Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory83.3 B

Variable types

Categorical2
Numeric7

Dataset

Description- 연령에 따른 1년 동안 여가 생활을 위한 한 달 평균 지출 금액 통계를 제공합니다. - 표본수(명)를 제외한 금액대별 값들은 표본수에서 차지하는 비율(%)을 의미합니다. - 데이터 제공처: KOSIS 국가통계포털
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/795

Alerts

3만원 미만 is highly overall correlated with 3~5만원 and 3 other fieldsHigh correlation
3~5만원 is highly overall correlated with 3만원 미만 and 3 other fieldsHigh correlation
5~7만원 is highly overall correlated with 3만원 미만 and 3 other fieldsHigh correlation
9-15만원 is highly overall correlated with 3만원 미만 and 2 other fieldsHigh correlation
15만원이상 is highly overall correlated with 3만원 미만 and 2 other fieldsHigh correlation
표본수 is highly overall correlated with 5~7만원 and 2 other fieldsHigh correlation
연령별 is highly overall correlated with 표본수High correlation
표본수 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:29:14.796041
Analysis finished2023-12-11 19:29:20.000294
Duration5.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일(년)
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2018
2019
2020
2021
2022

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%
2022 8
20.0%

Length

2023-12-12T04:29:20.351600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:20.498148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%
2022 8
20.0%

연령별
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
15~19세
20대
30대
40대
50대
Other values (3)
15 

Length

Max length6
Median length3
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15~19세
2nd row20대
3rd row30대
4th row40대
5th row50대

Common Values

ValueCountFrequency (%)
15~19세 5
12.5%
20대 5
12.5%
30대 5
12.5%
40대 5
12.5%
50대 5
12.5%
60대 5
12.5%
70세이상 5
12.5%
전체 5
12.5%

Length

2023-12-12T04:29:20.657258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:20.909028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15~19세 5
12.5%
20대 5
12.5%
30대 5
12.5%
40대 5
12.5%
50대 5
12.5%
60대 5
12.5%
70세이상 5
12.5%
전체 5
12.5%

3만원 미만
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.16
Minimum2
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:21.114012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.48
Q15.05
median8.05
Q314.575
95-th percentile28.425
Maximum37.5
Range35.5
Interquartile range (IQR)9.525

Descriptive statistics

Standard deviation8.7180567
Coefficient of variation (CV)0.78118788
Kurtosis1.1184431
Mean11.16
Median Absolute Deviation (MAD)3.35
Skewness1.3471067
Sum446.4
Variance76.004513
MonotonicityNot monotonic
2023-12-12T04:29:21.299904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
9.7 2
 
5.0%
7.0 2
 
5.0%
5.1 2
 
5.0%
13.4 1
 
2.5%
16.3 1
 
2.5%
28.9 1
 
2.5%
26.8 1
 
2.5%
6.6 1
 
2.5%
9.0 1
 
2.5%
9.6 1
 
2.5%
Other values (27) 27
67.5%
ValueCountFrequency (%)
2.0 1
2.5%
2.1 1
2.5%
2.5 1
2.5%
3.1 1
2.5%
4.1 1
2.5%
4.3 1
2.5%
4.5 1
2.5%
4.6 1
2.5%
4.8 1
2.5%
4.9 1
2.5%
ValueCountFrequency (%)
37.5 1
2.5%
28.9 1
2.5%
28.4 1
2.5%
26.8 1
2.5%
25.2 1
2.5%
22.4 1
2.5%
20.8 1
2.5%
20.1 1
2.5%
16.5 1
2.5%
16.3 1
2.5%

3~5만원
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1525
Minimum3.3
Maximum19.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:21.437339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile3.695
Q15.3
median7.75
Q312.15
95-th percentile17.585
Maximum19.2
Range15.9
Interquartile range (IQR)6.85

Descriptive statistics

Standard deviation4.8209472
Coefficient of variation (CV)0.52673556
Kurtosis-0.52239712
Mean9.1525
Median Absolute Deviation (MAD)2.65
Skewness0.85689353
Sum366.1
Variance23.241532
MonotonicityNot monotonic
2023-12-12T04:29:21.591873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
19.2 2
 
5.0%
7.8 2
 
5.0%
5.2 2
 
5.0%
17.4 2
 
5.0%
12.3 2
 
5.0%
5.3 2
 
5.0%
3.3 1
 
2.5%
3.6 1
 
2.5%
3.7 1
 
2.5%
17.1 1
 
2.5%
Other values (24) 24
60.0%
ValueCountFrequency (%)
3.3 1
2.5%
3.6 1
2.5%
3.7 1
2.5%
4.3 1
2.5%
4.5 1
2.5%
4.6 1
2.5%
4.8 1
2.5%
5.2 2
5.0%
5.3 2
5.0%
5.6 1
2.5%
ValueCountFrequency (%)
19.2 2
5.0%
17.5 1
2.5%
17.4 2
5.0%
17.1 1
2.5%
16.7 1
2.5%
14.4 1
2.5%
12.3 2
5.0%
12.1 1
2.5%
12.0 1
2.5%
10.5 1
2.5%

5~7만원
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.7875
Minimum7.2
Maximum29.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:21.800138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile10.095
Q112.975
median15.5
Q319.725
95-th percentile28.34
Maximum29.7
Range22.5
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation5.3982992
Coefficient of variation (CV)0.3215666
Kurtosis0.17520235
Mean16.7875
Median Absolute Deviation (MAD)3.2
Skewness0.73993037
Sum671.5
Variance29.141635
MonotonicityNot monotonic
2023-12-12T04:29:21.968782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
14.4 3
 
7.5%
12.3 3
 
7.5%
15.1 2
 
5.0%
16.5 2
 
5.0%
17.4 2
 
5.0%
15.5 2
 
5.0%
29.1 1
 
2.5%
17.1 1
 
2.5%
21.8 1
 
2.5%
19.6 1
 
2.5%
Other values (22) 22
55.0%
ValueCountFrequency (%)
7.2 1
 
2.5%
10.0 1
 
2.5%
10.1 1
 
2.5%
10.2 1
 
2.5%
10.4 1
 
2.5%
11.2 1
 
2.5%
12.1 1
 
2.5%
12.3 3
7.5%
13.2 1
 
2.5%
14.0 1
 
2.5%
ValueCountFrequency (%)
29.7 1
2.5%
29.1 1
2.5%
28.3 1
2.5%
24.3 1
2.5%
24.0 1
2.5%
23.3 1
2.5%
21.9 1
2.5%
21.8 1
2.5%
21.2 1
2.5%
20.1 1
2.5%

7~9만원
Real number (ℝ)

Distinct22
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.63
Minimum1.6
Maximum8.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:22.115275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6
5-th percentile1.9
Q12.75
median2.95
Q34.05
95-th percentile6.825
Maximum8.6
Range7
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.6519142
Coefficient of variation (CV)0.45507278
Kurtosis1.4295576
Mean3.63
Median Absolute Deviation (MAD)0.5
Skewness1.4538422
Sum145.2
Variance2.7288205
MonotonicityNot monotonic
2023-12-12T04:29:22.341251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2.9 7
17.5%
2.5 3
 
7.5%
3.0 3
 
7.5%
2.8 3
 
7.5%
2.2 3
 
7.5%
5.0 2
 
5.0%
6.4 2
 
5.0%
1.9 2
 
5.0%
3.8 2
 
5.0%
8.6 1
 
2.5%
Other values (12) 12
30.0%
ValueCountFrequency (%)
1.6 1
 
2.5%
1.9 2
 
5.0%
2.2 3
7.5%
2.5 3
7.5%
2.6 1
 
2.5%
2.8 3
7.5%
2.9 7
17.5%
3.0 3
7.5%
3.1 1
 
2.5%
3.2 1
 
2.5%
ValueCountFrequency (%)
8.6 1
2.5%
7.3 1
2.5%
6.8 1
2.5%
6.7 1
2.5%
6.4 2
5.0%
5.0 2
5.0%
4.3 1
2.5%
4.2 1
2.5%
4.0 1
2.5%
3.8 2
5.0%

9-15만원
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.0375
Minimum12.3
Maximum24.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:22.538609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.3
5-th percentile13.54
Q118.8
median20.35
Q322.425
95-th percentile24.31
Maximum24.9
Range12.6
Interquartile range (IQR)3.625

Descriptive statistics

Standard deviation3.3562561
Coefficient of variation (CV)0.16749875
Kurtosis-0.056982874
Mean20.0375
Median Absolute Deviation (MAD)2
Skewness-0.82795143
Sum801.5
Variance11.264455
MonotonicityNot monotonic
2023-12-12T04:29:22.731536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
20.1 2
 
5.0%
18.9 2
 
5.0%
20.3 2
 
5.0%
22.0 2
 
5.0%
16.4 1
 
2.5%
21.9 1
 
2.5%
14.4 1
 
2.5%
20.9 1
 
2.5%
13.6 1
 
2.5%
20.4 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
12.3 1
2.5%
12.4 1
2.5%
13.6 1
2.5%
14.4 1
2.5%
14.6 1
2.5%
15.3 1
2.5%
16.4 1
2.5%
16.9 1
2.5%
17.8 1
2.5%
18.5 1
2.5%
ValueCountFrequency (%)
24.9 1
2.5%
24.5 1
2.5%
24.3 1
2.5%
24.0 1
2.5%
23.5 1
2.5%
23.1 1
2.5%
23.0 1
2.5%
22.9 1
2.5%
22.7 1
2.5%
22.5 1
2.5%

15만원이상
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.2525
Minimum10.5
Maximum63.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:22.921316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.5
5-th percentile14.915
Q126.5
median43.8
Q350.025
95-th percentile59.625
Maximum63.3
Range52.8
Interquartile range (IQR)23.525

Descriptive statistics

Standard deviation15.158885
Coefficient of variation (CV)0.38618903
Kurtosis-0.94934466
Mean39.2525
Median Absolute Deviation (MAD)7.8
Skewness-0.55887511
Sum1570.1
Variance229.79179
MonotonicityNot monotonic
2023-12-12T04:29:23.114119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
51.4 2
 
5.0%
48.6 2
 
5.0%
13.3 1
 
2.5%
15.3 1
 
2.5%
21.5 1
 
2.5%
46.4 1
 
2.5%
44.0 1
 
2.5%
41.6 1
 
2.5%
28.1 1
 
2.5%
10.5 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
10.5 1
2.5%
13.3 1
2.5%
15.0 1
2.5%
15.3 1
2.5%
16.0 1
2.5%
16.6 1
2.5%
17.0 1
2.5%
17.4 1
2.5%
21.5 1
2.5%
21.7 1
2.5%
ValueCountFrequency (%)
63.3 1
2.5%
60.1 1
2.5%
59.6 1
2.5%
56.0 1
2.5%
53.6 1
2.5%
53.1 1
2.5%
51.8 1
2.5%
51.4 2
5.0%
51.3 1
2.5%
49.6 1
2.5%

표본수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2537.05
Minimum487
Maximum10498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T04:29:23.306464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum487
5-th percentile617.45
Q11367.5
median1524
Q31879
95-th percentile10061.4
Maximum10498
Range10011
Interquartile range (IQR)511.5

Descriptive statistics

Standard deviation2939.4489
Coefficient of variation (CV)1.158609
Kurtosis3.5396832
Mean2537.05
Median Absolute Deviation (MAD)282.5
Skewness2.2763631
Sum101482
Variance8640360.1
MonotonicityNot monotonic
2023-12-12T04:29:23.516892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
696 1
 
2.5%
1377 1
 
2.5%
10088 1
 
2.5%
588 1
 
2.5%
1512 1
 
2.5%
1492 1
 
2.5%
1782 1
 
2.5%
1900 1
 
2.5%
1477 1
 
2.5%
1298 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
487 1
2.5%
588 1
2.5%
619 1
2.5%
661 1
2.5%
696 1
2.5%
1166 1
2.5%
1202 1
2.5%
1298 1
2.5%
1324 1
2.5%
1357 1
2.5%
ValueCountFrequency (%)
10498 1
2.5%
10088 1
2.5%
10060 1
2.5%
10049 1
2.5%
10046 1
2.5%
2007 1
2.5%
1998 1
2.5%
1900 1
2.5%
1888 1
2.5%
1885 1
2.5%

Interactions

2023-12-12T04:29:19.058203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.109341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.678713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.297461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.940363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.699942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.382630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.149149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.195497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.761227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.380299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.051167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.783841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.474797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.248221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.282155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.846250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.466384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.171618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.886220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.608456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.343715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.359978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.924465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.551483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.277540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.964353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.698498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.455937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.441119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.009659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.645604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.387569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.070408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.787737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.566151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.524637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.105962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.737664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.507317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.214789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.882547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:19.693069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:15.604891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.201494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:16.837603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:17.615010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.301081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:18.966250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:29:23.668697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일(년)연령별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
기준일(년)1.0000.0000.0000.2590.1530.5210.5560.4330.000
연령별0.0001.0000.6700.6860.6960.1250.4820.6710.886
3만원 미만0.0000.6701.0000.8230.7480.7110.7430.6970.693
3~5만원0.2590.6860.8231.0000.8470.3680.7480.7900.834
5~7만원0.1530.6960.7480.8471.0000.0000.5660.8610.837
7~9만원0.5210.1250.7110.3680.0001.0000.3710.1340.000
9-15만원0.5560.4820.7430.7480.5660.3711.0000.7780.628
15만원이상0.4330.6710.6970.7900.8610.1340.7781.0000.745
표본수0.0000.8860.6930.8340.8370.0000.6280.7451.000
2023-12-12T04:29:23.841554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령별기준일(년)
연령별1.0000.000
기준일(년)0.0001.000
2023-12-12T04:29:23.957474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수기준일(년)연령별
3만원 미만1.0000.8390.789-0.189-0.690-0.853-0.4770.0000.396
3~5만원0.8391.0000.8890.248-0.539-0.956-0.4800.1220.412
5~7만원0.7890.8891.0000.213-0.498-0.931-0.5140.0350.422
7~9만원-0.1890.2480.2131.0000.167-0.206-0.1350.3090.160
9-15만원-0.690-0.539-0.4980.1671.0000.4730.5710.2310.233
15만원이상-0.853-0.956-0.931-0.2060.4731.0000.4860.1610.380
표본수-0.477-0.480-0.514-0.1350.5710.4861.0000.0000.805
기준일(년)0.0000.1220.0350.3090.2310.1610.0001.0000.000
연령별0.3960.4120.4220.1600.2330.3800.8050.0001.000

Missing values

2023-12-12T04:29:19.815397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:29:19.946251image/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

기준일(년)연령별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
0201815~19세13.419.229.18.616.413.3696
1201820대2.04.612.36.423.551.31458
2201830대2.55.910.15.022.953.61560
3201840대2.14.311.26.822.453.11998
4201850대3.16.512.36.724.946.62007
5201860대5.67.718.77.324.036.71422
6201870세이상16.516.723.35.016.921.71357
72018전체5.17.814.86.422.343.610498
8201915~19세20.819.228.34.312.315.0661
9201920대4.64.817.43.221.348.81468
기준일(년)연령별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
30202170세이상37.517.519.62.612.410.51298
312021전체14.09.516.52.819.937.310049
32202215~19세20.112.329.73.517.816.6487
33202220대5.13.710.02.518.560.11371
34202230대4.33.37.22.918.963.31433
35202240대6.13.610.21.618.959.61717
36202250대7.04.510.41.920.256.01831
37202260대9.76.314.42.224.542.91707
38202270세이상22.412.324.33.820.317.01500
392022전체9.35.713.22.520.149.210046