Overview

Dataset statistics

Number of variables4
Number of observations114
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory34.2 B

Variable types

Numeric1
Text2
DateTime1

Dataset

Description대한민국 전라남도 광양시에 있는 안전상비의약품 판매업 등록 정보에 대한 데이터를 안내하는 내용(점포명, 주소)을 제공합니다.
Author전라남도 광양시
URLhttps://www.data.go.kr/data/3079599/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
순번 has unique valuesUnique
판매점포명 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:49:11.499574
Analysis finished2023-12-12 18:49:12.174367
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.5
Minimum1
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T03:49:12.309831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.65
Q129.25
median57.5
Q385.75
95-th percentile108.35
Maximum114
Range113
Interquartile range (IQR)56.5

Descriptive statistics

Standard deviation33.052988
Coefficient of variation (CV)0.57483457
Kurtosis-1.2
Mean57.5
Median Absolute Deviation (MAD)28.5
Skewness0
Sum6555
Variance1092.5
MonotonicityStrictly increasing
2023-12-13T03:49:12.590907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
87 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
Other values (104) 104
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%

판매점포명
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T03:49:13.001232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.570175
Min length5

Characters and Unicode

Total characters1205
Distinct characters137
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

Unique114 ?
Unique (%)100.0%

Sample

1st rowGS25 마동중앙점
2nd row세븐일레븐 광양중마에에스점
3rd row씨유 광양와우동문점
4th row씨유 광양칠성매화점
5th row지에스25 광양마동주공점
ValueCountFrequency (%)
세븐일레븐 19
 
10.5%
씨유 11
 
6.1%
gs25 10
 
5.5%
미니스톱 7
 
3.9%
지에스25 5
 
2.8%
지에스(gs)25 3
 
1.7%
광양사동로점 3
 
1.7%
주)코리아세븐 2
 
1.1%
광양덕례점 2
 
1.1%
광양이편한점 2
 
1.1%
Other values (113) 117
64.6%
2023-12-13T03:49:13.723177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 106
 
8.8%
광 93
 
7.7%
양 83
 
6.9%
67
 
5.6%
븐 46
 
3.8%
2 39
 
3.2%
마 36
 
3.0%
중 36
 
3.0%
스 35
 
2.9%
5 34
 
2.8%
Other values (127) 630
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 950
78.8%
Uppercase Letter 81
 
6.7%
Decimal Number 77
 
6.4%
Space Separator 67
 
5.6%
Close Punctuation 15
 
1.2%
Open Punctuation 15
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 106
 
11.2%
광 93
 
9.8%
양 83
 
8.7%
븐 46
 
4.8%
마 36
 
3.8%
중 36
 
3.8%
스 35
 
3.7%
유 24
 
2.5%
세 24
 
2.5%
일 23
 
2.4%
Other values (116) 444
46.7%
Uppercase Letter
ValueCountFrequency (%)
S 25
30.9%
G 25
30.9%
U 15
18.5%
C 15
18.5%
R 1
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 39
50.6%
5 34
44.2%
4 4
 
5.2%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 950
78.8%
Common 174
 
14.4%
Latin 81
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 106
 
11.2%
광 93
 
9.8%
양 83
 
8.7%
븐 46
 
4.8%
마 36
 
3.8%
중 36
 
3.8%
스 35
 
3.7%
유 24
 
2.5%
세 24
 
2.5%
일 23
 
2.4%
Other values (116) 444
46.7%
Common
ValueCountFrequency (%)
67
38.5%
2 39
22.4%
5 34
19.5%
) 15
 
8.6%
( 15
 
8.6%
4 4
 
2.3%
Latin
ValueCountFrequency (%)
S 25
30.9%
G 25
30.9%
U 15
18.5%
C 15
18.5%
R 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 950
78.8%
ASCII 255
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 106
 
11.2%
광 93
 
9.8%
양 83
 
8.7%
븐 46
 
4.8%
마 36
 
3.8%
중 36
 
3.8%
스 35
 
3.7%
유 24
 
2.5%
세 24
 
2.5%
일 23
 
2.4%
Other values (116) 444
46.7%
ASCII
ValueCountFrequency (%)
67
26.3%
2 39
15.3%
5 34
13.3%
S 25
 
9.8%
G 25
 
9.8%
) 15
 
5.9%
U 15
 
5.9%
C 15
 
5.9%
( 15
 
5.9%
4 4
 
1.6%

소재지(도로명)
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T03:49:14.281568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length25.377193
Min length18

Characters and Unicode

Total characters2893
Distinct characters133
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

Unique114 ?
Unique (%)100.0%

Sample

1st row전라남도 광양시 사동로 175(마동)
2nd row전라남도 광양시 중마용소7길 13(중동)
3rd row전라남도 광양시 눈소10길 58, 상가1동 106,106호 (마동)
4th row전라남도 광양시 광양읍 서평로 93
5th row전라남도 광양시 진등6길 31, 상가동 103호 (마동, 마동주공아파트)
ValueCountFrequency (%)
전라남도 114
17.6%
광양시 114
17.6%
광양읍 40
 
6.2%
중동 36
 
5.6%
1층 21
 
3.2%
상가동 10
 
1.5%
사동로 9
 
1.4%
광영동 9
 
1.4%
광영로 8
 
1.2%
마동 8
 
1.2%
Other values (205) 279
43.1%
2023-12-13T03:49:15.034090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
534
18.5%
광 185
 
6.4%
양 159
 
5.5%
1 146
 
5.0%
남 116
 
4.0%
시 116
 
4.0%
라 115
 
4.0%
전 114
 
3.9%
도 114
 
3.9%
동 100
 
3.5%
Other values (123) 1194
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1703
58.9%
Space Separator 534
 
18.5%
Decimal Number 430
 
14.9%
Close Punctuation 79
 
2.7%
Open Punctuation 79
 
2.7%
Other Punctuation 56
 
1.9%
Dash Punctuation 7
 
0.2%
Math Symbol 3
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 185
 
10.9%
양 159
 
9.3%
남 116
 
6.8%
시 116
 
6.8%
라 115
 
6.8%
전 114
 
6.7%
도 114
 
6.7%
동 100
 
5.9%
로 72
 
4.2%
중 66
 
3.9%
Other values (106) 546
32.1%
Decimal Number
ValueCountFrequency (%)
1 146
34.0%
0 48
 
11.2%
2 48
 
11.2%
3 38
 
8.8%
4 37
 
8.6%
5 29
 
6.7%
6 22
 
5.1%
9 21
 
4.9%
8 21
 
4.9%
7 20
 
4.7%
Space Separator
ValueCountFrequency (%)
534
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Other Punctuation
ValueCountFrequency (%)
, 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1703
58.9%
Common 1188
41.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 185
 
10.9%
양 159
 
9.3%
남 116
 
6.8%
시 116
 
6.8%
라 115
 
6.8%
전 114
 
6.7%
도 114
 
6.7%
동 100
 
5.9%
로 72
 
4.2%
중 66
 
3.9%
Other values (106) 546
32.1%
Common
ValueCountFrequency (%)
534
44.9%
1 146
 
12.3%
) 79
 
6.6%
( 79
 
6.6%
, 56
 
4.7%
0 48
 
4.0%
2 48
 
4.0%
3 38
 
3.2%
4 37
 
3.1%
5 29
 
2.4%
Other values (6) 94
 
7.9%
Latin
ValueCountFrequency (%)
e 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1703
58.9%
ASCII 1190
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
534
44.9%
1 146
 
12.3%
) 79
 
6.6%
( 79
 
6.6%
, 56
 
4.7%
0 48
 
4.0%
2 48
 
4.0%
3 38
 
3.2%
4 37
 
3.1%
5 29
 
2.4%
Other values (7) 96
 
8.1%
Hangul
ValueCountFrequency (%)
광 185
 
10.9%
양 159
 
9.3%
남 116
 
6.8%
시 116
 
6.8%
라 115
 
6.8%
전 114
 
6.7%
도 114
 
6.7%
동 100
 
5.9%
로 72
 
4.2%
중 66
 
3.9%
Other values (106) 546
32.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2023-03-03 00:00:00
Maximum2023-03-03 00:00:00
2023-12-13T03:49:15.210649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:49:15.381551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:49:11.750591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T03:49:11.943958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:49:12.110383image/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

순번판매점포명소재지(도로명)데이터기준일자
01GS25 마동중앙점전라남도 광양시 사동로 175(마동)2023-03-03
12세븐일레븐 광양중마에에스점전라남도 광양시 중마용소7길 13(중동)2023-03-03
23씨유 광양와우동문점전라남도 광양시 눈소10길 58, 상가1동 106,106호 (마동)2023-03-03
34씨유 광양칠성매화점전라남도 광양시 광양읍 서평로 932023-03-03
45지에스25 광양마동주공점전라남도 광양시 진등6길 31, 상가동 103호 (마동, 마동주공아파트)2023-03-03
56지에스25 중마주공 2차점전라남도 광양시 구마9길 11, 상가동 지하층 (중동, 중마2주공아파트)2023-03-03
67세븐일레븐 광양덕례회암점전라남도 광양시 광양읍 회암1길 22, 1층2023-03-03
78CU 락희호텔광양점전라남도 광양시 항만9로 97, 1층 (중동)2023-03-03
89알리바이 광영점전라남도 광양시 광영로 119(광영동)2023-03-03
910지에스25 광양스위트점전라남도 광양시 눈소4길 34(마동)2023-03-03
순번판매점포명소재지(도로명)데이터기준일자
104105CU칠성로고스점전라남도 광양시 광양읍 인서중앙길 222023-03-03
105106세븐일레븐광양시청점전라남도 광양시 중동로 75-1 (중동)2023-03-03
106107CU광양사랑점전라남도 광양시 공영로 67 (중동)2023-03-03
107108GS25 포스코태인점전라남도 광양시 백운1로 13 (태인동)2023-03-03
108109미니스톱 태인용지점전라남도 광양시 백운1로 155 (태인동)2023-03-03
109110씨유 광양읍중앙점전라남도 광양시 광양읍 남등길 32023-03-03
110111뉴타운슈퍼전라남도 광양시 광양읍 칠성1길 362023-03-03
111112세븐일레븐 광양중마점전라남도 광양시 중마로 183 (중동)2023-03-03
112113GS25중마백운점전라남도 광양시 중마로 251 (중동)2023-03-03
113114GS25광양오성전라남도 광양시 광양읍 회암2길 322023-03-03