Overview

Dataset statistics

Number of variables61
Number of observations8602
Missing cells229120
Missing cells (%)43.7%
Duplicate rows13
Duplicate rows (%)0.2%
Total size in memory4.2 MiB
Average record size in memory517.0 B

Variable types

Categorical19
Numeric11
Unsupported11
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-11071/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
수거품처리 has constant value ""Constant
폐기방법 has constant value ""Constant
Dataset has 13 (0.2%) duplicate rowsDuplicates
업종명 is highly imbalanced (60.6%)Imbalance
지도점검계획 is highly imbalanced (68.8%)Imbalance
수거계획 is highly imbalanced (65.0%)Imbalance
수거사유코드 is highly imbalanced (56.6%)Imbalance
수거량(자유) is highly imbalanced (92.4%)Imbalance
국가명 is highly imbalanced (83.1%)Imbalance
판정구분 is highly imbalanced (51.7%)Imbalance
처리결과 is highly imbalanced (98.9%)Imbalance
폐기량(Kg) is highly imbalanced (99.7%)Imbalance
계획구분명 has 8602 (100.0%) missing valuesMissing
수거증번호 has 1259 (14.6%) missing valuesMissing
식품군코드 has 187 (2.2%) missing valuesMissing
식품군 has 1082 (12.6%) missing valuesMissing
품목명 has 566 (6.6%) missing valuesMissing
음식물명 has 8449 (98.2%) missing valuesMissing
원료명 has 8590 (99.9%) missing valuesMissing
생산업소 has 8315 (96.7%) missing valuesMissing
수거량(정량) has 397 (4.6%) missing valuesMissing
제품규격(정량) has 1657 (19.3%) missing valuesMissing
제조일자(일자) has 5674 (66.0%) missing valuesMissing
제조일자(롯트) has 8540 (99.3%) missing valuesMissing
유통기한(일자) has 8582 (99.8%) missing valuesMissing
유통기한(제조일기준) has 8577 (99.7%) missing valuesMissing
바코드번호 has 8602 (100.0%) missing valuesMissing
어린이기호식품유형 has 8602 (100.0%) missing valuesMissing
(구)제조사명 has 7149 (83.1%) missing valuesMissing
검사의뢰일자 has 5647 (65.6%) missing valuesMissing
결과회보일자 has 6852 (79.7%) missing valuesMissing
처리구분 has 8602 (100.0%) missing valuesMissing
수거검사구분코드 has 8602 (100.0%) missing valuesMissing
단속지역구분코드 has 8602 (100.0%) missing valuesMissing
수거장소구분코드 has 8602 (100.0%) missing valuesMissing
수거품처리 has 8601 (> 99.9%) missing valuesMissing
폐기일자 has 8602 (100.0%) missing valuesMissing
폐기금액(원) has 8602 (100.0%) missing valuesMissing
폐기장소 has 8602 (100.0%) missing valuesMissing
폐기방법 has 8601 (> 99.9%) missing valuesMissing
소재지(도로명) has 822 (9.6%) missing valuesMissing
소재지(지번) has 444 (5.2%) missing valuesMissing
업소전화번호 has 1561 (18.1%) missing valuesMissing
점검내용 has 8602 (100.0%) missing valuesMissing
(구)제조유통기한 has 8582 (99.8%) missing valuesMissing
(구)제조회사주소 has 7166 (83.3%) missing valuesMissing
부적합항목 has 8599 (> 99.9%) missing valuesMissing
기준치부적합내용 has 8599 (> 99.9%) missing valuesMissing
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
어린이기호식품유형 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-17 22:32:10.434290
Analysis finished2024-05-17 22:32:17.676926
Duration7.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
3210000
8602 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 8602
100.0%

Length

2024-05-18T07:32:17.984568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:18.496059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 8602
100.0%

업종코드
Real number (ℝ)

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.29249
Minimum101
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:18.875661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1106
median114
Q3114
95-th percentile114
Maximum135
Range34
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.5091018
Coefficient of variation (CV)0.04950111
Kurtosis1.8754959
Mean111.29249
Median Absolute Deviation (MAD)0
Skewness-0.24017833
Sum957338
Variance30.350203
MonotonicityNot monotonic
2024-05-18T07:32:19.370344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
114 5963
69.3%
101 1155
 
13.4%
105 774
 
9.0%
104 164
 
1.9%
112 135
 
1.6%
106 100
 
1.2%
134 80
 
0.9%
107 79
 
0.9%
110 59
 
0.7%
121 55
 
0.6%
Other values (7) 38
 
0.4%
ValueCountFrequency (%)
101 1155
13.4%
104 164
 
1.9%
105 774
9.0%
106 100
 
1.2%
107 79
 
0.9%
109 4
 
< 0.1%
110 59
 
0.7%
111 2
 
< 0.1%
112 135
 
1.6%
113 9
 
0.1%
ValueCountFrequency (%)
135 5
 
0.1%
134 80
 
0.9%
123 1
 
< 0.1%
122 12
 
0.1%
121 55
 
0.6%
120 5
 
0.1%
114 5963
69.3%
113 9
 
0.1%
112 135
 
1.6%
111 2
 
< 0.1%

업종명
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
기타식품판매업
5963 
일반음식점
1155 
집단급식소
774 
휴게음식점
 
164
식품자동판매기영업
 
135
Other values (12)
 
411

Length

Max length13
Median length7
Mean length6.6074169
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row휴게음식점
2nd row집단급식소
3rd row집단급식소
4th row일반음식점
5th row식품제조가공업

Common Values

ValueCountFrequency (%)
기타식품판매업 5963
69.3%
일반음식점 1155
 
13.4%
집단급식소 774
 
9.0%
휴게음식점 164
 
1.9%
식품자동판매기영업 135
 
1.6%
식품제조가공업 100
 
1.2%
건강기능식품일반판매업 80
 
0.9%
즉석판매제조가공업 79
 
0.9%
식품등 수입판매업 59
 
0.7%
제과점영업 55
 
0.6%
Other values (7) 38
 
0.4%

Length

2024-05-18T07:32:20.159682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 5963
68.8%
일반음식점 1155
 
13.3%
집단급식소 774
 
8.9%
휴게음식점 164
 
1.9%
식품자동판매기영업 135
 
1.6%
식품제조가공업 100
 
1.2%
건강기능식품일반판매업 80
 
0.9%
즉석판매제조가공업 79
 
0.9%
수입판매업 59
 
0.7%
식품등 59
 
0.7%
Other values (8) 93
 
1.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
5594 
999
2916 
7
 
92

Length

Max length4
Median length4
Mean length3.6289235
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5594
65.0%
999 2916
33.9%
7 92
 
1.1%

Length

2024-05-18T07:32:20.811227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:21.313538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5594
65.0%
999 2916
33.9%
7 92
 
1.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
5594 
지도점검
2909 
원산지표시점검(소고기수거유전자검사의뢰)
 
31
쇠고기 수거 유전자 검사
 
21
한우취급음식점소고기수거검사
 
16
Other values (5)
 
31

Length

Max length21
Median length4
Mean length4.127761
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> 5594
65.0%
지도점검 2909
33.8%
원산지표시점검(소고기수거유전자검사의뢰) 31
 
0.4%
쇠고기 수거 유전자 검사 21
 
0.2%
한우취급음식점소고기수거검사 16
 
0.2%
소고기 유전자 수거 검사 16
 
0.2%
2015년 지도점검 8
 
0.1%
영업소 폐쇄 현장점검 3
 
< 0.1%
부정불량식품 3
 
< 0.1%
시군구 지도점검 1
 
< 0.1%

Length

2024-05-18T07:32:21.801685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:22.224118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5594
64.1%
지도점검 2918
33.4%
수거 37
 
0.4%
유전자 37
 
0.4%
검사 37
 
0.4%
원산지표시점검(소고기수거유전자검사의뢰 31
 
0.4%
쇠고기 21
 
0.2%
한우취급음식점소고기수거검사 16
 
0.2%
소고기 16
 
0.2%
2015년 8
 
0.1%
Other values (5) 13
 
0.1%

수거계획
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
6851 
기타 일상수거검사
843 
2013년 식품수거 검사 계획
697 
2014년 서초구 유통식품수거검사 계획
 
120
명절 성수식품 수거
 
73
Other values (3)
 
18

Length

Max length27
Median length4
Mean length5.7826087
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> 6851
79.6%
기타 일상수거검사 843
 
9.8%
2013년 식품수거 검사 계획 697
 
8.1%
2014년 서초구 유통식품수거검사 계획 120
 
1.4%
명절 성수식품 수거 73
 
0.8%
2013년 식품검사 수거 계획 7
 
0.1%
부정불량식품 신고 관련 수거검사 6
 
0.1%
식음료 전문판매(프랜차이즈)업소 식용얼음 수거검사 5
 
0.1%

Length

2024-05-18T07:32:22.696771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:23.085099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6851
56.6%
일상수거검사 843
 
7.0%
기타 843
 
7.0%
계획 824
 
6.8%
2013년 704
 
5.8%
식품수거 697
 
5.8%
검사 697
 
5.8%
2014년 120
 
1.0%
서초구 120
 
1.0%
유통식품수거검사 120
 
1.0%
Other values (11) 277
 
2.3%

수거증번호
Text

MISSING 

Distinct5748
Distinct (%)78.3%
Missing1259
Missing (%)14.6%
Memory size67.3 KiB
2024-05-18T07:32:24.002281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.6026147
Min length1

Characters and Unicode

Total characters55826
Distinct characters26
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4683 ?
Unique (%)63.8%

Sample

1st row122-3-14-4
2nd row122-3-14-2
3rd row122-3-14-1
4th row122-3-14-3
5th row122-3-6-1
ValueCountFrequency (%)
122-4-13 4
 
0.1%
122-1-2 4
 
0.1%
122-1-4 4
 
0.1%
122-3-3 4
 
0.1%
122-2-19 4
 
0.1%
122-10-17 4
 
0.1%
122-3-1 4
 
0.1%
122-4-10 4
 
0.1%
122-1-31 4
 
0.1%
122-4-32 4
 
0.1%
Other values (5734) 7304
99.5%
2024-05-18T07:32:25.483553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 15149
27.1%
1 11609
20.8%
2 10850
19.4%
3 2723
 
4.9%
6 2296
 
4.1%
4 2244
 
4.0%
9 2127
 
3.8%
0 2053
 
3.7%
5 1914
 
3.4%
7 1812
 
3.2%
Other values (16) 3049
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39274
70.4%
Dash Punctuation 15149
 
27.1%
Other Letter 1370
 
2.5%
Uppercase Letter 28
 
0.1%
Lowercase Letter 3
 
< 0.1%
Space Separator 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11609
29.6%
2 10850
27.6%
3 2723
 
6.9%
6 2296
 
5.8%
4 2244
 
5.7%
9 2127
 
5.4%
0 2053
 
5.2%
5 1914
 
4.9%
7 1812
 
4.6%
8 1646
 
4.2%
Other Letter
ValueCountFrequency (%)
677
49.4%
676
49.3%
9
 
0.7%
6
 
0.4%
1
 
0.1%
1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
A 17
60.7%
B 5
 
17.9%
C 3
 
10.7%
D 3
 
10.7%
Lowercase Letter
ValueCountFrequency (%)
a 1
33.3%
b 1
33.3%
c 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 15149
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54425
97.5%
Hangul 1370
 
2.5%
Latin 31
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 15149
27.8%
1 11609
21.3%
2 10850
19.9%
3 2723
 
5.0%
6 2296
 
4.2%
4 2244
 
4.1%
9 2127
 
3.9%
0 2053
 
3.8%
5 1914
 
3.5%
7 1812
 
3.3%
Other values (3) 1648
 
3.0%
Latin
ValueCountFrequency (%)
A 17
54.8%
B 5
 
16.1%
C 3
 
9.7%
D 3
 
9.7%
a 1
 
3.2%
b 1
 
3.2%
c 1
 
3.2%
Hangul
ValueCountFrequency (%)
677
49.4%
676
49.3%
9
 
0.7%
6
 
0.4%
1
 
0.1%
1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54456
97.5%
Hangul 1370
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 15149
27.8%
1 11609
21.3%
2 10850
19.9%
3 2723
 
5.0%
6 2296
 
4.2%
4 2244
 
4.1%
9 2127
 
3.9%
0 2053
 
3.8%
5 1914
 
3.5%
7 1812
 
3.3%
Other values (10) 1679
 
3.1%
Hangul
ValueCountFrequency (%)
677
49.4%
676
49.3%
9
 
0.7%
6
 
0.4%
1
 
0.1%
1
 
0.1%

수거사유코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
검사용
6470 
<NA>
2055 
기타
 
70
압류
 
7

Length

Max length4
Median length3
Mean length3.2299465
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 6470
75.2%
<NA> 2055
 
23.9%
기타 70
 
0.8%
압류 7
 
0.1%

Length

2024-05-18T07:32:26.114688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:26.777392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 6470
75.2%
na 2055
 
23.9%
기타 70
 
0.8%
압류 7
 
0.1%
Distinct785
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
2024-05-18T07:32:27.681745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length9.8950244
Min length2

Characters and Unicode

Total characters85117
Distinct characters560
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

Unique398 ?
Unique (%)4.6%

Sample

1st row프랭크버거방배점
2nd row서울고등학교
3rd row서울고등학교
4th row피자다오 사당방배점
5th row플레이팅키친(교대점)
ValueCountFrequency (%)
양재점 2437
18.1%
주)이마트 1908
14.2%
주)농협유통양재하나로클럽 1144
 
8.5%
주)농협유통 727
 
5.4%
양재하나로클럽 727
 
5.4%
킴스클럽 537
 
4.0%
주)신세계이마트 464
 
3.5%
서초점 300
 
2.2%
롯데마트 291
 
2.2%
신세계백화점 246
 
1.8%
Other values (920) 4667
34.7%
2024-05-18T07:32:29.147020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4888
 
5.7%
) 4888
 
5.7%
4873
 
5.7%
4849
 
5.7%
4569
 
5.4%
4464
 
5.2%
3576
 
4.2%
3154
 
3.7%
3022
 
3.6%
2966
 
3.5%
Other values (550) 43868
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69761
82.0%
Open Punctuation 4888
 
5.7%
Close Punctuation 4888
 
5.7%
Space Separator 4849
 
5.7%
Uppercase Letter 324
 
0.4%
Lowercase Letter 202
 
0.2%
Other Punctuation 100
 
0.1%
Decimal Number 97
 
0.1%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4873
 
7.0%
4569
 
6.5%
4464
 
6.4%
3576
 
5.1%
3154
 
4.5%
3022
 
4.3%
2966
 
4.3%
2429
 
3.5%
2428
 
3.5%
2091
 
3.0%
Other values (490) 36189
51.9%
Uppercase Letter
ValueCountFrequency (%)
C 35
 
10.8%
N 29
 
9.0%
O 28
 
8.6%
E 26
 
8.0%
T 23
 
7.1%
G 18
 
5.6%
W 17
 
5.2%
L 16
 
4.9%
P 15
 
4.6%
A 15
 
4.6%
Other values (13) 102
31.5%
Lowercase Letter
ValueCountFrequency (%)
e 31
15.3%
i 28
13.9%
s 19
9.4%
n 17
8.4%
a 17
8.4%
r 14
6.9%
u 12
 
5.9%
o 12
 
5.9%
z 10
 
5.0%
f 8
 
4.0%
Other values (10) 34
16.8%
Decimal Number
ValueCountFrequency (%)
2 51
52.6%
1 22
22.7%
4 10
 
10.3%
0 6
 
6.2%
6 3
 
3.1%
3 3
 
3.1%
5 1
 
1.0%
9 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 77
77.0%
. 13
 
13.0%
@ 4
 
4.0%
& 4
 
4.0%
: 2
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 4888
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4888
100.0%
Space Separator
ValueCountFrequency (%)
4849
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69757
82.0%
Common 14830
 
17.4%
Latin 526
 
0.6%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4873
 
7.0%
4569
 
6.5%
4464
 
6.4%
3576
 
5.1%
3154
 
4.5%
3022
 
4.3%
2966
 
4.3%
2429
 
3.5%
2428
 
3.5%
2091
 
3.0%
Other values (489) 36185
51.9%
Latin
ValueCountFrequency (%)
C 35
 
6.7%
e 31
 
5.9%
N 29
 
5.5%
i 28
 
5.3%
O 28
 
5.3%
E 26
 
4.9%
T 23
 
4.4%
s 19
 
3.6%
G 18
 
3.4%
n 17
 
3.2%
Other values (33) 272
51.7%
Common
ValueCountFrequency (%)
( 4888
33.0%
) 4888
33.0%
4849
32.7%
, 77
 
0.5%
2 51
 
0.3%
1 22
 
0.1%
. 13
 
0.1%
4 10
 
0.1%
- 8
 
0.1%
0 6
 
< 0.1%
Other values (7) 18
 
0.1%
Han
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69757
82.0%
ASCII 15356
 
18.0%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4888
31.8%
) 4888
31.8%
4849
31.6%
, 77
 
0.5%
2 51
 
0.3%
C 35
 
0.2%
e 31
 
0.2%
N 29
 
0.2%
i 28
 
0.2%
O 28
 
0.2%
Other values (50) 452
 
2.9%
Hangul
ValueCountFrequency (%)
4873
 
7.0%
4569
 
6.5%
4464
 
6.4%
3576
 
5.1%
3154
 
4.5%
3022
 
4.3%
2966
 
4.3%
2429
 
3.5%
2428
 
3.5%
2091
 
3.0%
Other values (489) 36185
51.9%
CJK
ValueCountFrequency (%)
4
100.0%

식품군코드
Text

MISSING 

Distinct446
Distinct (%)5.3%
Missing187
Missing (%)2.2%
Memory size67.3 KiB
2024-05-18T07:32:29.907186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length11.453001
Min length1

Characters and Unicode

Total characters96377
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)1.2%

Sample

1st rowG0100000100000
2nd rowG0100000100000
3rd rowG0100000100000
4th rowG0100000100000
5th rowC0322020300000
ValueCountFrequency (%)
g0100000100000 789
 
9.9%
c01000000 385
 
4.8%
801000000 242
 
3.0%
201000000 222
 
2.8%
600000000 199
 
2.5%
815000000 192
 
2.4%
g0300000300000 190
 
2.4%
821000000 190
 
2.4%
818000000 147
 
1.8%
830000000 146
 
1.8%
Other values (434) 5256
66.0%
2024-05-18T07:32:31.225765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64755
67.2%
1 9340
 
9.7%
2 4204
 
4.4%
4105
 
4.3%
C 3089
 
3.2%
8 2745
 
2.8%
3 2642
 
2.7%
G 1100
 
1.1%
4 988
 
1.0%
5 875
 
0.9%
Other values (9) 2534
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87609
90.9%
Uppercase Letter 4663
 
4.8%
Space Separator 4105
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64755
73.9%
1 9340
 
10.7%
2 4204
 
4.8%
8 2745
 
3.1%
3 2642
 
3.0%
4 988
 
1.1%
5 875
 
1.0%
9 861
 
1.0%
7 664
 
0.8%
6 535
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 3089
66.2%
G 1100
 
23.6%
B 128
 
2.7%
E 111
 
2.4%
X 102
 
2.2%
F 68
 
1.5%
A 55
 
1.2%
H 10
 
0.2%
Space Separator
ValueCountFrequency (%)
4105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91714
95.2%
Latin 4663
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64755
70.6%
1 9340
 
10.2%
2 4204
 
4.6%
4105
 
4.5%
8 2745
 
3.0%
3 2642
 
2.9%
4 988
 
1.1%
5 875
 
1.0%
9 861
 
0.9%
7 664
 
0.7%
Latin
ValueCountFrequency (%)
C 3089
66.2%
G 1100
 
23.6%
B 128
 
2.7%
E 111
 
2.4%
X 102
 
2.2%
F 68
 
1.5%
A 55
 
1.2%
H 10
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64755
67.2%
1 9340
 
9.7%
2 4204
 
4.4%
4105
 
4.3%
C 3089
 
3.2%
8 2745
 
2.8%
3 2642
 
2.7%
G 1100
 
1.1%
4 988
 
1.0%
5 875
 
0.9%
Other values (9) 2534
 
2.6%

식품군
Text

MISSING 

Distinct341
Distinct (%)4.5%
Missing1082
Missing (%)12.6%
Memory size67.3 KiB
2024-05-18T07:32:32.226962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length26
Mean length5.937234
Min length1

Characters and Unicode

Total characters44648
Distinct characters323
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)1.1%

Sample

1st row조리식품 등
2nd row조리식품 등
3rd row조리식품 등
4th row조리식품 등
5th row즉석조리식품
ValueCountFrequency (%)
982
 
8.5%
조리식품 792
 
6.9%
과자류 464
 
4.0%
조미식품 291
 
2.5%
면류 254
 
2.2%
중인 209
 
1.8%
제외한다 207
 
1.8%
것은 207
 
1.8%
음료류 205
 
1.8%
식품접객업 199
 
1.7%
Other values (364) 7677
66.8%
2024-05-18T07:32:33.497327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3967
 
8.9%
3104
 
7.0%
2734
 
6.1%
2571
 
5.8%
1417
 
3.2%
1342
 
3.0%
983
 
2.2%
983
 
2.2%
958
 
2.1%
861
 
1.9%
Other values (313) 25728
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39052
87.5%
Space Separator 3967
 
8.9%
Other Punctuation 929
 
2.1%
Open Punctuation 296
 
0.7%
Close Punctuation 296
 
0.7%
Uppercase Letter 71
 
0.2%
Decimal Number 30
 
0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3104
 
7.9%
2734
 
7.0%
2571
 
6.6%
1417
 
3.6%
1342
 
3.4%
983
 
2.5%
983
 
2.5%
958
 
2.5%
861
 
2.2%
858
 
2.2%
Other values (286) 23241
59.5%
Uppercase Letter
ValueCountFrequency (%)
A 18
25.4%
D 12
16.9%
E 9
12.7%
P 8
11.3%
H 8
11.3%
C 6
 
8.5%
B 6
 
8.5%
M 2
 
2.8%
S 1
 
1.4%
Q 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 8
26.7%
1 6
20.0%
0 6
20.0%
3 5
16.7%
4 3
 
10.0%
5 1
 
3.3%
6 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 570
61.4%
. 324
34.9%
? 20
 
2.2%
/ 13
 
1.4%
% 1
 
0.1%
1
 
0.1%
Space Separator
ValueCountFrequency (%)
3967
100.0%
Open Punctuation
ValueCountFrequency (%)
( 296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39052
87.5%
Common 5525
 
12.4%
Latin 71
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3104
 
7.9%
2734
 
7.0%
2571
 
6.6%
1417
 
3.6%
1342
 
3.4%
983
 
2.5%
983
 
2.5%
958
 
2.5%
861
 
2.2%
858
 
2.2%
Other values (286) 23241
59.5%
Common
ValueCountFrequency (%)
3967
71.8%
, 570
 
10.3%
. 324
 
5.9%
( 296
 
5.4%
) 296
 
5.4%
? 20
 
0.4%
/ 13
 
0.2%
2 8
 
0.1%
- 7
 
0.1%
1 6
 
0.1%
Other values (7) 18
 
0.3%
Latin
ValueCountFrequency (%)
A 18
25.4%
D 12
16.9%
E 9
12.7%
P 8
11.3%
H 8
11.3%
C 6
 
8.5%
B 6
 
8.5%
M 2
 
2.8%
S 1
 
1.4%
Q 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39052
87.5%
ASCII 5595
 
12.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3967
70.9%
, 570
 
10.2%
. 324
 
5.8%
( 296
 
5.3%
) 296
 
5.3%
? 20
 
0.4%
A 18
 
0.3%
/ 13
 
0.2%
D 12
 
0.2%
E 9
 
0.2%
Other values (16) 70
 
1.3%
Hangul
ValueCountFrequency (%)
3104
 
7.9%
2734
 
7.0%
2571
 
6.6%
1417
 
3.6%
1342
 
3.4%
983
 
2.5%
983
 
2.5%
958
 
2.5%
861
 
2.2%
858
 
2.2%
Other values (286) 23241
59.5%
None
ValueCountFrequency (%)
1
100.0%

품목명
Text

MISSING 

Distinct459
Distinct (%)5.7%
Missing566
Missing (%)6.6%
Memory size67.3 KiB
2024-05-18T07:32:34.120781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length26
Mean length5.9268293
Min length1

Characters and Unicode

Total characters47628
Distinct characters381
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

Unique123 ?
Unique (%)1.5%

Sample

1st row조리식품 등
2nd row조리식품 등
3rd row조리식품 등
4th row조리식품 등
5th row즉석조리식품
ValueCountFrequency (%)
992
 
8.2%
조리식품 844
 
7.0%
소고기 352
 
2.9%
과자 248
 
2.0%
중인 209
 
1.7%
제외한다 207
 
1.7%
것은 207
 
1.7%
198
 
1.6%
190
 
1.6%
담는 190
 
1.6%
Other values (487) 8484
70.0%
2024-05-18T07:32:35.223308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4085
 
8.6%
2078
 
4.4%
1823
 
3.8%
1616
 
3.4%
1490
 
3.1%
1477
 
3.1%
1430
 
3.0%
1195
 
2.5%
1106
 
2.3%
993
 
2.1%
Other values (371) 30335
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41001
86.1%
Space Separator 4085
 
8.6%
Other Punctuation 1093
 
2.3%
Close Punctuation 646
 
1.4%
Open Punctuation 646
 
1.4%
Uppercase Letter 87
 
0.2%
Decimal Number 40
 
0.1%
Dash Punctuation 15
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2078
 
5.1%
1823
 
4.4%
1616
 
3.9%
1490
 
3.6%
1477
 
3.6%
1430
 
3.5%
1195
 
2.9%
1106
 
2.7%
993
 
2.4%
873
 
2.1%
Other values (334) 26920
65.7%
Uppercase Letter
ValueCountFrequency (%)
A 25
28.7%
D 13
14.9%
C 11
12.6%
P 9
 
10.3%
E 9
 
10.3%
H 8
 
9.2%
B 7
 
8.0%
M 2
 
2.3%
L 1
 
1.1%
Q 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
20.0%
u 3
20.0%
r 2
13.3%
l 2
13.3%
f 1
 
6.7%
o 1
 
6.7%
t 1
 
6.7%
s 1
 
6.7%
a 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
3 11
27.5%
2 11
27.5%
1 7
17.5%
0 6
15.0%
4 3
 
7.5%
6 1
 
2.5%
5 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 591
54.1%
. 462
42.3%
? 26
 
2.4%
/ 11
 
1.0%
2
 
0.2%
% 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4085
100.0%
Close Punctuation
ValueCountFrequency (%)
) 646
100.0%
Open Punctuation
ValueCountFrequency (%)
( 646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41001
86.1%
Common 6525
 
13.7%
Latin 102
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2078
 
5.1%
1823
 
4.4%
1616
 
3.9%
1490
 
3.6%
1477
 
3.6%
1430
 
3.5%
1195
 
2.9%
1106
 
2.7%
993
 
2.4%
873
 
2.1%
Other values (334) 26920
65.7%
Latin
ValueCountFrequency (%)
A 25
24.5%
D 13
12.7%
C 11
10.8%
P 9
 
8.8%
E 9
 
8.8%
H 8
 
7.8%
B 7
 
6.9%
e 3
 
2.9%
u 3
 
2.9%
r 2
 
2.0%
Other values (10) 12
11.8%
Common
ValueCountFrequency (%)
4085
62.6%
) 646
 
9.9%
( 646
 
9.9%
, 591
 
9.1%
. 462
 
7.1%
? 26
 
0.4%
- 15
 
0.2%
3 11
 
0.2%
/ 11
 
0.2%
2 11
 
0.2%
Other values (7) 21
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41001
86.1%
ASCII 6625
 
13.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4085
61.7%
) 646
 
9.8%
( 646
 
9.8%
, 591
 
8.9%
. 462
 
7.0%
? 26
 
0.4%
A 25
 
0.4%
- 15
 
0.2%
D 13
 
0.2%
3 11
 
0.2%
Other values (26) 105
 
1.6%
Hangul
ValueCountFrequency (%)
2078
 
5.1%
1823
 
4.4%
1616
 
3.9%
1490
 
3.6%
1477
 
3.6%
1430
 
3.5%
1195
 
2.9%
1106
 
2.7%
993
 
2.4%
873
 
2.1%
Other values (334) 26920
65.7%
None
ValueCountFrequency (%)
2
100.0%
Distinct6313
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
2024-05-18T07:32:36.132312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length34
Mean length7.6156708
Min length1

Characters and Unicode

Total characters65510
Distinct characters1023
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5416 ?
Unique (%)63.0%

Sample

1st row햄버거
2nd row철판삼겹살
3rd row잡채
4th row피자
5th row소세지 미트 파스타
ValueCountFrequency (%)
등심 177
 
1.1%
이마트 139
 
0.9%
커피 106
 
0.7%
오뚜기 90
 
0.6%
청정원 90
 
0.6%
유기농 88
 
0.6%
76
 
0.5%
도마 73
 
0.5%
고춧가루 71
 
0.5%
백설 69
 
0.4%
Other values (7106) 14656
93.7%
2024-05-18T07:32:37.657749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7037
 
10.7%
1347
 
2.1%
1271
 
1.9%
1197
 
1.8%
786
 
1.2%
744
 
1.1%
693
 
1.1%
690
 
1.1%
674
 
1.0%
605
 
0.9%
Other values (1013) 50466
77.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55068
84.1%
Space Separator 7037
 
10.7%
Decimal Number 879
 
1.3%
Uppercase Letter 855
 
1.3%
Lowercase Letter 560
 
0.9%
Close Punctuation 383
 
0.6%
Open Punctuation 380
 
0.6%
Other Punctuation 232
 
0.4%
Dash Punctuation 84
 
0.1%
Math Symbol 17
 
< 0.1%
Other values (4) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1347
 
2.4%
1271
 
2.3%
1197
 
2.2%
786
 
1.4%
744
 
1.4%
693
 
1.3%
690
 
1.3%
674
 
1.2%
605
 
1.1%
596
 
1.1%
Other values (929) 46465
84.4%
Uppercase Letter
ValueCountFrequency (%)
A 82
 
9.6%
I 76
 
8.9%
E 76
 
8.9%
L 63
 
7.4%
O 63
 
7.4%
N 63
 
7.4%
C 51
 
6.0%
M 51
 
6.0%
R 44
 
5.1%
S 32
 
3.7%
Other values (16) 254
29.7%
Lowercase Letter
ValueCountFrequency (%)
a 65
 
11.6%
e 59
 
10.5%
i 51
 
9.1%
o 36
 
6.4%
m 34
 
6.1%
r 30
 
5.4%
c 29
 
5.2%
l 28
 
5.0%
t 28
 
5.0%
p 25
 
4.5%
Other values (16) 175
31.2%
Other Punctuation
ValueCountFrequency (%)
% 54
23.3%
, 44
19.0%
& 42
18.1%
. 29
12.5%
; 20
 
8.6%
/ 13
 
5.6%
10
 
4.3%
! 7
 
3.0%
? 7
 
3.0%
3
 
1.3%
Decimal Number
ValueCountFrequency (%)
0 254
28.9%
1 222
25.3%
2 119
13.5%
3 108
12.3%
5 58
 
6.6%
4 46
 
5.2%
6 28
 
3.2%
7 17
 
1.9%
9 14
 
1.6%
8 13
 
1.5%
Math Symbol
ValueCountFrequency (%)
+ 14
82.4%
~ 3
 
17.6%
Other Symbol
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
7037
100.0%
Close Punctuation
ValueCountFrequency (%)
) 383
100.0%
Open Punctuation
ValueCountFrequency (%)
( 380
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55057
84.0%
Common 9025
 
13.8%
Latin 1417
 
2.2%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1347
 
2.4%
1271
 
2.3%
1197
 
2.2%
786
 
1.4%
744
 
1.4%
693
 
1.3%
690
 
1.3%
674
 
1.2%
605
 
1.1%
596
 
1.1%
Other values (920) 46454
84.4%
Latin
ValueCountFrequency (%)
A 82
 
5.8%
I 76
 
5.4%
E 76
 
5.4%
a 65
 
4.6%
L 63
 
4.4%
O 63
 
4.4%
N 63
 
4.4%
e 59
 
4.2%
i 51
 
3.6%
C 51
 
3.6%
Other values (43) 768
54.2%
Common
ValueCountFrequency (%)
7037
78.0%
) 383
 
4.2%
( 380
 
4.2%
0 254
 
2.8%
1 222
 
2.5%
2 119
 
1.3%
3 108
 
1.2%
- 84
 
0.9%
5 58
 
0.6%
% 54
 
0.6%
Other values (21) 326
 
3.6%
Han
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55057
84.0%
ASCII 10424
 
15.9%
None 13
 
< 0.1%
CJK 11
 
< 0.1%
CJK Compat 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7037
67.5%
) 383
 
3.7%
( 380
 
3.6%
0 254
 
2.4%
1 222
 
2.1%
2 119
 
1.1%
3 108
 
1.0%
- 84
 
0.8%
A 82
 
0.8%
I 76
 
0.7%
Other values (69) 1679
 
16.1%
Hangul
ValueCountFrequency (%)
1347
 
2.4%
1271
 
2.3%
1197
 
2.2%
786
 
1.4%
744
 
1.4%
693
 
1.3%
690
 
1.3%
674
 
1.2%
605
 
1.1%
596
 
1.1%
Other values (920) 46454
84.4%
None
ValueCountFrequency (%)
10
76.9%
3
 
23.1%
CJK Compat
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Number Forms
ValueCountFrequency (%)
2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

음식물명
Text

MISSING 

Distinct77
Distinct (%)50.3%
Missing8449
Missing (%)98.2%
Memory size67.3 KiB
2024-05-18T07:32:38.184656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.0784314
Min length1

Characters and Unicode

Total characters624
Distinct characters146
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)35.9%

Sample

1st row양념게장
2nd row광어회
3rd row안심(한우)
4th row양지(한우)
5th row채끝(한우)
ValueCountFrequency (%)
커피 24
 
15.7%
식용얼음 16
 
10.5%
수족관물 13
 
8.5%
먹는샘물 7
 
4.6%
등심(한우 4
 
2.6%
안심(한우 2
 
1.3%
코코아 2
 
1.3%
냉면육수 2
 
1.3%
불고기(한우 2
 
1.3%
꽃등심(한우 2
 
1.3%
Other values (67) 79
51.6%
2024-05-18T07:32:39.087378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
5.4%
( 33
 
5.3%
) 33
 
5.3%
30
 
4.8%
24
 
3.8%
24
 
3.8%
23
 
3.7%
17
 
2.7%
16
 
2.6%
16
 
2.6%
Other values (136) 374
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 555
88.9%
Open Punctuation 33
 
5.3%
Close Punctuation 33
 
5.3%
Uppercase Letter 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
34
 
6.1%
30
 
5.4%
24
 
4.3%
24
 
4.3%
23
 
4.1%
17
 
3.1%
16
 
2.9%
16
 
2.9%
16
 
2.9%
15
 
2.7%
Other values (131) 340
61.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Other Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 555
88.9%
Common 67
 
10.7%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
34
 
6.1%
30
 
5.4%
24
 
4.3%
24
 
4.3%
23
 
4.1%
17
 
3.1%
16
 
2.9%
16
 
2.9%
16
 
2.9%
15
 
2.7%
Other values (131) 340
61.3%
Common
ValueCountFrequency (%)
( 33
49.3%
) 33
49.3%
1
 
1.5%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 555
88.9%
ASCII 68
 
10.9%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
34
 
6.1%
30
 
5.4%
24
 
4.3%
24
 
4.3%
23
 
4.1%
17
 
3.1%
16
 
2.9%
16
 
2.9%
16
 
2.9%
15
 
2.7%
Other values (131) 340
61.3%
ASCII
ValueCountFrequency (%)
( 33
48.5%
) 33
48.5%
S 1
 
1.5%
K 1
 
1.5%
None
ValueCountFrequency (%)
1
100.0%

원료명
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing8590
Missing (%)99.9%
Memory size67.3 KiB
2024-05-18T07:32:39.489640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.6666667
Min length2

Characters and Unicode

Total characters32
Distinct characters26
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

Unique12 ?
Unique (%)100.0%

Sample

1st row광어
2nd row도마
3rd row깐밤
4th row고등어
5th row사과
ValueCountFrequency (%)
광어 1
8.3%
도마 1
8.3%
깐밤 1
8.3%
고등어 1
8.3%
사과 1
8.3%
생오징어 1
8.3%
멸치 1
8.3%
건오징어 1
8.3%
감자 1
8.3%
오이 1
8.3%
Other values (2) 2
16.7%
2024-05-18T07:32:40.162115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
12.5%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (16) 16
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
12.5%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (16) 16
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
12.5%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (16) 16
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
 
12.5%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (16) 16
50.0%

생산업소
Text

MISSING 

Distinct91
Distinct (%)31.7%
Missing8315
Missing (%)96.7%
Memory size67.3 KiB
2024-05-18T07:32:40.668576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length6.9756098
Min length1

Characters and Unicode

Total characters2002
Distinct characters251
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

Unique50 ?
Unique (%)17.4%

Sample

1st row서울고등학교 집단급식소/ 서초구 효령로 197
2nd row서울고등학교 집단급식소/ 서초구 효령로 197
3rd row(주)상진/경기도 김포시 월곶면 대곶로 484번길 43-39
4th row나리내전집
5th row나리내전집
ValueCountFrequency (%)
삼라정 16
 
4.1%
오징어이야기 16
 
4.1%
트랭블루 15
 
3.9%
별난 12
 
3.1%
채빛 11
 
2.8%
노랑저고리 10
 
2.6%
코스트코코리아 10
 
2.6%
김밥천국 9
 
2.3%
주)에프아이씨 8
 
2.1%
강창구찹쌀진순대 8
 
2.1%
Other values (132) 273
70.4%
2024-05-18T07:32:41.691149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
5.0%
) 44
 
2.2%
( 44
 
2.2%
41
 
2.0%
39
 
1.9%
39
 
1.9%
35
 
1.7%
34
 
1.7%
32
 
1.6%
31
 
1.5%
Other values (241) 1562
78.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1630
81.4%
Decimal Number 121
 
6.0%
Space Separator 101
 
5.0%
Close Punctuation 44
 
2.2%
Open Punctuation 44
 
2.2%
Uppercase Letter 35
 
1.7%
Dash Punctuation 15
 
0.7%
Other Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
41
 
2.5%
39
 
2.4%
39
 
2.4%
35
 
2.1%
34
 
2.1%
32
 
2.0%
31
 
1.9%
31
 
1.9%
28
 
1.7%
28
 
1.7%
Other values (208) 1292
79.3%
Uppercase Letter
ValueCountFrequency (%)
L 6
17.1%
A 5
14.3%
I 3
8.6%
O 3
8.6%
D 3
8.6%
E 2
 
5.7%
T 2
 
5.7%
B 2
 
5.7%
S 2
 
5.7%
K 1
 
2.9%
Other values (6) 6
17.1%
Decimal Number
ValueCountFrequency (%)
1 30
24.8%
5 19
15.7%
8 17
14.0%
2 15
12.4%
3 9
 
7.4%
9 8
 
6.6%
0 7
 
5.8%
4 7
 
5.8%
6 6
 
5.0%
7 3
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 7
58.3%
/ 3
25.0%
. 2
 
16.7%
Space Separator
ValueCountFrequency (%)
101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1630
81.4%
Common 337
 
16.8%
Latin 35
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
41
 
2.5%
39
 
2.4%
39
 
2.4%
35
 
2.1%
34
 
2.1%
32
 
2.0%
31
 
1.9%
31
 
1.9%
28
 
1.7%
28
 
1.7%
Other values (208) 1292
79.3%
Common
ValueCountFrequency (%)
101
30.0%
) 44
13.1%
( 44
13.1%
1 30
 
8.9%
5 19
 
5.6%
8 17
 
5.0%
- 15
 
4.5%
2 15
 
4.5%
3 9
 
2.7%
9 8
 
2.4%
Other values (7) 35
 
10.4%
Latin
ValueCountFrequency (%)
L 6
17.1%
A 5
14.3%
I 3
8.6%
O 3
8.6%
D 3
8.6%
E 2
 
5.7%
T 2
 
5.7%
B 2
 
5.7%
S 2
 
5.7%
K 1
 
2.9%
Other values (6) 6
17.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1630
81.4%
ASCII 372
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
27.2%
) 44
11.8%
( 44
11.8%
1 30
 
8.1%
5 19
 
5.1%
8 17
 
4.6%
- 15
 
4.0%
2 15
 
4.0%
3 9
 
2.4%
9 8
 
2.2%
Other values (23) 70
18.8%
Hangul
ValueCountFrequency (%)
41
 
2.5%
39
 
2.4%
39
 
2.4%
35
 
2.1%
34
 
2.1%
32
 
2.0%
31
 
1.9%
31
 
1.9%
28
 
1.7%
28
 
1.7%
Other values (208) 1292
79.3%

수거일자
Real number (ℝ)

Distinct660
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20150522
Minimum20080902
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:42.169584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080902
5-th percentile20090723
Q120120220
median20151116
Q320180625
95-th percentile20210813
Maximum20240314
Range159412
Interquartile range (IQR)60404.75

Descriptive statistics

Standard deviation38553.475
Coefficient of variation (CV)0.0019132742
Kurtosis-0.96250978
Mean20150522
Median Absolute Deviation (MAD)30089
Skewness0.13410756
Sum1.7333479 × 1011
Variance1.4863704 × 109
MonotonicityDecreasing
2024-05-18T07:32:42.737762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090723 125
 
1.5%
20111202 123
 
1.4%
20230906 94
 
1.1%
20180514 89
 
1.0%
20190624 86
 
1.0%
20190920 74
 
0.9%
20091207 66
 
0.8%
20171102 63
 
0.7%
20160127 56
 
0.7%
20151007 55
 
0.6%
Other values (650) 7771
90.3%
ValueCountFrequency (%)
20080902 1
 
< 0.1%
20080926 1
 
< 0.1%
20080929 1
 
< 0.1%
20081007 3
 
< 0.1%
20081008 5
 
0.1%
20081009 3
 
< 0.1%
20090112 25
0.3%
20090116 38
0.4%
20090123 1
 
< 0.1%
20090212 15
 
0.2%
ValueCountFrequency (%)
20240314 4
 
< 0.1%
20240306 1
 
< 0.1%
20240227 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 1
 
< 0.1%
20240115 2
 
< 0.1%
20231229 34
0.4%
20231212 7
 
0.1%
20231115 1
 
< 0.1%
20231102 1
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)0.5%
Missing397
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean12.010835
Minimum0
Maximum1330
Zeros7
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:43.327032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile10
Maximum1330
Range1330
Interquartile range (IQR)2

Descriptive statistics

Standard deviation64.15936
Coefficient of variation (CV)5.3417902
Kurtosis75.465903
Mean12.010835
Median Absolute Deviation (MAD)1
Skewness8.0302685
Sum98548.9
Variance4116.4234
MonotonicityNot monotonic
2024-05-18T07:32:43.822096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1.0 3411
39.7%
2.0 1891
22.0%
3.0 1095
 
12.7%
6.0 533
 
6.2%
4.0 374
 
4.3%
5.0 289
 
3.4%
8.0 84
 
1.0%
7.0 68
 
0.8%
500.0 64
 
0.7%
10.0 63
 
0.7%
Other values (35) 333
 
3.9%
(Missing) 397
 
4.6%
ValueCountFrequency (%)
0.0 7
 
0.1%
1.0 3411
39.7%
2.0 1891
22.0%
2.9 1
 
< 0.1%
3.0 1095
 
12.7%
4.0 374
 
4.3%
5.0 289
 
3.4%
6.0 533
 
6.2%
7.0 68
 
0.8%
8.0 84
 
1.0%
ValueCountFrequency (%)
1330.0 1
 
< 0.1%
870.0 1
 
< 0.1%
800.0 1
 
< 0.1%
600.0 23
 
0.3%
510.0 2
 
< 0.1%
500.0 64
0.7%
435.0 1
 
< 0.1%
400.0 1
 
< 0.1%
350.0 1
 
< 0.1%
300.0 44
0.5%

제품규격(정량)
Text

MISSING 

Distinct701
Distinct (%)10.1%
Missing1657
Missing (%)19.3%
Memory size67.3 KiB
2024-05-18T07:32:44.881365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9219582
Min length1

Characters and Unicode

Total characters20293
Distinct characters26
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique354 ?
Unique (%)5.1%

Sample

1st row750
2nd row600
3rd row600
4th row800
5th row350.2
ValueCountFrequency (%)
1 636
 
9.2%
500 483
 
7.0%
100 446
 
6.4%
200 423
 
6.1%
300 348
 
5.0%
600 328
 
4.7%
400 202
 
2.9%
150 185
 
2.7%
900 178
 
2.6%
250 167
 
2.4%
Other values (689) 3549
51.1%
2024-05-18T07:32:46.297268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8240
40.6%
1 2452
 
12.1%
5 1996
 
9.8%
2 1697
 
8.4%
3 1340
 
6.6%
4 883
 
4.4%
6 865
 
4.3%
g 597
 
2.9%
7 563
 
2.8%
8 561
 
2.8%
Other values (16) 1099
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19040
93.8%
Lowercase Letter 975
 
4.8%
Other Punctuation 250
 
1.2%
Other Letter 15
 
0.1%
Uppercase Letter 10
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8240
43.3%
1 2452
 
12.9%
5 1996
 
10.5%
2 1697
 
8.9%
3 1340
 
7.0%
4 883
 
4.6%
6 865
 
4.5%
7 563
 
3.0%
8 561
 
2.9%
9 443
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
g 597
61.2%
l 171
 
17.5%
m 152
 
15.6%
k 51
 
5.2%
3
 
0.3%
c 1
 
0.1%
Other Letter
ValueCountFrequency (%)
6
40.0%
6
40.0%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 238
95.2%
, 12
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
G 7
70.0%
L 3
30.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19296
95.1%
Latin 982
 
4.8%
Hangul 15
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8240
42.7%
1 2452
 
12.7%
5 1996
 
10.3%
2 1697
 
8.8%
3 1340
 
6.9%
4 883
 
4.6%
6 865
 
4.5%
7 563
 
2.9%
8 561
 
2.9%
9 443
 
2.3%
Other values (4) 256
 
1.3%
Latin
ValueCountFrequency (%)
g 597
60.8%
l 171
 
17.4%
m 152
 
15.5%
k 51
 
5.2%
G 7
 
0.7%
L 3
 
0.3%
c 1
 
0.1%
Hangul
ValueCountFrequency (%)
6
40.0%
6
40.0%
1
 
6.7%
1
 
6.7%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20272
99.9%
Hangul 15
 
0.1%
Letterlike Symbols 3
 
< 0.1%
CJK Compat 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8240
40.6%
1 2452
 
12.1%
5 1996
 
9.8%
2 1697
 
8.4%
3 1340
 
6.6%
4 883
 
4.4%
6 865
 
4.3%
g 597
 
2.9%
7 563
 
2.8%
8 561
 
2.8%
Other values (9) 1078
 
5.3%
Hangul
ValueCountFrequency (%)
6
40.0%
6
40.0%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Letterlike Symbols
ValueCountFrequency (%)
3
100.0%
CJK Compat
ValueCountFrequency (%)
3
100.0%

단위(정량)
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
g
4276 
<NA>
2450 
ML
1059 
KG
485 
LT
 
215

Length

Max length4
Median length1
Mean length2.0589398
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 4276
49.7%
<NA> 2450
28.5%
ML 1059
 
12.3%
KG 485
 
5.6%
LT 215
 
2.5%
117
 
1.4%

Length

2024-05-18T07:32:46.823843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:47.469078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 4276
49.7%
na 2450
28.5%
ml 1059
 
12.3%
kg 485
 
5.6%
lt 215
 
2.5%
117
 
1.4%

수거량(자유)
Categorical

IMBALANCE 

Distinct32
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
8216 
1개
 
223
소형용기1개
 
26
600g
 
24
3개
 
23
Other values (27)
 
90

Length

Max length9
Median length4
Mean length3.942339
Min length1

Unique

Unique13 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8216
95.5%
1개 223
 
2.6%
소형용기1개 26
 
0.3%
600g 24
 
0.3%
3개 23
 
0.3%
1 17
 
0.2%
2개 14
 
0.2%
3건 8
 
0.1%
스왑 면봉 검체 8
 
0.1%
1L 7
 
0.1%
Other values (22) 36
 
0.4%

Length

2024-05-18T07:32:48.017762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8216
95.2%
1개 227
 
2.6%
소형용기1개 26
 
0.3%
3개 25
 
0.3%
600g 24
 
0.3%
1 17
 
0.2%
2개 17
 
0.2%
스왑 11
 
0.1%
3건 8
 
0.1%
면봉 8
 
0.1%
Other values (25) 52
 
0.6%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct955
Distinct (%)32.6%
Missing5674
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean20717475
Minimum20060502
Maximum99990101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:48.551465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060502
5-th percentile20120821
Q120160814
median20170907
Q320181114
95-th percentile20230629
Maximum99990101
Range79929599
Interquartile range (IQR)20299.75

Descriptive statistics

Standard deviation6575351.7
Coefficient of variation (CV)0.3173819
Kurtosis141.64568
Mean20717475
Median Absolute Deviation (MAD)10187
Skewness11.981084
Sum6.0660767 × 1010
Variance4.323525 × 1013
MonotonicityNot monotonic
2024-05-18T07:32:49.070062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180514 91
 
1.1%
20191211 49
 
0.6%
20200120 46
 
0.5%
20180906 45
 
0.5%
20180601 45
 
0.5%
20230519 44
 
0.5%
20180308 38
 
0.4%
20210624 29
 
0.3%
20170907 26
 
0.3%
20170120 23
 
0.3%
Other values (945) 2492
29.0%
(Missing) 5674
66.0%
ValueCountFrequency (%)
20060502 1
 
< 0.1%
20090612 1
 
< 0.1%
20100428 1
 
< 0.1%
20100711 1
 
< 0.1%
20101116 1
 
< 0.1%
20110705 1
 
< 0.1%
20110829 6
0.1%
20111009 1
 
< 0.1%
20111103 1
 
< 0.1%
20111118 1
 
< 0.1%
ValueCountFrequency (%)
99990101 20
0.2%
20240314 4
 
< 0.1%
20240227 2
 
< 0.1%
20240226 1
 
< 0.1%
20240115 2
 
< 0.1%
20231229 7
 
0.1%
20231228 17
0.2%
20231227 7
 
0.1%
20231226 3
 
< 0.1%
20231212 7
 
0.1%

제조일자(롯트)
Text

MISSING 

Distinct62
Distinct (%)100.0%
Missing8540
Missing (%)99.3%
Memory size67.3 KiB
2024-05-18T07:32:49.712995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.7741935
Min length4

Characters and Unicode

Total characters606
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st rowW22001
2nd row1655001
3rd row20159271
4th row20149882
5th row305032005
ValueCountFrequency (%)
l 4
 
3.8%
8 4
 
3.8%
kye 3
 
2.9%
8809642 2
 
1.9%
l2 2
 
1.9%
19 2
 
1.9%
1218503 1
 
1.0%
217242 1
 
1.0%
l2331 1
 
1.0%
l8130 1
 
1.0%
Other values (83) 83
79.8%
2024-05-18T07:32:50.456493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 95
15.7%
2 80
13.2%
0 76
12.5%
3 48
7.9%
42
6.9%
L 41
6.8%
8 40
6.6%
4 31
 
5.1%
7 28
 
4.6%
9 27
 
4.5%
Other values (23) 98
16.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 467
77.1%
Uppercase Letter 78
 
12.9%
Space Separator 42
 
6.9%
Other Punctuation 9
 
1.5%
Dash Punctuation 6
 
1.0%
Lowercase Letter 4
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 41
52.6%
A 7
 
9.0%
E 6
 
7.7%
K 4
 
5.1%
Y 3
 
3.8%
C 3
 
3.8%
V 2
 
2.6%
J 2
 
2.6%
D 2
 
2.6%
G 1
 
1.3%
Other values (7) 7
 
9.0%
Decimal Number
ValueCountFrequency (%)
1 95
20.3%
2 80
17.1%
0 76
16.3%
3 48
10.3%
8 40
8.6%
4 31
 
6.6%
7 28
 
6.0%
9 27
 
5.8%
5 24
 
5.1%
6 18
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 5
55.6%
: 4
44.4%
Lowercase Letter
ValueCountFrequency (%)
l 3
75.0%
c 1
 
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 524
86.5%
Latin 82
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 41
50.0%
A 7
 
8.5%
E 6
 
7.3%
K 4
 
4.9%
Y 3
 
3.7%
C 3
 
3.7%
l 3
 
3.7%
V 2
 
2.4%
J 2
 
2.4%
D 2
 
2.4%
Other values (9) 9
 
11.0%
Common
ValueCountFrequency (%)
1 95
18.1%
2 80
15.3%
0 76
14.5%
3 48
9.2%
42
8.0%
8 40
7.6%
4 31
 
5.9%
7 28
 
5.3%
9 27
 
5.2%
5 24
 
4.6%
Other values (4) 33
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 95
15.7%
2 80
13.2%
0 76
12.5%
3 48
7.9%
42
6.9%
L 41
6.8%
8 40
6.6%
4 31
 
5.1%
7 28
 
4.6%
9 27
 
4.5%
Other values (23) 98
16.2%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)80.0%
Missing8582
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean18115509
Minimum1
Maximum20150128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:50.792444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q120120528
median20120616
Q320133270
95-th percentile20150121
Maximum20150128
Range20150127
Interquartile range (IQR)12742.75

Descriptive statistics

Standard deviation6195384.1
Coefficient of variation (CV)0.34199338
Kurtosis7.0369634
Mean18115509
Median Absolute Deviation (MAD)5008
Skewness-2.8879194
Sum3.6231018 × 108
Variance3.8382784 × 1013
MonotonicityNot monotonic
2024-05-18T07:32:51.207105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20120529 5
 
0.1%
20120916 1
 
< 0.1%
20130328 1
 
< 0.1%
20120110 1
 
< 0.1%
20120523 1
 
< 0.1%
1 1
 
< 0.1%
20111107 1
 
< 0.1%
20120923 1
 
< 0.1%
20150119 1
 
< 0.1%
20150121 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 8582
99.8%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 1
 
< 0.1%
20111107 1
 
< 0.1%
20120110 1
 
< 0.1%
20120523 1
 
< 0.1%
20120529 5
0.1%
20120704 1
 
< 0.1%
20120916 1
 
< 0.1%
20120923 1
 
< 0.1%
20130328 1
 
< 0.1%
ValueCountFrequency (%)
20150128 1
< 0.1%
20150121 1
< 0.1%
20150119 1
< 0.1%
20140919 1
< 0.1%
20140912 1
< 0.1%
20130723 1
< 0.1%
20130328 1
< 0.1%
20120923 1
< 0.1%
20120916 1
< 0.1%
20120704 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)68.0%
Missing8577
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean7242430.5
Minimum7
Maximum20121121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:51.585298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile30
Q130
median360
Q320111220
95-th percentile20120804
Maximum20121121
Range20121114
Interquartile range (IQR)20111190

Descriptive statistics

Standard deviation9855432.3
Coefficient of variation (CV)1.3607907
Kurtosis-1.7621863
Mean7242430.5
Median Absolute Deviation (MAD)330
Skewness0.62124767
Sum1.8106076 × 108
Variance9.7129546 × 1013
MonotonicityNot monotonic
2024-05-18T07:32:52.169305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
30 8
 
0.1%
180 2
 
< 0.1%
20120620 1
 
< 0.1%
20111220 1
 
< 0.1%
20110705 1
 
< 0.1%
20120804 1
 
< 0.1%
20120802 1
 
< 0.1%
20120406 1
 
< 0.1%
20121121 1
 
< 0.1%
7 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 8577
99.7%
ValueCountFrequency (%)
7 1
 
< 0.1%
30 8
0.1%
180 2
 
< 0.1%
270 1
 
< 0.1%
360 1
 
< 0.1%
365 1
 
< 0.1%
450 1
 
< 0.1%
1095 1
 
< 0.1%
20110705 1
 
< 0.1%
20111212 1
 
< 0.1%
ValueCountFrequency (%)
20121121 1
< 0.1%
20120804 1
< 0.1%
20120802 1
< 0.1%
20120725 1
< 0.1%
20120620 1
< 0.1%
20120406 1
< 0.1%
20111220 1
< 0.1%
20111212 1
< 0.1%
20110705 1
< 0.1%
1095 1
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
실온
3525 
<NA>
2106 
기타
1690 
냉장
1078 
냉동
 
203

Length

Max length4
Median length2
Mean length2.4896536
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row냉장
2nd row실온
3rd row실온
4th row냉장
5th row냉장

Common Values

ValueCountFrequency (%)
실온 3525
41.0%
<NA> 2106
24.5%
기타 1690
19.6%
냉장 1078
 
12.5%
냉동 203
 
2.4%

Length

2024-05-18T07:32:52.695801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:53.115764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3525
41.0%
na 2106
24.5%
기타 1690
19.6%
냉장 1078
 
12.5%
냉동 203
 
2.4%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

어린이기호식품유형
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

검사기관명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
4465 
1
4136 
2
 
1

Length

Max length4
Median length4
Mean length2.557196
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4465
51.9%
1 4136
48.1%
2 1
 
< 0.1%

Length

2024-05-18T07:32:53.597786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:53.958275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4465
51.9%
1 4136
48.1%
2 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct706
Distinct (%)48.6%
Missing7149
Missing (%)83.1%
Memory size67.3 KiB
2024-05-18T07:32:54.532372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length6.3000688
Min length2

Characters and Unicode

Total characters9154
Distinct characters393
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

Unique475 ?
Unique (%)32.7%

Sample

1st row㈜오뚜기
2nd row대상㈜
3rd row㈜세방유통
4th row삼약제넥스
5th row한진식품
ValueCountFrequency (%)
대상 34
 
2.1%
씨제이제일제당 32
 
2.0%
주식회사 28
 
1.7%
오뚜기 23
 
1.4%
농심 21
 
1.3%
대상㈜ 18
 
1.1%
씨제이 17
 
1.0%
삼양식품 14
 
0.9%
대상(주 14
 
0.9%
주)이마트 13
 
0.8%
Other values (741) 1408
86.8%
2024-05-18T07:32:55.754796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
629
 
6.9%
( 549
 
6.0%
) 548
 
6.0%
288
 
3.1%
278
 
3.0%
219
 
2.4%
197
 
2.2%
170
 
1.9%
169
 
1.8%
144
 
1.6%
Other values (383) 5963
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7645
83.5%
Open Punctuation 549
 
6.0%
Close Punctuation 548
 
6.0%
Space Separator 169
 
1.8%
Lowercase Letter 97
 
1.1%
Other Symbol 71
 
0.8%
Uppercase Letter 39
 
0.4%
Other Punctuation 32
 
0.3%
Decimal Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
629
 
8.2%
288
 
3.8%
278
 
3.6%
219
 
2.9%
197
 
2.6%
170
 
2.2%
144
 
1.9%
138
 
1.8%
129
 
1.7%
114
 
1.5%
Other values (361) 5339
69.8%
Lowercase Letter
ValueCountFrequency (%)
f 21
21.6%
a 16
16.5%
p 16
16.5%
m 16
16.5%
b 15
15.5%
s 5
 
5.2%
n 5
 
5.2%
c 2
 
2.1%
j 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
F 22
56.4%
N 11
28.2%
B 6
 
15.4%
Other Punctuation
ValueCountFrequency (%)
; 16
50.0%
& 14
43.8%
: 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
0 1
25.0%
3 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 549
100.0%
Close Punctuation
ValueCountFrequency (%)
) 548
100.0%
Space Separator
ValueCountFrequency (%)
169
100.0%
Other Symbol
ValueCountFrequency (%)
71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7716
84.3%
Common 1302
 
14.2%
Latin 136
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
629
 
8.2%
288
 
3.7%
278
 
3.6%
219
 
2.8%
197
 
2.6%
170
 
2.2%
144
 
1.9%
138
 
1.8%
129
 
1.7%
114
 
1.5%
Other values (362) 5410
70.1%
Latin
ValueCountFrequency (%)
F 22
16.2%
f 21
15.4%
a 16
11.8%
p 16
11.8%
m 16
11.8%
b 15
11.0%
N 11
8.1%
B 6
 
4.4%
s 5
 
3.7%
n 5
 
3.7%
Other values (2) 3
 
2.2%
Common
ValueCountFrequency (%)
( 549
42.2%
) 548
42.1%
169
 
13.0%
; 16
 
1.2%
& 14
 
1.1%
2 2
 
0.2%
: 2
 
0.2%
0 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7645
83.5%
ASCII 1438
 
15.7%
None 71
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
629
 
8.2%
288
 
3.8%
278
 
3.6%
219
 
2.9%
197
 
2.6%
170
 
2.2%
144
 
1.9%
138
 
1.8%
129
 
1.7%
114
 
1.5%
Other values (361) 5339
69.8%
ASCII
ValueCountFrequency (%)
( 549
38.2%
) 548
38.1%
169
 
11.8%
F 22
 
1.5%
f 21
 
1.5%
a 16
 
1.1%
; 16
 
1.1%
p 16
 
1.1%
m 16
 
1.1%
b 15
 
1.0%
Other values (11) 50
 
3.5%
None
ValueCountFrequency (%)
71
100.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
국내
6444 
국외
2158 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내 6444
74.9%
국외 2158
 
25.1%

Length

2024-05-18T07:32:56.251205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:56.633087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 6444
74.9%
국외 2158
 
25.1%

국가명
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
7703 
미국
 
187
이탈리아
 
113
일본
 
97
독일
 
54
Other values (39)
 
448

Length

Max length7
Median length4
Mean length3.869914
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> 7703
89.5%
미국 187
 
2.2%
이탈리아 113
 
1.3%
일본 97
 
1.1%
독일 54
 
0.6%
태국 49
 
0.6%
중국 48
 
0.6%
프랑스 35
 
0.4%
스페인 33
 
0.4%
캐나다 30
 
0.3%
Other values (34) 253
 
2.9%

Length

2024-05-18T07:32:57.140131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7703
89.5%
미국 187
 
2.2%
이탈리아 113
 
1.3%
일본 97
 
1.1%
독일 54
 
0.6%
태국 49
 
0.6%
중국 49
 
0.6%
프랑스 35
 
0.4%
스페인 33
 
0.4%
캐나다 30
 
0.3%
Other values (35) 259
 
3.0%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
1
4877 
<NA>
2438 
2
1287 

Length

Max length4
Median length1
Mean length1.8502674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 4877
56.7%
<NA> 2438
28.3%
2 1287
 
15.0%

Length

2024-05-18T07:32:57.720471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:32:58.172735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4877
56.7%
na 2438
28.3%
2 1287
 
15.0%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct246
Distinct (%)8.3%
Missing5647
Missing (%)65.6%
Infinite0
Infinite (%)0.0%
Mean20163478
Minimum20100512
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:32:58.754321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100512
5-th percentile20110518
Q120111209
median20161214
Q320180807
95-th percentile20230906
Maximum20240314
Range139802
Interquartile range (IQR)69598

Descriptive statistics

Standard deviation38811.274
Coefficient of variation (CV)0.0019248303
Kurtosis-0.79904951
Mean20163478
Median Absolute Deviation (MAD)20010
Skewness0.13786156
Sum5.9583077 × 1010
Variance1.506315 × 109
MonotonicityNot monotonic
2024-05-18T07:32:59.332823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111202 123
 
1.4%
20230906 94
 
1.1%
20171102 59
 
0.7%
20160127 56
 
0.7%
20160831 53
 
0.6%
20200916 50
 
0.6%
20170904 49
 
0.6%
20110707 45
 
0.5%
20230703 45
 
0.5%
20230519 44
 
0.5%
Other values (236) 2337
27.2%
(Missing) 5647
65.6%
ValueCountFrequency (%)
20100512 2
 
< 0.1%
20100715 1
 
< 0.1%
20100802 1
 
< 0.1%
20100803 1
 
< 0.1%
20100920 6
 
0.1%
20101103 3
 
< 0.1%
20110113 30
0.3%
20110211 1
 
< 0.1%
20110215 30
0.3%
20110216 1
 
< 0.1%
ValueCountFrequency (%)
20240314 4
 
< 0.1%
20240306 1
 
< 0.1%
20240227 3
 
< 0.1%
20240119 1
 
< 0.1%
20240115 2
 
< 0.1%
20240103 7
 
0.1%
20231229 27
0.3%
20231212 7
 
0.1%
20231115 1
 
< 0.1%
20231102 1
 
< 0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct168
Distinct (%)9.6%
Missing6852
Missing (%)79.7%
Infinite0
Infinite (%)0.0%
Mean20088197
Minimum2170216
Maximum20220404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:33:00.051154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2170216
5-th percentile20160128
Q120160912
median20170310
Q320171128
95-th percentile20201007
Maximum20220404
Range18050188
Interquartile range (IQR)10216

Descriptive statistics

Standard deviation1214694.3
Coefficient of variation (CV)0.060468057
Kurtosis214.30424
Mean20088197
Median Absolute Deviation (MAD)9295.5
Skewness-14.697822
Sum3.5154345 × 1010
Variance1.4754821 × 1012
MonotonicityNot monotonic
2024-05-18T07:33:00.723589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171116 59
 
0.7%
20160205 56
 
0.7%
20171214 54
 
0.6%
20160318 40
 
0.5%
20170206 32
 
0.4%
20161007 31
 
0.4%
20210210 31
 
0.4%
20181004 28
 
0.3%
20171219 27
 
0.3%
20170918 27
 
0.3%
Other values (158) 1365
 
15.9%
(Missing) 6852
79.7%
ValueCountFrequency (%)
2170216 8
0.1%
20100721 1
 
< 0.1%
20100810 1
 
< 0.1%
20140227 1
 
< 0.1%
20140711 5
0.1%
20140715 5
0.1%
20140721 11
0.1%
20141010 5
0.1%
20141013 6
0.1%
20141014 6
0.1%
ValueCountFrequency (%)
20220404 1
 
< 0.1%
20220303 5
 
0.1%
20220302 3
 
< 0.1%
20211206 7
 
0.1%
20211110 2
 
< 0.1%
20210427 21
0.2%
20210210 31
0.4%
20201008 3
 
< 0.1%
20201007 22
0.3%
20200929 27
0.3%

판정구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
6732 
1
1861 
2
 
9

Length

Max length4
Median length4
Mean length3.3478261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6732
78.3%
1 1861
 
21.6%
2 9
 
0.1%

Length

2024-05-18T07:33:01.404460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:01.840898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6732
78.3%
1 1861
 
21.6%
2 9
 
0.1%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

처리결과
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
8584 
한우
 
16
이첩
 
1
영업정지1일에 갈음하여 과징금 367만원 및 해당제품폐기
 
1

Length

Max length31
Median length4
Mean length3.9991862
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8584
99.8%
한우 16
 
0.2%
이첩 1
 
< 0.1%
영업정지1일에 갈음하여 과징금 367만원 및 해당제품폐기 1
 
< 0.1%

Length

2024-05-18T07:33:02.574958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:03.030890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8584
99.7%
한우 16
 
0.2%
이첩 1
 
< 0.1%
영업정지1일에 1
 
< 0.1%
갈음하여 1
 
< 0.1%
과징금 1
 
< 0.1%
367만원 1
 
< 0.1%
1
 
< 0.1%
해당제품폐기 1
 
< 0.1%

수거품처리
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing8601
Missing (%)> 99.9%
Memory size67.3 KiB
2024-05-18T07:33:03.525046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
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

Unique1 ?
Unique (%)100.0%

Sample

1st row재고 없음
ValueCountFrequency (%)
재고 1
50.0%
없음 1
50.0%
2024-05-18T07:33:04.510594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
80.0%
Space Separator 1
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
80.0%
Common 1
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
80.0%
ASCII 1
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
ASCII
ValueCountFrequency (%)
1
100.0%

교부번호
Real number (ℝ)

Distinct785
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0034895 × 1010
Minimum1.9760098 × 1010
Maximum2.0230131 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:33:05.074993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9760098 × 1010
5-th percentile1.9950099 × 1010
Q11.99901 × 1010
median2.0040101 × 1010
Q32.0050098 × 1010
95-th percentile2.0170099 × 1010
Maximum2.0230131 × 1010
Range4.7003287 × 108
Interquartile range (IQR)59997990

Descriptive statistics

Standard deviation65305542
Coefficient of variation (CV)0.00325959
Kurtosis0.54012825
Mean2.0034895 × 1010
Median Absolute Deviation (MAD)50000836
Skewness0.53129363
Sum1.7234016 × 1014
Variance4.2648138 × 1015
MonotonicityNot monotonic
2024-05-18T07:33:05.524640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050098297 2338
27.2%
19990100307 1886
21.9%
19950098595 537
 
6.2%
20170099317 290
 
3.4%
20000099126 246
 
2.9%
20010099397 128
 
1.5%
20110098071 93
 
1.1%
20040098113 90
 
1.0%
20010098111 75
 
0.9%
19900098146 60
 
0.7%
Other values (775) 2859
33.2%
ValueCountFrequency (%)
19760098014 5
0.1%
19800098001 3
< 0.1%
19800098046 1
 
< 0.1%
19830098047 2
 
< 0.1%
19830098298 1
 
< 0.1%
19840098306 1
 
< 0.1%
19840098367 2
 
< 0.1%
19850098048 1
 
< 0.1%
19850098198 1
 
< 0.1%
19850098219 2
 
< 0.1%
ValueCountFrequency (%)
20230130886 1
 
< 0.1%
20230129599 2
 
< 0.1%
20230129226 1
 
< 0.1%
20220123239 1
 
< 0.1%
20220123011 44
0.5%
20220122953 1
 
< 0.1%
20220122235 1
 
< 0.1%
20220122159 1
 
< 0.1%
20220122007 3
 
< 0.1%
20220121581 2
 
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

폐기량(Kg)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
8600 
0
 
2

Length

Max length4
Median length4
Mean length3.9993025
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8600
> 99.9%
0 2
 
< 0.1%

Length

2024-05-18T07:33:06.016261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:06.362543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8600
> 99.9%
0 2
 
< 0.1%

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB

폐기방법
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing8601
Missing (%)> 99.9%
Memory size67.3 KiB
2024-05-18T07:33:06.632434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row재고량 없음
ValueCountFrequency (%)
재고량 1
50.0%
없음 1
50.0%
2024-05-18T07:33:07.423260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
83.3%
Space Separator 1
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
83.3%
Common 1
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
83.3%
ASCII 1
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
ASCII
ValueCountFrequency (%)
1
100.0%

소재지(도로명)
Text

MISSING 

Distinct481
Distinct (%)6.2%
Missing822
Missing (%)9.6%
Memory size67.3 KiB
2024-05-18T07:33:08.412221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length64
Mean length28.955141
Min length22

Characters and Unicode

Total characters225271
Distinct characters271
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique196 ?
Unique (%)2.5%

Sample

1st row서울특별시 서초구 명달로 51, 1층 103호 (방배동)
2nd row서울특별시 서초구 효령로 197, (서초동)
3rd row서울특별시 서초구 효령로 197, (서초동)
4th row서울특별시 서초구 도구로 119-2, 1층 103호 (방배동)
5th row서울특별시 서초구 서초대로 277, 기영빌딩 2층 (서초동)
ValueCountFrequency (%)
서울특별시 7780
17.9%
서초구 7780
17.9%
양재동 2460
 
5.7%
16 2430
 
5.6%
매헌로 2383
 
5.5%
양재동,지하1층 2312
 
5.3%
10 1936
 
4.5%
청계산로 1932
 
4.5%
서초동 1249
 
2.9%
1층 693
 
1.6%
Other values (698) 12453
28.7%
2024-05-18T07:33:09.914989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35629
 
15.8%
18088
 
8.0%
, 12259
 
5.4%
1 11278
 
5.0%
10238
 
4.5%
8106
 
3.6%
7861
 
3.5%
7813
 
3.5%
) 7809
 
3.5%
( 7809
 
3.5%
Other values (261) 98381
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134688
59.8%
Space Separator 35629
 
15.8%
Decimal Number 26561
 
11.8%
Other Punctuation 12275
 
5.4%
Close Punctuation 7809
 
3.5%
Open Punctuation 7809
 
3.5%
Dash Punctuation 179
 
0.1%
Uppercase Letter 167
 
0.1%
Math Symbol 152
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18088
 
13.4%
10238
 
7.6%
8106
 
6.0%
7861
 
5.8%
7813
 
5.8%
7789
 
5.8%
7783
 
5.8%
7780
 
5.8%
7780
 
5.8%
5033
 
3.7%
Other values (232) 46417
34.5%
Decimal Number
ValueCountFrequency (%)
1 11278
42.5%
6 3789
 
14.3%
0 3012
 
11.3%
2 2395
 
9.0%
3 1328
 
5.0%
9 1163
 
4.4%
5 1042
 
3.9%
7 948
 
3.6%
8 857
 
3.2%
4 749
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
B 137
82.0%
A 8
 
4.8%
E 6
 
3.6%
J 4
 
2.4%
W 4
 
2.4%
T 3
 
1.8%
S 2
 
1.2%
L 1
 
0.6%
K 1
 
0.6%
O 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 12259
99.9%
? 14
 
0.1%
. 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
35629
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7809
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7809
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 179
100.0%
Math Symbol
ValueCountFrequency (%)
~ 152
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134688
59.8%
Common 90414
40.1%
Latin 169
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18088
 
13.4%
10238
 
7.6%
8106
 
6.0%
7861
 
5.8%
7813
 
5.8%
7789
 
5.8%
7783
 
5.8%
7780
 
5.8%
7780
 
5.8%
5033
 
3.7%
Other values (232) 46417
34.5%
Common
ValueCountFrequency (%)
35629
39.4%
, 12259
 
13.6%
1 11278
 
12.5%
) 7809
 
8.6%
( 7809
 
8.6%
6 3789
 
4.2%
0 3012
 
3.3%
2 2395
 
2.6%
3 1328
 
1.5%
9 1163
 
1.3%
Other values (8) 3943
 
4.4%
Latin
ValueCountFrequency (%)
B 137
81.1%
A 8
 
4.7%
E 6
 
3.6%
J 4
 
2.4%
W 4
 
2.4%
T 3
 
1.8%
S 2
 
1.2%
a 2
 
1.2%
L 1
 
0.6%
K 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134688
59.8%
ASCII 90583
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35629
39.3%
, 12259
 
13.5%
1 11278
 
12.5%
) 7809
 
8.6%
( 7809
 
8.6%
6 3789
 
4.2%
0 3012
 
3.3%
2 2395
 
2.6%
3 1328
 
1.5%
9 1163
 
1.3%
Other values (19) 4112
 
4.5%
Hangul
ValueCountFrequency (%)
18088
 
13.4%
10238
 
7.6%
8106
 
6.0%
7861
 
5.8%
7813
 
5.8%
7789
 
5.8%
7783
 
5.8%
7780
 
5.8%
7780
 
5.8%
5033
 
3.7%
Other values (232) 46417
34.5%

소재지(지번)
Text

MISSING 

Distinct774
Distinct (%)9.5%
Missing444
Missing (%)5.2%
Memory size67.3 KiB
2024-05-18T07:33:10.736293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length56
Mean length28.129321
Min length21

Characters and Unicode

Total characters229479
Distinct characters298
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique398 ?
Unique (%)4.9%

Sample

1st row서울특별시 서초구 방배동 1002번지 15호 부흥빌딩-103
2nd row서울특별시 서초구 서초동 1526번지 1호
3rd row서울특별시 서초구 서초동 1526번지 1호
4th row서울특별시 서초구 방배동 864번지 37호 1층-103
5th row서울특별시 서초구 서초동 1716번지 6호 기영빌딩, 2층
ValueCountFrequency (%)
서울특별시 8158
18.1%
서초구 8158
18.1%
양재동 4698
 
10.4%
지하1층 2477
 
5.5%
215번지 2264
 
5.0%
230번지 1849
 
4.1%
서초동 1614
 
3.6%
0호 1280
 
2.8%
1층 1029
 
2.3%
1호 858
 
1.9%
Other values (875) 12576
28.0%
2024-05-18T07:33:12.131701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56258
24.5%
18282
 
8.0%
12148
 
5.3%
1 11691
 
5.1%
10112
 
4.4%
8248
 
3.6%
8228
 
3.6%
8180
 
3.6%
8169
 
3.6%
8166
 
3.6%
Other values (288) 79997
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133006
58.0%
Space Separator 56258
24.5%
Decimal Number 37691
 
16.4%
Other Punctuation 1001
 
0.4%
Close Punctuation 496
 
0.2%
Open Punctuation 496
 
0.2%
Uppercase Letter 197
 
0.1%
Math Symbol 170
 
0.1%
Dash Punctuation 140
 
0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18282
13.7%
12148
 
9.1%
10112
 
7.6%
8248
 
6.2%
8228
 
6.2%
8180
 
6.2%
8169
 
6.1%
8166
 
6.1%
8159
 
6.1%
8158
 
6.1%
Other values (252) 35156
26.4%
Uppercase Letter
ValueCountFrequency (%)
B 152
77.2%
A 10
 
5.1%
E 6
 
3.0%
T 6
 
3.0%
W 5
 
2.5%
J 5
 
2.5%
L 4
 
2.0%
C 3
 
1.5%
G 2
 
1.0%
S 2
 
1.0%
Other values (2) 2
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 11691
31.0%
2 6601
17.5%
0 5087
13.5%
3 4123
 
10.9%
5 3675
 
9.8%
4 1639
 
4.3%
7 1368
 
3.6%
8 1297
 
3.4%
6 1197
 
3.2%
9 1013
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 658
65.7%
? 323
32.3%
/ 18
 
1.8%
. 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
m 5
31.2%
e 5
31.2%
i 5
31.2%
l 1
 
6.2%
Space Separator
ValueCountFrequency (%)
56258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 496
100.0%
Open Punctuation
ValueCountFrequency (%)
( 496
100.0%
Math Symbol
ValueCountFrequency (%)
~ 170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Letter Number
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133006
58.0%
Common 96252
41.9%
Latin 221
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18282
13.7%
12148
 
9.1%
10112
 
7.6%
8248
 
6.2%
8228
 
6.2%
8180
 
6.2%
8169
 
6.1%
8166
 
6.1%
8159
 
6.1%
8158
 
6.1%
Other values (252) 35156
26.4%
Common
ValueCountFrequency (%)
56258
58.4%
1 11691
 
12.1%
2 6601
 
6.9%
0 5087
 
5.3%
3 4123
 
4.3%
5 3675
 
3.8%
4 1639
 
1.7%
7 1368
 
1.4%
8 1297
 
1.3%
6 1197
 
1.2%
Other values (9) 3316
 
3.4%
Latin
ValueCountFrequency (%)
B 152
68.8%
A 10
 
4.5%
8
 
3.6%
E 6
 
2.7%
T 6
 
2.7%
m 5
 
2.3%
e 5
 
2.3%
W 5
 
2.3%
J 5
 
2.3%
i 5
 
2.3%
Other values (7) 14
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133006
58.0%
ASCII 96465
42.0%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56258
58.3%
1 11691
 
12.1%
2 6601
 
6.8%
0 5087
 
5.3%
3 4123
 
4.3%
5 3675
 
3.8%
4 1639
 
1.7%
7 1368
 
1.4%
8 1297
 
1.3%
6 1197
 
1.2%
Other values (25) 3529
 
3.7%
Hangul
ValueCountFrequency (%)
18282
13.7%
12148
 
9.1%
10112
 
7.6%
8248
 
6.2%
8228
 
6.2%
8180
 
6.2%
8169
 
6.1%
8166
 
6.1%
8159
 
6.1%
8158
 
6.1%
Other values (252) 35156
26.4%
Number Forms
ValueCountFrequency (%)
8
100.0%

업소전화번호
Text

MISSING 

Distinct513
Distinct (%)7.3%
Missing1561
Missing (%)18.1%
Memory size67.3 KiB
2024-05-18T07:33:13.255195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.103963
Min length2

Characters and Unicode

Total characters71142
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)3.7%

Sample

1st row02 5258902
2nd row02 5258902
3rd row070 42541920
4th row02 587 7151
5th row0234981140
ValueCountFrequency (%)
0221551052 2307
24.3%
0234981140 1886
19.9%
02 1845
19.4%
02530 234
 
2.5%
5713 234
 
2.5%
0234791204 202
 
2.1%
5725959 151
 
1.6%
597 98
 
1.0%
5008 93
 
1.0%
5220468 90
 
0.9%
Other values (559) 2346
24.7%
2024-05-18T07:33:15.053619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13526
19.0%
2 13444
18.9%
5 10516
14.8%
1 10116
14.2%
4 5701
8.0%
3 4565
 
6.4%
8 3619
 
5.1%
9 3315
 
4.7%
3045
 
4.3%
7 2146
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68097
95.7%
Space Separator 3045
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13526
19.9%
2 13444
19.7%
5 10516
15.4%
1 10116
14.9%
4 5701
8.4%
3 4565
 
6.7%
8 3619
 
5.3%
9 3315
 
4.9%
7 2146
 
3.2%
6 1149
 
1.7%
Space Separator
ValueCountFrequency (%)
3045
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71142
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13526
19.0%
2 13444
18.9%
5 10516
14.8%
1 10116
14.2%
4 5701
8.0%
3 4565
 
6.4%
8 3619
 
5.1%
9 3315
 
4.7%
3045
 
4.3%
7 2146
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71142
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13526
19.0%
2 13444
18.9%
5 10516
14.8%
1 10116
14.2%
4 5701
8.0%
3 4565
 
6.4%
8 3619
 
5.1%
9 3315
 
4.7%
3045
 
4.3%
7 2146
 
3.0%

점검목적
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
3881 
위생점검(전체)
3187 
수거
1485 
위생점검(부분)
 
42
시설점검
 
7

Length

Max length8
Median length4
Mean length5.1562427
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3881
45.1%
위생점검(전체) 3187
37.0%
수거 1485
 
17.3%
위생점검(부분) 42
 
0.5%
시설점검 7
 
0.1%

Length

2024-05-18T07:33:15.712643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:16.210079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3881
45.1%
위생점검(전체 3187
37.0%
수거 1485
 
17.3%
위생점검(부분 42
 
0.5%
시설점검 7
 
0.1%

점검일자
Real number (ℝ)

Distinct538
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20150444
Minimum20080902
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:33:16.829837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080902
5-th percentile20091127
Q120120119
median20151106
Q320180625
95-th percentile20210813
Maximum20240314
Range159412
Interquartile range (IQR)60506

Descriptive statistics

Standard deviation38587.977
Coefficient of variation (CV)0.0019149939
Kurtosis-0.96828815
Mean20150444
Median Absolute Deviation (MAD)30592
Skewness0.13295969
Sum1.7333412 × 1011
Variance1.489032 × 109
MonotonicityNot monotonic
2024-05-18T07:33:17.502978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120514 343
 
4.0%
20120119 268
 
3.1%
20130610 265
 
3.1%
20130313 219
 
2.5%
20130612 157
 
1.8%
20131127 124
 
1.4%
20111202 123
 
1.4%
20091123 105
 
1.2%
20091125 93
 
1.1%
20180514 91
 
1.1%
Other values (528) 6814
79.2%
ValueCountFrequency (%)
20080902 1
 
< 0.1%
20080926 2
 
< 0.1%
20081007 3
 
< 0.1%
20081008 5
 
0.1%
20081009 3
 
< 0.1%
20090302 15
0.2%
20090331 1
 
< 0.1%
20090402 5
 
0.1%
20090423 6
 
0.1%
20090520 1
 
< 0.1%
ValueCountFrequency (%)
20240314 4
 
< 0.1%
20240306 1
 
< 0.1%
20240227 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 1
 
< 0.1%
20240115 2
 
< 0.1%
20231229 34
0.4%
20231212 7
 
0.1%
20231115 1
 
< 0.1%
20231102 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
<NA>
3873 
수시
3513 
기타
999 
합동
 
148
일제
 
69

Length

Max length4
Median length2
Mean length2.9004883
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3873
45.0%
수시 3513
40.8%
기타 999
 
11.6%
합동 148
 
1.7%
일제 69
 
0.8%

Length

2024-05-18T07:33:18.384991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:18.890071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3873
45.0%
수시 3513
40.8%
기타 999
 
11.6%
합동 148
 
1.7%
일제 69
 
0.8%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8602
Missing (%)100.0%
Memory size75.7 KiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.3 KiB
1
4415 
<NA>
3873 
2
 
314

Length

Max length4
Median length1
Mean length2.3507324
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4415
51.3%
<NA> 3873
45.0%
2 314
 
3.7%

Length

2024-05-18T07:33:19.291705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:33:19.647751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4415
51.3%
na 3873
45.0%
2 314
 
3.7%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)80.0%
Missing8582
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean18115509
Minimum1
Maximum20150128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.7 KiB
2024-05-18T07:33:20.029123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q120120528
median20120616
Q320133270
95-th percentile20150121
Maximum20150128
Range20150127
Interquartile range (IQR)12742.75

Descriptive statistics

Standard deviation6195384.1
Coefficient of variation (CV)0.34199338
Kurtosis7.0369634
Mean18115509
Median Absolute Deviation (MAD)5008
Skewness-2.8879194
Sum3.6231018 × 108
Variance3.8382784 × 1013
MonotonicityNot monotonic
2024-05-18T07:33:20.465480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20120529 5
 
0.1%
20120916 1
 
< 0.1%
20130328 1
 
< 0.1%
20120110 1
 
< 0.1%
20120523 1
 
< 0.1%
1 1
 
< 0.1%
20111107 1
 
< 0.1%
20120923 1
 
< 0.1%
20150119 1
 
< 0.1%
20150121 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 8582
99.8%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 1
 
< 0.1%
20111107 1
 
< 0.1%
20120110 1
 
< 0.1%
20120523 1
 
< 0.1%
20120529 5
0.1%
20120704 1
 
< 0.1%
20120916 1
 
< 0.1%
20120923 1
 
< 0.1%
20130328 1
 
< 0.1%
ValueCountFrequency (%)
20150128 1
< 0.1%
20150121 1
< 0.1%
20150119 1
< 0.1%
20140919 1
< 0.1%
20140912 1
< 0.1%
20130723 1
< 0.1%
20130328 1
< 0.1%
20120923 1
< 0.1%
20120916 1
< 0.1%
20120704 1
< 0.1%
Distinct905
Distinct (%)63.0%
Missing7166
Missing (%)83.3%
Memory size67.3 KiB
2024-05-18T07:33:21.286488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length18.974234
Min length3

Characters and Unicode

Total characters27247
Distinct characters336
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

Unique673 ?
Unique (%)46.9%

Sample

1st row경기도 안양시 동안구 흥안대로 405
2nd row전라북도 군산시 외향1길 208
3rd row경기동 용인시 처인구 모현면 곡현리 641
4th row울산광역시 남구 매암로 115번길
5th row부산 사하구 장림번영로 88-3
ValueCountFrequency (%)
경기도 288
 
4.3%
서울시 162
 
2.4%
충남 132
 
2.0%
충북 124
 
1.8%
서초구 91
 
1.3%
서울 88
 
1.3%
경기 81
 
1.2%
강원도 74
 
1.1%
전북 58
 
0.9%
경북 57
 
0.8%
Other values (1777) 5588
82.9%
2024-05-18T07:33:22.485145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5334
 
19.6%
1 1171
 
4.3%
904
 
3.3%
2 829
 
3.0%
- 699
 
2.6%
3 615
 
2.3%
609
 
2.2%
607
 
2.2%
507
 
1.9%
5 501
 
1.8%
Other values (326) 15471
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15841
58.1%
Space Separator 5334
 
19.6%
Decimal Number 5325
 
19.5%
Dash Punctuation 699
 
2.6%
Other Punctuation 12
 
< 0.1%
Close Punctuation 11
 
< 0.1%
Open Punctuation 11
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Uppercase Letter 5
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
904
 
5.7%
609
 
3.8%
607
 
3.8%
507
 
3.2%
500
 
3.2%
497
 
3.1%
489
 
3.1%
487
 
3.1%
456
 
2.9%
415
 
2.6%
Other values (303) 10370
65.5%
Decimal Number
ValueCountFrequency (%)
1 1171
22.0%
2 829
15.6%
3 615
11.5%
5 501
9.4%
4 452
 
8.5%
0 432
 
8.1%
7 408
 
7.7%
6 377
 
7.1%
8 310
 
5.8%
9 230
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
c 3
37.5%
j 3
37.5%
k 1
 
12.5%
s 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
40.0%
A 2
40.0%
I 1
20.0%
Space Separator
ValueCountFrequency (%)
5334
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 699
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15841
58.1%
Common 11393
41.8%
Latin 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
904
 
5.7%
609
 
3.8%
607
 
3.8%
507
 
3.2%
500
 
3.2%
497
 
3.1%
489
 
3.1%
487
 
3.1%
456
 
2.9%
415
 
2.6%
Other values (303) 10370
65.5%
Common
ValueCountFrequency (%)
5334
46.8%
1 1171
 
10.3%
2 829
 
7.3%
- 699
 
6.1%
3 615
 
5.4%
5 501
 
4.4%
4 452
 
4.0%
0 432
 
3.8%
7 408
 
3.6%
6 377
 
3.3%
Other values (6) 575
 
5.0%
Latin
ValueCountFrequency (%)
c 3
23.1%
j 3
23.1%
T 2
15.4%
A 2
15.4%
k 1
 
7.7%
s 1
 
7.7%
I 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15840
58.1%
ASCII 11406
41.9%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5334
46.8%
1 1171
 
10.3%
2 829
 
7.3%
- 699
 
6.1%
3 615
 
5.4%
5 501
 
4.4%
4 452
 
4.0%
0 432
 
3.8%
7 408
 
3.6%
6 377
 
3.3%
Other values (13) 588
 
5.2%
Hangul
ValueCountFrequency (%)
904
 
5.7%
609
 
3.8%
607
 
3.8%
507
 
3.2%
500
 
3.2%
497
 
3.1%
489
 
3.1%
487
 
3.1%
456
 
2.9%
415
 
2.6%
Other values (302) 10369
65.5%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

부적합항목
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing8599
Missing (%)> 99.9%
Memory size67.3 KiB
2024-05-18T07:33:22.888297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.6666667
Min length2

Characters and Unicode

Total characters11
Distinct characters10
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

Unique3 ?
Unique (%)100.0%

Sample

1st row대장균 검사
2nd row산가
3rd row세균수
ValueCountFrequency (%)
대장균 1
25.0%
검사 1
25.0%
산가 1
25.0%
세균수 1
25.0%
2024-05-18T07:33:23.617037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
90.9%
Space Separator 1
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
90.9%
ASCII 1
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
ASCII
ValueCountFrequency (%)
1
100.0%
Distinct3
Distinct (%)100.0%
Missing8599
Missing (%)> 99.9%
Memory size67.3 KiB
2024-05-18T07:33:23.956896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length16.666667
Min length3

Characters and Unicode

Total characters50
Distinct characters28
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row대장균 : 양성 (기준 - 대장균 : 음성)
2nd row산가 부적합(기준2.0 검사결과16.2)
3rd row190
ValueCountFrequency (%)
3
25.0%
대장균 2
16.7%
양성 1
 
8.3%
기준 1
 
8.3%
음성 1
 
8.3%
산가 1
 
8.3%
부적합(기준2.0 1
 
8.3%
검사결과16.2 1
 
8.3%
190 1
 
8.3%
2024-05-18T07:33:24.663230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
20.0%
2
 
4.0%
2
 
4.0%
0 2
 
4.0%
2
 
4.0%
) 2
 
4.0%
1 2
 
4.0%
. 2
 
4.0%
2
 
4.0%
( 2
 
4.0%
Other values (18) 22
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23
46.0%
Space Separator 10
20.0%
Decimal Number 8
 
16.0%
Other Punctuation 4
 
8.0%
Close Punctuation 2
 
4.0%
Open Punctuation 2
 
4.0%
Dash Punctuation 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (7) 7
30.4%
Decimal Number
ValueCountFrequency (%)
0 2
25.0%
1 2
25.0%
2 2
25.0%
6 1
12.5%
9 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
: 2
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27
54.0%
Hangul 23
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (7) 7
30.4%
Common
ValueCountFrequency (%)
10
37.0%
0 2
 
7.4%
) 2
 
7.4%
1 2
 
7.4%
. 2
 
7.4%
( 2
 
7.4%
: 2
 
7.4%
2 2
 
7.4%
6 1
 
3.7%
- 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
54.0%
Hangul 23
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
37.0%
0 2
 
7.4%
) 2
 
7.4%
1 2
 
7.4%
. 2
 
7.4%
( 2
 
7.4%
: 2
 
7.4%
2 2
 
7.4%
6 1
 
3.7%
- 1
 
3.7%
Hangul
ValueCountFrequency (%)
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (7) 7
30.4%

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
03210000104휴게음식점<NA><NA><NA><NA>122-3-14-4검사용프랭크버거방배점G0100000100000조리식품 등조리식품 등햄버거<NA><NA><NA>202403141.0750g<NA>20240314<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120240314<NA><NA><NA><NA><NA><NA><NA><NA>20220122953<NA><NA><NA><NA><NA>서울특별시 서초구 명달로 51, 1층 103호 (방배동)서울특별시 서초구 방배동 1002번지 15호 부흥빌딩-103<NA>위생점검(전체)20240314기타<NA>1<NA><NA><NA><NA>
13210000105집단급식소<NA><NA><NA><NA>122-3-14-2검사용서울고등학교G0100000100000조리식품 등조리식품 등철판삼겹살<NA><NA>서울고등학교 집단급식소/ 서초구 효령로 197202403141.0600g<NA>20240314<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>19990100222<NA><NA><NA><NA><NA>서울특별시 서초구 효령로 197, (서초동)서울특별시 서초구 서초동 1526번지 1호02 5258902위생점검(전체)20240314합동<NA>1<NA><NA><NA><NA>
23210000105집단급식소<NA><NA><NA><NA>122-3-14-1검사용서울고등학교G0100000100000조리식품 등조리식품 등잡채<NA><NA>서울고등학교 집단급식소/ 서초구 효령로 197202403141.0600g<NA>20240314<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>19990100222<NA><NA><NA><NA><NA>서울특별시 서초구 효령로 197, (서초동)서울특별시 서초구 서초동 1526번지 1호02 5258902위생점검(전체)20240314합동<NA>1<NA><NA><NA><NA>
33210000101일반음식점<NA><NA><NA><NA>122-3-14-3검사용피자다오 사당방배점G0100000100000조리식품 등조리식품 등피자<NA><NA><NA>202403141.0800g<NA>20240314<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200100323<NA><NA><NA><NA><NA>서울특별시 서초구 도구로 119-2, 1층 103호 (방배동)서울특별시 서초구 방배동 864번지 37호 1층-103<NA>위생점검(전체)20240314기타<NA>1<NA><NA><NA><NA>
43210000106식품제조가공업<NA><NA><NA><NA>122-3-6-1검사용플레이팅키친(교대점)C0322020300000즉석조리식품즉석조리식품소세지 미트 파스타<NA><NA><NA>202403066.0350.2g<NA><NA><NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>20220122007<NA><NA><NA><NA><NA>서울특별시 서초구 서초대로 277, 기영빌딩 2층 (서초동)서울특별시 서초구 서초동 1716번지 6호 기영빌딩, 2층070 42541920<NA>20240306합동<NA>1<NA><NA><NA><NA>
53210000101일반음식점<NA><NA><NA><NA>122-2-27-1검사용카페핸드메이드 양재점G0100000100000조리식품 등조리식품 등식용얼음<NA><NA><NA>202402271.0820g<NA>20240227<NA><NA><NA>냉동<NA><NA>1<NA>국내<NA>220240227<NA><NA><NA><NA><NA><NA><NA><NA>20220122235<NA><NA><NA><NA><NA>서울특별시 서초구 남부순환로350길 40, 1층 (양재동)서울특별시 서초구 양재동 13번지 14호 1층<NA><NA>20240227<NA><NA><NA><NA><NA><NA><NA>
63210000104휴게음식점<NA><NA><NA><NA>122-2-27-2검사용바나프레소 양재이안점G0100000100000조리식품 등조리식품 등식용얼음<NA><NA><NA>202402271.0808g<NA>20240227<NA><NA><NA>냉동<NA><NA>1<NA>국내<NA>220240227<NA><NA><NA><NA><NA><NA><NA><NA>20230129226<NA><NA><NA><NA><NA>서울특별시 서초구 강남대로34길 7, 이안빌딩 1층 (양재동)서울특별시 서초구 양재동 13번지 13호<NA><NA>20240227<NA><NA><NA><NA><NA><NA><NA>
73210000101일반음식점<NA><NA><NA><NA>122-2-26-02검사용성화마라탕 강남점F0100000400000폴리스티렌폴리스티렌소몸통 100ea<NA><NA>(주)상진/경기도 김포시 월곶면 대곶로 484번길 43-3920240226<NA><NA><NA>30ea20240226<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>220240227<NA><NA><NA><NA><NA><NA><NA><NA>20160099919<NA><NA><NA><NA><NA>서울특별시 서초구 서초중앙로22길 25, 1층 108-1호 (서초동, 서초리시온)서울특별시 서초구 서초동 1671번지 5호 서초리시온 1층 108-1호02 587 7151수거20240226기타<NA>1<NA><NA><NA><NA>
83210000114기타식품판매업<NA><NA><NA><NA>서초-설-0119-2검사용(주)농협유통 양재하나로클럽C0301050000000떡류떡류호랑이가 살던 마을 쑥 가래떡<NA><NA><NA>202401181.0700g<NA><NA><NA><NA>7실온<NA><NA>1<NA>국내<NA>120240119<NA><NA><NA><NA><NA><NA><NA><NA>19990100307<NA><NA><NA><NA><NA>서울특별시 서초구 청계산로 10, (양재동)서울특별시 서초구 양재동 230번지0234981140<NA>20240118합동<NA>1<NA><NA><NA><NA>
93210000101일반음식점<NA><NA><NA><NA>122-1-15-2검사용나리내전집G0100000100000조리식품 등조리식품 등해물파전<NA><NA>나리내전집202401151.0600g<NA>20240115<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120240115<NA><NA><NA><NA><NA><NA><NA><NA>20020098482<NA><NA><NA><NA><NA>서울특별시 서초구 남부순환로333길 15-4, 1층 (서초동)서울특별시 서초구 서초동 1428번지 13호 1층<NA>위생점검(전체)20240115합동<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
85923210000105집단급식소<NA><NA><NA><NA><NA><NA>롯데칠성음료(주)<NA><NA>오징어떡볶음<NA><NA><NA>20081008250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050098406<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1322번지 1호 2층0234749839위생점검(전체)20081008일제<NA>1<NA><NA><NA><NA>
85933210000105집단급식소<NA><NA><NA><NA><NA><NA>휠라코리아(주)급식소<NA><NA>쭈꾸미오징어볶음<NA><NA><NA>20081008250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990098120<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1467번지 10호0234709521위생점검(전체)20081008일제<NA>1<NA><NA><NA><NA>
85943210000105집단급식소<NA><NA><NA><NA><NA><NA>텔코웨어 주식회사<NA><NA>오징어초무침<NA><NA><NA>20081008250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20060098488<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1708번지 2호 5층0221059859위생점검(전체)20081008일제<NA>1<NA><NA><NA><NA>
85953210000105집단급식소<NA><NA><NA><NA><NA><NA>국제방송교류재단급식<NA><NA>닭갈비<NA><NA><NA>20081008250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19960099205<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1467번지 80호0234755047위생점검(전체)20081008일제<NA>1<NA><NA><NA><NA>
85963210000105집단급식소<NA><NA><NA><NA><NA><NA>한전케이디엔(주)<NA><NA>돈가스<NA><NA><NA>20081007250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050098372<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1355번지 0호 1층<NA><NA>20081007일제<NA>1<NA><NA><NA><NA>
85973210000105집단급식소<NA><NA><NA><NA><NA><NA>천사유치원<NA><NA>오징어볶음<NA><NA><NA>20081007250.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990098287<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1356번지 3호02 5250539<NA>20081007일제<NA>1<NA><NA><NA><NA>
85983210000105집단급식소<NA><NA><NA><NA><NA><NA>서초장미어린이집<NA><NA>제육볶음<NA><NA><NA>20081007100.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20040098868<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1353번지 3호 (지하1층)0234619280<NA>20081007일제<NA>1<NA><NA><NA><NA>
85993210000114기타식품판매업<NA><NA><NA><NA><NA><NA>(주)신세계이마트 양재점201000000과자류초콜릿가공품피넛엠앤드엠즈<NA><NA><NA>200809291.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050098297<NA><NA><NA><NA><NA>서울특별시 서초구 매헌로 16, (양재동,지하1층)서울특별시 서초구 양재동 215번지 지하1층0221551052수거20080926수시<NA>1<NA><NA><NA><NA>
86003210000114기타식품판매업<NA><NA><NA><NA><NA><NA>(주)신세계이마트 양재점201000000과자류초콜릿가공품피넛엠앤드엠즈<NA><NA><NA>200809261.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050098297<NA><NA><NA><NA><NA>서울특별시 서초구 매헌로 16, (양재동,지하1층)서울특별시 서초구 양재동 215번지 지하1층0221551052수거20080926수시<NA>1<NA><NA><NA><NA>
86013210000101일반음식점<NA><NA><NA><NA><NA><NA>함평천지<NA><NA>안창살<NA><NA><NA>20080902600.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19990099019<NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1534번지 2호 1층0234860481위생점검(부분)20080902수시<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)보관상태코드검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과수거품처리교부번호폐기량(Kg)폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용# duplicates
33210000105집단급식소<NA><NA><NA><NA><NA>서울서이초등학교<NA><NA>배추김치<NA><NA><NA>20101125150.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19980099486<NA><NA><NA>서울특별시 서초구 서초동 1334번지 2호0234747025위생점검(전체)20101125기타1<NA><NA><NA><NA>4
43210000105집단급식소<NA><NA><NA><NA><NA>서울서이초등학교<NA><NA>식수<NA><NA><NA>201011251.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19980099486<NA><NA><NA>서울특별시 서초구 서초동 1334번지 2호0234747025위생점검(전체)20101125기타1<NA><NA><NA><NA>4
53210000105집단급식소<NA><NA><NA><NA><NA>서울서이초등학교<NA><NA>우유<NA><NA><NA>20101125150.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19980099486<NA><NA><NA>서울특별시 서초구 서초동 1334번지 2호0234747025위생점검(전체)20101125기타1<NA><NA><NA><NA>4
03210000104휴게음식점<NA><NA><NA><NA><NA>르꼬르돈블루<NA><NA>허니스모크치킨<NA><NA><NA>20101015200.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA>20040100505<NA><NA><NA>서울특별시 서초구 반포동 19번지 3호 신세계백화점 지하1층 식품매장031 9079240위생점검(전체)20101015기타1<NA><NA><NA><NA>2
13210000105집단급식소<NA><NA><NA>서초-8-20검사용경원중학교600000000식품접객업접객업소조리식품등닭볶음탕<NA><NA><NA>201108291.0150g<NA><NA><NA><NA><NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA>19990098958<NA><NA><NA>서울특별시 서초구 잠원동 66번지 1호02 5328787위생점검(전체)20110829기타1<NA><NA><NA><NA>2
23210000105집단급식소<NA><NA><NA><NA><NA>서울서이초등학교<NA><NA><NA><NA><NA>20101125150.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19980099486<NA><NA><NA>서울특별시 서초구 서초동 1334번지 2호0234747025위생점검(전체)20101125기타1<NA><NA><NA><NA>2
63210000105집단급식소<NA><NA><NA><NA><NA>서울서이초등학교<NA><NA>현미밥<NA><NA><NA>20101125150.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19980099486<NA><NA><NA>서울특별시 서초구 서초동 1334번지 2호0234747025위생점검(전체)20101125기타1<NA><NA><NA><NA>2
73210000114기타식품판매업<NA><NA><NA><NA><NA>(주)농협유통양재하나로클럽201000000과자류강정(또는유과)찹쌀산자<NA><NA><NA>201009096.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19990100307<NA><NA>서울특별시 서초구 청계산로 10, (양재동)서울특별시 서초구 양재동 230번지 0호0234981140수거20100910수시1<NA><NA><NA><NA>2
83210000114기타식품판매업<NA><NA><NA><NA><NA>(주)농협유통양재하나로클럽209000000면류냉면(숙면류)함흥 비빔냉면<NA><NA><NA>201006143.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>19990100307<NA><NA>서울특별시 서초구 청계산로 10, (양재동)서울특별시 서초구 양재동 230번지 0호0234981140위생점검(전체)20100615기타1<NA><NA><NA><NA>2
93210000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계이마트 양재점209000000면류냉면(숙면류)생가득 평양 물냉면<NA><NA><NA>200906043.0<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA><NA>20050098297<NA><NA>서울특별시 서초구 매헌로 16, (양재동,지하1층)서울특별시 서초구 양재동 215번지 지하1층0221551052<NA>20091120<NA><NA><NA><NA><NA><NA>2