Overview

Dataset statistics

Number of variables61
Number of observations5664
Missing cells164990
Missing cells (%)47.8%
Duplicate rows14
Duplicate rows (%)0.2%
Total size in memory2.8 MiB
Average record size in memory518.0 B

Variable types

Categorical16
Numeric12
Unsupported13
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-9992/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 14 (0.2%) duplicate rowsDuplicates
업종명 is highly imbalanced (61.4%)Imbalance
지도점검계획 is highly imbalanced (62.3%)Imbalance
수거계획 is highly imbalanced (67.4%)Imbalance
수거사유코드 is highly imbalanced (50.9%)Imbalance
어린이기호식품유형 is highly imbalanced (97.1%)Imbalance
검사기관명 is highly imbalanced (58.0%)Imbalance
국가명 is highly imbalanced (88.7%)Imbalance
계획구분코드 has 4274 (75.5%) missing valuesMissing
계획구분명 has 5664 (100.0%) missing valuesMissing
수거증번호 has 1257 (22.2%) missing valuesMissing
식품군코드 has 95 (1.7%) missing valuesMissing
식품군 has 1173 (20.7%) missing valuesMissing
품목명 has 245 (4.3%) missing valuesMissing
음식물명 has 5536 (97.7%) missing valuesMissing
원료명 has 5633 (99.5%) missing valuesMissing
생산업소 has 4587 (81.0%) missing valuesMissing
수거량(정량) has 314 (5.5%) missing valuesMissing
제품규격(정량) has 1571 (27.7%) missing valuesMissing
수거량(자유) has 5350 (94.5%) missing valuesMissing
제조일자(일자) has 4526 (79.9%) missing valuesMissing
제조일자(롯트) has 5639 (99.6%) missing valuesMissing
유통기한(일자) has 4704 (83.1%) missing valuesMissing
유통기한(제조일기준) has 5637 (99.5%) missing valuesMissing
바코드번호 has 5664 (100.0%) missing valuesMissing
(구)제조사명 has 4546 (80.3%) missing valuesMissing
검사의뢰일자 has 2723 (48.1%) missing valuesMissing
결과회보일자 has 3818 (67.4%) missing valuesMissing
처리구분 has 5664 (100.0%) missing valuesMissing
수거검사구분코드 has 5664 (100.0%) missing valuesMissing
단속지역구분코드 has 5664 (100.0%) missing valuesMissing
수거장소구분코드 has 5664 (100.0%) missing valuesMissing
처리결과 has 5661 (99.9%) missing valuesMissing
수거품처리 has 5664 (100.0%) missing valuesMissing
폐기일자 has 5664 (100.0%) missing valuesMissing
폐기량(kg) has 5664 (100.0%) missing valuesMissing
폐기금액(원) has 5664 (100.0%) missing valuesMissing
폐기장소 has 5664 (100.0%) missing valuesMissing
폐기방법 has 5664 (100.0%) missing valuesMissing
소재지(도로명) has 2614 (46.2%) missing valuesMissing
소재지(지번) has 501 (8.8%) missing valuesMissing
업소전화번호 has 251 (4.4%) missing valuesMissing
점검내용 has 5664 (100.0%) missing valuesMissing
(구)제조유통기한 has 4704 (83.1%) missing valuesMissing
(구)제조회사주소 has 4670 (82.5%) missing valuesMissing
부적합항목 has 5660 (99.9%) missing valuesMissing
기준치부적합내용 has 5661 (99.9%) missing valuesMissing
수거량(정량) is highly skewed (γ1 = 73.14369411)Skewed
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 07:58:44.574468
Analysis finished2024-05-11 07:58:47.769151
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
3150000
5664 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 5664
100.0%

Length

2024-05-11T16:58:47.866399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:58:47.974723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 5664
100.0%

업종코드
Real number (ℝ)

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.71028
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:48.082012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation4.9355293
Coefficient of variation (CV)0.044181516
Kurtosis2.7000786
Mean111.71028
Median Absolute Deviation (MAD)0
Skewness-0.46847644
Sum632727
Variance24.359449
MonotonicityIncreasing
2024-05-11T16:58:48.223171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
114 4146
73.2%
105 550
 
9.7%
101 503
 
8.9%
112 150
 
2.6%
104 131
 
2.3%
107 56
 
1.0%
106 49
 
0.9%
134 43
 
0.8%
109 14
 
0.2%
121 12
 
0.2%
Other values (4) 10
 
0.2%
ValueCountFrequency (%)
101 503
 
8.9%
104 131
 
2.3%
105 550
 
9.7%
106 49
 
0.9%
107 56
 
1.0%
108 1
 
< 0.1%
109 14
 
0.2%
110 1
 
< 0.1%
112 150
 
2.6%
114 4146
73.2%
ValueCountFrequency (%)
134 43
 
0.8%
122 1
 
< 0.1%
121 12
 
0.2%
120 7
 
0.1%
114 4146
73.2%
112 150
 
2.6%
110 1
 
< 0.1%
109 14
 
0.2%
108 1
 
< 0.1%
107 56
 
1.0%

업종명
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
기타식품판매업
4146 
집단급식소
550 
일반음식점
503 
식품자동판매기영업
 
150
휴게음식점
 
131
Other values (9)
 
184

Length

Max length11
Median length7
Mean length6.6756709
Min length5

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 4146
73.2%
집단급식소 550
 
9.7%
일반음식점 503
 
8.9%
식품자동판매기영업 150
 
2.6%
휴게음식점 131
 
2.3%
즉석판매제조가공업 56
 
1.0%
식품제조가공업 49
 
0.9%
건강기능식품일반판매업 43
 
0.8%
식품소분업 14
 
0.2%
제과점영업 12
 
0.2%
Other values (4) 10
 
0.2%

Length

2024-05-11T16:58:48.363116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 4146
73.2%
집단급식소 550
 
9.7%
일반음식점 503
 
8.9%
식품자동판매기영업 150
 
2.6%
휴게음식점 131
 
2.3%
즉석판매제조가공업 56
 
1.0%
식품제조가공업 49
 
0.9%
건강기능식품일반판매업 43
 
0.8%
식품소분업 14
 
0.2%
제과점영업 12
 
0.2%
Other values (5) 11
 
0.2%

계획구분코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.4%
Missing4274
Missing (%)75.5%
Infinite0
Infinite (%)0.0%
Mean600.51799
Minimum1
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:48.465688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median999
Q3999
95-th percentile999
Maximum999
Range998
Interquartile range (IQR)997

Descriptive statistics

Standard deviation488.21585
Coefficient of variation (CV)0.81299123
Kurtosis-1.835578
Mean600.51799
Median Absolute Deviation (MAD)0
Skewness-0.40870702
Sum834720
Variance238354.72
MonotonicityNot monotonic
2024-05-11T16:58:48.564764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
999 834
 
14.7%
2 414
 
7.3%
3 68
 
1.2%
7 48
 
0.8%
9 20
 
0.4%
1 6
 
0.1%
(Missing) 4274
75.5%
ValueCountFrequency (%)
1 6
 
0.1%
2 414
7.3%
3 68
 
1.2%
7 48
 
0.8%
9 20
 
0.4%
999 834
14.7%
ValueCountFrequency (%)
999 834
14.7%
9 20
 
0.4%
7 48
 
0.8%
3 68
 
1.2%
2 414
7.3%
1 6
 
0.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
4274 
기타식품판매업소 점검
 
396
집단급식소 지도점검
 
244
식품접객업소 위생점검 및 지도
 
176
학교급식소 지도점검
 
170
Other values (12)
 
404

Length

Max length21
Median length4
Mean length6.0044138
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row식품접객업소 위생점검 및 지도
2nd row식품접객업소 위생점검 및 지도
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4274
75.5%
기타식품판매업소 점검 396
 
7.0%
집단급식소 지도점검 244
 
4.3%
식품접객업소 위생점검 및 지도 176
 
3.1%
학교급식소 지도점검 170
 
3.0%
식품안전업소 지도점검 137
 
2.4%
기타 일상단속(수거)검사 114
 
2.0%
여름철 활어회 취급업소 지도점검 계획 39
 
0.7%
여름철 다소비식품 취급업소 지도점검계획 29
 
0.5%
식품소분판매업소 합동점검계획 26
 
0.5%
Other values (7) 59
 
1.0%

Length

2024-05-11T16:58:48.677523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4274
56.2%
지도점검 633
 
8.3%
점검 406
 
5.3%
기타식품판매업소 396
 
5.2%
집단급식소 244
 
3.2%
식품접객업소 176
 
2.3%
위생점검 176
 
2.3%
및 176
 
2.3%
지도 176
 
2.3%
학교급식소 170
 
2.2%
Other values (21) 780
 
10.3%

수거계획
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
4687 
유통식품수거검사
 
416
유통식품 수거검사
 
205
2019년 식품 제조유통 안전관리 계획
 
103
어린이식생활안전 시행계획
 
77
Other values (5)
 
176

Length

Max length21
Median length4
Mean length5.2635946
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> 4687
82.8%
유통식품수거검사 416
 
7.3%
유통식품 수거검사 205
 
3.6%
2019년 식품 제조유통 안전관리 계획 103
 
1.8%
어린이식생활안전 시행계획 77
 
1.4%
기타식품판매업소 점검 63
 
1.1%
2015 시민다소비식품 수거검사 계획 62
 
1.1%
설 성수식품 전국합동점검 계획 30
 
0.5%
2014년 유통식품 수거계획 12
 
0.2%
20'식품제조유통안전관리계획 9
 
0.2%

Length

2024-05-11T16:58:48.800416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:58:48.918400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4687
69.7%
유통식품수거검사 416
 
6.2%
수거검사 267
 
4.0%
유통식품 217
 
3.2%
계획 195
 
2.9%
2019년 103
 
1.5%
식품 103
 
1.5%
제조유통 103
 
1.5%
안전관리 103
 
1.5%
시행계획 77
 
1.1%
Other values (11) 450
 
6.7%

수거증번호
Text

MISSING 

Distinct2619
Distinct (%)59.4%
Missing1257
Missing (%)22.2%
Memory size44.4 KiB
2024-05-11T16:58:49.286809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.5956433
Min length1

Characters and Unicode

Total characters37881
Distinct characters72
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

Unique1609 ?
Unique (%)36.5%

Sample

1st row116-4-1
2nd row116-10-7
3rd row116-8-49
4th row116-7-식품14
5th row116-12-3
ValueCountFrequency (%)
116-11-13 7
 
0.2%
116-10-1 7
 
0.2%
116-11-14 7
 
0.2%
116-11-17 7
 
0.2%
116-11-16 7
 
0.2%
116-11-15 7
 
0.2%
116-6-18 6
 
0.1%
116-6-11 6
 
0.1%
116-6-7 6
 
0.1%
116-6-9 6
 
0.1%
Other values (2609) 4355
98.5%
2024-05-11T16:58:49.804009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11825
31.2%
- 8729
23.0%
6 5567
14.7%
2 1614
 
4.3%
7 1387
 
3.7%
3 1292
 
3.4%
0 1250
 
3.3%
9 1163
 
3.1%
4 1117
 
2.9%
5 1082
 
2.9%
Other values (62) 2855
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27028
71.3%
Dash Punctuation 8729
 
23.0%
Other Letter 1933
 
5.1%
Uppercase Letter 77
 
0.2%
Close Punctuation 40
 
0.1%
Open Punctuation 40
 
0.1%
Lowercase Letter 18
 
< 0.1%
Space Separator 14
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 677
35.0%
품 584
30.2%
강 103
 
5.3%
중 90
 
4.7%
독 90
 
4.7%
서 67
 
3.5%
건 52
 
2.7%
구 25
 
1.3%
수 17
 
0.9%
물 17
 
0.9%
Other values (40) 211
 
10.9%
Decimal Number
ValueCountFrequency (%)
1 11825
43.8%
6 5567
20.6%
2 1614
 
6.0%
7 1387
 
5.1%
3 1292
 
4.8%
0 1250
 
4.6%
9 1163
 
4.3%
4 1117
 
4.1%
5 1082
 
4.0%
8 731
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
G 27
35.1%
O 25
32.5%
M 25
32.5%
Lowercase Letter
ValueCountFrequency (%)
g 6
33.3%
m 6
33.3%
o 6
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 8729
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35853
94.6%
Hangul 1933
 
5.1%
Latin 95
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 677
35.0%
품 584
30.2%
강 103
 
5.3%
중 90
 
4.7%
독 90
 
4.7%
서 67
 
3.5%
건 52
 
2.7%
구 25
 
1.3%
수 17
 
0.9%
물 17
 
0.9%
Other values (40) 211
 
10.9%
Common
ValueCountFrequency (%)
1 11825
33.0%
- 8729
24.3%
6 5567
15.5%
2 1614
 
4.5%
7 1387
 
3.9%
3 1292
 
3.6%
0 1250
 
3.5%
9 1163
 
3.2%
4 1117
 
3.1%
5 1082
 
3.0%
Other values (6) 827
 
2.3%
Latin
ValueCountFrequency (%)
G 27
28.4%
O 25
26.3%
M 25
26.3%
g 6
 
6.3%
m 6
 
6.3%
o 6
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35948
94.9%
Hangul 1933
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11825
32.9%
- 8729
24.3%
6 5567
15.5%
2 1614
 
4.5%
7 1387
 
3.9%
3 1292
 
3.6%
0 1250
 
3.5%
9 1163
 
3.2%
4 1117
 
3.1%
5 1082
 
3.0%
Other values (12) 922
 
2.6%
Hangul
ValueCountFrequency (%)
식 677
35.0%
품 584
30.2%
강 103
 
5.3%
중 90
 
4.7%
독 90
 
4.7%
서 67
 
3.5%
건 52
 
2.7%
구 25
 
1.3%
수 17
 
0.9%
물 17
 
0.9%
Other values (40) 211
 
10.9%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
검사용
3462 
<NA>
1999 
기타
 
200
압류
 
2
증거용
 
1

Length

Max length4
Median length3
Mean length3.3172669
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 3462
61.1%
<NA> 1999
35.3%
기타 200
 
3.5%
압류 2
 
< 0.1%
증거용 1
 
< 0.1%

Length

2024-05-11T16:58:49.947361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:58:50.052575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 3462
61.1%
na 1999
35.3%
기타 200
 
3.5%
압류 2
 
< 0.1%
증거용 1
 
< 0.1%

업소명
Text

Distinct499
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-05-11T16:58:50.279626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length10.502472
Min length1

Characters and Unicode

Total characters59486
Distinct characters486
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

Unique267 ?
Unique (%)4.7%

Sample

1st row보성각
2nd row보성각
3rd row밀향기해물손칼국수
4th row밀향기해물손칼국수
5th row현대회집
ValueCountFrequency (%)
주)이마트 1229
 
13.9%
가양점 970
 
11.0%
강서농협 500
 
5.7%
롯데쇼핑(주)롯데슈퍼염창2점 449
 
5.1%
홈플러스 377
 
4.3%
하나로마트 324
 
3.7%
홈플러스테스코(주)가양점 303
 
3.4%
주식회사 303
 
3.4%
주)신세계이마트가양점 296
 
3.3%
공항점 268
 
3.0%
Other values (560) 3827
43.3%
2024-05-11T16:58:50.675098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 3409
 
5.7%
( 3336
 
5.6%
주 3282
 
5.5%
3182
 
5.3%
점 3080
 
5.2%
마 2498
 
4.2%
트 2466
 
4.1%
이 2137
 
3.6%
스 1947
 
3.3%
양 1924
 
3.2%
Other values (476) 32225
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47281
79.5%
Close Punctuation 3409
 
5.7%
Open Punctuation 3336
 
5.6%
Space Separator 3182
 
5.3%
Lowercase Letter 1369
 
2.3%
Decimal Number 547
 
0.9%
Uppercase Letter 325
 
0.5%
Other Punctuation 35
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3282
 
6.9%
점 3080
 
6.5%
마 2498
 
5.3%
트 2466
 
5.2%
이 2137
 
4.5%
스 1947
 
4.1%
양 1924
 
4.1%
가 1893
 
4.0%
데 1236
 
2.6%
롯 1234
 
2.6%
Other values (422) 25584
54.1%
Lowercase Letter
ValueCountFrequency (%)
e 327
23.9%
a 197
14.4%
r 196
14.3%
s 131
9.6%
t 101
 
7.4%
l 97
 
7.1%
c 97
 
7.1%
n 68
 
5.0%
o 38
 
2.8%
y 34
 
2.5%
Other values (8) 83
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
T 136
41.8%
C 108
33.2%
H 17
 
5.2%
B 17
 
5.2%
N 7
 
2.2%
K 5
 
1.5%
D 5
 
1.5%
E 4
 
1.2%
O 4
 
1.2%
R 4
 
1.2%
Other values (8) 18
 
5.5%
Decimal Number
ValueCountFrequency (%)
2 455
83.2%
3 26
 
4.8%
0 24
 
4.4%
9 24
 
4.4%
1 6
 
1.1%
6 5
 
0.9%
5 3
 
0.5%
4 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
& 18
51.4%
, 9
25.7%
. 4
 
11.4%
; 4
 
11.4%
Close Punctuation
ValueCountFrequency (%)
) 3409
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3336
100.0%
Space Separator
ValueCountFrequency (%)
3182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47280
79.5%
Common 10511
 
17.7%
Latin 1694
 
2.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3282
 
6.9%
점 3080
 
6.5%
마 2498
 
5.3%
트 2466
 
5.2%
이 2137
 
4.5%
스 1947
 
4.1%
양 1924
 
4.1%
가 1893
 
4.0%
데 1236
 
2.6%
롯 1234
 
2.6%
Other values (421) 25583
54.1%
Latin
ValueCountFrequency (%)
e 327
19.3%
a 197
11.6%
r 196
11.6%
T 136
8.0%
s 131
7.7%
C 108
 
6.4%
t 101
 
6.0%
l 97
 
5.7%
c 97
 
5.7%
n 68
 
4.0%
Other values (26) 236
13.9%
Common
ValueCountFrequency (%)
) 3409
32.4%
( 3336
31.7%
3182
30.3%
2 455
 
4.3%
3 26
 
0.2%
0 24
 
0.2%
9 24
 
0.2%
& 18
 
0.2%
, 9
 
0.1%
1 6
 
0.1%
Other values (8) 22
 
0.2%
Han
ValueCountFrequency (%)
林 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47280
79.5%
ASCII 12205
 
20.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 3409
27.9%
( 3336
27.3%
3182
26.1%
2 455
 
3.7%
e 327
 
2.7%
a 197
 
1.6%
r 196
 
1.6%
T 136
 
1.1%
s 131
 
1.1%
C 108
 
0.9%
Other values (44) 728
 
6.0%
Hangul
ValueCountFrequency (%)
주 3282
 
6.9%
점 3080
 
6.5%
마 2498
 
5.3%
트 2466
 
5.2%
이 2137
 
4.5%
스 1947
 
4.1%
양 1924
 
4.1%
가 1893
 
4.0%
데 1236
 
2.6%
롯 1234
 
2.6%
Other values (421) 25583
54.1%
CJK
ValueCountFrequency (%)
林 1
100.0%

식품군코드
Text

MISSING 

Distinct294
Distinct (%)5.3%
Missing95
Missing (%)1.7%
Memory size44.4 KiB
2024-05-11T16:58:50.911582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.8631711
Min length1

Characters and Unicode

Total characters54928
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)1.8%

Sample

1st rowC01000000
2nd rowG0400000000000
3rd row
4th rowG0100000100000
5th row
ValueCountFrequency (%)
c01000000 537
 
10.6%
g0100000100000 291
 
5.7%
829000000 255
 
5.0%
801000000 222
 
4.4%
818000000 216
 
4.2%
821000000 197
 
3.9%
815000000 185
 
3.6%
816000000 173
 
3.4%
220000000 138
 
2.7%
830000000 126
 
2.5%
Other values (282) 2748
54.0%
2024-05-11T16:58:51.285006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38120
69.4%
1 4815
 
8.8%
8 2652
 
4.8%
2 2145
 
3.9%
1641
 
3.0%
C 1576
 
2.9%
3 1059
 
1.9%
4 637
 
1.2%
5 597
 
1.1%
9 467
 
0.9%
Other values (11) 1219
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51185
93.2%
Uppercase Letter 2102
 
3.8%
Space Separator 1641
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38120
74.5%
1 4815
 
9.4%
8 2652
 
5.2%
2 2145
 
4.2%
3 1059
 
2.1%
4 637
 
1.2%
5 597
 
1.2%
9 467
 
0.9%
6 428
 
0.8%
7 265
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 1576
75.0%
G 388
 
18.5%
E 69
 
3.3%
H 22
 
1.0%
Z 14
 
0.7%
A 14
 
0.7%
X 9
 
0.4%
F 5
 
0.2%
B 4
 
0.2%
D 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1641
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 52826
96.2%
Latin 2102
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38120
72.2%
1 4815
 
9.1%
8 2652
 
5.0%
2 2145
 
4.1%
1641
 
3.1%
3 1059
 
2.0%
4 637
 
1.2%
5 597
 
1.1%
9 467
 
0.9%
6 428
 
0.8%
Latin
ValueCountFrequency (%)
C 1576
75.0%
G 388
 
18.5%
E 69
 
3.3%
H 22
 
1.0%
Z 14
 
0.7%
A 14
 
0.7%
X 9
 
0.4%
F 5
 
0.2%
B 4
 
0.2%
D 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54928
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38120
69.4%
1 4815
 
8.8%
8 2652
 
4.8%
2 2145
 
3.9%
1641
 
3.0%
C 1576
 
2.9%
3 1059
 
1.9%
4 637
 
1.2%
5 597
 
1.1%
9 467
 
0.9%
Other values (11) 1219
 
2.2%

식품군
Text

MISSING 

Distinct230
Distinct (%)5.1%
Missing1173
Missing (%)20.7%
Memory size44.4 KiB
2024-05-11T16:58:51.553267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.6802494
Min length1

Characters and Unicode

Total characters21019
Distinct characters282
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

Unique77 ?
Unique (%)1.7%

Sample

1st row기타
2nd row조리식품 등
3rd row기구류
4th row기구류
5th row기구류
ValueCountFrequency (%)
기타식품류 393
 
7.5%
등 337
 
6.4%
음료류 302
 
5.8%
과자류 298
 
5.7%
조리식품 291
 
5.6%
조미식품 276
 
5.3%
다류 232
 
4.4%
면류 225
 
4.3%
커피 136
 
2.6%
규격외일반가공식품 126
 
2.4%
Other values (251) 2621
50.0%
2024-05-11T16:58:51.926835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 2562
 
12.2%
품 1702
 
8.1%
식 1548
 
7.4%
746
 
3.5%
기 661
 
3.1%
조 655
 
3.1%
가 514
 
2.4%
음 504
 
2.4%
과 503
 
2.4%
료 482
 
2.3%
Other values (272) 11142
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19937
94.9%
Space Separator 746
 
3.5%
Other Punctuation 178
 
0.8%
Uppercase Letter 61
 
0.3%
Open Punctuation 44
 
0.2%
Close Punctuation 44
 
0.2%
Decimal Number 7
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 2562
 
12.9%
품 1702
 
8.5%
식 1548
 
7.8%
기 661
 
3.3%
조 655
 
3.3%
가 514
 
2.6%
음 504
 
2.5%
과 503
 
2.5%
료 482
 
2.4%
공 464
 
2.3%
Other values (251) 10342
51.9%
Uppercase Letter
ValueCountFrequency (%)
A 18
29.5%
D 10
16.4%
E 8
13.1%
C 8
13.1%
P 7
 
11.5%
H 7
 
11.5%
B 2
 
3.3%
Q 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
6 1
 
14.3%
3 1
 
14.3%
0 1
 
14.3%
2 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 110
61.8%
, 59
33.1%
/ 7
 
3.9%
? 2
 
1.1%
Space Separator
ValueCountFrequency (%)
746
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19937
94.9%
Common 1021
 
4.9%
Latin 61
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 2562
 
12.9%
품 1702
 
8.5%
식 1548
 
7.8%
기 661
 
3.3%
조 655
 
3.3%
가 514
 
2.6%
음 504
 
2.5%
과 503
 
2.5%
료 482
 
2.4%
공 464
 
2.3%
Other values (251) 10342
51.9%
Common
ValueCountFrequency (%)
746
73.1%
. 110
 
10.8%
, 59
 
5.8%
( 44
 
4.3%
) 44
 
4.3%
/ 7
 
0.7%
1 3
 
0.3%
- 2
 
0.2%
? 2
 
0.2%
6 1
 
0.1%
Other values (3) 3
 
0.3%
Latin
ValueCountFrequency (%)
A 18
29.5%
D 10
16.4%
E 8
13.1%
C 8
13.1%
P 7
 
11.5%
H 7
 
11.5%
B 2
 
3.3%
Q 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19937
94.9%
ASCII 1082
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 2562
 
12.9%
품 1702
 
8.5%
식 1548
 
7.8%
기 661
 
3.3%
조 655
 
3.3%
가 514
 
2.6%
음 504
 
2.5%
과 503
 
2.5%
료 482
 
2.4%
공 464
 
2.3%
Other values (251) 10342
51.9%
ASCII
ValueCountFrequency (%)
746
68.9%
. 110
 
10.2%
, 59
 
5.5%
( 44
 
4.1%
) 44
 
4.1%
A 18
 
1.7%
D 10
 
0.9%
E 8
 
0.7%
C 8
 
0.7%
P 7
 
0.6%
Other values (11) 28
 
2.6%

품목명
Text

MISSING 

Distinct326
Distinct (%)6.0%
Missing245
Missing (%)4.3%
Memory size44.4 KiB
2024-05-11T16:58:52.178582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length5.254475
Min length1

Characters and Unicode

Total characters28474
Distinct characters333
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

Unique97 ?
Unique (%)1.8%

Sample

1st row배추김치
2nd row사용 중인 튀김용 유지
3rd row조리식품 등
4th row기구류중기타
5th row기구류중기타
ValueCountFrequency (%)
등 753
 
10.3%
조리식품 738
 
10.1%
유탕면류 224
 
3.1%
혼합음료 155
 
2.1%
탄산음료 150
 
2.1%
과자 142
 
2.0%
즉석조리식품 133
 
1.8%
초콜릿가공품 132
 
1.8%
소스류 132
 
1.8%
수산물가공품 112
 
1.5%
Other values (347) 4609
63.3%
2024-05-11T16:58:52.608207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1861
 
6.5%
품 1602
 
5.6%
식 1302
 
4.6%
조 1191
 
4.2%
류 1174
 
4.1%
리 1024
 
3.6%
가 797
 
2.8%
등 780
 
2.7%
기 669
 
2.3%
과 612
 
2.1%
Other values (323) 17462
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25497
89.5%
Space Separator 1861
 
6.5%
Other Punctuation 486
 
1.7%
Open Punctuation 276
 
1.0%
Close Punctuation 276
 
1.0%
Uppercase Letter 67
 
0.2%
Decimal Number 8
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 1602
 
6.3%
식 1302
 
5.1%
조 1191
 
4.7%
류 1174
 
4.6%
리 1024
 
4.0%
가 797
 
3.1%
등 780
 
3.1%
기 669
 
2.6%
과 612
 
2.4%
공 570
 
2.2%
Other values (302) 15776
61.9%
Uppercase Letter
ValueCountFrequency (%)
A 20
29.9%
D 11
16.4%
E 9
13.4%
H 8
 
11.9%
P 8
 
11.9%
C 8
 
11.9%
B 2
 
3.0%
Q 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
0 1
 
12.5%
6 1
 
12.5%
3 1
 
12.5%
2 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 279
57.4%
, 183
37.7%
? 19
 
3.9%
/ 5
 
1.0%
Space Separator
ValueCountFrequency (%)
1861
100.0%
Open Punctuation
ValueCountFrequency (%)
( 276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 276
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25497
89.5%
Common 2910
 
10.2%
Latin 67
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 1602
 
6.3%
식 1302
 
5.1%
조 1191
 
4.7%
류 1174
 
4.6%
리 1024
 
4.0%
가 797
 
3.1%
등 780
 
3.1%
기 669
 
2.6%
과 612
 
2.4%
공 570
 
2.2%
Other values (302) 15776
61.9%
Common
ValueCountFrequency (%)
1861
64.0%
. 279
 
9.6%
( 276
 
9.5%
) 276
 
9.5%
, 183
 
6.3%
? 19
 
0.7%
/ 5
 
0.2%
1 4
 
0.1%
- 3
 
0.1%
0 1
 
< 0.1%
Other values (3) 3
 
0.1%
Latin
ValueCountFrequency (%)
A 20
29.9%
D 11
16.4%
E 9
13.4%
H 8
 
11.9%
P 8
 
11.9%
C 8
 
11.9%
B 2
 
3.0%
Q 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25497
89.5%
ASCII 2977
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1861
62.5%
. 279
 
9.4%
( 276
 
9.3%
) 276
 
9.3%
, 183
 
6.1%
A 20
 
0.7%
? 19
 
0.6%
D 11
 
0.4%
E 9
 
0.3%
H 8
 
0.3%
Other values (11) 35
 
1.2%
Hangul
ValueCountFrequency (%)
품 1602
 
6.3%
식 1302
 
5.1%
조 1191
 
4.7%
류 1174
 
4.6%
리 1024
 
4.0%
가 797
 
3.1%
등 780
 
3.1%
기 669
 
2.6%
과 612
 
2.4%
공 570
 
2.2%
Other values (302) 15776
61.9%

제품명
Text

Distinct4305
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-05-11T16:58:52.907681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length7.1486582
Min length1

Characters and Unicode

Total characters40490
Distinct characters923
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3721 ?
Unique (%)65.7%

Sample

1st row배추김치(비살균제품)
2nd row사용중인 튀김용 유지
3rd row콩국물
4th row콩국물
5th row
ValueCountFrequency (%)
커피 71
 
0.9%
오뚜기 70
 
0.8%
청정원 60
 
0.7%
백설 44
 
0.5%
수족관물 42
 
0.5%
밀크커피 36
 
0.4%
두부 36
 
0.4%
김밥 31
 
0.4%
이마트 31
 
0.4%
냉면육수 29
 
0.3%
Other values (4835) 7855
94.6%
2024-05-11T16:58:53.607204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2669
 
6.6%
스 876
 
2.2%
이 783
 
1.9%
리 679
 
1.7%
치 503
 
1.2%
기 499
 
1.2%
오 468
 
1.2%
라 428
 
1.1%
드 416
 
1.0%
고 396
 
1.0%
Other values (913) 32773
80.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34312
84.7%
Space Separator 2669
 
6.6%
Uppercase Letter 2060
 
5.1%
Decimal Number 534
 
1.3%
Lowercase Letter 287
 
0.7%
Open Punctuation 220
 
0.5%
Close Punctuation 218
 
0.5%
Other Punctuation 144
 
0.4%
Dash Punctuation 33
 
0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 876
 
2.6%
이 783
 
2.3%
리 679
 
2.0%
치 503
 
1.5%
기 499
 
1.5%
오 468
 
1.4%
라 428
 
1.2%
드 416
 
1.2%
고 396
 
1.2%
면 381
 
1.1%
Other values (837) 28883
84.2%
Uppercase Letter
ValueCountFrequency (%)
E 216
 
10.5%
A 200
 
9.7%
I 156
 
7.6%
O 148
 
7.2%
C 140
 
6.8%
R 135
 
6.6%
N 124
 
6.0%
L 121
 
5.9%
T 102
 
5.0%
S 97
 
4.7%
Other values (16) 621
30.1%
Lowercase Letter
ValueCountFrequency (%)
a 45
15.7%
m 41
14.3%
p 33
11.5%
e 27
9.4%
i 21
 
7.3%
r 15
 
5.2%
o 13
 
4.5%
t 12
 
4.2%
u 10
 
3.5%
g 9
 
3.1%
Other values (13) 61
21.3%
Decimal Number
ValueCountFrequency (%)
0 157
29.4%
1 132
24.7%
3 101
18.9%
2 54
 
10.1%
5 24
 
4.5%
7 20
 
3.7%
9 19
 
3.6%
4 12
 
2.2%
8 8
 
1.5%
6 7
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 30
20.8%
% 28
19.4%
, 28
19.4%
; 25
17.4%
/ 10
 
6.9%
. 9
 
6.2%
？ 6
 
4.2%
! 4
 
2.8%
? 3
 
2.1%
: 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
+ 7
58.3%
~ 5
41.7%
Space Separator
ValueCountFrequency (%)
2669
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34309
84.7%
Common 3831
 
9.5%
Latin 2347
 
5.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 876
 
2.6%
이 783
 
2.3%
리 679
 
2.0%
치 503
 
1.5%
기 499
 
1.5%
오 468
 
1.4%
라 428
 
1.2%
드 416
 
1.2%
고 396
 
1.2%
면 381
 
1.1%
Other values (834) 28880
84.2%
Latin
ValueCountFrequency (%)
E 216
 
9.2%
A 200
 
8.5%
I 156
 
6.6%
O 148
 
6.3%
C 140
 
6.0%
R 135
 
5.8%
N 124
 
5.3%
L 121
 
5.2%
T 102
 
4.3%
S 97
 
4.1%
Other values (39) 908
38.7%
Common
ValueCountFrequency (%)
2669
69.7%
( 220
 
5.7%
) 218
 
5.7%
0 157
 
4.1%
1 132
 
3.4%
3 101
 
2.6%
2 54
 
1.4%
- 33
 
0.9%
& 30
 
0.8%
% 28
 
0.7%
Other values (17) 189
 
4.9%
Han
ValueCountFrequency (%)
泉 1
33.3%
淵 1
33.3%
純 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34308
84.7%
ASCII 6172
 
15.2%
None 6
 
< 0.1%
CJK 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2669
43.2%
( 220
 
3.6%
) 218
 
3.5%
E 216
 
3.5%
A 200
 
3.2%
0 157
 
2.5%
I 156
 
2.5%
O 148
 
2.4%
C 140
 
2.3%
R 135
 
2.2%
Other values (65) 1913
31.0%
Hangul
ValueCountFrequency (%)
스 876
 
2.6%
이 783
 
2.3%
리 679
 
2.0%
치 503
 
1.5%
기 499
 
1.5%
오 468
 
1.4%
라 428
 
1.2%
드 416
 
1.2%
고 396
 
1.2%
면 381
 
1.1%
Other values (833) 28879
84.2%
None
ValueCountFrequency (%)
？ 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅎ 1
100.0%
CJK
ValueCountFrequency (%)
泉 1
33.3%
淵 1
33.3%
純 1
33.3%

음식물명
Text

MISSING 

Distinct90
Distinct (%)70.3%
Missing5536
Missing (%)97.7%
Memory size44.4 KiB
2024-05-11T16:58:53.902013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9
Mean length4.6484375
Min length1

Characters and Unicode

Total characters595
Distinct characters172
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)60.2%

Sample

1st row콩국물
2nd row수족관물
3rd row수족관물
4th row냉면육수
5th row개고기수육
ValueCountFrequency (%)
커피 16
 
11.9%
수족관물 6
 
4.5%
육회 4
 
3.0%
불고기 4
 
3.0%
원료식육 3
 
2.2%
율무차 3
 
2.2%
핫쵸코 3
 
2.2%
햄버거 3
 
2.2%
냉면육수 3
 
2.2%
현미밥 2
 
1.5%
Other values (83) 87
64.9%
2024-05-11T16:58:54.352651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 20
 
3.4%
커 19
 
3.2%
피 19
 
3.2%
치 17
 
2.9%
물 14
 
2.4%
김 14
 
2.4%
무 14
 
2.4%
1 13
 
2.2%
2 11
 
1.8%
육 11
 
1.8%
Other values (162) 443
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 531
89.2%
Decimal Number 41
 
6.9%
Open Punctuation 8
 
1.3%
Close Punctuation 8
 
1.3%
Space Separator 6
 
1.0%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 20
 
3.8%
커 19
 
3.6%
피 19
 
3.6%
치 17
 
3.2%
물 14
 
2.6%
김 14
 
2.6%
무 14
 
2.6%
육 11
 
2.1%
밥 10
 
1.9%
추 10
 
1.9%
Other values (152) 383
72.1%
Decimal Number
ValueCountFrequency (%)
1 13
31.7%
2 11
26.8%
0 8
19.5%
3 7
17.1%
9 1
 
2.4%
6 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 531
89.2%
Common 64
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 20
 
3.8%
커 19
 
3.6%
피 19
 
3.6%
치 17
 
3.2%
물 14
 
2.6%
김 14
 
2.6%
무 14
 
2.6%
육 11
 
2.1%
밥 10
 
1.9%
추 10
 
1.9%
Other values (152) 383
72.1%
Common
ValueCountFrequency (%)
1 13
20.3%
2 11
17.2%
( 8
12.5%
) 8
12.5%
0 8
12.5%
3 7
10.9%
6
9.4%
. 1
 
1.6%
9 1
 
1.6%
6 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 531
89.2%
ASCII 64
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 20
 
3.8%
커 19
 
3.6%
피 19
 
3.6%
치 17
 
3.2%
물 14
 
2.6%
김 14
 
2.6%
무 14
 
2.6%
육 11
 
2.1%
밥 10
 
1.9%
추 10
 
1.9%
Other values (152) 383
72.1%
ASCII
ValueCountFrequency (%)
1 13
20.3%
2 11
17.2%
( 8
12.5%
) 8
12.5%
0 8
12.5%
3 7
10.9%
6
9.4%
. 1
 
1.6%
9 1
 
1.6%
6 1
 
1.6%

원료명
Text

MISSING 

Distinct24
Distinct (%)77.4%
Missing5633
Missing (%)99.5%
Memory size44.4 KiB
2024-05-11T16:58:54.558065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.6129032
Min length1

Characters and Unicode

Total characters112
Distinct characters57
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)67.7%

Sample

1st row종사자손(황효순)
2nd row종사자손(김성호)
3rd row종사자손(황광호)
4th row종사자손(지춘옥)
5th row정수기물
ValueCountFrequency (%)
배추김치 4
 
12.9%
콩 3
 
9.7%
콩류 3
 
9.7%
열무 1
 
3.2%
오이 1
 
3.2%
야채 1
 
3.2%
양념바지락젓갈 1
 
3.2%
버섯 1
 
3.2%
상추 1
 
3.2%
고사리 1
 
3.2%
Other values (14) 14
45.2%
2024-05-11T16:58:54.926267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
콩 7
 
6.2%
김 6
 
5.4%
치 6
 
5.4%
추 5
 
4.5%
사 5
 
4.5%
배 4
 
3.6%
) 4
 
3.6%
종 4
 
3.6%
자 4
 
3.6%
손 4
 
3.6%
Other values (47) 63
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
92.9%
Close Punctuation 4
 
3.6%
Open Punctuation 4
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
콩 7
 
6.7%
김 6
 
5.8%
치 6
 
5.8%
추 5
 
4.8%
사 5
 
4.8%
배 4
 
3.8%
종 4
 
3.8%
자 4
 
3.8%
손 4
 
3.8%
물 3
 
2.9%
Other values (45) 56
53.8%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
92.9%
Common 8
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
콩 7
 
6.7%
김 6
 
5.8%
치 6
 
5.8%
추 5
 
4.8%
사 5
 
4.8%
배 4
 
3.8%
종 4
 
3.8%
자 4
 
3.8%
손 4
 
3.8%
물 3
 
2.9%
Other values (45) 56
53.8%
Common
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
92.9%
ASCII 8
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
콩 7
 
6.7%
김 6
 
5.8%
치 6
 
5.8%
추 5
 
4.8%
사 5
 
4.8%
배 4
 
3.8%
종 4
 
3.8%
자 4
 
3.8%
손 4
 
3.8%
물 3
 
2.9%
Other values (45) 56
53.8%
ASCII
ValueCountFrequency (%)
) 4
50.0%
( 4
50.0%

생산업소
Text

MISSING 

Distinct342
Distinct (%)31.8%
Missing4587
Missing (%)81.0%
Memory size44.4 KiB
2024-05-11T16:58:55.198251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length6.7678737
Min length1

Characters and Unicode

Total characters7289
Distinct characters359
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

Unique190 ?
Unique (%)17.6%

Sample

1st rowQingdad hanaai food co. LTD
2nd row황효순
3rd row현대회집
4th row황효순
5th row현대회집
ValueCountFrequency (%)
씨제이제일제당(주 51
 
4.6%
주)오뚜기 50
 
4.5%
세현고등학교 49
 
4.4%
서울화곡초등학교 45
 
4.1%
주)대상 39
 
3.5%
송정초등학교 37
 
3.3%
염창초교 35
 
3.2%
주식회사오뚜기 32
 
2.9%
대상(주 17
 
1.5%
주)동원f&amp;amp;b 14
 
1.3%
Other values (350) 738
66.7%
2024-05-11T16:58:55.642700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 546
 
7.5%
( 487
 
6.7%
) 486
 
6.7%
제 237
 
3.3%
교 199
 
2.7%
식 181
 
2.5%
등 166
 
2.3%
학 162
 
2.2%
오 142
 
1.9%
초 130
 
1.8%
Other values (349) 4553
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5897
80.9%
Open Punctuation 487
 
6.7%
Close Punctuation 486
 
6.7%
Lowercase Letter 162
 
2.2%
Uppercase Letter 137
 
1.9%
Other Punctuation 83
 
1.1%
Space Separator 30
 
0.4%
Decimal Number 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 546
 
9.3%
제 237
 
4.0%
교 199
 
3.4%
식 181
 
3.1%
등 166
 
2.8%
학 162
 
2.7%
오 142
 
2.4%
초 130
 
2.2%
품 119
 
2.0%
기 115
 
2.0%
Other values (312) 3900
66.1%
Uppercase Letter
ValueCountFrequency (%)
F 57
41.6%
B 34
24.8%
N 10
 
7.3%
S 6
 
4.4%
C 6
 
4.4%
L 5
 
3.6%
T 4
 
2.9%
D 4
 
2.9%
I 3
 
2.2%
O 2
 
1.5%
Other values (4) 6
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
a 52
32.1%
p 48
29.6%
m 48
29.6%
o 3
 
1.9%
d 3
 
1.9%
i 2
 
1.2%
n 2
 
1.2%
c 1
 
0.6%
f 1
 
0.6%
h 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
9 2
28.6%
6 1
14.3%
3 1
14.3%
2 1
14.3%
1 1
14.3%
5 1
14.3%
Other Punctuation
ValueCountFrequency (%)
; 48
57.8%
& 32
38.6%
. 3
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 487
100.0%
Close Punctuation
ValueCountFrequency (%)
) 486
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5897
80.9%
Common 1093
 
15.0%
Latin 299
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 546
 
9.3%
제 237
 
4.0%
교 199
 
3.4%
식 181
 
3.1%
등 166
 
2.8%
학 162
 
2.7%
오 142
 
2.4%
초 130
 
2.2%
품 119
 
2.0%
기 115
 
2.0%
Other values (312) 3900
66.1%
Latin
ValueCountFrequency (%)
F 57
19.1%
a 52
17.4%
p 48
16.1%
m 48
16.1%
B 34
11.4%
N 10
 
3.3%
S 6
 
2.0%
C 6
 
2.0%
L 5
 
1.7%
T 4
 
1.3%
Other values (15) 29
9.7%
Common
ValueCountFrequency (%)
( 487
44.6%
) 486
44.5%
; 48
 
4.4%
& 32
 
2.9%
30
 
2.7%
. 3
 
0.3%
9 2
 
0.2%
6 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5897
80.9%
ASCII 1392
 
19.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 546
 
9.3%
제 237
 
4.0%
교 199
 
3.4%
식 181
 
3.1%
등 166
 
2.8%
학 162
 
2.7%
오 142
 
2.4%
초 130
 
2.2%
품 119
 
2.0%
기 115
 
2.0%
Other values (312) 3900
66.1%
ASCII
ValueCountFrequency (%)
( 487
35.0%
) 486
34.9%
F 57
 
4.1%
a 52
 
3.7%
p 48
 
3.4%
m 48
 
3.4%
; 48
 
3.4%
B 34
 
2.4%
& 32
 
2.3%
30
 
2.2%
Other values (27) 70
 
5.0%

수거일자
Real number (ℝ)

Distinct286
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20141490
Minimum20090120
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:55.812953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090120
5-th percentile20090730
Q120110705
median20130610
Q320170602
95-th percentile20230808
Maximum20240314
Range150194
Interquartile range (IQR)59897

Descriptive statistics

Standard deviation39951.69
Coefficient of variation (CV)0.0019835519
Kurtosis-0.34385078
Mean20141490
Median Absolute Deviation (MAD)29706
Skewness0.70675551
Sum1.140814 × 1011
Variance1.5961376 × 109
MonotonicityNot monotonic
2024-05-11T16:58:55.987787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151209 166
 
2.9%
20160615 120
 
2.1%
20120704 107
 
1.9%
20121122 98
 
1.7%
20240119 97
 
1.7%
20180321 96
 
1.7%
20150904 94
 
1.7%
20100420 93
 
1.6%
20170602 92
 
1.6%
20130611 91
 
1.6%
Other values (276) 4610
81.4%
ValueCountFrequency (%)
20090120 40
0.7%
20090305 37
0.7%
20090518 14
 
0.2%
20090521 5
 
0.1%
20090604 56
1.0%
20090710 73
1.3%
20090713 10
 
0.2%
20090721 5
 
0.1%
20090730 67
1.2%
20090807 12
 
0.2%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240307 1
 
< 0.1%
20240306 4
 
0.1%
20240305 30
 
0.5%
20240227 3
 
0.1%
20240119 97
1.7%
20240117 2
 
< 0.1%
20240116 18
 
0.3%
20231208 36
 
0.6%
20231121 5
 
0.1%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct41
Distinct (%)0.8%
Missing314
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean22471.31
Minimum1
Maximum1.2017041 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:56.136487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile8
Maximum1.2017041 × 108
Range1.201704 × 108
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1642935.8
Coefficient of variation (CV)73.112597
Kurtosis5350
Mean22471.31
Median Absolute Deviation (MAD)1
Skewness73.143694
Sum1.2022151 × 108
Variance2.6992382 × 1012
MonotonicityNot monotonic
2024-05-11T16:58:56.309714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 2092
36.9%
2 789
 
13.9%
4 736
 
13.0%
3 641
 
11.3%
6 509
 
9.0%
5 268
 
4.7%
300 75
 
1.3%
8 38
 
0.7%
7 32
 
0.6%
9 24
 
0.4%
Other values (31) 146
 
2.6%
(Missing) 314
 
5.5%
ValueCountFrequency (%)
1 2092
36.9%
2 789
 
13.9%
3 641
 
11.3%
4 736
 
13.0%
5 268
 
4.7%
6 509
 
9.0%
7 32
 
0.6%
8 38
 
0.7%
9 24
 
0.4%
10 23
 
0.4%
ValueCountFrequency (%)
120170406 1
 
< 0.1%
600 4
 
0.1%
470 1
 
< 0.1%
420 1
 
< 0.1%
400 1
 
< 0.1%
370 2
 
< 0.1%
360 1
 
< 0.1%
350 6
 
0.1%
330 2
 
< 0.1%
300 75
1.3%

제품규격(정량)
Text

MISSING 

Distinct541
Distinct (%)13.2%
Missing1571
Missing (%)27.7%
Memory size44.4 KiB
2024-05-11T16:58:56.751076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9914488
Min length1

Characters and Unicode

Total characters12244
Distinct characters23
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)5.6%

Sample

1st row500
2nd row600
3rd rowL
4th row1
5th row개
ValueCountFrequency (%)
200 330
 
8.1%
1 286
 
7.0%
600 250
 
6.1%
500 161
 
3.9%
300 156
 
3.8%
1.5 122
 
3.0%
100 103
 
2.5%
900 84
 
2.1%
150 78
 
1.9%
400 73
 
1.8%
Other values (530) 2450
59.9%
2024-05-11T16:58:57.425771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4259
34.8%
1 1529
 
12.5%
5 1198
 
9.8%
2 1170
 
9.6%
3 759
 
6.2%
4 549
 
4.5%
g 537
 
4.4%
6 523
 
4.3%
8 379
 
3.1%
7 336
 
2.7%
Other values (13) 1005
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10976
89.6%
Lowercase Letter 879
 
7.2%
Other Punctuation 323
 
2.6%
Other Letter 38
 
0.3%
Uppercase Letter 28
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4259
38.8%
1 1529
 
13.9%
5 1198
 
10.9%
2 1170
 
10.7%
3 759
 
6.9%
4 549
 
5.0%
6 523
 
4.8%
8 379
 
3.5%
7 336
 
3.1%
9 274
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
g 537
61.1%
m 140
 
15.9%
l 139
 
15.8%
k 62
 
7.1%
p 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
L 17
60.7%
G 7
25.0%
E 2
 
7.1%
A 2
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 243
75.2%
* 66
 
20.4%
, 14
 
4.3%
Other Letter
ValueCountFrequency (%)
개 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11299
92.3%
Latin 907
 
7.4%
Hangul 38
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4259
37.7%
1 1529
 
13.5%
5 1198
 
10.6%
2 1170
 
10.4%
3 759
 
6.7%
4 549
 
4.9%
6 523
 
4.6%
8 379
 
3.4%
7 336
 
3.0%
9 274
 
2.4%
Other values (3) 323
 
2.9%
Latin
ValueCountFrequency (%)
g 537
59.2%
m 140
 
15.4%
l 139
 
15.3%
k 62
 
6.8%
L 17
 
1.9%
G 7
 
0.8%
E 2
 
0.2%
A 2
 
0.2%
p 1
 
0.1%
Hangul
ValueCountFrequency (%)
개 38
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12206
99.7%
Hangul 38
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4259
34.9%
1 1529
 
12.5%
5 1198
 
9.8%
2 1170
 
9.6%
3 759
 
6.2%
4 549
 
4.5%
g 537
 
4.4%
6 523
 
4.3%
8 379
 
3.1%
7 336
 
2.8%
Other values (12) 967
 
7.9%
Hangul
ValueCountFrequency (%)
개 38
100.0%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
g
2322 
<NA>
2313 
ML
529 
LT
270 
KG
 
212
Other values (2)
 
18

Length

Max length4
Median length2
Mean length2.4037782
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 2322
41.0%
<NA> 2313
40.8%
ML 529
 
9.3%
LT 270
 
4.8%
KG 212
 
3.7%
매 17
 
0.3%
mm 1
 
< 0.1%

Length

2024-05-11T16:58:57.592177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:58:57.714408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 2322
41.0%
na 2313
40.8%
ml 529
 
9.3%
lt 270
 
4.8%
kg 212
 
3.7%
매 17
 
0.3%
mm 1
 
< 0.1%

수거량(자유)
Text

MISSING 

Distinct71
Distinct (%)22.6%
Missing5350
Missing (%)94.5%
Memory size44.4 KiB
2024-05-11T16:58:57.983304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length6
Mean length5.5700637
Min length2

Characters and Unicode

Total characters1749
Distinct characters63
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

Unique39 ?
Unique (%)12.4%

Sample

1st row면봉3개
2nd row면봉 3개
3rd row면봉 3개
4th row면봉 3개
5th row면봉 3개
ValueCountFrequency (%)
보존식 104
21.2%
규격 104
21.2%
1개 33
 
6.7%
3개 33
 
6.7%
면봉 28
 
5.7%
210g*3 10
 
2.0%
표면 9
 
1.8%
도말 9
 
1.8%
1kg*1개 8
 
1.6%
340g*2 7
 
1.4%
Other values (69) 145
29.6%
2024-05-11T16:58:58.405669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
10.1%
1 119
 
6.8%
개 119
 
6.8%
0 110
 
6.3%
보 104
 
5.9%
식 104
 
5.9%
규 104
 
5.9%
격 104
 
5.9%
존 104
 
5.9%
* 99
 
5.7%
Other values (53) 606
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 858
49.1%
Decimal Number 494
28.2%
Space Separator 176
 
10.1%
Other Punctuation 106
 
6.1%
Lowercase Letter 106
 
6.1%
Uppercase Letter 5
 
0.3%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 119
13.9%
보 104
12.1%
식 104
12.1%
규 104
12.1%
격 104
12.1%
존 104
12.1%
면 46
 
5.4%
봉 32
 
3.7%
도 16
 
1.9%
표 15
 
1.7%
Other values (30) 110
12.8%
Decimal Number
ValueCountFrequency (%)
1 119
24.1%
0 110
22.3%
3 81
16.4%
2 66
13.4%
4 40
 
8.1%
5 32
 
6.5%
6 20
 
4.0%
8 19
 
3.8%
7 7
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
g 91
85.8%
k 9
 
8.5%
x 4
 
3.8%
o 1
 
0.9%
r 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
* 99
93.4%
, 6
 
5.7%
. 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
G 3
60.0%
A 1
 
20.0%
E 1
 
20.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 858
49.1%
Common 780
44.6%
Latin 111
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 119
13.9%
보 104
12.1%
식 104
12.1%
규 104
12.1%
격 104
12.1%
존 104
12.1%
면 46
 
5.4%
봉 32
 
3.7%
도 16
 
1.9%
표 15
 
1.7%
Other values (30) 110
12.8%
Common
ValueCountFrequency (%)
176
22.6%
1 119
15.3%
0 110
14.1%
* 99
12.7%
3 81
10.4%
2 66
 
8.5%
4 40
 
5.1%
5 32
 
4.1%
6 20
 
2.6%
8 19
 
2.4%
Other values (5) 18
 
2.3%
Latin
ValueCountFrequency (%)
g 91
82.0%
k 9
 
8.1%
x 4
 
3.6%
G 3
 
2.7%
o 1
 
0.9%
r 1
 
0.9%
A 1
 
0.9%
E 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 891
50.9%
Hangul 856
48.9%
Compat Jamo 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
19.8%
1 119
13.4%
0 110
12.3%
* 99
11.1%
g 91
10.2%
3 81
9.1%
2 66
 
7.4%
4 40
 
4.5%
5 32
 
3.6%
6 20
 
2.2%
Other values (13) 57
 
6.4%
Hangul
ValueCountFrequency (%)
개 119
13.9%
보 104
12.1%
식 104
12.1%
규 104
12.1%
격 104
12.1%
존 104
12.1%
면 46
 
5.4%
봉 32
 
3.7%
도 16
 
1.9%
표 15
 
1.8%
Other values (29) 108
12.6%
Compat Jamo
ValueCountFrequency (%)
ㅎ 2
100.0%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct271
Distinct (%)23.8%
Missing4526
Missing (%)79.9%
Infinite0
Infinite (%)0.0%
Mean20175167
Minimum20110929
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:58.590240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110929
5-th percentile20120625
Q120151143
median20180307
Q320190411
95-th percentile20240119
Maximum20240314
Range129385
Interquartile range (IQR)39268.25

Descriptive statistics

Standard deviation33339.75
Coefficient of variation (CV)0.0016525142
Kurtosis-0.32966399
Mean20175167
Median Absolute Deviation (MAD)19586
Skewness0.36135235
Sum2.295934 × 1010
Variance1.1115389 × 109
MonotonicityNot monotonic
2024-05-11T16:58:58.772607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20240119 97
 
1.7%
20180319 29
 
0.5%
20180316 26
 
0.5%
20180320 25
 
0.4%
20190410 25
 
0.4%
20180427 24
 
0.4%
20190408 17
 
0.3%
20160728 17
 
0.3%
20190409 16
 
0.3%
20160721 16
 
0.3%
Other values (261) 846
 
14.9%
(Missing) 4526
79.9%
ValueCountFrequency (%)
20110929 1
 
< 0.1%
20111115 1
 
< 0.1%
20111121 1
 
< 0.1%
20111124 1
 
< 0.1%
20111129 1
 
< 0.1%
20111219 2
 
< 0.1%
20120105 1
 
< 0.1%
20120106 6
0.1%
20120117 1
 
< 0.1%
20120119 1
 
< 0.1%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240227 3
 
0.1%
20240119 97
1.7%
20231208 4
 
0.1%
20231207 7
 
0.1%
20231206 9
 
0.2%
20231205 8
 
0.1%
20231204 8
 
0.1%
20231024 3
 
0.1%
20231012 1
 
< 0.1%

제조일자(롯트)
Text

MISSING 

Distinct19
Distinct (%)76.0%
Missing5639
Missing (%)99.6%
Memory size44.4 KiB
2024-05-11T16:58:58.969222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.92
Min length2

Characters and Unicode

Total characters173
Distinct characters29
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st rowL17048H
2nd row614825
3rd rowLIB300617QA
4th row600934 롯데주류
5th row603555
ValueCountFrequency (%)
미상 7
26.9%
600934 1
 
3.8%
614825 1
 
3.8%
lib300617qa 1
 
3.8%
l8138 1
 
3.8%
la125a045t12 1
 
3.8%
l11901172216 1
 
3.8%
l8179x22 1
 
3.8%
l6221 1
 
3.8%
l3ca29417 1
 
3.8%
Other values (10) 10
38.5%
2024-05-11T16:58:59.271140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
13.9%
0 20
11.6%
2 14
 
8.1%
4 14
 
8.1%
L 14
 
8.1%
7 10
 
5.8%
5 10
 
5.8%
3 10
 
5.8%
8 9
 
5.2%
상 7
 
4.0%
Other values (19) 41
23.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123
71.1%
Uppercase Letter 31
 
17.9%
Other Letter 18
 
10.4%
Space Separator 1
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 14
45.2%
A 4
 
12.9%
C 2
 
6.5%
I 2
 
6.5%
F 2
 
6.5%
B 1
 
3.2%
T 1
 
3.2%
X 1
 
3.2%
H 1
 
3.2%
P 1
 
3.2%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 24
19.5%
0 20
16.3%
2 14
11.4%
4 14
11.4%
7 10
8.1%
5 10
8.1%
3 10
8.1%
8 9
 
7.3%
6 7
 
5.7%
9 5
 
4.1%
Other Letter
ValueCountFrequency (%)
상 7
38.9%
미 7
38.9%
류 1
 
5.6%
주 1
 
5.6%
롯 1
 
5.6%
데 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
71.7%
Latin 31
 
17.9%
Hangul 18
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 14
45.2%
A 4
 
12.9%
C 2
 
6.5%
I 2
 
6.5%
F 2
 
6.5%
B 1
 
3.2%
T 1
 
3.2%
X 1
 
3.2%
H 1
 
3.2%
P 1
 
3.2%
Other values (2) 2
 
6.5%
Common
ValueCountFrequency (%)
1 24
19.4%
0 20
16.1%
2 14
11.3%
4 14
11.3%
7 10
8.1%
5 10
8.1%
3 10
8.1%
8 9
 
7.3%
6 7
 
5.6%
9 5
 
4.0%
Hangul
ValueCountFrequency (%)
상 7
38.9%
미 7
38.9%
류 1
 
5.6%
주 1
 
5.6%
롯 1
 
5.6%
데 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155
89.6%
Hangul 18
 
10.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
15.5%
0 20
12.9%
2 14
9.0%
4 14
9.0%
L 14
9.0%
7 10
6.5%
5 10
6.5%
3 10
6.5%
8 9
 
5.8%
6 7
 
4.5%
Other values (13) 23
14.8%
Hangul
ValueCountFrequency (%)
상 7
38.9%
미 7
38.9%
류 1
 
5.6%
주 1
 
5.6%
롯 1
 
5.6%
데 1
 
5.6%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct614
Distinct (%)64.0%
Missing4704
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean20132097
Minimum20090710
Maximum20191028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:59.418476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090710
5-th percentile20111124
Q120121115
median20130920
Q320140510
95-th percentile20150323
Maximum20191028
Range100318
Interquartile range (IQR)19395.25

Descriptive statistics

Standard deviation11096.157
Coefficient of variation (CV)0.00055116747
Kurtosis0.73657209
Mean20132097
Median Absolute Deviation (MAD)9703
Skewness0.22391238
Sum1.9326813 × 1010
Variance1.231247 × 108
MonotonicityNot monotonic
2024-05-11T16:58:59.554005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111117 8
 
0.1%
20130228 7
 
0.1%
20140515 7
 
0.1%
20120501 6
 
0.1%
20121119 5
 
0.1%
20140513 5
 
0.1%
20140509 5
 
0.1%
20140415 5
 
0.1%
20121019 5
 
0.1%
20111120 5
 
0.1%
Other values (604) 902
 
15.9%
(Missing) 4704
83.1%
ValueCountFrequency (%)
20090710 1
< 0.1%
20100527 1
< 0.1%
20100921 1
< 0.1%
20110629 1
< 0.1%
20110907 1
< 0.1%
20110914 1
< 0.1%
20110922 1
< 0.1%
20110926 1
< 0.1%
20110929 1
< 0.1%
20110930 2
< 0.1%
ValueCountFrequency (%)
20191028 1
< 0.1%
20170217 1
< 0.1%
20161004 1
< 0.1%
20160928 1
< 0.1%
20160907 1
< 0.1%
20160906 1
< 0.1%
20160905 1
< 0.1%
20160815 1
< 0.1%
20160810 1
< 0.1%
20160731 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)33.3%
Missing5637
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean5217916.5
Minimum1
Maximum20160416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:58:59.666965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q17
median180
Q310060413
95-th percentile20120107
Maximum20160416
Range20160415
Interquartile range (IQR)10060406

Descriptive statistics

Standard deviation8987673
Coefficient of variation (CV)1.7224639
Kurtosis-0.70198974
Mean5217916.5
Median Absolute Deviation (MAD)173
Skewness1.1644176
Sum1.4088375 × 108
Variance8.0778265 × 1013
MonotonicityNot monotonic
2024-05-11T16:58:59.778171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
7 9
 
0.2%
180 4
 
0.1%
20120107 4
 
0.1%
365 3
 
0.1%
20120106 2
 
< 0.1%
1 2
 
< 0.1%
90 1
 
< 0.1%
720 1
 
< 0.1%
20160416 1
 
< 0.1%
(Missing) 5637
99.5%
ValueCountFrequency (%)
1 2
 
< 0.1%
7 9
0.2%
90 1
 
< 0.1%
180 4
0.1%
365 3
 
0.1%
720 1
 
< 0.1%
20120106 2
 
< 0.1%
20120107 4
0.1%
20160416 1
 
< 0.1%
ValueCountFrequency (%)
20160416 1
 
< 0.1%
20120107 4
0.1%
20120106 2
 
< 0.1%
720 1
 
< 0.1%
365 3
 
0.1%
180 4
0.1%
90 1
 
< 0.1%
7 9
0.2%
1 2
 
< 0.1%

보관상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
실온
2647 
<NA>
1999 
냉장
494 
냉동
475 
기타
 
49

Length

Max length4
Median length2
Mean length2.7058616
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 2647
46.7%
<NA> 1999
35.3%
냉장 494
 
8.7%
냉동 475
 
8.4%
기타 49
 
0.9%

Length

2024-05-11T16:58:59.905950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:00.011668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 2647
46.7%
na 1999
35.3%
냉장 494
 
8.7%
냉동 475
 
8.4%
기타 49
 
0.9%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

어린이기호식품유형
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5620 
과자(한과류제외)
 
11
캔디류
 
8
초콜릿류
 
7
유탕면류(용기면)
 
5
Other values (3)
 
13

Length

Max length9
Median length4
Mean length4.013065
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5620
99.2%
과자(한과류제외) 11
 
0.2%
캔디류 8
 
0.1%
초콜릿류 7
 
0.1%
유탕면류(용기면) 5
 
0.1%
혼합음료 5
 
0.1%
과?채음료 5
 
0.1%
빙과류 3
 
0.1%

Length

2024-05-11T16:59:00.124067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:00.237055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5620
99.2%
과자(한과류제외 11
 
0.2%
캔디류 8
 
0.1%
초콜릿류 7
 
0.1%
유탕면류(용기면 5
 
0.1%
혼합음료 5
 
0.1%
과?채음료 5
 
0.1%
빙과류 3
 
0.1%

검사기관명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
4191 
<NA>
1466 
2
 
4
3
 
3

Length

Max length4
Median length1
Mean length1.7764831
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4191
74.0%
<NA> 1466
 
25.9%
2 4
 
0.1%
3 3
 
0.1%

Length

2024-05-11T16:59:00.364431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:00.465124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4191
74.0%
na 1466
 
25.9%
2 4
 
0.1%
3 3
 
0.1%

(구)제조사명
Text

MISSING 

Distinct348
Distinct (%)31.1%
Missing4546
Missing (%)80.3%
Memory size44.4 KiB
2024-05-11T16:59:00.666454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.734347
Min length2

Characters and Unicode

Total characters7529
Distinct characters311
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

Unique166 ?
Unique (%)14.8%

Sample

1st row밀향기해물손칼국수
2nd row현대회집
3rd row현대회집
4th row현대회집
5th row현대회집
ValueCountFrequency (%)
씨제이제일제당(주 45
 
3.8%
오뚜기 40
 
3.4%
농심 36
 
3.0%
대상(주 29
 
2.5%
롯데칠성음료(주 28
 
2.4%
주)대상 26
 
2.2%
주)삼립식품 23
 
1.9%
공항컨벤션웨딩 22
 
1.9%
주식회사 21
 
1.8%
주)오뚜기 20
 
1.7%
Other values (355) 893
75.5%
2024-05-11T16:59:01.015010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 774
 
10.3%
( 714
 
9.5%
) 714
 
9.5%
식 308
 
4.1%
제 243
 
3.2%
품 240
 
3.2%
기 120
 
1.6%
오 120
 
1.6%
사 103
 
1.4%
음 103
 
1.4%
Other values (301) 4090
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5817
77.3%
Open Punctuation 714
 
9.5%
Close Punctuation 714
 
9.5%
Uppercase Letter 146
 
1.9%
Space Separator 65
 
0.9%
Lowercase Letter 42
 
0.6%
Other Punctuation 28
 
0.4%
Decimal Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 774
 
13.3%
식 308
 
5.3%
제 243
 
4.2%
품 240
 
4.1%
기 120
 
2.1%
오 120
 
2.1%
사 103
 
1.8%
음 103
 
1.8%
료 101
 
1.7%
이 97
 
1.7%
Other values (281) 3608
62.0%
Uppercase Letter
ValueCountFrequency (%)
F 65
44.5%
B 38
26.0%
S 13
 
8.9%
N 12
 
8.2%
O 6
 
4.1%
I 4
 
2.7%
D 3
 
2.1%
C 3
 
2.1%
M 2
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
m 14
33.3%
p 14
33.3%
a 14
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
0 1
33.3%
1 1
33.3%
Other Punctuation
ValueCountFrequency (%)
& 14
50.0%
; 14
50.0%
Open Punctuation
ValueCountFrequency (%)
( 714
100.0%
Close Punctuation
ValueCountFrequency (%)
) 714
100.0%
Space Separator
ValueCountFrequency (%)
65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5817
77.3%
Common 1524
 
20.2%
Latin 188
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 774
 
13.3%
식 308
 
5.3%
제 243
 
4.2%
품 240
 
4.1%
기 120
 
2.1%
오 120
 
2.1%
사 103
 
1.8%
음 103
 
1.8%
료 101
 
1.7%
이 97
 
1.7%
Other values (281) 3608
62.0%
Latin
ValueCountFrequency (%)
F 65
34.6%
B 38
20.2%
m 14
 
7.4%
p 14
 
7.4%
a 14
 
7.4%
S 13
 
6.9%
N 12
 
6.4%
O 6
 
3.2%
I 4
 
2.1%
D 3
 
1.6%
Other values (2) 5
 
2.7%
Common
ValueCountFrequency (%)
( 714
46.9%
) 714
46.9%
65
 
4.3%
& 14
 
0.9%
; 14
 
0.9%
2 1
 
0.1%
0 1
 
0.1%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5817
77.3%
ASCII 1712
 
22.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 774
 
13.3%
식 308
 
5.3%
제 243
 
4.2%
품 240
 
4.1%
기 120
 
2.1%
오 120
 
2.1%
사 103
 
1.8%
음 103
 
1.8%
료 101
 
1.7%
이 97
 
1.7%
Other values (281) 3608
62.0%
ASCII
ValueCountFrequency (%)
( 714
41.7%
) 714
41.7%
F 65
 
3.8%
65
 
3.8%
B 38
 
2.2%
m 14
 
0.8%
p 14
 
0.8%
& 14
 
0.8%
a 14
 
0.8%
; 14
 
0.8%
Other values (10) 46
 
2.7%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
국내
4056 
국외
1608 

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 4056
71.6%
국외 1608
 
28.4%

Length

2024-05-11T16:59:01.135829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:01.224568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4056
71.6%
국외 1608
 
28.4%

국가명
Categorical

IMBALANCE 

Distinct39
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5313 
미국
 
48
중국
 
45
일본
 
42
태국
 
26
Other values (34)
 
190

Length

Max length6
Median length4
Mean length3.9247881
Min length2

Unique

Unique12 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5313
93.8%
미국 48
 
0.8%
중국 45
 
0.8%
일본 42
 
0.7%
태국 26
 
0.5%
말레이지아 24
 
0.4%
독일 22
 
0.4%
이탈리아 16
 
0.3%
필리핀 13
 
0.2%
베트남 13
 
0.2%
Other values (29) 102
 
1.8%

Length

2024-05-11T16:59:01.342818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5313
93.7%
미국 48
 
0.8%
중국 45
 
0.8%
일본 42
 
0.7%
태국 26
 
0.5%
말레이지아 24
 
0.4%
독일 22
 
0.4%
이탈리아 16
 
0.3%
필리핀 13
 
0.2%
베트남 13
 
0.2%
Other values (30) 110
 
1.9%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
3017 
<NA>
1881 
2
766 

Length

Max length4
Median length1
Mean length1.9962924
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3017
53.3%
<NA> 1881
33.2%
2 766
 
13.5%

Length

2024-05-11T16:59:01.513008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:01.622028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3017
53.3%
na 1881
33.2%
2 766
 
13.5%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct148
Distinct (%)5.0%
Missing2723
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean20161749
Minimum20110308
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:59:01.975883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110308
5-th percentile20110705
Q120120922
median20170330
Q320190415
95-th percentile20240117
Maximum20240314
Range130006
Interquartile range (IQR)69493

Descriptive statistics

Standard deviation40499.2
Coefficient of variation (CV)0.0020087146
Kurtosis-0.96287503
Mean20161749
Median Absolute Deviation (MAD)39719
Skewness0.24312037
Sum5.9295704 × 1010
Variance1.6401852 × 109
MonotonicityNot monotonic
2024-05-11T16:59:02.131737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130611 138
 
2.4%
20160615 121
 
2.1%
20240119 96
 
1.7%
20180321 96
 
1.7%
20170603 92
 
1.6%
20110706 88
 
1.6%
20110719 86
 
1.5%
20130524 83
 
1.5%
20111031 80
 
1.4%
20190725 72
 
1.3%
Other values (138) 1989
35.1%
(Missing) 2723
48.1%
ValueCountFrequency (%)
20110308 22
 
0.4%
20110414 66
1.2%
20110517 12
 
0.2%
20110518 8
 
0.1%
20110601 7
 
0.1%
20110628 15
 
0.3%
20110705 48
0.8%
20110706 88
1.6%
20110719 86
1.5%
20110817 43
0.8%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240306 35
 
0.6%
20240227 3
 
0.1%
20240119 96
1.7%
20240117 21
 
0.4%
20231208 36
 
0.6%
20231121 5
 
0.1%
20231115 1
 
< 0.1%
20231024 3
 
0.1%
20231018 2
 
< 0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)6.4%
Missing3818
Missing (%)67.4%
Infinite0
Infinite (%)0.0%
Mean20164425
Minimum20110314
Maximum20210330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:59:02.270019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110314
5-th percentile20130124
Q120130813
median20170630
Q320181008
95-th percentile20190809
Maximum20210330
Range100016
Interquartile range (IQR)50195

Descriptive statistics

Standard deviation24070.245
Coefficient of variation (CV)0.0011936986
Kurtosis-0.75900486
Mean20164425
Median Absolute Deviation (MAD)10378
Skewness-0.69769865
Sum3.7223529 × 1010
Variance5.7937669 × 108
MonotonicityNot monotonic
2024-05-11T16:59:02.401772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160701 121
 
2.1%
20180404 96
 
1.7%
20170630 92
 
1.6%
20130605 80
 
1.4%
20130701 65
 
1.1%
20181008 63
 
1.1%
20190614 60
 
1.1%
20190809 56
 
1.0%
20190424 52
 
0.9%
20180919 49
 
0.9%
Other values (108) 1112
 
19.6%
(Missing) 3818
67.4%
ValueCountFrequency (%)
20110314 7
0.1%
20110315 15
0.3%
20110610 7
0.1%
20110706 12
0.2%
20110725 3
 
0.1%
20110830 6
 
0.1%
20110928 15
0.3%
20111215 9
0.2%
20120529 1
 
< 0.1%
20121113 8
0.1%
ValueCountFrequency (%)
20210330 3
 
0.1%
20201217 2
 
< 0.1%
20201214 1
 
< 0.1%
20201204 5
0.1%
20200804 1
 
< 0.1%
20191128 11
0.2%
20191126 10
0.2%
20191119 1
 
< 0.1%
20191107 1
 
< 0.1%
20191106 1
 
< 0.1%

판정구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
3665 
1
1988 
2
 
11

Length

Max length4
Median length4
Mean length2.9412076
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3665
64.7%
1 1988
35.1%
2 11
 
0.2%

Length

2024-05-11T16:59:02.527882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:02.623031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3665
64.7%
1 1988
35.1%
2 11
 
0.2%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

처리결과
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing5661
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T16:59:02.747366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.6666667
Min length2

Characters and Unicode

Total characters14
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row적합
2nd row노로바이러스검출
3rd row행정처분
ValueCountFrequency (%)
적합 1
33.3%
노로바이러스검출 1
33.3%
행정처분 1
33.3%
2024-05-11T16:59:03.003151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
적 1
 
7.1%
합 1
 
7.1%
노 1
 
7.1%
로 1
 
7.1%
바 1
 
7.1%
이 1
 
7.1%
러 1
 
7.1%
스 1
 
7.1%
검 1
 
7.1%
출 1
 
7.1%
Other values (4) 4
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
적 1
 
7.1%
합 1
 
7.1%
노 1
 
7.1%
로 1
 
7.1%
바 1
 
7.1%
이 1
 
7.1%
러 1
 
7.1%
스 1
 
7.1%
검 1
 
7.1%
출 1
 
7.1%
Other values (4) 4
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
적 1
 
7.1%
합 1
 
7.1%
노 1
 
7.1%
로 1
 
7.1%
바 1
 
7.1%
이 1
 
7.1%
러 1
 
7.1%
스 1
 
7.1%
검 1
 
7.1%
출 1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
적 1
 
7.1%
합 1
 
7.1%
노 1
 
7.1%
로 1
 
7.1%
바 1
 
7.1%
이 1
 
7.1%
러 1
 
7.1%
스 1
 
7.1%
검 1
 
7.1%
출 1
 
7.1%
Other values (4) 4
28.6%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

교부번호
Real number (ℝ)

Distinct503
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0036974 × 1010
Minimum1.9780076 × 1010
Maximum2.0230103 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:59:03.131493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9780076 × 1010
5-th percentile1.9980077 × 1010
Q12.0000077 × 1010
median2.0020077 × 1010
Q32.0050077 × 1010
95-th percentile2.0140076 × 1010
Maximum2.0230103 × 1010
Range4.5002667 × 108
Interquartile range (IQR)50000200

Descriptive statistics

Standard deviation50706921
Coefficient of variation (CV)0.0025306676
Kurtosis1.6698195
Mean2.0036974 × 1010
Median Absolute Deviation (MAD)29999181
Skewness0.71780312
Sum1.1348942 × 1014
Variance2.5711919 × 1015
MonotonicityNot monotonic
2024-05-11T16:59:03.283700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010076090 1257
22.2%
20000076721 545
 
9.6%
20050076101 449
 
7.9%
20050076871 413
 
7.3%
19980077354 324
 
5.7%
20030076097 269
 
4.7%
20060076007 175
 
3.1%
20140076038 161
 
2.8%
20020076920 97
 
1.7%
20110076832 89
 
1.6%
Other values (493) 1885
33.3%
ValueCountFrequency (%)
19780076021 1
 
< 0.1%
19800076046 3
 
0.1%
19810076025 2
 
< 0.1%
19810076054 2
 
< 0.1%
19830076060 1
 
< 0.1%
19830076123 1
 
< 0.1%
19840076132 9
0.2%
19850076064 1
 
< 0.1%
19870076210 1
 
< 0.1%
19890076063 2
 
< 0.1%
ValueCountFrequency (%)
20230102689 1
 
< 0.1%
20230102411 1
 
< 0.1%
20230101212 2
< 0.1%
20220095083 1
 
< 0.1%
20220094315 1
 
< 0.1%
20220093901 1
 
< 0.1%
20220093061 1
 
< 0.1%
20210077240 1
 
< 0.1%
20210077187 3
0.1%
20210077022 2
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

소재지(도로명)
Text

MISSING 

Distinct279
Distinct (%)9.1%
Missing2614
Missing (%)46.2%
Memory size44.4 KiB
2024-05-11T16:59:03.572838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length53
Mean length34.911475
Min length23

Characters and Unicode

Total characters106480
Distinct characters235
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

Unique115 ?
Unique (%)3.8%

Sample

1st row서울특별시 강서구 공항대로 555, 지하1~3층 (염창동)
2nd row서울특별시 강서구 공항대로 555, 지하1~3층 (염창동)
3rd row서울특별시 강서구 공항대로 625, (염창동)
4th row서울특별시 강서구 공항대로61길 10-11, (염창동)
5th row서울특별시 강서구 공항대로59다길 276, (염창동)
ValueCountFrequency (%)
서울특별시 3050
 
15.2%
강서구 3050
 
15.2%
양천로 1090
 
5.4%
559 657
 
3.3%
매장동 654
 
3.3%
가양동,가양이마트 654
 
3.3%
1층 635
 
3.2%
지하 542
 
2.7%
2동 475
 
2.4%
공항대로59다길 421
 
2.1%
Other values (511) 8786
43.9%
2024-05-11T16:59:04.004685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16969
 
15.9%
서 6411
 
6.0%
, 5362
 
5.0%
동 4611
 
4.3%
1 3603
 
3.4%
강 3337
 
3.1%
) 3174
 
3.0%
( 3174
 
3.0%
양 3164
 
3.0%
울 3062
 
2.9%
Other values (225) 53613
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63755
59.9%
Space Separator 16969
 
15.9%
Decimal Number 13445
 
12.6%
Other Punctuation 5362
 
5.0%
Close Punctuation 3174
 
3.0%
Open Punctuation 3174
 
3.0%
Math Symbol 218
 
0.2%
Uppercase Letter 218
 
0.2%
Dash Punctuation 164
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 6411
 
10.1%
동 4611
 
7.2%
강 3337
 
5.2%
양 3164
 
5.0%
울 3062
 
4.8%
시 3055
 
4.8%
구 3053
 
4.8%
특 3050
 
4.8%
별 3050
 
4.8%
로 2929
 
4.6%
Other values (197) 28033
44.0%
Uppercase Letter
ValueCountFrequency (%)
C 99
45.4%
N 95
43.6%
S 9
 
4.1%
A 6
 
2.8%
M 2
 
0.9%
E 2
 
0.9%
B 1
 
0.5%
T 1
 
0.5%
U 1
 
0.5%
O 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 3603
26.8%
5 2201
16.4%
9 1519
11.3%
2 1424
 
10.6%
3 1296
 
9.6%
0 892
 
6.6%
4 806
 
6.0%
8 609
 
4.5%
6 582
 
4.3%
7 513
 
3.8%
Space Separator
ValueCountFrequency (%)
16969
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5362
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3174
100.0%
Math Symbol
ValueCountFrequency (%)
~ 218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63755
59.9%
Common 42506
39.9%
Latin 219
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 6411
 
10.1%
동 4611
 
7.2%
강 3337
 
5.2%
양 3164
 
5.0%
울 3062
 
4.8%
시 3055
 
4.8%
구 3053
 
4.8%
특 3050
 
4.8%
별 3050
 
4.8%
로 2929
 
4.6%
Other values (197) 28033
44.0%
Common
ValueCountFrequency (%)
16969
39.9%
, 5362
 
12.6%
1 3603
 
8.5%
) 3174
 
7.5%
( 3174
 
7.5%
5 2201
 
5.2%
9 1519
 
3.6%
2 1424
 
3.4%
3 1296
 
3.0%
0 892
 
2.1%
Other values (6) 2892
 
6.8%
Latin
ValueCountFrequency (%)
C 99
45.2%
N 95
43.4%
S 9
 
4.1%
A 6
 
2.7%
M 2
 
0.9%
E 2
 
0.9%
B 1
 
0.5%
Ⅱ 1
 
0.5%
T 1
 
0.5%
U 1
 
0.5%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63755
59.9%
ASCII 42724
40.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16969
39.7%
, 5362
 
12.6%
1 3603
 
8.4%
) 3174
 
7.4%
( 3174
 
7.4%
5 2201
 
5.2%
9 1519
 
3.6%
2 1424
 
3.3%
3 1296
 
3.0%
0 892
 
2.1%
Other values (17) 3110
 
7.3%
Hangul
ValueCountFrequency (%)
서 6411
 
10.1%
동 4611
 
7.2%
강 3337
 
5.2%
양 3164
 
5.0%
울 3062
 
4.8%
시 3055
 
4.8%
구 3053
 
4.8%
특 3050
 
4.8%
별 3050
 
4.8%
로 2929
 
4.6%
Other values (197) 28033
44.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지(지번)
Text

MISSING 

Distinct499
Distinct (%)9.7%
Missing501
Missing (%)8.8%
Memory size44.4 KiB
2024-05-11T16:59:04.275321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length60
Mean length30.965524
Min length21

Characters and Unicode

Total characters159875
Distinct characters248
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

Unique279 ?
Unique (%)5.4%

Sample

1st row서울특별시 강서구 염창동 275번지 3호 외 3필지 (지하1층~지상3층)
2nd row서울특별시 강서구 염창동 275번지 3호 외 3필지 (지하1층~지상3층)
3rd row서울특별시 강서구 염창동 282번지 24호
4th row서울특별시 강서구 염창동 282번지 24호
5th row서울특별시 강서구 방화동 619번지 7호
ValueCountFrequency (%)
서울특별시 5163
16.1%
강서구 5163
16.1%
가양동 1996
 
6.2%
19호 1325
 
4.1%
449번지 1289
 
4.0%
가양이마트 1089
 
3.4%
매장 1086
 
3.4%
방화동 934
 
2.9%
등촌동 673
 
2.1%
0호 552
 
1.7%
Other values (641) 12799
39.9%
2024-05-11T16:59:04.688940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38130
23.8%
서 10460
 
6.5%
지 6840
 
4.3%
1 5677
 
3.6%
동 5292
 
3.3%
강 5282
 
3.3%
시 5208
 
3.3%
울 5174
 
3.2%
구 5167
 
3.2%
번 5164
 
3.2%
Other values (238) 67481
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92658
58.0%
Space Separator 38130
23.8%
Decimal Number 26142
 
16.4%
Open Punctuation 1133
 
0.7%
Close Punctuation 1133
 
0.7%
Uppercase Letter 235
 
0.1%
Dash Punctuation 185
 
0.1%
Other Punctuation 174
 
0.1%
Math Symbol 82
 
0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 10460
 
11.3%
지 6840
 
7.4%
동 5292
 
5.7%
강 5282
 
5.7%
시 5208
 
5.6%
울 5174
 
5.6%
구 5167
 
5.6%
번 5164
 
5.6%
별 5164
 
5.6%
특 5163
 
5.6%
Other values (207) 33744
36.4%
Uppercase Letter
ValueCountFrequency (%)
C 99
42.1%
N 95
40.4%
D 13
 
5.5%
S 9
 
3.8%
A 7
 
3.0%
B 4
 
1.7%
M 2
 
0.9%
E 2
 
0.9%
O 1
 
0.4%
U 1
 
0.4%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 5677
21.7%
4 4281
16.4%
9 4172
16.0%
2 3365
12.9%
6 2205
 
8.4%
8 1964
 
7.5%
3 1476
 
5.6%
0 1280
 
4.9%
7 1098
 
4.2%
5 624
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 172
98.9%
/ 2
 
1.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%
Space Separator
ValueCountFrequency (%)
38130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Math Symbol
ValueCountFrequency (%)
~ 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92658
58.0%
Common 66979
41.9%
Latin 238
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 10460
 
11.3%
지 6840
 
7.4%
동 5292
 
5.7%
강 5282
 
5.7%
시 5208
 
5.6%
울 5174
 
5.6%
구 5167
 
5.6%
번 5164
 
5.6%
별 5164
 
5.6%
특 5163
 
5.6%
Other values (207) 33744
36.4%
Common
ValueCountFrequency (%)
38130
56.9%
1 5677
 
8.5%
4 4281
 
6.4%
9 4172
 
6.2%
2 3365
 
5.0%
6 2205
 
3.3%
8 1964
 
2.9%
3 1476
 
2.2%
0 1280
 
1.9%
( 1133
 
1.7%
Other values (7) 3296
 
4.9%
Latin
ValueCountFrequency (%)
C 99
41.6%
N 95
39.9%
D 13
 
5.5%
S 9
 
3.8%
A 7
 
2.9%
B 4
 
1.7%
M 2
 
0.8%
E 2
 
0.8%
Ⅰ 2
 
0.8%
O 1
 
0.4%
Other values (4) 4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92658
58.0%
ASCII 67214
42.0%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38130
56.7%
1 5677
 
8.4%
4 4281
 
6.4%
9 4172
 
6.2%
2 3365
 
5.0%
6 2205
 
3.3%
8 1964
 
2.9%
3 1476
 
2.2%
0 1280
 
1.9%
( 1133
 
1.7%
Other values (19) 3531
 
5.3%
Hangul
ValueCountFrequency (%)
서 10460
 
11.3%
지 6840
 
7.4%
동 5292
 
5.7%
강 5282
 
5.7%
시 5208
 
5.6%
울 5174
 
5.6%
구 5167
 
5.6%
번 5164
 
5.6%
별 5164
 
5.6%
특 5163
 
5.6%
Other values (207) 33744
36.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%

업소전화번호
Text

MISSING 

Distinct414
Distinct (%)7.6%
Missing251
Missing (%)4.4%
Memory size44.4 KiB
2024-05-11T16:59:04.976411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.052466
Min length2

Characters and Unicode

Total characters54414
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

Unique228 ?
Unique (%)4.2%

Sample

1st row0236640043
2nd row0236640043
3rd row0236633038
4th row0236633038
5th row0226620674
ValueCountFrequency (%)
02 829
13.3%
0221011234 655
 
10.5%
0221011053 618
 
9.9%
0226608150 420
 
6.7%
0236637763 364
 
5.8%
6696000 324
 
5.2%
0236639400 303
 
4.9%
0221661052 269
 
4.3%
0220632080 242
 
3.9%
0226696000 175
 
2.8%
Other values (412) 2036
32.7%
2024-05-11T16:59:05.375268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13585
25.0%
2 11255
20.7%
6 8570
15.7%
1 5903
10.8%
3 4720
 
8.7%
5 2691
 
4.9%
4 2048
 
3.8%
9 1887
 
3.5%
7 1496
 
2.7%
8 1156
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53311
98.0%
Space Separator 1103
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13585
25.5%
2 11255
21.1%
6 8570
16.1%
1 5903
11.1%
3 4720
 
8.9%
5 2691
 
5.0%
4 2048
 
3.8%
9 1887
 
3.5%
7 1496
 
2.8%
8 1156
 
2.2%
Space Separator
ValueCountFrequency (%)
1103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54414
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13585
25.0%
2 11255
20.7%
6 8570
15.7%
1 5903
10.8%
3 4720
 
8.7%
5 2691
 
4.9%
4 2048
 
3.8%
9 1887
 
3.5%
7 1496
 
2.7%
8 1156
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54414
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13585
25.0%
2 11255
20.7%
6 8570
15.7%
1 5903
10.8%
3 4720
 
8.7%
5 2691
 
4.9%
4 2048
 
3.8%
9 1887
 
3.5%
7 1496
 
2.7%
8 1156
 
2.1%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
수거
2661 
<NA>
1883 
위생점검(전체)
929 
위생점검(부분)
 
191

Length

Max length8
Median length4
Mean length3.8513418
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수거 2661
47.0%
<NA> 1883
33.2%
위생점검(전체) 929
 
16.4%
위생점검(부분) 191
 
3.4%

Length

2024-05-11T16:59:05.506486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:05.602519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 2661
47.0%
na 1883
33.2%
위생점검(전체 929
 
16.4%
위생점검(부분 191
 
3.4%

점검일자
Real number (ℝ)

Distinct265
Distinct (%)4.7%
Missing8
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean20141729
Minimum20090120
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:59:05.720154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090120
5-th percentile20090730
Q120110705
median20130610
Q320170602
95-th percentile20230808
Maximum20240314
Range150194
Interquartile range (IQR)59897

Descriptive statistics

Standard deviation39767.325
Coefficient of variation (CV)0.0019743749
Kurtosis-0.32162969
Mean20141729
Median Absolute Deviation (MAD)29507
Skewness0.71775066
Sum1.1392162 × 1011
Variance1.5814401 × 109
MonotonicityNot monotonic
2024-05-11T16:59:05.868300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150722 302
 
5.3%
20190507 180
 
3.2%
20110125 154
 
2.7%
20120704 107
 
1.9%
20160614 106
 
1.9%
20240119 97
 
1.7%
20180321 97
 
1.7%
20150630 96
 
1.7%
20120911 96
 
1.7%
20100420 93
 
1.6%
Other values (255) 4328
76.4%
ValueCountFrequency (%)
20090120 40
0.7%
20090305 37
0.7%
20090518 14
 
0.2%
20090521 5
 
0.1%
20090604 56
1.0%
20090710 73
1.3%
20090713 10
 
0.2%
20090721 5
 
0.1%
20090730 67
1.2%
20090807 12
 
0.2%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240306 35
 
0.6%
20240227 3
 
0.1%
20240119 97
1.7%
20240117 2
 
< 0.1%
20240116 18
 
0.3%
20231208 36
 
0.6%
20231121 5
 
0.1%
20231114 1
 
< 0.1%
20231024 3
 
0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
기타
2007 
<NA>
1855 
수시
1242 
합동
532 
일제
 
28

Length

Max length4
Median length2
Mean length2.6550141
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2007
35.4%
<NA> 1855
32.8%
수시 1242
21.9%
합동 532
 
9.4%
일제 28
 
0.5%

Length

2024-05-11T16:59:06.005958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:06.124308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2007
35.4%
na 1855
32.8%
수시 1242
21.9%
합동 532
 
9.4%
일제 28
 
0.5%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5664
Missing (%)100.0%
Memory size49.9 KiB

점검결과코드
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
3788 
<NA>
1855 
2
 
21

Length

Max length4
Median length1
Mean length1.9825212
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3788
66.9%
<NA> 1855
32.8%
2 21
 
0.4%

Length

2024-05-11T16:59:06.253021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:06.362023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3788
66.9%
na 1855
32.8%
2 21
 
0.4%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct614
Distinct (%)64.0%
Missing4704
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean20132097
Minimum20090710
Maximum20191028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size49.9 KiB
2024-05-11T16:59:06.480215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090710
5-th percentile20111124
Q120121115
median20130920
Q320140510
95-th percentile20150323
Maximum20191028
Range100318
Interquartile range (IQR)19395.25

Descriptive statistics

Standard deviation11096.157
Coefficient of variation (CV)0.00055116747
Kurtosis0.73657209
Mean20132097
Median Absolute Deviation (MAD)9703
Skewness0.22391238
Sum1.9326813 × 1010
Variance1.231247 × 108
MonotonicityNot monotonic
2024-05-11T16:59:06.635382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111117 8
 
0.1%
20130228 7
 
0.1%
20140515 7
 
0.1%
20120501 6
 
0.1%
20121119 5
 
0.1%
20140513 5
 
0.1%
20140509 5
 
0.1%
20140415 5
 
0.1%
20121019 5
 
0.1%
20111120 5
 
0.1%
Other values (604) 902
 
15.9%
(Missing) 4704
83.1%
ValueCountFrequency (%)
20090710 1
< 0.1%
20100527 1
< 0.1%
20100921 1
< 0.1%
20110629 1
< 0.1%
20110907 1
< 0.1%
20110914 1
< 0.1%
20110922 1
< 0.1%
20110926 1
< 0.1%
20110929 1
< 0.1%
20110930 2
< 0.1%
ValueCountFrequency (%)
20191028 1
< 0.1%
20170217 1
< 0.1%
20161004 1
< 0.1%
20160928 1
< 0.1%
20160907 1
< 0.1%
20160906 1
< 0.1%
20160905 1
< 0.1%
20160815 1
< 0.1%
20160810 1
< 0.1%
20160731 1
< 0.1%

(구)제조회사주소
Text

MISSING 

Distinct455
Distinct (%)45.8%
Missing4670
Missing (%)82.5%
Memory size44.4 KiB
2024-05-11T16:59:06.918790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31
Mean length19.492958
Min length8

Characters and Unicode

Total characters19376
Distinct characters282
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

Unique253 ?
Unique (%)25.5%

Sample

1st row충남 연기군 조치원읍 죽림리 264-7
2nd row등촌동 672-2
3rd row가양동 150-11
4th row가양동 54-5
5th row가양동 130-1
ValueCountFrequency (%)
경기도 268
 
5.8%
충북 135
 
2.9%
서울시 117
 
2.5%
충남 93
 
2.0%
음성군 67
 
1.4%
경남 63
 
1.4%
대소면 56
 
1.2%
전북 50
 
1.1%
용인시 44
 
0.9%
평택시 39
 
0.8%
Other values (1004) 3723
80.0%
2024-05-11T16:59:07.357780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3662
 
18.9%
1 875
 
4.5%
시 753
 
3.9%
- 608
 
3.1%
2 576
 
3.0%
동 523
 
2.7%
구 476
 
2.5%
3 452
 
2.3%
경 397
 
2.0%
기 346
 
1.8%
Other values (272) 10708
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11098
57.3%
Decimal Number 3952
 
20.4%
Space Separator 3662
 
18.9%
Dash Punctuation 608
 
3.1%
Other Punctuation 29
 
0.1%
Lowercase Letter 15
 
0.1%
Uppercase Letter 6
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 753
 
6.8%
동 523
 
4.7%
구 476
 
4.3%
경 397
 
3.6%
기 346
 
3.1%
리 321
 
2.9%
도 311
 
2.8%
면 310
 
2.8%
북 296
 
2.7%
남 293
 
2.6%
Other values (249) 7072
63.7%
Decimal Number
ValueCountFrequency (%)
1 875
22.1%
2 576
14.6%
3 452
11.4%
0 330
 
8.4%
4 330
 
8.4%
5 323
 
8.2%
7 289
 
7.3%
6 280
 
7.1%
8 265
 
6.7%
9 232
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 2
33.3%
T 2
33.3%
L 1
16.7%
I 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
s 7
46.7%
k 7
46.7%
a 1
 
6.7%
Space Separator
ValueCountFrequency (%)
3662
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 608
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11098
57.3%
Common 8257
42.6%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 753
 
6.8%
동 523
 
4.7%
구 476
 
4.3%
경 397
 
3.6%
기 346
 
3.1%
리 321
 
2.9%
도 311
 
2.8%
면 310
 
2.8%
북 296
 
2.7%
남 293
 
2.6%
Other values (249) 7072
63.7%
Common
ValueCountFrequency (%)
3662
44.4%
1 875
 
10.6%
- 608
 
7.4%
2 576
 
7.0%
3 452
 
5.5%
0 330
 
4.0%
4 330
 
4.0%
5 323
 
3.9%
7 289
 
3.5%
6 280
 
3.4%
Other values (6) 532
 
6.4%
Latin
ValueCountFrequency (%)
s 7
33.3%
k 7
33.3%
B 2
 
9.5%
T 2
 
9.5%
L 1
 
4.8%
I 1
 
4.8%
a 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11098
57.3%
ASCII 8278
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3662
44.2%
1 875
 
10.6%
- 608
 
7.3%
2 576
 
7.0%
3 452
 
5.5%
0 330
 
4.0%
4 330
 
4.0%
5 323
 
3.9%
7 289
 
3.5%
6 280
 
3.4%
Other values (13) 553
 
6.7%
Hangul
ValueCountFrequency (%)
시 753
 
6.8%
동 523
 
4.7%
구 476
 
4.3%
경 397
 
3.6%
기 346
 
3.1%
리 321
 
2.9%
도 311
 
2.8%
면 310
 
2.8%
북 296
 
2.7%
남 293
 
2.6%
Other values (249) 7072
63.7%

부적합항목
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing5660
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T16:59:07.504424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.5
Min length3

Characters and Unicode

Total characters26
Distinct characters20
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

Unique4 ?
Unique (%)100.0%

Sample

1st row리스테리아모노사이토제네스
2nd row대장균
3rd row세균수
4th row대장균 부적합
ValueCountFrequency (%)
대장균 2
40.0%
리스테리아모노사이토제네스 1
20.0%
세균수 1
20.0%
부적합 1
20.0%
2024-05-11T16:59:07.758964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
균 3
 
11.5%
리 2
 
7.7%
스 2
 
7.7%
장 2
 
7.7%
대 2
 
7.7%
적 1
 
3.8%
부 1
 
3.8%
1
 
3.8%
수 1
 
3.8%
세 1
 
3.8%
Other values (10) 10
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
96.2%
Space Separator 1
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
균 3
 
12.0%
리 2
 
8.0%
스 2
 
8.0%
장 2
 
8.0%
대 2
 
8.0%
적 1
 
4.0%
부 1
 
4.0%
수 1
 
4.0%
세 1
 
4.0%
네 1
 
4.0%
Other values (9) 9
36.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
96.2%
Common 1
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
균 3
 
12.0%
리 2
 
8.0%
스 2
 
8.0%
장 2
 
8.0%
대 2
 
8.0%
적 1
 
4.0%
부 1
 
4.0%
수 1
 
4.0%
세 1
 
4.0%
네 1
 
4.0%
Other values (9) 9
36.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
96.2%
ASCII 1
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
균 3
 
12.0%
리 2
 
8.0%
스 2
 
8.0%
장 2
 
8.0%
대 2
 
8.0%
적 1
 
4.0%
부 1
 
4.0%
수 1
 
4.0%
세 1
 
4.0%
네 1
 
4.0%
Other values (9) 9
36.0%
ASCII
ValueCountFrequency (%)
1
100.0%

기준치부적합내용
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing5661
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T16:59:07.888043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Characters and Unicode

Total characters7
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 (%)33.3%

Sample

1st row양성
2nd row양성
3rd row230
ValueCountFrequency (%)
양성 2
66.7%
230 1
33.3%
2024-05-11T16:59:08.139039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 2
28.6%
성 2
28.6%
2 1
14.3%
3 1
14.3%
0 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
57.1%
Decimal Number 3
42.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
0 1
33.3%
Other Letter
ValueCountFrequency (%)
양 2
50.0%
성 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
57.1%
Common 3
42.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
0 1
33.3%
Hangul
ValueCountFrequency (%)
양 2
50.0%
성 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
57.1%
ASCII 3
42.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 2
50.0%
성 2
50.0%
ASCII
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
0 1
33.3%

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03150000101일반음식점999<NA>식품접객업소 위생점검 및 지도<NA>116-4-1검사용보성각C01000000<NA>배추김치배추김치(비살균제품)<NA><NA>Qingdad hanaai food co. LTD201504081500g<NA>20150325<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19810076054<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 555, 지하1~3층 (염창동)서울특별시 강서구 염창동 275번지 3호 외 3필지 (지하1층~지상3층)0236640043위생점검(전체)20150408기타<NA>1<NA><NA><NA><NA>
13150000101일반음식점999<NA>식품접객업소 위생점검 및 지도<NA>116-10-7검사용보성각G0400000000000기타사용 중인 튀김용 유지사용중인 튀김용 유지<NA><NA><NA>201610271600ML<NA>20161027<NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19810076054<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 555, 지하1~3층 (염창동)서울특별시 강서구 염창동 275번지 3호 외 3필지 (지하1층~지상3층)0236640043수거20161027기타<NA>1<NA><NA><NA><NA>
23150000101일반음식점<NA><NA><NA><NA>116-8-49<NA>밀향기해물손칼국수<NA><NA>콩국물콩국물<NA><NA>201108231L<NA><NA><NA><NA><NA><NA><NA><NA><NA>1밀향기해물손칼국수국내<NA>120110823201108301<NA><NA><NA><NA><NA><NA>19810076025<NA><NA><NA><NA><NA><NA>서울특별시 강서구 염창동 282번지 24호0236633038위생점검(전체)20110823합동<NA>1<NA><NA><NA><NA>
33150000101일반음식점<NA><NA><NA><NA>116-7-식품14검사용밀향기해물손칼국수G0100000100000조리식품 등조리식품 등콩국물<NA><NA><NA>2016072011LT<NA>20160720<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120160720201607271<NA><NA><NA><NA><NA><NA>19810076025<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 625, (염창동)서울특별시 강서구 염창동 282번지 24호0236633038위생점검(전체)20160720합동<NA>1<NA><NA><NA><NA>
43150000101일반음식점<NA><NA><NA><NA>116-12-3<NA>현대회집<NA><NA><NA>종사자손(황효순)황효순201112023개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<NA>1<NA><NA><NA><NA>
53150000101일반음식점<NA><NA><NA><NA>116-12-4<NA>현대회집<NA><NA><NA>종사자손(김성호)현대회집201112023개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<NA>1<NA><NA><NA><NA>
63150000101일반음식점<NA><NA><NA><NA>116-12-5<NA>현대회집<NA><NA><NA>종사자손(황광호)황효순201112023개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<NA>1<NA><NA><NA><NA>
73150000101일반음식점<NA><NA><NA><NA>116-12-6<NA>현대회집<NA><NA><NA>종사자손(지춘옥)현대회집201112023개<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<NA>1<NA><NA><NA><NA>
83150000101일반음식점<NA><NA><NA><NA>116-12-7<NA>현대회집<NA><NA><NA>정수기물황효순201112021L<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<NA>1<NA><NA><NA><NA>
93150000101일반음식점<NA><NA><NA><NA>116-12-8<NA>현대회집<NA><NA><NA>수족관물황효순201112021L<NA><NA><NA><NA><NA><NA><NA><NA><NA>1현대회집국내<NA>220111202201112151<NA><NA><NA><NA><NA><NA>19840076132<NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 619번지 7호0226620674위생점검(전체)20111202수시<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
56543150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강6검사용(주)지에스리테일H&B 염창역점X0100017800000비타민/무기질비타민/무기질GUMMY BEARS CALCIUM + VITAMIN D3<NA><NA><NA>201708114126g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국외미국120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56553150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강7검사용(주)지에스리테일H&B 염창역점E0202500000000가르시니아캄보지아 추출물가르시니아캄보지아 추출물글램디 이지슬림 레몬맛<NA><NA><NA>201708112300g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56563150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강8검사용(주)지에스리테일H&B 염창역점E0202500000000가르시니아캄보지아 추출물가르시니아캄보지아 추출물없었던일로<NA><NA><NA>20170811368g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56573150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강9검사용(주)지에스리테일H&B 염창역점E0100100000000비타민 A비타민 A츄어블 멀티비타민 밸런스(CHEWABLE MULTI VITAMIN BALANCE)<NA><NA><NA>201708111200g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56583150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강10검사용(주)지에스리테일H&B 염창역점X0100017600000비타민비타민GUMMY VITAMIN C SLICES<NA><NA><NA>201708112203g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국외콜롬비아120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56593150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강11검사용(주)지에스리테일H&B 염창역점E0202500000000가르시니아캄보지아 추출물가르시니아캄보지아 추출물NAKATTAKOTONI<NA><NA><NA>20170811395g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국외일본120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56603150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강12검사용(주)지에스리테일H&B 염창역점X0100017800000비타민/무기질비타민/무기질ENERHEIM ZINC +VITAMIN C<NA><NA><NA>20170811586g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국외독일120170811201709151<NA><NA><NA><NA><NA><NA>20170076821<NA><NA><NA><NA><NA>서울특별시 강서구 공항대로 지하 631, 지하1층 (염창동)서울특별시 강서구 염창동 284번지 84호0236657568위생점검(부분)20170811기타<NA>1<NA><NA><NA><NA>
56613150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강-2검사용뉴트리코어E0100600000000비타민 B1비타민 B1비타민B콤플렉스<NA><NA>(주)다움20190816460g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120190820201910171<NA><NA><NA><NA><NA><NA>20180076282<NA><NA><NA><NA><NA>서울특별시 강서구 양천로 559, 가양이마트 1층 (가양동)서울특별시 강서구 가양동 449번지 19호 가양이마트0262652531위생점검(전체)20190816합동<NA>1<NA><NA><NA><NA>
56623150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강-3검사용뉴트리코어E0100300000000비타민 D비타민 D더맘스<NA><NA>(주)다움20190816390g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120190820201910171<NA><NA><NA><NA><NA><NA>20180076282<NA><NA><NA><NA><NA>서울특별시 강서구 양천로 559, 가양이마트 1층 (가양동)서울특별시 강서구 가양동 449번지 19호 가양이마트0262652531위생점검(전체)20190816합동<NA>1<NA><NA><NA><NA>
56633150000134건강기능식품일반판매업9<NA>건강기능식품판매업소 지도점검<NA>116-건강-4검사용이마트 가양 아모레E0101400000000비타민 C비타민 C프리미엄비타민C1000<NA><NA>(주)에스엘에스201908161216g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120190820201910171<NA><NA><NA><NA><NA><NA>20190076497<NA><NA><NA><NA><NA>서울특별시 강서구 양천로 559, 가양이마트 1층 (가양동)서울특별시 강서구 가양동 449번지 19호 가양이마트0236655957위생점검(전체)20190816합동<NA>1<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용# duplicates
03150000112식품자동판매기영업<NA><NA><NA><NA><NA>(주)휘닉스벤딩서비스210000000다류조제커피커피<NA><NA><NA>200907101<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20050076921<NA>서울특별시 강서구 등촌동 639번지 11호0236622820수거20090710합동1<NA><NA><NA><NA>2
13150000112식품자동판매기영업<NA><NA><NA><NA><NA>그랜드마트<NA><NA>커피<NA><NA><NA>20101103300<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA>20010076791<NA>서울특별시 강서구 등촌동 678번지 14호 (4대)<NA>수거20101103수시1<NA><NA><NA><NA>2
23150000112식품자동판매기영업<NA><NA><NA><NA><NA>주)대한항공교육원210000000다류조제커피커피<NA><NA><NA>200907131<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20030076263<NA>서울특별시 강서구 등촌동 653번지 25호<NA>수거20090713합동1<NA><NA><NA><NA>2
33150000114기타식품판매업<NA><NA><NA>116-9-26검사용(주)이마트 가양점C0308040000000유탕면유탕면일품해물라면<NA><NA><NA>201809045120g<NA><NA><NA><NA><NA>실온<NA>1<NA>국내<NA>120180913201809191<NA>20010076090서울특별시 강서구 양천로 559, 매장동 (가양동,가양이마트)서울특별시 강서구 가양동 449번지 19호 매장 가양이마트0221011053<NA>20180904<NA><NA><NA><NA><NA><NA>2
43150000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계이마트가양점250000000식품별기준및규격외의일반가공식품수산물가공품동원참치살코기<NA><NA><NA>200908076<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20010076090<NA>서울특별시 강서구 가양동 449번지 19호0221011234수거20090807기타1<NA><NA><NA><NA>2
53150000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계이마트가양점250000000식품별기준및규격외의일반가공식품수산물가공품살코기 동원참치<NA><NA><NA>200908076<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20010076090<NA>서울특별시 강서구 가양동 449번지 19호0221011234수거20090807기타1<NA><NA><NA><NA>2
63150000114기타식품판매업<NA><NA><NA><NA><NA>강서농협 하나로마트829000000기타식품류기타전분감자전분<NA><NA><NA>201004201<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980077354<NA>서울특별시 강서구 방화동 829번지 3호 지하1층02 6696000수거20100420기타1<NA><NA><NA><NA>2
73150000114기타식품판매업<NA><NA><NA><NA><NA>강서농협 하나로마트829000000기타식품류기타전분치킨튀김가루<NA><NA><NA>201004201<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980077354<NA>서울특별시 강서구 방화동 829번지 3호 지하1층02 6696000수거20100420기타1<NA><NA><NA><NA>2
83150000114기타식품판매업<NA><NA><NA><NA><NA>강서농협 하나로마트830000000규격외일반가공식품곡류가공품부침가루<NA><NA><NA>201009011<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980077354<NA>서울특별시 강서구 방화동 829번지 3호 지하1층02 6696000수거20100901기타1<NA><NA><NA><NA>2
93150000114기타식품판매업<NA><NA><NA><NA><NA>강서농협 하나로마트830000000규격외일반가공식품곡류가공품튀김가루<NA><NA><NA>201009011<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980077354<NA>서울특별시 강서구 방화동 829번지 3호 지하1층02 6696000수거20100901기타1<NA><NA><NA><NA>2