Overview

Dataset statistics

Number of variables8
Number of observations146
Missing cells54
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.3 KiB
Average record size in memory64.9 B

Variable types

Text6
Categorical1
DateTime1

Dataset

Description경기도 여주시 관내 식품위생업 중 식품제조가공업현황 정보(업종, 업소명, 업태, 인허가일자, 전화번호, 소재재, 식품의종류, 식품의유형, 면적)를 제공합니다.
Author경기도 여주시
URLhttps://www.data.go.kr/data/15038674/fileData.do

Alerts

업종 has constant value ""Constant
소재지전화번호 has 38 (26.0%) missing valuesMissing
식품의유형 has 14 (9.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:12:56.321855
Analysis finished2023-12-12 18:12:57.242035
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct145
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T03:12:57.426224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.4246575
Min length3

Characters and Unicode

Total characters1230
Distinct characters244
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)98.6%

Sample

1st row코카콜라음료(주)
2nd row삼한식품공업사
3rd row상일식품(주)
4th row삼송식품
5th row우수농산식품
ValueCountFrequency (%)
주식회사 25
 
11.9%
농업회사법인 19
 
9.0%
여주공장 2
 
1.0%
팜드림 2
 
1.0%
식품 2
 
1.0%
주)농업회사법인 2
 
1.0%
은성 2
 
1.0%
레드푸드 1
 
0.5%
한얼용사촌 1
 
0.5%
신여주농산 1
 
0.5%
Other values (153) 153
72.9%
2023-12-13T03:12:58.242750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 81
 
6.6%
64
 
5.2%
농 63
 
5.1%
사 58
 
4.7%
회 56
 
4.6%
식 50
 
4.1%
( 42
 
3.4%
) 42
 
3.4%
인 38
 
3.1%
법 37
 
3.0%
Other values (234) 699
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1064
86.5%
Space Separator 64
 
5.2%
Open Punctuation 42
 
3.4%
Close Punctuation 42
 
3.4%
Uppercase Letter 13
 
1.1%
Other Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 81
 
7.6%
농 63
 
5.9%
사 58
 
5.5%
회 56
 
5.3%
식 50
 
4.7%
인 38
 
3.6%
법 37
 
3.5%
업 34
 
3.2%
산 26
 
2.4%
품 23
 
2.2%
Other values (220) 598
56.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
P 2
15.4%
D 2
15.4%
F 2
15.4%
J 1
7.7%
O 1
7.7%
A 1
7.7%
H 1
7.7%
B 1
7.7%
Other Punctuation
ValueCountFrequency (%)
& 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1063
86.4%
Common 153
 
12.4%
Latin 13
 
1.1%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 81
 
7.6%
농 63
 
5.9%
사 58
 
5.5%
회 56
 
5.3%
식 50
 
4.7%
인 38
 
3.6%
법 37
 
3.5%
업 34
 
3.2%
산 26
 
2.4%
품 23
 
2.2%
Other values (219) 597
56.2%
Latin
ValueCountFrequency (%)
C 2
15.4%
P 2
15.4%
D 2
15.4%
F 2
15.4%
J 1
7.7%
O 1
7.7%
A 1
7.7%
H 1
7.7%
B 1
7.7%
Common
ValueCountFrequency (%)
64
41.8%
( 42
27.5%
) 42
27.5%
& 4
 
2.6%
. 1
 
0.7%
Han
ValueCountFrequency (%)
色 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1063
86.4%
ASCII 166
 
13.5%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 81
 
7.6%
농 63
 
5.9%
사 58
 
5.5%
회 56
 
5.3%
식 50
 
4.7%
인 38
 
3.6%
법 37
 
3.5%
업 34
 
3.2%
산 26
 
2.4%
품 23
 
2.2%
Other values (219) 597
56.2%
ASCII
ValueCountFrequency (%)
64
38.6%
( 42
25.3%
) 42
25.3%
& 4
 
2.4%
C 2
 
1.2%
P 2
 
1.2%
D 2
 
1.2%
F 2
 
1.2%
J 1
 
0.6%
O 1
 
0.6%
Other values (4) 4
 
2.4%
CJK
ValueCountFrequency (%)
色 1
100.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
식품제조가공업
146 

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 146
100.0%

Length

2023-12-13T03:12:58.409045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:12:58.553647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 146
100.0%

인허가일자
Date

Distinct142
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1980-05-08 00:00:00
Maximum2021-04-09 00:00:00
2023-12-13T03:12:58.700274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:12:58.859100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지전화번호
Text

MISSING 

Distinct106
Distinct (%)98.1%
Missing38
Missing (%)26.0%
Memory size1.3 KiB
2023-12-13T03:12:59.165742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.990741
Min length13

Characters and Unicode

Total characters1511
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

Unique104 ?
Unique (%)96.3%

Sample

1st row 031- 880-2114
2nd row 031- 882-2873
3rd row 031- 884-9685
4th row 031- 883-3798
5th row 031- 884-8337
ValueCountFrequency (%)
031 100
39.1%
20
 
7.8%
883 5
 
2.0%
881 5
 
2.0%
884 5
 
2.0%
885 3
 
1.2%
886 2
 
0.8%
882 2
 
0.8%
070 2
 
0.8%
886-6744 2
 
0.8%
Other values (109) 110
43.0%
2023-12-13T03:12:59.564224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 260
17.2%
- 216
14.3%
212
14.0%
3 176
11.6%
0 169
11.2%
1 162
10.7%
4 68
 
4.5%
7 58
 
3.8%
5 55
 
3.6%
6 54
 
3.6%
Other values (2) 81
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1083
71.7%
Dash Punctuation 216
 
14.3%
Space Separator 212
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 260
24.0%
3 176
16.3%
0 169
15.6%
1 162
15.0%
4 68
 
6.3%
7 58
 
5.4%
5 55
 
5.1%
6 54
 
5.0%
2 44
 
4.1%
9 37
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%
Space Separator
ValueCountFrequency (%)
212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 260
17.2%
- 216
14.3%
212
14.0%
3 176
11.6%
0 169
11.2%
1 162
10.7%
4 68
 
4.5%
7 58
 
3.8%
5 55
 
3.6%
6 54
 
3.6%
Other values (2) 81
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 260
17.2%
- 216
14.3%
212
14.0%
3 176
11.6%
0 169
11.2%
1 162
10.7%
4 68
 
4.5%
7 58
 
3.8%
5 55
 
3.6%
6 54
 
3.6%
Other values (2) 81
 
5.4%

소재지
Text

Distinct143
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T03:12:59.880615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length21.787671
Min length14

Characters and Unicode

Total characters3181
Distinct characters148
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)95.9%

Sample

1st row경기도 여주시 세종로 415
2nd row경기도 여주시 가남읍 가남로 40
3rd row경기도 여주시 삼교1길 16
4th row경기도 여주시 대신면 옥촌3길 76-82
5th row경기도 여주시 흥천면 신율로 319-15
ValueCountFrequency (%)
경기도 146
19.1%
여주시 145
18.9%
가남읍 32
 
4.2%
1층 24
 
3.1%
능서면 19
 
2.5%
점동면 15
 
2.0%
대신면 12
 
1.6%
산북면 11
 
1.4%
강천면 10
 
1.3%
여주남로 10
 
1.3%
Other values (256) 342
44.6%
2023-12-13T03:13:00.328444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
622
19.6%
여 179
 
5.6%
주 167
 
5.2%
1 158
 
5.0%
경 149
 
4.7%
기 149
 
4.7%
도 147
 
4.6%
시 146
 
4.6%
로 92
 
2.9%
면 84
 
2.6%
Other values (138) 1288
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1824
57.3%
Space Separator 622
 
19.6%
Decimal Number 584
 
18.4%
Dash Punctuation 63
 
2.0%
Other Punctuation 42
 
1.3%
Open Punctuation 18
 
0.6%
Close Punctuation 18
 
0.6%
Math Symbol 7
 
0.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 179
 
9.8%
주 167
 
9.2%
경 149
 
8.2%
기 149
 
8.2%
도 147
 
8.1%
시 146
 
8.0%
로 92
 
5.0%
면 84
 
4.6%
길 58
 
3.2%
동 51
 
2.8%
Other values (119) 602
33.0%
Decimal Number
ValueCountFrequency (%)
1 158
27.1%
2 74
12.7%
4 55
 
9.4%
5 50
 
8.6%
0 49
 
8.4%
6 47
 
8.0%
7 41
 
7.0%
3 41
 
7.0%
8 39
 
6.7%
9 30
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
622
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1824
57.3%
Common 1354
42.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 179
 
9.8%
주 167
 
9.2%
경 149
 
8.2%
기 149
 
8.2%
도 147
 
8.1%
시 146
 
8.0%
로 92
 
5.0%
면 84
 
4.6%
길 58
 
3.2%
동 51
 
2.8%
Other values (119) 602
33.0%
Common
ValueCountFrequency (%)
622
45.9%
1 158
 
11.7%
2 74
 
5.5%
- 63
 
4.7%
4 55
 
4.1%
5 50
 
3.7%
0 49
 
3.6%
6 47
 
3.5%
, 42
 
3.1%
7 41
 
3.0%
Other values (6) 153
 
11.3%
Latin
ValueCountFrequency (%)
C 1
33.3%
B 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1824
57.3%
ASCII 1357
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
622
45.8%
1 158
 
11.6%
2 74
 
5.5%
- 63
 
4.6%
4 55
 
4.1%
5 50
 
3.7%
0 49
 
3.6%
6 47
 
3.5%
, 42
 
3.1%
7 41
 
3.0%
Other values (9) 156
 
11.5%
Hangul
ValueCountFrequency (%)
여 179
 
9.8%
주 167
 
9.2%
경 149
 
8.2%
기 149
 
8.2%
도 147
 
8.1%
시 146
 
8.0%
로 92
 
5.0%
면 84
 
4.6%
길 58
 
3.2%
동 51
 
2.8%
Other values (119) 602
33.0%

식품의종류
Text

Distinct113
Distinct (%)77.9%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T03:13:00.588433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length161
Median length77
Mean length30.827586
Min length4

Characters and Unicode

Total characters4470
Distinct characters122
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)68.3%

Sample

1st row 다류, 커피, 음료류, 커피, 음료류, 음료류
2nd row 장류, 장류, 재래한식간장, 된장, 고추장, 장류
3rd row 과자류, 과자류, 과자류, 빵류 또는 떡류
4th row 조미식품, 복합조미식품
5th row 과자류, 빵또는떡류, 다류, 조미식품, 기타식품류, 규격외일반가공식품, 빵또는떡류, 떡류, 면류, 절임식품, 기타식품류, 규격외일반가공식품, 과자류, 빵류 또는 떡류, 음료류, 절임류 또는 조림류, 농산가공식품류, 수산가공식품류, 즉석식품류, 기타식품류
ValueCountFrequency (%)
규격외일반가공식품 68
 
10.6%
기타식품류 64
 
10.0%
조미식품 59
 
9.2%
음료류 45
 
7.0%
과자류 40
 
6.2%
또는 34
 
5.3%
농산가공식품류 32
 
5.0%
빵류 23
 
3.6%
다류 21
 
3.3%
떡류 20
 
3.1%
Other values (69) 237
36.9%
2023-12-13T03:13:01.023472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1192
26.7%
, 423
 
9.5%
류 404
 
9.0%
품 300
 
6.7%
식 298
 
6.7%
가 143
 
3.2%
공 140
 
3.1%
조 77
 
1.7%
타 73
 
1.6%
기 73
 
1.6%
Other values (112) 1347
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2851
63.8%
Space Separator 1192
26.7%
Other Punctuation 423
 
9.5%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 404
 
14.2%
품 300
 
10.5%
식 298
 
10.5%
가 143
 
5.0%
공 140
 
4.9%
조 77
 
2.7%
타 73
 
2.6%
기 73
 
2.6%
외 69
 
2.4%
반 68
 
2.4%
Other values (108) 1206
42.3%
Space Separator
ValueCountFrequency (%)
1192
100.0%
Other Punctuation
ValueCountFrequency (%)
, 423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2851
63.8%
Common 1619
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 404
 
14.2%
품 300
 
10.5%
식 298
 
10.5%
가 143
 
5.0%
공 140
 
4.9%
조 77
 
2.7%
타 73
 
2.6%
기 73
 
2.6%
외 69
 
2.4%
반 68
 
2.4%
Other values (108) 1206
42.3%
Common
ValueCountFrequency (%)
1192
73.6%
, 423
 
26.1%
( 2
 
0.1%
) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2851
63.8%
ASCII 1619
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1192
73.6%
, 423
 
26.1%
( 2
 
0.1%
) 2
 
0.1%
Hangul
ValueCountFrequency (%)
류 404
 
14.2%
품 300
 
10.5%
식 298
 
10.5%
가 143
 
5.0%
공 140
 
4.9%
조 77
 
2.7%
타 73
 
2.6%
기 73
 
2.6%
외 69
 
2.4%
반 68
 
2.4%
Other values (108) 1206
42.3%

식품의유형
Text

MISSING 

Distinct99
Distinct (%)75.0%
Missing14
Missing (%)9.6%
Memory size1.3 KiB
2023-12-13T03:13:01.270534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length50
Mean length18.401515
Min length4

Characters and Unicode

Total characters2429
Distinct characters137
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)62.9%

Sample

1st row 액상차, 커피, 과.채주스, 과.채음료, 탄산음료, 탄산수, 혼합음료, 음료베이스
2nd row 한식간장, 양조간장, 된장, 고추장, 춘장, 혼합장
3rd row 과자
4th row 발효식초, 복합조미식품
5th row 과자, 빵류, 떡류, 침출차, 액상차, 고형차, 혼합음료, 당절임, 전분가공품, 곡류가공품, 두류가공품, 서류가공품, 기타 수산물가공품, 즉석조리식품, 기타가공품
ValueCountFrequency (%)
기타가공품 31
 
8.2%
액상차 17
 
4.5%
소스 12
 
3.2%
곡류가공품 12
 
3.2%
기타 12
 
3.2%
과.채가공품 12
 
3.2%
고춧가루 11
 
2.9%
과자 10
 
2.6%
서류가공품 10
 
2.6%
절임식품 9
 
2.4%
Other values (79) 242
64.0%
2023-12-13T03:13:01.671098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
728
30.0%
, 218
 
9.0%
품 139
 
5.7%
가 117
 
4.8%
공 106
 
4.4%
기 60
 
2.5%
류 60
 
2.5%
식 59
 
2.4%
타 53
 
2.2%
장 36
 
1.5%
Other values (127) 853
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1460
60.1%
Space Separator 728
30.0%
Other Punctuation 237
 
9.8%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 139
 
9.5%
가 117
 
8.0%
공 106
 
7.3%
기 60
 
4.1%
류 60
 
4.1%
식 59
 
4.0%
타 53
 
3.6%
장 36
 
2.5%
과 35
 
2.4%
조 31
 
2.1%
Other values (122) 764
52.3%
Other Punctuation
ValueCountFrequency (%)
, 218
92.0%
. 19
 
8.0%
Space Separator
ValueCountFrequency (%)
728
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1460
60.1%
Common 969
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 139
 
9.5%
가 117
 
8.0%
공 106
 
7.3%
기 60
 
4.1%
류 60
 
4.1%
식 59
 
4.0%
타 53
 
3.6%
장 36
 
2.5%
과 35
 
2.4%
조 31
 
2.1%
Other values (122) 764
52.3%
Common
ValueCountFrequency (%)
728
75.1%
, 218
 
22.5%
. 19
 
2.0%
( 2
 
0.2%
) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1460
60.1%
ASCII 969
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
728
75.1%
, 218
 
22.5%
. 19
 
2.0%
( 2
 
0.2%
) 2
 
0.2%
Hangul
ValueCountFrequency (%)
품 139
 
9.5%
가 117
 
8.0%
공 106
 
7.3%
기 60
 
4.1%
류 60
 
4.1%
식 59
 
4.0%
타 53
 
3.6%
장 36
 
2.5%
과 35
 
2.4%
조 31
 
2.1%
Other values (122) 764
52.3%

면적
Text

Distinct142
Distinct (%)97.9%
Missing1
Missing (%)0.7%
Memory size1.3 KiB
2023-12-13T03:13:02.009742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.2137931
Min length2

Characters and Unicode

Total characters756
Distinct characters12
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

Unique139 ?
Unique (%)95.9%

Sample

1st row50,096.42
2nd row2,490.07
3rd row4,918.61
4th row194.4
5th row675
ValueCountFrequency (%)
198 2
 
1.4%
195 2
 
1.4%
98 2
 
1.4%
183.98 1
 
0.7%
41.54 1
 
0.7%
46.61 1
 
0.7%
49.68 1
 
0.7%
50,096.42 1
 
0.7%
242.7 1
 
0.7%
445.45 1
 
0.7%
Other values (132) 132
91.0%
2023-12-13T03:13:02.565093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 111
14.7%
1 95
12.6%
2 71
9.4%
5 69
9.1%
8 65
8.6%
4 64
8.5%
9 62
8.2%
7 53
7.0%
3 53
7.0%
6 50
6.6%
Other values (2) 63
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 619
81.9%
Other Punctuation 137
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 95
15.3%
2 71
11.5%
5 69
11.1%
8 65
10.5%
4 64
10.3%
9 62
10.0%
7 53
8.6%
3 53
8.6%
6 50
8.1%
0 37
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 111
81.0%
, 26
 
19.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 111
14.7%
1 95
12.6%
2 71
9.4%
5 69
9.1%
8 65
8.6%
4 64
8.5%
9 62
8.2%
7 53
7.0%
3 53
7.0%
6 50
6.6%
Other values (2) 63
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 111
14.7%
1 95
12.6%
2 71
9.4%
5 69
9.1%
8 65
8.6%
4 64
8.5%
9 62
8.2%
7 53
7.0%
3 53
7.0%
6 50
6.6%
Other values (2) 63
8.3%

Missing values

2023-12-13T03:12:56.844798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:12:57.030960image/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.
2023-12-13T03:12:57.175718image/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

업소명업종인허가일자소재지전화번호소재지식품의종류식품의유형면적
0코카콜라음료(주)식품제조가공업1980-05-08031- 880-2114경기도 여주시 세종로 415다류, 커피, 음료류, 커피, 음료류, 음료류액상차, 커피, 과.채주스, 과.채음료, 탄산음료, 탄산수, 혼합음료, 음료베이스50,096.42
1삼한식품공업사식품제조가공업1981-11-06031- 882-2873경기도 여주시 가남읍 가남로 40장류, 장류, 재래한식간장, 된장, 고추장, 장류한식간장, 양조간장, 된장, 고추장, 춘장, 혼합장2,490.07
2상일식품(주)식품제조가공업1996-05-22031- 884-9685경기도 여주시 삼교1길 16과자류, 과자류, 과자류, 빵류 또는 떡류과자4,918.61
3삼송식품식품제조가공업1996-07-26031- 883-3798경기도 여주시 대신면 옥촌3길 76-82조미식품, 복합조미식품발효식초, 복합조미식품194.4
4우수농산식품식품제조가공업1996-11-22031- 884-8337경기도 여주시 흥천면 신율로 319-15과자류, 빵또는떡류, 다류, 조미식품, 기타식품류, 규격외일반가공식품, 빵또는떡류, 떡류, 면류, 절임식품, 기타식품류, 규격외일반가공식품, 과자류, 빵류 또는 떡류, 음료류, 절임류 또는 조림류, 농산가공식품류, 수산가공식품류, 즉석식품류, 기타식품류과자, 빵류, 떡류, 침출차, 액상차, 고형차, 혼합음료, 당절임, 전분가공품, 곡류가공품, 두류가공품, 서류가공품, 기타 수산물가공품, 즉석조리식품, 기타가공품675
5(주)맛고을식품식품제조가공업1996-09-10031- 746-9970경기도 여주시 점동면 선사길 104과자류, 당시럽류, 과자류, 과자류, 빵류 또는 떡류과자, 캔디류2,280.51
6와이에프영농조합법인식품제조가공업1997-12-05031- 884-4449경기도 여주군 대신면 양촌로 84-76다류, 특수용도식품, 기타식품류, 기타식품류, 규격외일반가공식품<NA>186.17
7오곡식품식품제조가공업1998-07-20031 - 884-8711경기도 여주시 산북면 백자1길 22장류, 조미식품, 규격외일반가공식품개량메주, 곡류가공품, 두류가공품, 기타가공품674.56
8청미식품식품제조가공업1999-09-09031- 885-3866경기도 여주시 여흥로160번길 49-18두부류또는묵류묵류39.2
9주식회사 신한에프앤비(F&B)식품제조가공업1999-10-09031- 881-3989경기도 여주시 산북면 광여로 1264과자류, 빵또는떡류, 어육가공품, 건포류, 규격외일반가공식품, 어육가공품, 기타 어육가공품, 건포류, 규격외일반가공식품, 수산가공식품류기타 어육가공품, 조미건어포, 기타 수산물가공품882.81
업소명업종인허가일자소재지전화번호소재지식품의종류식품의유형면적
136농업회사법인 주식회사 예림원식품제조가공업2020-08-07031-8830-178경기도 여주시 강천면 긴등길 14조미식품고춧가루183.98
137농업회사법인 주식회사 여주게걸무식품제조가공업2020-09-04031- 881-6432경기도 여주시 가남읍 안금3길 35식용유지류기타식물성유지113.75
138대신식품식품제조가공업2020-10-20<NA>경기도 여주시 대신면 보통1길 38조미식품, 기타식품류소스, 기타가공품169.8
139제이앤씨(J&C)식품제조가공업2020-10-21031- 882-7561경기도 여주시 여양로 372-20 (오학동)기타식품류기타가공품188.6
140태평농산식품제조가공업2020-12-18<NA>경기도 여주시 가남읍 여주남로 609조미식품고춧가루374
141커피전설미아몰리에(주)식품제조가공업2020-12-30031- 885-4988경기도 여주시 강천면 강문로 864음료류<NA>17.1
142제이케이식품식품제조가공업2021-01-07<NA>경기도 여주시 강천면 곱새기로 106커피원두, 당류, 음료류커피원두, 액상차, 커피195.84
143씨앤알식품제조가공업2021-03-29<NA>경기도 여주시 점동면 건장이길 57-44, 2동동물성가공식품류<NA>81.72
144곤충산업진흥협동조합식품제조가공업2021-03-29<NA>경기도 여주시 점동면 건장이길 57-44, 2동동물성가공식품류<NA>78.4
145주식회사 이엘푸드식품제조가공업2021-04-09<NA>경기도 여주시 대신면 무촌길 11, 3동조미식품, 농산가공식품류, 기타식품류복합조미식품98