Overview

Dataset statistics

Number of variables4
Number of observations180
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory33.7 B

Variable types

Categorical3
Numeric1

Dataset

Description경상남도 양산시에 등록된 장애인 현황입니다. 지체, 시각, 청각, 언어, 지적, 뇌병변,자폐성, 정신, 신장, 심장, 호흡기,간, 안면, 장루, 뇌전증 등 읍면동 현황을 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3065866

Alerts

인원수 has 59 (32.8%) zerosZeros

Reproduction

Analysis started2023-12-22 21:56:57.862426
Analysis finished2023-12-22 21:57:00.094721
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장애유형
Categorical

Distinct15
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
지체
 
12
시각
 
12
청각
 
12
언어
 
12
지적
 
12
Other values (10)
120 

Length

Max length5
Median length2
Mean length2.4
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지체 12
 
6.7%
시각 12
 
6.7%
청각 12
 
6.7%
언어 12
 
6.7%
지적 12
 
6.7%
뇌병변 12
 
6.7%
자폐성 12
 
6.7%
정신 12
 
6.7%
신장 12
 
6.7%
심장 12
 
6.7%
Other values (5) 60
33.3%

Length

2023-12-22T21:57:00.689443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지체 12
 
6.7%
시각 12
 
6.7%
청각 12
 
6.7%
언어 12
 
6.7%
지적 12
 
6.7%
뇌병변 12
 
6.7%
자폐성 12
 
6.7%
정신 12
 
6.7%
신장 12
 
6.7%
심장 12
 
6.7%
Other values (5) 60
33.3%

성별
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
남
90 
여
90 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row남
4th row여
5th row남

Common Values

ValueCountFrequency (%)
남 90
50.0%
여 90
50.0%

Length

2023-12-22T21:57:01.320929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:57:02.098414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 90
50.0%
여 90
50.0%

장애등급
Categorical

Distinct6
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
1급
30 
2급
30 
3급
30 
4급
30 
5급
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1급
2nd row1급
3rd row2급
4th row2급
5th row3급

Common Values

ValueCountFrequency (%)
1급 30
16.7%
2급 30
16.7%
3급 30
16.7%
4급 30
16.7%
5급 30
16.7%
6급 30
16.7%

Length

2023-12-22T21:57:02.672393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-22T21:57:03.228030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1급 30
16.7%
2급 30
16.7%
3급 30
16.7%
4급 30
16.7%
5급 30
16.7%
6급 30
16.7%

인원수
Real number (ℝ)

ZEROS 

Distinct80
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.922222
Minimum0
Maximum1589
Zeros59
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-22T21:57:03.848466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q387.25
95-th percentile343.25
Maximum1589
Range1589
Interquartile range (IQR)87.25

Descriptive statistics

Standard deviation199.1556
Coefficient of variation (CV)2.345153
Kurtosis23.898193
Mean84.922222
Median Absolute Deviation (MAD)6
Skewness4.3994296
Sum15286
Variance39662.955
MonotonicityNot monotonic
2023-12-22T21:57:04.480592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
32.8%
2 10
 
5.6%
1 9
 
5.0%
3 5
 
2.8%
4 4
 
2.2%
7 3
 
1.7%
130 3
 
1.7%
6 3
 
1.7%
8 3
 
1.7%
13 2
 
1.1%
Other values (70) 79
43.9%
ValueCountFrequency (%)
0 59
32.8%
1 9
 
5.0%
2 10
 
5.6%
3 5
 
2.8%
4 4
 
2.2%
5 1
 
0.6%
6 3
 
1.7%
7 3
 
1.7%
8 3
 
1.7%
10 1
 
0.6%
ValueCountFrequency (%)
1589 1
0.6%
1098 1
0.6%
860 1
0.6%
822 1
0.6%
721 1
0.6%
697 1
0.6%
675 1
0.6%
585 1
0.6%
367 1
0.6%
342 1
0.6%

Interactions

2023-12-22T21:56:58.343401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-22T21:57:04.989619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애유형성별장애등급인원수
장애유형1.0000.0000.0000.450
성별0.0001.0000.0000.132
장애등급0.0000.0001.0000.000
인원수0.4500.1320.0001.000
2023-12-22T21:57:05.620544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애등급성별장애유형
장애등급1.0000.0000.000
성별0.0001.0000.000
장애유형0.0000.0001.000
2023-12-22T21:57:06.022686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원수장애유형성별장애등급
인원수1.0000.2060.0960.000
장애유형0.2061.0000.0000.000
성별0.0960.0001.0000.000
장애등급0.0000.0000.0001.000

Missing values

2023-12-22T21:56:58.865470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-22T21:56:59.789497image/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

장애유형성별장애등급인원수
0지체남1급142
1지체여1급72
2지체남2급230
3지체여2급110
4지체남3급675
5지체여3급263
6지체남4급697
7지체여4급585
8지체남5급1098
9지체여5급860
장애유형성별장애등급인원수
170뇌전증남2급2
171뇌전증여2급0
172뇌전증남3급7
173뇌전증여3급7
174뇌전증남4급7
175뇌전증여4급8
176뇌전증남5급1
177뇌전증여5급2
178뇌전증남6급0
179뇌전증여6급0