Overview

Dataset statistics

Number of variables5
Number of observations261
Missing cells261
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.8 KiB
Average record size in memory42.5 B

Variable types

Numeric1
Text2
Categorical1
Unsupported1

Dataset

Description충청남도 보령시 마을회관의 시설명, 도로명 주소, 지번 주소, 위도, 경도, 동수/층수, 건축면적, 연면적, 사용승인일, 소유자, 경로다겸용여부, 건축년도에 대한 데이터를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=425&beforeMenuCd=DOM_000000201001001000&publicdatapk=15037749

Alerts

종류 has constant value ""Constant
전화번호 has 261 (100.0%) missing valuesMissing
연번 has unique valuesUnique
시설소재지 주소 has unique valuesUnique
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 21:35:10.769933
Analysis finished2024-01-09 21:35:11.405607
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct261
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131
Minimum1
Maximum261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-10T06:35:11.467885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14
Q166
median131
Q3196
95-th percentile248
Maximum261
Range260
Interquartile range (IQR)130

Descriptive statistics

Standard deviation75.48841
Coefficient of variation (CV)0.5762474
Kurtosis-1.2
Mean131
Median Absolute Deviation (MAD)65
Skewness0
Sum34191
Variance5698.5
MonotonicityStrictly increasing
2024-01-10T06:35:11.576179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
165 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
Other values (251) 251
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%

시설명
Text

Distinct254
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:11.771806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length18
Mean length10.413793
Min length5

Characters and Unicode

Total characters2718
Distinct characters184
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

Unique247 ?
Unique (%)94.6%

Sample

1st row수부1리 마을회관 (신기 경로당)
2nd row수부2리 마을회관
3rd row수부3리 마을회관 (부당 경로당)
4th row성동1리 마을회관 (내성 경로당)
5th row성동2,3리 노인회관 (외성 경로당)
ValueCountFrequency (%)
마을회관 144
32.6%
경로당 13
 
2.9%
노인회관 4
 
0.9%
대천2리 2
 
0.5%
관산리 2
 
0.5%
죽청2리 2
 
0.5%
관당2리 2
 
0.5%
독산2리 2
 
0.5%
궁촌2통마을회관 2
 
0.5%
두룡1리 2
 
0.5%
Other values (261) 267
60.4%
2024-01-10T06:35:12.089923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 262
 
9.6%
회 255
 
9.4%
마 246
 
9.1%
을 243
 
8.9%
리 200
 
7.4%
182
 
6.7%
( 99
 
3.6%
) 99
 
3.6%
2 88
 
3.2%
1 77
 
2.8%
Other values (174) 967
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2098
77.2%
Decimal Number 236
 
8.7%
Space Separator 182
 
6.7%
Open Punctuation 99
 
3.6%
Close Punctuation 99
 
3.6%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 262
 
12.5%
회 255
 
12.2%
마 246
 
11.7%
을 243
 
11.6%
리 200
 
9.5%
통 42
 
2.0%
대 34
 
1.6%
당 31
 
1.5%
신 30
 
1.4%
성 28
 
1.3%
Other values (159) 727
34.7%
Decimal Number
ValueCountFrequency (%)
2 88
37.3%
1 77
32.6%
3 31
 
13.1%
4 13
 
5.5%
5 10
 
4.2%
7 5
 
2.1%
8 4
 
1.7%
6 4
 
1.7%
9 2
 
0.8%
0 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2098
77.2%
Common 620
 
22.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 262
 
12.5%
회 255
 
12.2%
마 246
 
11.7%
을 243
 
11.6%
리 200
 
9.5%
통 42
 
2.0%
대 34
 
1.6%
당 31
 
1.5%
신 30
 
1.4%
성 28
 
1.3%
Other values (159) 727
34.7%
Common
ValueCountFrequency (%)
182
29.4%
( 99
16.0%
) 99
16.0%
2 88
14.2%
1 77
12.4%
3 31
 
5.0%
4 13
 
2.1%
5 10
 
1.6%
7 5
 
0.8%
8 4
 
0.6%
Other values (5) 12
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2098
77.2%
ASCII 620
 
22.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 262
 
12.5%
회 255
 
12.2%
마 246
 
11.7%
을 243
 
11.6%
리 200
 
9.5%
통 42
 
2.0%
대 34
 
1.6%
당 31
 
1.5%
신 30
 
1.4%
성 28
 
1.3%
Other values (159) 727
34.7%
ASCII
ValueCountFrequency (%)
182
29.4%
( 99
16.0%
) 99
16.0%
2 88
14.2%
1 77
12.4%
3 31
 
5.0%
4 13
 
2.1%
5 10
 
1.6%
7 5
 
0.8%
8 4
 
0.6%
Other values (5) 12
 
1.9%

종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
마을회관
261 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
마을회관 261
100.0%

Length

2024-01-10T06:35:12.200441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:12.268174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회관 261
100.0%

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing261
Missing (%)100.0%
Memory size2.4 KiB

시설소재지 주소
Text

UNIQUE 

Distinct261
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:12.562721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length13.739464
Min length6

Characters and Unicode

Total characters3586
Distinct characters119
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

Unique261 ?
Unique (%)100.0%

Sample

1st row웅천읍 수부리 297-3
2nd row웅천읍 수부리 805-2
3rd row웅천읍 수부리 586
4th row웅천읍 성동리 199-1
5th row웅천읍 성동리 781-3
ValueCountFrequency (%)
외 45
 
5.4%
1필지 38
 
4.6%
오천면 33
 
4.0%
천북면 29
 
3.5%
미산면 23
 
2.8%
주산면 21
 
2.5%
주교면 21
 
2.5%
웅천읍 20
 
2.4%
남포면 18
 
2.2%
청소면 17
 
2.0%
Other values (362) 569
68.2%
2024-01-10T06:35:12.997237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
706
19.7%
1 220
 
6.1%
리 219
 
6.1%
- 210
 
5.9%
면 199
 
5.5%
2 151
 
4.2%
3 129
 
3.6%
5 117
 
3.3%
4 106
 
3.0%
천 103
 
2.9%
Other values (109) 1426
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1603
44.7%
Decimal Number 1063
29.6%
Space Separator 706
19.7%
Dash Punctuation 210
 
5.9%
Other Punctuation 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 219
 
13.7%
면 199
 
12.4%
천 103
 
6.4%
주 80
 
5.0%
산 65
 
4.1%
동 55
 
3.4%
외 47
 
2.9%
지 47
 
2.9%
필 46
 
2.9%
성 39
 
2.4%
Other values (94) 703
43.9%
Decimal Number
ValueCountFrequency (%)
1 220
20.7%
2 151
14.2%
3 129
12.1%
5 117
11.0%
4 106
10.0%
6 80
 
7.5%
7 75
 
7.1%
8 69
 
6.5%
0 62
 
5.8%
9 54
 
5.1%
Space Separator
ValueCountFrequency (%)
706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Other Punctuation
ValueCountFrequency (%)
\ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1983
55.3%
Hangul 1603
44.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 219
 
13.7%
면 199
 
12.4%
천 103
 
6.4%
주 80
 
5.0%
산 65
 
4.1%
동 55
 
3.4%
외 47
 
2.9%
지 47
 
2.9%
필 46
 
2.9%
성 39
 
2.4%
Other values (94) 703
43.9%
Common
ValueCountFrequency (%)
706
35.6%
1 220
 
11.1%
- 210
 
10.6%
2 151
 
7.6%
3 129
 
6.5%
5 117
 
5.9%
4 106
 
5.3%
6 80
 
4.0%
7 75
 
3.8%
8 69
 
3.5%
Other values (5) 120
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1983
55.3%
Hangul 1603
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
706
35.6%
1 220
 
11.1%
- 210
 
10.6%
2 151
 
7.6%
3 129
 
6.5%
5 117
 
5.9%
4 106
 
5.3%
6 80
 
4.0%
7 75
 
3.8%
8 69
 
3.5%
Other values (5) 120
 
6.1%
Hangul
ValueCountFrequency (%)
리 219
 
13.7%
면 199
 
12.4%
천 103
 
6.4%
주 80
 
5.0%
산 65
 
4.1%
동 55
 
3.4%
외 47
 
2.9%
지 47
 
2.9%
필 46
 
2.9%
성 39
 
2.4%
Other values (94) 703
43.9%

Interactions

2024-01-10T06:35:11.222262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-01-10T06:35:11.301374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:35:11.372173image/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

연번시설명종류전화번호시설소재지 주소
01수부1리 마을회관 (신기 경로당)마을회관<NA>웅천읍 수부리 297-3
12수부2리 마을회관마을회관<NA>웅천읍 수부리 805-2
23수부3리 마을회관 (부당 경로당)마을회관<NA>웅천읍 수부리 586
34성동1리 마을회관 (내성 경로당)마을회관<NA>웅천읍 성동리 199-1
45성동2,3리 노인회관 (외성 경로당)마을회관<NA>웅천읍 성동리 781-3
56대창5리 마을회관마을회관<NA>웅천읍 대창리 483
67대창5리 마을회관마을회관<NA>웅천읍 대창리 483-2
78대창6리 마을회관마을회관<NA>웅천읍 대창리 453-1
89대창9리 노인회관 (웅천읍분회경로당)마을회관<NA>웅천읍 대창리 685-1 외 2필지
910대천2리 마을회관 (대천2리 경로당)마을회관<NA>웅천읍 대천리 166-2 외 1필지
연번시설명종류전화번호시설소재지 주소
251252창암2리마을회관마을회관<NA>주산면 창암리 480-2
252253삼곡1리(큰샘실)마을회관마을회관<NA>주산면 삼곡리 158
253254평라리마을회관마을회관<NA>미산면 평라리 25
254255대천17통마을회관마을회관<NA>대천동 331-46
255256명천2통마을회관마을회관<NA>명천동 224-1
256257명천4통마을회관마을회관<NA>명천동 531-9
257258명천6통마을회관마을회관<NA>궁촌동 6-1
258259궁촌2통마을회관마을회관<NA>궁촌동 105-5
259260신흑8통마을(노인)회관마을회관<NA>신흑동 911-107
260261신흑10통마을(노인)회관마을회관<NA>신흑동 1457-4