Overview

Dataset statistics

Number of variables13
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory118.1 B

Variable types

Numeric12
Categorical1

Dataset

Description통계연도,만나이,만나이명칭,전체아동수_남,국공립아동수_남,민간아동수_남,가정아동수_남,기타아동수_남,전체아동수_여,국공립아동수_여,민간아동수_여,가정아동수_여,기타아동수_여
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15452/S/1/datasetView.do

Alerts

만나이 is highly overall correlated with 가정아동수_남 and 2 other fieldsHigh correlation
전체아동수_남 is highly overall correlated with 국공립아동수_남 and 9 other fieldsHigh correlation
국공립아동수_남 is highly overall correlated with 전체아동수_남 and 7 other fieldsHigh correlation
민간아동수_남 is highly overall correlated with 전체아동수_남 and 9 other fieldsHigh correlation
가정아동수_남 is highly overall correlated with 만나이 and 5 other fieldsHigh correlation
기타아동수_남 is highly overall correlated with 전체아동수_남 and 7 other fieldsHigh correlation
전체아동수_여 is highly overall correlated with 전체아동수_남 and 9 other fieldsHigh correlation
국공립아동수_여 is highly overall correlated with 전체아동수_남 and 7 other fieldsHigh correlation
민간아동수_여 is highly overall correlated with 전체아동수_남 and 9 other fieldsHigh correlation
가정아동수_여 is highly overall correlated with 만나이 and 5 other fieldsHigh correlation
기타아동수_여 is highly overall correlated with 전체아동수_남 and 7 other fieldsHigh correlation
만나이명칭 is highly overall correlated with 만나이 and 8 other fieldsHigh correlation
전체아동수_남 has unique valuesUnique
기타아동수_남 has unique valuesUnique
전체아동수_여 has unique valuesUnique
국공립아동수_여 has unique valuesUnique
만나이 has 9 (14.3%) zerosZeros

Reproduction

Analysis started2024-04-06 10:47:51.782994
Analysis finished2024-04-06 10:48:17.437288
Duration25.65 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
2024-04-06T19:48:17.550023image/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
2024-04-06T19:48:17.874658image/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
2024-04-06T19:48:18.098014image/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
2024-04-06T19:48:18.273234image/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
5세
4세
방과후 (6세이상)
3세
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

2024-04-06T19:48:18.565662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:48:18.799346image/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%

전체아동수_남
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15908.984
Minimum657
Maximum33642
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:19.039602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum657
5-th percentile1044.3
Q110867
median14944
Q322047
95-th percentile30946.2
Maximum33642
Range32985
Interquartile range (IQR)11180

Descriptive statistics

Standard deviation8737.0831
Coefficient of variation (CV)0.54919177
Kurtosis-0.48376365
Mean15908.984
Median Absolute Deviation (MAD)5066
Skewness0.0056565947
Sum1002266
Variance76336621
MonotonicityNot monotonic
2024-04-06T19:48:19.283191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10297 1
 
1.6%
11047 1
 
1.6%
1272 1
 
1.6%
10738 1
 
1.6%
1318 1
 
1.6%
14576 1
 
1.6%
16905 1
 
1.6%
19827 1
 
1.6%
30964 1
 
1.6%
26402 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
657 1
1.6%
712 1
1.6%
832 1
1.6%
1019 1
1.6%
1272 1
1.6%
1318 1
1.6%
1490 1
1.6%
1561 1
1.6%
1712 1
1.6%
9661 1
1.6%
ValueCountFrequency (%)
33642 1
1.6%
32779 1
1.6%
30996 1
1.6%
30964 1
1.6%
30786 1
1.6%
29342 1
1.6%
27792 1
1.6%
26402 1
1.6%
25543 1
1.6%
25306 1
1.6%

국공립아동수_남
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5587.7302
Minimum253
Maximum10852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:19.532007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum253
5-th percentile434.8
Q13375
median6694
Q37384
95-th percentile10205.5
Maximum10852
Range10599
Interquartile range (IQR)4009

Descriptive statistics

Standard deviation3035.4588
Coefficient of variation (CV)0.54323647
Kurtosis-0.7787381
Mean5587.7302
Median Absolute Deviation (MAD)1499
Skewness-0.52278622
Sum352027
Variance9214010.3
MonotonicityNot monotonic
2024-04-06T19:48:20.136611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
549 2
 
3.2%
3974 1
 
1.6%
7242 1
 
1.6%
1648 1
 
1.6%
583 1
 
1.6%
6716 1
 
1.6%
7368 1
 
1.6%
7433 1
 
1.6%
8240 1
 
1.6%
6145 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
253 1
1.6%
270 1
1.6%
331 1
1.6%
424 1
1.6%
532 1
1.6%
549 2
3.2%
583 1
1.6%
597 1
1.6%
927 1
1.6%
987 1
1.6%
ValueCountFrequency (%)
10852 1
1.6%
10671 1
1.6%
10401 1
1.6%
10286 1
1.6%
9481 1
1.6%
8704 1
1.6%
8522 1
1.6%
8429 1
1.6%
8323 1
1.6%
8240 1
1.6%

민간아동수_남
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6092.1587
Minimum133
Maximum16188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:20.445665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum133
5-th percentile165.3
Q12827
median6005
Q38476.5
95-th percentile13345.7
Maximum16188
Range16055
Interquartile range (IQR)5649.5

Descriptive statistics

Standard deviation4117.9165
Coefficient of variation (CV)0.67593716
Kurtosis-0.25802674
Mean6092.1587
Median Absolute Deviation (MAD)2976
Skewness0.47369872
Sum383806
Variance16957236
MonotonicityNot monotonic
2024-04-06T19:48:20.780044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
155 2
 
3.2%
2307 1
 
1.6%
3033 1
 
1.6%
2835 1
 
1.6%
224 1
 
1.6%
6320 1
 
1.6%
7654 1
 
1.6%
10121 1
 
1.6%
13383 1
 
1.6%
9348 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
133 1
1.6%
155 2
3.2%
160 1
1.6%
213 1
1.6%
224 1
1.6%
238 1
1.6%
250 1
1.6%
288 1
1.6%
2081 1
1.6%
2170 1
1.6%
ValueCountFrequency (%)
16188 1
1.6%
15897 1
1.6%
13763 1
1.6%
13383 1
1.6%
13010 1
1.6%
12467 1
1.6%
12410 1
1.6%
12138 1
1.6%
10688 1
1.6%
10626 1
1.6%

가정아동수_남
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2746.9048
Minimum1
Maximum11438
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:21.079085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q117
median40
Q35555.5
95-th percentile8996.2
Maximum11438
Range11437
Interquartile range (IQR)5538.5

Descriptive statistics

Standard deviation3465.3319
Coefficient of variation (CV)1.2615406
Kurtosis-0.74188748
Mean2746.9048
Median Absolute Deviation (MAD)39
Skewness0.81366878
Sum173055
Variance12008525
MonotonicityNot monotonic
2024-04-06T19:48:21.336744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 4
 
6.3%
17 3
 
4.8%
21 3
 
4.8%
1 3
 
4.8%
32 2
 
3.2%
5 2
 
3.2%
13 2
 
3.2%
40 1
 
1.6%
6938 1
 
1.6%
9029 1
 
1.6%
Other values (41) 41
65.1%
ValueCountFrequency (%)
1 3
4.8%
2 4
6.3%
3 1
 
1.6%
4 1
 
1.6%
5 2
3.2%
10 1
 
1.6%
13 2
3.2%
14 1
 
1.6%
17 3
4.8%
18 1
 
1.6%
ValueCountFrequency (%)
11438 1
1.6%
9854 1
1.6%
9655 1
1.6%
9029 1
1.6%
8701 1
1.6%
8310 1
1.6%
8140 1
1.6%
7451 1
1.6%
7174 1
1.6%
6954 1
1.6%

기타아동수_남
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1482.1905
Minimum236
Maximum2540
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:21.593357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236
5-th percentile264.3
Q1715.5
median1677
Q32090
95-th percentile2398.1
Maximum2540
Range2304
Interquartile range (IQR)1374.5

Descriptive statistics

Standard deviation757.30571
Coefficient of variation (CV)0.51093683
Kurtosis-1.1216715
Mean1482.1905
Median Absolute Deviation (MAD)534
Skewness-0.5285097
Sum93378
Variance573511.93
MonotonicityNot monotonic
2024-04-06T19:48:21.816977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
370 1
 
1.6%
1175 1
 
1.6%
508 1
 
1.6%
262 1
 
1.6%
509 1
 
1.6%
1527 1
 
1.6%
1847 1
 
1.6%
2233 1
 
1.6%
2403 1
 
1.6%
1880 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
236 1
1.6%
262 1
1.6%
263 1
1.6%
264 1
1.6%
267 1
1.6%
284 1
1.6%
287 1
1.6%
290 1
1.6%
292 1
1.6%
301 1
1.6%
ValueCountFrequency (%)
2540 1
1.6%
2534 1
1.6%
2483 1
1.6%
2403 1
1.6%
2354 1
1.6%
2350 1
1.6%
2330 1
1.6%
2318 1
1.6%
2263 1
1.6%
2258 1
1.6%

전체아동수_여
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14947.587
Minimum535
Maximum31932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:22.094161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum535
5-th percentile883.9
Q110020.5
median14072
Q320493.5
95-th percentile29675.4
Maximum31932
Range31397
Interquartile range (IQR)10473

Descriptive statistics

Standard deviation8344.0402
Coefficient of variation (CV)0.55821986
Kurtosis-0.46586544
Mean14947.587
Median Absolute Deviation (MAD)4838
Skewness0.047428973
Sum941698
Variance69623006
MonotonicityNot monotonic
2024-04-06T19:48:22.352881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9471 1
 
1.6%
10426 1
 
1.6%
973 1
 
1.6%
9924 1
 
1.6%
1125 1
 
1.6%
13810 1
 
1.6%
15949 1
 
1.6%
18586 1
 
1.6%
29722 1
 
1.6%
25021 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
535 1
1.6%
600 1
1.6%
707 1
1.6%
874 1
1.6%
973 1
1.6%
1125 1
1.6%
1275 1
1.6%
1453 1
1.6%
1671 1
1.6%
8624 1
1.6%
ValueCountFrequency (%)
31932 1
1.6%
31392 1
1.6%
29725 1
1.6%
29722 1
1.6%
29256 1
1.6%
27991 1
1.6%
26208 1
1.6%
25021 1
1.6%
24134 1
1.6%
23990 1
1.6%

국공립아동수_여
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5230.0794
Minimum173
Maximum9960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:22.693590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173
5-th percentile321.1
Q12921
median6253
Q36900.5
95-th percentile9693.4
Maximum9960
Range9787
Interquartile range (IQR)3979.5

Descriptive statistics

Standard deviation2878.2942
Coefficient of variation (CV)0.5503347
Kurtosis-0.80045462
Mean5230.0794
Median Absolute Deviation (MAD)1346
Skewness-0.5319956
Sum329495
Variance8284577.3
MonotonicityNot monotonic
2024-04-06T19:48:22.971675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3608 1
 
1.6%
5728 1
 
1.6%
367 1
 
1.6%
1624 1
 
1.6%
420 1
 
1.6%
6336 1
 
1.6%
6851 1
 
1.6%
6979 1
 
1.6%
7867 1
 
1.6%
5888 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
173 1
1.6%
194 1
1.6%
230 1
1.6%
316 1
1.6%
367 1
1.6%
420 1
1.6%
464 1
1.6%
481 1
1.6%
534 1
1.6%
819 1
1.6%
ValueCountFrequency (%)
9960 1
1.6%
9955 1
1.6%
9828 1
1.6%
9754 1
1.6%
9148 1
1.6%
8110 1
1.6%
8000 1
1.6%
7883 1
1.6%
7867 1
1.6%
7780 1
1.6%

민간아동수_여
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5751.2063
Minimum110
Maximum15591
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:23.359009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile150.5
Q12618.5
median5531
Q38015
95-th percentile12776.6
Maximum15591
Range15481
Interquartile range (IQR)5396.5

Descriptive statistics

Standard deviation3932.3299
Coefficient of variation (CV)0.68374002
Kurtosis-0.23044414
Mean5751.2063
Median Absolute Deviation (MAD)2858
Skewness0.48951913
Sum362326
Variance15463219
MonotonicityNot monotonic
2024-04-06T19:48:23.625136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6467 2
 
3.2%
2156 1
 
1.6%
6145 1
 
1.6%
2673 1
 
1.6%
179 1
 
1.6%
6068 1
 
1.6%
7319 1
 
1.6%
9521 1
 
1.6%
12836 1
 
1.6%
8734 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
110 1
1.6%
123 1
1.6%
126 1
1.6%
149 1
1.6%
164 1
1.6%
179 1
1.6%
188 1
1.6%
209 1
1.6%
259 1
1.6%
1869 1
1.6%
ValueCountFrequency (%)
15591 1
1.6%
15089 1
1.6%
13192 1
1.6%
12836 1
1.6%
12242 1
1.6%
11813 1
1.6%
11686 1
1.6%
11336 1
1.6%
10271 1
1.6%
9847 1
1.6%

가정아동수_여
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2583.1746
Minimum1
Maximum11023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:23.884535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113.5
median36
Q35183
95-th percentile8578.7
Maximum11023
Range11022
Interquartile range (IQR)5169.5

Descriptive statistics

Standard deviation3277.5381
Coefficient of variation (CV)1.2688024
Kurtosis-0.65716032
Mean2583.1746
Median Absolute Deviation (MAD)35
Skewness0.84198459
Sum162740
Variance10742256
MonotonicityNot monotonic
2024-04-06T19:48:24.207170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7
 
11.1%
25 3
 
4.8%
23 3
 
4.8%
24 2
 
3.2%
15 2
 
3.2%
11 2
 
3.2%
8596 1
 
1.6%
9044 1
 
1.6%
36 1
 
1.6%
31 1
 
1.6%
Other values (40) 40
63.5%
ValueCountFrequency (%)
1 7
11.1%
3 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
9 1
 
1.6%
10 1
 
1.6%
11 2
 
3.2%
12 1
 
1.6%
13 1
 
1.6%
14 1
 
1.6%
ValueCountFrequency (%)
11023 1
1.6%
9306 1
1.6%
9044 1
1.6%
8596 1
1.6%
8423 1
1.6%
7919 1
1.6%
7407 1
1.6%
7108 1
1.6%
6713 1
1.6%
6583 1
1.6%

기타아동수_여
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1383.127
Minimum241
Maximum2446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-06T19:48:24.458323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum241
5-th percentile252
Q1690
median1539
Q31905
95-th percentile2297.5
Maximum2446
Range2205
Interquartile range (IQR)1215

Descriptive statistics

Standard deviation702.26469
Coefficient of variation (CV)0.50773696
Kurtosis-1.0834506
Mean1383.127
Median Absolute Deviation (MAD)473
Skewness-0.49971323
Sum87137
Variance493175.69
MonotonicityNot monotonic
2024-04-06T19:48:24.693144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1394 2
 
3.2%
252 2
 
3.2%
2062 2
 
3.2%
2112 1
 
1.6%
441 1
 
1.6%
270 1
 
1.6%
525 1
 
1.6%
1756 1
 
1.6%
2035 1
 
1.6%
2306 1
 
1.6%
Other values (50) 50
79.4%
ValueCountFrequency (%)
241 1
1.6%
249 1
1.6%
251 1
1.6%
252 2
3.2%
256 1
1.6%
261 1
1.6%
270 1
1.6%
279 1
1.6%
311 1
1.6%
353 1
1.6%
ValueCountFrequency (%)
2446 1
1.6%
2425 1
1.6%
2337 1
1.6%
2306 1
1.6%
2221 1
1.6%
2173 1
1.6%
2167 1
1.6%
2148 1
1.6%
2116 1
1.6%
2112 1
1.6%

Interactions

2024-04-06T19:48:14.841928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:52.536307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.489873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.360361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:58.491521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.046332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.941391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.764247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.631090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.580186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.776353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.862930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.030998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:52.700568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.652584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.553678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:58.777788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.250597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.112508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.914350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.836836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.782737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.951965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.027870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.248274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:52.873987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.814550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.705607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:59.003921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.394675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.262376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.078249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.987569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.945893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:11.141449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.214424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.410887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.042681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.982788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.855628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:59.168677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.578478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.408730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.239074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.155580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:09.111352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:11.359538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.509627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.556273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.232713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.117912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.023253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:59.302294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.713317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.553254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.385817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.309900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:09.246928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:11.523894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.718328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.765117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.419657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.277332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.217663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:59.814528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:01.891363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.724184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.546613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.473709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:09.398523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:11.697674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.862872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:15.907221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.586629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.412561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.402954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:59.948030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.032517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:03.870044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.709967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.624726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:09.930139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:11.858753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:13.995010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:16.040458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.722937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.541960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.542777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:00.098890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.167515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.017333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.853509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.757423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.062298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.004976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:14.140530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:16.194009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:53.874447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.699734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.745239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:00.288913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.313303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.178839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:05.969586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:07.911879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.205906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.197975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:14.292244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:16.377080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.016002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:55.862435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:57.905692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:00.483712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.476116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.331821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.100863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.091710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.340317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.357948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:14.431633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:16.617832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.228160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.035905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:58.101065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:00.701395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.652476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.502005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.295609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.259874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.497343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.549122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:14.592239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:16.763094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:54.361554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:56.197541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:47:58.268530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:00.851711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:02.812090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:04.629285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:06.467278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:08.418757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:10.644766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:12.704872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:48:14.720654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T19:48:24.907619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도만나이만나이명칭전체아동수_남국공립아동수_남민간아동수_남가정아동수_남기타아동수_남전체아동수_여국공립아동수_여민간아동수_여가정아동수_여기타아동수_여
통계연도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
만나이0.0001.0001.0000.8600.7760.8430.6090.8260.8620.8060.8540.6300.795
만나이명칭0.0001.0001.0000.8600.7760.8430.6090.8260.8620.8060.8540.6300.795
전체아동수_남0.0000.8600.8601.0000.7700.8890.8620.8670.9990.7840.9040.8700.846
국공립아동수_남0.0000.7760.7760.7701.0000.7810.7140.5910.7800.9910.7580.7560.648
민간아동수_남0.0000.8430.8430.8890.7811.0000.6970.7190.8840.7910.9990.7380.682
가정아동수_남0.0000.6090.6090.8620.7140.6971.0000.0000.8540.7830.7210.9950.000
기타아동수_남0.0000.8260.8260.8670.5910.7190.0001.0000.8690.6650.7350.0000.978
전체아동수_여0.0000.8620.8620.9990.7800.8840.8540.8691.0000.7860.8990.8730.847
국공립아동수_여0.0000.8060.8060.7840.9910.7910.7830.6650.7861.0000.7880.8200.639
민간아동수_여0.0000.8540.8540.9040.7580.9990.7210.7350.8990.7881.0000.7660.661
가정아동수_여0.0000.6300.6300.8700.7560.7380.9950.0000.8730.8200.7661.0000.000
기타아동수_여0.0000.7950.7950.8460.6480.6820.0000.9780.8470.6390.6610.0001.000
2024-04-06T19:48:25.212204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도만나이전체아동수_남국공립아동수_남민간아동수_남가정아동수_남기타아동수_남전체아동수_여국공립아동수_여민간아동수_여가정아동수_여기타아동수_여만나이명칭
통계연도1.0000.000-0.2330.277-0.413-0.246-0.025-0.2430.270-0.415-0.257-0.0350.000
만나이0.0001.000-0.411-0.218-0.255-0.890-0.116-0.403-0.222-0.253-0.888-0.1191.000
전체아동수_남-0.233-0.4111.0000.7190.9280.6830.8620.9980.7270.9270.6900.8670.680
국공립아동수_남0.277-0.2180.7191.0000.6140.2800.8480.7130.9960.6110.2880.8420.529
민간아동수_남-0.413-0.2550.9280.6141.0000.5610.8300.9350.6220.9990.5610.8360.624
가정아동수_남-0.246-0.8900.6830.2800.5611.0000.3280.6790.2870.5620.9870.3390.370
기타아동수_남-0.025-0.1160.8620.8480.8300.3281.0000.8600.8540.8270.3410.9910.625
전체아동수_여-0.243-0.4030.9980.7130.9350.6790.8601.0000.7220.9340.6850.8660.683
국공립아동수_여0.270-0.2220.7270.9960.6220.2870.8540.7221.0000.6190.2980.8480.570
민간아동수_여-0.415-0.2530.9270.6110.9990.5620.8270.9340.6191.0000.5610.8330.642
가정아동수_여-0.257-0.8880.6900.2880.5610.9870.3410.6850.2980.5611.0000.3460.389
기타아동수_여-0.035-0.1190.8670.8420.8360.3390.9910.8660.8480.8330.3461.0000.578
만나이명칭0.0001.0000.6800.5290.6240.3700.6250.6830.5700.6420.3890.5781.000

Missing values

2024-04-06T19:48:16.945650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T19:48:17.300582image/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

통계연도만나이만나이명칭전체아동수_남국공립아동수_남민간아동수_남가정아동수_남기타아동수_남전체아동수_여국공립아동수_여민간아동수_여가정아동수_여기타아동수_여
0202200세102973974230736463709471360821563344363
1202255세1104760273840511751042657283557101131
2202244세1065457173524171396984953383258111242
320226방과후 (6세이상)65725313342675351731101251
4202233세13091706042442317641190364653819231596
5202222세2227910852600532842138204459960553130131941
6202211세189438704443240121795178308110416338651692
7202100세96613560208137193018818310619573444311
820216방과후 (6세이상)71227015532846001941261279
9202155세13011691645761715021224264524339151436
통계연도만나이만나이명칭전체아동수_남국공립아동수_남민간아동수_남가정아동수_남기타아동수_남전체아동수_여국공립아동수_여민간아동수_여가정아동수_여기타아동수_여
53201533세213696902121381432186198906449113361221983
54201522세33642669415897870123503193262531508984232167
55201500세10996987281969542361017488925646465256
56201411세277924171106261143815572620838769847110231462
5720146방과후 (6세이상)1712549288187416715342593875
58201455세14328596369052114391352155376566181400
59201444세15576618876783316771479959097328231539
60201433세219696572130101762211205426120122421682012
61201422세32779605116188831022303139258201559179192062
62201400세11026927266271742631011781924636583252