Overview

Dataset statistics

Number of variables13
Number of observations1955
Missing cells85
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory223.5 KiB
Average record size in memory117.1 B

Variable types

Numeric13

Dataset

Description연월일,10대이하 남자,10대이하 여자,20대 남자,20대 여자,30대 남자,30대 여자,40대 남자,40대 여자,50대 남자,50대 여자,60대이상 남자,60대이상 여자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20886/S/1/datasetView.do

Alerts

연월일 is highly overall correlated with 10대이하 남자 and 11 other fieldsHigh correlation
10대이하 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
10대이하 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
20대 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
20대 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
30대 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
30대 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
40대 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
40대 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
50대 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
50대 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
60대이상 남자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
60대이상 여자 is highly overall correlated with 연월일 and 11 other fieldsHigh correlation
연월일 has unique valuesUnique
10대이하 남자 has 44 (2.3%) zerosZeros
10대이하 여자 has 27 (1.4%) zerosZeros
60대이상 여자 has 21 (1.1%) zerosZeros

Reproduction

Analysis started2024-04-21 16:43:02.068324
Analysis finished2024-04-21 16:43:37.343518
Duration35.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1955
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20201380
Minimum20171101
Maximum20230329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:37.470492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20171101
5-th percentile20180227
Q120190324
median20200725
Q320211126
95-th percentile20221221
Maximum20230329
Range59228
Interquartile range (IQR)20801

Descriptive statistics

Standard deviation15618.718
Coefficient of variation (CV)0.00077315107
Kurtosis-1.103815
Mean20201380
Median Absolute Deviation (MAD)10401
Skewness0.027058672
Sum3.9493697 × 1010
Variance2.4394436 × 108
MonotonicityStrictly decreasing
2024-04-22T01:43:37.724793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230329 1
 
0.1%
20190823 1
 
0.1%
20190825 1
 
0.1%
20190826 1
 
0.1%
20190827 1
 
0.1%
20190828 1
 
0.1%
20190829 1
 
0.1%
20190830 1
 
0.1%
20190831 1
 
0.1%
20190901 1
 
0.1%
Other values (1945) 1945
99.5%
ValueCountFrequency (%)
20171101 1
0.1%
20171102 1
0.1%
20171103 1
0.1%
20171108 1
0.1%
20171115 1
0.1%
20171116 1
0.1%
20171117 1
0.1%
20171120 1
0.1%
20171129 1
0.1%
20171130 1
0.1%
ValueCountFrequency (%)
20230329 1
0.1%
20230328 1
0.1%
20230327 1
0.1%
20230326 1
0.1%
20230325 1
0.1%
20230324 1
0.1%
20230323 1
0.1%
20230322 1
0.1%
20230321 1
0.1%
20230320 1
0.1%

10대이하 남자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct241
Distinct (%)12.4%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean60.279918
Minimum0
Maximum306
Zeros44
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:37.973794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q115
median38
Q393
95-th percentile175.7
Maximum306
Range306
Interquartile range (IQR)78

Descriptive statistics

Standard deviation59.863198
Coefficient of variation (CV)0.99308692
Kurtosis1.6627398
Mean60.279918
Median Absolute Deviation (MAD)31
Skewness1.361768
Sum117365
Variance3583.6025
MonotonicityNot monotonic
2024-04-22T01:43:38.221557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 62
 
3.2%
2 44
 
2.3%
0 44
 
2.3%
3 44
 
2.3%
4 39
 
2.0%
19 34
 
1.7%
22 33
 
1.7%
27 32
 
1.6%
5 32
 
1.6%
6 32
 
1.6%
Other values (231) 1551
79.3%
ValueCountFrequency (%)
0 44
2.3%
1 62
3.2%
2 44
2.3%
3 44
2.3%
4 39
2.0%
5 32
1.6%
6 32
1.6%
7 25
1.3%
8 19
 
1.0%
9 24
 
1.2%
ValueCountFrequency (%)
306 1
 
0.1%
300 1
 
0.1%
298 1
 
0.1%
296 1
 
0.1%
292 1
 
0.1%
286 2
0.1%
283 3
0.2%
281 2
0.1%
280 1
 
0.1%
276 1
 
0.1%

10대이하 여자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct297
Distinct (%)15.3%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean89.657935
Minimum0
Maximum351
Zeros27
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:38.468530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q125
median69
Q3141
95-th percentile232.1
Maximum351
Range351
Interquartile range (IQR)116

Descriptive statistics

Standard deviation76.18268
Coefficient of variation (CV)0.84970371
Kurtosis0.17425829
Mean89.657935
Median Absolute Deviation (MAD)53
Skewness0.88494728
Sum174564
Variance5803.8007
MonotonicityNot monotonic
2024-04-22T01:43:38.718579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 37
 
1.9%
3 35
 
1.8%
2 31
 
1.6%
7 29
 
1.5%
5 29
 
1.5%
0 27
 
1.4%
1 23
 
1.2%
17 20
 
1.0%
22 18
 
0.9%
39 18
 
0.9%
Other values (287) 1680
85.9%
ValueCountFrequency (%)
0 27
1.4%
1 23
1.2%
2 31
1.6%
3 35
1.8%
4 37
1.9%
5 29
1.5%
6 10
 
0.5%
7 29
1.5%
8 15
0.8%
9 13
 
0.7%
ValueCountFrequency (%)
351 1
0.1%
348 1
0.1%
341 1
0.1%
340 1
0.1%
336 1
0.1%
335 1
0.1%
334 1
0.1%
333 2
0.1%
331 1
0.1%
328 2
0.1%

20대 남자
Real number (ℝ)

HIGH CORRELATION 

Distinct593
Distinct (%)30.5%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean219.83975
Minimum0
Maximum969
Zeros5
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:39.189686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q161.5
median180
Q3293
95-th percentile664.8
Maximum969
Range969
Interquartile range (IQR)231.5

Descriptive statistics

Standard deviation198.42381
Coefficient of variation (CV)0.90258387
Kurtosis0.8544749
Mean219.83975
Median Absolute Deviation (MAD)117
Skewness1.2130971
Sum428028
Variance39372.01
MonotonicityNot monotonic
2024-04-22T01:43:39.452092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 20
 
1.0%
16 19
 
1.0%
11 18
 
0.9%
20 16
 
0.8%
12 16
 
0.8%
6 15
 
0.8%
22 14
 
0.7%
51 13
 
0.7%
17 12
 
0.6%
209 12
 
0.6%
Other values (583) 1792
91.7%
ValueCountFrequency (%)
0 5
 
0.3%
1 4
 
0.2%
2 1
 
0.1%
4 5
 
0.3%
5 5
 
0.3%
6 15
0.8%
7 10
0.5%
8 10
0.5%
9 20
1.0%
10 10
0.5%
ValueCountFrequency (%)
969 1
0.1%
948 1
0.1%
934 1
0.1%
884 1
0.1%
879 1
0.1%
868 1
0.1%
852 1
0.1%
834 1
0.1%
822 1
0.1%
806 1
0.1%

20대 여자
Real number (ℝ)

HIGH CORRELATION 

Distinct965
Distinct (%)49.6%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean502.68875
Minimum0
Maximum2553
Zeros6
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:39.702762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25
Q1162
median422
Q3705
95-th percentile1428.7
Maximum2553
Range2553
Interquartile range (IQR)543

Descriptive statistics

Standard deviation430.56518
Coefficient of variation (CV)0.85652441
Kurtosis0.91961686
Mean502.68875
Median Absolute Deviation (MAD)269
Skewness1.1211217
Sum978735
Variance185386.38
MonotonicityNot monotonic
2024-04-22T01:43:39.954320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 14
 
0.7%
20 10
 
0.5%
26 10
 
0.5%
38 10
 
0.5%
37 9
 
0.5%
41 9
 
0.5%
25 9
 
0.5%
44 9
 
0.5%
35 9
 
0.5%
36 9
 
0.5%
Other values (955) 1849
94.6%
ValueCountFrequency (%)
0 6
0.3%
1 3
0.2%
2 1
 
0.1%
5 2
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
10 3
0.2%
11 3
0.2%
12 2
 
0.1%
13 7
0.4%
ValueCountFrequency (%)
2553 1
0.1%
2349 1
0.1%
2018 1
0.1%
1946 1
0.1%
1941 1
0.1%
1938 1
0.1%
1924 1
0.1%
1914 1
0.1%
1911 1
0.1%
1898 1
0.1%

30대 남자
Real number (ℝ)

HIGH CORRELATION 

Distinct798
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365.95141
Minimum1
Maximum1905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:40.199415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27
Q1130.5
median305
Q3486
95-th percentile1019
Maximum1905
Range1904
Interquartile range (IQR)355.5

Descriptive statistics

Standard deviation307.95624
Coefficient of variation (CV)0.84152221
Kurtosis1.3770895
Mean365.95141
Median Absolute Deviation (MAD)177
Skewness1.2304615
Sum715435
Variance94837.043
MonotonicityNot monotonic
2024-04-22T01:43:40.459425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29 16
 
0.8%
34 15
 
0.8%
31 13
 
0.7%
27 12
 
0.6%
32 12
 
0.6%
30 12
 
0.6%
33 10
 
0.5%
28 10
 
0.5%
140 10
 
0.5%
401 9
 
0.5%
Other values (788) 1836
93.9%
ValueCountFrequency (%)
1 3
0.2%
2 2
 
0.1%
3 2
 
0.1%
5 2
 
0.1%
7 1
 
0.1%
10 2
 
0.1%
11 1
 
0.1%
12 5
0.3%
13 3
0.2%
14 4
0.2%
ValueCountFrequency (%)
1905 1
0.1%
1804 1
0.1%
1770 1
0.1%
1570 2
0.1%
1550 1
0.1%
1536 1
0.1%
1469 1
0.1%
1466 1
0.1%
1443 1
0.1%
1420 1
0.1%

30대 여자
Real number (ℝ)

HIGH CORRELATION 

Distinct1228
Distinct (%)63.0%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean901.32923
Minimum0
Maximum4129
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:40.721126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile58
Q1313.5
median773.5
Q31316.5
95-th percentile2383.65
Maximum4129
Range4129
Interquartile range (IQR)1003

Descriptive statistics

Standard deviation728.50976
Coefficient of variation (CV)0.80826154
Kurtosis0.50035189
Mean901.32923
Median Absolute Deviation (MAD)491.5
Skewness0.94065986
Sum1757592
Variance530726.47
MonotonicityNot monotonic
2024-04-22T01:43:40.958254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 9
 
0.5%
56 9
 
0.5%
68 8
 
0.4%
61 8
 
0.4%
93 8
 
0.4%
75 8
 
0.4%
72 6
 
0.3%
54 6
 
0.3%
77 6
 
0.3%
781 6
 
0.3%
Other values (1218) 1876
96.0%
ValueCountFrequency (%)
0 3
0.2%
1 3
0.2%
4 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
10 1
 
0.1%
11 1
 
0.1%
12 1
 
0.1%
14 1
 
0.1%
15 2
0.1%
ValueCountFrequency (%)
4129 1
0.1%
4053 1
0.1%
3774 1
0.1%
3736 1
0.1%
3608 1
0.1%
3509 1
0.1%
3501 1
0.1%
3443 1
0.1%
3219 1
0.1%
3099 1
0.1%

40대 남자
Real number (ℝ)

HIGH CORRELATION 

Distinct960
Distinct (%)49.3%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean496.76066
Minimum2
Maximum3027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:41.193078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile39
Q1172
median373
Q3704
95-th percentile1316.1
Maximum3027
Range3025
Interquartile range (IQR)532

Descriptive statistics

Standard deviation431.09482
Coefficient of variation (CV)0.86781192
Kurtosis2.1464283
Mean496.76066
Median Absolute Deviation (MAD)237
Skewness1.3247999
Sum967193
Variance185842.74
MonotonicityNot monotonic
2024-04-22T01:43:41.438815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49 13
 
0.7%
44 12
 
0.6%
51 12
 
0.6%
53 11
 
0.6%
38 11
 
0.6%
48 10
 
0.5%
41 9
 
0.5%
404 8
 
0.4%
43 8
 
0.4%
46 8
 
0.4%
Other values (950) 1845
94.4%
(Missing) 8
 
0.4%
ValueCountFrequency (%)
2 1
 
0.1%
3 1
 
0.1%
9 1
 
0.1%
14 2
0.1%
15 3
0.2%
16 2
0.1%
17 1
 
0.1%
18 1
 
0.1%
19 2
0.1%
21 3
0.2%
ValueCountFrequency (%)
3027 1
0.1%
2756 1
0.1%
2649 1
0.1%
2544 1
0.1%
2451 1
0.1%
2423 1
0.1%
2395 1
0.1%
2249 1
0.1%
2192 1
0.1%
2121 1
0.1%

40대 여자
Real number (ℝ)

HIGH CORRELATION 

Distinct1266
Distinct (%)65.0%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1010.964
Minimum0
Maximum5173
Zeros5
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:41.689124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55
Q1326.5
median813
Q31530.5
95-th percentile2683.6
Maximum5173
Range5173
Interquartile range (IQR)1204

Descriptive statistics

Standard deviation853.28961
Coefficient of variation (CV)0.84403556
Kurtosis0.82740845
Mean1010.964
Median Absolute Deviation (MAD)558
Skewness1.0211994
Sum1968347
Variance728103.15
MonotonicityNot monotonic
2024-04-22T01:43:41.943250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 10
 
0.5%
78 8
 
0.4%
53 8
 
0.4%
61 7
 
0.4%
73 7
 
0.4%
59 7
 
0.4%
72 7
 
0.4%
82 6
 
0.3%
377 6
 
0.3%
334 5
 
0.3%
Other values (1256) 1876
96.0%
(Missing) 8
 
0.4%
ValueCountFrequency (%)
0 5
0.3%
1 2
 
0.1%
2 1
 
0.1%
3 2
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
16 1
 
0.1%
20 1
 
0.1%
22 1
 
0.1%
26 2
 
0.1%
ValueCountFrequency (%)
5173 1
0.1%
5014 1
0.1%
4777 1
0.1%
4720 1
0.1%
4645 1
0.1%
4510 1
0.1%
3834 1
0.1%
3742 1
0.1%
3738 1
0.1%
3736 1
0.1%

50대 남자
Real number (ℝ)

HIGH CORRELATION 

Distinct676
Distinct (%)34.7%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean267.00257
Minimum0
Maximum1675
Zeros11
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:42.186169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q177
median173
Q3363
95-th percentile803.4
Maximum1675
Range1675
Interquartile range (IQR)286

Descriptive statistics

Standard deviation263.92777
Coefficient of variation (CV)0.98848402
Kurtosis2.1291084
Mean267.00257
Median Absolute Deviation (MAD)124
Skewness1.5007021
Sum519854
Variance69657.869
MonotonicityNot monotonic
2024-04-22T01:43:42.437402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 26
 
1.3%
22 23
 
1.2%
21 21
 
1.1%
20 17
 
0.9%
18 15
 
0.8%
28 14
 
0.7%
25 14
 
0.7%
27 14
 
0.7%
29 13
 
0.7%
15 13
 
0.7%
Other values (666) 1777
90.9%
ValueCountFrequency (%)
0 11
0.6%
2 1
 
0.1%
5 2
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
9 4
 
0.2%
10 7
0.4%
11 7
0.4%
12 5
0.3%
13 9
0.5%
ValueCountFrequency (%)
1675 1
0.1%
1674 1
0.1%
1638 1
0.1%
1429 1
0.1%
1392 1
0.1%
1249 1
0.1%
1158 1
0.1%
1154 1
0.1%
1120 1
0.1%
1092 1
0.1%

50대 여자
Real number (ℝ)

HIGH CORRELATION 

Distinct825
Distinct (%)42.4%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean386.68413
Minimum0
Maximum2556
Zeros2
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:42.696645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q1111.5
median266
Q3490
95-th percentile1266.2
Maximum2556
Range2556
Interquartile range (IQR)378.5

Descriptive statistics

Standard deviation395.8762
Coefficient of variation (CV)1.0237715
Kurtosis2.2134159
Mean386.68413
Median Absolute Deviation (MAD)175
Skewness1.5851218
Sum752874
Variance156717.97
MonotonicityNot monotonic
2024-04-22T01:43:42.952890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 19
 
1.0%
23 18
 
0.9%
18 17
 
0.9%
21 16
 
0.8%
16 15
 
0.8%
25 15
 
0.8%
22 15
 
0.8%
17 15
 
0.8%
20 13
 
0.7%
13 12
 
0.6%
Other values (815) 1792
91.7%
ValueCountFrequency (%)
0 2
 
0.1%
1 2
 
0.1%
4 2
 
0.1%
5 3
 
0.2%
6 4
0.2%
7 2
 
0.1%
8 2
 
0.1%
9 9
0.5%
10 5
0.3%
11 4
0.2%
ValueCountFrequency (%)
2556 1
0.1%
2430 1
0.1%
2180 1
0.1%
1859 1
0.1%
1753 1
0.1%
1728 1
0.1%
1720 1
0.1%
1710 1
0.1%
1664 1
0.1%
1656 1
0.1%

60대이상 남자
Real number (ℝ)

HIGH CORRELATION 

Distinct464
Distinct (%)23.8%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean142.85311
Minimum0
Maximum923
Zeros12
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:43.203121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q141
median99
Q3176.5
95-th percentile465.7
Maximum923
Range923
Interquartile range (IQR)135.5

Descriptive statistics

Standard deviation147.22597
Coefficient of variation (CV)1.0306109
Kurtosis2.621473
Mean142.85311
Median Absolute Deviation (MAD)68
Skewness1.6571515
Sum278135
Variance21675.485
MonotonicityNot monotonic
2024-04-22T01:43:43.447827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 38
 
1.9%
8 36
 
1.8%
10 33
 
1.7%
11 30
 
1.5%
9 30
 
1.5%
5 24
 
1.2%
6 21
 
1.1%
14 21
 
1.1%
3 18
 
0.9%
12 18
 
0.9%
Other values (454) 1678
85.8%
ValueCountFrequency (%)
0 12
 
0.6%
1 5
 
0.3%
2 7
 
0.4%
3 18
0.9%
4 13
 
0.7%
5 24
1.2%
6 21
1.1%
7 38
1.9%
8 36
1.8%
9 30
1.5%
ValueCountFrequency (%)
923 1
0.1%
883 1
0.1%
842 1
0.1%
806 1
0.1%
699 1
0.1%
694 1
0.1%
661 1
0.1%
659 1
0.1%
653 1
0.1%
652 1
0.1%

60대이상 여자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct561
Distinct (%)28.8%
Missing8
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean191.90858
Minimum0
Maximum1501
Zeros21
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size17.3 KiB
2024-04-22T01:43:43.686636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q147
median111
Q3212.5
95-th percentile724.8
Maximum1501
Range1501
Interquartile range (IQR)165.5

Descriptive statistics

Standard deviation232.11379
Coefficient of variation (CV)1.2095019
Kurtosis3.7380045
Mean191.90858
Median Absolute Deviation (MAD)78
Skewness1.976045
Sum373646
Variance53876.811
MonotonicityNot monotonic
2024-04-22T01:43:43.932515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 40
 
2.0%
6 38
 
1.9%
8 35
 
1.8%
3 32
 
1.6%
2 28
 
1.4%
4 26
 
1.3%
0 21
 
1.1%
7 21
 
1.1%
1 19
 
1.0%
67 17
 
0.9%
Other values (551) 1670
85.4%
ValueCountFrequency (%)
0 21
1.1%
1 19
1.0%
2 28
1.4%
3 32
1.6%
4 26
1.3%
5 40
2.0%
6 38
1.9%
7 21
1.1%
8 35
1.8%
9 16
 
0.8%
ValueCountFrequency (%)
1501 1
0.1%
1127 1
0.1%
1114 1
0.1%
1107 1
0.1%
1095 1
0.1%
1094 2
0.1%
1093 1
0.1%
1090 1
0.1%
1087 1
0.1%
1078 2
0.1%

Interactions

2024-04-22T01:43:34.181116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:03.829489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:07.545628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:10.684459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.921807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:15.735075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:18.347146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.024349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.055774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.417603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.569031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.778195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.882759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:34.360625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:04.306868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:07.816920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:10.866880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.094219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.002618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:18.629605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.190309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.229346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.585060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.749102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.953374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:32.070582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:34.527405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:04.577980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:08.079499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.039333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.254004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.250581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:18.902455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.347509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.396784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.749890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.918397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.117394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:32.239870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:34.711649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:04.854352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:08.347054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.212211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.423578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.418578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:19.184262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.513297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.571819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.916955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.095816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.287800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:32.404533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:34.876736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:05.117505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:08.603567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.376536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.574851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.575311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:19.448679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.663540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.731364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.074845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.256188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.440859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:32.558699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.038610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:05.380768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:08.858771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.536693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.731837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.732709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:19.665659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.814301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:23.886098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.229622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.419604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.596798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:32.922317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.225642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:05.668494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:09.135160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.720071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:13.905706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:16.907097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:19.845282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:21.982324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:24.075367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.405365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.598940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.770889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.096318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.382011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:05.926577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:09.383010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:11.874485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:14.057775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:17.059016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.006877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.127810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:24.440825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.551236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.758744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:30.922022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.240895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.552651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:06.200335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:09.652193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.047325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:14.244438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:17.216922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.181022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.283641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:24.604211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.751325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:28.935873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.083162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.398606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.714715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:06.467519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:09.913749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.210799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:14.707580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:17.373875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.344564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.435237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:24.760692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:26.913246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.105066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.244448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.549527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:35.895817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:06.746912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:10.193237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.386472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:14.972922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:17.572281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.522580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.596907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:24.932045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.086769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.278114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.411443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.719587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:36.089688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:07.012771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:10.353023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.550771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:15.223914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:17.828189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.686929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.749164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.088564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.241457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.438104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.565578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:33.870619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:36.267738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:07.270325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:10.510812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:12.711725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:15.470819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:18.075743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:20.847358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:22.893012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:25.243258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:27.392399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:29.596707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:31.713981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:43:34.016039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T01:43:44.331970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월일10대이하 남자10대이하 여자20대 남자20대 여자30대 남자30대 여자40대 남자40대 여자50대 남자50대 여자60대이상 남자60대이상 여자
연월일1.0000.7360.7210.6910.6870.7190.6980.7010.6970.7270.6830.6950.658
10대이하 남자0.7361.0000.9030.8250.7060.8140.8170.8350.8210.8180.7970.7900.622
10대이하 여자0.7210.9031.0000.8150.7250.8240.8300.8080.8240.7750.7540.7510.582
20대 남자0.6910.8250.8151.0000.8730.9110.9260.8700.9040.8610.8920.8580.716
20대 여자0.6870.7060.7250.8731.0000.8700.8710.7830.8310.7610.7720.7380.850
30대 남자0.7190.8140.8240.9110.8701.0000.9610.9520.9540.9360.9340.9200.779
30대 여자0.6980.8170.8300.9260.8710.9611.0000.9380.9600.9190.9230.8960.751
40대 남자0.7010.8350.8080.8700.7830.9520.9381.0000.9630.9580.9390.9330.761
40대 여자0.6970.8210.8240.9040.8310.9540.9600.9631.0000.9520.9480.9270.764
50대 남자0.7270.8180.7750.8610.7610.9360.9190.9580.9521.0000.9710.9630.834
50대 여자0.6830.7970.7540.8920.7720.9340.9230.9390.9480.9711.0000.9630.856
60대이상 남자0.6950.7900.7510.8580.7380.9200.8960.9330.9270.9630.9631.0000.846
60대이상 여자0.6580.6220.5820.7160.8500.7790.7510.7610.7640.8340.8560.8461.000
2024-04-22T01:43:44.584300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월일10대이하 남자10대이하 여자20대 남자20대 여자30대 남자30대 여자40대 남자40대 여자50대 남자50대 여자60대이상 남자60대이상 여자
연월일1.0000.8940.8520.8110.8330.8240.8490.8610.8700.8820.8570.8600.840
10대이하 남자0.8941.0000.9510.9110.9190.9210.9230.9320.9230.9200.8930.8920.868
10대이하 여자0.8520.9511.0000.9090.9250.9130.9180.9160.9090.8950.8730.8690.846
20대 남자0.8110.9110.9091.0000.9800.9680.9750.9390.9580.9320.9450.9320.932
20대 여자0.8330.9190.9250.9801.0000.9690.9810.9470.9650.9370.9490.9350.935
30대 남자0.8240.9210.9130.9680.9691.0000.9770.9770.9680.9600.9530.9480.936
30대 여자0.8490.9230.9180.9750.9810.9771.0000.9680.9910.9650.9730.9590.949
40대 남자0.8610.9320.9160.9390.9470.9770.9681.0000.9740.9790.9560.9550.928
40대 여자0.8700.9230.9090.9580.9650.9680.9910.9741.0000.9780.9820.9690.953
50대 남자0.8820.9200.8950.9320.9370.9600.9650.9790.9781.0000.9730.9700.946
50대 여자0.8570.8930.8730.9450.9490.9530.9730.9560.9820.9731.0000.9740.972
60대이상 남자0.8600.8920.8690.9320.9350.9480.9590.9550.9690.9700.9741.0000.966
60대이상 여자0.8400.8680.8460.9320.9350.9360.9490.9280.9530.9460.9720.9661.000

Missing values

2024-04-22T01:43:36.533892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T01:43:36.845760image/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.
2024-04-22T01:43:37.122352image/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

연월일10대이하 남자10대이하 여자20대 남자20대 여자30대 남자30대 여자40대 남자40대 여자50대 남자50대 여자60대이상 남자60대이상 여자
0202303291581907461461114023301402299799915556191030
1202303281411297681480111425061431298410161512575946
2202303271311436681288106221861474252798915895681093
32023032616922230464350513369611600501552194235
420230325237311455923686168412022051783868514581
5202303241441726881303101922181459284296115055891078
6202303231211326761536107324571412290910031623608919
72023032215917770915401200249914962817103815896301054
820230321160176780168211892598151630269751626559983
92023032013316567814401077220614682600102416076521094
연월일10대이하 남자10대이하 여자20대 남자20대 여자30대 남자30대 여자40대 남자40대 여자50대 남자50대 여자60대이상 남자60대이상 여자
19452017113000002314200000
1946201711290000140300000
194720171120<NA><NA><NA><NA>10<NA><NA><NA><NA><NA><NA><NA>
194820171117<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>
194920171116<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>
195020171115<NA><NA><NA><NA>3<NA><NA><NA><NA><NA><NA><NA>
195120171108<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>
195220171103<NA><NA><NA><NA>31<NA><NA><NA><NA><NA><NA>
195320171102<NA><NA><NA><NA>21<NA><NA><NA><NA><NA><NA>
195420171101<NA><NA><NA><NA>57<NA><NA><NA><NA><NA><NA>