Overview

Dataset statistics

Number of variables5
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory43.1 B

Variable types

Text3
Categorical2

Dataset

Description전라남도 순천시 지적측량기준점 데이터입니다. 점종류(삼각보조점/삼각점), 점명칭, 원점, 소재지 등의 항목을 제공합니다.
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15063599/fileData.do

Alerts

원점 has constant value ""Constant
점명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:00:36.415350
Analysis finished2023-12-12 19:00:37.017816
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct35
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T04:00:37.245194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.3095238
Min length4

Characters and Unicode

Total characters265
Distinct characters67
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)69.0%

Sample

1st row별량면 죽산리
2nd row주암면 요곡리
3rd row송광면 이읍리
4th row해룡면 복성리
5th row해룡면 신대리
ValueCountFrequency (%)
별량면 9
 
12.0%
주암면 7
 
9.3%
해룡면 5
 
6.7%
연향동 3
 
4.0%
낙안면 3
 
4.0%
상사면 2
 
2.7%
승주읍 2
 
2.7%
응령리 2
 
2.7%
봉림리 2
 
2.7%
대구리 2
 
2.7%
Other values (35) 38
50.7%
2023-12-13T04:00:37.928413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
15.8%
리 33
 
12.5%
면 31
 
11.7%
별 9
 
3.4%
주 9
 
3.4%
동 9
 
3.4%
량 9
 
3.4%
곡 7
 
2.6%
암 7
 
2.6%
해 5
 
1.9%
Other values (57) 104
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
84.2%
Space Separator 42
 
15.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 33
 
14.8%
면 31
 
13.9%
별 9
 
4.0%
주 9
 
4.0%
동 9
 
4.0%
량 9
 
4.0%
곡 7
 
3.1%
암 7
 
3.1%
해 5
 
2.2%
룡 5
 
2.2%
Other values (56) 99
44.4%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
84.2%
Common 42
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 33
 
14.8%
면 31
 
13.9%
별 9
 
4.0%
주 9
 
4.0%
동 9
 
4.0%
량 9
 
4.0%
곡 7
 
3.1%
암 7
 
3.1%
해 5
 
2.2%
룡 5
 
2.2%
Other values (56) 99
44.4%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
84.2%
ASCII 42
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
100.0%
Hangul
ValueCountFrequency (%)
리 33
 
14.8%
면 31
 
13.9%
별 9
 
4.0%
주 9
 
4.0%
동 9
 
4.0%
량 9
 
4.0%
곡 7
 
3.1%
암 7
 
3.1%
해 5
 
2.2%
룡 5
 
2.2%
Other values (56) 99
44.4%

점종류
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
삼각보조점
29 
삼각점
13 

Length

Max length5
Median length5
Mean length4.3809524
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
삼각보조점 29
69.0%
삼각점 13
31.0%

Length

2023-12-13T04:00:38.183429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:00:38.392092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼각보조점 29
69.0%
삼각점 13
31.0%

점명칭
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T04:00:38.732508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.4285714
Min length2

Characters and Unicode

Total characters144
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row보102
2nd row보104
3rd row보109
4th row보111
5th row보113
ValueCountFrequency (%)
보102 1
 
2.4%
전남21 1
 
2.4%
전남41 1
 
2.4%
보80 1
 
2.4%
보91 1
 
2.4%
보93 1
 
2.4%
보96 1
 
2.4%
보98 1
 
2.4%
보99 1
 
2.4%
전남20 1
 
2.4%
Other values (32) 32
76.2%
2023-12-13T04:00:39.323093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 29
20.1%
1 17
11.8%
2 14
9.7%
전 13
9.0%
남 13
9.0%
3 11
 
7.6%
9 9
 
6.2%
0 8
 
5.6%
5 7
 
4.9%
7 7
 
4.9%
Other values (3) 16
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
61.8%
Other Letter 55
38.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
19.1%
2 14
15.7%
3 11
12.4%
9 9
10.1%
0 8
9.0%
5 7
7.9%
7 7
7.9%
4 7
7.9%
8 5
 
5.6%
6 4
 
4.5%
Other Letter
ValueCountFrequency (%)
보 29
52.7%
전 13
23.6%
남 13
23.6%

Most occurring scripts

ValueCountFrequency (%)
Common 89
61.8%
Hangul 55
38.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.1%
2 14
15.7%
3 11
12.4%
9 9
10.1%
0 8
9.0%
5 7
7.9%
7 7
7.9%
4 7
7.9%
8 5
 
5.6%
6 4
 
4.5%
Hangul
ValueCountFrequency (%)
보 29
52.7%
전 13
23.6%
남 13
23.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
61.8%
Hangul 55
38.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 29
52.7%
전 13
23.6%
남 13
23.6%
ASCII
ValueCountFrequency (%)
1 17
19.1%
2 14
15.7%
3 11
12.4%
9 9
10.1%
0 8
9.0%
5 7
7.9%
7 7
7.9%
4 7
7.9%
8 5
 
5.6%
6 4
 
4.5%

원점
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
중부
42 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중부 42
100.0%

Length

2023-12-13T04:00:39.560178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:00:39.755116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중부 42
100.0%

소재지
Text

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T04:00:40.219223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length11.428571
Min length7

Characters and Unicode

Total characters480
Distinct characters78
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

Unique40 ?
Unique (%)95.2%

Sample

1st row별량면 죽산리 산8
2nd row주암면 요곡리 201
3rd row송광면 이읍리 산124
4th row해룡면 복성리 106-4
5th row해룡면 신대리 산56-8
ValueCountFrequency (%)
별량면 9
 
7.7%
주암면 7
 
6.0%
해룡면 5
 
4.3%
연향동 3
 
2.6%
낙안면 3
 
2.6%
선월리 2
 
1.7%
승주읍 2
 
1.7%
서면 2
 
1.7%
봉림리 2
 
1.7%
응령리 2
 
1.7%
Other values (75) 80
68.4%
2023-12-13T04:00:41.022415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
15.6%
리 33
 
6.9%
면 31
 
6.5%
산 26
 
5.4%
- 25
 
5.2%
1 24
 
5.0%
4 19
 
4.0%
2 17
 
3.5%
3 15
 
3.1%
0 14
 
2.9%
Other values (68) 201
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 245
51.0%
Decimal Number 135
28.1%
Space Separator 75
 
15.6%
Dash Punctuation 25
 
5.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 33
 
13.5%
면 31
 
12.7%
산 26
 
10.6%
량 9
 
3.7%
동 9
 
3.7%
별 9
 
3.7%
주 9
 
3.7%
암 7
 
2.9%
곡 7
 
2.9%
해 5
 
2.0%
Other values (56) 100
40.8%
Decimal Number
ValueCountFrequency (%)
1 24
17.8%
4 19
14.1%
2 17
12.6%
3 15
11.1%
0 14
10.4%
5 14
10.4%
8 11
8.1%
6 9
 
6.7%
7 7
 
5.2%
9 5
 
3.7%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 245
51.0%
Common 235
49.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 33
 
13.5%
면 31
 
12.7%
산 26
 
10.6%
량 9
 
3.7%
동 9
 
3.7%
별 9
 
3.7%
주 9
 
3.7%
암 7
 
2.9%
곡 7
 
2.9%
해 5
 
2.0%
Other values (56) 100
40.8%
Common
ValueCountFrequency (%)
75
31.9%
- 25
 
10.6%
1 24
 
10.2%
4 19
 
8.1%
2 17
 
7.2%
3 15
 
6.4%
0 14
 
6.0%
5 14
 
6.0%
8 11
 
4.7%
6 9
 
3.8%
Other values (2) 12
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 245
51.0%
ASCII 235
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
31.9%
- 25
 
10.6%
1 24
 
10.2%
4 19
 
8.1%
2 17
 
7.2%
3 15
 
6.4%
0 14
 
6.0%
5 14
 
6.0%
8 11
 
4.7%
6 9
 
3.8%
Other values (2) 12
 
5.1%
Hangul
ValueCountFrequency (%)
리 33
 
13.5%
면 31
 
12.7%
산 26
 
10.6%
량 9
 
3.7%
동 9
 
3.7%
별 9
 
3.7%
주 9
 
3.7%
암 7
 
2.9%
곡 7
 
2.9%
해 5
 
2.0%
Other values (56) 100
40.8%

Correlations

2023-12-13T04:00:41.204780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분점종류점명칭소재지
구분1.0000.8701.0001.000
점종류0.8701.0001.0001.000
점명칭1.0001.0001.0001.000
소재지1.0001.0001.0001.000

Missing values

2023-12-13T04:00:36.784543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:00:36.958536image/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

구분점종류점명칭원점소재지
0별량면 죽산리삼각보조점보102중부별량면 죽산리 산8
1주암면 요곡리삼각보조점보104중부주암면 요곡리 201
2송광면 이읍리삼각보조점보109중부송광면 이읍리 산124
3해룡면 복성리삼각보조점보111중부해룡면 복성리 106-4
4해룡면 신대리삼각보조점보113중부해룡면 신대리 산56-8
5해룡면 선월리삼각보조점보114중부해룡면 선월리 744-3
6석현동삼각보조점보12중부석현동 903
7가곡동삼각보조점보18중부가곡동 산125-1
8조례동삼각보조점보22중부조례동 480-29
9별량면 학산리삼각보조점보25중부별량면 학산리 125
구분점종류점명칭원점소재지
32서면 선평리삼각점전남25중부서면 선평리 산2
33서면 압곡리삼각점전남26중부서면 압곡리 산149-19
34해룡면 대안리삼각점전남27중부해룡면 대안리 산4
35낙안면 용능리삼각점전남32중부낙안면 용능리 산80
36주암면 고산리삼각점전남35중부주암면 고산리 산64-1
37주암면 문길리삼각점전남37중부주암면 문길리 산56
38승주읍 신성리삼각점전남38중부승주읍 신성리 산286
39승주읍 평중리삼각점전남39중부승주읍 평중리 산5
40별량면 송기리삼각점전남41중부별량면 송기리 산74-2
41별량면 마산리삼각점전남42중부별량면 마산리 산104