Overview

Dataset statistics

Number of variables61
Number of observations6984
Missing cells136549
Missing cells (%)32.1%
Duplicate rows22
Duplicate rows (%)0.3%
Total size in memory3.4 MiB
Average record size in memory514.0 B

Variable types

Categorical26
Numeric12
Unsupported7
Text16

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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-10377/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 22 (0.3%) duplicate rowsDuplicates
업종명 is highly imbalanced (66.7%)Imbalance
계획구분코드 is highly imbalanced (52.4%)Imbalance
수거계획 is highly imbalanced (73.7%)Imbalance
원료명 is highly imbalanced (96.6%)Imbalance
수거량(자유) is highly imbalanced (95.1%)Imbalance
제조일자(롯트) is highly imbalanced (93.1%)Imbalance
어린이기호식품유형 is highly imbalanced (97.6%)Imbalance
검사기관명 is highly imbalanced (60.1%)Imbalance
국가명 is highly imbalanced (89.3%)Imbalance
처리결과 is highly imbalanced (93.5%)Imbalance
수거품처리 is highly imbalanced (98.4%)Imbalance
폐기량(kg) is highly imbalanced (97.2%)Imbalance
폐기금액(원) is highly imbalanced (97.7%)Imbalance
폐기장소 is highly imbalanced (98.6%)Imbalance
폐기방법 is highly imbalanced (98.7%)Imbalance
점검결과코드 is highly imbalanced (66.1%)Imbalance
계획구분명 has 6984 (100.0%) missing valuesMissing
수거증번호 has 1458 (20.9%) missing valuesMissing
식품군 has 850 (12.2%) missing valuesMissing
품목명 has 198 (2.8%) missing valuesMissing
음식물명 has 6969 (99.8%) missing valuesMissing
생산업소 has 6216 (89.0%) missing valuesMissing
수거량(정량) has 160 (2.3%) missing valuesMissing
제품규격(정량) has 1618 (23.2%) missing valuesMissing
제조일자(일자) has 5872 (84.1%) missing valuesMissing
유통기한(일자) has 6780 (97.1%) missing valuesMissing
유통기한(제조일기준) has 6946 (99.5%) missing valuesMissing
바코드번호 has 6984 (100.0%) missing valuesMissing
(구)제조사명 has 6180 (88.5%) missing valuesMissing
검사의뢰일자 has 2897 (41.5%) missing valuesMissing
결과회보일자 has 3445 (49.3%) missing valuesMissing
처리구분 has 6984 (100.0%) missing valuesMissing
수거검사구분코드 has 6984 (100.0%) missing valuesMissing
단속지역구분코드 has 6984 (100.0%) missing valuesMissing
수거장소구분코드 has 6984 (100.0%) missing valuesMissing
폐기일자 has 6962 (99.7%) missing valuesMissing
소재지(도로명) has 2931 (42.0%) missing valuesMissing
소재지(지번) has 255 (3.7%) missing valuesMissing
업소전화번호 has 515 (7.4%) missing valuesMissing
점검내용 has 6984 (100.0%) missing valuesMissing
(구)제조유통기한 has 6780 (97.1%) missing valuesMissing
(구)제조회사주소 has 6654 (95.3%) missing valuesMissing
부적합항목 has 6979 (99.9%) missing valuesMissing
기준치부적합내용 has 6981 (> 99.9%) missing valuesMissing
계획구분명 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
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
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:43:38.431981
Analysis finished2024-05-11 05:43:41.981068
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
3050000
6984 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 6984
100.0%

Length

2024-05-11T14:43:42.063847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:42.201103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 6984
100.0%

업종코드
Real number (ℝ)

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.27033
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:42.313017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1114
median114
Q3114
95-th percentile114
Maximum134
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.2062264
Coefficient of variation (CV)0.037465164
Kurtosis3.5276082
Mean112.27033
Median Absolute Deviation (MAD)0
Skewness-1.2029348
Sum784096
Variance17.69234
MonotonicityIncreasing
2024-05-11T14:43:42.454332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
114 5595
80.1%
101 445
 
6.4%
105 429
 
6.1%
107 159
 
2.3%
104 100
 
1.4%
112 85
 
1.2%
106 79
 
1.1%
109 33
 
0.5%
134 22
 
0.3%
121 19
 
0.3%
Other values (3) 18
 
0.3%
ValueCountFrequency (%)
101 445
 
6.4%
104 100
 
1.4%
105 429
 
6.1%
106 79
 
1.1%
107 159
 
2.3%
109 33
 
0.5%
111 4
 
0.1%
112 85
 
1.2%
113 3
 
< 0.1%
114 5595
80.1%
ValueCountFrequency (%)
134 22
 
0.3%
122 11
 
0.2%
121 19
 
0.3%
114 5595
80.1%
113 3
 
< 0.1%
112 85
 
1.2%
111 4
 
0.1%
109 33
 
0.5%
107 159
 
2.3%
106 79
 
1.1%

업종명
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
기타식품판매업
5595 
일반음식점
 
445
집단급식소
 
429
즉석판매제조가공업
 
159
휴게음식점
 
100
Other values (8)
 
256

Length

Max length11
Median length7
Mean length6.7933849
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 5595
80.1%
일반음식점 445
 
6.4%
집단급식소 429
 
6.1%
즉석판매제조가공업 159
 
2.3%
휴게음식점 100
 
1.4%
식품자동판매기영업 85
 
1.2%
식품제조가공업 79
 
1.1%
식품소분업 33
 
0.5%
건강기능식품일반판매업 22
 
0.3%
제과점영업 19
 
0.3%
Other values (3) 18
 
0.3%

Length

2024-05-11T14:43:42.619642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 5595
80.1%
일반음식점 445
 
6.4%
집단급식소 429
 
6.1%
즉석판매제조가공업 159
 
2.3%
휴게음식점 100
 
1.4%
식품자동판매기영업 85
 
1.2%
식품제조가공업 79
 
1.1%
식품소분업 33
 
0.5%
건강기능식품일반판매업 22
 
0.3%
제과점영업 19
 
0.3%
Other values (3) 18
 
0.3%

계획구분코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
3740 
999
3001 
2
 
129
3
 
57
8
 
49

Length

Max length4
Median length4
Mean length3.4659221
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row999

Common Values

ValueCountFrequency (%)
<NA> 3740
53.6%
999 3001
43.0%
2 129
 
1.8%
3 57
 
0.8%
8 49
 
0.7%
1 8
 
0.1%

Length

2024-05-11T14:43:42.819892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:42.988327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3740
53.6%
999 3001
43.0%
2 129
 
1.8%
3 57
 
0.8%
8 49
 
0.7%
1 8
 
0.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB
Distinct32
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
3740 
2018년도 일상 지도점검(식품안전팀)
480 
공중위생업소 지도점검
395 
2013년도 식품안전관리시행계획
391 
2015년도 식품안전관리계획
377 
Other values (27)
1601 

Length

Max length52
Median length4
Mean length9.939433
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row2018년 정육식당 등 한우고기 취급 전문 음식점에 대한 원산지 표시 및 위생지도 점검 계획

Common Values

ValueCountFrequency (%)
<NA> 3740
53.6%
2018년도 일상 지도점검(식품안전팀) 480
 
6.9%
공중위생업소 지도점검 395
 
5.7%
2013년도 식품안전관리시행계획 391
 
5.6%
2015년도 식품안전관리계획 377
 
5.4%
2016년 동대문구 식품안전관리계획 328
 
4.7%
2017년 일상 지도점검 306
 
4.4%
2012년 시설조사 및 위생점검 204
 
2.9%
기타 일상단속(식품안전팀) 201
 
2.9%
기타 일상단속(식품위생팀) 183
 
2.6%
Other values (22) 379
 
5.4%

Length

2024-05-11T14:43:43.173042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3740
28.7%
일상 786
 
6.0%
식품안전관리계획 730
 
5.6%
지도점검 725
 
5.6%
2018년도 500
 
3.8%
지도점검(식품안전팀 480
 
3.7%
공중위생업소 395
 
3.0%
식품안전관리시행계획 391
 
3.0%
2013년도 391
 
3.0%
기타 384
 
2.9%
Other values (73) 4495
34.5%

수거계획
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
5973 
여름철 성수식품 수거검사 계획
 
353
가공식품 수거검사
 
225
2015 가공식품안전관리계획
 
87
2016년 일상단속
 
86
Other values (9)
 
260

Length

Max length25
Median length4
Mean length5.5372279
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row다소비 식품 수거 검사
4th row다소비 식품 수거 검사
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5973
85.5%
여름철 성수식품 수거검사 계획 353
 
5.1%
가공식품 수거검사 225
 
3.2%
2015 가공식품안전관리계획 87
 
1.2%
2016년 일상단속 86
 
1.2%
다소비 식품 수거 검사 80
 
1.1%
농수산물 원산지표시 관련 국내산 확인 수거 54
 
0.8%
2015 음식점 한우 유전자 수거검사 47
 
0.7%
기타 민원신고 등 일상 수거검사(식품위생팀) 33
 
0.5%
2018년도 일상 수거검사 계획(식품안전팀) 16
 
0.2%
Other values (4) 30
 
0.4%

Length

2024-05-11T14:43:43.370327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5973
63.6%
수거검사 647
 
6.9%
성수식품 353
 
3.8%
계획 353
 
3.8%
여름철 353
 
3.8%
가공식품 226
 
2.4%
수거 135
 
1.4%
2015 134
 
1.4%
가공식품안전관리계획 87
 
0.9%
2016년 87
 
0.9%
Other values (27) 1050
 
11.2%

수거증번호
Text

MISSING 

Distinct2836
Distinct (%)51.3%
Missing1458
Missing (%)20.9%
Memory size54.7 KiB
2024-05-11T14:43:43.822478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.4390156
Min length1

Characters and Unicode

Total characters46634
Distinct characters60
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1842 ?
Unique (%)33.3%

Sample

1st row2011-식-13
2nd row동대문-음식점-13
3rd row동대문-음식점-43
4th row동대문-축-2
5th row동대문-축-3
ValueCountFrequency (%)
106-10-19 9
 
0.2%
106-10-12 9
 
0.2%
106-10-18 9
 
0.2%
106-7-1 9
 
0.2%
106-10-1 9
 
0.2%
106-10-6 9
 
0.2%
106-10-5 9
 
0.2%
106-10-20 9
 
0.2%
106-10-4 9
 
0.2%
106-10-15 9
 
0.2%
Other values (2826) 5436
98.4%
2024-05-11T14:43:44.391928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 10804
23.2%
1 9726
20.9%
0 7286
15.6%
6 6007
12.9%
2 2492
 
5.3%
3 1698
 
3.6%
5 1472
 
3.2%
7 1433
 
3.1%
4 1325
 
2.8%
8 1127
 
2.4%
Other values (50) 3264
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33541
71.9%
Dash Punctuation 10804
 
23.2%
Other Letter 2246
 
4.8%
Uppercase Letter 42
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
410
18.3%
410
18.3%
410
18.3%
132
 
5.9%
123
 
5.5%
113
 
5.0%
101
 
4.5%
97
 
4.3%
89
 
4.0%
54
 
2.4%
Other values (35) 307
13.7%
Decimal Number
ValueCountFrequency (%)
1 9726
29.0%
0 7286
21.7%
6 6007
17.9%
2 2492
 
7.4%
3 1698
 
5.1%
5 1472
 
4.4%
7 1433
 
4.3%
4 1325
 
4.0%
8 1127
 
3.4%
9 975
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
G 32
76.2%
M 5
 
11.9%
O 5
 
11.9%
Dash Punctuation
ValueCountFrequency (%)
- 10804
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44346
95.1%
Hangul 2246
 
4.8%
Latin 42
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
410
18.3%
410
18.3%
410
18.3%
132
 
5.9%
123
 
5.5%
113
 
5.0%
101
 
4.5%
97
 
4.3%
89
 
4.0%
54
 
2.4%
Other values (35) 307
13.7%
Common
ValueCountFrequency (%)
- 10804
24.4%
1 9726
21.9%
0 7286
16.4%
6 6007
13.5%
2 2492
 
5.6%
3 1698
 
3.8%
5 1472
 
3.3%
7 1433
 
3.2%
4 1325
 
3.0%
8 1127
 
2.5%
Other values (2) 976
 
2.2%
Latin
ValueCountFrequency (%)
G 32
76.2%
M 5
 
11.9%
O 5
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44388
95.2%
Hangul 2245
 
4.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 10804
24.3%
1 9726
21.9%
0 7286
16.4%
6 6007
13.5%
2 2492
 
5.6%
3 1698
 
3.8%
5 1472
 
3.3%
7 1433
 
3.2%
4 1325
 
3.0%
8 1127
 
2.5%
Other values (5) 1018
 
2.3%
Hangul
ValueCountFrequency (%)
410
18.3%
410
18.3%
410
18.3%
132
 
5.9%
123
 
5.5%
113
 
5.0%
101
 
4.5%
97
 
4.3%
89
 
4.0%
54
 
2.4%
Other values (34) 306
13.6%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
검사용
4428 
<NA>
2258 
기타
 
253
증거용
 
25
압류
 
20

Length

Max length4
Median length3
Mean length3.2842211
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 4428
63.4%
<NA> 2258
32.3%
기타 253
 
3.6%
증거용 25
 
0.4%
압류 20
 
0.3%

Length

2024-05-11T14:43:44.593042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:44.746559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 4428
63.4%
na 2258
32.3%
기타 253
 
3.6%
증거용 25
 
0.4%
압류 20
 
0.3%
Distinct497
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T14:43:45.027603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length10.248425
Min length2

Characters and Unicode

Total characters71575
Distinct characters456
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

Unique258 ?
Unique (%)3.7%

Sample

1st row홍능갈비집
2nd row마포회관
3rd row마포회관
4th row마포회관
5th row마포회관
ValueCountFrequency (%)
청량리점 1056
 
11.4%
롯데쇼핑(주)롯데마트 1050
 
11.4%
홈플러스(주)동대문점 1004
 
10.9%
이문점 661
 
7.2%
주)이마트 419
 
4.5%
삼성테스코(주)홈플러스동대문점 350
 
3.8%
진로마트 272
 
2.9%
롯데쇼핑(주)롯데슈퍼전농점 257
 
2.8%
주)신세계이마트 241
 
2.6%
주)이마트장안점 219
 
2.4%
Other values (544) 3714
40.2%
2024-05-11T14:43:45.682627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4508
 
6.3%
( 4296
 
6.0%
) 4296
 
6.0%
4149
 
5.8%
3643
 
5.1%
3521
 
4.9%
3367
 
4.7%
3250
 
4.5%
2717
 
3.8%
2260
 
3.2%
Other values (446) 35568
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60510
84.5%
Open Punctuation 4296
 
6.0%
Close Punctuation 4296
 
6.0%
Space Separator 2260
 
3.2%
Decimal Number 86
 
0.1%
Uppercase Letter 60
 
0.1%
Lowercase Letter 37
 
0.1%
Other Punctuation 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4508
 
7.5%
4149
 
6.9%
3643
 
6.0%
3521
 
5.8%
3367
 
5.6%
3250
 
5.4%
2717
 
4.5%
2171
 
3.6%
1864
 
3.1%
1665
 
2.8%
Other values (405) 29655
49.0%
Lowercase Letter
ValueCountFrequency (%)
o 14
37.8%
i 3
 
8.1%
f 3
 
8.1%
g 3
 
8.1%
z 2
 
5.4%
e 2
 
5.4%
a 2
 
5.4%
p 2
 
5.4%
c 1
 
2.7%
l 1
 
2.7%
Other values (4) 4
 
10.8%
Uppercase Letter
ValueCountFrequency (%)
G 13
21.7%
S 9
15.0%
M 8
13.3%
C 6
10.0%
T 5
 
8.3%
A 3
 
5.0%
D 3
 
5.0%
F 3
 
5.0%
I 3
 
5.0%
U 3
 
5.0%
Other values (2) 4
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 55
64.0%
0 11
 
12.8%
5 8
 
9.3%
6 5
 
5.8%
1 3
 
3.5%
4 2
 
2.3%
3 1
 
1.2%
7 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 26
86.7%
, 2
 
6.7%
& 1
 
3.3%
; 1
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 4296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4296
100.0%
Space Separator
ValueCountFrequency (%)
2260
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60510
84.5%
Common 10968
 
15.3%
Latin 97
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4508
 
7.5%
4149
 
6.9%
3643
 
6.0%
3521
 
5.8%
3367
 
5.6%
3250
 
5.4%
2717
 
4.5%
2171
 
3.6%
1864
 
3.1%
1665
 
2.8%
Other values (405) 29655
49.0%
Latin
ValueCountFrequency (%)
o 14
14.4%
G 13
13.4%
S 9
 
9.3%
M 8
 
8.2%
C 6
 
6.2%
T 5
 
5.2%
i 3
 
3.1%
f 3
 
3.1%
A 3
 
3.1%
D 3
 
3.1%
Other values (16) 30
30.9%
Common
ValueCountFrequency (%)
( 4296
39.2%
) 4296
39.2%
2260
20.6%
2 55
 
0.5%
. 26
 
0.2%
0 11
 
0.1%
5 8
 
0.1%
6 5
 
< 0.1%
1 3
 
< 0.1%
, 2
 
< 0.1%
Other values (5) 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60510
84.5%
ASCII 11065
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4508
 
7.5%
4149
 
6.9%
3643
 
6.0%
3521
 
5.8%
3367
 
5.6%
3250
 
5.4%
2717
 
4.5%
2171
 
3.6%
1864
 
3.1%
1665
 
2.8%
Other values (405) 29655
49.0%
ASCII
ValueCountFrequency (%)
( 4296
38.8%
) 4296
38.8%
2260
20.4%
2 55
 
0.5%
. 26
 
0.2%
o 14
 
0.1%
G 13
 
0.1%
0 11
 
0.1%
S 9
 
0.1%
M 8
 
0.1%
Other values (31) 77
 
0.7%
Distinct325
Distinct (%)4.7%
Missing15
Missing (%)0.2%
Memory size54.7 KiB
2024-05-11T14:43:46.009373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.875305
Min length1

Characters and Unicode

Total characters75790
Distinct characters19
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

Unique83 ?
Unique (%)1.2%

Sample

1st row19Z000000
2nd row121000000
3rd row121000000
4th row121000000
5th rowB0103000000000
ValueCountFrequency (%)
821000000 706
 
10.4%
c01000000 448
 
6.6%
g0100000100000 380
 
5.6%
815000000 335
 
5.0%
801000000 328
 
4.9%
829000000 205
 
3.0%
c0101010000000 198
 
2.9%
830000000 190
 
2.8%
c0115040000000 177
 
2.6%
814000000 135
 
2.0%
Other values (313) 3657
54.1%
2024-05-11T14:43:46.535967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51458
67.9%
1 7850
 
10.4%
8 3547
 
4.7%
2 3468
 
4.6%
C 2619
 
3.5%
3 1733
 
2.3%
1354
 
1.8%
5 898
 
1.2%
4 778
 
1.0%
9 605
 
0.8%
Other values (9) 1480
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71077
93.8%
Uppercase Letter 3359
 
4.4%
Space Separator 1354
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51458
72.4%
1 7850
 
11.0%
8 3547
 
5.0%
2 3468
 
4.9%
3 1733
 
2.4%
5 898
 
1.3%
4 778
 
1.1%
9 605
 
0.9%
6 393
 
0.6%
7 347
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 2619
78.0%
G 476
 
14.2%
B 113
 
3.4%
A 64
 
1.9%
Z 23
 
0.7%
F 22
 
0.7%
X 22
 
0.7%
E 20
 
0.6%
Space Separator
ValueCountFrequency (%)
1354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72431
95.6%
Latin 3359
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51458
71.0%
1 7850
 
10.8%
8 3547
 
4.9%
2 3468
 
4.8%
3 1733
 
2.4%
1354
 
1.9%
5 898
 
1.2%
4 778
 
1.1%
9 605
 
0.8%
6 393
 
0.5%
Latin
ValueCountFrequency (%)
C 2619
78.0%
G 476
 
14.2%
B 113
 
3.4%
A 64
 
1.9%
Z 23
 
0.7%
F 22
 
0.7%
X 22
 
0.7%
E 20
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51458
67.9%
1 7850
 
10.4%
8 3547
 
4.7%
2 3468
 
4.6%
C 2619
 
3.5%
3 1733
 
2.3%
1354
 
1.8%
5 898
 
1.2%
4 778
 
1.0%
9 605
 
0.8%
Other values (9) 1480
 
2.0%

식품군
Text

MISSING 

Distinct229
Distinct (%)3.7%
Missing850
Missing (%)12.2%
Memory size54.7 KiB
2024-05-11T14:43:47.000261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.6483534
Min length1

Characters and Unicode

Total characters28513
Distinct characters268
Distinct categories7 ?
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 (%)1.0%

Sample

1st row식육류중육류
2nd row식육류중육류
3rd row식육류중육류
4th row기타축산물
5th row기타축산물
ValueCountFrequency (%)
조미식품 752
 
10.4%
과자류 426
 
5.9%
421
 
5.8%
조리식품 380
 
5.3%
면류 359
 
5.0%
과자 237
 
3.3%
기타식품류 225
 
3.1%
규격외일반가공식품 190
 
2.6%
유탕면류 177
 
2.4%
음료류 156
 
2.2%
Other values (247) 3904
54.0%
2024-05-11T14:43:47.674193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2722
 
9.5%
2382
 
8.4%
2205
 
7.7%
1296
 
4.5%
1093
 
3.8%
908
 
3.2%
789
 
2.8%
788
 
2.8%
786
 
2.8%
677
 
2.4%
Other values (258) 14867
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26957
94.5%
Space Separator 1093
 
3.8%
Other Punctuation 287
 
1.0%
Open Punctuation 73
 
0.3%
Close Punctuation 73
 
0.3%
Lowercase Letter 20
 
0.1%
Uppercase Letter 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2722
 
10.1%
2382
 
8.8%
2205
 
8.2%
1296
 
4.8%
908
 
3.4%
789
 
2.9%
788
 
2.9%
786
 
2.9%
677
 
2.5%
675
 
2.5%
Other values (234) 13729
50.9%
Lowercase Letter
ValueCountFrequency (%)
l 3
15.0%
e 3
15.0%
n 2
10.0%
y 2
10.0%
h 2
10.0%
t 2
10.0%
u 1
 
5.0%
s 1
 
5.0%
f 1
 
5.0%
o 1
 
5.0%
Other values (2) 2
10.0%
Uppercase Letter
ValueCountFrequency (%)
D 3
30.0%
M 3
30.0%
C 2
20.0%
S 1
 
10.0%
E 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 152
53.0%
, 124
43.2%
/ 7
 
2.4%
? 4
 
1.4%
Space Separator
ValueCountFrequency (%)
1093
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26957
94.5%
Common 1526
 
5.4%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2722
 
10.1%
2382
 
8.8%
2205
 
8.2%
1296
 
4.8%
908
 
3.4%
789
 
2.9%
788
 
2.9%
786
 
2.9%
677
 
2.5%
675
 
2.5%
Other values (234) 13729
50.9%
Latin
ValueCountFrequency (%)
l 3
10.0%
e 3
10.0%
D 3
10.0%
M 3
10.0%
n 2
 
6.7%
y 2
 
6.7%
h 2
 
6.7%
t 2
 
6.7%
C 2
 
6.7%
u 1
 
3.3%
Other values (7) 7
23.3%
Common
ValueCountFrequency (%)
1093
71.6%
. 152
 
10.0%
, 124
 
8.1%
( 73
 
4.8%
) 73
 
4.8%
/ 7
 
0.5%
? 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26957
94.5%
ASCII 1556
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2722
 
10.1%
2382
 
8.8%
2205
 
8.2%
1296
 
4.8%
908
 
3.4%
789
 
2.9%
788
 
2.9%
786
 
2.9%
677
 
2.5%
675
 
2.5%
Other values (234) 13729
50.9%
ASCII
ValueCountFrequency (%)
1093
70.2%
. 152
 
9.8%
, 124
 
8.0%
( 73
 
4.7%
) 73
 
4.7%
/ 7
 
0.4%
? 4
 
0.3%
l 3
 
0.2%
e 3
 
0.2%
D 3
 
0.2%
Other values (14) 21
 
1.3%

품목명
Text

MISSING 

Distinct344
Distinct (%)5.1%
Missing198
Missing (%)2.8%
Memory size54.7 KiB
2024-05-11T14:43:48.083518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.4730327
Min length1

Characters and Unicode

Total characters30354
Distinct characters328
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

Unique88 ?
Unique (%)1.3%

Sample

1st row소고기
2nd row소고기
3rd row기타축산물
4th row기타축산물
5th row조리식품 등
ValueCountFrequency (%)
531
 
6.5%
조리식품 499
 
6.1%
소스류 498
 
6.1%
과자 391
 
4.8%
국수 280
 
3.4%
유탕면류 262
 
3.2%
카레 206
 
2.5%
캔디류 168
 
2.1%
즉석조리식품 167
 
2.0%
소고기 151
 
1.8%
Other values (366) 5010
61.4%
2024-05-11T14:43:48.667901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1636
 
5.4%
1526
 
5.0%
1377
 
4.5%
1074
 
3.5%
986
 
3.2%
975
 
3.2%
901
 
3.0%
806
 
2.7%
775
 
2.6%
772
 
2.5%
Other values (318) 19526
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27958
92.1%
Space Separator 1377
 
4.5%
Other Punctuation 428
 
1.4%
Close Punctuation 279
 
0.9%
Open Punctuation 279
 
0.9%
Lowercase Letter 20
 
0.1%
Uppercase Letter 11
 
< 0.1%
Decimal Number 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1636
 
5.9%
1526
 
5.5%
1074
 
3.8%
986
 
3.5%
975
 
3.5%
901
 
3.2%
806
 
2.9%
775
 
2.8%
772
 
2.8%
770
 
2.8%
Other values (292) 17737
63.4%
Lowercase Letter
ValueCountFrequency (%)
l 3
15.0%
e 3
15.0%
t 2
10.0%
h 2
10.0%
y 2
10.0%
n 2
10.0%
m 1
 
5.0%
a 1
 
5.0%
o 1
 
5.0%
f 1
 
5.0%
Other values (2) 2
10.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
27.3%
M 3
27.3%
D 3
27.3%
E 1
 
9.1%
S 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 256
59.8%
, 154
36.0%
? 11
 
2.6%
/ 7
 
1.6%
Space Separator
ValueCountFrequency (%)
1377
100.0%
Close Punctuation
ValueCountFrequency (%)
) 279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27958
92.1%
Common 2365
 
7.8%
Latin 31
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1636
 
5.9%
1526
 
5.5%
1074
 
3.8%
986
 
3.5%
975
 
3.5%
901
 
3.2%
806
 
2.9%
775
 
2.8%
772
 
2.8%
770
 
2.8%
Other values (292) 17737
63.4%
Latin
ValueCountFrequency (%)
l 3
9.7%
C 3
9.7%
M 3
9.7%
e 3
9.7%
D 3
9.7%
t 2
 
6.5%
h 2
 
6.5%
y 2
 
6.5%
n 2
 
6.5%
m 1
 
3.2%
Other values (7) 7
22.6%
Common
ValueCountFrequency (%)
1377
58.2%
) 279
 
11.8%
( 279
 
11.8%
. 256
 
10.8%
, 154
 
6.5%
? 11
 
0.5%
/ 7
 
0.3%
3 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27958
92.1%
ASCII 2396
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1636
 
5.9%
1526
 
5.5%
1074
 
3.8%
986
 
3.5%
975
 
3.5%
901
 
3.2%
806
 
2.9%
775
 
2.8%
772
 
2.8%
770
 
2.8%
Other values (292) 17737
63.4%
ASCII
ValueCountFrequency (%)
1377
57.5%
) 279
 
11.6%
( 279
 
11.6%
. 256
 
10.7%
, 154
 
6.4%
? 11
 
0.5%
/ 7
 
0.3%
l 3
 
0.1%
C 3
 
0.1%
M 3
 
0.1%
Other values (16) 24
 
1.0%
Distinct5091
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
2024-05-11T14:43:49.120124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length38
Mean length7.5975086
Min length1

Characters and Unicode

Total characters53061
Distinct characters914
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4236 ?
Unique (%)60.7%

Sample

1st row냉면육수
2nd row한우 등심
3rd row한우듬심
4th row한우등심
5th row한우등심
ValueCountFrequency (%)
참기름 90
 
0.8%
오뚜기 73
 
0.7%
청정원 64
 
0.6%
매운맛 63
 
0.6%
3분 61
 
0.6%
한우등심 56
 
0.5%
백설 54
 
0.5%
카레 42
 
0.4%
유기농 40
 
0.4%
커피 40
 
0.4%
Other values (5537) 10251
94.6%
2024-05-11T14:43:49.734752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3857
 
7.3%
1247
 
2.4%
849
 
1.6%
796
 
1.5%
706
 
1.3%
686
 
1.3%
592
 
1.1%
556
 
1.0%
544
 
1.0%
543
 
1.0%
Other values (904) 42685
80.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44374
83.6%
Space Separator 3857
 
7.3%
Uppercase Letter 2715
 
5.1%
Decimal Number 814
 
1.5%
Lowercase Letter 396
 
0.7%
Close Punctuation 312
 
0.6%
Open Punctuation 311
 
0.6%
Other Punctuation 236
 
0.4%
Dash Punctuation 34
 
0.1%
Math Symbol 10
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1247
 
2.8%
849
 
1.9%
796
 
1.8%
706
 
1.6%
686
 
1.5%
592
 
1.3%
556
 
1.3%
544
 
1.2%
543
 
1.2%
542
 
1.2%
Other values (827) 37313
84.1%
Uppercase Letter
ValueCountFrequency (%)
E 290
 
10.7%
A 246
 
9.1%
I 204
 
7.5%
O 188
 
6.9%
C 177
 
6.5%
S 172
 
6.3%
T 164
 
6.0%
R 158
 
5.8%
N 157
 
5.8%
L 152
 
5.6%
Other values (16) 807
29.7%
Lowercase Letter
ValueCountFrequency (%)
a 57
14.4%
p 47
11.9%
m 43
10.9%
e 38
9.6%
o 30
 
7.6%
s 21
 
5.3%
l 19
 
4.8%
r 19
 
4.8%
t 18
 
4.5%
g 17
 
4.3%
Other values (13) 87
22.0%
Other Punctuation
ValueCountFrequency (%)
% 54
22.9%
& 42
17.8%
; 31
13.1%
/ 31
13.1%
, 20
 
8.5%
. 17
 
7.2%
' 15
 
6.4%
10
 
4.2%
! 9
 
3.8%
? 6
 
2.5%
Decimal Number
ValueCountFrequency (%)
0 229
28.1%
1 187
23.0%
3 161
19.8%
2 97
11.9%
5 37
 
4.5%
6 33
 
4.1%
9 22
 
2.7%
7 18
 
2.2%
4 18
 
2.2%
8 12
 
1.5%
Space Separator
ValueCountFrequency (%)
3857
100.0%
Close Punctuation
ValueCountFrequency (%)
) 312
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Math Symbol
ValueCountFrequency (%)
+ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
˚ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44350
83.6%
Common 5576
 
10.5%
Latin 3111
 
5.9%
Han 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1247
 
2.8%
849
 
1.9%
796
 
1.8%
706
 
1.6%
686
 
1.5%
592
 
1.3%
556
 
1.3%
544
 
1.2%
543
 
1.2%
542
 
1.2%
Other values (817) 37289
84.1%
Latin
ValueCountFrequency (%)
E 290
 
9.3%
A 246
 
7.9%
I 204
 
6.6%
O 188
 
6.0%
C 177
 
5.7%
S 172
 
5.5%
T 164
 
5.3%
R 158
 
5.1%
N 157
 
5.0%
L 152
 
4.9%
Other values (39) 1203
38.7%
Common
ValueCountFrequency (%)
3857
69.2%
) 312
 
5.6%
( 311
 
5.6%
0 229
 
4.1%
1 187
 
3.4%
3 161
 
2.9%
2 97
 
1.7%
% 54
 
1.0%
& 42
 
0.8%
5 37
 
0.7%
Other values (18) 289
 
5.2%
Han
ValueCountFrequency (%)
9
37.5%
6
25.0%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44350
83.6%
ASCII 8675
 
16.3%
CJK 15
 
< 0.1%
None 11
 
< 0.1%
CJK Compat Ideographs 9
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3857
44.5%
) 312
 
3.6%
( 311
 
3.6%
E 290
 
3.3%
A 246
 
2.8%
0 229
 
2.6%
I 204
 
2.4%
O 188
 
2.2%
1 187
 
2.2%
C 177
 
2.0%
Other values (64) 2674
30.8%
Hangul
ValueCountFrequency (%)
1247
 
2.8%
849
 
1.9%
796
 
1.8%
706
 
1.6%
686
 
1.5%
592
 
1.3%
556
 
1.3%
544
 
1.2%
543
 
1.2%
542
 
1.2%
Other values (817) 37289
84.1%
None
ValueCountFrequency (%)
10
90.9%
1
 
9.1%
CJK Compat Ideographs
ValueCountFrequency (%)
9
100.0%
CJK
ValueCountFrequency (%)
6
40.0%
2
 
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%

음식물명
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing6969
Missing (%)99.8%
Memory size54.7 KiB
2024-05-11T14:43:49.975508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.2
Min length2

Characters and Unicode

Total characters93
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)80.0%

Sample

1st row한우(등심)
2nd row등심
3rd row칼국수
4th row한우(안심)
5th row한우(안심)
ValueCountFrequency (%)
한우(안심 3
15.8%
국내산 3
15.8%
한우(등심 2
10.5%
등심 1
 
5.3%
칼국수 1
 
5.3%
한우(부채살 1
 
5.3%
쇠고기(국내산 1
 
5.3%
한우 1
 
5.3%
한우(업진 1
 
5.3%
콩국수물 1
 
5.3%
Other values (4) 4
21.1%
2024-05-11T14:43:50.366205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
8.6%
( 8
 
8.6%
) 8
 
8.6%
8
 
8.6%
6
 
6.5%
6
 
6.5%
4
 
4.3%
4
 
4.3%
4
 
4.3%
3
 
3.2%
Other values (30) 34
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
77.4%
Open Punctuation 8
 
8.6%
Close Punctuation 8
 
8.6%
Space Separator 4
 
4.3%
Other Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
 
11.1%
8
 
11.1%
6
 
8.3%
6
 
8.3%
4
 
5.6%
4
 
5.6%
3
 
4.2%
3
 
4.2%
2
 
2.8%
2
 
2.8%
Other values (26) 26
36.1%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
77.4%
Common 21
 
22.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8
 
11.1%
8
 
11.1%
6
 
8.3%
6
 
8.3%
4
 
5.6%
4
 
5.6%
3
 
4.2%
3
 
4.2%
2
 
2.8%
2
 
2.8%
Other values (26) 26
36.1%
Common
ValueCountFrequency (%)
( 8
38.1%
) 8
38.1%
4
19.0%
1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
77.4%
ASCII 20
 
21.5%
None 1
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8
 
11.1%
8
 
11.1%
6
 
8.3%
6
 
8.3%
4
 
5.6%
4
 
5.6%
3
 
4.2%
3
 
4.2%
2
 
2.8%
2
 
2.8%
Other values (26) 26
36.1%
ASCII
ValueCountFrequency (%)
( 8
40.0%
) 8
40.0%
4
20.0%
None
ValueCountFrequency (%)
1
100.0%

원료명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6898 
소고기
 
80
소괴
 
1
칼국수
 
1
한우
 
1
Other values (3)
 
3

Length

Max length7
Median length4
Mean length3.9882589
Min length2

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6898
98.8%
소고기 80
 
1.1%
소괴 1
 
< 0.1%
칼국수 1
 
< 0.1%
한우 1
 
< 0.1%
돼지고기 1
 
< 0.1%
우동장국 1
 
< 0.1%
홍삼농축액 등 1
 
< 0.1%

Length

2024-05-11T14:43:50.548034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:50.743971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6898
98.8%
소고기 80
 
1.1%
소괴 1
 
< 0.1%
칼국수 1
 
< 0.1%
한우 1
 
< 0.1%
돼지고기 1
 
< 0.1%
우동장국 1
 
< 0.1%
홍삼농축액 1
 
< 0.1%
1
 
< 0.1%

생산업소
Text

MISSING 

Distinct237
Distinct (%)30.9%
Missing6216
Missing (%)89.0%
Memory size54.7 KiB
2024-05-11T14:43:51.016630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.4713542
Min length2

Characters and Unicode

Total characters4970
Distinct characters268
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

Unique119 ?
Unique (%)15.5%

Sample

1st row낙지천국
2nd row바닷가에서
3rd row동의보쌈
4th row맥도날드 장안사거리점
5th row농림수산
ValueCountFrequency (%)
주)오뚜기 80
 
10.2%
주)대상 46
 
5.8%
주)씨제이제일제당 37
 
4.7%
대광고등학교 26
 
3.3%
종암초등학교 19
 
2.4%
주)매크로통상 19
 
2.4%
주)크라운제과 15
 
1.9%
동서식품 14
 
1.8%
주)농심 12
 
1.5%
주)삼조쎌텍 12
 
1.5%
Other values (236) 507
64.4%
2024-05-11T14:43:51.505729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
526
 
10.6%
( 522
 
10.5%
) 521
 
10.5%
212
 
4.3%
123
 
2.5%
121
 
2.4%
116
 
2.3%
106
 
2.1%
105
 
2.1%
85
 
1.7%
Other values (258) 2533
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3865
77.8%
Open Punctuation 522
 
10.5%
Close Punctuation 521
 
10.5%
Uppercase Letter 20
 
0.4%
Space Separator 19
 
0.4%
Lowercase Letter 11
 
0.2%
Other Punctuation 7
 
0.1%
Decimal Number 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
526
 
13.6%
212
 
5.5%
123
 
3.2%
121
 
3.1%
116
 
3.0%
106
 
2.7%
105
 
2.7%
85
 
2.2%
79
 
2.0%
73
 
1.9%
Other values (237) 2319
60.0%
Uppercase Letter
ValueCountFrequency (%)
F 6
30.0%
J 4
20.0%
C 4
20.0%
S 3
15.0%
V 2
 
10.0%
B 1
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
27.3%
m 3
27.3%
p 3
27.3%
g 1
 
9.1%
s 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
8 1
20.0%
5 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 3
42.9%
; 3
42.9%
, 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 522
100.0%
Close Punctuation
ValueCountFrequency (%)
) 521
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3865
77.8%
Common 1074
 
21.6%
Latin 31
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
526
 
13.6%
212
 
5.5%
123
 
3.2%
121
 
3.1%
116
 
3.0%
106
 
2.7%
105
 
2.7%
85
 
2.2%
79
 
2.0%
73
 
1.9%
Other values (237) 2319
60.0%
Latin
ValueCountFrequency (%)
F 6
19.4%
J 4
12.9%
C 4
12.9%
a 3
9.7%
m 3
9.7%
p 3
9.7%
S 3
9.7%
V 2
 
6.5%
B 1
 
3.2%
g 1
 
3.2%
Common
ValueCountFrequency (%)
( 522
48.6%
) 521
48.5%
19
 
1.8%
& 3
 
0.3%
; 3
 
0.3%
2 2
 
0.2%
1 1
 
0.1%
8 1
 
0.1%
, 1
 
0.1%
5 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3865
77.8%
ASCII 1105
 
22.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
526
 
13.6%
212
 
5.5%
123
 
3.2%
121
 
3.1%
116
 
3.0%
106
 
2.7%
105
 
2.7%
85
 
2.2%
79
 
2.0%
73
 
1.9%
Other values (237) 2319
60.0%
ASCII
ValueCountFrequency (%)
( 522
47.2%
) 521
47.1%
19
 
1.7%
F 6
 
0.5%
J 4
 
0.4%
C 4
 
0.4%
& 3
 
0.3%
a 3
 
0.3%
m 3
 
0.3%
; 3
 
0.3%
Other values (11) 17
 
1.5%

수거일자
Real number (ℝ)

Distinct351
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20142801
Minimum20061120
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:51.692298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20061120
5-th percentile20090806
Q120110727
median20131209
Q320171130
95-th percentile20201117
Maximum20240314
Range179194
Interquartile range (IQR)60403

Descriptive statistics

Standard deviation38171.572
Coefficient of variation (CV)0.0018950478
Kurtosis-0.74749754
Mean20142801
Median Absolute Deviation (MAD)29996
Skewness0.43106125
Sum1.4067732 × 1011
Variance1.4570689 × 109
MonotonicityNot monotonic
2024-05-11T14:43:51.853833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120320 204
 
2.9%
20111005 134
 
1.9%
20150512 127
 
1.8%
20110517 125
 
1.8%
20121023 120
 
1.7%
20151111 116
 
1.7%
20161207 94
 
1.3%
20090414 86
 
1.2%
20111014 84
 
1.2%
20161013 80
 
1.1%
Other values (341) 5814
83.2%
ValueCountFrequency (%)
20061120 1
 
< 0.1%
20070621 4
 
0.1%
20070730 2
 
< 0.1%
20070731 1
 
< 0.1%
20090109 4
 
0.1%
20090119 18
 
0.3%
20090213 51
0.7%
20090414 86
1.2%
20090522 5
 
0.1%
20090609 45
0.6%
ValueCountFrequency (%)
20240314 25
0.4%
20240312 1
 
< 0.1%
20240311 2
 
< 0.1%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240226 1
 
< 0.1%
20240215 15
0.2%
20240116 2
 
< 0.1%
20240112 2
 
< 0.1%
20231114 1
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)0.6%
Missing160
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean14.011482
Minimum0.35
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:52.016758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.35
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum1000
Range999.65
Interquartile range (IQR)3

Descriptive statistics

Standard deviation77.027416
Coefficient of variation (CV)5.4974498
Kurtosis95.991347
Mean14.011482
Median Absolute Deviation (MAD)2
Skewness9.158605
Sum95614.35
Variance5933.2228
MonotonicityNot monotonic
2024-05-11T14:43:52.184154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
3.0 1988
28.5%
1.0 1410
20.2%
6.0 1258
18.0%
2.0 985
14.1%
5.0 407
 
5.8%
4.0 342
 
4.9%
8.0 100
 
1.4%
300.0 62
 
0.9%
7.0 39
 
0.6%
10.0 37
 
0.5%
Other values (32) 196
 
2.8%
(Missing) 160
 
2.3%
ValueCountFrequency (%)
0.35 1
 
< 0.1%
1.0 1410
20.2%
2.0 985
14.1%
3.0 1988
28.5%
4.0 342
 
4.9%
5.0 407
 
5.8%
6.0 1258
18.0%
7.0 39
 
0.6%
8.0 100
 
1.4%
9.0 33
 
0.5%
ValueCountFrequency (%)
1000.0 20
0.3%
790.0 1
 
< 0.1%
726.0 1
 
< 0.1%
622.0 1
 
< 0.1%
620.0 1
 
< 0.1%
600.0 25
0.4%
546.0 1
 
< 0.1%
500.0 1
 
< 0.1%
498.0 1
 
< 0.1%
432.0 1
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct553
Distinct (%)10.3%
Missing1618
Missing (%)23.2%
Memory size54.7 KiB
2024-05-11T14:43:52.755783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0152814
Min length1

Characters and Unicode

Total characters16180
Distinct characters25
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique255 ?
Unique (%)4.8%

Sample

1st rowg
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
300 383
 
7.1%
100 367
 
6.8%
500 294
 
5.5%
600 236
 
4.4%
200 234
 
4.4%
1 230
 
4.3%
150 180
 
3.4%
250 138
 
2.6%
400 135
 
2.5%
350 110
 
2.0%
Other values (542) 3059
57.0%
2024-05-11T14:43:53.609295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6240
38.6%
1 2091
 
12.9%
5 1641
 
10.1%
2 1416
 
8.8%
3 1160
 
7.2%
4 762
 
4.7%
g 707
 
4.4%
6 599
 
3.7%
8 479
 
3.0%
9 356
 
2.2%
Other values (15) 729
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15056
93.1%
Lowercase Letter 925
 
5.7%
Other Punctuation 152
 
0.9%
Other Symbol 35
 
0.2%
Other Letter 7
 
< 0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6240
41.4%
1 2091
 
13.9%
5 1641
 
10.9%
2 1416
 
9.4%
3 1160
 
7.7%
4 762
 
5.1%
6 599
 
4.0%
8 479
 
3.2%
9 356
 
2.4%
7 312
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
g 707
76.4%
m 76
 
8.2%
l 76
 
8.2%
k 62
 
6.7%
4
 
0.4%
Other Symbol
ValueCountFrequency (%)
27
77.1%
7
 
20.0%
1
 
2.9%
Other Letter
ValueCountFrequency (%)
3
42.9%
3
42.9%
1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 149
98.0%
, 3
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
L 4
80.0%
G 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15247
94.2%
Latin 926
 
5.7%
Hangul 7
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6240
40.9%
1 2091
 
13.7%
5 1641
 
10.8%
2 1416
 
9.3%
3 1160
 
7.6%
4 762
 
5.0%
6 599
 
3.9%
8 479
 
3.1%
9 356
 
2.3%
7 312
 
2.0%
Other values (6) 191
 
1.3%
Latin
ValueCountFrequency (%)
g 707
76.3%
m 76
 
8.2%
l 76
 
8.2%
k 62
 
6.7%
L 4
 
0.4%
G 1
 
0.1%
Hangul
ValueCountFrequency (%)
3
42.9%
3
42.9%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16134
99.7%
CJK Compat 35
 
0.2%
Hangul 7
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6240
38.7%
1 2091
 
13.0%
5 1641
 
10.2%
2 1416
 
8.8%
3 1160
 
7.2%
4 762
 
4.7%
g 707
 
4.4%
6 599
 
3.7%
8 479
 
3.0%
9 356
 
2.2%
Other values (8) 683
 
4.2%
CJK Compat
ValueCountFrequency (%)
27
77.1%
7
 
20.0%
1
 
2.9%
Letterlike Symbols
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
3
42.9%
3
42.9%
1
 
14.3%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
g
3592 
<NA>
2418 
ML
626 
KG
 
219
LT
 
94
Other values (2)
 
35

Length

Max length4
Median length1
Mean length2.1732532
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 3592
51.4%
<NA> 2418
34.6%
ML 626
 
9.0%
KG 219
 
3.1%
LT 94
 
1.3%
34
 
0.5%
mm 1
 
< 0.1%

Length

2024-05-11T14:43:53.837353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:54.018288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3592
51.4%
na 2418
34.6%
ml 626
 
9.0%
kg 219
 
3.1%
lt 94
 
1.3%
34
 
0.5%
mm 1
 
< 0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct31
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6824 
1개
 
40
환경검체
 
22
1
 
21
2건
 
12
Other values (26)
 
65

Length

Max length17
Median length4
Mean length3.9833906
Min length1

Unique

Unique16 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6824
97.7%
1개 40
 
0.6%
환경검체 22
 
0.3%
1 21
 
0.3%
2건 12
 
0.2%
2 10
 
0.1%
2개 9
 
0.1%
1팩 8
 
0.1%
3개-규격(스왑) 5
 
0.1%
3줄 5
 
0.1%
Other values (21) 28
 
0.4%

Length

2024-05-11T14:43:54.206332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6824
97.6%
1개 40
 
0.6%
환경검체 22
 
0.3%
1 21
 
0.3%
2건 12
 
0.2%
2개 11
 
0.2%
2 10
 
0.1%
1팩 8
 
0.1%
3개-규격(스왑 5
 
0.1%
3줄 5
 
0.1%
Other values (25) 32
 
0.5%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct257
Distinct (%)23.1%
Missing5872
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean20106282
Minimum11111111
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:54.394504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11111111
5-th percentile20121019
Q120140620
median20180308
Q320191030
95-th percentile20230615
Maximum20240311
Range9129200
Interquartile range (IQR)50410

Descriptive statistics

Standard deviation766783.75
Coefficient of variation (CV)0.038136526
Kurtosis134.10149
Mean20106282
Median Absolute Deviation (MAD)29587
Skewness-11.644643
Sum2.2358186 × 1010
Variance5.8795732 × 1011
MonotonicityNot monotonic
2024-05-11T14:43:54.932215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20220711 76
 
1.1%
20210401 56
 
0.8%
20200710 49
 
0.7%
20150909 35
 
0.5%
20190719 30
 
0.4%
20150213 29
 
0.4%
20161207 27
 
0.4%
20180625 26
 
0.4%
20140620 24
 
0.3%
20191030 20
 
0.3%
Other values (247) 740
 
10.6%
(Missing) 5872
84.1%
ValueCountFrequency (%)
11111111 8
0.1%
20110729 1
 
< 0.1%
20120319 8
0.1%
20120516 1
 
< 0.1%
20120522 1
 
< 0.1%
20120528 1
 
< 0.1%
20120608 10
0.1%
20120610 1
 
< 0.1%
20120613 1
 
< 0.1%
20120618 1
 
< 0.1%
ValueCountFrequency (%)
20240311 2
 
< 0.1%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240226 1
 
< 0.1%
20240116 2
 
< 0.1%
20231108 1
 
< 0.1%
20231025 2
 
< 0.1%
20231019 4
 
0.1%
20231017 10
0.1%
20231011 2
 
< 0.1%

제조일자(롯트)
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6787 
1111
 
76
11111
 
74
111111
 
14
111ㅂㅂ
 
7
Other values (7)
 
26

Length

Max length11
Median length4
Mean length4.032646
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6787
97.2%
1111 76
 
1.1%
11111 74
 
1.1%
111111 14
 
0.2%
111ㅂㅂ 7
 
0.1%
1111111111 6
 
0.1%
111111111 6
 
0.1%
11111111 5
 
0.1%
1111111 4
 
0.1%
11111111111 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2024-05-11T14:43:55.109367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6787
97.2%
1111 76
 
1.1%
11111 74
 
1.1%
111111 14
 
0.2%
111ㅂㅂ 7
 
0.1%
1111111111 6
 
0.1%
111111111 6
 
0.1%
11111111 5
 
0.1%
1111111 4
 
0.1%
11111111111 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct171
Distinct (%)83.8%
Missing6780
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean19827213
Minimum0
Maximum20150329
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:55.285119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20111120
Q120120506
median20121019
Q320130404
95-th percentile20131024
Maximum20150329
Range20150329
Interquartile range (IQR)9898.25

Descriptive statistics

Standard deviation2428165.9
Coefficient of variation (CV)0.12246632
Kurtosis64.616041
Mean19827213
Median Absolute Deviation (MAD)699.5
Skewness-8.1229342
Sum4.0447515 × 109
Variance5.8959898 × 1012
MonotonicityNot monotonic
2024-05-11T14:43:55.498635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111219 4
 
0.1%
20121027 3
 
< 0.1%
20111220 3
 
< 0.1%
20120310 3
 
< 0.1%
20121011 3
 
< 0.1%
20121003 2
 
< 0.1%
20121017 2
 
< 0.1%
20121206 2
 
< 0.1%
20120921 2
 
< 0.1%
20121019 2
 
< 0.1%
Other values (161) 178
 
2.5%
(Missing) 6780
97.1%
ValueCountFrequency (%)
0 1
< 0.1%
3 1
< 0.1%
2011 1
< 0.1%
20100127 1
< 0.1%
20110517 1
< 0.1%
20110723 1
< 0.1%
20111015 1
< 0.1%
20111018 1
< 0.1%
20111020 1
< 0.1%
20111022 1
< 0.1%
ValueCountFrequency (%)
20150329 1
< 0.1%
20141007 2
< 0.1%
20140612 1
< 0.1%
20131226 1
< 0.1%
20131221 1
< 0.1%
20131205 1
< 0.1%
20131201 1
< 0.1%
20131130 1
< 0.1%
20131117 1
< 0.1%
20131026 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)42.1%
Missing6946
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean2156139.1
Minimum0
Maximum20190521
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:55.646022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median3
Q3160
95-th percentile20182145
Maximum20190521
Range20190521
Interquartile range (IQR)159

Descriptive statistics

Standard deviation6268290
Coefficient of variation (CV)2.9071825
Kurtosis5.453179
Mean2156139.1
Median Absolute Deviation (MAD)2
Skewness2.6761094
Sum81933287
Variance3.929146 × 1013
MonotonicityNot monotonic
2024-05-11T14:43:55.767968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 15
 
0.2%
3 5
 
0.1%
180 2
 
< 0.1%
2 2
 
< 0.1%
100000 2
 
< 0.1%
90 2
 
< 0.1%
20190305 1
 
< 0.1%
0 1
 
< 0.1%
10 1
 
< 0.1%
365 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 6946
99.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 15
0.2%
2 2
 
< 0.1%
3 5
 
0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
90 2
 
< 0.1%
100 1
 
< 0.1%
180 2
 
< 0.1%
365 1
 
< 0.1%
ValueCountFrequency (%)
20190521 1
< 0.1%
20190305 1
< 0.1%
20180705 1
< 0.1%
20170701 1
< 0.1%
1000000 1
< 0.1%
100000 2
< 0.1%
365 1
< 0.1%
180 2
< 0.1%
100 1
< 0.1%
90 2
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
실온
3676 
<NA>
2258 
냉장
656 
냉동
 
272
기타
 
122

Length

Max length4
Median length2
Mean length2.6466208
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 3676
52.6%
<NA> 2258
32.3%
냉장 656
 
9.4%
냉동 272
 
3.9%
기타 122
 
1.7%

Length

2024-05-11T14:43:55.899264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:56.010019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3676
52.6%
na 2258
32.3%
냉장 656
 
9.4%
냉동 272
 
3.9%
기타 122
 
1.7%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

어린이기호식품유형
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6935 
과자(한과류제외)
 
23
캔디류
 
10
초콜릿류
 
6
혼합음료
 
4
Other values (4)
 
6

Length

Max length22
Median length4
Mean length4.0174685
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6935
99.3%
과자(한과류제외) 23
 
0.3%
캔디류 10
 
0.1%
초콜릿류 6
 
0.1%
혼합음료 4
 
0.1%
어육소시지 2
 
< 0.1%
빵류 2
 
< 0.1%
과?채음료 1
 
< 0.1%
발효유류(발효버터유 및 발효유분말 제외) 1
 
< 0.1%

Length

2024-05-11T14:43:56.143140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:56.342941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6935
99.3%
과자(한과류제외 23
 
0.3%
캔디류 10
 
0.1%
초콜릿류 6
 
0.1%
혼합음료 4
 
0.1%
어육소시지 2
 
< 0.1%
빵류 2
 
< 0.1%
과?채음료 1
 
< 0.1%
발효유류(발효버터유 1
 
< 0.1%
1
 
< 0.1%
Other values (2) 2
 
< 0.1%

검사기관명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
001
5490 
<NA>
1439 
000
 
54
서울시보건환경연구원
 
1

Length

Max length10
Median length3
Mean length3.2070447
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row001
2nd row001
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
001 5490
78.6%
<NA> 1439
 
20.6%
000 54
 
0.8%
서울시보건환경연구원 1
 
< 0.1%

Length

2024-05-11T14:43:56.496893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:56.629211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 5490
78.6%
na 1439
 
20.6%
000 54
 
0.8%
서울시보건환경연구원 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct239
Distinct (%)29.7%
Missing6180
Missing (%)88.5%
Memory size54.7 KiB
2024-05-11T14:43:56.907830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length5.8718905
Min length2

Characters and Unicode

Total characters4721
Distinct characters256
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)16.9%

Sample

1st row한우 등심
2nd row한우 등심
3rd row한우 등심
4th row한우 등심
5th row한우(등심)
ValueCountFrequency (%)
주)오뚜기 78
 
9.4%
오뚜기 51
 
6.1%
주)씨제이제일제당 42
 
5.0%
씨제이제일제당 35
 
4.2%
주)대상 30
 
3.6%
대상 21
 
2.5%
대상(주 19
 
2.3%
주)롯데제과 19
 
2.3%
홈플러스 13
 
1.6%
주)삼립식품 13
 
1.6%
Other values (249) 513
61.5%
2024-05-11T14:43:57.381006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 401
 
8.5%
391
 
8.3%
( 389
 
8.2%
332
 
7.0%
155
 
3.3%
138
 
2.9%
136
 
2.9%
122
 
2.6%
120
 
2.5%
113
 
2.4%
Other values (246) 2424
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3779
80.0%
Close Punctuation 401
 
8.5%
Open Punctuation 389
 
8.2%
Uppercase Letter 86
 
1.8%
Space Separator 30
 
0.6%
Lowercase Letter 28
 
0.6%
Decimal Number 7
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
391
 
10.3%
332
 
8.8%
155
 
4.1%
138
 
3.7%
136
 
3.6%
122
 
3.2%
120
 
3.2%
113
 
3.0%
95
 
2.5%
93
 
2.5%
Other values (207) 2084
55.1%
Uppercase Letter
ValueCountFrequency (%)
A 11
12.8%
R 7
 
8.1%
B 7
 
8.1%
F 6
 
7.0%
N 6
 
7.0%
I 6
 
7.0%
O 6
 
7.0%
U 5
 
5.8%
T 5
 
5.8%
L 4
 
4.7%
Other values (9) 23
26.7%
Lowercase Letter
ValueCountFrequency (%)
a 7
25.0%
n 7
25.0%
i 3
10.7%
g 3
10.7%
d 3
10.7%
b 1
 
3.6%
x 1
 
3.6%
y 1
 
3.6%
t 1
 
3.6%
r 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
3 1
14.3%
2 1
14.3%
8 1
14.3%
9 1
14.3%
7 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 401
100.0%
Open Punctuation
ValueCountFrequency (%)
( 389
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3779
80.0%
Common 828
 
17.5%
Latin 114
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
391
 
10.3%
332
 
8.8%
155
 
4.1%
138
 
3.7%
136
 
3.6%
122
 
3.2%
120
 
3.2%
113
 
3.0%
95
 
2.5%
93
 
2.5%
Other values (207) 2084
55.1%
Latin
ValueCountFrequency (%)
A 11
 
9.6%
a 7
 
6.1%
n 7
 
6.1%
R 7
 
6.1%
B 7
 
6.1%
F 6
 
5.3%
N 6
 
5.3%
I 6
 
5.3%
O 6
 
5.3%
U 5
 
4.4%
Other values (19) 46
40.4%
Common
ValueCountFrequency (%)
) 401
48.4%
( 389
47.0%
30
 
3.6%
4 2
 
0.2%
3 1
 
0.1%
2 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
- 1
 
0.1%
7 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3778
80.0%
ASCII 942
 
20.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 401
42.6%
( 389
41.3%
30
 
3.2%
A 11
 
1.2%
a 7
 
0.7%
n 7
 
0.7%
R 7
 
0.7%
B 7
 
0.7%
F 6
 
0.6%
N 6
 
0.6%
Other values (29) 71
 
7.5%
Hangul
ValueCountFrequency (%)
391
 
10.3%
332
 
8.8%
155
 
4.1%
138
 
3.7%
136
 
3.6%
122
 
3.2%
120
 
3.2%
113
 
3.0%
95
 
2.5%
93
 
2.5%
Other values (206) 2083
55.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
국내
5099 
국외
1885 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내 5099
73.0%
국외 1885
 
27.0%

Length

2024-05-11T14:43:57.596090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:57.723181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 5099
73.0%
국외 1885
 
27.0%

국가명
Categorical

IMBALANCE 

Distinct49
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6557 
미국
 
81
중국
 
69
태국
 
29
이탈리아
 
29
Other values (44)
 
219

Length

Max length10
Median length4
Mean length3.9228236
Min length2

Unique

Unique11 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6557
93.9%
미국 81
 
1.2%
중국 69
 
1.0%
태국 29
 
0.4%
이탈리아 29
 
0.4%
일본 25
 
0.4%
독일 19
 
0.3%
프랑스 18
 
0.3%
말레이지아 17
 
0.2%
스페인 14
 
0.2%
Other values (39) 126
 
1.8%

Length

2024-05-11T14:43:57.877106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6557
93.8%
미국 81
 
1.2%
중국 71
 
1.0%
태국 29
 
0.4%
이탈리아 29
 
0.4%
일본 25
 
0.4%
독일 19
 
0.3%
프랑스 18
 
0.3%
말레이지아 17
 
0.2%
스페인 14
 
0.2%
Other values (43) 131
 
1.9%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
1
4161 
<NA>
1960 
2
863 

Length

Max length4
Median length1
Mean length1.8419244
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 4161
59.6%
<NA> 1960
28.1%
2 863
 
12.4%

Length

2024-05-11T14:43:58.078044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:58.228472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4161
59.6%
na 1960
28.1%
2 863
 
12.4%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct199
Distinct (%)4.9%
Missing2897
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean20163000
Minimum20101013
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:58.387982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20101013
5-th percentile20110708
Q120150610
median20161014
Q320181214
95-th percentile20230615
Maximum20240314
Range139301
Interquartile range (IQR)30604

Descriptive statistics

Standard deviation33804.879
Coefficient of variation (CV)0.0016765799
Kurtosis-0.49999907
Mean20163000
Median Absolute Deviation (MAD)19988
Skewness0.0024899625
Sum8.2406179 × 1010
Variance1.1427699 × 109
MonotonicityNot monotonic
2024-05-11T14:43:58.594795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111005 134
 
1.9%
20110520 126
 
1.8%
20151111 108
 
1.5%
20171130 91
 
1.3%
20161207 86
 
1.2%
20111014 84
 
1.2%
20160420 78
 
1.1%
20161014 77
 
1.1%
20220711 76
 
1.1%
20150610 71
 
1.0%
Other values (189) 3156
45.2%
(Missing) 2897
41.5%
ValueCountFrequency (%)
20101013 1
 
< 0.1%
20110520 126
1.8%
20110607 10
 
0.1%
20110705 2
 
< 0.1%
20110706 40
 
0.6%
20110708 66
0.9%
20110711 21
 
0.3%
20110725 3
 
< 0.1%
20110727 2
 
< 0.1%
20110729 54
0.8%
ValueCountFrequency (%)
20240314 26
0.4%
20240311 2
 
< 0.1%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240226 1
 
< 0.1%
20240216 15
0.2%
20240116 4
 
0.1%
20231114 1
 
< 0.1%
20231113 6
 
0.1%
20231108 1
 
< 0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)5.8%
Missing3445
Missing (%)49.3%
Infinite0
Infinite (%)0.0%
Mean20165053
Minimum20110610
Maximum20220721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:43:58.828555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110610
5-th percentile20111128
Q120151106
median20161101
Q320181203
95-th percentile20201126
Maximum20220721
Range110111
Interquartile range (IQR)30097

Descriptive statistics

Standard deviation26058.881
Coefficient of variation (CV)0.0012922793
Kurtosis-0.23223367
Mean20165053
Median Absolute Deviation (MAD)19302
Skewness-0.32420908
Sum7.1364122 × 1010
Variance6.7906526 × 108
MonotonicityNot monotonic
2024-05-11T14:43:59.048691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120417 168
 
2.4%
20111021 135
 
1.9%
20171231 92
 
1.3%
20130227 77
 
1.1%
20161027 77
 
1.1%
20160503 69
 
1.0%
20150622 65
 
0.9%
20160613 62
 
0.9%
20160607 58
 
0.8%
20160729 53
 
0.8%
Other values (195) 2683
38.4%
(Missing) 3445
49.3%
ValueCountFrequency (%)
20110610 10
 
0.1%
20111021 135
1.9%
20111123 26
 
0.4%
20111128 10
 
0.1%
20111209 21
 
0.3%
20111222 9
 
0.1%
20120118 11
 
0.2%
20120119 32
 
0.5%
20120403 2
 
< 0.1%
20120406 12
 
0.2%
ValueCountFrequency (%)
20220721 41
0.6%
20220715 34
0.5%
20220711 1
 
< 0.1%
20210413 35
0.5%
20210409 21
0.3%
20210209 1
 
< 0.1%
20201216 1
 
< 0.1%
20201209 1
 
< 0.1%
20201203 12
 
0.2%
20201202 4
 
0.1%

판정구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
1
4562 
<NA>
2382 
2
 
40

Length

Max length4
Median length1
Mean length2.0231959
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4562
65.3%
<NA> 2382
34.1%
2 40
 
0.6%

Length

2024-05-11T14:43:59.296480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:59.432659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4562
65.3%
na 2382
34.1%
2 40
 
0.6%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

처리결과
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6743 
적합
 
219
이우엽피소 검출
 
11
한우
 
2
산가26.7
 
1
Other values (8)
 
8

Length

Max length25
Median length4
Mean length3.9537514
Min length2

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6743
96.5%
적합 219
 
3.1%
이우엽피소 검출 11
 
0.2%
한우 2
 
< 0.1%
산가26.7 1
 
< 0.1%
클로스트리디움퍼프리젠스 양성 1
 
< 0.1%
EPA_DHA 적합 1
 
< 0.1%
EPA와 DHA의 합 적합 1
 
< 0.1%
로사빈, 진세노사이드Rg1+Rb1+Rg3 적합 1
 
< 0.1%
비타민C적합 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2024-05-11T14:43:59.578554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6743
96.2%
적합 225
 
3.2%
이우엽피소 11
 
0.2%
검출 11
 
0.2%
한우 2
 
< 0.1%
로사빈 1
 
< 0.1%
비타민b6 1
 
< 0.1%
칼슘,마그네슘 1
 
< 0.1%
로사빈,대장균군 1
 
< 0.1%
비타민c적합 1
 
< 0.1%
Other values (9) 9
 
0.1%

수거품처리
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6974 
폐기
 
10

Length

Max length4
Median length4
Mean length3.9971363
Min length2

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> 6974
99.9%
폐기 10
 
0.1%

Length

2024-05-11T14:43:59.779583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:43:59.949865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6974
99.9%
폐기 10
 
0.1%

교부번호
Real number (ℝ)

Distinct510
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.00606 × 1010
Minimum1.9720042 × 1010
Maximum2.0230058 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:44:00.088826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9720042 × 1010
5-th percentile1.9960042 × 1010
Q12.0030043 × 1010
median2.0070043 × 1010
Q32.0100043 × 1010
95-th percentile2.0140043 × 1010
Maximum2.0230058 × 1010
Range5.1001559 × 108
Interquartile range (IQR)69999767

Descriptive statistics

Standard deviation60139536
Coefficient of variation (CV)0.0029978932
Kurtosis2.4317572
Mean2.00606 × 1010
Median Absolute Deviation (MAD)39999570
Skewness-0.70330481
Sum1.4010323 × 1014
Variance3.6167638 × 1015
MonotonicityNot monotonic
2024-05-11T14:44:00.261086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030043067 1341
19.2%
20100042834 1049
15.0%
20090042202 659
 
9.4%
20010042386 257
 
3.7%
20120042439 219
 
3.1%
19940042290 188
 
2.7%
20110042062 183
 
2.6%
19960042451 181
 
2.6%
20130105300 169
 
2.4%
20030042708 166
 
2.4%
Other values (500) 2572
36.8%
ValueCountFrequency (%)
19720042015 1
 
< 0.1%
19720042017 1
 
< 0.1%
19720042019 1
 
< 0.1%
19720042021 2
 
< 0.1%
19720042032 2
 
< 0.1%
19720042033 1
 
< 0.1%
19720042045 1
 
< 0.1%
19760042003 1
 
< 0.1%
19800042051 5
0.1%
19810042036 2
 
< 0.1%
ValueCountFrequency (%)
20230057607 2
 
< 0.1%
20230057282 1
 
< 0.1%
20230057211 1
 
< 0.1%
20220049974 1
 
< 0.1%
20220049841 1
 
< 0.1%
20220049350 1
 
< 0.1%
20220049309 1
 
< 0.1%
20220049075 1
 
< 0.1%
20220049046 76
1.1%
20210042909 1
 
< 0.1%

폐기일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)27.3%
Missing6962
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean20108459
Minimum20100413
Maximum20181205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:44:00.403883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100413
5-th percentile20100413
Q120100917
median20101201
Q320110613
95-th percentile20110613
Maximum20181205
Range80792
Interquartile range (IQR)9695.75

Descriptive statistics

Standard deviation16962.794
Coefficient of variation (CV)0.00084356509
Kurtosis17.999508
Mean20108459
Median Absolute Deviation (MAD)788
Skewness4.0739047
Sum4.4238609 × 108
Variance2.8773637 × 108
MonotonicityNot monotonic
2024-05-11T14:44:00.550879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20110613 9
 
0.1%
20100413 5
 
0.1%
20101201 3
 
< 0.1%
20100930 3
 
< 0.1%
20100913 1
 
< 0.1%
20181205 1
 
< 0.1%
(Missing) 6962
99.7%
ValueCountFrequency (%)
20100413 5
0.1%
20100913 1
 
< 0.1%
20100930 3
 
< 0.1%
20101201 3
 
< 0.1%
20110613 9
0.1%
20181205 1
 
< 0.1%
ValueCountFrequency (%)
20181205 1
 
< 0.1%
20110613 9
0.1%
20101201 3
 
< 0.1%
20100930 3
 
< 0.1%
20100913 1
 
< 0.1%
20100413 5
0.1%

폐기량(kg)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6964 
0.1
 
20

Length

Max length4
Median length4
Mean length3.9971363
Min length3

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> 6964
99.7%
0.1 20
 
0.3%

Length

2024-05-11T14:44:00.806965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:01.027382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6964
99.7%
0.1 20
 
0.3%

폐기금액(원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6968 
0
 
16

Length

Max length4
Median length4
Mean length3.9931271
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> 6968
99.8%
0 16
 
0.2%

Length

2024-05-11T14:44:01.256938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:01.412186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6968
99.8%
0 16
 
0.2%

폐기장소
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6961 
구청 구내식당
 
10
구내식당
 
6
구청 내 구내식당
 
4
동대문구청 구내식당
 
1
Other values (2)
 
2

Length

Max length10
Median length4
Mean length4.0083047
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6961
99.7%
구청 구내식당 10
 
0.1%
구내식당 6
 
0.1%
구청 내 구내식당 4
 
0.1%
동대문구청 구내식당 1
 
< 0.1%
구청내 식당 1
 
< 0.1%
폐기없음 1
 
< 0.1%

Length

2024-05-11T14:44:01.641404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:01.836285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6961
99.4%
구내식당 21
 
0.3%
구청 14
 
0.2%
4
 
0.1%
동대문구청 1
 
< 0.1%
구청내 1
 
< 0.1%
식당 1
 
< 0.1%
폐기없음 1
 
< 0.1%

폐기방법
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
<NA>
6961 
음식물쓰레기로 처리
 
14
음식물쓰레기
 
5
음식물쓰레기로 배출
 
1
음식물쓰레기로 분류 폐기
 
1
Other values (2)
 
2

Length

Max length13
Median length4
Mean length4.0160367
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6961
99.7%
음식물쓰레기로 처리 14
 
0.2%
음식물쓰레기 5
 
0.1%
음식물쓰레기로 배출 1
 
< 0.1%
음식물쓰레기로 분류 폐기 1
 
< 0.1%
음식물 쓰레기 1
 
< 0.1%
폐기없음 1
 
< 0.1%

Length

2024-05-11T14:44:02.057202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:02.308421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6961
99.4%
음식물쓰레기로 16
 
0.2%
처리 14
 
0.2%
음식물쓰레기 5
 
0.1%
배출 1
 
< 0.1%
분류 1
 
< 0.1%
폐기 1
 
< 0.1%
음식물 1
 
< 0.1%
쓰레기 1
 
< 0.1%
폐기없음 1
 
< 0.1%

소재지(도로명)
Text

MISSING 

Distinct281
Distinct (%)6.9%
Missing2931
Missing (%)42.0%
Memory size54.7 KiB
2024-05-11T14:44:02.624796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length47
Mean length33.184061
Min length23

Characters and Unicode

Total characters134495
Distinct characters181
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

Unique126 ?
Unique (%)3.1%

Sample

1st row서울특별시 동대문구 왕산로28길 7, (용두동)
2nd row서울특별시 동대문구 왕산로28길 7, (용두동)
3rd row서울특별시 동대문구 왕산로28길 7, (용두동)
4th row서울특별시 동대문구 왕산로28길 7, (용두동)
5th row서울특별시 동대문구 망우로 83, (휘경동,(망우로 193))
ValueCountFrequency (%)
서울특별시 4053
 
15.9%
동대문구 4053
 
15.9%
전농동 1269
 
5.0%
왕산로 966
 
3.8%
214 928
 
3.6%
5층 796
 
3.1%
청량리역사 784
 
3.1%
지하2층 671
 
2.6%
용두동 647
 
2.5%
1층 637
 
2.5%
Other values (405) 10727
42.0%
2024-05-11T14:44:03.243320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21481
 
16.0%
8268
 
6.1%
, 6140
 
4.6%
1 5348
 
4.0%
5182
 
3.9%
4883
 
3.6%
) 4364
 
3.2%
( 4364
 
3.2%
4183
 
3.1%
4149
 
3.1%
Other values (171) 66133
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80149
59.6%
Space Separator 21481
 
16.0%
Decimal Number 16990
 
12.6%
Other Punctuation 6140
 
4.6%
Close Punctuation 4420
 
3.3%
Open Punctuation 4420
 
3.3%
Uppercase Letter 553
 
0.4%
Dash Punctuation 329
 
0.2%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8268
 
10.3%
5182
 
6.5%
4883
 
6.1%
4183
 
5.2%
4149
 
5.2%
4122
 
5.1%
4114
 
5.1%
4056
 
5.1%
4053
 
5.1%
4053
 
5.1%
Other values (138) 33086
41.3%
Uppercase Letter
ValueCountFrequency (%)
S 225
40.7%
K 222
40.1%
B 61
 
11.0%
A 19
 
3.4%
T 7
 
1.3%
P 6
 
1.1%
D 3
 
0.5%
N 2
 
0.4%
G 2
 
0.4%
C 1
 
0.2%
Other values (5) 5
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 5348
31.5%
2 2689
15.8%
3 2161
12.7%
4 2153
12.7%
6 1415
 
8.3%
5 1199
 
7.1%
0 704
 
4.1%
9 560
 
3.3%
8 465
 
2.7%
7 296
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 4364
98.7%
] 56
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 4364
98.7%
[ 56
 
1.3%
Space Separator
ValueCountFrequency (%)
21481
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 329
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80149
59.6%
Common 53793
40.0%
Latin 553
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8268
 
10.3%
5182
 
6.5%
4883
 
6.1%
4183
 
5.2%
4149
 
5.2%
4122
 
5.1%
4114
 
5.1%
4056
 
5.1%
4053
 
5.1%
4053
 
5.1%
Other values (138) 33086
41.3%
Common
ValueCountFrequency (%)
21481
39.9%
, 6140
 
11.4%
1 5348
 
9.9%
) 4364
 
8.1%
( 4364
 
8.1%
2 2689
 
5.0%
3 2161
 
4.0%
4 2153
 
4.0%
6 1415
 
2.6%
5 1199
 
2.2%
Other values (8) 2479
 
4.6%
Latin
ValueCountFrequency (%)
S 225
40.7%
K 222
40.1%
B 61
 
11.0%
A 19
 
3.4%
T 7
 
1.3%
P 6
 
1.1%
D 3
 
0.5%
N 2
 
0.4%
G 2
 
0.4%
C 1
 
0.2%
Other values (5) 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80149
59.6%
ASCII 54346
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21481
39.5%
, 6140
 
11.3%
1 5348
 
9.8%
) 4364
 
8.0%
( 4364
 
8.0%
2 2689
 
4.9%
3 2161
 
4.0%
4 2153
 
4.0%
6 1415
 
2.6%
5 1199
 
2.2%
Other values (23) 3032
 
5.6%
Hangul
ValueCountFrequency (%)
8268
 
10.3%
5182
 
6.5%
4883
 
6.1%
4183
 
5.2%
4149
 
5.2%
4122
 
5.1%
4114
 
5.1%
4056
 
5.1%
4053
 
5.1%
4053
 
5.1%
Other values (138) 33086
41.3%

소재지(지번)
Text

MISSING 

Distinct489
Distinct (%)7.3%
Missing255
Missing (%)3.7%
Memory size54.7 KiB
2024-05-11T14:44:03.692318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length48
Mean length32.166444
Min length22

Characters and Unicode

Total characters216448
Distinct characters212
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)3.7%

Sample

1st row서울특별시 동대문구 청량리동 520번지 14호 (제기로 85)
2nd row서울특별시 동대문구 용두동 23번지 27호 (용우물4길7)
3rd row서울특별시 동대문구 용두동 23번지 27호
4th row서울특별시 동대문구 용두동 23번지 27호
5th row서울특별시 동대문구 용두동 23번지 27호
ValueCountFrequency (%)
서울특별시 6729
16.7%
동대문구 6729
16.7%
1호 1883
 
4.7%
전농동 1737
 
4.3%
용두동 1454
 
3.6%
지하2층 1384
 
3.4%
33번지 1353
 
3.4%
53호 1214
 
3.0%
591번지 1157
 
2.9%
장안동 1072
 
2.7%
Other values (712) 15605
38.7%
2024-05-11T14:44:04.335451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50271
23.2%
13515
 
6.2%
1 9394
 
4.3%
8938
 
4.1%
8265
 
3.8%
7185
 
3.3%
3 7142
 
3.3%
6811
 
3.1%
6788
 
3.1%
6738
 
3.1%
Other values (202) 91401
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122095
56.4%
Space Separator 50271
23.2%
Decimal Number 36641
 
16.9%
Open Punctuation 3419
 
1.6%
Close Punctuation 3419
 
1.6%
Dash Punctuation 301
 
0.1%
Uppercase Letter 207
 
0.1%
Other Punctuation 89
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13515
 
11.1%
8938
 
7.3%
8265
 
6.8%
7185
 
5.9%
6811
 
5.6%
6788
 
5.6%
6738
 
5.5%
6734
 
5.5%
6731
 
5.5%
6731
 
5.5%
Other values (167) 43659
35.8%
Uppercase Letter
ValueCountFrequency (%)
B 71
34.3%
S 39
18.8%
K 36
17.4%
D 28
 
13.5%
A 9
 
4.3%
T 7
 
3.4%
P 6
 
2.9%
N 2
 
1.0%
F 2
 
1.0%
G 2
 
1.0%
Other values (5) 5
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 9394
25.6%
3 7142
19.5%
2 4779
13.0%
5 4324
11.8%
9 2794
 
7.6%
0 2603
 
7.1%
6 1914
 
5.2%
4 1489
 
4.1%
8 1140
 
3.1%
7 1062
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 61
68.5%
/ 25
28.1%
3
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 2691
78.7%
[ 728
 
21.3%
Close Punctuation
ValueCountFrequency (%)
) 2691
78.7%
] 728
 
21.3%
Space Separator
ValueCountFrequency (%)
50271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 301
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122095
56.4%
Common 94146
43.5%
Latin 207
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13515
 
11.1%
8938
 
7.3%
8265
 
6.8%
7185
 
5.9%
6811
 
5.6%
6788
 
5.6%
6738
 
5.5%
6734
 
5.5%
6731
 
5.5%
6731
 
5.5%
Other values (167) 43659
35.8%
Common
ValueCountFrequency (%)
50271
53.4%
1 9394
 
10.0%
3 7142
 
7.6%
2 4779
 
5.1%
5 4324
 
4.6%
9 2794
 
3.0%
( 2691
 
2.9%
) 2691
 
2.9%
0 2603
 
2.8%
6 1914
 
2.0%
Other values (10) 5543
 
5.9%
Latin
ValueCountFrequency (%)
B 71
34.3%
S 39
18.8%
K 36
17.4%
D 28
 
13.5%
A 9
 
4.3%
T 7
 
3.4%
P 6
 
2.9%
N 2
 
1.0%
F 2
 
1.0%
G 2
 
1.0%
Other values (5) 5
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122095
56.4%
ASCII 94350
43.6%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50271
53.3%
1 9394
 
10.0%
3 7142
 
7.6%
2 4779
 
5.1%
5 4324
 
4.6%
9 2794
 
3.0%
( 2691
 
2.9%
) 2691
 
2.9%
0 2603
 
2.8%
6 1914
 
2.0%
Other values (24) 5747
 
6.1%
Hangul
ValueCountFrequency (%)
13515
 
11.1%
8938
 
7.3%
8265
 
6.8%
7185
 
5.9%
6811
 
5.6%
6788
 
5.6%
6738
 
5.5%
6734
 
5.5%
6731
 
5.5%
6731
 
5.5%
Other values (167) 43659
35.8%
None
ValueCountFrequency (%)
3
100.0%

업소전화번호
Text

MISSING 

Distinct371
Distinct (%)5.7%
Missing515
Missing (%)7.4%
Memory size54.7 KiB
2024-05-11T14:44:04.781651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.076364
Min length7

Characters and Unicode

Total characters65184
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

Unique190 ?
Unique (%)2.9%

Sample

1st row0209660420
2nd row02 9648387
3rd row02 9648387
4th row02 9648387
5th row02 9648387
ValueCountFrequency (%)
02 1929
22.1%
0221738153 1145
13.1%
0237064711 1049
 
12.0%
9591234 660
 
7.6%
0222487800 257
 
2.9%
0269082123 219
 
2.5%
0221738000 196
 
2.2%
9581002 188
 
2.2%
9695930 183
 
2.1%
0222467292 181
 
2.1%
Other values (380) 2721
31.2%
2024-05-11T14:44:05.712883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14100
21.6%
0 10582
16.2%
1 7339
11.3%
7 5898
9.0%
3 5826
8.9%
9 4317
 
6.6%
4 4296
 
6.6%
5 3709
 
5.7%
6 3539
 
5.4%
8 2993
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62599
96.0%
Space Separator 2585
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14100
22.5%
0 10582
16.9%
1 7339
11.7%
7 5898
9.4%
3 5826
9.3%
9 4317
 
6.9%
4 4296
 
6.9%
5 3709
 
5.9%
6 3539
 
5.7%
8 2993
 
4.8%
Space Separator
ValueCountFrequency (%)
2585
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14100
21.6%
0 10582
16.2%
1 7339
11.3%
7 5898
9.0%
3 5826
8.9%
9 4317
 
6.6%
4 4296
 
6.6%
5 3709
 
5.7%
6 3539
 
5.4%
8 2993
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14100
21.6%
0 10582
16.2%
1 7339
11.3%
7 5898
9.0%
3 5826
8.9%
9 4317
 
6.6%
4 4296
 
6.6%
5 3709
 
5.7%
6 3539
 
5.4%
8 2993
 
4.6%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
위생점검(전체)
3141 
수거
2483 
<NA>
720 
위생점검(부분)
640 

Length

Max length8
Median length8
Mean length5.4544674
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위생점검(전체) 3141
45.0%
수거 2483
35.6%
<NA> 720
 
10.3%
위생점검(부분) 640
 
9.2%

Length

2024-05-11T14:44:05.938976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:06.099542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위생점검(전체 3141
45.0%
수거 2483
35.6%
na 720
 
10.3%
위생점검(부분 640
 
9.2%

점검일자
Real number (ℝ)

Distinct324
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20142845
Minimum20061120
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:44:06.302458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20061120
5-th percentile20090806
Q120110727
median20131209
Q320171130
95-th percentile20201117
Maximum20240314
Range179194
Interquartile range (IQR)60403

Descriptive statistics

Standard deviation38207.242
Coefficient of variation (CV)0.0018968146
Kurtosis-0.75595138
Mean20142845
Median Absolute Deviation (MAD)30012
Skewness0.42680769
Sum1.4067763 × 1011
Variance1.4597933 × 109
MonotonicityNot monotonic
2024-05-11T14:44:06.508035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161221 447
 
6.4%
20120320 204
 
2.9%
20111005 134
 
1.9%
20110517 126
 
1.8%
20121023 124
 
1.8%
20151111 116
 
1.7%
20090414 86
 
1.2%
20111014 84
 
1.2%
20091104 82
 
1.2%
20090611 80
 
1.1%
Other values (314) 5501
78.8%
ValueCountFrequency (%)
20061120 1
 
< 0.1%
20070621 4
 
0.1%
20070730 2
 
< 0.1%
20070731 1
 
< 0.1%
20090109 4
 
0.1%
20090119 18
 
0.3%
20090213 52
0.7%
20090414 86
1.2%
20090522 5
 
0.1%
20090609 45
0.6%
ValueCountFrequency (%)
20240314 25
0.4%
20240312 1
 
< 0.1%
20240311 2
 
< 0.1%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240226 1
 
< 0.1%
20240215 15
0.2%
20240116 2
 
< 0.1%
20240112 2
 
< 0.1%
20231114 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
수시
3969 
기타
2112 
<NA>
720 
합동
 
121
일제
 
62

Length

Max length4
Median length2
Mean length2.2061856
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 3969
56.8%
기타 2112
30.2%
<NA> 720
 
10.3%
합동 121
 
1.7%
일제 62
 
0.9%

Length

2024-05-11T14:44:06.735932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:06.913024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 3969
56.8%
기타 2112
30.2%
na 720
 
10.3%
합동 121
 
1.7%
일제 62
 
0.9%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6984
Missing (%)100.0%
Memory size61.5 KiB

점검결과코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.7 KiB
1
6215 
<NA>
720 
2
 
49

Length

Max length4
Median length1
Mean length1.3092784
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 6215
89.0%
<NA> 720
 
10.3%
2 49
 
0.7%

Length

2024-05-11T14:44:07.063893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:44:07.213939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6215
89.0%
na 720
 
10.3%
2 49
 
0.7%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct171
Distinct (%)83.8%
Missing6780
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean19827213
Minimum0
Maximum20150329
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size61.5 KiB
2024-05-11T14:44:07.375835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20111120
Q120120506
median20121019
Q320130404
95-th percentile20131024
Maximum20150329
Range20150329
Interquartile range (IQR)9898.25

Descriptive statistics

Standard deviation2428165.9
Coefficient of variation (CV)0.12246632
Kurtosis64.616041
Mean19827213
Median Absolute Deviation (MAD)699.5
Skewness-8.1229342
Sum4.0447515 × 109
Variance5.8959898 × 1012
MonotonicityNot monotonic
2024-05-11T14:44:07.586884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111219 4
 
0.1%
20121027 3
 
< 0.1%
20111220 3
 
< 0.1%
20120310 3
 
< 0.1%
20121011 3
 
< 0.1%
20121003 2
 
< 0.1%
20121017 2
 
< 0.1%
20121206 2
 
< 0.1%
20120921 2
 
< 0.1%
20121019 2
 
< 0.1%
Other values (161) 178
 
2.5%
(Missing) 6780
97.1%
ValueCountFrequency (%)
0 1
< 0.1%
3 1
< 0.1%
2011 1
< 0.1%
20100127 1
< 0.1%
20110517 1
< 0.1%
20110723 1
< 0.1%
20111015 1
< 0.1%
20111018 1
< 0.1%
20111020 1
< 0.1%
20111022 1
< 0.1%
ValueCountFrequency (%)
20150329 1
< 0.1%
20141007 2
< 0.1%
20140612 1
< 0.1%
20131226 1
< 0.1%
20131221 1
< 0.1%
20131205 1
< 0.1%
20131201 1
< 0.1%
20131130 1
< 0.1%
20131117 1
< 0.1%
20131026 1
< 0.1%
Distinct164
Distinct (%)49.7%
Missing6654
Missing (%)95.3%
Memory size54.7 KiB
2024-05-11T14:44:07.975520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length13.463636
Min length5

Characters and Unicode

Total characters4443
Distinct characters172
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)32.7%

Sample

1st row서울시 동대문구 답십리동474
2nd row서울시 동대문구 답십리동474
3rd row서울시 동대문구 답십리동474
4th row서울시 동대문구 답십리동474
5th row서울시 동대문구 답십리동474
ValueCountFrequency (%)
경기도 63
 
5.8%
서울시 46
 
4.2%
안양시 31
 
2.9%
동안구 27
 
2.5%
충북 26
 
2.4%
영등포구 23
 
2.1%
평촌동 22
 
2.0%
서초구 22
 
2.0%
중구 19
 
1.8%
동대문구 18
 
1.7%
Other values (260) 788
72.6%
2024-05-11T14:44:08.526492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
756
 
17.0%
305
 
6.9%
226
 
5.1%
214
 
4.8%
1 123
 
2.8%
98
 
2.2%
- 95
 
2.1%
92
 
2.1%
83
 
1.9%
83
 
1.9%
Other values (162) 2368
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3011
67.8%
Space Separator 756
 
17.0%
Decimal Number 575
 
12.9%
Dash Punctuation 95
 
2.1%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
305
 
10.1%
226
 
7.5%
214
 
7.1%
98
 
3.3%
92
 
3.1%
83
 
2.8%
83
 
2.8%
72
 
2.4%
71
 
2.4%
67
 
2.2%
Other values (148) 1700
56.5%
Decimal Number
ValueCountFrequency (%)
1 123
21.4%
3 81
14.1%
5 79
13.7%
2 64
11.1%
6 44
 
7.7%
4 40
 
7.0%
7 39
 
6.8%
0 38
 
6.6%
8 35
 
6.1%
9 32
 
5.6%
Space Separator
ValueCountFrequency (%)
756
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3011
67.8%
Common 1432
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
305
 
10.1%
226
 
7.5%
214
 
7.1%
98
 
3.3%
92
 
3.1%
83
 
2.8%
83
 
2.8%
72
 
2.4%
71
 
2.4%
67
 
2.2%
Other values (148) 1700
56.5%
Common
ValueCountFrequency (%)
756
52.8%
1 123
 
8.6%
- 95
 
6.6%
3 81
 
5.7%
5 79
 
5.5%
2 64
 
4.5%
6 44
 
3.1%
4 40
 
2.8%
7 39
 
2.7%
0 38
 
2.7%
Other values (4) 73
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3011
67.8%
ASCII 1432
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
756
52.8%
1 123
 
8.6%
- 95
 
6.6%
3 81
 
5.7%
5 79
 
5.5%
2 64
 
4.5%
6 44
 
3.1%
4 40
 
2.8%
7 39
 
2.7%
0 38
 
2.7%
Other values (4) 73
 
5.1%
Hangul
ValueCountFrequency (%)
305
 
10.1%
226
 
7.5%
214
 
7.1%
98
 
3.3%
92
 
3.1%
83
 
2.8%
83
 
2.8%
72
 
2.4%
71
 
2.4%
67
 
2.2%
Other values (148) 1700
56.5%

부적합항목
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing6979
Missing (%)99.9%
Memory size54.7 KiB
2024-05-11T14:44:08.748859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9
Mean length9.2
Min length3

Characters and Unicode

Total characters46
Distinct characters29
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row한우유전자 불일치
2nd row금속성이물 검출
3rd row카페인
4th row금속성이물 검출
5th row금속성이물(기준치 10mg/kg)
ValueCountFrequency (%)
금속성이물 2
22.2%
검출 2
22.2%
한우유전자 1
11.1%
불일치 1
11.1%
카페인 1
11.1%
금속성이물(기준치 1
11.1%
10mg/kg 1
11.1%
2024-05-11T14:44:09.197685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
8.7%
3
 
6.5%
3
 
6.5%
3
 
6.5%
3
 
6.5%
3
 
6.5%
2
 
4.3%
2
 
4.3%
2
 
4.3%
g 2
 
4.3%
Other values (19) 19
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
71.7%
Space Separator 4
 
8.7%
Lowercase Letter 4
 
8.7%
Decimal Number 2
 
4.3%
Other Punctuation 1
 
2.2%
Open Punctuation 1
 
2.2%
Close Punctuation 1
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
Other values (10) 10
30.3%
Lowercase Letter
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
k 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
71.7%
Common 9
 
19.6%
Latin 4
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
Other values (10) 10
30.3%
Common
ValueCountFrequency (%)
4
44.4%
1 1
 
11.1%
/ 1
 
11.1%
0 1
 
11.1%
( 1
 
11.1%
) 1
 
11.1%
Latin
ValueCountFrequency (%)
g 2
50.0%
m 1
25.0%
k 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
71.7%
ASCII 13
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
30.8%
g 2
15.4%
1 1
 
7.7%
/ 1
 
7.7%
0 1
 
7.7%
m 1
 
7.7%
( 1
 
7.7%
k 1
 
7.7%
) 1
 
7.7%
Hangul
ValueCountFrequency (%)
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
3
 
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
Other values (10) 10
30.3%
Distinct3
Distinct (%)100.0%
Missing6981
Missing (%)> 99.9%
Memory size54.7 KiB
2024-05-11T14:44:09.402308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.3333333
Min length3

Characters and Unicode

Total characters22
Distinct characters14
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row68.6mg 검출
2nd row120
3rd row150.6mg/kg
ValueCountFrequency (%)
68.6mg 1
25.0%
검출 1
25.0%
120 1
25.0%
150.6mg/kg 1
25.0%
2024-05-11T14:44:09.752792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 3
13.6%
g 3
13.6%
. 2
9.1%
m 2
9.1%
1 2
9.1%
0 2
9.1%
8 1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (4) 4
18.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
45.5%
Lowercase Letter 6
27.3%
Other Punctuation 3
 
13.6%
Other Letter 2
 
9.1%
Space Separator 1
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3
30.0%
1 2
20.0%
0 2
20.0%
8 1
 
10.0%
2 1
 
10.0%
5 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
g 3
50.0%
m 2
33.3%
k 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
63.6%
Latin 6
27.3%
Hangul 2
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
6 3
21.4%
. 2
14.3%
1 2
14.3%
0 2
14.3%
8 1
 
7.1%
1
 
7.1%
2 1
 
7.1%
5 1
 
7.1%
/ 1
 
7.1%
Latin
ValueCountFrequency (%)
g 3
50.0%
m 2
33.3%
k 1
 
16.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
90.9%
Hangul 2
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 3
15.0%
g 3
15.0%
. 2
10.0%
m 2
10.0%
1 2
10.0%
0 2
10.0%
8 1
 
5.0%
1
 
5.0%
2 1
 
5.0%
5 1
 
5.0%
Other values (2) 2
10.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

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
03050000101일반음식점<NA><NA><NA><NA><NA><NA>홍능갈비집19Z000000<NA><NA>냉면육수<NA><NA><NA>200907161.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19760042003<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 청량리동 520번지 14호 (제기로 85)0209660420수거20090716수시<NA>1<NA><NA><NA><NA>
13050000101일반음식점<NA><NA><NA><NA>2011-식-13<NA>마포회관121000000식육류중육류<NA>한우 등심<NA><NA><NA>20111118200.0g<NA><NA><NA><NA><NA><NA><NA><NA><NA>001한우 등심국내<NA>120111122201111281<NA><NA><NA><NA><NA><NA>19800042051<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 23번지 27호 (용우물4길7)02 9648387수거20111118기타<NA>1<NA><NA><NA><NA>
23050000101일반음식점<NA><NA><NA>다소비 식품 수거 검사동대문-음식점-13증거용마포회관121000000식육류중육류소고기한우듬심<NA>소고기<NA>201304302.0100g<NA>20130430<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19800042051<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로28길 7, (용두동)서울특별시 동대문구 용두동 23번지 27호02 9648387<NA>20130430<NA><NA><NA><NA><NA><NA><NA>
33050000101일반음식점<NA><NA><NA>다소비 식품 수거 검사동대문-음식점-43압류마포회관121000000식육류중육류소고기한우등심<NA>소고기<NA>201306272.0100g<NA>20130627<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>19800042051<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로28길 7, (용두동)서울특별시 동대문구 용두동 23번지 27호02 9648387<NA>20130627<NA><NA><NA><NA><NA><NA><NA>
43050000101일반음식점999<NA>2018년 정육식당 등 한우고기 취급 전문 음식점에 대한 원산지 표시 및 위생지도 점검 계획<NA>동대문-축-2검사용마포회관B0103000000000기타축산물기타축산물한우등심<NA><NA><NA>201804301.0100g<NA>20180430<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>19800042051<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로28길 7, (용두동)서울특별시 동대문구 용두동 23번지 27호02 9648387위생점검(전체)20180430수시<NA>1<NA><NA><NA><NA>
53050000101일반음식점999<NA>2018년 정육식당 등 한우고기 취급 전문 음식점에 대한 원산지 표시 및 위생지도 점검 계획<NA>동대문-축-3검사용마포회관B0103000000000기타축산물기타축산물한우 설깃<NA><NA><NA>201804301.0100g<NA>20180430<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>19800042051<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로28길 7, (용두동)서울특별시 동대문구 용두동 23번지 27호02 9648387위생점검(전체)20180430수시<NA>1<NA><NA><NA><NA>
63050000101일반음식점<NA><NA><NA><NA><NA><NA>국가대표바지락손칼국수<NA><NA>콩국물<NA><NA><NA>201006171000.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19820042103<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 448번지 1호 (장평2길 5-1)0222492626<NA>20100624<NA><NA><NA><NA><NA><NA><NA>
73050000101일반음식점2<NA>여름철 다소비 식품 수거검사 계획<NA>동대문-조리-48검사용김밥천국G0100000100000조리식품 등조리식품 등김밥은<NA><NA><NA>201908261.0600g<NA>20190826<NA><NA><NA>실온<NA><NA>001<NA>국내<NA>220190826201909061<NA><NA><NA><NA><NA><NA>19820042093<NA><NA><NA><NA><NA>서울특별시 동대문구 망우로 83, (휘경동,(망우로 193))서울특별시 동대문구 휘경동 270번지 1호 (망우로 193)0222422035위생점검(전체)20190826수시<NA>1<NA><NA><NA><NA>
83050000101일반음식점2<NA>여름철 다소비 식품 수거검사 계획<NA>동대문-조리-49검사용김밥천국G0100000100000조리식품 등조리식품 등비빔국수<NA><NA><NA>201908261.0600g<NA>20190826<NA><NA><NA>실온<NA><NA>001<NA>국내<NA>220190826201909061<NA><NA><NA><NA><NA><NA>19820042093<NA><NA><NA><NA><NA>서울특별시 동대문구 망우로 83, (휘경동,(망우로 193))서울특별시 동대문구 휘경동 270번지 1호 (망우로 193)0222422035위생점검(전체)20190826수시<NA>1<NA><NA><NA><NA>
93050000101일반음식점2<NA>여름철 다소비 식품 수거검사 계획<NA>동대문-조리-50검사용김밥천국G0100000100000조리식품 등조리식품 등잔치국수<NA><NA><NA>201908261.0600g<NA>20190826<NA><NA><NA>실온<NA><NA>001<NA>국내<NA>220190826201909061<NA><NA><NA><NA><NA><NA>19820042093<NA><NA><NA><NA><NA>서울특별시 동대문구 망우로 83, (휘경동,(망우로 193))서울특별시 동대문구 휘경동 270번지 1호 (망우로 193)0222422035위생점검(전체)20190826수시<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
69743050000134건강기능식품일반판매업<NA><NA><NA><NA>106-5-5검사용썬라이더롯데백화점청량리점X0100026100000일반원료일반원료씨트릭씨탭<NA><NA><NA>202005064.0126g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외미국120200508202006281<NA><NA><NA><NA><NA><NA>20130042300<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 214, 지하2층 (전농동, 롯데백화점청량리점)서울특별시 동대문구 전농동 591번지 53호 롯데백화점청량리점지하202 15881234<NA>20200506<NA><NA><NA><NA><NA><NA><NA>
69753050000134건강기능식품일반판매업<NA><NA><NA><NA>106-4-15검사용파워스 코프레이션E0101500000000칼슘칼슘닥터칼슘플러스<NA><NA><NA>20190416<NA><NA><NA>144g*2=288g<NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120190419201906141<NA><NA><NA><NA>칼슘,마그네슘 적합<NA>20150042720<NA><NA><NA><NA><NA>서울특별시 동대문구 답십리로 266, 2~3층 (장안동, 린여성병원)서울특별시 동대문구 장안동 370번지 1호02 22441212위생점검(전체)20190416수시<NA>1<NA><NA><NA><NA>
69763050000134건강기능식품일반판매업<NA><NA><NA><NA>106-4-19검사용(주)레인보우앤네이처코리아E0205800000000히알루론산히알루론산히알루론산젤리<NA><NA><NA>20190417<NA><NA><NA>560g*2=1120g<NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120190419201906141<NA><NA><NA><NA><NA><NA>20160042640<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 지하 2층 (전농동)서울특별시 동대문구 전농동 591번지 53호 청량리역,롯데백화점<NA>위생점검(전체)20190417수시<NA>1<NA><NA><NA><NA>
69773050000134건강기능식품일반판매업<NA><NA><NA><NA>106-4-16검사용씨제이올리브네트윅스(주) 신설동역점E0203600000000난소화성말토덱스트린난소화성말토덱스트린프롬바이오와일드망고젤리<NA><NA><NA>20190416<NA><NA><NA>300g*3=900g<NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120190419201906141<NA><NA><NA><NA>비타민B6, 대장균군 적합<NA>20160042921<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 4, 지상1층 (신설동)서울특별시 동대문구 신설동 101번지 6호<NA>위생점검(전체)20190416수시<NA>1<NA><NA><NA><NA>
69783050000134건강기능식품일반판매업<NA><NA><NA><NA>106-5-7검사용씨제이올리브영(주) 장한평역점X0100026100000일반원료일반원료고려은단비타민C1000<NA><NA><NA>202005084.0129.6g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120200508202006281<NA><NA><NA><NA><NA><NA>20170042011<NA><NA><NA><NA><NA>서울특별시 동대문구 장한로 3, (장안동)서울특별시 동대문구 장안동 416번지 5호02 22122490<NA>20200508<NA><NA><NA><NA><NA><NA><NA>
69793050000134건강기능식품일반판매업<NA><NA><NA><NA>106-5-10검사용더페이스샵홈플러스동대문점엔씨X0100026100000일반원료일반원료프리미엄비타민C1000<NA><NA><NA>20200508432.0216g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120200508202006281<NA><NA><NA><NA><NA><NA>20180042687<NA><NA><NA><NA><NA>서울특별시 동대문구 천호대로 133, 홈플러스 동대문점 지하1층 (용두동)서울특별시 동대문구 용두동 33번지 1호 홈플러스 동대문점<NA><NA>20200508<NA><NA><NA><NA><NA><NA><NA>
69803050000134건강기능식품일반판매업<NA><NA><NA><NA>106-4-20검사용뉴트라라이프X0100026100000일반원료일반원료프리미엄키즈칼슘꾸미<NA><NA><NA>20190417<NA><NA><NA>460*2=920g<NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120190419201906141<NA><NA><NA><NA><NA><NA>20190042181<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 지하2층 (전농동)서울특별시 동대문구 전농동 591번지 53호 청량리역,롯데백화점<NA>위생점검(전체)20190417수시<NA>1<NA><NA><NA><NA>
69813050000134건강기능식품일반판매업<NA><NA><NA><NA>106-5-2검사용뉴트라라이프X0100026100000일반원료일반원료프리미엄종합비타민&amp;미네랄<NA><NA><NA>202005062.0270g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120200508202006281<NA><NA><NA><NA><NA><NA>20190042181<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 지하2층 (전농동)서울특별시 동대문구 전농동 591번지 53호 청량리역,롯데백화점<NA><NA>20200511<NA><NA><NA><NA><NA><NA><NA>
69823050000134건강기능식품일반판매업999<NA>기타 일상단속(식품안전팀)<NA>106-6-1검사용천삼향기C0309010300000고형차고형차보리새싹분말<NA><NA><NA>202006187.0150g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>220200619202007022<NA><NA><NA><NA><NA><NA>20200042334<NA><NA><NA><NA><NA>서울특별시 동대문구 정릉천동로 123, 102호 (제기동)서울특별시 동대문구 제기동 1191번지<NA>수거20200618기타<NA>1<NA><NA><NA><NA>
69833050000134건강기능식품일반판매업<NA><NA><NA><NA>106-4-2검사용(주)콜라지코리아E0205100000000프로바이오틱스프로바이오틱스프리미엄 프로바이오틱스 유산균19<NA><NA><NA>202304044.060g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120230405<NA><NA><NA><NA><NA><NA><NA><NA>20230057211<NA><NA><NA><NA><NA>서울특별시 동대문구 왕산로 214, 청량리역,롯데백화점 지하2층 (전농동)서울특별시 동대문구 전농동 591번지 53호 청량리역,롯데백화점031 3929586<NA>20230407<NA><NA><NA><NA><NA><NA><NA>

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시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용# duplicates
93050000112식품자동판매기영업<NA><NA><NA><NA><NA>동대문홈플러스<NA><NA>밀크커피<NA><NA><NA>20101116300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>20030043049<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 33번지 1호 (하정로137)0234539622<NA>20101117<NA><NA><NA><NA><NA><NA>7
173050000112식품자동판매기영업<NA><NA><NA><NA><NA>한국마사회동대문지점<NA><NA>커피<NA><NA><NA>20100512300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20050043261<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 신설동 117번지 4호 (난계로5)0262333671<NA>20100519<NA><NA><NA><NA><NA><NA>7
13050000112식품자동판매기영업<NA><NA><NA><NA><NA>(주)예신퍼슨스기술지원본부<NA><NA>커피<NA><NA><NA>20100511300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20050042693<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 368번지 1호 (답십리길288)<NA><NA>20100519<NA><NA><NA><NA><NA><NA>6
23050000112식품자동판매기영업<NA><NA><NA><NA><NA>경주사업본부 장안매점<NA><NA>커피<NA><NA><NA>20100512300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20000043102<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 462번지 0호 (장평1길19)0222473654<NA>20100519<NA><NA><NA><NA><NA><NA>5
73050000112식품자동판매기영업<NA><NA><NA><NA><NA>동대문종합사회복지관<NA><NA>커피<NA><NA><NA>20100512300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20100042407<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 제기동 220번지 동대문종합사회복지관<NA><NA>20100519<NA><NA><NA><NA><NA><NA>5
163050000112식품자동판매기영업<NA><NA><NA><NA><NA>하나벤딩(주)<NA><NA>밀크커피<NA><NA><NA>20101116300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>20100043134<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 620번지 69호 롯데백화점내5792520<NA>20101116<NA><NA><NA><NA><NA><NA>5
153050000112식품자동판매기영업<NA><NA><NA><NA><NA>하나벤딩(주)<NA><NA>밀크커피<NA><NA><NA>20101116300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>20080042392<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 591번지 53호 롯데백화점내<NA><NA>20101117<NA><NA><NA><NA><NA><NA>4
43050000112식품자동판매기영업<NA><NA><NA><NA><NA>경희의료원817000000커피액상커피커피(자판기)<NA><NA><NA>200907211.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20070042517<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 회기동 1번지 (청량새싹길21)<NA>수거20090721수시1<NA><NA><NA><NA>3
53050000112식품자동판매기영업<NA><NA><NA><NA><NA>구민회관(시설공단)<NA><NA>커피<NA><NA><NA>20100511300.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20040042590<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 354번지 5호 (장안둑길77)0222479659<NA>20100519<NA><NA><NA><NA><NA><NA>3
133050000112식품자동판매기영업<NA><NA><NA><NA><NA>서울시립대학교817000000커피액상커피커피(자판기)<NA><NA><NA>200907211.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>20000043052<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 90번지 0호 (시립대길13)0222102724수거20090721수시1<NA><NA><NA><NA>3