Overview

Dataset statistics

Number of variables5
Number of observations1004
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.3 KiB
Average record size in memory40.1 B

Variable types

Text4
Categorical1

Dataset

Description대구광역시교육청 대구광역시립서부도서관 2024년 1분기 신착도서목록을 공공데이터개방목록에 개방하고자 합니다.
Author대구광역시교육청 대구광역시립서부도서관
URLhttps://www.data.go.kr/data/3049525/fileData.do

Alerts

등록번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:09:25.257707
Analysis finished2024-04-06 08:09:26.961910
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct1004
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-06T17:09:27.219178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12048
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

Unique1004 ?
Unique (%)100.0%

Sample

1st rowBRP000503356
2nd rowBRP000503357
3rd rowBRP000503358
4th rowBRP000503359
5th rowBRP000503360
ValueCountFrequency (%)
brp000503356 1
 
0.1%
brp000504028 1
 
0.1%
brp000504016 1
 
0.1%
brp000504044 1
 
0.1%
brp000504017 1
 
0.1%
brp000504018 1
 
0.1%
brp000504019 1
 
0.1%
brp000504020 1
 
0.1%
brp000504021 1
 
0.1%
brp000504022 1
 
0.1%
Other values (994) 994
99.0%
2024-04-06T17:09:27.822472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4323
35.9%
5 1344
 
11.2%
B 1004
 
8.3%
R 1004
 
8.3%
P 1004
 
8.3%
3 903
 
7.5%
4 613
 
5.1%
2 346
 
2.9%
1 304
 
2.5%
6 301
 
2.5%
Other values (3) 902
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9036
75.0%
Uppercase Letter 3012
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4323
47.8%
5 1344
 
14.9%
3 903
 
10.0%
4 613
 
6.8%
2 346
 
3.8%
1 304
 
3.4%
6 301
 
3.3%
8 301
 
3.3%
7 301
 
3.3%
9 300
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 1004
33.3%
R 1004
33.3%
P 1004
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 9036
75.0%
Latin 3012
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4323
47.8%
5 1344
 
14.9%
3 903
 
10.0%
4 613
 
6.8%
2 346
 
3.8%
1 304
 
3.4%
6 301
 
3.3%
8 301
 
3.3%
7 301
 
3.3%
9 300
 
3.3%
Latin
ValueCountFrequency (%)
B 1004
33.3%
R 1004
33.3%
P 1004
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4323
35.9%
5 1344
 
11.2%
B 1004
 
8.3%
R 1004
 
8.3%
P 1004
 
8.3%
3 903
 
7.5%
4 613
 
5.1%
2 346
 
2.9%
1 304
 
2.5%
6 301
 
2.5%
Other values (3) 902
 
7.5%

서명
Text

Distinct930
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-06T17:09:28.557852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length143
Median length68
Mean length25.7749
Min length2

Characters and Unicode

Total characters25878
Distinct characters937
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique920 ?
Unique (%)91.6%

Sample

1st row질문할 수 없는 나라 일본 : 아베-스가 정권 언론통제 잔혹사
2nd row편집의 말들 : 미지의 길을 개척하는 편집자의 모험
3rd row한 번 읽은 책은 절대 잊지 않는다
4th row100일 아침 습관의 기적=The miracle of golden morning : 최고의 나를 만나는 하루 20분의 약속
5th row『순자』 읽기
ValueCountFrequency (%)
554
 
8.3%
위한 40
 
0.6%
이야기 39
 
0.6%
장편소설 30
 
0.5%
1 25
 
0.4%
2 25
 
0.4%
한 25
 
0.4%
어떻게 22
 
0.3%
나는 22
 
0.3%
한티재 20
 
0.3%
Other values (4010) 5860
88.0%
2024-04-06T17:09:29.552361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5658
 
21.9%
: 547
 
2.1%
의 517
 
2.0%
이 453
 
1.8%
는 356
 
1.4%
기 282
 
1.1%
한 254
 
1.0%
사 253
 
1.0%
리 235
 
0.9%
가 229
 
0.9%
Other values (927) 17094
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16369
63.3%
Space Separator 5658
 
21.9%
Lowercase Letter 1770
 
6.8%
Other Punctuation 1020
 
3.9%
Decimal Number 436
 
1.7%
Uppercase Letter 258
 
1.0%
Close Punctuation 127
 
0.5%
Open Punctuation 127
 
0.5%
Math Symbol 89
 
0.3%
Dash Punctuation 21
 
0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 517
 
3.2%
이 453
 
2.8%
는 356
 
2.2%
기 282
 
1.7%
한 254
 
1.6%
사 253
 
1.5%
리 235
 
1.4%
가 229
 
1.4%
지 212
 
1.3%
하 195
 
1.2%
Other values (842) 13383
81.8%
Lowercase Letter
ValueCountFrequency (%)
e 178
 
10.1%
o 176
 
9.9%
i 170
 
9.6%
t 146
 
8.2%
a 130
 
7.3%
n 121
 
6.8%
r 116
 
6.6%
s 99
 
5.6%
c 79
 
4.5%
h 79
 
4.5%
Other values (15) 476
26.9%
Uppercase Letter
ValueCountFrequency (%)
T 27
 
10.5%
A 27
 
10.5%
S 24
 
9.3%
I 22
 
8.5%
G 17
 
6.6%
E 14
 
5.4%
P 14
 
5.4%
M 13
 
5.0%
K 13
 
5.0%
C 12
 
4.7%
Other values (15) 75
29.1%
Other Punctuation
ValueCountFrequency (%)
: 547
53.6%
, 214
 
21.0%
. 114
 
11.2%
· 46
 
4.5%
! 38
 
3.7%
? 31
 
3.0%
' 18
 
1.8%
& 8
 
0.8%
# 3
 
0.3%
% 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 102
23.4%
2 89
20.4%
0 85
19.5%
4 28
 
6.4%
3 27
 
6.2%
5 26
 
6.0%
9 25
 
5.7%
7 23
 
5.3%
6 21
 
4.8%
8 10
 
2.3%
Math Symbol
ValueCountFrequency (%)
= 79
88.8%
~ 8
 
9.0%
+ 1
 
1.1%
× 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 117
92.1%
』 9
 
7.1%
》 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 117
92.1%
『 9
 
7.1%
《 1
 
0.8%
Other Number
ValueCountFrequency (%)
④ 1
50.0%
③ 1
50.0%
Space Separator
ValueCountFrequency (%)
5658
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16325
63.1%
Common 7481
28.9%
Latin 2028
 
7.8%
Han 44
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 517
 
3.2%
이 453
 
2.8%
는 356
 
2.2%
기 282
 
1.7%
한 254
 
1.6%
사 253
 
1.5%
리 235
 
1.4%
가 229
 
1.4%
지 212
 
1.3%
하 195
 
1.2%
Other values (801) 13339
81.7%
Latin
ValueCountFrequency (%)
e 178
 
8.8%
o 176
 
8.7%
i 170
 
8.4%
t 146
 
7.2%
a 130
 
6.4%
n 121
 
6.0%
r 116
 
5.7%
s 99
 
4.9%
c 79
 
3.9%
h 79
 
3.9%
Other values (40) 734
36.2%
Han
ValueCountFrequency (%)
譯 2
 
4.5%
國 2
 
4.5%
半 2
 
4.5%
道 1
 
2.3%
人 1
 
2.3%
探 1
 
2.3%
究 1
 
2.3%
蓬 1
 
2.3%
二 1
 
2.3%
樂 1
 
2.3%
Other values (31) 31
70.5%
Common
ValueCountFrequency (%)
5658
75.6%
: 547
 
7.3%
, 214
 
2.9%
) 117
 
1.6%
( 117
 
1.6%
. 114
 
1.5%
1 102
 
1.4%
2 89
 
1.2%
0 85
 
1.1%
= 79
 
1.1%
Other values (25) 359
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16322
63.1%
ASCII 9439
36.5%
None 67
 
0.3%
CJK 44
 
0.2%
Compat Jamo 3
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5658
59.9%
: 547
 
5.8%
, 214
 
2.3%
e 178
 
1.9%
o 176
 
1.9%
i 170
 
1.8%
t 146
 
1.5%
a 130
 
1.4%
n 121
 
1.3%
) 117
 
1.2%
Other values (66) 1982
 
21.0%
Hangul
ValueCountFrequency (%)
의 517
 
3.2%
이 453
 
2.8%
는 356
 
2.2%
기 282
 
1.7%
한 254
 
1.6%
사 253
 
1.6%
리 235
 
1.4%
가 229
 
1.4%
지 212
 
1.3%
하 195
 
1.2%
Other values (798) 13336
81.7%
None
ValueCountFrequency (%)
· 46
68.7%
『 9
 
13.4%
』 9
 
13.4%
《 1
 
1.5%
》 1
 
1.5%
× 1
 
1.5%
CJK
ValueCountFrequency (%)
譯 2
 
4.5%
國 2
 
4.5%
半 2
 
4.5%
道 1
 
2.3%
人 1
 
2.3%
探 1
 
2.3%
究 1
 
2.3%
蓬 1
 
2.3%
二 1
 
2.3%
樂 1
 
2.3%
Other values (31) 31
70.5%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
33.3%
ㄴ 1
33.3%
ㄷ 1
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
④ 1
50.0%
③ 1
50.0%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%

저자
Text

Distinct899
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-06T17:09:30.098923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length43
Mean length11.290837
Min length2

Characters and Unicode

Total characters11336
Distinct characters554
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique863 ?
Unique (%)86.0%

Sample

1st row미나미 아키라 지음 ; 이상현 옮김
2nd row김미래 지음
3rd row허필우 지음
4th row켈리 최 지음
5th row김철운 지음
ValueCountFrequency (%)
지음 741
21.5%
366
 
10.6%
옮김 180
 
5.2%
그림 142
 
4.1%
글 120
 
3.5%
외 64
 
1.9%
공저 50
 
1.5%
글·그림 23
 
0.7%
권정생 20
 
0.6%
엮음 20
 
0.6%
Other values (1465) 1721
49.9%
2024-04-06T17:09:30.952356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2457
21.7%
지 798
 
7.0%
음 766
 
6.8%
김 416
 
3.7%
; 366
 
3.2%
이 288
 
2.5%
옮 180
 
1.6%
림 171
 
1.5%
그 170
 
1.5%
글 151
 
1.3%
Other values (544) 5573
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8028
70.8%
Space Separator 2457
 
21.7%
Other Punctuation 542
 
4.8%
Lowercase Letter 108
 
1.0%
Close Punctuation 70
 
0.6%
Open Punctuation 70
 
0.6%
Uppercase Letter 50
 
0.4%
Decimal Number 9
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 798
 
9.9%
음 766
 
9.5%
김 416
 
5.2%
이 288
 
3.6%
옮 180
 
2.2%
림 171
 
2.1%
그 170
 
2.1%
글 151
 
1.9%
정 148
 
1.8%
영 106
 
1.3%
Other values (487) 4834
60.2%
Lowercase Letter
ValueCountFrequency (%)
a 15
13.9%
e 11
10.2%
i 11
10.2%
l 10
9.3%
n 10
9.3%
r 7
 
6.5%
o 7
 
6.5%
y 6
 
5.6%
s 4
 
3.7%
u 4
 
3.7%
Other values (10) 23
21.3%
Uppercase Letter
ValueCountFrequency (%)
S 6
12.0%
A 5
 
10.0%
D 5
 
10.0%
I 4
 
8.0%
L 4
 
8.0%
K 3
 
6.0%
J 3
 
6.0%
B 3
 
6.0%
W 2
 
4.0%
P 2
 
4.0%
Other values (10) 13
26.0%
Other Punctuation
ValueCountFrequency (%)
; 366
67.5%
, 131
 
24.2%
· 31
 
5.7%
. 10
 
1.8%
: 3
 
0.6%
' 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
7 3
33.3%
9 2
22.2%
1 2
22.2%
5 1
 
11.1%
3 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
] 67
95.7%
) 3
 
4.3%
Open Punctuation
ValueCountFrequency (%)
[ 67
95.7%
( 3
 
4.3%
Space Separator
ValueCountFrequency (%)
2457
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7991
70.5%
Common 3150
 
27.8%
Latin 158
 
1.4%
Han 37
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 798
 
10.0%
음 766
 
9.6%
김 416
 
5.2%
이 288
 
3.6%
옮 180
 
2.3%
림 171
 
2.1%
그 170
 
2.1%
글 151
 
1.9%
정 148
 
1.9%
영 106
 
1.3%
Other values (462) 4797
60.0%
Latin
ValueCountFrequency (%)
a 15
 
9.5%
e 11
 
7.0%
i 11
 
7.0%
l 10
 
6.3%
n 10
 
6.3%
r 7
 
4.4%
o 7
 
4.4%
S 6
 
3.8%
y 6
 
3.8%
A 5
 
3.2%
Other values (30) 70
44.3%
Han
ValueCountFrequency (%)
派 2
 
5.4%
宗 2
 
5.4%
中 2
 
5.4%
公 2
 
5.4%
尹 2
 
5.4%
密 2
 
5.4%
陽 2
 
5.4%
朴 2
 
5.4%
氏 2
 
5.4%
慶 2
 
5.4%
Other values (15) 17
45.9%
Common
ValueCountFrequency (%)
2457
78.0%
; 366
 
11.6%
, 131
 
4.2%
] 67
 
2.1%
[ 67
 
2.1%
· 31
 
1.0%
. 10
 
0.3%
: 3
 
0.1%
) 3
 
0.1%
( 3
 
0.1%
Other values (7) 12
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7991
70.5%
ASCII 3277
28.9%
CJK 37
 
0.3%
None 31
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2457
75.0%
; 366
 
11.2%
, 131
 
4.0%
] 67
 
2.0%
[ 67
 
2.0%
a 15
 
0.5%
e 11
 
0.3%
i 11
 
0.3%
. 10
 
0.3%
l 10
 
0.3%
Other values (46) 132
 
4.0%
Hangul
ValueCountFrequency (%)
지 798
 
10.0%
음 766
 
9.6%
김 416
 
5.2%
이 288
 
3.6%
옮 180
 
2.3%
림 171
 
2.1%
그 170
 
2.1%
글 151
 
1.9%
정 148
 
1.9%
영 106
 
1.3%
Other values (462) 4797
60.0%
None
ValueCountFrequency (%)
· 31
100.0%
CJK
ValueCountFrequency (%)
派 2
 
5.4%
宗 2
 
5.4%
中 2
 
5.4%
公 2
 
5.4%
尹 2
 
5.4%
密 2
 
5.4%
陽 2
 
5.4%
朴 2
 
5.4%
氏 2
 
5.4%
慶 2
 
5.4%
Other values (15) 17
45.9%

발행자
Text

Distinct588
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-04-06T17:09:31.461248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length5.0776892
Min length1

Characters and Unicode

Total characters5098
Distinct characters508
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)42.2%

Sample

1st row틔움(틔움출판)
2nd row유유
3rd row알에이치코리아
4th row다산북스
5th row세창미디어
ValueCountFrequency (%)
문학동네 26
 
2.4%
지식산업사 22
 
2.0%
문학과지성사 22
 
2.0%
창비 14
 
1.3%
국립민속박물관 12
 
1.1%
작가정신 11
 
1.0%
위즈덤하우스 11
 
1.0%
국립장애인도서관 11
 
1.0%
양철북 9
 
0.8%
박영사 9
 
0.8%
Other values (624) 930
86.4%
2024-04-06T17:09:32.239987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 186
 
3.6%
스 161
 
3.2%
북 132
 
2.6%
이 111
 
2.2%
문 95
 
1.9%
학 87
 
1.7%
지 75
 
1.5%
어 75
 
1.5%
73
 
1.4%
아 72
 
1.4%
Other values (498) 4031
79.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4397
86.2%
Lowercase Letter 295
 
5.8%
Uppercase Letter 178
 
3.5%
Space Separator 73
 
1.4%
Close Punctuation 65
 
1.3%
Open Punctuation 65
 
1.3%
Decimal Number 18
 
0.4%
Other Punctuation 6
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 186
 
4.2%
스 161
 
3.7%
북 132
 
3.0%
이 111
 
2.5%
문 95
 
2.2%
학 87
 
2.0%
지 75
 
1.7%
어 75
 
1.7%
아 72
 
1.6%
판 62
 
1.4%
Other values (440) 3341
76.0%
Lowercase Letter
ValueCountFrequency (%)
o 48
16.3%
k 24
 
8.1%
a 23
 
7.8%
n 22
 
7.5%
r 20
 
6.8%
e 20
 
6.8%
u 19
 
6.4%
s 18
 
6.1%
i 17
 
5.8%
t 12
 
4.1%
Other values (13) 72
24.4%
Uppercase Letter
ValueCountFrequency (%)
K 23
12.9%
H 22
12.4%
R 21
11.8%
B 20
11.2%
S 14
 
7.9%
M 10
 
5.6%
I 9
 
5.1%
O 8
 
4.5%
A 6
 
3.4%
D 5
 
2.8%
Other values (12) 40
22.5%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
2 6
33.3%
0 2
 
11.1%
7 1
 
5.6%
6 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 2
33.3%
& 2
33.3%
; 1
16.7%
# 1
16.7%
Space Separator
ValueCountFrequency (%)
73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4366
85.6%
Latin 473
 
9.3%
Common 228
 
4.5%
Han 31
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 186
 
4.3%
스 161
 
3.7%
북 132
 
3.0%
이 111
 
2.5%
문 95
 
2.2%
학 87
 
2.0%
지 75
 
1.7%
어 75
 
1.7%
아 72
 
1.6%
판 62
 
1.4%
Other values (416) 3310
75.8%
Latin
ValueCountFrequency (%)
o 48
 
10.1%
k 24
 
5.1%
K 23
 
4.9%
a 23
 
4.9%
H 22
 
4.7%
n 22
 
4.7%
R 21
 
4.4%
B 20
 
4.2%
r 20
 
4.2%
e 20
 
4.2%
Other values (35) 230
48.6%
Han
ValueCountFrequency (%)
文 4
 
12.9%
社 3
 
9.7%
法 2
 
6.5%
學 2
 
6.5%
光 1
 
3.2%
閣 1
 
3.2%
究 1
 
3.2%
校 1
 
3.2%
民 1
 
3.2%
族 1
 
3.2%
Other values (14) 14
45.2%
Common
ValueCountFrequency (%)
73
32.0%
) 65
28.5%
( 65
28.5%
1 8
 
3.5%
2 6
 
2.6%
. 2
 
0.9%
& 2
 
0.9%
0 2
 
0.9%
; 1
 
0.4%
7 1
 
0.4%
Other values (3) 3
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4364
85.6%
ASCII 701
 
13.8%
CJK 31
 
0.6%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 186
 
4.3%
스 161
 
3.7%
북 132
 
3.0%
이 111
 
2.5%
문 95
 
2.2%
학 87
 
2.0%
지 75
 
1.7%
어 75
 
1.7%
아 72
 
1.6%
판 62
 
1.4%
Other values (414) 3308
75.8%
ASCII
ValueCountFrequency (%)
73
 
10.4%
) 65
 
9.3%
( 65
 
9.3%
o 48
 
6.8%
k 24
 
3.4%
K 23
 
3.3%
a 23
 
3.3%
H 22
 
3.1%
n 22
 
3.1%
R 21
 
3.0%
Other values (48) 315
44.9%
CJK
ValueCountFrequency (%)
文 4
 
12.9%
社 3
 
9.7%
法 2
 
6.5%
學 2
 
6.5%
光 1
 
3.2%
閣 1
 
3.2%
究 1
 
3.2%
校 1
 
3.2%
民 1
 
3.2%
族 1
 
3.2%
Other values (14) 14
45.2%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
50.0%
ㅎ 1
50.0%

발행년
Categorical

Distinct32
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023
452 
2022
259 
2024
120 
2021
 
36
2020
 
30
Other values (27)
107 

Length

Max length10
Median length4
Mean length4.0179283
Min length4

Unique

Unique5 ?
Unique (%)0.5%

Sample

1st row2022
2nd row2023
3rd row2023
4th row2023
5th row2021

Common Values

ValueCountFrequency (%)
2023 452
45.0%
2022 259
25.8%
2024 120
 
12.0%
2021 36
 
3.6%
2020 30
 
3.0%
2015 22
 
2.2%
2018 11
 
1.1%
2013 8
 
0.8%
2023; 8
 
0.8%
2010 6
 
0.6%
Other values (22) 52
 
5.2%

Length

2024-04-06T17:09:32.564723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023 460
45.8%
2022 259
25.8%
2024 123
 
12.3%
2021 36
 
3.6%
2020 30
 
3.0%
2015 22
 
2.2%
2018 11
 
1.1%
2013 8
 
0.8%
2010 6
 
0.6%
2011 5
 
0.5%
Other values (19) 44
 
4.4%

Missing values

2024-04-06T17:09:26.719675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:09:26.893017image/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

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