Overview

Dataset statistics

Number of variables8
Number of observations111
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory66.2 B

Variable types

Numeric1
Categorical4
Text3

Dataset

Description서울교통공사의 역사별 휠체어리프트 설치 정보(연번, 호선, 역명, 장비종류, 호기, 승강기번호, 운행구간, 설치위치)입니다. 2023년 11월 기준 데이터 업데이트 합니다.
Author서울교통공사
URLhttps://www.data.go.kr/data/15044262/fileData.do

Alerts

장비종류 has constant value ""Constant
연번 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
승강기번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:57:45.722962
Analysis finished2023-12-12 16:57:46.572455
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56
Minimum1
Maximum111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T01:57:46.662154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.5
Q128.5
median56
Q383.5
95-th percentile105.5
Maximum111
Range110
Interquartile range (IQR)55

Descriptive statistics

Standard deviation32.186954
Coefficient of variation (CV)0.57476703
Kurtosis-1.2
Mean56
Median Absolute Deviation (MAD)28
Skewness0
Sum6216
Variance1036
MonotonicityStrictly increasing
2023-12-13T01:57:46.817811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
2 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
Other values (101) 101
91.0%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%

호선
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1020.0 B
7
40 
6
24 
5
14 
2
12 
1
7 
Other values (4)
14 

Length

Max length5
Median length1
Mean length1.036036
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
7 40
36.0%
6 24
21.6%
5 14
 
12.6%
2 12
 
10.8%
1 7
 
6.3%
8 6
 
5.4%
4 5
 
4.5%
3 2
 
1.8%
7(기타) 1
 
0.9%

Length

2023-12-13T01:57:46.966223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:47.096046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 40
36.0%
6 24
21.6%
5 14
 
12.6%
2 12
 
10.8%
1 7
 
6.3%
8 6
 
5.4%
4 5
 
4.5%
3 2
 
1.8%
7(기타 1
 
0.9%

역명
Text

Distinct55
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T01:57:47.326306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.990991
Min length2

Characters and Unicode

Total characters554
Distinct characters103
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)27.0%

Sample

1st row서울역(1)
2nd row신설동(1)
3rd row신설동(1)
4th row신설동(1)
5th row신설동(1)
ValueCountFrequency (%)
남구로 11
 
9.9%
신설동(2 6
 
5.4%
온수(7 5
 
4.5%
신설동(1 5
 
4.5%
신당(6 5
 
4.5%
가산디지털단지(7 4
 
3.6%
고속터미널(7 4
 
3.6%
디지털미디어시티(6 3
 
2.7%
잠실(8 3
 
2.7%
건대입구(7 3
 
2.7%
Other values (45) 62
55.9%
2023-12-13T01:57:47.686175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 65
 
11.7%
) 65
 
11.7%
7 21
 
3.8%
동 20
 
3.6%
신 17
 
3.1%
구 16
 
2.9%
6 16
 
2.9%
남 12
 
2.2%
로 12
 
2.2%
산 11
 
2.0%
Other values (93) 299
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
64.6%
Decimal Number 66
 
11.9%
Open Punctuation 65
 
11.7%
Close Punctuation 65
 
11.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 20
 
5.6%
신 17
 
4.7%
구 16
 
4.5%
남 12
 
3.4%
로 12
 
3.4%
산 11
 
3.1%
설 11
 
3.1%
대 11
 
3.1%
지 11
 
3.1%
수 10
 
2.8%
Other values (83) 227
63.4%
Decimal Number
ValueCountFrequency (%)
7 21
31.8%
6 16
24.2%
1 7
 
10.6%
2 7
 
10.6%
8 6
 
9.1%
5 3
 
4.5%
3 3
 
4.5%
4 3
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 358
64.6%
Common 196
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 20
 
5.6%
신 17
 
4.7%
구 16
 
4.5%
남 12
 
3.4%
로 12
 
3.4%
산 11
 
3.1%
설 11
 
3.1%
대 11
 
3.1%
지 11
 
3.1%
수 10
 
2.8%
Other values (83) 227
63.4%
Common
ValueCountFrequency (%)
( 65
33.2%
) 65
33.2%
7 21
 
10.7%
6 16
 
8.2%
1 7
 
3.6%
2 7
 
3.6%
8 6
 
3.1%
5 3
 
1.5%
3 3
 
1.5%
4 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
64.6%
ASCII 196
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 65
33.2%
) 65
33.2%
7 21
 
10.7%
6 16
 
8.2%
1 7
 
3.6%
2 7
 
3.6%
8 6
 
3.1%
5 3
 
1.5%
3 3
 
1.5%
4 3
 
1.5%
Hangul
ValueCountFrequency (%)
동 20
 
5.6%
신 17
 
4.7%
구 16
 
4.5%
남 12
 
3.4%
로 12
 
3.4%
산 11
 
3.1%
설 11
 
3.1%
대 11
 
3.1%
지 11
 
3.1%
수 10
 
2.8%
Other values (83) 227
63.4%

장비종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
W/L
111 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowW/L
2nd rowW/L
3rd rowW/L
4th rowW/L
5th rowW/L

Common Values

ValueCountFrequency (%)
W/L 111
100.0%

Length

2023-12-13T01:57:47.809000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:47.882293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
w/l 111
100.0%

호기
Categorical

Distinct19
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size1020.0 B
1
37 
2
20 
내부#1
12 
3
11 
4
7 
Other values (14)
24 

Length

Max length4
Median length1
Mean length1.7207207
Min length1

Unique

Unique10 ?
Unique (%)9.0%

Sample

1st row내부#1
2nd row외부#2
3rd row내부#1
4th row내부#2
5th row내부#3

Common Values

ValueCountFrequency (%)
1 37
33.3%
2 20
18.0%
내부#1 12
 
10.8%
3 11
 
9.9%
4 7
 
6.3%
내부#2 5
 
4.5%
5 4
 
3.6%
내부#3 3
 
2.7%
내부#4 2
 
1.8%
7 1
 
0.9%
Other values (9) 9
 
8.1%

Length

2023-12-13T01:57:47.970842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 37
33.3%
2 20
18.0%
내부#1 12
 
10.8%
3 11
 
9.9%
4 7
 
6.3%
내부#2 5
 
4.5%
5 4
 
3.6%
내부#3 3
 
2.7%
내부#4 2
 
1.8%
6 1
 
0.9%
Other values (9) 9
 
8.1%

승강기번호
Text

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T01:57:48.245633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters888
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)100.0%

Sample

1st row1902-362
2nd row1903-467
3rd row1903-415
4th row1903-417
5th row1903-416
ValueCountFrequency (%)
1902-362 1
 
0.9%
1901-121 1
 
0.9%
1901-118 1
 
0.9%
1901-117 1
 
0.9%
1901-128 1
 
0.9%
1901-234 1
 
0.9%
1901-233 1
 
0.9%
1901-232 1
 
0.9%
1900-766 1
 
0.9%
1900-765 1
 
0.9%
Other values (101) 101
91.0%
2023-12-13T01:57:48.628163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 204
23.0%
0 181
20.4%
9 137
15.4%
- 111
12.5%
3 54
 
6.1%
4 52
 
5.9%
2 50
 
5.6%
7 30
 
3.4%
5 26
 
2.9%
6 24
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 777
87.5%
Dash Punctuation 111
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 204
26.3%
0 181
23.3%
9 137
17.6%
3 54
 
6.9%
4 52
 
6.7%
2 50
 
6.4%
7 30
 
3.9%
5 26
 
3.3%
6 24
 
3.1%
8 19
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 204
23.0%
0 181
20.4%
9 137
15.4%
- 111
12.5%
3 54
 
6.1%
4 52
 
5.9%
2 50
 
5.6%
7 30
 
3.4%
5 26
 
2.9%
6 24
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 204
23.0%
0 181
20.4%
9 137
15.4%
- 111
12.5%
3 54
 
6.1%
4 52
 
5.9%
2 50
 
5.6%
7 30
 
3.4%
5 26
 
2.9%
6 24
 
2.7%

운행구간
Categorical

Distinct20
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
B2-B1
35 
B3-B2
14 
B1-F1
13 
B1-B1
8 
B5-B4
7 
Other values (15)
34 

Length

Max length15
Median length5
Mean length5.3063063
Min length4

Unique

Unique6 ?
Unique (%)5.4%

Sample

1st rowB2-B1
2nd row1F-B1
3rd rowB2-B1
4th rowB2-B1
5th rowB1-B1

Common Values

ValueCountFrequency (%)
B2-B1 35
31.5%
B3-B2 14
 
12.6%
B1-F1 13
 
11.7%
B1-B1 8
 
7.2%
B5-B4 7
 
6.3%
B4-B2 5
 
4.5%
B1-BM1 5
 
4.5%
B1-1F 4
 
3.6%
1F-2F 3
 
2.7%
B4-B3 3
 
2.7%
Other values (10) 14
 
12.6%

Length

2023-12-13T01:57:48.746425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
b2-b1 35
31.5%
b3-b2 14
 
12.6%
b1-f1 13
 
11.7%
b1-b1 8
 
7.2%
b5-b4 7
 
6.3%
b4-b2 5
 
4.5%
b1-bm1 5
 
4.5%
b1-1f 4
 
3.6%
1f-2f 3
 
2.7%
b4-b3 3
 
2.7%
Other values (10) 14
 
12.6%

설치위치
Text

Distinct86
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-13T01:57:48.982709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length10.657658
Min length3

Characters and Unicode

Total characters1183
Distinct characters136
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)66.7%

Sample

1st rowC계단 측
2nd row6번 출입구
3rd row제기동 방면
4th row동묘앞 방면
5th row연결통로(대합실)
ValueCountFrequency (%)
출입구 21
 
8.8%
방면1-1 17
 
7.1%
출입구방면 12
 
5.0%
방면8-4 12
 
5.0%
대합실 9
 
3.8%
환승통로 7
 
2.9%
방면 6
 
2.5%
계단 5
 
2.1%
3번 5
 
2.1%
측 5
 
2.1%
Other values (106) 139
58.4%
2023-12-13T01:57:49.346176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
11.1%
1 64
 
5.4%
면 61
 
5.2%
방 61
 
5.2%
- 48
 
4.1%
) 38
 
3.2%
( 38
 
3.2%
구 37
 
3.1%
입 34
 
2.9%
번 33
 
2.8%
Other values (126) 638
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 719
60.8%
Decimal Number 169
 
14.3%
Space Separator 131
 
11.1%
Dash Punctuation 48
 
4.1%
Close Punctuation 38
 
3.2%
Open Punctuation 38
 
3.2%
Other Punctuation 25
 
2.1%
Uppercase Letter 9
 
0.8%
Math Symbol 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 61
 
8.5%
방 61
 
8.5%
구 37
 
5.1%
입 34
 
4.7%
번 33
 
4.6%
출 33
 
4.6%
승 32
 
4.5%
대 32
 
4.5%
로 31
 
4.3%
통 30
 
4.2%
Other values (104) 335
46.6%
Decimal Number
ValueCountFrequency (%)
1 64
37.9%
4 25
 
14.8%
2 22
 
13.0%
8 15
 
8.9%
3 12
 
7.1%
6 10
 
5.9%
7 8
 
4.7%
5 8
 
4.7%
0 3
 
1.8%
9 2
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
B 6
66.7%
S 1
 
11.1%
E 1
 
11.1%
C 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 23
92.0%
# 1
 
4.0%
/ 1
 
4.0%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 719
60.8%
Common 455
38.5%
Latin 9
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 61
 
8.5%
방 61
 
8.5%
구 37
 
5.1%
입 34
 
4.7%
번 33
 
4.6%
출 33
 
4.6%
승 32
 
4.5%
대 32
 
4.5%
로 31
 
4.3%
통 30
 
4.2%
Other values (104) 335
46.6%
Common
ValueCountFrequency (%)
131
28.8%
1 64
14.1%
- 48
 
10.5%
) 38
 
8.4%
( 38
 
8.4%
4 25
 
5.5%
, 23
 
5.1%
2 22
 
4.8%
8 15
 
3.3%
3 12
 
2.6%
Other values (8) 39
 
8.6%
Latin
ValueCountFrequency (%)
B 6
66.7%
S 1
 
11.1%
E 1
 
11.1%
C 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 719
60.8%
ASCII 464
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
28.2%
1 64
13.8%
- 48
 
10.3%
) 38
 
8.2%
( 38
 
8.2%
4 25
 
5.4%
, 23
 
5.0%
2 22
 
4.7%
8 15
 
3.2%
3 12
 
2.6%
Other values (12) 48
 
10.3%
Hangul
ValueCountFrequency (%)
면 61
 
8.5%
방 61
 
8.5%
구 37
 
5.1%
입 34
 
4.7%
번 33
 
4.6%
출 33
 
4.6%
승 32
 
4.5%
대 32
 
4.5%
로 31
 
4.3%
통 30
 
4.2%
Other values (104) 335
46.6%

Interactions

2023-12-13T01:57:46.281561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:57:49.426651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역명호기운행구간설치위치
연번1.0000.8620.9880.5210.7890.889
호선0.8621.0001.0000.5540.7400.980
역명0.9881.0001.0000.0000.9480.980
호기0.5210.5540.0001.0000.7040.000
운행구간0.7890.7400.9480.7041.0000.000
설치위치0.8890.9800.9800.0000.0001.000
2023-12-13T01:57:49.510900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호기호선운행구간
호기1.0000.2380.278
호선0.2381.0000.382
운행구간0.2780.3821.000
2023-12-13T01:57:49.586335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선호기운행구간
연번1.0000.6080.2030.369
호선0.6081.0000.2380.382
호기0.2030.2381.0000.278
운행구간0.3690.3820.2781.000

Missing values

2023-12-13T01:57:46.406364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:57:46.527883image/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

연번호선역명장비종류호기승강기번호운행구간설치위치
011서울역(1)W/L내부#11902-362B2-B1C계단 측
121신설동(1)W/L외부#21903-4671F-B16번 출입구
231신설동(1)W/L내부#11903-415B2-B1제기동 방면
341신설동(1)W/L내부#21903-417B2-B1동묘앞 방면
451신설동(1)W/L내부#31903-416B1-B1연결통로(대합실)
561신설동(1)W/L내부#41903-414B1-B1연결통로(대합실)
671청량리(1)W/L내부#21901-053B2-B1회기 방면8-2
782한양대W/L내부#11900-1691F-2F뚝섬 방면8-2
892용답W/L내부#21900-1681F-2F성수 방면2-2
9102용답W/L내부#11900-2761F-2F신답 방면1-4
연번호선역명장비종류호기승강기번호운행구간설치위치
1011027(기타)어린이대공원집W/L11902-175B1-F1대공원승무사업소 내 어린이집
1021038잠실(8)W/L11900-789B2-B1몽촌토성 방면6-4 환승통로 계단
1031048잠실(8)W/L21900-790B3-B2석촌 방면1-1 환승통로 계단
1041058잠실(8)W/L31900-791통로-B2사당 방면환승통로 끝 계단
1051068복정(8)W/L11900-771B1-F14번 출입구
1061078모란(8)W/L13900-941B3-B2환승통로(암사방면 6-4)
1071088모란(8)W/L23900-942B3-B2환승통로(모란방면 1-1)
1081095까치산W/L31901-413B1-F12번 출입구
1091106효창공원앞(6)W/L21900-407B1-1F3번 출입구
1101117강남구청(7)W/L11901-555B2-B1대합실(1~4번 출입구방면)