Overview

Dataset statistics

Number of variables11
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory101.9 B

Variable types

Numeric10
Categorical1

Dataset

Description음주폐해예방 관련 지표- 국외통계지표 > 청소년 음주행동> 청소년 중 현재 음주자의 위험 음주율, 문제 음주율 지표데이터를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15050193/fileData.do

Alerts

연도 is highly overall correlated with 중1(학년)High correlation
전체 is highly overall correlated with 남(성별) and 7 other fieldsHigh correlation
남(성별) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
여(성별) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
중1(학년) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
중2(학년) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
중3(학년) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
고1(학년) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
고2(학년) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
고3(학년) is highly overall correlated with 전체 and 7 other fieldsHigh correlation
구분 is highly overall correlated with 전체 and 7 other fieldsHigh correlation
전체 has 5 (14.7%) zerosZeros
남(성별) has 5 (14.7%) zerosZeros
여(성별) has 5 (14.7%) zerosZeros
중1(학년) has 5 (14.7%) zerosZeros
중2(학년) has 5 (14.7%) zerosZeros
중3(학년) has 5 (14.7%) zerosZeros
고1(학년) has 5 (14.7%) zerosZeros
고2(학년) has 5 (14.7%) zerosZeros
고3(학년) has 6 (17.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:46:15.998194
Analysis finished2023-12-12 04:46:27.980081
Duration11.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013
Minimum2005
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:28.076211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005.65
Q12009
median2013
Q32017
95-th percentile2020.35
Maximum2021
Range16
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.9726525
Coefficient of variation (CV)0.0024702695
Kurtosis-1.2072833
Mean2013
Median Absolute Deviation (MAD)4
Skewness0
Sum68442
Variance24.727273
MonotonicityIncreasing
2023-12-12T13:46:28.222673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2005 2
 
5.9%
2006 2
 
5.9%
2021 2
 
5.9%
2020 2
 
5.9%
2019 2
 
5.9%
2018 2
 
5.9%
2017 2
 
5.9%
2016 2
 
5.9%
2015 2
 
5.9%
2014 2
 
5.9%
Other values (7) 14
41.2%
ValueCountFrequency (%)
2005 2
5.9%
2006 2
5.9%
2007 2
5.9%
2008 2
5.9%
2009 2
5.9%
2010 2
5.9%
2011 2
5.9%
2012 2
5.9%
2013 2
5.9%
2014 2
5.9%
ValueCountFrequency (%)
2021 2
5.9%
2020 2
5.9%
2019 2
5.9%
2018 2
5.9%
2017 2
5.9%
2016 2
5.9%
2015 2
5.9%
2014 2
5.9%
2013 2
5.9%
2012 2
5.9%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
위험 음주율
17 
문제 음주율
17 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위험 음주율
2nd row문제 음주율
3rd row위험 음주율
4th row문제 음주율
5th row위험 음주율

Common Values

ValueCountFrequency (%)
위험 음주율 17
50.0%
문제 음주율 17
50.0%

Length

2023-12-12T13:46:28.406826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:46:28.501838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음주율 34
50.0%
위험 17
25.0%
문제 17
25.0%

전체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.047059
Minimum0
Maximum52.5
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:28.637508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q138.75
median43.25
Q347.475
95-th percentile51.615
Maximum52.5
Range52.5
Interquartile range (IQR)8.725

Descriptive statistics

Standard deviation16.641209
Coefficient of variation (CV)0.4373849
Kurtosis1.7880961
Mean38.047059
Median Absolute Deviation (MAD)4.35
Skewness-1.7785197
Sum1293.6
Variance276.92984
MonotonicityNot monotonic
2023-12-12T13:46:28.827311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 5
 
14.7%
38.7 2
 
5.9%
44.2 1
 
2.9%
46.8 1
 
2.9%
45.5 1
 
2.9%
49.0 1
 
2.9%
52.2 1
 
2.9%
52.5 1
 
2.9%
37.9 1
 
2.9%
51.3 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0.0 5
14.7%
35.8 1
 
2.9%
37.9 1
 
2.9%
38.7 2
 
5.9%
38.9 1
 
2.9%
39.0 1
 
2.9%
39.8 1
 
2.9%
40.0 1
 
2.9%
40.5 1
 
2.9%
41.3 1
 
2.9%
ValueCountFrequency (%)
52.5 1
2.9%
52.2 1
2.9%
51.3 1
2.9%
50.4 1
2.9%
50.2 1
2.9%
49.0 1
2.9%
48.8 1
2.9%
47.6 1
2.9%
47.5 1
2.9%
47.4 1
2.9%

남(성별)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.173529
Minimum0
Maximum49.1
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:28.976547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q137.7
median40.65
Q345.425
95-th percentile48.64
Maximum49.1
Range49.1
Interquartile range (IQR)7.725

Descriptive statistics

Standard deviation15.723411
Coefficient of variation (CV)0.4346662
Kurtosis1.9057053
Mean36.173529
Median Absolute Deviation (MAD)4.1
Skewness-1.8235099
Sum1229.9
Variance247.22564
MonotonicityNot monotonic
2023-12-12T13:46:29.118738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 5
 
14.7%
39.8 2
 
5.9%
41.0 2
 
5.9%
37.7 2
 
5.9%
37.9 1
 
2.9%
46.1 1
 
2.9%
42.5 1
 
2.9%
46.2 1
 
2.9%
48.4 1
 
2.9%
48.9 1
 
2.9%
Other values (17) 17
50.0%
ValueCountFrequency (%)
0.0 5
14.7%
36.2 1
 
2.9%
36.3 1
 
2.9%
37.2 1
 
2.9%
37.7 2
 
5.9%
37.9 1
 
2.9%
38.8 1
 
2.9%
38.9 1
 
2.9%
39.1 1
 
2.9%
39.8 2
 
5.9%
ValueCountFrequency (%)
49.1 1
2.9%
48.9 1
2.9%
48.5 1
2.9%
48.4 1
2.9%
48.2 1
2.9%
46.3 1
2.9%
46.2 1
2.9%
46.1 1
2.9%
45.6 1
2.9%
44.9 1
2.9%

여(성별)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.476471
Minimum0
Maximum57.4
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:29.258045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q140.35
median47.45
Q351.375
95-th percentile54.895
Maximum57.4
Range57.4
Interquartile range (IQR)11.025

Descriptive statistics

Standard deviation18.015281
Coefficient of variation (CV)0.44508033
Kurtosis1.4774289
Mean40.476471
Median Absolute Deviation (MAD)5.75
Skewness-1.6584766
Sum1376.2
Variance324.55034
MonotonicityNot monotonic
2023-12-12T13:46:29.404583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 5
 
14.7%
41.2 2
 
5.9%
53.6 2
 
5.9%
52.5 2
 
5.9%
49.9 2
 
5.9%
41.8 1
 
2.9%
49.8 1
 
2.9%
52.9 1
 
2.9%
57.4 1
 
2.9%
57.3 1
 
2.9%
Other values (16) 16
47.1%
ValueCountFrequency (%)
0.0 5
14.7%
35.3 1
 
2.9%
35.7 1
 
2.9%
38.4 1
 
2.9%
40.2 1
 
2.9%
40.8 1
 
2.9%
41.2 2
 
5.9%
41.6 1
 
2.9%
41.8 1
 
2.9%
42.5 1
 
2.9%
ValueCountFrequency (%)
57.4 1
2.9%
57.3 1
2.9%
53.6 2
5.9%
52.9 1
2.9%
52.5 2
5.9%
52.3 1
2.9%
51.4 1
2.9%
51.3 1
2.9%
51.2 1
2.9%
51.0 1
2.9%

중1(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.655882
Minimum0
Maximum21.5
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:29.587790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111.875
median15.4
Q318.1
95-th percentile21.235
Maximum21.5
Range21.5
Interquartile range (IQR)6.225

Descriptive statistics

Standard deviation6.7248608
Coefficient of variation (CV)0.49245157
Kurtosis0.1929589
Mean13.655882
Median Absolute Deviation (MAD)3.45
Skewness-1.0644481
Sum464.3
Variance45.223752
MonotonicityNot monotonic
2023-12-12T13:46:29.761698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 5
 
14.7%
18.1 2
 
5.9%
15.4 2
 
5.9%
16.4 1
 
2.9%
19.1 1
 
2.9%
15.6 1
 
2.9%
13.3 1
 
2.9%
18.0 1
 
2.9%
12.7 1
 
2.9%
13.2 1
 
2.9%
Other values (18) 18
52.9%
ValueCountFrequency (%)
0.0 5
14.7%
7.7 1
 
2.9%
8.6 1
 
2.9%
11.5 1
 
2.9%
11.8 1
 
2.9%
12.1 1
 
2.9%
12.7 1
 
2.9%
12.8 1
 
2.9%
13.2 1
 
2.9%
13.3 1
 
2.9%
ValueCountFrequency (%)
21.5 1
2.9%
21.3 1
2.9%
21.2 1
2.9%
21.0 1
2.9%
20.6 1
2.9%
19.4 1
2.9%
19.3 1
2.9%
19.1 1
2.9%
18.1 2
5.9%
18.0 1
2.9%

중2(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.647059
Minimum0
Maximum33.4
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:29.914460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.125
median27.15
Q328.85
95-th percentile30.97
Maximum33.4
Range33.4
Interquartile range (IQR)7.725

Descriptive statistics

Standard deviation10.2085
Coefficient of variation (CV)0.45076494
Kurtosis1.2651861
Mean22.647059
Median Absolute Deviation (MAD)2.8
Skewness-1.5839183
Sum770
Variance104.21348
MonotonicityNot monotonic
2023-12-12T13:46:30.073491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 5
 
14.7%
29.0 2
 
5.9%
30.1 1
 
2.9%
28.6 1
 
2.9%
27.7 1
 
2.9%
27.1 1
 
2.9%
33.4 1
 
2.9%
32.4 1
 
2.9%
22.8 1
 
2.9%
29.3 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0.0 5
14.7%
17.8 1
 
2.9%
19.2 1
 
2.9%
20.2 1
 
2.9%
21.0 1
 
2.9%
21.5 1
 
2.9%
21.9 1
 
2.9%
22.8 1
 
2.9%
24.0 1
 
2.9%
25.4 1
 
2.9%
ValueCountFrequency (%)
33.4 1
2.9%
32.4 1
2.9%
30.2 1
2.9%
30.1 1
2.9%
29.8 1
2.9%
29.3 1
2.9%
29.0 2
5.9%
28.9 1
2.9%
28.7 1
2.9%
28.6 1
2.9%

중3(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.629412
Minimum0
Maximum42.2
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:30.266862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130.9
median35.85
Q337.875
95-th percentile41.635
Maximum42.2
Range42.2
Interquartile range (IQR)6.975

Descriptive statistics

Standard deviation13.390692
Coefficient of variation (CV)0.4371841
Kurtosis1.7865723
Mean30.629412
Median Absolute Deviation (MAD)2.45
Skewness-1.7918756
Sum1041.4
Variance179.31062
MonotonicityNot monotonic
2023-12-12T13:46:30.443992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 5
 
14.7%
38.3 2
 
5.9%
34.1 2
 
5.9%
27.3 2
 
5.9%
30.4 2
 
5.9%
37.5 1
 
2.9%
35.7 1
 
2.9%
38.4 1
 
2.9%
42.2 1
 
2.9%
41.7 1
 
2.9%
Other values (16) 16
47.1%
ValueCountFrequency (%)
0.0 5
14.7%
27.3 2
 
5.9%
30.4 2
 
5.9%
32.4 1
 
2.9%
33.4 1
 
2.9%
33.6 1
 
2.9%
34.1 2
 
5.9%
34.2 1
 
2.9%
35.0 1
 
2.9%
35.7 1
 
2.9%
ValueCountFrequency (%)
42.2 1
2.9%
41.7 1
2.9%
41.6 1
2.9%
40.4 1
2.9%
40.2 1
2.9%
38.4 1
2.9%
38.3 2
5.9%
38.0 1
2.9%
37.5 1
2.9%
37.4 1
2.9%

고1(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.623529
Minimum0
Maximum53.9
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:30.603560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q138
median43.95
Q349.325
95-th percentile51.58
Maximum53.9
Range53.9
Interquartile range (IQR)11.325

Descriptive statistics

Standard deviation17.039278
Coefficient of variation (CV)0.44116316
Kurtosis1.6280098
Mean38.623529
Median Absolute Deviation (MAD)5.7
Skewness-1.7198002
Sum1313.2
Variance290.33701
MonotonicityNot monotonic
2023-12-12T13:46:30.738164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 5
 
14.7%
48.6 2
 
5.9%
50.9 1
 
2.9%
40.5 1
 
2.9%
46.7 1
 
2.9%
49.5 1
 
2.9%
53.9 1
 
2.9%
52.1 1
 
2.9%
36.7 1
 
2.9%
48.8 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0.0 5
14.7%
35.0 1
 
2.9%
36.7 1
 
2.9%
36.9 1
 
2.9%
37.9 1
 
2.9%
38.3 1
 
2.9%
39.2 1
 
2.9%
40.4 1
 
2.9%
40.5 1
 
2.9%
41.0 1
 
2.9%
ValueCountFrequency (%)
53.9 1
2.9%
52.1 1
2.9%
51.3 1
2.9%
51.2 1
2.9%
50.9 1
2.9%
50.7 1
2.9%
50.6 1
2.9%
49.7 1
2.9%
49.5 1
2.9%
48.8 1
2.9%

고2(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.852941
Minimum0
Maximum58.5
Zeros5
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:30.904117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q142.225
median50.6
Q354.975
95-th percentile57.65
Maximum58.5
Range58.5
Interquartile range (IQR)12.75

Descriptive statistics

Standard deviation19.064949
Coefficient of variation (CV)0.44489242
Kurtosis1.4714746
Mean42.852941
Median Absolute Deviation (MAD)6.05
Skewness-1.6685239
Sum1457
Variance363.47226
MonotonicityNot monotonic
2023-12-12T13:46:31.031709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 5
 
14.7%
52.0 2
 
5.9%
54.9 2
 
5.9%
58.3 1
 
2.9%
56.4 1
 
2.9%
58.5 1
 
2.9%
40.1 1
 
2.9%
57.3 1
 
2.9%
37.0 1
 
2.9%
55.6 1
 
2.9%
Other values (18) 18
52.9%
ValueCountFrequency (%)
0.0 5
14.7%
37.0 1
 
2.9%
37.6 1
 
2.9%
40.1 1
 
2.9%
42.1 1
 
2.9%
42.6 1
 
2.9%
42.7 1
 
2.9%
43.2 1
 
2.9%
44.1 1
 
2.9%
45.8 1
 
2.9%
ValueCountFrequency (%)
58.5 1
2.9%
58.3 1
2.9%
57.3 1
2.9%
56.9 1
2.9%
56.4 1
2.9%
55.6 1
2.9%
55.5 1
2.9%
55.3 1
2.9%
55.0 1
2.9%
54.9 2
5.9%

고3(학년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.947059
Minimum0
Maximum62.1
Zeros6
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:46:31.194559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q145.85
median52.9
Q360.15
95-th percentile60.705
Maximum62.1
Range62.1
Interquartile range (IQR)14.3

Descriptive statistics

Standard deviation21.869839
Coefficient of variation (CV)0.48656885
Kurtosis0.723107
Mean44.947059
Median Absolute Deviation (MAD)7.3
Skewness-1.514416
Sum1528.2
Variance478.28984
MonotonicityNot monotonic
2023-12-12T13:46:31.368398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 6
 
17.6%
60.3 3
 
8.8%
60.6 2
 
5.9%
59.7 2
 
5.9%
47.9 1
 
2.9%
52.7 1
 
2.9%
58.2 1
 
2.9%
60.9 1
 
2.9%
45.7 1
 
2.9%
43.8 1
 
2.9%
Other values (15) 15
44.1%
ValueCountFrequency (%)
0.0 6
17.6%
42.7 1
 
2.9%
43.8 1
 
2.9%
45.7 1
 
2.9%
46.3 1
 
2.9%
46.9 1
 
2.9%
47.9 1
 
2.9%
48.8 1
 
2.9%
49.0 1
 
2.9%
49.9 1
 
2.9%
ValueCountFrequency (%)
62.1 1
 
2.9%
60.9 1
 
2.9%
60.6 2
5.9%
60.5 1
 
2.9%
60.4 1
 
2.9%
60.3 3
8.8%
59.7 2
5.9%
59.2 1
 
2.9%
58.4 1
 
2.9%
58.2 1
 
2.9%

Interactions

2023-12-12T13:46:26.562331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.328334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:17.412852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.815281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.903451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.038537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.054744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.318629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.326065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.587524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.681623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.438396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:17.908701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.960826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.019636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.172553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.209708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.457593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.418630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.710300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.802594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.540325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.026297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.100854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.120796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.267939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.312400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.569422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.529589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.797360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.905679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.642044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.122049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.205334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.217751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.370936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.432230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.678878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.642374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.887952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.023431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.740262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.211751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.313871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.339898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.472487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.553918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.795636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.748246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.983667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.144196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.836517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.296009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.401590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.451178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.546938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.654193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.884417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.826705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.065911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.257803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:16.968130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.403117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.513405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.573102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.632298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.774952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.971373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.921534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.158076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.340433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:17.088254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.500639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.616527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.666971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.726094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:22.890825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.058646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.293675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.249095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.451194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:17.205854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.598110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.701529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.765382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.812050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.016364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.145872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.392853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.343843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:27.546432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:17.318760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:18.701547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:19.795118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:20.910773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:21.934542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:23.167594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:24.234533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:25.482283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:46:26.462491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:46:31.496160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분전체남(성별)여(성별)중1(학년)중2(학년)중3(학년)고1(학년)고2(학년)고3(학년)
연도1.0000.0000.5650.6010.6060.4760.7610.7960.6330.5720.000
구분0.0001.0000.7600.9471.0000.7930.6760.6390.7660.8010.750
전체0.5650.7601.0000.8190.9700.6660.7280.9550.9700.9770.928
남(성별)0.6010.9470.8191.0000.7760.8900.7970.7900.7860.7960.747
여(성별)0.6061.0000.9700.7761.0000.7860.7440.9700.9650.9560.944
중1(학년)0.4760.7930.6660.8900.7861.0000.7760.7070.7210.7680.601
중2(학년)0.7610.6760.7280.7970.7440.7761.0000.8190.7190.7650.670
중3(학년)0.7960.6390.9550.7900.9700.7070.8191.0000.9380.9560.916
고1(학년)0.6330.7660.9700.7860.9650.7210.7190.9381.0000.9810.936
고2(학년)0.5720.8010.9770.7960.9560.7680.7650.9560.9811.0000.963
고3(학년)0.0000.7500.9280.7470.9440.6010.6700.9160.9360.9631.000
2023-12-12T13:46:31.976519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체남(성별)여(성별)중1(학년)중2(학년)중3(학년)고1(학년)고2(학년)고3(학년)구분
연도1.0000.0030.085-0.093-0.500-0.2590.000-0.148-0.187-0.1280.000
전체0.0031.0000.9770.9610.2430.6140.9110.9400.9220.8790.851
남(성별)0.0850.9771.0000.9000.2160.5640.8740.8740.8470.8720.766
여(성별)-0.0930.9610.9001.0000.2660.6290.9250.9720.9590.8670.952
중1(학년)-0.5000.2430.2160.2661.0000.6840.3740.3130.2530.2660.578
중2(학년)-0.2590.6140.5640.6290.6841.0000.6950.6730.6250.5370.460
중3(학년)0.0000.9110.8740.9250.3740.6951.0000.9130.8930.7610.730
고1(학년)-0.1480.9400.8740.9720.3130.6730.9131.0000.9530.8160.856
고2(학년)-0.1870.9220.8470.9590.2530.6250.8930.9531.0000.8200.886
고3(학년)-0.1280.8790.8720.8670.2660.5370.7610.8160.8201.0000.841
구분0.0000.8510.7660.9520.5780.4600.7300.8560.8860.8411.000

Missing values

2023-12-12T13:46:27.699765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:46:27.905133image/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

연도구분전체남(성별)여(성별)중1(학년)중2(학년)중3(학년)고1(학년)고2(학년)고3(학년)
02005위험 음주율44.237.951.216.430.137.550.958.30.0
12005문제 음주율0.00.00.00.00.00.00.00.00.0
22006위험 음주율47.342.353.616.727.438.350.656.960.3
32006문제 음주율39.036.342.518.125.432.439.246.550.0
42007위험 음주율46.042.251.015.227.036.948.655.562.1
52007문제 음주율42.239.845.221.328.036.243.349.253.5
62008위험 음주율44.641.049.216.824.034.147.352.958.4
72008문제 음주율42.339.845.721.028.935.044.347.353.1
82009위험 음주율47.444.651.415.430.236.850.754.960.6
92009문제 음주율40.038.941.617.626.233.442.745.848.8
연도구분전체남(성별)여(성별)중1(학년)중2(학년)중3(학년)고1(학년)고2(학년)고3(학년)
242017위험 음주율51.348.552.513.229.340.448.857.360.6
252017문제 음주율37.937.241.212.722.830.436.740.145.7
262018위험 음주율52.548.957.315.432.441.652.158.560.3
272018문제 음주율0.00.00.00.00.00.00.00.00.0
282019위험 음주율52.248.457.418.033.441.753.956.460.9
292019문제 음주율0.00.00.00.00.00.00.00.00.0
302020위험 음주율49.046.252.913.327.142.249.554.958.2
312020문제 음주율0.00.00.00.00.00.00.00.00.0
322021위험 음주율45.542.549.815.627.738.446.752.052.7
332021문제 음주율0.00.00.00.00.00.00.00.00.0