Overview

Dataset statistics

Number of variables6
Number of observations285
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory51.5 B

Variable types

Numeric3
Categorical2
Text1

Alerts

파견인원수(자대학교 → 타대학교)(명) is highly overall correlated with 유치인원수(타대학교 → 자대학교)(명)High correlation
유치인원수(타대학교 → 자대학교)(명) is highly overall correlated with 파견인원수(자대학교 → 타대학교)(명)High correlation
학교종류명 is highly overall correlated with 설립구분명High correlation
설립구분명 is highly overall correlated with 학교종류명High correlation
설립구분명 is highly imbalanced (73.3%)Imbalance
파견인원수(자대학교 → 타대학교)(명) has 32 (11.2%) zerosZeros
유치인원수(타대학교 → 자대학교)(명) has 82 (28.8%) zerosZeros

Reproduction

Analysis started2023-12-10 22:15:55.445780
Analysis finished2023-12-10 22:15:56.501073
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct6
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.3298
Minimum2013
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T07:15:56.540751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12014
median2015
Q32017
95-th percentile2018
Maximum2018
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6021514
Coefficient of variation (CV)0.00079498222
Kurtosis-1.1280994
Mean2015.3298
Median Absolute Deviation (MAD)1
Skewness0.076266591
Sum574369
Variance2.5668891
MonotonicityDecreasing
2023-12-11T07:15:56.621371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2015 56
19.6%
2016 52
18.2%
2014 50
17.5%
2017 49
17.2%
2013 48
16.8%
2018 30
10.5%
ValueCountFrequency (%)
2013 48
16.8%
2014 50
17.5%
2015 56
19.6%
2016 52
18.2%
2017 49
17.2%
2018 30
10.5%
ValueCountFrequency (%)
2018 30
10.5%
2017 49
17.2%
2016 52
18.2%
2015 56
19.6%
2014 50
17.5%
2013 48
16.8%

학교종류명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
대학교
176 
전문대학(3년제)
38 
전문대학(2년제)
27 
일반대학원
 
16
특수대학원
 
11
Other values (3)
 
17

Length

Max length9
Median length3
Mean length4.6350877
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대학교
2nd row대학교
3rd row대학교
4th row대학교
5th row교육대학

Common Values

ValueCountFrequency (%)
대학교 176
61.8%
전문대학(3년제) 38
 
13.3%
전문대학(2년제) 27
 
9.5%
일반대학원 16
 
5.6%
특수대학원 11
 
3.9%
산업대학 8
 
2.8%
전문대학원 5
 
1.8%
교육대학 4
 
1.4%

Length

2023-12-11T07:15:56.716455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:56.807749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대학교 176
61.8%
전문대학(3년제 38
 
13.3%
전문대학(2년제 27
 
9.5%
일반대학원 16
 
5.6%
특수대학원 11
 
3.9%
산업대학 8
 
2.8%
전문대학원 5
 
1.8%
교육대학 4
 
1.4%

설립구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
사립
265 
국립
 
15
특별법법인
 
5

Length

Max length5
Median length2
Mean length2.0526316
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사립
2nd row사립
3rd row사립
4th row사립
5th row국립

Common Values

ValueCountFrequency (%)
사립 265
93.0%
국립 15
 
5.3%
특별법법인 5
 
1.8%

Length

2023-12-11T07:15:56.926978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:15:57.020580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 265
93.0%
국립 15
 
5.3%
특별법법인 5
 
1.8%

학교명
Text

Distinct137
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T07:15:57.174621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length9.6210526
Min length5

Characters and Unicode

Total characters2742
Distinct characters98
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)15.4%

Sample

1st row가천대학교
2nd row가톨릭대학교
3rd row강남대학교
4th row경기대학교
5th row경인교육대학교 _제2캠퍼스
ValueCountFrequency (%)
본교 138
29.2%
제2캠퍼스 22
 
4.7%
분교 11
 
2.3%
신한대학교 10
 
2.1%
한양대학교(erica 8
 
1.7%
한세대학교 8
 
1.7%
가톨릭대학교 8
 
1.7%
대학원 7
 
1.5%
수원대학교 7
 
1.5%
강남대학교 7
 
1.5%
Other values (63) 247
52.2%
2023-12-11T07:15:57.477539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 433
15.8%
학 347
12.7%
대 331
 
12.1%
277
 
10.1%
_ 171
 
6.2%
본 138
 
5.0%
한 75
 
2.7%
신 52
 
1.9%
원 46
 
1.7%
경 39
 
1.4%
Other values (88) 833
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2198
80.2%
Space Separator 277
 
10.1%
Connector Punctuation 171
 
6.2%
Uppercase Letter 40
 
1.5%
Decimal Number 22
 
0.8%
Close Punctuation 17
 
0.6%
Open Punctuation 17
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 433
19.7%
학 347
15.8%
대 331
15.1%
본 138
 
6.3%
한 75
 
3.4%
신 52
 
2.4%
원 46
 
2.1%
경 39
 
1.8%
국 38
 
1.7%
산 29
 
1.3%
Other values (78) 670
30.5%
Uppercase Letter
ValueCountFrequency (%)
I 8
20.0%
C 8
20.0%
R 8
20.0%
E 8
20.0%
A 8
20.0%
Space Separator
ValueCountFrequency (%)
277
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 171
100.0%
Decimal Number
ValueCountFrequency (%)
2 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2198
80.2%
Common 504
 
18.4%
Latin 40
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 433
19.7%
학 347
15.8%
대 331
15.1%
본 138
 
6.3%
한 75
 
3.4%
신 52
 
2.4%
원 46
 
2.1%
경 39
 
1.8%
국 38
 
1.7%
산 29
 
1.3%
Other values (78) 670
30.5%
Common
ValueCountFrequency (%)
277
55.0%
_ 171
33.9%
2 22
 
4.4%
) 17
 
3.4%
( 17
 
3.4%
Latin
ValueCountFrequency (%)
I 8
20.0%
C 8
20.0%
R 8
20.0%
E 8
20.0%
A 8
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2198
80.2%
ASCII 544
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 433
19.7%
학 347
15.8%
대 331
15.1%
본 138
 
6.3%
한 75
 
3.4%
신 52
 
2.4%
원 46
 
2.1%
경 39
 
1.8%
국 38
 
1.7%
산 29
 
1.3%
Other values (78) 670
30.5%
ASCII
ValueCountFrequency (%)
277
50.9%
_ 171
31.4%
2 22
 
4.0%
) 17
 
3.1%
( 17
 
3.1%
I 8
 
1.5%
C 8
 
1.5%
R 8
 
1.5%
E 8
 
1.5%
A 8
 
1.5%

파견인원수(자대학교 → 타대학교)(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct135
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.203509
Minimum0
Maximum1341
Zeros32
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T07:15:57.598262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median29
Q394
95-th percentile432.8
Maximum1341
Range1341
Interquartile range (IQR)90

Descriptive statistics

Standard deviation185.95776
Coefficient of variation (CV)1.8935959
Kurtosis16.861215
Mean98.203509
Median Absolute Deviation (MAD)28
Skewness3.6895833
Sum27988
Variance34580.289
MonotonicityNot monotonic
2023-12-11T07:15:57.737299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32
 
11.2%
1 14
 
4.9%
3 12
 
4.2%
4 9
 
3.2%
9 8
 
2.8%
22 6
 
2.1%
2 6
 
2.1%
14 5
 
1.8%
11 5
 
1.8%
25 5
 
1.8%
Other values (125) 183
64.2%
ValueCountFrequency (%)
0 32
11.2%
1 14
4.9%
2 6
 
2.1%
3 12
 
4.2%
4 9
 
3.2%
5 3
 
1.1%
6 3
 
1.1%
7 4
 
1.4%
8 2
 
0.7%
9 8
 
2.8%
ValueCountFrequency (%)
1341 1
0.4%
1256 1
0.4%
1065 1
0.4%
1002 1
0.4%
877 1
0.4%
732 1
0.4%
559 1
0.4%
558 1
0.4%
544 1
0.4%
515 1
0.4%

유치인원수(타대학교 → 자대학교)(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.347368
Minimum0
Maximum687
Zeros82
Zeros (%)28.8%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T07:15:57.855608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q336
95-th percentile241.6
Maximum687
Range687
Interquartile range (IQR)36

Descriptive statistics

Standard deviation98.613033
Coefficient of variation (CV)2.0827564
Kurtosis14.144466
Mean47.347368
Median Absolute Deviation (MAD)8
Skewness3.4504139
Sum13494
Variance9724.5303
MonotonicityNot monotonic
2023-12-11T07:15:57.962848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
28.8%
1 22
 
7.7%
3 17
 
6.0%
2 9
 
3.2%
15 6
 
2.1%
16 6
 
2.1%
17 5
 
1.8%
9 5
 
1.8%
32 5
 
1.8%
4 4
 
1.4%
Other values (88) 124
43.5%
ValueCountFrequency (%)
0 82
28.8%
1 22
 
7.7%
2 9
 
3.2%
3 17
 
6.0%
4 4
 
1.4%
5 2
 
0.7%
6 3
 
1.1%
7 2
 
0.7%
8 4
 
1.4%
9 5
 
1.8%
ValueCountFrequency (%)
687 1
0.4%
625 1
0.4%
537 1
0.4%
457 1
0.4%
423 1
0.4%
375 1
0.4%
374 1
0.4%
341 1
0.4%
328 1
0.4%
326 1
0.4%

Interactions

2023-12-11T07:15:56.099988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:55.631813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:55.837128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:56.189994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:55.694102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:55.908695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:56.269478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:55.765354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:15:56.001478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:15:58.036527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도학교종류명설립구분명파견인원수(자대학교 → 타대학교)(명)유치인원수(타대학교 → 자대학교)(명)
기준년도1.0000.0000.0000.0000.128
학교종류명0.0001.0000.7130.0000.000
설립구분명0.0000.7131.0000.0000.000
파견인원수(자대학교 → 타대학교)(명)0.0000.0000.0001.0000.863
유치인원수(타대학교 → 자대학교)(명)0.1280.0000.0000.8631.000
2023-12-11T07:15:58.123461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명학교종류명
설립구분명1.0000.598
학교종류명0.5981.000
2023-12-11T07:15:58.188735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도파견인원수(자대학교 → 타대학교)(명)유치인원수(타대학교 → 자대학교)(명)학교종류명설립구분명
기준년도1.0000.0770.0880.0000.000
파견인원수(자대학교 → 타대학교)(명)0.0771.0000.6240.0000.000
유치인원수(타대학교 → 자대학교)(명)0.0880.6241.0000.0000.000
학교종류명0.0000.0000.0001.0000.598
설립구분명0.0000.0000.0000.5981.000

Missing values

2023-12-11T07:15:56.373345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:15:56.466790image/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

기준년도학교종류명설립구분명학교명파견인원수(자대학교 → 타대학교)(명)유치인원수(타대학교 → 자대학교)(명)
02018대학교사립가천대학교877328
12018대학교사립가톨릭대학교301197
22018대학교사립강남대학교9897
32018대학교사립경기대학교201101
42018교육대학국립경인교육대학교 _제2캠퍼스200
52018대학교사립단국대학교435687
62018대학교사립대진대학교346120
72018대학교사립명지대학교113122
82018대학교사립서울신학대학교420
92018대학교사립서울장신대학교01
기준년도학교종류명설립구분명학교명파견인원수(자대학교 → 타대학교)(명)유치인원수(타대학교 → 자대학교)(명)
2752013대학교사립한국외국어대학교(용인) _분교7328
2762013일반대학원특별법법인한국학대학원 _본교02
2772013대학교사립한국항공대학교 _본교4856
2782013대학교사립한북대학교 _본교270
2792013대학교사립한세대학교 _본교1912
2802013특수대학원사립한세대학교 영산신학대학원 _본교41
2812013대학교사립한신대학교 _본교7731
2822013일반대학원사립한양대학교 대학원 _분교13
2832013대학교사립한양대학교(ERICA) _분교451135
2842013대학교사립협성대학교 _본교601