Overview

Dataset statistics

Number of variables5
Number of observations104
Missing cells7
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory42.3 B

Variable types

Numeric1
Text4

Dataset

Description목포시에서 지정한 모범음식점에 대한 현황을 상호명, 소재지, 전화번호, 주된음식 현황을 제공하여 많은 관광객들이 와서 맛의도시 목포시를 알리고자 합니다.
URLhttps://www.data.go.kr/data/3079048/fileData.do

Alerts

연번 has 6 (5.8%) missing valuesMissing
상호명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:15:57.259924
Analysis finished2023-12-12 04:15:58.128706
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

MISSING 

Distinct98
Distinct (%)100.0%
Missing6
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean49.5
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T13:15:58.255887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.85
Q125.25
median49.5
Q373.75
95-th percentile93.15
Maximum98
Range97
Interquartile range (IQR)48.5

Descriptive statistics

Standard deviation28.434134
Coefficient of variation (CV)0.57442696
Kurtosis-1.2
Mean49.5
Median Absolute Deviation (MAD)24.5
Skewness0
Sum4851
Variance808.5
MonotonicityStrictly increasing
2023-12-12T13:15:58.445273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (88) 88
84.6%
(Missing) 6
 
5.8%
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 (%)
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%

상호명
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-12T13:15:58.787573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length6
Min length2

Characters and Unicode

Total characters624
Distinct characters203
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

Unique104 ?
Unique (%)100.0%

Sample

1st row24시돌솥밥 설렁탕
2nd row가산팔복초밥목포법원점
3rd row고려삼계탕
4th row고흥삼계탕
5th row곰집갈비
ValueCountFrequency (%)
24시돌솥밥 1
 
0.9%
송옥정 1
 
0.9%
입큰아구찜알곤이찜북항점 1
 
0.9%
일식수 1
 
0.9%
인동주마을 1
 
0.9%
이가본가 1
 
0.9%
유달산숯불갈비 1
 
0.9%
울도숯불갈비 1
 
0.9%
옥정 1
 
0.9%
오거리 1
 
0.9%
Other values (96) 96
90.6%
2023-12-12T13:15:59.275258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 21
 
3.4%
포 21
 
3.4%
목 18
 
2.9%
집 17
 
2.7%
식 16
 
2.6%
가 14
 
2.2%
비 13
 
2.1%
탕 12
 
1.9%
정 12
 
1.9%
당 9
 
1.4%
Other values (193) 471
75.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 597
95.7%
Open Punctuation 8
 
1.3%
Close Punctuation 8
 
1.3%
Decimal Number 5
 
0.8%
Space Separator 2
 
0.3%
Lowercase Letter 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 21
 
3.5%
포 21
 
3.5%
목 18
 
3.0%
집 17
 
2.8%
식 16
 
2.7%
가 14
 
2.3%
비 13
 
2.2%
탕 12
 
2.0%
정 12
 
2.0%
당 9
 
1.5%
Other values (181) 444
74.4%
Decimal Number
ValueCountFrequency (%)
2 1
20.0%
0 1
20.0%
5 1
20.0%
9 1
20.0%
4 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
i 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
I 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 597
95.7%
Common 23
 
3.7%
Latin 4
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 21
 
3.5%
포 21
 
3.5%
목 18
 
3.0%
집 17
 
2.8%
식 16
 
2.7%
가 14
 
2.3%
비 13
 
2.2%
탕 12
 
2.0%
정 12
 
2.0%
당 9
 
1.5%
Other values (181) 444
74.4%
Common
ValueCountFrequency (%)
( 8
34.8%
) 8
34.8%
2
 
8.7%
2 1
 
4.3%
0 1
 
4.3%
5 1
 
4.3%
9 1
 
4.3%
4 1
 
4.3%
Latin
ValueCountFrequency (%)
n 1
25.0%
i 1
25.0%
N 1
25.0%
I 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 597
95.7%
ASCII 27
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 21
 
3.5%
포 21
 
3.5%
목 18
 
3.0%
집 17
 
2.8%
식 16
 
2.7%
가 14
 
2.3%
비 13
 
2.2%
탕 12
 
2.0%
정 12
 
2.0%
당 9
 
1.5%
Other values (181) 444
74.4%
ASCII
ValueCountFrequency (%)
( 8
29.6%
) 8
29.6%
2
 
7.4%
2 1
 
3.7%
0 1
 
3.7%
5 1
 
3.7%
9 1
 
3.7%
n 1
 
3.7%
i 1
 
3.7%
N 1
 
3.7%
Other values (2) 2
 
7.4%

소재지
Text

UNIQUE 

Distinct104
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-12T13:15:59.609717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length36
Mean length26.336538
Min length19

Characters and Unicode

Total characters2739
Distinct characters118
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

Unique104 ?
Unique (%)100.0%

Sample

1st row전라남도 목포시 연산로 138, 1층 (연산동)
2nd row전라남도 목포시 정의로 4-5, 1층 (옥암동)
3rd row전라남도 목포시 교육로 11 (상동)
4th row전라남도 목포시 복산길6번길 40 (옥암동)
5th row전라남도 목포시 호남로58번길 14 (창평동,,11,12)
ValueCountFrequency (%)
전라남도 104
18.2%
목포시 104
18.2%
1층 33
 
5.8%
상동 33
 
5.8%
옥암동 21
 
3.7%
평화로 13
 
2.3%
산정동 10
 
1.7%
미항로 7
 
1.2%
영산로 4
 
0.7%
원형동로 4
 
0.7%
Other values (185) 239
41.8%
2023-12-12T13:16:00.104383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
468
 
17.1%
1 146
 
5.3%
남 114
 
4.2%
동 111
 
4.1%
포 106
 
3.9%
시 105
 
3.8%
전 104
 
3.8%
도 104
 
3.8%
목 104
 
3.8%
라 104
 
3.8%
Other values (108) 1273
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1514
55.3%
Space Separator 468
 
17.1%
Decimal Number 435
 
15.9%
Close Punctuation 104
 
3.8%
Open Punctuation 104
 
3.8%
Other Punctuation 79
 
2.9%
Dash Punctuation 29
 
1.1%
Math Symbol 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 114
 
7.5%
동 111
 
7.3%
포 106
 
7.0%
시 105
 
6.9%
전 104
 
6.9%
도 104
 
6.9%
목 104
 
6.9%
라 104
 
6.9%
로 100
 
6.6%
층 55
 
3.6%
Other values (89) 507
33.5%
Decimal Number
ValueCountFrequency (%)
1 146
33.6%
2 68
15.6%
4 36
 
8.3%
3 34
 
7.8%
5 29
 
6.7%
6 29
 
6.7%
0 27
 
6.2%
8 23
 
5.3%
9 23
 
5.3%
7 20
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 78
98.7%
. 1
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
468
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1514
55.3%
Common 1222
44.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 114
 
7.5%
동 111
 
7.3%
포 106
 
7.0%
시 105
 
6.9%
전 104
 
6.9%
도 104
 
6.9%
목 104
 
6.9%
라 104
 
6.9%
로 100
 
6.6%
층 55
 
3.6%
Other values (89) 507
33.5%
Common
ValueCountFrequency (%)
468
38.3%
1 146
 
11.9%
) 104
 
8.5%
( 104
 
8.5%
, 78
 
6.4%
2 68
 
5.6%
4 36
 
2.9%
3 34
 
2.8%
- 29
 
2.4%
5 29
 
2.4%
Other values (7) 126
 
10.3%
Latin
ValueCountFrequency (%)
A 2
66.7%
M 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1514
55.3%
ASCII 1225
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
468
38.2%
1 146
 
11.9%
) 104
 
8.5%
( 104
 
8.5%
, 78
 
6.4%
2 68
 
5.6%
4 36
 
2.9%
3 34
 
2.8%
- 29
 
2.4%
5 29
 
2.4%
Other values (9) 129
 
10.5%
Hangul
ValueCountFrequency (%)
남 114
 
7.5%
동 111
 
7.3%
포 106
 
7.0%
시 105
 
6.9%
전 104
 
6.9%
도 104
 
6.9%
목 104
 
6.9%
라 104
 
6.9%
로 100
 
6.6%
층 55
 
3.6%
Other values (89) 507
33.5%

전화번호
Text

Distinct103
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Memory size964.0 B
2023-12-12T13:16:00.405986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.980583
Min length12

Characters and Unicode

Total characters1440
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)100.0%

Sample

1st row 061- 272-6900
2nd row0507-1487-8857
3rd row 061- 282-4464
4th row0507-1361-2928
5th row 061- 244-1567
ValueCountFrequency (%)
061 95
35.8%
282 9
 
3.4%
283 8
 
3.0%
284 7
 
2.6%
287 6
 
2.3%
285 4
 
1.5%
243 3
 
1.1%
281 3
 
1.1%
274 3
 
1.1%
2
 
0.8%
Other values (118) 125
47.2%
2023-12-12T13:16:00.860744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 206
14.3%
197
13.7%
0 169
11.7%
2 166
11.5%
1 142
9.9%
6 128
8.9%
8 104
7.2%
7 79
 
5.5%
4 73
 
5.1%
3 72
 
5.0%
Other values (2) 104
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1037
72.0%
Dash Punctuation 206
 
14.3%
Space Separator 197
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169
16.3%
2 166
16.0%
1 142
13.7%
6 128
12.3%
8 104
10.0%
7 79
7.6%
4 73
7.0%
3 72
6.9%
5 61
 
5.9%
9 43
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 206
100.0%
Space Separator
ValueCountFrequency (%)
197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 206
14.3%
197
13.7%
0 169
11.7%
2 166
11.5%
1 142
9.9%
6 128
8.9%
8 104
7.2%
7 79
 
5.5%
4 73
 
5.1%
3 72
 
5.0%
Other values (2) 104
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 206
14.3%
197
13.7%
0 169
11.7%
2 166
11.5%
1 142
9.9%
6 128
8.9%
8 104
7.2%
7 79
 
5.5%
4 73
 
5.1%
3 72
 
5.0%
Other values (2) 104
7.2%

주된음식
Text

Distinct72
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Memory size964.0 B
2023-12-12T13:16:01.156185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.8653846
Min length1

Characters and Unicode

Total characters402
Distinct characters104
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)51.0%

Sample

1st row설렁탕
2nd row초밥
3rd row삼계탕
4th row보양탕
5th row육류
ValueCountFrequency (%)
설렁탕 4
 
3.5%
감자탕 4
 
3.5%
생선구이 4
 
3.5%
한정식 4
 
3.5%
갈비 4
 
3.5%
회 4
 
3.5%
육류 4
 
3.5%
삼계탕 3
 
2.6%
일식회 3
 
2.6%
생고기 3
 
2.6%
Other values (66) 78
67.8%
2023-12-12T13:16:01.669554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 19
 
4.7%
식 19
 
4.7%
탕 17
 
4.2%
, 16
 
4.0%
생 13
 
3.2%
어 11
 
2.7%
11
 
2.7%
갈 11
 
2.7%
선 10
 
2.5%
비 10
 
2.5%
Other values (94) 265
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 375
93.3%
Other Punctuation 16
 
4.0%
Space Separator 11
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 19
 
5.1%
식 19
 
5.1%
탕 17
 
4.5%
생 13
 
3.5%
어 11
 
2.9%
갈 11
 
2.9%
선 10
 
2.7%
비 10
 
2.7%
찜 9
 
2.4%
정 9
 
2.4%
Other values (92) 247
65.9%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 375
93.3%
Common 27
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 19
 
5.1%
식 19
 
5.1%
탕 17
 
4.5%
생 13
 
3.5%
어 11
 
2.9%
갈 11
 
2.9%
선 10
 
2.7%
비 10
 
2.7%
찜 9
 
2.4%
정 9
 
2.4%
Other values (92) 247
65.9%
Common
ValueCountFrequency (%)
, 16
59.3%
11
40.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 375
93.3%
ASCII 27
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 19
 
5.1%
식 19
 
5.1%
탕 17
 
4.5%
생 13
 
3.5%
어 11
 
2.9%
갈 11
 
2.9%
선 10
 
2.7%
비 10
 
2.7%
찜 9
 
2.4%
정 9
 
2.4%
Other values (92) 247
65.9%
ASCII
ValueCountFrequency (%)
, 16
59.3%
11
40.7%

Interactions

2023-12-12T13:15:57.650498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:16:01.824432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주된음식
연번1.0000.138
주된음식0.1381.000

Missing values

2023-12-12T13:15:57.785143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:15:57.923750image/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.
2023-12-12T13:15:58.050182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호명소재지전화번호주된음식
0124시돌솥밥 설렁탕전라남도 목포시 연산로 138, 1층 (연산동)061- 272-6900설렁탕
12가산팔복초밥목포법원점전라남도 목포시 정의로 4-5, 1층 (옥암동)0507-1487-8857초밥
23고려삼계탕전라남도 목포시 교육로 11 (상동)061- 282-4464삼계탕
34고흥삼계탕전라남도 목포시 복산길6번길 40 (옥암동)0507-1361-2928보양탕
45곰집갈비전라남도 목포시 호남로58번길 14 (창평동,,11,12)061- 244-1567육류
56금강산감자탕전라남도 목포시 연산로 181 (산정동,외1필지)061 -278 -4080감자탕
67금메달전라남도 목포시 후광대로143번길 8, 1층 (옥암동)061 -272 -2697홍어
78김근호해물한정식in목포전라남도 목포시 정의로 4-3 (옥암동)061 -283 -5777해물한정식
89김영희강남동태찜전라남도 목포시 복산길 52 (옥암동)061- 287-7707동태찜, 탕
910꽃마름(목포하당점)전라남도 목포시 평화로61번길 19 (상동,,2층)061 -287 -5115샤브샤브
연번상호명소재지전화번호주된음식
9495한양한정식전라남도 목포시 평화로 126 (옥암동,외1필지)061- 283-8225한정식
9596해물의제왕전라남도 목포시 영산로 252, 1층 (용당동)061 -279 -5977해물전골
9697해빔목포비빔밥전라남도 목포시 미항로 83, 1층 (상동)061 -282 -2770해초비빔밥
9798해왕궁계절음식전라남도 목포시 평화로 55 (상동)061 -282 -6364일식회
98<NA>해촌전라남도 목포시 미항로 133 (상동,1층)061- 283-7011바지락회무침
99<NA>호화대반점전라남도 목포시 옥암로46번길 8 (옥암동)061- 283-9985중국식
100<NA>홍가네생고기전문점전라남도 목포시 포미로10번길 18 (용해동)061 -274 -6522식육
101<NA>홍길동선어회전라남도 목포시 비파로43번길 42-1, 1층 (상동)061 -283 -8540선어회
102<NA>황금밥상전라남도 목포시 평화로 112, 1층 (옥암동)061 -287 -7400회, 찜
103<NA>황금어장전라남도 목포시 미항로 89 (상동)061 -281 -3772일식회