Overview

Dataset statistics

Number of variables9
Number of observations285
Missing cells72
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.4 KiB
Average record size in memory73.5 B

Variable types

Categorical4
Text4
Numeric1

Dataset

Description경상남도 창녕군 마을회관현황에 대한 데이터를 포함하고 있습니다.(마을명, 회관명, 건축년도, 규모, 정원 등)
URLhttps://www.data.go.kr/data/15054782/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
규모 is highly imbalanced (51.1%)Imbalance
전화번호 has 72 (25.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 02:56:49.957601
Analysis finished2023-12-12 02:56:51.084275
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
경상남도
285 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 285
100.0%

Length

2023-12-12T11:56:51.187431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:51.332258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 285
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
창녕군
285 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창녕군 285
100.0%

Length

2023-12-12T11:56:51.477383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:51.642171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창녕군 285
100.0%

읍면
Categorical

Distinct14
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
남지읍
38 
창녕읍
31 
대합면
31 
이방면
21 
장마면
21 
Other values (9)
143 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남지읍 38
13.3%
창녕읍 31
10.9%
대합면 31
10.9%
이방면 21
 
7.4%
장마면 21
 
7.4%
유어면 19
 
6.7%
성산면 18
 
6.3%
대지면 18
 
6.3%
고암면 17
 
6.0%
계성면 17
 
6.0%
Other values (4) 54
18.9%

Length

2023-12-12T11:56:51.792358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남지읍 38
13.3%
창녕읍 31
10.9%
대합면 31
10.9%
이방면 21
 
7.4%
장마면 21
 
7.4%
유어면 19
 
6.7%
성산면 18
 
6.3%
대지면 18
 
6.3%
고암면 17
 
6.0%
계성면 17
 
6.0%
Other values (4) 54
18.9%

마을명
Text

Distinct254
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T11:56:52.217352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.6631579
Min length2

Characters and Unicode

Total characters759
Distinct characters147
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

Unique238 ?
Unique (%)83.5%

Sample

1st row교리
2nd row갈전
3rd row창서
4th row교상
5th row교하
ValueCountFrequency (%)
남지리 7
 
2.4%
성사리 5
 
1.7%
학계리 4
 
1.4%
반포리 3
 
1.0%
원동 3
 
1.0%
월하리 3
 
1.0%
신전리 3
 
1.0%
마산리 3
 
1.0%
대동 3
 
1.0%
신당 3
 
1.0%
Other values (240) 250
87.1%
2023-12-12T11:56:52.946255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 82
 
10.8%
39
 
5.1%
구 36
 
4.7%
산 26
 
3.4%
곡 23
 
3.0%
동 19
 
2.5%
신 18
 
2.4%
마 18
 
2.4%
계 16
 
2.1%
대 16
 
2.1%
Other values (137) 466
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 692
91.2%
Space Separator 39
 
5.1%
Decimal Number 28
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 82
 
11.8%
구 36
 
5.2%
산 26
 
3.8%
곡 23
 
3.3%
동 19
 
2.7%
신 18
 
2.6%
마 18
 
2.6%
계 16
 
2.3%
대 16
 
2.3%
남 15
 
2.2%
Other values (133) 423
61.1%
Decimal Number
ValueCountFrequency (%)
1 13
46.4%
2 13
46.4%
3 2
 
7.1%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 692
91.2%
Common 67
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 82
 
11.8%
구 36
 
5.2%
산 26
 
3.8%
곡 23
 
3.3%
동 19
 
2.7%
신 18
 
2.6%
마 18
 
2.6%
계 16
 
2.3%
대 16
 
2.3%
남 15
 
2.2%
Other values (133) 423
61.1%
Common
ValueCountFrequency (%)
39
58.2%
1 13
 
19.4%
2 13
 
19.4%
3 2
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 692
91.2%
ASCII 67
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 82
 
11.8%
구 36
 
5.2%
산 26
 
3.8%
곡 23
 
3.3%
동 19
 
2.7%
신 18
 
2.6%
마 18
 
2.6%
계 16
 
2.3%
대 16
 
2.3%
남 15
 
2.2%
Other values (133) 423
61.1%
ASCII
ValueCountFrequency (%)
39
58.2%
1 13
 
19.4%
2 13
 
19.4%
3 2
 
3.0%

회관명
Text

Distinct275
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T11:56:53.292420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.7122807
Min length6

Characters and Unicode

Total characters1913
Distinct characters153
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

Unique267 ?
Unique (%)93.7%

Sample

1st row교리 마을회관
2nd row갈전 마을회관
3rd row창서 마을회관
4th row교상 마을회관
5th row교하 마을회관
ValueCountFrequency (%)
마을회관 111
28.0%
원동마을회관 3
 
0.8%
관동마을회관 3
 
0.8%
교리 2
 
0.5%
대동 2
 
0.5%
명리마을회관 2
 
0.5%
신당 2
 
0.5%
부곡마을회관 2
 
0.5%
대신마을회관 2
 
0.5%
효정마을회관 1
 
0.3%
Other values (266) 266
67.2%
2023-12-12T11:56:53.821526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 292
15.3%
관 288
15.1%
회 287
15.0%
을 286
15.0%
111
 
5.8%
리 45
 
2.4%
구 34
 
1.8%
산 25
 
1.3%
곡 24
 
1.3%
동 23
 
1.2%
Other values (143) 498
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1776
92.8%
Space Separator 111
 
5.8%
Decimal Number 26
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 292
16.4%
관 288
16.2%
회 287
16.2%
을 286
16.1%
리 45
 
2.5%
구 34
 
1.9%
산 25
 
1.4%
곡 24
 
1.4%
동 23
 
1.3%
대 19
 
1.1%
Other values (139) 453
25.5%
Decimal Number
ValueCountFrequency (%)
1 12
46.2%
2 12
46.2%
3 2
 
7.7%
Space Separator
ValueCountFrequency (%)
111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1776
92.8%
Common 137
 
7.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 292
16.4%
관 288
16.2%
회 287
16.2%
을 286
16.1%
리 45
 
2.5%
구 34
 
1.9%
산 25
 
1.4%
곡 24
 
1.4%
동 23
 
1.3%
대 19
 
1.1%
Other values (139) 453
25.5%
Common
ValueCountFrequency (%)
111
81.0%
1 12
 
8.8%
2 12
 
8.8%
3 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1776
92.8%
ASCII 137
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 292
16.4%
관 288
16.2%
회 287
16.2%
을 286
16.1%
리 45
 
2.5%
구 34
 
1.9%
산 25
 
1.4%
곡 24
 
1.4%
동 23
 
1.3%
대 19
 
1.1%
Other values (139) 453
25.5%
ASCII
ValueCountFrequency (%)
111
81.0%
1 12
 
8.8%
2 12
 
8.8%
3 2
 
1.5%

소재지도로명주소
Text

Distinct281
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T11:56:54.275480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.105263
Min length8

Characters and Unicode

Total characters3165
Distinct characters183
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

Unique277 ?
Unique (%)97.2%

Sample

1st row창녕읍 향교길18
2nd row창녕읍 우포로1203
3rd row창녕읍 창서 798-1
4th row창녕읍 교상길 5-5
5th row창녕읍 교하리 263-18
ValueCountFrequency (%)
남지읍 38
 
5.0%
대합면 31
 
4.1%
창녕읍 31
 
4.1%
이방면 21
 
2.8%
장마면 21
 
2.8%
유어면 19
 
2.5%
성산면 18
 
2.4%
대지면 18
 
2.4%
계성면 17
 
2.2%
고암면 17
 
2.2%
Other values (429) 529
69.6%
2023-12-12T11:56:54.851188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
15.5%
길 230
 
7.3%
면 216
 
6.8%
1 178
 
5.6%
2 110
 
3.5%
- 88
 
2.8%
3 85
 
2.7%
대 76
 
2.4%
5 71
 
2.2%
읍 69
 
2.2%
Other values (173) 1551
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1825
57.7%
Decimal Number 761
24.0%
Space Separator 491
 
15.5%
Dash Punctuation 88
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 230
 
12.6%
면 216
 
11.8%
대 76
 
4.2%
읍 69
 
3.8%
지 68
 
3.7%
산 68
 
3.7%
남 52
 
2.8%
성 50
 
2.7%
곡 47
 
2.6%
리 43
 
2.4%
Other values (161) 906
49.6%
Decimal Number
ValueCountFrequency (%)
1 178
23.4%
2 110
14.5%
3 85
11.2%
5 71
 
9.3%
4 66
 
8.7%
0 56
 
7.4%
7 53
 
7.0%
9 50
 
6.6%
8 46
 
6.0%
6 46
 
6.0%
Space Separator
ValueCountFrequency (%)
491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1825
57.7%
Common 1340
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 230
 
12.6%
면 216
 
11.8%
대 76
 
4.2%
읍 69
 
3.8%
지 68
 
3.7%
산 68
 
3.7%
남 52
 
2.8%
성 50
 
2.7%
곡 47
 
2.6%
리 43
 
2.4%
Other values (161) 906
49.6%
Common
ValueCountFrequency (%)
491
36.6%
1 178
 
13.3%
2 110
 
8.2%
- 88
 
6.6%
3 85
 
6.3%
5 71
 
5.3%
4 66
 
4.9%
0 56
 
4.2%
7 53
 
4.0%
9 50
 
3.7%
Other values (2) 92
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1825
57.7%
ASCII 1340
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
36.6%
1 178
 
13.3%
2 110
 
8.2%
- 88
 
6.6%
3 85
 
6.3%
5 71
 
5.3%
4 66
 
4.9%
0 56
 
4.2%
7 53
 
4.0%
9 50
 
3.7%
Other values (2) 92
 
6.9%
Hangul
ValueCountFrequency (%)
길 230
 
12.6%
면 216
 
11.8%
대 76
 
4.2%
읍 69
 
3.8%
지 68
 
3.7%
산 68
 
3.7%
남 52
 
2.8%
성 50
 
2.7%
곡 47
 
2.6%
리 43
 
2.4%
Other values (161) 906
49.6%

건축년도
Real number (ℝ)

Distinct41
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.3614
Minimum1938
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T11:56:55.048261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1938
5-th percentile1979
Q11997
median2002
Q32006
95-th percentile2010.8
Maximum2015
Range77
Interquartile range (IQR)9

Descriptive statistics

Standard deviation9.3046587
Coefficient of variation (CV)0.0046514888
Kurtosis7.6468555
Mean2000.3614
Median Absolute Deviation (MAD)4
Skewness-2.0411225
Sum570103
Variance86.576674
MonotonicityNot monotonic
2023-12-12T11:56:55.226269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2004 30
 
10.5%
2009 21
 
7.4%
2005 20
 
7.0%
2002 18
 
6.3%
2007 17
 
6.0%
2000 17
 
6.0%
2003 14
 
4.9%
1995 14
 
4.9%
1999 13
 
4.6%
1998 13
 
4.6%
Other values (31) 108
37.9%
ValueCountFrequency (%)
1938 1
 
0.4%
1972 1
 
0.4%
1974 4
1.4%
1975 1
 
0.4%
1976 1
 
0.4%
1977 2
0.7%
1978 3
1.1%
1979 4
1.4%
1980 1
 
0.4%
1981 2
0.7%
ValueCountFrequency (%)
2015 3
 
1.1%
2014 3
 
1.1%
2013 4
 
1.4%
2012 3
 
1.1%
2011 2
 
0.7%
2010 4
 
1.4%
2009 21
7.4%
2008 9
3.2%
2007 17
6.0%
2006 9
3.2%

규모
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
지상1층
209 
지상2층
57 
1층
 
10
2층
 
8
지상3층
 
1

Length

Max length4
Median length4
Mean length3.8736842
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row지상1층
2nd row지상1층
3rd row지상2층
4th row지상2층
5th row지상2층

Common Values

ValueCountFrequency (%)
지상1층 209
73.3%
지상2층 57
 
20.0%
1층 10
 
3.5%
2층 8
 
2.8%
지상3층 1
 
0.4%

Length

2023-12-12T11:56:55.378520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:55.498070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상1층 209
73.3%
지상2층 57
 
20.0%
1층 10
 
3.5%
2층 8
 
2.8%
지상3층 1
 
0.4%

전화번호
Text

MISSING 

Distinct211
Distinct (%)99.1%
Missing72
Missing (%)25.3%
Memory size2.4 KiB
2023-12-12T11:56:55.758279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2556
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

Unique209 ?
Unique (%)98.1%

Sample

1st row055-533-2102
2nd row055-533-7689
3rd row055-532-8416
4th row055-533-6164
5th row055-533-3446
ValueCountFrequency (%)
055-536-3928 2
 
0.9%
055-536-8534 2
 
0.9%
055-536-5587 1
 
0.5%
055-536-5118 1
 
0.5%
055-521-1955 1
 
0.5%
055-532-9491 1
 
0.5%
055-521-3018 1
 
0.5%
055-521-2889 1
 
0.5%
055-532-0856 1
 
0.5%
055-533-9180 1
 
0.5%
Other values (201) 201
94.4%
2023-12-12T11:56:56.532609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 738
28.9%
- 426
16.7%
3 303
11.9%
0 296
11.6%
2 198
 
7.7%
6 167
 
6.5%
1 115
 
4.5%
9 86
 
3.4%
4 82
 
3.2%
8 75
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2130
83.3%
Dash Punctuation 426
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 738
34.6%
3 303
14.2%
0 296
13.9%
2 198
 
9.3%
6 167
 
7.8%
1 115
 
5.4%
9 86
 
4.0%
4 82
 
3.8%
8 75
 
3.5%
7 70
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 738
28.9%
- 426
16.7%
3 303
11.9%
0 296
11.6%
2 198
 
7.7%
6 167
 
6.5%
1 115
 
4.5%
9 86
 
3.4%
4 82
 
3.2%
8 75
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 738
28.9%
- 426
16.7%
3 303
11.9%
0 296
11.6%
2 198
 
7.7%
6 167
 
6.5%
1 115
 
4.5%
9 86
 
3.4%
4 82
 
3.2%
8 75
 
2.9%

Interactions

2023-12-12T11:56:50.576751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:56:56.642110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면건축년도규모
읍면1.0000.4080.726
건축년도0.4081.0000.228
규모0.7260.2281.000
2023-12-12T11:56:56.748789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모읍면
규모1.0000.478
읍면0.4781.000
2023-12-12T11:56:56.841321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축년도읍면규모
건축년도1.0000.1950.222
읍면0.1951.0000.478
규모0.2220.4781.000

Missing values

2023-12-12T11:56:50.791632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:56:50.998036image/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

시도명시군구명읍면마을명회관명소재지도로명주소건축년도규모전화번호
0경상남도창녕군창녕읍교리교리 마을회관창녕읍 향교길181995지상1층<NA>
1경상남도창녕군창녕읍갈전갈전 마을회관창녕읍 우포로12032001지상1층055-533-2102
2경상남도창녕군창녕읍창서창서 마을회관창녕읍 창서 798-11994지상2층055-533-7689
3경상남도창녕군창녕읍교상교상 마을회관창녕읍 교상길 5-51994지상2층055-532-8416
4경상남도창녕군창녕읍교하교하 마을회관창녕읍 교하리 263-182005지상2층055-533-6164
5경상남도창녕군창녕읍옥만옥만 마을회관창녕읍 교하새갈502011지상1층<NA>
6경상남도창녕군창녕읍학천학천 마을회관창녕읍 학천리 227-12004지상2층055-533-3446
7경상남도창녕군창녕읍봉천봉천 마을회관창녕읍 봉천리 247-21988지상1층055-533-7793
8경상남도창녕군창녕읍말흘말흘리 마을회관창녕읍 말흘 1길182015지상2층055-533-1755
9경상남도창녕군창녕읍낙영낙영 마을회관창녕읍 낙영 7362004지상1층055-533-0062
시도명시군구명읍면마을명회관명소재지도로명주소건축년도규모전화번호
275경상남도창녕군부곡면온정온정마을회관부곡면 온정리96-142014지상1층<NA>
276경상남도창녕군부곡면차실차실마을회관부곡면 차실길36-32005지상1층<NA>
277경상남도창녕군부곡면청암청암마을회관부곡면 청암1길221998지상1층<NA>
278경상남도창녕군부곡면노리노리마을회관부곡면 노리2길42006지상1층<NA>
279경상남도창녕군부곡면신포신포마을회관부곡면 신포길312007지상1층<NA>
280경상남도창녕군부곡면학포학포마을회관부곡면 학포1길40-11993지상1층<NA>
281경상남도창녕군부곡면구산구산마을회관부곡면 구산1길91998지상1층<NA>
282경상남도창녕군부곡면비봉비봉마을회관부곡면 비봉길772007지상1층<NA>
283경상남도창녕군부곡면수다수다마을회관부곡면 수다리232015지상1층055-521-2836
284경상남도창녕군부곡면수성수성마을회관부곡면 수성길29-42014지상1층<NA>