Overview

Dataset statistics

Number of variables8
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory73.1 B

Variable types

Numeric7
Categorical1

Dataset

Description통계연도,만나이,만나이명칭,전체_아동수,전체_국공립아동수,전체_민간아동수,전체_가정아동수,전체_기타아동수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15451/S/1/datasetView.do

Alerts

만나이 is highly overall correlated with 전체_가정아동수 and 1 other fieldsHigh correlation
전체_아동수 is highly overall correlated with 전체_국공립아동수 and 4 other fieldsHigh correlation
전체_국공립아동수 is highly overall correlated with 전체_아동수 and 3 other fieldsHigh correlation
전체_민간아동수 is highly overall correlated with 전체_아동수 and 4 other fieldsHigh correlation
전체_가정아동수 is highly overall correlated with 만나이 and 2 other fieldsHigh correlation
전체_기타아동수 is highly overall correlated with 전체_아동수 and 3 other fieldsHigh correlation
만나이명칭 is highly overall correlated with 만나이 and 4 other fieldsHigh correlation
전체_아동수 has unique valuesUnique
전체_국공립아동수 has unique valuesUnique
전체_민간아동수 has unique valuesUnique
전체_기타아동수 has unique valuesUnique
만나이 has 9 (14.3%) zerosZeros

Reproduction

Analysis started2024-04-06 11:07:43.019236
Analysis finished2024-04-06 11:07:51.822577
Duration8.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Real number (ℝ)

Distinct9
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:51.924442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32020
95-th percentile2022
Maximum2022
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6027281
Coefficient of variation (CV)0.0012897562
Kurtosis-1.2318689
Mean2018
Median Absolute Deviation (MAD)2
Skewness0
Sum127134
Variance6.7741935
MonotonicityDecreasing
2024-04-06T20:07:52.172623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2022 7
11.1%
2021 7
11.1%
2020 7
11.1%
2019 7
11.1%
2018 7
11.1%
2017 7
11.1%
2016 7
11.1%
2015 7
11.1%
2014 7
11.1%
ValueCountFrequency (%)
2014 7
11.1%
2015 7
11.1%
2016 7
11.1%
2017 7
11.1%
2018 7
11.1%
2019 7
11.1%
2020 7
11.1%
2021 7
11.1%
2022 7
11.1%
ValueCountFrequency (%)
2022 7
11.1%
2021 7
11.1%
2020 7
11.1%
2019 7
11.1%
2018 7
11.1%
2017 7
11.1%
2016 7
11.1%
2015 7
11.1%
2014 7
11.1%

만나이
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3
Minimum0
Maximum6
Zeros9
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:52.375328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0160645
Coefficient of variation (CV)0.67202151
Kurtosis-1.2535519
Mean3
Median Absolute Deviation (MAD)2
Skewness0
Sum189
Variance4.0645161
MonotonicityNot monotonic
2024-04-06T20:07:52.592423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 9
14.3%
5 9
14.3%
4 9
14.3%
6 9
14.3%
3 9
14.3%
2 9
14.3%
1 9
14.3%
ValueCountFrequency (%)
0 9
14.3%
1 9
14.3%
2 9
14.3%
3 9
14.3%
4 9
14.3%
5 9
14.3%
6 9
14.3%
ValueCountFrequency (%)
6 9
14.3%
5 9
14.3%
4 9
14.3%
3 9
14.3%
2 9
14.3%
1 9
14.3%
0 9
14.3%

만나이명칭
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size636.0 B
0세
9 
5세
9 
4세
9 
방과후 (6세이상)
9 
3세
9 
Other values (2)
18 

Length

Max length10
Median length2
Mean length3.1428571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0세
2nd row5세
3rd row4세
4th row방과후 (6세이상)
5th row3세

Common Values

ValueCountFrequency (%)
0세 9
14.3%
5세 9
14.3%
4세 9
14.3%
방과후 (6세이상) 9
14.3%
3세 9
14.3%
2세 9
14.3%
1세 9
14.3%

Length

2024-04-06T20:07:52.824214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:07:53.028506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0세 9
12.5%
5세 9
12.5%
4세 9
12.5%
방과후 9
12.5%
6세이상 9
12.5%
3세 9
12.5%
2세 9
12.5%
1세 9
12.5%

전체_아동수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30856.571
Minimum1192
Maximum65574
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:53.221309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1192
5-th percentile1928.2
Q120902.5
median29025
Q342617.5
95-th percentile60621.6
Maximum65574
Range64382
Interquartile range (IQR)21715

Descriptive statistics

Standard deviation17079.652
Coefficient of variation (CV)0.55351748
Kurtosis-0.47523882
Mean30856.571
Median Absolute Deviation (MAD)9622
Skewness0.025927621
Sum1943964
Variance2.917145 × 108
MonotonicityNot monotonic
2024-04-06T20:07:53.827717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19768 1
 
1.6%
21473 1
 
1.6%
2245 1
 
1.6%
20662 1
 
1.6%
2443 1
 
1.6%
28386 1
 
1.6%
32854 1
 
1.6%
38413 1
 
1.6%
60686 1
 
1.6%
51423 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
1192 1
1.6%
1312 1
1.6%
1539 1
1.6%
1893 1
1.6%
2245 1
1.6%
2443 1
1.6%
2765 1
1.6%
3014 1
1.6%
3383 1
1.6%
18479 1
1.6%
ValueCountFrequency (%)
65574 1
1.6%
64171 1
1.6%
60721 1
1.6%
60686 1
1.6%
60042 1
1.6%
57333 1
1.6%
54000 1
1.6%
51423 1
1.6%
49677 1
1.6%
49296 1
1.6%

전체_국공립아동수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10817.81
Minimum426
Maximum20812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:54.064469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum426
5-th percentile757.6
Q16296
median12947
Q314284.5
95-th percentile19898.9
Maximum20812
Range20386
Interquartile range (IQR)7988.5

Descriptive statistics

Standard deviation5912.574
Coefficient of variation (CV)0.54655926
Kurtosis-0.79018579
Mean10817.81
Median Absolute Deviation (MAD)3026
Skewness-0.52825903
Sum681522
Variance34958532
MonotonicityNot monotonic
2024-04-06T20:07:54.321454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7582 1
 
1.6%
11755 1
 
1.6%
916 1
 
1.6%
3272 1
 
1.6%
1003 1
 
1.6%
13052 1
 
1.6%
14219 1
 
1.6%
14412 1
 
1.6%
16107 1
 
1.6%
12033 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
426 1
1.6%
464 1
1.6%
561 1
1.6%
740 1
1.6%
916 1
1.6%
1003 1
1.6%
1013 1
1.6%
1061 1
1.6%
1083 1
1.6%
1746 1
1.6%
ValueCountFrequency (%)
20812 1
1.6%
20499 1
1.6%
20356 1
1.6%
20040 1
1.6%
18629 1
1.6%
16814 1
1.6%
16405 1
1.6%
16323 1
1.6%
16107 1
1.6%
16028 1
1.6%

전체_민간아동수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11843.365
Minimum243
Maximum31779
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:54.544175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243
5-th percentile315.8
Q15445.5
median11536
Q316491.5
95-th percentile26122.3
Maximum31779
Range31536
Interquartile range (IQR)11046

Descriptive statistics

Standard deviation8049.6821
Coefficient of variation (CV)0.67967862
Kurtosis-0.24488681
Mean11843.365
Median Absolute Deviation (MAD)6028
Skewness0.4813012
Sum746132
Variance64797382
MonotonicityNot monotonic
2024-04-06T20:07:54.760981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4463 1
 
1.6%
7397 1
 
1.6%
377 1
 
1.6%
5508 1
 
1.6%
403 1
 
1.6%
12388 1
 
1.6%
14973 1
 
1.6%
19642 1
 
1.6%
26219 1
 
1.6%
18082 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
243 1
1.6%
278 1
1.6%
281 1
1.6%
309 1
1.6%
377 1
1.6%
403 1
1.6%
426 1
1.6%
459 1
1.6%
547 1
1.6%
4038 1
1.6%
ValueCountFrequency (%)
31779 1
1.6%
30986 1
1.6%
26955 1
1.6%
26219 1
1.6%
25252 1
1.6%
24280 1
1.6%
24096 1
1.6%
23474 1
1.6%
20959 1
1.6%
20473 1
1.6%

전체_가정아동수
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5330.0794
Minimum2
Maximum22461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:55.059422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q130
median74
Q310738.5
95-th percentile17574.9
Maximum22461
Range22459
Interquartile range (IQR)10708.5

Descriptive statistics

Standard deviation6742.0222
Coefficient of variation (CV)1.2649009
Kurtosis-0.70198715
Mean5330.0794
Median Absolute Deviation (MAD)72
Skewness0.82692304
Sum335795
Variance45454863
MonotonicityNot monotonic
2024-04-06T20:07:55.333394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 3
 
4.8%
34 2
 
3.2%
4 2
 
3.2%
32 2
 
3.2%
2 2
 
3.2%
59 1
 
1.6%
91 1
 
1.6%
13651 1
 
1.6%
17625 1
 
1.6%
18699 1
 
1.6%
Other values (47) 47
74.6%
ValueCountFrequency (%)
2 2
3.2%
3 3
4.8%
4 2
3.2%
5 1
 
1.6%
7 1
 
1.6%
11 1
 
1.6%
15 1
 
1.6%
23 1
 
1.6%
24 1
 
1.6%
25 1
 
1.6%
ValueCountFrequency (%)
22461 1
1.6%
19160 1
1.6%
18699 1
1.6%
17625 1
1.6%
17124 1
1.6%
16229 1
1.6%
15547 1
1.6%
14559 1
1.6%
13757 1
1.6%
13651 1
1.6%

전체_기타아동수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2865.3175
Minimum492
Maximum4986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T20:07:55.548898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum492
5-th percentile519.4
Q11405.5
median3216
Q33995
95-th percentile4695.6
Maximum4986
Range4494
Interquartile range (IQR)2589.5

Descriptive statistics

Standard deviation1458.9524
Coefficient of variation (CV)0.50917652
Kurtosis-1.1040671
Mean2865.3175
Median Absolute Deviation (MAD)1007
Skewness-0.51636833
Sum180515
Variance2128542
MonotonicityNot monotonic
2024-04-06T20:07:55.803999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
733 1
 
1.6%
2306 1
 
1.6%
949 1
 
1.6%
532 1
 
1.6%
1034 1
 
1.6%
2921 1
 
1.6%
3603 1
 
1.6%
4268 1
 
1.6%
4709 1
 
1.6%
3683 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
492 1
1.6%
515 1
1.6%
516 1
1.6%
518 1
1.6%
532 1
1.6%
533 1
1.6%
539 1
1.6%
548 1
1.6%
563 1
1.6%
612 1
1.6%
ValueCountFrequency (%)
4986 1
1.6%
4959 1
1.6%
4820 1
1.6%
4709 1
1.6%
4575 1
1.6%
4517 1
1.6%
4491 1
1.6%
4442 1
1.6%
4411 1
1.6%
4374 1
1.6%

Interactions

2024-04-06T20:07:50.132836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:43.444297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:44.950354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.055389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.056686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.063660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.143928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:50.308478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:43.654634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.108032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.213462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.221935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.224440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.302370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:50.446064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:43.809858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.309779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.372775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.363774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.400012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.431998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:50.659827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:43.965028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.473068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.521406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.509436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.578519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.571239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:50.807893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:44.138950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.624052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.678440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.666616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.722513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.718957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:50.969912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:44.657491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.755877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.811816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.808671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:48.887865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.856357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:51.174070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:44.799612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:45.881477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:46.932772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:47.937569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.011565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:07:49.981271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T20:07:55.964201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도만나이만나이명칭전체_아동수전체_국공립아동수전체_민간아동수전체_가정아동수전체_기타아동수
통계연도1.0000.0000.0000.0000.0000.0000.0000.000
만나이0.0001.0001.0000.8550.7880.8530.6050.828
만나이명칭0.0001.0001.0000.8550.7880.8530.6050.828
전체_아동수0.0000.8550.8551.0000.7580.8920.8490.841
전체_국공립아동수0.0000.7880.7880.7581.0000.7850.7740.617
전체_민간아동수0.0000.8530.8530.8920.7851.0000.7300.726
전체_가정아동수0.0000.6050.6050.8490.7740.7301.0000.000
전체_기타아동수0.0000.8280.8280.8410.6170.7260.0001.000
2024-04-06T20:07:56.222906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도만나이전체_아동수전체_국공립아동수전체_민간아동수전체_가정아동수전체_기타아동수만나이명칭
통계연도1.0000.000-0.2370.270-0.413-0.253-0.0240.000
만나이0.0001.000-0.408-0.222-0.254-0.891-0.1141.000
전체_아동수-0.237-0.4081.0000.7230.9300.6870.8640.671
전체_국공립아동수0.270-0.2220.7231.0000.6190.2930.8500.546
전체_민간아동수-0.413-0.2540.9300.6191.0000.5650.8320.642
전체_가정아동수-0.253-0.8910.6870.2930.5651.0000.3410.366
전체_기타아동수-0.024-0.1140.8640.8500.8320.3411.0000.627
만나이명칭0.0001.0000.6710.5460.6420.3660.6271.000

Missing values

2024-04-06T20:07:51.421860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T20:07:51.738992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

통계연도만나이만나이명칭전체_아동수전체_국공립아동수전체_민간아동수전체_가정아동수전체_기타아동수
0202200세19768758244636990733
1202255세21473117557397152306
2202244세20503110556782282638
320226방과후 (6세이상)11924262435518
4202233세24994135258063463360
5202222세42724208121153662974079
6202211세3677316814859578773487
7202100세18479666640387163612
820216방과후 (6세이상)13124642814563
9202155세25253133688915322938
통계연도만나이만나이명칭전체_아동수전체_국공립아동수전체_민간아동수전체_가정아동수전체_기타아동수
53201533세4125913351234742654169
54201522세655741294730986171244517
55201500세211701876538313419492
56201411세54000804720473224613019
5720146방과후 (6세이상)3383108354741749
58201455세278491150013471392839
59201444세303751209715006563216
60201433세4251112692252523444223
61201422세641711187131779162294292
62201400세211431746512513757515