Overview

Dataset statistics

Number of variables7
Number of observations454
Missing cells64
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.0 KiB
Average record size in memory56.3 B

Variable types

Categorical3
Text4

Dataset

Description제주특별자치도에서 지정하는 모범음식점과 관련한 데이터로 행정시,업소명,소재지(도로명),읍면동,전화번호,업태와 관련한 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15043694/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업태 is highly imbalanced (59.6%)Imbalance
전화번호 has 64 (14.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:48:41.591074
Analysis finished2023-12-12 03:48:42.425060
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정시
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
제주시
270 
서귀포시
184 

Length

Max length4
Median length3
Mean length3.4052863
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주시
2nd row제주시
3rd row제주시
4th row제주시
5th row제주시

Common Values

ValueCountFrequency (%)
제주시 270
59.5%
서귀포시 184
40.5%

Length

2023-12-12T12:48:42.518353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:42.662222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 270
59.5%
서귀포시 184
40.5%

업소명
Text

Distinct452
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T12:48:42.909617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length5.814978
Min length2

Characters and Unicode

Total characters2640
Distinct characters397
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique450 ?
Unique (%)99.1%

Sample

1st row푸른밤의해안속초식당
2nd row화순식당
3rd row남또리
4th row제주광해애월점
5th row장촌한우마을
ValueCountFrequency (%)
신창흑돼지두루치기 2
 
0.4%
바다풍경 2
 
0.4%
전원일기본점 1
 
0.2%
제주일도 1
 
0.2%
푸른밤의해안속초식당 1
 
0.2%
제주고가네 1
 
0.2%
백록 1
 
0.2%
티라한식당 1
 
0.2%
성산미소복집 1
 
0.2%
성산일출봉어멍횟집 1
 
0.2%
Other values (445) 445
97.4%
2023-12-12T12:48:43.410166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 103
 
3.9%
주 79
 
3.0%
제 76
 
2.9%
해 48
 
1.8%
가 44
 
1.7%
지 41
 
1.6%
이 40
 
1.5%
장 40
 
1.5%
국 35
 
1.3%
집 35
 
1.3%
Other values (387) 2099
79.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2628
99.5%
Space Separator 3
 
0.1%
Other Symbol 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Decimal Number 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 103
 
3.9%
주 79
 
3.0%
제 76
 
2.9%
해 48
 
1.8%
가 44
 
1.7%
지 41
 
1.6%
이 40
 
1.5%
장 40
 
1.5%
국 35
 
1.3%
집 35
 
1.3%
Other values (380) 2087
79.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2630
99.6%
Common 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 103
 
3.9%
주 79
 
3.0%
제 76
 
2.9%
해 48
 
1.8%
가 44
 
1.7%
지 41
 
1.6%
이 40
 
1.5%
장 40
 
1.5%
국 35
 
1.3%
집 35
 
1.3%
Other values (381) 2089
79.4%
Common
ValueCountFrequency (%)
3
30.0%
( 2
20.0%
) 2
20.0%
. 1
 
10.0%
1 1
 
10.0%
2 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2628
99.5%
ASCII 10
 
0.4%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 103
 
3.9%
주 79
 
3.0%
제 76
 
2.9%
해 48
 
1.8%
가 44
 
1.7%
지 41
 
1.6%
이 40
 
1.5%
장 40
 
1.5%
국 35
 
1.3%
집 35
 
1.3%
Other values (380) 2087
79.4%
ASCII
ValueCountFrequency (%)
3
30.0%
( 2
20.0%
) 2
20.0%
. 1
 
10.0%
1 1
 
10.0%
2 1
 
10.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

소재지(도로명)
Text

Distinct443
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T12:48:43.726471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length21.669604
Min length16

Characters and Unicode

Total characters9838
Distinct characters186
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

Unique434 ?
Unique (%)95.6%

Sample

1st row제주특별자치도 제주시 노형로 40
2nd row제주특별자치도 제주시 광성로 269
3rd row제주특별자치도 제주시 애월읍 애월해안로 384
4th row제주특별자치도 제주시 애월해안로 867
5th row제주특별자치도 제주시 애월읍 천덕로 440-4
ValueCountFrequency (%)
제주특별자치도 454
23.2%
제주시 270
 
13.8%
서귀포시 184
 
9.4%
조천읍 28
 
1.4%
성산읍 28
 
1.4%
일주동로 15
 
0.8%
대정읍 15
 
0.8%
애월읍 14
 
0.7%
안덕면 13
 
0.7%
연북로 13
 
0.7%
Other values (545) 926
47.2%
2023-12-12T12:48:44.243930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1506
15.3%
주 750
 
7.6%
제 735
 
7.5%
도 478
 
4.9%
자 458
 
4.7%
시 456
 
4.6%
특 454
 
4.6%
별 454
 
4.6%
치 454
 
4.6%
로 381
 
3.9%
Other values (176) 3712
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6887
70.0%
Space Separator 1506
 
15.3%
Decimal Number 1367
 
13.9%
Dash Punctuation 78
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 750
 
10.9%
제 735
 
10.7%
도 478
 
6.9%
자 458
 
6.7%
시 456
 
6.6%
특 454
 
6.6%
별 454
 
6.6%
치 454
 
6.6%
로 381
 
5.5%
서 229
 
3.3%
Other values (164) 2038
29.6%
Decimal Number
ValueCountFrequency (%)
1 265
19.4%
2 181
13.2%
4 170
12.4%
3 156
11.4%
6 123
9.0%
5 122
8.9%
8 91
 
6.7%
7 89
 
6.5%
0 88
 
6.4%
9 82
 
6.0%
Space Separator
ValueCountFrequency (%)
1506
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6887
70.0%
Common 2951
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 750
 
10.9%
제 735
 
10.7%
도 478
 
6.9%
자 458
 
6.7%
시 456
 
6.6%
특 454
 
6.6%
별 454
 
6.6%
치 454
 
6.6%
로 381
 
5.5%
서 229
 
3.3%
Other values (164) 2038
29.6%
Common
ValueCountFrequency (%)
1506
51.0%
1 265
 
9.0%
2 181
 
6.1%
4 170
 
5.8%
3 156
 
5.3%
6 123
 
4.2%
5 122
 
4.1%
8 91
 
3.1%
7 89
 
3.0%
0 88
 
3.0%
Other values (2) 160
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6887
70.0%
ASCII 2951
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1506
51.0%
1 265
 
9.0%
2 181
 
6.1%
4 170
 
5.8%
3 156
 
5.3%
6 123
 
4.2%
5 122
 
4.1%
8 91
 
3.1%
7 89
 
3.0%
0 88
 
3.0%
Other values (2) 160
 
5.4%
Hangul
ValueCountFrequency (%)
주 750
 
10.9%
제 735
 
10.7%
도 478
 
6.9%
자 458
 
6.7%
시 456
 
6.6%
특 454
 
6.6%
별 454
 
6.6%
치 454
 
6.6%
로 381
 
5.5%
서 229
 
3.3%
Other values (164) 2038
29.6%

읍면동
Text

Distinct61
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T12:48:44.492715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.160793
Min length2

Characters and Unicode

Total characters1435
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.2%

Sample

1st row해안동
2nd row애월읍
3rd row애월읍
4th row애월읍
5th row애월읍
ValueCountFrequency (%)
노형동 37
 
8.1%
연동 35
 
7.7%
성산읍 30
 
6.6%
서귀동 28
 
6.2%
조천읍 28
 
6.2%
이도이동 17
 
3.7%
색달동 17
 
3.7%
대정읍 16
 
3.5%
애월읍 16
 
3.5%
안덕면 13
 
2.9%
Other values (51) 217
47.8%
2023-12-12T12:48:44.905367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 320
22.3%
읍 117
 
8.2%
이 84
 
5.9%
도 56
 
3.9%
일 48
 
3.3%
노 37
 
2.6%
서 37
 
2.6%
형 37
 
2.6%
연 35
 
2.4%
성 30
 
2.1%
Other values (58) 634
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1435
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 320
22.3%
읍 117
 
8.2%
이 84
 
5.9%
도 56
 
3.9%
일 48
 
3.3%
노 37
 
2.6%
서 37
 
2.6%
형 37
 
2.6%
연 35
 
2.4%
성 30
 
2.1%
Other values (58) 634
44.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1435
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 320
22.3%
읍 117
 
8.2%
이 84
 
5.9%
도 56
 
3.9%
일 48
 
3.3%
노 37
 
2.6%
서 37
 
2.6%
형 37
 
2.6%
연 35
 
2.4%
성 30
 
2.1%
Other values (58) 634
44.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1435
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 320
22.3%
읍 117
 
8.2%
이 84
 
5.9%
도 56
 
3.9%
일 48
 
3.3%
노 37
 
2.6%
서 37
 
2.6%
형 37
 
2.6%
연 35
 
2.4%
성 30
 
2.1%
Other values (58) 634
44.2%

전화번호
Text

MISSING 

Distinct389
Distinct (%)99.7%
Missing64
Missing (%)14.1%
Memory size3.7 KiB
2023-12-12T12:48:45.164338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.002564
Min length9

Characters and Unicode

Total characters4681
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

Unique388 ?
Unique (%)99.5%

Sample

1st row064-753-3919
2nd row064-747-7873
3rd row064-799-1711
4th row064-713-4789
5th row064-799-7889
ValueCountFrequency (%)
064-738-5435 2
 
0.5%
064-733-5921 1
 
0.3%
064-753-3919 1
 
0.3%
064-782-6868 1
 
0.3%
064-782-1150 1
 
0.3%
064-784-9779 1
 
0.3%
064-784-6888 1
 
0.3%
064-782-1089 1
 
0.3%
064-783-5656 1
 
0.3%
064-784-8001 1
 
0.3%
Other values (379) 379
97.2%
2023-12-12T12:48:45.671443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 778
16.6%
0 616
13.2%
4 608
13.0%
7 576
12.3%
6 571
12.2%
8 296
 
6.3%
2 294
 
6.3%
3 275
 
5.9%
9 247
 
5.3%
1 215
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3903
83.4%
Dash Punctuation 778
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 616
15.8%
4 608
15.6%
7 576
14.8%
6 571
14.6%
8 296
7.6%
2 294
7.5%
3 275
7.0%
9 247
6.3%
1 215
 
5.5%
5 205
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 778
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4681
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 778
16.6%
0 616
13.2%
4 608
13.0%
7 576
12.3%
6 571
12.2%
8 296
 
6.3%
2 294
 
6.3%
3 275
 
5.9%
9 247
 
5.3%
1 215
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4681
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 778
16.6%
0 616
13.2%
4 608
13.0%
7 576
12.3%
6 571
12.2%
8 296
 
6.3%
2 294
 
6.3%
3 275
 
5.9%
9 247
 
5.3%
1 215
 
4.6%

업태
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
한식
352 
일식
67 
중식
 
15
서양식
 
9
양식
 
5
Other values (2)
 
6

Length

Max length3
Median length2
Mean length2.0330396
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 352
77.5%
일식 67
 
14.8%
중식 15
 
3.3%
서양식 9
 
2.0%
양식 5
 
1.1%
뷔페식 3
 
0.7%
뷔폐식 3
 
0.7%

Length

2023-12-12T12:48:45.982610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:46.137971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 352
77.5%
일식 67
 
14.8%
중식 15
 
3.3%
서양식 9
 
2.0%
양식 5
 
1.1%
뷔페식 3
 
0.7%
뷔폐식 3
 
0.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-08-07
454 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 454
100.0%

Length

2023-12-12T12:48:46.323891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:48:46.443897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 454
100.0%

Correlations

2023-12-12T12:48:46.520902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정시읍면동업태
행정시1.0001.0000.185
읍면동1.0001.0000.000
업태0.1850.0001.000
2023-12-12T12:48:46.647658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태행정시
업태1.0000.197
행정시0.1971.000
2023-12-12T12:48:46.760049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정시업태
행정시1.0000.197
업태0.1971.000

Missing values

2023-12-12T12:48:42.196074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:48:42.356581image/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

행정시업소명소재지(도로명)읍면동전화번호업태데이터기준일자
0제주시푸른밤의해안속초식당제주특별자치도 제주시 노형로 40해안동064-753-3919한식2023-08-07
1제주시화순식당제주특별자치도 제주시 광성로 269애월읍064-747-7873한식2023-08-07
2제주시남또리제주특별자치도 제주시 애월읍 애월해안로 384애월읍064-799-1711일식2023-08-07
3제주시제주광해애월점제주특별자치도 제주시 애월해안로 867애월읍064-713-4789한식2023-08-07
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