Overview

Dataset statistics

Number of variables30
Number of observations2054
Missing cells10302
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory501.6 KiB
Average record size in memory250.1 B

Variable types

Text11
Boolean1
Categorical10
Numeric5
DateTime3

Dataset

Description한국개발연구원(KDI) 발간물 목록입니다. KDI가 발간하는 연구보고정, 정책연구시리즈 등 인쇄하여 배포하는 발간물의 전체 목록을 제공합니다.
Author한국개발연구원
URLhttps://www.data.go.kr/data/15091316/fileData.do

Alerts

서비스코드 has constant value ""Constant
캘린더 is highly imbalanced (59.1%)Imbalance
언어 is highly imbalanced (56.6%)Imbalance
입고 is highly imbalanced (92.4%)Imbalance
발행처 is highly imbalanced (59.5%)Imbalance
발행처영문 is highly imbalanced (95.3%)Imbalance
보기 is highly imbalanced (95.3%)Imbalance
영문서명 has 912 (44.4%) missing valuesMissing
한글서명 has 1172 (57.1%) missing valuesMissing
캘린더 has 1504 (73.2%) missing valuesMissing
제이엘코드 has 892 (43.4%) missing valuesMissing
주제코드2 has 151 (7.4%) missing valuesMissing
주제코드3 has 121 (5.9%) missing valuesMissing
가격 has 164 (8.0%) missing valuesMissing
시리즈번호 has 313 (15.2%) missing valuesMissing
시리즈번호영문 has 1053 (51.3%) missing valuesMissing
제출일 has 1961 (95.5%) missing valuesMissing
제출처 has 2050 (99.8%) missing valuesMissing
발간번호 has unique valuesUnique
카운트 has 1159 (56.4%) zerosZeros
다운로드 has 658 (32.0%) zerosZeros
입고수량 has 506 (24.6%) zerosZeros

Reproduction

Analysis started2023-12-12 20:31:41.338598
Analysis finished2023-12-12 20:31:42.898691
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서명
Text

Distinct2045
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2023-12-13T05:31:43.111794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length181
Median length122
Mean length36.468354
Min length4

Characters and Unicode

Total characters74906
Distinct characters540
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2036 ?
Unique (%)99.1%

Sample

1st row한국 가계금융자산 구성의 결정요인 분석 : 주식보유를 중심으로
2nd rowKDI Annual Report 2002
3rd rowAn Analysis of Systemic Factors of the Asian Financial Crisis : The Cases of Korea and Japan
4th rowAn Agenda for Economic Reform in Korea
5th row일본경제의 10년 불황에서 배워야 할 교훈
ValueCountFrequency (%)
468
 
3.5%
the 370
 
2.8%
and 359
 
2.7%
of 348
 
2.6%
in 285
 
2.1%
korea 278
 
2.1%
연구 194
 
1.4%
및 156
 
1.2%
중심으로 154
 
1.2%
관한 145
 
1.1%
Other values (4786) 10627
79.4%
2023-12-13T05:31:43.566331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11337
 
15.1%
e 3478
 
4.6%
o 3043
 
4.1%
n 2956
 
3.9%
a 2633
 
3.5%
i 2503
 
3.3%
t 2324
 
3.1%
r 2301
 
3.1%
s 1571
 
2.1%
의 1291
 
1.7%
Other values (530) 41469
55.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29367
39.2%
Other Letter 26888
35.9%
Space Separator 11337
 
15.1%
Uppercase Letter 4569
 
6.1%
Decimal Number 1217
 
1.6%
Other Punctuation 1042
 
1.4%
Dash Punctuation 151
 
0.2%
Close Punctuation 140
 
0.2%
Open Punctuation 140
 
0.2%
Math Symbol 29
 
< 0.1%
Other values (4) 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1291
 
4.8%
제 932
 
3.5%
과 750
 
2.8%
한 733
 
2.7%
정 716
 
2.7%
구 551
 
2.0%
경 505
 
1.9%
업 487
 
1.8%
국 444
 
1.7%
방 432
 
1.6%
Other values (445) 20047
74.6%
Lowercase Letter
ValueCountFrequency (%)
e 3478
11.8%
o 3043
10.4%
n 2956
10.1%
a 2633
9.0%
i 2503
8.5%
t 2324
 
7.9%
r 2301
 
7.8%
s 1571
 
5.3%
c 1229
 
4.2%
l 1093
 
3.7%
Other values (16) 6236
21.2%
Uppercase Letter
ValueCountFrequency (%)
K 488
10.7%
E 433
9.5%
P 429
9.4%
I 394
 
8.6%
S 370
 
8.1%
C 329
 
7.2%
T 294
 
6.4%
A 275
 
6.0%
R 262
 
5.7%
D 258
 
5.6%
Other values (15) 1037
22.7%
Decimal Number
ValueCountFrequency (%)
9 272
22.4%
1 258
21.2%
0 204
16.8%
2 110
9.0%
7 83
 
6.8%
8 82
 
6.7%
5 82
 
6.7%
4 45
 
3.7%
6 42
 
3.5%
3 39
 
3.2%
Other Punctuation
ValueCountFrequency (%)
: 676
64.9%
, 159
 
15.3%
· 76
 
7.3%
' 67
 
6.4%
. 29
 
2.8%
? 16
 
1.5%
/ 12
 
1.2%
& 4
 
0.4%
; 3
 
0.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
40.0%
Ⅰ 5
33.3%
Ⅲ 3
20.0%
Ⅳ 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 138
98.6%
] 2
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 138
98.6%
[ 2
 
1.4%
Final Punctuation
ValueCountFrequency (%)
’ 4
57.1%
” 3
42.9%
Space Separator
ValueCountFrequency (%)
11337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%
Math Symbol
ValueCountFrequency (%)
~ 29
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33951
45.3%
Hangul 26874
35.9%
Common 14067
18.8%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1291
 
4.8%
제 932
 
3.5%
과 750
 
2.8%
한 733
 
2.7%
정 716
 
2.7%
구 551
 
2.1%
경 505
 
1.9%
업 487
 
1.8%
국 444
 
1.7%
방 432
 
1.6%
Other values (436) 20033
74.5%
Latin
ValueCountFrequency (%)
e 3478
 
10.2%
o 3043
 
9.0%
n 2956
 
8.7%
a 2633
 
7.8%
i 2503
 
7.4%
t 2324
 
6.8%
r 2301
 
6.8%
s 1571
 
4.6%
c 1229
 
3.6%
l 1093
 
3.2%
Other values (45) 10820
31.9%
Common
ValueCountFrequency (%)
11337
80.6%
: 676
 
4.8%
9 272
 
1.9%
1 258
 
1.8%
0 204
 
1.5%
, 159
 
1.1%
- 151
 
1.1%
) 138
 
1.0%
( 138
 
1.0%
2 110
 
0.8%
Other values (20) 624
 
4.4%
Han
ValueCountFrequency (%)
年 6
42.9%
觀 1
 
7.1%
槪 1
 
7.1%
濟 1
 
7.1%
經 1
 
7.1%
韓 1
 
7.1%
北 1
 
7.1%
型 1
 
7.1%
模 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47917
64.0%
Hangul 26874
35.9%
None 76
 
0.1%
Number Forms 15
 
< 0.1%
CJK 14
 
< 0.1%
Punctuation 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11337
23.7%
e 3478
 
7.3%
o 3043
 
6.4%
n 2956
 
6.2%
a 2633
 
5.5%
i 2503
 
5.2%
t 2324
 
4.9%
r 2301
 
4.8%
s 1571
 
3.3%
c 1229
 
2.6%
Other values (67) 14542
30.3%
Hangul
ValueCountFrequency (%)
의 1291
 
4.8%
제 932
 
3.5%
과 750
 
2.8%
한 733
 
2.7%
정 716
 
2.7%
구 551
 
2.1%
경 505
 
1.9%
업 487
 
1.8%
국 444
 
1.7%
방 432
 
1.6%
Other values (436) 20033
74.5%
None
ValueCountFrequency (%)
· 76
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
40.0%
Ⅰ 5
33.3%
Ⅲ 3
20.0%
Ⅳ 1
 
6.7%
CJK
ValueCountFrequency (%)
年 6
42.9%
觀 1
 
7.1%
槪 1
 
7.1%
濟 1
 
7.1%
經 1
 
7.1%
韓 1
 
7.1%
北 1
 
7.1%
型 1
 
7.1%
模 1
 
7.1%
Punctuation
ValueCountFrequency (%)
’ 4
40.0%
” 3
30.0%
“ 3
30.0%

영문서명
Text

MISSING 

Distinct1132
Distinct (%)99.1%
Missing912
Missing (%)44.4%
Memory size16.2 KiB
2023-12-13T05:31:43.898322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length181
Median length120
Mean length70.984238
Min length14

Characters and Unicode

Total characters81064
Distinct characters86
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1122 ?
Unique (%)98.2%

Sample

1st rowDeterminants of Stock Market Participation Decision
2nd rowKDI Annual Report 2002
3rd rowAn Analysis of Systemic Factors of the Asian Financial Crisis : The Cases of Korea and Japan
4th rowAn Agenda for Economic Reform in Korea
5th rowLessons from the Japanese Lost Decade
ValueCountFrequency (%)
of 719
 
6.1%
the 704
 
5.9%
and 672
 
5.7%
in 481
 
4.1%
korea 405
 
3.4%
on 287
 
2.4%
263
 
2.2%
a 212
 
1.8%
policy 201
 
1.7%
economic 192
 
1.6%
Other values (1877) 7704
65.1%
2023-12-13T05:31:44.469437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10710
13.2%
e 6608
 
8.2%
n 6195
 
7.6%
o 6155
 
7.6%
i 5134
 
6.3%
a 5087
 
6.3%
t 4912
 
6.1%
r 4308
 
5.3%
s 3313
 
4.1%
c 2697
 
3.3%
Other values (76) 25945
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59783
73.7%
Space Separator 10710
 
13.2%
Uppercase Letter 8721
 
10.8%
Other Punctuation 725
 
0.9%
Decimal Number 665
 
0.8%
Dash Punctuation 246
 
0.3%
Open Punctuation 71
 
0.1%
Close Punctuation 71
 
0.1%
Final Punctuation 44
 
0.1%
Math Symbol 12
 
< 0.1%
Other values (3) 16
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6608
11.1%
n 6195
10.4%
o 6155
10.3%
i 5134
 
8.6%
a 5087
 
8.5%
t 4912
 
8.2%
r 4308
 
7.2%
s 3313
 
5.5%
c 2697
 
4.5%
l 2229
 
3.7%
Other values (16) 13145
22.0%
Uppercase Letter
ValueCountFrequency (%)
S 857
9.8%
P 856
9.8%
E 839
9.6%
I 749
 
8.6%
K 748
 
8.6%
C 643
 
7.4%
A 594
 
6.8%
R 492
 
5.6%
T 463
 
5.3%
D 439
 
5.0%
Other values (16) 2041
23.4%
Decimal Number
ValueCountFrequency (%)
9 155
23.3%
1 148
22.3%
0 92
13.8%
2 54
 
8.1%
5 53
 
8.0%
7 49
 
7.4%
8 36
 
5.4%
4 30
 
4.5%
6 26
 
3.9%
3 22
 
3.3%
Other Punctuation
ValueCountFrequency (%)
: 424
58.5%
, 136
 
18.8%
' 87
 
12.0%
. 32
 
4.4%
? 19
 
2.6%
& 17
 
2.3%
/ 8
 
1.1%
; 1
 
0.1%
# 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
36.4%
Ⅰ 4
36.4%
Ⅲ 2
18.2%
Ⅳ 1
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 245
99.6%
― 1
 
0.4%
Final Punctuation
ValueCountFrequency (%)
’ 41
93.2%
” 3
 
6.8%
Initial Punctuation
ValueCountFrequency (%)
“ 3
75.0%
‘ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
10710
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 68515
84.5%
Common 12549
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6608
 
9.6%
n 6195
 
9.0%
o 6155
 
9.0%
i 5134
 
7.5%
a 5087
 
7.4%
t 4912
 
7.2%
r 4308
 
6.3%
s 3313
 
4.8%
c 2697
 
3.9%
l 2229
 
3.3%
Other values (46) 21877
31.9%
Common
ValueCountFrequency (%)
10710
85.3%
: 424
 
3.4%
- 245
 
2.0%
9 155
 
1.2%
1 148
 
1.2%
, 136
 
1.1%
0 92
 
0.7%
' 87
 
0.7%
( 71
 
0.6%
) 71
 
0.6%
Other values (20) 410
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81004
99.9%
Punctuation 49
 
0.1%
Number Forms 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10710
13.2%
e 6608
 
8.2%
n 6195
 
7.6%
o 6155
 
7.6%
i 5134
 
6.3%
a 5087
 
6.3%
t 4912
 
6.1%
r 4308
 
5.3%
s 3313
 
4.1%
c 2697
 
3.3%
Other values (67) 25885
32.0%
Punctuation
ValueCountFrequency (%)
’ 41
83.7%
“ 3
 
6.1%
” 3
 
6.1%
‘ 1
 
2.0%
― 1
 
2.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
36.4%
Ⅰ 4
36.4%
Ⅲ 2
18.2%
Ⅳ 1
 
9.1%

한글서명
Text

MISSING 

Distinct876
Distinct (%)99.3%
Missing1172
Missing (%)57.1%
Memory size16.2 KiB
2023-12-13T05:31:44.802086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length48
Mean length21.439909
Min length4

Characters and Unicode

Total characters18910
Distinct characters970
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique870 ?
Unique (%)98.6%

Sample

1st row상호주 규제의 검토
2nd row金融制度 改善 및 動向分析
3rd row公務員 人事 및 報酬制度의 改善方案
4th row韓國의 流通近代化 方向
5th row短期金融市場의 改善方案
ValueCountFrequency (%)
207
 
5.4%
및 83
 
2.2%
위한 56
 
1.5%
관한 52
 
1.4%
韓國의 45
 
1.2%
硏究 42
 
1.1%
改善方案 39
 
1.0%
中心으로 37
 
1.0%
分析 36
 
0.9%
우리나라 32
 
0.8%
Other values (2122) 3182
83.5%
2023-12-13T05:31:45.369349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2934
 
15.5%
의 679
 
3.6%
業 300
 
1.6%
國 289
 
1.5%
方 276
 
1.5%
과 267
 
1.4%
政 263
 
1.4%
策 238
 
1.3%
經 227
 
1.2%
: 215
 
1.1%
Other values (960) 13222
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14341
75.8%
Space Separator 2934
 
15.5%
Decimal Number 523
 
2.8%
Lowercase Letter 462
 
2.4%
Other Punctuation 320
 
1.7%
Uppercase Letter 174
 
0.9%
Open Punctuation 62
 
0.3%
Close Punctuation 62
 
0.3%
Math Symbol 17
 
0.1%
Dash Punctuation 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 679
 
4.7%
業 300
 
2.1%
國 289
 
2.0%
方 276
 
1.9%
과 267
 
1.9%
政 263
 
1.8%
策 238
 
1.7%
經 227
 
1.6%
濟 191
 
1.3%
韓 181
 
1.3%
Other values (887) 11430
79.7%
Lowercase Letter
ValueCountFrequency (%)
o 54
11.7%
e 44
9.5%
t 43
9.3%
i 41
8.9%
r 36
 
7.8%
s 35
 
7.6%
a 33
 
7.1%
n 33
 
7.1%
l 22
 
4.8%
d 22
 
4.8%
Other values (15) 99
21.4%
Uppercase Letter
ValueCountFrequency (%)
I 35
20.1%
E 16
9.2%
D 16
9.2%
C 13
 
7.5%
T 11
 
6.3%
R 11
 
6.3%
O 11
 
6.3%
A 8
 
4.6%
G 8
 
4.6%
S 8
 
4.6%
Other values (13) 37
21.3%
Decimal Number
ValueCountFrequency (%)
9 106
20.3%
0 106
20.3%
1 105
20.1%
2 55
10.5%
8 45
8.6%
7 32
 
6.1%
5 28
 
5.4%
6 17
 
3.3%
3 16
 
3.1%
4 13
 
2.5%
Other Punctuation
ValueCountFrequency (%)
: 215
67.2%
· 47
 
14.7%
, 43
 
13.4%
/ 3
 
0.9%
? 3
 
0.9%
' 3
 
0.9%
& 2
 
0.6%
; 2
 
0.6%
. 2
 
0.6%
Space Separator
ValueCountFrequency (%)
2934
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 11612
61.4%
Common 3932
 
20.8%
Hangul 2729
 
14.4%
Latin 637
 
3.4%

Most frequent character per script

Han
ValueCountFrequency (%)
業 300
 
2.6%
國 289
 
2.5%
方 276
 
2.4%
政 263
 
2.3%
策 238
 
2.0%
經 227
 
2.0%
濟 191
 
1.6%
韓 181
 
1.6%
制 174
 
1.5%
案 165
 
1.4%
Other values (674) 9308
80.2%
Hangul
ValueCountFrequency (%)
의 679
24.9%
과 267
 
9.8%
와 177
 
6.5%
한 172
 
6.3%
에 113
 
4.1%
을 86
 
3.2%
및 84
 
3.1%
로 63
 
2.3%
리 61
 
2.2%
위 58
 
2.1%
Other values (203) 969
35.5%
Latin
ValueCountFrequency (%)
o 54
 
8.5%
e 44
 
6.9%
t 43
 
6.8%
i 41
 
6.4%
r 36
 
5.7%
s 35
 
5.5%
I 35
 
5.5%
a 33
 
5.2%
n 33
 
5.2%
l 22
 
3.5%
Other values (39) 261
41.0%
Common
ValueCountFrequency (%)
2934
74.6%
: 215
 
5.5%
9 106
 
2.7%
0 106
 
2.7%
1 105
 
2.7%
( 62
 
1.6%
) 62
 
1.6%
2 55
 
1.4%
· 47
 
1.2%
8 45
 
1.1%
Other values (14) 195
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 11330
59.9%
ASCII 4521
 
23.9%
Hangul 2729
 
14.4%
CJK Compat Ideographs 282
 
1.5%
None 47
 
0.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2934
64.9%
: 215
 
4.8%
9 106
 
2.3%
0 106
 
2.3%
1 105
 
2.3%
( 62
 
1.4%
) 62
 
1.4%
2 55
 
1.2%
o 54
 
1.2%
8 45
 
1.0%
Other values (61) 777
 
17.2%
Hangul
ValueCountFrequency (%)
의 679
24.9%
과 267
 
9.8%
와 177
 
6.5%
한 172
 
6.3%
에 113
 
4.1%
을 86
 
3.2%
및 84
 
3.1%
로 63
 
2.3%
리 61
 
2.2%
위 58
 
2.1%
Other values (203) 969
35.5%
CJK
ValueCountFrequency (%)
業 300
 
2.6%
國 289
 
2.6%
方 276
 
2.4%
政 263
 
2.3%
策 238
 
2.1%
經 227
 
2.0%
濟 191
 
1.7%
韓 181
 
1.6%
制 174
 
1.5%
案 165
 
1.5%
Other values (644) 9026
79.7%
CJK Compat Ideographs
ValueCountFrequency (%)
金 125
44.3%
率 32
 
11.3%
勞 32
 
11.3%
行 18
 
6.4%
來 16
 
5.7%
論 11
 
3.9%
數 7
 
2.5%
率 4
 
1.4%
老 3
 
1.1%
車 3
 
1.1%
Other values (20) 31
 
11.0%
None
ValueCountFrequency (%)
· 47
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

캘린더
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing1504
Missing (%)73.2%
Memory size4.1 KiB
False
505 
True
 
45
(Missing)
1504 
ValueCountFrequency (%)
False 505
 
24.6%
True 45
 
2.2%
(Missing) 1504
73.2%
2023-12-13T05:31:45.870061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

보고서종류
Categorical

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
A3
674 
A2
406 
A8
389 
A7
281 
A6
135 
Other values (3)
169 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA3
2nd rowA7
3rd rowA7
4th rowA7
5th rowA7

Common Values

ValueCountFrequency (%)
A3 674
32.8%
A2 406
19.8%
A8 389
18.9%
A7 281
13.7%
A6 135
 
6.6%
A1 102
 
5.0%
A5 52
 
2.5%
A4 15
 
0.7%

Length

2023-12-13T05:31:45.982544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:46.151397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a3 674
32.8%
a2 406
19.8%
a8 389
18.9%
a7 281
13.7%
a6 135
 
6.6%
a1 102
 
5.0%
a5 52
 
2.5%
a4 15
 
0.7%

서비스코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2
2054 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2054
100.0%

Length

2023-12-13T05:31:46.304817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:46.414327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2054
100.0%

제이엘코드
Text

MISSING 

Distinct882
Distinct (%)75.9%
Missing892
Missing (%)43.4%
Memory size16.2 KiB
2023-12-13T05:31:46.770860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.6385542
Min length3

Characters and Unicode

Total characters6552
Distinct characters30
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

Unique732 ?
Unique (%)63.0%

Sample

1st rowG23H55
2nd rowE30E31
3rd rowR12
4th rowO58P11A10
5th rowL16L52O38
ValueCountFrequency (%)
p60 20
 
1.7%
l32 9
 
0.8%
f31 8
 
0.7%
z00 8
 
0.7%
h21 8
 
0.7%
f14 7
 
0.6%
f13 7
 
0.6%
l41 7
 
0.6%
l32m00 7
 
0.6%
l61 6
 
0.5%
Other values (872) 1075
92.5%
2023-12-13T05:31:47.276022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 926
14.1%
0 776
11.8%
2 637
 
9.7%
3 586
 
8.9%
5 405
 
6.2%
4 335
 
5.1%
6 293
 
4.5%
L 286
 
4.4%
F 269
 
4.1%
O 264
 
4.0%
Other values (20) 1775
27.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4368
66.7%
Uppercase Letter 2184
33.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 286
13.1%
F 269
12.3%
O 264
12.1%
H 199
9.1%
G 166
7.6%
E 160
7.3%
J 157
7.2%
I 130
 
6.0%
R 102
 
4.7%
P 89
 
4.1%
Other values (10) 362
16.6%
Decimal Number
ValueCountFrequency (%)
1 926
21.2%
0 776
17.8%
2 637
14.6%
3 586
13.4%
5 405
9.3%
4 335
 
7.7%
6 293
 
6.7%
8 219
 
5.0%
7 103
 
2.4%
9 88
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4368
66.7%
Latin 2184
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 286
13.1%
F 269
12.3%
O 264
12.1%
H 199
9.1%
G 166
7.6%
E 160
7.3%
J 157
7.2%
I 130
 
6.0%
R 102
 
4.7%
P 89
 
4.1%
Other values (10) 362
16.6%
Common
ValueCountFrequency (%)
1 926
21.2%
0 776
17.8%
2 637
14.6%
3 586
13.4%
5 405
9.3%
4 335
 
7.7%
6 293
 
6.7%
8 219
 
5.0%
7 103
 
2.4%
9 88
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 926
14.1%
0 776
11.8%
2 637
 
9.7%
3 586
 
8.9%
5 405
 
6.2%
4 335
 
5.1%
6 293
 
4.5%
L 286
 
4.4%
F 269
 
4.1%
O 264
 
4.0%
Other values (20) 1775
27.1%

주제코드1
Text

Distinct773
Distinct (%)37.8%
Missing9
Missing (%)0.4%
Memory size16.2 KiB
2023-12-13T05:31:47.596203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.1545232
Min length4

Characters and Unicode

Total characters14631
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique519 ?
Unique (%)25.4%

Sample

1st rowB03|
2nd rowA09|
3rd rowA07|
4th rowA99|
5th rowA07|
ValueCountFrequency (%)
a09 73
 
3.6%
a02 53
 
2.6%
j02 37
 
1.8%
k99 33
 
1.6%
a04 33
 
1.6%
i00 32
 
1.6%
j01 32
 
1.6%
a99 31
 
1.5%
h00 27
 
1.3%
c05|c03 25
 
1.2%
Other values (760) 1669
81.6%
2023-12-13T05:31:48.018185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3675
25.1%
| 3654
25.0%
9 1266
 
8.7%
1 592
 
4.0%
2 585
 
4.0%
G 546
 
3.7%
A 524
 
3.6%
C 472
 
3.2%
B 436
 
3.0%
4 410
 
2.8%
Other values (17) 2471
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7318
50.0%
Uppercase Letter 3659
25.0%
Math Symbol 3654
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 546
14.9%
A 524
14.3%
C 472
12.9%
B 436
11.9%
E 328
9.0%
H 277
7.6%
I 268
7.3%
J 207
 
5.7%
K 179
 
4.9%
D 125
 
3.4%
Other values (6) 297
8.1%
Decimal Number
ValueCountFrequency (%)
0 3675
50.2%
9 1266
 
17.3%
1 592
 
8.1%
2 585
 
8.0%
4 410
 
5.6%
3 320
 
4.4%
5 167
 
2.3%
6 154
 
2.1%
7 112
 
1.5%
8 37
 
0.5%
Math Symbol
ValueCountFrequency (%)
| 3654
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10972
75.0%
Latin 3659
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 546
14.9%
A 524
14.3%
C 472
12.9%
B 436
11.9%
E 328
9.0%
H 277
7.6%
I 268
7.3%
J 207
 
5.7%
K 179
 
4.9%
D 125
 
3.4%
Other values (6) 297
8.1%
Common
ValueCountFrequency (%)
0 3675
33.5%
| 3654
33.3%
9 1266
 
11.5%
1 592
 
5.4%
2 585
 
5.3%
4 410
 
3.7%
3 320
 
2.9%
5 167
 
1.5%
6 154
 
1.4%
7 112
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3675
25.1%
| 3654
25.0%
9 1266
 
8.7%
1 592
 
4.0%
2 585
 
4.0%
G 546
 
3.7%
A 524
 
3.6%
C 472
 
3.2%
B 436
 
3.0%
4 410
 
2.8%
Other values (17) 2471
16.9%

언어
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
1
1487 
2
563 
3
 
3
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 1487
72.4%
2 563
 
27.4%
3 3
 
0.1%
0 1
 
< 0.1%

Length

2023-12-13T05:31:48.137954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:48.242273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1487
72.4%
2 563
 
27.4%
3 3
 
0.1%
0 1
 
< 0.1%

주제코드2
Text

MISSING 

Distinct690
Distinct (%)36.3%
Missing151
Missing (%)7.4%
Memory size16.2 KiB
2023-12-13T05:31:48.523648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.1066737
Min length4

Characters and Unicode

Total characters13524
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique451 ?
Unique (%)23.7%

Sample

1st rowB03|
2nd rowA09|
3rd rowA07|
4th rowA99|
5th rowA07|
ValueCountFrequency (%)
a09 73
 
3.8%
a02 53
 
2.8%
j02 37
 
1.9%
a04 33
 
1.7%
i00 32
 
1.7%
j01 32
 
1.7%
k99 30
 
1.6%
a99 29
 
1.5%
h00 26
 
1.4%
c05|c03 25
 
1.3%
Other values (680) 1533
80.6%
2023-12-13T05:31:48.922376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3408
25.2%
| 3381
25.0%
9 1158
 
8.6%
2 543
 
4.0%
1 537
 
4.0%
G 510
 
3.8%
A 495
 
3.7%
C 434
 
3.2%
B 395
 
2.9%
4 384
 
2.8%
Other values (16) 2279
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6762
50.0%
Math Symbol 3381
25.0%
Uppercase Letter 3381
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 510
15.1%
A 495
14.6%
C 434
12.8%
B 395
11.7%
E 302
8.9%
H 270
8.0%
I 243
7.2%
J 196
 
5.8%
K 158
 
4.7%
D 113
 
3.3%
Other values (5) 265
7.8%
Decimal Number
ValueCountFrequency (%)
0 3408
50.4%
9 1158
 
17.1%
2 543
 
8.0%
1 537
 
7.9%
4 384
 
5.7%
3 293
 
4.3%
5 154
 
2.3%
6 144
 
2.1%
7 106
 
1.6%
8 35
 
0.5%
Math Symbol
ValueCountFrequency (%)
| 3381
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10143
75.0%
Latin 3381
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 510
15.1%
A 495
14.6%
C 434
12.8%
B 395
11.7%
E 302
8.9%
H 270
8.0%
I 243
7.2%
J 196
 
5.8%
K 158
 
4.7%
D 113
 
3.3%
Other values (5) 265
7.8%
Common
ValueCountFrequency (%)
0 3408
33.6%
| 3381
33.3%
9 1158
 
11.4%
2 543
 
5.4%
1 537
 
5.3%
4 384
 
3.8%
3 293
 
2.9%
5 154
 
1.5%
6 144
 
1.4%
7 106
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3408
25.2%
| 3381
25.0%
9 1158
 
8.6%
2 543
 
4.0%
1 537
 
4.0%
G 510
 
3.8%
A 495
 
3.7%
C 434
 
3.2%
B 395
 
2.9%
4 384
 
2.8%
Other values (16) 2279
16.9%

주제코드3
Text

MISSING 

Distinct861
Distinct (%)44.5%
Missing121
Missing (%)5.9%
Memory size16.2 KiB
2023-12-13T05:31:49.228226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.4495603
Min length2

Characters and Unicode

Total characters6668
Distinct characters20
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

Unique596 ?
Unique (%)30.8%

Sample

1st rowI2
2nd rowJ4
3rd rowA0
4th rowA0C0E0
5th rowF5
ValueCountFrequency (%)
g0 53
 
2.7%
e6 41
 
2.1%
a6 34
 
1.8%
e3 33
 
1.7%
j5 31
 
1.6%
h1 24
 
1.2%
a7 24
 
1.2%
b8 24
 
1.2%
d1 22
 
1.1%
b2 22
 
1.1%
Other values (851) 1625
84.1%
2023-12-13T05:31:49.608953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 585
 
8.8%
B 560
 
8.4%
A 546
 
8.2%
1 533
 
8.0%
0 523
 
7.8%
5 405
 
6.1%
3 368
 
5.5%
D 366
 
5.5%
F 329
 
4.9%
2 305
 
4.6%
Other values (10) 2148
32.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3334
50.0%
Decimal Number 3334
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 585
17.5%
B 560
16.8%
A 546
16.4%
D 366
11.0%
F 329
9.9%
C 280
8.4%
J 271
8.1%
I 155
 
4.6%
G 132
 
4.0%
H 110
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 533
16.0%
0 523
15.7%
5 405
12.1%
3 368
11.0%
2 305
9.1%
6 276
8.3%
4 264
7.9%
8 253
7.6%
7 246
7.4%
9 161
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 3334
50.0%
Common 3334
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 585
17.5%
B 560
16.8%
A 546
16.4%
D 366
11.0%
F 329
9.9%
C 280
8.4%
J 271
8.1%
I 155
 
4.6%
G 132
 
4.0%
H 110
 
3.3%
Common
ValueCountFrequency (%)
1 533
16.0%
0 523
15.7%
5 405
12.1%
3 368
11.0%
2 305
9.1%
6 276
8.3%
4 264
7.9%
8 253
7.6%
7 246
7.4%
9 161
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 585
 
8.8%
B 560
 
8.4%
A 546
 
8.2%
1 533
 
8.0%
0 523
 
7.8%
5 405
 
6.1%
3 368
 
5.5%
D 366
 
5.5%
F 329
 
4.9%
2 305
 
4.6%
Other values (10) 2148
32.2%

카운트
Real number (ℝ)

ZEROS 

Distinct401
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296.09299
Minimum0
Maximum11975
Zeros1159
Zeros (%)56.4%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-13T05:31:49.742524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q357.5
95-th percentile1556.45
Maximum11975
Range11975
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation669.79709
Coefficient of variation (CV)2.2621173
Kurtosis84.915468
Mean296.09299
Median Absolute Deviation (MAD)0
Skewness5.9937653
Sum608175
Variance448628.14
MonotonicityNot monotonic
2023-12-13T05:31:49.901193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1159
56.4%
1 62
 
3.0%
5 35
 
1.7%
2 25
 
1.2%
18 18
 
0.9%
6 17
 
0.8%
16 17
 
0.8%
9 13
 
0.6%
4 12
 
0.6%
7 11
 
0.5%
Other values (391) 685
33.3%
ValueCountFrequency (%)
0 1159
56.4%
1 62
 
3.0%
2 25
 
1.2%
3 10
 
0.5%
4 12
 
0.6%
5 35
 
1.7%
6 17
 
0.8%
7 11
 
0.5%
8 8
 
0.4%
9 13
 
0.6%
ValueCountFrequency (%)
11975 1
< 0.1%
11647 1
< 0.1%
3996 1
< 0.1%
2754 1
< 0.1%
2569 1
< 0.1%
2474 1
< 0.1%
2380 1
< 0.1%
2306 1
< 0.1%
2279 1
< 0.1%
1997 1
< 0.1%

페이지
Real number (ℝ)

Distinct457
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.55794
Minimum4
Maximum1051
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-13T05:31:50.074630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile25
Q149
median80
Q3182.75
95-th percentile434
Maximum1051
Range1047
Interquartile range (IQR)133.75

Descriptive statistics

Standard deviation139.62098
Coefficient of variation (CV)1.0004518
Kurtosis5.037681
Mean139.55794
Median Absolute Deviation (MAD)44
Skewness2.0494021
Sum286652
Variance19494.019
MonotonicityNot monotonic
2023-12-13T05:31:50.211628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41 28
 
1.4%
55 27
 
1.3%
42 25
 
1.2%
50 23
 
1.1%
58 23
 
1.1%
60 23
 
1.1%
51 22
 
1.1%
47 22
 
1.1%
35 22
 
1.1%
39 21
 
1.0%
Other values (447) 1818
88.5%
ValueCountFrequency (%)
4 1
 
< 0.1%
8 1
 
< 0.1%
11 2
 
0.1%
12 2
 
0.1%
13 4
0.2%
14 4
0.2%
15 5
0.2%
16 4
0.2%
17 6
0.3%
18 8
0.4%
ValueCountFrequency (%)
1051 1
< 0.1%
933 1
< 0.1%
884 1
< 0.1%
875 1
< 0.1%
872 1
< 0.1%
845 1
< 0.1%
811 1
< 0.1%
781 1
< 0.1%
750 2
0.1%
721 1
< 0.1%

다운로드
Real number (ℝ)

ZEROS 

Distinct154
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.127069
Minimum0
Maximum1342
Zeros658
Zeros (%)32.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-13T05:31:50.368760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q317
95-th percentile77.7
Maximum1342
Range1342
Interquartile range (IQR)17

Descriptive statistics

Standard deviation62.448872
Coefficient of variation (CV)3.1027305
Kurtosis161.78024
Mean20.127069
Median Absolute Deviation (MAD)6
Skewness10.662315
Sum41341
Variance3899.8616
MonotonicityNot monotonic
2023-12-13T05:31:50.533680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 658
32.0%
4 94
 
4.6%
6 82
 
4.0%
5 79
 
3.8%
3 72
 
3.5%
7 66
 
3.2%
1 57
 
2.8%
9 57
 
2.8%
8 54
 
2.6%
10 52
 
2.5%
Other values (144) 783
38.1%
ValueCountFrequency (%)
0 658
32.0%
1 57
 
2.8%
2 49
 
2.4%
3 72
 
3.5%
4 94
 
4.6%
5 79
 
3.8%
6 82
 
4.0%
7 66
 
3.2%
8 54
 
2.6%
9 57
 
2.8%
ValueCountFrequency (%)
1342 1
< 0.1%
979 1
< 0.1%
730 1
< 0.1%
719 1
< 0.1%
701 1
< 0.1%
695 1
< 0.1%
670 1
< 0.1%
374 1
< 0.1%
355 1
< 0.1%
332 1
< 0.1%

가격
Text

MISSING 

Distinct121
Distinct (%)6.4%
Missing164
Missing (%)8.0%
Memory size16.2 KiB
2023-12-13T05:31:50.784581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9603175
Min length1

Characters and Unicode

Total characters7485
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)2.9%

Sample

1st row2000
2nd row6000
3rd row19000
4th row2000
5th row12000
ValueCountFrequency (%)
2000 658
34.8%
3000 326
17.2%
4000 248
 
13.1%
5000 66
 
3.5%
0 49
 
2.6%
6000 49
 
2.6%
4500 28
 
1.5%
1000 28
 
1.5%
3500 24
 
1.3%
8000 20
 
1.1%
Other values (111) 394
20.8%
2023-12-13T05:31:51.174056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5223
69.8%
2 773
 
10.3%
3 435
 
5.8%
4 344
 
4.6%
5 248
 
3.3%
1 166
 
2.2%
8 108
 
1.4%
6 103
 
1.4%
7 51
 
0.7%
9 33
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7484
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5223
69.8%
2 773
 
10.3%
3 435
 
5.8%
4 344
 
4.6%
5 248
 
3.3%
1 166
 
2.2%
8 108
 
1.4%
6 103
 
1.4%
7 51
 
0.7%
9 33
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7485
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5223
69.8%
2 773
 
10.3%
3 435
 
5.8%
4 344
 
4.6%
5 248
 
3.3%
1 166
 
2.2%
8 108
 
1.4%
6 103
 
1.4%
7 51
 
0.7%
9 33
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5223
69.8%
2 773
 
10.3%
3 435
 
5.8%
4 344
 
4.6%
5 248
 
3.3%
1 166
 
2.2%
8 108
 
1.4%
6 103
 
1.4%
7 51
 
0.7%
9 33
 
0.4%

발간일
Date

Distinct889
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1971-06-01 00:00:00
Maximum2021-06-10 00:00:00
2023-12-13T05:31:51.324760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:31:51.503760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발간번호
Real number (ℝ)

UNIQUE 

Distinct2054
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4582.2259
Minimum1
Maximum17140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2023-12-13T05:31:51.671788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile105.3
Q1556.25
median1834.5
Q38970.75
95-th percentile15790.35
Maximum17140
Range17139
Interquartile range (IQR)8414.5

Descriptive statistics

Standard deviation5433.6336
Coefficient of variation (CV)1.1858066
Kurtosis-0.48685318
Mean4582.2259
Median Absolute Deviation (MAD)1531.5
Skewness1.0341035
Sum9411892
Variance29524374
MonotonicityNot monotonic
2023-12-13T05:31:51.834205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6939 1
 
< 0.1%
2147 1
 
< 0.1%
1550 1
 
< 0.1%
6004 1
 
< 0.1%
6981 1
 
< 0.1%
6979 1
 
< 0.1%
6342 1
 
< 0.1%
2181 1
 
< 0.1%
1548 1
 
< 0.1%
88 1
 
< 0.1%
Other values (2044) 2044
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
17140 1
< 0.1%
17129 1
< 0.1%
17128 1
< 0.1%
17124 1
< 0.1%
17116 1
< 0.1%
17115 1
< 0.1%
17056 1
< 0.1%
17052 1
< 0.1%
17051 1
< 0.1%
16993 1
< 0.1%

입고
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
0
2035 
10
 
19

Length

Max length2
Median length1
Mean length1.0092502
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2035
99.1%
10 19
 
0.9%

Length

2023-12-13T05:31:51.958128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:52.055743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2035
99.1%
10 19
 
0.9%

발행처
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
韓國開發硏究院
831 
한국개발연구원
715 
Korea Development Institute
476 
Harvard University Press
 
13
비봉출판사
 
5
Other values (13)
 
14

Length

Max length46
Median length7
Mean length11.787244
Min length3

Unique

Unique12 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
韓國開發硏究院 831
40.5%
한국개발연구원 715
34.8%
Korea Development Institute 476
23.2%
Harvard University Press 13
 
0.6%
비봉출판사 5
 
0.2%
博英社 2
 
0.1%
재정경제부, 한국개발연구원 1
 
< 0.1%
Korea Development Institute, Republic of Korea 1
 
< 0.1%
세경사 1
 
< 0.1%
한국개발연구원,농외소득기획단 실무작업반 1
 
< 0.1%
Other values (8) 8
 
0.4%

Length

2023-12-13T05:31:52.158225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
韓國開發硏究院 832
27.3%
한국개발연구원 719
23.6%
korea 479
15.7%
institute 478
15.7%
development 477
15.7%
harvard 13
 
0.4%
university 13
 
0.4%
press 13
 
0.4%
비봉출판사 6
 
0.2%
博英社 2
 
0.1%
Other values (12) 13
 
0.4%

발행처영문
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Korea Development Institute
2025 
Harvard University Press
 
13
<NA>
 
12
Korea Development Institute, Republic of KoreaKorea Development Institute, Republic of Korea
 
1
Korea Development Institute
 
1
Other values (2)
 
2

Length

Max length92
Median length27
Mean length26.895326
Min length4

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st rowKorea Development Institute
2nd rowKorea Development Institute
3rd rowKorea Development Institute
4th rowKorea Development Institute
5th rowKorea Development Institute

Common Values

ValueCountFrequency (%)
Korea Development Institute 2025
98.6%
Harvard University Press 13
 
0.6%
<NA> 12
 
0.6%
Korea Development Institute, Republic of KoreaKorea Development Institute, Republic of Korea 1
 
< 0.1%
Korea Development Institute 1
 
< 0.1%
Ministry of Finance and Economy, Korea Development Institute 1
 
< 0.1%
Korea Developement Institute 1
 
< 0.1%

Length

2023-12-13T05:31:52.283289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:52.413243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
korea 2030
33.0%
institute 2030
33.0%
development 2029
33.0%
harvard 13
 
0.2%
university 13
 
0.2%
press 13
 
0.2%
na 12
 
0.2%
of 3
 
< 0.1%
republic 2
 
< 0.1%
koreakorea 1
 
< 0.1%
Other values (5) 5
 
0.1%

보고서타입
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2
1258 
<NA>
795 
1
 
1

Length

Max length4
Median length1
Mean length2.161149
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 1258
61.2%
<NA> 795
38.7%
1 1
 
< 0.1%

Length

2023-12-13T05:31:52.572444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:52.674634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1258
61.2%
na 795
38.7%
1 1
 
< 0.1%

등록일
Date

Distinct621
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1971-03-11 00:00:00
Maximum2021-06-29 10:15:00
2023-12-13T05:31:52.800628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:31:52.937387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

입고수량
Real number (ℝ)

ZEROS 

Distinct186
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.229796
Minimum-1641
Maximum1085
Zeros506
Zeros (%)24.6%
Negative6
Negative (%)0.3%
Memory size18.2 KiB
2023-12-13T05:31:53.081712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1641
5-th percentile0
Q11
median5
Q311
95-th percentile142.35
Maximum1085
Range2726
Interquartile range (IQR)10

Descriptive statistics

Standard deviation93.788056
Coefficient of variation (CV)3.8707737
Kurtosis133.07353
Mean24.229796
Median Absolute Deviation (MAD)5
Skewness-5.259937
Sum49768
Variance8796.1995
MonotonicityNot monotonic
2023-12-13T05:31:53.232797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 584
28.4%
0 506
24.6%
3 102
 
5.0%
10 97
 
4.7%
4 91
 
4.4%
110 79
 
3.8%
1 75
 
3.7%
30 31
 
1.5%
15 30
 
1.5%
9 26
 
1.3%
Other values (176) 433
21.1%
ValueCountFrequency (%)
-1641 1
 
< 0.1%
-1417 1
 
< 0.1%
-1386 1
 
< 0.1%
-1254 1
 
< 0.1%
-539 1
 
< 0.1%
-330 1
 
< 0.1%
0 506
24.6%
1 75
 
3.7%
2 15
 
0.7%
3 102
 
5.0%
ValueCountFrequency (%)
1085 1
 
< 0.1%
1000 1
 
< 0.1%
626 1
 
< 0.1%
510 4
0.2%
488 1
 
< 0.1%
445 1
 
< 0.1%
423 1
 
< 0.1%
416 1
 
< 0.1%
402 1
 
< 0.1%
336 1
 
< 0.1%

시리즈
Categorical

Distinct39
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Working Paper
376 
정책연구시리즈
368 
<NA>
278 
연구보고서
192 
政策硏究資料
123 
Other values (34)
717 

Length

Max length44
Median length18
Mean length7.1903603
Min length2

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row정책연구시리즈
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
Working Paper 376
18.3%
정책연구시리즈 368
17.9%
<NA> 278
13.5%
연구보고서 192
9.3%
政策硏究資料 123
 
6.0%
硏究資料 109
 
5.3%
硏究報告 90
 
4.4%
硏究叢書 67
 
3.3%
硏究調査報告 66
 
3.2%
硏究報告書 58
 
2.8%
Other values (29) 327
15.9%

Length

2023-12-13T05:31:53.368430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
working 377
14.8%
paper 377
14.8%
정책연구시리즈 368
14.5%
na 278
10.9%
연구보고서 192
 
7.5%
政策硏究資料 123
 
4.8%
硏究資料 119
 
4.7%
硏究報告 90
 
3.5%
硏究叢書 67
 
2.6%
硏究調査報告 66
 
2.6%
Other values (35) 489
19.2%

시리즈영문
Categorical

Distinct13
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1051 
Working Paper
376 
Policy Study
367 
Research Monograph
207 
Monograph
 
21
Other values (8)
 
32

Length

Max length29
Median length4
Mean length8.7643622
Min length4

Unique

Unique4 ?
Unique (%)0.2%

Sample

1st rowPolicy Study
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1051
51.2%
Working Paper 376
 
18.3%
Policy Study 367
 
17.9%
Research Monograph 207
 
10.1%
Monograph 21
 
1.0%
Harvard East Asian Monographs 10
 
0.5%
Interim Report 8
 
0.4%
Policy Monograph 7
 
0.3%
Memorandum 3
 
0.1%
KDI Working Paper 1
 
< 0.1%
Other values (3) 3
 
0.1%

Length

2023-12-13T05:31:53.790699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1051
34.4%
working 377
 
12.3%
paper 377
 
12.3%
policy 376
 
12.3%
study 369
 
12.1%
monograph 235
 
7.7%
research 207
 
6.8%
harvard 10
 
0.3%
east 10
 
0.3%
asian 10
 
0.3%
Other values (6) 31
 
1.0%

시리즈번호
Text

MISSING 

Distinct1260
Distinct (%)72.4%
Missing313
Missing (%)15.2%
Memory size16.2 KiB
2023-12-13T05:31:54.151645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length5.3831132
Min length1

Characters and Unicode

Total characters9372
Distinct characters40
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique931 ?
Unique (%)53.5%

Sample

1st rowApr-02
2nd row99-30
3rd rowApr-01
4th rowFeb-01
5th rowAug-01
ValueCountFrequency (%)
jan-93 7
 
0.4%
jan-00 6
 
0.3%
jan-92 6
 
0.3%
jan-12 5
 
0.3%
jan-91 5
 
0.3%
jan-02 5
 
0.3%
jan-99 5
 
0.3%
jan-13 5
 
0.3%
may-93 5
 
0.3%
feb-01 5
 
0.3%
Other values (1253) 1690
96.9%
2023-12-13T05:31:54.768721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1284
13.7%
1 904
 
9.6%
0 824
 
8.8%
9 784
 
8.4%
8 611
 
6.5%
2 536
 
5.7%
7 364
 
3.9%
a 342
 
3.6%
3 307
 
3.3%
J 304
 
3.2%
Other values (30) 3112
33.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5097
54.4%
Lowercase Letter 1903
 
20.3%
Dash Punctuation 1284
 
13.7%
Uppercase Letter 948
 
10.1%
Other Letter 134
 
1.4%
Other Punctuation 3
 
< 0.1%
Space Separator 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 342
18.0%
n 231
12.1%
u 216
11.4%
e 209
11.0%
r 200
10.5%
p 150
7.9%
b 116
 
6.1%
y 90
 
4.7%
c 84
 
4.4%
l 73
 
3.8%
Other values (5) 192
10.1%
Decimal Number
ValueCountFrequency (%)
1 904
17.7%
0 824
16.2%
9 784
15.4%
8 611
12.0%
2 536
10.5%
7 364
7.1%
3 307
 
6.0%
4 275
 
5.4%
5 269
 
5.3%
6 223
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
J 304
32.1%
M 192
20.3%
A 158
16.7%
F 115
 
12.1%
S 54
 
5.7%
O 47
 
5.0%
N 41
 
4.3%
D 37
 
3.9%
Other Letter
ValueCountFrequency (%)
卷 66
49.3%
第 66
49.3%
제 1
 
0.7%
호 1
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 1284
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6387
68.1%
Latin 2851
30.4%
Han 132
 
1.4%
Hangul 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 342
12.0%
J 304
10.7%
n 231
 
8.1%
u 216
 
7.6%
e 209
 
7.3%
r 200
 
7.0%
M 192
 
6.7%
A 158
 
5.5%
p 150
 
5.3%
b 116
 
4.1%
Other values (13) 733
25.7%
Common
ValueCountFrequency (%)
- 1284
20.1%
1 904
14.2%
0 824
12.9%
9 784
12.3%
8 611
9.6%
2 536
8.4%
7 364
 
5.7%
3 307
 
4.8%
4 275
 
4.3%
5 269
 
4.2%
Other values (3) 229
 
3.6%
Han
ValueCountFrequency (%)
卷 66
50.0%
第 66
50.0%
Hangul
ValueCountFrequency (%)
제 1
50.0%
호 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9238
98.6%
CJK 132
 
1.4%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1284
13.9%
1 904
 
9.8%
0 824
 
8.9%
9 784
 
8.5%
8 611
 
6.6%
2 536
 
5.8%
7 364
 
3.9%
a 342
 
3.7%
3 307
 
3.3%
J 304
 
3.3%
Other values (26) 2978
32.2%
CJK
ValueCountFrequency (%)
卷 66
50.0%
第 66
50.0%
Hangul
ValueCountFrequency (%)
제 1
50.0%
호 1
50.0%

시리즈번호영문
Text

MISSING 

Distinct755
Distinct (%)75.4%
Missing1053
Missing (%)51.3%
Memory size16.2 KiB
2023-12-13T05:31:55.251315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length6
Mean length5.3826174
Min length2

Characters and Unicode

Total characters5388
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique564 ?
Unique (%)56.3%

Sample

1st rowApr-02
2nd rowApr-01
3rd rowAug-01
4th rowJul-01
5th rowDec-02
ValueCountFrequency (%)
jan-12 5
 
0.5%
jan-00 5
 
0.5%
jan-03 5
 
0.5%
jan-16 4
 
0.4%
feb-00 4
 
0.4%
jan-14 4
 
0.4%
jan-07 4
 
0.4%
jan-04 4
 
0.4%
jan-13 4
 
0.4%
feb-12 4
 
0.4%
Other values (748) 961
95.7%
2023-12-13T05:31:55.900232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 719
13.3%
1 690
12.8%
- 631
 
11.7%
2 348
 
6.5%
9 315
 
5.8%
8 299
 
5.5%
7 230
 
4.3%
a 183
 
3.4%
J 168
 
3.1%
5 162
 
3.0%
Other values (26) 1643
30.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3196
59.3%
Lowercase Letter 1039
 
19.3%
Dash Punctuation 631
 
11.7%
Uppercase Letter 516
 
9.6%
Other Punctuation 3
 
0.1%
Space Separator 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 183
17.6%
n 129
12.4%
u 117
11.3%
e 116
11.2%
r 101
9.7%
p 82
7.9%
b 58
 
5.6%
c 52
 
5.0%
y 46
 
4.4%
l 39
 
3.8%
Other values (5) 116
11.2%
Decimal Number
ValueCountFrequency (%)
0 719
22.5%
1 690
21.6%
2 348
10.9%
9 315
9.9%
8 299
9.4%
7 230
 
7.2%
5 162
 
5.1%
3 162
 
5.1%
4 140
 
4.4%
6 131
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
J 168
32.6%
M 97
18.8%
A 83
16.1%
F 57
 
11.0%
S 34
 
6.6%
O 30
 
5.8%
N 25
 
4.8%
D 22
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 631
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3833
71.1%
Latin 1555
28.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 183
11.8%
J 168
 
10.8%
n 129
 
8.3%
u 117
 
7.5%
e 116
 
7.5%
r 101
 
6.5%
M 97
 
6.2%
A 83
 
5.3%
p 82
 
5.3%
b 58
 
3.7%
Other values (13) 421
27.1%
Common
ValueCountFrequency (%)
0 719
18.8%
1 690
18.0%
- 631
16.5%
2 348
9.1%
9 315
8.2%
8 299
7.8%
7 230
 
6.0%
5 162
 
4.2%
3 162
 
4.2%
4 140
 
3.7%
Other values (3) 137
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 719
13.3%
1 690
12.8%
- 631
 
11.7%
2 348
 
6.5%
9 315
 
5.8%
8 299
 
5.5%
7 230
 
4.3%
a 183
 
3.4%
J 168
 
3.1%
5 162
 
3.0%
Other values (26) 1643
30.5%

제출일
Date

MISSING 

Distinct52
Distinct (%)55.9%
Missing1961
Missing (%)95.5%
Memory size16.2 KiB
Minimum1975-07-01 00:00:00
Maximum2003-05-28 00:00:00
2023-12-13T05:31:56.073432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:31:56.281781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제출처
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing2050
Missing (%)99.8%
Memory size16.2 KiB
2023-12-13T05:31:56.507603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length8
Mean length21.75
Min length5

Characters and Unicode

Total characters87
Distinct characters41
Distinct categories5 ?
Distinct scripts3 ?
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 row대외경제정책연구원
2nd rowKDI, Korea Research Institute For Vocational Education & training
3rd row한국개발연구원
4th row기획재정부
ValueCountFrequency (%)
대외경제정책연구원 1
8.3%
kdi 1
8.3%
korea 1
8.3%
research 1
8.3%
institute 1
8.3%
for 1
8.3%
vocational 1
8.3%
education 1
8.3%
1
8.3%
training 1
8.3%
Other values (2) 2
16.7%
2023-12-13T05:31:56.920788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
10.3%
t 6
 
6.9%
a 6
 
6.9%
o 5
 
5.7%
i 5
 
5.7%
n 5
 
5.7%
e 4
 
4.6%
r 4
 
4.6%
c 3
 
3.4%
K 2
 
2.3%
Other values (31) 38
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46
52.9%
Other Letter 21
24.1%
Space Separator 9
 
10.3%
Uppercase Letter 9
 
10.3%
Other Punctuation 2
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 2
 
9.5%
구 2
 
9.5%
연 2
 
9.5%
정 2
 
9.5%
재 1
 
4.8%
획 1
 
4.8%
국 1
 
4.8%
한 1
 
4.8%
발 1
 
4.8%
기 1
 
4.8%
Other values (7) 7
33.3%
Lowercase Letter
ValueCountFrequency (%)
t 6
13.0%
a 6
13.0%
o 5
10.9%
i 5
10.9%
n 5
10.9%
e 4
8.7%
r 4
8.7%
c 3
6.5%
u 2
 
4.3%
s 2
 
4.3%
Other values (4) 4
8.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
22.2%
I 2
22.2%
E 1
11.1%
V 1
11.1%
F 1
11.1%
R 1
11.1%
D 1
11.1%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55
63.2%
Hangul 21
 
24.1%
Common 11
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
10.9%
a 6
10.9%
o 5
 
9.1%
i 5
 
9.1%
n 5
 
9.1%
e 4
 
7.3%
r 4
 
7.3%
c 3
 
5.5%
K 2
 
3.6%
I 2
 
3.6%
Other values (11) 13
23.6%
Hangul
ValueCountFrequency (%)
원 2
 
9.5%
구 2
 
9.5%
연 2
 
9.5%
정 2
 
9.5%
재 1
 
4.8%
획 1
 
4.8%
국 1
 
4.8%
한 1
 
4.8%
발 1
 
4.8%
기 1
 
4.8%
Other values (7) 7
33.3%
Common
ValueCountFrequency (%)
9
81.8%
& 1
 
9.1%
, 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
75.9%
Hangul 21
 
24.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
13.6%
t 6
 
9.1%
a 6
 
9.1%
o 5
 
7.6%
i 5
 
7.6%
n 5
 
7.6%
e 4
 
6.1%
r 4
 
6.1%
c 3
 
4.5%
K 2
 
3.0%
Other values (14) 17
25.8%
Hangul
ValueCountFrequency (%)
원 2
 
9.5%
구 2
 
9.5%
연 2
 
9.5%
정 2
 
9.5%
재 1
 
4.8%
획 1
 
4.8%
국 1
 
4.8%
한 1
 
4.8%
발 1
 
4.8%
기 1
 
4.8%
Other values (7) 7
33.3%

보기
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
1
2034 
2
 
10
4
 
6
<NA>
 
4

Length

Max length4
Median length1
Mean length1.0058423
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2034
99.0%
2 10
 
0.5%
4 6
 
0.3%
<NA> 4
 
0.2%

Length

2023-12-13T05:31:57.076490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:31:57.236537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2034
99.0%
2 10
 
0.5%
4 6
 
0.3%
na 4
 
0.2%

Sample

서명영문서명한글서명캘린더보고서종류서비스코드제이엘코드주제코드1언어주제코드2주제코드3카운트페이지다운로드가격발간일발간번호입고발행처발행처영문보고서타입등록일입고수량시리즈시리즈영문시리즈번호시리즈번호영문제출일제출처보기
0한국 가계금융자산 구성의 결정요인 분석 : 주식보유를 중심으로Determinants of Stock Market Participation Decision<NA><NA>A32<NA>B03|1B03|I213094015220002002-12-31693910한국개발연구원Korea Development Institute22003-03-06 0:005정책연구시리즈Policy StudyApr-02Apr-02<NA><NA>1
1KDI Annual Report 2002KDI Annual Report 2002<NA><NA>A72<NA>A09|2A09|J4256923910460002003-03-05695710한국개발연구원Korea Development Institute22003-03-20 0:00445<NA><NA><NA><NA><NA><NA>1
2An Analysis of Systemic Factors of the Asian Financial Crisis : The Cases of Korea and JapanAn Analysis of Systemic Factors of the Asian Financial Crisis : The Cases of Korea and Japan<NA><NA>A72<NA>A07|2A07|A0762860<NA>2001-12-3166920한국개발연구원Korea Development Institute22002-11-18 0:0024<NA><NA><NA><NA><NA><NA>1
3An Agenda for Economic Reform in KoreaAn Agenda for Economic Reform in Korea<NA><NA>A72<NA>A99|2A99|A0C0E035350190002000-12-3166940한국개발연구원Korea Development Institute22002-11-19 0:00161<NA><NA><NA><NA><NA><NA>1
4일본경제의 10년 불황에서 배워야 할 교훈Lessons from the Japanese Lost Decade<NA><NA>A72<NA>A07|1A07|F5128510071920002002-06-3065980한국개발연구원Korea Development Institute22002-07-15 0:0022<NA><NA><NA><NA><NA><NA>1
5Restructuring the Korean Financial Market in a Global EconomyRestructuring the Korean Financial Market in a Global Economy<NA><NA>A72<NA>B06|H02|A07|2B06|H02|A07|A7D41691371218120002002-01-3165970한국개발연구원Korea Development Institute22002-07-09 0:009KDI-EWC<NA><NA><NA><NA><NA>1
6상호주 규제의 검토A Study of Regulating the Cross-shareholdings of the Korean Chaebols상호주 규제의 검토<NA>A62<NA>B00|C04|1B00|C04|A9E83325430001999-12-3165010한국개발연구원Korea Development Institute<NA>2002-04-08 0:0017연구자료<NA>99-30<NA><NA><NA>1
7한국, 필리핀, 태국 외환위기에서의 이자율과 환율Interest Rates and Exchange Rates in the Korean, Phillipine and Thai Exchange Rate Crises<NA><NA>A32<NA>A04|H02|1A04|H02|A5D312553910220002001-12-2262800한국개발연구원Korea Development Institute22001-12-22 0:007정책연구시리즈Policy StudyApr-01Apr-012001-12-22<NA>1
8구조적 실업률의 추정 및 정책과제<NA><NA><NA>A62<NA>E01|E99|1E01|E99|C649243130002001-12-3164220한국개발연구원Korea Development Institute22002-04-27 0:001연구자료<NA>Feb-01<NA><NA><NA>1
9Development of Economic Statistics in KoreaDevelopment of Economic Statistics in Korea<NA><NA>A82<NA>P99|2P99|J0J5252614230002001-12-3164240Korea Development InstituteKorea Development Institute22002-02-27 0:0025Working PaperWorking PaperAug-01Aug-012001-12-31<NA>1
서명영문서명한글서명캘린더보고서종류서비스코드제이엘코드주제코드1언어주제코드2주제코드3카운트페이지다운로드가격발간일발간번호입고발행처발행처영문보고서타입등록일입고수량시리즈시리즈영문시리즈번호시리즈번호영문제출일제출처보기
2044소득이동성의 추이 및 정책 시사점Income Mobility in Korea and Policy Implications<NA>nA32<NA>I00|I04|J99|1<NA><NA>0103020002020-12-31170520한국개발연구원Korea Development Institute22021-04-23 13:51210정책연구시리즈Policy StudySep-20Sep-20<NA><NA>1
2045재생에너지 발전시설에 대한 지역 수용성 결정요인 연구: 외부효과를 중심으로A Study on Local Acceptance of Renewable Energy Installations: Focusing on Externalities<NA>nA22<NA>G07|M04|L99|1<NA><NA>0180045002020-12-31169620한국개발연구원Korea Development Institute22021-03-17 9:28210연구보고서Research MonographApr-20Apr-20<NA><NA>1
2046투자와 경기변동: 기업의 투자의사결정 모형을 중심으로Investment and Business Cycles: focusing on Investment Dispersion<NA>nA32<NA>A03|A09|B00|1<NA><NA>056020002020-12-31171280한국개발연구원Korea Development Institute22021-06-11 13:48110정책연구시리즈Policy StudyJul-20Jul-20<NA><NA>1
2047북한 수출구조의 질적 변화에 관한 연구: 대중수출비중 증대의 효과를 중심으로Increase in Exports to China and Qualitative Decline in the Export Structure of North Korea<NA>nA32<NA>K00|K99|1<NA><NA>065020002020-12-31170510한국개발연구원Korea Development Institute22021-04-23 11:26110정책연구시리즈Policy StudyOct-20Oct-20<NA><NA>1
2048The Economic Reform of North Korea in the Kim Jong Un Era: Status & EvaluationThe Economic Reform of North Korea in the Kim Jong Un Era: Status & Evaluation<NA>nA82<NA>K00|K99|2<NA><NA>0240<NA>2021-06-10171160한국개발연구원Korea Development Institute22021-06-03 15:2910Working PaperWorking PaperJune, 2021June, 2021<NA><NA>1
2049자영업에 대한 종합적 분석과 정책제언Study on Self-Employment and Policy Suggestions<NA>nA22<NA>E01|G06|I04|1<NA><NA>0248061002020-12-31171400한국개발연구원Korea Development Institute22021-06-29 10:1510연구보고서Research MonographJun-20Jun-20<NA><NA>1
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