Overview

Dataset statistics

Number of variables15
Number of observations37
Missing cells79
Missing cells (%)14.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory137.6 B

Variable types

Text1
Numeric14

Dataset

Description사립학교교직원연금공단 사학연금수급자 현황 (장해연금수급자)과 관련된 데이터로 연령별(42세 미만 ~ 77세 이상), 재직기간별(21년 미만 ~ 33년 이상) 수급자 현황 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15045819/fileData.do

Alerts

21년미만 is highly overall correlated with 22년미만 and 12 other fieldsHigh correlation
22년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
23년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
24년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
25년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
26년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
27년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
28년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
29년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
30년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
31년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
32년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
33년미만 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
33년이상 is highly overall correlated with 21년미만 and 12 other fieldsHigh correlation
22년미만 has 5 (13.5%) missing valuesMissing
23년미만 has 5 (13.5%) missing valuesMissing
24년미만 has 6 (16.2%) missing valuesMissing
25년미만 has 6 (16.2%) missing valuesMissing
26년미만 has 8 (21.6%) missing valuesMissing
27년미만 has 6 (16.2%) missing valuesMissing
28년미만 has 8 (21.6%) missing valuesMissing
29년미만 has 7 (18.9%) missing valuesMissing
30년미만 has 6 (16.2%) missing valuesMissing
31년미만 has 6 (16.2%) missing valuesMissing
32년미만 has 7 (18.9%) missing valuesMissing
33년미만 has 8 (21.6%) missing valuesMissing
33년이상 has 1 (2.7%) missing valuesMissing
연령 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:29:02.226935
Analysis finished2023-12-12 21:29:21.815127
Duration19.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연령
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-13T06:29:21.918948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters222
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row42세 미만
2nd row43세 미만
3rd row44세 미만
4th row45세 미만
5th row46세 미만
ValueCountFrequency (%)
미만 36
48.6%
77세 2
 
2.7%
42세 1
 
1.4%
68세 1
 
1.4%
62세 1
 
1.4%
63세 1
 
1.4%
64세 1
 
1.4%
65세 1
 
1.4%
66세 1
 
1.4%
67세 1
 
1.4%
Other values (28) 28
37.8%
2023-12-13T06:29:22.201581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
16.7%
37
16.7%
36
16.2%
36
16.2%
5 14
 
6.3%
6 14
 
6.3%
7 14
 
6.3%
4 12
 
5.4%
2 4
 
1.8%
3 4
 
1.8%
Other values (6) 14
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
50.0%
Decimal Number 74
33.3%
Space Separator 37
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
18.9%
6 14
18.9%
7 14
18.9%
4 12
16.2%
2 4
 
5.4%
3 4
 
5.4%
8 3
 
4.1%
9 3
 
4.1%
0 3
 
4.1%
1 3
 
4.1%
Other Letter
ValueCountFrequency (%)
37
33.3%
36
32.4%
36
32.4%
1
 
0.9%
1
 
0.9%
Space Separator
ValueCountFrequency (%)
37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
50.0%
Common 111
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
37
33.3%
5 14
 
12.6%
6 14
 
12.6%
7 14
 
12.6%
4 12
 
10.8%
2 4
 
3.6%
3 4
 
3.6%
8 3
 
2.7%
9 3
 
2.7%
0 3
 
2.7%
Hangul
ValueCountFrequency (%)
37
33.3%
36
32.4%
36
32.4%
1
 
0.9%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
50.0%
ASCII 111
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
37
33.3%
36
32.4%
36
32.4%
1
 
0.9%
1
 
0.9%
ASCII
ValueCountFrequency (%)
37
33.3%
5 14
 
12.6%
6 14
 
12.6%
7 14
 
12.6%
4 12
 
10.8%
2 4
 
3.6%
3 4
 
3.6%
8 3
 
2.7%
9 3
 
2.7%
0 3
 
2.7%

21년미만
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean255.7027
Minimum5
Maximum1021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:22.322716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10.2
Q121
median89
Q3408
95-th percentile857
Maximum1021
Range1016
Interquartile range (IQR)387

Descriptive statistics

Standard deviation314.46046
Coefficient of variation (CV)1.2297894
Kurtosis-0.087841771
Mean255.7027
Median Absolute Deviation (MAD)75
Skewness1.1639538
Sum9461
Variance98885.381
MonotonicityNot monotonic
2023-12-13T06:29:22.447847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
86 2
 
5.4%
11 2
 
5.4%
131 1
 
2.7%
408 1
 
2.7%
777 1
 
2.7%
776 1
 
2.7%
1021 1
 
2.7%
844 1
 
2.7%
715 1
 
2.7%
532 1
 
2.7%
Other values (25) 25
67.6%
ValueCountFrequency (%)
5 1
2.7%
7 1
2.7%
11 2
5.4%
12 1
2.7%
14 1
2.7%
16 1
2.7%
17 1
2.7%
20 1
2.7%
21 1
2.7%
22 1
2.7%
ValueCountFrequency (%)
1021 1
2.7%
909 1
2.7%
844 1
2.7%
777 1
2.7%
776 1
2.7%
728 1
2.7%
715 1
2.7%
532 1
2.7%
490 1
2.7%
408 1
2.7%

22년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct27
Distinct (%)84.4%
Missing5
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean76.5625
Minimum1
Maximum532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:22.563013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q111
median65
Q3108.5
95-th percentile154.7
Maximum532
Range531
Interquartile range (IQR)97.5

Descriptive statistics

Standard deviation97.18122
Coefficient of variation (CV)1.2693057
Kurtosis15.747019
Mean76.5625
Median Absolute Deviation (MAD)52
Skewness3.458997
Sum2450
Variance9444.1895
MonotonicityNot monotonic
2023-12-13T06:29:22.929719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3 3
 
8.1%
11 2
 
5.4%
65 2
 
5.4%
1 2
 
5.4%
135 1
 
2.7%
532 1
 
2.7%
79 1
 
2.7%
80 1
 
2.7%
78 1
 
2.7%
118 1
 
2.7%
Other values (17) 17
45.9%
(Missing) 5
 
13.5%
ValueCountFrequency (%)
1 2
5.4%
2 1
 
2.7%
3 3
8.1%
10 1
 
2.7%
11 2
5.4%
19 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
46 1
 
2.7%
ValueCountFrequency (%)
532 1
2.7%
169 1
2.7%
143 1
2.7%
135 1
2.7%
132 1
2.7%
122 1
2.7%
118 1
2.7%
116 1
2.7%
106 1
2.7%
102 1
2.7%

23년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)78.1%
Missing5
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean80.125
Minimum1
Maximum545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:23.032285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q17.5
median68
Q3114.75
95-th percentile162.65
Maximum545
Range544
Interquartile range (IQR)107.25

Descriptive statistics

Standard deviation101.35016
Coefficient of variation (CV)1.2649006
Kurtosis14.215228
Mean80.125
Median Absolute Deviation (MAD)57.5
Skewness3.2285953
Sum2564
Variance10271.855
MonotonicityNot monotonic
2023-12-13T06:29:23.139306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
20 2
 
5.4%
155 2
 
5.4%
114 2
 
5.4%
8 2
 
5.4%
2 2
 
5.4%
1 2
 
5.4%
5 2
 
5.4%
6 1
 
2.7%
109 1
 
2.7%
545 1
 
2.7%
Other values (15) 15
40.5%
(Missing) 5
 
13.5%
ValueCountFrequency (%)
1 2
5.4%
2 2
5.4%
3 1
2.7%
5 2
5.4%
6 1
2.7%
8 2
5.4%
20 2
5.4%
38 1
2.7%
45 1
2.7%
47 1
2.7%
ValueCountFrequency (%)
545 1
2.7%
172 1
2.7%
155 2
5.4%
143 1
2.7%
130 1
2.7%
123 1
2.7%
117 1
2.7%
114 2
5.4%
109 1
2.7%
95 1
2.7%

24년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)83.9%
Missing6
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean90.451613
Minimum1
Maximum614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:23.257740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15.5
median78
Q3134
95-th percentile176.5
Maximum614
Range613
Interquartile range (IQR)128.5

Descriptive statistics

Standard deviation114.79165
Coefficient of variation (CV)1.2690945
Kurtosis14.479667
Mean90.451613
Median Absolute Deviation (MAD)64
Skewness3.2656603
Sum2804
Variance13177.123
MonotonicityNot monotonic
2023-12-13T06:29:23.368125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 3
 
8.1%
2 3
 
8.1%
103 2
 
5.4%
4 1
 
2.7%
152 1
 
2.7%
614 1
 
2.7%
104 1
 
2.7%
98 1
 
2.7%
78 1
 
2.7%
68 1
 
2.7%
Other values (16) 16
43.2%
(Missing) 6
 
16.2%
ValueCountFrequency (%)
1 3
8.1%
2 3
8.1%
3 1
 
2.7%
4 1
 
2.7%
7 1
 
2.7%
16 1
 
2.7%
22 1
 
2.7%
34 1
 
2.7%
46 1
 
2.7%
50 1
 
2.7%
ValueCountFrequency (%)
614 1
2.7%
190 1
2.7%
163 1
2.7%
152 1
2.7%
149 1
2.7%
146 1
2.7%
142 1
2.7%
137 1
2.7%
131 1
2.7%
118 1
2.7%

25년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)77.4%
Missing6
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean93.774194
Minimum1
Maximum673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:23.476784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median92
Q3133.5
95-th percentile166.5
Maximum673
Range672
Interquartile range (IQR)125.5

Descriptive statistics

Standard deviation122.92483
Coefficient of variation (CV)1.3108599
Kurtosis16.887497
Mean93.774194
Median Absolute Deviation (MAD)55
Skewness3.6110173
Sum2907
Variance15110.514
MonotonicityNot monotonic
2023-12-13T06:29:23.637565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 4
 
10.8%
95 3
 
8.1%
132 2
 
5.4%
8 2
 
5.4%
7 1
 
2.7%
175 1
 
2.7%
673 1
 
2.7%
87 1
 
2.7%
92 1
 
2.7%
3 1
 
2.7%
Other values (14) 14
37.8%
(Missing) 6
16.2%
ValueCountFrequency (%)
1 4
10.8%
3 1
 
2.7%
4 1
 
2.7%
7 1
 
2.7%
8 2
5.4%
18 1
 
2.7%
20 1
 
2.7%
45 1
 
2.7%
50 1
 
2.7%
52 1
 
2.7%
ValueCountFrequency (%)
673 1
2.7%
175 1
2.7%
158 1
2.7%
152 1
2.7%
147 1
2.7%
144 1
2.7%
140 1
2.7%
135 1
2.7%
132 2
5.4%
127 1
2.7%

26년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)82.8%
Missing8
Missing (%)21.6%
Infinite0
Infinite (%)0.0%
Mean115.62069
Minimum1
Maximum707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:23.771641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q120
median99
Q3158
95-th percentile213
Maximum707
Range706
Interquartile range (IQR)138

Descriptive statistics

Standard deviation135.72883
Coefficient of variation (CV)1.1739147
Kurtosis12.81283
Mean115.62069
Median Absolute Deviation (MAD)79
Skewness3.0392492
Sum3353
Variance18422.315
MonotonicityNot monotonic
2023-12-13T06:29:23.899805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
6 2
 
5.4%
20 2
 
5.4%
99 2
 
5.4%
152 2
 
5.4%
213 2
 
5.4%
158 1
 
2.7%
707 1
 
2.7%
108 1
 
2.7%
126 1
 
2.7%
83 1
 
2.7%
Other values (14) 14
37.8%
(Missing) 8
21.6%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
6 2
5.4%
10 1
2.7%
20 2
5.4%
27 1
2.7%
58 1
2.7%
69 1
2.7%
ValueCountFrequency (%)
707 1
2.7%
213 2
5.4%
198 1
2.7%
195 1
2.7%
185 1
2.7%
174 1
2.7%
158 1
2.7%
155 1
2.7%
152 2
5.4%
126 1
2.7%

27년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)83.9%
Missing6
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean114.41935
Minimum1
Maximum790
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:24.032380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19
median91
Q3166
95-th percentile237
Maximum790
Range789
Interquartile range (IQR)157

Descriptive statistics

Standard deviation148.98071
Coefficient of variation (CV)1.3020586
Kurtosis14.087847
Mean114.41935
Median Absolute Deviation (MAD)81
Skewness3.2387961
Sum3547
Variance22195.252
MonotonicityNot monotonic
2023-12-13T06:29:24.166115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 4
 
10.8%
3 3
 
8.1%
224 1
 
2.7%
790 1
 
2.7%
91 1
 
2.7%
82 1
 
2.7%
109 1
 
2.7%
95 1
 
2.7%
108 1
 
2.7%
146 1
 
2.7%
Other values (16) 16
43.2%
(Missing) 6
 
16.2%
ValueCountFrequency (%)
1 4
10.8%
3 3
8.1%
4 1
 
2.7%
14 1
 
2.7%
18 1
 
2.7%
22 1
 
2.7%
39 1
 
2.7%
62 1
 
2.7%
74 1
 
2.7%
82 1
 
2.7%
ValueCountFrequency (%)
790 1
2.7%
250 1
2.7%
224 1
2.7%
223 1
2.7%
207 1
2.7%
189 1
2.7%
178 1
2.7%
172 1
2.7%
160 1
2.7%
156 1
2.7%

28년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)86.2%
Missing8
Missing (%)21.6%
Infinite0
Infinite (%)0.0%
Mean134.65517
Minimum1
Maximum919
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:24.289112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q126
median100
Q3185
95-th percentile286.4
Maximum919
Range918
Interquartile range (IQR)159

Descriptive statistics

Standard deviation173.26204
Coefficient of variation (CV)1.2867091
Kurtosis15.406018
Mean134.65517
Median Absolute Deviation (MAD)85
Skewness3.487033
Sum3905
Variance30019.734
MonotonicityNot monotonic
2023-12-13T06:29:24.401592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
9 2
 
5.4%
100 2
 
5.4%
116 2
 
5.4%
1 2
 
5.4%
186 1
 
2.7%
919 1
 
2.7%
111 1
 
2.7%
87 1
 
2.7%
156 1
 
2.7%
185 1
 
2.7%
Other values (15) 15
40.5%
(Missing) 8
21.6%
ValueCountFrequency (%)
1 2
5.4%
4 1
2.7%
9 2
5.4%
10 1
2.7%
12 1
2.7%
26 1
2.7%
33 1
2.7%
47 1
2.7%
75 1
2.7%
87 1
2.7%
ValueCountFrequency (%)
919 1
2.7%
304 1
2.7%
260 1
2.7%
226 1
2.7%
210 1
2.7%
190 1
2.7%
186 1
2.7%
185 1
2.7%
181 1
2.7%
156 1
2.7%

29년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct27
Distinct (%)90.0%
Missing7
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean142.8
Minimum1
Maximum919
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:24.525724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q124.75
median109
Q3196.25
95-th percentile302.3
Maximum919
Range918
Interquartile range (IQR)171.5

Descriptive statistics

Standard deviation173.79485
Coefficient of variation (CV)1.2170507
Kurtosis13.759964
Mean142.8
Median Absolute Deviation (MAD)89.5
Skewness3.2071951
Sum4284
Variance30204.648
MonotonicityNot monotonic
2023-12-13T06:29:24.648954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
200 2
 
5.4%
5 2
 
5.4%
2 2
 
5.4%
12 1
 
2.7%
277 1
 
2.7%
919 1
 
2.7%
122 1
 
2.7%
132 1
 
2.7%
111 1
 
2.7%
101 1
 
2.7%
Other values (17) 17
45.9%
(Missing) 7
18.9%
ValueCountFrequency (%)
1 1
2.7%
2 2
5.4%
5 2
5.4%
7 1
2.7%
12 1
2.7%
21 1
2.7%
36 1
2.7%
41 1
2.7%
70 1
2.7%
86 1
2.7%
ValueCountFrequency (%)
919 1
2.7%
323 1
2.7%
277 1
2.7%
258 1
2.7%
236 1
2.7%
202 1
2.7%
200 2
5.4%
185 1
2.7%
183 1
2.7%
178 1
2.7%

30년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)90.3%
Missing6
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean153.19355
Minimum1
Maximum1108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:24.773250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q123
median112
Q3220
95-th percentile322
Maximum1108
Range1107
Interquartile range (IQR)197

Descriptive statistics

Standard deviation203.42147
Coefficient of variation (CV)1.3278723
Kurtosis16.594976
Mean153.19355
Median Absolute Deviation (MAD)103
Skewness3.6131526
Sum4749
Variance41380.295
MonotonicityNot monotonic
2023-12-13T06:29:24.893050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 3
 
8.1%
6 2
 
5.4%
4 1
 
2.7%
12 1
 
2.7%
1108 1
 
2.7%
133 1
 
2.7%
97 1
 
2.7%
132 1
 
2.7%
99 1
 
2.7%
108 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 6
 
16.2%
ValueCountFrequency (%)
1 3
8.1%
4 1
 
2.7%
5 1
 
2.7%
6 2
5.4%
12 1
 
2.7%
34 1
 
2.7%
48 1
 
2.7%
63 1
 
2.7%
79 1
 
2.7%
97 1
 
2.7%
ValueCountFrequency (%)
1108 1
2.7%
339 1
2.7%
305 1
2.7%
278 1
2.7%
242 1
2.7%
227 1
2.7%
226 1
2.7%
225 1
2.7%
215 1
2.7%
185 1
2.7%

31년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)83.9%
Missing6
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean189.03226
Minimum1
Maximum1228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:25.012442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q149
median140
Q3258
95-th percentile382
Maximum1228
Range1227
Interquartile range (IQR)209

Descriptive statistics

Standard deviation225.88485
Coefficient of variation (CV)1.194954
Kurtosis15.113919
Mean189.03226
Median Absolute Deviation (MAD)118
Skewness3.3853204
Sum5860
Variance51023.966
MonotonicityNot monotonic
2023-12-13T06:29:25.162100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
149 2
 
5.4%
128 2
 
5.4%
1 2
 
5.4%
258 2
 
5.4%
3 2
 
5.4%
53 1
 
2.7%
440 1
 
2.7%
1228 1
 
2.7%
140 1
 
2.7%
130 1
 
2.7%
Other values (16) 16
43.2%
(Missing) 6
 
16.2%
ValueCountFrequency (%)
1 2
5.4%
3 2
5.4%
9 1
2.7%
15 1
2.7%
17 1
2.7%
45 1
2.7%
53 1
2.7%
91 1
2.7%
112 1
2.7%
114 1
2.7%
ValueCountFrequency (%)
1228 1
2.7%
440 1
2.7%
324 1
2.7%
307 1
2.7%
303 1
2.7%
286 1
2.7%
284 1
2.7%
258 2
5.4%
245 1
2.7%
228 1
2.7%

32년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)93.3%
Missing7
Missing (%)18.9%
Infinite0
Infinite (%)0.0%
Mean212.6
Minimum1
Maximum1369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:25.277050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q167.5
median159.5
Q3301.75
95-th percentile389.35
Maximum1369
Range1368
Interquartile range (IQR)234.25

Descriptive statistics

Standard deviation251.50246
Coefficient of variation (CV)1.1829843
Kurtosis15.791755
Mean212.6
Median Absolute Deviation (MAD)125.5
Skewness3.483542
Sum6378
Variance63253.49
MonotonicityNot monotonic
2023-12-13T06:29:25.406715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
231 2
 
5.4%
3 2
 
5.4%
14 1
 
2.7%
15 1
 
2.7%
1369 1
 
2.7%
148 1
 
2.7%
163 1
 
2.7%
156 1
 
2.7%
149 1
 
2.7%
121 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 7
 
18.9%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 2
5.4%
14 1
2.7%
15 1
2.7%
41 1
2.7%
60 1
2.7%
90 1
2.7%
113 1
2.7%
121 1
2.7%
ValueCountFrequency (%)
1369 1
2.7%
424 1
2.7%
347 1
2.7%
340 1
2.7%
332 1
2.7%
326 1
2.7%
319 1
2.7%
305 1
2.7%
292 1
2.7%
264 1
2.7%

33년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)96.6%
Missing8
Missing (%)21.6%
Infinite0
Infinite (%)0.0%
Mean253.2069
Minimum1
Maximum1527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:25.548962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.8
Q180
median188
Q3370
95-th percentile451.6
Maximum1527
Range1526
Interquartile range (IQR)290

Descriptive statistics

Standard deviation287.7482
Coefficient of variation (CV)1.1364153
Kurtosis13.846286
Mean253.2069
Median Absolute Deviation (MAD)168
Skewness3.1957108
Sum7343
Variance82799.027
MonotonicityNot monotonic
2023-12-13T06:29:25.702656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 2
 
5.4%
370 1
 
2.7%
1527 1
 
2.7%
199 1
 
2.7%
171 1
 
2.7%
177 1
 
2.7%
168 1
 
2.7%
164 1
 
2.7%
281 1
 
2.7%
289 1
 
2.7%
Other values (18) 18
48.6%
(Missing) 8
21.6%
ValueCountFrequency (%)
1 2
5.4%
3 1
2.7%
5 1
2.7%
11 1
2.7%
20 1
2.7%
49 1
2.7%
80 1
2.7%
91 1
2.7%
149 1
2.7%
164 1
2.7%
ValueCountFrequency (%)
1527 1
2.7%
468 1
2.7%
427 1
2.7%
420 1
2.7%
397 1
2.7%
381 1
2.7%
376 1
2.7%
370 1
2.7%
361 1
2.7%
316 1
2.7%

33년이상
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct29
Distinct (%)80.6%
Missing1
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean1487.6111
Minimum1
Maximum11186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T06:29:25.828910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19
median935.5
Q32514.25
95-th percentile3460.75
Maximum11186
Range11185
Interquartile range (IQR)2505.25

Descriptive statistics

Standard deviation2091.8395
Coefficient of variation (CV)1.4061736
Kurtosis12.647187
Mean1487.6111
Median Absolute Deviation (MAD)933.5
Skewness2.9737944
Sum53554
Variance4375792.6
MonotonicityNot monotonic
2023-12-13T06:29:25.946072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 6
 
16.2%
9 2
 
5.4%
1585 2
 
5.4%
11 1
 
2.7%
2871 1
 
2.7%
11186 1
 
2.7%
1584 1
 
2.7%
1655 1
 
2.7%
1536 1
 
2.7%
2345 1
 
2.7%
Other values (19) 19
51.4%
ValueCountFrequency (%)
1 6
16.2%
3 1
 
2.7%
6 1
 
2.7%
9 2
 
5.4%
11 1
 
2.7%
14 1
 
2.7%
23 1
 
2.7%
66 1
 
2.7%
119 1
 
2.7%
250 1
 
2.7%
ValueCountFrequency (%)
11186 1
2.7%
3556 1
2.7%
3429 1
2.7%
3381 1
2.7%
3204 1
2.7%
2873 1
2.7%
2871 1
2.7%
2814 1
2.7%
2545 1
2.7%
2504 1
2.7%

Interactions

2023-12-13T06:29:19.823585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:02.693300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.986739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.061341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.200036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.299805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.607902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.951293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.646053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.832923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.010846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.172139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.636986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.348697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.912317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:02.777340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.056074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.128242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.259194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.374887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.709855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.045995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.711416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.907304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.088007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.264974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.736002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.463494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.008763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:02.873596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.122902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.192329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.321873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.448228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.788632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.139242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.782195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.995488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.163197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.362886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.823601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.560097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.110132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:02.980927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.202155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.252964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.401498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.525374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.883339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.221118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.857838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.082779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.234655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.455363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.926976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.670146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.209007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.060160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.272171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.316116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.487146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.605571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.980493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.317974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.942975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.163940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.314900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.575876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.028907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.792152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.308008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.156906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.349188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.385792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.564921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.703304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.092093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.424621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.039210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.248694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.400910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.712939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.440558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.921021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.405322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.261201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.430783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.451292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.640016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.795037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.186787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.530762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.119965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.328222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.492738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.827392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.555416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.019479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.519446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.373451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.512953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.526499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.710407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.898060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.277488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.654155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.206254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.408005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.574966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.933756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.669303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.129805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.619033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.475196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.589381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.584183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.773564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.992204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.359871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.757698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.296453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.489818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.649996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.045393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.764182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.214826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.706598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.557698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.659154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.648556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.853562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.078221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.462827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.854196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.397106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.576876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.727374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.135355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.858148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.314462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.816203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.675205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.731896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.714859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.921587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.178124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.556076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:10.971725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.466448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.660097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.801675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.223702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:17.955034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.411201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:20.939595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.754696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.818318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:05.778604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.988739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.295175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.661290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.079374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.570812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.738327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:14.895456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.323200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.047395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.516959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:21.057343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.838484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.909331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.071219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.068269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.386362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.771324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.475192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.672035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.829497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.000633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.430476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.152214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.611195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:21.179829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:03.918887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:04.986117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:06.138343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:07.177740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:08.493492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:09.863493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:11.568593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:12.757986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:13.935636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:15.089592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:16.543172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:18.268332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:29:19.713978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:29:26.060674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
연령1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
21년미만1.0001.0000.7650.7720.8480.7170.8440.8880.8670.8050.8700.8570.8310.8550.854
22년미만1.0000.7651.0000.9940.9830.8490.9730.9560.9500.9580.9060.9370.9140.9280.964
23년미만1.0000.7720.9941.0000.9670.8970.9820.9820.9670.9680.9340.9500.9310.9570.978
24년미만1.0000.8480.9830.9671.0000.8680.9890.9930.9870.9620.9710.9820.9720.9830.981
25년미만1.0000.7170.8490.8970.8681.0000.8920.8690.8190.8260.7710.7960.7760.8120.855
26년미만1.0000.8440.9730.9820.9890.8921.0000.9890.9780.9630.9510.9650.9470.9690.996
27년미만1.0000.8880.9560.9820.9930.8690.9891.0000.9980.9750.9890.9940.9880.9960.979
28년미만1.0000.8670.9500.9670.9870.8190.9780.9981.0000.9750.9860.9950.9870.9910.966
29년미만1.0000.8050.9580.9680.9620.8260.9630.9750.9751.0000.9770.9640.9760.9690.970
30년미만1.0000.8700.9060.9340.9710.7710.9510.9890.9860.9771.0000.9870.9950.9920.953
31년미만1.0000.8570.9370.9500.9820.7960.9650.9940.9950.9640.9871.0000.9931.0000.968
32년미만1.0000.8310.9140.9310.9720.7760.9470.9880.9870.9760.9950.9931.0000.9960.950
33년미만1.0000.8550.9280.9570.9830.8120.9690.9960.9910.9690.9921.0000.9961.0000.970
33년이상1.0000.8540.9640.9780.9810.8550.9960.9790.9660.9700.9530.9680.9500.9701.000
2023-12-13T06:29:26.257538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
21년미만1.0000.9060.9200.9150.9270.9140.9510.9300.9300.9290.9060.8970.9160.955
22년미만0.9061.0000.9750.9790.9600.9730.9750.9540.9610.9510.9320.9200.9080.973
23년미만0.9200.9751.0000.9750.9510.9680.9760.9530.9490.9530.9300.9120.9260.971
24년미만0.9150.9790.9751.0000.9750.9770.9730.9610.9700.9600.9460.9210.9340.980
25년미만0.9270.9600.9510.9751.0000.9670.9640.9540.9660.9520.9370.9330.9410.967
26년미만0.9140.9730.9680.9770.9671.0000.9860.9780.9840.9700.9590.9380.9650.991
27년미만0.9510.9750.9760.9730.9640.9861.0000.9770.9670.9700.9550.9400.9490.988
28년미만0.9300.9540.9530.9610.9540.9780.9771.0000.9840.9800.9680.9540.9650.980
29년미만0.9300.9610.9490.9700.9660.9840.9670.9841.0000.9760.9730.9530.9760.982
30년미만0.9290.9510.9530.9600.9520.9700.9700.9800.9761.0000.9850.9650.9830.972
31년미만0.9060.9320.9300.9460.9370.9590.9550.9680.9730.9851.0000.9840.9870.966
32년미만0.8970.9200.9120.9210.9330.9380.9400.9540.9530.9650.9841.0000.9790.954
33년미만0.9160.9080.9260.9340.9410.9650.9490.9650.9760.9830.9870.9791.0000.968
33년이상0.9550.9730.9710.9800.9670.9910.9880.9800.9820.9720.9660.9540.9681.000

Missing values

2023-12-13T06:29:21.323372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:29:21.511356image/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.
2023-12-13T06:29:21.674662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
042세 미만1311082434105633311
143세 미만7<NA><NA>1<NA><NA>1<NA><NA><NA>1<NA><NA>1
244세 미만5<NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA>1<NA>
345세 미만14<NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA>1
446세 미만12<NA><NA><NA><NA>2<NA><NA>1<NA>1<NA><NA>1
547세 미만11<NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA>11
648세 미만201<NA>1111<NA>2<NA><NA><NA><NA>1
749세 미만16111<NA><NA><NA>121<NA><NA><NA>1
850세 미만1731<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>3
951세 미만2222<NA>3<NA>1<NA><NA>133<NA>6
연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
2769세 미만7151431551631582132072602582783243473973381
2870세 미만5321321431461321742231851782152582643162873
2971세 미만4081161091311351521561561851612262312892545
3072세 미만3891181301421441521461161831742282312812345
3173세 미만173658268958310887921081281211641536
3274세 미만1467890103929995100101991281491681655
3375세 미만117807278951261091161111321301561771585
3476세 미만119796498959982100132971401631711584
3577세 미만89659510487108911111221331491481991585
3677세 이상728532545614673707790919919110812281369152711186