Overview

Dataset statistics

Number of variables9
Number of observations61
Missing cells261
Missing cells (%)47.5%
Duplicate rows1
Duplicate rows (%)1.6%
Total size in memory4.7 KiB
Average record size in memory79.2 B

Variable types

Text4
Categorical4
Unsupported1

Dataset

Description샘플 데이터
AuthorMBN
URLhttps://kdx.kr/data/view/29651

Alerts

contents has constant value ""Constant
Dataset has 1 (1.6%) duplicate rowsDuplicates
bcast_seq_no is highly overall correlated with play_sec and 2 other fieldsHigh correlation
play_hour is highly overall correlated with bcast_seq_no and 2 other fieldsHigh correlation
play_sec is highly overall correlated with bcast_seq_no and 2 other fieldsHigh correlation
file_size is highly overall correlated with bcast_seq_no and 2 other fieldsHigh correlation
bcast_seq_no is highly imbalanced (84.8%)Imbalance
play_sec is highly imbalanced (84.8%)Imbalance
play_hour is highly imbalanced (84.8%)Imbalance
file_size is highly imbalanced (84.8%)Imbalance
vod_seq_no has 23 (37.7%) missing valuesMissing
vod_path has 59 (96.7%) missing valuesMissing
title has 59 (96.7%) missing valuesMissing
contents has 59 (96.7%) missing valuesMissing
Unnamed: 8 has 61 (100.0%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-11 03:25:34.693787
Analysis finished2024-03-11 03:25:36.828407
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

vod_seq_no
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing23
Missing (%)37.7%
Memory size620.0 B
2024-03-11T12:25:37.028362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length141
Median length71.5
Mean length51.894737
Min length5

Characters and Unicode

Total characters1972
Distinct characters314
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row476671
2nd row 오늘부터 저희 MBN이 조간신문이 보도한 주요 뉴스를 정리해 드리는 시간을 갖기로 했는데요.
3rd row 가장 먼저, 매일경제 1면 보시겠습니다.
4th row1) 매일경제 1면입니다.
5th row 총사업비 31조 원이죠, 단군 이래 최대 개발 프로젝트라는 용산역세권 개발 사업이 기로에 처했는데요, 감사원이 오는 18일부터 용산 개발 사업에 대해 대규모 특별감사에 들어간다는 소식입니다.
ValueCountFrequency (%)
어제 6
 
1.4%
협상을 5
 
1.2%
등 4
 
0.9%
못했습니다 4
 
0.9%
보시겠습니다 3
 
0.7%
군 3
 
0.7%
감사원이 3
 
0.7%
대해 3
 
0.7%
개발 3
 
0.7%
협상 3
 
0.7%
Other values (354) 391
91.4%
2024-03-11T12:25:37.443631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
446
 
22.6%
이 57
 
2.9%
다 36
 
1.8%
. 34
 
1.7%
니 29
 
1.5%
, 27
 
1.4%
에 26
 
1.3%
는 24
 
1.2%
을 23
 
1.2%
지 22
 
1.1%
Other values (304) 1248
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1390
70.5%
Space Separator 446
 
22.6%
Other Punctuation 78
 
4.0%
Decimal Number 38
 
1.9%
Uppercase Letter 14
 
0.7%
Close Punctuation 5
 
0.3%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 57
 
4.1%
다 36
 
2.6%
니 29
 
2.1%
에 26
 
1.9%
는 24
 
1.7%
을 23
 
1.7%
지 22
 
1.6%
대 21
 
1.5%
습 21
 
1.5%
의 21
 
1.5%
Other values (277) 1110
79.9%
Decimal Number
ValueCountFrequency (%)
1 12
31.6%
2 5
13.2%
6 5
13.2%
7 4
 
10.5%
4 4
 
10.5%
3 3
 
7.9%
9 2
 
5.3%
0 1
 
2.6%
5 1
 
2.6%
8 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
14.3%
N 2
14.3%
V 2
14.3%
I 2
14.3%
P 2
14.3%
T 2
14.3%
B 1
7.1%
M 1
7.1%
Other Punctuation
ValueCountFrequency (%)
. 34
43.6%
, 27
34.6%
' 6
 
7.7%
· 5
 
6.4%
" 4
 
5.1%
? 2
 
2.6%
Space Separator
ValueCountFrequency (%)
446
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1390
70.5%
Common 568
28.8%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 57
 
4.1%
다 36
 
2.6%
니 29
 
2.1%
에 26
 
1.9%
는 24
 
1.7%
을 23
 
1.7%
지 22
 
1.6%
대 21
 
1.5%
습 21
 
1.5%
의 21
 
1.5%
Other values (277) 1110
79.9%
Common
ValueCountFrequency (%)
446
78.5%
. 34
 
6.0%
, 27
 
4.8%
1 12
 
2.1%
' 6
 
1.1%
2 5
 
0.9%
· 5
 
0.9%
6 5
 
0.9%
) 5
 
0.9%
7 4
 
0.7%
Other values (9) 19
 
3.3%
Latin
ValueCountFrequency (%)
L 2
14.3%
N 2
14.3%
V 2
14.3%
I 2
14.3%
P 2
14.3%
T 2
14.3%
B 1
7.1%
M 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1390
70.5%
ASCII 577
29.3%
None 5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
446
77.3%
. 34
 
5.9%
, 27
 
4.7%
1 12
 
2.1%
' 6
 
1.0%
2 5
 
0.9%
6 5
 
0.9%
) 5
 
0.9%
7 4
 
0.7%
4 4
 
0.7%
Other values (16) 29
 
5.0%
Hangul
ValueCountFrequency (%)
이 57
 
4.1%
다 36
 
2.6%
니 29
 
2.1%
에 26
 
1.9%
는 24
 
1.7%
을 23
 
1.7%
지 22
 
1.6%
대 21
 
1.5%
습 21
 
1.5%
의 21
 
1.5%
Other values (277) 1110
79.9%
None
ValueCountFrequency (%)
· 5
100.0%

bcast_seq_no
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
59 
1042628
 
1
1042630
 
1

Length

Max length7
Median length4
Mean length4.0983607
Min length4

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row1042628
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
96.7%
1042628 1
 
1.6%
1042630 1
 
1.6%

Length

2024-03-11T12:25:37.552969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-11T12:25:37.644922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
96.7%
1042628 1
 
1.6%
1042630 1
 
1.6%

play_sec
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
59 
80
 
1
276
 
1

Length

Max length4
Median length4
Mean length3.9508197
Min length2

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row80
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
96.7%
80 1
 
1.6%
276 1
 
1.6%

Length

2024-03-11T12:25:37.733706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-11T12:25:37.827342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
96.7%
80 1
 
1.6%
276 1
 
1.6%

play_hour
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
59 
0.0222
 
1
0.0767
 
1

Length

Max length6
Median length4
Mean length4.0655738
Min length4

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row0.0222
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
96.7%
0.0222 1
 
1.6%
0.0767 1
 
1.6%

Length

2024-03-11T12:25:37.930586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-11T12:25:38.021573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
96.7%
0.0222 1
 
1.6%
0.0767 1
 
1.6%

file_size
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
59 
5366506
 
1
46604889
 
1

Length

Max length8
Median length4
Mean length4.1147541
Min length4

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row5366506
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
96.7%
5366506 1
 
1.6%
46604889 1
 
1.6%

Length

2024-03-11T12:25:38.110914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-11T12:25:38.193020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
96.7%
5366506 1
 
1.6%
46604889 1
 
1.6%

vod_path
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing59
Missing (%)96.7%
Memory size620.0 B
2024-03-11T12:25:38.347483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length61
Mean length61
Min length61

Characters and Unicode

Total characters122
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row/mbnvod2/605/2013/03/04/20130304085625_20_605_1042628_360.mp4
2nd row/mbnvod2/605/2013/03/04/20130304085625_20_605_1042630_360.mp4
ValueCountFrequency (%)
mbnvod2/605/2013/03/04/20130304085625_20_605_1042628_360.mp4 1
50.0%
mbnvod2/605/2013/03/04/20130304085625_20_605_1042630_360.mp4 1
50.0%
2024-03-11T12:25:38.588475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25
20.5%
2 13
10.7%
/ 12
9.8%
3 11
9.0%
6 10
 
8.2%
5 8
 
6.6%
4 8
 
6.6%
_ 8
 
6.6%
1 6
 
4.9%
m 4
 
3.3%
Other values (8) 17
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
68.9%
Lowercase Letter 16
 
13.1%
Other Punctuation 14
 
11.5%
Connector Punctuation 8
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
29.8%
2 13
15.5%
3 11
13.1%
6 10
 
11.9%
5 8
 
9.5%
4 8
 
9.5%
1 6
 
7.1%
8 3
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
m 4
25.0%
n 2
12.5%
v 2
12.5%
o 2
12.5%
d 2
12.5%
b 2
12.5%
p 2
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 12
85.7%
. 2
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106
86.9%
Latin 16
 
13.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25
23.6%
2 13
12.3%
/ 12
11.3%
3 11
10.4%
6 10
 
9.4%
5 8
 
7.5%
4 8
 
7.5%
_ 8
 
7.5%
1 6
 
5.7%
8 3
 
2.8%
Latin
ValueCountFrequency (%)
m 4
25.0%
n 2
12.5%
v 2
12.5%
o 2
12.5%
d 2
12.5%
b 2
12.5%
p 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25
20.5%
2 13
10.7%
/ 12
9.8%
3 11
9.0%
6 10
 
8.2%
5 8
 
6.6%
4 8
 
6.6%
_ 8
 
6.6%
1 6
 
4.9%
m 4
 
3.3%
Other values (8) 17
13.9%

title
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing59
Missing (%)96.7%
Memory size620.0 B
2024-03-11T12:25:38.748593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9.5
Mean length9.5
Min length8

Characters and Unicode

Total characters19
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row조간신문 브리핑
2nd row여야 심야 회동 불발
ValueCountFrequency (%)
조간신문 1
16.7%
브리핑 1
16.7%
여야 1
16.7%
심야 1
16.7%
회동 1
16.7%
불발 1
16.7%
2024-03-11T12:25:38.959662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
21.1%
야 2
 
10.5%
조 1
 
5.3%
간 1
 
5.3%
신 1
 
5.3%
문 1
 
5.3%
브 1
 
5.3%
리 1
 
5.3%
핑 1
 
5.3%
여 1
 
5.3%
Other values (5) 5
26.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
78.9%
Space Separator 4
 
21.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
야 2
13.3%
조 1
 
6.7%
간 1
 
6.7%
신 1
 
6.7%
문 1
 
6.7%
브 1
 
6.7%
리 1
 
6.7%
핑 1
 
6.7%
여 1
 
6.7%
심 1
 
6.7%
Other values (4) 4
26.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
78.9%
Common 4
 
21.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
야 2
13.3%
조 1
 
6.7%
간 1
 
6.7%
신 1
 
6.7%
문 1
 
6.7%
브 1
 
6.7%
리 1
 
6.7%
핑 1
 
6.7%
여 1
 
6.7%
심 1
 
6.7%
Other values (4) 4
26.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
78.9%
ASCII 4
 
21.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
야 2
13.3%
조 1
 
6.7%
간 1
 
6.7%
신 1
 
6.7%
문 1
 
6.7%
브 1
 
6.7%
리 1
 
6.7%
핑 1
 
6.7%
여 1
 
6.7%
심 1
 
6.7%
Other values (4) 4
26.7%

contents
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing59
Missing (%)96.7%
Memory size620.0 B
2024-03-11T12:25:39.070910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters16
Distinct characters7
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row【 앵커멘트 】
2nd row【 앵커멘트 】
ValueCountFrequency (%)
【 2
33.3%
앵커멘트 2
33.3%
】 2
33.3%
2024-03-11T12:25:39.268237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
【 2
12.5%
앵 2
12.5%
커 2
12.5%
멘 2
12.5%
트 2
12.5%
】 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
50.0%
Space Separator 4
25.0%
Open Punctuation 2
 
12.5%
Close Punctuation 2
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앵 2
25.0%
커 2
25.0%
멘 2
25.0%
트 2
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
【 2
100.0%
Close Punctuation
ValueCountFrequency (%)
】 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
50.0%
Hangul 8
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앵 2
25.0%
커 2
25.0%
멘 2
25.0%
트 2
25.0%
Common
ValueCountFrequency (%)
4
50.0%
【 2
25.0%
】 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
50.0%
ASCII 4
25.0%
None 4
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
None
ValueCountFrequency (%)
【 2
50.0%
】 2
50.0%
Hangul
ValueCountFrequency (%)
앵 2
25.0%
커 2
25.0%
멘 2
25.0%
트 2
25.0%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

Correlations

2024-03-11T12:25:39.356131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitle
vod_seq_no1.0000.0000.0000.0000.0000.0000.000
bcast_seq_no0.0001.0000.0000.0000.0000.0000.000
play_sec0.0000.0001.0000.0000.0000.0000.000
play_hour0.0000.0000.0001.0000.0000.0000.000
file_size0.0000.0000.0000.0001.0000.0000.000
vod_path0.0000.0000.0000.0000.0001.0000.000
title0.0000.0000.0000.0000.0000.0001.000
2024-03-11T12:25:39.443019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
bcast_seq_noplay_hourplay_secfile_size
bcast_seq_no1.0001.0001.0001.000
play_hour1.0001.0001.0001.000
play_sec1.0001.0001.0001.000
file_size1.0001.0001.0001.000
2024-03-11T12:25:39.515112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
bcast_seq_noplay_secplay_hourfile_size
bcast_seq_no1.0001.0001.0001.000
play_sec1.0001.0001.0001.000
play_hour1.0001.0001.0001.000
file_size1.0001.0001.0001.000

Missing values

2024-03-11T12:25:36.487231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-11T12:25:36.627974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-11T12:25:36.745592image/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

vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontentsUnnamed: 8
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
14766711042628800.02225366506/mbnvod2/605/2013/03/04/20130304085625_20_605_1042628_360.mp4조간신문 브리핑【 앵커멘트 】<NA>
2오늘부터 저희 MBN이 조간신문이 보도한 주요 뉴스를 정리해 드리는 시간을 갖기로 했는데요.<NA><NA><NA><NA><NA><NA><NA><NA>
3가장 먼저, 매일경제 1면 보시겠습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51) 매일경제 1면입니다.<NA><NA><NA><NA><NA><NA><NA><NA>
6총사업비 31조 원이죠, 단군 이래 최대 개발 프로젝트라는 용산역세권 개발 사업이 기로에 처했는데요, 감사원이 오는 18일부터 용산 개발 사업에 대해 대규모 특별감사에 들어간다는 소식입니다.<NA><NA><NA><NA><NA><NA><NA><NA>
7감사원이 박근혜 정부 출범 이후 처음으로 용산 개발사업을 손대기로 한 것은 그만큼 사안이 심각하다고 판단했기 때문으로 보입니다.<NA><NA><NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA><NA><NA><NA>
vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontentsUnnamed: 8
51어제 오후 재개된 원내수석부대표 간 실무협상에서 의견접근을 이뤄 9개 항으로 된 합의문까지 만들어놓았지만, 막판 추인과정에서 의견이 엇갈려 접점을 찾지 못했습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
52<NA><NA><NA><NA><NA><NA><NA><NA><NA>
53여야 간 협상의 걸림돌은 종합유선방송국의 업무 이관 문제였습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
54<NA><NA><NA><NA><NA><NA><NA><NA><NA>
55새누리당이 '인허가권의 경우 방통위가 갖되, 법률 제개정권은 미래부가 갖도록 하자'고 제안한 데 대해 민주당이 반대하면서 결론을 내리지 못했습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
56<NA><NA><NA><NA><NA><NA><NA><NA><NA>
57하지만, 여야는 협상에서 IPTV의 경우 미래창조과학부로 이관하고, 위성방송은 방송통신위에 잔류하기로 합의한 것으로 알려졌습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
58<NA><NA><NA><NA><NA><NA><NA><NA><NA>
59또 농림축산부를 농림축산식품부로 변경하는 한편 원자력안전위원회를 독립기구로 하고, 중소기업청의 기능을 강화하는 동시에 중소기업청장을 국무회의에 배석하도록 하기로 의견을 모았습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
60<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontents# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>23