Overview

Dataset statistics

Number of variables7
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory59.3 B

Variable types

Numeric2
Categorical1
Text3
DateTime1

Dataset

Description전라남도 여수시 관내 착한가격업소(업종, 주소, 주요품목, 가격등)현황 정보를 제공하는 데이터로 우리시 착한가격업소을 안내함
Author전라남도 여수시
URLhttps://www.data.go.kr/data/3073418/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-05-04 08:00:38.681868
Analysis finished2024-05-04 08:00:42.268832
Duration3.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.5
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-04T08:00:42.503922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.05
Q126.25
median51.5
Q376.75
95-th percentile96.95
Maximum102
Range101
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation29.588849
Coefficient of variation (CV)0.57454076
Kurtosis-1.2
Mean51.5
Median Absolute Deviation (MAD)25.5
Skewness0
Sum5253
Variance875.5
MonotonicityStrictly increasing
2024-05-04T08:00:43.026971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
66 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
Other values (92) 92
90.2%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%

업종
Categorical

Distinct7
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size948.0 B
한식
68 
미용업
20 
양식
 
4
이용업
 
3
기타요식업
 
3
Other values (2)
 
4

Length

Max length5
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한식
2nd row한식
3rd row한식
4th row미용업
5th row한식

Common Values

ValueCountFrequency (%)
한식 68
66.7%
미용업 20
 
19.6%
양식 4
 
3.9%
이용업 3
 
2.9%
기타요식업 3
 
2.9%
목욕업 2
 
2.0%
중식 2
 
2.0%

Length

2024-05-04T08:00:43.582286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T08:00:44.054855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 68
66.7%
미용업 20
 
19.6%
양식 4
 
3.9%
이용업 3
 
2.9%
기타요식업 3
 
2.9%
목욕업 2
 
2.0%
중식 2
 
2.0%

업소명
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-04T08:00:44.788210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.9411765
Min length2

Characters and Unicode

Total characters504
Distinct characters195
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)100.0%

Sample

1st row두꺼비
2nd row광장서대회
3rd row광장서대회(교동점)
4th row퀸즈헤나 헤어샵
5th row사계절
ValueCountFrequency (%)
헤어샵 2
 
1.7%
미용실 2
 
1.7%
두꺼비 1
 
0.9%
수라식당 1
 
0.9%
숯불구이 1
 
0.9%
바다장어 1
 
0.9%
늘고운 1
 
0.9%
한마음 1
 
0.9%
짱구머리 1
 
0.9%
서교미용실 1
 
0.9%
Other values (103) 103
89.6%
2024-05-04T08:00:46.075126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 29
 
5.8%
당 28
 
5.6%
미 13
 
2.6%
용 13
 
2.6%
수 13
 
2.6%
13
 
2.6%
이 11
 
2.2%
실 11
 
2.2%
장 10
 
2.0%
국 10
 
2.0%
Other values (185) 353
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
96.0%
Space Separator 13
 
2.6%
Decimal Number 4
 
0.8%
Close Punctuation 2
 
0.4%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 29
 
6.0%
당 28
 
5.8%
미 13
 
2.7%
용 13
 
2.7%
수 13
 
2.7%
이 11
 
2.3%
실 11
 
2.3%
장 10
 
2.1%
국 10
 
2.1%
어 8
 
1.7%
Other values (179) 338
69.8%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
3 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 484
96.0%
Common 20
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 29
 
6.0%
당 28
 
5.8%
미 13
 
2.7%
용 13
 
2.7%
수 13
 
2.7%
이 11
 
2.3%
실 11
 
2.3%
장 10
 
2.1%
국 10
 
2.1%
어 8
 
1.7%
Other values (179) 338
69.8%
Common
ValueCountFrequency (%)
13
65.0%
) 2
 
10.0%
0 2
 
10.0%
3 1
 
5.0%
1 1
 
5.0%
( 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
96.0%
ASCII 20
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 29
 
6.0%
당 28
 
5.8%
미 13
 
2.7%
용 13
 
2.7%
수 13
 
2.7%
이 11
 
2.3%
실 11
 
2.3%
장 10
 
2.1%
국 10
 
2.1%
어 8
 
1.7%
Other values (179) 338
69.8%
ASCII
ValueCountFrequency (%)
13
65.0%
) 2
 
10.0%
0 2
 
10.0%
3 1
 
5.0%
1 1
 
5.0%
( 1
 
5.0%

주 취급음식
Text

Distinct53
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-04T08:00:46.712657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.4803922
Min length2

Characters and Unicode

Total characters355
Distinct characters113
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

Unique42 ?
Unique (%)41.2%

Sample

1st row장어구이(1인)
2nd row서대회(1인)
3rd row서대회(1인)
4th row파마
5th row고등어쌈밥
ValueCountFrequency (%)
백반 20
19.4%
커트 20
19.4%
게장백반 4
 
3.9%
자장면 2
 
1.9%
아메리카노 2
 
1.9%
갈치조림 2
 
1.9%
장어탕 2
 
1.9%
돈가스 2
 
1.9%
잔치국수 2
 
1.9%
서대회(1인 2
 
1.9%
Other values (44) 45
43.7%
2024-05-04T08:00:47.938341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
백 25
 
7.0%
반 25
 
7.0%
커 22
 
6.2%
트 22
 
6.2%
장 14
 
3.9%
) 9
 
2.5%
( 9
 
2.5%
탕 8
 
2.3%
국 8
 
2.3%
어 7
 
2.0%
Other values (103) 206
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 325
91.5%
Close Punctuation 9
 
2.5%
Open Punctuation 9
 
2.5%
Decimal Number 8
 
2.3%
Space Separator 2
 
0.6%
Lowercase Letter 1
 
0.3%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
백 25
 
7.7%
반 25
 
7.7%
커 22
 
6.8%
트 22
 
6.8%
장 14
 
4.3%
탕 8
 
2.5%
국 8
 
2.5%
어 7
 
2.2%
이 6
 
1.8%
지 6
 
1.8%
Other values (94) 182
56.0%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
0 2
25.0%
4 1
 
12.5%
2 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 325
91.5%
Common 29
 
8.2%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
백 25
 
7.7%
반 25
 
7.7%
커 22
 
6.8%
트 22
 
6.8%
장 14
 
4.3%
탕 8
 
2.5%
국 8
 
2.5%
어 7
 
2.2%
이 6
 
1.8%
지 6
 
1.8%
Other values (94) 182
56.0%
Common
ValueCountFrequency (%)
) 9
31.0%
( 9
31.0%
1 4
13.8%
2
 
6.9%
0 2
 
6.9%
4 1
 
3.4%
2 1
 
3.4%
+ 1
 
3.4%
Latin
ValueCountFrequency (%)
g 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 325
91.5%
ASCII 30
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
백 25
 
7.7%
반 25
 
7.7%
커 22
 
6.8%
트 22
 
6.8%
장 14
 
4.3%
탕 8
 
2.5%
국 8
 
2.5%
어 7
 
2.2%
이 6
 
1.8%
지 6
 
1.8%
Other values (94) 182
56.0%
ASCII
ValueCountFrequency (%)
) 9
30.0%
( 9
30.0%
1 4
13.3%
2
 
6.7%
0 2
 
6.7%
4 1
 
3.3%
2 1
 
3.3%
g 1
 
3.3%
+ 1
 
3.3%

소재지 주소
Text

Distinct99
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-05-04T08:00:48.806604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length22.039216
Min length15

Characters and Unicode

Total characters2248
Distinct characters109
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)95.1%

Sample

1st row전라남도 여수시 학동2길 7-4(학동)
2nd row전라남도 여수시 이순신광장로 129(중앙동)
3rd row전라남도 여수시 교동남1길 6-8(교동)
4th row전라남도 여수시 신기남2길 24-1(신기동)
5th row전라남도 여수시 여서동5길 9(여서동)
ValueCountFrequency (%)
전라남도 102
23.6%
여수시 102
23.6%
학동2길 5
 
1.2%
충무로 3
 
0.7%
2길 3
 
0.7%
장성1길 3
 
0.7%
교동남1길 3
 
0.7%
좌수영로 3
 
0.7%
7(학동 3
 
0.7%
이순신광장로 3
 
0.7%
Other values (186) 203
46.9%
2024-05-04T08:00:50.038955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
331
 
14.7%
여 126
 
5.6%
수 122
 
5.4%
남 120
 
5.3%
동 117
 
5.2%
시 110
 
4.9%
도 103
 
4.6%
전 102
 
4.5%
라 102
 
4.5%
( 96
 
4.3%
Other values (99) 919
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1384
61.6%
Space Separator 331
 
14.7%
Decimal Number 296
 
13.2%
Open Punctuation 96
 
4.3%
Close Punctuation 96
 
4.3%
Dash Punctuation 38
 
1.7%
Other Punctuation 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 126
 
9.1%
수 122
 
8.8%
남 120
 
8.7%
동 117
 
8.5%
시 110
 
7.9%
도 103
 
7.4%
전 102
 
7.4%
라 102
 
7.4%
길 71
 
5.1%
서 33
 
2.4%
Other values (84) 378
27.3%
Decimal Number
ValueCountFrequency (%)
1 82
27.7%
2 53
17.9%
3 35
11.8%
5 26
 
8.8%
4 24
 
8.1%
9 18
 
6.1%
6 18
 
6.1%
8 15
 
5.1%
7 14
 
4.7%
0 11
 
3.7%
Space Separator
ValueCountFrequency (%)
331
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1384
61.6%
Common 864
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 126
 
9.1%
수 122
 
8.8%
남 120
 
8.7%
동 117
 
8.5%
시 110
 
7.9%
도 103
 
7.4%
전 102
 
7.4%
라 102
 
7.4%
길 71
 
5.1%
서 33
 
2.4%
Other values (84) 378
27.3%
Common
ValueCountFrequency (%)
331
38.3%
( 96
 
11.1%
) 96
 
11.1%
1 82
 
9.5%
2 53
 
6.1%
- 38
 
4.4%
3 35
 
4.1%
5 26
 
3.0%
4 24
 
2.8%
9 18
 
2.1%
Other values (5) 65
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1384
61.6%
ASCII 864
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
38.3%
( 96
 
11.1%
) 96
 
11.1%
1 82
 
9.5%
2 53
 
6.1%
- 38
 
4.4%
3 35
 
4.1%
5 26
 
3.0%
4 24
 
2.8%
9 18
 
2.1%
Other values (5) 65
 
7.5%
Hangul
ValueCountFrequency (%)
여 126
 
9.1%
수 122
 
8.8%
남 120
 
8.7%
동 117
 
8.5%
시 110
 
7.9%
도 103
 
7.4%
전 102
 
7.4%
라 102
 
7.4%
길 71
 
5.1%
서 33
 
2.4%
Other values (84) 378
27.3%

가격(원)
Real number (ℝ)

Distinct20
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10377.451
Minimum1200
Maximum60000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-04T08:00:50.412306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile5000
Q17000
median9000
Q312000
95-th percentile19750
Maximum60000
Range58800
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation7269.9014
Coefficient of variation (CV)0.70054789
Kurtosis23.741456
Mean10377.451
Median Absolute Deviation (MAD)2000
Skewness4.273209
Sum1058500
Variance52851467
MonotonicityNot monotonic
2024-05-04T08:00:50.844684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
10000 22
21.6%
7000 16
15.7%
8000 13
12.7%
12000 11
10.8%
6000 10
9.8%
9000 5
 
4.9%
5000 5
 
4.9%
13000 5
 
4.9%
15000 3
 
2.9%
14000 2
 
2.0%
Other values (10) 10
9.8%
ValueCountFrequency (%)
1200 1
 
1.0%
2800 1
 
1.0%
3500 1
 
1.0%
5000 5
 
4.9%
6000 10
9.8%
7000 16
15.7%
8000 13
12.7%
9000 5
 
4.9%
10000 22
21.6%
11000 1
 
1.0%
ValueCountFrequency (%)
60000 1
 
1.0%
37000 1
 
1.0%
35000 1
 
1.0%
30000 1
 
1.0%
22000 1
 
1.0%
20000 1
 
1.0%
15000 3
 
2.9%
14000 2
 
2.0%
13000 5
4.9%
12000 11
10.8%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
Minimum2024-04-01 00:00:00
Maximum2024-04-01 00:00:00
2024-05-04T08:00:51.325969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:00:51.814327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-05-04T08:00:41.041812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:00:40.440190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:00:41.288269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T08:00:40.728780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T08:00:52.199049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종주 취급음식소재지 주소가격(원)
연번1.0000.2060.5790.9080.202
업종0.2061.0000.9811.0000.000
주 취급음식0.5790.9811.0000.9970.995
소재지 주소0.9081.0000.9971.0000.989
가격(원)0.2020.0000.9950.9891.000
2024-05-04T08:00:52.505658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번가격(원)업종
연번1.0000.0070.099
가격(원)0.0071.0000.000
업종0.0990.0001.000

Missing values

2024-05-04T08:00:41.631581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T08:00:42.088823image/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

연번업종업소명주 취급음식소재지 주소가격(원)기준일자
01한식두꺼비장어구이(1인)전라남도 여수시 학동2길 7-4(학동)150002024-04-01
12한식광장서대회서대회(1인)전라남도 여수시 이순신광장로 129(중앙동)100002024-04-01
23한식광장서대회(교동점)서대회(1인)전라남도 여수시 교동남1길 6-8(교동)100002024-04-01
34미용업퀸즈헤나 헤어샵파마전라남도 여수시 신기남2길 24-1(신기동)300002024-04-01
45한식사계절고등어쌈밥전라남도 여수시 여서동5길 9(여서동)90002024-04-01
56미용업원경미용실커트(성인여성)전라남도 여수시 덕충2길 68-12(덕충동)70002024-04-01
67이용업새로나이용원커트+세발전라남도 여수시 여서1로 32(여서동)100002024-04-01
78이용업문수이용원커트전라남도 여수시 문수북6길 3(문수동)120002024-04-01
89한식하얀집낙지전문점산낙지전골(소)전라남도 여수시 장성1길 19(안산동)370002024-04-01
910한식대승백반전라남도 여수시 진남로 6-3(서교동)60002024-04-01
연번업종업소명주 취급음식소재지 주소가격(원)기준일자
9293미용업머리풍경커트전라남도 여수시 죽림중앙로 30-28100002024-04-01
9394한식조개까는세상조개구이전라남도 여수시 시청동5길 21-2(학동)350002024-04-01
9495한식대성국밥선지국밥전라남도 여수시 좌수영로 42(서교동)60002024-04-01
9596한식여천명신낙지산낙지볶음전라남도 여수시 거북선공원 1길 13(학동)130002024-04-01
9697중식박가네 옛날짜장자장면전라남도 여수시 학동2길 7-4(진남시장내)50002024-04-01
9798한식하나횟집회덮밥전라남도 여수시 대치3길 5-6(여서동)80002024-04-01
9899한식참죽사랑팥죽전라남도 여수시 광무1길 10(광무동)70002024-04-01
99100한식구이구이식당백반전라남도 여수시 공화남 2길 19 (공화동)60002024-04-01
100101한식남촌식당삼겹살전라남도 여수시 신기남길 33(신기동)100002024-04-01
101102한식영애네집밥백반전라남도 여수시 여수산단로 48, 1층(봉계동)80002024-04-01