Overview

Dataset statistics

Number of variables3
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)2.6%
Total size in memory1.0 KiB
Average record size in memory27.4 B

Variable types

Categorical2
Text1

Dataset

Description서울특별시 성동구 내에 설치한 바닥형 보행신호등 설치 현황에 관한 자료입니다. 시설물 설치 위치, 교차로 방향 수 등의 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15064608/fileData.do

Alerts

자치구 has constant value ""Constant
Dataset has 1 (2.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 02:50:36.616080
Analysis finished2023-12-12 02:50:36.911365
Duration0.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
성동구
39 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 39
100.0%

Length

2023-12-12T11:50:37.001361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:50:37.130290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성동구 39
100.0%

설치위치
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T11:50:37.339616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.2307692
Min length5

Characters and Unicode

Total characters360
Distinct characters105
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

Unique37 ?
Unique (%)94.9%

Sample

1st row무학여고 교차로
2nd row무학여고 교차로
3rd row성동구청 앞
4th row왕십리역4번출구
5th row경일초등학교 정문 앞
ValueCountFrequency (%)
앞 7
 
9.7%
왕십리역 5
 
6.9%
정문 4
 
5.6%
교차로 4
 
5.6%
후문 3
 
4.2%
무학여고 2
 
2.8%
마장동주민센터 2
 
2.8%
경동초등학교 2
 
2.8%
오거리(9,10 1
 
1.4%
오거리(8,9 1
 
1.4%
Other values (41) 41
56.9%
2023-12-12T11:50:37.697016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
9.4%
교 13
 
3.6%
리 12
 
3.3%
문 12
 
3.3%
초 10
 
2.8%
역 9
 
2.5%
동 9
 
2.5%
( 9
 
2.5%
) 9
 
2.5%
정 8
 
2.2%
Other values (95) 235
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 282
78.3%
Space Separator 34
 
9.4%
Decimal Number 20
 
5.6%
Open Punctuation 9
 
2.5%
Close Punctuation 9
 
2.5%
Other Punctuation 6
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 13
 
4.6%
리 12
 
4.3%
문 12
 
4.3%
초 10
 
3.5%
역 9
 
3.2%
동 9
 
3.2%
정 8
 
2.8%
주 7
 
2.5%
앞 7
 
2.5%
차 6
 
2.1%
Other values (82) 189
67.0%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
0 2
 
10.0%
9 2
 
10.0%
3 2
 
10.0%
2 2
 
10.0%
8 2
 
10.0%
4 2
 
10.0%
5 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
@ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 282
78.3%
Common 78
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 13
 
4.6%
리 12
 
4.3%
문 12
 
4.3%
초 10
 
3.5%
역 9
 
3.2%
동 9
 
3.2%
정 8
 
2.8%
주 7
 
2.5%
앞 7
 
2.5%
차 6
 
2.1%
Other values (82) 189
67.0%
Common
ValueCountFrequency (%)
34
43.6%
( 9
 
11.5%
) 9
 
11.5%
1 7
 
9.0%
, 5
 
6.4%
0 2
 
2.6%
9 2
 
2.6%
3 2
 
2.6%
2 2
 
2.6%
8 2
 
2.6%
Other values (3) 4
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 282
78.3%
ASCII 78
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
43.6%
( 9
 
11.5%
) 9
 
11.5%
1 7
 
9.0%
, 5
 
6.4%
0 2
 
2.6%
9 2
 
2.6%
3 2
 
2.6%
2 2
 
2.6%
8 2
 
2.6%
Other values (3) 4
 
5.1%
Hangul
ValueCountFrequency (%)
교 13
 
4.6%
리 12
 
4.3%
문 12
 
4.3%
초 10
 
3.5%
역 9
 
3.2%
동 9
 
3.2%
정 8
 
2.8%
주 7
 
2.5%
앞 7
 
2.5%
차 6
 
2.1%
Other values (82) 189
67.0%

교차로방향수
Categorical

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
4지
16 
3지
12 
단일로
6 
5지
5 

Length

Max length3
Median length2
Mean length2.1538462
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4지
2nd row4지
3rd row단일로
4th row3지
5th row4지

Common Values

ValueCountFrequency (%)
4지 16
41.0%
3지 12
30.8%
단일로 6
 
15.4%
5지 5
 
12.8%

Length

2023-12-12T11:50:37.842766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:50:37.956075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4지 16
41.0%
3지 12
30.8%
단일로 6
 
15.4%
5지 5
 
12.8%

Correlations

2023-12-12T11:50:38.037318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치위치교차로방향수
설치위치1.0001.000
교차로방향수1.0001.000

Missing values

2023-12-12T11:50:36.801124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:50:36.879431image/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

자치구설치위치교차로방향수
0성동구무학여고 교차로4지
1성동구무학여고 교차로4지
2성동구성동구청 앞단일로
3성동구왕십리역4번출구3지
4성동구경일초등학교 정문 앞4지
5성동구옥정초 정문3지
6성동구마장동주민센터 교차로3지
7성동구응봉파출소 앞3지
8성동구금호초 후문3지
9성동구금호파크힐스 후문 앞4지
자치구설치위치교차로방향수
29성동구마장동주민센터(명성연립)4지
30성동구행당초 주변(육교남측)단일로
31성동구교육문화회관단일로
32성동구왕십리역 오거리(9,10)5지
33성동구왕십리역 오거리(8,9)5지
34성동구왕십리역 오거리(3,8)5지
35성동구왕십리역 오거리(2)5지
36성동구왕십리역 오거리(10,11)5지
37성동구경동초등학교 교차로(북측)4지
38성동구경동초등학교 교차로(남측)4지

Duplicate rows

Most frequently occurring

자치구설치위치교차로방향수# duplicates
0성동구무학여고 교차로4지2