Overview

Dataset statistics

Number of variables8
Number of observations25
Missing cells24
Missing cells (%)12.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory70.3 B

Variable types

Text4
Categorical2
DateTime1
Numeric1

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/70484c7b-dac9-43a1-907d-c24d3477976d

Alerts

REVIV_LIST_CHNNL_ID has constant value ""Constant
REVIV_LIST_COLCT_DE has constant value ""Constant
REVIV_LIST_DC has constant value ""Constant
REVIV_LIST_DC has 24 (96.0%) missing valuesMissing
REVIV_LIST_ID has unique valuesUnique
VIDO_LIST has 3 (12.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:14:38.582844
Analysis finished2023-12-10 14:14:39.690637
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

REVIV_LIST_ID
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:14:39.960757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length34
Min length34

Characters and Unicode

Total characters850
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowPLtqYizcPqxZSFT21R3q37QoQoevX7dFdb
2nd rowPLtqYizcPqxZTD1mmSarC1-hjAvuDoA5vi
3rd rowPLtqYizcPqxZQSoZsxZ7h008rYhqW22Pc8
4th rowPLtqYizcPqxZTqzWdmpS6V-cV3LbCgdoQs
5th rowPLtqYizcPqxZTJG1a2y30b4sSQg8Gz1Zu2
ValueCountFrequency (%)
pltqyizcpqxzsft21r3q37qoqoevx7dfdb 1
 
4.0%
pltqyizcpqxzsx_o3aews9_u2j8uca6no 1
 
4.0%
pltqyizcpqxzrt9aativlyuc5jtdnl5zqd 1
 
4.0%
pltqyizcpqxzsdrxsacyn2xcoawp6eqe9i 1
 
4.0%
pltqyizcpqxztmofp8njptp7rfla11yhrh 1
 
4.0%
pltqyizcpqxzq1eocyvignypqujsmm8atz 1
 
4.0%
pltqyizcpqxzqqe8400zbjggqyvkwrwq3d 1
 
4.0%
pltqyizcpqxzsjr4n-mi9veg76fjidsq4r 1
 
4.0%
pltqyizcpqxzs6s5vlkbumg7osry2wov3c 1
 
4.0%
pltqyizcpqxzr1wmutvkqxq3o11am2yipu 1
 
4.0%
Other values (15) 15
60.0%
2023-12-10T23:14:40.662930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
q 60
 
7.1%
P 56
 
6.6%
c 37
 
4.4%
i 34
 
4.0%
Y 33
 
3.9%
z 32
 
3.8%
x 32
 
3.8%
t 29
 
3.4%
Z 29
 
3.4%
L 29
 
3.4%
Other values (54) 479
56.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 395
46.5%
Uppercase Letter 342
40.2%
Decimal Number 103
 
12.1%
Connector Punctuation 5
 
0.6%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
q 60
15.2%
c 37
 
9.4%
i 34
 
8.6%
z 32
 
8.1%
x 32
 
8.1%
t 29
 
7.3%
e 15
 
3.8%
a 14
 
3.5%
o 14
 
3.5%
s 13
 
3.3%
Other values (16) 115
29.1%
Uppercase Letter
ValueCountFrequency (%)
P 56
16.4%
Y 33
 
9.6%
Z 29
 
8.5%
L 29
 
8.5%
T 19
 
5.6%
Q 18
 
5.3%
S 18
 
5.3%
V 12
 
3.5%
R 11
 
3.2%
J 11
 
3.2%
Other values (16) 106
31.0%
Decimal Number
ValueCountFrequency (%)
3 16
15.5%
2 13
12.6%
1 12
11.7%
8 12
11.7%
6 11
10.7%
4 8
7.8%
0 8
7.8%
5 8
7.8%
7 8
7.8%
9 7
6.8%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 737
86.7%
Common 113
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
q 60
 
8.1%
P 56
 
7.6%
c 37
 
5.0%
i 34
 
4.6%
Y 33
 
4.5%
z 32
 
4.3%
x 32
 
4.3%
t 29
 
3.9%
Z 29
 
3.9%
L 29
 
3.9%
Other values (42) 366
49.7%
Common
ValueCountFrequency (%)
3 16
14.2%
2 13
11.5%
1 12
10.6%
8 12
10.6%
6 11
9.7%
4 8
7.1%
0 8
7.1%
5 8
7.1%
7 8
7.1%
9 7
6.2%
Other values (2) 10
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
q 60
 
7.1%
P 56
 
6.6%
c 37
 
4.4%
i 34
 
4.0%
Y 33
 
3.9%
z 32
 
3.8%
x 32
 
3.8%
t 29
 
3.4%
Z 29
 
3.4%
L 29
 
3.4%
Other values (54) 479
56.4%

REVIV_LIST_CHNNL_ID
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
UCiBr0bK06imaMbLc8sAEz0A
25 

Length

Max length24
Median length24
Mean length24
Min length24

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUCiBr0bK06imaMbLc8sAEz0A
2nd rowUCiBr0bK06imaMbLc8sAEz0A
3rd rowUCiBr0bK06imaMbLc8sAEz0A
4th rowUCiBr0bK06imaMbLc8sAEz0A
5th rowUCiBr0bK06imaMbLc8sAEz0A

Common Values

ValueCountFrequency (%)
UCiBr0bK06imaMbLc8sAEz0A 25
100.0%

Length

2023-12-10T23:14:40.941448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:41.091598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ucibr0bk06imamblc8saez0a 25
100.0%

REVIV_LIST_COLCT_DE
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2020-09-01
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-09-01
2nd row2020-09-01
3rd row2020-09-01
4th row2020-09-01
5th row2020-09-01

Common Values

ValueCountFrequency (%)
2020-09-01 25
100.0%

Length

2023-12-10T23:14:41.244292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:14:41.381215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-09-01 25
100.0%

REVIV_LIST_UPLOAD_DE
Date

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum2019-12-14 00:00:00
Maximum2020-08-03 00:00:00
2023-12-10T23:14:41.510365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:14:41.711539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

REVIV_LIST_NM
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:14:42.109994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length28
Mean length23.4
Min length5

Characters and Unicode

Total characters585
Distinct characters174
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row슈퍼시니어
2nd row[백파더 확장판] 월요일밤 10시 50분 방송!
3rd row[아무튼 출근] 월요일 밤 9시 30분 방송!
4th row[안싸우면 다행이야] 월요일 밤 9시 30분 방송!
5th row[트로트의 민족]
ValueCountFrequency (%)
방송 7
 
5.3%
hot 6
 
4.5%
밤 6
 
4.5%
9시 5
 
3.8%
월요일 4
 
3.0%
50분 3
 
2.3%
20191213 3
 
2.3%
3
 
2.3%
나 2
 
1.5%
x 2
 
1.5%
Other values (83) 92
69.2%
2023-12-10T23:14:42.813447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
18.5%
[ 24
 
4.1%
] 24
 
4.1%
1 24
 
4.1%
2 17
 
2.9%
0 17
 
2.9%
! 14
 
2.4%
9 14
 
2.4%
요 12
 
2.1%
일 11
 
1.9%
Other values (164) 320
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 279
47.7%
Space Separator 108
 
18.5%
Decimal Number 85
 
14.5%
Uppercase Letter 28
 
4.8%
Open Punctuation 25
 
4.3%
Close Punctuation 25
 
4.3%
Other Punctuation 19
 
3.2%
Lowercase Letter 14
 
2.4%
Other Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
요 12
 
4.3%
일 11
 
3.9%
시 11
 
3.9%
이 8
 
2.9%
월 8
 
2.9%
송 8
 
2.9%
방 8
 
2.9%
밤 7
 
2.5%
분 6
 
2.2%
트 5
 
1.8%
Other values (126) 195
69.9%
Uppercase Letter
ValueCountFrequency (%)
T 7
25.0%
H 6
21.4%
O 6
21.4%
X 2
 
7.1%
S 1
 
3.6%
W 1
 
3.6%
C 1
 
3.6%
B 1
 
3.6%
M 1
 
3.6%
V 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
t 3
21.4%
i 2
14.3%
s 2
14.3%
a 2
14.3%
y 1
 
7.1%
d 1
 
7.1%
u 1
 
7.1%
h 1
 
7.1%
m 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 24
28.2%
2 17
20.0%
0 17
20.0%
9 14
16.5%
3 7
 
8.2%
5 4
 
4.7%
4 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
! 14
73.7%
? 2
 
10.5%
; 2
 
10.5%
: 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
[ 24
96.0%
( 1
 
4.0%
Close Punctuation
ValueCountFrequency (%)
] 24
96.0%
) 1
 
4.0%
Other Symbol
ValueCountFrequency (%)
☜ 1
50.0%
☞ 1
50.0%
Space Separator
ValueCountFrequency (%)
108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
47.7%
Common 264
45.1%
Latin 42
 
7.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
요 12
 
4.3%
일 11
 
3.9%
시 11
 
3.9%
이 8
 
2.9%
월 8
 
2.9%
송 8
 
2.9%
방 8
 
2.9%
밤 7
 
2.5%
분 6
 
2.2%
트 5
 
1.8%
Other values (126) 195
69.9%
Latin
ValueCountFrequency (%)
T 7
16.7%
H 6
14.3%
O 6
14.3%
t 3
 
7.1%
i 2
 
4.8%
X 2
 
4.8%
s 2
 
4.8%
a 2
 
4.8%
y 1
 
2.4%
d 1
 
2.4%
Other values (10) 10
23.8%
Common
ValueCountFrequency (%)
108
40.9%
[ 24
 
9.1%
] 24
 
9.1%
1 24
 
9.1%
2 17
 
6.4%
0 17
 
6.4%
! 14
 
5.3%
9 14
 
5.3%
3 7
 
2.7%
5 4
 
1.5%
Other values (8) 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 304
52.0%
Hangul 278
47.5%
Misc Symbols 2
 
0.3%
Compat Jamo 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
35.5%
[ 24
 
7.9%
] 24
 
7.9%
1 24
 
7.9%
2 17
 
5.6%
0 17
 
5.6%
! 14
 
4.6%
9 14
 
4.6%
3 7
 
2.3%
T 7
 
2.3%
Other values (26) 48
15.8%
Hangul
ValueCountFrequency (%)
요 12
 
4.3%
일 11
 
4.0%
시 11
 
4.0%
이 8
 
2.9%
월 8
 
2.9%
송 8
 
2.9%
방 8
 
2.9%
밤 7
 
2.5%
분 6
 
2.2%
트 5
 
1.8%
Other values (125) 194
69.8%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
☜ 1
50.0%
☞ 1
50.0%

REVIV_LIST_DC
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing24
Missing (%)96.0%
Memory size332.0 B
2023-12-10T23:14:43.092508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length34
Min length34

Characters and Unicode

Total characters34
Distinct characters26
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

Unique1 ?
Unique (%)100.0%

Sample

1st row대한민국의 트로트 판을 싹 다~ 갈아엎어줄 지원자를 찾습니다!
ValueCountFrequency (%)
대한민국의 1
12.5%
트로트 1
12.5%
판을 1
12.5%
싹 1
12.5%
다 1
12.5%
갈아엎어줄 1
12.5%
지원자를 1
12.5%
찾습니다 1
12.5%
2023-12-10T23:14:43.579711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
20.6%
트 2
 
5.9%
다 2
 
5.9%
대 1
 
2.9%
엎 1
 
2.9%
니 1
 
2.9%
습 1
 
2.9%
찾 1
 
2.9%
를 1
 
2.9%
자 1
 
2.9%
Other values (16) 16
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
73.5%
Space Separator 7
 
20.6%
Math Symbol 1
 
2.9%
Other Punctuation 1
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 2
 
8.0%
다 2
 
8.0%
대 1
 
4.0%
엎 1
 
4.0%
니 1
 
4.0%
습 1
 
4.0%
찾 1
 
4.0%
를 1
 
4.0%
자 1
 
4.0%
원 1
 
4.0%
Other values (13) 13
52.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
! 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
73.5%
Common 9
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 2
 
8.0%
다 2
 
8.0%
대 1
 
4.0%
엎 1
 
4.0%
니 1
 
4.0%
습 1
 
4.0%
찾 1
 
4.0%
를 1
 
4.0%
자 1
 
4.0%
원 1
 
4.0%
Other values (13) 13
52.0%
Common
ValueCountFrequency (%)
7
77.8%
~ 1
 
11.1%
! 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
73.5%
ASCII 9
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
77.8%
~ 1
 
11.1%
! 1
 
11.1%
Hangul
ValueCountFrequency (%)
트 2
 
8.0%
다 2
 
8.0%
대 1
 
4.0%
엎 1
 
4.0%
니 1
 
4.0%
습 1
 
4.0%
찾 1
 
4.0%
를 1
 
4.0%
자 1
 
4.0%
원 1
 
4.0%
Other values (13) 13
52.0%

REVIV_LIST_ICON
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:14:44.047393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length47.4
Min length46

Characters and Unicode

Total characters1185
Distinct characters66
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

Unique20 ?
Unique (%)80.0%

Sample

1st rowhttp://s.ytimg.com/yts/img/no_thumbnail-vfl4t3-4R.jpg
2nd rowhttps://i.ytimg.com/vi/38SNDQ5_cxA/default.jpg
3rd rowhttps://i.ytimg.com/vi/AiusQODLdBI/default.jpg
4th rowhttps://i.ytimg.com/vi/EnQkN1jjzXk/default.jpg
5th rowhttps://i.ytimg.com/vi/WeAa00OJWAA/default.jpg
ValueCountFrequency (%)
http://s.ytimg.com/yts/img/no_thumbnail-vfl4t3-4r.jpg 5
20.0%
https://i.ytimg.com/vi/defmxrie1_0/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/d9-4lr0p92s/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/mgsdvwzzwsq/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/hvp1ixwbpc8/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/2hrfua62uru/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/gyf-kssabto/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/jphnfshnpru/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/i6cfbr-qola/default.jpg 1
 
4.0%
https://i.ytimg.com/vi/-vvqnt8wkua/default.jpg 1
 
4.0%
Other values (11) 11
44.0%
2023-12-10T23:14:44.944607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 125
 
10.5%
t 112
 
9.5%
i 76
 
6.4%
. 75
 
6.3%
m 61
 
5.1%
g 57
 
4.8%
p 54
 
4.6%
h 34
 
2.9%
s 34
 
2.9%
y 32
 
2.7%
Other values (56) 525
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 785
66.2%
Other Punctuation 225
 
19.0%
Uppercase Letter 107
 
9.0%
Decimal Number 45
 
3.8%
Dash Punctuation 16
 
1.4%
Connector Punctuation 7
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 112
14.3%
i 76
 
9.7%
m 61
 
7.8%
g 57
 
7.3%
p 54
 
6.9%
h 34
 
4.3%
s 34
 
4.3%
y 32
 
4.1%
o 31
 
3.9%
l 31
 
3.9%
Other values (16) 263
33.5%
Uppercase Letter
ValueCountFrequency (%)
R 11
 
10.3%
A 7
 
6.5%
D 6
 
5.6%
W 6
 
5.6%
Y 6
 
5.6%
U 6
 
5.6%
Q 6
 
5.6%
S 5
 
4.7%
T 5
 
4.7%
I 5
 
4.7%
Other values (16) 44
41.1%
Decimal Number
ValueCountFrequency (%)
4 12
26.7%
0 7
15.6%
3 6
13.3%
1 6
13.3%
6 4
 
8.9%
8 3
 
6.7%
9 3
 
6.7%
2 3
 
6.7%
5 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 125
55.6%
. 75
33.3%
: 25
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 892
75.3%
Common 293
 
24.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 112
 
12.6%
i 76
 
8.5%
m 61
 
6.8%
g 57
 
6.4%
p 54
 
6.1%
h 34
 
3.8%
s 34
 
3.8%
y 32
 
3.6%
o 31
 
3.5%
l 31
 
3.5%
Other values (42) 370
41.5%
Common
ValueCountFrequency (%)
/ 125
42.7%
. 75
25.6%
: 25
 
8.5%
- 16
 
5.5%
4 12
 
4.1%
0 7
 
2.4%
_ 7
 
2.4%
3 6
 
2.0%
1 6
 
2.0%
6 4
 
1.4%
Other values (4) 10
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 125
 
10.5%
t 112
 
9.5%
i 76
 
6.4%
. 75
 
6.3%
m 61
 
5.1%
g 57
 
4.8%
p 54
 
4.6%
h 34
 
2.9%
s 34
 
2.9%
y 32
 
2.7%
Other values (56) 525
44.3%

VIDO_LIST
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.08
Minimum0
Maximum386
Zeros3
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:14:45.365251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median22
Q374
95-th percentile193.4
Maximum386
Range386
Interquartile range (IQR)68

Descriptive statistics

Standard deviation88.610534
Coefficient of variation (CV)1.4998398
Kurtosis7.1328029
Mean59.08
Median Absolute Deviation (MAD)20
Skewness2.4870073
Sum1477
Variance7851.8267
MonotonicityNot monotonic
2023-12-10T23:14:45.576212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 3
 
12.0%
20 2
 
8.0%
1 1
 
4.0%
51 1
 
4.0%
16 1
 
4.0%
22 1
 
4.0%
3 1
 
4.0%
32 1
 
4.0%
80 1
 
4.0%
197 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
0 3
12.0%
1 1
 
4.0%
2 1
 
4.0%
3 1
 
4.0%
6 1
 
4.0%
9 1
 
4.0%
12 1
 
4.0%
16 1
 
4.0%
20 2
8.0%
22 1
 
4.0%
ValueCountFrequency (%)
386 1
4.0%
197 1
4.0%
179 1
4.0%
137 1
4.0%
127 1
4.0%
80 1
4.0%
74 1
4.0%
51 1
4.0%
40 1
4.0%
37 1
4.0%

Interactions

2023-12-10T23:14:39.071661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:14:45.811292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
REVIV_LIST_IDREVIV_LIST_UPLOAD_DEREVIV_LIST_NMREVIV_LIST_ICONVIDO_LIST
REVIV_LIST_ID1.0001.0001.0001.0001.000
REVIV_LIST_UPLOAD_DE1.0001.0001.0000.9371.000
REVIV_LIST_NM1.0001.0001.0000.9801.000
REVIV_LIST_ICON1.0000.9370.9801.0001.000
VIDO_LIST1.0001.0001.0001.0001.000

Missing values

2023-12-10T23:14:39.333060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:14:39.590704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

REVIV_LIST_IDREVIV_LIST_CHNNL_IDREVIV_LIST_COLCT_DEREVIV_LIST_UPLOAD_DEREVIV_LIST_NMREVIV_LIST_DCREVIV_LIST_ICONVIDO_LIST
0PLtqYizcPqxZSFT21R3q37QoQoevX7dFdbUCiBr0bK06imaMbLc8sAEz0A2020-09-012020-08-03슈퍼시니어<NA>http://s.ytimg.com/yts/img/no_thumbnail-vfl4t3-4R.jpg1
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4PLtqYizcPqxZTJG1a2y30b4sSQg8Gz1Zu2UCiBr0bK06imaMbLc8sAEz0A2020-09-012020-06-21[트로트의 민족]대한민국의 트로트 판을 싹 다~ 갈아엎어줄 지원자를 찾습니다!https://i.ytimg.com/vi/WeAa00OJWAA/default.jpg6
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6PLtqYizcPqxZQxi4s-sEluvi4rJknX6EneUCiBr0bK06imaMbLc8sAEz0A2020-09-012020-05-26[최애 엔터테인먼트] 토요일 밤 9시 50분 방송!<NA>https://i.ytimg.com/vi/tC-dBkbMkFk/default.jpg179
7PLtqYizcPqxZQ6a8UTFHzvf0U8vH3-rNwIUCiBr0bK06imaMbLc8sAEz0A2020-09-012020-04-24[출발! 비디오 여행]<NA>https://i.ytimg.com/vi/yUYY9KKbnW0/default.jpg2
8PLtqYizcPqxZR7XeQIDIQhaeNjL938TPejUCiBr0bK06imaMbLc8sAEz0A2020-09-012020-02-14[탐나는 TV]<NA>http://s.ytimg.com/yts/img/no_thumbnail-vfl4t3-4R.jpg0
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REVIV_LIST_IDREVIV_LIST_CHNNL_IDREVIV_LIST_COLCT_DEREVIV_LIST_UPLOAD_DEREVIV_LIST_NMREVIV_LIST_DCREVIV_LIST_ICONVIDO_LIST
15PLtqYizcPqxZSRYe5JST5ENP1QAVVSGA3iUCiBr0bK06imaMbLc8sAEz0A2020-09-012020-01-03[오! 나의 파트; 너] 토요일 밤 9시 5분 방송!<NA>https://i.ytimg.com/vi/I6Cfbr-qOLA/default.jpg197
16PLtqYizcPqxZR1WmUTVKQXq3O11am2YIpUUCiBr0bK06imaMbLc8sAEz0A2020-09-012019-12-24[우리말 나들이]<NA>https://i.ytimg.com/vi/jphNfShnprU/default.jpg80
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22PLtqYizcPqxZSdrxsaCyN2xCoAWp6eQe9IUCiBr0bK06imaMbLc8sAEz0A2020-09-012019-12-14[HOT] 나 혼자 산다 20191213<NA>https://i.ytimg.com/vi/d9-4lR0P92s/default.jpg20
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