Overview

Dataset statistics

Number of variables20
Number of observations341
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.4 KiB
Average record size in memory178.4 B

Variable types

Numeric12
Categorical8

Dataset

Description장애인일자리사업 장애유형별 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ZYRPYYTYGL8BWWPMEVFE26175868&infSeq=1

Alerts

총계(명) is highly overall correlated with 지체장애인수(명) and 7 other fieldsHigh correlation
지체장애인수(명) is highly overall correlated with 총계(명) and 6 other fieldsHigh correlation
뇌병변장애인수(명) is highly overall correlated with 총계(명) and 5 other fieldsHigh correlation
시각장애인수(명) is highly overall correlated with 총계(명) and 5 other fieldsHigh correlation
청각장애인수(명) is highly overall correlated with 총계(명) and 2 other fieldsHigh correlation
신장장애인수(명) is highly overall correlated with 총계(명) and 4 other fieldsHigh correlation
지적장애인수(명) is highly overall correlated with 총계(명) and 5 other fieldsHigh correlation
정신장애인수(명) is highly overall correlated with 총계(명)High correlation
자폐성장애인수(명) is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
안면장애인수(명) is highly imbalanced (78.8%)Imbalance
심장장애인수(명) is highly imbalanced (68.4%)Imbalance
간장애인수(명) is highly imbalanced (57.6%)Imbalance
호흡기장애인수(명) is highly imbalanced (63.4%)Imbalance
지체장애인수(명) has 4 (1.2%) zerosZeros
뇌병변장애인수(명) has 16 (4.7%) zerosZeros
시각장애인수(명) has 31 (9.1%) zerosZeros
청각장애인수(명) has 19 (5.6%) zerosZeros
신장장애인수(명) has 78 (22.9%) zerosZeros
뇌전증장애인수(명) has 233 (68.3%) zerosZeros
지적장애인수(명) has 8 (2.3%) zerosZeros
정신장애인수(명) has 31 (9.1%) zerosZeros
자폐성장애인수(명) has 108 (31.7%) zerosZeros
특수교육대상자수(명) has 241 (70.7%) zerosZeros

Reproduction

Analysis started2024-04-29 13:36:16.778659
Analysis finished2024-04-29 13:36:34.019753
Duration17.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct7
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.9091
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:34.087125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12019
median2022
Q32023
95-th percentile2023
Maximum2023
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0235247
Coefficient of variation (CV)0.0010012943
Kurtosis-0.91959264
Mean2020.9091
Median Absolute Deviation (MAD)1
Skewness-0.67237857
Sum689130
Variance4.0946524
MonotonicityDecreasing
2024-04-29T22:36:34.200384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2023 93
27.3%
2022 93
27.3%
2021 31
 
9.1%
2020 31
 
9.1%
2019 31
 
9.1%
2018 31
 
9.1%
2017 31
 
9.1%
ValueCountFrequency (%)
2017 31
 
9.1%
2018 31
 
9.1%
2019 31
 
9.1%
2020 31
 
9.1%
2021 31
 
9.1%
2022 93
27.3%
2023 93
27.3%
ValueCountFrequency (%)
2023 93
27.3%
2022 93
27.3%
2021 31
 
9.1%
2020 31
 
9.1%
2019 31
 
9.1%
2018 31
 
9.1%
2017 31
 
9.1%

시군명
Categorical

Distinct31
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
가평군
 
11
고양시
 
11
과천시
 
11
광명시
 
11
광주시
 
11
Other values (26)
286 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
가평군 11
 
3.2%
고양시 11
 
3.2%
과천시 11
 
3.2%
광명시 11
 
3.2%
광주시 11
 
3.2%
구리시 11
 
3.2%
군포시 11
 
3.2%
김포시 11
 
3.2%
남양주시 11
 
3.2%
동두천시 11
 
3.2%
Other values (21) 231
67.7%

Length

2024-04-29T22:36:34.461694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 11
 
3.2%
안양시 11
 
3.2%
하남시 11
 
3.2%
포천시 11
 
3.2%
평택시 11
 
3.2%
파주시 11
 
3.2%
이천시 11
 
3.2%
의정부시 11
 
3.2%
의왕시 11
 
3.2%
용인시 11
 
3.2%
Other values (21) 231
67.7%

성별
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
총계
217 
여성
62 
남성
62 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row총계
2nd row여성
3rd row남성
4th row여성
5th row총계

Common Values

ValueCountFrequency (%)
총계 217
63.6%
여성 62
 
18.2%
남성 62
 
18.2%

Length

2024-04-29T22:36:34.576096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:34.666480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
총계 217
63.6%
여성 62
 
18.2%
남성 62
 
18.2%

총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct150
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.217009
Minimum9
Maximum356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:34.794649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile24
Q148
median74
Q3112
95-th percentile201
Maximum356
Range347
Interquartile range (IQR)64

Descriptive statistics

Standard deviation55.925421
Coefficient of variation (CV)0.6486588
Kurtosis2.8599556
Mean86.217009
Median Absolute Deviation (MAD)29
Skewness1.4822057
Sum29400
Variance3127.6528
MonotonicityNot monotonic
2024-04-29T22:36:34.936491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 8
 
2.3%
87 7
 
2.1%
76 7
 
2.1%
81 6
 
1.8%
25 6
 
1.8%
75 5
 
1.5%
58 5
 
1.5%
129 5
 
1.5%
50 5
 
1.5%
48 5
 
1.5%
Other values (140) 282
82.7%
ValueCountFrequency (%)
9 2
0.6%
12 1
 
0.3%
13 1
 
0.3%
16 2
0.6%
17 1
 
0.3%
18 1
 
0.3%
20 1
 
0.3%
21 3
0.9%
22 2
0.6%
23 2
0.6%
ValueCountFrequency (%)
356 1
0.3%
327 1
0.3%
294 1
0.3%
265 1
0.3%
258 1
0.3%
236 1
0.3%
229 1
0.3%
227 1
0.3%
226 2
0.6%
225 1
0.3%

지체장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.304985
Minimum0
Maximum96
Zeros4
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:35.080535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q113
median24
Q338
95-th percentile63
Maximum96
Range96
Interquartile range (IQR)25

Descriptive statistics

Standard deviation18.276494
Coefficient of variation (CV)0.66934642
Kurtosis0.7188996
Mean27.304985
Median Absolute Deviation (MAD)12
Skewness0.93505279
Sum9311
Variance334.03024
MonotonicityNot monotonic
2024-04-29T22:36:35.240358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 16
 
4.7%
12 16
 
4.7%
8 12
 
3.5%
19 12
 
3.5%
27 10
 
2.9%
21 10
 
2.9%
9 10
 
2.9%
22 8
 
2.3%
10 8
 
2.3%
38 8
 
2.3%
Other values (63) 231
67.7%
ValueCountFrequency (%)
0 4
 
1.2%
1 1
 
0.3%
2 6
1.8%
3 4
 
1.2%
4 5
1.5%
5 3
 
0.9%
6 5
1.5%
7 7
2.1%
8 12
3.5%
9 10
2.9%
ValueCountFrequency (%)
96 1
 
0.3%
88 1
 
0.3%
85 1
 
0.3%
80 1
 
0.3%
77 3
0.9%
74 1
 
0.3%
71 1
 
0.3%
70 3
0.9%
69 2
0.6%
66 1
 
0.3%

뇌병변장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3372434
Minimum0
Maximum30
Zeros16
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:35.373363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median7
Q312
95-th percentile20
Maximum30
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.331113
Coefficient of variation (CV)0.75937725
Kurtosis1.1445437
Mean8.3372434
Median Absolute Deviation (MAD)4
Skewness1.1117812
Sum2843
Variance40.082991
MonotonicityNot monotonic
2024-04-29T22:36:35.493581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
7 30
 
8.8%
6 27
 
7.9%
5 25
 
7.3%
8 25
 
7.3%
1 22
 
6.5%
2 22
 
6.5%
3 22
 
6.5%
4 21
 
6.2%
11 17
 
5.0%
0 16
 
4.7%
Other values (19) 114
33.4%
ValueCountFrequency (%)
0 16
4.7%
1 22
6.5%
2 22
6.5%
3 22
6.5%
4 21
6.2%
5 25
7.3%
6 27
7.9%
7 30
8.8%
8 25
7.3%
9 13
3.8%
ValueCountFrequency (%)
30 2
 
0.6%
28 3
0.9%
27 4
1.2%
26 1
 
0.3%
24 1
 
0.3%
23 1
 
0.3%
22 3
0.9%
21 2
 
0.6%
20 7
2.1%
19 3
0.9%

시각장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0029326
Minimum0
Maximum124
Zeros31
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:35.630090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q37
95-th percentile12
Maximum124
Range124
Interquartile range (IQR)5

Descriptive statistics

Standard deviation13.110952
Coefficient of variation (CV)2.1840911
Kurtosis55.275746
Mean6.0029326
Median Absolute Deviation (MAD)2
Skewness7.2018678
Sum2047
Variance171.89705
MonotonicityNot monotonic
2024-04-29T22:36:35.752899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2 47
13.8%
1 41
12.0%
3 40
11.7%
5 38
11.1%
4 35
10.3%
0 31
9.1%
7 28
8.2%
6 22
6.5%
8 14
 
4.1%
10 12
 
3.5%
Other values (13) 33
9.7%
ValueCountFrequency (%)
0 31
9.1%
1 41
12.0%
2 47
13.8%
3 40
11.7%
4 35
10.3%
5 38
11.1%
6 22
6.5%
7 28
8.2%
8 14
 
4.1%
9 8
 
2.3%
ValueCountFrequency (%)
124 1
 
0.3%
114 1
 
0.3%
107 1
 
0.3%
105 1
 
0.3%
87 1
 
0.3%
45 1
 
0.3%
16 1
 
0.3%
15 4
1.2%
14 3
0.9%
13 2
0.6%

청각장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0557185
Minimum0
Maximum24
Zeros19
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:35.869832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q37
95-th percentile13
Maximum24
Range24
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.1166596
Coefficient of variation (CV)0.81425808
Kurtosis3.1079896
Mean5.0557185
Median Absolute Deviation (MAD)2
Skewness1.5627015
Sum1724
Variance16.946886
MonotonicityNot monotonic
2024-04-29T22:36:35.975063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3 57
16.7%
2 45
13.2%
4 44
12.9%
5 32
9.4%
1 31
9.1%
6 22
 
6.5%
0 19
 
5.6%
8 18
 
5.3%
7 17
 
5.0%
9 11
 
3.2%
Other values (12) 45
13.2%
ValueCountFrequency (%)
0 19
 
5.6%
1 31
9.1%
2 45
13.2%
3 57
16.7%
4 44
12.9%
5 32
9.4%
6 22
 
6.5%
7 17
 
5.0%
8 18
 
5.3%
9 11
 
3.2%
ValueCountFrequency (%)
24 1
 
0.3%
23 1
 
0.3%
21 1
 
0.3%
20 2
 
0.6%
17 1
 
0.3%
16 1
 
0.3%
15 5
1.5%
14 2
 
0.6%
13 9
2.6%
12 6
1.8%
Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
198 
1
98 
2
37 
3
 
6
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 198
58.1%
1 98
28.7%
2 37
 
10.9%
3 6
 
1.8%
4 2
 
0.6%

Length

2024-04-29T22:36:36.085769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:36.180620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 198
58.1%
1 98
28.7%
2 37
 
10.9%
3 6
 
1.8%
4 2
 
0.6%

안면장애인수(명)
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
315 
1
 
24
3
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 315
92.4%
1 24
 
7.0%
3 1
 
0.3%
2 1
 
0.3%

Length

2024-04-29T22:36:36.284673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:36.381784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 315
92.4%
1 24
 
7.0%
3 1
 
0.3%
2 1
 
0.3%

신장장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2903226
Minimum0
Maximum15
Zeros78
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:36.477242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile7
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4711619
Coefficient of variation (CV)1.078958
Kurtosis4.7288201
Mean2.2903226
Median Absolute Deviation (MAD)1
Skewness1.8876516
Sum781
Variance6.1066414
MonotonicityNot monotonic
2024-04-29T22:36:36.574347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 90
26.4%
0 78
22.9%
2 56
16.4%
3 39
11.4%
4 27
 
7.9%
5 19
 
5.6%
6 13
 
3.8%
8 5
 
1.5%
10 4
 
1.2%
7 4
 
1.2%
Other values (5) 6
 
1.8%
ValueCountFrequency (%)
0 78
22.9%
1 90
26.4%
2 56
16.4%
3 39
11.4%
4 27
 
7.9%
5 19
 
5.6%
6 13
 
3.8%
7 4
 
1.2%
8 5
 
1.5%
9 1
 
0.3%
ValueCountFrequency (%)
15 1
 
0.3%
13 2
 
0.6%
12 1
 
0.3%
11 1
 
0.3%
10 4
 
1.2%
9 1
 
0.3%
8 5
 
1.5%
7 4
 
1.2%
6 13
3.8%
5 19
5.6%

심장장애인수(명)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
290 
1
43 
2
 
5
3
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 290
85.0%
1 43
 
12.6%
2 5
 
1.5%
3 2
 
0.6%
4 1
 
0.3%

Length

2024-04-29T22:36:36.690974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:36.786346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 290
85.0%
1 43
 
12.6%
2 5
 
1.5%
3 2
 
0.6%
4 1
 
0.3%

간장애인수(명)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
265 
1
58 
2
 
15
3
 
2
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 265
77.7%
1 58
 
17.0%
2 15
 
4.4%
3 2
 
0.6%
5 1
 
0.3%

Length

2024-04-29T22:36:36.885976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:36.978299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 265
77.7%
1 58
 
17.0%
2 15
 
4.4%
3 2
 
0.6%
5 1
 
0.3%

호흡기장애인수(명)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
298 
1
41 
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 298
87.4%
1 41
 
12.0%
2 2
 
0.6%

Length

2024-04-29T22:36:37.083659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:37.174635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 298
87.4%
1 41
 
12.0%
2 2
 
0.6%
Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
264 
1
67 
2
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 264
77.4%
1 67
 
19.6%
2 10
 
2.9%

Length

2024-04-29T22:36:37.285017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:36:37.382170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 264
77.4%
1 67
 
19.6%
2 10
 
2.9%

뇌전증장애인수(명)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40175953
Minimum0
Maximum6
Zeros233
Zeros (%)68.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:37.465776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.71116918
Coefficient of variation (CV)1.7701364
Kurtosis13.378284
Mean0.40175953
Median Absolute Deviation (MAD)0
Skewness2.7935783
Sum137
Variance0.5057616
MonotonicityNot monotonic
2024-04-29T22:36:37.560349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 233
68.3%
1 88
 
25.8%
2 15
 
4.4%
3 3
 
0.9%
6 1
 
0.3%
4 1
 
0.3%
ValueCountFrequency (%)
0 233
68.3%
1 88
 
25.8%
2 15
 
4.4%
3 3
 
0.9%
4 1
 
0.3%
6 1
 
0.3%
ValueCountFrequency (%)
6 1
 
0.3%
4 1
 
0.3%
3 3
 
0.9%
2 15
 
4.4%
1 88
 
25.8%
0 233
68.3%

지적장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct72
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.57478
Minimum0
Maximum90
Zeros8
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:37.866235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q113
median21
Q335
95-th percentile63
Maximum90
Range90
Interquartile range (IQR)22

Descriptive statistics

Standard deviation17.937747
Coefficient of variation (CV)0.70138422
Kurtosis1.008004
Mean25.57478
Median Absolute Deviation (MAD)10
Skewness1.1454457
Sum8721
Variance321.76277
MonotonicityNot monotonic
2024-04-29T22:36:37.994668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 15
 
4.4%
17 13
 
3.8%
14 13
 
3.8%
11 13
 
3.8%
10 12
 
3.5%
15 11
 
3.2%
21 10
 
2.9%
18 10
 
2.9%
12 10
 
2.9%
9 10
 
2.9%
Other values (62) 224
65.7%
ValueCountFrequency (%)
0 8
2.3%
1 1
 
0.3%
2 2
 
0.6%
3 3
 
0.9%
4 3
 
0.9%
5 6
1.8%
6 2
 
0.6%
7 8
2.3%
8 5
1.5%
9 10
2.9%
ValueCountFrequency (%)
90 1
 
0.3%
84 1
 
0.3%
82 1
 
0.3%
81 1
 
0.3%
78 1
 
0.3%
74 4
1.2%
71 1
 
0.3%
70 1
 
0.3%
69 2
0.6%
68 1
 
0.3%

정신장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6803519
Minimum0
Maximum38
Zeros31
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:38.112613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile20
Maximum38
Range38
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.213874
Coefficient of variation (CV)0.93017166
Kurtosis3.1231519
Mean6.6803519
Median Absolute Deviation (MAD)3
Skewness1.5953893
Sum2278
Variance38.61223
MonotonicityNot monotonic
2024-04-29T22:36:38.246336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2 36
10.6%
4 34
10.0%
1 31
9.1%
0 31
9.1%
3 28
 
8.2%
6 25
 
7.3%
7 22
 
6.5%
9 21
 
6.2%
5 18
 
5.3%
8 18
 
5.3%
Other values (21) 77
22.6%
ValueCountFrequency (%)
0 31
9.1%
1 31
9.1%
2 36
10.6%
3 28
8.2%
4 34
10.0%
5 18
5.3%
6 25
7.3%
7 22
6.5%
8 18
5.3%
9 21
6.2%
ValueCountFrequency (%)
38 1
 
0.3%
30 1
 
0.3%
29 1
 
0.3%
27 1
 
0.3%
26 2
0.6%
25 1
 
0.3%
24 2
0.6%
23 2
0.6%
22 3
0.9%
21 2
0.6%

자폐성장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5953079
Minimum0
Maximum19
Zeros108
Zeros (%)31.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:38.353008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile10
Maximum19
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.2828218
Coefficient of variation (CV)1.2649065
Kurtosis5.4758605
Mean2.5953079
Median Absolute Deviation (MAD)2
Skewness2.1049272
Sum885
Variance10.776919
MonotonicityNot monotonic
2024-04-29T22:36:38.461029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 108
31.7%
1 61
17.9%
2 47
13.8%
3 33
 
9.7%
4 23
 
6.7%
5 21
 
6.2%
6 16
 
4.7%
7 7
 
2.1%
8 6
 
1.8%
10 5
 
1.5%
Other values (9) 14
 
4.1%
ValueCountFrequency (%)
0 108
31.7%
1 61
17.9%
2 47
13.8%
3 33
 
9.7%
4 23
 
6.7%
5 21
 
6.2%
6 16
 
4.7%
7 7
 
2.1%
8 6
 
1.8%
9 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
18 1
 
0.3%
17 1
 
0.3%
16 1
 
0.3%
14 3
0.9%
13 1
 
0.3%
12 2
 
0.6%
11 3
0.9%
10 5
1.5%
9 1
 
0.3%

특수교육대상자수(명)
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.84164223
Minimum0
Maximum22
Zeros241
Zeros (%)70.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-29T22:36:38.573936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum22
Range22
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.3069261
Coefficient of variation (CV)2.7409818
Kurtosis39.579801
Mean0.84164223
Median Absolute Deviation (MAD)0
Skewness5.5412491
Sum287
Variance5.3219079
MonotonicityNot monotonic
2024-04-29T22:36:38.676150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 241
70.7%
1 45
 
13.2%
2 25
 
7.3%
3 9
 
2.6%
5 6
 
1.8%
4 4
 
1.2%
7 3
 
0.9%
6 2
 
0.6%
9 2
 
0.6%
20 1
 
0.3%
Other values (3) 3
 
0.9%
ValueCountFrequency (%)
0 241
70.7%
1 45
 
13.2%
2 25
 
7.3%
3 9
 
2.6%
4 4
 
1.2%
5 6
 
1.8%
6 2
 
0.6%
7 3
 
0.9%
9 2
 
0.6%
11 1
 
0.3%
ValueCountFrequency (%)
22 1
 
0.3%
20 1
 
0.3%
15 1
 
0.3%
11 1
 
0.3%
9 2
 
0.6%
7 3
 
0.9%
6 2
 
0.6%
5 6
1.8%
4 4
1.2%
3 9
2.6%

Interactions

2024-04-29T22:36:32.169333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.199143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.207670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.252995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.386241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.559211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.708621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.809109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.225785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.582468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.715604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.001590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.249624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.323623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.300608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.332854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.482835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.682377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.802001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.080916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.343502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.698779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.815588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.106363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.347316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.413543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.400846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.410604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.573223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.769371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.900764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.185174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.449724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.793087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.908908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.209321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.432334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.497206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.489255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.490043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.658979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.853001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.988517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.272405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.535925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.890622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.007601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.300184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.534560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.582382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.574239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.570346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.742499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.948035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.078589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.368795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.631366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.988312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.092189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.405763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.632684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.659045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.673447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.654578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.827150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.038555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.181159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.459066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.732886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.085552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.369084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.504800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.738237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.726686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.745481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.739123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.905527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.144840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.272177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.554963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.831216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.183933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.447378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.614248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.840417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.803350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.829469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.847086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.020689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.253063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.371902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.649074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.955757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.262328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.546747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.718034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.931086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.884165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.916521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.928426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.111945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.344917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.470843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.774854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.047819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.345741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.634462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.804737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:33.033966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:19.951830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.994759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.993750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.215047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.432280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.548987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:26.914859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.190546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.438956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.707326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.881372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:33.179626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.030471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.081250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.086155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.309378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.519927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.638751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.019076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.332688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.538234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.808452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:31.986229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:33.325782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:20.123095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:21.168889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:22.315238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:23.395818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:24.619136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:25.736104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:27.119125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:28.464513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:29.628634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:30.920583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:36:32.076905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:36:38.777248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명성별총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)언어장애인수(명)안면장애인수(명)신장장애인수(명)심장장애인수(명)간장애인수(명)호흡기장애인수(명)장루요루장애인수(명)뇌전증장애인수(명)지적장애인수(명)정신장애인수(명)자폐성장애인수(명)특수교육대상자수(명)
기준년도1.0000.0000.7790.4040.4170.3250.1900.2520.1540.0000.2610.1820.1900.2740.3690.2310.2590.0860.1540.000
시군명0.0001.0000.0000.5990.6060.6660.4690.5600.6130.4740.6000.4800.4640.5930.6000.4200.6650.6410.6470.138
성별0.7790.0001.0000.4790.4340.4910.1700.3620.2210.0800.2410.1320.0680.1560.3080.2130.3500.0730.3730.137
총계(명)0.4040.5990.4791.0000.9140.8390.8370.6410.5510.3670.7650.4260.6140.4870.1670.3320.8520.6110.6960.000
지체장애인수(명)0.4170.6060.4340.9141.0000.8070.5710.7200.5540.2500.7360.5360.5750.3020.2010.2620.7350.4930.7000.000
뇌병변장애인수(명)0.3250.6660.4910.8390.8071.0000.4930.6720.5180.1890.7240.4750.4300.6120.1340.1580.6520.4580.6610.000
시각장애인수(명)0.1900.4690.1700.8370.5710.4931.0000.1700.2190.0000.4460.2230.2390.2640.0000.3170.5150.5700.2720.404
청각장애인수(명)0.2520.5600.3620.6410.7200.6720.1701.0000.3140.2010.5980.3080.3020.2750.3070.0510.4120.5440.4000.129
언어장애인수(명)0.1540.6130.2210.5510.5540.5180.2190.3141.0000.1640.5040.4640.5470.4160.2260.0820.4310.2750.6520.000
안면장애인수(명)0.0000.4740.0800.3670.2500.1890.0000.2010.1641.0000.5210.0000.0000.1090.0360.1670.3870.2750.5970.000
신장장애인수(명)0.2610.6000.2410.7650.7360.7240.4460.5980.5040.5211.0000.7080.8490.3660.3380.1610.6960.4190.7830.195
심장장애인수(명)0.1820.4800.1320.4260.5360.4750.2230.3080.4640.0000.7081.0000.7200.1690.0440.1510.3960.0700.7170.000
간장애인수(명)0.1900.4640.0680.6140.5750.4300.2390.3020.5470.0000.8490.7201.0000.0310.0000.0450.4390.0000.7110.000
호흡기장애인수(명)0.2740.5930.1560.4870.3020.6120.2640.2750.4160.1090.3660.1690.0311.0000.4030.0000.2080.5190.3420.000
장루요루장애인수(명)0.3690.6000.3080.1670.2010.1340.0000.3070.2260.0360.3380.0440.0000.4031.0000.2410.2500.3140.3820.000
뇌전증장애인수(명)0.2310.4200.2130.3320.2620.1580.3170.0510.0820.1670.1610.1510.0450.0000.2411.0000.3730.4800.5260.000
지적장애인수(명)0.2590.6650.3500.8520.7350.6520.5150.4120.4310.3870.6960.3960.4390.2080.2500.3731.0000.4950.7350.000
정신장애인수(명)0.0860.6410.0730.6110.4930.4580.5700.5440.2750.2750.4190.0700.0000.5190.3140.4800.4951.0000.3610.382
자폐성장애인수(명)0.1540.6470.3730.6960.7000.6610.2720.4000.6520.5970.7830.7170.7110.3420.3820.5260.7350.3611.0000.000
특수교육대상자수(명)0.0000.1380.1370.0000.0000.0000.4040.1290.0000.0000.1950.0000.0000.0000.0000.0000.0000.3820.0001.000
2024-04-29T22:36:38.980914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호흡기장애인수(명)성별간장애인수(명)안면장애인수(명)시군명언어장애인수(명)심장장애인수(명)장루요루장애인수(명)
호흡기장애인수(명)1.0000.0470.0220.1030.3540.3450.1280.149
성별0.0471.0000.0500.0750.0000.1690.0990.104
간장애인수(명)0.0220.0501.0000.0000.2290.2310.3460.000
안면장애인수(명)0.1030.0750.0001.0000.2530.1340.0000.033
시군명0.3540.0000.2290.2531.0000.3290.2390.361
언어장애인수(명)0.3450.1690.2310.1340.3291.0000.1880.174
심장장애인수(명)0.1280.0990.3460.0000.2390.1881.0000.032
장루요루장애인수(명)0.1490.1040.0000.0330.3610.1740.0321.000
2024-04-29T22:36:39.102091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)신장장애인수(명)뇌전증장애인수(명)지적장애인수(명)정신장애인수(명)자폐성장애인수(명)특수교육대상자수(명)시군명성별언어장애인수(명)안면장애인수(명)심장장애인수(명)간장애인수(명)호흡기장애인수(명)장루요루장애인수(명)
기준년도1.000-0.087-0.091-0.199-0.0570.036-0.010-0.007-0.0740.067-0.129-0.0320.0000.4710.1390.0150.1220.1150.1000.146
총계(명)-0.0871.0000.9230.8100.7750.5890.6660.2730.8280.5200.6520.1560.2480.3250.2580.2250.1890.2980.3310.099
지체장애인수(명)-0.0910.9231.0000.7890.7330.5760.6160.2220.6340.3930.5420.0820.2520.2870.2600.1500.2490.2730.1870.121
뇌병변장애인수(명)-0.1990.8100.7891.0000.6370.4830.5230.1470.5350.3870.5890.0720.3170.3370.2860.1590.2490.2240.3850.095
시각장애인수(명)-0.0570.7750.7330.6371.0000.5530.5110.2230.5370.3730.4850.0230.2180.0700.1500.0000.1520.1630.1120.000
청각장애인수(명)0.0360.5890.5760.4830.5531.0000.4310.2410.3170.2100.3150.0130.2280.2280.1280.1010.1460.1330.2140.191
신장장애인수(명)-0.0100.6660.6160.5230.5110.4311.0000.2170.5350.2790.4860.1000.2430.1380.1640.3440.2440.3690.2130.196
뇌전증장애인수(명)-0.0070.2730.2220.1470.2230.2410.2171.0000.2310.1700.2150.0160.1900.0890.0550.1080.1020.0300.0000.102
지적장애인수(명)-0.0740.8280.6340.5350.5370.3170.5350.2311.0000.4340.5610.1820.2890.2360.1820.2390.1600.1960.1280.147
정신장애인수(명)0.0670.5200.3930.3870.3730.2100.2790.1700.4341.0000.3700.0310.2920.0320.1670.1720.0460.0000.2670.140
자폐성장애인수(명)-0.1290.6520.5420.5890.4850.3150.4860.2150.5610.3701.0000.0990.2790.2390.3240.3980.3750.3700.2160.245
특수교육대상자수(명)-0.0320.1560.0820.0720.0230.0130.1000.0160.1820.0310.0991.0000.1130.0570.0000.0000.0000.0000.0000.000
시군명0.0000.2480.2520.3170.2180.2280.2430.1900.2890.2920.2790.1131.0000.0000.3290.2530.2390.2290.3540.361
성별0.4710.3250.2870.3370.0700.2280.1380.0890.2360.0320.2390.0570.0001.0000.1690.0750.0990.0500.0470.104
언어장애인수(명)0.1390.2580.2600.2860.1500.1280.1640.0550.1820.1670.3240.0000.3290.1691.0000.1340.1880.2310.3450.174
안면장애인수(명)0.0150.2250.1500.1590.0000.1010.3440.1080.2390.1720.3980.0000.2530.0750.1341.0000.0000.0000.1030.033
심장장애인수(명)0.1220.1890.2490.2490.1520.1460.2440.1020.1600.0460.3750.0000.2390.0990.1880.0001.0000.3460.1280.032
간장애인수(명)0.1150.2980.2730.2240.1630.1330.3690.0300.1960.0000.3700.0000.2290.0500.2310.0000.3461.0000.0220.000
호흡기장애인수(명)0.1000.3310.1870.3850.1120.2140.2130.0000.1280.2670.2160.0000.3540.0470.3450.1030.1280.0221.0000.149
장루요루장애인수(명)0.1460.0990.1210.0950.0000.1910.1960.1020.1470.1400.2450.0000.3610.1040.1740.0330.0320.0000.1491.000

Missing values

2024-04-29T22:36:33.539283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:36:33.885348image/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

기준년도시군명성별총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)언어장애인수(명)안면장애인수(명)신장장애인수(명)심장장애인수(명)간장애인수(명)호흡기장애인수(명)장루요루장애인수(명)뇌전증장애인수(명)지적장애인수(명)정신장애인수(명)자폐성장애인수(명)특수교육대상자수(명)
02023가평군총계561521010000000171406
12023가평군여성257110100000006702
22023가평군남성3181000000000011704
32023고양시여성1033326400100000039720
42023고양시총계2267714127001301100741980
52023고양시남성12344126300301100351260
62023과천시총계762277100030010015650
72023과천시여성35123130000010011220
82023과천시남성4110467003000004430
92023광명시총계150411314600301001422540
기준년도시군명성별총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)언어장애인수(명)안면장애인수(명)신장장애인수(명)심장장애인수(명)간장애인수(명)호흡기장애인수(명)장루요루장애인수(명)뇌전증장애인수(명)지적장애인수(명)정신장애인수(명)자폐성장애인수(명)특수교육대상자수(명)
3312017오산시총계55211342201000006213
3322017용인시총계1443911762140101156780
3332017의왕시총계46137330000002010530
3342017의정부시총계923914241010000124321
3352017이천시총계832710491000101125103
3362017파주시총계75258210050000026341
3372017평택시총계91356711021111028025
3382017포천시총계48155121010000017501
3392017하남시총계813211551000100115154
3402017화성시총계9728162440212000271010