Overview

Dataset statistics

Number of variables19
Number of observations260
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.3 KiB
Average record size in memory170.5 B

Variable types

Numeric8
Categorical11

Dataset

Description장애인 보조기기 교부 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=66GALOVS40M295UYV2U426036490&infSeq=1

Alerts

안면장애인수(명) has constant value ""Constant
간장애인수(명) has constant value ""Constant
뇌전증장애인수(명) has constant value ""Constant
총계(명) is highly overall correlated with 지체장애인수(명) and 2 other fieldsHigh correlation
지체장애인수(명) is highly overall correlated with 총계(명) and 2 other fieldsHigh correlation
뇌병변장애인수(명) is highly overall correlated with 총계(명) and 3 other fieldsHigh correlation
시각장애인수(명) is highly overall correlated with 총계(명) and 2 other fieldsHigh correlation
언어장애인수(명) is highly overall correlated with 뇌병변장애인수(명)High correlation
언어장애인수(명) is highly imbalanced (89.1%)Imbalance
신장장애인수(명) is highly imbalanced (85.2%)Imbalance
심장장애인수(명) is highly imbalanced (93.5%)Imbalance
호흡기장애인수(명) is highly imbalanced (86.0%)Imbalance
장루요루장애인수(명) is highly imbalanced (93.5%)Imbalance
정신장애인수(명) is highly imbalanced (90.9%)Imbalance
자폐성장애인수(명) is highly imbalanced (77.6%)Imbalance
총계(명) has 10 (3.8%) zerosZeros
지체장애인수(명) has 29 (11.2%) zerosZeros
뇌병변장애인수(명) has 35 (13.5%) zerosZeros
시각장애인수(명) has 84 (32.3%) zerosZeros
청각장애인수(명) has 191 (73.5%) zerosZeros
지적장애인수(명) has 202 (77.7%) zerosZeros
중복장애인수(명) has 182 (70.0%) zerosZeros

Reproduction

Analysis started2023-12-10 21:33:28.365175
Analysis finished2023-12-10 21:33:36.220475
Duration7.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct10
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.9808
Minimum2013
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:36.275069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12016
median2018
Q32020
95-th percentile2022
Maximum2022
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8372208
Coefficient of variation (CV)0.0014059702
Kurtosis-1.119517
Mean2017.9808
Median Absolute Deviation (MAD)2
Skewness-0.25634733
Sum524675
Variance8.0498218
MonotonicityDecreasing
2023-12-11T06:33:36.391169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2022 31
11.9%
2021 31
11.9%
2020 31
11.9%
2019 31
11.9%
2018 31
11.9%
2017 21
8.1%
2016 21
8.1%
2015 21
8.1%
2014 21
8.1%
2013 21
8.1%
ValueCountFrequency (%)
2013 21
8.1%
2014 21
8.1%
2015 21
8.1%
2016 21
8.1%
2017 21
8.1%
2018 31
11.9%
2019 31
11.9%
2020 31
11.9%
2021 31
11.9%
2022 31
11.9%
ValueCountFrequency (%)
2022 31
11.9%
2021 31
11.9%
2020 31
11.9%
2019 31
11.9%
2018 31
11.9%
2017 21
8.1%
2016 21
8.1%
2015 21
8.1%
2014 21
8.1%
2013 21
8.1%

시군명
Categorical

Distinct31
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
안성시
 
10
안산시
 
10
부천시
 
10
군포시
 
10
성남시
 
10
Other values (26)
210 

Length

Max length4
Median length3
Mean length3.0576923
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row광명시
5th row광주시

Common Values

ValueCountFrequency (%)
안성시 10
 
3.8%
안산시 10
 
3.8%
부천시 10
 
3.8%
군포시 10
 
3.8%
성남시 10
 
3.8%
광주시 10
 
3.8%
광명시 10
 
3.8%
시흥시 10
 
3.8%
김포시 10
 
3.8%
수원시 10
 
3.8%
Other values (21) 160
61.5%

Length

2023-12-11T06:33:36.549325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안성시 10
 
3.8%
과천시 10
 
3.8%
양평군 10
 
3.8%
하남시 10
 
3.8%
평택시 10
 
3.8%
이천시 10
 
3.8%
의왕시 10
 
3.8%
안산시 10
 
3.8%
오산시 10
 
3.8%
여주시 10
 
3.8%
Other values (21) 160
61.5%

총계(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.015385
Minimum0
Maximum75
Zeros10
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:36.678026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15.75
median11
Q319.25
95-th percentile47.25
Maximum75
Range75
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation15.202613
Coefficient of variation (CV)0.9492506
Kurtosis1.9577866
Mean16.015385
Median Absolute Deviation (MAD)7
Skewness1.5133709
Sum4164
Variance231.11945
MonotonicityNot monotonic
2023-12-11T06:33:36.814819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 15
 
5.8%
9 15
 
5.8%
2 14
 
5.4%
6 13
 
5.0%
7 13
 
5.0%
12 11
 
4.2%
0 10
 
3.8%
4 10
 
3.8%
1 10
 
3.8%
11 9
 
3.5%
Other values (42) 140
53.8%
ValueCountFrequency (%)
0 10
3.8%
1 10
3.8%
2 14
5.4%
3 15
5.8%
4 10
3.8%
5 6
 
2.3%
6 13
5.0%
7 13
5.0%
8 7
2.7%
9 15
5.8%
ValueCountFrequency (%)
75 1
 
0.4%
66 2
0.8%
64 1
 
0.4%
62 2
0.8%
59 1
 
0.4%
57 1
 
0.4%
54 2
0.8%
52 3
1.2%
47 1
 
0.4%
46 2
0.8%

지체장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5923077
Minimum0
Maximum40
Zeros29
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:36.971293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile20
Maximum40
Range40
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.5614954
Coefficient of variation (CV)0.99532603
Kurtosis4.071708
Mean6.5923077
Median Absolute Deviation (MAD)3
Skewness1.8004472
Sum1714
Variance43.053222
MonotonicityNot monotonic
2023-12-11T06:33:37.123200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3 31
11.9%
0 29
11.2%
1 23
8.8%
2 23
8.8%
4 21
 
8.1%
6 19
 
7.3%
8 17
 
6.5%
7 17
 
6.5%
5 13
 
5.0%
9 10
 
3.8%
Other values (18) 57
21.9%
ValueCountFrequency (%)
0 29
11.2%
1 23
8.8%
2 23
8.8%
3 31
11.9%
4 21
8.1%
5 13
5.0%
6 19
7.3%
7 17
6.5%
8 17
6.5%
9 10
 
3.8%
ValueCountFrequency (%)
40 1
 
0.4%
31 2
 
0.8%
30 1
 
0.4%
25 2
 
0.8%
24 2
 
0.8%
23 2
 
0.8%
22 2
 
0.8%
20 5
1.9%
19 1
 
0.4%
18 1
 
0.4%

뇌병변장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1653846
Minimum0
Maximum30
Zeros35
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:37.262115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q37
95-th percentile15.05
Maximum30
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.4559975
Coefficient of variation (CV)1.0562616
Kurtosis5.0162294
Mean5.1653846
Median Absolute Deviation (MAD)3
Skewness2.0046818
Sum1343
Variance29.767909
MonotonicityNot monotonic
2023-12-11T06:33:37.412554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 35
13.5%
1 35
13.5%
2 30
11.5%
4 27
10.4%
3 24
9.2%
5 21
8.1%
7 15
 
5.8%
6 14
 
5.4%
9 11
 
4.2%
8 9
 
3.5%
Other values (17) 39
15.0%
ValueCountFrequency (%)
0 35
13.5%
1 35
13.5%
2 30
11.5%
3 24
9.2%
4 27
10.4%
5 21
8.1%
6 14
 
5.4%
7 15
5.8%
8 9
 
3.5%
9 11
 
4.2%
ValueCountFrequency (%)
30 1
0.4%
29 1
0.4%
27 1
0.4%
26 2
0.8%
24 1
0.4%
22 1
0.4%
21 1
0.4%
19 1
0.4%
18 1
0.4%
17 2
0.8%

시각장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5307692
Minimum0
Maximum21
Zeros84
Zeros (%)32.3%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:37.534192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile11
Maximum21
Range21
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.646945
Coefficient of variation (CV)1.4410421
Kurtosis5.5607575
Mean2.5307692
Median Absolute Deviation (MAD)1
Skewness2.2261825
Sum658
Variance13.300208
MonotonicityNot monotonic
2023-12-11T06:33:37.944930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 84
32.3%
1 70
26.9%
2 31
 
11.9%
3 17
 
6.5%
4 11
 
4.2%
6 8
 
3.1%
5 7
 
2.7%
11 6
 
2.3%
9 5
 
1.9%
12 5
 
1.9%
Other values (6) 16
 
6.2%
ValueCountFrequency (%)
0 84
32.3%
1 70
26.9%
2 31
 
11.9%
3 17
 
6.5%
4 11
 
4.2%
5 7
 
2.7%
6 8
 
3.1%
7 4
 
1.5%
8 3
 
1.2%
9 5
 
1.9%
ValueCountFrequency (%)
21 2
 
0.8%
14 1
 
0.4%
13 3
 
1.2%
12 5
1.9%
11 6
2.3%
10 3
 
1.2%
9 5
1.9%
8 3
 
1.2%
7 4
1.5%
6 8
3.1%

청각장애인수(명)
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55384615
Minimum0
Maximum10
Zeros191
Zeros (%)73.5%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:38.094119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2243447
Coefficient of variation (CV)2.2106223
Kurtosis15.705005
Mean0.55384615
Median Absolute Deviation (MAD)0
Skewness3.3342677
Sum144
Variance1.4990199
MonotonicityNot monotonic
2023-12-11T06:33:38.227747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 191
73.5%
1 36
 
13.8%
2 12
 
4.6%
3 9
 
3.5%
4 8
 
3.1%
5 3
 
1.2%
10 1
 
0.4%
ValueCountFrequency (%)
0 191
73.5%
1 36
 
13.8%
2 12
 
4.6%
3 9
 
3.5%
4 8
 
3.1%
5 3
 
1.2%
10 1
 
0.4%
ValueCountFrequency (%)
10 1
 
0.4%
5 3
 
1.2%
4 8
 
3.1%
3 9
 
3.5%
2 12
 
4.6%
1 36
 
13.8%
0 191
73.5%

언어장애인수(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
254 
1
 
5
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 254
97.7%
1 5
 
1.9%
2 1
 
0.4%

Length

2023-12-11T06:33:38.379466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:38.488081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 254
97.7%
1 5
 
1.9%
2 1
 
0.4%

안면장애인수(명)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
260 

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 (%)
0 260
100.0%

Length

2023-12-11T06:33:38.607556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:38.713897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 260
100.0%

신장장애인수(명)
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
251 
1
 
8
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 251
96.5%
1 8
 
3.1%
2 1
 
0.4%

Length

2023-12-11T06:33:38.809366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:38.918238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 251
96.5%
1 8
 
3.1%
2 1
 
0.4%

심장장애인수(명)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
258 
1
 
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 row0

Common Values

ValueCountFrequency (%)
0 258
99.2%
1 2
 
0.8%

Length

2023-12-11T06:33:39.012386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:39.100664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 258
99.2%
1 2
 
0.8%

간장애인수(명)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
260 

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 (%)
0 260
100.0%

Length

2023-12-11T06:33:39.187175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:39.267464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 260
100.0%

호흡기장애인수(명)
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
250 
1
 
7
2
 
2
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 250
96.2%
1 7
 
2.7%
2 2
 
0.8%
3 1
 
0.4%

Length

2023-12-11T06:33:39.351614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:39.440875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 250
96.2%
1 7
 
2.7%
2 2
 
0.8%
3 1
 
0.4%

장루요루장애인수(명)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
258 
1
 
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 row0

Common Values

ValueCountFrequency (%)
0 258
99.2%
1 2
 
0.8%

Length

2023-12-11T06:33:39.533953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:39.618471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 258
99.2%
1 2
 
0.8%

뇌전증장애인수(명)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
260 

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 (%)
0 260
100.0%

Length

2023-12-11T06:33:39.724322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:39.831387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 260
100.0%

지적장애인수(명)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34615385
Minimum0
Maximum5
Zeros202
Zeros (%)77.7%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:39.905545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.79779172
Coefficient of variation (CV)2.3047316
Kurtosis12.018512
Mean0.34615385
Median Absolute Deviation (MAD)0
Skewness3.1572844
Sum90
Variance0.63647164
MonotonicityNot monotonic
2023-12-11T06:33:39.999470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 202
77.7%
1 39
 
15.0%
2 12
 
4.6%
3 3
 
1.2%
4 2
 
0.8%
5 2
 
0.8%
ValueCountFrequency (%)
0 202
77.7%
1 39
 
15.0%
2 12
 
4.6%
3 3
 
1.2%
4 2
 
0.8%
5 2
 
0.8%
ValueCountFrequency (%)
5 2
 
0.8%
4 2
 
0.8%
3 3
 
1.2%
2 12
 
4.6%
1 39
 
15.0%
0 202
77.7%

정신장애인수(명)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
257 
1
 
3

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 (%)
0 257
98.8%
1 3
 
1.2%

Length

2023-12-11T06:33:40.108956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:40.223112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 257
98.8%
1 3
 
1.2%

자폐성장애인수(명)
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
0
244 
1
 
15
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 244
93.8%
1 15
 
5.8%
3 1
 
0.4%

Length

2023-12-11T06:33:40.317622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:40.421202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 244
93.8%
1 15
 
5.8%
3 1
 
0.4%

중복장애인수(명)
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66923077
Minimum0
Maximum8
Zeros182
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T06:33:40.544607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.388805
Coefficient of variation (CV)2.0752259
Kurtosis9.0479544
Mean0.66923077
Median Absolute Deviation (MAD)0
Skewness2.8399032
Sum174
Variance1.9287793
MonotonicityNot monotonic
2023-12-11T06:33:40.679419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 182
70.0%
1 38
 
14.6%
2 17
 
6.5%
3 9
 
3.5%
4 5
 
1.9%
5 4
 
1.5%
8 2
 
0.8%
6 2
 
0.8%
7 1
 
0.4%
ValueCountFrequency (%)
0 182
70.0%
1 38
 
14.6%
2 17
 
6.5%
3 9
 
3.5%
4 5
 
1.9%
5 4
 
1.5%
6 2
 
0.8%
7 1
 
0.4%
8 2
 
0.8%
ValueCountFrequency (%)
8 2
 
0.8%
7 1
 
0.4%
6 2
 
0.8%
5 4
 
1.5%
4 5
 
1.9%
3 9
 
3.5%
2 17
 
6.5%
1 38
 
14.6%
0 182
70.0%

Interactions

2023-12-11T06:33:34.854409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.267931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.096045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.883837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.729944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.666842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.340010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.102929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.942602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.347726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.196460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.978044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.811284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.767886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.426934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.178074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.045183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.433866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.312768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.094037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.907051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.866882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.547679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.259217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.166153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.536400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.413521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.197819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.028431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.952134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.644351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.355676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.265368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.689990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.497077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.314894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.111381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.027888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.741542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.458558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.378405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.768084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.573102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.412690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.190171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.099211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.827363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.556352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.508770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.867821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.674342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.512110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.273211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.173531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.919241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.676698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:35.606065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:29.984319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:30.762063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:31.632168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:32.572079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:33.246147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.009193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:34.761595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:33:40.778295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)언어장애인수(명)신장장애인수(명)심장장애인수(명)호흡기장애인수(명)장루요루장애인수(명)지적장애인수(명)정신장애인수(명)자폐성장애인수(명)중복장애인수(명)
기준년도1.0000.0000.3700.2750.2730.2140.1950.3530.1350.0000.0000.0800.2070.1730.0000.461
시군명0.0001.0000.6300.6400.6470.4620.5170.0000.0000.0000.0000.0000.3930.0000.4040.000
총계(명)0.3700.6301.0000.7970.9020.7260.6040.4920.3350.0870.3730.1160.5010.0000.2690.529
지체장애인수(명)0.2750.6400.7971.0000.6960.4760.5610.3960.0000.1520.4990.1950.3350.1220.2320.558
뇌병변장애인수(명)0.2730.6470.9020.6961.0000.5440.4100.5780.0000.0000.0000.1640.5010.0000.1470.419
시각장애인수(명)0.2140.4620.7260.4760.5441.0000.5220.3390.1420.1590.1950.0000.4940.0000.3490.530
청각장애인수(명)0.1950.5170.6040.5610.4100.5221.0000.3040.0000.0000.0000.0000.2540.2750.1070.483
언어장애인수(명)0.3530.0000.4920.3960.5780.3390.3041.0000.0000.0000.0000.0000.5500.1400.0000.423
신장장애인수(명)0.1350.0000.3350.0000.0000.1420.0000.0001.0000.0000.0000.0000.4420.0000.0000.000
심장장애인수(명)0.0000.0000.0870.1520.0000.1590.0000.0000.0001.0000.0000.0000.0000.0000.0000.000
호흡기장애인수(명)0.0000.0000.3730.4990.0000.1950.0000.0000.0000.0001.0000.0000.4210.0000.0000.174
장루요루장애인수(명)0.0800.0000.1160.1950.1640.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.123
지적장애인수(명)0.2070.3930.5010.3350.5010.4940.2540.5500.4420.0000.4210.0001.0000.0000.3390.368
정신장애인수(명)0.1730.0000.0000.1220.0000.0000.2750.1400.0000.0000.0000.0000.0001.0000.0000.000
자폐성장애인수(명)0.0000.4040.2690.2320.1470.3490.1070.0000.0000.0000.0000.0000.3390.0001.0000.611
중복장애인수(명)0.4610.0000.5290.5580.4190.5300.4830.4230.0000.0000.1740.1230.3680.0000.6111.000
2023-12-11T06:33:40.942569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
언어장애인수(명)신장장애인수(명)정신장애인수(명)자폐성장애인수(명)심장장애인수(명)시군명장루요루장애인수(명)호흡기장애인수(명)
언어장애인수(명)1.0000.0000.2310.0000.0000.0000.0000.000
신장장애인수(명)0.0001.0000.0000.0000.0000.0000.0000.000
정신장애인수(명)0.2310.0001.0000.0000.0000.0000.0000.000
자폐성장애인수(명)0.0000.0000.0001.0000.0000.2100.0000.000
심장장애인수(명)0.0000.0000.0000.0001.0000.0000.0000.000
시군명0.0000.0000.0000.2100.0001.0000.0000.000
장루요루장애인수(명)0.0000.0000.0000.0000.0000.0001.0000.000
호흡기장애인수(명)0.0000.0000.0000.0000.0000.0000.0001.000
2023-12-11T06:33:41.086128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도총계(명)지체장애인수(명)뇌병변장애인수(명)시각장애인수(명)청각장애인수(명)지적장애인수(명)중복장애인수(명)시군명언어장애인수(명)신장장애인수(명)심장장애인수(명)호흡기장애인수(명)장루요루장애인수(명)정신장애인수(명)자폐성장애인수(명)
기준년도1.000-0.271-0.206-0.270-0.280-0.149-0.140-0.1190.0000.1630.0530.0000.0000.0740.1700.000
총계(명)-0.2711.0000.9150.8820.7490.4870.4230.4200.2700.3180.1670.0580.2350.0980.0000.202
지체장애인수(명)-0.2060.9151.0000.7410.6250.4260.3080.3290.2710.1410.0000.1060.3320.1610.1850.095
뇌병변장애인수(명)-0.2700.8820.7411.0000.5540.2940.4000.2620.2220.5180.0000.0000.0000.1670.0580.195
시각장애인수(명)-0.2800.7490.6250.5541.0000.4610.3610.3750.1880.2270.0880.1170.0870.0000.0000.234
청각장애인수(명)-0.1490.4870.4260.2940.4611.0000.2500.3430.2000.2180.0000.0000.0000.0000.2960.000
지적장애인수(명)-0.1400.4230.3080.4000.3610.2501.0000.2290.1740.2680.2030.0000.2830.0000.0000.148
중복장애인수(명)-0.1190.4200.3290.2620.3750.3430.2291.0000.0000.2040.0000.0000.1100.1200.0000.330
시군명0.0000.2700.2710.2220.1880.2000.1740.0001.0000.0000.0000.0000.0000.0000.0000.210
언어장애인수(명)0.1630.3180.1410.5180.2270.2180.2680.2040.0001.0000.0000.0000.0000.0000.2310.000
신장장애인수(명)0.0530.1670.0000.0000.0880.0000.2030.0000.0000.0001.0000.0000.0000.0000.0000.000
심장장애인수(명)0.0000.0580.1060.0000.1170.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.000
호흡기장애인수(명)0.0000.2350.3320.0000.0870.0000.2830.1100.0000.0000.0000.0001.0000.0000.0000.000
장루요루장애인수(명)0.0740.0980.1610.1670.0000.0000.0000.1200.0000.0000.0000.0000.0001.0000.0000.000
정신장애인수(명)0.1700.0000.1850.0580.0000.2960.0000.0000.0000.2310.0000.0000.0000.0001.0000.000
자폐성장애인수(명)0.0000.2020.0950.1950.2340.0000.1480.3300.2100.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T06:33:35.780809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:33:36.110449image/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

기준년도시군명총계(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)중복장애인수(명)
02022가평군20200000000000000
12022고양시2616910000000000000
22022과천시00000000000000000
32022광명시41100000000000000
42022광주시62400000000000000
52022구리시00000000000000000
62022군포시52110000000000000
72022김포시75200000000000000
82022남양주시28171120001001000004
92022동두천시31200000000000000
기준년도시군명총계(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)중복장애인수(명)
2502013안양시186750000000000000
2512013양평군103330000000000001
2522013여주시73300000000000001
2532013오산시62210001000000000
2542013용인시2871470000000000000
2552013의왕시61400000000001000
2562013이천시93040001000000001
2572013평택시196461000001000001
2582013하남시31200000000000000
2592013화성시72400000000001000