Overview

Dataset statistics

Number of variables5
Number of observations359
Missing cells88
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.9 KiB
Average record size in memory42.4 B

Variable types

Numeric2
Categorical2
Text1

Dataset

Description경기도 교육재정 재정분석(결산) 현황
Author교육부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=SAM25M4PO6BDEW3KYA8323831812&infSeq=2

Alerts

지표명 is highly imbalanced (63.6%)Imbalance
비율/증감율(%) has 88 (24.5%) missing valuesMissing
비율/증감율(%) has 17 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-10 22:48:24.706682
Analysis finished2023-12-10 22:48:25.993054
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Real number (ℝ)

Distinct8
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5292
Minimum2014
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T07:48:26.053518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2017
Q32019
95-th percentile2021
Maximum2021
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2432038
Coefficient of variation (CV)0.0011118569
Kurtosis-1.2399518
Mean2017.5292
Median Absolute Deviation (MAD)2
Skewness0.038957582
Sum724293
Variance5.0319634
MonotonicityDecreasing
2023-12-11T07:48:26.184286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2016 67
18.7%
2019 54
15.0%
2021 44
12.3%
2020 43
12.0%
2015 42
11.7%
2017 37
10.3%
2018 36
10.0%
2014 36
10.0%
ValueCountFrequency (%)
2014 36
10.0%
2015 42
11.7%
2016 67
18.7%
2017 37
10.3%
2018 36
10.0%
2019 54
15.0%
2020 43
12.0%
2021 44
12.3%
ValueCountFrequency (%)
2021 44
12.3%
2020 43
12.0%
2019 54
15.0%
2018 36
10.0%
2017 37
10.3%
2016 67
18.7%
2015 42
11.7%
2014 36
10.0%

지표명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
재정효율성
298 
재정건전성
38 
재정책무성
 
9
사회적책무성
 
6
감점지표
 
5

Length

Max length6
Median length5
Mean length4.994429
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가점지표
2nd row감점지표
3rd row재정건전성
4th row재정건전성
5th row재정건전성

Common Values

ValueCountFrequency (%)
재정효율성 298
83.0%
재정건전성 38
 
10.6%
재정책무성 9
 
2.5%
사회적책무성 6
 
1.7%
감점지표 5
 
1.4%
가점지표 3
 
0.8%

Length

2023-12-11T07:48:26.364197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:26.514056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재정효율성 298
83.0%
재정건전성 38
 
10.6%
재정책무성 9
 
2.5%
사회적책무성 6
 
1.7%
감점지표 5
 
1.4%
가점지표 3
 
0.8%

항목명
Text

Distinct273
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-11T07:48:26.784739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length34
Mean length18.08078
Min length6

Characters and Unicode

Total characters6491
Distinct characters175
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)57.7%

Sample

1st row지방교육재정 운용 효율화 제고를 위한 노력도
2nd row재정 법령 준수 및 재정분석 대응도
3rd row1.통합재정수지 비율
4th row3-1.총 관리채무 비율
5th row3.관리채무 비율
ValueCountFrequency (%)
비율 254
 
20.1%
증감률 85
 
6.7%
집행 68
 
5.4%
및 44
 
3.5%
비율의 27
 
2.1%
전입 25
 
2.0%
총액인건비 18
 
1.4%
예측 15
 
1.2%
학교수 14
 
1.1%
편성 13
 
1.0%
Other values (336) 703
55.5%
2023-12-11T07:48:27.243676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
907
 
14.0%
비 429
 
6.6%
. 355
 
5.5%
1 311
 
4.8%
율 292
 
4.5%
- 250
 
3.9%
2 142
 
2.2%
교 126
 
1.9%
행 122
 
1.9%
집 109
 
1.7%
Other values (165) 3448
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4044
62.3%
Space Separator 907
 
14.0%
Decimal Number 805
 
12.4%
Other Punctuation 388
 
6.0%
Dash Punctuation 250
 
3.9%
Open Punctuation 36
 
0.6%
Close Punctuation 35
 
0.5%
Math Symbol 17
 
0.3%
Modifier Symbol 6
 
0.1%
Final Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 429
 
10.6%
율 292
 
7.2%
교 126
 
3.1%
행 122
 
3.0%
집 109
 
2.7%
감 92
 
2.3%
증 90
 
2.2%
률 88
 
2.2%
지 88
 
2.2%
정 88
 
2.2%
Other values (142) 2520
62.3%
Decimal Number
ValueCountFrequency (%)
1 311
38.6%
2 142
17.6%
3 82
 
10.2%
9 52
 
6.5%
4 46
 
5.7%
5 46
 
5.7%
6 39
 
4.8%
7 35
 
4.3%
0 26
 
3.2%
8 26
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 355
91.5%
· 18
 
4.6%
/ 9
 
2.3%
' 4
 
1.0%
, 2
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 15
88.2%
≥ 2
 
11.8%
Space Separator
ValueCountFrequency (%)
907
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 250
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 6
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4044
62.3%
Common 2447
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 429
 
10.6%
율 292
 
7.2%
교 126
 
3.1%
행 122
 
3.0%
집 109
 
2.7%
감 92
 
2.3%
증 90
 
2.2%
률 88
 
2.2%
지 88
 
2.2%
정 88
 
2.2%
Other values (142) 2520
62.3%
Common
ValueCountFrequency (%)
907
37.1%
. 355
 
14.5%
1 311
 
12.7%
- 250
 
10.2%
2 142
 
5.8%
3 82
 
3.4%
9 52
 
2.1%
4 46
 
1.9%
5 46
 
1.9%
6 39
 
1.6%
Other values (13) 217
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4044
62.3%
ASCII 2418
37.3%
None 24
 
0.4%
Punctuation 3
 
< 0.1%
Math Operators 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
907
37.5%
. 355
 
14.7%
1 311
 
12.9%
- 250
 
10.3%
2 142
 
5.9%
3 82
 
3.4%
9 52
 
2.2%
4 46
 
1.9%
5 46
 
1.9%
6 39
 
1.6%
Other values (9) 188
 
7.8%
Hangul
ValueCountFrequency (%)
비 429
 
10.6%
율 292
 
7.2%
교 126
 
3.1%
행 122
 
3.0%
집 109
 
2.7%
감 92
 
2.3%
증 90
 
2.2%
률 88
 
2.2%
지 88
 
2.2%
정 88
 
2.2%
Other values (142) 2520
62.3%
None
ValueCountFrequency (%)
· 18
75.0%
´ 6
 
25.0%
Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Math Operators
ValueCountFrequency (%)
≥ 2
100.0%

구분명
Categorical

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
비율
197 
<NA>
98 
증감률
59 
편차평균
 
4
편차 평균
 
1

Length

Max length5
Median length2
Mean length2.7409471
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
비율 197
54.9%
<NA> 98
27.3%
증감률 59
 
16.4%
편차평균 4
 
1.1%
편차 평균 1
 
0.3%

Length

2023-12-11T07:48:27.391662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:48:27.513154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비율 197
54.7%
na 98
27.2%
증감률 59
 
16.4%
편차평균 4
 
1.1%
편차 1
 
0.3%
평균 1
 
0.3%

비율/증감율(%)
Real number (ℝ)

MISSING  ZEROS 

Distinct238
Distinct (%)87.8%
Missing88
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean-29.305129
Minimum-19033.3
Maximum324.56
Zeros17
Zeros (%)4.7%
Negative37
Negative (%)10.3%
Memory size3.3 KiB
2023-12-11T07:48:27.639046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-19033.3
5-th percentile-12.9
Q10.25
median21.83
Q384.285
95-th percentile114.51
Maximum324.56
Range19357.86
Interquartile range (IQR)84.035

Descriptive statistics

Standard deviation1159.855
Coefficient of variation (CV)-39.578566
Kurtosis269.89707
Mean-29.305129
Median Absolute Deviation (MAD)25.33
Skewness-16.41188
Sum-7941.69
Variance1345263.6
MonotonicityNot monotonic
2023-12-11T07:48:27.799646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
4.7%
100.0 5
 
1.4%
0.1 3
 
0.8%
56.1 2
 
0.6%
2.4 2
 
0.6%
0.19 2
 
0.6%
0.01 2
 
0.6%
5.03 2
 
0.6%
0.2 2
 
0.6%
0.02 2
 
0.6%
Other values (228) 232
64.6%
(Missing) 88
 
24.5%
ValueCountFrequency (%)
-19033.3 1
0.3%
-58.4 1
0.3%
-56.8 1
0.3%
-48.1 1
0.3%
-42.9 1
0.3%
-39.2 1
0.3%
-35.6 1
0.3%
-29.19 1
0.3%
-23.38 1
0.3%
-22.7 1
0.3%
ValueCountFrequency (%)
324.56 1
0.3%
230.7 1
0.3%
210.8 1
0.3%
170.8 1
0.3%
159.5 1
0.3%
158.5 1
0.3%
157.04 1
0.3%
144.74 1
0.3%
140.03 1
0.3%
133.6 1
0.3%

Interactions

2023-12-11T07:48:25.572876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:24.992054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:25.689204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:48:25.130334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:48:27.935973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도지표명구분명비율/증감율(%)
회계연도1.0000.1530.170NaN
지표명0.1531.0000.183NaN
구분명0.1700.1831.000NaN
비율/증감율(%)NaNNaNNaN1.000
2023-12-11T07:48:28.027023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분명지표명
구분명1.0000.073
지표명0.0731.000
2023-12-11T07:48:28.125864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도비율/증감율(%)지표명구분명
회계연도1.0000.0480.0930.153
비율/증감율(%)0.0481.0000.0000.032
지표명0.0930.0001.0000.073
구분명0.1530.0320.0731.000

Missing values

2023-12-11T07:48:25.826320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:48:25.944401image/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

회계연도지표명항목명구분명비율/증감율(%)
02021가점지표지방교육재정 운용 효율화 제고를 위한 노력도<NA>0.0
12021감점지표재정 법령 준수 및 재정분석 대응도<NA>0.0
22021재정건전성1.통합재정수지 비율비율5.03
32021재정건전성3-1.총 관리채무 비율비율11.37
42021재정건전성3.관리채무 비율<NA>0.0
52021재정건전성3-2.자체부담 관리채무 비율비율0.01
62021재정건전성2.경상적 지출 비율비율68.84
72021재정책무성14.주민참여예산 운영 실적<NA>0.0
82021재정책무성15.지방교육재정 정보공개 실적<NA>0.0
92021재정책무성16.사회적 약자기업 제품구매 비율비율0.0
회계연도지표명항목명구분명비율/증감율(%)
3492014재정효율성14.시설비 집행비율70.8
3502014재정효율성14.시설비 집행증감률-0.3
3512014재정효율성15.중앙투자심사사업 적정 집행비율15.4
3522014재정효율성16.집행잔액비율1.4
3532014재정효율성3.지방세(법정) 이전수입 전입비율17.0
3542014재정효율성2.시설사업 예측증감률-19033.3
3552014재정효율성2.시설사업 예측비율-56.8
3562014재정효율성1.예산 총규모 예측증감률2.6
3572014재정효율성1.예산 총규모 예측비율95.0
3582014재정효율성7.핵심 교육서비스 투자비율99.5