Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells149156
Missing cells (%)82.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory155.0 B

Variable types

Text15
Unsupported3

Dataset

Description충남도서관 소장 도서에 대한 정보로, 개별 도서에 대한 메타데이터(서명, 저자명, 발행처, 청구기호, ISBN 등의 정보)가 포함되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=26&beforeMenuCd=DOM_000000201001001000&publicdatapk=15119625

Alerts

Unnamed: 14 has constant value ""Constant
Unnamed: 3 has 9402 (94.0%) missing valuesMissing
Unnamed: 4 has 9849 (98.5%) missing valuesMissing
Unnamed: 5 has 9960 (99.6%) missing valuesMissing
Unnamed: 6 has 9985 (99.9%) missing valuesMissing
Unnamed: 7 has 9992 (99.9%) missing valuesMissing
Unnamed: 8 has 9993 (99.9%) missing valuesMissing
Unnamed: 9 has 9995 (> 99.9%) missing valuesMissing
Unnamed: 10 has 9995 (> 99.9%) missing valuesMissing
Unnamed: 11 has 9995 (> 99.9%) missing valuesMissing
Unnamed: 12 has 9996 (> 99.9%) missing valuesMissing
Unnamed: 13 has 9996 (> 99.9%) missing valuesMissing
Unnamed: 14 has 9998 (> 99.9%) missing valuesMissing
Unnamed: 15 has 10000 (100.0%) missing valuesMissing
Unnamed: 16 has 10000 (100.0%) missing valuesMissing
Unnamed: 17 has 10000 (100.0%) missing valuesMissing
등록번호 has unique valuesUnique
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 23:17:26.189523
Analysis finished2024-01-09 23:17:29.079205
Duration2.89 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
2024-01-10T08:17:29.253351image/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 rowKM0025061
2nd rowKM0004967
3rd rowKM0005259
4th rowKM0055067
5th rowKM0060951
ValueCountFrequency (%)
km0025061 1
 
< 0.1%
km0050468 1
 
< 0.1%
km0008212 1
 
< 0.1%
km0067697 1
 
< 0.1%
km0071045 1
 
< 0.1%
km0033746 1
 
< 0.1%
km0075594 1
 
< 0.1%
km0016876 1
 
< 0.1%
km0062025 1
 
< 0.1%
km0021533 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-01-10T08:17:29.577952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25175
28.0%
K 10000
 
11.1%
M 10000
 
11.1%
6 5590
 
6.2%
5 5384
 
6.0%
4 5343
 
5.9%
3 5330
 
5.9%
2 5321
 
5.9%
1 5203
 
5.8%
7 4922
 
5.5%
Other values (2) 7732
 
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25175
36.0%
6 5590
 
8.0%
5 5384
 
7.7%
4 5343
 
7.6%
3 5330
 
7.6%
2 5321
 
7.6%
1 5203
 
7.4%
7 4922
 
7.0%
9 3890
 
5.6%
8 3842
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
K 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 25175
36.0%
6 5590
 
8.0%
5 5384
 
7.7%
4 5343
 
7.6%
3 5330
 
7.6%
2 5321
 
7.6%
1 5203
 
7.4%
7 4922
 
7.0%
9 3890
 
5.6%
8 3842
 
5.5%
Latin
ValueCountFrequency (%)
K 10000
50.0%
M 10000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25175
28.0%
K 10000
 
11.1%
M 10000
 
11.1%
6 5590
 
6.2%
5 5384
 
6.0%
4 5343
 
5.9%
3 5330
 
5.9%
2 5321
 
5.9%
1 5203
 
5.8%
7 4922
 
5.5%
Other values (2) 7732
 
8.6%

서명
Text

Distinct9321
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:17:29.879896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length214
Median length145
Mean length20.9773
Min length1

Characters and Unicode

Total characters209773
Distinct characters2196
Distinct categories18 ?
Distinct scripts6 ?
Distinct blocks14 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8716 ?
Unique (%)87.2%

Sample

1st row지식논쟁 : 포스트모던 시대의 사회이론
2nd row법화행자의 초상
3rd row한국문화와 한국인
4th row바리스타 = Barista. 1
5th row(2014) 상수도 통계 = STATISTICS OF WATERWORKS
ValueCountFrequency (%)
5234
 
10.8%
2 330
 
0.7%
장편소설 318
 
0.7%
1 303
 
0.6%
of 262
 
0.5%
the 198
 
0.4%
연구 194
 
0.4%
위한 192
 
0.4%
및 172
 
0.4%
한국 140
 
0.3%
Other values (21405) 41291
84.9%
2024-01-10T08:17:30.313306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39121
 
18.6%
: 4307
 
2.1%
의 3918
 
1.9%
e 2883
 
1.4%
사 2527
 
1.2%
기 2449
 
1.2%
n 2394
 
1.1%
o 2368
 
1.1%
i 2331
 
1.1%
a 2240
 
1.1%
Other values (2186) 145235
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119985
57.2%
Space Separator 39121
 
18.6%
Lowercase Letter 25899
 
12.3%
Decimal Number 7444
 
3.5%
Other Punctuation 7056
 
3.4%
Uppercase Letter 4744
 
2.3%
Open Punctuation 1994
 
1.0%
Close Punctuation 1973
 
0.9%
Math Symbol 961
 
0.5%
Dash Punctuation 475
 
0.2%
Other values (8) 121
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 3918
 
3.3%
사 2527
 
2.1%
기 2449
 
2.0%
이 2154
 
1.8%
한 1763
 
1.5%
학 1520
 
1.3%
지 1447
 
1.2%
과 1438
 
1.2%
리 1365
 
1.1%
는 1310
 
1.1%
Other values (2065) 100094
83.4%
Lowercase Letter
ValueCountFrequency (%)
e 2883
11.1%
n 2394
 
9.2%
o 2368
 
9.1%
i 2331
 
9.0%
a 2240
 
8.6%
t 2042
 
7.9%
r 1718
 
6.6%
s 1433
 
5.5%
l 1233
 
4.8%
c 1062
 
4.1%
Other values (16) 6195
23.9%
Uppercase Letter
ValueCountFrequency (%)
S 413
 
8.7%
C 395
 
8.3%
A 378
 
8.0%
T 375
 
7.9%
E 319
 
6.7%
I 293
 
6.2%
P 248
 
5.2%
O 238
 
5.0%
M 230
 
4.8%
D 227
 
4.8%
Other values (16) 1628
34.3%
Other Punctuation
ValueCountFrequency (%)
: 4307
61.0%
. 1899
26.9%
· 330
 
4.7%
' 129
 
1.8%
/ 91
 
1.3%
? 82
 
1.2%
! 77
 
1.1%
& 75
 
1.1%
＆ 26
 
0.4%
" 10
 
0.1%
Other values (8) 30
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 1748
23.5%
1 1740
23.4%
0 1479
19.9%
9 565
 
7.6%
3 529
 
7.1%
4 338
 
4.5%
5 307
 
4.1%
8 265
 
3.6%
6 237
 
3.2%
7 236
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 1870
93.8%
[ 89
 
4.5%
『 20
 
1.0%
「 8
 
0.4%
《 3
 
0.2%
〈 2
 
0.1%
【 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1850
93.8%
] 88
 
4.5%
』 20
 
1.0%
」 8
 
0.4%
》 3
 
0.2%
〉 2
 
0.1%
】 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 821
85.4%
~ 58
 
6.0%
+ 57
 
5.9%
< 8
 
0.8%
> 8
 
0.8%
∼ 7
 
0.7%
× 2
 
0.2%
Other Number
ValueCountFrequency (%)
① 2
28.6%
⑤ 1
14.3%
⑨ 1
14.3%
② 1
14.3%
③ 1
14.3%
⑦ 1
14.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 44
45.4%
Ⅰ 35
36.1%
Ⅳ 9
 
9.3%
Ⅲ 7
 
7.2%
Ⅴ 2
 
2.1%
Other Symbol
ValueCountFrequency (%)
★ 4
80.0%
▼ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
39121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 475
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Control
ValueCountFrequency (%)
 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113085
53.9%
Common 59048
28.1%
Latin 30740
 
14.7%
Han 6893
 
3.3%
Katakana 4
 
< 0.1%
Hiragana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 3918
 
3.5%
사 2527
 
2.2%
기 2449
 
2.2%
이 2154
 
1.9%
한 1763
 
1.6%
학 1520
 
1.3%
지 1447
 
1.3%
과 1438
 
1.3%
리 1365
 
1.2%
는 1310
 
1.2%
Other values (1132) 93194
82.4%
Han
ValueCountFrequency (%)
學 241
 
3.5%
國 172
 
2.5%
論 151
 
2.2%
韓 130
 
1.9%
大 121
 
1.8%
法 81
 
1.2%
政 80
 
1.2%
新 77
 
1.1%
代 76
 
1.1%
理 71
 
1.0%
Other values (916) 5693
82.6%
Common
ValueCountFrequency (%)
39121
66.3%
: 4307
 
7.3%
. 1899
 
3.2%
( 1870
 
3.2%
) 1850
 
3.1%
2 1748
 
3.0%
1 1740
 
2.9%
0 1479
 
2.5%
= 821
 
1.4%
9 565
 
1.0%
Other values (54) 3648
 
6.2%
Latin
ValueCountFrequency (%)
e 2883
 
9.4%
n 2394
 
7.8%
o 2368
 
7.7%
i 2331
 
7.6%
a 2240
 
7.3%
t 2042
 
6.6%
r 1718
 
5.6%
s 1433
 
4.7%
l 1233
 
4.0%
c 1062
 
3.5%
Other values (47) 11036
35.9%
Katakana
ValueCountFrequency (%)
ル 1
25.0%
ブ 1
25.0%
タ 1
25.0%
ポ 1
25.0%
Hiragana
ValueCountFrequency (%)
な 1
33.3%
き 1
33.3%
と 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112983
53.9%
ASCII 89227
42.5%
CJK 6725
 
3.2%
None 436
 
0.2%
CJK Compat Ideographs 168
 
0.1%
Compat Jamo 102
 
< 0.1%
Number Forms 97
 
< 0.1%
Punctuation 9
 
< 0.1%
Math Operators 7
 
< 0.1%
Enclosed Alphanum 7
 
< 0.1%
Other values (4) 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39121
43.8%
: 4307
 
4.8%
e 2883
 
3.2%
n 2394
 
2.7%
o 2368
 
2.7%
i 2331
 
2.6%
a 2240
 
2.5%
t 2042
 
2.3%
. 1899
 
2.1%
( 1870
 
2.1%
Other values (79) 27772
31.1%
Hangul
ValueCountFrequency (%)
의 3918
 
3.5%
사 2527
 
2.2%
기 2449
 
2.2%
이 2154
 
1.9%
한 1763
 
1.6%
학 1520
 
1.3%
지 1447
 
1.3%
과 1438
 
1.3%
리 1365
 
1.2%
는 1310
 
1.2%
Other values (1126) 93092
82.4%
None
ValueCountFrequency (%)
· 330
75.7%
＆ 26
 
6.0%
『 20
 
4.6%
』 20
 
4.6%
」 8
 
1.8%
「 8
 
1.8%
％ 6
 
1.4%
《 3
 
0.7%
》 3
 
0.7%
〈 2
 
0.5%
Other values (6) 10
 
2.3%
CJK
ValueCountFrequency (%)
學 241
 
3.6%
國 172
 
2.6%
論 151
 
2.2%
韓 130
 
1.9%
大 121
 
1.8%
法 81
 
1.2%
政 80
 
1.2%
新 77
 
1.1%
代 76
 
1.1%
理 71
 
1.1%
Other values (870) 5525
82.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 93
91.2%
ㄱ 3
 
2.9%
ㅅ 3
 
2.9%
ㄴ 1
 
1.0%
ㅎ 1
 
1.0%
ㅇ 1
 
1.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 44
45.4%
Ⅰ 35
36.1%
Ⅳ 9
 
9.3%
Ⅲ 7
 
7.2%
Ⅴ 2
 
2.1%
CJK Compat Ideographs
ValueCountFrequency (%)
理 25
14.9%
力 20
 
11.9%
李 20
 
11.9%
論 9
 
5.4%
歷 8
 
4.8%
不 6
 
3.6%
年 6
 
3.6%
旅 6
 
3.6%
倫 5
 
3.0%
金 4
 
2.4%
Other values (36) 59
35.1%
Math Operators
ValueCountFrequency (%)
∼ 7
100.0%
Punctuation
ValueCountFrequency (%)
’ 5
55.6%
‘ 4
44.4%
Misc Symbols
ValueCountFrequency (%)
★ 4
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 2
28.6%
⑤ 1
14.3%
⑨ 1
14.3%
② 1
14.3%
③ 1
14.3%
⑦ 1
14.3%
Geometric Shapes
ValueCountFrequency (%)
▼ 1
100.0%
Katakana
ValueCountFrequency (%)
ル 1
25.0%
ブ 1
25.0%
タ 1
25.0%
ポ 1
25.0%
Hiragana
ValueCountFrequency (%)
な 1
33.3%
き 1
33.3%
と 1
33.3%

청구기호
Text

Distinct8515
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-10T08:17:30.526678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length114
Median length62
Mean length12.0622
Min length1

Characters and Unicode

Total characters120622
Distinct characters810
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

Unique7601 ?
Unique (%)76.0%

Sample

1st row300.1-사287ㅈ박
2nd row223.54-곽852ㅂ
3rd row331.50911-국462ㅎ
4th row833.6-하127ㅂ-1-C
5th row539.1025-환619ㅅ-G
ValueCountFrequency (%)
132
 
1.2%
080-대383-r 37
 
0.3%
그리고 24
 
0.2%
322.004-국464ㄱ-g 23
 
0.2%
그 20
 
0.2%
337-충85ㅊ-g 19
 
0.2%
833.6-아334ㅋ오-c 16
 
0.1%
813.608-동875ㅎ 13
 
0.1%
080-시316 12
 
0.1%
320.911-한419ㅇ-g 11
 
0.1%
Other values (9361) 11039
97.3%
2024-01-10T08:17:30.861860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 11101
 
9.2%
3 10126
 
8.4%
1 9923
 
8.2%
. 7644
 
6.3%
5 7549
 
6.3%
9 7403
 
6.1%
8 7230
 
6.0%
6 6735
 
5.6%
7 6681
 
5.5%
2 6161
 
5.1%
Other values (800) 40069
33.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71960
59.7%
Other Letter 25345
 
21.0%
Dash Punctuation 11101
 
9.2%
Other Punctuation 7795
 
6.5%
Space Separator 1896
 
1.6%
Uppercase Letter 1878
 
1.6%
Lowercase Letter 574
 
0.5%
Close Punctuation 28
 
< 0.1%
Math Symbol 23
 
< 0.1%
Open Punctuation 18
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ㅇ 1545
 
6.1%
김 1443
 
5.7%
ㅅ 1337
 
5.3%
이 1315
 
5.2%
ㄱ 1226
 
4.8%
ㅎ 1164
 
4.6%
ㅈ 1062
 
4.2%
ㄷ 591
 
2.3%
ㅂ 538
 
2.1%
박 525
 
2.1%
Other values (719) 14599
57.6%
Uppercase Letter
ValueCountFrequency (%)
G 485
25.8%
R 415
22.1%
C 323
17.2%
E 201
10.7%
X 196
10.4%
U 111
 
5.9%
A 32
 
1.7%
T 29
 
1.5%
S 10
 
0.5%
D 9
 
0.5%
Other values (16) 67
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
e 60
 
10.5%
o 59
 
10.3%
i 47
 
8.2%
a 47
 
8.2%
t 45
 
7.8%
n 41
 
7.1%
r 37
 
6.4%
s 33
 
5.7%
u 27
 
4.7%
l 25
 
4.4%
Other values (13) 153
26.7%
Decimal Number
ValueCountFrequency (%)
3 10126
14.1%
1 9923
13.8%
5 7549
10.5%
9 7403
10.3%
8 7230
10.0%
6 6735
9.4%
7 6681
9.3%
2 6161
8.6%
4 5685
7.9%
0 4467
6.2%
Other Punctuation
ValueCountFrequency (%)
. 7644
98.1%
: 108
 
1.4%
? 16
 
0.2%
! 14
 
0.2%
· 5
 
0.1%
' 4
 
0.1%
& 2
 
< 0.1%
/ 1
 
< 0.1%
％ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 25
89.3%
] 2
 
7.1%
』 1
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 16
88.9%
[ 1
 
5.6%
『 1
 
5.6%
Math Symbol
ValueCountFrequency (%)
= 16
69.6%
~ 7
30.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 11101
100.0%
Space Separator
ValueCountFrequency (%)
1896
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92822
77.0%
Hangul 25328
 
21.0%
Latin 2455
 
2.0%
Han 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
ㅇ 1545
 
6.1%
김 1443
 
5.7%
ㅅ 1337
 
5.3%
이 1315
 
5.2%
ㄱ 1226
 
4.8%
ㅎ 1164
 
4.6%
ㅈ 1062
 
4.2%
ㄷ 591
 
2.3%
ㅂ 538
 
2.1%
박 525
 
2.1%
Other values (704) 14582
57.6%
Latin
ValueCountFrequency (%)
G 485
19.8%
R 415
16.9%
C 323
13.2%
E 201
 
8.2%
X 196
 
8.0%
U 111
 
4.5%
e 60
 
2.4%
o 59
 
2.4%
i 47
 
1.9%
a 47
 
1.9%
Other values (41) 511
20.8%
Common
ValueCountFrequency (%)
- 11101
12.0%
3 10126
10.9%
1 9923
10.7%
. 7644
8.2%
5 7549
8.1%
9 7403
8.0%
8 7230
7.8%
6 6735
7.3%
7 6681
7.2%
2 6161
6.6%
Other values (20) 12269
13.2%
Han
ValueCountFrequency (%)
計 2
 
11.8%
設 2
 
11.8%
世 1
 
5.9%
紀 1
 
5.9%
諺 1
 
5.9%
簡 1
 
5.9%
治 1
 
5.9%
相 1
 
5.9%
暴 1
 
5.9%
語 1
 
5.9%
Other values (5) 5
29.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95265
79.0%
Hangul 15759
 
13.1%
Compat Jamo 9569
 
7.9%
CJK 17
 
< 0.1%
None 8
 
< 0.1%
Number Forms 3
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 11101
11.7%
3 10126
10.6%
1 9923
10.4%
. 7644
8.0%
5 7549
7.9%
9 7403
7.8%
8 7230
7.6%
6 6735
7.1%
7 6681
7.0%
2 6161
6.5%
Other values (64) 14712
15.4%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1545
16.1%
ㅅ 1337
14.0%
ㄱ 1226
12.8%
ㅎ 1164
12.2%
ㅈ 1062
11.1%
ㄷ 591
 
6.2%
ㅂ 538
 
5.6%
ㅁ 478
 
5.0%
ㅊ 442
 
4.6%
ㄴ 340
 
3.6%
Other values (9) 846
8.8%
Hangul
ValueCountFrequency (%)
김 1443
 
9.2%
이 1315
 
8.3%
박 525
 
3.3%
한 465
 
3.0%
정 407
 
2.6%
최 292
 
1.9%
조 245
 
1.6%
충 242
 
1.5%
오 224
 
1.4%
신 205
 
1.3%
Other values (685) 10396
66.0%
None
ValueCountFrequency (%)
· 5
62.5%
％ 1
 
12.5%
』 1
 
12.5%
『 1
 
12.5%
CJK
ValueCountFrequency (%)
計 2
 
11.8%
設 2
 
11.8%
世 1
 
5.9%
紀 1
 
5.9%
諺 1
 
5.9%
簡 1
 
5.9%
治 1
 
5.9%
相 1
 
5.9%
暴 1
 
5.9%
語 1
 
5.9%
Other values (5) 5
29.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Unnamed: 3
Text

MISSING 

Distinct558
Distinct (%)93.3%
Missing9402
Missing (%)94.0%
Memory size156.2 KiB
2024-01-10T08:17:31.058603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length51
Mean length11.944816
Min length1

Characters and Unicode

Total characters7143
Distinct characters433
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique524 ?
Unique (%)87.6%

Sample

1st row813.6-김911ㅂㄱ
2nd row510.4-이172ㄱ
3rd row189-양856ㅎ
4th row325.5-후839ㄷ윤
5th row530.8-브888ㄷ조
ValueCountFrequency (%)
25
 
2.8%
그리고 9
 
1.0%
중심으로 6
 
0.7%
813.6-김911ㅂ 5
 
0.6%
및 4
 
0.5%
대한 4
 
0.5%
813.6-조852ㅇ 4
 
0.5%
and 4
 
0.5%
문화 3
 
0.3%
813.6-최693ㅎ 3
 
0.3%
Other values (764) 818
92.4%
2024-01-10T08:17:31.374004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 522
 
7.3%
- 504
 
7.1%
3 437
 
6.1%
428
 
6.0%
. 370
 
5.2%
9 367
 
5.1%
8 344
 
4.8%
2 325
 
4.5%
5 320
 
4.5%
6 319
 
4.5%
Other values (423) 3207
44.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3430
48.0%
Other Letter 2023
28.3%
Dash Punctuation 504
 
7.1%
Space Separator 428
 
6.0%
Other Punctuation 395
 
5.5%
Lowercase Letter 275
 
3.8%
Uppercase Letter 76
 
1.1%
Close Punctuation 7
 
0.1%
Math Symbol 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ㅇ 99
 
4.9%
이 86
 
4.3%
김 79
 
3.9%
ㅅ 57
 
2.8%
ㅈ 55
 
2.7%
ㄱ 52
 
2.6%
의 42
 
2.1%
박 29
 
1.4%
ㅂ 29
 
1.4%
ㅎ 29
 
1.4%
Other values (362) 1466
72.5%
Lowercase Letter
ValueCountFrequency (%)
e 29
 
10.5%
o 27
 
9.8%
t 26
 
9.5%
a 24
 
8.7%
r 23
 
8.4%
n 20
 
7.3%
i 16
 
5.8%
l 13
 
4.7%
u 12
 
4.4%
c 12
 
4.4%
Other values (13) 73
26.5%
Uppercase Letter
ValueCountFrequency (%)
G 34
44.7%
R 11
 
14.5%
C 5
 
6.6%
J 4
 
5.3%
A 3
 
3.9%
K 3
 
3.9%
T 2
 
2.6%
E 2
 
2.6%
P 2
 
2.6%
B 2
 
2.6%
Other values (8) 8
 
10.5%
Decimal Number
ValueCountFrequency (%)
1 522
15.2%
3 437
12.7%
9 367
10.7%
8 344
10.0%
2 325
9.5%
5 320
9.3%
6 319
9.3%
4 303
8.8%
7 268
7.8%
0 225
6.6%
Other Punctuation
ValueCountFrequency (%)
. 370
93.7%
: 21
 
5.3%
? 2
 
0.5%
· 1
 
0.3%
' 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 504
100.0%
Space Separator
ValueCountFrequency (%)
428
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4769
66.8%
Hangul 2017
28.2%
Latin 351
 
4.9%
Han 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
ㅇ 99
 
4.9%
이 86
 
4.3%
김 79
 
3.9%
ㅅ 57
 
2.8%
ㅈ 55
 
2.7%
ㄱ 52
 
2.6%
의 42
 
2.1%
박 29
 
1.4%
ㅂ 29
 
1.4%
ㅎ 29
 
1.4%
Other values (356) 1460
72.4%
Latin
ValueCountFrequency (%)
G 34
 
9.7%
e 29
 
8.3%
o 27
 
7.7%
t 26
 
7.4%
a 24
 
6.8%
r 23
 
6.6%
n 20
 
5.7%
i 16
 
4.6%
l 13
 
3.7%
u 12
 
3.4%
Other values (31) 127
36.2%
Common
ValueCountFrequency (%)
1 522
10.9%
- 504
10.6%
3 437
9.2%
428
9.0%
. 370
7.8%
9 367
7.7%
8 344
7.2%
2 325
 
6.8%
5 320
 
6.7%
6 319
 
6.7%
Other values (10) 833
17.5%
Han
ValueCountFrequency (%)
施 1
16.7%
工 1
16.7%
交 1
16.7%
通 1
16.7%
運 1
16.7%
營 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5119
71.7%
Hangul 1572
 
22.0%
Compat Jamo 445
 
6.2%
CJK 6
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 522
10.2%
- 504
9.8%
3 437
 
8.5%
428
 
8.4%
. 370
 
7.2%
9 367
 
7.2%
8 344
 
6.7%
2 325
 
6.3%
5 320
 
6.3%
6 319
 
6.2%
Other values (50) 1183
23.1%
Compat Jamo
ValueCountFrequency (%)
ㅇ 99
22.2%
ㅅ 57
12.8%
ㅈ 55
12.4%
ㄱ 52
11.7%
ㅂ 29
 
6.5%
ㅎ 29
 
6.5%
ㄷ 27
 
6.1%
ㅊ 23
 
5.2%
ㄴ 21
 
4.7%
ㅁ 20
 
4.5%
Other values (6) 33
 
7.4%
Hangul
ValueCountFrequency (%)
이 86
 
5.5%
김 79
 
5.0%
의 42
 
2.7%
박 29
 
1.8%
리 25
 
1.6%
한 24
 
1.5%
인 23
 
1.5%
정 23
 
1.5%
대 23
 
1.5%
국 21
 
1.3%
Other values (340) 1197
76.1%
CJK
ValueCountFrequency (%)
施 1
16.7%
工 1
16.7%
交 1
16.7%
通 1
16.7%
運 1
16.7%
營 1
16.7%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 4
Text

MISSING 

Distinct146
Distinct (%)96.7%
Missing9849
Missing (%)98.5%
Memory size156.2 KiB
2024-01-10T08:17:31.586042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length28
Mean length12.046358
Min length2

Characters and Unicode

Total characters1819
Distinct characters224
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

Unique141 ?
Unique (%)93.4%

Sample

1st row 6調 紀行時 4集 : 김운중 시집
2nd row005.7-오728ㄷ유
3rd row365.5-양987ㅎ
4th row 그밖의 중세 발명품들
5th row679.222-이436ㅅ
ValueCountFrequency (%)
and 3
 
1.4%
3
 
1.4%
325.2-블914ㄱ조 2
 
0.9%
위한 2
 
0.9%
state 2
 
0.9%
909-이835ㅇ 2
 
0.9%
무엇인가 2
 
0.9%
정의란 2
 
0.9%
453.9-램316ㄱ김 2
 
0.9%
부동산권리분석사 2
 
0.9%
Other values (189) 189
89.6%
2024-01-10T08:17:31.922234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 131
 
7.2%
3 131
 
7.2%
- 121
 
6.7%
5 100
 
5.5%
97
 
5.3%
. 97
 
5.3%
2 83
 
4.6%
4 83
 
4.6%
8 80
 
4.4%
9 79
 
4.3%
Other values (214) 817
44.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 881
48.4%
Other Letter 472
25.9%
Lowercase Letter 130
 
7.1%
Dash Punctuation 121
 
6.7%
Other Punctuation 102
 
5.6%
Space Separator 97
 
5.3%
Uppercase Letter 11
 
0.6%
Close Punctuation 4
 
0.2%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 26
 
5.5%
이 20
 
4.2%
ㅇ 18
 
3.8%
ㄱ 16
 
3.4%
ㅅ 15
 
3.2%
ㅁ 14
 
3.0%
ㅈ 11
 
2.3%
조 10
 
2.1%
의 9
 
1.9%
박 8
 
1.7%
Other values (169) 325
68.9%
Lowercase Letter
ValueCountFrequency (%)
e 17
13.1%
n 14
10.8%
t 14
10.8%
a 13
10.0%
i 12
9.2%
r 9
 
6.9%
c 7
 
5.4%
o 7
 
5.4%
l 6
 
4.6%
s 5
 
3.8%
Other values (9) 26
20.0%
Decimal Number
ValueCountFrequency (%)
1 131
14.9%
3 131
14.9%
5 100
11.4%
2 83
9.4%
4 83
9.4%
8 80
9.1%
9 79
9.0%
7 67
7.6%
6 67
7.6%
0 60
6.8%
Uppercase Letter
ValueCountFrequency (%)
G 4
36.4%
T 1
 
9.1%
I 1
 
9.1%
C 1
 
9.1%
H 1
 
9.1%
P 1
 
9.1%
R 1
 
9.1%
K 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 97
95.1%
: 2
 
2.0%
! 2
 
2.0%
& 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1206
66.3%
Hangul 467
 
25.7%
Latin 141
 
7.8%
Han 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 26
 
5.6%
이 20
 
4.3%
ㅇ 18
 
3.9%
ㄱ 16
 
3.4%
ㅅ 15
 
3.2%
ㅁ 14
 
3.0%
ㅈ 11
 
2.4%
조 10
 
2.1%
의 9
 
1.9%
박 8
 
1.7%
Other values (164) 320
68.5%
Latin
ValueCountFrequency (%)
e 17
12.1%
n 14
 
9.9%
t 14
 
9.9%
a 13
 
9.2%
i 12
 
8.5%
r 9
 
6.4%
c 7
 
5.0%
o 7
 
5.0%
l 6
 
4.3%
s 5
 
3.5%
Other values (17) 37
26.2%
Common
ValueCountFrequency (%)
1 131
10.9%
3 131
10.9%
- 121
10.0%
5 100
8.3%
97
8.0%
. 97
8.0%
2 83
6.9%
4 83
6.9%
8 80
 
6.6%
9 79
 
6.6%
Other values (8) 204
16.9%
Han
ValueCountFrequency (%)
集 1
20.0%
時 1
20.0%
行 1
20.0%
紀 1
20.0%
調 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1347
74.1%
Hangul 356
 
19.6%
Compat Jamo 111
 
6.1%
CJK 5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 131
 
9.7%
3 131
 
9.7%
- 121
 
9.0%
5 100
 
7.4%
97
 
7.2%
. 97
 
7.2%
2 83
 
6.2%
4 83
 
6.2%
8 80
 
5.9%
9 79
 
5.9%
Other values (35) 345
25.6%
Hangul
ValueCountFrequency (%)
김 26
 
7.3%
이 20
 
5.6%
조 10
 
2.8%
의 9
 
2.5%
박 8
 
2.2%
오 7
 
2.0%
장 7
 
2.0%
가 7
 
2.0%
동 6
 
1.7%
한 6
 
1.7%
Other values (149) 250
70.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 18
16.2%
ㄱ 16
14.4%
ㅅ 15
13.5%
ㅁ 14
12.6%
ㅈ 11
9.9%
ㅎ 8
7.2%
ㅂ 7
 
6.3%
ㄷ 5
 
4.5%
ㄴ 4
 
3.6%
ㅌ 3
 
2.7%
Other values (5) 10
9.0%
CJK
ValueCountFrequency (%)
集 1
20.0%
時 1
20.0%
行 1
20.0%
紀 1
20.0%
調 1
20.0%

Unnamed: 5
Text

MISSING 

Distinct38
Distinct (%)95.0%
Missing9960
Missing (%)99.6%
Memory size156.2 KiB
2024-01-10T08:17:32.131558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length15
Mean length11.175
Min length2

Characters and Unicode

Total characters447
Distinct characters122
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

Unique36 ?
Unique (%)90.0%

Sample

1st row811.7-김719ㅅ
2nd row920.3-프868ㅋ
3rd row340.1-이299ㅎ
4th row915.1-이482ㅇ
5th row Pollution
ValueCountFrequency (%)
522.2-이496ㅈ 2
 
3.4%
165.77-백973ㄴ 2
 
3.4%
the 2
 
3.4%
911.05-임975ㅇ 1
 
1.7%
and 1
 
1.7%
lives 1
 
1.7%
of 1
 
1.7%
people 1
 
1.7%
710.77-케324ㅋ-12 1
 
1.7%
임철우(사평역 1
 
1.7%
Other values (46) 46
78.0%
2024-01-10T08:17:32.483412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
7.4%
1 27
 
6.0%
- 27
 
6.0%
2 24
 
5.4%
3 23
 
5.1%
7 23
 
5.1%
. 20
 
4.5%
9 20
 
4.5%
0 16
 
3.6%
5 15
 
3.4%
Other values (112) 219
49.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
42.3%
Other Letter 124
27.7%
Lowercase Letter 46
 
10.3%
Space Separator 33
 
7.4%
Dash Punctuation 27
 
6.0%
Other Punctuation 21
 
4.7%
Open Punctuation 3
 
0.7%
Close Punctuation 2
 
0.4%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 8
 
6.5%
ㅇ 7
 
5.6%
김 3
 
2.4%
백 3
 
2.4%
ㅈ 3
 
2.4%
법 2
 
1.6%
준 2
 
1.6%
노 2
 
1.6%
화 2
 
1.6%
태 2
 
1.6%
Other values (77) 90
72.6%
Lowercase Letter
ValueCountFrequency (%)
e 9
19.6%
t 5
10.9%
l 4
8.7%
o 4
8.7%
h 3
 
6.5%
i 3
 
6.5%
n 3
 
6.5%
s 3
 
6.5%
p 2
 
4.3%
a 2
 
4.3%
Other values (7) 8
17.4%
Decimal Number
ValueCountFrequency (%)
1 27
14.3%
2 24
12.7%
3 23
12.2%
7 23
12.2%
9 20
10.6%
0 16
8.5%
5 15
7.9%
6 14
7.4%
4 14
7.4%
8 13
6.9%
Other Punctuation
ValueCountFrequency (%)
. 20
95.2%
& 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 275
61.5%
Hangul 124
27.7%
Latin 48
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 8
 
6.5%
ㅇ 7
 
5.6%
김 3
 
2.4%
백 3
 
2.4%
ㅈ 3
 
2.4%
법 2
 
1.6%
준 2
 
1.6%
노 2
 
1.6%
화 2
 
1.6%
태 2
 
1.6%
Other values (77) 90
72.6%
Latin
ValueCountFrequency (%)
e 9
18.8%
t 5
10.4%
l 4
 
8.3%
o 4
 
8.3%
h 3
 
6.2%
i 3
 
6.2%
n 3
 
6.2%
s 3
 
6.2%
p 2
 
4.2%
a 2
 
4.2%
Other values (9) 10
20.8%
Common
ValueCountFrequency (%)
33
12.0%
1 27
9.8%
- 27
9.8%
2 24
8.7%
3 23
8.4%
7 23
8.4%
. 20
7.3%
9 20
7.3%
0 16
 
5.8%
5 15
 
5.5%
Other values (6) 47
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
72.3%
Hangul 100
 
22.4%
Compat Jamo 24
 
5.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33
 
10.2%
1 27
 
8.4%
- 27
 
8.4%
2 24
 
7.4%
3 23
 
7.1%
7 23
 
7.1%
. 20
 
6.2%
9 20
 
6.2%
0 16
 
5.0%
5 15
 
4.6%
Other values (25) 95
29.4%
Hangul
ValueCountFrequency (%)
이 8
 
8.0%
김 3
 
3.0%
백 3
 
3.0%
법 2
 
2.0%
준 2
 
2.0%
노 2
 
2.0%
화 2
 
2.0%
태 2
 
2.0%
임 2
 
2.0%
시 2
 
2.0%
Other values (67) 72
72.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 7
29.2%
ㅈ 3
12.5%
ㅍ 2
 
8.3%
ㅁ 2
 
8.3%
ㅅ 2
 
8.3%
ㅎ 2
 
8.3%
ㅋ 2
 
8.3%
ㄴ 2
 
8.3%
ㄱ 1
 
4.2%
ㅊ 1
 
4.2%

Unnamed: 6
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing9985
Missing (%)99.9%
Memory size156.2 KiB
2024-01-10T08:17:32.675314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length9
Min length2

Characters and Unicode

Total characters135
Distinct characters53
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row517-권662ㅇ
2nd row 비츠
3rd row843.509-민971ㅈ
4th row219-김955ㅈ
5th row527.4786-김982ㅇ
ValueCountFrequency (%)
517-권662ㅇ 1
 
5.6%
비츠 1
 
5.6%
머저리 1
 
5.6%
병신과 1
 
5.6%
만화 1
 
5.6%
364.4-법146ㅇ-g 1
 
5.6%
329-김418ㅈㅇ 1
 
5.6%
붉은방 1
 
5.6%
서다 1
 
5.6%
비탈에 1
 
5.6%
Other values (8) 8
44.4%
2024-01-10T08:17:32.941799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
 
7.4%
- 9
 
6.7%
9
 
6.7%
9 9
 
6.7%
5 6
 
4.4%
7 6
 
4.4%
6 6
 
4.4%
2 6
 
4.4%
4 6
 
4.4%
. 5
 
3.7%
Other values (43) 63
46.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
45.2%
Other Letter 47
34.8%
Dash Punctuation 9
 
6.7%
Space Separator 9
 
6.7%
Other Punctuation 5
 
3.7%
Close Punctuation 2
 
1.5%
Uppercase Letter 1
 
0.7%
Open Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ㅇ 4
 
8.5%
김 3
 
6.4%
ㅈ 3
 
6.4%
비 2
 
4.3%
다 2
 
4.3%
리 2
 
4.3%
만 1
 
2.1%
서 1
 
2.1%
붉 1
 
2.1%
은 1
 
2.1%
Other values (27) 27
57.4%
Decimal Number
ValueCountFrequency (%)
1 10
16.4%
9 9
14.8%
5 6
9.8%
7 6
9.8%
6 6
9.8%
2 6
9.8%
4 6
9.8%
8 5
8.2%
3 5
8.2%
0 2
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 87
64.4%
Hangul 47
34.8%
Latin 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
ㅇ 4
 
8.5%
김 3
 
6.4%
ㅈ 3
 
6.4%
비 2
 
4.3%
다 2
 
4.3%
리 2
 
4.3%
만 1
 
2.1%
서 1
 
2.1%
붉 1
 
2.1%
은 1
 
2.1%
Other values (27) 27
57.4%
Common
ValueCountFrequency (%)
1 10
11.5%
- 9
10.3%
9
10.3%
9 9
10.3%
5 6
 
6.9%
7 6
 
6.9%
6 6
 
6.9%
2 6
 
6.9%
4 6
 
6.9%
. 5
 
5.7%
Other values (5) 15
17.2%
Latin
ValueCountFrequency (%)
G 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
65.2%
Hangul 38
28.1%
Compat Jamo 9
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
11.4%
- 9
10.2%
9
10.2%
9 9
10.2%
5 6
 
6.8%
7 6
 
6.8%
6 6
 
6.8%
2 6
 
6.8%
4 6
 
6.8%
. 5
 
5.7%
Other values (6) 16
18.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 4
44.4%
ㅈ 3
33.3%
ㅊ 1
 
11.1%
ㅂ 1
 
11.1%
Hangul
ValueCountFrequency (%)
김 3
 
7.9%
비 2
 
5.3%
다 2
 
5.3%
리 2
 
5.3%
만 1
 
2.6%
서 1
 
2.6%
붉 1
 
2.6%
은 1
 
2.6%
방 1
 
2.6%
법 1
 
2.6%
Other values (23) 23
60.5%

Unnamed: 7
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2024-01-10T08:17:33.322002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length10.5
Mean length9.875
Min length2

Characters and Unicode

Total characters79
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row326.4-한419ㅇ
2nd row 키바나의 모든 것
3rd row 해방 전후)
4th row 전광용(사수
5th row 너와 나만의 시간) 손창섭(비오는 날)
ValueCountFrequency (%)
326.4-한419ㅇ 1
 
5.9%
시간 1
 
5.9%
건방진 1
 
5.9%
영화 1
 
5.9%
방 1
 
5.9%
강석경(숲속의 1
 
5.9%
날 1
 
5.9%
손창섭(비오는 1
 
5.9%
나만의 1
 
5.9%
키바나의 1
 
5.9%
Other values (7) 7
41.2%
2024-01-10T08:17:33.591848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
19.0%
) 4
 
5.1%
방 3
 
3.8%
의 3
 
3.8%
( 3
 
3.8%
4 2
 
2.5%
나 2
 
2.5%
전 2
 
2.5%
3 1
 
1.3%
는 1
 
1.3%
Other values (43) 43
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48
60.8%
Space Separator 15
 
19.0%
Decimal Number 7
 
8.9%
Close Punctuation 4
 
5.1%
Open Punctuation 3
 
3.8%
Other Punctuation 1
 
1.3%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 3
 
6.2%
의 3
 
6.2%
나 2
 
4.2%
전 2
 
4.2%
는 1
 
2.1%
오 1
 
2.1%
강 1
 
2.1%
비 1
 
2.1%
섭 1
 
2.1%
창 1
 
2.1%
Other values (32) 32
66.7%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
3 1
14.3%
6 1
14.3%
1 1
14.3%
9 1
14.3%
2 1
14.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48
60.8%
Common 31
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 3
 
6.2%
의 3
 
6.2%
나 2
 
4.2%
전 2
 
4.2%
는 1
 
2.1%
오 1
 
2.1%
강 1
 
2.1%
비 1
 
2.1%
섭 1
 
2.1%
창 1
 
2.1%
Other values (32) 32
66.7%
Common
ValueCountFrequency (%)
15
48.4%
) 4
 
12.9%
( 3
 
9.7%
4 2
 
6.5%
3 1
 
3.2%
6 1
 
3.2%
. 1
 
3.2%
- 1
 
3.2%
1 1
 
3.2%
9 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47
59.5%
ASCII 31
39.2%
Compat Jamo 1
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
48.4%
) 4
 
12.9%
( 3
 
9.7%
4 2
 
6.5%
3 1
 
3.2%
6 1
 
3.2%
. 1
 
3.2%
- 1
 
3.2%
1 1
 
3.2%
9 1
 
3.2%
Hangul
ValueCountFrequency (%)
방 3
 
6.4%
의 3
 
6.4%
나 2
 
4.3%
전 2
 
4.3%
는 1
 
2.1%
오 1
 
2.1%
강 1
 
2.1%
비 1
 
2.1%
섭 1
 
2.1%
창 1
 
2.1%
Other values (31) 31
66.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

Unnamed: 8
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing9993
Missing (%)99.9%
Memory size156.2 KiB
2024-01-10T08:17:33.741935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.7142857
Min length4

Characters and Unicode

Total characters61
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row005.76-김836ㅇ
2nd row 정비석(성황당)
3rd row 끼삐딴 리)
4th row 오영수(갯마을)
5th row 최일남(흐르는 북)
ValueCountFrequency (%)
005.76-김836ㅇ 1
11.1%
정비석(성황당 1
11.1%
끼삐딴 1
11.1%
리 1
11.1%
오영수(갯마을 1
11.1%
최일남(흐르는 1
11.1%
북 1
11.1%
101-김696ㅅ 1
11.1%
서편제 1
11.1%
2024-01-10T08:17:34.017116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
11.5%
6 4
 
6.6%
) 4
 
6.6%
0 3
 
4.9%
( 3
 
4.9%
- 2
 
3.3%
김 2
 
3.3%
1 2
 
3.3%
흐 1
 
1.6%
갯 1
 
1.6%
Other values (32) 32
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30
49.2%
Decimal Number 14
23.0%
Space Separator 7
 
11.5%
Close Punctuation 4
 
6.6%
Open Punctuation 3
 
4.9%
Dash Punctuation 2
 
3.3%
Other Punctuation 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2
 
6.7%
흐 1
 
3.3%
갯 1
 
3.3%
마 1
 
3.3%
을 1
 
3.3%
최 1
 
3.3%
일 1
 
3.3%
남 1
 
3.3%
는 1
 
3.3%
르 1
 
3.3%
Other values (19) 19
63.3%
Decimal Number
ValueCountFrequency (%)
6 4
28.6%
0 3
21.4%
1 2
14.3%
9 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%
3 1
 
7.1%
5 1
 
7.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31
50.8%
Hangul 30
49.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2
 
6.7%
흐 1
 
3.3%
갯 1
 
3.3%
마 1
 
3.3%
을 1
 
3.3%
최 1
 
3.3%
일 1
 
3.3%
남 1
 
3.3%
는 1
 
3.3%
르 1
 
3.3%
Other values (19) 19
63.3%
Common
ValueCountFrequency (%)
7
22.6%
6 4
12.9%
) 4
12.9%
0 3
9.7%
( 3
9.7%
- 2
 
6.5%
1 2
 
6.5%
9 1
 
3.2%
. 1
 
3.2%
7 1
 
3.2%
Other values (3) 3
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
50.8%
Hangul 28
45.9%
Compat Jamo 2
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
22.6%
6 4
12.9%
) 4
12.9%
0 3
9.7%
( 3
9.7%
- 2
 
6.5%
1 2
 
6.5%
9 1
 
3.2%
. 1
 
3.2%
7 1
 
3.2%
Other values (3) 3
9.7%
Hangul
ValueCountFrequency (%)
김 2
 
7.1%
흐 1
 
3.6%
갯 1
 
3.6%
마 1
 
3.6%
을 1
 
3.6%
최 1
 
3.6%
일 1
 
3.6%
남 1
 
3.6%
는 1
 
3.6%
르 1
 
3.6%
Other values (17) 17
60.7%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
50.0%
ㅇ 1
50.0%

Unnamed: 9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:34.158876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length8.8
Min length4

Characters and Unicode

Total characters44
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row 채만식(치숙
2nd row 강신재(젊은 느티나무)
3rd row 이호철(탈향
4th row 이인성(당신에 대해서)
5th row 눈길)
ValueCountFrequency (%)
채만식(치숙 1
14.3%
강신재(젊은 1
14.3%
느티나무 1
14.3%
이호철(탈향 1
14.3%
이인성(당신에 1
14.3%
대해서 1
14.3%
눈길 1
14.3%
2024-01-10T08:17:34.398647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
15.9%
( 4
 
9.1%
) 3
 
6.8%
이 2
 
4.5%
신 2
 
4.5%
서 1
 
2.3%
눈 1
 
2.3%
해 1
 
2.3%
대 1
 
2.3%
에 1
 
2.3%
Other values (21) 21
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30
68.2%
Space Separator 7
 
15.9%
Open Punctuation 4
 
9.1%
Close Punctuation 3
 
6.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2
 
6.7%
신 2
 
6.7%
서 1
 
3.3%
눈 1
 
3.3%
해 1
 
3.3%
대 1
 
3.3%
에 1
 
3.3%
당 1
 
3.3%
성 1
 
3.3%
인 1
 
3.3%
Other values (18) 18
60.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30
68.2%
Common 14
31.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2
 
6.7%
신 2
 
6.7%
서 1
 
3.3%
눈 1
 
3.3%
해 1
 
3.3%
대 1
 
3.3%
에 1
 
3.3%
당 1
 
3.3%
성 1
 
3.3%
인 1
 
3.3%
Other values (18) 18
60.0%
Common
ValueCountFrequency (%)
7
50.0%
( 4
28.6%
) 3
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30
68.2%
ASCII 14
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
50.0%
( 4
28.6%
) 3
21.4%
Hangul
ValueCountFrequency (%)
이 2
 
6.7%
신 2
 
6.7%
서 1
 
3.3%
눈 1
 
3.3%
해 1
 
3.3%
대 1
 
3.3%
에 1
 
3.3%
당 1
 
3.3%
성 1
 
3.3%
인 1
 
3.3%
Other values (18) 18
60.0%

Unnamed: 10
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:34.549841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.8
Min length5

Characters and Unicode

Total characters39
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row 태평천하
2nd row 최인훈(광장)
3rd row 닳아지는 살들)
4th row 김학철(종횡만리)
5th row 서정인(강)
ValueCountFrequency (%)
태평천하 1
16.7%
최인훈(광장 1
16.7%
닳아지는 1
16.7%
살들 1
16.7%
김학철(종횡만리 1
16.7%
서정인(강 1
16.7%
2024-01-10T08:17:34.799173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
15.4%
) 4
 
10.3%
( 3
 
7.7%
인 2
 
5.1%
살 1
 
2.6%
정 1
 
2.6%
서 1
 
2.6%
리 1
 
2.6%
만 1
 
2.6%
횡 1
 
2.6%
Other values (18) 18
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
66.7%
Space Separator 6
 
15.4%
Close Punctuation 4
 
10.3%
Open Punctuation 3
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 2
 
7.7%
살 1
 
3.8%
정 1
 
3.8%
서 1
 
3.8%
리 1
 
3.8%
만 1
 
3.8%
횡 1
 
3.8%
종 1
 
3.8%
철 1
 
3.8%
학 1
 
3.8%
Other values (15) 15
57.7%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
66.7%
Common 13
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 2
 
7.7%
살 1
 
3.8%
정 1
 
3.8%
서 1
 
3.8%
리 1
 
3.8%
만 1
 
3.8%
횡 1
 
3.8%
종 1
 
3.8%
철 1
 
3.8%
학 1
 
3.8%
Other values (15) 15
57.7%
Common
ValueCountFrequency (%)
6
46.2%
) 4
30.8%
( 3
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
66.7%
ASCII 13
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
46.2%
) 4
30.8%
( 3
23.1%
Hangul
ValueCountFrequency (%)
인 2
 
7.7%
살 1
 
3.8%
정 1
 
3.8%
서 1
 
3.8%
리 1
 
3.8%
만 1
 
3.8%
횡 1
 
3.8%
종 1
 
3.8%
철 1
 
3.8%
학 1
 
3.8%
Other values (15) 15
57.7%

Unnamed: 11
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:34.944385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10
Min length4

Characters and Unicode

Total characters50
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row 허생전
2nd row 김정한(모래톱 이야기
3rd row 오상원(유예)
4th row813.6082-김964ㄲ
5th row 황석영(아우를 위하여
ValueCountFrequency (%)
허생전 1
14.3%
김정한(모래톱 1
14.3%
이야기 1
14.3%
오상원(유예 1
14.3%
813.6082-김964ㄲ 1
14.3%
황석영(아우를 1
14.3%
위하여 1
14.3%
2024-01-10T08:17:35.213479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
12.0%
( 3
 
6.0%
김 2
 
4.0%
6 2
 
4.0%
8 2
 
4.0%
정 1
 
2.0%
황 1
 
2.0%
0 1
 
2.0%
2 1
 
2.0%
- 1
 
2.0%
Other values (30) 30
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
56.0%
Decimal Number 10
 
20.0%
Space Separator 6
 
12.0%
Open Punctuation 3
 
6.0%
Dash Punctuation 1
 
2.0%
Other Punctuation 1
 
2.0%
Close Punctuation 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2
 
7.1%
정 1
 
3.6%
황 1
 
3.6%
ㄲ 1
 
3.6%
석 1
 
3.6%
영 1
 
3.6%
아 1
 
3.6%
우 1
 
3.6%
를 1
 
3.6%
위 1
 
3.6%
Other values (17) 17
60.7%
Decimal Number
ValueCountFrequency (%)
6 2
20.0%
8 2
20.0%
0 1
10.0%
2 1
10.0%
9 1
10.0%
4 1
10.0%
3 1
10.0%
1 1
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
56.0%
Common 22
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2
 
7.1%
정 1
 
3.6%
황 1
 
3.6%
ㄲ 1
 
3.6%
석 1
 
3.6%
영 1
 
3.6%
아 1
 
3.6%
우 1
 
3.6%
를 1
 
3.6%
위 1
 
3.6%
Other values (17) 17
60.7%
Common
ValueCountFrequency (%)
6
27.3%
( 3
13.6%
6 2
 
9.1%
8 2
 
9.1%
0 1
 
4.5%
2 1
 
4.5%
- 1
 
4.5%
9 1
 
4.5%
4 1
 
4.5%
. 1
 
4.5%
Other values (3) 3
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
54.0%
ASCII 22
44.0%
Compat Jamo 1
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
27.3%
( 3
13.6%
6 2
 
9.1%
8 2
 
9.1%
0 1
 
4.5%
2 1
 
4.5%
- 1
 
4.5%
9 1
 
4.5%
4 1
 
4.5%
. 1
 
4.5%
Other values (3) 3
13.6%
Hangul
ValueCountFrequency (%)
김 2
 
7.4%
정 1
 
3.7%
황 1
 
3.7%
석 1
 
3.7%
영 1
 
3.7%
아 1
 
3.7%
우 1
 
3.7%
를 1
 
3.7%
위 1
 
3.7%
하 1
 
3.7%
Other values (16) 16
59.3%
Compat Jamo
ValueCountFrequency (%)
ㄲ 1
100.0%

Unnamed: 12
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:35.354432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.25
Min length5

Characters and Unicode

Total characters29
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row 논 이야기
2nd row 수라도)
3rd row 장용학(요한시집)
4th row 삼포가는 길)
ValueCountFrequency (%)
논 1
16.7%
이야기 1
16.7%
수라도 1
16.7%
장용학(요한시집 1
16.7%
삼포가는 1
16.7%
길 1
16.7%
2024-01-10T08:17:35.608937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
20.7%
) 3
 
10.3%
( 1
 
3.4%
는 1
 
3.4%
가 1
 
3.4%
포 1
 
3.4%
삼 1
 
3.4%
집 1
 
3.4%
시 1
 
3.4%
한 1
 
3.4%
Other values (12) 12
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19
65.5%
Space Separator 6
 
20.7%
Close Punctuation 3
 
10.3%
Open Punctuation 1
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
는 1
 
5.3%
가 1
 
5.3%
포 1
 
5.3%
삼 1
 
5.3%
집 1
 
5.3%
시 1
 
5.3%
한 1
 
5.3%
요 1
 
5.3%
학 1
 
5.3%
논 1
 
5.3%
Other values (9) 9
47.4%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19
65.5%
Common 10
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
는 1
 
5.3%
가 1
 
5.3%
포 1
 
5.3%
삼 1
 
5.3%
집 1
 
5.3%
시 1
 
5.3%
한 1
 
5.3%
요 1
 
5.3%
학 1
 
5.3%
논 1
 
5.3%
Other values (9) 9
47.4%
Common
ValueCountFrequency (%)
6
60.0%
) 3
30.0%
( 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19
65.5%
ASCII 10
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
60.0%
) 3
30.0%
( 1
 
10.0%
Hangul
ValueCountFrequency (%)
는 1
 
5.3%
가 1
 
5.3%
포 1
 
5.3%
삼 1
 
5.3%
집 1
 
5.3%
시 1
 
5.3%
한 1
 
5.3%
요 1
 
5.3%
학 1
 
5.3%
논 1
 
5.3%
Other values (9) 9
47.4%

Unnamed: 13
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:35.753040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11.5
Mean length11
Min length7

Characters and Unicode

Total characters44
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row 미스터 방)
2nd row813.6082-김964ㄲ
3rd row 이범선(오발탄)
4th row813.6082-김964ㄲ
ValueCountFrequency (%)
813.6082-김964ㄲ 2
40.0%
미스터 1
20.0%
방 1
20.0%
이범선(오발탄 1
20.0%
2024-01-10T08:17:35.992393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 4
 
9.1%
6 4
 
9.1%
3
 
6.8%
. 2
 
4.5%
0 2
 
4.5%
2 2
 
4.5%
- 2
 
4.5%
김 2
 
4.5%
9 2
 
4.5%
4 2
 
4.5%
Other values (15) 19
43.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
45.5%
Other Letter 14
31.8%
Space Separator 3
 
6.8%
Other Punctuation 2
 
4.5%
Dash Punctuation 2
 
4.5%
Close Punctuation 2
 
4.5%
Open Punctuation 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2
14.3%
ㄲ 2
14.3%
범 1
7.1%
발 1
7.1%
오 1
7.1%
선 1
7.1%
스 1
7.1%
이 1
7.1%
방 1
7.1%
터 1
7.1%
Other values (2) 2
14.3%
Decimal Number
ValueCountFrequency (%)
8 4
20.0%
6 4
20.0%
0 2
10.0%
2 2
10.0%
9 2
10.0%
4 2
10.0%
1 2
10.0%
3 2
10.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30
68.2%
Hangul 14
31.8%

Most frequent character per script

Common
ValueCountFrequency (%)
8 4
13.3%
6 4
13.3%
3
10.0%
. 2
 
6.7%
0 2
 
6.7%
2 2
 
6.7%
- 2
 
6.7%
9 2
 
6.7%
4 2
 
6.7%
1 2
 
6.7%
Other values (3) 5
16.7%
Hangul
ValueCountFrequency (%)
김 2
14.3%
ㄲ 2
14.3%
범 1
7.1%
발 1
7.1%
오 1
7.1%
선 1
7.1%
스 1
7.1%
이 1
7.1%
방 1
7.1%
터 1
7.1%
Other values (2) 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
68.2%
Hangul 12
 
27.3%
Compat Jamo 2
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 4
13.3%
6 4
13.3%
3
10.0%
. 2
 
6.7%
0 2
 
6.7%
2 2
 
6.7%
- 2
 
6.7%
9 2
 
6.7%
4 2
 
6.7%
1 2
 
6.7%
Other values (3) 5
16.7%
Hangul
ValueCountFrequency (%)
김 2
16.7%
범 1
8.3%
발 1
8.3%
오 1
8.3%
선 1
8.3%
스 1
8.3%
이 1
8.3%
방 1
8.3%
터 1
8.3%
미 1
8.3%
Compat Jamo
ValueCountFrequency (%)
ㄲ 2
100.0%

Unnamed: 14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-01-10T08:17:36.114937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters28
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row813.6082-김964ㄲ
2nd row813.6082-김964ㄲ
ValueCountFrequency (%)
813.6082-김964ㄲ 2
100.0%
2024-01-10T08:17:36.333052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 4
14.3%
6 4
14.3%
1 2
7.1%
3 2
7.1%
. 2
7.1%
0 2
7.1%
2 2
7.1%
- 2
7.1%
김 2
7.1%
9 2
7.1%
Other values (2) 4
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
71.4%
Other Letter 4
 
14.3%
Other Punctuation 2
 
7.1%
Dash Punctuation 2
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 4
20.0%
6 4
20.0%
1 2
10.0%
3 2
10.0%
0 2
10.0%
2 2
10.0%
9 2
10.0%
4 2
10.0%
Other Letter
ValueCountFrequency (%)
김 2
50.0%
ㄲ 2
50.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
85.7%
Hangul 4
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
8 4
16.7%
6 4
16.7%
1 2
8.3%
3 2
8.3%
. 2
8.3%
0 2
8.3%
2 2
8.3%
- 2
8.3%
9 2
8.3%
4 2
8.3%
Hangul
ValueCountFrequency (%)
김 2
50.0%
ㄲ 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
85.7%
Hangul 2
 
7.1%
Compat Jamo 2
 
7.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 4
16.7%
6 4
16.7%
1 2
8.3%
3 2
8.3%
. 2
8.3%
0 2
8.3%
2 2
8.3%
- 2
8.3%
9 2
8.3%
4 2
8.3%
Hangul
ValueCountFrequency (%)
김 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄲ 2
100.0%

Unnamed: 15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 16
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Unnamed: 17
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Correlations

2024-01-10T08:17:36.410636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
Unnamed: 51.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 61.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 81.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 91.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 101.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 111.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 121.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 131.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-01-10T08:17:28.573966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T08:17:28.765994image/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.
2024-01-10T08:17:28.942159image/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

등록번호서명청구기호Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
20144KM0025061지식논쟁 : 포스트모던 시대의 사회이론300.1-사287ㅈ박<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3860KM0004967법화행자의 초상223.54-곽852ㅂ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4053KM0005259한국문화와 한국인331.50911-국462ㅎ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45719KM0055067바리스타 = Barista. 1833.6-하127ㅂ-1-C<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51103KM0060951(2014) 상수도 통계 = STATISTICS OF WATERWORKS539.1025-환619ㅅ-G<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15574KM0019431팬시화 : 인물편. 1658-이632ㄷ-R<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
49627KM0059404생쥐가 궁금해863-피956ㅅ홍-아<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66967KM0077103(2022 에듀윌) 소방공무원 실전동형 모의고사 한국사 : 10회911.0077-임979ㅅ-EX<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
226KM0000347北韓戰略思想新論392.3-서826ㅂ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1324KM0001720民法總則. 1997365-김829ㅁ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
등록번호서명청구기호Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
42174KM0050915고려의 후삼국 통일과 후백제911.04-김111ㄱ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48654KM0058215선박해양 유체역학 = Introduction to marine hydrodynamics559.41-이436ㅅ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61657KM0071774노년철학 : 학술회의 보고서. 권1-권3199.7-보458ㄴ-G<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
57764KM0067848활기찬 도심 만들기 : 도시설계와 재생의 원칙539.7-포584ㅎ장<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26358KM0032327사망원인통계연보 : 인구동태신고에 의한 집계. 1998년319.5059-통772ㅅ-G<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21898KM0027226위진 현학152.33-정314ㅇ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58968KM0069057충남도립대학교 2017년 졸업생 취업실태 조사377.25-충69ㅊ-CU<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4669KM0006023부초813.6-한725ㅂㄱ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66205KM0076341신은 지금 어디에 있는가 : 이철호 장편소설813.62-이713ㅅ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10242KM0013014동양철학의 이해150-최789ㄷ<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>