Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells62
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.6 KiB
Average record size in memory40.0 B

Variable types

Text4

Dataset

Description농식품공무원교육원 집합교육 교육생 및 직원을 위해 대여하고 있는 농식품분야 및 다양한 분야 등 소장하고 있는 도서목록
Author농림축산식품부 농식품공무원교육원
URLhttps://www.data.go.kr/data/15025405/fileData.do

Alerts

등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:16:19.847837
Analysis finished2023-12-12 06:16:22.032685
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:16:22.297925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st rowAM0011542
2nd rowAM0009384
3rd rowAM0010909
4th rowAM0014189
5th rowAM0006771
ValueCountFrequency (%)
am0011542 1
 
< 0.1%
am0005732 1
 
< 0.1%
am0001777 1
 
< 0.1%
am0005787 1
 
< 0.1%
am0001207 1
 
< 0.1%
am0009777 1
 
< 0.1%
am0010367 1
 
< 0.1%
am0004327 1
 
< 0.1%
am0010146 1
 
< 0.1%
am0011045 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T15:16:22.764901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30404
33.8%
A 10000
 
11.1%
M 10000
 
11.1%
1 8543
 
9.5%
2 4594
 
5.1%
3 4267
 
4.7%
4 4037
 
4.5%
6 3942
 
4.4%
7 3883
 
4.3%
5 3814
 
4.2%
Other values (2) 6516
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70000
77.8%
Uppercase Letter 20000
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30404
43.4%
1 8543
 
12.2%
2 4594
 
6.6%
3 4267
 
6.1%
4 4037
 
5.8%
6 3942
 
5.6%
7 3883
 
5.5%
5 3814
 
5.4%
9 3509
 
5.0%
8 3007
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 10000
50.0%
M 10000
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
77.8%
Latin 20000
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30404
43.4%
1 8543
 
12.2%
2 4594
 
6.6%
3 4267
 
6.1%
4 4037
 
5.8%
6 3942
 
5.6%
7 3883
 
5.5%
5 3814
 
5.4%
9 3509
 
5.0%
8 3007
 
4.3%
Latin
ValueCountFrequency (%)
A 10000
50.0%
M 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30404
33.8%
A 10000
 
11.1%
M 10000
 
11.1%
1 8543
 
9.5%
2 4594
 
5.1%
3 4267
 
4.7%
4 4037
 
4.5%
6 3942
 
4.4%
7 3883
 
4.3%
5 3814
 
4.2%
Other values (2) 6516
 
7.2%

도서명
Text

Distinct9593
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:16:23.122740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length94
Mean length25.1856
Min length1

Characters and Unicode

Total characters251856
Distinct characters1884
Distinct categories17 ?
Distinct scripts7 ?
Distinct blocks15 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9263 ?
Unique (%)92.6%

Sample

1st row주름 : 박범신 장편소설
2nd row절대강자
3rd row어느 시골 신부의 일기
4th row나는 미술관에 간다:전문가의 맞춤 해설로 내 방에서 즐기는 세계 10대 미술관
5th row환경스페셜7집(특선2) : 6. 초고층 아파트, 대안인가 재앙인가, 제3의 피부 집, 흙으로 부활하다
ValueCountFrequency (%)
2123
 
3.8%
위한 384
 
0.7%
dvd 334
 
0.6%
이야기 292
 
0.5%
2 262
 
0.5%
1 257
 
0.5%
of 209
 
0.4%
the 200
 
0.4%
및 193
 
0.3%
장편소설 179
 
0.3%
Other values (23059) 51625
92.1%
2023-12-12T15:16:23.729167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47588
 
18.9%
의 4645
 
1.8%
: 4172
 
1.7%
이 3176
 
1.3%
) 2814
 
1.1%
( 2813
 
1.1%
는 2655
 
1.1%
e 2627
 
1.0%
기 2466
 
1.0%
1 2358
 
0.9%
Other values (1874) 176542
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148357
58.9%
Space Separator 47589
 
18.9%
Lowercase Letter 21326
 
8.5%
Decimal Number 10133
 
4.0%
Other Punctuation 8851
 
3.5%
Uppercase Letter 7972
 
3.2%
Close Punctuation 2842
 
1.1%
Open Punctuation 2841
 
1.1%
Math Symbol 1187
 
0.5%
Dash Punctuation 393
 
0.2%
Other values (7) 365
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 4645
 
3.1%
이 3176
 
2.1%
는 2655
 
1.8%
기 2466
 
1.7%
사 2343
 
1.6%
한 2276
 
1.5%
지 1966
 
1.3%
가 1913
 
1.3%
리 1767
 
1.2%
다 1674
 
1.1%
Other values (1756) 123476
83.2%
Lowercase Letter
ValueCountFrequency (%)
e 2627
12.3%
o 1787
 
8.4%
a 1729
 
8.1%
i 1721
 
8.1%
r 1689
 
7.9%
t 1557
 
7.3%
n 1543
 
7.2%
s 1253
 
5.9%
l 1060
 
5.0%
u 834
 
3.9%
Other values (17) 5526
25.9%
Uppercase Letter
ValueCountFrequency (%)
D 1321
16.6%
T 584
 
7.3%
V 561
 
7.0%
A 548
 
6.9%
E 536
 
6.7%
S 507
 
6.4%
O 435
 
5.5%
R 406
 
5.1%
C 397
 
5.0%
I 349
 
4.4%
Other values (16) 2328
29.2%
Other Punctuation
ValueCountFrequency (%)
: 4172
47.1%
. 1444
 
16.3%
, 1360
 
15.4%
; 930
 
10.5%
! 253
 
2.9%
· 238
 
2.7%
? 139
 
1.6%
/ 123
 
1.4%
& 103
 
1.2%
% 49
 
0.6%
Other values (4) 40
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 2358
23.3%
0 2244
22.1%
2 2150
21.2%
3 777
 
7.7%
5 575
 
5.7%
4 515
 
5.1%
9 464
 
4.6%
7 375
 
3.7%
6 357
 
3.5%
8 318
 
3.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 47
37.6%
Ⅰ 38
30.4%
Ⅲ 20
16.0%
Ⅳ 14
 
11.2%
Ⅴ 4
 
3.2%
ⅴ 1
 
0.8%
Ⅵ 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 2814
99.0%
] 24
 
0.8%
」 1
 
< 0.1%
} 1
 
< 0.1%
》 1
 
< 0.1%
』 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2813
99.0%
[ 24
 
0.8%
「 1
 
< 0.1%
{ 1
 
< 0.1%
《 1
 
< 0.1%
『 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 1015
85.5%
~ 72
 
6.1%
< 41
 
3.5%
> 41
 
3.5%
+ 18
 
1.5%
Other Number
ValueCountFrequency (%)
① 3
50.0%
② 1
 
16.7%
③ 1
 
16.7%
④ 1
 
16.7%
Modifier Symbol
ValueCountFrequency (%)
` 137
61.4%
´ 84
37.7%
˚ 2
 
0.9%
Other Symbol
ValueCountFrequency (%)
│ 5
71.4%
℃ 1
 
14.3%
□ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
47588
> 99.9%
　 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 391
99.5%
― 2
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146116
58.0%
Common 74076
29.4%
Latin 29421
 
11.7%
Han 2201
 
0.9%
Katakana 24
 
< 0.1%
Hiragana 16
 
< 0.1%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 4645
 
3.2%
이 3176
 
2.2%
는 2655
 
1.8%
기 2466
 
1.7%
사 2343
 
1.6%
한 2276
 
1.6%
지 1966
 
1.3%
가 1913
 
1.3%
리 1767
 
1.2%
다 1674
 
1.1%
Other values (1182) 121235
83.0%
Han
ValueCountFrequency (%)
國 55
 
2.5%
家 50
 
2.3%
德 44
 
2.0%
川 43
 
2.0%
康 43
 
2.0%
說 36
 
1.6%
小 35
 
1.6%
三 35
 
1.6%
大 35
 
1.6%
志 30
 
1.4%
Other values (535) 1795
81.6%
Latin
ValueCountFrequency (%)
e 2627
 
8.9%
o 1787
 
6.1%
a 1729
 
5.9%
i 1721
 
5.8%
r 1689
 
5.7%
t 1557
 
5.3%
n 1543
 
5.2%
D 1321
 
4.5%
s 1253
 
4.3%
l 1060
 
3.6%
Other values (49) 13134
44.6%
Common
ValueCountFrequency (%)
47588
64.2%
: 4172
 
5.6%
) 2814
 
3.8%
( 2813
 
3.8%
1 2358
 
3.2%
0 2244
 
3.0%
2 2150
 
2.9%
. 1444
 
1.9%
, 1360
 
1.8%
= 1015
 
1.4%
Other values (48) 6118
 
8.3%
Katakana
ValueCountFrequency (%)
ス 3
12.5%
リ 2
 
8.3%
ム 2
 
8.3%
テ 2
 
8.3%
ド 2
 
8.3%
フ 2
 
8.3%
シ 1
 
4.2%
ツ 1
 
4.2%
ネ 1
 
4.2%
ヅ 1
 
4.2%
Other values (7) 7
29.2%
Hiragana
ValueCountFrequency (%)
の 3
18.8%
か 2
12.5%
る 2
12.5%
も 1
 
6.2%
め 1
 
6.2%
を 1
 
6.2%
え 1
 
6.2%
と 1
 
6.2%
よ 1
 
6.2%
ゎ 1
 
6.2%
Other values (2) 2
12.5%
Greek
ValueCountFrequency (%)
α 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146098
58.0%
ASCII 103022
40.9%
CJK 2154
 
0.9%
None 331
 
0.1%
Number Forms 125
 
< 0.1%
CJK Compat Ideographs 47
 
< 0.1%
Katakana 24
 
< 0.1%
Compat Jamo 18
 
< 0.1%
Hiragana 16
 
< 0.1%
Enclosed Alphanum 6
 
< 0.1%
Other values (5) 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47588
46.2%
: 4172
 
4.0%
) 2814
 
2.7%
( 2813
 
2.7%
e 2627
 
2.5%
1 2358
 
2.3%
0 2244
 
2.2%
2 2150
 
2.1%
o 1787
 
1.7%
a 1729
 
1.7%
Other values (79) 32740
31.8%
Hangul
ValueCountFrequency (%)
의 4645
 
3.2%
이 3176
 
2.2%
는 2655
 
1.8%
기 2466
 
1.7%
사 2343
 
1.6%
한 2276
 
1.6%
지 1966
 
1.3%
가 1913
 
1.3%
리 1767
 
1.2%
다 1674
 
1.1%
Other values (1172) 121217
83.0%
None
ValueCountFrequency (%)
· 238
71.9%
´ 84
 
25.4%
α 2
 
0.6%
　 1
 
0.3%
」 1
 
0.3%
「 1
 
0.3%
》 1
 
0.3%
《 1
 
0.3%
』 1
 
0.3%
『 1
 
0.3%
CJK
ValueCountFrequency (%)
國 55
 
2.6%
家 50
 
2.3%
德 44
 
2.0%
川 43
 
2.0%
康 43
 
2.0%
說 36
 
1.7%
小 35
 
1.6%
三 35
 
1.6%
大 35
 
1.6%
志 30
 
1.4%
Other values (514) 1748
81.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 47
37.6%
Ⅰ 38
30.4%
Ⅲ 20
16.0%
Ⅳ 14
 
11.2%
Ⅴ 4
 
3.2%
ⅴ 1
 
0.8%
Ⅵ 1
 
0.8%
CJK Compat Ideographs
ValueCountFrequency (%)
林 11
23.4%
盧 6
12.8%
不 5
10.6%
女 4
 
8.5%
李 2
 
4.3%
落 2
 
4.3%
論 2
 
4.3%
茶 2
 
4.3%
力 1
 
2.1%
蘭 1
 
2.1%
Other values (11) 11
23.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
38.9%
ㄱ 2
 
11.1%
ㅁ 2
 
11.1%
ㅎ 1
 
5.6%
ㅈ 1
 
5.6%
ㅂ 1
 
5.6%
ㅇ 1
 
5.6%
ㄷ 1
 
5.6%
ㄴ 1
 
5.6%
ㄹ 1
 
5.6%
Box Drawing
ValueCountFrequency (%)
│ 5
100.0%
Hiragana
ValueCountFrequency (%)
の 3
18.8%
か 2
12.5%
る 2
12.5%
も 1
 
6.2%
め 1
 
6.2%
を 1
 
6.2%
え 1
 
6.2%
と 1
 
6.2%
よ 1
 
6.2%
ゎ 1
 
6.2%
Other values (2) 2
12.5%
Katakana
ValueCountFrequency (%)
ス 3
12.5%
リ 2
 
8.3%
ム 2
 
8.3%
テ 2
 
8.3%
ド 2
 
8.3%
フ 2
 
8.3%
シ 1
 
4.2%
ツ 1
 
4.2%
ネ 1
 
4.2%
ヅ 1
 
4.2%
Other values (7) 7
29.2%
Enclosed Alphanum
ValueCountFrequency (%)
① 3
50.0%
② 1
 
16.7%
③ 1
 
16.7%
④ 1
 
16.7%
Modifier Letters
ValueCountFrequency (%)
˚ 2
100.0%
Punctuation
ValueCountFrequency (%)
― 2
33.3%
… 2
33.3%
‘ 1
16.7%
’ 1
16.7%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
Geometric Shapes
ValueCountFrequency (%)
□ 1
100.0%

저자명
Text

Distinct6911
Distinct (%)69.2%
Missing15
Missing (%)0.1%
Memory size156.2 KiB
2023-12-12T15:16:24.059179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length324
Median length195
Mean length12.777066
Min length1

Characters and Unicode

Total characters127579
Distinct characters1178
Distinct categories14 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5911 ?
Unique (%)59.2%

Sample

1st row박범신
2nd row이외수;정태련 그림
3rd row조르주 베르나노스 지음;정영란 옮김
4th row김영애 지음
5th rowKBS미디어
ValueCountFrequency (%)
지음 2553
 
8.8%
옮김 2004
 
6.9%
저 493
 
1.7%
지은이 407
 
1.4%
385
 
1.3%
그림 289
 
1.0%
편 280
 
1.0%
글 256
 
0.9%
공저 179
 
0.6%
한국농촌경제연구원 144
 
0.5%
Other values (10810) 21863
75.8%
2023-12-12T15:16:24.621888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20000
 
15.7%
; 4754
 
3.7%
지 4507
 
3.5%
김 4327
 
3.4%
음 3594
 
2.8%
이 3282
 
2.6%
, 2848
 
2.2%
옮 2230
 
1.7%
정 1564
 
1.2%
원 1279
 
1.0%
Other values (1168) 79194
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89381
70.1%
Space Separator 20000
 
15.7%
Other Punctuation 9441
 
7.4%
Lowercase Letter 3653
 
2.9%
Uppercase Letter 2736
 
2.1%
Open Punctuation 1091
 
0.9%
Close Punctuation 1090
 
0.9%
Decimal Number 92
 
0.1%
Math Symbol 52
 
< 0.1%
Dash Punctuation 20
 
< 0.1%
Other values (4) 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4507
 
5.0%
김 4327
 
4.8%
음 3594
 
4.0%
이 3282
 
3.7%
옮 2230
 
2.5%
정 1564
 
1.7%
원 1279
 
1.4%
영 1202
 
1.3%
림 1102
 
1.2%
저 1101
 
1.2%
Other values (1079) 65193
72.9%
Lowercase Letter
ValueCountFrequency (%)
a 526
14.4%
i 419
11.5%
e 330
 
9.0%
o 286
 
7.8%
r 223
 
6.1%
s 206
 
5.6%
t 206
 
5.6%
u 203
 
5.6%
n 196
 
5.4%
h 175
 
4.8%
Other values (15) 883
24.2%
Uppercase Letter
ValueCountFrequency (%)
S 372
13.6%
B 346
12.6%
E 251
 
9.2%
A 200
 
7.3%
K 169
 
6.2%
T 161
 
5.9%
O 139
 
5.1%
D 136
 
5.0%
C 126
 
4.6%
R 118
 
4.3%
Other values (15) 718
26.2%
Decimal Number
ValueCountFrequency (%)
0 21
22.8%
2 20
21.7%
1 11
12.0%
5 10
10.9%
6 10
10.9%
4 8
 
8.7%
3 7
 
7.6%
9 2
 
2.2%
8 2
 
2.2%
7 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
; 4754
50.4%
, 2848
30.2%
: 775
 
8.2%
. 643
 
6.8%
· 379
 
4.0%
/ 17
 
0.2%
& 17
 
0.2%
? 7
 
0.1%
# 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 992
90.9%
( 97
 
8.9%
〈 1
 
0.1%
『 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
] 990
90.8%
) 98
 
9.0%
〉 1
 
0.1%
』 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
< 25
48.1%
> 24
46.2%
| 2
 
3.8%
= 1
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 19
95.0%
― 1
 
5.0%
Modifier Symbol
ValueCountFrequency (%)
´ 4
66.7%
` 2
33.3%
Space Separator
ValueCountFrequency (%)
20000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Control
ValueCountFrequency (%)
 2
100.0%
Other Symbol
ValueCountFrequency (%)
ⓔ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88570
69.4%
Common 31809
 
24.9%
Latin 6389
 
5.0%
Han 792
 
0.6%
Hiragana 13
 
< 0.1%
Katakana 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4507
 
5.1%
김 4327
 
4.9%
음 3594
 
4.1%
이 3282
 
3.7%
옮 2230
 
2.5%
정 1564
 
1.8%
원 1279
 
1.4%
영 1202
 
1.4%
림 1102
 
1.2%
저 1101
 
1.2%
Other values (818) 64382
72.7%
Han
ValueCountFrequency (%)
著 97
 
12.2%
趙 31
 
3.9%
李 31
 
3.9%
來 29
 
3.7%
廷 29
 
3.7%
編 21
 
2.7%
共 20
 
2.5%
國 16
 
2.0%
譯 15
 
1.9%
金 12
 
1.5%
Other values (234) 491
62.0%
Latin
ValueCountFrequency (%)
a 526
 
8.2%
i 419
 
6.6%
S 372
 
5.8%
B 346
 
5.4%
e 330
 
5.2%
o 286
 
4.5%
E 251
 
3.9%
r 223
 
3.5%
s 206
 
3.2%
t 206
 
3.2%
Other values (40) 3224
50.5%
Common
ValueCountFrequency (%)
20000
62.9%
; 4754
 
14.9%
, 2848
 
9.0%
[ 992
 
3.1%
] 990
 
3.1%
: 775
 
2.4%
. 643
 
2.0%
· 379
 
1.2%
) 98
 
0.3%
( 97
 
0.3%
Other values (29) 233
 
0.7%
Hiragana
ValueCountFrequency (%)
お 2
15.4%
つ 2
15.4%
る 1
7.7%
げ 1
7.7%
し 1
7.7%
か 1
7.7%
み 1
7.7%
き 1
7.7%
ぱ 1
7.7%
く 1
7.7%
Katakana
ValueCountFrequency (%)
フ 1
16.7%
ム 1
16.7%
テ 1
16.7%
ス 1
16.7%
ツ 1
16.7%
ド 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88566
69.4%
ASCII 37809
29.6%
CJK 742
 
0.6%
None 387
 
0.3%
CJK Compat Ideographs 50
 
< 0.1%
Hiragana 13
 
< 0.1%
Katakana 6
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20000
52.9%
; 4754
 
12.6%
, 2848
 
7.5%
[ 992
 
2.6%
] 990
 
2.6%
: 775
 
2.0%
. 643
 
1.7%
a 526
 
1.4%
i 419
 
1.1%
S 372
 
1.0%
Other values (71) 5490
 
14.5%
Hangul
ValueCountFrequency (%)
지 4507
 
5.1%
김 4327
 
4.9%
음 3594
 
4.1%
이 3282
 
3.7%
옮 2230
 
2.5%
정 1564
 
1.8%
원 1279
 
1.4%
영 1202
 
1.4%
림 1102
 
1.2%
저 1101
 
1.2%
Other values (817) 64378
72.7%
None
ValueCountFrequency (%)
· 379
97.9%
´ 4
 
1.0%
〉 1
 
0.3%
〈 1
 
0.3%
』 1
 
0.3%
『 1
 
0.3%
CJK
ValueCountFrequency (%)
著 97
 
13.1%
趙 31
 
4.2%
來 29
 
3.9%
廷 29
 
3.9%
編 21
 
2.8%
共 20
 
2.7%
國 16
 
2.2%
譯 15
 
2.0%
金 12
 
1.6%
部 12
 
1.6%
Other values (226) 460
62.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 31
62.0%
烈 12
 
24.0%
龍 2
 
4.0%
沈 1
 
2.0%
寧 1
 
2.0%
玲 1
 
2.0%
劉 1
 
2.0%
列 1
 
2.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%
Hiragana
ValueCountFrequency (%)
お 2
15.4%
つ 2
15.4%
る 1
7.7%
げ 1
7.7%
し 1
7.7%
か 1
7.7%
み 1
7.7%
き 1
7.7%
ぱ 1
7.7%
く 1
7.7%
Enclosed Alphanum
ValueCountFrequency (%)
ⓔ 1
100.0%
Katakana
ValueCountFrequency (%)
フ 1
16.7%
ム 1
16.7%
テ 1
16.7%
ス 1
16.7%
ツ 1
16.7%
ド 1
16.7%
Punctuation
ValueCountFrequency (%)
― 1
100.0%

출판사
Text

Distinct3426
Distinct (%)34.4%
Missing47
Missing (%)0.5%
Memory size156.2 KiB
2023-12-12T15:16:24.878148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length46
Mean length7.0297398
Min length1

Characters and Unicode

Total characters69967
Distinct characters809
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

Unique2164 ?
Unique (%)21.7%

Sample

1st row한겨레출판
2nd row해냄
3rd row민음사
4th row서울 :마로니에북스
5th rowKBS미디어
ValueCountFrequency (%)
서울 570
 
4.5%
한국농촌경제연구원 304
 
2.4%
파주 264
 
2.1%
김영사 150
 
1.2%
141
 
1.1%
농림수산식품부 134
 
1.1%
한국여성정책연구원 118
 
0.9%
ebs 116
 
0.9%
농촌진흥청 115
 
0.9%
민음사 115
 
0.9%
Other values (3007) 10601
83.9%
2023-12-12T15:16:25.333178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4313
 
6.2%
사 2090
 
3.0%
주 1623
 
2.3%
: 1607
 
2.3%
) 1502
 
2.1%
( 1502
 
2.1%
스 1483
 
2.1%
판 1409
 
2.0%
출 1385
 
2.0%
서 1371
 
2.0%
Other values (799) 51682
73.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55840
79.8%
Space Separator 4313
 
6.2%
Uppercase Letter 2236
 
3.2%
Other Punctuation 1953
 
2.8%
Lowercase Letter 1951
 
2.8%
Close Punctuation 1627
 
2.3%
Open Punctuation 1627
 
2.3%
Decimal Number 398
 
0.6%
Dash Punctuation 18
 
< 0.1%
Modifier Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 2090
 
3.7%
주 1623
 
2.9%
스 1483
 
2.7%
판 1409
 
2.5%
출 1385
 
2.5%
서 1371
 
2.5%
원 1168
 
2.1%
농 1147
 
2.1%
한 1016
 
1.8%
문 989
 
1.8%
Other values (718) 42159
75.5%
Uppercase Letter
ValueCountFrequency (%)
B 382
17.1%
S 281
12.6%
E 278
12.4%
K 145
 
6.5%
M 141
 
6.3%
C 132
 
5.9%
O 104
 
4.7%
R 102
 
4.6%
D 101
 
4.5%
H 96
 
4.3%
Other values (16) 474
21.2%
Lowercase Letter
ValueCountFrequency (%)
o 306
15.7%
e 187
 
9.6%
i 174
 
8.9%
n 145
 
7.4%
s 132
 
6.8%
a 131
 
6.7%
t 116
 
5.9%
r 95
 
4.9%
l 88
 
4.5%
k 87
 
4.5%
Other values (15) 490
25.1%
Other Punctuation
ValueCountFrequency (%)
: 1607
82.3%
; 142
 
7.3%
, 76
 
3.9%
& 73
 
3.7%
. 37
 
1.9%
? 6
 
0.3%
/ 6
 
0.3%
· 4
 
0.2%
* 1
 
0.1%
" 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 164
41.2%
1 146
36.7%
0 42
 
10.6%
3 13
 
3.3%
5 8
 
2.0%
4 7
 
1.8%
6 6
 
1.5%
7 6
 
1.5%
8 4
 
1.0%
9 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 1502
92.3%
] 125
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 1502
92.3%
[ 125
 
7.7%
Modifier Symbol
ValueCountFrequency (%)
` 1
50.0%
´ 1
50.0%
Math Symbol
ValueCountFrequency (%)
| 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
4313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55543
79.4%
Common 9940
 
14.2%
Latin 4187
 
6.0%
Han 293
 
0.4%
Katakana 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 2090
 
3.8%
주 1623
 
2.9%
스 1483
 
2.7%
판 1409
 
2.5%
출 1385
 
2.5%
서 1371
 
2.5%
원 1168
 
2.1%
농 1147
 
2.1%
한 1016
 
1.8%
문 989
 
1.8%
Other values (606) 41862
75.4%
Han
ValueCountFrequency (%)
社 43
 
14.7%
文 13
 
4.4%
民 12
 
4.1%
部 11
 
3.8%
音 11
 
3.8%
林 10
 
3.4%
農 10
 
3.4%
版 8
 
2.7%
出 8
 
2.7%
法 7
 
2.4%
Other values (98) 160
54.6%
Latin
ValueCountFrequency (%)
B 382
 
9.1%
o 306
 
7.3%
S 281
 
6.7%
E 278
 
6.6%
e 187
 
4.5%
i 174
 
4.2%
n 145
 
3.5%
K 145
 
3.5%
M 141
 
3.4%
C 132
 
3.2%
Other values (41) 2016
48.1%
Common
ValueCountFrequency (%)
4313
43.4%
: 1607
 
16.2%
) 1502
 
15.1%
( 1502
 
15.1%
2 164
 
1.6%
1 146
 
1.5%
; 142
 
1.4%
[ 125
 
1.3%
] 125
 
1.3%
, 76
 
0.8%
Other values (20) 238
 
2.4%
Katakana
ValueCountFrequency (%)
テ 1
25.0%
ム 1
25.0%
ス 1
25.0%
シ 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55543
79.4%
ASCII 14122
 
20.2%
CJK 293
 
0.4%
None 5
 
< 0.1%
Katakana 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4313
30.5%
: 1607
 
11.4%
) 1502
 
10.6%
( 1502
 
10.6%
B 382
 
2.7%
o 306
 
2.2%
S 281
 
2.0%
E 278
 
2.0%
e 187
 
1.3%
i 174
 
1.2%
Other values (69) 3590
25.4%
Hangul
ValueCountFrequency (%)
사 2090
 
3.8%
주 1623
 
2.9%
스 1483
 
2.7%
판 1409
 
2.5%
출 1385
 
2.5%
서 1371
 
2.5%
원 1168
 
2.1%
농 1147
 
2.1%
한 1016
 
1.8%
문 989
 
1.8%
Other values (606) 41862
75.4%
CJK
ValueCountFrequency (%)
社 43
 
14.7%
文 13
 
4.4%
民 12
 
4.1%
部 11
 
3.8%
音 11
 
3.8%
林 10
 
3.4%
農 10
 
3.4%
版 8
 
2.7%
出 8
 
2.7%
法 7
 
2.4%
Other values (98) 160
54.6%
None
ValueCountFrequency (%)
· 4
80.0%
´ 1
 
20.0%
Katakana
ValueCountFrequency (%)
テ 1
25.0%
ム 1
25.0%
ス 1
25.0%
シ 1
25.0%

Missing values

2023-12-12T15:16:21.803357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:16:21.894944image/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.
2023-12-12T15:16:21.980671image/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

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