Overview

Dataset statistics

Number of variables3
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory28.5 B

Variable types

Numeric2
Categorical1

Dataset

Description경기도 교육재정 부채 총괄(결산) 현황
Author교육부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=9YBU7DZ8DAGT59WD6EAA23724662&infSeq=2

Alerts

금액(원) is highly overall correlated with 항목구분명High correlation
항목구분명 is highly overall correlated with 금액(원)High correlation
금액(원) has 13 (25.0%) zerosZeros

Reproduction

Analysis started2023-12-10 21:22:26.385545
Analysis finished2023-12-10 21:22:26.968167
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Real number (ℝ)

Distinct13
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016
Minimum2010
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T06:22:27.018623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2010
Q12013
median2016
Q32019
95-th percentile2022
Maximum2022
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7781622
Coefficient of variation (CV)0.0018740884
Kurtosis-1.2147813
Mean2016
Median Absolute Deviation (MAD)3
Skewness0
Sum104832
Variance14.27451
MonotonicityDecreasing
2023-12-11T06:22:27.118765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2022 4
 
7.7%
2021 4
 
7.7%
2020 4
 
7.7%
2019 4
 
7.7%
2018 4
 
7.7%
2017 4
 
7.7%
2016 4
 
7.7%
2015 4
 
7.7%
2014 4
 
7.7%
2013 4
 
7.7%
Other values (3) 12
23.1%
ValueCountFrequency (%)
2010 4
7.7%
2011 4
7.7%
2012 4
7.7%
2013 4
7.7%
2014 4
7.7%
2015 4
7.7%
2016 4
7.7%
2017 4
7.7%
2018 4
7.7%
2019 4
7.7%
ValueCountFrequency (%)
2022 4
7.7%
2021 4
7.7%
2020 4
7.7%
2019 4
7.7%
2018 4
7.7%
2017 4
7.7%
2016 4
7.7%
2015 4
7.7%
2014 4
7.7%
2013 4
7.7%

항목구분명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
부채
13 
우발부채
13 
통합부채
13 
통합자산
13 

Length

Max length4
Median length4
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부채
2nd row우발부채
3rd row통합부채
4th row통합자산
5th row부채

Common Values

ValueCountFrequency (%)
부채 13
25.0%
우발부채 13
25.0%
통합부채 13
25.0%
통합자산 13
25.0%

Length

2023-12-11T06:22:27.254094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:22:27.378791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부채 13
25.0%
우발부채 13
25.0%
통합부채 13
25.0%
통합자산 13
25.0%

금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6067745 × 1012
Minimum0
Maximum3.9876823 × 1013
Zeros13
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T06:22:27.492796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.2591687 × 1012
median3.9985888 × 1012
Q39.579625 × 1012
95-th percentile2.9895936 × 1013
Maximum3.9876823 × 1013
Range3.9876823 × 1013
Interquartile range (IQR)8.3204563 × 1012

Descriptive statistics

Standard deviation1.0831039 × 1013
Coefficient of variation (CV)1.2584319
Kurtosis0.50588342
Mean8.6067745 × 1012
Median Absolute Deviation (MAD)3.2151665 × 1012
Skewness1.340548
Sum4.4755227 × 1014
Variance1.1731142 × 1026
MonotonicityNot monotonic
2023-12-11T06:22:27.648759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 13
25.0%
1678891577515 2
 
3.8%
3920290194676 2
 
3.8%
5851210045452 2
 
3.8%
6430333005808 2
 
3.8%
3870035506049 2
 
3.8%
5853414305735 2
 
3.8%
4177958882356 2
 
3.8%
4907748092752 2
 
3.8%
2990521415144 2
 
3.8%
Other values (17) 21
40.4%
ValueCountFrequency (%)
0 13
25.0%
1678891577515 2
 
3.8%
2193177381346 2
 
3.8%
2809454361751 2
 
3.8%
2990521415144 2
 
3.8%
3870035506049 2
 
3.8%
3920290194676 2
 
3.8%
3998588789240 2
 
3.8%
4177958882356 2
 
3.8%
4613477659345 2
 
3.8%
ValueCountFrequency (%)
39876822856578 1
1.9%
33448849081385 1
1.9%
31099796212687 1
1.9%
28910960101931 1
1.9%
26810105424163 1
1.9%
25308749879835 1
1.9%
24558311978411 1
1.9%
24143060234407 1
1.9%
23170166233877 1
1.9%
21951664799570 1
1.9%

Interactions

2023-12-11T06:22:26.651829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:26.461394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:26.751644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:22:26.545687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:22:27.767324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도항목구분명금액(원)
회계연도1.0000.0000.000
항목구분명0.0001.0000.889
금액(원)0.0000.8891.000
2023-12-11T06:22:27.885321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도금액(원)항목구분명
회계연도1.000-0.0380.000
금액(원)-0.0381.0000.555
항목구분명0.0000.5551.000

Missing values

2023-12-11T06:22:26.871639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:22:26.936523image/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

회계연도항목구분명금액(원)
02022부채1678891577515
12022우발부채0
22022통합부채1678891577515
32022통합자산39876822856578
42021부채2193177381346
52021우발부채0
62021통합부채2193177381346
72021통합자산33448849081385
82020부채2809454361751
92020우발부채0
회계연도항목구분명금액(원)
422012통합부채3870035506049
432012통합자산21447011374256
442011부채3920290194676
452011우발부채0
462011통합부채3920290194676
472011통합자산21209071479242
482010부채3998588789240
492010우발부채0
502010통합부채3998588789240
512010통합자산19027501035133