Overview

Dataset statistics

Number of variables10
Number of observations955
Missing cells8
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory82.2 KiB
Average record size in memory88.1 B

Variable types

Numeric8
Categorical1
Text1

Dataset

Description장애인방송 의무사업자(지상파, 보도PP, 종편PP, SO)의 연도별 장애인방송 유형별(폐쇄자막방송, 화면해설방송, 수어통역방송) 목표 대비 실적 현황
URLhttps://www.data.go.kr/data/3068657/fileData.do

Alerts

연번 is highly overall correlated with 폐쇄자막방송_목표 and 4 other fieldsHigh correlation
폐쇄자막방송_목표 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
폐쇄자막방송_실적 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
화면해설방송_목표 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
화면해설방송_실적 is highly overall correlated with 폐쇄자막방송_목표 and 3 other fieldsHigh correlation
수어통역방송_목표 is highly overall correlated with 연번 and 5 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 04:53:42.505811
Analysis finished2023-12-12 04:53:52.778504
Duration10.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

평가년도
Real number (ℝ)

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.9173
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:52.840356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2019
Q32021
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0100546
Coefficient of variation (CV)0.0009956102
Kurtosis-1.2743328
Mean2018.9173
Median Absolute Deviation (MAD)2
Skewness0.066235058
Sum1928066
Variance4.0403196
MonotonicityIncreasing
2023-12-12T13:53:53.006707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2017 157
16.4%
2016 140
14.7%
2018 134
14.0%
2020 132
13.8%
2021 132
13.8%
2022 131
13.7%
2019 129
13.5%
ValueCountFrequency (%)
2016 140
14.7%
2017 157
16.4%
2018 134
14.0%
2019 129
13.5%
2020 132
13.8%
2021 132
13.8%
2022 131
13.7%
ValueCountFrequency (%)
2022 131
13.7%
2021 132
13.8%
2020 132
13.8%
2019 129
13.5%
2018 134
14.0%
2017 157
16.4%
2016 140
14.7%

구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
SO
474 
지상파
338 
PP
91 
종편PP
 
29
보도PP
 
15

Length

Max length4
Median length2
Mean length2.4460733
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SO 474
49.6%
지상파 338
35.4%
PP 91
 
9.5%
종편PP 29
 
3.0%
보도PP 15
 
1.6%
위성 8
 
0.8%

Length

2023-12-12T13:53:53.168587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:53.306550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
so 474
49.6%
지상파 338
35.4%
pp 91
 
9.5%
종편pp 29
 
3.0%
보도pp 15
 
1.6%
위성 8
 
0.8%

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct155
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.59267
Minimum1
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:53.456726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q134
median68
Q3102
95-th percentile130
Maximum155
Range154
Interquartile range (IQR)68

Descriptive statistics

Standard deviation39.709804
Coefficient of variation (CV)0.57892197
Kurtosis-1.1202217
Mean68.59267
Median Absolute Deviation (MAD)34
Skewness0.054998349
Sum65506
Variance1576.8685
MonotonicityNot monotonic
2023-12-12T13:53:53.649588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 8
 
0.8%
30 8
 
0.8%
29 8
 
0.8%
55 8
 
0.8%
1 7
 
0.7%
89 7
 
0.7%
85 7
 
0.7%
86 7
 
0.7%
87 7
 
0.7%
88 7
 
0.7%
Other values (145) 881
92.3%
ValueCountFrequency (%)
1 7
0.7%
2 7
0.7%
3 7
0.7%
4 7
0.7%
5 7
0.7%
6 7
0.7%
7 7
0.7%
8 7
0.7%
9 7
0.7%
10 7
0.7%
ValueCountFrequency (%)
155 1
0.1%
154 1
0.1%
153 1
0.1%
152 1
0.1%
151 1
0.1%
150 1
0.1%
149 1
0.1%
148 1
0.1%
147 1
0.1%
146 2
0.2%

방송사업자명
Text

Distinct381
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2023-12-12T13:53:53.917645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length11.572775
Min length2

Characters and Unicode

Total characters11052
Distinct characters202
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)15.9%

Sample

1st row한국방송공사
2nd row(주)문화방송
3rd row(주)SBS
4th row한국교육방송공사
5th row한국방송공사(부산방송총국)
ValueCountFrequency (%)
주)딜라이브 97
 
6.3%
주식회사 78
 
5.1%
엘지헬로비전 69
 
4.5%
주)씨제이헬로비전 66
 
4.3%
주)티브로드 54
 
3.5%
주)현대hcn 41
 
2.7%
채널 24
 
1.6%
주)skb 24
 
1.6%
주)씨제이헬로 23
 
1.5%
주)씨엠비 21
 
1.4%
Other values (305) 1031
67.5%
2023-12-12T13:53:54.330398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 786
 
7.1%
( 703
 
6.4%
) 703
 
6.4%
송 622
 
5.6%
방 615
 
5.6%
573
 
5.2%
이 534
 
4.8%
브 290
 
2.6%
로 249
 
2.3%
비 216
 
2.0%
Other values (192) 5761
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8168
73.9%
Uppercase Letter 752
 
6.8%
Open Punctuation 703
 
6.4%
Close Punctuation 703
 
6.4%
Space Separator 573
 
5.2%
Other Symbol 78
 
0.7%
Decimal Number 43
 
0.4%
Lowercase Letter 31
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 786
 
9.6%
송 622
 
7.6%
방 615
 
7.5%
이 534
 
6.5%
브 290
 
3.6%
로 249
 
3.0%
비 216
 
2.6%
전 208
 
2.5%
티 201
 
2.5%
씨 174
 
2.1%
Other values (149) 4273
52.3%
Uppercase Letter
ValueCountFrequency (%)
B 163
21.7%
S 132
17.6%
K 112
14.9%
C 92
12.2%
N 72
9.6%
H 42
 
5.6%
M 35
 
4.7%
T 34
 
4.5%
V 22
 
2.9%
J 10
 
1.3%
Other values (9) 38
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
t 8
25.8%
v 6
19.4%
o 3
 
9.7%
m 2
 
6.5%
p 2
 
6.5%
r 2
 
6.5%
s 2
 
6.5%
u 1
 
3.2%
z 1
 
3.2%
i 1
 
3.2%
Other values (3) 3
 
9.7%
Decimal Number
ValueCountFrequency (%)
1 17
39.5%
2 10
23.3%
4 7
16.3%
3 5
 
11.6%
0 3
 
7.0%
9 1
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 703
100.0%
Close Punctuation
ValueCountFrequency (%)
) 703
100.0%
Space Separator
ValueCountFrequency (%)
573
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 78
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8246
74.6%
Common 2023
 
18.3%
Latin 783
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 786
 
9.5%
송 622
 
7.5%
방 615
 
7.5%
이 534
 
6.5%
브 290
 
3.5%
로 249
 
3.0%
비 216
 
2.6%
전 208
 
2.5%
티 201
 
2.4%
씨 174
 
2.1%
Other values (150) 4351
52.8%
Latin
ValueCountFrequency (%)
B 163
20.8%
S 132
16.9%
K 112
14.3%
C 92
11.7%
N 72
9.2%
H 42
 
5.4%
M 35
 
4.5%
T 34
 
4.3%
V 22
 
2.8%
J 10
 
1.3%
Other values (22) 69
8.8%
Common
ValueCountFrequency (%)
( 703
34.8%
) 703
34.8%
573
28.3%
1 17
 
0.8%
2 10
 
0.5%
4 7
 
0.3%
3 5
 
0.2%
0 3
 
0.1%
, 1
 
< 0.1%
9 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8168
73.9%
ASCII 2806
 
25.4%
None 78
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 786
 
9.6%
송 622
 
7.6%
방 615
 
7.5%
이 534
 
6.5%
브 290
 
3.6%
로 249
 
3.0%
비 216
 
2.6%
전 208
 
2.5%
티 201
 
2.5%
씨 174
 
2.1%
Other values (149) 4273
52.3%
ASCII
ValueCountFrequency (%)
( 703
25.1%
) 703
25.1%
573
20.4%
B 163
 
5.8%
S 132
 
4.7%
K 112
 
4.0%
C 92
 
3.3%
N 72
 
2.6%
H 42
 
1.5%
M 35
 
1.2%
Other values (32) 179
 
6.4%
None
ValueCountFrequency (%)
㈜ 78
100.0%

폐쇄자막방송_목표
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.9%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean79.931794
Minimum0
Maximum100
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:54.486383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile60
Q170
median70
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.8321
Coefficient of variation (CV)0.22309145
Kurtosis0.32299051
Mean79.931794
Median Absolute Deviation (MAD)0
Skewness-0.42082995
Sum76175
Variance317.98379
MonotonicityNot monotonic
2023-12-12T13:53:54.646221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
70 496
51.9%
100 374
39.2%
60 42
 
4.4%
30 24
 
2.5%
45 9
 
0.9%
50 3
 
0.3%
0 2
 
0.2%
90 2
 
0.2%
80 1
 
0.1%
(Missing) 2
 
0.2%
ValueCountFrequency (%)
0 2
 
0.2%
30 24
 
2.5%
45 9
 
0.9%
50 3
 
0.3%
60 42
 
4.4%
70 496
51.9%
80 1
 
0.1%
90 2
 
0.2%
100 374
39.2%
ValueCountFrequency (%)
100 374
39.2%
90 2
 
0.2%
80 1
 
0.1%
70 496
51.9%
60 42
 
4.4%
50 3
 
0.3%
45 9
 
0.9%
30 24
 
2.5%
0 2
 
0.2%

폐쇄자막방송_실적
Real number (ℝ)

HIGH CORRELATION 

Distinct359
Distinct (%)37.7%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean84.272036
Minimum3.25
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:54.802638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.25
5-th percentile70
Q173.92
median80.46
Q3100
95-th percentile100
Maximum100
Range96.75
Interquartile range (IQR)26.08

Descriptive statistics

Standard deviation14.901404
Coefficient of variation (CV)0.17682501
Kurtosis1.7110937
Mean84.272036
Median Absolute Deviation (MAD)9.2
Skewness-0.84767264
Sum80311.25
Variance222.05183
MonotonicityNot monotonic
2023-12-12T13:53:55.003653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 302
31.6%
99.99 33
 
3.5%
99.9 22
 
2.3%
73.0 13
 
1.4%
77.3 13
 
1.4%
72.9 9
 
0.9%
76.05 8
 
0.8%
73.1 8
 
0.8%
73.95 6
 
0.6%
71.1 6
 
0.6%
Other values (349) 533
55.8%
ValueCountFrequency (%)
3.25 1
0.1%
27.79 1
0.1%
29.14 1
0.1%
30.6 1
0.1%
30.9 1
0.1%
31.4 1
0.1%
31.5 1
0.1%
32.4 1
0.1%
32.5 1
0.1%
32.8 1
0.1%
ValueCountFrequency (%)
100.0 302
31.6%
99.99 33
 
3.5%
99.98 5
 
0.5%
99.97 5
 
0.5%
99.95 1
 
0.1%
99.94 1
 
0.1%
99.93 2
 
0.2%
99.9 22
 
2.3%
99.87 1
 
0.1%
99.81 1
 
0.1%

화면해설방송_목표
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)1.0%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean7.8856243
Minimum2
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:55.144798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q17
median7
Q310
95-th percentile10
Maximum10
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9278022
Coefficient of variation (CV)0.24447046
Kurtosis-0.056838844
Mean7.8856243
Median Absolute Deviation (MAD)2
Skewness-0.47864815
Sum7515
Variance3.7164213
MonotonicityNot monotonic
2023-12-12T13:53:55.260194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
7.0 467
48.9%
10.0 375
39.3%
5.0 74
 
7.7%
3.0 15
 
1.6%
2.0 14
 
1.5%
5.5 2
 
0.2%
6.0 2
 
0.2%
9.0 2
 
0.2%
4.0 1
 
0.1%
8.0 1
 
0.1%
(Missing) 2
 
0.2%
ValueCountFrequency (%)
2.0 14
 
1.5%
3.0 15
 
1.6%
4.0 1
 
0.1%
5.0 74
 
7.7%
5.5 2
 
0.2%
6.0 2
 
0.2%
7.0 467
48.9%
8.0 1
 
0.1%
9.0 2
 
0.2%
10.0 375
39.3%
ValueCountFrequency (%)
10.0 375
39.3%
9.0 2
 
0.2%
8.0 1
 
0.1%
7.0 467
48.9%
6.0 2
 
0.2%
5.5 2
 
0.2%
5.0 74
 
7.7%
4.0 1
 
0.1%
3.0 15
 
1.6%
2.0 14
 
1.5%

화면해설방송_실적
Real number (ℝ)

HIGH CORRELATION 

Distinct418
Distinct (%)43.9%
Missing2
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean11.182267
Minimum1.99
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:55.403469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.99
5-th percentile5.9
Q18.65
median11.1
Q312.7
95-th percentile17.412
Maximum100
Range98.01
Interquartile range (IQR)4.05

Descriptive statistics

Standard deviation4.7720691
Coefficient of variation (CV)0.4267533
Kurtosis141.66011
Mean11.182267
Median Absolute Deviation (MAD)2.1
Skewness8.3914335
Sum10656.7
Variance22.772644
MonotonicityNot monotonic
2023-12-12T13:53:55.583613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.6 22
 
2.3%
12.3 20
 
2.1%
10.5 14
 
1.5%
9.2 13
 
1.4%
13.2 12
 
1.3%
11.45 12
 
1.3%
11.61 11
 
1.2%
13.5 11
 
1.2%
10.4 11
 
1.2%
12.0 11
 
1.2%
Other values (408) 816
85.4%
ValueCountFrequency (%)
1.99 1
0.1%
2.0 1
0.1%
2.08 1
0.1%
2.26 1
0.1%
2.3 1
0.1%
2.47 1
0.1%
2.5 1
0.1%
2.6 1
0.1%
2.64 1
0.1%
2.7 1
0.1%
ValueCountFrequency (%)
100.0 1
0.1%
64.8 1
0.1%
27.74 1
0.1%
23.39 1
0.1%
23.01 1
0.1%
21.87 1
0.1%
21.7 1
0.1%
20.6 1
0.1%
20.58 1
0.1%
19.76 1
0.1%

수어통역방송_목표
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.228
Minimum1
Maximum5.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:55.737207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q35
95-th percentile5.06
Maximum5.06
Range4.06
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8265635
Coefficient of variation (CV)0.19549752
Kurtosis3.8113687
Mean4.228
Median Absolute Deviation (MAD)1
Skewness-1.5516786
Sum4037.74
Variance0.68320721
MonotonicityNot monotonic
2023-12-12T13:53:55.883394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4.0 468
49.0%
5.0 323
33.8%
3.0 76
 
8.0%
5.06 54
 
5.7%
1.0 23
 
2.4%
2.0 8
 
0.8%
2.5 1
 
0.1%
3.5 1
 
0.1%
4.5 1
 
0.1%
ValueCountFrequency (%)
1.0 23
 
2.4%
2.0 8
 
0.8%
2.5 1
 
0.1%
3.0 76
 
8.0%
3.5 1
 
0.1%
4.0 468
49.0%
4.5 1
 
0.1%
5.0 323
33.8%
5.06 54
 
5.7%
ValueCountFrequency (%)
5.06 54
 
5.7%
5.0 323
33.8%
4.5 1
 
0.1%
4.0 468
49.0%
3.5 1
 
0.1%
3.0 76
 
8.0%
2.5 1
 
0.1%
2.0 8
 
0.8%
1.0 23
 
2.4%

수어통역방송_실적
Real number (ℝ)

Distinct393
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6514346
Minimum1.03
Maximum44.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2023-12-12T13:53:56.048572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.03
5-th percentile3.528
Q15.56
median6.91
Q39
95-th percentile13.66
Maximum44.96
Range43.93
Interquartile range (IQR)3.44

Descriptive statistics

Standard deviation3.7075462
Coefficient of variation (CV)0.48455569
Kurtosis25.256143
Mean7.6514346
Median Absolute Deviation (MAD)1.61
Skewness3.6117055
Sum7307.12
Variance13.745899
MonotonicityNot monotonic
2023-12-12T13:53:56.203290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.6 23
 
2.4%
7.3 23
 
2.4%
9.1 20
 
2.1%
6.4 20
 
2.1%
6.0 19
 
2.0%
6.71 12
 
1.3%
6.2 12
 
1.3%
7.1 10
 
1.0%
5.7 10
 
1.0%
6.3 10
 
1.0%
Other values (383) 796
83.4%
ValueCountFrequency (%)
1.03 1
 
0.1%
1.1 1
 
0.1%
1.2 1
 
0.1%
1.5 1
 
0.1%
1.7 2
0.2%
2.0 1
 
0.1%
2.2 4
0.4%
2.26 1
 
0.1%
2.3 1
 
0.1%
2.4 1
 
0.1%
ValueCountFrequency (%)
44.96 1
0.1%
40.43 1
0.1%
35.78 1
0.1%
33.8 1
0.1%
30.36 1
0.1%
26.21 2
0.2%
25.1 1
0.1%
20.8 1
0.1%
20.5 1
0.1%
20.1 1
0.1%

Interactions

2023-12-12T13:53:50.921974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.055658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.275971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.435747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.405014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.466653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.654524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.834454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.049731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.168427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.396358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.555050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.571454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.606970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.818868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.988253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.186841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.286978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.527654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.688443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.709411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.776588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.950609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.143888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.295203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.395666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.676175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.807333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.820246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.932784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.067189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.271848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.421691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.515438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.863645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.914526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.957423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.081959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.214103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.399277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.585687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.625673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:44.999750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.051983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.102682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.219003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.364849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.553199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.704922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.735210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.115624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.182369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.207055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.331281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.508660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.674782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:51.873707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:43.860240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:45.288588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:46.302755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:47.351903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:48.510825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:49.700427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:53:50.805682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:53:56.336212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가년도구분연번폐쇄자막방송_목표폐쇄자막방송_실적화면해설방송_목표화면해설방송_실적수어통역방송_목표수어통역방송_실적
평가년도1.0000.0000.1790.1870.2380.1270.2130.1340.324
구분0.0001.0000.8300.6780.7310.8230.3060.7970.453
연번0.1790.8301.0000.6680.6610.8530.4860.7350.584
폐쇄자막방송_목표0.1870.6780.6681.0000.8380.9240.3570.9590.330
폐쇄자막방송_실적0.2380.7310.6610.8381.0000.7770.3980.7840.375
화면해설방송_목표0.1270.8230.8530.9240.7771.0000.4900.8960.518
화면해설방송_실적0.2130.3060.4860.3570.3980.4901.0000.3990.290
수어통역방송_목표0.1340.7970.7350.9590.7840.8960.3991.0000.415
수어통역방송_실적0.3240.4530.5840.3300.3750.5180.2900.4151.000
2023-12-12T13:53:56.495699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가년도연번폐쇄자막방송_목표폐쇄자막방송_실적화면해설방송_목표화면해설방송_실적수어통역방송_목표수어통역방송_실적구분
평가년도1.000-0.0620.1190.0460.0470.1150.1110.1730.000
연번-0.0621.000-0.812-0.762-0.892-0.386-0.876-0.4360.630
폐쇄자막방송_목표0.119-0.8121.0000.8630.9290.5390.9180.3750.462
폐쇄자막방송_실적0.046-0.7620.8631.0000.8360.5000.8310.3740.469
화면해설방송_목표0.047-0.8920.9290.8361.0000.5230.9830.4540.615
화면해설방송_실적0.115-0.3860.5390.5000.5231.0000.5320.3900.213
수어통역방송_목표0.111-0.8760.9180.8310.9830.5321.0000.4860.605
수어통역방송_실적0.173-0.4360.3750.3740.4540.3900.4861.0000.257
구분0.0000.6300.4620.4690.6150.2130.6050.2571.000

Missing values

2023-12-12T13:53:52.338297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:53:52.546520image/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.
2023-12-12T13:53:52.691247image/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

평가년도구분연번방송사업자명폐쇄자막방송_목표폐쇄자막방송_실적화면해설방송_목표화면해설방송_실적수어통역방송_목표수어통역방송_실적
02016지상파1한국방송공사100100.010.011.15.06.0
12016지상파2(주)문화방송100100.010.011.05.06.2
22016지상파3(주)SBS100100.010.010.65.05.7
32016지상파4한국교육방송공사100100.010.012.25.06.1
42016지상파5한국방송공사(부산방송총국)100100.010.010.55.06.2
52016지상파6한국방송공사(창원방송총국)100100.010.010.55.06.2
62016지상파7한국방송공사(대구방송총국)100100.010.010.55.06.2
72016지상파8한국방송공사(대전방송총국)100100.010.010.55.06.2
82016지상파9한국방송공사(광주방송총국)100100.010.010.45.06.3
92016지상파10한국방송공사(전주방송총국)100100.010.010.45.06.3
평가년도구분연번방송사업자명폐쇄자막방송_목표폐쇄자막방송_실적화면해설방송_목표화면해설방송_실적수어통역방송_목표수어통역방송_실적
9452022PP122㈜엠비씨플러스(4개 채널)7078.055.08.193.05.81
9462022PP123㈜에스비에스플러스(2개 채널)7079.235.05.493.03.54
9472022PP124씨제이이앤엠㈜(10개 채널)7078.945.023.013.04.61
9482022PP125제이티비씨포 주식회사(1개 채널)7073.25.09.53.05.88
9492022PP126㈜에스비에스미디어넷(2개 채널)7075.885.010.833.07.3
9502022PP127㈜이채널7076.535.07.833.04.01
9512022PP128㈜미디어넷플러스(kizmom)7091.25.06.573.06.3
9522022PP129㈜ 현대홈쇼핑7070.835.07.823.03.03
9532022PP130㈜ 채널더무비(더 무비)7083.295.027.743.08.91
9542022PP131㈜아이에이치큐(2개채널)7073.855.05.383.04.22