Overview

Dataset statistics

Number of variables6
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory54.0 B

Variable types

Numeric3
Categorical3

Dataset

Description제주특별자치도 행정 구역 현황 데이터로, 2010년에서 2020년까지 제주특별자치도 내 도시지역과 비도시지역 구분에 따른 면적 및 비율 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15096917/fileData.do

Alerts

시도 has constant value ""Constant
면적 is highly overall correlated with 비율 and 2 other fieldsHigh correlation
비율 is highly overall correlated with 면적 and 2 other fieldsHigh correlation
시군구 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
지역 구분 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
면적 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:40:59.712255
Analysis finished2023-12-12 13:41:01.265516
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015
Minimum2010
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T22:41:01.343363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2010
Q12012
median2015
Q32018
95-th percentile2020
Maximum2020
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.198837
Coefficient of variation (CV)0.0015875122
Kurtosis-1.2210801
Mean2015
Median Absolute Deviation (MAD)3
Skewness0
Sum88660
Variance10.232558
MonotonicityNot monotonic
2023-12-12T22:41:01.492876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2010 4
9.1%
2011 4
9.1%
2012 4
9.1%
2013 4
9.1%
2014 4
9.1%
2015 4
9.1%
2016 4
9.1%
2017 4
9.1%
2018 4
9.1%
2019 4
9.1%
ValueCountFrequency (%)
2010 4
9.1%
2011 4
9.1%
2012 4
9.1%
2013 4
9.1%
2014 4
9.1%
2015 4
9.1%
2016 4
9.1%
2017 4
9.1%
2018 4
9.1%
2019 4
9.1%
ValueCountFrequency (%)
2020 4
9.1%
2019 4
9.1%
2018 4
9.1%
2017 4
9.1%
2016 4
9.1%
2015 4
9.1%
2014 4
9.1%
2013 4
9.1%
2012 4
9.1%
2011 4
9.1%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
제주특별자치도
44 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주특별자치도 44
100.0%

Length

2023-12-12T22:41:01.651533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:01.785358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 44
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
제주시
22 
서귀포시
22 

Length

Max length4
Median length3.5
Mean length3.5
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주시
2nd row서귀포시
3rd row제주시
4th row서귀포시
5th row제주시

Common Values

ValueCountFrequency (%)
제주시 22
50.0%
서귀포시 22
50.0%

Length

2023-12-12T22:41:01.914684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:02.027691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 22
50.0%
서귀포시 22
50.0%

지역 구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
도시지역
22 
비도시지역
22 

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도시지역 22
50.0%
비도시지역 22
50.0%

Length

2023-12-12T22:41:02.150315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:02.282719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시지역 22
50.0%
비도시지역 22
50.0%

면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6237896 × 108
Minimum92459811
Maximum8.8606684 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T22:41:02.431707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92459811
5-th percentile92464216
Q12.0372648 × 108
median4.354108 × 108
Q36.9440351 × 108
95-th percentile8.8604214 × 108
Maximum8.8606684 × 108
Range7.9360703 × 108
Interquartile range (IQR)4.9067704 × 108

Descriptive statistics

Standard deviation3.1725833 × 108
Coefficient of variation (CV)0.68614354
Kurtosis-1.6507546
Mean4.6237896 × 108
Median Absolute Deviation (MAD)2.6903435 × 108
Skewness0.16139891
Sum2.0344674 × 1010
Variance1.0065285 × 1017
MonotonicityNot monotonic
2023-12-12T22:41:02.587252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
885519893 1
 
2.3%
240761850 1
 
2.3%
240758853 1
 
2.3%
92465305 1
 
2.3%
240767101 1
 
2.3%
92465283 1
 
2.3%
240766709 1
 
2.3%
92464028 1
 
2.3%
240767136 1
 
2.3%
92495338 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
92459811 1
2.3%
92463102 1
2.3%
92464028 1
2.3%
92465283 1
2.3%
92465305 1
2.3%
92495338 1
2.3%
92504319 1
2.3%
92618903 1
2.3%
92626767 1
2.3%
92627566 1
2.3%
ValueCountFrequency (%)
886066839 1
2.3%
886065505 1
2.3%
886042192 1
2.3%
886041854 1
2.3%
885922676 1
2.3%
885909484 1
2.3%
885867608 1
2.3%
885866408 1
2.3%
885851693 1
2.3%
885785544 1
2.3%

비율
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50
Minimum9.5
Maximum90.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T22:41:02.729036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.5
5-th percentile9.5
Q123.075
median50
Q376.925
95-th percentile90.5
Maximum90.5
Range81
Interquartile range (IQR)53.85

Descriptive statistics

Standard deviation33.095141
Coefficient of variation (CV)0.66190282
Kurtosis-1.7790752
Mean50
Median Absolute Deviation (MAD)31.45
Skewness4.0344685 × 10-17
Sum2200
Variance1095.2884
MonotonicityNot monotonic
2023-12-12T22:41:02.839149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
90.5 11
25.0%
9.5 11
25.0%
72.4 8
18.2%
27.6 8
18.2%
72.3 3
 
6.8%
27.7 3
 
6.8%
ValueCountFrequency (%)
9.5 11
25.0%
27.6 8
18.2%
27.7 3
 
6.8%
72.3 3
 
6.8%
72.4 8
18.2%
90.5 11
25.0%
ValueCountFrequency (%)
90.5 11
25.0%
72.4 8
18.2%
72.3 3
 
6.8%
27.7 3
 
6.8%
27.6 8
18.2%
9.5 11
25.0%

Interactions

2023-12-12T22:41:00.647155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:40:59.940870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.285445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.780264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.052807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.406812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.920709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.186266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:00.532198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:41:02.925619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군구지역 구분면적비율
연도1.0000.0000.0000.0000.000
시군구0.0001.0000.0001.0001.000
지역 구분0.0000.0001.0001.0001.000
면적0.0001.0001.0001.0001.000
비율0.0001.0001.0001.0001.000
2023-12-12T22:41:03.013804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구지역 구분
시군구1.0000.000
지역 구분0.0001.000
2023-12-12T22:41:03.121918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도면적비율시군구지역 구분
연도1.0000.2000.0000.0000.000
면적0.2001.0000.9670.9760.976
비율0.0000.9671.0000.9760.976
시군구0.0000.9760.9761.0000.000
지역 구분0.0000.9760.9760.0001.000

Missing values

2023-12-12T22:41:01.087518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:41:01.210465image/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

연도시도시군구지역 구분면적비율
02010제주특별자치도제주시도시지역88551989390.5
12010제주특별자치도서귀포시도시지역63010742672.4
22011제주특별자치도제주시도시지역88578554490.5
32011제주특별자치도서귀포시도시지역63017246272.4
42012제주특별자치도제주시도시지역88586760890.5
52012제주특별자치도서귀포시도시지역63019581072.4
62013제주특별자치도제주시도시지역88586640890.5
72013제주특별자치도서귀포시도시지역63016437672.4
82014제주특별자치도제주시도시지역88585169390.5
92014제주특별자치도서귀포시도시지역62996265272.3
연도시도시군구지역 구분면적비율
342016제주특별자치도제주시비도시지역925043199.5
352016제주특별자치도서귀포시비도시지역24076185727.7
362017제주특별자치도제주시비도시지역926189039.5
372017제주특별자치도서귀포시비도시지역24079081727.6
382018제주특별자치도제주시비도시지역926293419.5
392018제주특별자치도서귀포시비도시지역24079571527.6
402019제주특별자치도제주시비도시지역926267679.5
412019제주특별자치도서귀포시비도시지역24086038127.6
422020제주특별자치도제주시비도시지역926275669.5
432020제주특별자치도서귀포시비도시지역24086160027.6