Overview

Dataset statistics

Number of variables4
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory38.8 B

Variable types

Text1
Numeric3

Dataset

Description음주폐해예방 관련 지표- 국외통계지표 > 소비수준 > 음주자의 하루 평균 알코올 섭취량 지표데이터를 제공합니다.- 국외통계지표 > 소비수준 > 음주자의 하루 평균 알코올 섭취량 지표데이터를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15050185/fileData.do

Alerts

양성 is highly overall correlated with 여성 and 1 other fieldsHigh correlation
여성 is highly overall correlated with 양성 and 1 other fieldsHigh correlation
남성 is highly overall correlated with 양성 and 1 other fieldsHigh correlation
국가 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:30:58.677306
Analysis finished2023-12-12 19:31:00.057535
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T04:31:00.233040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.3714286
Min length2

Characters and Unicode

Total characters118
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row대한민국
2nd row호주
3rd row오스트리아
4th row벨기에
5th row캐나다
ValueCountFrequency (%)
대한민국 1
 
2.9%
일본 1
 
2.9%
룩셈부르그 1
 
2.9%
멕시코 1
 
2.9%
네덜란드 1
 
2.9%
뉴질랜드 1
 
2.9%
노르웨이 1
 
2.9%
폴란드 1
 
2.9%
라트비아 1
 
2.9%
포르투갈 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T04:31:00.703348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 9
 
7.6%
아 8
 
6.8%
드 6
 
5.1%
이 4
 
3.4%
란 4
 
3.4%
리 4
 
3.4%
르 3
 
2.5%
일 3
 
2.5%
슬 3
 
2.5%
국 3
 
2.5%
Other values (60) 71
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 9
 
7.6%
아 8
 
6.8%
드 6
 
5.1%
이 4
 
3.4%
란 4
 
3.4%
리 4
 
3.4%
르 3
 
2.5%
일 3
 
2.5%
슬 3
 
2.5%
국 3
 
2.5%
Other values (60) 71
60.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 9
 
7.6%
아 8
 
6.8%
드 6
 
5.1%
이 4
 
3.4%
란 4
 
3.4%
리 4
 
3.4%
르 3
 
2.5%
일 3
 
2.5%
슬 3
 
2.5%
국 3
 
2.5%
Other values (60) 71
60.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 9
 
7.6%
아 8
 
6.8%
드 6
 
5.1%
이 4
 
3.4%
란 4
 
3.4%
리 4
 
3.4%
르 3
 
2.5%
일 3
 
2.5%
슬 3
 
2.5%
국 3
 
2.5%
Other values (60) 71
60.2%

양성
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.765714
Minimum15.1
Maximum61.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T04:31:00.892624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.1
5-th percentile24.25
Q129.75
median32.2
Q335.95
95-th percentile39.27
Maximum61.7
Range46.6
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation7.2071428
Coefficient of variation (CV)0.21995989
Kurtosis7.6038483
Mean32.765714
Median Absolute Deviation (MAD)2.6
Skewness1.4175962
Sum1146.8
Variance51.942908
MonotonicityNot monotonic
2023-12-13T04:31:01.038077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
34.6 2
 
5.7%
30.6 2
 
5.7%
37.0 2
 
5.7%
29.6 2
 
5.7%
38.4 1
 
2.9%
33.1 1
 
2.9%
26.0 1
 
2.9%
30.9 1
 
2.9%
20.4 1
 
2.9%
35.8 1
 
2.9%
Other values (21) 21
60.0%
ValueCountFrequency (%)
15.1 1
2.9%
20.4 1
2.9%
25.9 1
2.9%
26.0 1
2.9%
27.1 1
2.9%
27.6 1
2.9%
28.9 1
2.9%
29.6 2
5.7%
29.9 1
2.9%
30.1 1
2.9%
ValueCountFrequency (%)
61.7 1
2.9%
41.3 1
2.9%
38.4 1
2.9%
38.3 1
2.9%
37.2 1
2.9%
37.0 2
5.7%
36.5 1
2.9%
36.1 1
2.9%
35.8 1
2.9%
34.6 2
5.7%

여성
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.837143
Minimum7.2
Maximum25.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T04:31:01.197435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile11.61
Q114.4
median15.5
Q317.6
95-th percentile19.19
Maximum25.8
Range18.6
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation3.0861251
Coefficient of variation (CV)0.19486628
Kurtosis3.5072741
Mean15.837143
Median Absolute Deviation (MAD)1.5
Skewness0.21540204
Sum554.3
Variance9.5241681
MonotonicityNot monotonic
2023-12-13T04:31:01.369690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
17.9 3
 
8.6%
14.4 3
 
8.6%
15.5 2
 
5.7%
16.5 2
 
5.7%
15.4 2
 
5.7%
16.4 1
 
2.9%
18.7 1
 
2.9%
25.8 1
 
2.9%
15.2 1
 
2.9%
13.2 1
 
2.9%
Other values (18) 18
51.4%
ValueCountFrequency (%)
7.2 1
 
2.9%
10.0 1
 
2.9%
12.3 1
 
2.9%
12.6 1
 
2.9%
13.2 1
 
2.9%
13.4 1
 
2.9%
14.2 1
 
2.9%
14.3 1
 
2.9%
14.4 3
8.6%
14.8 1
 
2.9%
ValueCountFrequency (%)
25.8 1
 
2.9%
20.1 1
 
2.9%
18.8 1
 
2.9%
18.7 1
 
2.9%
18.3 1
 
2.9%
18.0 1
 
2.9%
17.9 3
8.6%
17.3 1
 
2.9%
17.2 1
 
2.9%
17.0 1
 
2.9%

남성
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.342857
Minimum20.1
Maximum71.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T04:31:01.555913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20.1
5-th percentile33.5
Q140.9
median44.5
Q350.55
95-th percentile55.47
Maximum71.9
Range51.8
Interquartile range (IQR)9.65

Descriptive statistics

Standard deviation8.8531578
Coefficient of variation (CV)0.19524923
Kurtosis2.7636379
Mean45.342857
Median Absolute Deviation (MAD)4.6
Skewness0.0049171464
Sum1587
Variance78.378403
MonotonicityNot monotonic
2023-12-13T04:31:01.743648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
43.6 2
 
5.7%
54.3 2
 
5.7%
41.0 2
 
5.7%
47.0 1
 
2.9%
35.6 1
 
2.9%
47.1 1
 
2.9%
71.9 1
 
2.9%
37.6 1
 
2.9%
43.8 1
 
2.9%
53.2 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
20.1 1
2.9%
28.6 1
2.9%
35.6 1
2.9%
36.0 1
2.9%
37.6 1
2.9%
38.0 1
2.9%
40.6 1
2.9%
40.7 1
2.9%
40.8 1
2.9%
41.0 2
5.7%
ValueCountFrequency (%)
71.9 1
2.9%
58.2 1
2.9%
54.3 2
5.7%
53.2 1
2.9%
51.9 1
2.9%
51.8 1
2.9%
51.5 1
2.9%
51.1 1
2.9%
50.0 1
2.9%
49.4 1
2.9%

Interactions

2023-12-13T04:30:59.532923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:58.829044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.132877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.661515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:58.914595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.242432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.786210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.031398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:30:59.370326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:31:01.875120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가양성여성남성
국가1.0001.0001.0001.000
양성1.0001.0000.9340.972
여성1.0000.9341.0000.943
남성1.0000.9720.9431.000
2023-12-13T04:31:01.988235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
양성여성남성
양성1.0000.9820.985
여성0.9821.0000.993
남성0.9850.9931.000

Missing values

2023-12-13T04:30:59.923863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:31:00.017086image/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

국가양성여성남성
0대한민국34.616.447.0
1호주28.914.440.7
2오스트리아32.215.945.7
3벨기에34.316.848.4
4캐나다29.914.340.8
5칠레29.614.440.6
6체코41.320.158.2
7덴마크30.114.842.1
8에스토니아34.417.049.4
9핀란드31.915.544.5
국가양성여성남성
25폴란드37.017.951.5
26포르투갈38.418.854.3
27슬로바키아35.817.350.0
28슬로베니아38.318.353.2
29스페인31.515.143.8
30스웨덴27.113.237.6
31스위스30.615.243.6
32터키61.725.871.9
33영국33.716.547.1
34미국29.614.441.0