Overview

Dataset statistics

Number of variables7
Number of observations277
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory62.5 B

Variable types

Numeric6
Text1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-21720/F/1/datasetView.do

Alerts

연번 is highly overall correlated with 호선 and 1 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
역번호 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
경로 is highly overall correlated with 장애 and 1 other fieldsHigh correlation
장애 is highly overall correlated with 경로 and 1 other fieldsHigh correlation
유공자 is highly overall correlated with 경로 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
역번호 has unique valuesUnique
경로 has unique valuesUnique

Reproduction

Analysis started2024-04-29 21:10:03.513896
Analysis finished2024-04-29 21:10:06.852248
Duration3.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139
Minimum1
Maximum277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:06.913963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.8
Q170
median139
Q3208
95-th percentile263.2
Maximum277
Range276
Interquartile range (IQR)138

Descriptive statistics

Standard deviation80.10722
Coefficient of variation (CV)0.57631093
Kurtosis-1.2
Mean139
Median Absolute Deviation (MAD)69
Skewness0
Sum38503
Variance6417.1667
MonotonicityStrictly increasing
2024-04-30T06:10:07.027654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
183 1
 
0.4%
175 1
 
0.4%
Other values (267) 267
96.4%
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 (%)
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.66787
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:07.131598image/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 deviation2.0247061
Coefficient of variation (CV)0.43375375
Kurtosis-1.1986103
Mean4.66787
Median Absolute Deviation (MAD)2
Skewness-0.10486387
Sum1293
Variance4.0994349
MonotonicityIncreasing
2024-04-30T06:10:07.233682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 53
19.1%
7 51
18.4%
2 50
18.1%
6 37
13.4%
3 33
11.9%
4 26
9.4%
8 17
 
6.1%
1 10
 
3.6%
ValueCountFrequency (%)
1 10
 
3.6%
2 50
18.1%
3 33
11.9%
4 26
9.4%
5 53
19.1%
6 37
13.4%
7 51
18.4%
8 17
 
6.1%
ValueCountFrequency (%)
8 17
 
6.1%
7 51
18.4%
6 37
13.4%
5 53
19.1%
4 26
9.4%
3 33
11.9%
2 50
18.1%
1 10
 
3.6%

역번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638.0975
Minimum150
Maximum2827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:07.345132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile204.8
Q1318
median2530
Q32647
95-th percentile2813.2
Maximum2827
Range2677
Interquartile range (IQR)2329

Descriptive statistics

Standard deviation1175.7807
Coefficient of variation (CV)0.7177721
Kurtosis-1.9085471
Mean1638.0975
Median Absolute Deviation (MAD)229
Skewness-0.28044538
Sum453753
Variance1382460.2
MonotonicityStrictly increasing
2024-04-30T06:10:07.471595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150 1
 
0.4%
2623 1
 
0.4%
2629 1
 
0.4%
2628 1
 
0.4%
2627 1
 
0.4%
2626 1
 
0.4%
2625 1
 
0.4%
2624 1
 
0.4%
2622 1
 
0.4%
2613 1
 
0.4%
Other values (267) 267
96.4%
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 (%)
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%
2818 1
0.4%

역명
Text

Distinct244
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-30T06:10:07.683078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.9386282
Min length2

Characters and Unicode

Total characters814
Distinct characters210
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)76.9%

Sample

1st row서울역
2nd row시청
3rd row종각
4th row종로3가
5th row종로5가
ValueCountFrequency (%)
종로3가 3
 
1.1%
동대문역사문화공원 3
 
1.1%
공덕 2
 
0.7%
사당 2
 
0.7%
서울역 2
 
0.7%
영등포구청 2
 
0.7%
대림 2
 
0.7%
불광 2
 
0.7%
약수 2
 
0.7%
오금 2
 
0.7%
Other values (234) 255
92.1%
2024-04-30T06:10:08.018782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 32
 
3.9%
구 29
 
3.6%
동 25
 
3.1%
신 23
 
2.8%
산 19
 
2.3%
지 15
 
1.8%
청 15
 
1.8%
문 15
 
1.8%
원 14
 
1.7%
입 14
 
1.7%
Other values (200) 613
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 806
99.0%
Decimal Number 8
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 32
 
4.0%
구 29
 
3.6%
동 25
 
3.1%
신 23
 
2.9%
산 19
 
2.4%
지 15
 
1.9%
청 15
 
1.9%
문 15
 
1.9%
원 14
 
1.7%
입 14
 
1.7%
Other values (197) 605
75.1%
Decimal Number
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 806
99.0%
Common 8
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 32
 
4.0%
구 29
 
3.6%
동 25
 
3.1%
신 23
 
2.9%
산 19
 
2.4%
지 15
 
1.9%
청 15
 
1.9%
문 15
 
1.9%
원 14
 
1.7%
입 14
 
1.7%
Other values (197) 605
75.1%
Common
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 806
99.0%
ASCII 8
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 32
 
4.0%
구 29
 
3.6%
동 25
 
3.1%
신 23
 
2.9%
산 19
 
2.4%
지 15
 
1.9%
청 15
 
1.9%
문 15
 
1.9%
원 14
 
1.7%
입 14
 
1.7%
Other values (197) 605
75.1%
ASCII
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

경로
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean577810.46
Minimum53396
Maximum2554908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:08.133302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53396
5-th percentile133383.8
Q1312152
median479804
Q3712902
95-th percentile1373997.2
Maximum2554908
Range2501512
Interquartile range (IQR)400750

Descriptive statistics

Standard deviation411310.15
Coefficient of variation (CV)0.71184268
Kurtosis5.0874206
Mean577810.46
Median Absolute Deviation (MAD)192276
Skewness1.9187913
Sum1.600535 × 108
Variance1.6917604 × 1011
MonotonicityNot monotonic
2024-04-30T06:10:08.263011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1391862 1
 
0.4%
288738 1
 
0.4%
117741 1
 
0.4%
307429 1
 
0.4%
580354 1
 
0.4%
347906 1
 
0.4%
366647 1
 
0.4%
170527 1
 
0.4%
661533 1
 
0.4%
324281 1
 
0.4%
Other values (267) 267
96.4%
ValueCountFrequency (%)
53396 1
0.4%
68596 1
0.4%
68843 1
0.4%
73809 1
0.4%
75087 1
0.4%
79204 1
0.4%
84989 1
0.4%
98360 1
0.4%
110331 1
0.4%
116090 1
0.4%
ValueCountFrequency (%)
2554908 1
0.4%
2419969 1
0.4%
2395667 1
0.4%
2183302 1
0.4%
2103893 1
0.4%
1758463 1
0.4%
1692153 1
0.4%
1540968 1
0.4%
1517381 1
0.4%
1472638 1
0.4%

장애
Real number (ℝ)

HIGH CORRELATION 

Distinct276
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120793.84
Minimum10974
Maximum434534
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:08.401143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10974
5-th percentile28320.2
Q165410
median99777
Q3155429
95-th percentile302903.4
Maximum434534
Range423560
Interquartile range (IQR)90019

Descriptive statistics

Standard deviation82820.67
Coefficient of variation (CV)0.68563653
Kurtosis2.1981431
Mean120793.84
Median Absolute Deviation (MAD)39317
Skewness1.4428554
Sum33459894
Variance6.8592633 × 109
MonotonicityNot monotonic
2024-04-30T06:10:08.513470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101136 2
 
0.7%
422653 1
 
0.4%
68147 1
 
0.4%
29508 1
 
0.4%
63851 1
 
0.4%
113608 1
 
0.4%
63224 1
 
0.4%
56161 1
 
0.4%
28113 1
 
0.4%
124025 1
 
0.4%
Other values (266) 266
96.0%
ValueCountFrequency (%)
10974 1
0.4%
12170 1
0.4%
14720 1
0.4%
15999 1
0.4%
16589 1
0.4%
17293 1
0.4%
17448 1
0.4%
17986 1
0.4%
22601 1
0.4%
24354 1
0.4%
ValueCountFrequency (%)
434534 1
0.4%
422653 1
0.4%
420447 1
0.4%
398776 1
0.4%
396489 1
0.4%
367591 1
0.4%
352770 1
0.4%
335899 1
0.4%
321039 1
0.4%
320507 1
0.4%

유공자
Real number (ℝ)

HIGH CORRELATION 

Distinct275
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7858.2491
Minimum330
Maximum37296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-04-30T06:10:08.818797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330
5-th percentile1516.2
Q13687
median6263
Q310044
95-th percentile21334.8
Maximum37296
Range36966
Interquartile range (IQR)6357

Descriptive statistics

Standard deviation5977.6394
Coefficient of variation (CV)0.76068337
Kurtosis3.8943776
Mean7858.2491
Median Absolute Deviation (MAD)3082
Skewness1.7614692
Sum2176735
Variance35732173
MonotonicityNot monotonic
2024-04-30T06:10:08.944697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2274 2
 
0.7%
3941 2
 
0.7%
29653 1
 
0.4%
2575 1
 
0.4%
1493 1
 
0.4%
5500 1
 
0.4%
3596 1
 
0.4%
8890 1
 
0.4%
5260 1
 
0.4%
5421 1
 
0.4%
Other values (265) 265
95.7%
ValueCountFrequency (%)
330 1
0.4%
501 1
0.4%
918 1
0.4%
939 1
0.4%
953 1
0.4%
959 1
0.4%
1123 1
0.4%
1136 1
0.4%
1171 1
0.4%
1396 1
0.4%
ValueCountFrequency (%)
37296 1
0.4%
32211 1
0.4%
29653 1
0.4%
27650 1
0.4%
25864 1
0.4%
25573 1
0.4%
24163 1
0.4%
23890 1
0.4%
23502 1
0.4%
23430 1
0.4%

Interactions

2024-04-30T06:10:06.198035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:03.787224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.398201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.900074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.336591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.756557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.272873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:03.857139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.480486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.969847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.407739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.835773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.350506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:03.927072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.567600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.053248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.480758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.917752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.420558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:03.988253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.640901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.129265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.550268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.989530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.504052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.054477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.721274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.200599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.615427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.063914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.591871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.313938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:04.813561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.261969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:05.678327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T06:10:06.129078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T06:10:09.027227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호경로장애유공자
연번1.0000.9200.9240.3860.4900.554
호선0.9201.0000.9950.4970.4660.470
역번호0.9240.9951.0000.3590.3900.411
경로0.3860.4970.3591.0000.8270.808
장애0.4900.4660.3900.8271.0000.877
유공자0.5540.4700.4110.8080.8771.000
2024-04-30T06:10:09.126090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호경로장애유공자
연번1.0000.9881.000-0.377-0.332-0.380
호선0.9881.0000.988-0.347-0.298-0.351
역번호1.0000.9881.000-0.377-0.332-0.380
경로-0.377-0.347-0.3771.0000.9410.905
장애-0.332-0.298-0.3320.9411.0000.900
유공자-0.380-0.351-0.3800.9050.9001.000

Missing values

2024-04-30T06:10:06.718550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T06:10:06.816255image/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

연번호선역번호역명경로장애유공자
011150서울역139186242265329653
121151시청59297414588911317
231152종각106229725312518286
341153종로3가255490843453437296
451154종로5가218330231862123890
561155동대문99436421092110462
671156신설동95736619278811000
781157제기동241996932103918679
891158청량리239566739648925864
9101159동묘앞122585224692915832
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26726882818가락시장513081816456311
26826982819문정431388997776904
26927082820장지5431851354379700
27027182821복정332606759025628
27127282822산성285000604603115
27227382823남한산성입구6002181364117592
27327482824단대오거리5055201313653339
27427582825신흥310474775683021
27527682826수진335197804892758
27627782827모란415945858134157