Overview

Dataset statistics

Number of variables17
Number of observations988
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory136.2 KiB
Average record size in memory141.1 B

Variable types

Numeric3
Text5
Categorical9

Dataset

Description자료코드,등록번호,자료명,저자,출판사,발행년,청구기호,분류기호,언어,언어명,국가명,소장처,소장처명,자료실 코드,자료실 이름,대출상태,대출상태메시지
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22194/S/1/datasetView.do

Alerts

소장처 has constant value ""Constant
소장처명 has constant value ""Constant
자료실 코드 has constant value ""Constant
자료실 이름 has constant value ""Constant
대출상태 is highly overall correlated with 언어명 and 1 other fieldsHigh correlation
언어 is highly overall correlated with 언어명High correlation
대출상태메시지 is highly overall correlated with 언어명 and 1 other fieldsHigh correlation
국가명 is highly overall correlated with 언어명High correlation
언어명 is highly overall correlated with 자료코드 and 6 other fieldsHigh correlation
자료코드 is highly overall correlated with 발행년 and 1 other fieldsHigh correlation
발행년 is highly overall correlated with 자료코드 and 1 other fieldsHigh correlation
분류기호 is highly overall correlated with 언어명High correlation
언어 is highly imbalanced (97.9%)Imbalance
언어명 is highly imbalanced (97.9%)Imbalance
국가명 is highly imbalanced (61.3%)Imbalance
자료코드 has unique valuesUnique
등록번호 has unique valuesUnique
자료명 has unique valuesUnique
청구기호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 01:49:01.434889
Analysis finished2024-05-04 01:49:08.360930
Duration6.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자료코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct988
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1508700.1
Minimum1315
Maximum1645306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-04T01:49:08.579319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1315
5-th percentile1303147.8
Q11481844.2
median1570522.5
Q31620021.5
95-th percentile1637982
Maximum1645306
Range1643991
Interquartile range (IQR)138177.25

Descriptive statistics

Standard deviation218035.14
Coefficient of variation (CV)0.14451854
Kurtosis24.089923
Mean1508700.1
Median Absolute Deviation (MAD)57006
Skewness-4.491484
Sum1.4905957 × 109
Variance4.7539322 × 1010
MonotonicityNot monotonic
2024-05-04T01:49:09.024696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1619744 1
 
0.1%
1577536 1
 
0.1%
1525733 1
 
0.1%
1546919 1
 
0.1%
1573272 1
 
0.1%
1556087 1
 
0.1%
1564285 1
 
0.1%
1610228 1
 
0.1%
1569982 1
 
0.1%
1525741 1
 
0.1%
Other values (978) 978
99.0%
ValueCountFrequency (%)
1315 1
0.1%
2196 1
0.1%
5212 1
0.1%
5397 1
0.1%
9959 1
0.1%
34286 1
0.1%
48328 1
0.1%
162592 1
0.1%
269483 1
0.1%
270510 1
0.1%
ValueCountFrequency (%)
1645306 1
0.1%
1645305 1
0.1%
1645304 1
0.1%
1645301 1
0.1%
1645296 1
0.1%
1645295 1
0.1%
1645291 1
0.1%
1645232 1
0.1%
1645132 1
0.1%
1645118 1
0.1%

등록번호
Text

UNIQUE 

Distinct988
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-05-04T01:49:09.543820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters11856
Distinct characters12
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

Unique988 ?
Unique (%)100.0%

Sample

1st rowEM0000471020
2nd rowEM0000471103
3rd rowEM0000457559
4th rowEM0000471102
5th rowEM0000471085
ValueCountFrequency (%)
em0000471020 1
 
0.1%
em0000454561 1
 
0.1%
em0000458100 1
 
0.1%
em0000458102 1
 
0.1%
em0000454554 1
 
0.1%
em0000454560 1
 
0.1%
em0000470945 1
 
0.1%
em0000457552 1
 
0.1%
em0000470935 1
 
0.1%
em0000457473 1
 
0.1%
Other values (978) 978
99.0%
2024-05-04T01:49:10.459029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4395
37.1%
4 1393
 
11.7%
E 988
 
8.3%
M 988
 
8.3%
7 738
 
6.2%
6 676
 
5.7%
1 587
 
5.0%
3 541
 
4.6%
5 526
 
4.4%
8 416
 
3.5%
Other values (2) 608
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9880
83.3%
Uppercase Letter 1976
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4395
44.5%
4 1393
 
14.1%
7 738
 
7.5%
6 676
 
6.8%
1 587
 
5.9%
3 541
 
5.5%
5 526
 
5.3%
8 416
 
4.2%
9 355
 
3.6%
2 253
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
E 988
50.0%
M 988
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9880
83.3%
Latin 1976
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4395
44.5%
4 1393
 
14.1%
7 738
 
7.5%
6 676
 
6.8%
1 587
 
5.9%
3 541
 
5.5%
5 526
 
5.3%
8 416
 
4.2%
9 355
 
3.6%
2 253
 
2.6%
Latin
ValueCountFrequency (%)
E 988
50.0%
M 988
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4395
37.1%
4 1393
 
11.7%
E 988
 
8.3%
M 988
 
8.3%
7 738
 
6.2%
6 676
 
5.7%
1 587
 
5.0%
3 541
 
4.6%
5 526
 
4.4%
8 416
 
3.5%
Other values (2) 608
 
5.1%

자료명
Text

UNIQUE 

Distinct988
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-05-04T01:49:11.337049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length105
Median length66
Mean length31.092105
Min length2

Characters and Unicode

Total characters30719
Distinct characters961
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique988 ?
Unique (%)100.0%

Sample

1st row경우 없는 세계 :백온유 장편소설
2nd rowG는 파랑 :피아니스트가 음악을 기억하는 방법
3rd row(몸으로 읽는) 세계사 :사소한 몸에 숨겨진 독특하고 거대한 문명의 역사
4th row가장 아끼는 너에게 주고 싶은 말 :도연화 에세이
5th row여행 아닌 여행기 :요시모토 바나나 에세이
ValueCountFrequency (%)
장편소설 129
 
1.7%
위한 60
 
0.8%
법 33
 
0.4%
모든 33
 
0.4%
소설 33
 
0.4%
32
 
0.4%
나는 32
 
0.4%
이야기 30
 
0.4%
어떻게 29
 
0.4%
나를 28
 
0.4%
Other values (4523) 7310
94.3%
2024-05-04T01:49:12.854849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6762
 
22.0%
: 846
 
2.8%
의 651
 
2.1%
는 575
 
1.9%
이 523
 
1.7%
가 337
 
1.1%
하 318
 
1.0%
지 316
 
1.0%
기 309
 
1.0%
한 293
 
1.0%
Other values (951) 19789
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20192
65.7%
Space Separator 6762
 
22.0%
Lowercase Letter 1544
 
5.0%
Other Punctuation 1194
 
3.9%
Decimal Number 425
 
1.4%
Uppercase Letter 263
 
0.9%
Close Punctuation 124
 
0.4%
Open Punctuation 123
 
0.4%
Math Symbol 83
 
0.3%
Dash Punctuation 7
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 651
 
3.2%
는 575
 
2.8%
이 523
 
2.6%
가 337
 
1.7%
하 318
 
1.6%
지 316
 
1.6%
기 309
 
1.5%
한 293
 
1.5%
다 287
 
1.4%
에 287
 
1.4%
Other values (865) 16296
80.7%
Lowercase Letter
ValueCountFrequency (%)
e 170
11.0%
i 141
 
9.1%
t 127
 
8.2%
o 127
 
8.2%
a 113
 
7.3%
n 112
 
7.3%
s 100
 
6.5%
r 93
 
6.0%
h 73
 
4.7%
l 64
 
4.1%
Other values (16) 424
27.5%
Uppercase Letter
ValueCountFrequency (%)
T 54
20.5%
P 27
10.3%
G 26
9.9%
I 22
 
8.4%
A 19
 
7.2%
M 11
 
4.2%
F 11
 
4.2%
S 10
 
3.8%
N 10
 
3.8%
B 10
 
3.8%
Other values (14) 63
24.0%
Other Punctuation
ValueCountFrequency (%)
: 846
70.9%
, 178
 
14.9%
' 46
 
3.9%
? 42
 
3.5%
. 37
 
3.1%
! 28
 
2.3%
% 7
 
0.6%
/ 6
 
0.5%
& 2
 
0.2%
％ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 126
29.6%
1 83
19.5%
2 60
14.1%
3 40
 
9.4%
5 39
 
9.2%
4 21
 
4.9%
8 16
 
3.8%
9 16
 
3.8%
7 12
 
2.8%
6 12
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 118
95.2%
》 2
 
1.6%
] 2
 
1.6%
」 1
 
0.8%
』 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 118
95.9%
《 2
 
1.6%
[ 2
 
1.6%
「 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
= 81
97.6%
~ 2
 
2.4%
Space Separator
ValueCountFrequency (%)
6762
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20180
65.7%
Common 8720
28.4%
Latin 1807
 
5.9%
Han 10
 
< 0.1%
Katakana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 651
 
3.2%
는 575
 
2.8%
이 523
 
2.6%
가 337
 
1.7%
하 318
 
1.6%
지 316
 
1.6%
기 309
 
1.5%
한 293
 
1.5%
다 287
 
1.4%
에 287
 
1.4%
Other values (853) 16284
80.7%
Latin
ValueCountFrequency (%)
e 170
 
9.4%
i 141
 
7.8%
t 127
 
7.0%
o 127
 
7.0%
a 113
 
6.3%
n 112
 
6.2%
s 100
 
5.5%
r 93
 
5.1%
h 73
 
4.0%
l 64
 
3.5%
Other values (40) 687
38.0%
Common
ValueCountFrequency (%)
6762
77.5%
: 846
 
9.7%
, 178
 
2.0%
0 126
 
1.4%
) 118
 
1.4%
( 118
 
1.4%
1 83
 
1.0%
= 81
 
0.9%
2 60
 
0.7%
' 46
 
0.5%
Other values (26) 302
 
3.5%
Han
ValueCountFrequency (%)
詩 1
10.0%
話 1
10.0%
壽 1
10.0%
長 1
10.0%
道 1
10.0%
老 1
10.0%
莊 1
10.0%
小 1
10.0%
食 1
10.0%
富 1
10.0%
Katakana
ValueCountFrequency (%)
バ 1
50.0%
ン 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20180
65.7%
ASCII 10517
34.2%
CJK 9
 
< 0.1%
None 8
 
< 0.1%
Punctuation 2
 
< 0.1%
Katakana 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6762
64.3%
: 846
 
8.0%
, 178
 
1.7%
e 170
 
1.6%
i 141
 
1.3%
t 127
 
1.2%
o 127
 
1.2%
0 126
 
1.2%
) 118
 
1.1%
( 118
 
1.1%
Other values (68) 1804
 
17.2%
Hangul
ValueCountFrequency (%)
의 651
 
3.2%
는 575
 
2.8%
이 523
 
2.6%
가 337
 
1.7%
하 318
 
1.6%
지 316
 
1.6%
기 309
 
1.5%
한 293
 
1.5%
다 287
 
1.4%
에 287
 
1.4%
Other values (853) 16284
80.7%
None
ValueCountFrequency (%)
》 2
25.0%
《 2
25.0%
」 1
12.5%
「 1
12.5%
％ 1
12.5%
』 1
12.5%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%
Katakana
ValueCountFrequency (%)
バ 1
50.0%
ン 1
50.0%
CJK
ValueCountFrequency (%)
詩 1
11.1%
話 1
11.1%
壽 1
11.1%
長 1
11.1%
道 1
11.1%
莊 1
11.1%
小 1
11.1%
食 1
11.1%
富 1
11.1%
CJK Compat Ideographs
ValueCountFrequency (%)
老 1
100.0%

저자
Text

Distinct863
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-05-04T01:49:13.491414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.3663968
Min length2

Characters and Unicode

Total characters7278
Distinct characters495
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique778 ?
Unique (%)78.7%

Sample

1st row백온유 지음
2nd row김지희 지음
3rd row캐스린 페트라스
4th row도연화 지음
5th row요시모토 바나나 지음
ValueCountFrequency (%)
지음 880
37.9%
히가시노 13
 
0.6%
게이고 13
 
0.6%
글 10
 
0.4%
베르베르 9
 
0.4%
베르나르 8
 
0.3%
존 7
 
0.3%
데이비드 6
 
0.3%
리처드 6
 
0.3%
저 6
 
0.3%
Other values (1138) 1365
58.8%
2024-05-04T01:49:14.685318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1335
 
18.3%
지 931
 
12.8%
음 886
 
12.2%
이 187
 
2.6%
김 128
 
1.8%
스 95
 
1.3%
리 93
 
1.3%
정 79
 
1.1%
르 64
 
0.9%
라 55
 
0.8%
Other values (485) 3425
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5844
80.3%
Space Separator 1335
 
18.3%
Lowercase Letter 26
 
0.4%
Other Punctuation 23
 
0.3%
Uppercase Letter 23
 
0.3%
Close Punctuation 12
 
0.2%
Open Punctuation 12
 
0.2%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 931
 
15.9%
음 886
 
15.2%
이 187
 
3.2%
김 128
 
2.2%
스 95
 
1.6%
리 93
 
1.6%
정 79
 
1.4%
르 64
 
1.1%
라 55
 
0.9%
미 54
 
0.9%
Other values (449) 3272
56.0%
Lowercase Letter
ValueCountFrequency (%)
a 6
23.1%
n 3
11.5%
v 2
 
7.7%
o 2
 
7.7%
t 2
 
7.7%
c 2
 
7.7%
h 2
 
7.7%
i 2
 
7.7%
s 1
 
3.8%
m 1
 
3.8%
Other values (3) 3
11.5%
Uppercase Letter
ValueCountFrequency (%)
J 5
21.7%
A 3
13.0%
D 2
 
8.7%
B 2
 
8.7%
F 2
 
8.7%
M 2
 
8.7%
N 1
 
4.3%
S 1
 
4.3%
K 1
 
4.3%
W 1
 
4.3%
Other values (3) 3
13.0%
Other Punctuation
ValueCountFrequency (%)
. 14
60.9%
? 9
39.1%
Close Punctuation
ValueCountFrequency (%)
] 11
91.7%
〉 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
[ 11
91.7%
〈 1
 
8.3%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
1335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5844
80.3%
Common 1385
 
19.0%
Latin 49
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 931
 
15.9%
음 886
 
15.2%
이 187
 
3.2%
김 128
 
2.2%
스 95
 
1.6%
리 93
 
1.6%
정 79
 
1.4%
르 64
 
1.1%
라 55
 
0.9%
미 54
 
0.9%
Other values (449) 3272
56.0%
Latin
ValueCountFrequency (%)
a 6
 
12.2%
J 5
 
10.2%
A 3
 
6.1%
n 3
 
6.1%
D 2
 
4.1%
v 2
 
4.1%
B 2
 
4.1%
o 2
 
4.1%
F 2
 
4.1%
t 2
 
4.1%
Other values (16) 20
40.8%
Common
ValueCountFrequency (%)
1335
96.4%
. 14
 
1.0%
] 11
 
0.8%
[ 11
 
0.8%
? 9
 
0.6%
> 1
 
0.1%
< 1
 
0.1%
〉 1
 
0.1%
〈 1
 
0.1%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5844
80.3%
ASCII 1432
 
19.7%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1335
93.2%
. 14
 
1.0%
] 11
 
0.8%
[ 11
 
0.8%
? 9
 
0.6%
a 6
 
0.4%
J 5
 
0.3%
A 3
 
0.2%
n 3
 
0.2%
D 2
 
0.1%
Other values (24) 33
 
2.3%
Hangul
ValueCountFrequency (%)
지 931
 
15.9%
음 886
 
15.2%
이 187
 
3.2%
김 128
 
2.2%
스 95
 
1.6%
리 93
 
1.6%
정 79
 
1.4%
르 64
 
1.1%
라 55
 
0.9%
미 54
 
0.9%
Other values (449) 3272
56.0%
None
ValueCountFrequency (%)
〉 1
50.0%
〈 1
50.0%

출판사
Text

Distinct468
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-05-04T01:49:15.486544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length6.6912955
Min length1

Characters and Unicode

Total characters6611
Distinct characters428
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)31.4%

Sample

1st row창비
2nd row윌북
3rd row다산초당: 다산북스
4th row부크럼
5th row민음사
ValueCountFrequency (%)
74
 
5.3%
문학동네 56
 
4.0%
창비 30
 
2.1%
다산북스 30
 
2.1%
민음사 25
 
1.8%
김영사 21
 
1.5%
길벗 21
 
1.5%
위즈덤하우스 20
 
1.4%
웅진씽크빅 17
 
1.2%
북이십일 16
 
1.1%
Other values (518) 1090
77.9%
2024-05-04T01:49:16.503766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
412
 
6.2%
스 345
 
5.2%
: 254
 
3.8%
북 219
 
3.3%
이 150
 
2.3%
사 143
 
2.2%
문 98
 
1.5%
) 77
 
1.2%
( 77
 
1.2%
디 75
 
1.1%
Other values (418) 4761
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5102
77.2%
Lowercase Letter 469
 
7.1%
Space Separator 412
 
6.2%
Other Punctuation 261
 
3.9%
Uppercase Letter 178
 
2.7%
Close Punctuation 77
 
1.2%
Open Punctuation 77
 
1.2%
Decimal Number 35
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 345
 
6.8%
북 219
 
4.3%
이 150
 
2.9%
사 143
 
2.8%
문 98
 
1.9%
디 75
 
1.5%
학 74
 
1.5%
비 69
 
1.4%
아 69
 
1.4%
트 67
 
1.3%
Other values (366) 3793
74.3%
Lowercase Letter
ValueCountFrequency (%)
o 62
13.2%
e 59
12.6%
n 44
9.4%
i 44
9.4%
a 36
 
7.7%
t 30
 
6.4%
s 30
 
6.4%
k 27
 
5.8%
l 21
 
4.5%
r 18
 
3.8%
Other values (13) 98
20.9%
Uppercase Letter
ValueCountFrequency (%)
B 28
15.7%
R 24
13.5%
H 19
10.7%
K 16
9.0%
M 11
 
6.2%
P 11
 
6.2%
F 9
 
5.1%
A 8
 
4.5%
C 7
 
3.9%
W 6
 
3.4%
Other values (9) 39
21.9%
Other Punctuation
ValueCountFrequency (%)
: 254
97.3%
. 4
 
1.5%
& 2
 
0.8%
# 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 20
57.1%
1 13
37.1%
6 2
 
5.7%
Space Separator
ValueCountFrequency (%)
412
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5102
77.2%
Common 862
 
13.0%
Latin 647
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 345
 
6.8%
북 219
 
4.3%
이 150
 
2.9%
사 143
 
2.8%
문 98
 
1.9%
디 75
 
1.5%
학 74
 
1.5%
비 69
 
1.4%
아 69
 
1.4%
트 67
 
1.3%
Other values (366) 3793
74.3%
Latin
ValueCountFrequency (%)
o 62
 
9.6%
e 59
 
9.1%
n 44
 
6.8%
i 44
 
6.8%
a 36
 
5.6%
t 30
 
4.6%
s 30
 
4.6%
B 28
 
4.3%
k 27
 
4.2%
R 24
 
3.7%
Other values (32) 263
40.6%
Common
ValueCountFrequency (%)
412
47.8%
: 254
29.5%
) 77
 
8.9%
( 77
 
8.9%
2 20
 
2.3%
1 13
 
1.5%
. 4
 
0.5%
& 2
 
0.2%
6 2
 
0.2%
# 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5102
77.2%
ASCII 1509
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
412
27.3%
: 254
16.8%
) 77
 
5.1%
( 77
 
5.1%
o 62
 
4.1%
e 59
 
3.9%
n 44
 
2.9%
i 44
 
2.9%
a 36
 
2.4%
t 30
 
2.0%
Other values (42) 414
27.4%
Hangul
ValueCountFrequency (%)
스 345
 
6.8%
북 219
 
4.3%
이 150
 
2.9%
사 143
 
2.8%
문 98
 
1.9%
디 75
 
1.5%
학 74
 
1.5%
비 69
 
1.4%
아 69
 
1.4%
트 67
 
1.3%
Other values (366) 3793
74.3%

발행년
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2021.5749
Minimum2001
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-04T01:49:16.897578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2019
Q12021
median2022
Q32023
95-th percentile2023
Maximum2023
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3600563
Coefficient of variation (CV)0.0011674345
Kurtosis24.242379
Mean2021.5749
Median Absolute Deviation (MAD)1
Skewness-4.1602552
Sum1997316
Variance5.5698657
MonotonicityDecreasing
2024-05-04T01:49:17.290291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2023 426
43.1%
2022 239
24.2%
2021 133
 
13.5%
2020 114
 
11.5%
2019 30
 
3.0%
2018 13
 
1.3%
2011 5
 
0.5%
2014 5
 
0.5%
2016 4
 
0.4%
2017 3
 
0.3%
Other values (10) 16
 
1.6%
ValueCountFrequency (%)
2001 1
 
0.1%
2002 1
 
0.1%
2003 1
 
0.1%
2005 1
 
0.1%
2006 1
 
0.1%
2007 1
 
0.1%
2009 3
0.3%
2011 5
0.5%
2012 3
0.3%
2013 2
 
0.2%
ValueCountFrequency (%)
2023 426
43.1%
2022 239
24.2%
2021 133
 
13.5%
2020 114
 
11.5%
2019 30
 
3.0%
2018 13
 
1.3%
2017 3
 
0.3%
2016 4
 
0.4%
2015 2
 
0.2%
2014 5
 
0.5%

청구기호
Text

UNIQUE 

Distinct988
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-05-04T01:49:17.878059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length13.065789
Min length10

Characters and Unicode

Total characters12909
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique988 ?
Unique (%)100.0%

Sample

1st row813.7 2023-96
2nd row670.4 2023-5
3rd row909 2023-3
4th row818 2023-427
5th row834 2023-12
ValueCountFrequency (%)
813.7 129
 
6.4%
818 66
 
3.3%
2023-1 63
 
3.1%
833.6 54
 
2.7%
325.211 49
 
2.4%
2023-2 41
 
2.0%
2022-1 39
 
1.9%
843.6 29
 
1.4%
814.7 21
 
1.0%
2023-3 21
 
1.0%
Other values (762) 1509
74.7%
2024-05-04T01:49:18.963309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2805
21.7%
1 1484
11.5%
0 1483
11.5%
3 1296
10.0%
- 1041
 
8.1%
1033
 
8.0%
8 793
 
6.1%
. 793
 
6.1%
7 501
 
3.9%
5 486
 
3.8%
Other values (3) 1194
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10042
77.8%
Dash Punctuation 1041
 
8.1%
Space Separator 1033
 
8.0%
Other Punctuation 793
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2805
27.9%
1 1484
14.8%
0 1483
14.8%
3 1296
12.9%
8 793
 
7.9%
7 501
 
5.0%
5 486
 
4.8%
4 471
 
4.7%
9 376
 
3.7%
6 347
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 1041
100.0%
Space Separator
ValueCountFrequency (%)
1033
100.0%
Other Punctuation
ValueCountFrequency (%)
. 793
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12909
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2805
21.7%
1 1484
11.5%
0 1483
11.5%
3 1296
10.0%
- 1041
 
8.1%
1033
 
8.0%
8 793
 
6.1%
. 793
 
6.1%
7 501
 
3.9%
5 486
 
3.8%
Other values (3) 1194
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2805
21.7%
1 1484
11.5%
0 1483
11.5%
3 1296
10.0%
- 1041
 
8.1%
1033
 
8.0%
8 793
 
6.1%
. 793
 
6.1%
7 501
 
3.9%
5 486
 
3.8%
Other values (3) 1194
9.2%

분류기호
Real number (ℝ)

HIGH CORRELATION 

Distinct324
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean567.35211
Minimum1.3
Maximum985.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-05-04T01:49:19.408319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile160
Q1325.2113
median600.04
Q3814.7
95-th percentile863
Maximum985.02
Range983.72
Interquartile range (IQR)489.4887

Descriptive statistics

Standard deviation275.57201
Coefficient of variation (CV)0.48571601
Kurtosis-1.3168043
Mean567.35211
Median Absolute Deviation (MAD)233.56
Skewness-0.35849964
Sum560543.89
Variance75939.931
MonotonicityNot monotonic
2024-05-04T01:49:19.878112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
813.7 129
 
13.1%
818.0 66
 
6.7%
833.6 54
 
5.5%
325.211 49
 
5.0%
843.6 29
 
2.9%
814.7 21
 
2.1%
327.04 19
 
1.9%
199.1 17
 
1.7%
327.856 14
 
1.4%
189.1 12
 
1.2%
Other values (314) 578
58.5%
ValueCountFrequency (%)
1.3 4
0.4%
1.4 1
 
0.1%
4.0 1
 
0.1%
4.16 1
 
0.1%
4.73 8
0.8%
5.1 1
 
0.1%
5.13 1
 
0.1%
5.133 2
 
0.2%
5.51 1
 
0.1%
5.53 1
 
0.1%
ValueCountFrequency (%)
985.02 1
 
0.1%
982.802 1
 
0.1%
982.702 1
 
0.1%
982.02 1
 
0.1%
981.32302 1
 
0.1%
981.302 3
0.3%
981.19902 2
0.2%
981.102 3
0.3%
981.1 1
 
0.1%
980.24 1
 
0.1%

언어
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
kor
986 
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kor 986
99.8%
2
 
0.2%

Length

2024-05-04T01:49:20.287768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:20.621872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kor 986
100.0%

언어명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
한국어
986 
<NA>
 
2

Length

Max length4
Median length3
Mean length3.0020243
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국어 986
99.8%
<NA> 2
 
0.2%

Length

2024-05-04T01:49:21.036896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:21.337364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국어 986
99.8%
na 2
 
0.2%

국가명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
ulk
631 
ggk
351 
tjk
 
2
tgk
 
2
gbk
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowulk
2nd rowggk
3rd rowggk
4th rowulk
5th rowulk

Common Values

ValueCountFrequency (%)
ulk 631
63.9%
ggk 351
35.5%
tjk 2
 
0.2%
tgk 2
 
0.2%
gbk 1
 
0.1%
jnk 1
 
0.1%

Length

2024-05-04T01:49:21.653957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:21.983796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ulk 631
63.9%
ggk 351
35.5%
tjk 2
 
0.2%
tgk 2
 
0.2%
gbk 1
 
0.1%
jnk 1
 
0.1%

소장처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
F0000000
988 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF0000000
2nd rowF0000000
3rd rowF0000000
4th rowF0000000
5th rowF0000000

Common Values

ValueCountFrequency (%)
F0000000 988
100.0%

Length

2024-05-04T01:49:22.375221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:22.638202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f0000000 988
100.0%

소장처명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
서울도서관
988 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울도서관 988
100.0%

Length

2024-05-04T01:49:22.883576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:23.133216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울도서관 988
100.0%

자료실 코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
300
988 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row300
2nd row300
3rd row300
4th row300
5th row300

Common Values

ValueCountFrequency (%)
300 988
100.0%

Length

2024-05-04T01:49:23.455868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:23.721482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
300 988
100.0%

자료실 이름
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
스마트도서관(시청역)
988 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row스마트도서관(시청역)
2nd row스마트도서관(시청역)
3rd row스마트도서관(시청역)
4th row스마트도서관(시청역)
5th row스마트도서관(시청역)

Common Values

ValueCountFrequency (%)
스마트도서관(시청역) 988
100.0%

Length

2024-05-04T01:49:24.168614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:24.468412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스마트도서관(시청역 988
100.0%

대출상태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
1
687 
2
301 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 687
69.5%
2 301
30.5%

Length

2024-05-04T01:49:24.767477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:25.077664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 687
69.5%
2 301
30.5%

대출상태메시지
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
대출가능
687 
대출중
301 

Length

Max length4
Median length4
Mean length3.6953441
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대출가능
2nd row대출가능
3rd row대출가능
4th row대출중
5th row대출중

Common Values

ValueCountFrequency (%)
대출가능 687
69.5%
대출중 301
30.5%

Length

2024-05-04T01:49:25.538362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T01:49:25.850932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대출가능 687
69.5%
대출중 301
30.5%

Interactions

2024-05-04T01:49:06.417255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:04.350657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:05.470773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:06.747700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:04.720135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:05.761646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:07.034775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:05.059048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T01:49:06.033162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T01:49:26.094462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자료코드발행년분류기호언어국가명대출상태대출상태메시지
자료코드1.0000.9550.0650.0000.0000.1950.195
발행년0.9551.0000.0000.0000.0000.1790.179
분류기호0.0650.0001.0000.0000.1570.1390.139
언어0.0000.0000.0001.0000.0000.0000.000
국가명0.0000.0000.1570.0001.0000.0000.000
대출상태0.1950.1790.1390.0000.0001.0001.000
대출상태메시지0.1950.1790.1390.0000.0001.0001.000
2024-05-04T01:49:26.394786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대출상태언어대출상태메시지국가명언어명
대출상태1.0000.0000.9980.0001.000
언어0.0001.0000.0000.0001.000
대출상태메시지0.9980.0001.0000.0001.000
국가명0.0000.0000.0001.0001.000
언어명1.0001.0001.0001.0001.000
2024-05-04T01:49:26.675529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자료코드발행년분류기호언어언어명국가명대출상태대출상태메시지
자료코드1.0000.941-0.0180.0001.0000.0000.1540.154
발행년0.9411.000-0.0240.0001.0000.0000.1450.145
분류기호-0.018-0.0241.0000.0001.0000.0830.1060.106
언어0.0000.0000.0001.0001.0000.0000.0000.000
언어명1.0001.0001.0001.0001.0001.0001.0001.000
국가명0.0000.0000.0830.0001.0001.0000.0000.000
대출상태0.1540.1450.1060.0001.0000.0001.0000.998
대출상태메시지0.1540.1450.1060.0001.0000.0000.9981.000

Missing values

2024-05-04T01:49:07.451612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T01:49:08.120924image/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

자료코드등록번호자료명저자출판사발행년청구기호분류기호언어언어명국가명소장처소장처명자료실 코드자료실 이름대출상태대출상태메시지
01619744EM0000471020경우 없는 세계 :백온유 장편소설백온유 지음창비2023813.7 2023-96813.7kor한국어ulkF0000000서울도서관300스마트도서관(시청역)1대출가능
11644171EM0000471103G는 파랑 :피아니스트가 음악을 기억하는 방법김지희 지음윌북2023670.4 2023-5670.4kor한국어ggkF0000000서울도서관300스마트도서관(시청역)1대출가능
21589661EM0000457559(몸으로 읽는) 세계사 :사소한 몸에 숨겨진 독특하고 거대한 문명의 역사캐스린 페트라스다산초당: 다산북스2023909 2023-3909.0kor한국어ggkF0000000서울도서관300스마트도서관(시청역)1대출가능
31644170EM0000471102가장 아끼는 너에게 주고 싶은 말 :도연화 에세이도연화 지음부크럼2023818 2023-427818.0kor한국어ulkF0000000서울도서관300스마트도서관(시청역)2대출중
41645296EM0000471085여행 아닌 여행기 :요시모토 바나나 에세이요시모토 바나나 지음민음사2023834 2023-12834.0kor한국어ulkF0000000서울도서관300스마트도서관(시청역)2대출중
51643517EM0000471082멜랑콜리아 .I-II욘 포세 지음민음사2023808 2013-100 431808.0kor한국어ggkF0000000서울도서관300스마트도서관(시청역)2대출중
61645291EM0000471080영혼이 강한 아이로 키워라 :대한민국 부모 멘토 조선미 교수의 자녀교육 명강조선미 지음북하우스 : 북하우스 퍼블리셔스2023598.1 2014-20-2598.1kor한국어ulkF0000000서울도서관300스마트도서관(시청역)1대출가능
71635187EM0000471104마흔에 읽는 쇼펜하우어 :마음의 위기를 다스리는 철학 수업강용수 지음유노북스: 유노콘텐츠그룹2023165.47 2023-4165.47kor한국어ulkF0000000서울도서관300스마트도서관(시청역)2대출중
81629859EM0000471078홀로다니엘 슈라이버 지음바다출판사2023858 2023-2858.0kor한국어ulkF0000000서울도서관300스마트도서관(시청역)1대출가능
91610108EM0000471075피아노에 몹시 진심입니다만 :고독한 방구석 피아니스트들을 위하여: 임승수 에세이임승수 지음낮은산2023676.204 2023-1676.204kor한국어ulkF0000000서울도서관300스마트도서관(시청역)1대출가능
자료코드등록번호자료명저자출판사발행년청구기호분류기호언어언어명국가명소장처소장처명자료실 코드자료실 이름대출상태대출상태메시지
9789959EM0000415128(베르나르 베르베르의) 상상력 사전 :새롭게 증보된 상대적이며 절대적인 지식의 백과사전베르나르 베르베르 지음열린책들2011868 2012-1868.0kor한국어ggkF0000000서울도서관300스마트도서관(시청역)2대출중
9791315EM0000037706청춘의 독서 :세상을 바꾼 위험하고 위대한 생각들유시민 지음웅진지식하우스2009029.1 2009-129.1kor한국어ulkF0000000서울도서관300스마트도서관(시청역)2대출중
9802196EM0000364938예지몽 :히가시노 게이고 소설히가시노 게이고 [지음]재인2009833.6 2009-2833.6kor한국어ulkF0000000서울도서관300스마트도서관(시청역)2대출중
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