Overview

Dataset statistics

Number of variables10
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)3.2%
Total size in memory2.6 KiB
Average record size in memory87.1 B

Variable types

Categorical8
Text2

Dataset

Description인천교통공사에서 운영하는 1호선 도시광역철도역들의 철도운영기관명, 선명, 역명, 지상지하구분, 역층, 출입구번호, 상세위치, 제세동기출력에너지, 제세동기운영방식,수량 에 대한 데이터가 있습니다.
Author국가철도공단
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15041490&srcSe=7661IVAWM27C61E190

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
수량 has constant value ""Constant
Dataset has 1 (3.2%) duplicate rowsDuplicates
지상지하구분 is highly imbalanced (65.5%)Imbalance
제세동기운영방식 is highly imbalanced (54.1%)Imbalance

Reproduction

Analysis started2024-04-20 16:24:00.550108
Analysis finished2024-04-20 16:24:01.817084
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
인천교통공사
31 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천교통공사 31
100.0%

Length

2024-04-21T01:24:02.021438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:02.325473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천교통공사 31
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
인천1호선
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천1호선
2nd row인천1호선
3rd row인천1호선
4th row인천1호선
5th row인천1호선

Common Values

ValueCountFrequency (%)
인천1호선 31
100.0%

Length

2024-04-21T01:24:02.656634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:02.963726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천1호선 31
100.0%

역명
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size376.0 B
2024-04-21T01:24:03.574193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.6774194
Min length2

Characters and Unicode

Total characters114
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row간석오거리
2nd row갈산
3rd row경인교대입구
4th row계산
5th row계양
ValueCountFrequency (%)
부평 2
 
6.5%
간석오거리 1
 
3.2%
선학 1
 
3.2%
캠퍼스타운 1
 
3.2%
지식정보단지 1
 
3.2%
작전 1
 
3.2%
임학 1
 
3.2%
인천터미널 1
 
3.2%
인천시청 1
 
3.2%
인천대입구 1
 
3.2%
Other values (20) 20
64.5%
2024-04-21T01:24:04.657408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 5
 
4.4%
인 5
 
4.4%
평 5
 
4.4%
구 4
 
3.5%
크 3
 
2.6%
천 3
 
2.6%
학 3
 
2.6%
지 3
 
2.6%
동 3
 
2.6%
거 2
 
1.8%
Other values (65) 78
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 5
 
4.4%
인 5
 
4.4%
평 5
 
4.4%
구 4
 
3.5%
크 3
 
2.6%
천 3
 
2.6%
학 3
 
2.6%
지 3
 
2.6%
동 3
 
2.6%
거 2
 
1.8%
Other values (65) 78
68.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 5
 
4.4%
인 5
 
4.4%
평 5
 
4.4%
구 4
 
3.5%
크 3
 
2.6%
천 3
 
2.6%
학 3
 
2.6%
지 3
 
2.6%
동 3
 
2.6%
거 2
 
1.8%
Other values (65) 78
68.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 5
 
4.4%
인 5
 
4.4%
평 5
 
4.4%
구 4
 
3.5%
크 3
 
2.6%
천 3
 
2.6%
학 3
 
2.6%
지 3
 
2.6%
동 3
 
2.6%
거 2
 
1.8%
Other values (65) 78
68.4%

지상지하구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size376.0 B
지하
29 
지상
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지하
2nd row지하
3rd row지하
4th row지하
5th row지상

Common Values

ValueCountFrequency (%)
지하 29
93.5%
지상 2
 
6.5%

Length

2024-04-21T01:24:05.272415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:05.578459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하 29
93.5%
지상 2
 
6.5%

역층
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size376.0 B
1
25 
2
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 25
80.6%
2 6
 
19.4%

Length

2024-04-21T01:24:05.905643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:06.212146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
80.6%
2 6
 
19.4%

출입구번호
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size376.0 B
<NA>
19 
1
7 
5
2 
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.8387097
Min length1

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 19
61.3%
1 7
 
22.6%
5 2
 
6.5%
2 1
 
3.2%
3 1
 
3.2%
6 1
 
3.2%

Length

2024-04-21T01:24:06.574669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:06.908251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
61.3%
1 7
 
22.6%
5 2
 
6.5%
2 1
 
3.2%
3 1
 
3.2%
6 1
 
3.2%

상세위치
Text

Distinct25
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size376.0 B
2024-04-21T01:24:07.525418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length19.096774
Min length8

Characters and Unicode

Total characters592
Distinct characters60
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)67.7%

Sample

1st row(B2) 역무실 앞
2nd row(B1) 대합실 고객안내센터 앞
3rd row(B2) 대합실 고객센터 근처/ 표내는 방향
4th row(B2) 대합실 고객센터/ 1/2/5/6번 출입구 방향
5th row(1F) 대합실 고객안내센터 내
ValueCountFrequency (%)
b1 24
16.7%
대합실 21
14.6%
고객센터 13
 
9.0%
고객안내센터 11
 
7.6%
방향 8
 
5.6%
출입구 7
 
4.9%
내부 6
 
4.2%
앞 6
 
4.2%
역무실 5
 
3.5%
근처 5
 
3.5%
Other values (28) 38
26.4%
2024-04-21T01:24:08.352057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
19.6%
( 32
 
5.4%
) 32
 
5.4%
1 30
 
5.1%
B 29
 
4.9%
실 27
 
4.6%
객 24
 
4.1%
내 24
 
4.1%
센 24
 
4.1%
터 24
 
4.1%
Other values (50) 230
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 319
53.9%
Space Separator 116
 
19.6%
Decimal Number 44
 
7.4%
Open Punctuation 32
 
5.4%
Close Punctuation 32
 
5.4%
Uppercase Letter 31
 
5.2%
Other Punctuation 17
 
2.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 27
 
8.5%
객 24
 
7.5%
내 24
 
7.5%
센 24
 
7.5%
터 24
 
7.5%
고 24
 
7.5%
합 21
 
6.6%
대 21
 
6.6%
안 11
 
3.4%
방 9
 
2.8%
Other values (35) 110
34.5%
Decimal Number
ValueCountFrequency (%)
1 30
68.2%
2 6
 
13.6%
3 2
 
4.5%
4 2
 
4.5%
5 2
 
4.5%
6 1
 
2.3%
9 1
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
B 29
93.5%
F 2
 
6.5%
Other Punctuation
ValueCountFrequency (%)
/ 16
94.1%
. 1
 
5.9%
Space Separator
ValueCountFrequency (%)
116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 319
53.9%
Common 242
40.9%
Latin 31
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 27
 
8.5%
객 24
 
7.5%
내 24
 
7.5%
센 24
 
7.5%
터 24
 
7.5%
고 24
 
7.5%
합 21
 
6.6%
대 21
 
6.6%
안 11
 
3.4%
방 9
 
2.8%
Other values (35) 110
34.5%
Common
ValueCountFrequency (%)
116
47.9%
( 32
 
13.2%
) 32
 
13.2%
1 30
 
12.4%
/ 16
 
6.6%
2 6
 
2.5%
3 2
 
0.8%
4 2
 
0.8%
5 2
 
0.8%
6 1
 
0.4%
Other values (3) 3
 
1.2%
Latin
ValueCountFrequency (%)
B 29
93.5%
F 2
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 319
53.9%
ASCII 273
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
42.5%
( 32
 
11.7%
) 32
 
11.7%
1 30
 
11.0%
B 29
 
10.6%
/ 16
 
5.9%
2 6
 
2.2%
3 2
 
0.7%
4 2
 
0.7%
5 2
 
0.7%
Other values (5) 6
 
2.2%
Hangul
ValueCountFrequency (%)
실 27
 
8.5%
객 24
 
7.5%
내 24
 
7.5%
센 24
 
7.5%
터 24
 
7.5%
고 24
 
7.5%
합 21
 
6.6%
대 21
 
6.6%
안 11
 
3.4%
방 9
 
2.8%
Other values (35) 110
34.5%

제세동기출력에너지
Categorical

Distinct7
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size376.0 B
200
17 
150
7 
180
3 
185~200
 
1
성인 150/ 어린이 50
 
1
Other values (2)
2 

Length

Max length14
Median length3
Mean length3.8387097
Min length3

Unique

Unique4 ?
Unique (%)12.9%

Sample

1st row185~200
2nd row200
3rd row150
4th row180
5th row180

Common Values

ValueCountFrequency (%)
200 17
54.8%
150 7
22.6%
180 3
 
9.7%
185~200 1
 
3.2%
성인 150/ 어린이 50 1
 
3.2%
160 1
 
3.2%
성인 180/ 어린이 50 1
 
3.2%

Length

2024-04-21T01:24:08.568128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:08.764516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 17
45.9%
150 8
21.6%
180 4
 
10.8%
성인 2
 
5.4%
어린이 2
 
5.4%
50 2
 
5.4%
185~200 1
 
2.7%
160 1
 
2.7%

제세동기운영방식
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size376.0 B
자동
28 
수동
3 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동 28
90.3%
수동 3
 
9.7%

Length

2024-04-21T01:24:08.994219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:09.162675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동 28
90.3%
수동 3
 
9.7%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size376.0 B
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 31
100.0%

Length

2024-04-21T01:24:09.337435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T01:24:09.500832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
100.0%

Correlations

2024-04-21T01:24:09.609784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기운영방식
역명1.0001.0001.0001.0001.0001.0001.000
지상지하구분1.0001.0000.0000.0001.0000.0000.000
역층1.0000.0001.0000.0000.3370.0000.000
출입구번호1.0000.0000.0001.0001.0000.0000.350
상세위치1.0001.0000.3371.0001.0000.8551.000
제세동기출력에너지1.0000.0000.0000.0000.8551.0000.409
제세동기운영방식1.0000.0000.0000.3501.0000.4091.000
2024-04-21T01:24:09.820098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지상지하구분출입구번호제세동기출력에너지제세동기운영방식역층
지상지하구분1.0000.0000.0000.0000.000
출입구번호0.0001.0000.0000.3160.000
제세동기출력에너지0.0000.0001.0000.3920.000
제세동기운영방식0.0000.3160.3921.0000.000
역층0.0000.0000.0000.0001.000
2024-04-21T01:24:09.992301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지상지하구분역층출입구번호제세동기출력에너지제세동기운영방식
지상지하구분1.0000.0000.0000.0000.000
역층0.0001.0000.0000.0000.000
출입구번호0.0000.0001.0000.0000.316
제세동기출력에너지0.0000.0000.0001.0000.392
제세동기운영방식0.0000.0000.3160.3921.000

Missing values

2024-04-21T01:24:01.151237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T01:24:01.630256image/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

철도운영기관명선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기운영방식수량
0인천교통공사인천1호선간석오거리지하2<NA>(B2) 역무실 앞185~200자동1
1인천교통공사인천1호선갈산지하11(B1) 대합실 고객안내센터 앞200자동1
2인천교통공사인천1호선경인교대입구지하2<NA>(B2) 대합실 고객센터 근처/ 표내는 방향150자동1
3인천교통공사인천1호선계산지하21(B2) 대합실 고객센터/ 1/2/5/6번 출입구 방향180자동1
4인천교통공사인천1호선계양지상11(1F) 대합실 고객안내센터 내180자동1
5인천교통공사인천1호선국제업무지구지하15(B1) 대합실 고객안내센터 내부/ 5번 출입구 방향200자동1
6인천교통공사인천1호선귤현지상11(1F) 고객안내센터 내(박촌 방면 승강장 4-1 앞)200자동1
7인천교통공사인천1호선동막지하1<NA>(B1) 대합실 고객안내센터 앞200자동1
8인천교통공사인천1호선동수지하12(B1) 대합실 고객센터 옆/ 2번 출입구 방향150자동1
9인천교통공사인천1호선동춘지하1<NA>(B1) 대합실 고객센터 앞200수동1
철도운영기관명선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기운영방식수량
21인천교통공사인천1호선예술회관지하25(B2) 대합실 고객센터 근처/하선 게이트 옆200수동1
22인천교통공사인천1호선원인재지하16(B1) 대합실 고객안내센터200자동1
23인천교통공사인천1호선인천대입구지하1<NA>(B1) 역무실 앞150자동1
24인천교통공사인천1호선인천시청지하1<NA>(B3) 상.하 표내는곳 사이/ 1/9번 출입구 방향200자동1
25인천교통공사인천1호선인천터미널지하1<NA>(B1) 고객안내센터 내부200자동1
26인천교통공사인천1호선임학지하1<NA>(B1) 역무실200자동1
27인천교통공사인천1호선작전지하1<NA>(B1) 고객안내센터 내/ 역사 비상장비 보관함성인 180/ 어린이 50수동1
28인천교통공사인천1호선지식정보단지지하1<NA>(B1) 고객안내센터200자동1
29인천교통공사인천1호선캠퍼스타운지하11(B1) 대합실 고객센터 내부200자동1
30인천교통공사인천1호선테크노파크지하1<NA>(B1) 대합실 고객센터 내150자동1

Duplicate rows

Most frequently occurring

철도운영기관명선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기운영방식수량# duplicates
0인천교통공사인천1호선부평지하2<NA>(B1) 대합실 고객센터 내부200자동12