Overview

Dataset statistics

Number of variables4
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory37.6 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description서울시설공단 도로기전처에서 관리중인 지하차도 현황입니다.지하차도 이용 중 불편사항 발생 시 서울시설공단 관할 지하차도를 확인하실 수 있습니다.
Author서울시설공단
URLhttps://www.data.go.kr/data/15125445/fileData.do

Alerts

연번 is highly overall correlated with 관할관리소High correlation
관할관리소 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
지하차도 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:28:56.791488
Analysis finished2024-04-21 02:28:58.490519
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2024-04-21T11:28:58.560122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2024-04-21T11:28:58.673787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

지하차도
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T11:28:58.853225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length6
Mean length7.2758621
Min length6

Characters and Unicode

Total characters211
Distinct characters68
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

Unique29 ?
Unique (%)100.0%

Sample

1st row가양지하차도
2nd row경인1지하차도(주, 부)
3rd row경인2지하차도
4th row수서지하차도
5th row일원지하차도
ValueCountFrequency (%)
가양지하차도 1
 
3.3%
경인1지하차도(주 1
 
3.3%
장암지하차도 1
 
3.3%
상도지하차도 1
 
3.3%
도봉지하차도 1
 
3.3%
아천ic램프-i지하차도 1
 
3.3%
아천ic램프-h지하차도 1
 
3.3%
망원초록길지하차도 1
 
3.3%
성수대교북단지하차도 1
 
3.3%
한강대교동측지하차도 1
 
3.3%
Other values (20) 20
66.7%
2024-04-21T11:28:59.169594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 31
14.7%
하 30
 
14.2%
지 29
 
13.7%
차 29
 
13.7%
포 3
 
1.4%
I 3
 
1.4%
원 3
 
1.4%
수 3
 
1.4%
아 2
 
0.9%
초 2
 
0.9%
Other values (58) 76
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
93.4%
Uppercase Letter 6
 
2.8%
Dash Punctuation 2
 
0.9%
Decimal Number 2
 
0.9%
Open Punctuation 1
 
0.5%
Other Punctuation 1
 
0.5%
Space Separator 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 31
15.7%
하 30
15.2%
지 29
14.7%
차 29
14.7%
포 3
 
1.5%
원 3
 
1.5%
수 3
 
1.5%
아 2
 
1.0%
초 2
 
1.0%
교 2
 
1.0%
Other values (48) 63
32.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
50.0%
C 2
33.3%
H 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
93.4%
Common 8
 
3.8%
Latin 6
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 31
15.7%
하 30
15.2%
지 29
14.7%
차 29
14.7%
포 3
 
1.5%
원 3
 
1.5%
수 3
 
1.5%
아 2
 
1.0%
초 2
 
1.0%
교 2
 
1.0%
Other values (48) 63
32.0%
Common
ValueCountFrequency (%)
- 2
25.0%
1 1
12.5%
( 1
12.5%
, 1
12.5%
1
12.5%
) 1
12.5%
2 1
12.5%
Latin
ValueCountFrequency (%)
I 3
50.0%
C 2
33.3%
H 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
93.4%
ASCII 14
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 31
15.7%
하 30
15.2%
지 29
14.7%
차 29
14.7%
포 3
 
1.5%
원 3
 
1.5%
수 3
 
1.5%
아 2
 
1.0%
초 2
 
1.0%
교 2
 
1.0%
Other values (48) 63
32.0%
ASCII
ValueCountFrequency (%)
I 3
21.4%
C 2
14.3%
- 2
14.3%
H 1
 
7.1%
1 1
 
7.1%
( 1
 
7.1%
, 1
 
7.1%
1
 
7.1%
) 1
 
7.1%
2 1
 
7.1%

관할관리소
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size364.0 B
강남도로기전관리소
13 
강북도로기전관리소
12 
도봉지하차도관리소
4 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강남도로기전관리소 13
44.8%
강북도로기전관리소 12
41.4%
도봉지하차도관리소 4
 
13.8%

Length

2024-04-21T11:28:59.285814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:28:59.371448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강남도로기전관리소 13
44.8%
강북도로기전관리소 12
41.4%
도봉지하차도관리소 4
 
13.8%

위치
Text

Distinct20
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-21T11:28:59.523125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.5172414
Min length6

Characters and Unicode

Total characters218
Distinct characters51
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

Unique14 ?
Unique (%)48.3%

Sample

1st row강서구 가양동
2nd row양천구 목동
3rd row양천구 목동
4th row강남구 수서동
5th row강남구 개포동
ValueCountFrequency (%)
노원구 8
 
13.3%
강남구 4
 
6.7%
상계동 4
 
6.7%
개포동 3
 
5.0%
강서구 3
 
5.0%
서초구 3
 
5.0%
아천동 2
 
3.3%
양천구 2
 
3.3%
목동 2
 
3.3%
구리시 2
 
3.3%
Other values (23) 27
45.0%
2024-04-21T11:28:59.808063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 33
15.1%
31
14.2%
구 29
13.3%
원 10
 
4.6%
계 9
 
4.1%
노 8
 
3.7%
강 8
 
3.7%
상 7
 
3.2%
서 7
 
3.2%
포 6
 
2.8%
Other values (41) 70
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
83.0%
Space Separator 31
 
14.2%
Decimal Number 5
 
2.3%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
18.2%
구 29
16.0%
원 10
 
5.5%
계 9
 
5.0%
노 8
 
4.4%
강 8
 
4.4%
상 7
 
3.9%
서 7
 
3.9%
포 6
 
3.3%
양 5
 
2.8%
Other values (35) 59
32.6%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
8 1
20.0%
4 1
20.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181
83.0%
Common 37
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
18.2%
구 29
16.0%
원 10
 
5.5%
계 9
 
5.0%
노 8
 
4.4%
강 8
 
4.4%
상 7
 
3.9%
서 7
 
3.9%
포 6
 
3.3%
양 5
 
2.8%
Other values (35) 59
32.6%
Common
ValueCountFrequency (%)
31
83.8%
1 2
 
5.4%
~ 1
 
2.7%
8 1
 
2.7%
4 1
 
2.7%
3 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181
83.0%
ASCII 37
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 33
18.2%
구 29
16.0%
원 10
 
5.5%
계 9
 
5.0%
노 8
 
4.4%
강 8
 
4.4%
상 7
 
3.9%
서 7
 
3.9%
포 6
 
3.3%
양 5
 
2.8%
Other values (35) 59
32.6%
ASCII
ValueCountFrequency (%)
31
83.8%
1 2
 
5.4%
~ 1
 
2.7%
8 1
 
2.7%
4 1
 
2.7%
3 1
 
2.7%

Interactions

2024-04-21T11:28:58.223871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:28:59.893414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지하차도관할관리소위치
연번1.0001.0000.9180.968
지하차도1.0001.0001.0001.000
관할관리소0.9181.0001.0001.000
위치0.9681.0001.0001.000
2024-04-21T11:28:59.975127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관할관리소
연번1.0000.744
관할관리소0.7441.000

Missing values

2024-04-21T11:28:58.378415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:28:58.454829image/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

연번지하차도관할관리소위치
01가양지하차도강남도로기전관리소강서구 가양동
12경인1지하차도(주, 부)강남도로기전관리소양천구 목동
23경인2지하차도강남도로기전관리소양천구 목동
34수서지하차도강남도로기전관리소강남구 수서동
45일원지하차도강남도로기전관리소강남구 개포동
56개포지하차도강남도로기전관리소강남구 개포동
67구룡지하차도강남도로기전관리소강남구 개포동
78염곡동서지하차도강남도로기전관리소서초구 양재동
89금하지하차도강남도로기전관리소금천구 독산동
910구반포지하차도강남도로기전관리소서초구 반포동
연번지하차도관할관리소위치
1920암사지하차도강북도로기전관리소강동구 암사동
2021한강대교동측지하차도강북도로기전관리소용산구 동부이촌동
2122성수대교북단지하차도강북도로기전관리소성동구 성수동
2223망원초록길지하차도강북도로기전관리소마포구 망원동
2324아천IC램프-H지하차도강북도로기전관리소경기 구리시 아천동
2425아천IC램프-I지하차도강북도로기전관리소경기 구리시 아천동
2526도봉지하차도도봉지하차도관리소노원구 월계4동~상계8동
2627상도지하차도도봉지하차도관리소노원구 상계1동
2728장암지하차도도봉지하차도관리소노원구 상계1동
2829초안산지하차도도봉지하차도관리소노원구 월계3동