Overview

Dataset statistics

Number of variables4
Number of observations251
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory35.5 B

Variable types

Categorical2
Numeric2

Dataset

Description기능별 단체별 세출예산 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=99K2I8MX5K33MU5LPPFA22367367&infSeq=1

Alerts

세출예산총계액(원) is highly overall correlated with 세출예산순계액(원)High correlation
세출예산순계액(원) is highly overall correlated with 세출예산총계액(원)High correlation
회계연도 is highly imbalanced (69.0%)Imbalance
세출예산총계액(원) has unique valuesUnique
세출예산순계액(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:52:11.521289
Analysis finished2023-12-10 22:52:12.249797
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2022
237 
2023
 
14

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2022 237
94.4%
2023 14
 
5.6%

Length

2023-12-11T07:52:12.609689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:52:12.713888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 237
94.4%
2023 14
 
5.6%

분야명
Categorical

Distinct14
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
일반공공행정
18 
공공질서및안전
18 
교육
18 
문화및관광
18 
환경
18 
Other values (9)
161 

Length

Max length11
Median length6
Mean length4.7171315
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반공공행정
2nd row공공질서및안전
3rd row교육
4th row문화및관광
5th row환경

Common Values

ValueCountFrequency (%)
일반공공행정 18
 
7.2%
공공질서및안전 18
 
7.2%
교육 18
 
7.2%
문화및관광 18
 
7.2%
환경 18
 
7.2%
사회복지 18
 
7.2%
기타 18
 
7.2%
농림해양수산 18
 
7.2%
산업ㆍ중소기업및에너지 18
 
7.2%
교통및물류 18
 
7.2%
Other values (4) 71
28.3%

Length

2023-12-11T07:52:12.835117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반공공행정 18
 
7.2%
공공질서및안전 18
 
7.2%
교육 18
 
7.2%
문화및관광 18
 
7.2%
환경 18
 
7.2%
사회복지 18
 
7.2%
기타 18
 
7.2%
농림해양수산 18
 
7.2%
산업ㆍ중소기업및에너지 18
 
7.2%
교통및물류 18
 
7.2%
Other values (4) 71
28.3%

세출예산총계액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4968563 × 1011
Minimum1.01739 × 109
Maximum1.5953228 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T07:52:12.974779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.01739 × 109
5-th percentile2.3856524 × 1010
Q11.8036816 × 1011
median4.2967802 × 1011
Q37.803876 × 1011
95-th percentile3.6075391 × 1012
Maximum1.5953228 × 1013
Range1.5952211 × 1013
Interquartile range (IQR)6.0001943 × 1011

Descriptive statistics

Standard deviation1.9189678 × 1012
Coefficient of variation (CV)2.0206347
Kurtosis32.872194
Mean9.4968563 × 1011
Median Absolute Deviation (MAD)2.8836535 × 1011
Skewness5.2171471
Sum2.3837109 × 1014
Variance3.6824372 × 1024
MonotonicityNot monotonic
2023-12-11T07:52:13.173158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6049848672000 1
 
0.4%
718043366000 1
 
0.4%
124423210000 1
 
0.4%
71609454000 1
 
0.4%
100972443000 1
 
0.4%
199051625000 1
 
0.4%
6787911000 1
 
0.4%
9018543000 1
 
0.4%
221922590000 1
 
0.4%
7341003391000 1
 
0.4%
Other values (241) 241
96.0%
ValueCountFrequency (%)
1017390000 1
0.4%
1843741000 1
0.4%
3318578000 1
0.4%
3827370000 1
0.4%
6787911000 1
0.4%
6835937000 1
0.4%
6930100000 1
0.4%
9018543000 1
0.4%
9069720000 1
0.4%
10445491000 1
0.4%
ValueCountFrequency (%)
15953228320000 1
0.4%
14887978191000 1
0.4%
13425975344000 1
0.4%
7542604287000 1
0.4%
7341003391000 1
0.4%
6049848672000 1
0.4%
5996446797000 1
0.4%
5636941350000 1
0.4%
4476144196000 1
0.4%
4464911131000 1
0.4%

세출예산순계액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct251
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0576115 × 1011
Minimum1.01739 × 109
Maximum6.2236478 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T07:52:13.315195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.01739 × 109
5-th percentile1.0869846 × 1010
Q17.2655714 × 1010
median1.8111912 × 1011
Q34.6064518 × 1011
95-th percentile1.4107945 × 1012
Maximum6.2236478 × 1012
Range6.2226304 × 1012
Interquartile range (IQR)3.8798947 × 1011

Descriptive statistics

Standard deviation6.9454119 × 1011
Coefficient of variation (CV)1.7116996
Kurtosis28.261005
Mean4.0576115 × 1011
Median Absolute Deviation (MAD)1.4395667 × 1011
Skewness4.6418643
Sum1.0184605 × 1014
Variance4.8238746 × 1023
MonotonicityNot monotonic
2023-12-11T07:52:13.462693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
570476925000 1
 
0.4%
144376053000 1
 
0.4%
124423210000 1
 
0.4%
70417674000 1
 
0.4%
100334443000 1
 
0.4%
198248625000 1
 
0.4%
6787911000 1
 
0.4%
9018543000 1
 
0.4%
221922590000 1
 
0.4%
1132566098000 1
 
0.4%
Other values (241) 241
96.0%
ValueCountFrequency (%)
1017390000 1
0.4%
1843741000 1
0.4%
2318578000 1
0.4%
3827370000 1
0.4%
4981178000 1
0.4%
5120100000 1
0.4%
5764497000 1
0.4%
6787911000 1
0.4%
9018543000 1
0.4%
9069720000 1
0.4%
ValueCountFrequency (%)
6223647778000 1
0.4%
4369193425000 1
0.4%
4258397515000 1
0.4%
3165358110000 1
0.4%
3155999138000 1
0.4%
2333925915000 1
0.4%
2171713538000 1
0.4%
2105926168000 1
0.4%
1986275284000 1
0.4%
1469886721000 1
0.4%

Interactions

2023-12-11T07:52:11.884920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:11.674882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:11.999777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:52:11.787346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:52:13.587083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도분야명세출예산총계액(원)세출예산순계액(원)
회계연도1.0000.0000.2070.282
분야명0.0001.0000.5920.380
세출예산총계액(원)0.2070.5921.0000.753
세출예산순계액(원)0.2820.3800.7531.000
2023-12-11T07:52:13.670286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도분야명
회계연도1.0000.000
분야명0.0001.000
2023-12-11T07:52:13.749541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세출예산총계액(원)세출예산순계액(원)회계연도분야명
세출예산총계액(원)1.0000.7800.2200.256
세출예산순계액(원)0.7801.0000.2090.175
회계연도0.2200.2091.0000.000
분야명0.2560.1750.0001.000

Missing values

2023-12-11T07:52:12.109972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:52:12.207443image/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

회계연도분야명세출예산총계액(원)세출예산순계액(원)
02023일반공공행정6049848672000570476925000
12023공공질서및안전1743714628000579624662000
22023교육31639540510003155999138000
32023문화및관광616749371000295140077000
42023환경143759860000052232519000
52023사회복지148879781910002333925915000
62023기타14407168630001457217973000
72023농림해양수산1049379503000359092228000
82023산업ㆍ중소기업및에너지414477713000252943966000
92023교통및물류17599066400001346574955000
회계연도분야명세출예산총계액(원)세출예산순계액(원)
2412022사회복지3224114818000575840066000
2422022보건16107387000033359326000
2432022농림해양수산1845129193000181119125000
2442022산업ㆍ중소기업및에너지293460791000143468309000
2452022국토및지역개발36281173100026826430000
2462022과학기술69301000005120100000
2472022예비비9068114700090681147000
2482022기타599665775000599665775000
2492022일반공공행정875099619000139224378000
2502022공공질서및안전765773185000189797474000