Overview

Dataset statistics

Number of variables17
Number of observations6628
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory945.1 KiB
Average record size in memory146.0 B

Variable types

Text1
Categorical6
Numeric10

Dataset

Description공공기관 운영에 관한 법률에 따라 지정된 370개 공공기관의(부설기관 포함) 손익계산서(또는 포괄 손익계산서)상 주요항목으로 공기업은 반기결산 정보와 연도별 결산정보를, 그외 공공기관은 연도별 결산 정보 데이터를 제공
Author기획재정부
URLhttps://www.data.go.kr/data/15050505/fileData.do

Alerts

구분 is highly overall correlated with 항목 and 2 other fieldsHigh correlation
기금명 is highly overall correlated with 2018년 반기 and 7 other fieldsHigh correlation
기관유형 is highly overall correlated with 주무부처 and 2 other fieldsHigh correlation
주무부처 is highly overall correlated with 기관유형 and 2 other fieldsHigh correlation
상위기관 is highly overall correlated with 2018년 반기 and 12 other fieldsHigh correlation
2018년 반기 is highly overall correlated with 2019년 반기 and 3 other fieldsHigh correlation
2018년 결산 is highly overall correlated with 2019년 결산 and 4 other fieldsHigh correlation
2019년 반기 is highly overall correlated with 2018년 반기 and 5 other fieldsHigh correlation
2019년 결산 is highly overall correlated with 2018년 결산 and 4 other fieldsHigh correlation
2020년 반기 is highly overall correlated with 2019년 반기 and 4 other fieldsHigh correlation
2020년 결산 is highly overall correlated with 2018년 결산 and 4 other fieldsHigh correlation
2021년 반기 is highly overall correlated with 2019년 반기 and 4 other fieldsHigh correlation
2021년 결산 is highly overall correlated with 2018년 결산 and 4 other fieldsHigh correlation
2022년 반기 is highly overall correlated with 2018년 반기 and 5 other fieldsHigh correlation
2022년 결산 is highly overall correlated with 2018년 결산 and 4 other fieldsHigh correlation
항목 is highly overall correlated with 구분High correlation
기금명 is highly imbalanced (86.6%)Imbalance
상위기관 is highly imbalanced (91.2%)Imbalance
2018년 반기 is highly skewed (γ1 = 31.14468497)Skewed
2019년 반기 is highly skewed (γ1 = 31.39026419)Skewed
2020년 반기 is highly skewed (γ1 = 32.06986894)Skewed
2021년 반기 is highly skewed (γ1 = 30.47591031)Skewed
2022년 반기 is highly skewed (γ1 = 25.39571749)Skewed
2018년 반기 has 6011 (90.7%) zerosZeros
2018년 결산 has 1592 (24.0%) zerosZeros
2019년 반기 has 6002 (90.6%) zerosZeros
2019년 결산 has 1407 (21.2%) zerosZeros
2020년 반기 has 6000 (90.5%) zerosZeros
2020년 결산 has 1384 (20.9%) zerosZeros
2021년 반기 has 6002 (90.6%) zerosZeros
2021년 결산 has 1327 (20.0%) zerosZeros
2022년 반기 has 5975 (90.1%) zerosZeros
2022년 결산 has 1352 (20.4%) zerosZeros

Reproduction

Analysis started2023-12-11 23:28:23.689447
Analysis finished2023-12-11 23:28:37.330638
Duration13.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct360
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
2023-12-12T08:28:37.455455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.5372661
Min length5

Characters and Unicode

Total characters56585
Distinct characters266
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row(사)남북교류협력지원협회
2nd row(사)남북교류협력지원협회
3rd row(사)남북교류협력지원협회
4th row(사)남북교류협력지원협회
5th row(사)남북교류협력지원협회
ValueCountFrequency (%)
재단법인 117
 
1.7%
예금보험공사 52
 
0.8%
한국국제협력단 52
 
0.8%
한국농수산식품유통공사 45
 
0.7%
한국수출입은행 45
 
0.7%
한국방송통신전파진흥원 43
 
0.6%
한국언론진흥재단 43
 
0.6%
한국연구재단 43
 
0.6%
한국부동산원 40
 
0.6%
한국방송광고진흥공사 40
 
0.6%
Other values (352) 6258
92.3%
2023-12-12T08:28:37.847166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4602
 
8.1%
4051
 
7.2%
3815
 
6.7%
1855
 
3.3%
1451
 
2.6%
1317
 
2.3%
1223
 
2.2%
1115
 
2.0%
1096
 
1.9%
1026
 
1.8%
Other values (256) 35034
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54916
97.1%
Open Punctuation 594
 
1.0%
Close Punctuation 594
 
1.0%
Uppercase Letter 275
 
0.5%
Space Separator 150
 
0.3%
Decimal Number 28
 
< 0.1%
Other Punctuation 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4602
 
8.4%
4051
 
7.4%
3815
 
6.9%
1855
 
3.4%
1451
 
2.6%
1317
 
2.4%
1223
 
2.2%
1115
 
2.0%
1096
 
2.0%
1026
 
1.9%
Other values (241) 33365
60.8%
Uppercase Letter
ValueCountFrequency (%)
K 54
19.6%
S 40
14.5%
P 35
12.7%
D 33
12.0%
C 33
12.0%
M 19
 
6.9%
N 19
 
6.9%
I 14
 
5.1%
A 14
 
5.1%
E 14
 
5.1%
Open Punctuation
ValueCountFrequency (%)
( 594
100.0%
Close Punctuation
ValueCountFrequency (%)
) 594
100.0%
Space Separator
ValueCountFrequency (%)
150
100.0%
Decimal Number
ValueCountFrequency (%)
8 28
100.0%
Other Punctuation
ValueCountFrequency (%)
· 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54916
97.1%
Common 1394
 
2.5%
Latin 275
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4602
 
8.4%
4051
 
7.4%
3815
 
6.9%
1855
 
3.4%
1451
 
2.6%
1317
 
2.4%
1223
 
2.2%
1115
 
2.0%
1096
 
2.0%
1026
 
1.9%
Other values (241) 33365
60.8%
Latin
ValueCountFrequency (%)
K 54
19.6%
S 40
14.5%
P 35
12.7%
D 33
12.0%
C 33
12.0%
M 19
 
6.9%
N 19
 
6.9%
I 14
 
5.1%
A 14
 
5.1%
E 14
 
5.1%
Common
ValueCountFrequency (%)
( 594
42.6%
) 594
42.6%
150
 
10.8%
8 28
 
2.0%
· 28
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54916
97.1%
ASCII 1641
 
2.9%
None 28
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4602
 
8.4%
4051
 
7.4%
3815
 
6.9%
1855
 
3.4%
1451
 
2.6%
1317
 
2.4%
1223
 
2.2%
1115
 
2.0%
1096
 
2.0%
1026
 
1.9%
Other values (241) 33365
60.8%
ASCII
ValueCountFrequency (%)
( 594
36.2%
) 594
36.2%
150
 
9.1%
K 54
 
3.3%
S 40
 
2.4%
P 35
 
2.1%
D 33
 
2.0%
C 33
 
2.0%
8 28
 
1.7%
M 19
 
1.2%
Other values (4) 61
 
3.7%
None
ValueCountFrequency (%)
· 28
100.0%

기관유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
기타공공기관
4396 
준정부기관(위탁집행형)
1116 
공기업(준시장형)
496 
준정부기관(기금관리형)
 
316
공기업(시장형)
 
304

Length

Max length12
Median length6
Mean length7.6125528
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타공공기관 4396
66.3%
준정부기관(위탁집행형) 1116
 
16.8%
공기업(준시장형) 496
 
7.5%
준정부기관(기금관리형) 316
 
4.8%
공기업(시장형) 304
 
4.6%

Length

2023-12-12T08:28:37.991596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:28:38.094843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타공공기관 4396
66.3%
준정부기관(위탁집행형 1116
 
16.8%
공기업(준시장형 496
 
7.5%
준정부기관(기금관리형 316
 
4.8%
공기업(시장형 304
 
4.6%

주무부처
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
산업통상자원부
896 
과학기술정보통신부
843 
문화체육관광부
578 
국토교통부
552 
보건복지부
508 
Other values (30)
3251 

Length

Max length9
Median length8
Mean length5.8714544
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산업통상자원부 896
13.5%
과학기술정보통신부 843
12.7%
문화체육관광부 578
 
8.7%
국토교통부 552
 
8.3%
보건복지부 508
 
7.7%
국무조정실 378
 
5.7%
해양수산부 345
 
5.2%
교육부 328
 
4.9%
농림축산식품부 269
 
4.1%
금융위원회 229
 
3.5%
Other values (25) 1702
25.7%

Length

2023-12-12T08:28:38.218304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
산업통상자원부 896
13.5%
과학기술정보통신부 843
12.7%
문화체육관광부 578
 
8.7%
국토교통부 552
 
8.3%
보건복지부 508
 
7.7%
국무조정실 378
 
5.7%
해양수산부 345
 
5.2%
교육부 328
 
4.9%
농림축산식품부 269
 
4.1%
금융위원회 229
 
3.5%
Other values (25) 1702
25.7%

구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
고유사업(요약손익계산서(K-GAAP))
2982 
고유사업(요약 포괄손익계산서(K-IFRS))
1957 
고유사업(요약 연결포괄손익계산서(K-IFRS))
1218 
기금계정(요약 재정운영표)
372 
기금계정(요약 재정운영표)2
 
72
Other values (2)
 
27

Length

Max length26
Median length24
Mean length22.340223
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고유사업(요약손익계산서(K-GAAP))
2nd row고유사업(요약손익계산서(K-GAAP))
3rd row고유사업(요약손익계산서(K-GAAP))
4th row고유사업(요약손익계산서(K-GAAP))
5th row고유사업(요약손익계산서(K-GAAP))

Common Values

ValueCountFrequency (%)
고유사업(요약손익계산서(K-GAAP)) 2982
45.0%
고유사업(요약 포괄손익계산서(K-IFRS)) 1957
29.5%
고유사업(요약 연결포괄손익계산서(K-IFRS)) 1218
18.4%
기금계정(요약 재정운영표) 372
 
5.6%
기금계정(요약 재정운영표)2 72
 
1.1%
고유사업(요약연결손익계산서(K-GAAP)) 15
 
0.2%
기금계정(요약 재정운영표)3 12
 
0.2%

Length

2023-12-12T08:28:38.383654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:28:38.540781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고유사업(요약 3175
30.9%
고유사업(요약손익계산서(k-gaap 2982
29.1%
포괄손익계산서(k-ifrs 1957
19.1%
연결포괄손익계산서(k-ifrs 1218
 
11.9%
기금계정(요약 456
 
4.4%
재정운영표 372
 
3.6%
재정운영표)2 72
 
0.7%
고유사업(요약연결손익계산서(k-gaap 15
 
0.1%
재정운영표)3 12
 
0.1%

항목
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
03.매출원가
 
375
05.영업이익
 
375
02.순매출
 
375
04.판관비
 
375
10.총 비용
 
214
Other values (45)
4914 

Length

Max length25
Median length20
Mean length8.4983404
Min length5

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row01.매출
2nd row02.순매출
3rd row03.매출원가
4th row04.판관비
5th row05.영업이익

Common Values

ValueCountFrequency (%)
03.매출원가 375
 
5.7%
05.영업이익 375
 
5.7%
02.순매출 375
 
5.7%
04.판관비 375
 
5.7%
10.총 비용 214
 
3.2%
06.영업이익외 수익 214
 
3.2%
08.법인세 비용 214
 
3.2%
07.영업외 비용 214
 
3.2%
11.당기 순이익 214
 
3.2%
09.총 수익 214
 
3.2%
Other values (40) 3844
58.0%

Length

2023-12-12T08:28:38.688439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
비용 680
 
8.0%
수익 466
 
5.5%
03.매출원가 375
 
4.4%
02.순매출 375
 
4.4%
04.판관비 375
 
4.4%
05.영업이익 375
 
4.4%
11.당기 214
 
2.5%
01.매출 214
 
2.5%
09.총 214
 
2.5%
순이익 214
 
2.5%
Other values (47) 4980
58.7%

기금명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct37
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
<NA>
6184 
국민체육진흥기금
 
24
국제질병퇴치기금
 
12
소상공인시장진흥기금
 
12
국민연금기금
 
12
Other values (32)
 
384

Length

Max length14
Median length4
Mean length4.3041642
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6184
93.3%
국민체육진흥기금 24
 
0.4%
국제질병퇴치기금 12
 
0.2%
소상공인시장진흥기금 12
 
0.2%
국민연금기금 12
 
0.2%
중소기업매출채권보험계정 12
 
0.2%
근로복지진흥기금 12
 
0.2%
기술보증기금 12
 
0.2%
농어업재해재보험 12
 
0.2%
사립학교교직원연금기금 12
 
0.2%
Other values (27) 324
 
4.9%

Length

2023-12-12T08:28:38.852978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6184
93.0%
국민체육진흥기금 24
 
0.4%
방사성폐기물관리기금 12
 
0.2%
원자력기금원자력안전규제계정 12
 
0.2%
무역보험기금 12
 
0.2%
전력산업기반기금 12
 
0.2%
대외경제협력기금 12
 
0.2%
언론진흥기금 12
 
0.2%
문화예술진흥기금 12
 
0.2%
방송통신발전기금 12
 
0.2%
Other values (29) 348
 
5.2%

2018년 반기
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct577
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43720.673
Minimum-1962430
Maximum29043203
Zeros6011
Zeros (%)90.7%
Negative84
Negative (%)1.3%
Memory size58.4 KiB
2023-12-12T08:28:39.023176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1962430
5-th percentile0
Q10
median0
Q30
95-th percentile8547.75
Maximum29043203
Range31005633
Interquartile range (IQR)0

Descriptive statistics

Standard deviation736010.85
Coefficient of variation (CV)16.83439
Kurtosis1129.2522
Mean43720.673
Median Absolute Deviation (MAD)0
Skewness31.144685
Sum2.8978062 × 108
Variance5.4171198 × 1011
MonotonicityNot monotonic
2023-12-12T08:28:39.187115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6011
90.7%
2954664.0 2
 
< 0.1%
3775961.0 2
 
< 0.1%
1510877.0 2
 
< 0.1%
44528.0 2
 
< 0.1%
54118.0 2
 
< 0.1%
280985.0 2
 
< 0.1%
2603362.0 2
 
< 0.1%
3965563.0 2
 
< 0.1%
1379423.0 2
 
< 0.1%
Other values (567) 599
 
9.0%
ValueCountFrequency (%)
-1962430.0 1
< 0.1%
-1226489.0 1
< 0.1%
-1169058.0 1
< 0.1%
-1127739.0 1
< 0.1%
-830814.0 1
< 0.1%
-814731.0 1
< 0.1%
-793372.0 1
< 0.1%
-716019.0 1
< 0.1%
-692885.0 1
< 0.1%
-683319.0 1
< 0.1%
ValueCountFrequency (%)
29043203.0 2
< 0.1%
28603783.0 1
< 0.1%
13828064.0 2
< 0.1%
12674906.0 1
< 0.1%
9710718.0 2
< 0.1%
7142079.0 1
< 0.1%
3965563.0 2
< 0.1%
3775961.0 2
< 0.1%
3641308.0 1
< 0.1%
3463773.0 1
< 0.1%

2018년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3976
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224643.08
Minimum-44404108
Maximum78331098
Zeros1592
Zeros (%)24.0%
Negative851
Negative (%)12.8%
Memory size58.4 KiB
2023-12-12T08:28:39.358989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-44404108
5-th percentile-2388.45
Q10
median188.125
Q318748.5
95-th percentile472547.65
Maximum78331098
Range1.2273521 × 108
Interquartile range (IQR)18748.5

Descriptive statistics

Standard deviation2695005.7
Coefficient of variation (CV)11.996834
Kurtosis453.74216
Mean224643.08
Median Absolute Deviation (MAD)774
Skewness18.124742
Sum1.4889343 × 109
Variance7.2630559 × 1012
MonotonicityNot monotonic
2023-12-12T08:28:39.512425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1592
 
24.0%
1.0 25
 
0.4%
2.0 22
 
0.3%
4.0 17
 
0.3%
3.0 17
 
0.3%
5.0 15
 
0.2%
15.0 11
 
0.2%
6.0 10
 
0.2%
7.0 10
 
0.2%
35.0 10
 
0.2%
Other values (3966) 4899
73.9%
ValueCountFrequency (%)
-44404108.0 1
< 0.1%
-14831660.0 1
< 0.1%
-14821503.0 1
< 0.1%
-13880062.0 1
< 0.1%
-4347449.0 1
< 0.1%
-3959609.0 1
< 0.1%
-3916795.0 1
< 0.1%
-3895366.0 1
< 0.1%
-3893847.0 1
< 0.1%
-3521441.0 1
< 0.1%
ValueCountFrequency (%)
78331098.0 1
< 0.1%
75365372.0 2
< 0.1%
60627610.0 2
< 0.1%
58207721.0 1
< 0.1%
44958903.0 1
< 0.1%
44940670.0 1
< 0.1%
33842525.0 2
< 0.1%
32200792.0 1
< 0.1%
31078841.0 1
< 0.1%
30884820.0 1
< 0.1%

2019년 반기
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct574
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42805.017
Minimum-1545753
Maximum28319378
Zeros6002
Zeros (%)90.6%
Negative89
Negative (%)1.3%
Memory size58.4 KiB
2023-12-12T08:28:39.666696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1545753
5-th percentile0
Q10
median0
Q30
95-th percentile9254.05
Maximum28319378
Range29865131
Interquartile range (IQR)0

Descriptive statistics

Standard deviation715645.83
Coefficient of variation (CV)16.718737
Kurtosis1144.1027
Mean42805.017
Median Absolute Deviation (MAD)0
Skewness31.390264
Sum2.8371165 × 108
Variance5.1214895 × 1011
MonotonicityNot monotonic
2023-12-12T08:28:39.813965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6002
90.6%
68.0 3
 
< 0.1%
28795.0 3
 
< 0.1%
-66524.0 2
 
< 0.1%
245550.0 2
 
< 0.1%
482315.0 2
 
< 0.1%
25.0 2
 
< 0.1%
2003359.0 2
 
< 0.1%
13576115.0 2
 
< 0.1%
1325000.0 2
 
< 0.1%
Other values (564) 606
 
9.1%
ValueCountFrequency (%)
-1545753.0 1
< 0.1%
-1249730.0 1
< 0.1%
-1235344.0 1
< 0.1%
-1173334.0 1
< 0.1%
-928539.0 1
< 0.1%
-372419.0 1
< 0.1%
-292508.0 1
< 0.1%
-225668.0 1
< 0.1%
-216477.0 1
< 0.1%
-190110.0 1
< 0.1%
ValueCountFrequency (%)
28319378.0 2
< 0.1%
27964266.0 1
< 0.1%
13576115.0 2
< 0.1%
12298365.0 1
< 0.1%
8580634.0 2
< 0.1%
7191333.0 1
< 0.1%
4610778.0 2
< 0.1%
3791302.0 2
< 0.1%
3766656.0 2
< 0.1%
3705402.0 1
< 0.1%

2019년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4047
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean235854.68
Minimum-47832899
Maximum87484516
Zeros1407
Zeros (%)21.2%
Negative877
Negative (%)13.2%
Memory size58.4 KiB
2023-12-12T08:28:39.960508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-47832899
5-th percentile-2204.25
Q10
median281.835
Q321035.75
95-th percentile453217.65
Maximum87484516
Range1.3531742 × 108
Interquartile range (IQR)21035.75

Descriptive statistics

Standard deviation2867115
Coefficient of variation (CV)12.156277
Kurtosis492.0193
Mean235854.68
Median Absolute Deviation (MAD)976.5
Skewness18.71832
Sum1.5632448 × 109
Variance8.2203482 × 1012
MonotonicityNot monotonic
2023-12-12T08:28:40.177563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1407
 
21.2%
1.0 31
 
0.5%
3.0 27
 
0.4%
2.0 21
 
0.3%
5.0 17
 
0.3%
10.0 15
 
0.2%
6.0 12
 
0.2%
4.0 11
 
0.2%
36.0 11
 
0.2%
27.0 10
 
0.2%
Other values (4037) 5066
76.4%
ValueCountFrequency (%)
-47832899.0 1
< 0.1%
-15991837.0 1
< 0.1%
-15981660.0 1
< 0.1%
-15012855.0 1
< 0.1%
-4264152.0 1
< 0.1%
-4112346.0 1
< 0.1%
-3626601.0 1
< 0.1%
-3625278.0 1
< 0.1%
-3611417.0 1
< 0.1%
-3336348.0 1
< 0.1%
ValueCountFrequency (%)
87484516.0 1
< 0.1%
84809648.0 2
< 0.1%
59172890.0 2
< 0.1%
57779835.0 1
< 0.1%
48375775.0 1
< 0.1%
48008217.0 1
< 0.1%
35211722.0 2
< 0.1%
32995362.0 1
< 0.1%
32742360.0 1
< 0.1%
32447939.0 1
< 0.1%

2020년 반기
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct573
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38351.062
Minimum-1271792
Maximum28165660
Zeros6000
Zeros (%)90.5%
Negative140
Negative (%)2.1%
Memory size58.4 KiB
2023-12-12T08:28:40.329749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1271792
5-th percentile0
Q10
median0
Q30
95-th percentile3450.35
Maximum28165660
Range29437452
Interquartile range (IQR)0

Descriptive statistics

Standard deviation689725.77
Coefficient of variation (CV)17.984529
Kurtosis1190.7396
Mean38351.062
Median Absolute Deviation (MAD)0
Skewness32.069869
Sum2.5419084 × 108
Variance4.7572164 × 1011
MonotonicityNot monotonic
2023-12-12T08:28:40.506110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6000
90.5%
-8841.0 3
 
< 0.1%
280297.0 2
 
< 0.1%
814440.0 2
 
< 0.1%
2242278.0 2
 
< 0.1%
28165660.0 2
 
< 0.1%
-64086.0 2
 
< 0.1%
17901.0 2
 
< 0.1%
12062361.0 2
 
< 0.1%
15048.0 2
 
< 0.1%
Other values (563) 609
 
9.2%
ValueCountFrequency (%)
-1271792.0 1
< 0.1%
-1182835.0 1
< 0.1%
-1164840.0 1
< 0.1%
-1109786.0 1
< 0.1%
-770292.0 1
< 0.1%
-714536.0 1
< 0.1%
-701023.0 1
< 0.1%
-669300.0 1
< 0.1%
-581361.0 1
< 0.1%
-532784.0 1
< 0.1%
ValueCountFrequency (%)
28165660.0 2
< 0.1%
26065936.0 1
< 0.1%
12062361.0 2
< 0.1%
10996308.0 1
< 0.1%
9605825.0 2
< 0.1%
7140966.0 1
< 0.1%
4829024.0 2
< 0.1%
4100806.0 1
< 0.1%
4017724.0 2
< 0.1%
3498068.0 1
< 0.1%

2020년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4066
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248923.74
Minimum-51247541
Maximum92595008
Zeros1384
Zeros (%)20.9%
Negative923
Negative (%)13.9%
Memory size58.4 KiB
2023-12-12T08:28:40.677719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-51247541
5-th percentile-3060.7
Q10
median239
Q320920.5
95-th percentile521654
Maximum92595008
Range1.4384255 × 108
Interquartile range (IQR)20920.5

Descriptive statistics

Standard deviation2943746.2
Coefficient of variation (CV)11.825896
Kurtosis541.27644
Mean248923.74
Median Absolute Deviation (MAD)1030
Skewness19.308911
Sum1.6498665 × 109
Variance8.6656418 × 1012
MonotonicityNot monotonic
2023-12-12T08:28:40.835973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1384
 
20.9%
1.0 43
 
0.6%
2.0 23
 
0.3%
4.0 20
 
0.3%
5.0 17
 
0.3%
3.0 17
 
0.3%
30.0 13
 
0.2%
14.0 11
 
0.2%
16.0 10
 
0.2%
62.0 10
 
0.2%
Other values (4056) 5080
76.6%
ValueCountFrequency (%)
-51247541.0 1
< 0.1%
-17013534.0 1
< 0.1%
-17003357.0 1
< 0.1%
-15939175.0 1
< 0.1%
-4355539.0 1
< 0.1%
-3387544.0 1
< 0.1%
-2439173.0 1
< 0.1%
-2434548.0 1
< 0.1%
-2346501.0 1
< 0.1%
-2176590.0 1
< 0.1%
ValueCountFrequency (%)
92595008.0 2
< 0.1%
90939464.0 1
< 0.1%
58569314.0 2
< 0.1%
51818588.0 1
< 0.1%
51804596.0 1
< 0.1%
44527711.0 1
< 0.1%
34734854.0 2
< 0.1%
33040738.0 1
< 0.1%
28588536.0 1
< 0.1%
28151204.0 1
< 0.1%

2021년 반기
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct570
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42303.745
Minimum-655067
Maximum28684828
Zeros6002
Zeros (%)90.6%
Negative142
Negative (%)2.1%
Memory size58.4 KiB
2023-12-12T08:28:41.017494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-655067
5-th percentile0
Q10
median0
Q30
95-th percentile2912.95
Maximum28684828
Range29339895
Interquartile range (IQR)0

Descriptive statistics

Standard deviation731146.56
Coefficient of variation (CV)17.283259
Kurtosis1078.6366
Mean42303.745
Median Absolute Deviation (MAD)0
Skewness30.47591
Sum2.8038922 × 108
Variance5.345753 × 1011
MonotonicityNot monotonic
2023-12-12T08:28:41.177622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6002
90.6%
-55485.0 3
 
< 0.1%
2150858.0 2
 
< 0.1%
2551873.0 2
 
< 0.1%
55575.0 2
 
< 0.1%
1827274.0 2
 
< 0.1%
4298802.0 2
 
< 0.1%
355159.0 2
 
< 0.1%
20657.0 2
 
< 0.1%
12609234.0 2
 
< 0.1%
Other values (560) 607
 
9.2%
ValueCountFrequency (%)
-655067.0 1
< 0.1%
-626153.0 1
< 0.1%
-620188.0 1
< 0.1%
-609106.0 1
< 0.1%
-604252.0 1
< 0.1%
-595475.0 1
< 0.1%
-549569.0 1
< 0.1%
-489307.0 1
< 0.1%
-488482.0 1
< 0.1%
-468552.0 1
< 0.1%
ValueCountFrequency (%)
28684828.0 2
< 0.1%
27567141.0 1
< 0.1%
12609234.0 2
< 0.1%
12552350.0 2
< 0.1%
11537420.0 1
< 0.1%
8992828.0 1
< 0.1%
5504017.0 2
< 0.1%
4298802.0 2
< 0.1%
4039142.0 1
< 0.1%
3853300.0 1
< 0.1%

2021년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4094
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean282760.37
Minimum-53571609
Maximum1.0257251 × 108
Zeros1327
Zeros (%)20.0%
Negative787
Negative (%)11.9%
Memory size58.4 KiB
2023-12-12T08:28:41.345551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-53571609
5-th percentile-1981.65
Q10
median404.5
Q324238
95-th percentile564817
Maximum1.0257251 × 108
Range1.5614412 × 108
Interquartile range (IQR)24238

Descriptive statistics

Standard deviation3353822.4
Coefficient of variation (CV)11.861006
Kurtosis474.7898
Mean282760.37
Median Absolute Deviation (MAD)1095.5
Skewness17.439245
Sum1.8741357 × 109
Variance1.1248125 × 1013
MonotonicityNot monotonic
2023-12-12T08:28:41.513207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1327
 
20.0%
1.0 46
 
0.7%
3.0 20
 
0.3%
2.0 19
 
0.3%
4.0 17
 
0.3%
5.0 16
 
0.2%
7.0 13
 
0.2%
9.0 11
 
0.2%
15.0 11
 
0.2%
20.0 11
 
0.2%
Other values (4084) 5137
77.5%
ValueCountFrequency (%)
-53571609.0 1
< 0.1%
-37485169.0 1
< 0.1%
-37474970.0 1
< 0.1%
-16050383.0 1
< 0.1%
-7071570.0 1
< 0.1%
-5846499.0 1
< 0.1%
-5304522.0 1
< 0.1%
-5215581.0 1
< 0.1%
-4615967.0 1
< 0.1%
-4433836.0 1
< 0.1%
ValueCountFrequency (%)
102572511.0 2
< 0.1%
98744206.0 1
< 0.1%
63644290.0 1
< 0.1%
60673587.0 2
< 0.1%
54172519.0 1
< 0.1%
50911519.0 1
< 0.1%
42414186.0 1
< 0.1%
35587512.0 2
< 0.1%
34861136.0 1
< 0.1%
34207483.0 1
< 0.1%

2022년 반기
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct596
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46649.47
Minimum-14917294
Maximum44877826
Zeros5975
Zeros (%)90.1%
Negative131
Negative (%)2.0%
Memory size58.4 KiB
2023-12-12T08:28:41.998583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-14917294
5-th percentile0
Q10
median0
Q30
95-th percentile6107.45
Maximum44877826
Range59795120
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1026853.8
Coefficient of variation (CV)22.012121
Kurtosis950.88586
Mean46649.47
Median Absolute Deviation (MAD)0
Skewness25.395717
Sum3.0919269 × 108
Variance1.0544286 × 1012
MonotonicityNot monotonic
2023-12-12T08:28:42.205648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5975
90.1%
5317.0 3
 
< 0.1%
-18766.0 3
 
< 0.1%
619.0 2
 
< 0.1%
1926290.0 2
 
< 0.1%
278018.0 2
 
< 0.1%
3457.0 2
 
< 0.1%
-114391.0 2
 
< 0.1%
198563.0 2
 
< 0.1%
296833.0 2
 
< 0.1%
Other values (586) 633
 
9.6%
ValueCountFrequency (%)
-14917294.0 1
< 0.1%
-14303270.0 1
< 0.1%
-10790049.0 1
< 0.1%
-10761744.0 1
< 0.1%
-9881740.0 1
< 0.1%
-4155550.0 1
< 0.1%
-438185.0 1
< 0.1%
-434664.0 1
< 0.1%
-394926.0 1
< 0.1%
-338641.0 1
< 0.1%
ValueCountFrequency (%)
44877826.0 1
< 0.1%
31992105.0 2
< 0.1%
22832411.0 2
< 0.1%
21427204.0 1
< 0.1%
9053810.0 2
< 0.1%
7150133.0 1
< 0.1%
5133437.0 2
< 0.1%
4429599.0 1
< 0.1%
4375585.0 2
< 0.1%
4254469.0 1
< 0.1%

2022년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4152
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346002.64
Minimum-55949251
Maximum1.1376001 × 108
Zeros1352
Zeros (%)20.4%
Negative700
Negative (%)10.6%
Memory size58.4 KiB
2023-12-12T08:28:42.370876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-55949251
5-th percentile-1189.25
Q10
median625.5
Q326986
95-th percentile642059.3
Maximum1.1376001 × 108
Range1.6970926 × 108
Interquartile range (IQR)26986

Descriptive statistics

Standard deviation4225620.4
Coefficient of variation (CV)12.212683
Kurtosis342.78946
Mean346002.64
Median Absolute Deviation (MAD)1179.5
Skewness15.344679
Sum2.2933055 × 109
Variance1.7855868 × 1013
MonotonicityNot monotonic
2023-12-12T08:28:42.571571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1352
 
20.4%
1.0 34
 
0.5%
2.0 25
 
0.4%
3.0 18
 
0.3%
5.0 14
 
0.2%
10.0 13
 
0.2%
6.0 11
 
0.2%
4.0 11
 
0.2%
15.0 10
 
0.2%
7.0 10
 
0.2%
Other values (4142) 5130
77.4%
ValueCountFrequency (%)
-55949251.0 1
< 0.1%
-33843619.0 1
< 0.1%
-32655153.0 1
< 0.1%
-26461557.0 1
< 0.1%
-26451219.0 1
< 0.1%
-24466853.0 1
< 0.1%
-24429108.0 1
< 0.1%
-23182239.0 1
< 0.1%
-16805559.0 1
< 0.1%
-9926416.0 1
< 0.1%
ValueCountFrequency (%)
113760010.0 2
< 0.1%
107787501.0 1
< 0.1%
100903594.0 1
< 0.1%
71257863.0 2
< 0.1%
56555839.0 1
< 0.1%
54380550.0 2
< 0.1%
53620703.0 1
< 0.1%
53168642.0 1
< 0.1%
51724287.0 2
< 0.1%
48828263.0 1
< 0.1%

상위기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size51.9 KiB
<NA>
6403 
국민건강보험공단
 
33
한국해양과학기술원
 
28
한국연구재단
 
19
정보통신산업진흥원
 
19
Other values (9)
 
126

Length

Max length11
Median length4
Mean length4.1371454
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6403
96.6%
국민건강보험공단 33
 
0.5%
한국해양과학기술원 28
 
0.4%
한국연구재단 19
 
0.3%
정보통신산업진흥원 19
 
0.3%
한국화학연구원 14
 
0.2%
한국원자력의학원 14
 
0.2%
한국식품연구원 14
 
0.2%
한국과학기술연구원 14
 
0.2%
한국과학기술기획평가원 14
 
0.2%
Other values (4) 56
 
0.8%

Length

2023-12-12T08:28:42.718780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6403
96.6%
국민건강보험공단 33
 
0.5%
한국해양과학기술원 28
 
0.4%
한국연구재단 19
 
0.3%
정보통신산업진흥원 19
 
0.3%
한국화학연구원 14
 
0.2%
한국원자력의학원 14
 
0.2%
한국식품연구원 14
 
0.2%
한국과학기술연구원 14
 
0.2%
한국과학기술기획평가원 14
 
0.2%
Other values (4) 56
 
0.8%

Interactions

2023-12-12T08:28:35.750917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.335434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.413825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.341315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.326002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.599570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.550542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.560316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.657635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.809083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.846770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.427676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.494273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.431454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.432740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.695602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.661926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.667966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.767712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.911507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.221395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.539559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.579676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.553137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.540763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.789467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.777863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.781669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.876340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.005219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.303320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.681067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.680530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.648649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.908409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.877625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.885389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.894054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.969050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.090932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.386527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.779819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.770619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.740265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.002372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.963648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.975752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.990438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.078000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.173298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.469847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:26.898206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.856995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.833646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.094724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.082217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.064838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.084023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.217881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.256334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.554823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.017115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.947454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.929586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.200415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.190625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.153796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.183424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.342643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.343739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.652824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.142123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.048732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.047756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.305001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.290226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.245981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.297995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.471329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.428167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.756422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.246806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.153227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.145499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.411530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.385697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.354902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.429202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.586479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.531657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:36.840625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:27.326073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:28.244502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:29.232638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:30.507085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:31.467898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:32.454026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:33.547730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:34.706448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:28:35.641334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:28:42.814151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
기관유형1.0000.8160.5900.6430.9980.2230.1890.2030.1450.1860.1390.1460.1580.2260.1501.000
주무부처0.8161.0000.6670.2821.0000.0000.2150.0000.2100.0000.2490.0000.2090.0000.2141.000
구분0.5900.6671.0000.8871.0000.1700.1310.1480.1760.1060.1580.0860.1070.0990.1090.900
항목0.6430.2820.8871.0000.0000.0950.3040.0550.2230.0000.2360.0000.2620.0000.1620.000
기금명0.9981.0001.0000.0001.000NaN0.416NaN0.416NaN0.416NaN0.694NaN0.611NaN
2018년 반기0.2230.0000.1700.095NaN1.0000.7650.9970.8320.9430.8400.9130.7180.9010.733NaN
2018년 결산0.1890.2150.1310.3040.4160.7651.0000.7840.9460.8020.9550.7800.9850.8920.943NaN
2019년 반기0.2030.0000.1480.055NaN0.9970.7841.0000.8450.9810.8560.9040.7340.9120.719NaN
2019년 결산0.1450.2100.1760.2230.4160.8320.9460.8451.0000.6840.9890.6920.9250.6620.825NaN
2020년 반기0.1860.0000.1060.000NaN0.9430.8020.9810.6841.0000.6830.9860.7620.9450.747NaN
2020년 결산0.1390.2490.1580.2360.4160.8400.9550.8560.9890.6831.0000.6850.9270.6630.835NaN
2021년 반기0.1460.0000.0860.000NaN0.9130.7800.9040.6920.9860.6851.0000.7640.8440.709NaN
2021년 결산0.1580.2090.1070.2620.6940.7180.9850.7340.9250.7620.9270.7641.0000.8590.952NaN
2022년 반기0.2260.0000.0990.000NaN0.9010.8920.9120.6620.9450.6630.8440.8591.0000.942NaN
2022년 결산0.1500.2140.1090.1620.6110.7330.9430.7190.8250.7470.8350.7090.9520.9421.000NaN
상위기관1.0001.0000.9000.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1.000
2023-12-12T08:28:42.960125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기금명기관유형항목주무부처상위기관
구분1.0000.9620.4310.6050.3190.872
기금명0.9621.0000.9530.0000.973NaN
기관유형0.4310.9531.0000.3370.5070.975
항목0.6050.0000.3371.0000.0580.000
주무부처0.3190.9730.5070.0581.0000.982
상위기관0.872NaN0.9750.0000.9821.000
2023-12-12T08:28:43.119050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산기관유형주무부처구분항목기금명상위기관
2018년 반기1.0000.2370.6980.1810.4820.0590.4480.1140.5020.1210.1440.0000.0600.0381.0001.000
2018년 결산0.2371.0000.2630.8100.1750.6960.1600.6680.1640.6470.1190.0770.0720.1210.1541.000
2019년 반기0.6980.2631.0000.2510.5950.1130.6040.1580.5960.1440.1300.0000.0520.0221.0001.000
2019년 결산0.1810.8100.2511.0000.1960.7750.1990.7590.1900.7380.0960.0710.0640.0980.1541.000
2020년 반기0.4820.1750.5950.1961.0000.2500.6780.2170.5370.1610.1260.0000.0630.0001.0001.000
2020년 결산0.0590.6960.1130.7750.2501.0000.2260.8280.1840.7500.0920.0860.0580.1030.1541.000
2021년 반기0.4480.1600.6040.1990.6780.2261.0000.2890.7460.2360.0990.0000.0510.0001.0001.000
2021년 결산0.1140.6680.1580.7590.2170.8280.2891.0000.2520.8450.1000.0740.0590.1060.3261.000
2022년 반기0.5020.1640.5960.1900.5370.1840.7460.2521.0000.2670.1430.0000.0540.0001.0001.000
2022년 결산0.1210.6470.1440.7380.1610.7500.2360.8450.2671.0000.0950.0760.0610.0750.2691.000
기관유형0.1440.1190.1300.0960.1260.0920.0990.1000.1430.0951.0000.5070.4310.3370.9530.975
주무부처0.0000.0770.0000.0710.0000.0860.0000.0740.0000.0760.5071.0000.3190.0580.9730.982
구분0.0600.0720.0520.0640.0630.0580.0510.0590.0540.0610.4310.3191.0000.6050.9620.872
항목0.0380.1210.0220.0980.0000.1030.0000.1060.0000.0750.3370.0580.6051.0000.0000.000
기금명1.0000.1541.0000.1541.0000.1541.0000.3261.0000.2690.9530.9730.9620.0001.0000.000
상위기관1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.9750.9820.8720.0000.0001.000

Missing values

2023-12-12T08:28:36.970159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:28:37.219117image/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

기관명기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
0(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))01.매출<NA>0.06140.00.04489.00.03857.00.03925.00.04113.0<NA>
1(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))02.순매출<NA>0.06140.00.04489.00.03857.00.03925.00.04113.0<NA>
2(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))03.매출원가<NA>0.03882.00.02199.00.01190.00.01074.00.01421.0<NA>
3(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))04.판관비<NA>0.02182.00.02334.00.02511.00.02684.00.02722.0<NA>
4(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))05.영업이익<NA>0.076.00.0-44.00.0156.00.0167.00.0-30.0<NA>
5(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))06.영업이익외 수익<NA>0.00.00.00.00.00.00.00.00.00.0<NA>
6(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))07.영업외 비용<NA>0.00.00.00.00.00.00.00.00.00.0<NA>
7(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))08.법인세 비용<NA>0.00.00.00.00.00.00.00.00.00.0<NA>
8(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))09.총 수익<NA>0.06140.00.04489.00.03857.00.03925.00.04113.0<NA>
9(사)남북교류협력지원협회기타공공기관통일부고유사업(요약손익계산서(K-GAAP))10.총 비용<NA>0.06064.00.04533.00.03701.00.03758.00.04143.0<NA>
기관명기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
6618육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))05.영업이익<NA>0.073.00.0153.00.0-572.00.016.00.0-77.0경제인문사회연구회
6619육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))06.영업이익외 수익<NA>0.0113.00.0172.00.0253.00.0156.00.0159.0경제인문사회연구회
6620육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))07.영업외 비용<NA>0.058.00.0204.00.0177.00.084.00.051.0경제인문사회연구회
6621육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))08.법인세 비용<NA>0.00.00.00.00.00.00.00.00.00.0경제인문사회연구회
6622육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))09.총 수익<NA>0.09070.00.011309.00.09966.00.010008.00.010524.0경제인문사회연구회
6623육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))10.총 비용<NA>0.08942.00.011188.00.010462.00.09920.00.010493.0경제인문사회연구회
6624육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))11.당기 순이익<NA>0.0128.00.0121.00.0-496.00.088.00.031.0경제인문사회연구회
6625육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))12.매출액순이익률<NA>0.01.430.01.090.0-5.110.00.890.00.3경제인문사회연구회
6626육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))13.자기자본회전율<NA>0.0596.340.0725.070.01426.280.01541.780.01985.63경제인문사회연구회
6627육아정책연구소기타공공기관국무조정실고유사업(요약손익계산서(K-GAAP))14.이자비용<NA>0.00.00.00.00.00.00.00.00.00.0경제인문사회연구회