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datetime
timestamp[ns]
STATION_ID
int64
od_out_cnt
int64
od_in_cnt
int64
od_net_cnt
int64
2017-01-01T04:30:00
150
21
11
-10
2017-01-01T04:30:00
151
6
6
0
2017-01-01T04:30:00
152
12
5
-7
2017-01-01T04:30:00
153
3
2
-1
2017-01-01T04:30:00
154
1
1
0
2017-01-01T04:30:00
155
7
5
-2
2017-01-01T04:30:00
156
3
0
-3
2017-01-01T04:30:00
157
4
1
-3
2017-01-01T04:30:00
158
9
10
1
2017-01-01T04:30:00
159
1
3
2
2017-01-01T04:30:00
201
4
6
2
2017-01-01T04:30:00
202
0
2
2
2017-01-01T04:30:00
203
0
3
3
2017-01-01T04:30:00
204
0
2
2
2017-01-01T04:30:00
205
2
8
6
2017-01-01T04:30:00
206
1
3
2
2017-01-01T04:30:00
207
0
2
2
2017-01-01T04:30:00
208
4
3
-1
2017-01-01T04:30:00
210
0
1
1
2017-01-01T04:30:00
212
35
18
-17
2017-01-01T04:30:00
213
0
6
6
2017-01-01T04:30:00
214
1
34
33
2017-01-01T04:30:00
216
3
2
-1
2017-01-01T04:30:00
217
0
6
6
2017-01-01T04:30:00
218
0
1
1
2017-01-01T04:30:00
219
4
4
0
2017-01-01T04:30:00
220
1
5
4
2017-01-01T04:30:00
221
1
2
1
2017-01-01T04:30:00
222
3
10
7
2017-01-01T04:30:00
223
0
1
1
2017-01-01T04:30:00
224
0
2
2
2017-01-01T04:30:00
225
1
2
1
2017-01-01T04:30:00
226
2
8
6
2017-01-01T04:30:00
227
1
4
3
2017-01-01T04:30:00
228
10
6
-4
2017-01-01T04:30:00
229
0
2
2
2017-01-01T04:30:00
230
6
12
6
2017-01-01T04:30:00
231
3
6
3
2017-01-01T04:30:00
232
6
8
2
2017-01-01T04:30:00
233
8
2
-6
2017-01-01T04:30:00
234
26
21
-5
2017-01-01T04:30:00
235
0
5
5
2017-01-01T04:30:00
236
1
1
0
2017-01-01T04:30:00
237
0
8
8
2017-01-01T04:30:00
238
16
6
-10
2017-01-01T04:30:00
239
271
8
-263
2017-01-01T04:30:00
240
5
15
10
2017-01-01T04:30:00
241
1
1
0
2017-01-01T04:30:00
242
0
2
2
2017-01-01T04:30:00
243
1
0
-1
2017-01-01T04:30:00
244
0
5
5
2017-01-01T04:30:00
245
0
1
1
2017-01-01T04:30:00
246
1
0
-1
2017-01-01T04:30:00
248
2
2
0
2017-01-01T04:30:00
249
1
1
0
2017-01-01T04:30:00
309
1
1
0
2017-01-01T04:30:00
310
2
0
-2
2017-01-01T04:30:00
311
4
6
2
2017-01-01T04:30:00
312
1
6
5
2017-01-01T04:30:00
313
1
3
2
2017-01-01T04:30:00
314
1
2
1
2017-01-01T04:30:00
316
2
0
-2
2017-01-01T04:30:00
317
2
2
0
2017-01-01T04:30:00
319
1
1
0
2017-01-01T04:30:00
320
0
1
1
2017-01-01T04:30:00
322
0
3
3
2017-01-01T04:30:00
324
0
4
4
2017-01-01T04:30:00
325
0
1
1
2017-01-01T04:30:00
327
3
1
-2
2017-01-01T04:30:00
328
0
1
1
2017-01-01T04:30:00
329
1
12
11
2017-01-01T04:30:00
331
3
4
1
2017-01-01T04:30:00
332
2
3
1
2017-01-01T04:30:00
333
2
2
0
2017-01-01T04:30:00
334
1
1
0
2017-01-01T04:30:00
335
0
2
2
2017-01-01T04:30:00
337
0
3
3
2017-01-01T04:30:00
339
3
0
-3
2017-01-01T04:30:00
409
1
1
0
2017-01-01T04:30:00
410
2
6
4
2017-01-01T04:30:00
411
3
5
2
2017-01-01T04:30:00
412
5
2
-3
2017-01-01T04:30:00
413
1
2
1
2017-01-01T04:30:00
414
6
3
-3
2017-01-01T04:30:00
415
0
2
2
2017-01-01T04:30:00
416
4
7
3
2017-01-01T04:30:00
417
1
3
2
2017-01-01T04:30:00
418
1
3
2
2017-01-01T04:30:00
419
4
1
-3
2017-01-01T04:30:00
420
0
2
2
2017-01-01T04:30:00
421
12
0
-12
2017-01-01T04:30:00
422
2
1
-1
2017-01-01T04:30:00
423
5
5
0
2017-01-01T04:30:00
424
0
6
6
2017-01-01T04:30:00
425
2
4
2
2017-01-01T04:30:00
426
1
2
1
2017-01-01T04:30:00
428
1
0
-1
2017-01-01T04:30:00
429
0
1
1
2017-01-01T04:30:00
430
2
2
0
2017-01-01T04:30:00
432
0
1
1
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30_od_subway

This dataset contains 30-minute interval subway station-level statistics for the Seoul metropolitan transit system.
It is intended for mobility demand analysis, temporal flow pattern analysis, and comparison with other urban mobility datasets.

Dataset Description

Each file provides station-level subway usage statistics aggregated by 30-minute time windows.
The dataset can be used to analyze temporal demand fluctuations, peak-hour concentration, and station-level mobility patterns.

Number of Elements

  • Number of files: add your actual number here
  • Number of rows: add your actual total row count here
  • Unit of observation: station × date × 30-minute time interval

Main Columns

  • station_id: Subway station identifier
  • station_name: Subway station name
  • line_name: Subway line name
  • date: Observation date
  • time_bin: 30-minute time interval
  • boarding_count: Number of passengers boarding
  • alighting_count: Number of passengers alighting

Intended Use

30_od_subway

This dataset contains 30-minute interval subway station-level statistics for the Seoul metropolitan transit system.
It is intended for mobility demand analysis, temporal flow pattern analysis, and comparison with other urban mobility datasets.

Dataset Description

Each file provides station-level subway usage statistics aggregated by 30-minute time windows.
The dataset can be used to analyze temporal demand fluctuations, peak-hour concentration, and station-level mobility patterns.

Number of Elements

  • Number of files: add your actual number here
  • Number of rows: add your actual total row count here
  • Unit of observation: station × date × 30-minute time interval

Main Columns

  • station_id: Subway station identifier
  • station_name: Subway station name
  • line_name: Subway line name
  • date: Observation date
  • time_bin: 30-minute time interval
  • boarding_count: Number of passengers boarding
  • alighting_count: Number of passengers alighting

Intended Use

사용하시려겨든 thdud041113@g.skku.edu로 메일로 허가 얻으시고 사용해주세요 If you would like to use it, please obtain permission by email at thdud041113@g.skku.edu before using it.

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