Overview

Dataset statistics

Number of variables4
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory34.1 B

Variable types

Categorical3
Text1

Dataset

Description국립공원 LOD 공간데이터 테이블 목록 데이터입니다. 구성하고있는 테이블, 컬럼, 참조형식, 데이터 형식 등 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15118945/fileData.do

Reproduction

Analysis started2023-12-12 10:14:53.055235
Analysis finished2023-12-12 10:14:53.419744
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

테이블명
Categorical

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size636.0 B
RASTER_INFO
14 
GEOMETRY_COLUMNS
12 
THEMES
11 
PATHS
8 
PYRAMID_INFO
7 
Other values (2)
11 

Length

Max length16
Median length12
Mean length10.698413
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
RASTER_INFO 14
22.2%
GEOMETRY_COLUMNS 12
19.0%
THEMES 11
17.5%
PATHS 8
12.7%
PYRAMID_INFO 7
11.1%
GEOMETRY_LODS 6
9.5%
PATHREGISTRY 5
 
7.9%

Length

2023-12-12T19:14:53.511065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:14:53.642814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
raster_info 14
22.2%
geometry_columns 12
19.0%
themes 11
17.5%
paths 8
12.7%
pyramid_info 7
11.1%
geometry_lods 6
9.5%
pathregistry 5
 
7.9%

컬럼명
Text

Distinct50
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T19:14:53.939575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.7619048
Min length2

Characters and Unicode

Total characters489
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)66.7%

Sample

1st rowF_TABLE_CATALOG
2nd rowF_TABLE_SCHEMA
3rd rowF_TABLE_NAME
4th rowF_GEOMETRY_COLUMN
5th rowG_TABLE_CATALOG
ValueCountFrequency (%)
miny 3
 
4.8%
minx 3
 
4.8%
maxy 3
 
4.8%
owner 3
 
4.8%
maxx 3
 
4.8%
raster_id 2
 
3.2%
srid 2
 
3.2%
theme_id 2
 
3.2%
bit_encode_value 1
 
1.6%
link_id 1
 
1.6%
Other values (40) 40
63.5%
2023-12-12T19:14:54.424021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 55
 
11.2%
I 41
 
8.4%
_ 40
 
8.2%
T 36
 
7.4%
M 35
 
7.2%
N 34
 
7.0%
A 34
 
7.0%
R 25
 
5.1%
D 24
 
4.9%
L 23
 
4.7%
Other values (16) 142
29.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 449
91.8%
Connector Punctuation 40
 
8.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 55
12.2%
I 41
 
9.1%
T 36
 
8.0%
M 35
 
7.8%
N 34
 
7.6%
A 34
 
7.6%
R 25
 
5.6%
D 24
 
5.3%
L 23
 
5.1%
O 23
 
5.1%
Other values (15) 119
26.5%
Connector Punctuation
ValueCountFrequency (%)
_ 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 449
91.8%
Common 40
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 55
12.2%
I 41
 
9.1%
T 36
 
8.0%
M 35
 
7.8%
N 34
 
7.6%
A 34
 
7.6%
R 25
 
5.6%
D 24
 
5.3%
L 23
 
5.1%
O 23
 
5.1%
Other values (15) 119
26.5%
Common
ValueCountFrequency (%)
_ 40
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 55
 
11.2%
I 41
 
8.4%
_ 40
 
8.2%
T 36
 
7.4%
M 35
 
7.2%
N 34
 
7.0%
A 34
 
7.0%
R 25
 
5.1%
D 24
 
4.9%
L 23
 
4.7%
Other values (16) 142
29.0%

데이터타입
Categorical

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
NUMBER(38)
26 
NUMBER(38,8)
21 
VARCHAR2(32)
14 
LONG RAW
 
1
VARCHAR2(15)
 
1

Length

Max length12
Median length12
Mean length11.111111
Min length8

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st rowVARCHAR2(32)
2nd rowVARCHAR2(32)
3rd rowVARCHAR2(32)
4th rowVARCHAR2(32)
5th rowVARCHAR2(32)

Common Values

ValueCountFrequency (%)
NUMBER(38) 26
41.3%
NUMBER(38,8) 21
33.3%
VARCHAR2(32) 14
22.2%
LONG RAW 1
 
1.6%
VARCHAR2(15) 1
 
1.6%

Length

2023-12-12T19:14:54.598412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:14:54.735599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
number(38 26
40.6%
number(38,8 21
32.8%
varchar2(32 14
21.9%
long 1
 
1.6%
raw 1
 
1.6%
varchar2(15 1
 
1.6%

참조형식
Categorical

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
Not Null
46 
<NA>
10 
PK1
5 
PK2
 
1
PK3
 
1

Length

Max length8
Median length8
Mean length6.8095238
Min length3

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st rowPK1
2nd rowPK2
3rd rowPK3
4th rowNot Null
5th row<NA>

Common Values

ValueCountFrequency (%)
Not Null 46
73.0%
<NA> 10
 
15.9%
PK1 5
 
7.9%
PK2 1
 
1.6%
PK3 1
 
1.6%

Length

2023-12-12T19:14:54.895760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:14:55.034457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
not 46
42.2%
null 46
42.2%
na 10
 
9.2%
pk1 5
 
4.6%
pk2 1
 
0.9%
pk3 1
 
0.9%

Correlations

2023-12-12T19:14:55.142231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
테이블명컬럼명데이터타입참조형식
테이블명1.0000.0000.4550.000
컬럼명0.0001.0001.0000.985
데이터타입0.4551.0001.0000.325
참조형식0.0000.9850.3251.000
2023-12-12T19:14:55.244226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
테이블명데이터타입참조형식
테이블명1.0000.3050.000
데이터타입0.3051.0000.127
참조형식0.0000.1271.000
2023-12-12T19:14:55.367738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
테이블명데이터타입참조형식
테이블명1.0000.3050.000
데이터타입0.3051.0000.127
참조형식0.0000.1271.000

Missing values

2023-12-12T19:14:53.271493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:14:53.371401image/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

테이블명컬럼명데이터타입참조형식
0GEOMETRY_COLUMNSF_TABLE_CATALOGVARCHAR2(32)PK1
1GEOMETRY_COLUMNSF_TABLE_SCHEMAVARCHAR2(32)PK2
2GEOMETRY_COLUMNSF_TABLE_NAMEVARCHAR2(32)PK3
3GEOMETRY_COLUMNSF_GEOMETRY_COLUMNVARCHAR2(32)Not Null
4GEOMETRY_COLUMNSG_TABLE_CATALOGVARCHAR2(32)<NA>
5GEOMETRY_COLUMNSG_TABLE_SCHEMAVARCHAR2(32)Not Null
6GEOMETRY_COLUMNSG_TABLE_NAMEVARCHAR2(32)Not Null
7GEOMETRY_COLUMNSSTORAGE_TYPENUMBER(38)Not Null
8GEOMETRY_COLUMNSGEOMETRY_TYPENUMBER(38)Not Null
9GEOMETRY_COLUMNSCOORD_DIMENSIONNUMBER(38)Not Null
테이블명컬럼명데이터타입참조형식
53THEMESVLINKNUMBER(38)<NA>
54THEMESNLINKNUMBER(38)<NA>
55THEMESBIT_ENCODE_VALUENUMBER(38)<NA>
56PYRAMID_INFORASTER_IDNUMBER(38)Not Null
57PYRAMID_INFOLVLNUMBER(38)Not Null
58PYRAMID_INFORESOLUTIONNUMBER(38,8)Not Null
59PYRAMID_INFOMINXNUMBER(38,8)Not Null
60PYRAMID_INFOMINYNUMBER(38,8)Not Null
61PYRAMID_INFOMAXXNUMBER(38,8)Not Null
62PYRAMID_INFOMAXYNUMBER(38,8)Not Null