Overview

Dataset statistics

Number of variables7
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory66.2 B

Variable types

Numeric7

Dataset

Description사립학교교직원연금공단 해당연도의 합산내역별 승인 건수와 관련된 데이터로 연도, 유형별(사립학교, 재임용, 공무원, 군인), 교직원별(교원, 사무직원) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15049779/fileData.do

Alerts

연도 is highly overall correlated with 사립학교교원 and 4 other fieldsHigh correlation
사립학교교원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
사립학교사무직원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
재임용교원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
재임용사무직원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
공무원군인사무직원 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
연도 has unique valuesUnique
사립학교교원 has unique valuesUnique
재임용교원 has unique valuesUnique
공무원군인교원 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:57:35.834013
Analysis finished2023-12-12 14:57:41.199968
Duration5.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002
Minimum1982
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:41.263938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1982
5-th percentile1984
Q11992
median2002
Q32012
95-th percentile2020
Maximum2022
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.0059835907
Kurtosis-1.2
Mean2002
Median Absolute Deviation (MAD)10
Skewness0
Sum82082
Variance143.5
MonotonicityStrictly increasing
2023-12-12T23:57:41.398700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1982 1
 
2.4%
2013 1
 
2.4%
2005 1
 
2.4%
2006 1
 
2.4%
2007 1
 
2.4%
2008 1
 
2.4%
2009 1
 
2.4%
2010 1
 
2.4%
2011 1
 
2.4%
2012 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1982 1
2.4%
1983 1
2.4%
1984 1
2.4%
1985 1
2.4%
1986 1
2.4%
1987 1
2.4%
1988 1
2.4%
1989 1
2.4%
1990 1
2.4%
1991 1
2.4%
ValueCountFrequency (%)
2022 1
2.4%
2021 1
2.4%
2020 1
2.4%
2019 1
2.4%
2018 1
2.4%
2017 1
2.4%
2016 1
2.4%
2015 1
2.4%
2014 1
2.4%
2013 1
2.4%

사립학교교원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean674.63415
Minimum225
Maximum1689
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:41.519942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum225
5-th percentile238
Q1453
median601
Q3908
95-th percentile993
Maximum1689
Range1464
Interquartile range (IQR)455

Descriptive statistics

Standard deviation314.14509
Coefficient of variation (CV)0.46565252
Kurtosis1.6022662
Mean674.63415
Median Absolute Deviation (MAD)182
Skewness1.0188508
Sum27660
Variance98687.138
MonotonicityNot monotonic
2023-12-12T23:57:41.650022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
238 1
 
2.4%
913 1
 
2.4%
601 1
 
2.4%
955 1
 
2.4%
749 1
 
2.4%
992 1
 
2.4%
915 1
 
2.4%
1689 1
 
2.4%
852 1
 
2.4%
783 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
225 1
2.4%
237 1
2.4%
238 1
2.4%
272 1
2.4%
345 1
2.4%
413 1
2.4%
420 1
2.4%
431 1
2.4%
448 1
2.4%
452 1
2.4%
ValueCountFrequency (%)
1689 1
2.4%
1425 1
2.4%
993 1
2.4%
992 1
2.4%
987 1
2.4%
981 1
2.4%
955 1
2.4%
919 1
2.4%
915 1
2.4%
913 1
2.4%

사립학교사무직원
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.34146
Minimum43
Maximum1150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:41.806606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile97
Q1158
median245
Q3477
95-th percentile709
Maximum1150
Range1107
Interquartile range (IQR)319

Descriptive statistics

Standard deviation239.13434
Coefficient of variation (CV)0.6944686
Kurtosis1.6176891
Mean344.34146
Median Absolute Deviation (MAD)135
Skewness1.2010296
Sum14118
Variance57185.23
MonotonicityNot monotonic
2023-12-12T23:57:41.963210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
191 2
 
4.9%
110 2
 
4.9%
158 2
 
4.9%
445 1
 
2.4%
502 1
 
2.4%
467 1
 
2.4%
706 1
 
2.4%
477 1
 
2.4%
420 1
 
2.4%
476 1
 
2.4%
Other values (28) 28
68.3%
ValueCountFrequency (%)
43 1
2.4%
92 1
2.4%
97 1
2.4%
110 2
4.9%
133 1
2.4%
142 1
2.4%
143 1
2.4%
144 1
2.4%
158 2
4.9%
160 1
2.4%
ValueCountFrequency (%)
1150 1
2.4%
719 1
2.4%
709 1
2.4%
706 1
2.4%
699 1
2.4%
669 1
2.4%
596 1
2.4%
536 1
2.4%
502 1
2.4%
483 1
2.4%

재임용교원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1001.561
Minimum84
Maximum2799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:42.127938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84
5-th percentile93
Q1238
median557
Q31944
95-th percentile2702
Maximum2799
Range2715
Interquartile range (IQR)1706

Descriptive statistics

Standard deviation961.09971
Coefficient of variation (CV)0.95960179
Kurtosis-1.0043116
Mean1001.561
Median Absolute Deviation (MAD)444
Skewness0.79164913
Sum41064
Variance923712.65
MonotonicityNot monotonic
2023-12-12T23:57:42.264379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
808 1
 
2.4%
2150 1
 
2.4%
557 1
 
2.4%
755 1
 
2.4%
1064 1
 
2.4%
1118 1
 
2.4%
1038 1
 
2.4%
1303 1
 
2.4%
1494 1
 
2.4%
1944 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
84 1
2.4%
92 1
2.4%
93 1
2.4%
99 1
2.4%
113 1
2.4%
140 1
2.4%
141 1
2.4%
162 1
2.4%
175 1
2.4%
234 1
2.4%
ValueCountFrequency (%)
2799 1
2.4%
2728 1
2.4%
2702 1
2.4%
2612 1
2.4%
2604 1
2.4%
2461 1
2.4%
2418 1
2.4%
2311 1
2.4%
2245 1
2.4%
2150 1
2.4%

재임용사무직원
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224.73171
Minimum11
Maximum1594
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:42.377218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile24
Q149
median82
Q3166
95-th percentile1028
Maximum1594
Range1583
Interquartile range (IQR)117

Descriptive statistics

Standard deviation358.86516
Coefficient of variation (CV)1.5968604
Kurtosis5.780808
Mean224.73171
Median Absolute Deviation (MAD)38
Skewness2.4904951
Sum9214
Variance128784.2
MonotonicityNot monotonic
2023-12-12T23:57:42.500555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
54 2
 
4.9%
82 2
 
4.9%
44 2
 
4.9%
166 2
 
4.9%
83 2
 
4.9%
75 2
 
4.9%
38 1
 
2.4%
393 1
 
2.4%
126 1
 
2.4%
219 1
 
2.4%
Other values (25) 25
61.0%
ValueCountFrequency (%)
11 1
2.4%
13 1
2.4%
24 1
2.4%
29 1
2.4%
32 1
2.4%
38 1
2.4%
42 1
2.4%
44 2
4.9%
46 1
2.4%
49 1
2.4%
ValueCountFrequency (%)
1594 1
2.4%
1174 1
2.4%
1028 1
2.4%
963 1
2.4%
754 1
2.4%
499 1
2.4%
393 1
2.4%
240 1
2.4%
226 1
2.4%
219 1
2.4%

공무원군인교원
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean983.97561
Minimum169
Maximum5206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:42.626409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum169
5-th percentile368
Q1485
median862
Q31115
95-th percentile1918
Maximum5206
Range5037
Interquartile range (IQR)630

Descriptive statistics

Standard deviation837.71787
Coefficient of variation (CV)0.8513604
Kurtosis15.909116
Mean983.97561
Median Absolute Deviation (MAD)355
Skewness3.4420709
Sum40343
Variance701771.22
MonotonicityNot monotonic
2023-12-12T23:57:42.763457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
169 1
 
2.4%
1099 1
 
2.4%
485 1
 
2.4%
589 1
 
2.4%
548 1
 
2.4%
552 1
 
2.4%
432 1
 
2.4%
1897 1
 
2.4%
854 1
 
2.4%
2282 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
169 1
2.4%
301 1
2.4%
368 1
2.4%
382 1
2.4%
388 1
2.4%
410 1
2.4%
412 1
2.4%
427 1
2.4%
432 1
2.4%
480 1
2.4%
ValueCountFrequency (%)
5206 1
2.4%
2282 1
2.4%
1918 1
2.4%
1897 1
2.4%
1831 1
2.4%
1676 1
2.4%
1317 1
2.4%
1246 1
2.4%
1217 1
2.4%
1125 1
2.4%

공무원군인사무직원
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean340.17073
Minimum36
Maximum1701
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T23:57:42.888304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile144
Q1210
median260
Q3388
95-th percentile720
Maximum1701
Range1665
Interquartile range (IQR)178

Descriptive statistics

Standard deviation271.77315
Coefficient of variation (CV)0.79893161
Kurtosis15.834593
Mean340.17073
Median Absolute Deviation (MAD)60
Skewness3.5359273
Sum13947
Variance73860.645
MonotonicityNot monotonic
2023-12-12T23:57:43.007542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
210 2
 
4.9%
215 2
 
4.9%
237 2
 
4.9%
338 1
 
2.4%
260 1
 
2.4%
247 1
 
2.4%
457 1
 
2.4%
305 1
 
2.4%
917 1
 
2.4%
409 1
 
2.4%
Other values (28) 28
68.3%
ValueCountFrequency (%)
36 1
2.4%
115 1
2.4%
144 1
2.4%
182 1
2.4%
183 1
2.4%
185 1
2.4%
200 1
2.4%
202 1
2.4%
203 1
2.4%
206 1
2.4%
ValueCountFrequency (%)
1701 1
2.4%
917 1
2.4%
720 1
2.4%
529 1
2.4%
502 1
2.4%
495 1
2.4%
478 1
2.4%
457 1
2.4%
446 1
2.4%
409 1
2.4%

Interactions

2023-12-12T23:57:40.360548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.031950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.672943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.302140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.047056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.742468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.392040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.465308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.137581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.773945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.400381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.143420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.835522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.497752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.573994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.226618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.868084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.519416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.258129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.922913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.618077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.659222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.316822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.948652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.623199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.366140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.009360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.717729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.748907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.397384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.030859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.729610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.444100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.099143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.792706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.839479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.489840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.124974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.837749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.549598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.209907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.185889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.925743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:36.580064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.205830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:37.943861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:38.649733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:39.307304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:57:40.272081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:57:43.107033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도사립학교교원사립학교사무직원재임용교원재임용사무직원공무원군인교원공무원군인사무직원
연도1.0000.7380.7390.9400.5760.6940.674
사립학교교원0.7381.0000.8550.7640.6500.4800.624
사립학교사무직원0.7390.8551.0000.6390.9320.0890.627
재임용교원0.9400.7640.6391.0000.6970.7690.779
재임용사무직원0.5760.6500.9320.6971.0000.0000.685
공무원군인교원0.6940.4800.0890.7690.0001.0000.921
공무원군인사무직원0.6740.6240.6270.7790.6850.9211.000
2023-12-12T23:57:43.212679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도사립학교교원사립학교사무직원재임용교원재임용사무직원공무원군인교원공무원군인사무직원
연도1.0000.7030.9210.7510.824-0.4180.514
사립학교교원0.7031.0000.8140.7280.7810.0950.759
사립학교사무직원0.9210.8141.0000.6980.804-0.2610.580
재임용교원0.7510.7280.6981.0000.848-0.2310.660
재임용사무직원0.8240.7810.8040.8481.000-0.1780.652
공무원군인교원-0.4180.095-0.261-0.231-0.1781.0000.375
공무원군인사무직원0.5140.7590.5800.6600.6520.3751.000

Missing values

2023-12-12T23:57:41.047808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:57:41.159317image/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

연도사립학교교원사립학교사무직원재임용교원재임용사무직원공무원군인교원공무원군인사무직원
01982238438083816936
11983683110475565206720
2198446592762541831291
31985624143412821918308
41986448133234111676277
51987431110238441115200
61988569188175131217322
71989489142258831317214
81990420160241421061215
9199151315835183933237
연도사립학교교원사립학교사무직원재임용교원재임용사무직원공무원군인교원공무원군인사무직원
31201391347621502191099409
3220149004832245240865307
3320159814452612226862338
34201690870927283936081701
3520179195962799499725478
3620189045362702754607388
37201999366926041174558446
38202014256992461963494502
39202198771923111028480529
402022781115024181594388495