Overview

Dataset statistics

Number of variables7
Number of observations217
Missing cells14
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory57.6 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description인천광역시 부평구 아동급식지정식당 현황 데이터는 관할기관, 가맹점명, 전화번호, 업태, 주소 등에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15102569/fileData.do

Alerts

가맹구분 has constant value ""Constant
순번 is highly overall correlated with 관할기관High correlation
관할기관 is highly overall correlated with 순번High correlation
전화번호 has 14 (6.5%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:37:41.078992
Analysis finished2023-12-12 12:37:41.734319
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct217
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109
Minimum1
Maximum217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T21:37:41.818875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.8
Q155
median109
Q3163
95-th percentile206.2
Maximum217
Range216
Interquartile range (IQR)108

Descriptive statistics

Standard deviation62.786676
Coefficient of variation (CV)0.57602455
Kurtosis-1.2
Mean109
Median Absolute Deviation (MAD)54
Skewness0
Sum23653
Variance3942.1667
MonotonicityStrictly increasing
2023-12-12T21:37:41.977978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
150 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
146 1
 
0.5%
Other values (207) 207
95.4%
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 (%)
217 1
0.5%
216 1
0.5%
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%
209 1
0.5%
208 1
0.5%

관할기관
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
부평4동
20 
삼산1동
17 
부개3동
17 
청천2동
15 
삼산2동
14 
Other values (18)
134 

Length

Max length4
Median length4
Mean length3.9585253
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부평4동 20
 
9.2%
삼산1동 17
 
7.8%
부개3동 17
 
7.8%
청천2동 15
 
6.9%
삼산2동 14
 
6.5%
십정2동 13
 
6.0%
부평1동 13
 
6.0%
부평5동 11
 
5.1%
산곡2동 11
 
5.1%
부평3동 10
 
4.6%
Other values (13) 76
35.0%

Length

2023-12-12T21:37:42.104935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부평4동 20
 
9.2%
삼산1동 17
 
7.8%
부개3동 17
 
7.8%
청천2동 15
 
6.9%
삼산2동 14
 
6.5%
십정2동 13
 
6.0%
부평1동 13
 
6.0%
부평5동 11
 
5.1%
산곡2동 11
 
5.1%
부평3동 10
 
4.6%
Other values (13) 76
35.0%

가맹점명
Text

Distinct208
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T21:37:42.345026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.1797235
Min length2

Characters and Unicode

Total characters1775
Distinct characters317
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)93.1%

Sample

1st rowCU(구,훼미리마트)(인천부평구)
2nd row코리아세븐(인천부평구)
3rd row한국미니스톱㈜(인천부평구)
4th row지에스리테일(GS25)(인천부평구)
5th row바이더웨이(부평구)
ValueCountFrequency (%)
파리바게트 22
 
6.9%
파리바게뜨 8
 
2.5%
본죽 6
 
1.9%
삼산점 5
 
1.6%
김밥천국 4
 
1.3%
본 4
 
1.3%
부평점 4
 
1.3%
뚜레쥬르 4
 
1.3%
죽&비빔밥 4
 
1.3%
인천삼산점 4
 
1.3%
Other values (221) 253
79.6%
2023-12-12T21:37:42.782921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 111
 
6.3%
101
 
5.7%
부 72
 
4.1%
리 54
 
3.0%
평 53
 
3.0%
트 42
 
2.4%
바 40
 
2.3%
천 39
 
2.2%
산 39
 
2.2%
파 38
 
2.1%
Other values (307) 1186
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1596
89.9%
Space Separator 101
 
5.7%
Decimal Number 19
 
1.1%
Open Punctuation 15
 
0.8%
Close Punctuation 15
 
0.8%
Uppercase Letter 13
 
0.7%
Other Punctuation 11
 
0.6%
Lowercase Letter 3
 
0.2%
Other Symbol 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 111
 
7.0%
부 72
 
4.5%
리 54
 
3.4%
평 53
 
3.3%
트 42
 
2.6%
바 40
 
2.5%
천 39
 
2.4%
산 39
 
2.4%
파 38
 
2.4%
게 37
 
2.3%
Other values (278) 1071
67.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
H 2
15.4%
G 2
15.4%
U 1
7.7%
S 1
7.7%
O 1
7.7%
P 1
7.7%
A 1
7.7%
B 1
7.7%
M 1
7.7%
Decimal Number
ValueCountFrequency (%)
4 4
21.1%
9 3
15.8%
1 3
15.8%
2 3
15.8%
8 2
10.5%
5 2
10.5%
0 1
 
5.3%
6 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
& 8
72.7%
. 2
 
18.2%
, 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
g 1
33.3%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1597
90.0%
Common 162
 
9.1%
Latin 16
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 111
 
7.0%
부 72
 
4.5%
리 54
 
3.4%
평 53
 
3.3%
트 42
 
2.6%
바 40
 
2.5%
천 39
 
2.4%
산 39
 
2.4%
파 38
 
2.4%
게 37
 
2.3%
Other values (279) 1072
67.1%
Common
ValueCountFrequency (%)
101
62.3%
( 15
 
9.3%
) 15
 
9.3%
& 8
 
4.9%
4 4
 
2.5%
9 3
 
1.9%
1 3
 
1.9%
2 3
 
1.9%
. 2
 
1.2%
8 2
 
1.2%
Other values (5) 6
 
3.7%
Latin
ValueCountFrequency (%)
C 2
12.5%
H 2
12.5%
G 2
12.5%
U 1
 
6.2%
S 1
 
6.2%
a 1
 
6.2%
g 1
 
6.2%
i 1
 
6.2%
O 1
 
6.2%
P 1
 
6.2%
Other values (3) 3
18.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1596
89.9%
ASCII 178
 
10.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 111
 
7.0%
부 72
 
4.5%
리 54
 
3.4%
평 53
 
3.3%
트 42
 
2.6%
바 40
 
2.5%
천 39
 
2.4%
산 39
 
2.4%
파 38
 
2.4%
게 37
 
2.3%
Other values (278) 1071
67.1%
ASCII
ValueCountFrequency (%)
101
56.7%
( 15
 
8.4%
) 15
 
8.4%
& 8
 
4.5%
4 4
 
2.2%
9 3
 
1.7%
1 3
 
1.7%
2 3
 
1.7%
C 2
 
1.1%
. 2
 
1.1%
Other values (18) 22
 
12.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct196
Distinct (%)96.6%
Missing14
Missing (%)6.5%
Memory size1.8 KiB
2023-12-12T21:37:43.038849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.004926
Min length9

Characters and Unicode

Total characters2437
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

Unique189 ?
Unique (%)93.1%

Sample

1st row1577-3663
2nd row02-2006-3439
3rd row02-6916-1500
4th row032-528-6688
5th row032-511-1478
ValueCountFrequency (%)
032-512-6288 2
 
1.0%
032-523-1023 2
 
1.0%
032-522-9098 2
 
1.0%
032-330-8265 2
 
1.0%
032-505-3582 2
 
1.0%
032-424-6661 2
 
1.0%
032-266-5400 2
 
1.0%
032-501-6288 1
 
0.5%
032-511-8255 1
 
0.5%
1577-3663 1
 
0.5%
Other values (186) 186
91.6%
2023-12-12T21:37:43.471951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 411
16.9%
- 405
16.6%
0 400
16.4%
3 328
13.5%
5 253
10.4%
1 141
 
5.8%
8 137
 
5.6%
6 104
 
4.3%
4 88
 
3.6%
7 87
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2032
83.4%
Dash Punctuation 405
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 411
20.2%
0 400
19.7%
3 328
16.1%
5 253
12.5%
1 141
 
6.9%
8 137
 
6.7%
6 104
 
5.1%
4 88
 
4.3%
7 87
 
4.3%
9 83
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 405
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2437
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 411
16.9%
- 405
16.6%
0 400
16.4%
3 328
13.5%
5 253
10.4%
1 141
 
5.8%
8 137
 
5.6%
6 104
 
4.3%
4 88
 
3.6%
7 87
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 411
16.9%
- 405
16.6%
0 400
16.4%
3 328
13.5%
5 253
10.4%
1 141
 
5.8%
8 137
 
5.6%
6 104
 
4.3%
4 88
 
3.6%
7 87
 
3.6%

업태
Categorical

Distinct7
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
한식
66 
분식
61 
제과점
61 
중식
11 
반찬
8 
Other values (2)
10 

Length

Max length3
Median length2
Mean length2.3087558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 66
30.4%
분식 61
28.1%
제과점 61
28.1%
중식 11
 
5.1%
반찬 8
 
3.7%
편의점 6
 
2.8%
마트 4
 
1.8%

Length

2023-12-12T21:37:43.619387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:37:43.731272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 66
30.4%
분식 61
28.1%
제과점 61
28.1%
중식 11
 
5.1%
반찬 8
 
3.7%
편의점 6
 
2.8%
마트 4
 
1.8%

가맹구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
일반
217 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 217
100.0%

Length

2023-12-12T21:37:43.853806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:37:43.950306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 217
100.0%

주소1
Text

Distinct202
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T21:37:44.213275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length24.40553
Min length15

Characters and Unicode

Total characters5296
Distinct characters161
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

Unique193 ?
Unique (%)88.9%

Sample

1st row인천광역시 부평구 전체 편의점 주소 해당
2nd row인천광역시 부평구 전체 편의점 주소 해당
3rd row인천광역시 부평구 전체 편의점 주소 해당
4th row인천광역시 부평구 전체 편의점 주소 해당
5th row인천광역시 부평구 전체 편의점 주소 해당
ValueCountFrequency (%)
인천광역시 217
19.9%
부평구 217
19.9%
부평동 44
 
4.0%
부개동 26
 
2.4%
산곡동 25
 
2.3%
삼산동 21
 
1.9%
갈산동 13
 
1.2%
청천동 12
 
1.1%
마장로 12
 
1.1%
십정동 11
 
1.0%
Other values (298) 493
45.2%
2023-12-12T21:37:44.642092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
874
 
16.5%
부 348
 
6.6%
평 294
 
5.6%
천 243
 
4.6%
인 225
 
4.2%
시 222
 
4.2%
광 221
 
4.2%
역 219
 
4.1%
구 217
 
4.1%
로 197
 
3.7%
Other values (151) 2236
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3377
63.8%
Space Separator 874
 
16.5%
Decimal Number 675
 
12.7%
Close Punctuation 137
 
2.6%
Open Punctuation 137
 
2.6%
Other Punctuation 66
 
1.2%
Dash Punctuation 28
 
0.5%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 348
 
10.3%
평 294
 
8.7%
천 243
 
7.2%
인 225
 
6.7%
시 222
 
6.6%
광 221
 
6.5%
역 219
 
6.5%
구 217
 
6.4%
로 197
 
5.8%
동 176
 
5.2%
Other values (135) 1015
30.1%
Decimal Number
ValueCountFrequency (%)
1 146
21.6%
2 90
13.3%
4 85
12.6%
3 79
11.7%
6 54
 
8.0%
5 51
 
7.6%
0 47
 
7.0%
7 43
 
6.4%
8 43
 
6.4%
9 37
 
5.5%
Space Separator
ValueCountFrequency (%)
874
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Other Punctuation
ValueCountFrequency (%)
, 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3377
63.8%
Common 1917
36.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 348
 
10.3%
평 294
 
8.7%
천 243
 
7.2%
인 225
 
6.7%
시 222
 
6.6%
광 221
 
6.5%
역 219
 
6.5%
구 217
 
6.4%
로 197
 
5.8%
동 176
 
5.2%
Other values (135) 1015
30.1%
Common
ValueCountFrequency (%)
874
45.6%
1 146
 
7.6%
) 137
 
7.1%
( 137
 
7.1%
2 90
 
4.7%
4 85
 
4.4%
3 79
 
4.1%
, 66
 
3.4%
6 54
 
2.8%
5 51
 
2.7%
Other values (5) 198
 
10.3%
Latin
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3377
63.8%
ASCII 1917
36.2%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
874
45.6%
1 146
 
7.6%
) 137
 
7.1%
( 137
 
7.1%
2 90
 
4.7%
4 85
 
4.4%
3 79
 
4.1%
, 66
 
3.4%
6 54
 
2.8%
5 51
 
2.7%
Other values (5) 198
 
10.3%
Hangul
ValueCountFrequency (%)
부 348
 
10.3%
평 294
 
8.7%
천 243
 
7.2%
인 225
 
6.7%
시 222
 
6.6%
광 221
 
6.5%
역 219
 
6.5%
구 217
 
6.4%
로 197
 
5.8%
동 176
 
5.2%
Other values (135) 1015
30.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

Interactions

2023-12-12T21:37:41.479117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:37:44.740124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번관할기관업태
순번1.0000.9820.358
관할기관0.9821.0000.720
업태0.3580.7201.000
2023-12-12T21:37:44.820931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할기관업태
관할기관1.0000.396
업태0.3961.000
2023-12-12T21:37:44.902122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번관할기관업태
순번1.0000.8660.187
관할기관0.8661.0000.396
업태0.1870.3961.000

Missing values

2023-12-12T21:37:41.593519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:37:41.694811image/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

순번관할기관가맹점명전화번호업태가맹구분주소1
01부평구CU(구,훼미리마트)(인천부평구)1577-3663편의점일반인천광역시 부평구 전체 편의점 주소 해당
12부평구코리아세븐(인천부평구)<NA>편의점일반인천광역시 부평구 전체 편의점 주소 해당
23부평구한국미니스톱㈜(인천부평구)<NA>편의점일반인천광역시 부평구 전체 편의점 주소 해당
34부평구지에스리테일(GS25)(인천부평구)02-2006-3439편의점일반인천광역시 부평구 전체 편의점 주소 해당
45부평구바이더웨이(부평구)<NA>편의점일반인천광역시 부평구 전체 편의점 주소 해당
56부평구(주)이마트24(인천부평구)02-6916-1500편의점일반인천광역시 부평구 전체 편의점 주소 해당
67부평1동정직한 총각네축산032-528-6688마트일반인천광역시 부평구 부평대로87번길 13
78부평1동봉구스부평역점032-511-1478분식일반인천광역시 부평구 경원대로 1404 (부평동, 그랑프리 빌딩)
89부평1동반찬이랑032-361-3301한식일반인천광역시 부평구 부흥로 265 (부평동, 우림빌딩)
910부평1동찐찐짬뽕070-4155-8720중식일반인천광역시 부평구 부평문화로 45 (부평동)
순번관할기관가맹점명전화번호업태가맹구분주소1
207208십정2동멕시카나동암점032-424-6661분식일반인천광역시 부평구 십정동 315-39
208209십정2동피자마루 동암남부역점032-426-1081분식일반인천광역시 부평구 동암남로 16 (십정동, 효승빌딩)
209210십정2동문가네 분식032-423-8967분식일반인천광역시 부평구 경인로701번길 49 (십정동, 동암역 목동 휘버스아파트)
210211십정2동함경꿩만두032-434-2759한식일반인천광역시 부평구 백범로468번길 32
211212십정2동이용철고쌈냉면032-446-8789한식일반인천광역시 부평구 동암광장로 22
212213십정2동우리김치반찬032-421-0058반찬일반인천광역시 부평구 백범로422번길 50 (십정동)
213214십정2동김밥나라032-434-6664분식일반인천광역시 부평구 동암남로 5
214215십정2동감탄떡볶이032-433-1427분식일반인천광역시 부평구 열우물로 26
215216십정2동본죽&비빔밥 인천동암역점032-425-6288한식일반인천광역시 부평구 열우물로 22 (십정동)
216217십정2동파리바게트 동암북부점032-425-5590제과점일반인천광역시 부평구 동암광장로 16