Overview

Dataset statistics

Number of variables9
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory85.3 B

Variable types

Categorical2
Numeric7

Dataset

Description- 학력에 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/796

Alerts

3만원 미만 is highly overall correlated with 3~5만원 and 4 other fieldsHigh correlation
3~5만원 is highly overall correlated with 3만원 미만 and 4 other fieldsHigh correlation
5~7만원 is highly overall correlated with 3만원 미만 and 4 other fieldsHigh correlation
9-15만원 is highly overall correlated with 3만원 미만 and 4 other fieldsHigh correlation
15만원이상 is highly overall correlated with 3만원 미만 and 5 other fieldsHigh correlation
표본수 is highly overall correlated with 3만원 미만 and 5 other fieldsHigh correlation
학력별 is highly overall correlated with 15만원이상 and 1 other fieldsHigh correlation
3만원 미만 has unique valuesUnique
5~7만원 has unique valuesUnique
15만원이상 has unique valuesUnique
표본수 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:47:24.407420
Analysis finished2023-12-11 19:47:31.958445
Duration7.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일(년)
Categorical

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 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 5
20.0%
2019 5
20.0%
2020 5
20.0%
2021 5
20.0%
2022 5
20.0%

Length

2023-12-12T04:47:32.033206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:47:32.165933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 5
20.0%
2019 5
20.0%
2020 5
20.0%
2021 5
20.0%
2022 5
20.0%

학력별
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
고졸
전체
중졸
초졸 이하
대졸 이상

Length

Max length5
Median length2
Mean length3.12
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고졸
2nd row대졸 이상
3rd row전체
4th row중졸
5th row초졸 이하

Common Values

ValueCountFrequency (%)
고졸 5
20.0%
전체 5
20.0%
중졸 5
20.0%
초졸 이하 5
20.0%
대졸 이상 3
12.0%
대졸이상 2
 
8.0%

Length

2023-12-12T04:47:32.318313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:47:32.469950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고졸 5
15.2%
전체 5
15.2%
중졸 5
15.2%
초졸 5
15.2%
이하 5
15.2%
대졸 3
9.1%
이상 3
9.1%
대졸이상 2
 
6.1%

3만원 미만
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.192
Minimum2.2
Maximum39.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:32.612977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3.54
Q16.2
median9.8
Q319.8
95-th percentile33.56
Maximum39.7
Range37.5
Interquartile range (IQR)13.6

Descriptive statistics

Standard deviation10.736772
Coefficient of variation (CV)0.7565369
Kurtosis-0.048051319
Mean14.192
Median Absolute Deviation (MAD)5.6
Skewness1.0084247
Sum354.8
Variance115.27827
MonotonicityNot monotonic
2023-12-12T04:47:32.761791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3.4 1
 
4.0%
2.2 1
 
4.0%
9.3 1
 
4.0%
5.0 1
 
4.0%
7.8 1
 
4.0%
16.0 1
 
4.0%
28.0 1
 
4.0%
14.0 1
 
4.0%
6.8 1
 
4.0%
11.1 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
2.2 1
4.0%
3.4 1
4.0%
4.1 1
4.0%
4.2 1
4.0%
5.0 1
4.0%
5.1 1
4.0%
6.2 1
4.0%
6.8 1
4.0%
7.4 1
4.0%
7.8 1
4.0%
ValueCountFrequency (%)
39.7 1
4.0%
33.9 1
4.0%
32.2 1
4.0%
28.0 1
4.0%
27.9 1
4.0%
21.2 1
4.0%
19.8 1
4.0%
19.0 1
4.0%
16.0 1
4.0%
14.0 1
4.0%

3~5만원
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.628
Minimum3.2
Maximum20.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:32.922786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2
5-th percentile4
Q15.7
median9.4
Q315.3
95-th percentile20.14
Maximum20.6
Range17.4
Interquartile range (IQR)9.6

Descriptive statistics

Standard deviation5.4318137
Coefficient of variation (CV)0.51108522
Kurtosis-1.0614729
Mean10.628
Median Absolute Deviation (MAD)4.6
Skewness0.45234191
Sum265.7
Variance29.5046
MonotonicityNot monotonic
2023-12-12T04:47:33.068337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
15.3 2
 
8.0%
6.9 1
 
4.0%
15.2 1
 
4.0%
5.7 1
 
4.0%
3.2 1
 
4.0%
4.8 1
 
4.0%
11.7 1
 
4.0%
9.5 1
 
4.0%
5.4 1
 
4.0%
9.7 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
3.2 1
4.0%
3.9 1
4.0%
4.4 1
4.0%
4.8 1
4.0%
5.4 1
4.0%
5.5 1
4.0%
5.7 1
4.0%
6.9 1
4.0%
7.5 1
4.0%
7.8 1
4.0%
ValueCountFrequency (%)
20.6 1
4.0%
20.4 1
4.0%
19.1 1
4.0%
17.0 1
4.0%
15.8 1
4.0%
15.3 2
8.0%
15.2 1
4.0%
14.3 1
4.0%
11.7 1
4.0%
9.7 1
4.0%

5~7만원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.112
Minimum7.6
Maximum27.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:33.227191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.6
5-th percentile10.38
Q113.2
median17.5
Q323.1
95-th percentile26.98
Maximum27.7
Range20.1
Interquartile range (IQR)9.9

Descriptive statistics

Standard deviation5.5632964
Coefficient of variation (CV)0.3071608
Kurtosis-0.85840906
Mean18.112
Median Absolute Deviation (MAD)4.5
Skewness0.13128165
Sum452.8
Variance30.950267
MonotonicityNot monotonic
2023-12-12T04:47:33.372572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
14.5 1
 
4.0%
9.9 1
 
4.0%
13.2 1
 
4.0%
7.6 1
 
4.0%
13.0 1
 
4.0%
24.7 1
 
4.0%
27.3 1
 
4.0%
16.5 1
 
4.0%
12.8 1
 
4.0%
18.3 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
7.6 1
4.0%
9.9 1
4.0%
12.3 1
4.0%
12.8 1
4.0%
12.9 1
4.0%
13.0 1
4.0%
13.2 1
4.0%
14.5 1
4.0%
14.8 1
4.0%
16.5 1
4.0%
ValueCountFrequency (%)
27.7 1
4.0%
27.3 1
4.0%
25.7 1
4.0%
25.1 1
4.0%
24.7 1
4.0%
23.5 1
4.0%
23.1 1
4.0%
21.3 1
4.0%
20.4 1
4.0%
18.5 1
4.0%

7~9만원
Real number (ℝ)

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.524
Minimum1.8
Maximum7.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:33.507856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile1.86
Q12.5
median3
Q33.6
95-th percentile6.56
Maximum7.8
Range6
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation1.5780473
Coefficient of variation (CV)0.44780003
Kurtosis1.4054595
Mean3.524
Median Absolute Deviation (MAD)0.5
Skewness1.463266
Sum88.1
Variance2.4902333
MonotonicityNot monotonic
2023-12-12T04:47:33.663693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2.9 3
12.0%
1.8 2
 
8.0%
3.4 2
 
8.0%
2.3 2
 
8.0%
3.0 2
 
8.0%
3.6 2
 
8.0%
2.8 2
 
8.0%
2.5 2
 
8.0%
2.1 1
 
4.0%
3.5 1
 
4.0%
Other values (6) 6
24.0%
ValueCountFrequency (%)
1.8 2
8.0%
2.1 1
 
4.0%
2.3 2
8.0%
2.5 2
8.0%
2.8 2
8.0%
2.9 3
12.0%
3.0 2
8.0%
3.3 1
 
4.0%
3.4 2
8.0%
3.5 1
 
4.0%
ValueCountFrequency (%)
7.8 1
4.0%
6.6 1
4.0%
6.4 1
4.0%
5.9 1
4.0%
5.0 1
4.0%
3.6 2
8.0%
3.5 1
4.0%
3.4 2
8.0%
3.3 1
4.0%
3.0 2
8.0%

9-15만원
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.284
Minimum10.4
Maximum23.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:33.825969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.4
5-th percentile13.2
Q117.3
median20.3
Q321.8
95-th percentile23.36
Maximum23.8
Range13.4
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.6832594
Coefficient of variation (CV)0.1910008
Kurtosis-0.10241051
Mean19.284
Median Absolute Deviation (MAD)2.1
Skewness-0.90137584
Sum482.1
Variance13.5664
MonotonicityNot monotonic
2023-12-12T04:47:33.991779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
21.1 2
 
8.0%
22.3 2
 
8.0%
13.2 2
 
8.0%
17.9 1
 
4.0%
20.1 1
 
4.0%
18.2 1
 
4.0%
23.1 1
 
4.0%
15.4 1
 
4.0%
19.9 1
 
4.0%
21.6 1
 
4.0%
Other values (12) 12
48.0%
ValueCountFrequency (%)
10.4 1
4.0%
13.2 2
8.0%
14.4 1
4.0%
15.4 1
4.0%
15.7 1
4.0%
17.3 1
4.0%
17.9 1
4.0%
18.2 1
4.0%
19.9 1
4.0%
20.0 1
4.0%
ValueCountFrequency (%)
23.8 1
4.0%
23.4 1
4.0%
23.2 1
4.0%
23.1 1
4.0%
22.3 2
8.0%
21.8 1
4.0%
21.6 1
4.0%
21.5 1
4.0%
21.1 2
8.0%
20.9 1
4.0%

15만원이상
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.252
Minimum8.6
Maximum63.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:34.143177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.6
5-th percentile9.6
Q120.3
median40.3
Q349.2
95-th percentile54.7
Maximum63.9
Range55.3
Interquartile range (IQR)28.9

Descriptive statistics

Standard deviation17.183716
Coefficient of variation (CV)0.50168504
Kurtosis-1.3718355
Mean34.252
Median Absolute Deviation (MAD)14
Skewness-0.15899297
Sum856.3
Variance295.2801
MonotonicityNot monotonic
2023-12-12T04:47:34.288038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
45.5 1
 
4.0%
54.3 1
 
4.0%
49.2 1
 
4.0%
63.9 1
 
4.0%
49.7 1
 
4.0%
20.9 1
 
4.0%
10.4 1
 
4.0%
37.3 1
 
4.0%
51.1 1
 
4.0%
36.3 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
8.6 1
4.0%
9.4 1
4.0%
10.4 1
4.0%
11.5 1
4.0%
12.3 1
4.0%
16.5 1
4.0%
20.3 1
4.0%
20.6 1
4.0%
20.9 1
4.0%
22.5 1
4.0%
ValueCountFrequency (%)
63.9 1
4.0%
54.8 1
4.0%
54.3 1
4.0%
53.4 1
4.0%
51.1 1
4.0%
49.7 1
4.0%
49.2 1
4.0%
45.5 1
4.0%
43.6 1
4.0%
42.0 1
4.0%

표본수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4059.28
Minimum923
Maximum10498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T04:47:34.432698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum923
5-th percentile1073.8
Q11146
median3805
Q34039
95-th percentile10082.4
Maximum10498
Range9575
Interquartile range (IQR)2893

Descriptive statistics

Standard deviation3362.8183
Coefficient of variation (CV)0.82842728
Kurtosis-0.21743459
Mean4059.28
Median Absolute Deviation (MAD)2654
Skewness1.0503752
Sum101482
Variance11308547
MonotonicityNot monotonic
2023-12-12T04:47:34.568933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4491 1
 
4.0%
3632 1
 
4.0%
10046 1
 
4.0%
3974 1
 
4.0%
3790 1
 
4.0%
1136 1
 
4.0%
1146 1
 
4.0%
10049 1
 
4.0%
3841 1
 
4.0%
3927 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
923 1
4.0%
1067 1
4.0%
1101 1
4.0%
1136 1
4.0%
1139 1
4.0%
1142 1
4.0%
1146 1
4.0%
1151 1
4.0%
1164 1
4.0%
1452 1
4.0%
ValueCountFrequency (%)
10498 1
4.0%
10088 1
4.0%
10060 1
4.0%
10049 1
4.0%
10046 1
4.0%
4491 1
4.0%
4039 1
4.0%
3974 1
4.0%
3940 1
4.0%
3927 1
4.0%

Interactions

2023-12-12T04:47:30.878020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:24.777093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.574829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.511075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.600853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.556508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:29.971014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.010635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:24.887275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.714579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.727463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.731968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.717215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.103070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.139953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:24.999024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.840758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.887430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.867590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.866380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.214421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.256090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.115089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.952587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.035020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.010630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:29.025815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.356135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.369111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.214811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.081351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.177675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.144536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:29.575092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.491339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.479317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.345296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.225590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.337126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.285396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:29.719726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.626107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:31.564914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:25.456498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:26.366207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:27.469054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:28.415378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:29.860876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:47:30.763467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:47:34.719023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일(년)학력별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
기준일(년)1.0000.0000.0000.3880.3840.1770.0000.0000.000
학력별0.0001.0000.4840.6730.6860.6130.5420.9080.901
3만원 미만0.0000.4841.0000.7100.6550.0000.7990.6690.095
3~5만원0.3880.6730.7101.0000.7560.4260.5750.9090.865
5~7만원0.3840.6860.6550.7561.0000.7240.6410.8780.756
7~9만원0.1770.6130.0000.4260.7241.0000.0000.4620.666
9-15만원0.0000.5420.7990.5750.6410.0001.0000.5830.399
15만원이상0.0000.9080.6690.9090.8780.4620.5831.0000.838
표본수0.0000.9010.0950.8650.7560.6660.3990.8381.000
2023-12-12T04:47:35.009971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학력별기준일(년)
학력별1.0000.000
기준일(년)0.0001.000
2023-12-12T04:47:35.241806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수기준일(년)학력별
3만원 미만1.0000.9000.825-0.219-0.809-0.936-0.6290.0000.152
3~5만원0.9001.0000.9210.111-0.720-0.971-0.5960.2000.419
5~7만원0.8250.9211.0000.262-0.571-0.916-0.6070.0630.380
7~9만원-0.2190.1110.2621.0000.343-0.0300.0100.1930.295
9-15만원-0.809-0.720-0.5710.3431.0000.6950.5100.0000.335
15만원이상-0.936-0.971-0.916-0.0300.6951.0000.6060.0000.745
표본수-0.629-0.596-0.6070.0100.5100.6061.0000.0000.745
기준일(년)0.0000.2000.0630.1930.0000.0000.0001.0000.000
학력별0.1520.4190.3800.2950.3350.7450.7450.0001.000

Missing values

2023-12-12T04:47:31.719680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:47:31.900629image/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)학력별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
02018고졸3.46.914.56.623.245.54491
12018대졸 이상2.23.99.95.923.854.33632
22018전체5.17.814.86.422.343.610498
32018중졸11.015.323.57.820.022.51452
42018초졸 이하21.220.627.75.013.212.3923
52019고졸7.47.518.23.021.842.03940
62019대졸 이상4.14.412.32.921.554.83805
72019전체9.88.117.42.920.341.510060
82019중졸19.015.825.73.615.720.31164
92019초졸 이하32.217.025.11.814.49.41151
기준일(년)학력별3만원 미만3~5만원5~7만원7~9만원9-15만원15만원이상표본수
152021초졸 이하39.720.418.52.510.48.61139
162021중졸27.914.321.32.817.316.51142
172021고졸11.19.718.33.421.136.33927
182021대졸이상6.85.412.82.321.651.13841
192021전체14.09.516.52.819.937.310049
202022초졸 이하28.015.327.33.515.410.41146
212022중졸16.011.724.73.623.120.91136
222022고졸7.84.813.02.322.349.73790
232022대졸이상5.03.27.62.118.263.93974
242022전체9.35.713.22.520.149.210046