0902\u0924 \u0922\u0942\u0902\u0922\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f scipy.stats.linregress<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/span><\/p>\n

 import<\/span> scipy\nimport<\/span> seaborn as<\/span> sns\n\n#create regplot\n<\/span>p = sns. regplot<\/span> (data=df, x=df. x<\/span> , y=df. y<\/span> )\n\n#calculate slope and intercept of regression equation\n<\/span>slope, intercept, r, p, sterr = scipy. stats<\/span> . linregress<\/span> (x= p.get_lines<\/span> ()[0] .get_xdata<\/span> (),\n                                                       y=p. get_lines<\/span> ()[0]. get_ydata<\/span> ())\n<\/strong><\/pre>\n
 \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0909\u0926\u093e\u0939\u0930\u0923 \u0926\u093f\u0916\u093e\u0924\u093e \u0939\u0948 \u0915\u093f \u0935\u094d\u092f\u0935\u0939\u093e\u0930 \u092e\u0947\u0902 \u0907\u0938 \u0935\u093e\u0915\u094d\u092f\u0935\u093f\u0928\u094d\u092f\u093e\u0938 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0948\u0938\u0947 \u0915\u0930\u0947\u0902\u0964<\/span><\/p>\n
 \u0909\u0926\u093e\u0939\u0930\u0923: \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f \u092e\u0947\u0902 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u0926\u093f\u0916\u093e\u090f\u0902<\/strong><\/span><\/h2>\n
 \u092e\u093e\u0928 \u0932\u0940\u091c\u093f\u090f \u0915\u093f \u0939\u092e\u093e\u0930\u0947 \u092a\u093e\u0938 \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u092a\u093e\u0902\u0921\u093e \u0921\u0947\u091f\u093e\u092b\u093c\u094d\u0930\u0947\u092e \u0939\u0948 \u091c\u093f\u0938\u092e\u0947\u0902 \u0935\u093f\u092d\u093f\u0928\u094d\u0928 \u091b\u093e\u0924\u094d\u0930\u094b\u0902 \u0915\u0947 \u0905\u0927\u094d\u092f\u092f\u0928 \u0915\u0947 \u0918\u0902\u091f\u094b\u0902 \u0914\u0930 \u0905\u0902\u0924\u093f\u092e \u092a\u0930\u0940\u0915\u094d\u0937\u093e \u0905\u0902\u0915\u094b\u0902 \u0915\u0947 \u092c\u093e\u0930\u0947 \u092e\u0947\u0902 \u091c\u093e\u0928\u0915\u093e\u0930\u0940 \u0936\u093e\u092e\u093f\u0932 \u0939\u0948:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' hours<\/span> ': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n                   ' score<\/span> ': [77, 79, 84, 80, 81, 89, 95, 90, 83, 89]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   hours score\n0 1 77\n1 2 79\n2 3 84\n3 4 80\n4 5 81\n5 6 89\n6 7 95\n7 8 90\n8 9 83\n9 10 89\n<\/strong><\/pre>\n
 \u092e\u093e\u0928 \u0932\u0940\u091c\u093f\u090f \u0915\u093f \u0939\u092e \u0921\u0947\u091f\u093e \u092c\u093f\u0902\u0926\u0941\u0913\u0902 \u0915\u094b \u092a\u094d\u0932\u0949\u091f \u0915\u0930\u0928\u093e \u091a\u093e\u0939\u0924\u0947 \u0939\u0948\u0902 \u0914\u0930 \u0921\u0947\u091f\u093e \u092e\u0947\u0902 \u090f\u0915 \u092b\u093f\u091f\u0947\u0921 \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0932\u093e\u0907\u0928 \u091c\u094b\u0921\u093c\u0928\u093e \u091a\u093e\u0939\u0924\u0947 \u0939\u0948\u0902\u0964<\/span><\/p>\n
 \u0910\u0938\u093e \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0939\u092e \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0938\u093f\u0902\u091f\u0948\u0915\u094d\u0938 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/span> <\/p>\n
 import<\/span> scipy\nimport<\/span> seaborn as<\/span> sns\n\n#create regplot\n<\/span>p = sns. regplot<\/span> (data=df, x=df. hours<\/span> , y=df. score<\/span> )\n\n#calculate slope and intercept of regression equation\n<\/span>slope, intercept, r, p, sterr = scipy. stats<\/span> . linregress<\/span> (x= p.get_lines<\/span> ()[0] .get_xdata<\/span> (),\n                                                       y=p. get_lines<\/span> ()[0]. get_ydata<\/span> ())\n\n#display slope and intercept of regression equation\n<\/span>print<\/span> (intercept, slope)\n\n77.39999999999995 1.3272727272727356\n<\/strong><\/pre>\n
\"\"<\/p>\n
 \u092a\u0930\u093f\u0923\u093e\u092e \u0938\u0947, \u0939\u092e \u0926\u0947\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902 \u0915\u093f \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0930\u0947\u0916\u093e \u092e\u0947\u0902 \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u0938\u092e\u0940\u0915\u0930\u0923 \u0939\u0948\u0902:<\/span><\/p>\n
 y = 77.4 + 1.327<\/strong><\/span><\/p>\n
 \u092f\u0926\u093f \u0939\u092e \u0907\u0938 \u0938\u092e\u0940\u0915\u0930\u0923 \u0915\u094b \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f<\/strong> \u092a\u0930 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0915\u0930\u0928\u093e \u091a\u093e\u0939\u0924\u0947 \u0939\u0948\u0902, \u0924\u094b \u0939\u092e matplotlib text()<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902:<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt<\/span>\nimport<\/span> scipy\nimport<\/span> seaborn as<\/span> sns\n\n#create regplot\n<\/span>p = sns. regplot<\/span> (data=df, x=df. hours<\/span> , y=df. score<\/span> )\n\n#calculate slope and intercept of regression equation\n<\/span>slope, intercept, r, p, sterr = scipy. stats<\/span> . linregress<\/span> (x= p.get_lines<\/span> ()[0] .get_xdata<\/span> (),\n                                                       y=p. get_lines<\/span> ()[0]. get_ydata<\/span> ())\n\n#add regression equation to plot\n<\/span>plt. text<\/span> (2, 95, ' y =<\/span> ' + str(round(intercept,3)) + ' +<\/span> ' + str(round(slope,3)) + ' x<\/span> ')<\/span><\/strong> <\/pre>\n
\"\u0938\u0940\u092c\u0949\u0930\u094d\u0928<\/p>\n
 \u0927\u094d\u092f\u093e\u0928 \u0926\u0947\u0902 \u0915\u093f \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u0905\u092c \u092a\u094d\u0932\u0949\u091f \u0915\u0947 \u090a\u092a\u0930\u0940 \u092c\u093e\u090f\u0901 \u0915\u094b\u0928\u0947 \u092e\u0947\u0902 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0939\u094b\u0924\u093e \u0939\u0948\u0964<\/span><\/p>\n
 \u0927\u094d\u092f\u093e\u0928 \u0926\u0947\u0902 \u0915\u093f \u091f\u0947\u0915\u094d\u0938\u094d\u091f()<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u092e\u0947\u0902 \u0939\u092e\u0928\u0947 \u0928\u093f\u0930\u094d\u0926\u093f\u0937\u094d\u091f \u0915\u093f\u092f\u093e \u0939\u0948 \u0915\u093f \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 (2, 95) \u0915\u0947 (x, y) \u0928\u093f\u0930\u094d\u0926\u0947\u0936\u093e\u0902\u0915 \u0938\u0947 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0915\u093f\u092f\u093e \u091c\u093e\u0928\u093e \u091a\u093e\u0939\u093f\u090f\u0964<\/span><\/p>\n
 \u0906\u092a \u0905\u092a\u0928\u0947 \u092a\u094d\u0932\u0949\u091f \u092e\u0947\u0902 \u091c\u0939\u093e\u0902 \u092d\u0940 \u091a\u093e\u0939\u0947\u0902, \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u092a\u094d\u0930\u0926\u0930\u094d\u0936\u093f\u0924 \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0907\u0928 \u0928\u093f\u0930\u094d\u0926\u0947\u0936\u093e\u0902\u0915\u094b\u0902 \u0915\u094b \u092c\u0947\u091d\u093f\u091d\u0915 \u0938\u0902\u0936\u094b\u0927\u093f\u0924 \u0915\u0930\u0947\u0902\u0964<\/span><\/p>\n
 \u0928\u094b\u091f<\/strong> : \u0906\u092a \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f<\/strong> \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u0947 \u0932\u093f\u090f \u0938\u0902\u092a\u0942\u0930\u094d\u0923 \u0926\u0938\u094d\u0924\u093e\u0935\u0947\u091c\u093c \u092f\u0939\u093e\u0902<\/a> \u092a\u093e \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964<\/span><\/p>\n
 \u0905\u0924\u093f\u0930\u093f\u0915\u094d\u0924 \u0938\u0902\u0938\u093e\u0927\u0928<\/strong><\/span><\/h2>\n
 \u0928\u093f\u092e\u094d\u0928\u0932\u093f\u0916\u093f\u0924 \u091f\u094d\u092f\u0942\u091f\u094b\u0930\u093f\u092f\u0932 \u092c\u0924\u093e\u0924\u0947 \u0939\u0948\u0902 \u0915\u093f \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u092e\u0947\u0902 \u0905\u0928\u094d\u092f \u0938\u093e\u092e\u093e\u0928\u094d\u092f \u0915\u093e\u0930\u094d\u092f \u0915\u0948\u0938\u0947 \u0915\u0930\u0947\u0902:<\/span><\/p>\n
 \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u092a\u094d\u0932\u0949\u091f \u0915\u0947 \u0906\u0915\u0943\u0924\u093f \u0906\u0915\u093e\u0930 \u0915\u094b \u0915\u0948\u0938\u0947 \u0938\u092e\u093e\u092f\u094b\u091c\u093f\u0924 \u0915\u0930\u0947\u0902<\/a>
 \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u092e\u0947\u0902 \u090f\u0915 \u0932\u0940\u091c\u0947\u0902\u0921 \u0915\u0940 \u0938\u094d\u0925\u093f\u0924\u093f \u0915\u0948\u0938\u0947 \u092c\u0926\u0932\u0947\u0902<\/a>
 \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u092a\u094d\u0932\u0949\u091f \u092a\u0930 \u0905\u0915\u094d\u0937 \u0932\u0947\u092c\u0932 \u0915\u0948\u0938\u0947 \u092c\u0926\u0932\u0947\u0902<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0906\u092a \u0921\u0947\u091f\u093e \u0938\u0947\u091f \u092e\u0947\u0902 \u092b\u093f\u091f \u0939\u094b\u0928\u0947 \u0935\u093e\u0932\u0947 \u0930\u0948\u0916\u093f\u0915 \u092a\u094d\u0930\u0924\u093f\u0917\u092e\u0928 \u092e\u0949\u0921\u0932 \u0915\u094b \u092a\u094d\u0932\u0949\u091f \u0915\u0930\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0926\u0941\u0930\u094d\u092d\u093e\u0917\u094d\u092f \u0938\u0947, \u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0915\u0947 \u092a\u093e\u0938 \u0932\u093e\u0907\u0928 \u0938\u0947 \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0938\u092e\u0940\u0915\u0930\u0923 \u0928\u093f\u0915\u093e\u0932\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u0915\u094b\u0908 \u0905\u0902\u0924\u0930\u094d\u0928\u093f\u0939\u093f\u0924 \u0938\u0941\u0935\u093f\u0927\u093e \u0928\u0939\u0940\u0902 \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u0906\u092a \u0930\u093f\u0917\u094d\u0930\u0947\u0936\u0928 \u0917\u0941\u0923\u093e\u0902\u0915 \u0915\u094b \u0924\u0941\u0930\u0902\u0924 \u0922\u0942\u0902\u0922\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f scipy.stats.linregress \u092b\u093c\u0902\u0915\u094d\u0936\u0928 \u0915\u093e \u0909\u092a\u092f\u094b\u0917 \u0915\u0930 \u0938\u0915\u0924\u0947 […]<\/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":[],"class_list":["post-4236","post","type-post","status-publish","format-standard","hentry","category-3"],"yoast_head":"\n\u0938\u0940\u092c\u0949\u0930\u094d\u0928 \u0930\u0947\u0917\u092a\u094d\u0932\u0949\u091f \u092e\u0947\u0902 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