Overview

Dataset statistics

Number of variables3
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory828.0 B
Average record size in memory28.6 B

Variable types

Text2
Categorical1

Dataset

Description충청북도 단양군 지적통합관리시스템 DB 추출 데이터로 시스템 내에서 사용하는 지목명칭 및 비고(추가설명), 데이터 기준일자 등의 데이터를 포함하고 있음.
Author충청북도 단양군
URLhttps://www.data.go.kr/data/15089419/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
지목명칭 has unique valuesUnique
비고 has unique valuesUnique

Reproduction

Analysis started2024-04-18 03:02:21.485744
Analysis finished2024-04-18 03:02:22.917490
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지목명칭
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-18T12:02:23.028482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters29
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row무
2nd row전
3rd row답
4th row과
5th row목
ValueCountFrequency (%)
무 1
 
3.4%
철 1
 
3.4%
묘 1
 
3.4%
사 1
 
3.4%
종 1
 
3.4%
원 1
 
3.4%
체 1
 
3.4%
공 1
 
3.4%
수 1
 
3.4%
양 1
 
3.4%
Other values (19) 19
65.5%
2024-04-18T12:02:23.279777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
무 1
 
3.4%
철 1
 
3.4%
묘 1
 
3.4%
사 1
 
3.4%
종 1
 
3.4%
원 1
 
3.4%
체 1
 
3.4%
공 1
 
3.4%
수 1
 
3.4%
양 1
 
3.4%
Other values (19) 19
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 1
 
3.4%
철 1
 
3.4%
묘 1
 
3.4%
사 1
 
3.4%
종 1
 
3.4%
원 1
 
3.4%
체 1
 
3.4%
공 1
 
3.4%
수 1
 
3.4%
양 1
 
3.4%
Other values (19) 19
65.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 1
 
3.4%
철 1
 
3.4%
묘 1
 
3.4%
사 1
 
3.4%
종 1
 
3.4%
원 1
 
3.4%
체 1
 
3.4%
공 1
 
3.4%
수 1
 
3.4%
양 1
 
3.4%
Other values (19) 19
65.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
무 1
 
3.4%
철 1
 
3.4%
묘 1
 
3.4%
사 1
 
3.4%
종 1
 
3.4%
원 1
 
3.4%
체 1
 
3.4%
공 1
 
3.4%
수 1
 
3.4%
양 1
 
3.4%
Other values (19) 19
65.5%

비고
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2024-04-18T12:02:23.443580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.862069
Min length1

Characters and Unicode

Total characters83
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row구분없음
2nd row전
3rd row답
4th row과수원
5th row목장용지
ValueCountFrequency (%)
구분없음 1
 
3.4%
철도용지 1
 
3.4%
묘지 1
 
3.4%
사적지 1
 
3.4%
종교용지 1
 
3.4%
유원지 1
 
3.4%
체육용지 1
 
3.4%
공원 1
 
3.4%
수도용지 1
 
3.4%
양어장 1
 
3.4%
Other values (19) 19
65.5%
2024-04-18T12:02:23.724689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 15
 
18.1%
용 9
 
10.8%
장 4
 
4.8%
도 3
 
3.6%
유 3
 
3.6%
원 3
 
3.6%
구 2
 
2.4%
종 2
 
2.4%
교 2
 
2.4%
공 2
 
2.4%
Other values (34) 38
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 15
 
18.1%
용 9
 
10.8%
장 4
 
4.8%
도 3
 
3.6%
유 3
 
3.6%
원 3
 
3.6%
구 2
 
2.4%
종 2
 
2.4%
교 2
 
2.4%
공 2
 
2.4%
Other values (34) 38
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 15
 
18.1%
용 9
 
10.8%
장 4
 
4.8%
도 3
 
3.6%
유 3
 
3.6%
원 3
 
3.6%
구 2
 
2.4%
종 2
 
2.4%
교 2
 
2.4%
공 2
 
2.4%
Other values (34) 38
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 15
 
18.1%
용 9
 
10.8%
장 4
 
4.8%
도 3
 
3.6%
유 3
 
3.6%
원 3
 
3.6%
구 2
 
2.4%
종 2
 
2.4%
교 2
 
2.4%
공 2
 
2.4%
Other values (34) 38
45.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2022-09-25
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-25
2nd row2022-09-25
3rd row2022-09-25
4th row2022-09-25
5th row2022-09-25

Common Values

ValueCountFrequency (%)
2022-09-25 29
100.0%

Length

2024-04-18T12:02:23.836661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T12:02:23.915485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-25 29
100.0%

Correlations

2024-04-18T12:02:23.962942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목명칭비고
지목명칭1.0001.000
비고1.0001.000

Missing values

2024-04-18T12:02:22.890841image/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

지목명칭비고데이터기준일자
0무구분없음2022-09-25
1전전2022-09-25
2답답2022-09-25
3과과수원2022-09-25
4목목장용지2022-09-25
5임임야2022-09-25
6광광천지2022-09-25
7염염전2022-09-25
8대대2022-09-25
9장공장용지2022-09-25
지목명칭비고데이터기준일자
19유유지2022-09-25
20양양어장2022-09-25
21수수도용지2022-09-25
22공공원2022-09-25
23체체육용지2022-09-25
24원유원지2022-09-25
25종종교용지2022-09-25
26사사적지2022-09-25
27묘묘지2022-09-25
28잡잡종지2022-09-25