Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory160.0 B

Variable types

Numeric7
Text6
Categorical2
Boolean1
DateTime2

Dataset

DescriptionKTV 국민방송에서 방송된 정책공공 프로그램 방송 목록으로 제목,프로그램명,방송일,링크주소 등의 데이터를 제공합니다.
Author문화체육관광부 한국정책방송원
URLhttps://www.data.go.kr/data/15050738/fileData.do

Alerts

카테고리아이디 has constant value ""Constant
카테고리명 has constant value ""Constant
콘텐츠아이디 is highly overall correlated with 조회수High correlation
조회수 is highly overall correlated with 콘텐츠아이디High correlation
조회수 is highly skewed (γ1 = 21.34096037)Skewed
콘텐츠아이디 has unique valuesUnique
링크주소 has unique valuesUnique
팝업링크주소 has unique valuesUnique
방송시간(시) has 624 (6.2%) zerosZeros
방송시간(분) has 2882 (28.8%) zerosZeros
재생시간(초) has 233 (2.3%) zerosZeros

Reproduction

Analysis started2024-04-21 01:16:13.783082
Analysis finished2024-04-21 01:16:22.391494
Duration8.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

콘텐츠아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean593636.16
Minimum516477
Maximum698367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:22.471621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum516477
5-th percentile521990.45
Q1544053
median587952
Q3636490.5
95-th percentile687764.2
Maximum698367
Range181890
Interquartile range (IQR)92437.5

Descriptive statistics

Standard deviation53530.171
Coefficient of variation (CV)0.090173368
Kurtosis-1.1188488
Mean593636.16
Median Absolute Deviation (MAD)45912.5
Skewness0.32343952
Sum5.9363616 × 109
Variance2.8654792 × 109
MonotonicityNot monotonic
2024-04-21T10:16:22.618919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
583577 1
 
< 0.1%
601815 1
 
< 0.1%
541781 1
 
< 0.1%
594488 1
 
< 0.1%
530558 1
 
< 0.1%
594422 1
 
< 0.1%
683275 1
 
< 0.1%
616400 1
 
< 0.1%
566725 1
 
< 0.1%
557894 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
516477 1
< 0.1%
516493 1
< 0.1%
516507 1
< 0.1%
516513 1
< 0.1%
516514 1
< 0.1%
516515 1
< 0.1%
516516 1
< 0.1%
516517 1
< 0.1%
516521 1
< 0.1%
516522 1
< 0.1%
ValueCountFrequency (%)
698367 1
< 0.1%
698366 1
< 0.1%
698363 1
< 0.1%
698361 1
< 0.1%
698360 1
< 0.1%
698359 1
< 0.1%
698354 1
< 0.1%
698344 1
< 0.1%
698343 1
< 0.1%
698289 1
< 0.1%

제목
Text

Distinct8938
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:22.971176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length104
Median length93
Mean length25.7081
Min length2

Characters and Unicode

Total characters257081
Distinct characters1324
Distinct categories17 ?
Distinct scripts4 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8205 ?
Unique (%)82.0%

Sample

1st row열린소통포럼···1인 가구에 필요한 정책은?
2nd row소녀주의보 그리고 한 남자, 청소년들과 1%의 희망나누기
3rd row"아픈 식물 치료해요"…사이버식물병원 인기
4th row5·18, 38년 통곡의 '한'
5th row포항 지진 피해현장에 가다
ValueCountFrequency (%)
749
 
1.2%
브리핑 589
 
1.0%
대통령 487
 
0.8%
문 391
 
0.7%
톡톡 334
 
0.6%
사이다경제 322
 
0.5%
정책 247
 
0.4%
코로나19 241
 
0.4%
속 223
 
0.4%
인기 220
 
0.4%
Other values (21893) 56226
93.7%
2024-04-21T10:16:23.429201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50055
 
19.5%
· 5463
 
2.1%
' 4507
 
1.8%
이 3026
 
1.2%
대 3018
 
1.2%
의 2800
 
1.1%
1 2423
 
0.9%
기 2347
 
0.9%
회 2269
 
0.9%
한 2238
 
0.9%
Other values (1314) 178935
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168999
65.7%
Space Separator 50055
 
19.5%
Other Punctuation 18163
 
7.1%
Decimal Number 10781
 
4.2%
Close Punctuation 2484
 
1.0%
Open Punctuation 2482
 
1.0%
Uppercase Letter 1871
 
0.7%
Dash Punctuation 778
 
0.3%
Math Symbol 640
 
0.2%
Lowercase Letter 403
 
0.2%
Other values (7) 425
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3026
 
1.8%
대 3018
 
1.8%
의 2800
 
1.7%
기 2347
 
1.4%
회 2269
 
1.3%
한 2238
 
1.3%
사 2130
 
1.3%
정 2058
 
1.2%
인 2032
 
1.2%
로 2015
 
1.2%
Other values (1205) 145066
85.8%
Uppercase Letter
ValueCountFrequency (%)
K 320
17.1%
T 279
14.9%
V 221
11.8%
S 100
 
5.3%
I 95
 
5.1%
A 89
 
4.8%
O 86
 
4.6%
C 81
 
4.3%
D 78
 
4.2%
N 69
 
3.7%
Other values (16) 453
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 75
18.6%
t 44
10.9%
o 38
 
9.4%
a 34
 
8.4%
f 29
 
7.2%
m 23
 
5.7%
i 18
 
4.5%
s 16
 
4.0%
n 16
 
4.0%
r 15
 
3.7%
Other values (15) 95
23.6%
Other Punctuation
ValueCountFrequency (%)
· 5463
30.1%
' 4507
24.8%
, 2038
 
11.2%
" 1583
 
8.7%
. 1484
 
8.2%
! 1063
 
5.9%
… 847
 
4.7%
? 667
 
3.7%
& 276
 
1.5%
/ 195
 
1.1%
Other values (4) 40
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 2423
22.5%
2 1897
17.6%
0 1705
15.8%
3 832
 
7.7%
4 757
 
7.0%
9 746
 
6.9%
5 661
 
6.1%
6 606
 
5.6%
8 581
 
5.4%
7 573
 
5.3%
Math Symbol
ValueCountFrequency (%)
< 245
38.3%
> 245
38.3%
~ 106
16.6%
+ 39
 
6.1%
= 2
 
0.3%
→ 2
 
0.3%
∼ 1
 
0.2%
Other Symbol
ValueCountFrequency (%)
★ 5
41.7%
☆ 2
 
16.7%
♥ 2
 
16.7%
㎞ 2
 
16.7%
♬ 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 2053
82.6%
] 427
 
17.2%
」 3
 
0.1%
』 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2052
82.7%
[ 426
 
17.2%
「 3
 
0.1%
『 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
33.3%
Ⅱ 2
33.3%
Ⅵ 1
16.7%
Ⅳ 1
16.7%
Final Punctuation
ValueCountFrequency (%)
’ 234
94.7%
” 13
 
5.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 112
75.2%
“ 37
 
24.8%
Other Number
ValueCountFrequency (%)
② 2
66.7%
① 1
33.3%
Space Separator
ValueCountFrequency (%)
50055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 778
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168815
65.7%
Common 85802
33.4%
Latin 2280
 
0.9%
Han 184
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3026
 
1.8%
대 3018
 
1.8%
의 2800
 
1.7%
기 2347
 
1.4%
회 2269
 
1.3%
한 2238
 
1.3%
사 2130
 
1.3%
정 2058
 
1.2%
인 2032
 
1.2%
로 2015
 
1.2%
Other values (1167) 144882
85.8%
Latin
ValueCountFrequency (%)
K 320
 
14.0%
T 279
 
12.2%
V 221
 
9.7%
S 100
 
4.4%
I 95
 
4.2%
A 89
 
3.9%
O 86
 
3.8%
C 81
 
3.6%
D 78
 
3.4%
e 75
 
3.3%
Other values (45) 856
37.5%
Common
ValueCountFrequency (%)
50055
58.3%
· 5463
 
6.4%
' 4507
 
5.3%
1 2423
 
2.8%
) 2053
 
2.4%
( 2052
 
2.4%
, 2038
 
2.4%
2 1897
 
2.2%
0 1705
 
2.0%
" 1583
 
1.8%
Other values (44) 12026
 
14.0%
Han
ValueCountFrequency (%)
美 81
44.0%
北 16
 
8.7%
靑 13
 
7.1%
日 9
 
4.9%
前 7
 
3.8%
新 7
 
3.8%
故 6
 
3.3%
史 3
 
1.6%
中 3
 
1.6%
之 2
 
1.1%
Other values (28) 37
20.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168791
65.7%
ASCII 81341
31.6%
None 5471
 
2.1%
Punctuation 1246
 
0.5%
CJK 178
 
0.1%
Compat Jamo 24
 
< 0.1%
Misc Symbols 10
 
< 0.1%
Number Forms 6
 
< 0.1%
CJK Compat Ideographs 6
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50055
61.5%
' 4507
 
5.5%
1 2423
 
3.0%
) 2053
 
2.5%
( 2052
 
2.5%
, 2038
 
2.5%
2 1897
 
2.3%
0 1705
 
2.1%
" 1583
 
1.9%
. 1484
 
1.8%
Other values (74) 11544
 
14.2%
None
ValueCountFrequency (%)
· 5463
99.9%
」 3
 
0.1%
「 3
 
0.1%
『 1
 
< 0.1%
』 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
이 3026
 
1.8%
대 3018
 
1.8%
의 2800
 
1.7%
기 2347
 
1.4%
회 2269
 
1.3%
한 2238
 
1.3%
사 2130
 
1.3%
정 2058
 
1.2%
인 2032
 
1.2%
로 2015
 
1.2%
Other values (1164) 144858
85.8%
Punctuation
ValueCountFrequency (%)
… 847
68.0%
’ 234
 
18.8%
‘ 112
 
9.0%
“ 37
 
3.0%
” 13
 
1.0%
※ 2
 
0.2%
‥ 1
 
0.1%
CJK
ValueCountFrequency (%)
美 81
45.5%
北 16
 
9.0%
靑 13
 
7.3%
日 9
 
5.1%
前 7
 
3.9%
新 7
 
3.9%
故 6
 
3.4%
史 3
 
1.7%
中 3
 
1.7%
之 2
 
1.1%
Other values (24) 31
 
17.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 16
66.7%
ㅎ 7
29.2%
ㅅ 1
 
4.2%
Misc Symbols
ValueCountFrequency (%)
★ 5
50.0%
☆ 2
 
20.0%
♥ 2
 
20.0%
♬ 1
 
10.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
33.3%
Ⅱ 2
33.3%
Ⅵ 1
16.7%
Ⅳ 1
16.7%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
66.7%
① 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
老 2
33.3%
樂 2
33.3%
不 1
16.7%
黎 1
16.7%
CJK Compat
ValueCountFrequency (%)
㎞ 2
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

프로그램아이디
Text

Distinct168
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:23.685700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
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

Unique11 ?
Unique (%)0.1%

Sample

1st rowPG2150012D
2nd rowPG2190002D
3rd rowPG2150012D
4th rowPG2140026D
5th rowPG2150012D
ValueCountFrequency (%)
pg2150012d 4119
41.2%
pg2170035d 524
 
5.2%
pg2160034d 442
 
4.4%
pg2170027d 378
 
3.8%
pg1110705d 374
 
3.7%
pg2190015d 325
 
3.2%
pg2190058d 241
 
2.4%
pg2220021d 171
 
1.7%
pg2130038d 159
 
1.6%
pg1110975d 144
 
1.4%
Other values (158) 3123
31.2%
2024-04-21T10:16:24.038951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20424
20.4%
2 16651
16.7%
1 15865
15.9%
P 10000
10.0%
G 10000
10.0%
D 10000
10.0%
5 6844
 
6.8%
7 2674
 
2.7%
3 2012
 
2.0%
8 1467
 
1.5%
Other values (3) 4063
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70000
70.0%
Uppercase Letter 30000
30.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20424
29.2%
2 16651
23.8%
1 15865
22.7%
5 6844
 
9.8%
7 2674
 
3.8%
3 2012
 
2.9%
8 1467
 
2.1%
4 1398
 
2.0%
6 1386
 
2.0%
9 1279
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
P 10000
33.3%
G 10000
33.3%
D 10000
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
70.0%
Latin 30000
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20424
29.2%
2 16651
23.8%
1 15865
22.7%
5 6844
 
9.8%
7 2674
 
3.8%
3 2012
 
2.9%
8 1467
 
2.1%
4 1398
 
2.0%
6 1386
 
2.0%
9 1279
 
1.8%
Latin
ValueCountFrequency (%)
P 10000
33.3%
G 10000
33.3%
D 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20424
20.4%
2 16651
16.7%
1 15865
15.9%
P 10000
10.0%
G 10000
10.0%
D 10000
10.0%
5 6844
 
6.8%
7 2674
 
2.7%
3 2012
 
2.0%
8 1467
 
1.5%
Other values (3) 4063
 
4.1%

프로그램명
Text

Distinct168
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:24.352482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length7.0911
Min length3

Characters and Unicode

Total characters70911
Distinct characters353
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row국민리포트
2nd row시청자에세이 날려라 하이킥
3rd row국민리포트
4th rowPD리포트 이슈 본(本)
5th row국민리포트
ValueCountFrequency (%)
국민리포트 4278
24.7%
브리핑 603
 
3.5%
ktv 568
 
3.3%
문워크 533
 
3.1%
4시 442
 
2.6%
국민소통 378
 
2.2%
1번가 378
 
2.2%
정책브리핑 374
 
2.2%
톡톡 359
 
2.1%
시즌2 327
 
1.9%
Other values (298) 9059
52.4%
2024-04-21T10:16:25.048516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7299
 
10.3%
리 5909
 
8.3%
국 5027
 
7.1%
민 4873
 
6.9%
트 4617
 
6.5%
포 4509
 
6.4%
정 1315
 
1.9%
이 1119
 
1.6%
책 1056
 
1.5%
핑 1007
 
1.4%
Other values (343) 34180
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56786
80.1%
Space Separator 7299
 
10.3%
Uppercase Letter 2750
 
3.9%
Decimal Number 1990
 
2.8%
Other Punctuation 1068
 
1.5%
Lowercase Letter 480
 
0.7%
Open Punctuation 177
 
0.2%
Close Punctuation 177
 
0.2%
Math Symbol 129
 
0.2%
Dash Punctuation 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 5909
 
10.4%
국 5027
 
8.9%
민 4873
 
8.6%
트 4617
 
8.1%
포 4509
 
7.9%
정 1315
 
2.3%
이 1119
 
2.0%
책 1056
 
1.9%
핑 1007
 
1.8%
브 977
 
1.7%
Other values (293) 26377
46.4%
Uppercase Letter
ValueCountFrequency (%)
K 641
23.3%
T 633
23.0%
V 633
23.0%
O 182
 
6.6%
D 145
 
5.3%
P 143
 
5.2%
N 138
 
5.0%
W 129
 
4.7%
J 23
 
0.8%
B 23
 
0.8%
Other values (7) 60
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 502
25.2%
1 466
23.4%
4 449
22.6%
0 274
13.8%
3 114
 
5.7%
5 92
 
4.6%
6 32
 
1.6%
8 31
 
1.6%
7 16
 
0.8%
9 14
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
e 78
16.2%
s 59
12.3%
n 57
11.9%
i 56
11.7%
u 50
10.4%
t 50
10.4%
m 41
8.5%
r 34
7.1%
o 28
 
5.8%
a 27
 
5.6%
Other Punctuation
ValueCountFrequency (%)
& 612
57.3%
! 167
 
15.6%
' 83
 
7.8%
, 77
 
7.2%
? 69
 
6.5%
. 60
 
5.6%
Math Symbol
ValueCountFrequency (%)
+ 128
99.2%
~ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
7299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56646
79.9%
Common 10895
 
15.4%
Latin 3230
 
4.6%
Han 140
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 5909
 
10.4%
국 5027
 
8.9%
민 4873
 
8.6%
트 4617
 
8.2%
포 4509
 
8.0%
정 1315
 
2.3%
이 1119
 
2.0%
책 1056
 
1.9%
핑 1007
 
1.8%
브 977
 
1.7%
Other values (291) 26237
46.3%
Latin
ValueCountFrequency (%)
K 641
19.8%
T 633
19.6%
V 633
19.6%
O 182
 
5.6%
D 145
 
4.5%
P 143
 
4.4%
N 138
 
4.3%
W 129
 
4.0%
e 78
 
2.4%
s 59
 
1.8%
Other values (17) 449
13.9%
Common
ValueCountFrequency (%)
7299
67.0%
& 612
 
5.6%
2 502
 
4.6%
1 466
 
4.3%
4 449
 
4.1%
0 274
 
2.5%
( 177
 
1.6%
) 177
 
1.6%
! 167
 
1.5%
+ 128
 
1.2%
Other values (13) 644
 
5.9%
Han
ValueCountFrequency (%)
本 131
93.6%
人 9
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56646
79.9%
ASCII 14101
 
19.9%
CJK 140
 
0.2%
Letterlike Symbols 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7299
51.8%
K 641
 
4.5%
T 633
 
4.5%
V 633
 
4.5%
& 612
 
4.3%
2 502
 
3.6%
1 466
 
3.3%
4 449
 
3.2%
0 274
 
1.9%
O 182
 
1.3%
Other values (39) 2410
 
17.1%
Hangul
ValueCountFrequency (%)
리 5909
 
10.4%
국 5027
 
8.9%
민 4873
 
8.6%
트 4617
 
8.2%
포 4509
 
8.0%
정 1315
 
2.3%
이 1119
 
2.0%
책 1056
 
1.9%
핑 1007
 
1.8%
브 977
 
1.7%
Other values (291) 26237
46.3%
CJK
ValueCountFrequency (%)
本 131
93.6%
人 9
 
6.4%
Letterlike Symbols
ValueCountFrequency (%)
℃ 24
100.0%

카테고리아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
100109
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100109
2nd row100109
3rd row100109
4th row100109
5th row100109

Common Values

ValueCountFrequency (%)
100109 10000
100.0%

Length

2024-04-21T10:16:25.163476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:16:25.244329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100109 10000
100.0%

카테고리명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정책공공
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정책공공 10000
100.0%

Length

2024-04-21T10:16:25.326042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:16:25.401463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정책공공 10000
100.0%

전체영상여부
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
5299 
False
4701 
ValueCountFrequency (%)
True 5299
53.0%
False 4701
47.0%
2024-04-21T10:16:25.466922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

섬네일주소
Text

Distinct9993
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:25.690394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length68
Mean length68.1269
Min length68

Characters and Unicode

Total characters681269
Distinct characters66
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

Unique9986 ?
Unique (%)99.9%

Sample

1st rowhttps://www.ktv.go.kr/media/contents/image/2019/09/24/e0xP7q2mmz.jpg
2nd rowhttps://www.ktv.go.kr/media/contents/image/2019/01/30/wUj1ezxhre.jpg
3rd rowhttps://www.ktv.go.kr/media/contents/image/2017/02/24/GGNfF20q4V.jpg
4th rowhttps://www.ktv.go.kr/media/contents/image/2018/05/20/rClFpde9vL.jpg
5th rowhttps://www.ktv.go.kr/media/contents/image/2017/11/20/8IXAYlXqDt.jpg
ValueCountFrequency (%)
https://www.ktv.go.kr/media/contents/image/2019/09/18/d2agme1f6s.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/08/17/e2hicz8rcm.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/09/13/f6pfiqzhob.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/04/25/ikegguzvet.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2019/09/18/sxzre1rd0k.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/06/20/binopuewzs.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/06/21/fkn7rqvtma.jpg 2
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2020/03/03/qyas0vz9vx.jpg 1
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2018/07/20/qo5ndxzlfz.jpg 1
 
< 0.1%
https://www.ktv.go.kr/media/contents/image/2019/09/24/e0xp7q2mmz.jpg 1
 
< 0.1%
Other values (9983) 9983
99.8%
2024-04-21T10:16:26.028293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 89859
 
13.2%
t 51620
 
7.6%
. 40141
 
5.9%
g 31647
 
4.6%
w 31646
 
4.6%
e 31595
 
4.6%
0 24761
 
3.6%
2 23282
 
3.4%
m 21904
 
3.2%
o 21896
 
3.2%
Other values (56) 312918
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 403159
59.2%
Other Punctuation 140000
 
20.5%
Decimal Number 96283
 
14.1%
Uppercase Letter 41263
 
6.1%
Connector Punctuation 564
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 51620
12.8%
g 31647
 
7.8%
w 31646
 
7.8%
e 31595
 
7.8%
m 21904
 
5.4%
o 21896
 
5.4%
p 21783
 
5.4%
a 21740
 
5.4%
k 21680
 
5.4%
n 21596
 
5.4%
Other values (16) 126052
31.3%
Uppercase Letter
ValueCountFrequency (%)
R 1662
 
4.0%
D 1639
 
4.0%
B 1637
 
4.0%
I 1624
 
3.9%
X 1615
 
3.9%
Y 1608
 
3.9%
U 1602
 
3.9%
Q 1601
 
3.9%
L 1598
 
3.9%
T 1594
 
3.9%
Other values (16) 25083
60.8%
Decimal Number
ValueCountFrequency (%)
0 24761
25.7%
2 23282
24.2%
1 16971
17.6%
3 5104
 
5.3%
7 5040
 
5.2%
8 4731
 
4.9%
6 4597
 
4.8%
9 4587
 
4.8%
4 3696
 
3.8%
5 3514
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/ 89859
64.2%
. 40141
28.7%
: 10000
 
7.1%
Connector Punctuation
ValueCountFrequency (%)
_ 564
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 444422
65.2%
Common 236847
34.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 51620
 
11.6%
g 31647
 
7.1%
w 31646
 
7.1%
e 31595
 
7.1%
m 21904
 
4.9%
o 21896
 
4.9%
p 21783
 
4.9%
a 21740
 
4.9%
k 21680
 
4.9%
n 21596
 
4.9%
Other values (42) 167315
37.6%
Common
ValueCountFrequency (%)
/ 89859
37.9%
. 40141
16.9%
0 24761
 
10.5%
2 23282
 
9.8%
1 16971
 
7.2%
: 10000
 
4.2%
3 5104
 
2.2%
7 5040
 
2.1%
8 4731
 
2.0%
6 4597
 
1.9%
Other values (4) 12361
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 681269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 89859
 
13.2%
t 51620
 
7.6%
. 40141
 
5.9%
g 31647
 
4.6%
w 31646
 
4.6%
e 31595
 
4.6%
0 24761
 
3.6%
2 23282
 
3.4%
m 21904
 
3.2%
o 21896
 
3.2%
Other values (56) 312918
45.9%

링크주소
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:26.256837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length52
Mean length52
Min length52

Characters and Unicode

Total characters520000
Distinct characters31
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

Unique10000 ?
Unique (%)100.0%

Sample

1st rowhttps://www.ktv.go.kr/content/view?content_id=583577
2nd rowhttps://www.ktv.go.kr/content/view?content_id=569413
3rd rowhttps://www.ktv.go.kr/content/view?content_id=533316
4th rowhttps://www.ktv.go.kr/content/view?content_id=554106
5th rowhttps://www.ktv.go.kr/content/view?content_id=545196
ValueCountFrequency (%)
https://www.ktv.go.kr/content/view?content_id=583577 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=616400 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=557620 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=620137 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=541781 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=594488 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=530558 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=594422 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=683275 1
 
< 0.1%
https://www.ktv.go.kr/content/view?content_id=601815 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-21T10:16:26.594212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 70000
 
13.5%
/ 40000
 
7.7%
w 40000
 
7.7%
n 40000
 
7.7%
e 30000
 
5.8%
. 30000
 
5.8%
o 30000
 
5.8%
i 20000
 
3.8%
k 20000
 
3.8%
v 20000
 
3.8%
Other values (21) 180000
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 350000
67.3%
Other Punctuation 90000
 
17.3%
Decimal Number 60000
 
11.5%
Math Symbol 10000
 
1.9%
Connector Punctuation 10000
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 70000
20.0%
w 40000
11.4%
n 40000
11.4%
e 30000
8.6%
o 30000
8.6%
i 20000
 
5.7%
k 20000
 
5.7%
v 20000
 
5.7%
c 20000
 
5.7%
d 10000
 
2.9%
Other values (5) 50000
14.3%
Decimal Number
ValueCountFrequency (%)
5 10522
17.5%
6 9303
15.5%
3 5412
9.0%
2 5412
9.0%
4 5225
8.7%
7 5045
8.4%
8 4955
8.3%
9 4816
8.0%
1 4760
7.9%
0 4550
7.6%
Other Punctuation
ValueCountFrequency (%)
/ 40000
44.4%
. 30000
33.3%
? 10000
 
11.1%
: 10000
 
11.1%
Math Symbol
ValueCountFrequency (%)
= 10000
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 350000
67.3%
Common 170000
32.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 40000
23.5%
. 30000
17.6%
5 10522
 
6.2%
= 10000
 
5.9%
_ 10000
 
5.9%
? 10000
 
5.9%
: 10000
 
5.9%
6 9303
 
5.5%
3 5412
 
3.2%
2 5412
 
3.2%
Other values (6) 29351
17.3%
Latin
ValueCountFrequency (%)
t 70000
20.0%
w 40000
11.4%
n 40000
11.4%
e 30000
8.6%
o 30000
8.6%
i 20000
 
5.7%
k 20000
 
5.7%
v 20000
 
5.7%
c 20000
 
5.7%
d 10000
 
2.9%
Other values (5) 50000
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 520000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 70000
 
13.5%
/ 40000
 
7.7%
w 40000
 
7.7%
n 40000
 
7.7%
e 30000
 
5.8%
. 30000
 
5.8%
o 30000
 
5.8%
i 20000
 
3.8%
k 20000
 
3.8%
v 20000
 
3.8%
Other values (21) 180000
34.6%

팝업링크주소
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:16:26.835170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length53
Mean length53
Min length53

Characters and Unicode

Total characters530000
Distinct characters32
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

Unique10000 ?
Unique (%)100.0%

Sample

1st rowhttps://www.ktv.go.kr/content/popup?content_id=583577
2nd rowhttps://www.ktv.go.kr/content/popup?content_id=569413
3rd rowhttps://www.ktv.go.kr/content/popup?content_id=533316
4th rowhttps://www.ktv.go.kr/content/popup?content_id=554106
5th rowhttps://www.ktv.go.kr/content/popup?content_id=545196
ValueCountFrequency (%)
https://www.ktv.go.kr/content/popup?content_id=583577 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=616400 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=557620 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=620137 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=541781 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=594488 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=530558 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=594422 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=683275 1
 
< 0.1%
https://www.ktv.go.kr/content/popup?content_id=601815 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-21T10:16:27.147655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 70000
 
13.2%
o 40000
 
7.5%
p 40000
 
7.5%
n 40000
 
7.5%
/ 40000
 
7.5%
w 30000
 
5.7%
. 30000
 
5.7%
e 20000
 
3.8%
c 20000
 
3.8%
k 20000
 
3.8%
Other values (22) 180000
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 360000
67.9%
Other Punctuation 90000
 
17.0%
Decimal Number 60000
 
11.3%
Connector Punctuation 10000
 
1.9%
Math Symbol 10000
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 70000
19.4%
o 40000
11.1%
p 40000
11.1%
n 40000
11.1%
w 30000
8.3%
e 20000
 
5.6%
c 20000
 
5.6%
k 20000
 
5.6%
i 10000
 
2.8%
d 10000
 
2.8%
Other values (6) 60000
16.7%
Decimal Number
ValueCountFrequency (%)
5 10522
17.5%
6 9303
15.5%
3 5412
9.0%
2 5412
9.0%
4 5225
8.7%
7 5045
8.4%
8 4955
8.3%
9 4816
8.0%
1 4760
7.9%
0 4550
7.6%
Other Punctuation
ValueCountFrequency (%)
/ 40000
44.4%
. 30000
33.3%
? 10000
 
11.1%
: 10000
 
11.1%
Connector Punctuation
ValueCountFrequency (%)
_ 10000
100.0%
Math Symbol
ValueCountFrequency (%)
= 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 360000
67.9%
Common 170000
32.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 70000
19.4%
o 40000
11.1%
p 40000
11.1%
n 40000
11.1%
w 30000
8.3%
e 20000
 
5.6%
c 20000
 
5.6%
k 20000
 
5.6%
i 10000
 
2.8%
d 10000
 
2.8%
Other values (6) 60000
16.7%
Common
ValueCountFrequency (%)
/ 40000
23.5%
. 30000
17.6%
5 10522
 
6.2%
_ 10000
 
5.9%
? 10000
 
5.9%
= 10000
 
5.9%
: 10000
 
5.9%
6 9303
 
5.5%
3 5412
 
3.2%
2 5412
 
3.2%
Other values (6) 29351
17.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 530000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 70000
 
13.2%
o 40000
 
7.5%
p 40000
 
7.5%
n 40000
 
7.5%
/ 40000
 
7.5%
w 30000
 
5.7%
. 30000
 
5.7%
e 20000
 
3.8%
c 20000
 
3.8%
k 20000
 
3.8%
Other values (22) 180000
34.0%

조회수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1757
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean431.4803
Minimum1
Maximum46448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:27.281912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22
Q158
median207
Q3540
95-th percentile1500.05
Maximum46448
Range46447
Interquartile range (IQR)482

Descriptive statistics

Standard deviation851.73808
Coefficient of variation (CV)1.9739907
Kurtosis943.57363
Mean431.4803
Median Absolute Deviation (MAD)167
Skewness21.34096
Sum4314803
Variance725457.76
MonotonicityNot monotonic
2024-04-21T10:16:27.397440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 74
 
0.7%
47 72
 
0.7%
42 71
 
0.7%
45 70
 
0.7%
52 69
 
0.7%
50 68
 
0.7%
46 65
 
0.7%
30 64
 
0.6%
54 64
 
0.6%
39 62
 
0.6%
Other values (1747) 9321
93.2%
ValueCountFrequency (%)
1 3
 
< 0.1%
2 3
 
< 0.1%
3 5
 
0.1%
4 8
 
0.1%
5 7
 
0.1%
6 12
0.1%
7 17
0.2%
8 14
0.1%
9 28
0.3%
10 17
0.2%
ValueCountFrequency (%)
46448 1
< 0.1%
21544 1
< 0.1%
17619 1
< 0.1%
17323 1
< 0.1%
15515 1
< 0.1%
11913 1
< 0.1%
10600 1
< 0.1%
9885 1
< 0.1%
9622 1
< 0.1%
8765 1
< 0.1%

프로그램회차
Real number (ℝ)

Distinct2148
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean667.1853
Minimum1
Maximum2267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:27.522284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q198
median435.5
Q31144.25
95-th percentile1932.05
Maximum2267
Range2266
Interquartile range (IQR)1046.25

Descriptive statistics

Standard deviation645.55433
Coefficient of variation (CV)0.96757876
Kurtosis-0.62815721
Mean667.1853
Median Absolute Deviation (MAD)395.5
Skewness0.77905986
Sum6671853
Variance416740.39
MonotonicityNot monotonic
2024-04-21T10:16:27.633843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 71
 
0.7%
11 59
 
0.6%
2 57
 
0.6%
4 56
 
0.6%
16 53
 
0.5%
3 53
 
0.5%
15 52
 
0.5%
6 52
 
0.5%
19 51
 
0.5%
10 50
 
0.5%
Other values (2138) 9446
94.5%
ValueCountFrequency (%)
1 71
0.7%
2 57
0.6%
3 53
0.5%
4 56
0.6%
5 45
0.4%
6 52
0.5%
7 38
0.4%
8 42
0.4%
9 38
0.4%
10 50
0.5%
ValueCountFrequency (%)
2267 2
< 0.1%
2266 2
< 0.1%
2265 3
< 0.1%
2264 2
< 0.1%
2263 1
 
< 0.1%
2262 3
< 0.1%
2261 1
 
< 0.1%
2260 2
< 0.1%
2259 2
< 0.1%
2258 1
 
< 0.1%

방송일
Date

Distinct2830
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-12-14 00:00:00
Maximum2024-03-31 00:00:00
2024-04-21T10:16:27.745276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:27.863939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

방송시간(시)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.2555
Minimum0
Maximum23
Zeros624
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:27.984382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median11
Q316
95-th percentile19
Maximum23
Range23
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.2602649
Coefficient of variation (CV)0.46735062
Kurtosis-0.58129467
Mean11.2555
Median Absolute Deviation (MAD)4
Skewness-0.22334294
Sum112555
Variance27.670387
MonotonicityNot monotonic
2024-04-21T10:16:28.095141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
8 1712
17.1%
7 1531
15.3%
12 953
9.5%
16 906
9.1%
17 788
7.9%
19 633
 
6.3%
0 624
 
6.2%
15 544
 
5.4%
18 399
 
4.0%
9 324
 
3.2%
Other values (14) 1586
15.9%
ValueCountFrequency (%)
0 624
 
6.2%
1 52
 
0.5%
2 48
 
0.5%
3 39
 
0.4%
4 34
 
0.3%
5 28
 
0.3%
6 63
 
0.6%
7 1531
15.3%
8 1712
17.1%
9 324
 
3.2%
ValueCountFrequency (%)
23 47
 
0.5%
22 9
 
0.1%
21 19
 
0.2%
20 132
 
1.3%
19 633
6.3%
18 399
4.0%
17 788
7.9%
16 906
9.1%
15 544
5.4%
14 240
 
2.4%

방송시간(분)
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.6983
Minimum0
Maximum59
Zeros2882
Zeros (%)28.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:28.190478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q340
95-th percentile50
Maximum59
Range59
Interquartile range (IQR)40

Descriptive statistics

Standard deviation17.787645
Coefficient of variation (CV)0.78365539
Kurtosis-1.4434663
Mean22.6983
Median Absolute Deviation (MAD)10
Skewness-0.12674723
Sum226983
Variance316.40032
MonotonicityNot monotonic
2024-04-21T10:16:28.291972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 2882
28.8%
30 2444
24.4%
40 2192
21.9%
50 560
 
5.6%
20 435
 
4.3%
10 431
 
4.3%
5 172
 
1.7%
55 154
 
1.5%
25 146
 
1.5%
1 134
 
1.3%
Other values (12) 450
 
4.5%
ValueCountFrequency (%)
0 2882
28.8%
1 134
 
1.3%
2 64
 
0.6%
3 15
 
0.1%
4 7
 
0.1%
5 172
 
1.7%
6 1
 
< 0.1%
9 1
 
< 0.1%
10 431
 
4.3%
11 1
 
< 0.1%
ValueCountFrequency (%)
59 4
 
< 0.1%
55 154
 
1.5%
50 560
 
5.6%
45 112
 
1.1%
40 2192
21.9%
35 132
 
1.3%
30 2444
24.4%
29 2
 
< 0.1%
28 1
 
< 0.1%
25 146
 
1.5%

재생시간(분)
Real number (ℝ)

Distinct84
Distinct (%)0.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean12.908691
Minimum0
Maximum235
Zeros26
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:28.405330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median7
Q319
95-th percentile40
Maximum235
Range235
Interquartile range (IQR)16

Descriptive statistics

Standard deviation14.254901
Coefficient of variation (CV)1.1042871
Kurtosis13.068757
Mean12.908691
Median Absolute Deviation (MAD)5
Skewness2.3188626
Sum129074
Variance203.2022
MonotonicityNot monotonic
2024-04-21T10:16:28.538601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 2063
20.6%
2 1529
15.3%
4 702
 
7.0%
27 321
 
3.2%
9 309
 
3.1%
1 276
 
2.8%
17 262
 
2.6%
16 259
 
2.6%
28 258
 
2.6%
10 253
 
2.5%
Other values (74) 3767
37.7%
ValueCountFrequency (%)
0 26
 
0.3%
1 276
 
2.8%
2 1529
15.3%
3 2063
20.6%
4 702
 
7.0%
5 206
 
2.1%
6 196
 
2.0%
7 241
 
2.4%
8 246
 
2.5%
9 309
 
3.1%
ValueCountFrequency (%)
235 1
< 0.1%
157 1
< 0.1%
152 1
< 0.1%
144 1
< 0.1%
142 1
< 0.1%
138 1
< 0.1%
136 2
< 0.1%
119 2
< 0.1%
118 1
< 0.1%
115 1
< 0.1%

재생시간(초)
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)0.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean29.180518
Minimum0
Maximum59
Zeros233
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:16:28.652521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median29
Q345
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.573687
Coefficient of variation (CV)0.60224041
Kurtosis-1.2257066
Mean29.180518
Median Absolute Deviation (MAD)15
Skewness0.015269635
Sum291776
Variance308.83448
MonotonicityNot monotonic
2024-04-21T10:16:28.784946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 233
 
2.3%
58 195
 
1.9%
7 190
 
1.9%
13 187
 
1.9%
12 185
 
1.8%
6 183
 
1.8%
46 179
 
1.8%
36 178
 
1.8%
19 176
 
1.8%
5 175
 
1.8%
Other values (50) 8118
81.2%
ValueCountFrequency (%)
0 233
2.3%
1 173
1.7%
2 173
1.7%
3 156
1.6%
4 160
1.6%
5 175
1.8%
6 183
1.8%
7 190
1.9%
8 168
1.7%
9 166
1.7%
ValueCountFrequency (%)
59 157
1.6%
58 195
1.9%
57 171
1.7%
56 168
1.7%
55 171
1.7%
54 164
1.6%
53 159
1.6%
52 157
1.6%
51 158
1.6%
50 165
1.7%

등록일
Date

Distinct2600
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-12-28 00:00:00
Maximum2024-03-31 00:00:00
2024-04-21T10:16:28.910707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:29.030584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-21T10:16:21.353431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:17.714301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.383759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.101304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.663812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.191264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.784753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.439008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:17.849149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.481461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.182214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.749666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.293491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.870190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.513157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:17.944815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.563040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.257674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.822355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.367180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.939329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.589820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.026352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.637036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.327850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.893874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.447654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.010717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.671892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.114098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.710302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.409756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.963840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.535428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.080035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.757255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.204975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.947198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.494295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.041904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.629917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.184432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.828187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:18.288431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.017622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:19.577302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.113081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:20.705550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:16:21.274344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:16:29.347612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
콘텐츠아이디전체영상여부조회수프로그램회차방송시간(시)방송시간(분)재생시간(분)재생시간(초)
콘텐츠아이디1.0000.1260.0000.8540.5930.4930.1090.058
전체영상여부0.1261.0000.0450.4430.4800.4760.6540.032
조회수0.0000.0451.0000.0360.0000.0000.0000.000
프로그램회차0.8540.4430.0361.0000.7700.6370.2840.031
방송시간(시)0.5930.4800.0000.7701.0000.6630.2810.067
방송시간(분)0.4930.4760.0000.6370.6631.0000.2580.051
재생시간(분)0.1090.6540.0000.2840.2810.2581.0000.033
재생시간(초)0.0580.0320.0000.0310.0670.0510.0331.000
2024-04-21T10:16:29.457915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
콘텐츠아이디조회수프로그램회차방송시간(시)방송시간(분)재생시간(분)재생시간(초)전체영상여부
콘텐츠아이디1.000-0.5800.3220.0300.1390.082-0.0070.097
조회수-0.5801.000-0.0110.0060.137-0.1320.0090.033
프로그램회차0.322-0.0111.000-0.2950.307-0.2960.0120.340
방송시간(시)0.0300.006-0.2951.000-0.1120.133-0.0220.369
방송시간(분)0.1390.1370.307-0.1121.000-0.197-0.0010.366
재생시간(분)0.082-0.132-0.2960.133-0.1971.000-0.0730.497
재생시간(초)-0.0070.0090.012-0.022-0.001-0.0731.0000.024
전체영상여부0.0970.0330.3400.3690.3660.4970.0241.000

Missing values

2024-04-21T10:16:21.954811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:16:22.164312image/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.
2024-04-21T10:16:22.307993image/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

콘텐츠아이디제목프로그램아이디프로그램명카테고리아이디카테고리명전체영상여부섬네일주소링크주소팝업링크주소조회수프로그램회차방송일방송시간(시)방송시간(분)재생시간(분)재생시간(초)등록일
15140583577열린소통포럼···1인 가구에 필요한 정책은?PG2150012D국민리포트100109정책공공Nhttps://www.ktv.go.kr/media/contents/image/2019/09/24/e0xP7q2mmz.jpghttps://www.ktv.go.kr/content/view?content_id=583577https://www.ktv.go.kr/content/popup?content_id=58357731111462019-09-246152482019-09-24
17273569413소녀주의보 그리고 한 남자, 청소년들과 1%의 희망나누기PG2190002D시청자에세이 날려라 하이킥100109정책공공Yhttps://www.ktv.go.kr/media/contents/image/2019/01/30/wUj1ezxhre.jpghttps://www.ktv.go.kr/content/view?content_id=569413https://www.ktv.go.kr/content/popup?content_id=56941376022019-01-3017302702019-01-30
24721533316"아픈 식물 치료해요"…사이버식물병원 인기PG2150012D국민리포트100109정책공공Nhttps://www.ktv.go.kr/media/contents/image/2017/02/24/GGNfF20q4V.jpghttps://www.ktv.go.kr/content/view?content_id=533316https://www.ktv.go.kr/content/popup?content_id=5333167135112017-02-248303182017-02-24
197875541065·18, 38년 통곡의 '한'PG2140026DPD리포트 이슈 본(本)100109정책공공Yhttps://www.ktv.go.kr/media/contents/image/2018/05/20/rClFpde9vL.jpghttps://www.ktv.go.kr/content/view?content_id=554106https://www.ktv.go.kr/content/popup?content_id=5541061231992018-05-18191028332018-05-20
21564545196포항 지진 피해현장에 가다PG2150012D국민리포트100109정책공공Yhttps://www.ktv.go.kr/media/contents/image/2017/11/20/8IXAYlXqDt.jpghttps://www.ktv.go.kr/content/view?content_id=545196https://www.ktv.go.kr/content/popup?content_id=54519611586912017-11-2084018132017-11-20
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