Overview

Dataset statistics

Number of variables3
Number of observations699
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory24.2 B

Variable types

Text2
Boolean1

Dataset

Description인천광역시 통합전자도서관 홈페이지에서 제공하는 도서 카테고리(카테고리키, 카테고리이름, 사용여부)정보에 대한 파일.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15049231&srcSe=7661IVAWM27C61E190

Alerts

사용여부(Y_N) has constant value ""Constant
카테고리키 has unique valuesUnique

Reproduction

Analysis started2024-03-18 03:17:09.476142
Analysis finished2024-03-18 03:17:09.762807
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

카테고리키
Text

UNIQUE 

Distinct699
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-03-18T12:17:10.070652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2796
Distinct characters13
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

Unique699 ?
Unique (%)100.0%

Sample

1st rowL001
2nd rowL002
3rd rowL003
4th rowL004
5th rowL005
ValueCountFrequency (%)
l001 1
 
0.1%
s305 1
 
0.1%
s307 1
 
0.1%
s298 1
 
0.1%
s299 1
 
0.1%
s300 1
 
0.1%
s301 1
 
0.1%
s302 1
 
0.1%
s303 1
 
0.1%
s304 1
 
0.1%
Other values (689) 689
98.6%
2024-03-18T12:17:10.563623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 535
19.1%
0 377
13.5%
1 304
10.9%
2 255
9.1%
3 247
8.8%
4 232
8.3%
5 166
 
5.9%
M 141
 
5.0%
6 129
 
4.6%
7 129
 
4.6%
Other values (3) 281
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2097
75.0%
Uppercase Letter 699
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 377
18.0%
1 304
14.5%
2 255
12.2%
3 247
11.8%
4 232
11.1%
5 166
7.9%
6 129
 
6.2%
7 129
 
6.2%
8 129
 
6.2%
9 129
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 535
76.5%
M 141
 
20.2%
L 23
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2097
75.0%
Latin 699
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 377
18.0%
1 304
14.5%
2 255
12.2%
3 247
11.8%
4 232
11.1%
5 166
7.9%
6 129
 
6.2%
7 129
 
6.2%
8 129
 
6.2%
9 129
 
6.2%
Latin
ValueCountFrequency (%)
S 535
76.5%
M 141
 
20.2%
L 23
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2796
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 535
19.1%
0 377
13.5%
1 304
10.9%
2 255
9.1%
3 247
8.8%
4 232
8.3%
5 166
 
5.9%
M 141
 
5.0%
6 129
 
4.6%
7 129
 
4.6%
Other values (3) 281
10.1%

카테고리명
Text

Distinct679
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size5.6 KiB
2024-03-18T12:17:10.824355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length5.7625179
Min length1

Characters and Unicode

Total characters4028
Distinct characters399
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

Unique660 ?
Unique (%)94.4%

Sample

1st row가정과생활
2nd row경제/경영
3rd row인문
4th row종교
5th row정치/사회
ValueCountFrequency (%)
일반 5
 
0.7%
에세이 4
 
0.5%
기타 4
 
0.5%
영어전자책 3
 
0.4%
외국 3
 
0.4%
한국 3
 
0.4%
소설 3
 
0.4%
자녀교육 2
 
0.3%
프랑스어 2
 
0.3%
시 2
 
0.3%
Other values (678) 701
95.8%
2024-03-18T12:17:11.158957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 353
 
8.8%
사 128
 
3.2%
학 127
 
3.2%
기 79
 
2.0%
어 76
 
1.9%
이 68
 
1.7%
문 68
 
1.7%
화 67
 
1.7%
국 56
 
1.4%
리 56
 
1.4%
Other values (389) 2950
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3481
86.4%
Other Punctuation 354
 
8.8%
Uppercase Letter 118
 
2.9%
Space Separator 33
 
0.8%
Decimal Number 12
 
0.3%
Math Symbol 9
 
0.2%
Lowercase Letter 9
 
0.2%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 128
 
3.7%
학 127
 
3.6%
기 79
 
2.3%
어 76
 
2.2%
이 68
 
2.0%
문 68
 
2.0%
화 67
 
1.9%
국 56
 
1.6%
리 56
 
1.6%
교 55
 
1.6%
Other values (341) 2701
77.6%
Uppercase Letter
ValueCountFrequency (%)
T 17
14.4%
S 13
11.0%
E 11
 
9.3%
I 8
 
6.8%
O 8
 
6.8%
F 7
 
5.9%
A 7
 
5.9%
L 7
 
5.9%
D 6
 
5.1%
P 6
 
5.1%
Other values (14) 28
23.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
11.1%
e 1
11.1%
t 1
11.1%
w 1
11.1%
o 1
11.1%
r 1
11.1%
g 1
11.1%
n 1
11.1%
i 1
11.1%
Decimal Number
ValueCountFrequency (%)
4 2
16.7%
3 2
16.7%
6 2
16.7%
1 2
16.7%
5 1
8.3%
7 1
8.3%
0 1
8.3%
2 1
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 353
99.7%
. 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 7
77.8%
+ 2
 
22.2%
Space Separator
ValueCountFrequency (%)
33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3481
86.4%
Common 420
 
10.4%
Latin 127
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 128
 
3.7%
학 127
 
3.6%
기 79
 
2.3%
어 76
 
2.2%
이 68
 
2.0%
문 68
 
2.0%
화 67
 
1.9%
국 56
 
1.6%
리 56
 
1.6%
교 55
 
1.6%
Other values (341) 2701
77.6%
Latin
ValueCountFrequency (%)
T 17
13.4%
S 13
 
10.2%
E 11
 
8.7%
I 8
 
6.3%
O 8
 
6.3%
F 7
 
5.5%
A 7
 
5.5%
L 7
 
5.5%
D 6
 
4.7%
P 6
 
4.7%
Other values (23) 37
29.1%
Common
ValueCountFrequency (%)
/ 353
84.0%
33
 
7.9%
~ 7
 
1.7%
( 6
 
1.4%
) 6
 
1.4%
+ 2
 
0.5%
4 2
 
0.5%
3 2
 
0.5%
6 2
 
0.5%
1 2
 
0.5%
Other values (5) 5
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3481
86.4%
ASCII 547
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 353
64.5%
33
 
6.0%
T 17
 
3.1%
S 13
 
2.4%
E 11
 
2.0%
I 8
 
1.5%
O 8
 
1.5%
F 7
 
1.3%
A 7
 
1.3%
L 7
 
1.3%
Other values (38) 83
 
15.2%
Hangul
ValueCountFrequency (%)
사 128
 
3.7%
학 127
 
3.6%
기 79
 
2.3%
어 76
 
2.2%
이 68
 
2.0%
문 68
 
2.0%
화 67
 
1.9%
국 56
 
1.6%
리 56
 
1.6%
교 55
 
1.6%
Other values (341) 2701
77.6%

사용여부(Y_N)
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size831.0 B
True
699 
ValueCountFrequency (%)
True 699
100.0%
2024-03-18T12:17:11.247323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-18T12:17:09.677175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:17:09.734692image/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

카테고리키카테고리명사용여부(Y_N)
0L001가정과생활Y
1L002경제/경영Y
2L003인문Y
3L004종교Y
4L005정치/사회Y
5L006역사/문화/지리Y
6L007자연/과학Y
7L008기술/공학Y
8L009취미/실용/스포츠Y
9L010여행Y
카테고리키카테고리명사용여부(Y_N)
689S526뜨개질/퀼트/십자수/바느질Y
690S527비즈/리본/선물포장Y
691S528목공예Y
692S529공예/기타Y
693S530국어/한자Y
694S531정치가Y
695S532영어전자책Y
696S533문학/교양Y
697S534패션/여성Y
698S535경제/시사Y