Overview

Dataset statistics

Number of variables61
Number of observations4333
Missing cells114987
Missing cells (%)43.5%
Duplicate rows3
Duplicate rows (%)0.1%
Total size in memory2.2 MiB
Average record size in memory523.0 B

Variable types

Categorical19
Numeric11
Unsupported18
Text13

Dataset

Description시군구코드,업종코드,업종명,계획구분코드,계획구분명,지도점검계획,수거계획,수거증번호,수거사유코드,업소명,식품군코드,식품군,품목명,제품명,음식물명,원료명,생산업소,수거일자,수거량(정량),제품규격(정량),단위(정량),수거량(자유),제조일자(일자),제조일자(롯트),유통기한(일자),유통기한(제조일기준),보관상태코드,바코드번호,어린이기호식품유형,검사기관명,(구)제조사명,내외국산,국가명,검사구분,검사의뢰일자,결과회보일자,판정구분,처리구분,수거검사구분코드,단속지역구분코드,수거장소구분코드,처리결과,수거품처리,교부번호,폐기일자,폐기량(kg),폐기금액(원),폐기장소,폐기방법,소재지(도로명),소재지(지번),업소전화번호,점검목적,점검일자,점검구분,점검내용,점검결과코드,(구)제조유통기한,(구)제조회사주소,부적합항목,기준치부적합내용
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-10916/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 3 (0.1%) duplicate rowsDuplicates
업종명 is highly imbalanced (52.0%)Imbalance
계획구분코드 is highly imbalanced (53.8%)Imbalance
지도점검계획 is highly imbalanced (61.5%)Imbalance
수거계획 is highly imbalanced (52.6%)Imbalance
수거량(자유) is highly imbalanced (95.1%)Imbalance
(구)제조사명 is highly imbalanced (95.3%)Imbalance
내외국산 is highly imbalanced (51.5%)Imbalance
국가명 is highly imbalanced (94.0%)Imbalance
판정구분 is highly imbalanced (57.3%)Imbalance
(구)제조회사주소 is highly imbalanced (98.2%)Imbalance
계획구분명 has 4333 (100.0%) missing valuesMissing
수거증번호 has 337 (7.8%) missing valuesMissing
식품군코드 has 174 (4.0%) missing valuesMissing
식품군 has 812 (18.7%) missing valuesMissing
품목명 has 192 (4.4%) missing valuesMissing
음식물명 has 4077 (94.1%) missing valuesMissing
원료명 has 4330 (99.9%) missing valuesMissing
생산업소 has 4010 (92.5%) missing valuesMissing
수거량(정량) has 107 (2.5%) missing valuesMissing
제품규격(정량) has 444 (10.2%) missing valuesMissing
제조일자(일자) has 3269 (75.4%) missing valuesMissing
제조일자(롯트) has 4333 (100.0%) missing valuesMissing
유통기한(일자) has 4279 (98.8%) missing valuesMissing
유통기한(제조일기준) has 4317 (99.6%) missing valuesMissing
바코드번호 has 4333 (100.0%) missing valuesMissing
어린이기호식품유형 has 4333 (100.0%) missing valuesMissing
검사의뢰일자 has 2008 (46.3%) missing valuesMissing
결과회보일자 has 3565 (82.3%) missing valuesMissing
처리구분 has 4333 (100.0%) missing valuesMissing
수거검사구분코드 has 4333 (100.0%) missing valuesMissing
단속지역구분코드 has 4333 (100.0%) missing valuesMissing
수거장소구분코드 has 4333 (100.0%) missing valuesMissing
처리결과 has 4333 (100.0%) missing valuesMissing
수거품처리 has 4333 (100.0%) missing valuesMissing
폐기일자 has 4333 (100.0%) missing valuesMissing
폐기량(kg) has 4333 (100.0%) missing valuesMissing
폐기금액(원) has 4333 (100.0%) missing valuesMissing
폐기장소 has 4333 (100.0%) missing valuesMissing
폐기방법 has 4333 (100.0%) missing valuesMissing
소재지(도로명) has 382 (8.8%) missing valuesMissing
소재지(지번) has 66 (1.5%) missing valuesMissing
업소전화번호 has 345 (8.0%) missing valuesMissing
점검내용 has 4333 (100.0%) missing valuesMissing
(구)제조유통기한 has 4279 (98.8%) missing valuesMissing
부적합항목 has 4333 (100.0%) missing valuesMissing
기준치부적합내용 has 4333 (100.0%) missing valuesMissing
수거량(정량) is highly skewed (γ1 = 25.8298774)Skewed
제조일자(일자) is highly skewed (γ1 = 25.5688164)Skewed
검사의뢰일자 is highly skewed (γ1 = -43.88808915)Skewed
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제조일자(롯트) is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
어린이기호식품유형 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부적합항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 03:32:05.771134
Analysis finished2024-05-11 03:32:10.367796
Duration4.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
3080000
4333 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 4333
100.0%

Length

2024-05-11T03:32:10.493833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:10.747076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 4333
100.0%

업종코드
Real number (ℝ)

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.80175
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:11.043427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1112
median114
Q3114
95-th percentile114
Maximum134
Range33
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.6397855
Coefficient of variation (CV)0.050444517
Kurtosis2.1140599
Mean111.80175
Median Absolute Deviation (MAD)0
Skewness-0.18072848
Sum484437
Variance31.807181
MonotonicityIncreasing
2024-05-11T03:32:11.424956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
114 3038
70.1%
101 569
 
13.1%
105 134
 
3.1%
104 129
 
3.0%
121 111
 
2.6%
106 100
 
2.3%
107 90
 
2.1%
112 86
 
2.0%
134 52
 
1.2%
122 21
 
0.5%
ValueCountFrequency (%)
101 569
 
13.1%
104 129
 
3.0%
105 134
 
3.1%
106 100
 
2.3%
107 90
 
2.1%
109 3
 
0.1%
112 86
 
2.0%
114 3038
70.1%
121 111
 
2.6%
122 21
 
0.5%
ValueCountFrequency (%)
134 52
 
1.2%
122 21
 
0.5%
121 111
 
2.6%
114 3038
70.1%
112 86
 
2.0%
109 3
 
0.1%
107 90
 
2.1%
106 100
 
2.3%
105 134
 
3.1%
104 129
 
3.0%

업종명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
기타식품판매업
3038 
일반음식점
569 
집단급식소
 
134
휴게음식점
 
129
제과점영업
 
111
Other values (6)
352 

Length

Max length11
Median length7
Mean length6.7071313
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 3038
70.1%
일반음식점 569
 
13.1%
집단급식소 134
 
3.1%
휴게음식점 129
 
3.0%
제과점영업 111
 
2.6%
식품제조가공업 100
 
2.3%
즉석판매제조가공업 90
 
2.1%
식품자동판매기영업 86
 
2.0%
건강기능식품일반판매업 52
 
1.2%
집단급식소식품판매업 21
 
0.5%

Length

2024-05-11T03:32:11.873431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 3038
70.1%
일반음식점 569
 
13.1%
집단급식소 134
 
3.1%
휴게음식점 129
 
3.0%
제과점영업 111
 
2.6%
식품제조가공업 100
 
2.3%
즉석판매제조가공업 90
 
2.1%
식품자동판매기영업 86
 
2.0%
건강기능식품일반판매업 52
 
1.2%
집단급식소식품판매업 21
 
0.5%

계획구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
3245 
999
1009 
2
 
56
7
 
23

Length

Max length4
Median length4
Mean length3.7124394
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3245
74.9%
999 1009
 
23.3%
2 56
 
1.3%
7 23
 
0.5%

Length

2024-05-11T03:32:12.124564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:12.336317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3245
74.9%
999 1009
 
23.3%
2 56
 
1.3%
7 23
 
0.5%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
3245 
시군구-일상단속
 
245
2021년 식품제조유통 등 안전관리 계획
 
185
한우유전자 수거 계획
 
100
시군구 식품접객업소 지도점검
 
86
Other values (17)
472 

Length

Max length40
Median length4
Mean length6.9953843
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3245
74.9%
시군구-일상단속 245
 
5.7%
2021년 식품제조유통 등 안전관리 계획 185
 
4.3%
한우유전자 수거 계획 100
 
2.3%
시군구 식품접객업소 지도점검 86
 
2.0%
2022년 식품제조유통 등 안전관리계획 74
 
1.7%
가공식품 일상단속 69
 
1.6%
2019년 시군구 식품접객업소 지도점검 59
 
1.4%
- 2017년도 하반기 -구민 먹거리 안전을 위한 식품접객업소 수거 계획 56
 
1.3%
일상점검 38
 
0.9%
Other values (12) 176
 
4.1%

Length

2024-05-11T03:32:12.591119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3245
47.6%
계획 404
 
5.9%
식품제조유통 294
 
4.3%
294
 
4.3%
식품접객업소 253
 
3.7%
시군구-일상단속 245
 
3.6%
안전관리 220
 
3.2%
지도점검 194
 
2.8%
2021년 186
 
2.7%
수거 156
 
2.3%
Other values (38) 1320
19.4%

수거계획
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
3267 
일상수거
397 
가공식품 수거검사
 
289
2019 유통식품 수거검사 계획
 
182
2020 유통식품 수거검사
 
120
Other values (2)
 
78

Length

Max length24
Median length4
Mean length5.3985691
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일상수거
2nd row<NA>
3rd row<NA>
4th row일상수거
5th row일상수거

Common Values

ValueCountFrequency (%)
<NA> 3267
75.4%
일상수거 397
 
9.2%
가공식품 수거검사 289
 
6.7%
2019 유통식품 수거검사 계획 182
 
4.2%
2020 유통식품 수거검사 120
 
2.8%
2023년 유통식품 등 수거검사 73
 
1.7%
2019 시중유통준인 먹는샘물 수거검사 계획 5
 
0.1%

Length

2024-05-11T03:32:12.891582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:13.281253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3267
57.9%
수거검사 669
 
11.8%
일상수거 397
 
7.0%
유통식품 375
 
6.6%
가공식품 289
 
5.1%
2019 187
 
3.3%
계획 187
 
3.3%
2020 120
 
2.1%
2023년 73
 
1.3%
73
 
1.3%
Other values (2) 10
 
0.2%

수거증번호
Text

MISSING 

Distinct2097
Distinct (%)52.5%
Missing337
Missing (%)7.8%
Memory size34.0 KiB
2024-05-11T03:32:13.929711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.0385385
Min length1

Characters and Unicode

Total characters32122
Distinct characters49
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1334 ?
Unique (%)33.4%

Sample

1st row109-5-1
2nd row2010-6-11
3rd row109-6-4
4th row109-05-47
5th row109-05-48
ValueCountFrequency (%)
109-6-50 13
 
0.3%
109-11-10 10
 
0.3%
109-6-23 9
 
0.2%
109-6-21 9
 
0.2%
109-6-22 9
 
0.2%
109-6-18 9
 
0.2%
109-6-16 9
 
0.2%
109-6-14 9
 
0.2%
109-6-12 9
 
0.2%
109-6-11 9
 
0.2%
Other values (2082) 3902
97.6%
2024-05-11T03:32:15.084112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7436
23.1%
1 6786
21.1%
0 5207
16.2%
9 4684
14.6%
2 1556
 
4.8%
3 1189
 
3.7%
6 1084
 
3.4%
4 984
 
3.1%
5 982
 
3.1%
8 739
 
2.3%
Other values (39) 1475
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23925
74.5%
Dash Punctuation 7436
 
23.1%
Other Letter 689
 
2.1%
Lowercase Letter 42
 
0.1%
Uppercase Letter 29
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
236
34.3%
51
 
7.4%
46
 
6.7%
46
 
6.7%
46
 
6.7%
41
 
6.0%
41
 
6.0%
25
 
3.6%
25
 
3.6%
18
 
2.6%
Other values (20) 114
16.5%
Decimal Number
ValueCountFrequency (%)
1 6786
28.4%
0 5207
21.8%
9 4684
19.6%
2 1556
 
6.5%
3 1189
 
5.0%
6 1084
 
4.5%
4 984
 
4.1%
5 982
 
4.1%
8 739
 
3.1%
7 714
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
L 20
69.0%
G 3
 
10.3%
M 3
 
10.3%
O 3
 
10.3%
Lowercase Letter
ValueCountFrequency (%)
o 14
33.3%
g 14
33.3%
m 14
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 7436
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31362
97.6%
Hangul 689
 
2.1%
Latin 71
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
236
34.3%
51
 
7.4%
46
 
6.7%
46
 
6.7%
46
 
6.7%
41
 
6.0%
41
 
6.0%
25
 
3.6%
25
 
3.6%
18
 
2.6%
Other values (20) 114
16.5%
Common
ValueCountFrequency (%)
- 7436
23.7%
1 6786
21.6%
0 5207
16.6%
9 4684
14.9%
2 1556
 
5.0%
3 1189
 
3.8%
6 1084
 
3.5%
4 984
 
3.1%
5 982
 
3.1%
8 739
 
2.4%
Other values (2) 715
 
2.3%
Latin
ValueCountFrequency (%)
L 20
28.2%
o 14
19.7%
g 14
19.7%
m 14
19.7%
G 3
 
4.2%
M 3
 
4.2%
O 3
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31433
97.9%
Hangul 453
 
1.4%
Compat Jamo 236
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7436
23.7%
1 6786
21.6%
0 5207
16.6%
9 4684
14.9%
2 1556
 
5.0%
3 1189
 
3.8%
6 1084
 
3.4%
4 984
 
3.1%
5 982
 
3.1%
8 739
 
2.4%
Other values (9) 786
 
2.5%
Compat Jamo
ValueCountFrequency (%)
236
100.0%
Hangul
ValueCountFrequency (%)
51
11.3%
46
10.2%
46
10.2%
46
10.2%
41
9.1%
41
9.1%
25
 
5.5%
25
 
5.5%
18
 
4.0%
18
 
4.0%
Other values (19) 96
21.2%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
검사용
2530 
<NA>
1711 
기타
 
82
증거용
 
10

Length

Max length4
Median length3
Mean length3.375952
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row검사용
2nd row<NA>
3rd row검사용
4th row검사용
5th row검사용

Common Values

ValueCountFrequency (%)
검사용 2530
58.4%
<NA> 1711
39.5%
기타 82
 
1.9%
증거용 10
 
0.2%

Length

2024-05-11T03:32:15.392798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:15.635831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 2530
58.4%
na 1711
39.5%
기타 82
 
1.9%
증거용 10
 
0.2%
Distinct402
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
2024-05-11T03:32:15.991259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length10.897992
Min length2

Characters and Unicode

Total characters47221
Distinct characters424
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)4.7%

Sample

1st row서울왕족발
2nd row장가네세수대냉면
3rd row수봉냉면
4th row똘끼차이나
5th row똘끼차이나
ValueCountFrequency (%)
삼양점 672
 
9.4%
롯데쇼핑(주)롯데마트 666
 
9.3%
번동점 567
 
7.9%
수유점 494
 
6.9%
롯데쇼핑(주)롯데슈퍼 490
 
6.9%
주)이마트에브리데이 302
 
4.2%
주)지에스리테일 232
 
3.2%
주)킴스클럽마트 218
 
3.1%
롯데쇼핑(주)미아점 163
 
2.3%
강북미아점 145
 
2.0%
Other values (448) 3198
44.7%
2024-05-11T03:32:16.669010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2978
 
6.3%
2815
 
6.0%
2698
 
5.7%
( 2689
 
5.7%
) 2689
 
5.7%
2573
 
5.4%
2511
 
5.3%
1860
 
3.9%
1821
 
3.9%
1324
 
2.8%
Other values (414) 23263
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37970
80.4%
Space Separator 2815
 
6.0%
Open Punctuation 2689
 
5.7%
Close Punctuation 2689
 
5.7%
Uppercase Letter 554
 
1.2%
Lowercase Letter 328
 
0.7%
Decimal Number 75
 
0.2%
Dash Punctuation 53
 
0.1%
Other Punctuation 48
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2978
 
7.8%
2698
 
7.1%
2573
 
6.8%
2511
 
6.6%
1860
 
4.9%
1821
 
4.8%
1324
 
3.5%
1324
 
3.5%
1034
 
2.7%
1001
 
2.6%
Other values (376) 18846
49.6%
Lowercase Letter
ValueCountFrequency (%)
e 80
24.4%
h 69
21.0%
f 39
11.9%
t 34
10.4%
r 32
 
9.8%
s 30
 
9.1%
c 11
 
3.4%
a 11
 
3.4%
l 9
 
2.7%
m 9
 
2.7%
Other values (2) 4
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
S 274
49.5%
G 143
25.8%
K 93
 
16.8%
C 13
 
2.3%
F 12
 
2.2%
D 7
 
1.3%
T 7
 
1.3%
A 2
 
0.4%
U 1
 
0.2%
O 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 51
68.0%
5 8
 
10.7%
2 6
 
8.0%
9 4
 
5.3%
0 3
 
4.0%
3 2
 
2.7%
6 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 33
68.8%
9
 
18.8%
/ 4
 
8.3%
& 2
 
4.2%
Space Separator
ValueCountFrequency (%)
2815
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2689
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37967
80.4%
Common 8369
 
17.7%
Latin 882
 
1.9%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2978
 
7.8%
2698
 
7.1%
2573
 
6.8%
2511
 
6.6%
1860
 
4.9%
1821
 
4.8%
1324
 
3.5%
1324
 
3.5%
1034
 
2.7%
1001
 
2.6%
Other values (374) 18843
49.6%
Latin
ValueCountFrequency (%)
S 274
31.1%
G 143
16.2%
K 93
 
10.5%
e 80
 
9.1%
h 69
 
7.8%
f 39
 
4.4%
t 34
 
3.9%
r 32
 
3.6%
s 30
 
3.4%
C 13
 
1.5%
Other values (13) 75
 
8.5%
Common
ValueCountFrequency (%)
2815
33.6%
( 2689
32.1%
) 2689
32.1%
- 53
 
0.6%
1 51
 
0.6%
. 33
 
0.4%
9
 
0.1%
5 8
 
0.1%
2 6
 
0.1%
/ 4
 
< 0.1%
Other values (5) 12
 
0.1%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37967
80.4%
ASCII 9242
 
19.6%
None 9
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2978
 
7.8%
2698
 
7.1%
2573
 
6.8%
2511
 
6.6%
1860
 
4.9%
1821
 
4.8%
1324
 
3.5%
1324
 
3.5%
1034
 
2.7%
1001
 
2.6%
Other values (374) 18843
49.6%
ASCII
ValueCountFrequency (%)
2815
30.5%
( 2689
29.1%
) 2689
29.1%
S 274
 
3.0%
G 143
 
1.5%
K 93
 
1.0%
e 80
 
0.9%
h 69
 
0.7%
- 53
 
0.6%
1 51
 
0.6%
Other values (27) 286
 
3.1%
None
ValueCountFrequency (%)
9
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
2
66.7%
1
33.3%

식품군코드
Text

MISSING 

Distinct272
Distinct (%)6.5%
Missing174
Missing (%)4.0%
Memory size34.0 KiB
2024-05-11T03:32:17.164953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.590527
Min length1

Characters and Unicode

Total characters44046
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)2.0%

Sample

1st row600000000
2nd row
3rd rowC0121020000000
4th rowG0100000100000
5th rowG0100000100000
ValueCountFrequency (%)
c01000000 271
 
6.9%
g0100000100000 268
 
6.9%
821000000 220
 
5.6%
829000000 178
 
4.6%
816000000 118
 
3.0%
801000000 115
 
2.9%
802000000 111
 
2.8%
600000000 93
 
2.4%
c0312020100000 90
 
2.3%
818000000 81
 
2.1%
Other values (260) 2357
60.4%
2024-05-11T03:32:18.109448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30168
68.5%
1 3639
 
8.3%
2 2242
 
5.1%
8 1744
 
4.0%
1369
 
3.1%
C 1326
 
3.0%
3 1324
 
3.0%
4 456
 
1.0%
9 432
 
1.0%
G 356
 
0.8%
Other values (11) 990
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40755
92.5%
Uppercase Letter 1922
 
4.4%
Space Separator 1369
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30168
74.0%
1 3639
 
8.9%
2 2242
 
5.5%
8 1744
 
4.3%
3 1324
 
3.2%
4 456
 
1.1%
9 432
 
1.1%
6 306
 
0.8%
5 268
 
0.7%
7 176
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 1326
69.0%
G 356
 
18.5%
H 57
 
3.0%
A 53
 
2.8%
E 52
 
2.7%
B 34
 
1.8%
F 27
 
1.4%
X 11
 
0.6%
Z 3
 
0.2%
D 3
 
0.2%
Space Separator
ValueCountFrequency (%)
1369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42124
95.6%
Latin 1922
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30168
71.6%
1 3639
 
8.6%
2 2242
 
5.3%
8 1744
 
4.1%
1369
 
3.2%
3 1324
 
3.1%
4 456
 
1.1%
9 432
 
1.0%
6 306
 
0.7%
5 268
 
0.6%
Latin
ValueCountFrequency (%)
C 1326
69.0%
G 356
 
18.5%
H 57
 
3.0%
A 53
 
2.8%
E 52
 
2.7%
B 34
 
1.8%
F 27
 
1.4%
X 11
 
0.6%
Z 3
 
0.2%
D 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30168
68.5%
1 3639
 
8.3%
2 2242
 
5.1%
8 1744
 
4.0%
1369
 
3.1%
C 1326
 
3.0%
3 1324
 
3.0%
4 456
 
1.0%
9 432
 
1.0%
G 356
 
0.8%
Other values (11) 990
 
2.2%

식품군
Text

MISSING 

Distinct206
Distinct (%)5.9%
Missing812
Missing (%)18.7%
Memory size34.0 KiB
2024-05-11T03:32:19.023661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length15
Mean length4.7157058
Min length1

Characters and Unicode

Total characters16604
Distinct characters246
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

Unique61 ?
Unique (%)1.7%

Sample

1st row식품접객업
2nd row소스류
3rd row조리식품 등
4th row조리식품 등
5th row조리식품 등
ValueCountFrequency (%)
284
 
6.9%
조리식품 268
 
6.5%
조미식품 238
 
5.8%
기타식품류 201
 
4.9%
과자류 186
 
4.5%
다류 143
 
3.5%
빵또는떡류 111
 
2.7%
식품접객업 93
 
2.3%
과자 92
 
2.2%
소스 90
 
2.2%
Other values (220) 2407
58.5%
2024-05-11T03:32:20.371083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1697
 
10.2%
1437
 
8.7%
1243
 
7.5%
673
 
4.1%
602
 
3.6%
592
 
3.6%
458
 
2.8%
418
 
2.5%
400
 
2.4%
321
 
1.9%
Other values (236) 8763
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15725
94.7%
Space Separator 592
 
3.6%
Other Punctuation 111
 
0.7%
Open Punctuation 63
 
0.4%
Close Punctuation 63
 
0.4%
Decimal Number 24
 
0.1%
Uppercase Letter 17
 
0.1%
Dash Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1697
 
10.8%
1437
 
9.1%
1243
 
7.9%
673
 
4.3%
602
 
3.8%
458
 
2.9%
418
 
2.7%
400
 
2.5%
321
 
2.0%
319
 
2.0%
Other values (216) 8157
51.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
23.5%
D 3
17.6%
C 3
17.6%
B 2
11.8%
E 1
 
5.9%
P 1
 
5.9%
H 1
 
5.9%
Q 1
 
5.9%
L 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 18
75.0%
3 4
 
16.7%
0 1
 
4.2%
2 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 59
53.2%
, 49
44.1%
? 3
 
2.7%
Space Separator
ValueCountFrequency (%)
592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15725
94.7%
Common 862
 
5.2%
Latin 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1697
 
10.8%
1437
 
9.1%
1243
 
7.9%
673
 
4.3%
602
 
3.8%
458
 
2.9%
418
 
2.7%
400
 
2.5%
321
 
2.0%
319
 
2.0%
Other values (216) 8157
51.9%
Common
ValueCountFrequency (%)
592
68.7%
( 63
 
7.3%
) 63
 
7.3%
. 59
 
6.8%
, 49
 
5.7%
1 18
 
2.1%
- 9
 
1.0%
3 4
 
0.5%
? 3
 
0.3%
0 1
 
0.1%
Latin
ValueCountFrequency (%)
A 4
23.5%
D 3
17.6%
C 3
17.6%
B 2
11.8%
E 1
 
5.9%
P 1
 
5.9%
H 1
 
5.9%
Q 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15725
94.7%
ASCII 879
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1697
 
10.8%
1437
 
9.1%
1243
 
7.9%
673
 
4.3%
602
 
3.8%
458
 
2.9%
418
 
2.7%
400
 
2.5%
321
 
2.0%
319
 
2.0%
Other values (216) 8157
51.9%
ASCII
ValueCountFrequency (%)
592
67.3%
( 63
 
7.2%
) 63
 
7.2%
. 59
 
6.7%
, 49
 
5.6%
1 18
 
2.0%
- 9
 
1.0%
A 4
 
0.5%
3 4
 
0.5%
D 3
 
0.3%
Other values (10) 15
 
1.7%

품목명
Text

MISSING 

Distinct304
Distinct (%)7.3%
Missing192
Missing (%)4.4%
Memory size34.0 KiB
2024-05-11T03:32:21.021349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length26
Mean length4.9983096
Min length1

Characters and Unicode

Total characters20698
Distinct characters304
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

Unique92 ?
Unique (%)2.2%

Sample

1st row접객업소조리식품등
2nd row소스류
3rd row조리식품 등
4th row조리식품 등
5th row조리식품 등
ValueCountFrequency (%)
615
 
11.8%
조리식품 599
 
11.4%
소스류 164
 
3.1%
과자 159
 
3.0%
즉석조리식품 142
 
2.7%
기타가공품 131
 
2.5%
캔디류 99
 
1.9%
소스 92
 
1.8%
기타 88
 
1.7%
복합조미식품 87
 
1.7%
Other values (322) 3058
58.4%
2024-05-11T03:32:22.111721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1306
 
6.3%
1093
 
5.3%
1034
 
5.0%
1025
 
5.0%
953
 
4.6%
852
 
4.1%
804
 
3.9%
630
 
3.0%
560
 
2.7%
461
 
2.2%
Other values (294) 11980
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18755
90.6%
Space Separator 1093
 
5.3%
Other Punctuation 283
 
1.4%
Close Punctuation 228
 
1.1%
Open Punctuation 228
 
1.1%
Decimal Number 62
 
0.3%
Dash Punctuation 29
 
0.1%
Uppercase Letter 20
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1306
 
7.0%
1034
 
5.5%
1025
 
5.5%
953
 
5.1%
852
 
4.5%
804
 
4.3%
630
 
3.4%
560
 
3.0%
461
 
2.5%
449
 
2.4%
Other values (273) 10681
57.0%
Uppercase Letter
ValueCountFrequency (%)
C 6
30.0%
A 4
20.0%
D 3
15.0%
B 2
 
10.0%
L 1
 
5.0%
H 1
 
5.0%
E 1
 
5.0%
P 1
 
5.0%
Q 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 51
82.3%
3 6
 
9.7%
4 3
 
4.8%
0 1
 
1.6%
2 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 220
77.7%
, 60
 
21.2%
? 3
 
1.1%
Space Separator
ValueCountFrequency (%)
1093
100.0%
Close Punctuation
ValueCountFrequency (%)
) 228
100.0%
Open Punctuation
ValueCountFrequency (%)
( 228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18755
90.6%
Common 1923
 
9.3%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1306
 
7.0%
1034
 
5.5%
1025
 
5.5%
953
 
5.1%
852
 
4.5%
804
 
4.3%
630
 
3.4%
560
 
3.0%
461
 
2.5%
449
 
2.4%
Other values (273) 10681
57.0%
Common
ValueCountFrequency (%)
1093
56.8%
) 228
 
11.9%
( 228
 
11.9%
. 220
 
11.4%
, 60
 
3.1%
1 51
 
2.7%
- 29
 
1.5%
3 6
 
0.3%
? 3
 
0.2%
4 3
 
0.2%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
C 6
30.0%
A 4
20.0%
D 3
15.0%
B 2
 
10.0%
L 1
 
5.0%
H 1
 
5.0%
E 1
 
5.0%
P 1
 
5.0%
Q 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18755
90.6%
ASCII 1943
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1306
 
7.0%
1034
 
5.5%
1025
 
5.5%
953
 
5.1%
852
 
4.5%
804
 
4.3%
630
 
3.4%
560
 
3.0%
461
 
2.5%
449
 
2.4%
Other values (273) 10681
57.0%
ASCII
ValueCountFrequency (%)
1093
56.3%
) 228
 
11.7%
( 228
 
11.7%
. 220
 
11.3%
, 60
 
3.1%
1 51
 
2.6%
- 29
 
1.5%
C 6
 
0.3%
3 6
 
0.3%
A 4
 
0.2%
Other values (11) 18
 
0.9%
Distinct3145
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
2024-05-11T03:32:22.735912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length38
Mean length6.6277406
Min length1

Characters and Unicode

Total characters28718
Distinct characters865
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2656 ?
Unique (%)61.3%

Sample

1st row직화불족발
2nd row육수
3rd row[외식]물냉면육수
4th row새우볶음밥
5th row삼선볶음밥
ValueCountFrequency (%)
56
 
1.0%
커피 52
 
0.9%
두부 36
 
0.6%
한우 34
 
0.6%
자판기 30
 
0.5%
쇠고기 29
 
0.5%
청정원 23
 
0.4%
오뚜기 21
 
0.4%
19
 
0.3%
업진살 17
 
0.3%
Other values (3519) 5288
94.3%
2024-05-11T03:32:23.842472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1273
 
4.4%
752
 
2.6%
577
 
2.0%
494
 
1.7%
491
 
1.7%
370
 
1.3%
322
 
1.1%
304
 
1.1%
299
 
1.0%
289
 
1.0%
Other values (855) 23547
82.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25476
88.7%
Space Separator 1273
 
4.4%
Uppercase Letter 1004
 
3.5%
Decimal Number 294
 
1.0%
Lowercase Letter 242
 
0.8%
Close Punctuation 154
 
0.5%
Open Punctuation 154
 
0.5%
Other Punctuation 95
 
0.3%
Dash Punctuation 13
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
752
 
3.0%
577
 
2.3%
494
 
1.9%
491
 
1.9%
370
 
1.5%
322
 
1.3%
304
 
1.2%
299
 
1.2%
289
 
1.1%
289
 
1.1%
Other values (773) 21289
83.6%
Uppercase Letter
ValueCountFrequency (%)
E 86
 
8.6%
A 83
 
8.3%
O 77
 
7.7%
C 76
 
7.6%
I 71
 
7.1%
S 70
 
7.0%
T 61
 
6.1%
R 61
 
6.1%
L 48
 
4.8%
M 46
 
4.6%
Other values (16) 325
32.4%
Lowercase Letter
ValueCountFrequency (%)
a 38
15.7%
p 27
11.2%
m 23
 
9.5%
e 22
 
9.1%
i 17
 
7.0%
o 13
 
5.4%
s 13
 
5.4%
c 10
 
4.1%
u 10
 
4.1%
h 9
 
3.7%
Other values (13) 60
24.8%
Decimal Number
ValueCountFrequency (%)
0 103
35.0%
1 79
26.9%
3 29
 
9.9%
2 28
 
9.5%
5 24
 
8.2%
7 13
 
4.4%
6 9
 
3.1%
9 5
 
1.7%
4 3
 
1.0%
8 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
& 21
22.1%
; 17
17.9%
12
12.6%
% 11
11.6%
, 11
11.6%
/ 8
 
8.4%
' 6
 
6.3%
. 5
 
5.3%
? 3
 
3.2%
! 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 152
98.7%
] 2
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 152
98.7%
[ 2
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
~ 1
 
20.0%
Modifier Symbol
ValueCountFrequency (%)
˚ 2
50.0%
` 2
50.0%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
1273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25474
88.7%
Common 1993
 
6.9%
Latin 1249
 
4.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
752
 
3.0%
577
 
2.3%
494
 
1.9%
491
 
1.9%
370
 
1.5%
322
 
1.3%
304
 
1.2%
299
 
1.2%
289
 
1.1%
289
 
1.1%
Other values (771) 21287
83.6%
Latin
ValueCountFrequency (%)
E 86
 
6.9%
A 83
 
6.6%
O 77
 
6.2%
C 76
 
6.1%
I 71
 
5.7%
S 70
 
5.6%
T 61
 
4.9%
R 61
 
4.9%
L 48
 
3.8%
M 46
 
3.7%
Other values (41) 570
45.6%
Common
ValueCountFrequency (%)
1273
63.9%
) 152
 
7.6%
( 152
 
7.6%
0 103
 
5.2%
1 79
 
4.0%
3 29
 
1.5%
2 28
 
1.4%
5 24
 
1.2%
& 21
 
1.1%
; 17
 
0.9%
Other values (21) 115
 
5.8%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25472
88.7%
ASCII 3224
 
11.2%
None 12
 
< 0.1%
Number Forms 3
 
< 0.1%
Modifier Letters 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1273
39.5%
) 152
 
4.7%
( 152
 
4.7%
0 103
 
3.2%
E 86
 
2.7%
A 83
 
2.6%
1 79
 
2.5%
O 77
 
2.4%
C 76
 
2.4%
I 71
 
2.2%
Other values (67) 1072
33.3%
Hangul
ValueCountFrequency (%)
752
 
3.0%
577
 
2.3%
494
 
1.9%
491
 
1.9%
370
 
1.5%
322
 
1.3%
304
 
1.2%
299
 
1.2%
289
 
1.1%
289
 
1.1%
Other values (770) 21285
83.6%
None
ValueCountFrequency (%)
12
100.0%
Modifier Letters
ValueCountFrequency (%)
˚ 2
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

음식물명
Text

MISSING 

Distinct121
Distinct (%)47.3%
Missing4077
Missing (%)94.1%
Memory size34.0 KiB
2024-05-11T03:32:24.488981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.6914062
Min length1

Characters and Unicode

Total characters945
Distinct characters184
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

Unique89 ?
Unique (%)34.8%

Sample

1st row냉면육수
2nd row해물찜
3rd row보쌈
4th row콩국수 국물
5th row광어
ValueCountFrequency (%)
커피 26
 
9.8%
생크림케이크 15
 
5.7%
쿠키 15
 
5.7%
단팥빵 15
 
5.7%
식빵 14
 
5.3%
무농약쌀 7
 
2.6%
먹는물 6
 
2.3%
패스츄리 6
 
2.3%
패스추리 5
 
1.9%
먹는샘물 5
 
1.9%
Other values (115) 151
57.0%
2024-05-11T03:32:25.636415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
3.7%
32
 
3.4%
30
 
3.2%
30
 
3.2%
29
 
3.1%
27
 
2.9%
26
 
2.8%
22
 
2.3%
21
 
2.2%
21
 
2.2%
Other values (174) 672
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 931
98.5%
Space Separator 9
 
1.0%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
35
 
3.8%
32
 
3.4%
30
 
3.2%
30
 
3.2%
29
 
3.1%
27
 
2.9%
26
 
2.8%
22
 
2.4%
21
 
2.3%
21
 
2.3%
Other values (170) 658
70.7%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
! 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 931
98.5%
Common 14
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
35
 
3.8%
32
 
3.4%
30
 
3.2%
30
 
3.2%
29
 
3.1%
27
 
2.9%
26
 
2.8%
22
 
2.4%
21
 
2.3%
21
 
2.3%
Other values (170) 658
70.7%
Common
ValueCountFrequency (%)
9
64.3%
) 2
 
14.3%
( 2
 
14.3%
! 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 931
98.5%
ASCII 14
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
35
 
3.8%
32
 
3.4%
30
 
3.2%
30
 
3.2%
29
 
3.1%
27
 
2.9%
26
 
2.8%
22
 
2.4%
21
 
2.3%
21
 
2.3%
Other values (170) 658
70.7%
ASCII
ValueCountFrequency (%)
9
64.3%
) 2
 
14.3%
( 2
 
14.3%
! 1
 
7.1%

원료명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing4330
Missing (%)99.9%
Memory size34.0 KiB
2024-05-11T03:32:25.989901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3333333
Min length1

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row콜드부르
2nd row커피
3rd row
ValueCountFrequency (%)
콜드부르 1
33.3%
커피 1
33.3%
1
33.3%
2024-05-11T03:32:26.881087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

생산업소
Text

MISSING 

Distinct130
Distinct (%)40.2%
Missing4010
Missing (%)92.5%
Memory size34.0 KiB
2024-05-11T03:32:27.513760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length5.3591331
Min length2

Characters and Unicode

Total characters1731
Distinct characters232
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

Unique66 ?
Unique (%)20.4%

Sample

1st row강북구 도봉로87길 7
2nd row백만전
3rd row피자글릭/서울특별시 강북구 오패산로 381
4th row한천로139길 10
5th row피자헛 번동점/강북구 한천로 936
ValueCountFrequency (%)
오뚜기 18
 
4.6%
씨제이제일제당 13
 
3.3%
제일제당 13
 
3.3%
want 12
 
3.1%
오뚜기라면 10
 
2.6%
강북구 10
 
2.6%
오리온 9
 
2.3%
해태음료 8
 
2.0%
코카콜라 8
 
2.0%
씨제이 8
 
2.0%
Other values (148) 282
72.1%
2024-05-11T03:32:28.550145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
104
 
6.0%
68
 
3.9%
50
 
2.9%
41
 
2.4%
40
 
2.3%
39
 
2.3%
34
 
2.0%
31
 
1.8%
31
 
1.8%
29
 
1.7%
Other values (222) 1264
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1439
83.1%
Uppercase Letter 92
 
5.3%
Decimal Number 78
 
4.5%
Space Separator 68
 
3.9%
Other Punctuation 18
 
1.0%
Close Punctuation 16
 
0.9%
Open Punctuation 16
 
0.9%
Lowercase Letter 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
104
 
7.2%
50
 
3.5%
41
 
2.8%
40
 
2.8%
39
 
2.7%
34
 
2.4%
31
 
2.2%
31
 
2.2%
29
 
2.0%
29
 
2.0%
Other values (188) 1011
70.3%
Uppercase Letter
ValueCountFrequency (%)
T 15
16.3%
N 13
14.1%
O 13
14.1%
W 12
13.0%
A 12
13.0%
D 8
8.7%
S 7
7.6%
F 7
7.6%
B 1
 
1.1%
P 1
 
1.1%
Other values (3) 3
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 16
20.5%
3 15
19.2%
2 10
12.8%
9 9
11.5%
5 8
10.3%
7 7
9.0%
0 5
 
6.4%
6 4
 
5.1%
4 2
 
2.6%
8 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 15
83.3%
; 1
 
5.6%
. 1
 
5.6%
& 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
p 1
33.3%
m 1
33.3%
Space Separator
ValueCountFrequency (%)
68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1439
83.1%
Common 197
 
11.4%
Latin 95
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
104
 
7.2%
50
 
3.5%
41
 
2.8%
40
 
2.8%
39
 
2.7%
34
 
2.4%
31
 
2.2%
31
 
2.2%
29
 
2.0%
29
 
2.0%
Other values (188) 1011
70.3%
Common
ValueCountFrequency (%)
68
34.5%
) 16
 
8.1%
1 16
 
8.1%
( 16
 
8.1%
3 15
 
7.6%
/ 15
 
7.6%
2 10
 
5.1%
9 9
 
4.6%
5 8
 
4.1%
7 7
 
3.6%
Other values (8) 17
 
8.6%
Latin
ValueCountFrequency (%)
T 15
15.8%
N 13
13.7%
O 13
13.7%
W 12
12.6%
A 12
12.6%
D 8
8.4%
S 7
7.4%
F 7
7.4%
a 1
 
1.1%
B 1
 
1.1%
Other values (6) 6
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1439
83.1%
ASCII 292
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
104
 
7.2%
50
 
3.5%
41
 
2.8%
40
 
2.8%
39
 
2.7%
34
 
2.4%
31
 
2.2%
31
 
2.2%
29
 
2.0%
29
 
2.0%
Other values (188) 1011
70.3%
ASCII
ValueCountFrequency (%)
68
23.3%
) 16
 
5.5%
1 16
 
5.5%
( 16
 
5.5%
3 15
 
5.1%
T 15
 
5.1%
/ 15
 
5.1%
N 13
 
4.5%
O 13
 
4.5%
W 12
 
4.1%
Other values (24) 93
31.8%

수거일자
Real number (ℝ)

Distinct261
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20145885
Minimum20080707
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:29.395765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080707
5-th percentile20090707
Q120110315
median20150527
Q320180917
95-th percentile20220622
Maximum20240314
Range159607
Interquartile range (IQR)70602

Descriptive statistics

Standard deviation41936.412
Coefficient of variation (CV)0.0020816366
Kurtosis-1.1577082
Mean20145885
Median Absolute Deviation (MAD)40003
Skewness0.33677334
Sum8.7292121 × 1010
Variance1.7586626 × 109
MonotonicityNot monotonic
2024-05-11T03:32:30.436579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110419 89
 
2.1%
20210929 85
 
2.0%
20131118 84
 
1.9%
20201013 75
 
1.7%
20180918 74
 
1.7%
20120906 68
 
1.6%
20101209 68
 
1.6%
20110816 68
 
1.6%
20110516 65
 
1.5%
20190625 64
 
1.5%
Other values (251) 3593
82.9%
ValueCountFrequency (%)
20080707 1
 
< 0.1%
20090122 50
1.2%
20090209 50
1.2%
20090211 4
 
0.1%
20090223 18
 
0.4%
20090422 31
0.7%
20090514 20
 
0.5%
20090521 5
 
0.1%
20090707 43
1.0%
20090720 2
 
< 0.1%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240307 1
 
< 0.1%
20240229 3
 
0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20240115 2
 
< 0.1%
20231218 4
 
0.1%
20231205 7
 
0.2%
20231121 35
0.8%
20231113 2
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct211
Distinct (%)5.0%
Missing107
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean290.81401
Minimum1
Maximum54000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:31.267817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q3200
95-th percentile1300
Maximum54000
Range53999
Interquartile range (IQR)199

Descriptive statistics

Standard deviation1537.9203
Coefficient of variation (CV)5.2883296
Kurtosis807.08784
Mean290.81401
Median Absolute Deviation (MAD)2
Skewness25.829877
Sum1228980
Variance2365199
MonotonicityNot monotonic
2024-05-11T03:32:31.820403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1145
26.4%
6 577
13.3%
3 574
13.2%
2 449
 
10.4%
600 172
 
4.0%
300 85
 
2.0%
5 84
 
1.9%
1000 76
 
1.8%
4 70
 
1.6%
8 52
 
1.2%
Other values (201) 942
21.7%
(Missing) 107
 
2.5%
ValueCountFrequency (%)
1 1145
26.4%
2 449
 
10.4%
3 574
13.2%
4 70
 
1.6%
5 84
 
1.9%
6 577
13.3%
7 23
 
0.5%
8 52
 
1.2%
9 5
 
0.1%
10 21
 
0.5%
ValueCountFrequency (%)
54000 1
 
< 0.1%
48000 2
 
< 0.1%
24000 1
 
< 0.1%
14000 2
 
< 0.1%
12000 2
 
< 0.1%
7200 2
 
< 0.1%
6000 1
 
< 0.1%
4800 6
0.1%
4500 3
0.1%
3600 2
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct363
Distinct (%)9.3%
Missing444
Missing (%)10.2%
Memory size34.0 KiB
2024-05-11T03:32:32.646655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length2.3175624
Min length1

Characters and Unicode

Total characters9013
Distinct characters36
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)4.4%

Sample

1st row600
2nd rowml
3rd row600
4th row200
5th row200
ValueCountFrequency (%)
g 863
22.2%
600 311
 
8.0%
100 304
 
7.8%
ml 215
 
5.5%
1 161
 
4.1%
300 153
 
3.9%
500 146
 
3.8%
200 113
 
2.9%
250 58
 
1.5%
180 42
 
1.1%
Other values (344) 1523
39.2%
2024-05-11T03:32:33.702359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3212
35.6%
1 1034
 
11.5%
g 963
 
10.7%
5 645
 
7.2%
2 613
 
6.8%
6 501
 
5.6%
3 399
 
4.4%
8 258
 
2.9%
4 253
 
2.8%
l 253
 
2.8%
Other values (26) 882
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7205
79.9%
Lowercase Letter 1545
 
17.1%
Other Letter 113
 
1.3%
Other Punctuation 92
 
1.0%
Uppercase Letter 37
 
0.4%
Other Symbol 20
 
0.2%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3212
44.6%
1 1034
 
14.4%
5 645
 
9.0%
2 613
 
8.5%
6 501
 
7.0%
3 399
 
5.5%
8 258
 
3.6%
4 253
 
3.5%
9 149
 
2.1%
7 141
 
2.0%
Other Letter
ValueCountFrequency (%)
59
52.2%
24
21.2%
17
 
15.0%
3
 
2.7%
3
 
2.7%
3
 
2.7%
1
 
0.9%
1
 
0.9%
1
 
0.9%
1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
g 963
62.3%
l 253
 
16.4%
m 240
 
15.5%
k 41
 
2.7%
p 28
 
1.8%
s 11
 
0.7%
c 9
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
G 21
56.8%
K 7
 
18.9%
L 5
 
13.5%
E 2
 
5.4%
A 2
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 91
98.9%
* 1
 
1.1%
Other Symbol
ValueCountFrequency (%)
20
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7318
81.2%
Latin 1582
 
17.6%
Hangul 113
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3212
43.9%
1 1034
 
14.1%
5 645
 
8.8%
2 613
 
8.4%
6 501
 
6.8%
3 399
 
5.5%
8 258
 
3.5%
4 253
 
3.5%
9 149
 
2.0%
7 141
 
1.9%
Other values (4) 113
 
1.5%
Latin
ValueCountFrequency (%)
g 963
60.9%
l 253
 
16.0%
m 240
 
15.2%
k 41
 
2.6%
p 28
 
1.8%
G 21
 
1.3%
s 11
 
0.7%
c 9
 
0.6%
K 7
 
0.4%
L 5
 
0.3%
Other values (2) 4
 
0.3%
Hangul
ValueCountFrequency (%)
59
52.2%
24
21.2%
17
 
15.0%
3
 
2.7%
3
 
2.7%
3
 
2.7%
1
 
0.9%
1
 
0.9%
1
 
0.9%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8880
98.5%
Hangul 113
 
1.3%
CJK Compat 20
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3212
36.2%
1 1034
 
11.6%
g 963
 
10.8%
5 645
 
7.3%
2 613
 
6.9%
6 501
 
5.6%
3 399
 
4.5%
8 258
 
2.9%
4 253
 
2.8%
l 253
 
2.8%
Other values (15) 749
 
8.4%
Hangul
ValueCountFrequency (%)
59
52.2%
24
21.2%
17
 
15.0%
3
 
2.7%
3
 
2.7%
3
 
2.7%
1
 
0.9%
1
 
0.9%
1
 
0.9%
1
 
0.9%
CJK Compat
ValueCountFrequency (%)
20
100.0%

단위(정량)
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
g
1952 
<NA>
1817 
ML
312 
KG
 
183
LT
 
69

Length

Max length4
Median length2
Mean length2.3881837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowg
2nd row<NA>
3rd rowg
4th rowML
5th rowML

Common Values

ValueCountFrequency (%)
g 1952
45.0%
<NA> 1817
41.9%
ML 312
 
7.2%
KG 183
 
4.2%
LT 69
 
1.6%

Length

2024-05-11T03:32:34.228296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:34.583338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 1952
45.0%
na 1817
41.9%
ml 312
 
7.2%
kg 183
 
4.2%
lt 69
 
1.6%

수거량(자유)
Categorical

IMBALANCE 

Distinct48
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
4226 
1
 
37
4잔
 
7
3개
 
5
2
 
4
Other values (43)
 
54

Length

Max length9
Median length4
Mean length3.9868451
Min length1

Unique

Unique33 ?
Unique (%)0.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4226
97.5%
1 37
 
0.9%
4잔 7
 
0.2%
3개 5
 
0.1%
2 4
 
0.1%
1인분 3
 
0.1%
25개입 3 2
 
< 0.1%
1개 2
 
< 0.1%
4개 2
 
< 0.1%
50개입 3 2
 
< 0.1%
Other values (38) 43
 
1.0%

Length

2024-05-11T03:32:35.347115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4226
96.6%
1 43
 
1.0%
3 18
 
0.4%
13
 
0.3%
2 7
 
0.2%
4잔 7
 
0.2%
3개 5
 
0.1%
10개입 4
 
0.1%
470입 4
 
0.1%
1인분 3
 
0.1%
Other values (36) 45
 
1.0%

제조일자(일자)
Real number (ℝ)

MISSING  SKEWED 

Distinct205
Distinct (%)19.3%
Missing3269
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean20173869
Minimum20120210
Maximum22190709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:35.937080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120210
5-th percentile20121102
Q120160178
median20170912
Q320190409
95-th percentile20230824
Maximum22190709
Range2070499
Interquartile range (IQR)30231.5

Descriptive statistics

Standard deviation67119.886
Coefficient of variation (CV)0.0033270706
Kurtosis768.32146
Mean20173869
Median Absolute Deviation (MAD)19189
Skewness25.568816
Sum2.1464996 × 1010
Variance4.505079 × 109
MonotonicityNot monotonic
2024-05-11T03:32:36.444853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160526 48
 
1.1%
20151020 38
 
0.9%
20180919 37
 
0.9%
20180918 37
 
0.9%
20170912 32
 
0.7%
20180629 25
 
0.6%
20160101 24
 
0.6%
20190924 23
 
0.5%
20190902 21
 
0.5%
20170808 21
 
0.5%
Other values (195) 758
 
17.5%
(Missing) 3269
75.4%
ValueCountFrequency (%)
20120210 4
0.1%
20120222 3
 
0.1%
20120314 1
 
< 0.1%
20120423 2
 
< 0.1%
20120508 1
 
< 0.1%
20120511 3
 
0.1%
20120514 4
0.1%
20120516 5
0.1%
20120524 8
0.2%
20120712 8
0.2%
ValueCountFrequency (%)
22190709 1
 
< 0.1%
20240314 3
 
0.1%
20240307 1
 
< 0.1%
20240229 3
 
0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20231218 4
 
0.1%
20231109 1
 
< 0.1%
20231012 2
 
< 0.1%
20231011 11
0.3%

제조일자(롯트)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)90.7%
Missing4279
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean20122039
Minimum20110314
Maximum20140531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:36.962175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110314
5-th percentile20111026
Q120120348
median20120860
Q320121028
95-th percentile20134317
Maximum20140531
Range30217
Interquartile range (IQR)679.5

Descriptive statistics

Standard deviation7171.7881
Coefficient of variation (CV)0.00035641458
Kurtosis0.95756643
Mean20122039
Median Absolute Deviation (MAD)400
Skewness0.72511353
Sum1.0865901 × 109
Variance51434544
MonotonicityNot monotonic
2024-05-11T03:32:37.616350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
20120101 3
 
0.1%
20140531 2
 
< 0.1%
20120930 2
 
< 0.1%
20120928 2
 
< 0.1%
20111122 1
 
< 0.1%
20131026 1
 
< 0.1%
20120314 1
 
< 0.1%
20111023 1
 
< 0.1%
20111027 1
 
< 0.1%
20111101 1
 
< 0.1%
Other values (39) 39
 
0.9%
(Missing) 4279
98.8%
ValueCountFrequency (%)
20110314 1
 
< 0.1%
20110826 1
 
< 0.1%
20111023 1
 
< 0.1%
20111027 1
 
< 0.1%
20111101 1
 
< 0.1%
20111122 1
 
< 0.1%
20111207 1
 
< 0.1%
20111217 1
 
< 0.1%
20120101 3
0.1%
20120301 1
 
< 0.1%
ValueCountFrequency (%)
20140531 2
< 0.1%
20140430 1
< 0.1%
20131026 1
< 0.1%
20130914 1
< 0.1%
20130728 1
< 0.1%
20130720 1
< 0.1%
20130703 1
< 0.1%
20130505 1
< 0.1%
20130418 1
< 0.1%
20130317 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)37.5%
Missing4317
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean10082395
Minimum3
Maximum20190630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:38.095032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile23.25
Q1365
median10080586
Q320160808
95-th percentile20168264
Maximum20190630
Range20190627
Interquartile range (IQR)20160443

Descriptive statistics

Standard deviation10412792
Coefficient of variation (CV)1.0327697
Kurtosis-2.3076896
Mean10082395
Median Absolute Deviation (MAD)10080222
Skewness1.5891875 × 10-6
Sum1.6131832 × 108
Variance1.0842625 × 1014
MonotonicityNot monotonic
2024-05-11T03:32:38.580019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20160808 7
 
0.2%
365 5
 
0.1%
3 1
 
< 0.1%
180 1
 
< 0.1%
20190630 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 4317
99.6%
ValueCountFrequency (%)
3 1
 
< 0.1%
30 1
 
< 0.1%
180 1
 
< 0.1%
365 5
0.1%
20160808 7
0.2%
20190630 1
 
< 0.1%
ValueCountFrequency (%)
20190630 1
 
< 0.1%
20160808 7
0.2%
365 5
0.1%
180 1
 
< 0.1%
30 1
 
< 0.1%
3 1
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
실온
2163 
<NA>
1711 
냉장
278 
냉동
 
172
기타
 
9

Length

Max length4
Median length2
Mean length2.7897531
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row실온
2nd row<NA>
3rd row실온
4th row냉장
5th row냉장

Common Values

ValueCountFrequency (%)
실온 2163
49.9%
<NA> 1711
39.5%
냉장 278
 
6.4%
냉동 172
 
4.0%
기타 9
 
0.2%

Length

2024-05-11T03:32:39.148276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:39.574910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 2163
49.9%
na 1711
39.5%
냉장 278
 
6.4%
냉동 172
 
4.0%
기타 9
 
0.2%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

어린이기호식품유형
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

검사기관명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
1
2607 
<NA>
1700 
0
 
26

Length

Max length4
Median length1
Mean length2.1770136
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2607
60.2%
<NA> 1700
39.2%
0 26
 
0.6%

Length

2024-05-11T03:32:40.102338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:40.544945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2607
60.2%
na 1700
39.2%
0 26
 
0.6%

(구)제조사명
Categorical

IMBALANCE 

Distinct49
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
4228 
(주)비알코리아던킨도너츠
 
41
롯데제약(주)
 
7
한비식품
 
4
로망스제과
 
3
Other values (44)
 
50

Length

Max length13
Median length4
Mean length4.1038541
Min length2

Unique

Unique39 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4228
97.6%
(주)비알코리아던킨도너츠 41
 
0.9%
롯데제약(주) 7
 
0.2%
한비식품 4
 
0.1%
로망스제과 3
 
0.1%
맥필드베이커리 3
 
0.1%
케익하우스몽마 2
 
< 0.1%
육회지존 2
 
< 0.1%
왕가 2
 
< 0.1%
케익하우스 몽마 2
 
< 0.1%
Other values (39) 39
 
0.9%

Length

2024-05-11T03:32:41.094532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4228
97.5%
주)비알코리아던킨도너츠 41
 
0.9%
롯데제약(주 7
 
0.2%
한비식품 4
 
0.1%
로망스제과 3
 
0.1%
맥필드베이커리 3
 
0.1%
왕가 2
 
< 0.1%
몽마 2
 
< 0.1%
케익하우스 2
 
< 0.1%
육회지존 2
 
< 0.1%
Other values (41) 42
 
1.0%

내외국산
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
국내
3877 
국외
456 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내 3877
89.5%
국외 456
 
10.5%

Length

2024-05-11T03:32:41.514182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:42.031287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 3877
89.5%
국외 456
 
10.5%

국가명
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
4214 
미국
 
27
이탈리아
 
17
중국
 
13
일본
 
7
Other values (23)
 
55

Length

Max length5
Median length4
Mean length3.9681514
Min length2

Unique

Unique9 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4214
97.3%
미국 27
 
0.6%
이탈리아 17
 
0.4%
중국 13
 
0.3%
일본 7
 
0.2%
말레이지아 6
 
0.1%
독일 6
 
0.1%
인도네시아 4
 
0.1%
프랑스 4
 
0.1%
스페인 4
 
0.1%
Other values (18) 31
 
0.7%

Length

2024-05-11T03:32:42.541198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4214
97.3%
미국 27
 
0.6%
이탈리아 17
 
0.4%
중국 13
 
0.3%
일본 7
 
0.2%
말레이지아 6
 
0.1%
독일 6
 
0.1%
인도네시아 4
 
0.1%
프랑스 4
 
0.1%
스페인 4
 
0.1%
Other values (18) 31
 
0.7%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
1
2555 
<NA>
1337 
2
441 

Length

Max length4
Median length1
Mean length1.9256866
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2555
59.0%
<NA> 1337
30.9%
2 441
 
10.2%

Length

2024-05-11T03:32:43.078284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:43.563696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2555
59.0%
na 1337
30.9%
2 441
 
10.2%

검사의뢰일자
Real number (ℝ)

MISSING  SKEWED 

Distinct139
Distinct (%)6.0%
Missing2008
Missing (%)46.3%
Infinite0
Infinite (%)0.0%
Mean20140631
Minimum10911023
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:44.084099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10911023
5-th percentile20100224
Q120101129
median20110817
Q320201015
95-th percentile20230613
Maximum20240314
Range9329291
Interquartile range (IQR)99886

Descriptive statistics

Standard deviation197578.65
Coefficient of variation (CV)0.0098099532
Kurtosis2051.2756
Mean20140631
Median Absolute Deviation (MAD)10404
Skewness-43.888089
Sum4.6826967 × 1010
Variance3.9037323 × 1010
MonotonicityNot monotonic
2024-05-11T03:32:44.723336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210831 100
 
2.3%
20110420 89
 
2.1%
20111021 76
 
1.8%
20201015 75
 
1.7%
20101210 68
 
1.6%
20110817 68
 
1.6%
20110516 65
 
1.5%
20110608 64
 
1.5%
20100512 59
 
1.4%
20110708 58
 
1.3%
Other values (129) 1603
37.0%
(Missing) 2008
46.3%
ValueCountFrequency (%)
10911023 1
 
< 0.1%
20100107 2
 
< 0.1%
20100114 5
 
0.1%
20100127 45
1.0%
20100128 1
 
< 0.1%
20100217 22
0.5%
20100223 2
 
< 0.1%
20100224 47
1.1%
20100322 6
 
0.1%
20100324 50
1.2%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240307 1
 
< 0.1%
20240229 3
 
0.1%
20240226 1
 
< 0.1%
20240118 4
 
0.1%
20231219 4
 
0.1%
20231205 7
 
0.2%
20231123 35
0.8%
20231114 1
 
< 0.1%
20231113 5
 
0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct64
Distinct (%)8.3%
Missing3565
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean20188831
Minimum20100326
Maximum20220811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:45.479633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100326
5-th percentile20160610
Q120180713
median20200625
Q320210621
95-th percentile20220707
Maximum20220811
Range120485
Interquartile range (IQR)29908

Descriptive statistics

Standard deviation26471.377
Coefficient of variation (CV)0.0013111892
Kurtosis3.1451317
Mean20188831
Median Absolute Deviation (MAD)10397
Skewness-1.6299836
Sum1.5505022 × 1010
Variance7.0073382 × 108
MonotonicityNot monotonic
2024-05-11T03:32:46.227044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211022 85
 
2.0%
20201029 66
 
1.5%
20201204 45
 
1.0%
20160610 45
 
1.0%
20220707 44
 
1.0%
20211118 34
 
0.8%
20180809 32
 
0.7%
20210407 26
 
0.6%
20201216 25
 
0.6%
20180713 25
 
0.6%
Other values (54) 341
 
7.9%
(Missing) 3565
82.3%
ValueCountFrequency (%)
20100326 3
 
0.1%
20100513 1
 
< 0.1%
20100520 10
0.2%
20100526 6
0.1%
20100527 2
 
< 0.1%
20100621 1
 
< 0.1%
20100630 3
 
0.1%
20100701 4
 
0.1%
20100915 1
 
< 0.1%
20100927 3
 
0.1%
ValueCountFrequency (%)
20220811 1
 
< 0.1%
20220707 44
1.0%
20211118 34
 
0.8%
20211101 1
 
< 0.1%
20211022 85
2.0%
20210623 22
 
0.5%
20210622 4
 
0.1%
20210621 13
 
0.3%
20210430 1
 
< 0.1%
20210421 1
 
< 0.1%

판정구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
3565 
1
767 
2
 
1

Length

Max length4
Median length4
Mean length3.4682668
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 3565
82.3%
1 767
 
17.7%
2 1
 
< 0.1%

Length

2024-05-11T03:32:46.756511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:47.234540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3565
82.3%
1 767
 
17.7%
2 1
 
< 0.1%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

처리결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

교부번호
Real number (ℝ)

Distinct393
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0051298 × 1010
Minimum1.9690053 × 1010
Maximum2.0230072 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:47.751478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9690053 × 1010
5-th percentile1.9990053 × 1010
Q12.0000054 × 1010
median2.0040054 × 1010
Q32.0110054 × 1010
95-th percentile2.0170053 × 1010
Maximum2.0230072 × 1010
Range5.400187 × 108
Interquartile range (IQR)1.0999957 × 108

Descriptive statistics

Standard deviation67618771
Coefficient of variation (CV)0.003372289
Kurtosis0.9284464
Mean2.0051298 × 1010
Median Absolute Deviation (MAD)49999771
Skewness-0.062287836
Sum8.6882273 × 1013
Variance4.5722982 × 1015
MonotonicityNot monotonic
2024-05-11T03:32:48.239172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110053532 666
 
15.4%
20010053012 586
 
13.5%
19990053881 484
 
11.2%
20000053965 206
 
4.8%
20060053647 163
 
3.8%
19990053972 123
 
2.8%
20090053386 120
 
2.8%
20090053490 120
 
2.8%
20100053167 109
 
2.5%
20030053051 80
 
1.8%
Other values (383) 1676
38.7%
ValueCountFrequency (%)
19690053009 1
 
< 0.1%
19740053005 1
 
< 0.1%
19760053029 2
 
< 0.1%
19770053009 1
 
< 0.1%
19790053014 8
0.2%
19800053004 5
0.1%
19810053016 1
 
< 0.1%
19820053069 4
0.1%
19830053047 5
0.1%
19840053010 5
0.1%
ValueCountFrequency (%)
20230071705 1
 
< 0.1%
20230071402 2
 
< 0.1%
20230071210 2
 
< 0.1%
20230071071 2
 
< 0.1%
20220063821 2
 
< 0.1%
20220063403 2
 
< 0.1%
20220063297 44
1.0%
20220063269 30
0.7%
20220063023 1
 
< 0.1%
20210053906 1
 
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

소재지(도로명)
Text

MISSING 

Distinct270
Distinct (%)6.8%
Missing382
Missing (%)8.8%
Memory size34.0 KiB
2024-05-11T03:32:49.011458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length28.751962
Min length22

Characters and Unicode

Total characters113599
Distinct characters147
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

Unique109 ?
Unique (%)2.8%

Sample

1st row서울특별시 강북구 덕릉로26길 16, (수유동)
2nd row서울특별시 강북구 도봉로 45, (미아동)
3rd row서울특별시 강북구 도봉로97길 1, (수유동)
4th row서울특별시 강북구 도봉로97길 1, (수유동)
5th row서울특별시 강북구 도봉로97길 1, (수유동)
ValueCountFrequency (%)
서울특별시 3951
18.5%
강북구 3951
18.5%
18 1262
 
5.9%
수유동 1059
 
5.0%
미아동 975
 
4.6%
번동 963
 
4.5%
삼양로 807
 
3.8%
247 678
 
3.2%
오현로32길 569
 
2.7%
도봉로67길 557
 
2.6%
Other values (367) 6584
30.8%
2024-05-11T03:32:50.390728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17412
 
15.3%
, 5091
 
4.5%
) 4659
 
4.1%
( 4659
 
4.1%
4153
 
3.7%
4126
 
3.6%
4046
 
3.6%
1 4036
 
3.6%
4029
 
3.5%
3954
 
3.5%
Other values (137) 57434
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64167
56.5%
Space Separator 17412
 
15.3%
Decimal Number 17229
 
15.2%
Other Punctuation 5104
 
4.5%
Close Punctuation 4659
 
4.1%
Open Punctuation 4659
 
4.1%
Dash Punctuation 259
 
0.2%
Uppercase Letter 80
 
0.1%
Math Symbol 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4153
 
6.5%
4126
 
6.4%
4046
 
6.3%
4029
 
6.3%
3954
 
6.2%
3954
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
Other values (115) 24101
37.6%
Decimal Number
ValueCountFrequency (%)
1 4036
23.4%
2 3195
18.5%
7 2281
13.2%
8 1696
9.8%
3 1643
9.5%
6 1213
 
7.0%
4 1162
 
6.7%
5 901
 
5.2%
0 679
 
3.9%
9 423
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
B 72
90.0%
F 5
 
6.2%
P 1
 
1.2%
T 1
 
1.2%
A 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 5091
99.7%
. 13
 
0.3%
Space Separator
ValueCountFrequency (%)
17412
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4659
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4659
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 259
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64167
56.5%
Common 49352
43.4%
Latin 80
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4153
 
6.5%
4126
 
6.4%
4046
 
6.3%
4029
 
6.3%
3954
 
6.2%
3954
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
Other values (115) 24101
37.6%
Common
ValueCountFrequency (%)
17412
35.3%
, 5091
 
10.3%
) 4659
 
9.4%
( 4659
 
9.4%
1 4036
 
8.2%
2 3195
 
6.5%
7 2281
 
4.6%
8 1696
 
3.4%
3 1643
 
3.3%
6 1213
 
2.5%
Other values (7) 3467
 
7.0%
Latin
ValueCountFrequency (%)
B 72
90.0%
F 5
 
6.2%
P 1
 
1.2%
T 1
 
1.2%
A 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64167
56.5%
ASCII 49432
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17412
35.2%
, 5091
 
10.3%
) 4659
 
9.4%
( 4659
 
9.4%
1 4036
 
8.2%
2 3195
 
6.5%
7 2281
 
4.6%
8 1696
 
3.4%
3 1643
 
3.3%
6 1213
 
2.5%
Other values (12) 3547
 
7.2%
Hangul
ValueCountFrequency (%)
4153
 
6.5%
4126
 
6.4%
4046
 
6.3%
4029
 
6.3%
3954
 
6.2%
3954
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
3951
 
6.2%
Other values (115) 24101
37.6%

소재지(지번)
Text

MISSING 

Distinct377
Distinct (%)8.8%
Missing66
Missing (%)1.5%
Memory size34.0 KiB
2024-05-11T03:32:51.217918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length43
Mean length27.742911
Min length21

Characters and Unicode

Total characters118379
Distinct characters153
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

Unique185 ?
Unique (%)4.3%

Sample

1st row서울특별시 강북구 수유동 104번지 2호
2nd row서울특별시 강북구 미아동 60번지 16호
3rd row서울특별시 강북구 미아동 60번지 16호
4th row서울특별시 강북구 수유동 173번지 14호
5th row서울특별시 강북구 수유동 173번지 14호
ValueCountFrequency (%)
서울특별시 4267
18.5%
강북구 4267
18.5%
미아동 1765
 
7.6%
수유동 1265
 
5.5%
번동 1158
 
5.0%
1호 875
 
3.8%
5호 716
 
3.1%
1359번지 678
 
2.9%
54번지 573
 
2.5%
161번지 565
 
2.4%
Other values (467) 6943
30.1%
2024-05-11T03:32:52.660583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30138
25.5%
5476
 
4.6%
1 5245
 
4.4%
4873
 
4.1%
4523
 
3.8%
4433
 
3.7%
4356
 
3.7%
4280
 
3.6%
4271
 
3.6%
4270
 
3.6%
Other values (143) 46514
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66157
55.9%
Space Separator 30138
25.5%
Decimal Number 19995
 
16.9%
Close Punctuation 942
 
0.8%
Open Punctuation 942
 
0.8%
Other Punctuation 116
 
0.1%
Dash Punctuation 56
 
< 0.1%
Uppercase Letter 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5476
 
8.3%
4873
 
7.4%
4523
 
6.8%
4433
 
6.7%
4356
 
6.6%
4280
 
6.5%
4271
 
6.5%
4270
 
6.5%
4269
 
6.5%
4267
 
6.4%
Other values (121) 21139
32.0%
Decimal Number
ValueCountFrequency (%)
1 5245
26.2%
5 3194
16.0%
3 2501
12.5%
2 1963
 
9.8%
4 1819
 
9.1%
6 1434
 
7.2%
9 1215
 
6.1%
7 1088
 
5.4%
0 778
 
3.9%
8 758
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
36.4%
S 7
21.2%
K 7
21.2%
F 5
15.2%
A 2
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 84
72.4%
. 23
 
19.8%
@ 9
 
7.8%
Space Separator
ValueCountFrequency (%)
30138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 942
100.0%
Open Punctuation
ValueCountFrequency (%)
( 942
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66157
55.9%
Common 52189
44.1%
Latin 33
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5476
 
8.3%
4873
 
7.4%
4523
 
6.8%
4433
 
6.7%
4356
 
6.6%
4280
 
6.5%
4271
 
6.5%
4270
 
6.5%
4269
 
6.5%
4267
 
6.4%
Other values (121) 21139
32.0%
Common
ValueCountFrequency (%)
30138
57.7%
1 5245
 
10.1%
5 3194
 
6.1%
3 2501
 
4.8%
2 1963
 
3.8%
4 1819
 
3.5%
6 1434
 
2.7%
9 1215
 
2.3%
7 1088
 
2.1%
) 942
 
1.8%
Other values (7) 2650
 
5.1%
Latin
ValueCountFrequency (%)
B 12
36.4%
S 7
21.2%
K 7
21.2%
F 5
15.2%
A 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66157
55.9%
ASCII 52222
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30138
57.7%
1 5245
 
10.0%
5 3194
 
6.1%
3 2501
 
4.8%
2 1963
 
3.8%
4 1819
 
3.5%
6 1434
 
2.7%
9 1215
 
2.3%
7 1088
 
2.1%
) 942
 
1.8%
Other values (12) 2683
 
5.1%
Hangul
ValueCountFrequency (%)
5476
 
8.3%
4873
 
7.4%
4523
 
6.8%
4433
 
6.7%
4356
 
6.6%
4280
 
6.5%
4271
 
6.5%
4270
 
6.5%
4269
 
6.5%
4267
 
6.4%
Other values (121) 21139
32.0%

업소전화번호
Text

MISSING 

Distinct294
Distinct (%)7.4%
Missing345
Missing (%)8.0%
Memory size34.0 KiB
2024-05-11T03:32:53.451719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.666249
Min length2

Characters and Unicode

Total characters42537
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

Unique154 ?
Unique (%)3.9%

Sample

1st row02 9804141
2nd row02 9886701
3rd row02 9886701
4th row02 998 5069
5th row02 998 5069
ValueCountFrequency (%)
02 3757
43.6%
9859500 586
 
6.8%
9815601 412
 
4.8%
944 369
 
4.3%
1520 369
 
4.3%
22482500 301
 
3.5%
9042872 206
 
2.4%
9442500 172
 
2.0%
980 167
 
1.9%
69338701 139
 
1.6%
Other values (314) 2137
24.8%
2024-05-11T03:32:55.058965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9054
21.3%
2 6470
15.2%
6070
14.3%
9 5030
11.8%
8 3521
 
8.3%
5 3345
 
7.9%
4 2440
 
5.7%
1 2368
 
5.6%
7 1564
 
3.7%
6 1486
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36467
85.7%
Space Separator 6070
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9054
24.8%
2 6470
17.7%
9 5030
13.8%
8 3521
 
9.7%
5 3345
 
9.2%
4 2440
 
6.7%
1 2368
 
6.5%
7 1564
 
4.3%
6 1486
 
4.1%
3 1189
 
3.3%
Space Separator
ValueCountFrequency (%)
6070
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42537
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9054
21.3%
2 6470
15.2%
6070
14.3%
9 5030
11.8%
8 3521
 
8.3%
5 3345
 
7.9%
4 2440
 
5.7%
1 2368
 
5.6%
7 1564
 
3.7%
6 1486
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42537
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9054
21.3%
2 6470
15.2%
6070
14.3%
9 5030
11.8%
8 3521
 
8.3%
5 3345
 
7.9%
4 2440
 
5.7%
1 2368
 
5.6%
7 1564
 
3.7%
6 1486
 
3.5%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
위생점검(전체)
1720 
수거
1364 
<NA>
1208 
위생점검(부분)
 
41

Length

Max length8
Median length4
Mean length4.9960766
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row수거
3rd row위생점검(전체)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
위생점검(전체) 1720
39.7%
수거 1364
31.5%
<NA> 1208
27.9%
위생점검(부분) 41
 
0.9%

Length

2024-05-11T03:32:55.959496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:56.393955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위생점검(전체 1720
39.7%
수거 1364
31.5%
na 1208
27.9%
위생점검(부분 41
 
0.9%

점검일자
Real number (ℝ)

Distinct243
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20145179
Minimum20090122
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:32:56.793963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090122
5-th percentile20090707
Q120110225
median20140320
Q320180917
95-th percentile20220622
Maximum20240314
Range150192
Interquartile range (IQR)70692

Descriptive statistics

Standard deviation41828.61
Coefficient of variation (CV)0.0020763583
Kurtosis-1.1187315
Mean20145179
Median Absolute Deviation (MAD)39111
Skewness0.39054096
Sum8.7289059 × 1010
Variance1.7496326 × 109
MonotonicityNot monotonic
2024-05-11T03:32:57.475087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150126 177
 
4.1%
20180918 115
 
2.7%
20210929 85
 
2.0%
20160201 79
 
1.8%
20110328 73
 
1.7%
20110419 72
 
1.7%
20130614 69
 
1.6%
20110816 68
 
1.6%
20101209 68
 
1.6%
20110516 65
 
1.5%
Other values (233) 3462
79.9%
ValueCountFrequency (%)
20090122 50
1.2%
20090209 50
1.2%
20090211 4
 
0.1%
20090223 18
 
0.4%
20090422 31
0.7%
20090514 20
 
0.5%
20090521 5
 
0.1%
20090707 44
1.0%
20090720 2
 
< 0.1%
20090827 34
0.8%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240307 1
 
< 0.1%
20240229 3
 
0.1%
20240226 1
 
< 0.1%
20240118 3
 
0.1%
20240112 1
 
< 0.1%
20231218 4
 
0.1%
20231205 7
 
0.2%
20231121 35
0.8%
20231113 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
수시
1467 
기타
1417 
<NA>
1208 
합동
213 
일제
 
28

Length

Max length4
Median length2
Mean length2.5575814
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row기타
3rd row기타
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
수시 1467
33.9%
기타 1417
32.7%
<NA> 1208
27.9%
합동 213
 
4.9%
일제 28
 
0.6%

Length

2024-05-11T03:32:58.228416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:58.701466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 1467
33.9%
기타 1417
32.7%
na 1208
27.9%
합동 213
 
4.9%
일제 28
 
0.6%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
1
3087 
<NA>
1208 
2
 
38

Length

Max length4
Median length1
Mean length1.836372
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 3087
71.2%
<NA> 1208
 
27.9%
2 38
 
0.9%

Length

2024-05-11T03:32:59.156370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:32:59.712257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3087
71.2%
na 1208
 
27.9%
2 38
 
0.9%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct49
Distinct (%)90.7%
Missing4279
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean20122039
Minimum20110314
Maximum20140531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.2 KiB
2024-05-11T03:33:00.263190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110314
5-th percentile20111026
Q120120348
median20120860
Q320121028
95-th percentile20134317
Maximum20140531
Range30217
Interquartile range (IQR)679.5

Descriptive statistics

Standard deviation7171.7881
Coefficient of variation (CV)0.00035641458
Kurtosis0.95756643
Mean20122039
Median Absolute Deviation (MAD)400
Skewness0.72511353
Sum1.0865901 × 109
Variance51434544
MonotonicityNot monotonic
2024-05-11T03:33:00.917696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
20120101 3
 
0.1%
20140531 2
 
< 0.1%
20120930 2
 
< 0.1%
20120928 2
 
< 0.1%
20111122 1
 
< 0.1%
20131026 1
 
< 0.1%
20120314 1
 
< 0.1%
20111023 1
 
< 0.1%
20111027 1
 
< 0.1%
20111101 1
 
< 0.1%
Other values (39) 39
 
0.9%
(Missing) 4279
98.8%
ValueCountFrequency (%)
20110314 1
 
< 0.1%
20110826 1
 
< 0.1%
20111023 1
 
< 0.1%
20111027 1
 
< 0.1%
20111101 1
 
< 0.1%
20111122 1
 
< 0.1%
20111207 1
 
< 0.1%
20111217 1
 
< 0.1%
20120101 3
0.1%
20120301 1
 
< 0.1%
ValueCountFrequency (%)
20140531 2
< 0.1%
20140430 1
< 0.1%
20131026 1
< 0.1%
20130914 1
< 0.1%
20130728 1
< 0.1%
20130720 1
< 0.1%
20130703 1
< 0.1%
20130505 1
< 0.1%
20130418 1
< 0.1%
20130317 1
< 0.1%

(구)제조회사주소
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.0 KiB
<NA>
4322 
경기도 화성시 향남읍 상신리 904-8
 
7
강북구 미아동 1359 롯데마트삼양점
 
4

Length

Max length21
Median length4
Mean length4.042234
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4322
99.7%
경기도 화성시 향남읍 상신리 904-8 7
 
0.2%
강북구 미아동 1359 롯데마트삼양점 4
 
0.1%

Length

2024-05-11T03:33:01.497349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:33:01.878028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4322
98.8%
경기도 7
 
0.2%
화성시 7
 
0.2%
향남읍 7
 
0.2%
상신리 7
 
0.2%
904-8 7
 
0.2%
강북구 4
 
0.1%
미아동 4
 
0.1%
1359 4
 
0.1%
롯데마트삼양점 4
 
0.1%

부적합항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4333
Missing (%)100.0%
Memory size38.2 KiB

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03080000101일반음식점<NA><NA><NA>일상수거109-5-1검사용서울왕족발600000000식품접객업접객업소조리식품등직화불족발<NA><NA><NA>201305011600g<NA>20130501<NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19740053005<NA><NA><NA><NA><NA>서울특별시 강북구 덕릉로26길 16, (수유동)서울특별시 강북구 수유동 104번지 2호02 9804141<NA>20130807<NA><NA><NA><NA><NA><NA><NA>
13080000101일반음식점<NA><NA><NA><NA>2010-6-11<NA>장가네세수대냉면<NA><NA>육수냉면육수<NA><NA>201006211000ml<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20100621<NA><NA><NA><NA><NA><NA><NA><NA>19760053029<NA><NA><NA><NA><NA><NA>서울특별시 강북구 미아동 60번지 16호02 9886701수거20100621기타<NA>1<NA><NA><NA><NA>
23080000101일반음식점<NA><NA><NA><NA>109-6-4검사용수봉냉면C0121020000000소스류소스류[외식]물냉면육수<NA><NA><NA>201706281600g<NA>20170628<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120170728201707121<NA><NA><NA><NA><NA><NA>19760053029<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 45, (미아동)서울특별시 강북구 미아동 60번지 16호02 9886701위생점검(전체)20170628기타<NA>1<NA><NA><NA><NA>
33080000101일반음식점<NA><NA><NA>일상수거109-05-47검사용똘끼차이나G0100000100000조리식품 등조리식품 등새우볶음밥<NA><NA><NA>201906131200ML<NA>20190527<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120190527201906101<NA><NA><NA><NA><NA><NA>19800053004<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로97길 1, (수유동)서울특별시 강북구 수유동 173번지 14호02 998 5069<NA>20190527<NA><NA><NA><NA><NA><NA><NA>
43080000101일반음식점<NA><NA><NA>일상수거109-05-48검사용똘끼차이나G0100000100000조리식품 등조리식품 등삼선볶음밥<NA><NA><NA>201906131200ML<NA>20190527<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120190527201906101<NA><NA><NA><NA><NA><NA>19800053004<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로97길 1, (수유동)서울특별시 강북구 수유동 173번지 14호02 998 5069<NA>20190527<NA><NA><NA><NA><NA><NA><NA>
53080000101일반음식점<NA><NA><NA>일상수거109-05-49검사용똘끼차이나G0100000100000조리식품 등조리식품 등잡채밥<NA><NA><NA>201906131200ML<NA>20190527<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120190527201906101<NA><NA><NA><NA><NA><NA>19800053004<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로97길 1, (수유동)서울특별시 강북구 수유동 173번지 14호02 998 5069<NA>20190527<NA><NA><NA><NA><NA><NA><NA>
63080000101일반음식점<NA><NA><NA>일상수거109-05-50검사용똘끼차이나G0100000100000조리식품 등조리식품 등짜장<NA><NA><NA>201906131200ML<NA>20190527<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120190527201906101<NA><NA><NA><NA><NA><NA>19800053004<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로97길 1, (수유동)서울특별시 강북구 수유동 173번지 14호02 998 5069<NA>20190527<NA><NA><NA><NA><NA><NA><NA>
73080000101일반음식점<NA><NA><NA>일상수거109-05-51검사용똘끼차이나G0100000100000조리식품 등조리식품 등짬뽕<NA><NA><NA>201906131200ML<NA>20190527<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120190527201906101<NA><NA><NA><NA><NA><NA>19800053004<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로97길 1, (수유동)서울특별시 강북구 수유동 173번지 14호02 998 5069<NA>20190527<NA><NA><NA><NA><NA><NA><NA>
83080000101일반음식점<NA><NA><NA><NA>109-10-001<NA>군산해물탕<NA><NA>해물찜해물찜<NA><NA>201110041600g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>220111004<NA><NA><NA><NA><NA><NA><NA><NA>19840053016<NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 191번지 77호02 9904176수거20111004기타<NA>1<NA><NA><NA><NA>
93080000101일반음식점<NA><NA><NA><NA>109-09-101검사용본도시락G0100000100000조리식품 등조리식품 등돼지고기묵은지<NA><NA><NA>201909241600g<NA>20190924<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120190924201910081<NA><NA><NA><NA><NA><NA>19840053010<NA><NA><NA><NA><NA>서울특별시 강북구 한천로 1023, (번동,(한천로 1025)(지상1층))서울특별시 강북구 번동 418번지 2호 (한천로 1025)(지상1층)02 9940470수거20190924수시<NA>1<NA><NA><NA><NA>
시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
43233080000134건강기능식품일반판매업<NA><NA><NA><NA>109-6-2검사용롯데쇼핑(주) 롯데마트 삼양점E0200500000000스피루리나스피루리나스피루리나<NA><NA><NA>20170418672g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20110053540<NA><NA><NA><NA><NA>서울특별시 강북구 삼양로 247, (미아동,지하1층)서울특별시 강북구 미아동 1359번지 지하1층02 944 1520위생점검(전체)20170418기타<NA>1<NA><NA><NA><NA>
43243080000134건강기능식품일반판매업<NA><NA><NA><NA>109-4-6-3검사용롯데쇼핑(주) 롯데마트 삼양점E0200800000000프로폴리스추출물프로폴리스추출물로열골드 비타민ADE<NA><NA><NA>20170418672g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20110053540<NA><NA><NA><NA><NA>서울특별시 강북구 삼양로 247, (미아동,지하1층)서울특별시 강북구 미아동 1359번지 지하1층02 944 1520위생점검(전체)20170418기타<NA>1<NA><NA><NA><NA>
43253080000134건강기능식품일반판매업<NA><NA><NA><NA>109-4-7-1검사용롯데쇼핑(주) 롯데마트 삼양점E0200200000000홍삼홍삼황작홍삼농축액<NA><NA><NA>201704182240g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20110053540<NA><NA><NA><NA><NA>서울특별시 강북구 삼양로 247, (미아동,지하1층)서울특별시 강북구 미아동 1359번지 지하1층02 944 1520위생점검(전체)20170418기타<NA>1<NA><NA><NA><NA>
43263080000134건강기능식품일반판매업<NA><NA><NA><NA>109-4-7-2검사용롯데쇼핑(주) 롯데마트 삼양점E0200200000000홍삼홍삼황작홍삼캡슐<NA><NA><NA>20170418336g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20110053540<NA><NA><NA><NA><NA>서울특별시 강북구 삼양로 247, (미아동,지하1층)서울특별시 강북구 미아동 1359번지 지하1층02 944 1520위생점검(전체)20170418기타<NA>1<NA><NA><NA><NA>
43273080000134건강기능식품일반판매업<NA><NA><NA><NA>5-1검사용천호식품 롯데미아점X0100026100000일반원료일반원료관절 건강에 도움이 될 수 있는 청춘관절<NA><NA><NA>20160929120500ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20160053389<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 62, (미아동, 롯데백화점 미아점 지하1층)서울특별시 강북구 미아동 70번지 6호 롯데백화점 미아점 지하1층<NA><NA>20160929<NA><NA><NA><NA><NA><NA><NA>
43283080000134건강기능식품일반판매업<NA><NA><NA><NA>5-2검사용천호식품 롯데미아점X0100026100000일반원료일반원료프로폴리스3플러스<NA><NA><NA>20160929120350ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20160053389<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 62, (미아동, 롯데백화점 미아점 지하1층)서울특별시 강북구 미아동 70번지 6호 롯데백화점 미아점 지하1층<NA><NA>20160929<NA><NA><NA><NA><NA><NA><NA>
43293080000134건강기능식품일반판매업<NA><NA><NA><NA>6-1검사용천호식품 롯데미아점C0118050000000인삼.홍삼음료인삼.홍삼음료6년근홍삼진액<NA><NA><NA>201609293300ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20160053389<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 62, (미아동, 롯데백화점 미아점 지하1층)서울특별시 강북구 미아동 70번지 6호 롯데백화점 미아점 지하1층<NA><NA>20160929<NA><NA><NA><NA><NA><NA><NA>
43303080000134건강기능식품일반판매업<NA><NA><NA><NA>109-6-2검사용천호식품 롯데미아점X0100026100000일반원료일반원료우먼솔루션<NA><NA><NA>201609293075g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20160053389<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 62, (미아동, 롯데백화점 미아점 지하1층)서울특별시 강북구 미아동 70번지 6호 롯데백화점 미아점 지하1층<NA><NA>20160929<NA><NA><NA><NA><NA><NA><NA>
43313080000134건강기능식품일반판매업<NA><NA><NA><NA>109-8-8검사용백세건강지킴이E0205100000000프로바이오틱스프로바이오틱스락토생유산균17플러스<NA><NA><NA>202108302250g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120210831<NA><NA><NA><NA><NA><NA><NA><NA>20190053674<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로67길 18, 수유시장 15호 (수유동)서울특별시 강북구 수유동 54번지 5호 수유시장-15<NA>위생점검(전체)20210830기타<NA>1<NA><NA><NA><NA>
43323080000134건강기능식품일반판매업<NA><NA><NA><NA>109-4-3검사용팔레오(롯데-미아점)E0100100000000비타민 A비타민 A슈퍼포뮬러 멀티비타민미네랄21<NA><NA><NA>20230412460g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230413<NA><NA><NA><NA><NA><NA><NA><NA>20220063023<NA><NA><NA><NA><NA>서울특별시 강북구 도봉로 62, 롯데백화점 미아점 지하2층 (미아동)서울특별시 강북구 미아동 70번지 6호 롯데백화점 미아점<NA>수거20230412수시<NA>1<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)유통기한(일자)유통기한(제조일기준)보관상태코드검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소# duplicates
03080000101일반음식점<NA><NA><NA>109-9-15<NA>보나쿠아829000000기타식품류즉석조리식품도미<NA><NA><NA>20100920200g<NA><NA><NA><NA><NA><NA>1<NA>국내<NA>220100920<NA><NA>20070053248<NA>서울특별시 강북구 수유동 229번지 49호 (구청길 31)(지상4층)<NA><NA>20110125<NA><NA><NA><NA>2
13080000114기타식품판매업<NA><NA>일상수거109-6-27검사용(주)삼우마트C01000000<NA>탄산음료비타민워터<NA><NA>오케이에프201506301500ML<NA><NA><NA><NA>실온<NA><NA>국내<NA>1<NA><NA><NA>20000053965서울특별시 강북구 노해로17길 21, (수유동)<NA>02 9042872위생점검(전체)20150331수시1<NA><NA>2
23080000114기타식품판매업<NA><NA><NA><NA><NA>플러스마트899000000축산물가공품가공유류목장의신선함이살아있는우유<NA><NA><NA>200907203<NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA>20010053696서울특별시 강북구 솔샘로 233, (미아동)서울특별시 강북구 미아동 701번지 3호02 9825949수거20090720수시1<NA><NA>2