Overview

Dataset statistics

Number of variables61
Number of observations8136
Missing cells198258
Missing cells (%)39.9%
Duplicate rows9
Duplicate rows (%)0.1%
Total size in memory4.0 MiB
Average record size in memory516.0 B

Variable types

Categorical21
Numeric11
Unsupported9
Text20

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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-10609/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
제조일자(롯트) has constant value ""Constant
폐기방법 has constant value ""Constant
Dataset has 9 (0.1%) duplicate rowsDuplicates
업종명 is highly imbalanced (66.4%)Imbalance
계획구분코드 is highly imbalanced (69.4%)Imbalance
지도점검계획 is highly imbalanced (75.7%)Imbalance
수거사유코드 is highly imbalanced (56.1%)Imbalance
수거량(자유) is highly imbalanced (95.0%)Imbalance
어린이기호식품유형 is highly imbalanced (99.4%)Imbalance
국가명 is highly imbalanced (92.5%)Imbalance
처리결과 is highly imbalanced (96.9%)Imbalance
폐기일자 is highly imbalanced (99.8%)Imbalance
폐기량(Kg) is highly imbalanced (99.8%)Imbalance
계획구분명 has 8136 (100.0%) missing valuesMissing
수거증번호 has 1221 (15.0%) missing valuesMissing
식품군 has 774 (9.5%) missing valuesMissing
품목명 has 536 (6.6%) missing valuesMissing
음식물명 has 7933 (97.5%) missing valuesMissing
원료명 has 8044 (98.9%) missing valuesMissing
생산업소 has 7180 (88.2%) missing valuesMissing
수거량(정량) has 199 (2.4%) missing valuesMissing
제품규격(정량) has 1420 (17.5%) missing valuesMissing
제조일자(일자) has 6810 (83.7%) missing valuesMissing
제조일자(롯트) has 8135 (> 99.9%) missing valuesMissing
유통기한(일자) has 7893 (97.0%) missing valuesMissing
유통기한(제조일기준) has 8126 (99.9%) missing valuesMissing
바코드번호 has 8136 (100.0%) missing valuesMissing
(구)제조사명 has 6449 (79.3%) missing valuesMissing
검사의뢰일자 has 4679 (57.5%) missing valuesMissing
결과회보일자 has 6310 (77.6%) missing valuesMissing
처리구분 has 8136 (100.0%) missing valuesMissing
수거검사구분코드 has 8136 (100.0%) missing valuesMissing
단속지역구분코드 has 8136 (100.0%) missing valuesMissing
수거장소구분코드 has 8136 (100.0%) missing valuesMissing
수거품처리 has 8136 (100.0%) missing valuesMissing
폐기금액(원) has 8136 (100.0%) missing valuesMissing
폐기장소 has 8134 (> 99.9%) missing valuesMissing
폐기방법 has 8134 (> 99.9%) missing valuesMissing
소재지(도로명) has 711 (8.7%) missing valuesMissing
소재지(지번) has 275 (3.4%) missing valuesMissing
업소전화번호 has 1620 (19.9%) missing valuesMissing
점검내용 has 8136 (100.0%) missing valuesMissing
(구)제조유통기한 has 7893 (97.0%) missing valuesMissing
(구)제조회사주소 has 6292 (77.3%) missing valuesMissing
부적합항목 has 8132 (> 99.9%) missing valuesMissing
기준치부적합내용 has 8132 (> 99.9%) missing valuesMissing
수거량(정량) is highly skewed (γ1 = 23.39215105)Skewed
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
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:53:33.698733
Analysis finished2024-05-11 05:53:38.720890
Duration5.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
3190000
8136 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 8136
100.0%

Length

2024-05-11T14:53:38.883839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:39.096433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 8136
100.0%

업종코드
Real number (ℝ)

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.18265
Minimum101
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:39.262686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1114
median114
Q3114
95-th percentile114
Maximum135
Range34
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.6005877
Coefficient of variation (CV)0.041009799
Kurtosis2.9399692
Mean112.18265
Median Absolute Deviation (MAD)0
Skewness-1.022949
Sum912718
Variance21.165407
MonotonicityIncreasing
2024-05-11T14:53:39.457213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
114 6389
78.5%
101 716
 
8.8%
105 501
 
6.2%
104 114
 
1.4%
112 103
 
1.3%
107 87
 
1.1%
121 70
 
0.9%
106 43
 
0.5%
120 37
 
0.5%
113 34
 
0.4%
Other values (4) 42
 
0.5%
ValueCountFrequency (%)
101 716
 
8.8%
104 114
 
1.4%
105 501
 
6.2%
106 43
 
0.5%
107 87
 
1.1%
110 7
 
0.1%
111 1
 
< 0.1%
112 103
 
1.3%
113 34
 
0.4%
114 6389
78.5%
ValueCountFrequency (%)
135 3
 
< 0.1%
134 31
 
0.4%
121 70
 
0.9%
120 37
 
0.5%
114 6389
78.5%
113 34
 
0.4%
112 103
 
1.3%
111 1
 
< 0.1%
110 7
 
0.1%
107 87
 
1.1%

업종명
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
기타식품판매업
6389 
일반음식점
716 
집단급식소
 
501
휴게음식점
 
114
식품자동판매기영업
 
103
Other values (9)
 
313

Length

Max length13
Median length7
Mean length6.7169371
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 6389
78.5%
일반음식점 716
 
8.8%
집단급식소 501
 
6.2%
휴게음식점 114
 
1.4%
식품자동판매기영업 103
 
1.3%
즉석판매제조가공업 87
 
1.1%
제과점영업 70
 
0.9%
식품제조가공업 43
 
0.5%
위탁급식영업 37
 
0.5%
유통전문판매업 34
 
0.4%
Other values (4) 42
 
0.5%

Length

2024-05-11T14:53:39.717228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 6389
78.5%
일반음식점 716
 
8.8%
집단급식소 501
 
6.2%
휴게음식점 114
 
1.4%
식품자동판매기영업 103
 
1.3%
즉석판매제조가공업 87
 
1.1%
제과점영업 70
 
0.9%
식품제조가공업 43
 
0.5%
위탁급식영업 37
 
0.5%
유통전문판매업 34
 
0.4%
Other values (5) 49
 
0.6%

계획구분코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
6714 
999
1260 
2
 
62
7
 
49
5
 
47

Length

Max length4
Median length4
Mean length3.7853982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row7
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6714
82.5%
999 1260
 
15.5%
2 62
 
0.8%
7 49
 
0.6%
5 47
 
0.6%
1 4
 
< 0.1%

Length

2024-05-11T14:53:39.930728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:40.147064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6714
82.5%
999 1260
 
15.5%
2 62
 
0.8%
7 49
 
0.6%
5 47
 
0.6%
1 4
 
< 0.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
6714 
2016년 식품안전관리 계획
 
635
2012 식품수거 계획
 
201
민원처리
 
156
음식점 원산지표시 지도점검
 
109
Other values (23)
 
321

Length

Max length28
Median length4
Mean length5.6913717
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row2017. 개고기 조리.판매업소 위생점검
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 6714
82.5%
2016년 식품안전관리 계획 635
 
7.8%
2012 식품수거 계획 201
 
2.5%
민원처리 156
 
1.9%
음식점 원산지표시 지도점검 109
 
1.3%
2017년 식품안전관리계획 80
 
1.0%
초콜릿 및 캔디류 판매업소 점검계획 47
 
0.6%
2015 음식점 원산지표시 지도점검 31
 
0.4%
여름철 성수식품 수거검사 및 지도점검 계획 31
 
0.4%
식품접객업소 지도점검 24
 
0.3%
Other values (18) 108
 
1.3%

Length

2024-05-11T14:53:40.368923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6714
62.2%
계획 888
 
8.2%
식품안전관리 636
 
5.9%
2016년 635
 
5.9%
지도점검 230
 
2.1%
2012 201
 
1.9%
식품수거 201
 
1.9%
민원처리 156
 
1.4%
원산지표시 143
 
1.3%
음식점 140
 
1.3%
Other values (57) 850
 
7.9%

수거계획
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
3861 
식품수거검사계획
1975 
2017년 유통식품 수거검사 계획
543 
2020년 일상수거검사
399 
2021년 유통식품 수거검사
 
335
Other values (11)
1023 

Length

Max length28
Median length23
Mean length8.2325467
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3861
47.5%
식품수거검사계획 1975
24.3%
2017년 유통식품 수거검사 계획 543
 
6.7%
2020년 일상수거검사 399
 
4.9%
2021년 유통식품 수거검사 335
 
4.1%
여름철 성수식품 수거검사 280
 
3.4%
2018년 유통식품 수거검사 계획 265
 
3.3%
2023 유통식품 수거검사 193
 
2.4%
2019년 유통식품수거검사 계획 114
 
1.4%
2024년 유통식품 수거검사 92
 
1.1%
Other values (6) 79
 
1.0%

Length

2024-05-11T14:53:40.595361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3861
29.2%
식품수거검사계획 1975
14.9%
수거검사 1740
13.2%
유통식품 1428
 
10.8%
계획 928
 
7.0%
2017년 543
 
4.1%
2020년 399
 
3.0%
일상수거검사 399
 
3.0%
2021년 341
 
2.6%
성수식품 280
 
2.1%
Other values (28) 1331
 
10.1%

수거증번호
Text

MISSING 

Distinct4167
Distinct (%)60.3%
Missing1221
Missing (%)15.0%
Memory size63.7 KiB
2024-05-11T14:53:41.279869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.3702097
Min length1

Characters and Unicode

Total characters57880
Distinct characters75
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

Unique3135 ?
Unique (%)45.3%

Sample

1st row12010181
2nd row120-9-22-1
3rd row120-9-22-2
4th row120-9-22-3
5th row120-9-22-4
ValueCountFrequency (%)
120-10-23 9
 
0.1%
120-10-19 8
 
0.1%
120-10-12 8
 
0.1%
120-10-17 8
 
0.1%
특별관리 8
 
0.1%
120-10-14 8
 
0.1%
120-10-24 8
 
0.1%
120-10-21 8
 
0.1%
120-10-20 8
 
0.1%
120-10-22 8
 
0.1%
Other values (4156) 6843
98.8%
2024-05-11T14:53:42.139838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 12974
22.4%
1 12408
21.4%
2 10551
18.2%
0 8421
14.5%
3 2571
 
4.4%
5 2105
 
3.6%
4 2051
 
3.5%
7 1760
 
3.0%
6 1647
 
2.8%
8 1474
 
2.5%
Other values (65) 1918
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44296
76.5%
Dash Punctuation 12974
 
22.4%
Other Letter 516
 
0.9%
Uppercase Letter 44
 
0.1%
Other Punctuation 26
 
< 0.1%
Space Separator 9
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 75
14.5%
작 75
14.5%
관 30
 
5.8%
별 30
 
5.8%
특 30
 
5.8%
리 29
 
5.6%
위 28
 
5.4%
원 24
 
4.7%
구 17
 
3.3%
생 17
 
3.3%
Other values (45) 161
31.2%
Decimal Number
ValueCountFrequency (%)
1 12408
28.0%
2 10551
23.8%
0 8421
19.0%
3 2571
 
5.8%
5 2105
 
4.8%
4 2051
 
4.6%
7 1760
 
4.0%
6 1647
 
3.7%
8 1474
 
3.3%
9 1308
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
M 15
34.1%
G 15
34.1%
O 9
20.5%
C 5
 
11.4%
Dash Punctuation
ValueCountFrequency (%)
- 12974
100.0%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57320
99.0%
Hangul 516
 
0.9%
Latin 44
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 75
14.5%
작 75
14.5%
관 30
 
5.8%
별 30
 
5.8%
특 30
 
5.8%
리 29
 
5.6%
위 28
 
5.4%
원 24
 
4.7%
구 17
 
3.3%
생 17
 
3.3%
Other values (45) 161
31.2%
Common
ValueCountFrequency (%)
- 12974
22.6%
1 12408
21.6%
2 10551
18.4%
0 8421
14.7%
3 2571
 
4.5%
5 2105
 
3.7%
4 2051
 
3.6%
7 1760
 
3.1%
6 1647
 
2.9%
8 1474
 
2.6%
Other values (6) 1358
 
2.4%
Latin
ValueCountFrequency (%)
M 15
34.1%
G 15
34.1%
O 9
20.5%
C 5
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57364
99.1%
Hangul 516
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 12974
22.6%
1 12408
21.6%
2 10551
18.4%
0 8421
14.7%
3 2571
 
4.5%
5 2105
 
3.7%
4 2051
 
3.6%
7 1760
 
3.1%
6 1647
 
2.9%
8 1474
 
2.6%
Other values (10) 1402
 
2.4%
Hangul
ValueCountFrequency (%)
동 75
14.5%
작 75
14.5%
관 30
 
5.8%
별 30
 
5.8%
특 30
 
5.8%
리 29
 
5.6%
위 28
 
5.4%
원 24
 
4.7%
구 17
 
3.3%
생 17
 
3.3%
Other values (45) 161
31.2%

수거사유코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
검사용
5889 
<NA>
2221 
기타
 
13
압류
 
13

Length

Max length4
Median length3
Mean length3.2697886
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 5889
72.4%
<NA> 2221
 
27.3%
기타 13
 
0.2%
압류 13
 
0.2%

Length

2024-05-11T14:53:42.409885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:42.610946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 5889
72.4%
na 2221
 
27.3%
기타 13
 
0.2%
압류 13
 
0.2%

업소명
Text

Distinct499
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-05-11T14:53:43.011399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length7.1045969
Min length2

Characters and Unicode

Total characters57803
Distinct characters460
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)2.8%

Sample

1st row안동장
2nd row춘하추동
3rd row진주식당
4th row진주식당
5th row진주식당
ValueCountFrequency (%)
진로마트 2091
20.9%
성대유통(주 742
 
7.4%
수협바다마트노량진점 688
 
6.9%
월드마트 680
 
6.8%
성대지마트주식회사 509
 
5.1%
상도 333
 
3.3%
후레쉬 333
 
3.3%
마트 333
 
3.3%
이수점 327
 
3.3%
주)이마트 321
 
3.2%
Other values (557) 3649
36.5%
2024-05-11T14:53:43.782659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 5142
 
8.9%
트 5067
 
8.8%
진 2867
 
5.0%
로 2337
 
4.0%
주 2242
 
3.9%
점 2136
 
3.7%
1871
 
3.2%
) 1859
 
3.2%
( 1859
 
3.2%
성 1426
 
2.5%
Other values (450) 30997
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51726
89.5%
Space Separator 1871
 
3.2%
Close Punctuation 1859
 
3.2%
Open Punctuation 1859
 
3.2%
Decimal Number 341
 
0.6%
Lowercase Letter 72
 
0.1%
Uppercase Letter 70
 
0.1%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 5142
 
9.9%
트 5067
 
9.8%
진 2867
 
5.5%
로 2337
 
4.5%
주 2242
 
4.3%
점 2136
 
4.1%
성 1426
 
2.8%
대 1401
 
2.7%
수 1142
 
2.2%
협 986
 
1.9%
Other values (406) 26980
52.2%
Uppercase Letter
ValueCountFrequency (%)
K 15
21.4%
F 12
17.1%
C 11
15.7%
S 8
11.4%
A 4
 
5.7%
O 4
 
5.7%
T 2
 
2.9%
P 2
 
2.9%
E 2
 
2.9%
G 2
 
2.9%
Other values (7) 8
11.4%
Lowercase Letter
ValueCountFrequency (%)
a 22
30.6%
d 17
23.6%
n 17
23.6%
c 3
 
4.2%
e 2
 
2.8%
m 2
 
2.8%
h 2
 
2.8%
r 2
 
2.8%
y 1
 
1.4%
w 1
 
1.4%
Other values (3) 3
 
4.2%
Decimal Number
ValueCountFrequency (%)
3 233
68.3%
2 55
 
16.1%
1 20
 
5.9%
0 14
 
4.1%
4 9
 
2.6%
5 4
 
1.2%
7 4
 
1.2%
6 2
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
? 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1871
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1859
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1859
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51724
89.5%
Common 5935
 
10.3%
Latin 142
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 5142
 
9.9%
트 5067
 
9.8%
진 2867
 
5.5%
로 2337
 
4.5%
주 2242
 
4.3%
점 2136
 
4.1%
성 1426
 
2.8%
대 1401
 
2.7%
수 1142
 
2.2%
협 986
 
1.9%
Other values (404) 26978
52.2%
Latin
ValueCountFrequency (%)
a 22
15.5%
d 17
12.0%
n 17
12.0%
K 15
10.6%
F 12
8.5%
C 11
 
7.7%
S 8
 
5.6%
A 4
 
2.8%
O 4
 
2.8%
c 3
 
2.1%
Other values (20) 29
20.4%
Common
ValueCountFrequency (%)
1871
31.5%
) 1859
31.3%
( 1859
31.3%
3 233
 
3.9%
2 55
 
0.9%
1 20
 
0.3%
0 14
 
0.2%
4 9
 
0.2%
5 4
 
0.1%
7 4
 
0.1%
Other values (4) 7
 
0.1%
Han
ValueCountFrequency (%)
牛 1
50.0%
火 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51724
89.5%
ASCII 6077
 
10.5%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 5142
 
9.9%
트 5067
 
9.8%
진 2867
 
5.5%
로 2337
 
4.5%
주 2242
 
4.3%
점 2136
 
4.1%
성 1426
 
2.8%
대 1401
 
2.7%
수 1142
 
2.2%
협 986
 
1.9%
Other values (404) 26978
52.2%
ASCII
ValueCountFrequency (%)
1871
30.8%
) 1859
30.6%
( 1859
30.6%
3 233
 
3.8%
2 55
 
0.9%
a 22
 
0.4%
1 20
 
0.3%
d 17
 
0.3%
n 17
 
0.3%
K 15
 
0.2%
Other values (34) 109
 
1.8%
CJK
ValueCountFrequency (%)
牛 1
50.0%
火 1
50.0%

식품군코드
Text

Distinct357
Distinct (%)4.4%
Missing2
Missing (%)< 0.1%
Memory size63.7 KiB
2024-05-11T14:53:44.168215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length11.171011
Min length1

Characters and Unicode

Total characters90865
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)1.0%

Sample

1st row
2nd rowG0100000100000
3rd row
4th row
5th row
ValueCountFrequency (%)
g0100000100000 444
 
5.8%
801000000 358
 
4.7%
818000000 349
 
4.6%
821000000 263
 
3.4%
600000000 229
 
3.0%
830000000 208
 
2.7%
803000000 199
 
2.6%
816000000 190
 
2.5%
829000000 182
 
2.4%
121000000 167
 
2.2%
Other values (345) 5080
66.2%
2024-05-11T14:53:44.764539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59829
65.8%
1 8565
 
9.4%
2 4098
 
4.5%
4089
 
4.5%
8 3884
 
4.3%
C 3092
 
3.4%
3 2819
 
3.1%
4 981
 
1.1%
5 712
 
0.8%
6 654
 
0.7%
Other values (11) 2142
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82827
91.2%
Space Separator 4089
 
4.5%
Uppercase Letter 3949
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59829
72.2%
1 8565
 
10.3%
2 4098
 
4.9%
8 3884
 
4.7%
3 2819
 
3.4%
4 981
 
1.2%
5 712
 
0.9%
6 654
 
0.8%
7 646
 
0.8%
9 639
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 3092
78.3%
G 649
 
16.4%
A 63
 
1.6%
F 39
 
1.0%
E 32
 
0.8%
B 28
 
0.7%
H 26
 
0.7%
D 11
 
0.3%
X 7
 
0.2%
Z 2
 
0.1%
Space Separator
ValueCountFrequency (%)
4089
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86916
95.7%
Latin 3949
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59829
68.8%
1 8565
 
9.9%
2 4098
 
4.7%
4089
 
4.7%
8 3884
 
4.5%
3 2819
 
3.2%
4 981
 
1.1%
5 712
 
0.8%
6 654
 
0.8%
7 646
 
0.7%
Latin
ValueCountFrequency (%)
C 3092
78.3%
G 649
 
16.4%
A 63
 
1.6%
F 39
 
1.0%
E 32
 
0.8%
B 28
 
0.7%
H 26
 
0.7%
D 11
 
0.3%
X 7
 
0.2%
Z 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90865
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59829
65.8%
1 8565
 
9.4%
2 4098
 
4.5%
4089
 
4.5%
8 3884
 
4.3%
C 3092
 
3.4%
3 2819
 
3.1%
4 981
 
1.1%
5 712
 
0.8%
6 654
 
0.7%
Other values (11) 2142
 
2.4%

식품군
Text

MISSING 

Distinct266
Distinct (%)3.6%
Missing774
Missing (%)9.5%
Memory size63.7 KiB
2024-05-11T14:53:45.374878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length19
Mean length4.7377071
Min length1

Characters and Unicode

Total characters34879
Distinct characters295
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

Unique64 ?
Unique (%)0.9%

Sample

1st row조리식품 등
2nd row식품접객업
3rd row식품접객업
4th row식품접객업
5th row식품접객업
ValueCountFrequency (%)
등 474
 
5.7%
조리식품 444
 
5.3%
과자류 418
 
5.0%
음료류 358
 
4.3%
조미식품 326
 
3.9%
식품접객업 229
 
2.7%
기타식품류 209
 
2.5%
규격외일반가공식품 208
 
2.5%
코코아가공품류또는초콜릿류 201
 
2.4%
다류 190
 
2.3%
Other values (287) 5312
63.5%
2024-05-11T14:53:46.249644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 3511
 
10.1%
품 2673
 
7.7%
식 2279
 
6.5%
가 1217
 
3.5%
공 1101
 
3.2%
조 1030
 
3.0%
1007
 
2.9%
기 755
 
2.2%
리 709
 
2.0%
과 648
 
1.9%
Other values (285) 19949
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33278
95.4%
Space Separator 1007
 
2.9%
Other Punctuation 192
 
0.6%
Close Punctuation 181
 
0.5%
Open Punctuation 181
 
0.5%
Uppercase Letter 27
 
0.1%
Dash Punctuation 8
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 3511
 
10.6%
품 2673
 
8.0%
식 2279
 
6.8%
가 1217
 
3.7%
공 1101
 
3.3%
조 1030
 
3.1%
기 755
 
2.3%
리 709
 
2.1%
과 648
 
1.9%
자 568
 
1.7%
Other values (266) 18787
56.5%
Uppercase Letter
ValueCountFrequency (%)
C 8
29.6%
L 6
22.2%
A 4
14.8%
B 4
14.8%
D 2
 
7.4%
P 1
 
3.7%
E 1
 
3.7%
H 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 91
47.4%
, 90
46.9%
/ 8
 
4.2%
? 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 1
 
20.0%
6 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1007
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Open Punctuation
ValueCountFrequency (%)
( 181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33278
95.4%
Common 1574
 
4.5%
Latin 27
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 3511
 
10.6%
품 2673
 
8.0%
식 2279
 
6.8%
가 1217
 
3.7%
공 1101
 
3.3%
조 1030
 
3.1%
기 755
 
2.3%
리 709
 
2.1%
과 648
 
1.9%
자 568
 
1.7%
Other values (266) 18787
56.5%
Common
ValueCountFrequency (%)
1007
64.0%
) 181
 
11.5%
( 181
 
11.5%
. 91
 
5.8%
, 90
 
5.7%
/ 8
 
0.5%
- 8
 
0.5%
1 3
 
0.2%
? 3
 
0.2%
2 1
 
0.1%
Latin
ValueCountFrequency (%)
C 8
29.6%
L 6
22.2%
A 4
14.8%
B 4
14.8%
D 2
 
7.4%
P 1
 
3.7%
E 1
 
3.7%
H 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33278
95.4%
ASCII 1601
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 3511
 
10.6%
품 2673
 
8.0%
식 2279
 
6.8%
가 1217
 
3.7%
공 1101
 
3.3%
조 1030
 
3.1%
기 755
 
2.3%
리 709
 
2.1%
과 648
 
1.9%
자 568
 
1.7%
Other values (266) 18787
56.5%
ASCII
ValueCountFrequency (%)
1007
62.9%
) 181
 
11.3%
( 181
 
11.3%
. 91
 
5.7%
, 90
 
5.6%
C 8
 
0.5%
/ 8
 
0.5%
- 8
 
0.5%
L 6
 
0.4%
A 4
 
0.2%
Other values (9) 17
 
1.1%

품목명
Text

MISSING 

Distinct344
Distinct (%)4.5%
Missing536
Missing (%)6.6%
Memory size63.7 KiB
2024-05-11T14:53:46.762754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length28
Mean length4.7372368
Min length1

Characters and Unicode

Total characters36003
Distinct characters334
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

Unique85 ?
Unique (%)1.1%

Sample

1st row조리식품 등
2nd row접객용 음용수
3rd row접객용 음용수
4th row기타
5th row기타
ValueCountFrequency (%)
등 619
 
6.9%
조리식품 598
 
6.7%
과자 254
 
2.8%
소스류 227
 
2.5%
초콜릿가공품 217
 
2.4%
기타가공품 201
 
2.2%
곡류가공품 183
 
2.0%
캔디류 181
 
2.0%
소스 158
 
1.8%
혼합음료 146
 
1.6%
Other values (367) 6172
68.9%
2024-05-11T14:53:47.532143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 2018
 
5.6%
류 1619
 
4.5%
1356
 
3.8%
식 1299
 
3.6%
조 1285
 
3.6%
가 1174
 
3.3%
리 1065
 
3.0%
기 1023
 
2.8%
공 1013
 
2.8%
소 823
 
2.3%
Other values (324) 23328
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33129
92.0%
Space Separator 1356
 
3.8%
Open Punctuation 527
 
1.5%
Close Punctuation 527
 
1.5%
Other Punctuation 389
 
1.1%
Uppercase Letter 32
 
0.1%
Decimal Number 24
 
0.1%
Dash Punctuation 11
 
< 0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 2018
 
6.1%
류 1619
 
4.9%
식 1299
 
3.9%
조 1285
 
3.9%
가 1174
 
3.5%
리 1065
 
3.2%
기 1023
 
3.1%
공 1013
 
3.1%
소 823
 
2.5%
등 757
 
2.3%
Other values (299) 21053
63.5%
Uppercase Letter
ValueCountFrequency (%)
C 9
28.1%
L 7
21.9%
A 6
18.8%
B 5
15.6%
D 2
 
6.2%
P 1
 
3.1%
E 1
 
3.1%
H 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 263
67.6%
, 115
29.6%
/ 7
 
1.8%
? 3
 
0.8%
: 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 20
83.3%
2 2
 
8.3%
4 1
 
4.2%
6 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
r 2
25.0%
l 2
25.0%
c 2
25.0%
y 2
25.0%
Space Separator
ValueCountFrequency (%)
1356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 527
100.0%
Close Punctuation
ValueCountFrequency (%)
) 527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33129
92.0%
Common 2834
 
7.9%
Latin 40
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 2018
 
6.1%
류 1619
 
4.9%
식 1299
 
3.9%
조 1285
 
3.9%
가 1174
 
3.5%
리 1065
 
3.2%
기 1023
 
3.1%
공 1013
 
3.1%
소 823
 
2.5%
등 757
 
2.3%
Other values (299) 21053
63.5%
Common
ValueCountFrequency (%)
1356
47.8%
( 527
 
18.6%
) 527
 
18.6%
. 263
 
9.3%
, 115
 
4.1%
1 20
 
0.7%
- 11
 
0.4%
/ 7
 
0.2%
? 3
 
0.1%
2 2
 
0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
C 9
22.5%
L 7
17.5%
A 6
15.0%
B 5
12.5%
D 2
 
5.0%
r 2
 
5.0%
l 2
 
5.0%
c 2
 
5.0%
y 2
 
5.0%
P 1
 
2.5%
Other values (2) 2
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33129
92.0%
ASCII 2874
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 2018
 
6.1%
류 1619
 
4.9%
식 1299
 
3.9%
조 1285
 
3.9%
가 1174
 
3.5%
리 1065
 
3.2%
기 1023
 
3.1%
공 1013
 
3.1%
소 823
 
2.5%
등 757
 
2.3%
Other values (299) 21053
63.5%
ASCII
ValueCountFrequency (%)
1356
47.2%
( 527
 
18.3%
) 527
 
18.3%
. 263
 
9.2%
, 115
 
4.0%
1 20
 
0.7%
- 11
 
0.4%
C 9
 
0.3%
L 7
 
0.2%
/ 7
 
0.2%
Other values (15) 32
 
1.1%

제품명
Text

Distinct5241
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-05-11T14:53:48.070827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length7.3410767
Min length1

Characters and Unicode

Total characters59727
Distinct characters918
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

Unique4036 ?
Unique (%)49.6%

Sample

1st row콩국물
2nd row개고기 수육
3rd row수족관수
4th row도마
5th row칼
ValueCountFrequency (%)
한우 237
 
2.0%
청정원 152
 
1.3%
백설 78
 
0.7%
커피 72
 
0.6%
등심 67
 
0.6%
음용수 49
 
0.4%
오뚜기 46
 
0.4%
차돌박이 39
 
0.3%
부침가루 37
 
0.3%
도마 36
 
0.3%
Other values (5582) 10858
93.0%
2024-05-11T14:53:48.768951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3555
 
6.0%
스 1504
 
2.5%
이 1076
 
1.8%
리 967
 
1.6%
기 787
 
1.3%
드 751
 
1.3%
오 689
 
1.2%
레 667
 
1.1%
고 653
 
1.1%
카 645
 
1.1%
Other values (908) 48433
81.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52978
88.7%
Space Separator 3555
 
6.0%
Decimal Number 892
 
1.5%
Uppercase Letter 573
 
1.0%
Lowercase Letter 571
 
1.0%
Close Punctuation 416
 
0.7%
Open Punctuation 416
 
0.7%
Other Punctuation 281
 
0.5%
Dash Punctuation 36
 
0.1%
Math Symbol 5
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1504
 
2.8%
이 1076
 
2.0%
리 967
 
1.8%
기 787
 
1.5%
드 751
 
1.4%
오 689
 
1.3%
레 667
 
1.3%
고 653
 
1.2%
카 645
 
1.2%
한 635
 
1.2%
Other values (832) 44604
84.2%
Uppercase Letter
ValueCountFrequency (%)
E 53
 
9.2%
A 49
 
8.6%
S 46
 
8.0%
O 41
 
7.2%
L 40
 
7.0%
C 38
 
6.6%
M 35
 
6.1%
I 26
 
4.5%
N 26
 
4.5%
B 24
 
4.2%
Other values (14) 195
34.0%
Lowercase Letter
ValueCountFrequency (%)
a 78
13.7%
s 54
 
9.5%
i 50
 
8.8%
e 47
 
8.2%
p 42
 
7.4%
r 39
 
6.8%
m 36
 
6.3%
w 32
 
5.6%
x 23
 
4.0%
h 21
 
3.7%
Other values (13) 149
26.1%
Other Punctuation
ValueCountFrequency (%)
, 61
21.7%
/ 55
19.6%
% 43
15.3%
& 40
14.2%
. 27
9.6%
? 15
 
5.3%
; 13
 
4.6%
？ 13
 
4.6%
! 8
 
2.8%
' 3
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 309
34.6%
1 246
27.6%
3 91
 
10.2%
2 73
 
8.2%
9 43
 
4.8%
5 42
 
4.7%
7 28
 
3.1%
8 21
 
2.4%
6 20
 
2.2%
4 19
 
2.1%
Math Symbol
ValueCountFrequency (%)
+ 4
80.0%
~ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3555
100.0%
Close Punctuation
ValueCountFrequency (%)
) 416
100.0%
Open Punctuation
ValueCountFrequency (%)
( 416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52974
88.7%
Common 5601
 
9.4%
Latin 1146
 
1.9%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1504
 
2.8%
이 1076
 
2.0%
리 967
 
1.8%
기 787
 
1.5%
드 751
 
1.4%
오 689
 
1.3%
레 667
 
1.3%
고 653
 
1.2%
카 645
 
1.2%
한 635
 
1.2%
Other values (830) 44600
84.2%
Latin
ValueCountFrequency (%)
a 78
 
6.8%
s 54
 
4.7%
E 53
 
4.6%
i 50
 
4.4%
A 49
 
4.3%
e 47
 
4.1%
S 46
 
4.0%
p 42
 
3.7%
O 41
 
3.6%
L 40
 
3.5%
Other values (38) 646
56.4%
Common
ValueCountFrequency (%)
3555
63.5%
) 416
 
7.4%
( 416
 
7.4%
0 309
 
5.5%
1 246
 
4.4%
3 91
 
1.6%
2 73
 
1.3%
, 61
 
1.1%
/ 55
 
1.0%
9 43
 
0.8%
Other values (17) 336
 
6.0%
Han
ValueCountFrequency (%)
眞 3
50.0%
大 2
33.3%
純 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52971
88.7%
ASCII 6732
 
11.3%
None 15
 
< 0.1%
CJK 6
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3555
52.8%
) 416
 
6.2%
( 416
 
6.2%
0 309
 
4.6%
1 246
 
3.7%
3 91
 
1.4%
a 78
 
1.2%
2 73
 
1.1%
, 61
 
0.9%
/ 55
 
0.8%
Other values (63) 1432
21.3%
Hangul
ValueCountFrequency (%)
스 1504
 
2.8%
이 1076
 
2.0%
리 967
 
1.8%
기 787
 
1.5%
드 751
 
1.4%
오 689
 
1.3%
레 667
 
1.3%
고 653
 
1.2%
카 645
 
1.2%
한 635
 
1.2%
Other values (828) 44597
84.2%
None
ValueCountFrequency (%)
？ 13
86.7%
㈜ 2
 
13.3%
CJK
ValueCountFrequency (%)
眞 3
50.0%
大 2
33.3%
純 1
 
16.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

음식물명
Text

MISSING 

Distinct111
Distinct (%)54.7%
Missing7933
Missing (%)97.5%
Memory size63.7 KiB
2024-05-11T14:53:49.200989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.7339901
Min length1

Characters and Unicode

Total characters758
Distinct characters189
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

Unique92 ?
Unique (%)45.3%

Sample

1st row수족관수
2nd row도마
3rd row칼
4th row행주
5th row음용수
ValueCountFrequency (%)
커피 19
 
9.3%
보존식 11
 
5.4%
수족관수 10
 
4.9%
음용수 10
 
4.9%
냉면육수 9
 
4.4%
배추김치 9
 
4.4%
율무차 7
 
3.4%
쿠키 5
 
2.4%
먹는샘물 5
 
2.4%
쌀밥 4
 
2.0%
Other values (103) 116
56.6%
2024-05-11T14:53:49.823702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 44
 
5.8%
커 20
 
2.6%
음 20
 
2.6%
피 20
 
2.6%
육 20
 
2.6%
치 19
 
2.5%
무 19
 
2.5%
추 18
 
2.4%
김 17
 
2.2%
식 15
 
2.0%
Other values (179) 546
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 749
98.8%
Space Separator 2
 
0.3%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Decimal Number 2
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 44
 
5.9%
커 20
 
2.7%
음 20
 
2.7%
피 20
 
2.7%
육 20
 
2.7%
치 19
 
2.5%
무 19
 
2.5%
추 18
 
2.4%
김 17
 
2.3%
식 15
 
2.0%
Other values (173) 537
71.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 749
98.8%
Common 9
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 44
 
5.9%
커 20
 
2.7%
음 20
 
2.7%
피 20
 
2.7%
육 20
 
2.7%
치 19
 
2.5%
무 19
 
2.5%
추 18
 
2.4%
김 17
 
2.3%
식 15
 
2.0%
Other values (173) 537
71.7%
Common
ValueCountFrequency (%)
2
22.2%
) 2
22.2%
( 2
22.2%
1 1
11.1%
5 1
11.1%
, 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 749
98.8%
ASCII 9
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 44
 
5.9%
커 20
 
2.7%
음 20
 
2.7%
피 20
 
2.7%
육 20
 
2.7%
치 19
 
2.5%
무 19
 
2.5%
추 18
 
2.4%
김 17
 
2.3%
식 15
 
2.0%
Other values (173) 537
71.7%
ASCII
ValueCountFrequency (%)
2
22.2%
) 2
22.2%
( 2
22.2%
1 1
11.1%
5 1
11.1%
, 1
11.1%

원료명
Text

MISSING 

Distinct58
Distinct (%)63.0%
Missing8044
Missing (%)98.9%
Memory size63.7 KiB
2024-05-11T14:53:50.151080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length7
Mean length4.0108696
Min length1

Characters and Unicode

Total characters369
Distinct characters100
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)47.8%

Sample

1st row한우 등심
2nd row한우 등심
3rd row한우 차돌박이
4th row한우 육회
5th row한우 등심
ValueCountFrequency (%)
한우 38
29.2%
등심 15
 
11.5%
차돌박이 4
 
3.1%
육회용 4
 
3.1%
육회 3
 
2.3%
콩 3
 
2.3%
무 3
 
2.3%
대추 2
 
1.5%
서리태 2
 
1.5%
깐도라지 2
 
1.5%
Other values (50) 54
41.5%
2024-05-11T14:53:50.684772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
10.6%
한 38
 
10.3%
우 38
 
10.3%
심 17
 
4.6%
등 15
 
4.1%
고 9
 
2.4%
육 7
 
1.9%
회 7
 
1.9%
추 7
 
1.9%
기 7
 
1.9%
Other values (90) 185
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 328
88.9%
Space Separator 39
 
10.6%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 38
 
11.6%
우 38
 
11.6%
심 17
 
5.2%
등 15
 
4.6%
고 9
 
2.7%
육 7
 
2.1%
회 7
 
2.1%
추 7
 
2.1%
기 7
 
2.1%
차 6
 
1.8%
Other values (87) 177
54.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 328
88.9%
Common 41
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 38
 
11.6%
우 38
 
11.6%
심 17
 
5.2%
등 15
 
4.6%
고 9
 
2.7%
육 7
 
2.1%
회 7
 
2.1%
추 7
 
2.1%
기 7
 
2.1%
차 6
 
1.8%
Other values (87) 177
54.0%
Common
ValueCountFrequency (%)
39
95.1%
( 1
 
2.4%
) 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 328
88.9%
ASCII 41
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
95.1%
( 1
 
2.4%
) 1
 
2.4%
Hangul
ValueCountFrequency (%)
한 38
 
11.6%
우 38
 
11.6%
심 17
 
5.2%
등 15
 
4.6%
고 9
 
2.7%
육 7
 
2.1%
회 7
 
2.1%
추 7
 
2.1%
기 7
 
2.1%
차 6
 
1.8%
Other values (87) 177
54.0%

생산업소
Text

MISSING 

Distinct296
Distinct (%)31.0%
Missing7180
Missing (%)88.2%
Memory size63.7 KiB
2024-05-11T14:53:50.985616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length24
Mean length6.5303347
Min length1

Characters and Unicode

Total characters6243
Distinct characters306
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

Unique148 ?
Unique (%)15.5%

Sample

1st row문송례
2nd row정원일
3rd row김밥25
4th row김밥25
5th row진경련
ValueCountFrequency (%)
주 85
 
7.5%
롯데칠성음료㈜ 39
 
3.4%
37
 
3.2%
롯데제과주식회사 35
 
3.1%
코카콜라음료㈜ 34
 
3.0%
동서식품 32
 
2.8%
씨제이제일제당 28
 
2.5%
㈜오뚜기 20
 
1.8%
씨제이제일제당(주 20
 
1.8%
샘표식품주식회사 20
 
1.8%
Other values (308) 790
69.3%
2024-05-11T14:53:51.521542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 327
 
5.2%
제 308
 
4.9%
주 308
 
4.9%
식 260
 
4.2%
) 216
 
3.5%
( 216
 
3.5%
184
 
2.9%
품 178
 
2.9%
료 152
 
2.4%
음 150
 
2.4%
Other values (296) 3944
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4866
77.9%
Other Symbol 327
 
5.2%
Lowercase Letter 221
 
3.5%
Close Punctuation 216
 
3.5%
Open Punctuation 216
 
3.5%
Space Separator 184
 
2.9%
Uppercase Letter 149
 
2.4%
Other Punctuation 39
 
0.6%
Decimal Number 25
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 308
 
6.3%
주 308
 
6.3%
식 260
 
5.3%
품 178
 
3.7%
료 152
 
3.1%
음 150
 
3.1%
과 120
 
2.5%
오 116
 
2.4%
사 111
 
2.3%
데 110
 
2.3%
Other values (246) 3053
62.7%
Uppercase Letter
ValueCountFrequency (%)
F 26
17.4%
B 16
10.7%
E 14
9.4%
C 12
 
8.1%
T 11
 
7.4%
S 11
 
7.4%
M 8
 
5.4%
G 7
 
4.7%
P 6
 
4.0%
V 6
 
4.0%
Other values (8) 32
21.5%
Lowercase Letter
ValueCountFrequency (%)
a 30
13.6%
e 29
13.1%
m 21
9.5%
p 20
9.0%
o 18
8.1%
r 18
8.1%
h 13
 
5.9%
n 13
 
5.9%
y 13
 
5.9%
s 12
 
5.4%
Other values (7) 34
15.4%
Decimal Number
ValueCountFrequency (%)
3 12
48.0%
2 6
24.0%
5 3
 
12.0%
1 2
 
8.0%
6 1
 
4.0%
0 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
; 15
38.5%
& 14
35.9%
. 4
 
10.3%
' 3
 
7.7%
/ 3
 
7.7%
Other Symbol
ValueCountFrequency (%)
㈜ 327
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Space Separator
ValueCountFrequency (%)
184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5193
83.2%
Common 680
 
10.9%
Latin 370
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 327
 
6.3%
제 308
 
5.9%
주 308
 
5.9%
식 260
 
5.0%
품 178
 
3.4%
료 152
 
2.9%
음 150
 
2.9%
과 120
 
2.3%
오 116
 
2.2%
사 111
 
2.1%
Other values (247) 3163
60.9%
Latin
ValueCountFrequency (%)
a 30
 
8.1%
e 29
 
7.8%
F 26
 
7.0%
m 21
 
5.7%
p 20
 
5.4%
o 18
 
4.9%
r 18
 
4.9%
B 16
 
4.3%
E 14
 
3.8%
h 13
 
3.5%
Other values (25) 165
44.6%
Common
ValueCountFrequency (%)
) 216
31.8%
( 216
31.8%
184
27.1%
; 15
 
2.2%
& 14
 
2.1%
3 12
 
1.8%
2 6
 
0.9%
. 4
 
0.6%
' 3
 
0.4%
/ 3
 
0.4%
Other values (4) 7
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4866
77.9%
ASCII 1050
 
16.8%
None 327
 
5.2%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 327
100.0%
Hangul
ValueCountFrequency (%)
제 308
 
6.3%
주 308
 
6.3%
식 260
 
5.3%
품 178
 
3.7%
료 152
 
3.1%
음 150
 
3.1%
과 120
 
2.5%
오 116
 
2.4%
사 111
 
2.3%
데 110
 
2.3%
Other values (246) 3053
62.7%
ASCII
ValueCountFrequency (%)
) 216
20.6%
( 216
20.6%
184
17.5%
a 30
 
2.9%
e 29
 
2.8%
F 26
 
2.5%
m 21
 
2.0%
p 20
 
1.9%
o 18
 
1.7%
r 18
 
1.7%
Other values (39) 272
25.9%

수거일자
Real number (ℝ)

Distinct432
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20147441
Minimum20080904
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:51.719859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080904
5-th percentile20090825
Q120111020
median20131120
Q320180201
95-th percentile20220215
Maximum20240305
Range159401
Interquartile range (IQR)69181

Descriptive statistics

Standard deviation40231.14
Coefficient of variation (CV)0.0019968362
Kurtosis-0.84530955
Mean20147441
Median Absolute Deviation (MAD)30002
Skewness0.46801871
Sum1.6391958 × 1011
Variance1.6185447 × 109
MonotonicityNot monotonic
2024-05-11T14:53:51.935095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200513 202
 
2.5%
20160808 173
 
2.1%
20170203 132
 
1.6%
20110411 130
 
1.6%
20121018 126
 
1.5%
20130725 126
 
1.5%
20121127 108
 
1.3%
20171205 108
 
1.3%
20131016 107
 
1.3%
20170216 103
 
1.3%
Other values (422) 6821
83.8%
ValueCountFrequency (%)
20080904 3
 
< 0.1%
20090116 14
 
0.2%
20090203 61
0.7%
20090209 23
 
0.3%
20090210 19
 
0.2%
20090223 24
 
0.3%
20090303 28
0.3%
20090325 25
0.3%
20090410 30
0.4%
20090430 3
 
< 0.1%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240227 3
 
< 0.1%
20240222 62
0.8%
20240129 6
 
0.1%
20240117 3
 
< 0.1%
20240116 30
0.4%
20231212 6
 
0.1%
20231208 4
 
< 0.1%
20231121 9
 
0.1%
20231120 67
0.8%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct116
Distinct (%)1.5%
Missing199
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean34.484623
Minimum1
Maximum12000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:52.096808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile8
Maximum12000
Range11999
Interquartile range (IQR)2

Descriptive statistics

Standard deviation289.85928
Coefficient of variation (CV)8.4054646
Kurtosis822.28678
Mean34.484623
Median Absolute Deviation (MAD)1
Skewness23.392151
Sum273704.45
Variance84018.4
MonotonicityNot monotonic
2024-05-11T14:53:52.280084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 2378
29.2%
2.0 2047
25.2%
3.0 1784
21.9%
4.0 483
 
5.9%
6.0 469
 
5.8%
5.0 284
 
3.5%
8.0 70
 
0.9%
7.0 57
 
0.7%
10.0 47
 
0.6%
1000.0 22
 
0.3%
Other values (106) 296
 
3.6%
(Missing) 199
 
2.4%
ValueCountFrequency (%)
1.0 2378
29.2%
2.0 2047
25.2%
2.45 1
 
< 0.1%
3.0 1784
21.9%
4.0 483
 
5.9%
5.0 284
 
3.5%
6.0 469
 
5.8%
7.0 57
 
0.7%
8.0 70
 
0.9%
9.0 19
 
0.2%
ValueCountFrequency (%)
12000.0 2
< 0.1%
7800.0 1
 
< 0.1%
3600.0 4
< 0.1%
3300.0 1
 
< 0.1%
3060.0 1
 
< 0.1%
3000.0 2
< 0.1%
2790.0 1
 
< 0.1%
2700.0 2
< 0.1%
2505.0 1
 
< 0.1%
2160.0 2
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct615
Distinct (%)9.2%
Missing1420
Missing (%)17.5%
Memory size63.7 KiB
2024-05-11T14:53:52.913967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0016379
Min length1

Characters and Unicode

Total characters20159
Distinct characters39
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique247 ?
Unique (%)3.7%

Sample

1st row600
2nd rowㅣ
3rd row개
4th row개
5th row개
ValueCountFrequency (%)
500 490
 
7.3%
600 390
 
5.8%
300 383
 
5.7%
1 323
 
4.8%
200 286
 
4.3%
100 285
 
4.2%
400 239
 
3.6%
900 223
 
3.3%
250 152
 
2.3%
150 141
 
2.1%
Other values (604) 3804
56.6%
2024-05-11T14:53:54.039448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7918
39.3%
5 2119
 
10.5%
1 2056
 
10.2%
2 1759
 
8.7%
3 1427
 
7.1%
6 941
 
4.7%
4 922
 
4.6%
g 704
 
3.5%
7 555
 
2.8%
9 520
 
2.6%
Other values (29) 1238
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18734
92.9%
Lowercase Letter 1148
 
5.7%
Other Punctuation 184
 
0.9%
Other Letter 67
 
0.3%
Other Symbol 19
 
0.1%
Uppercase Letter 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 704
61.3%
l 195
 
17.0%
m 186
 
16.2%
k 41
 
3.6%
ℓ 11
 
1.0%
c 6
 
0.5%
s 1
 
0.1%
p 1
 
0.1%
b 1
 
0.1%
o 1
 
0.1%
Other Letter
ValueCountFrequency (%)
개 35
52.2%
봉 10
 
14.9%
면 10
 
14.9%
매 5
 
7.5%
ㅣ 1
 
1.5%
터 1
 
1.5%
리 1
 
1.5%
입 1
 
1.5%
묶 1
 
1.5%
음 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
0 7918
42.3%
5 2119
 
11.3%
1 2056
 
11.0%
2 1759
 
9.4%
3 1427
 
7.6%
6 941
 
5.0%
4 922
 
4.9%
7 555
 
3.0%
9 520
 
2.8%
8 517
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 180
97.8%
, 4
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
K 2
50.0%
Other Symbol
ValueCountFrequency (%)
㎖ 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18951
94.0%
Latin 1141
 
5.7%
Hangul 67
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7918
41.8%
5 2119
 
11.2%
1 2056
 
10.8%
2 1759
 
9.3%
3 1427
 
7.5%
6 941
 
5.0%
4 922
 
4.9%
7 555
 
2.9%
9 520
 
2.7%
8 517
 
2.7%
Other values (6) 217
 
1.1%
Latin
ValueCountFrequency (%)
g 704
61.7%
l 195
 
17.1%
m 186
 
16.3%
k 41
 
3.6%
c 6
 
0.5%
D 2
 
0.2%
K 2
 
0.2%
s 1
 
0.1%
p 1
 
0.1%
b 1
 
0.1%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
개 35
52.2%
봉 10
 
14.9%
면 10
 
14.9%
매 5
 
7.5%
ㅣ 1
 
1.5%
터 1
 
1.5%
리 1
 
1.5%
입 1
 
1.5%
묶 1
 
1.5%
음 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20062
99.5%
Hangul 66
 
0.3%
CJK Compat 19
 
0.1%
Letterlike Symbols 11
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7918
39.5%
5 2119
 
10.6%
1 2056
 
10.2%
2 1759
 
8.8%
3 1427
 
7.1%
6 941
 
4.7%
4 922
 
4.6%
g 704
 
3.5%
7 555
 
2.8%
9 520
 
2.6%
Other values (16) 1141
 
5.7%
Hangul
ValueCountFrequency (%)
개 35
53.0%
봉 10
 
15.2%
면 10
 
15.2%
매 5
 
7.6%
터 1
 
1.5%
리 1
 
1.5%
입 1
 
1.5%
묶 1
 
1.5%
음 1
 
1.5%
통 1
 
1.5%
CJK Compat
ValueCountFrequency (%)
㎖ 19
100.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 11
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

단위(정량)
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
g
4107 
<NA>
2420 
ML
1131 
KG
 
247
LT
 
213

Length

Max length4
Median length1
Mean length2.087881
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 4107
50.5%
<NA> 2420
29.7%
ML 1131
 
13.9%
KG 247
 
3.0%
LT 213
 
2.6%
매 18
 
0.2%

Length

2024-05-11T14:53:54.284754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:54.485831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 4107
50.5%
na 2420
29.7%
ml 1131
 
13.9%
kg 247
 
3.0%
lt 213
 
2.6%
매 18
 
0.2%

수거량(자유)
Categorical

IMBALANCE 

Distinct29
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
7937 
1인분
 
77
3개
 
35
1개
 
25
햄버거 1개
 
12
Other values (24)
 
50

Length

Max length8
Median length4
Mean length3.9729597
Min length1

Unique

Unique15 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7937
97.6%
1인분 77
 
0.9%
3개 35
 
0.4%
1개 25
 
0.3%
햄버거 1개 12
 
0.1%
1ea 6
 
0.1%
10개 6
 
0.1%
10매 5
 
0.1%
1 5
 
0.1%
1묶음 4
 
< 0.1%
Other values (19) 24
 
0.3%

Length

2024-05-11T14:53:54.725575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7937
97.4%
1인분 77
 
0.9%
1개 37
 
0.5%
3개 35
 
0.4%
햄버거 12
 
0.1%
1ea 8
 
0.1%
10개 6
 
0.1%
1 6
 
0.1%
10매 5
 
0.1%
1묶음 4
 
< 0.1%
Other values (20) 25
 
0.3%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct321
Distinct (%)24.2%
Missing6810
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean20161649
Minimum20110930
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:54.998713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110930
5-th percentile20120420
Q120130621
median20161011
Q320180706
95-th percentile20230814
Maximum20240305
Range129375
Interquartile range (IQR)50085

Descriptive statistics

Standard deviation32751.765
Coefficient of variation (CV)0.0016244586
Kurtosis-0.32977001
Mean20161649
Median Absolute Deviation (MAD)20208
Skewness0.58128314
Sum2.6734347 × 1010
Variance1.0726781 × 109
MonotonicityNot monotonic
2024-05-11T14:53:55.277628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150718 77
 
0.9%
20121108 40
 
0.5%
20181211 39
 
0.5%
20181219 25
 
0.3%
20180201 21
 
0.3%
20130123 20
 
0.2%
20180623 18
 
0.2%
20170806 18
 
0.2%
20170804 18
 
0.2%
20170803 18
 
0.2%
Other values (311) 1032
 
12.7%
(Missing) 6810
83.7%
ValueCountFrequency (%)
20110930 1
 
< 0.1%
20120130 1
 
< 0.1%
20120207 14
0.2%
20120210 5
 
0.1%
20120215 2
 
< 0.1%
20120221 4
 
< 0.1%
20120320 6
 
0.1%
20120322 3
 
< 0.1%
20120327 16
0.2%
20120419 11
0.1%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240227 3
 
< 0.1%
20240129 6
0.1%
20240117 3
 
< 0.1%
20231212 6
0.1%
20231121 6
0.1%
20231116 1
 
< 0.1%
20231109 2
 
< 0.1%
20231103 1
 
< 0.1%
20231031 8
0.1%

제조일자(롯트)
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing8135
Missing (%)> 99.9%
Memory size63.7 KiB
2024-05-11T14:53:55.512244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row포장년월일 : 2021. 2. 18.
ValueCountFrequency (%)
포장년월일 1
20.0%
1
20.0%
2021 1
20.0%
2 1
20.0%
18 1
20.0%
2024-05-11T14:53:55.951192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
20.0%
2 3
15.0%
. 3
15.0%
1 2
10.0%
포 1
 
5.0%
장 1
 
5.0%
년 1
 
5.0%
월 1
 
5.0%
일 1
 
5.0%
: 1
 
5.0%
Other values (2) 2
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
35.0%
Other Letter 5
25.0%
Space Separator 4
20.0%
Other Punctuation 4
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 1
20.0%
장 1
20.0%
년 1
20.0%
월 1
20.0%
일 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
1 2
28.6%
0 1
 
14.3%
8 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
: 1
 
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
75.0%
Hangul 5
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4
26.7%
2 3
20.0%
. 3
20.0%
1 2
13.3%
: 1
 
6.7%
0 1
 
6.7%
8 1
 
6.7%
Hangul
ValueCountFrequency (%)
포 1
20.0%
장 1
20.0%
년 1
20.0%
월 1
20.0%
일 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
75.0%
Hangul 5
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
26.7%
2 3
20.0%
. 3
20.0%
1 2
13.3%
: 1
 
6.7%
0 1
 
6.7%
8 1
 
6.7%
Hangul
ValueCountFrequency (%)
포 1
20.0%
장 1
20.0%
년 1
20.0%
월 1
20.0%
일 1
20.0%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct173
Distinct (%)71.2%
Missing7893
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean19716484
Minimum0
Maximum20160920
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:56.196412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20110514
Q120111216
median20120502
Q320130265
95-th percentile20140695
Maximum20160920
Range20160920
Interquartile range (IQR)19049

Descriptive statistics

Standard deviation2804391.3
Coefficient of variation (CV)0.14223588
Kurtosis44.861341
Mean19716484
Median Absolute Deviation (MAD)9293
Skewness-6.8131053
Sum4.7911055 × 109
Variance7.8646106 × 1012
MonotonicityNot monotonic
2024-05-11T14:53:56.489248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110519 14
 
0.2%
20111218 7
 
0.1%
20111216 5
 
0.1%
20110513 5
 
0.1%
20111215 4
 
< 0.1%
20110818 4
 
< 0.1%
0 3
 
< 0.1%
20130706 3
 
< 0.1%
20140323 3
 
< 0.1%
20120208 3
 
< 0.1%
Other values (163) 192
 
2.4%
(Missing) 7893
97.0%
ValueCountFrequency (%)
0 3
 
< 0.1%
110621 1
 
< 0.1%
2010418 1
 
< 0.1%
20110418 2
 
< 0.1%
20110421 1
 
< 0.1%
20110513 5
 
0.1%
20110519 14
0.2%
20110527 1
 
< 0.1%
20110608 1
 
< 0.1%
20110627 2
 
< 0.1%
ValueCountFrequency (%)
20160920 1
< 0.1%
20160907 1
< 0.1%
20160822 1
< 0.1%
20160818 1
< 0.1%
20160510 1
< 0.1%
20141206 1
< 0.1%
20141122 1
< 0.1%
20141102 1
< 0.1%
20141021 1
< 0.1%
20141020 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)60.0%
Missing8126
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean2012173.7
Minimum3
Maximum20120903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:53:56.705342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q13
median9
Q348.5
95-th percentile11066825
Maximum20120903
Range20120900
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation6362758.9
Coefficient of variation (CV)3.162132
Kurtosis10
Mean2012173.7
Median Absolute Deviation (MAD)6
Skewness3.1622777
Sum20121737
Variance4.0484701 × 1013
MonotonicityNot monotonic
2024-05-11T14:53:56.929756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 4
 
< 0.1%
14 2
 
< 0.1%
60 1
 
< 0.1%
4 1
 
< 0.1%
20120903 1
 
< 0.1%
730 1
 
< 0.1%
(Missing) 8126
99.9%
ValueCountFrequency (%)
3 4
< 0.1%
4 1
 
< 0.1%
14 2
< 0.1%
60 1
 
< 0.1%
730 1
 
< 0.1%
20120903 1
 
< 0.1%
ValueCountFrequency (%)
20120903 1
 
< 0.1%
730 1
 
< 0.1%
60 1
 
< 0.1%
14 2
< 0.1%
4 1
 
< 0.1%
3 4
< 0.1%

보관상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
실온
5216 
<NA>
2221 
냉장
 
379
냉동
 
279
기타
 
41

Length

Max length4
Median length2
Mean length2.5459685
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 5216
64.1%
<NA> 2221
27.3%
냉장 379
 
4.7%
냉동 279
 
3.4%
기타 41
 
0.5%

Length

2024-05-11T14:53:57.180553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:57.437692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 5216
64.1%
na 2221
27.3%
냉장 379
 
4.7%
냉동 279
 
3.4%
기타 41
 
0.5%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

어린이기호식품유형
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
8129 
과자(한과류제외)
 
3
캔디류
 
3
빵류
 
1

Length

Max length9
Median length4
Mean length4.0012291
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8129
99.9%
과자(한과류제외) 3
 
< 0.1%
캔디류 3
 
< 0.1%
빵류 1
 
< 0.1%

Length

2024-05-11T14:53:57.638587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:57.824259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8129
99.9%
과자(한과류제외 3
 
< 0.1%
캔디류 3
 
< 0.1%
빵류 1
 
< 0.1%

검사기관명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
1
4543 
<NA>
3470 
0
 
123

Length

Max length4
Median length1
Mean length2.2794985
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4543
55.8%
<NA> 3470
42.6%
0 123
 
1.5%

Length

2024-05-11T14:53:58.022671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:58.214097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4543
55.8%
na 3470
42.6%
0 123
 
1.5%

(구)제조사명
Text

MISSING 

Distinct572
Distinct (%)33.9%
Missing6449
Missing (%)79.3%
Memory size63.7 KiB
2024-05-11T14:53:58.623954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length6.6318909
Min length2

Characters and Unicode

Total characters11188
Distinct characters377
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)18.0%

Sample

1st row진주식당
2nd row진주식당
3rd row진주식당
4th row진주식당
5th row진주식당
ValueCountFrequency (%)
동서식품 67
 
3.6%
㈜오뚜기 55
 
3.0%
씨제이제일제당(주 43
 
2.3%
씨제이제일제당㈜ 41
 
2.2%
롯데제과㈜ 39
 
2.1%
롯데칠성음료㈜ 36
 
2.0%
대상㈜ 29
 
1.6%
씨제이제일제당 26
 
1.4%
코카콜라음료㈜ 21
 
1.1%
롯데제과(주 20
 
1.1%
Other values (635) 1467
79.6%
2024-05-11T14:53:59.363540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 696
 
6.2%
제 594
 
5.3%
식 456
 
4.1%
주 444
 
4.0%
품 407
 
3.6%
) 346
 
3.1%
( 345
 
3.1%
이 203
 
1.8%
동 166
 
1.5%
오 163
 
1.5%
Other values (367) 7368
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8417
75.2%
Other Symbol 696
 
6.2%
Uppercase Letter 614
 
5.5%
Lowercase Letter 501
 
4.5%
Close Punctuation 346
 
3.1%
Open Punctuation 345
 
3.1%
Space Separator 157
 
1.4%
Other Punctuation 80
 
0.7%
Decimal Number 26
 
0.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 594
 
7.1%
식 456
 
5.4%
주 444
 
5.3%
품 407
 
4.8%
이 203
 
2.4%
동 166
 
2.0%
오 163
 
1.9%
씨 162
 
1.9%
과 155
 
1.8%
사 145
 
1.7%
Other values (304) 5522
65.6%
Uppercase Letter
ValueCountFrequency (%)
O 57
 
9.3%
F 55
 
9.0%
A 54
 
8.8%
N 45
 
7.3%
I 40
 
6.5%
C 40
 
6.5%
S 39
 
6.4%
H 35
 
5.7%
E 34
 
5.5%
T 34
 
5.5%
Other values (15) 181
29.5%
Lowercase Letter
ValueCountFrequency (%)
a 75
15.0%
e 55
11.0%
o 39
 
7.8%
p 35
 
7.0%
m 34
 
6.8%
l 33
 
6.6%
r 30
 
6.0%
i 27
 
5.4%
n 27
 
5.4%
s 27
 
5.4%
Other values (13) 119
23.8%
Other Punctuation
ValueCountFrequency (%)
; 24
30.0%
. 23
28.7%
& 22
27.5%
？ 5
 
6.2%
' 3
 
3.8%
, 3
 
3.8%
Decimal Number
ValueCountFrequency (%)
2 12
46.2%
1 6
23.1%
3 5
19.2%
4 3
 
11.5%
Other Symbol
ValueCountFrequency (%)
㈜ 696
100.0%
Close Punctuation
ValueCountFrequency (%)
) 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 345
100.0%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9113
81.5%
Latin 1115
 
10.0%
Common 960
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 696
 
7.6%
제 594
 
6.5%
식 456
 
5.0%
주 444
 
4.9%
품 407
 
4.5%
이 203
 
2.2%
동 166
 
1.8%
오 163
 
1.8%
씨 162
 
1.8%
과 155
 
1.7%
Other values (305) 5667
62.2%
Latin
ValueCountFrequency (%)
a 75
 
6.7%
O 57
 
5.1%
e 55
 
4.9%
F 55
 
4.9%
A 54
 
4.8%
N 45
 
4.0%
I 40
 
3.6%
C 40
 
3.6%
S 39
 
3.5%
o 39
 
3.5%
Other values (38) 616
55.2%
Common
ValueCountFrequency (%)
) 346
36.0%
( 345
35.9%
157
16.4%
; 24
 
2.5%
. 23
 
2.4%
& 22
 
2.3%
2 12
 
1.2%
- 6
 
0.6%
1 6
 
0.6%
？ 5
 
0.5%
Other values (4) 14
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8417
75.2%
ASCII 2070
 
18.5%
None 701
 
6.3%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 696
99.3%
？ 5
 
0.7%
Hangul
ValueCountFrequency (%)
제 594
 
7.1%
식 456
 
5.4%
주 444
 
5.3%
품 407
 
4.8%
이 203
 
2.4%
동 166
 
2.0%
오 163
 
1.9%
씨 162
 
1.9%
과 155
 
1.8%
사 145
 
1.7%
Other values (304) 5522
65.6%
ASCII
ValueCountFrequency (%)
) 346
16.7%
( 345
16.7%
157
 
7.6%
a 75
 
3.6%
O 57
 
2.8%
e 55
 
2.7%
F 55
 
2.7%
A 54
 
2.6%
N 45
 
2.2%
I 40
 
1.9%
Other values (51) 841
40.6%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
국내
6617 
국외
1519 

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 6617
81.3%
국외 1519
 
18.7%

Length

2024-05-11T14:53:59.653138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:59.825652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 6617
81.3%
국외 1519
 
18.7%

국가명
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
7838 
미국
 
70
중국
 
67
이탈리아
 
23
말레이지아
 
19
Other values (23)
 
119

Length

Max length9
Median length4
Mean length3.9525565
Min length2

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7838
96.3%
미국 70
 
0.9%
중국 67
 
0.8%
이탈리아 23
 
0.3%
말레이지아 19
 
0.2%
태국 18
 
0.2%
일본 17
 
0.2%
베트남 14
 
0.2%
독일 12
 
0.1%
스페인 9
 
0.1%
Other values (18) 49
 
0.6%

Length

2024-05-11T14:54:00.028875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7838
96.3%
미국 70
 
0.9%
중국 70
 
0.9%
이탈리아 23
 
0.3%
말레이지아 19
 
0.2%
태국 18
 
0.2%
일본 17
 
0.2%
베트남 14
 
0.2%
독일 12
 
0.1%
스페인 9
 
0.1%
Other values (19) 51
 
0.6%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
1
3760 
<NA>
3438 
2
938 

Length

Max length4
Median length1
Mean length2.2676991
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3760
46.2%
<NA> 3438
42.3%
2 938
 
11.5%

Length

2024-05-11T14:54:00.333965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:00.548393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3760
46.2%
na 3438
42.3%
2 938
 
11.5%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct166
Distinct (%)4.8%
Missing4679
Missing (%)57.5%
Infinite0
Infinite (%)0.0%
Mean20161657
Minimum20110114
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:54:00.772987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110114
5-th percentile20110314
Q120111102
median20160808
Q320170809
95-th percentile20231121
Maximum20240305
Range130191
Interquartile range (IQR)59707

Descriptive statistics

Standard deviation40978.086
Coefficient of variation (CV)0.0020324761
Kurtosis-0.92793144
Mean20161657
Median Absolute Deviation (MAD)49594
Skewness0.29099734
Sum6.9698847 × 1010
Variance1.6792035 × 109
MonotonicityNot monotonic
2024-05-11T14:54:01.044436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160808 173
 
2.1%
20170206 132
 
1.6%
20110412 105
 
1.3%
20170217 103
 
1.3%
20170202 97
 
1.2%
20211020 91
 
1.1%
20111214 86
 
1.1%
20110222 85
 
1.0%
20111021 83
 
1.0%
20150718 79
 
1.0%
Other values (156) 2423
29.8%
(Missing) 4679
57.5%
ValueCountFrequency (%)
20110114 70
0.9%
20110131 6
 
0.1%
20110217 4
 
< 0.1%
20110222 85
1.0%
20110311 3
 
< 0.1%
20110314 7
 
0.1%
20110331 17
 
0.2%
20110411 25
 
0.3%
20110412 105
1.3%
20110418 4
 
< 0.1%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240227 3
 
< 0.1%
20240223 62
0.8%
20240129 6
 
0.1%
20240117 33
0.4%
20231212 6
 
0.1%
20231211 4
 
< 0.1%
20231121 76
0.9%
20231116 1
 
< 0.1%
20231109 2
 
< 0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct94
Distinct (%)5.1%
Missing6310
Missing (%)77.6%
Infinite0
Infinite (%)0.0%
Mean20172000
Minimum20060317
Maximum20220303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:54:01.295264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060317
5-th percentile20111215
Q120160822
median20170217
Q320170823
95-th percentile20211104
Maximum20220303
Range159986
Interquartile range (IQR)10001

Descriptive statistics

Standard deviation24658.693
Coefficient of variation (CV)0.0012224218
Kurtosis0.79782388
Mean20172000
Median Absolute Deviation (MAD)9395
Skewness0.088801233
Sum3.6834072 × 1010
Variance6.0805115 × 108
MonotonicityNot monotonic
2024-05-11T14:54:01.559634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160822 173
 
2.1%
20170220 132
 
1.6%
20170306 103
 
1.3%
20170217 97
 
1.2%
20211103 83
 
1.0%
20170823 78
 
1.0%
20210910 78
 
1.0%
20220303 63
 
0.8%
20170414 54
 
0.7%
20210412 50
 
0.6%
Other values (84) 915
 
11.2%
(Missing) 6310
77.6%
ValueCountFrequency (%)
20060317 1
 
< 0.1%
20110216 6
 
0.1%
20110302 4
 
< 0.1%
20110317 9
0.1%
20110523 5
 
0.1%
20110526 9
0.1%
20110704 1
 
< 0.1%
20110727 15
0.2%
20110930 2
 
< 0.1%
20111012 6
 
0.1%
ValueCountFrequency (%)
20220303 63
0.8%
20211222 2
 
< 0.1%
20211215 2
 
< 0.1%
20211210 6
 
0.1%
20211117 18
 
0.2%
20211105 1
 
< 0.1%
20211103 83
1.0%
20211101 6
 
0.1%
20210915 16
 
0.2%
20210910 78
1.0%

판정구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
5946 
1
2179 
2
 
11

Length

Max length4
Median length4
Mean length3.1924779
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5946
73.1%
1 2179
 
26.8%
2 11
 
0.1%

Length

2024-05-11T14:54:01.854908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:02.039900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5946
73.1%
1 2179
 
26.8%
2 11
 
0.1%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

처리결과
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
8080 
업소에 통보
 
53
양성
 
2
음성
 
1

Length

Max length6
Median length4
Mean length4.0122911
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8080
99.3%
업소에 통보 53
 
0.7%
양성 2
 
< 0.1%
음성 1
 
< 0.1%

Length

2024-05-11T14:54:02.248592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:02.413778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8080
98.7%
업소에 53
 
0.6%
통보 53
 
0.6%
양성 2
 
< 0.1%
음성 1
 
< 0.1%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

교부번호
Real number (ℝ)

Distinct504
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0057027 × 1010
Minimum1.9700091 × 1010
Maximum2.023012 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:54:02.618221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9700091 × 1010
5-th percentile1.9960091 × 1010
Q11.9990091 × 1010
median2.0040092 × 1010
Q32.0100092 × 1010
95-th percentile2.0200092 × 1010
Maximum2.023012 × 1010
Range5.300294 × 108
Interquartile range (IQR)1.100006 × 108

Descriptive statistics

Standard deviation77376250
Coefficient of variation (CV)0.0038578125
Kurtosis-0.060811313
Mean2.0057027 × 1010
Median Absolute Deviation (MAD)59999456
Skewness0.10752571
Sum1.6318397 × 1014
Variance5.9870841 × 1015
MonotonicityNot monotonic
2024-05-11T14:54:02.872923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040091586 2091
25.7%
19960091246 742
 
9.1%
19990091029 688
 
8.5%
20170091771 680
 
8.4%
20200091516 509
 
6.3%
20100091042 333
 
4.1%
20100091811 321
 
3.9%
20100091172 237
 
2.9%
20100091221 185
 
2.3%
19970091375 139
 
1.7%
Other values (494) 2211
27.2%
ValueCountFrequency (%)
19700091009 1
 
< 0.1%
19710091006 2
 
< 0.1%
19720091009 1
 
< 0.1%
19720091019 2
 
< 0.1%
19770091026 9
0.1%
19790091017 1
 
< 0.1%
19790091019 12
0.1%
19800091031 6
0.1%
19800091033 1
 
< 0.1%
19810091077 3
 
< 0.1%
ValueCountFrequency (%)
20230120410 2
< 0.1%
20230120303 1
< 0.1%
20230120204 1
< 0.1%
20230120185 1
< 0.1%
20230120067 1
< 0.1%
20220112789 1
< 0.1%
20220112751 1
< 0.1%
20210091502 1
< 0.1%
20210091339 1
< 0.1%
20200092008 1
< 0.1%

폐기일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
8135 
20160608
 
1

Length

Max length8
Median length4
Mean length4.0004916
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8135
> 99.9%
20160608 1
 
< 0.1%

Length

2024-05-11T14:54:03.134351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:03.313248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8135
> 99.9%
20160608 1
 
< 0.1%

폐기량(Kg)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
8135 
2
 
1

Length

Max length4
Median length4
Mean length3.9996313
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8135
> 99.9%
2 1
 
< 0.1%

Length

2024-05-11T14:54:03.520919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:03.707304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8135
> 99.9%
2 1
 
< 0.1%

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

폐기장소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing8134
Missing (%)> 99.9%
Memory size63.7 KiB
2024-05-11T14:54:03.880380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8.5
Mean length8.5
Min length3

Characters and Unicode

Total characters17
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row음성군
2nd row음성군 업소 동방푸드마스타
ValueCountFrequency (%)
음성군 2
50.0%
업소 1
25.0%
동방푸드마스타 1
25.0%
2024-05-11T14:54:04.346067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
음 2
11.8%
성 2
11.8%
군 2
11.8%
2
11.8%
업 1
 
5.9%
소 1
 
5.9%
동 1
 
5.9%
방 1
 
5.9%
푸 1
 
5.9%
드 1
 
5.9%
Other values (3) 3
17.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
88.2%
Space Separator 2
 
11.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 2
13.3%
성 2
13.3%
군 2
13.3%
업 1
6.7%
소 1
6.7%
동 1
6.7%
방 1
6.7%
푸 1
6.7%
드 1
6.7%
마 1
6.7%
Other values (2) 2
13.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
88.2%
Common 2
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 2
13.3%
성 2
13.3%
군 2
13.3%
업 1
6.7%
소 1
6.7%
동 1
6.7%
방 1
6.7%
푸 1
6.7%
드 1
6.7%
마 1
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
88.2%
ASCII 2
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
음 2
13.3%
성 2
13.3%
군 2
13.3%
업 1
6.7%
소 1
6.7%
동 1
6.7%
방 1
6.7%
푸 1
6.7%
드 1
6.7%
마 1
6.7%
Other values (2) 2
13.3%
ASCII
ValueCountFrequency (%)
2
100.0%

폐기방법
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing8134
Missing (%)> 99.9%
Memory size63.7 KiB
2024-05-11T14:54:04.545285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자진회수
2nd row자진회수
ValueCountFrequency (%)
자진회수 2
100.0%
2024-05-11T14:54:04.892080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 2
25.0%
진 2
25.0%
회 2
25.0%
수 2
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 2
25.0%
진 2
25.0%
회 2
25.0%
수 2
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 2
25.0%
진 2
25.0%
회 2
25.0%
수 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 2
25.0%
진 2
25.0%
회 2
25.0%
수 2
25.0%

소재지(도로명)
Text

MISSING 

Distinct387
Distinct (%)5.2%
Missing711
Missing (%)8.7%
Memory size63.7 KiB
2024-05-11T14:54:05.342978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length59
Mean length30.022088
Min length22

Characters and Unicode

Total characters222914
Distinct characters189
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

Unique167 ?
Unique (%)2.2%

Sample

1st row서울특별시 동작구 등용로14길 77-2, (노량진동)
2nd row서울특별시 동작구 흑석로 101-7, (흑석동)
3rd row서울특별시 동작구 흑석로 101-7, (흑석동)
4th row서울특별시 동작구 흑석로 101-7, (흑석동)
5th row서울특별시 동작구 대림로 52, (신대방동)
ValueCountFrequency (%)
서울특별시 7425
18.1%
동작구 7425
18.1%
상도동 2741
 
6.7%
노량진동 2357
 
5.7%
장승배기로 2140
 
5.2%
113 2097
 
5.1%
상도로 1751
 
4.3%
102 1263
 
3.1%
사당동 795
 
1.9%
만양로 766
 
1.9%
Other values (469) 12310
30.0%
2024-05-11T14:54:06.403419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33647
 
15.1%
동 15261
 
6.8%
1 11057
 
5.0%
, 9259
 
4.2%
시 7970
 
3.6%
서 7750
 
3.5%
작 7698
 
3.5%
) 7462
 
3.3%
( 7462
 
3.3%
구 7432
 
3.3%
Other values (179) 107916
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134900
60.5%
Space Separator 33647
 
15.1%
Decimal Number 29283
 
13.1%
Other Punctuation 9264
 
4.2%
Close Punctuation 7462
 
3.3%
Open Punctuation 7462
 
3.3%
Math Symbol 691
 
0.3%
Dash Punctuation 144
 
0.1%
Uppercase Letter 61
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15261
 
11.3%
시 7970
 
5.9%
서 7750
 
5.7%
작 7698
 
5.7%
구 7432
 
5.5%
울 7425
 
5.5%
특 7425
 
5.5%
별 7425
 
5.5%
로 7325
 
5.4%
상 6908
 
5.1%
Other values (160) 52281
38.8%
Decimal Number
ValueCountFrequency (%)
1 11057
37.8%
3 4275
 
14.6%
0 3880
 
13.3%
2 3722
 
12.7%
4 2312
 
7.9%
5 1551
 
5.3%
8 1197
 
4.1%
7 525
 
1.8%
6 519
 
1.8%
9 245
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 9259
99.9%
@ 5
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 60
98.4%
A 1
 
1.6%
Space Separator
ValueCountFrequency (%)
33647
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7462
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7462
100.0%
Math Symbol
ValueCountFrequency (%)
~ 691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134900
60.5%
Common 87953
39.5%
Latin 61
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15261
 
11.3%
시 7970
 
5.9%
서 7750
 
5.7%
작 7698
 
5.7%
구 7432
 
5.5%
울 7425
 
5.5%
특 7425
 
5.5%
별 7425
 
5.5%
로 7325
 
5.4%
상 6908
 
5.1%
Other values (160) 52281
38.8%
Common
ValueCountFrequency (%)
33647
38.3%
1 11057
 
12.6%
, 9259
 
10.5%
) 7462
 
8.5%
( 7462
 
8.5%
3 4275
 
4.9%
0 3880
 
4.4%
2 3722
 
4.2%
4 2312
 
2.6%
5 1551
 
1.8%
Other values (7) 3326
 
3.8%
Latin
ValueCountFrequency (%)
B 60
98.4%
A 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134900
60.5%
ASCII 88014
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33647
38.2%
1 11057
 
12.6%
, 9259
 
10.5%
) 7462
 
8.5%
( 7462
 
8.5%
3 4275
 
4.9%
0 3880
 
4.4%
2 3722
 
4.2%
4 2312
 
2.6%
5 1551
 
1.8%
Other values (9) 3387
 
3.8%
Hangul
ValueCountFrequency (%)
동 15261
 
11.3%
시 7970
 
5.9%
서 7750
 
5.7%
작 7698
 
5.7%
구 7432
 
5.5%
울 7425
 
5.5%
특 7425
 
5.5%
별 7425
 
5.5%
로 7325
 
5.4%
상 6908
 
5.1%
Other values (160) 52281
38.8%

소재지(지번)
Text

MISSING 

Distinct459
Distinct (%)5.8%
Missing275
Missing (%)3.4%
Memory size63.7 KiB
2024-05-11T14:54:06.747301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length45
Mean length28.099097
Min length22

Characters and Unicode

Total characters220887
Distinct characters169
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

Unique208 ?
Unique (%)2.6%

Sample

1st row서울특별시 동작구 흑석동 184번지 18호
2nd row서울특별시 동작구 노량진동 266번지 8호
3rd row서울특별시 동작구 노량진동 16번지 1호
4th row서울특별시 동작구 노량진동 16번지 1호
5th row서울특별시 동작구 노량진동 16번지 1호
ValueCountFrequency (%)
서울특별시 7861
18.8%
동작구 7861
18.8%
상도동 3081
 
7.4%
노량진동 3009
 
7.2%
6호 2100
 
5.0%
312번지 2056
 
4.9%
1호 1661
 
4.0%
324번지 1253
 
3.0%
지층 998
 
2.4%
사당동 931
 
2.2%
Other values (464) 11013
26.3%
2024-05-11T14:54:07.253696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54809
24.8%
동 16081
 
7.3%
지 9695
 
4.4%
시 8373
 
3.8%
작 7889
 
3.6%
구 7868
 
3.6%
서 7861
 
3.6%
번 7861
 
3.6%
울 7861
 
3.6%
별 7861
 
3.6%
Other values (159) 84728
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132838
60.1%
Space Separator 54809
24.8%
Decimal Number 32812
 
14.9%
Other Punctuation 111
 
0.1%
Dash Punctuation 97
 
< 0.1%
Open Punctuation 77
 
< 0.1%
Close Punctuation 77
 
< 0.1%
Uppercase Letter 66
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16081
 
12.1%
지 9695
 
7.3%
시 8373
 
6.3%
작 7889
 
5.9%
구 7868
 
5.9%
서 7861
 
5.9%
번 7861
 
5.9%
울 7861
 
5.9%
별 7861
 
5.9%
특 7861
 
5.9%
Other values (139) 43627
32.8%
Decimal Number
ValueCountFrequency (%)
1 6953
21.2%
3 6805
20.7%
2 6459
19.7%
6 3204
9.8%
4 2616
 
8.0%
5 2436
 
7.4%
0 1445
 
4.4%
8 1005
 
3.1%
7 982
 
3.0%
9 907
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 100
90.1%
& 6
 
5.4%
@ 5
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 54
81.8%
R 6
 
9.1%
D 6
 
9.1%
Space Separator
ValueCountFrequency (%)
54809
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132838
60.1%
Common 87983
39.8%
Latin 66
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16081
 
12.1%
지 9695
 
7.3%
시 8373
 
6.3%
작 7889
 
5.9%
구 7868
 
5.9%
서 7861
 
5.9%
번 7861
 
5.9%
울 7861
 
5.9%
별 7861
 
5.9%
특 7861
 
5.9%
Other values (139) 43627
32.8%
Common
ValueCountFrequency (%)
54809
62.3%
1 6953
 
7.9%
3 6805
 
7.7%
2 6459
 
7.3%
6 3204
 
3.6%
4 2616
 
3.0%
5 2436
 
2.8%
0 1445
 
1.6%
8 1005
 
1.1%
7 982
 
1.1%
Other values (7) 1269
 
1.4%
Latin
ValueCountFrequency (%)
B 54
81.8%
R 6
 
9.1%
D 6
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132838
60.1%
ASCII 88049
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54809
62.2%
1 6953
 
7.9%
3 6805
 
7.7%
2 6459
 
7.3%
6 3204
 
3.6%
4 2616
 
3.0%
5 2436
 
2.8%
0 1445
 
1.6%
8 1005
 
1.1%
7 982
 
1.1%
Other values (10) 1335
 
1.5%
Hangul
ValueCountFrequency (%)
동 16081
 
12.1%
지 9695
 
7.3%
시 8373
 
6.3%
작 7889
 
5.9%
구 7868
 
5.9%
서 7861
 
5.9%
번 7861
 
5.9%
울 7861
 
5.9%
별 7861
 
5.9%
특 7861
 
5.9%
Other values (139) 43627
32.8%

업소전화번호
Text

MISSING 

Distinct355
Distinct (%)5.4%
Missing1620
Missing (%)19.9%
Memory size63.7 KiB
2024-05-11T14:54:07.772286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.350061
Min length2

Characters and Unicode

Total characters67441
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)2.4%

Sample

1st row02 8130572
2nd row02 8130685
3rd row02 8154772
4th row02 8154772
5th row02 8154772
ValueCountFrequency (%)
02 5446
41.5%
8170091 2091
 
15.9%
8252882 742
 
5.7%
0208136114 688
 
5.2%
825 337
 
2.6%
4222 333
 
2.5%
595 328
 
2.5%
1234 321
 
2.4%
821 227
 
1.7%
2551 227
 
1.7%
Other values (386) 2378
18.1%
2024-05-11T14:54:08.542204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13195
19.6%
2 12000
17.8%
1 8815
13.1%
8 8221
12.2%
7982
11.8%
5 3811
 
5.7%
9 3432
 
5.1%
3 3225
 
4.8%
7 2806
 
4.2%
4 2433
 
3.6%
Other values (2) 1521
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59455
88.2%
Space Separator 7982
 
11.8%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13195
22.2%
2 12000
20.2%
1 8815
14.8%
8 8221
13.8%
5 3811
 
6.4%
9 3432
 
5.8%
3 3225
 
5.4%
7 2806
 
4.7%
4 2433
 
4.1%
6 1517
 
2.6%
Space Separator
ValueCountFrequency (%)
7982
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13195
19.6%
2 12000
17.8%
1 8815
13.1%
8 8221
12.2%
7982
11.8%
5 3811
 
5.7%
9 3432
 
5.1%
3 3225
 
4.8%
7 2806
 
4.2%
4 2433
 
3.6%
Other values (2) 1521
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13195
19.6%
2 12000
17.8%
1 8815
13.1%
8 8221
12.2%
7982
11.8%
5 3811
 
5.7%
9 3432
 
5.1%
3 3225
 
4.8%
7 2806
 
4.2%
4 2433
 
3.6%
Other values (2) 1521
 
2.3%

점검목적
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
3951 
수거
2317 
위생점검(전체)
975 
위생점검(부분)
893 

Length

Max length8
Median length4
Mean length4.3488201
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위생점검(전체)
2nd row위생점검(전체)
3rd row위생점검(전체)
4th row위생점검(전체)
5th row위생점검(전체)

Common Values

ValueCountFrequency (%)
<NA> 3951
48.6%
수거 2317
28.5%
위생점검(전체) 975
 
12.0%
위생점검(부분) 893
 
11.0%

Length

2024-05-11T14:54:08.874138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:09.066756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3951
48.6%
수거 2317
28.5%
위생점검(전체 975
 
12.0%
위생점검(부분 893
 
11.0%

점검일자
Real number (ℝ)

Distinct384
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20147480
Minimum20080904
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:54:09.281889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080904
5-th percentile20091104
Q120111020
median20131120
Q320180221
95-th percentile20220215
Maximum20240305
Range159401
Interquartile range (IQR)69201

Descriptive statistics

Standard deviation40038.516
Coefficient of variation (CV)0.0019872717
Kurtosis-0.85793735
Mean20147480
Median Absolute Deviation (MAD)29990
Skewness0.47274223
Sum1.6391989 × 1011
Variance1.6030828 × 109
MonotonicityNot monotonic
2024-05-11T14:54:09.597612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200513 249
 
3.1%
20160808 168
 
2.1%
20110411 130
 
1.6%
20170203 128
 
1.6%
20130725 126
 
1.5%
20121018 126
 
1.5%
20121127 108
 
1.3%
20131016 107
 
1.3%
20170201 104
 
1.3%
20190507 102
 
1.3%
Other values (374) 6788
83.4%
ValueCountFrequency (%)
20080904 3
 
< 0.1%
20090116 4
 
< 0.1%
20090203 61
0.7%
20090209 21
 
0.3%
20090223 24
 
0.3%
20090303 27
0.3%
20090325 25
0.3%
20090410 30
0.4%
20090514 49
0.6%
20090604 25
0.3%
ValueCountFrequency (%)
20240305 1
 
< 0.1%
20240229 1
 
< 0.1%
20240227 2
 
< 0.1%
20240129 6
 
0.1%
20240117 2
 
< 0.1%
20240116 67
0.8%
20231212 6
 
0.1%
20231208 30
0.4%
20231121 9
 
0.1%
20231120 67
0.8%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
<NA>
3948 
수시
3213 
기타
874 
합동
 
85
일제
 
16

Length

Max length4
Median length2
Mean length2.9705015
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수시
2nd row기타
3rd row수시
4th row수시
5th row수시

Common Values

ValueCountFrequency (%)
<NA> 3948
48.5%
수시 3213
39.5%
기타 874
 
10.7%
합동 85
 
1.0%
일제 16
 
0.2%

Length

2024-05-11T14:54:09.876715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:10.092431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3948
48.5%
수시 3213
39.5%
기타 874
 
10.7%
합동 85
 
1.0%
일제 16
 
0.2%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8136
Missing (%)100.0%
Memory size71.6 KiB

점검결과코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
1
4157 
<NA>
3948 
2
 
31

Length

Max length4
Median length1
Mean length2.4557522
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 4157
51.1%
<NA> 3948
48.5%
2 31
 
0.4%

Length

2024-05-11T14:54:10.303319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:10.481226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4157
51.1%
na 3948
48.5%
2 31
 
0.4%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct173
Distinct (%)71.2%
Missing7893
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean19716484
Minimum0
Maximum20160920
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size71.6 KiB
2024-05-11T14:54:10.674373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20110514
Q120111216
median20120502
Q320130265
95-th percentile20140695
Maximum20160920
Range20160920
Interquartile range (IQR)19049

Descriptive statistics

Standard deviation2804391.3
Coefficient of variation (CV)0.14223588
Kurtosis44.861341
Mean19716484
Median Absolute Deviation (MAD)9293
Skewness-6.8131053
Sum4.7911055 × 109
Variance7.8646106 × 1012
MonotonicityNot monotonic
2024-05-11T14:54:11.036354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110519 14
 
0.2%
20111218 7
 
0.1%
20111216 5
 
0.1%
20110513 5
 
0.1%
20111215 4
 
< 0.1%
20110818 4
 
< 0.1%
0 3
 
< 0.1%
20130706 3
 
< 0.1%
20140323 3
 
< 0.1%
20120208 3
 
< 0.1%
Other values (163) 192
 
2.4%
(Missing) 7893
97.0%
ValueCountFrequency (%)
0 3
 
< 0.1%
110621 1
 
< 0.1%
2010418 1
 
< 0.1%
20110418 2
 
< 0.1%
20110421 1
 
< 0.1%
20110513 5
 
0.1%
20110519 14
0.2%
20110527 1
 
< 0.1%
20110608 1
 
< 0.1%
20110627 2
 
< 0.1%
ValueCountFrequency (%)
20160920 1
< 0.1%
20160907 1
< 0.1%
20160822 1
< 0.1%
20160818 1
< 0.1%
20160510 1
< 0.1%
20141206 1
< 0.1%
20141122 1
< 0.1%
20141102 1
< 0.1%
20141021 1
< 0.1%
20141020 1
< 0.1%

(구)제조회사주소
Text

MISSING 

Distinct649
Distinct (%)35.2%
Missing6292
Missing (%)77.3%
Memory size63.7 KiB
2024-05-11T14:54:11.574921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length31
Mean length18.119306
Min length2

Characters and Unicode

Total characters33412
Distinct characters334
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

Unique316 ?
Unique (%)17.1%

Sample

1st row노량진동 16-1 진주식당
2nd row노량진동 16-1 진주식당
3rd row노량진동 16-1 진주식당
4th row노량진동 16-1 진주식당
5th row노량진동 16-1 진주식당
ValueCountFrequency (%)
충북 319
 
3.8%
경기 245
 
2.9%
경기도 236
 
2.8%
충남 153
 
1.8%
경남 153
 
1.8%
음성군 122
 
1.5%
대소면 87
 
1.0%
전북 87
 
1.0%
진천군 85
 
1.0%
인천시 76
 
0.9%
Other values (1351) 6822
81.4%
2024-05-11T14:54:12.311832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6543
 
19.6%
1 1444
 
4.3%
시 1157
 
3.5%
2 1048
 
3.1%
- 896
 
2.7%
동 758
 
2.3%
구 728
 
2.2%
경 717
 
2.1%
3 706
 
2.1%
리 696
 
2.1%
Other values (324) 18719
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19322
57.8%
Space Separator 6543
 
19.6%
Decimal Number 6468
 
19.4%
Dash Punctuation 896
 
2.7%
Lowercase Letter 112
 
0.3%
Uppercase Letter 40
 
0.1%
Other Punctuation 17
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1157
 
6.0%
동 758
 
3.9%
구 728
 
3.8%
경 717
 
3.7%
리 696
 
3.6%
면 594
 
3.1%
기 582
 
3.0%
북 557
 
2.9%
군 523
 
2.7%
충 488
 
2.5%
Other values (270) 12522
64.8%
Lowercase Letter
ValueCountFrequency (%)
a 17
15.2%
i 13
11.6%
t 10
8.9%
u 9
 
8.0%
o 9
 
8.0%
n 8
 
7.1%
l 7
 
6.2%
e 5
 
4.5%
r 5
 
4.5%
s 5
 
4.5%
Other values (10) 24
21.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
12.5%
A 5
12.5%
S 4
10.0%
E 3
 
7.5%
U 3
 
7.5%
P 3
 
7.5%
O 3
 
7.5%
N 2
 
5.0%
J 2
 
5.0%
D 2
 
5.0%
Other values (8) 8
20.0%
Decimal Number
ValueCountFrequency (%)
1 1444
22.3%
2 1048
16.2%
3 706
10.9%
4 612
9.5%
5 549
 
8.5%
6 514
 
7.9%
7 507
 
7.8%
0 488
 
7.5%
8 320
 
4.9%
9 280
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 15
88.2%
. 2
 
11.8%
Space Separator
ValueCountFrequency (%)
6543
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 896
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19322
57.8%
Common 13938
41.7%
Latin 152
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1157
 
6.0%
동 758
 
3.9%
구 728
 
3.8%
경 717
 
3.7%
리 696
 
3.6%
면 594
 
3.1%
기 582
 
3.0%
북 557
 
2.9%
군 523
 
2.7%
충 488
 
2.5%
Other values (270) 12522
64.8%
Latin
ValueCountFrequency (%)
a 17
 
11.2%
i 13
 
8.6%
t 10
 
6.6%
u 9
 
5.9%
o 9
 
5.9%
n 8
 
5.3%
l 7
 
4.6%
e 5
 
3.3%
r 5
 
3.3%
s 5
 
3.3%
Other values (28) 64
42.1%
Common
ValueCountFrequency (%)
6543
46.9%
1 1444
 
10.4%
2 1048
 
7.5%
- 896
 
6.4%
3 706
 
5.1%
4 612
 
4.4%
5 549
 
3.9%
6 514
 
3.7%
7 507
 
3.6%
0 488
 
3.5%
Other values (6) 631
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19322
57.8%
ASCII 14090
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6543
46.4%
1 1444
 
10.2%
2 1048
 
7.4%
- 896
 
6.4%
3 706
 
5.0%
4 612
 
4.3%
5 549
 
3.9%
6 514
 
3.6%
7 507
 
3.6%
0 488
 
3.5%
Other values (44) 783
 
5.6%
Hangul
ValueCountFrequency (%)
시 1157
 
6.0%
동 758
 
3.9%
구 728
 
3.8%
경 717
 
3.7%
리 696
 
3.6%
면 594
 
3.1%
기 582
 
3.0%
북 557
 
2.9%
군 523
 
2.7%
충 488
 
2.5%
Other values (270) 12522
64.8%

부적합항목
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing8132
Missing (%)> 99.9%
Memory size63.7 KiB
2024-05-11T14:54:12.530819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.25
Min length3

Characters and Unicode

Total characters13
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row대장균
2nd row대장균
3rd row리놀렌산
4th row세균수
ValueCountFrequency (%)
대장균 2
50.0%
리놀렌산 1
25.0%
세균수 1
25.0%
2024-05-11T14:54:12.970204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
균 3
23.1%
대 2
15.4%
장 2
15.4%
리 1
 
7.7%
놀 1
 
7.7%
렌 1
 
7.7%
산 1
 
7.7%
세 1
 
7.7%
수 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
균 3
23.1%
대 2
15.4%
장 2
15.4%
리 1
 
7.7%
놀 1
 
7.7%
렌 1
 
7.7%
산 1
 
7.7%
세 1
 
7.7%
수 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
균 3
23.1%
대 2
15.4%
장 2
15.4%
리 1
 
7.7%
놀 1
 
7.7%
렌 1
 
7.7%
산 1
 
7.7%
세 1
 
7.7%
수 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
균 3
23.1%
대 2
15.4%
장 2
15.4%
리 1
 
7.7%
놀 1
 
7.7%
렌 1
 
7.7%
산 1
 
7.7%
세 1
 
7.7%
수 1
 
7.7%

기준치부적합내용
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing8132
Missing (%)> 99.9%
Memory size63.7 KiB
2024-05-11T14:54:13.202629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6.5
Mean length6.25
Min length3

Characters and Unicode

Total characters25
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row음성이어야 한다.
2nd row음성이어야 한다.
3rd row1.4
4th row3000
ValueCountFrequency (%)
음성이어야 2
33.3%
한다 2
33.3%
1.4 1
16.7%
3000 1
16.7%
2024-05-11T14:54:13.671101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3
12.0%
0 3
12.0%
음 2
8.0%
성 2
8.0%
이 2
8.0%
어 2
8.0%
야 2
8.0%
2
8.0%
한 2
8.0%
다 2
8.0%
Other values (3) 3
12.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
56.0%
Decimal Number 6
24.0%
Other Punctuation 3
 
12.0%
Space Separator 2
 
8.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
음 2
14.3%
성 2
14.3%
이 2
14.3%
어 2
14.3%
야 2
14.3%
한 2
14.3%
다 2
14.3%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
1 1
 
16.7%
4 1
 
16.7%
3 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
56.0%
Common 11
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
음 2
14.3%
성 2
14.3%
이 2
14.3%
어 2
14.3%
야 2
14.3%
한 2
14.3%
다 2
14.3%
Common
ValueCountFrequency (%)
. 3
27.3%
0 3
27.3%
2
18.2%
1 1
 
9.1%
4 1
 
9.1%
3 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
56.0%
ASCII 11
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3
27.3%
0 3
27.3%
2
18.2%
1 1
 
9.1%
4 1
 
9.1%
3 1
 
9.1%
Hangul
ValueCountFrequency (%)
음 2
14.3%
성 2
14.3%
이 2
14.3%
어 2
14.3%
야 2
14.3%
한 2
14.3%
다 2
14.3%

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
03190000101일반음식점<NA><NA><NA><NA><NA><NA>안동장<NA><NA>콩국물<NA><NA><NA>201006251.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19720091009<NA><NA><NA><NA><NA><NA>서울특별시 동작구 흑석동 184번지 18호02 8130572위생점검(전체)20100625수시<NA>1<NA><NA><NA><NA>
13190000101일반음식점7<NA>2017. 개고기 조리.판매업소 위생점검<NA>12010181검사용춘하추동G0100000100000조리식품 등조리식품 등개고기 수육<NA><NA><NA>201710181.0600g<NA>20171018<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120171018201711021<NA><NA><NA><NA><NA><NA>19790091017<NA><NA><NA><NA><NA>서울특별시 동작구 등용로14길 77-2, (노량진동)서울특별시 동작구 노량진동 266번지 8호02 8130685위생점검(전체)20171018기타<NA>1<NA><NA><NA><NA>
23190000101일반음식점<NA><NA><NA><NA>120-9-22-1<NA>진주식당<NA><NA>수족관수수족관수<NA><NA>201109221.0ㅣ<NA><NA><NA><NA><NA><NA><NA><NA><NA>1진주식당국내<NA>220110922<NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20110922수시<NA>1<NA>노량진동 16-1 진주식당<NA><NA>
33190000101일반음식점<NA><NA><NA><NA>120-9-22-2<NA>진주식당<NA><NA>도마도마<NA><NA>201109223.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1진주식당국내<NA>220110922<NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20110922수시<NA>1<NA>노량진동 16-1 진주식당<NA><NA>
43190000101일반음식점<NA><NA><NA><NA>120-9-22-3<NA>진주식당<NA><NA>칼칼<NA><NA>201109223.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1진주식당국내<NA>220110922<NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20110922수시<NA>1<NA>노량진동 16-1 진주식당<NA><NA>
53190000101일반음식점<NA><NA><NA><NA>120-9-22-4<NA>진주식당<NA><NA>행주행주<NA><NA>201109223.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1진주식당국내<NA>220110922<NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20110922수시<NA>1<NA>노량진동 16-1 진주식당<NA><NA>
63190000101일반음식점<NA><NA><NA><NA>120-9-22-5<NA>진주식당<NA><NA>음용수음용수<NA><NA>201109221.0리터<NA><NA><NA><NA><NA><NA><NA><NA><NA>1진주식당국내<NA>220110922<NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20110922수시<NA>1<NA>노량진동 16-1 진주식당<NA><NA>
73190000101일반음식점999<NA>민원처리<NA>120-9-25-1검사용진주식당600000000식품접객업접객용 음용수음용수(세진)<NA><NA><NA>201209251.01LT<NA>20120925<NA><NA><NA>기타<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20120925수시<NA>1<NA><NA><NA><NA>
83190000101일반음식점999<NA>민원처리<NA>120-9-25-2검사용진주식당600000000식품접객업접객용 음용수음용수(아쿠아)<NA><NA><NA>201209251.01LT<NA>20120925<NA><NA><NA>기타<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20120925수시<NA>1<NA><NA><NA><NA>
93190000101일반음식점999<NA>민원처리<NA>120-9-25-3검사용진주식당600000000식품접객업기타도마<NA><NA><NA>20120925<NA><NA><NA>3개20120925<NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19790091019<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 16번지 1호02 8154772위생점검(전체)20120925수시<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
81263190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-09검사용씨제이올리브영(주) 장승배기역점X0100017800000비타민/무기질비타민/무기질얼라이브원스데일리<NA><NA><NA>202308312.0103.4g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국외미국120230905<NA><NA><NA><NA><NA><NA><NA><NA>20160091692<NA><NA><NA><NA><NA>서울특별시 동작구 장승배기로11가길 11, 지하2층 106호 (상도동)서울특별시 동작구 상도동 363번지 3호 지하2층-10602 20085824위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81273190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-10검사용씨제이올리브영(주) 장승배기역점X0100017800000비타민/무기질비타민/무기질센트룸실버맨<NA><NA><NA>202308313.0113.2g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20160091692<NA><NA><NA><NA><NA>서울특별시 동작구 장승배기로11가길 11, 지하2층 106호 (상도동)서울특별시 동작구 상도동 363번지 3호 지하2층-10602 20085824위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81283190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-11검사용씨제이올리브영(주) 장승배기역점X0100017800000비타민/무기질비타민/무기질네이처메이드액티브데일리멀티포우먼<NA><NA><NA>202308312.0109.1g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20160091692<NA><NA><NA><NA><NA>서울특별시 동작구 장승배기로11가길 11, 지하2층 106호 (상도동)서울특별시 동작구 상도동 363번지 3호 지하2층-10602 20085824위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81293190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-12검사용씨제이올리브영(주) 장승배기역점E0101400000000비타민 C비타민 C고려은단 비타민C1000 이지+비타민D<NA><NA><NA>202308313.072g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20160091692<NA><NA><NA><NA><NA>서울특별시 동작구 장승배기로11가길 11, 지하2층 106호 (상도동)서울특별시 동작구 상도동 363번지 3호 지하2층-10602 20085824위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81303190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-13검사용씨제이올리브영(주) 장승배기역점E0101400000000비타민 C비타민 C고려은단비타민C1000<NA><NA><NA>202309082.0129.6g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20160091692<NA><NA><NA><NA><NA>서울특별시 동작구 장승배기로11가길 11, 지하2층 106호 (상도동)서울특별시 동작구 상도동 363번지 3호 지하2층-10602 20085824위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81313190000134건강기능식품일반판매업<NA><NA><NA><NA>동작건-04검사용초록마을 장승배기역점E0101400000000비타민 C비타민 C건강한 비타C<NA><NA><NA>202308312.090g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20170091530<NA><NA><NA><NA><NA>서울특별시 동작구 상도로30길 39, 1층 112호 (상도동)서울특별시 동작구 상도동 529번지02 812 6262위생점검(전체)20230831수시<NA>1<NA><NA><NA><NA>
81323190000134건강기능식품일반판매업<NA><NA><NA>2021년 유통식품 수거검사120-9-3-1검사용참다한홍삼E0201700000000감마리놀렌산 함유 유지감마리놀렌산 함유 유지달맞이꽃종자유<NA><NA><NA>202109072.0102g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120210907202109151<NA><NA><NA><NA><NA><NA>20170091608<NA><NA><NA><NA><NA>서울특별시 동작구 상도로 343, (상도동)서울특별시 동작구 상도동 477번지 15호02 63358331<NA>20210907<NA><NA><NA><NA><NA><NA><NA>
81333190000135건강기능식품유통전문판매업<NA><NA><NA><NA>동작건-02검사용(주)유한양행E0101400000000비타민 C비타민 C비타 바이탈씨 과립 레몬맛<NA><NA><NA>202308291.0240g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20040091294<NA><NA><NA><NA><NA>서울특별시 동작구 노량진로 74, (대방동,19층)서울특별시 동작구 대방동 49번지 6호 19층02 828 0527위생점검(전체)20230830수시<NA>1<NA><NA><NA><NA>
81343190000135건강기능식품유통전문판매업<NA><NA><NA><NA>동작건-01검사용(주)유한양행E0100600000000비타민 B1비타민 B1센스밸런스<NA><NA><NA>202308294.050.4g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20040091294<NA><NA><NA><NA><NA>서울특별시 동작구 노량진로 74, (대방동,19층)서울특별시 동작구 대방동 49번지 6호 19층02 828 0527위생점검(전체)20230830수시<NA>1<NA><NA><NA><NA>
81353190000135건강기능식품유통전문판매업<NA><NA><NA><NA>동작건-03검사용부광약품 주식회사E0101400000000비타민 C비타민 C비케이랩 비타민C 인디안구스베리 1,000mg<NA><NA><NA>202308283.060g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120230905<NA><NA><NA><NA><NA><NA><NA><NA>20130091334<NA><NA><NA><NA><NA>서울특별시 동작구 상도로 7, (대방동)서울특별시 동작구 대방동 398번지 1호02828 8078위생점검(전체)20230830수시<NA>1<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호폐기일자폐기량(Kg)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용# duplicates
03190000101일반음식점<NA><NA><NA><NA><NA>황금어장 회 센타<NA><NA>행주<NA><NA><NA>201004201.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20010091704<NA><NA><NA><NA><NA>서울특별시 동작구 사당동 133번지 2호0205917108위생점검(전체)20100420수시1<NA><NA><NA><NA>2
13190000114기타식품판매업<NA><NA>2017년 유통식품 수거검사 계획120-2-109검사용진로마트C0127040000000맥주맥주카스 후레쉬(CASS Fresh)<NA><NA>(주) 오비맥주201702032.0355ML<NA>20170126<NA><NA><NA>실온<NA>1<NA>국내<NA>120170206201702201<NA>20040091586<NA><NA><NA><NA>서울특별시 동작구 장승배기로 113, (노량진동)서울특별시 동작구 노량진동 312번지 6호02 8170091<NA>20170203<NA><NA><NA><NA><NA><NA>2
23190000114기타식품판매업<NA><NA>2017년 유통식품 수거검사 계획120-2-320검사용진로마트C0115030000000당면당면민속당면<NA><NA><NA>201702162.0500g<NA><NA><NA><NA><NA>실온<NA>1<NA>국내<NA>120170217201703061<NA>20040091586<NA><NA><NA><NA>서울특별시 동작구 장승배기로 113, (노량진동)서울특별시 동작구 노량진동 312번지 6호02 8170091<NA>20170216<NA><NA><NA><NA><NA><NA>2
33190000114기타식품판매업<NA><NA>2018년 유통식품 수거검사 계획120-11-40검사용진로마트C0121070000000복합조미식품복합조미식품다시다남해산멸치<NA><NA><NA>201811214.096g<NA><NA><NA><NA><NA>실온<NA><NA><NA>국내<NA>1<NA><NA><NA><NA>20040091586<NA><NA><NA><NA>서울특별시 동작구 장승배기로 113, (노량진동)서울특별시 동작구 노량진동 312번지 6호02 8170091<NA>20181121<NA><NA><NA><NA><NA><NA>2
43190000114기타식품판매업<NA><NA>2019년 유통식품수거검사 계획120-10-23검사용월드마트C0301020000000캔디류캔디류LOTTE 목캔디 믹스베리<NA><NA><NA>201910183.0243g<NA><NA><NA><NA><NA>실온<NA><NA><NA>국내<NA>2<NA><NA><NA><NA>20170091771<NA><NA><NA><NA>서울특별시 동작구 상도로30길 40, 125~131호 (상도동, 상도2차두산위브트레지움아파트)서울특별시 동작구 상도동 535번지 상도2차두산위브트레지움아파트<NA><NA>20191018<NA><NA><NA><NA><NA><NA>2
53190000114기타식품판매업<NA><NA>2020년 일상수거검사12005216검사용월드마트C0308040000000유탕면유탕면오징어짬뽕<NA><NA><NA>202005245.0124g<NA><NA><NA><NA><NA>실온<NA><NA><NA>국내<NA>1<NA><NA><NA><NA>20170091771<NA><NA><NA><NA>서울특별시 동작구 상도로30길 40, 125~131호 (상도동, 상도2차두산위브트레지움아파트)서울특별시 동작구 상도동 535번지 상도2차두산위브트레지움아파트<NA><NA>20200524<NA><NA><NA><NA><NA><NA>2
63190000114기타식품판매업<NA><NA><NA><NA><NA>성대유통(주)214000000조미식품고형(또는분말)카레약간 매운맛 오뚜기<NA><NA><NA>200902036.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19960091246<NA><NA><NA><NA>서울특별시 동작구 상도로 102, (상도동)서울특별시 동작구 상도동 324번지 1호02 8252882수거20090203수시1<NA><NA><NA><NA>2
73190000114기타식품판매업<NA><NA><NA><NA><NA>진로마트827000000주류기타주류복분자주<NA><NA><NA>200905143.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040091586<NA><NA><NA><NA>서울특별시 동작구 장승배기로 113, (노량진동)서울특별시 동작구 노량진동 312번지 6호02 8170091수거20090514수시1<NA><NA><NA><NA>2
83190000114기타식품판매업<NA><NA><NA><NA><NA>진로마트828000000건포류기타건포류쥐포구이채<NA><NA><NA>201001153.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040091586<NA><NA><NA><NA>서울특별시 동작구 장승배기로 113, (노량진동)서울특별시 동작구 노량진동 312번지 6호02 8170091수거20100115수시1<NA><NA><NA><NA>2