Overview

Dataset statistics

Number of variables13
Number of observations8967
Missing cells9247
Missing cells (%)7.9%
Duplicate rows51
Duplicate rows (%)0.6%
Total size in memory963.4 KiB
Average record size in memory110.0 B

Variable types

Categorical2
Text5
Numeric5
Unsupported1

Dataset

DescriptionHACCP 적용업소 지정 현황 (식품)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=CKMPRXMB5DMQG7ZXZVA727731835&infSeq=1

Alerts

Dataset has 51 (0.6%) duplicate rowsDuplicates
우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
업종구분명 is highly imbalanced (94.8%)Imbalance
도로명주소 has 178 (2.0%) missing valuesMissing
소규모업소여부 has 8967 (100.0%) missing valuesMissing
소규모업소여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:39:04.298303
Analysis finished2023-12-10 22:39:08.561278
Duration4.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size70.2 KiB
광주시
750 
화성시
736 
파주시
716 
성남시
662 
용인시
648 
Other values (26)
5455 

Length

Max length4
Median length3
Mean length3.0604438
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이천시
2nd row이천시
3rd row화성시
4th row안산시
5th row안산시

Common Values

ValueCountFrequency (%)
광주시 750
 
8.4%
화성시 736
 
8.2%
파주시 716
 
8.0%
성남시 662
 
7.4%
용인시 648
 
7.2%
포천시 596
 
6.6%
이천시 507
 
5.7%
고양시 462
 
5.2%
남양주시 456
 
5.1%
평택시 388
 
4.3%
Other values (21) 3046
34.0%

Length

2023-12-11T07:39:08.620049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광주시 750
 
8.4%
화성시 736
 
8.2%
파주시 716
 
8.0%
성남시 662
 
7.4%
용인시 648
 
7.2%
포천시 596
 
6.6%
이천시 507
 
5.7%
고양시 462
 
5.2%
남양주시 456
 
5.1%
평택시 388
 
4.3%
Other values (21) 3046
34.0%

HACCP지정번호
Text

Distinct8270
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size70.2 KiB
2023-12-11T07:39:08.849704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11
Min length9

Characters and Unicode

Total characters98637
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

Unique7622 ?
Unique (%)85.0%

Sample

1st row2020-3-1271
2nd row2020-3-1272
3rd row2023-3-0934
4th row2023-3-0932
5th row2023-3-0933
ValueCountFrequency (%)
2021-1-0069 5
 
0.1%
2019-3-9198 4
 
< 0.1%
2017-3-9033 4
 
< 0.1%
2017-3-9032 4
 
< 0.1%
2016-3-8430 4
 
< 0.1%
2020-3-1034 4
 
< 0.1%
2016-3-8237 4
 
< 0.1%
2018-3-9303 4
 
< 0.1%
2019-3-9197 4
 
< 0.1%
2022-3-0646 4
 
< 0.1%
Other values (8260) 8926
99.5%
2023-12-11T07:39:09.202441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 17998
18.2%
0 17957
18.2%
- 17934
18.2%
1 13026
13.2%
3 10173
10.3%
8 5074
 
5.1%
9 5015
 
5.1%
5 2929
 
3.0%
4 2884
 
2.9%
7 2866
 
2.9%
Other values (2) 2781
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80702
81.8%
Dash Punctuation 17934
 
18.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17998
22.3%
0 17957
22.3%
1 13026
16.1%
3 10173
12.6%
8 5074
 
6.3%
9 5015
 
6.2%
5 2929
 
3.6%
4 2884
 
3.6%
7 2866
 
3.6%
6 2780
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 17934
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 17998
18.2%
0 17957
18.2%
- 17934
18.2%
1 13026
13.2%
3 10173
10.3%
8 5074
 
5.1%
9 5015
 
5.1%
5 2929
 
3.0%
4 2884
 
2.9%
7 2866
 
2.9%
Other values (2) 2781
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 17998
18.2%
0 17957
18.2%
- 17934
18.2%
1 13026
13.2%
3 10173
10.3%
8 5074
 
5.1%
9 5015
 
5.1%
5 2929
 
3.0%
4 2884
 
2.9%
7 2866
 
2.9%
Other values (2) 2781
 
2.8%

HACCP지정일자
Real number (ℝ)

Distinct1723
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20208434
Minimum20061218
Maximum20231201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.9 KiB
2023-12-11T07:39:09.312765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20061218
5-th percentile20160928
Q120200803
median20210831
Q320220911
95-th percentile20230526
Maximum20231201
Range169983
Interquartile range (IQR)20108

Descriptive statistics

Standard deviation20316.843
Coefficient of variation (CV)0.0010053645
Kurtosis4.2574104
Mean20208434
Median Absolute Deviation (MAD)10078
Skewness-1.7161175
Sum1.8120903 × 1011
Variance4.1277411 × 108
MonotonicityDecreasing
2023-12-11T07:39:09.418047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211130 56
 
0.6%
20201117 40
 
0.4%
20230118 39
 
0.4%
20220628 38
 
0.4%
20200707 37
 
0.4%
20200609 36
 
0.4%
20200615 32
 
0.4%
20211126 31
 
0.3%
20230224 31
 
0.3%
20230316 30
 
0.3%
Other values (1713) 8597
95.9%
ValueCountFrequency (%)
20061218 1
< 0.1%
20070430 1
< 0.1%
20071029 1
< 0.1%
20071030 1
< 0.1%
20071112 1
< 0.1%
20071218 1
< 0.1%
20080115 1
< 0.1%
20090424 1
< 0.1%
20101104 2
< 0.1%
20101105 1
< 0.1%
ValueCountFrequency (%)
20231201 2
 
< 0.1%
20231130 11
0.1%
20231129 1
 
< 0.1%
20231127 6
0.1%
20231124 5
0.1%
20231123 7
0.1%
20231121 1
 
< 0.1%
20231120 2
 
< 0.1%
20231117 2
 
< 0.1%
20231116 7
0.1%

인허가번호
Real number (ℝ)

Distinct3691
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0106816 × 1010
Minimum1.9670086 × 1010
Maximum2.0230535 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.9 KiB
2023-12-11T07:39:09.521771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9670086 × 1010
5-th percentile1.9880324 × 1010
Q12.0060377 × 1010
median2.0130368 × 1010
Q32.0180384 × 1010
95-th percentile2.0220476 × 1010
Maximum2.0230535 × 1010
Range5.6044914 × 108
Interquartile range (IQR)1.2000781 × 108

Descriptive statistics

Standard deviation1.0363133 × 108
Coefficient of variation (CV)0.00515404
Kurtosis2.2906971
Mean2.0106816 × 1010
Median Absolute Deviation (MAD)59957751
Skewness-1.4824447
Sum1.8029782 × 1014
Variance1.0739454 × 1016
MonotonicityNot monotonic
2023-12-11T07:39:09.627262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19720288002 35
 
0.4%
20190280327 31
 
0.3%
19880355033 30
 
0.3%
20070358224 27
 
0.3%
19990364158 22
 
0.2%
20130362215 22
 
0.2%
20110311336 21
 
0.2%
19860309018 21
 
0.2%
19830358006 20
 
0.2%
19850311001 20
 
0.2%
Other values (3681) 8718
97.2%
ValueCountFrequency (%)
19670086001 1
 
< 0.1%
19690364004 17
0.2%
19700086012 1
 
< 0.1%
19710275001 1
 
< 0.1%
19710275003 3
 
< 0.1%
19710372001 5
 
0.1%
19720275004 2
 
< 0.1%
19720288002 35
0.4%
19720338001 2
 
< 0.1%
19720347001 1
 
< 0.1%
ValueCountFrequency (%)
20230535138 1
 
< 0.1%
20230535016 6
0.1%
20230533023 2
 
< 0.1%
20230533022 1
 
< 0.1%
20230528282 2
 
< 0.1%
20230528273 2
 
< 0.1%
20230528157 3
< 0.1%
20230528144 6
0.1%
20230528124 1
 
< 0.1%
20230528123 1
 
< 0.1%

업종구분명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size70.2 KiB
식품제조가공업
8798 
식품소분업
 
85
식품제조가공업(주류)
 
21
일반음식점
 
18
식품첨가물제조업
 
17
Other values (6)
 
28

Length

Max length11
Median length7
Mean length6.994424
Min length5

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 8798
98.1%
식품소분업 85
 
0.9%
식품제조가공업(주류) 21
 
0.2%
일반음식점 18
 
0.2%
식품첨가물제조업 17
 
0.2%
집단급식소 식품판매업 14
 
0.2%
위탁급식영업 6
 
0.1%
즉석판매제조가공업 4
 
< 0.1%
휴게음식점 2
 
< 0.1%
유통전문판매업 1
 
< 0.1%

Length

2023-12-11T07:39:09.732337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
식품제조가공업 8798
98.0%
식품소분업 85
 
0.9%
식품제조가공업(주류 21
 
0.2%
일반음식점 18
 
0.2%
식품첨가물제조업 17
 
0.2%
집단급식소 14
 
0.2%
식품판매업 14
 
0.2%
위탁급식영업 6
 
0.1%
즉석판매제조가공업 4
 
< 0.1%
휴게음식점 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

업소명
Text

Distinct3634
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size70.2 KiB
2023-12-11T07:39:09.890509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length8.3366789
Min length1

Characters and Unicode

Total characters74755
Distinct characters740
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

Unique1598 ?
Unique (%)17.8%

Sample

1st row(주)초코텍
2nd row(주)초코텍
3rd row새싹푸드
4th row새싹푸드
5th row새싹푸드
ValueCountFrequency (%)
주식회사 1468
 
12.3%
농업회사법인 366
 
3.1%
2공장 53
 
0.4%
주 46
 
0.4%
제2공장 45
 
0.4%
주)한미양행 44
 
0.4%
주)현대그린푸드 40
 
0.3%
오뚜기 37
 
0.3%
스마트푸드센터 31
 
0.3%
유한회사 30
 
0.3%
Other values (3812) 9732
81.8%
2023-12-11T07:39:10.271233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6402
 
8.6%
) 4663
 
6.2%
( 4642
 
6.2%
식 3105
 
4.2%
2925
 
3.9%
사 2718
 
3.6%
회 2563
 
3.4%
드 1812
 
2.4%
푸 1675
 
2.2%
이 1612
 
2.2%
Other values (730) 42638
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61007
81.6%
Close Punctuation 4666
 
6.2%
Open Punctuation 4645
 
6.2%
Space Separator 2925
 
3.9%
Uppercase Letter 641
 
0.9%
Lowercase Letter 404
 
0.5%
Decimal Number 351
 
0.5%
Other Punctuation 94
 
0.1%
Other Symbol 11
 
< 0.1%
Dash Punctuation 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6402
 
10.5%
식 3105
 
5.1%
사 2718
 
4.5%
회 2563
 
4.2%
드 1812
 
3.0%
푸 1675
 
2.7%
이 1612
 
2.6%
품 1240
 
2.0%
스 1166
 
1.9%
에 1165
 
1.9%
Other values (663) 37549
61.5%
Uppercase Letter
ValueCountFrequency (%)
F 114
17.8%
B 70
 
10.9%
S 54
 
8.4%
O 42
 
6.6%
C 41
 
6.4%
D 33
 
5.1%
T 32
 
5.0%
E 28
 
4.4%
P 26
 
4.1%
A 21
 
3.3%
Other values (14) 180
28.1%
Lowercase Letter
ValueCountFrequency (%)
o 67
16.6%
a 47
11.6%
e 40
9.9%
n 29
 
7.2%
i 26
 
6.4%
c 23
 
5.7%
r 19
 
4.7%
l 19
 
4.7%
h 18
 
4.5%
t 18
 
4.5%
Other values (11) 98
24.3%
Decimal Number
ValueCountFrequency (%)
2 207
59.0%
1 65
 
18.5%
3 29
 
8.3%
5 19
 
5.4%
6 11
 
3.1%
0 8
 
2.3%
4 5
 
1.4%
7 4
 
1.1%
8 2
 
0.6%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
& 64
68.1%
. 22
 
23.4%
' 4
 
4.3%
, 2
 
2.1%
＆ 2
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 4663
99.9%
] 3
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 4642
99.9%
[ 3
 
0.1%
Space Separator
ValueCountFrequency (%)
2925
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61018
81.6%
Common 12692
 
17.0%
Latin 1045
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6402
 
10.5%
식 3105
 
5.1%
사 2718
 
4.5%
회 2563
 
4.2%
드 1812
 
3.0%
푸 1675
 
2.7%
이 1612
 
2.6%
품 1240
 
2.0%
스 1166
 
1.9%
에 1165
 
1.9%
Other values (664) 37560
61.6%
Latin
ValueCountFrequency (%)
F 114
 
10.9%
B 70
 
6.7%
o 67
 
6.4%
S 54
 
5.2%
a 47
 
4.5%
O 42
 
4.0%
C 41
 
3.9%
e 40
 
3.8%
D 33
 
3.2%
T 32
 
3.1%
Other values (35) 505
48.3%
Common
ValueCountFrequency (%)
) 4663
36.7%
( 4642
36.6%
2925
23.0%
2 207
 
1.6%
1 65
 
0.5%
& 64
 
0.5%
3 29
 
0.2%
. 22
 
0.2%
5 19
 
0.1%
6 11
 
0.1%
Other values (11) 45
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61007
81.6%
ASCII 13735
 
18.4%
None 13
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6402
 
10.5%
식 3105
 
5.1%
사 2718
 
4.5%
회 2563
 
4.2%
드 1812
 
3.0%
푸 1675
 
2.7%
이 1612
 
2.6%
품 1240
 
2.0%
스 1166
 
1.9%
에 1165
 
1.9%
Other values (663) 37549
61.5%
ASCII
ValueCountFrequency (%)
) 4663
33.9%
( 4642
33.8%
2925
21.3%
2 207
 
1.5%
F 114
 
0.8%
B 70
 
0.5%
o 67
 
0.5%
1 65
 
0.5%
& 64
 
0.5%
S 54
 
0.4%
Other values (55) 864
 
6.3%
None
ValueCountFrequency (%)
㈜ 11
84.6%
＆ 2
 
15.4%

품목명
Text

Distinct451
Distinct (%)5.0%
Missing4
Missing (%)< 0.1%
Memory size70.2 KiB
2023-12-11T07:39:10.482827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length47
Mean length6.3065938
Min length1

Characters and Unicode

Total characters56526
Distinct characters300
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)2.3%

Sample

1st row과자
2nd row캔디류
3rd row즉석조리식품
4th row소스
5th row조림류
ValueCountFrequency (%)
중 1187
 
9.9%
기타수산물가공품 1064
 
8.9%
빵류 677
 
5.7%
과자 567
 
4.7%
기타가공품 427
 
3.6%
냉동어류 414
 
3.5%
냉동연체류 375
 
3.1%
즉석조리식품 294
 
2.5%
냉동식품 273
 
2.3%
소스 266
 
2.2%
Other values (462) 6410
53.6%
2023-12-11T07:39:10.827256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 4572
 
8.1%
2992
 
5.3%
가 2950
 
5.2%
공 2830
 
5.0%
류 2822
 
5.0%
기 2084
 
3.7%
식 2026
 
3.6%
타 1959
 
3.5%
수 1301
 
2.3%
냉 1284
 
2.3%
Other values (290) 31706
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50989
90.2%
Space Separator 2992
 
5.3%
Open Punctuation 1174
 
2.1%
Close Punctuation 1174
 
2.1%
Other Punctuation 160
 
0.3%
Decimal Number 31
 
0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 4572
 
9.0%
가 2950
 
5.8%
공 2830
 
5.6%
류 2822
 
5.5%
기 2084
 
4.1%
식 2026
 
4.0%
타 1959
 
3.8%
수 1301
 
2.6%
냉 1284
 
2.5%
산 1259
 
2.5%
Other values (275) 27902
54.7%
Decimal Number
ValueCountFrequency (%)
1 6
19.4%
0 6
19.4%
8 5
16.1%
9 5
16.1%
2 4
12.9%
3 3
9.7%
6 2
 
6.5%
Open Punctuation
ValueCountFrequency (%)
( 1173
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1173
99.9%
] 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 138
86.2%
. 22
 
13.8%
Space Separator
ValueCountFrequency (%)
2992
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50989
90.2%
Common 5537
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 4572
 
9.0%
가 2950
 
5.8%
공 2830
 
5.6%
류 2822
 
5.5%
기 2084
 
4.1%
식 2026
 
4.0%
타 1959
 
3.8%
수 1301
 
2.6%
냉 1284
 
2.5%
산 1259
 
2.5%
Other values (275) 27902
54.7%
Common
ValueCountFrequency (%)
2992
54.0%
( 1173
 
21.2%
) 1173
 
21.2%
, 138
 
2.5%
. 22
 
0.4%
1 6
 
0.1%
- 6
 
0.1%
0 6
 
0.1%
8 5
 
0.1%
9 5
 
0.1%
Other values (5) 11
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50989
90.2%
ASCII 5537
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 4572
 
9.0%
가 2950
 
5.8%
공 2830
 
5.6%
류 2822
 
5.5%
기 2084
 
4.1%
식 2026
 
4.0%
타 1959
 
3.8%
수 1301
 
2.6%
냉 1284
 
2.5%
산 1259
 
2.5%
Other values (275) 27902
54.7%
ASCII
ValueCountFrequency (%)
2992
54.0%
( 1173
 
21.2%
) 1173
 
21.2%
, 138
 
2.5%
. 22
 
0.4%
1 6
 
0.1%
- 6
 
0.1%
0 6
 
0.1%
8 5
 
0.1%
9 5
 
0.1%
Other values (5) 11
 
0.2%

도로명주소
Text

MISSING 

Distinct3236
Distinct (%)36.8%
Missing178
Missing (%)2.0%
Memory size70.2 KiB
2023-12-11T07:39:11.097840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length21.162021
Min length13

Characters and Unicode

Total characters185993
Distinct characters398
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

Unique1427 ?
Unique (%)16.2%

Sample

1st row경기도 이천시 대월면 대월로667번길 38-48
2nd row경기도 이천시 대월면 대월로667번길 38-48
3rd row경기도 화성시 매송면 야목길 42
4th row경기도 안산시 상록구 고목로 21
5th row경기도 안산시 상록구 고목로 21
ValueCountFrequency (%)
경기도 8789
 
20.8%
화성시 726
 
1.7%
광주시 723
 
1.7%
파주시 708
 
1.7%
용인시 648
 
1.5%
성남시 601
 
1.4%
포천시 587
 
1.4%
중원구 570
 
1.3%
이천시 497
 
1.2%
처인구 470
 
1.1%
Other values (3932) 27934
66.1%
2023-12-11T07:39:11.480577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33464
 
18.0%
기 9313
 
5.0%
도 9261
 
5.0%
경 9026
 
4.9%
시 8875
 
4.8%
1 7341
 
3.9%
로 6974
 
3.7%
길 5124
 
2.8%
2 5049
 
2.7%
3 4061
 
2.2%
Other values (388) 87505
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 112918
60.7%
Decimal Number 36429
 
19.6%
Space Separator 33464
 
18.0%
Dash Punctuation 3180
 
1.7%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 9313
 
8.2%
도 9261
 
8.2%
경 9026
 
8.0%
시 8875
 
7.9%
로 6974
 
6.2%
길 5124
 
4.5%
번 3204
 
2.8%
면 2643
 
2.3%
주 2475
 
2.2%
구 2391
 
2.1%
Other values (375) 53632
47.5%
Decimal Number
ValueCountFrequency (%)
1 7341
20.2%
2 5049
13.9%
3 4061
11.1%
4 3664
10.1%
5 3546
9.7%
6 2864
 
7.9%
7 2697
 
7.4%
8 2599
 
7.1%
0 2377
 
6.5%
9 2231
 
6.1%
Space Separator
ValueCountFrequency (%)
33464
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3180
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 112918
60.7%
Common 73075
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 9313
 
8.2%
도 9261
 
8.2%
경 9026
 
8.0%
시 8875
 
7.9%
로 6974
 
6.2%
길 5124
 
4.5%
번 3204
 
2.8%
면 2643
 
2.3%
주 2475
 
2.2%
구 2391
 
2.1%
Other values (375) 53632
47.5%
Common
ValueCountFrequency (%)
33464
45.8%
1 7341
 
10.0%
2 5049
 
6.9%
3 4061
 
5.6%
4 3664
 
5.0%
5 3546
 
4.9%
- 3180
 
4.4%
6 2864
 
3.9%
7 2697
 
3.7%
8 2599
 
3.6%
Other values (3) 4610
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 112918
60.7%
ASCII 73075
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33464
45.8%
1 7341
 
10.0%
2 5049
 
6.9%
3 4061
 
5.6%
4 3664
 
5.0%
5 3546
 
4.9%
- 3180
 
4.4%
6 2864
 
3.9%
7 2697
 
3.7%
8 2599
 
3.6%
Other values (3) 4610
 
6.3%
Hangul
ValueCountFrequency (%)
기 9313
 
8.2%
도 9261
 
8.2%
경 9026
 
8.0%
시 8875
 
7.9%
로 6974
 
6.2%
길 5124
 
4.5%
번 3204
 
2.8%
면 2643
 
2.3%
주 2475
 
2.2%
구 2391
 
2.1%
Other values (375) 53632
47.5%

지번주소
Text

Distinct3860
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size70.2 KiB
2023-12-11T07:39:11.749408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length67
Mean length29.327534
Min length15

Characters and Unicode

Total characters262980
Distinct characters495
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1813 ?
Unique (%)20.2%

Sample

1st row경기도 이천시 대월면 초지리 733-1번지
2nd row경기도 이천시 대월면 초지리 733-1번지
3rd row경기도 화성시 매송면 야목리 382번지 1층 전체호
4th row경기도 안산시 상록구 본오동 977-11번지 1층 본오동
5th row경기도 안산시 상록구 본오동 977-11번지 1층 본오동
ValueCountFrequency (%)
경기도 8968
 
16.2%
1층 1765
 
3.2%
상대원동 972
 
1.8%
광주시 750
 
1.4%
화성시 736
 
1.3%
파주시 716
 
1.3%
성남시 662
 
1.2%
용인시 648
 
1.2%
중원구 630
 
1.1%
포천시 596
 
1.1%
Other values (5312) 38992
70.3%
2023-12-11T07:39:12.134076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46468
 
17.7%
1 11780
 
4.5%
지 10096
 
3.8%
동 9537
 
3.6%
도 9502
 
3.6%
기 9227
 
3.5%
시 9106
 
3.5%
경 8990
 
3.4%
번 8939
 
3.4%
- 7052
 
2.7%
Other values (485) 132283
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152070
57.8%
Decimal Number 47162
 
17.9%
Space Separator 46468
 
17.7%
Dash Punctuation 7052
 
2.7%
Other Punctuation 2894
 
1.1%
Close Punctuation 2713
 
1.0%
Open Punctuation 2713
 
1.0%
Uppercase Letter 1500
 
0.6%
Math Symbol 266
 
0.1%
Lowercase Letter 99
 
< 0.1%
Other values (2) 43
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 10096
 
6.6%
동 9537
 
6.3%
도 9502
 
6.2%
기 9227
 
6.1%
시 9106
 
6.0%
경 8990
 
5.9%
번 8939
 
5.9%
리 5348
 
3.5%
층 4186
 
2.8%
주 2740
 
1.8%
Other values (425) 74399
48.9%
Uppercase Letter
ValueCountFrequency (%)
B 538
35.9%
A 344
22.9%
C 98
 
6.5%
S 79
 
5.3%
F 77
 
5.1%
K 71
 
4.7%
T 53
 
3.5%
E 44
 
2.9%
I 40
 
2.7%
D 39
 
2.6%
Other values (13) 117
 
7.8%
Lowercase Letter
ValueCountFrequency (%)
n 30
30.3%
e 20
20.2%
r 11
 
11.1%
t 11
 
11.1%
c 9
 
9.1%
o 7
 
7.1%
w 4
 
4.0%
m 2
 
2.0%
b 2
 
2.0%
l 1
 
1.0%
Other values (2) 2
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 11780
25.0%
2 7026
14.9%
3 5484
11.6%
4 4411
 
9.4%
5 4077
 
8.6%
6 3443
 
7.3%
0 3286
 
7.0%
7 2777
 
5.9%
8 2504
 
5.3%
9 2374
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 2717
93.9%
. 151
 
5.2%
/ 16
 
0.6%
: 7
 
0.2%
· 2
 
0.1%
& 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
㎡ 29
72.5%
ⓝ 11
 
27.5%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
46468
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7052
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2713
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2713
100.0%
Math Symbol
ValueCountFrequency (%)
~ 266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152070
57.8%
Common 109308
41.6%
Latin 1602
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 10096
 
6.6%
동 9537
 
6.3%
도 9502
 
6.2%
기 9227
 
6.1%
시 9106
 
6.0%
경 8990
 
5.9%
번 8939
 
5.9%
리 5348
 
3.5%
층 4186
 
2.8%
주 2740
 
1.8%
Other values (425) 74399
48.9%
Latin
ValueCountFrequency (%)
B 538
33.6%
A 344
21.5%
C 98
 
6.1%
S 79
 
4.9%
F 77
 
4.8%
K 71
 
4.4%
T 53
 
3.3%
E 44
 
2.7%
I 40
 
2.5%
D 39
 
2.4%
Other values (27) 219
13.7%
Common
ValueCountFrequency (%)
46468
42.5%
1 11780
 
10.8%
- 7052
 
6.5%
2 7026
 
6.4%
3 5484
 
5.0%
4 4411
 
4.0%
5 4077
 
3.7%
6 3443
 
3.1%
0 3286
 
3.0%
7 2777
 
2.5%
Other values (13) 13504
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152067
57.8%
ASCII 110865
42.2%
CJK Compat 29
 
< 0.1%
Enclosed Alphanum 11
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Number Forms 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46468
41.9%
1 11780
 
10.6%
- 7052
 
6.4%
2 7026
 
6.3%
3 5484
 
4.9%
4 4411
 
4.0%
5 4077
 
3.7%
6 3443
 
3.1%
0 3286
 
3.0%
7 2777
 
2.5%
Other values (45) 15061
 
13.6%
Hangul
ValueCountFrequency (%)
지 10096
 
6.6%
동 9537
 
6.3%
도 9502
 
6.2%
기 9227
 
6.1%
시 9106
 
6.0%
경 8990
 
5.9%
번 8939
 
5.9%
리 5348
 
3.5%
층 4186
 
2.8%
주 2740
 
1.8%
Other values (424) 74396
48.9%
CJK Compat
ValueCountFrequency (%)
㎡ 29
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓝ 11
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
66.7%
Ⅰ 1
33.3%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1327
Distinct (%)14.8%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean14033.251
Minimum10003
Maximum18633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.9 KiB
2023-12-11T07:39:12.264060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10003
5-th percentile10208
Q111413
median13201
Q317130
95-th percentile18519
Maximum18633
Range8630
Interquartile range (IQR)5717

Descriptive statistics

Standard deviation2826.3992
Coefficient of variation (CV)0.2014073
Kurtosis-1.4186981
Mean14033.251
Median Absolute Deviation (MAD)2291
Skewness0.25191711
Sum1.2575196 × 108
Variance7988532.2
MonotonicityNot monotonic
2023-12-11T07:39:12.604551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12774 121
 
1.3%
13201 119
 
1.3%
13207 65
 
0.7%
13211 63
 
0.7%
11154 59
 
0.7%
11167 53
 
0.6%
13202 52
 
0.6%
11517 52
 
0.6%
13209 50
 
0.6%
10594 45
 
0.5%
Other values (1317) 8282
92.4%
ValueCountFrequency (%)
10003 4
 
< 0.1%
10005 8
 
0.1%
10008 5
 
0.1%
10009 9
 
0.1%
10010 6
 
0.1%
10011 21
0.2%
10012 10
 
0.1%
10013 25
0.3%
10014 5
 
0.1%
10015 6
 
0.1%
ValueCountFrequency (%)
18633 13
 
0.1%
18632 1
 
< 0.1%
18630 1
 
< 0.1%
18629 1
 
< 0.1%
18628 3
 
< 0.1%
18627 38
0.4%
18626 13
 
0.1%
18625 7
 
0.1%
18624 26
0.3%
18623 7
 
0.1%

소규모업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8967
Missing (%)100.0%
Memory size78.9 KiB

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3298
Distinct (%)37.0%
Missing46
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean37.451871
Minimum36.933393
Maximum38.217554
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.9 KiB
2023-12-11T07:39:12.719297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.933393
5-th percentile37.032517
Q137.253445
median37.420431
Q337.695985
95-th percentile37.867754
Maximum38.217554
Range1.2841613
Interquartile range (IQR)0.44253944

Descriptive statistics

Standard deviation0.26515302
Coefficient of variation (CV)0.0070798338
Kurtosis-0.98774576
Mean37.451871
Median Absolute Deviation (MAD)0.22426928
Skewness0.15064654
Sum334108.14
Variance0.070306124
MonotonicityNot monotonic
2023-12-11T07:39:12.846345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6490702916 45
 
0.5%
37.4404884338 40
 
0.4%
37.3906256591 35
 
0.4%
37.4388645413 34
 
0.4%
37.4399480135 34
 
0.4%
37.4412173177 33
 
0.4%
37.8774641574 30
 
0.3%
37.443122783 27
 
0.3%
37.2164221095 27
 
0.3%
37.4406568155 22
 
0.2%
Other values (3288) 8594
95.8%
(Missing) 46
 
0.5%
ValueCountFrequency (%)
36.9333931511 3
 
< 0.1%
36.9388029302 4
 
< 0.1%
36.9402870569 2
 
< 0.1%
36.9422188477 1
 
< 0.1%
36.9462030458 1
 
< 0.1%
36.9469848837 3
 
< 0.1%
36.9523591039 17
0.2%
36.9537542644 2
 
< 0.1%
36.9544706399 1
 
< 0.1%
36.9563185772 8
0.1%
ValueCountFrequency (%)
38.217554465 1
 
< 0.1%
38.1223274355 1
 
< 0.1%
38.0857792983 3
< 0.1%
38.0751087888 1
 
< 0.1%
38.074273132 1
 
< 0.1%
38.0741222512 1
 
< 0.1%
38.0598698206 3
< 0.1%
38.0503066389 3
< 0.1%
38.040968574 3
< 0.1%
38.0407579057 6
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3298
Distinct (%)37.0%
Missing46
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean127.07227
Minimum126.53676
Maximum127.79248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.9 KiB
2023-12-11T07:39:12.970678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53676
5-th percentile126.70165
Q1126.85916
median127.12648
Q3127.2265
95-th percentile127.47197
Maximum127.79248
Range1.255718
Interquartile range (IQR)0.36734438

Descriptive statistics

Standard deviation0.24172592
Coefficient of variation (CV)0.0019022713
Kurtosis-0.68118946
Mean127.07227
Median Absolute Deviation (MAD)0.17739293
Skewness0.0081865701
Sum1133611.7
Variance0.058431422
MonotonicityNot monotonic
2023-12-11T07:39:13.091051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9019008596 45
 
0.5%
127.1735598142 40
 
0.4%
126.9698549937 35
 
0.4%
127.1698025599 34
 
0.4%
127.1769873928 34
 
0.4%
127.1731157691 33
 
0.4%
126.7856459464 30
 
0.3%
127.1810208896 27
 
0.3%
127.3709583557 27
 
0.3%
127.1725190689 22
 
0.2%
Other values (3288) 8594
95.8%
(Missing) 46
 
0.5%
ValueCountFrequency (%)
126.5367577017 1
 
< 0.1%
126.5405481825 1
 
< 0.1%
126.548166584 3
< 0.1%
126.5494113543 2
 
< 0.1%
126.5501482832 2
 
< 0.1%
126.5509613977 5
0.1%
126.5511818824 2
 
< 0.1%
126.5515008852 1
 
< 0.1%
126.5518630664 1
 
< 0.1%
126.5526545138 2
 
< 0.1%
ValueCountFrequency (%)
127.7924757138 1
 
< 0.1%
127.7677831997 1
 
< 0.1%
127.7525033426 1
 
< 0.1%
127.7489168517 1
 
< 0.1%
127.7479402801 2
< 0.1%
127.7368800969 1
 
< 0.1%
127.733995613 1
 
< 0.1%
127.7163169577 3
< 0.1%
127.7119935392 1
 
< 0.1%
127.7112355609 1
 
< 0.1%

Interactions

2023-12-11T07:39:07.757798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:05.860248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.259624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.673965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.320245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.857714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:05.935522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.356594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.750536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.405671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.956076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.016907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.431453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.046225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.486277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:08.036651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.089057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.504565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.123703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.567612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:08.120563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.165500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:06.588203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.224861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:39:07.650559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:39:13.170971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명HACCP지정일자인허가번호업종구분명우편번호WGS84위도WGS84경도
시군명1.0000.1840.4740.1740.9940.9450.929
HACCP지정일자0.1841.0000.3180.1020.1350.1220.142
인허가번호0.4740.3181.0000.0200.4240.3620.334
업종구분명0.1740.1020.0201.0000.0400.0600.104
우편번호0.9940.1350.4240.0401.0000.9020.838
WGS84위도0.9450.1220.3620.0600.9021.0000.627
WGS84경도0.9290.1420.3340.1040.8380.6271.000
2023-12-11T07:39:13.258358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분명시군명
업종구분명1.0000.060
시군명0.0601.000
2023-12-11T07:39:13.351849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HACCP지정일자인허가번호우편번호WGS84위도WGS84경도시군명업종구분명
HACCP지정일자1.0000.194-0.0570.060-0.0450.0660.043
인허가번호0.1941.000-0.0850.063-0.0170.1860.009
우편번호-0.057-0.0851.000-0.8940.2120.9490.017
WGS84위도0.0600.063-0.8941.000-0.2200.7180.025
WGS84경도-0.045-0.0170.212-0.2201.0000.6690.044
시군명0.0660.1860.9490.7180.6691.0000.060
업종구분명0.0430.0090.0170.0250.0440.0601.000

Missing values

2023-12-11T07:39:08.233213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:39:08.378943image/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.
2023-12-11T07:39:08.492617image/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

시군명HACCP지정번호HACCP지정일자인허가번호업종구분명업소명품목명도로명주소지번주소우편번호소규모업소여부WGS84위도WGS84경도
0이천시2020-3-12712023120120160358514식품제조가공업(주)초코텍과자경기도 이천시 대월면 대월로667번길 38-48경기도 이천시 대월면 초지리 733-1번지17343<NA>37.217411127.490679
1이천시2020-3-12722023120120160358514식품제조가공업(주)초코텍캔디류경기도 이천시 대월면 대월로667번길 38-48경기도 이천시 대월면 초지리 733-1번지17343<NA>37.217411127.490679
2화성시2023-3-09342023113020120311458식품제조가공업새싹푸드즉석조리식품경기도 화성시 매송면 야목길 42경기도 화성시 매송면 야목리 382번지 1층 전체호18286<NA>37.268198126.880328
3안산시2023-3-09322023113020120311458식품제조가공업새싹푸드소스경기도 안산시 상록구 고목로 21경기도 안산시 상록구 본오동 977-11번지 1층 본오동15574<NA>37.282446126.857909
4안산시2023-3-09332023113020120311458식품제조가공업새싹푸드조림류경기도 안산시 상록구 고목로 21경기도 안산시 상록구 본오동 977-11번지 1층 본오동15574<NA>37.282446126.857909
5화성시2023-3-09332023113020120311458식품제조가공업새싹푸드조림류경기도 화성시 매송면 야목길 42경기도 화성시 매송면 야목리 382번지 1층 전체호18286<NA>37.268198126.880328
6부천시2023-3-09352023113020220396721식품제조가공업주식회사 푸른공식과자경기도 부천시 오정로 194경기도 부천시 오정동 594번지 일광오정파크 4층 일부호 오정동14443<NA>37.526271126.782105
7부천시2023-3-09372023113020100294870식품제조가공업샘물자리곡류가공품경기도 부천시 부천로 342경기도 부천시 도당동 75-3번지 (부천시장애인직업재활시설 5,6층 일부호 도당동)14487<NA>37.51468126.785101
8부천시2023-3-09362023113020220396721식품제조가공업주식회사 푸른공식빵류경기도 부천시 오정로 194경기도 부천시 오정동 594번지 일광오정파크 4층 일부호 오정동14443<NA>37.526271126.782105
9안성시2023-3-09382023113020190376144식품제조가공업주식회사 케이지이혼합음료경기도 안성시 공도읍 신두만곡로 216-18경기도 안성시 공도읍 신두리 139-1번지17558<NA>36.991113127.201966
시군명HACCP지정번호HACCP지정일자인허가번호업종구분명업소명품목명도로명주소지번주소우편번호소규모업소여부WGS84위도WGS84경도
8957양주시2010-1-80292010110420100370135식품제조가공업농업회사법인 송산 주식회사김치(기타김치)경기도 양주시 장흥면 권율로29번길 115-84경기도 양주시 장흥면 일영리 64-5번지 (주1동 1,2,3층)11520<NA>37.721843126.938568
8958양주시2010-1-80282010110420100370135식품제조가공업농업회사법인 송산 주식회사김치(배추김치)경기도 양주시 장흥면 권율로29번길 115-84경기도 양주시 장흥면 일영리 64-5번지 (주1동 1,2,3층)11520<NA>37.721843126.938568
8959평택시2009-3-80202009042419950306274식품제조가공업롯데후레쉬델리카제2호(주)냉동식품 중 면류(국수)경기도 평택시 세교산단로101번길 47경기도 평택시 세교동 536-9번지17843<NA>37.014226127.079799
8960김포시2008-3-80012008011520030362122식품제조가공업(주)호텔리어쿡김치(배추김치)(배추김치, 기타김치)경기도 김포시 통진읍 고척로 251경기도 김포시 통진읍 고정리 261-1번지10009<NA>37.717161126.595722
8961화성시2007-3-80412007121819950364019식품제조가공업(주)늘푸른김치(배추김치)(배추김치, 기타김치, 절임식품(식염절임))경기도 화성시 장안면 한천3길 26-11경기도 화성시 장안면 독정리 862-1번지18583<NA>37.069406126.844051
8962용인시2007-3-80382007111219860347002식품제조가공업(주)동성식품떡류(생면류)경기도 용인시 처인구 유림로 135경기도 용인시 처인구 유방동 625번지17042<NA>37.259956127.199658
8963용인시2007-3-80332007103019800347002식품제조가공업대상(주)기흥공장토마토케첩(토마토케첩, 소스류, 드레싱류)경기도 용인시 기흥구 동탄기흥로681번길 28경기도 용인시 기흥구 농서동 72-2번지17102<NA>37.220818127.091595
8964여주시2007-3-80322007102920070375129식품제조가공업농업회사법인 한둘 주식회사묵류경기도 여주시 가남읍 금당2길 118경기도 여주시 가남읍 금당리 572번지12660<NA>37.210203127.610424
8965포천시2007-6-80222007043020090372366식품제조가공업농업회사법인 늘만나식품(주)김치(배추김치)(배추김치, 기타김치)경기도 포천시 내촌면 금강로3029번길 14-1경기도 포천시 내촌면 신팔리 408번지11188<NA>37.833713127.266851
8966포천시2006-1-80182006121819900372085식품제조가공업(주)동성식품 포천지점냉동식품 중 면류경기도 포천시 군내면 용두로 47경기도 포천시 군내면 용정리 6-1번지11154<NA>37.871644127.219159

Duplicate rows

Most frequently occurring

시군명HACCP지정번호HACCP지정일자인허가번호업종구분명업소명품목명도로명주소지번주소우편번호WGS84위도WGS84경도# duplicates
23안산시2016-3-84302022120120110311336식품제조가공업씨제이제일제당(주)전분경기도 안산시 상록구 용담로 141경기도 안산시 상록구 팔곡이동 27번지 외 1필지1552837.291947126.8920594
1고양시2021-1-00692021021520150355712식품제조가공업(주)손맛커피커피경기도 고양시 일산동구 문원길 30-63경기도 고양시 일산동구 지영동 399-13번지1025437.710631126.8220123
20안산시2016-3-80782022120120110311336식품제조가공업씨제이제일제당(주)물엿경기도 안산시 상록구 용담로 141경기도 안산시 상록구 팔곡이동 27번지 외 1필지1552837.291947126.8920593
21안산시2016-3-80792022120120110311336식품제조가공업씨제이제일제당(주)기타과당경기도 안산시 상록구 용담로 141경기도 안산시 상록구 팔곡이동 27번지 외 1필지1552837.291947126.8920593
22안산시2016-3-80802022120120110311336식품제조가공업씨제이제일제당(주)올리고당경기도 안산시 상록구 용담로 141경기도 안산시 상록구 팔곡이동 27번지 외 1필지1552837.291947126.8920593
29오산시2019-3-91282022041720020336425식품제조가공업(주)신세계푸드 오산공장냉동식품 중 피자류경기도 오산시 동부대로 387경기도 오산시 원동 542-2번지1814437.136043127.076753
30오산시2021-6-08392021090820190352055식품제조가공업주식회사큐앤비푸드과자경기도 오산시 청학로 14경기도 오산시 청학동 38-2번지 3층 청학동1811937.150728127.0621193
31오산시2022-6-04642022080320190352055식품제조가공업주식회사큐앤비푸드빵류경기도 오산시 청학로 14경기도 오산시 청학동 38-2번지 3층 청학동1811937.150728127.0621193
33용인시2019-3-91762022060520190363040식품제조가공업농업회사법인 마음이가(주)떡류경기도 용인시 처인구 포곡읍 곡현로 89-25경기도 용인시 처인구 포곡읍 유운리 381-4번지1702237.294562127.2183973
35용인시2020-3-10382020101920140069906식품제조가공업(주)브리에잇과자경기도 용인시 처인구 모현읍 곡현로 784경기도 용인시 처인구 모현읍 일산리 518-1번지 2층 일부호1703337.351416127.2316323