Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells88
Missing cells (%)45.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory69.5 B

Variable types

Text6
Boolean2

Dataset

Description재능기부 완료 현황입니다.
Author한국사회적기업진흥원
URLhttps://www.data.go.kr/data/15093607/fileData.do

Alerts

DB구분 has constant value ""Constant
테이블명(한글) has constant value ""Constant
테이블명(영문) has constant value ""Constant
PK has constant value ""Constant
DB구분 has 23 (95.8%) missing valuesMissing
테이블명(한글) has 23 (95.8%) missing valuesMissing
테이블명(영문) has 23 (95.8%) missing valuesMissing
PK has 19 (79.2%) missing valuesMissing
컬럼명(한글) has unique valuesUnique
컬럼명(영문) has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:39:33.906767
Analysis finished2023-12-12 00:39:34.478323
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

DB구분
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing23
Missing (%)95.8%
Memory size324.0 B
2023-12-12T09:39:34.583922image/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 categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row재능기부뱅크시스템
ValueCountFrequency (%)
재능기부뱅크시스템 1
100.0%
2023-12-12T09:39:34.821301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
재 1
11.1%
능 1
11.1%
기 1
11.1%
부 1
11.1%
뱅 1
11.1%
크 1
11.1%
시 1
11.1%
스 1
11.1%
템 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
재 1
11.1%
능 1
11.1%
기 1
11.1%
부 1
11.1%
뱅 1
11.1%
크 1
11.1%
시 1
11.1%
스 1
11.1%
템 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
재 1
11.1%
능 1
11.1%
기 1
11.1%
부 1
11.1%
뱅 1
11.1%
크 1
11.1%
시 1
11.1%
스 1
11.1%
템 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
재 1
11.1%
능 1
11.1%
기 1
11.1%
부 1
11.1%
뱅 1
11.1%
크 1
11.1%
시 1
11.1%
스 1
11.1%
템 1
11.1%

테이블명(한글)
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing23
Missing (%)95.8%
Memory size324.0 B
2023-12-12T09:39:34.936567image/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 row재능기부 완료보고
ValueCountFrequency (%)
재능기부 1
50.0%
완료보고 1
50.0%
2023-12-12T09:39:35.153523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
재 1
11.1%
능 1
11.1%
기 1
11.1%
부 1
11.1%
1
11.1%
완 1
11.1%
료 1
11.1%
보 1
11.1%
고 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Space Separator 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
재 1
12.5%
능 1
12.5%
기 1
12.5%
부 1
12.5%
완 1
12.5%
료 1
12.5%
보 1
12.5%
고 1
12.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
재 1
12.5%
능 1
12.5%
기 1
12.5%
부 1
12.5%
완 1
12.5%
료 1
12.5%
보 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 (%)
재 1
12.5%
능 1
12.5%
기 1
12.5%
부 1
12.5%
완 1
12.5%
료 1
12.5%
보 1
12.5%
고 1
12.5%
ASCII
ValueCountFrequency (%)
1
100.0%

테이블명(영문)
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing23
Missing (%)95.8%
Memory size324.0 B
2023-12-12T09:39:35.321561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters15
Distinct characters9
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

Unique1 ?
Unique (%)100.0%

Sample

1st rowTB_COMPT_REPORT
ValueCountFrequency (%)
tb_compt_report 1
100.0%
2023-12-12T09:39:35.593333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 3
20.0%
_ 2
13.3%
O 2
13.3%
P 2
13.3%
R 2
13.3%
B 1
 
6.7%
C 1
 
6.7%
M 1
 
6.7%
E 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 13
86.7%
Connector Punctuation 2
 
13.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 3
23.1%
O 2
15.4%
P 2
15.4%
R 2
15.4%
B 1
 
7.7%
C 1
 
7.7%
M 1
 
7.7%
E 1
 
7.7%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
86.7%
Common 2
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 3
23.1%
O 2
15.4%
P 2
15.4%
R 2
15.4%
B 1
 
7.7%
C 1
 
7.7%
M 1
 
7.7%
E 1
 
7.7%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 3
20.0%
_ 2
13.3%
O 2
13.3%
P 2
13.3%
R 2
13.3%
B 1
 
6.7%
C 1
 
6.7%
M 1
 
6.7%
E 1
 
6.7%

컬럼명(한글)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T09:39:35.800605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length5.3333333
Min length3

Characters and Unicode

Total characters128
Distinct characters66
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

Unique24 ?
Unique (%)100.0%

Sample

1st row프로보노번호
2nd row마스터번호
3rd row분야코드1
4th row분야코드2
5th row지원구분
ValueCountFrequency (%)
프로보노번호 1
 
4.2%
마스터번호 1
 
4.2%
완료여부 1
 
4.2%
지원시간 1
 
4.2%
지원횟수 1
 
4.2%
활동종료기간 1
 
4.2%
활동시작기간 1
 
4.2%
수정일시 1
 
4.2%
수정자 1
 
4.2%
등록일시 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T09:39:36.105945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 6
 
4.7%
활 6
 
4.7%
일 5
 
3.9%
원 4
 
3.1%
시 4
 
3.1%
부 4
 
3.1%
분 4
 
3.1%
지 3
 
2.3%
내 3
 
2.3%
용 3
 
2.3%
Other values (56) 86
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
98.4%
Decimal Number 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6
 
4.8%
활 6
 
4.8%
일 5
 
4.0%
원 4
 
3.2%
시 4
 
3.2%
부 4
 
3.2%
분 4
 
3.2%
지 3
 
2.4%
내 3
 
2.4%
용 3
 
2.4%
Other values (54) 84
66.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
98.4%
Common 2
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6
 
4.8%
활 6
 
4.8%
일 5
 
4.0%
원 4
 
3.2%
시 4
 
3.2%
부 4
 
3.2%
분 4
 
3.2%
지 3
 
2.4%
내 3
 
2.4%
용 3
 
2.4%
Other values (54) 84
66.7%
Common
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
98.4%
ASCII 2
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 6
 
4.8%
활 6
 
4.8%
일 5
 
4.0%
원 4
 
3.2%
시 4
 
3.2%
부 4
 
3.2%
분 4
 
3.2%
지 3
 
2.4%
내 3
 
2.4%
용 3
 
2.4%
Other values (54) 84
66.7%
ASCII
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

컬럼명(영문)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T09:39:36.291167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length11.75
Min length5

Characters and Unicode

Total characters282
Distinct characters21
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

Unique24 ?
Unique (%)100.0%

Sample

1st rowMB_NO
2nd rowMASTR_NO
3rd rowREALM_CODE_ONE
4th rowREALM_CODE_TWO
5th rowSPORT_SE
ValueCountFrequency (%)
mb_no 1
 
4.2%
mastr_no 1
 
4.2%
compt_at 1
 
4.2%
sport_time 1
 
4.2%
sport_co 1
 
4.2%
act_end_pd 1
 
4.2%
act_begin_pd 1
 
4.2%
updt_dt 1
 
4.2%
updusr 1
 
4.2%
regist_dt 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T09:39:36.613086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 37
13.1%
T 32
11.3%
E 23
 
8.2%
R 21
 
7.4%
C 20
 
7.1%
N 20
 
7.1%
A 18
 
6.4%
S 16
 
5.7%
O 15
 
5.3%
D 15
 
5.3%
Other values (11) 65
23.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 245
86.9%
Connector Punctuation 37
 
13.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 32
13.1%
E 23
9.4%
R 21
8.6%
C 20
 
8.2%
N 20
 
8.2%
A 18
 
7.3%
S 16
 
6.5%
O 15
 
6.1%
D 15
 
6.1%
M 14
 
5.7%
Other values (10) 51
20.8%
Connector Punctuation
ValueCountFrequency (%)
_ 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 245
86.9%
Common 37
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 32
13.1%
E 23
9.4%
R 21
8.6%
C 20
 
8.2%
N 20
 
8.2%
A 18
 
7.3%
S 16
 
6.5%
O 15
 
6.1%
D 15
 
6.1%
M 14
 
5.7%
Other values (10) 51
20.8%
Common
ValueCountFrequency (%)
_ 37
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 37
13.1%
T 32
11.3%
E 23
 
8.2%
R 21
 
7.4%
C 20
 
7.1%
N 20
 
7.1%
A 18
 
6.4%
S 16
 
5.7%
O 15
 
5.3%
D 15
 
5.3%
Other values (11) 65
23.0%

데이터타입
Text

Distinct12
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T09:39:36.745257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.958333
Min length12

Characters and Unicode

Total characters407
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st rowNUMBER(10,0)
2nd rowVARCHAR2(13 BYTE)
3rd rowVARCHAR2(6 BYTE)
4th rowVARCHAR2(6 BYTE)
5th rowVARCHAR2(100 BYTE)
ValueCountFrequency (%)
byte 23
48.9%
varchar2(200 4
 
8.5%
varchar2(6 3
 
6.4%
varchar2(100 3
 
6.4%
varchar2(10 3
 
6.4%
varchar2(13 2
 
4.3%
varchar2(64 2
 
4.3%
varchar2(20 2
 
4.3%
number(10,0 1
 
2.1%
varchar2(500 1
 
2.1%
Other values (3) 3
 
6.4%
2023-12-12T09:39:37.058927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 47
 
11.5%
A 46
 
11.3%
2 31
 
7.6%
B 24
 
5.9%
) 24
 
5.9%
E 24
 
5.9%
( 24
 
5.9%
V 23
 
5.7%
Y 23
 
5.7%
T 23
 
5.7%
Other values (13) 118
29.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 259
63.6%
Decimal Number 76
 
18.7%
Close Punctuation 24
 
5.9%
Open Punctuation 24
 
5.9%
Space Separator 23
 
5.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 47
18.1%
A 46
17.8%
B 24
9.3%
E 24
9.3%
V 23
8.9%
Y 23
8.9%
T 23
8.9%
H 23
8.9%
C 23
8.9%
N 1
 
0.4%
Other values (2) 2
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 31
40.8%
0 23
30.3%
1 9
 
11.8%
6 6
 
7.9%
4 3
 
3.9%
3 2
 
2.6%
5 2
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 259
63.6%
Common 148
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 47
18.1%
A 46
17.8%
B 24
9.3%
E 24
9.3%
V 23
8.9%
Y 23
8.9%
T 23
8.9%
H 23
8.9%
C 23
8.9%
N 1
 
0.4%
Other values (2) 2
 
0.8%
Common
ValueCountFrequency (%)
2 31
20.9%
) 24
16.2%
( 24
16.2%
23
15.5%
0 23
15.5%
1 9
 
6.1%
6 6
 
4.1%
4 3
 
2.0%
3 2
 
1.4%
5 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 47
 
11.5%
A 46
 
11.3%
2 31
 
7.6%
B 24
 
5.9%
) 24
 
5.9%
E 24
 
5.9%
( 24
 
5.9%
V 23
 
5.7%
Y 23
 
5.7%
T 23
 
5.7%
Other values (13) 118
29.0%

Null여부
Boolean

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size156.0 B
True
19 
False
5 
ValueCountFrequency (%)
True 19
79.2%
False 5
 
20.8%
2023-12-12T09:39:37.171247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

PK
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)20.0%
Missing19
Missing (%)79.2%
Memory size180.0 B
True
5 
(Missing)
19 
ValueCountFrequency (%)
True 5
 
20.8%
(Missing) 19
79.2%
2023-12-12T09:39:37.255671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:39:37.319430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
컬럼명(한글)컬럼명(영문)데이터타입Null여부
컬럼명(한글)1.0001.0001.0001.000
컬럼명(영문)1.0001.0001.0001.000
데이터타입1.0001.0001.0000.959
Null여부1.0001.0000.9591.000

Missing values

2023-12-12T09:39:34.166109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:39:34.284281image/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.
2023-12-12T09:39:34.406156image/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

DB구분테이블명(한글)테이블명(영문)컬럼명(한글)컬럼명(영문)데이터타입Null여부PK
0재능기부뱅크시스템재능기부 완료보고TB_COMPT_REPORT프로보노번호MB_NONUMBER(10,0)NY
1<NA><NA><NA>마스터번호MASTR_NOVARCHAR2(13 BYTE)NY
2<NA><NA><NA>분야코드1REALM_CODE_ONEVARCHAR2(6 BYTE)NY
3<NA><NA><NA>분야코드2REALM_CODE_TWOVARCHAR2(6 BYTE)NY
4<NA><NA><NA>지원구분SPORT_SEVARCHAR2(100 BYTE)Y<NA>
5<NA><NA><NA>활동내용전활동전상황ACT_CN_BFE_ACT_BFE_SITTNVARCHAR2(200 BYTE)Y<NA>
6<NA><NA><NA>활동내용중역할ACT_CN_MIDDL_ROLEVARCHAR2(200 BYTE)Y<NA>
7<NA><NA><NA>활동내용후결과ACT_CN_AFTER_RESULTVARCHAR2(200 BYTE)Y<NA>
8<NA><NA><NA>주요성과특이사항MAIN_RSLT_PARTCLR_MATTERVARCHAR2(500 BYTE)Y<NA>
9<NA><NA><NA>첨부파일주소ATCHMNFL_ADRESVARCHAR2(256 BYTE)Y<NA>
DB구분테이블명(한글)테이블명(영문)컬럼명(한글)컬럼명(영문)데이터타입Null여부PK
14<NA><NA><NA>등록자REGISTERVARCHAR2(64 BYTE)Y<NA>
15<NA><NA><NA>등록일시REGIST_DTVARCHAR2(20 BYTE)Y<NA>
16<NA><NA><NA>수정자UPDUSRVARCHAR2(64 BYTE)Y<NA>
17<NA><NA><NA>수정일시UPDT_DTVARCHAR2(20 BYTE)Y<NA>
18<NA><NA><NA>활동시작기간ACT_BEGIN_PDVARCHAR2(10 BYTE)Y<NA>
19<NA><NA><NA>활동종료기간ACT_END_PDVARCHAR2(10 BYTE)Y<NA>
20<NA><NA><NA>지원횟수SPORT_COVARCHAR2(2 BYTE)Y<NA>
21<NA><NA><NA>지원시간SPORT_TIMEVARCHAR2(4 BYTE)Y<NA>
22<NA><NA><NA>완료여부COMPT_ATVARCHAR2(10 BYTE)Y<NA>
23<NA><NA><NA>신청서관리번호REQSTDOC_NOVARCHAR2(13 BYTE)NY