Overview

Dataset statistics

Number of variables12
Number of observations223
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.0 KiB
Average record size in memory105.6 B

Variable types

Numeric8
Categorical3
Text1

Dataset

Description해외방송시장조사 보고서 중 OTT관련 이용행태 및 만족도 등에 대한 데이터 중 해외국가별(미국, 호주, 말레이시아, 영국, 터키, 러시아 등 15개국) 연령, 소득, 성별,고객가치, 직업 등에 따른 주로 이용하는 OTT 서비스에 대한 통계데이터
URLhttps://www.data.go.kr/data/15102285/fileData.do

Alerts

조사연도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
국가 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 기타(비율) and 2 other fieldsHigh correlation
넷플릭스(비율) is highly overall correlated with 조사연도 and 1 other fieldsHigh correlation
기타(비율) is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
넷플릭스(비율) has 4 (1.8%) zerosZeros
유튜브(비율) has 4 (1.8%) zerosZeros
아마존프리미엄비디오(비율) has 93 (41.7%) zerosZeros
디즈니플러스(비율) has 194 (87.0%) zerosZeros
애플티비(비율) has 190 (85.2%) zerosZeros
기타(비율) has 12 (5.4%) zerosZeros

Reproduction

Analysis started2023-12-12 10:24:00.744238
Analysis finished2023-12-12 10:24:08.853300
Duration8.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct223
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112
Minimum1
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:08.925150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.1
Q156.5
median112
Q3167.5
95-th percentile211.9
Maximum223
Range222
Interquartile range (IQR)111

Descriptive statistics

Standard deviation64.518731
Coefficient of variation (CV)0.5760601
Kurtosis-1.2
Mean112
Median Absolute Deviation (MAD)56
Skewness0
Sum24976
Variance4162.6667
MonotonicityStrictly increasing
2023-12-12T19:24:09.081724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
2 1
 
0.4%
143 1
 
0.4%
144 1
 
0.4%
145 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
Other values (213) 213
95.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%
217 1
0.4%
216 1
0.4%
215 1
0.4%
214 1
0.4%

조사연도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2019
103 
2020
90 
2018
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2019 103
46.2%
2020 90
40.4%
2018 30
 
13.5%

Length

2023-12-12T19:24:09.208956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:24:09.339844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 103
46.2%
2020 90
40.4%
2018 30
 
13.5%

국가
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
미국
31 
인도
18 
터키
18 
캐나다
18 
헝가리
18 
Other values (10)
120 

Length

Max length5
Median length4
Mean length2.6457399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미국 31
13.9%
인도 18
8.1%
터키 18
8.1%
캐나다 18
8.1%
헝가리 18
8.1%
영국 18
8.1%
호주 18
8.1%
러시아 18
8.1%
브라질 18
8.1%
UAE 18
8.1%
Other values (5) 30
13.5%

Length

2023-12-12T19:24:09.491326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미국 31
13.9%
인도 18
8.1%
터키 18
8.1%
캐나다 18
8.1%
헝가리 18
8.1%
영국 18
8.1%
호주 18
8.1%
러시아 18
8.1%
브라질 18
8.1%
uae 18
8.1%
Other values (5) 30
13.5%

분류
Categorical

Distinct9
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
연령별
80 
직업별
54 
소득별
27 
학력별
21 
성별
20 
Other values (4)
21 

Length

Max length3
Median length3
Mean length2.9103139
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연령별 80
35.9%
직업별 54
24.2%
소득별 27
 
12.1%
학력별 21
 
9.4%
성별 20
 
9.0%
가치별 8
 
3.6%
인종별 6
 
2.7%
국가별 4
 
1.8%
지역별 3
 
1.3%

Length

2023-12-12T19:24:09.631023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:24:09.786402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연령별 80
35.9%
직업별 54
24.2%
소득별 27
 
12.1%
학력별 21
 
9.4%
성별 20
 
9.0%
가치별 8
 
3.6%
인종별 6
 
2.7%
국가별 4
 
1.8%
지역별 3
 
1.3%

구분
Text

Distinct54
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T19:24:10.049414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length4.4887892
Min length2

Characters and Unicode

Total characters1001
Distinct characters82
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)13.0%

Sample

1st row전체
2nd row10대
3rd row20대
4th row30대
5th row40대
ValueCountFrequency (%)
이상 35
 
11.9%
10대 15
 
5.1%
30대 15
 
5.1%
20대 15
 
5.1%
이하 15
 
5.1%
50대 15
 
5.1%
40대 15
 
5.1%
남성 10
 
3.4%
여성 10
 
3.4%
고졸 10
 
3.4%
Other values (45) 138
47.1%
2023-12-12T19:24:10.488703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137
 
13.7%
대 86
 
8.6%
70
 
7.0%
이 51
 
5.1%
자 42
 
4.2%
상 36
 
3.6%
직 25
 
2.5%
여 22
 
2.2%
성 20
 
2.0%
졸 20
 
2.0%
Other values (72) 492
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 648
64.7%
Decimal Number 228
 
22.8%
Space Separator 70
 
7.0%
Other Punctuation 42
 
4.2%
Currency Symbol 8
 
0.8%
Math Symbol 3
 
0.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 86
 
13.3%
이 51
 
7.9%
자 42
 
6.5%
상 36
 
5.6%
직 25
 
3.9%
여 22
 
3.4%
성 20
 
3.1%
졸 20
 
3.1%
전 19
 
2.9%
무 16
 
2.5%
Other values (57) 311
48.0%
Decimal Number
ValueCountFrequency (%)
0 137
60.1%
2 19
 
8.3%
3 19
 
8.3%
5 17
 
7.5%
4 17
 
7.5%
1 17
 
7.5%
7 2
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 18
42.9%
/ 15
35.7%
· 9
21.4%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 648
64.7%
Common 351
35.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 86
 
13.3%
이 51
 
7.9%
자 42
 
6.5%
상 36
 
5.6%
직 25
 
3.9%
여 22
 
3.4%
성 20
 
3.1%
졸 20
 
3.1%
전 19
 
2.9%
무 16
 
2.5%
Other values (57) 311
48.0%
Common
ValueCountFrequency (%)
0 137
39.0%
70
19.9%
2 19
 
5.4%
3 19
 
5.4%
, 18
 
5.1%
5 17
 
4.8%
4 17
 
4.8%
1 17
 
4.8%
/ 15
 
4.3%
· 9
 
2.6%
Other values (3) 13
 
3.7%
Latin
ValueCountFrequency (%)
L 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 648
64.7%
ASCII 344
34.4%
None 9
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137
39.8%
70
20.3%
2 19
 
5.5%
3 19
 
5.5%
, 18
 
5.2%
5 17
 
4.9%
4 17
 
4.9%
1 17
 
4.9%
/ 15
 
4.4%
$ 8
 
2.3%
Other values (4) 7
 
2.0%
Hangul
ValueCountFrequency (%)
대 86
 
13.3%
이 51
 
7.9%
자 42
 
6.5%
상 36
 
5.6%
직 25
 
3.9%
여 22
 
3.4%
성 20
 
3.1%
졸 20
 
3.1%
전 19
 
2.9%
무 16
 
2.5%
Other values (57) 311
48.0%
None
ValueCountFrequency (%)
· 9
100.0%

사례수(명)
Real number (ℝ)

Distinct137
Distinct (%)61.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.748879
Minimum2
Maximum322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:10.698066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile17.1
Q145
median70
Q3135
95-th percentile222.7
Maximum322
Range320
Interquartile range (IQR)90

Descriptive statistics

Standard deviation69.380007
Coefficient of variation (CV)0.73225148
Kurtosis0.8157434
Mean94.748879
Median Absolute Deviation (MAD)37
Skewness1.1425193
Sum21129
Variance4813.5853
MonotonicityNot monotonic
2023-12-12T19:24:10.886380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65 5
 
2.2%
48 5
 
2.2%
45 4
 
1.8%
87 4
 
1.8%
39 4
 
1.8%
60 4
 
1.8%
64 4
 
1.8%
52 4
 
1.8%
58 4
 
1.8%
34 3
 
1.3%
Other values (127) 182
81.6%
ValueCountFrequency (%)
2 1
0.4%
4 1
0.4%
10 1
0.4%
11 1
0.4%
12 1
0.4%
14 2
0.9%
15 2
0.9%
16 2
0.9%
17 1
0.4%
18 1
0.4%
ValueCountFrequency (%)
322 1
0.4%
321 1
0.4%
319 1
0.4%
293 1
0.4%
281 1
0.4%
274 1
0.4%
267 1
0.4%
266 1
0.4%
260 1
0.4%
241 1
0.4%

넷플릭스(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct150
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.972646
Minimum0
Maximum81.8
Zeros4
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:11.103015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.36
Q129.7
median42
Q354.75
95-th percentile68.9
Maximum81.8
Range81.8
Interquartile range (IQR)25.05

Descriptive statistics

Standard deviation17.181354
Coefficient of variation (CV)0.40934647
Kurtosis-0.38150718
Mean41.972646
Median Absolute Deviation (MAD)12.6
Skewness-0.18358095
Sum9359.9
Variance295.19893
MonotonicityNot monotonic
2023-12-12T19:24:11.305763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.0 5
 
2.2%
24.0 4
 
1.8%
0.0 4
 
1.8%
38.0 4
 
1.8%
42.0 4
 
1.8%
25.0 4
 
1.8%
26.0 4
 
1.8%
31.0 4
 
1.8%
28.0 3
 
1.3%
35.0 3
 
1.3%
Other values (140) 184
82.5%
ValueCountFrequency (%)
0.0 4
1.8%
6.6 1
 
0.4%
7.1 1
 
0.4%
8.3 1
 
0.4%
9.1 1
 
0.4%
9.3 1
 
0.4%
10.7 1
 
0.4%
11.7 1
 
0.4%
12.3 1
 
0.4%
12.9 1
 
0.4%
ValueCountFrequency (%)
81.8 1
0.4%
81.1 1
0.4%
78.6 1
0.4%
76.3 1
0.4%
73.0 1
0.4%
71.7 1
0.4%
71.0 1
0.4%
70.7 1
0.4%
70.0 1
0.4%
69.9 1
0.4%

유튜브(비율)
Real number (ℝ)

ZEROS 

Distinct131
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.673543
Minimum0
Maximum68
Zeros4
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:11.519214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.51
Q110.95
median18
Q327.15
95-th percentile38.5
Maximum68
Range68
Interquartile range (IQR)16.2

Descriptive statistics

Standard deviation11.304785
Coefficient of variation (CV)0.57461869
Kurtosis0.74001568
Mean19.673543
Median Absolute Deviation (MAD)7.7
Skewness0.7259731
Sum4387.2
Variance127.79817
MonotonicityNot monotonic
2023-12-12T19:24:11.750392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.0 8
 
3.6%
25.0 6
 
2.7%
12.0 6
 
2.7%
10.0 5
 
2.2%
15.0 5
 
2.2%
20.0 5
 
2.2%
22.2 4
 
1.8%
10.3 4
 
1.8%
31.0 4
 
1.8%
21.0 4
 
1.8%
Other values (121) 172
77.1%
ValueCountFrequency (%)
0.0 4
1.8%
1.8 1
 
0.4%
2.7 1
 
0.4%
3.4 1
 
0.4%
3.7 1
 
0.4%
3.9 1
 
0.4%
4.2 1
 
0.4%
4.3 1
 
0.4%
4.5 1
 
0.4%
4.6 1
 
0.4%
ValueCountFrequency (%)
68.0 1
0.4%
53.0 1
0.4%
51.2 1
0.4%
45.8 1
0.4%
43.0 1
0.4%
41.7 1
0.4%
41.0 1
0.4%
40.5 1
0.4%
39.1 1
0.4%
39.0 1
0.4%

아마존프리미엄비디오(비율)
Real number (ℝ)

ZEROS 

Distinct89
Distinct (%)39.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5152466
Minimum0
Maximum50
Zeros93
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:11.960825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q37.7
95-th percentile24.9
Maximum50
Range50
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation7.7326522
Coefficient of variation (CV)1.4020501
Kurtosis6.0422351
Mean5.5152466
Median Absolute Deviation (MAD)3
Skewness2.1572299
Sum1229.9
Variance59.793911
MonotonicityNot monotonic
2023-12-12T19:24:12.151310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 93
41.7%
5.0 5
 
2.2%
7.7 5
 
2.2%
6.0 5
 
2.2%
3.0 4
 
1.8%
0.5 3
 
1.3%
4.2 3
 
1.3%
25.0 3
 
1.3%
4.3 3
 
1.3%
7.0 3
 
1.3%
Other values (79) 96
43.0%
ValueCountFrequency (%)
0.0 93
41.7%
0.4 1
 
0.4%
0.5 3
 
1.3%
0.9 1
 
0.4%
1.6 1
 
0.4%
1.7 1
 
0.4%
1.8 1
 
0.4%
1.9 1
 
0.4%
2.0 2
 
0.9%
2.2 1
 
0.4%
ValueCountFrequency (%)
50.0 1
 
0.4%
32.0 1
 
0.4%
30.0 1
 
0.4%
28.0 2
0.9%
27.0 2
0.9%
26.0 2
0.9%
25.0 3
1.3%
24.0 1
 
0.4%
23.0 1
 
0.4%
19.0 2
0.9%

디즈니플러스(비율)
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24125561
Minimum0
Maximum10
Zeros194
Zeros (%)87.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:12.304707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.5
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.93909207
Coefficient of variation (CV)3.8925192
Kurtosis62.316528
Mean0.24125561
Median Absolute Deviation (MAD)0
Skewness7.0385752
Sum53.8
Variance0.88189391
MonotonicityNot monotonic
2023-12-12T19:24:12.473587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 194
87.0%
1.5 3
 
1.3%
1.7 3
 
1.3%
1.3 3
 
1.3%
0.6 3
 
1.3%
0.4 2
 
0.9%
0.5 2
 
0.9%
2.4 2
 
0.9%
1.4 2
 
0.9%
2.1 1
 
0.4%
Other values (8) 8
 
3.6%
ValueCountFrequency (%)
0.0 194
87.0%
0.4 2
 
0.9%
0.5 2
 
0.9%
0.6 3
 
1.3%
0.8 1
 
0.4%
1.0 1
 
0.4%
1.1 1
 
0.4%
1.3 3
 
1.3%
1.4 2
 
0.9%
1.5 3
 
1.3%
ValueCountFrequency (%)
10.0 1
 
0.4%
6.7 1
 
0.4%
2.9 1
 
0.4%
2.6 1
 
0.4%
2.4 2
0.9%
2.1 1
 
0.4%
1.9 1
 
0.4%
1.7 3
1.3%
1.5 3
1.3%
1.4 2
0.9%

애플티비(비율)
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2058296
Minimum0
Maximum5.3
Zeros190
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:12.633792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.5
Maximum5.3
Range5.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.65972429
Coefficient of variation (CV)3.2051964
Kurtosis25.325464
Mean0.2058296
Median Absolute Deviation (MAD)0
Skewness4.5857822
Sum45.9
Variance0.43523613
MonotonicityNot monotonic
2023-12-12T19:24:12.781508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 190
85.2%
0.5 7
 
3.1%
1.6 3
 
1.3%
0.6 3
 
1.3%
1.5 3
 
1.3%
0.7 2
 
0.9%
2.2 2
 
0.9%
0.4 2
 
0.9%
1.8 1
 
0.4%
3.6 1
 
0.4%
Other values (9) 9
 
4.0%
ValueCountFrequency (%)
0.0 190
85.2%
0.4 2
 
0.9%
0.5 7
 
3.1%
0.6 3
 
1.3%
0.7 2
 
0.9%
0.8 1
 
0.4%
1.0 1
 
0.4%
1.1 1
 
0.4%
1.2 1
 
0.4%
1.4 1
 
0.4%
ValueCountFrequency (%)
5.3 1
 
0.4%
4.2 1
 
0.4%
3.6 1
 
0.4%
2.6 1
 
0.4%
2.2 2
0.9%
1.8 1
 
0.4%
1.7 1
 
0.4%
1.6 3
1.3%
1.5 3
1.3%
1.4 1
 
0.4%

기타(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct118
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.34574
Minimum0
Maximum75
Zeros12
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T19:24:13.318321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.11
Q16
median11.1
Q319
95-th percentile29.9
Maximum75
Range75
Interquartile range (IQR)13

Descriptive statistics

Standard deviation10.240235
Coefficient of variation (CV)0.76730362
Kurtosis5.5017071
Mean13.34574
Median Absolute Deviation (MAD)6.1
Skewness1.5881245
Sum2976.1
Variance104.8624
MonotonicityNot monotonic
2023-12-12T19:24:13.499988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 12
 
5.4%
7.0 6
 
2.7%
6.0 6
 
2.7%
26.0 6
 
2.7%
24.0 5
 
2.2%
4.0 5
 
2.2%
19.0 5
 
2.2%
27.0 5
 
2.2%
5.0 4
 
1.8%
29.0 4
 
1.8%
Other values (108) 165
74.0%
ValueCountFrequency (%)
0.0 12
5.4%
1.1 1
 
0.4%
1.3 1
 
0.4%
1.9 1
 
0.4%
2.0 2
 
0.9%
2.1 2
 
0.9%
2.4 1
 
0.4%
2.6 1
 
0.4%
2.9 3
 
1.3%
3.2 2
 
0.9%
ValueCountFrequency (%)
75.0 1
0.4%
50.0 1
0.4%
43.0 1
0.4%
41.0 1
0.4%
34.0 1
0.4%
33.0 2
0.9%
32.0 1
0.4%
31.0 2
0.9%
30.3 1
0.4%
30.0 1
0.4%

Interactions

2023-12-12T19:24:07.711887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.342793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.218945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.093712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.965661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.974277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.795565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.955343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.802570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.448737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.332455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.185629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.068949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.087240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.891347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.031698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.909502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.541278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.446961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.282572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.212065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.204679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.002648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.119089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:08.013063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.655138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.576187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.385589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.336370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.305887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.117001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.219638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:08.114110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.808120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.683288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.484863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.459341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.414565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.221942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.331383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:08.202521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:01.911552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.786283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.609573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.575876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.508711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.336990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.439963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:08.319912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.009592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.897788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.718769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.687586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.594573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.739065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.523239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:08.424768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.107164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:02.998873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:03.856397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:04.802959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:05.678934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:06.840192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:07.617821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:24:13.627953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번조사연도국가분류구분사례수(명)넷플릭스(비율)유튜브(비율)아마존프리미엄비디오(비율)디즈니플러스(비율)애플티비(비율)기타(비율)
연번1.0000.9480.9780.4890.0000.4510.7960.5060.5570.4910.3130.578
조사연도0.9481.0001.0000.7160.7100.2240.7270.5450.3690.3080.3580.564
국가0.9781.0001.0000.3560.0000.2550.8410.7630.7090.4670.3620.724
분류0.4890.7160.3561.0000.9990.6340.2220.0000.3350.0000.0000.277
구분0.0000.7100.0000.9991.0000.8010.0000.0000.8160.0000.0000.849
사례수(명)0.4510.2240.2550.6340.8011.0000.3570.0000.2750.0000.0000.000
넷플릭스(비율)0.7960.7270.8410.2220.0000.3571.0000.4100.4690.1870.0970.397
유튜브(비율)0.5060.5450.7630.0000.0000.0000.4101.0000.3460.0000.0000.231
아마존프리미엄비디오(비율)0.5570.3690.7090.3350.8160.2750.4690.3461.0000.0000.0000.829
디즈니플러스(비율)0.4910.3080.4670.0000.0000.0000.1870.0000.0001.0000.2780.000
애플티비(비율)0.3130.3580.3620.0000.0000.0000.0970.0000.0000.2781.0000.000
기타(비율)0.5780.5640.7240.2770.8490.0000.3970.2310.8290.0000.0001.000
2023-12-12T19:24:13.777364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류조사연도국가
분류1.0000.4170.150
조사연도0.4171.0000.972
국가0.1500.9721.000
2023-12-12T19:24:13.894768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사례수(명)넷플릭스(비율)유튜브(비율)아마존프리미엄비디오(비율)디즈니플러스(비율)애플티비(비율)기타(비율)조사연도국가분류
연번1.000-0.0490.414-0.0950.1800.3400.441-0.5320.9240.8320.263
사례수(명)-0.0491.0000.124-0.0660.1490.1070.1850.0510.1420.0910.360
넷플릭스(비율)0.4140.1241.000-0.4750.1180.003-0.013-0.3510.5810.5010.101
유튜브(비율)-0.095-0.066-0.4751.000-0.408-0.0710.006-0.0620.2840.4360.000
아마존프리미엄비디오(비율)0.1800.1490.118-0.4081.0000.0400.075-0.1490.2450.3870.179
디즈니플러스(비율)0.3400.1070.003-0.0710.0401.0000.320-0.2030.2350.2010.000
애플티비(비율)0.4410.185-0.0130.0060.0750.3201.000-0.2890.2410.1600.000
기타(비율)-0.5320.051-0.351-0.062-0.149-0.203-0.2891.0000.4250.4030.135
조사연도0.9240.1420.5810.2840.2450.2350.2410.4251.0000.9720.417
국가0.8320.0910.5010.4360.3870.2010.1600.4030.9721.0000.150
분류0.2630.3600.1010.0000.1790.0000.0000.1350.4170.1501.000

Missing values

2023-12-12T19:24:08.587487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:24:08.783942image/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

연번조사연도국가분류구분사례수(명)넷플릭스(비율)유튜브(비율)아마존프리미엄비디오(비율)디즈니플러스(비율)애플티비(비율)기타(비율)
012018말레이시아연령별전체19224.022.90.00.00.010.4
122018말레이시아연령별10대3638.922.20.00.00.011.1
232018말레이시아연령별20대4820.820.80.00.00.010.4
342018말레이시아연령별30대4520.017.80.00.00.011.1
452018말레이시아연령별40대4420.525.00.00.00.013.6
562018말레이시아연령별50대 이상1921.136.80.00.00.015.8
672018베트남연령별전체2667.127.80.00.00.010.5
782018베트남연령별10대368.333.30.00.00.08.3
892018베트남연령별20대6011.730.00.00.00.08.3
9102018베트남연령별30대780.024.40.00.00.023.1
연번조사연도국가분류구분사례수(명)넷플릭스(비율)유튜브(비율)아마존프리미엄비디오(비율)디즈니플러스(비율)애플티비(비율)기타(비율)
2132142020UAE학력별대졸 이상27441.227.45.80.40.47.0
2142152020UAE직업별전일제근로자19939.224.65.50.50.59.0
2152162020UAE직업별자영업자3429.426.55.90.00.02.9
2162172020UAE직업별시간제근로자1533.333.36.70.00.06.7
2172182020UAE직업별학생4650.026.10.00.02.20.0
2182192020UAE직업별가사노동자2821.432.13.60.03.67.1
2192202020UAE직업별은퇴자1643.818.812.50.00.00.0
2202212020UAE직업별무직/구직 중1250.025.08.30.00.00.0
2212222020UAE소득별평균 이하16533.923.64.20.61.88.4
2222232020UAE소득별평균 이상12245.125.47.40.00.04.1