Overview

Dataset statistics

Number of variables61
Number of observations5421
Missing cells144968
Missing cells (%)43.8%
Duplicate rows19
Duplicate rows (%)0.4%
Total size in memory2.7 MiB
Average record size in memory519.0 B

Variable types

Categorical19
Numeric13
Unsupported13
Text16

Dataset

Description시군구코드,업종코드,업종명,계획구분코드,계획구분명,지도점검계획,수거계획,수거증번호,수거사유코드,업소명,식품군코드,식품군,품목명,제품명,음식물명,원료명,생산업소,수거일자,수거량(정량),제품규격(정량),단위(정량),수거량(자유),제조일자(일자),제조일자(롯트),유통기한(일자),유통기한(제조일기준),보관상태코드,바코드번호,어린이기호식품유형,검사기관명,(구)제조사명,내외국산,국가명,검사구분,검사의뢰일자,결과회보일자,판정구분,처리구분,수거검사구분코드,단속지역구분코드,수거장소구분코드,처리결과,수거품처리,교부번호,폐기일자,폐기량(kg),폐기금액(원),폐기장소,폐기방법,소재지(도로명),소재지(지번),업소전화번호,점검목적,점검일자,점검구분,점검내용,점검결과코드,(구)제조유통기한,(구)제조회사주소,부적합항목,기준치부적합내용
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-10839/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 19 (0.4%) duplicate rowsDuplicates
업종명 is highly imbalanced (58.5%)Imbalance
수거계획 is highly imbalanced (91.4%)Imbalance
어린이기호식품유형 is highly imbalanced (94.1%)Imbalance
검사기관명 is highly imbalanced (70.4%)Imbalance
국가명 is highly imbalanced (91.2%)Imbalance
처리결과 is highly imbalanced (98.0%)Imbalance
폐기금액(원) is highly imbalanced (96.5%)Imbalance
폐기방법 is highly imbalanced (93.6%)Imbalance
점검결과코드 is highly imbalanced (58.4%)Imbalance
계획구분코드 has 2920 (53.9%) missing valuesMissing
계획구분명 has 5421 (100.0%) missing valuesMissing
수거증번호 has 1337 (24.7%) missing valuesMissing
식품군 has 786 (14.5%) missing valuesMissing
품목명 has 405 (7.5%) missing valuesMissing
음식물명 has 5270 (97.2%) missing valuesMissing
원료명 has 5411 (99.8%) missing valuesMissing
생산업소 has 5189 (95.7%) missing valuesMissing
수거량(정량) has 846 (15.6%) missing valuesMissing
제품규격(정량) has 2183 (40.3%) missing valuesMissing
수거량(자유) has 4575 (84.4%) missing valuesMissing
제조일자(일자) has 4104 (75.7%) missing valuesMissing
제조일자(롯트) has 5421 (100.0%) missing valuesMissing
유통기한(일자) has 5389 (99.4%) missing valuesMissing
유통기한(제조일기준) has 5307 (97.9%) missing valuesMissing
바코드번호 has 5421 (100.0%) missing valuesMissing
(구)제조사명 has 4988 (92.0%) missing valuesMissing
검사의뢰일자 has 2830 (52.2%) missing valuesMissing
결과회보일자 has 3828 (70.6%) missing valuesMissing
처리구분 has 5421 (100.0%) missing valuesMissing
수거검사구분코드 has 5421 (100.0%) missing valuesMissing
단속지역구분코드 has 5421 (100.0%) missing valuesMissing
수거장소구분코드 has 5421 (100.0%) missing valuesMissing
수거품처리 has 5421 (100.0%) missing valuesMissing
폐기일자 has 5313 (98.0%) missing valuesMissing
폐기량(kg) has 5401 (99.6%) missing valuesMissing
폐기장소 has 5421 (100.0%) missing valuesMissing
소재지(도로명) has 2597 (47.9%) missing valuesMissing
소재지(지번) has 114 (2.1%) missing valuesMissing
업소전화번호 has 267 (4.9%) missing valuesMissing
점검내용 has 5421 (100.0%) missing valuesMissing
(구)제조유통기한 has 5389 (99.4%) missing valuesMissing
(구)제조회사주소 has 5421 (100.0%) missing valuesMissing
부적합항목 has 5421 (100.0%) missing valuesMissing
기준치부적합내용 has 5421 (100.0%) missing valuesMissing
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제조일자(롯트) is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조회사주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부적합항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 07:59:31.069370
Analysis finished2024-05-11 07:59:33.765775
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
3140000
5421 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 5421
100.0%

Length

2024-05-11T16:59:33.850553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:33.962335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 5421
100.0%

업종코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.96292
Minimum101
Maximum202
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:34.075722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1112
median114
Q3114
95-th percentile114
Maximum202
Range101
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.8322735
Coefficient of variation (CV)0.052091116
Kurtosis23.054243
Mean111.96292
Median Absolute Deviation (MAD)0
Skewness1.4872894
Sum606951
Variance34.015415
MonotonicityNot monotonic
2024-05-11T16:59:34.206643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
114 3803
70.2%
105 544
 
10.0%
101 527
 
9.7%
112 119
 
2.2%
104 102
 
1.9%
107 73
 
1.3%
134 65
 
1.2%
121 65
 
1.2%
106 37
 
0.7%
120 37
 
0.7%
Other values (6) 49
 
0.9%
ValueCountFrequency (%)
101 527
 
9.7%
104 102
 
1.9%
105 544
 
10.0%
106 37
 
0.7%
107 73
 
1.3%
109 2
 
< 0.1%
111 1
 
< 0.1%
112 119
 
2.2%
113 1
 
< 0.1%
114 3803
70.2%
ValueCountFrequency (%)
202 2
 
< 0.1%
135 22
 
0.4%
134 65
 
1.2%
122 21
 
0.4%
121 65
 
1.2%
120 37
 
0.7%
114 3803
70.2%
113 1
 
< 0.1%
112 119
 
2.2%
111 1
 
< 0.1%

업종명
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
기타식품판매업
3803 
집단급식소
544 
일반음식점
527 
식품자동판매기영업
 
119
휴게음식점
 
102
Other values (11)
 
326

Length

Max length13
Median length7
Mean length6.6893562
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 3803
70.2%
집단급식소 544
 
10.0%
일반음식점 527
 
9.7%
식품자동판매기영업 119
 
2.2%
휴게음식점 102
 
1.9%
즉석판매제조가공업 73
 
1.3%
건강기능식품일반판매업 65
 
1.2%
제과점영업 65
 
1.2%
식품제조가공업 37
 
0.7%
위탁급식영업 37
 
0.7%
Other values (6) 49
 
0.9%

Length

2024-05-11T16:59:34.353098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 3803
70.2%
집단급식소 544
 
10.0%
일반음식점 527
 
9.7%
식품자동판매기영업 119
 
2.2%
휴게음식점 102
 
1.9%
즉석판매제조가공업 73
 
1.3%
건강기능식품일반판매업 65
 
1.2%
제과점영업 65
 
1.2%
식품제조가공업 37
 
0.7%
위탁급식영업 37
 
0.7%
Other values (6) 49
 
0.9%

계획구분코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.2%
Missing2920
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean715.79848
Minimum1
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:34.470252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median999
Q3999
95-th percentile999
Maximum999
Range998
Interquartile range (IQR)991

Descriptive statistics

Standard deviation449.00437
Coefficient of variation (CV)0.62727763
Kurtosis-1.0889956
Mean715.79848
Median Absolute Deviation (MAD)0
Skewness-0.95488672
Sum1790212
Variance201604.93
MonotonicityNot monotonic
2024-05-11T16:59:34.591001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
999 1789
33.0%
8 245
 
4.5%
2 230
 
4.2%
1 177
 
3.3%
7 56
 
1.0%
3 4
 
0.1%
(Missing) 2920
53.9%
ValueCountFrequency (%)
1 177
 
3.3%
2 230
 
4.2%
3 4
 
0.1%
7 56
 
1.0%
8 245
 
4.5%
999 1789
33.0%
ValueCountFrequency (%)
999 1789
33.0%
8 245
 
4.5%
7 56
 
1.0%
3 4
 
0.1%
2 230
 
4.2%
1 177
 
3.3%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

지도점검계획
Categorical

Distinct40
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
2920 
식품위생업소 지도점검
546 
식품수거검사 계획
482 
2012년 식품위생업소 민원신고처리계획
 
237
2015년 식품안전팀 지도점검
 
209
Other values (35)
1027 

Length

Max length24
Median length4
Mean length8.8616491
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2920
53.9%
식품위생업소 지도점검 546
 
10.1%
식품수거검사 계획 482
 
8.9%
2012년 식품위생업소 민원신고처리계획 237
 
4.4%
2015년 식품안전팀 지도점검 209
 
3.9%
식중독 신고 업무처리 152
 
2.8%
2019년 식품접객업소 민원처리 105
 
1.9%
2013년 식품접객업소 민원신고처리 계획 95
 
1.8%
2023년도 식품접객업소 지도 점검 92
 
1.7%
음식점 한우 쇠고기 유전자 검사 81
 
1.5%
Other values (30) 502
 
9.3%

Length

2024-05-11T16:59:34.743607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2920
28.5%
지도점검 848
 
8.3%
계획 840
 
8.2%
식품위생업소 787
 
7.7%
식품수거검사 482
 
4.7%
식품접객업소 318
 
3.1%
2012년 241
 
2.4%
민원신고처리계획 237
 
2.3%
2015년 209
 
2.0%
식품안전팀 209
 
2.0%
Other values (57) 3147
30.7%

수거계획
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5277 
2023년 유통(가공)식품 수거검사
 
122
어린이집 급식 식재료 방사능검사
 
12
유전자변형식품 수거검사
 
8
명절 성수식품 안전관리
 
2

Length

Max length19
Median length4
Mean length4.3811105
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> 5277
97.3%
2023년 유통(가공)식품 수거검사 122
 
2.3%
어린이집 급식 식재료 방사능검사 12
 
0.2%
유전자변형식품 수거검사 8
 
0.1%
명절 성수식품 안전관리 2
 
< 0.1%

Length

2024-05-11T16:59:34.916416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:35.040687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5277
92.4%
수거검사 130
 
2.3%
2023년 122
 
2.1%
유통(가공)식품 122
 
2.1%
어린이집 12
 
0.2%
급식 12
 
0.2%
식재료 12
 
0.2%
방사능검사 12
 
0.2%
유전자변형식품 8
 
0.1%
명절 2
 
< 0.1%
Other values (2) 4
 
0.1%

수거증번호
Text

MISSING 

Distinct2239
Distinct (%)54.8%
Missing1337
Missing (%)24.7%
Memory size42.5 KiB
2024-05-11T16:59:35.399747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.3871205
Min length1

Characters and Unicode

Total characters34253
Distinct characters52
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

Unique1388 ?
Unique (%)34.0%

Sample

1st row24-양천-1-집단2
2nd row24-양천-1-집단1
3rd row115-3-6-안전1
4th row24-양천-1-2
5th row24-양천-1-3
ValueCountFrequency (%)
양천 13
 
0.3%
115-11-10 7
 
0.2%
115-11-12 7
 
0.2%
115-11-39 7
 
0.2%
115-11-35 7
 
0.2%
115-11-34 7
 
0.2%
115-11-33 7
 
0.2%
115-11-32 7
 
0.2%
115-11-31 7
 
0.2%
115-11-30 7
 
0.2%
Other values (2230) 4022
98.1%
2024-05-11T16:59:36.142052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11704
34.2%
- 7828
22.9%
5 4771
13.9%
0 1393
 
4.1%
2 1272
 
3.7%
9 1123
 
3.3%
4 1068
 
3.1%
3 1037
 
3.0%
6 935
 
2.7%
7 846
 
2.5%
Other values (42) 2276
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24927
72.8%
Dash Punctuation 7828
 
22.9%
Other Letter 1383
 
4.0%
Uppercase Letter 69
 
0.2%
Lowercase Letter 24
 
0.1%
Space Separator 14
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 420
30.4%
품 420
30.4%
천 172
12.4%
양 172
12.4%
건 23
 
1.7%
강 23
 
1.7%
전 19
 
1.4%
자 18
 
1.3%
안 13
 
0.9%
물 12
 
0.9%
Other values (22) 91
 
6.6%
Decimal Number
ValueCountFrequency (%)
1 11704
47.0%
5 4771
19.1%
0 1393
 
5.6%
2 1272
 
5.1%
9 1123
 
4.5%
4 1068
 
4.3%
3 1037
 
4.2%
6 935
 
3.8%
7 846
 
3.4%
8 778
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
G 23
33.3%
M 23
33.3%
O 23
33.3%
Lowercase Letter
ValueCountFrequency (%)
o 8
33.3%
m 8
33.3%
g 8
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 7828
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32777
95.7%
Hangul 1383
 
4.0%
Latin 93
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 420
30.4%
품 420
30.4%
천 172
12.4%
양 172
12.4%
건 23
 
1.7%
강 23
 
1.7%
전 19
 
1.4%
자 18
 
1.3%
안 13
 
0.9%
물 12
 
0.9%
Other values (22) 91
 
6.6%
Common
ValueCountFrequency (%)
1 11704
35.7%
- 7828
23.9%
5 4771
14.6%
0 1393
 
4.2%
2 1272
 
3.9%
9 1123
 
3.4%
4 1068
 
3.3%
3 1037
 
3.2%
6 935
 
2.9%
7 846
 
2.6%
Other values (4) 800
 
2.4%
Latin
ValueCountFrequency (%)
G 23
24.7%
M 23
24.7%
O 23
24.7%
o 8
 
8.6%
m 8
 
8.6%
g 8
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32870
96.0%
Hangul 1383
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11704
35.6%
- 7828
23.8%
5 4771
14.5%
0 1393
 
4.2%
2 1272
 
3.9%
9 1123
 
3.4%
4 1068
 
3.2%
3 1037
 
3.2%
6 935
 
2.8%
7 846
 
2.6%
Other values (10) 893
 
2.7%
Hangul
ValueCountFrequency (%)
식 420
30.4%
품 420
30.4%
천 172
12.4%
양 172
12.4%
건 23
 
1.7%
강 23
 
1.7%
전 19
 
1.4%
자 18
 
1.3%
안 13
 
0.9%
물 12
 
0.9%
Other values (22) 91
 
6.6%

수거사유코드
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
검사용
3184 
<NA>
2177 
기타
 
54
증거용
 
6

Length

Max length4
Median length3
Mean length3.3916252
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 3184
58.7%
<NA> 2177
40.2%
기타 54
 
1.0%
증거용 6
 
0.1%

Length

2024-05-11T16:59:36.292265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:36.417157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 3184
58.7%
na 2177
40.2%
기타 54
 
1.0%
증거용 6
 
0.1%

업소명
Text

Distinct458
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
2024-05-11T16:59:36.614215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.7956097
Min length2

Characters and Unicode

Total characters53102
Distinct characters433
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)4.6%

Sample

1st row서울강신초등학교
2nd row서울강신초등학교
3rd row산들해반찬
4th row(주)커피빈코리아 오목교역사거리점
5th row디저트39
ValueCountFrequency (%)
목동점 1311
 
16.6%
주)이마트 700
 
8.9%
홈플러스테스코(주)목동점 612
 
7.7%
주)신세계 355
 
4.5%
이마트 354
 
4.5%
주)양천현대홈마트 286
 
3.6%
홈마트 242
 
3.1%
양천구청점 228
 
2.9%
주)지에스리테일gs수퍼 227
 
2.9%
한무쇼핑(주)목동점 162
 
2.1%
Other values (479) 3424
43.3%
2024-05-11T16:59:37.055700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 3106
 
5.8%
( 3083
 
5.8%
) 3083
 
5.8%
점 2836
 
5.3%
동 2643
 
5.0%
목 2601
 
4.9%
마 2563
 
4.8%
트 2535
 
4.8%
2480
 
4.7%
스 1936
 
3.6%
Other values (423) 26236
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43569
82.0%
Open Punctuation 3083
 
5.8%
Close Punctuation 3083
 
5.8%
Space Separator 2480
 
4.7%
Uppercase Letter 690
 
1.3%
Lowercase Letter 126
 
0.2%
Decimal Number 57
 
0.1%
Other Punctuation 9
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3106
 
7.1%
점 2836
 
6.5%
동 2643
 
6.1%
목 2601
 
6.0%
마 2563
 
5.9%
트 2535
 
5.8%
스 1936
 
4.4%
홈 1333
 
3.1%
이 1221
 
2.8%
테 872
 
2.0%
Other values (391) 21923
50.3%
Uppercase Letter
ValueCountFrequency (%)
S 311
45.1%
G 306
44.3%
K 21
 
3.0%
D 19
 
2.8%
C 16
 
2.3%
N 10
 
1.4%
F 3
 
0.4%
J 2
 
0.3%
T 1
 
0.1%
I 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 17
29.8%
1 9
15.8%
3 8
14.0%
4 5
 
8.8%
5 5
 
8.8%
9 4
 
7.0%
8 4
 
7.0%
0 3
 
5.3%
7 2
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
a 36
28.6%
m 18
14.3%
e 18
14.3%
u 18
14.3%
r 18
14.3%
l 18
14.3%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
& 2
 
22.2%
. 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 3083
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3083
100.0%
Space Separator
ValueCountFrequency (%)
2480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43569
82.0%
Common 8717
 
16.4%
Latin 816
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3106
 
7.1%
점 2836
 
6.5%
동 2643
 
6.1%
목 2601
 
6.0%
마 2563
 
5.9%
트 2535
 
5.8%
스 1936
 
4.4%
홈 1333
 
3.1%
이 1221
 
2.8%
테 872
 
2.0%
Other values (391) 21923
50.3%
Common
ValueCountFrequency (%)
( 3083
35.4%
) 3083
35.4%
2480
28.5%
2 17
 
0.2%
1 9
 
0.1%
3 8
 
0.1%
, 6
 
0.1%
4 5
 
0.1%
- 5
 
0.1%
5 5
 
0.1%
Other values (6) 16
 
0.2%
Latin
ValueCountFrequency (%)
S 311
38.1%
G 306
37.5%
a 36
 
4.4%
K 21
 
2.6%
D 19
 
2.3%
m 18
 
2.2%
e 18
 
2.2%
u 18
 
2.2%
r 18
 
2.2%
l 18
 
2.2%
Other values (6) 33
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43569
82.0%
ASCII 9533
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 3106
 
7.1%
점 2836
 
6.5%
동 2643
 
6.1%
목 2601
 
6.0%
마 2563
 
5.9%
트 2535
 
5.8%
스 1936
 
4.4%
홈 1333
 
3.1%
이 1221
 
2.8%
테 872
 
2.0%
Other values (391) 21923
50.3%
ASCII
ValueCountFrequency (%)
( 3083
32.3%
) 3083
32.3%
2480
26.0%
S 311
 
3.3%
G 306
 
3.2%
a 36
 
0.4%
K 21
 
0.2%
D 19
 
0.2%
m 18
 
0.2%
e 18
 
0.2%
Other values (22) 158
 
1.7%

식품군코드
Text

Distinct299
Distinct (%)5.5%
Missing30
Missing (%)0.6%
Memory size42.5 KiB
2024-05-11T16:59:37.290363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.7679466
Min length1

Characters and Unicode

Total characters52659
Distinct characters20
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

Unique99 ?
Unique (%)1.8%

Sample

1st rowG0300000300000
2nd rowG0100000100000
3rd rowC0322020300000
4th rowG0200000200000
5th rowG0200000200000
ValueCountFrequency (%)
801000000 454
 
9.6%
821000000 442
 
9.3%
600000000 301
 
6.3%
829000000 233
 
4.9%
814000000 219
 
4.6%
g0100000100000 209
 
4.4%
816000000 203
 
4.3%
820000000 199
 
4.2%
830000000 156
 
3.3%
818000000 136
 
2.9%
Other values (287) 2193
46.2%
2024-05-11T16:59:37.635239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35272
67.0%
1 4519
 
8.6%
3214
 
6.1%
8 3063
 
5.8%
2 1930
 
3.7%
C 960
 
1.8%
3 937
 
1.8%
6 663
 
1.3%
4 618
 
1.2%
9 359
 
0.7%
Other values (10) 1124
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47906
91.0%
Space Separator 3214
 
6.1%
Uppercase Letter 1539
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35272
73.6%
1 4519
 
9.4%
8 3063
 
6.4%
2 1930
 
4.0%
3 937
 
2.0%
6 663
 
1.4%
4 618
 
1.3%
9 359
 
0.7%
5 354
 
0.7%
7 191
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 960
62.4%
G 293
 
19.0%
E 75
 
4.9%
F 70
 
4.5%
B 68
 
4.4%
H 43
 
2.8%
D 11
 
0.7%
A 10
 
0.6%
X 9
 
0.6%
Space Separator
ValueCountFrequency (%)
3214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51120
97.1%
Latin 1539
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35272
69.0%
1 4519
 
8.8%
3214
 
6.3%
8 3063
 
6.0%
2 1930
 
3.8%
3 937
 
1.8%
6 663
 
1.3%
4 618
 
1.2%
9 359
 
0.7%
5 354
 
0.7%
Latin
ValueCountFrequency (%)
C 960
62.4%
G 293
 
19.0%
E 75
 
4.9%
F 70
 
4.5%
B 68
 
4.4%
H 43
 
2.8%
D 11
 
0.7%
A 10
 
0.6%
X 9
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35272
67.0%
1 4519
 
8.6%
3214
 
6.1%
8 3063
 
5.8%
2 1930
 
3.7%
C 960
 
1.8%
3 937
 
1.8%
6 663
 
1.3%
4 618
 
1.2%
9 359
 
0.7%
Other values (10) 1124
 
2.1%

식품군
Text

MISSING 

Distinct235
Distinct (%)5.1%
Missing786
Missing (%)14.5%
Memory size42.5 KiB
2024-05-11T16:59:37.911753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length33
Mean length4.6168285
Min length1

Characters and Unicode

Total characters21399
Distinct characters301
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)1.6%

Sample

1st row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
2nd row조리식품 등
3rd row즉석조리식품
4th row자가제조얼음
5th row자가제조얼음
ValueCountFrequency (%)
조미식품 473
 
8.9%
과자류 456
 
8.6%
식품접객업 301
 
5.7%
등 254
 
4.8%
기타식품류 243
 
4.6%
다류 220
 
4.1%
식용유지류 219
 
4.1%
조리식품 213
 
4.0%
장류 200
 
3.8%
규격외일반가공식품 160
 
3.0%
Other values (259) 2576
48.5%
2024-05-11T16:59:38.336090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 2507
 
11.7%
식 1846
 
8.6%
품 1822
 
8.5%
조 812
 
3.8%
680
 
3.2%
기 556
 
2.6%
과 539
 
2.5%
자 516
 
2.4%
가 516
 
2.4%
미 512
 
2.4%
Other values (291) 11093
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20391
95.3%
Space Separator 680
 
3.2%
Other Punctuation 132
 
0.6%
Close Punctuation 55
 
0.3%
Open Punctuation 55
 
0.3%
Uppercase Letter 47
 
0.2%
Decimal Number 23
 
0.1%
Lowercase Letter 9
 
< 0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 2507
 
12.3%
식 1846
 
9.1%
품 1822
 
8.9%
조 812
 
4.0%
기 556
 
2.7%
과 539
 
2.6%
자 516
 
2.5%
가 516
 
2.5%
미 512
 
2.5%
공 447
 
2.2%
Other values (260) 10318
50.6%
Uppercase Letter
ValueCountFrequency (%)
C 15
31.9%
D 9
19.1%
L 5
 
10.6%
A 5
 
10.6%
B 5
 
10.6%
P 3
 
6.4%
E 2
 
4.3%
H 2
 
4.3%
J 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
a 2
22.2%
p 1
11.1%
l 1
11.1%
r 1
11.1%
n 1
11.1%
t 1
11.1%
u 1
11.1%
m 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 9
39.1%
2 5
21.7%
3 4
17.4%
6 2
 
8.7%
0 2
 
8.7%
8 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 66
50.0%
. 54
40.9%
/ 10
 
7.6%
? 2
 
1.5%
Space Separator
ValueCountFrequency (%)
680
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20391
95.3%
Common 952
 
4.4%
Latin 56
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 2507
 
12.3%
식 1846
 
9.1%
품 1822
 
8.9%
조 812
 
4.0%
기 556
 
2.7%
과 539
 
2.6%
자 516
 
2.5%
가 516
 
2.5%
미 512
 
2.5%
공 447
 
2.2%
Other values (260) 10318
50.6%
Latin
ValueCountFrequency (%)
C 15
26.8%
D 9
16.1%
L 5
 
8.9%
A 5
 
8.9%
B 5
 
8.9%
P 3
 
5.4%
a 2
 
3.6%
E 2
 
3.6%
H 2
 
3.6%
p 1
 
1.8%
Other values (7) 7
12.5%
Common
ValueCountFrequency (%)
680
71.4%
, 66
 
6.9%
) 55
 
5.8%
( 55
 
5.8%
. 54
 
5.7%
/ 10
 
1.1%
1 9
 
0.9%
- 7
 
0.7%
2 5
 
0.5%
3 4
 
0.4%
Other values (4) 7
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20391
95.3%
ASCII 1008
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 2507
 
12.3%
식 1846
 
9.1%
품 1822
 
8.9%
조 812
 
4.0%
기 556
 
2.7%
과 539
 
2.6%
자 516
 
2.5%
가 516
 
2.5%
미 512
 
2.5%
공 447
 
2.2%
Other values (260) 10318
50.6%
ASCII
ValueCountFrequency (%)
680
67.5%
, 66
 
6.5%
) 55
 
5.5%
( 55
 
5.5%
. 54
 
5.4%
C 15
 
1.5%
/ 10
 
1.0%
1 9
 
0.9%
D 9
 
0.9%
- 7
 
0.7%
Other values (21) 48
 
4.8%

품목명
Text

MISSING 

Distinct315
Distinct (%)6.3%
Missing405
Missing (%)7.5%
Memory size42.5 KiB
2024-05-11T16:59:38.646562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length33
Mean length5.3181818
Min length1

Characters and Unicode

Total characters26676
Distinct characters336
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)1.8%

Sample

1st row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
2nd row조리식품 등
3rd row즉석조리식품
4th row자가제조얼음
5th row자가제조얼음
ValueCountFrequency (%)
등 502
 
7.9%
조리식품 500
 
7.8%
과자(비스킷 201
 
3.1%
카레 192
 
3.0%
접객업소조리식품등 190
 
3.0%
소스류 162
 
2.5%
복합조미식품 144
 
2.3%
과자 138
 
2.2%
소고기 124
 
1.9%
즉석조리식품 113
 
1.8%
Other values (338) 4122
64.5%
2024-05-11T16:59:39.087454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 1446
 
5.4%
1372
 
5.1%
조 1322
 
5.0%
식 1200
 
4.5%
리 872
 
3.3%
류 840
 
3.1%
기 773
 
2.9%
등 692
 
2.6%
가 605
 
2.3%
소 590
 
2.2%
Other values (326) 16964
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23962
89.8%
Space Separator 1372
 
5.1%
Open Punctuation 467
 
1.8%
Close Punctuation 467
 
1.8%
Other Punctuation 292
 
1.1%
Uppercase Letter 62
 
0.2%
Decimal Number 31
 
0.1%
Dash Punctuation 14
 
0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 1446
 
6.0%
조 1322
 
5.5%
식 1200
 
5.0%
리 872
 
3.6%
류 840
 
3.5%
기 773
 
3.2%
등 692
 
2.9%
가 605
 
2.5%
소 590
 
2.5%
과 488
 
2.0%
Other values (293) 15134
63.2%
Uppercase Letter
ValueCountFrequency (%)
C 20
32.3%
D 11
17.7%
A 7
 
11.3%
B 7
 
11.3%
L 6
 
9.7%
P 4
 
6.5%
E 3
 
4.8%
H 3
 
4.8%
J 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
22.2%
n 1
11.1%
l 1
11.1%
p 1
11.1%
t 1
11.1%
r 1
11.1%
u 1
11.1%
m 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 12
38.7%
3 8
25.8%
2 5
16.1%
6 2
 
6.5%
0 2
 
6.5%
5 1
 
3.2%
8 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 141
48.3%
, 136
46.6%
/ 8
 
2.7%
? 6
 
2.1%
' 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 467
100.0%
Close Punctuation
ValueCountFrequency (%)
) 467
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23962
89.8%
Common 2643
 
9.9%
Latin 71
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 1446
 
6.0%
조 1322
 
5.5%
식 1200
 
5.0%
리 872
 
3.6%
류 840
 
3.5%
기 773
 
3.2%
등 692
 
2.9%
가 605
 
2.5%
소 590
 
2.5%
과 488
 
2.0%
Other values (293) 15134
63.2%
Latin
ValueCountFrequency (%)
C 20
28.2%
D 11
15.5%
A 7
 
9.9%
B 7
 
9.9%
L 6
 
8.5%
P 4
 
5.6%
E 3
 
4.2%
H 3
 
4.2%
a 2
 
2.8%
n 1
 
1.4%
Other values (7) 7
 
9.9%
Common
ValueCountFrequency (%)
1372
51.9%
( 467
 
17.7%
) 467
 
17.7%
. 141
 
5.3%
, 136
 
5.1%
- 14
 
0.5%
1 12
 
0.5%
/ 8
 
0.3%
3 8
 
0.3%
? 6
 
0.2%
Other values (6) 12
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23962
89.8%
ASCII 2714
 
10.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 1446
 
6.0%
조 1322
 
5.5%
식 1200
 
5.0%
리 872
 
3.6%
류 840
 
3.5%
기 773
 
3.2%
등 692
 
2.9%
가 605
 
2.5%
소 590
 
2.5%
과 488
 
2.0%
Other values (293) 15134
63.2%
ASCII
ValueCountFrequency (%)
1372
50.6%
( 467
 
17.2%
) 467
 
17.2%
. 141
 
5.2%
, 136
 
5.0%
C 20
 
0.7%
- 14
 
0.5%
1 12
 
0.4%
D 11
 
0.4%
/ 8
 
0.3%
Other values (23) 66
 
2.4%

제품명
Text

Distinct4097
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
2024-05-11T16:59:39.415121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length38
Mean length6.9878251
Min length1

Characters and Unicode

Total characters37881
Distinct characters867
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

Unique3491 ?
Unique (%)64.4%

Sample

1st row도마 swab
2nd row햄모듬찌개
3rd row한돈 고추장찌개
4th row식용얼음
5th row식용얼음
ValueCountFrequency (%)
커피 53
 
0.8%
등심 42
 
0.6%
음용수 41
 
0.6%
김치 39
 
0.6%
청정원 38
 
0.5%
밥 32
 
0.5%
이마트 29
 
0.4%
오뚜기 27
 
0.4%
행주 27
 
0.4%
수족관물 23
 
0.3%
Other values (4484) 6692
95.0%
2024-05-11T16:59:39.982534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1623
 
4.3%
스 939
 
2.5%
이 724
 
1.9%
리 645
 
1.7%
기 586
 
1.5%
치 467
 
1.2%
오 432
 
1.1%
마 429
 
1.1%
수 418
 
1.1%
맛 406
 
1.1%
Other values (857) 31212
82.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33940
89.6%
Space Separator 1623
 
4.3%
Decimal Number 906
 
2.4%
Uppercase Letter 450
 
1.2%
Close Punctuation 259
 
0.7%
Open Punctuation 257
 
0.7%
Lowercase Letter 216
 
0.6%
Other Punctuation 185
 
0.5%
Dash Punctuation 37
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 939
 
2.8%
이 724
 
2.1%
리 645
 
1.9%
기 586
 
1.7%
치 467
 
1.4%
오 432
 
1.3%
마 429
 
1.3%
수 418
 
1.2%
맛 406
 
1.2%
고 405
 
1.2%
Other values (780) 28489
83.9%
Uppercase Letter
ValueCountFrequency (%)
A 55
 
12.2%
I 35
 
7.8%
C 33
 
7.3%
N 33
 
7.3%
D 30
 
6.7%
T 27
 
6.0%
M 26
 
5.8%
E 24
 
5.3%
S 20
 
4.4%
L 18
 
4.0%
Other values (15) 149
33.1%
Lowercase Letter
ValueCountFrequency (%)
a 29
13.4%
m 28
13.0%
p 24
11.1%
s 22
10.2%
e 20
9.3%
u 13
 
6.0%
l 12
 
5.6%
o 10
 
4.6%
w 9
 
4.2%
r 8
 
3.7%
Other values (12) 41
19.0%
Other Punctuation
ValueCountFrequency (%)
/ 64
34.6%
, 36
19.5%
. 20
 
10.8%
& 19
 
10.3%
% 16
 
8.6%
; 14
 
7.6%
？ 7
 
3.8%
@ 2
 
1.1%
! 2
 
1.1%
* 2
 
1.1%
Other values (3) 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 271
29.9%
0 152
16.8%
3 125
13.8%
2 99
 
10.9%
5 54
 
6.0%
9 47
 
5.2%
7 45
 
5.0%
6 45
 
5.0%
4 36
 
4.0%
8 32
 
3.5%
Math Symbol
ValueCountFrequency (%)
+ 6
85.7%
＋ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1623
100.0%
Close Punctuation
ValueCountFrequency (%)
) 259
100.0%
Open Punctuation
ValueCountFrequency (%)
( 257
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33937
89.6%
Common 3275
 
8.6%
Latin 666
 
1.8%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 939
 
2.8%
이 724
 
2.1%
리 645
 
1.9%
기 586
 
1.7%
치 467
 
1.4%
오 432
 
1.3%
마 429
 
1.3%
수 418
 
1.2%
맛 406
 
1.2%
고 405
 
1.2%
Other values (778) 28486
83.9%
Latin
ValueCountFrequency (%)
A 55
 
8.3%
I 35
 
5.3%
C 33
 
5.0%
N 33
 
5.0%
D 30
 
4.5%
a 29
 
4.4%
m 28
 
4.2%
T 27
 
4.1%
M 26
 
3.9%
E 24
 
3.6%
Other values (37) 346
52.0%
Common
ValueCountFrequency (%)
1623
49.6%
1 271
 
8.3%
) 259
 
7.9%
( 257
 
7.8%
0 152
 
4.6%
3 125
 
3.8%
2 99
 
3.0%
/ 64
 
2.0%
5 54
 
1.6%
9 47
 
1.4%
Other values (20) 324
 
9.9%
Han
ValueCountFrequency (%)
生 2
66.7%
大 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33935
89.6%
ASCII 3932
 
10.4%
None 9
 
< 0.1%
CJK 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1623
41.3%
1 271
 
6.9%
) 259
 
6.6%
( 257
 
6.5%
0 152
 
3.9%
3 125
 
3.2%
2 99
 
2.5%
/ 64
 
1.6%
A 55
 
1.4%
5 54
 
1.4%
Other values (64) 973
24.7%
Hangul
ValueCountFrequency (%)
스 939
 
2.8%
이 724
 
2.1%
리 645
 
1.9%
기 586
 
1.7%
치 467
 
1.4%
오 432
 
1.3%
마 429
 
1.3%
수 418
 
1.2%
맛 406
 
1.2%
고 405
 
1.2%
Other values (776) 28484
83.9%
None
ValueCountFrequency (%)
？ 7
77.8%
＆ 1
 
11.1%
＋ 1
 
11.1%
CJK
ValueCountFrequency (%)
生 2
66.7%
大 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
50.0%
ㄴ 1
50.0%

음식물명
Text

MISSING 

Distinct109
Distinct (%)72.2%
Missing5270
Missing (%)97.2%
Memory size42.5 KiB
2024-05-11T16:59:40.322867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length4.3774834
Min length1

Characters and Unicode

Total characters661
Distinct characters173
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)60.9%

Sample

1st row양파
2nd row양상추
3rd row찐빵
4th row김치만두
5th row고기만두
ValueCountFrequency (%)
커피 9
 
5.6%
자판기 8
 
4.9%
김치 6
 
3.7%
우유 5
 
3.1%
수족관물 4
 
2.5%
쿠키 4
 
2.5%
케？ 4
 
2.5%
행주 4
 
2.5%
율무차 3
 
1.9%
도마 3
 
1.9%
Other values (98) 112
69.1%
2024-05-11T16:59:40.870601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
치 21
 
3.2%
물 20
 
3.0%
( 16
 
2.4%
기 16
 
2.4%
) 16
 
2.4%
마 15
 
2.3%
수 15
 
2.3%
무 14
 
2.1%
검 13
 
2.0%
체 13
 
2.0%
Other values (163) 502
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 599
90.6%
Open Punctuation 16
 
2.4%
Close Punctuation 16
 
2.4%
Other Punctuation 12
 
1.8%
Space Separator 11
 
1.7%
Decimal Number 5
 
0.8%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 21
 
3.5%
물 20
 
3.3%
기 16
 
2.7%
마 15
 
2.5%
수 15
 
2.5%
무 14
 
2.3%
검 13
 
2.2%
체 13
 
2.2%
김 13
 
2.2%
자 12
 
2.0%
Other values (153) 447
74.6%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
3 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 8
66.7%
？ 4
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 599
90.6%
Common 60
 
9.1%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 21
 
3.5%
물 20
 
3.3%
기 16
 
2.7%
마 15
 
2.5%
수 15
 
2.5%
무 14
 
2.3%
검 13
 
2.2%
체 13
 
2.2%
김 13
 
2.2%
자 12
 
2.0%
Other values (153) 447
74.6%
Common
ValueCountFrequency (%)
( 16
26.7%
) 16
26.7%
11
18.3%
, 8
13.3%
？ 4
 
6.7%
1 2
 
3.3%
2 2
 
3.3%
3 1
 
1.7%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 599
90.6%
ASCII 58
 
8.8%
None 4
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
치 21
 
3.5%
물 20
 
3.3%
기 16
 
2.7%
마 15
 
2.5%
수 15
 
2.5%
무 14
 
2.3%
검 13
 
2.2%
체 13
 
2.2%
김 13
 
2.2%
자 12
 
2.0%
Other values (153) 447
74.6%
ASCII
ValueCountFrequency (%)
( 16
27.6%
) 16
27.6%
11
19.0%
, 8
13.8%
1 2
 
3.4%
2 2
 
3.4%
3 1
 
1.7%
B 1
 
1.7%
A 1
 
1.7%
None
ValueCountFrequency (%)
？ 4
100.0%

원료명
Text

MISSING 

Distinct6
Distinct (%)60.0%
Missing5411
Missing (%)99.8%
Memory size42.5 KiB
2024-05-11T16:59:41.053739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length5
Min length2

Characters and Unicode

Total characters50
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st row두부
2nd row빨간양파
3rd row수산물 패류(우렁)
4th row먹는해양심층수
5th row먹는샘물
ValueCountFrequency (%)
먹는샘물 4
36.4%
먹는해양심층수 2
18.2%
두부 1
 
9.1%
빨간양파 1
 
9.1%
수산물 1
 
9.1%
패류(우렁 1
 
9.1%
한우우둔 1
 
9.1%
2024-05-11T16:59:41.354634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
먹 6
12.0%
는 6
12.0%
물 5
 
10.0%
샘 4
 
8.0%
양 3
 
6.0%
수 3
 
6.0%
우 3
 
6.0%
해 2
 
4.0%
심 2
 
4.0%
층 2
 
4.0%
Other values (14) 14
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47
94.0%
Close Punctuation 1
 
2.0%
Open Punctuation 1
 
2.0%
Space Separator 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
먹 6
12.8%
는 6
12.8%
물 5
10.6%
샘 4
 
8.5%
양 3
 
6.4%
수 3
 
6.4%
우 3
 
6.4%
해 2
 
4.3%
심 2
 
4.3%
층 2
 
4.3%
Other values (11) 11
23.4%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47
94.0%
Common 3
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
먹 6
12.8%
는 6
12.8%
물 5
10.6%
샘 4
 
8.5%
양 3
 
6.4%
수 3
 
6.4%
우 3
 
6.4%
해 2
 
4.3%
심 2
 
4.3%
층 2
 
4.3%
Other values (11) 11
23.4%
Common
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47
94.0%
ASCII 3
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
먹 6
12.8%
는 6
12.8%
물 5
10.6%
샘 4
 
8.5%
양 3
 
6.4%
수 3
 
6.4%
우 3
 
6.4%
해 2
 
4.3%
심 2
 
4.3%
층 2
 
4.3%
Other values (11) 11
23.4%
ASCII
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

생산업소
Text

MISSING 

Distinct102
Distinct (%)44.0%
Missing5189
Missing (%)95.7%
Memory size42.5 KiB
2024-05-11T16:59:41.608981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length18.060345
Min length3

Characters and Unicode

Total characters4190
Distinct characters259
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)30.2%

Sample

1st row양천구 목동동로12길 22
2nd row(주)케이피코리아
3rd row(주)쌍용씨앤비
4th row(주)쌍용씨앤비
5th row양천경찰서(목동동로 99, 서울양천경찰서 지하1층(신정동))
ValueCountFrequency (%)
양천경찰서(목동동로 50
 
9.3%
서울양천경찰서 50
 
9.3%
지하1층(신정동 50
 
9.3%
99 50
 
9.3%
서울서정초등학교(목동로8길 39
 
7.3%
19(목동 39
 
7.3%
롯데제과(주 6
 
1.1%
양천구 6
 
1.1%
롯데칠성음료(주 4
 
0.7%
조치원읍 4
 
0.7%
Other values (172) 238
44.4%
2024-05-11T16:59:42.116615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
 
7.3%
) 253
 
6.0%
( 253
 
6.0%
동 246
 
5.9%
서 240
 
5.7%
9 143
 
3.4%
목 138
 
3.3%
천 114
 
2.7%
양 111
 
2.6%
1 109
 
2.6%
Other values (249) 2279
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2588
61.8%
Decimal Number 352
 
8.4%
Space Separator 304
 
7.3%
Close Punctuation 253
 
6.0%
Open Punctuation 253
 
6.0%
Lowercase Letter 234
 
5.6%
Uppercase Letter 118
 
2.8%
Other Punctuation 86
 
2.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 246
 
9.5%
서 240
 
9.3%
목 138
 
5.3%
천 114
 
4.4%
양 111
 
4.3%
경 106
 
4.1%
로 104
 
4.0%
찰 100
 
3.9%
정 99
 
3.8%
울 95
 
3.7%
Other values (191) 1235
47.7%
Uppercase Letter
ValueCountFrequency (%)
A 15
12.7%
S 14
11.9%
F 11
9.3%
P 10
8.5%
E 9
 
7.6%
R 9
 
7.6%
C 8
 
6.8%
T 8
 
6.8%
L 6
 
5.1%
I 5
 
4.2%
Other values (10) 23
19.5%
Lowercase Letter
ValueCountFrequency (%)
a 30
12.8%
o 29
12.4%
n 20
 
8.5%
i 20
 
8.5%
r 18
 
7.7%
e 15
 
6.4%
s 14
 
6.0%
d 12
 
5.1%
c 12
 
5.1%
p 11
 
4.7%
Other values (9) 53
22.6%
Decimal Number
ValueCountFrequency (%)
9 143
40.6%
1 109
31.0%
8 44
 
12.5%
2 21
 
6.0%
3 11
 
3.1%
7 9
 
2.6%
5 4
 
1.1%
0 4
 
1.1%
6 4
 
1.1%
4 3
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 58
67.4%
/ 11
 
12.8%
. 8
 
9.3%
& 5
 
5.8%
; 4
 
4.7%
Space Separator
ValueCountFrequency (%)
304
100.0%
Close Punctuation
ValueCountFrequency (%)
) 253
100.0%
Open Punctuation
ValueCountFrequency (%)
( 253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2588
61.8%
Common 1250
29.8%
Latin 352
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 246
 
9.5%
서 240
 
9.3%
목 138
 
5.3%
천 114
 
4.4%
양 111
 
4.3%
경 106
 
4.1%
로 104
 
4.0%
찰 100
 
3.9%
정 99
 
3.8%
울 95
 
3.7%
Other values (191) 1235
47.7%
Latin
ValueCountFrequency (%)
a 30
 
8.5%
o 29
 
8.2%
n 20
 
5.7%
i 20
 
5.7%
r 18
 
5.1%
e 15
 
4.3%
A 15
 
4.3%
s 14
 
4.0%
S 14
 
4.0%
d 12
 
3.4%
Other values (29) 165
46.9%
Common
ValueCountFrequency (%)
304
24.3%
) 253
20.2%
( 253
20.2%
9 143
11.4%
1 109
 
8.7%
, 58
 
4.6%
8 44
 
3.5%
2 21
 
1.7%
3 11
 
0.9%
/ 11
 
0.9%
Other values (9) 43
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2588
61.8%
ASCII 1602
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304
19.0%
) 253
15.8%
( 253
15.8%
9 143
 
8.9%
1 109
 
6.8%
, 58
 
3.6%
8 44
 
2.7%
a 30
 
1.9%
o 29
 
1.8%
2 21
 
1.3%
Other values (48) 358
22.3%
Hangul
ValueCountFrequency (%)
동 246
 
9.5%
서 240
 
9.3%
목 138
 
5.3%
천 114
 
4.4%
양 111
 
4.3%
경 106
 
4.1%
로 104
 
4.0%
찰 100
 
3.9%
정 99
 
3.8%
울 95
 
3.7%
Other values (191) 1235
47.7%

수거일자
Real number (ℝ)

Distinct290
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20134283
Minimum20010921
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:42.306713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010921
5-th percentile20090724
Q120110114
median20121031
Q320160513
95-th percentile20220825
Maximum20240314
Range229393
Interquartile range (IQR)50399

Descriptive statistics

Standard deviation38191.893
Coefficient of variation (CV)0.0018968589
Kurtosis0.21038971
Mean20134283
Median Absolute Deviation (MAD)20506
Skewness0.93393745
Sum1.0914795 × 1011
Variance1.4586207 × 109
MonotonicityDecreasing
2024-05-11T16:59:42.477217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111124 216
 
4.0%
20120906 187
 
3.4%
20121023 149
 
2.7%
20100621 147
 
2.7%
20111007 138
 
2.5%
20100511 134
 
2.5%
20121230 131
 
2.4%
20151006 114
 
2.1%
20120508 105
 
1.9%
20090731 105
 
1.9%
Other values (280) 3995
73.7%
ValueCountFrequency (%)
20010921 3
 
0.1%
20040116 1
 
< 0.1%
20050824 1
 
< 0.1%
20051102 2
 
< 0.1%
20051103 1
 
< 0.1%
20051109 2
 
< 0.1%
20060111 2
 
< 0.1%
20060118 5
 
0.1%
20060614 7
 
0.1%
20090115 50
0.9%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240306 1
 
< 0.1%
20240305 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20231121 5
 
0.1%
20231115 37
0.7%
20231111 50
0.9%
20231024 2
 
< 0.1%
20231019 42
0.8%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)0.8%
Missing846
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean26.900798
Minimum0.05
Maximum2628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:42.636632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile1
Q11
median3
Q34
95-th percentile26
Maximum2628
Range2627.95
Interquartile range (IQR)3

Descriptive statistics

Standard deviation137.86149
Coefficient of variation (CV)5.1248106
Kurtosis77.466442
Mean26.900798
Median Absolute Deviation (MAD)1
Skewness7.8180531
Sum123071.15
Variance19005.792
MonotonicityNot monotonic
2024-05-11T16:59:42.799730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1.0 1482
27.3%
3.0 1138
21.0%
2.0 673
12.4%
4.0 516
 
9.5%
6.0 292
 
5.4%
5.0 134
 
2.5%
200.0 72
 
1.3%
1000.0 61
 
1.1%
8.0 37
 
0.7%
300.0 36
 
0.7%
Other values (25) 134
 
2.5%
(Missing) 846
15.6%
ValueCountFrequency (%)
0.05 3
 
0.1%
1.0 1482
27.3%
2.0 673
12.4%
3.0 1138
21.0%
4.0 516
 
9.5%
5.0 134
 
2.5%
6.0 292
 
5.4%
7.0 9
 
0.2%
8.0 37
 
0.7%
9.0 15
 
0.3%
ValueCountFrequency (%)
2628.0 1
 
< 0.1%
2000.0 2
 
< 0.1%
1000.0 61
1.1%
600.0 8
 
0.1%
500.0 16
 
0.3%
350.0 3
 
0.1%
300.0 36
0.7%
250.0 11
 
0.2%
200.0 72
1.3%
180.0 1
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct404
Distinct (%)12.5%
Missing2183
Missing (%)40.3%
Memory size42.5 KiB
2024-05-11T16:59:43.149583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.0543545
Min length1

Characters and Unicode

Total characters9890
Distinct characters30
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

Unique194 ?
Unique (%)6.0%

Sample

1st row600
2nd row400
3rd row600
4th row600
5th row600
ValueCountFrequency (%)
100 483
 
14.9%
200 232
 
7.2%
500 178
 
5.5%
600 165
 
5.1%
1 143
 
4.4%
300 141
 
4.4%
g 86
 
2.7%
250 65
 
2.0%
400 55
 
1.7%
150 49
 
1.5%
Other values (392) 1641
50.7%
2024-05-11T16:59:43.735190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4207
42.5%
1 1253
 
12.7%
2 811
 
8.2%
5 750
 
7.6%
g 596
 
6.0%
3 491
 
5.0%
6 362
 
3.7%
4 319
 
3.2%
8 209
 
2.1%
7 203
 
2.1%
Other values (20) 689
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8797
88.9%
Lowercase Letter 970
 
9.8%
Other Letter 58
 
0.6%
Other Punctuation 52
 
0.5%
Uppercase Letter 13
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4207
47.8%
1 1253
 
14.2%
2 811
 
9.2%
5 750
 
8.5%
3 491
 
5.6%
6 362
 
4.1%
4 319
 
3.6%
8 209
 
2.4%
7 203
 
2.3%
9 192
 
2.2%
Other Letter
ValueCountFrequency (%)
개 32
55.2%
매 10
 
17.2%
미 2
 
3.4%
터 2
 
3.4%
장 2
 
3.4%
입 2
 
3.4%
면 2
 
3.4%
봉 2
 
3.4%
마 2
 
3.4%
리 2
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
g 596
61.4%
m 188
 
19.4%
l 181
 
18.7%
c 4
 
0.4%
k 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 49
94.2%
* 2
 
3.8%
, 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
L 9
69.2%
M 4
30.8%

Most occurring scripts

ValueCountFrequency (%)
Common 8849
89.5%
Latin 983
 
9.9%
Hangul 58
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4207
47.5%
1 1253
 
14.2%
2 811
 
9.2%
5 750
 
8.5%
3 491
 
5.5%
6 362
 
4.1%
4 319
 
3.6%
8 209
 
2.4%
7 203
 
2.3%
9 192
 
2.2%
Other values (3) 52
 
0.6%
Hangul
ValueCountFrequency (%)
개 32
55.2%
매 10
 
17.2%
미 2
 
3.4%
터 2
 
3.4%
장 2
 
3.4%
입 2
 
3.4%
면 2
 
3.4%
봉 2
 
3.4%
마 2
 
3.4%
리 2
 
3.4%
Latin
ValueCountFrequency (%)
g 596
60.6%
m 188
 
19.1%
l 181
 
18.4%
L 9
 
0.9%
M 4
 
0.4%
c 4
 
0.4%
k 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9832
99.4%
Hangul 58
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4207
42.8%
1 1253
 
12.7%
2 811
 
8.2%
5 750
 
7.6%
g 596
 
6.1%
3 491
 
5.0%
6 362
 
3.7%
4 319
 
3.2%
8 209
 
2.1%
7 203
 
2.1%
Other values (10) 631
 
6.4%
Hangul
ValueCountFrequency (%)
개 32
55.2%
매 10
 
17.2%
미 2
 
3.4%
터 2
 
3.4%
장 2
 
3.4%
입 2
 
3.4%
면 2
 
3.4%
봉 2
 
3.4%
마 2
 
3.4%
리 2
 
3.4%

단위(정량)
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
3022 
g
1891 
ML
335 
KG
 
112
LT
 
61

Length

Max length4
Median length4
Mean length2.7660948
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3022
55.7%
g 1891
34.9%
ML 335
 
6.2%
KG 112
 
2.1%
LT 61
 
1.1%

Length

2024-05-11T16:59:43.884828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:44.020878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3022
55.7%
g 1891
34.9%
ml 335
 
6.2%
kg 112
 
2.1%
lt 61
 
1.1%

수거량(자유)
Text

MISSING 

Distinct237
Distinct (%)28.0%
Missing4575
Missing (%)84.4%
Memory size42.5 KiB
2024-05-11T16:59:44.250482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length3.6973995
Min length1

Characters and Unicode

Total characters3128
Distinct characters55
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)17.4%

Sample

1st rowswab*2
2nd row150ml*3개
3rd row200매*4입
4th row30롤
5th row개별 6개
ValueCountFrequency (%)
1 156
 
16.9%
3개 44
 
4.8%
1개 44
 
4.8%
1000 31
 
3.4%
300*2 28
 
3.0%
500*2 23
 
2.5%
900*1 22
 
2.4%
400*2 21
 
2.3%
500 16
 
1.7%
15
 
1.6%
Other values (236) 523
56.7%
2024-05-11T16:59:44.681487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 789
25.2%
1 438
14.0%
* 357
11.4%
2 314
 
10.0%
3 235
 
7.5%
5 182
 
5.8%
4 129
 
4.1%
개 128
 
4.1%
78
 
2.5%
7 66
 
2.1%
Other values (45) 412
13.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2334
74.6%
Other Punctuation 358
 
11.4%
Other Letter 272
 
8.7%
Space Separator 78
 
2.5%
Lowercase Letter 68
 
2.2%
Uppercase Letter 11
 
0.4%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 128
47.1%
입 17
 
6.2%
롤 16
 
5.9%
보 12
 
4.4%
존 12
 
4.4%
식 12
 
4.4%
매 10
 
3.7%
건 8
 
2.9%
스 6
 
2.2%
왑 6
 
2.2%
Other values (17) 45
 
16.5%
Decimal Number
ValueCountFrequency (%)
0 789
33.8%
1 438
18.8%
2 314
 
13.5%
3 235
 
10.1%
5 182
 
7.8%
4 129
 
5.5%
7 66
 
2.8%
8 64
 
2.7%
6 62
 
2.7%
9 55
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
g 52
76.5%
m 3
 
4.4%
w 2
 
2.9%
a 2
 
2.9%
b 2
 
2.9%
l 2
 
2.9%
s 2
 
2.9%
o 1
 
1.5%
r 1
 
1.5%
c 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
* 357
99.7%
, 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
X 9
81.8%
L 2
 
18.2%
Space Separator
ValueCountFrequency (%)
78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2777
88.8%
Hangul 272
 
8.7%
Latin 79
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 128
47.1%
입 17
 
6.2%
롤 16
 
5.9%
보 12
 
4.4%
존 12
 
4.4%
식 12
 
4.4%
매 10
 
3.7%
건 8
 
2.9%
스 6
 
2.2%
왑 6
 
2.2%
Other values (17) 45
 
16.5%
Common
ValueCountFrequency (%)
0 789
28.4%
1 438
15.8%
* 357
12.9%
2 314
 
11.3%
3 235
 
8.5%
5 182
 
6.6%
4 129
 
4.6%
78
 
2.8%
7 66
 
2.4%
8 64
 
2.3%
Other values (6) 125
 
4.5%
Latin
ValueCountFrequency (%)
g 52
65.8%
X 9
 
11.4%
m 3
 
3.8%
w 2
 
2.5%
a 2
 
2.5%
b 2
 
2.5%
L 2
 
2.5%
l 2
 
2.5%
s 2
 
2.5%
o 1
 
1.3%
Other values (2) 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2856
91.3%
Hangul 272
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 789
27.6%
1 438
15.3%
* 357
12.5%
2 314
 
11.0%
3 235
 
8.2%
5 182
 
6.4%
4 129
 
4.5%
78
 
2.7%
7 66
 
2.3%
8 64
 
2.2%
Other values (18) 204
 
7.1%
Hangul
ValueCountFrequency (%)
개 128
47.1%
입 17
 
6.2%
롤 16
 
5.9%
보 12
 
4.4%
존 12
 
4.4%
식 12
 
4.4%
매 10
 
3.7%
건 8
 
2.9%
스 6
 
2.2%
왑 6
 
2.2%
Other values (17) 45
 
16.5%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct303
Distinct (%)23.0%
Missing4104
Missing (%)75.7%
Infinite0
Infinite (%)0.0%
Mean20166294
Minimum20100122
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:44.863692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100122
5-th percentile20121004
Q120130415
median20170915
Q320190614
95-th percentile20231019
Maximum20240314
Range140192
Interquartile range (IQR)60199

Descriptive statistics

Standard deviation35774.889
Coefficient of variation (CV)0.0017739942
Kurtosis-1.0674269
Mean20166294
Median Absolute Deviation (MAD)30100
Skewness0.15970354
Sum2.6559009 × 1010
Variance1.2798427 × 109
MonotonicityNot monotonic
2024-05-11T16:59:45.049398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121230 130
 
2.4%
20121123 75
 
1.4%
20160516 28
 
0.5%
20181209 26
 
0.5%
20180920 21
 
0.4%
20130717 19
 
0.4%
20130610 18
 
0.3%
20171016 18
 
0.3%
20130712 17
 
0.3%
20161202 17
 
0.3%
Other values (293) 948
 
17.5%
(Missing) 4104
75.7%
ValueCountFrequency (%)
20100122 1
 
< 0.1%
20110117 1
 
< 0.1%
20110520 1
 
< 0.1%
20111130 1
 
< 0.1%
20120107 1
 
< 0.1%
20120208 5
0.1%
20120220 2
 
< 0.1%
20120222 8
0.1%
20120327 1
 
< 0.1%
20120329 5
0.1%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240305 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20231113 1
 
< 0.1%
20231111 4
 
0.1%
20231110 11
0.2%
20231109 15
0.3%
20231108 5
 
0.1%
20231107 9
0.2%

제조일자(롯트)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)96.9%
Missing5389
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20124773
Minimum20101011
Maximum20140731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:45.229408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20101011
5-th percentile20110427
Q120120792
median20121117
Q320130617
95-th percentile20140668
Maximum20140731
Range39720
Interquartile range (IQR)9825

Descriptive statistics

Standard deviation10266.828
Coefficient of variation (CV)0.0005101587
Kurtosis-0.38683241
Mean20124773
Median Absolute Deviation (MAD)9186.5
Skewness-0.19461097
Sum6.4399275 × 108
Variance1.0540776 × 108
MonotonicityNot monotonic
2024-05-11T16:59:45.419586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20120717 2
 
< 0.1%
20111119 1
 
< 0.1%
20101011 1
 
< 0.1%
20110307 1
 
< 0.1%
20110526 1
 
< 0.1%
20120928 1
 
< 0.1%
20130201 1
 
< 0.1%
20130301 1
 
< 0.1%
20111128 1
 
< 0.1%
20121025 1
 
< 0.1%
Other values (21) 21
 
0.4%
(Missing) 5389
99.4%
ValueCountFrequency (%)
20101011 1
< 0.1%
20110307 1
< 0.1%
20110526 1
< 0.1%
20111118 1
< 0.1%
20111119 1
< 0.1%
20111128 1
< 0.1%
20120717 2
< 0.1%
20120817 1
< 0.1%
20120901 1
< 0.1%
20120913 1
< 0.1%
ValueCountFrequency (%)
20140731 1
< 0.1%
20140720 1
< 0.1%
20140626 1
< 0.1%
20140415 1
< 0.1%
20140212 1
< 0.1%
20131227 1
< 0.1%
20131027 1
< 0.1%
20130623 1
< 0.1%
20130615 1
< 0.1%
20130306 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)7.9%
Missing5307
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean177054.02
Minimum1
Maximum20181210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:45.573603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile184.5
Maximum20181210
Range20181209
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1890141.1
Coefficient of variation (CV)10.675505
Kurtosis114
Mean177054.02
Median Absolute Deviation (MAD)0
Skewness10.677078
Sum20184158
Variance3.5726332 × 1012
MonotonicityNot monotonic
2024-05-11T16:59:45.712620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 97
 
1.8%
1 9
 
0.2%
540 2
 
< 0.1%
365 1
 
< 0.1%
20181210 1
 
< 0.1%
90 1
 
< 0.1%
12 1
 
< 0.1%
450 1
 
< 0.1%
360 1
 
< 0.1%
(Missing) 5307
97.9%
ValueCountFrequency (%)
1 9
 
0.2%
6 97
1.8%
12 1
 
< 0.1%
90 1
 
< 0.1%
360 1
 
< 0.1%
365 1
 
< 0.1%
450 1
 
< 0.1%
540 2
 
< 0.1%
20181210 1
 
< 0.1%
ValueCountFrequency (%)
20181210 1
 
< 0.1%
540 2
 
< 0.1%
450 1
 
< 0.1%
365 1
 
< 0.1%
360 1
 
< 0.1%
90 1
 
< 0.1%
12 1
 
< 0.1%
6 97
1.8%
1 9
 
0.2%

보관상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
실온
2344 
<NA>
2176 
냉장
446 
냉동
395 
기타
 
60

Length

Max length4
Median length2
Mean length2.8028039
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 2344
43.2%
<NA> 2176
40.1%
냉장 446
 
8.2%
냉동 395
 
7.3%
기타 60
 
1.1%

Length

2024-05-11T16:59:45.876124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:46.012637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 2344
43.2%
na 2176
40.1%
냉장 446
 
8.2%
냉동 395
 
7.3%
기타 60
 
1.1%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

어린이기호식품유형
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5316 
과자(한과류제외)
 
31
캔디류
 
23
빵류
 
22
초콜릿류
 
10
Other values (4)
 
19

Length

Max length9
Median length4
Mean length4.0215827
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5316
98.1%
과자(한과류제외) 31
 
0.6%
캔디류 23
 
0.4%
빵류 22
 
0.4%
초콜릿류 10
 
0.2%
과?채음료 6
 
0.1%
탄산음료 6
 
0.1%
유탕면류(용기면) 4
 
0.1%
어육소시지 3
 
0.1%

Length

2024-05-11T16:59:46.190440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:46.676828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5316
98.1%
과자(한과류제외 31
 
0.6%
캔디류 23
 
0.4%
빵류 22
 
0.4%
초콜릿류 10
 
0.2%
과?채음료 6
 
0.1%
탄산음료 6
 
0.1%
유탕면류(용기면 4
 
0.1%
어육소시지 3
 
0.1%

검사기관명
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
001
3843 
<NA>
1500 
000
 
36
080
 
22
양천보건소
 
6
Other values (5)
 
14

Length

Max length15
Median length3
Mean length3.2870319
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row001
2nd row001
3rd row001
4th row001
5th row001

Common Values

ValueCountFrequency (%)
001 3843
70.9%
<NA> 1500
 
27.7%
000 36
 
0.7%
080 22
 
0.4%
양천보건소 6
 
0.1%
양천구보건소 6
 
0.1%
002 3
 
0.1%
보건환경연구원 3
 
0.1%
양청보건소 1
 
< 0.1%
서울시보건환경연구원식의약품부 1
 
< 0.1%

Length

2024-05-11T16:59:46.852736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:47.011613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 3843
70.9%
na 1500
 
27.7%
000 36
 
0.7%
080 22
 
0.4%
양천보건소 6
 
0.1%
양천구보건소 6
 
0.1%
002 3
 
0.1%
보건환경연구원 3
 
0.1%
양청보건소 1
 
< 0.1%
서울시보건환경연구원식의약품부 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct180
Distinct (%)41.6%
Missing4988
Missing (%)92.0%
Memory size42.5 KiB
2024-05-11T16:59:47.284699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length7.595843
Min length2

Characters and Unicode

Total characters3289
Distinct characters256
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)22.2%

Sample

1st row(주)와이앤에스지
2nd row(주)한국씨엔에스팜
3rd rowCAPTEK SOFTGEL INTL INC CerritosCA
4th rowCAPTEK SOFTGEL INTL INC CerritosCA
5th rowGMP Pharmaceuticals Ltd.
ValueCountFrequency (%)
씨제이제일제당(주 37
 
7.8%
주식회사 14
 
3.0%
오뚜기 10
 
2.1%
샘표식품주식회사 8
 
1.7%
주)롯데제과 8
 
1.7%
대상(주)오산공장 8
 
1.7%
주)오뚜기 8
 
1.7%
삼조쎌텍(주 7
 
1.5%
롯데칠성음료(주 7
 
1.5%
코카콜라음료(주 7
 
1.5%
Other values (180) 360
75.9%
2024-05-11T16:59:47.710045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 328
 
10.0%
( 276
 
8.4%
) 276
 
8.4%
제 161
 
4.9%
식 120
 
3.6%
사 67
 
2.0%
품 67
 
2.0%
회 58
 
1.8%
이 57
 
1.7%
오 55
 
1.7%
Other values (246) 1824
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2452
74.6%
Open Punctuation 276
 
8.4%
Close Punctuation 276
 
8.4%
Lowercase Letter 120
 
3.6%
Uppercase Letter 117
 
3.6%
Space Separator 41
 
1.2%
Other Punctuation 6
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 328
 
13.4%
제 161
 
6.6%
식 120
 
4.9%
사 67
 
2.7%
품 67
 
2.7%
회 58
 
2.4%
이 57
 
2.3%
오 55
 
2.2%
일 53
 
2.2%
기 43
 
1.8%
Other values (209) 1443
58.8%
Uppercase Letter
ValueCountFrequency (%)
C 17
14.5%
T 13
11.1%
L 12
10.3%
P 10
8.5%
N 9
7.7%
A 9
7.7%
E 8
6.8%
I 8
6.8%
G 8
6.8%
K 4
 
3.4%
Other values (7) 19
16.2%
Lowercase Letter
ValueCountFrequency (%)
a 15
12.5%
t 14
11.7%
e 13
10.8%
i 12
10.0%
r 12
10.0%
s 10
8.3%
u 8
6.7%
c 8
6.7%
o 7
5.8%
l 5
 
4.2%
Other values (4) 16
13.3%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
？ 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 276
100.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2452
74.6%
Common 600
 
18.2%
Latin 237
 
7.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 328
 
13.4%
제 161
 
6.6%
식 120
 
4.9%
사 67
 
2.7%
품 67
 
2.7%
회 58
 
2.4%
이 57
 
2.3%
오 55
 
2.2%
일 53
 
2.2%
기 43
 
1.8%
Other values (209) 1443
58.8%
Latin
ValueCountFrequency (%)
C 17
 
7.2%
a 15
 
6.3%
t 14
 
5.9%
T 13
 
5.5%
e 13
 
5.5%
L 12
 
5.1%
i 12
 
5.1%
r 12
 
5.1%
P 10
 
4.2%
s 10
 
4.2%
Other values (21) 109
46.0%
Common
ValueCountFrequency (%)
( 276
46.0%
) 276
46.0%
41
 
6.8%
. 4
 
0.7%
？ 2
 
0.3%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2452
74.6%
ASCII 835
 
25.4%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 328
 
13.4%
제 161
 
6.6%
식 120
 
4.9%
사 67
 
2.7%
품 67
 
2.7%
회 58
 
2.4%
이 57
 
2.3%
오 55
 
2.2%
일 53
 
2.2%
기 43
 
1.8%
Other values (209) 1443
58.8%
ASCII
ValueCountFrequency (%)
( 276
33.1%
) 276
33.1%
41
 
4.9%
C 17
 
2.0%
a 15
 
1.8%
t 14
 
1.7%
T 13
 
1.6%
e 13
 
1.6%
L 12
 
1.4%
i 12
 
1.4%
Other values (26) 146
17.5%
None
ValueCountFrequency (%)
？ 2
100.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
국내
3836 
국외
1585 

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 3836
70.8%
국외 1585
29.2%

Length

2024-05-11T16:59:47.842898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:47.938544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 3836
70.8%
국외 1585
29.2%

국가명
Categorical

IMBALANCE 

Distinct32
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5173 
미국
 
57
중국
 
41
이탈리아
 
26
일본
 
23
Other values (27)
 
101

Length

Max length9
Median length4
Mean length3.9380188
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> 5173
95.4%
미국 57
 
1.1%
중국 41
 
0.8%
이탈리아 26
 
0.5%
일본 23
 
0.4%
태국 15
 
0.3%
베트남 13
 
0.2%
영국 8
 
0.1%
캐나다 8
 
0.1%
독일 7
 
0.1%
Other values (22) 50
 
0.9%

Length

2024-05-11T16:59:48.064690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5173
95.4%
미국 57
 
1.1%
중국 42
 
0.8%
이탈리아 26
 
0.5%
일본 23
 
0.4%
태국 15
 
0.3%
베트남 13
 
0.2%
영국 8
 
0.1%
캐나다 8
 
0.1%
독일 7
 
0.1%
Other values (22) 52
 
1.0%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
2652 
1
2091 
2
678 

Length

Max length4
Median length1
Mean length2.4676259
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2652
48.9%
1 2091
38.6%
2 678
 
12.5%

Length

2024-05-11T16:59:48.230878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:48.356131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2652
48.9%
1 2091
38.6%
2 678
 
12.5%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)5.2%
Missing2830
Missing (%)52.2%
Infinite0
Infinite (%)0.0%
Mean20157342
Minimum20110114
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:48.488817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110114
5-th percentile20110426
Q120111128
median20160513
Q320180917
95-th percentile20231019
Maximum20240314
Range130200
Interquartile range (IQR)69789

Descriptive statistics

Standard deviation39039.506
Coefficient of variation (CV)0.0019367388
Kurtosis-0.82117056
Mean20157342
Median Absolute Deviation (MAD)30105
Skewness0.32362535
Sum5.2227672 × 1010
Variance1.524083 × 109
MonotonicityNot monotonic
2024-05-11T16:59:48.640860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111128 216
 
4.0%
20111011 135
 
2.5%
20151007 114
 
2.1%
20110426 105
 
1.9%
20190618 98
 
1.8%
20151124 92
 
1.7%
20110726 90
 
1.7%
20160128 65
 
1.2%
20180322 61
 
1.1%
20170118 60
 
1.1%
Other values (125) 1555
28.7%
(Missing) 2830
52.2%
ValueCountFrequency (%)
20110114 20
 
0.4%
20110309 12
 
0.2%
20110426 105
1.9%
20110531 8
 
0.1%
20110607 3
 
0.1%
20110610 6
 
0.1%
20110628 4
 
0.1%
20110705 13
 
0.2%
20110707 3
 
0.1%
20110713 5
 
0.1%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240306 1
 
< 0.1%
20240305 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20231121 5
 
0.1%
20231115 37
0.7%
20231111 50
0.9%
20231024 2
 
< 0.1%
20231019 42
0.8%

결과회보일자
Real number (ℝ)

MISSING 

Distinct109
Distinct (%)6.8%
Missing3828
Missing (%)70.6%
Infinite0
Infinite (%)0.0%
Mean20164465
Minimum20110607
Maximum20770706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:48.787033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110607
5-th percentile20111026
Q120151210
median20161207
Q320180509
95-th percentile20200526
Maximum20770706
Range660099
Interquartile range (IQR)29299

Descriptive statistics

Standard deviation27049.254
Coefficient of variation (CV)0.0013414318
Kurtosis157.89623
Mean20164465
Median Absolute Deviation (MAD)10185
Skewness6.6743272
Sum3.2121992 × 1010
Variance7.3166214 × 108
MonotonicityNot monotonic
2024-05-11T16:59:48.943244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190628 98
 
1.8%
20160530 82
 
1.5%
20151022 81
 
1.5%
20180406 61
 
1.1%
20151210 51
 
0.9%
20150917 50
 
0.9%
20171012 50
 
0.9%
20181004 42
 
0.8%
20151223 41
 
0.8%
20151005 39
 
0.7%
Other values (99) 998
 
18.4%
(Missing) 3828
70.6%
ValueCountFrequency (%)
20110607 8
 
0.1%
20110624 6
 
0.1%
20110706 2
 
< 0.1%
20110725 1
 
< 0.1%
20110727 5
 
0.1%
20110908 2
 
< 0.1%
20110916 3
 
0.1%
20110919 37
0.7%
20111026 35
0.6%
20111027 3
 
0.1%
ValueCountFrequency (%)
20770706 1
 
< 0.1%
20211101 6
 
0.1%
20211029 8
 
0.1%
20210723 9
 
0.2%
20210419 20
0.4%
20201105 15
0.3%
20200526 26
0.5%
20191018 10
 
0.2%
20190916 19
0.4%
20190718 10
 
0.2%

판정구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
3735 
1
1671 
2
 
15

Length

Max length4
Median length4
Mean length3.0669618
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3735
68.9%
1 1671
30.8%
2 15
 
0.3%

Length

2024-05-11T16:59:49.105674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:49.215342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3735
68.9%
1 1671
30.8%
2 15
 
0.3%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

처리결과
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5392 
트랜스지방 : 0.00
 
11
미생물부-105892
 
8
서울시보건환경연구원 미생물부-106991
 
6
고발
 
1
Other values (3)
 
3

Length

Max length22
Median length4
Mean length4.0518355
Min length2

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5392
99.5%
트랜스지방 : 0.00 11
 
0.2%
미생물부-105892 8
 
0.1%
서울시보건환경연구원 미생물부-106991 6
 
0.1%
고발 1
 
< 0.1%
고발 및 시정명령, 기소유예 1
 
< 0.1%
식중독9종 및 대장균 : 적합 1
 
< 0.1%
트랜스지방 : 0.15 1
 
< 0.1%

Length

2024-05-11T16:59:49.358605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:49.487810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5392
98.8%
13
 
0.2%
트랜스지방 12
 
0.2%
0.00 11
 
0.2%
미생물부-105892 8
 
0.1%
서울시보건환경연구원 6
 
0.1%
미생물부-106991 6
 
0.1%
고발 2
 
< 0.1%
및 2
 
< 0.1%
시정명령 1
 
< 0.1%
Other values (5) 5
 
0.1%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

교부번호
Text

Distinct440
Distinct (%)8.1%
Missing16
Missing (%)0.3%
Memory size42.5 KiB
2024-05-11T16:59:49.771315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.996855
Min length4

Characters and Unicode

Total characters59438
Distinct characters15
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

Unique230 ?
Unique (%)4.3%

Sample

1st row19990073400
2nd row19990073400
3rd row20200115393
4th row20150073530
5th row20170074065
ValueCountFrequency (%)
20090073266 1043
19.3%
20010073163 765
 
14.2%
20110073044 400
 
7.4%
20060073189 309
 
5.7%
20080073687 242
 
4.5%
20020073874 162
 
3.0%
20130073626 160
 
3.0%
20070073730 143
 
2.6%
19770073013 98
 
1.8%
19990073945 91
 
1.7%
Other values (430) 1992
36.9%
2024-05-11T16:59:50.226013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20519
34.5%
3 6992
 
11.8%
7 6933
 
11.7%
2 6874
 
11.6%
1 4990
 
8.4%
6 4391
 
7.4%
9 4080
 
6.9%
4 1973
 
3.3%
8 1900
 
3.2%
5 771
 
1.3%
Other values (5) 15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59423
> 99.9%
Other Letter 12
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20519
34.5%
3 6992
 
11.8%
7 6933
 
11.7%
2 6874
 
11.6%
1 4990
 
8.4%
6 4391
 
7.4%
9 4080
 
6.9%
4 1973
 
3.3%
8 1900
 
3.2%
5 771
 
1.3%
Other Letter
ValueCountFrequency (%)
양 3
25.0%
천 3
25.0%
제 3
25.0%
조 3
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59426
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20519
34.5%
3 6992
 
11.8%
7 6933
 
11.7%
2 6874
 
11.6%
1 4990
 
8.4%
6 4391
 
7.4%
9 4080
 
6.9%
4 1973
 
3.3%
8 1900
 
3.2%
5 771
 
1.3%
Hangul
ValueCountFrequency (%)
양 3
25.0%
천 3
25.0%
제 3
25.0%
조 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59426
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20519
34.5%
3 6992
 
11.8%
7 6933
 
11.7%
2 6874
 
11.6%
1 4990
 
8.4%
6 4391
 
7.4%
9 4080
 
6.9%
4 1973
 
3.3%
8 1900
 
3.2%
5 771
 
1.3%
Hangul
ValueCountFrequency (%)
양 3
25.0%
천 3
25.0%
제 3
25.0%
조 3
25.0%

폐기일자
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)13.0%
Missing5313
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean20171996
Minimum20050823
Maximum20210423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:50.380666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050823
5-th percentile20054260
Q120181025
median20200529
Q320201106
95-th percentile20210423
Maximum20210423
Range159600
Interquartile range (IQR)20081

Descriptive statistics

Standard deviation56339.226
Coefficient of variation (CV)0.0027929425
Kurtosis0.42216658
Mean20171996
Median Absolute Deviation (MAD)9606
Skewness-1.5114381
Sum2.1785756 × 109
Variance3.1741083 × 109
MonotonicityNot monotonic
2024-05-11T16:59:50.507886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20200529 26
 
0.5%
20190923 19
 
0.4%
20210423 18
 
0.3%
20201106 15
 
0.3%
20181025 7
 
0.1%
20060614 7
 
0.1%
20060118 5
 
0.1%
20210419 2
 
< 0.1%
20060111 2
 
< 0.1%
20051109 2
 
< 0.1%
Other values (4) 5
 
0.1%
(Missing) 5313
98.0%
ValueCountFrequency (%)
20050823 1
 
< 0.1%
20051102 2
 
< 0.1%
20051103 1
 
< 0.1%
20051109 2
 
< 0.1%
20060111 2
 
< 0.1%
20060118 5
 
0.1%
20060614 7
 
0.1%
20090605 1
 
< 0.1%
20181025 7
 
0.1%
20190923 19
0.4%
ValueCountFrequency (%)
20210423 18
0.3%
20210419 2
 
< 0.1%
20201106 15
0.3%
20200529 26
0.5%
20190923 19
0.4%
20181025 7
 
0.1%
20090605 1
 
< 0.1%
20060614 7
 
0.1%
20060118 5
 
0.1%
20060111 2
 
< 0.1%

폐기량(kg)
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)35.0%
Missing5401
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean133.95
Minimum1
Maximum2628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:50.640740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile140.9
Maximum2628
Range2627
Interquartile range (IQR)2

Descriptive statistics

Standard deviation587.04214
Coefficient of variation (CV)4.3825468
Kurtosis19.999415
Mean133.95
Median Absolute Deviation (MAD)1.5
Skewness4.4720426
Sum2679
Variance344618.47
MonotonicityNot monotonic
2024-05-11T16:59:50.751550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 7
 
0.1%
3 7
 
0.1%
2 2
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
4 1
 
< 0.1%
2628 1
 
< 0.1%
(Missing) 5401
99.6%
ValueCountFrequency (%)
1 7
0.1%
2 2
 
< 0.1%
3 7
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
2628 1
 
< 0.1%
ValueCountFrequency (%)
2628 1
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
4 1
 
< 0.1%
3 7
0.1%
2 2
 
< 0.1%
1 7
0.1%

폐기금액(원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5401 
0
 
20

Length

Max length4
Median length4
Mean length3.9889319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5401
99.6%
0 20
 
0.4%

Length

2024-05-11T16:59:50.891397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:50.996686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5401
99.6%
0 20
 
0.4%

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

폐기방법
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
<NA>
5334 
음식물처리
 
76
음식물 처리
 
10
음식물쓰레기처리업소에서 대행처리(청송환경)
 
1

Length

Max length23
Median length4
Mean length4.0212138
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5334
98.4%
음식물처리 76
 
1.4%
음식물 처리 10
 
0.2%
음식물쓰레기처리업소에서 대행처리(청송환경) 1
 
< 0.1%

Length

2024-05-11T16:59:51.124230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:51.262261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5334
98.2%
음식물처리 76
 
1.4%
음식물 10
 
0.2%
처리 10
 
0.2%
음식물쓰레기처리업소에서 1
 
< 0.1%
대행처리(청송환경 1
 
< 0.1%

소재지(도로명)
Text

MISSING 

Distinct248
Distinct (%)8.8%
Missing2597
Missing (%)47.9%
Memory size42.5 KiB
2024-05-11T16:59:51.535286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length53
Mean length33.376771
Min length23

Characters and Unicode

Total characters94256
Distinct characters202
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

Unique100 ?
Unique (%)3.5%

Sample

1st row서울특별시 양천구 월정로 280, (신월동)
2nd row서울특별시 양천구 월정로 280, (신월동)
3rd row서울특별시 양천구 목동서로 349, 센트럴프라자 지하 1층 (신정동)
4th row서울특별시 양천구 오목로 350, 썬택씨티빌딩 1~2층 (목동)
5th row서울특별시 양천구 목동서로 221, 굿모닝탑 1층 116~117호 (목동)
ValueCountFrequency (%)
서울특별시 2824
 
15.3%
양천구 2824
 
15.3%
신정동 1035
 
5.6%
목동 768
 
4.2%
신월동 711
 
3.9%
지하1층 557
 
3.0%
목동서로 536
 
2.9%
신월로 468
 
2.5%
220 400
 
2.2%
동방아파트 400
 
2.2%
Other values (445) 7896
42.9%
2024-05-11T16:59:51.960885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15595
 
16.5%
동 5904
 
6.3%
, 4524
 
4.8%
서 3513
 
3.7%
양 3128
 
3.3%
1 3107
 
3.3%
목 3092
 
3.3%
천 3006
 
3.2%
시 2940
 
3.1%
) 2921
 
3.1%
Other values (192) 46526
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56605
60.1%
Space Separator 15595
 
16.5%
Decimal Number 11372
 
12.1%
Other Punctuation 4526
 
4.8%
Close Punctuation 2921
 
3.1%
Open Punctuation 2921
 
3.1%
Uppercase Letter 154
 
0.2%
Dash Punctuation 125
 
0.1%
Math Symbol 31
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5904
 
10.4%
서 3513
 
6.2%
양 3128
 
5.5%
목 3092
 
5.5%
천 3006
 
5.3%
시 2940
 
5.2%
울 2904
 
5.1%
로 2837
 
5.0%
구 2826
 
5.0%
특 2824
 
5.0%
Other values (169) 23631
41.7%
Decimal Number
ValueCountFrequency (%)
1 3107
27.3%
2 2224
19.6%
0 1771
15.6%
3 985
 
8.7%
7 975
 
8.6%
5 688
 
6.0%
9 636
 
5.6%
4 517
 
4.5%
6 263
 
2.3%
8 206
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
B 148
96.1%
A 5
 
3.2%
C 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
c 2
33.3%
h 2
33.3%
a 2
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4524
> 99.9%
. 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15595
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2921
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2921
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125
100.0%
Math Symbol
ValueCountFrequency (%)
~ 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56605
60.1%
Common 37491
39.8%
Latin 160
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5904
 
10.4%
서 3513
 
6.2%
양 3128
 
5.5%
목 3092
 
5.5%
천 3006
 
5.3%
시 2940
 
5.2%
울 2904
 
5.1%
로 2837
 
5.0%
구 2826
 
5.0%
특 2824
 
5.0%
Other values (169) 23631
41.7%
Common
ValueCountFrequency (%)
15595
41.6%
, 4524
 
12.1%
1 3107
 
8.3%
) 2921
 
7.8%
( 2921
 
7.8%
2 2224
 
5.9%
0 1771
 
4.7%
3 985
 
2.6%
7 975
 
2.6%
5 688
 
1.8%
Other values (7) 1780
 
4.7%
Latin
ValueCountFrequency (%)
B 148
92.5%
A 5
 
3.1%
c 2
 
1.2%
h 2
 
1.2%
a 2
 
1.2%
C 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56605
60.1%
ASCII 37651
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15595
41.4%
, 4524
 
12.0%
1 3107
 
8.3%
) 2921
 
7.8%
( 2921
 
7.8%
2 2224
 
5.9%
0 1771
 
4.7%
3 985
 
2.6%
7 975
 
2.6%
5 688
 
1.8%
Other values (13) 1940
 
5.2%
Hangul
ValueCountFrequency (%)
동 5904
 
10.4%
서 3513
 
6.2%
양 3128
 
5.5%
목 3092
 
5.5%
천 3006
 
5.3%
시 2940
 
5.2%
울 2904
 
5.1%
로 2837
 
5.0%
구 2826
 
5.0%
특 2824
 
5.0%
Other values (169) 23631
41.7%

소재지(지번)
Text

MISSING 

Distinct448
Distinct (%)8.4%
Missing114
Missing (%)2.1%
Memory size42.5 KiB
2024-05-11T16:59:52.230377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length32.777841
Min length21

Characters and Unicode

Total characters173952
Distinct characters238
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

Unique239 ?
Unique (%)4.5%

Sample

1st row서울특별시 양천구 신월동 6번지 7호
2nd row서울특별시 양천구 신월동 6번지 7호
3rd row서울특별시 양천구 신정동 321번지 6호 센트럴프라자 지하 1층
4th row서울특별시 양천구 목동 404번지 177호 썬택씨티빌딩
5th row서울특별시 양천구 목동 923번지 15호 굿모닝탑 1층-116~117
ValueCountFrequency (%)
서울특별시 5307
16.0%
양천구 5303
16.0%
목동 2719
 
8.2%
신정동 1826
 
5.5%
962번지 1070
 
3.2%
트라팰리스 1015
 
3.1%
이마트 1011
 
3.1%
목동점(지하2층 1010
 
3.1%
7호 872
 
2.6%
919번지 798
 
2.4%
Other values (629) 12135
36.7%
2024-05-11T16:59:52.712128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39559
22.7%
지 8345
 
4.8%
동 7347
 
4.2%
1 7323
 
4.2%
양 5517
 
3.2%
천 5480
 
3.2%
서 5450
 
3.1%
시 5424
 
3.1%
울 5387
 
3.1%
구 5311
 
3.1%
Other values (228) 78809
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103243
59.4%
Space Separator 39559
 
22.7%
Decimal Number 26730
 
15.4%
Open Punctuation 1750
 
1.0%
Close Punctuation 1750
 
1.0%
Other Punctuation 345
 
0.2%
Dash Punctuation 298
 
0.2%
Uppercase Letter 219
 
0.1%
Math Symbol 50
 
< 0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 8345
 
8.1%
동 7347
 
7.1%
양 5517
 
5.3%
천 5480
 
5.3%
서 5450
 
5.3%
시 5424
 
5.3%
울 5387
 
5.2%
구 5311
 
5.1%
별 5308
 
5.1%
번 5307
 
5.1%
Other values (205) 44367
43.0%
Decimal Number
ValueCountFrequency (%)
1 7323
27.4%
2 5067
19.0%
9 3870
14.5%
6 2490
 
9.3%
3 2132
 
8.0%
0 1973
 
7.4%
7 1952
 
7.3%
8 809
 
3.0%
5 634
 
2.4%
4 480
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
B 202
92.2%
A 15
 
6.8%
C 2
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
a 4
50.0%
h 2
25.0%
c 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 339
98.3%
. 6
 
1.7%
Space Separator
ValueCountFrequency (%)
39559
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1750
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1750
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 298
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 103243
59.4%
Common 70482
40.5%
Latin 227
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 8345
 
8.1%
동 7347
 
7.1%
양 5517
 
5.3%
천 5480
 
5.3%
서 5450
 
5.3%
시 5424
 
5.3%
울 5387
 
5.2%
구 5311
 
5.1%
별 5308
 
5.1%
번 5307
 
5.1%
Other values (205) 44367
43.0%
Common
ValueCountFrequency (%)
39559
56.1%
1 7323
 
10.4%
2 5067
 
7.2%
9 3870
 
5.5%
6 2490
 
3.5%
3 2132
 
3.0%
0 1973
 
2.8%
7 1952
 
2.8%
( 1750
 
2.5%
) 1750
 
2.5%
Other values (7) 2616
 
3.7%
Latin
ValueCountFrequency (%)
B 202
89.0%
A 15
 
6.6%
a 4
 
1.8%
C 2
 
0.9%
h 2
 
0.9%
c 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 103243
59.4%
ASCII 70709
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39559
55.9%
1 7323
 
10.4%
2 5067
 
7.2%
9 3870
 
5.5%
6 2490
 
3.5%
3 2132
 
3.0%
0 1973
 
2.8%
7 1952
 
2.8%
( 1750
 
2.5%
) 1750
 
2.5%
Other values (13) 2843
 
4.0%
Hangul
ValueCountFrequency (%)
지 8345
 
8.1%
동 7347
 
7.1%
양 5517
 
5.3%
천 5480
 
5.3%
서 5450
 
5.3%
시 5424
 
5.3%
울 5387
 
5.2%
구 5311
 
5.1%
별 5308
 
5.1%
번 5307
 
5.1%
Other values (205) 44367
43.0%

업소전화번호
Text

MISSING 

Distinct363
Distinct (%)7.0%
Missing267
Missing (%)4.9%
Memory size42.5 KiB
2024-05-11T16:59:53.000567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.086147
Min length2

Characters and Unicode

Total characters51984
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)3.6%

Sample

1st row0226973035
2nd row0226973035
3rd row15771759
4th row0226527133
5th row0269231055
ValueCountFrequency (%)
0269231053 1034
18.4%
0226442080 476
 
8.5%
02 461
 
8.2%
0226521215 294
 
5.2%
0220652527 286
 
5.1%
0220624949 242
 
4.3%
26058900 216
 
3.8%
0221632233 162
 
2.9%
0226997357 114
 
2.0%
69252242 108
 
1.9%
Other values (355) 2224
39.6%
2024-05-11T16:59:53.444513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13634
26.2%
0 10142
19.5%
6 5787
11.1%
5 4135
 
8.0%
3 3731
 
7.2%
4 3678
 
7.1%
9 3436
 
6.6%
1 2792
 
5.4%
8 2143
 
4.1%
7 1613
 
3.1%
Other values (2) 893
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51091
98.3%
Space Separator 871
 
1.7%
Dash Punctuation 22
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13634
26.7%
0 10142
19.9%
6 5787
11.3%
5 4135
 
8.1%
3 3731
 
7.3%
4 3678
 
7.2%
9 3436
 
6.7%
1 2792
 
5.5%
8 2143
 
4.2%
7 1613
 
3.2%
Space Separator
ValueCountFrequency (%)
871
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51984
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13634
26.2%
0 10142
19.5%
6 5787
11.1%
5 4135
 
8.0%
3 3731
 
7.2%
4 3678
 
7.1%
9 3436
 
6.6%
1 2792
 
5.4%
8 2143
 
4.1%
7 1613
 
3.1%
Other values (2) 893
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13634
26.2%
0 10142
19.5%
6 5787
11.1%
5 4135
 
8.0%
3 3731
 
7.2%
4 3678
 
7.1%
9 3436
 
6.6%
1 2792
 
5.4%
8 2143
 
4.1%
7 1613
 
3.1%
Other values (2) 893
 
1.7%

점검목적
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
수거
3544 
위생점검(전체)
871 
위생점검(부분)
591 
<NA>
412 
시설점검
 
3

Length

Max length8
Median length2
Mean length3.7712599
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수거 3544
65.4%
위생점검(전체) 871
 
16.1%
위생점검(부분) 591
 
10.9%
<NA> 412
 
7.6%
시설점검 3
 
0.1%

Length

2024-05-11T16:59:53.629348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:53.752415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 3544
65.4%
위생점검(전체 871
 
16.1%
위생점검(부분 591
 
10.9%
na 412
 
7.6%
시설점검 3
 
0.1%

점검일자
Real number (ℝ)

Distinct295
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20134352
Minimum20010921
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:53.895709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010921
5-th percentile20090724
Q120110114
median20121023
Q320160513
95-th percentile20220825
Maximum20240314
Range229393
Interquartile range (IQR)50399

Descriptive statistics

Standard deviation38198.334
Coefficient of variation (CV)0.0018971722
Kurtosis0.20445374
Mean20134352
Median Absolute Deviation (MAD)20498
Skewness0.93124664
Sum1.0914832 × 1011
Variance1.4591127 × 109
MonotonicityNot monotonic
2024-05-11T16:59:54.070368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111124 216
 
4.0%
20120906 187
 
3.4%
20121023 155
 
2.9%
20100621 147
 
2.7%
20111007 138
 
2.5%
20100511 134
 
2.5%
20121207 131
 
2.4%
20120508 129
 
2.4%
20151006 114
 
2.1%
20090731 105
 
1.9%
Other values (285) 3965
73.1%
ValueCountFrequency (%)
20010921 3
 
0.1%
20040116 1
 
< 0.1%
20050824 1
 
< 0.1%
20051102 2
 
< 0.1%
20051103 1
 
< 0.1%
20051109 2
 
< 0.1%
20060111 2
 
< 0.1%
20060118 5
 
0.1%
20060614 7
 
0.1%
20090115 50
0.9%
ValueCountFrequency (%)
20240314 2
 
< 0.1%
20240306 1
 
< 0.1%
20240305 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20231121 5
 
0.1%
20231115 37
0.7%
20231111 50
0.9%
20231024 2
 
< 0.1%
20231019 42
0.8%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
수시
2540 
기타
2281 
<NA>
361 
합동
 
143
일제
 
96

Length

Max length4
Median length2
Mean length2.1331858
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 2540
46.9%
기타 2281
42.1%
<NA> 361
 
6.7%
합동 143
 
2.6%
일제 96
 
1.8%

Length

2024-05-11T16:59:54.229237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:54.355824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 2540
46.9%
기타 2281
42.1%
na 361
 
6.7%
합동 143
 
2.6%
일제 96
 
1.8%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

점검결과코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size42.5 KiB
1
4755 
<NA>
 
361
2
 
305

Length

Max length4
Median length1
Mean length1.1997786
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4755
87.7%
<NA> 361
 
6.7%
2 305
 
5.6%

Length

2024-05-11T16:59:54.503876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:59:54.669036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4755
87.7%
na 361
 
6.7%
2 305
 
5.6%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)96.9%
Missing5389
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20124773
Minimum20101011
Maximum20140731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.8 KiB
2024-05-11T16:59:54.785723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20101011
5-th percentile20110427
Q120120792
median20121117
Q320130617
95-th percentile20140668
Maximum20140731
Range39720
Interquartile range (IQR)9825

Descriptive statistics

Standard deviation10266.828
Coefficient of variation (CV)0.0005101587
Kurtosis-0.38683241
Mean20124773
Median Absolute Deviation (MAD)9186.5
Skewness-0.19461097
Sum6.4399275 × 108
Variance1.0540776 × 108
MonotonicityNot monotonic
2024-05-11T16:59:54.972394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20120717 2
 
< 0.1%
20111119 1
 
< 0.1%
20101011 1
 
< 0.1%
20110307 1
 
< 0.1%
20110526 1
 
< 0.1%
20120928 1
 
< 0.1%
20130201 1
 
< 0.1%
20130301 1
 
< 0.1%
20111128 1
 
< 0.1%
20121025 1
 
< 0.1%
Other values (21) 21
 
0.4%
(Missing) 5389
99.4%
ValueCountFrequency (%)
20101011 1
< 0.1%
20110307 1
< 0.1%
20110526 1
< 0.1%
20111118 1
< 0.1%
20111119 1
< 0.1%
20111128 1
< 0.1%
20120717 2
< 0.1%
20120817 1
< 0.1%
20120901 1
< 0.1%
20120913 1
< 0.1%
ValueCountFrequency (%)
20140731 1
< 0.1%
20140720 1
< 0.1%
20140626 1
< 0.1%
20140415 1
< 0.1%
20140212 1
< 0.1%
20131227 1
< 0.1%
20131027 1
< 0.1%
20130623 1
< 0.1%
20130615 1
< 0.1%
20130306 1
< 0.1%

(구)제조회사주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

부적합항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5421
Missing (%)100.0%
Memory size47.8 KiB

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03140000105집단급식소<NA><NA><NA><NA>24-양천-1-집단2검사용서울강신초등학교G0300000300000칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)도마 swab<NA><NA><NA>20240314<NA><NA><NA>swab*220240314<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>19990073400<NA><NA><NA><NA><NA>서울특별시 양천구 월정로 280, (신월동)서울특별시 양천구 신월동 6번지 7호0226973035수거20240314합동<NA>1<NA><NA><NA><NA>
13140000105집단급식소<NA><NA><NA><NA>24-양천-1-집단1검사용서울강신초등학교G0100000100000조리식품 등조리식품 등햄모듬찌개<NA><NA><NA>202403141.0600g<NA>20240314<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>19990073400<NA><NA><NA><NA><NA>서울특별시 양천구 월정로 280, (신월동)서울특별시 양천구 신월동 6번지 7호0226973035수거20240314합동<NA>1<NA><NA><NA><NA>
23140000106식품제조가공업<NA><NA><NA><NA>115-3-6-안전1검사용산들해반찬C0322020300000즉석조리식품즉석조리식품한돈 고추장찌개<NA><NA><NA>202403065.0400g<NA><NA><NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>20200115393<NA><NA><NA><NA><NA>서울특별시 양천구 목동서로 349, 센트럴프라자 지하 1층 (신정동)서울특별시 양천구 신정동 321번지 6호 센트럴프라자 지하 1층15771759위생점검(전체)20240306합동<NA>1<NA><NA><NA><NA>
33140000104휴게음식점<NA><NA><NA><NA>24-양천-1-2검사용(주)커피빈코리아 오목교역사거리점G0200000200000자가제조얼음자가제조얼음식용얼음<NA><NA><NA>202403051.0600g<NA>20240305<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240305<NA><NA><NA><NA><NA><NA><NA><NA>20150073530<NA><NA><NA><NA><NA>서울특별시 양천구 오목로 350, 썬택씨티빌딩 1~2층 (목동)서울특별시 양천구 목동 404번지 177호 썬택씨티빌딩<NA>수거20240305수시<NA>1<NA><NA><NA><NA>
43140000104휴게음식점<NA><NA><NA><NA>24-양천-1-3검사용디저트39G0200000200000자가제조얼음자가제조얼음식용얼음<NA><NA><NA>202403051.0600g<NA>20240305<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240305<NA><NA><NA><NA><NA><NA><NA><NA>20170074065<NA><NA><NA><NA><NA>서울특별시 양천구 목동서로 221, 굿모닝탑 1층 116~117호 (목동)서울특별시 양천구 목동 923번지 15호 굿모닝탑 1층-116~1170226527133수거20240305수시<NA>1<NA><NA><NA><NA>
53140000101일반음식점<NA><NA><NA><NA>24-양천-1-1검사용마라영웅G0100000100000조리식품 등조리식품 등마라탕<NA><NA>양천구 목동동로12길 22202402261.0600g<NA>20240226<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240226<NA><NA><NA><NA><NA><NA><NA><NA>20220090091<NA><NA><NA><NA><NA>서울특별시 양천구 목동동로12길 22, 1층 104호 (신정동, 프리우스아파트)서울특별시 양천구 신정동 86번지 6호 프리우스아파트 1층-104<NA><NA>20240226수시<NA>1<NA><NA><NA><NA>
63140000107즉석판매제조가공업<NA><NA><NA><NA>115-1-안전3검사용(주)찬장 목동점C0322020100000즉석섭취식품즉석섭취식품애호박채전<NA><NA><NA>202401181.0600g<NA>20240118<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240118<NA><NA><NA><NA><NA><NA><NA><NA>20220089707<NA><NA><NA><NA><NA>서울특별시 양천구 목동로 177, 정동프라자 106호, 301호 (신정동)서울특별시 양천구 신정동 995번지 6호 정동프라자<NA>위생점검(전체)20240118합동<NA>1<NA><NA><NA><NA>
73140000107즉석판매제조가공업<NA><NA><NA><NA>115-1-안전4검사용(주)찬장 목동점C0322020100000즉석섭취식품즉석섭취식품오징어김치전<NA><NA><NA>202401181.0600g<NA>20240118<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240118<NA><NA><NA><NA><NA><NA><NA><NA>20220089707<NA><NA><NA><NA><NA>서울특별시 양천구 목동로 177, 정동프라자 106호, 301호 (신정동)서울특별시 양천구 신정동 995번지 6호 정동프라자<NA>위생점검(전체)20240118합동<NA>1<NA><NA><NA><NA>
83140000114기타식품판매업<NA><NA><NA><NA>양천2023-11-2검사용(주)이마트 목동점H0100400000000과일.채소용 세척제과일.채소용 세척제에이포레사이프러스<NA><NA>(주)케이피코리아20231121<NA><NA><NA>150ml*3개20230517<NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120231121<NA><NA><NA><NA><NA><NA><NA><NA>20090073266<NA><NA><NA><NA><NA>서울특별시 양천구 오목로 299, 지하2층 (목동, 목동트라팰리스 웨스턴에비뉴)서울특별시 양천구 목동 962번지 목동트라팰리스 웨스턴에비뉴 지하2층0269231055수거20231121기타<NA>1<NA><NA><NA><NA>
93140000114기타식품판매업<NA><NA><NA><NA>양천 2023-11-5검사용(주)이마트 목동점H0301300200000미용 화장지미용 화장지코디 시카로션 티슈<NA><NA>(주)쌍용씨앤비20231121<NA><NA><NA>200매*4입20230912<NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120231121<NA><NA><NA><NA><NA><NA><NA><NA>20090073266<NA><NA><NA><NA><NA>서울특별시 양천구 오목로 299, 지하2층 (목동, 목동트라팰리스 웨스턴에비뉴)서울특별시 양천구 목동 962번지 목동트라팰리스 웨스턴에비뉴 지하2층0269231055수거20231121기타<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
54113140000106식품제조가공업<NA><NA><NA><NA><NA><NA>양천자활지원센터016<NA><NA>배추포기김치<NA><NA><NA>200511093.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005110930<NA><NA><NA>서울특별시 양천구 목동 555번지 2호<NA><NA>20051109수시<NA>1<NA><NA><NA><NA>
54123140000106식품제조가공업<NA><NA><NA><NA><NA><NA>명가김치016<NA><NA>배추포기김치<NA><NA><NA>200511095.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>양천제조-1402005110950<NA><NA><NA>서울특별시 양천구 신월동 601번지 21호02-2697-4755<NA>20051109수시<NA>1<NA><NA><NA><NA>
54133140000114기타식품판매업<NA><NA><NA><NA><NA><NA>부봉016<NA><NA>새샘김치<NA><NA><NA>2005110310.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20051103100<NA><NA><NA>서울특별시 양천구 신월동 145번지 10호<NA><NA>20051103수시<NA>1<NA><NA><NA><NA>
54143140000106식품제조가공업<NA><NA><NA><NA><NA><NA>수라청김치016<NA><NA>배추김치<NA><NA><NA>200511024.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>양천제조-1672005110240<NA><NA><NA>서울특별시 양천구 신월동 557번지 3호02-2696-8230<NA>20051102수시<NA>1<NA><NA><NA><NA>
54153140000106식품제조가공업<NA><NA><NA><NA><NA><NA>(주)실로암식품016<NA><NA>배추김치<NA><NA><NA>200511023.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>양천제조-272005110230<NA><NA><NA>서울특별시 양천구 신월동 988번지 8호02-2694-9822<NA>20051102수시<NA>1<NA><NA><NA><NA>
54163140000113유통전문판매업<NA><NA><NA><NA><NA><NA>남미수산(주)005<NA><NA>분홍새우살외<NA><NA><NA>200508242628.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>양천구보건소<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005082326280<NA>음식물쓰레기처리업소에서 대행처리(청송환경)<NA>서울특별시 중랑구 면목동 520번지 8호<NA><NA>20050824일제<NA>1<NA><NA><NA><NA>
54173140000107즉석판매제조가공업<NA><NA><NA><NA><NA><NA>홍제기름집<NA><NA>참기름<NA><NA><NA>20040116350.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원식의약품부<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19730073001<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 119번지 69호0226453253<NA>20040116기타<NA>2<NA><NA><NA><NA>
54183140000101일반음식점<NA><NA><NA><NA><NA><NA>김밥천국<NA><NA>김밥<NA><NA><NA>200109210.05<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19990074282<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1183번지 3호02 6981581<NA>20010921수시<NA>2<NA><NA><NA><NA>
54193140000101일반음식점<NA><NA><NA><NA><NA><NA>호호아줌마분식<NA><NA>김밥<NA><NA><NA>200109210.05<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19980073398<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1032번지 9호02 6498300<NA>20010921일제<NA>2<NA><NA><NA><NA>
54203140000101일반음식점<NA><NA><NA><NA><NA><NA>장우동<NA><NA>김밥<NA><NA><NA>200109210.05<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19930073388<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1032번지 8호0206465152<NA>20010921일제<NA>2<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)유통기한(일자)유통기한(제조일기준)보관상태코드어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호폐기일자폐기량(kg)폐기금액(원)폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한# duplicates
23140000112식품자동판매기영업<NA><NA><NA><NA><NA>양천구시설관리공단<NA><NA>음용수<NA><NA><NA>201006221000.0<NA><NA><NA><NA><NA><NA><NA><NA>000<NA>국외<NA><NA><NA><NA><NA><NA>20000073301<NA><NA><NA><NA><NA>서울특별시 양천구 신정동 310번지 7호 (실외,총5대)0226523458위생점검(부분)20100622기타1<NA>4
03140000101일반음식점<NA><NA><NA><NA><NA>목포수산<NA><NA>검체<NA><NA><NA>201011303.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA>20080073734<NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1032번지 7호 1층 ( 가림길 34 )0226552096위생점검(전체)20101130기타1<NA>3
33140000112식품자동판매기영업<NA><NA><NA><NA><NA>홈플러스목동점<NA><NA>음용수<NA><NA><NA>201006221000.0<NA><NA><NA><NA><NA><NA><NA><NA>000<NA>국외<NA><NA><NA><NA><NA><NA>20100073268<NA><NA><NA><NA><NA>서울특별시 양천구 목동 919번지 7호 홈플러스 목동점(실내, 8대)0234539622위생점검(부분)20100622기타1<NA>3
143140000114기타식품판매업<NA><NA><NA><NA><NA>홈플러스테스코(주)목동점410000000기구류기구류중기타물티슈<NA><NA><NA>200907313.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20010073163<NA><NA><NA><NA><NA>서울특별시 양천구 목동 919번지 7호0226442080수거20090731기타1<NA>3
13140000112식품자동판매기영업<NA><NA><NA><NA><NA>(주)신세계푸드<NA><NA>음용수<NA><NA><NA>201006251000.0<NA><NA><NA><NA><NA><NA><NA><NA>000<NA>국외<NA><NA><NA><NA><NA><NA>20090073293<NA><NA><NA><NA><NA>서울특별시 양천구 목동 962번지 트라팰리스 이마트목동점 지하2층(5대,실내)0233976100위생점검(부분)20100625기타1<NA>2
43140000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계 이마트 목동점814000000식용유지류참기름이마트베스트참기름<NA><NA><NA>201009033.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090073266<NA><NA><NA><NA><NA>서울특별시 양천구 목동 962번지 트라팰리스 이마트 목동점(지하2층)0269231053수거20100903수시1<NA>2
53140000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계 이마트 목동점814000000식용유지류콩기름(대두유)콩기름<NA><NA><NA>201001294.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090073266<NA><NA><NA><NA><NA>서울특별시 양천구 목동 962번지 트라팰리스 이마트 목동점(지하2층)0269231053수거20100129수시1<NA>2
63140000114기타식품판매업<NA><NA><NA><NA><NA>(주)지에스리테일GS수퍼 양천구청점801000000과자류추잉껌아쿠오<NA><NA><NA>201005113.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20060073189<NA><NA><NA><NA><NA>서울특별시 양천구 신정동 321번지 6호 외1필지26058900수거20100511기타1<NA>2
73140000114기타식품판매업<NA><NA><NA><NA><NA>(주)지에스리테일GS수퍼 양천구청점814000000식용유지류콩기름(대두유)콩기름<NA><NA><NA>201005113.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20060073189<NA><NA><NA><NA><NA>서울특별시 양천구 신정동 321번지 6호 외1필지26058900수거20100511기타1<NA>2
83140000114기타식품판매업<NA><NA><NA><NA><NA>(주)지에스리테일GS수퍼 양천구청점817000000커피인스턴트커피테이스터스초이스수프리모<NA><NA><NA>201005113.0<NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20060073189<NA><NA><NA><NA><NA>서울특별시 양천구 신정동 321번지 6호 외1필지26058900수거20100511기타1<NA>2