Overview

Dataset statistics

Number of variables11
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory102.1 B

Variable types

Numeric10
Categorical1

Dataset

Description음주폐해예방 관련 지표- 국외통계지표 > 성인의 음주행동유형> 19세 이상 성인의 고위험 음주율 지표데이터를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15050197/fileData.do

Alerts

전체 is highly overall correlated with 동(거주지) and 8 other fieldsHigh correlation
동(거주지) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
읍면(거주지) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
19-29(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
30-39(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
40-49(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
50-59(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
60-69(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
70세 이상(연령별) is highly overall correlated with 전체 and 8 other fieldsHigh correlation
구분 is highly overall correlated with 전체 and 8 other fieldsHigh correlation
70세 이상(연령별) has 1 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-12 06:55:38.944278
Analysis finished2023-12-12 06:55:49.708196
Duration10.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.4375
Minimum2005
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:49.773063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2006.1
Q12009.75
median2013.5
Q32017.25
95-th percentile2020.45
Maximum2021
Range16
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation4.7920465
Coefficient of variation (CV)0.0023800324
Kurtosis-1.0932186
Mean2013.4375
Median Absolute Deviation (MAD)4
Skewness-0.078488262
Sum64430
Variance22.96371
MonotonicityIncreasing
2023-12-12T15:55:49.905029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2005 2
 
6.2%
2015 2
 
6.2%
2021 2
 
6.2%
2020 2
 
6.2%
2019 2
 
6.2%
2018 2
 
6.2%
2017 2
 
6.2%
2016 2
 
6.2%
2014 2
 
6.2%
2007 2
 
6.2%
Other values (6) 12
37.5%
ValueCountFrequency (%)
2005 2
6.2%
2007 2
6.2%
2008 2
6.2%
2009 2
6.2%
2010 2
6.2%
2011 2
6.2%
2012 2
6.2%
2013 2
6.2%
2014 2
6.2%
2015 2
6.2%
ValueCountFrequency (%)
2021 2
6.2%
2020 2
6.2%
2019 2
6.2%
2018 2
6.2%
2017 2
6.2%
2016 2
6.2%
2015 2
6.2%
2014 2
6.2%
2013 2
6.2%
2012 2
6.2%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
남
16 
여
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row남
4th row여
5th row남

Common Values

ValueCountFrequency (%)
남 16
50.0%
여 16
50.0%

Length

2023-12-12T15:55:50.075943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:55:50.193711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 16
50.0%
여 16
50.0%

전체
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.521875
Minimum3.4
Maximum24.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:50.302444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4
5-th percentile4.27
Q16.15
median13.5
Q321.05
95-th percentile22.54
Maximum24.5
Range21.1
Interquartile range (IQR)14.9

Descriptive statistics

Standard deviation7.8478571
Coefficient of variation (CV)0.58038231
Kurtosis-1.9968528
Mean13.521875
Median Absolute Deviation (MAD)7.5
Skewness0.010393745
Sum432.7
Variance61.588861
MonotonicityNot monotonic
2023-12-12T15:55:50.450944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6.3 2
 
6.2%
20.8 2
 
6.2%
19.7 2
 
6.2%
19.9 1
 
3.1%
20.7 1
 
3.1%
6.9 1
 
3.1%
21.6 1
 
3.1%
6.5 1
 
3.1%
18.6 1
 
3.1%
8.4 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
3.4 1
3.1%
3.5 1
3.1%
4.9 1
3.1%
5.4 1
3.1%
5.5 1
3.1%
5.6 1
3.1%
5.8 1
3.1%
6.0 1
3.1%
6.2 1
3.1%
6.3 2
6.2%
ValueCountFrequency (%)
24.5 1
3.1%
23.2 1
3.1%
22.0 1
3.1%
21.8 1
3.1%
21.6 1
3.1%
21.4 1
3.1%
21.3 1
3.1%
21.2 1
3.1%
21.0 1
3.1%
20.8 2
6.2%

동(거주지)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.29375
Minimum3.4
Maximum24.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:50.956332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4
5-th percentile4.56
Q15.6
median13.1
Q320.8
95-th percentile21.89
Maximum24.3
Range20.9
Interquartile range (IQR)15.2

Descriptive statistics

Standard deviation7.7890716
Coefficient of variation (CV)0.58591982
Kurtosis-2.0137679
Mean13.29375
Median Absolute Deviation (MAD)7.5
Skewness0.018475194
Sum425.4
Variance60.669637
MonotonicityNot monotonic
2023-12-12T15:55:51.112046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
5.6 3
 
9.4%
6.2 2
 
6.2%
21.6 2
 
6.2%
5.4 2
 
6.2%
19.8 2
 
6.2%
20.6 1
 
3.1%
21.1 1
 
3.1%
18.1 1
 
3.1%
8.1 1
 
3.1%
20.5 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
3.4 1
 
3.1%
3.9 1
 
3.1%
5.1 1
 
3.1%
5.3 1
 
3.1%
5.4 2
6.2%
5.6 3
9.4%
5.8 1
 
3.1%
6.2 2
6.2%
6.4 1
 
3.1%
6.6 1
 
3.1%
ValueCountFrequency (%)
24.3 1
3.1%
22.0 1
3.1%
21.8 1
3.1%
21.6 2
6.2%
21.4 1
3.1%
21.3 1
3.1%
21.1 1
3.1%
20.7 1
3.1%
20.6 1
3.1%
20.5 1
3.1%

읍면(거주지)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.7625
Minimum2
Maximum29.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:51.251970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.31
Q15.2
median14.2
Q321.7
95-th percentile25.98
Maximum29.3
Range27.3
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation8.7775281
Coefficient of variation (CV)0.63778588
Kurtosis-1.5948318
Mean13.7625
Median Absolute Deviation (MAD)7.9
Skewness0.10945276
Sum440.4
Variance77.045
MonotonicityNot monotonic
2023-12-12T15:55:51.385744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
21.7 3
 
9.4%
20.9 2
 
6.2%
3.9 2
 
6.2%
20.4 1
 
3.1%
3.8 1
 
3.1%
17.7 1
 
3.1%
3.2 1
 
3.1%
22.7 1
 
3.1%
5.5 1
 
3.1%
11.7 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
2.0 1
3.1%
3.2 1
3.1%
3.4 1
3.1%
3.8 1
3.1%
3.9 2
6.2%
4.5 1
3.1%
4.6 1
3.1%
5.4 1
3.1%
5.5 1
3.1%
5.9 1
3.1%
ValueCountFrequency (%)
29.3 1
 
3.1%
28.4 1
 
3.1%
24.0 1
 
3.1%
22.7 1
 
3.1%
22.2 1
 
3.1%
22.0 1
 
3.1%
21.8 1
 
3.1%
21.7 3
9.4%
20.9 2
6.2%
20.4 1
 
3.1%

19-29(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.015625
Minimum5.4
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:51.510628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.4
5-th percentile7.08
Q18.975
median13.05
Q316.85
95-th percentile19.925
Maximum21
Range15.6
Interquartile range (IQR)7.875

Descriptive statistics

Standard deviation4.5670707
Coefficient of variation (CV)0.35089139
Kurtosis-1.2962056
Mean13.015625
Median Absolute Deviation (MAD)4
Skewness0.14835826
Sum416.5
Variance20.858135
MonotonicityNot monotonic
2023-12-12T15:55:51.644283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
14.6 2
 
6.2%
6.2 1
 
3.1%
9.5 1
 
3.1%
16.0 1
 
3.1%
8.3 1
 
3.1%
14.3 1
 
3.1%
9.0 1
 
3.1%
13.1 1
 
3.1%
14.9 1
 
3.1%
16.7 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
5.4 1
3.1%
6.2 1
3.1%
7.8 1
3.1%
8.1 1
3.1%
8.2 1
3.1%
8.3 1
3.1%
8.8 1
3.1%
8.9 1
3.1%
9.0 1
3.1%
9.2 1
3.1%
ValueCountFrequency (%)
21.0 1
3.1%
20.2 1
3.1%
19.7 1
3.1%
19.3 1
3.1%
18.7 1
3.1%
17.8 1
3.1%
17.7 1
3.1%
17.0 1
3.1%
16.8 1
3.1%
16.7 1
3.1%

30-39(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.8375
Minimum3.1
Maximum30.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:51.810499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile5.21
Q18.25
median14.65
Q323.8
95-th percentile26.99
Maximum30.5
Range27.4
Interquartile range (IQR)15.55

Descriptive statistics

Standard deviation8.7638462
Coefficient of variation (CV)0.55336045
Kurtosis-1.7227927
Mean15.8375
Median Absolute Deviation (MAD)8.05
Skewness0.11055665
Sum506.8
Variance76.805
MonotonicityNot monotonic
2023-12-12T15:55:51.938331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
9.1 2
 
6.2%
19.3 1
 
3.1%
3.1 1
 
3.1%
10.3 1
 
3.1%
20.3 1
 
3.1%
23.3 1
 
3.1%
8.1 1
 
3.1%
19.0 1
 
3.1%
9.5 1
 
3.1%
20.6 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
3.1 1
3.1%
4.0 1
3.1%
6.2 1
3.1%
6.3 1
3.1%
6.9 1
3.1%
7.0 1
3.1%
7.6 1
3.1%
8.1 1
3.1%
8.3 1
3.1%
8.4 1
3.1%
ValueCountFrequency (%)
30.5 1
3.1%
27.1 1
3.1%
26.9 1
3.1%
26.7 1
3.1%
26.2 1
3.1%
25.4 1
3.1%
25.1 1
3.1%
24.1 1
3.1%
23.7 1
3.1%
23.6 1
3.1%

40-49(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.678125
Minimum3.4
Maximum31.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:52.074862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4
5-th percentile4.2
Q16.4
median15.6
Q327.375
95-th percentile30.145
Maximum31.1
Range27.7
Interquartile range (IQR)20.975

Descriptive statistics

Standard deviation10.947845
Coefficient of variation (CV)0.65641942
Kurtosis-2.015943
Mean16.678125
Median Absolute Deviation (MAD)10.65
Skewness0.027097195
Sum533.7
Variance119.85531
MonotonicityNot monotonic
2023-12-12T15:55:52.200314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
28.1 2
 
6.2%
4.2 2
 
6.2%
7.1 2
 
6.2%
8.0 2
 
6.2%
6.4 2
 
6.2%
4.7 1
 
3.1%
24.3 1
 
3.1%
7.3 1
 
3.1%
30.1 1
 
3.1%
7.2 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
3.4 1
3.1%
4.2 2
6.2%
4.4 1
3.1%
4.7 1
3.1%
5.7 1
3.1%
6.0 1
3.1%
6.4 2
6.2%
6.6 1
3.1%
7.1 2
6.2%
7.2 1
3.1%
ValueCountFrequency (%)
31.1 1
3.1%
30.2 1
3.1%
30.1 1
3.1%
28.1 2
6.2%
27.8 1
3.1%
27.7 1
3.1%
27.6 1
3.1%
27.3 1
3.1%
27.2 1
3.1%
26.7 1
3.1%

50-59(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.86875
Minimum2.1
Maximum30.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:52.316215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.1
5-th percentile2.5
Q13.775
median12.05
Q324.125
95-th percentile25.89
Maximum30.1
Range28
Interquartile range (IQR)20.35

Descriptive statistics

Standard deviation10.490501
Coefficient of variation (CV)0.75641285
Kurtosis-1.9805076
Mean13.86875
Median Absolute Deviation (MAD)9.55
Skewness0.070562293
Sum443.8
Variance110.0506
MonotonicityNot monotonic
2023-12-12T15:55:52.440264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.5 3
 
9.4%
23.6 1
 
3.1%
23.1 1
 
3.1%
3.3 1
 
3.1%
24.2 1
 
3.1%
3.5 1
 
3.1%
24.3 1
 
3.1%
4.0 1
 
3.1%
24.0 1
 
3.1%
5.1 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
2.1 1
 
3.1%
2.5 3
9.4%
2.6 1
 
3.1%
3.3 1
 
3.1%
3.5 1
 
3.1%
3.7 1
 
3.1%
3.8 1
 
3.1%
4.0 1
 
3.1%
4.2 1
 
3.1%
4.5 1
 
3.1%
ValueCountFrequency (%)
30.1 1
3.1%
26.0 1
3.1%
25.8 1
3.1%
25.2 1
3.1%
24.8 1
3.1%
24.5 1
3.1%
24.3 1
3.1%
24.2 1
3.1%
24.1 1
3.1%
24.0 1
3.1%

60-69(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.58125
Minimum0.3
Maximum21.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:52.664650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.455
Q10.975
median6.2
Q315.475
95-th percentile19.28
Maximum21.2
Range20.9
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation7.6958069
Coefficient of variation (CV)0.89681653
Kurtosis-1.7670441
Mean8.58125
Median Absolute Deviation (MAD)5.85
Skewness0.20466871
Sum274.6
Variance59.225444
MonotonicityNot monotonic
2023-12-12T15:55:52.794284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.5 2
 
6.2%
2.0 2
 
6.2%
0.8 2
 
6.2%
1.0 2
 
6.2%
17.8 1
 
3.1%
16.7 1
 
3.1%
18.2 1
 
3.1%
21.2 1
 
3.1%
3.5 1
 
3.1%
17.7 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0.3 1
3.1%
0.4 1
3.1%
0.5 2
6.2%
0.7 1
3.1%
0.8 2
6.2%
0.9 1
3.1%
1.0 2
6.2%
1.4 1
3.1%
2.0 2
6.2%
2.3 1
3.1%
ValueCountFrequency (%)
21.2 1
3.1%
20.6 1
3.1%
18.2 1
3.1%
17.8 1
3.1%
17.7 1
3.1%
17.5 1
3.1%
16.7 1
3.1%
16.3 1
3.1%
15.2 1
3.1%
14.9 1
3.1%

70세 이상(연령별)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.865625
Minimum0
Maximum12.8
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:55:52.919581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.4
median2.4
Q37.125
95-th percentile9.51
Maximum12.8
Range12.8
Interquartile range (IQR)6.725

Descriptive statistics

Standard deviation3.8143709
Coefficient of variation (CV)0.98674106
Kurtosis-0.95079997
Mean3.865625
Median Absolute Deviation (MAD)2.2
Skewness0.56399216
Sum123.7
Variance14.549425
MonotonicityNot monotonic
2023-12-12T15:55:53.066881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.2 3
 
9.4%
0.3 3
 
9.4%
0.8 2
 
6.2%
7.2 2
 
6.2%
0.4 2
 
6.2%
0.5 2
 
6.2%
12.8 1
 
3.1%
6.6 1
 
3.1%
8.3 1
 
3.1%
7.9 1
 
3.1%
Other values (14) 14
43.8%
ValueCountFrequency (%)
0.0 1
 
3.1%
0.2 3
9.4%
0.3 3
9.4%
0.4 2
6.2%
0.5 2
6.2%
0.6 1
 
3.1%
0.8 2
6.2%
0.9 1
 
3.1%
1.0 1
 
3.1%
3.8 1
 
3.1%
ValueCountFrequency (%)
12.8 1
3.1%
10.5 1
3.1%
8.7 1
3.1%
8.6 1
3.1%
8.3 1
3.1%
7.9 1
3.1%
7.2 2
6.2%
7.1 1
3.1%
6.8 1
3.1%
6.6 1
3.1%

Interactions

2023-12-12T15:55:48.359294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.311484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.234064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.152464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.184302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.237359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.470551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.334041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.394478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.432230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.443432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.390066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.328758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.268956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.316562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.337714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.559249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.440739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.510513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.531623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.529994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.464098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.400121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.348439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.423679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.437510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.645479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.533137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.611273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.617969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.606499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.542614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.506825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.448165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.511664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.533949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.724587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.640484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.712988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.712451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.738972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.628732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.602008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.566307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.607336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.636736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.801287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.757060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.836253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.811354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.845918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.739570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.708564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.666586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.696416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.746499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.905349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.876635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.961591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.931829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.951307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.842716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.817813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.763098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.789314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.129709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.999821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.992844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.055542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.021681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:49.076744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:39.926567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.898341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.874527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.913604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.214675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.081650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.096722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.155588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.124410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:49.189742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.025170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.979992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.989150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.008922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.307152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.165876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.201914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.239908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.214478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:49.275362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:40.123922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:41.063919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:42.083463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:43.123726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:44.382427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:45.247561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:46.297234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:47.330830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:55:48.283038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:55:53.161452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분전체동(거주지)읍면(거주지)19-29(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
연도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
구분0.0001.0001.0001.0001.0000.9981.0001.0001.0001.0001.000
전체0.0001.0001.0000.9830.8900.8790.8030.7820.7380.7810.687
동(거주지)0.0001.0000.9831.0000.9120.8300.6790.7150.7940.7730.607
읍면(거주지)0.0001.0000.8900.9121.0000.5590.6930.7310.8140.7180.533
19-29(연령별)0.0000.9980.8790.8300.5591.0000.8180.8030.5940.6060.614
30-39(연령별)0.0001.0000.8030.6790.6930.8181.0000.7100.6390.9070.861
40-49(연령별)0.0001.0000.7820.7150.7310.8030.7101.0000.7060.6830.799
50-59(연령별)0.0001.0000.7380.7940.8140.5940.6390.7061.0000.7850.786
60-69(연령별)0.0001.0000.7810.7730.7180.6060.9070.6830.7851.0000.880
70세 이상(연령별)0.0001.0000.6870.6070.5330.6140.8610.7990.7860.8801.000
2023-12-12T15:55:53.323591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체동(거주지)읍면(거주지)19-29(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)구분
연도1.0000.0960.008-0.0130.0530.0660.0370.1510.232-0.0310.000
전체0.0961.0000.9620.9040.9190.9460.9340.8940.7600.7370.931
동(거주지)0.0080.9621.0000.8800.9360.9230.8920.8840.7360.7070.931
읍면(거주지)-0.0130.9040.8801.0000.8480.8470.8340.9190.7790.7350.876
19-29(연령별)0.0530.9190.9360.8481.0000.8760.8190.8600.6910.6440.818
30-39(연령별)0.0660.9460.9230.8470.8761.0000.9010.8330.6730.6690.894
40-49(연령별)0.0370.9340.8920.8340.8190.9011.0000.7920.7700.7390.949
50-59(연령별)0.1510.8940.8840.9190.8600.8330.7921.0000.8360.7590.913
60-69(연령별)0.2320.7600.7360.7790.6910.6730.7700.8361.0000.8160.894
70세 이상(연령별)-0.0310.7370.7070.7350.6440.6690.7390.7590.8161.0000.894
구분0.0000.9310.9310.8760.8180.8940.9490.9130.8940.8941.000

Missing values

2023-12-12T15:55:49.416747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:55:49.618546image/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

연도구분전체동(거주지)읍면(거주지)19-29(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
02005남19.919.320.913.019.328.123.617.812.8
12005여3.43.43.46.23.13.42.51.00.9
22007남21.321.422.016.826.930.218.614.93.8
32007여3.53.92.05.44.04.22.10.50.6
42008남24.524.324.021.026.731.130.116.38.7
52008여6.26.45.410.47.07.13.70.40.8
62009남21.421.321.720.223.627.322.314.67.1
72009여5.45.63.98.16.36.03.82.00.2
82010남22.021.622.217.827.126.725.213.78.6
92010여5.65.46.87.88.36.62.50.30.4
연도구분전체동(거주지)읍면(거주지)19-29(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
222017남21.021.616.717.024.127.223.515.27.2
232017여7.27.08.811.19.06.45.53.40.5
242018남20.820.520.916.720.627.724.120.67.2
252018여8.48.111.714.99.58.05.12.30.2
262019남18.618.121.713.119.023.224.017.710.5
272019여6.55.65.59.08.17.24.03.50.8
282020남21.621.122.714.323.330.124.321.27.9
292020여6.35.43.28.39.17.33.51.00.3
302021남19.719.817.716.020.324.324.218.28.3
312021여6.95.63.89.510.38.03.30.50.4