Overview

Dataset statistics

Number of variables5
Number of observations34
Missing cells14
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.9 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 집단급식소 식품판매업 현황입니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15084147

Alerts

업종명 has constant value ""Constant
소재지전화 has 14 (41.2%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 11:20:27.656314
Analysis finished2024-01-28 11:20:28.027238
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
집단급식소 식품판매업
34 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 34
100.0%

Length

2024-01-28T20:20:28.075722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:20:28.144453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 34
50.0%
식품판매업 34
50.0%

업소명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-01-28T20:20:28.306248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.0588235
Min length2

Characters and Unicode

Total characters206
Distinct characters91
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

Unique34 ?
Unique (%)100.0%

Sample

1st row유푸드
2nd row크린수진
3rd row(주)서울축산
4th row(주)네이처테이블
5th row대동유통
ValueCountFrequency (%)
유푸드 1
 
2.8%
씨엠푸드시스템(주 1
 
2.8%
대한식자재마트 1
 
2.8%
참샘유통 1
 
2.8%
담덕푸드스토리 1
 
2.8%
길상회 1
 
2.8%
주식회사정도 1
 
2.8%
농업회사법인 1
 
2.8%
제이키즈푸드 1
 
2.8%
크린수진 1
 
2.8%
Other values (26) 26
72.2%
2024-01-28T20:20:28.572978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
6.3%
13
 
6.3%
12
 
5.8%
( 9
 
4.4%
) 9
 
4.4%
8
 
3.9%
6
 
2.9%
6
 
2.9%
4
 
1.9%
4
 
1.9%
Other values (81) 122
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 186
90.3%
Open Punctuation 9
 
4.4%
Close Punctuation 9
 
4.4%
Space Separator 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
7.0%
13
 
7.0%
12
 
6.5%
8
 
4.3%
6
 
3.2%
6
 
3.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (78) 112
60.2%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 186
90.3%
Common 20
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
7.0%
13
 
7.0%
12
 
6.5%
8
 
4.3%
6
 
3.2%
6
 
3.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (78) 112
60.2%
Common
ValueCountFrequency (%)
( 9
45.0%
) 9
45.0%
2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 186
90.3%
ASCII 20
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13
 
7.0%
13
 
7.0%
12
 
6.5%
8
 
4.3%
6
 
3.2%
6
 
3.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (78) 112
60.2%
ASCII
ValueCountFrequency (%)
( 9
45.0%
) 9
45.0%
2
 
10.0%
Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-01-28T20:20:28.781456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length40.5
Mean length35.235294
Min length24

Characters and Unicode

Total characters1198
Distinct characters101
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)88.2%

Sample

1st row인천광역시 부평구 여우재로26번길 31 나동 1~2층 (십정동)
2nd row인천광역시 부평구 길주남로89번길 12-17 101호 (부평동 풀하우스)
3rd row인천광역시 부평구 열우물로 157 (십정동)
4th row인천광역시 부평구 부평대로 283 부평우림라이온스밸리 A동 B115-16(7호실)호 (청천동)
5th row인천광역시 부평구 영성중로37번길 8 1층 (삼산동)
ValueCountFrequency (%)
인천광역시 34
 
14.5%
부평구 34
 
14.5%
1층 12
 
5.1%
삼산동 11
 
4.7%
일부호 8
 
3.4%
부평동 7
 
3.0%
십정동 5
 
2.1%
지하1층 4
 
1.7%
청천동 4
 
1.7%
3층 4
 
1.7%
Other values (88) 112
47.7%
2024-01-28T20:20:29.089474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
234
19.5%
64
 
5.3%
1 53
 
4.4%
49
 
4.1%
46
 
3.8%
42
 
3.5%
36
 
3.0%
36
 
3.0%
35
 
2.9%
) 35
 
2.9%
Other values (91) 568
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 683
57.0%
Space Separator 234
 
19.5%
Decimal Number 195
 
16.3%
Close Punctuation 35
 
2.9%
Open Punctuation 35
 
2.9%
Dash Punctuation 9
 
0.8%
Uppercase Letter 6
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
64
 
9.4%
49
 
7.2%
46
 
6.7%
42
 
6.1%
36
 
5.3%
36
 
5.3%
35
 
5.1%
34
 
5.0%
34
 
5.0%
34
 
5.0%
Other values (72) 273
40.0%
Decimal Number
ValueCountFrequency (%)
1 53
27.2%
2 27
13.8%
3 26
13.3%
0 19
 
9.7%
8 14
 
7.2%
6 13
 
6.7%
7 12
 
6.2%
5 11
 
5.6%
9 11
 
5.6%
4 9
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
M 1
 
16.7%
S 1
 
16.7%
A 1
 
16.7%
Space Separator
ValueCountFrequency (%)
234
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 683
57.0%
Common 509
42.5%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
64
 
9.4%
49
 
7.2%
46
 
6.7%
42
 
6.1%
36
 
5.3%
36
 
5.3%
35
 
5.1%
34
 
5.0%
34
 
5.0%
34
 
5.0%
Other values (72) 273
40.0%
Common
ValueCountFrequency (%)
234
46.0%
1 53
 
10.4%
) 35
 
6.9%
( 35
 
6.9%
2 27
 
5.3%
3 26
 
5.1%
0 19
 
3.7%
8 14
 
2.8%
6 13
 
2.6%
7 12
 
2.4%
Other values (5) 41
 
8.1%
Latin
ValueCountFrequency (%)
B 3
50.0%
M 1
 
16.7%
S 1
 
16.7%
A 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 683
57.0%
ASCII 515
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234
45.4%
1 53
 
10.3%
) 35
 
6.8%
( 35
 
6.8%
2 27
 
5.2%
3 26
 
5.0%
0 19
 
3.7%
8 14
 
2.7%
6 13
 
2.5%
7 12
 
2.3%
Other values (9) 47
 
9.1%
Hangul
ValueCountFrequency (%)
64
 
9.4%
49
 
7.2%
46
 
6.7%
42
 
6.1%
36
 
5.3%
36
 
5.3%
35
 
5.1%
34
 
5.0%
34
 
5.0%
34
 
5.0%
Other values (72) 273
40.0%
Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-01-28T20:20:29.492592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length24.588235
Min length17

Characters and Unicode

Total characters836
Distinct characters73
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)88.2%

Sample

1st row인천광역시 부평구 십정동 96-1 외 1필지 나동 1~2층
2nd row인천광역시 부평구 부평동 10-659 풀하우스 101호
3rd row인천광역시 부평구 십정동 118
4th row인천광역시 부평구 청천동 425 부평우림라이온스밸리 A동 B115-16(7호실)
5th row인천광역시 부평구 삼산동 117-14 1층
ValueCountFrequency (%)
인천광역시 34
18.8%
부평구 34
18.8%
삼산동 11
 
6.1%
1층 8
 
4.4%
부평동 7
 
3.9%
십정동 5
 
2.8%
일부 5
 
2.8%
청천동 4
 
2.2%
부개동 3
 
1.7%
7-1 2
 
1.1%
Other values (58) 68
37.6%
2024-01-28T20:20:29.780649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
17.7%
1 50
 
6.0%
50
 
6.0%
42
 
5.0%
39
 
4.7%
38
 
4.5%
35
 
4.2%
35
 
4.2%
34
 
4.1%
34
 
4.1%
Other values (63) 331
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
56.3%
Decimal Number 178
 
21.3%
Space Separator 148
 
17.7%
Dash Punctuation 32
 
3.8%
Uppercase Letter 4
 
0.5%
Math Symbol 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
10.6%
42
 
8.9%
39
 
8.3%
38
 
8.1%
35
 
7.4%
35
 
7.4%
34
 
7.2%
34
 
7.2%
34
 
7.2%
16
 
3.4%
Other values (44) 114
24.2%
Decimal Number
ValueCountFrequency (%)
1 50
28.1%
0 19
 
10.7%
3 16
 
9.0%
5 16
 
9.0%
6 15
 
8.4%
4 15
 
8.4%
7 13
 
7.3%
2 13
 
7.3%
9 12
 
6.7%
8 9
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
25.0%
M 1
25.0%
B 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
56.3%
Common 361
43.2%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
10.6%
42
 
8.9%
39
 
8.3%
38
 
8.1%
35
 
7.4%
35
 
7.4%
34
 
7.2%
34
 
7.2%
34
 
7.2%
16
 
3.4%
Other values (44) 114
24.2%
Common
ValueCountFrequency (%)
148
41.0%
1 50
 
13.9%
- 32
 
8.9%
0 19
 
5.3%
3 16
 
4.4%
5 16
 
4.4%
6 15
 
4.2%
4 15
 
4.2%
7 13
 
3.6%
2 13
 
3.6%
Other values (5) 24
 
6.6%
Latin
ValueCountFrequency (%)
S 1
25.0%
M 1
25.0%
B 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
56.3%
ASCII 365
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
40.5%
1 50
 
13.7%
- 32
 
8.8%
0 19
 
5.2%
3 16
 
4.4%
5 16
 
4.4%
6 15
 
4.1%
4 15
 
4.1%
7 13
 
3.6%
2 13
 
3.6%
Other values (9) 28
 
7.7%
Hangul
ValueCountFrequency (%)
50
10.6%
42
 
8.9%
39
 
8.3%
38
 
8.1%
35
 
7.4%
35
 
7.4%
34
 
7.2%
34
 
7.2%
34
 
7.2%
16
 
3.4%
Other values (44) 114
24.2%

소재지전화
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing14
Missing (%)41.2%
Memory size404.0 B
2024-01-28T20:20:29.930030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.05
Min length12

Characters and Unicode

Total characters241
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

Unique18 ?
Unique (%)90.0%

Sample

1st row032-462-6545
2nd row032-614-9164
3rd row032-577-8650
4th row070-8838-0223
5th row032-503-6422
ValueCountFrequency (%)
032-564-2691 2
 
10.0%
032-512-1309 1
 
5.0%
032-462-6545 1
 
5.0%
032-655-1573 1
 
5.0%
032-506-1700 1
 
5.0%
032-505-1100 1
 
5.0%
032-522-0747 1
 
5.0%
032-465-3500 1
 
5.0%
032-521-7133 1
 
5.0%
032-513-2882 1
 
5.0%
Other values (9) 9
45.0%
2024-01-28T20:20:30.171976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
17.8%
- 40
16.6%
2 36
14.9%
3 29
12.0%
5 25
10.4%
1 16
 
6.6%
6 15
 
6.2%
4 12
 
5.0%
7 10
 
4.1%
8 8
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
83.4%
Dash Punctuation 40
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
21.4%
2 36
17.9%
3 29
14.4%
5 25
12.4%
1 16
 
8.0%
6 15
 
7.5%
4 12
 
6.0%
7 10
 
5.0%
8 8
 
4.0%
9 7
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 241
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
17.8%
- 40
16.6%
2 36
14.9%
3 29
12.0%
5 25
10.4%
1 16
 
6.6%
6 15
 
6.2%
4 12
 
5.0%
7 10
 
4.1%
8 8
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
17.8%
- 40
16.6%
2 36
14.9%
3 29
12.0%
5 25
10.4%
1 16
 
6.6%
6 15
 
6.2%
4 12
 
5.0%
7 10
 
4.1%
8 8
 
3.3%

Correlations

2024-01-28T20:20:30.249855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지(지번)소재지전화
업소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2024-01-28T20:20:27.912272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:20:27.996928image/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

업종명업소명소재지(도로명)소재지(지번)소재지전화
0집단급식소 식품판매업유푸드인천광역시 부평구 여우재로26번길 31 나동 1~2층 (십정동)인천광역시 부평구 십정동 96-1 외 1필지 나동 1~2층032-462-6545
1집단급식소 식품판매업크린수진인천광역시 부평구 길주남로89번길 12-17 101호 (부평동 풀하우스)인천광역시 부평구 부평동 10-659 풀하우스 101호032-614-9164
2집단급식소 식품판매업(주)서울축산인천광역시 부평구 열우물로 157 (십정동)인천광역시 부평구 십정동 118032-577-8650
3집단급식소 식품판매업(주)네이처테이블인천광역시 부평구 부평대로 283 부평우림라이온스밸리 A동 B115-16(7호실)호 (청천동)인천광역시 부평구 청천동 425 부평우림라이온스밸리 A동 B115-16(7호실)070-8838-0223
4집단급식소 식품판매업대동유통인천광역시 부평구 영성중로37번길 8 1층 (삼산동)인천광역시 부평구 삼산동 117-14 1층<NA>
5집단급식소 식품판매업푸르닮인천광역시 부평구 체육관로174번길 13-18 1층 일부호 (삼산동)인천광역시 부평구 삼산동 449-12 1층 일부<NA>
6집단급식소 식품판매업영일상회인천광역시 부평구 부흥로316번길 19-5 (부평동 1층 일부)인천광역시 부평구 부평동 250-8 1층 일부032-503-6422
7집단급식소 식품판매업주식회사 돌봄푸드인천인천광역시 부평구 함봉로42번길 18 2층 일부호 (십정동)인천광역시 부평구 십정동 25-1 2층 일부<NA>
8집단급식소 식품판매업주식회사옥희네수산인천광역시 부평구 영성로 88 나동 2층 206 207호 (삼산동 청호빌딩)인천광역시 부평구 삼산동 507-3 외 1필지 청호빌딩 나동 206 207호032-508-9402
9집단급식소 식품판매업씨엠푸드시스템(주)인천광역시 부평구 동수로38번길 3 3층 (부평동)인천광역시 부평구 부평동 665-17032-432-8270
업종명업소명소재지(도로명)소재지(지번)소재지전화
24집단급식소 식품판매업다함푸드인천광역시 부평구 부흥로 395 지하1층 일부호 (부개동)인천광역시 부평구 부개동 66-3<NA>
25집단급식소 식품판매업(주)우리먹거리인천광역시 부평구 부평북로 123 상가동 지하1층 B08호 (청천동 무지개아파트)인천광역시 부평구 청천동 390-5 무지개아파트<NA>
26집단급식소 식품판매업채원인천광역시 부평구 백운로52번길 12 1층 (십정동)인천광역시 부평구 십정동 180-16<NA>
27집단급식소 식품판매업제이키즈푸드인천광역시 부평구 경인로1099번길 2 3층 일부호 (일신동)인천광역시 부평구 일신동 90-4 3층 일부<NA>
28집단급식소 식품판매업주식회사정도 농업회사법인인천광역시 부평구 여우재로26번길 31 (십정동 가동 1 3층)인천광역시 부평구 십정동 96-1 가동 1 3층032-465-3500
29집단급식소 식품판매업길상회인천광역시 부평구 부영로28번길 31-2 (부평동)인천광역시 부평구 부평동 751-158032-522-0747
30집단급식소 식품판매업담덕푸드스토리인천광역시 부평구 체육관로174번길 21 (삼산동)인천광역시 부평구 삼산동 449-22032-505-1100
31집단급식소 식품판매업참샘유통인천광역시 부평구 길주남로114번길 17 1층 (부개동)인천광역시 부평구 부개동 13-14 1층032-506-1700
32집단급식소 식품판매업대한식자재마트인천광역시 부평구 부흥북로107번길 39 (부평동)인천광역시 부평구 부평동 143-239 1층032-524-9005
33집단급식소 식품판매업프레시포유인천광역시 부평구 원적로300번길 36 1층 일부호 (산곡동)인천광역시 부평구 산곡동 180-421<NA>