Overview

Dataset statistics

Number of variables6
Number of observations984
Missing cells4
Missing cells (%)0.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory47.2 KiB
Average record size in memory49.1 B

Variable types

Text3
Numeric1
Categorical2

Dataset

Description전북특별자치도 장수군에 소재중인 작은도서관에서 구입한 도서 목록(도서명, 저자, 출판사, 수량, 분류, 지역)에 대하여 정보를 제공하고자 합니다
Author전북특별자치도 장수군
URLhttps://www.data.go.kr/data/15055048/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
분류 is highly imbalanced (57.3%)Imbalance

Reproduction

Analysis started2024-03-30 09:24:40.964030
Analysis finished2024-03-30 09:24:44.069634
Duration3.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도서명
Text

Distinct930
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2024-03-30T09:24:44.797229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length37
Mean length11.114837
Min length2

Characters and Unicode

Total characters10937
Distinct characters756
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique883 ?
Unique (%)89.7%

Sample

1st rowA Frog and Dog Book 1 : Frog Meets Dog
2nd rowA Frog and Dog Book 2 : Frog Meets Dog
3rd rowOxford Reading Tree: Level1 - The Big
4th row오늘도 플라스틱을 먹었습니다
5th row별일 아닌데 뿌듯합니다
ValueCountFrequency (%)
시즌2 21
 
0.7%
쿠키런 19
 
0.7%
내일은 15
 
0.5%
좀비고등학교 14
 
0.5%
코믹스 14
 
0.5%
내가 12
 
0.4%
시간 12
 
0.4%
나를 12
 
0.4%
세트 10
 
0.4%
만화 10
 
0.4%
Other values (1912) 2669
95.0%
2024-03-30T09:24:46.314723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1827
 
16.7%
의 232
 
2.1%
이 209
 
1.9%
다 133
 
1.2%
는 122
 
1.1%
어 120
 
1.1%
한 114
 
1.0%
2 112
 
1.0%
1 112
 
1.0%
지 107
 
1.0%
Other values (746) 7849
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8170
74.7%
Space Separator 1827
 
16.7%
Decimal Number 554
 
5.1%
Other Punctuation 141
 
1.3%
Lowercase Letter 117
 
1.1%
Math Symbol 43
 
0.4%
Uppercase Letter 43
 
0.4%
Open Punctuation 19
 
0.2%
Close Punctuation 19
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 232
 
2.8%
이 209
 
2.6%
다 133
 
1.6%
는 122
 
1.5%
어 120
 
1.5%
한 114
 
1.4%
지 107
 
1.3%
가 106
 
1.3%
사 103
 
1.3%
고 102
 
1.2%
Other values (685) 6822
83.5%
Lowercase Letter
ValueCountFrequency (%)
e 17
14.5%
g 14
12.0%
o 14
12.0%
a 10
8.5%
n 10
8.5%
r 10
8.5%
i 9
7.7%
d 7
6.0%
t 7
6.0%
h 3
 
2.6%
Other values (10) 16
13.7%
Uppercase Letter
ValueCountFrequency (%)
F 5
11.6%
D 5
11.6%
T 5
11.6%
A 4
9.3%
B 4
9.3%
O 4
9.3%
M 3
7.0%
G 3
7.0%
R 2
 
4.7%
P 2
 
4.7%
Other values (6) 6
14.0%
Decimal Number
ValueCountFrequency (%)
2 112
20.2%
1 112
20.2%
3 80
14.4%
4 68
12.3%
5 59
10.6%
0 36
 
6.5%
6 28
 
5.1%
7 24
 
4.3%
9 19
 
3.4%
8 16
 
2.9%
Other Punctuation
ValueCountFrequency (%)
: 47
33.3%
, 45
31.9%
? 26
18.4%
! 16
 
11.3%
/ 6
 
4.3%
& 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 29
67.4%
+ 11
 
25.6%
= 3
 
7.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
1827
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8170
74.7%
Common 2605
 
23.8%
Latin 162
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 232
 
2.8%
이 209
 
2.6%
다 133
 
1.6%
는 122
 
1.5%
어 120
 
1.5%
한 114
 
1.4%
지 107
 
1.3%
가 106
 
1.3%
사 103
 
1.3%
고 102
 
1.2%
Other values (685) 6822
83.5%
Latin
ValueCountFrequency (%)
e 17
 
10.5%
g 14
 
8.6%
o 14
 
8.6%
a 10
 
6.2%
n 10
 
6.2%
r 10
 
6.2%
i 9
 
5.6%
d 7
 
4.3%
t 7
 
4.3%
F 5
 
3.1%
Other values (28) 59
36.4%
Common
ValueCountFrequency (%)
1827
70.1%
2 112
 
4.3%
1 112
 
4.3%
3 80
 
3.1%
4 68
 
2.6%
5 59
 
2.3%
: 47
 
1.8%
, 45
 
1.7%
0 36
 
1.4%
~ 29
 
1.1%
Other values (13) 190
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8170
74.7%
ASCII 2765
 
25.3%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1827
66.1%
2 112
 
4.1%
1 112
 
4.1%
3 80
 
2.9%
4 68
 
2.5%
5 59
 
2.1%
: 47
 
1.7%
, 45
 
1.6%
0 36
 
1.3%
~ 29
 
1.0%
Other values (49) 350
 
12.7%
Hangul
ValueCountFrequency (%)
의 232
 
2.8%
이 209
 
2.6%
다 133
 
1.6%
는 122
 
1.5%
어 120
 
1.5%
한 114
 
1.4%
지 107
 
1.3%
가 106
 
1.3%
사 103
 
1.3%
고 102
 
1.2%
Other values (685) 6822
83.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

저자
Text

Distinct658
Distinct (%)67.1%
Missing3
Missing (%)0.3%
Memory size7.8 KiB
2024-03-30T09:24:46.958979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length4.3893986
Min length1

Characters and Unicode

Total characters4306
Distinct characters453
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique544 ?
Unique (%)55.5%

Sample

1st row Janes Trasler
2nd row Janes Trasler
3rd rowOxford press
4th row롤프 할든
5th row이은재
ValueCountFrequency (%)
송도수 20
 
1.6%
김미영 14
 
1.1%
박순영 14
 
1.1%
야옹이 11
 
0.9%
에린 11
 
0.9%
헌터 11
 
0.9%
김강현 10
 
0.8%
이낙준 10
 
0.8%
앤서니 8
 
0.7%
브라운 8
 
0.7%
Other values (809) 1106
90.4%
2024-03-30T09:24:48.194086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
 
5.7%
이 190
 
4.4%
김 122
 
2.8%
리 88
 
2.0%
스 79
 
1.8%
영 75
 
1.7%
정 72
 
1.7%
, 66
 
1.5%
미 64
 
1.5%
현 56
 
1.3%
Other values (443) 3247
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3915
90.9%
Space Separator 247
 
5.7%
Other Punctuation 74
 
1.7%
Lowercase Letter 39
 
0.9%
Uppercase Letter 19
 
0.4%
Decimal Number 7
 
0.2%
Dash Punctuation 3
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 190
 
4.9%
김 122
 
3.1%
리 88
 
2.2%
스 79
 
2.0%
영 75
 
1.9%
정 72
 
1.8%
미 64
 
1.6%
현 56
 
1.4%
박 53
 
1.4%
도 49
 
1.3%
Other values (408) 3067
78.3%
Lowercase Letter
ValueCountFrequency (%)
a 10
25.6%
s 7
17.9%
r 6
15.4%
e 5
12.8%
n 2
 
5.1%
l 2
 
5.1%
b 1
 
2.6%
k 1
 
2.6%
p 1
 
2.6%
d 1
 
2.6%
Other values (3) 3
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
T 5
26.3%
D 3
15.8%
O 2
 
10.5%
J 2
 
10.5%
M 2
 
10.5%
E 2
 
10.5%
N 1
 
5.3%
G 1
 
5.3%
P 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
5 2
28.6%
7 1
14.3%
4 1
14.3%
8 1
14.3%
1 1
14.3%
0 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 66
89.2%
. 4
 
5.4%
/ 4
 
5.4%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3915
90.9%
Common 333
 
7.7%
Latin 58
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 190
 
4.9%
김 122
 
3.1%
리 88
 
2.2%
스 79
 
2.0%
영 75
 
1.9%
정 72
 
1.8%
미 64
 
1.6%
현 56
 
1.4%
박 53
 
1.4%
도 49
 
1.3%
Other values (408) 3067
78.3%
Latin
ValueCountFrequency (%)
a 10
17.2%
s 7
12.1%
r 6
10.3%
e 5
 
8.6%
T 5
 
8.6%
D 3
 
5.2%
O 2
 
3.4%
J 2
 
3.4%
n 2
 
3.4%
l 2
 
3.4%
Other values (12) 14
24.1%
Common
ValueCountFrequency (%)
247
74.2%
, 66
 
19.8%
. 4
 
1.2%
/ 4
 
1.2%
- 3
 
0.9%
5 2
 
0.6%
) 1
 
0.3%
( 1
 
0.3%
7 1
 
0.3%
4 1
 
0.3%
Other values (3) 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3915
90.9%
ASCII 391
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
63.2%
, 66
 
16.9%
a 10
 
2.6%
s 7
 
1.8%
r 6
 
1.5%
e 5
 
1.3%
T 5
 
1.3%
. 4
 
1.0%
/ 4
 
1.0%
D 3
 
0.8%
Other values (25) 34
 
8.7%
Hangul
ValueCountFrequency (%)
이 190
 
4.9%
김 122
 
3.1%
리 88
 
2.2%
스 79
 
2.0%
영 75
 
1.9%
정 72
 
1.8%
미 64
 
1.6%
현 56
 
1.4%
박 53
 
1.4%
도 49
 
1.3%
Other values (408) 3067
78.3%

출판사
Text

Distinct403
Distinct (%)41.0%
Missing1
Missing (%)0.1%
Memory size7.8 KiB
2024-03-30T09:24:48.992063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length4.1658189
Min length1

Characters and Unicode

Total characters4095
Distinct characters382
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

Unique259 ?
Unique (%)26.3%

Sample

1st rowScholasic
2nd row Scholasic
3rd rowOxford Education
4th row한문화
5th row클랩북스
ValueCountFrequency (%)
미래엔아이세움 41
 
4.0%
문학동네 38
 
3.7%
서울문화사 32
 
3.1%
영컴 27
 
2.7%
웅진주니어 25
 
2.5%
아울북 24
 
2.4%
창비 23
 
2.3%
비룡소 22
 
2.2%
책읽는곰 18
 
1.8%
위즈덤하우스 15
 
1.5%
Other values (410) 753
74.0%
2024-03-30T09:24:50.153988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 160
 
3.9%
스 158
 
3.9%
북 157
 
3.8%
아 111
 
2.7%
어 107
 
2.6%
사 103
 
2.5%
문 93
 
2.3%
비 72
 
1.8%
미 69
 
1.7%
울 59
 
1.4%
Other values (372) 3006
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3921
95.8%
Lowercase Letter 83
 
2.0%
Uppercase Letter 47
 
1.1%
Space Separator 37
 
0.9%
Decimal Number 4
 
0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 160
 
4.1%
스 158
 
4.0%
북 157
 
4.0%
아 111
 
2.8%
어 107
 
2.7%
사 103
 
2.6%
문 93
 
2.4%
비 72
 
1.8%
미 69
 
1.8%
울 59
 
1.5%
Other values (329) 2832
72.2%
Lowercase Letter
ValueCountFrequency (%)
o 13
15.7%
a 9
10.8%
n 8
9.6%
s 7
8.4%
e 7
8.4%
i 6
7.2%
d 6
7.2%
c 5
 
6.0%
b 4
 
4.8%
m 4
 
4.8%
Other values (9) 14
16.9%
Uppercase Letter
ValueCountFrequency (%)
Y 8
17.0%
U 8
17.0%
S 5
10.6%
J 4
8.5%
E 3
 
6.4%
B 3
 
6.4%
H 2
 
4.3%
L 2
 
4.3%
P 2
 
4.3%
I 2
 
4.3%
Other values (8) 8
17.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3921
95.8%
Latin 130
 
3.2%
Common 44
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 160
 
4.1%
스 158
 
4.0%
북 157
 
4.0%
아 111
 
2.8%
어 107
 
2.7%
사 103
 
2.6%
문 93
 
2.4%
비 72
 
1.8%
미 69
 
1.8%
울 59
 
1.5%
Other values (329) 2832
72.2%
Latin
ValueCountFrequency (%)
o 13
 
10.0%
a 9
 
6.9%
n 8
 
6.2%
Y 8
 
6.2%
U 8
 
6.2%
s 7
 
5.4%
e 7
 
5.4%
i 6
 
4.6%
d 6
 
4.6%
c 5
 
3.8%
Other values (27) 53
40.8%
Common
ValueCountFrequency (%)
37
84.1%
1 2
 
4.5%
2 2
 
4.5%
& 1
 
2.3%
) 1
 
2.3%
( 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3921
95.8%
ASCII 174
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 160
 
4.1%
스 158
 
4.0%
북 157
 
4.0%
아 111
 
2.8%
어 107
 
2.7%
사 103
 
2.6%
문 93
 
2.4%
비 72
 
1.8%
미 69
 
1.8%
울 59
 
1.5%
Other values (329) 2832
72.2%
ASCII
ValueCountFrequency (%)
37
21.3%
o 13
 
7.5%
a 9
 
5.2%
n 8
 
4.6%
Y 8
 
4.6%
U 8
 
4.6%
s 7
 
4.0%
e 7
 
4.0%
i 6
 
3.4%
d 6
 
3.4%
Other values (33) 65
37.4%

수량
Real number (ℝ)

Distinct20
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4410569
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2024-03-30T09:24:50.531511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum55
Range54
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5356895
Coefficient of variation (CV)2.4535391
Kurtosis139.98102
Mean1.4410569
Median Absolute Deviation (MAD)0
Skewness11.251761
Sum1418
Variance12.5011
MonotonicityNot monotonic
2024-03-30T09:24:50.982802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 938
95.3%
3 11
 
1.1%
2 9
 
0.9%
4 5
 
0.5%
5 3
 
0.3%
7 2
 
0.2%
20 2
 
0.2%
6 2
 
0.2%
15 1
 
0.1%
16 1
 
0.1%
Other values (10) 10
 
1.0%
ValueCountFrequency (%)
1 938
95.3%
2 9
 
0.9%
3 11
 
1.1%
4 5
 
0.5%
5 3
 
0.3%
6 2
 
0.2%
7 2
 
0.2%
8 1
 
0.1%
10 1
 
0.1%
12 1
 
0.1%
ValueCountFrequency (%)
55 1
0.1%
52 1
0.1%
42 1
0.1%
40 1
0.1%
34 1
0.1%
30 1
0.1%
20 2
0.2%
16 1
0.1%
15 1
0.1%
14 1
0.1%

분류
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
아동
509 
일반
449 
큰글자책
 
11
<NA>
 
6
청소년
 
5
Other values (2)
 
4

Length

Max length4
Median length2
Mean length2.0406504
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
아동 509
51.7%
일반 449
45.6%
큰글자책 11
 
1.1%
<NA> 6
 
0.6%
청소년 5
 
0.5%
성인 3
 
0.3%
일반 1
 
0.1%

Length

2024-03-30T09:24:51.495071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:24:51.866834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아동 509
51.7%
일반 450
45.7%
큰글자책 11
 
1.1%
na 6
 
0.6%
청소년 5
 
0.5%
성인 3
 
0.3%

지역
Categorical

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
장수
268 
번암
194 
계남
192 
천천
140 
계북
98 
Other values (2)
92 

Length

Max length4
Median length2
Mean length2.0121951
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장수 268
27.2%
번암 194
19.7%
계남 192
19.5%
천천 140
14.2%
계북 98
 
10.0%
산서 86
 
8.7%
<NA> 6
 
0.6%

Length

2024-03-30T09:24:52.419602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:24:52.872977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장수 268
27.2%
번암 194
19.7%
계남 192
19.5%
천천 140
14.2%
계북 98
 
10.0%
산서 86
 
8.7%
na 6
 
0.6%

Interactions

2024-03-30T09:24:42.987749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T09:24:53.139912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량분류지역
수량1.0000.0000.175
분류0.0001.0000.359
지역0.1750.3591.000
2024-03-30T09:24:53.415662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류
지역1.0000.137
분류0.1371.000
2024-03-30T09:24:53.682606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량분류지역
수량1.0000.0000.098
분류0.0001.0000.137
지역0.0980.1371.000

Missing values

2024-03-30T09:24:43.302261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T09:24:43.641084image/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.
2024-03-30T09:24:43.936538image/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

도서명저자출판사수량분류지역
0A Frog and Dog Book 1 : Frog Meets DogJanes TraslerScholasic1일반장수
1A Frog and Dog Book 2 : Frog Meets DogJanes TraslerScholasic1일반장수
2Oxford Reading Tree: Level1 - The BigOxford pressOxford Education1일반장수
3오늘도 플라스틱을 먹었습니다롤프 할든한문화1일반장수
4별일 아닌데 뿌듯합니다이은재클랩북스1일반장수
5눈에 보이지 않는 지도책제임스 체셔, 올리버 우버티윌북1일반장수
62050 패권의 미래해미시 맥레이서경 B&B1일반장수
7매일 아침 여섯 시, 일기를 씁니다박선희나무발전소1일반장수
8부는 어디서 오는가윌리스 와틀스포레스트북스1일반장수
9적당히 느슨하게 조금씩 행복해지는 습관유메쿠이 바쿠부키1일반장수
도서명저자출판사수량분류지역
974올빼미 기사크리스토퍼 데니스비룡소1아동계북
975후우 바구니 타자아소비교육연구소아소비교육1아동계북
976모두 예술가야애드비어주니어알에이치케이1아동계북
977곰과 수레앙드레 프리장목요일1아동계북
978엄마를 기다리며쟝사오치한림출판사1아동계북
979바다로 간 여우연우다정다감1아동계북
980나에게도 강아지가 있었어민소원다정다감1아동계북
981봄이와 제비꽃에토웅진주니어1아동계북
982말이야와 친구들7김정욱/이혜림주니어김영사1아동계북
983남성해방옌스펀투리흐트노닐다1일반계북

Duplicate rows

Most frequently occurring

도서명저자출판사수량분류지역# duplicates
0흔한남매13흔한남매미래엔아이세움1아동장수2