Overview

Dataset statistics

Number of variables10
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory83.5 B

Variable types

Categorical9
Text1

Dataset

Description부산교통공사에서 운영하는 노선의 제세동기에 대한 데이터로 철도운영기관명,선명,역명,지상지하구분 ,역층, 출입구번호, 상세위치, 제세동기출력에너지,제세동기출력방식, 수량 등이 있습니다.
Author국가철도공단
URLhttps://www.data.go.kr/data/15041479/fileData.do

Alerts

철도운영기관명 has constant value ""Constant
수량 has constant value ""Constant
선명 is highly overall correlated with 상세위치High correlation
지상지하구분 is highly overall correlated with 상세위치High correlation
역층 is highly overall correlated with 상세위치High correlation
상세위치 is highly overall correlated with 선명 and 2 other fieldsHigh correlation
역층 is highly imbalanced (68.9%)Imbalance
제세동기출력방식 is highly imbalanced (73.2%)Imbalance
역명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:45:27.752170
Analysis finished2023-12-12 02:45:28.549711
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
부산교통공사
87 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산교통공사 87
100.0%

Length

2023-12-12T11:45:28.625398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:28.763252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산교통공사 87
100.0%

선명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
1호선
39 
2호선
33 
4호선
9 
3호선
6 

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 (%)
1호선 39
44.8%
2호선 33
37.9%
4호선 9
 
10.3%
3호선 6
 
6.9%

Length

2023-12-12T11:45:28.926500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:29.057294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1호선 39
44.8%
2호선 33
37.9%
4호선 9
 
10.3%
3호선 6
 
6.9%

역명
Text

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
2023-12-12T11:45:29.384352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.5517241
Min length2

Characters and Unicode

Total characters222
Distinct characters117
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

Unique87 ?
Unique (%)100.0%

Sample

1st row다대포해수욕장
2nd row다대포항
3rd row낫개
4th row신장림
5th row장림
ValueCountFrequency (%)
다대포해수욕장 1
 
1.1%
수정 1
 
1.1%
구남 1
 
1.1%
모라 1
 
1.1%
모덕 1
 
1.1%
덕포 1
 
1.1%
사상 1
 
1.1%
감전 1
 
1.1%
주례 1
 
1.1%
냉정 1
 
1.1%
Other values (77) 77
88.5%
2023-12-12T11:45:29.909645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 13
 
5.9%
산 10
 
4.5%
장 9
 
4.1%
동 7
 
3.2%
부 6
 
2.7%
포 6
 
2.7%
남 5
 
2.3%
사 5
 
2.3%
수 4
 
1.8%
천 4
 
1.8%
Other values (107) 153
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 13
 
5.9%
산 10
 
4.5%
장 9
 
4.1%
동 7
 
3.2%
부 6
 
2.7%
포 6
 
2.7%
남 5
 
2.3%
사 5
 
2.3%
수 4
 
1.8%
천 4
 
1.8%
Other values (107) 153
68.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 13
 
5.9%
산 10
 
4.5%
장 9
 
4.1%
동 7
 
3.2%
부 6
 
2.7%
포 6
 
2.7%
남 5
 
2.3%
사 5
 
2.3%
수 4
 
1.8%
천 4
 
1.8%
Other values (107) 153
68.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 13
 
5.9%
산 10
 
4.5%
장 9
 
4.1%
동 7
 
3.2%
부 6
 
2.7%
포 6
 
2.7%
남 5
 
2.3%
사 5
 
2.3%
수 4
 
1.8%
천 4
 
1.8%
Other values (107) 153
68.9%

지상지하구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size828.0 B
지하
71 
지상
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하 71
81.6%
지상 16
 
18.4%

Length

2023-12-12T11:45:30.057499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:30.213638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하 71
81.6%
지상 16
 
18.4%

역층
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size828.0 B
1
79 
2
 
7
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 79
90.8%
2 7
 
8.0%
4 1
 
1.1%

Length

2023-12-12T11:45:30.330532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:30.424823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 79
90.8%
2 7
 
8.0%
4 1
 
1.1%

출입구번호
Categorical

Distinct16
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size828.0 B
<NA>
44 
2번
8 
3번
7 
1번
6 
5번
 
4
Other values (11)
18 

Length

Max length12
Median length4
Mean length4.0344828
Min length3

Unique

Unique6 ?
Unique (%)6.9%

Sample

1st row2번 4번
2nd row1번 2번
3rd row1번
4th row<NA>
5th row3번

Common Values

ValueCountFrequency (%)
<NA> 44
50.6%
2번 8
 
9.2%
3번 7
 
8.0%
1번 6
 
6.9%
5번 4
 
4.6%
1번 2번 3
 
3.4%
4번 3
 
3.4%
2번 4번 2
 
2.3%
3번 4번 2
 
2.3%
1번 3번 2
 
2.3%
Other values (6) 6
 
6.9%

Length

2023-12-12T11:45:30.549071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 44
43.1%
2번 13
 
12.7%
3번 13
 
12.7%
1번 11
 
10.8%
4번 9
 
8.8%
5번 6
 
5.9%
6번 2
 
2.0%
7번 2
 
2.0%
17번 1
 
1.0%
8번 1
 
1.0%

상세위치
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
(B1) 역무안전실
44 
(1F) 역무안전실
5 
(1F) 고객센터
5 
(B1) 고객센터
 
3
(B1) 역무안전실 앞
 
3
Other values (22)
27 

Length

Max length24
Median length10
Mean length11.011494
Min length8

Unique

Unique18 ?
Unique (%)20.7%

Sample

1st row(B1) 역무안전실 옆
2nd row(B1) 역무안전실 앞
3rd row(B1) E/L 1호기 인근 표사는 곳 옆
4th row(B1) 역무안전실 근처
5th row(B1)역무안전실 근처

Common Values

ValueCountFrequency (%)
(B1) 역무안전실 44
50.6%
(1F) 역무안전실 5
 
5.7%
(1F) 고객센터 5
 
5.7%
(B1) 고객센터 3
 
3.4%
(B1) 역무안전실 앞 3
 
3.4%
(B2) 역무안전실 3
 
3.4%
(B1) 역무안전실 옆 2
 
2.3%
(B1) 역무안전실 근처 2
 
2.3%
(1F) 대합실 2
 
2.3%
(B2) 역무안전실 앞 1
 
1.1%
Other values (17) 17
 
19.5%

Length

2023-12-12T11:45:30.718112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
역무안전실 70
34.1%
b1 63
30.7%
1f 13
 
6.3%
고객센터 9
 
4.4%
앞 7
 
3.4%
b2 5
 
2.4%
옆 5
 
2.4%
근처 4
 
2.0%
대합실 4
 
2.0%
맞은편 3
 
1.5%
Other values (16) 22
 
10.7%

제세동기출력에너지
Categorical

Distinct4
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
성인 150 / 소아 50
44 
200
29 
150
13 
성인150 소아50
 
1

Length

Max length14
Median length14
Mean length8.6436782
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row성인 150 / 소아 50
2nd row성인 150 / 소아 50
3rd row성인 150 / 소아 50
4th row성인 150 / 소아 50
5th row성인 150 / 소아 50

Common Values

ValueCountFrequency (%)
성인 150 / 소아 50 44
50.6%
200 29
33.3%
150 13
 
14.9%
성인150 소아50 1
 
1.1%

Length

2023-12-12T11:45:30.874144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:30.991505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
150 57
21.6%
성인 44
16.7%
44
16.7%
소아 44
16.7%
50 44
16.7%
200 29
11.0%
성인150 1
 
0.4%
소아50 1
 
0.4%

제세동기출력방식
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size828.0 B
자동
81 
수동
 
4
자동/수동
 
2

Length

Max length5
Median length2
Mean length2.0689655
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동 81
93.1%
수동 4
 
4.6%
자동/수동 2
 
2.3%

Length

2023-12-12T11:45:31.136540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:31.234680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동 81
93.1%
수동 4
 
4.6%
자동/수동 2
 
2.3%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
1
87 

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 87
100.0%

Length

2023-12-12T11:45:31.352816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:31.476128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 87
100.0%

Correlations

2023-12-12T11:45:31.570134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기출력방식
선명1.0001.0000.4350.2510.0000.9020.8110.000
역명1.0001.0001.0001.0001.0001.0001.0001.000
지상지하구분0.4351.0001.0000.1160.0001.0000.0000.000
역층0.2511.0000.1161.0000.0001.0000.0000.000
출입구번호0.0001.0000.0000.0001.0000.6170.0000.000
상세위치0.9021.0001.0001.0000.6171.0000.0000.000
제세동기출력에너지0.8111.0000.0000.0000.0000.0001.0000.000
제세동기출력방식0.0001.0000.0000.0000.0000.0000.0001.000
2023-12-12T11:45:31.694437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제세동기출력방식선명지상지하구분출입구번호역층상세위치제세동기출력에너지
제세동기출력방식1.0000.0000.0000.0000.0000.0000.000
선명0.0001.0000.2890.0000.2380.6130.453
지상지하구분0.0000.2891.0000.0000.1900.8400.000
출입구번호0.0000.0000.0001.0000.0000.2190.000
역층0.0000.2380.1900.0001.0000.8450.000
상세위치0.0000.6130.8400.2190.8451.0000.000
제세동기출력에너지0.0000.4530.0000.0000.0000.0001.000
2023-12-12T11:45:31.825195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기출력방식
선명1.0000.2890.2380.0000.6130.4530.000
지상지하구분0.2891.0000.1900.0000.8400.0000.000
역층0.2380.1901.0000.0000.8450.0000.000
출입구번호0.0000.0000.0001.0000.2190.0000.000
상세위치0.6130.8400.8450.2191.0000.0000.000
제세동기출력에너지0.4530.0000.0000.0000.0001.0000.000
제세동기출력방식0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T11:45:28.317616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:45:28.464376image/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

철도운영기관명선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기출력방식수량
0부산교통공사1호선다대포해수욕장지하12번 4번(B1) 역무안전실 옆성인 150 / 소아 50자동1
1부산교통공사1호선다대포항지하11번 2번(B1) 역무안전실 앞성인 150 / 소아 50자동1
2부산교통공사1호선낫개지하11번(B1) E/L 1호기 인근 표사는 곳 옆성인 150 / 소아 50자동1
3부산교통공사1호선신장림지하1<NA>(B1) 역무안전실 근처성인 150 / 소아 50자동1
4부산교통공사1호선장림지하13번(B1)역무안전실 근처성인 150 / 소아 50자동1
5부산교통공사1호선동매지하11번(B1) 역무안전실 맞은편 벽면성인 150 / 소아 50자동1
6부산교통공사1호선신평지하1<NA>(B1) 역무안전실 근처성인 150 / 소아 50자동1
7부산교통공사1호선하단지하13번 4번 5번 6번(B1) 대합실 역무안전실 맞은편성인 150 / 소아 50자동1
8부산교통공사1호선당리지하1<NA>(B1) 역무안전실성인 150 / 소아 50자동1
9부산교통공사1호선사하지하1<NA>(B1) 역무안전실 옆성인 150 / 소아 50자동1
철도운영기관명선명역명지상지하구분역층출입구번호상세위치제세동기출력에너지제세동기출력방식수량
77부산교통공사3호선강서구청지상4<NA>(4F) 역무안전실 맞은편 벽면200자동1
78부산교통공사4호선수안지하15번 7번(B1) 고객센터200자동1
79부산교통공사4호선낙민지하13번(B1) 고객센터200자동1
80부산교통공사4호선충렬사지하13번(B1) 고객센터 옆성인 150 / 소아 50수동1
81부산교통공사4호선명장지하11번 3번(B1) 고객센터200자동1
82부산교통공사4호선반여농산물시장지상11번(1F) 고객센터200자동1
83부산교통공사4호선석대지상12번(1F) 고객센터200자동1
84부산교통공사4호선영산대지상12번(1F) 고객센터200자동1
85부산교통공사4호선윗반송지상11번 3번(1F) 고객센터200자동1
86부산교통공사4호선고촌지상14번(1F) 고객센터200자동1