Overview

Dataset statistics

Number of variables12
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory110.7 B

Variable types

Numeric9
Categorical3

Dataset

Description특수교육 보조인력 운영 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=U0Q2SGNLA8YKII5FWRSE25278882&infSeq=1

Alerts

공공근로인원수(명) has constant value ""Constant
기준년도 is highly overall correlated with 유급자치단체인원수(명)High correlation
총계(명) is highly overall correlated with 유급전체인원수(명) and 3 other fieldsHigh correlation
유급전체인원수(명) is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
유급국고지방비인원수(명) is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
유급자치단체인원수(명) is highly overall correlated with 기준년도High correlation
사회복무요원인원수(명) is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
무급전체인원수(명) is highly overall correlated with 무급자원봉사인원수(명) and 1 other fieldsHigh correlation
무급자원봉사인원수(명) is highly overall correlated with 무급전체인원수(명) and 1 other fieldsHigh correlation
학교유형명 is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
무급기타인원수(명) is highly overall correlated with 무급전체인원수(명) and 1 other fieldsHigh correlation
무급기타인원수(명) is highly imbalanced (69.1%)Imbalance
유급전체인원수(명) has 2 (5.6%) zerosZeros
유급국고지방비인원수(명) has 3 (8.3%) zerosZeros
유급자치단체인원수(명) has 25 (69.4%) zerosZeros
유급기타인원수(명) has 26 (72.2%) zerosZeros
사회복무요원인원수(명) has 1 (2.8%) zerosZeros
무급전체인원수(명) has 26 (72.2%) zerosZeros
무급자원봉사인원수(명) has 27 (75.0%) zerosZeros

Reproduction

Analysis started2023-12-10 21:00:55.955857
Analysis finished2023-12-10 21:01:05.041700
Duration9.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:05.132707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014.75
median2017.5
Q32020.25
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.5010203
Coefficient of variation (CV)0.001735326
Kurtosis-1.217232
Mean2017.5
Median Absolute Deviation (MAD)3
Skewness0
Sum72630
Variance12.257143
MonotonicityDecreasing
2023-12-11T06:01:05.286061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2023 3
8.3%
2022 3
8.3%
2021 3
8.3%
2020 3
8.3%
2019 3
8.3%
2018 3
8.3%
2017 3
8.3%
2016 3
8.3%
2015 3
8.3%
2014 3
8.3%
Other values (2) 6
16.7%
ValueCountFrequency (%)
2012 3
8.3%
2013 3
8.3%
2014 3
8.3%
2015 3
8.3%
2016 3
8.3%
2017 3
8.3%
2018 3
8.3%
2019 3
8.3%
2020 3
8.3%
2021 3
8.3%
ValueCountFrequency (%)
2023 3
8.3%
2022 3
8.3%
2021 3
8.3%
2020 3
8.3%
2019 3
8.3%
2018 3
8.3%
2017 3
8.3%
2016 3
8.3%
2015 3
8.3%
2014 3
8.3%

학교유형명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
일반학급
12 
특수학교
12 
특수학급
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반학급
2nd row특수학교
3rd row특수학급
4th row일반학급
5th row특수학교

Common Values

ValueCountFrequency (%)
일반학급 12
33.3%
특수학교 12
33.3%
특수학급 12
33.3%

Length

2023-12-11T06:01:05.458760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:05.588080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반학급 12
33.3%
특수학교 12
33.3%
특수학급 12
33.3%

총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean656.97222
Minimum2
Maximum2006
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:05.721864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7
Q121.75
median530
Q31339.75
95-th percentile1825.75
Maximum2006
Range2004
Interquartile range (IQR)1318

Descriptive statistics

Standard deviation647.02292
Coefficient of variation (CV)0.98485582
Kurtosis-0.90386432
Mean656.97222
Median Absolute Deviation (MAD)512.5
Skewness0.66217221
Sum23651
Variance418638.66
MonotonicityNot monotonic
2023-12-11T06:01:05.892060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
18 2
 
5.6%
7 2
 
5.6%
689 2
 
5.6%
23 2
 
5.6%
1338 1
 
2.8%
398 1
 
2.8%
1347 1
 
2.8%
17 1
 
2.8%
483 1
 
2.8%
347 1
 
2.8%
Other values (22) 22
61.1%
ValueCountFrequency (%)
2 1
2.8%
7 2
5.6%
11 1
2.8%
13 1
2.8%
14 1
2.8%
17 1
2.8%
18 2
5.6%
23 2
5.6%
35 1
2.8%
194 1
2.8%
ValueCountFrequency (%)
2006 1
2.8%
1837 1
2.8%
1822 1
2.8%
1729 1
2.8%
1472 1
2.8%
1401 1
2.8%
1354 1
2.8%
1347 1
2.8%
1345 1
2.8%
1338 1
2.8%

유급전체인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean372
Minimum0
Maximum935
Zeros2
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:06.054437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75
Q118.25
median268.5
Q3839
95-th percentile875.25
Maximum935
Range935
Interquartile range (IQR)820.75

Descriptive statistics

Standard deviation366.60902
Coefficient of variation (CV)0.98550811
Kurtosis-1.5396948
Mean372
Median Absolute Deviation (MAD)260.5
Skewness0.50193834
Sum13392
Variance134402.17
MonotonicityNot monotonic
2023-12-11T06:01:06.198064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 2
 
5.6%
874 2
 
5.6%
8 2
 
5.6%
20 2
 
5.6%
839 2
 
5.6%
1 1
 
2.8%
228 1
 
2.8%
835 1
 
2.8%
130 1
 
2.8%
23 1
 
2.8%
Other values (21) 21
58.3%
ValueCountFrequency (%)
0 2
5.6%
1 1
2.8%
2 1
2.8%
7 1
2.8%
8 2
5.6%
12 1
2.8%
13 1
2.8%
20 2
5.6%
23 1
2.8%
130 1
2.8%
ValueCountFrequency (%)
935 1
2.8%
876 1
2.8%
875 1
2.8%
874 2
5.6%
873 1
2.8%
855 1
2.8%
847 1
2.8%
839 2
5.6%
835 1
2.8%
828 1
2.8%

유급국고지방비인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean345.22222
Minimum0
Maximum875
Zeros3
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:06.359528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median252
Q3726.25
95-th percentile873.5
Maximum875
Range875
Interquartile range (IQR)718.25

Descriptive statistics

Standard deviation347.34348
Coefficient of variation (CV)1.0061446
Kurtosis-1.4024528
Mean345.22222
Median Absolute Deviation (MAD)247.5
Skewness0.53752555
Sum12428
Variance120647.49
MonotonicityNot monotonic
2023-12-11T06:01:06.516097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 3
 
8.3%
8 3
 
8.3%
2 2
 
5.6%
875 2
 
5.6%
618 1
 
2.8%
130 1
 
2.8%
710 1
 
2.8%
18 1
 
2.8%
868 1
 
2.8%
839 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
0 3
8.3%
1 1
 
2.8%
2 2
5.6%
7 1
 
2.8%
8 3
8.3%
12 1
 
2.8%
18 1
 
2.8%
20 1
 
2.8%
130 1
 
2.8%
212 1
 
2.8%
ValueCountFrequency (%)
875 2
5.6%
873 1
2.8%
872 1
2.8%
868 1
2.8%
847 1
2.8%
839 1
2.8%
827 1
2.8%
775 1
2.8%
710 1
2.8%
649 1
2.8%

유급자치단체인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.861111
Minimum0
Maximum217
Zeros25
Zeros (%)69.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:06.677192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.75
95-th percentile162.25
Maximum217
Range217
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation54.730588
Coefficient of variation (CV)2.6235701
Kurtosis8.5069357
Mean20.861111
Median Absolute Deviation (MAD)0
Skewness3.0438763
Sum751
Variance2995.4373
MonotonicityNot monotonic
2023-12-11T06:01:06.814562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 25
69.4%
33 1
 
2.8%
62 1
 
2.8%
5 1
 
2.8%
13 1
 
2.8%
214 1
 
2.8%
8 1
 
2.8%
31 1
 
2.8%
2 1
 
2.8%
145 1
 
2.8%
Other values (2) 2
 
5.6%
ValueCountFrequency (%)
0 25
69.4%
2 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%
13 1
 
2.8%
21 1
 
2.8%
31 1
 
2.8%
33 1
 
2.8%
62 1
 
2.8%
145 1
 
2.8%
ValueCountFrequency (%)
217 1
2.8%
214 1
2.8%
145 1
2.8%
62 1
2.8%
33 1
2.8%
31 1
2.8%
21 1
2.8%
13 1
2.8%
8 1
2.8%
5 1
2.8%

유급기타인원수(명)
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9166667
Minimum0
Maximum142
Zeros26
Zeros (%)72.2%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:06.941195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile20.25
Maximum142
Range142
Interquartile range (IQR)1

Descriptive statistics

Standard deviation24.238547
Coefficient of variation (CV)4.0966558
Kurtosis30.509744
Mean5.9166667
Median Absolute Deviation (MAD)0
Skewness5.4007366
Sum213
Variance587.50714
MonotonicityNot monotonic
2023-12-11T06:01:07.081652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 26
72.2%
1 4
 
11.1%
2 1
 
2.8%
3 1
 
2.8%
11 1
 
2.8%
15 1
 
2.8%
36 1
 
2.8%
142 1
 
2.8%
ValueCountFrequency (%)
0 26
72.2%
1 4
 
11.1%
2 1
 
2.8%
3 1
 
2.8%
11 1
 
2.8%
15 1
 
2.8%
36 1
 
2.8%
142 1
 
2.8%
ValueCountFrequency (%)
142 1
 
2.8%
36 1
 
2.8%
15 1
 
2.8%
11 1
 
2.8%
3 1
 
2.8%
2 1
 
2.8%
1 4
 
11.1%
0 26
72.2%

공공근로인원수(명)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 36
100.0%

Length

2023-12-11T06:01:07.235393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:07.328830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
100.0%

사회복무요원인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.19444
Minimum0
Maximum1131
Zeros1
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:07.424511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.75
Q19
median264.5
Q3465
95-th percentile948
Maximum1131
Range1131
Interquartile range (IQR)456

Descriptive statistics

Standard deviation317.34423
Coefficient of variation (CV)1.03981
Kurtosis0.23956078
Mean305.19444
Median Absolute Deviation (MAD)254
Skewness0.99498353
Sum10987
Variance100707.36
MonotonicityNot monotonic
2023-12-11T06:01:07.543698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
6 4
 
11.1%
10 2
 
5.6%
948 2
 
5.6%
342 2
 
5.6%
112 1
 
2.8%
165 1
 
2.8%
500 1
 
2.8%
4 1
 
2.8%
178 1
 
2.8%
458 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
0 1
 
2.8%
2 1
 
2.8%
3 1
 
2.8%
4 1
 
2.8%
5 1
 
2.8%
6 4
11.1%
10 2
5.6%
11 1
 
2.8%
64 1
 
2.8%
112 1
 
2.8%
ValueCountFrequency (%)
1131 1
2.8%
948 2
5.6%
853 1
2.8%
729 1
2.8%
633 1
2.8%
562 1
2.8%
500 1
2.8%
486 1
2.8%
458 1
2.8%
398 1
2.8%

무급전체인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8888889
Minimum0
Maximum38
Zeros26
Zeros (%)72.2%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:07.657734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.75
95-th percentile23
Maximum38
Range38
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation8.8890873
Coefficient of variation (CV)2.2857653
Kurtosis6.9382002
Mean3.8888889
Median Absolute Deviation (MAD)0
Skewness2.6765081
Sum140
Variance79.015873
MonotonicityNot monotonic
2023-12-11T06:01:07.782347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 26
72.2%
5 2
 
5.6%
1 1
 
2.8%
15 1
 
2.8%
38 1
 
2.8%
16 1
 
2.8%
29 1
 
2.8%
6 1
 
2.8%
21 1
 
2.8%
4 1
 
2.8%
ValueCountFrequency (%)
0 26
72.2%
1 1
 
2.8%
4 1
 
2.8%
5 2
 
5.6%
6 1
 
2.8%
15 1
 
2.8%
16 1
 
2.8%
21 1
 
2.8%
29 1
 
2.8%
38 1
 
2.8%
ValueCountFrequency (%)
38 1
 
2.8%
29 1
 
2.8%
21 1
 
2.8%
16 1
 
2.8%
15 1
 
2.8%
6 1
 
2.8%
5 2
 
5.6%
4 1
 
2.8%
1 1
 
2.8%
0 26
72.2%

무급자원봉사인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2222222
Minimum0
Maximum38
Zeros27
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T06:01:07.895578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile19.75
Maximum38
Range38
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation8.4010581
Coefficient of variation (CV)2.6072249
Kurtosis9.6994923
Mean3.2222222
Median Absolute Deviation (MAD)0
Skewness3.1160279
Sum116
Variance70.577778
MonotonicityNot monotonic
2023-12-11T06:01:08.036396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 27
75.0%
5 2
 
5.6%
1 1
 
2.8%
38 1
 
2.8%
16 1
 
2.8%
28 1
 
2.8%
2 1
 
2.8%
17 1
 
2.8%
4 1
 
2.8%
ValueCountFrequency (%)
0 27
75.0%
1 1
 
2.8%
2 1
 
2.8%
4 1
 
2.8%
5 2
 
5.6%
16 1
 
2.8%
17 1
 
2.8%
28 1
 
2.8%
38 1
 
2.8%
ValueCountFrequency (%)
38 1
 
2.8%
28 1
 
2.8%
17 1
 
2.8%
16 1
 
2.8%
5 2
 
5.6%
4 1
 
2.8%
2 1
 
2.8%
1 1
 
2.8%
0 27
75.0%

무급기타인원수(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
33 
4
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 33
91.7%
4 2
 
5.6%
1 1
 
2.8%

Length

2023-12-11T06:01:08.156769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:08.254252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 33
91.7%
4 2
 
5.6%
1 1
 
2.8%

Interactions

2023-12-11T06:01:03.563966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.422975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.337473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.210350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.958511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.677327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.379869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.382669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.587210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.658965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.537125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.436544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.310172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.051566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.753486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.538731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.469607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.694783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.790043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.686610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.548671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.397860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.133794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.825338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.659319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.551224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.807266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.880972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.781109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.636911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.475250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.206249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.888383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.752403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.622051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.898936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.973791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.859756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.729138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.545697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.273378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.961710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.865129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.702326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.984184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:04.071338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:56.951421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.814312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.621242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.363938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.036922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.955560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.800730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.067960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:04.180182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.062374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.907213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.715727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.449431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.116823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.061085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.181560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.157670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:04.347085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.151002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.995453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.793817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.519695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.185289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.170889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.314825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.275827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:04.494090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:57.244358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.099146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:58.875253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:00:59.600975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:00.271139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:01.297470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:02.463219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:03.419369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:01:08.323999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도학교유형명총계(명)유급전체인원수(명)유급국고지방비인원수(명)유급자치단체인원수(명)유급기타인원수(명)사회복무요원인원수(명)무급전체인원수(명)무급자원봉사인원수(명)무급기타인원수(명)
기준년도1.0000.0000.0000.0000.0000.4910.4020.0000.4950.6520.357
학교유형명0.0001.0000.9941.0000.9350.2490.0560.8780.0000.0000.460
총계(명)0.0000.9941.0000.8950.8370.7710.3890.9450.0780.0000.575
유급전체인원수(명)0.0001.0000.8951.0000.8520.1020.4830.8120.1200.0630.359
유급국고지방비인원수(명)0.0000.9350.8370.8521.0000.7840.0000.7460.0000.0700.361
유급자치단체인원수(명)0.4910.2490.7710.1020.7841.0000.2970.7940.6070.8580.445
유급기타인원수(명)0.4020.0560.3890.4830.0000.2971.0000.0000.5960.2990.426
사회복무요원인원수(명)0.0000.8780.9450.8120.7460.7940.0001.0000.3580.0000.000
무급전체인원수(명)0.4950.0000.0780.1200.0000.6070.5960.3581.0000.9610.880
무급자원봉사인원수(명)0.6520.0000.0000.0630.0700.8580.2990.0000.9611.0000.749
무급기타인원수(명)0.3570.4600.5750.3590.3610.4450.4260.0000.8800.7491.000
2023-12-11T06:01:08.461780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
무급기타인원수(명)학교유형명
무급기타인원수(명)1.0000.175
학교유형명0.1751.000
2023-12-11T06:01:08.781711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도총계(명)유급전체인원수(명)유급국고지방비인원수(명)유급자치단체인원수(명)유급기타인원수(명)사회복무요원인원수(명)무급전체인원수(명)무급자원봉사인원수(명)학교유형명무급기타인원수(명)
기준년도1.0000.0910.0070.148-0.569-0.1520.238-0.158-0.2360.0000.244
총계(명)0.0911.0000.9760.9630.1960.4090.9520.3410.2430.8160.266
유급전체인원수(명)0.0070.9761.0000.9550.2900.4720.9130.3900.3030.9530.138
유급국고지방비인원수(명)0.1480.9630.9551.0000.1370.3370.9290.3170.2250.8930.235
유급자치단체인원수(명)-0.5690.1960.2900.1371.0000.3120.0490.3960.4400.1790.361
유급기타인원수(명)-0.1520.4090.4720.3370.3121.0000.4070.3140.2190.0120.410
사회복무요원인원수(명)0.2380.9520.9130.9290.0490.4071.0000.2890.1930.7200.000
무급전체인원수(명)-0.1580.3410.3900.3170.3960.3140.2891.0000.9260.0000.817
무급자원봉사인원수(명)-0.2360.2430.3030.2250.4400.2190.1930.9261.0000.0000.726
학교유형명0.0000.8160.9530.8930.1790.0120.7200.0000.0001.0000.175
무급기타인원수(명)0.2440.2660.1380.2350.3610.4100.0000.8170.7260.1751.000

Missing values

2023-12-11T06:01:04.719407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:01:04.948542image/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

기준년도학교유형명총계(명)유급전체인원수(명)유급국고지방비인원수(명)유급자치단체인원수(명)유급기타인원수(명)공공근로인원수(명)사회복무요원인원수(명)무급전체인원수(명)무급자원봉사인원수(명)무급기타인원수(명)
02023일반학급2000002000
12023특수학교658269269000389000
22023특수학급20068758750001131000
32022일반학급110000011000
42022특수학교577268268000309000
52022특수학급1822873872010948110
62021일반학급7110006000
72021특수학교628286286000342000
82021특수학급18378748730109481500
92020일반학급7220005000
기준년도학교유형명총계(명)유급전체인원수(명)유급국고지방비인원수(명)유급자치단체인원수(명)유급기타인원수(명)공공근로인원수(명)사회복무요원인원수(명)무급전체인원수(명)무급자원봉사인원수(명)무급기타인원수(명)
262015특수학급1338874649214110458624
272014일반학급1812120006000
282014특수학교3472352128150112000
292014특수학급13549358683136039821174
302013일반학급35201820010550
312013특수학교267142001420125000
322013특수학급134585571014500486440
332012일반학급2323221000000
342012특수학교19413013000064000
352012특수학급117783561821700342000