Overview

Dataset statistics

Number of variables8
Number of observations62
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory68.1 B

Variable types

Numeric2
Categorical3
Text2
DateTime1

Dataset

Description산지전용 허가 현황 정보를 제공합니다. 시도, 시군구, 읍면동, 허가목적, 전용면적 등의 정보를 제공합니다.*지번 등 특정할 수 있는 정보는 미개방
Author전라남도 광양시
URLhttps://www.data.go.kr/data/3079580/fileData.do

Alerts

구분 has constant value ""Constant
시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 23:54:25.288776
Analysis finished2024-03-14 23:54:27.449708
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size686.0 B
2024-03-15T08:54:27.659803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2024-03-15T08:54:28.108746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size624.0 B
전용협의
62 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전용협의 62
100.0%

Length

2024-03-15T08:54:28.459644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:54:28.666289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전용협의 62
100.0%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size624.0 B
전라남도
62 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 62
100.0%

Length

2024-03-15T08:54:29.070612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:54:29.403603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 62
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size624.0 B
광양시
62 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광양시 62
100.0%

Length

2024-03-15T08:54:29.672475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:54:29.839730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광양시 62
100.0%

읍면동
Text

Distinct39
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Memory size624.0 B
2024-03-15T08:54:30.455244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length6.4193548
Min length2

Characters and Unicode

Total characters398
Distinct characters60
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)37.1%

Sample

1st row봉강면 부저리
2nd row성황동
3rd row진월면 오사리
4th row진상면 비평리
5th row다압면 금천리
ValueCountFrequency (%)
봉강면 12
 
10.5%
광양읍 9
 
7.9%
옥룡면 8
 
7.0%
마동 6
 
5.3%
진월면 5
 
4.4%
옥곡면 5
 
4.4%
진상면 5
 
4.4%
성황동 5
 
4.4%
부저리 4
 
3.5%
다압면 3
 
2.6%
Other values (35) 52
45.6%
2024-03-15T08:54:31.331586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
 
15.6%
리 49
 
12.3%
면 38
 
9.5%
동 19
 
4.8%
옥 14
 
3.5%
강 14
 
3.5%
봉 12
 
3.0%
진 11
 
2.8%
곡 11
 
2.8%
광 10
 
2.5%
Other values (50) 158
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
83.2%
Space Separator 62
 
15.6%
Other Punctuation 5
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 49
 
14.8%
면 38
 
11.5%
동 19
 
5.7%
옥 14
 
4.2%
강 14
 
4.2%
봉 12
 
3.6%
진 11
 
3.3%
곡 11
 
3.3%
광 10
 
3.0%
양 9
 
2.7%
Other values (48) 144
43.5%
Space Separator
ValueCountFrequency (%)
62
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
83.2%
Common 67
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 49
 
14.8%
면 38
 
11.5%
동 19
 
5.7%
옥 14
 
4.2%
강 14
 
4.2%
봉 12
 
3.6%
진 11
 
3.3%
곡 11
 
3.3%
광 10
 
3.0%
양 9
 
2.7%
Other values (48) 144
43.5%
Common
ValueCountFrequency (%)
62
92.5%
, 5
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
83.2%
ASCII 67
 
16.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
92.5%
, 5
 
7.5%
Hangul
ValueCountFrequency (%)
리 49
 
14.8%
면 38
 
11.5%
동 19
 
5.7%
옥 14
 
4.2%
강 14
 
4.2%
봉 12
 
3.6%
진 11
 
3.3%
곡 11
 
3.3%
광 10
 
3.0%
양 9
 
2.7%
Other values (48) 144
43.5%

허가목적
Text

Distinct37
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Memory size624.0 B
2024-03-15T08:54:32.161674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length11.677419
Min length4

Characters and Unicode

Total characters724
Distinct characters124
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)46.8%

Sample

1st row제2종근린생활시설(일반음식점) 부지조성
2nd row도시계획시설사업(중로2-69호선)
3rd row종중문종자연장지조성
4th row개간사업
5th row도시계획시설사업(도로, 수변공원)
ValueCountFrequency (%)
신축 10
 
9.0%
가연자연장지조성 7
 
6.3%
개간사업 7
 
6.3%
단독주택 7
 
6.3%
제2종근린생활시설(사무소 6
 
5.4%
개설 5
 
4.5%
종중자연장지조성 4
 
3.6%
가족자연장지조성 4
 
3.6%
및 4
 
3.6%
태양광발전시설 2
 
1.8%
Other values (49) 55
49.5%
2024-03-15T08:54:33.245277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
6.9%
사 30
 
4.1%
시 28
 
3.9%
지 27
 
3.7%
성 26
 
3.6%
연 25
 
3.5%
설 24
 
3.3%
장 23
 
3.2%
업 23
 
3.2%
조 22
 
3.0%
Other values (114) 446
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 610
84.3%
Space Separator 50
 
6.9%
Decimal Number 22
 
3.0%
Close Punctuation 18
 
2.5%
Open Punctuation 18
 
2.5%
Dash Punctuation 4
 
0.6%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 30
 
4.9%
시 28
 
4.6%
지 27
 
4.4%
성 26
 
4.3%
연 25
 
4.1%
설 24
 
3.9%
장 23
 
3.8%
업 23
 
3.8%
조 22
 
3.6%
자 18
 
3.0%
Other values (102) 364
59.7%
Decimal Number
ValueCountFrequency (%)
2 11
50.0%
1 4
 
18.2%
6 2
 
9.1%
9 2
 
9.1%
3 1
 
4.5%
8 1
 
4.5%
5 1
 
4.5%
Space Separator
ValueCountFrequency (%)
50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 610
84.3%
Common 114
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 30
 
4.9%
시 28
 
4.6%
지 27
 
4.4%
성 26
 
4.3%
연 25
 
4.1%
설 24
 
3.9%
장 23
 
3.8%
업 23
 
3.8%
조 22
 
3.6%
자 18
 
3.0%
Other values (102) 364
59.7%
Common
ValueCountFrequency (%)
50
43.9%
) 18
 
15.8%
( 18
 
15.8%
2 11
 
9.6%
1 4
 
3.5%
- 4
 
3.5%
, 2
 
1.8%
6 2
 
1.8%
9 2
 
1.8%
3 1
 
0.9%
Other values (2) 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 610
84.3%
ASCII 114
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
43.9%
) 18
 
15.8%
( 18
 
15.8%
2 11
 
9.6%
1 4
 
3.5%
- 4
 
3.5%
, 2
 
1.8%
6 2
 
1.8%
9 2
 
1.8%
3 1
 
0.9%
Other values (2) 2
 
1.8%
Hangul
ValueCountFrequency (%)
사 30
 
4.9%
시 28
 
4.6%
지 27
 
4.4%
성 26
 
4.3%
연 25
 
4.1%
설 24
 
3.9%
장 23
 
3.8%
업 23
 
3.8%
조 22
 
3.6%
자 18
 
3.0%
Other values (102) 364
59.7%

전용면적(제곱미터)
Real number (ℝ)

Distinct54
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2092.9952
Minimum5.5
Maximum42536
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size686.0 B
2024-03-15T08:54:33.493761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile95
Q1140.25
median570
Q31455.5
95-th percentile7531.3
Maximum42536
Range42530.5
Interquartile range (IQR)1315.25

Descriptive statistics

Standard deviation5789.5248
Coefficient of variation (CV)2.7661434
Kurtosis40.339238
Mean2092.9952
Median Absolute Deviation (MAD)471
Skewness5.9691043
Sum129765.7
Variance33518597
MonotonicityNot monotonic
2024-03-15T08:54:33.801783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 7
 
11.3%
95.0 2
 
3.2%
98.0 2
 
3.2%
655.0 1
 
1.6%
136.0 1
 
1.6%
153.0 1
 
1.6%
1459.0 1
 
1.6%
182.0 1
 
1.6%
177.0 1
 
1.6%
4220.0 1
 
1.6%
Other values (44) 44
71.0%
ValueCountFrequency (%)
5.5 1
 
1.6%
52.0 1
 
1.6%
83.0 1
 
1.6%
95.0 2
 
3.2%
98.0 2
 
3.2%
99.0 7
11.3%
124.0 1
 
1.6%
136.0 1
 
1.6%
153.0 1
 
1.6%
177.0 1
 
1.6%
ValueCountFrequency (%)
42536.0 1
1.6%
14064.0 1
1.6%
9969.0 1
1.6%
7627.0 1
1.6%
5713.0 1
1.6%
4885.0 1
1.6%
4733.0 1
1.6%
4220.0 1
1.6%
3870.0 1
1.6%
2594.0 1
1.6%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size624.0 B
Minimum2024-01-08 00:00:00
Maximum2024-01-08 00:00:00
2024-03-15T08:54:34.142188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:54:34.383953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T08:54:26.279358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:54:25.736701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:54:26.527122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:54:25.977243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:54:34.512155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동허가목적전용면적(제곱미터)
연번1.0000.0000.7570.000
읍면동0.0001.0000.7080.000
허가목적0.7570.7081.0000.974
전용면적(제곱미터)0.0000.0000.9741.000
2024-03-15T08:54:34.673509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전용면적(제곱미터)
연번1.0000.185
전용면적(제곱미터)0.1851.000

Missing values

2024-03-15T08:54:26.860042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:54:27.279445image/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

연번구분시도시군구읍면동허가목적전용면적(제곱미터)데이터기준일
01전용협의전라남도광양시봉강면 부저리제2종근린생활시설(일반음식점) 부지조성655.02024-01-08
12전용협의전라남도광양시성황동도시계획시설사업(중로2-69호선)1537.02024-01-08
23전용협의전라남도광양시진월면 오사리종중문종자연장지조성52.02024-01-08
34전용협의전라남도광양시진상면 비평리개간사업622.02024-01-08
45전용협의전라남도광양시다압면 금천리도시계획시설사업(도로, 수변공원)998.02024-01-08
56전용협의전라남도광양시마동단독주택 신축1322.02024-01-08
67전용협의전라남도광양시진월면 진정리종중자연장지조성620.02024-01-08
78전용협의전라남도광양시진상면 섬거리가역자연장지조성83.02024-01-08
89전용협의전라남도광양시광양읍 용강리도시계획시설사업(대로1-6호선)7627.02024-01-08
910전용협의전라남도광양시옥룡면 용곡리가연자연장지조성99.02024-01-08
연번구분시도시군구읍면동허가목적전용면적(제곱미터)데이터기준일
5253전용협의전라남도광양시봉강면 조령리단독주택 신축 및 진입로 개설656.02024-01-08
5354전용협의전라남도광양시광양읍 사곡리단독주택 신축215.02024-01-08
5455전용협의전라남도광양시봉강면 신룡리개간사업2060.02024-01-08
5556전용협의전라남도광양시성황동정산마을 하수관로 정비사엽5.52024-01-08
5657전용협의전라남도광양시마동도시계획시설사업(소공원, 주차장)9969.02024-01-08
5758전용협의전라남도광양시광양읍 사곡리개간사업4733.02024-01-08
5859전용협의전라남도광양시봉강면 부저리태양광발전시설 진출입로 개설124.02024-01-08
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