Overview

Dataset statistics

Number of variables10
Number of observations101
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.5 KiB
Average record size in memory86.3 B

Variable types

Categorical6
Text1
Numeric3

Alerts

PROGRM_GENRE_MLSFC_NM is highly overall correlated with BRDCST_DE and 2 other fieldsHigh correlation
PROGRM_GENRE_SCLAS_NM is highly overall correlated with PROGRM_GENRE_LCLAS_NM and 1 other fieldsHigh correlation
PROGRM_GENRE_LCLAS_NM is highly overall correlated with PROGRM_GENRE_MLSFC_NM and 1 other fieldsHigh correlation
PROGRM_BEGIN_TIME is highly overall correlated with PROGRM_END_TIME and 1 other fieldsHigh correlation
PROGRM_END_TIME is highly overall correlated with PROGRM_BEGIN_TIME and 2 other fieldsHigh correlation
BRDCST_DE is highly overall correlated with PROGRM_BEGIN_TIME and 3 other fieldsHigh correlation
BRDCST_END_DE is highly overall correlated with PROGRM_END_TIME and 1 other fieldsHigh correlation
BRDCST_DE is highly imbalanced (86.0%)Imbalance
BRDCST_END_DE is highly imbalanced (80.7%)Imbalance
WTCHNG_RT has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:53:53.269128
Analysis finished2023-12-10 09:53:56.804349
Duration3.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

BRDCST_DE
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
20210701
99 
20210702
 
2

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210701
2nd row20210701
3rd row20210701
4th row20210701
5th row20210701

Common Values

ValueCountFrequency (%)
20210701 99
98.0%
20210702 2
 
2.0%

Length

2023-12-10T18:53:56.933342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:57.114063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210701 99
98.0%
20210702 2
 
2.0%

BRDCST_END_DE
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
20210701
98 
20210702
 
3

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210701
2nd row20210701
3rd row20210701
4th row20210701
5th row20210701

Common Values

ValueCountFrequency (%)
20210701 98
97.0%
20210702 3
 
3.0%

Length

2023-12-10T18:53:57.338117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:57.545329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210701 98
97.0%
20210702 3
 
3.0%

CHNNEL_NM
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
KBS1
76 
KBS2
25 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKBS1
2nd rowKBS1
3rd rowKBS1
4th rowKBS1
5th rowKBS1

Common Values

ValueCountFrequency (%)
KBS1 76
75.2%
KBS2 25
 
24.8%

Length

2023-12-10T18:53:57.811374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:57.984351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kbs1 76
75.2%
kbs2 25
 
24.8%

PROGRM_NM
Text

Distinct100
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-10T18:53:58.390876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length11.316832
Min length4

Characters and Unicode

Total characters1143
Distinct characters211
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)98.0%

Sample

1st rowKBS중계석
2nd rowUHD숨터(재)
3rd row굿모닝대한민국라이브스페셜
4th row아침마당(재)
5th row생활의발견스페셜<KBS1>
ValueCountFrequency (%)
kbs중계석 2
 
1.9%
kbs뉴스광장 2
 
1.9%
kbs뉴스7부산 1
 
1.0%
kbs뉴스라인 1
 
1.0%
더라이브 1
 
1.0%
다큐인사이트 1
 
1.0%
kbs뉴스9 1
 
1.0%
일일드라마<속아도꿈결 1
 
1.0%
한국인의밥상 1
 
1.0%
kbs뉴스7강원 1
 
1.0%
Other values (91) 91
88.3%
2023-12-10T18:53:59.214674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 56
 
4.9%
( 51
 
4.5%
) 51
 
4.5%
0 44
 
3.8%
뉴 39
 
3.4%
K 37
 
3.2%
S 35
 
3.1%
B 35
 
3.1%
9 32
 
2.8%
1 30
 
2.6%
Other values (201) 733
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 706
61.8%
Decimal Number 168
 
14.7%
Uppercase Letter 129
 
11.3%
Open Punctuation 51
 
4.5%
Close Punctuation 51
 
4.5%
Math Symbol 36
 
3.1%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 56
 
7.9%
뉴 39
 
5.5%
이 17
 
2.4%
로 16
 
2.3%
재 15
 
2.1%
나 14
 
2.0%
룸 13
 
1.8%
라 13
 
1.8%
합 13
 
1.8%
국 13
 
1.8%
Other values (174) 497
70.4%
Uppercase Letter
ValueCountFrequency (%)
K 37
28.7%
S 35
27.1%
B 35
27.1%
T 5
 
3.9%
V 4
 
3.1%
P 2
 
1.6%
C 2
 
1.6%
I 2
 
1.6%
U 2
 
1.6%
H 2
 
1.6%
Other values (2) 3
 
2.3%
Decimal Number
ValueCountFrequency (%)
0 44
26.2%
9 32
19.0%
1 30
17.9%
5 16
 
9.5%
7 12
 
7.1%
2 11
 
6.5%
3 11
 
6.5%
4 10
 
6.0%
8 1
 
0.6%
6 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
> 18
50.0%
< 18
50.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 706
61.8%
Common 308
26.9%
Latin 129
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 56
 
7.9%
뉴 39
 
5.5%
이 17
 
2.4%
로 16
 
2.3%
재 15
 
2.1%
나 14
 
2.0%
룸 13
 
1.8%
라 13
 
1.8%
합 13
 
1.8%
국 13
 
1.8%
Other values (174) 497
70.4%
Common
ValueCountFrequency (%)
( 51
16.6%
) 51
16.6%
0 44
14.3%
9 32
10.4%
1 30
9.7%
> 18
 
5.8%
< 18
 
5.8%
5 16
 
5.2%
7 12
 
3.9%
2 11
 
3.6%
Other values (5) 25
8.1%
Latin
ValueCountFrequency (%)
K 37
28.7%
S 35
27.1%
B 35
27.1%
T 5
 
3.9%
V 4
 
3.1%
P 2
 
1.6%
C 2
 
1.6%
I 2
 
1.6%
U 2
 
1.6%
H 2
 
1.6%
Other values (2) 3
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 706
61.8%
ASCII 437
38.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 56
 
7.9%
뉴 39
 
5.5%
이 17
 
2.4%
로 16
 
2.3%
재 15
 
2.1%
나 14
 
2.0%
룸 13
 
1.8%
라 13
 
1.8%
합 13
 
1.8%
국 13
 
1.8%
Other values (174) 497
70.4%
ASCII
ValueCountFrequency (%)
( 51
11.7%
) 51
11.7%
0 44
10.1%
K 37
8.5%
S 35
8.0%
B 35
8.0%
9 32
 
7.3%
1 30
 
6.9%
> 18
 
4.1%
< 18
 
4.1%
Other values (17) 86
19.7%

PROGRM_BEGIN_TIME
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128885.42
Minimum1014
Maximum232956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:59.500121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1014
5-th percentile24753
Q192916
median135409
Q3173805
95-th percentile203513
Maximum232956
Range231942
Interquartile range (IQR)80889

Descriptive statistics

Standard deviation54808.389
Coefficient of variation (CV)0.42524896
Kurtosis-0.77806419
Mean128885.42
Median Absolute Deviation (MAD)41000
Skewness-0.30973391
Sum13017427
Variance3.0039595 × 109
MonotonicityNot monotonic
2023-12-10T18:53:59.757872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92919 3
 
3.0%
20000 2
 
2.0%
94409 2
 
2.0%
92914 2
 
2.0%
185955 1
 
1.0%
10520 1
 
1.0%
1014 1
 
1.0%
232956 1
 
1.0%
224816 1
 
1.0%
215924 1
 
1.0%
Other values (86) 86
85.1%
ValueCountFrequency (%)
1014 1
1.0%
10520 1
1.0%
20000 2
2.0%
23934 1
1.0%
24753 1
1.0%
34655 1
1.0%
50005 1
1.0%
50020 1
1.0%
51019 1
1.0%
55803 1
1.0%
ValueCountFrequency (%)
232956 1
1.0%
224816 1
1.0%
215924 1
1.0%
213520 1
1.0%
210004 1
1.0%
203513 1
1.0%
203115 1
1.0%
195051 1
1.0%
194010 1
1.0%
185955 1
1.0%

PROGRM_END_TIME
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131105.58
Minimum727
Maximum232817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:00.028488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum727
5-th percentile24355
Q194630
median135750
Q3175700
95-th percentile205920
Maximum232817
Range232090
Interquartile range (IQR)81070

Descriptive statistics

Standard deviation55958.559
Coefficient of variation (CV)0.42682056
Kurtosis-0.76339891
Mean131105.58
Median Absolute Deviation (MAD)40445
Skewness-0.3208946
Sum13241664
Variance3.1313603 × 109
MonotonicityNot monotonic
2023-12-10T18:54:00.314780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94850 2
 
2.0%
95652 2
 
2.0%
95650 2
 
2.0%
94352 2
 
2.0%
94357 2
 
2.0%
23542 1
 
1.0%
55430 1
 
1.0%
20110 1
 
1.0%
15959 1
 
1.0%
10149 1
 
1.0%
Other values (86) 86
85.1%
ValueCountFrequency (%)
727 1
1.0%
10149 1
1.0%
15959 1
1.0%
20110 1
1.0%
23542 1
1.0%
24355 1
1.0%
33943 1
1.0%
44956 1
1.0%
50900 1
1.0%
55430 1
1.0%
ValueCountFrequency (%)
232817 1
1.0%
224723 1
1.0%
223714 1
1.0%
215753 1
1.0%
212539 1
1.0%
205920 1
1.0%
202753 1
1.0%
202652 1
1.0%
194138 1
1.0%
193752 1
1.0%

PROGRM_GENRE_LCLAS_NM
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
보도
41 
정보
39 
어린이(유아)
9 
오락
8 
드라마&영화
 
4

Length

Max length7
Median length2
Mean length2.6039604
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row오락
2nd row정보
3rd row정보
4th row정보
5th row정보

Common Values

ValueCountFrequency (%)
보도 41
40.6%
정보 39
38.6%
어린이(유아) 9
 
8.9%
오락 8
 
7.9%
드라마&영화 4
 
4.0%

Length

2023-12-10T18:54:00.668766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:54:00.946893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보도 41
40.6%
정보 39
38.6%
어린이(유아 9
 
8.9%
오락 8
 
7.9%
드라마&영화 4
 
4.0%

PROGRM_GENRE_MLSFC_NM
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size940.0 B
뉴스
40 
생활정보
25 
다큐멘터리
12 
만화&인형극
7 
드라마
 
4
Other values (8)
13 

Length

Max length6
Median length5
Mean length3.3861386
Min length2

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row공연예술
2nd row다큐멘터리
3rd row생활정보
4th row생활정보
5th row생활정보

Common Values

ValueCountFrequency (%)
뉴스 40
39.6%
생활정보 25
24.8%
다큐멘터리 12
 
11.9%
만화&인형극 7
 
6.9%
드라마 4
 
4.0%
오락기타 3
 
3.0%
토크쇼 3
 
3.0%
공연예술 2
 
2.0%
시사 1
 
1.0%
정보기타 1
 
1.0%
Other values (3) 3
 
3.0%

Length

2023-12-10T18:54:01.250930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
뉴스 40
39.6%
생활정보 25
24.8%
다큐멘터리 12
 
11.9%
만화&인형극 7
 
6.9%
드라마 4
 
4.0%
오락기타 3
 
3.0%
토크쇼 3
 
3.0%
공연예술 2
 
2.0%
시사 1
 
1.0%
정보기타 1
 
1.0%
Other values (3) 3
 
3.0%

PROGRM_GENRE_SCLAS_NM
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size940.0 B
뉴스(스트레이트)
22 
뉴스(종합)
17 
생활정보(종합)
13 
주간만화
7 
생활정보(기타)
5 
Other values (18)
37 

Length

Max length13
Median length11
Mean length7.3069307
Min length3

Unique

Unique10 ?
Unique (%)9.9%

Sample

1st row공연예술
2nd row다큐멘터리(휴먼)
3rd row생활정보(종합)
4th row생활정보(종합)
5th row생활정보(가사)

Common Values

ValueCountFrequency (%)
뉴스(스트레이트) 22
21.8%
뉴스(종합) 17
16.8%
생활정보(종합) 13
12.9%
주간만화 7
 
6.9%
생활정보(기타) 5
 
5.0%
생활정보(지역) 5
 
5.0%
다큐멘터리(휴먼) 4
 
4.0%
일일연속극 4
 
4.0%
다큐멘터리(역사기행문예) 4
 
4.0%
토크쇼 3
 
3.0%
Other values (13) 17
16.8%

Length

2023-12-10T18:54:01.517101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
뉴스(스트레이트 22
21.8%
뉴스(종합 17
16.8%
생활정보(종합 13
12.9%
주간만화 7
 
6.9%
생활정보(기타 5
 
5.0%
생활정보(지역 5
 
5.0%
다큐멘터리(휴먼 4
 
4.0%
일일연속극 4
 
4.0%
다큐멘터리(역사기행문예 4
 
4.0%
토크쇼 3
 
3.0%
Other values (13) 17
16.8%

WTCHNG_RT
Real number (ℝ)

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7884653
Minimum0.01592
Maximum17.06039
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:54:01.768141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01592
5-th percentile0.04758
Q10.23023
median0.62074
Q32.13451
95-th percentile7.5985
Maximum17.06039
Range17.04447
Interquartile range (IQR)1.90428

Descriptive statistics

Standard deviation2.9437578
Coefficient of variation (CV)1.6459686
Kurtosis11.135206
Mean1.7884653
Median Absolute Deviation (MAD)0.48831
Skewness3.1233495
Sum180.635
Variance8.6657099
MonotonicityNot monotonic
2023-12-10T18:54:02.054249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.25865 1
 
1.0%
3.26831 1
 
1.0%
1.06955 1
 
1.0%
2.13451 1
 
1.0%
2.95608 1
 
1.0%
3.79078 1
 
1.0%
10.86018 1
 
1.0%
14.8238 1
 
1.0%
5.00463 1
 
1.0%
0.13829 1
 
1.0%
Other values (91) 91
90.1%
ValueCountFrequency (%)
0.01592 1
1.0%
0.01761 1
1.0%
0.02639 1
1.0%
0.04416 1
1.0%
0.04692 1
1.0%
0.04758 1
1.0%
0.05768 1
1.0%
0.06437 1
1.0%
0.06845 1
1.0%
0.07476 1
1.0%
ValueCountFrequency (%)
17.06039 1
1.0%
14.8238 1
1.0%
10.86018 1
1.0%
10.29982 1
1.0%
8.86278 1
1.0%
7.5985 1
1.0%
7.40015 1
1.0%
5.00463 1
1.0%
4.7935 1
1.0%
4.68973 1
1.0%

Interactions

2023-12-10T18:53:55.176512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:54.217285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:54.674961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:55.350362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:54.364458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:54.836968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:55.554790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:54.510220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:55.015769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:54:02.246310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRDCST_DEBRDCST_END_DECHNNEL_NMPROGRM_NMPROGRM_BEGIN_TIMEPROGRM_END_TIMEPROGRM_GENRE_LCLAS_NMPROGRM_GENRE_MLSFC_NMPROGRM_GENRE_SCLAS_NMWTCHNG_RT
BRDCST_DE1.0000.8070.0000.0000.5310.8300.3700.6060.5580.000
BRDCST_END_DE0.8071.0000.0000.0000.4710.8300.2770.4350.3130.000
CHNNEL_NM0.0000.0001.0001.0000.0000.1740.2840.4500.5650.000
PROGRM_NM0.0000.0001.0001.0001.0001.0001.0001.0001.0001.000
PROGRM_BEGIN_TIME0.5310.4710.0001.0001.0000.9790.8220.7180.8370.463
PROGRM_END_TIME0.8300.8300.1741.0000.9791.0000.8200.7250.8620.376
PROGRM_GENRE_LCLAS_NM0.3700.2770.2841.0000.8220.8201.0001.0001.0000.438
PROGRM_GENRE_MLSFC_NM0.6060.4350.4501.0000.7180.7251.0001.0001.0000.318
PROGRM_GENRE_SCLAS_NM0.5580.3130.5651.0000.8370.8621.0001.0001.0000.000
WTCHNG_RT0.0000.0000.0001.0000.4630.3760.4380.3180.0001.000
2023-12-10T18:54:02.533513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
PROGRM_GENRE_MLSFC_NMBRDCST_DEBRDCST_END_DEPROGRM_GENRE_SCLAS_NMCHNNEL_NMPROGRM_GENRE_LCLAS_NM
PROGRM_GENRE_MLSFC_NM1.0000.5360.3820.9410.3950.957
BRDCST_DE0.5361.0000.5980.4320.0000.444
BRDCST_END_DE0.3820.5981.0000.2380.0000.333
PROGRM_GENRE_SCLAS_NM0.9410.4320.2381.0000.4380.901
CHNNEL_NM0.3950.0000.0000.4381.0000.341
PROGRM_GENRE_LCLAS_NM0.9570.4440.3330.9010.3411.000
2023-12-10T18:54:02.759703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
PROGRM_BEGIN_TIMEPROGRM_END_TIMEWTCHNG_RTBRDCST_DEBRDCST_END_DECHNNEL_NMPROGRM_GENRE_LCLAS_NMPROGRM_GENRE_MLSFC_NMPROGRM_GENRE_SCLAS_NM
PROGRM_BEGIN_TIME1.0000.9370.0380.5490.4750.0000.4830.3710.447
PROGRM_END_TIME0.9371.0000.0260.5490.7090.1290.4470.3720.482
WTCHNG_RT0.0380.0261.0000.0000.0000.0000.2820.1410.000
BRDCST_DE0.5490.5490.0001.0000.5980.0000.4440.5360.432
BRDCST_END_DE0.4750.7090.0000.5981.0000.0000.3330.3820.238
CHNNEL_NM0.0000.1290.0000.0000.0001.0000.3410.3950.438
PROGRM_GENRE_LCLAS_NM0.4830.4470.2820.4440.3330.3411.0000.9570.901
PROGRM_GENRE_MLSFC_NM0.3710.3720.1410.5360.3820.3950.9571.0000.941
PROGRM_GENRE_SCLAS_NM0.4470.4820.0000.4320.2380.4380.9010.9411.000

Missing values

2023-12-10T18:53:55.922445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:53:56.224041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

BRDCST_DEBRDCST_END_DECHNNEL_NMPROGRM_NMPROGRM_BEGIN_TIMEPROGRM_END_TIMEPROGRM_GENRE_LCLAS_NMPROGRM_GENRE_MLSFC_NMPROGRM_GENRE_SCLAS_NMWTCHNG_RT
02021070120210701KBS1KBS중계석2000023542오락공연예술공연예술0.25865
12021070120210701KBS1UHD숨터(재)2393424355정보다큐멘터리다큐멘터리(휴먼)0.30157
22021070120210701KBS1굿모닝대한민국라이브스페셜2475333943정보생활정보생활정보(종합)0.13243
32021070120210701KBS1아침마당(재)3465544956정보생활정보생활정보(종합)0.45425
42021070120210701KBS1생활의발견스페셜<KBS1>5000550900정보생활정보생활정보(가사)0.36114
52021070120210701KBS1한국인의밥상(재)5101955828정보다큐멘터리다큐멘터리(역사기행문예)1.3073
62021070120210701KBS1KBS뉴스광장 1부6001565858보도뉴스뉴스(종합)4.68973
72021070120210701KBS1KBS뉴스광장 2부6590874757보도뉴스뉴스(종합)7.40015
82021070120210701KBS1인간극장<KBS1>7500882214정보다큐멘터리다큐멘터리(휴먼)10.29982
92021070120210701KBS1아침마당8235392634정보생활정보생활정보(종합)8.86278
BRDCST_DEBRDCST_END_DECHNNEL_NMPROGRM_NMPROGRM_BEGIN_TIMEPROGRM_END_TIMEPROGRM_GENRE_LCLAS_NMPROGRM_GENRE_MLSFC_NMPROGRM_GENRE_SCLAS_NMWTCHNG_RT
912021070120210701KBS2TV유치원152926155537어린이(유아)유아교육유아교육0.451
922021070120210701KBS2누가누가잘하나<KBS2>155802165349어린이(유아)어린이기타어린이기타0.29044
932021070120210701KBS2만화1700<마카앤로니>165908171212어린이(유아)만화&인형극주간만화0.09078
942021070120210701KBS2만화1715<몬스터탑>171413172452어린이(유아)만화&인형극주간만화0.04758
952021070120210701KBS2놓친예능따라잡기172745174409오락오락기타오락기타0.36223
962021070120210701KBS2통합뉴스룸ET175100182348보도뉴스뉴스(종합)1.09737
972021070120210701KBS22TV생생정보183223194138정보정보종합정보종합4.47903
982021070120210701KBS2일일드라마<미스몬테크리스토>195051202652드라마&영화드라마일일연속극17.06039
992021070120210701KBS2환경스페셜203513212539정보다큐멘터리다큐멘터리(기타)3.07742
1002021070120210701KBS2트롯매직유랑단스페셜213520223714오락오락기타오락기타2.75331