Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells19352
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://www.data.go.kr/data/15097804/fileData.do

Alerts

대출상태 is highly imbalanced (87.7%)Imbalance
대출일 has 298 (3.0%) missing valuesMissing
반납일 has 298 (3.0%) missing valuesMissing
예약일 has 9053 (90.5%) missing valuesMissing
예약취소일 has 9703 (97.0%) missing valuesMissing
대출번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:58:09.609751
Analysis finished2023-12-11 23:58:10.854086
Duration1.24 second
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%
Mean33433.114
Minimum1
Maximum79549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:58:10.928160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3223.95
Q116078.5
median32585.5
Q348993.5
95-th percentile76428.25
Maximum79549
Range79548
Interquartile range (IQR)32915

Descriptive statistics

Standard deviation20480.938
Coefficient of variation (CV)0.6125944
Kurtosis-0.71639246
Mean33433.114
Median Absolute Deviation (MAD)16463.5
Skewness0.2900132
Sum3.3433114 × 108
Variance4.1946883 × 108
MonotonicityNot monotonic
2023-12-12T08:58:11.058273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3962 1
 
< 0.1%
60248 1
 
< 0.1%
21781 1
 
< 0.1%
46566 1
 
< 0.1%
37299 1
 
< 0.1%
31712 1
 
< 0.1%
34636 1
 
< 0.1%
34728 1
 
< 0.1%
62289 1
 
< 0.1%
7891 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
11 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
26 1
< 0.1%
28 1
< 0.1%
33 1
< 0.1%
40 1
< 0.1%
46 1
< 0.1%
ValueCountFrequency (%)
79549 1
< 0.1%
79548 1
< 0.1%
79541 1
< 0.1%
79534 1
< 0.1%
79527 1
< 0.1%
79521 1
< 0.1%
79512 1
< 0.1%
79511 1
< 0.1%
79501 1
< 0.1%
79492 1
< 0.1%

도서번호
Text

Distinct3868
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:58:11.346971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length14
Mean length10.9678
Min length2

Characters and Unicode

Total characters109678
Distinct characters26
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

Unique3002 ?
Unique (%)30.0%

Sample

1st row4801160000000
2nd row180500393
3rd row4808970000000
4th row975626
5th row822776
ValueCountFrequency (%)
4801190000000 1023
 
10.2%
4801160000000 1003
 
10.0%
4808960000000 281
 
2.8%
4808970000000 266
 
2.7%
4808950000000 249
 
2.5%
4808930000000 234
 
2.3%
4801200000000 198
 
2.0%
4808990000000 182
 
1.8%
4801130000000 166
 
1.7%
4809000000000 128
 
1.3%
Other values (3858) 6270
62.7%
2023-12-12T08:58:11.755038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44349
40.4%
1 11997
 
10.9%
9682
 
8.8%
8 9305
 
8.5%
4 7076
 
6.5%
9 6569
 
6.0%
2 4626
 
4.2%
6 4431
 
4.0%
3 3790
 
3.5%
7 3696
 
3.4%
Other values (16) 4157
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99508
90.7%
Space Separator 9682
 
8.8%
Uppercase Letter 424
 
0.4%
Dash Punctuation 48
 
< 0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44349
44.6%
1 11997
 
12.1%
8 9305
 
9.4%
4 7076
 
7.1%
9 6569
 
6.6%
2 4626
 
4.6%
6 4431
 
4.5%
3 3790
 
3.8%
7 3696
 
3.7%
5 3669
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 190
44.8%
D 120
28.3%
X 46
 
10.8%
C 19
 
4.5%
E 17
 
4.0%
B 17
 
4.0%
F 11
 
2.6%
M 4
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
a 7
43.8%
b 3
18.8%
c 2
 
12.5%
d 2
 
12.5%
f 1
 
6.2%
e 1
 
6.2%
Space Separator
ValueCountFrequency (%)
9682
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109238
99.6%
Latin 440
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 190
43.2%
D 120
27.3%
X 46
 
10.5%
C 19
 
4.3%
E 17
 
3.9%
B 17
 
3.9%
F 11
 
2.5%
a 7
 
1.6%
M 4
 
0.9%
b 3
 
0.7%
Other values (4) 6
 
1.4%
Common
ValueCountFrequency (%)
0 44349
40.6%
1 11997
 
11.0%
9682
 
8.9%
8 9305
 
8.5%
4 7076
 
6.5%
9 6569
 
6.0%
2 4626
 
4.2%
6 4431
 
4.1%
3 3790
 
3.5%
7 3696
 
3.4%
Other values (2) 3717
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109678
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44349
40.4%
1 11997
 
10.9%
9682
 
8.8%
8 9305
 
8.5%
4 7076
 
6.5%
9 6569
 
6.0%
2 4626
 
4.2%
6 4431
 
4.0%
3 3790
 
3.5%
7 3696
 
3.4%
Other values (16) 4157
 
3.8%

대출일
Date

MISSING 

Distinct8911
Distinct (%)91.8%
Missing298
Missing (%)3.0%
Memory size156.2 KiB
Minimum2020-01-06 09:01:00
Maximum2020-10-27 00:05:00
2023-12-12T08:58:11.896903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:12.038352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

반납일
Date

MISSING 

Distinct5576
Distinct (%)57.5%
Missing298
Missing (%)3.0%
Memory size156.2 KiB
Minimum2020-01-06 09:08:00
Maximum2020-11-10 00:04:00
2023-12-12T08:58:12.161052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:12.288430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예약일
Date

MISSING 

Distinct937
Distinct (%)98.9%
Missing9053
Missing (%)90.5%
Memory size156.2 KiB
Minimum2020-01-09 13:46:00
Maximum2020-08-26 23:13:00
2023-12-12T08:58:12.427800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:12.557427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

예약취소일
Date

MISSING 

Distinct264
Distinct (%)88.9%
Missing9703
Missing (%)97.0%
Memory size156.2 KiB
Minimum2020-02-03 17:58:00
Maximum2020-09-20 21:29:00
2023-12-12T08:58:12.691343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:12.822620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대출상태
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
반납
9702 
예약취소
 
297
예약
 
1

Length

Max length4
Median length2
Mean length2.0594
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
반납 9702
97.0%
예약취소 297
 
3.0%
예약 1
 
< 0.1%

Length

2023-12-12T08:58:13.010985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:58:13.104112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
반납 9702
97.0%
예약취소 297
 
3.0%
예약 1
 
< 0.1%

도서정보키
Real number (ℝ)

Distinct5753
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38574.889
Minimum1
Maximum119628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:58:13.200786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile713.85
Q13006
median10128.5
Q374548.25
95-th percentile107236.65
Maximum119628
Range119627
Interquartile range (IQR)71542.25

Descriptive statistics

Standard deviation42441.614
Coefficient of variation (CV)1.1002394
Kurtosis-1.2382771
Mean38574.889
Median Absolute Deviation (MAD)9365
Skewness0.66841333
Sum3.857489 × 108
Variance1.8012906 × 109
MonotonicityNot monotonic
2023-12-12T08:58:13.325950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4665 27
 
0.3%
6051 25
 
0.2%
94288 22
 
0.2%
6059 20
 
0.2%
10823 20
 
0.2%
887 20
 
0.2%
600 19
 
0.2%
725 19
 
0.2%
10510 19
 
0.2%
2293 19
 
0.2%
Other values (5743) 9790
97.9%
ValueCountFrequency (%)
1 2
< 0.1%
18 2
< 0.1%
21 3
< 0.1%
28 2
< 0.1%
37 1
 
< 0.1%
43 1
 
< 0.1%
47 1
 
< 0.1%
57 1
 
< 0.1%
62 2
< 0.1%
63 4
< 0.1%
ValueCountFrequency (%)
119628 1
< 0.1%
119622 1
< 0.1%
119552 1
< 0.1%
119512 1
< 0.1%
119505 1
< 0.1%
119502 1
< 0.1%
119471 1
< 0.1%
119461 1
< 0.1%
119456 1
< 0.1%
119445 1
< 0.1%

Interactions

2023-12-12T08:58:10.371254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:10.188314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:10.459257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:58:10.283664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:58:13.405473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출번호대출상태도서정보키
대출번호1.0000.1100.446
대출상태0.1101.0000.135
도서정보키0.4460.1351.000
2023-12-12T08:58:13.490598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출번호도서정보키대출상태
대출번호1.0000.1420.048
도서정보키0.1421.0000.081
대출상태0.0480.0811.000

Missing values

2023-12-12T08:58:10.580850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:58:10.689326image/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.
2023-12-12T08:58:10.788838image/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
5190396248011600000002020-02-23 00:052020-02-27 14:572020-02-18 20:55<NA>반납640
57859792721805003932020-08-26 13:592020-09-09 00:06<NA><NA>반납5099
248231551048089700000002020-03-17 07:272020-03-18 08:25<NA><NA>반납94380
54852616109756262020-07-02 15:052020-07-16 00:06<NA><NA>반납9189
44009439348227762020-04-30 02:262020-05-14 00:06<NA><NA>반납6660
609695452748011900000002020-06-18 00:052020-07-07 00:112020-06-04 20:10<NA>반납31278
1848204610000202020-02-09 18:532020-02-09 18:54<NA><NA>반납6233
466023946310801192020-04-23 15:582020-04-23 15:59<NA><NA>반납100968
21834185884801160000000<NA><NA>2020-03-22 23:432020-03-25 00:06예약취소773
96411094448089700000002020-03-09 15:162020-03-23 00:06<NA><NA>반납73597
대출번호도서번호대출일반납일예약일예약취소일대출상태도서정보키
425054778748011900000002020-06-09 00:082020-07-07 00:062020-05-11 22:15<NA>반납1643
378512657758000500000002020-04-07 20:112020-04-21 00:06<NA><NA>반납311
188742078248011300000002020-03-26 22:492020-04-09 00:06<NA><NA>반납94161
635955710748011600000002020-06-18 00:082020-07-07 00:442020-06-15 15:12<NA>반납863
4244312748012000000002020-02-14 23:102020-02-28 00:05<NA><NA>반납1947
3473823694722637882020-04-02 02:032020-04-02 02:04<NA><NA>반납10535
3523317048089700000002020-02-15 03:312020-02-23 17:06<NA><NA>반납32485
60191590839056842020-06-23 21:402020-07-07 00:09<NA><NA>반납7822
498753880730404782020-04-23 10:012020-04-23 10:02<NA><NA>반납104944
35329610038612020-01-09 01:222020-01-23 00:05<NA><NA>반납6312