Overview

Dataset statistics

Number of variables3
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory28.0 B

Variable types

Numeric2
Categorical1

Dataset

Description경기도 교육재정 성질별 세출 자본지출(예산) 현황
Author교육부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=IQPXZ9O7LD73RZWT09S423929006&infSeq=2

Alerts

금액(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:33:52.160453
Analysis finished2023-12-10 21:33:52.612041
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Real number (ℝ)

Distinct11
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-11T06:33:52.663507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12015
median2018
Q32021
95-th percentile2023
Maximum2023
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.18651
Coefficient of variation (CV)0.0015790436
Kurtosis-1.2210069
Mean2018
Median Absolute Deviation (MAD)3
Skewness0
Sum133188
Variance10.153846
MonotonicityDecreasing
2023-12-11T06:33:52.755712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2023 6
9.1%
2022 6
9.1%
2021 6
9.1%
2020 6
9.1%
2019 6
9.1%
2018 6
9.1%
2017 6
9.1%
2016 6
9.1%
2015 6
9.1%
2014 6
9.1%
ValueCountFrequency (%)
2013 6
9.1%
2014 6
9.1%
2015 6
9.1%
2016 6
9.1%
2017 6
9.1%
2018 6
9.1%
2019 6
9.1%
2020 6
9.1%
2021 6
9.1%
2022 6
9.1%
ValueCountFrequency (%)
2023 6
9.1%
2022 6
9.1%
2021 6
9.1%
2020 6
9.1%
2019 6
9.1%
2018 6
9.1%
2017 6
9.1%
2016 6
9.1%
2015 6
9.1%
2014 6
9.1%

항목구분명
Categorical

Distinct6
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
건설비
11 
기타자산 취득비
11 
세출예산액
11 
유·무형 자산취득비
11 
자본지출
11 

Length

Max length10
Median length6.5
Mean length5.8333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건설비
2nd row기타자산 취득비
3rd row세출예산액
4th row유·무형 자산취득비
5th row자본지출

Common Values

ValueCountFrequency (%)
건설비 11
16.7%
기타자산 취득비 11
16.7%
세출예산액 11
16.7%
유·무형 자산취득비 11
16.7%
자본지출 11
16.7%
토지매입비 11
16.7%

Length

2023-12-11T06:33:52.871539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:52.969896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설비 11
12.5%
기타자산 11
12.5%
취득비 11
12.5%
세출예산액 11
12.5%
유·무형 11
12.5%
자산취득비 11
12.5%
자본지출 11
12.5%
토지매입비 11
12.5%

금액(원)
Real number (ℝ)

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8754822 × 1012
Minimum1.540756 × 109
Maximum2.2334511 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-11T06:33:53.084971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.540756 × 109
5-th percentile2.187308 × 109
Q12.1793264 × 1010
median4.1011526 × 1011
Q31.4043469 × 1012
95-th percentile1.5795793 × 1013
Maximum2.2334511 × 1013
Range2.233297 × 1013
Interquartile range (IQR)1.3825536 × 1012

Descriptive statistics

Standard deviation5.5631633 × 1012
Coefficient of variation (CV)1.9346888
Kurtosis3.0736402
Mean2.8754822 × 1012
Median Absolute Deviation (MAD)4.037645 × 1011
Skewness2.0741836
Sum1.8978183 × 1014
Variance3.0948786 × 1025
MonotonicityNot monotonic
2023-12-11T06:33:53.213119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2435360248000 1
 
1.5%
11764860214000 1
 
1.5%
404816948000 1
 
1.5%
1540756000 1
 
1.5%
12052413872000 1
 
1.5%
16478402000 1
 
1.5%
504518891000 1
 
1.5%
81682785000 1
 
1.5%
588910055000 1
 
1.5%
2249503000 1
 
1.5%
Other values (56) 56
84.8%
ValueCountFrequency (%)
1540756000 1
1.5%
1653201000 1
1.5%
1941818000 1
1.5%
2186729000 1
1.5%
2189045000 1
1.5%
2249503000 1
1.5%
2345355000 1
1.5%
5306486000 1
1.5%
7395039000 1
1.5%
14205726000 1
1.5%
ValueCountFrequency (%)
22334511186000 1
1.5%
19195902297000 1
1.5%
16465048025000 1
1.5%
15921804872000 1
1.5%
15417755831000 1
1.5%
14548472098000 1
1.5%
12122991238000 1
1.5%
12052413872000 1
1.5%
11764860214000 1
1.5%
11278472732000 1
1.5%

Interactions

2023-12-11T06:33:52.370626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:52.231823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:52.436460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:52.305742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:33:53.290128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도항목구분명금액(원)
회계연도1.0000.0000.000
항목구분명0.0001.0000.562
금액(원)0.0000.5621.000
2023-12-11T06:33:53.409969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도금액(원)항목구분명
회계연도1.0000.1390.000
금액(원)0.1391.0000.350
항목구분명0.0000.3501.000

Missing values

2023-12-11T06:33:52.520766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:33:52.586339image/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)
02023건설비2435360248000
12023기타자산 취득비15008006000
22023세출예산액22334511186000
32023유·무형 자산취득비56909744000
42023자본지출2650240664000
52023토지매입비142962666000
62022건설비1938879783000
72022기타자산 취득비14205726000
82022세출예산액19195902297000
92022유·무형 자산취득비180222829000
회계연도항목구분명금액(원)
562014세출예산액11278472732000
572014유·무형 자산취득비17521997000
582014자본지출727468057000
592014토지매입비216927273000
602013건설비617547179000
612013기타자산 취득비2189045000
622013세출예산액10933647855000
632013유·무형 자산취득비16527903000
642013자본지출1051677695000
652013토지매입비415413568000