Overview

Dataset statistics

Number of variables4
Number of observations1475
Missing cells1066
Missing cells (%)18.1%
Duplicate rows9
Duplicate rows (%)0.6%
Total size in memory46.2 KiB
Average record size in memory32.1 B

Variable types

Categorical1
Text3

Dataset

Description전라남도 내(목포, 여수, 순천, 나주, 광양, 담양 등 22개 시군, 1475개소) 폐의약품 수거함 현황에 대한 정보를 제공합니다
Author전라남도
URLhttps://www.data.go.kr/data/15113201/fileData.do

Alerts

Dataset has 9 (0.6%) duplicate rowsDuplicates
비고 has 1066 (72.3%) missing valuesMissing

Reproduction

Analysis started2024-03-15 00:26:23.986582
Analysis finished2024-03-15 00:26:25.234043
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Categorical

Distinct20
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
강진군
336 
순천시
173 
목포시
120 
나주시
115 
고흥군
75 
Other values (15)
656 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강진군 336
22.8%
순천시 173
11.7%
목포시 120
 
8.1%
나주시 115
 
7.8%
고흥군 75
 
5.1%
광양시 73
 
4.9%
여수시 68
 
4.6%
화순군 59
 
4.0%
신안군 51
 
3.5%
장성군 49
 
3.3%
Other values (10) 356
24.1%

Length

2024-03-15T09:26:25.455574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강진군 336
22.8%
순천시 173
11.7%
목포시 120
 
8.1%
나주시 115
 
7.8%
고흥군 75
 
5.1%
광양시 73
 
4.9%
여수시 68
 
4.6%
화순군 59
 
4.0%
신안군 51
 
3.5%
장성군 49
 
3.3%
Other values (10) 356
24.1%

설치장소
Text

Distinct1310
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2024-03-15T09:26:26.580639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.3111864
Min length2

Characters and Unicode

Total characters7834
Distinct characters378
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1207 ?
Unique (%)81.8%

Sample

1st row목포시보건소
2nd row하당보건지소
3rd row목포산정약국
4th row이로약국
5th row포도나무약국
ValueCountFrequency (%)
행정복지센터 54
 
3.3%
보건소 17
 
1.1%
보건진료소 15
 
0.9%
약국 14
 
0.9%
건강약국 11
 
0.7%
우리약국 9
 
0.6%
하나로약국 8
 
0.5%
조은약국 8
 
0.5%
앞 6
 
0.4%
호남약국 6
 
0.4%
Other values (1312) 1467
90.8%
2024-03-15T09:26:28.187635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 582
 
7.4%
약 563
 
7.2%
소 498
 
6.4%
건 481
 
6.1%
보 475
 
6.1%
진 298
 
3.8%
료 260
 
3.3%
지 258
 
3.3%
141
 
1.8%
동 134
 
1.7%
Other values (368) 4144
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7616
97.2%
Space Separator 141
 
1.8%
Decimal Number 41
 
0.5%
Uppercase Letter 13
 
0.2%
Other Punctuation 6
 
0.1%
Lowercase Letter 6
 
0.1%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 582
 
7.6%
약 563
 
7.4%
소 498
 
6.5%
건 481
 
6.3%
보 475
 
6.2%
진 298
 
3.9%
료 260
 
3.4%
지 258
 
3.4%
동 134
 
1.8%
정 98
 
1.3%
Other values (349) 3969
52.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
16.7%
r 1
16.7%
o 1
16.7%
t 1
16.7%
s 1
16.7%
w 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 14
34.1%
2 13
31.7%
3 6
14.6%
6 4
 
9.8%
5 4
 
9.8%
Uppercase Letter
ValueCountFrequency (%)
H 5
38.5%
L 5
38.5%
S 3
23.1%
Space Separator
ValueCountFrequency (%)
141
100.0%
Other Punctuation
ValueCountFrequency (%)
? 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7616
97.2%
Common 199
 
2.5%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 582
 
7.6%
약 563
 
7.4%
소 498
 
6.5%
건 481
 
6.3%
보 475
 
6.2%
진 298
 
3.9%
료 260
 
3.4%
지 258
 
3.4%
동 134
 
1.8%
정 98
 
1.3%
Other values (349) 3969
52.1%
Common
ValueCountFrequency (%)
141
70.9%
1 14
 
7.0%
2 13
 
6.5%
? 6
 
3.0%
3 6
 
3.0%
) 5
 
2.5%
( 5
 
2.5%
6 4
 
2.0%
5 4
 
2.0%
- 1
 
0.5%
Latin
ValueCountFrequency (%)
H 5
26.3%
L 5
26.3%
S 3
15.8%
e 1
 
5.3%
r 1
 
5.3%
o 1
 
5.3%
t 1
 
5.3%
s 1
 
5.3%
w 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7616
97.2%
ASCII 218
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 582
 
7.6%
약 563
 
7.4%
소 498
 
6.5%
건 481
 
6.3%
보 475
 
6.2%
진 298
 
3.9%
료 260
 
3.4%
지 258
 
3.4%
동 134
 
1.8%
정 98
 
1.3%
Other values (349) 3969
52.1%
ASCII
ValueCountFrequency (%)
141
64.7%
1 14
 
6.4%
2 13
 
6.0%
? 6
 
2.8%
3 6
 
2.8%
) 5
 
2.3%
( 5
 
2.3%
H 5
 
2.3%
L 5
 
2.3%
6 4
 
1.8%
Other values (9) 14
 
6.4%

도로명주소
Text

Distinct1448
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2024-03-15T09:26:29.511060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length20.720678
Min length8

Characters and Unicode

Total characters30563
Distinct characters359
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1421 ?
Unique (%)96.3%

Sample

1st row전라남도 목포시 원산로 45번길 5
2nd row전라남도 목포시 석현로 48
3rd row전라남도 목포시 양을로 151, 1층 (산정동)
4th row전라남도 목포시 송림로 73, 2층 (용해동)
5th row전라남도 목포시 비파로 106, 삼성전자사옥 1층 (상동)
ValueCountFrequency (%)
전라남도 1363
 
18.9%
강진군 302
 
4.2%
순천시 173
 
2.4%
목포시 120
 
1.7%
나주시 114
 
1.6%
1층 84
 
1.2%
광양시 73
 
1.0%
여수시 68
 
0.9%
고흥군 59
 
0.8%
화순군 58
 
0.8%
Other values (2074) 4800
66.5%
2024-03-15T09:26:31.332289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5796
 
19.0%
도 1589
 
5.2%
전 1470
 
4.8%
남 1465
 
4.8%
라 1374
 
4.5%
1 1098
 
3.6%
군 890
 
2.9%
면 794
 
2.6%
길 753
 
2.5%
로 717
 
2.3%
Other values (349) 14617
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19404
63.5%
Space Separator 5796
 
19.0%
Decimal Number 4229
 
13.8%
Open Punctuation 335
 
1.1%
Close Punctuation 335
 
1.1%
Dash Punctuation 318
 
1.0%
Other Punctuation 139
 
0.5%
Uppercase Letter 5
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1589
 
8.2%
전 1470
 
7.6%
남 1465
 
7.5%
라 1374
 
7.1%
군 890
 
4.6%
면 794
 
4.1%
길 753
 
3.9%
로 717
 
3.7%
시 577
 
3.0%
동 523
 
2.7%
Other values (328) 9252
47.7%
Decimal Number
ValueCountFrequency (%)
1 1098
26.0%
2 558
13.2%
3 426
 
10.1%
5 365
 
8.6%
4 334
 
7.9%
7 325
 
7.7%
6 310
 
7.3%
8 287
 
6.8%
0 264
 
6.2%
9 262
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
B 1
20.0%
S 1
20.0%
M 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 126
90.6%
? 13
 
9.4%
Space Separator
ValueCountFrequency (%)
5796
100.0%
Open Punctuation
ValueCountFrequency (%)
( 335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 335
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 318
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19404
63.5%
Common 11154
36.5%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1589
 
8.2%
전 1470
 
7.6%
남 1465
 
7.5%
라 1374
 
7.1%
군 890
 
4.6%
면 794
 
4.1%
길 753
 
3.9%
로 717
 
3.7%
시 577
 
3.0%
동 523
 
2.7%
Other values (328) 9252
47.7%
Common
ValueCountFrequency (%)
5796
52.0%
1 1098
 
9.8%
2 558
 
5.0%
3 426
 
3.8%
5 365
 
3.3%
( 335
 
3.0%
) 335
 
3.0%
4 334
 
3.0%
7 325
 
2.9%
- 318
 
2.9%
Other values (7) 1264
 
11.3%
Latin
ValueCountFrequency (%)
A 2
40.0%
B 1
20.0%
S 1
20.0%
M 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19404
63.5%
ASCII 11159
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5796
51.9%
1 1098
 
9.8%
2 558
 
5.0%
3 426
 
3.8%
5 365
 
3.3%
( 335
 
3.0%
) 335
 
3.0%
4 334
 
3.0%
7 325
 
2.9%
- 318
 
2.8%
Other values (11) 1269
 
11.4%
Hangul
ValueCountFrequency (%)
도 1589
 
8.2%
전 1470
 
7.6%
남 1465
 
7.5%
라 1374
 
7.1%
군 890
 
4.6%
면 794
 
4.1%
길 753
 
3.9%
로 717
 
3.7%
시 577
 
3.0%
동 523
 
2.7%
Other values (328) 9252
47.7%

비고
Text

MISSING 

Distinct61
Distinct (%)14.9%
Missing1066
Missing (%)72.3%
Memory size11.6 KiB
2024-03-15T09:26:32.373399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length3
Mean length4.6234719
Min length2

Characters and Unicode

Total characters1891
Distinct characters72
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

Unique57 ?
Unique (%)13.9%

Sample

1st row110동 안 관리사무소
2nd row관리사무소 내
3rd row관리사무소 내
4th row관리사무소 출입문 사이
5th row관리동1층(203동 커뮤니티1층)
ValueCountFrequency (%)
경로당 336
66.4%
우체통(우체통 28
 
5.5%
관리사무소 22
 
4.3%
번호 22
 
4.3%
내 8
 
1.6%
앞 5
 
1.0%
옆 5
 
1.0%
분리수거장 4
 
0.8%
경비실 4
 
0.8%
관리동 3
 
0.6%
Other values (67) 69
 
13.6%
2024-03-15T09:26:33.703369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 341
18.0%
로 338
17.9%
당 336
17.8%
100
 
5.3%
우 56
 
3.0%
체 56
 
3.0%
통 56
 
3.0%
1 53
 
2.8%
리 38
 
2.0%
) 37
 
2.0%
Other values (62) 480
25.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1518
80.3%
Decimal Number 183
 
9.7%
Space Separator 100
 
5.3%
Close Punctuation 37
 
2.0%
Open Punctuation 37
 
2.0%
Dash Punctuation 16
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 341
22.5%
로 338
22.3%
당 336
22.1%
우 56
 
3.7%
체 56
 
3.7%
통 56
 
3.7%
리 38
 
2.5%
관 34
 
2.2%
사 32
 
2.1%
무 31
 
2.0%
Other values (48) 200
13.2%
Decimal Number
ValueCountFrequency (%)
1 53
29.0%
0 31
16.9%
6 22
12.0%
2 21
 
11.5%
8 19
 
10.4%
3 13
 
7.1%
5 8
 
4.4%
9 7
 
3.8%
4 5
 
2.7%
7 4
 
2.2%
Space Separator
ValueCountFrequency (%)
100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1518
80.3%
Common 373
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 341
22.5%
로 338
22.3%
당 336
22.1%
우 56
 
3.7%
체 56
 
3.7%
통 56
 
3.7%
리 38
 
2.5%
관 34
 
2.2%
사 32
 
2.1%
무 31
 
2.0%
Other values (48) 200
13.2%
Common
ValueCountFrequency (%)
100
26.8%
1 53
14.2%
) 37
 
9.9%
( 37
 
9.9%
0 31
 
8.3%
6 22
 
5.9%
2 21
 
5.6%
8 19
 
5.1%
- 16
 
4.3%
3 13
 
3.5%
Other values (4) 24
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1518
80.3%
ASCII 373
 
19.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 341
22.5%
로 338
22.3%
당 336
22.1%
우 56
 
3.7%
체 56
 
3.7%
통 56
 
3.7%
리 38
 
2.5%
관 34
 
2.2%
사 32
 
2.1%
무 31
 
2.0%
Other values (48) 200
13.2%
ASCII
ValueCountFrequency (%)
100
26.8%
1 53
14.2%
) 37
 
9.9%
( 37
 
9.9%
0 31
 
8.3%
6 22
 
5.9%
2 21
 
5.6%
8 19
 
5.1%
- 16
 
4.3%
3 13
 
3.5%
Other values (4) 24
 
6.4%

Correlations

2024-03-15T09:26:33.959666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군비고
시군1.0001.000
비고1.0001.000

Missing values

2024-03-15T09:26:24.827127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:26:25.120034image/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

시군설치장소도로명주소비고
0목포시목포시보건소전라남도 목포시 원산로 45번길 5<NA>
1목포시하당보건지소전라남도 목포시 석현로 48<NA>
2목포시목포산정약국전라남도 목포시 양을로 151, 1층 (산정동)<NA>
3목포시이로약국전라남도 목포시 송림로 73, 2층 (용해동)<NA>
4목포시포도나무약국전라남도 목포시 비파로 106, 삼성전자사옥 1층 (상동)<NA>
5목포시다온약국전라남도 목포시 용당로 211, 1층 (용당동)<NA>
6목포시보라약국전라남도 목포시 백년대로 258, 1층 (상동)<NA>
7목포시대진약국전라남도 목포시 용당로 281, 종원빌딩 (용해동)<NA>
8목포시수약국전라남도 목포시 원형서로 15, 롯데마트목포점 (상동)<NA>
9목포시대림약국전라남도 목포시 산대로2번길 2, 1층 (산정동)<NA>
시군설치장소도로명주소비고
1465신안군지도중앙 약국전라남도 신안군 지도읍 봉리길 16-1<NA>
1466신안군지도행복 약국전라남도 신안군 지도읍 봉리길 3<NA>
1467신안군천사 약국전라남도 신안군 압해읍 압해로 872<NA>
1468신안군압해종로 약국전라남도 신안군 압해읍 압해로 869<NA>
1469신안군유한 약국전라남도 신안군 임자면 임자로 146<NA>
1470신안군신안 약국전라남도 신안군 자은면 구영2길 46<NA>
1471신안군세명 약국전라남도 신안군 비금면 송치길 155-19<NA>
1472신안군녹십자 약국전라남도 신안군 흑산면 예리1길 68-4<NA>
1473신안군대창 약국전라남도 신안군 안좌면 중부로 852<NA>
1474신안군구영 약국전라남도 신안군 암태면 중부로 1820-4<NA>

Duplicate rows

Most frequently occurring

시군설치장소도로명주소비고# duplicates
0강진군내동전라남도 강진군 작천면 작천내동길 65경로당2
1강진군대곡전라남도 강진군 옴천면 옴천대곡길 71경로당2
2강진군벽송전라남도 강진군 칠량면 벽송길 2경로당2
3강진군부춘전라남도 강진군 강진읍 지전부춘길 20경로당2
4강진군신기전라남도 강진군 성전면 성전신기2길 6경로당2
5강진군신리전라남도 강진군 군동면 신리길 10-6경로당2
6강진군신흥전라남도 강진군 신전면 신흥길 54경로당2
7강진군용정전라남도 강진군 작천면 용상리 153번지 1호경로당2
8강진군월남전라남도 강진군 성전면 월남리 887경로당2