Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells100
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.2 KiB
Average record size in memory135.3 B

Variable types

Categorical14
Unsupported1
Numeric1

Alerts

progrm_brdcst_area_nm has constant value ""Constant
progrm_genre_lclas_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
chnnel_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
brdcst_de is highly overall correlated with brdcst_end_de and 9 other fieldsHigh correlation
occp_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
progrm_genre_sclas_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
progrm_genre_mlsfc_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
brdcst_end_de is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
brdcst_tme_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
progrm_end_time is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
progrm_begin_time is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
progrm_nm is highly overall correlated with brdcst_de and 9 other fieldsHigh correlation
brdcst_de is highly imbalanced (80.6%)Imbalance
brdcst_end_de is highly imbalanced (80.6%)Imbalance
chnnel_nm is highly imbalanced (80.6%)Imbalance
progrm_begin_time is highly imbalanced (80.6%)Imbalance
progrm_end_time is highly imbalanced (80.6%)Imbalance
progrm_nm is highly imbalanced (80.6%)Imbalance
brdcst_tme_nm is highly imbalanced (80.6%)Imbalance
progrm_genre_lclas_nm is highly imbalanced (80.6%)Imbalance
progrm_genre_mlsfc_nm is highly imbalanced (80.6%)Imbalance
progrm_genre_sclas_nm is highly imbalanced (80.6%)Imbalance
occp_nm is highly imbalanced (72.6%)Imbalance
progrm_dc has 100 (100.0%) missing valuesMissing
progrm_dc is an unsupported type, check if it needs cleaning or further analysisUnsupported
aude_co has 90 (90.0%) zerosZeros

Reproduction

Analysis started2023-12-10 09:56:08.597636
Analysis finished2023-12-10 09:56:11.920607
Duration3.32 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 size932.0 B
20211001
97 
20211031
 
3

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211001
2nd row20211031
3rd row20211001
4th row20211001
5th row20211001

Common Values

ValueCountFrequency (%)
20211001 97
97.0%
20211031 3
 
3.0%

Length

2023-12-10T18:56:12.105926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:12.378658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211001 97
97.0%
20211031 3
 
3.0%

brdcst_end_de
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20211001
97 
20211031
 
3

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211001
2nd row20211031
3rd row20211001
4th row20211001
5th row20211001

Common Values

ValueCountFrequency (%)
20211001 97
97.0%
20211031 3
 
3.0%

Length

2023-12-10T18:56:12.605319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:12.856519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211001 97
97.0%
20211031 3
 
3.0%

chnnel_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KBS1
97 
NQQ
 
3

Length

Max length4
Median length4
Mean length3.97
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KBS1 97
97.0%
NQQ 3
 
3.0%

Length

2023-12-10T18:56:13.158447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:13.455379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kbs1 97
97.0%
nqq 3
 
3.0%

progrm_begin_time
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
175839
97 
195359
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row175839
2nd row195359
3rd row175839
4th row175839
5th row175839

Common Values

ValueCountFrequency (%)
175839 97
97.0%
195359 3
 
3.0%

Length

2023-12-10T18:56:13.712365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:14.052954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
175839 97
97.0%
195359 3
 
3.0%

progrm_end_time
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
185626
97 
212818
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row185626
2nd row212818
3rd row185626
4th row185626
5th row185626

Common Values

ValueCountFrequency (%)
185626 97
97.0%
212818 3
 
3.0%

Length

2023-12-10T18:56:14.497590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:14.793940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
185626 97
97.0%
212818 3
 
3.0%

progrm_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
6시내고향
97 
전지적참견시점
 
3

Length

Max length7
Median length5
Mean length5.06
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6시내고향
2nd row전지적참견시점
3rd row6시내고향
4th row6시내고향
5th row6시내고향

Common Values

ValueCountFrequency (%)
6시내고향 97
97.0%
전지적참견시점 3
 
3.0%

Length

2023-12-10T18:56:15.188700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:15.504048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6시내고향 97
97.0%
전지적참견시점 3
 
3.0%

progrm_dc
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

brdcst_tme_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
7375회
97 
162회
 
3

Length

Max length5
Median length5
Mean length4.97
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7375회
2nd row162회
3rd row7375회
4th row7375회
5th row7375회

Common Values

ValueCountFrequency (%)
7375회 97
97.0%
162회 3
 
3.0%

Length

2023-12-10T18:56:15.784883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:16.076833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7375회 97
97.0%
162회 3
 
3.0%

progrm_brdcst_area_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전국
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전국 100
100.0%

Length

2023-12-10T18:56:16.346826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:16.543030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전국 100
100.0%

progrm_genre_lclas_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정보
97 
오락
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보 97
97.0%
오락 3
 
3.0%

Length

2023-12-10T18:56:16.815736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:17.197814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보 97
97.0%
오락 3
 
3.0%

progrm_genre_mlsfc_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
생활정보
97 
오락기타
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활정보
2nd row오락기타
3rd row생활정보
4th row생활정보
5th row생활정보

Common Values

ValueCountFrequency (%)
생활정보 97
97.0%
오락기타 3
 
3.0%

Length

2023-12-10T18:56:17.529034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:17.815382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활정보 97
97.0%
오락기타 3
 
3.0%

progrm_genre_sclas_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
생활정보(종합)
97 
오락기타
 
3

Length

Max length8
Median length8
Mean length7.88
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활정보(종합)
2nd row오락기타
3rd row생활정보(종합)
4th row생활정보(종합)
5th row생활정보(종합)

Common Values

ValueCountFrequency (%)
생활정보(종합) 97
97.0%
오락기타 3
 
3.0%

Length

2023-12-10T18:56:18.082314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:18.303641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활정보(종합 97
97.0%
오락기타 3
 
3.0%

income_nm
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수입없음
13 
400만원 이상~500만원 미만
13 
100만원 이상~200만원 미만
13 
200만원 이상~300만원 미만
13 
500만원 이상~600만원 미만
13 
Other values (3)
35 

Length

Max length17
Median length17
Mean length13.24
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수입없음
2nd row400만원 이상~500만원 미만
3rd row100만원 이상~200만원 미만
4th row200만원 이상~300만원 미만
5th row300만원 이상~400만원 미만

Common Values

ValueCountFrequency (%)
수입없음 13
13.0%
400만원 이상~500만원 미만 13
13.0%
100만원 이상~200만원 미만 13
13.0%
200만원 이상~300만원 미만 13
13.0%
500만원 이상~600만원 미만 13
13.0%
300만원 이상~400만원 미만 12
12.0%
100만원 미만 12
12.0%
600만원 이상 11
11.0%

Length

2023-12-10T18:56:18.518909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:18.797902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 76
30.3%
100만원 25
 
10.0%
수입없음 13
 
5.2%
400만원 13
 
5.2%
이상~500만원 13
 
5.2%
이상~200만원 13
 
5.2%
200만원 13
 
5.2%
이상~300만원 13
 
5.2%
500만원 13
 
5.2%
이상~600만원 13
 
5.2%
Other values (4) 46
18.3%

acdmcr_nm
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
미취학
11 
초등졸 이하
10 
중졸
8 
고졸
8 
대학원졸 이상
8 
Other values (7)
55 

Length

Max length7
Median length6
Mean length3.47
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row초등졸 이하
2nd row미취학
3rd row초등졸 이하
4th row초등졸 이하
5th row초등졸 이하

Common Values

ValueCountFrequency (%)
미취학 11
11.0%
초등졸 이하 10
10.0%
중졸 8
8.0%
고졸 8
8.0%
대학원졸 이상 8
8.0%
대재 8
8.0%
대학원재 8
8.0%
대학원 수료 8
8.0%
고재 8
8.0%
중재 8
8.0%
Other values (2) 15
15.0%

Length

2023-12-10T18:56:19.119215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미취학 11
 
8.7%
초등졸 10
 
7.9%
이하 10
 
7.9%
중졸 8
 
6.3%
고졸 8
 
6.3%
대학원졸 8
 
6.3%
이상 8
 
6.3%
대재 8
 
6.3%
대학원재 8
 
6.3%
대학원 8
 
6.3%
Other values (5) 39
31.0%

occp_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
관리자
93 
전문가 및 관련종사자
 
4
무직
 
3

Length

Max length11
Median length3
Mean length3.29
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관리자
2nd row무직
3rd row관리자
4th row관리자
5th row관리자

Common Values

ValueCountFrequency (%)
관리자 93
93.0%
전문가 및 관련종사자 4
 
4.0%
무직 3
 
3.0%

Length

2023-12-10T18:56:19.364285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:56:19.556446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관리자 93
86.1%
전문가 4
 
3.7%
및 4
 
3.7%
관련종사자 4
 
3.7%
무직 3
 
2.8%

aude_co
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.42777
Minimum0
Maximum8.848
Zeros90
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:56:19.727348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.1008
Maximum8.848
Range8.848
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6070072
Coefficient of variation (CV)3.7567084
Kurtosis17.583972
Mean0.42777
Median Absolute Deviation (MAD)0
Skewness4.2006166
Sum42.777
Variance2.582472
MonotonicityNot monotonic
2023-12-10T18:56:19.915871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 90
90.0%
8.56 1
 
1.0%
7.615 1
 
1.0%
3.024 1
 
1.0%
2.626 1
 
1.0%
0.306 1
 
1.0%
8.848 1
 
1.0%
1.615 1
 
1.0%
0.682 1
 
1.0%
4.941 1
 
1.0%
ValueCountFrequency (%)
0.0 90
90.0%
0.306 1
 
1.0%
0.682 1
 
1.0%
1.615 1
 
1.0%
2.626 1
 
1.0%
3.024 1
 
1.0%
4.56 1
 
1.0%
4.941 1
 
1.0%
7.615 1
 
1.0%
8.56 1
 
1.0%
ValueCountFrequency (%)
8.848 1
1.0%
8.56 1
1.0%
7.615 1
1.0%
4.941 1
1.0%
4.56 1
1.0%
3.024 1
1.0%
2.626 1
1.0%
1.615 1
1.0%
0.682 1
1.0%
0.306 1
1.0%

Interactions

2023-12-10T18:56:10.890521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:56:20.414951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
brdcst_debrdcst_end_dechnnel_nmprogrm_begin_timeprogrm_end_timeprogrm_nmbrdcst_tme_nmprogrm_genre_lclas_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nmaude_co
brdcst_de1.0000.9630.9630.9630.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
brdcst_end_de0.9631.0000.9630.9630.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
chnnel_nm0.9630.9631.0000.9630.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
progrm_begin_time0.9630.9630.9631.0000.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
progrm_end_time0.9630.9630.9630.9631.0000.9630.9630.9630.9630.9630.0000.5091.0000.000
progrm_nm0.9630.9630.9630.9630.9631.0000.9630.9630.9630.9630.0000.5091.0000.000
brdcst_tme_nm0.9630.9630.9630.9630.9630.9631.0000.9630.9630.9630.0000.5091.0000.000
progrm_genre_lclas_nm0.9630.9630.9630.9630.9630.9630.9631.0000.9630.9630.0000.5091.0000.000
progrm_genre_mlsfc_nm0.9630.9630.9630.9630.9630.9630.9630.9631.0000.9630.0000.5091.0000.000
progrm_genre_sclas_nm0.9630.9630.9630.9630.9630.9630.9630.9630.9631.0000.0000.5091.0000.000
income_nm0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
acdmcr_nm0.5090.5090.5090.5090.5090.5090.5090.5090.5090.5090.0001.0000.7570.241
occp_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.7571.0000.000
aude_co0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.2410.0001.000
2023-12-10T18:56:20.709325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
progrm_genre_lclas_nmchnnel_nmbrdcst_deoccp_nmprogrm_genre_sclas_nmprogrm_genre_mlsfc_nmincome_nmbrdcst_end_debrdcst_tme_nmacdmcr_nmprogrm_end_timeprogrm_begin_timeprogrm_nm
progrm_genre_lclas_nm1.0000.8260.8260.9950.8260.8260.0000.8260.8260.3750.8260.8260.826
chnnel_nm0.8261.0000.8260.9950.8260.8260.0000.8260.8260.3750.8260.8260.826
brdcst_de0.8260.8261.0000.9950.8260.8260.0000.8260.8260.3750.8260.8260.826
occp_nm0.9950.9950.9951.0000.9950.9950.0000.9950.9950.4520.9950.9950.995
progrm_genre_sclas_nm0.8260.8260.8260.9951.0000.8260.0000.8260.8260.3750.8260.8260.826
progrm_genre_mlsfc_nm0.8260.8260.8260.9950.8261.0000.0000.8260.8260.3750.8260.8260.826
income_nm0.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.000
brdcst_end_de0.8260.8260.8260.9950.8260.8260.0001.0000.8260.3750.8260.8260.826
brdcst_tme_nm0.8260.8260.8260.9950.8260.8260.0000.8261.0000.3750.8260.8260.826
acdmcr_nm0.3750.3750.3750.4520.3750.3750.0000.3750.3751.0000.3750.3750.375
progrm_end_time0.8260.8260.8260.9950.8260.8260.0000.8260.8260.3751.0000.8260.826
progrm_begin_time0.8260.8260.8260.9950.8260.8260.0000.8260.8260.3750.8261.0000.826
progrm_nm0.8260.8260.8260.9950.8260.8260.0000.8260.8260.3750.8260.8261.000
2023-12-10T18:56:21.065052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
aude_cobrdcst_debrdcst_end_dechnnel_nmprogrm_begin_timeprogrm_end_timeprogrm_nmbrdcst_tme_nmprogrm_genre_lclas_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nm
aude_co1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1110.000
brdcst_de0.0001.0000.8260.8260.8260.8260.8260.8260.8260.8260.8260.0000.3750.995
brdcst_end_de0.0000.8261.0000.8260.8260.8260.8260.8260.8260.8260.8260.0000.3750.995
chnnel_nm0.0000.8260.8261.0000.8260.8260.8260.8260.8260.8260.8260.0000.3750.995
progrm_begin_time0.0000.8260.8260.8261.0000.8260.8260.8260.8260.8260.8260.0000.3750.995
progrm_end_time0.0000.8260.8260.8260.8261.0000.8260.8260.8260.8260.8260.0000.3750.995
progrm_nm0.0000.8260.8260.8260.8260.8261.0000.8260.8260.8260.8260.0000.3750.995
brdcst_tme_nm0.0000.8260.8260.8260.8260.8260.8261.0000.8260.8260.8260.0000.3750.995
progrm_genre_lclas_nm0.0000.8260.8260.8260.8260.8260.8260.8261.0000.8260.8260.0000.3750.995
progrm_genre_mlsfc_nm0.0000.8260.8260.8260.8260.8260.8260.8260.8261.0000.8260.0000.3750.995
progrm_genre_sclas_nm0.0000.8260.8260.8260.8260.8260.8260.8260.8260.8261.0000.0000.3750.995
income_nm0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.000
acdmcr_nm0.1110.3750.3750.3750.3750.3750.3750.3750.3750.3750.3750.0001.0000.452
occp_nm0.0000.9950.9950.9950.9950.9950.9950.9950.9950.9950.9950.0000.4521.000

Missing values

2023-12-10T18:56:11.143382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:56:11.752119image/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_begin_timeprogrm_end_timeprogrm_nmprogrm_dcbrdcst_tme_nmprogrm_brdcst_area_nmprogrm_genre_lclas_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nmaude_co
02021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)수입없음초등졸 이하관리자0.0
12021103120211031NQQ195359212818전지적참견시점<NA>162회전국오락오락기타오락기타400만원 이상~500만원 미만미취학무직0.0
22021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)100만원 이상~200만원 미만초등졸 이하관리자0.0
32021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)200만원 이상~300만원 미만초등졸 이하관리자0.0
42021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)300만원 이상~400만원 미만초등졸 이하관리자0.0
52021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)400만원 이상~500만원 미만초등졸 이하관리자0.0
62021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)500만원 이상~600만원 미만초등졸 이하관리자0.0
72021103120211031NQQ195359212818전지적참견시점<NA>162회전국오락오락기타오락기타500만원 이상~600만원 미만미취학무직0.0
82021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)수입없음중졸관리자0.0
92021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)100만원 미만중졸관리자0.0
brdcst_debrdcst_end_dechnnel_nmprogrm_begin_timeprogrm_end_timeprogrm_nmprogrm_dcbrdcst_tme_nmprogrm_brdcst_area_nmprogrm_genre_lclas_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nmaude_co
902021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)100만원 이상~200만원 미만미취학관리자0.0
912021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)200만원 이상~300만원 미만미취학관리자0.0
922021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)300만원 이상~400만원 미만미취학관리자0.0
932021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)400만원 이상~500만원 미만미취학관리자0.0
942021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)500만원 이상~600만원 미만미취학관리자0.0
952021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)600만원 이상미취학관리자0.0
962021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)수입없음초등졸 이하전문가 및 관련종사자0.0
972021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)100만원 미만초등졸 이하전문가 및 관련종사자0.0
982021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)100만원 이상~200만원 미만초등졸 이하전문가 및 관련종사자0.0
992021100120211001KBS11758391856266시내고향<NA>7375회전국정보생활정보생활정보(종합)200만원 이상~300만원 미만초등졸 이하전문가 및 관련종사자0.0