init
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eda528a8f2
216
Placement_Data_Full_Class.csv
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216
Placement_Data_Full_Class.csv
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sl_no,gender,ssc_p,ssc_b,hsc_p,hsc_b,hsc_s,degree_p,degree_t,workex,etest_p,specialisation,mba_p,status,salary
|
||||
1,M,67.00,Others,91.00,Others,Commerce,58.00,Sci&Tech,No,55,Mkt&HR,58.8,Placed,270000
|
||||
2,M,79.33,Central,78.33,Others,Science,77.48,Sci&Tech,Yes,86.5,Mkt&Fin,66.28,Placed,200000
|
||||
3,M,65.00,Central,68.00,Central,Arts,64.00,Comm&Mgmt,No,75,Mkt&Fin,57.8,Placed,250000
|
||||
4,M,56.00,Central,52.00,Central,Science,52.00,Sci&Tech,No,66,Mkt&HR,59.43,Not Placed,
|
||||
5,M,85.80,Central,73.60,Central,Commerce,73.30,Comm&Mgmt,No,96.8,Mkt&Fin,55.5,Placed,425000
|
||||
6,M,55.00,Others,49.80,Others,Science,67.25,Sci&Tech,Yes,55,Mkt&Fin,51.58,Not Placed,
|
||||
7,F,46.00,Others,49.20,Others,Commerce,79.00,Comm&Mgmt,No,74.28,Mkt&Fin,53.29,Not Placed,
|
||||
8,M,82.00,Central,64.00,Central,Science,66.00,Sci&Tech,Yes,67,Mkt&Fin,62.14,Placed,252000
|
||||
9,M,73.00,Central,79.00,Central,Commerce,72.00,Comm&Mgmt,No,91.34,Mkt&Fin,61.29,Placed,231000
|
||||
10,M,58.00,Central,70.00,Central,Commerce,61.00,Comm&Mgmt,No,54,Mkt&Fin,52.21,Not Placed,
|
||||
11,M,58.00,Central,61.00,Central,Commerce,60.00,Comm&Mgmt,Yes,62,Mkt&HR,60.85,Placed,260000
|
||||
12,M,69.60,Central,68.40,Central,Commerce,78.30,Comm&Mgmt,Yes,60,Mkt&Fin,63.7,Placed,250000
|
||||
13,F,47.00,Central,55.00,Others,Science,65.00,Comm&Mgmt,No,62,Mkt&HR,65.04,Not Placed,
|
||||
14,F,77.00,Central,87.00,Central,Commerce,59.00,Comm&Mgmt,No,68,Mkt&Fin,68.63,Placed,218000
|
||||
15,M,62.00,Central,47.00,Central,Commerce,50.00,Comm&Mgmt,No,76,Mkt&HR,54.96,Not Placed,
|
||||
16,F,65.00,Central,75.00,Central,Commerce,69.00,Comm&Mgmt,Yes,72,Mkt&Fin,64.66,Placed,200000
|
||||
17,M,63.00,Central,66.20,Central,Commerce,65.60,Comm&Mgmt,Yes,60,Mkt&Fin,62.54,Placed,300000
|
||||
18,F,55.00,Central,67.00,Central,Commerce,64.00,Comm&Mgmt,No,60,Mkt&Fin,67.28,Not Placed,
|
||||
19,F,63.00,Central,66.00,Central,Commerce,64.00,Comm&Mgmt,No,68,Mkt&HR,64.08,Not Placed,
|
||||
20,M,60.00,Others,67.00,Others,Arts,70.00,Comm&Mgmt,Yes,50.48,Mkt&Fin,77.89,Placed,236000
|
||||
21,M,62.00,Others,65.00,Others,Commerce,66.00,Comm&Mgmt,No,50,Mkt&HR,56.7,Placed,265000
|
||||
22,F,79.00,Others,76.00,Others,Commerce,85.00,Comm&Mgmt,No,95,Mkt&Fin,69.06,Placed,393000
|
||||
23,F,69.80,Others,60.80,Others,Science,72.23,Sci&Tech,No,55.53,Mkt&HR,68.81,Placed,360000
|
||||
24,F,77.40,Others,60.00,Others,Science,64.74,Sci&Tech,Yes,92,Mkt&Fin,63.62,Placed,300000
|
||||
25,M,76.50,Others,97.70,Others,Science,78.86,Sci&Tech,No,97.4,Mkt&Fin,74.01,Placed,360000
|
||||
26,F,52.58,Others,54.60,Central,Commerce,50.20,Comm&Mgmt,Yes,76,Mkt&Fin,65.33,Not Placed,
|
||||
27,M,71.00,Others,79.00,Others,Commerce,66.00,Comm&Mgmt,Yes,94,Mkt&Fin,57.55,Placed,240000
|
||||
28,M,63.00,Others,67.00,Others,Commerce,66.00,Comm&Mgmt,No,68,Mkt&HR,57.69,Placed,265000
|
||||
29,M,76.76,Others,76.50,Others,Commerce,67.50,Comm&Mgmt,Yes,73.35,Mkt&Fin,64.15,Placed,350000
|
||||
30,M,62.00,Central,67.00,Central,Commerce,58.00,Comm&Mgmt,No,77,Mkt&Fin,51.29,Not Placed,
|
||||
31,F,64.00,Central,73.50,Central,Commerce,73.00,Comm&Mgmt,No,52,Mkt&HR,56.7,Placed,250000
|
||||
32,F,67.00,Central,53.00,Central,Science,65.00,Sci&Tech,No,64,Mkt&HR,58.32,Not Placed,
|
||||
33,F,61.00,Central,81.00,Central,Commerce,66.40,Comm&Mgmt,No,50.89,Mkt&HR,62.21,Placed,278000
|
||||
34,F,87.00,Others,65.00,Others,Science,81.00,Comm&Mgmt,Yes,88,Mkt&Fin,72.78,Placed,260000
|
||||
35,M,62.00,Others,51.00,Others,Science,52.00,Others,No,68.44,Mkt&HR,62.77,Not Placed,
|
||||
36,F,69.00,Central,78.00,Central,Commerce,72.00,Comm&Mgmt,No,71,Mkt&HR,62.74,Placed,300000
|
||||
37,M,51.00,Central,44.00,Central,Commerce,57.00,Comm&Mgmt,No,64,Mkt&Fin,51.45,Not Placed,
|
||||
38,F,79.00,Central,76.00,Central,Science,65.60,Sci&Tech,No,58,Mkt&HR,55.47,Placed,320000
|
||||
39,F,73.00,Others,58.00,Others,Science,66.00,Comm&Mgmt,No,53.7,Mkt&HR,56.86,Placed,240000
|
||||
40,M,81.00,Others,68.00,Others,Science,64.00,Sci&Tech,No,93,Mkt&Fin,62.56,Placed,411000
|
||||
41,F,78.00,Central,77.00,Others,Commerce,80.00,Comm&Mgmt,No,60,Mkt&Fin,66.72,Placed,287000
|
||||
42,F,74.00,Others,63.16,Others,Commerce,65.00,Comm&Mgmt,Yes,65,Mkt&HR,69.76,Not Placed,
|
||||
43,M,49.00,Others,39.00,Central,Science,65.00,Others,No,63,Mkt&Fin,51.21,Not Placed,
|
||||
44,M,87.00,Others,87.00,Others,Commerce,68.00,Comm&Mgmt,No,95,Mkt&HR,62.9,Placed,300000
|
||||
45,F,77.00,Others,73.00,Others,Commerce,81.00,Comm&Mgmt,Yes,89,Mkt&Fin,69.7,Placed,200000
|
||||
46,F,76.00,Central,64.00,Central,Science,72.00,Sci&Tech,No,58,Mkt&HR,66.53,Not Placed,
|
||||
47,F,70.89,Others,71.98,Others,Science,65.60,Comm&Mgmt,No,68,Mkt&HR,71.63,Not Placed,
|
||||
48,M,63.00,Central,60.00,Central,Commerce,57.00,Comm&Mgmt,Yes,78,Mkt&Fin,54.55,Placed,204000
|
||||
49,M,63.00,Others,62.00,Others,Commerce,68.00,Comm&Mgmt,No,64,Mkt&Fin,62.46,Placed,250000
|
||||
50,F,50.00,Others,37.00,Others,Arts,52.00,Others,No,65,Mkt&HR,56.11,Not Placed,
|
||||
51,F,75.20,Central,73.20,Central,Science,68.40,Comm&Mgmt,No,65,Mkt&HR,62.98,Placed,200000
|
||||
52,M,54.40,Central,61.12,Central,Commerce,56.20,Comm&Mgmt,No,67,Mkt&HR,62.65,Not Placed,
|
||||
53,F,40.89,Others,45.83,Others,Commerce,53.00,Comm&Mgmt,No,71.2,Mkt&HR,65.49,Not Placed,
|
||||
54,M,80.00,Others,70.00,Others,Science,72.00,Sci&Tech,No,87,Mkt&HR,71.04,Placed,450000
|
||||
55,F,74.00,Central,60.00,Others,Science,69.00,Comm&Mgmt,No,78,Mkt&HR,65.56,Placed,216000
|
||||
56,M,60.40,Central,66.60,Others,Science,65.00,Comm&Mgmt,No,71,Mkt&HR,52.71,Placed,220000
|
||||
57,M,63.00,Others,71.40,Others,Commerce,61.40,Comm&Mgmt,No,68,Mkt&Fin,66.88,Placed,240000
|
||||
58,M,68.00,Central,76.00,Central,Commerce,74.00,Comm&Mgmt,No,80,Mkt&Fin,63.59,Placed,360000
|
||||
59,M,74.00,Central,62.00,Others,Science,68.00,Comm&Mgmt,No,74,Mkt&Fin,57.99,Placed,268000
|
||||
60,M,52.60,Central,65.58,Others,Science,72.11,Sci&Tech,No,57.6,Mkt&Fin,56.66,Placed,265000
|
||||
61,M,74.00,Central,70.00,Central,Science,72.00,Comm&Mgmt,Yes,60,Mkt&Fin,57.24,Placed,260000
|
||||
62,M,84.20,Central,73.40,Central,Commerce,66.89,Comm&Mgmt,No,61.6,Mkt&Fin,62.48,Placed,300000
|
||||
63,F,86.50,Others,64.20,Others,Science,67.40,Sci&Tech,No,59,Mkt&Fin,59.69,Placed,240000
|
||||
64,M,61.00,Others,70.00,Others,Commerce,64.00,Comm&Mgmt,No,68.5,Mkt&HR,59.5,Not Placed,
|
||||
65,M,80.00,Others,73.00,Others,Commerce,75.00,Comm&Mgmt,No,61,Mkt&Fin,58.78,Placed,240000
|
||||
66,M,54.00,Others,47.00,Others,Science,57.00,Comm&Mgmt,No,89.69,Mkt&HR,57.1,Not Placed,
|
||||
67,M,83.00,Others,74.00,Others,Science,66.00,Comm&Mgmt,No,68.92,Mkt&HR,58.46,Placed,275000
|
||||
68,M,80.92,Others,78.50,Others,Commerce,67.00,Comm&Mgmt,No,68.71,Mkt&Fin,60.99,Placed,275000
|
||||
69,F,69.70,Central,47.00,Central,Commerce,72.70,Sci&Tech,No,79,Mkt&HR,59.24,Not Placed,
|
||||
70,M,73.00,Central,73.00,Central,Science,66.00,Sci&Tech,Yes,70,Mkt&Fin,68.07,Placed,275000
|
||||
71,M,82.00,Others,61.00,Others,Science,62.00,Sci&Tech,No,89,Mkt&Fin,65.45,Placed,360000
|
||||
72,M,75.00,Others,70.29,Others,Commerce,71.00,Comm&Mgmt,No,95,Mkt&Fin,66.94,Placed,240000
|
||||
73,M,84.86,Others,67.00,Others,Science,78.00,Comm&Mgmt,No,95.5,Mkt&Fin,68.53,Placed,240000
|
||||
74,M,64.60,Central,83.83,Others,Commerce,71.72,Comm&Mgmt,No,86,Mkt&Fin,59.75,Placed,218000
|
||||
75,M,56.60,Central,64.80,Central,Commerce,70.20,Comm&Mgmt,No,84.27,Mkt&Fin,67.2,Placed,336000
|
||||
76,F,59.00,Central,62.00,Others,Commerce,77.50,Comm&Mgmt,No,74,Mkt&HR,67,Not Placed,
|
||||
77,F,66.50,Others,70.40,Central,Arts,71.93,Comm&Mgmt,No,61,Mkt&Fin,64.27,Placed,230000
|
||||
78,M,64.00,Others,80.00,Others,Science,65.00,Sci&Tech,Yes,69,Mkt&Fin,57.65,Placed,500000
|
||||
79,M,84.00,Others,90.90,Others,Science,64.50,Sci&Tech,No,86.04,Mkt&Fin,59.42,Placed,270000
|
||||
80,F,69.00,Central,62.00,Central,Science,66.00,Sci&Tech,No,75,Mkt&HR,67.99,Not Placed,
|
||||
81,F,69.00,Others,62.00,Others,Commerce,69.00,Comm&Mgmt,Yes,67,Mkt&HR,62.35,Placed,240000
|
||||
82,M,81.70,Others,63.00,Others,Science,67.00,Comm&Mgmt,Yes,86,Mkt&Fin,70.2,Placed,300000
|
||||
83,M,63.00,Central,67.00,Central,Commerce,74.00,Comm&Mgmt,No,82,Mkt&Fin,60.44,Not Placed,
|
||||
84,M,84.00,Others,79.00,Others,Science,68.00,Sci&Tech,Yes,84,Mkt&Fin,66.69,Placed,300000
|
||||
85,M,70.00,Central,63.00,Others,Science,70.00,Sci&Tech,Yes,55,Mkt&Fin,62,Placed,300000
|
||||
86,F,83.84,Others,89.83,Others,Commerce,77.20,Comm&Mgmt,Yes,78.74,Mkt&Fin,76.18,Placed,400000
|
||||
87,M,62.00,Others,63.00,Others,Commerce,64.00,Comm&Mgmt,No,67,Mkt&Fin,57.03,Placed,220000
|
||||
88,M,59.60,Central,51.00,Central,Science,60.00,Others,No,75,Mkt&HR,59.08,Not Placed,
|
||||
89,F,66.00,Central,62.00,Central,Commerce,73.00,Comm&Mgmt,No,58,Mkt&HR,64.36,Placed,210000
|
||||
90,F,84.00,Others,75.00,Others,Science,69.00,Sci&Tech,Yes,62,Mkt&HR,62.36,Placed,210000
|
||||
91,F,85.00,Others,90.00,Others,Commerce,82.00,Comm&Mgmt,No,92,Mkt&Fin,68.03,Placed,300000
|
||||
92,M,52.00,Central,57.00,Central,Commerce,50.80,Comm&Mgmt,No,67,Mkt&HR,62.79,Not Placed,
|
||||
93,F,60.23,Central,69.00,Central,Science,66.00,Comm&Mgmt,No,72,Mkt&Fin,59.47,Placed,230000
|
||||
94,M,52.00,Central,62.00,Central,Commerce,54.00,Comm&Mgmt,No,72,Mkt&HR,55.41,Not Placed,
|
||||
95,M,58.00,Central,62.00,Central,Commerce,64.00,Comm&Mgmt,No,53.88,Mkt&Fin,54.97,Placed,260000
|
||||
96,M,73.00,Central,78.00,Others,Commerce,65.00,Comm&Mgmt,Yes,95.46,Mkt&Fin,62.16,Placed,420000
|
||||
97,F,76.00,Central,70.00,Central,Science,76.00,Comm&Mgmt,Yes,66,Mkt&Fin,64.44,Placed,300000
|
||||
98,F,70.50,Central,62.50,Others,Commerce,61.00,Comm&Mgmt,No,93.91,Mkt&Fin,69.03,Not Placed,
|
||||
99,F,69.00,Central,73.00,Central,Commerce,65.00,Comm&Mgmt,No,70,Mkt&Fin,57.31,Placed,220000
|
||||
100,M,54.00,Central,82.00,Others,Commerce,63.00,Sci&Tech,No,50,Mkt&Fin,59.47,Not Placed,
|
||||
101,F,45.00,Others,57.00,Others,Commerce,58.00,Comm&Mgmt,Yes,56.39,Mkt&HR,64.95,Not Placed,
|
||||
102,M,63.00,Central,72.00,Central,Commerce,68.00,Comm&Mgmt,No,78,Mkt&HR,60.44,Placed,380000
|
||||
103,F,77.00,Others,61.00,Others,Commerce,68.00,Comm&Mgmt,Yes,57.5,Mkt&Fin,61.31,Placed,300000
|
||||
104,M,73.00,Central,78.00,Central,Science,73.00,Sci&Tech,Yes,85,Mkt&HR,65.83,Placed,240000
|
||||
105,M,69.00,Central,63.00,Others,Science,65.00,Comm&Mgmt,Yes,55,Mkt&HR,58.23,Placed,360000
|
||||
106,M,59.00,Central,64.00,Others,Science,58.00,Sci&Tech,No,85,Mkt&HR,55.3,Not Placed,
|
||||
107,M,61.08,Others,50.00,Others,Science,54.00,Sci&Tech,No,71,Mkt&Fin,65.69,Not Placed,
|
||||
108,M,82.00,Others,90.00,Others,Commerce,83.00,Comm&Mgmt,No,80,Mkt&HR,73.52,Placed,200000
|
||||
109,M,61.00,Central,82.00,Central,Commerce,69.00,Comm&Mgmt,No,84,Mkt&Fin,58.31,Placed,300000
|
||||
110,M,52.00,Central,63.00,Others,Science,65.00,Sci&Tech,Yes,86,Mkt&HR,56.09,Not Placed,
|
||||
111,F,69.50,Central,70.00,Central,Science,72.00,Sci&Tech,No,57.2,Mkt&HR,54.8,Placed,250000
|
||||
112,M,51.00,Others,54.00,Others,Science,61.00,Sci&Tech,No,60,Mkt&HR,60.64,Not Placed,
|
||||
113,M,58.00,Others,61.00,Others,Commerce,61.00,Comm&Mgmt,No,58,Mkt&HR,53.94,Placed,250000
|
||||
114,F,73.96,Others,79.00,Others,Commerce,67.00,Comm&Mgmt,No,72.15,Mkt&Fin,63.08,Placed,280000
|
||||
115,M,65.00,Central,68.00,Others,Science,69.00,Comm&Mgmt,No,53.7,Mkt&HR,55.01,Placed,250000
|
||||
116,F,73.00,Others,63.00,Others,Science,66.00,Comm&Mgmt,No,89,Mkt&Fin,60.5,Placed,216000
|
||||
117,M,68.20,Central,72.80,Central,Commerce,66.60,Comm&Mgmt,Yes,96,Mkt&Fin,70.85,Placed,300000
|
||||
118,M,77.00,Others,75.00,Others,Science,73.00,Sci&Tech,No,80,Mkt&Fin,67.05,Placed,240000
|
||||
119,M,76.00,Central,80.00,Central,Science,78.00,Sci&Tech,Yes,97,Mkt&HR,70.48,Placed,276000
|
||||
120,M,60.80,Central,68.40,Central,Commerce,64.60,Comm&Mgmt,Yes,82.66,Mkt&Fin,64.34,Placed,940000
|
||||
121,M,58.00,Others,40.00,Others,Science,59.00,Comm&Mgmt,No,73,Mkt&HR,58.81,Not Placed,
|
||||
122,F,64.00,Central,67.00,Others,Science,69.60,Sci&Tech,Yes,55.67,Mkt&HR,71.49,Placed,250000
|
||||
123,F,66.50,Central,66.80,Central,Arts,69.30,Comm&Mgmt,Yes,80.4,Mkt&Fin,71,Placed,236000
|
||||
124,M,74.00,Others,59.00,Others,Commerce,73.00,Comm&Mgmt,Yes,60,Mkt&HR,56.7,Placed,240000
|
||||
125,M,67.00,Central,71.00,Central,Science,64.33,Others,Yes,64,Mkt&HR,61.26,Placed,250000
|
||||
126,F,84.00,Central,73.00,Central,Commerce,73.00,Comm&Mgmt,No,75,Mkt&Fin,73.33,Placed,350000
|
||||
127,F,79.00,Others,61.00,Others,Science,75.50,Sci&Tech,Yes,70,Mkt&Fin,68.2,Placed,210000
|
||||
128,F,72.00,Others,60.00,Others,Science,69.00,Comm&Mgmt,No,55.5,Mkt&HR,58.4,Placed,250000
|
||||
129,M,80.40,Central,73.40,Central,Science,77.72,Sci&Tech,Yes,81.2,Mkt&HR,76.26,Placed,400000
|
||||
130,M,76.70,Central,89.70,Others,Commerce,66.00,Comm&Mgmt,Yes,90,Mkt&Fin,68.55,Placed,250000
|
||||
131,M,62.00,Central,65.00,Others,Commerce,60.00,Comm&Mgmt,No,84,Mkt&Fin,64.15,Not Placed,
|
||||
132,F,74.90,Others,57.00,Others,Science,62.00,Others,Yes,80,Mkt&Fin,60.78,Placed,360000
|
||||
133,M,67.00,Others,68.00,Others,Commerce,64.00,Comm&Mgmt,Yes,74.4,Mkt&HR,53.49,Placed,300000
|
||||
134,M,73.00,Central,64.00,Others,Commerce,77.00,Comm&Mgmt,Yes,65,Mkt&HR,60.98,Placed,250000
|
||||
135,F,77.44,Central,92.00,Others,Commerce,72.00,Comm&Mgmt,Yes,94,Mkt&Fin,67.13,Placed,250000
|
||||
136,F,72.00,Central,56.00,Others,Science,69.00,Comm&Mgmt,No,55.6,Mkt&HR,65.63,Placed,200000
|
||||
137,F,47.00,Central,59.00,Central,Arts,64.00,Comm&Mgmt,No,78,Mkt&Fin,61.58,Not Placed,
|
||||
138,M,67.00,Others,63.00,Central,Commerce,72.00,Comm&Mgmt,No,56,Mkt&HR,60.41,Placed,225000
|
||||
139,F,82.00,Others,64.00,Others,Science,73.00,Sci&Tech,Yes,96,Mkt&Fin,71.77,Placed,250000
|
||||
140,M,77.00,Central,70.00,Central,Commerce,59.00,Comm&Mgmt,Yes,58,Mkt&Fin,54.43,Placed,220000
|
||||
141,M,65.00,Central,64.80,Others,Commerce,69.50,Comm&Mgmt,Yes,56,Mkt&Fin,56.94,Placed,265000
|
||||
142,M,66.00,Central,64.00,Central,Science,60.00,Comm&Mgmt,No,60,Mkt&HR,61.9,Not Placed,
|
||||
143,M,85.00,Central,60.00,Others,Science,73.43,Sci&Tech,Yes,60,Mkt&Fin,61.29,Placed,260000
|
||||
144,M,77.67,Others,64.89,Others,Commerce,70.67,Comm&Mgmt,No,89,Mkt&Fin,60.39,Placed,300000
|
||||
145,M,52.00,Others,50.00,Others,Arts,61.00,Comm&Mgmt,No,60,Mkt&Fin,58.52,Not Placed,
|
||||
146,M,89.40,Others,65.66,Others,Science,71.25,Sci&Tech,No,72,Mkt&HR,63.23,Placed,400000
|
||||
147,M,62.00,Central,63.00,Others,Science,66.00,Comm&Mgmt,No,85,Mkt&HR,55.14,Placed,233000
|
||||
148,M,70.00,Central,74.00,Central,Commerce,65.00,Comm&Mgmt,No,83,Mkt&Fin,62.28,Placed,300000
|
||||
149,F,77.00,Central,86.00,Central,Arts,56.00,Others,No,57,Mkt&Fin,64.08,Placed,240000
|
||||
150,M,44.00,Central,58.00,Central,Arts,55.00,Comm&Mgmt,Yes,64.25,Mkt&HR,58.54,Not Placed,
|
||||
151,M,71.00,Central,58.66,Central,Science,58.00,Sci&Tech,Yes,56,Mkt&Fin,61.3,Placed,690000
|
||||
152,M,65.00,Central,65.00,Central,Commerce,75.00,Comm&Mgmt,No,83,Mkt&Fin,58.87,Placed,270000
|
||||
153,F,75.40,Others,60.50,Central,Science,84.00,Sci&Tech,No,98,Mkt&Fin,65.25,Placed,240000
|
||||
154,M,49.00,Others,59.00,Others,Science,65.00,Sci&Tech,Yes,86,Mkt&Fin,62.48,Placed,340000
|
||||
155,M,53.00,Central,63.00,Others,Science,60.00,Comm&Mgmt,Yes,70,Mkt&Fin,53.2,Placed,250000
|
||||
156,M,51.57,Others,74.66,Others,Commerce,59.90,Comm&Mgmt,Yes,56.15,Mkt&HR,65.99,Not Placed,
|
||||
157,M,84.20,Central,69.40,Central,Science,65.00,Sci&Tech,Yes,80,Mkt&HR,52.72,Placed,255000
|
||||
158,M,66.50,Central,62.50,Central,Commerce,60.90,Comm&Mgmt,No,93.4,Mkt&Fin,55.03,Placed,300000
|
||||
159,M,67.00,Others,63.00,Others,Science,64.00,Sci&Tech,No,60,Mkt&Fin,61.87,Not Placed,
|
||||
160,M,52.00,Central,49.00,Others,Commerce,58.00,Comm&Mgmt,No,62,Mkt&HR,60.59,Not Placed,
|
||||
161,M,87.00,Central,74.00,Central,Science,65.00,Sci&Tech,Yes,75,Mkt&HR,72.29,Placed,300000
|
||||
162,M,55.60,Others,51.00,Others,Commerce,57.50,Comm&Mgmt,No,57.63,Mkt&HR,62.72,Not Placed,
|
||||
163,M,74.20,Central,87.60,Others,Commerce,77.25,Comm&Mgmt,Yes,75.2,Mkt&Fin,66.06,Placed,285000
|
||||
164,M,63.00,Others,67.00,Others,Science,64.00,Sci&Tech,No,75,Mkt&Fin,66.46,Placed,500000
|
||||
165,F,67.16,Central,72.50,Central,Commerce,63.35,Comm&Mgmt,No,53.04,Mkt&Fin,65.52,Placed,250000
|
||||
166,F,63.30,Central,78.33,Others,Commerce,74.00,Comm&Mgmt,No,80,Mkt&Fin,74.56,Not Placed,
|
||||
167,M,62.00,Others,62.00,Others,Commerce,60.00,Comm&Mgmt,Yes,63,Mkt&HR,52.38,Placed,240000
|
||||
168,M,67.90,Others,62.00,Others,Science,67.00,Sci&Tech,Yes,58.1,Mkt&Fin,75.71,Not Placed,
|
||||
169,F,48.00,Central,51.00,Central,Commerce,58.00,Comm&Mgmt,Yes,60,Mkt&HR,58.79,Not Placed,
|
||||
170,M,59.96,Others,42.16,Others,Science,61.26,Sci&Tech,No,54.48,Mkt&HR,65.48,Not Placed,
|
||||
171,F,63.40,Others,67.20,Others,Commerce,60.00,Comm&Mgmt,No,58.06,Mkt&HR,69.28,Not Placed,
|
||||
172,M,80.00,Others,80.00,Others,Commerce,72.00,Comm&Mgmt,Yes,63.79,Mkt&Fin,66.04,Placed,290000
|
||||
173,M,73.00,Others,58.00,Others,Commerce,56.00,Comm&Mgmt,No,84,Mkt&HR,52.64,Placed,300000
|
||||
174,F,52.00,Others,52.00,Others,Science,55.00,Sci&Tech,No,67,Mkt&HR,59.32,Not Placed,
|
||||
175,M,73.24,Others,50.83,Others,Science,64.27,Sci&Tech,Yes,64,Mkt&Fin,66.23,Placed,500000
|
||||
176,M,63.00,Others,62.00,Others,Science,65.00,Sci&Tech,No,87.5,Mkt&HR,60.69,Not Placed,
|
||||
177,F,59.00,Central,60.00,Others,Commerce,56.00,Comm&Mgmt,No,55,Mkt&HR,57.9,Placed,220000
|
||||
178,F,73.00,Central,97.00,Others,Commerce,79.00,Comm&Mgmt,Yes,89,Mkt&Fin,70.81,Placed,650000
|
||||
179,M,68.00,Others,56.00,Others,Science,68.00,Sci&Tech,No,73,Mkt&HR,68.07,Placed,350000
|
||||
180,F,77.80,Central,64.00,Central,Science,64.20,Sci&Tech,No,75.5,Mkt&HR,72.14,Not Placed,
|
||||
181,M,65.00,Central,71.50,Others,Commerce,62.80,Comm&Mgmt,Yes,57,Mkt&Fin,56.6,Placed,265000
|
||||
182,M,62.00,Central,60.33,Others,Science,64.21,Sci&Tech,No,63,Mkt&HR,60.02,Not Placed,
|
||||
183,M,52.00,Others,65.00,Others,Arts,57.00,Others,Yes,75,Mkt&Fin,59.81,Not Placed,
|
||||
184,M,65.00,Central,77.00,Central,Commerce,69.00,Comm&Mgmt,No,60,Mkt&HR,61.82,Placed,276000
|
||||
185,F,56.28,Others,62.83,Others,Commerce,59.79,Comm&Mgmt,No,60,Mkt&HR,57.29,Not Placed,
|
||||
186,F,88.00,Central,72.00,Central,Science,78.00,Others,No,82,Mkt&HR,71.43,Placed,252000
|
||||
187,F,52.00,Central,64.00,Central,Commerce,61.00,Comm&Mgmt,No,55,Mkt&Fin,62.93,Not Placed,
|
||||
188,M,78.50,Central,65.50,Central,Science,67.00,Sci&Tech,Yes,95,Mkt&Fin,64.86,Placed,280000
|
||||
189,M,61.80,Others,47.00,Others,Commerce,54.38,Comm&Mgmt,No,57,Mkt&Fin,56.13,Not Placed,
|
||||
190,F,54.00,Central,77.60,Others,Commerce,69.20,Comm&Mgmt,No,95.65,Mkt&Fin,66.94,Not Placed,
|
||||
191,F,64.00,Others,70.20,Central,Commerce,61.00,Comm&Mgmt,No,50,Mkt&Fin,62.5,Not Placed,
|
||||
192,M,67.00,Others,61.00,Central,Science,72.00,Comm&Mgmt,No,72,Mkt&Fin,61.01,Placed,264000
|
||||
193,M,65.20,Central,61.40,Central,Commerce,64.80,Comm&Mgmt,Yes,93.4,Mkt&Fin,57.34,Placed,270000
|
||||
194,F,60.00,Central,63.00,Central,Arts,56.00,Others,Yes,80,Mkt&HR,56.63,Placed,300000
|
||||
195,M,52.00,Others,55.00,Others,Commerce,56.30,Comm&Mgmt,No,59,Mkt&Fin,64.74,Not Placed,
|
||||
196,M,66.00,Central,76.00,Central,Commerce,72.00,Comm&Mgmt,Yes,84,Mkt&HR,58.95,Placed,275000
|
||||
197,M,72.00,Others,63.00,Others,Science,77.50,Sci&Tech,Yes,78,Mkt&Fin,54.48,Placed,250000
|
||||
198,F,83.96,Others,53.00,Others,Science,91.00,Sci&Tech,No,59.32,Mkt&HR,69.71,Placed,260000
|
||||
199,F,67.00,Central,70.00,Central,Commerce,65.00,Others,No,88,Mkt&HR,71.96,Not Placed,
|
||||
200,M,69.00,Others,65.00,Others,Commerce,57.00,Comm&Mgmt,No,73,Mkt&HR,55.8,Placed,265000
|
||||
201,M,69.00,Others,60.00,Others,Commerce,65.00,Comm&Mgmt,No,87.55,Mkt&Fin,52.81,Placed,300000
|
||||
202,M,54.20,Central,63.00,Others,Science,58.00,Comm&Mgmt,No,79,Mkt&HR,58.44,Not Placed,
|
||||
203,M,70.00,Central,63.00,Central,Science,66.00,Sci&Tech,No,61.28,Mkt&HR,60.11,Placed,240000
|
||||
204,M,55.68,Others,61.33,Others,Commerce,56.87,Comm&Mgmt,No,66,Mkt&HR,58.3,Placed,260000
|
||||
205,F,74.00,Others,73.00,Others,Commerce,73.00,Comm&Mgmt,Yes,80,Mkt&Fin,67.69,Placed,210000
|
||||
206,M,61.00,Others,62.00,Others,Commerce,65.00,Comm&Mgmt,No,62,Mkt&Fin,56.81,Placed,250000
|
||||
207,M,41.00,Central,42.00,Central,Science,60.00,Comm&Mgmt,No,97,Mkt&Fin,53.39,Not Placed,
|
||||
208,M,83.33,Central,78.00,Others,Commerce,61.00,Comm&Mgmt,Yes,88.56,Mkt&Fin,71.55,Placed,300000
|
||||
209,F,43.00,Central,60.00,Others,Science,65.00,Comm&Mgmt,No,92.66,Mkt&HR,62.92,Not Placed,
|
||||
210,M,62.00,Central,72.00,Central,Commerce,65.00,Comm&Mgmt,No,67,Mkt&Fin,56.49,Placed,216000
|
||||
211,M,80.60,Others,82.00,Others,Commerce,77.60,Comm&Mgmt,No,91,Mkt&Fin,74.49,Placed,400000
|
||||
212,M,58.00,Others,60.00,Others,Science,72.00,Sci&Tech,No,74,Mkt&Fin,53.62,Placed,275000
|
||||
213,M,67.00,Others,67.00,Others,Commerce,73.00,Comm&Mgmt,Yes,59,Mkt&Fin,69.72,Placed,295000
|
||||
214,F,74.00,Others,66.00,Others,Commerce,58.00,Comm&Mgmt,No,70,Mkt&HR,60.23,Placed,204000
|
||||
215,M,62.00,Central,58.00,Others,Science,53.00,Comm&Mgmt,No,89,Mkt&HR,60.22,Not Placed,
|
|
1
config.txt
Normal file
1
config.txt
Normal file
@ -0,0 +1 @@
|
||||
--metric RMSE --precision 1
|
1000
dev-0/expected.tsv
Normal file
1000
dev-0/expected.tsv
Normal file
File diff suppressed because it is too large
Load Diff
1000
dev-0/in.tsv
Normal file
1000
dev-0/in.tsv
Normal file
File diff suppressed because it is too large
Load Diff
1000
dev-0/out.tsv
Normal file
1000
dev-0/out.tsv
Normal file
File diff suppressed because it is too large
Load Diff
255
main.ipynb
Normal file
255
main.ipynb
Normal file
@ -0,0 +1,255 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 144,
|
||||
"id": "44a708aa",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas\n",
|
||||
"from sklearn.linear_model import LinearRegression\n",
|
||||
"from sklearn.metrics import mean_squared_error\n",
|
||||
"from sklearn.metrics import precision_score\n",
|
||||
"import torch\n",
|
||||
"from torch import nn\n",
|
||||
"from sklearn import preprocessing\n",
|
||||
"import numpy as np\n",
|
||||
"from sklearn.naive_bayes import GaussianNB"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7a4557aa",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Przygotowanie danych"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 146,
|
||||
"id": "de736649",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"r_in = './train/train.tsv'\n",
|
||||
"dev_expected= './dev-0/expected.tsv'\n",
|
||||
"r_ind_ev = './dev-0/in.tsv'\n",
|
||||
"\n",
|
||||
"expected = pd.read_csv(dev_expected, error_bad_lines=False, header=None, sep=\"\\t\")\n",
|
||||
"Y_test = expected[0]\n",
|
||||
"\n",
|
||||
"with open('./names') as f_names:\n",
|
||||
" names = f_names.read().rstrip('\\n').split('\\t')\n",
|
||||
"\n",
|
||||
"tsv_read = pandas.read_table(r_in, error_bad_lines=False, sep='\\t', names=names)\n",
|
||||
"tsv_read_dev = pandas.read_table(r_ind_ev, error_bad_lines=False, sep='\\t',\n",
|
||||
" names=['mileage', 'year', 'brand', 'engineType', 'engineCapacity'])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"train = pandas.get_dummies(tsv_read, columns=['engineType'])\n",
|
||||
"\n",
|
||||
"categorical_cols = train.select_dtypes(include=object).columns.values\n",
|
||||
"for col in categorical_cols:\n",
|
||||
" train[col] = train[col].astype('category').cat.codes\n",
|
||||
"\n",
|
||||
"train = train.loc[(train['price'] > 1000)]\n",
|
||||
"\n",
|
||||
"X = train.loc[:, train.columns != 'price']\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"dev = pandas.get_dummies(tsv_read_dev, columns=['engineType'])\n",
|
||||
"\n",
|
||||
"categorical_cols1 = dev.select_dtypes(include=object).columns.values\n",
|
||||
"for col in categorical_cols1:\n",
|
||||
" dev[col] = dev[col].astype('category').cat.codes\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 147,
|
||||
"id": "b8e71b16",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"335531\n",
|
||||
"7000\n",
|
||||
"1000\n",
|
||||
"Index(['mileage', 'year', 'brand', 'engineCapacity', 'engineType_benzyna',\n",
|
||||
" 'engineType_diesel', 'engineType_gaz'],\n",
|
||||
" dtype='object')\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"print(X.size)\n",
|
||||
"print(dev.size)\n",
|
||||
"print(Y_test.size)\n",
|
||||
"print(dev.columns)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "add6af4d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Regresja Liniowa"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 148,
|
||||
"id": "ac09c69c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 1163801682.3714898\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"clf = LinearRegression().fit(X, train['price'])\n",
|
||||
"predictions = clf.predict(dev)\n",
|
||||
"\n",
|
||||
"test = pandas.get_dummies(tsv_read_test_A, columns=['engineType'])\n",
|
||||
"print(\"MSE: \", mean_squared_error(Y_test, predictions))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6e19cd2f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Pytroch regresja logistyczna"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 149,
|
||||
"id": "fb9d136a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"dev = dev[['mileage','year','brand','engineCapacity', 'engineType_benzyna', 'engineType_diesel', 'engineType_gaz']].astype(np.float32)\n",
|
||||
"X = X[['mileage','year','brand','engineCapacity', 'engineType_benzyna', 'engineType_diesel', 'engineType_gaz']].astype(np.float32)\n",
|
||||
"ytrain = train['price'].astype(np.float32)\n",
|
||||
"Y_test = Y_test.astype(np.float32)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"torch_tensor_X = torch.from_numpy(X.values)\n",
|
||||
"torch_tensor_Y = torch.from_numpy(ytrain.values.reshape(47933,1))\n",
|
||||
"torch_tensor_dev = torch.from_numpy(dev.values)\n",
|
||||
"torch_tensor_Y_test = torch.from_numpy(Y_test.values)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 151,
|
||||
"id": "9d50f6f4",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 4107035476.14\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"class LogisticRegressionModel(nn.Module):\n",
|
||||
" def __init__(self, input_dim, output_dim):\n",
|
||||
" super(LogisticRegressionModel, self).__init__()\n",
|
||||
" self.linear = nn.Linear(input_dim, output_dim)\n",
|
||||
" self.sigmoid = nn.Sigmoid()\n",
|
||||
" def forward(self, x):\n",
|
||||
" out = self.linear(x)\n",
|
||||
" return self.sigmoid(out)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"learning_rate = 0.0002\n",
|
||||
"input_dim = 7\n",
|
||||
"output_dim = 1\n",
|
||||
"\n",
|
||||
"model = LogisticRegressionModel(input_dim, output_dim)\n",
|
||||
"criterion = torch.nn.BCELoss(reduction='mean')\n",
|
||||
"optimizer = torch.optim.SGD(model.parameters(), lr = learning_rate)\n",
|
||||
"\n",
|
||||
"for epoch in range(10):\n",
|
||||
" # print (\"Epoch #\",epoch)\n",
|
||||
" model.train()\n",
|
||||
" optimizer.zero_grad()\n",
|
||||
" # Forward pass\n",
|
||||
" y_pred = model(torch_tensor_X)\n",
|
||||
" # Compute Loss\n",
|
||||
" loss = criterion(y_pred, torch_tensor_Y)\n",
|
||||
" # print(loss.item())\n",
|
||||
" # Backward pass\n",
|
||||
" loss.backward()\n",
|
||||
" optimizer.step()\n",
|
||||
"predictions = model(torch_tensor_dev)\n",
|
||||
"print(\"MSE: \", mean_squared_error(torch_tensor_Y_test, np.argmax(predictions.detach().numpy(), axis=1)))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "995ea3a5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Naiwny Bayes"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 152,
|
||||
"id": "0aa24c4c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"MSE: 1648858588.032\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"gnb = GaussianNB()\n",
|
||||
"predictions = gnb.fit(X, train['price']).predict(dev)\n",
|
||||
"print(\"MSE: \", mean_squared_error(Y_test, predictions))"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
BIN
raport.docx
Normal file
BIN
raport.docx
Normal file
Binary file not shown.
48002
train/train.tsv
Normal file
48002
train/train.tsv
Normal file
File diff suppressed because it is too large
Load Diff
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Reference in New Issue
Block a user