Overview

Dataset statistics

Number of variables12
Number of observations370
Missing cells31
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.9 KiB
Average record size in memory99.4 B

Variable types

Text4
Categorical5
Numeric3

Dataset

Description홍성군내 경로당 현황으로 시설명, 시설유형, 주소, 위도, 경도, 영업상태, 전화번호, 건립일자, 데이터 기준일 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=3073652

Alerts

시설유형 has constant value ""Constant
영업상태명 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지지번주소 has 12 (3.2%) missing valuesMissing
전화번호 has 19 (5.1%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:35:48.779008
Analysis finished2024-01-09 21:35:50.213999
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-10T06:35:50.407656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9
Mean length9.7918919
Min length9

Characters and Unicode

Total characters3623
Distinct characters216
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique370 ?
Unique (%)100.0%

Sample

1st row홍성읍 가좌동경로당
2nd row홍성읍 경성아파트경로당
3rd row홍성읍 고암4구경로당
4th row홍성읍 광경동경로당
5th row홍성읍 교동경로당
ValueCountFrequency (%)
홍성읍 56
 
7.6%
광천읍 44
 
5.9%
홍북읍 37
 
5.0%
홍동면 34
 
4.6%
장곡면 34
 
4.6%
갈산면 31
 
4.2%
서부면 30
 
4.0%
금마면 28
 
3.8%
은하면 26
 
3.5%
결성면 26
 
3.5%
Other values (342) 395
53.3%
2024-01-10T06:35:50.743861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 378
 
10.4%
경 375
 
10.4%
371
 
10.2%
로 370
 
10.2%
면 234
 
6.5%
읍 137
 
3.8%
홍 133
 
3.7%
성 100
 
2.8%
동 88
 
2.4%
구 68
 
1.9%
Other values (206) 1369
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3191
88.1%
Space Separator 371
 
10.2%
Decimal Number 58
 
1.6%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 378
 
11.8%
경 375
 
11.8%
로 370
 
11.6%
면 234
 
7.3%
읍 137
 
4.3%
홍 133
 
4.2%
성 100
 
3.1%
동 88
 
2.8%
구 68
 
2.1%
산 57
 
1.8%
Other values (193) 1251
39.2%
Decimal Number
ValueCountFrequency (%)
2 22
37.9%
1 22
37.9%
3 7
 
12.1%
4 2
 
3.4%
9 1
 
1.7%
5 1
 
1.7%
7 1
 
1.7%
8 1
 
1.7%
0 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
H 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
371
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3191
88.1%
Common 429
 
11.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 378
 
11.8%
경 375
 
11.8%
로 370
 
11.6%
면 234
 
7.3%
읍 137
 
4.3%
홍 133
 
4.2%
성 100
 
3.1%
동 88
 
2.8%
구 68
 
2.1%
산 57
 
1.8%
Other values (193) 1251
39.2%
Common
ValueCountFrequency (%)
371
86.5%
2 22
 
5.1%
1 22
 
5.1%
3 7
 
1.6%
4 2
 
0.5%
9 1
 
0.2%
5 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
0 1
 
0.2%
Latin
ValueCountFrequency (%)
S 1
33.3%
H 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3191
88.1%
ASCII 432
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 378
 
11.8%
경 375
 
11.8%
로 370
 
11.6%
면 234
 
7.3%
읍 137
 
4.3%
홍 133
 
4.2%
성 100
 
3.1%
동 88
 
2.8%
구 68
 
2.1%
산 57
 
1.8%
Other values (193) 1251
39.2%
ASCII
ValueCountFrequency (%)
371
85.9%
2 22
 
5.1%
1 22
 
5.1%
3 7
 
1.6%
4 2
 
0.5%
9 1
 
0.2%
5 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
S 1
 
0.2%
Other values (3) 3
 
0.7%

시설유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
경로당
370 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경로당 370
100.0%

Length

2024-01-10T06:35:50.850448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:50.923638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경로당 370
100.0%

소재지도로명주소
Text

Distinct362
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-10T06:35:51.122074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length23.640541
Min length18

Characters and Unicode

Total characters8747
Distinct characters117
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

Unique354 ?
Unique (%)95.7%

Sample

1st row충청남도 홍성군 홍성읍 충서로1707번길 366-2
2nd row충청남도 홍성군 홍성읍 문화로80번길 32-14
3rd row충청남도 홍성군 홍성읍 조양로202번길 11
4th row충청남도 홍성군 홍성읍 의사로57번길 14-1
5th row충청남도 홍성군 홍성읍 충서로1575번길 100
ValueCountFrequency (%)
충청남도 370
20.0%
홍성군 370
20.0%
홍성읍 56
 
3.0%
광천읍 44
 
2.4%
홍북읍 37
 
2.0%
홍동면 34
 
1.8%
장곡면 34
 
1.8%
갈산면 31
 
1.7%
서부면 30
 
1.6%
금마면 28
 
1.5%
Other values (565) 819
44.2%
2024-01-10T06:35:51.462154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1483
17.0%
홍 570
 
6.5%
성 466
 
5.3%
남 454
 
5.2%
충 411
 
4.7%
청 375
 
4.3%
도 374
 
4.3%
1 372
 
4.3%
군 370
 
4.2%
길 340
 
3.9%
Other values (107) 3532
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5408
61.8%
Decimal Number 1740
 
19.9%
Space Separator 1483
 
17.0%
Dash Punctuation 112
 
1.3%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 570
 
10.5%
성 466
 
8.6%
남 454
 
8.4%
충 411
 
7.6%
청 375
 
6.9%
도 374
 
6.9%
군 370
 
6.8%
길 340
 
6.3%
로 263
 
4.9%
번 233
 
4.3%
Other values (93) 1552
28.7%
Decimal Number
ValueCountFrequency (%)
1 372
21.4%
3 198
11.4%
2 198
11.4%
4 172
9.9%
5 166
9.5%
7 153
8.8%
6 140
 
8.0%
8 117
 
6.7%
9 116
 
6.7%
0 108
 
6.2%
Space Separator
ValueCountFrequency (%)
1483
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5408
61.8%
Common 3339
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 570
 
10.5%
성 466
 
8.6%
남 454
 
8.4%
충 411
 
7.6%
청 375
 
6.9%
도 374
 
6.9%
군 370
 
6.8%
길 340
 
6.3%
로 263
 
4.9%
번 233
 
4.3%
Other values (93) 1552
28.7%
Common
ValueCountFrequency (%)
1483
44.4%
1 372
 
11.1%
3 198
 
5.9%
2 198
 
5.9%
4 172
 
5.2%
5 166
 
5.0%
7 153
 
4.6%
6 140
 
4.2%
8 117
 
3.5%
9 116
 
3.5%
Other values (4) 224
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5408
61.8%
ASCII 3339
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1483
44.4%
1 372
 
11.1%
3 198
 
5.9%
2 198
 
5.9%
4 172
 
5.2%
5 166
 
5.0%
7 153
 
4.6%
6 140
 
4.2%
8 117
 
3.5%
9 116
 
3.5%
Other values (4) 224
 
6.7%
Hangul
ValueCountFrequency (%)
홍 570
 
10.5%
성 466
 
8.6%
남 454
 
8.4%
충 411
 
7.6%
청 375
 
6.9%
도 374
 
6.9%
군 370
 
6.8%
길 340
 
6.3%
로 263
 
4.9%
번 233
 
4.3%
Other values (93) 1552
28.7%

소재지지번주소
Text

MISSING 

Distinct350
Distinct (%)97.8%
Missing12
Missing (%)3.2%
Memory size3.0 KiB
2024-01-10T06:35:51.720112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length21.432961
Min length18

Characters and Unicode

Total characters7673
Distinct characters122
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

Unique342 ?
Unique (%)95.5%

Sample

1st row충청남도 홍성군 홍성읍 대교리 30-2
2nd row충청남도 홍성군 홍성읍 오관리 518
3rd row충청남도 홍성군 홍성읍 고암리 547-22
4th row충청남도 홍성군 홍성읍 대교리 510
5th row충청남도 홍성군 홍성읍 대교리 251-1
ValueCountFrequency (%)
충청남도 358
20.0%
홍성군 358
20.0%
홍성읍 56
 
3.1%
광천읍 41
 
2.3%
홍북읍 34
 
1.9%
홍동면 33
 
1.8%
장곡면 31
 
1.7%
갈산면 31
 
1.7%
서부면 30
 
1.7%
금마면 28
 
1.6%
Other values (486) 793
44.2%
2024-01-10T06:35:52.085573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1435
18.7%
홍 484
 
6.3%
성 458
 
6.0%
남 373
 
4.9%
도 362
 
4.7%
청 360
 
4.7%
충 358
 
4.7%
군 358
 
4.7%
리 358
 
4.7%
- 259
 
3.4%
Other values (112) 2868
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4640
60.5%
Space Separator 1435
 
18.7%
Decimal Number 1339
 
17.5%
Dash Punctuation 259
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 484
10.4%
성 458
 
9.9%
남 373
 
8.0%
도 362
 
7.8%
청 360
 
7.8%
충 358
 
7.7%
군 358
 
7.7%
리 358
 
7.7%
면 227
 
4.9%
읍 134
 
2.9%
Other values (100) 1168
25.2%
Decimal Number
ValueCountFrequency (%)
1 238
17.8%
2 184
13.7%
3 175
13.1%
4 139
10.4%
5 133
9.9%
6 118
8.8%
7 98
7.3%
8 90
 
6.7%
9 84
 
6.3%
0 80
 
6.0%
Space Separator
ValueCountFrequency (%)
1435
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 259
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4640
60.5%
Common 3033
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 484
10.4%
성 458
 
9.9%
남 373
 
8.0%
도 362
 
7.8%
청 360
 
7.8%
충 358
 
7.7%
군 358
 
7.7%
리 358
 
7.7%
면 227
 
4.9%
읍 134
 
2.9%
Other values (100) 1168
25.2%
Common
ValueCountFrequency (%)
1435
47.3%
- 259
 
8.5%
1 238
 
7.8%
2 184
 
6.1%
3 175
 
5.8%
4 139
 
4.6%
5 133
 
4.4%
6 118
 
3.9%
7 98
 
3.2%
8 90
 
3.0%
Other values (2) 164
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4640
60.5%
ASCII 3033
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1435
47.3%
- 259
 
8.5%
1 238
 
7.8%
2 184
 
6.1%
3 175
 
5.8%
4 139
 
4.6%
5 133
 
4.4%
6 118
 
3.9%
7 98
 
3.2%
8 90
 
3.0%
Other values (2) 164
 
5.4%
Hangul
ValueCountFrequency (%)
홍 484
10.4%
성 458
 
9.9%
남 373
 
8.0%
도 362
 
7.8%
청 360
 
7.8%
충 358
 
7.7%
군 358
 
7.7%
리 358
 
7.7%
면 227
 
4.9%
읍 134
 
2.9%
Other values (100) 1168
25.2%

위도
Real number (ℝ)

Distinct362
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.567908
Minimum36.478939
Maximum36.669302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-10T06:35:52.200647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.478939
5-th percentile36.492965
Q136.529489
median36.57409
Q336.602777
95-th percentile36.644015
Maximum36.669302
Range0.19036222
Interquartile range (IQR)0.073287503

Descriptive statistics

Standard deviation0.046889694
Coefficient of variation (CV)0.0012822635
Kurtosis-0.99125496
Mean36.567908
Median Absolute Deviation (MAD)0.036701755
Skewness-0.037310881
Sum13530.126
Variance0.0021986434
MonotonicityNot monotonic
2024-01-10T06:35:52.532157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.51153938 2
 
0.5%
36.48602104 2
 
0.5%
36.53474118 2
 
0.5%
36.48525286 2
 
0.5%
36.57052522 2
 
0.5%
36.56578837 2
 
0.5%
36.5980328 2
 
0.5%
36.55958088 2
 
0.5%
36.54528637 1
 
0.3%
36.54356388 1
 
0.3%
Other values (352) 352
95.1%
ValueCountFrequency (%)
36.47893948 1
0.3%
36.48146346 1
0.3%
36.48161574 1
0.3%
36.48174674 1
0.3%
36.48517403 1
0.3%
36.48525286 2
0.5%
36.48549153 1
0.3%
36.48602104 2
0.5%
36.48684373 1
0.3%
36.48687781 1
0.3%
ValueCountFrequency (%)
36.6693017 1
0.3%
36.66799665 1
0.3%
36.6650817 1
0.3%
36.65938778 1
0.3%
36.65891134 1
0.3%
36.6569497 1
0.3%
36.6542981 1
0.3%
36.653563 1
0.3%
36.652293 1
0.3%
36.65165786 1
0.3%

경도
Real number (ℝ)

Distinct362
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.63632
Minimum126.44075
Maximum126.76737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-10T06:35:52.652807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.44075
5-th percentile126.50834
Q1126.58196
median126.65238
Q3126.69134
95-th percentile126.73958
Maximum126.76737
Range0.3266238
Interquartile range (IQR)0.10938147

Descriptive statistics

Standard deviation0.072974179
Coefficient of variation (CV)0.00057624999
Kurtosis-0.63452291
Mean126.63632
Median Absolute Deviation (MAD)0.0502131
Skewness-0.46736138
Sum46855.439
Variance0.0053252307
MonotonicityNot monotonic
2024-01-10T06:35:52.767823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6414302 2
 
0.5%
126.6789205 2
 
0.5%
126.592573 2
 
0.5%
126.6950176 2
 
0.5%
126.6092873 2
 
0.5%
126.6960562 2
 
0.5%
126.6659343 2
 
0.5%
126.7188069 2
 
0.5%
126.5545452 1
 
0.3%
126.6023291 1
 
0.3%
Other values (352) 352
95.1%
ValueCountFrequency (%)
126.4407468 1
0.3%
126.4601162 1
0.3%
126.467645 1
0.3%
126.4686208 1
0.3%
126.4718744 1
0.3%
126.4722379 1
0.3%
126.4727629 1
0.3%
126.4774936 1
0.3%
126.4775067 1
0.3%
126.4798323 1
0.3%
ValueCountFrequency (%)
126.7673706 1
0.3%
126.7616267 1
0.3%
126.7563472 1
0.3%
126.7560473 1
0.3%
126.7539722 1
0.3%
126.7530553 1
0.3%
126.7491558 1
0.3%
126.7471337 1
0.3%
126.7470979 1
0.3%
126.7462018 1
0.3%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
영업
370 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 370
100.0%

Length

2024-01-10T06:35:52.878136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:52.952566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 370
100.0%

전화번호
Text

MISSING 

Distinct321
Distinct (%)91.5%
Missing19
Missing (%)5.1%
Memory size3.0 KiB
2024-01-10T06:35:53.139637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters4212
Distinct characters11
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

Unique299 ?
Unique (%)85.2%

Sample

1st row041-633-2882
2nd row041-633-0402
3rd row041-634-8696
4th row041-632-6267
5th row041-632-6191
ValueCountFrequency (%)
041-641-6703 5
 
1.4%
041-633-9870 3
 
0.9%
041-633-6936 3
 
0.9%
041-642-8955 3
 
0.9%
041-634-5460 3
 
0.9%
041-631-2465 3
 
0.9%
041-634-7750 2
 
0.6%
041-642-2260 2
 
0.6%
041-642-7577 2
 
0.6%
041-632-9678 2
 
0.6%
Other values (311) 323
92.0%
2024-01-10T06:35:53.430347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 702
16.7%
4 670
15.9%
1 555
13.2%
6 512
12.2%
0 489
11.6%
3 444
10.5%
2 248
 
5.9%
7 159
 
3.8%
5 153
 
3.6%
9 148
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3510
83.3%
Dash Punctuation 702
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 670
19.1%
1 555
15.8%
6 512
14.6%
0 489
13.9%
3 444
12.6%
2 248
 
7.1%
7 159
 
4.5%
5 153
 
4.4%
9 148
 
4.2%
8 132
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 702
16.7%
4 670
15.9%
1 555
13.2%
6 512
12.2%
0 489
11.6%
3 444
10.5%
2 248
 
5.9%
7 159
 
3.8%
5 153
 
3.6%
9 148
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 702
16.7%
4 670
15.9%
1 555
13.2%
6 512
12.2%
0 489
11.6%
3 444
10.5%
2 248
 
5.9%
7 159
 
3.8%
5 153
 
3.6%
9 148
 
3.5%

건립일자
Categorical

Distinct37
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2002-01-01
44 
1999-01-01
39 
2001-01-01
36 
1998-01-01
35 
1997-01-01
26 
Other values (32)
190 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique6 ?
Unique (%)1.6%

Sample

1st row1999-01-01
2nd row1997-01-01
3rd row2002-01-01
4th row2009-01-01
5th row1996-01-01

Common Values

ValueCountFrequency (%)
2002-01-01 44
 
11.9%
1999-01-01 39
 
10.5%
2001-01-01 36
 
9.7%
1998-01-01 35
 
9.5%
1997-01-01 26
 
7.0%
1995-01-01 17
 
4.6%
2000-01-01 16
 
4.3%
2003-01-01 16
 
4.3%
1996-01-01 15
 
4.1%
2004-01-01 14
 
3.8%
Other values (27) 112
30.3%

Length

2024-01-10T06:35:53.542485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2002-01-01 44
 
11.9%
1999-01-01 39
 
10.5%
2001-01-01 36
 
9.7%
1998-01-01 35
 
9.5%
1997-01-01 26
 
7.0%
1995-01-01 17
 
4.6%
2000-01-01 16
 
4.3%
2003-01-01 16
 
4.3%
1996-01-01 15
 
4.1%
2004-01-01 14
 
3.8%
Other values (27) 112
30.3%

건물면적
Real number (ℝ)

Distinct138
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136.57838
Minimum32
Maximum374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-10T06:35:53.634774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile80.35
Q196
median112
Q3169
95-th percentile276
Maximum374
Range342
Interquartile range (IQR)73

Descriptive statistics

Standard deviation60.399264
Coefficient of variation (CV)0.44223152
Kurtosis2.778539
Mean136.57838
Median Absolute Deviation (MAD)25
Skewness1.5766568
Sum50534
Variance3648.0711
MonotonicityNot monotonic
2024-01-10T06:35:53.746572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 14
 
3.8%
98 11
 
3.0%
94 11
 
3.0%
101 10
 
2.7%
83 8
 
2.2%
105 8
 
2.2%
89 8
 
2.2%
100 8
 
2.2%
84 7
 
1.9%
169 7
 
1.9%
Other values (128) 278
75.1%
ValueCountFrequency (%)
32 1
0.3%
38 1
0.3%
45 1
0.3%
59 1
0.3%
62 1
0.3%
63 1
0.3%
64 1
0.3%
65 1
0.3%
70 2
0.5%
72 2
0.5%
ValueCountFrequency (%)
374 2
0.5%
363 3
0.8%
348 1
 
0.3%
335 1
 
0.3%
326 1
 
0.3%
304 1
 
0.3%
303 1
 
0.3%
297 1
 
0.3%
294 1
 
0.3%
289 1
 
0.3%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
충청남도 홍성군청
370 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 홍성군청
2nd row충청남도 홍성군청
3rd row충청남도 홍성군청
4th row충청남도 홍성군청
5th row충청남도 홍성군청

Common Values

ValueCountFrequency (%)
충청남도 홍성군청 370
100.0%

Length

2024-01-10T06:35:53.846766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:53.921724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 370
50.0%
홍성군청 370
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-09-12
370 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-12
2nd row2023-09-12
3rd row2023-09-12
4th row2023-09-12
5th row2023-09-12

Common Values

ValueCountFrequency (%)
2023-09-12 370
100.0%

Length

2024-01-10T06:35:54.001016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:54.075328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-12 370
100.0%

Interactions

2024-01-10T06:35:49.594215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.143014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.372024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.670857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.224639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.451902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.760664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.300169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:49.522386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:35:54.120072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도건립일자건물면적
위도1.0000.4610.2250.000
경도0.4611.0000.0000.281
건립일자0.2250.0001.0000.504
건물면적0.0000.2810.5041.000
2024-01-10T06:35:54.191541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도건물면적건립일자
위도1.0000.1600.1020.075
경도0.1601.0000.0250.000
건물면적0.1020.0251.0000.193
건립일자0.0750.0000.1931.000

Missing values

2024-01-10T06:35:49.893389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:35:50.055747image/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.
2024-01-10T06:35:50.165259image/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

시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자
0홍성읍 가좌동경로당경로당충청남도 홍성군 홍성읍 충서로1707번길 366-2충청남도 홍성군 홍성읍 대교리 30-236.605778126.677213영업041-633-28821999-01-01195충청남도 홍성군청2023-09-12
1홍성읍 경성아파트경로당경로당충청남도 홍성군 홍성읍 문화로80번길 32-14충청남도 홍성군 홍성읍 오관리 51836.594412126.664214영업041-633-04021997-01-0164충청남도 홍성군청2023-09-12
2홍성읍 고암4구경로당경로당충청남도 홍성군 홍성읍 조양로202번길 11충청남도 홍성군 홍성읍 고암리 547-2236.599474126.67141영업041-634-86962002-01-01111충청남도 홍성군청2023-09-12
3홍성읍 광경동경로당경로당충청남도 홍성군 홍성읍 의사로57번길 14-1충청남도 홍성군 홍성읍 대교리 51036.603151126.669903영업041-632-62672009-01-01228충청남도 홍성군청2023-09-12
4홍성읍 교동경로당경로당충청남도 홍성군 홍성읍 충서로1575번길 100충청남도 홍성군 홍성읍 대교리 251-136.609074126.666813영업041-632-61911996-01-01149충청남도 홍성군청2023-09-12
5홍성읍 구룡리 동구경로당경로당충청남도 홍성군 홍성읍 충절로810번길 18충청남도 홍성군 홍성읍 구룡리 596136.588892126.690067영업041-632-02361993-01-01206충청남도 홍성군청2023-09-12
6홍성읍 남문동경로당경로당충청남도 홍성군 홍성읍 조양로10번길 76충청남도 홍성군 홍성읍 오관리 443-1136.597955126.660587영업041-634-55741992-01-01198충청남도 홍성군청2023-09-12
7홍성읍 남산경로당경로당충청남도 홍성군 홍성읍 충서로1159번길 18-5충청남도 홍성군 홍성읍 남장리 361-336.581131126.654331영업041-633-63141977-01-01129충청남도 홍성군청2023-09-12
8홍성읍 남장2구경로당경로당충청남도 홍성군 홍성읍 남장중로 63-7충청남도 홍성군 홍성읍 남장리 55436.586878126.664123영업041-633-57642011-01-01182충청남도 홍성군청2023-09-12
9홍성읍 남장3리경로당경로당충청남도 홍성군 홍성읍 홍장북로441번길 17충청남도 홍성군 홍성읍 남장리 95-636.593516126.667052영업041-631-16081990-01-0196충청남도 홍성군청2023-09-12
시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자
360구항면 외중경로당경로당충청남도 홍성군 구항면 구항남길 456-15충청남도 홍성군 구항면 태봉리 114-736.561898126.602459영업041-631-04481997-01-0195충청남도 홍성군청2023-09-12
361구항면 장양경로당경로당충청남도 홍성군 구항면 구항서길100번길 2-3충청남도 홍성군 구항면 장양리 606-336.57984126.587039영업041-633-86612012-01-01214충청남도 홍성군청2023-09-12
362구항면 지석경로당경로당충청남도 홍성군 구항면 거북로 202충청남도 홍성군 구항면 지정리 81636.55676126.62524영업041-642-68682022-01-01208충청남도 홍성군청2023-09-12
363구항면 척괴경로당경로당충청남도 홍성군 구항면 충서로726번길 142충청남도 홍성군 구항면 신곡리 69036.542629126.648673영업041-642-19842001-01-01158충청남도 홍성군청2023-09-12
364구항면 청광경로당경로당충청남도 홍성군 구항면 충서로877번길 30충청남도 홍성군 구항면 청광리 460-336.557571126.643918영업041-631-08361997-01-01186충청남도 홍성군청2023-09-12
365구항면 태봉경로당경로당충청남도 홍성군 구항면 구항남길 544충청남도 홍성군 구항면 태봉리 330-636.568258126.597287영업041-632-72981995-01-0195충청남도 홍성군청2023-09-12
366구항면 하대경로당경로당충청남도 홍성군 구항면 구항길193번길 76충청남도 홍성군 구항면 황곡리 428-2136.590489126.619924영업041-634-59151997-01-01156충청남도 홍성군청2023-09-12
367구항면 화리경로당경로당충청남도 홍성군 구항면 내포로686번길 240충청남도 홍성군 구항면 공리 243-136.605054126.592814영업041-633-53311999-01-01145충청남도 홍성군청2023-09-12
368구항면 화산경로당경로당충청남도 홍성군 구항면 거북로 440충청남도 홍성군 구항면 내현리 375-136.570525126.609287영업041-631-56782002-01-01175충청남도 홍성군청2023-09-12
369구항면 황곡경로당경로당충청남도 홍성군 구항면 구항길240번길 23충청남도 홍성군 구항면 황곡리 산 126-136.58279126.623979영업041-634-86561995-01-0196충청남도 홍성군청2023-09-12