Overview

Dataset statistics

Number of variables5
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory43.6 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description대한민국 전라남도 광양시에 있는 약국정보에 대한 데이터를 국민들 전부에게 무료로 제공(상호, 주소, 전화번호 등)합니다.
Author전라남도 광양시
URLhttps://www.data.go.kr/data/3077910/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 has unique valuesUnique
약국명칭 has unique valuesUnique
약국전화번호 has unique valuesUnique
약국소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2024-03-30 07:57:22.400286
Analysis finished2024-03-30 07:57:24.003192
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-30T07:57:24.234262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-30T07:57:24.821781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

약국명칭
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-30T07:57:25.640593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length5.26
Min length3

Characters and Unicode

Total characters263
Distinct characters105
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

Unique50 ?
Unique (%)100.0%

Sample

1st row청춘약국
2nd row녹십자약국
3rd row공약국
4th row광양나라약국
5th row열린 약국
ValueCountFrequency (%)
청춘약국 1
 
2.0%
건강약국 1
 
2.0%
백제약국 1
 
2.0%
선샤인약국 1
 
2.0%
맑은샘약국 1
 
2.0%
인성약국 1
 
2.0%
보배약국 1
 
2.0%
하나약국 1
 
2.0%
로타리큰약국 1
 
2.0%
한우리약국 1
 
2.0%
Other values (41) 41
80.4%
2024-03-30T07:57:27.323478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 51
19.4%
약 50
19.0%
리 9
 
3.4%
누 6
 
2.3%
온 6
 
2.3%
마 5
 
1.9%
한 4
 
1.5%
나 4
 
1.5%
인 3
 
1.1%
제 3
 
1.1%
Other values (95) 122
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
97.0%
Lowercase Letter 6
 
2.3%
Space Separator 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 51
20.0%
약 50
19.6%
리 9
 
3.5%
누 6
 
2.4%
온 6
 
2.4%
마 5
 
2.0%
한 4
 
1.6%
나 4
 
1.6%
인 3
 
1.2%
제 3
 
1.2%
Other values (87) 114
44.7%
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%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
97.0%
Latin 6
 
2.3%
Common 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 51
20.0%
약 50
19.6%
리 9
 
3.5%
누 6
 
2.4%
온 6
 
2.4%
마 5
 
2.0%
한 4
 
1.6%
나 4
 
1.6%
인 3
 
1.2%
제 3
 
1.2%
Other values (87) 114
44.7%
Latin
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%
Common
ValueCountFrequency (%)
1
50.0%
- 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
97.0%
ASCII 8
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 51
20.0%
약 50
19.6%
리 9
 
3.5%
누 6
 
2.4%
온 6
 
2.4%
마 5
 
2.0%
한 4
 
1.6%
나 4
 
1.6%
인 3
 
1.2%
제 3
 
1.2%
Other values (87) 114
44.7%
ASCII
ValueCountFrequency (%)
1
12.5%
e 1
12.5%
r 1
12.5%
o 1
12.5%
t 1
12.5%
s 1
12.5%
- 1
12.5%
w 1
12.5%

약국전화번호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-30T07:57:28.041034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters600
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

Unique50 ?
Unique (%)100.0%

Sample

1st row061-818-4333
2nd row061-763-6800
3rd row061-794-0911
4th row061-763-8847
5th row061-791-7162
ValueCountFrequency (%)
061-818-4333 1
 
2.0%
061-792-8575 1
 
2.0%
061-763-1356 1
 
2.0%
061-793-3151 1
 
2.0%
061-795-7582 1
 
2.0%
061-792-9919 1
 
2.0%
061-795-0077 1
 
2.0%
061-772-1989 1
 
2.0%
061-761-6789 1
 
2.0%
061-793-7714 1
 
2.0%
Other values (40) 40
80.0%
2024-03-30T07:57:29.390670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 100
16.7%
1 83
13.8%
7 79
13.2%
6 78
13.0%
0 75
12.5%
9 46
7.7%
2 36
 
6.0%
5 32
 
5.3%
3 29
 
4.8%
8 22
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 500
83.3%
Dash Punctuation 100
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 83
16.6%
7 79
15.8%
6 78
15.6%
0 75
15.0%
9 46
9.2%
2 36
7.2%
5 32
 
6.4%
3 29
 
5.8%
8 22
 
4.4%
4 20
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 100
16.7%
1 83
13.8%
7 79
13.2%
6 78
13.0%
0 75
12.5%
9 46
7.7%
2 36
 
6.0%
5 32
 
5.3%
3 29
 
4.8%
8 22
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 100
16.7%
1 83
13.8%
7 79
13.2%
6 78
13.0%
0 75
12.5%
9 46
7.7%
2 36
 
6.0%
5 32
 
5.3%
3 29
 
4.8%
8 22
 
3.7%

약국소재지(도로명)
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-30T07:57:30.204179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length24.28
Min length19

Characters and Unicode

Total characters1214
Distinct characters96
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

Unique50 ?
Unique (%)100.0%

Sample

1st row전라남도 광양시 발섬5길 9(중동)
2nd row전라남도 광양시 광양읍 대림오성로 100, 1층
3rd row전라남도 광양시 중마중앙로 81, 1층 (중동)
4th row전라남도 광양시 광양읍 숲샘길 88, 1층
5th row전라남도 광양시 광장로 70, 상가2동 107호 (중동, 성호2차아파트)
ValueCountFrequency (%)
전라남도 50
17.8%
광양시 50
17.8%
중동 21
 
7.5%
1층 18
 
6.4%
광양읍 16
 
5.7%
중마중앙로 9
 
3.2%
광영동 5
 
1.8%
광장로 4
 
1.4%
공영로 4
 
1.4%
백운로 3
 
1.1%
Other values (85) 101
35.9%
2024-03-30T07:57:31.545054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
19.0%
광 82
 
6.8%
양 68
 
5.6%
1 62
 
5.1%
남 51
 
4.2%
시 51
 
4.2%
라 51
 
4.2%
전 50
 
4.1%
도 50
 
4.1%
중 42
 
3.5%
Other values (86) 476
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 715
58.9%
Space Separator 231
 
19.0%
Decimal Number 169
 
13.9%
Open Punctuation 33
 
2.7%
Close Punctuation 33
 
2.7%
Other Punctuation 24
 
2.0%
Dash Punctuation 7
 
0.6%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 82
11.5%
양 68
 
9.5%
남 51
 
7.1%
시 51
 
7.1%
라 51
 
7.1%
전 50
 
7.0%
도 50
 
7.0%
중 42
 
5.9%
로 41
 
5.7%
동 37
 
5.2%
Other values (69) 192
26.9%
Decimal Number
ValueCountFrequency (%)
1 62
36.7%
5 17
 
10.1%
7 16
 
9.5%
9 14
 
8.3%
0 12
 
7.1%
4 11
 
6.5%
8 11
 
6.5%
2 10
 
5.9%
3 8
 
4.7%
6 8
 
4.7%
Space Separator
ValueCountFrequency (%)
231
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 715
58.9%
Common 498
41.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 82
11.5%
양 68
 
9.5%
남 51
 
7.1%
시 51
 
7.1%
라 51
 
7.1%
전 50
 
7.0%
도 50
 
7.0%
중 42
 
5.9%
로 41
 
5.7%
동 37
 
5.2%
Other values (69) 192
26.9%
Common
ValueCountFrequency (%)
231
46.4%
1 62
 
12.4%
( 33
 
6.6%
) 33
 
6.6%
, 24
 
4.8%
5 17
 
3.4%
7 16
 
3.2%
9 14
 
2.8%
0 12
 
2.4%
4 11
 
2.2%
Other values (6) 45
 
9.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 715
58.9%
ASCII 499
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
46.3%
1 62
 
12.4%
( 33
 
6.6%
) 33
 
6.6%
, 24
 
4.8%
5 17
 
3.4%
7 16
 
3.2%
9 14
 
2.8%
0 12
 
2.4%
4 11
 
2.2%
Other values (7) 46
 
9.2%
Hangul
ValueCountFrequency (%)
광 82
11.5%
양 68
 
9.5%
남 51
 
7.1%
시 51
 
7.1%
라 51
 
7.1%
전 50
 
7.0%
도 50
 
7.0%
중 42
 
5.9%
로 41
 
5.7%
동 37
 
5.2%
Other values (69) 192
26.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-15
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-15
2nd row2024-03-15
3rd row2024-03-15
4th row2024-03-15
5th row2024-03-15

Common Values

ValueCountFrequency (%)
2024-03-15 50
100.0%

Length

2024-03-30T07:57:31.931835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T07:57:32.233126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-15 50
100.0%

Interactions

2024-03-30T07:57:22.869213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T07:57:32.458952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번약국명칭약국전화번호약국소재지(도로명)
연번1.0001.0001.0001.000
약국명칭1.0001.0001.0001.000
약국전화번호1.0001.0001.0001.000
약국소재지(도로명)1.0001.0001.0001.000

Missing values

2024-03-30T07:57:23.279828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T07:57:23.788633image/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

연번약국명칭약국전화번호약국소재지(도로명)데이터기준일
01청춘약국061-818-4333전라남도 광양시 발섬5길 9(중동)2024-03-15
12녹십자약국061-763-6800전라남도 광양시 광양읍 대림오성로 100, 1층2024-03-15
23공약국061-794-0911전라남도 광양시 중마중앙로 81, 1층 (중동)2024-03-15
34광양나라약국061-763-8847전라남도 광양시 광양읍 숲샘길 88, 1층2024-03-15
45열린 약국061-791-7162전라남도 광양시 광장로 70, 상가2동 107호 (중동, 성호2차아파트)2024-03-15
56호남약국061-762-8844전라남도 광양시 광양읍 신재로 752024-03-15
67중동프라자약국061-791-5607전라남도 광양시 중마중앙로 87-1, 1층 101호 (중동)2024-03-15
78길약국061-794-7292전라남도 광양시 중마중앙로 71-1, 1층 북동쪽 일부호 (중동)2024-03-15
89하나로약국061-793-0076전라남도 광양시 중마중앙로 75 (중동)2024-03-15
910바른약국061-795-1058전라남도 광양시 사동로 187 (마동)2024-03-15
연번약국명칭약국전화번호약국소재지(도로명)데이터기준일
4041한샘약국061-791-9906전라남도 광양시 중마중앙로 55 (중동)2024-03-15
4142세종약국061-763-8275전라남도 광양시 광양읍 칠성로 552024-03-15
4243팔마약국061-762-3288전라남도 광양시 광양읍 신재로 482024-03-15
4344십자당약국061-762-0258전라남도 광양시 광양읍 읍성길 1512024-03-15
4445메디팜명재약국061-762-7349전라남도 광양시 광양읍 순광로 6972024-03-15
4546메디팜유진약국061-792-1581전라남도 광양시 중마로 172, 1층 (중동)2024-03-15
4647내츄럴팜약국061-792-3957전라남도 광양시 광영로 121 (광영동)2024-03-15
4748천일온누리약국061-792-4441전라남도 광양시 중마중앙로 79 (중동)2024-03-15
4849백제약국061-763-1356전라남도 광양시 광양읍 순광로 6892024-03-15
4950제철구내약국061-792-4885전라남도 광양시 백운로 1638-11 (금호동)2024-03-15