Overview

Dataset statistics

Number of variables9
Number of observations5287
Missing cells0
Missing cells (%)0.0%
Duplicate rows25
Duplicate rows (%)0.5%
Total size in memory418.3 KiB
Average record size in memory81.0 B

Variable types

Numeric9

Dataset

Description대학도서관 이용 및 이용자에 관한 데이터 항목(재학생(학부생 + 대학원생) 대출책수, 상호대차 신청 및 제공 건수) 등의 정보를 제공합니다.
Author한국교육학술정보원
URLhttps://www.data.go.kr/data/15071926/fileData.do

Alerts

Dataset has 25 (0.5%) duplicate rowsDuplicates
대출현황-대출책수-계 is highly overall correlated with 재학생(학부생+대학원생) 대출책수 and 4 other fieldsHigh correlation
재학생(학부생+대학원생) 대출책수 is highly overall correlated with 대출현황-대출책수-계 and 4 other fieldsHigh correlation
재학생(학부생+대학원생) 대출책수(연장포함) is highly overall correlated with 대출현황-대출책수-계 and 4 other fieldsHigh correlation
참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공 is highly overall correlated with 대출현황-대출책수-계 and 4 other fieldsHigh correlation
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청 is highly overall correlated with 대출현황-대출책수-계 and 4 other fieldsHigh correlation
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공 is highly overall correlated with 대출현황-대출책수-계 and 4 other fieldsHigh correlation
이용자교육-교육횟수-직접교육-학부생 is highly overall correlated with 이용자교육-교육횟수-직접교육-대학원생High correlation
이용자교육-교육횟수-직접교육-대학원생 is highly overall correlated with 이용자교육-교육횟수-직접교육-학부생High correlation
이용자교육-교육횟수-직접교육-기타 is highly skewed (γ1 = 43.58545517)Skewed
대출현황-대출책수-계 has 149 (2.8%) zerosZeros
재학생(학부생+대학원생) 대출책수 has 159 (3.0%) zerosZeros
재학생(학부생+대학원생) 대출책수(연장포함) has 159 (3.0%) zerosZeros
참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공 has 2811 (53.2%) zerosZeros
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청 has 2447 (46.3%) zerosZeros
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공 has 2151 (40.7%) zerosZeros
이용자교육-교육횟수-직접교육-학부생 has 4331 (81.9%) zerosZeros
이용자교육-교육횟수-직접교육-대학원생 has 4708 (89.0%) zerosZeros
이용자교육-교육횟수-직접교육-기타 has 5036 (95.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:35:10.919164
Analysis finished2023-12-12 04:35:24.093240
Duration13.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대출현황-대출책수-계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4750
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47744.113
Minimum0
Maximum884076
Zeros149
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:24.214841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile123
Q13236
median13402
Q349795.5
95-th percentile215734.9
Maximum884076
Range884076
Interquartile range (IQR)46559.5

Descriptive statistics

Standard deviation88411.807
Coefficient of variation (CV)1.8517845
Kurtosis20.213534
Mean47744.113
Median Absolute Deviation (MAD)12483
Skewness3.8559888
Sum2.5242312 × 108
Variance7.8166477 × 109
MonotonicityNot monotonic
2023-12-12T13:35:24.377924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 149
 
2.8%
350 5
 
0.1%
429 5
 
0.1%
106 4
 
0.1%
1741 4
 
0.1%
10 4
 
0.1%
63 4
 
0.1%
600 4
 
0.1%
276 4
 
0.1%
2634 3
 
0.1%
Other values (4740) 5101
96.5%
ValueCountFrequency (%)
0 149
2.8%
3 1
 
< 0.1%
4 1
 
< 0.1%
9 1
 
< 0.1%
10 4
 
0.1%
11 2
 
< 0.1%
12 3
 
0.1%
15 1
 
< 0.1%
16 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
884076 1
< 0.1%
870304 1
< 0.1%
847278 1
< 0.1%
820297 1
< 0.1%
814300 1
< 0.1%
808764 1
< 0.1%
803792 1
< 0.1%
803063 1
< 0.1%
703337 1
< 0.1%
693160 1
< 0.1%

재학생(학부생+대학원생) 대출책수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4671
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38567.479
Minimum0
Maximum746446
Zeros159
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:24.548245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile75
Q12403.5
median9998
Q340399
95-th percentile175496.5
Maximum746446
Range746446
Interquartile range (IQR)37995.5

Descriptive statistics

Standard deviation73595.838
Coefficient of variation (CV)1.9082357
Kurtosis22.64325
Mean38567.479
Median Absolute Deviation (MAD)9401
Skewness4.0283236
Sum2.0390626 × 108
Variance5.4163474 × 109
MonotonicityNot monotonic
2023-12-12T13:35:24.725818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 159
 
3.0%
300 8
 
0.2%
250 5
 
0.1%
825 5
 
0.1%
12 5
 
0.1%
271 4
 
0.1%
387 4
 
0.1%
81 4
 
0.1%
194 4
 
0.1%
242 4
 
0.1%
Other values (4661) 5085
96.2%
ValueCountFrequency (%)
0 159
3.0%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
9 3
 
0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
12 5
 
0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
746446 1
< 0.1%
741285 1
< 0.1%
736686 1
< 0.1%
734627 1
< 0.1%
732353 1
< 0.1%
727267 1
< 0.1%
700860 1
< 0.1%
667838 1
< 0.1%
646352 1
< 0.1%
624275 1
< 0.1%

재학생(학부생+대학원생) 대출책수(연장포함)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4697
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46271.299
Minimum0
Maximum1404232
Zeros159
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:24.900768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile75
Q12588.5
median11167
Q346642.5
95-th percentile214019.3
Maximum1404232
Range1404232
Interquartile range (IQR)44054

Descriptive statistics

Standard deviation92902.602
Coefficient of variation (CV)2.0077803
Kurtosis28.631262
Mean46271.299
Median Absolute Deviation (MAD)10546
Skewness4.428596
Sum2.4463636 × 108
Variance8.6308934 × 109
MonotonicityNot monotonic
2023-12-12T13:35:25.086541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 159
 
3.0%
300 8
 
0.2%
12 5
 
0.1%
556 5
 
0.1%
271 5
 
0.1%
27 4
 
0.1%
81 4
 
0.1%
387 4
 
0.1%
825 4
 
0.1%
193 4
 
0.1%
Other values (4687) 5085
96.2%
ValueCountFrequency (%)
0 159
3.0%
3 2
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
9 3
 
0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
12 5
 
0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
1404232 1
< 0.1%
980292 1
< 0.1%
907625 1
< 0.1%
797620 1
< 0.1%
765806 1
< 0.1%
746446 1
< 0.1%
741285 1
< 0.1%
736686 1
< 0.1%
734627 1
< 0.1%
733047 1
< 0.1%

참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct576
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.95404
Minimum0
Maximum19261
Zeros2811
Zeros (%)53.2%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:25.250349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q326
95-th percentile418.5
Maximum19261
Range19261
Interquartile range (IQR)26

Descriptive statistics

Standard deviation763.80361
Coefficient of variation (CV)5.3806402
Kurtosis151.71472
Mean141.95404
Median Absolute Deviation (MAD)0
Skewness10.609747
Sum750511
Variance583395.95
MonotonicityNot monotonic
2023-12-12T13:35:25.422992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2811
53.2%
1 188
 
3.6%
2 126
 
2.4%
3 92
 
1.7%
4 72
 
1.4%
5 69
 
1.3%
6 62
 
1.2%
7 52
 
1.0%
10 44
 
0.8%
9 41
 
0.8%
Other values (566) 1730
32.7%
ValueCountFrequency (%)
0 2811
53.2%
1 188
 
3.6%
2 126
 
2.4%
3 92
 
1.7%
4 72
 
1.4%
5 69
 
1.3%
6 62
 
1.2%
7 52
 
1.0%
8 40
 
0.8%
9 41
 
0.8%
ValueCountFrequency (%)
19261 1
< 0.1%
10816 1
< 0.1%
10711 1
< 0.1%
10539 1
< 0.1%
10401 1
< 0.1%
10385 1
< 0.1%
9397 1
< 0.1%
9236 1
< 0.1%
9181 1
< 0.1%
9149 1
< 0.1%

참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct584
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.39928
Minimum0
Maximum11923
Zeros2447
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:25.581598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q334.5
95-th percentile491.4
Maximum11923
Range11923
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation647.79895
Coefficient of variation (CV)4.7843603
Kurtosis114.33105
Mean135.39928
Median Absolute Deviation (MAD)2
Skewness9.4021017
Sum715856
Variance419643.48
MonotonicityNot monotonic
2023-12-12T13:35:25.772672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2447
46.3%
1 182
 
3.4%
2 144
 
2.7%
3 100
 
1.9%
4 91
 
1.7%
5 79
 
1.5%
8 68
 
1.3%
10 66
 
1.2%
12 55
 
1.0%
7 54
 
1.0%
Other values (574) 2001
37.8%
ValueCountFrequency (%)
0 2447
46.3%
1 182
 
3.4%
2 144
 
2.7%
3 100
 
1.9%
4 91
 
1.7%
5 79
 
1.5%
6 51
 
1.0%
7 54
 
1.0%
8 68
 
1.3%
9 50
 
0.9%
ValueCountFrequency (%)
11923 1
< 0.1%
11481 1
< 0.1%
10648 1
< 0.1%
10554 1
< 0.1%
9890 1
< 0.1%
8779 1
< 0.1%
8040 1
< 0.1%
8006 1
< 0.1%
7078 1
< 0.1%
7010 1
< 0.1%

참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct850
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean322.22451
Minimum0
Maximum43620
Zeros2151
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:25.936805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q368.5
95-th percentile1316.6
Maximum43620
Range43620
Interquartile range (IQR)68.5

Descriptive statistics

Standard deviation1701.6298
Coefficient of variation (CV)5.2808825
Kurtosis197.79361
Mean322.22451
Median Absolute Deviation (MAD)3
Skewness12.270015
Sum1703601
Variance2895543.9
MonotonicityNot monotonic
2023-12-12T13:35:26.070625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2151
40.7%
1 240
 
4.5%
2 152
 
2.9%
3 110
 
2.1%
5 82
 
1.6%
4 64
 
1.2%
6 54
 
1.0%
7 50
 
0.9%
13 48
 
0.9%
15 46
 
0.9%
Other values (840) 2290
43.3%
ValueCountFrequency (%)
0 2151
40.7%
1 240
 
4.5%
2 152
 
2.9%
3 110
 
2.1%
4 64
 
1.2%
5 82
 
1.6%
6 54
 
1.0%
7 50
 
0.9%
8 45
 
0.9%
9 35
 
0.7%
ValueCountFrequency (%)
43620 1
< 0.1%
30091 1
< 0.1%
29424 1
< 0.1%
28866 1
< 0.1%
27418 1
< 0.1%
26424 1
< 0.1%
25264 1
< 0.1%
22837 1
< 0.1%
21678 1
< 0.1%
21671 1
< 0.1%

이용자교육-교육횟수-직접교육-학부생
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct116
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3945527
Minimum0
Maximum420
Zeros4331
Zeros (%)81.9%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:26.228043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28
Maximum420
Range420
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.098853
Coefficient of variation (CV)4.1184744
Kurtosis133.34086
Mean4.3945527
Median Absolute Deviation (MAD)0
Skewness9.4554424
Sum23234
Variance327.56848
MonotonicityNot monotonic
2023-12-12T13:35:26.366493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4331
81.9%
1 101
 
1.9%
2 73
 
1.4%
4 45
 
0.9%
3 38
 
0.7%
5 31
 
0.6%
6 26
 
0.5%
22 26
 
0.5%
10 25
 
0.5%
8 24
 
0.5%
Other values (106) 567
 
10.7%
ValueCountFrequency (%)
0 4331
81.9%
1 101
 
1.9%
2 73
 
1.4%
3 38
 
0.7%
4 45
 
0.9%
5 31
 
0.6%
6 26
 
0.5%
7 20
 
0.4%
8 24
 
0.5%
9 19
 
0.4%
ValueCountFrequency (%)
420 1
< 0.1%
307 1
< 0.1%
295 1
< 0.1%
287 1
< 0.1%
270 1
< 0.1%
243 1
< 0.1%
229 1
< 0.1%
227 1
< 0.1%
202 1
< 0.1%
196 1
< 0.1%

이용자교육-교육횟수-직접교육-대학원생
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct84
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7839985
Minimum0
Maximum284
Zeros4708
Zeros (%)89.0%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:26.489105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum284
Range284
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.381156
Coefficient of variation (CV)6.3795771
Kurtosis191.77544
Mean1.7839985
Median Absolute Deviation (MAD)0
Skewness12.049158
Sum9432
Variance129.53071
MonotonicityNot monotonic
2023-12-12T13:35:26.644995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4708
89.0%
1 112
 
2.1%
2 90
 
1.7%
3 52
 
1.0%
4 35
 
0.7%
6 31
 
0.6%
8 19
 
0.4%
5 16
 
0.3%
13 14
 
0.3%
12 13
 
0.2%
Other values (74) 197
 
3.7%
ValueCountFrequency (%)
0 4708
89.0%
1 112
 
2.1%
2 90
 
1.7%
3 52
 
1.0%
4 35
 
0.7%
5 16
 
0.3%
6 31
 
0.6%
7 9
 
0.2%
8 19
 
0.4%
9 11
 
0.2%
ValueCountFrequency (%)
284 1
< 0.1%
225 1
< 0.1%
216 1
< 0.1%
177 1
< 0.1%
171 1
< 0.1%
170 1
< 0.1%
149 1
< 0.1%
144 1
< 0.1%
142 1
< 0.1%
137 1
< 0.1%

이용자교육-교육횟수-직접교육-기타
Real number (ℝ)

SKEWED  ZEROS 

Distinct37
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.39020238
Minimum0
Maximum368
Zeros5036
Zeros (%)95.3%
Negative0
Negative (%)0.0%
Memory size46.6 KiB
2023-12-12T13:35:26.766642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum368
Range368
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.1771982
Coefficient of variation (CV)15.830755
Kurtosis2420.6307
Mean0.39020238
Median Absolute Deviation (MAD)0
Skewness43.585455
Sum2063
Variance38.157778
MonotonicityNot monotonic
2023-12-12T13:35:26.874566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 5036
95.3%
1 88
 
1.7%
2 61
 
1.2%
3 32
 
0.6%
5 10
 
0.2%
4 7
 
0.1%
7 5
 
0.1%
8 5
 
0.1%
6 5
 
0.1%
15 4
 
0.1%
Other values (27) 34
 
0.6%
ValueCountFrequency (%)
0 5036
95.3%
1 88
 
1.7%
2 61
 
1.2%
3 32
 
0.6%
4 7
 
0.1%
5 10
 
0.2%
6 5
 
0.1%
7 5
 
0.1%
8 5
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
368 1
< 0.1%
102 1
< 0.1%
91 1
< 0.1%
86 1
< 0.1%
84 1
< 0.1%
75 1
< 0.1%
68 1
< 0.1%
65 1
< 0.1%
55 1
< 0.1%
49 1
< 0.1%

Interactions

2023-12-12T13:35:22.380492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:12.769968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:14.161796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.946347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.158330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.373895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.377550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.373899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.383058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:22.827094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:12.903133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:14.645788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.091539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.300056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.498770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.462826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.470249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.491190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:22.936779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.083489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:14.820045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.217656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.431533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.632416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.577385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.581129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.602091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.043375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.241250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:14.991639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.405607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.568635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.749678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.673982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.713655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.708594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.188292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.393814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.165362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.546800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.704161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.863857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.782850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.835161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.811252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.324060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.544430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.331082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.658692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.848258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.963821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.880766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.965263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.941285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.423439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.691973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.496765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.766350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.979448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.054032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.996142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.071982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:22.058183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.587054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.830851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.612997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:16.900065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.111723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.139946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.117266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.165998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:22.154952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:23.698090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:13.971896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:15.757428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:17.021861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:18.249929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:19.265588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:20.221684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:21.265073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:35:22.249666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:35:26.972151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출현황-대출책수-계재학생(학부생+대학원생) 대출책수재학생(학부생+대학원생) 대출책수(연장포함)참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공이용자교육-교육횟수-직접교육-학부생이용자교육-교육횟수-직접교육-대학원생이용자교육-교육횟수-직접교육-기타
대출현황-대출책수-계1.0000.9420.8170.4620.5070.3940.3760.5070.139
재학생(학부생+대학원생) 대출책수0.9421.0000.8560.4730.6350.3680.2230.2940.154
재학생(학부생+대학원생) 대출책수(연장포함)0.8170.8561.0000.4180.4860.6090.2560.3550.244
참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공0.4620.4730.4181.0000.7070.2570.2950.2630.163
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청0.5070.6350.4860.7071.0000.3670.3850.3670.192
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공0.3940.3680.6090.2570.3671.0000.2840.4590.310
이용자교육-교육횟수-직접교육-학부생0.3760.2230.2560.2950.3850.2841.0000.7560.442
이용자교육-교육횟수-직접교육-대학원생0.5070.2940.3550.2630.3670.4590.7561.0000.392
이용자교육-교육횟수-직접교육-기타0.1390.1540.2440.1630.1920.3100.4420.3921.000
2023-12-12T13:35:27.104442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출현황-대출책수-계재학생(학부생+대학원생) 대출책수재학생(학부생+대학원생) 대출책수(연장포함)참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공이용자교육-교육횟수-직접교육-학부생이용자교육-교육횟수-직접교육-대학원생이용자교육-교육횟수-직접교육-기타
대출현황-대출책수-계1.0000.9880.9870.6710.6590.7430.1270.1790.118
재학생(학부생+대학원생) 대출책수0.9881.0000.9980.6620.6440.7340.0940.1560.089
재학생(학부생+대학원생) 대출책수(연장포함)0.9870.9981.0000.6670.6500.7390.1090.1730.098
참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공0.6710.6620.6671.0000.8730.6930.1400.2590.132
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청0.6590.6440.6500.8731.0000.6320.1340.2550.136
참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공0.7430.7340.7390.6930.6321.0000.0450.2200.100
이용자교육-교육횟수-직접교육-학부생0.1270.0940.1090.1400.1340.0451.0000.5980.417
이용자교육-교육횟수-직접교육-대학원생0.1790.1560.1730.2590.2550.2200.5981.0000.415
이용자교육-교육횟수-직접교육-기타0.1180.0890.0980.1320.1360.1000.4170.4151.000

Missing values

2023-12-12T13:35:23.849966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:35:24.009034image/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

대출현황-대출책수-계재학생(학부생+대학원생) 대출책수재학생(학부생+대학원생) 대출책수(연장포함)참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공이용자교육-교육횟수-직접교육-학부생이용자교육-교육횟수-직접교육-대학원생이용자교육-교육횟수-직접교육-기타
0323292624830209257014115
1188165165000000
234215119921397501003000
322580018929728720738512437211450
41703497002981995588153265227280
512531654135802212701049
61079210038108770003600
758839310789323414362322433
82019312105145742076600
937254303763863415205454420
대출현황-대출책수-계재학생(학부생+대학원생) 대출책수재학생(학부생+대학원생) 대출책수(연장포함)참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공이용자교육-교육횟수-직접교육-학부생이용자교육-교육횟수-직접교육-대학원생이용자교육-교육횟수-직접교육-기타
52771789414016169210111000
5278981186371020715018000
52796065552078564965714989000
528091672843761283715391019270000
5281535250435969002000
5282719956726712000000
52832280118225225792613210000
52841250191093081523530043620000
5285412530242515000
52862884726309344260065000

Duplicate rows

Most frequently occurring

대출현황-대출책수-계재학생(학부생+대학원생) 대출책수재학생(학부생+대학원생) 대출책수(연장포함)참고서비스 및 상호협력-상호대차 신청 및 제공 건수-제공참고서비스 및 상호협력-원문복사 신청 및 제공 건수-신청참고서비스 및 상호협력-원문복사 신청 및 제공 건수-제공이용자교육-교육횟수-직접교육-학부생이용자교육-교육횟수-직접교육-대학원생이용자교육-교육횟수-직접교육-기타# duplicates
0000000000121
10001100003
41212120000003
102762452450000003
123503003000000003
20002200002
31010100000002
51616160000002
62523230000002
72927270000002