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 memory102.0 B

Variable types

Numeric10
Categorical1

Dataset

Description음주폐해예방 관련 지표- 국외통계지표 > 성인의 음주행동유형> 19세 이상 성인의 월간 음주율 지표데이터를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15050195/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
읍면(거주지) has unique valuesUnique
19-29(연령별) has unique valuesUnique

Reproduction

Analysis started2024-04-20 21:15:39.985936
Analysis finished2024-04-20 21:16:00.804444
Duration20.82 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 size416.0 B
2024-04-21T06:16:00.920874image/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
2024-04-21T06:16:01.131644image/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 size384.0 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

2024-04-21T06:16:01.356089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T06:16:01.527445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 16
50.0%
여 16
50.0%

전체
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.7375
Minimum37
Maximum77.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:01.699035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile42.27
Q146.225
median59.75
Q374.1
95-th percentile76.655
Maximum77.8
Range40.8
Interquartile range (IQR)27.875

Descriptive statistics

Standard deviation14.704898
Coefficient of variation (CV)0.24615858
Kurtosis-1.9259873
Mean59.7375
Median Absolute Deviation (MAD)14.15
Skewness-0.048438277
Sum1911.6
Variance216.23403
MonotonicityNot monotonic
2024-04-21T06:16:01.927990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
75.3 2
 
6.2%
72.6 1
 
3.1%
46.4 1
 
3.1%
46.6 1
 
3.1%
68.3 1
 
3.1%
47.8 1
 
3.1%
70.2 1
 
3.1%
48.4 1
 
3.1%
73.4 1
 
3.1%
51.2 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
37.0 1
3.1%
41.5 1
3.1%
42.9 1
3.1%
43.3 1
3.1%
43.4 1
3.1%
44.2 1
3.1%
45.0 1
3.1%
45.7 1
3.1%
46.4 1
3.1%
46.5 1
3.1%
ValueCountFrequency (%)
77.8 1
3.1%
77.7 1
3.1%
75.8 1
3.1%
75.3 2
6.2%
75.2 1
3.1%
74.7 1
3.1%
74.4 1
3.1%
74.0 1
3.1%
73.6 1
3.1%
73.5 1
3.1%

동(거주지)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.553125
Minimum37
Maximum78.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:02.159504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile41.74
Q144.075
median60.05
Q374.5
95-th percentile77.285
Maximum78.1
Range41.1
Interquartile range (IQR)30.425

Descriptive statistics

Standard deviation15.144614
Coefficient of variation (CV)0.25430428
Kurtosis-1.9418639
Mean59.553125
Median Absolute Deviation (MAD)14.95
Skewness-0.038671982
Sum1905.7
Variance229.35934
MonotonicityNot monotonic
2024-04-21T06:16:02.368156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
74.5 2
 
6.2%
68.7 2
 
6.2%
75.3 2
 
6.2%
44.0 2
 
6.2%
72.5 1
 
3.1%
46.5 1
 
3.1%
42.1 1
 
3.1%
43.5 1
 
3.1%
43.9 1
 
3.1%
73.5 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
37.0 1
3.1%
41.3 1
3.1%
42.1 1
3.1%
43.3 1
3.1%
43.5 1
3.1%
43.9 1
3.1%
44.0 2
6.2%
44.1 1
3.1%
45.3 1
3.1%
45.8 1
3.1%
ValueCountFrequency (%)
78.1 1
3.1%
78.0 1
3.1%
76.7 1
3.1%
75.9 1
3.1%
75.3 2
6.2%
75.2 1
3.1%
74.5 2
6.2%
74.1 1
3.1%
73.8 1
3.1%
73.5 1
3.1%

읍면(거주지)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.059375
Minimum27.7
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:02.578377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.7
5-th percentile33.495
Q141.625
median55.35
Q371.475
95-th percentile75.92
Maximum77
Range49.3
Interquartile range (IQR)29.85

Descriptive statistics

Standard deviation16.061994
Coefficient of variation (CV)0.28651754
Kurtosis-1.6126595
Mean56.059375
Median Absolute Deviation (MAD)15.3
Skewness-0.10751079
Sum1793.9
Variance257.98765
MonotonicityNot monotonic
2024-04-21T06:16:02.796809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
71.7 1
 
3.1%
44.4 1
 
3.1%
27.7 1
 
3.1%
59.5 1
 
3.1%
31.9 1
 
3.1%
68.5 1
 
3.1%
39.7 1
 
3.1%
67.0 1
 
3.1%
51.2 1
 
3.1%
64.6 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
27.7 1
3.1%
31.9 1
3.1%
34.8 1
3.1%
37.1 1
3.1%
39.7 1
3.1%
40.0 1
3.1%
40.1 1
3.1%
40.8 1
3.1%
41.9 1
3.1%
43.2 1
3.1%
ValueCountFrequency (%)
77.0 1
3.1%
76.8 1
3.1%
75.2 1
3.1%
74.9 1
3.1%
74.5 1
3.1%
73.6 1
3.1%
73.5 1
3.1%
71.7 1
3.1%
71.4 1
3.1%
71.1 1
3.1%

19-29(연령별)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.928125
Minimum51.8
Maximum84.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:03.278844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.8
5-th percentile53.915
Q160.525
median66
Q375.9
95-th percentile82.095
Maximum84.8
Range33
Interquartile range (IQR)15.375

Descriptive statistics

Standard deviation9.3083117
Coefficient of variation (CV)0.13703178
Kurtosis-1.0461115
Mean67.928125
Median Absolute Deviation (MAD)8.25
Skewness0.11239652
Sum2173.7
Variance86.644667
MonotonicityNot monotonic
2024-04-21T06:16:03.677381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
78.4 1
 
3.1%
60.3 1
 
3.1%
60.6 1
 
3.1%
66.8 1
 
3.1%
60.0 1
 
3.1%
68.5 1
 
3.1%
64.5 1
 
3.1%
71.6 1
 
3.1%
65.7 1
 
3.1%
63.5 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
51.8 1
3.1%
52.1 1
3.1%
55.4 1
3.1%
56.6 1
3.1%
57.7 1
3.1%
60.0 1
3.1%
60.2 1
3.1%
60.3 1
3.1%
60.6 1
3.1%
62.3 1
3.1%
ValueCountFrequency (%)
84.8 1
3.1%
82.7 1
3.1%
81.6 1
3.1%
81.2 1
3.1%
78.4 1
3.1%
77.1 1
3.1%
76.9 1
3.1%
76.8 1
3.1%
75.6 1
3.1%
74.9 1
3.1%

30-39(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.9
Minimum41.2
Maximum84.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:04.056859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41.2
5-th percentile45.975
Q153.575
median66.7
Q379
95-th percentile82.215
Maximum84.9
Range43.7
Interquartile range (IQR)25.425

Descriptive statistics

Standard deviation14.172736
Coefficient of variation (CV)0.21506428
Kurtosis-1.662569
Mean65.9
Median Absolute Deviation (MAD)12.55
Skewness-0.18033036
Sum2108.8
Variance200.86645
MonotonicityNot monotonic
2024-04-21T06:16:04.443808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
79.9 2
 
6.2%
79.0 2
 
6.2%
77.8 1
 
3.1%
50.6 1
 
3.1%
56.9 1
 
3.1%
73.4 1
 
3.1%
59.9 1
 
3.1%
77.6 1
 
3.1%
55.0 1
 
3.1%
80.8 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
41.2 1
3.1%
43.5 1
3.1%
48.0 1
3.1%
49.1 1
3.1%
50.1 1
3.1%
50.3 1
3.1%
50.6 1
3.1%
52.6 1
3.1%
53.9 1
3.1%
55.0 1
3.1%
ValueCountFrequency (%)
84.9 1
3.1%
82.6 1
3.1%
81.9 1
3.1%
80.8 1
3.1%
80.0 1
3.1%
79.9 2
6.2%
79.0 2
6.2%
78.6 1
3.1%
78.5 1
3.1%
78.1 1
3.1%

40-49(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.65
Minimum38.6
Maximum80.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:04.823202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.6
5-th percentile41.975
Q149.6
median63.55
Q377.625
95-th percentile79.58
Maximum80.5
Range41.9
Interquartile range (IQR)28.025

Descriptive statistics

Standard deviation15.121657
Coefficient of variation (CV)0.24136723
Kurtosis-1.8141445
Mean62.65
Median Absolute Deviation (MAD)14
Skewness-0.12607414
Sum2004.8
Variance228.66452
MonotonicityNot monotonic
2024-04-21T06:16:05.215810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
49.6 2
 
6.2%
76.1 1
 
3.1%
38.6 1
 
3.1%
72.0 1
 
3.1%
74.2 1
 
3.1%
50.5 1
 
3.1%
74.9 1
 
3.1%
55.1 1
 
3.1%
77.7 1
 
3.1%
54.7 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
38.6 1
3.1%
40.6 1
3.1%
43.1 1
3.1%
43.3 1
3.1%
44.6 1
3.1%
47.5 1
3.1%
48.6 1
3.1%
49.6 2
6.2%
50.4 1
3.1%
50.5 1
3.1%
ValueCountFrequency (%)
80.5 1
3.1%
79.8 1
3.1%
79.4 1
3.1%
79.3 1
3.1%
79.1 1
3.1%
78.7 1
3.1%
77.8 1
3.1%
77.7 1
3.1%
77.6 1
3.1%
76.5 1
3.1%

50-59(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.640625
Minimum28.6
Maximum81.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:05.591149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.6
5-th percentile34.175
Q138.25
median55.25
Q374.025
95-th percentile76.835
Maximum81.2
Range52.6
Interquartile range (IQR)35.775

Descriptive statistics

Standard deviation18.782264
Coefficient of variation (CV)0.33756387
Kurtosis-1.9774272
Mean55.640625
Median Absolute Deviation (MAD)18.7
Skewness-0.014477796
Sum1780.5
Variance352.77346
MonotonicityNot monotonic
2024-04-21T06:16:05.991194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
71.5 2
 
6.2%
74.1 2
 
6.2%
72.1 1
 
3.1%
38.8 1
 
3.1%
68.4 1
 
3.1%
39.6 1
 
3.1%
69.7 1
 
3.1%
40.6 1
 
3.1%
71.9 1
 
3.1%
41.4 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
28.6 1
3.1%
33.9 1
3.1%
34.4 1
3.1%
34.9 1
3.1%
35.7 1
3.1%
36.0 1
3.1%
36.4 1
3.1%
36.6 1
3.1%
38.8 1
3.1%
39.0 1
3.1%
ValueCountFrequency (%)
81.2 1
3.1%
78.1 1
3.1%
75.8 1
3.1%
75.6 1
3.1%
75.1 1
3.1%
74.9 1
3.1%
74.1 2
6.2%
74.0 1
3.1%
73.4 1
3.1%
72.1 1
3.1%

60-69(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.75
Minimum20.3
Maximum72.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:06.367504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20.3
5-th percentile20.51
Q124.45
median59.5
Q366.7
95-th percentile71.185
Maximum72.5
Range52.2
Interquartile range (IQR)42.25

Descriptive statistics

Standard deviation21.823515
Coefficient of variation (CV)0.46681315
Kurtosis-2.0144294
Mean46.75
Median Absolute Deviation (MAD)12.7
Skewness-0.11585329
Sum1496
Variance476.26581
MonotonicityNot monotonic
2024-04-21T06:16:06.766902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
65.0 2
 
6.2%
23.2 2
 
6.2%
21.1 1
 
3.1%
20.8 1
 
3.1%
67.0 1
 
3.1%
25.9 1
 
3.1%
63.7 1
 
3.1%
26.3 1
 
3.1%
72.5 1
 
3.1%
30.2 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
20.3 1
3.1%
20.4 1
3.1%
20.6 1
3.1%
20.8 1
3.1%
21.1 1
3.1%
23.2 2
6.2%
23.4 1
3.1%
24.8 1
3.1%
25.9 1
3.1%
26.0 1
3.1%
ValueCountFrequency (%)
72.5 1
3.1%
71.9 1
3.1%
70.6 1
3.1%
69.9 1
3.1%
69.8 1
3.1%
68.2 1
3.1%
67.4 1
3.1%
67.0 1
3.1%
66.6 1
3.1%
66.4 1
3.1%

70세 이상(연령별)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.065625
Minimum9.7
Maximum58.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size416.0 B
2024-04-21T06:16:07.153517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.7
5-th percentile10.31
Q114.475
median32.8
Q351.175
95-th percentile57.69
Maximum58.8
Range49.1
Interquartile range (IQR)36.7

Descriptive statistics

Standard deviation19.450858
Coefficient of variation (CV)0.58825012
Kurtosis-1.9873283
Mean33.065625
Median Absolute Deviation (MAD)18.35
Skewness0.043249085
Sum1058.1
Variance378.33588
MonotonicityNot monotonic
2024-04-21T06:16:07.484780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
13.8 2
 
6.2%
45.3 1
 
3.1%
20.3 1
 
3.1%
9.7 1
 
3.1%
46.4 1
 
3.1%
10.2 1
 
3.1%
48.5 1
 
3.1%
15.9 1
 
3.1%
54.7 1
 
3.1%
12.5 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
9.7 1
3.1%
10.2 1
3.1%
10.4 1
3.1%
12.5 1
3.1%
13.5 1
3.1%
13.8 2
6.2%
14.4 1
3.1%
14.5 1
3.1%
15.0 1
3.1%
15.3 1
3.1%
ValueCountFrequency (%)
58.8 1
3.1%
57.8 1
3.1%
57.6 1
3.1%
55.8 1
3.1%
54.7 1
3.1%
53.6 1
3.1%
53.2 1
3.1%
51.4 1
3.1%
51.1 1
3.1%
50.5 1
3.1%

Interactions

2024-04-21T06:15:58.572835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:40.514426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:43.040719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:45.756453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:47.672881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:49.756758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.485769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:53.264200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:55.483394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.998607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:58.792254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:40.780669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:43.309593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.012187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:47.925549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.016330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.633908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:53.515550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:55.742562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.199615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:58.964641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:41.043600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:43.776615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.221757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:48.185659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.278173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.791331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:53.670866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:55.903107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.366344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.107996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:41.284678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:44.022593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.408005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:48.423606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.463621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.918340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:53.846000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.040587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.502455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.327711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:41.525342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:44.270212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.641684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:48.571673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.604959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:52.049212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:54.077384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.175824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.636588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.497515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:41.786720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:44.525280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.789114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:48.720681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.749374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:52.197368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:54.476061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.325095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.783405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.650866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:42.040190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:44.768285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:46.926955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:48.856823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:50.886090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:52.428899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:54.602876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.455018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:57.940547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.813247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:42.284345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:45.009611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:47.055562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:49.039664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.020624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:52.606406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:54.761691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.588648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:58.088565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:59.978059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:42.534674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:45.259692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:47.195053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:49.283172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.166042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:52.776087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:54.997569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.723396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:58.275340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:16:00.181573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:42.791509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:45.509010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:47.430367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:49.518053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:51.339074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:53.016887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:55.235387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:56.862036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T06:15:58.423126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T06:16:07.668402image/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)
연도1.0000.0000.0000.3350.6970.3390.0000.0000.5400.0000.373
구분0.0001.0001.0001.0001.0000.9741.0001.0001.0000.8081.000
전체0.0001.0001.0000.9760.8890.7680.7710.9560.8460.7390.557
동(거주지)0.3351.0000.9761.0000.8270.6920.6910.9430.8710.6830.612
읍면(거주지)0.6971.0000.8890.8271.0000.7480.7370.7970.7680.6980.557
19-29(연령별)0.3390.9740.7680.6920.7481.0000.5890.5990.7370.7530.734
30-39(연령별)0.0001.0000.7710.6910.7370.5891.0000.7640.7850.6740.641
40-49(연령별)0.0001.0000.9560.9430.7970.5990.7641.0000.7690.6810.557
50-59(연령별)0.5401.0000.8460.8710.7680.7370.7850.7691.0000.7620.850
60-69(연령별)0.0000.8080.7390.6830.6980.7530.6740.6810.7621.0000.586
70세 이상(연령별)0.3731.0000.5570.6120.5570.7340.6410.5570.8500.5861.000
2024-04-21T06:16:08.006636image/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
연도1.0000.100-0.032-0.160-0.0610.1470.0180.0350.0970.0140.000
전체0.1001.0000.9510.8680.9320.9480.9170.9500.6940.7660.913
동(거주지)-0.0320.9511.0000.9000.9020.9120.9020.9130.6660.8190.913
읍면(거주지)-0.1600.8680.9001.0000.8750.8070.8350.8580.6430.7910.876
19-29(연령별)-0.0610.9320.9020.8751.0000.8690.8250.8750.5810.7170.735
30-39(연령별)0.1470.9480.9120.8070.8691.0000.8660.9180.6700.7820.894
40-49(연령별)0.0180.9170.9020.8350.8250.8661.0000.8960.6590.7520.913
50-59(연령별)0.0350.9500.9130.8580.8750.9180.8961.0000.6640.7490.931
60-69(연령별)0.0970.6940.6660.6430.5810.6700.6590.6641.0000.6920.888
70세 이상(연령별)0.0140.7660.8190.7910.7170.7820.7520.7490.6921.0000.931
구분0.0000.9130.9130.8760.7350.8940.9130.9310.8880.9311.000

Missing values

2024-04-21T06:16:00.412709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T06:16:00.688882image/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)
02005남72.672.571.778.477.876.171.560.745.3
12005여37.037.037.151.841.238.628.671.914.5
22007남73.574.571.174.679.979.475.858.347.8
32007여41.541.341.963.143.540.636.020.610.4
42008남74.775.268.475.679.980.574.165.650.3
52008여45.045.340.163.850.347.534.420.415.0
62009남75.875.377.082.778.179.175.166.450.5
72009여43.444.040.855.450.148.633.923.213.8
82010남77.878.176.881.684.979.878.166.651.1
92010여43.343.343.252.149.150.636.423.415.5
연도구분전체동(거주지)읍면(거주지)19-29(연령별)30-39(연령별)40-49(연령별)50-59(연령별)60-69(연령별)70세 이상(연령별)
222017남74.074.173.574.278.677.673.469.953.2
232017여50.550.748.366.358.654.739.027.116.6
242018남70.571.264.663.575.277.771.569.853.6
252018여51.251.451.265.760.055.141.430.212.5
262019남73.473.567.071.680.874.971.972.554.7
272019여48.443.939.764.555.050.540.626.315.9
282020남70.268.768.568.577.674.269.763.748.5
292020여47.843.531.960.059.949.639.625.910.2
302021남68.368.759.566.873.472.068.467.046.4
312021여46.642.127.760.656.949.638.820.89.7