Overview

Dataset statistics

Number of variables12
Number of observations190
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.4 KiB
Average record size in memory104.7 B

Variable types

Numeric7
Categorical5

Dataset

Description해외방송시장조사 보고서 중 OTT관련 이용행태 및 만족도 등에 대한 데이터 중 국가별(영국, 호주, 러시아 등 5개국) 연령, 소득, 인종, 지역, 학력 성별 OTT 서비스 주로 이용하는 장소에 대한 통계데이터
URLhttps://www.data.go.kr/data/15102277/fileData.do

Alerts

조사연도 has constant value ""Constant
구분 is highly overall correlated with 사례수(명) and 1 other fieldsHigh correlation
분류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 학교직장(비율) and 2 other fieldsHigh correlation
사례수(명) is highly overall correlated with 분류 and 1 other fieldsHigh correlation
집(비율) is highly overall correlated with 학교직장(비율) and 3 other fieldsHigh correlation
학교직장(비율) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
교통수단(비율) is highly overall correlated with 집(비율) and 1 other fieldsHigh correlation
실내공간(집학교직장제외)(비율) is highly overall correlated with 집(비율) and 1 other fieldsHigh correlation
실외공간(비율) is highly overall correlated with 집(비율)High correlation
주말구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
학교직장(비율) has 27 (14.2%) zerosZeros
교통수단(비율) has 28 (14.7%) zerosZeros
실내공간(집학교직장제외)(비율) has 23 (12.1%) zerosZeros
실외공간(비율) has 32 (16.8%) zerosZeros

Reproduction

Analysis started2023-12-13 00:34:11.591099
Analysis finished2023-12-13 00:34:15.671136
Duration4.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.5
Minimum1
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:15.724590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.45
Q148.25
median95.5
Q3142.75
95-th percentile180.55
Maximum190
Range189
Interquartile range (IQR)94.5

Descriptive statistics

Standard deviation54.992424
Coefficient of variation (CV)0.5758369
Kurtosis-1.2
Mean95.5
Median Absolute Deviation (MAD)47.5
Skewness0
Sum18145
Variance3024.1667
MonotonicityStrictly increasing
2023-12-13T09:34:15.839499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
132 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
Other values (180) 180
94.7%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%

조사연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2020
190 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 190
100.0%

Length

2023-12-13T09:34:15.940587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:34:16.013034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 190
100.0%

국가
Categorical

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
영국
38 
호주
38 
러시아
38 
브라질
38 
UAE
38 

Length

Max length3
Median length3
Mean length2.6
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영국
2nd row호주
3rd row러시아
4th row브라질
5th rowUAE

Common Values

ValueCountFrequency (%)
영국 38
20.0%
호주 38
20.0%
러시아 38
20.0%
브라질 38
20.0%
UAE 38
20.0%

Length

2023-12-13T09:34:16.098762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:34:16.180665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영국 38
20.0%
호주 38
20.0%
러시아 38
20.0%
브라질 38
20.0%
uae 38
20.0%

분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
직업별
70 
연령별
50 
성별
20 
학력별
20 
소득별
20 

Length

Max length3
Median length3
Mean length2.8947368
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
직업별 70
36.8%
연령별 50
26.3%
성별 20
 
10.5%
학력별 20
 
10.5%
소득별 20
 
10.5%
국가별 10
 
5.3%

Length

2023-12-13T09:34:16.278701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:34:16.380351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직업별 70
36.8%
연령별 50
26.3%
성별 20
 
10.5%
학력별 20
 
10.5%
소득별 20
 
10.5%
국가별 10
 
5.3%

구분
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
전체
 
10
남성
 
10
여성
 
10
10대
 
10
20대
 
10
Other values (14)
140 

Length

Max length7
Median length6
Mean length4.0526316
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 10
 
5.3%
남성 10
 
5.3%
여성 10
 
5.3%
10대 10
 
5.3%
20대 10
 
5.3%
30대 10
 
5.3%
40대 10
 
5.3%
50대 이상 10
 
5.3%
고졸 이하 10
 
5.3%
대졸 이상 10
 
5.3%
Other values (9) 90
47.4%

Length

2023-12-13T09:34:16.486803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이상 30
 
12.0%
이하 20
 
8.0%
평균 20
 
8.0%
10대 10
 
4.0%
20대 10
 
4.0%
중 10
 
4.0%
무직/구직 10
 
4.0%
은퇴자 10
 
4.0%
가사노동자 10
 
4.0%
학생 10
 
4.0%
Other values (11) 110
44.0%

사례수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.53684
Minimum10
Maximum373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:16.580283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q138.25
median75
Q3165.75
95-th percentile288.85
Maximum373
Range363
Interquartile range (IQR)127.5

Descriptive statistics

Standard deviation86.927789
Coefficient of variation (CV)0.8159411
Kurtosis1.3760483
Mean106.53684
Median Absolute Deviation (MAD)46
Skewness1.2839895
Sum20242
Variance7556.4404
MonotonicityNot monotonic
2023-12-13T09:34:16.692435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65 6
 
3.2%
185 4
 
2.1%
103 4
 
2.1%
59 4
 
2.1%
64 4
 
2.1%
15 4
 
2.1%
48 4
 
2.1%
45 4
 
2.1%
34 4
 
2.1%
52 4
 
2.1%
Other values (70) 148
77.9%
ValueCountFrequency (%)
10 2
1.1%
11 2
1.1%
12 2
1.1%
14 2
1.1%
15 4
2.1%
16 2
1.1%
18 2
1.1%
19 2
1.1%
20 2
1.1%
22 2
1.1%
ValueCountFrequency (%)
373 2
1.1%
368 2
1.1%
367 2
1.1%
355 2
1.1%
301 2
1.1%
274 2
1.1%
260 2
1.1%
220 2
1.1%
210 2
1.1%
200 2
1.1%

집(비율)
Real number (ℝ)

HIGH CORRELATION 

Distinct142
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.434211
Minimum47.4
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:16.802061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47.4
5-th percentile60
Q171.875
median77.65
Q386.65
95-th percentile94.055
Maximum100
Range52.6
Interquartile range (IQR)14.775

Descriptive statistics

Standard deviation10.595264
Coefficient of variation (CV)0.13508473
Kurtosis-0.37110024
Mean78.434211
Median Absolute Deviation (MAD)7.7
Skewness-0.23198555
Sum14902.5
Variance112.25962
MonotonicityNot monotonic
2023-12-13T09:34:16.911788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.8 4
 
2.1%
78.5 3
 
1.6%
92.0 3
 
1.6%
70.0 3
 
1.6%
100.0 3
 
1.6%
86.7 3
 
1.6%
75.0 3
 
1.6%
76.9 3
 
1.6%
91.7 3
 
1.6%
88.9 2
 
1.1%
Other values (132) 160
84.2%
ValueCountFrequency (%)
47.4 1
0.5%
52.9 1
0.5%
53.3 1
0.5%
56.5 1
0.5%
57.1 1
0.5%
57.8 1
0.5%
58.8 1
0.5%
59.4 1
0.5%
59.5 1
0.5%
60.0 2
1.1%
ValueCountFrequency (%)
100.0 3
1.6%
97.1 2
1.1%
95.8 1
 
0.5%
95.5 1
 
0.5%
95.3 1
 
0.5%
94.8 1
 
0.5%
94.1 1
 
0.5%
94.0 1
 
0.5%
93.9 1
 
0.5%
93.8 1
 
0.5%

학교직장(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct93
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5215789
Minimum0
Maximum21.7
Zeros27
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:17.015559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.225
median5.05
Q37.7
95-th percentile14.435
Maximum21.7
Range21.7
Interquartile range (IQR)5.475

Descriptive statistics

Standard deviation4.5989656
Coefficient of variation (CV)0.83290769
Kurtosis1.8207892
Mean5.5215789
Median Absolute Deviation (MAD)2.8
Skewness1.2010127
Sum1049.1
Variance21.150484
MonotonicityNot monotonic
2023-12-13T09:34:17.115919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 27
 
14.2%
6.7 6
 
3.2%
10.7 5
 
2.6%
7.1 5
 
2.6%
6.8 4
 
2.1%
1.6 4
 
2.1%
4.0 4
 
2.1%
3.4 3
 
1.6%
5.6 3
 
1.6%
2.6 3
 
1.6%
Other values (83) 126
66.3%
ValueCountFrequency (%)
0.0 27
14.2%
0.5 1
 
0.5%
0.6 1
 
0.5%
0.9 2
 
1.1%
1.0 2
 
1.1%
1.1 1
 
0.5%
1.2 2
 
1.1%
1.3 1
 
0.5%
1.5 1
 
0.5%
1.6 4
 
2.1%
ValueCountFrequency (%)
21.7 1
0.5%
21.1 1
0.5%
20.6 1
0.5%
20.0 2
1.1%
18.0 1
0.5%
16.9 1
0.5%
16.2 1
0.5%
15.8 1
0.5%
15.2 1
0.5%
13.5 1
0.5%

교통수단(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct84
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0484211
Minimum0
Maximum18.2
Zeros28
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:17.218845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6
median5
Q37.325
95-th percentile10.72
Maximum18.2
Range18.2
Interquartile range (IQR)4.725

Descriptive statistics

Standard deviation3.5324456
Coefficient of variation (CV)0.69971296
Kurtosis0.57028495
Mean5.0484211
Median Absolute Deviation (MAD)2.4
Skewness0.55291761
Sum959.2
Variance12.478172
MonotonicityNot monotonic
2023-12-13T09:34:17.323105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 28
 
14.7%
6.8 5
 
2.6%
4.4 5
 
2.6%
7.6 5
 
2.6%
5.0 5
 
2.6%
5.9 4
 
2.1%
3.1 4
 
2.1%
6.3 4
 
2.1%
5.6 4
 
2.1%
3.4 3
 
1.6%
Other values (74) 123
64.7%
ValueCountFrequency (%)
0.0 28
14.7%
0.5 1
 
0.5%
1.0 1
 
0.5%
1.1 3
 
1.6%
1.2 2
 
1.1%
1.3 1
 
0.5%
1.5 2
 
1.1%
1.6 1
 
0.5%
1.9 2
 
1.1%
2.0 2
 
1.1%
ValueCountFrequency (%)
18.2 1
0.5%
16.7 1
0.5%
13.6 1
0.5%
13.3 1
0.5%
13.2 1
0.5%
12.8 1
0.5%
11.9 1
0.5%
11.4 1
0.5%
11.1 1
0.5%
10.9 1
0.5%

실내공간(집학교직장제외)(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct97
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0594737
Minimum0
Maximum21.4
Zeros23
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:17.433337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.125
median5.5
Q38.775
95-th percentile13.665
Maximum21.4
Range21.4
Interquartile range (IQR)5.65

Descriptive statistics

Standard deviation4.2794068
Coefficient of variation (CV)0.70623407
Kurtosis0.88175969
Mean6.0594737
Median Absolute Deviation (MAD)2.8
Skewness0.78142497
Sum1151.3
Variance18.313322
MonotonicityNot monotonic
2023-12-13T09:34:17.531647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 23
 
12.1%
6.7 6
 
3.2%
8.8 4
 
2.1%
5.3 4
 
2.1%
4.9 4
 
2.1%
5.0 4
 
2.1%
8.3 4
 
2.1%
2.7 4
 
2.1%
3.8 4
 
2.1%
5.8 3
 
1.6%
Other values (87) 130
68.4%
ValueCountFrequency (%)
0.0 23
12.1%
0.9 1
 
0.5%
1.1 1
 
0.5%
1.2 1
 
0.5%
1.5 2
 
1.1%
1.6 3
 
1.6%
1.7 2
 
1.1%
2.0 1
 
0.5%
2.2 1
 
0.5%
2.3 2
 
1.1%
ValueCountFrequency (%)
21.4 1
0.5%
21.1 1
0.5%
17.9 1
0.5%
17.4 1
0.5%
15.5 1
0.5%
15.4 1
0.5%
15.0 1
0.5%
14.7 1
0.5%
14.5 1
0.5%
13.8 1
0.5%

실외공간(비율)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4347368
Minimum0
Maximum26.7
Zeros32
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T09:34:17.644870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.6
median4.55
Q36.7
95-th percentile9.865
Maximum26.7
Range26.7
Interquartile range (IQR)5.1

Descriptive statistics

Standard deviation3.6224686
Coefficient of variation (CV)0.81683959
Kurtosis6.9098491
Mean4.4347368
Median Absolute Deviation (MAD)2.35
Skewness1.5336642
Sum842.6
Variance13.122279
MonotonicityNot monotonic
2023-12-13T09:34:17.776488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 32
 
16.8%
6.7 7
 
3.7%
5.8 6
 
3.2%
6.0 5
 
2.6%
2.2 5
 
2.6%
5.6 4
 
2.1%
5.4 4
 
2.1%
7.1 4
 
2.1%
1.6 4
 
2.1%
2.7 4
 
2.1%
Other values (69) 115
60.5%
ValueCountFrequency (%)
0.0 32
16.8%
0.4 1
 
0.5%
0.6 2
 
1.1%
0.9 1
 
0.5%
1.0 2
 
1.1%
1.1 1
 
0.5%
1.2 1
 
0.5%
1.3 2
 
1.1%
1.4 1
 
0.5%
1.5 4
 
2.1%
ValueCountFrequency (%)
26.7 1
0.5%
17.9 1
0.5%
11.7 2
1.1%
10.9 1
0.5%
10.5 1
0.5%
10.4 1
0.5%
10.1 1
0.5%
10.0 2
1.1%
9.7 1
0.5%
9.5 2
1.1%

주말구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
주중
95 
주말
95 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주중 95
50.0%
주말 95
50.0%

Length

2023-12-13T09:34:17.870289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:34:17.946035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주중 95
50.0%
주말 95
50.0%

Interactions

2023-12-13T09:34:14.808664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.013533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.464805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.969777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.414548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.845982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.333599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.891810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.082902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.545655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.036703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.476951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.914804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.402304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.965945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.149385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.631798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.100845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.542551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.981459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.466587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:15.024966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.212569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.701183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.164061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.603115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.047946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.527032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:15.080078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.272878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.774591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.230349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.656473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.111777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.586890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:15.148602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.339112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.844183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.297344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.729463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.188910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.665568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:15.204964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.399446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:12.906305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.356190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:13.788571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.256634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:34:14.735290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:34:17.999291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번국가분류구분사례수(명)집(비율)학교직장(비율)교통수단(비율)실내공간(집학교직장제외)(비율)실외공간(비율)주말구분
연번1.0000.5230.8540.7890.6850.4190.5520.2950.1240.0001.000
국가0.5231.0000.0000.0000.4100.7070.4440.4620.7210.4910.000
분류0.8540.0001.0001.0000.8740.0000.0000.0000.1280.0000.000
구분0.7890.0001.0001.0000.8950.1120.0680.1860.3350.0000.000
사례수(명)0.6850.4100.8740.8951.0000.0000.0000.0000.2060.0000.000
집(비율)0.4190.7070.0000.1120.0001.0000.7860.5910.8540.5200.433
학교직장(비율)0.5520.4440.0000.0680.0000.7861.0000.3230.6040.5170.699
교통수단(비율)0.2950.4620.0000.1860.0000.5910.3231.0000.4320.2010.374
실내공간(집학교직장제외)(비율)0.1240.7210.1280.3350.2060.8540.6040.4321.0000.3650.109
실외공간(비율)0.0000.4910.0000.0000.0000.5200.5170.2010.3651.0000.000
주말구분1.0000.0000.0000.0000.0000.4330.6990.3740.1090.0001.000
2023-12-13T09:34:18.115012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분분류주말구분국가
구분1.0000.9640.0000.000
분류0.9641.0000.0000.000
주말구분0.0000.0001.0000.000
국가0.0000.0000.0001.000
2023-12-13T09:34:18.203361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사례수(명)집(비율)학교직장(비율)교통수단(비율)실내공간(집학교직장제외)(비율)실외공간(비율)국가분류구분주말구분
연번1.000-0.2020.332-0.523-0.370-0.0790.0320.2400.6640.4300.978
사례수(명)-0.2021.000-0.1050.1820.2370.0650.0690.1790.6990.5990.000
집(비율)0.332-0.1051.000-0.660-0.674-0.815-0.5990.3640.0000.0340.325
학교직장(비율)-0.5230.182-0.6601.0000.3300.3700.1750.1970.0000.0090.533
교통수단(비율)-0.3700.237-0.6740.3301.0000.5100.2460.2800.0000.0870.366
실내공간(집학교직장제외)(비율)-0.0790.065-0.8150.3700.5101.0000.4060.3760.0650.1260.080
실외공간(비율)0.0320.069-0.5990.1750.2460.4061.0000.3400.0000.0000.000
국가0.2400.1790.3640.1970.2800.3760.3401.0000.0000.0000.000
분류0.6640.6990.0000.0000.0000.0650.0000.0001.0000.9640.000
구분0.4300.5990.0340.0090.0870.1260.0000.0000.9641.0000.000
주말구분0.9780.0000.3250.5330.3660.0800.0000.0000.0000.0001.000

Missing values

2023-12-13T09:34:15.294055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:34:15.414492image/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)집(비율)학교직장(비율)교통수단(비율)실내공간(집학교직장제외)(비율)실외공간(비율)주말구분
012020영국국가별전체37371.86.78.08.04.8주중
122020호주국가별전체30173.86.67.05.66.0주중
232020러시아국가별전체36776.810.46.04.61.9주중
342020브라질국가별전체36884.06.84.33.31.4주중
452020UAE국가별전체35564.210.77.69.97.6주중
562020영국성별남성21069.57.17.610.54.3주중
672020영국성별여성16374.86.18.64.95.5주중
782020호주성별남성14670.55.59.66.26.8주중
892020호주성별여성15576.87.74.55.25.2주중
9102020러시아성별남성18573.012.46.55.91.6주중
연번조사연도국가분류구분사례수(명)집(비율)학교직장(비율)교통수단(비율)실내공간(집학교직장제외)(비율)실외공간(비율)주말구분
1801812020영국소득별평균 이하16176.46.25.65.06.2주말
1811822020영국소득별평균 이상11476.31.86.110.54.4주말
1821832020호주소득별평균 이하11974.85.95.06.76.7주말
1831842020호주소득별평균 이상8385.51.23.66.02.4주말
1841852020러시아소득별평균 이하19188.51.64.73.71.6주말
1851862020러시아소득별평균 이상12282.84.94.94.92.5주말
1861872020브라질소득별평균 이하17893.80.61.11.72.8주말
1871882020브라질소득별평균 이상8792.03.40.02.32.3주말
1881892020UAE소득별평균 이하16567.36.76.710.98.5주말
1891902020UAE소득별평균 이상12277.93.36.65.76.6주말