Overview

Dataset statistics

Number of variables8
Number of observations371
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory66.4 B

Variable types

Numeric2
Categorical2
Text3
DateTime1

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

관리기관명 has constant value ""Constant
데이터등록일자 has constant value ""Constant
연번 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
관리기관전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:35:55.150337
Analysis finished2024-01-09 21:35:55.868015
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct371
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186
Minimum1
Maximum371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-10T06:35:55.942249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.5
Q193.5
median186
Q3278.5
95-th percentile352.5
Maximum371
Range370
Interquartile range (IQR)185

Descriptive statistics

Standard deviation107.24272
Coefficient of variation (CV)0.57657374
Kurtosis-1.2
Mean186
Median Absolute Deviation (MAD)93
Skewness0
Sum69006
Variance11501
MonotonicityStrictly increasing
2024-01-10T06:35:56.068026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
246 1
 
0.3%
255 1
 
0.3%
254 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
Other values (361) 361
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
371 1
0.3%
370 1
0.3%
369 1
0.3%
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%

읍면
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
홍성읍
58 
광천읍
43 
홍북읍
37 
홍동면
34 
장곡면
34 
Other values (6)
165 

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 58
15.6%
광천읍 43
11.6%
홍북읍 37
10.0%
홍동면 34
9.2%
장곡면 34
9.2%
갈산면 31
8.4%
서부면 30
8.1%
금마면 28
7.5%
은하면 26
7.0%
결성면 26
7.0%

Length

2024-01-10T06:35:56.203743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
홍성읍 58
15.6%
광천읍 43
11.6%
홍북읍 37
10.0%
홍동면 34
9.2%
장곡면 34
9.2%
갈산면 31
8.4%
서부면 30
8.1%
금마면 28
7.5%
은하면 26
7.0%
결성면 26
7.0%

경로당 명칭
Text

Distinct341
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-10T06:35:56.525599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length2.8221024
Min length2

Characters and Unicode

Total characters1047
Distinct characters219
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique319 ?
Unique (%)86.0%

Sample

1st row홍성읍분회(남)
2nd row가좌동
3rd row경성아파트
4th row고암4구
5th row광경동
ValueCountFrequency (%)
신촌 5
 
1.3%
중리 3
 
0.8%
하리 3
 
0.8%
내동 3
 
0.8%
신곡 3
 
0.8%
동막 3
 
0.8%
묵동 2
 
0.5%
월곡 2
 
0.5%
신대 2
 
0.5%
백동 2
 
0.5%
Other values (332) 344
92.5%
2024-01-10T06:35:56.930975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 54
 
5.2%
구 44
 
4.2%
리 38
 
3.6%
신 27
 
2.6%
산 26
 
2.5%
2 22
 
2.1%
1 22
 
2.1%
성 20
 
1.9%
아 20
 
1.9%
상 19
 
1.8%
Other values (209) 755
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 981
93.7%
Decimal Number 58
 
5.5%
Uppercase Letter 3
 
0.3%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 54
 
5.5%
구 44
 
4.5%
리 38
 
3.9%
신 27
 
2.8%
산 26
 
2.7%
성 20
 
2.0%
아 20
 
2.0%
상 19
 
1.9%
파 18
 
1.8%
곡 18
 
1.8%
Other values (194) 697
71.0%
Decimal Number
ValueCountFrequency (%)
2 22
37.9%
1 22
37.9%
3 7
 
12.1%
4 2
 
3.4%
7 1
 
1.7%
9 1
 
1.7%
5 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%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 981
93.7%
Common 63
 
6.0%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 54
 
5.5%
구 44
 
4.5%
리 38
 
3.9%
신 27
 
2.8%
산 26
 
2.7%
성 20
 
2.0%
아 20
 
2.0%
상 19
 
1.9%
파 18
 
1.8%
곡 18
 
1.8%
Other values (194) 697
71.0%
Common
ValueCountFrequency (%)
2 22
34.9%
1 22
34.9%
3 7
 
11.1%
4 2
 
3.2%
) 2
 
3.2%
( 2
 
3.2%
7 1
 
1.6%
9 1
 
1.6%
5 1
 
1.6%
8 1
 
1.6%
Other values (2) 2
 
3.2%
Latin
ValueCountFrequency (%)
S 1
33.3%
H 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 981
93.7%
ASCII 66
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 54
 
5.5%
구 44
 
4.5%
리 38
 
3.9%
신 27
 
2.8%
산 26
 
2.7%
성 20
 
2.0%
아 20
 
2.0%
상 19
 
1.9%
파 18
 
1.8%
곡 18
 
1.8%
Other values (194) 697
71.0%
ASCII
ValueCountFrequency (%)
2 22
33.3%
1 22
33.3%
3 7
 
10.6%
4 2
 
3.0%
) 2
 
3.0%
( 2
 
3.0%
7 1
 
1.5%
9 1
 
1.5%
5 1
 
1.5%
8 1
 
1.5%
Other values (5) 5
 
7.6%

회원수
Real number (ℝ)

Distinct61
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.121294
Minimum12
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-10T06:35:57.050219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile20
Q131
median38
Q348
95-th percentile63
Maximum110
Range98
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.659324
Coefficient of variation (CV)0.34045074
Kurtosis2.3911159
Mean40.121294
Median Absolute Deviation (MAD)8
Skewness0.9526992
Sum14885
Variance186.57714
MonotonicityNot monotonic
2024-01-10T06:35:57.158837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 18
 
4.9%
41 17
 
4.6%
36 16
 
4.3%
43 16
 
4.3%
37 15
 
4.0%
35 13
 
3.5%
40 12
 
3.2%
32 11
 
3.0%
30 11
 
3.0%
48 10
 
2.7%
Other values (51) 232
62.5%
ValueCountFrequency (%)
12 1
 
0.3%
14 1
 
0.3%
16 3
 
0.8%
17 3
 
0.8%
18 4
1.1%
19 3
 
0.8%
20 5
1.3%
21 3
 
0.8%
22 7
1.9%
23 9
2.4%
ValueCountFrequency (%)
110 1
0.3%
102 1
0.3%
84 1
0.3%
76 2
0.5%
74 1
0.3%
73 2
0.5%
71 1
0.3%
69 2
0.5%
67 1
0.3%
66 1
0.3%

소재지도로명주소
Text

Distinct364
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-10T06:35:57.366866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length23.789757
Min length18

Characters and Unicode

Total characters8826
Distinct characters126
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)96.2%

Sample

1st row충청남도 홍성군 홍성읍 문화로176번길 21. 2층
2nd row충청남도 홍성군 홍성읍 충서로1707번길 366-2
3rd row충청남도 홍성군 홍성읍 문화로80번길 32-14(관리사무실 1층)
4th row충청남도 홍성군 홍성읍 조양로202번길 11
5th row충청남도 홍성군 홍성읍 의사로57번길 14-1
ValueCountFrequency (%)
충청남도 371
20.0%
홍성군 371
20.0%
홍성읍 58
 
3.1%
광천읍 43
 
2.3%
홍북읍 39
 
2.1%
홍동면 35
 
1.9%
장곡면 34
 
1.8%
갈산면 31
 
1.7%
서부면 30
 
1.6%
금마면 28
 
1.5%
Other values (569) 815
43.9%
2024-01-10T06:35:57.698178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1487
16.8%
홍 577
 
6.5%
성 470
 
5.3%
남 456
 
5.2%
충 412
 
4.7%
1 376
 
4.3%
청 376
 
4.3%
도 375
 
4.2%
군 371
 
4.2%
길 342
 
3.9%
Other values (116) 3584
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5455
61.8%
Decimal Number 1753
 
19.9%
Space Separator 1487
 
16.8%
Dash Punctuation 112
 
1.3%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Uppercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 577
 
10.6%
성 470
 
8.6%
남 456
 
8.4%
충 412
 
7.6%
청 376
 
6.9%
도 375
 
6.9%
군 371
 
6.8%
길 342
 
6.3%
로 264
 
4.8%
번 235
 
4.3%
Other values (99) 1577
28.9%
Decimal Number
ValueCountFrequency (%)
1 376
21.4%
2 203
11.6%
3 198
11.3%
4 173
9.9%
5 166
9.5%
7 153
8.7%
6 142
 
8.1%
9 117
 
6.7%
8 117
 
6.7%
0 108
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
1487
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5455
61.8%
Common 3369
38.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 577
 
10.6%
성 470
 
8.6%
남 456
 
8.4%
충 412
 
7.6%
청 376
 
6.9%
도 375
 
6.9%
군 371
 
6.8%
길 342
 
6.3%
로 264
 
4.8%
번 235
 
4.3%
Other values (99) 1577
28.9%
Common
ValueCountFrequency (%)
1487
44.1%
1 376
 
11.2%
2 203
 
6.0%
3 198
 
5.9%
4 173
 
5.1%
5 166
 
4.9%
7 153
 
4.5%
6 142
 
4.2%
9 117
 
3.5%
8 117
 
3.5%
Other values (5) 237
 
7.0%
Latin
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5455
61.8%
ASCII 3371
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1487
44.1%
1 376
 
11.2%
2 203
 
6.0%
3 198
 
5.9%
4 173
 
5.1%
5 166
 
4.9%
7 153
 
4.5%
6 142
 
4.2%
9 117
 
3.5%
8 117
 
3.5%
Other values (7) 239
 
7.1%
Hangul
ValueCountFrequency (%)
홍 577
 
10.6%
성 470
 
8.6%
남 456
 
8.4%
충 412
 
7.6%
청 376
 
6.9%
도 375
 
6.9%
군 371
 
6.8%
길 342
 
6.3%
로 264
 
4.8%
번 235
 
4.3%
Other values (99) 1577
28.9%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
홍성군청 가정행복과
371 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row홍성군청 가정행복과
2nd row홍성군청 가정행복과
3rd row홍성군청 가정행복과
4th row홍성군청 가정행복과
5th row홍성군청 가정행복과

Common Values

ValueCountFrequency (%)
홍성군청 가정행복과 371
100.0%

Length

2024-01-10T06:35:57.801915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:35:57.875712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홍성군청 371
50.0%
가정행복과 371
50.0%

관리기관전화번호
Text

UNIQUE 

Distinct371
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-10T06:35:58.057173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters4452
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

Unique371 ?
Unique (%)100.0%

Sample

1st row041-630-1958
2nd row041-630-1959
3rd row041-630-1960
4th row041-630-1961
5th row041-630-1962
ValueCountFrequency (%)
041-630-1958 1
 
0.3%
041-630-2201 1
 
0.3%
041-630-2211 1
 
0.3%
041-630-2210 1
 
0.3%
041-630-2209 1
 
0.3%
041-630-2208 1
 
0.3%
041-630-2207 1
 
0.3%
041-630-2206 1
 
0.3%
041-630-2205 1
 
0.3%
041-630-2204 1
 
0.3%
Other values (361) 361
97.3%
2024-01-10T06:35:58.369246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 919
20.6%
- 742
16.7%
1 590
13.3%
2 505
11.3%
3 467
10.5%
6 448
10.1%
4 438
9.8%
9 119
 
2.7%
8 78
 
1.8%
7 77
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3710
83.3%
Dash Punctuation 742
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 919
24.8%
1 590
15.9%
2 505
13.6%
3 467
12.6%
6 448
12.1%
4 438
11.8%
9 119
 
3.2%
8 78
 
2.1%
7 77
 
2.1%
5 69
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 742
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 919
20.6%
- 742
16.7%
1 590
13.3%
2 505
11.3%
3 467
10.5%
6 448
10.1%
4 438
9.8%
9 119
 
2.7%
8 78
 
1.8%
7 77
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 919
20.6%
- 742
16.7%
1 590
13.3%
2 505
11.3%
3 467
10.5%
6 448
10.1%
4 438
9.8%
9 119
 
2.7%
8 78
 
1.8%
7 77
 
1.7%

데이터등록일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2022-09-30 00:00:00
Maximum2022-09-30 00:00:00
2024-01-10T06:35:58.458410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:58.527135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T06:35:55.548881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:55.410986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:55.617704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:35:55.484490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:35:58.580835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면회원수
연번1.0000.9360.000
읍면0.9361.0000.184
회원수0.0000.1841.000
2024-01-10T06:35:58.647337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번회원수읍면
연번1.000-0.0390.761
회원수-0.0391.0000.086
읍면0.7610.0861.000

Missing values

2024-01-10T06:35:55.701078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:35:55.817715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번읍면경로당 명칭회원수소재지도로명주소관리기관명관리기관전화번호데이터등록일자
01홍성읍홍성읍분회(남)29충청남도 홍성군 홍성읍 문화로176번길 21. 2층홍성군청 가정행복과041-630-19582022-09-30
12홍성읍가좌동34충청남도 홍성군 홍성읍 충서로1707번길 366-2홍성군청 가정행복과041-630-19592022-09-30
23홍성읍경성아파트41충청남도 홍성군 홍성읍 문화로80번길 32-14(관리사무실 1층)홍성군청 가정행복과041-630-19602022-09-30
34홍성읍고암4구31충청남도 홍성군 홍성읍 조양로202번길 11홍성군청 가정행복과041-630-19612022-09-30
45홍성읍광경동24충청남도 홍성군 홍성읍 의사로57번길 14-1홍성군청 가정행복과041-630-19622022-09-30
56홍성읍교동53충청남도 홍성군 홍성읍 충서로1575번길 100홍성군청 가정행복과041-630-19632022-09-30
67홍성읍구룡리 동구43충청남도 홍성군 홍성읍 충절로810번길 18홍성군청 가정행복과041-630-19642022-09-30
78홍성읍남문동62충청남도 홍성군 홍성읍 조양로10번길 76홍성군청 가정행복과041-630-19652022-09-30
89홍성읍남산52충청남도 홍성군 홍성읍 충서로1159번길 18-5홍성군청 가정행복과041-630-19662022-09-30
910홍성읍남장2구41충청남도 홍성군 홍성읍 남장중로 63-7홍성군청 가정행복과041-630-19672022-09-30
연번읍면경로당 명칭회원수소재지도로명주소관리기관명관리기관전화번호데이터등록일자
361362구항면외중30충청남도 홍성군 구항면 구항남길 456-15홍성군청 가정행복과041-630-23192022-09-30
362363구항면장양59충청남도 홍성군 구항면 구항서길100번길 2-3홍성군청 가정행복과041-630-23202022-09-30
363364구항면지석39충청남도 홍성군 구항면 거북로 202홍성군청 가정행복과041-630-23212022-09-30
364365구항면척괴51충청남도 홍성군 구항면 충서로726번길 142홍성군청 가정행복과041-630-23222022-09-30
365366구항면청광64충청남도 홍성군 구항면 충서로877번길 30홍성군청 가정행복과041-630-23232022-09-30
366367구항면태봉51충청남도 홍성군 구항면 구항남길 544홍성군청 가정행복과041-630-23242022-09-30
367368구항면하대51충청남도 홍성군 구항면 구항길193번길 76홍성군청 가정행복과041-630-23252022-09-30
368369구항면화리43충청남도 홍성군 구항면 내포로686번길 240홍성군청 가정행복과041-630-23262022-09-30
369370구항면화산43충청남도 홍성군 구항면 거북로 440홍성군청 가정행복과041-630-23272022-09-30
370371구항면황곡76충청남도 홍성군 구항면 구항길240번길 23홍성군청 가정행복과041-630-23282022-09-30