Overview

Dataset statistics

Number of variables11
Number of observations592
Missing cells480
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.2 KiB
Average record size in memory90.2 B

Variable types

Categorical5
Numeric2
Text4

Dataset

Description울산광역시_동구_작은도서관_대출현황관리에 대한 데이터로 발행형태구분, 대출형태, 반납형태 등의 정보를 포함하고 있습니다
Author울산광역시 동구
URLhttps://www.data.go.kr/data/15050254/fileData.do

Alerts

기준일자 has constant value ""Constant
대출일자 is highly overall correlated with 연체일수 and 2 other fieldsHigh correlation
작성일자 is highly overall correlated with 연체일수 and 2 other fieldsHigh correlation
연체일수 is highly overall correlated with 대출일자 and 2 other fieldsHigh correlation
반납일자 is highly overall correlated with 대출일자 and 1 other fieldsHigh correlation
작업장 is highly overall correlated with 연체일수High correlation
작가 has 7 (1.2%) missing valuesMissing
출판사 has 10 (1.7%) missing valuesMissing
연체일수 has 460 (77.7%) missing valuesMissing
등록번호 has unique valuesUnique
연체일수 has 30 (5.1%) zerosZeros

Reproduction

Analysis started2024-03-14 22:43:21.969853
Analysis finished2024-03-14 22:43:25.426348
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대출일자
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-01-27
110 
2024-01-31
93 
2024-01-28
93 
2024-01-30
88 
2024-01-26
62 
Other values (16)
146 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row2024-01-02
2nd row2024-01-02
3rd row2024-01-03
4th row2024-01-03
5th row2024-01-03

Common Values

ValueCountFrequency (%)
2024-01-27 110
18.6%
2024-01-31 93
15.7%
2024-01-28 93
15.7%
2024-01-30 88
14.9%
2024-01-26 62
10.5%
2024-01-24 36
 
6.1%
2024-01-25 17
 
2.9%
2024-01-21 15
 
2.5%
2024-01-19 14
 
2.4%
2024-01-23 13
 
2.2%
Other values (11) 51
8.6%

Length

2024-03-15T07:43:25.554410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-01-27 110
18.6%
2024-01-31 93
15.7%
2024-01-28 93
15.7%
2024-01-30 88
14.9%
2024-01-26 62
10.5%
2024-01-24 36
 
6.1%
2024-01-25 17
 
2.9%
2024-01-21 15
 
2.5%
2024-01-19 14
 
2.4%
2024-01-23 13
 
2.2%
Other values (11) 51
8.6%

반납일자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
460 
24/02/15
90 
24/02/14
 
42

Length

Max length8
Median length4
Mean length4.8918919
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 460
77.7%
24/02/15 90
 
15.2%
24/02/14 42
 
7.1%

Length

2024-03-15T07:43:25.892919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:43:26.215849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 460
77.7%
24/02/15 90
 
15.2%
24/02/14 42
 
7.1%

분류기호
Real number (ℝ)

Distinct156
Distinct (%)26.5%
Missing3
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean673.42757
Minimum1.3
Maximum998.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-03-15T07:43:26.585215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile189.52
Q1490.99
median813.7
Q3818
95-th percentile886.86
Maximum998.34
Range997.04
Interquartile range (IQR)327.01

Descriptive statistics

Standard deviation233.32475
Coefficient of variation (CV)0.34647342
Kurtosis0.13264745
Mean673.42757
Median Absolute Deviation (MAD)29.9
Skewness-1.1361986
Sum396648.84
Variance54440.44
MonotonicityNot monotonic
2024-03-15T07:43:26.874640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
813.8 80
 
13.5%
813.7 45
 
7.6%
818.0 30
 
5.1%
833.6 26
 
4.4%
843.6 20
 
3.4%
747.0 18
 
3.0%
833.8 18
 
3.0%
843.0 15
 
2.5%
375.1 14
 
2.4%
808.9 14
 
2.4%
Other values (146) 309
52.2%
ValueCountFrequency (%)
1.3 3
0.5%
4.73 1
 
0.2%
5.13 1
 
0.2%
5.58 1
 
0.2%
29.1 1
 
0.2%
31.0 3
0.5%
69.5 1
 
0.2%
82.0 6
1.0%
104.0 1
 
0.2%
160.25 1
 
0.2%
ValueCountFrequency (%)
998.34 1
 
0.2%
991.1 1
 
0.2%
990.8 1
 
0.2%
986.6102 2
0.3%
982.0 1
 
0.2%
981.32302 2
0.3%
981.1 2
0.3%
980.24 3
0.5%
911.07 2
0.3%
911.05 1
 
0.2%

등록번호
Text

UNIQUE 

Distinct592
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-03-15T07:43:27.694318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters7104
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique592 ?
Unique (%)100.0%

Sample

1st rowDN0000021989
2nd rowDN0000021534
3rd rowDN0000000618
4th rowDN0000001328
5th rowDN0000026058
ValueCountFrequency (%)
dn0000021989 1
 
0.2%
am0000022339 1
 
0.2%
dn0000022653 1
 
0.2%
dn0000024809 1
 
0.2%
dn0000002445 1
 
0.2%
db0000024809 1
 
0.2%
dn0000015051 1
 
0.2%
dn0000017380 1
 
0.2%
dn0000012272 1
 
0.2%
dn0000019071 1
 
0.2%
Other values (582) 582
98.3%
2024-03-15T07:43:28.991090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3345
47.1%
2 595
 
8.4%
1 397
 
5.6%
N 272
 
3.8%
7 247
 
3.5%
6 237
 
3.3%
5 230
 
3.2%
9 224
 
3.2%
3 223
 
3.1%
4 214
 
3.0%
Other values (10) 1120
 
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5920
83.3%
Uppercase Letter 1184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3345
56.5%
2 595
 
10.1%
1 397
 
6.7%
7 247
 
4.2%
6 237
 
4.0%
5 230
 
3.9%
9 224
 
3.8%
3 223
 
3.8%
4 214
 
3.6%
8 208
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
N 272
23.0%
A 200
16.9%
D 195
16.5%
H 193
16.3%
M 180
15.2%
J 118
10.0%
E 18
 
1.5%
F 3
 
0.3%
S 3
 
0.3%
B 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 5920
83.3%
Latin 1184
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3345
56.5%
2 595
 
10.1%
1 397
 
6.7%
7 247
 
4.2%
6 237
 
4.0%
5 230
 
3.9%
9 224
 
3.8%
3 223
 
3.8%
4 214
 
3.6%
8 208
 
3.5%
Latin
ValueCountFrequency (%)
N 272
23.0%
A 200
16.9%
D 195
16.5%
H 193
16.3%
M 180
15.2%
J 118
10.0%
E 18
 
1.5%
F 3
 
0.3%
S 3
 
0.3%
B 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3345
47.1%
2 595
 
8.4%
1 397
 
5.6%
N 272
 
3.8%
7 247
 
3.5%
6 237
 
3.3%
5 230
 
3.2%
9 224
 
3.2%
3 223
 
3.1%
4 214
 
3.0%
Other values (10) 1120
 
15.8%

도서명
Text

Distinct583
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-03-15T07:43:30.137643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length49
Mean length21.067568
Min length1

Characters and Unicode

Total characters12472
Distinct characters785
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)97.0%

Sample

1st row0~5세 성장 발달에 맞추는 놀이 육아
2nd row나는 이렇게 세 딸을 하버드에 보냈다
3rd row(강방천＆존리와 함께하는) 나의 첫 주식 교과서 : 기본부터 제대로 배우는 평생 투자의 원칙
4th row존리의 부자되기 습관 : 대한민국 경제독립 액션 플랜
5th row설자은, 금성으로 돌아오다 : 정세랑 장편소설
ValueCountFrequency (%)
242
 
7.2%
1 44
 
1.3%
2 44
 
1.3%
장편소설 31
 
0.9%
3 23
 
0.7%
4 20
 
0.6%
이야기 18
 
0.5%
5 17
 
0.5%
만화 13
 
0.4%
손오공의 12
 
0.4%
Other values (1997) 2901
86.2%
2024-03-15T07:43:31.824056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2776
 
22.3%
: 239
 
1.9%
. 221
 
1.8%
의 219
 
1.8%
이 200
 
1.6%
는 156
 
1.3%
, 140
 
1.1%
1 106
 
0.8%
지 105
 
0.8%
기 99
 
0.8%
Other values (775) 8211
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7483
60.0%
Space Separator 2776
 
22.3%
Other Punctuation 706
 
5.7%
Lowercase Letter 701
 
5.6%
Decimal Number 388
 
3.1%
Uppercase Letter 172
 
1.4%
Open Punctuation 104
 
0.8%
Close Punctuation 104
 
0.8%
Math Symbol 27
 
0.2%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 219
 
2.9%
이 200
 
2.7%
는 156
 
2.1%
지 105
 
1.4%
기 99
 
1.3%
리 99
 
1.3%
한 94
 
1.3%
사 93
 
1.2%
가 92
 
1.2%
자 84
 
1.1%
Other values (699) 6242
83.4%
Lowercase Letter
ValueCountFrequency (%)
e 92
13.1%
o 68
 
9.7%
a 66
 
9.4%
r 48
 
6.8%
i 47
 
6.7%
s 43
 
6.1%
t 43
 
6.1%
n 41
 
5.8%
h 40
 
5.7%
y 28
 
4.0%
Other values (14) 185
26.4%
Uppercase Letter
ValueCountFrequency (%)
T 23
13.4%
D 21
12.2%
G 14
 
8.1%
M 12
 
7.0%
S 12
 
7.0%
W 11
 
6.4%
A 10
 
5.8%
N 9
 
5.2%
K 9
 
5.2%
L 8
 
4.7%
Other values (13) 43
25.0%
Other Punctuation
ValueCountFrequency (%)
: 239
33.9%
. 221
31.3%
, 140
19.8%
! 47
 
6.7%
? 19
 
2.7%
' 17
 
2.4%
· 15
 
2.1%
/ 6
 
0.8%
＆ 1
 
0.1%
& 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 106
27.3%
2 67
17.3%
3 42
 
10.8%
0 39
 
10.1%
4 34
 
8.8%
5 32
 
8.2%
7 20
 
5.2%
9 18
 
4.6%
8 17
 
4.4%
6 13
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 98
94.2%
[ 6
 
5.8%
Close Punctuation
ValueCountFrequency (%)
) 98
94.2%
] 6
 
5.8%
Math Symbol
ValueCountFrequency (%)
= 22
81.5%
~ 5
 
18.5%
Space Separator
ValueCountFrequency (%)
2776
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7468
59.9%
Common 4116
33.0%
Latin 873
 
7.0%
Hiragana 8
 
0.1%
Han 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 219
 
2.9%
이 200
 
2.7%
는 156
 
2.1%
지 105
 
1.4%
기 99
 
1.3%
리 99
 
1.3%
한 94
 
1.3%
사 93
 
1.2%
가 92
 
1.2%
자 84
 
1.1%
Other values (684) 6227
83.4%
Latin
ValueCountFrequency (%)
e 92
 
10.5%
o 68
 
7.8%
a 66
 
7.6%
r 48
 
5.5%
i 47
 
5.4%
s 43
 
4.9%
t 43
 
4.9%
n 41
 
4.7%
h 40
 
4.6%
y 28
 
3.2%
Other values (37) 357
40.9%
Common
ValueCountFrequency (%)
2776
67.4%
: 239
 
5.8%
. 221
 
5.4%
, 140
 
3.4%
1 106
 
2.6%
( 98
 
2.4%
) 98
 
2.4%
2 67
 
1.6%
! 47
 
1.1%
3 42
 
1.0%
Other values (19) 282
 
6.9%
Hiragana
ValueCountFrequency (%)
せ 1
12.5%
こ 1
12.5%
の 1
12.5%
お 1
12.5%
み 1
12.5%
な 1
12.5%
あ 1
12.5%
に 1
12.5%
Han
ValueCountFrequency (%)
知 1
14.3%
輝 1
14.3%
善 1
14.3%
決 1
14.3%
信 1
14.3%
號 1
14.3%
大 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7468
59.9%
ASCII 4973
39.9%
None 16
 
0.1%
Hiragana 8
 
0.1%
CJK 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2776
55.8%
: 239
 
4.8%
. 221
 
4.4%
, 140
 
2.8%
1 106
 
2.1%
( 98
 
2.0%
) 98
 
2.0%
e 92
 
1.8%
o 68
 
1.4%
2 67
 
1.3%
Other values (64) 1068
 
21.5%
Hangul
ValueCountFrequency (%)
의 219
 
2.9%
이 200
 
2.7%
는 156
 
2.1%
지 105
 
1.4%
기 99
 
1.3%
리 99
 
1.3%
한 94
 
1.3%
사 93
 
1.2%
가 92
 
1.2%
자 84
 
1.1%
Other values (684) 6227
83.4%
None
ValueCountFrequency (%)
· 15
93.8%
＆ 1
 
6.2%
Hiragana
ValueCountFrequency (%)
せ 1
12.5%
こ 1
12.5%
の 1
12.5%
お 1
12.5%
み 1
12.5%
な 1
12.5%
あ 1
12.5%
に 1
12.5%
CJK
ValueCountFrequency (%)
知 1
14.3%
輝 1
14.3%
善 1
14.3%
決 1
14.3%
信 1
14.3%
號 1
14.3%
大 1
14.3%

작가
Text

MISSING 

Distinct452
Distinct (%)77.3%
Missing7
Missing (%)1.2%
Memory size4.8 KiB
2024-03-15T07:43:33.032228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length47
Mean length16.290598
Min length2

Characters and Unicode

Total characters9530
Distinct characters484
Distinct categories7 ?
Distinct scripts6 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique378 ?
Unique (%)64.6%

Sample

1st row김원철 외 지음 ; 전선진 그림
2nd row심활경 지음
3rd row강방천 ; 존리 지음 ; 정민영 일러스트
4th row존리 지음
5th row정세랑 지음
ValueCountFrequency (%)
449
 
15.9%
지음 241
 
8.5%
그림 199
 
7.0%
글 159
 
5.6%
옮김 141
 
5.0%
글·그림 64
 
2.3%
원작 49
 
1.7%
by 31
 
1.1%
만화 22
 
0.8%
편 11
 
0.4%
Other values (965) 1463
51.7%
2024-03-15T07:43:34.709714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2263
23.7%
; 457
 
4.8%
지 292
 
3.1%
그 290
 
3.0%
김 290
 
3.0%
림 274
 
2.9%
음 255
 
2.7%
글 244
 
2.6%
이 160
 
1.7%
옮 143
 
1.5%
Other values (474) 4862
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5606
58.8%
Space Separator 2263
23.7%
Lowercase Letter 804
 
8.4%
Other Punctuation 612
 
6.4%
Uppercase Letter 165
 
1.7%
Close Punctuation 40
 
0.4%
Open Punctuation 40
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 292
 
5.2%
그 290
 
5.2%
김 290
 
5.2%
림 274
 
4.9%
음 255
 
4.5%
글 244
 
4.4%
이 160
 
2.9%
옮 143
 
2.6%
정 104
 
1.9%
스 95
 
1.7%
Other values (416) 3459
61.7%
Lowercase Letter
ValueCountFrequency (%)
t 82
 
10.2%
o 79
 
9.8%
i 68
 
8.5%
a 66
 
8.2%
y 61
 
7.6%
e 58
 
7.2%
r 57
 
7.1%
n 50
 
6.2%
s 41
 
5.1%
u 37
 
4.6%
Other values (14) 205
25.5%
Uppercase Letter
ValueCountFrequency (%)
K 18
 
10.9%
R 13
 
7.9%
A 13
 
7.9%
M 12
 
7.3%
C 11
 
6.7%
D 11
 
6.7%
H 10
 
6.1%
S 8
 
4.8%
J 8
 
4.8%
T 8
 
4.8%
Other values (13) 53
32.1%
Other Punctuation
ValueCountFrequency (%)
; 457
74.7%
· 74
 
12.1%
. 35
 
5.7%
, 32
 
5.2%
: 11
 
1.8%
/ 3
 
0.5%
Close Punctuation
ValueCountFrequency (%)
] 32
80.0%
) 8
 
20.0%
Open Punctuation
ValueCountFrequency (%)
[ 32
80.0%
( 8
 
20.0%
Space Separator
ValueCountFrequency (%)
2263
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5594
58.7%
Common 2955
31.0%
Latin 969
 
10.2%
Hiragana 7
 
0.1%
Katakana 4
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 292
 
5.2%
그 290
 
5.2%
김 290
 
5.2%
림 274
 
4.9%
음 255
 
4.6%
글 244
 
4.4%
이 160
 
2.9%
옮 143
 
2.6%
정 104
 
1.9%
스 95
 
1.7%
Other values (405) 3447
61.6%
Latin
ValueCountFrequency (%)
t 82
 
8.5%
o 79
 
8.2%
i 68
 
7.0%
a 66
 
6.8%
y 61
 
6.3%
e 58
 
6.0%
r 57
 
5.9%
n 50
 
5.2%
s 41
 
4.2%
u 37
 
3.8%
Other values (37) 370
38.2%
Common
ValueCountFrequency (%)
2263
76.6%
; 457
 
15.5%
· 74
 
2.5%
. 35
 
1.2%
] 32
 
1.1%
, 32
 
1.1%
[ 32
 
1.1%
: 11
 
0.4%
( 8
 
0.3%
) 8
 
0.3%
Hiragana
ValueCountFrequency (%)
う 2
28.6%
た 1
14.3%
こ 1
14.3%
し 1
14.3%
ろ 1
14.3%
は 1
14.3%
Katakana
ValueCountFrequency (%)
ト 1
25.0%
イ 1
25.0%
ラ 1
25.0%
ス 1
25.0%
Han
ValueCountFrequency (%)
著 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5594
58.7%
ASCII 3850
40.4%
None 74
 
0.8%
Hiragana 7
 
0.1%
Katakana 4
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2263
58.8%
; 457
 
11.9%
t 82
 
2.1%
o 79
 
2.1%
i 68
 
1.8%
a 66
 
1.7%
y 61
 
1.6%
e 58
 
1.5%
r 57
 
1.5%
n 50
 
1.3%
Other values (47) 609
 
15.8%
Hangul
ValueCountFrequency (%)
지 292
 
5.2%
그 290
 
5.2%
김 290
 
5.2%
림 274
 
4.9%
음 255
 
4.6%
글 244
 
4.4%
이 160
 
2.9%
옮 143
 
2.6%
정 104
 
1.9%
스 95
 
1.7%
Other values (405) 3447
61.6%
None
ValueCountFrequency (%)
· 74
100.0%
Hiragana
ValueCountFrequency (%)
う 2
28.6%
た 1
14.3%
こ 1
14.3%
し 1
14.3%
ろ 1
14.3%
は 1
14.3%
Katakana
ValueCountFrequency (%)
ト 1
25.0%
イ 1
25.0%
ラ 1
25.0%
ス 1
25.0%
CJK
ValueCountFrequency (%)
著 1
100.0%

출판사
Text

MISSING 

Distinct263
Distinct (%)45.2%
Missing10
Missing (%)1.7%
Memory size4.8 KiB
2024-03-15T07:43:35.886656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length4.733677
Min length1

Characters and Unicode

Total characters2755
Distinct characters331
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)28.2%

Sample

1st row마음책방
2nd row쌤앤파커스
3rd rowPage2
4th row지식노마드
5th row문학동네
ValueCountFrequency (%)
비룡소 21
 
3.4%
창비 19
 
3.1%
학산문화사 16
 
2.6%
아울북 15
 
2.4%
문학동네 14
 
2.3%
미래엔 14
 
2.3%
서울문화사 13
 
2.1%
위즈덤하우스 12
 
1.9%
아이세움 11
 
1.8%
사계절 10
 
1.6%
Other values (266) 471
76.5%
2024-03-15T07:43:37.311538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 106
 
3.8%
이 87
 
3.2%
북 84
 
3.0%
사 79
 
2.9%
아 63
 
2.3%
비 54
 
2.0%
o 53
 
1.9%
문 53
 
1.9%
어 47
 
1.7%
s 46
 
1.7%
Other values (321) 2083
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2249
81.6%
Lowercase Letter 362
 
13.1%
Uppercase Letter 78
 
2.8%
Space Separator 37
 
1.3%
Open Punctuation 11
 
0.4%
Close Punctuation 11
 
0.4%
Decimal Number 4
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 106
 
4.7%
이 87
 
3.9%
북 84
 
3.7%
사 79
 
3.5%
아 63
 
2.8%
비 54
 
2.4%
문 53
 
2.4%
어 47
 
2.1%
미 43
 
1.9%
산 39
 
1.7%
Other values (267) 1594
70.9%
Lowercase Letter
ValueCountFrequency (%)
o 53
14.6%
s 46
12.7%
r 36
9.9%
i 32
 
8.8%
e 31
 
8.6%
n 20
 
5.5%
k 19
 
5.2%
a 14
 
3.9%
p 13
 
3.6%
l 12
 
3.3%
Other values (13) 86
23.8%
Uppercase Letter
ValueCountFrequency (%)
B 17
21.8%
P 10
12.8%
G 6
 
7.7%
O 6
 
7.7%
U 6
 
7.7%
H 5
 
6.4%
R 5
 
6.4%
T 4
 
5.1%
K 3
 
3.8%
F 2
 
2.6%
Other values (11) 14
17.9%
Other Punctuation
ValueCountFrequency (%)
: 1
33.3%
& 1
33.3%
· 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 10
90.9%
[ 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 10
90.9%
] 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%
Space Separator
ValueCountFrequency (%)
37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2245
81.5%
Latin 440
 
16.0%
Common 66
 
2.4%
Katakana 3
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 106
 
4.7%
이 87
 
3.9%
북 84
 
3.7%
사 79
 
3.5%
아 63
 
2.8%
비 54
 
2.4%
문 53
 
2.4%
어 47
 
2.1%
미 43
 
1.9%
산 39
 
1.7%
Other values (263) 1590
70.8%
Latin
ValueCountFrequency (%)
o 53
 
12.0%
s 46
 
10.5%
r 36
 
8.2%
i 32
 
7.3%
e 31
 
7.0%
n 20
 
4.5%
k 19
 
4.3%
B 17
 
3.9%
a 14
 
3.2%
p 13
 
3.0%
Other values (34) 159
36.1%
Common
ValueCountFrequency (%)
37
56.1%
( 10
 
15.2%
) 10
 
15.2%
2 3
 
4.5%
: 1
 
1.5%
1 1
 
1.5%
& 1
 
1.5%
] 1
 
1.5%
· 1
 
1.5%
[ 1
 
1.5%
Katakana
ValueCountFrequency (%)
ラ 1
33.3%
プ 1
33.3%
ポ 1
33.3%
Han
ValueCountFrequency (%)
社 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2245
81.5%
ASCII 505
 
18.3%
Katakana 3
 
0.1%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 106
 
4.7%
이 87
 
3.9%
북 84
 
3.7%
사 79
 
3.5%
아 63
 
2.8%
비 54
 
2.4%
문 53
 
2.4%
어 47
 
2.1%
미 43
 
1.9%
산 39
 
1.7%
Other values (263) 1590
70.8%
ASCII
ValueCountFrequency (%)
o 53
 
10.5%
s 46
 
9.1%
37
 
7.3%
r 36
 
7.1%
i 32
 
6.3%
e 31
 
6.1%
n 20
 
4.0%
k 19
 
3.8%
B 17
 
3.4%
a 14
 
2.8%
Other values (43) 200
39.6%
CJK
ValueCountFrequency (%)
社 1
100.0%
Katakana
ValueCountFrequency (%)
ラ 1
33.3%
プ 1
33.3%
ポ 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

연체일수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct11
Distinct (%)8.3%
Missing460
Missing (%)77.7%
Infinite0
Infinite (%)0.0%
Mean2.969697
Minimum0
Maximum29
Zeros30
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size5.3 KiB
2024-03-15T07:43:37.693591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile13.9
Maximum29
Range29
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.7565774
Coefficient of variation (CV)1.6017046
Kurtosis11.268022
Mean2.969697
Median Absolute Deviation (MAD)0.5
Skewness3.1798076
Sum392
Variance22.625029
MonotonicityNot monotonic
2024-03-15T07:43:38.055154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 66
 
11.1%
0 30
 
5.1%
1 17
 
2.9%
8 4
 
0.7%
7 4
 
0.7%
15 3
 
0.5%
11 3
 
0.5%
19 2
 
0.3%
29 1
 
0.2%
25 1
 
0.2%
(Missing) 460
77.7%
ValueCountFrequency (%)
0 30
5.1%
1 17
 
2.9%
2 66
11.1%
7 4
 
0.7%
8 4
 
0.7%
11 3
 
0.5%
13 1
 
0.2%
15 3
 
0.5%
19 2
 
0.3%
25 1
 
0.2%
ValueCountFrequency (%)
29 1
 
0.2%
25 1
 
0.2%
19 2
 
0.3%
15 3
 
0.5%
13 1
 
0.2%
11 3
 
0.5%
8 4
 
0.7%
7 4
 
0.7%
2 66
11.1%
1 17
 
2.9%

작업장
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
KLAS
368 
2F대출기
109 
대출반납기
61 
1F대출기1
 
32
1F대출기2
 
16

Length

Max length6
Median length4
Mean length4.4594595
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2F대출기
2nd row2F대출기
3rd row2F대출기
4th row2F대출기
5th row2F대출기

Common Values

ValueCountFrequency (%)
KLAS 368
62.2%
2F대출기 109
 
18.4%
대출반납기 61
 
10.3%
1F대출기1 32
 
5.4%
1F대출기2 16
 
2.7%
예약대출기 6
 
1.0%

Length

2024-03-15T07:43:38.484801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:43:38.855007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
klas 368
62.2%
2f대출기 109
 
18.4%
대출반납기 61
 
10.3%
1f대출기1 32
 
5.4%
1f대출기2 16
 
2.7%
예약대출기 6
 
1.0%

작성일자
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-01-27
110 
2024-01-31
93 
2024-01-28
93 
2024-01-30
88 
2024-01-26
62 
Other values (16)
146 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row2024-01-02
2nd row2024-01-02
3rd row2024-01-03
4th row2024-01-03
5th row2024-01-03

Common Values

ValueCountFrequency (%)
2024-01-27 110
18.6%
2024-01-31 93
15.7%
2024-01-28 93
15.7%
2024-01-30 88
14.9%
2024-01-26 62
10.5%
2024-01-24 36
 
6.1%
2024-01-25 17
 
2.9%
2024-01-21 15
 
2.5%
2024-01-19 14
 
2.4%
2024-01-23 13
 
2.2%
Other values (11) 51
8.6%

Length

2024-03-15T07:43:39.235821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-01-27 110
18.6%
2024-01-31 93
15.7%
2024-01-28 93
15.7%
2024-01-30 88
14.9%
2024-01-26 62
10.5%
2024-01-24 36
 
6.1%
2024-01-25 17
 
2.9%
2024-01-21 15
 
2.5%
2024-01-19 14
 
2.4%
2024-01-23 13
 
2.2%
Other values (11) 51
8.6%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-01-31
592 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-31
2nd row2024-01-31
3rd row2024-01-31
4th row2024-01-31
5th row2024-01-31

Common Values

ValueCountFrequency (%)
2024-01-31 592
100.0%

Length

2024-03-15T07:43:39.616686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:43:39.857281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-31 592
100.0%

Interactions

2024-03-15T07:43:23.960854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:43:23.584702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:43:24.193405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:43:23.761936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T07:43:40.158771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출일자반납일자분류기호연체일수작업장작성일자
대출일자1.0000.7450.5361.0000.5011.000
반납일자0.7451.0000.0000.3820.2390.745
분류기호0.5360.0001.0000.6360.3090.536
연체일수1.0000.3820.6361.0000.6851.000
작업장0.5010.2390.3090.6851.0000.501
작성일자1.0000.7450.5361.0000.5011.000
2024-03-15T07:43:40.411457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
작업장대출일자작성일자반납일자
작업장1.0000.2480.2480.289
대출일자0.2481.0001.0000.681
작성일자0.2481.0001.0000.681
반납일자0.2890.6810.6811.000
2024-03-15T07:43:40.676031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류기호연체일수대출일자반납일자작업장작성일자
분류기호1.000-0.2010.2270.0000.1670.227
연체일수-0.2011.0000.9800.2800.5040.980
대출일자0.2270.9801.0000.6810.2481.000
반납일자0.0000.2800.6811.0000.2890.681
작업장0.1670.5040.2480.2891.0000.248
작성일자0.2270.9801.0000.6810.2481.000

Missing values

2024-03-15T07:43:24.466808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T07:43:24.864424image/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.
2024-03-15T07:43:25.233343image/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

대출일자반납일자분류기호등록번호도서명작가출판사연체일수작업장작성일자기준일자
02024-01-02<NA>598.1DN00000219890~5세 성장 발달에 맞추는 놀이 육아김원철 외 지음 ; 전선진 그림마음책방<NA>2F대출기2024-01-022024-01-31
12024-01-02<NA>598.1DN0000021534나는 이렇게 세 딸을 하버드에 보냈다심활경 지음쌤앤파커스<NA>2F대출기2024-01-022024-01-31
22024-01-03<NA>327.856DN0000000618(강방천＆존리와 함께하는) 나의 첫 주식 교과서 : 기본부터 제대로 배우는 평생 투자의 원칙강방천 ; 존리 지음 ; 정민영 일러스트Page2<NA>2F대출기2024-01-032024-01-31
32024-01-03<NA>327.04DN0000001328존리의 부자되기 습관 : 대한민국 경제독립 액션 플랜존리 지음지식노마드<NA>2F대출기2024-01-032024-01-31
42024-01-03<NA>813.7DN0000026058설자은, 금성으로 돌아오다 : 정세랑 장편소설정세랑 지음문학동네<NA>2F대출기2024-01-032024-01-31
52024-01-03<NA>814.7DN0000026192겨울의 언어 : 김겨울 산문집김겨울 지음웅진지식하우스<NA>2F대출기2024-01-032024-01-31
62024-01-03<NA>859.82DN0000026038보트하우스 : 욘 표세 장편소설욘 표세 지음 ; 홍재웅 옮김새움<NA>2F대출기2024-01-032024-01-31
72024-01-03<NA>813.7DN0000026187해피 엔드 : 이주란 소설이주란 지음창비<NA>2F대출기2024-01-032024-01-31
82024-01-03<NA>813.7DN0000026167테디베어는 죽지 않아 : 조예은 장편소설조예은 지음안전가옥<NA>2F대출기2024-01-032024-01-31
92024-01-03<NA>833.6AM0000021057어느 날, 내 죽음에 네가 들어왔다세이카 료겐 지음 ; 김윤경 옮김모모(바이포엠스튜디오)<NA>2F대출기2024-01-032024-01-31
대출일자반납일자분류기호등록번호도서명작가출판사연체일수작업장작성일자기준일자
5822024-01-3124/02/14813.8DN0000020150브레드 이발소=Bread barbershop. 6, 달콤쌉쌀 브레드의 추억몬스터 스튜디오 원작·그림한솔수북01F대출기12024-01-312024-01-31
5832024-01-3124/02/15833.8HA0000027488뼈뼈 사우루스. 15, 사라진 왕국, '뼈뼈란티스'의 비밀암모나이트 글·그림 ; 김정화 옮김미래엔1KLAS2024-01-312024-01-31
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