Overview

Dataset statistics

Number of variables5
Number of observations112
Missing cells46
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory41.2 B

Variable types

Categorical1
Text4

Dataset

Description인천광역시 부평구 식품제조가공업 현황입니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15084141&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
소재지전화 has 46 (41.1%) missing valuesMissing

Reproduction

Analysis started2024-03-18 04:47:27.732773
Analysis finished2024-03-18 04:47:28.395287
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
식품제조가공업
112 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 112
100.0%

Length

2024-03-18T13:47:28.447082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:47:28.516813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 112
100.0%

업소명
Text

Distinct109
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-18T13:47:28.677053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length6.75
Min length2

Characters and Unicode

Total characters756
Distinct characters229
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

Unique106 ?
Unique (%)94.6%

Sample

1st row카레가조쿠
2nd row프리노을 주식회사
3rd row(주)지에프코리아
4th row대진농산
5th row주식회사토부리
ValueCountFrequency (%)
주식회사 11
 
8.2%
삼진농산 2
 
1.5%
대진농산 2
 
1.5%
동서식품(주 2
 
1.5%
농업회사법인 2
 
1.5%
부평공장 2
 
1.5%
커퍼스협동조합 1
 
0.7%
병천토속대가순대 1
 
0.7%
정다함 1
 
0.7%
영식품 1
 
0.7%
Other values (109) 109
81.3%
2024-03-18T13:47:29.002169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 39
 
5.2%
식 35
 
4.6%
) 29
 
3.8%
( 29
 
3.8%
23
 
3.0%
품 21
 
2.8%
스 21
 
2.8%
회 19
 
2.5%
사 19
 
2.5%
드 18
 
2.4%
Other values (219) 503
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 649
85.8%
Close Punctuation 29
 
3.8%
Open Punctuation 29
 
3.8%
Space Separator 23
 
3.0%
Uppercase Letter 14
 
1.9%
Lowercase Letter 9
 
1.2%
Other Punctuation 2
 
0.3%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 39
 
6.0%
식 35
 
5.4%
품 21
 
3.2%
스 21
 
3.2%
회 19
 
2.9%
사 19
 
2.9%
드 18
 
2.8%
이 16
 
2.5%
푸 16
 
2.5%
에 12
 
1.8%
Other values (193) 433
66.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
14.3%
E 2
14.3%
T 1
7.1%
I 1
7.1%
K 1
7.1%
F 1
7.1%
R 1
7.1%
S 1
7.1%
C 1
7.1%
J 1
7.1%
Other values (2) 2
14.3%
Lowercase Letter
ValueCountFrequency (%)
n 2
22.2%
o 1
11.1%
h 1
11.1%
l 1
11.1%
c 1
11.1%
s 1
11.1%
a 1
11.1%
e 1
11.1%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 650
86.0%
Common 83
 
11.0%
Latin 23
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 39
 
6.0%
식 35
 
5.4%
품 21
 
3.2%
스 21
 
3.2%
회 19
 
2.9%
사 19
 
2.9%
드 18
 
2.8%
이 16
 
2.5%
푸 16
 
2.5%
에 12
 
1.8%
Other values (194) 434
66.8%
Latin
ValueCountFrequency (%)
A 2
 
8.7%
E 2
 
8.7%
n 2
 
8.7%
T 1
 
4.3%
I 1
 
4.3%
K 1
 
4.3%
o 1
 
4.3%
h 1
 
4.3%
l 1
 
4.3%
c 1
 
4.3%
Other values (10) 10
43.5%
Common
ValueCountFrequency (%)
) 29
34.9%
( 29
34.9%
23
27.7%
: 1
 
1.2%
. 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 649
85.8%
ASCII 106
 
14.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 39
 
6.0%
식 35
 
5.4%
품 21
 
3.2%
스 21
 
3.2%
회 19
 
2.9%
사 19
 
2.9%
드 18
 
2.8%
이 16
 
2.5%
푸 16
 
2.5%
에 12
 
1.8%
Other values (193) 433
66.7%
ASCII
ValueCountFrequency (%)
) 29
27.4%
( 29
27.4%
23
21.7%
A 2
 
1.9%
E 2
 
1.9%
n 2
 
1.9%
T 1
 
0.9%
: 1
 
0.9%
I 1
 
0.9%
K 1
 
0.9%
Other values (15) 15
14.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지(도로명)
Text

Distinct111
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-18T13:47:29.291490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length44.5
Mean length34.6875
Min length22

Characters and Unicode

Total characters3885
Distinct characters137
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

Unique110 ?
Unique (%)98.2%

Sample

1st row인천광역시 부평구 갈월동로 45 상가(114)동 1층 106호 (갈산동 두산아파트)
2nd row인천광역시 부평구 열우물로 149 (십정동 1층)
3rd row인천광역시 부평구 경인로1009번길 15 (부평동)
4th row인천광역시 부평구 원적로421번길 12 (산곡동)
5th row인천광역시 부평구 부평북로 1 2층 (청천동)
ValueCountFrequency (%)
인천광역시 112
 
14.5%
부평구 112
 
14.5%
청천동 42
 
5.4%
1층 39
 
5.0%
부평동 24
 
3.1%
일부호 24
 
3.1%
2층 17
 
2.2%
십정동 13
 
1.7%
삼산동 12
 
1.6%
일부 12
 
1.6%
Other values (246) 366
47.3%
2024-03-18T13:47:29.769176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
768
19.8%
부 230
 
5.9%
평 175
 
4.5%
1 170
 
4.4%
천 169
 
4.4%
동 138
 
3.6%
인 120
 
3.1%
광 120
 
3.1%
로 117
 
3.0%
) 116
 
3.0%
Other values (127) 1762
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2199
56.6%
Space Separator 768
 
19.8%
Decimal Number 645
 
16.6%
Close Punctuation 119
 
3.1%
Open Punctuation 119
 
3.1%
Dash Punctuation 24
 
0.6%
Uppercase Letter 8
 
0.2%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 230
 
10.5%
평 175
 
8.0%
천 169
 
7.7%
동 138
 
6.3%
인 120
 
5.5%
광 120
 
5.5%
로 117
 
5.3%
구 113
 
5.1%
시 112
 
5.1%
역 112
 
5.1%
Other values (106) 793
36.1%
Decimal Number
ValueCountFrequency (%)
1 170
26.4%
3 89
13.8%
2 74
11.5%
0 61
 
9.5%
5 57
 
8.8%
4 55
 
8.5%
8 43
 
6.7%
9 35
 
5.4%
6 32
 
5.0%
7 29
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
C 3
37.5%
A 2
25.0%
B 2
25.0%
K 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 116
97.5%
] 3
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 116
97.5%
[ 3
 
2.5%
Space Separator
ValueCountFrequency (%)
768
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2199
56.6%
Common 1678
43.2%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 230
 
10.5%
평 175
 
8.0%
천 169
 
7.7%
동 138
 
6.3%
인 120
 
5.5%
광 120
 
5.5%
로 117
 
5.3%
구 113
 
5.1%
시 112
 
5.1%
역 112
 
5.1%
Other values (106) 793
36.1%
Common
ValueCountFrequency (%)
768
45.8%
1 170
 
10.1%
) 116
 
6.9%
( 116
 
6.9%
3 89
 
5.3%
2 74
 
4.4%
0 61
 
3.6%
5 57
 
3.4%
4 55
 
3.3%
8 43
 
2.6%
Other values (7) 129
 
7.7%
Latin
ValueCountFrequency (%)
C 3
37.5%
A 2
25.0%
B 2
25.0%
K 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2199
56.6%
ASCII 1686
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
768
45.6%
1 170
 
10.1%
) 116
 
6.9%
( 116
 
6.9%
3 89
 
5.3%
2 74
 
4.4%
0 61
 
3.6%
5 57
 
3.4%
4 55
 
3.3%
8 43
 
2.6%
Other values (11) 137
 
8.1%
Hangul
ValueCountFrequency (%)
부 230
 
10.5%
평 175
 
8.0%
천 169
 
7.7%
동 138
 
6.3%
인 120
 
5.5%
광 120
 
5.5%
로 117
 
5.3%
구 113
 
5.1%
시 112
 
5.1%
역 112
 
5.1%
Other values (106) 793
36.1%

소재지(지번)
Text

Distinct108
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-18T13:47:30.115957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length25.428571
Min length17

Characters and Unicode

Total characters2848
Distinct characters105
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

Unique105 ?
Unique (%)93.8%

Sample

1st row인천광역시 부평구 갈산동 368 두산아파트
2nd row인천광역시 부평구 십정동 118-5 1층
3rd row인천광역시 부평구 부평동 620-15
4th row인천광역시 부평구 산곡동 412-30
5th row인천광역시 부평구 청천동 373-18 2층
ValueCountFrequency (%)
인천광역시 112
18.4%
부평구 112
18.4%
청천동 43
 
7.0%
1층 26
 
4.3%
부평동 24
 
3.9%
일부 23
 
3.8%
십정동 13
 
2.1%
삼산동 12
 
2.0%
2층 11
 
1.8%
440-4 7
 
1.1%
Other values (175) 227
37.2%
2024-03-18T13:47:30.558023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
511
17.9%
부 177
 
6.2%
천 158
 
5.5%
평 141
 
5.0%
1 139
 
4.9%
동 130
 
4.6%
광 119
 
4.2%
구 113
 
4.0%
인 113
 
4.0%
역 112
 
3.9%
Other values (95) 1135
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1587
55.7%
Decimal Number 628
 
22.1%
Space Separator 511
 
17.9%
Dash Punctuation 103
 
3.6%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Uppercase Letter 5
 
0.2%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 177
11.2%
천 158
10.0%
평 141
 
8.9%
동 130
 
8.2%
광 119
 
7.5%
구 113
 
7.1%
인 113
 
7.1%
역 112
 
7.1%
시 112
 
7.1%
층 55
 
3.5%
Other values (74) 357
22.5%
Decimal Number
ValueCountFrequency (%)
1 139
22.1%
2 95
15.1%
4 80
12.7%
3 71
11.3%
0 59
9.4%
6 41
 
6.5%
5 41
 
6.5%
7 41
 
6.5%
9 32
 
5.1%
8 29
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
K 1
20.0%
A 1
20.0%
B 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 3
50.0%
] 3
50.0%
Open Punctuation
ValueCountFrequency (%)
( 3
50.0%
[ 3
50.0%
Space Separator
ValueCountFrequency (%)
511
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1587
55.7%
Common 1256
44.1%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 177
11.2%
천 158
10.0%
평 141
 
8.9%
동 130
 
8.2%
광 119
 
7.5%
구 113
 
7.1%
인 113
 
7.1%
역 112
 
7.1%
시 112
 
7.1%
층 55
 
3.5%
Other values (74) 357
22.5%
Common
ValueCountFrequency (%)
511
40.7%
1 139
 
11.1%
- 103
 
8.2%
2 95
 
7.6%
4 80
 
6.4%
3 71
 
5.7%
0 59
 
4.7%
6 41
 
3.3%
5 41
 
3.3%
7 41
 
3.3%
Other values (7) 75
 
6.0%
Latin
ValueCountFrequency (%)
C 2
40.0%
K 1
20.0%
A 1
20.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1587
55.7%
ASCII 1261
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
511
40.5%
1 139
 
11.0%
- 103
 
8.2%
2 95
 
7.5%
4 80
 
6.3%
3 71
 
5.6%
0 59
 
4.7%
6 41
 
3.3%
5 41
 
3.3%
7 41
 
3.3%
Other values (11) 80
 
6.3%
Hangul
ValueCountFrequency (%)
부 177
11.2%
천 158
10.0%
평 141
 
8.9%
동 130
 
8.2%
광 119
 
7.5%
구 113
 
7.1%
인 113
 
7.1%
역 112
 
7.1%
시 112
 
7.1%
층 55
 
3.5%
Other values (74) 357
22.5%

소재지전화
Text

MISSING 

Distinct65
Distinct (%)98.5%
Missing46
Missing (%)41.1%
Memory size1.0 KiB
2024-03-18T13:47:30.749979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030303
Min length9

Characters and Unicode

Total characters794
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 (%)97.0%

Sample

1st row032-578-0109
2nd row032-505-3997
3rd row032-526-8886
4th row032-524-8470
5th row032-361-2311
ValueCountFrequency (%)
032-500-3228 2
 
3.0%
032-516-9934 1
 
1.5%
070-7737-8192 1
 
1.5%
032-507-0781 1
 
1.5%
032-519-8265 1
 
1.5%
032-362-3394 1
 
1.5%
032-428-8801 1
 
1.5%
032-421-2191 1
 
1.5%
032-501-8888 1
 
1.5%
032-511-3349 1
 
1.5%
Other values (55) 55
83.3%
2024-03-18T13:47:31.061306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 131
16.5%
0 122
15.4%
2 111
14.0%
3 108
13.6%
5 80
10.1%
1 54
6.8%
4 41
 
5.2%
8 39
 
4.9%
9 39
 
4.9%
7 39
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 663
83.5%
Dash Punctuation 131
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
18.4%
2 111
16.7%
3 108
16.3%
5 80
12.1%
1 54
8.1%
4 41
 
6.2%
8 39
 
5.9%
9 39
 
5.9%
7 39
 
5.9%
6 30
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 794
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 131
16.5%
0 122
15.4%
2 111
14.0%
3 108
13.6%
5 80
10.1%
1 54
6.8%
4 41
 
5.2%
8 39
 
4.9%
9 39
 
4.9%
7 39
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 131
16.5%
0 122
15.4%
2 111
14.0%
3 108
13.6%
5 80
10.1%
1 54
6.8%
4 41
 
5.2%
8 39
 
4.9%
9 39
 
4.9%
7 39
 
4.9%

Missing values

2024-03-18T13:47:28.290030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:47:28.362646image/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
0식품제조가공업카레가조쿠인천광역시 부평구 갈월동로 45 상가(114)동 1층 106호 (갈산동 두산아파트)인천광역시 부평구 갈산동 368 두산아파트<NA>
1식품제조가공업프리노을 주식회사인천광역시 부평구 열우물로 149 (십정동 1층)인천광역시 부평구 십정동 118-5 1층032-578-0109
2식품제조가공업(주)지에프코리아인천광역시 부평구 경인로1009번길 15 (부평동)인천광역시 부평구 부평동 620-15032-505-3997
3식품제조가공업대진농산인천광역시 부평구 원적로421번길 12 (산곡동)인천광역시 부평구 산곡동 412-30032-526-8886
4식품제조가공업주식회사토부리인천광역시 부평구 부평북로 1 2층 (청천동)인천광역시 부평구 청천동 373-18 2층032-524-8470
5식품제조가공업주식회사 금강미트인천광역시 부평구 부평대로 301 남광센트렉스 3층 311호 (청천동)인천광역시 부평구 청천동 440-4 남광센트렉스<NA>
6식품제조가공업푸디안인천광역시 부평구 부평대로98번길 35 (부평동)인천광역시 부평구 부평동 438-1032-361-2311
7식품제조가공업룽가인천광역시 부평구 영성중로37번길 28 2층 일부 (삼산동)인천광역시 부평구 삼산동 88-10 외 1필지 2층 일부032-326-5861
8식품제조가공업디메이커인천광역시 부평구 배곶남로21번길 8-8 7호 (십정동)인천광역시 부평구 십정동 320-1 7호<NA>
9식품제조가공업논앤밭위드인천광역시 부평구 평천로 381 지하1층 (갈산동)인천광역시 부평구 갈산동 51-1 지하1층<NA>
업종명업소명소재지(도로명)소재지(지번)소재지전화
102식품제조가공업제일식품인천광역시 부평구 부평북로 307 (갈산동)인천광역시 부평구 갈산동 418032-524-2574
103식품제조가공업티(TEA):달빛인천광역시 부평구 길주로565번길 8 1층 일부호 (갈산동)인천광역시 부평구 갈산동 383-2<NA>
104식품제조가공업(주)성민에프에스인천광역시 부평구 평천로199번길 56 (청천동 제1동 3층 일부)인천광역시 부평구 청천동 419-8 제1동 3층 일부02-1833-2813
105식품제조가공업(주)옥희네수산인천광역시 부평구 영성로 88 청호빌딩 나동 2층 206호 207호 (삼산동)인천광역시 부평구 삼산동 507-3032-508-9402
106식품제조가공업(주)살루스인천광역시 부평구 백범로577번길 20 경인센타 공장동 4층 444호 (십정동)인천광역시 부평구 십정동 562-3 경인센타 공장동 444호<NA>
107식품제조가공업야미인천광역시 부평구 청농로 53 (청천동)인천광역시 부평구 청천동 70-45032-515-0835
108식품제조가공업해뜨는 식품인천광역시 부평구 부평대로 301 (청천동 남광센트렉스 518호)인천광역시 부평구 청천동 440-4 남광센트렉스 518호032-363-3919
109식품제조가공업(주)이랜드이츠식품 부평공장인천광역시 부평구 부평대로313번길 63 (청천동 이랜드부평공장 5층)인천광역시 부평구 청천동 420-2 이랜드부평공장 5층032-500-7794
110식품제조가공업부평냉동물산(주)인천광역시 부평구 세월천로40번길 11 (청천동)인천광역시 부평구 청천동 179-11032-528-7771
111식품제조가공업삼성푸드인천광역시 부평구 부흥로 395 지하1층 일부호 (부개동)인천광역시 부평구 부개동 66-3<NA>