Overview

Dataset statistics

Number of variables13
Number of observations165
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.8 KiB
Average record size in memory116.8 B

Variable types

Numeric12
Categorical1

Dataset

Description등록장애인 집계현황(장애유형별, 연령별)
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=YIN8M7Y2PO0IDIVHI2OE24856941&infSeq=1

Alerts

총계(명) is highly overall correlated with 10세미만장애인수(0-9세)(명) and 10 other fieldsHigh correlation
10세미만장애인수(0-9세)(명) is highly overall correlated with 총계(명) and 4 other fieldsHigh correlation
10대장애인수(10-19세)(명) is highly overall correlated with 총계(명) and 4 other fieldsHigh correlation
20대장애인수(20-29세)(명) is highly overall correlated with 총계(명) and 7 other fieldsHigh correlation
30대장애인수(30-39세)(명) is highly overall correlated with 총계(명) and 7 other fieldsHigh correlation
40대장애인수(40-49세)(명) is highly overall correlated with 총계(명) and 7 other fieldsHigh correlation
50대장애인수(50-59세)(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
60대장애인수(60-69세)(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
70대장애인수(70-79세)(명) is highly overall correlated with 총계(명) and 7 other fieldsHigh correlation
80대장애인수(80-89세)(명) is highly overall correlated with 총계(명) and 5 other fieldsHigh correlation
90세이상장애인수(명) is highly overall correlated with 총계(명) and 5 other fieldsHigh correlation
장애유형 is highly overall correlated with 총계(명) and 6 other fieldsHigh correlation
10세미만장애인수(0-9세)(명) has 10 (6.1%) zerosZeros
70대장애인수(70-79세)(명) has 8 (4.8%) zerosZeros
80대장애인수(80-89세)(명) has 11 (6.7%) zerosZeros
90세이상장애인수(명) has 37 (22.4%) zerosZeros

Reproduction

Analysis started2024-04-11 03:04:25.399616
Analysis finished2024-04-11 03:04:39.756300
Duration14.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct11
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:39.806413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12015
median2018
Q32021
95-th percentile2023
Maximum2023
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1719041
Coefficient of variation (CV)0.0015718058
Kurtosis-1.2205287
Mean2018
Median Absolute Deviation (MAD)3
Skewness0
Sum332970
Variance10.060976
MonotonicityDecreasing
2024-04-11T12:04:39.899360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2023 15
9.1%
2022 15
9.1%
2021 15
9.1%
2020 15
9.1%
2019 15
9.1%
2018 15
9.1%
2017 15
9.1%
2016 15
9.1%
2015 15
9.1%
2014 15
9.1%
ValueCountFrequency (%)
2013 15
9.1%
2014 15
9.1%
2015 15
9.1%
2016 15
9.1%
2017 15
9.1%
2018 15
9.1%
2019 15
9.1%
2020 15
9.1%
2021 15
9.1%
2022 15
9.1%
ValueCountFrequency (%)
2023 15
9.1%
2022 15
9.1%
2021 15
9.1%
2020 15
9.1%
2019 15
9.1%
2018 15
9.1%
2017 15
9.1%
2016 15
9.1%
2015 15
9.1%
2014 15
9.1%

장애유형
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
 
11
언어
 
11
지체
 
11
지적
 
11
정신
 
11
Other values (12)
110 

Length

Max length5
Median length2
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row뇌병변
3rd row뇌전증
4th row시각
5th row신장

Common Values

ValueCountFrequency (%)
11
 
6.7%
언어 11
 
6.7%
지체 11
 
6.7%
지적 11
 
6.7%
정신 11
 
6.7%
호흡기 11
 
6.7%
청각 11
 
6.7%
뇌병변 11
 
6.7%
안면 11
 
6.7%
심장 11
 
6.7%
Other values (7) 55
33.3%

Length

2024-04-11T12:04:40.012332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11
 
6.7%
뇌병변 11
 
6.7%
뇌전증 11
 
6.7%
시각 11
 
6.7%
신장 11
 
6.7%
심장 11
 
6.7%
언어 11
 
6.7%
안면 11
 
6.7%
청각 11
 
6.7%
호흡기 11
 
6.7%
Other values (7) 55
33.3%

총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct161
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36395.212
Minimum576
Maximum270229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:40.132661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum576
5-th percentile633
Q12482
median6465
Q349698
95-th percentile265798
Maximum270229
Range269653
Interquartile range (IQR)47216

Descriptive statistics

Standard deviation65813.4
Coefficient of variation (CV)1.8082983
Kurtosis7.5450438
Mean36395.212
Median Absolute Deviation (MAD)5849
Skewness2.8739849
Sum6005210
Variance4.3314036 × 109
MonotonicityNot monotonic
2024-04-11T12:04:40.251735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
633 2
 
1.2%
1416 2
 
1.2%
576 2
 
1.2%
53728 2
 
1.2%
2601 1
 
0.6%
598 1
 
0.6%
52693 1
 
0.6%
52333 1
 
0.6%
1356 1
 
0.6%
51482 1
 
0.6%
Other values (151) 151
91.5%
ValueCountFrequency (%)
576 2
1.2%
581 1
0.6%
598 1
0.6%
615 1
0.6%
616 1
0.6%
622 1
0.6%
629 1
0.6%
633 2
1.2%
651 1
0.6%
1243 1
0.6%
ValueCountFrequency (%)
270229 1
0.6%
269090 1
0.6%
268930 1
0.6%
268832 1
0.6%
268816 1
0.6%
268668 1
0.6%
267797 1
0.6%
267043 1
0.6%
266179 1
0.6%
264274 1
0.6%

10세미만장애인수(0-9세)(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct104
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean508.64242
Minimum0
Maximum3514
Zeros10
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:40.362466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111
median48
Q3503
95-th percentile2593.2
Maximum3514
Range3514
Interquartile range (IQR)492

Descriptive statistics

Standard deviation825.94518
Coefficient of variation (CV)1.6238228
Kurtosis2.3669981
Mean508.64242
Median Absolute Deviation (MAD)48
Skewness1.8250051
Sum83926
Variance682185.44
MonotonicityNot monotonic
2024-04-11T12:04:40.479326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
6.1%
10 8
 
4.8%
11 7
 
4.2%
19 5
 
3.0%
21 4
 
2.4%
4 4
 
2.4%
1 4
 
2.4%
13 3
 
1.8%
14 3
 
1.8%
2 3
 
1.8%
Other values (94) 114
69.1%
ValueCountFrequency (%)
0 10
6.1%
1 4
 
2.4%
2 3
 
1.8%
3 2
 
1.2%
4 4
 
2.4%
5 2
 
1.2%
8 3
 
1.8%
9 3
 
1.8%
10 8
4.8%
11 7
4.2%
ValueCountFrequency (%)
3514 1
0.6%
2986 1
0.6%
2905 1
0.6%
2893 1
0.6%
2862 1
0.6%
2818 1
0.6%
2748 1
0.6%
2709 1
0.6%
2602 1
0.6%
2558 1
0.6%

10대장애인수(10-19세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct128
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1059.2545
Minimum6
Maximum8875
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:40.600994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile11.2
Q134
median94
Q3871
95-th percentile8378.6
Maximum8875
Range8869
Interquartile range (IQR)837

Descriptive statistics

Standard deviation2149.3801
Coefficient of variation (CV)2.0291441
Kurtosis7.2463825
Mean1059.2545
Median Absolute Deviation (MAD)80
Skewness2.844965
Sum174777
Variance4619834.9
MonotonicityNot monotonic
2024-04-11T12:04:40.713495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 5
 
3.0%
19 3
 
1.8%
10 3
 
1.8%
78 3
 
1.8%
14 3
 
1.8%
24 3
 
1.8%
81 3
 
1.8%
73 2
 
1.2%
20 2
 
1.2%
37 2
 
1.2%
Other values (118) 136
82.4%
ValueCountFrequency (%)
6 1
 
0.6%
7 2
 
1.2%
8 1
 
0.6%
10 3
1.8%
11 2
 
1.2%
12 2
 
1.2%
14 3
1.8%
15 5
3.0%
16 2
 
1.2%
18 2
 
1.2%
ValueCountFrequency (%)
8875 1
0.6%
8867 1
0.6%
8641 1
0.6%
8615 1
0.6%
8584 1
0.6%
8465 1
0.6%
8442 1
0.6%
8425 1
0.6%
8398 1
0.6%
8301 1
0.6%

20대장애인수(20-29세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct138
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1485.7515
Minimum11
Maximum12507
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:40.830208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile21
Q174
median303
Q31486
95-th percentile9501.8
Maximum12507
Range12496
Interquartile range (IQR)1412

Descriptive statistics

Standard deviation2766.1469
Coefficient of variation (CV)1.861783
Kurtosis7.8854794
Mean1485.7515
Median Absolute Deviation (MAD)288
Skewness2.8870052
Sum245149
Variance7651568.5
MonotonicityNot monotonic
2024-04-11T12:04:40.965283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26 4
 
2.4%
27 4
 
2.4%
30 3
 
1.8%
25 3
 
1.8%
97 3
 
1.8%
105 3
 
1.8%
29 3
 
1.8%
38 2
 
1.2%
303 2
 
1.2%
100 2
 
1.2%
Other values (128) 136
82.4%
ValueCountFrequency (%)
11 1
 
0.6%
13 2
1.2%
14 1
 
0.6%
15 2
1.2%
18 1
 
0.6%
19 1
 
0.6%
21 2
1.2%
22 1
 
0.6%
25 3
1.8%
26 4
2.4%
ValueCountFrequency (%)
12507 1
0.6%
12506 1
0.6%
12488 1
0.6%
12327 1
0.6%
11876 1
0.6%
10881 1
0.6%
10779 1
0.6%
10237 1
0.6%
9643 1
0.6%
8937 1
0.6%

30대장애인수(30-39세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct153
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2140.697
Minimum32
Maximum19855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:41.082206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile51.4
Q195
median437
Q32073
95-th percentile8988.2
Maximum19855
Range19823
Interquartile range (IQR)1978

Descriptive statistics

Standard deviation3615.4543
Coefficient of variation (CV)1.6889146
Kurtosis7.9034712
Mean2140.697
Median Absolute Deviation (MAD)401
Skewness2.7153806
Sum353215
Variance13071510
MonotonicityNot monotonic
2024-04-11T12:04:41.203883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
73 3
 
1.8%
59 3
 
1.8%
82 3
 
1.8%
183 2
 
1.2%
98 2
 
1.2%
49 2
 
1.2%
55 2
 
1.2%
95 2
 
1.2%
53 2
 
1.2%
51 1
 
0.6%
Other values (143) 143
86.7%
ValueCountFrequency (%)
32 1
0.6%
35 1
0.6%
36 1
0.6%
44 1
0.6%
48 1
0.6%
49 2
1.2%
50 1
0.6%
51 1
0.6%
53 2
1.2%
55 2
1.2%
ValueCountFrequency (%)
19855 1
0.6%
18029 1
0.6%
16495 1
0.6%
15127 1
0.6%
13884 1
0.6%
13764 1
0.6%
11340 1
0.6%
10137 1
0.6%
9016 1
0.6%
8877 1
0.6%

40대장애인수(40-49세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct150
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4188.8788
Minimum20
Maximum45237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:41.324190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile95
Q1147
median548
Q33979
95-th percentile26807.4
Maximum45237
Range45217
Interquartile range (IQR)3832

Descriptive statistics

Standard deviation8427.0118
Coefficient of variation (CV)2.0117583
Kurtosis11.049041
Mean4188.8788
Median Absolute Deviation (MAD)501
Skewness3.3544114
Sum691165
Variance71014528
MonotonicityNot monotonic
2024-04-11T12:04:41.431211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 3
 
1.8%
103 3
 
1.8%
34994 2
 
1.2%
305 2
 
1.2%
133 2
 
1.2%
143 2
 
1.2%
95 2
 
1.2%
312 2
 
1.2%
141 2
 
1.2%
129 2
 
1.2%
Other values (140) 143
86.7%
ValueCountFrequency (%)
20 1
0.6%
24 1
0.6%
28 1
0.6%
35 1
0.6%
40 1
0.6%
47 1
0.6%
63 1
0.6%
69 1
0.6%
95 2
1.2%
98 1
0.6%
ValueCountFrequency (%)
45237 1
0.6%
42609 1
0.6%
40211 1
0.6%
37732 1
0.6%
34994 2
1.2%
30356 1
0.6%
28833 1
0.6%
27170 1
0.6%
25357 1
0.6%
23449 1
0.6%

50대장애인수(50-59세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct157
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7238.9818
Minimum8
Maximum71870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:41.540606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile16.8
Q1376
median1031
Q36660
95-th percentile55096.4
Maximum71870
Range71862
Interquartile range (IQR)6284

Descriptive statistics

Standard deviation15564.062
Coefficient of variation (CV)2.1500347
Kurtosis10.012725
Mean7238.9818
Median Absolute Deviation (MAD)1019
Skewness3.3195864
Sum1194432
Variance2.4224003 × 108
MonotonicityNot monotonic
2024-04-11T12:04:41.666822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144 2
 
1.2%
145 2
 
1.2%
349 2
 
1.2%
12 2
 
1.2%
501 2
 
1.2%
20 2
 
1.2%
13 2
 
1.2%
132 2
 
1.2%
68804 1
 
0.6%
7020 1
 
0.6%
Other values (147) 147
89.1%
ValueCountFrequency (%)
8 1
0.6%
9 1
0.6%
10 1
0.6%
11 1
0.6%
12 2
1.2%
13 2
1.2%
16 1
0.6%
20 2
1.2%
129 1
0.6%
132 2
1.2%
ValueCountFrequency (%)
71870 1
0.6%
71490 1
0.6%
69865 1
0.6%
68804 1
0.6%
67662 1
0.6%
67523 1
0.6%
63360 1
0.6%
59347 1
0.6%
55792 1
0.6%
52314 1
0.6%

60대장애인수(60-69세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct152
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7943.7152
Minimum1
Maximum77388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:41.802762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q1317
median1147
Q38928
95-th percentile60691.4
Maximum77388
Range77387
Interquartile range (IQR)8611

Descriptive statistics

Standard deviation16675.259
Coefficient of variation (CV)2.0991763
Kurtosis9.2266697
Mean7943.7152
Median Absolute Deviation (MAD)1055
Skewness3.17014
Sum1310713
Variance2.7806426 × 108
MonotonicityNot monotonic
2024-04-11T12:04:42.132354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
803 3
 
1.8%
92 3
 
1.8%
4 3
 
1.8%
798 2
 
1.2%
6 2
 
1.2%
181 2
 
1.2%
297 2
 
1.2%
5 2
 
1.2%
834 2
 
1.2%
7 2
 
1.2%
Other values (142) 142
86.1%
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
4 3
1.8%
5 2
1.2%
6 2
1.2%
7 2
1.2%
92 3
1.8%
97 1
 
0.6%
98 1
 
0.6%
99 1
 
0.6%
ValueCountFrequency (%)
77388 1
0.6%
76974 1
0.6%
76207 1
0.6%
72566 1
0.6%
69074 1
0.6%
64673 1
0.6%
64573 1
0.6%
63323 1
0.6%
61231 1
0.6%
58533 1
0.6%

70대장애인수(70-79세)(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct142
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7238.7455
Minimum0
Maximum57670
Zeros8
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:42.284600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q1280
median798
Q311045
95-th percentile54248
Maximum57670
Range57670
Interquartile range (IQR)10765

Descriptive statistics

Standard deviation14313.157
Coefficient of variation (CV)1.9772981
Kurtosis6.4901954
Mean7238.7455
Median Absolute Deviation (MAD)729
Skewness2.6801734
Sum1194393
Variance2.0486647 × 108
MonotonicityNot monotonic
2024-04-11T12:04:42.406423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8
 
4.8%
45 4
 
2.4%
798 4
 
2.4%
789 3
 
1.8%
56593 2
 
1.2%
69 2
 
1.2%
81 2
 
1.2%
57 2
 
1.2%
1 2
 
1.2%
998 2
 
1.2%
Other values (132) 134
81.2%
ValueCountFrequency (%)
0 8
4.8%
1 2
 
1.2%
2 1
 
0.6%
44 1
 
0.6%
45 4
2.4%
52 1
 
0.6%
53 1
 
0.6%
57 2
 
1.2%
60 1
 
0.6%
63 1
 
0.6%
ValueCountFrequency (%)
57670 1
0.6%
57655 1
0.6%
57436 1
0.6%
57384 1
0.6%
57024 1
0.6%
56593 2
1.2%
54980 1
0.6%
54332 1
0.6%
53912 1
0.6%
52797 1
0.6%

80대장애인수(80-89세)(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct135
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4025.3576
Minimum0
Maximum36924
Zeros11
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:42.532257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q140
median231
Q34690
95-th percentile24372
Maximum36924
Range36924
Interquartile range (IQR)4650

Descriptive statistics

Standard deviation8112.731
Coefficient of variation (CV)2.0154063
Kurtosis5.6498897
Mean4025.3576
Median Absolute Deviation (MAD)225
Skewness2.5015725
Sum664184
Variance65816404
MonotonicityNot monotonic
2024-04-11T12:04:42.654369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
6.7%
5 5
 
3.0%
12 4
 
2.4%
132 3
 
1.8%
24372 2
 
1.2%
341 2
 
1.2%
108 2
 
1.2%
137 2
 
1.2%
230 2
 
1.2%
31 2
 
1.2%
Other values (125) 130
78.8%
ValueCountFrequency (%)
0 11
6.7%
3 1
 
0.6%
4 1
 
0.6%
5 5
3.0%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
9 1
 
0.6%
11 2
 
1.2%
12 4
 
2.4%
ValueCountFrequency (%)
36924 1
0.6%
36269 1
0.6%
33387 1
0.6%
31095 1
0.6%
30895 1
0.6%
29459 1
0.6%
29148 1
0.6%
26619 1
0.6%
24372 2
1.2%
23995 1
0.6%

90세이상장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct88
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean565.18788
Minimum0
Maximum7970
Zeros37
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-11T12:04:42.777639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median14
Q3516
95-th percentile3176
Maximum7970
Range7970
Interquartile range (IQR)515

Descriptive statistics

Standard deviation1317.578
Coefficient of variation (CV)2.3312212
Kurtosis12.760233
Mean565.18788
Median Absolute Deviation (MAD)14
Skewness3.396073
Sum93256
Variance1736011.7
MonotonicityNot monotonic
2024-04-11T12:04:42.904958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37
22.4%
10 8
 
4.8%
1 6
 
3.6%
13 6
 
3.6%
6 5
 
3.0%
5 4
 
2.4%
16 3
 
1.8%
4 3
 
1.8%
9 3
 
1.8%
8 3
 
1.8%
Other values (78) 87
52.7%
ValueCountFrequency (%)
0 37
22.4%
1 6
 
3.6%
2 2
 
1.2%
4 3
 
1.8%
5 4
 
2.4%
6 5
 
3.0%
7 2
 
1.2%
8 3
 
1.8%
9 3
 
1.8%
10 8
 
4.8%
ValueCountFrequency (%)
7970 1
0.6%
7287 1
0.6%
6205 1
0.6%
5299 1
0.6%
4789 1
0.6%
4353 1
0.6%
4311 1
0.6%
3725 1
0.6%
3264 1
0.6%
2824 1
0.6%

Interactions

2024-04-11T12:04:38.215112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:26.948658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.044487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.948038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.930645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.005683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.005923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.054331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.125132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.099679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.108928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.232679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.299822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.075006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.112283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.023832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.996420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.089248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.105629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.121352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.199888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.187641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.193619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.304961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.391027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.283103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.181411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.102108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.063959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.170763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.201710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.191812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.277100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.268433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.277792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.377490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.477985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.357759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.255648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.187797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.142900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.247207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.301400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.264558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.364212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.358016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.358564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.457834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.552029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.432903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.321940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.256920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.395961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.314896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.375234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.331399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.438987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.431566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.426549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.527852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.638346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.507600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.396756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.350096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.469618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.402110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.456299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.589788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.516172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.519212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.676291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.619996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.721656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.588628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.477282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.438859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.551183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.505435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.539174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.668641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.601801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.608057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.754074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.705572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.795382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.655187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.553362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.517905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.624413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.579298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.615642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.736593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.676076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.689594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.834321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.790822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.895780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.735366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.632065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.602899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.700833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.658507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.719255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.816599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.761829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.782124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.911980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.879610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:39.004176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.817069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.710207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.688615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.774171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.738399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.808014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.901413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.848491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.868313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.993411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.967262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:39.084994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.890739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.780125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.765090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.845378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.814225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.888918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:33.972048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.925012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.944300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.066643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.045607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:39.169298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:27.962434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:28.864015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:29.847900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:30.921031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:31.905276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:32.968618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:34.047996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:35.007631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:36.025004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:37.149517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T12:04:38.132391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T12:04:43.008196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도장애유형총계(명)10세미만장애인수(0-9세)(명)10대장애인수(10-19세)(명)20대장애인수(20-29세)(명)30대장애인수(30-39세)(명)40대장애인수(40-49세)(명)50대장애인수(50-59세)(명)60대장애인수(60-69세)(명)70대장애인수(70-79세)(명)80대장애인수(80-89세)(명)90세이상장애인수(명)
기준년도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
장애유형0.0001.0000.9000.8660.9140.8420.7610.7730.8290.8540.8950.7160.631
총계(명)0.0000.9001.0000.7220.5440.7590.8870.7060.7220.9320.8760.9620.843
10세미만장애인수(0-9세)(명)0.0000.8660.7221.0000.8900.8450.6810.1220.2380.4900.5480.4230.201
10대장애인수(10-19세)(명)0.0000.9140.5440.8901.0000.8510.6990.5350.6990.4820.6150.4200.278
20대장애인수(20-29세)(명)0.0000.8420.7590.8450.8511.0000.8500.8080.8230.8140.7290.7550.571
30대장애인수(30-39세)(명)0.0000.7610.8870.6810.6990.8501.0000.9480.8850.9750.7830.9280.680
40대장애인수(40-49세)(명)0.0000.7730.7060.1220.5350.8080.9481.0000.8580.8540.6430.8760.754
50대장애인수(50-59세)(명)0.0000.8290.7220.2380.6990.8230.8850.8581.0000.8580.9120.8920.847
60대장애인수(60-69세)(명)0.0000.8540.9320.4900.4820.8140.9750.8540.8581.0000.7960.9830.818
70대장애인수(70-79세)(명)0.0000.8950.8760.5480.6150.7290.7830.6430.9120.7961.0000.8670.898
80대장애인수(80-89세)(명)0.0000.7160.9620.4230.4200.7550.9280.8760.8920.9830.8671.0000.857
90세이상장애인수(명)0.0000.6310.8430.2010.2780.5710.6800.7540.8470.8180.8980.8571.000
2024-04-11T12:04:43.155026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도총계(명)10세미만장애인수(0-9세)(명)10대장애인수(10-19세)(명)20대장애인수(20-29세)(명)30대장애인수(30-39세)(명)40대장애인수(40-49세)(명)50대장애인수(50-59세)(명)60대장애인수(60-69세)(명)70대장애인수(70-79세)(명)80대장애인수(80-89세)(명)90세이상장애인수(명)장애유형
기준년도1.0000.0910.029-0.0300.066-0.045-0.0360.0020.1270.1010.1630.1260.000
총계(명)0.0911.0000.5600.6640.8040.8500.8080.8610.8780.7990.7460.7330.713
10세미만장애인수(0-9세)(명)0.0290.5601.0000.9290.7100.5250.2930.2660.2760.1600.1950.2310.560
10대장애인수(10-19세)(명)-0.0300.6640.9291.0000.8560.7070.4150.3640.3660.2160.2170.2520.710
20대장애인수(20-29세)(명)0.0660.8040.7100.8561.0000.9110.6570.5590.5350.3660.3320.3500.526
30대장애인수(30-39세)(명)-0.0450.8500.5250.7070.9111.0000.8740.7630.7030.5240.4580.4540.414
40대장애인수(40-49세)(명)-0.0360.8080.2930.4150.6570.8741.0000.9150.8420.7040.6310.5930.473
50대장애인수(50-59세)(명)0.0020.8610.2660.3640.5590.7630.9151.0000.9650.8770.8000.7520.559
60대장애인수(60-69세)(명)0.1270.8780.2760.3660.5350.7030.8420.9651.0000.9360.8790.8240.630
70대장애인수(70-79세)(명)0.1010.7990.1600.2160.3660.5240.7040.8770.9361.0000.9730.9370.671
80대장애인수(80-89세)(명)0.1630.7460.1950.2170.3320.4580.6310.8000.8790.9731.0000.9780.367
90세이상장애인수(명)0.1260.7330.2310.2520.3500.4540.5930.7520.8240.9370.9781.0000.302
장애유형0.0000.7130.5600.7100.5260.4140.4730.5590.6300.6710.3670.3021.000

Missing values

2024-04-11T12:04:39.297622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T12:04:39.472617image/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

기준년도장애유형총계(명)10세미만장애인수(0-9세)(명)10대장애인수(10-19세)(명)20대장애인수(20-29세)(명)30대장애인수(30-39세)(명)40대장애인수(40-49세)(명)50대장애인수(50-59세)(명)60대장애인수(60-69세)(명)70대장애인수(70-79세)(명)80대장애인수(80-89세)(명)90세이상장애인수(명)
02023404644818711232210011634693720
12023뇌병변54230130213621791192235027386140651301988341047
22023뇌전증1428195610618229037628796160
32023시각546851334601237245058379533130811168887901476
42023신장266171158304104931736489801249232415183
52023심장124323521359510515327924414413
62023안면65137305914415014381322
72023언어52661044227132138415850119081642133
82023자폐117673514388928951270172207000
92023장루ㆍ요루40331939476917350410211168863130
기준년도장애유형총계(명)10세미만장애인수(0-9세)(명)10대장애인수(10-19세)(명)20대장애인수(20-29세)(명)30대장애인수(30-39세)(명)40대장애인수(40-49세)(명)50대장애인수(50-59세)(명)60대장애인수(60-69세)(명)70대장애인수(70-79세)(명)80대장애인수(80-89세)(명)90세이상장애인수(명)
1552013심장15613712874751182553484111087
1562013안면57652235114126132924550
1572013언어353315915610531958973767663913716
1582013자폐성4450801235211281402081000
1592013장루.요루28631112256117149774194836235
1602013정신168960376052248545055352254694685
1612013지적353312267864183836029488334231131501694
1622013지체270229289148050541985545237718705765352797147021292
1632013청각47438478852111521623979705189281316282031508
1642013호흡기2584111011681535018517891846