Overview

Dataset statistics

Number of variables15
Number of observations47
Missing cells113
Missing cells (%)16.0%
Duplicate rows1
Duplicate rows (%)2.1%
Total size in memory6.3 KiB
Average record size in memory136.8 B

Variable types

Text1
Numeric14

Dataset

Description사립학교교직원연금공단 사학연금수급자 현황 (재직기간별, 연령별 퇴직연금수급자)과 관련된 데이터로 연령별(50세 미만 ~ 90세 이상), 재직기간별(21년 미만 ~ 33년 이상) 수급자 현황 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15045816/fileData.do

Alerts

Dataset has 1 (2.1%) duplicate rowsDuplicates
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
연령 has 5 (10.6%) missing valuesMissing
21년미만 has 5 (10.6%) missing valuesMissing
22년미만 has 8 (17.0%) missing valuesMissing
23년미만 has 7 (14.9%) missing valuesMissing
24년미만 has 10 (21.3%) missing valuesMissing
25년미만 has 10 (21.3%) missing valuesMissing
26년미만 has 8 (17.0%) missing valuesMissing
27년미만 has 9 (19.1%) missing valuesMissing
28년미만 has 8 (17.0%) missing valuesMissing
29년미만 has 8 (17.0%) missing valuesMissing
30년미만 has 7 (14.9%) missing valuesMissing
31년미만 has 6 (12.8%) missing valuesMissing
32년미만 has 6 (12.8%) missing valuesMissing
33년미만 has 8 (17.0%) missing valuesMissing
33년이상 has 8 (17.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 06:16:42.753582
Analysis finished2023-12-12 06:17:05.971592
Duration23.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연령
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing5
Missing (%)10.6%
Memory size508.0 B
2023-12-12T15:17:06.111309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters252
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

Unique42 ?
Unique (%)100.0%

Sample

1st row50세 미만
2nd row51세 미만
3rd row52세 미만
4th row53세 미만
5th row54세 미만
ValueCountFrequency (%)
미만 41
48.8%
90세 2
 
2.4%
81세 1
 
1.2%
83세 1
 
1.2%
74세 1
 
1.2%
75세 1
 
1.2%
76세 1
 
1.2%
77세 1
 
1.2%
78세 1
 
1.2%
79세 1
 
1.2%
Other values (33) 33
39.3%
2023-12-12T15:17:06.512527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
16.7%
42
16.7%
41
16.3%
41
16.3%
6 14
 
5.6%
5 14
 
5.6%
7 14
 
5.6%
8 14
 
5.6%
9 6
 
2.4%
0 6
 
2.4%
Other values (6) 18
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
50.0%
Decimal Number 84
33.3%
Space Separator 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 14
16.7%
5 14
16.7%
7 14
16.7%
8 14
16.7%
9 6
7.1%
0 6
7.1%
1 4
 
4.8%
2 4
 
4.8%
3 4
 
4.8%
4 4
 
4.8%
Other Letter
ValueCountFrequency (%)
42
33.3%
41
32.5%
41
32.5%
1
 
0.8%
1
 
0.8%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
50.0%
Common 126
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
42
33.3%
6 14
 
11.1%
5 14
 
11.1%
7 14
 
11.1%
8 14
 
11.1%
9 6
 
4.8%
0 6
 
4.8%
1 4
 
3.2%
2 4
 
3.2%
3 4
 
3.2%
Hangul
ValueCountFrequency (%)
42
33.3%
41
32.5%
41
32.5%
1
 
0.8%
1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
50.0%
ASCII 126
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
42
33.3%
41
32.5%
41
32.5%
1
 
0.8%
1
 
0.8%
ASCII
ValueCountFrequency (%)
42
33.3%
6 14
 
11.1%
5 14
 
11.1%
7 14
 
11.1%
8 14
 
11.1%
9 6
 
4.8%
0 6
 
4.8%
1 4
 
3.2%
2 4
 
3.2%
3 4
 
3.2%

21년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)88.1%
Missing5
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean143.71429
Minimum4
Maximum678
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:06.660141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10.25
Q123.25
median54.5
Q3203.75
95-th percentile520.35
Maximum678
Range674
Interquartile range (IQR)180.5

Descriptive statistics

Standard deviation185.88054
Coefficient of variation (CV)1.2934034
Kurtosis0.95239419
Mean143.71429
Median Absolute Deviation (MAD)38
Skewness1.4879205
Sum6036
Variance34551.575
MonotonicityNot monotonic
2023-12-12T15:17:06.831551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
15 3
 
6.4%
26 2
 
4.3%
29 2
 
4.3%
41 2
 
4.3%
72 1
 
2.1%
125 1
 
2.1%
110 1
 
2.1%
86 1
 
2.1%
95 1
 
2.1%
80 1
 
2.1%
Other values (27) 27
57.4%
(Missing) 5
 
10.6%
ValueCountFrequency (%)
4 1
 
2.1%
9 1
 
2.1%
10 1
 
2.1%
15 3
6.4%
16 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
20 1
 
2.1%
23 1
 
2.1%
24 1
 
2.1%
ValueCountFrequency (%)
678 1
2.1%
555 1
2.1%
522 1
2.1%
489 1
2.1%
462 1
2.1%
439 1
2.1%
438 1
2.1%
318 1
2.1%
315 1
2.1%
255 1
2.1%

22년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)87.2%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean48.871795
Minimum2
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:07.011290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q118
median39
Q372
95-th percentile117.2
Maximum155
Range153
Interquartile range (IQR)54

Descriptive statistics

Standard deviation39.659856
Coefficient of variation (CV)0.81150807
Kurtosis0.017575507
Mean48.871795
Median Absolute Deviation (MAD)25
Skewness0.9004603
Sum1906
Variance1572.9042
MonotonicityNot monotonic
2023-12-12T15:17:07.547603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
19 2
 
4.3%
36 2
 
4.3%
71 2
 
4.3%
4 2
 
4.3%
18 2
 
4.3%
9 1
 
2.1%
14 1
 
2.1%
12 1
 
2.1%
23 1
 
2.1%
7 1
 
2.1%
Other values (24) 24
51.1%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
2 1
2.1%
4 2
4.3%
7 1
2.1%
8 1
2.1%
9 1
2.1%
12 1
2.1%
14 1
2.1%
15 1
2.1%
18 2
4.3%
19 2
4.3%
ValueCountFrequency (%)
155 1
2.1%
128 1
2.1%
116 1
2.1%
115 1
2.1%
105 1
2.1%
101 1
2.1%
100 1
2.1%
78 1
2.1%
75 1
2.1%
73 1
2.1%

23년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)85.0%
Missing7
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean50.575
Minimum1
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:07.719195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q118
median41
Q379
95-th percentile139.3
Maximum157
Range156
Interquartile range (IQR)61

Descriptive statistics

Standard deviation44.403677
Coefficient of variation (CV)0.87797681
Kurtosis-0.242736
Mean50.575
Median Absolute Deviation (MAD)28.5
Skewness0.87474237
Sum2023
Variance1971.6865
MonotonicityNot monotonic
2023-12-12T15:17:07.929457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
18 4
 
8.5%
1 2
 
4.3%
96 2
 
4.3%
2 2
 
4.3%
22 1
 
2.1%
11 1
 
2.1%
19 1
 
2.1%
14 1
 
2.1%
15 1
 
2.1%
20 1
 
2.1%
Other values (24) 24
51.1%
(Missing) 7
 
14.9%
ValueCountFrequency (%)
1 2
4.3%
2 2
4.3%
3 1
 
2.1%
5 1
 
2.1%
11 1
 
2.1%
14 1
 
2.1%
15 1
 
2.1%
18 4
8.5%
19 1
 
2.1%
20 1
 
2.1%
ValueCountFrequency (%)
157 1
2.1%
145 1
2.1%
139 1
2.1%
130 1
2.1%
112 1
2.1%
99 1
2.1%
96 2
4.3%
92 1
2.1%
91 1
2.1%
75 1
2.1%

24년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)91.9%
Missing10
Missing (%)21.3%
Infinite0
Infinite (%)0.0%
Mean60.216216
Minimum2
Maximum173
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:08.138668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.4
Q121
median51
Q387
95-th percentile136.8
Maximum173
Range171
Interquartile range (IQR)66

Descriptive statistics

Standard deviation46.373565
Coefficient of variation (CV)0.77011755
Kurtosis-0.52626662
Mean60.216216
Median Absolute Deviation (MAD)34
Skewness0.69246709
Sum2228
Variance2150.5075
MonotonicityNot monotonic
2023-12-12T15:17:08.281254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
126 2
 
4.3%
14 2
 
4.3%
51 2
 
4.3%
43 1
 
2.1%
85 1
 
2.1%
39 1
 
2.1%
45 1
 
2.1%
52 1
 
2.1%
38 1
 
2.1%
67 1
 
2.1%
Other values (24) 24
51.1%
(Missing) 10
21.3%
ValueCountFrequency (%)
2 1
2.1%
3 1
2.1%
6 1
2.1%
9 1
2.1%
11 1
2.1%
14 2
4.3%
17 1
2.1%
19 1
2.1%
21 1
2.1%
22 1
2.1%
ValueCountFrequency (%)
173 1
2.1%
144 1
2.1%
135 1
2.1%
126 2
4.3%
122 1
2.1%
120 1
2.1%
117 1
2.1%
90 1
2.1%
87 1
2.1%
85 1
2.1%

25년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)94.6%
Missing10
Missing (%)21.3%
Infinite0
Infinite (%)0.0%
Mean62.675676
Minimum1
Maximum156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:08.448158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q125
median51
Q3103
95-th percentile134.4
Maximum156
Range155
Interquartile range (IQR)78

Descriptive statistics

Standard deviation45.633841
Coefficient of variation (CV)0.72809492
Kurtosis-1.0267051
Mean62.675676
Median Absolute Deviation (MAD)32
Skewness0.46588967
Sum2319
Variance2082.4474
MonotonicityNot monotonic
2023-12-12T15:17:08.603543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
19 2
 
4.3%
29 2
 
4.3%
48 1
 
2.1%
76 1
 
2.1%
79 1
 
2.1%
54 1
 
2.1%
50 1
 
2.1%
51 1
 
2.1%
46 1
 
2.1%
35 1
 
2.1%
Other values (25) 25
53.2%
(Missing) 10
 
21.3%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
5 1
2.1%
6 1
2.1%
13 1
2.1%
19 2
4.3%
22 1
2.1%
23 1
2.1%
25 1
2.1%
27 1
2.1%
ValueCountFrequency (%)
156 1
2.1%
144 1
2.1%
132 1
2.1%
130 1
2.1%
128 1
2.1%
124 1
2.1%
121 1
2.1%
111 1
2.1%
108 1
2.1%
103 1
2.1%

26년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)94.9%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean69.923077
Minimum1
Maximum198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:08.773747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q118.5
median48
Q3117
95-th percentile185.9
Maximum198
Range197
Interquartile range (IQR)98.5

Descriptive statistics

Standard deviation61.575535
Coefficient of variation (CV)0.88061822
Kurtosis-0.68594507
Mean69.923077
Median Absolute Deviation (MAD)35
Skewness0.76602809
Sum2727
Variance3791.5466
MonotonicityNot monotonic
2023-12-12T15:17:08.907247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 3
 
6.4%
41 1
 
2.1%
81 1
 
2.1%
82 1
 
2.1%
59 1
 
2.1%
47 1
 
2.1%
54 1
 
2.1%
62 1
 
2.1%
48 1
 
2.1%
40 1
 
2.1%
Other values (27) 27
57.4%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
1 3
6.4%
2 1
 
2.1%
6 1
 
2.1%
8 1
 
2.1%
10 1
 
2.1%
11 1
 
2.1%
15 1
 
2.1%
17 1
 
2.1%
20 1
 
2.1%
29 1
 
2.1%
ValueCountFrequency (%)
198 1
2.1%
194 1
2.1%
185 1
2.1%
172 1
2.1%
163 1
2.1%
159 1
2.1%
147 1
2.1%
142 1
2.1%
133 1
2.1%
124 1
2.1%

27년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)94.7%
Missing9
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean76.684211
Minimum1
Maximum234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:09.065068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q130.25
median60
Q3119.75
95-th percentile205.15
Maximum234
Range233
Interquartile range (IQR)89.5

Descriptive statistics

Standard deviation64.886223
Coefficient of variation (CV)0.84614841
Kurtosis-0.14386426
Mean76.684211
Median Absolute Deviation (MAD)34
Skewness0.90523234
Sum2914
Variance4210.2219
MonotonicityNot monotonic
2023-12-12T15:17:09.238309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
34 2
 
4.3%
1 2
 
4.3%
6 1
 
2.1%
69 1
 
2.1%
74 1
 
2.1%
68 1
 
2.1%
50 1
 
2.1%
54 1
 
2.1%
56 1
 
2.1%
73 1
 
2.1%
Other values (26) 26
55.3%
(Missing) 9
 
19.1%
ValueCountFrequency (%)
1 2
4.3%
4 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
18 1
2.1%
19 1
2.1%
27 1
2.1%
30 1
2.1%
31 1
2.1%
ValueCountFrequency (%)
234 1
2.1%
206 1
2.1%
205 1
2.1%
196 1
2.1%
161 1
2.1%
157 1
2.1%
151 1
2.1%
142 1
2.1%
131 1
2.1%
128 1
2.1%

28년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct34
Distinct (%)87.2%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean83.051282
Minimum1
Maximum291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:09.383677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.8
Q132
median65
Q3107
95-th percentile218.3
Maximum291
Range290
Interquartile range (IQR)75

Descriptive statistics

Standard deviation70.282119
Coefficient of variation (CV)0.84624966
Kurtosis0.97079742
Mean83.051282
Median Absolute Deviation (MAD)38
Skewness1.1680432
Sum3239
Variance4939.5762
MonotonicityNot monotonic
2023-12-12T15:17:09.537296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
27 2
 
4.3%
75 2
 
4.3%
164 2
 
4.3%
56 2
 
4.3%
107 2
 
4.3%
37 1
 
2.1%
39 1
 
2.1%
19 1
 
2.1%
95 1
 
2.1%
46 1
 
2.1%
Other values (24) 24
51.1%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
1 1
2.1%
4 1
2.1%
6 1
2.1%
7 1
2.1%
9 1
2.1%
16 1
2.1%
18 1
2.1%
19 1
2.1%
27 2
4.3%
37 1
2.1%
ValueCountFrequency (%)
291 1
2.1%
239 1
2.1%
216 1
2.1%
180 1
2.1%
172 1
2.1%
166 1
2.1%
164 2
4.3%
139 1
2.1%
107 2
4.3%
95 1
2.1%

29년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)92.3%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean94.769231
Minimum2
Maximum314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:09.701246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile7.8
Q135.5
median73
Q3145
95-th percentile245.9
Maximum314
Range312
Interquartile range (IQR)109.5

Descriptive statistics

Standard deviation78.556202
Coefficient of variation (CV)0.82892097
Kurtosis0.44663224
Mean94.769231
Median Absolute Deviation (MAD)45
Skewness1.0591886
Sum3696
Variance6171.0769
MonotonicityNot monotonic
2023-12-12T15:17:09.846584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
26 2
 
4.3%
52 2
 
4.3%
170 2
 
4.3%
13 1
 
2.1%
96 1
 
2.1%
39 1
 
2.1%
16 1
 
2.1%
21 1
 
2.1%
35 1
 
2.1%
36 1
 
2.1%
Other values (26) 26
55.3%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
2 1
2.1%
6 1
2.1%
8 1
2.1%
13 1
2.1%
16 1
2.1%
21 1
2.1%
26 2
4.3%
28 1
2.1%
35 1
2.1%
36 1
2.1%
ValueCountFrequency (%)
314 1
2.1%
263 1
2.1%
244 1
2.1%
219 1
2.1%
191 1
2.1%
188 1
2.1%
181 1
2.1%
170 2
4.3%
162 1
2.1%
128 1
2.1%

30년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)97.5%
Missing7
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean102.6
Minimum2
Maximum322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:09.974769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.95
Q140.5
median83.5
Q3147.5
95-th percentile257.65
Maximum322
Range320
Interquartile range (IQR)107

Descriptive statistics

Standard deviation82.291789
Coefficient of variation (CV)0.80206422
Kurtosis0.29783948
Mean102.6
Median Absolute Deviation (MAD)49.5
Skewness0.98407758
Sum4104
Variance6771.9385
MonotonicityNot monotonic
2023-12-12T15:17:10.088552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
20 2
 
4.3%
78 1
 
2.1%
81 1
 
2.1%
104 1
 
2.1%
77 1
 
2.1%
110 1
 
2.1%
122 1
 
2.1%
86 1
 
2.1%
67 1
 
2.1%
95 1
 
2.1%
Other values (29) 29
61.7%
(Missing) 7
 
14.9%
ValueCountFrequency (%)
2 1
2.1%
4 1
2.1%
5 1
2.1%
9 1
2.1%
20 2
4.3%
21 1
2.1%
26 1
2.1%
32 1
2.1%
36 1
2.1%
42 1
2.1%
ValueCountFrequency (%)
322 1
2.1%
289 1
2.1%
256 1
2.1%
226 1
2.1%
214 1
2.1%
210 1
2.1%
209 1
2.1%
191 1
2.1%
168 1
2.1%
155 1
2.1%

31년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct41
Distinct (%)100.0%
Missing6
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean126.97561
Minimum3
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:10.233181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile14
Q144
median106
Q3205
95-th percentile291
Maximum429
Range426
Interquartile range (IQR)161

Descriptive statistics

Standard deviation100.50808
Coefficient of variation (CV)0.79155423
Kurtosis0.57592055
Mean126.97561
Median Absolute Deviation (MAD)64
Skewness1.0137222
Sum5206
Variance10101.874
MonotonicityNot monotonic
2023-12-12T15:17:10.371384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
90 1
 
2.1%
112 1
 
2.1%
114 1
 
2.1%
117 1
 
2.1%
128 1
 
2.1%
110 1
 
2.1%
101 1
 
2.1%
95 1
 
2.1%
91 1
 
2.1%
85 1
 
2.1%
Other values (31) 31
66.0%
(Missing) 6
 
12.8%
ValueCountFrequency (%)
3 1
2.1%
7 1
2.1%
14 1
2.1%
16 1
2.1%
21 1
2.1%
25 1
2.1%
32 1
2.1%
37 1
2.1%
41 1
2.1%
42 1
2.1%
ValueCountFrequency (%)
429 1
2.1%
303 1
2.1%
291 1
2.1%
287 1
2.1%
273 1
2.1%
269 1
2.1%
240 1
2.1%
238 1
2.1%
227 1
2.1%
213 1
2.1%

32년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)92.7%
Missing6
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean138.7561
Minimum2
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:10.500823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile13
Q158
median108
Q3202
95-th percentile325
Maximum400
Range398
Interquartile range (IQR)144

Descriptive statistics

Standard deviation107.21539
Coefficient of variation (CV)0.77268955
Kurtosis-0.40907655
Mean138.7561
Median Absolute Deviation (MAD)70
Skewness0.77478992
Sum5689
Variance11495.139
MonotonicityNot monotonic
2023-12-12T15:17:10.689935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
131 2
 
4.3%
108 2
 
4.3%
2 2
 
4.3%
58 1
 
2.1%
72 1
 
2.1%
129 1
 
2.1%
105 1
 
2.1%
94 1
 
2.1%
14 1
 
2.1%
86 1
 
2.1%
Other values (28) 28
59.6%
(Missing) 6
 
12.8%
ValueCountFrequency (%)
2 2
4.3%
13 1
2.1%
14 1
2.1%
21 1
2.1%
22 1
2.1%
37 1
2.1%
38 1
2.1%
45 1
2.1%
51 1
2.1%
58 1
2.1%
ValueCountFrequency (%)
400 1
2.1%
330 1
2.1%
325 1
2.1%
313 1
2.1%
312 1
2.1%
304 1
2.1%
293 1
2.1%
273 1
2.1%
241 1
2.1%
211 1
2.1%

33년미만
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)97.4%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean169.15385
Minimum3
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:10.834586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile18.7
Q163
median143
Q3266
95-th percentile394.7
Maximum440
Range437
Interquartile range (IQR)203

Descriptive statistics

Standard deviation129.848
Coefficient of variation (CV)0.76763254
Kurtosis-0.82000514
Mean169.15385
Median Absolute Deviation (MAD)97
Skewness0.67192844
Sum6597
Variance16860.502
MonotonicityNot monotonic
2023-12-12T15:17:10.976367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
150 2
 
4.3%
116 1
 
2.1%
165 1
 
2.1%
161 1
 
2.1%
107 1
 
2.1%
114 1
 
2.1%
110 1
 
2.1%
148 1
 
2.1%
97 1
 
2.1%
152 1
 
2.1%
Other values (28) 28
59.6%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
3 1
2.1%
7 1
2.1%
20 1
2.1%
28 1
2.1%
31 1
2.1%
37 1
2.1%
39 1
2.1%
46 1
2.1%
49 1
2.1%
58 1
2.1%
ValueCountFrequency (%)
440 1
2.1%
410 1
2.1%
393 1
2.1%
370 1
2.1%
365 1
2.1%
355 1
2.1%
352 1
2.1%
351 1
2.1%
299 1
2.1%
268 1
2.1%

33년이상
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)100.0%
Missing8
Missing (%)17.0%
Infinite0
Infinite (%)0.0%
Mean1255.5897
Minimum7
Maximum3465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T15:17:11.153369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile19.4
Q1391
median922
Q32099.5
95-th percentile3262.2
Maximum3465
Range3458
Interquartile range (IQR)1708.5

Descriptive statistics

Standard deviation1071.646
Coefficient of variation (CV)0.8535001
Kurtosis-0.76054942
Mean1255.5897
Median Absolute Deviation (MAD)584
Skewness0.72583433
Sum48968
Variance1148425.1
MonotonicityNot monotonic
2023-12-12T15:17:11.346588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
14 1
 
2.1%
1421 1
 
2.1%
1405 1
 
2.1%
1392 1
 
2.1%
1166 1
 
2.1%
1067 1
 
2.1%
922 1
 
2.1%
794 1
 
2.1%
773 1
 
2.1%
654 1
 
2.1%
Other values (29) 29
61.7%
(Missing) 8
 
17.0%
ValueCountFrequency (%)
7 1
2.1%
14 1
2.1%
20 1
2.1%
58 1
2.1%
113 1
2.1%
241 1
2.1%
277 1
2.1%
296 1
2.1%
338 1
2.1%
376 1
2.1%
ValueCountFrequency (%)
3465 1
2.1%
3345 1
2.1%
3253 1
2.1%
3074 1
2.1%
2790 1
2.1%
2738 1
2.1%
2724 1
2.1%
2433 1
2.1%
2403 1
2.1%
2205 1
2.1%

Interactions

2023-12-12T15:17:03.758219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.278093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.936028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.472510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.792613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.614879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.164954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.738225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.272904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.001906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.516140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.972989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.370937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.210767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.871583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.381603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.062428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.586819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.125736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.717664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.285221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.862693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.713855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.144602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.616980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.085950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.465344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.337002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.977140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.517067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.197231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.703003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.229440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.818290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.383155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.985420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.838615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.279064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.730820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.189637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.564025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.455468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.095374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.674235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.300721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.807662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.349114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.929088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.508234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.100534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.969002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.423015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.847387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.306991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.662680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.582597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.232664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.788393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.393920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.891750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.466516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.020168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.624872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.198089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.059038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.509776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.955408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.434671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.770107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.686233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.344692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:43.915623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.528769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.980298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.584641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.146930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.762487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.312092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.169284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.658351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.066742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.565676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.152605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.792593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.475626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.046229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.647905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.069410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.722075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.240186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.871069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.415933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.272732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.767211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.176212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.682945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.332964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.883715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.573947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.142582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.754025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.148587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.856629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.339281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.979451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.510530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.355914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.850643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.286238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.758478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.431550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.974590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.675133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.236731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.862328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.243176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:48.967034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.433741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.089298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.639874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.445739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:56.978626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.400101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.853715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.548503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.085327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.783128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.363084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:45.958237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.348446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.079365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.571011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.201746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.749703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.536450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.061708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.503517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:59.941437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.659444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.201684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.896850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.488306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.043729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.451239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.194909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.674163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.322235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:53.874281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.633809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.149959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.596227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.040913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.778094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.327725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:04.996094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.600680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.131684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.530952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.307883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.779518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.431458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.010497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.712048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.234264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.677297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.119383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.874519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.440425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:05.096227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.713051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.250965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.621052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.425604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:50.890196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.548267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.111042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.809653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.336968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.783471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.218403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:01.991252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.539210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:05.179577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:44.817090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:46.378072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:47.706296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:49.516373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:51.007947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:52.645247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:54.188557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:55.889664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:57.428669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:16:58.880937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:00.291473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:02.101008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:17:03.644292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:17:11.473097image/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
21년미만1.0001.0000.8450.8190.8330.8400.7480.8110.9020.9350.9530.8970.8740.8200.878
22년미만1.0000.8451.0000.9000.8190.7740.8530.8910.8750.8760.9050.9260.8390.8080.787
23년미만1.0000.8190.9001.0000.9320.9320.9560.9200.9410.9270.9180.7850.9280.8940.917
24년미만1.0000.8330.8190.9321.0000.9590.9210.8570.9550.9390.9060.8310.8870.8460.881
25년미만1.0000.8400.7740.9320.9591.0000.9360.8530.9170.9590.8870.7210.8290.8460.910
26년미만1.0000.7480.8530.9560.9210.9361.0000.9200.9500.9200.8420.7140.8970.8570.908
27년미만1.0000.8110.8910.9200.8570.8530.9201.0000.8940.8750.8210.8720.8020.7190.757
28년미만1.0000.9020.8750.9410.9550.9170.9500.8941.0000.9680.9730.8780.9440.8790.923
29년미만1.0000.9350.8760.9270.9390.9590.9200.8750.9681.0000.9770.8720.9270.9100.946
30년미만1.0000.9530.9050.9180.9060.8870.8420.8210.9730.9771.0000.9290.9620.9250.945
31년미만1.0000.8970.9260.7850.8310.7210.7140.8720.8780.8720.9291.0000.9410.8300.822
32년미만1.0000.8740.8390.9280.8870.8290.8970.8020.9440.9270.9620.9411.0000.9510.955
33년미만1.0000.8200.8080.8940.8460.8460.8570.7190.8790.9100.9250.8300.9511.0000.927
33년이상1.0000.8780.7870.9170.8810.9100.9080.7570.9230.9460.9450.8220.9550.9271.000
2023-12-12T15:17:11.649903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
21년미만1.0000.8950.9100.8790.9150.9120.9400.9540.9630.9380.9370.9160.9400.965
22년미만0.8951.0000.9650.9620.9670.9710.9610.9590.9460.9000.8630.8200.8780.956
23년미만0.9100.9651.0000.9690.9750.9740.9730.9700.9510.9110.8570.8340.8800.960
24년미만0.8790.9620.9691.0000.9720.9760.9640.9650.9360.8730.8070.7710.8290.943
25년미만0.9150.9670.9750.9721.0000.9780.9760.9710.9380.8880.8150.7750.8520.955
26년미만0.9120.9710.9740.9760.9781.0000.9780.9800.9580.9070.8520.8200.8850.978
27년미만0.9400.9610.9730.9640.9760.9781.0000.9810.9520.9290.8570.8340.8910.969
28년미만0.9540.9590.9700.9650.9710.9800.9811.0000.9750.9490.8960.8700.9230.980
29년미만0.9630.9460.9510.9360.9380.9580.9520.9751.0000.9660.9360.9210.9650.981
30년미만0.9380.9000.9110.8730.8880.9070.9290.9490.9661.0000.9460.9340.9730.943
31년미만0.9370.8630.8570.8070.8150.8520.8570.8960.9360.9461.0000.9710.9760.915
32년미만0.9160.8200.8340.7710.7750.8200.8340.8700.9210.9340.9711.0000.9660.887
33년미만0.9400.8780.8800.8290.8520.8850.8910.9230.9650.9730.9760.9661.0000.942
33년이상0.9650.9560.9600.9430.9550.9780.9690.9800.9810.9430.9150.8870.9421.000

Missing values

2023-12-12T15:17:05.340868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:17:05.525490image/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.
2023-12-12T15:17:05.741449image/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
050세 미만59222<NA>2<NA><NA><NA><NA><NA><NA><NA><NA>
151세 미만10<NA><NA><NA><NA><NA>1<NA><NA><NA>32<NA><NA>
252세 미만9<NA>2<NA><NA><NA><NA><NA><NA>572<NA><NA>
353세 미만441<NA><NA><NA><NA>124141337
454세 미만16<NA><NA><NA><NA>1<NA>6821614714
555세 미만1841<NA>21176941382020
656세 미만158331184132647584658
757세 미만291856667182636849078113
858세 미만2018111158616285311111089241
959세 미만41152214191519275272106131140464
연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상
3787세 미만23141822221030372646424539376
3888세 미만1591821191727273520323737338
3989세 미만17121519252018192121252131296
4090세 미만1571491311491620212228277
4190세 이상26191914272931383932376349546
42<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연령21년미만22년미만23년미만24년미만25년미만26년미만27년미만28년미만29년미만30년미만31년미만32년미만33년미만33년이상# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5