Overview

Dataset statistics

Number of variables11
Number of observations32
Missing cells34
Missing cells (%)9.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory102.1 B

Variable types

Text1
Numeric9
Unsupported1

Dataset

Description사립학교교직원연금공단 신분변동 현황과 관련된 데이터로 신분변동내용,접수 건수,비고(특이사항) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15081260/fileData.do

Alerts

유치원 is highly overall correlated with 초등학교 and 7 other fieldsHigh correlation
초등학교 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
중학교 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
고등학교 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
전문대학 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
대학교 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
특수학교 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
법인 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
접수건수 is highly overall correlated with 유치원 and 7 other fieldsHigh correlation
초등학교 has 1 (3.1%) missing valuesMissing
법인 has 1 (3.1%) missing valuesMissing
비고 has 32 (100.0%) missing valuesMissing
신분변동 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported
유치원 has 3 (9.4%) zerosZeros
초등학교 has 10 (31.2%) zerosZeros
중학교 has 7 (21.9%) zerosZeros
고등학교 has 6 (18.8%) zerosZeros
전문대학 has 5 (15.6%) zerosZeros
대학교 has 3 (9.4%) zerosZeros
특수학교 has 11 (34.4%) zerosZeros
법인 has 12 (37.5%) zerosZeros
접수건수 has 2 (6.2%) zerosZeros

Reproduction

Analysis started2023-12-12 18:15:57.927912
Analysis finished2023-12-12 18:16:08.596526
Duration10.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신분변동
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T03:16:08.786961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.03125
Min length2

Characters and Unicode

Total characters161
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row미고지정정
2nd row병역복무경력승인
3rd row병역복무경력정정
4th row병역복무경력취소
5th row복직
ValueCountFrequency (%)
미고지정정 1
 
3.1%
병역복무경력승인 1
 
3.1%
합산취소 1
 
3.1%
합산정정 1
 
3.1%
합산승인 1
 
3.1%
학교기관정정 1
 
3.1%
학교기관정원 1
 
3.1%
학교기관사업자번호 1
 
3.1%
학교기관등록 1
 
3.1%
학교기관기관장 1
 
3.1%
Other values (22) 22
68.8%
2023-12-13T03:16:09.222124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 13
 
8.1%
소 9
 
5.6%
신 6
 
3.7%
관 6
 
3.7%
기 6
 
3.7%
계 6
 
3.7%
산 6
 
3.7%
연 5
 
3.1%
취 5
 
3.1%
직 5
 
3.1%
Other values (50) 94
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 13
 
8.1%
소 9
 
5.6%
신 6
 
3.7%
관 6
 
3.7%
기 6
 
3.7%
계 6
 
3.7%
산 6
 
3.7%
연 5
 
3.1%
취 5
 
3.1%
직 5
 
3.1%
Other values (50) 94
58.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 13
 
8.1%
소 9
 
5.6%
신 6
 
3.7%
관 6
 
3.7%
기 6
 
3.7%
계 6
 
3.7%
산 6
 
3.7%
연 5
 
3.1%
취 5
 
3.1%
직 5
 
3.1%
Other values (50) 94
58.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 13
 
8.1%
소 9
 
5.6%
신 6
 
3.7%
관 6
 
3.7%
기 6
 
3.7%
계 6
 
3.7%
산 6
 
3.7%
연 5
 
3.1%
취 5
 
3.1%
직 5
 
3.1%
Other values (50) 94
58.4%

유치원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean747.625
Minimum0
Maximum7241
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:09.366616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.75
median27.5
Q3236.75
95-th percentile5964.45
Maximum7241
Range7241
Interquartile range (IQR)231

Descriptive statistics

Standard deviation1928.4462
Coefficient of variation (CV)2.5794298
Kurtosis7.6303876
Mean747.625
Median Absolute Deviation (MAD)26.5
Skewness2.9357308
Sum23924
Variance3718904.8
MonotonicityNot monotonic
2023-12-13T03:16:09.515215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 3
 
9.4%
1 2
 
6.2%
7241 2
 
6.2%
9 2
 
6.2%
30 2
 
6.2%
25 1
 
3.1%
7 1
 
3.1%
194 1
 
3.1%
18 1
 
3.1%
328 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0 3
9.4%
1 2
6.2%
2 1
 
3.1%
4 1
 
3.1%
5 1
 
3.1%
6 1
 
3.1%
7 1
 
3.1%
8 1
 
3.1%
9 2
6.2%
13 1
 
3.1%
ValueCountFrequency (%)
7241 2
6.2%
4920 1
3.1%
1628 1
3.1%
979 1
3.1%
441 1
3.1%
328 1
3.1%
266 1
3.1%
227 1
3.1%
194 1
3.1%
140 1
3.1%

초등학교
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct15
Distinct (%)48.4%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean24.193548
Minimum0
Maximum265
Zeros10
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:09.666680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile105
Maximum265
Range265
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation53.7596
Coefficient of variation (CV)2.2220635
Kurtosis13.546664
Mean24.193548
Median Absolute Deviation (MAD)2
Skewness3.4247628
Sum750
Variance2890.0946
MonotonicityNot monotonic
2023-12-13T03:16:09.793387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 10
31.2%
1 4
 
12.5%
2 2
 
6.2%
105 2
 
6.2%
8 2
 
6.2%
3 2
 
6.2%
12 1
 
3.1%
20 1
 
3.1%
54 1
 
3.1%
265 1
 
3.1%
Other values (5) 5
15.6%
ValueCountFrequency (%)
0 10
31.2%
1 4
 
12.5%
2 2
 
6.2%
3 2
 
6.2%
5 1
 
3.1%
6 1
 
3.1%
8 2
 
6.2%
12 1
 
3.1%
17 1
 
3.1%
20 1
 
3.1%
ValueCountFrequency (%)
265 1
3.1%
105 2
6.2%
69 1
3.1%
62 1
3.1%
54 1
3.1%
20 1
3.1%
17 1
3.1%
12 1
3.1%
8 2
6.2%
6 1
3.1%

중학교
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean275.21875
Minimum0
Maximum5177
Zeros7
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:10.258876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10.5
Q3140
95-th percentile671.25
Maximum5177
Range5177
Interquartile range (IQR)139

Descriptive statistics

Standard deviation919.8599
Coefficient of variation (CV)3.3422865
Kurtosis28.271795
Mean275.21875
Median Absolute Deviation (MAD)10.5
Skewness5.1985496
Sum8807
Variance846142.24
MonotonicityNot monotonic
2023-12-13T03:16:10.398247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 7
21.9%
4 3
 
9.4%
1 2
 
6.2%
507 2
 
6.2%
2 2
 
6.2%
62 1
 
3.1%
8 1
 
3.1%
525 1
 
3.1%
44 1
 
3.1%
5 1
 
3.1%
Other values (11) 11
34.4%
ValueCountFrequency (%)
0 7
21.9%
1 2
 
6.2%
2 2
 
6.2%
4 3
9.4%
5 1
 
3.1%
8 1
 
3.1%
13 1
 
3.1%
21 1
 
3.1%
35 1
 
3.1%
41 1
 
3.1%
ValueCountFrequency (%)
5177 1
3.1%
850 1
3.1%
525 1
3.1%
516 1
3.1%
507 2
6.2%
151 1
3.1%
146 1
3.1%
138 1
3.1%
62 1
3.1%
44 1
3.1%

고등학교
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean865.875
Minimum0
Maximum19136
Zeros6
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:10.527602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.75
median25.5
Q3279
95-th percentile1442
Maximum19136
Range19136
Interquartile range (IQR)277.25

Descriptive statistics

Standard deviation3368.4562
Coefficient of variation (CV)3.8902338
Kurtosis30.576213
Mean865.875
Median Absolute Deviation (MAD)25.5
Skewness5.4784635
Sum27708
Variance11346497
MonotonicityNot monotonic
2023-12-13T03:16:10.664503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 6
18.8%
8 2
 
6.2%
11 2
 
6.2%
1442 2
 
6.2%
1 2
 
6.2%
87 1
 
3.1%
1414 1
 
3.1%
12 1
 
3.1%
120 1
 
3.1%
21 1
 
3.1%
Other values (13) 13
40.6%
ValueCountFrequency (%)
0 6
18.8%
1 2
 
6.2%
2 1
 
3.1%
8 2
 
6.2%
11 2
 
6.2%
12 1
 
3.1%
13 1
 
3.1%
21 1
 
3.1%
30 1
 
3.1%
39 1
 
3.1%
ValueCountFrequency (%)
19136 1
3.1%
1442 2
6.2%
1414 1
3.1%
1298 1
3.1%
1070 1
3.1%
472 1
3.1%
453 1
3.1%
221 1
3.1%
164 1
3.1%
152 1
3.1%

전문대학
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.71875
Minimum0
Maximum1163
Zeros5
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:10.788441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.75
median12.5
Q3151.5
95-th percentile892.4
Maximum1163
Range1163
Interquartile range (IQR)149.75

Descriptive statistics

Standard deviation299.06966
Coefficient of variation (CV)2.140512
Kurtosis7.8420576
Mean139.71875
Median Absolute Deviation (MAD)12.5
Skewness2.8889691
Sum4471
Variance89442.66
MonotonicityNot monotonic
2023-12-13T03:16:10.908429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 5
15.6%
1 3
 
9.4%
15 2
 
6.2%
2 2
 
6.2%
6 2
 
6.2%
1163 2
 
6.2%
230 1
 
3.1%
169 1
 
3.1%
9 1
 
3.1%
10 1
 
3.1%
Other values (12) 12
37.5%
ValueCountFrequency (%)
0 5
15.6%
1 3
9.4%
2 2
 
6.2%
3 1
 
3.1%
6 2
 
6.2%
8 1
 
3.1%
9 1
 
3.1%
10 1
 
3.1%
15 2
 
6.2%
22 1
 
3.1%
ValueCountFrequency (%)
1163 2
6.2%
671 1
3.1%
254 1
3.1%
230 1
3.1%
169 1
3.1%
167 1
3.1%
162 1
3.1%
148 1
3.1%
105 1
3.1%
76 1
3.1%

대학교
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2432.3438
Minimum0
Maximum23454
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:11.055631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.25
median95
Q31458.5
95-th percentile16249.55
Maximum23454
Range23454
Interquartile range (IQR)1444.25

Descriptive statistics

Standard deviation5963.9102
Coefficient of variation (CV)2.4519191
Kurtosis8.9453554
Mean2432.3438
Median Absolute Deviation (MAD)93.5
Skewness3.0734812
Sum77835
Variance35568225
MonotonicityNot monotonic
2023-12-13T03:16:11.219063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 3
 
9.4%
23454 2
 
6.2%
733 1
 
3.1%
2647 1
 
3.1%
7908 1
 
3.1%
113 1
 
3.1%
53 1
 
3.1%
2128 1
 
3.1%
6 1
 
3.1%
26 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0 3
9.4%
1 1
 
3.1%
2 1
 
3.1%
5 1
 
3.1%
6 1
 
3.1%
12 1
 
3.1%
15 1
 
3.1%
26 1
 
3.1%
37 1
 
3.1%
53 1
 
3.1%
ValueCountFrequency (%)
23454 2
6.2%
10355 1
3.1%
7908 1
3.1%
2647 1
3.1%
2128 1
3.1%
2073 1
3.1%
1679 1
3.1%
1385 1
3.1%
858 1
3.1%
733 1
3.1%

특수학교
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.0625
Minimum0
Maximum802
Zeros11
Zeros (%)34.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:11.348548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q321.5
95-th percentile177
Maximum802
Range802
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation147.04398
Coefficient of variation (CV)2.8796862
Kurtosis23.386216
Mean51.0625
Median Absolute Deviation (MAD)1
Skewness4.6158496
Sum1634
Variance21621.931
MonotonicityNot monotonic
2023-12-13T03:16:11.487672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 11
34.4%
1 6
18.8%
177 2
 
6.2%
2 2
 
6.2%
13 1
 
3.1%
36 1
 
3.1%
151 1
 
3.1%
802 1
 
3.1%
10 1
 
3.1%
38 1
 
3.1%
Other values (5) 5
15.6%
ValueCountFrequency (%)
0 11
34.4%
1 6
18.8%
2 2
 
6.2%
10 1
 
3.1%
12 1
 
3.1%
13 1
 
3.1%
19 1
 
3.1%
20 1
 
3.1%
26 1
 
3.1%
36 1
 
3.1%
ValueCountFrequency (%)
802 1
3.1%
177 2
6.2%
151 1
3.1%
143 1
3.1%
38 1
3.1%
36 1
3.1%
26 1
3.1%
20 1
3.1%
19 1
3.1%
13 1
3.1%

법인
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct13
Distinct (%)41.9%
Missing1
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean13.354839
Minimum0
Maximum170
Zeros12
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:11.640161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37.5
95-th percentile70.5
Maximum170
Range170
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation34.22236
Coefficient of variation (CV)2.5625438
Kurtosis15.307958
Mean13.354839
Median Absolute Deviation (MAD)1
Skewness3.7384162
Sum414
Variance1171.1699
MonotonicityNot monotonic
2023-12-13T03:16:11.787231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 12
37.5%
1 8
25.0%
22 1
 
3.1%
10 1
 
3.1%
170 1
 
3.1%
27 1
 
3.1%
6 1
 
3.1%
61 1
 
3.1%
80 1
 
3.1%
2 1
 
3.1%
Other values (3) 3
 
9.4%
ValueCountFrequency (%)
0 12
37.5%
1 8
25.0%
2 1
 
3.1%
6 1
 
3.1%
7 1
 
3.1%
8 1
 
3.1%
10 1
 
3.1%
13 1
 
3.1%
22 1
 
3.1%
27 1
 
3.1%
ValueCountFrequency (%)
170 1
3.1%
80 1
3.1%
61 1
3.1%
27 1
3.1%
22 1
3.1%
13 1
3.1%
10 1
3.1%
8 1
3.1%
7 1
3.1%
6 1
3.1%

접수건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4548.2188
Minimum0
Maximum38204
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T03:16:11.914695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q169.25
median226.5
Q32845.75
95-th percentile34125
Maximum38204
Range38204
Interquartile range (IQR)2776.5

Descriptive statistics

Standard deviation10395.46
Coefficient of variation (CV)2.2856113
Kurtosis6.153059
Mean4548.2188
Median Absolute Deviation (MAD)224.5
Skewness2.7055141
Sum145543
Variance1.0806559 × 108
MonotonicityNot monotonic
2023-12-13T03:16:12.060628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2 2
 
6.2%
0 2
 
6.2%
10 2
 
6.2%
1024 1
 
3.1%
3010 1
 
3.1%
10435 1
 
3.1%
167 1
 
3.1%
94 1
 
3.1%
2812 1
 
3.1%
298 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0 2
6.2%
2 2
6.2%
10 2
6.2%
21 1
3.1%
28 1
3.1%
83 1
3.1%
94 1
3.1%
115 1
3.1%
127 1
3.1%
167 1
3.1%
ValueCountFrequency (%)
38204 1
3.1%
34169 1
3.1%
34089 1
3.1%
10435 1
3.1%
7949 1
3.1%
3608 1
3.1%
3010 1
3.1%
2947 1
3.1%
2812 1
3.1%
2305 1
3.1%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

Interactions

2023-12-13T03:16:07.047927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.271621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.337955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.325299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.413785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.702582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.706146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.841130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.972976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.173441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.386969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.452438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.440835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.540561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.810098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.842493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.969684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.085541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.279797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.506418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.551753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.545777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.645057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.904276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.953665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.084725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.193882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.379361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.607927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.651231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.652567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.763289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.005977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.123094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.206986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.305818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.500772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.720268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.761740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.785536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.859693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.127051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.251175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.363151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.435543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.617234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.833935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.876135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.908497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.952622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.233635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.361481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.489023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.556875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.728257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:58.969195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.966153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.007365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.037798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.335559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.469486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.599958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.671408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.847882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.098686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.087508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.192029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.139678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.484334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.595838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.723413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.811057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:07.971170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:15:59.203933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:00.207455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:01.298143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:02.233133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:03.601376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:04.712813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:05.828774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:16:06.917848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:16:12.194310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신분변동유치원초등학교중학교고등학교전문대학대학교특수학교법인접수건수
신분변동1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원1.0001.0000.8210.6821.0000.9920.9890.8210.9700.896
초등학교1.0000.8211.0000.8281.0000.8230.8700.9980.8700.983
중학교1.0000.6820.8281.0001.0000.6990.8140.7140.8140.714
고등학교1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전문대학1.0000.9920.8230.6991.0001.0000.9630.8300.9740.877
대학교1.0000.9890.8700.8141.0000.9631.0000.8960.9391.000
특수학교1.0000.8210.9980.7141.0000.8300.8961.0000.8210.987
법인1.0000.9700.8700.8141.0000.9740.9390.8211.0000.821
접수건수1.0000.8960.9830.7141.0000.8771.0000.9870.8211.000
2023-12-13T03:16:12.400331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원초등학교중학교고등학교전문대학대학교특수학교법인접수건수
유치원1.0000.6970.6670.7360.7900.7610.6910.5880.848
초등학교0.6971.0000.9210.9580.8630.8390.9300.6900.894
중학교0.6670.9211.0000.9600.8320.7910.9240.7030.887
고등학교0.7360.9580.9601.0000.9020.8590.9180.6610.925
전문대학0.7900.8630.8320.9021.0000.9390.8870.6370.927
대학교0.7610.8390.7910.8590.9391.0000.8250.6470.935
특수학교0.6910.9300.9240.9180.8870.8251.0000.7040.852
법인0.5880.6900.7030.6610.6370.6470.7041.0000.732
접수건수0.8480.8940.8870.9250.9270.9350.8520.7321.000

Missing values

2023-12-13T03:16:08.166330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:16:08.400263image/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.
2023-12-13T03:16:08.533195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

신분변동유치원초등학교중학교고등학교전문대학대학교특수학교법인접수건수비고
0미고지정정251262164157331301024<NA>
1병역복무경력승인3020146453167207336222947<NA>
2병역복무경력정정81413826601301<NA>
3병역복무경력취소224112601183<NA>
4복직66545161298105105151102305<NA>
5소급통산승인101000002<NA>
6소급통산정정000011002<NA>
7소급통산취소000000000<NA>
8소득총액16282655177191366711035580217038204<NA>
9소득총액정정13<NA>358063711173<NA>
신분변동유치원초등학교중학교고등학교전문대학대학교특수학교법인접수건수비고
22퇴직724110550714421163234541778034169<NA>
23학교기관기관장22781382213459190706<NA>
24학교기관등록6000020210<NA>
25학교기관사업자번호000000000<NA>
26학교기관정원402212122621115<NA>
27학교기관정정26615111608298<NA>
28합산승인328174412014821282072812<NA>
29합산정정18101210530094<NA>
30합산취소30318911321167<NA>
31휴직19469525141416979081431310435<NA>