Overview

Dataset statistics

Number of variables6
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory56.8 B

Variable types

Numeric5
Categorical1

Dataset

Description사립학교교직원연금공단 재심위원회 운영 현황과 관련된 데이터로 연도, 급여재심위원회 상정건수, 인용, 기각, 보류, 각하 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15081283/fileData.do

Alerts

연도 is highly overall correlated with 급여재심위원회 상정건수 and 3 other fieldsHigh correlation
급여재심위원회 상정건수 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
인용 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
기각 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
보류 is highly overall correlated with 연도 and 3 other fieldsHigh correlation
연도 has unique valuesUnique
급여재심위원회 상정건수 has 1 (2.1%) zerosZeros
인용 has 3 (6.4%) zerosZeros
기각 has 1 (2.1%) zerosZeros
보류 has 22 (46.8%) zerosZeros

Reproduction

Analysis started2023-12-12 22:09:57.441315
Analysis finished2023-12-12 22:10:00.252125
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999
Minimum1976
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-13T07:10:00.319236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1976
5-th percentile1978.3
Q11987.5
median1999
Q32010.5
95-th percentile2019.7
Maximum2022
Range46
Interquartile range (IQR)23

Descriptive statistics

Standard deviation13.711309
Coefficient of variation (CV)0.0068590841
Kurtosis-1.2
Mean1999
Median Absolute Deviation (MAD)12
Skewness0
Sum93953
Variance188
MonotonicityStrictly increasing
2023-12-13T07:10:00.476524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
1976 1
 
2.1%
1977 1
 
2.1%
2002 1
 
2.1%
2003 1
 
2.1%
2004 1
 
2.1%
2005 1
 
2.1%
2006 1
 
2.1%
2007 1
 
2.1%
2008 1
 
2.1%
2009 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
1976 1
2.1%
1977 1
2.1%
1978 1
2.1%
1979 1
2.1%
1980 1
2.1%
1981 1
2.1%
1982 1
2.1%
1983 1
2.1%
1984 1
2.1%
1985 1
2.1%
ValueCountFrequency (%)
2022 1
2.1%
2021 1
2.1%
2020 1
2.1%
2019 1
2.1%
2018 1
2.1%
2017 1
2.1%
2016 1
2.1%
2015 1
2.1%
2014 1
2.1%
2013 1
2.1%

급여재심위원회 상정건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.425532
Minimum0
Maximum153
Zeros1
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-13T07:10:00.621899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3
Q18.5
median42
Q366.5
95-th percentile97.7
Maximum153
Range153
Interquartile range (IQR)58

Descriptive statistics

Standard deviation36.253782
Coefficient of variation (CV)0.85452746
Kurtosis0.18475028
Mean42.425532
Median Absolute Deviation (MAD)33
Skewness0.69693447
Sum1994
Variance1314.3367
MonotonicityNot monotonic
2023-12-13T07:10:00.748088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3 4
 
8.5%
9 3
 
6.4%
58 3
 
6.4%
1 2
 
4.3%
78 2
 
4.3%
11 2
 
4.3%
60 2
 
4.3%
6 2
 
4.3%
8 1
 
2.1%
73 1
 
2.1%
Other values (25) 25
53.2%
ValueCountFrequency (%)
0 1
 
2.1%
1 2
4.3%
2 1
 
2.1%
3 4
8.5%
4 1
 
2.1%
6 2
4.3%
8 1
 
2.1%
9 3
6.4%
11 2
4.3%
17 1
 
2.1%
ValueCountFrequency (%)
153 1
2.1%
105 1
2.1%
98 1
2.1%
97 1
2.1%
94 1
2.1%
86 1
2.1%
79 1
2.1%
78 2
4.3%
73 1
2.1%
70 1
2.1%

인용
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6595745
Minimum0
Maximum42
Zeros3
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-13T07:10:00.895208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q12.5
median6
Q311
95-th percentile21
Maximum42
Range42
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation8.6785007
Coefficient of variation (CV)1.0021856
Kurtosis4.3279474
Mean8.6595745
Median Absolute Deviation (MAD)5
Skewness1.8329414
Sum407
Variance75.316374
MonotonicityNot monotonic
2023-12-13T07:10:01.010973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 8
17.0%
8 4
 
8.5%
6 4
 
8.5%
0 3
 
6.4%
11 3
 
6.4%
3 3
 
6.4%
4 3
 
6.4%
9 3
 
6.4%
19 2
 
4.3%
17 2
 
4.3%
Other values (9) 12
25.5%
ValueCountFrequency (%)
0 3
 
6.4%
1 8
17.0%
2 1
 
2.1%
3 3
 
6.4%
4 3
 
6.4%
5 2
 
4.3%
6 4
8.5%
7 1
 
2.1%
8 4
8.5%
9 3
 
6.4%
ValueCountFrequency (%)
42 1
 
2.1%
33 1
 
2.1%
21 2
4.3%
19 2
4.3%
18 1
 
2.1%
17 2
4.3%
13 2
4.3%
11 3
6.4%
10 1
 
2.1%
9 3
6.4%

기각
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.319149
Minimum0
Maximum141
Zeros1
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-13T07:10:01.124597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14.5
median28
Q351.5
95-th percentile74
Maximum141
Range141
Interquartile range (IQR)47

Descriptive statistics

Standard deviation29.109319
Coefficient of variation (CV)0.92944157
Kurtosis2.7449478
Mean31.319149
Median Absolute Deviation (MAD)24
Skewness1.2624711
Sum1472
Variance847.35245
MonotonicityNot monotonic
2023-12-13T07:10:01.248596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 4
 
8.5%
2 4
 
8.5%
35 3
 
6.4%
23 2
 
4.3%
63 2
 
4.3%
67 2
 
4.3%
4 2
 
4.3%
28 2
 
4.3%
58 2
 
4.3%
8 2
 
4.3%
Other values (22) 22
46.8%
ValueCountFrequency (%)
0 1
 
2.1%
1 4
8.5%
2 4
8.5%
3 1
 
2.1%
4 2
4.3%
5 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
8 2
4.3%
14 1
 
2.1%
ValueCountFrequency (%)
141 1
2.1%
79 1
2.1%
77 1
2.1%
67 2
4.3%
63 2
4.3%
58 2
4.3%
54 1
2.1%
53 1
2.1%
52 1
2.1%
51 1
2.1%

보류
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2
Minimum0
Maximum11
Zeros22
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-13T07:10:01.357759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile6.7
Maximum11
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6209855
Coefficient of variation (CV)1.3104928
Kurtosis1.6207086
Mean2
Median Absolute Deviation (MAD)1
Skewness1.3770708
Sum94
Variance6.8695652
MonotonicityNot monotonic
2023-12-13T07:10:01.456648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 22
46.8%
1 6
 
12.8%
4 6
 
12.8%
2 4
 
8.5%
6 3
 
6.4%
7 2
 
4.3%
5 2
 
4.3%
3 1
 
2.1%
11 1
 
2.1%
ValueCountFrequency (%)
0 22
46.8%
1 6
 
12.8%
2 4
 
8.5%
3 1
 
2.1%
4 6
 
12.8%
5 2
 
4.3%
6 3
 
6.4%
7 2
 
4.3%
11 1
 
2.1%
ValueCountFrequency (%)
11 1
 
2.1%
7 2
 
4.3%
6 3
 
6.4%
5 2
 
4.3%
4 6
 
12.8%
3 1
 
2.1%
2 4
 
8.5%
1 6
 
12.8%
0 22
46.8%

각하
Categorical

Distinct4
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
0
34 
1
7 
2
5 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
72.3%
1 7
 
14.9%
2 5
 
10.6%
4 1
 
2.1%

Length

2023-12-13T07:10:01.584523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:10:01.699735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
72.3%
1 7
 
14.9%
2 5
 
10.6%
4 1
 
2.1%

Interactions

2023-12-13T07:09:59.542703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:57.643004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.034004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.693918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.059918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.630601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:57.716162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.113947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.758085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.139524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.761402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:57.805969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.202126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.840660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.222779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.877534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:57.876718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.292080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.907804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.304230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.958472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:57.956511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.377234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:58.986339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:09:59.419554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:10:01.782768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도급여재심위원회 상정건수인용기각보류각하
연도1.0000.7700.6770.7510.5580.450
급여재심위원회 상정건수0.7701.0000.8570.8670.9010.732
인용0.6770.8571.0000.6580.6880.624
기각0.7510.8670.6581.0000.8100.486
보류0.5580.9010.6880.8101.0000.848
각하0.4500.7320.6240.4860.8481.000
2023-12-13T07:10:01.898701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도급여재심위원회 상정건수인용기각보류각하
연도1.0000.8970.6980.9330.6830.267
급여재심위원회 상정건수0.8971.0000.8450.9810.7870.379
인용0.6980.8451.0000.7690.7240.314
기각0.9330.9810.7691.0000.7250.339
보류0.6830.7870.7240.7251.0000.495
각하0.2670.3790.3140.3390.4951.000

Missing values

2023-12-13T07:10:00.094920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:10:00.211128image/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

연도급여재심위원회 상정건수인용기각보류각하
0197610100
1197731110
2197841300
3197921100
4198010100
5198100000
6198231200
7198331200
8198462400
9198531200
연도급여재심위원회 상정건수인용기각보류각하
3720135884901
3820144573800
39201565115310
4020166865822
41201770105172
4220187866354
43201994677110
44202097117961
4520217996352
46202286116762