Overview

Dataset statistics

Number of variables15
Number of observations60
Missing cells142
Missing cells (%)15.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory136.2 B

Variable types

Text1
Numeric14

Dataset

Description사립학교교직원연금공단 사학연금수급자 현황(유족연금수급자)과 관련된 데이터로 연령별(37세 미만 ~ 95세 이상), 재직기간별(21년 미만 ~ 33년 이상) 수급자 현황 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15045814/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 9 (15.0%) missing valuesMissing
23년미만 has 11 (18.3%) missing valuesMissing
24년미만 has 11 (18.3%) missing valuesMissing
25년미만 has 11 (18.3%) missing valuesMissing
26년미만 has 13 (21.7%) missing valuesMissing
27년미만 has 11 (18.3%) missing valuesMissing
28년미만 has 13 (21.7%) missing valuesMissing
29년미만 has 12 (20.0%) missing valuesMissing
30년미만 has 11 (18.3%) missing valuesMissing
31년미만 has 11 (18.3%) missing valuesMissing
32년미만 has 12 (20.0%) missing valuesMissing
33년미만 has 13 (21.7%) missing valuesMissing
33년이상 has 4 (6.7%) missing valuesMissing
연령 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:07:00.820140
Analysis finished2023-12-12 09:07:24.849249
Duration24.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연령
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T18:07:25.051264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters360
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

Unique60 ?
Unique (%)100.0%

Sample

1st row37세 미만
2nd row38세 미만
3rd row39세 미만
4th row40세 미만
5th row41세 미만
ValueCountFrequency (%)
미만 59
49.2%
95세 2
 
1.7%
80세 1
 
0.8%
68세 1
 
0.8%
81세 1
 
0.8%
69세 1
 
0.8%
70세 1
 
0.8%
71세 1
 
0.8%
72세 1
 
0.8%
73세 1
 
0.8%
Other values (51) 51
42.5%
2023-12-12T18:07:25.475342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
16.7%
60
16.7%
59
16.4%
59
16.4%
5 17
 
4.7%
7 16
 
4.4%
8 16
 
4.4%
4 16
 
4.4%
6 15
 
4.2%
9 13
 
3.6%
Other values (6) 29
8.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
50.0%
Decimal Number 120
33.3%
Space Separator 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 17
14.2%
7 16
13.3%
8 16
13.3%
4 16
13.3%
6 15
12.5%
9 13
10.8%
3 9
7.5%
1 6
 
5.0%
0 6
 
5.0%
2 6
 
5.0%
Other Letter
ValueCountFrequency (%)
60
33.3%
59
32.8%
59
32.8%
1
 
0.6%
1
 
0.6%
Space Separator
ValueCountFrequency (%)
60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
50.0%
Common 180
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
60
33.3%
5 17
 
9.4%
7 16
 
8.9%
8 16
 
8.9%
4 16
 
8.9%
6 15
 
8.3%
9 13
 
7.2%
3 9
 
5.0%
1 6
 
3.3%
0 6
 
3.3%
Hangul
ValueCountFrequency (%)
60
33.3%
59
32.8%
59
32.8%
1
 
0.6%
1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
50.0%
ASCII 180
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
60
33.3%
59
32.8%
59
32.8%
1
 
0.6%
1
 
0.6%
ASCII
ValueCountFrequency (%)
60
33.3%
5 17
 
9.4%
7 16
 
8.9%
8 16
 
8.9%
4 16
 
8.9%
6 15
 
8.3%
9 13
 
7.2%
3 9
 
5.0%
1 6
 
3.3%
0 6
 
3.3%

21년미만
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.68333
Minimum1
Maximum1021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:25.651527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q115.5
median42.5
Q3117.5
95-th percentile780.35
Maximum1021
Range1020
Interquartile range (IQR)102

Descriptive statistics

Standard deviation260.11852
Coefficient of variation (CV)1.649626
Kurtosis3.1570272
Mean157.68333
Median Absolute Deviation (MAD)33.5
Skewness2.0662835
Sum9461
Variance67661.644
MonotonicityNot monotonic
2023-12-12T18:07:25.822491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
7 3
 
5.0%
3 3
 
5.0%
11 2
 
3.3%
89 2
 
3.3%
35 2
 
3.3%
17 2
 
3.3%
37 2
 
3.3%
20 2
 
3.3%
86 2
 
3.3%
9 2
 
3.3%
Other values (38) 38
63.3%
ValueCountFrequency (%)
1 1
 
1.7%
3 3
5.0%
5 1
 
1.7%
7 3
5.0%
9 2
3.3%
10 1
 
1.7%
11 2
3.3%
12 1
 
1.7%
14 1
 
1.7%
16 1
 
1.7%
ValueCountFrequency (%)
1021 1
1.7%
909 1
1.7%
844 1
1.7%
777 1
1.7%
776 1
1.7%
715 1
1.7%
532 1
1.7%
490 1
1.7%
408 1
1.7%
400 1
1.7%

22년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)74.5%
Missing9
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean48.039216
Minimum1
Maximum169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:25.986739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.5
Q111
median37
Q374
95-th percentile133.5
Maximum169
Range168
Interquartile range (IQR)63

Descriptive statistics

Standard deviation45.083904
Coefficient of variation (CV)0.93848127
Kurtosis-0.10469685
Mean48.039216
Median Absolute Deviation (MAD)30
Skewness0.92325765
Sum2450
Variance2032.5584
MonotonicityNot monotonic
2023-12-12T18:07:26.143614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
3 3
 
5.0%
1 3
 
5.0%
11 3
 
5.0%
12 2
 
3.3%
45 2
 
3.3%
46 2
 
3.3%
53 2
 
3.3%
65 2
 
3.3%
4 2
 
3.3%
19 2
 
3.3%
Other values (28) 28
46.7%
(Missing) 9
 
15.0%
ValueCountFrequency (%)
1 3
5.0%
2 1
 
1.7%
3 3
5.0%
4 2
3.3%
6 1
 
1.7%
7 1
 
1.7%
9 1
 
1.7%
11 3
5.0%
12 2
3.3%
16 1
 
1.7%
ValueCountFrequency (%)
169 1
1.7%
143 1
1.7%
135 1
1.7%
132 1
1.7%
122 1
1.7%
118 1
1.7%
116 1
1.7%
106 1
1.7%
102 1
1.7%
94 1
1.7%

23년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)73.5%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean52.326531
Minimum1
Maximum172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:26.290766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median38
Q382
95-th percentile150.2
Maximum172
Range171
Interquartile range (IQR)74

Descriptive statistics

Standard deviation48.941456
Coefficient of variation (CV)0.93530864
Kurtosis-0.31895257
Mean52.326531
Median Absolute Deviation (MAD)30
Skewness0.88633828
Sum2564
Variance2395.2662
MonotonicityNot monotonic
2023-12-12T18:07:26.432725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
8 4
 
6.7%
20 3
 
5.0%
1 2
 
3.3%
5 2
 
3.3%
6 2
 
3.3%
9 2
 
3.3%
26 2
 
3.3%
2 2
 
3.3%
114 2
 
3.3%
155 2
 
3.3%
Other values (26) 26
43.3%
(Missing) 11
18.3%
ValueCountFrequency (%)
1 2
3.3%
2 2
3.3%
3 1
 
1.7%
5 2
3.3%
6 2
3.3%
8 4
6.7%
9 2
3.3%
20 3
5.0%
24 1
 
1.7%
26 2
3.3%
ValueCountFrequency (%)
172 1
1.7%
155 2
3.3%
143 1
1.7%
130 1
1.7%
123 1
1.7%
117 1
1.7%
114 2
3.3%
109 1
1.7%
95 1
1.7%
90 1
1.7%

24년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)81.6%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean57.22449
Minimum1
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:26.563512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.4
Q17
median47
Q3103
95-th percentile150.8
Maximum190
Range189
Interquartile range (IQR)96

Descriptive statistics

Standard deviation54.049077
Coefficient of variation (CV)0.94450955
Kurtosis-0.57816898
Mean57.22449
Median Absolute Deviation (MAD)41
Skewness0.77221046
Sum2804
Variance2921.3027
MonotonicityNot monotonic
2023-12-12T18:07:26.701819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2 4
 
6.7%
1 3
 
5.0%
33 2
 
3.3%
61 2
 
3.3%
6 2
 
3.3%
103 2
 
3.3%
53 1
 
1.7%
63 1
 
1.7%
48 1
 
1.7%
56 1
 
1.7%
Other values (30) 30
50.0%
(Missing) 11
 
18.3%
ValueCountFrequency (%)
1 3
5.0%
2 4
6.7%
3 1
 
1.7%
4 1
 
1.7%
5 1
 
1.7%
6 2
3.3%
7 1
 
1.7%
9 1
 
1.7%
11 1
 
1.7%
13 1
 
1.7%
ValueCountFrequency (%)
190 1
1.7%
163 1
1.7%
152 1
1.7%
149 1
1.7%
146 1
1.7%
142 1
1.7%
137 1
1.7%
131 1
1.7%
118 1
1.7%
117 1
1.7%

25년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)75.5%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean59.326531
Minimum1
Maximum175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:26.832867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median48
Q395
95-th percentile150
Maximum175
Range174
Interquartile range (IQR)87

Descriptive statistics

Standard deviation52.811137
Coefficient of variation (CV)0.8901774
Kurtosis-0.88790869
Mean59.326531
Median Absolute Deviation (MAD)40
Skewness0.63523102
Sum2907
Variance2789.0162
MonotonicityNot monotonic
2023-12-12T18:07:26.971906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
8 4
 
6.7%
1 4
 
6.7%
95 3
 
5.0%
7 2
 
3.3%
59 2
 
3.3%
69 2
 
3.3%
132 2
 
3.3%
33 1
 
1.7%
28 1
 
1.7%
87 1
 
1.7%
Other values (27) 27
45.0%
(Missing) 11
18.3%
ValueCountFrequency (%)
1 4
6.7%
3 1
 
1.7%
4 1
 
1.7%
5 1
 
1.7%
7 2
3.3%
8 4
6.7%
9 1
 
1.7%
13 1
 
1.7%
18 1
 
1.7%
19 1
 
1.7%
ValueCountFrequency (%)
175 1
1.7%
158 1
1.7%
152 1
1.7%
147 1
1.7%
144 1
1.7%
140 1
1.7%
135 1
1.7%
132 2
3.3%
127 1
1.7%
109 1
1.7%

26년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)76.6%
Missing13
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean71.340426
Minimum1
Maximum213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:27.144236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3
Q113.5
median58
Q3109
95-th percentile197.1
Maximum213
Range212
Interquartile range (IQR)95.5

Descriptive statistics

Standard deviation66.328654
Coefficient of variation (CV)0.9297485
Kurtosis-0.58565152
Mean71.340426
Median Absolute Deviation (MAD)48
Skewness0.8099286
Sum3353
Variance4399.4903
MonotonicityNot monotonic
2023-12-12T18:07:27.268067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
6 3
 
5.0%
20 3
 
5.0%
58 2
 
3.3%
99 2
 
3.3%
213 2
 
3.3%
69 2
 
3.3%
152 2
 
3.3%
27 2
 
3.3%
10 2
 
3.3%
78 1
 
1.7%
Other values (26) 26
43.3%
(Missing) 13
21.7%
ValueCountFrequency (%)
1 1
 
1.7%
2 1
 
1.7%
3 1
 
1.7%
4 1
 
1.7%
6 3
5.0%
7 1
 
1.7%
8 1
 
1.7%
10 2
3.3%
13 1
 
1.7%
14 1
 
1.7%
ValueCountFrequency (%)
213 2
3.3%
198 1
1.7%
195 1
1.7%
185 1
1.7%
174 1
1.7%
158 1
1.7%
155 1
1.7%
152 2
3.3%
126 1
1.7%
110 1
1.7%

27년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)81.6%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean72.387755
Minimum1
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:27.424515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110
median54
Q3108
95-th percentile216.6
Maximum250
Range249
Interquartile range (IQR)98

Descriptive statistics

Standard deviation70.849846
Coefficient of variation (CV)0.97875457
Kurtosis-0.13408168
Mean72.387755
Median Absolute Deviation (MAD)44
Skewness0.93257152
Sum3547
Variance5019.7007
MonotonicityNot monotonic
2023-12-12T18:07:27.562452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 4
 
6.7%
3 3
 
5.0%
10 2
 
3.3%
41 2
 
3.3%
82 2
 
3.3%
14 2
 
3.3%
2 1
 
1.7%
13 1
 
1.7%
5 1
 
1.7%
23 1
 
1.7%
Other values (30) 30
50.0%
(Missing) 11
 
18.3%
ValueCountFrequency (%)
1 4
6.7%
2 1
 
1.7%
3 3
5.0%
4 1
 
1.7%
5 1
 
1.7%
9 1
 
1.7%
10 2
3.3%
13 1
 
1.7%
14 2
3.3%
18 1
 
1.7%
ValueCountFrequency (%)
250 1
1.7%
224 1
1.7%
223 1
1.7%
207 1
1.7%
189 1
1.7%
178 1
1.7%
172 1
1.7%
160 1
1.7%
156 1
1.7%
146 1
1.7%

28년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)83.0%
Missing13
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean83.085106
Minimum1
Maximum304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:27.700022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q118.5
median76
Q3113.5
95-th percentile221.2
Maximum304
Range303
Interquartile range (IQR)95

Descriptive statistics

Standard deviation75.374955
Coefficient of variation (CV)0.90720177
Kurtosis0.60910847
Mean83.085106
Median Absolute Deviation (MAD)53
Skewness1.0598264
Sum3905
Variance5681.3839
MonotonicityNot monotonic
2023-12-12T18:07:27.847028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 2
 
3.3%
7 2
 
3.3%
23 2
 
3.3%
85 2
 
3.3%
100 2
 
3.3%
10 2
 
3.3%
116 2
 
3.3%
9 2
 
3.3%
93 1
 
1.7%
13 1
 
1.7%
Other values (29) 29
48.3%
(Missing) 13
21.7%
ValueCountFrequency (%)
1 2
3.3%
4 1
1.7%
7 2
3.3%
9 2
3.3%
10 2
3.3%
12 1
1.7%
13 1
1.7%
14 1
1.7%
23 2
3.3%
25 1
1.7%
ValueCountFrequency (%)
304 1
1.7%
260 1
1.7%
226 1
1.7%
210 1
1.7%
190 1
1.7%
186 1
1.7%
185 1
1.7%
181 1
1.7%
156 1
1.7%
139 1
1.7%

29년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)87.5%
Missing12
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean89.25
Minimum1
Maximum323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:28.006774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q115.5
median73.5
Q3124.5
95-th percentile250.3
Maximum323
Range322
Interquartile range (IQR)109

Descriptive statistics

Standard deviation83.486398
Coefficient of variation (CV)0.93542183
Kurtosis0.23526512
Mean89.25
Median Absolute Deviation (MAD)58
Skewness0.993003
Sum4284
Variance6969.9787
MonotonicityNot monotonic
2023-12-12T18:07:28.173170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
36 2
 
3.3%
101 2
 
3.3%
200 2
 
3.3%
5 2
 
3.3%
2 2
 
3.3%
12 2
 
3.3%
21 1
 
1.7%
40 1
 
1.7%
88 1
 
1.7%
81 1
 
1.7%
Other values (32) 32
53.3%
(Missing) 12
 
20.0%
ValueCountFrequency (%)
1 1
1.7%
2 2
3.3%
4 1
1.7%
5 2
3.3%
7 1
1.7%
8 1
1.7%
11 1
1.7%
12 2
3.3%
14 1
1.7%
16 1
1.7%
ValueCountFrequency (%)
323 1
1.7%
277 1
1.7%
258 1
1.7%
236 1
1.7%
202 1
1.7%
200 2
3.3%
185 1
1.7%
183 1
1.7%
178 1
1.7%
170 1
1.7%

30년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)89.8%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean96.918367
Minimum1
Maximum339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:28.670187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q115
median87
Q3133
95-th percentile263.6
Maximum339
Range338
Interquartile range (IQR)118

Descriptive statistics

Standard deviation88.9112
Coefficient of variation (CV)0.91738236
Kurtosis0.18828367
Mean96.918367
Median Absolute Deviation (MAD)65
Skewness0.94377685
Sum4749
Variance7905.2015
MonotonicityNot monotonic
2023-12-12T18:07:28.848768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 3
 
5.0%
6 3
 
5.0%
12 2
 
3.3%
4 1
 
1.7%
78 1
 
1.7%
133 1
 
1.7%
145 1
 
1.7%
103 1
 
1.7%
87 1
 
1.7%
98 1
 
1.7%
Other values (34) 34
56.7%
(Missing) 11
 
18.3%
ValueCountFrequency (%)
1 3
5.0%
4 1
 
1.7%
5 1
 
1.7%
6 3
5.0%
8 1
 
1.7%
10 1
 
1.7%
12 2
3.3%
15 1
 
1.7%
22 1
 
1.7%
30 1
 
1.7%
ValueCountFrequency (%)
339 1
1.7%
305 1
1.7%
278 1
1.7%
242 1
1.7%
227 1
1.7%
226 1
1.7%
225 1
1.7%
215 1
1.7%
185 1
1.7%
174 1
1.7%

31년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)89.8%
Missing11
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean119.59184
Minimum1
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:29.008260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q126
median113
Q3149
95-th percentile305.4
Maximum440
Range439
Interquartile range (IQR)123

Descriptive statistics

Standard deviation106.73993
Coefficient of variation (CV)0.89253527
Kurtosis0.35520746
Mean119.59184
Median Absolute Deviation (MAD)78
Skewness0.95279543
Sum5860
Variance11393.413
MonotonicityNot monotonic
2023-12-12T18:07:29.183475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
149 2
 
3.3%
1 2
 
3.3%
258 2
 
3.3%
3 2
 
3.3%
128 2
 
3.3%
53 1
 
1.7%
115 1
 
1.7%
117 1
 
1.7%
113 1
 
1.7%
118 1
 
1.7%
Other values (34) 34
56.7%
(Missing) 11
 
18.3%
ValueCountFrequency (%)
1 2
3.3%
3 2
3.3%
5 1
1.7%
7 1
1.7%
9 1
1.7%
11 1
1.7%
12 1
1.7%
15 1
1.7%
17 1
1.7%
20 1
1.7%
ValueCountFrequency (%)
440 1
1.7%
324 1
1.7%
307 1
1.7%
303 1
1.7%
286 1
1.7%
284 1
1.7%
258 2
3.3%
245 1
1.7%
228 1
1.7%
226 1
1.7%

32년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)87.5%
Missing12
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean132.875
Minimum1
Maximum424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:29.329243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q133.5
median112.5
Q3186.5
95-th percentile337.2
Maximum424
Range423
Interquartile range (IQR)153

Descriptive statistics

Standard deviation114.33948
Coefficient of variation (CV)0.86050406
Kurtosis-0.33685394
Mean132.875
Median Absolute Deviation (MAD)78
Skewness0.79210536
Sum6378
Variance13073.516
MonotonicityNot monotonic
2023-12-12T18:07:29.466642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
15 4
 
6.7%
90 2
 
3.3%
3 2
 
3.3%
231 2
 
3.3%
102 1
 
1.7%
148 1
 
1.7%
131 1
 
1.7%
110 1
 
1.7%
134 1
 
1.7%
112 1
 
1.7%
Other values (32) 32
53.3%
(Missing) 12
 
20.0%
ValueCountFrequency (%)
1 1
 
1.7%
2 1
 
1.7%
3 2
3.3%
12 1
 
1.7%
14 1
 
1.7%
15 4
6.7%
27 1
 
1.7%
29 1
 
1.7%
35 1
 
1.7%
41 1
 
1.7%
ValueCountFrequency (%)
424 1
1.7%
347 1
1.7%
340 1
1.7%
332 1
1.7%
326 1
1.7%
319 1
1.7%
305 1
1.7%
292 1
1.7%
264 1
1.7%
231 2
3.3%

33년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)95.7%
Missing13
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean156.23404
Minimum1
Maximum468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:29.733835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q132.5
median135
Q3226
95-th percentile413.1
Maximum468
Range467
Interquartile range (IQR)193.5

Descriptive statistics

Standard deviation138.75349
Coefficient of variation (CV)0.88811304
Kurtosis-0.59587512
Mean156.23404
Median Absolute Deviation (MAD)110
Skewness0.75249525
Sum7343
Variance19252.531
MonotonicityNot monotonic
2023-12-12T18:07:29.932264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 2
 
3.3%
177 2
 
3.3%
8 1
 
1.7%
13 1
 
1.7%
171 1
 
1.7%
199 1
 
1.7%
186 1
 
1.7%
133 1
 
1.7%
140 1
 
1.7%
135 1
 
1.7%
Other values (35) 35
58.3%
(Missing) 13
 
21.7%
ValueCountFrequency (%)
1 2
3.3%
3 1
1.7%
5 1
1.7%
8 1
1.7%
11 1
1.7%
13 1
1.7%
18 1
1.7%
20 1
1.7%
23 1
1.7%
24 1
1.7%
ValueCountFrequency (%)
468 1
1.7%
427 1
1.7%
420 1
1.7%
397 1
1.7%
381 1
1.7%
376 1
1.7%
370 1
1.7%
361 1
1.7%
316 1
1.7%
289 1
1.7%

33년이상
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct46
Distinct (%)82.1%
Missing4
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean956.32143
Minimum1
Maximum3556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T18:07:30.127726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q120.75
median515
Q31584.25
95-th percentile3248.25
Maximum3556
Range3555
Interquartile range (IQR)1563.5

Descriptive statistics

Standard deviation1092.9759
Coefficient of variation (CV)1.1428959
Kurtosis-0.096209507
Mean956.32143
Median Absolute Deviation (MAD)513
Skewness1.0620696
Sum53554
Variance1194596.2
MonotonicityNot monotonic
2023-12-12T18:07:30.289261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 8
 
13.3%
9 3
 
5.0%
1585 2
 
3.3%
14 1
 
1.7%
1303 1
 
1.7%
1222 1
 
1.7%
1055 1
 
1.7%
934 1
 
1.7%
960 1
 
1.7%
852 1
 
1.7%
Other values (36) 36
60.0%
(Missing) 4
 
6.7%
ValueCountFrequency (%)
1 8
13.3%
3 1
 
1.7%
6 1
 
1.7%
9 3
 
5.0%
14 1
 
1.7%
23 1
 
1.7%
66 1
 
1.7%
105 1
 
1.7%
107 1
 
1.7%
119 1
 
1.7%
ValueCountFrequency (%)
3556 1
1.7%
3429 1
1.7%
3381 1
1.7%
3204 1
1.7%
2873 1
1.7%
2871 1
1.7%
2814 1
1.7%
2545 1
1.7%
2504 1
1.7%
2345 1
1.7%

Interactions

2023-12-12T18:07:22.105058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:01.426149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.100513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.694502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.147482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.458868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.975620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.534286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.307883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.738307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.917166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.555509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.933283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.348001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:22.236606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:01.531857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.217239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.802565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.230773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.792781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.077544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.661806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.435122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.846429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.047614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.660501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.028929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.444880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:22.393190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:01.664984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.345593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.911080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.328454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.907294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.209389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.784579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.519855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.983681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.174095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.766522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.133456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.600771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:22.531133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:01.823512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.462522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.021672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.425394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.007987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.331525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.924676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.633903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.118614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.313714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.865629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.230479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.712259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:22.992230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:01.957261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.564464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.113973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.543862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.112983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.445256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.164165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.755872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.286596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.430343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.972899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.332612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.877846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.098384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.100209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.686982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.229130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.641205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.203570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.556361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.286788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.862906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.436741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.539415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.075145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.449784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.143347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.210719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.193822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.803473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.332589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.751176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.295029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.659627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.385036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.942739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.562881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.649769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.154536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.532719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.288789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.323042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.294986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:03.925271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.432743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.855533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.385596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.756807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.494552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.037841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.677467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.763024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.261947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.633811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.383534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.452818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.406546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.038698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.540778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.941208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.468093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.878306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.632009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.132263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:14.791057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.862599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.367806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.752373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.468595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.576092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.523071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.149851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.643981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.034330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.545673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:09.999562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.758338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.245139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.268082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:16.957196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.484669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.865023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.573112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.681205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.649381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.245378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.761780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.122466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.628532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.117156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.887111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.355587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.422630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.073598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.583729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:19.963947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.668937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.770048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.770006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.367989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.877257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.206874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.707703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.215166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:11.985466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.444758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.532930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.189837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.669232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.042608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.756812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.872924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.868973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.463007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:05.967578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.293679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.791799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.316087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.071626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.530901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.667983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.312080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.758238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.157564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.854899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:23.981139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:02.982464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:04.576012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:06.055181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:07.370790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:08.890111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:10.417605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:12.176572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:13.630492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:15.797981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:17.421777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:18.836652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:20.256792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:07:21.951990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:07:30.423575image/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
21년미만1.0001.0000.8850.8190.8430.7770.8930.8340.8770.8950.8590.9500.8660.7700.836
22년미만1.0000.8851.0000.9160.9560.9240.8030.9200.9650.9420.9310.8340.9340.8710.910
23년미만1.0000.8190.9161.0000.9240.9500.8540.9680.9240.9410.9260.7320.9030.9090.965
24년미만1.0000.8430.9560.9241.0000.9590.8630.9580.9580.9420.9440.8740.9350.8860.940
25년미만1.0000.7770.9240.9500.9591.0000.8460.9380.9560.9020.9070.8140.9010.9210.969
26년미만1.0000.8930.8030.8540.8630.8461.0000.8530.7830.8160.7790.8500.7380.7440.927
27년미만1.0000.8340.9200.9680.9580.9380.8531.0000.9660.9520.9520.8370.9480.9350.975
28년미만1.0000.8770.9650.9240.9580.9560.7830.9661.0000.9820.9600.9000.9580.9260.950
29년미만1.0000.8950.9420.9410.9420.9020.8160.9520.9821.0000.9570.9020.9490.9380.924
30년미만1.0000.8590.9310.9260.9440.9070.7790.9520.9600.9571.0000.8420.9530.9440.936
31년미만1.0000.9500.8340.7320.8740.8140.8500.8370.9000.9020.8421.0000.9070.8740.802
32년미만1.0000.8660.9340.9030.9350.9010.7380.9480.9580.9490.9530.9071.0000.9570.906
33년미만1.0000.7700.8710.9090.8860.9210.7440.9350.9260.9380.9440.8740.9571.0000.919
33년이상1.0000.8360.9100.9650.9400.9690.9270.9750.9500.9240.9360.8020.9060.9191.000
2023-12-12T18:07:30.594726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
21년미만1.0000.9040.8860.8840.8930.8770.8940.8940.9060.8930.9120.8970.9030.889
22년미만0.9041.0000.9740.9720.9660.9730.9700.9570.9690.9630.9630.9460.9480.970
23년미만0.8860.9741.0000.9790.9810.9810.9780.9710.9680.9570.9370.9330.9490.981
24년미만0.8840.9720.9791.0000.9830.9830.9790.9770.9740.9600.9460.9330.9520.984
25년미만0.8930.9660.9810.9831.0000.9800.9800.9780.9770.9640.9480.9420.9570.983
26년미만0.8770.9730.9810.9830.9801.0000.9800.9760.9800.9600.9530.9360.9620.988
27년미만0.8940.9700.9780.9790.9800.9801.0000.9840.9780.9730.9490.9450.9600.983
28년미만0.8940.9570.9710.9770.9780.9760.9841.0000.9830.9710.9480.9470.9650.980
29년미만0.9060.9690.9680.9740.9770.9800.9780.9831.0000.9780.9730.9620.9820.977
30년미만0.8930.9630.9570.9600.9640.9600.9730.9710.9781.0000.9760.9660.9840.962
31년미만0.9120.9630.9370.9460.9480.9530.9490.9480.9730.9761.0000.9770.9790.950
32년미만0.8970.9460.9330.9330.9420.9360.9450.9470.9620.9660.9771.0000.9840.937
33년미만0.9030.9480.9490.9520.9570.9620.9600.9650.9820.9840.9790.9841.0000.956
33년이상0.8890.9700.9810.9840.9830.9880.9830.9800.9770.9620.9500.9370.9561.000

Missing values

2023-12-12T18:07:24.160854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:07:24.416776image/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.
2023-12-12T18:07:24.654390image/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
037세 미만11298243410563339
138세 미만3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1
239세 미만1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
340세 미만3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
441세 미만31<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1
542세 미만9<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
643세 미만7<NA><NA>1<NA><NA>1<NA><NA><NA>1<NA><NA>1
744세 미만5<NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA>1<NA>
845세 미만14<NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA>1
946세 미만12<NA><NA><NA><NA>2<NA><NA>1<NA>1<NA><NA>1
연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
5087세 미만37222633361841543658616656537
5188세 미만29162028282741364632515651493
5289세 미만35192627333023233136424240444
5390세 미만23122413192014232730353542393
5491세 미만17496131010141622262924244
5592세 미만2068118131325121271525217
5693세 미만91185881010118111518179
5794세 미만7769772746121513105
5895세 미만74<NA>256578105128107
5995세 이상1012969149131415202723151