Overview

Dataset statistics

Number of variables6
Number of observations43
Missing cells144
Missing cells (%)55.8%
Duplicate rows6
Duplicate rows (%)14.0%
Total size in memory2.2 KiB
Average record size in memory53.1 B

Variable types

Text4
Categorical1
Unsupported1

Dataset

Description샘플 데이터
AuthorMBN
URLhttps://kdx.kr/data/view/1008

Alerts

Dataset has 6 (14.0%) duplicate rowsDuplicates
reg_dt is highly imbalanced (76.2%)Imbalance
clip_seq_no has 9 (20.9%) missing valuesMissing
title has 26 (60.5%) missing valuesMissing
contents has 26 (60.5%) missing valuesMissing
vod has 40 (93.0%) missing valuesMissing
Unnamed: 5 has 43 (100.0%) missing valuesMissing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 21:24:21.836801
Analysis finished2023-12-11 21:24:22.396266
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

clip_seq_no
Text

MISSING 

Distinct29
Distinct (%)85.3%
Missing9
Missing (%)20.9%
Memory size476.0 B
2023-12-12T06:24:22.605555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length25.352941
Min length7

Characters and Unicode

Total characters862
Distinct characters176
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

Unique24 ?
Unique (%)70.6%

Sample

1st row1036380
2nd row믿고 보는 알토란의 마스코트! 임성근 조리기능장의 <새해 밥상>
3rd row“밥?국만 바꿔도 한 해가 건강하다?”
4th row건강한 <밥?국>의 새로운 표준이 밝혀진다!
5th row2018년 꼭 챙겨 먹어야 할 건강밥상의 표준! 알토란 표 <미역국>?
ValueCountFrequency (%)
밥상 8
 
3.9%
새해 7
 
3.4%
먹어야 4
 
2.0%
한 4
 
2.0%
꼭 4
 
2.0%
진한 3
 
1.5%
할 3
 
1.5%
건강 3
 
1.5%
보약 3
 
1.5%
표 3
 
1.5%
Other values (120) 162
79.4%
2023-12-12T06:24:22.980072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
 
19.7%
한 18
 
2.1%
6 17
 
2.0%
< 17
 
2.0%
> 17
 
2.0%
1 16
 
1.9%
의 16
 
1.9%
3 16
 
1.9%
0 16
 
1.9%
는 16
 
1.9%
Other values (166) 543
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 503
58.4%
Space Separator 170
 
19.7%
Decimal Number 87
 
10.1%
Math Symbol 35
 
4.1%
Other Punctuation 35
 
4.1%
Initial Punctuation 9
 
1.0%
Final Punctuation 9
 
1.0%
Close Punctuation 7
 
0.8%
Open Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 18
 
3.6%
의 16
 
3.2%
는 16
 
3.2%
밥 14
 
2.8%
국 12
 
2.4%
해 12
 
2.4%
강 11
 
2.2%
하 11
 
2.2%
건 11
 
2.2%
새 9
 
1.8%
Other values (144) 373
74.2%
Decimal Number
ValueCountFrequency (%)
6 17
19.5%
1 16
18.4%
3 16
18.4%
0 16
18.4%
8 10
11.5%
2 6
 
6.9%
7 3
 
3.4%
4 2
 
2.3%
9 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
< 17
48.6%
> 17
48.6%
~ 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
! 16
45.7%
? 12
34.3%
, 7
20.0%
Initial Punctuation
ValueCountFrequency (%)
“ 5
55.6%
‘ 4
44.4%
Final Punctuation
ValueCountFrequency (%)
” 5
55.6%
’ 4
44.4%
Space Separator
ValueCountFrequency (%)
170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
57.2%
Common 359
41.6%
Han 10
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 18
 
3.7%
의 16
 
3.2%
는 16
 
3.2%
밥 14
 
2.8%
국 12
 
2.4%
해 12
 
2.4%
강 11
 
2.2%
하 11
 
2.2%
건 11
 
2.2%
새 9
 
1.8%
Other values (137) 363
73.6%
Common
ValueCountFrequency (%)
170
47.4%
6 17
 
4.7%
< 17
 
4.7%
> 17
 
4.7%
1 16
 
4.5%
3 16
 
4.5%
0 16
 
4.5%
! 16
 
4.5%
? 12
 
3.3%
8 10
 
2.8%
Other values (12) 52
 
14.5%
Han
ValueCountFrequency (%)
病 2
20.0%
大 2
20.0%
家 2
20.0%
石 1
10.0%
定 1
10.0%
藥 1
10.0%
腸 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
57.2%
ASCII 341
39.6%
Punctuation 18
 
2.1%
CJK 10
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
49.9%
6 17
 
5.0%
< 17
 
5.0%
> 17
 
5.0%
1 16
 
4.7%
3 16
 
4.7%
0 16
 
4.7%
! 16
 
4.7%
? 12
 
3.5%
8 10
 
2.9%
Other values (8) 34
 
10.0%
Hangul
ValueCountFrequency (%)
한 18
 
3.7%
의 16
 
3.2%
는 16
 
3.2%
밥 14
 
2.8%
국 12
 
2.4%
해 12
 
2.4%
강 11
 
2.2%
하 11
 
2.2%
건 11
 
2.2%
새 9
 
1.8%
Other values (137) 363
73.6%
Punctuation
ValueCountFrequency (%)
“ 5
27.8%
” 5
27.8%
‘ 4
22.2%
’ 4
22.2%
CJK
ValueCountFrequency (%)
病 2
20.0%
大 2
20.0%
家 2
20.0%
石 1
10.0%
定 1
10.0%
藥 1
10.0%
腸 1
10.0%

title
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing26
Missing (%)60.5%
Memory size476.0 B
2023-12-12T06:24:23.162280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length41
Mean length24.058824
Min length15

Characters and Unicode

Total characters409
Distinct characters100
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

Unique17 ?
Unique (%)100.0%

Sample

1st row[미공개 영상] <2018 약(藥) 되는 ‘새해 밥상’> ‘가자미 미역국’
2nd row20180101011249
3rd row[미공개 영상] <2018 약(藥) 되는 ‘새해 밥상’> ‘건강 잡곡밥’
4th row20180101011707
5th row[미공개 영상] <2018 약(藥) 되는 ‘새해 밥상’> ‘떡국&떡국 육수’
ValueCountFrequency (%)
미공개 5
 
6.4%
2018 5
 
6.4%
약(藥 5
 
6.4%
되는 5
 
6.4%
‘새해 5
 
6.4%
밥상’ 5
 
6.4%
영상 5
 
6.4%
‘양배추 2
 
2.6%
메주를 2
 
2.6%
완성된 1
 
1.3%
Other values (38) 38
48.7%
2023-12-12T06:24:23.627069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
 
16.6%
0 37
 
9.0%
1 36
 
8.8%
2 18
 
4.4%
8 15
 
3.7%
’ 10
 
2.4%
상 10
 
2.4%
‘ 10
 
2.4%
미 7
 
1.7%
밥 6
 
1.5%
Other values (90) 192
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
40.3%
Decimal Number 118
28.9%
Space Separator 68
16.6%
Final Punctuation 10
 
2.4%
Initial Punctuation 10
 
2.4%
Math Symbol 10
 
2.4%
Open Punctuation 10
 
2.4%
Close Punctuation 10
 
2.4%
Other Punctuation 8
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 10
 
6.1%
미 7
 
4.2%
밥 6
 
3.6%
는 6
 
3.6%
되 5
 
3.0%
해 5
 
3.0%
새 5
 
3.0%
藥 5
 
3.0%
약 5
 
3.0%
공 5
 
3.0%
Other values (68) 106
64.2%
Decimal Number
ValueCountFrequency (%)
0 37
31.4%
1 36
30.5%
2 18
15.3%
8 15
12.7%
3 3
 
2.5%
4 3
 
2.5%
5 2
 
1.7%
7 2
 
1.7%
9 1
 
0.8%
6 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
? 5
62.5%
! 2
 
25.0%
& 1
 
12.5%
Math Symbol
ValueCountFrequency (%)
> 5
50.0%
< 5
50.0%
Open Punctuation
ValueCountFrequency (%)
[ 5
50.0%
( 5
50.0%
Close Punctuation
ValueCountFrequency (%)
) 5
50.0%
] 5
50.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 10
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 244
59.7%
Hangul 160
39.1%
Han 5
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 10
 
6.2%
미 7
 
4.4%
밥 6
 
3.8%
는 6
 
3.8%
되 5
 
3.1%
해 5
 
3.1%
새 5
 
3.1%
약 5
 
3.1%
공 5
 
3.1%
영 5
 
3.1%
Other values (67) 101
63.1%
Common
ValueCountFrequency (%)
68
27.9%
0 37
15.2%
1 36
14.8%
2 18
 
7.4%
8 15
 
6.1%
’ 10
 
4.1%
‘ 10
 
4.1%
? 5
 
2.0%
> 5
 
2.0%
[ 5
 
2.0%
Other values (12) 35
14.3%
Han
ValueCountFrequency (%)
藥 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 224
54.8%
Hangul 160
39.1%
Punctuation 20
 
4.9%
CJK 5
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
30.4%
0 37
16.5%
1 36
16.1%
2 18
 
8.0%
8 15
 
6.7%
? 5
 
2.2%
> 5
 
2.2%
[ 5
 
2.2%
) 5
 
2.2%
( 5
 
2.2%
Other values (10) 25
 
11.2%
Punctuation
ValueCountFrequency (%)
’ 10
50.0%
‘ 10
50.0%
Hangul
ValueCountFrequency (%)
상 10
 
6.2%
미 7
 
4.4%
밥 6
 
3.8%
는 6
 
3.8%
되 5
 
3.1%
해 5
 
3.1%
새 5
 
3.1%
약 5
 
3.1%
공 5
 
3.1%
영 5
 
3.1%
Other values (67) 101
63.1%
CJK
ValueCountFrequency (%)
藥 5
100.0%

contents
Text

MISSING 

Distinct13
Distinct (%)76.5%
Missing26
Missing (%)60.5%
Memory size476.0 B
2023-12-12T06:24:23.784029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length37
Mean length44.882353
Min length12

Characters and Unicode

Total characters763
Distinct characters116
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)70.6%

Sample

1st row159회 알토란 레시피
2nd rowhttp://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036380
3rd row159회 알토란 레시피
4th rowhttp://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036381
5th row159회 알토란 레시피
ValueCountFrequency (%)
159회 5
 
9.1%
레시피 5
 
9.1%
알토란 5
 
9.1%
꼭 2
 
3.6%
메주의 2
 
3.6%
막장 1
 
1.8%
숙성도가 1
 
1.8%
해보세요 1
 
1.8%
제거&다른 1
 
1.8%
따라 1
 
1.8%
Other values (31) 31
56.4%
2023-12-12T06:24:24.038288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 56
 
7.3%
n 56
 
7.3%
38
 
5.0%
e 35
 
4.6%
o 35
 
4.6%
c 35
 
4.6%
. 28
 
3.7%
/ 28
 
3.7%
m 21
 
2.8%
_ 21
 
2.8%
Other values (106) 410
53.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 392
51.4%
Other Letter 127
 
16.6%
Other Punctuation 83
 
10.9%
Decimal Number 78
 
10.2%
Space Separator 38
 
5.0%
Connector Punctuation 21
 
2.8%
Math Symbol 17
 
2.2%
Uppercase Letter 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
알 7
 
5.5%
피 5
 
3.9%
레 5
 
3.9%
란 5
 
3.9%
토 5
 
3.9%
회 5
 
3.9%
시 5
 
3.9%
주 4
 
3.1%
장 4
 
3.1%
다 3
 
2.4%
Other values (66) 79
62.2%
Lowercase Letter
ValueCountFrequency (%)
t 56
14.3%
n 56
14.3%
e 35
 
8.9%
o 35
 
8.9%
c 35
 
8.9%
m 21
 
5.4%
w 21
 
5.4%
s 14
 
3.6%
d 14
 
3.6%
b 14
 
3.6%
Other values (9) 91
23.2%
Decimal Number
ValueCountFrequency (%)
1 20
25.6%
3 13
16.7%
6 10
12.8%
2 9
11.5%
0 8
 
10.3%
8 6
 
7.7%
9 5
 
6.4%
5 5
 
6.4%
4 1
 
1.3%
7 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 28
33.7%
/ 28
33.7%
& 8
 
9.6%
: 7
 
8.4%
? 7
 
8.4%
! 5
 
6.0%
Math Symbol
ValueCountFrequency (%)
= 14
82.4%
~ 3
 
17.6%
Space Separator
ValueCountFrequency (%)
38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 21
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 399
52.3%
Common 237
31.1%
Hangul 127
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
알 7
 
5.5%
피 5
 
3.9%
레 5
 
3.9%
란 5
 
3.9%
토 5
 
3.9%
회 5
 
3.9%
시 5
 
3.9%
주 4
 
3.1%
장 4
 
3.1%
다 3
 
2.4%
Other values (66) 79
62.2%
Latin
ValueCountFrequency (%)
t 56
14.0%
n 56
14.0%
e 35
 
8.8%
o 35
 
8.8%
c 35
 
8.8%
m 21
 
5.3%
w 21
 
5.3%
s 14
 
3.5%
d 14
 
3.5%
b 14
 
3.5%
Other values (10) 98
24.6%
Common
ValueCountFrequency (%)
38
16.0%
. 28
11.8%
/ 28
11.8%
_ 21
8.9%
1 20
8.4%
= 14
 
5.9%
3 13
 
5.5%
6 10
 
4.2%
2 9
 
3.8%
& 8
 
3.4%
Other values (10) 48
20.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 636
83.4%
Hangul 127
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 56
 
8.8%
n 56
 
8.8%
38
 
6.0%
e 35
 
5.5%
o 35
 
5.5%
c 35
 
5.5%
. 28
 
4.4%
/ 28
 
4.4%
m 21
 
3.3%
_ 21
 
3.3%
Other values (30) 283
44.5%
Hangul
ValueCountFrequency (%)
알 7
 
5.5%
피 5
 
3.9%
레 5
 
3.9%
란 5
 
3.9%
토 5
 
3.9%
회 5
 
3.9%
시 5
 
3.9%
주 4
 
3.1%
장 4
 
3.1%
다 3
 
2.4%
Other values (66) 79
62.2%

reg_dt
Categorical

IMBALANCE 

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
40 
20180108005932
 
1
20180108010118
 
1
20180108010258
 
1

Length

Max length14
Median length4
Mean length4.6976744
Min length4

Unique

Unique3 ?
Unique (%)7.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 40
93.0%
20180108005932 1
 
2.3%
20180108010118 1
 
2.3%
20180108010258 1
 
2.3%

Length

2023-12-12T06:24:24.134516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T06:24:24.212890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
93.0%
20180108005932 1
 
2.3%
20180108010118 1
 
2.3%
20180108010258 1
 
2.3%

vod
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing40
Missing (%)93.0%
Memory size476.0 B
2023-12-12T06:24:24.371913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length82
Mean length82
Min length82

Characters and Unicode

Total characters246
Distinct characters34
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowhttp://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036669
2nd rowhttp://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036670
3rd rowhttp://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036671
ValueCountFrequency (%)
http://www.mbn.co.kr/player/moviecontents.mbn?content_cls_cd=21&content_id=1036669 1
33.3%
http://www.mbn.co.kr/player/moviecontents.mbn?content_cls_cd=21&content_id=1036670 1
33.3%
http://www.mbn.co.kr/player/moviecontents.mbn?content_cls_cd=21&content_id=1036671 1
33.3%
2023-12-12T06:24:24.625989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 24
 
9.8%
t 24
 
9.8%
e 15
 
6.1%
o 15
 
6.1%
c 15
 
6.1%
/ 12
 
4.9%
. 12
 
4.9%
_ 9
 
3.7%
m 9
 
3.7%
w 9
 
3.7%
Other values (24) 102
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 168
68.3%
Other Punctuation 33
 
13.4%
Decimal Number 27
 
11.0%
Connector Punctuation 9
 
3.7%
Math Symbol 6
 
2.4%
Uppercase Letter 3
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 24
14.3%
t 24
14.3%
e 15
 
8.9%
o 15
 
8.9%
c 15
 
8.9%
m 9
 
5.4%
w 9
 
5.4%
b 6
 
3.6%
d 6
 
3.6%
r 6
 
3.6%
Other values (9) 39
23.2%
Decimal Number
ValueCountFrequency (%)
6 7
25.9%
1 7
25.9%
0 4
14.8%
2 3
11.1%
3 3
11.1%
7 2
 
7.4%
9 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/ 12
36.4%
. 12
36.4%
& 3
 
9.1%
? 3
 
9.1%
: 3
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Math Symbol
ValueCountFrequency (%)
= 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 171
69.5%
Common 75
30.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 24
14.0%
t 24
14.0%
e 15
 
8.8%
o 15
 
8.8%
c 15
 
8.8%
m 9
 
5.3%
w 9
 
5.3%
b 6
 
3.5%
d 6
 
3.5%
r 6
 
3.5%
Other values (10) 42
24.6%
Common
ValueCountFrequency (%)
/ 12
16.0%
. 12
16.0%
_ 9
12.0%
6 7
9.3%
1 7
9.3%
= 6
8.0%
0 4
 
5.3%
& 3
 
4.0%
2 3
 
4.0%
3 3
 
4.0%
Other values (4) 9
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 24
 
9.8%
t 24
 
9.8%
e 15
 
6.1%
o 15
 
6.1%
c 15
 
6.1%
/ 12
 
4.9%
. 12
 
4.9%
_ 9
 
3.7%
m 9
 
3.7%
w 9
 
3.7%
Other values (24) 102
41.5%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size519.0 B

Correlations

2023-12-12T06:24:24.696131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
clip_seq_notitlecontentsreg_dtvod
clip_seq_no1.0001.0001.0001.0001.000
title1.0001.0001.0001.0001.000
contents1.0001.0001.0001.0001.000
reg_dt1.0001.0001.0001.0001.000
vod1.0001.0001.0001.0001.000

Missing values

2023-12-12T06:24:22.184796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T06:24:22.264420image/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.
2023-12-12T06:24:22.344947image/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

clip_seq_notitlecontentsreg_dtvodUnnamed: 5
0<NA><NA><NA><NA><NA><NA>
11036380[미공개 영상] <2018 약(藥) 되는 ‘새해 밥상’> ‘가자미 미역국’159회 알토란 레시피<NA><NA><NA>
2<NA><NA><NA><NA><NA><NA>
3믿고 보는 알토란의 마스코트! 임성근 조리기능장의 <새해 밥상><NA><NA><NA><NA><NA>
4“밥?국만 바꿔도 한 해가 건강하다?”<NA><NA><NA><NA><NA>
5건강한 <밥?국>의 새로운 표준이 밝혀진다!<NA><NA><NA><NA><NA>
62018년 꼭 챙겨 먹어야 할 건강밥상의 표준! 알토란 표 <미역국>?<NA><NA><NA><NA><NA>
7사골보다 진한 <미역국> 끓이는 비법?20180101011249http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036380<NA><NA><NA>
81036381[미공개 영상] <2018 약(藥) 되는 ‘새해 밥상’> ‘건강 잡곡밥’159회 알토란 레시피<NA><NA><NA>
9<NA><NA><NA><NA><NA><NA>
clip_seq_notitlecontentsreg_dtvodUnnamed: 5
33알토란이 선정한 최고의 식재료 ‘양배추’로 차리는 보약 밥상!<NA><NA><NA><NA><NA>
34영양 가득한 <양배추 제육볶음> 만드는 법?20180101013111http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036384<NA><NA><NA>
351036668발효 음식! 겨울에 꼭 챙겨 먹어야 하는 이유?발효 음식의 모든 것! 절대 놓치지 마세요~<NA><NA><NA>
36<NA>20180108005802http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036668<NA><NA><NA>
371036669완성된 메주를 믹서에 갈아주기?!막장용 콩알메주는 꼭 굵직하게 갈아주세요~20180108005932http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036669<NA>
381036670메주를 베란다에서 저온 숙성 시켜라?메주의 날내를 완벽 제거&다른 재료와 배합할 때 숙성도가 높아진다!20180108010118http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036670<NA>
391036671막장에 들어갈 고추씨의 효능은?고추씨! 메주의 저장성을 높인다!20180108010258http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036671<NA>
401036672막장을 만들 때 국간장을 넣어라?알짜 비법 국간장 넣은 막장! 꼭 따라 해보세요~<NA><NA><NA>
41<NA>20180108010434http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1036672<NA><NA><NA>
42<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

clip_seq_notitlecontentsreg_dtvod# duplicates
5<NA><NA><NA><NA><NA>7
0“2018년, 꼭 먹어야 할 건강 식재료?”<NA><NA><NA><NA>2
1“밥?국만 바꿔도 한 해가 건강하다?”<NA><NA><NA><NA>2
2떠오르는 한식의 대가(大家)! 원승식 셰프가 공개하는 <새해 밥상><NA><NA><NA><NA>2
3믿고 보는 알토란의 마스코트! 임성근 조리기능장의 <새해 밥상><NA><NA><NA><NA>2
4올 한 해, 병(病) 없이 건강하고 싶다면 밥상 위의 보약, <양배추>에 주목하라!<NA><NA><NA><NA>2