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

Categorical15
Unsupported1

Alerts

progrm_brdcst_area_nm has constant value ""Constant
progrm_genre_lclas_nm has constant value ""Constant
aude_co is highly overall correlated with brdcst_tme_nmHigh correlation
progrm_genre_sclas_nm is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
brdcst_tme_nm is highly overall correlated with brdcst_de and 11 other fieldsHigh correlation
occp_nm is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
chnnel_nm is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
income_nm is highly overall correlated with brdcst_tme_nmHigh correlation
brdcst_end_de is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
progrm_genre_mlsfc_nm is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
progrm_nm is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
brdcst_de is highly overall correlated with brdcst_end_de and 8 other fieldsHigh correlation
progrm_end_time is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
progrm_begin_time is highly overall correlated with brdcst_de and 8 other fieldsHigh correlation
acdmcr_nm is highly overall correlated with brdcst_tme_nmHigh 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_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
aude_co is highly imbalanced (89.8%)Imbalance
progrm_dc has 100 (100.0%) missing valuesMissing
progrm_dc is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 10:15:54.043367
Analysis finished2023-12-10 10:15:56.154785
Duration2.11 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

2023-12-10T19:15:56.290254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:56.465655image/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

2023-12-10T19:15:56.641527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:56.807097image/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 
KBS Story
 
3

Length

Max length9
Median length4
Mean length4.15
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KBS1 97
97.0%
KBS Story 3
 
3.0%

Length

2023-12-10T19:15:57.018383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:57.217284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kbs1 97
94.2%
kbs 3
 
2.9%
story 3
 
2.9%

progrm_begin_time
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
50027
97 
34510
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50027
2nd row34510
3rd row50027
4th row50027
5th row50027

Common Values

ValueCountFrequency (%)
50027 97
97.0%
34510 3
 
3.0%

Length

2023-12-10T19:15:57.405651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:57.623593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50027 97
97.0%
34510 3
 
3.0%

progrm_end_time
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
50910
97 
45350
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50910
2nd row45350
3rd row50910
4th row50910
5th row50910

Common Values

ValueCountFrequency (%)
50910 97
97.0%
45350 3
 
3.0%

Length

2023-12-10T19:15:57.788627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:57.962195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50910 97
97.0%
45350 3
 
3.0%

progrm_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
생활의발견스페셜<KBS1>
97 
2TV생생정보
 
3

Length

Max length14
Median length14
Mean length13.79
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활의발견스페셜<KBS1>
2nd row2TV생생정보
3rd row생활의발견스페셜<KBS1>
4th row생활의발견스페셜<KBS1>
5th row생활의발견스페셜<KBS1>

Common Values

ValueCountFrequency (%)
생활의발견스페셜<KBS1> 97
97.0%
2TV생생정보 3
 
3.0%

Length

2023-12-10T19:15:58.161309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:58.336473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활의발견스페셜<kbs1 97
97.0%
2tv생생정보 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
<NA>
97 
1415회
 
3

Length

Max length5
Median length4
Mean length4.03
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1415회
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 97
97.0%
1415회 3
 
3.0%

Length

2023-12-10T19:15:58.841007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:58.959299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 97
97.0%
1415회 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

2023-12-10T19:15:59.109866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:59.248073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전국 100
100.0%

progrm_genre_lclas_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보 100
100.0%

Length

2023-12-10T19:15:59.413844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:59.560248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보 100
100.0%

progrm_genre_mlsfc_nm
Categorical

HIGH CORRELATION  IMBALANCE 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2023-12-10T19:15:59.693099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:59.813234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활정보 97
97.0%
정보종합 3
 
3.0%

progrm_genre_sclas_nm
Categorical

HIGH CORRELATION  IMBALANCE 

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

Length

Max length8
Median length8
Mean length7.88
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활정보(가사)
2nd row정보종합
3rd row생활정보(가사)
4th row생활정보(가사)
5th row생활정보(가사)

Common Values

ValueCountFrequency (%)
생활정보(가사) 97
97.0%
정보종합 3
 
3.0%

Length

2023-12-10T19:15:59.962482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:16:00.117299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활정보(가사 97
97.0%
정보종합 3
 
3.0%

income_nm
Categorical

HIGH CORRELATION 

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

2023-12-10T19:16:00.282336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:16:00.470355image/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

HIGH CORRELATION 

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

2023-12-10T19:16:00.745677image/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

2023-12-10T19:16:00.948292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:16:01.141171image/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
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
98 
1.859
 
1
2.945
 
1

Length

Max length5
Median length3
Mean length3.04
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 98
98.0%
1.859 1
 
1.0%
2.945 1
 
1.0%

Length

2023-12-10T19:16:01.390471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:16:01.622398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 98
98.0%
1.859 1
 
1.0%
2.945 1
 
1.0%

Correlations

2023-12-10T19:16:01.853648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
brdcst_debrdcst_end_dechnnel_nmprogrm_begin_timeprogrm_end_timeprogrm_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nmaude_co
brdcst_de1.0000.9630.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
brdcst_end_de0.9631.0000.9630.9630.9630.9630.9630.9630.0000.5091.0000.000
chnnel_nm0.9630.9631.0000.9630.9630.9630.9630.9630.0000.5091.0000.000
progrm_begin_time0.9630.9630.9631.0000.9630.9630.9630.9630.0000.5091.0000.000
progrm_end_time0.9630.9630.9630.9631.0000.9630.9630.9630.0000.5091.0000.000
progrm_nm0.9630.9630.9630.9630.9631.0000.9630.9630.0000.5091.0000.000
progrm_genre_mlsfc_nm0.9630.9630.9630.9630.9630.9631.0000.9630.0000.5091.0000.000
progrm_genre_sclas_nm0.9630.9630.9630.9630.9630.9630.9631.0000.0000.5091.0000.000
income_nm0.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.045
acdmcr_nm0.5090.5090.5090.5090.5090.5090.5090.5090.0001.0000.7570.279
occp_nm1.0001.0001.0001.0001.0001.0001.0001.0000.0000.7571.0000.000
aude_co0.0000.0000.0000.0000.0000.0000.0000.0000.0450.2790.0001.000
2023-12-10T19:16:02.095339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
aude_coprogrm_genre_sclas_nmbrdcst_tme_nmoccp_nmchnnel_nmincome_nmbrdcst_end_deprogrm_genre_mlsfc_nmprogrm_nmbrdcst_deprogrm_end_timeprogrm_begin_timeacdmcr_nm
aude_co1.0000.0001.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.119
progrm_genre_sclas_nm0.0001.0001.0000.9950.8260.0000.8260.8260.8260.8260.8260.8260.375
brdcst_tme_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
occp_nm0.0000.9951.0001.0000.9950.0000.9950.9950.9950.9950.9950.9950.452
chnnel_nm0.0000.8261.0000.9951.0000.0000.8260.8260.8260.8260.8260.8260.375
income_nm0.0060.0001.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.000
brdcst_end_de0.0000.8261.0000.9950.8260.0001.0000.8260.8260.8260.8260.8260.375
progrm_genre_mlsfc_nm0.0000.8261.0000.9950.8260.0000.8261.0000.8260.8260.8260.8260.375
progrm_nm0.0000.8261.0000.9950.8260.0000.8260.8261.0000.8260.8260.8260.375
brdcst_de0.0000.8261.0000.9950.8260.0000.8260.8260.8261.0000.8260.8260.375
progrm_end_time0.0000.8261.0000.9950.8260.0000.8260.8260.8260.8261.0000.8260.375
progrm_begin_time0.0000.8261.0000.9950.8260.0000.8260.8260.8260.8260.8261.0000.375
acdmcr_nm0.1190.3751.0000.4520.3750.0000.3750.3750.3750.3750.3750.3751.000
2023-12-10T19:16:02.374151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
brdcst_debrdcst_end_dechnnel_nmprogrm_begin_timeprogrm_end_timeprogrm_nmbrdcst_tme_nmprogrm_genre_mlsfc_nmprogrm_genre_sclas_nmincome_nmacdmcr_nmoccp_nmaude_co
brdcst_de1.0000.8260.8260.8260.8260.8261.0000.8260.8260.0000.3750.9950.000
brdcst_end_de0.8261.0000.8260.8260.8260.8261.0000.8260.8260.0000.3750.9950.000
chnnel_nm0.8260.8261.0000.8260.8260.8261.0000.8260.8260.0000.3750.9950.000
progrm_begin_time0.8260.8260.8261.0000.8260.8261.0000.8260.8260.0000.3750.9950.000
progrm_end_time0.8260.8260.8260.8261.0000.8261.0000.8260.8260.0000.3750.9950.000
progrm_nm0.8260.8260.8260.8260.8261.0001.0000.8260.8260.0000.3750.9950.000
brdcst_tme_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
progrm_genre_mlsfc_nm0.8260.8260.8260.8260.8260.8261.0001.0000.8260.0000.3750.9950.000
progrm_genre_sclas_nm0.8260.8260.8260.8260.8260.8261.0000.8261.0000.0000.3750.9950.000
income_nm0.0000.0000.0000.0000.0000.0001.0000.0000.0001.0000.0000.0000.006
acdmcr_nm0.3750.3750.3750.3750.3750.3751.0000.3750.3750.0001.0000.4520.119
occp_nm0.9950.9950.9950.9950.9950.9951.0000.9950.9950.0000.4521.0000.000
aude_co0.0000.0000.0000.0000.0000.0001.0000.0000.0000.0060.1190.0001.000

Missing values

2023-12-10T19:15:55.626226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:15:55.992320image/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
02021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)수입없음초등졸 이하관리자0.0
12021103120211031KBS Story34510453502TV생생정보<NA>1415회전국정보정보종합정보종합400만원 이상~500만원 미만미취학무직0.0
22021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)100만원 이상~200만원 미만초등졸 이하관리자0.0
32021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)200만원 이상~300만원 미만초등졸 이하관리자0.0
42021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)300만원 이상~400만원 미만초등졸 이하관리자0.0
52021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)400만원 이상~500만원 미만초등졸 이하관리자0.0
62021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)500만원 이상~600만원 미만초등졸 이하관리자0.0
72021103120211031KBS Story34510453502TV생생정보<NA>1415회전국정보정보종합정보종합500만원 이상~600만원 미만미취학무직0.0
82021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)수입없음중졸관리자0.0
92021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)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
902021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)100만원 이상~200만원 미만미취학관리자0.0
912021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)200만원 이상~300만원 미만미취학관리자0.0
922021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)300만원 이상~400만원 미만미취학관리자0.0
932021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)400만원 이상~500만원 미만미취학관리자0.0
942021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)500만원 이상~600만원 미만미취학관리자0.0
952021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)600만원 이상미취학관리자0.0
962021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)수입없음초등졸 이하전문가 및 관련종사자0.0
972021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)100만원 미만초등졸 이하전문가 및 관련종사자0.0
982021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)100만원 이상~200만원 미만초등졸 이하전문가 및 관련종사자0.0
992021100120211001KBS15002750910생활의발견스페셜<KBS1><NA><NA>전국정보생활정보생활정보(가사)200만원 이상~300만원 미만초등졸 이하전문가 및 관련종사자0.0