Overview

Dataset statistics

Number of variables11
Number of observations234
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.5 KiB
Average record size in memory98.6 B

Variable types

Numeric10
Categorical1

Dataset

Description통계연도,자치구코드,자치구명,정원합계,정원_국공립,정원_사회복지법인,정원_법인단체등,정원_민간,정원_가정,정원_부모협동,정원_직장
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15458/S/1/datasetView.do

Alerts

자치구코드 is highly overall correlated with 자치구명High correlation
정원합계 is highly overall correlated with 정원_국공립 and 3 other fieldsHigh correlation
정원_국공립 is highly overall correlated with 정원합계High correlation
정원_사회복지법인 is highly overall correlated with 자치구명High correlation
정원_민간 is highly overall correlated with 정원합계 and 1 other fieldsHigh correlation
정원_가정 is highly overall correlated with 정원합계 and 1 other fieldsHigh correlation
정원_부모협동 is highly overall correlated with 자치구명High correlation
자치구명 is highly overall correlated with 자치구코드 and 3 other fieldsHigh correlation
정원_사회복지법인 has 91 (38.9%) zerosZeros
정원_법인단체등 has 17 (7.3%) zerosZeros
정원_부모협동 has 67 (28.6%) zerosZeros

Reproduction

Analysis started2024-04-06 11:38:56.445489
Analysis finished2024-04-06 11:39:17.594099
Duration21.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Real number (ℝ)

Distinct9
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:17.697827image/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 deviation2.5875237
Coefficient of variation (CV)0.0012822219
Kurtosis-1.2306062
Mean2018
Median Absolute Deviation (MAD)2
Skewness0
Sum472212
Variance6.695279
MonotonicityDecreasing
2024-04-06T20:39:17.899891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2022 26
11.1%
2021 26
11.1%
2020 26
11.1%
2019 26
11.1%
2018 26
11.1%
2017 26
11.1%
2016 26
11.1%
2015 26
11.1%
2014 26
11.1%
ValueCountFrequency (%)
2014 26
11.1%
2015 26
11.1%
2016 26
11.1%
2017 26
11.1%
2018 26
11.1%
2019 26
11.1%
2020 26
11.1%
2021 26
11.1%
2022 26
11.1%
ValueCountFrequency (%)
2022 26
11.1%
2021 26
11.1%
2020 26
11.1%
2019 26
11.1%
2018 26
11.1%
2017 26
11.1%
2016 26
11.1%
2015 26
11.1%
2014 26
11.1%

자치구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11400.577
Minimum11000
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:18.104754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile11110
Q111230
median11395
Q311560
95-th percentile11710
Maximum11740
Range740
Interquartile range (IQR)330

Descriptive statistics

Standard deviation199.94309
Coefficient of variation (CV)0.01753798
Kurtosis-1.0021198
Mean11400.577
Median Absolute Deviation (MAD)165
Skewness-0.047847509
Sum2667735
Variance39977.241
MonotonicityNot monotonic
2024-04-06T20:39:18.353066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
11000 9
 
3.8%
11380 9
 
3.8%
11110 9
 
3.8%
11140 9
 
3.8%
11170 9
 
3.8%
11200 9
 
3.8%
11215 9
 
3.8%
11230 9
 
3.8%
11260 9
 
3.8%
11290 9
 
3.8%
Other values (16) 144
61.5%
ValueCountFrequency (%)
11000 9
3.8%
11110 9
3.8%
11140 9
3.8%
11170 9
3.8%
11200 9
3.8%
11215 9
3.8%
11230 9
3.8%
11260 9
3.8%
11290 9
3.8%
11305 9
3.8%
ValueCountFrequency (%)
11740 9
3.8%
11710 9
3.8%
11680 9
3.8%
11650 9
3.8%
11620 9
3.8%
11590 9
3.8%
11560 9
3.8%
11545 9
3.8%
11530 9
3.8%
11500 9
3.8%

자치구명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
 
9
송파
 
9
강남
 
9
서초
 
9
관악
 
9
Other values (21)
189 

Length

Max length3
Median length2
Mean length2.0769231
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row송파
3rd row강남
4th row서초
5th row관악

Common Values

ValueCountFrequency (%)
9
 
3.8%
송파 9
 
3.8%
강남 9
 
3.8%
서초 9
 
3.8%
관악 9
 
3.8%
동작 9
 
3.8%
영등포 9
 
3.8%
금천 9
 
3.8%
구로 9
 
3.8%
강서 9
 
3.8%
Other values (16) 144
61.5%

Length

2024-04-06T20:39:18.574326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9
 
3.8%
송파 9
 
3.8%
중구 9
 
3.8%
용산 9
 
3.8%
성동 9
 
3.8%
광진 9
 
3.8%
동대문 9
 
3.8%
중랑 9
 
3.8%
성북 9
 
3.8%
강북 9
 
3.8%
Other values (16) 144
61.5%

정원합계
Real number (ℝ)

HIGH CORRELATION 

Distinct232
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19750.385
Minimum4039
Maximum275464
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:18.830275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4039
5-th percentile4701.3
Q18218.25
median10243.5
Q312544
95-th percentile17549.15
Maximum275464
Range271425
Interquartile range (IQR)4325.75

Descriptive statistics

Standard deviation47732.431
Coefficient of variation (CV)2.4167849
Kurtosis21.793383
Mean19750.385
Median Absolute Deviation (MAD)2213
Skewness4.8331342
Sum4621590
Variance2.278385 × 109
MonotonicityNot monotonic
2024-04-06T20:39:19.150842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5554 2
 
0.9%
11123 2
 
0.9%
223628 1
 
0.4%
11827 1
 
0.4%
9413 1
 
0.4%
9203 1
 
0.4%
8243 1
 
0.4%
4279 1
 
0.4%
4702 1
 
0.4%
7311 1
 
0.4%
Other values (222) 222
94.9%
ValueCountFrequency (%)
4039 1
0.4%
4067 1
0.4%
4109 1
0.4%
4118 1
0.4%
4136 1
0.4%
4279 1
0.4%
4305 1
0.4%
4394 1
0.4%
4409 1
0.4%
4459 1
0.4%
ValueCountFrequency (%)
275464 1
0.4%
274132 1
0.4%
270231 1
0.4%
268100 1
0.4%
263157 1
0.4%
254538 1
0.4%
245863 1
0.4%
235682 1
0.4%
223628 1
0.4%
17967 1
0.4%

정원_국공립
Real number (ℝ)

HIGH CORRELATION 

Distinct222
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6732.1197
Minimum1535
Maximum103922
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:19.398962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1535
5-th percentile1801.05
Q12733.25
median3560.5
Q34550.25
95-th percentile5800.95
Maximum103922
Range102387
Interquartile range (IQR)1817

Descriptive statistics

Standard deviation16457.221
Coefficient of variation (CV)2.4445824
Kurtosis23.998333
Mean6732.1197
Median Absolute Deviation (MAD)935.5
Skewness5.0029431
Sum1575316
Variance2.7084012 × 108
MonotonicityNot monotonic
2024-04-06T20:39:19.632757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4762 2
 
0.9%
5405 2
 
0.9%
1850 2
 
0.9%
2216 2
 
0.9%
2812 2
 
0.9%
4486 2
 
0.9%
4565 2
 
0.9%
3550 2
 
0.9%
1970 2
 
0.9%
4467 2
 
0.9%
Other values (212) 214
91.5%
ValueCountFrequency (%)
1535 1
0.4%
1601 1
0.4%
1654 1
0.4%
1672 1
0.4%
1686 1
0.4%
1750 1
0.4%
1765 1
0.4%
1766 1
0.4%
1781 1
0.4%
1786 1
0.4%
ValueCountFrequency (%)
103922 1
0.4%
103678 1
0.4%
101037 1
0.4%
96595 1
0.4%
89293 1
0.4%
81612 1
0.4%
74851 1
0.4%
70561 1
0.4%
66109 1
0.4%
6581 1
0.4%

정원_사회복지법인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.80342
Minimum0
Maximum2464
Zeros91
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:19.860533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median80.5
Q3123
95-th percentile311
Maximum2464
Range2464
Interquartile range (IQR)123

Descriptive statistics

Standard deviation391.89968
Coefficient of variation (CV)2.4993057
Kurtosis21.436886
Mean156.80342
Median Absolute Deviation (MAD)80.5
Skewness4.6354599
Sum36692
Variance153585.36
MonotonicityNot monotonic
2024-04-06T20:39:20.104705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 91
38.9%
223 9
 
3.8%
87 9
 
3.8%
33 9
 
3.8%
89 9
 
3.8%
123 8
 
3.4%
74 8
 
3.4%
79 7
 
3.0%
103 6
 
2.6%
311 5
 
2.1%
Other values (38) 73
31.2%
ValueCountFrequency (%)
0 91
38.9%
33 9
 
3.8%
39 1
 
0.4%
63 1
 
0.4%
74 8
 
3.4%
79 7
 
3.0%
82 3
 
1.3%
83 1
 
0.4%
84 1
 
0.4%
87 9
 
3.8%
ValueCountFrequency (%)
2464 1
0.4%
2367 1
0.4%
2327 1
0.4%
2266 1
0.4%
1948 1
0.4%
1890 1
0.4%
1861 1
0.4%
1690 1
0.4%
1533 1
0.4%
344 1
0.4%

정원_법인단체등
Real number (ℝ)

ZEROS 

Distinct92
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483.4188
Minimum0
Maximum8089
Zeros17
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:20.428031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1101
median202
Q3356
95-th percentile1054.1
Maximum8089
Range8089
Interquartile range (IQR)255

Descriptive statistics

Standard deviation1200.9096
Coefficient of variation (CV)2.4842013
Kurtosis22.553168
Mean483.4188
Median Absolute Deviation (MAD)120
Skewness4.769092
Sum113120
Variance1442183.9
MonotonicityNot monotonic
2024-04-06T20:39:20.705088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
7.3%
237 9
 
3.8%
204 9
 
3.8%
101 9
 
3.8%
202 9
 
3.8%
156 7
 
3.0%
276 7
 
3.0%
149 6
 
2.6%
20 6
 
2.6%
74 5
 
2.1%
Other values (82) 150
64.1%
ValueCountFrequency (%)
0 17
7.3%
20 6
 
2.6%
27 1
 
0.4%
40 2
 
0.9%
43 3
 
1.3%
49 3
 
1.3%
63 2
 
0.9%
66 3
 
1.3%
67 3
 
1.3%
70 1
 
0.4%
ValueCountFrequency (%)
8089 1
0.4%
7475 1
0.4%
7035 1
0.4%
6366 1
0.4%
5909 1
0.4%
5878 1
0.4%
5427 2
0.9%
4954 1
0.4%
1282 1
0.4%
1136 1
0.4%

정원_민간
Real number (ℝ)

HIGH CORRELATION 

Distinct228
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7655.9829
Minimum193
Maximum126378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:20.939228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum193
5-th percentile458
Q12502.5
median3854.5
Q35544.5
95-th percentile10324.7
Maximum126378
Range126185
Interquartile range (IQR)3042

Descriptive statistics

Standard deviation18998.979
Coefficient of variation (CV)2.4815858
Kurtosis25.25841
Mean7655.9829
Median Absolute Deviation (MAD)1473
Skewness5.0688388
Sum1791500
Variance3.6096119 × 108
MonotonicityNot monotonic
2024-04-06T20:39:21.303642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
458 3
 
1.3%
237 3
 
1.3%
419 2
 
0.9%
344 2
 
0.9%
65662 1
 
0.4%
4636 1
 
0.4%
3968 1
 
0.4%
5265 1
 
0.4%
2199 1
 
0.4%
1432 1
 
0.4%
Other values (218) 218
93.2%
ValueCountFrequency (%)
193 1
 
0.4%
237 3
1.3%
272 1
 
0.4%
344 2
0.9%
370 1
 
0.4%
419 2
0.9%
442 1
 
0.4%
458 3
1.3%
527 1
 
0.4%
759 1
 
0.4%
ValueCountFrequency (%)
126378 1
0.4%
122831 1
0.4%
117842 1
0.4%
112384 1
0.4%
103278 1
0.4%
91892 1
0.4%
82308 1
0.4%
73175 1
0.4%
65662 1
0.4%
11615 1
0.4%

정원_가정
Real number (ℝ)

HIGH CORRELATION 

Distinct221
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3276.0085
Minimum39
Maximum58623
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:22.011383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile214.75
Q1977
median1524
Q32279.5
95-th percentile5342.95
Maximum58623
Range58584
Interquartile range (IQR)1302.5

Descriptive statistics

Standard deviation8237.5398
Coefficient of variation (CV)2.514505
Kurtosis27.085524
Mean3276.0085
Median Absolute Deviation (MAD)605.5
Skewness5.1867444
Sum766586
Variance67857062
MonotonicityNot monotonic
2024-04-06T20:39:22.211116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
977 3
 
1.3%
859 2
 
0.9%
70 2
 
0.9%
884 2
 
0.9%
50 2
 
0.9%
1006 2
 
0.9%
1698 2
 
0.9%
148 2
 
0.9%
2853 2
 
0.9%
979 2
 
0.9%
Other values (211) 213
91.0%
ValueCountFrequency (%)
39 1
0.4%
50 2
0.9%
70 2
0.9%
90 1
0.4%
130 1
0.4%
148 2
0.9%
166 1
0.4%
185 1
0.4%
205 1
0.4%
220 1
0.4%
ValueCountFrequency (%)
58623 1
0.4%
55916 1
0.4%
51025 1
0.4%
46895 1
0.4%
42957 1
0.4%
38168 1
0.4%
33972 1
0.4%
29967 1
0.4%
25770 1
0.4%
6541 1
0.4%

정원_부모협동
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.273504
Minimum0
Maximum1042
Zeros67
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:22.460018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q349.75
95-th percentile153
Maximum1042
Range1042
Interquartile range (IQR)49.75

Descriptive statistics

Standard deviation174.05944
Coefficient of variation (CV)2.4768857
Kurtosis20.126908
Mean70.273504
Median Absolute Deviation (MAD)30
Skewness4.5418599
Sum16444
Variance30296.689
MonotonicityNot monotonic
2024-04-06T20:39:22.691963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 67
28.6%
49 17
 
7.3%
20 16
 
6.8%
16 11
 
4.7%
82 9
 
3.8%
153 9
 
3.8%
39 9
 
3.8%
33 8
 
3.4%
37 7
 
3.0%
30 7
 
3.0%
Other values (33) 74
31.6%
ValueCountFrequency (%)
0 67
28.6%
14 5
 
2.1%
16 11
 
4.7%
19 1
 
0.4%
20 16
 
6.8%
26 4
 
1.7%
27 6
 
2.6%
29 6
 
2.6%
30 7
 
3.0%
31 1
 
0.4%
ValueCountFrequency (%)
1042 1
 
0.4%
1038 1
 
0.4%
973 1
 
0.4%
928 1
 
0.4%
903 1
 
0.4%
859 1
 
0.4%
852 1
 
0.4%
822 1
 
0.4%
805 1
 
0.4%
153 9
3.8%

정원_직장
Real number (ℝ)

Distinct142
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1375.7778
Minimum52
Maximum21226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-06T20:39:22.938826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum52
5-th percentile101
Q1264
median424
Q31127.75
95-th percentile2897.15
Maximum21226
Range21174
Interquartile range (IQR)863.75

Descriptive statistics

Standard deviation3420.4546
Coefficient of variation (CV)2.486197
Kurtosis21.852014
Mean1375.7778
Median Absolute Deviation (MAD)250
Skewness4.7135879
Sum321932
Variance11699510
MonotonicityNot monotonic
2024-04-06T20:39:23.194789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 7
 
3.0%
524 7
 
3.0%
132 6
 
2.6%
264 6
 
2.6%
360 6
 
2.6%
174 6
 
2.6%
384 5
 
2.1%
526 4
 
1.7%
270 4
 
1.7%
277 4
 
1.7%
Other values (132) 179
76.5%
ValueCountFrequency (%)
52 2
 
0.9%
70 2
 
0.9%
76 4
1.7%
101 7
3.0%
108 1
 
0.4%
132 6
2.6%
138 1
 
0.4%
143 1
 
0.4%
145 1
 
0.4%
158 4
1.7%
ValueCountFrequency (%)
21226 1
0.4%
20642 1
0.4%
20285 1
0.4%
19073 1
0.4%
18734 1
0.4%
17649 1
0.4%
16248 1
0.4%
14130 1
0.4%
12979 1
0.4%
3104 1
0.4%

Interactions

2024-04-06T20:39:15.551424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:58.654677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:01.208405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.530416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.184551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:06.847446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:08.590206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.316473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.947757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.957210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.697169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:58.867002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:01.458002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.711991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.356079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.040003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:08.809872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.502018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:12.171190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.107772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.855341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:59.053678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:02.048375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.916635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.505310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.265866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.003112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.671995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:12.808550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.280764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.984588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:59.344640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:02.206665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.054206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.671061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.507146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.156149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.809896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:12.951885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.442415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.119741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:59.600021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:02.364209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.218144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.827080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.670698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.340019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.949846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.087297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.599290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.272053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:38:59.767804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:02.532090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.359807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.995479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.815588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.509668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.126149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.239194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.753083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.486186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:00.008153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:02.813028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.530513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:06.216818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:07.984783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.697894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.332185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.391872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:14.924070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.635712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:00.317577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.010375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.714938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:06.417969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:08.142747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:09.864025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.521041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.532459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.083148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.804882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:00.560728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.171207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:04.891279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:06.548646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:08.307726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.025707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.679314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.678445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.245777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:16.947399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:00.832750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:03.317070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:05.039697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:06.684256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:08.451971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:10.172215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:11.816714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:13.833261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:39:15.423481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T20:39:23.376485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도자치구코드자치구명정원합계정원_국공립정원_사회복지법인정원_법인단체등정원_민간정원_가정정원_부모협동정원_직장
통계연도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
자치구코드0.0001.0001.000NaNNaN0.4710.373NaN0.1770.3960.297
자치구명0.0001.0001.0000.8440.6730.8600.7820.6030.5780.8480.767
정원합계0.000NaN0.8441.0000.8590.8681.0001.0001.0000.7241.000
정원_국공립0.000NaN0.6730.8591.0000.9640.8970.8740.9360.9370.897
정원_사회복지법인0.0000.4710.8600.8680.9641.0000.8160.8860.8560.9670.816
정원_법인단체등0.0000.3730.7821.0000.8970.8161.0000.9760.9560.7350.995
정원_민간0.000NaN0.6031.0000.8740.8860.9761.0000.9700.7850.976
정원_가정0.0000.1770.5781.0000.9360.8560.9560.9701.0000.8300.956
정원_부모협동0.0000.3960.8480.7240.9370.9670.7350.7850.8301.0000.735
정원_직장0.0000.2970.7671.0000.8970.8160.9950.9760.9560.7351.000
2024-04-06T20:39:23.635492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계연도자치구코드정원합계정원_국공립정원_사회복지법인정원_법인단체등정원_민간정원_가정정원_부모협동정원_직장자치구명
통계연도1.0000.000-0.2020.455-0.129-0.130-0.358-0.3940.0210.1670.000
자치구코드0.0001.0000.4220.3570.040-0.2100.2320.2680.1480.1170.964
정원합계-0.2020.4221.0000.5200.4540.0620.8320.8660.3580.0140.629
정원_국공립0.4550.3570.5201.0000.066-0.0170.1530.3670.3530.3220.381
정원_사회복지법인-0.1290.0400.4540.0661.0000.3100.3730.4560.1460.1100.596
정원_법인단체등-0.130-0.2100.062-0.0170.3101.0000.0770.0480.1310.1120.472
정원_민간-0.3580.2320.8320.1530.3730.0771.0000.7540.290-0.3260.308
정원_가정-0.3940.2680.8660.3670.4560.0480.7541.0000.294-0.0720.261
정원_부모협동0.0210.1480.3580.3530.1460.1310.2900.2941.0000.0930.579
정원_직장0.1670.1170.0140.3220.1100.112-0.326-0.0720.0931.0000.455
자치구명0.0000.9640.6290.3810.5960.4720.3080.2610.5790.4551.000

Missing values

2024-04-06T20:39:17.155625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T20:39:17.472577image/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

통계연도자치구코드자치구명정원합계정원_국공립정원_사회복지법인정원_법인단체등정원_민간정원_가정정원_부모협동정원_직장
020221100022362810367815334954656622577080521226
1202211710송파15563658110711649162288481507
2202211680강남107255150002472683692351
3202211650서초10016540802371372663742262
4202211620관악898847318229922909050681
5202211590동작756142110101194094149319
6202211560영등포11461453679662499117703104
7202211545금천6932296522357323993880384
8202211530구로1159553312292953548165659477
9202211500강서1404354051733764816219782994
통계연도자치구코드자치구명정원합계정원_국공립정원_사회복지법인정원_법인단체등정원_민간정원_가정정원_부모협동정원_직장
224201411380은평1602816721313321161521633976
225201411350노원151083079228204905654130305
226201411320도봉1115117863374606230774970
227201411305강북96951750153216606014372752
228201411290성북12560276915112825195298337143
229201411260중랑123892768114276686722060158
230201411230동대문969726990204446220550277
231201411215광진9674201801835764149285132
232201411200성동821035500202251316400305
233201411170용산5670153589453200397933578