Overview

Dataset statistics

Number of variables6
Number of observations76
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory51.7 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description제주특별자치도 서귀포시 관내에 운영 중인 약국현황에 관한 데이터로 약국명, 주소, 전화번호, 위도, 경도 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/3082313/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
약국명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:02:41.151382
Analysis finished2023-12-12 17:02:42.138804
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

약국명
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-13T02:02:42.354542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.6710526
Min length3

Characters and Unicode

Total characters355
Distinct characters113
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)100.0%

Sample

1st row올레약국
2nd row안덕유선약국
3rd row오름약국
4th row용머리약국
5th row감귤약국
ValueCountFrequency (%)
올레약국 1
 
1.2%
동남온누리약국 1
 
1.2%
동원약국 1
 
1.2%
중앙약국 1
 
1.2%
제주사랑약국 1
 
1.2%
한마음약국 1
 
1.2%
부부약국 1
 
1.2%
메디팜현대약국 1
 
1.2%
위미약국 1
 
1.2%
조광약국 1
 
1.2%
Other values (70) 70
87.5%
2023-12-13T02:02:42.809428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 77
21.7%
약 76
21.4%
온 7
 
2.0%
리 7
 
2.0%
한 7
 
2.0%
동 6
 
1.7%
정 5
 
1.4%
누 5
 
1.4%
대 4
 
1.1%
강 4
 
1.1%
Other values (103) 157
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
98.9%
Space Separator 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 77
21.9%
약 76
21.7%
온 7
 
2.0%
리 7
 
2.0%
한 7
 
2.0%
동 6
 
1.7%
정 5
 
1.4%
누 5
 
1.4%
대 4
 
1.1%
강 4
 
1.1%
Other values (102) 153
43.6%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
98.9%
Common 4
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 77
21.9%
약 76
21.7%
온 7
 
2.0%
리 7
 
2.0%
한 7
 
2.0%
동 6
 
1.7%
정 5
 
1.4%
누 5
 
1.4%
대 4
 
1.1%
강 4
 
1.1%
Other values (102) 153
43.6%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
98.9%
ASCII 4
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 77
21.9%
약 76
21.7%
온 7
 
2.0%
리 7
 
2.0%
한 7
 
2.0%
동 6
 
1.7%
정 5
 
1.4%
누 5
 
1.4%
대 4
 
1.1%
강 4
 
1.1%
Other values (102) 153
43.6%
ASCII
ValueCountFrequency (%)
4
100.0%

주소
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-13T02:02:43.143653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length35.5
Mean length28.802632
Min length24

Characters and Unicode

Total characters2189
Distinct characters127
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 중앙로 43 1층 (서귀동)
2nd row제주특별자치도 서귀포시 안덕면 화순로 132 1층
3rd row제주특별자치도 서귀포시 중정로 70 (서귀동)
4th row제주특별자치도 서귀포시 안덕면 사계남로216번길 29
5th row제주특별자치도 서귀포시 동문로 64(서귀동)
ValueCountFrequency (%)
제주특별자치도 76
 
18.2%
서귀포시 76
 
18.2%
서귀동 20
 
4.8%
대정읍 11
 
2.6%
중정로 8
 
1.9%
일주동로 8
 
1.9%
동홍동 7
 
1.7%
남원읍 7
 
1.7%
중문동 7
 
1.7%
중앙로 7
 
1.7%
Other values (145) 190
45.6%
2023-12-13T02:02:43.627850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
343
 
15.7%
서 109
 
5.0%
귀 99
 
4.5%
주 84
 
3.8%
제 80
 
3.7%
포 78
 
3.6%
시 78
 
3.6%
자 77
 
3.5%
로 77
 
3.5%
치 76
 
3.5%
Other values (117) 1088
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1476
67.4%
Space Separator 343
 
15.7%
Decimal Number 246
 
11.2%
Open Punctuation 56
 
2.6%
Close Punctuation 56
 
2.6%
Dash Punctuation 9
 
0.4%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 109
 
7.4%
귀 99
 
6.7%
주 84
 
5.7%
제 80
 
5.4%
포 78
 
5.3%
시 78
 
5.3%
자 77
 
5.2%
로 77
 
5.2%
치 76
 
5.1%
도 76
 
5.1%
Other values (100) 642
43.5%
Decimal Number
ValueCountFrequency (%)
1 49
19.9%
6 30
12.2%
2 27
11.0%
3 25
10.2%
4 22
8.9%
0 22
8.9%
8 21
8.5%
7 20
8.1%
5 17
 
6.9%
9 13
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
G 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
343
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1476
67.4%
Common 710
32.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 109
 
7.4%
귀 99
 
6.7%
주 84
 
5.7%
제 80
 
5.4%
포 78
 
5.3%
시 78
 
5.3%
자 77
 
5.2%
로 77
 
5.2%
치 76
 
5.1%
도 76
 
5.1%
Other values (100) 642
43.5%
Common
ValueCountFrequency (%)
343
48.3%
( 56
 
7.9%
) 56
 
7.9%
1 49
 
6.9%
6 30
 
4.2%
2 27
 
3.8%
3 25
 
3.5%
4 22
 
3.1%
0 22
 
3.1%
8 21
 
3.0%
Other values (4) 59
 
8.3%
Latin
ValueCountFrequency (%)
B 1
33.3%
G 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1476
67.4%
ASCII 713
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
343
48.1%
( 56
 
7.9%
) 56
 
7.9%
1 49
 
6.9%
6 30
 
4.2%
2 27
 
3.8%
3 25
 
3.5%
4 22
 
3.1%
0 22
 
3.1%
8 21
 
2.9%
Other values (7) 62
 
8.7%
Hangul
ValueCountFrequency (%)
서 109
 
7.4%
귀 99
 
6.7%
주 84
 
5.7%
제 80
 
5.4%
포 78
 
5.3%
시 78
 
5.3%
자 77
 
5.2%
로 77
 
5.2%
치 76
 
5.1%
도 76
 
5.1%
Other values (100) 642
43.5%

전화번호
Text

UNIQUE 

Distinct76
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size740.0 B
2023-12-13T02:02:44.178561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.039474
Min length12

Characters and Unicode

Total characters915
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

Unique76 ?
Unique (%)100.0%

Sample

1st row064-762-3618
2nd row064-792-7723
3rd row064-803-0550
4th row070-7757-7128
5th row064-901-2046
ValueCountFrequency (%)
064-762-3618 1
 
1.3%
064-794-8380 1
 
1.3%
064-762-4958 1
 
1.3%
064-782-3075 1
 
1.3%
064-739-0381 1
 
1.3%
064-767-6013 1
 
1.3%
064-794-0719 1
 
1.3%
064-764-6603 1
 
1.3%
064-764-4159 1
 
1.3%
064-792-7723 1
 
1.3%
Other values (66) 66
86.8%
2023-12-13T02:02:44.603106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 152
16.6%
7 124
13.6%
0 120
13.1%
6 117
12.8%
4 112
12.2%
3 69
7.5%
2 57
 
6.2%
8 45
 
4.9%
5 42
 
4.6%
9 41
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 763
83.4%
Dash Punctuation 152
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 124
16.3%
0 120
15.7%
6 117
15.3%
4 112
14.7%
3 69
9.0%
2 57
7.5%
8 45
 
5.9%
5 42
 
5.5%
9 41
 
5.4%
1 36
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 152
16.6%
7 124
13.6%
0 120
13.1%
6 117
12.8%
4 112
12.2%
3 69
7.5%
2 57
 
6.2%
8 45
 
4.9%
5 42
 
4.6%
9 41
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 152
16.6%
7 124
13.6%
0 120
13.1%
6 117
12.8%
4 112
12.2%
3 69
7.5%
2 57
 
6.2%
8 45
 
4.9%
5 42
 
4.6%
9 41
 
4.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.493362
Minimum33.221686
Maximum126.25121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-13T02:02:44.749274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.221686
5-th percentile33.247189
Q133.248207
median33.252264
Q333.256463
95-th percentile33.44959
Maximum126.25121
Range93.029525
Interquartile range (IQR)0.0082559975

Descriptive statistics

Standard deviation10.665813
Coefficient of variation (CV)0.30921348
Kurtosis75.996214
Mean34.493362
Median Absolute Deviation (MAD)0.00416731
Skewness8.7174768
Sum2621.4955
Variance113.75956
MonotonicityNot monotonic
2023-12-13T02:02:44.918366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.25646346 2
 
2.6%
33.27963509 1
 
1.3%
33.26347996 1
 
1.3%
33.45024976 1
 
1.3%
33.25148758 1
 
1.3%
33.2542874 1
 
1.3%
33.22168551 1
 
1.3%
33.27499622 1
 
1.3%
33.27822026 1
 
1.3%
33.2478642 1
 
1.3%
Other values (65) 65
85.5%
ValueCountFrequency (%)
33.22168551 1
1.3%
33.22215049 1
1.3%
33.24513435 1
1.3%
33.24659786 1
1.3%
33.24738561 1
1.3%
33.24751016 1
1.3%
33.24752195 1
1.3%
33.24778425 1
1.3%
33.24778886 1
1.3%
33.24780718 1
1.3%
ValueCountFrequency (%)
126.2512102 1
1.3%
33.46332618 1
1.3%
33.45024976 1
1.3%
33.44961771 1
1.3%
33.44958077 1
1.3%
33.4472649 1
1.3%
33.32602924 1
1.3%
33.32583506 1
1.3%
33.32433564 1
1.3%
33.32425012 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57815
Minimum126.25121
Maximum126.93331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size816.0 B
2023-12-13T02:02:45.053461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.25121
5-th percentile126.4009
Q1126.55089
median126.56354
Q3126.57151
95-th percentile126.91462
Maximum126.93331
Range0.6820985
Interquartile range (IQR)0.02062045

Descriptive statistics

Standard deviation0.14463696
Coefficient of variation (CV)0.0011426692
Kurtosis1.1076875
Mean126.57815
Median Absolute Deviation (MAD)0.00808185
Skewness0.56393136
Sum9619.9397
Variance0.02091985
MonotonicityNot monotonic
2023-12-13T02:02:45.211349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5615855 2
 
2.6%
126.5642454 2
 
2.6%
126.7202886 1
 
1.3%
126.3346349 1
 
1.3%
126.9149518 1
 
1.3%
126.4270354 1
 
1.3%
126.5653039 1
 
1.3%
126.2517052 1
 
1.3%
126.6610795 1
 
1.3%
126.7144149 1
 
1.3%
Other values (64) 64
84.2%
ValueCountFrequency (%)
126.2512102 1
1.3%
126.2517052 1
1.3%
126.2541051 1
1.3%
126.3346349 1
1.3%
126.4229942 1
1.3%
126.4230283 1
1.3%
126.4232279 1
1.3%
126.4254531 1
1.3%
126.4260665 1
1.3%
126.4267769 1
1.3%
ValueCountFrequency (%)
126.9333087 1
1.3%
126.915077 1
1.3%
126.9149518 1
1.3%
126.9147192 1
1.3%
126.9145934 1
1.3%
126.8328655 1
1.3%
126.8324398 1
1.3%
126.8316227 1
1.3%
126.8308578 1
1.3%
126.7202886 1
1.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size740.0 B
Minimum2023-09-19 00:00:00
Maximum2023-09-19 00:00:00
2023-12-13T02:02:45.337015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:45.447297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:02:41.742275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:41.561828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:41.849703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:02:41.647839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:02:45.539839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
약국명주소전화번호위도경도
약국명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.494
경도1.0001.0001.0000.4941.000
2023-12-13T02:02:45.651556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.515
경도0.5151.000

Missing values

2023-12-13T02:02:41.971533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:02:42.090775image/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

약국명주소전화번호위도경도데이터기준일자
0올레약국제주특별자치도 서귀포시 중앙로 43 1층 (서귀동)064-762-361833.279635126.7202892023-09-19
1안덕유선약국제주특별자치도 서귀포시 안덕면 화순로 132 1층064-792-772333.2548126.5604872023-09-19
2오름약국제주특별자치도 서귀포시 중정로 70 (서귀동)064-803-055033.247807126.5636172023-09-19
3용머리약국제주특별자치도 서귀포시 안덕면 사계남로216번길 29070-7757-712833.251482126.4267792023-09-19
4감귤약국제주특별자치도 서귀포시 동문로 64(서귀동)064-901-204633.24751126.5622282023-09-19
5모슬포약국제주특별자치도 서귀포시 대정읍 신영로 75 1층064-792-897533.247386126.5616792023-09-19
6신통약국제주특별자치도 서귀포시 대정읍 중산간서로 2276 B동 101호064-794-758033.253019126.5616892023-09-19
7새현대약국제주특별자치도 서귀포시 중앙로 35-1 현대약국 (서귀동)064-733-614333.252695126.4230282023-09-19
8금강한약국제주특별자치도 서귀포시 신서로 69 (강정동 강정지예타운)064-738-288033.447265126.9147192023-09-19
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