Overview

Dataset statistics

Number of variables8
Number of observations272
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.7 KiB
Average record size in memory70.5 B

Variable types

Numeric6
Text1
Categorical1

Dataset

Description서울교통공사 역사별 세부 정보 데이터 입니다. 해당 데이터는 연번, 호선, 고유역번호, 역번호, 역명, 직원수, 수송인원, 운수수입, 비고 항목으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15107020/fileData.do

Alerts

연번 is highly overall correlated with 호선 and 3 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
역번호 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
직원수 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
수송인원 is highly overall correlated with 직원수 and 2 other fieldsHigh correlation
운수수입 is highly overall correlated with 직원수 and 2 other fieldsHigh correlation
비고 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
비고 is highly imbalanced (80.9%)Imbalance
연번 has unique valuesUnique
역번호 has unique valuesUnique
역명 has unique valuesUnique
수송인원 has unique valuesUnique
운수수입 has unique valuesUnique
직원수 has 7 (2.6%) zerosZeros

Reproduction

Analysis started2023-12-12 00:34:47.148874
Analysis finished2023-12-12 00:34:50.089688
Duration2.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.5
Minimum1
Maximum272
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:50.148686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.55
Q168.75
median136.5
Q3204.25
95-th percentile258.45
Maximum272
Range271
Interquartile range (IQR)135.5

Descriptive statistics

Standard deviation78.663842
Coefficient of variation (CV)0.57629188
Kurtosis-1.2
Mean136.5
Median Absolute Deviation (MAD)68
Skewness0
Sum37128
Variance6188
MonotonicityStrictly increasing
2023-12-12T09:34:50.265483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
181 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
182 1
 
0.4%
180 1
 
0.4%
138 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6066176
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:50.374674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.008201
Coefficient of variation (CV)0.43593828
Kurtosis-1.1478026
Mean4.6066176
Median Absolute Deviation (MAD)2
Skewness-0.052624328
Sum1253
Variance4.0328712
MonotonicityIncreasing
2023-12-12T09:34:50.688835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 56
20.6%
2 50
18.4%
7 42
15.4%
6 37
13.6%
3 33
12.1%
4 26
9.6%
8 18
 
6.6%
1 10
 
3.7%
ValueCountFrequency (%)
1 10
 
3.7%
2 50
18.4%
3 33
12.1%
4 26
9.6%
5 56
20.6%
6 37
13.6%
7 42
15.4%
8 18
 
6.6%
ValueCountFrequency (%)
8 18
 
6.6%
7 42
15.4%
6 37
13.6%
5 56
20.6%
4 26
9.6%
3 33
12.1%
2 50
18.4%
1 10
 
3.7%

역번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1615.6654
Minimum150
Maximum2828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:50.787318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile204.55
Q1316.75
median2527.5
Q32640.25
95-th percentile2814.45
Maximum2828
Range2678
Interquartile range (IQR)2323.5

Descriptive statistics

Standard deviation1174.9919
Coefficient of variation (CV)0.7272495
Kurtosis-1.9259226
Mean1615.6654
Median Absolute Deviation (MAD)284
Skewness-0.24809565
Sum439461
Variance1380605.9
MonotonicityStrictly increasing
2023-12-12T09:34:50.891225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150 1
 
0.4%
2617 1
 
0.4%
2623 1
 
0.4%
2622 1
 
0.4%
2621 1
 
0.4%
2620 1
 
0.4%
2619 1
 
0.4%
2618 1
 
0.4%
2616 1
 
0.4%
2529 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
150 1
0.4%
151 1
0.4%
152 1
0.4%
153 1
0.4%
154 1
0.4%
155 1
0.4%
156 1
0.4%
157 1
0.4%
158 1
0.4%
159 1
0.4%
ValueCountFrequency (%)
2828 1
0.4%
2827 1
0.4%
2826 1
0.4%
2825 1
0.4%
2824 1
0.4%
2823 1
0.4%
2822 1
0.4%
2821 1
0.4%
2820 1
0.4%
2819 1
0.4%

역명
Text

UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T09:34:51.181268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.8529412
Min length2

Characters and Unicode

Total characters1048
Distinct characters214
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique272 ?
Unique (%)100.0%

Sample

1st row서울역(1)
2nd row시청(1)
3rd row종각
4th row종로3가(1)
5th row종로5가
ValueCountFrequency (%)
서울역(1 1
 
0.4%
독바위 1
 
0.4%
하남시청 1
 
0.4%
하남검단산 1
 
0.4%
응암 1
 
0.4%
역촌 1
 
0.4%
불광(6 1
 
0.4%
시청(1 1
 
0.4%
새절 1
 
0.4%
청량리 1
 
0.4%
Other values (262) 262
96.3%
2023-12-12T09:34:51.577368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 84
 
8.0%
) 84
 
8.0%
대 32
 
3.1%
구 28
 
2.7%
동 22
 
2.1%
신 22
 
2.1%
산 19
 
1.8%
5 18
 
1.7%
2 16
 
1.5%
문 15
 
1.4%
Other values (204) 708
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 789
75.3%
Decimal Number 91
 
8.7%
Open Punctuation 84
 
8.0%
Close Punctuation 84
 
8.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 32
 
4.1%
구 28
 
3.5%
동 22
 
2.8%
신 22
 
2.8%
산 19
 
2.4%
문 15
 
1.9%
지 15
 
1.9%
로 14
 
1.8%
입 14
 
1.8%
원 14
 
1.8%
Other values (194) 594
75.3%
Decimal Number
ValueCountFrequency (%)
5 18
19.8%
2 16
17.6%
3 14
15.4%
6 11
12.1%
7 11
12.1%
4 9
9.9%
1 6
 
6.6%
8 6
 
6.6%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
75.3%
Common 259
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 32
 
4.1%
구 28
 
3.5%
동 22
 
2.8%
신 22
 
2.8%
산 19
 
2.4%
문 15
 
1.9%
지 15
 
1.9%
로 14
 
1.8%
입 14
 
1.8%
원 14
 
1.8%
Other values (194) 594
75.3%
Common
ValueCountFrequency (%)
( 84
32.4%
) 84
32.4%
5 18
 
6.9%
2 16
 
6.2%
3 14
 
5.4%
6 11
 
4.2%
7 11
 
4.2%
4 9
 
3.5%
1 6
 
2.3%
8 6
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
75.3%
ASCII 259
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 84
32.4%
) 84
32.4%
5 18
 
6.9%
2 16
 
6.2%
3 14
 
5.4%
6 11
 
4.2%
7 11
 
4.2%
4 9
 
3.5%
1 6
 
2.3%
8 6
 
2.3%
Hangul
ValueCountFrequency (%)
대 32
 
4.1%
구 28
 
3.5%
동 22
 
2.8%
신 22
 
2.8%
산 19
 
2.4%
문 15
 
1.9%
지 15
 
1.9%
로 14
 
1.8%
입 14
 
1.8%
원 14
 
1.8%
Other values (194) 594
75.3%

직원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.393382
Minimum0
Maximum25
Zeros7
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:51.678847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q110
median12
Q314
95-th percentile18.45
Maximum25
Range25
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.729264
Coefficient of variation (CV)0.30090768
Kurtosis2.7911915
Mean12.393382
Median Absolute Deviation (MAD)2
Skewness-0.077940894
Sum3371
Variance13.90741
MonotonicityNot monotonic
2023-12-12T09:34:51.766235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
10 66
24.3%
13 48
17.6%
14 25
 
9.2%
11 23
 
8.5%
9 21
 
7.7%
16 17
 
6.2%
15 16
 
5.9%
12 16
 
5.9%
17 9
 
3.3%
0 7
 
2.6%
Other values (9) 24
 
8.8%
ValueCountFrequency (%)
0 7
 
2.6%
8 4
 
1.5%
9 21
 
7.7%
10 66
24.3%
11 23
 
8.5%
12 16
 
5.9%
13 48
17.6%
14 25
 
9.2%
15 16
 
5.9%
16 17
 
6.2%
ValueCountFrequency (%)
25 1
 
0.4%
24 1
 
0.4%
23 2
 
0.7%
22 2
 
0.7%
21 3
 
1.1%
20 1
 
0.4%
19 4
 
1.5%
18 6
 
2.2%
17 9
3.3%
16 17
6.2%

수송인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7918056.3
Minimum669461
Maximum36184549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:51.864609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum669461
5-th percentile1731406.9
Q13985068.2
median6462403.5
Q39776761.8
95-th percentile20332837
Maximum36184549
Range35515088
Interquartile range (IQR)5791693.5

Descriptive statistics

Standard deviation6041102.6
Coefficient of variation (CV)0.76295272
Kurtosis4.4382625
Mean7918056.3
Median Absolute Deviation (MAD)2753342
Skewness1.8839011
Sum2.1537113 × 109
Variance3.649492 × 1013
MonotonicityNot monotonic
2023-12-12T09:34:51.980705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26147934 1
 
0.4%
6492776 1
 
0.4%
5950511 1
 
0.4%
7790745 1
 
0.4%
7001749 1
 
0.4%
2971823 1
 
0.4%
7232219 1
 
0.4%
5245476 1
 
0.4%
3679235 1
 
0.4%
7226231 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
669461 1
0.4%
705465 1
0.4%
707705 1
0.4%
949171 1
0.4%
1033089 1
0.4%
1065634 1
0.4%
1139361 1
0.4%
1268406 1
0.4%
1323311 1
0.4%
1357138 1
0.4%
ValueCountFrequency (%)
36184549 1
0.4%
34209780 1
0.4%
33488236 1
0.4%
28109759 1
0.4%
27262648 1
0.4%
26147934 1
0.4%
24498111 1
0.4%
24367213 1
0.4%
24183085 1
0.4%
23691521 1
0.4%

운수수입
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.914783 × 109
Minimum3.8038068 × 108
Maximum2.7481205 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T09:34:52.104954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.8038068 × 108
5-th percentile1.0615402 × 109
Q12.3128102 × 109
median3.9254965 × 109
Q35.8230576 × 109
95-th percentile1.3304541 × 1010
Maximum2.7481205 × 1010
Range2.7100825 × 1010
Interquartile range (IQR)3.5102474 × 109

Descriptive statistics

Standard deviation4.0803786 × 109
Coefficient of variation (CV)0.83022558
Kurtosis6.9320962
Mean4.914783 × 109
Median Absolute Deviation (MAD)1.728287 × 109
Skewness2.2808703
Sum1.336821 × 1012
Variance1.6649489 × 1019
MonotonicityNot monotonic
2023-12-12T09:34:52.218518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15927243582 1
 
0.4%
3349927405 1
 
0.4%
4428010776 1
 
0.4%
4456146331 1
 
0.4%
4272881498 1
 
0.4%
1352838588 1
 
0.4%
3811517829 1
 
0.4%
2880898637 1
 
0.4%
2259195960 1
 
0.4%
4418945658 1
 
0.4%
Other values (262) 262
96.3%
ValueCountFrequency (%)
380380680 1
0.4%
401515910 1
0.4%
413668919 1
0.4%
468338892 1
0.4%
581406995 1
0.4%
604125558 1
0.4%
711998838 1
0.4%
765376031 1
0.4%
792845652 1
0.4%
936198836 1
0.4%
ValueCountFrequency (%)
27481205327 1
0.4%
24665863082 1
0.4%
22622478425 1
0.4%
18401107571 1
0.4%
17950178469 1
0.4%
17406845872 1
0.4%
16802404107 1
0.4%
16156923598 1
0.4%
15927243582 1
0.4%
15766554313 1
0.4%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
264 
통합환승역
 
8

Length

Max length5
Median length4
Mean length4.0294118
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 264
97.1%
통합환승역 8
 
2.9%

Length

2023-12-12T09:34:52.319809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:34:52.394338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 264
97.1%
통합환승역 8
 
2.9%

Interactions

2023-12-12T09:34:49.508283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.450676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.836754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.254060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.638544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.070884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.575446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.510585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.903385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.319007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.703112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.148430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.644502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.580479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.976101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.386022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.774906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.221983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.704453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.642056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.044447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.443532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.844435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.297251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.770519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.704297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.111133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.504179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.908607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.364239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.858389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:47.774150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.187671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.573819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:48.986426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:34:49.439788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:34:52.444799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호직원수수송인원운수수입
연번1.0000.9180.9160.4320.4220.417
호선0.9181.0000.9940.6320.4010.368
역번호0.9160.9941.0000.6300.3690.325
직원수0.4320.6320.6301.0000.6770.669
수송인원0.4220.4010.3690.6771.0000.961
운수수입0.4170.3680.3250.6690.9611.000
2023-12-12T09:34:52.528096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호직원수수송인원운수수입비고
연번1.0000.9881.000-0.533-0.361-0.3421.000
호선0.9881.0000.988-0.526-0.334-0.3121.000
역번호1.0000.9881.000-0.533-0.361-0.3421.000
직원수-0.533-0.526-0.5331.0000.6210.6051.000
수송인원-0.361-0.334-0.3610.6211.0000.9811.000
운수수입-0.342-0.312-0.3420.6050.9811.0001.000
비고1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T09:34:49.959900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:34:50.054245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번호선역번호역명직원수수송인원운수수입비고
011150서울역(1)222614793415927243582<NA>
121151시청(1)16134170437774169453<NA>
231152종각162063794311798053057<NA>
341153종로3가(1)20135323036281939386<NA>
451154종로5가16136022945543430536<NA>
561155동대문(1)1562242882914335075<NA>
671156신설동(1)1772881373505996122<NA>
781157제기동15101066793084662385<NA>
891158청량리21116599633988614651<NA>
9101159동묘앞(1)1954248311744747941<NA>
연번호선역번호역명직원수수송인원운수수입비고
26226382819문정10112558697059110124<NA>
26326482820장지1091717695305520797<NA>
26426582821복정(8)1151628422657913479통합환승역
26526682822산성1028342991684784296<NA>
26626782823남한산성입구1072387874217169675<NA>
26726882824단대오거리956012893243188905<NA>
26826982825신흥1023460441310608599<NA>
26927082826수진826692741598827339<NA>
27027182827모란(8)1218429031064418380<NA>
27127282828남위례1127984141694702043<NA>