Overview

Dataset statistics

Number of variables14
Number of observations239
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.7 KiB
Average record size in memory118.6 B

Variable types

Numeric6
Text4
Categorical2
DateTime1
Boolean1

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

데이터기준일 has constant value ""Constant
건축면적 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 건축면적High correlation
동수-층수 is highly imbalanced (50.8%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:35:18.507877
Analysis finished2024-01-09 21:35:22.224810
Duration3.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct239
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120
Minimum1
Maximum239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:22.287305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.9
Q160.5
median120
Q3179.5
95-th percentile227.1
Maximum239
Range238
Interquartile range (IQR)119

Descriptive statistics

Standard deviation69.137544
Coefficient of variation (CV)0.5761462
Kurtosis-1.2
Mean120
Median Absolute Deviation (MAD)60
Skewness0
Sum28680
Variance4780
MonotonicityStrictly increasing
2024-01-10T06:35:22.398874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
2 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
155 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
Other values (229) 229
95.8%
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 (%)
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%
233 1
0.4%
232 1
0.4%
231 1
0.4%
230 1
0.4%

마을회관 이름
Text

Distinct234
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-10T06:35:22.601779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length10.48954
Min length5

Characters and Unicode

Total characters2507
Distinct characters181
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

Unique229 ?
Unique (%)95.8%

Sample

1st row수부1리 마을회관 (신기 경로당)
2nd row수부2리 마을회관
3rd row수부3리 마을회관 (부당 경로당)
4th row성동1리 마을회관 (내성 경로당)
5th row성동2리 노인회관
ValueCountFrequency (%)
마을회관 135
32.9%
경로당 11
 
2.7%
노인회관 5
 
1.2%
도흥리마을회관 2
 
0.5%
원산1리(선촌 2
 
0.5%
관당2리 2
 
0.5%
관산리 2
 
0.5%
독산2리 2
 
0.5%
대천2리 2
 
0.5%
두룡1리 2
 
0.5%
Other values (240) 245
59.8%
2024-01-10T06:35:22.973445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 243
 
9.7%
회 236
 
9.4%
마 226
 
9.0%
을 223
 
8.9%
리 187
 
7.5%
172
 
6.9%
) 92
 
3.7%
( 92
 
3.7%
2 82
 
3.3%
1 69
 
2.8%
Other values (171) 885
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1934
77.1%
Decimal Number 214
 
8.5%
Space Separator 172
 
6.9%
Close Punctuation 92
 
3.7%
Open Punctuation 92
 
3.7%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 243
 
12.6%
회 236
 
12.2%
마 226
 
11.7%
을 223
 
11.5%
리 187
 
9.7%
통 35
 
1.8%
대 32
 
1.7%
성 29
 
1.5%
당 28
 
1.4%
신 25
 
1.3%
Other values (156) 670
34.6%
Decimal Number
ValueCountFrequency (%)
2 82
38.3%
1 69
32.2%
3 29
 
13.6%
4 11
 
5.1%
5 10
 
4.7%
7 4
 
1.9%
8 3
 
1.4%
6 3
 
1.4%
9 2
 
0.9%
0 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
172
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1934
77.1%
Common 573
 
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 243
 
12.6%
회 236
 
12.2%
마 226
 
11.7%
을 223
 
11.5%
리 187
 
9.7%
통 35
 
1.8%
대 32
 
1.7%
성 29
 
1.5%
당 28
 
1.4%
신 25
 
1.3%
Other values (156) 670
34.6%
Common
ValueCountFrequency (%)
172
30.0%
) 92
16.1%
( 92
16.1%
2 82
14.3%
1 69
12.0%
3 29
 
5.1%
4 11
 
1.9%
5 10
 
1.7%
7 4
 
0.7%
8 3
 
0.5%
Other values (5) 9
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1934
77.1%
ASCII 573
 
22.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 243
 
12.6%
회 236
 
12.2%
마 226
 
11.7%
을 223
 
11.5%
리 187
 
9.7%
통 35
 
1.8%
대 32
 
1.7%
성 29
 
1.5%
당 28
 
1.4%
신 25
 
1.3%
Other values (156) 670
34.6%
ASCII
ValueCountFrequency (%)
172
30.0%
) 92
16.1%
( 92
16.1%
2 82
14.3%
1 69
12.0%
3 29
 
5.1%
4 11
 
1.9%
5 10
 
1.7%
7 4
 
0.7%
8 3
 
0.5%
Other values (5) 9
 
1.6%

도로명 주소
Text

Distinct237
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2024-01-10T06:35:23.261622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.37395
Min length14

Characters and Unicode

Total characters4849
Distinct characters217
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

Unique236 ?
Unique (%)99.2%

Sample

1st row충청남도 보령시 웅천읍 만수로 454-7
2nd row충청남도 보령시 웅천읍 수안1길 47-11
3rd row충청남도 보령시 웅천읍 부당길 27
4th row충청남도 보령시 웅천읍 내성1길 42
5th row충청남도 보령시 웅천읍 성동큰길 239
ValueCountFrequency (%)
충청남도 238
20.7%
보령시 237
20.6%
오천면 28
 
2.4%
천북면 26
 
2.3%
미산면 21
 
1.8%
주교면 20
 
1.7%
웅천읍 19
 
1.7%
청소면 19
 
1.7%
남포면 17
 
1.5%
청라면 16
 
1.4%
Other values (393) 509
44.3%
2024-01-10T06:35:23.647768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
914
18.8%
청 278
 
5.7%
도 261
 
5.4%
남 259
 
5.3%
시 244
 
5.0%
보 243
 
5.0%
충 242
 
5.0%
령 240
 
4.9%
길 194
 
4.0%
면 183
 
3.8%
Other values (207) 1791
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3150
65.0%
Space Separator 914
 
18.8%
Decimal Number 710
 
14.6%
Dash Punctuation 75
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 278
 
8.8%
도 261
 
8.3%
남 259
 
8.2%
시 244
 
7.7%
보 243
 
7.7%
충 242
 
7.7%
령 240
 
7.6%
길 194
 
6.2%
면 183
 
5.8%
천 81
 
2.6%
Other values (195) 925
29.4%
Decimal Number
ValueCountFrequency (%)
1 147
20.7%
2 106
14.9%
4 77
10.8%
3 76
10.7%
9 63
8.9%
5 58
 
8.2%
6 57
 
8.0%
7 49
 
6.9%
8 47
 
6.6%
0 30
 
4.2%
Space Separator
ValueCountFrequency (%)
914
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3150
65.0%
Common 1699
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 278
 
8.8%
도 261
 
8.3%
남 259
 
8.2%
시 244
 
7.7%
보 243
 
7.7%
충 242
 
7.7%
령 240
 
7.6%
길 194
 
6.2%
면 183
 
5.8%
천 81
 
2.6%
Other values (195) 925
29.4%
Common
ValueCountFrequency (%)
914
53.8%
1 147
 
8.7%
2 106
 
6.2%
4 77
 
4.5%
3 76
 
4.5%
- 75
 
4.4%
9 63
 
3.7%
5 58
 
3.4%
6 57
 
3.4%
7 49
 
2.9%
Other values (2) 77
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3150
65.0%
ASCII 1699
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
914
53.8%
1 147
 
8.7%
2 106
 
6.2%
4 77
 
4.5%
3 76
 
4.5%
- 75
 
4.4%
9 63
 
3.7%
5 58
 
3.4%
6 57
 
3.4%
7 49
 
2.9%
Other values (2) 77
 
4.5%
Hangul
ValueCountFrequency (%)
청 278
 
8.8%
도 261
 
8.3%
남 259
 
8.2%
시 244
 
7.7%
보 243
 
7.7%
충 242
 
7.7%
령 240
 
7.6%
길 194
 
6.2%
면 183
 
5.8%
천 81
 
2.6%
Other values (195) 925
29.4%

지번 주소
Text

Distinct238
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-10T06:35:23.960830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.112971
Min length15

Characters and Unicode

Total characters5046
Distinct characters115
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

Unique237 ?
Unique (%)99.2%

Sample

1st row충청남도 보령시 웅천읍 수부리 878-2
2nd row충청남도 보령시 웅천읍 수부리 805-2
3rd row충청남도 보령시 웅천읍 수부리 633
4th row충청남도 보령시 웅천읍 성동리 199-1
5th row충청남도 보령시 웅천읍 성동리 782-1
ValueCountFrequency (%)
보령시 239
20.6%
충청남도 238
20.5%
오천면 28
 
2.4%
천북면 26
 
2.2%
미산면 21
 
1.8%
청소면 20
 
1.7%
주교면 19
 
1.6%
웅천읍 19
 
1.6%
남포면 18
 
1.6%
청라면 17
 
1.5%
Other values (337) 516
44.4%
2024-01-10T06:35:24.378389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
922
18.3%
청 276
 
5.5%
남 260
 
5.2%
도 258
 
5.1%
시 244
 
4.8%
보 242
 
4.8%
령 240
 
4.8%
충 239
 
4.7%
리 204
 
4.0%
- 189
 
3.7%
Other values (105) 1972
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3018
59.8%
Space Separator 922
 
18.3%
Decimal Number 917
 
18.2%
Dash Punctuation 189
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 276
 
9.1%
남 260
 
8.6%
도 258
 
8.5%
시 244
 
8.1%
보 242
 
8.0%
령 240
 
8.0%
충 239
 
7.9%
리 204
 
6.8%
면 185
 
6.1%
천 91
 
3.0%
Other values (93) 779
25.8%
Decimal Number
ValueCountFrequency (%)
1 159
17.3%
2 133
14.5%
3 121
13.2%
5 100
10.9%
4 92
10.0%
6 73
8.0%
7 70
7.6%
8 66
7.2%
0 52
 
5.7%
9 51
 
5.6%
Space Separator
ValueCountFrequency (%)
922
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3018
59.8%
Common 2028
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 276
 
9.1%
남 260
 
8.6%
도 258
 
8.5%
시 244
 
8.1%
보 242
 
8.0%
령 240
 
8.0%
충 239
 
7.9%
리 204
 
6.8%
면 185
 
6.1%
천 91
 
3.0%
Other values (93) 779
25.8%
Common
ValueCountFrequency (%)
922
45.5%
- 189
 
9.3%
1 159
 
7.8%
2 133
 
6.6%
3 121
 
6.0%
5 100
 
4.9%
4 92
 
4.5%
6 73
 
3.6%
7 70
 
3.5%
8 66
 
3.3%
Other values (2) 103
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3018
59.8%
ASCII 2028
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
922
45.5%
- 189
 
9.3%
1 159
 
7.8%
2 133
 
6.6%
3 121
 
6.0%
5 100
 
4.9%
4 92
 
4.5%
6 73
 
3.6%
7 70
 
3.5%
8 66
 
3.3%
Other values (2) 103
 
5.1%
Hangul
ValueCountFrequency (%)
청 276
 
9.1%
남 260
 
8.6%
도 258
 
8.5%
시 244
 
8.1%
보 242
 
8.0%
령 240
 
8.0%
충 239
 
7.9%
리 204
 
6.8%
면 185
 
6.1%
천 91
 
3.0%
Other values (93) 779
25.8%

위도
Real number (ℝ)

Distinct237
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean36.351986
Minimum36.180302
Maximum36.509583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:24.492471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.180302
5-th percentile36.199953
Q136.281962
median36.359444
Q336.420214
95-th percentile36.490914
Maximum36.509583
Range0.32928103
Interquartile range (IQR)0.13825139

Descriptive statistics

Standard deviation0.088334766
Coefficient of variation (CV)0.0024299846
Kurtosis-0.91802421
Mean36.351986
Median Absolute Deviation (MAD)0.064798405
Skewness-0.19378472
Sum8651.7726
Variance0.0078030308
MonotonicityNot monotonic
2024-01-10T06:35:24.598763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.34134813 2
 
0.8%
36.26991105 1
 
0.4%
36.21070031 1
 
0.4%
36.27997399 1
 
0.4%
36.29580099 1
 
0.4%
36.26582104 1
 
0.4%
36.25719558 1
 
0.4%
36.26305901 1
 
0.4%
36.1973445 1
 
0.4%
36.19411091 1
 
0.4%
Other values (227) 227
95.0%
ValueCountFrequency (%)
36.18030238 1
0.4%
36.18107225 1
0.4%
36.18765426 1
0.4%
36.18802843 1
0.4%
36.19055545 1
0.4%
36.19293624 1
0.4%
36.19381173 1
0.4%
36.19411091 1
0.4%
36.1965442 1
0.4%
36.19720799 1
0.4%
ValueCountFrequency (%)
36.50958341 1
0.4%
36.50934108 1
0.4%
36.50877872 1
0.4%
36.50273439 1
0.4%
36.50221255 1
0.4%
36.50182795 1
0.4%
36.49563876 1
0.4%
36.49544219 1
0.4%
36.49439519 1
0.4%
36.4930368 1
0.4%

경도
Real number (ℝ)

Distinct237
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean126.58044
Minimum126.08038
Maximum126.7293
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:24.706178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.08038
5-th percentile126.43511
Q1126.54927
median126.58819
Q3126.6224
95-th percentile126.68393
Maximum126.7293
Range0.64892
Interquartile range (IQR)0.0731296

Descriptive statistics

Standard deviation0.078891125
Coefficient of variation (CV)0.00062324894
Kurtosis7.6988271
Mean126.58044
Median Absolute Deviation (MAD)0.0376454
Skewness-1.8103523
Sum30126.145
Variance0.0062238096
MonotonicityNot monotonic
2024-01-10T06:35:24.812831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6544937 2
 
0.8%
126.6255533 1
 
0.4%
126.6794289 1
 
0.4%
126.5636206 1
 
0.4%
126.5642607 1
 
0.4%
126.5665878 1
 
0.4%
126.561908 1
 
0.4%
126.5493995 1
 
0.4%
126.6367575 1
 
0.4%
126.630838 1
 
0.4%
Other values (227) 227
95.0%
ValueCountFrequency (%)
126.080382 1
0.4%
126.2644392 1
0.4%
126.3376485 1
0.4%
126.3382884 1
0.4%
126.356342 1
0.4%
126.3565252 1
0.4%
126.367607 1
0.4%
126.4184116 1
0.4%
126.4320969 1
0.4%
126.432192 1
0.4%
ValueCountFrequency (%)
126.729302 1
0.4%
126.7142477 1
0.4%
126.7106164 1
0.4%
126.7028811 1
0.4%
126.7006607 1
0.4%
126.6997639 1
0.4%
126.6939929 1
0.4%
126.6939459 1
0.4%
126.6937024 1
0.4%
126.6933382 1
0.4%

동수-층수
Categorical

IMBALANCE 

Distinct11
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1동-지상1
142 
1동-지상2
61 
2동-지상1
15 
2동-지상2
 
11
3동-지상1
 
4
Other values (6)
 
6

Length

Max length11
Median length6
Mean length6.0502092
Min length4

Unique

Unique6 ?
Unique (%)2.5%

Sample

1st row1동-지상2
2nd row1동-지상1
3rd row1동-지상1
4th row1동-지상1
5th row1동-지상1

Common Values

ValueCountFrequency (%)
1동-지상1 142
59.4%
1동-지상2 61
25.5%
2동-지상1 15
 
6.3%
2동-지상2 11
 
4.6%
3동-지상1 4
 
1.7%
1동-지상2층 1
 
0.4%
1동-지상1+지하1 1
 
0.4%
1동-지상1+지하1+ 1
 
0.4%
1동-지상2+지하1 1
 
0.4%
1동-지상3 1
 
0.4%

Length

2024-01-10T06:35:24.950114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1동-지상1 142
59.4%
1동-지상2 61
25.5%
2동-지상1 15
 
6.3%
2동-지상2 11
 
4.6%
3동-지상1 4
 
1.7%
1동-지상1+지하1 2
 
0.8%
1동-지상2층 1
 
0.4%
1동-지상2+지하1 1
 
0.4%
1동-지상3 1
 
0.4%
na 1
 
0.4%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct229
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.03965
Minimum0
Maximum538.89
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:25.087987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.796
Q188.825
median105.3
Q3131.21
95-th percentile227.613
Maximum538.89
Range538.89
Interquartile range (IQR)42.385

Descriptive statistics

Standard deviation57.748893
Coefficient of variation (CV)0.48923301
Kurtosis14.772825
Mean118.03965
Median Absolute Deviation (MAD)18.76
Skewness2.9635624
Sum28211.476
Variance3334.9346
MonotonicityNot monotonic
2024-01-10T06:35:25.232473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104.39 4
 
1.7%
111.56 3
 
1.3%
101.61 2
 
0.8%
99.0 2
 
0.8%
111.4 2
 
0.8%
86.598 2
 
0.8%
97.86 2
 
0.8%
197.83 1
 
0.4%
84.44 1
 
0.4%
132.5 1
 
0.4%
Other values (219) 219
91.6%
ValueCountFrequency (%)
0.0 1
0.4%
32.4 1
0.4%
35.03 1
0.4%
39.6 1
0.4%
43.08 1
0.4%
44.64 1
0.4%
45.36 1
0.4%
47.31 1
0.4%
48.38 1
0.4%
53.6 1
0.4%
ValueCountFrequency (%)
538.89 1
0.4%
406.92 1
0.4%
327.68 1
0.4%
309.6 1
0.4%
280.48 1
0.4%
265.54 1
0.4%
261.6 1
0.4%
257.18 1
0.4%
249.18 1
0.4%
237.84 1
0.4%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct234
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.94674
Minimum32.4
Maximum584.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:25.340997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.4
5-th percentile65.562
Q191.815
median124.5
Q3167.175
95-th percentile320.612
Maximum584.25
Range551.85
Interquartile range (IQR)75.36

Descriptive statistics

Standard deviation78.913741
Coefficient of variation (CV)0.54821485
Kurtosis5.9794499
Mean143.94674
Median Absolute Deviation (MAD)35.5
Skewness2.0749798
Sum34403.271
Variance6227.3785
MonotonicityNot monotonic
2024-01-10T06:35:25.441175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.63 4
 
1.7%
86.598 2
 
0.8%
144.43 2
 
0.8%
105.42 1
 
0.4%
124.5 1
 
0.4%
140.22 1
 
0.4%
74.88 1
 
0.4%
90.42 1
 
0.4%
95.2 1
 
0.4%
169.16 1
 
0.4%
Other values (224) 224
93.7%
ValueCountFrequency (%)
32.4 1
0.4%
35.03 1
0.4%
39.6 1
0.4%
44.64 1
0.4%
45.36 1
0.4%
47.31 1
0.4%
53.6 1
0.4%
57.67 1
0.4%
59.04 1
0.4%
62.93 1
0.4%
ValueCountFrequency (%)
584.25 1
0.4%
484.3 1
0.4%
405.92 1
0.4%
402.72 1
0.4%
366.7 1
0.4%
364.98 1
0.4%
361.88 1
0.4%
354.81 1
0.4%
340.37 1
0.4%
340.14 1
0.4%

사용승인일
Date

Distinct222
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1970-07-25 00:00:00
Maximum2022-01-01 00:00:00
2024-01-10T06:35:25.809398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:25.917492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소유자
Text

Distinct223
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-10T06:35:26.118947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length8.5481172
Min length3

Characters and Unicode

Total characters2043
Distinct characters166
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

Unique212 ?
Unique (%)88.7%

Sample

1st row수부1리 마을회
2nd row수부2리마을회
3rd row수부3리마을회
4th row성동1리마을회
5th row성동2,3리대동회
ValueCountFrequency (%)
마을회 13
 
5.0%
보령시 7
 
2.7%
주교2리 3
 
1.2%
삽시1리마을회 2
 
0.8%
미산면봉성리마을회 2
 
0.8%
성주3리마을회 2
 
0.8%
청소면성연2리음지마을 2
 
0.8%
장고도마을회 2
 
0.8%
웅천읍대창5리마을회 2
 
0.8%
호도마을회 2
 
0.8%
Other values (218) 223
85.8%
2024-01-10T06:35:26.421128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 224
 
11.0%
마 206
 
10.1%
을 204
 
10.0%
191
 
9.3%
리 177
 
8.7%
2 66
 
3.2%
1 61
 
3.0%
대 35
 
1.7%
동 31
 
1.5%
3 30
 
1.5%
Other values (156) 818
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1656
81.1%
Space Separator 191
 
9.3%
Decimal Number 186
 
9.1%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Other Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 224
 
13.5%
마 206
 
12.4%
을 204
 
12.3%
리 177
 
10.7%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.8%
면 27
 
1.6%
주 25
 
1.5%
통 24
 
1.4%
Other values (141) 674
40.7%
Decimal Number
ValueCountFrequency (%)
2 66
35.5%
1 61
32.8%
3 30
16.1%
4 13
 
7.0%
5 7
 
3.8%
7 4
 
2.2%
6 2
 
1.1%
0 1
 
0.5%
9 1
 
0.5%
8 1
 
0.5%
Space Separator
ValueCountFrequency (%)
191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1656
81.1%
Common 387
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 224
 
13.5%
마 206
 
12.4%
을 204
 
12.3%
리 177
 
10.7%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.8%
면 27
 
1.6%
주 25
 
1.5%
통 24
 
1.4%
Other values (141) 674
40.7%
Common
ValueCountFrequency (%)
191
49.4%
2 66
 
17.1%
1 61
 
15.8%
3 30
 
7.8%
4 13
 
3.4%
5 7
 
1.8%
7 4
 
1.0%
) 3
 
0.8%
( 3
 
0.8%
, 3
 
0.8%
Other values (5) 6
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1656
81.1%
ASCII 387
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 224
 
13.5%
마 206
 
12.4%
을 204
 
12.3%
리 177
 
10.7%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.8%
면 27
 
1.6%
주 25
 
1.5%
통 24
 
1.4%
Other values (141) 674
40.7%
ASCII
ValueCountFrequency (%)
191
49.4%
2 66
 
17.1%
1 61
 
15.8%
3 30
 
7.8%
4 13
 
3.4%
5 7
 
1.8%
7 4
 
1.0%
) 3
 
0.8%
( 3
 
0.8%
, 3
 
0.8%
Other values (5) 6
 
1.6%

경로당겸용여부
Boolean

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size371.0 B
True
201 
False
38 
ValueCountFrequency (%)
True 201
84.1%
False 38
 
15.9%
2024-01-10T06:35:26.508936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

건축년도
Real number (ℝ)

Distinct33
Distinct (%)13.9%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean2002.5798
Minimum1970
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-10T06:35:26.588067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1994
Q11998.25
median2001.5
Q32008
95-th percentile2012
Maximum2022
Range52
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation6.7897861
Coefficient of variation (CV)0.0033905196
Kurtosis3.4999332
Mean2002.5798
Median Absolute Deviation (MAD)3.5
Skewness-0.71086053
Sum476614
Variance46.101195
MonotonicityNot monotonic
2024-01-10T06:35:26.718034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1999 22
 
9.2%
1998 21
 
8.8%
2001 20
 
8.4%
2000 17
 
7.1%
1997 16
 
6.7%
2009 13
 
5.4%
2003 13
 
5.4%
2002 11
 
4.6%
2011 10
 
4.2%
2005 10
 
4.2%
Other values (23) 85
35.6%
ValueCountFrequency (%)
1970 1
 
0.4%
1974 1
 
0.4%
1976 1
 
0.4%
1985 1
 
0.4%
1987 1
 
0.4%
1990 1
 
0.4%
1992 2
 
0.8%
1993 3
1.3%
1994 2
 
0.8%
1995 5
2.1%
ValueCountFrequency (%)
2022 1
 
0.4%
2020 1
 
0.4%
2019 1
 
0.4%
2017 1
 
0.4%
2014 2
 
0.8%
2013 5
 
2.1%
2012 8
3.3%
2011 10
4.2%
2010 10
4.2%
2009 13
5.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-04-10
239 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-10
2nd row2023-04-10
3rd row2023-04-10
4th row2023-04-10
5th row2023-04-10

Common Values

ValueCountFrequency (%)
2023-04-10 239
100.0%

Length

2024-01-10T06:35:26.846852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:26.935035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-10 239
100.0%

Interactions

2024-01-10T06:35:21.302310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.083785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.480272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.883661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.496328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.899710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.368679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.145261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.549941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.946788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.562746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.967432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.452480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.212742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.617227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.232205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.635645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.034793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.595616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.279724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.688264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.298666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.704576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.106305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.701803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.340783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.752403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.364452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.766280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.170874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.790365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.407260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:19.816896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.428833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:20.830871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:21.236383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:35:26.997019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도동수-층수건축면적연면적경로당겸용여부건축년도
연번1.0000.9200.6560.3770.0000.2050.3040.306
위도0.9201.0000.4350.2980.0000.0000.2790.119
경도0.6560.4351.0000.0000.5550.4440.2520.000
동수-층수0.3770.2980.0001.0000.3130.5160.0000.000
건축면적0.0000.0000.5550.3131.0000.9220.0000.000
연면적0.2050.0000.4440.5160.9221.0000.1160.000
경로당겸용여부0.3040.2790.2520.0000.0000.1161.0000.369
건축년도0.3060.1190.0000.0000.0000.0000.3691.000
2024-01-10T06:35:27.111333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경로당겸용여부동수-층수
경로당겸용여부1.0000.000
동수-층수0.0001.000
2024-01-10T06:35:27.183735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축면적연면적건축년도동수-층수경로당겸용여부
연번1.000-0.3310.426-0.0690.045-0.0080.1220.232
위도-0.3311.000-0.3730.048-0.011-0.0530.0950.210
경도0.426-0.3731.000-0.086-0.0140.0030.0000.247
건축면적-0.0690.048-0.0861.0000.806-0.0180.1470.000
연면적0.045-0.011-0.0140.8061.000-0.0710.2640.114
건축년도-0.008-0.0530.003-0.018-0.0711.0000.0000.286
동수-층수0.1220.0950.0000.1470.2640.0001.0000.000
경로당겸용여부0.2320.2100.2470.0000.1140.2860.0001.000

Missing values

2024-01-10T06:35:21.925206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:35:22.069277image/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.
2024-01-10T06:35:22.174753image/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

연번마을회관 이름도로명 주소지번 주소위도경도동수-층수건축면적연면적사용승인일소유자경로당겸용여부건축년도데이터기준일
01수부1리 마을회관 (신기 경로당)충청남도 보령시 웅천읍 만수로 454-7충청남도 보령시 웅천읍 수부리 878-236.269911126.6255531동-지상270.545105.421999-01-15수부1리 마을회Y19992023-04-10
12수부2리 마을회관충청남도 보령시 웅천읍 수안1길 47-11충청남도 보령시 웅천읍 수부리 805-236.259123126.6160321동-지상178.7978.792009-09-25수부2리마을회N20092023-04-10
23수부3리 마을회관 (부당 경로당)충청남도 보령시 웅천읍 부당길 27충청남도 보령시 웅천읍 수부리 63336.264756126.6179481동-지상191.2683.71998-10-08수부3리마을회Y19982023-04-10
34성동1리 마을회관 (내성 경로당)충청남도 보령시 웅천읍 내성1길 42충청남도 보령시 웅천읍 성동리 199-136.247907126.6242051동-지상1153.44203.932004-12-28성동1리마을회Y20042023-04-10
45성동2리 노인회관충청남도 보령시 웅천읍 성동큰길 239충청남도 보령시 웅천읍 성동리 782-136.250928126.6160821동-지상1108.86184.621993-04-20성동2,3리대동회Y19932023-04-10
56성동3리 노인회관충청남도 보령시 웅천읍 외성1길 2충청남도 보령시 웅천읍 성동리 651-136.24901126.6125151동-지상135.0335.032020-09-23성동3리 노인회N20202023-04-10
67대창5리 마을회관(한내마을회관)충청남도 보령시 웅천읍 한내1길 98충청남도 보령시 웅천읍 대창리 48336.23585126.6051741동-지상197.597.52008-01-03웅천읍대창5리마을회Y20082023-04-10
78대창5리 마을회관충청남도 보령시 웅천읍 한내1길 94충청남도 보령시 웅천읍 대창리 483-236.235793126.6052761동-지상1115.37115.372008-06-24웅천읍대창5리마을회Y20082023-04-10
89대창6리 마을회관충청남도 보령시 웅천읍 방축길 95충청남도 보령시 웅천읍 대창리 453-136.233204126.6043891동-지상194.3294.322004-09-10한축마을회N20042023-04-10
910대창9리 노인회관 (웅천읍분회경로당)충청남도 보령시 웅천읍 장터8길 46충청남도 보령시 웅천읍 대창리 687-136.235725126.6000821동-지상1188.82366.71988-06-09웅천면노인회새마을지도자+보령군웅천면협의회Y19982023-04-10
연번마을회관 이름도로명 주소지번 주소위도경도동수-층수건축면적연면적사용승인일소유자경로당겸용여부건축년도데이터기준일
229230요암1통1반마을(노인)회관충청남도 보령시 서낭길 19-3충청남도 보령시 요암동 141-336.32835126.5580711동-지상188.6584.572008-05-01요암1통마을회Y20082023-04-10
230231요암1통마을(노인)회관충청남도 보령시 육굴길 141충청남도 보령시 요암동 256-336.328573126.5502632동-지상2158.06257.321993-07-14보령시Y19932023-04-10
231232요암2통마을(노인)회관충청남도 보령시 절터길 4충청남도 보령시 요암동 868-336.328113126.5425661동-지상1120.21111.571998-06-22보령시Y19982023-04-10
232233요암3통마을(노인)회관충청남도 보령시 뒷골길 21-67충청남도 보령시 요암동 504-236.320871126.5533181동-지상2140.29189.971997-12-22보령시요암3통마을대동회Y19972023-04-10
233234신흑1통마을(노인)회관충청남도 보령시 해망산길 79충청남도 보령시 신흑동 126-736.321676126.541031동-지상295.19165.761993-06-26보령시Y19932023-04-10
234235신흑2통마을회관충청남도 보령시 흑포1길 33-22충청남도 보령시 신흑동 245-136.318746126.5352921동-지상2101.61183.472010-08-31신흑2통마을회N20102023-04-10
235236신흑3통1반마을(노인)회관충청남도 보령시 달푸미길 39-5충청남도 보령시 신흑동 900-3136.320146126.5131161동-지상157.6757.672013-03-15보령시Y20132023-04-10
236237신흑4통마을(노인)회관충청남도 보령시 대천항로 142-40충청남도 보령시 신흑동 775-1336.317393126.5207621동-지상2129.98197.892010-01-18신흑4통청룡마을회Y20102023-04-10
237238신흑7통마을(노인)회관충청남도 보령시 대천항로 370충청남도 보령시 신흑동 2240-736.326609126.5061071동-지상2265.54484.32007-06-18신흑7통마을회Y20072023-04-10
238239신흑8통 마을회관충청남도 보령시 시영길 18충청남도 보령시 신흑동 911-5136.322985126.510551<NA>106.65165.511996-07-23보령시Y19962023-04-10