Overview

Dataset statistics

Number of variables7
Number of observations323
Missing cells78
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.1 KiB
Average record size in memory57.4 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description경상남도 진주시 마을회관 정보에 대해 상세하게 제공합니다.(읍면동명, 마을회관명, 소재지, 건축년도, 규모, 전화번호, 비고 등)
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15045216

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 78 (24.1%) missing valuesMissing
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:01:37.877338
Analysis finished2023-12-11 00:01:38.530774
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동명
Categorical

Distinct17
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
명석면
30 
수곡면
27 
금곡면
24 
이반성면
24 
대곡면
24 
Other values (12)
194 

Length

Max length4
Median length3
Mean length3.1331269
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
명석면 30
 
9.3%
수곡면 27
 
8.4%
금곡면 24
 
7.4%
이반성면 24
 
7.4%
대곡면 24
 
7.4%
문산읍 23
 
7.1%
집현면 22
 
6.8%
정촌면 21
 
6.5%
금산면 19
 
5.9%
미천면 19
 
5.9%
Other values (7) 90
27.9%

Length

2023-12-11T09:01:38.615544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
명석면 30
 
9.3%
수곡면 27
 
8.4%
금곡면 24
 
7.4%
이반성면 24
 
7.4%
대곡면 24
 
7.4%
문산읍 23
 
7.1%
집현면 22
 
6.8%
정촌면 21
 
6.5%
일반성면 19
 
5.9%
사봉면 19
 
5.9%
Other values (7) 90
27.9%

마을회관명
Text

Distinct285
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-11T09:01:38.890077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.1547988
Min length5

Characters and Unicode

Total characters1988
Distinct characters160
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique257 ?
Unique (%)79.6%

Sample

1st row갈곡마을회관
2nd row계리마을회관
3rd row남동마을회관
4th row남서마을회관
5th row대호마을회관
ValueCountFrequency (%)
마을회관 18
 
5.3%
신촌마을회관 5
 
1.5%
상촌마을회관 4
 
1.2%
중촌마을회관 3
 
0.9%
원동마을회관 3
 
0.9%
덕곡마을회관 3
 
0.9%
원당마을회관 3
 
0.9%
오동마을회관 3
 
0.9%
서촌마을회관 2
 
0.6%
용암마을회관 2
 
0.6%
Other values (276) 295
86.5%
2023-12-11T09:01:39.626843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 327
16.4%
관 324
16.3%
을 323
16.2%
회 322
16.2%
동 54
 
2.7%
촌 33
 
1.7%
곡 28
 
1.4%
정 24
 
1.2%
19
 
1.0%
신 18
 
0.9%
Other values (150) 516
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1967
98.9%
Space Separator 19
 
1.0%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 327
16.6%
관 324
16.5%
을 323
16.4%
회 322
16.4%
동 54
 
2.7%
촌 33
 
1.7%
곡 28
 
1.4%
정 24
 
1.2%
신 18
 
0.9%
대 18
 
0.9%
Other values (147) 496
25.2%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1967
98.9%
Common 21
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 327
16.6%
관 324
16.5%
을 323
16.4%
회 322
16.4%
동 54
 
2.7%
촌 33
 
1.7%
곡 28
 
1.4%
정 24
 
1.2%
신 18
 
0.9%
대 18
 
0.9%
Other values (147) 496
25.2%
Common
ValueCountFrequency (%)
19
90.5%
) 1
 
4.8%
( 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1967
98.9%
ASCII 21
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 327
16.6%
관 324
16.5%
을 323
16.4%
회 322
16.4%
동 54
 
2.7%
촌 33
 
1.7%
곡 28
 
1.4%
정 24
 
1.2%
신 18
 
0.9%
대 18
 
0.9%
Other values (147) 496
25.2%
ASCII
ValueCountFrequency (%)
19
90.5%
) 1
 
4.8%
( 1
 
4.8%

소재지
Text

UNIQUE 

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-11T09:01:39.971453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length22.894737
Min length15

Characters and Unicode

Total characters7395
Distinct characters143
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)100.0%

Sample

1st row경상남도 진주시 문산읍 갈곡길 24
2nd row경상남도 진주시 문산읍 두산길5번길 1
3rd row경상남도 진주시 문산읍 소문길17번길 6
4th row경상남도 진주시 문산읍 월아산로1094번길 7
5th row경상남도 진주시 문산읍 문정로540번길 13
ValueCountFrequency (%)
진주시 324
 
19.7%
경상남도 323
 
19.7%
수곡면 27
 
1.6%
대곡면 25
 
1.5%
금곡면 24
 
1.5%
이반성면 24
 
1.5%
문산읍 23
 
1.4%
집현면 22
 
1.3%
정촌면 21
 
1.3%
금산면 19
 
1.2%
Other values (521) 810
49.3%
2023-12-11T09:01:40.477605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1342
18.1%
진 373
 
5.0%
주 339
 
4.6%
남 331
 
4.5%
상 331
 
4.5%
시 326
 
4.4%
경 324
 
4.4%
도 324
 
4.4%
길 279
 
3.8%
면 252
 
3.4%
Other values (133) 3174
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4556
61.6%
Decimal Number 1366
 
18.5%
Space Separator 1342
 
18.1%
Dash Punctuation 89
 
1.2%
Open Punctuation 21
 
0.3%
Close Punctuation 21
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 373
 
8.2%
주 339
 
7.4%
남 331
 
7.3%
상 331
 
7.3%
시 326
 
7.2%
경 324
 
7.1%
도 324
 
7.1%
길 279
 
6.1%
면 252
 
5.5%
로 213
 
4.7%
Other values (119) 1464
32.1%
Decimal Number
ValueCountFrequency (%)
1 249
18.2%
2 183
13.4%
5 143
10.5%
3 133
9.7%
4 126
9.2%
6 121
8.9%
9 110
8.1%
7 106
7.8%
8 99
 
7.2%
0 96
 
7.0%
Space Separator
ValueCountFrequency (%)
1342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4556
61.6%
Common 2839
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 373
 
8.2%
주 339
 
7.4%
남 331
 
7.3%
상 331
 
7.3%
시 326
 
7.2%
경 324
 
7.1%
도 324
 
7.1%
길 279
 
6.1%
면 252
 
5.5%
로 213
 
4.7%
Other values (119) 1464
32.1%
Common
ValueCountFrequency (%)
1342
47.3%
1 249
 
8.8%
2 183
 
6.4%
5 143
 
5.0%
3 133
 
4.7%
4 126
 
4.4%
6 121
 
4.3%
9 110
 
3.9%
7 106
 
3.7%
8 99
 
3.5%
Other values (4) 227
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4556
61.6%
ASCII 2839
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1342
47.3%
1 249
 
8.8%
2 183
 
6.4%
5 143
 
5.0%
3 133
 
4.7%
4 126
 
4.4%
6 121
 
4.3%
9 110
 
3.9%
7 106
 
3.7%
8 99
 
3.5%
Other values (4) 227
 
8.0%
Hangul
ValueCountFrequency (%)
진 373
 
8.2%
주 339
 
7.4%
남 331
 
7.3%
상 331
 
7.3%
시 326
 
7.2%
경 324
 
7.1%
도 324
 
7.1%
길 279
 
6.1%
면 252
 
5.5%
로 213
 
4.7%
Other values (119) 1464
32.1%

건축년도
Real number (ℝ)

Distinct39
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1998.4706
Minimum1967
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-11T09:01:40.663748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1967
5-th percentile1982.1
Q11995
median1998
Q32004
95-th percentile2009
Maximum2020
Range53
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.6784102
Coefficient of variation (CV)0.0038421432
Kurtosis2.36658
Mean1998.4706
Median Absolute Deviation (MAD)4
Skewness-0.93619926
Sum645506
Variance58.957983
MonotonicityNot monotonic
2023-12-11T09:01:40.796578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1998 40
 
12.4%
1995 28
 
8.7%
1997 26
 
8.0%
1994 22
 
6.8%
2006 21
 
6.5%
1996 19
 
5.9%
2005 16
 
5.0%
1999 15
 
4.6%
2000 14
 
4.3%
2002 14
 
4.3%
Other values (29) 108
33.4%
ValueCountFrequency (%)
1967 1
 
0.3%
1970 1
 
0.3%
1972 2
0.6%
1975 2
0.6%
1976 2
0.6%
1978 1
 
0.3%
1980 3
0.9%
1981 1
 
0.3%
1982 4
1.2%
1983 2
0.6%
ValueCountFrequency (%)
2020 1
 
0.3%
2015 2
 
0.6%
2013 3
 
0.9%
2011 2
 
0.6%
2010 6
 
1.9%
2009 8
 
2.5%
2008 9
2.8%
2007 10
3.1%
2006 21
6.5%
2005 16
5.0%

규모(면적)
Text

Distinct289
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-11T09:01:41.120159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.4613003
Min length7

Characters and Unicode

Total characters3056
Distinct characters16
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)82.7%

Sample

1st row2층(149.52㎡)
2nd row1층(90.04㎡)
3rd row2층(94.44㎡)
4th row1층(65㎡)
5th row1층(88.11㎡)
ValueCountFrequency (%)
2층(103.2㎡ 6
 
1.8%
1층(100㎡ 6
 
1.8%
2층(106.84㎡ 5
 
1.5%
㎡ 3
 
0.9%
1층(87.9㎡ 3
 
0.9%
1층(97.74㎡ 2
 
0.6%
1층(67.2㎡ 2
 
0.6%
1층(82.6㎡ 2
 
0.6%
1층(91㎡ 2
 
0.6%
2층(166.14㎡ 2
 
0.6%
Other values (279) 293
89.9%
2023-12-11T09:01:41.572767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 432
14.1%
층 323
10.6%
㎡ 323
10.6%
( 322
10.5%
) 320
10.5%
. 252
8.2%
2 178
 
5.8%
8 163
 
5.3%
6 134
 
4.4%
9 131
 
4.3%
Other values (6) 478
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1513
49.5%
Other Letter 323
 
10.6%
Other Symbol 323
 
10.6%
Open Punctuation 322
 
10.5%
Close Punctuation 320
 
10.5%
Other Punctuation 252
 
8.2%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 432
28.6%
2 178
11.8%
8 163
 
10.8%
6 134
 
8.9%
9 131
 
8.7%
7 119
 
7.9%
4 111
 
7.3%
3 85
 
5.6%
5 85
 
5.6%
0 75
 
5.0%
Other Letter
ValueCountFrequency (%)
층 323
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 323
100.0%
Open Punctuation
ValueCountFrequency (%)
( 322
100.0%
Close Punctuation
ValueCountFrequency (%)
) 320
100.0%
Other Punctuation
ValueCountFrequency (%)
. 252
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2733
89.4%
Hangul 323
 
10.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 432
15.8%
㎡ 323
11.8%
( 322
11.8%
) 320
11.7%
. 252
9.2%
2 178
6.5%
8 163
 
6.0%
6 134
 
4.9%
9 131
 
4.8%
7 119
 
4.4%
Other values (5) 359
13.1%
Hangul
ValueCountFrequency (%)
층 323
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2410
78.9%
Hangul 323
 
10.6%
CJK Compat 323
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 432
17.9%
( 322
13.4%
) 320
13.3%
. 252
10.5%
2 178
7.4%
8 163
 
6.8%
6 134
 
5.6%
9 131
 
5.4%
7 119
 
4.9%
4 111
 
4.6%
Other values (4) 248
10.3%
Hangul
ValueCountFrequency (%)
층 323
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 323
100.0%

전화번호
Text

MISSING 

Distinct242
Distinct (%)98.8%
Missing78
Missing (%)24.1%
Memory size2.7 KiB
2023-12-11T09:01:41.871438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2940
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

Unique239 ?
Unique (%)97.6%

Sample

1st row055-761-8236
2nd row055-761-7187
3rd row055-759-4614
4th row055-761-1939
5th row055-761-2669
ValueCountFrequency (%)
055-761-7698 2
 
0.8%
055-745-7643 2
 
0.8%
055-756-0435 2
 
0.8%
055-754-6629 1
 
0.4%
055-763-2717 1
 
0.4%
055-746-9484 1
 
0.4%
055-761-3244 1
 
0.4%
055-758-0632 1
 
0.4%
055-744-0485 1
 
0.4%
055-744-6113 1
 
0.4%
Other values (232) 232
94.7%
2023-12-11T09:01:42.296351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 741
25.2%
- 490
16.7%
0 332
11.3%
7 332
11.3%
4 282
 
9.6%
6 172
 
5.9%
1 134
 
4.6%
8 132
 
4.5%
9 116
 
3.9%
2 109
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2450
83.3%
Dash Punctuation 490
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 741
30.2%
0 332
13.6%
7 332
13.6%
4 282
 
11.5%
6 172
 
7.0%
1 134
 
5.5%
8 132
 
5.4%
9 116
 
4.7%
2 109
 
4.4%
3 100
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 741
25.2%
- 490
16.7%
0 332
11.3%
7 332
11.3%
4 282
 
9.6%
6 172
 
5.9%
1 134
 
4.6%
8 132
 
4.5%
9 116
 
3.9%
2 109
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 741
25.2%
- 490
16.7%
0 332
11.3%
7 332
11.3%
4 282
 
9.6%
6 172
 
5.9%
1 134
 
4.6%
8 132
 
4.5%
9 116
 
3.9%
2 109
 
3.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-05-16
323 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-16
2nd row2023-05-16
3rd row2023-05-16
4th row2023-05-16
5th row2023-05-16

Common Values

ValueCountFrequency (%)
2023-05-16 323
100.0%

Length

2023-12-11T09:01:42.444878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:01:42.551631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-16 323
100.0%

Interactions

2023-12-11T09:01:38.190624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:01:42.607859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명건축년도
읍면동명1.0000.349
건축년도0.3491.000
2023-12-11T09:01:42.683988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축년도읍면동명
건축년도1.0000.140
읍면동명0.1401.000

Missing values

2023-12-11T09:01:38.327074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:01:38.478276image/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

읍면동명마을회관명소재지건축년도규모(면적)전화번호데이터기준일자
0문산읍갈곡마을회관경상남도 진주시 문산읍 갈곡길 2419982층(149.52㎡)<NA>2023-05-16
1문산읍계리마을회관경상남도 진주시 문산읍 두산길5번길 119971층(90.04㎡)<NA>2023-05-16
2문산읍남동마을회관경상남도 진주시 문산읍 소문길17번길 620092층(94.44㎡)<NA>2023-05-16
3문산읍남서마을회관경상남도 진주시 문산읍 월아산로1094번길 719851층(65㎡)<NA>2023-05-16
4문산읍대호마을회관경상남도 진주시 문산읍 문정로540번길 1320001층(88.11㎡)055-761-82362023-05-16
5문산읍덕동마을회관경상남도 진주시 문산읍 동부로587번길 920061층(86.76㎡)<NA>2023-05-16
6문산읍덕촌마을회관경상남도 진주시 문산읍 동부로591번길 6-119982층(112.4㎡)055-761-71872023-05-16
7문산읍동방마을회관경상남도 진주시 문산읍 정자천로 20419952층(196.8㎡)055-759-46142023-05-16
8문산읍동정마을회관경상남도 진주시 문산읍 소문길53번길 320011층(61.65㎡)<NA>2023-05-16
9문산읍두산마을회관경상남도 진주시 문산읍 두산길203번길 1620061층(89.46㎡)055-761-19392023-05-16
읍면동명마을회관명소재지건축년도규모(면적)전화번호데이터기준일자
313수곡면원외마을회관경상남도 진주시 수곡면 원외길123번길 320091층(78㎡)055-758-90902023-05-16
314수곡면월계마을회관경상남도 진주시 수곡면 곤수로1407번길 4019981층(88.44㎡)055-754-46682023-05-16
315수곡면자매마을회관경상남도 진주시 수곡면 사곡로 69919951층(78.68㎡)055-758-77822023-05-16
316수곡면조계마을회관경상남도 진주시 수곡면 덕천로268번길 1619981층(94.25㎡)055-759-41392023-05-16
317수곡면중전마을회관경상남도 진주시 수곡면 중전길 19220101층(67.2㎡)055-755-40802023-05-16
318수곡면직금마을회관경상남도 진주시 수곡면 옥수로555번길 720091층(68㎡)055-754-47332023-05-16
319수곡면창촌마을회관경상남도 진주시 수곡면 옥수로 46119971층(92.71㎡)055-754-50122023-05-16
320수곡면효남마을회관경상남도 진주시 수곡면 곤수로 72520101층(68.4㎡)055-758-96872023-05-16
321수곡면효동마을회관경상남도 진주시 수곡면 곤수로865번길 6620041층(67.86㎡)055-754-66292023-05-16
322초장동초북마을회관경상남도 진주시 초전북로19번길 6(초전동)19942층(116 ㎡)055-761-06062023-05-16