Overview

Dataset statistics

Number of variables14
Number of observations7717
Missing cells14877
Missing cells (%)13.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory866.8 KiB
Average record size in memory115.0 B

Variable types

Numeric3
Text3
Categorical3
DateTime2
Boolean3

Dataset

Description한국저작권보호원이 수행하는 온라인 불법복제물 모니터링 관련 심의시스템 내 업무관리 정보 및 저작물 세부정보, 중점관리대상정보 여부를 제공함
Author(재)한국저작권보호원
URLhttps://www.data.go.kr/data/15092283/fileData.do

Alerts

중점저작물여부 is highly overall correlated with 중점보호시작일 and 1 other fieldsHigh correlation
중점보호종료일 is highly overall correlated with 저작물가격 and 3 other fieldsHigh correlation
중점보호시작일 is highly overall correlated with 저작물가격 and 2 other fieldsHigh correlation
저작물가격 is highly overall correlated with 보호요청번호 and 2 other fieldsHigh correlation
보호요청번호 is highly overall correlated with 저작물가격 and 3 other fieldsHigh correlation
국내외_구분코드 is highly overall correlated with 보호요청번호High correlation
삭제여부 is highly overall correlated with 보호요청번호High correlation
보호요청여부 is highly overall correlated with 보호요청번호 and 1 other fieldsHigh correlation
중점저작물여부 is highly imbalanced (96.5%)Imbalance
중점보호시작일 is highly imbalanced (98.3%)Imbalance
중점보호종료일 is highly imbalanced (98.2%)Imbalance
보호요청여부 is highly imbalanced (91.2%)Imbalance
저작물명_영문 has 5242 (67.9%) missing valuesMissing
수정일시 has 2004 (26.0%) missing valuesMissing
보호요청번호 has 7631 (98.9%) missing valuesMissing
저작물가격 is highly skewed (γ1 = 28.57237942)Skewed
저작물아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:06:11.344849
Analysis finished2023-12-11 23:06:14.081921
Duration2.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

저작물아이디
Real number (ℝ)

UNIQUE 

Distinct7717
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33750.404
Minimum223
Maximum64695
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2023-12-12T08:06:14.168659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum223
5-th percentile8924.8
Q131288
median37404
Q342093
95-th percentile46429.2
Maximum64695
Range64472
Interquartile range (IQR)10805

Descriptive statistics

Standard deviation12311.797
Coefficient of variation (CV)0.36478962
Kurtosis0.21453885
Mean33750.404
Median Absolute Deviation (MAD)5342
Skewness-0.93066064
Sum2.6045187 × 108
Variance1.5158035 × 108
MonotonicityNot monotonic
2023-12-12T08:06:14.328186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24212 1
 
< 0.1%
47003 1
 
< 0.1%
36710 1
 
< 0.1%
36752 1
 
< 0.1%
36711 1
 
< 0.1%
36753 1
 
< 0.1%
36712 1
 
< 0.1%
36754 1
 
< 0.1%
36713 1
 
< 0.1%
36756 1
 
< 0.1%
Other values (7707) 7707
99.9%
ValueCountFrequency (%)
223 1
< 0.1%
386 1
< 0.1%
398 1
< 0.1%
404 1
< 0.1%
412 1
< 0.1%
418 1
< 0.1%
426 1
< 0.1%
433 1
< 0.1%
440 1
< 0.1%
447 1
< 0.1%
ValueCountFrequency (%)
64695 1
< 0.1%
64694 1
< 0.1%
64693 1
< 0.1%
64692 1
< 0.1%
64691 1
< 0.1%
64690 1
< 0.1%
64689 1
< 0.1%
64688 1
< 0.1%
64687 1
< 0.1%
64686 1
< 0.1%

저작물분류아이디
Text

Distinct55
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
2023-12-12T08:06:14.522750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.998445
Min length3

Characters and Unicode

Total characters69441
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st rowM01A05A01
2nd rowP01A01A01
3rd rowM01A02A01
4th rowP01A01A01
5th rowP01A01A01
ValueCountFrequency (%)
p01a12a02 1747
22.6%
p01a01a01 1110
14.4%
m01a02a01 857
11.1%
m01a05a01 523
 
6.8%
p01a06a01 446
 
5.8%
p01a04a01 444
 
5.8%
p01a13a02 385
 
5.0%
p01a05a18 299
 
3.9%
p01a12a01 269
 
3.5%
p01a13a04 250
 
3.2%
Other values (45) 1387
18.0%
2023-12-12T08:06:14.818137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19515
28.1%
1 16299
23.5%
A 15430
22.2%
P 6258
 
9.0%
2 5477
 
7.9%
5 1500
 
2.2%
M 1459
 
2.1%
3 1395
 
2.0%
4 846
 
1.2%
6 656
 
0.9%
Other values (3) 606
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46294
66.7%
Uppercase Letter 23147
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19515
42.2%
1 16299
35.2%
2 5477
 
11.8%
5 1500
 
3.2%
3 1395
 
3.0%
4 846
 
1.8%
6 656
 
1.4%
8 326
 
0.7%
7 156
 
0.3%
9 124
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 15430
66.7%
P 6258
27.0%
M 1459
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 46294
66.7%
Latin 23147
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19515
42.2%
1 16299
35.2%
2 5477
 
11.8%
5 1500
 
3.2%
3 1395
 
3.0%
4 846
 
1.8%
6 656
 
1.4%
8 326
 
0.7%
7 156
 
0.3%
9 124
 
0.3%
Latin
ValueCountFrequency (%)
A 15430
66.7%
P 6258
27.0%
M 1459
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19515
28.1%
1 16299
23.5%
A 15430
22.2%
P 6258
 
9.0%
2 5477
 
7.9%
5 1500
 
2.2%
M 1459
 
2.1%
3 1395
 
2.0%
4 846
 
1.2%
6 656
 
0.9%
Other values (3) 606
 
0.9%

저작물명_한글
Text

Distinct7689
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
2023-12-12T08:06:15.172406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length55
Mean length20.61695
Min length1

Characters and Unicode

Total characters159101
Distinct characters1403
Distinct categories17 ?
Distinct scripts8 ?
Distinct blocks14 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7663 ?
Unique (%)99.3%

Sample

1st rowAppMonster Pro (AD)
2nd row나비 (가수: 박기영)
3rd row마제스티 - 판타지 왕국의 전설 (AD)
4th row머릿속에서니가막걸어다녀 (가수: 조은)
5th row이방인(FEAT. NU SOUL) (가수: JOOSUC)
ValueCountFrequency (%)
ad 893
 
3.2%
596
 
2.2%
가수 581
 
2.1%
the 460
 
1.7%
2012 443
 
1.6%
2011 332
 
1.2%
2013 319
 
1.2%
2010 233
 
0.8%
of 233
 
0.8%
2 223
 
0.8%
Other values (13069) 23257
84.4%
2023-12-12T08:06:15.656086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19966
 
12.5%
( 8585
 
5.4%
) 8572
 
5.4%
e 5043
 
3.2%
0 4255
 
2.7%
2 3645
 
2.3%
o 3419
 
2.1%
a 3402
 
2.1%
r 3251
 
2.0%
i 2992
 
1.9%
Other values (1393) 95971
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48084
30.2%
Lowercase Letter 37702
23.7%
Space Separator 19968
12.6%
Uppercase Letter 17864
 
11.2%
Decimal Number 14227
 
8.9%
Open Punctuation 8597
 
5.4%
Close Punctuation 8584
 
5.4%
Other Punctuation 3581
 
2.3%
Dash Punctuation 372
 
0.2%
Math Symbol 68
 
< 0.1%
Other values (7) 54
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 1955
 
4.1%
이 1541
 
3.2%
영 1536
 
3.2%
가 1531
 
3.2%
수 1392
 
2.9%
판 1387
 
2.9%
출 1354
 
2.8%
스 1185
 
2.5%
사 870
 
1.8%
의 730
 
1.5%
Other values (1260) 34603
72.0%
Lowercase Letter
ValueCountFrequency (%)
e 5043
13.4%
o 3419
 
9.1%
a 3402
 
9.0%
r 3251
 
8.6%
i 2992
 
7.9%
n 2676
 
7.1%
t 2438
 
6.5%
s 2084
 
5.5%
l 1946
 
5.2%
h 1309
 
3.5%
Other values (30) 9142
24.2%
Uppercase Letter
ValueCountFrequency (%)
A 2009
 
11.2%
D 1859
 
10.4%
S 1383
 
7.7%
T 1258
 
7.0%
E 949
 
5.3%
M 883
 
4.9%
C 826
 
4.6%
R 817
 
4.6%
P 789
 
4.4%
B 788
 
4.4%
Other values (27) 6303
35.3%
Other Punctuation
ValueCountFrequency (%)
: 2798
78.1%
, 273
 
7.6%
. 241
 
6.7%
! 123
 
3.4%
& 65
 
1.8%
/ 28
 
0.8%
; 18
 
0.5%
' 16
 
0.4%
· 3
 
0.1%
% 3
 
0.1%
Other values (7) 13
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 4255
29.9%
2 3645
25.6%
1 2830
19.9%
9 1137
 
8.0%
3 724
 
5.1%
7 383
 
2.7%
8 355
 
2.5%
4 320
 
2.2%
5 298
 
2.1%
6 280
 
2.0%
Other Symbol
ValueCountFrequency (%)
™ 18
52.9%
☆ 6
 
17.6%
★ 5
 
14.7%
♥ 3
 
8.8%
® 1
 
2.9%
● 1
 
2.9%
Math Symbol
ValueCountFrequency (%)
~ 35
51.5%
+ 29
42.6%
× 2
 
2.9%
= 1
 
1.5%
∞ 1
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 8585
99.9%
[ 10
 
0.1%
（ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 8572
99.9%
] 10
 
0.1%
） 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
19966
> 99.9%
　 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 370
99.5%
― 2
 
0.5%
Final Punctuation
ValueCountFrequency (%)
’ 9
81.8%
” 2
 
18.2%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55542
34.9%
Common 55449
34.9%
Hangul 47651
30.0%
Han 180
 
0.1%
Katakana 154
 
0.1%
Hiragana 99
 
0.1%
Cyrillic 25
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 1955
 
4.1%
이 1541
 
3.2%
영 1536
 
3.2%
가 1531
 
3.2%
수 1392
 
2.9%
판 1387
 
2.9%
출 1354
 
2.8%
스 1185
 
2.5%
사 870
 
1.8%
의 730
 
1.5%
Other values (1025) 34170
71.7%
Han
ValueCountFrequency (%)
人 4
 
2.2%
魔 4
 
2.2%
女 4
 
2.2%
愛 3
 
1.7%
京 3
 
1.7%
家 3
 
1.7%
法 3
 
1.7%
一 3
 
1.7%
月 3
 
1.7%
偵 2
 
1.1%
Other values (132) 148
82.2%
Common
ValueCountFrequency (%)
19966
36.0%
( 8585
15.5%
) 8572
15.5%
0 4255
 
7.7%
2 3645
 
6.6%
1 2830
 
5.1%
: 2798
 
5.0%
9 1137
 
2.1%
3 724
 
1.3%
7 383
 
0.7%
Other values (44) 2554
 
4.6%
Latin
ValueCountFrequency (%)
e 5043
 
9.1%
o 3419
 
6.2%
a 3402
 
6.1%
r 3251
 
5.9%
i 2992
 
5.4%
n 2676
 
4.8%
t 2438
 
4.4%
s 2084
 
3.8%
A 2009
 
3.6%
l 1946
 
3.5%
Other values (44) 26282
47.3%
Katakana
ValueCountFrequency (%)
ン 15
 
9.7%
ク 7
 
4.5%
ト 7
 
4.5%
ッ 6
 
3.9%
リ 6
 
3.9%
ル 6
 
3.9%
ロ 5
 
3.2%
マ 5
 
3.2%
ラ 5
 
3.2%
ド 5
 
3.2%
Other values (42) 87
56.5%
Hiragana
ValueCountFrequency (%)
の 14
 
14.1%
な 7
 
7.1%
ま 5
 
5.1%
る 5
 
5.1%
い 5
 
5.1%
ん 4
 
4.0%
か 3
 
3.0%
と 3
 
3.0%
す 3
 
3.0%
う 3
 
3.0%
Other values (31) 47
47.5%
Cyrillic
ValueCountFrequency (%)
о 2
 
8.0%
к 1
 
4.0%
б 1
 
4.0%
р 1
 
4.0%
Я 1
 
4.0%
Т 1
 
4.0%
Н 1
 
4.0%
А 1
 
4.0%
С 1
 
4.0%
Р 1
 
4.0%
Other values (14) 14
56.0%
Greek
ValueCountFrequency (%)
Σ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110920
69.7%
Hangul 47651
30.0%
CJK 178
 
0.1%
Katakana 154
 
0.1%
Hiragana 99
 
0.1%
Cyrillic 25
 
< 0.1%
Letterlike Symbols 18
 
< 0.1%
Punctuation 18
 
< 0.1%
None 18
 
< 0.1%
Misc Symbols 14
 
< 0.1%
Other values (4) 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19966
18.0%
( 8585
 
7.7%
) 8572
 
7.7%
e 5043
 
4.5%
0 4255
 
3.8%
2 3645
 
3.3%
o 3419
 
3.1%
a 3402
 
3.1%
r 3251
 
2.9%
i 2992
 
2.7%
Other values (75) 47790
43.1%
Hangul
ValueCountFrequency (%)
화 1955
 
4.1%
이 1541
 
3.2%
영 1536
 
3.2%
가 1531
 
3.2%
수 1392
 
2.9%
판 1387
 
2.9%
출 1354
 
2.8%
스 1185
 
2.5%
사 870
 
1.8%
의 730
 
1.5%
Other values (1025) 34170
71.7%
Letterlike Symbols
ValueCountFrequency (%)
™ 18
100.0%
Katakana
ValueCountFrequency (%)
ン 15
 
9.7%
ク 7
 
4.5%
ト 7
 
4.5%
ッ 6
 
3.9%
リ 6
 
3.9%
ル 6
 
3.9%
ロ 5
 
3.2%
マ 5
 
3.2%
ラ 5
 
3.2%
ド 5
 
3.2%
Other values (42) 87
56.5%
Hiragana
ValueCountFrequency (%)
の 14
 
14.1%
な 7
 
7.1%
ま 5
 
5.1%
る 5
 
5.1%
い 5
 
5.1%
ん 4
 
4.0%
か 3
 
3.0%
と 3
 
3.0%
す 3
 
3.0%
う 3
 
3.0%
Other values (31) 47
47.5%
Punctuation
ValueCountFrequency (%)
’ 9
50.0%
― 2
 
11.1%
… 2
 
11.1%
“ 2
 
11.1%
” 2
 
11.1%
′ 1
 
5.6%
Misc Symbols
ValueCountFrequency (%)
☆ 6
42.9%
★ 5
35.7%
♥ 3
21.4%
CJK
ValueCountFrequency (%)
人 4
 
2.2%
魔 4
 
2.2%
女 4
 
2.2%
愛 3
 
1.7%
京 3
 
1.7%
家 3
 
1.7%
法 3
 
1.7%
一 3
 
1.7%
月 3
 
1.7%
偵 2
 
1.1%
Other values (130) 146
82.0%
None
ValueCountFrequency (%)
· 3
16.7%
、 2
11.1%
： 2
11.1%
　 2
11.1%
× 2
11.1%
） 2
11.1%
（ 2
11.1%
Σ 1
 
5.6%
® 1
 
5.6%
／ 1
 
5.6%
Cyrillic
ValueCountFrequency (%)
о 2
 
8.0%
к 1
 
4.0%
б 1
 
4.0%
р 1
 
4.0%
Я 1
 
4.0%
Т 1
 
4.0%
Н 1
 
4.0%
А 1
 
4.0%
С 1
 
4.0%
Р 1
 
4.0%
Other values (14) 14
56.0%
CJK Compat Ideographs
ValueCountFrequency (%)
龍 1
50.0%
樂 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
50.0%
Ⅱ 1
50.0%
Geometric Shapes
ValueCountFrequency (%)
● 1
100.0%
Math Operators
ValueCountFrequency (%)
∞ 1
100.0%

저작물명_영문
Text

MISSING 

Distinct2432
Distinct (%)98.3%
Missing5242
Missing (%)67.9%
Memory size60.4 KiB
2023-12-12T08:06:15.960611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length52
Mean length22.511515
Min length1

Characters and Unicode

Total characters55716
Distinct characters524
Distinct categories13 ?
Distinct scripts8 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2404 ?
Unique (%)97.1%

Sample

1st rowBreach
2nd rowDrunk Man (AD)
3rd rowChu Chu Rocket
4th rowMr. Driller 2 (2005)
5th rowFinal Fight One (2001)
ValueCountFrequency (%)
ad 751
 
8.0%
the 353
 
3.7%
of 199
 
2.1%
2012 197
 
2.1%
2013 167
 
1.8%
137
 
1.5%
pro 137
 
1.5%
2011 130
 
1.4%
2010 103
 
1.1%
2 90
 
1.0%
Other values (3655) 7168
76.0%
2023-12-12T08:06:16.640019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6979
 
12.5%
e 3879
 
7.0%
a 2643
 
4.7%
o 2542
 
4.6%
r 2514
 
4.5%
i 2190
 
3.9%
n 2110
 
3.8%
t 1896
 
3.4%
( 1846
 
3.3%
) 1842
 
3.3%
Other values (514) 27275
49.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28948
52.0%
Uppercase Letter 9603
 
17.2%
Space Separator 6980
 
12.5%
Decimal Number 4952
 
8.9%
Open Punctuation 1853
 
3.3%
Close Punctuation 1849
 
3.3%
Other Letter 848
 
1.5%
Other Punctuation 508
 
0.9%
Dash Punctuation 128
 
0.2%
Other Symbol 23
 
< 0.1%
Other values (3) 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
2.2%
스 16
 
1.9%
の 15
 
1.8%
시 11
 
1.3%
ン 11
 
1.3%
ル 11
 
1.3%
ド 9
 
1.1%
リ 8
 
0.9%
즌 8
 
0.9%
리 8
 
0.9%
Other values (413) 732
86.3%
Lowercase Letter
ValueCountFrequency (%)
e 3879
13.4%
a 2643
 
9.1%
o 2542
 
8.8%
r 2514
 
8.7%
i 2190
 
7.6%
n 2110
 
7.3%
t 1896
 
6.5%
s 1543
 
5.3%
l 1484
 
5.1%
h 1010
 
3.5%
Other values (20) 7137
24.7%
Uppercase Letter
ValueCountFrequency (%)
D 1333
13.9%
A 1274
13.3%
S 711
 
7.4%
T 706
 
7.4%
P 543
 
5.7%
M 482
 
5.0%
C 465
 
4.8%
R 408
 
4.2%
B 386
 
4.0%
L 347
 
3.6%
Other values (18) 2948
30.7%
Other Punctuation
ValueCountFrequency (%)
: 273
53.7%
. 78
 
15.4%
, 49
 
9.6%
! 47
 
9.3%
& 35
 
6.9%
/ 15
 
3.0%
！ 3
 
0.6%
* 3
 
0.6%
% 1
 
0.2%
、 1
 
0.2%
Other values (3) 3
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 1424
28.8%
2 1300
26.3%
1 1058
21.4%
9 385
 
7.8%
3 311
 
6.3%
7 114
 
2.3%
8 113
 
2.3%
6 105
 
2.1%
4 74
 
1.5%
5 68
 
1.4%
Other Symbol
ValueCountFrequency (%)
™ 17
73.9%
♥ 2
 
8.7%
♪ 1
 
4.3%
® 1
 
4.3%
★ 1
 
4.3%
ⓒ 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 1846
99.6%
[ 5
 
0.3%
（ 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1842
99.6%
] 5
 
0.3%
） 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 18
85.7%
~ 2
 
9.5%
∞ 1
 
4.8%
Space Separator
ValueCountFrequency (%)
6979
> 99.9%
　 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38545
69.2%
Common 16317
29.3%
Hangul 443
 
0.8%
Katakana 188
 
0.3%
Han 157
 
0.3%
Hiragana 60
 
0.1%
Cyrillic 5
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 19
 
4.3%
스 16
 
3.6%
시 11
 
2.5%
즌 8
 
1.8%
리 8
 
1.8%
어 8
 
1.8%
다 7
 
1.6%
사 7
 
1.6%
라 7
 
1.6%
판 7
 
1.6%
Other values (192) 345
77.9%
Han
ValueCountFrequency (%)
魔 3
 
1.9%
男 3
 
1.9%
語 3
 
1.9%
金 3
 
1.9%
王 3
 
1.9%
篇 3
 
1.9%
物 3
 
1.9%
西 2
 
1.3%
遊 2
 
1.3%
手 2
 
1.3%
Other values (121) 130
82.8%
Katakana
ValueCountFrequency (%)
ン 11
 
5.9%
ル 11
 
5.9%
ド 9
 
4.8%
リ 8
 
4.3%
ク 8
 
4.3%
イ 8
 
4.3%
ト 8
 
4.3%
ッ 7
 
3.7%
ス 7
 
3.7%
ラ 6
 
3.2%
Other values (49) 105
55.9%
Latin
ValueCountFrequency (%)
e 3879
 
10.1%
a 2643
 
6.9%
o 2542
 
6.6%
r 2514
 
6.5%
i 2190
 
5.7%
n 2110
 
5.5%
t 1896
 
4.9%
s 1543
 
4.0%
l 1484
 
3.9%
D 1333
 
3.5%
Other values (42) 16411
42.6%
Common
ValueCountFrequency (%)
6979
42.8%
( 1846
 
11.3%
) 1842
 
11.3%
0 1424
 
8.7%
2 1300
 
8.0%
1 1058
 
6.5%
9 385
 
2.4%
3 311
 
1.9%
: 273
 
1.7%
- 128
 
0.8%
Other values (33) 771
 
4.7%
Hiragana
ValueCountFrequency (%)
の 15
25.0%
り 3
 
5.0%
と 3
 
5.0%
こ 3
 
5.0%
が 2
 
3.3%
る 2
 
3.3%
た 2
 
3.3%
よ 2
 
3.3%
い 2
 
3.3%
ん 2
 
3.3%
Other values (21) 24
40.0%
Cyrillic
ValueCountFrequency (%)
г 1
20.0%
е 1
20.0%
б 1
20.0%
о 1
20.0%
П 1
20.0%
Greek
ValueCountFrequency (%)
Σ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54827
98.4%
Hangul 442
 
0.8%
Katakana 188
 
0.3%
CJK 157
 
0.3%
Hiragana 60
 
0.1%
Letterlike Symbols 17
 
< 0.1%
None 11
 
< 0.1%
Cyrillic 5
 
< 0.1%
Misc Symbols 4
 
< 0.1%
Punctuation 2
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6979
 
12.7%
e 3879
 
7.1%
a 2643
 
4.8%
o 2542
 
4.6%
r 2514
 
4.6%
i 2190
 
4.0%
n 2110
 
3.8%
t 1896
 
3.5%
( 1846
 
3.4%
) 1842
 
3.4%
Other values (71) 26386
48.1%
Hangul
ValueCountFrequency (%)
이 19
 
4.3%
스 16
 
3.6%
시 11
 
2.5%
즌 8
 
1.8%
리 8
 
1.8%
어 8
 
1.8%
다 7
 
1.6%
사 7
 
1.6%
라 7
 
1.6%
판 7
 
1.6%
Other values (191) 344
77.8%
Letterlike Symbols
ValueCountFrequency (%)
™ 17
100.0%
Hiragana
ValueCountFrequency (%)
の 15
25.0%
り 3
 
5.0%
と 3
 
5.0%
こ 3
 
5.0%
が 2
 
3.3%
る 2
 
3.3%
た 2
 
3.3%
よ 2
 
3.3%
い 2
 
3.3%
ん 2
 
3.3%
Other values (21) 24
40.0%
Katakana
ValueCountFrequency (%)
ン 11
 
5.9%
ル 11
 
5.9%
ド 9
 
4.8%
リ 8
 
4.3%
ク 8
 
4.3%
イ 8
 
4.3%
ト 8
 
4.3%
ッ 7
 
3.7%
ス 7
 
3.7%
ラ 6
 
3.2%
Other values (49) 105
55.9%
CJK
ValueCountFrequency (%)
魔 3
 
1.9%
男 3
 
1.9%
語 3
 
1.9%
金 3
 
1.9%
王 3
 
1.9%
篇 3
 
1.9%
物 3
 
1.9%
西 2
 
1.3%
遊 2
 
1.3%
手 2
 
1.3%
Other values (121) 130
82.8%
None
ValueCountFrequency (%)
！ 3
27.3%
） 2
18.2%
（ 2
18.2%
Σ 1
 
9.1%
、 1
 
9.1%
® 1
 
9.1%
　 1
 
9.1%
Misc Symbols
ValueCountFrequency (%)
♥ 2
50.0%
♪ 1
25.0%
★ 1
25.0%
Math Operators
ValueCountFrequency (%)
∞ 1
100.0%
Cyrillic
ValueCountFrequency (%)
г 1
20.0%
е 1
20.0%
б 1
20.0%
о 1
20.0%
П 1
20.0%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
100.0%
Punctuation
ValueCountFrequency (%)
′ 1
50.0%
’ 1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓒ 1
100.0%

저작물가격
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct561
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77806.264
Minimum0
Maximum43000000
Zeros17
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2023-12-12T08:06:16.767583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile133
Q1748
median2897
Q35248
95-th percentile52000
Maximum43000000
Range43000000
Interquartile range (IQR)4500

Descriptive statistics

Standard deviation1019840.7
Coefficient of variation (CV)13.107437
Kurtosis990.28549
Mean77806.264
Median Absolute Deviation (MAD)2149
Skewness28.572379
Sum6.0043094 × 108
Variance1.040075 × 1012
MonotonicityNot monotonic
2023-12-12T08:06:16.875520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2897 2386
30.9%
133 1220
15.8%
26410 859
 
11.1%
748 702
 
9.1%
2414 639
 
8.3%
5248 450
 
5.8%
11000 58
 
0.8%
1100 56
 
0.7%
22000 47
 
0.6%
2300 37
 
0.5%
Other values (551) 1263
16.4%
ValueCountFrequency (%)
0 17
 
0.2%
133 1220
15.8%
600 1
 
< 0.1%
748 702
9.1%
999 1
 
< 0.1%
1000 20
 
0.3%
1064 1
 
< 0.1%
1071 1
 
< 0.1%
1100 56
 
0.7%
1106 1
 
< 0.1%
ValueCountFrequency (%)
43000000 1
< 0.1%
39600000 1
< 0.1%
33300000 1
< 0.1%
29614800 1
< 0.1%
22700000 1
< 0.1%
16195990 1
< 0.1%
13409000 1
< 0.1%
13200000 1
< 0.1%
11180000 1
< 0.1%
10793990 1
< 0.1%

국내외_구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
CP080020
5373 
CP080010
2344 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCP080020
2nd rowCP080010
3rd rowCP080020
4th rowCP080010
5th rowCP080010

Common Values

ValueCountFrequency (%)
CP080020 5373
69.6%
CP080010 2344
30.4%

Length

2023-12-12T08:06:16.970413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:17.068781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
cp080020 5373
69.6%
cp080010 2344
30.4%

등록일시
Date

Distinct376
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
Minimum2012-01-01 00:00:00
Maximum2015-09-21 00:00:00
2023-12-12T08:06:17.166775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:17.303668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

MISSING 

Distinct597
Distinct (%)10.4%
Missing2004
Missing (%)26.0%
Memory size60.4 KiB
Minimum2012-01-09 00:00:00
Maximum2021-08-30 00:00:00
2023-12-12T08:06:17.450259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:17.571086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

삭제여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
False
6138 
True
1579 
ValueCountFrequency (%)
False 6138
79.5%
True 1579
 
20.5%
2023-12-12T08:06:17.687063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

중점저작물여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
False
7689 
True
 
28
ValueCountFrequency (%)
False 7689
99.6%
True 28
 
0.4%
2023-12-12T08:06:17.780936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

중점보호시작일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
<NA>
7689 
2014-03-01
 
18
2014-04-01
 
5
2014-03-15
 
3
2014-04-16
 
2

Length

Max length10
Median length4
Mean length4.0217701
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7689
99.6%
2014-03-01 18
 
0.2%
2014-04-01 5
 
0.1%
2014-03-15 3
 
< 0.1%
2014-04-16 2
 
< 0.1%

Length

2023-12-12T08:06:17.883166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:17.980329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7689
99.6%
2014-03-01 18
 
0.2%
2014-04-01 5
 
0.1%
2014-03-15 3
 
< 0.1%
2014-04-16 2
 
< 0.1%

중점보호종료일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.4 KiB
<NA>
7689 
2014-03-14
 
10
2014-04-30
 
9
2014-03-31
 
7
2014-04-15
 
2

Length

Max length10
Median length4
Mean length4.0217701
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7689
99.6%
2014-03-14 10
 
0.1%
2014-04-30 9
 
0.1%
2014-03-31 7
 
0.1%
2014-04-15 2
 
< 0.1%

Length

2023-12-12T08:06:18.103377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:06:18.250060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7689
99.6%
2014-03-14 10
 
0.1%
2014-04-30 9
 
0.1%
2014-03-31 7
 
0.1%
2014-04-15 2
 
< 0.1%

보호요청여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
False
7631 
True
 
86
ValueCountFrequency (%)
False 7631
98.9%
True 86
 
1.1%
2023-12-12T08:06:18.344349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

보호요청번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)44.2%
Missing7631
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean614.96512
Minimum8
Maximum1610
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.0 KiB
2023-12-12T08:06:18.445237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile123
Q1152.25
median296
Q31247
95-th percentile1452.75
Maximum1610
Range1602
Interquartile range (IQR)1094.75

Descriptive statistics

Standard deviation532.01182
Coefficient of variation (CV)0.86510894
Kurtosis-1.4361301
Mean614.96512
Median Absolute Deviation (MAD)173
Skewness0.59722655
Sum52887
Variance283036.58
MonotonicityNot monotonic
2023-12-12T08:06:18.615884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
296 14
 
0.2%
123 14
 
0.2%
299 9
 
0.1%
124 7
 
0.1%
237 5
 
0.1%
295 4
 
0.1%
1034 2
 
< 0.1%
1269 1
 
< 0.1%
1298 1
 
< 0.1%
1493 1
 
< 0.1%
Other values (28) 28
 
0.4%
(Missing) 7631
98.9%
ValueCountFrequency (%)
8 1
 
< 0.1%
123 14
0.2%
124 7
0.1%
237 5
 
0.1%
295 4
 
0.1%
296 14
0.2%
299 9
0.1%
1009 1
 
< 0.1%
1026 1
 
< 0.1%
1034 2
 
< 0.1%
ValueCountFrequency (%)
1610 1
< 0.1%
1609 1
< 0.1%
1601 1
< 0.1%
1591 1
< 0.1%
1493 1
< 0.1%
1332 1
< 0.1%
1331 1
< 0.1%
1324 1
< 0.1%
1323 1
< 0.1%
1320 1
< 0.1%

Interactions

2023-12-12T08:06:13.421071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:12.934119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.163961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.502471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.016443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.259735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.582731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.088856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:06:13.341106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:06:18.751601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저작물아이디저작물분류아이디저작물가격국내외_구분코드삭제여부중점저작물여부중점보호시작일중점보호종료일보호요청여부보호요청번호
저작물아이디1.0000.8560.0940.4510.3800.1000.0000.0000.0440.401
저작물분류아이디0.8561.0000.6930.9670.9860.2320.0000.5860.2300.825
저작물가격0.0940.6931.0000.0460.0240.000NaNNaN0.000NaN
국내외_구분코드0.4510.9670.0461.0000.3590.0000.4740.0000.1430.991
삭제여부0.3800.9860.0240.3591.0000.0000.0000.0000.0650.920
중점저작물여부0.1000.2320.0000.0000.0001.000NaNNaN0.0000.000
중점보호시작일0.0000.000NaN0.4740.000NaN1.0000.8570.397NaN
중점보호종료일0.0000.586NaN0.0000.000NaN0.8571.0000.850NaN
보호요청여부0.0440.2300.0000.1430.0650.0000.3970.8501.000NaN
보호요청번호0.4010.825NaN0.9910.9200.000NaNNaNNaN1.000
2023-12-12T08:06:18.921686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
삭제여부중점저작물여부중점보호종료일중점보호시작일보호요청여부국내외_구분코드
삭제여부1.0000.0000.0000.0000.0420.234
중점저작물여부0.0001.0001.0001.0000.0000.000
중점보호종료일0.0001.0001.0000.5120.6200.000
중점보호시작일0.0001.0000.5121.0000.2480.302
보호요청여부0.0420.0000.6200.2481.0000.092
국내외_구분코드0.2340.0000.0000.3020.0921.000
2023-12-12T08:06:19.073268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저작물아이디저작물가격보호요청번호국내외_구분코드삭제여부중점저작물여부중점보호시작일중점보호종료일보호요청여부
저작물아이디1.0000.1770.1170.4510.3800.0990.0000.0000.044
저작물가격0.1771.0000.7630.0350.0180.0001.0001.0000.000
보호요청번호0.1170.7631.0000.8930.7300.000NaNNaN1.000
국내외_구분코드0.4510.0350.8931.0000.2340.0000.3020.0000.092
삭제여부0.3800.0180.7300.2341.0000.0000.0000.0000.042
중점저작물여부0.0990.0000.0000.0000.0001.0001.0001.0000.000
중점보호시작일0.0001.000NaN0.3020.0001.0001.0000.5120.248
중점보호종료일0.0001.000NaN0.0000.0001.0000.5121.0000.620
보호요청여부0.0440.0001.0000.0920.0420.0000.2480.6201.000

Missing values

2023-12-12T08:06:13.715121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:06:13.884425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T08:06:14.014473image/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

저작물아이디저작물분류아이디저작물명_한글저작물명_영문저작물가격국내외_구분코드등록일시수정일시삭제여부중점저작물여부중점보호시작일중점보호종료일보호요청여부보호요청번호
024212M01A05A01AppMonster Pro (AD)<NA>3800CP0800202012-01-012019-12-17YN<NA><NA>N<NA>
134456P01A01A01나비 (가수: 박기영)<NA>133CP0800102012-05-10<NA>NN<NA><NA>N<NA>
234405M01A02A01마제스티 - 판타지 왕국의 전설 (AD)<NA>26410CP0800202012-05-082019-12-17YN<NA><NA>N<NA>
334404P01A01A01머릿속에서니가막걸어다녀 (가수: 조은)<NA>133CP0800102012-05-08<NA>NN<NA><NA>N<NA>
434403P01A01A01이방인(FEAT. NU SOUL) (가수: JOOSUC)<NA>133CP0800102012-05-082012-05-08NN<NA><NA>N<NA>
534399P01A12A02브리치 Breach (2007)Breach2897CP0800202012-05-08<NA>NN<NA><NA>N<NA>
634396P01A01A01눈물만 (가수: 인피니트)<NA>133CP0800102012-05-08<NA>NN<NA><NA>N<NA>
734390P01A13A02더 리버 The River (2012)<NA>748CP0800202012-05-082012-05-08NN<NA><NA>N<NA>
834385M01A02A01Drunk Man (AD)Drunk Man (AD)26410CP0800202012-05-082019-12-17YN<NA><NA>N<NA>
97352P01A04A01아독(출판:D&C MEDIA(디앤씨미디어) ;파피루스)<NA>5248CP0800102012-01-01<NA>NN<NA><NA>N<NA>
저작물아이디저작물분류아이디저작물명_한글저작물명_영문저작물가격국내외_구분코드등록일시수정일시삭제여부중점저작물여부중점보호시작일중점보호종료일보호요청여부보호요청번호
770741130P01A01A01눈금자(FEAT.테이커스)(가수:소지섭)<NA>133CP0800102013-01-29<NA>NN<NA><NA>N<NA>
770841129P01A01A01범이,낭이(작곡,작사,편곡)<NA>133CP0800102013-01-292018-10-17YN<NA><NA>N<NA>
770941128P01A01A01눈물(Feat.유진)(가수:리쌍)<NA>133CP0800102013-01-292013-01-29NN<NA><NA>N<NA>
771041127P01A01A01맘이너무아프다(가수:신재)<NA>133CP0800102013-01-292013-01-29NN<NA><NA>N<NA>
771141122P01A05A18The Binding of Isaac (2011)<NA>5400CP0800202013-01-282013-01-28NN<NA><NA>N<NA>
771241073P01A12A02곤히 주무세요 Mientras duermes (2011)<NA>2897CP0800202013-01-242013-01-25NN<NA><NA>N<NA>
771341062P01A12A02(영화)트릭 - 극장판 2 (2006)<NA>2897CP0800202013-01-242019-02-15NN<NA><NA>N<NA>
771441061P01A12A02소름 Torihada The Movie (2012)<NA>2897CP0800202013-01-242013-01-24NN<NA><NA>N<NA>
771541057P01A12A02라면 걸 (2008)The Ramen Girl (2008)2897CP0800202013-01-24<NA>NN<NA><NA>N<NA>
771639719P01A06A03(만화)범죄 교섭인 (출판 : 대원씨아이)<NA>2414CP0800202012-11-082020-03-11NN<NA><NA>N<NA>