Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells19384
Missing cells (%)24.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

Numeric2
Text1
DateTime4
Categorical1

Dataset

Description경남대표도서관의 전자도서관 대출반납 내역 공공데이터입니다. 도서관 운영을 위한 정보를 포함하고있습니다. 대출일 반납일등의 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15097804

Alerts

대출상태 is highly imbalanced (79.2%)Imbalance
대출일 has 327 (3.3%) missing valuesMissing
반납일 has 328 (3.3%) missing valuesMissing
예약일 has 9057 (90.6%) missing valuesMissing
예약취소일 has 9672 (96.7%) missing valuesMissing
대출번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:56:00.495494
Analysis finished2023-12-10 23:56:03.329233
Duration2.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대출번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33783.092
Minimum1
Maximum79552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:56:03.418815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3486.7
Q116417.75
median32857
Q349510.75
95-th percentile76314.35
Maximum79552
Range79551
Interquartile range (IQR)33093

Descriptive statistics

Standard deviation20431.137
Coefficient of variation (CV)0.60477404
Kurtosis-0.75707473
Mean33783.092
Median Absolute Deviation (MAD)16543.5
Skewness0.26961733
Sum3.3783092 × 108
Variance4.1743136 × 108
MonotonicityNot monotonic
2023-12-11T08:56:03.570702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2951 1
 
< 0.1%
9347 1
 
< 0.1%
8343 1
 
< 0.1%
7841 1
 
< 0.1%
37815 1
 
< 0.1%
37771 1
 
< 0.1%
1008 1
 
< 0.1%
43757 1
 
< 0.1%
321 1
 
< 0.1%
27369 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
9 1
< 0.1%
26 1
< 0.1%
38 1
< 0.1%
41 1
< 0.1%
44 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
53 1
< 0.1%
63 1
< 0.1%
ValueCountFrequency (%)
79552 1
< 0.1%
79550 1
< 0.1%
79547 1
< 0.1%
79546 1
< 0.1%
79542 1
< 0.1%
79537 1
< 0.1%
79523 1
< 0.1%
79520 1
< 0.1%
79518 1
< 0.1%
79512 1
< 0.1%

도서번호
Text

Distinct3813
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:56:03.865436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length14
Mean length11.0565
Min length2

Characters and Unicode

Total characters110565
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2966 ?
Unique (%)29.7%

Sample

1st row968018
2nd row4808930000000
3rd row5051113
4th row140800866
5th row171005899
ValueCountFrequency (%)
4801190000000 1051
 
10.5%
4801160000000 1026
 
10.3%
4808960000000 276
 
2.8%
4808930000000 268
 
2.7%
4808970000000 261
 
2.6%
4808950000000 251
 
2.5%
4801200000000 214
 
2.1%
4808990000000 175
 
1.8%
4809000000000 160
 
1.6%
4801130000000 149
 
1.5%
Other values (3803) 6169
61.7%
2023-12-11T08:56:04.358937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 45010
40.7%
1 11999
 
10.9%
9667
 
8.7%
8 9376
 
8.5%
4 7061
 
6.4%
9 6684
 
6.0%
2 4442
 
4.0%
6 4433
 
4.0%
3 3910
 
3.5%
7 3693
 
3.3%
Other values (15) 4290
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100233
90.7%
Space Separator 9667
 
8.7%
Uppercase Letter 548
 
0.5%
Dash Punctuation 92
 
0.1%
Lowercase Letter 25
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45010
44.9%
1 11999
 
12.0%
8 9376
 
9.4%
4 7061
 
7.0%
9 6684
 
6.7%
2 4442
 
4.4%
6 4433
 
4.4%
3 3910
 
3.9%
7 3693
 
3.7%
5 3625
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 224
40.9%
D 136
24.8%
X 46
 
8.4%
C 35
 
6.4%
F 35
 
6.4%
B 35
 
6.4%
E 33
 
6.0%
M 4
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
a 8
32.0%
f 8
32.0%
b 4
16.0%
e 3
 
12.0%
d 2
 
8.0%
Space Separator
ValueCountFrequency (%)
9667
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109992
99.5%
Latin 573
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 224
39.1%
D 136
23.7%
X 46
 
8.0%
C 35
 
6.1%
F 35
 
6.1%
B 35
 
6.1%
E 33
 
5.8%
a 8
 
1.4%
f 8
 
1.4%
M 4
 
0.7%
Other values (3) 9
 
1.6%
Common
ValueCountFrequency (%)
0 45010
40.9%
1 11999
 
10.9%
9667
 
8.8%
8 9376
 
8.5%
4 7061
 
6.4%
9 6684
 
6.1%
2 4442
 
4.0%
6 4433
 
4.0%
3 3910
 
3.6%
7 3693
 
3.4%
Other values (2) 3717
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45010
40.7%
1 11999
 
10.9%
9667
 
8.7%
8 9376
 
8.5%
4 7061
 
6.4%
9 6684
 
6.0%
2 4442
 
4.0%
6 4433
 
4.0%
3 3910
 
3.5%
7 3693
 
3.3%
Other values (15) 4290
 
3.9%

대출일
Date

MISSING 

Distinct8882
Distinct (%)91.8%
Missing327
Missing (%)3.3%
Memory size156.2 KiB
Minimum2020-01-06 09:01:00
Maximum2020-10-27 00:05:00
2023-12-11T08:56:04.519036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:04.658147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

반납일
Date

MISSING 

Distinct5527
Distinct (%)57.1%
Missing328
Missing (%)3.3%
Memory size156.2 KiB
Minimum2020-01-06 09:32:00
Maximum2020-11-10 00:04:00
2023-12-11T08:56:04.788863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:04.944925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예약일
Date

MISSING 

Distinct929
Distinct (%)98.5%
Missing9057
Missing (%)90.6%
Memory size156.2 KiB
Minimum2020-02-04 09:48:00
Maximum2020-08-27 01:06:00
2023-12-11T08:56:05.092108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:05.240452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예약취소일
Date

MISSING 

Distinct290
Distinct (%)88.4%
Missing9672
Missing (%)96.7%
Memory size156.2 KiB
Minimum2020-02-05 17:05:00
Maximum2020-09-05 00:05:00
2023-12-11T08:56:05.623377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:05.781383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대출상태
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
반납
9672 
예약취소
 
328

Length

Max length4
Median length2
Mean length2.0656
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
반납 9672
96.7%
예약취소 328
 
3.3%

Length

2023-12-11T08:56:05.920400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:56:06.035842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반납 9672
96.7%
예약취소 328
 
3.3%

도서정보키
Real number (ℝ)

Distinct5773
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37460.743
Minimum1
Maximum119637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:56:06.145633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile736.9
Q12870
median9703
Q374309.25
95-th percentile107114.05
Maximum119637
Range119636
Interquartile range (IQR)71439.25

Descriptive statistics

Standard deviation41915.299
Coefficient of variation (CV)1.1189126
Kurtosis-1.1574088
Mean37460.743
Median Absolute Deviation (MAD)8843
Skewness0.71605572
Sum3.7460743 × 108
Variance1.7568923 × 109
MonotonicityNot monotonic
2023-12-11T08:56:06.284361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10510 22
 
0.2%
663 21
 
0.2%
6059 21
 
0.2%
600 21
 
0.2%
1007 20
 
0.2%
6051 19
 
0.2%
6198 19
 
0.2%
1781 19
 
0.2%
10461 18
 
0.2%
864 18
 
0.2%
Other values (5763) 9802
98.0%
ValueCountFrequency (%)
1 4
< 0.1%
18 2
 
< 0.1%
19 1
 
< 0.1%
21 8
0.1%
25 1
 
< 0.1%
28 2
 
< 0.1%
29 1
 
< 0.1%
36 1
 
< 0.1%
38 1
 
< 0.1%
43 1
 
< 0.1%
ValueCountFrequency (%)
119637 1
< 0.1%
119636 1
< 0.1%
119627 1
< 0.1%
119620 1
< 0.1%
119619 1
< 0.1%
119618 1
< 0.1%
119609 1
< 0.1%
119591 1
< 0.1%
119570 1
< 0.1%
119548 1
< 0.1%

Interactions

2023-12-11T08:56:02.689583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:02.342352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:02.805206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:56:02.559338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:56:06.371318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출번호대출상태도서정보키
대출번호1.0000.0560.456
대출상태0.0561.0000.137
도서정보키0.4560.1371.000
2023-12-11T08:56:06.448232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출번호도서정보키대출상태
대출번호1.0000.1520.056
도서정보키0.1521.0000.105
대출상태0.0560.1051.000

Missing values

2023-12-11T08:56:02.940865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:56:03.105122image/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.
2023-12-11T08:56:03.249874image/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

대출번호도서번호대출일반납일예약일예약취소일대출상태도서정보키
261729519680182020-02-14 00:012020-02-28 00:05<NA><NA>반납8906
406604635748089300000002020-05-07 09:032020-05-21 00:08<NA><NA>반납2117
319473023150511132020-04-14 15:042020-04-14 15:05<NA><NA>반납106479
50768408141408008662020-04-26 08:552020-05-10 00:07<NA><NA>반납37075
27679324401710058992020-04-17 01:572020-05-01 00:06<NA><NA>반납62012
36483257931708056992020-04-06 13:432020-04-06 13:44<NA><NA>반납4722
325042111448089300000002020-03-27 16:202020-04-10 00:06<NA><NA>반납2150
45704433591810004122020-07-07 00:062020-07-21 00:052020-04-28 17:32<NA>반납5527
738109842072020-01-06 13:492020-01-06 13:49<NA><NA>반납10195
547286146848011900000002020-07-02 11:152020-07-02 11:16<NA><NA>반납118075
대출번호도서번호대출일반납일예약일예약취소일대출상태도서정보키
48083367581308015722020-04-21 14:202020-04-21 14:27<NA><NA>반납3351
401994522148011900000002020-05-03 22:192020-05-17 00:07<NA><NA>반납52809
400294505148089600000002020-05-03 14:032020-05-17 00:06<NA><NA>반납2452
197621761810004092020-02-10 18:262020-02-10 19:32<NA><NA>반납5526
407894651748011600000002020-05-07 16:382020-05-21 00:06<NA><NA>반납1034
519733598848011900000002020-04-21 02:102020-04-25 11:34<NA><NA>반납30903
4368743837633314372020-04-29 20:462020-04-29 20:49<NA><NA>반납10507
210061840348011300000002020-03-31 00:062020-04-14 00:062020-03-22 18:54<NA>반납94154
5299398048011600000002020-02-18 22:342020-02-27 00:09<NA><NA>반납847
456244327930218282020-04-28 15:422020-04-28 15:42<NA><NA>반납104767