Overview

Dataset statistics

Number of variables4
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory804.0 B
Average record size in memory38.3 B

Variable types

Text3
DateTime1

Dataset

Description대전광역시 중구 폐의약품 수거함 현황 (구분, 주소지, 전화번호, 데이터 기준일자) 정보를 제공합니다. 수거함은 가까운 약국에도 설치가 되어 있지만 설치되어 있는 약국 정보를 보유하고 있지 않아 보유 자료만 제공하는 것을 양해 부탁드립니다.
URLhttps://www.data.go.kr/data/15101285/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:51:19.580852
Analysis finished2023-12-12 18:51:20.034469
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T03:51:20.229518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.7619048
Min length5

Characters and Unicode

Total characters184
Distinct characters43
Distinct categories3 ?
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 (%)100.0%

Sample

1st row중구보건소
2nd row중구보건지소
3rd row정생보건진료소
4th row대전 중구청
5th row은행선화동행정복지센터
ValueCountFrequency (%)
중구보건소 1
 
4.5%
중구보건지소 1
 
4.5%
문화2동행정복지센터 1
 
4.5%
문화1동행정복지센터 1
 
4.5%
유천2동행정복지센터 1
 
4.5%
유천1동행정복지센터 1
 
4.5%
태평2동행정복지센터 1
 
4.5%
태평1동행정복지센터 1
 
4.5%
오류동행정복지센터 1
 
4.5%
용두동행정복지센터 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T03:51:20.678859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
행 18
 
9.8%
지 18
 
9.8%
정 18
 
9.8%
터 17
 
9.2%
센 17
 
9.2%
복 17
 
9.2%
동 17
 
9.2%
중 4
 
2.2%
문 3
 
1.6%
1 3
 
1.6%
Other values (33) 52
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 177
96.2%
Decimal Number 6
 
3.3%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
행 18
 
10.2%
지 18
 
10.2%
정 18
 
10.2%
터 17
 
9.6%
센 17
 
9.6%
복 17
 
9.6%
동 17
 
9.6%
중 4
 
2.3%
문 3
 
1.7%
구 3
 
1.7%
Other values (30) 45
25.4%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 177
96.2%
Common 7
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
행 18
 
10.2%
지 18
 
10.2%
정 18
 
10.2%
터 17
 
9.6%
센 17
 
9.6%
복 17
 
9.6%
동 17
 
9.6%
중 4
 
2.3%
문 3
 
1.7%
구 3
 
1.7%
Other values (30) 45
25.4%
Common
ValueCountFrequency (%)
1 3
42.9%
2 3
42.9%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 177
96.2%
ASCII 7
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
행 18
 
10.2%
지 18
 
10.2%
정 18
 
10.2%
터 17
 
9.6%
센 17
 
9.6%
복 17
 
9.6%
동 17
 
9.6%
중 4
 
2.3%
문 3
 
1.7%
구 3
 
1.7%
Other values (30) 45
25.4%
ASCII
ValueCountFrequency (%)
1 3
42.9%
2 3
42.9%
1
 
14.3%

주소지
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T03:51:20.997143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length23.095238
Min length16

Characters and Unicode

Total characters485
Distinct characters65
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

Unique19 ?
Unique (%)90.5%

Sample

1st row대전광역시 중구 뿌리공원로 47 (안영동)
2nd row대전광역시 중구 중앙로 100
3rd row대전광역시 중구 산서로 635
4th row대전광역시 중구 중앙로 100
5th row대전광역시 중구 보문로337번길 33 (선화동)
ValueCountFrequency (%)
대전광역시 21
20.4%
중구 21
20.4%
문화동 2
 
1.9%
태평동 2
 
1.9%
유천동 2
 
1.9%
대종로 2
 
1.9%
중앙로 2
 
1.9%
100 2
 
1.9%
90 1
 
1.0%
당디로6번길 1
 
1.0%
Other values (47) 47
45.6%
2023-12-13T03:51:21.463339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
16.9%
대 29
 
6.0%
중 25
 
5.2%
전 21
 
4.3%
구 21
 
4.3%
로 21
 
4.3%
시 21
 
4.3%
역 21
 
4.3%
광 21
 
4.3%
동 20
 
4.1%
Other values (55) 203
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 287
59.2%
Space Separator 82
 
16.9%
Decimal Number 78
 
16.1%
Close Punctuation 18
 
3.7%
Open Punctuation 18
 
3.7%
Other Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 29
 
10.1%
중 25
 
8.7%
전 21
 
7.3%
구 21
 
7.3%
로 21
 
7.3%
시 21
 
7.3%
역 21
 
7.3%
광 21
 
7.3%
동 20
 
7.0%
번 9
 
3.1%
Other values (40) 78
27.2%
Decimal Number
ValueCountFrequency (%)
3 15
19.2%
1 13
16.7%
0 9
11.5%
6 8
10.3%
5 8
10.3%
2 7
9.0%
7 5
 
6.4%
4 5
 
6.4%
9 5
 
6.4%
8 3
 
3.8%
Space Separator
ValueCountFrequency (%)
82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 287
59.2%
Common 198
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 29
 
10.1%
중 25
 
8.7%
전 21
 
7.3%
구 21
 
7.3%
로 21
 
7.3%
시 21
 
7.3%
역 21
 
7.3%
광 21
 
7.3%
동 20
 
7.0%
번 9
 
3.1%
Other values (40) 78
27.2%
Common
ValueCountFrequency (%)
82
41.4%
) 18
 
9.1%
( 18
 
9.1%
3 15
 
7.6%
1 13
 
6.6%
0 9
 
4.5%
6 8
 
4.0%
5 8
 
4.0%
2 7
 
3.5%
7 5
 
2.5%
Other values (5) 15
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 287
59.2%
ASCII 198
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
41.4%
) 18
 
9.1%
( 18
 
9.1%
3 15
 
7.6%
1 13
 
6.6%
0 9
 
4.5%
6 8
 
4.0%
5 8
 
4.0%
2 7
 
3.5%
7 5
 
2.5%
Other values (5) 15
 
7.6%
Hangul
ValueCountFrequency (%)
대 29
 
10.1%
중 25
 
8.7%
전 21
 
7.3%
구 21
 
7.3%
로 21
 
7.3%
시 21
 
7.3%
역 21
 
7.3%
광 21
 
7.3%
동 20
 
7.0%
번 9
 
3.1%
Other values (40) 78
27.2%

전화번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T03:51:21.680407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row042-288-8000
2nd row042-288-8150
3rd row042-285-0421
4th row042-606-7314
5th row042-288-8400
ValueCountFrequency (%)
042-288-8000 1
 
4.8%
042-288-8630 1
 
4.8%
042-288-8870 1
 
4.8%
042-288-8840 1
 
4.8%
042-288-8810 1
 
4.8%
042-288-8780 1
 
4.8%
042-288-8750 1
 
4.8%
042-288-8720 1
 
4.8%
042-288-8690 1
 
4.8%
042-288-8660 1
 
4.8%
Other values (11) 11
52.4%
2023-12-13T03:51:22.097136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 62
24.6%
0 48
19.0%
2 43
17.1%
- 42
16.7%
4 28
11.1%
6 8
 
3.2%
5 6
 
2.4%
7 6
 
2.4%
1 4
 
1.6%
3 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 62
29.5%
0 48
22.9%
2 43
20.5%
4 28
13.3%
6 8
 
3.8%
5 6
 
2.9%
7 6
 
2.9%
1 4
 
1.9%
3 3
 
1.4%
9 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 62
24.6%
0 48
19.0%
2 43
17.1%
- 42
16.7%
4 28
11.1%
6 8
 
3.2%
5 6
 
2.4%
7 6
 
2.4%
1 4
 
1.6%
3 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 62
24.6%
0 48
19.0%
2 43
17.1%
- 42
16.7%
4 28
11.1%
6 8
 
3.2%
5 6
 
2.4%
7 6
 
2.4%
1 4
 
1.6%
3 3
 
1.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2023-06-16 00:00:00
Maximum2023-06-16 00:00:00
2023-12-13T03:51:22.265651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:51:22.415515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T03:51:22.526507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분주소지전화번호
구분1.0001.0001.000
주소지1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-13T03:51:19.841358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:51:19.984412image/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

구분주소지전화번호데이터기준일자
0중구보건소대전광역시 중구 뿌리공원로 47 (안영동)042-288-80002023-06-16
1중구보건지소대전광역시 중구 중앙로 100042-288-81502023-06-16
2정생보건진료소대전광역시 중구 산서로 635042-285-04212023-06-16
3대전 중구청대전광역시 중구 중앙로 100042-606-73142023-06-16
4은행선화동행정복지센터대전광역시 중구 보문로337번길 33 (선화동)042-288-84002023-06-16
5목동행정복지센터대전광역시 중구 목중로39번길 39 (목동)042-288-84402023-06-16
6중촌동행정복지센터대전광역시 중구 대종로 663-7 (중촌동)042-288-84702023-06-16
7대흥동행정복지센터대전광역시 중구 대흥로 109, 3층 (대흥동)042-288-85002023-06-16
8문창동행정복지센터대전광역시 중구 보문로20번길 38 (문창동)042-288-85302023-06-16
9석교동행정복지센터대전광역시 중구 대종로 228 (석교동)042-288-85602023-06-16
구분주소지전화번호데이터기준일자
11부사동행정복지센터대전광역시 중구 보문로68번길 20 (부사동)042-288-86302023-06-16
12용두동행정복지센터대전광역시 중구 동서대로1322번길 111 (용두동)042-288-86602023-06-16
13오류동행정복지센터대전광역시 중구 오류로 56 (오류동)042-288-86902023-06-16
14태평1동행정복지센터대전광역시 중구 동서대로 1234 (태평동)042-288-87202023-06-16
15태평2동행정복지센터대전광역시 중구 평촌로 51 (태평동)042-288-87502023-06-16
16유천1동행정복지센터대전광역시 중구 계백로1566번길 57 (유천동)042-288-87802023-06-16
17유천2동행정복지센터대전광역시 중구 문화로133번길 55 (유천동)042-288-88102023-06-16
18문화1동행정복지센터대전광역시 중구 문화로 195 (문화동)042-288-88402023-06-16
19문화2동행정복지센터대전광역시 중구 당디로6번길 90 (문화동)042-288-88702023-06-16
20산성동행정복지센터대전광역시 중구 대둔산로 403 (산성동)042-288-89002023-06-16