Overview

Dataset statistics

Number of variables5
Number of observations152
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory41.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description서울특별시 보도육교 설치 위치정보에 대한 데이터입니다. 번호, 관리기관, 보도육교명, 위치, 노선명 등을 제공합니다.
Author서울특별시
URLhttps://www.data.go.kr/data/15097073/fileData.do

Alerts

연번 is highly overall correlated with 관리기관High correlation
관리기관 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:32:23.416405
Analysis finished2023-12-12 05:32:24.226324
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.5
Minimum1
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T14:32:24.337923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.55
Q138.75
median76.5
Q3114.25
95-th percentile144.45
Maximum152
Range151
Interquartile range (IQR)75.5

Descriptive statistics

Standard deviation44.022721
Coefficient of variation (CV)0.57546041
Kurtosis-1.2
Mean76.5
Median Absolute Deviation (MAD)38
Skewness0
Sum11628
Variance1938
MonotonicityStrictly increasing
2023-12-12T14:32:24.507174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (142) 142
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%

관리기관
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서초구청
17 
양천구청
14 
용산구청
12 
강동구청
 
9
구로구청
 
9
Other values (18)
91 

Length

Max length5
Median length4
Mean length4.1381579
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row종로구청
2nd row종로구청
3rd row종로구청
4th row중구청
5th row중구청

Common Values

ValueCountFrequency (%)
서초구청 17
 
11.2%
양천구청 14
 
9.2%
용산구청 12
 
7.9%
강동구청 9
 
5.9%
구로구청 9
 
5.9%
강남구청 8
 
5.3%
관악구청 8
 
5.3%
영등포구청 8
 
5.3%
동대문구청 8
 
5.3%
금천구청 7
 
4.6%
Other values (13) 52
34.2%

Length

2023-12-12T14:32:24.722726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서초구청 17
 
11.2%
양천구청 14
 
9.2%
용산구청 12
 
7.9%
강동구청 9
 
5.9%
구로구청 9
 
5.9%
강남구청 8
 
5.3%
관악구청 8
 
5.3%
영등포구청 8
 
5.3%
동대문구청 8
 
5.3%
노원구청 7
 
4.6%
Other values (13) 52
34.2%

보도육교명
Text

Distinct151
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T14:32:25.046044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.7105263
Min length2

Characters and Unicode

Total characters716
Distinct characters208
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

Unique150 ?
Unique (%)98.7%

Sample

1st row서울예고앞
2nd row신영로타리
3rd row세검
4th row리라초교앞
5th row충무초교앞
ValueCountFrequency (%)
보도육교 3
 
1.8%
겸재교 2
 
1.2%
보행교 2
 
1.2%
전용교량 2
 
1.2%
선유도 1
 
0.6%
보라매공원 1
 
0.6%
도림천 1
 
0.6%
문래 1
 
0.6%
양평1 1
 
0.6%
양평2 1
 
0.6%
Other values (154) 154
91.1%
2023-12-12T14:32:25.536315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
앞 51
 
7.1%
교 48
 
6.7%
초 32
 
4.5%
20
 
2.8%
리 16
 
2.2%
신 14
 
2.0%
원 14
 
2.0%
산 13
 
1.8%
구 12
 
1.7%
한 11
 
1.5%
Other values (198) 485
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 678
94.7%
Space Separator 20
 
2.8%
Decimal Number 9
 
1.3%
Uppercase Letter 4
 
0.6%
Math Symbol 2
 
0.3%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 51
 
7.5%
교 48
 
7.1%
초 32
 
4.7%
리 16
 
2.4%
신 14
 
2.1%
원 14
 
2.1%
산 13
 
1.9%
구 12
 
1.8%
한 11
 
1.6%
동 10
 
1.5%
Other values (186) 457
67.4%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
S 1
25.0%
G 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
1 3
33.3%
3 2
22.2%
Space Separator
ValueCountFrequency (%)
20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 678
94.7%
Common 34
 
4.7%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 51
 
7.5%
교 48
 
7.1%
초 32
 
4.7%
리 16
 
2.4%
신 14
 
2.1%
원 14
 
2.1%
산 13
 
1.9%
구 12
 
1.8%
한 11
 
1.6%
동 10
 
1.5%
Other values (186) 457
67.4%
Common
ValueCountFrequency (%)
20
58.8%
2 4
 
11.8%
1 3
 
8.8%
3 2
 
5.9%
~ 2
 
5.9%
@ 1
 
2.9%
) 1
 
2.9%
( 1
 
2.9%
Latin
ValueCountFrequency (%)
I 1
25.0%
C 1
25.0%
S 1
25.0%
G 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 678
94.7%
ASCII 38
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
앞 51
 
7.5%
교 48
 
7.1%
초 32
 
4.7%
리 16
 
2.4%
신 14
 
2.1%
원 14
 
2.1%
산 13
 
1.9%
구 12
 
1.8%
한 11
 
1.6%
동 10
 
1.5%
Other values (186) 457
67.4%
ASCII
ValueCountFrequency (%)
20
52.6%
2 4
 
10.5%
1 3
 
7.9%
3 2
 
5.3%
~ 2
 
5.3%
@ 1
 
2.6%
) 1
 
2.6%
( 1
 
2.6%
I 1
 
2.6%
C 1
 
2.6%
Other values (2) 2
 
5.3%

위치
Text

Distinct151
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T14:32:26.107463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length11.907895
Min length6

Characters and Unicode

Total characters1810
Distinct characters153
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)98.7%

Sample

1st row평창동 187-2
2nd row신영동 20-1
3rd row신영동 128-2 ~ 196-4
4th row예장동 8-3 앞
5th row장충동2가 173-7 앞
ValueCountFrequency (%)
앞 68
 
15.3%
21
 
4.7%
∼ 9
 
2.0%
정릉동 5
 
1.1%
반포동 4
 
0.9%
독산동 3
 
0.7%
한남동 3
 
0.7%
휘경동 3
 
0.7%
전농동 3
 
0.7%
이태원동 3
 
0.7%
Other values (282) 323
72.6%
2023-12-12T14:32:26.554921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293
16.2%
1 150
 
8.3%
동 147
 
8.1%
- 121
 
6.7%
2 100
 
5.5%
앞 69
 
3.8%
7 65
 
3.6%
5 60
 
3.3%
8 57
 
3.1%
0 57
 
3.1%
Other values (143) 691
38.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 700
38.7%
Other Letter 654
36.1%
Space Separator 293
16.2%
Dash Punctuation 121
 
6.7%
Math Symbol 34
 
1.9%
Uppercase Letter 4
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 147
22.5%
앞 69
 
10.6%
신 24
 
3.7%
산 19
 
2.9%
가 15
 
2.3%
로 14
 
2.1%
정 14
 
2.1%
상 9
 
1.4%
곡 8
 
1.2%
원 8
 
1.2%
Other values (124) 327
50.0%
Decimal Number
ValueCountFrequency (%)
1 150
21.4%
2 100
14.3%
7 65
9.3%
5 60
 
8.6%
8 57
 
8.1%
0 57
 
8.1%
3 56
 
8.0%
4 55
 
7.9%
9 51
 
7.3%
6 49
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
C 1
25.0%
I 1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 24
70.6%
∼ 10
29.4%
Space Separator
ValueCountFrequency (%)
293
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1152
63.6%
Hangul 654
36.1%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 147
22.5%
앞 69
 
10.6%
신 24
 
3.7%
산 19
 
2.9%
가 15
 
2.3%
로 14
 
2.1%
정 14
 
2.1%
상 9
 
1.4%
곡 8
 
1.2%
원 8
 
1.2%
Other values (124) 327
50.0%
Common
ValueCountFrequency (%)
293
25.4%
1 150
13.0%
- 121
10.5%
2 100
 
8.7%
7 65
 
5.6%
5 60
 
5.2%
8 57
 
4.9%
0 57
 
4.9%
3 56
 
4.9%
4 55
 
4.8%
Other values (6) 138
12.0%
Latin
ValueCountFrequency (%)
A 2
50.0%
C 1
25.0%
I 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1146
63.3%
Hangul 654
36.1%
Math Operators 10
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293
25.6%
1 150
13.1%
- 121
10.6%
2 100
 
8.7%
7 65
 
5.7%
5 60
 
5.2%
8 57
 
5.0%
0 57
 
5.0%
3 56
 
4.9%
4 55
 
4.8%
Other values (8) 132
11.5%
Hangul
ValueCountFrequency (%)
동 147
22.5%
앞 69
 
10.6%
신 24
 
3.7%
산 19
 
2.9%
가 15
 
2.3%
로 14
 
2.1%
정 14
 
2.1%
상 9
 
1.4%
곡 8
 
1.2%
원 8
 
1.2%
Other values (124) 327
50.0%
Math Operators
ValueCountFrequency (%)
∼ 10
100.0%

노선명
Text

Distinct95
Distinct (%)62.9%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-12T14:32:26.859058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.0397351
Min length1

Characters and Unicode

Total characters610
Distinct characters128
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)47.0%

Sample

1st row평창문화로
2nd row세검정로 진흥로
3rd row세검정로
4th row소파로
5th row동호로
ValueCountFrequency (%)
남부순환로 9
 
5.8%
서부간선도로 8
 
5.2%
동일로 6
 
3.9%
녹사평대로 6
 
3.9%
양재대로 4
 
2.6%
제물포로 4
 
2.6%
정릉로 4
 
2.6%
헌릉로 4
 
2.6%
고산자로 3
 
1.9%
한남대로 3
 
1.9%
Other values (87) 103
66.9%
2023-12-12T14:32:27.349817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 128
 
21.0%
부 22
 
3.6%
대 22
 
3.6%
길 21
 
3.4%
동 16
 
2.6%
서 15
 
2.5%
선 14
 
2.3%
남 13
 
2.1%
고 12
 
2.0%
도 11
 
1.8%
Other values (118) 336
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 594
97.4%
Decimal Number 7
 
1.1%
Space Separator 3
 
0.5%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 128
 
21.5%
부 22
 
3.7%
대 22
 
3.7%
길 21
 
3.5%
동 16
 
2.7%
서 15
 
2.5%
선 14
 
2.4%
남 13
 
2.2%
고 12
 
2.0%
도 11
 
1.9%
Other values (111) 320
53.9%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 2
28.6%
4 2
28.6%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 594
97.4%
Common 16
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 128
 
21.5%
부 22
 
3.7%
대 22
 
3.7%
길 21
 
3.5%
동 16
 
2.7%
서 15
 
2.5%
선 14
 
2.4%
남 13
 
2.2%
고 12
 
2.0%
도 11
 
1.9%
Other values (111) 320
53.9%
Common
ValueCountFrequency (%)
3
18.8%
1 3
18.8%
( 2
12.5%
) 2
12.5%
2 2
12.5%
4 2
12.5%
- 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 594
97.4%
ASCII 16
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 128
 
21.5%
부 22
 
3.7%
대 22
 
3.7%
길 21
 
3.5%
동 16
 
2.7%
서 15
 
2.5%
선 14
 
2.4%
남 13
 
2.2%
고 12
 
2.0%
도 11
 
1.9%
Other values (111) 320
53.9%
ASCII
ValueCountFrequency (%)
3
18.8%
1 3
18.8%
( 2
12.5%
) 2
12.5%
2 2
12.5%
4 2
12.5%
- 2
12.5%

Interactions

2023-12-12T14:32:23.836029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:32:27.467536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리기관노선명
연번1.0000.9800.963
관리기관0.9801.0000.993
노선명0.9630.9931.000
2023-12-12T14:32:27.577331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리기관
연번1.0000.844
관리기관0.8441.000

Missing values

2023-12-12T14:32:24.021791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:32:24.166924image/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

연번관리기관보도육교명위치노선명
01종로구청서울예고앞평창동 187-2평창문화로
12종로구청신영로타리신영동 20-1세검정로 진흥로
23종로구청세검신영동 128-2 ~ 196-4세검정로
34중구청리라초교앞예장동 8-3 앞소파로
45중구청충무초교앞장충동2가 173-7 앞동호로
56용산구청한강초교앞한강로3가 57 앞한강대로
67용산구청남산3호터널이태원동 685녹사평대로
78용산구청남산2호터널이태원동 488녹사평대로
89용산구청한남초교앞한남동 725-14한남대로
910용산구청한남오거리한남동 707-41한남대로
연번관리기관보도육교명위치노선명
142143송파구청방이2보행자 전용교량송파2동 166 삼익A ~ 가락동 2-11오금로
143144강동구청신암암사동 459-2 ∼ 신암중학교고덕동길
144145강동구청고덕고덕동 287 ∼ 고덕동 296샘터길
145146강동구청한영상일동 171 앞방아다리길
146147강동구청천동천호동 121-91 ∼ 길동 371-1성내길
147148강동구청암사암사동 507-4 앞고덕동길
148149강동구청리엔강일동 707~717고덕천
149150강동구청게내강일동 714고덕천
150151강동구청강일강일동 673-1 ~ 685아리수로
151152강동구청숲길교상일동 산43구천면로