Overview

Dataset statistics

Number of variables8
Number of observations205
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 KiB
Average record size in memory67.6 B

Variable types

Numeric3
Text3
Categorical2

Dataset

Description전라남도 광양시 에 있는 마을회관 정보(법정리, 마을명, 마을회관 주소, 연면적(㎡), 구조물 형태, 규모, 건립년도)에 대한 데이터를 무료로 제공
Author전라남도 광양시
URLhttps://www.data.go.kr/data/15040201/fileData.do

Alerts

연번 is highly overall correlated with 건립년도High correlation
건립년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:17:50.218138
Analysis finished2023-12-12 22:17:51.734976
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct205
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103
Minimum1
Maximum205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T07:17:51.800670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.2
Q152
median103
Q3154
95-th percentile194.8
Maximum205
Range204
Interquartile range (IQR)102

Descriptive statistics

Standard deviation59.322565
Coefficient of variation (CV)0.57594723
Kurtosis-1.2
Mean103
Median Absolute Deviation (MAD)51
Skewness0
Sum21115
Variance3519.1667
MonotonicityStrictly increasing
2023-12-13T07:17:51.936520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
142 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
Other values (195) 195
95.1%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%

법정리
Text

Distinct68
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T07:17:52.188317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9707317
Min length2

Characters and Unicode

Total characters609
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)4.4%

Sample

1st row죽천리
2nd row황길동
3rd row황길동
4th row송금리
5th row도이동
ValueCountFrequency (%)
세풍리 7
 
3.4%
금천리 6
 
2.9%
덕례리 5
 
2.4%
중동 5
 
2.4%
태인동 5
 
2.4%
신원리 5
 
2.4%
용곡리 5
 
2.4%
신금리 5
 
2.4%
황길동 5
 
2.4%
우산리 5
 
2.4%
Other values (58) 152
74.1%
2023-12-13T07:17:52.598528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 179
29.4%
동 32
 
5.3%
금 19
 
3.1%
사 19
 
3.1%
신 18
 
3.0%
죽 16
 
2.6%
곡 14
 
2.3%
천 14
 
2.3%
황 13
 
2.1%
산 12
 
2.0%
Other values (67) 273
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 609
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 179
29.4%
동 32
 
5.3%
금 19
 
3.1%
사 19
 
3.1%
신 18
 
3.0%
죽 16
 
2.6%
곡 14
 
2.3%
천 14
 
2.3%
황 13
 
2.1%
산 12
 
2.0%
Other values (67) 273
44.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 609
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 179
29.4%
동 32
 
5.3%
금 19
 
3.1%
사 19
 
3.1%
신 18
 
3.0%
죽 16
 
2.6%
곡 14
 
2.3%
천 14
 
2.3%
황 13
 
2.1%
산 12
 
2.0%
Other values (67) 273
44.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 609
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 179
29.4%
동 32
 
5.3%
금 19
 
3.1%
사 19
 
3.1%
신 18
 
3.0%
죽 16
 
2.6%
곡 14
 
2.3%
천 14
 
2.3%
황 13
 
2.1%
산 12
 
2.0%
Other values (67) 273
44.8%

마을명
Text

Distinct193
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T07:17:53.002382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.2341463
Min length2

Characters and Unicode

Total characters458
Distinct characters141
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

Unique184 ?
Unique (%)89.8%

Sample

1st row개현
2nd row평촌
3rd row기동
4th row금동
5th row대화
ValueCountFrequency (%)
신기 4
 
1.9%
1통 3
 
1.4%
신촌 3
 
1.4%
항동 2
 
0.9%
추동 2
 
0.9%
도촌 2
 
0.9%
대리 2
 
0.9%
동동 2
 
0.9%
하포 2
 
0.9%
평촌 2
 
0.9%
Other values (190) 192
88.9%
2023-12-13T07:17:53.553276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 31
 
6.8%
신 18
 
3.9%
촌 11
 
2.4%
통 11
 
2.4%
11
 
2.4%
곡 9
 
2.0%
평 9
 
2.0%
1 9
 
2.0%
암 8
 
1.7%
산 8
 
1.7%
Other values (131) 333
72.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 427
93.2%
Decimal Number 20
 
4.4%
Space Separator 11
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 31
 
7.3%
신 18
 
4.2%
촌 11
 
2.6%
통 11
 
2.6%
곡 9
 
2.1%
평 9
 
2.1%
암 8
 
1.9%
산 8
 
1.9%
정 8
 
1.9%
기 8
 
1.9%
Other values (125) 306
71.7%
Decimal Number
ValueCountFrequency (%)
1 9
45.0%
2 5
25.0%
3 4
20.0%
4 1
 
5.0%
5 1
 
5.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 427
93.2%
Common 31
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 31
 
7.3%
신 18
 
4.2%
촌 11
 
2.6%
통 11
 
2.6%
곡 9
 
2.1%
평 9
 
2.1%
암 8
 
1.9%
산 8
 
1.9%
정 8
 
1.9%
기 8
 
1.9%
Other values (125) 306
71.7%
Common
ValueCountFrequency (%)
11
35.5%
1 9
29.0%
2 5
16.1%
3 4
 
12.9%
4 1
 
3.2%
5 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 427
93.2%
ASCII 31
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 31
 
7.3%
신 18
 
4.2%
촌 11
 
2.6%
통 11
 
2.6%
곡 9
 
2.1%
평 9
 
2.1%
암 8
 
1.9%
산 8
 
1.9%
정 8
 
1.9%
기 8
 
1.9%
Other values (125) 306
71.7%
ASCII
ValueCountFrequency (%)
11
35.5%
1 9
29.0%
2 5
16.1%
3 4
 
12.9%
4 1
 
3.2%
5 1
 
3.2%

마을회관 주소
Text

Distinct204
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T07:17:53.951797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length19.185366
Min length15

Characters and Unicode

Total characters3933
Distinct characters101
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

Unique203 ?
Unique (%)99.0%

Sample

1st row전라남도 광양시 죽천리 929-1
2nd row전라남도 광양시 황길동 514
3rd row전라남도 광양시 황길동 421-7
4th row전라남도 광양시 송금리 298-6
5th row전라남도 광양시 도이동 648-1
ValueCountFrequency (%)
전라남도 205
24.1%
광양시 205
24.1%
1필지 15
 
1.8%
세풍리 7
 
0.8%
금천리 6
 
0.7%
신원리 5
 
0.6%
죽림리 5
 
0.6%
2필지 5
 
0.6%
덕례리 5
 
0.6%
우산리 5
 
0.6%
Other values (276) 388
45.6%
2023-12-13T07:17:54.501250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
777
19.8%
도 211
 
5.4%
남 209
 
5.3%
광 208
 
5.3%
전 205
 
5.2%
양 205
 
5.2%
시 205
 
5.2%
라 205
 
5.2%
1 195
 
5.0%
리 179
 
4.6%
Other values (91) 1334
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2120
53.9%
Decimal Number 860
21.9%
Space Separator 777
 
19.8%
Dash Punctuation 166
 
4.2%
Other Punctuation 6
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 211
10.0%
남 209
9.9%
광 208
9.8%
전 205
9.7%
양 205
9.7%
시 205
9.7%
라 205
9.7%
리 179
8.4%
동 34
 
1.6%
지 27
 
1.3%
Other values (76) 432
20.4%
Decimal Number
ValueCountFrequency (%)
1 195
22.7%
3 97
11.3%
2 96
11.2%
4 92
10.7%
6 70
 
8.1%
8 68
 
7.9%
5 67
 
7.8%
7 67
 
7.8%
9 59
 
6.9%
0 49
 
5.7%
Space Separator
ValueCountFrequency (%)
777
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2120
53.9%
Common 1813
46.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 211
10.0%
남 209
9.9%
광 208
9.8%
전 205
9.7%
양 205
9.7%
시 205
9.7%
라 205
9.7%
리 179
8.4%
동 34
 
1.6%
지 27
 
1.3%
Other values (76) 432
20.4%
Common
ValueCountFrequency (%)
777
42.9%
1 195
 
10.8%
- 166
 
9.2%
3 97
 
5.4%
2 96
 
5.3%
4 92
 
5.1%
6 70
 
3.9%
8 68
 
3.8%
5 67
 
3.7%
7 67
 
3.7%
Other values (5) 118
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2120
53.9%
ASCII 1813
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
777
42.9%
1 195
 
10.8%
- 166
 
9.2%
3 97
 
5.4%
2 96
 
5.3%
4 92
 
5.1%
6 70
 
3.9%
8 68
 
3.8%
5 67
 
3.7%
7 67
 
3.7%
Other values (5) 118
 
6.5%
Hangul
ValueCountFrequency (%)
도 211
10.0%
남 209
9.9%
광 208
9.8%
전 205
9.7%
양 205
9.7%
시 205
9.7%
라 205
9.7%
리 179
8.4%
동 34
 
1.6%
지 27
 
1.3%
Other values (76) 432
20.4%

연면적_제곱미터
Real number (ℝ)

Distinct196
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.46307
Minimum47.71
Maximum494.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T07:17:54.655202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47.71
5-th percentile67.248
Q197.44
median117.44
Q3149.8
95-th percentile262.796
Maximum494.98
Range447.27
Interquartile range (IQR)52.36

Descriptive statistics

Standard deviation64.801712
Coefficient of variation (CV)0.48192943
Kurtosis6.9774024
Mean134.46307
Median Absolute Deviation (MAD)26.3
Skewness2.20824
Sum27564.93
Variance4199.2619
MonotonicityNot monotonic
2023-12-13T07:17:54.812188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.18 3
 
1.5%
133.92 2
 
1.0%
83.58 2
 
1.0%
101.4 2
 
1.0%
168.24 2
 
1.0%
110.07 2
 
1.0%
83.6 2
 
1.0%
175.36 2
 
1.0%
148.2 1
 
0.5%
111.96 1
 
0.5%
Other values (186) 186
90.7%
ValueCountFrequency (%)
47.71 1
0.5%
50.0 1
0.5%
52.43 1
0.5%
55.8 1
0.5%
59.5 1
0.5%
62.64 1
0.5%
64.9 1
0.5%
66.0 1
0.5%
66.6 1
0.5%
66.73 1
0.5%
ValueCountFrequency (%)
494.98 1
0.5%
394.89 1
0.5%
387.33 1
0.5%
371.4 1
0.5%
346.24 1
0.5%
297.98 1
0.5%
274.91 1
0.5%
271.46 1
0.5%
266.49 1
0.5%
265.12 1
0.5%

구조물 형태
Categorical

Distinct14
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
철콘
76 
벽돌
43 
조적
31 
시멘트벽돌
29 
블록
11 
Other values (9)
15 

Length

Max length8
Median length2
Mean length2.6195122
Min length2

Unique

Unique4 ?
Unique (%)2.0%

Sample

1st row벽돌
2nd row블록
3rd row목조
4th row시멘트벽돌
5th row목조

Common Values

ValueCountFrequency (%)
철콘 76
37.1%
벽돌 43
21.0%
조적 31
15.1%
시멘트벽돌 29
 
14.1%
블록 11
 
5.4%
경량철골 3
 
1.5%
목조 2
 
1.0%
시멘트블록 2
 
1.0%
철콘,시멘트벽돌 2
 
1.0%
철콘조 2
 
1.0%
Other values (4) 4
 
2.0%

Length

2023-12-13T07:17:54.973585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철콘 77
37.4%
벽돌 44
21.4%
조적 31
15.0%
시멘트벽돌 29
 
14.1%
블록 11
 
5.3%
경량철골 3
 
1.5%
목조 2
 
1.0%
시멘트블록 2
 
1.0%
철콘,시멘트벽돌 2
 
1.0%
철콘조 2
 
1.0%
Other values (3) 3
 
1.5%

규모
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1층
104 
2층
100 
3층
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row1층
2nd row1층
3rd row1층
4th row1층
5th row1층

Common Values

ValueCountFrequency (%)
1층 104
50.7%
2층 100
48.8%
3층 1
 
0.5%

Length

2023-12-13T07:17:55.107808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:17:55.239997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1층 104
50.7%
2층 100
48.8%
3층 1
 
0.5%

건립년도
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001.5268
Minimum1900
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T07:17:55.362815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1983.8
Q11995
median2003
Q32009
95-th percentile2019.8
Maximum2022
Range122
Interquartile range (IQR)14

Descriptive statistics

Standard deviation12.968117
Coefficient of variation (CV)0.0064791125
Kurtosis18.125615
Mean2001.5268
Median Absolute Deviation (MAD)7
Skewness-2.6869783
Sum410313
Variance168.17207
MonotonicityIncreasing
2023-12-13T07:17:55.511612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2004 15
 
7.3%
1997 14
 
6.8%
1994 12
 
5.9%
1993 11
 
5.4%
2009 11
 
5.4%
2008 10
 
4.9%
2006 10
 
4.9%
2019 9
 
4.4%
2005 9
 
4.4%
1996 9
 
4.4%
Other values (33) 95
46.3%
ValueCountFrequency (%)
1900 1
0.5%
1960 1
0.5%
1965 1
0.5%
1968 1
0.5%
1970 1
0.5%
1971 1
0.5%
1974 1
0.5%
1979 1
0.5%
1982 1
0.5%
1983 2
1.0%
ValueCountFrequency (%)
2022 1
 
0.5%
2021 5
2.4%
2020 5
2.4%
2019 9
4.4%
2017 3
 
1.5%
2016 2
 
1.0%
2014 6
2.9%
2013 1
 
0.5%
2012 2
 
1.0%
2011 3
 
1.5%

Interactions

2023-12-13T07:17:51.063433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.578137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.844179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:51.161866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.682143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.921139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:51.483587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.763349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:17:50.990311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:17:55.622379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법정리연면적_제곱미터구조물 형태규모건립년도
연번1.0000.6290.2670.5590.3190.850
법정리0.6291.0000.6940.5870.0000.468
연면적_제곱미터0.2670.6941.0000.2580.5470.130
구조물 형태0.5590.5870.2581.0000.0000.759
규모0.3190.0000.5470.0001.0000.469
건립년도0.8500.4680.1300.7590.4691.000
2023-12-13T07:17:55.731083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모구조물 형태
규모1.0000.000
구조물 형태0.0001.000
2023-12-13T07:17:55.825000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적_제곱미터건립년도구조물 형태규모
연번1.0000.0900.9990.2600.197
연면적_제곱미터0.0901.0000.0890.1090.282
건립년도0.9990.0891.0000.4430.211
구조물 형태0.2600.1090.4431.0000.000
규모0.1970.2820.2110.0001.000

Missing values

2023-12-13T07:17:51.583296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:17:51.695363image/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

연번법정리마을명마을회관 주소연면적_제곱미터구조물 형태규모건립년도
01죽천리개현전라남도 광양시 죽천리 929-150.0벽돌1층1900
12황길동평촌전라남도 광양시 황길동 51464.9블록1층1960
23황길동기동전라남도 광양시 황길동 421-752.43목조1층1965
34송금리금동전라남도 광양시 송금리 298-668.24시멘트벽돌1층1968
45도이동대화전라남도 광양시 도이동 648-166.6목조1층1970
56신원리원동전라남도 광양시 신원리 45079.4블록1층1971
67황길동하포전라남도 광양시 황길동 894-1175.36블록1층1974
78사곡리억만전라남도 광양시 사곡리 115559.5시멘트블록1층1979
89마룡리방죽전라남도 광양시 마룡리 964-666.0블록1층1982
910용강리석정전라남도 광양시 용강리 184-6130.0블록2층1983
연번법정리마을명마을회관 주소연면적_제곱미터구조물 형태규모건립년도
195196산남리산본전라남도 광양시 옥룡면 산남리 226-1106.95철콘1층2020
196197세풍리신촌전라남도 광양시 세풍리 6-2699.72철콘1층2020
197198인서리인서전라남도 광양시 인서리 105-4110.07철콘1층2020
198199칠성리호북전라남도 광양시 칠성리264114.63철콘1층2020
199200광영동영수전라남도 광양시 광영동 780-5100.32철콘1층2021
200201중동오류전라남도 광양시 중동 1775-399.51철콘1층2021
201202지원리창원전라남도 광양시 지원리 995-6233.52철콘2층2021
202203조령리하조전라남도 광양시 조령리 611 외3 필지160.74철콘1층2021
203204세풍리해두전라남도 광양시 세풍리 723-8110.07철콘1층2021
204205죽천리죽림전라남도 광양시 죽림리 1067-3,1068,1321-1167.76철콘1층2022