Overview

Dataset statistics

Number of variables6
Number of observations93
Missing cells50
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory51.4 B

Variable types

Text3
Numeric2
Categorical1

Dataset

Description제주특별자치도 서귀포시 식품유통판매업체(유통전문판매업) 현황에 관한 데이터로 업소명, 주소, 연락처 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15030333/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
연락처 has 50 (53.8%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:45:14.021555
Analysis finished2023-12-12 11:45:15.285919
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T20:45:15.510996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.6989247
Min length2

Characters and Unicode

Total characters809
Distinct characters217
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

Unique93 ?
Unique (%)100.0%

Sample

1st row(주)푸드플러스
2nd row(주)청룡수산
3rd row모슬포수산업협동조합
4th row태림상사(주)농업회사법인
5th row(주)제주 남용통상
ValueCountFrequency (%)
주식회사 2
 
2.0%
영농조합법인 2
 
2.0%
주)푸드플러스 1
 
1.0%
주)진바이옴 1
 
1.0%
귤메달하우스 1
 
1.0%
수망다원 1
 
1.0%
연담 1
 
1.0%
바타타식탁 1
 
1.0%
더푸른채영농조합법인 1
 
1.0%
주식회사펭귄박스 1
 
1.0%
Other values (89) 89
88.1%
2023-12-12T20:45:16.012513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 65
 
8.0%
사 42
 
5.2%
회 38
 
4.7%
농 30
 
3.7%
제 29
 
3.6%
인 28
 
3.5%
법 26
 
3.2%
( 21
 
2.6%
) 21
 
2.6%
식 20
 
2.5%
Other values (207) 489
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
91.0%
Open Punctuation 21
 
2.6%
Close Punctuation 21
 
2.6%
Uppercase Letter 15
 
1.9%
Space Separator 8
 
1.0%
Decimal Number 7
 
0.9%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 65
 
8.8%
사 42
 
5.7%
회 38
 
5.2%
농 30
 
4.1%
제 29
 
3.9%
인 28
 
3.8%
법 26
 
3.5%
식 20
 
2.7%
업 19
 
2.6%
조 18
 
2.4%
Other values (186) 421
57.2%
Uppercase Letter
ValueCountFrequency (%)
R 2
13.3%
T 2
13.3%
I 2
13.3%
L 2
13.3%
O 1
6.7%
C 1
6.7%
A 1
6.7%
Y 1
6.7%
F 1
6.7%
U 1
6.7%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
1 1
14.3%
9 1
14.3%
7 1
14.3%
3 1
14.3%
4 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 736
91.0%
Common 57
 
7.0%
Latin 16
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 65
 
8.8%
사 42
 
5.7%
회 38
 
5.2%
농 30
 
4.1%
제 29
 
3.9%
인 28
 
3.8%
법 26
 
3.5%
식 20
 
2.7%
업 19
 
2.6%
조 18
 
2.4%
Other values (186) 421
57.2%
Latin
ValueCountFrequency (%)
R 2
12.5%
T 2
12.5%
I 2
12.5%
L 2
12.5%
O 1
6.2%
C 1
6.2%
A 1
6.2%
Y 1
6.2%
F 1
6.2%
U 1
6.2%
Other values (2) 2
12.5%
Common
ValueCountFrequency (%)
( 21
36.8%
) 21
36.8%
8
 
14.0%
2 2
 
3.5%
1 1
 
1.8%
9 1
 
1.8%
7 1
 
1.8%
3 1
 
1.8%
4 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
91.0%
ASCII 73
 
9.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 65
 
8.8%
사 42
 
5.7%
회 38
 
5.2%
농 30
 
4.1%
제 29
 
3.9%
인 28
 
3.8%
법 26
 
3.5%
식 20
 
2.7%
업 19
 
2.6%
조 18
 
2.4%
Other values (186) 421
57.2%
ASCII
ValueCountFrequency (%)
( 21
28.8%
) 21
28.8%
8
 
11.0%
R 2
 
2.7%
2 2
 
2.7%
T 2
 
2.7%
I 2
 
2.7%
L 2
 
2.7%
1 1
 
1.4%
9 1
 
1.4%
Other values (11) 11
15.1%

주소
Text

Distinct91
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-12T20:45:16.428758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length44
Mean length31.204301
Min length21

Characters and Unicode

Total characters2902
Distinct characters165
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

Unique89 ?
Unique (%)95.7%

Sample

1st row제주특별자치도 서귀포시 안덕면 덕수서로 167
2nd row제주특별자치도 서귀포시 남원읍 일주동로 7825
3rd row제주특별자치도 서귀포시 대정읍 최남단해안로 58 1층
4th row제주특별자치도 서귀포시 대정읍 일주서로3000번길 155-15
5th row제주특별자치도 서귀포시 토평공단로127번길 46 (토평동)
ValueCountFrequency (%)
제주특별자치도 93
 
17.3%
서귀포시 93
 
17.3%
안덕면 13
 
2.4%
2층 13
 
2.4%
남원읍 12
 
2.2%
서귀동 11
 
2.0%
표선면 11
 
2.0%
1층 11
 
2.0%
성산읍 10
 
1.9%
토평동 9
 
1.7%
Other values (214) 261
48.6%
2023-12-12T20:45:17.071961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
445
 
15.3%
서 134
 
4.6%
귀 105
 
3.6%
주 105
 
3.6%
시 97
 
3.3%
제 96
 
3.3%
포 96
 
3.3%
치 95
 
3.3%
도 95
 
3.3%
특 93
 
3.2%
Other values (155) 1541
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1892
65.2%
Decimal Number 449
 
15.5%
Space Separator 445
 
15.3%
Open Punctuation 41
 
1.4%
Close Punctuation 41
 
1.4%
Dash Punctuation 23
 
0.8%
Lowercase Letter 7
 
0.2%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 134
 
7.1%
귀 105
 
5.5%
주 105
 
5.5%
시 97
 
5.1%
제 96
 
5.1%
포 96
 
5.1%
치 95
 
5.0%
도 95
 
5.0%
특 93
 
4.9%
별 93
 
4.9%
Other values (131) 883
46.7%
Decimal Number
ValueCountFrequency (%)
1 90
20.0%
2 62
13.8%
3 52
11.6%
0 49
10.9%
5 43
9.6%
7 38
8.5%
4 33
 
7.3%
8 31
 
6.9%
6 30
 
6.7%
9 21
 
4.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
d 1
14.3%
u 1
14.3%
n 1
14.3%
o 1
14.3%
z 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
A 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
445
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1892
65.2%
Common 1000
34.5%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 134
 
7.1%
귀 105
 
5.5%
주 105
 
5.5%
시 97
 
5.1%
제 96
 
5.1%
포 96
 
5.1%
치 95
 
5.0%
도 95
 
5.0%
특 93
 
4.9%
별 93
 
4.9%
Other values (131) 883
46.7%
Common
ValueCountFrequency (%)
445
44.5%
1 90
 
9.0%
2 62
 
6.2%
3 52
 
5.2%
0 49
 
4.9%
5 43
 
4.3%
( 41
 
4.1%
) 41
 
4.1%
7 38
 
3.8%
4 33
 
3.3%
Other values (5) 106
 
10.6%
Latin
ValueCountFrequency (%)
e 2
20.0%
d 1
10.0%
u 1
10.0%
G 1
10.0%
A 1
10.0%
n 1
10.0%
o 1
10.0%
z 1
10.0%
B 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1892
65.2%
ASCII 1010
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
445
44.1%
1 90
 
8.9%
2 62
 
6.1%
3 52
 
5.1%
0 49
 
4.9%
5 43
 
4.3%
( 41
 
4.1%
) 41
 
4.1%
7 38
 
3.8%
4 33
 
3.3%
Other values (14) 116
 
11.5%
Hangul
ValueCountFrequency (%)
서 134
 
7.1%
귀 105
 
5.5%
주 105
 
5.5%
시 97
 
5.1%
제 96
 
5.1%
포 96
 
5.1%
치 95
 
5.0%
도 95
 
5.0%
특 93
 
4.9%
별 93
 
4.9%
Other values (131) 883
46.7%

연락처
Text

MISSING 

Distinct42
Distinct (%)97.7%
Missing50
Missing (%)53.8%
Memory size876.0 B
2023-12-12T20:45:17.397752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters516
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

Unique41 ?
Unique (%)95.3%

Sample

1st row02-755-0608
2nd row064-733-3111
3rd row064-792-0553
4th row064-794-5333
5th row064-733-2139
ValueCountFrequency (%)
064-733-3809 2
 
4.7%
032-832-5193 1
 
2.3%
021-6616-619 1
 
2.3%
064-738-9752 1
 
2.3%
064-742-8181 1
 
2.3%
064-733-2268 1
 
2.3%
064-763-2332 1
 
2.3%
064-792-8245 1
 
2.3%
064-738-7949 1
 
2.3%
064-783-9898 1
 
2.3%
Other values (32) 32
74.4%
2023-12-12T20:45:17.906420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 86
16.7%
0 65
12.6%
3 61
11.8%
4 60
11.6%
6 56
10.9%
7 56
10.9%
8 33
 
6.4%
9 32
 
6.2%
2 30
 
5.8%
1 23
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 430
83.3%
Dash Punctuation 86
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65
15.1%
3 61
14.2%
4 60
14.0%
6 56
13.0%
7 56
13.0%
8 33
7.7%
9 32
7.4%
2 30
7.0%
1 23
 
5.3%
5 14
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 86
16.7%
0 65
12.6%
3 61
11.8%
4 60
11.6%
6 56
10.9%
7 56
10.9%
8 33
 
6.4%
9 32
 
6.2%
2 30
 
5.8%
1 23
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 86
16.7%
0 65
12.6%
3 61
11.8%
4 60
11.6%
6 56
10.9%
7 56
10.9%
8 33
 
6.4%
9 32
 
6.2%
2 30
 
5.8%
1 23
 
4.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.296442
Minimum33.215279
Maximum33.471846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T20:45:18.111619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.215279
5-th percentile33.240589
Q133.252946
median33.275482
Q333.3226
95-th percentile33.423176
Maximum33.471846
Range0.25656787
Interquartile range (IQR)0.06965372

Descriptive statistics

Standard deviation0.060100426
Coefficient of variation (CV)0.0018050105
Kurtosis1.2730387
Mean33.296442
Median Absolute Deviation (MAD)0.02558341
Skewness1.3808875
Sum3096.5691
Variance0.0036120612
MonotonicityNot monotonic
2023-12-12T20:45:18.293802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.24815673 2
 
2.2%
33.25198724 2
 
2.2%
33.26383139 1
 
1.1%
33.31617805 1
 
1.1%
33.32522553 1
 
1.1%
33.30823541 1
 
1.1%
33.33544656 1
 
1.1%
33.28819445 1
 
1.1%
33.33398298 1
 
1.1%
33.46304525 1
 
1.1%
Other values (81) 81
87.1%
ValueCountFrequency (%)
33.21527852 1
1.1%
33.22498018 1
1.1%
33.22528617 1
1.1%
33.23153799 1
1.1%
33.24038929 1
1.1%
33.24072277 1
1.1%
33.24611656 1
1.1%
33.24654783 1
1.1%
33.24815673 2
2.2%
33.24847468 1
1.1%
ValueCountFrequency (%)
33.47184639 1
1.1%
33.47112677 1
1.1%
33.46304525 1
1.1%
33.46029772 1
1.1%
33.43047188 1
1.1%
33.41831266 1
1.1%
33.41500274 1
1.1%
33.40702634 1
1.1%
33.40067521 1
1.1%
33.38719965 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57289
Minimum126.20043
Maximum126.9295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-12T20:45:18.498888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.20043
5-th percentile126.24216
Q1126.42454
median126.57493
Q3126.71778
95-th percentile126.85519
Maximum126.9295
Range0.7290659
Interquartile range (IQR)0.2932415

Descriptive statistics

Standard deviation0.19556962
Coefficient of variation (CV)0.0015451146
Kurtosis-0.84229345
Mean126.57289
Median Absolute Deviation (MAD)0.1503936
Skewness-0.10560084
Sum11771.279
Variance0.038247476
MonotonicityNot monotonic
2023-12-12T20:45:18.713351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5654591 2
 
2.2%
126.5590975 2
 
2.2%
126.3862131 1
 
1.1%
126.6891641 1
 
1.1%
126.8287366 1
 
1.1%
126.6331022 1
 
1.1%
126.7177808 1
 
1.1%
126.3043845 1
 
1.1%
126.8415199 1
 
1.1%
126.859322 1
 
1.1%
Other values (81) 81
87.1%
ValueCountFrequency (%)
126.2004345 1
1.1%
126.2120034 1
1.1%
126.2135223 1
1.1%
126.2295224 1
1.1%
126.2296116 1
1.1%
126.2505261 1
1.1%
126.2524305 1
1.1%
126.2679741 1
1.1%
126.2742159 1
1.1%
126.2963164 1
1.1%
ValueCountFrequency (%)
126.9295004 1
1.1%
126.9294504 1
1.1%
126.9127083 1
1.1%
126.8615542 1
1.1%
126.859322 1
1.1%
126.8524274 1
1.1%
126.8454489 1
1.1%
126.8439794 1
1.1%
126.8430839 1
1.1%
126.8415199 1
1.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-09-30
93 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 93
100.0%

Length

2023-12-12T20:45:18.901608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:45:19.006205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 93
100.0%

Interactions

2023-12-12T20:45:14.753651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:14.505908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:14.876838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:45:14.614075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:45:19.076337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소연락처위도경도
업소명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.767
경도1.0001.0001.0000.7671.000
2023-12-12T20:45:19.215975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.645
경도0.6451.000

Missing values

2023-12-12T20:45:15.064227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:45:15.219988image/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

업소명주소연락처위도경도데이터기준일자
0(주)푸드플러스제주특별자치도 서귀포시 안덕면 덕수서로 16702-755-060833.265544126.3041572023-09-30
1(주)청룡수산제주특별자치도 서귀포시 남원읍 일주동로 7825064-733-311133.270793126.6473382023-09-30
2모슬포수산업협동조합제주특별자치도 서귀포시 대정읍 최남단해안로 58 1층064-792-055333.215279126.2524312023-09-30
3태림상사(주)농업회사법인제주특별자치도 서귀포시 대정읍 일주서로3000번길 155-15064-794-533333.259393126.2295222023-09-30
4(주)제주 남용통상제주특별자치도 서귀포시 토평공단로127번길 46 (토평동)064-733-213933.290992126.5788122023-09-30
5해비치호텔앤드리조트(주)제주특별자치도 서귀포시 표선면 민속해안로 537064-780-821133.3226126.8439792023-09-30
6씨제이대한통운(주)클럽나인브릿지제주특별자치도 서귀포시 안덕면 광평로 34-156064-793-999933.340374126.4042462023-09-30
7영주원제주특별자치도 서귀포시 호근남로137번길 9-19 (호근동)064-739-319633.249652126.5359472023-09-30
8유기촌제주특별자치도 서귀포시 성산읍 삼달로229번길 7064-784-226233.374088126.8454492023-09-30
9제주한라블루베리영농조합제주특별자치도 서귀포시 안덕면 화순서동로 323<NA>33.279563126.3301082023-09-30
업소명주소연락처위도경도데이터기준일자
83한국올리브제주특별자치도 서귀포시 동문로 13 지하 1층 (서귀동)<NA>33.252083126.5627442023-09-30
84주식회사 위드라이크제주특별자치도 서귀포시 서문로 1 3층 (서귀동)<NA>33.252241126.5607572023-09-30
85에코소랑제주특별자치도 서귀포시 인정오름로85번길 41 정혜원 (토평동)<NA>33.284675126.581482023-09-30
86구규농산제주특별자치도 서귀포시 대정읍 하모중앙로32번길 19 2층 205호 (루체빌)<NA>33.225286126.2505262023-09-30
87로컬리티(LOCALITY)제주특별자치도 서귀포시 성산읍 중산간동로 4553-19<NA>33.386012126.808612023-09-30
88바딜제주특별자치도 서귀포시 안덕면 한창로100번길 27<NA>33.271606126.367762023-09-30
89에스케이핀크스주식회사제주특별자치도 서귀포시 안덕면 산록남로 863<NA>33.305356126.3936852023-09-30
90프루트립(FRUTRIP)제주특별자치도 서귀포시 중정로 86 3층 (서귀동)<NA>33.248157126.5654592023-09-30
91주식회사삼다올레제주특별자치도 서귀포시 성산읍 서성일로 249<NA>33.407026126.8187292023-09-30
92주식회사스윗크루제주특별자치도 서귀포시 남원읍 중산간동로 7137<NA>33.283145126.6299612023-09-30