Overview

Dataset statistics

Number of variables9
Number of observations27
Missing cells108
Missing cells (%)44.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory76.9 B

Variable types

Unsupported3
Text4
Categorical1
Boolean1

Dataset

Description지적측량시 수평위치측량의 기준으로 사용하기 위하여 국가기준점을 기준으로 하여 정한 기준점정보
Author국토교통부
URLhttps://www.vworld.kr/dtmk/dtmk_ntads_s002.do?dsId=30577

Alerts

Unnamed: 5 has constant value ""Constant
Unnamed: 8 has constant value ""Constant
Unnamed: 1 has 6 (22.2%) missing valuesMissing
Unnamed: 2 has 1 (3.7%) missing valuesMissing
Unnamed: 4 has 5 (18.5%) missing valuesMissing
Unnamed: 5 has 23 (85.2%) missing valuesMissing
Unnamed: 6 has 23 (85.2%) missing valuesMissing
Unnamed: 7 has 24 (88.9%) missing valuesMissing
Unnamed: 8 has 26 (96.3%) missing valuesMissing
테이블정의서 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
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 22:42:35.945109
Analysis finished2024-04-17 22:42:37.201005
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

테이블정의서
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 1
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing6
Missing (%)22.2%
Memory size348.0 B
2024-04-18T07:42:37.322218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length9
Mean length7.5714286
Min length4

Characters and Unicode

Total characters159
Distinct characters26
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row컬럼ID
2nd rowBASE_POINT_NO
3rd rowLAND_LOC_CD
4th rowTRAG_POINT_NM
5th rowWONJUM
ValueCountFrequency (%)
컬럼id 1
 
4.8%
build_gbn 1
 
4.8%
point_y 1
 
4.8%
point_x 1
 
4.8%
y_code 1
 
4.8%
x_code 1
 
4.8%
shape 1
 
4.8%
objectid 1
 
4.8%
col_adm_sect_cd 1
 
4.8%
sgg_oid 1
 
4.8%
Other values (11) 11
52.4%
2024-04-18T07:42:37.659012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 17
 
10.7%
D 16
 
10.1%
O 15
 
9.4%
T 12
 
7.5%
N 11
 
6.9%
I 10
 
6.3%
C 10
 
6.3%
L 9
 
5.7%
E 8
 
5.0%
G 7
 
4.4%
Other values (16) 44
27.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 140
88.1%
Connector Punctuation 17
 
10.7%
Other Letter 2
 
1.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 16
11.4%
O 15
10.7%
T 12
 
8.6%
N 11
 
7.9%
I 10
 
7.1%
C 10
 
7.1%
L 9
 
6.4%
E 8
 
5.7%
G 7
 
5.0%
B 6
 
4.3%
Other values (13) 36
25.7%
Other Letter
ValueCountFrequency (%)
럼 1
50.0%
컬 1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140
88.1%
Common 17
 
10.7%
Hangul 2
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 16
11.4%
O 15
10.7%
T 12
 
8.6%
N 11
 
7.9%
I 10
 
7.1%
C 10
 
7.1%
L 9
 
6.4%
E 8
 
5.7%
G 7
 
5.0%
B 6
 
4.3%
Other values (13) 36
25.7%
Hangul
ValueCountFrequency (%)
럼 1
50.0%
컬 1
50.0%
Common
ValueCountFrequency (%)
_ 17
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 157
98.7%
Hangul 2
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 17
10.8%
D 16
 
10.2%
O 15
 
9.6%
T 12
 
7.6%
N 11
 
7.0%
I 10
 
6.4%
C 10
 
6.4%
L 9
 
5.7%
E 8
 
5.1%
G 7
 
4.5%
Other values (14) 42
26.8%
Hangul
ValueCountFrequency (%)
럼 1
50.0%
컬 1
50.0%

Unnamed: 2
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size348.0 B
2024-04-18T07:42:37.849690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length10
Mean length4.8846154
Min length2

Characters and Unicode

Total characters127
Distinct characters74
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row최민선
2nd row행정업무
3rd row지적삼각점 기본정보
4th row컬럼명
5th row기준점번호
ValueCountFrequency (%)
최민선 1
 
3.6%
행정업무 1
 
3.6%
base_point_no 1
 
3.6%
인덱스키 1
 
3.6%
좌표구분 1
 
3.6%
y포인트 1
 
3.6%
x포인트 1
 
3.6%
y코드 1
 
3.6%
x코드 1
 
3.6%
공간데이터 1
 
3.6%
Other values (18) 18
64.3%
2024-04-18T07:42:38.177945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
치 4
 
3.1%
I 4
 
3.1%
코 4
 
3.1%
드 4
 
3.1%
점 4
 
3.1%
도 4
 
3.1%
원 3
 
2.4%
D 3
 
2.4%
인 3
 
2.4%
지 3
 
2.4%
Other values (64) 91
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
75.6%
Uppercase Letter 25
 
19.7%
Connector Punctuation 3
 
2.4%
Space Separator 2
 
1.6%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 4
 
4.2%
코 4
 
4.2%
드 4
 
4.2%
점 4
 
4.2%
도 4
 
4.2%
원 3
 
3.1%
인 3
 
3.1%
지 3
 
3.1%
구 3
 
3.1%
트 2
 
2.1%
Other values (48) 62
64.6%
Uppercase Letter
ValueCountFrequency (%)
I 4
16.0%
D 3
12.0%
O 3
12.0%
Y 2
8.0%
G 2
8.0%
X 2
8.0%
S 2
8.0%
N 2
8.0%
B 1
 
4.0%
A 1
 
4.0%
Other values (3) 3
12.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
75.6%
Latin 25
 
19.7%
Common 6
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 4
 
4.2%
코 4
 
4.2%
드 4
 
4.2%
점 4
 
4.2%
도 4
 
4.2%
원 3
 
3.1%
인 3
 
3.1%
지 3
 
3.1%
구 3
 
3.1%
트 2
 
2.1%
Other values (48) 62
64.6%
Latin
ValueCountFrequency (%)
I 4
16.0%
D 3
12.0%
O 3
12.0%
Y 2
8.0%
G 2
8.0%
X 2
8.0%
S 2
8.0%
N 2
8.0%
B 1
 
4.0%
A 1
 
4.0%
Other values (3) 3
12.0%
Common
ValueCountFrequency (%)
_ 3
50.0%
2
33.3%
, 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
75.6%
ASCII 31
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
치 4
 
4.2%
코 4
 
4.2%
드 4
 
4.2%
점 4
 
4.2%
도 4
 
4.2%
원 3
 
3.1%
인 3
 
3.1%
지 3
 
3.1%
구 3
 
3.1%
트 2
 
2.1%
Other values (48) 62
64.6%
ASCII
ValueCountFrequency (%)
I 4
12.9%
D 3
9.7%
O 3
9.7%
_ 3
9.7%
Y 2
 
6.5%
G 2
 
6.5%
X 2
 
6.5%
S 2
 
6.5%
2
 
6.5%
N 2
 
6.5%
Other values (6) 6
19.4%

Unnamed: 3
Categorical

Distinct7
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
VARCHAR2
15 
<NA>
5 
INTEGER
2 
NUMBER
2 
테이블ID
 
1
Other values (2)
2 

Length

Max length11
Median length8
Mean length6.8148148
Min length2

Unique

Unique3 ?
Unique (%)11.1%

Sample

1st row<NA>
2nd row테이블ID
3rd row<NA>
4th row타입
5th rowVARCHAR2

Common Values

ValueCountFrequency (%)
VARCHAR2 15
55.6%
<NA> 5
 
18.5%
INTEGER 2
 
7.4%
NUMBER 2
 
7.4%
테이블ID 1
 
3.7%
타입 1
 
3.7%
ST_GEOMETRY 1
 
3.7%

Length

2024-04-18T07:42:38.310547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:42:38.424400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
varchar2 15
55.6%
na 5
 
18.5%
integer 2
 
7.4%
number 2
 
7.4%
테이블id 1
 
3.7%
타입 1
 
3.7%
st_geometry 1
 
3.7%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)18.5%
Memory size348.0 B

Unnamed: 5
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)25.0%
Missing23
Missing (%)85.2%
Memory size186.0 B
False
4 
(Missing)
23 
ValueCountFrequency (%)
False 4
 
14.8%
(Missing) 23
85.2%
2024-04-18T07:42:38.536461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 6
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing23
Missing (%)85.2%
Memory size348.0 B
2024-04-18T07:42:38.664457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row작성일
2nd row테이블명
3rd rowPK/FK
4th rowPK
ValueCountFrequency (%)
작성일 1
25.0%
테이블명 1
25.0%
pk/fk 1
25.0%
pk 1
25.0%
2024-04-18T07:42:38.952123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 3
21.4%
P 2
14.3%
작 1
 
7.1%
성 1
 
7.1%
일 1
 
7.1%
테 1
 
7.1%
이 1
 
7.1%
블 1
 
7.1%
명 1
 
7.1%
/ 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
50.0%
Uppercase Letter 6
42.9%
Other Punctuation 1
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
작 1
14.3%
성 1
14.3%
일 1
14.3%
테 1
14.3%
이 1
14.3%
블 1
14.3%
명 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
50.0%
P 2
33.3%
F 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
50.0%
Latin 6
42.9%
Common 1
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
작 1
14.3%
성 1
14.3%
일 1
14.3%
테 1
14.3%
이 1
14.3%
블 1
14.3%
명 1
14.3%
Latin
ValueCountFrequency (%)
K 3
50.0%
P 2
33.3%
F 1
 
16.7%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
50.0%
Hangul 7
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 3
42.9%
P 2
28.6%
/ 1
 
14.3%
F 1
 
14.3%
Hangul
ValueCountFrequency (%)
작 1
14.3%
성 1
14.3%
일 1
14.3%
테 1
14.3%
이 1
14.3%
블 1
14.3%
명 1
14.3%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing24
Missing (%)88.9%
Memory size348.0 B

Unnamed: 8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing26
Missing (%)96.3%
Memory size348.0 B
2024-04-18T07:42:39.103602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters9
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

Unique1 ?
Unique (%)100.0%

Sample

1st row참조테이블명/비고
ValueCountFrequency (%)
참조테이블명/비고 1
100.0%
2024-04-18T07:42:39.368199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
참 1
11.1%
조 1
11.1%
테 1
11.1%
이 1
11.1%
블 1
11.1%
명 1
11.1%
/ 1
11.1%
비 1
11.1%
고 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Other Punctuation 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
참 1
12.5%
조 1
12.5%
테 1
12.5%
이 1
12.5%
블 1
12.5%
명 1
12.5%
비 1
12.5%
고 1
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
참 1
12.5%
조 1
12.5%
테 1
12.5%
이 1
12.5%
블 1
12.5%
명 1
12.5%
비 1
12.5%
고 1
12.5%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
88.9%
ASCII 1
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
참 1
12.5%
조 1
12.5%
테 1
12.5%
이 1
12.5%
블 1
12.5%
명 1
12.5%
비 1
12.5%
고 1
12.5%
ASCII
ValueCountFrequency (%)
/ 1
100.0%

Correlations

2024-04-18T07:42:39.464933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 6
Unnamed: 11.0001.0001.0000.000
Unnamed: 21.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.000
Unnamed: 60.0001.0001.0001.000

Missing values

2024-04-18T07:42:36.979861image/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.
2024-04-18T07:42:37.099810image/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

테이블정의서Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0작성자<NA>최민선<NA>NaN<NA>작성일2016-01-19 00:00:00<NA>
1주제영역명<NA>행정업무테이블IDLPTD_LDREG_TRAG_POINT_INFO<NA>테이블명지적삼각점정보<NA>
2테이블설명<NA>지적삼각점 기본정보<NA>NaN<NA><NA>NaN<NA>
3No컬럼ID컬럼명타입길이(Byte)<NA>PK/FKDefault참조테이블명/비고
41BASE_POINT_NO기준점번호VARCHAR215NPKNaN<NA>
52LAND_LOC_CD토지소재지코드VARCHAR25N<NA>NaN<NA>
63TRAG_POINT_NM삼각점명VARCHAR290N<NA>NaN<NA>
74WONJUM원점VARCHAR25<NA><NA>NaN<NA>
85LTTD위도VARCHAR220<NA><NA>NaN<NA>
96LGTD경도VARCHAR220<NA><NA>NaN<NA>
테이블정의서Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
1714OBJECTID도형IDINTEGER22N<NA>NaN<NA>
1815SHAPE공간데이터ST_GEOMETRY256<NA><NA>NaN<NA>
1916X_CODEX코드VARCHAR220<NA><NA>NaN<NA>
2017Y_CODEY코드VARCHAR220<NA><NA>NaN<NA>
2118POINT_XX포인트NUMBER22<NA><NA>NaN<NA>
2219POINT_YY포인트NUMBER22<NA><NA>NaN<NA>
2320COORD_GBN좌표구분VARCHAR22<NA><NA>NaN<NA>
24인덱스명<NA>인덱스키<NA>NaN<NA><NA>NaN<NA>
25LPTD_LDREG_TRAG_POINT_INFO_INX1<NA>BASE_POINT_NO, SGG_OID<NA>NaN<NA><NA>NaN<NA>
26업무규칙<NA><NA><NA>NaN<NA><NA>NaN<NA>