Mapping of eras from old to new

Data Science
1

I mapped the old eras to the new eras by comparing ids. It seems

  • some eras don’t map to the new data (perhaps ids were changed?)
  • when they do map, a few ids are dropped, but no new ids are added
old_era new_era ids_in_new_and_old ids_only_in_old ids_only_in_new
1 5 2405 3 0
2 9 2368 3 0
3 no match - 2424 -
4 no match - 2543 -
5 22 2672 7 0
6 no match - 2875 -
7 no match - 3026 -
8 35 3014 4 0
9 no match - 3171 -
10 44 3330 6 0
11 48 3379 10 0
12 no match - 3419 -
13 57 3277 13 0
14 61 3307 6 0
15 no match - 3587 -
16 70 3581 8 0
17 no match - 3529 -
18 no match - 3583 -
19 83 3558 7 0
20 no match - 3507 -
21 no match - 3499 -
22 96 3544 5 0
23 no match - 3670 -
24 105 3756 4 0
25 no match - 3847 -
26 no match - 3885 -
27 no match - 3941 -
28 122 3909 12 0
29 no match - 3865 -
30 no match - 3940 -
31 135 3958 18 0
32 no match - 3957 -
33 144 3987 20 0
34 no match - 4047 -
35 no match - 4097 -
36 157 4141 20 0
37 no match - 4240 -
38 no match - 4310 -
39 170 4357 9 0
40 174 4417 20 0
41 no match - 4260 -
42 183 4254 20 0
43 no match - 4251 -
44 no match - 4209 -
45 196 4189 19 0
46 no match - 4307 -
47 no match - 4409 -
48 209 4477 26 0
49 no match - 4581 -
50 no match - 4657 -
51 222 4693 16 0
52 no match - 4757 -
53 no match - 4799 -
54 235 4866 21 0
55 no match - 4893 -
56 244 4856 23 0
57 248 4841 29 0
58 no match - 4893 -
59 257 4820 22 0
60 no match - 4835 -
61 no match - 4780 -
62 270 4758 19 0
63 no match - 4735 -
64 no match - 4743 -
65 283 4677 42 0
66 no match - 4628 -
67 no match - 4609 -
68 296 4550 23 0
69 no match - 4432 -
70 305 4120 18 0
71 309 4026 16 0
72 no match - 4058 -
73 318 3925 7 0
74 322 3782 12 0
75 no match - 3790 -
76 no match - 3967 -
77 335 4155 10 0
78 no match - 4257 -
79 344 4252 8 0
80 no match - 4351 -
81 no match - 4418 -
82 357 4418 9 0
83 no match - 4393 -
84 no match - 4384 -
85 370 4369 12 0
86 374 4337 17 0
87 no match - 4428 -
88 383 4412 13 0
89 no match - 4410 -
90 no match - 4468 -
91 396 4424 19 0
92 no match - 4381 -
93 no match - 4454 -
94 409 4488 21 0
95 no match - 4534 -
96 418 4642 16 0
97 no match - 4696 -
98 no match - 4717 -
99 no match - 4749 -
100 435 4726 22 0
101 no match - 4730 -
102 no match - 4704 -
103 448 4694 15 0
104 no match - 4643 -
105 457 4556 21 0
106 no match - 4638 -
107 no match - 4517 -
108 470 4403 18 0
109 no match - 4420 -
110 no match - 4553 -
111 483 4587 24 0
112 no match - 4588 -
113 no match - 4461 -
114 496 4478 18 0
115 no match - 4500 -
116 505 4413 22 0
117 509 4463 19 0
118 no match - 4450 -
119 518 4468 26 0
120 no match - 4532 -
121 no match - 4573 -
122 no match - 4658 -
123 535 4589 20 0
124 no match - 4630 -
125 544 4671 27 0
126 548 4660 22 0
127 no match - 4688 -
128 557 4616 20 0
129 no match - 4705 -
130 no match - 4756 -
131 570 4791 23 0
132 no match - 4812 -
197 857 4947 23 0
198 861 4958 23 0
199 no match - 5006 -
200 870 4907 22 0
201 no match - 5083 -
202 no match - 5090 -
203 883 5094 25 0
204 no match - 5152 -
205 892 5137 24 0
206 896 5119 24 0
207 no match - 4991 -
208 no match - 5114 -
209 909 5142 22 0
210 no match - 5227 -
211 918 5174 23 0
212 no match - 5191 -
3 Likes
2

Very interesting, mic – and great data sleuthing.

So, when the id of an old row matches the id of a new row: do you find that either features or target of those rows also match (or correlate)?

3

I didn’t check features as the team has said they won’t match.

The targets aren’t a perfect match, based on checking a sample. They do seem to match for about 70-80% of rows.

1 Like
4

Thx 4 that info! (20 char. min)