Overview

Dataset statistics

Number of variables8
Number of observations584
Missing cells354
Missing cells (%)7.6%
Duplicate rows19
Duplicate rows (%)3.3%
Total size in memory37.2 KiB
Average record size in memory65.2 B

Variable types

Categorical5
Text2
Numeric1

Dataset

Description대구교통공사에서 관리하는 도시광역철도역들의 철도운영기관명, 선명, 역명, 상하행구분, 출입구번호, 상세위치, 시작층, 종료층의 데이터가 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041357/fileData.do

Alerts

철도운영기관 has constant value ""Constant
Dataset has 19 (3.3%) duplicate rowsDuplicates
선명 is highly overall correlated with 시작층 and 1 other fieldsHigh correlation
시작층 is highly overall correlated with 선명 and 1 other fieldsHigh correlation
종료층 is highly overall correlated with 선명 and 1 other fieldsHigh correlation
출입구번호 has 354 (60.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:35:47.308734
Analysis finished2023-12-12 05:35:48.207615
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
대구교통공사
584 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구교통공사
2nd row대구교통공사
3rd row대구교통공사
4th row대구교통공사
5th row대구교통공사

Common Values

ValueCountFrequency (%)
대구교통공사 584
100.0%

Length

2023-12-12T14:35:48.582147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:48.711843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구교통공사 584
100.0%

선명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2호선
241 
3호선
172 
1호선
171 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1호선
2nd row1호선
3rd row1호선
4th row1호선
5th row1호선

Common Values

ValueCountFrequency (%)
2호선 241
41.3%
3호선 172
29.5%
1호선 171
29.3%

Length

2023-12-12T14:35:48.837830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:48.976320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 241
41.3%
3호선 172
29.5%
1호선 171
29.3%

역명
Text

Distinct83
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T14:35:49.242144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length3.7208904
Min length2

Characters and Unicode

Total characters2173
Distinct characters129
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row반월당
2nd row반월당
3rd row반월당
4th row반월당
5th row반월당
ValueCountFrequency (%)
대구역 18
 
3.1%
청라언덕 18
 
3.1%
동대구역 17
 
2.9%
반월당 16
 
2.7%
설화명곡 16
 
2.7%
명덕(2.28민주운동기념회관 16
 
2.7%
대공원 14
 
2.4%
교대 12
 
2.1%
죽전 12
 
2.1%
계명대 12
 
2.1%
Other values (73) 433
74.1%
2023-12-12T14:35:49.717063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 143
 
6.6%
구 81
 
3.7%
원 64
 
2.9%
( 60
 
2.8%
) 60
 
2.8%
동 57
 
2.6%
산 51
 
2.3%
청 48
 
2.2%
명 46
 
2.1%
성 41
 
1.9%
Other values (119) 1522
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1921
88.4%
Open Punctuation 60
 
2.8%
Close Punctuation 60
 
2.8%
Decimal Number 48
 
2.2%
Uppercase Letter 48
 
2.2%
Other Punctuation 36
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 143
 
7.4%
구 81
 
4.2%
원 64
 
3.3%
동 57
 
3.0%
산 51
 
2.7%
청 48
 
2.5%
명 46
 
2.4%
성 41
 
2.1%
곡 40
 
2.1%
역 35
 
1.8%
Other values (108) 1315
68.5%
Uppercase Letter
ValueCountFrequency (%)
B 16
33.3%
S 10
20.8%
K 10
20.8%
C 6
 
12.5%
T 6
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 32
66.7%
8 16
33.3%
Other Punctuation
ValueCountFrequency (%)
· 20
55.6%
. 16
44.4%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1921
88.4%
Common 204
 
9.4%
Latin 48
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 143
 
7.4%
구 81
 
4.2%
원 64
 
3.3%
동 57
 
3.0%
산 51
 
2.7%
청 48
 
2.5%
명 46
 
2.4%
성 41
 
2.1%
곡 40
 
2.1%
역 35
 
1.8%
Other values (108) 1315
68.5%
Common
ValueCountFrequency (%)
( 60
29.4%
) 60
29.4%
2 32
15.7%
· 20
 
9.8%
. 16
 
7.8%
8 16
 
7.8%
Latin
ValueCountFrequency (%)
B 16
33.3%
S 10
20.8%
K 10
20.8%
C 6
 
12.5%
T 6
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1921
88.4%
ASCII 232
 
10.7%
None 20
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 143
 
7.4%
구 81
 
4.2%
원 64
 
3.3%
동 57
 
3.0%
산 51
 
2.7%
청 48
 
2.5%
명 46
 
2.4%
성 41
 
2.1%
곡 40
 
2.1%
역 35
 
1.8%
Other values (108) 1315
68.5%
ASCII
ValueCountFrequency (%)
( 60
25.9%
) 60
25.9%
2 32
13.8%
B 16
 
6.9%
. 16
 
6.9%
8 16
 
6.9%
S 10
 
4.3%
K 10
 
4.3%
C 6
 
2.6%
T 6
 
2.6%
None
ValueCountFrequency (%)
· 20
100.0%

상하행구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
상행
389 
하행
195 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row하행
2nd row상행
3rd row상행
4th row상행
5th row상행

Common Values

ValueCountFrequency (%)
상행 389
66.6%
하행 195
33.4%

Length

2023-12-12T14:35:49.906978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:50.046748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상행 389
66.6%
하행 195
33.4%

출입구번호
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)3.9%
Missing354
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean2.7869565
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2023-12-12T14:35:50.175096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile6
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6932448
Coefficient of variation (CV)0.60756055
Kurtosis1.290116
Mean2.7869565
Median Absolute Deviation (MAD)1
Skewness1.0733186
Sum641
Variance2.867078
MonotonicityNot monotonic
2023-12-12T14:35:50.382321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 67
 
11.5%
4 48
 
8.2%
3 47
 
8.0%
2 44
 
7.5%
6 9
 
1.5%
5 6
 
1.0%
7 5
 
0.9%
8 2
 
0.3%
9 2
 
0.3%
(Missing) 354
60.6%
ValueCountFrequency (%)
1 67
11.5%
2 44
7.5%
3 47
8.0%
4 48
8.2%
5 6
 
1.0%
6 9
 
1.5%
7 5
 
0.9%
8 2
 
0.3%
9 2
 
0.3%
ValueCountFrequency (%)
9 2
 
0.3%
8 2
 
0.3%
7 5
 
0.9%
6 9
 
1.5%
5 6
 
1.0%
4 48
8.2%
3 47
8.0%
2 44
7.5%
1 67
11.5%

상세위치
Text

Distinct455
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2023-12-12T14:35:50.764232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length28
Mean length18.481164
Min length7

Characters and Unicode

Total characters10793
Distinct characters267
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)67.3%

Sample

1st row(B1F) 메트로환경 대기실 옆
2nd row(B2F) 고객안내센터 옆
3rd row(B3F) 상선 승강장(3-4F)
4th row(B3F) 상선 승강장(6-2F)
5th row(B3F) 하선 승강장6-1F)
ValueCountFrequency (%)
방향 247
 
9.0%
출입구 242
 
8.8%
앞 176
 
6.4%
출입문 125
 
4.5%
옆 118
 
4.3%
b1f 104
 
3.8%
1f 93
 
3.4%
b3f 93
 
3.4%
승강장 91
 
3.3%
b2f 67
 
2.4%
Other values (379) 1393
50.7%
2023-12-12T14:35:51.411024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2188
20.3%
) 589
 
5.5%
( 588
 
5.4%
F 587
 
5.4%
출 416
 
3.9%
1 407
 
3.8%
입 393
 
3.6%
B 340
 
3.2%
구 315
 
2.9%
방 313
 
2.9%
Other values (257) 4657
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5030
46.6%
Space Separator 2188
20.3%
Decimal Number 1215
 
11.3%
Uppercase Letter 985
 
9.1%
Close Punctuation 589
 
5.5%
Open Punctuation 588
 
5.4%
Dash Punctuation 157
 
1.5%
Other Punctuation 32
 
0.3%
Lowercase Letter 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
출 416
 
8.3%
입 393
 
7.8%
구 315
 
6.3%
방 313
 
6.2%
번 290
 
5.8%
향 274
 
5.4%
앞 189
 
3.8%
문 149
 
3.0%
역 147
 
2.9%
장 140
 
2.8%
Other values (225) 2404
47.8%
Uppercase Letter
ValueCountFrequency (%)
F 587
59.6%
B 340
34.5%
M 20
 
2.0%
E 12
 
1.2%
L 11
 
1.1%
S 3
 
0.3%
P 3
 
0.3%
D 2
 
0.2%
G 1
 
0.1%
A 1
 
0.1%
Other values (5) 5
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 407
33.5%
2 289
23.8%
3 279
23.0%
4 133
 
10.9%
6 63
 
5.2%
5 31
 
2.6%
7 9
 
0.7%
9 2
 
0.2%
8 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 24
75.0%
" 8
 
25.0%
Space Separator
ValueCountFrequency (%)
2188
100.0%
Close Punctuation
ValueCountFrequency (%)
) 589
100.0%
Open Punctuation
ValueCountFrequency (%)
( 588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 157
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 8
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5030
46.6%
Common 4770
44.2%
Latin 993
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
출 416
 
8.3%
입 393
 
7.8%
구 315
 
6.3%
방 313
 
6.2%
번 290
 
5.8%
향 274
 
5.4%
앞 189
 
3.8%
문 149
 
3.0%
역 147
 
2.9%
장 140
 
2.8%
Other values (225) 2404
47.8%
Common
ValueCountFrequency (%)
2188
45.9%
) 589
 
12.3%
( 588
 
12.3%
1 407
 
8.5%
2 289
 
6.1%
3 279
 
5.8%
- 157
 
3.3%
4 133
 
2.8%
6 63
 
1.3%
5 31
 
0.6%
Other values (6) 46
 
1.0%
Latin
ValueCountFrequency (%)
F 587
59.1%
B 340
34.2%
M 20
 
2.0%
E 12
 
1.2%
L 11
 
1.1%
m 8
 
0.8%
S 3
 
0.3%
P 3
 
0.3%
D 2
 
0.2%
G 1
 
0.1%
Other values (6) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5763
53.4%
Hangul 5030
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2188
38.0%
) 589
 
10.2%
( 588
 
10.2%
F 587
 
10.2%
1 407
 
7.1%
B 340
 
5.9%
2 289
 
5.0%
3 279
 
4.8%
- 157
 
2.7%
4 133
 
2.3%
Other values (22) 206
 
3.6%
Hangul
ValueCountFrequency (%)
출 416
 
8.3%
입 393
 
7.8%
구 315
 
6.3%
방 313
 
6.2%
번 290
 
5.8%
향 274
 
5.4%
앞 189
 
3.8%
문 149
 
3.0%
역 147
 
2.9%
장 140
 
2.8%
Other values (225) 2404
47.8%

시작층
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
지하1
139 
지상1
126 
지하3
99 
지상2
81 
지하2
73 
Other values (4)
66 

Length

Max length3
Median length3
Mean length2.9982877
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row지하1
2nd row지하2
3rd row지하3
4th row지하3
5th row지하3

Common Values

ValueCountFrequency (%)
지하1 139
23.8%
지상1 126
21.6%
지하3 99
17.0%
지상2 81
13.9%
지하2 73
12.5%
지상3 39
 
6.7%
지하4 22
 
3.8%
지하5 4
 
0.7%
지상 1
 
0.2%

Length

2023-12-12T14:35:51.576289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:51.740794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하1 139
23.8%
지상1 126
21.6%
지하3 99
17.0%
지상2 81
13.9%
지하2 73
12.5%
지상3 39
 
6.7%
지하4 22
 
3.8%
지하5 4
 
0.7%
지상 1
 
0.2%

종료층
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
지하1
160 
지상1
124 
지하2
93 
지상2
82 
지하3
59 
Other values (4)
66 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지하2
2nd row지하1
3rd row지하2
4th row지하2
5th row지하2

Common Values

ValueCountFrequency (%)
지하1 160
27.4%
지상1 124
21.2%
지하2 93
15.9%
지상2 82
14.0%
지하3 59
 
10.1%
지상3 58
 
9.9%
지하5 4
 
0.7%
지상4 2
 
0.3%
지하4 2
 
0.3%

Length

2023-12-12T14:35:51.909403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:52.046093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하1 160
27.4%
지상1 124
21.2%
지하2 93
15.9%
지상2 82
14.0%
지하3 59
 
10.1%
지상3 58
 
9.9%
지하5 4
 
0.7%
지상4 2
 
0.3%
지하4 2
 
0.3%

Interactions

2023-12-12T14:35:47.871591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:35:52.179810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선명역명상하행구분출입구번호시작층종료층
선명1.0000.9950.0240.4830.8660.881
역명0.9951.0000.0000.8160.7180.786
상하행구분0.0240.0001.0000.0000.4960.396
출입구번호0.4830.8160.0001.0000.0000.000
시작층0.8660.7180.4960.0001.0000.920
종료층0.8810.7860.3960.0000.9201.000
2023-12-12T14:35:52.324161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종료층시작층상하행구분선명
종료층1.0000.5530.3940.605
시작층0.5531.0000.4940.583
상하행구분0.3940.4941.0000.040
선명0.6050.5830.0401.000
2023-12-12T14:35:52.450920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출입구번호선명상하행구분시작층종료층
출입구번호1.0000.2400.0000.0000.000
선명0.2401.0000.0400.5830.605
상하행구분0.0000.0401.0000.4940.394
시작층0.0000.5830.4941.0000.553
종료층0.0000.6050.3940.5531.000

Missing values

2023-12-12T14:35:48.021398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:35:48.150796image/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

철도운영기관선명역명상하행구분출입구번호상세위치시작층종료층
0대구교통공사1호선반월당하행<NA>(B1F) 메트로환경 대기실 옆지하1지하2
1대구교통공사1호선반월당상행<NA>(B2F) 고객안내센터 옆지하2지하1
2대구교통공사1호선반월당상행<NA>(B3F) 상선 승강장(3-4F)지하3지하2
3대구교통공사1호선반월당상행<NA>(B3F) 상선 승강장(6-2F)지하3지하2
4대구교통공사1호선반월당상행<NA>(B3F) 하선 승강장6-1F)지하3지하2
5대구교통공사1호선반월당상행<NA>(B3F) 하선 승강장(3-3F)지하3지하2
6대구교통공사1호선반월당하행1(1F) 1번출구지상1지하1
7대구교통공사1호선반월당상행1(B1F) 메트로환경 대기실 옆지하1지상1
8대구교통공사1호선방촌상행1(B1F) 1번 출입구지하1지상1
9대구교통공사1호선방촌하행1(1F) 1번 출입구지상1지하1
철도운영기관선명역명상하행구분출입구번호상세위치시작층종료층
574대구교통공사1호선명덕(2.28민주운동기념회관)상행<NA>(B2F) 교대역 방향 승강장 5-4 출입문 앞지하2지하1
575대구교통공사1호선명덕(2.28민주운동기념회관)상행<NA>(B2F) 반월당역 방향 승강장 6-1 출입문 앞지하2지하1
576대구교통공사1호선명덕(2.28민주운동기념회관)상행<NA>(B2F) 반월당역 방향 승강장 4-1 출입문 앞지하2지하1
577대구교통공사1호선명덕(2.28민주운동기념회관)상행1(B1F) 1번 출입구 방향지하1지상1
578대구교통공사1호선명덕(2.28민주운동기념회관)하행1(1F) 1번 출입구 앞지상1지하1
579대구교통공사1호선반야월상행4(B1F) 4번 출입구지하1지상1
580대구교통공사1호선반야월하행4(1F) 4번 출입구 타이어뱅크 앞지상1지하1
581대구교통공사1호선반야월상행2(B1F) 2번 출입구지하1지상1
582대구교통공사1호선반야월하행2(1F) 2번 출입구 한국자원 앞지상1지하1
583대구교통공사1호선칠성시장상행<NA>(B3F) 대구역 방향 승강장3-4 출입문 앞지하3지하2

Duplicate rows

Most frequently occurring

철도운영기관선명역명상하행구분출입구번호상세위치시작층종료층# duplicates
5대구교통공사1호선동대구역하행<NA>(B1F) 표내는곳 내 계단 옆지하1지하34
0대구교통공사1호선대구역하행<NA>(B1F) 12번 출입구 방향지하1지하22
1대구교통공사1호선대구역하행<NA>(B1F) 34번 출입구 방향지하1지하22
2대구교통공사1호선대구역하행<NA>(B2F) 설화명곡 방면 표 내는 곳 근처지하2지하32
3대구교통공사1호선대구역하행<NA>(B2F) 안심 방면 표 내는 곳 근처지하2지하32
4대구교통공사1호선동대구역상행3(1F) 3번 출구 신세계백화점 광장 중앙지상1지상32
6대구교통공사1호선설화명곡하행<NA>(B2F) 표 내는 곳 옆지하2지하32
7대구교통공사1호선화원하행<NA>(B2F) 대곡역 방향 대합실지하2지하32
8대구교통공사2호선경대병원상행<NA>(B2F) 알림마당 옆지하2지하12
9대구교통공사2호선계명대상행<NA>(B2F) 대합실 내 계단 옆지하2지하12