Overview

Dataset statistics

Number of variables12
Number of observations179
Missing cells3
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory100.7 B

Variable types

Categorical4
Text4
Numeric4

Dataset

Description통영시 관내 마을회관에 대하여 행정구역,시설명,전화번호,소재지도로명주소,소재지지번주소,이용인원,준공연도,대지면적(㎡),건축면적(㎡),연면적(㎡),구조,데이터기준일자 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15006902/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
대지면적 is highly overall correlated with 건축면적High correlation
건축면적 is highly overall correlated with 대지면적High correlation
전화번호 is highly imbalanced (55.2%)Imbalance
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:37:45.731186
Analysis finished2023-12-12 13:37:48.489539
Duration2.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역
Categorical

Distinct9
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
한산면
31 
산양읍
30 
욕지면
28 
용남면
26 
광도면
24 
Other values (4)
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한산면 31
17.3%
산양읍 30
16.8%
욕지면 28
15.6%
용남면 26
14.5%
광도면 24
13.4%
도산면 22
12.3%
사량면 14
7.8%
도천동 2
 
1.1%
명정동 2
 
1.1%

Length

2023-12-12T22:37:48.569728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:37:48.737049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한산면 31
17.3%
산양읍 30
16.8%
욕지면 28
15.6%
용남면 26
14.5%
광도면 24
13.4%
도산면 22
12.3%
사량면 14
7.8%
도천동 2
 
1.1%
명정동 2
 
1.1%

시설명
Text

Distinct168
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:37:49.053068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0726257
Min length5

Characters and Unicode

Total characters1087
Distinct characters138
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)88.8%

Sample

1st row일운마을회관
2nd row이운마을회관
3rd row수륙마을회관
4th row신봉마을회관
5th row봉전마을회관
ValueCountFrequency (%)
대항마을회관 3
 
1.7%
상촌마을회관 3
 
1.7%
죽전마을회관 2
 
1.1%
동촌마을회관 2
 
1.1%
대촌마을회관 2
 
1.1%
서촌마을회관 2
 
1.1%
원문마을회관 2
 
1.1%
동부마을회관 2
 
1.1%
덕동마을회관 2
 
1.1%
조선마을회관 1
 
0.6%
Other values (158) 158
88.3%
2023-12-12T22:37:49.859761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 181
16.7%
관 180
16.6%
을 179
16.5%
회 178
16.4%
촌 22
 
2.0%
포 19
 
1.7%
동 15
 
1.4%
대 12
 
1.1%
도 9
 
0.8%
항 9
 
0.8%
Other values (128) 283
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1086
99.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 181
16.7%
관 180
16.6%
을 179
16.5%
회 178
16.4%
촌 22
 
2.0%
포 19
 
1.7%
동 15
 
1.4%
대 12
 
1.1%
도 9
 
0.8%
항 9
 
0.8%
Other values (127) 282
26.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1086
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 181
16.7%
관 180
16.6%
을 179
16.5%
회 178
16.4%
촌 22
 
2.0%
포 19
 
1.7%
동 15
 
1.4%
대 12
 
1.1%
도 9
 
0.8%
항 9
 
0.8%
Other values (127) 282
26.0%
Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1086
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 181
16.7%
관 180
16.6%
을 179
16.5%
회 178
16.4%
촌 22
 
2.0%
포 19
 
1.7%
동 15
 
1.4%
대 12
 
1.1%
도 9
 
0.8%
항 9
 
0.8%
Other values (127) 282
26.0%
ASCII
ValueCountFrequency (%)
1 1
100.0%

전화번호
Categorical

IMBALANCE 

Distinct47
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
데이터 부존재
126 
055-643-9037
 
3
055-641-0591
 
3
055-641-4160
 
2
055-643-8565
 
2
Other values (42)
43 

Length

Max length12
Median length7
Mean length8.4804469
Min length7

Unique

Unique41 ?
Unique (%)22.9%

Sample

1st row055-643-8369
2nd row055-641-4160
3rd row데이터 부존재
4th row데이터 부존재
5th row055-642-0888

Common Values

ValueCountFrequency (%)
데이터 부존재 126
70.4%
055-643-9037 3
 
1.7%
055-641-0591 3
 
1.7%
055-641-4160 2
 
1.1%
055-643-8565 2
 
1.1%
055-649-2194 2
 
1.1%
055-644-1735 1
 
0.6%
055-642-0888 1
 
0.6%
055-642-1561 1
 
0.6%
055-642-1070 1
 
0.6%
Other values (37) 37
 
20.7%

Length

2023-12-12T22:37:50.009193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
데이터 126
41.3%
부존재 126
41.3%
055-643-9037 3
 
1.0%
055-641-0591 3
 
1.0%
055-641-4160 2
 
0.7%
055-643-8565 2
 
0.7%
055-649-2194 2
 
0.7%
055-643-8369 1
 
0.3%
055-648-8515 1
 
0.3%
055-644-0853 1
 
0.3%
Other values (38) 38
 
12.5%

소재지도로명주소
Text

Distinct177
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:37:50.398334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.039106
Min length18

Characters and Unicode

Total characters3766
Distinct characters155
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

Unique175 ?
Unique (%)97.8%

Sample

1st row경상남도 통영시 산양읍 산양일주로 285
2nd row경상남도 통영시 산양읍 이운길 54
3rd row경상남도 통영시 산양읍 수륙길 40-12
4th row경상남도 통영시 산양읍 신봉천상길 6
5th row경상남도 통영시 산양읍 산양일주로 694
ValueCountFrequency (%)
경상남도 179
20.0%
통영시 179
20.0%
한산면 31
 
3.5%
산양읍 30
 
3.4%
도산면 25
 
2.8%
용남면 25
 
2.8%
광도면 24
 
2.7%
욕지면 24
 
2.7%
사량면 15
 
1.7%
욕지일주로 7
 
0.8%
Other values (303) 354
39.6%
2023-12-12T22:37:50.875552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
734
19.5%
도 248
 
6.6%
남 207
 
5.5%
상 184
 
4.9%
경 179
 
4.8%
통 179
 
4.8%
영 179
 
4.8%
시 179
 
4.8%
면 144
 
3.8%
길 132
 
3.5%
Other values (145) 1401
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2435
64.7%
Space Separator 734
 
19.5%
Decimal Number 534
 
14.2%
Dash Punctuation 55
 
1.5%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 248
 
10.2%
남 207
 
8.5%
상 184
 
7.6%
경 179
 
7.4%
통 179
 
7.4%
영 179
 
7.4%
시 179
 
7.4%
면 144
 
5.9%
길 132
 
5.4%
산 113
 
4.6%
Other values (131) 691
28.4%
Decimal Number
ValueCountFrequency (%)
1 118
22.1%
2 77
14.4%
3 56
10.5%
4 55
10.3%
8 49
9.2%
5 43
 
8.1%
6 37
 
6.9%
7 36
 
6.7%
0 35
 
6.6%
9 28
 
5.2%
Space Separator
ValueCountFrequency (%)
734
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2435
64.7%
Common 1331
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 248
 
10.2%
남 207
 
8.5%
상 184
 
7.6%
경 179
 
7.4%
통 179
 
7.4%
영 179
 
7.4%
시 179
 
7.4%
면 144
 
5.9%
길 132
 
5.4%
산 113
 
4.6%
Other values (131) 691
28.4%
Common
ValueCountFrequency (%)
734
55.1%
1 118
 
8.9%
2 77
 
5.8%
3 56
 
4.2%
- 55
 
4.1%
4 55
 
4.1%
8 49
 
3.7%
5 43
 
3.2%
6 37
 
2.8%
7 36
 
2.7%
Other values (4) 71
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2435
64.7%
ASCII 1331
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
734
55.1%
1 118
 
8.9%
2 77
 
5.8%
3 56
 
4.2%
- 55
 
4.1%
4 55
 
4.1%
8 49
 
3.7%
5 43
 
3.2%
6 37
 
2.8%
7 36
 
2.7%
Other values (4) 71
 
5.3%
Hangul
ValueCountFrequency (%)
도 248
 
10.2%
남 207
 
8.5%
상 184
 
7.6%
경 179
 
7.4%
통 179
 
7.4%
영 179
 
7.4%
시 179
 
7.4%
면 144
 
5.9%
길 132
 
5.4%
산 113
 
4.6%
Other values (131) 691
28.4%

소재지지번주소
Text

UNIQUE 

Distinct179
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:37:51.247583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length22
Mean length22.368715
Min length16

Characters and Unicode

Total characters4004
Distinct characters93
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

Unique179 ?
Unique (%)100.0%

Sample

1st row경상남도 통영시 산양읍 영운리 668-6
2nd row경상남도 통영시 산양읍 영운리 517-1
3rd row경상남도 통영시 산양읍 영운리 48
4th row경상남도 통영시 산양읍 신전리 611-2
5th row경상남도 통영시 산양읍 신전리 851-3
ValueCountFrequency (%)
경상남도 179
19.8%
통영시 179
19.8%
한산면 31
 
3.4%
산양읍 30
 
3.3%
욕지면 28
 
3.1%
용남면 26
 
2.9%
광도면 24
 
2.7%
도산면 22
 
2.4%
동항리 16
 
1.8%
사량면 14
 
1.5%
Other values (242) 356
39.3%
2023-12-12T22:37:51.711853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
726
18.1%
도 234
 
5.8%
남 211
 
5.3%
영 182
 
4.5%
리 180
 
4.5%
경 179
 
4.5%
시 179
 
4.5%
상 179
 
4.5%
통 179
 
4.5%
- 156
 
3.9%
Other values (83) 1599
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2345
58.6%
Decimal Number 759
 
19.0%
Space Separator 726
 
18.1%
Dash Punctuation 156
 
3.9%
Other Punctuation 10
 
0.2%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 234
10.0%
남 211
 
9.0%
영 182
 
7.8%
리 180
 
7.7%
경 179
 
7.6%
시 179
 
7.6%
상 179
 
7.6%
통 179
 
7.6%
면 145
 
6.2%
산 98
 
4.2%
Other values (68) 579
24.7%
Decimal Number
ValueCountFrequency (%)
1 147
19.4%
2 95
12.5%
5 88
11.6%
7 70
9.2%
4 65
8.6%
3 62
8.2%
6 61
8.0%
8 60
7.9%
9 56
 
7.4%
0 55
 
7.2%
Space Separator
ValueCountFrequency (%)
726
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2345
58.6%
Common 1659
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 234
10.0%
남 211
 
9.0%
영 182
 
7.8%
리 180
 
7.7%
경 179
 
7.6%
시 179
 
7.6%
상 179
 
7.6%
통 179
 
7.6%
면 145
 
6.2%
산 98
 
4.2%
Other values (68) 579
24.7%
Common
ValueCountFrequency (%)
726
43.8%
- 156
 
9.4%
1 147
 
8.9%
2 95
 
5.7%
5 88
 
5.3%
7 70
 
4.2%
4 65
 
3.9%
3 62
 
3.7%
6 61
 
3.7%
8 60
 
3.6%
Other values (5) 129
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2345
58.6%
ASCII 1659
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
726
43.8%
- 156
 
9.4%
1 147
 
8.9%
2 95
 
5.7%
5 88
 
5.3%
7 70
 
4.2%
4 65
 
3.9%
3 62
 
3.7%
6 61
 
3.7%
8 60
 
3.6%
Other values (5) 129
 
7.8%
Hangul
ValueCountFrequency (%)
도 234
10.0%
남 211
 
9.0%
영 182
 
7.8%
리 180
 
7.7%
경 179
 
7.6%
시 179
 
7.6%
상 179
 
7.6%
통 179
 
7.6%
면 145
 
6.2%
산 98
 
4.2%
Other values (68) 579
24.7%

이용인원
Real number (ℝ)

Distinct146
Distinct (%)82.0%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean175.03371
Minimum4
Maximum1123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T22:37:51.849015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile28.7
Q169.75
median118.5
Q3241.5
95-th percentile435.6
Maximum1123
Range1119
Interquartile range (IQR)171.75

Descriptive statistics

Standard deviation161.84878
Coefficient of variation (CV)0.92467206
Kurtosis8.4112655
Mean175.03371
Median Absolute Deviation (MAD)67.5
Skewness2.3838381
Sum31156
Variance26195.027
MonotonicityNot monotonic
2023-12-12T22:37:51.997866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 5
 
2.8%
48 3
 
1.7%
93 3
 
1.7%
145 3
 
1.7%
73 3
 
1.7%
76 2
 
1.1%
20 2
 
1.1%
161 2
 
1.1%
41 2
 
1.1%
205 2
 
1.1%
Other values (136) 151
84.4%
ValueCountFrequency (%)
4 1
0.6%
15 1
0.6%
17 1
0.6%
20 2
1.1%
23 1
0.6%
24 1
0.6%
26 1
0.6%
27 1
0.6%
29 1
0.6%
31 1
0.6%
ValueCountFrequency (%)
1123 1
0.6%
813 1
0.6%
799 1
0.6%
744 1
0.6%
548 1
0.6%
538 1
0.6%
499 1
0.6%
470 1
0.6%
439 1
0.6%
435 1
0.6%

준공연도
Real number (ℝ)

Distinct49
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.8101
Minimum1971
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T22:37:52.135735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1971
5-th percentile1976.9
Q11991
median2000
Q32009.5
95-th percentile2019
Maximum2022
Range51
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation12.614763
Coefficient of variation (CV)0.0063079808
Kurtosis-0.73700704
Mean1999.8101
Median Absolute Deviation (MAD)9
Skewness-0.26627402
Sum357966
Variance159.13226
MonotonicityNot monotonic
2023-12-12T22:37:52.335213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1991 10
 
5.6%
2004 9
 
5.0%
2007 9
 
5.0%
1995 8
 
4.5%
2019 8
 
4.5%
2005 7
 
3.9%
1994 6
 
3.4%
2000 6
 
3.4%
2010 6
 
3.4%
2008 6
 
3.4%
Other values (39) 104
58.1%
ValueCountFrequency (%)
1971 1
 
0.6%
1972 1
 
0.6%
1973 2
1.1%
1975 2
1.1%
1976 3
1.7%
1977 1
 
0.6%
1978 1
 
0.6%
1979 2
1.1%
1980 1
 
0.6%
1981 2
1.1%
ValueCountFrequency (%)
2022 1
 
0.6%
2021 1
 
0.6%
2020 3
 
1.7%
2019 8
4.5%
2018 3
 
1.7%
2017 6
3.4%
2016 1
 
0.6%
2015 1
 
0.6%
2014 3
 
1.7%
2013 5
2.8%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct144
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300.97933
Minimum62
Maximum1886
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T22:37:52.466556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile101.5
Q1157.5
median225
Q3336
95-th percentile676.7
Maximum1886
Range1824
Interquartile range (IQR)178.5

Descriptive statistics

Standard deviation280.52759
Coefficient of variation (CV)0.93204936
Kurtosis13.997476
Mean300.97933
Median Absolute Deviation (MAD)84
Skewness3.4075603
Sum53875.3
Variance78695.73
MonotonicityNot monotonic
2023-12-12T22:37:52.608146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185.0 4
 
2.2%
201.0 3
 
1.7%
107.0 3
 
1.7%
225.0 3
 
1.7%
131.0 3
 
1.7%
235.0 3
 
1.7%
166.0 3
 
1.7%
238.0 3
 
1.7%
165.0 3
 
1.7%
159.0 2
 
1.1%
Other values (134) 149
83.2%
ValueCountFrequency (%)
62.0 1
0.6%
66.0 2
1.1%
74.0 1
0.6%
76.0 1
0.6%
92.0 1
0.6%
93.0 2
1.1%
97.0 1
0.6%
102.0 1
0.6%
103.0 1
0.6%
105.0 1
0.6%
ValueCountFrequency (%)
1886.0 1
0.6%
1857.0 1
0.6%
1552.0 1
0.6%
1455.0 1
0.6%
1189.0 1
0.6%
1178.0 1
0.6%
996.0 1
0.6%
884.0 1
0.6%
728.0 1
0.6%
671.0 1
0.6%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct171
Distinct (%)96.1%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean96.382247
Minimum33
Maximum416.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-12T22:37:52.742963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile53.572
Q168.9075
median86.445
Q3107.6625
95-th percentile184.9135
Maximum416.85
Range383.85
Interquartile range (IQR)38.755

Descriptive statistics

Standard deviation47.595088
Coefficient of variation (CV)0.49381592
Kurtosis14.289426
Mean96.382247
Median Absolute Deviation (MAD)18.34
Skewness3.0879271
Sum17156.04
Variance2265.2924
MonotonicityNot monotonic
2023-12-12T22:37:52.897060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.11 3
 
1.7%
33.0 2
 
1.1%
66.0 2
 
1.1%
48.6 2
 
1.1%
66.12 2
 
1.1%
118.0 2
 
1.1%
109.58 1
 
0.6%
61.2 1
 
0.6%
68.08 1
 
0.6%
54.55 1
 
0.6%
Other values (161) 161
89.9%
ValueCountFrequency (%)
33.0 2
1.1%
38.61 1
0.6%
40.3 1
0.6%
47.7 1
0.6%
48.0 1
0.6%
48.6 2
1.1%
51.6 1
0.6%
53.92 1
0.6%
54.55 1
0.6%
54.76 1
0.6%
ValueCountFrequency (%)
416.85 1
0.6%
299.74 1
0.6%
285.89 1
0.6%
246.51 1
0.6%
243.5 1
0.6%
200.28 1
0.6%
194.96 1
0.6%
190.55 1
0.6%
186.69 1
0.6%
184.6 1
0.6%

연면적
Text

Distinct175
Distinct (%)98.3%
Missing1
Missing (%)0.6%
Memory size1.5 KiB
2023-12-12T22:37:53.372592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length5.3146067
Min length2

Characters and Unicode

Total characters946
Distinct characters12
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

Unique172 ?
Unique (%)96.6%

Sample

1st row189.66
2nd row116.04
3rd row99.65
4th row270.24
5th row132
ValueCountFrequency (%)
33 2
 
1.1%
164.25 2
 
1.1%
56.2 2
 
1.1%
159.71 1
 
0.6%
70.56 1
 
0.6%
189.66 1
 
0.6%
114.8 1
 
0.6%
117/94.55 1
 
0.6%
108.23 1
 
0.6%
54.55 1
 
0.6%
Other values (165) 165
92.7%
2023-12-12T22:37:53.872508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 168
17.8%
. 161
17.0%
5 88
9.3%
6 80
8.5%
2 79
8.4%
4 74
7.8%
9 71
7.5%
3 62
 
6.6%
8 61
 
6.4%
7 57
 
6.0%
Other values (2) 45
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 782
82.7%
Other Punctuation 164
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 168
21.5%
5 88
11.3%
6 80
10.2%
2 79
10.1%
4 74
9.5%
9 71
9.1%
3 62
 
7.9%
8 61
 
7.8%
7 57
 
7.3%
0 42
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 161
98.2%
/ 3
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 168
17.8%
. 161
17.0%
5 88
9.3%
6 80
8.5%
2 79
8.4%
4 74
7.8%
9 71
7.5%
3 62
 
6.6%
8 61
 
6.4%
7 57
 
6.0%
Other values (2) 45
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 168
17.8%
. 161
17.0%
5 88
9.3%
6 80
8.5%
2 79
8.4%
4 74
7.8%
9 71
7.5%
3 62
 
6.6%
8 61
 
6.4%
7 57
 
6.0%
Other values (2) 45
 
4.8%

구조
Categorical

Distinct49
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
철근콘크리트조/슬래브
48 
철근콘크리트/슬래브
17 
철근콘크리트/스라브
16 
조적조/슬래브
15 
벽돌조/슬래브
15 
Other values (44)
68 

Length

Max length40
Median length26
Mean length10.385475
Min length6

Unique

Unique36 ?
Unique (%)20.1%

Sample

1st row조적조/슬래브
2nd row철근콘크리트조/슬래브
3rd row철근콘크리트조/슬래브
4th row철근콘크리트조/슬래브
5th row1층블록조2층벽돌조/슬래브

Common Values

ValueCountFrequency (%)
철근콘크리트조/슬래브 48
26.8%
철근콘크리트/슬래브 17
 
9.5%
철근콘크리트/스라브 16
 
8.9%
조적조/슬래브 15
 
8.4%
벽돌조/슬래브 15
 
8.4%
블록조/슬래브 11
 
6.1%
블록조/슬레이트 5
 
2.8%
철근콘크리트조/경사슬래브 5
 
2.8%
철근콘크리트구조/아스팔트싱글 3
 
1.7%
벽돌조/스라브 2
 
1.1%
Other values (39) 42
23.5%

Length

2023-12-12T22:37:54.021326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트조/슬래브 48
25.8%
철근콘크리트/슬래브 17
 
9.1%
철근콘크리트/스라브 16
 
8.6%
조적조/슬래브 15
 
8.1%
벽돌조/슬래브 15
 
8.1%
블록조/슬래브 11
 
5.9%
블록조/슬레이트 5
 
2.7%
철근콘크리트조/경사슬래브 5
 
2.7%
철근콘크리트구조/아스팔트싱글 3
 
1.6%
1층철근콘크리트조2층벽돌조 2
 
1.1%
Other values (44) 49
26.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-08-29
179 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-29
2nd row2023-08-29
3rd row2023-08-29
4th row2023-08-29
5th row2023-08-29

Common Values

ValueCountFrequency (%)
2023-08-29 179
100.0%

Length

2023-12-12T22:37:54.134416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:37:54.221670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-29 179
100.0%

Interactions

2023-12-12T22:37:47.391646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.281236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.563258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.978447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.584706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.343762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.653749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.077208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.770867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.410840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.764186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.181415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.910774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.479553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:46.859293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:37:47.279807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:37:54.282545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역전화번호이용인원준공연도대지면적건축면적구조
행정구역1.0000.5790.3210.1410.0000.1200.755
전화번호0.5791.0000.8730.3490.7030.6760.865
이용인원0.3210.8731.0000.1180.5400.7810.827
준공연도0.1410.3490.1181.0000.0000.3190.603
대지면적0.0000.7030.5400.0001.0000.7690.000
건축면적0.1200.6760.7810.3190.7691.0000.689
구조0.7550.8650.8270.6030.0000.6891.000
2023-12-12T22:37:54.377547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구조행정구역전화번호
구조1.0000.3370.288
행정구역0.3371.0000.216
전화번호0.2880.2161.000
2023-12-12T22:37:54.466091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용인원준공연도대지면적건축면적행정구역전화번호구조
이용인원1.0000.0670.2540.4430.1620.4940.403
준공연도0.0671.0000.1700.1330.0640.1190.215
대지면적0.2540.1701.0000.5460.0000.2850.000
건축면적0.4430.1330.5461.0000.0560.2870.293
행정구역0.1620.0640.0000.0561.0000.2160.337
전화번호0.4940.1190.2850.2870.2161.0000.288
구조0.4030.2150.0000.2930.3370.2881.000

Missing values

2023-12-12T22:37:48.097249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:37:48.272795image/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.
2023-12-12T22:37:48.410809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

행정구역시설명전화번호소재지도로명주소소재지지번주소이용인원준공연도대지면적건축면적연면적구조데이터기준일자
0산양읍일운마을회관055-643-8369경상남도 통영시 산양읍 산양일주로 285경상남도 통영시 산양읍 영운리 668-649919941857.0109.58189.66조적조/슬래브2023-08-29
1산양읍이운마을회관055-641-4160경상남도 통영시 산양읍 이운길 54경상남도 통영시 산양읍 영운리 517-12902005113.067.54116.04철근콘크리트조/슬래브2023-08-29
2산양읍수륙마을회관데이터 부존재경상남도 통영시 산양읍 수륙길 40-12경상남도 통영시 산양읍 영운리 481002004325.0144.6699.65철근콘크리트조/슬래브2023-08-29
3산양읍신봉마을회관데이터 부존재경상남도 통영시 산양읍 신봉천상길 6경상남도 통영시 산양읍 신전리 611-24351992358.0137.64270.24철근콘크리트조/슬래브2023-08-29
4산양읍봉전마을회관055-642-0888경상남도 통영시 산양읍 산양일주로 694경상남도 통영시 산양읍 신전리 851-3671991198.066.01321층블록조2층벽돌조/슬래브2023-08-29
5산양읍마동마을회관055-641-4160경상남도 통영시 산양읍 척포길 183-5경상남도 통영시 산양읍 미남리 178-124420021189.0160.29289.4철근콘크리트조/슬래브2023-08-29
6산양읍달아마을회관데이터 부존재경상남도 통영시 산양읍 산양일주로 1024경상남도 통영시 산양읍 미남리 800-121519911552.0285.89285.89블록조/슬래브2023-08-29
7산양읍연명마을회관055-642-1561경상남도 통영시 산양읍 연명1길 1경상남도 통영시 산양읍 연화리 328-1327199193.054.76108.52철근콘크리트조/슬래브2023-08-29
8산양읍중화마을회관055-642-1070경상남도 통영시 산양읍 산양일주로 1436경상남도 통영시 산양읍 연화리 882-14071975289.0120.82227.68철근콘크리트조/슬래브2023-08-29
9산양읍당포마을회관055-642-1105경상남도 통영시 산양읍 당포길 9경상남도 통영시 산양읍 삼덕리 369-33041994132.076.87144.5조적조/슬래브2023-08-29
행정구역시설명전화번호소재지도로명주소소재지지번주소이용인원준공연도대지면적건축면적연면적구조데이터기준일자
169사량면덕동마을회관055-649-2194경상남도 통영시 사량면 하도일주로 42-113경상남도 통영시 사량면 읍덕리 199-81432020169.075.21111.3철근콘크리트조/슬래브2023-08-29
170사량면먹방마을회관055-649-2006경상남도 통영시 사량면 하도일주로 1281경상남도 통영시 사량면 읍덕리 57-241199592.056.256.21층블록조2층조적조/슬래브2023-08-29
171사량면읍포마을회관055-648-7725경상남도 통영시 사량면 읍포2길 33경상남도 통영시 사량면 읍덕리 700-91571995244.098.09149.04철근콘크리트조/슬래브2023-08-29
172사량면외지마을회관055-649-7794경상남도 통영시 사량면 외지길 6경상남도 통영시 사량면 양지리 712-2581976476.0114.04114.04블록조/슬래브2023-08-29
173사량면능양마을회관데이터 부존재경상남도 통영시 사량면 능양길 24경상남도 통영시 사량면 양지리 187-51271995173.0102.4192철근콘크리트조/슬래브2023-08-29
174사량면백학마을회관055-649-7060경상남도 통영시 사량면 백학길 5경상남도 통영시 사량면 양지리 176-8911998319.062.94103.94블록조/슬래브2023-08-29
175도천동우포마을회관데이터 부존재경상남도 통영시 평인일주로 529 (평림동)경상남도 통영시 평림동 898-33141998165.093.12159.71철근콘크리트조/슬래브2023-08-29
176도천동국치마을회관데이터 부존재경상남도 통영시 국치1길 36 (인평동)경상남도 통영시 인평동 494781998225.088.5883.14조적조/슬래브2023-08-29
177명정동소포마을회관055-644-4892경상남도 통영시 작은개길 16-12(평림동)경상남도 통영시 평림동 95-2, 95-4, 67-141152016219.081.1677.16철근콘크리트조/슬래브2023-08-29
178명정동대평마을회관데이터 부존재경상남도 통영시 큰개길 5(평림동)경상남도 통영시 평림동 222-5, 222-102091991172.070.0136.12철근콘크리트조/슬래브2023-08-29