Overview

Dataset statistics

Number of variables5
Number of observations28
Missing cells66
Missing cells (%)47.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory46.7 B

Variable types

Unsupported3
Text2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21695/S/1/datasetView.do

Alerts

Unnamed: 0 has 28 (100.0%) missing valuesMissing
Unnamed: 1 has 28 (100.0%) missing valuesMissing
Unnamed: 3 has 4 (14.3%) missing valuesMissing
Unnamed: 4 has 6 (21.4%) missing valuesMissing
안심귀갓길 경로 기반 링크 데이터 has unique valuesUnique
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 07:46:59.780153
Analysis finished2023-12-11 07:47:00.318037
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing28
Missing (%)100.0%
Memory size384.0 B

안심귀갓길 경로 기반 링크 데이터
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T16:47:00.517300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.2142857
Min length2

Characters and Unicode

Total characters174
Distinct characters68
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row항목명
2nd row링크 WKT
3rd row링크 ID
4th row링크 유형 코드
5th row시작노드 ID
ValueCountFrequency (%)
링크 4
 
8.2%
id 4
 
8.2%
안심귀갓길 4
 
8.2%
코드 3
 
6.1%
시설물 2
 
4.1%
안내판 2
 
4.1%
항목명 1
 
2.0%
가로등 1
 
2.0%
위치신고 1
 
2.0%
기타 1
 
2.0%
Other values (26) 26
53.1%
2023-12-11T16:47:00.985949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
12.1%
안 10
 
5.7%
명 6
 
3.4%
길 6
 
3.4%
심 6
 
3.4%
드 5
 
2.9%
시 5
 
2.9%
갓 5
 
2.9%
귀 5
 
2.9%
I 4
 
2.3%
Other values (58) 101
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135
77.6%
Space Separator 21
 
12.1%
Uppercase Letter 15
 
8.6%
Decimal Number 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 10
 
7.4%
명 6
 
4.4%
길 6
 
4.4%
심 6
 
4.4%
드 5
 
3.7%
시 5
 
3.7%
갓 5
 
3.7%
귀 5
 
3.7%
링 4
 
3.0%
크 4
 
3.0%
Other values (48) 79
58.5%
Uppercase Letter
ValueCountFrequency (%)
I 4
26.7%
D 4
26.7%
T 2
13.3%
C 2
13.3%
V 1
 
6.7%
K 1
 
6.7%
W 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135
77.6%
Common 24
 
13.8%
Latin 15
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 10
 
7.4%
명 6
 
4.4%
길 6
 
4.4%
심 6
 
4.4%
드 5
 
3.7%
시 5
 
3.7%
갓 5
 
3.7%
귀 5
 
3.7%
링 4
 
3.0%
크 4
 
3.0%
Other values (48) 79
58.5%
Latin
ValueCountFrequency (%)
I 4
26.7%
D 4
26.7%
T 2
13.3%
C 2
13.3%
V 1
 
6.7%
K 1
 
6.7%
W 1
 
6.7%
Common
ValueCountFrequency (%)
21
87.5%
1 2
 
8.3%
2 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135
77.6%
ASCII 39
 
22.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
53.8%
I 4
 
10.3%
D 4
 
10.3%
T 2
 
5.1%
1 2
 
5.1%
C 2
 
5.1%
2 1
 
2.6%
V 1
 
2.6%
K 1
 
2.6%
W 1
 
2.6%
Hangul
ValueCountFrequency (%)
안 10
 
7.4%
명 6
 
4.4%
길 6
 
4.4%
심 6
 
4.4%
드 5
 
3.7%
시 5
 
3.7%
갓 5
 
3.7%
귀 5
 
3.7%
링 4
 
3.0%
크 4
 
3.0%
Other values (48) 79
58.5%

Unnamed: 3
Text

MISSING 

Distinct23
Distinct (%)95.8%
Missing4
Missing (%)14.3%
Memory size356.0 B
2023-12-11T16:47:01.353743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length147
Median length36
Mean length23.666667
Min length2

Characters and Unicode

Total characters568
Distinct characters149
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row설명
2nd rowMULTILINESTRING(경도 위도,경도 위도) *경도 : X좌표, 동, 세로선 *위도 : Y좌표, 북, 가로선 *소수점 6자리 이상 10자리 이하까지 작성 *ESPG:4326 – WGS 84 좌표계 *경도와 위도 사이는 띄어쓰기, 쉼표 뒤는 띄어쓰기 없음
3rd row안심귀갓길 아이디_L001 ~ *각 안심귀갓길 객체마다 01부터 다시 시작
4th row숫자만 입력 201 일반 보도 202 계단 203 터널 204 교량 205 고가로(육교 등) 206 지하로
5th row해당 링크와 연결된 시작노드 ID
ValueCountFrequency (%)
개수 8
 
5.8%
입력 6
 
4.3%
4
 
2.9%
숫자만 4
 
2.9%
해당 3
 
2.2%
10자리 3
 
2.2%
안심귀갓길 3
 
2.2%
id 3
 
2.2%
위도 3
 
2.2%
소수점 2
 
1.4%
Other values (90) 100
71.9%
2023-12-11T16:47:01.897938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
 
17.4%
24
 
4.2%
2 14
 
2.5%
수 12
 
2.1%
1 12
 
2.1%
0 12
 
2.1%
자 12
 
2.1%
표 10
 
1.8%
도 9
 
1.6%
, 9
 
1.6%
Other values (139) 355
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
55.3%
Space Separator 101
 
17.8%
Decimal Number 49
 
8.6%
Uppercase Letter 41
 
7.2%
Control 24
 
4.2%
Other Punctuation 21
 
3.7%
Close Punctuation 5
 
0.9%
Open Punctuation 5
 
0.9%
Lowercase Letter 4
 
0.7%
Connector Punctuation 2
 
0.4%
Other values (2) 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 12
 
3.8%
자 12
 
3.8%
표 10
 
3.2%
도 9
 
2.9%
안 9
 
2.9%
개 8
 
2.5%
지 7
 
2.2%
의 6
 
1.9%
입 6
 
1.9%
숫 6
 
1.9%
Other values (101) 229
72.9%
Uppercase Letter
ValueCountFrequency (%)
I 6
14.6%
D 4
9.8%
L 4
9.8%
T 3
 
7.3%
N 3
 
7.3%
E 3
 
7.3%
S 3
 
7.3%
G 3
 
7.3%
C 2
 
4.9%
Y 2
 
4.9%
Other values (7) 8
19.5%
Decimal Number
ValueCountFrequency (%)
2 14
28.6%
1 12
24.5%
0 12
24.5%
6 3
 
6.1%
4 3
 
6.1%
3 3
 
6.1%
5 1
 
2.0%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 9
42.9%
* 7
33.3%
: 4
19.0%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
99
98.0%
  2
 
2.0%
Control
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
– 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
55.3%
Common 209
36.8%
Latin 45
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 12
 
3.8%
자 12
 
3.8%
표 10
 
3.2%
도 9
 
2.9%
안 9
 
2.9%
개 8
 
2.5%
지 7
 
2.2%
의 6
 
1.9%
입 6
 
1.9%
숫 6
 
1.9%
Other values (101) 229
72.9%
Common
ValueCountFrequency (%)
99
47.4%
24
 
11.5%
2 14
 
6.7%
1 12
 
5.7%
0 12
 
5.7%
, 9
 
4.3%
* 7
 
3.3%
) 5
 
2.4%
( 5
 
2.4%
: 4
 
1.9%
Other values (10) 18
 
8.6%
Latin
ValueCountFrequency (%)
I 6
13.3%
x 4
 
8.9%
D 4
 
8.9%
L 4
 
8.9%
T 3
 
6.7%
N 3
 
6.7%
E 3
 
6.7%
S 3
 
6.7%
G 3
 
6.7%
C 2
 
4.4%
Other values (8) 10
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 314
55.3%
ASCII 251
44.2%
None 2
 
0.4%
Punctuation 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
39.4%
24
 
9.6%
2 14
 
5.6%
1 12
 
4.8%
0 12
 
4.8%
, 9
 
3.6%
* 7
 
2.8%
I 6
 
2.4%
) 5
 
2.0%
( 5
 
2.0%
Other values (26) 58
23.1%
Hangul
ValueCountFrequency (%)
수 12
 
3.8%
자 12
 
3.8%
표 10
 
3.2%
도 9
 
2.9%
안 9
 
2.9%
개 8
 
2.5%
지 7
 
2.2%
의 6
 
1.9%
입 6
 
1.9%
숫 6
 
1.9%
Other values (101) 229
72.9%
None
ValueCountFrequency (%)
  2
100.0%
Punctuation
ValueCountFrequency (%)
– 1
100.0%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6
Missing (%)21.4%
Memory size356.0 B

Correlations

2023-12-11T16:47:02.076215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안심귀갓길 경로 기반 링크 데이터Unnamed: 3
안심귀갓길 경로 기반 링크 데이터1.0001.000
Unnamed: 31.0001.000

Missing values

2023-12-11T16:46:59.988660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T16:47:00.133355image/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.
2023-12-11T16:47:00.255771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0Unnamed: 1안심귀갓길 경로 기반 링크 데이터Unnamed: 3Unnamed: 4
0<NA><NA>항목명설명예시
1<NA><NA>링크 WKTMULTILINESTRING(경도 위도,경도 위도) *경도 : X좌표, 동, 세로선 *위도 : Y좌표, 북, 가로선 *소수점 6자리 이상 10자리 이하까지 작성 *ESPG:4326 – WGS 84 좌표계 *경도와 위도 사이는 띄어쓰기, 쉼표 뒤는 띄어쓰기 없음MULTILINESTRING((127.068284 37.543106, 127.068008 37.543204))
2<NA><NA>링크 ID안심귀갓길 아이디_L001 ~ *각 안심귀갓길 객체마다 01부터 다시 시작1121510700_01_L001
3<NA><NA>링크 유형 코드숫자만 입력 201 일반 보도 202 계단 203 터널 204 교량 205 고가로(육교 등) 206 지하로201
4<NA><NA>시작노드 ID해당 링크와 연결된 시작노드 ID1121510700_01_N001
5<NA><NA>종료노드 ID해당 링크와 연결된 종료노드 ID1121510700_01_N002
6<NA><NA>링크 길이단위 : 미터(M) 숫자만 입력, 소수점 2자리, 단위까지 입력26.68
7<NA><NA>시군구 코드십진수 10자리 (행정표준코드 참조)1121500000
8<NA><NA>시군구명<NA>서울특별시 광진구
9<NA><NA>읍면동 코드십진수 10자리 (행정표준코드 참조)1121510700
Unnamed: 0Unnamed: 1안심귀갓길 경로 기반 링크 데이터Unnamed: 3Unnamed: 4
18<NA><NA>기타 시설물기타 시설물 개수NaN
19<NA><NA>부가 시설물숫자만 입력 211 LED 212 로고젝터 213 기타212
20<NA><NA>가로등 유무Y 있음 N 없음N
21<NA><NA>안심귀갓길 ID읍면동코드_xx *xx는 해당 안심귀갓길명 뒤에 붙은 숫자, 숫자 없을 시 임의로 생성1121510700_01
22<NA><NA>안심귀갓길명<NA>광진안심01
23<NA><NA>조성년월숫자만 입력2014
24<NA><NA>세부위치 설명<NA>동일로24길
25<NA><NA>비고특이사항NaN
26<NA><NA>데이터 기준일자현장조사일20220727
27<NA><NA>이미지명링크 ID 와 동일. 확장자까지 입력1121510700_01_L001.jpeg