Overview

Dataset statistics

Number of variables14
Number of observations4959
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory610.3 KiB
Average record size in memory126.0 B

Variable types

Numeric11
Categorical3

Dataset

Description대학 시설 및 설비에 관한 데이터 항목(재학생 수, 도서관 건물 연면적, 열람석-자유열람석 수) 등에 대한 정보를 제공합니다.
Author한국교육학술정보원
URLhttps://www.data.go.kr/data/15071928/fileData.do

Alerts

조사년도 키 is highly overall correlated with 열람석-자유열람석수 and 1 other fieldsHigh correlation
대학 키 is highly overall correlated with 재학생 수 and 5 other fieldsHigh correlation
재학생 수 is highly overall correlated with 대학 키 and 5 other fieldsHigh correlation
도서관 건물 연면적 is highly overall correlated with 대학 키 and 5 other fieldsHigh correlation
열람석-자유열람석수 is highly overall correlated with 조사년도 키 and 3 other fieldsHigh correlation
열람석-자료실열람석수 is highly overall correlated with 조사년도 키 and 4 other fieldsHigh correlation
열람석-총열람석수 is highly overall correlated with 대학 키 and 7 other fieldsHigh correlation
설비-업무용 컴퓨터(PC) 수 is highly overall correlated with 대학 키 and 7 other fieldsHigh correlation
설비-이용자용 컴퓨터 (PC) 수 is highly overall correlated with 대학 키 and 5 other fieldsHigh correlation
설비-총 보유 컴퓨터(PC) 수 is highly overall correlated with 대학 키 and 6 other fieldsHigh correlation
설립유형 키 is highly overall correlated with 학교유형 키High correlation
학교유형 키 is highly overall correlated with 설립유형 키 and 1 other fieldsHigh correlation
대학규모 키 is highly overall correlated with 학교유형 키High correlation
설립유형 키 is highly imbalanced (61.2%)Imbalance
도서관 건물 연면적 is highly skewed (γ1 = 40.15199213)Skewed
지역 키 has 59 (1.2%) zerosZeros
재학생 수 has 64 (1.3%) zerosZeros
도서관 건물 연면적 has 120 (2.4%) zerosZeros
열람석-자유열람석수 has 1500 (30.2%) zerosZeros
열람석-자료실열람석수 has 1450 (29.2%) zerosZeros
열람석-총열람석수 has 120 (2.4%) zerosZeros
설비-업무용 컴퓨터(PC) 수 has 533 (10.7%) zerosZeros
설비-이용자용 컴퓨터 (PC) 수 has 215 (4.3%) zerosZeros
설비-총 보유 컴퓨터(PC) 수 has 102 (2.1%) zerosZeros

Reproduction

Analysis started2023-12-11 23:22:53.835617
Analysis finished2023-12-11 23:23:07.981991
Duration14.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사년도 키
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.6832
Minimum2008
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:08.032000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2008
Q12011
median2014
Q32017
95-th percentile2019
Maximum2019
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4058924
Coefficient of variation (CV)0.0016913745
Kurtosis-1.185985
Mean2013.6832
Median Absolute Deviation (MAD)3
Skewness-0.059677044
Sum9985855
Variance11.600103
MonotonicityNot monotonic
2023-12-12T08:23:08.126085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2017 435
8.8%
2016 435
8.8%
2019 434
8.8%
2015 431
8.7%
2013 430
8.7%
2014 430
8.7%
2018 427
8.6%
2011 405
8.2%
2012 402
8.1%
2010 397
8.0%
Other values (2) 733
14.8%
ValueCountFrequency (%)
2008 353
7.1%
2009 380
7.7%
2010 397
8.0%
2011 405
8.2%
2012 402
8.1%
2013 430
8.7%
2014 430
8.7%
2015 431
8.7%
2016 435
8.8%
2017 435
8.8%
ValueCountFrequency (%)
2019 434
8.8%
2018 427
8.6%
2017 435
8.8%
2016 435
8.8%
2015 431
8.7%
2014 430
8.7%
2013 430
8.7%
2012 402
8.1%
2011 405
8.2%
2010 397
8.0%

대학 키
Real number (ℝ)

HIGH CORRELATION 

Distinct458
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.94071
Minimum1
Maximum458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:08.261263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q1104
median211
Q3321
95-th percentile426
Maximum458
Range457
Interquartile range (IQR)217

Descriptive statistics

Standard deviation127.95223
Coefficient of variation (CV)0.59529078
Kurtosis-1.1350189
Mean214.94071
Median Absolute Deviation (MAD)108
Skewness0.10239268
Sum1065891
Variance16371.772
MonotonicityNot monotonic
2023-12-12T08:23:08.404038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 12
 
0.2%
385 12
 
0.2%
82 12
 
0.2%
70 12
 
0.2%
62 12
 
0.2%
60 12
 
0.2%
54 12
 
0.2%
48 12
 
0.2%
397 12
 
0.2%
394 12
 
0.2%
Other values (448) 4839
97.6%
ValueCountFrequency (%)
1 12
0.2%
2 12
0.2%
3 12
0.2%
4 12
0.2%
5 12
0.2%
6 12
0.2%
7 12
0.2%
8 12
0.2%
9 12
0.2%
10 12
0.2%
ValueCountFrequency (%)
458 12
0.2%
457 1
 
< 0.1%
456 3
 
0.1%
455 9
0.2%
454 9
0.2%
453 4
 
0.1%
452 5
0.1%
451 5
0.1%
450 6
0.1%
449 7
0.1%

설립유형 키
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
3
4203 
1
571 
2
 
102
4
 
83

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4203
84.8%
1 571
 
11.5%
2 102
 
2.1%
4 83
 
1.7%

Length

2023-12-12T08:23:08.511840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:23:08.605838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4203
84.8%
1 571
 
11.5%
2 102
 
2.1%
4 83
 
1.7%

학교유형 키
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
1
2586 
2
1851 
3
439 
4
 
83

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 2586
52.1%
2 1851
37.3%
3 439
 
8.9%
4 83
 
1.7%

Length

2023-12-12T08:23:08.695599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:23:08.781874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2586
52.1%
2 1851
37.3%
3 439
 
8.9%
4 83
 
1.7%

대학규모 키
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.9 KiB
3
1735 
1
1446 
2
1256 
0
522 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row3
5th row2

Common Values

ValueCountFrequency (%)
3 1735
35.0%
1 1446
29.2%
2 1256
25.3%
0 522
 
10.5%

Length

2023-12-12T08:23:08.875054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:23:08.996458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1735
35.0%
1 1446
29.2%
2 1256
25.3%
0 522
 
10.5%

지역 키
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1814882
Minimum0
Maximum17
Zeros59
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:09.146598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median9
Q313
95-th percentile16
Maximum17
Range17
Interquartile range (IQR)11

Descriptive statistics

Standard deviation5.201015
Coefficient of variation (CV)0.63570525
Kurtosis-1.3252235
Mean8.1814882
Median Absolute Deviation (MAD)5
Skewness-0.097110518
Sum40572
Variance27.050557
MonotonicityNot monotonic
2023-12-12T08:23:09.294213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9 921
18.6%
1 915
18.5%
15 443
8.9%
12 321
 
6.5%
2 282
 
5.7%
16 273
 
5.5%
13 257
 
5.2%
14 232
 
4.7%
10 226
 
4.6%
6 218
 
4.4%
Other values (8) 871
17.6%
ValueCountFrequency (%)
0 59
 
1.2%
1 915
18.5%
2 282
 
5.7%
3 147
 
3.0%
4 112
 
2.3%
5 202
 
4.1%
6 218
 
4.4%
7 62
 
1.3%
8 20
 
0.4%
9 921
18.6%
ValueCountFrequency (%)
17 55
 
1.1%
16 273
 
5.5%
15 443
8.9%
14 232
 
4.7%
13 257
 
5.2%
12 321
 
6.5%
11 214
 
4.3%
10 226
 
4.6%
9 921
18.6%
8 20
 
0.4%

재학생 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3565
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6010.4319
Minimum0
Maximum184470
Zeros64
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:09.459131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile84
Q11041
median3572
Q37564
95-th percentile21596.2
Maximum184470
Range184470
Interquartile range (IQR)6523

Descriptive statistics

Standard deviation9696.4034
Coefficient of variation (CV)1.6132623
Kurtosis139.23885
Mean6010.4319
Median Absolute Deviation (MAD)2787
Skewness9.2361571
Sum29805732
Variance94020239
MonotonicityNot monotonic
2023-12-12T08:23:09.677802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64
 
1.3%
60 8
 
0.2%
76 7
 
0.1%
66 7
 
0.1%
88 7
 
0.1%
87 6
 
0.1%
97 6
 
0.1%
86 6
 
0.1%
83 6
 
0.1%
57 6
 
0.1%
Other values (3555) 4836
97.5%
ValueCountFrequency (%)
0 64
1.3%
2 4
 
0.1%
3 1
 
< 0.1%
5 3
 
0.1%
9 1
 
< 0.1%
11 1
 
< 0.1%
15 1
 
< 0.1%
17 2
 
< 0.1%
18 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
184470 1
< 0.1%
182890 1
< 0.1%
179726 1
< 0.1%
173758 1
< 0.1%
162036 1
< 0.1%
157446 1
< 0.1%
145221 1
< 0.1%
136642 1
< 0.1%
125385 2
< 0.1%
117765 1
< 0.1%

도서관 건물 연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1562
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6904.6788
Minimum0
Maximum1050207
Zeros120
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:09.861177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile121.6
Q11031
median3217
Q38961
95-th percentile23849.09
Maximum1050207
Range1050207
Interquartile range (IQR)7930

Descriptive statistics

Standard deviation18178.339
Coefficient of variation (CV)2.6327567
Kurtosis2221.0666
Mean6904.6788
Median Absolute Deviation (MAD)2647
Skewness40.151992
Sum34240302
Variance3.3045202 × 108
MonotonicityNot monotonic
2023-12-12T08:23:10.075091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 120
 
2.4%
583.0 22
 
0.4%
379.0 22
 
0.4%
210.0 21
 
0.4%
906.0 21
 
0.4%
1657.0 17
 
0.3%
20454.0 16
 
0.3%
2883.0 14
 
0.3%
1195.0 14
 
0.3%
7791.0 13
 
0.3%
Other values (1552) 4679
94.4%
ValueCountFrequency (%)
0.0 120
2.4%
10.0 7
 
0.1%
13.0 4
 
0.1%
15.0 2
 
< 0.1%
15.5 1
 
< 0.1%
18.0 3
 
0.1%
26.0 1
 
< 0.1%
31.0 2
 
< 0.1%
33.0 12
 
0.2%
37.0 3
 
0.1%
ValueCountFrequency (%)
1050207.0 1
< 0.1%
368560.0 1
< 0.1%
119450.0 2
< 0.1%
78604.0 1
< 0.1%
78585.0 1
< 0.1%
78226.0 1
< 0.1%
76051.0 1
< 0.1%
75222.0 1
< 0.1%
70075.0 1
< 0.1%
69736.0 1
< 0.1%

열람석-자유열람석수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1104
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean523.07784
Minimum0
Maximum8362
Zeros1500
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:10.263136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median168
Q3672
95-th percentile2232
Maximum8362
Range8362
Interquartile range (IQR)672

Descriptive statistics

Standard deviation901.85114
Coefficient of variation (CV)1.7241242
Kurtosis13.095762
Mean523.07784
Median Absolute Deviation (MAD)168
Skewness3.2445546
Sum2593943
Variance813335.48
MonotonicityNot monotonic
2023-12-12T08:23:10.423334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1500
30.2%
72 49
 
1.0%
48 41
 
0.8%
80 38
 
0.8%
90 27
 
0.5%
36 24
 
0.5%
40 23
 
0.5%
102 23
 
0.5%
120 22
 
0.4%
56 22
 
0.4%
Other values (1094) 3190
64.3%
ValueCountFrequency (%)
0 1500
30.2%
3 1
 
< 0.1%
4 1
 
< 0.1%
6 7
 
0.1%
7 1
 
< 0.1%
8 7
 
0.1%
9 7
 
0.1%
10 19
 
0.4%
11 3
 
0.1%
12 13
 
0.3%
ValueCountFrequency (%)
8362 1
 
< 0.1%
6867 1
 
< 0.1%
6573 1
 
< 0.1%
6557 1
 
< 0.1%
6462 1
 
< 0.1%
6330 1
 
< 0.1%
6279 1
 
< 0.1%
6164 1
 
< 0.1%
5972 2
< 0.1%
5929 4
0.1%

열람석-자료실열람석수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct928
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean270.77374
Minimum0
Maximum3170
Zeros1450
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:10.556266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median70
Q3316.5
95-th percentile1292
Maximum3170
Range3170
Interquartile range (IQR)316.5

Descriptive statistics

Standard deviation461.45766
Coefficient of variation (CV)1.7042186
Kurtosis8.3254577
Mean270.77374
Median Absolute Deviation (MAD)70
Skewness2.6886276
Sum1342767
Variance212943.18
MonotonicityNot monotonic
2023-12-12T08:23:10.714331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1450
29.2%
20 72
 
1.5%
12 65
 
1.3%
30 60
 
1.2%
24 58
 
1.2%
6 44
 
0.9%
40 40
 
0.8%
50 34
 
0.7%
48 33
 
0.7%
8 29
 
0.6%
Other values (918) 3074
62.0%
ValueCountFrequency (%)
0 1450
29.2%
1 5
 
0.1%
2 9
 
0.2%
3 7
 
0.1%
4 22
 
0.4%
5 10
 
0.2%
6 44
 
0.9%
7 10
 
0.2%
8 29
 
0.6%
9 8
 
0.2%
ValueCountFrequency (%)
3170 2
< 0.1%
3142 1
< 0.1%
3098 1
< 0.1%
3023 1
< 0.1%
2947 1
< 0.1%
2930 1
< 0.1%
2909 1
< 0.1%
2891 1
< 0.1%
2889 1
< 0.1%
2885 2
< 0.1%

열람석-총열람석수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1767
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1065.0964
Minimum0
Maximum9809
Zeros120
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:10.911177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25
Q1188.5
median570
Q31406
95-th percentile3930.7
Maximum9809
Range9809
Interquartile range (IQR)1217.5

Descriptive statistics

Standard deviation1369.022
Coefficient of variation (CV)1.2853503
Kurtosis7.6476687
Mean1065.0964
Median Absolute Deviation (MAD)449
Skewness2.4861016
Sum5281813
Variance1874221.1
MonotonicityNot monotonic
2023-12-12T08:23:11.135454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 120
 
2.4%
160 36
 
0.7%
60 30
 
0.6%
24 29
 
0.6%
180 26
 
0.5%
80 26
 
0.5%
42 25
 
0.5%
120 22
 
0.4%
16 20
 
0.4%
110 20
 
0.4%
Other values (1757) 4605
92.9%
ValueCountFrequency (%)
0 120
2.4%
1 1
 
< 0.1%
2 5
 
0.1%
3 3
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
9 1
 
< 0.1%
10 10
 
0.2%
12 8
 
0.2%
13 1
 
< 0.1%
ValueCountFrequency (%)
9809 1
< 0.1%
9792 1
< 0.1%
9715 1
< 0.1%
9614 1
< 0.1%
9560 1
< 0.1%
9448 1
< 0.1%
9376 1
< 0.1%
8823 1
< 0.1%
8808 1
< 0.1%
8803 1
< 0.1%

설비-업무용 컴퓨터(PC) 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct166
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.398467
Minimum0
Maximum276
Zeros533
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:11.372781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q320
95-th percentile69
Maximum276
Range276
Interquartile range (IQR)18

Descriptive statistics

Standard deviation27.748658
Coefficient of variation (CV)1.5948909
Kurtosis16.73457
Mean17.398467
Median Absolute Deviation (MAD)6
Skewness3.5207405
Sum86279
Variance769.98803
MonotonicityNot monotonic
2023-12-12T08:23:11.531902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 533
 
10.7%
2 409
 
8.2%
1 368
 
7.4%
3 291
 
5.9%
4 262
 
5.3%
5 236
 
4.8%
8 221
 
4.5%
6 219
 
4.4%
7 195
 
3.9%
10 146
 
2.9%
Other values (156) 2079
41.9%
ValueCountFrequency (%)
0 533
10.7%
1 368
7.4%
2 409
8.2%
3 291
5.9%
4 262
5.3%
5 236
4.8%
6 219
4.4%
7 195
 
3.9%
8 221
4.5%
9 137
 
2.8%
ValueCountFrequency (%)
276 1
< 0.1%
248 2
< 0.1%
234 1
< 0.1%
227 1
< 0.1%
221 1
< 0.1%
219 1
< 0.1%
215 1
< 0.1%
213 1
< 0.1%
211 2
< 0.1%
206 2
< 0.1%

설비-이용자용 컴퓨터 (PC) 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct393
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.864489
Minimum0
Maximum989
Zeros215
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:12.023174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median38
Q391
95-th percentile264
Maximum989
Range989
Interquartile range (IQR)81

Descriptive statistics

Standard deviation101.24976
Coefficient of variation (CV)1.4088983
Kurtosis18.873491
Mean71.864489
Median Absolute Deviation (MAD)33
Skewness3.5152646
Sum356376
Variance10251.513
MonotonicityNot monotonic
2023-12-12T08:23:12.207288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 215
 
4.3%
2 201
 
4.1%
1 134
 
2.7%
3 131
 
2.6%
4 114
 
2.3%
8 104
 
2.1%
6 99
 
2.0%
5 94
 
1.9%
10 82
 
1.7%
12 80
 
1.6%
Other values (383) 3705
74.7%
ValueCountFrequency (%)
0 215
4.3%
1 134
2.7%
2 201
4.1%
3 131
2.6%
4 114
2.3%
5 94
1.9%
6 99
2.0%
7 38
 
0.8%
8 104
2.1%
9 62
 
1.3%
ValueCountFrequency (%)
989 1
< 0.1%
983 1
< 0.1%
978 1
< 0.1%
966 1
< 0.1%
937 1
< 0.1%
852 2
< 0.1%
826 1
< 0.1%
820 1
< 0.1%
818 2
< 0.1%
810 1
< 0.1%

설비-총 보유 컴퓨터(PC) 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct462
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.202057
Minimum0
Maximum1177
Zeros102
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size43.7 KiB
2023-12-12T08:23:12.368943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median48
Q3110
95-th percentile322
Maximum1177
Range1177
Interquartile range (IQR)96

Descriptive statistics

Standard deviation124.49655
Coefficient of variation (CV)1.395669
Kurtosis17.751498
Mean89.202057
Median Absolute Deviation (MAD)40
Skewness3.4433318
Sum442353
Variance15499.39
MonotonicityNot monotonic
2023-12-12T08:23:12.543412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 135
 
2.7%
2 133
 
2.7%
3 118
 
2.4%
0 102
 
2.1%
5 97
 
2.0%
1 87
 
1.8%
8 86
 
1.7%
12 83
 
1.7%
9 73
 
1.5%
23 70
 
1.4%
Other values (452) 3975
80.2%
ValueCountFrequency (%)
0 102
2.1%
1 87
1.8%
2 133
2.7%
3 118
2.4%
4 135
2.7%
5 97
2.0%
6 70
1.4%
7 70
1.4%
8 86
1.7%
9 73
1.5%
ValueCountFrequency (%)
1177 1
< 0.1%
1175 1
< 0.1%
1151 1
< 0.1%
1124 1
< 0.1%
1117 1
< 0.1%
1047 1
< 0.1%
1037 1
< 0.1%
1025 1
< 0.1%
1023 1
< 0.1%
996 1
< 0.1%

Interactions

2023-12-12T08:23:06.693786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:55.654235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.652042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.585082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.684362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.849013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.376331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.606325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.593645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.524177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.526047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.777027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:55.754276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.745191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.665637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.788882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.209091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.480250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.688589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.687506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.608072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.606889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.856851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:55.845278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.839723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.752626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.896157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.317847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.569069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.767580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.758673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.683520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.691062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.946028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:55.939819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.935119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.868996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.022062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.444763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.690409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.862227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.856224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.771253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.778460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.035320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.044474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.030308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.996850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.127147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.602554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.840845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.951673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.949992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.877297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.866497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.134473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.140044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.125318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.109024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.232057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.712788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.014813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.052517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.031975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.967675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.947078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.217302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.224803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.199692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.219180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.330673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.840272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.145101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.148394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.110005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.053592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.022740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.301258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.313478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.282910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.317649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.437260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:00.945621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.266533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.249149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.196442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.141066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.103920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.385439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.393216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.357352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.420088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.548187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.046860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.340733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.332119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.276636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.245210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.180166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.467025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.475255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.432284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.508148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.651591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.168279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.440718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.415768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.362477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.340400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.260911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:07.551924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:56.560687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:57.507815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:58.594529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:22:59.744409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:01.273013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:02.522304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:03.509073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:04.446357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:05.430149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:06.342354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:23:12.655817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사년도 키대학 키설립유형 키학교유형 키대학규모 키지역 키재학생 수도서관 건물 연면적열람석-자유열람석수열람석-자료실열람석수열람석-총열람석수설비-업무용 컴퓨터(PC) 수설비-이용자용 컴퓨터 (PC) 수설비-총 보유 컴퓨터(PC) 수
조사년도 키1.0000.0000.0000.0000.0000.0000.0000.0240.3050.3520.0000.1020.0000.000
대학 키0.0001.0000.5410.6100.4840.5050.2870.0550.5030.5180.6150.5620.5380.578
설립유형 키0.0000.5411.0000.9100.5460.2260.1730.0000.2080.1450.2590.2170.2100.214
학교유형 키0.0000.6100.9101.0000.8950.3490.2030.0420.3640.3830.4920.3960.4020.431
대학규모 키0.0000.4840.5460.8951.0000.3610.3400.0510.4680.4770.6150.4880.4980.510
지역 키0.0000.5050.2260.3490.3611.0000.1620.0980.2420.3460.3360.3000.2750.305
재학생 수0.0000.2870.1730.2030.3400.1621.0000.0000.5420.4150.6110.5890.5600.564
도서관 건물 연면적0.0240.0550.0000.0420.0510.0980.0001.0000.0000.0320.0000.0000.0400.037
열람석-자유열람석수0.3050.5030.2080.3640.4680.2420.5420.0001.0000.7340.9040.8870.8240.793
열람석-자료실열람석수0.3520.5180.1450.3830.4770.3460.4150.0320.7341.0000.7910.8190.7770.813
열람석-총열람석수0.0000.6150.2590.4920.6150.3360.6110.0000.9040.7911.0000.8540.8890.880
설비-업무용 컴퓨터(PC) 수0.1020.5620.2170.3960.4880.3000.5890.0000.8870.8190.8541.0000.8740.896
설비-이용자용 컴퓨터 (PC) 수0.0000.5380.2100.4020.4980.2750.5600.0400.8240.7770.8890.8741.0000.978
설비-총 보유 컴퓨터(PC) 수0.0000.5780.2140.4310.5100.3050.5640.0370.7930.8130.8800.8960.9781.000
2023-12-12T08:23:12.823739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대학규모 키학교유형 키설립유형 키
대학규모 키1.0000.5780.238
학교유형 키0.5781.0000.606
설립유형 키0.2380.6061.000
2023-12-12T08:23:12.932987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사년도 키대학 키지역 키재학생 수도서관 건물 연면적열람석-자유열람석수열람석-자료실열람석수열람석-총열람석수설비-업무용 컴퓨터(PC) 수설비-이용자용 컴퓨터 (PC) 수설비-총 보유 컴퓨터(PC) 수설립유형 키학교유형 키대학규모 키
조사년도 키1.0000.084-0.012-0.050-0.017-0.586-0.568-0.039-0.279-0.016-0.0490.0000.0000.018
대학 키0.0841.0000.069-0.633-0.655-0.402-0.399-0.690-0.568-0.638-0.6540.3540.4130.310
지역 키-0.0120.0691.000-0.149-0.100-0.002-0.076-0.079-0.147-0.121-0.1300.1370.2150.223
재학생 수-0.050-0.633-0.1491.0000.7980.4860.4650.8610.6970.8020.8180.1190.1410.239
도서관 건물 연면적-0.017-0.655-0.1000.7981.0000.4940.4940.9280.7490.8720.8900.0000.0170.020
열람석-자유열람석수-0.586-0.402-0.0020.4860.4941.0000.8740.5610.6240.4510.4840.1260.2250.298
열람석-자료실열람석수-0.568-0.399-0.0760.4650.4940.8741.0000.5170.6580.4980.5290.0870.2380.305
열람석-총열람석수-0.039-0.690-0.0790.8610.9280.5610.5171.0000.7450.8720.8900.1570.3160.418
설비-업무용 컴퓨터(PC) 수-0.279-0.568-0.1470.6970.7490.6240.6580.7451.0000.7380.7950.1310.2470.313
설비-이용자용 컴퓨터 (PC) 수-0.016-0.638-0.1210.8020.8720.4510.4980.8720.7381.0000.9920.1270.2510.321
설비-총 보유 컴퓨터(PC) 수-0.049-0.654-0.1300.8180.8900.4840.5290.8900.7950.9921.0000.1290.2710.329
설립유형 키0.0000.3540.1370.1190.0000.1260.0870.1570.1310.1270.1291.0000.6060.238
학교유형 키0.0000.4130.2150.1410.0170.2250.2380.3160.2470.2510.2710.6061.0000.578
대학규모 키0.0180.3100.2230.2390.0200.2980.3050.4180.3130.3210.3290.2380.5781.000

Missing values

2023-12-12T08:23:07.680697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:23:07.880958image/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

조사년도 키대학 키설립유형 키학교유형 키대학규모 키지역 키재학생 수도서관 건물 연면적열람석-자유열람석수열람석-자료실열람석수열람석-총열람석수설비-업무용 컴퓨터(PC) 수설비-이용자용 컴퓨터 (PC) 수설비-총 보유 컴퓨터(PC) 수
0201913120810810221.000168008181
120185931111587936199.000382250354404
220081093121276207488.06905901280144761
3200887313158803914.050421672085058
420081763229348411352.017410527943135
520136531111175615275.0118715942781115132247
62013723129608713168.0426755118130104134
720124631111801516120.01740990273062106168
8201243344013466223.040040000
9201436332312957412.0104791834610
조사년도 키대학 키설립유형 키학교유형 키대학규모 키지역 키재학생 수도서관 건물 연면적열람석-자유열람석수열람석-자료실열람석수열람석-총열람석수설비-업무용 컴퓨터(PC) 수설비-이용자용 컴퓨터 (PC) 수설비-총 보유 컴퓨터(PC) 수
494920181693231311381027.00034633841
4950201831012396321976.000297101727
4951201514411211988411832.01242206144832178210
495220154013231662100.020626336
495320122763221722951274.0207802873811
495420143493301235217.003030257
4955201440032311524396.017739021113
495620092721111092912689.01605744234930272302
495720097631211835411602.01034278131221131152
4958200910111121661022780.02222817303962256318