Overview

Dataset statistics

Number of variables5
Number of observations90
Missing cells26
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory41.5 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 식품소분업 현황입니다.
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15084138/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 26 (28.9%) missing valuesMissing

Reproduction

Analysis started2024-04-18 02:41:51.127199
Analysis finished2024-04-18 02:41:52.978404
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
식품소분업
90 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 90
100.0%

Length

2024-04-18T11:41:53.037040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:41:53.126481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 90
100.0%

업소명
Text

Distinct87
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-18T11:41:53.332352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length5.7666667
Min length2

Characters and Unicode

Total characters519
Distinct characters170
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)94.4%

Sample

1st row삼진농산
2nd row진광종합식품
3rd row우리유통
4th row(주)시루아네
5th row주)알싸한
ValueCountFrequency (%)
동서식품(주 3
 
3.1%
삼진농산 2
 
2.1%
현대그린마트 1
 
1.0%
대삼푸드 1
 
1.0%
오복상회 1
 
1.0%
바다와나무 1
 
1.0%
남도식품 1
 
1.0%
영농조합법인 1
 
1.0%
논앤밭 1
 
1.0%
주)푸른세상 1
 
1.0%
Other values (83) 83
86.5%
2024-04-18T11:41:53.685436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 18
 
3.5%
주 17
 
3.3%
회 17
 
3.3%
) 14
 
2.7%
상 14
 
2.7%
이 13
 
2.5%
품 13
 
2.5%
( 13
 
2.5%
유 12
 
2.3%
산 11
 
2.1%
Other values (160) 377
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
92.7%
Close Punctuation 14
 
2.7%
Open Punctuation 13
 
2.5%
Space Separator 6
 
1.2%
Uppercase Letter 3
 
0.6%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 18
 
3.7%
주 17
 
3.5%
회 17
 
3.5%
상 14
 
2.9%
이 13
 
2.7%
품 13
 
2.7%
유 12
 
2.5%
산 11
 
2.3%
건 11
 
2.3%
어 11
 
2.3%
Other values (153) 344
71.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
S 1
33.3%
H 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 481
92.7%
Common 35
 
6.7%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 18
 
3.7%
주 17
 
3.5%
회 17
 
3.5%
상 14
 
2.9%
이 13
 
2.7%
품 13
 
2.7%
유 12
 
2.5%
산 11
 
2.3%
건 11
 
2.3%
어 11
 
2.3%
Other values (153) 344
71.5%
Common
ValueCountFrequency (%)
) 14
40.0%
( 13
37.1%
6
17.1%
. 2
 
5.7%
Latin
ValueCountFrequency (%)
L 1
33.3%
S 1
33.3%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 481
92.7%
ASCII 38
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 18
 
3.7%
주 17
 
3.5%
회 17
 
3.5%
상 14
 
2.9%
이 13
 
2.7%
품 13
 
2.7%
유 12
 
2.5%
산 11
 
2.3%
건 11
 
2.3%
어 11
 
2.3%
Other values (153) 344
71.5%
ASCII
ValueCountFrequency (%)
) 14
36.8%
( 13
34.2%
6
15.8%
. 2
 
5.3%
L 1
 
2.6%
S 1
 
2.6%
H 1
 
2.6%

소재지(도로명)
Text

Distinct89
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-18T11:41:53.937752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length39
Mean length33.555556
Min length23

Characters and Unicode

Total characters3020
Distinct characters110
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

Unique88 ?
Unique (%)97.8%

Sample

1st row인천광역시 부평구 부흥로304번길 27 21호 (부평동)
2nd row인천광역시 부평구 영성로 76-4 (삼산동)
3rd row인천광역시 부평구 부흥로316번길 37 (부평동 1층 일부)
4th row인천광역시 부평구 부평대로313번길 18 3층 일부호 (청천동)
5th row인천광역시 부평구 영성로 88 나동 2층 201호 202호 (삼산동)
ValueCountFrequency (%)
인천광역시 90
 
14.8%
부평구 90
 
14.8%
1층 39
 
6.4%
부평동 33
 
5.4%
일부호 20
 
3.3%
삼산동 18
 
3.0%
2층 15
 
2.5%
부흥로304번길 13
 
2.1%
청천동 11
 
1.8%
십정동 10
 
1.6%
Other values (164) 271
44.4%
2024-04-18T11:41:54.319270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
597
19.8%
부 193
 
6.4%
1 134
 
4.4%
평 133
 
4.4%
동 124
 
4.1%
천 103
 
3.4%
인 95
 
3.1%
광 95
 
3.1%
) 94
 
3.1%
( 94
 
3.1%
Other values (100) 1358
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1687
55.9%
Space Separator 597
 
19.8%
Decimal Number 515
 
17.1%
Close Punctuation 94
 
3.1%
Open Punctuation 94
 
3.1%
Dash Punctuation 26
 
0.9%
Uppercase Letter 6
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 193
 
11.4%
평 133
 
7.9%
동 124
 
7.4%
천 103
 
6.1%
인 95
 
5.6%
광 95
 
5.6%
시 91
 
5.4%
구 91
 
5.4%
로 91
 
5.4%
역 90
 
5.3%
Other values (82) 581
34.4%
Decimal Number
ValueCountFrequency (%)
1 134
26.0%
2 85
16.5%
3 76
14.8%
0 47
 
9.1%
4 46
 
8.9%
7 35
 
6.8%
8 30
 
5.8%
5 27
 
5.2%
6 25
 
4.9%
9 10
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
S 1
 
16.7%
Space Separator
ValueCountFrequency (%)
597
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1687
55.9%
Common 1327
43.9%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 193
 
11.4%
평 133
 
7.9%
동 124
 
7.4%
천 103
 
6.1%
인 95
 
5.6%
광 95
 
5.6%
시 91
 
5.4%
구 91
 
5.4%
로 91
 
5.4%
역 90
 
5.3%
Other values (82) 581
34.4%
Common
ValueCountFrequency (%)
597
45.0%
1 134
 
10.1%
) 94
 
7.1%
( 94
 
7.1%
2 85
 
6.4%
3 76
 
5.7%
0 47
 
3.5%
4 46
 
3.5%
7 35
 
2.6%
8 30
 
2.3%
Other values (5) 89
 
6.7%
Latin
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
S 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1687
55.9%
ASCII 1333
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
597
44.8%
1 134
 
10.1%
) 94
 
7.1%
( 94
 
7.1%
2 85
 
6.4%
3 76
 
5.7%
0 47
 
3.5%
4 46
 
3.5%
7 35
 
2.6%
8 30
 
2.3%
Other values (8) 95
 
7.1%
Hangul
ValueCountFrequency (%)
부 193
 
11.4%
평 133
 
7.9%
동 124
 
7.4%
천 103
 
6.1%
인 95
 
5.6%
광 95
 
5.6%
시 91
 
5.4%
구 91
 
5.4%
로 91
 
5.4%
역 90
 
5.3%
Other values (82) 581
34.4%

소재지(지번)
Text

Distinct87
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-18T11:41:54.575485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length24.488889
Min length17

Characters and Unicode

Total characters2204
Distinct characters78
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

Unique85 ?
Unique (%)94.4%

Sample

1st row인천광역시 부평구 부평동 252-52 21호
2nd row인천광역시 부평구 삼산동 394-6
3rd row인천광역시 부평구 부평동 239-11 1층 일부
4th row인천광역시 부평구 청천동 427-10
5th row인천광역시 부평구 삼산동 507-3
ValueCountFrequency (%)
인천광역시 90
18.6%
부평구 90
18.6%
부평동 33
 
6.8%
1층 30
 
6.2%
삼산동 18
 
3.7%
일부 17
 
3.5%
2층 11
 
2.3%
청천동 11
 
2.3%
십정동 10
 
2.1%
507-3 6
 
1.2%
Other values (121) 169
34.8%
2024-04-18T11:41:54.972093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
398
18.1%
부 147
 
6.7%
평 123
 
5.6%
동 109
 
4.9%
천 101
 
4.6%
1 100
 
4.5%
광 93
 
4.2%
구 91
 
4.1%
2 90
 
4.1%
인 90
 
4.1%
Other values (68) 862
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1217
55.2%
Decimal Number 491
22.3%
Space Separator 398
 
18.1%
Dash Punctuation 83
 
3.8%
Uppercase Letter 6
 
0.3%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 147
12.1%
평 123
10.1%
동 109
9.0%
천 101
8.3%
광 93
 
7.6%
구 91
 
7.5%
인 90
 
7.4%
시 90
 
7.4%
역 90
 
7.4%
층 46
 
3.8%
Other values (50) 237
19.5%
Decimal Number
ValueCountFrequency (%)
1 100
20.4%
2 90
18.3%
3 60
12.2%
4 50
10.2%
5 48
9.8%
0 46
9.4%
9 30
 
6.1%
7 29
 
5.9%
6 25
 
5.1%
8 13
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
S 1
 
16.7%
Space Separator
ValueCountFrequency (%)
398
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1217
55.2%
Common 981
44.5%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 147
12.1%
평 123
10.1%
동 109
9.0%
천 101
8.3%
광 93
 
7.6%
구 91
 
7.5%
인 90
 
7.4%
시 90
 
7.4%
역 90
 
7.4%
층 46
 
3.8%
Other values (50) 237
19.5%
Common
ValueCountFrequency (%)
398
40.6%
1 100
 
10.2%
2 90
 
9.2%
- 83
 
8.5%
3 60
 
6.1%
4 50
 
5.1%
5 48
 
4.9%
0 46
 
4.7%
9 30
 
3.1%
7 29
 
3.0%
Other values (5) 47
 
4.8%
Latin
ValueCountFrequency (%)
B 4
66.7%
C 1
 
16.7%
S 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1217
55.2%
ASCII 987
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
398
40.3%
1 100
 
10.1%
2 90
 
9.1%
- 83
 
8.4%
3 60
 
6.1%
4 50
 
5.1%
5 48
 
4.9%
0 46
 
4.7%
9 30
 
3.0%
7 29
 
2.9%
Other values (8) 53
 
5.4%
Hangul
ValueCountFrequency (%)
부 147
12.1%
평 123
10.1%
동 109
9.0%
천 101
8.3%
광 93
 
7.6%
구 91
 
7.5%
인 90
 
7.4%
시 90
 
7.4%
역 90
 
7.4%
층 46
 
3.8%
Other values (50) 237
19.5%

소재지전화
Text

MISSING 

Distinct64
Distinct (%)100.0%
Missing26
Missing (%)28.9%
Memory size852.0 B
2024-04-18T11:41:55.213073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015625
Min length12

Characters and Unicode

Total characters769
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

Unique64 ?
Unique (%)100.0%

Sample

1st row032-529-3056
2nd row032-506-4450
3rd row032-330-3380
4th row032-426-6624
5th row032-512-5945
ValueCountFrequency (%)
032-529-3056 1
 
1.6%
032-506-4450 1
 
1.6%
032-361-4363 1
 
1.6%
032-567-3622 1
 
1.6%
032-516-4503 1
 
1.6%
032-522-6893 1
 
1.6%
032-529-0794 1
 
1.6%
032-651-3665 1
 
1.6%
032-501-6500 1
 
1.6%
032-515-7345 1
 
1.6%
Other values (54) 54
84.4%
2024-04-18T11:41:55.567061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 128
16.6%
0 118
15.3%
2 111
14.4%
3 110
14.3%
5 79
10.3%
1 49
 
6.4%
4 41
 
5.3%
6 40
 
5.2%
8 35
 
4.6%
7 30
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 641
83.4%
Dash Punctuation 128
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118
18.4%
2 111
17.3%
3 110
17.2%
5 79
12.3%
1 49
7.6%
4 41
 
6.4%
6 40
 
6.2%
8 35
 
5.5%
7 30
 
4.7%
9 28
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 769
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 128
16.6%
0 118
15.3%
2 111
14.4%
3 110
14.3%
5 79
10.3%
1 49
 
6.4%
4 41
 
5.3%
6 40
 
5.2%
8 35
 
4.6%
7 30
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 769
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 128
16.6%
0 118
15.3%
2 111
14.4%
3 110
14.3%
5 79
10.3%
1 49
 
6.4%
4 41
 
5.3%
6 40
 
5.2%
8 35
 
4.6%
7 30
 
3.9%

Correlations

2024-04-18T11:41:55.655983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지(지번)소재지전화
업소명1.0000.9960.9911.000
소재지(도로명)0.9961.0001.0001.000
소재지(지번)0.9911.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2024-04-18T11:41:52.945069image/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
0식품소분업삼진농산인천광역시 부평구 부흥로304번길 27 21호 (부평동)인천광역시 부평구 부평동 252-52 21호<NA>
1식품소분업진광종합식품인천광역시 부평구 영성로 76-4 (삼산동)인천광역시 부평구 삼산동 394-6032-529-3056
2식품소분업우리유통인천광역시 부평구 부흥로316번길 37 (부평동 1층 일부)인천광역시 부평구 부평동 239-11 1층 일부032-506-4450
3식품소분업(주)시루아네인천광역시 부평구 부평대로313번길 18 3층 일부호 (청천동)인천광역시 부평구 청천동 427-10<NA>
4식품소분업주)알싸한인천광역시 부평구 영성로 88 나동 2층 201호 202호 (삼산동)인천광역시 부평구 삼산동 507-3032-330-3380
5식품소분업가미중국식품인천광역시 부평구 백범로422번길 29 1층 일부호 (십정동)인천광역시 부평구 십정동 521-13<NA>
6식품소분업천자비 비누꽃인천광역시 부평구 동암광장로14번길 25-8 (십정동 지하1층 일부)인천광역시 부평구 십정동 400-19 지하1층 일부032-426-6624
7식품소분업하이웨이클럽 청천점인천광역시 부평구 세월천로 9 2층 일부호 (청천동)인천광역시 부평구 청천동 191-9 2층 일부032-512-5945
8식품소분업마녀의부엌인천광역시 부평구 부평대로 301 남광센트렉스 7층 723호 (청천동)인천광역시 부평구 청천동 440-4 남광센트렉스 723호070-8851-3345
9식품소분업보람유통인천광역시 부평구 대보로12번길 11 1층 일부호 (삼산동)인천광역시 부평구 삼산동 167-7<NA>
업종명업소명소재지(도로명)소재지(지번)소재지전화
80식품소분업대박건어물인천광역시 부평구 부흥로304번길 16 (부평동 102호)인천광역시 부평구 부평동 372-7 102호<NA>
81식품소분업남해건어물인천광역시 부평구 대정로35번길 13 1층 (부평동)인천광역시 부평구 부평동 360-15 1층032-518-6677
82식품소분업해농물산인천광역시 부평구 경인로1002번길 10-3 (부평동 (1층))인천광역시 부평구 부평동 625-9 (1층)032-516-9934
83식품소분업다몽식품인천광역시 부평구 원적로471번길 36 B동 1층 (부평동)인천광역시 부평구 부평동 56-11 외1필지 1층 B동<NA>
84식품소분업유케이코리아인천광역시 부평구 항동로143번길 28 2동 2층 일부호 (일신동)인천광역시 부평구 일신동 79-5 2동 2층 일부<NA>
85식품소분업삼진농산인천광역시 부평구 부흥로304번길 27 라동 12호 (부평동)인천광역시 부평구 부평동 252-35 라동 12호032-501-8888
86식품소분업시루방아인천광역시 부평구 부평대로 301 남광센트렉스 218호 일부호 (청천동)인천광역시 부평구 청천동 440-4 남광센트렉스 218호 일부<NA>
87식품소분업은하유통인천광역시 부평구 길주로602번길 20 1층 일부호 (부평동)인천광역시 부평구 부평동 895-1 1층 일부032-330-2635
88식품소분업동서식품(주)인천광역시 부평구 부평북로 215 (청천동)인천광역시 부평구 청천동 407032-500-3228
89식품소분업호남상회인천광역시 부평구 부흥로316번길 38-3 (부평동 외1필지 (1층))인천광역시 부평구 부평동 360-1 외1필지 (1층)032-522-7361