Overview

Dataset statistics

Number of variables5
Number of observations372
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory44.4 B

Variable types

Numeric4
Categorical1

Dataset

Description시군별 주민등록인구 대비 장애인 비율현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7K610D6JKOBKSTADK9FC24785755&infSeq=1

Alerts

주민등록인구수(명) is highly overall correlated with 등록장애인수(명) and 2 other fieldsHigh correlation
등록장애인수(명) is highly overall correlated with 주민등록인구수(명) and 1 other fieldsHigh correlation
등록장애인비율(%) is highly overall correlated with 주민등록인구수(명) and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 주민등록인구수(명) and 2 other fieldsHigh correlation
주민등록인구수(명) has unique valuesUnique

Reproduction

Analysis started2024-04-14 03:06:47.201063
Analysis finished2024-04-14 03:06:49.604612
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct12
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-14T12:06:49.646706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014.75
median2017.5
Q32020.25
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4567018
Coefficient of variation (CV)0.001713359
Kurtosis-1.2169934
Mean2017.5
Median Absolute Deviation (MAD)3
Skewness0
Sum750510
Variance11.948787
MonotonicityDecreasing
2024-04-14T12:06:49.727517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2023 31
8.3%
2022 31
8.3%
2021 31
8.3%
2020 31
8.3%
2019 31
8.3%
2018 31
8.3%
2017 31
8.3%
2016 31
8.3%
2015 31
8.3%
2014 31
8.3%
Other values (2) 62
16.7%
ValueCountFrequency (%)
2012 31
8.3%
2013 31
8.3%
2014 31
8.3%
2015 31
8.3%
2016 31
8.3%
2017 31
8.3%
2018 31
8.3%
2019 31
8.3%
2020 31
8.3%
2021 31
8.3%
ValueCountFrequency (%)
2023 31
8.3%
2022 31
8.3%
2021 31
8.3%
2020 31
8.3%
2019 31
8.3%
2018 31
8.3%
2017 31
8.3%
2016 31
8.3%
2015 31
8.3%
2014 31
8.3%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
가평군
 
12
고양시
 
12
과천시
 
12
광명시
 
12
광주시
 
12
Other values (26)
312 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가평군 12
 
3.2%
고양시 12
 
3.2%
과천시 12
 
3.2%
광명시 12
 
3.2%
광주시 12
 
3.2%
구리시 12
 
3.2%
군포시 12
 
3.2%
김포시 12
 
3.2%
남양주시 12
 
3.2%
동두천시 12
 
3.2%
Other values (21) 252
67.7%

Length

2024-04-14T12:06:49.816058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 12
 
3.2%
안양시 12
 
3.2%
하남시 12
 
3.2%
포천시 12
 
3.2%
평택시 12
 
3.2%
파주시 12
 
3.2%
이천시 12
 
3.2%
의정부시 12
 
3.2%
의왕시 12
 
3.2%
용인시 12
 
3.2%
Other values (21) 252
67.7%

주민등록인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct372
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean417243.49
Minimum41584
Maximum1202628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-14T12:06:49.908894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41584
5-th percentile61877.05
Q1158773
median312442
Q3602576
95-th percentile1074504.9
Maximum1202628
Range1161044
Interquartile range (IQR)443803

Descriptive statistics

Standard deviation322235.87
Coefficient of variation (CV)0.77229692
Kurtosis-0.34609601
Mean417243.49
Median Absolute Deviation (MAD)190665.5
Skewness0.87811144
Sum1.5521458 × 108
Variance1.0383595 × 1011
MonotonicityNot monotonic
2024-04-14T12:06:50.016626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62302 1
 
0.3%
209330 1
 
0.3%
349990 1
 
0.3%
287519 1
 
0.3%
186721 1
 
0.3%
312579 1
 
0.3%
344978 1
 
0.3%
68946 1
 
0.3%
1027546 1
 
0.3%
62008 1
 
0.3%
Other values (362) 362
97.3%
ValueCountFrequency (%)
41584 1
0.3%
42062 1
0.3%
42721 1
0.3%
43516 1
0.3%
43824 1
0.3%
44633 1
0.3%
45348 1
0.3%
45363 1
0.3%
45431 1
0.3%
45599 1
0.3%
ValueCountFrequency (%)
1202628 1
0.3%
1201166 1
0.3%
1197257 1
0.3%
1194465 1
0.3%
1190964 1
0.3%
1186078 1
0.3%
1185179 1
0.3%
1184624 1
0.3%
1183714 1
0.3%
1174228 1
0.3%

등록장애인수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct367
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17515.586
Minimum1863
Maximum44396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-14T12:06:50.119715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1863
5-th percentile3406.65
Q18042.25
median13073
Q325058.5
95-th percentile38531.8
Maximum44396
Range42533
Interquartile range (IQR)17016.25

Descriptive statistics

Standard deviation11616.852
Coefficient of variation (CV)0.66322944
Kurtosis-0.77216218
Mean17515.586
Median Absolute Deviation (MAD)6919.5
Skewness0.69156957
Sum6515798
Variance1.3495126 × 108
MonotonicityNot monotonic
2024-04-14T12:06:50.217051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3438 2
 
0.5%
3358 2
 
0.5%
10214 2
 
0.5%
35921 2
 
0.5%
11213 2
 
0.5%
10957 1
 
0.3%
7873 1
 
0.3%
13599 1
 
0.3%
13889 1
 
0.3%
2152 1
 
0.3%
Other values (357) 357
96.0%
ValueCountFrequency (%)
1863 1
0.3%
1879 1
0.3%
1898 1
0.3%
1962 1
0.3%
2070 1
0.3%
2152 1
0.3%
2154 1
0.3%
2166 1
0.3%
2175 1
0.3%
2225 1
0.3%
ValueCountFrequency (%)
44396 1
0.3%
44033 1
0.3%
43501 1
0.3%
43065 1
0.3%
42894 1
0.3%
42689 1
0.3%
42414 1
0.3%
42393 1
0.3%
42247 1
0.3%
41908 1
0.3%

등록장애인비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7575538
Minimum2.8
Maximum12.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-14T12:06:50.318347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.8
5-th percentile3.364
Q13.87
median4.4
Q35.125
95-th percentile7.4
Maximum12.1
Range9.3
Interquartile range (IQR)1.255

Descriptive statistics

Standard deviation1.3220947
Coefficient of variation (CV)0.2778938
Kurtosis2.781937
Mean4.7575538
Median Absolute Deviation (MAD)0.6
Skewness1.4997499
Sum1769.81
Variance1.7479344
MonotonicityNot monotonic
2024-04-14T12:06:50.415777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.9 25
 
6.7%
4.5 24
 
6.5%
4.4 23
 
6.2%
3.8 22
 
5.9%
3.6 17
 
4.6%
4.3 15
 
4.0%
4.2 14
 
3.8%
3.7 14
 
3.8%
4.1 12
 
3.2%
6.6 11
 
3.0%
Other values (68) 195
52.4%
ValueCountFrequency (%)
2.8 1
 
0.3%
2.9 1
 
0.3%
3.0 1
 
0.3%
3.1 5
1.3%
3.2 4
 
1.1%
3.26 1
 
0.3%
3.3 5
1.3%
3.32 1
 
0.3%
3.4 10
2.7%
3.43 1
 
0.3%
ValueCountFrequency (%)
12.1 1
 
0.3%
8.5 2
 
0.5%
8.41 1
 
0.3%
8.4 5
1.3%
8.3 2
 
0.5%
8.2 2
 
0.5%
8.1 2
 
0.5%
7.9 1
 
0.3%
7.52 1
 
0.3%
7.4 4
1.1%

Interactions

2024-04-14T12:06:49.182532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.239701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.675036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.931670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:49.245416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.346023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.740181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.994799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:49.329701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.550971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.807097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:49.060870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:49.407272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.610156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:48.867299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:06:49.122573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T12:06:50.480159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명주민등록인구수(명)등록장애인수(명)등록장애인비율(%)
기준년도1.0000.0000.0000.0000.000
시군명0.0001.0000.9780.9500.926
주민등록인구수(명)0.0000.9781.0000.9510.656
등록장애인수(명)0.0000.9500.9511.0000.574
등록장애인비율(%)0.0000.9260.6560.5741.000
2024-04-14T12:06:50.555098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도주민등록인구수(명)등록장애인수(명)등록장애인비율(%)시군명
기준년도1.0000.0590.0920.0600.000
주민등록인구수(명)0.0591.0000.979-0.5790.826
등록장애인수(명)0.0920.9791.000-0.4350.712
등록장애인비율(%)0.060-0.579-0.4351.0000.672
시군명0.0000.8260.7120.6721.000

Missing values

2024-04-14T12:06:49.501215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T12:06:49.570548image/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

기준년도시군명주민등록인구수(명)등록장애인수(명)등록장애인비율(%)
02023가평군6230250708.1
12023고양시1074907424143.9
22023과천시8100022932.8
32023광명시280197123814.4
42023광주시391377174714.5
52023구리시18709385524.6
62023군포시261229117344.5
72023김포시486172189543.9
82023남양주시732265331724.5
92023동두천시8862663237.1
기준년도시군명주민등록인구수(명)등록장애인수(명)등록장애인비율(%)
3622012오산시20029175713.8
3632012용인시915959305753.3
3642012의왕시15475759863.9
3652012의정부시429147190474.4
3662012이천시204917102595.0
3672012파주시394201180144.6
3682012평택시434305220595.1
3692012포천시15755997156.2
3702012하남시14626968594.7
3712012화성시525490203803.9