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 > 성인의 음주행동유형> 19세 이상 성인의 연간 음주율 지표데이터를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15050196/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
20-29(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 4 (11.8%) zerosZeros

Reproduction

Analysis started2023-12-12 18:18:37.239979
Analysis finished2023-12-12 18:18:49.298915
Duration12.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.3529
Minimum1998
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:49.373659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1998
5-th percentile1999.95
Q12008
median2012
Q32016
95-th percentile2019.35
Maximum2020
Range22
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.1194293
Coefficient of variation (CV)0.0030424443
Kurtosis-0.28076817
Mean2011.3529
Median Absolute Deviation (MAD)4
Skewness-0.60218438
Sum68386
Variance37.447415
MonotonicityIncreasing
2023-12-13T03:18:49.486711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1998 2
 
5.9%
2001 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%
Other values (7) 14
41.2%
ValueCountFrequency (%)
1998 2
5.9%
2001 2
5.9%
2005 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%
ValueCountFrequency (%)
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%
2011 2
5.9%

구분
Categorical

HIGH CORRELATION 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
17
50.0%
17
50.0%

Length

2023-12-13T03:18:49.618547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:18:49.736820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17
50.0%
17
50.0%

전체
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.564706
Minimum59.3
Maximum88.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:49.838987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59.3
5-th percentile63.24
Q170.675
median78.85
Q386.1
95-th percentile87.45
Maximum88.1
Range28.8
Interquartile range (IQR)15.425

Descriptive statistics

Standard deviation9.0788426
Coefficient of variation (CV)0.11704863
Kurtosis-1.2765745
Mean77.564706
Median Absolute Deviation (MAD)7.7
Skewness-0.35260204
Sum2637.2
Variance82.425383
MonotonicityNot monotonic
2023-12-13T03:18:49.972873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
86.1 3
 
8.8%
70.9 2
 
5.9%
88.1 2
 
5.9%
83.4 1
 
2.9%
71.6 1
 
2.9%
86.3 1
 
2.9%
70.6 1
 
2.9%
86.6 1
 
2.9%
87.1 1
 
2.9%
75.0 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
59.3 1
2.9%
59.6 1
2.9%
65.2 1
2.9%
67.7 1
2.9%
68.5 1
2.9%
68.8 1
2.9%
69.2 1
2.9%
70.5 1
2.9%
70.6 1
2.9%
70.9 2
5.9%
ValueCountFrequency (%)
88.1 2
5.9%
87.1 1
 
2.9%
86.7 1
 
2.9%
86.6 1
 
2.9%
86.5 1
 
2.9%
86.3 1
 
2.9%
86.1 3
8.8%
85.9 1
 
2.9%
85.8 1
 
2.9%
85.7 1
 
2.9%

동(거주지)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.723529
Minimum58
Maximum88.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:50.116644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile64.495
Q170.225
median79.7
Q386.3
95-th percentile88.175
Maximum88.7
Range30.7
Interquartile range (IQR)16.075

Descriptive statistics

Standard deviation9.345427
Coefficient of variation (CV)0.12023935
Kurtosis-1.3685304
Mean77.723529
Median Absolute Deviation (MAD)7.8
Skewness-0.33039021
Sum2642.6
Variance87.337005
MonotonicityNot monotonic
2023-12-13T03:18:50.236092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
67.3 2
 
5.9%
86.3 2
 
5.9%
86.7 2
 
5.9%
85.0 1
 
2.9%
86.2 1
 
2.9%
84.0 1
 
2.9%
85.7 1
 
2.9%
74.3 1
 
2.9%
75.4 1
 
2.9%
72.7 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
58.0 1
2.9%
61.7 1
2.9%
66.0 1
2.9%
67.3 2
5.9%
67.6 1
2.9%
68.9 1
2.9%
69.1 1
2.9%
70.2 1
2.9%
70.3 1
2.9%
70.8 1
2.9%
ValueCountFrequency (%)
88.7 1
2.9%
88.5 1
2.9%
88.0 1
2.9%
87.2 1
2.9%
86.7 2
5.9%
86.6 1
2.9%
86.4 1
2.9%
86.3 2
5.9%
86.2 1
2.9%
86.1 1
2.9%

읍면(거주지)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.214706
Minimum43.5
Maximum87.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:50.346774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.5
5-th percentile52.465
Q166.95
median73.7
Q383.35
95-th percentile85.97
Maximum87.5
Range44
Interquartile range (IQR)16.4

Descriptive statistics

Standard deviation11.35726
Coefficient of variation (CV)0.15512266
Kurtosis0.024690589
Mean73.214706
Median Absolute Deviation (MAD)9.15
Skewness-0.74298429
Sum2489.3
Variance128.98735
MonotonicityNot monotonic
2023-12-13T03:18:50.463947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
85.2 2
 
5.9%
70.6 2
 
5.9%
76.2 1
 
2.9%
82.9 1
 
2.9%
67.2 1
 
2.9%
84.4 1
 
2.9%
66.0 1
 
2.9%
82.3 1
 
2.9%
63.9 1
 
2.9%
82.8 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
43.5 1
2.9%
49.8 1
2.9%
53.9 1
2.9%
60.3 1
2.9%
61.1 1
2.9%
63.9 1
2.9%
64.0 1
2.9%
66.0 1
2.9%
66.9 1
2.9%
67.1 1
2.9%
ValueCountFrequency (%)
87.5 1
2.9%
86.1 1
2.9%
85.9 1
2.9%
85.2 2
5.9%
84.5 1
2.9%
84.4 1
2.9%
84.0 1
2.9%
83.5 1
2.9%
82.9 1
2.9%
82.8 1
2.9%

20-29(19-29)(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.432353
Minimum77.2
Maximum96.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:50.586154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum77.2
5-th percentile80.825
Q185.55
median88.75
Q391.975
95-th percentile94.715
Maximum96.7
Range19.5
Interquartile range (IQR)6.425

Descriptive statistics

Standard deviation4.4654716
Coefficient of variation (CV)0.050495904
Kurtosis-0.052615323
Mean88.432353
Median Absolute Deviation (MAD)3.25
Skewness-0.39914457
Sum3006.7
Variance19.940437
MonotonicityNot monotonic
2023-12-13T03:18:50.706461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
83.5 2
 
5.9%
93.1 2
 
5.9%
85.4 2
 
5.9%
88.1 1
 
2.9%
92.1 1
 
2.9%
86.2 1
 
2.9%
94.4 1
 
2.9%
92.6 1
 
2.9%
85.5 1
 
2.9%
89.8 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
77.2 1
2.9%
80.5 1
2.9%
81.0 1
2.9%
83.5 2
5.9%
84.0 1
2.9%
85.4 2
5.9%
85.5 1
2.9%
85.7 1
2.9%
86.2 1
2.9%
86.5 1
2.9%
ValueCountFrequency (%)
96.7 1
2.9%
95.3 1
2.9%
94.4 1
2.9%
93.4 1
2.9%
93.1 2
5.9%
92.6 1
2.9%
92.1 1
2.9%
92.0 1
2.9%
91.9 1
2.9%
90.9 1
2.9%

30-39(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.235294
Minimum68.3
Maximum94.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:50.843445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68.3
5-th percentile72.955
Q177.775
median85.7
Q391.75
95-th percentile93.505
Maximum94.3
Range26
Interquartile range (IQR)13.975

Descriptive statistics

Standard deviation8.0452464
Coefficient of variation (CV)0.09550921
Kurtosis-1.4898657
Mean84.235294
Median Absolute Deviation (MAD)6.5
Skewness-0.267258
Sum2864
Variance64.725989
MonotonicityNot monotonic
2023-12-13T03:18:50.961098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
92.1 3
 
8.8%
90.0 2
 
5.9%
76.4 2
 
5.9%
79.5 2
 
5.9%
89.9 1
 
2.9%
79.6 1
 
2.9%
91.6 1
 
2.9%
78.8 1
 
2.9%
81.7 1
 
2.9%
90.6 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
68.3 1
2.9%
72.5 1
2.9%
73.2 1
2.9%
73.7 1
2.9%
74.1 1
2.9%
74.7 1
2.9%
76.4 2
5.9%
77.5 1
2.9%
78.6 1
2.9%
78.8 1
2.9%
ValueCountFrequency (%)
94.3 1
 
2.9%
93.7 1
 
2.9%
93.4 1
 
2.9%
93.3 1
 
2.9%
92.8 1
 
2.9%
92.1 3
8.8%
91.8 1
 
2.9%
91.6 1
 
2.9%
91.3 1
 
2.9%
90.6 1
 
2.9%

40-49(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.770588
Minimum53.3
Maximum90.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:51.077458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53.3
5-th percentile66.82
Q175.15
median83
Q388.375
95-th percentile89.635
Maximum90.2
Range36.9
Interquartile range (IQR)13.225

Descriptive statistics

Standard deviation8.901499
Coefficient of variation (CV)0.11020718
Kurtosis1.1380642
Mean80.770588
Median Absolute Deviation (MAD)6.4
Skewness-1.0492
Sum2746.2
Variance79.236684
MonotonicityNot monotonic
2023-12-13T03:18:51.209170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
88.0 2
 
5.9%
89.4 2
 
5.9%
81.0 1
 
2.9%
90.2 1
 
2.9%
75.4 1
 
2.9%
87.3 1
 
2.9%
78.6 1
 
2.9%
87.8 1
 
2.9%
76.9 1
 
2.9%
89.3 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
53.3 1
2.9%
63.7 1
2.9%
68.5 1
2.9%
70.3 1
2.9%
72.4 1
2.9%
74.1 1
2.9%
74.6 1
2.9%
74.8 1
2.9%
75.1 1
2.9%
75.3 1
2.9%
ValueCountFrequency (%)
90.2 1
2.9%
89.7 1
2.9%
89.6 1
2.9%
89.5 1
2.9%
89.4 2
5.9%
89.3 1
2.9%
88.6 1
2.9%
88.5 1
2.9%
88.0 2
5.9%
87.8 1
2.9%

50-59(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.855882
Minimum36.8
Maximum86.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:51.336677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.8
5-th percentile53.205
Q162.45
median72.55
Q383.525
95-th percentile85.305
Maximum86.9
Range50.1
Interquartile range (IQR)21.075

Descriptive statistics

Standard deviation12.816022
Coefficient of variation (CV)0.17835731
Kurtosis0.15839038
Mean71.855882
Median Absolute Deviation (MAD)10.65
Skewness-0.75717549
Sum2443.1
Variance164.25042
MonotonicityNot monotonic
2023-12-13T03:18:51.458298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
83.3 2
 
5.9%
77.7 1
 
2.9%
67.7 1
 
2.9%
62.9 1
 
2.9%
80.4 1
 
2.9%
62.0 1
 
2.9%
82.3 1
 
2.9%
66.4 1
 
2.9%
85.5 1
 
2.9%
84.0 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
36.8 1
2.9%
44.3 1
2.9%
58.0 1
2.9%
59.0 1
2.9%
59.8 1
2.9%
61.6 1
2.9%
62.0 1
2.9%
62.1 1
2.9%
62.3 1
2.9%
62.9 1
2.9%
ValueCountFrequency (%)
86.9 1
2.9%
85.5 1
2.9%
85.2 1
2.9%
85.0 1
2.9%
84.6 1
2.9%
84.5 1
2.9%
84.4 1
2.9%
84.0 1
2.9%
83.6 1
2.9%
83.3 2
5.9%

60-69(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.814706
Minimum26.6
Maximum82.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:51.592726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.6
5-th percentile37.605
Q147.625
median60.9
Q375.775
95-th percentile81.215
Maximum82.3
Range55.7
Interquartile range (IQR)28.15

Descriptive statistics

Standard deviation16.317459
Coefficient of variation (CV)0.26831436
Kurtosis-1.1875009
Mean60.814706
Median Absolute Deviation (MAD)14.55
Skewness-0.28474163
Sum2067.7
Variance266.25947
MonotonicityNot monotonic
2023-12-13T03:18:51.730724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
74.8 3
 
8.8%
69.4 1
 
2.9%
49.3 1
 
2.9%
45.6 1
 
2.9%
76.0 1
 
2.9%
46.6 1
 
2.9%
53.9 1
 
2.9%
77.6 1
 
2.9%
80.9 1
 
2.9%
47.5 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
26.6 1
2.9%
30.0 1
2.9%
41.7 1
2.9%
42.5 1
2.9%
43.9 1
2.9%
45.0 1
2.9%
45.6 1
2.9%
46.6 1
2.9%
47.5 1
2.9%
48.0 1
2.9%
ValueCountFrequency (%)
82.3 1
2.9%
81.8 1
2.9%
80.9 1
2.9%
80.4 1
2.9%
77.6 1
2.9%
77.4 1
2.9%
76.3 1
2.9%
76.0 1
2.9%
75.8 1
2.9%
75.7 1
2.9%

70세 이상(연령별)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.511765
Minimum0
Maximum67.2
Zeros4
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-13T03:18:51.851205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129.025
median32.9
Q361.575
95-th percentile65.57
Maximum67.2
Range67.2
Interquartile range (IQR)32.55

Descriptive statistics

Standard deviation21.582369
Coefficient of variation (CV)0.53274324
Kurtosis-0.85030849
Mean40.511765
Median Absolute Deviation (MAD)25.3
Skewness-0.420997
Sum1377.4
Variance465.79865
MonotonicityNot monotonic
2023-12-13T03:18:51.987027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 4
 
11.8%
59.7 2
 
5.9%
61.6 2
 
5.9%
29.1 2
 
5.9%
27.0 1
 
2.9%
30.0 1
 
2.9%
62.1 1
 
2.9%
32.2 1
 
2.9%
64.8 1
 
2.9%
29.7 1
 
2.9%
Other values (18) 18
52.9%
ValueCountFrequency (%)
0.0 4
11.8%
25.1 1
 
2.9%
26.7 1
 
2.9%
27.0 1
 
2.9%
28.5 1
 
2.9%
29.0 1
 
2.9%
29.1 2
5.9%
29.3 1
 
2.9%
29.7 1
 
2.9%
30.0 1
 
2.9%
ValueCountFrequency (%)
67.2 1
2.9%
67.0 1
2.9%
64.8 1
2.9%
64.5 1
2.9%
63.9 1
2.9%
62.3 1
2.9%
62.1 1
2.9%
61.6 2
5.9%
61.5 1
2.9%
59.9 1
2.9%

Interactions

2023-12-13T03:18:47.873452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:37.628472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.101423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.246939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.235049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.086025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.172878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.034168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.186424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.833815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.969007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:37.729038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.214007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.350529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.313390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.199339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.254094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.143014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.303549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.932308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.061382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:37.836410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.330517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.456463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.404336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.302491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.340077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.253768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.441833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.044522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.176777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:37.957634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.450016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.579942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.488620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.402397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.419487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.362157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.560765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.151635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.302814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.052427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.543095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.677859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.559344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.502520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.492113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.458331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.671253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.250610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.456613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.176868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.693776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.793775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.655252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.636453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.591241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.590280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.180414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.388076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.555910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.292161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.817132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.871816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.739342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.742446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.678817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.722427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.309332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.493404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.662119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.410800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:39.936044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.969235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.831979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.850373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.771671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.840469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.502734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.601663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.767142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.512521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.036205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.058197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.908666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:42.954244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.847103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:44.937382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.599120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.692468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:48.877884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:38.628522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:40.136135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.146693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:41.985331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.067237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:43.941013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:45.047174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:46.722928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:18:47.778579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:18:52.110532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분전체동(거주지)읍면(거주지)20-29(19-29)(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
연도1.0000.0000.3860.3830.4180.0000.0000.0000.4170.4730.680
구분0.0001.0001.0001.0001.0000.8401.0001.0001.0001.0000.994
전체0.3861.0001.0000.8840.8230.6850.7650.8140.9180.9880.758
동(거주지)0.3831.0000.8841.0000.9100.7180.9630.9840.8790.8170.792
읍면(거주지)0.4181.0000.8230.9101.0000.7450.8290.8440.8830.8120.698
20-29(19-29)(연령별)0.0000.8400.6850.7180.7451.0000.7390.6840.6730.6070.552
30-39(연령별)0.0001.0000.7650.9630.8290.7391.0000.9430.8220.7130.658
40-49(연령별)0.0001.0000.8140.9840.8440.6840.9431.0000.8660.8000.731
50-59(연령별)0.4171.0000.9180.8790.8830.6730.8220.8661.0000.9210.721
60-69(연령별)0.4731.0000.9880.8170.8120.6070.7130.8000.9211.0000.786
70세 이상(연령별)0.6800.9940.7580.7920.6980.5520.6580.7310.7210.7861.000
2023-12-13T03:18:52.571902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체동(거주지)읍면(거주지)20-29(19-29)(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)구분
연도1.0000.2940.1640.0070.0110.1960.1990.2230.3700.4460.000
전체0.2941.0000.9380.8770.8850.9290.8880.9260.9330.8220.919
동(거주지)0.1640.9381.0000.9080.8290.8910.8780.9240.8900.8180.901
읍면(거주지)0.0070.8770.9081.0000.8460.8490.8780.8410.8290.7620.866
20-29(19-29)(연령별)0.0110.8850.8290.8461.0000.8320.7690.7890.7720.6420.768
30-39(연령별)0.1960.9290.8910.8490.8321.0000.8360.8970.8680.7080.901
40-49(연령별)0.1990.8880.8780.8780.7690.8361.0000.8610.8840.7740.901
50-59(연령별)0.2230.9260.9240.8410.7890.8970.8611.0000.8960.7750.919
60-69(연령별)0.3700.9330.8900.8290.7720.8680.8840.8961.0000.7950.919
70세 이상(연령별)0.4460.8220.8180.7620.6420.7080.7740.7750.7951.0000.868
구분0.0000.9190.9010.8660.7680.9010.9010.9190.9190.8681.000

Missing values

2023-12-13T03:18:49.017577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:18:49.211930image/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)20-29(19-29)(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
0199883.485.076.289.889.985.377.769.40.0
1199859.358.043.577.268.353.336.826.60.0
2200182.784.674.593.190.285.077.467.40.0
3200159.661.749.886.773.763.744.330.00.0
4200586.586.685.293.493.388.585.273.556.7
5200570.971.270.787.478.675.362.345.033.6
6200785.186.381.190.091.889.484.467.659.7
7200765.266.061.180.573.268.559.041.725.1
8200885.785.883.590.992.889.581.376.355.6
9200867.767.666.984.074.772.459.842.529.0
연도구분전체동(거주지)읍면(거주지)20-29(19-29)(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
24201687.188.082.392.693.487.885.577.663.9
25201671.672.763.985.577.576.967.749.330.3
26201786.186.782.988.192.189.484.080.961.6
27201775.075.470.690.781.581.066.754.429.7
28201886.186.782.889.490.689.383.380.464.8
29201873.674.368.285.481.779.566.854.332.2
30201986.785.781.692.092.188.681.881.862.1
31201972.067.360.387.378.876.464.352.530.0
32202085.084.077.589.591.687.283.374.859.7
33202071.467.353.985.779.675.166.149.029.1