Overview

Dataset statistics

Number of variables7
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory63.0 B

Variable types

Text5
Categorical1
Numeric1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13229/F/1/datasetView.do

Alerts

설 비 명 has unique valuesUnique

Reproduction

Analysis started2024-04-29 16:45:57.189582
Analysis finished2024-04-29 16:45:59.578992
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설 비 명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-30T01:45:59.712825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length8
Min length3

Characters and Unicode

Total characters176
Distinct characters68
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row합 계
2nd row선로전환기
3rd row융설장치
4th row자동폐색 ATS구간
5th row자동폐색 ATC구간
ValueCountFrequency (%)
자동폐색 3
 
8.3%
신호기장치 3
 
8.3%
궤도회로 2
 
5.6%
연동장치 2
 
5.6%
전원장치 2
 
5.6%
합 1
 
2.8%
pdt설비 1
 
2.8%
기구함 1
 
2.8%
전선로 1
 
2.8%
미니본드(cb-box포함 1
 
2.8%
Other values (19) 19
52.8%
2024-04-30T01:46:00.026645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
8.0%
장 11
 
6.2%
치 11
 
6.2%
기 10
 
5.7%
동 7
 
4.0%
신 5
 
2.8%
호 5
 
2.8%
전 5
 
2.8%
T 5
 
2.8%
연 4
 
2.3%
Other values (58) 99
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
77.3%
Uppercase Letter 23
 
13.1%
Space Separator 14
 
8.0%
Dash Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 11
 
8.1%
치 11
 
8.1%
기 10
 
7.4%
동 7
 
5.1%
신 5
 
3.7%
호 5
 
3.7%
전 5
 
3.7%
연 4
 
2.9%
구 4
 
2.9%
상 4
 
2.9%
Other values (44) 70
51.5%
Uppercase Letter
ValueCountFrequency (%)
T 5
21.7%
A 4
17.4%
S 3
13.0%
B 2
 
8.7%
P 2
 
8.7%
O 2
 
8.7%
C 2
 
8.7%
U 1
 
4.3%
D 1
 
4.3%
X 1
 
4.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
77.3%
Latin 23
 
13.1%
Common 17
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 11
 
8.1%
치 11
 
8.1%
기 10
 
7.4%
동 7
 
5.1%
신 5
 
3.7%
호 5
 
3.7%
전 5
 
3.7%
연 4
 
2.9%
구 4
 
2.9%
상 4
 
2.9%
Other values (44) 70
51.5%
Latin
ValueCountFrequency (%)
T 5
21.7%
A 4
17.4%
S 3
13.0%
B 2
 
8.7%
P 2
 
8.7%
O 2
 
8.7%
C 2
 
8.7%
U 1
 
4.3%
D 1
 
4.3%
X 1
 
4.3%
Common
ValueCountFrequency (%)
14
82.4%
- 1
 
5.9%
( 1
 
5.9%
) 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
77.3%
ASCII 40
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
35.0%
T 5
 
12.5%
A 4
 
10.0%
S 3
 
7.5%
B 2
 
5.0%
P 2
 
5.0%
O 2
 
5.0%
C 2
 
5.0%
- 1
 
2.5%
U 1
 
2.5%
Other values (4) 4
 
10.0%
Hangul
ValueCountFrequency (%)
장 11
 
8.1%
치 11
 
8.1%
기 10
 
7.4%
동 7
 
5.1%
신 5
 
3.7%
호 5
 
3.7%
전 5
 
3.7%
연 4
 
2.9%
구 4
 
2.9%
상 4
 
2.9%
Other values (44) 70
51.5%

단위
Categorical

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
개소
7 
대
6 
Km
4 
조
2 
각종
1 
Other values (2)
2 

Length

Max length2
Median length2
Mean length1.5454545
Min length1

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row각종
2nd row대
3rd row대
4th rowKm
5th rowKm

Common Values

ValueCountFrequency (%)
개소 7
31.8%
대 6
27.3%
Km 4
18.2%
조 2
 
9.1%
각종 1
 
4.5%
기 1
 
4.5%
개 1
 
4.5%

Length

2024-04-30T01:46:00.152990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:46:00.271588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개소 7
31.8%
대 6
27.3%
km 4
18.2%
조 2
 
9.1%
각종 1
 
4.5%
기 1
 
4.5%
개 1
 
4.5%

총계
Real number (ℝ)

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1362
Minimum32
Maximum14982
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T01:46:00.375461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile38
Q190.75
median346
Q31175.75
95-th percentile3314.85
Maximum14982
Range14950
Interquartile range (IQR)1085

Descriptive statistics

Standard deviation3174.5226
Coefficient of variation (CV)2.3307802
Kurtosis18.033653
Mean1362
Median Absolute Deviation (MAD)298.5
Skewness4.112164
Sum29964
Variance10077594
MonotonicityNot monotonic
2024-04-30T01:46:00.481862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
38 2
 
9.1%
14982 1
 
4.5%
482 1
 
4.5%
66 1
 
4.5%
238 1
 
4.5%
896 1
 
4.5%
3367 1
 
4.5%
2324 1
 
4.5%
829 1
 
4.5%
57 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
32 1
4.5%
38 2
9.1%
57 1
4.5%
66 1
4.5%
82 1
4.5%
117 1
4.5%
129 1
4.5%
136 1
4.5%
148 1
4.5%
238 1
4.5%
ValueCountFrequency (%)
14982 1
4.5%
3367 1
4.5%
2324 1
4.5%
2206 1
4.5%
1557 1
4.5%
1269 1
4.5%
896 1
4.5%
829 1
4.5%
517 1
4.5%
482 1
4.5%

1호선
Text

Distinct13
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-30T01:46:00.596590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2.5
Mean length1.8181818
Min length1

Characters and Unicode

Total characters40
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

Unique10 ?
Unique (%)45.5%

Sample

1st row832
2nd row24
3rd row-
4th row19
5th row-
ValueCountFrequency (%)
6
27.3%
4 4
18.2%
118 2
 
9.1%
832 1
 
4.5%
24 1
 
4.5%
19 1
 
4.5%
100 1
 
4.5%
20 1
 
4.5%
37 1
 
4.5%
126 1
 
4.5%
Other values (3) 3
13.6%
2024-04-30T01:46:00.841606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9
22.5%
- 6
15.0%
4 6
15.0%
2 4
10.0%
0 4
10.0%
8 3
 
7.5%
3 3
 
7.5%
6 2
 
5.0%
9 1
 
2.5%
7 1
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
85.0%
Dash Punctuation 6
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
26.5%
4 6
17.6%
2 4
11.8%
0 4
11.8%
8 3
 
8.8%
3 3
 
8.8%
6 2
 
5.9%
9 1
 
2.9%
7 1
 
2.9%
5 1
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9
22.5%
- 6
15.0%
4 6
15.0%
2 4
10.0%
0 4
10.0%
8 3
 
7.5%
3 3
 
7.5%
6 2
 
5.0%
9 1
 
2.5%
7 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9
22.5%
- 6
15.0%
4 6
15.0%
2 4
10.0%
0 4
10.0%
8 3
 
7.5%
3 3
 
7.5%
6 2
 
5.0%
9 1
 
2.5%
7 1
 
2.5%

2호선
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-30T01:46:00.996848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.6363636
Min length1

Characters and Unicode

Total characters58
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

Unique14 ?
Unique (%)63.6%

Sample

1st row7588
2nd row229
3rd row40
4th row117
5th row-
ValueCountFrequency (%)
1077 2
 
9.1%
13 2
 
9.1%
117 2
 
9.1%
2
 
9.1%
7588 1
 
4.5%
186 1
 
4.5%
608 1
 
4.5%
1698 1
 
4.5%
703 1
 
4.5%
30 1
 
4.5%
Other values (8) 8
36.4%
2024-04-30T01:46:01.283711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
22.4%
7 10
17.2%
0 7
12.1%
6 6
10.3%
8 6
10.3%
3 4
 
6.9%
2 4
 
6.9%
9 3
 
5.2%
- 2
 
3.4%
4 2
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
96.6%
Dash Punctuation 2
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
23.2%
7 10
17.9%
0 7
12.5%
6 6
10.7%
8 6
10.7%
3 4
 
7.1%
2 4
 
7.1%
9 3
 
5.4%
4 2
 
3.6%
5 1
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
22.4%
7 10
17.2%
0 7
12.1%
6 6
10.3%
8 6
10.3%
3 4
 
6.9%
2 4
 
6.9%
9 3
 
5.2%
- 2
 
3.4%
4 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
22.4%
7 10
17.2%
0 7
12.1%
6 6
10.3%
8 6
10.3%
3 4
 
6.9%
2 4
 
6.9%
9 3
 
5.2%
- 2
 
3.4%
4 2
 
3.4%

3호선
Text

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-30T01:46:01.475602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.3636364
Min length1

Characters and Unicode

Total characters52
Distinct characters10
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

Unique13 ?
Unique (%)59.1%

Sample

1st row3845
2nd row163
3rd row16
4th row-
5th row81
ValueCountFrequency (%)
3
13.6%
12 2
 
9.1%
671 2
 
9.1%
16 2
 
9.1%
13 1
 
4.5%
179 1
 
4.5%
143 1
 
4.5%
114 1
 
4.5%
863 1
 
4.5%
197 1
 
4.5%
Other values (7) 7
31.8%
2024-04-30T01:46:01.794401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
32.7%
6 6
 
11.5%
3 6
 
11.5%
7 5
 
9.6%
4 4
 
7.7%
9 4
 
7.7%
- 3
 
5.8%
2 3
 
5.8%
8 3
 
5.8%
5 1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
94.2%
Dash Punctuation 3
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
34.7%
6 6
 
12.2%
3 6
 
12.2%
7 5
 
10.2%
4 4
 
8.2%
9 4
 
8.2%
2 3
 
6.1%
8 3
 
6.1%
5 1
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
32.7%
6 6
 
11.5%
3 6
 
11.5%
7 5
 
9.6%
4 4
 
7.7%
9 4
 
7.7%
- 3
 
5.8%
2 3
 
5.8%
8 3
 
5.8%
5 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
32.7%
6 6
 
11.5%
3 6
 
11.5%
7 5
 
9.6%
4 4
 
7.7%
9 4
 
7.7%
- 3
 
5.8%
2 3
 
5.8%
8 3
 
5.8%
5 1
 
1.9%

4호선
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-30T01:46:01.926381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.1363636
Min length1

Characters and Unicode

Total characters47
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

Unique15 ?
Unique (%)68.2%

Sample

1st row2717
2nd row101
3rd row26
4th row-
5th row67
ValueCountFrequency (%)
3
 
13.6%
458 2
 
9.1%
9 2
 
9.1%
97 1
 
4.5%
324 1
 
4.5%
95 1
 
4.5%
71 1
 
4.5%
660 1
 
4.5%
10 1
 
4.5%
148 1
 
4.5%
Other values (8) 8
36.4%
2024-04-30T01:46:02.178298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
17.0%
7 6
12.8%
9 5
10.6%
4 4
8.5%
8 4
8.5%
2 4
8.5%
6 4
8.5%
0 4
8.5%
- 3
 
6.4%
5 3
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44
93.6%
Dash Punctuation 3
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
18.2%
7 6
13.6%
9 5
11.4%
4 4
9.1%
8 4
9.1%
2 4
9.1%
6 4
9.1%
0 4
9.1%
5 3
 
6.8%
3 2
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
17.0%
7 6
12.8%
9 5
10.6%
4 4
8.5%
8 4
8.5%
2 4
8.5%
6 4
8.5%
0 4
8.5%
- 3
 
6.4%
5 3
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
17.0%
7 6
12.8%
9 5
10.6%
4 4
8.5%
8 4
8.5%
2 4
8.5%
6 4
8.5%
0 4
8.5%
- 3
 
6.4%
5 3
 
6.4%

Interactions

2024-04-30T01:45:59.239856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:46:02.277607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설 비 명단위총계1호선2호선3호선4호선
설 비 명1.0001.0001.0001.0001.0001.0001.000
단위1.0001.0000.6750.8420.9390.9040.869
총계1.0000.6751.0000.9031.0001.0001.000
1호선1.0000.8420.9031.0000.9680.9110.897
2호선1.0000.9391.0000.9681.0000.9820.997
3호선1.0000.9041.0000.9110.9821.0001.000
4호선1.0000.8691.0000.8970.9971.0001.000
2024-04-30T01:46:02.378251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계단위
총계1.0000.480
단위0.4801.000

Missing values

2024-04-30T01:45:59.418966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:45:59.534890image/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

설 비 명단위총계1호선2호선3호선4호선
0합 계각종14982832758838452717
1선로전환기대51724229163101
2융설장치대82-401626
3자동폐색 ATS구간Km13619117--
4자동폐색 ATC구간Km148--8167
5자동폐색 ATO구간Km117-117--
6연동장치운전조작반개소38413129
7연동장치 연동장치역개소38413129
8연동장치 기기집중역개소32-1697
9신호기장치 지상신호기기1269118840191120
설 비 명단위총계1호선2호선3호선4호선
12궤도회로 가청주파수개소1557100662471324
13궤도회로 상용주파수개소4822018617997
14전원장치 정류기대4543772197148
15전원장치 UPS대574301310
16ATS 지상자조829126703--
17미니본드(CB-BOX포함)조23241181077671458
18전선로Km33671461698863660
19기구함개89610360811471
20PDT설비개소238--14395
21감시장치대665192319