Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory45.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description음식물류 폐기물 다량배출사업장 범위❍ 식품위생법 제2조제12호에 따른 집단급식소▷1일 평균 급식인원(아침+점심+저녁) 100명이상 *유치원의 경우 200명이상❍ 식품위생법 제36조제1항제3호에 따른 휴게음식점 및 일반음식점▷영업장 면적 600㎡이상❍ 유통산업발전법」제2조제3호에 따른 대규모점포❍ 관광진흥법 제3조제1항제2호에 따른 관광숙박업➥ 법 제17조제2항에 따른 사업장폐기물배출자인 경우에는 제외
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15025001/fileData.do

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:50:57.102998
Analysis finished2024-03-23 05:50:58.627905
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-23T05:50:58.813424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2024-03-23T05:50:59.296072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

업종별
Categorical

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
집단급식소
22 
일반음식점
4 
관광숙박업
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 22
81.5%
일반음식점 4
 
14.8%
관광숙박업 1
 
3.7%

Length

2024-03-23T05:50:59.948055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:51:00.454535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 22
81.5%
일반음식점 4
 
14.8%
관광숙박업 1
 
3.7%

업소명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-23T05:51:01.367366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.481481
Min length2

Characters and Unicode

Total characters283
Distinct characters127
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row연천초등학교
2nd row과정초등학교
3rd row연동초등학교
4th row㈜아워홈 부산외고점
5th row세영식품㈜ 부산교육대학교(생활3관)
ValueCountFrequency (%)
㈜유니온푸드 2
 
4.7%
연천초등학교 1
 
2.3%
아이사랑병원 1
 
2.3%
㈜웰스프레쉬홈플러스아시아드점 1
 
2.3%
부산검찰청 1
 
2.3%
㈜현대그린푸드현대차부산하이테크점 1
 
2.3%
㈜녹채원푸드시스템 1
 
2.3%
부산식약청점 1
 
2.3%
㈜올리브푸드 1
 
2.3%
삼성여객점 1
 
2.3%
Other values (32) 32
74.4%
2024-03-23T05:51:03.067624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
6.7%
㈜ 10
 
3.5%
산 8
 
2.8%
드 8
 
2.8%
점 8
 
2.8%
부 8
 
2.8%
푸 7
 
2.5%
스 7
 
2.5%
교 5
 
1.8%
청 5
 
1.8%
Other values (117) 198
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 248
87.6%
Space Separator 19
 
6.7%
Other Symbol 10
 
3.5%
Uppercase Letter 2
 
0.7%
Other Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 8
 
3.2%
드 8
 
3.2%
점 8
 
3.2%
부 8
 
3.2%
푸 7
 
2.8%
스 7
 
2.8%
교 5
 
2.0%
청 5
 
2.0%
아 5
 
2.0%
대 4
 
1.6%
Other values (109) 183
73.8%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
91.2%
Common 23
 
8.1%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 10
 
3.9%
산 8
 
3.1%
드 8
 
3.1%
점 8
 
3.1%
부 8
 
3.1%
푸 7
 
2.7%
스 7
 
2.7%
교 5
 
1.9%
청 5
 
1.9%
아 5
 
1.9%
Other values (110) 187
72.5%
Common
ValueCountFrequency (%)
19
82.6%
& 1
 
4.3%
( 1
 
4.3%
) 1
 
4.3%
3 1
 
4.3%
Latin
ValueCountFrequency (%)
G 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 248
87.6%
ASCII 25
 
8.8%
None 10
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
76.0%
& 1
 
4.0%
G 1
 
4.0%
( 1
 
4.0%
) 1
 
4.0%
M 1
 
4.0%
3 1
 
4.0%
None
ValueCountFrequency (%)
㈜ 10
100.0%
Hangul
ValueCountFrequency (%)
산 8
 
3.2%
드 8
 
3.2%
점 8
 
3.2%
부 8
 
3.2%
푸 7
 
2.8%
스 7
 
2.8%
교 5
 
2.0%
청 5
 
2.0%
아 5
 
2.0%
대 4
 
1.6%
Other values (109) 183
73.8%

주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-23T05:51:04.112087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length24.444444
Min length21

Characters and Unicode

Total characters660
Distinct characters60
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

Unique27 ?
Unique (%)100.0%

Sample

1st row부산광역시 연제구 과정로225번길 46 (연산동)
2nd row부산광역시 연제구 과정로 164번길37 (연산동)
3rd row부산광역시 연제구 고분로56번길 40 (연산동)
4th row부산광역시 연제구 고분로 144 (연산동)
5th row부산광역시 연제구 교대로 24 (거제동)
ValueCountFrequency (%)
부산광역시 27
20.6%
연제구 27
20.6%
연산동 13
 
9.9%
거제동 9
 
6.9%
중앙대로 5
 
3.8%
고분로 2
 
1.5%
월드컵대로 2
 
1.5%
아시아드대로 1
 
0.8%
거제천로269번길 1
 
0.8%
1168 1
 
0.8%
Other values (43) 43
32.8%
2024-03-23T05:51:05.444298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
15.9%
연 44
 
6.7%
제 44
 
6.7%
산 41
 
6.2%
동 28
 
4.2%
시 28
 
4.2%
부 27
 
4.1%
) 27
 
4.1%
( 27
 
4.1%
로 27
 
4.1%
Other values (50) 262
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 413
62.6%
Space Separator 105
 
15.9%
Decimal Number 85
 
12.9%
Close Punctuation 27
 
4.1%
Open Punctuation 27
 
4.1%
Other Punctuation 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 44
10.7%
제 44
10.7%
산 41
9.9%
동 28
 
6.8%
시 28
 
6.8%
부 27
 
6.5%
로 27
 
6.5%
구 27
 
6.5%
역 27
 
6.5%
광 27
 
6.5%
Other values (35) 93
22.5%
Decimal Number
ValueCountFrequency (%)
1 20
23.5%
2 14
16.5%
4 13
15.3%
0 10
11.8%
6 8
 
9.4%
3 6
 
7.1%
8 5
 
5.9%
5 4
 
4.7%
7 3
 
3.5%
9 2
 
2.4%
Space Separator
ValueCountFrequency (%)
105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 413
62.6%
Common 247
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 44
10.7%
제 44
10.7%
산 41
9.9%
동 28
 
6.8%
시 28
 
6.8%
부 27
 
6.5%
로 27
 
6.5%
구 27
 
6.5%
역 27
 
6.5%
광 27
 
6.5%
Other values (35) 93
22.5%
Common
ValueCountFrequency (%)
105
42.5%
) 27
 
10.9%
( 27
 
10.9%
1 20
 
8.1%
2 14
 
5.7%
4 13
 
5.3%
0 10
 
4.0%
6 8
 
3.2%
3 6
 
2.4%
8 5
 
2.0%
Other values (5) 12
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 413
62.6%
ASCII 247
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
42.5%
) 27
 
10.9%
( 27
 
10.9%
1 20
 
8.1%
2 14
 
5.7%
4 13
 
5.3%
0 10
 
4.0%
6 8
 
3.2%
3 6
 
2.4%
8 5
 
2.0%
Other values (5) 12
 
4.9%
Hangul
ValueCountFrequency (%)
연 44
10.7%
제 44
10.7%
산 41
9.9%
동 28
 
6.8%
시 28
 
6.8%
부 27
 
6.5%
로 27
 
6.5%
구 27
 
6.5%
역 27
 
6.5%
광 27
 
6.5%
Other values (35) 93
22.5%

규모
Text

Distinct23
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-23T05:51:06.130881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.2962963
Min length3

Characters and Unicode

Total characters116
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)70.4%

Sample

1st row891명
2nd row485명
3rd row702명
4th row1000명
5th row800명
ValueCountFrequency (%)
300명 2
 
7.4%
100명 2
 
7.4%
1000명 2
 
7.4%
120명 2
 
7.4%
160명 1
 
3.7%
500명 1
 
3.7%
608.37㎡ 1
 
3.7%
1423.46㎡ 1
 
3.7%
1115㎡ 1
 
3.7%
723㎡ 1
 
3.7%
Other values (13) 13
48.1%
2024-03-23T05:51:07.180920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
26.7%
명 22
19.0%
1 15
12.9%
2 8
 
6.9%
3 6
 
5.2%
5 6
 
5.2%
4 5
 
4.3%
7 5
 
4.3%
6 4
 
3.4%
8 4
 
3.4%
Other values (4) 10
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
75.0%
Other Letter 23
 
19.8%
Other Symbol 4
 
3.4%
Other Punctuation 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
35.6%
1 15
17.2%
2 8
 
9.2%
3 6
 
6.9%
5 6
 
6.9%
4 5
 
5.7%
7 5
 
5.7%
6 4
 
4.6%
8 4
 
4.6%
9 3
 
3.4%
Other Letter
ValueCountFrequency (%)
명 22
95.7%
실 1
 
4.3%
Other Symbol
ValueCountFrequency (%)
㎡ 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
80.2%
Hangul 23
 
19.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
33.3%
1 15
16.1%
2 8
 
8.6%
3 6
 
6.5%
5 6
 
6.5%
4 5
 
5.4%
7 5
 
5.4%
6 4
 
4.3%
8 4
 
4.3%
㎡ 4
 
4.3%
Other values (2) 5
 
5.4%
Hangul
ValueCountFrequency (%)
명 22
95.7%
실 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89
76.7%
Hangul 23
 
19.8%
CJK Compat 4
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
34.8%
1 15
16.9%
2 8
 
9.0%
3 6
 
6.7%
5 6
 
6.7%
4 5
 
5.6%
7 5
 
5.6%
6 4
 
4.5%
8 4
 
4.5%
9 3
 
3.4%
Hangul
ValueCountFrequency (%)
명 22
95.7%
실 1
 
4.3%
CJK Compat
ValueCountFrequency (%)
㎡ 4
100.0%

Interactions

2024-03-23T05:50:57.734047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:51:07.721950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종별업소명주소규모
연번1.0000.6311.0001.0000.944
업종별0.6311.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
규모0.9441.0001.0001.0001.000
2024-03-23T05:51:08.183920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종별
연번1.0000.388
업종별0.3881.000

Missing values

2024-03-23T05:50:58.100801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:50:58.521111image/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

연번업종별업소명주소규모
01집단급식소연천초등학교부산광역시 연제구 과정로225번길 46 (연산동)891명
12집단급식소과정초등학교부산광역시 연제구 과정로 164번길37 (연산동)485명
23집단급식소연동초등학교부산광역시 연제구 고분로56번길 40 (연산동)702명
34집단급식소㈜아워홈 부산외고점부산광역시 연제구 고분로 144 (연산동)1000명
45집단급식소세영식품㈜ 부산교육대학교(생활3관)부산광역시 연제구 교대로 24 (거제동)800명
56집단급식소부산광역시 구내식당부산광역시 연제구 중앙대로 1001(연산동)1000명
67집단급식소㈜현대그린푸드 국세청점부산광역시 연제구 연제로 12 (연산동)290명
78집단급식소㈜다조에프엔에스 국세청별관부산광역시 연제구 토곡로 20 (연산동)90명
89집단급식소㈜유니온푸드 연제우체국부산광역시 연제구 법원북로 33 (거제동)230명
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