Overview

Dataset statistics

Number of variables9
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory80.1 B

Variable types

Categorical4
Numeric2
Text1
DateTime2

Dataset

Description인천광역시 연수구 개발행위 허가 현황의 데이터로 연도, 연번, 동명, 지번, 면적, 허가목적, 용도, 허가일, 준공일 등 입니다.
Author인천광역시 연수구
URLhttps://www.data.go.kr/data/15036828/fileData.do

Alerts

연도 has constant value ""Constant
연번 is highly overall correlated with 용도High correlation
동명 is highly overall correlated with 용도High correlation
허가목적 is highly overall correlated with 용도High correlation
용도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:17:23.963203
Analysis finished2024-04-06 08:17:26.863960
Duration2.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023
26 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 26
100.0%

Length

2024-04-06T17:17:27.009889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:27.186366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 26
100.0%

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-06T17:17:27.369850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2024-04-06T17:17:27.712469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

동명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
옥련동
11 
동춘동
10 
선학동
3 
연수동
2 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row선학동
2nd row선학동
3rd row옥련동
4th row옥련동
5th row옥련동

Common Values

ValueCountFrequency (%)
옥련동 11
42.3%
동춘동 10
38.5%
선학동 3
 
11.5%
연수동 2
 
7.7%

Length

2024-04-06T17:17:27.966991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:28.165856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥련동 11
42.3%
동춘동 10
38.5%
선학동 3
 
11.5%
연수동 2
 
7.7%

지번
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-06T17:17:28.587176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7692308
Min length3

Characters and Unicode

Total characters124
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)92.3%

Sample

1st row137-22
2nd row137-4
3rd row79-1
4th row79-21
5th row79-31
ValueCountFrequency (%)
79-21 2
 
7.7%
137-22 1
 
3.8%
53-9 1
 
3.8%
405-8 1
 
3.8%
175 1
 
3.8%
636 1
 
3.8%
232-4 1
 
3.8%
475-1 1
 
3.8%
405-33 1
 
3.8%
405-18 1
 
3.8%
Other values (15) 15
57.7%
2024-04-06T17:17:29.471852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 23
18.5%
5 18
14.5%
1 17
13.7%
3 16
12.9%
7 11
8.9%
2 11
8.9%
9 9
 
7.3%
4 7
 
5.6%
0 6
 
4.8%
6 3
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
81.5%
Dash Punctuation 23
 
18.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 18
17.8%
1 17
16.8%
3 16
15.8%
7 11
10.9%
2 11
10.9%
9 9
8.9%
4 7
 
6.9%
0 6
 
5.9%
6 3
 
3.0%
8 3
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 23
18.5%
5 18
14.5%
1 17
13.7%
3 16
12.9%
7 11
8.9%
2 11
8.9%
9 9
 
7.3%
4 7
 
5.6%
0 6
 
4.8%
6 3
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 23
18.5%
5 18
14.5%
1 17
13.7%
3 16
12.9%
7 11
8.9%
2 11
8.9%
9 9
 
7.3%
4 7
 
5.6%
0 6
 
4.8%
6 3
 
2.4%

면적
Real number (ℝ)

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.33115
Minimum4
Maximum1464.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-06T17:17:29.903110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile12.3375
Q143.25
median95
Q3361.25
95-th percentile1083.7
Maximum1464.2
Range1460.2
Interquartile range (IQR)318

Descriptive statistics

Standard deviation394.43638
Coefficient of variation (CV)1.382381
Kurtosis2.5083628
Mean285.33115
Median Absolute Deviation (MAD)75.325
Skewness1.8016065
Sum7418.61
Variance155580.06
MonotonicityNot monotonic
2024-04-06T17:17:30.222350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
95.0 2
 
7.7%
1464.2 1
 
3.8%
20.0 1
 
3.8%
4.0 1
 
3.8%
1051.0 1
 
3.8%
40.5 1
 
3.8%
48.4 1
 
3.8%
77.0 1
 
3.8%
22.56 1
 
3.8%
130.0 1
 
3.8%
Other values (15) 15
57.7%
ValueCountFrequency (%)
4.0 1
3.8%
10.0 1
3.8%
19.35 1
3.8%
20.0 1
3.8%
22.56 1
3.8%
40.5 1
3.8%
43.0 1
3.8%
44.0 1
3.8%
48.4 1
3.8%
60.0 1
3.8%
ValueCountFrequency (%)
1464.2 1
3.8%
1094.6 1
3.8%
1051.0 1
3.8%
704.0 1
3.8%
673.0 1
3.8%
494.0 1
3.8%
391.0 1
3.8%
272.0 1
3.8%
189.0 1
3.8%
172.0 1
3.8%

허가목적
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
건축물의 건축, 토지형질변경(의제, 변경)
15 
공작물설치
6 
건축물의 건축, 토지형질변경(의제)
3 
토지형질변경
 
1
토지형질변경, 공작물설치
 
1

Length

Max length23
Median length23
Mean length17.346154
Min length5

Unique

Unique2 ?
Unique (%)7.7%

Sample

1st row공작물설치
2nd row공작물설치
3rd row건축물의 건축, 토지형질변경(의제)
4th row건축물의 건축, 토지형질변경(의제)
5th row건축물의 건축, 토지형질변경(의제)

Common Values

ValueCountFrequency (%)
건축물의 건축, 토지형질변경(의제, 변경) 15
57.7%
공작물설치 6
 
23.1%
건축물의 건축, 토지형질변경(의제) 3
 
11.5%
토지형질변경 1
 
3.8%
토지형질변경, 공작물설치 1
 
3.8%

Length

2024-04-06T17:17:30.551991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:30.821270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물의 18
23.1%
건축 18
23.1%
토지형질변경(의제 18
23.1%
변경 15
19.2%
공작물설치 7
 
9.0%
토지형질변경 2
 
2.6%

용도
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
공동주택
11 
근린생활시설
4 
태양광시설
4 
포장
3 
옹벽
2 
Other values (2)
2 

Length

Max length10
Median length6
Mean length4.3076923
Min length2

Unique

Unique2 ?
Unique (%)7.7%

Sample

1st row옹벽
2nd row옹벽
3rd row근린생활시설
4th row근린생활시설
5th row근린생활시설

Common Values

ValueCountFrequency (%)
공동주택 11
42.3%
근린생활시설 4
 
15.4%
태양광시설 4
 
15.4%
포장 3
 
11.5%
옹벽 2
 
7.7%
단독주택 1
 
3.8%
포장, 성토, 옹벽 1
 
3.8%

Length

2024-04-06T17:17:31.078027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:31.367682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 11
39.3%
근린생활시설 4
 
14.3%
태양광시설 4
 
14.3%
포장 4
 
14.3%
옹벽 3
 
10.7%
단독주택 1
 
3.6%
성토 1
 
3.6%

허가일
Date

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2023-03-29 00:00:00
Maximum2023-12-15 00:00:00
2024-04-06T17:17:31.627002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:17:31.831291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

준공일
Date

Distinct13
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2023-05-23 00:00:00
Maximum2025-06-30 00:00:00
2024-04-06T17:17:32.054005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:17:32.290914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

Interactions

2024-04-06T17:17:25.394461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:17:24.882940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:17:26.164970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:17:25.097261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:17:32.523160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동명지번면적허가목적용도허가일준공일
연번1.0000.6760.9160.0000.7900.7420.8200.819
동명0.6761.0001.0000.5280.4280.7340.8741.000
지번0.9161.0001.0001.0000.8780.8680.9490.959
면적0.0000.5281.0001.0000.0000.8020.5680.653
허가목적0.7900.4280.8780.0001.0000.8850.8741.000
용도0.7420.7340.8680.8020.8851.0000.9351.000
허가일0.8200.8740.9490.5680.8740.9351.0001.000
준공일0.8191.0000.9590.6531.0001.0001.0001.000
2024-04-06T17:17:32.775692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가목적용도동명
허가목적1.0000.7770.345
용도0.7771.0000.560
동명0.3450.5601.000
2024-04-06T17:17:32.939977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적동명허가목적용도
연번1.000-0.3150.4360.3040.549
면적-0.3151.0000.3520.0000.386
동명0.4360.3521.0000.3450.560
허가목적0.3040.0000.3451.0000.777
용도0.5490.3860.5600.7771.000

Missing values

2024-04-06T17:17:26.417351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:17:26.719842image/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

연도연번동명지번면적허가목적용도허가일준공일
020231선학동137-221464.2공작물설치옹벽2023-03-292023-05-23
120232선학동137-41094.6공작물설치옹벽2023-03-292023-05-23
220233옥련동79-1172.0건축물의 건축, 토지형질변경(의제)근린생활시설2023-03-292025-02-28
320234옥련동79-2195.0건축물의 건축, 토지형질변경(의제)근린생활시설2023-03-292025-02-28
420235옥련동79-3110.0건축물의 건축, 토지형질변경(의제)근린생활시설2023-03-292025-02-28
520236선학동127-3391.0건축물의 건축, 토지형질변경(의제, 변경)근린생활시설2023-05-012023-09-05
620237옥련동351-1919.35공작물설치태양광시설2023-06-302023-10-10
720238동춘동559-13673.0건축물의 건축, 토지형질변경(의제, 변경)단독주택2023-08-012025-03-30
820239동춘동29-343.0건축물의 건축, 토지형질변경(의제, 변경)공동주택2023-08-262024-06-30
9202310동춘동52-12189.0건축물의 건축, 토지형질변경(의제, 변경)공동주택2023-08-262024-06-30
연도연번동명지번면적허가목적용도허가일준공일
16202317옥련동405-17494.0건축물의 건축, 토지형질변경(의제, 변경)공동주택2023-09-062025-06-30
17202318옥련동405-1892.0건축물의 건축, 토지형질변경(의제, 변경)공동주택2023-09-062025-06-30
18202319옥련동405-33130.0건축물의 건축, 토지형질변경(의제, 변경)공동주택2023-09-062025-06-30
19202320연수동475-122.56공작물설치태양광시설2023-09-012024-08-31
20202321동춘동232-477.0토지형질변경포장2023-09-212023-10-17
21202322연수동63648.4공작물설치태양광시설2023-09-212023-12-04
22202323옥련동17540.5공작물설치태양광시설2023-10-102023-11-15
23202324옥련동405-81051.0토지형질변경, 공작물설치포장, 성토, 옹벽2023-11-132024-03-14
24202325옥련동79-2195.0건축물의 건축, 토지형질변경(의제, 변경)포장2023-12-152023-12-27
25202326옥련동79-154.0건축물의 건축, 토지형질변경(의제, 변경)포장2023-12-152023-12-27