Overview

Dataset statistics

Number of variables6
Number of observations385
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory49.3 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description대구교통공사 에 포함된 도시광역철도역들의 철도운영기관명,선명,역명,출구번호,출구별 주요시설명, 주소 등의 데이터 입니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15068954/fileData.do

Alerts

철도운영기관명 has constant value ""Constant

Reproduction

Analysis started2023-12-12 13:54:59.106425
Analysis finished2023-12-12 13:54:59.732344
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
대구교통공사
385 

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 385
100.0%

Length

2023-12-12T22:54:59.805762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:55:00.193636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구교통공사 385
100.0%

선명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2호선
142 
1호선
129 
3호선
114 

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 142
36.9%
1호선 129
33.5%
3호선 114
29.6%

Length

2023-12-12T22:55:00.287353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:55:00.391181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2호선 142
36.9%
1호선 129
33.5%
3호선 114
29.6%

역명
Text

Distinct86
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T22:55:00.661516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length2
Mean length4.0025974
Min length2

Characters and Unicode

Total characters1541
Distinct characters135
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

Unique0 ?
Unique (%)0.0%

Sample

1st row대곡(정부대구청사)
2nd row대곡(정부대구청사)
3rd row대곡(정부대구청사)
4th row대곡(정부대구청사)
5th row진천
ValueCountFrequency (%)
반월당 11
 
2.9%
상인 8
 
2.1%
월촌 8
 
2.1%
신천(경북대입구 8
 
2.1%
성서산업단지 8
 
2.1%
명덕(2.28민주운동기념회관 8
 
2.1%
임당 8
 
2.1%
신매 7
 
1.8%
계명대 7
 
1.8%
청라언덕 7
 
1.8%
Other values (76) 305
79.2%
2023-12-12T22:55:01.176869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 82
 
5.3%
( 58
 
3.8%
) 58
 
3.8%
구 52
 
3.4%
산 40
 
2.6%
원 38
 
2.5%
청 35
 
2.3%
동 33
 
2.1%
성 32
 
2.1%
월 31
 
2.0%
Other values (125) 1082
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1351
87.7%
Open Punctuation 58
 
3.8%
Close Punctuation 58
 
3.8%
Other Punctuation 26
 
1.7%
Decimal Number 24
 
1.6%
Uppercase Letter 24
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 82
 
6.1%
구 52
 
3.8%
산 40
 
3.0%
원 38
 
2.8%
청 35
 
2.6%
동 33
 
2.4%
성 32
 
2.4%
월 31
 
2.3%
장 30
 
2.2%
시 27
 
2.0%
Other values (114) 951
70.4%
Uppercase Letter
ValueCountFrequency (%)
B 8
33.3%
K 4
16.7%
S 4
16.7%
C 4
16.7%
T 4
16.7%
Other Punctuation
ValueCountFrequency (%)
· 18
69.2%
. 8
30.8%
Decimal Number
ValueCountFrequency (%)
2 16
66.7%
8 8
33.3%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1351
87.7%
Common 166
 
10.8%
Latin 24
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 82
 
6.1%
구 52
 
3.8%
산 40
 
3.0%
원 38
 
2.8%
청 35
 
2.6%
동 33
 
2.4%
성 32
 
2.4%
월 31
 
2.3%
장 30
 
2.2%
시 27
 
2.0%
Other values (114) 951
70.4%
Common
ValueCountFrequency (%)
( 58
34.9%
) 58
34.9%
· 18
 
10.8%
2 16
 
9.6%
8 8
 
4.8%
. 8
 
4.8%
Latin
ValueCountFrequency (%)
B 8
33.3%
K 4
16.7%
S 4
16.7%
C 4
16.7%
T 4
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1351
87.7%
ASCII 172
 
11.2%
None 18
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 82
 
6.1%
구 52
 
3.8%
산 40
 
3.0%
원 38
 
2.8%
청 35
 
2.6%
동 33
 
2.4%
성 32
 
2.4%
월 31
 
2.3%
장 30
 
2.2%
시 27
 
2.0%
Other values (114) 951
70.4%
ASCII
ValueCountFrequency (%)
( 58
33.7%
) 58
33.7%
2 16
 
9.3%
B 8
 
4.7%
8 8
 
4.7%
. 8
 
4.7%
K 4
 
2.3%
S 4
 
2.3%
C 4
 
2.3%
T 4
 
2.3%
None
ValueCountFrequency (%)
· 18
100.0%

출구번호
Real number (ℝ)

Distinct16
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8987013
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T22:55:01.325251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile7
Maximum23
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6314649
Coefficient of variation (CV)0.90780824
Kurtosis22.301078
Mean2.8987013
Median Absolute Deviation (MAD)1
Skewness3.8316427
Sum1116
Variance6.9246077
MonotonicityNot monotonic
2023-12-12T22:55:01.442838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 133
34.5%
3 70
18.2%
2 69
17.9%
4 65
16.9%
5 16
 
4.2%
6 10
 
2.6%
7 7
 
1.8%
8 6
 
1.6%
12 2
 
0.5%
14 1
 
0.3%
Other values (6) 6
 
1.6%
ValueCountFrequency (%)
1 133
34.5%
2 69
17.9%
3 70
18.2%
4 65
16.9%
5 16
 
4.2%
6 10
 
2.6%
7 7
 
1.8%
8 6
 
1.6%
10 1
 
0.3%
11 1
 
0.3%
ValueCountFrequency (%)
23 1
 
0.3%
22 1
 
0.3%
21 1
 
0.3%
14 1
 
0.3%
13 1
 
0.3%
12 2
 
0.5%
11 1
 
0.3%
10 1
 
0.3%
8 6
1.6%
7 7
1.8%

출구별 주요시설명
Text

Distinct371
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T22:55:01.783900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.8597403
Min length2

Characters and Unicode

Total characters2641
Distinct characters259
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)92.7%

Sample

1st row대구교도소
2nd row정부대구지방합동청사
3rd row월배차량기지사업소
4th row화원읍사무소
5th row진천동 주민센터
ValueCountFrequency (%)
주민센터 4
 
1.0%
계명대학교 4
 
1.0%
대구은행 3
 
0.7%
대구강북고용센터 2
 
0.5%
연호동 2
 
0.5%
아파트 2
 
0.5%
대구병원 2
 
0.5%
홈플러스 2
 
0.5%
상인점 2
 
0.5%
동구청 2
 
0.5%
Other values (376) 390
94.0%
2023-12-12T22:55:02.304819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 139
 
5.3%
대 101
 
3.8%
터 92
 
3.5%
센 88
 
3.3%
구 87
 
3.3%
교 81
 
3.1%
학 80
 
3.0%
민 69
 
2.6%
주 65
 
2.5%
지 55
 
2.1%
Other values (249) 1784
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2506
94.9%
Decimal Number 77
 
2.9%
Space Separator 39
 
1.5%
Uppercase Letter 8
 
0.3%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 139
 
5.5%
대 101
 
4.0%
터 92
 
3.7%
센 88
 
3.5%
구 87
 
3.5%
교 81
 
3.2%
학 80
 
3.2%
민 69
 
2.8%
주 65
 
2.6%
지 55
 
2.2%
Other values (231) 1649
65.8%
Decimal Number
ValueCountFrequency (%)
1 33
42.9%
2 17
22.1%
3 10
 
13.0%
4 7
 
9.1%
9 6
 
7.8%
5 2
 
2.6%
0 1
 
1.3%
6 1
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
37.5%
K 2
25.0%
B 1
 
12.5%
M 1
 
12.5%
C 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
· 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2506
94.9%
Common 127
 
4.8%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 139
 
5.5%
대 101
 
4.0%
터 92
 
3.7%
센 88
 
3.5%
구 87
 
3.5%
교 81
 
3.2%
학 80
 
3.2%
민 69
 
2.8%
주 65
 
2.6%
지 55
 
2.2%
Other values (231) 1649
65.8%
Common
ValueCountFrequency (%)
39
30.7%
1 33
26.0%
2 17
13.4%
3 10
 
7.9%
4 7
 
5.5%
9 6
 
4.7%
( 4
 
3.1%
) 4
 
3.1%
· 2
 
1.6%
5 2
 
1.6%
Other values (3) 3
 
2.4%
Latin
ValueCountFrequency (%)
T 3
37.5%
K 2
25.0%
B 1
 
12.5%
M 1
 
12.5%
C 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2506
94.9%
ASCII 133
 
5.0%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 139
 
5.5%
대 101
 
4.0%
터 92
 
3.7%
센 88
 
3.5%
구 87
 
3.5%
교 81
 
3.2%
학 80
 
3.2%
민 69
 
2.8%
주 65
 
2.6%
지 55
 
2.2%
Other values (231) 1649
65.8%
ASCII
ValueCountFrequency (%)
39
29.3%
1 33
24.8%
2 17
12.8%
3 10
 
7.5%
4 7
 
5.3%
9 6
 
4.5%
( 4
 
3.0%
) 4
 
3.0%
T 3
 
2.3%
K 2
 
1.5%
Other values (7) 8
 
6.0%
None
ValueCountFrequency (%)
· 2
100.0%

주소
Text

Distinct352
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T22:55:02.720366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length13.776623
Min length9

Characters and Unicode

Total characters5304
Distinct characters157
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique325 ?
Unique (%)84.4%

Sample

1st row대구 달성군 화원읍 비슬로 2625
2nd row대구 달서구 화암로 301 정부대구지방합동청사
3rd row대구 달서구 월배로 5길 39(유천동)
4th row대구 달성군 화원읍 비슬로 2594
5th row대구 달서구 진천로9길 33
ValueCountFrequency (%)
대구 367
26.0%
달서구 78
 
5.5%
수성구 76
 
5.4%
동구 56
 
4.0%
북구 53
 
3.8%
중구 50
 
3.5%
남구 26
 
1.8%
경산시 18
 
1.3%
경북 18
 
1.3%
서구 16
 
1.1%
Other values (451) 654
46.3%
2023-12-12T22:55:03.319534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1029
19.4%
구 777
14.6%
대 455
 
8.6%
로 284
 
5.4%
1 194
 
3.7%
동 188
 
3.5%
2 147
 
2.8%
달 142
 
2.7%
3 116
 
2.2%
길 111
 
2.1%
Other values (147) 1861
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3222
60.7%
Space Separator 1029
 
19.4%
Decimal Number 1020
 
19.2%
Dash Punctuation 27
 
0.5%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 777
24.1%
대 455
14.1%
로 284
 
8.8%
동 188
 
5.8%
달 142
 
4.4%
길 111
 
3.4%
성 110
 
3.4%
서 110
 
3.4%
수 81
 
2.5%
북 73
 
2.3%
Other values (131) 891
27.7%
Decimal Number
ValueCountFrequency (%)
1 194
19.0%
2 147
14.4%
3 116
11.4%
5 101
9.9%
4 88
8.6%
7 86
8.4%
0 84
8.2%
9 74
 
7.3%
6 70
 
6.9%
8 60
 
5.9%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
1029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3222
60.7%
Common 2082
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 777
24.1%
대 455
14.1%
로 284
 
8.8%
동 188
 
5.8%
달 142
 
4.4%
길 111
 
3.4%
성 110
 
3.4%
서 110
 
3.4%
수 81
 
2.5%
북 73
 
2.3%
Other values (131) 891
27.7%
Common
ValueCountFrequency (%)
1029
49.4%
1 194
 
9.3%
2 147
 
7.1%
3 116
 
5.6%
5 101
 
4.9%
4 88
 
4.2%
7 86
 
4.1%
0 84
 
4.0%
9 74
 
3.6%
6 70
 
3.4%
Other values (6) 93
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3222
60.7%
ASCII 2081
39.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1029
49.4%
1 194
 
9.3%
2 147
 
7.1%
3 116
 
5.6%
5 101
 
4.9%
4 88
 
4.2%
7 86
 
4.1%
0 84
 
4.0%
9 74
 
3.6%
6 70
 
3.4%
Other values (5) 92
 
4.4%
Hangul
ValueCountFrequency (%)
구 777
24.1%
대 455
14.1%
로 284
 
8.8%
동 188
 
5.8%
달 142
 
4.4%
길 111
 
3.4%
성 110
 
3.4%
서 110
 
3.4%
수 81
 
2.5%
북 73
 
2.3%
Other values (131) 891
27.7%
None
ValueCountFrequency (%)
· 1
100.0%

Interactions

2023-12-12T22:54:59.470563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:55:03.442486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선명역명출구번호
선명1.0000.9960.272
역명0.9961.0000.000
출구번호0.2720.0001.000
2023-12-12T22:55:03.541727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호선명
출구번호1.0000.188
선명0.1881.000

Missing values

2023-12-12T22:54:59.567629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:54:59.681479image/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

철도운영기관명선명역명출구번호출구별 주요시설명주소
0대구교통공사1호선대곡(정부대구청사)2대구교도소대구 달성군 화원읍 비슬로 2625
1대구교통공사1호선대곡(정부대구청사)3정부대구지방합동청사대구 달서구 화암로 301 정부대구지방합동청사
2대구교통공사1호선대곡(정부대구청사)4월배차량기지사업소대구 달서구 월배로 5길 39(유천동)
3대구교통공사1호선대곡(정부대구청사)1화원읍사무소대구 달성군 화원읍 비슬로 2594
4대구교통공사1호선진천4진천동 주민센터대구 달서구 진천로9길 33
5대구교통공사1호선진천1월배차량기지사업소대구 달서구 월배로 5길 39(유천동)
6대구교통공사1호선진천2진천우체국대구 달서구 월배로 32
7대구교통공사1호선진천3보강병원대구 달서구 월배로 102
8대구교통공사1호선월배4월배우체국대구 달서구 상원로 97
9대구교통공사1호선월배3상인2동 주민센터대구 달서구 상원로 27
철도운영기관명선명역명출구번호출구별 주요시설명주소
375대구교통공사3호선지산1지산2동주민센터대구 수성구 용학로33길 9
376대구교통공사3호선지산1지산동우체국대구 수성구 지범로 149
377대구교통공사3호선범물1대구지봉초등학교대구 수성구 지범로31길 45
378대구교통공사3호선범물4동아백화점수성점대구 수성구 지범로 191
379대구교통공사3호선범물3KT범물지사대구 수성구 범안로 33
380대구교통공사3호선범물2지산근린공원대구 수성구 지산동
381대구교통공사3호선용지4수성구립용학도서관대구 수성구 지범로41길 36
382대구교통공사3호선용지3범물1동주민센터대구 수성구 범안로 76
383대구교통공사3호선용지2범물2동주민센터대구 수성구 범안로 52
384대구교통공사3호선용지1범일중학교대구 수성구 지범로41길 23