Overview

Dataset statistics

Number of variables9
Number of observations114
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory81.2 B

Variable types

Numeric8
Categorical1

Dataset

Description경기도 교육재정 중기지방 교육재정계획(결산) 현황
Author교육부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=TD87JMZB981LIE6E4ERM23845075&infSeq=2

Alerts

회계년도금액(원) is highly overall correlated with 회계년도+1년금액(원) and 5 other fieldsHigh correlation
회계년도+1년금액(원) is highly overall correlated with 회계년도금액(원) and 5 other fieldsHigh correlation
회계년도+2년금액(원) is highly overall correlated with 회계년도금액(원) and 5 other fieldsHigh correlation
회계년도+3년금액(원) is highly overall correlated with 회계년도금액(원) and 5 other fieldsHigh correlation
회계년도+4년금액(원) is highly overall correlated with 회계년도금액(원) and 5 other fieldsHigh correlation
합계금액(원) is highly overall correlated with 회계년도금액(원) and 5 other fieldsHigh correlation
연평균증감률(%) is highly overall correlated with 회계년도금액(원) and 6 other fieldsHigh correlation
구분명 is highly overall correlated with 연평균증감률(%)High correlation
연평균증감률(%) has 6 (5.3%) missing valuesMissing
회계년도금액(원) has 6 (5.3%) zerosZeros
회계년도+1년금액(원) has 9 (7.9%) zerosZeros
회계년도+2년금액(원) has 9 (7.9%) zerosZeros
회계년도+3년금액(원) has 9 (7.9%) zerosZeros
회계년도+4년금액(원) has 9 (7.9%) zerosZeros
합계금액(원) has 6 (5.3%) zerosZeros

Reproduction

Analysis started2023-12-10 22:49:17.883694
Analysis finished2023-12-10 22:49:25.226846
Duration7.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Real number (ℝ)

Distinct9
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.6316
Minimum2015
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:25.284290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2019
Q32021
95-th percentile2023
Maximum2023
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4432068
Coefficient of variation (CV)0.0012103282
Kurtosis-1.0801113
Mean2018.6316
Median Absolute Deviation (MAD)2
Skewness0.12675596
Sum230124
Variance5.9692594
MonotonicityDecreasing
2023-12-11T07:49:25.417785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2021 14
12.3%
2020 14
12.3%
2019 14
12.3%
2018 14
12.3%
2017 14
12.3%
2016 14
12.3%
2015 14
12.3%
2023 8
7.0%
2022 8
7.0%
ValueCountFrequency (%)
2015 14
12.3%
2016 14
12.3%
2017 14
12.3%
2018 14
12.3%
2019 14
12.3%
2020 14
12.3%
2021 14
12.3%
2022 8
7.0%
2023 8
7.0%
ValueCountFrequency (%)
2023 8
7.0%
2022 8
7.0%
2021 14
12.3%
2020 14
12.3%
2019 14
12.3%
2018 14
12.3%
2017 14
12.3%
2016 14
12.3%
2015 14
12.3%

구분명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
교육일반
9 
자체수입
9 
인적자원운용
 
7
학교교육여건 개선시설
 
7
교육복지지원
 
7
Other values (18)
75 

Length

Max length12
Median length10
Mean length6.4385965
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row① 세입
2nd row② 세출
3rd row교육일반
4th row기타 및 내부거래
5th row이전수입

Common Values

ValueCountFrequency (%)
교육일반 9
 
7.9%
자체수입 9
 
7.9%
인적자원운용 7
 
6.1%
학교교육여건 개선시설 7
 
6.1%
교육복지지원 7
 
6.1%
학교재정 지원관리 7
 
6.1%
보전수입등 및 내부거래 5
 
4.4%
평생-직업교육 5
 
4.4%
교수-학습 활동지원 5
 
4.4%
보건/급식/체육활동 5
 
4.4%
Other values (13) 48
42.1%

Length

2023-12-11T07:49:25.573833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교육일반 9
 
5.6%
자체수입 9
 
5.6%
및 9
 
5.6%
내부거래 9
 
5.6%
인적자원운용 7
 
4.3%
학교교육여건 7
 
4.3%
개선시설 7
 
4.3%
교육복지지원 7
 
4.3%
학교재정 7
 
4.3%
지원관리 7
 
4.3%
Other values (20) 83
51.6%

회계년도금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9293687 × 1012
Minimum0
Maximum2.8855196 × 1013
Zeros6
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:25.719110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.07295 × 109
Q13.522255 × 1011
median9.453065 × 1011
Q38.8415175 × 1012
95-th percentile1.7803906 × 1013
Maximum2.8855196 × 1013
Range2.8855196 × 1013
Interquartile range (IQR)8.489292 × 1012

Descriptive statistics

Standard deviation7.0609257 × 1012
Coefficient of variation (CV)1.4324199
Kurtosis1.2636962
Mean4.9293687 × 1012
Median Absolute Deviation (MAD)8.72996 × 1011
Skewness1.4731413
Sum5.6194803 × 1014
Variance4.9856671 × 1025
MonotonicityNot monotonic
2023-12-11T07:49:25.882236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
5.3%
28855196000000 2
 
1.8%
12467639000000 2
 
1.8%
16606195000000 2
 
1.8%
12872657822000 2
 
1.8%
16939818000000 2
 
1.8%
16377656000000 2
 
1.8%
12309640000000 2
 
1.8%
14947981000000 2
 
1.8%
20482299000000 2
 
1.8%
Other values (90) 90
78.9%
ValueCountFrequency (%)
0 6
5.3%
9343000000 1
 
0.9%
10577000000 1
 
0.9%
10647827000 1
 
0.9%
13700000000 1
 
0.9%
14113180000 1
 
0.9%
15669000000 1
 
0.9%
17760000000 1
 
0.9%
26476000000 1
 
0.9%
27204000000 1
 
0.9%
ValueCountFrequency (%)
28855196000000 2
1.8%
22657782000000 1
0.9%
20482299000000 2
1.8%
19408640000000 1
0.9%
16939818000000 2
1.8%
16606195000000 2
1.8%
16377656000000 2
1.8%
16235777000000 1
0.9%
16019016000000 1
0.9%
15974238000000 1
0.9%

회계년도+1년금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct97
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1461497 × 1012
Minimum0
Maximum2.9415296 × 1013
Zeros9
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:26.041629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.0169375 × 1011
median9.574725 × 1011
Q39.1481062 × 1012
95-th percentile1.840184 × 1013
Maximum2.9415296 × 1013
Range2.9415296 × 1013
Interquartile range (IQR)8.8464125 × 1012

Descriptive statistics

Standard deviation7.3946373 × 1012
Coefficient of variation (CV)1.4369262
Kurtosis0.97065834
Mean5.1461497 × 1012
Median Absolute Deviation (MAD)9.4132184 × 1011
Skewness1.4167654
Sum5.8666106 × 1014
Variance5.468066 × 1025
MonotonicityNot monotonic
2023-12-11T07:49:26.200679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
7.9%
29415296000000 2
 
1.8%
13421130000000 2
 
1.8%
15795728000000 2
 
1.8%
17131074000000 2
 
1.8%
14451534040000 2
 
1.8%
12974705000000 2
 
1.8%
17044527000000 2
 
1.8%
17246107000000 2
 
1.8%
21358307000000 2
 
1.8%
Other values (87) 87
76.3%
ValueCountFrequency (%)
0 9
7.9%
9343000000 1
 
0.9%
10240000000 1
 
0.9%
10838731000 1
 
0.9%
14105000000 1
 
0.9%
15305326000 1
 
0.9%
16996000000 1
 
0.9%
17707000000 1
 
0.9%
27523000000 1
 
0.9%
37089000000 1
 
0.9%
ValueCountFrequency (%)
29415296000000 2
1.8%
23565438000000 1
0.9%
21358307000000 2
1.8%
20548200000000 1
0.9%
17246107000000 2
1.8%
17131074000000 2
1.8%
17044527000000 2
1.8%
16955759000000 1
0.9%
16642026000000 1
0.9%
16556945000000 1
0.9%

회계년도+2년금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3298296 × 1012
Minimum0
Maximum3.0166047 × 1013
Zeros9
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:26.347754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6399025 × 1011
median9.340685 × 1011
Q39.736436 × 1012
95-th percentile1.9185545 × 1013
Maximum3.0166047 × 1013
Range3.0166047 × 1013
Interquartile range (IQR)9.4724458 × 1012

Descriptive statistics

Standard deviation7.6717183 × 1012
Coefficient of variation (CV)1.4393928
Kurtosis0.87599111
Mean5.3298296 × 1012
Median Absolute Deviation (MAD)9.2165197 × 1011
Skewness1.3981121
Sum6.0760057 × 1014
Variance5.8855262 × 1025
MonotonicityNot monotonic
2023-12-11T07:49:26.471332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
7.9%
30166047000000 2
 
1.8%
21973219000000 2
 
1.8%
17826699000000 2
 
1.8%
14187444000000 2
 
1.8%
18027989000000 2
 
1.8%
13757482000000 2
 
1.8%
17827648000000 2
 
1.8%
15886507000000 2
 
1.8%
15921629000 1
 
0.9%
Other values (88) 88
77.2%
ValueCountFrequency (%)
0 9
7.9%
9352000000 1
 
0.9%
10444000000 1
 
0.9%
10962055000 1
 
0.9%
13871000000 1
 
0.9%
15921629000 1
 
0.9%
17686000000 1
 
0.9%
18023000000 1
 
0.9%
27978000000 1
 
0.9%
36594000000 1
 
0.9%
ValueCountFrequency (%)
30166047000000 2
1.8%
24767822000000 1
0.9%
21973219000000 2
1.8%
21335292000000 1
0.9%
18027989000000 2
1.8%
17827648000000 2
1.8%
17826699000000 2
1.8%
17626477000000 1
0.9%
17537587000000 1
0.9%
17264586000000 1
0.9%

회계년도+3년금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5063054 × 1012
Minimum0
Maximum3.0630701 × 1013
Zeros9
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:26.615313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.4068725 × 1011
median8.5939413 × 1011
Q31.046263 × 1013
95-th percentile2.0018949 × 1013
Maximum3.0630701 × 1013
Range3.0630701 × 1013
Interquartile range (IQR)1.0221943 × 1013

Descriptive statistics

Standard deviation7.9476053 × 1012
Coefficient of variation (CV)1.4433644
Kurtosis0.7429265
Mean5.5063054 × 1012
Median Absolute Deviation (MAD)8.4845647 × 1011
Skewness1.3761352
Sum6.2771881 × 1014
Variance6.316443 × 1025
MonotonicityNot monotonic
2023-12-11T07:49:26.785789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
7.9%
30630701000000 2
 
1.8%
22825490000000 2
 
1.8%
18849282000000 2
 
1.8%
13896900000000 2
 
1.8%
18735438000000 2
 
1.8%
15157297000000 2
 
1.8%
18597566000000 2
 
1.8%
16567889000000 2
 
1.8%
16443625000 1
 
0.9%
Other values (88) 88
77.2%
ValueCountFrequency (%)
0 9
7.9%
9352000000 1
 
0.9%
10747000000 1
 
0.9%
11128335000 1
 
0.9%
13924000000 1
 
0.9%
16443625000 1
 
0.9%
18271000000 1
 
0.9%
18464000000 1
 
0.9%
28403000000 1
 
0.9%
28438000000 1
 
0.9%
ValueCountFrequency (%)
30630701000000 2
1.8%
25680771000000 1
0.9%
22825490000000 2
1.8%
22191187000000 1
0.9%
18849282000000 2
1.8%
18735438000000 2
1.8%
18597566000000 2
1.8%
18561368000000 1
0.9%
18463256000000 1
0.9%
18041424000000 1
0.9%

회계년도+4년금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7355204 × 1012
Minimum0
Maximum3.1525417 × 1013
Zeros9
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:26.947867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.2744275 × 1011
median8.9452075 × 1011
Q31.1062962 × 1013
95-th percentile2.1081219 × 1013
Maximum3.1525417 × 1013
Range3.1525417 × 1013
Interquartile range (IQR)1.0835519 × 1013

Descriptive statistics

Standard deviation8.3006072 × 1012
Coefficient of variation (CV)1.4472283
Kurtosis0.69266766
Mean5.7355204 × 1012
Median Absolute Deviation (MAD)8.818905 × 1011
Skewness1.3703241
Sum6.5384932 × 1014
Variance6.890008 × 1025
MonotonicityNot monotonic
2023-12-11T07:49:27.090353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
7.9%
31525417000000 2
 
1.8%
24493802000000 2
 
1.8%
19567527000000 2
 
1.8%
14720800000000 2
 
1.8%
19383780000000 2
 
1.8%
15233729000000 2
 
1.8%
19549387000000 2
 
1.8%
17607026000000 2
 
1.8%
17091751000 1
 
0.9%
Other values (88) 88
77.2%
ValueCountFrequency (%)
0 9
7.9%
9632000000 1
 
0.9%
11063000000 1
 
0.9%
11310502000 1
 
0.9%
13950000000 1
 
0.9%
17091751000 1
 
0.9%
18896000000 1
 
0.9%
18996000000 1
 
0.9%
28539000000 1
 
0.9%
28909000000 1
 
0.9%
ValueCountFrequency (%)
31525417000000 2
1.8%
26603332000000 1
0.9%
24493802000000 2
1.8%
23892362000000 1
0.9%
19567527000000 2
1.8%
19549387000000 2
1.8%
19383780000000 2
1.8%
19280877000000 1
0.9%
19109096000000 1
0.9%
18987947000000 1
0.9%

합계금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct101
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6647174 × 1013
Minimum0
Maximum1.5059266 × 1014
Zeros6
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:49:27.231820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.05643 × 1010
Q11.363025 × 1012
median4.7357075 × 1012
Q34.9251652 × 1013
95-th percentile9.636062 × 1013
Maximum1.5059266 × 1014
Range1.5059266 × 1014
Interquartile range (IQR)4.7888626 × 1013

Descriptive statistics

Standard deviation3.8352985 × 1013
Coefficient of variation (CV)1.4392891
Kurtosis0.89153572
Mean2.6647174 × 1013
Median Absolute Deviation (MAD)4.587131 × 1012
Skewness1.4042615
Sum3.0377778 × 1015
Variance1.4709515 × 1027
MonotonicityNot monotonic
2023-12-11T07:49:27.371082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
5.3%
150592657000000 2
 
1.8%
70037277000000 2
 
1.8%
89711870000000 2
 
1.8%
80805131000000 2
 
1.8%
90429433000000 2
 
1.8%
89569390000000 2
 
1.8%
68089489000000 2
 
1.8%
111133117000000 2
 
1.8%
1887635000000 1
 
0.9%
Other values (91) 91
79.8%
ValueCountFrequency (%)
0 6
5.3%
47022000000 1
 
0.9%
53071000000 1
 
0.9%
54887450000 1
 
0.9%
69550000000 1
 
0.9%
78875511000 1
 
0.9%
87618000000 1
 
0.9%
90850000000 1
 
0.9%
140052000000 1
 
0.9%
157101000000 1
 
0.9%
ValueCountFrequency (%)
150592657000000 2
1.8%
123275145000000 1
0.9%
111133117000000 2
1.8%
107375681000000 1
0.9%
90429433000000 2
1.8%
89711870000000 2
1.8%
89569390000000 2
1.8%
88571368000000 1
0.9%
87815093000000 1
0.9%
86869918000000 1
0.9%

연평균증감률(%)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct71
Distinct (%)65.7%
Missing6
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean-1.5962963
Minimum-100
Maximum16
Zeros1
Zeros (%)0.9%
Negative30
Negative (%)26.3%
Memory size1.1 KiB
2023-12-11T07:49:27.549368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-14.83
Q1-1
median2.85
Q34.6
95-th percentile7.66
Maximum16
Range116
Interquartile range (IQR)5.6

Descriptive statistics

Standard deviation17.856389
Coefficient of variation (CV)-11.186137
Kurtosis24.341001
Mean-1.5962963
Median Absolute Deviation (MAD)2.05
Skewness-4.7799903
Sum-172.4
Variance318.85064
MonotonicityNot monotonic
2023-12-11T07:49:27.718977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.6 7
 
6.1%
4.0 5
 
4.4%
0.8 5
 
4.4%
4.2 4
 
3.5%
4.3 3
 
2.6%
-100.0 3
 
2.6%
3.7 3
 
2.6%
2.2 3
 
2.6%
1.5 3
 
2.6%
5.3 2
 
1.8%
Other values (61) 70
61.4%
(Missing) 6
 
5.3%
ValueCountFrequency (%)
-100.0 3
2.6%
-22.3 1
 
0.9%
-21.3 1
 
0.9%
-14.9 1
 
0.9%
-14.7 1
 
0.9%
-13.3 1
 
0.9%
-12.7 1
 
0.9%
-12.2 1
 
0.9%
-11.1 1
 
0.9%
-10.6 1
 
0.9%
ValueCountFrequency (%)
16.0 1
0.9%
14.6 1
0.9%
13.1 1
0.9%
8.4 1
0.9%
8.1 1
0.9%
7.8 1
0.9%
7.4 1
0.9%
7.2 1
0.9%
7.0 1
0.9%
6.3 1
0.9%

Interactions

2023-12-11T07:49:24.175074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.438426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.178658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.807738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.534657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.298271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.196391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.990972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.271656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.542934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.275170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.891258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.642566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.404962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.293227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.089475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.358332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.628805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.355915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.969997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.745316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.514243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.385743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.200468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.469257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.709084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.436346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.050613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.851758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.693924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.485070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.323456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.557948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.797225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.507798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.146820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.939901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.785732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.597661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.439141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.656848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:18.908761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.578712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.228767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.026814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.891595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.695692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.585385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.748384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.004631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.653391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.313599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.124454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.986470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.801892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:23.944500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.854327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.098094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:19.733058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:20.445235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:21.216610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.095821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:22.906726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:24.060330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:49:27.836635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도구분명회계년도금액(원)회계년도+1년금액(원)회계년도+2년금액(원)회계년도+3년금액(원)회계년도+4년금액(원)합계금액(원)연평균증감률(%)
회계연도1.0000.0000.5640.4950.5390.5820.5980.5450.143
구분명0.0001.0000.8050.7980.7930.7950.7790.7920.816
회계년도금액(원)0.5640.8051.0000.9790.9460.9470.9470.9460.170
회계년도+1년금액(원)0.4950.7980.9791.0000.9970.9720.9720.9970.114
회계년도+2년금액(원)0.5390.7930.9460.9971.0001.0001.0000.9980.293
회계년도+3년금액(원)0.5820.7950.9470.9721.0001.0001.0000.9820.329
회계년도+4년금액(원)0.5980.7790.9470.9721.0001.0001.0000.9820.331
합계금액(원)0.5450.7920.9460.9970.9980.9820.9821.0000.137
연평균증감률(%)0.1430.8160.1700.1140.2930.3290.3310.1371.000
2023-12-11T07:49:28.291536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도회계년도금액(원)회계년도+1년금액(원)회계년도+2년금액(원)회계년도+3년금액(원)회계년도+4년금액(원)합계금액(원)연평균증감률(%)구분명
회계연도1.0000.0690.0930.0950.0840.0900.073-0.0560.000
회계년도금액(원)0.0691.0000.9680.9660.9670.9670.9850.5260.448
회계년도+1년금액(원)0.0930.9681.0000.9980.9960.9950.9950.6030.431
회계년도+2년금액(원)0.0950.9660.9981.0000.9970.9960.9940.6160.425
회계년도+3년금액(원)0.0840.9670.9960.9971.0000.9990.9950.6300.414
회계년도+4년금액(원)0.0900.9670.9950.9960.9991.0000.9940.6350.396
합계금액(원)0.0730.9850.9950.9940.9950.9941.0000.5970.423
연평균증감률(%)-0.0560.5260.6030.6160.6300.6350.5971.0000.526
구분명0.0000.4480.4310.4250.4140.3960.4230.5261.000

Missing values

2023-12-11T07:49:24.988936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:49:25.156681image/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

회계연도구분명회계년도금액(원)회계년도+1년금액(원)회계년도+2년금액(원)회계년도+3년금액(원)회계년도+4년금액(원)합계금액(원)연평균증감률(%)
02023① 세입28855196000000294152960000003016604700000030630701000000315254170000001505926570000002.2
12023② 세출28855196000000294152960000003016604700000030630701000000315254170000001505926570000002.2
22023교육일반8244267000000610790300000056496670000005197742000000516034000000030359919000000-11.1
32023기타 및 내부거래7549620000009788510000009974530000006052020000006333610000003969829000000-4.3
42023이전수입22657782000000235654380000002476782200000025680771000000266033320000001232751450000004.1
52023자체수입2817640000001877220000001874670000001872270000001870040000001031184000000-9.7
62023차입000000<NA>
72023평생교육27204000000275230000002797800000028438000000289090000001400520000001.5
82022① 세입20482299000000213583070000002197321900000022825490000000244938020000001111331170000004.6
92022② 세출20482299000000213583070000002197321900000022825490000000244938020000001111331170000004.6
회계연도구분명회계년도금액(원)회계년도+1년금액(원)회계년도+2년금액(원)회계년도+3년금액(원)회계년도+4년금액(원)합계금액(원)연평균증감률(%)
1042015보전수입등 및 내부거래68131000000681310000006813100000068131000000681310000003406550000000.0
1052015세입예산액1246763900000013421130000000137574820000001515729700000015233729000000700372770000005.1
1062015세출예산액1246763900000013421130000000137574820000001515729700000015233729000000700372770000005.1
1072015의존수입1083524500000012969854000000133062060000001470602100000014782453000000665997790000008.1
1082015인적자원운용69379340000007372973000000783583100000083280600000008854896000000393296940000006.3
1092015자체수입35505500000038314500000038314500000038314500000038314500000018876350000001.9
1102015지방교육채120920800000000001209208000000-100.0
1112015평생-직업교육93430000009343000000935200000093520000009632000000470220000000.8
1122015학교교육여건 개선시설1067874000000141138300000011547390000001975736000000141116800000070209000000007.2
1132015학교재정 지원관리1726256000000177056000000018187170000001868844000000195311900000091374960000003.1