Overview

Dataset statistics

Number of variables6
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory52.0 B

Variable types

Text3
Numeric2
DateTime1

Dataset

Description제주특별자치도 서귀포시 관내에 위치하고 있는 주유소와 관련한 데이터로 상호, 연락처, 주소, 위도, 경도 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3083291/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 16:27:15.402339
Analysis finished2023-12-12 16:27:16.134708
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T01:27:16.291228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.0461538
Min length5

Characters and Unicode

Total characters458
Distinct characters123
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row성산일출봉농협주유소
2nd row혁신도시주유소
3rd row안덕하나주유소
4th row대정농협무릉주유소
5th row선반내주유소
ValueCountFrequency (%)
성산일출봉농협주유소 1
 
1.5%
예래주유소 1
 
1.5%
제주위미농협주유소 1
 
1.5%
주)서홍주유소 1
 
1.5%
삼화석유㈜법환self주유소 1
 
1.5%
환영주유소 1
 
1.5%
한신주유소 1
 
1.5%
대포주유소 1
 
1.5%
희진주유소 1
 
1.5%
삼남석유㈜ 1
 
1.5%
Other values (57) 57
85.1%
2023-12-13T01:27:16.647302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 74
 
16.2%
유 70
 
15.3%
소 64
 
14.0%
농 11
 
2.4%
협 11
 
2.4%
( 8
 
1.7%
) 8
 
1.7%
남 7
 
1.5%
서 6
 
1.3%
석 6
 
1.3%
Other values (113) 193
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
93.9%
Open Punctuation 8
 
1.7%
Close Punctuation 8
 
1.7%
Lowercase Letter 6
 
1.3%
Space Separator 2
 
0.4%
Other Symbol 2
 
0.4%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 74
17.2%
유 70
16.3%
소 64
 
14.9%
농 11
 
2.6%
협 11
 
2.6%
남 7
 
1.6%
서 6
 
1.4%
석 6
 
1.4%
산 5
 
1.2%
원 5
 
1.2%
Other values (105) 171
39.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
l 2
33.3%
f 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 432
94.3%
Common 18
 
3.9%
Latin 8
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 74
17.1%
유 70
16.2%
소 64
 
14.8%
농 11
 
2.5%
협 11
 
2.5%
남 7
 
1.6%
서 6
 
1.4%
석 6
 
1.4%
산 5
 
1.2%
원 5
 
1.2%
Other values (106) 173
40.0%
Latin
ValueCountFrequency (%)
S 2
25.0%
e 2
25.0%
l 2
25.0%
f 2
25.0%
Common
ValueCountFrequency (%)
( 8
44.4%
) 8
44.4%
2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 430
93.9%
ASCII 26
 
5.7%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 74
17.2%
유 70
16.3%
소 64
 
14.9%
농 11
 
2.6%
협 11
 
2.6%
남 7
 
1.6%
서 6
 
1.4%
석 6
 
1.4%
산 5
 
1.2%
원 5
 
1.2%
Other values (105) 171
39.8%
ASCII
ValueCountFrequency (%)
( 8
30.8%
) 8
30.8%
2
 
7.7%
S 2
 
7.7%
e 2
 
7.7%
l 2
 
7.7%
f 2
 
7.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

연락처
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T01:27:16.905657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015385
Min length12

Characters and Unicode

Total characters781
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

Unique65 ?
Unique (%)100.0%

Sample

1st row064-780-3135
2nd row064-739-5233
3rd row064-792-3088
4th row064-792-8201
5th row064-739-5008
ValueCountFrequency (%)
064-780-3135 1
 
1.5%
064-732-5149 1
 
1.5%
064-794-1116 1
 
1.5%
064-760-1080 1
 
1.5%
064-733-0111 1
 
1.5%
064-739-6051 1
 
1.5%
064-732-5177 1
 
1.5%
064-739-4942 1
 
1.5%
064-738-0833 1
 
1.5%
064-783-0115 1
 
1.5%
Other values (55) 55
84.6%
2023-12-13T01:27:17.310719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 130
16.6%
4 107
13.7%
0 105
13.4%
6 83
10.6%
7 79
10.1%
3 54
6.9%
5 54
6.9%
8 47
 
6.0%
1 47
 
6.0%
9 40
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 651
83.4%
Dash Punctuation 130
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 107
16.4%
0 105
16.1%
6 83
12.7%
7 79
12.1%
3 54
8.3%
5 54
8.3%
8 47
7.2%
1 47
7.2%
9 40
 
6.1%
2 35
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 781
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 130
16.6%
4 107
13.7%
0 105
13.4%
6 83
10.6%
7 79
10.1%
3 54
6.9%
5 54
6.9%
8 47
 
6.0%
1 47
 
6.0%
9 40
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 130
16.6%
4 107
13.7%
0 105
13.4%
6 83
10.6%
7 79
10.1%
3 54
6.9%
5 54
6.9%
8 47
 
6.0%
1 47
 
6.0%
9 40
 
5.1%

주소
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T01:27:17.564727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.261538
Min length19

Characters and Unicode

Total characters1512
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 성산읍 일주동로 4521
2nd row제주특별자치도 서귀포시 일주동로 9144
3rd row제주특별자치도 서귀포시 안덕면 한창로 182
4th row제주특별자치도 서귀포시 대정읍 서삼중로 66
5th row제주특별자치도 서귀포시 일주동로 8780
ValueCountFrequency (%)
제주특별자치도 65
22.3%
서귀포시 65
22.3%
일주서로 14
 
4.8%
일주동로 12
 
4.1%
중산간동로 8
 
2.7%
대정읍 7
 
2.4%
안덕면 7
 
2.4%
성산읍 7
 
2.4%
남원읍 6
 
2.1%
516로 4
 
1.4%
Other values (83) 96
33.0%
2023-12-13T01:27:17.952252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
14.9%
주 91
 
6.0%
서 84
 
5.6%
제 67
 
4.4%
도 66
 
4.4%
로 65
 
4.3%
특 65
 
4.3%
별 65
 
4.3%
자 65
 
4.3%
치 65
 
4.3%
Other values (52) 653
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1054
69.7%
Decimal Number 230
 
15.2%
Space Separator 226
 
14.9%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 91
 
8.6%
서 84
 
8.0%
제 67
 
6.4%
도 66
 
6.3%
로 65
 
6.2%
특 65
 
6.2%
별 65
 
6.2%
자 65
 
6.2%
치 65
 
6.2%
귀 65
 
6.2%
Other values (40) 356
33.8%
Decimal Number
ValueCountFrequency (%)
1 36
15.7%
8 31
13.5%
2 25
10.9%
6 23
10.0%
5 23
10.0%
3 22
9.6%
4 19
8.3%
7 19
8.3%
0 17
7.4%
9 15
6.5%
Space Separator
ValueCountFrequency (%)
226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1054
69.7%
Common 458
30.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 91
 
8.6%
서 84
 
8.0%
제 67
 
6.4%
도 66
 
6.3%
로 65
 
6.2%
특 65
 
6.2%
별 65
 
6.2%
자 65
 
6.2%
치 65
 
6.2%
귀 65
 
6.2%
Other values (40) 356
33.8%
Common
ValueCountFrequency (%)
226
49.3%
1 36
 
7.9%
8 31
 
6.8%
2 25
 
5.5%
6 23
 
5.0%
5 23
 
5.0%
3 22
 
4.8%
4 19
 
4.1%
7 19
 
4.1%
0 17
 
3.7%
Other values (2) 17
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1054
69.7%
ASCII 458
30.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
49.3%
1 36
 
7.9%
8 31
 
6.8%
2 25
 
5.5%
6 23
 
5.0%
5 23
 
5.0%
3 22
 
4.8%
4 19
 
4.1%
7 19
 
4.1%
0 17
 
3.7%
Other values (2) 17
 
3.7%
Hangul
ValueCountFrequency (%)
주 91
 
8.6%
서 84
 
8.0%
제 67
 
6.4%
도 66
 
6.3%
로 65
 
6.2%
특 65
 
6.2%
별 65
 
6.2%
자 65
 
6.2%
치 65
 
6.2%
귀 65
 
6.2%
Other values (40) 356
33.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.282299
Minimum33.222679
Maximum33.453756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-13T01:27:18.076599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.222679
5-th percentile33.230224
Q133.252642
median33.262106
Q333.284673
95-th percentile33.426831
Maximum33.453756
Range0.23107727
Interquartile range (IQR)0.03203155

Descriptive statistics

Standard deviation0.055397118
Coefficient of variation (CV)0.0016644619
Kurtosis2.9962597
Mean33.282299
Median Absolute Deviation (MAD)0.01413843
Skewness1.9313215
Sum2163.3494
Variance0.0030688407
MonotonicityNot monotonic
2023-12-13T01:27:18.201736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.42531058 1
 
1.5%
33.26470429 1
 
1.5%
33.2596985 1
 
1.5%
33.2709194 1
 
1.5%
33.26398421 1
 
1.5%
33.24796714 1
 
1.5%
33.26645482 1
 
1.5%
33.25564039 1
 
1.5%
33.25264191 1
 
1.5%
33.37686581 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
33.22267913 1
1.5%
33.22692245 1
1.5%
33.22754396 1
1.5%
33.22929616 1
1.5%
33.23393311 1
1.5%
33.23563274 1
1.5%
33.24546817 1
1.5%
33.24572657 1
1.5%
33.24671569 1
1.5%
33.24736078 1
1.5%
ValueCountFrequency (%)
33.4537564 1
1.5%
33.44695178 1
1.5%
33.43897982 1
1.5%
33.42721087 1
1.5%
33.42531058 1
1.5%
33.3847351 1
1.5%
33.37686581 1
1.5%
33.35935446 1
1.5%
33.33658609 1
1.5%
33.32452811 1
1.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.54754
Minimum126.20417
Maximum126.91462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-13T01:27:18.320828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.20417
5-th percentile126.2618
Q1126.39979
median126.55108
Q3126.63367
95-th percentile126.90143
Maximum126.91462
Range0.710458
Interquartile range (IQR)0.2338812

Descriptive statistics

Standard deviation0.19290729
Coefficient of variation (CV)0.0015243859
Kurtosis-0.66174032
Mean126.54754
Median Absolute Deviation (MAD)0.1445687
Skewness0.3497399
Sum8225.5901
Variance0.037213221
MonotonicityNot monotonic
2023-12-13T01:27:18.442194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5510797 2
 
3.1%
126.9070337 1
 
1.5%
126.5710447 1
 
1.5%
126.3564608 1
 
1.5%
126.6465123 1
 
1.5%
126.5762505 1
 
1.5%
126.4138418 1
 
1.5%
126.4493606 1
 
1.5%
126.8733873 1
 
1.5%
126.9074601 1
 
1.5%
Other values (54) 54
83.1%
ValueCountFrequency (%)
126.2041653 1
1.5%
126.247778 1
1.5%
126.2585298 1
1.5%
126.2603937 1
1.5%
126.267425 1
1.5%
126.2738835 1
1.5%
126.2874693 1
1.5%
126.3239795 1
1.5%
126.3334415 1
1.5%
126.3413565 1
1.5%
ValueCountFrequency (%)
126.9146233 1
1.5%
126.9130309 1
1.5%
126.9074601 1
1.5%
126.9070337 1
1.5%
126.8790193 1
1.5%
126.8759629 1
1.5%
126.8733873 1
1.5%
126.8317686 1
1.5%
126.8287777 1
1.5%
126.8269626 1
1.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-13T01:27:18.604968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:27:18.718651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:27:15.802156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:27:15.651146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:27:15.876497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:27:15.718509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:27:18.780584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호연락처주소위도경도
상호1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.886
경도1.0001.0001.0000.8861.000
2023-12-13T01:27:18.858461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.645
경도0.6451.000

Missing values

2023-12-13T01:27:15.998698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:27:16.093193image/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

상호연락처주소위도경도데이터기준일자
0성산일출봉농협주유소064-780-3135제주특별자치도 서귀포시 성산읍 일주동로 452133.425311126.9070342023-06-01
1혁신도시주유소064-739-5233제주특별자치도 서귀포시 일주동로 914433.248262126.5161412023-06-01
2안덕하나주유소064-792-3088제주특별자치도 서귀포시 안덕면 한창로 18233.277632126.3596172023-06-01
3대정농협무릉주유소064-792-8201제주특별자치도 서귀포시 대정읍 서삼중로 6633.269115126.2041652023-06-01
4선반내주유소064-739-5008제주특별자치도 서귀포시 일주동로 878033.253126126.5508512023-06-01
5유진주유소064-787-5189제주특별자치도 서귀포시 표선면 번영로 323933.359354126.8223612023-06-01
6선진주유소064-792-8951제주특별자치도 서귀포시 안덕면 한창로 33433.289479126.3521582023-06-01
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56중문주유소064-738-0502제주특별자치도 서귀포시 천제연로 24633.251193126.4309422023-06-01
57남원주유소064-764-5189제주특별자치도 서귀포시 남원읍 태위로 71033.279772126.7221292023-06-01
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59에이치디현대오일뱅크(주)직영 동남주유소064-782-1425제주특별자치도 서귀포시 성산읍 고성오조로 3533.446952126.9146232023-06-01
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61칠십리주유소064-732-5188제주특별자치도 서귀포시 중정로 4033.247361126.5605432023-06-01
62에이스주유소064-732-5145제주특별자치도 서귀포시 일주동로 851333.254802126.5788852023-06-01
63산방주유소064-794-2314제주특별자치도 서귀포시 대정읍 신영로 3433.222679126.2477782023-06-01
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