Overview

Dataset statistics

Number of variables6
Number of observations337
Missing cells12
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory50.4 B

Variable types

Categorical1
Text2
Numeric2
DateTime1

Dataset

Description홍성군내 마을회관 현황으로 시설명, 시설유형, 주소, 위도, 경도, 영업상태명, 건립일자, 건물면적, 데이터기준일 등을 제공합니다
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=443&beforeMenuCd=DOM_000000201001001000&publicdatapk=3073649

Alerts

데이터기준일자 has constant value ""Constant
건축년도 has 6 (1.8%) missing valuesMissing
건축면적(㎡) has 6 (1.8%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:10:53.048456
Analysis finished2024-01-09 21:10:53.865428
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면
Categorical

Distinct11
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
홍성읍
47 
광천읍
41 
홍동면
33 
장곡면
32 
서부면
29 
Other values (6)
155 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홍성읍 47
13.9%
광천읍 41
12.2%
홍동면 33
9.8%
장곡면 32
9.5%
서부면 29
8.6%
갈산면 29
8.6%
홍북읍 27
8.0%
금마면 26
7.7%
은하면 25
7.4%
결성면 25
7.4%

Length

2024-01-10T06:10:53.926826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
홍성읍 47
13.9%
광천읍 41
12.2%
홍동면 33
9.8%
장곡면 32
9.5%
서부면 29
8.6%
갈산면 29
8.6%
홍북읍 27
8.0%
금마면 26
7.7%
은하면 25
7.4%
결성면 25
7.4%

마을명
Text

Distinct317
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T06:10:54.252810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3560831
Min length2

Characters and Unicode

Total characters1131
Distinct characters166
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

Unique302 ?
Unique (%)89.6%

Sample

1st row오관1리
2nd row오관2리
3rd row오관3리
4th row오관4리
5th row오관5리
ValueCountFrequency (%)
신촌 5
 
1.5%
신곡 3
 
0.9%
내동 3
 
0.9%
하리 3
 
0.9%
동막 3
 
0.9%
석산 2
 
0.6%
내남 2
 
0.6%
중리 2
 
0.6%
노동 2
 
0.6%
용두 2
 
0.6%
Other values (302) 310
92.0%
2024-01-10T06:10:54.979549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
271
24.0%
리 94
 
8.3%
동 44
 
3.9%
산 28
 
2.5%
1 28
 
2.5%
2 24
 
2.1%
신 24
 
2.1%
상 19
 
1.7%
곡 17
 
1.5%
대 17
 
1.5%
Other values (156) 565
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 782
69.1%
Space Separator 271
 
24.0%
Decimal Number 78
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 94
 
12.0%
동 44
 
5.6%
산 28
 
3.6%
신 24
 
3.1%
상 19
 
2.4%
곡 17
 
2.2%
대 17
 
2.2%
원 17
 
2.2%
촌 17
 
2.2%
오 17
 
2.2%
Other values (145) 488
62.4%
Decimal Number
ValueCountFrequency (%)
1 28
35.9%
2 24
30.8%
3 10
 
12.8%
4 6
 
7.7%
5 3
 
3.8%
6 3
 
3.8%
9 1
 
1.3%
8 1
 
1.3%
7 1
 
1.3%
0 1
 
1.3%
Space Separator
ValueCountFrequency (%)
271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 782
69.1%
Common 349
30.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 94
 
12.0%
동 44
 
5.6%
산 28
 
3.6%
신 24
 
3.1%
상 19
 
2.4%
곡 17
 
2.2%
대 17
 
2.2%
원 17
 
2.2%
촌 17
 
2.2%
오 17
 
2.2%
Other values (145) 488
62.4%
Common
ValueCountFrequency (%)
271
77.7%
1 28
 
8.0%
2 24
 
6.9%
3 10
 
2.9%
4 6
 
1.7%
5 3
 
0.9%
6 3
 
0.9%
9 1
 
0.3%
8 1
 
0.3%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 782
69.1%
ASCII 349
30.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
271
77.7%
1 28
 
8.0%
2 24
 
6.9%
3 10
 
2.9%
4 6
 
1.7%
5 3
 
0.9%
6 3
 
0.9%
9 1
 
0.3%
8 1
 
0.3%
7 1
 
0.3%
Hangul
ValueCountFrequency (%)
리 94
 
12.0%
동 44
 
5.6%
산 28
 
3.6%
신 24
 
3.1%
상 19
 
2.4%
곡 17
 
2.2%
대 17
 
2.2%
원 17
 
2.2%
촌 17
 
2.2%
오 17
 
2.2%
Other values (145) 488
62.4%

소재지도로명주소
Text

Distinct336
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T06:10:55.239492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length24.035608
Min length19

Characters and Unicode

Total characters8100
Distinct characters133
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

Unique335 ?
Unique (%)99.4%

Sample

1st row충청남도 홍성군 홍성읍 조양로103번길 27-6
2nd row충청남도 홍성군 홍성읍 조양로143번길 35-12
3rd row충청남도 홍성군 홍성읍 아문길 60, 2층
4th row충청남도 홍성군 홍성읍 조양로10번길 76
5th row충청남도 홍성군 홍성읍 조양로33번길 20-18
ValueCountFrequency (%)
충청남도 337
19.9%
홍성군 337
19.9%
홍성읍 47
 
2.8%
광천읍 41
 
2.4%
홍동면 33
 
1.9%
장곡면 32
 
1.9%
서부면 29
 
1.7%
갈산면 29
 
1.7%
홍북읍 27
 
1.6%
금마면 26
 
1.5%
Other values (529) 758
44.7%
2024-01-10T06:10:55.605275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1364
16.8%
홍 513
 
6.3%
성 427
 
5.3%
남 416
 
5.1%
충 375
 
4.6%
청 339
 
4.2%
도 339
 
4.2%
군 337
 
4.2%
1 334
 
4.1%
길 319
 
3.9%
Other values (123) 3337
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5031
62.1%
Decimal Number 1593
 
19.7%
Space Separator 1364
 
16.8%
Dash Punctuation 97
 
1.2%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 513
 
10.2%
성 427
 
8.5%
남 416
 
8.3%
충 375
 
7.5%
청 339
 
6.7%
도 339
 
6.7%
군 337
 
6.7%
길 319
 
6.3%
로 237
 
4.7%
면 225
 
4.5%
Other values (108) 1504
29.9%
Decimal Number
ValueCountFrequency (%)
1 334
21.0%
2 189
11.9%
3 179
11.2%
4 154
9.7%
5 153
9.6%
7 142
8.9%
6 134
8.4%
9 106
 
6.7%
0 103
 
6.5%
8 99
 
6.2%
Space Separator
ValueCountFrequency (%)
1364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5031
62.1%
Common 3069
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 513
 
10.2%
성 427
 
8.5%
남 416
 
8.3%
충 375
 
7.5%
청 339
 
6.7%
도 339
 
6.7%
군 337
 
6.7%
길 319
 
6.3%
로 237
 
4.7%
면 225
 
4.5%
Other values (108) 1504
29.9%
Common
ValueCountFrequency (%)
1364
44.4%
1 334
 
10.9%
2 189
 
6.2%
3 179
 
5.8%
4 154
 
5.0%
5 153
 
5.0%
7 142
 
4.6%
6 134
 
4.4%
9 106
 
3.5%
0 103
 
3.4%
Other values (5) 211
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5031
62.1%
ASCII 3069
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1364
44.4%
1 334
 
10.9%
2 189
 
6.2%
3 179
 
5.8%
4 154
 
5.0%
5 153
 
5.0%
7 142
 
4.6%
6 134
 
4.4%
9 106
 
3.5%
0 103
 
3.4%
Other values (5) 211
 
6.9%
Hangul
ValueCountFrequency (%)
홍 513
 
10.2%
성 427
 
8.5%
남 416
 
8.3%
충 375
 
7.5%
청 339
 
6.7%
도 339
 
6.7%
군 337
 
6.7%
길 319
 
6.3%
로 237
 
4.7%
면 225
 
4.5%
Other values (108) 1504
29.9%

건축년도
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)10.9%
Missing6
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean2000.2115
Minimum1970
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-01-10T06:10:55.733502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1992.5
Q11997
median2000
Q32003
95-th percentile2011
Maximum2019
Range49
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.2738506
Coefficient of variation (CV)0.0031365936
Kurtosis4.4997787
Mean2000.2115
Median Absolute Deviation (MAD)3
Skewness-0.95802628
Sum662070
Variance39.361201
MonotonicityNot monotonic
2024-01-10T06:10:55.849008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1999 46
13.6%
2002 41
12.2%
2001 30
 
8.9%
1997 28
 
8.3%
1998 27
 
8.0%
2003 18
 
5.3%
2000 16
 
4.7%
1996 16
 
4.7%
1995 11
 
3.3%
2004 10
 
3.0%
Other values (26) 88
26.1%
ValueCountFrequency (%)
1970 1
 
0.3%
1972 1
 
0.3%
1975 1
 
0.3%
1978 2
0.6%
1979 1
 
0.3%
1980 1
 
0.3%
1981 1
 
0.3%
1983 1
 
0.3%
1985 1
 
0.3%
1990 3
0.9%
ValueCountFrequency (%)
2019 1
 
0.3%
2015 1
 
0.3%
2014 2
 
0.6%
2013 2
 
0.6%
2012 8
2.4%
2011 4
1.2%
2010 8
2.4%
2009 7
2.1%
2008 7
2.1%
2007 7
2.1%

건축면적(㎡)
Real number (ℝ)

MISSING 

Distinct287
Distinct (%)86.7%
Missing6
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean119.74817
Minimum32.5
Maximum511.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-01-10T06:10:55.990268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.5
5-th percentile82.5
Q190.485
median100.48
Q3135.67
95-th percentile207.54
Maximum511.75
Range479.25
Interquartile range (IQR)45.185

Descriptive statistics

Standard deviation51.103216
Coefficient of variation (CV)0.42675571
Kurtosis16.912534
Mean119.74817
Median Absolute Deviation (MAD)14.33
Skewness3.2326392
Sum39636.645
Variance2611.5387
MonotonicityNot monotonic
2024-01-10T06:10:56.139179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.24 6
 
1.8%
88.0 4
 
1.2%
96.23 4
 
1.2%
94.66 4
 
1.2%
94.5 3
 
0.9%
84.0 3
 
0.9%
96.39 3
 
0.9%
85.0 3
 
0.9%
101.4 3
 
0.9%
84.36 2
 
0.6%
Other values (277) 296
87.8%
(Missing) 6
 
1.8%
ValueCountFrequency (%)
32.5 1
0.3%
59.85 1
0.3%
66.0 1
0.3%
69.0 1
0.3%
72.36 1
0.3%
73.32 1
0.3%
77.37 1
0.3%
78.42 1
0.3%
79.14 2
0.6%
79.74 2
0.6%
ValueCountFrequency (%)
511.75 1
0.3%
460.8 1
0.3%
326.48 1
0.3%
303.4 1
0.3%
294.14 1
0.3%
276.0 1
0.3%
268.86 1
0.3%
247.23 1
0.3%
229.72 1
0.3%
222.25 1
0.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2024-01-10T06:10:56.252617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:56.345182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:10:53.451622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:53.309970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:53.524052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:10:53.384798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:10:56.420265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면건축년도건축면적(㎡)
읍면1.0000.2570.274
건축년도0.2571.0000.673
건축면적(㎡)0.2740.6731.000
2024-01-10T06:10:56.512983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축년도건축면적(㎡)읍면
건축년도1.0000.0900.109
건축면적(㎡)0.0901.0000.127
읍면0.1090.1271.000

Missing values

2024-01-10T06:10:53.613582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:10:53.728279image/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.
2024-01-10T06:10:53.823555image/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

읍면마을명소재지도로명주소건축년도건축면적(㎡)데이터기준일자
0홍성읍오관1리충청남도 홍성군 홍성읍 조양로103번길 27-62014169.862021-08-31
1홍성읍오관2리충청남도 홍성군 홍성읍 조양로143번길 35-122007128.522021-08-31
2홍성읍오관3리충청남도 홍성군 홍성읍 아문길 60, 2층198080.02021-08-31
3홍성읍오관4리충청남도 홍성군 홍성읍 조양로10번길 761997198.02021-08-31
4홍성읍오관5리충청남도 홍성군 홍성읍 조양로33번길 20-182013121.82021-08-31
5홍성읍오관6리충청남도 홍성군 홍성읍 조양로75번길 26-32002210.62021-08-31
6홍성읍오관7리충청남도 홍성군 홍성읍 충절로 1053번길 301990212.962021-08-31
7홍성읍오관8리충청남도 홍성군 홍성읍 충절로 1032번길 34-51994100.382021-08-31
8홍성읍오관9리충청남도 홍성군 홍성읍 충절로 1053번길 301990212.962021-08-31
9홍성읍오관10리충청남도 홍성군 홍성읍 충절로 1053번길 501994214.342021-08-31
읍면마을명소재지도로명주소건축년도건축면적(㎡)데이터기준일자
327구항면발현충청남도 홍성군 구항면 구성남로912번길 452001138.872021-08-31
328구항면지석충청남도 홍성군 구항면 거북로 2022002208.312021-08-31
329구항면묵동충청남도 홍성군 구항면 거북로8번길 5-14200384.852021-08-31
330구항면대정충청남도 홍성군 구항면 구성남길171번길 72002105.322021-08-31
331구항면신곡충청남도 홍성군 구항면 충서로641번길 14-32008133.152021-08-31
332구항면척괴충청남도 홍성군 구항면 충서로726번길 1422001116.162021-08-31
333구항면청광충청남도 홍성군 구항면 충서로877번길 301997186.02021-08-31
334구항면소반충청남도 홍성군 구항면 충서로872번길 43-171999152.242021-08-31
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