Overview

Dataset statistics

Number of variables20
Number of observations8802
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)< 0.1%
Total size in memory1.4 MiB
Average record size in memory167.0 B

Variable types

Categorical9
Text6
Numeric4
Boolean1

Alerts

회계년도 has constant value ""Constant
기준일자 has constant value ""Constant
재배정금액 has constant value ""Constant
사업자등록번호 has constant value ""Constant
Dataset has 2 (< 0.1%) duplicate rowsDuplicates
실국구분명 is highly overall correlated with 예산부서구분명 and 2 other fieldsHigh correlation
예산부서구분명 is highly overall correlated with 예산실국명 and 2 other fieldsHigh correlation
부서구분명 is highly overall correlated with 예산부서구분명 and 2 other fieldsHigh correlation
예산실국명 is highly overall correlated with 예산부서구분명 and 2 other fieldsHigh correlation
예산금액 is highly overall correlated with 예산현재금액 and 2 other fieldsHigh correlation
예산현재금액 is highly overall correlated with 예산금액 and 2 other fieldsHigh correlation
지출누계금액 is highly overall correlated with 예산금액 and 1 other fieldsHigh correlation
집행잔여금액 is highly overall correlated with 예산금액 and 1 other fieldsHigh correlation
회계구분명 is highly imbalanced (79.6%)Imbalance
이월구분명 is highly imbalanced (79.4%)Imbalance
예산금액 is highly skewed (γ1 = 41.05578774)Skewed
예산현재금액 is highly skewed (γ1 = 41.05578774)Skewed
지출누계금액 is highly skewed (γ1 = 35.826487)Skewed
집행잔여금액 is highly skewed (γ1 = 48.77341665)Skewed
지출누계금액 has 2066 (23.5%) zerosZeros
집행잔여금액 has 1212 (13.8%) zerosZeros

Reproduction

Analysis started2024-05-17 18:37:36.971341
Analysis finished2024-05-17 18:37:48.020120
Duration11.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024
8802 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024
2nd row2024
3rd row2024
4th row2024
5th row2024

Common Values

ValueCountFrequency (%)
2024 8802
100.0%

Length

2024-05-18T03:37:48.163260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:37:48.430145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024 8802
100.0%

회계구분명
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
일반회계
6843 
소방안전
1651 
팔당호관리
 
25
자원순환
 
23
기후대응기금
 
19
Other values (33)
 
241

Length

Max length18
Median length4
Mean length4.0858896
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반회계 6843
77.7%
소방안전 1651
 
18.8%
팔당호관리 25
 
0.3%
자원순환 23
 
0.3%
기후대응기금 19
 
0.2%
남북교류협력기금 17
 
0.2%
식품진흥기금 16
 
0.2%
광역교통시설 16
 
0.2%
청소년육성기금 16
 
0.2%
재난관리기금 15
 
0.2%
Other values (28) 161
 
1.8%

Length

2024-05-18T03:37:48.806384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반회계 6843
77.7%
소방안전 1651
 
18.8%
팔당호관리 25
 
0.3%
자원순환 23
 
0.3%
기후대응기금 19
 
0.2%
남북교류협력기금 17
 
0.2%
식품진흥기금 16
 
0.2%
광역교통시설 16
 
0.2%
청소년육성기금 16
 
0.2%
재난관리기금 15
 
0.2%
Other values (28) 161
 
1.8%

예산부서구분명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
본청
3873 
직속기관
2530 
외청
1583 
사업소
816 

Length

Max length4
Median length2
Mean length2.6675756
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본청 3873
44.0%
직속기관 2530
28.7%
외청 1583
18.0%
사업소 816
 
9.3%

Length

2024-05-18T03:37:49.250245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:37:49.623106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본청 3873
44.0%
직속기관 2530
28.7%
외청 1583
18.0%
사업소 816
 
9.3%

예산관서명
Text

Distinct62
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:50.076180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length3.993865
Min length2

Characters and Unicode

Total characters35154
Distinct characters105
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

Unique0 ?
Unique (%)0.0%

Sample

1st row본청
2nd row본청
3rd row본청
4th row본청
5th row본청
ValueCountFrequency (%)
본청 3480
39.2%
북부청 1617
18.2%
농업기술원 564
 
6.4%
소방재난본부 271
 
3.1%
보건환경연구원 255
 
2.9%
의회사무처 221
 
2.5%
산림환경연구소 147
 
1.7%
수자원본부 131
 
1.5%
해양수산자원연구소 107
 
1.2%
북부소방재난본부 88
 
1.0%
Other values (52) 1988
22.4%
2024-05-18T03:37:50.926914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (95) 13301
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35087
99.8%
Space Separator 67
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35087
99.8%
Common 67
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
Common
ValueCountFrequency (%)
67
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35087
99.8%
ASCII 67
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
ASCII
ValueCountFrequency (%)
67
100.0%

예산실국명
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
소방서
1175 
기후환경에너지국
580 
경기도농업기술원
564 
건설국
 
508
농수산생명과학국
 
466
Other values (39)
5509 

Length

Max length12
Median length10
Mean length5.7695978
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소방서 1175
 
13.3%
기후환경에너지국 580
 
6.6%
경기도농업기술원 564
 
6.4%
건설국 508
 
5.8%
농수산생명과학국 466
 
5.3%
축산동물복지국 376
 
4.3%
문화체육관광국 371
 
4.2%
복지국 368
 
4.2%
여성가족국 362
 
4.1%
보건건강국 323
 
3.7%
Other values (34) 3709
42.1%

Length

2024-05-18T03:37:51.357840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소방서 1175
 
13.3%
기후환경에너지국 580
 
6.6%
경기도농업기술원 564
 
6.4%
건설국 508
 
5.8%
농수산생명과학국 466
 
5.3%
축산동물복지국 376
 
4.3%
문화체육관광국 371
 
4.2%
복지국 368
 
4.2%
여성가족국 362
 
4.1%
보건건강국 323
 
3.7%
Other values (34) 3709
42.1%

예산부서명
Text

Distinct243
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:51.820565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.7333561
Min length3

Characters and Unicode

Total characters50465
Distinct characters219
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

Unique0 ?
Unique (%)0.0%

Sample

1st row평생교육과
2nd row평생교육과
3rd row평생교육과
4th row평생교육과
5th row평생교육과
ValueCountFrequency (%)
도로정책과 228
 
2.6%
하천과 168
 
1.9%
산림환경연구소 147
 
1.7%
산림녹지과 108
 
1.2%
장애인복지과 107
 
1.2%
해양수산자원연구소 107
 
1.2%
회계장비담당관 103
 
1.2%
해양수산과 101
 
1.1%
아동돌봄과 99
 
1.1%
정원산업과 96
 
1.1%
Other values (233) 7538
85.6%
2024-05-18T03:37:52.818892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.8%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
1.9%
Other values (209) 32480
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50252
99.6%
Uppercase Letter 114
 
0.2%
Decimal Number 99
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
Uppercase Letter
ValueCountFrequency (%)
Z 24
21.1%
M 24
21.1%
D 24
21.1%
I 21
18.4%
A 21
18.4%
Decimal Number
ValueCountFrequency (%)
1 66
66.7%
9 33
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50252
99.6%
Latin 114
 
0.2%
Common 99
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
Latin
ValueCountFrequency (%)
Z 24
21.1%
M 24
21.1%
D 24
21.1%
I 21
18.4%
A 21
18.4%
Common
ValueCountFrequency (%)
1 66
66.7%
9 33
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50252
99.6%
ASCII 213
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
ASCII
ValueCountFrequency (%)
1 66
31.0%
9 33
15.5%
Z 24
 
11.3%
M 24
 
11.3%
D 24
 
11.3%
I 21
 
9.9%
A 21
 
9.9%

부서구분명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
본청
3873 
직속기관
2530 
외청
1583 
사업소
816 

Length

Max length4
Median length2
Mean length2.6675756
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
본청 3873
44.0%
직속기관 2530
28.7%
외청 1583
18.0%
사업소 816
 
9.3%

Length

2024-05-18T03:37:53.255927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:37:53.699126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
본청 3873
44.0%
직속기관 2530
28.7%
외청 1583
18.0%
사업소 816
 
9.3%

관서명
Text

Distinct62
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:54.156384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length3.993865
Min length2

Characters and Unicode

Total characters35154
Distinct characters105
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

Unique0 ?
Unique (%)0.0%

Sample

1st row본청
2nd row본청
3rd row본청
4th row본청
5th row본청
ValueCountFrequency (%)
본청 3480
39.2%
북부청 1617
18.2%
농업기술원 564
 
6.4%
소방재난본부 271
 
3.1%
보건환경연구원 255
 
2.9%
의회사무처 221
 
2.5%
산림환경연구소 147
 
1.7%
수자원본부 131
 
1.5%
해양수산자원연구소 107
 
1.2%
북부소방재난본부 88
 
1.0%
Other values (52) 1988
22.4%
2024-05-18T03:37:55.008191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (95) 13301
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35087
99.8%
Space Separator 67
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35087
99.8%
Common 67
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
Common
ValueCountFrequency (%)
67
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35087
99.8%
ASCII 67
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 5129
 
14.6%
본 4063
 
11.6%
부 2684
 
7.6%
소 1990
 
5.7%
북 1924
 
5.5%
방 1588
 
4.5%
원 1384
 
3.9%
서 1175
 
3.3%
경 974
 
2.8%
기 942
 
2.7%
Other values (94) 13234
37.7%
ASCII
ValueCountFrequency (%)
67
100.0%

실국구분명
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
소방서
1175 
기후환경에너지국
580 
경기도농업기술원
564 
건설국
 
508
농수산생명과학국
 
466
Other values (39)
5509 

Length

Max length12
Median length10
Mean length5.7695978
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소방서 1175
 
13.3%
기후환경에너지국 580
 
6.6%
경기도농업기술원 564
 
6.4%
건설국 508
 
5.8%
농수산생명과학국 466
 
5.3%
축산동물복지국 376
 
4.3%
문화체육관광국 371
 
4.2%
복지국 368
 
4.2%
여성가족국 362
 
4.1%
보건건강국 323
 
3.7%
Other values (34) 3709
42.1%

Length

2024-05-18T03:37:55.434860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소방서 1175
 
13.3%
기후환경에너지국 580
 
6.6%
경기도농업기술원 564
 
6.4%
건설국 508
 
5.8%
농수산생명과학국 466
 
5.3%
축산동물복지국 376
 
4.3%
문화체육관광국 371
 
4.2%
복지국 368
 
4.2%
여성가족국 362
 
4.1%
보건건강국 323
 
3.7%
Other values (34) 3709
42.1%

부서명
Text

Distinct243
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:55.954887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.7333561
Min length3

Characters and Unicode

Total characters50465
Distinct characters219
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

Unique0 ?
Unique (%)0.0%

Sample

1st row평생교육과
2nd row평생교육과
3rd row평생교육과
4th row평생교육과
5th row평생교육과
ValueCountFrequency (%)
도로정책과 228
 
2.6%
하천과 168
 
1.9%
산림환경연구소 147
 
1.7%
산림녹지과 108
 
1.2%
장애인복지과 107
 
1.2%
해양수산자원연구소 107
 
1.2%
회계장비담당관 103
 
1.2%
해양수산과 101
 
1.1%
아동돌봄과 99
 
1.1%
정원산업과 96
 
1.1%
Other values (233) 7538
85.6%
2024-05-18T03:37:56.945821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.8%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
1.9%
Other values (209) 32480
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50252
99.6%
Uppercase Letter 114
 
0.2%
Decimal Number 99
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
Uppercase Letter
ValueCountFrequency (%)
Z 24
21.1%
M 24
21.1%
D 24
21.1%
I 21
18.4%
A 21
18.4%
Decimal Number
ValueCountFrequency (%)
1 66
66.7%
9 33
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50252
99.6%
Latin 114
 
0.2%
Common 99
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
Latin
ValueCountFrequency (%)
Z 24
21.1%
M 24
21.1%
D 24
21.1%
I 21
18.4%
A 21
18.4%
Common
ValueCountFrequency (%)
1 66
66.7%
9 33
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50252
99.6%
ASCII 213
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 5489
 
10.9%
소 2000
 
4.0%
정 1938
 
3.9%
관 1371
 
2.7%
방 1359
 
2.7%
산 1319
 
2.6%
책 1279
 
2.5%
서 1207
 
2.4%
지 1040
 
2.1%
당 983
 
2.0%
Other values (202) 32267
64.2%
ASCII
ValueCountFrequency (%)
1 66
31.0%
9 33
15.5%
Z 24
 
11.3%
M 24
 
11.3%
D 24
 
11.3%
I 21
 
9.9%
A 21
 
9.9%

세부사업내용
Text

Distinct4105
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:57.486628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length41.5
Mean length18.450807
Min length2

Characters and Unicode

Total characters162404
Distinct characters673
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2913 ?
Unique (%)33.1%

Sample

1st row경기도 평생학습 활성화(자체/직접)
2nd row독도 역사인식 확산(자체/직접)
3rd row경기도 청소년 노동인권 교육 사업(자체/직접)
4th row시군 청소년 노동인권 보호 지원(자체/지원)
5th row장애인·경계선 지능인 평생교육 체계 구축(자체/직접)
ValueCountFrequency (%)
운영(자체/직접 915
 
3.9%
지원(자체/직접 736
 
3.1%
및 590
 
2.5%
업무추진비 394
 
1.7%
일반운영비 332
 
1.4%
경기도 300
 
1.3%
지원(자체/지원 294
 
1.2%
운영 248
 
1.0%
여비 241
 
1.0%
등 168
 
0.7%
Other values (6091) 19428
82.2%
2024-05-18T03:37:58.496741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14868
 
9.2%
) 8965
 
5.5%
( 8965
 
5.5%
/ 7570
 
4.7%
자 6889
 
4.2%
체 6460
 
4.0%
직 6176
 
3.8%
접 6117
 
3.8%
지 5227
 
3.2%
원 4512
 
2.8%
Other values (663) 86655
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120631
74.3%
Space Separator 14868
 
9.2%
Close Punctuation 8966
 
5.5%
Open Punctuation 8966
 
5.5%
Other Punctuation 7826
 
4.8%
Uppercase Letter 486
 
0.3%
Decimal Number 349
 
0.2%
Dash Punctuation 240
 
0.1%
Lowercase Letter 51
 
< 0.1%
Math Symbol 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 6889
 
5.7%
체 6460
 
5.4%
직 6176
 
5.1%
접 6117
 
5.1%
지 5227
 
4.3%
원 4512
 
3.7%
비 2970
 
2.5%
기 2268
 
1.9%
사 2162
 
1.8%
영 2134
 
1.8%
Other values (596) 75716
62.8%
Uppercase Letter
ValueCountFrequency (%)
D 45
 
9.3%
G 43
 
8.8%
A 38
 
7.8%
S 38
 
7.8%
T 36
 
7.4%
I 34
 
7.0%
E 29
 
6.0%
C 29
 
6.0%
R 28
 
5.8%
P 22
 
4.5%
Other values (13) 144
29.6%
Lowercase Letter
ValueCountFrequency (%)
e 10
19.6%
o 6
11.8%
a 5
9.8%
t 4
 
7.8%
r 4
 
7.8%
h 4
 
7.8%
i 3
 
5.9%
p 3
 
5.9%
d 2
 
3.9%
n 2
 
3.9%
Other values (6) 8
15.7%
Decimal Number
ValueCountFrequency (%)
1 106
30.4%
2 74
21.2%
0 46
13.2%
3 35
 
10.0%
4 31
 
8.9%
9 25
 
7.2%
6 16
 
4.6%
8 8
 
2.3%
5 7
 
2.0%
7 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 7570
96.7%
· 163
 
2.1%
, 68
 
0.9%
. 8
 
0.1%
& 7
 
0.1%
" 4
 
0.1%
: 4
 
0.1%
? 1
 
< 0.1%
! 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8965
> 99.9%
」 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 8965
> 99.9%
「 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 15
78.9%
+ 4
 
21.1%
Space Separator
ValueCountFrequency (%)
14868
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120629
74.3%
Common 41236
 
25.4%
Latin 537
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 6889
 
5.7%
체 6460
 
5.4%
직 6176
 
5.1%
접 6117
 
5.1%
지 5227
 
4.3%
원 4512
 
3.7%
비 2970
 
2.5%
기 2268
 
1.9%
사 2162
 
1.8%
영 2134
 
1.8%
Other values (594) 75714
62.8%
Latin
ValueCountFrequency (%)
D 45
 
8.4%
G 43
 
8.0%
A 38
 
7.1%
S 38
 
7.1%
T 36
 
6.7%
I 34
 
6.3%
E 29
 
5.4%
C 29
 
5.4%
R 28
 
5.2%
P 22
 
4.1%
Other values (29) 195
36.3%
Common
ValueCountFrequency (%)
14868
36.1%
) 8965
21.7%
( 8965
21.7%
/ 7570
18.4%
- 240
 
0.6%
· 163
 
0.4%
1 106
 
0.3%
2 74
 
0.2%
, 68
 
0.2%
0 46
 
0.1%
Other values (18) 171
 
0.4%
Han
ValueCountFrequency (%)
道 1
50.0%
新 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120616
74.3%
ASCII 41608
 
25.6%
None 165
 
0.1%
Compat Jamo 13
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14868
35.7%
) 8965
21.5%
( 8965
21.5%
/ 7570
18.2%
- 240
 
0.6%
1 106
 
0.3%
2 74
 
0.2%
, 68
 
0.2%
0 46
 
0.1%
D 45
 
0.1%
Other values (54) 661
 
1.6%
Hangul
ValueCountFrequency (%)
자 6889
 
5.7%
체 6460
 
5.4%
직 6176
 
5.1%
접 6117
 
5.1%
지 5227
 
4.3%
원 4512
 
3.7%
비 2970
 
2.5%
기 2268
 
1.9%
사 2162
 
1.8%
영 2134
 
1.8%
Other values (593) 75701
62.8%
None
ValueCountFrequency (%)
· 163
98.8%
」 1
 
0.6%
「 1
 
0.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 13
100.0%
CJK
ValueCountFrequency (%)
道 1
50.0%
新 1
50.0%

세출관리세목구분명
Text

Distinct106
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
2024-05-18T03:37:58.944756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length7.0072711
Min length2

Characters and Unicode

Total characters61678
Distinct characters132
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)0.3%

Sample

1st row사무관리비
2nd row공기관등에대한경상적위탁사업비
3rd row공기관등에대한경상적위탁사업비
4th row자치단체경상보조금
5th row공기관등에대한경상적위탁사업비
ValueCountFrequency (%)
사무관리비 1436
16.1%
자치단체경상보조금 933
 
10.5%
시설비 542
 
6.1%
자치단체자본보조 510
 
5.7%
공기관등에대한경상적위탁사업비 500
 
5.6%
자산및물품취득비 494
 
5.5%
공공운영비 484
 
5.4%
국내여비 442
 
5.0%
시책추진업무추진비 280
 
3.1%
행사운영비 248
 
2.8%
Other values (103) 3054
34.2%
2024-05-18T03:37:59.921954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 6206
 
10.1%
사 2933
 
4.8%
자 2713
 
4.4%
보 2283
 
3.7%
무 2234
 
3.6%
관 2072
 
3.4%
상 1892
 
3.1%
경 1863
 
3.0%
조 1827
 
3.0%
금 1800
 
2.9%
Other values (122) 35855
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61174
99.2%
Close Punctuation 143
 
0.2%
Open Punctuation 143
 
0.2%
Space Separator 121
 
0.2%
Other Punctuation 97
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 6206
 
10.1%
사 2933
 
4.8%
자 2713
 
4.4%
보 2283
 
3.7%
무 2234
 
3.7%
관 2072
 
3.4%
상 1892
 
3.1%
경 1863
 
3.0%
조 1827
 
3.0%
금 1800
 
2.9%
Other values (117) 35351
57.8%
Other Punctuation
ValueCountFrequency (%)
, 91
93.8%
· 6
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Space Separator
ValueCountFrequency (%)
121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61174
99.2%
Common 504
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 6206
 
10.1%
사 2933
 
4.8%
자 2713
 
4.4%
보 2283
 
3.7%
무 2234
 
3.7%
관 2072
 
3.4%
상 1892
 
3.1%
경 1863
 
3.0%
조 1827
 
3.0%
금 1800
 
2.9%
Other values (117) 35351
57.8%
Common
ValueCountFrequency (%)
) 143
28.4%
( 143
28.4%
121
24.0%
, 91
18.1%
· 6
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61167
99.2%
ASCII 498
 
0.8%
Compat Jamo 7
 
< 0.1%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 6206
 
10.1%
사 2933
 
4.8%
자 2713
 
4.4%
보 2283
 
3.7%
무 2234
 
3.7%
관 2072
 
3.4%
상 1892
 
3.1%
경 1863
 
3.0%
조 1827
 
3.0%
금 1800
 
2.9%
Other values (116) 35344
57.8%
ASCII
ValueCountFrequency (%)
) 143
28.7%
( 143
28.7%
121
24.3%
, 91
18.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
100.0%
None
ValueCountFrequency (%)
· 6
100.0%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
20240517
8802 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20240517
2nd row20240517
3rd row20240517
4th row20240517
5th row20240517

Common Values

ValueCountFrequency (%)
20240517 8802
100.0%

Length

2024-05-18T03:38:00.310042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:38:00.637593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20240517 8802
100.0%

예산금액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4468
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6738305 × 109
Minimum24850
Maximum4.816346 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.5 KiB
2024-05-18T03:38:01.030267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24850
5-th percentile2000000
Q110000000
median55528500
Q33.5 × 108
95-th percentile5.0394535 × 109
Maximum4.816346 × 1012
Range4.816346 × 1012
Interquartile range (IQR)3.4 × 108

Descriptive statistics

Standard deviation8.4202029 × 1010
Coefficient of variation (CV)18.015636
Kurtosis1986.5135
Mean4.6738305 × 109
Median Absolute Deviation (MAD)52149000
Skewness41.055788
Sum4.1139056 × 1013
Variance7.0899817 × 1021
MonotonicityNot monotonic
2024-05-18T03:38:01.522725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 150
 
1.7%
10000000 145
 
1.6%
20000000 108
 
1.2%
4400000 107
 
1.2%
100000000 99
 
1.1%
50000000 96
 
1.1%
200000000 91
 
1.0%
5000000 90
 
1.0%
30000000 89
 
1.0%
300000000 85
 
1.0%
Other values (4458) 7742
88.0%
ValueCountFrequency (%)
24850 1
< 0.1%
64320 1
< 0.1%
100000 1
< 0.1%
124000 1
< 0.1%
129530 1
< 0.1%
136000 1
< 0.1%
150000 2
< 0.1%
170660 1
< 0.1%
184000 1
< 0.1%
200000 1
< 0.1%
ValueCountFrequency (%)
4816346000000 1
< 0.1%
3997437310000 1
< 0.1%
2808443229000 1
< 0.1%
1980475250000 1
< 0.1%
1457241215000 1
< 0.1%
1241772018000 1
< 0.1%
1166089425000 1
< 0.1%
1122312264000 1
< 0.1%
1049531334000 1
< 0.1%
738803487000 1
< 0.1%

예산현재금액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4468
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6738305 × 109
Minimum24850
Maximum4.816346 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.5 KiB
2024-05-18T03:38:02.019992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24850
5-th percentile2000000
Q110000000
median55528500
Q33.5 × 108
95-th percentile5.0394535 × 109
Maximum4.816346 × 1012
Range4.816346 × 1012
Interquartile range (IQR)3.4 × 108

Descriptive statistics

Standard deviation8.4202029 × 1010
Coefficient of variation (CV)18.015636
Kurtosis1986.5135
Mean4.6738305 × 109
Median Absolute Deviation (MAD)52149000
Skewness41.055788
Sum4.1139056 × 1013
Variance7.0899817 × 1021
MonotonicityNot monotonic
2024-05-18T03:38:02.485440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 150
 
1.7%
10000000 145
 
1.6%
20000000 108
 
1.2%
4400000 107
 
1.2%
100000000 99
 
1.1%
50000000 96
 
1.1%
200000000 91
 
1.0%
5000000 90
 
1.0%
30000000 89
 
1.0%
300000000 85
 
1.0%
Other values (4458) 7742
88.0%
ValueCountFrequency (%)
24850 1
< 0.1%
64320 1
< 0.1%
100000 1
< 0.1%
124000 1
< 0.1%
129530 1
< 0.1%
136000 1
< 0.1%
150000 2
< 0.1%
170660 1
< 0.1%
184000 1
< 0.1%
200000 1
< 0.1%
ValueCountFrequency (%)
4816346000000 1
< 0.1%
3997437310000 1
< 0.1%
2808443229000 1
< 0.1%
1980475250000 1
< 0.1%
1457241215000 1
< 0.1%
1241772018000 1
< 0.1%
1166089425000 1
< 0.1%
1122312264000 1
< 0.1%
1049531334000 1
< 0.1%
738803487000 1
< 0.1%

재배정금액
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
0
8802 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8802
100.0%

Length

2024-05-18T03:38:02.951882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:38:03.281664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8802
100.0%

지출누계금액
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct4614
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9352239 × 109
Minimum0
Maximum1.8885362 × 1012
Zeros2066
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size77.5 KiB
2024-05-18T03:38:03.945166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1338725
median7500000
Q390436930
95-th percentile1.914472 × 109
Maximum1.8885362 × 1012
Range1.8885362 × 1012
Interquartile range (IQR)90098205

Descriptive statistics

Standard deviation3.2833383 × 1010
Coefficient of variation (CV)16.966194
Kurtosis1613.6899
Mean1.9352239 × 109
Median Absolute Deviation (MAD)7500000
Skewness35.826487
Sum1.7033841 × 1013
Variance1.078031 × 1021
MonotonicityNot monotonic
2024-05-18T03:38:04.416069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2066
 
23.5%
10000000 76
 
0.9%
5000000 65
 
0.7%
2000000 62
 
0.7%
3000000 56
 
0.6%
1000000 52
 
0.6%
1500000 49
 
0.6%
6000000 41
 
0.5%
100000000 40
 
0.5%
15000000 39
 
0.4%
Other values (4604) 6256
71.1%
ValueCountFrequency (%)
0 2066
23.5%
10500 1
 
< 0.1%
24230 1
 
< 0.1%
26390 1
 
< 0.1%
29700 1
 
< 0.1%
36900 1
 
< 0.1%
44000 1
 
< 0.1%
48000 1
 
< 0.1%
49700 1
 
< 0.1%
50000 1
 
< 0.1%
ValueCountFrequency (%)
1888536151000 1
< 0.1%
1118048626000 1
< 0.1%
939315450000 1
< 0.1%
909179316000 1
< 0.1%
671522588000 1
< 0.1%
669711234000 1
< 0.1%
644420433000 1
< 0.1%
587000000000 1
< 0.1%
522741857870 1
< 0.1%
460142034000 1
< 0.1%

집행잔여금액
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct5312
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7386066 × 109
Minimum-2.9564813 × 108
Maximum3.6982974 × 1012
Zeros1212
Zeros (%)13.8%
Negative3
Negative (%)< 0.1%
Memory size77.5 KiB
2024-05-18T03:38:04.844685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.9564813 × 108
5-th percentile0
Q12500000
median18931675
Q31.6 × 108
95-th percentile2.7272305 × 109
Maximum3.6982974 × 1012
Range3.698593 × 1012
Interquartile range (IQR)1.575 × 108

Descriptive statistics

Standard deviation5.5642893 × 1010
Coefficient of variation (CV)20.317958
Kurtosis2784.8946
Mean2.7386066 × 109
Median Absolute Deviation (MAD)18931675
Skewness48.773417
Sum2.4105216 × 1013
Variance3.0961315 × 1021
MonotonicityNot monotonic
2024-05-18T03:38:05.307364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1212
 
13.8%
10000000 83
 
0.9%
3000000 68
 
0.8%
2000000 58
 
0.7%
100000000 58
 
0.7%
20000000 55
 
0.6%
30000000 54
 
0.6%
50000000 53
 
0.6%
200000000 51
 
0.6%
300000000 48
 
0.5%
Other values (5302) 7062
80.2%
ValueCountFrequency (%)
-295648130 1
 
< 0.1%
-212141090 1
 
< 0.1%
-444383 1
 
< 0.1%
0 1212
13.8%
30 1
 
< 0.1%
40 1
 
< 0.1%
240 1
 
< 0.1%
600 1
 
< 0.1%
640 1
 
< 0.1%
810 1
 
< 0.1%
ValueCountFrequency (%)
3698297374000 1
< 0.1%
2285701371130 1
< 0.1%
2108901159000 1
< 0.1%
1041159800000 1
< 0.1%
654772018000 1
< 0.1%
548061899000 1
< 0.1%
494566837000 1
< 0.1%
477891831000 1
< 0.1%
452127643630 1
< 0.1%
434930606000 1
< 0.1%

이월구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.9 KiB
당해예산
8283 
명시이월예산
 
218
계속비이월예산
 
198
사고이월예산
 
103

Length

Max length7
Median length4
Mean length4.1404226
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
당해예산 8283
94.1%
명시이월예산 218
 
2.5%
계속비이월예산 198
 
2.2%
사고이월예산 103
 
1.2%

Length

2024-05-18T03:38:05.835792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:38:06.240786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당해예산 8283
94.1%
명시이월예산 218
 
2.5%
계속비이월예산 198
 
2.2%
사고이월예산 103
 
1.2%

사업자등록번호
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
False
8802 
ValueCountFrequency (%)
False 8802
100.0%
2024-05-18T03:38:06.684906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-05-18T03:37:45.519968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:41.960134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:43.065673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:44.373260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:45.789398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:42.224971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:43.347271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:44.654116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:46.108907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:42.492808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:43.649558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:44.950802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:46.445355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:42.778639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:44.108475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:37:45.217353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T03:38:06.926003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계구분명예산부서구분명예산관서명예산실국명부서구분명관서명실국구분명예산금액예산현재금액지출누계금액집행잔여금액이월구분명
회계구분명1.0000.5930.6680.7820.5930.6680.7820.3650.3650.3880.4420.000
예산부서구분명0.5931.0001.0000.9771.0001.0000.9770.0000.0000.0140.0000.379
예산관서명0.6681.0001.0000.9871.0001.0000.9870.0000.0000.0000.0000.335
예산실국명0.7820.9770.9871.0000.9770.9871.0000.0000.0000.0000.0000.543
부서구분명0.5931.0001.0000.9771.0001.0000.9770.0000.0000.0140.0000.379
관서명0.6681.0001.0000.9871.0001.0000.9870.0000.0000.0000.0000.335
실국구분명0.7820.9770.9871.0000.9770.9871.0000.0000.0000.0000.0000.543
예산금액0.3650.0000.0000.0000.0000.0000.0001.0001.0000.9690.9960.000
예산현재금액0.3650.0000.0000.0000.0000.0000.0001.0001.0000.9690.9960.000
지출누계금액0.3880.0140.0000.0000.0140.0000.0000.9690.9691.0000.9300.000
집행잔여금액0.4420.0000.0000.0000.0000.0000.0000.9960.9960.9301.0000.000
이월구분명0.0000.3790.3350.5430.3790.3350.5430.0000.0000.0000.0001.000
2024-05-18T03:38:07.371590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실국구분명회계구분명예산부서구분명부서구분명이월구분명예산실국명
실국구분명1.0000.2420.8350.8350.2861.000
회계구분명0.2421.0000.3420.3420.0000.242
예산부서구분명0.8350.3421.0001.0000.1550.835
부서구분명0.8350.3421.0001.0000.1550.835
이월구분명0.2860.0000.1550.1551.0000.286
예산실국명1.0000.2420.8350.8350.2861.000
2024-05-18T03:38:07.705402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산금액예산현재금액지출누계금액집행잔여금액회계구분명예산부서구분명예산실국명부서구분명실국구분명이월구분명
예산금액1.0001.0000.5550.6860.1490.0000.0000.0000.0000.000
예산현재금액1.0001.0000.5550.6860.1490.0000.0000.0000.0000.000
지출누계금액0.5550.5551.0000.1050.1690.0100.0000.0100.0000.000
집행잔여금액0.6860.6860.1051.0000.2080.0000.0000.0000.0000.000
회계구분명0.1490.1490.1690.2081.0000.3420.2420.3420.2420.000
예산부서구분명0.0000.0000.0100.0000.3421.0000.8351.0000.8350.155
예산실국명0.0000.0000.0000.0000.2420.8351.0000.8351.0000.286
부서구분명0.0000.0000.0100.0000.3421.0000.8351.0000.8350.155
실국구분명0.0000.0000.0000.0000.2420.8351.0000.8351.0000.286
이월구분명0.0000.0000.0000.0000.0000.1550.2860.1550.2861.000

Missing values

2024-05-18T03:37:46.903059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T03:37:47.665566image/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

회계년도회계구분명예산부서구분명예산관서명예산실국명예산부서명부서구분명관서명실국구분명부서명세부사업내용세출관리세목구분명기준일자예산금액예산현재금액재배정금액지출누계금액집행잔여금액이월구분명사업자등록번호
02024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과경기도 평생학습 활성화(자체/직접)사무관리비2024051780000008000000008000000당해예산N
12024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과독도 역사인식 확산(자체/직접)공기관등에대한경상적위탁사업비20240517200000000200000000013000000070000000당해예산N
22024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과경기도 청소년 노동인권 교육 사업(자체/직접)공기관등에대한경상적위탁사업비202405174500000004500000000225000000225000000당해예산N
32024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과시군 청소년 노동인권 보호 지원(자체/지원)자치단체경상보조금2024051781000000810000000810000000당해예산N
42024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과장애인·경계선 지능인 평생교육 체계 구축(자체/직접)공기관등에대한경상적위탁사업비20240517520000005200000002600000026000000당해예산N
52024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과청소년 학습코칭 및 온라인서비스 제공(주민참여예산)(자체/직접)민간위탁금20240517129750000012975000000500000000797500000당해예산N
62024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과경기 청소년 사다리(기금/직접)공기관등에대한경상적위탁사업비20240517100000000010000000000679050000320950000당해예산N
72024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과자산취득비자산및물품취득비2024051746000046000000460000당해예산N
82024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과경기미래교육캠퍼스 활성화(자체/직접)공기관등에대한경상적위탁사업비202405176700000006700000000450000000220000000당해예산N
92024일반회계본청본청평생교육국평생교육과본청본청평생교육국평생교육과평생학습 활성화(자체/직접)출연금2024051790000000090000000000900000000당해예산N
회계년도회계구분명예산부서구분명예산관서명예산실국명예산부서명부서구분명관서명실국구분명부서명세부사업내용세출관리세목구분명기준일자예산금액예산현재금액재배정금액지출누계금액집행잔여금액이월구분명사업자등록번호
87922024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터축산진흥업무지원(자체/직접)시책추진업무추진비2024051744000004400000013550003045000당해예산N
87932024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터조사료 품질관리 지원(기금/직접)재료비2024051720000002000000019910009000당해예산N
87942024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터한우젖소개량 경상지원(자치단체)(기금/직접)사무관리비2024051740000000400000000040000000당해예산N
87952024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터경기도 보증씨수소 개발(자체/직접)시험연구비202405172865000002865000000110439550176060450당해예산N
87962024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터희소한우개량 경상지원(자치단체)(국비/직접)사무관리비2024051711000000110000000011000000당해예산N
87972024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터희소한우개량 경상지원(자치단체)(국비/직접)재료비2024051713000000130000000101368102863190당해예산N
87982024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터말과 함께하는 어린이 말체험(자체/직접)사무관리비20240517285500002855000001024932018300680당해예산N
87992024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터승용마 거점번식지원센터 운영(자체/직접)사무관리비2024051720000000200000000020000000당해예산N
88002024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터승용마 거점번식지원센터 운영(자체/직접)자산및물품취득비202405175950000595000005594340355660당해예산N
88012024일반회계사업소경기도축산진흥센터축산동물복지국축산진흥센터사업소경기도축산진흥센터축산동물복지국축산진흥센터젖소(저지 등) 및 수정란 구입(자체/직접)자산및물품취득비202405173340000003340000000161800000172200000당해예산N

Duplicate rows

Most frequently occurring

회계년도회계구분명예산부서구분명예산관서명예산실국명예산부서명부서구분명관서명실국구분명부서명세부사업내용세출관리세목구분명기준일자예산금액예산현재금액재배정금액지출누계금액집행잔여금액이월구분명사업자등록번호# duplicates
02024소방안전본청소방재난본부소방재난본부회계장비담당관본청소방재난본부소방재난본부회계장비담당관소방관서 신축 및 이전(자체/직접)감리비2024051734036200034036200000340362000계속비이월예산N2
12024소방안전본청소방재난본부소방재난본부회계장비담당관본청소방재난본부소방재난본부회계장비담당관소방관서 신축 및 이전(자체/직접)자산및물품취득비2024051721920000021920000000219200000당해예산N2