Overview

Dataset statistics

Number of variables14
Number of observations240
Missing cells4
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.8 KiB
Average record size in memory118.5 B

Variable types

Numeric6
Text4
Categorical1
DateTime2
Boolean1

Dataset

Description충청남도 보령시 마을회관의 시설명, 도로명 주소, 지번 주소, 위도, 경도, 동수/층수, 건축면적, 연면적, 사용승인일, 소유자, 경로다겸용여부, 건축년도에 대한 데이터를 제공합니다.
Author충청남도 보령시
URLhttps://www.data.go.kr/data/15037749/fileData.do

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 (51.2%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:06:11.287099
Analysis finished2024-04-21 01:06:16.202066
Duration4.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.6875
Minimum1
Maximum241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:16.282080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.95
Q160.75
median120.5
Q3180.25
95-th percentile229.05
Maximum241
Range240
Interquartile range (IQR)119.5

Descriptive statistics

Standard deviation69.691237
Coefficient of variation (CV)0.57745199
Kurtosis-1.1954965
Mean120.6875
Median Absolute Deviation (MAD)60
Skewness0.0083065405
Sum28965
Variance4856.8685
MonotonicityStrictly increasing
2024-04-21T10:06:16.600139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
122 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%
161 1
 
0.4%
Other values (230) 230
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 (%)
241 1
0.4%
240 1
0.4%
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%

마을회관 이름
Text

Distinct237
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-21T10:06:16.813073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length10.533333
Min length5

Characters and Unicode

Total characters2528
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

Unique234 ?
Unique (%)97.5%

Sample

1st row수부1리 마을회관 (신기 경로당)
2nd row수부2리 마을회관
3rd row수부3리 마을회관 (부당 경로당)
4th row성동1리 마을회관 (내성 경로당)
5th row성동2리 노인회관
ValueCountFrequency (%)
마을회관 137
33.2%
경로당 11
 
2.7%
노인회관 5
 
1.2%
장고도마을회관 2
 
0.5%
두룡1리 2
 
0.5%
대천2리 2
 
0.5%
독산2리 2
 
0.5%
원산1리(선촌 2
 
0.5%
대창5리 2
 
0.5%
죽청2리 2
 
0.5%
Other values (243) 246
59.6%
2024-04-21T10:06:17.147862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 244
 
9.7%
회 237
 
9.4%
마 227
 
9.0%
을 224
 
8.9%
리 189
 
7.5%
174
 
6.9%
) 94
 
3.7%
( 94
 
3.7%
2 82
 
3.2%
1 71
 
2.8%
Other values (171) 892
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1947
77.0%
Decimal Number 216
 
8.5%
Space Separator 174
 
6.9%
Close Punctuation 94
 
3.7%
Open Punctuation 94
 
3.7%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 244
 
12.5%
회 237
 
12.2%
마 227
 
11.7%
을 224
 
11.5%
리 189
 
9.7%
통 35
 
1.8%
대 32
 
1.6%
성 30
 
1.5%
당 28
 
1.4%
동 25
 
1.3%
Other values (156) 676
34.7%
Decimal Number
ValueCountFrequency (%)
2 82
38.0%
1 71
32.9%
3 29
 
13.4%
4 11
 
5.1%
5 10
 
4.6%
7 4
 
1.9%
6 3
 
1.4%
8 3
 
1.4%
9 2
 
0.9%
0 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
174
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1947
77.0%
Common 581
 
23.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 244
 
12.5%
회 237
 
12.2%
마 227
 
11.7%
을 224
 
11.5%
리 189
 
9.7%
통 35
 
1.8%
대 32
 
1.6%
성 30
 
1.5%
당 28
 
1.4%
동 25
 
1.3%
Other values (156) 676
34.7%
Common
ValueCountFrequency (%)
174
29.9%
) 94
16.2%
( 94
16.2%
2 82
14.1%
1 71
12.2%
3 29
 
5.0%
4 11
 
1.9%
5 10
 
1.7%
7 4
 
0.7%
6 3
 
0.5%
Other values (5) 9
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1947
77.0%
ASCII 581
 
23.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 244
 
12.5%
회 237
 
12.2%
마 227
 
11.7%
을 224
 
11.5%
리 189
 
9.7%
통 35
 
1.8%
대 32
 
1.6%
성 30
 
1.5%
당 28
 
1.4%
동 25
 
1.3%
Other values (156) 676
34.7%
ASCII
ValueCountFrequency (%)
174
29.9%
) 94
16.2%
( 94
16.2%
2 82
14.1%
1 71
12.2%
3 29
 
5.0%
4 11
 
1.9%
5 10
 
1.7%
7 4
 
0.7%
6 3
 
0.5%
Other values (5) 9
 
1.5%

도로명 주소
Text

Distinct238
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Memory size2.0 KiB
2024-04-21T10:06:17.443340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.393305
Min length14

Characters and Unicode

Total characters4874
Distinct characters219
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 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 239
20.7%
보령시 238
20.6%
오천면 28
 
2.4%
천북면 26
 
2.3%
미산면 21
 
1.8%
주교면 20
 
1.7%
웅천읍 20
 
1.7%
청소면 19
 
1.6%
남포면 17
 
1.5%
청라면 16
 
1.4%
Other values (393) 511
44.2%
2024-04-21T10:06:17.841434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
918
18.8%
청 279
 
5.7%
도 262
 
5.4%
남 260
 
5.3%
시 245
 
5.0%
보 244
 
5.0%
충 243
 
5.0%
령 241
 
4.9%
길 194
 
4.0%
면 183
 
3.8%
Other values (209) 1805
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3165
64.9%
Space Separator 918
 
18.8%
Decimal Number 715
 
14.7%
Dash Punctuation 76
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 279
 
8.8%
도 262
 
8.3%
남 260
 
8.2%
시 245
 
7.7%
보 244
 
7.7%
충 243
 
7.7%
령 241
 
7.6%
길 194
 
6.1%
면 183
 
5.8%
천 83
 
2.6%
Other values (197) 931
29.4%
Decimal Number
ValueCountFrequency (%)
1 147
20.6%
2 106
14.8%
3 78
10.9%
4 77
10.8%
9 63
8.8%
5 59
8.3%
6 57
 
8.0%
7 50
 
7.0%
8 48
 
6.7%
0 30
 
4.2%
Space Separator
ValueCountFrequency (%)
918
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3165
64.9%
Common 1709
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 279
 
8.8%
도 262
 
8.3%
남 260
 
8.2%
시 245
 
7.7%
보 244
 
7.7%
충 243
 
7.7%
령 241
 
7.6%
길 194
 
6.1%
면 183
 
5.8%
천 83
 
2.6%
Other values (197) 931
29.4%
Common
ValueCountFrequency (%)
918
53.7%
1 147
 
8.6%
2 106
 
6.2%
3 78
 
4.6%
4 77
 
4.5%
- 76
 
4.4%
9 63
 
3.7%
5 59
 
3.5%
6 57
 
3.3%
7 50
 
2.9%
Other values (2) 78
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3165
64.9%
ASCII 1709
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
918
53.7%
1 147
 
8.6%
2 106
 
6.2%
3 78
 
4.6%
4 77
 
4.5%
- 76
 
4.4%
9 63
 
3.7%
5 59
 
3.5%
6 57
 
3.3%
7 50
 
2.9%
Other values (2) 78
 
4.6%
Hangul
ValueCountFrequency (%)
청 279
 
8.8%
도 262
 
8.3%
남 260
 
8.2%
시 245
 
7.7%
보 244
 
7.7%
충 243
 
7.7%
령 241
 
7.6%
길 194
 
6.1%
면 183
 
5.8%
천 83
 
2.6%
Other values (197) 931
29.4%

지번 주소
Text

Distinct239
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-21T10:06:18.164588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.120833
Min length15

Characters and Unicode

Total characters5069
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

Unique238 ?
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 240
20.6%
충청남도 239
20.5%
오천면 29
 
2.5%
천북면 26
 
2.2%
미산면 21
 
1.8%
청소면 20
 
1.7%
웅천읍 19
 
1.6%
주교면 19
 
1.6%
남포면 18
 
1.5%
청라면 17
 
1.5%
Other values (337) 518
44.4%
2024-04-21T10:06:18.609136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
926
18.3%
청 277
 
5.5%
남 261
 
5.1%
도 259
 
5.1%
시 245
 
4.8%
보 243
 
4.8%
령 241
 
4.8%
충 240
 
4.7%
리 206
 
4.1%
- 190
 
3.7%
Other values (105) 1981
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3031
59.8%
Space Separator 926
 
18.3%
Decimal Number 922
 
18.2%
Dash Punctuation 190
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 277
 
9.1%
남 261
 
8.6%
도 259
 
8.5%
시 245
 
8.1%
보 243
 
8.0%
령 241
 
8.0%
충 240
 
7.9%
리 206
 
6.8%
면 186
 
6.1%
천 92
 
3.0%
Other values (93) 781
25.8%
Decimal Number
ValueCountFrequency (%)
1 160
17.4%
2 133
14.4%
3 120
13.0%
5 98
10.6%
4 92
10.0%
6 73
7.9%
7 73
7.9%
8 67
7.3%
0 55
 
6.0%
9 51
 
5.5%
Space Separator
ValueCountFrequency (%)
926
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3031
59.8%
Common 2038
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 277
 
9.1%
남 261
 
8.6%
도 259
 
8.5%
시 245
 
8.1%
보 243
 
8.0%
령 241
 
8.0%
충 240
 
7.9%
리 206
 
6.8%
면 186
 
6.1%
천 92
 
3.0%
Other values (93) 781
25.8%
Common
ValueCountFrequency (%)
926
45.4%
- 190
 
9.3%
1 160
 
7.9%
2 133
 
6.5%
3 120
 
5.9%
5 98
 
4.8%
4 92
 
4.5%
6 73
 
3.6%
7 73
 
3.6%
8 67
 
3.3%
Other values (2) 106
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3031
59.8%
ASCII 2038
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
926
45.4%
- 190
 
9.3%
1 160
 
7.9%
2 133
 
6.5%
3 120
 
5.9%
5 98
 
4.8%
4 92
 
4.5%
6 73
 
3.6%
7 73
 
3.6%
8 67
 
3.3%
Other values (2) 106
 
5.2%
Hangul
ValueCountFrequency (%)
청 277
 
9.1%
남 261
 
8.6%
도 259
 
8.5%
시 245
 
8.1%
보 243
 
8.0%
령 241
 
8.0%
충 240
 
7.9%
리 206
 
6.8%
면 186
 
6.1%
천 92
 
3.0%
Other values (93) 781
25.8%

위도
Real number (ℝ)

Distinct238
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean36.351908
Minimum36.180302
Maximum36.509583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:18.729552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.180302
5-th percentile36.200041
Q136.280905
median36.359552
Q336.421535
95-th percentile36.490845
Maximum36.509583
Range0.32928103
Interquartile range (IQR)0.14063012

Descriptive statistics

Standard deviation0.088705158
Coefficient of variation (CV)0.0024401788
Kurtosis-0.93996259
Mean36.351908
Median Absolute Deviation (MAD)0.06566849
Skewness-0.19675961
Sum8688.1061
Variance0.007868605
MonotonicityNot monotonic
2024-04-21T10:06:18.846334image/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%
36.22858999 1
 
0.4%
36.2781995 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%
Other values (228) 228
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)

Distinct238
Distinct (%)99.6%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean126.58012
Minimum126.08038
Maximum126.7293
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:18.971501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.08038
5-th percentile126.43522
Q1126.54859
median126.58814
Q3126.62197
95-th percentile126.68382
Maximum126.7293
Range0.64892
Interquartile range (IQR)0.0733849

Descriptive statistics

Standard deviation0.078852409
Coefficient of variation (CV)0.00062294463
Kurtosis7.6463176
Mean126.58012
Median Absolute Deviation (MAD)0.0383805
Skewness-1.7957223
Sum30252.65
Variance0.0062177024
MonotonicityNot monotonic
2024-04-21T10:06:19.098053image/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%
126.7006607 1
 
0.4%
126.571973 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%
Other values (228) 228
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
143 
1동-지상2
62 
2동-지상1
15 
2동-지상2
 
10
3동-지상1
 
4
Other values (6)
 
6

Length

Max length11
Median length6
Mean length6.0625
Min length6

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 143
59.6%
1동-지상2 62
25.8%
2동-지상1 15
 
6.2%
2동-지상2 10
 
4.2%
3동-지상1 4
 
1.7%
1동-지상1층 1
 
0.4%
1동-지상2층 1
 
0.4%
1동-지상1+지하1 1
 
0.4%
1동-지상1+지하1+ 1
 
0.4%
1동-지상2+지하1 1
 
0.4%

Length

2024-04-21T10:06:19.217485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1동-지상1 143
59.6%
1동-지상2 62
25.8%
2동-지상1 15
 
6.2%
2동-지상2 10
 
4.2%
3동-지상1 4
 
1.7%
1동-지상1+지하1 2
 
0.8%
1동-지상1층 1
 
0.4%
1동-지상2층 1
 
0.4%
1동-지상2+지하1 1
 
0.4%
1동-지상3 1
 
0.4%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct230
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.35419
Minimum32.4
Maximum538.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:19.324269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.4
5-th percentile58.9785
Q188.9125
median105.445
Q3131.56
95-th percentile227.5065
Maximum538.89
Range506.49
Interquartile range (IQR)42.6475

Descriptive statistics

Standard deviation57.200529
Coefficient of variation (CV)0.48329956
Kurtosis15.242256
Mean118.35419
Median Absolute Deviation (MAD)19.175
Skewness3.0533487
Sum28405.006
Variance3271.9006
MonotonicityNot monotonic
2024-04-21T10:06:19.431143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104.39 4
 
1.7%
111.56 3
 
1.2%
97.86 2
 
0.8%
86.598 2
 
0.8%
101.61 2
 
0.8%
111.4 2
 
0.8%
99.0 2
 
0.8%
115.73 1
 
0.4%
151.71 1
 
0.4%
107.9 1
 
0.4%
Other values (220) 220
91.7%
ValueCountFrequency (%)
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%
56.0 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 

Distinct235
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.07438
Minimum32.4
Maximum584.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:19.534223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.4
5-th percentile65.571
Q191.7075
median124.06
Q3166.6475
95-th percentile320.536
Maximum584.25
Range551.85
Interquartile range (IQR)74.94

Descriptive statistics

Standard deviation78.569842
Coefficient of variation (CV)0.54915382
Kurtosis6.1791424
Mean143.07438
Median Absolute Deviation (MAD)35.27
Skewness2.1103209
Sum34337.851
Variance6173.2201
MonotonicityNot monotonic
2024-04-21T10:06:19.659678image/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%
160.0 1
 
0.4%
87.93 1
 
0.4%
140.22 1
 
0.4%
74.88 1
 
0.4%
90.42 1
 
0.4%
95.2 1
 
0.4%
Other values (225) 225
93.8%
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

Distinct223
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1970-07-25 00:00:00
Maximum2023-11-09 00:00:00
2024-04-21T10:06:19.772576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:19.885247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소유자
Text

Distinct225
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-21T10:06:20.082794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length8.5583333
Min length3

Characters and Unicode

Total characters2054
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

Unique214 ?
Unique (%)89.2%

Sample

1st row수부1리 마을회
2nd row수부2리마을회
3rd row수부3리마을회
4th row성동1리마을회
5th row성동2,3리대동회
ValueCountFrequency (%)
마을회 13
 
5.0%
보령시 6
 
2.3%
주교2리 3
 
1.1%
웅천읍대창5리마을회 2
 
0.8%
교성1리마을회 2
 
0.8%
호도마을회 2
 
0.8%
미산면봉성리마을회 2
 
0.8%
도흥리마을회 2
 
0.8%
청소면성연2리음지마을 2
 
0.8%
삽시1리마을회 2
 
0.8%
Other values (220) 225
86.2%
2024-04-21T10:06:20.403722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 226
 
11.0%
마 208
 
10.1%
을 206
 
10.0%
191
 
9.3%
리 179
 
8.7%
2 66
 
3.2%
1 63
 
3.1%
대 35
 
1.7%
동 31
 
1.5%
3 30
 
1.5%
Other values (156) 819
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1665
81.1%
Space Separator 191
 
9.3%
Decimal Number 188
 
9.2%
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 226
 
13.6%
마 208
 
12.5%
을 206
 
12.4%
리 179
 
10.8%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.7%
면 27
 
1.6%
주 25
 
1.5%
산 24
 
1.4%
Other values (141) 675
40.5%
Decimal Number
ValueCountFrequency (%)
2 66
35.1%
1 63
33.5%
3 30
16.0%
4 13
 
6.9%
5 7
 
3.7%
7 4
 
2.1%
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 1665
81.1%
Common 389
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 226
 
13.6%
마 208
 
12.5%
을 206
 
12.4%
리 179
 
10.8%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.7%
면 27
 
1.6%
주 25
 
1.5%
산 24
 
1.4%
Other values (141) 675
40.5%
Common
ValueCountFrequency (%)
191
49.1%
2 66
 
17.0%
1 63
 
16.2%
3 30
 
7.7%
4 13
 
3.3%
5 7
 
1.8%
7 4
 
1.0%
) 3
 
0.8%
( 3
 
0.8%
, 3
 
0.8%
Other values (5) 6
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1665
81.1%
ASCII 389
 
18.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 226
 
13.6%
마 208
 
12.5%
을 206
 
12.4%
리 179
 
10.8%
대 35
 
2.1%
동 31
 
1.9%
성 29
 
1.7%
면 27
 
1.6%
주 25
 
1.5%
산 24
 
1.4%
Other values (141) 675
40.5%
ASCII
ValueCountFrequency (%)
191
49.1%
2 66
 
17.0%
1 63
 
16.2%
3 30
 
7.7%
4 13
 
3.3%
5 7
 
1.8%
7 4
 
1.0%
) 3
 
0.8%
( 3
 
0.8%
, 3
 
0.8%
Other values (5) 6
 
1.5%

경로당겸용여부
Boolean

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size372.0 B
True
200 
False
40 
ValueCountFrequency (%)
True 200
83.3%
False 40
 
16.7%
2024-04-21T10:06:20.496614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

건축년도
Real number (ℝ)

Distinct34
Distinct (%)14.2%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean2002.7866
Minimum1970
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-21T10:06:20.578608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1994.9
Q11999
median2002
Q32008
95-th percentile2013
Maximum2023
Range53
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.9868175
Coefficient of variation (CV)0.0034885481
Kurtosis3.383033
Mean2002.7866
Median Absolute Deviation (MAD)4
Skewness-0.53150462
Sum478666
Variance48.815618
MonotonicityNot monotonic
2024-04-21T10:06:20.693372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1999 22
 
9.2%
1998 21
 
8.8%
2001 20
 
8.3%
2000 17
 
7.1%
1997 16
 
6.7%
2003 13
 
5.4%
2009 13
 
5.4%
2002 11
 
4.6%
2011 10
 
4.2%
2008 10
 
4.2%
Other values (24) 86
35.8%
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 2
 
0.8%
1994 2
 
0.8%
1995 5
2.1%
ValueCountFrequency (%)
2023 1
 
0.4%
2022 2
 
0.8%
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%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2024-04-09 00:00:00
Maximum2024-04-09 00:00:00
2024-04-21T10:06:20.788887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:20.864599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T10:06:15.387546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.186956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.670794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.105548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.532925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.943943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.453419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.306620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.737808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.176390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.607795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.016527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.522341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.385777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.813895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.250689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.682788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.106737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.594149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.456791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.886968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.322893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.751719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.194961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.665532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.535265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.952600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.387930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.812665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.261128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.735542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:13.600930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.029166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.456464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:14.876026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:06:15.322676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:06:20.926905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도동수-층수건축면적연면적경로당겸용여부건축년도
연번1.0000.9120.6680.3090.1130.1510.3230.270
위도0.9121.0000.4290.2300.0000.0000.2840.000
경도0.6680.4291.0000.0000.3330.4540.2400.000
동수-층수0.3090.2300.0001.0000.1850.5040.0800.000
건축면적0.1130.0000.3330.1851.0000.8340.0350.220
연면적0.1510.0000.4540.5040.8341.0000.1290.163
경로당겸용여부0.3230.2840.2400.0800.0350.1291.0000.412
건축년도0.2700.0000.0000.0000.2200.1630.4121.000
2024-04-21T10:06:21.014230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수-층수경로당겸용여부
동수-층수1.0000.074
경로당겸용여부0.0741.000
2024-04-21T10:06:21.084877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축면적연면적건축년도동수-층수경로당겸용여부
연번1.000-0.3180.439-0.0550.045-0.0160.1360.253
위도-0.3181.000-0.3710.0590.001-0.0580.0990.214
경도0.439-0.3711.000-0.072-0.001-0.0200.0000.236
건축면적-0.0550.059-0.0721.0000.813-0.0310.0860.023
연면적0.0450.001-0.0010.8131.000-0.0730.2540.127
건축년도-0.016-0.058-0.020-0.031-0.0731.0000.0000.316
동수-층수0.1360.0990.0000.0860.2540.0001.0000.074
경로당겸용여부0.2530.2140.2360.0230.1270.3160.0741.000

Missing values

2024-04-21T10:06:15.843622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:06:16.029971image/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.
2024-04-21T10:06:16.141787image/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 마을회Y19992024-04-09
12수부2리 마을회관충청남도 보령시 웅천읍 수안1길 47-11충청남도 보령시 웅천읍 수부리 805-236.259123126.6160321동-지상178.7978.792009-09-25수부2리마을회N20092024-04-09
23수부3리 마을회관 (부당 경로당)충청남도 보령시 웅천읍 부당길 27충청남도 보령시 웅천읍 수부리 63336.264756126.6179481동-지상191.2683.71998-10-08수부3리마을회Y19982024-04-09
34성동1리 마을회관 (내성 경로당)충청남도 보령시 웅천읍 내성1길 42충청남도 보령시 웅천읍 성동리 199-136.247907126.6242051동-지상1153.44203.932004-12-28성동1리마을회Y20042024-04-09
45성동2리 노인회관충청남도 보령시 웅천읍 성동큰길 239충청남도 보령시 웅천읍 성동리 782-136.250928126.6160821동-지상1108.86184.621993-04-20성동2,3리대동회Y19932024-04-09
56성동3리 노인회관충청남도 보령시 웅천읍 외성1길 2충청남도 보령시 웅천읍 성동리 651-136.24901126.6125151동-지상135.0335.032020-09-23성동3리 노인회N20202024-04-09
67대창5리 마을회관(한내마을회관)충청남도 보령시 웅천읍 한내1길 98충청남도 보령시 웅천읍 대창리 48336.23585126.6051741동-지상197.597.52008-01-03웅천읍대창5리마을회Y20082024-04-09
78대창5리 마을회관충청남도 보령시 웅천읍 한내1길 94충청남도 보령시 웅천읍 대창리 483-236.235793126.6052761동-지상1115.37115.372008-06-24웅천읍대창5리마을회Y20082024-04-09
89대창6리 마을회관충청남도 보령시 웅천읍 방축길 95충청남도 보령시 웅천읍 대창리 453-136.233204126.6043891동-지상194.3294.322004-09-10한축마을회N20042024-04-09
910대창9리 노인회관 (웅천읍분회경로당)충청남도 보령시 웅천읍 장터8길 46충청남도 보령시 웅천읍 대창리 687-136.235725126.6000821동-지상1188.82366.71988-06-09웅천면노인회새마을지도자+보령군웅천면협의회Y19982024-04-09
연번마을회관 이름도로명 주소지번 주소위도경도동수-층수건축면적연면적사용승인일소유자경로당겸용여부건축년도데이터기준일
230232남곡3통마을(노인)회관충청남도 보령시 남서2길 117충청남도 보령시 남곡동 1030-236.337801126.5523471동-지상3154.04364.982007-12-20남곡3통영농조합Y20072024-04-09
231233요암1통1반마을(노인)회관충청남도 보령시 서낭길 19-3충청남도 보령시 요암동 141-336.32835126.5580711동-지상188.6584.572008-05-01요암1통마을회Y20082024-04-09
232234요암2통마을(노인)회관충청남도 보령시 절터길 4충청남도 보령시 요암동 868-336.328113126.5425661동-지상1120.21111.571998-06-22보령시Y19982024-04-09
233235요암3통마을(노인)회관충청남도 보령시 뒷골길 21-67충청남도 보령시 요암동 504-236.320871126.5533181동-지상2140.29189.971997-12-22보령시요암3통마을대동회Y19972024-04-09
234236신흑1통마을(노인)회관충청남도 보령시 해망산길 79충청남도 보령시 신흑동 126-736.321676126.541031동-지상295.19165.761993-06-26보령시Y19932024-04-09
235237신흑2통마을회관충청남도 보령시 흑포1길 33-22충청남도 보령시 신흑동 245-136.318746126.5352921동-지상2101.61183.472010-08-31신흑2통마을회N20102024-04-09
236238신흑3통1반마을(노인)회관충청남도 보령시 달푸미길 39-5충청남도 보령시 신흑동 900-3136.320146126.5131161동-지상157.6757.672013-03-15보령시Y20132024-04-09
237239신흑4통마을(노인)회관충청남도 보령시 대천항로 142-40충청남도 보령시 신흑동 775-1336.317393126.5207621동-지상2129.98197.892010-01-18신흑4통청룡마을회Y20102024-04-09
238240신흑7통마을(노인)회관충청남도 보령시 대천항로 370충청남도 보령시 신흑동 2240-736.326609126.5061071동-지상2265.54484.32007-06-18신흑7통마을회Y20072024-04-09
239241신흑8통 마을회관충청남도 보령시 시영길 18충청남도 보령시 신흑동 911-10736.322985126.5105511동-지상2106.65165.511996-07-23보령시Y19962024-04-09