Overview

Dataset statistics

Number of variables5
Number of observations1500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.7 KiB
Average record size in memory42.1 B

Variable types

Numeric2
Categorical2
Text1

Dataset

Description총계 기준으로 작성된 회계·기금별 규모 시계열 자료 *수치가 기본단위보다 적거나 수치가 없을 경우 0으로 표시. *2021년 일반회계 및 특별회계의 총계는 1, 2차 추경을 포함, 기금은 본예산 기준 *국가균형발전특별회계는 2010년부터 2014년까지는 광역지역발전특별회계, 2015년부터 2018년까지는 지역발전특별회계 *농업재해보험기금은 2007년부터 2008년까지는 농작물재해보험기금, 2009년은 농작물재해보험기금과 양식수산물재해보험기금의 합 *농업농촌공익기능증진직접지불기금은 2003년부터 2019년까지는 농업소득보전직접지불기금입니다. *산업기술진흥및사업화촉진기금은 2007년부터 2014년까지는 특정물질사용합리화기금(2015년부터는 산촉기금의 특설물질사용합리화 계정으로 편입) *양성평등기금은 2012년부터 2014년까지는 여성발전기금 *원자력기금은 2012년부터 2015년까지 원자력연구개발기금 *주택도시기금은 2021년부터 2014년까지는 국민주택기금 *중소기업창업및진흥기금은 2019년까지는 중소기업창업 및 진흥기금 *구조조정기금은 2014년 운용종료 *부실채권정리기금은 2012년 운용종료 *국가장학기금은 2011년부터 「한국장학재단 설립등에 관한 법률」에 따른 한국장학재단에서 잔여사무 및 관련사업 승계
URLhttps://www.data.go.kr/data/15062854/fileData.do

Alerts

연도 is highly overall correlated with 기준High correlation
기준 is highly overall correlated with 연도High correlation
기준 is highly imbalanced (59.8%)Imbalance
금액(억원) has 112 (7.5%) zerosZeros

Reproduction

Analysis started2023-12-12 01:25:07.606444
Analysis finished2023-12-12 01:25:08.776497
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015
Minimum2008
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T10:25:08.828398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12011
median2015
Q32019
95-th percentile2022
Maximum2022
Range14
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.3219347
Coefficient of variation (CV)0.0021448807
Kurtosis-1.210749
Mean2015
Median Absolute Deviation (MAD)4
Skewness0
Sum3022500
Variance18.679119
MonotonicityNot monotonic
2023-12-12T10:25:08.941688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2008 100
 
6.7%
2009 100
 
6.7%
2010 100
 
6.7%
2011 100
 
6.7%
2012 100
 
6.7%
2013 100
 
6.7%
2014 100
 
6.7%
2015 100
 
6.7%
2016 100
 
6.7%
2017 100
 
6.7%
Other values (5) 500
33.3%
ValueCountFrequency (%)
2008 100
6.7%
2009 100
6.7%
2010 100
6.7%
2011 100
6.7%
2012 100
6.7%
2013 100
6.7%
2014 100
6.7%
2015 100
6.7%
2016 100
6.7%
2017 100
6.7%
ValueCountFrequency (%)
2022 100
6.7%
2021 100
6.7%
2020 100
6.7%
2019 100
6.7%
2018 100
6.7%
2017 100
6.7%
2016 100
6.7%
2015 100
6.7%
2014 100
6.7%
2013 100
6.7%

기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
결산
1300 
본예산
176 
2차 추경
 
24

Length

Max length5
Median length2
Mean length2.1653333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
결산 1300
86.7%
본예산 176
 
11.7%
2차 추경 24
 
1.6%

Length

2023-12-12T10:25:09.084502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:25:09.192268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
결산 1300
85.3%
본예산 176
 
11.5%
2차 24
 
1.6%
추경 24
 
1.6%

구분
Categorical

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
기금 사업성기금
750 
특별회계 기타특별회계
240 
기금 금융성기금
180 
기금 사회보험성기금
105 
기금 계정성기금
90 
Other values (5)
135 

Length

Max length11
Median length8
Mean length8.69
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기금 사업성기금 750
50.0%
특별회계 기타특별회계 240
 
16.0%
기금 금융성기금 180
 
12.0%
기금 사회보험성기금 105
 
7.0%
기금 계정성기금 90
 
6.0%
특별회계 기업특별회계 75
 
5.0%
일반회계 15
 
1.0%
특별회계 15
 
1.0%
책임운영기관특별회계 15
 
1.0%
기금 15
 
1.0%

Length

2023-12-12T10:25:09.308465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:25:09.451798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기금 1140
38.8%
사업성기금 750
25.5%
특별회계 330
 
11.2%
기타특별회계 240
 
8.2%
금융성기금 180
 
6.1%
사회보험성기금 105
 
3.6%
계정성기금 90
 
3.1%
기업특별회계 75
 
2.6%
일반회계 15
 
0.5%
책임운영기관특별회계 15
 
0.5%

회계 기금명
Text

Distinct100
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-12T10:25:09.684903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length8.58
Min length3

Characters and Unicode

Total characters12870
Distinct characters173
Distinct categories3 ?
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 row일반회계
2nd row일반회계
3rd row일반회계
4th row일반회계
5th row일반회계
ValueCountFrequency (%)
기금 75
 
4.7%
특별회계 45
 
2.8%
일반회계 15
 
0.9%
자동차사고피해지원기금 15
 
0.9%
축산발전기금 15
 
0.9%
청소년육성기금 15
 
0.9%
지역신문발전기금 15
 
0.9%
중소기업창업및진흥기금 15
 
0.9%
주택도시기금 15
 
0.9%
정보통신진흥기금 15
 
0.9%
Other values (90) 1350
84.9%
2023-12-12T10:25:10.093177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1425
 
11.1%
금 1395
 
10.8%
계 465
 
3.6%
회 405
 
3.1%
별 375
 
2.9%
특 375
 
2.9%
보 270
 
2.1%
진 255
 
2.0%
업 255
 
2.0%
국 210
 
1.6%
Other values (163) 7440
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12675
98.5%
Space Separator 150
 
1.2%
Other Punctuation 45
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1425
 
11.2%
금 1395
 
11.0%
계 465
 
3.7%
회 405
 
3.2%
별 375
 
3.0%
특 375
 
3.0%
보 270
 
2.1%
진 255
 
2.0%
업 255
 
2.0%
국 210
 
1.7%
Other values (161) 7245
57.2%
Space Separator
ValueCountFrequency (%)
150
100.0%
Other Punctuation
ValueCountFrequency (%)
. 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12675
98.5%
Common 195
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1425
 
11.2%
금 1395
 
11.0%
계 465
 
3.7%
회 405
 
3.2%
별 375
 
3.0%
특 375
 
3.0%
보 270
 
2.1%
진 255
 
2.0%
업 255
 
2.0%
국 210
 
1.7%
Other values (161) 7245
57.2%
Common
ValueCountFrequency (%)
150
76.9%
. 45
 
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12675
98.5%
ASCII 195
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1425
 
11.2%
금 1395
 
11.0%
계 465
 
3.7%
회 405
 
3.2%
별 375
 
3.0%
특 375
 
3.0%
보 270
 
2.1%
진 255
 
2.0%
업 255
 
2.0%
국 210
 
1.7%
Other values (161) 7245
57.2%
ASCII
ValueCountFrequency (%)
150
76.9%
. 45
 
23.1%

금액(억원)
Real number (ℝ)

ZEROS 

Distinct1354
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217512.02
Minimum0
Maximum7736941
Zeros112
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-12T10:25:10.258901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12015.25
median9216
Q352559.25
95-th percentile1338310
Maximum7736941
Range7736941
Interquartile range (IQR)50544

Descriptive statistics

Standard deviation750715.58
Coefficient of variation (CV)3.4513752
Kurtosis38.738057
Mean217512.02
Median Absolute Deviation (MAD)8891
Skewness5.6831435
Sum3.2626802 × 108
Variance5.6357389 × 1011
MonotonicityNot monotonic
2023-12-12T10:25:10.419030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 112
 
7.5%
1378 3
 
0.2%
747 2
 
0.1%
23552 2
 
0.1%
1012 2
 
0.1%
1176 2
 
0.1%
7588 2
 
0.1%
1004 2
 
0.1%
651 2
 
0.1%
8269 2
 
0.1%
Other values (1344) 1369
91.3%
ValueCountFrequency (%)
0 112
7.5%
95 1
 
0.1%
98 1
 
0.1%
100 1
 
0.1%
101 1
 
0.1%
102 1
 
0.1%
104 1
 
0.1%
109 1
 
0.1%
111 1
 
0.1%
120 1
 
0.1%
ValueCountFrequency (%)
7736941 1
0.1%
7563337 1
0.1%
7247628 1
0.1%
6429754 1
0.1%
6215772 1
0.1%
6192914 1
0.1%
5832402 1
0.1%
5698990 1
0.1%
5426279 1
0.1%
5372430 1
0.1%

Interactions

2023-12-12T10:25:08.320066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:07.968249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:08.501840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:08.141278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:25:10.524075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도기준구분회계 기금명금액(억원)
연도1.0000.8090.0000.0000.000
기준0.8091.0000.2460.0000.031
구분0.0000.2461.0001.0000.830
회계 기금명0.0000.0001.0001.0000.872
금액(억원)0.0000.0310.8300.8721.000
2023-12-12T10:25:10.633243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준구분
기준1.0000.151
구분0.1511.000
2023-12-12T10:25:10.715739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도금액(억원)기준구분
연도1.0000.0980.7030.000
금액(억원)0.0981.0000.0180.397
기준0.7030.0181.0000.151
구분0.0000.3970.1511.000

Missing values

2023-12-12T10:25:08.641267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:25:08.739602image/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

연도기준구분회계 기금명금액(억원)
02008결산일반회계일반회계1754695
12009결산일반회계일반회계1998760
22010결산일반회계일반회계1971371
32011결산일반회계일반회계2074469
42012결산일반회계일반회계2206878
52013결산일반회계일반회계2295443
62014결산일반회계일반회계2363607
72015결산일반회계일반회계2578816
82016결산일반회계일반회계2739981
92017결산일반회계일반회계2804840
연도기준구분회계 기금명금액(억원)
14902013결산기금 금융성기금국가장학기금0
14912014결산기금 금융성기금국가장학기금0
14922015결산기금 금융성기금국가장학기금0
14932016결산기금 금융성기금국가장학기금0
14942017결산기금 금융성기금국가장학기금0
14952018결산기금 금융성기금국가장학기금0
14962019결산기금 금융성기금국가장학기금0
14972020결산기금 금융성기금국가장학기금0
14982021본예산기금 금융성기금국가장학기금0
14992022본예산기금 금융성기금국가장학기금0