Overview

Dataset statistics

Number of variables4
Number of observations170
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory34.8 B

Variable types

Categorical3
Numeric1

Dataset

Description행정구역(시도별) 귀촌 가구수 현황(2013년 ~ 2014년)정보
Author농림축산식품부
URLhttps://www.data.go.kr/data/15044119/fileData.do

Alerts

가구수 has 30 (17.6%) zerosZeros

Reproduction

Analysis started2023-12-12 06:18:25.565306
Analysis finished2023-12-12 06:18:26.002229
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2013
85 
2014
85 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 85
50.0%
2014 85
50.0%

Length

2023-12-12T15:18:26.084992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:18:26.199368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 85
50.0%
2014 85
50.0%

시도
Categorical

Distinct17
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
전국
 
10
부산광역시
 
10
대구광역시
 
10
인천광역시
 
10
광주광역시
 
10
Other values (12)
120 

Length

Max length7
Median length5
Mean length4.4705882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전국 10
 
5.9%
부산광역시 10
 
5.9%
대구광역시 10
 
5.9%
인천광역시 10
 
5.9%
광주광역시 10
 
5.9%
대전광역시 10
 
5.9%
울산광역시 10
 
5.9%
세종특별자치시 10
 
5.9%
경기도 10
 
5.9%
강원도 10
 
5.9%
Other values (7) 70
41.2%

Length

2023-12-12T15:18:26.307499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전국 10
 
5.9%
강원도 10
 
5.9%
경상남도 10
 
5.9%
경상북도 10
 
5.9%
전라남도 10
 
5.9%
전라북도 10
 
5.9%
충청남도 10
 
5.9%
충청북도 10
 
5.9%
경기도 10
 
5.9%
부산광역시 10
 
5.9%
Other values (7) 70
41.2%

가구원수별
Categorical

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
귀촌가구수 계
34 
1인가구
34 
2인가구
34 
3인가구
34 
4인가구이상
34 

Length

Max length7
Median length4
Mean length5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row귀촌가구수 계
2nd row1인가구
3rd row2인가구
4th row3인가구
5th row4인가구이상

Common Values

ValueCountFrequency (%)
귀촌가구수 계 34
20.0%
1인가구 34
20.0%
2인가구 34
20.0%
3인가구 34
20.0%
4인가구이상 34
20.0%

Length

2023-12-12T15:18:26.423975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:18:26.529319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
귀촌가구수 34
16.7%
계 34
16.7%
1인가구 34
16.7%
2인가구 34
16.7%
3인가구 34
16.7%
4인가구이상 34
16.7%

가구수
Real number (ℝ)

ZEROS 

Distinct129
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1292.7765
Minimum0
Maximum33442
Zeros30
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:18:26.665384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.25
median187.5
Q3864.75
95-th percentile4402.8
Maximum33442
Range33442
Interquartile range (IQR)858.5

Descriptive statistics

Standard deviation3644.0275
Coefficient of variation (CV)2.8187607
Kurtosis42.818415
Mean1292.7765
Median Absolute Deviation (MAD)187.5
Skewness5.9350124
Sum219772
Variance13278936
MonotonicityNot monotonic
2023-12-12T15:18:26.823554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
 
17.6%
1 5
 
2.9%
3 3
 
1.8%
2 2
 
1.2%
9 2
 
1.2%
29 2
 
1.2%
7 2
 
1.2%
14 2
 
1.2%
204 2
 
1.2%
4233 1
 
0.6%
Other values (119) 119
70.0%
ValueCountFrequency (%)
0 30
17.6%
1 5
 
2.9%
2 2
 
1.2%
3 3
 
1.8%
4 1
 
0.6%
5 1
 
0.6%
6 1
 
0.6%
7 2
 
1.2%
9 2
 
1.2%
10 1
 
0.6%
ValueCountFrequency (%)
33442 1
0.6%
21501 1
0.6%
16904 1
0.6%
11764 1
0.6%
10149 1
0.6%
8681 1
0.6%
8499 1
0.6%
5329 1
0.6%
4455 1
0.6%
4339 1
0.6%

Interactions

2023-12-12T15:18:25.723923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:18:26.921881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시도가구원수별가구수
연도1.0000.0000.0000.000
시도0.0001.0000.0000.289
가구원수별0.0000.0001.0000.000
가구수0.0000.2890.0001.000
2023-12-12T15:18:27.013577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가구원수별연도시도
가구원수별1.0000.0000.000
연도0.0001.0000.000
시도0.0000.0001.000
2023-12-12T15:18:27.107493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가구수연도시도가구원수별
가구수1.0000.0000.1280.000
연도0.0001.0000.0000.000
시도0.1280.0001.0000.000
가구원수별0.0000.0000.0001.000

Missing values

2023-12-12T15:18:25.863952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:18:25.965901image/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

연도시도가구원수별가구수
02013전국귀촌가구수 계21501
12013전국1인가구11764
22013전국2인가구5329
32013전국3인가구2389
42013전국4인가구이상2019
52013부산광역시귀촌가구수 계26
62013부산광역시1인가구5
72013부산광역시2인가구7
82013부산광역시3인가구3
92013부산광역시4인가구이상11
연도시도가구원수별가구수
1602014경상남도귀촌가구수 계1709
1612014경상남도1인가구831
1622014경상남도2인가구508
1632014경상남도3인가구204
1642014경상남도4인가구이상166
1652014제주특별자치도귀촌가구수 계3569
1662014제주특별자치도1인가구1702
1672014제주특별자치도2인가구610
1682014제주특별자치도3인가구517
1692014제주특별자치도4인가구이상740