Overview

Dataset statistics

Number of variables6
Number of observations185
Missing cells43
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory49.7 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천 광역시 서구 관내에 위치한 위탁급식영업(업종명, 업소명, 소재지(도로명), 전화번호)현행 데이터 입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089639&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지(도로명) has 26 (14.1%) missing valuesMissing
전화번호 has 17 (9.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 12:07:19.031185
Analysis finished2024-01-28 12:07:19.635937
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93
Minimum1
Maximum185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-01-28T21:07:19.703239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.2
Q147
median93
Q3139
95-th percentile175.8
Maximum185
Range184
Interquartile range (IQR)92

Descriptive statistics

Standard deviation53.549043
Coefficient of variation (CV)0.57579616
Kurtosis-1.2
Mean93
Median Absolute Deviation (MAD)46
Skewness0
Sum17205
Variance2867.5
MonotonicityStrictly increasing
2024-01-28T21:07:19.817062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
128 1
 
0.5%
119 1
 
0.5%
120 1
 
0.5%
121 1
 
0.5%
122 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
Other values (175) 175
94.6%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%
180 1
0.5%
179 1
0.5%
178 1
0.5%
177 1
0.5%
176 1
0.5%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
위탁급식영업
185 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 185
100.0%

Length

2024-01-28T21:07:19.931464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:07:20.018337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 185
100.0%

업소명
Text

Distinct181
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-01-28T21:07:20.205103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.9189189
Min length2

Characters and Unicode

Total characters1835
Distinct characters277
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

Unique178 ?
Unique (%)96.2%

Sample

1st row(주)디온푸드(포레스코점)
2nd row현대식당
3rd row월매한식뷔페
4th row대성구내식당
5th row(주)명성에프에스
ValueCountFrequency (%)
주)아워홈 11
 
4.6%
주)동원홈푸드 6
 
2.5%
구내식당 4
 
1.7%
주)푸르웰 3
 
1.2%
주식회사 3
 
1.2%
주)한성세종푸드 2
 
0.8%
주)웰스프레쉬 2
 
0.8%
주)엘에스씨푸드 2
 
0.8%
주)후니드 2
 
0.8%
씨제이프레시웨이(주 2
 
0.8%
Other values (203) 204
84.6%
2024-01-28T21:07:20.526605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 88
 
4.8%
( 85
 
4.6%
) 85
 
4.6%
식 64
 
3.5%
드 58
 
3.2%
푸 56
 
3.1%
56
 
3.1%
당 52
 
2.8%
스 47
 
2.6%
점 42
 
2.3%
Other values (267) 1202
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1563
85.2%
Open Punctuation 85
 
4.6%
Close Punctuation 85
 
4.6%
Space Separator 56
 
3.1%
Uppercase Letter 25
 
1.4%
Decimal Number 17
 
0.9%
Lowercase Letter 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 88
 
5.6%
식 64
 
4.1%
드 58
 
3.7%
푸 56
 
3.6%
당 52
 
3.3%
스 47
 
3.0%
점 42
 
2.7%
이 40
 
2.6%
인 31
 
2.0%
구 28
 
1.8%
Other values (243) 1057
67.6%
Uppercase Letter
ValueCountFrequency (%)
C 6
24.0%
G 3
12.0%
S 3
12.0%
O 2
 
8.0%
P 2
 
8.0%
K 2
 
8.0%
F 2
 
8.0%
J 1
 
4.0%
D 1
 
4.0%
A 1
 
4.0%
Other values (2) 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
2 7
41.2%
1 5
29.4%
4 2
 
11.8%
3 1
 
5.9%
6 1
 
5.9%
5 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o 2
66.7%
d 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1563
85.2%
Common 244
 
13.3%
Latin 28
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 88
 
5.6%
식 64
 
4.1%
드 58
 
3.7%
푸 56
 
3.6%
당 52
 
3.3%
스 47
 
3.0%
점 42
 
2.7%
이 40
 
2.6%
인 31
 
2.0%
구 28
 
1.8%
Other values (243) 1057
67.6%
Latin
ValueCountFrequency (%)
C 6
21.4%
G 3
10.7%
S 3
10.7%
O 2
 
7.1%
P 2
 
7.1%
K 2
 
7.1%
F 2
 
7.1%
o 2
 
7.1%
J 1
 
3.6%
D 1
 
3.6%
Other values (4) 4
14.3%
Common
ValueCountFrequency (%)
( 85
34.8%
) 85
34.8%
56
23.0%
2 7
 
2.9%
1 5
 
2.0%
4 2
 
0.8%
3 1
 
0.4%
6 1
 
0.4%
5 1
 
0.4%
/ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1563
85.2%
ASCII 272
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 88
 
5.6%
식 64
 
4.1%
드 58
 
3.7%
푸 56
 
3.6%
당 52
 
3.3%
스 47
 
3.0%
점 42
 
2.7%
이 40
 
2.6%
인 31
 
2.0%
구 28
 
1.8%
Other values (243) 1057
67.6%
ASCII
ValueCountFrequency (%)
( 85
31.2%
) 85
31.2%
56
20.6%
2 7
 
2.6%
C 6
 
2.2%
1 5
 
1.8%
G 3
 
1.1%
S 3
 
1.1%
O 2
 
0.7%
P 2
 
0.7%
Other values (14) 18
 
6.6%

소재지(도로명)
Text

MISSING 

Distinct159
Distinct (%)100.0%
Missing26
Missing (%)14.1%
Memory size1.6 KiB
2024-01-28T21:07:20.769547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length42
Mean length31.893082
Min length21

Characters and Unicode

Total characters5071
Distinct characters247
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

Unique159 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 봉수대로 206 1동 2층 (가좌동)
2nd row인천광역시 서구 원당대로117번길 22 (오류동 현대선기(주)부속건축물 제1동)
3rd row인천광역시 서구 마중로 171 1층 (오류동)
4th row인천광역시 서구 검단천로356번길 26 (오류동 우양기공(주))
5th row인천광역시 서구 원창로 61-11 5층 (원창동 은성SMT)
ValueCountFrequency (%)
인천광역시 160
 
15.0%
서구 160
 
15.0%
가좌동 51
 
4.8%
1층 50
 
4.7%
오류동 37
 
3.5%
원창동 29
 
2.7%
3층 13
 
1.2%
일부호 12
 
1.1%
2층 11
 
1.0%
일부 11
 
1.0%
Other values (351) 532
49.9%
2024-01-28T21:07:21.150133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
907
 
17.9%
1 203
 
4.0%
동 201
 
4.0%
( 187
 
3.7%
) 187
 
3.7%
서 186
 
3.7%
인 173
 
3.4%
천 170
 
3.4%
구 164
 
3.2%
로 164
 
3.2%
Other values (237) 2529
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3011
59.4%
Space Separator 907
 
17.9%
Decimal Number 731
 
14.4%
Open Punctuation 187
 
3.7%
Close Punctuation 187
 
3.7%
Uppercase Letter 29
 
0.6%
Dash Punctuation 17
 
0.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 201
 
6.7%
서 186
 
6.2%
인 173
 
5.7%
천 170
 
5.6%
구 164
 
5.4%
로 164
 
5.4%
역 161
 
5.3%
시 161
 
5.3%
광 160
 
5.3%
층 117
 
3.9%
Other values (207) 1354
45.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
17.2%
A 4
13.8%
T 4
13.8%
R 2
 
6.9%
K 2
 
6.9%
C 2
 
6.9%
S 2
 
6.9%
M 1
 
3.4%
D 1
 
3.4%
I 1
 
3.4%
Other values (5) 5
17.2%
Decimal Number
ValueCountFrequency (%)
1 203
27.8%
2 91
12.4%
3 87
11.9%
4 76
 
10.4%
5 55
 
7.5%
6 52
 
7.1%
0 48
 
6.6%
8 42
 
5.7%
7 40
 
5.5%
9 37
 
5.1%
Space Separator
ValueCountFrequency (%)
907
100.0%
Open Punctuation
ValueCountFrequency (%)
( 187
100.0%
Close Punctuation
ValueCountFrequency (%)
) 187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3011
59.4%
Common 2031
40.1%
Latin 29
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 201
 
6.7%
서 186
 
6.2%
인 173
 
5.7%
천 170
 
5.6%
구 164
 
5.4%
로 164
 
5.4%
역 161
 
5.3%
시 161
 
5.3%
광 160
 
5.3%
층 117
 
3.9%
Other values (207) 1354
45.0%
Common
ValueCountFrequency (%)
907
44.7%
1 203
 
10.0%
( 187
 
9.2%
) 187
 
9.2%
2 91
 
4.5%
3 87
 
4.3%
4 76
 
3.7%
5 55
 
2.7%
6 52
 
2.6%
0 48
 
2.4%
Other values (5) 138
 
6.8%
Latin
ValueCountFrequency (%)
B 5
17.2%
A 4
13.8%
T 4
13.8%
R 2
 
6.9%
K 2
 
6.9%
C 2
 
6.9%
S 2
 
6.9%
M 1
 
3.4%
D 1
 
3.4%
I 1
 
3.4%
Other values (5) 5
17.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3011
59.4%
ASCII 2060
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
907
44.0%
1 203
 
9.9%
( 187
 
9.1%
) 187
 
9.1%
2 91
 
4.4%
3 87
 
4.2%
4 76
 
3.7%
5 55
 
2.7%
6 52
 
2.5%
0 48
 
2.3%
Other values (20) 167
 
8.1%
Hangul
ValueCountFrequency (%)
동 201
 
6.7%
서 186
 
6.2%
인 173
 
5.7%
천 170
 
5.6%
구 164
 
5.4%
로 164
 
5.4%
역 161
 
5.3%
시 161
 
5.3%
광 160
 
5.3%
층 117
 
3.9%
Other values (207) 1354
45.0%

전화번호
Text

MISSING 

Distinct85
Distinct (%)50.6%
Missing17
Missing (%)9.2%
Memory size1.6 KiB
2024-01-28T21:07:21.374676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.7619048
Min length1

Characters and Unicode

Total characters1136
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

Unique81 ?
Unique (%)48.2%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
032-584-7151 3
 
3.4%
02-589-3550 2
 
2.3%
031-748-3600 2
 
2.3%
032-717-5560 1
 
1.1%
032-820-5294 1
 
1.1%
070-5096-6128 1
 
1.1%
032-579-8859 1
 
1.1%
032-579-1002 1
 
1.1%
032-578-3528 1
 
1.1%
032-578-2432 1
 
1.1%
Other values (74) 74
84.1%
2024-01-28T21:07:21.697909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 182
16.0%
- 176
15.5%
2 135
11.9%
3 121
10.7%
5 100
8.8%
80
7.0%
8 74
6.5%
6 69
 
6.1%
1 59
 
5.2%
7 55
 
4.8%
Other values (2) 85
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 880
77.5%
Dash Punctuation 176
 
15.5%
Space Separator 80
 
7.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 182
20.7%
2 135
15.3%
3 121
13.8%
5 100
11.4%
8 74
8.4%
6 69
 
7.8%
1 59
 
6.7%
7 55
 
6.2%
9 45
 
5.1%
4 40
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1136
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 182
16.0%
- 176
15.5%
2 135
11.9%
3 121
10.7%
5 100
8.8%
80
7.0%
8 74
6.5%
6 69
 
6.1%
1 59
 
5.2%
7 55
 
4.8%
Other values (2) 85
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 182
16.0%
- 176
15.5%
2 135
11.9%
3 121
10.7%
5 100
8.8%
80
7.0%
8 74
6.5%
6 69
 
6.1%
1 59
 
5.2%
7 55
 
4.8%
Other values (2) 85
7.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2022-09-06
185 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-06
2nd row2022-09-06
3rd row2022-09-06
4th row2022-09-06
5th row2022-09-06

Common Values

ValueCountFrequency (%)
2022-09-06 185
100.0%

Length

2024-01-28T21:07:21.813317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T21:07:21.898964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-06 185
100.0%

Interactions

2024-01-28T21:07:19.339813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T21:07:21.948676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호
연번1.0000.865
전화번호0.8651.000

Missing values

2024-01-28T21:07:19.434731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T21:07:19.515257image/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.
2024-01-28T21:07:19.593369image/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

연번업종명업소명소재지(도로명)전화번호데이터기준일자
01위탁급식영업(주)디온푸드(포레스코점)인천광역시 서구 봉수대로 206 1동 2층 (가좌동)2022-09-06
12위탁급식영업현대식당인천광역시 서구 원당대로117번길 22 (오류동 현대선기(주)부속건축물 제1동)2022-09-06
23위탁급식영업월매한식뷔페인천광역시 서구 마중로 171 1층 (오류동)2022-09-06
34위탁급식영업대성구내식당인천광역시 서구 검단천로356번길 26 (오류동 우양기공(주))2022-09-06
45위탁급식영업(주)명성에프에스인천광역시 서구 원창로 61-11 5층 (원창동 은성SMT)2022-09-06
56위탁급식영업진우구내식당인천광역시 서구 보듬3로 20 (오류동 2동1층)2022-09-06
67위탁급식영업스토리푸드인천광역시 서구 청라사파이어로 226 (경서동 한국가스공사 인천지역본부)2022-09-06
78위탁급식영업푸드하우스 바낙스점인천광역시 서구 도담8로 28 (오류동 1층일부)2022-09-06
89위탁급식영업태진정밀식당인천광역시 서구 마중3로 12 (오류동 검단일반산업단지 태진정밀(주))2022-09-06
910위탁급식영업대명식당인천광역시 서구 원창로89번길 14-13 B동 1층 (원창동 (주)경인텍 내)2022-09-06
연번업종명업소명소재지(도로명)전화번호데이터기준일자
175176위탁급식영업(주)아워홈 공영산업점인천광역시 서구 정서진로 94 1층 (오류동)070-5096-61282022-09-06
176177위탁급식영업(주)아워홈 하나금융데이터센터청라점인천광역시 서구 에코로 181 하나금융그룹 통합데이터센터 1층 (청라동)070-7545-60792022-09-06
177178위탁급식영업(주)아워홈GS칼텍스윤활유공장점인천광역시 서구 중봉대로 364 (원창동)<NA>2022-09-06
178179위탁급식영업(주)진주랑푸드서비스디어포스점인천광역시 서구 가좌로83번길 52 (가좌동)<NA>2022-09-06
179180위탁급식영업엘케이푸드<NA><NA>2022-09-06
180181위탁급식영업인라온인천광역시 서구 가좌로12번길 39 (가좌동)<NA>2022-09-06
181182위탁급식영업서부교육청 구내식당인천광역시 서구 경명대로 713 (공촌동 서부교육지원청 지하1층)<NA>2022-09-06
182183위탁급식영업(주)지오푸드시스템<NA><NA>2022-09-06
183184위탁급식영업한영구내식당인천광역시 서구 북항로 28-26 (원창동 1층일부)<NA>2022-09-06
184185위탁급식영업(주)아워홈 동화기업 가좌1공장점인천광역시 서구 가정로97번길 28 1층 (가좌동)<NA>2022-09-06