Overview

Dataset statistics

Number of variables9
Number of observations237
Missing cells1912
Missing cells (%)89.6%
Duplicate rows5
Duplicate rows (%)2.1%
Total size in memory17.9 KiB
Average record size in memory77.5 B

Variable types

Text4
Numeric4
Unsupported1

Dataset

Description샘플 데이터
AuthorMBN
URLhttps://kdx.kr/data/view/29831

Alerts

Dataset has 5 (2.1%) duplicate rowsDuplicates
play_sec is highly overall correlated with play_hour and 1 other fieldsHigh correlation
play_hour is highly overall correlated with play_sec and 1 other fieldsHigh correlation
file_size is highly overall correlated with play_sec and 1 other fieldsHigh correlation
vod_seq_no has 86 (36.3%) missing valuesMissing
bcast_seq_no has 227 (95.8%) missing valuesMissing
play_sec has 227 (95.8%) missing valuesMissing
play_hour has 227 (95.8%) missing valuesMissing
file_size has 227 (95.8%) missing valuesMissing
vod_path has 227 (95.8%) missing valuesMissing
title has 227 (95.8%) missing valuesMissing
contents has 227 (95.8%) missing valuesMissing
Unnamed: 8 has 237 (100.0%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-21 16:23:38.225012
Analysis finished2024-04-21 16:23:44.229703
Duration6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

vod_seq_no
Text

MISSING 

Distinct142
Distinct (%)94.0%
Missing86
Missing (%)36.3%
Memory size2.0 KiB
2024-04-22T01:23:44.933852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length95
Median length72
Mean length39.298013
Min length6

Characters and Unicode

Total characters5934
Distinct characters510
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)91.4%

Sample

1st row588417
2nd row 서울에 노란색 택시가 등장했습니다.
3rd row 법인택시도 아니고 개인택시도 아닌 이 노란색 택시는 국내 최초로 설립된 협동조합 택시인데요.
4th row 승차거부나 부당요금을 없애겠다고 다짐했습니다.
5th row 김수형 기자가 보도합니다.
ValueCountFrequency (%)
67
 
5.0%
▶ 18
 
1.4%
기자 16
 
1.2%
인터뷰 16
 
1.2%
있습니다 12
 
0.9%
유라시아 7
 
0.5%
이 7
 
0.5%
【 7
 
0.5%
】 7
 
0.5%
영상취재 6
 
0.5%
Other values (958) 1168
87.8%
2024-04-22T01:23:46.277627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1398
 
23.6%
. 123
 
2.1%
다 115
 
1.9%
이 99
 
1.7%
니 98
 
1.7%
시 90
 
1.5%
는 62
 
1.0%
의 61
 
1.0%
고 60
 
1.0%
에 60
 
1.0%
Other values (500) 3768
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3857
65.0%
Space Separator 1398
 
23.6%
Other Punctuation 269
 
4.5%
Decimal Number 213
 
3.6%
Lowercase Letter 83
 
1.4%
Uppercase Letter 40
 
0.7%
Open Punctuation 19
 
0.3%
Close Punctuation 19
 
0.3%
Dash Punctuation 18
 
0.3%
Other Symbol 18
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 115
 
3.0%
이 99
 
2.6%
니 98
 
2.5%
시 90
 
2.3%
는 62
 
1.6%
의 61
 
1.6%
고 60
 
1.6%
에 60
 
1.6%
기 58
 
1.5%
대 57
 
1.5%
Other values (441) 3097
80.3%
Lowercase Letter
ValueCountFrequency (%)
m 10
12.0%
n 8
 
9.6%
k 7
 
8.4%
o 7
 
8.4%
r 6
 
7.2%
c 6
 
7.2%
a 6
 
7.2%
s 4
 
4.8%
i 4
 
4.8%
h 4
 
4.8%
Other values (11) 21
25.3%
Other Punctuation
ValueCountFrequency (%)
. 123
45.7%
" 38
 
14.1%
, 34
 
12.6%
: 29
 
10.8%
/ 17
 
6.3%
' 9
 
3.3%
@ 6
 
2.2%
… 6
 
2.2%
· 4
 
1.5%
% 3
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 39
18.3%
0 39
18.3%
8 31
14.6%
2 24
11.3%
5 21
9.9%
3 16
7.5%
7 16
7.5%
4 12
 
5.6%
6 10
 
4.7%
9 5
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N 7
17.5%
B 7
17.5%
M 7
17.5%
A 5
12.5%
C 4
10.0%
P 4
10.0%
S 4
10.0%
T 1
 
2.5%
W 1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
【 7
36.8%
[ 6
31.6%
( 6
31.6%
Close Punctuation
ValueCountFrequency (%)
】 7
36.8%
] 6
31.6%
) 6
31.6%
Space Separator
ValueCountFrequency (%)
1398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Symbol
ValueCountFrequency (%)
▶ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3857
65.0%
Common 1954
32.9%
Latin 123
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 115
 
3.0%
이 99
 
2.6%
니 98
 
2.5%
시 90
 
2.3%
는 62
 
1.6%
의 61
 
1.6%
고 60
 
1.6%
에 60
 
1.6%
기 58
 
1.5%
대 57
 
1.5%
Other values (441) 3097
80.3%
Latin
ValueCountFrequency (%)
m 10
 
8.1%
n 8
 
6.5%
k 7
 
5.7%
o 7
 
5.7%
N 7
 
5.7%
B 7
 
5.7%
M 7
 
5.7%
r 6
 
4.9%
c 6
 
4.9%
a 6
 
4.9%
Other values (20) 52
42.3%
Common
ValueCountFrequency (%)
1398
71.5%
. 123
 
6.3%
1 39
 
2.0%
0 39
 
2.0%
" 38
 
1.9%
, 34
 
1.7%
8 31
 
1.6%
: 29
 
1.5%
2 24
 
1.2%
5 21
 
1.1%
Other values (19) 178
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3857
65.0%
ASCII 2035
34.3%
Geometric Shapes 18
 
0.3%
None 18
 
0.3%
Punctuation 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1398
68.7%
. 123
 
6.0%
1 39
 
1.9%
0 39
 
1.9%
" 38
 
1.9%
, 34
 
1.7%
8 31
 
1.5%
: 29
 
1.4%
2 24
 
1.2%
5 21
 
1.0%
Other values (44) 259
 
12.7%
Hangul
ValueCountFrequency (%)
다 115
 
3.0%
이 99
 
2.6%
니 98
 
2.5%
시 90
 
2.3%
는 62
 
1.6%
의 61
 
1.6%
고 60
 
1.6%
에 60
 
1.6%
기 58
 
1.5%
대 57
 
1.5%
Other values (441) 3097
80.3%
Geometric Shapes
ValueCountFrequency (%)
▶ 18
100.0%
None
ValueCountFrequency (%)
【 7
38.9%
】 7
38.9%
· 4
22.2%
Punctuation
ValueCountFrequency (%)
… 6
100.0%

bcast_seq_no
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)100.0%
Missing227
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean1100912.5
Minimum1100884
Maximum1100973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-22T01:23:46.647156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1100884
5-th percentile1100884.4
Q11100886.2
median1100888.5
Q31100950.8
95-th percentile1100972.6
Maximum1100973
Range89
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation41.099473
Coefficient of variation (CV)3.7332188 × 10-5
Kurtosis-1.22515
Mean1100912.5
Median Absolute Deviation (MAD)3
Skewness1.0284649
Sum11009125
Variance1689.1667
MonotonicityStrictly increasing
2024-04-22T01:23:46.997259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1100884 1
 
0.4%
1100885 1
 
0.4%
1100886 1
 
0.4%
1100887 1
 
0.4%
1100888 1
 
0.4%
1100889 1
 
0.4%
1100890 1
 
0.4%
1100971 1
 
0.4%
1100972 1
 
0.4%
1100973 1
 
0.4%
(Missing) 227
95.8%
ValueCountFrequency (%)
1100884 1
0.4%
1100885 1
0.4%
1100886 1
0.4%
1100887 1
0.4%
1100888 1
0.4%
1100889 1
0.4%
1100890 1
0.4%
1100971 1
0.4%
1100972 1
0.4%
1100973 1
0.4%
ValueCountFrequency (%)
1100973 1
0.4%
1100972 1
0.4%
1100971 1
0.4%
1100890 1
0.4%
1100889 1
0.4%
1100888 1
0.4%
1100887 1
0.4%
1100886 1
0.4%
1100885 1
0.4%
1100884 1
0.4%

play_sec
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)80.0%
Missing227
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean79.2
Minimum20
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-22T01:23:47.332588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20.45
Q138
median98.5
Q3105
95-th percentile119.4
Maximum123
Range103
Interquartile range (IQR)67

Descriptive statistics

Standard deviation41.480384
Coefficient of variation (CV)0.52374222
Kurtosis-1.2731476
Mean79.2
Median Absolute Deviation (MAD)13
Skewness-0.8314088
Sum792
Variance1720.6222
MonotonicityNot monotonic
2024-04-22T01:23:47.678330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
99 2
 
0.8%
21 2
 
0.8%
98 1
 
0.4%
89 1
 
0.4%
107 1
 
0.4%
20 1
 
0.4%
115 1
 
0.4%
123 1
 
0.4%
(Missing) 227
95.8%
ValueCountFrequency (%)
20 1
0.4%
21 2
0.8%
89 1
0.4%
98 1
0.4%
99 2
0.8%
107 1
0.4%
115 1
0.4%
123 1
0.4%
ValueCountFrequency (%)
123 1
0.4%
115 1
0.4%
107 1
0.4%
99 2
0.8%
98 1
0.4%
89 1
0.4%
21 2
0.8%
20 1
0.4%

play_hour
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)80.0%
Missing227
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean0.02199
Minimum0.0056
Maximum0.0342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-22T01:23:47.993603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0056
5-th percentile0.00569
Q10.010525
median0.02735
Q30.02915
95-th percentile0.033165
Maximum0.0342
Range0.0286
Interquartile range (IQR)0.018625

Descriptive statistics

Standard deviation0.011522003
Coefficient of variation (CV)0.52396558
Kurtosis-1.2729393
Mean0.02199
Median Absolute Deviation (MAD)0.0036
Skewness-0.83012866
Sum0.2199
Variance0.00013275656
MonotonicityNot monotonic
2024-04-22T01:23:48.327625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0275 2
 
0.8%
0.0058 2
 
0.8%
0.0272 1
 
0.4%
0.0247 1
 
0.4%
0.0297 1
 
0.4%
0.0056 1
 
0.4%
0.0319 1
 
0.4%
0.0342 1
 
0.4%
(Missing) 227
95.8%
ValueCountFrequency (%)
0.0056 1
0.4%
0.0058 2
0.8%
0.0247 1
0.4%
0.0272 1
0.4%
0.0275 2
0.8%
0.0297 1
0.4%
0.0319 1
0.4%
0.0342 1
0.4%
ValueCountFrequency (%)
0.0342 1
0.4%
0.0319 1
0.4%
0.0297 1
0.4%
0.0275 2
0.8%
0.0272 1
0.4%
0.0247 1
0.4%
0.0058 2
0.8%
0.0056 1
0.4%

file_size
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing227
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean12934689
Minimum3094308
Maximum20558238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-22T01:23:48.671144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3094308
5-th percentile3192738.3
Q16321855
median15846926
Q316856573
95-th percentile19953285
Maximum20558238
Range17463930
Interquartile range (IQR)10534718

Descriptive statistics

Standard deviation6849841.4
Coefficient of variation (CV)0.52957142
Kurtosis-1.2555113
Mean12934689
Median Absolute Deviation (MAD)2331330
Skewness-0.78249951
Sum1.2934689 × 108
Variance4.6920327 × 1013
MonotonicityNot monotonic
2024-04-22T01:23:49.035590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
15768640 1
 
0.4%
16302226 1
 
0.4%
14551239 1
 
0.4%
17041355 1
 
0.4%
3313042 1
 
0.4%
3578727 1
 
0.4%
3094308 1
 
0.4%
19213899 1
 
0.4%
15925212 1
 
0.4%
20558238 1
 
0.4%
(Missing) 227
95.8%
ValueCountFrequency (%)
3094308 1
0.4%
3313042 1
0.4%
3578727 1
0.4%
14551239 1
0.4%
15768640 1
0.4%
15925212 1
0.4%
16302226 1
0.4%
17041355 1
0.4%
19213899 1
0.4%
20558238 1
0.4%
ValueCountFrequency (%)
20558238 1
0.4%
19213899 1
0.4%
17041355 1
0.4%
16302226 1
0.4%
15925212 1
0.4%
15768640 1
0.4%
14551239 1
0.4%
3578727 1
0.4%
3313042 1
0.4%
3094308 1
0.4%

vod_path
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing227
Missing (%)95.8%
Memory size2.0 KiB
2024-04-22T01:23:49.768542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length61
Mean length61
Min length61

Characters and Unicode

Total characters610
Distinct characters20
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

Unique10 ?
Unique (%)100.0%

Sample

1st row/mbnvod2/689/2015/07/15/20150715104207_20_689_1100884_360.mp4
2nd row/mbnvod2/689/2015/07/15/20150715104602_20_689_1100885_360.mp4
3rd row/mbnvod2/689/2015/07/15/20150715104958_20_689_1100886_360.mp4
4th row/mbnvod2/689/2015/07/15/20150715105403_20_689_1100887_360.mp4
5th row/mbnvod2/689/2015/07/15/20150715105636_20_689_1100888_360.mp4
ValueCountFrequency (%)
mbnvod2/689/2015/07/15/20150715104207_20_689_1100884_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715104602_20_689_1100885_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715104958_20_689_1100886_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715105403_20_689_1100887_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715105636_20_689_1100888_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715105950_20_689_1100889_360.mp4 1
10.0%
mbnvod2/689/2015/07/15/20150715110205_20_689_1100890_360.mp4 1
10.0%
mbnvod2/689/2015/07/16/20150716105225_20_689_1100971_360.mp4 1
10.0%
mbnvod2/689/2015/07/16/20150716105602_20_689_1100972_360.mp4 1
10.0%
mbnvod2/689/2015/07/16/20150716105923_20_689_1100973_360.mp4 1
10.0%
2024-04-22T01:23:50.838401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97
15.9%
1 72
11.8%
/ 60
9.8%
2 48
7.9%
5 45
 
7.4%
6 41
 
6.7%
_ 40
 
6.6%
8 35
 
5.7%
9 28
 
4.6%
7 25
 
4.1%
Other values (10) 119
19.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
68.9%
Lowercase Letter 80
 
13.1%
Other Punctuation 70
 
11.5%
Connector Punctuation 40
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97
23.1%
1 72
17.1%
2 48
11.4%
5 45
10.7%
6 41
9.8%
8 35
 
8.3%
9 28
 
6.7%
7 25
 
6.0%
4 15
 
3.6%
3 14
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
m 20
25.0%
d 10
12.5%
o 10
12.5%
v 10
12.5%
n 10
12.5%
b 10
12.5%
p 10
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 60
85.7%
. 10
 
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 530
86.9%
Latin 80
 
13.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97
18.3%
1 72
13.6%
/ 60
11.3%
2 48
9.1%
5 45
8.5%
6 41
7.7%
_ 40
7.5%
8 35
 
6.6%
9 28
 
5.3%
7 25
 
4.7%
Other values (3) 39
7.4%
Latin
ValueCountFrequency (%)
m 20
25.0%
d 10
12.5%
o 10
12.5%
v 10
12.5%
n 10
12.5%
b 10
12.5%
p 10
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97
15.9%
1 72
11.8%
/ 60
9.8%
2 48
7.9%
5 45
 
7.4%
6 41
 
6.7%
_ 40
 
6.6%
8 35
 
5.7%
9 28
 
4.6%
7 25
 
4.1%
Other values (10) 119
19.5%

title
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing227
Missing (%)95.8%
Memory size2.0 KiB
2024-04-22T01:23:51.698959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27.5
Mean length26.2
Min length21

Characters and Unicode

Total characters262
Distinct characters127
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row노란색 택시 등장…"승차거부 없어요."
2nd row"공동육아가 혐오시설?"…주민 갈등에도 과천시 '수수방관'
3rd row400억대 불법 스포츠 사이트 일당 '덜미'
4th row[경북] '평화·통일 염원…유라시아 친선특급
5th row[경기] 국가건축정책위 '건축·도시정책 포럼' 개최
ValueCountFrequency (%)
부산 2
 
3.7%
경기 2
 
3.7%
노란색 1
 
1.9%
화백…두 1
 
1.9%
대전-충남 1
 
1.9%
지역 1
 
1.9%
공동 1
 
1.9%
현안 1
 
1.9%
해결 1
 
1.9%
상생협력협약 1
 
1.9%
Other values (42) 42
77.8%
2024-04-22T01:23:52.936077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
16.8%
' 11
 
4.2%
시 10
 
3.8%
… 6
 
2.3%
" 4
 
1.5%
[ 4
 
1.5%
기 4
 
1.5%
] 4
 
1.5%
부 4
 
1.5%
경 4
 
1.5%
Other values (117) 167
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
67.2%
Space Separator 44
 
16.8%
Other Punctuation 26
 
9.9%
Decimal Number 7
 
2.7%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10
 
5.7%
기 4
 
2.3%
부 4
 
2.3%
경 4
 
2.3%
아 4
 
2.3%
도 4
 
2.3%
산 4
 
2.3%
에 3
 
1.7%
일 3
 
1.7%
대 3
 
1.7%
Other values (102) 133
75.6%
Other Punctuation
ValueCountFrequency (%)
' 11
42.3%
… 6
23.1%
" 4
 
15.4%
· 3
 
11.5%
? 1
 
3.8%
. 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
5 1
 
14.3%
8 1
 
14.3%
6 1
 
14.3%
4 1
 
14.3%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 4
100.0%
Close Punctuation
ValueCountFrequency (%)
] 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
67.2%
Common 86
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10
 
5.7%
기 4
 
2.3%
부 4
 
2.3%
경 4
 
2.3%
아 4
 
2.3%
도 4
 
2.3%
산 4
 
2.3%
에 3
 
1.7%
일 3
 
1.7%
대 3
 
1.7%
Other values (102) 133
75.6%
Common
ValueCountFrequency (%)
44
51.2%
' 11
 
12.8%
… 6
 
7.0%
" 4
 
4.7%
[ 4
 
4.7%
] 4
 
4.7%
0 3
 
3.5%
· 3
 
3.5%
5 1
 
1.2%
- 1
 
1.2%
Other values (5) 5
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
67.2%
ASCII 77
29.4%
Punctuation 6
 
2.3%
None 3
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
57.1%
' 11
 
14.3%
" 4
 
5.2%
[ 4
 
5.2%
] 4
 
5.2%
0 3
 
3.9%
5 1
 
1.3%
- 1
 
1.3%
8 1
 
1.3%
6 1
 
1.3%
Other values (3) 3
 
3.9%
Hangul
ValueCountFrequency (%)
시 10
 
5.7%
기 4
 
2.3%
부 4
 
2.3%
경 4
 
2.3%
아 4
 
2.3%
도 4
 
2.3%
산 4
 
2.3%
에 3
 
1.7%
일 3
 
1.7%
대 3
 
1.7%
Other values (102) 133
75.6%
Punctuation
ValueCountFrequency (%)
… 6
100.0%
None
ValueCountFrequency (%)
· 3
100.0%

contents
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing227
Missing (%)95.8%
Memory size2.0 KiB
2024-04-22T01:23:53.675369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length8
Mean length21.6
Min length8

Characters and Unicode

Total characters216
Distinct characters87
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st row【 앵커논평 】
2nd row【 앵커멘트 】
3rd row【 앵커멘트 】
4th row【 앵커멘트 】
5th row경기도가 대통령직속 위원회인 국가건축정책위원회와 공동으로 첫 번째 건축·도시정책 포럼을 개최했습니다.
ValueCountFrequency (%)
【 7
 
12.5%
】 7
 
12.5%
앵커멘트 6
 
10.7%
손을 1
 
1.8%
지역 1
 
1.8%
활기를 1
 
1.8%
띤 1
 
1.8%
것으로 1
 
1.8%
나타났습니다 1
 
1.8%
대전광역시와 1
 
1.8%
Other values (29) 29
51.8%
2024-04-22T01:23:54.786390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
21.3%
【 7
 
3.2%
앵 7
 
3.2%
커 7
 
3.2%
】 7
 
3.2%
멘 6
 
2.8%
트 6
 
2.8%
도 4
 
1.9%
위 4
 
1.9%
을 4
 
1.9%
Other values (77) 118
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
70.4%
Space Separator 46
 
21.3%
Open Punctuation 7
 
3.2%
Close Punctuation 7
 
3.2%
Other Punctuation 4
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앵 7
 
4.6%
커 7
 
4.6%
멘 6
 
3.9%
트 6
 
3.9%
도 4
 
2.6%
위 4
 
2.6%
을 4
 
2.6%
기 4
 
2.6%
회 3
 
2.0%
니 3
 
2.0%
Other values (72) 104
68.4%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
46
100.0%
Open Punctuation
ValueCountFrequency (%)
【 7
100.0%
Close Punctuation
ValueCountFrequency (%)
】 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
70.4%
Common 64
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앵 7
 
4.6%
커 7
 
4.6%
멘 6
 
3.9%
트 6
 
3.9%
도 4
 
2.6%
위 4
 
2.6%
을 4
 
2.6%
기 4
 
2.6%
회 3
 
2.0%
니 3
 
2.0%
Other values (72) 104
68.4%
Common
ValueCountFrequency (%)
46
71.9%
【 7
 
10.9%
】 7
 
10.9%
. 3
 
4.7%
· 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
70.4%
ASCII 49
 
22.7%
None 15
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
93.9%
. 3
 
6.1%
None
ValueCountFrequency (%)
【 7
46.7%
】 7
46.7%
· 1
 
6.7%
Hangul
ValueCountFrequency (%)
앵 7
 
4.6%
커 7
 
4.6%
멘 6
 
3.9%
트 6
 
3.9%
도 4
 
2.6%
위 4
 
2.6%
을 4
 
2.6%
기 4
 
2.6%
회 3
 
2.0%
니 3
 
2.0%
Other values (72) 104
68.4%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing237
Missing (%)100.0%
Memory size2.2 KiB

Interactions

2024-04-22T01:23:42.077621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:38.946636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:40.116967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:41.084452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:42.322409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:39.176046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:40.349353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:41.323622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:42.567883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:39.620550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:40.584036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:41.568010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:42.824812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:39.864426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:40.829496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:23:41.818558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T01:23:55.047827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
bcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontents
bcast_seq_no1.0000.6160.6160.8571.0001.0000.000
play_sec0.6161.0001.0001.0001.0001.0000.000
play_hour0.6161.0001.0001.0001.0001.0000.000
file_size0.8571.0001.0001.0001.0001.0000.566
vod_path1.0001.0001.0001.0001.0001.0001.000
title1.0001.0001.0001.0001.0001.0001.000
contents0.0000.0000.0000.5661.0001.0001.000
2024-04-22T01:23:55.325624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
bcast_seq_noplay_secplay_hourfile_size
bcast_seq_no1.0000.2800.2800.261
play_sec0.2801.0001.0000.957
play_hour0.2801.0001.0000.957
file_size0.2610.9570.9571.000

Missing values

2024-04-22T01:23:43.183043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T01:23:43.627507image/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.
2024-04-22T01:23:43.993509image/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>
15884171100884990.027515768640/mbnvod2/689/2015/07/15/20150715104207_20_689_1100884_360.mp4노란색 택시 등장…"승차거부 없어요."【 앵커논평 】<NA>
2서울에 노란색 택시가 등장했습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
3법인택시도 아니고 개인택시도 아닌 이 노란색 택시는 국내 최초로 설립된 협동조합 택시인데요.<NA><NA><NA><NA><NA><NA><NA><NA>
4승차거부나 부당요금을 없애겠다고 다짐했습니다.<NA><NA><NA><NA><NA><NA><NA><NA>
5김수형 기자가 보도합니다.<NA><NA><NA><NA><NA><NA><NA><NA>
6<NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8【 기자 】<NA><NA><NA><NA><NA><NA><NA><NA>
9택시기사 정용준 씨.<NA><NA><NA><NA><NA><NA><NA><NA>
vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontentsUnnamed: 8
227대전시는 대전이 주도적으로 만든 세계과학도시연합, WTA를 함께 개최해 과학도시로서의 위상을 높일 계획입니다.<NA><NA><NA><NA><NA><NA><NA><NA>
228<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2292천7백억 원에 달하는 경제 파급 효과와 미래 성장동력으로 부상한 전시회의 산업도 활성화될 것으로 기대됩니다.<NA><NA><NA><NA><NA><NA><NA><NA>
230<NA><NA><NA><NA><NA><NA><NA><NA><NA>
231▶ 스탠딩 : 이상곤 / 기자<NA><NA><NA><NA><NA><NA><NA><NA>
232- "강력한 경쟁도시들을 제치고 대규모 국제대회 유치에 성공함에 따라 대전은 세계가 주목하는 국제도시로서의 위상을 한 단계 더 높이게 됐습니다. MBN뉴스 이상곤입니다."<NA><NA><NA><NA><NA><NA><NA><NA>
233[ lsk9017@mbn.co.kr ]<NA><NA><NA><NA><NA><NA><NA><NA>
234영상취재 : 박인학 기자<NA><NA><NA><NA><NA><NA><NA><NA>
235영상편집 : 김경준<NA><NA><NA><NA><NA><NA><NA><NA>
236<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

vod_seq_nobcast_seq_noplay_secplay_hourfile_sizevod_pathtitlecontents# duplicates
4<NA><NA><NA><NA><NA><NA><NA><NA>86
3【 기자 】<NA><NA><NA><NA><NA><NA><NA>7
0영상편집 : 김경준<NA><NA><NA><NA><NA><NA><NA>2
1영상편집 : 한남선<NA><NA><NA><NA><NA><NA><NA>2
2▶ 인터뷰 : 그라함 쿽 / 호주 브리즈번 시장<NA><NA><NA><NA><NA><NA><NA>2