Overview

Dataset statistics

Number of variables5
Number of observations36
Missing cells29
Missing cells (%)16.1%
Duplicate rows1
Duplicate rows (%)2.8%
Total size in memory1.5 KiB
Average record size in memory43.7 B

Variable types

Text4
Categorical1

Dataset

Description서천군 공동주택(아파트) 현황으로 아파트명(단지명), 주소, 관리사무소 전화번호, 팩스번호를 제공하고 있습니다
Author충청남도 서천군
URLhttps://www.data.go.kr/data/15080855/fileData.do

Alerts

Dataset has 1 (2.8%) duplicate rowsDuplicates
아파트명(단지명) has 7 (19.4%) missing valuesMissing
주소 has 7 (19.4%) missing valuesMissing
관리사무소연락처 has 7 (19.4%) missing valuesMissing
팩스번호 has 8 (22.2%) missing valuesMissing

Reproduction

Analysis started2024-04-19 05:48:27.685124
Analysis finished2024-04-19 05:48:28.163897
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명(단지명)
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing7
Missing (%)19.4%
Memory size420.0 B
2024-04-19T14:48:28.293402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.862069
Min length4

Characters and Unicode

Total characters228
Distinct characters77
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

Unique29 ?
Unique (%)100.0%

Sample

1st row명기주택 가동
2nd row영흥맨션
3rd row신흥아파트
4th rowLS메탈사원아파트
5th row금강아파트
ValueCountFrequency (%)
한전아파트 2
 
6.5%
영흥맨션 1
 
3.2%
서천사곡휴먼시아아파트 1
 
3.2%
꿈비채아파트 1
 
3.2%
장항성주lh천년나무아파트 1
 
3.2%
서천장항lh1단지아파트 1
 
3.2%
골든팰리스아파트 1
 
3.2%
장항이테크더리브아파트 1
 
3.2%
장항더포레아파트 1
 
3.2%
서천코아루천년가아파트 1
 
3.2%
Other values (20) 20
64.5%
2024-04-19T14:48:28.640213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 29
 
12.7%
파 25
 
11.0%
트 25
 
11.0%
천 12
 
5.3%
장 6
 
2.6%
항 6
 
2.6%
산 5
 
2.2%
서 4
 
1.8%
빌 4
 
1.8%
시 4
 
1.8%
Other values (67) 108
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
94.7%
Uppercase Letter 6
 
2.6%
Decimal Number 4
 
1.8%
Space Separator 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 29
 
13.4%
파 25
 
11.6%
트 25
 
11.6%
천 12
 
5.6%
장 6
 
2.8%
항 6
 
2.8%
산 5
 
2.3%
서 4
 
1.9%
빌 4
 
1.9%
시 4
 
1.9%
Other values (59) 96
44.4%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
8 1
25.0%
2 1
25.0%
3 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
L 3
50.0%
H 2
33.3%
S 1
 
16.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
94.7%
Latin 6
 
2.6%
Common 6
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 29
 
13.4%
파 25
 
11.6%
트 25
 
11.6%
천 12
 
5.6%
장 6
 
2.8%
항 6
 
2.8%
산 5
 
2.3%
서 4
 
1.9%
빌 4
 
1.9%
시 4
 
1.9%
Other values (59) 96
44.4%
Common
ValueCountFrequency (%)
2
33.3%
1 1
16.7%
8 1
16.7%
2 1
16.7%
3 1
16.7%
Latin
ValueCountFrequency (%)
L 3
50.0%
H 2
33.3%
S 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
94.7%
ASCII 12
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 29
 
13.4%
파 25
 
11.6%
트 25
 
11.6%
천 12
 
5.6%
장 6
 
2.8%
항 6
 
2.8%
산 5
 
2.3%
서 4
 
1.9%
빌 4
 
1.9%
시 4
 
1.9%
Other values (59) 96
44.4%
ASCII
ValueCountFrequency (%)
L 3
25.0%
2
16.7%
H 2
16.7%
1 1
 
8.3%
S 1
 
8.3%
8 1
 
8.3%
2 1
 
8.3%
3 1
 
8.3%

주소
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing7
Missing (%)19.4%
Memory size420.0 B
2024-04-19T14:48:28.879414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length21.758621
Min length19

Characters and Unicode

Total characters631
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row충청남도 서천군 장항읍 창선2리 366-4
2nd row충청남도 서천군 장항읍 신창리 243-50
3rd row충청남도 서천군 장항읍 화천리 303-7.305-2,5
4th row충청남도 서천군 장항읍 화천리 431
5th row충청남도 서천군 장항읍 성주리 278-2
ValueCountFrequency (%)
서천군 30
20.4%
충청남도 29
19.7%
서천읍 13
 
8.8%
장항읍 13
 
8.8%
사곡리 9
 
6.1%
창선2리 3
 
2.0%
원수리 3
 
2.0%
군사리 3
 
2.0%
화천리 2
 
1.4%
13 1
 
0.7%
Other values (41) 41
27.9%
2024-04-19T14:48:29.246711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
19.0%
천 47
 
7.4%
서 45
 
7.1%
군 33
 
5.2%
충 30
 
4.8%
도 30
 
4.8%
남 29
 
4.6%
청 29
 
4.6%
읍 26
 
4.1%
리 25
 
4.0%
Other values (38) 217
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 384
60.9%
Space Separator 120
 
19.0%
Decimal Number 111
 
17.6%
Dash Punctuation 14
 
2.2%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 47
12.2%
서 45
11.7%
군 33
8.6%
충 30
 
7.8%
도 30
 
7.8%
남 29
 
7.6%
청 29
 
7.6%
읍 26
 
6.8%
리 25
 
6.5%
항 14
 
3.6%
Other values (24) 76
19.8%
Decimal Number
ValueCountFrequency (%)
3 22
19.8%
1 17
15.3%
8 11
9.9%
2 11
9.9%
0 10
9.0%
7 10
9.0%
5 9
8.1%
6 8
 
7.2%
4 7
 
6.3%
9 6
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 384
60.9%
Common 247
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 47
12.2%
서 45
11.7%
군 33
8.6%
충 30
 
7.8%
도 30
 
7.8%
남 29
 
7.6%
청 29
 
7.6%
읍 26
 
6.8%
리 25
 
6.5%
항 14
 
3.6%
Other values (24) 76
19.8%
Common
ValueCountFrequency (%)
120
48.6%
3 22
 
8.9%
1 17
 
6.9%
- 14
 
5.7%
8 11
 
4.5%
2 11
 
4.5%
0 10
 
4.0%
7 10
 
4.0%
5 9
 
3.6%
6 8
 
3.2%
Other values (4) 15
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 384
60.9%
ASCII 247
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
48.6%
3 22
 
8.9%
1 17
 
6.9%
- 14
 
5.7%
8 11
 
4.5%
2 11
 
4.5%
0 10
 
4.0%
7 10
 
4.0%
5 9
 
3.6%
6 8
 
3.2%
Other values (4) 15
 
6.1%
Hangul
ValueCountFrequency (%)
천 47
12.2%
서 45
11.7%
군 33
8.6%
충 30
 
7.8%
도 30
 
7.8%
남 29
 
7.6%
청 29
 
7.6%
읍 26
 
6.8%
리 25
 
6.5%
항 14
 
3.6%
Other values (24) 76
19.8%

관리사무소연락처
Text

MISSING 

Distinct24
Distinct (%)82.8%
Missing7
Missing (%)19.4%
Memory size420.0 B
2024-04-19T14:48:29.416759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.310345
Min length2

Characters and Unicode

Total characters299
Distinct characters14
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

Unique23 ?
Unique (%)79.3%

Sample

1st row없음
2nd row041-956-5188
3rd row041-956-3807
4th row041-955-3202
5th row041- 956-7159
ValueCountFrequency (%)
없음 6
 
20.0%
041-952-3556 1
 
3.3%
041-956-3807 1
 
3.3%
041-952-3246 1
 
3.3%
041-631-2983 1
 
3.3%
041-957-0314 1
 
3.3%
041-957-1007 1
 
3.3%
041-956-2886 1
 
3.3%
041-956-7589 1
 
3.3%
041-951-1405 1
 
3.3%
Other values (15) 15
50.0%
2024-04-19T14:48:29.733655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 46
15.4%
1 37
12.4%
5 35
11.7%
0 34
11.4%
4 30
10.0%
9 29
9.7%
6 15
 
5.0%
3 14
 
4.7%
2 13
 
4.3%
7 12
 
4.0%
Other values (4) 34
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
76.9%
Dash Punctuation 46
 
15.4%
Other Letter 12
 
4.0%
Space Separator 11
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
16.1%
5 35
15.2%
0 34
14.8%
4 30
13.0%
9 29
12.6%
6 15
6.5%
3 14
 
6.1%
2 13
 
5.7%
7 12
 
5.2%
8 11
 
4.8%
Other Letter
ValueCountFrequency (%)
없 6
50.0%
음 6
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 287
96.0%
Hangul 12
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 46
16.0%
1 37
12.9%
5 35
12.2%
0 34
11.8%
4 30
10.5%
9 29
10.1%
6 15
 
5.2%
3 14
 
4.9%
2 13
 
4.5%
7 12
 
4.2%
Other values (2) 22
7.7%
Hangul
ValueCountFrequency (%)
없 6
50.0%
음 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 287
96.0%
Hangul 12
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 46
16.0%
1 37
12.9%
5 35
12.2%
0 34
11.8%
4 30
10.5%
9 29
10.1%
6 15
 
5.2%
3 14
 
4.9%
2 13
 
4.5%
7 12
 
4.2%
Other values (2) 22
7.7%
Hangul
ValueCountFrequency (%)
없 6
50.0%
음 6
50.0%

팩스번호
Text

MISSING 

Distinct22
Distinct (%)78.6%
Missing8
Missing (%)22.2%
Memory size420.0 B
2024-04-19T14:48:29.927006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.8214286
Min length2

Characters and Unicode

Total characters275
Distinct characters14
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

Unique21 ?
Unique (%)75.0%

Sample

1st row없음
2nd row041-956-5188
3rd row041-965-6185
4th row041-955-3207
5th row041-956-0383
ValueCountFrequency (%)
없음 7
25.0%
041-953-0157 1
 
3.6%
041-952-3244 1
 
3.6%
041-956-1006 1
 
3.6%
041-956-2885 1
 
3.6%
041-956-8589 1
 
3.6%
041-951-1406 1
 
3.6%
041-952-1024 1
 
3.6%
041-953-8063 1
 
3.6%
041-951-3302 1
 
3.6%
Other values (12) 12
42.9%
2024-04-19T14:48:30.221489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
15.3%
1 32
11.6%
0 31
11.3%
4 29
10.5%
5 29
10.5%
9 25
9.1%
3 15
 
5.5%
6 15
 
5.5%
2 14
 
5.1%
7 10
 
3.6%
Other values (4) 33
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
76.4%
Dash Punctuation 42
 
15.3%
Other Letter 14
 
5.1%
Space Separator 9
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
15.2%
0 31
14.8%
4 29
13.8%
5 29
13.8%
9 25
11.9%
3 15
7.1%
6 15
7.1%
2 14
6.7%
7 10
 
4.8%
8 10
 
4.8%
Other Letter
ValueCountFrequency (%)
없 7
50.0%
음 7
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 261
94.9%
Hangul 14
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.1%
1 32
12.3%
0 31
11.9%
4 29
11.1%
5 29
11.1%
9 25
9.6%
3 15
 
5.7%
6 15
 
5.7%
2 14
 
5.4%
7 10
 
3.8%
Other values (2) 19
7.3%
Hangul
ValueCountFrequency (%)
없 7
50.0%
음 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261
94.9%
Hangul 14
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.1%
1 32
12.3%
0 31
11.9%
4 29
11.1%
5 29
11.1%
9 25
9.6%
3 15
 
5.7%
6 15
 
5.7%
2 14
 
5.4%
7 10
 
3.8%
Other values (2) 19
7.3%
Hangul
ValueCountFrequency (%)
없 7
50.0%
음 7
50.0%

데이터기준일자
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-11-30
29 
<NA>
7 

Length

Max length10
Median length10
Mean length8.8333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 29
80.6%
<NA> 7
 
19.4%

Length

2024-04-19T14:48:30.373436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:48:30.479485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 29
80.6%
na 7
 
19.4%

Correlations

2024-04-19T14:48:30.547815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트명(단지명)주소관리사무소연락처팩스번호
아파트명(단지명)1.0001.0001.0001.000
주소1.0001.0001.0001.000
관리사무소연락처1.0001.0001.0001.000
팩스번호1.0001.0001.0001.000

Missing values

2024-04-19T14:48:27.905849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:48:27.996943image/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.
2024-04-19T14:48:28.097465image/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

아파트명(단지명)주소관리사무소연락처팩스번호데이터기준일자
0명기주택 가동충청남도 서천군 장항읍 창선2리 366-4없음없음2023-11-30
1영흥맨션충청남도 서천군 장항읍 신창리 243-50041-956-5188041-956-51882023-11-30
2신흥아파트충청남도 서천군 장항읍 화천리 303-7.305-2,5041-956-3807041-965-61852023-11-30
3LS메탈사원아파트충청남도 서천군 장항읍 화천리 431041-955-3202041-955-32072023-11-30
4금강아파트충청남도 서천군 장항읍 성주리 278-2041- 956-7159041-956-03832023-11-30
5임해아파트충청남도 서천군 장항읍 원수리 207041-956-5575<NA>2023-11-30
6장항원수휴먼시아아파트충청남도 서천군 장항읍 원수리 907041-957-0746041-956-27722023-11-30
7장항원수천산아파트충청남도 서천군 장항읍 원수리 1028041-956-1115041-956-27492023-11-30
8제일아파트충청남도 서천군 서천읍 군사리 693-1041-952-6795041-952-67952023-11-30
9남부주택충청남도 서천군 서천읍 군사리 715-17없음없음2023-11-30
아파트명(단지명)주소관리사무소연락처팩스번호데이터기준일자
26서천장항LH1단지아파트충청남도 서천군 장항읍 장항산단1길 60041-957-1007041-956-10062023-11-30
27장항성주LH천년나무아파트충청남도 서천군 서천군 장항읍 성주새길 8041-957-0314041-957-03132023-11-30
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아파트명(단지명)주소관리사무소연락처팩스번호데이터기준일자# duplicates
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