Overview

Dataset statistics

Number of variables17
Number of observations5041
Missing cells22725
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory718.9 KiB
Average record size in memory146.0 B

Variable types

Text1
Categorical6
Numeric10

Dataset

Description공공기관 운영에 관한 법률에 따라 지정된 370개 공공기관의(부설기관 포함) 재무상태표상 주요항목으로 공기업은 반기결산 정보와 연도별 결산정보를, 그외 공공기관은 연도별 걸산 정보 데이터를 제공
Author기획재정부
URLhttps://www.data.go.kr/data/3045608/fileData.do

Alerts

기관유형 is highly overall correlated with 주무부처 and 2 other fieldsHigh correlation
기금명 is highly overall correlated with 기관유형 and 2 other fieldsHigh correlation
주무부처 is highly overall correlated with 기관유형 and 2 other fieldsHigh correlation
구분 is highly overall correlated with 항목 and 2 other fieldsHigh correlation
상위기관 is highly overall correlated with 2018년 결산 and 7 other fieldsHigh correlation
2018년 반기 is highly overall correlated with 2018년 결산 and 8 other fieldsHigh correlation
2018년 결산 is highly overall correlated with 2018년 반기 and 9 other fieldsHigh correlation
2019년 반기 is highly overall correlated with 2018년 반기 and 8 other fieldsHigh correlation
2019년 결산 is highly overall correlated with 2018년 반기 and 9 other fieldsHigh correlation
2020년 반기 is highly overall correlated with 2018년 반기 and 8 other fieldsHigh correlation
2020년 결산 is highly overall correlated with 2018년 반기 and 9 other fieldsHigh correlation
2021년 반기 is highly overall correlated with 2018년 반기 and 8 other fieldsHigh correlation
2021년 결산 is highly overall correlated with 2018년 반기 and 9 other fieldsHigh correlation
2022년 반기 is highly overall correlated with 2018년 반기 and 8 other fieldsHigh correlation
2022년 결산 is highly overall correlated with 2018년 반기 and 9 other fieldsHigh correlation
항목 is highly overall correlated with 구분High correlation
기금명 is highly imbalanced (75.7%)Imbalance
상위기관 is highly imbalanced (91.3%)Imbalance
2018년 반기 has 4545 (90.2%) missing valuesMissing
2019년 반기 has 4545 (90.2%) missing valuesMissing
2020년 반기 has 4545 (90.2%) missing valuesMissing
2021년 반기 has 4545 (90.2%) missing valuesMissing
2022년 반기 has 4545 (90.2%) missing valuesMissing
2018년 반기 has 107 (2.1%) zerosZeros
2018년 결산 has 1016 (20.2%) zerosZeros
2019년 반기 has 104 (2.1%) zerosZeros
2019년 결산 has 925 (18.3%) zerosZeros
2020년 반기 has 103 (2.0%) zerosZeros
2020년 결산 has 917 (18.2%) zerosZeros
2021년 반기 has 102 (2.0%) zerosZeros
2021년 결산 has 894 (17.7%) zerosZeros
2022년 반기 has 89 (1.8%) zerosZeros
2022년 결산 has 919 (18.2%) zerosZeros

Reproduction

Analysis started2023-12-13 00:47:11.199763
Analysis finished2023-12-13 00:47:20.668162
Duration9.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct361
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
2023-12-13T09:47:20.797166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.5318389
Min length5

Characters and Unicode

Total characters43009
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 89
 
1.7%
신용보증기금 54
 
1.0%
한국농수산식품유통공사 49
 
1.0%
한국수출입은행 49
 
1.0%
한국방송통신전파진흥원 48
 
0.9%
한국연구재단 48
 
0.9%
한국언론진흥재단 48
 
0.9%
한국국제협력단 43
 
0.8%
예금보험공사 43
 
0.8%
한국전력공사 31
 
0.6%
Other values (353) 4651
90.3%
2023-12-13T09:47:21.080055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3489
 
8.1%
3040
 
7.1%
2878
 
6.7%
1400
 
3.3%
1152
 
2.7%
976
 
2.3%
947
 
2.2%
861
 
2.0%
849
 
2.0%
836
 
1.9%
Other values (256) 26581
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41859
97.3%
Close Punctuation 403
 
0.9%
Open Punctuation 403
 
0.9%
Uppercase Letter 188
 
0.4%
Space Separator 112
 
0.3%
Other Punctuation 22
 
0.1%
Decimal Number 22
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3489
 
8.3%
3040
 
7.3%
2878
 
6.9%
1400
 
3.3%
1152
 
2.8%
976
 
2.3%
947
 
2.3%
861
 
2.1%
849
 
2.0%
836
 
2.0%
Other values (241) 25431
60.8%
Uppercase Letter
ValueCountFrequency (%)
K 36
19.1%
S 25
13.3%
P 24
12.8%
C 23
12.2%
D 23
12.2%
M 12
 
6.4%
N 12
 
6.4%
I 11
 
5.9%
E 11
 
5.9%
A 11
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 403
100.0%
Open Punctuation
ValueCountFrequency (%)
( 403
100.0%
Space Separator
ValueCountFrequency (%)
112
100.0%
Other Punctuation
ValueCountFrequency (%)
· 22
100.0%
Decimal Number
ValueCountFrequency (%)
8 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41859
97.3%
Common 962
 
2.2%
Latin 188
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3489
 
8.3%
3040
 
7.3%
2878
 
6.9%
1400
 
3.3%
1152
 
2.8%
976
 
2.3%
947
 
2.3%
861
 
2.1%
849
 
2.0%
836
 
2.0%
Other values (241) 25431
60.8%
Latin
ValueCountFrequency (%)
K 36
19.1%
S 25
13.3%
P 24
12.8%
C 23
12.2%
D 23
12.2%
M 12
 
6.4%
N 12
 
6.4%
I 11
 
5.9%
E 11
 
5.9%
A 11
 
5.9%
Common
ValueCountFrequency (%)
) 403
41.9%
( 403
41.9%
112
 
11.6%
· 22
 
2.3%
8 22
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41859
97.3%
ASCII 1128
 
2.6%
None 22
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3489
 
8.3%
3040
 
7.3%
2878
 
6.9%
1400
 
3.3%
1152
 
2.8%
976
 
2.3%
947
 
2.3%
861
 
2.1%
849
 
2.0%
836
 
2.0%
Other values (241) 25431
60.8%
ASCII
ValueCountFrequency (%)
) 403
35.7%
( 403
35.7%
112
 
9.9%
K 36
 
3.2%
S 25
 
2.2%
P 24
 
2.1%
C 23
 
2.0%
D 23
 
2.0%
8 22
 
2.0%
M 12
 
1.1%
Other values (4) 45
 
4.0%
None
ValueCountFrequency (%)
· 22
100.0%

기관유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
기타공공기관
3369 
준정부기관(위탁집행형)
819 
준정부기관(기금관리형)
 
334
공기업(준시장형)
 
320
공기업(시장형)
 
199

Length

Max length12
Median length6
Mean length7.6417378
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타공공기관 3369
66.8%
준정부기관(위탁집행형) 819
 
16.2%
준정부기관(기금관리형) 334
 
6.6%
공기업(준시장형) 320
 
6.3%
공기업(시장형) 199
 
3.9%

Length

2023-12-13T09:47:21.191171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:47:21.271731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타공공기관 3369
66.8%
준정부기관(위탁집행형 819
 
16.2%
준정부기관(기금관리형 334
 
6.6%
공기업(준시장형 320
 
6.3%
공기업(시장형 199
 
3.9%

주무부처
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
과학기술정보통신부
658 
산업통상자원부
622 
문화체육관광부
474 
국토교통부
378 
보건복지부
372 
Other values (30)
2537 

Length

Max length9
Median length8
Mean length5.8893077
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
과학기술정보통신부 658
13.1%
산업통상자원부 622
12.3%
문화체육관광부 474
 
9.4%
국토교통부 378
 
7.5%
보건복지부 372
 
7.4%
국무조정실 297
 
5.9%
교육부 269
 
5.3%
해양수산부 236
 
4.7%
농림축산식품부 224
 
4.4%
금융위원회 209
 
4.1%
Other values (25) 1302
25.8%

Length

2023-12-13T09:47:21.362730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
과학기술정보통신부 658
13.1%
산업통상자원부 622
12.3%
문화체육관광부 474
 
9.4%
국토교통부 378
 
7.5%
보건복지부 372
 
7.4%
국무조정실 297
 
5.9%
교육부 269
 
5.3%
해양수산부 236
 
4.7%
농림축산식품부 224
 
4.4%
금융위원회 209
 
4.1%
Other values (25) 1302
25.8%

구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))
2354 
고유사업(요약 재무상태표(K-IFRS) - 자회사가 없는 경우)
1212 
고유사업(요약 연결재무상태표(K-IFRS) - 자회사가 있는 경우)
702 
기금계정(요약 재정상태표)
684 
고유사업(K-IFRS - 금융)
 
77

Length

Max length37
Median length36
Mean length31.689546
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))
2nd row고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))
3rd row고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))
4th row고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))
5th row고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))

Common Values

ValueCountFrequency (%)
고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우)) 2354
46.7%
고유사업(요약 재무상태표(K-IFRS) - 자회사가 없는 경우) 1212
24.0%
고유사업(요약 연결재무상태표(K-IFRS) - 자회사가 있는 경우) 702
 
13.9%
기금계정(요약 재정상태표) 684
 
13.6%
고유사업(K-IFRS - 금융) 77
 
1.5%
고유사업(요약 연결재무상태표(K-GAAP, 자회사가 있는 경우)) 12
 
0.2%

Length

2023-12-13T09:47:21.449164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:47:21.526633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고유사업(요약 4280
17.2%
자회사가 4280
17.2%
경우 4280
17.2%
없는 3566
14.3%
재무상태표(k-gaap 2354
9.4%
1991
8.0%
재무상태표(k-ifrs 1212
 
4.9%
있는 714
 
2.9%
연결재무상태표(k-ifrs 702
 
2.8%
기금계정(요약 684
 
2.7%
Other values (4) 850
 
3.4%

항목
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
01.유동자산
408 
06.부채총계
376 
03.자산총계
376 
04.유동부채
370 
05.비유동부채
370 
Other values (39)
3141 

Length

Max length18
Median length7
Mean length7.2997421
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row01.유동자산
2nd row02.비유동자산
3rd row03.자산총계
4th row04.유동부채
5th row05.비유동부채

Common Values

ValueCountFrequency (%)
01.유동자산 408
 
8.1%
06.부채총계 376
 
7.5%
03.자산총계 376
 
7.5%
04.유동부채 370
 
7.3%
05.비유동부채 370
 
7.3%
02.비유동자산 370
 
7.3%
07.자본금 316
 
6.3%
08.기타 316
 
6.3%
11.부채비율 214
 
4.2%
10.금융부채 214
 
4.2%
Other values (34) 1711
33.9%

Length

2023-12-13T09:47:21.624699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
01.유동자산 408
 
8.1%
03.자산총계 376
 
7.5%
06.부채총계 376
 
7.5%
04.유동부채 370
 
7.3%
05.비유동부채 370
 
7.3%
02.비유동자산 370
 
7.3%
07.자본금 316
 
6.3%
08.기타 316
 
6.3%
11.부채비율 214
 
4.2%
10.금융부채 214
 
4.2%
Other values (34) 1711
33.9%

기금명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct38
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
<NA>
4357 
국민체육진흥기금
 
36
산업기반신용보증기금
 
18
농산물가격안정기금
 
18
국민연금기금
 
18
Other values (33)
594 

Length

Max length14
Median length4
Mean length4.6105931
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> 4357
86.4%
국민체육진흥기금 36
 
0.7%
산업기반신용보증기금 18
 
0.4%
농산물가격안정기금 18
 
0.4%
국민연금기금 18
 
0.4%
근로복지진흥기금 18
 
0.4%
기술보증기금 18
 
0.4%
농어업재해재보험 18
 
0.4%
사립학교교직원연금기금 18
 
0.4%
소상공인시장진흥기금 18
 
0.4%
Other values (28) 504
 
10.0%

Length

2023-12-13T09:47:21.716775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4357
85.8%
국민체육진흥기금 36
 
0.7%
무역보험기금 18
 
0.4%
전력산업기반기금 18
 
0.4%
언론진흥기금 18
 
0.4%
문화예술진흥기금 18
 
0.4%
방송통신발전기금 18
 
0.4%
정보통신진흥기금 18
 
0.4%
사학진흥기금 18
 
0.4%
산업기술진흥및사업화촉진기금 18
 
0.4%
Other values (30) 540
 
10.6%

2018년 반기
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct385
Distinct (%)77.6%
Missing4545
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean6517000.8
Minimum-9737106
Maximum1.8578612 × 108
Zeros107
Zeros (%)2.1%
Negative9
Negative (%)0.2%
Memory size44.4 KiB
2023-12-13T09:47:22.052998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9737106
5-th percentile0
Q133.4775
median298808
Q33816777.5
95-th percentile31157265
Maximum1.8578612 × 108
Range1.9552323 × 108
Interquartile range (IQR)3816744

Descriptive statistics

Standard deviation20215633
Coefficient of variation (CV)3.1019842
Kurtosis35.900396
Mean6517000.8
Median Absolute Deviation (MAD)298808
Skewness5.4777572
Sum3.2324324 × 109
Variance4.0867183 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:22.174239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 107
 
2.1%
9000.0 2
 
< 0.1%
34448512.0 2
 
< 0.1%
4191345.0 2
 
< 0.1%
935025.0 2
 
< 0.1%
902930.0 2
 
< 0.1%
7739678.0 1
 
< 0.1%
31544.0 1
 
< 0.1%
7708134.0 1
 
< 0.1%
-739386.0 1
 
< 0.1%
Other values (375) 375
 
7.4%
(Missing) 4545
90.2%
ValueCountFrequency (%)
-9737106.0 1
 
< 0.1%
-5703981.0 1
 
< 0.1%
-1379958.0 1
 
< 0.1%
-983872.0 1
 
< 0.1%
-971927.0 1
 
< 0.1%
-739386.0 1
 
< 0.1%
-11945.0 1
 
< 0.1%
-2031.0 1
 
< 0.1%
-916.0 1
 
< 0.1%
0.0 107
2.1%
ValueCountFrequency (%)
185786125.0 1
< 0.1%
175007998.0 1
< 0.1%
165357340.0 1
< 0.1%
130870331.0 1
< 0.1%
114507734.0 1
< 0.1%
97665882.0 1
< 0.1%
89862692.0 1
< 0.1%
88269978.0 1
< 0.1%
85145306.0 1
< 0.1%
75186714.0 1
< 0.1%

2018년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3635
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2322600.3
Minimum-7.9513747 × 108
Maximum8.0702211 × 108
Zeros1016
Zeros (%)20.2%
Negative114
Negative (%)2.3%
Memory size44.4 KiB
2023-12-13T09:47:22.300679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.9513747 × 108
5-th percentile0
Q16.97
median3840
Q374133
95-th percentile3928477
Maximum8.0702211 × 108
Range1.6021596 × 109
Interquartile range (IQR)74126.03

Descriptive statistics

Standard deviation31497117
Coefficient of variation (CV)13.561144
Kurtosis431.74331
Mean2322600.3
Median Absolute Deviation (MAD)3840
Skewness6.6392841
Sum1.1708228 × 1010
Variance9.9206836 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:22.411431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1016
 
20.2%
1.0 69
 
1.4%
2.0 12
 
0.2%
112.0 7
 
0.1%
140.0 4
 
0.1%
341.0 4
 
0.1%
150.0 4
 
0.1%
34670.0 4
 
0.1%
1122.0 4
 
0.1%
1872.0 4
 
0.1%
Other values (3625) 3913
77.6%
ValueCountFrequency (%)
-795137469.0 1
< 0.1%
-788808337.0 1
< 0.1%
-54816073.0 1
< 0.1%
-11561475.0 1
< 0.1%
-10234260.0 1
< 0.1%
-8706101.0 1
< 0.1%
-3919027.0 1
< 0.1%
-2242789.0 1
< 0.1%
-1780591.0 1
< 0.1%
-1732602.0 1
< 0.1%
ValueCountFrequency (%)
807022109.0 1
< 0.1%
799706755.0 1
< 0.1%
638911762.0 1
< 0.1%
638781072.0 1
< 0.1%
565949733.0 1
< 0.1%
495230712.0 1
< 0.1%
289509449.0 1
< 0.1%
280113904.0 1
< 0.1%
268415273.0 1
< 0.1%
264218305.0 1
< 0.1%

2019년 반기
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct385
Distinct (%)77.6%
Missing4545
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean6713959.6
Minimum-10312527
Maximum1.9269076 × 108
Zeros104
Zeros (%)2.1%
Negative9
Negative (%)0.2%
Memory size44.4 KiB
2023-12-13T09:47:22.534587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10312527
5-th percentile0
Q145.4875
median303039
Q33749526.2
95-th percentile32674836
Maximum1.9269076 × 108
Range2.0300329 × 108
Interquartile range (IQR)3749480.8

Descriptive statistics

Standard deviation20711085
Coefficient of variation (CV)3.0847794
Kurtosis36.188363
Mean6713959.6
Median Absolute Deviation (MAD)303039
Skewness5.4929458
Sum3.330124 × 109
Variance4.2894902 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:22.672800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 104
 
2.1%
217463.0 2
 
< 0.1%
36048056.0 2
 
< 0.1%
550783.0 2
 
< 0.1%
1572321.0 2
 
< 0.1%
4268777.0 2
 
< 0.1%
9000.0 2
 
< 0.1%
990891.0 2
 
< 0.1%
945647.0 2
 
< 0.1%
8154645.0 1
 
< 0.1%
Other values (375) 375
 
7.4%
(Missing) 4545
90.2%
ValueCountFrequency (%)
-10312527.0 1
 
< 0.1%
-4218734.0 1
 
< 0.1%
-1477640.0 1
 
< 0.1%
-1054534.0 1
 
< 0.1%
-1042553.0 1
 
< 0.1%
-686217.0 1
 
< 0.1%
-11981.0 1
 
< 0.1%
-1975.0 1
 
< 0.1%
-952.0 1
 
< 0.1%
0.0 104
2.1%
ValueCountFrequency (%)
192690763.0 1
< 0.1%
175567645.0 1
< 0.1%
172574244.0 1
< 0.1%
128554302.0 1
< 0.1%
122899527.0 1
< 0.1%
98894623.0 1
< 0.1%
95836591.0 1
< 0.1%
94414246.0 1
< 0.1%
79731054.0 1
< 0.1%
78558860.0 1
< 0.1%

2019년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3714
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2499625.9
Minimum-7.9717242 × 108
Maximum8.0858722 × 108
Zeros925
Zeros (%)18.3%
Negative115
Negative (%)2.3%
Memory size44.4 KiB
2023-12-13T09:47:22.777639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.9717242 × 108
5-th percentile0
Q126
median4886
Q382839
95-th percentile4048246
Maximum8.0858722 × 108
Range1.6057596 × 109
Interquartile range (IQR)82813

Descriptive statistics

Standard deviation33154512
Coefficient of variation (CV)13.26379
Kurtosis407.27934
Mean2499625.9
Median Absolute Deviation (MAD)4886
Skewness7.9098439
Sum1.2600614 × 1010
Variance1.0992217 × 1015
MonotonicityNot monotonic
2023-12-13T09:47:22.887368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 925
 
18.3%
1.0 78
 
1.5%
2.0 12
 
0.2%
10.0 8
 
0.2%
30.0 5
 
0.1%
154.0 4
 
0.1%
620.0 4
 
0.1%
207.0 4
 
0.1%
802.0 4
 
0.1%
60.0 4
 
0.1%
Other values (3704) 3993
79.2%
ValueCountFrequency (%)
-797172417.0 1
< 0.1%
-789710247.0 1
< 0.1%
-52736219.0 1
< 0.1%
-11363683.0 1
< 0.1%
-10533206.0 1
< 0.1%
-8710866.0 1
< 0.1%
-4234812.0 1
< 0.1%
-2232955.0 1
< 0.1%
-1836721.0 1
< 0.1%
-1533807.0 1
< 0.1%
ValueCountFrequency (%)
808587221.0 1
< 0.1%
801819591.0 1
< 0.1%
736775355.0 1
< 0.1%
736653844.0 1
< 0.1%
606977283.0 1
< 0.1%
542790746.0 1
< 0.1%
318111038.0 1
< 0.1%
307726046.0 1
< 0.1%
295334391.0 1
< 0.1%
290302479.0 1
< 0.1%

2020년 반기
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct384
Distinct (%)77.4%
Missing4545
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean6982670.8
Minimum-11807044
Maximum2.0122521 × 108
Zeros103
Zeros (%)2.0%
Negative12
Negative (%)0.2%
Memory size44.4 KiB
2023-12-13T09:47:22.997365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-11807044
5-th percentile0
Q140.995
median302081
Q33813867.5
95-th percentile35405838
Maximum2.0122521 × 108
Range2.1303226 × 108
Interquartile range (IQR)3813826.5

Descriptive statistics

Standard deviation21717432
Coefficient of variation (CV)3.1101898
Kurtosis36.241816
Mean6982670.8
Median Absolute Deviation (MAD)302081
Skewness5.5052419
Sum3.4634047 × 109
Variance4.7164684 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:23.097375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 103
 
2.0%
1562467.0 2
 
< 0.1%
37390054.0 2
 
< 0.1%
543610.0 2
 
< 0.1%
4203921.0 2
 
< 0.1%
837939.0 2
 
< 0.1%
219058.0 2
 
< 0.1%
9000.0 2
 
< 0.1%
1052854.0 2
 
< 0.1%
477857.0 2
 
< 0.1%
Other values (374) 375
 
7.4%
(Missing) 4545
90.2%
ValueCountFrequency (%)
-11807044.0 1
< 0.1%
-4991810.0 1
< 0.1%
-1267971.0 1
< 0.1%
-1162714.0 1
< 0.1%
-1143569.0 1
< 0.1%
-1131082.0 1
< 0.1%
-556643.0 1
< 0.1%
-500169.0 1
< 0.1%
-12487.0 1
< 0.1%
-3342.0 1
< 0.1%
ValueCountFrequency (%)
201225213.0 1
< 0.1%
184324984.0 1
< 0.1%
181013357.0 1
< 0.1%
132265182.0 1
< 0.1%
131853863.0 1
< 0.1%
108937970.0 1
< 0.1%
103756615.0 1
< 0.1%
98147669.0 1
< 0.1%
83635234.0 1
< 0.1%
80568369.0 1
< 0.1%

2020년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3725
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2737347.3
Minimum-8.6832281 × 108
Maximum8.7988505 × 108
Zeros917
Zeros (%)18.2%
Negative123
Negative (%)2.4%
Memory size44.4 KiB
2023-12-13T09:47:23.195824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.6832281 × 108
5-th percentile0
Q126.5
median5521
Q385816
95-th percentile4183183
Maximum8.7988505 × 108
Range1.7482079 × 109
Interquartile range (IQR)85789.5

Descriptive statistics

Standard deviation36620937
Coefficient of variation (CV)13.378257
Kurtosis402.25967
Mean2737347.3
Median Absolute Deviation (MAD)5521
Skewness8.2692438
Sum1.3798968 × 1010
Variance1.341093 × 1015
MonotonicityNot monotonic
2023-12-13T09:47:23.299287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 917
 
18.2%
1.0 79
 
1.6%
2.0 11
 
0.2%
10.0 6
 
0.1%
3.0 6
 
0.1%
11.0 5
 
0.1%
1055.0 4
 
0.1%
52700.0 4
 
0.1%
103.0 4
 
0.1%
719.0 4
 
0.1%
Other values (3715) 4001
79.4%
ValueCountFrequency (%)
-868322812.0 1
< 0.1%
-860077943.0 1
< 0.1%
-50559630.0 1
< 0.1%
-12268174.0 1
< 0.1%
-8523513.0 1
< 0.1%
-8240997.0 1
< 0.1%
-3381041.0 1
< 0.1%
-2702366.0 1
< 0.1%
-2046121.0 1
< 0.1%
-1713801.0 1
< 0.1%
ValueCountFrequency (%)
879885054.0 1
< 0.1%
873456368.0 1
< 0.1%
833933087.0 1
< 0.1%
833727630.0 1
< 0.1%
649553898.0 1
< 0.1%
616549995.0 1
< 0.1%
361616177.0 1
< 0.1%
349305109.0 1
< 0.1%
336473828.0 1
< 0.1%
330717355.0 1
< 0.1%

2021년 반기
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct384
Distinct (%)77.4%
Missing4545
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean7246080.6
Minimum-12465367
Maximum2.0698294 × 108
Zeros102
Zeros (%)2.0%
Negative12
Negative (%)0.2%
Memory size44.4 KiB
2023-12-13T09:47:23.436701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12465367
5-th percentile0
Q139.86
median306396.5
Q33922417.5
95-th percentile37095792
Maximum2.0698294 × 108
Range2.1944831 × 108
Interquartile range (IQR)3922377.6

Descriptive statistics

Standard deviation22606151
Coefficient of variation (CV)3.1197764
Kurtosis36.040024
Mean7246080.6
Median Absolute Deviation (MAD)306396.5
Skewness5.4909748
Sum3.594056 × 109
Variance5.1103807 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:23.542623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 102
 
2.0%
1854983.0 2
 
< 0.1%
430905.0 2
 
< 0.1%
3927060.0 2
 
< 0.1%
917000.0 2
 
< 0.1%
222036.0 2
 
< 0.1%
9000.0 2
 
< 0.1%
1079508.0 2
 
< 0.1%
316541.0 2
 
< 0.1%
1855766.0 2
 
< 0.1%
Other values (374) 376
 
7.5%
(Missing) 4545
90.2%
ValueCountFrequency (%)
-12465367.0 1
< 0.1%
-3962828.0 1
< 0.1%
-1856679.0 1
< 0.1%
-1282820.0 1
< 0.1%
-1241110.0 1
< 0.1%
-1233051.0 1
< 0.1%
-1222719.0 1
< 0.1%
-22944.0 1
< 0.1%
-12538.0 1
< 0.1%
-10332.0 1
< 0.1%
ValueCountFrequency (%)
206982941.0 1
< 0.1%
196975558.0 1
< 0.1%
185535918.0 1
< 0.1%
137290234.0 1
< 0.1%
136620597.0 1
< 0.1%
110299301.0 1
< 0.1%
106301318.0 1
< 0.1%
102758330.0 1
< 0.1%
87262984.0 1
< 0.1%
86676257.0 1
< 0.1%

2021년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3747
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3003630.3
Minimum-9.4530064 × 108
Maximum9.5715686 × 108
Zeros894
Zeros (%)17.7%
Negative123
Negative (%)2.4%
Memory size44.4 KiB
2023-12-13T09:47:23.646210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.4530064 × 108
5-th percentile0
Q135.04
median5895
Q395633
95-th percentile4842639
Maximum9.5715686 × 108
Range1.9024575 × 109
Interquartile range (IQR)95597.96

Descriptive statistics

Standard deviation40411818
Coefficient of variation (CV)13.454325
Kurtosis404.76802
Mean3003630.3
Median Absolute Deviation (MAD)5895
Skewness8.7929588
Sum1.51413 × 1010
Variance1.633115 × 1015
MonotonicityNot monotonic
2023-12-13T09:47:23.757309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 894
 
17.7%
1.0 81
 
1.6%
2.0 12
 
0.2%
10.0 6
 
0.1%
17219.0 4
 
0.1%
459.0 4
 
0.1%
20.0 4
 
0.1%
66.0 4
 
0.1%
26647.0 4
 
0.1%
2636.0 4
 
0.1%
Other values (3737) 4024
79.8%
ValueCountFrequency (%)
-945300640.0 1
< 0.1%
-935847059.0 1
< 0.1%
-49143412.0 1
< 0.1%
-12785074.0 1
< 0.1%
-7783276.0 1
< 0.1%
-7439862.0 1
< 0.1%
-4411891.0 1
< 0.1%
-3675429.0 1
< 0.1%
-3318711.0 1
< 0.1%
-2472467.0 2
< 0.1%
ValueCountFrequency (%)
957156864.0 1
< 0.1%
951097169.0 1
< 0.1%
949040392.0 1
< 0.1%
948719359.0 1
< 0.1%
711781677.0 1
< 0.1%
711442493.0 1
< 0.1%
398071914.0 1
< 0.1%
383600294.0 1
< 0.1%
370538065.0 1
< 0.1%
364163212.0 1
< 0.1%

2022년 반기
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct398
Distinct (%)80.2%
Missing4545
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean7850726.6
Minimum-12958127
Maximum2.2122251 × 108
Zeros89
Zeros (%)1.8%
Negative15
Negative (%)0.3%
Memory size44.4 KiB
2023-12-13T09:47:23.871857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12958127
5-th percentile0
Q1123.54
median343698.5
Q34747941.2
95-th percentile40357584
Maximum2.2122251 × 108
Range2.3418063 × 108
Interquartile range (IQR)4747817.7

Descriptive statistics

Standard deviation24390236
Coefficient of variation (CV)3.1067489
Kurtosis36.073152
Mean7850726.6
Median Absolute Deviation (MAD)343698.5
Skewness5.5308402
Sum3.8939604 × 109
Variance5.948836 × 1014
MonotonicityNot monotonic
2023-12-13T09:47:23.977403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 89
 
1.8%
1130957.0 2
 
< 0.1%
301569.0 2
 
< 0.1%
9000.0 2
 
< 0.1%
229188.0 2
 
< 0.1%
41430335.0 2
 
< 0.1%
3693386.0 2
 
< 0.1%
519692.0 2
 
< 0.1%
1000237.0 2
 
< 0.1%
364782.0 2
 
< 0.1%
Other values (388) 389
 
7.7%
(Missing) 4545
90.2%
ValueCountFrequency (%)
-12958127.0 1
< 0.1%
-4671368.0 1
< 0.1%
-3646314.0 1
< 0.1%
-2282079.0 1
< 0.1%
-2231580.0 1
< 0.1%
-1627444.0 1
< 0.1%
-1610799.0 1
< 0.1%
-1412462.0 1
< 0.1%
-1348417.0 1
< 0.1%
-1325218.0 1
< 0.1%
ValueCountFrequency (%)
221222507.0 1
< 0.1%
210437162.0 1
< 0.1%
195368413.0 1
< 0.1%
165798785.0 1
< 0.1%
144511200.0 1
< 0.1%
128680752.0 1
< 0.1%
118580866.0 1
< 0.1%
114792822.0 1
< 0.1%
108193619.0 1
< 0.1%
91856296.0 1
< 0.1%

2022년 결산
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3734
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3131081.9
Minimum-9.8037353 × 108
Maximum9.9232606 × 108
Zeros919
Zeros (%)18.2%
Negative116
Negative (%)2.3%
Memory size44.4 KiB
2023-12-13T09:47:24.107685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.8037353 × 108
5-th percentile0
Q128.48
median5791
Q395704
95-th percentile5454465
Maximum9.9232606 × 108
Range1.9726996 × 109
Interquartile range (IQR)95675.52

Descriptive statistics

Standard deviation41248967
Coefficient of variation (CV)13.17403
Kurtosis388.31633
Mean3131081.9
Median Absolute Deviation (MAD)5791
Skewness7.8449978
Sum1.5783784 × 1010
Variance1.7014773 × 1015
MonotonicityNot monotonic
2023-12-13T09:47:24.251043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 919
 
18.2%
1.0 81
 
1.6%
2.0 11
 
0.2%
12.0 5
 
0.1%
10.0 5
 
0.1%
526.0 4
 
0.1%
101.0 4
 
0.1%
2525.0 4
 
0.1%
25044.0 4
 
0.1%
653.0 4
 
0.1%
Other values (3724) 4000
79.3%
ValueCountFrequency (%)
-980373528.0 1
< 0.1%
-971491748.0 1
< 0.1%
-48767641.0 1
< 0.1%
-12414830.0 1
< 0.1%
-6920950.0 1
< 0.1%
-6035342.0 1
< 0.1%
-5204583.0 2
< 0.1%
-4109074.0 1
< 0.1%
-3683278.0 1
< 0.1%
-2254456.0 1
< 0.1%
ValueCountFrequency (%)
992326058.0 1
< 0.1%
986688623.0 1
< 0.1%
890776853.0 1
< 0.1%
890465712.0 1
< 0.1%
759798003.0 1
< 0.1%
672868329.0 1
< 0.1%
431979690.0 1
< 0.1%
417162349.0 1
< 0.1%
402869127.0 1
< 0.1%
395456456.0 1
< 0.1%

상위기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size39.5 KiB
<NA>
4873 
국민건강보험공단
 
23
한국해양과학기술원
 
22
한국연구재단
 
12
정보통신산업진흥원
 
12
Other values (9)
 
99

Length

Max length11
Median length4
Mean length4.1352906
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> 4873
96.7%
국민건강보험공단 23
 
0.5%
한국해양과학기술원 22
 
0.4%
한국연구재단 12
 
0.2%
정보통신산업진흥원 12
 
0.2%
한국화학연구원 11
 
0.2%
한국원자력의학원 11
 
0.2%
한국식품연구원 11
 
0.2%
한국과학기술연구원 11
 
0.2%
한국과학기술기획평가원 11
 
0.2%
Other values (4) 44
 
0.9%

Length

2023-12-13T09:47:24.363639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4873
96.7%
국민건강보험공단 23
 
0.5%
한국해양과학기술원 22
 
0.4%
한국연구재단 12
 
0.2%
정보통신산업진흥원 12
 
0.2%
한국화학연구원 11
 
0.2%
한국원자력의학원 11
 
0.2%
한국식품연구원 11
 
0.2%
한국과학기술연구원 11
 
0.2%
한국과학기술기획평가원 11
 
0.2%
Other values (4) 44
 
0.9%

Interactions

2023-12-13T09:47:19.507647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:12.527491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.442312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.227085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.939023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.696044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.370060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.144142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.032285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.834216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.578503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:12.815118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.517962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.305274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.012166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.782725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.446375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.453838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.121033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.902979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.660726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:12.888397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.595707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.387526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.089335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.866701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.523021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.521992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.218122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.972909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.735490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:12.964201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.674443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.463966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.165179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.936344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.615368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.602328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.298194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.043814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.820132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.028429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.757710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.531908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.244286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.001357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.695472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.662450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.383296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.112097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.884137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.097860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.829086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.600450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.323576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.063192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.756481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.724132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.444212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.188336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.961434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.166853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.906125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.667423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.398600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.122873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.827348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.786343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.529210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.259469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:20.022171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.233845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.982055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.737517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.461867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.185353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.888978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.849715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.593147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.323503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:20.109246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.306919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.062453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.803490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.547400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.246734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.966763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.910728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.686876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.385501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:20.170621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:13.376816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.132345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:14.871974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:15.611814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:16.309336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.041771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:17.971696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:18.749444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:47:19.447353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:47:24.445802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
기관유형1.0000.8200.5860.5970.9970.0000.2460.0720.2540.1050.2650.1150.2660.1420.2881.000
주무부처0.8201.0000.6980.2631.0000.0000.3970.0000.3550.0000.3650.2640.3700.0000.3751.000
구분0.5860.6981.0000.899NaN0.1620.4990.1850.5000.1940.3250.2080.3330.1850.3400.893
항목0.5970.2630.8991.0000.0000.0000.4500.0000.4450.0000.4320.0000.4440.0000.4710.000
기금명0.9971.000NaN0.0001.000NaN0.566NaN0.488NaN0.521NaN0.521NaN0.493NaN
2018년 반기0.0000.0000.1620.000NaN1.0000.9340.9780.9240.9700.9240.9590.9210.9910.909NaN
2018년 결산0.2460.3970.4990.4500.5660.9341.0000.8600.9950.8670.9410.8790.9410.9450.940NaN
2019년 반기0.0720.0000.1850.000NaN0.9780.8601.0000.9100.9990.9100.9970.8430.9360.893NaN
2019년 결산0.2540.3550.5000.4450.4880.9240.9950.9101.0000.9160.9870.9250.9810.9350.985NaN
2020년 반기0.1050.0000.1940.000NaN0.9700.8670.9990.9161.0000.9161.0000.8500.9490.898NaN
2020년 결산0.2650.3650.3250.4320.5210.9240.9410.9100.9870.9161.0000.9251.0000.9350.998NaN
2021년 반기0.1150.2640.2080.000NaN0.9590.8790.9970.9251.0000.9251.0000.8600.9560.907NaN
2021년 결산0.2660.3700.3330.4440.5210.9210.9410.8430.9810.8501.0000.8601.0000.9310.998NaN
2022년 반기0.1420.0000.1850.000NaN0.9910.9450.9360.9350.9490.9350.9560.9311.0000.919NaN
2022년 결산0.2880.3750.3400.4710.4930.9090.9400.8930.9850.8980.9980.9070.9980.9191.000NaN
상위기관1.0001.0000.8930.000NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1.000
2023-12-13T09:47:24.578725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목기관유형기금명주무부처구분상위기관
항목1.0000.3220.0000.0550.6540.000
기관유형0.3221.0000.9660.5110.4460.966
기금명0.0000.9661.0000.9831.000NaN
주무부처0.0550.5110.9831.0000.3900.975
구분0.6540.4461.0000.3901.0000.854
상위기관0.0000.966NaN0.9750.8541.000
2023-12-13T09:47:24.667341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산기관유형주무부처구분항목기금명상위기관
2018년 반기1.0000.8610.8610.7990.7620.7310.7340.7000.6990.6980.0000.0000.0960.0000.0000.000
2018년 결산0.8611.0000.9980.8890.9020.8290.8730.7900.8330.7700.1710.2000.2000.2110.2941.000
2019년 반기0.8610.9981.0000.9390.9020.8720.8730.8350.8320.8340.0420.0000.1170.0000.0000.000
2019년 결산0.7990.8890.9391.0000.9630.9350.9320.8960.8900.8740.1760.1800.2010.2070.2501.000
2020년 반기0.7620.9020.9020.9631.0000.9700.9700.9290.9280.9300.0640.0000.1230.0000.0000.000
2020년 결산0.7310.8290.8720.9350.9701.0000.9990.9570.9560.9310.1750.1620.2000.1890.2681.000
2021년 반기0.7340.8730.8730.9320.9700.9991.0000.9590.9570.9550.0700.0910.1330.0000.0000.000
2021년 결산0.7000.7900.8350.8960.9290.9570.9591.0000.9970.9750.1760.1640.2060.1950.2681.000
2022년 반기0.6990.8330.8320.8900.9280.9560.9570.9971.0000.9960.0830.0000.1100.0000.0000.000
2022년 결산0.6980.7700.8340.8740.9300.9310.9550.9750.9961.0000.1900.1660.2100.2100.2521.000
기관유형0.0000.1710.0420.1760.0640.1750.0700.1760.0830.1901.0000.5110.4460.3220.9660.966
주무부처0.0000.2000.0000.1800.0000.1620.0910.1640.0000.1660.5111.0000.3900.0550.9830.975
구분0.0960.2000.1170.2010.1230.2000.1330.2060.1100.2100.4460.3901.0000.6541.0000.854
항목0.0000.2110.0000.2070.0000.1890.0000.1950.0000.2100.3220.0550.6541.0000.0000.000
기금명0.0000.2940.0000.2500.0000.2680.0000.2680.0000.2520.9660.9831.0000.0001.0000.000
상위기관0.0001.0000.0001.0000.0001.0000.0001.0000.0001.0000.9660.9750.8540.0000.0001.000

Missing values

2023-12-13T09:47:20.301976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:47:20.486631image/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.
2023-12-13T09:47:20.600941image/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

기관명기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
0(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))01.유동자산<NA><NA>870.0<NA>244.0<NA>245.0<NA>258.0<NA>568.0<NA>
1(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))02.비유동자산<NA><NA>376.0<NA>332.0<NA>489.0<NA>655.0<NA>625.0<NA>
2(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))03.자산총계<NA><NA>1246.0<NA>576.0<NA>734.0<NA>913.0<NA>1193.0<NA>
3(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))04.유동부채<NA><NA>870.0<NA>244.0<NA>245.0<NA>258.0<NA>568.0<NA>
4(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))05.비유동부채<NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>
5(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))06.부채총계<NA><NA>870.0<NA>244.0<NA>245.0<NA>258.0<NA>568.0<NA>
6(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))07.자본금<NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>
7(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))08.기타<NA><NA>376.0<NA>332.0<NA>489.0<NA>655.0<NA>625.0<NA>
8(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))09.자본총계<NA><NA>376.0<NA>332.0<NA>489.0<NA>655.0<NA>625.0<NA>
9(사)남북교류협력지원협회기타공공기관통일부고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))10.금융부채<NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>
기관명기관유형주무부처구분항목기금명2018년 반기2018년 결산2019년 반기2019년 결산2020년 반기2020년 결산2021년 반기2021년 결산2022년 반기2022년 결산상위기관
5031육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))02.비유동자산<NA><NA>1172.0<NA>1085.0<NA>2968.0<NA>3110.0<NA>3289.0경제인문사회연구회
5032육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))03.자산총계<NA><NA>3669.0<NA>5553.0<NA>4677.0<NA>4934.0<NA>5539.0경제인문사회연구회
5033육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))04.유동부채<NA><NA>384.0<NA>1913.0<NA>1650.0<NA>1710.0<NA>2146.0경제인문사회연구회
5034육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))05.비유동부채<NA><NA>1783.0<NA>2104.0<NA>2346.0<NA>2585.0<NA>2872.0경제인문사회연구회
5035육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))06.부채총계<NA><NA>2167.0<NA>4017.0<NA>3996.0<NA>4295.0<NA>5018.0경제인문사회연구회
5036육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))07.자본금<NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>0.0경제인문사회연구회
5037육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))08.기타<NA><NA>1502.0<NA>1536.0<NA>681.0<NA>639.0<NA>522.0경제인문사회연구회
5038육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))09.자본총계<NA><NA>1502.0<NA>1536.0<NA>681.0<NA>639.0<NA>522.0경제인문사회연구회
5039육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))10.금융부채<NA><NA>0.0<NA>0.0<NA>0.0<NA>0.0<NA>0.0경제인문사회연구회
5040육아정책연구소기타공공기관국무조정실고유사업(요약 재무상태표(K-GAAP, 자회사가 없는 경우))11.부채비율<NA><NA>144.27<NA>261.52<NA>586.78<NA>672.14<NA>961.3경제인문사회연구회