Overview

Dataset statistics

Number of variables61
Number of observations6024
Missing cells144444
Missing cells (%)39.3%
Duplicate rows17
Duplicate rows (%)0.3%
Total size in memory3.0 MiB
Average record size in memory517.0 B

Variable types

Categorical22
Numeric9
Unsupported12
Text18

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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-10301/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
(구)제조회사주소 has constant value ""Constant
Dataset has 17 (0.3%) duplicate rowsDuplicates
업종명 is highly imbalanced (62.4%)Imbalance
계획구분코드 is highly imbalanced (57.3%)Imbalance
지도점검계획 is highly imbalanced (62.4%)Imbalance
수거계획 is highly imbalanced (55.1%)Imbalance
원료명 is highly imbalanced (98.3%)Imbalance
수거량(자유) is highly imbalanced (94.2%)Imbalance
바코드번호 is highly imbalanced (99.4%)Imbalance
국가명 is highly imbalanced (86.0%)Imbalance
처리결과 is highly imbalanced (99.3%)Imbalance
폐기일자 is highly imbalanced (99.6%)Imbalance
폐기량(Kg) is highly imbalanced (99.6%)Imbalance
계획구분명 has 6024 (100.0%) missing valuesMissing
수거증번호 has 1153 (19.1%) missing valuesMissing
식품군코드 has 101 (1.7%) missing valuesMissing
식품군 has 438 (7.3%) missing valuesMissing
품목명 has 111 (1.8%) missing valuesMissing
음식물명 has 5939 (98.6%) missing valuesMissing
생산업소 has 5962 (99.0%) missing valuesMissing
수거량(정량) has 175 (2.9%) missing valuesMissing
제품규격(정량) has 1327 (22.0%) missing valuesMissing
제조일자(일자) has 5004 (83.1%) missing valuesMissing
제조일자(롯트) has 5997 (99.6%) missing valuesMissing
유통기한(일자) has 6024 (100.0%) missing valuesMissing
유통기한(제조일기준) has 5998 (99.6%) missing valuesMissing
어린이기호식품유형 has 6022 (> 99.9%) missing valuesMissing
(구)제조사명 has 6018 (99.9%) missing valuesMissing
검사의뢰일자 has 3892 (64.6%) missing valuesMissing
결과회보일자 has 4717 (78.3%) missing valuesMissing
처리구분 has 6024 (100.0%) missing valuesMissing
수거검사구분코드 has 6024 (100.0%) missing valuesMissing
단속지역구분코드 has 6024 (100.0%) missing valuesMissing
수거장소구분코드 has 6024 (100.0%) missing valuesMissing
수거품처리 has 6024 (100.0%) missing valuesMissing
폐기금액(원) has 6024 (100.0%) missing valuesMissing
폐기장소 has 6024 (100.0%) missing valuesMissing
폐기방법 has 6024 (100.0%) missing valuesMissing
소재지(도로명) has 673 (11.2%) missing valuesMissing
소재지(지번) has 104 (1.7%) missing valuesMissing
업소전화번호 has 457 (7.6%) missing valuesMissing
점검내용 has 6024 (100.0%) missing valuesMissing
(구)제조유통기한 has 6024 (100.0%) missing valuesMissing
(구)제조회사주소 has 6023 (> 99.9%) missing valuesMissing
부적합항목 has 6022 (> 99.9%) missing valuesMissing
기준치부적합내용 has 6022 (> 99.9%) missing valuesMissing
수거량(정량) is highly skewed (γ1 = 22.43086646)Skewed
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
유통기한(일자) is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조유통기한 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-10 22:31:17.703852
Analysis finished2024-05-10 22:31:22.723147
Duration5.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
3060000
6024 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 6024
100.0%

Length

2024-05-10T22:31:22.918715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:23.227712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 6024
100.0%

업종코드
Real number (ℝ)

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.36786
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:23.494934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation4.5639482
Coefficient of variation (CV)0.040616134
Kurtosis4.710585
Mean112.36786
Median Absolute Deviation (MAD)0
Skewness-0.44644556
Sum676904
Variance20.829623
MonotonicityNot monotonic
2024-05-10T22:31:23.848749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
114 4777
79.3%
105 419
 
7.0%
101 400
 
6.6%
112 92
 
1.5%
107 90
 
1.5%
106 89
 
1.5%
104 66
 
1.1%
134 52
 
0.9%
121 27
 
0.4%
122 12
 
0.2%
ValueCountFrequency (%)
101 400
 
6.6%
104 66
 
1.1%
105 419
 
7.0%
106 89
 
1.5%
107 90
 
1.5%
112 92
 
1.5%
114 4777
79.3%
121 27
 
0.4%
122 12
 
0.2%
134 52
 
0.9%
ValueCountFrequency (%)
134 52
 
0.9%
122 12
 
0.2%
121 27
 
0.4%
114 4777
79.3%
112 92
 
1.5%
107 90
 
1.5%
106 89
 
1.5%
105 419
 
7.0%
104 66
 
1.1%
101 400
 
6.6%

업종명
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
기타식품판매업
4777 
집단급식소
 
419
일반음식점
 
400
식품자동판매기영업
 
92
즉석판매제조가공업
 
90
Other values (5)
 
246

Length

Max length11
Median length7
Mean length6.7981408
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 4777
79.3%
집단급식소 419
 
7.0%
일반음식점 400
 
6.6%
식품자동판매기영업 92
 
1.5%
즉석판매제조가공업 90
 
1.5%
식품제조가공업 89
 
1.5%
휴게음식점 66
 
1.1%
건강기능식품일반판매업 52
 
0.9%
제과점영업 27
 
0.4%
집단급식소식품판매업 12
 
0.2%

Length

2024-05-10T22:31:24.239251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:24.557134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 4777
79.3%
집단급식소 419
 
7.0%
일반음식점 400
 
6.6%
식품자동판매기영업 92
 
1.5%
즉석판매제조가공업 90
 
1.5%
식품제조가공업 89
 
1.5%
휴게음식점 66
 
1.1%
건강기능식품일반판매업 52
 
0.9%
제과점영업 27
 
0.4%
집단급식소식품판매업 12
 
0.2%

계획구분코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
4019 
999
1822 
2
 
129
7
 
28
3
 
22

Length

Max length4
Median length4
Mean length3.6064077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row999
2nd row999
3rd row999
4th row999
5th row999

Common Values

ValueCountFrequency (%)
<NA> 4019
66.7%
999 1822
30.2%
2 129
 
2.1%
7 28
 
0.5%
3 22
 
0.4%
8 4
 
0.1%

Length

2024-05-10T22:31:24.920611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:25.226042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4019
66.7%
999 1822
30.2%
2 129
 
2.1%
7 28
 
0.5%
3 22
 
0.4%
8 4
 
0.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
4019 
식품제조판매업체 지도점검 계획
1006 
식품접객업 제외 식품관련업소 자체점검
 
366
2016년 유통식품수거 및 점검
 
214
식품접객업소 자체 점검
 
93
Other values (20)
 
326

Length

Max length30
Median length4
Mean length8.2310757
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row식품제조판매업체 지도점검 계획
2nd row식품제조판매업체 지도점검 계획
3rd row식품제조판매업체 지도점검 계획
4th row식품제조판매업체 지도점검 계획
5th row식품제조판매업체 지도점검 계획

Common Values

ValueCountFrequency (%)
<NA> 4019
66.7%
식품제조판매업체 지도점검 계획 1006
 
16.7%
식품접객업 제외 식품관련업소 자체점검 366
 
6.1%
2016년 유통식품수거 및 점검 214
 
3.6%
식품접객업소 자체 점검 93
 
1.5%
2017년 식품제조가공업소 등 자체점검 65
 
1.1%
집중관리시설 지도점검 59
 
1.0%
2019년도 식중독 예방관리 대책 34
 
0.6%
한우 취급 원산지표시 수거 계획 31
 
0.5%
2018년도 식중독 예방관리 대책 25
 
0.4%
Other values (15) 112
 
1.9%

Length

2024-05-10T22:31:25.528693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4019
37.2%
지도점검 1090
 
10.1%
계획 1059
 
9.8%
식품제조판매업체 1006
 
9.3%
자체점검 431
 
4.0%
식품접객업 366
 
3.4%
제외 366
 
3.4%
식품관련업소 366
 
3.4%
점검 328
 
3.0%
유통식품수거 236
 
2.2%
Other values (53) 1524
 
14.1%

수거계획
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
4109 
가공식품 관리계획
887 
구민 다소비 수거검사
466 
2021년 유통식품 등 수거검사 계획
 
196
2017년도 식품수거검사(모바일)
 
163
Other values (7)
 
203

Length

Max length20
Median length4
Mean length6.4168327
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> 4109
68.2%
가공식품 관리계획 887
 
14.7%
구민 다소비 수거검사 466
 
7.7%
2021년 유통식품 등 수거검사 계획 196
 
3.3%
2017년도 식품수거검사(모바일) 163
 
2.7%
2018년 유통식품 수거검사 78
 
1.3%
식품수거검사 53
 
0.9%
설 성수식품 수거검사 계획 34
 
0.6%
유통식품 수거검사 25
 
0.4%
식품수거 10
 
0.2%
Other values (2) 3
 
< 0.1%

Length

2024-05-10T22:31:25.906969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4109
45.3%
관리계획 887
 
9.8%
가공식품 887
 
9.8%
수거검사 799
 
8.8%
구민 466
 
5.1%
다소비 466
 
5.1%
유통식품 299
 
3.3%
계획 230
 
2.5%
등 196
 
2.2%
2021년 196
 
2.2%
Other values (9) 541
 
6.0%

수거증번호
Text

MISSING 

Distinct4002
Distinct (%)82.2%
Missing1153
Missing (%)19.1%
Memory size47.2 KiB
2024-05-10T22:31:26.678992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.7388627
Min length1

Characters and Unicode

Total characters42567
Distinct characters60
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3408 ?
Unique (%)70.0%

Sample

1st row107-3-47
2nd row107-3-48
3rd row107-3-49
4th row107-3-50
5th row107-3-51
ValueCountFrequency (%)
107집 41
 
0.8%
107 11
 
0.2%
107-09-한우1 10
 
0.2%
107-09-한우0 9
 
0.2%
107-09-한우2 8
 
0.2%
107-10-8 6
 
0.1%
107-10-14 5
 
0.1%
107-10-6 5
 
0.1%
107-10-7 5
 
0.1%
107-10-11 4
 
0.1%
Other values (4001) 4831
97.9%
2024-05-10T22:31:27.983388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9362
22.0%
1 7688
18.1%
0 7464
17.5%
2 4300
10.1%
7 3528
 
8.3%
6 2382
 
5.6%
3 1742
 
4.1%
4 1489
 
3.5%
9 1167
 
2.7%
5 1130
 
2.7%
Other values (50) 2315
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31688
74.4%
Dash Punctuation 9362
 
22.0%
Other Letter 1443
 
3.4%
Space Separator 67
 
0.2%
Math Symbol 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 314
21.8%
랑 295
20.4%
식 188
13.0%
방 153
10.6%
집 89
 
6.2%
어 61
 
4.2%
한 36
 
2.5%
구 36
 
2.5%
우 35
 
2.4%
축 29
 
2.0%
Other values (35) 207
14.3%
Decimal Number
ValueCountFrequency (%)
1 7688
24.3%
0 7464
23.6%
2 4300
13.6%
7 3528
11.1%
6 2382
 
7.5%
3 1742
 
5.5%
4 1489
 
4.7%
9 1167
 
3.7%
5 1130
 
3.6%
8 798
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 9362
100.0%
Space Separator
ValueCountFrequency (%)
67
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41124
96.6%
Hangul 1443
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 314
21.8%
랑 295
20.4%
식 188
13.0%
방 153
10.6%
집 89
 
6.2%
어 61
 
4.2%
한 36
 
2.5%
구 36
 
2.5%
우 35
 
2.4%
축 29
 
2.0%
Other values (35) 207
14.3%
Common
ValueCountFrequency (%)
- 9362
22.8%
1 7688
18.7%
0 7464
18.1%
2 4300
10.5%
7 3528
 
8.6%
6 2382
 
5.8%
3 1742
 
4.2%
4 1489
 
3.6%
9 1167
 
2.8%
5 1130
 
2.7%
Other values (5) 872
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41124
96.6%
Hangul 1443
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 9362
22.8%
1 7688
18.7%
0 7464
18.1%
2 4300
10.5%
7 3528
 
8.6%
6 2382
 
5.8%
3 1742
 
4.2%
4 1489
 
3.6%
9 1167
 
2.8%
5 1130
 
2.7%
Other values (5) 872
 
2.1%
Hangul
ValueCountFrequency (%)
중 314
21.8%
랑 295
20.4%
식 188
13.0%
방 153
10.6%
집 89
 
6.2%
어 61
 
4.2%
한 36
 
2.5%
구 36
 
2.5%
우 35
 
2.4%
축 29
 
2.0%
Other values (35) 207
14.3%

수거사유코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
검사용
4505 
<NA>
1517 
압류
 
2

Length

Max length4
Median length3
Mean length3.251494
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 4505
74.8%
<NA> 1517
 
25.2%
압류 2
 
< 0.1%

Length

2024-05-10T22:31:28.369433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:28.720614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 4505
74.8%
na 1517
 
25.2%
압류 2
 
< 0.1%

업소명
Text

Distinct389
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
2024-05-10T22:31:29.252215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length10.229582
Min length2

Characters and Unicode

Total characters61623
Distinct characters429
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)3.2%

Sample

1st row동서울농업협동조합 하나로마트 신내점
2nd row동서울농업협동조합 하나로마트 신내점
3rd row동서울농업협동조합 하나로마트 신내점
4th row동서울농업협동조합 하나로마트 신내점
5th row동서울농업협동조합 하나로마트 신내점
ValueCountFrequency (%)
홈플러스 990
 
10.5%
주)이마트 732
 
7.8%
테스코 696
 
7.4%
신내점 618
 
6.6%
홈플러스(주 517
 
5.5%
홈플러스신내점 483
 
5.1%
홈플러스(주)서울상봉점 463
 
4.9%
동서울농업협동조합 429
 
4.6%
하나로마트 429
 
4.6%
면목점 329
 
3.5%
Other values (427) 3709
39.5%
2024-05-10T22:31:30.318794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 4053
 
6.6%
3371
 
5.5%
( 3134
 
5.1%
) 3134
 
5.1%
주 3095
 
5.0%
점 2906
 
4.7%
홈 2675
 
4.3%
플 2635
 
4.3%
러 2633
 
4.3%
마 2217
 
3.6%
Other values (419) 31770
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51709
83.9%
Space Separator 3371
 
5.5%
Open Punctuation 3134
 
5.1%
Close Punctuation 3134
 
5.1%
Lowercase Letter 139
 
0.2%
Uppercase Letter 79
 
0.1%
Other Punctuation 33
 
0.1%
Decimal Number 18
 
< 0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 4053
 
7.8%
주 3095
 
6.0%
점 2906
 
5.6%
홈 2675
 
5.2%
플 2635
 
5.1%
러 2633
 
5.1%
마 2217
 
4.3%
트 2117
 
4.1%
신 1705
 
3.3%
코 1460
 
2.8%
Other values (377) 26213
50.7%
Uppercase Letter
ValueCountFrequency (%)
K 17
21.5%
O 16
20.3%
B 11
13.9%
S 7
8.9%
L 6
 
7.6%
F 4
 
5.1%
I 3
 
3.8%
G 3
 
3.8%
N 2
 
2.5%
C 2
 
2.5%
Other values (8) 8
10.1%
Lowercase Letter
ValueCountFrequency (%)
e 39
28.1%
r 18
12.9%
a 15
 
10.8%
f 11
 
7.9%
l 11
 
7.9%
d 11
 
7.9%
p 10
 
7.2%
o 7
 
5.0%
i 6
 
4.3%
s 6
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 11
33.3%
& 11
33.3%
' 6
18.2%
; 4
 
12.1%
？ 1
 
3.0%
Decimal Number
ValueCountFrequency (%)
5 7
38.9%
2 6
33.3%
0 3
16.7%
4 2
 
11.1%
Space Separator
ValueCountFrequency (%)
3371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51709
83.9%
Common 9696
 
15.7%
Latin 218
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 4053
 
7.8%
주 3095
 
6.0%
점 2906
 
5.6%
홈 2675
 
5.2%
플 2635
 
5.1%
러 2633
 
5.1%
마 2217
 
4.3%
트 2117
 
4.1%
신 1705
 
3.3%
코 1460
 
2.8%
Other values (377) 26213
50.7%
Latin
ValueCountFrequency (%)
e 39
17.9%
r 18
 
8.3%
K 17
 
7.8%
O 16
 
7.3%
a 15
 
6.9%
f 11
 
5.0%
l 11
 
5.0%
B 11
 
5.0%
d 11
 
5.0%
p 10
 
4.6%
Other values (19) 59
27.1%
Common
ValueCountFrequency (%)
3371
34.8%
( 3134
32.3%
) 3134
32.3%
, 11
 
0.1%
& 11
 
0.1%
5 7
 
0.1%
2 6
 
0.1%
- 6
 
0.1%
' 6
 
0.1%
; 4
 
< 0.1%
Other values (3) 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51709
83.9%
ASCII 9913
 
16.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 4053
 
7.8%
주 3095
 
6.0%
점 2906
 
5.6%
홈 2675
 
5.2%
플 2635
 
5.1%
러 2633
 
5.1%
마 2217
 
4.3%
트 2117
 
4.1%
신 1705
 
3.3%
코 1460
 
2.8%
Other values (377) 26213
50.7%
ASCII
ValueCountFrequency (%)
3371
34.0%
( 3134
31.6%
) 3134
31.6%
e 39
 
0.4%
r 18
 
0.2%
K 17
 
0.2%
O 16
 
0.2%
a 15
 
0.2%
f 11
 
0.1%
l 11
 
0.1%
Other values (31) 147
 
1.5%
None
ValueCountFrequency (%)
？ 1
100.0%

식품군코드
Text

MISSING 

Distinct427
Distinct (%)7.2%
Missing101
Missing (%)1.7%
Memory size47.2 KiB
2024-05-10T22:31:30.808902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length11.14182
Min length1

Characters and Unicode

Total characters65993
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)1.9%

Sample

1st rowC0308040000000
2nd rowC0308030000000
3rd rowC0308030000000
4th rowC0308040000000
5th rowC0308040000000
ValueCountFrequency (%)
801000000 371
 
6.5%
g0100000100000 358
 
6.2%
815000000 310
 
5.4%
829000000 291
 
5.1%
821000000 241
 
4.2%
802000000 151
 
2.6%
816000000 148
 
2.6%
830000000 146
 
2.5%
818000000 146
 
2.5%
c01000000 144
 
2.5%
Other values (415) 3442
59.9%
2024-05-10T22:31:31.745831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44832
67.9%
1 6403
 
9.7%
8 3181
 
4.8%
2 2707
 
4.1%
C 2144
 
3.2%
3 1864
 
2.8%
9 919
 
1.4%
831
 
1.3%
5 702
 
1.1%
4 702
 
1.1%
Other values (9) 1708
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62298
94.4%
Uppercase Letter 2864
 
4.3%
Space Separator 831
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44832
72.0%
1 6403
 
10.3%
8 3181
 
5.1%
2 2707
 
4.3%
3 1864
 
3.0%
9 919
 
1.5%
5 702
 
1.1%
4 702
 
1.1%
6 524
 
0.8%
7 464
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 2144
74.9%
G 418
 
14.6%
B 100
 
3.5%
A 72
 
2.5%
E 56
 
2.0%
F 48
 
1.7%
X 23
 
0.8%
D 3
 
0.1%
Space Separator
ValueCountFrequency (%)
831
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63129
95.7%
Latin 2864
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44832
71.0%
1 6403
 
10.1%
8 3181
 
5.0%
2 2707
 
4.3%
3 1864
 
3.0%
9 919
 
1.5%
831
 
1.3%
5 702
 
1.1%
4 702
 
1.1%
6 524
 
0.8%
Latin
ValueCountFrequency (%)
C 2144
74.9%
G 418
 
14.6%
B 100
 
3.5%
A 72
 
2.5%
E 56
 
2.0%
F 48
 
1.7%
X 23
 
0.8%
D 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65993
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44832
67.9%
1 6403
 
9.7%
8 3181
 
4.8%
2 2707
 
4.1%
C 2144
 
3.2%
3 1864
 
2.8%
9 919
 
1.4%
831
 
1.3%
5 702
 
1.1%
4 702
 
1.1%
Other values (9) 1708
 
2.6%

식품군
Text

MISSING 

Distinct313
Distinct (%)5.6%
Missing438
Missing (%)7.3%
Memory size47.2 KiB
2024-05-10T22:31:32.362543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length33
Mean length4.7010383
Min length1

Characters and Unicode

Total characters26260
Distinct characters317
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)1.3%

Sample

1st row유탕면
2nd row건면
3rd row건면
4th row유탕면
5th row유탕면
ValueCountFrequency (%)
과자류 418
 
6.3%
등 399
 
6.0%
조리식품 358
 
5.4%
면류 312
 
4.7%
기타식품류 302
 
4.5%
조미식품 251
 
3.8%
커피 168
 
2.5%
다류 157
 
2.4%
빵또는떡류 152
 
2.3%
음료류 151
 
2.3%
Other values (332) 3993
59.9%
2024-05-10T22:31:33.354760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 2490
 
9.5%
품 1908
 
7.3%
식 1704
 
6.5%
1075
 
4.1%
가 851
 
3.2%
조 848
 
3.2%
기 778
 
3.0%
공 686
 
2.6%
과 627
 
2.4%
타 554
 
2.1%
Other values (307) 14739
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24604
93.7%
Space Separator 1075
 
4.1%
Other Punctuation 244
 
0.9%
Open Punctuation 133
 
0.5%
Close Punctuation 133
 
0.5%
Uppercase Letter 41
 
0.2%
Lowercase Letter 20
 
0.1%
Decimal Number 7
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 2490
 
10.1%
품 1908
 
7.8%
식 1704
 
6.9%
가 851
 
3.5%
조 848
 
3.4%
기 778
 
3.2%
공 686
 
2.8%
과 627
 
2.5%
타 554
 
2.3%
자 554
 
2.3%
Other values (273) 13604
55.3%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
l 3
15.0%
t 2
10.0%
h 2
10.0%
y 2
10.0%
n 2
10.0%
o 1
 
5.0%
s 1
 
5.0%
u 1
 
5.0%
f 1
 
5.0%
Other values (2) 2
10.0%
Uppercase Letter
ValueCountFrequency (%)
A 12
29.3%
E 6
14.6%
P 5
12.2%
D 5
12.2%
H 5
12.2%
M 3
 
7.3%
C 3
 
7.3%
L 1
 
2.4%
S 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
3 2
28.6%
0 2
28.6%
2 1
14.3%
7 1
14.3%
1 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 120
49.2%
. 113
46.3%
/ 8
 
3.3%
？ 3
 
1.2%
Space Separator
ValueCountFrequency (%)
1075
100.0%
Open Punctuation
ValueCountFrequency (%)
( 133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24604
93.7%
Common 1595
 
6.1%
Latin 61
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 2490
 
10.1%
품 1908
 
7.8%
식 1704
 
6.9%
가 851
 
3.5%
조 848
 
3.4%
기 778
 
3.2%
공 686
 
2.8%
과 627
 
2.5%
타 554
 
2.3%
자 554
 
2.3%
Other values (273) 13604
55.3%
Latin
ValueCountFrequency (%)
A 12
19.7%
E 6
9.8%
P 5
 
8.2%
D 5
 
8.2%
H 5
 
8.2%
M 3
 
4.9%
e 3
 
4.9%
l 3
 
4.9%
C 3
 
4.9%
t 2
 
3.3%
Other values (11) 14
23.0%
Common
ValueCountFrequency (%)
1075
67.4%
( 133
 
8.3%
) 133
 
8.3%
, 120
 
7.5%
. 113
 
7.1%
/ 8
 
0.5%
- 3
 
0.2%
？ 3
 
0.2%
3 2
 
0.1%
0 2
 
0.1%
Other values (3) 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24604
93.7%
ASCII 1653
 
6.3%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 2490
 
10.1%
품 1908
 
7.8%
식 1704
 
6.9%
가 851
 
3.5%
조 848
 
3.4%
기 778
 
3.2%
공 686
 
2.8%
과 627
 
2.5%
타 554
 
2.3%
자 554
 
2.3%
Other values (273) 13604
55.3%
ASCII
ValueCountFrequency (%)
1075
65.0%
( 133
 
8.0%
) 133
 
8.0%
, 120
 
7.3%
. 113
 
6.8%
A 12
 
0.7%
/ 8
 
0.5%
E 6
 
0.4%
P 5
 
0.3%
D 5
 
0.3%
Other values (23) 43
 
2.6%
None
ValueCountFrequency (%)
？ 3
100.0%

품목명
Text

MISSING 

Distinct396
Distinct (%)6.7%
Missing111
Missing (%)1.8%
Memory size47.2 KiB
2024-05-10T22:31:33.916835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length39
Mean length4.927448
Min length1

Characters and Unicode

Total characters29136
Distinct characters367
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)1.7%

Sample

1st row유탕면
2nd row건면
3rd row건면
4th row유탕면
5th row유탕면
ValueCountFrequency (%)
등 445
 
6.2%
조리식품 419
 
5.8%
과자 273
 
3.8%
유탕면류 227
 
3.1%
즉석조리식품 188
 
2.6%
고형차 125
 
1.7%
빵류 122
 
1.7%
과자(비스킷 120
 
1.7%
소스류 118
 
1.6%
기타가공품 109
 
1.5%
Other values (420) 5083
70.3%
2024-05-10T22:31:34.934345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
품 1469
 
5.0%
1316
 
4.5%
류 1280
 
4.4%
식 1168
 
4.0%
조 1012
 
3.5%
가 869
 
3.0%
기 861
 
3.0%
리 779
 
2.7%
유 694
 
2.4%
공 667
 
2.3%
Other values (357) 19021
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26391
90.6%
Space Separator 1316
 
4.5%
Close Punctuation 447
 
1.5%
Open Punctuation 447
 
1.5%
Other Punctuation 395
 
1.4%
Uppercase Letter 54
 
0.2%
Decimal Number 42
 
0.1%
Lowercase Letter 29
 
0.1%
Dash Punctuation 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 1469
 
5.6%
류 1280
 
4.9%
식 1168
 
4.4%
조 1012
 
3.8%
가 869
 
3.3%
기 861
 
3.3%
리 779
 
3.0%
유 694
 
2.6%
공 667
 
2.5%
과 657
 
2.5%
Other values (313) 16935
64.2%
Lowercase Letter
ValueCountFrequency (%)
l 4
13.8%
t 3
10.3%
n 3
10.3%
a 3
10.3%
e 3
10.3%
m 2
6.9%
u 2
6.9%
y 2
6.9%
h 2
6.9%
r 1
 
3.4%
Other values (4) 4
13.8%
Uppercase Letter
ValueCountFrequency (%)
A 11
20.4%
C 10
18.5%
P 6
11.1%
E 6
11.1%
L 5
9.3%
D 4
 
7.4%
H 4
 
7.4%
M 3
 
5.6%
N 2
 
3.7%
B 1
 
1.9%
Other values (2) 2
 
3.7%
Decimal Number
ValueCountFrequency (%)
3 12
28.6%
0 10
23.8%
2 6
14.3%
1 6
14.3%
4 2
 
4.8%
5 2
 
4.8%
7 1
 
2.4%
6 1
 
2.4%
9 1
 
2.4%
8 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 242
61.3%
, 143
36.2%
/ 7
 
1.8%
？ 3
 
0.8%
Space Separator
ValueCountFrequency (%)
1316
100.0%
Close Punctuation
ValueCountFrequency (%)
) 447
100.0%
Open Punctuation
ValueCountFrequency (%)
( 447
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26391
90.6%
Common 2662
 
9.1%
Latin 83
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 1469
 
5.6%
류 1280
 
4.9%
식 1168
 
4.4%
조 1012
 
3.8%
가 869
 
3.3%
기 861
 
3.3%
리 779
 
3.0%
유 694
 
2.6%
공 667
 
2.5%
과 657
 
2.5%
Other values (313) 16935
64.2%
Latin
ValueCountFrequency (%)
A 11
13.3%
C 10
 
12.0%
P 6
 
7.2%
E 6
 
7.2%
L 5
 
6.0%
D 4
 
4.8%
H 4
 
4.8%
l 4
 
4.8%
M 3
 
3.6%
t 3
 
3.6%
Other values (16) 27
32.5%
Common
ValueCountFrequency (%)
1316
49.4%
) 447
 
16.8%
( 447
 
16.8%
. 242
 
9.1%
, 143
 
5.4%
- 15
 
0.6%
3 12
 
0.5%
0 10
 
0.4%
/ 7
 
0.3%
2 6
 
0.2%
Other values (8) 17
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26391
90.6%
ASCII 2742
 
9.4%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
품 1469
 
5.6%
류 1280
 
4.9%
식 1168
 
4.4%
조 1012
 
3.8%
가 869
 
3.3%
기 861
 
3.3%
리 779
 
3.0%
유 694
 
2.6%
공 667
 
2.5%
과 657
 
2.5%
Other values (313) 16935
64.2%
ASCII
ValueCountFrequency (%)
1316
48.0%
) 447
 
16.3%
( 447
 
16.3%
. 242
 
8.8%
, 143
 
5.2%
- 15
 
0.5%
3 12
 
0.4%
A 11
 
0.4%
0 10
 
0.4%
C 10
 
0.4%
Other values (33) 89
 
3.2%
None
ValueCountFrequency (%)
？ 3
100.0%

제품명
Text

Distinct4684
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
2024-05-10T22:31:35.712744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length40
Mean length7.6396082
Min length1

Characters and Unicode

Total characters46021
Distinct characters948
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4000 ?
Unique (%)66.4%

Sample

1st row진라면(순한맛)
2nd row오뚜기 옛날잡채
3rd row멸치칼국수
4th row삼양라면 매운맛
5th row무파마탕면
ValueCountFrequency (%)
한우 68
 
0.8%
커피 64
 
0.7%
청정원 59
 
0.7%
식품자동판매기용 59
 
0.7%
백설 30
 
0.3%
등심 26
 
0.3%
프리미엄 25
 
0.3%
오뚜기 25
 
0.3%
부침가루 25
 
0.3%
만든 23
 
0.3%
Other values (5365) 8641
95.5%
2024-05-10T22:31:37.110270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3030
 
6.6%
스 1171
 
2.5%
리 887
 
1.9%
이 802
 
1.7%
기 707
 
1.5%
고 478
 
1.0%
드 458
 
1.0%
오 442
 
1.0%
치 416
 
0.9%
마 398
 
0.9%
Other values (938) 37232
80.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39245
85.3%
Space Separator 3030
 
6.6%
Uppercase Letter 1559
 
3.4%
Decimal Number 725
 
1.6%
Lowercase Letter 643
 
1.4%
Close Punctuation 286
 
0.6%
Open Punctuation 285
 
0.6%
Other Punctuation 188
 
0.4%
Dash Punctuation 42
 
0.1%
Math Symbol 12
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1171
 
3.0%
리 887
 
2.3%
이 802
 
2.0%
기 707
 
1.8%
고 478
 
1.2%
드 458
 
1.2%
오 442
 
1.1%
치 416
 
1.1%
마 398
 
1.0%
미 397
 
1.0%
Other values (856) 33089
84.3%
Uppercase Letter
ValueCountFrequency (%)
E 148
 
9.5%
I 125
 
8.0%
C 114
 
7.3%
A 110
 
7.1%
O 109
 
7.0%
L 93
 
6.0%
S 88
 
5.6%
T 84
 
5.4%
N 83
 
5.3%
M 80
 
5.1%
Other values (16) 525
33.7%
Lowercase Letter
ValueCountFrequency (%)
e 67
 
10.4%
i 60
 
9.3%
a 60
 
9.3%
m 53
 
8.2%
o 47
 
7.3%
t 41
 
6.4%
l 39
 
6.1%
u 38
 
5.9%
r 35
 
5.4%
p 34
 
5.3%
Other values (14) 169
26.3%
Other Punctuation
ValueCountFrequency (%)
. 43
22.9%
% 33
17.6%
, 29
15.4%
& 26
13.8%
？ 14
 
7.4%
; 12
 
6.4%
/ 11
 
5.9%
! 6
 
3.2%
? 6
 
3.2%
' 5
 
2.7%
Other values (2) 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 178
24.6%
0 152
21.0%
2 134
18.5%
3 108
14.9%
5 31
 
4.3%
9 31
 
4.3%
7 26
 
3.6%
4 23
 
3.2%
6 22
 
3.0%
8 20
 
2.8%
Math Symbol
ValueCountFrequency (%)
+ 11
91.7%
~ 1
 
8.3%
Other Number
ValueCountFrequency (%)
② 2
50.0%
① 2
50.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
3030
100.0%
Close Punctuation
ValueCountFrequency (%)
) 286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39237
85.3%
Common 4572
 
9.9%
Latin 2204
 
4.8%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1171
 
3.0%
리 887
 
2.3%
이 802
 
2.0%
기 707
 
1.8%
고 478
 
1.2%
드 458
 
1.2%
오 442
 
1.1%
치 416
 
1.1%
마 398
 
1.0%
미 397
 
1.0%
Other values (848) 33081
84.3%
Latin
ValueCountFrequency (%)
E 148
 
6.7%
I 125
 
5.7%
C 114
 
5.2%
A 110
 
5.0%
O 109
 
4.9%
L 93
 
4.2%
S 88
 
4.0%
T 84
 
3.8%
N 83
 
3.8%
M 80
 
3.6%
Other values (42) 1170
53.1%
Common
ValueCountFrequency (%)
3030
66.3%
) 286
 
6.3%
( 285
 
6.2%
1 178
 
3.9%
0 152
 
3.3%
2 134
 
2.9%
3 108
 
2.4%
. 43
 
0.9%
- 42
 
0.9%
% 33
 
0.7%
Other values (20) 281
 
6.1%
Han
ValueCountFrequency (%)
新 1
12.5%
大 1
12.5%
生 1
12.5%
鋪 1
12.5%
金 1
12.5%
藥 1
12.5%
秀 1
12.5%
酒 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39236
85.3%
ASCII 6754
 
14.7%
None 16
 
< 0.1%
CJK 8
 
< 0.1%
Enclosed Alphanum 4
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3030
44.9%
) 286
 
4.2%
( 285
 
4.2%
1 178
 
2.6%
0 152
 
2.3%
E 148
 
2.2%
2 134
 
2.0%
I 125
 
1.9%
C 114
 
1.7%
A 110
 
1.6%
Other values (66) 2192
32.5%
Hangul
ValueCountFrequency (%)
스 1171
 
3.0%
리 887
 
2.3%
이 802
 
2.0%
기 707
 
1.8%
고 478
 
1.2%
드 458
 
1.2%
오 442
 
1.1%
치 416
 
1.1%
마 398
 
1.0%
미 397
 
1.0%
Other values (847) 33080
84.3%
None
ValueCountFrequency (%)
？ 14
87.5%
＆ 2
 
12.5%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
50.0%
① 2
50.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%
CJK
ValueCountFrequency (%)
新 1
12.5%
大 1
12.5%
生 1
12.5%
鋪 1
12.5%
金 1
12.5%
藥 1
12.5%
秀 1
12.5%
酒 1
12.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

음식물명
Text

MISSING 

Distinct64
Distinct (%)75.3%
Missing5939
Missing (%)98.6%
Memory size47.2 KiB
2024-05-10T22:31:37.608354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5
Min length1

Characters and Unicode

Total characters425
Distinct characters158
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)58.8%

Sample

1st row햄버거
2nd row햄버거
3rd row햄버거
4th row햄버거
5th row숙주나물(무농약 친환경)
ValueCountFrequency (%)
한우 30
25.4%
햄버거 5
 
4.2%
등심 4
 
3.4%
갈비살 3
 
2.5%
치마살 3
 
2.5%
친환경 3
 
2.5%
부채살 2
 
1.7%
순대 2
 
1.7%
쇠고기 2
 
1.7%
업진살 2
 
1.7%
Other values (56) 62
52.5%
2024-05-10T22:31:38.599194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
우 33
 
7.8%
33
 
7.8%
한 31
 
7.3%
살 19
 
4.5%
치 12
 
2.8%
심 7
 
1.6%
김 7
 
1.6%
물 6
 
1.4%
등 6
 
1.4%
햄 5
 
1.2%
Other values (148) 266
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 384
90.4%
Space Separator 33
 
7.8%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Decimal Number 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 33
 
8.6%
한 31
 
8.1%
살 19
 
4.9%
치 12
 
3.1%
심 7
 
1.8%
김 7
 
1.8%
물 6
 
1.6%
등 6
 
1.6%
햄 5
 
1.3%
버 5
 
1.3%
Other values (143) 253
65.9%
Decimal Number
ValueCountFrequency (%)
8 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 384
90.4%
Common 41
 
9.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 33
 
8.6%
한 31
 
8.1%
살 19
 
4.9%
치 12
 
3.1%
심 7
 
1.8%
김 7
 
1.8%
물 6
 
1.6%
등 6
 
1.6%
햄 5
 
1.3%
버 5
 
1.3%
Other values (143) 253
65.9%
Common
ValueCountFrequency (%)
33
80.5%
) 3
 
7.3%
( 3
 
7.3%
8 1
 
2.4%
0 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 384
90.4%
ASCII 41
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
우 33
 
8.6%
한 31
 
8.1%
살 19
 
4.9%
치 12
 
3.1%
심 7
 
1.8%
김 7
 
1.8%
물 6
 
1.6%
등 6
 
1.6%
햄 5
 
1.3%
버 5
 
1.3%
Other values (143) 253
65.9%
ASCII
ValueCountFrequency (%)
33
80.5%
) 3
 
7.3%
( 3
 
7.3%
8 1
 
2.4%
0 1
 
2.4%

원료명
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
5990 
콩
 
7
빵
 
5
조리기구
 
4
갈비살
 
3
Other values (12)
 
15

Length

Max length4
Median length4
Mean length3.9908699
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5990
99.4%
콩 7
 
0.1%
빵 5
 
0.1%
조리기구 4
 
0.1%
갈비살 3
 
< 0.1%
닭고기 2
 
< 0.1%
쇠고기 2
 
< 0.1%
행주 2
 
< 0.1%
시금치 1
 
< 0.1%
식용유 1
 
< 0.1%
Other values (7) 7
 
0.1%

Length

2024-05-10T22:31:38.907079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5990
99.4%
콩 7
 
0.1%
빵 5
 
0.1%
조리기구 4
 
0.1%
갈비살 3
 
< 0.1%
닭고기 2
 
< 0.1%
쇠고기 2
 
< 0.1%
행주 2
 
< 0.1%
등심 1
 
< 0.1%
앞다리 1
 
< 0.1%
Other values (7) 7
 
0.1%

생산업소
Text

MISSING 

Distinct44
Distinct (%)71.0%
Missing5962
Missing (%)99.0%
Memory size47.2 KiB
2024-05-10T22:31:39.399049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.3548387
Min length2

Characters and Unicode

Total characters518
Distinct characters148
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

Unique31 ?
Unique (%)50.0%

Sample

1st row(주)씨엔비위즈
2nd row롯데리아중화역점
3rd row롯데리아중화역점
4th row버거킹먹골역점
5th row버거킹먹골역점
ValueCountFrequency (%)
중화 4
 
5.2%
정육식당 4
 
5.2%
축산물 4
 
5.2%
코스트코코리아(즉석판매제조가공업소 3
 
3.9%
상봉초등학교 3
 
3.9%
착한정육식당 3
 
3.9%
주 3
 
3.9%
두리푸드(식품제조가공업소 2
 
2.6%
해표 2
 
2.6%
동원f&b 2
 
2.6%
Other values (40) 47
61.0%
2024-05-10T22:31:40.403990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 16
 
3.1%
15
 
2.9%
점 15
 
2.9%
리 14
 
2.7%
) 13
 
2.5%
( 13
 
2.5%
제 12
 
2.3%
중 11
 
2.1%
정 10
 
1.9%
당 10
 
1.9%
Other values (138) 389
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 433
83.6%
Lowercase Letter 32
 
6.2%
Space Separator 15
 
2.9%
Close Punctuation 13
 
2.5%
Open Punctuation 13
 
2.5%
Uppercase Letter 7
 
1.4%
Other Punctuation 4
 
0.8%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 16
 
3.7%
점 15
 
3.5%
리 14
 
3.2%
제 12
 
2.8%
중 11
 
2.5%
정 10
 
2.3%
당 10
 
2.3%
육 9
 
2.1%
코 9
 
2.1%
화 9
 
2.1%
Other values (116) 318
73.4%
Lowercase Letter
ValueCountFrequency (%)
s 6
18.8%
i 5
15.6%
o 4
12.5%
f 2
 
6.2%
g 2
 
6.2%
n 2
 
6.2%
d 2
 
6.2%
b 2
 
6.2%
t 2
 
6.2%
h 2
 
6.2%
Other values (3) 3
9.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
F 2
28.6%
S 1
 
14.3%
M 1
 
14.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 433
83.6%
Common 46
 
8.9%
Latin 39
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 16
 
3.7%
점 15
 
3.5%
리 14
 
3.2%
제 12
 
2.8%
중 11
 
2.5%
정 10
 
2.3%
당 10
 
2.3%
육 9
 
2.1%
코 9
 
2.1%
화 9
 
2.1%
Other values (116) 318
73.4%
Latin
ValueCountFrequency (%)
s 6
15.4%
i 5
12.8%
o 4
10.3%
B 3
 
7.7%
f 2
 
5.1%
g 2
 
5.1%
n 2
 
5.1%
d 2
 
5.1%
b 2
 
5.1%
t 2
 
5.1%
Other values (7) 9
23.1%
Common
ValueCountFrequency (%)
15
32.6%
) 13
28.3%
( 13
28.3%
& 4
 
8.7%
2 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 433
83.6%
ASCII 85
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 16
 
3.7%
점 15
 
3.5%
리 14
 
3.2%
제 12
 
2.8%
중 11
 
2.5%
정 10
 
2.3%
당 10
 
2.3%
육 9
 
2.1%
코 9
 
2.1%
화 9
 
2.1%
Other values (116) 318
73.4%
ASCII
ValueCountFrequency (%)
15
17.6%
) 13
15.3%
( 13
15.3%
s 6
 
7.1%
i 5
 
5.9%
o 4
 
4.7%
& 4
 
4.7%
B 3
 
3.5%
f 2
 
2.4%
g 2
 
2.4%
Other values (12) 18
21.2%

수거일자
Real number (ℝ)

Distinct294
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20148732
Minimum20011009
Maximum20240312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:40.798313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011009
5-th percentile20090324
Q120110620
median20151110
Q320180914
95-th percentile20230829
Maximum20240312
Range229303
Interquartile range (IQR)70294

Descriptive statistics

Standard deviation43230.739
Coefficient of variation (CV)0.0021455811
Kurtosis-0.86665898
Mean20148732
Median Absolute Deviation (MAD)30697
Skewness0.28357817
Sum1.2137596 × 1011
Variance1.8688968 × 109
MonotonicityDecreasing
2024-05-10T22:31:41.402946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090324 145
 
2.4%
20121030 118
 
2.0%
20151110 115
 
1.9%
20121214 113
 
1.9%
20091211 111
 
1.8%
20120413 111
 
1.8%
20100318 110
 
1.8%
20151116 104
 
1.7%
20101130 100
 
1.7%
20170915 93
 
1.5%
Other values (284) 4904
81.4%
ValueCountFrequency (%)
20011009 1
< 0.1%
20011129 2
< 0.1%
20050512 1
< 0.1%
20050610 1
< 0.1%
20050624 1
< 0.1%
20050726 1
< 0.1%
20050902 1
< 0.1%
20051006 2
< 0.1%
20051018 1
< 0.1%
20060727 1
< 0.1%
ValueCountFrequency (%)
20240312 28
0.5%
20240307 1
 
< 0.1%
20240305 25
0.4%
20240304 3
 
< 0.1%
20240228 1
 
< 0.1%
20240227 43
0.7%
20240119 3
 
< 0.1%
20240118 4
 
0.1%
20240115 59
1.0%
20240105 36
0.6%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct45
Distinct (%)0.8%
Missing175
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean5.3777227
Minimum0.3
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:41.834917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile1
Q11
median2
Q34
95-th percentile7
Maximum1000
Range999.7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation41.446514
Coefficient of variation (CV)7.7070754
Kurtosis523.07135
Mean5.3777227
Median Absolute Deviation (MAD)1
Skewness22.430866
Sum31454.3
Variance1717.8135
MonotonicityNot monotonic
2024-05-10T22:31:42.374198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1.0 1830
30.4%
2.0 1192
19.8%
3.0 1036
17.2%
6.0 782
13.0%
4.0 368
 
6.1%
5.0 327
 
5.4%
7.0 58
 
1.0%
8.0 57
 
0.9%
10.0 41
 
0.7%
12.0 23
 
0.4%
Other values (35) 135
 
2.2%
(Missing) 175
 
2.9%
ValueCountFrequency (%)
0.3 1
 
< 0.1%
1.0 1830
30.4%
2.0 1192
19.8%
3.0 1036
17.2%
4.0 368
 
6.1%
5.0 327
 
5.4%
6.0 782
13.0%
7.0 58
 
1.0%
8.0 57
 
0.9%
9.0 20
 
0.3%
ValueCountFrequency (%)
1000.0 9
0.1%
600.0 2
 
< 0.1%
204.0 1
 
< 0.1%
200.0 6
0.1%
150.0 1
 
< 0.1%
125.0 1
 
< 0.1%
100.0 1
 
< 0.1%
80.0 1
 
< 0.1%
70.0 1
 
< 0.1%
64.0 1
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct559
Distinct (%)11.9%
Missing1327
Missing (%)22.0%
Memory size47.2 KiB
2024-05-10T22:31:43.105449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.872046
Min length1

Characters and Unicode

Total characters13490
Distinct characters31
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)5.7%

Sample

1st row600
2nd row300
3rd row490
4th row600
5th row488
ValueCountFrequency (%)
1 349
 
7.4%
300 257
 
5.5%
500 240
 
5.1%
200 227
 
4.8%
100 204
 
4.3%
600 189
 
4.0%
900 181
 
3.9%
400 141
 
3.0%
120 122
 
2.6%
250 88
 
1.9%
Other values (545) 2699
57.5%
2024-05-10T22:31:44.164775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5268
39.1%
1 1764
 
13.1%
2 1374
 
10.2%
5 1149
 
8.5%
3 851
 
6.3%
4 610
 
4.5%
6 542
 
4.0%
8 496
 
3.7%
7 404
 
3.0%
9 391
 
2.9%
Other values (21) 641
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12849
95.2%
Lowercase Letter 382
 
2.8%
Other Punctuation 201
 
1.5%
Uppercase Letter 23
 
0.2%
Math Symbol 20
 
0.1%
Other Letter 14
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5268
41.0%
1 1764
 
13.7%
2 1374
 
10.7%
5 1149
 
8.9%
3 851
 
6.6%
4 610
 
4.7%
6 542
 
4.2%
8 496
 
3.9%
7 404
 
3.1%
9 391
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
g 306
80.1%
m 26
 
6.8%
k 22
 
5.8%
l 18
 
4.7%
e 5
 
1.3%
a 5
 
1.3%
Other Letter
ValueCountFrequency (%)
건 5
35.7%
ㅇ 2
 
14.3%
개 2
 
14.3%
반 2
 
14.3%
일 2
 
14.3%
매 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 195
97.0%
* 4
 
2.0%
/ 1
 
0.5%
, 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
L 22
95.7%
K 1
 
4.3%
Math Symbol
ValueCountFrequency (%)
× 19
95.0%
+ 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13071
96.9%
Latin 405
 
3.0%
Hangul 14
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5268
40.3%
1 1764
 
13.5%
2 1374
 
10.5%
5 1149
 
8.8%
3 851
 
6.5%
4 610
 
4.7%
6 542
 
4.1%
8 496
 
3.8%
7 404
 
3.1%
9 391
 
3.0%
Other values (7) 222
 
1.7%
Latin
ValueCountFrequency (%)
g 306
75.6%
m 26
 
6.4%
L 22
 
5.4%
k 22
 
5.4%
l 18
 
4.4%
e 5
 
1.2%
a 5
 
1.2%
K 1
 
0.2%
Hangul
ValueCountFrequency (%)
건 5
35.7%
ㅇ 2
 
14.3%
개 2
 
14.3%
반 2
 
14.3%
일 2
 
14.3%
매 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13457
99.8%
None 19
 
0.1%
Hangul 12
 
0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5268
39.1%
1 1764
 
13.1%
2 1374
 
10.2%
5 1149
 
8.5%
3 851
 
6.3%
4 610
 
4.5%
6 542
 
4.0%
8 496
 
3.7%
7 404
 
3.0%
9 391
 
2.9%
Other values (14) 608
 
4.5%
None
ValueCountFrequency (%)
× 19
100.0%
Hangul
ValueCountFrequency (%)
건 5
41.7%
개 2
 
16.7%
반 2
 
16.7%
일 2
 
16.7%
매 1
 
8.3%
Compat Jamo
ValueCountFrequency (%)
ㅇ 2
100.0%

단위(정량)
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
g
3170 
<NA>
1690 
ML
585 
KG
471 
LT
 
107

Length

Max length4
Median length1
Mean length2.0348606
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 3170
52.6%
<NA> 1690
28.1%
ML 585
 
9.7%
KG 471
 
7.8%
LT 107
 
1.8%
mm 1
 
< 0.1%

Length

2024-05-10T22:31:44.556675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:44.858439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3170
52.6%
na 1690
28.1%
ml 585
 
9.7%
kg 471
 
7.8%
lt 107
 
1.8%
mm 1
 
< 0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
5849 
1개
 
124
2개
 
11
1인분
 
9
스왑1개
 
8
Other values (14)
 
23

Length

Max length19
Median length4
Mean length3.9631474
Min length2

Unique

Unique8 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5849
97.1%
1개 124
 
2.1%
2개 11
 
0.2%
1인분 9
 
0.1%
스왑1개 8
 
0.1%
스왑 2개 4
 
0.1%
검사용 시료채취 3
 
< 0.1%
600ml 2
 
< 0.1%
약300g(2줄) 2
 
< 0.1%
600g 2
 
< 0.1%
Other values (9) 10
 
0.2%

Length

2024-05-10T22:31:45.299320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5849
96.8%
1개 125
 
2.1%
2개 15
 
0.2%
1인분 9
 
0.1%
스왑1개 8
 
0.1%
스왑 4
 
0.1%
시료채취 3
 
< 0.1%
600g 3
 
< 0.1%
검사용 3
 
< 0.1%
600ml 2
 
< 0.1%
Other values (17) 24
 
0.4%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct305
Distinct (%)29.9%
Missing5004
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean20182531
Minimum20001212
Maximum20240304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:45.715912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001212
5-th percentile20130108
Q120170327
median20180706
Q320191070
95-th percentile20240111
Maximum20240304
Range239092
Interquartile range (IQR)20743.5

Descriptive statistics

Standard deviation33035.916
Coefficient of variation (CV)0.001636857
Kurtosis1.1541959
Mean20182531
Median Absolute Deviation (MAD)10381.5
Skewness-0.22775437
Sum2.0586182 × 1010
Variance1.0913718 × 109
MonotonicityNot monotonic
2024-05-10T22:31:46.191709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171123 50
 
0.8%
20240105 36
 
0.6%
20190214 29
 
0.5%
20181026 25
 
0.4%
20190903 25
 
0.4%
20130109 20
 
0.3%
20180914 20
 
0.3%
20170712 18
 
0.3%
20130108 18
 
0.3%
20211122 16
 
0.3%
Other values (295) 763
 
12.7%
(Missing) 5004
83.1%
ValueCountFrequency (%)
20001212 2
< 0.1%
20111229 1
 
< 0.1%
20120105 2
< 0.1%
20120106 1
 
< 0.1%
20120207 4
0.1%
20120227 4
0.1%
20120302 1
 
< 0.1%
20120308 1
 
< 0.1%
20120402 1
 
< 0.1%
20120403 1
 
< 0.1%
ValueCountFrequency (%)
20240304 3
 
< 0.1%
20240227 12
 
0.2%
20240118 4
 
0.1%
20240117 1
 
< 0.1%
20240115 4
 
0.1%
20240112 15
0.2%
20240111 13
 
0.2%
20240110 13
 
0.2%
20240109 14
 
0.2%
20240105 36
0.6%

제조일자(롯트)
Text

MISSING 

Distinct15
Distinct (%)55.6%
Missing5997
Missing (%)99.6%
Memory size47.2 KiB
2024-05-10T22:31:46.538088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.6296296
Min length3

Characters and Unicode

Total characters152
Distinct characters18
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

Unique12 ?
Unique (%)44.4%

Sample

1st row9397
2nd row13920
3rd row12850
4th rowL18346
5th rowL909217
ValueCountFrequency (%)
미기재 10
35.7%
2016.1 3
 
10.7%
2016.10.27 2
 
7.1%
9397 1
 
3.6%
13920 1
 
3.6%
12850 1
 
3.6%
l18346 1
 
3.6%
l909217 1
 
3.6%
000 1
 
3.6%
2015.10 1
 
3.6%
Other values (6) 6
21.4%
2024-05-10T22:31:47.410972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25
16.4%
0 21
13.8%
2 20
13.2%
. 15
9.9%
미 10
 
6.6%
재 10
 
6.6%
기 10
 
6.6%
9 7
 
4.6%
6 7
 
4.6%
7 5
 
3.3%
Other values (8) 22
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98
64.5%
Other Letter 30
 
19.7%
Other Punctuation 16
 
10.5%
Uppercase Letter 7
 
4.6%
Space Separator 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
25.5%
0 21
21.4%
2 20
20.4%
9 7
 
7.1%
6 7
 
7.1%
7 5
 
5.1%
3 5
 
5.1%
8 4
 
4.1%
5 3
 
3.1%
4 1
 
1.0%
Other Letter
ValueCountFrequency (%)
미 10
33.3%
재 10
33.3%
기 10
33.3%
Other Punctuation
ValueCountFrequency (%)
. 15
93.8%
/ 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
L 5
71.4%
M 2
 
28.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 115
75.7%
Hangul 30
 
19.7%
Latin 7
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
21.7%
0 21
18.3%
2 20
17.4%
. 15
13.0%
9 7
 
6.1%
6 7
 
6.1%
7 5
 
4.3%
3 5
 
4.3%
8 4
 
3.5%
5 3
 
2.6%
Other values (3) 3
 
2.6%
Hangul
ValueCountFrequency (%)
미 10
33.3%
재 10
33.3%
기 10
33.3%
Latin
ValueCountFrequency (%)
L 5
71.4%
M 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122
80.3%
Hangul 30
 
19.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25
20.5%
0 21
17.2%
2 20
16.4%
. 15
12.3%
9 7
 
5.7%
6 7
 
5.7%
7 5
 
4.1%
3 5
 
4.1%
L 5
 
4.1%
8 4
 
3.3%
Other values (5) 8
 
6.6%
Hangul
ValueCountFrequency (%)
미 10
33.3%
재 10
33.3%
기 10
33.3%

유통기한(일자)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)38.5%
Missing5998
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1555542.6
Minimum0
Maximum20231011
Zeros10
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:47.782169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q3281.25
95-th percentile15158012
Maximum20231011
Range20231011
Interquartile range (IQR)281.25

Descriptive statistics

Standard deviation5494863.9
Coefficient of variation (CV)3.5324419
Kurtosis10.156267
Mean1555542.6
Median Absolute Deviation (MAD)1
Skewness3.3732437
Sum40444108
Variance3.0193529 × 1013
MonotonicityNot monotonic
2024-05-10T22:31:48.190365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 10
 
0.2%
1 5
 
0.1%
365 3
 
< 0.1%
2 2
 
< 0.1%
20231011 1
 
< 0.1%
20210318 1
 
< 0.1%
30 1
 
< 0.1%
10 1
 
< 0.1%
540 1
 
< 0.1%
1095 1
 
< 0.1%
(Missing) 5998
99.6%
ValueCountFrequency (%)
0 10
0.2%
1 5
0.1%
2 2
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
365 3
 
< 0.1%
540 1
 
< 0.1%
1095 1
 
< 0.1%
20210318 1
 
< 0.1%
20231011 1
 
< 0.1%
ValueCountFrequency (%)
20231011 1
 
< 0.1%
20210318 1
 
< 0.1%
1095 1
 
< 0.1%
540 1
 
< 0.1%
365 3
 
< 0.1%
30 1
 
< 0.1%
10 1
 
< 0.1%
2 2
 
< 0.1%
1 5
0.1%
0 10
0.2%

보관상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
실온
3722 
<NA>
1517 
냉장
644 
냉동
 
131
기타
 
10

Length

Max length4
Median length2
Mean length2.5036521
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 3722
61.8%
<NA> 1517
25.2%
냉장 644
 
10.7%
냉동 131
 
2.2%
기타 10
 
0.2%

Length

2024-05-10T22:31:48.644736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:48.999593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3722
61.8%
na 1517
25.2%
냉장 644
 
10.7%
냉동 131
 
2.2%
기타 10
 
0.2%

바코드번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
6021 
2113017078
 
3

Length

Max length10
Median length4
Mean length4.002988
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> 6021
> 99.9%
2113017078 3
 
< 0.1%

Length

2024-05-10T22:31:49.432620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:49.749503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6021
> 99.9%
2113017078 3
 
< 0.1%

어린이기호식품유형
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing6022
Missing (%)> 99.9%
Memory size47.2 KiB
2024-05-10T22:31:49.954011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row빵류
2nd row김밥
ValueCountFrequency (%)
빵류 1
50.0%
김밥 1
50.0%
2024-05-10T22:31:50.597605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빵 1
25.0%
류 1
25.0%
김 1
25.0%
밥 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빵 1
25.0%
류 1
25.0%
김 1
25.0%
밥 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빵 1
25.0%
류 1
25.0%
김 1
25.0%
밥 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빵 1
25.0%
류 1
25.0%
김 1
25.0%
밥 1
25.0%

검사기관명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
001
3270 
<NA>
2747 
서울시보건환경연구원
 
5
002
 
2

Length

Max length10
Median length3
Mean length3.4618194
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
001 3270
54.3%
<NA> 2747
45.6%
서울시보건환경연구원 5
 
0.1%
002 2
 
< 0.1%

Length

2024-05-10T22:31:51.011290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:51.365413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 3270
54.3%
na 2747
45.6%
서울시보건환경연구원 5
 
0.1%
002 2
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing6018
Missing (%)99.9%
Memory size47.2 KiB
2024-05-10T22:31:51.645849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.3333333
Min length3

Characters and Unicode

Total characters26
Distinct characters13
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

Unique3 ?
Unique (%)50.0%

Sample

1st row국제제과
2nd row은하수산
3rd row은하수산(주)
4th row은하수산
5th row은하수산
ValueCountFrequency (%)
은하수산 3
50.0%
국제제과 1
 
16.7%
은하수산(주 1
 
16.7%
오백집 1
 
16.7%
2024-05-10T22:31:52.558463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 4
15.4%
하 4
15.4%
수 4
15.4%
산 4
15.4%
제 2
7.7%
국 1
 
3.8%
과 1
 
3.8%
( 1
 
3.8%
주 1
 
3.8%
) 1
 
3.8%
Other values (3) 3
11.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
92.3%
Open Punctuation 1
 
3.8%
Close Punctuation 1
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 4
16.7%
하 4
16.7%
수 4
16.7%
산 4
16.7%
제 2
8.3%
국 1
 
4.2%
과 1
 
4.2%
주 1
 
4.2%
오 1
 
4.2%
백 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
92.3%
Common 2
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 4
16.7%
하 4
16.7%
수 4
16.7%
산 4
16.7%
제 2
8.3%
국 1
 
4.2%
과 1
 
4.2%
주 1
 
4.2%
오 1
 
4.2%
백 1
 
4.2%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
92.3%
ASCII 2
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 4
16.7%
하 4
16.7%
수 4
16.7%
산 4
16.7%
제 2
8.3%
국 1
 
4.2%
과 1
 
4.2%
주 1
 
4.2%
오 1
 
4.2%
백 1
 
4.2%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
국내
4380 
국외
1644 

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 4380
72.7%
국외 1644
 
27.3%

Length

2024-05-10T22:31:53.006999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:53.372091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4380
72.7%
국외 1644
 
27.3%

국가명
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
5532 
미국
 
130
중국
 
45
태국
 
29
독일
 
25
Other values (36)
 
263

Length

Max length6
Median length4
Mean length3.8846282
Min length2

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5532
91.8%
미국 130
 
2.2%
중국 45
 
0.7%
태국 29
 
0.5%
독일 25
 
0.4%
영국 25
 
0.4%
일본 24
 
0.4%
이탈리아 23
 
0.4%
스페인 18
 
0.3%
베트남 17
 
0.3%
Other values (31) 156
 
2.6%

Length

2024-05-10T22:31:53.753657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5532
91.8%
미국 130
 
2.2%
중국 47
 
0.8%
태국 29
 
0.5%
독일 25
 
0.4%
영국 25
 
0.4%
일본 24
 
0.4%
이탈리아 23
 
0.4%
스페인 18
 
0.3%
벨기에 17
 
0.3%
Other values (32) 159
 
2.6%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
2864 
1
1942 
2
1218 

Length

Max length4
Median length1
Mean length2.4262948
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2864
47.5%
1 1942
32.2%
2 1218
20.2%

Length

2024-05-10T22:31:54.180035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:54.568130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2864
47.5%
1 1942
32.2%
2 1218
20.2%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)5.5%
Missing3892
Missing (%)64.6%
Infinite0
Infinite (%)0.0%
Mean20175796
Minimum20100115
Maximum20240313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:54.997851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100115
5-th percentile20100903
Q120151215
median20161124
Q320210825
95-th percentile20240118
Maximum20240313
Range140198
Interquartile range (IQR)59610

Descriptive statistics

Standard deviation43144.258
Coefficient of variation (CV)0.0021384166
Kurtosis-0.82433442
Mean20175796
Median Absolute Deviation (MAD)39986
Skewness-0.27241151
Sum4.3014797 × 1010
Variance1.861427 × 109
MonotonicityNot monotonic
2024-05-10T22:31:55.551875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151110 116
 
1.9%
20101102 77
 
1.3%
20160321 76
 
1.3%
20160329 73
 
1.2%
20200624 71
 
1.2%
20151116 63
 
1.0%
20160608 59
 
1.0%
20240115 59
 
1.0%
20160223 59
 
1.0%
20100624 58
 
1.0%
Other values (107) 1421
 
23.6%
(Missing) 3892
64.6%
ValueCountFrequency (%)
20100115 1
 
< 0.1%
20100222 5
 
0.1%
20100226 6
 
0.1%
20100624 58
1.0%
20100719 4
 
0.1%
20100903 55
0.9%
20100915 4
 
0.1%
20101102 77
1.3%
20101104 42
0.7%
20101117 4
 
0.1%
ValueCountFrequency (%)
20240313 1
 
< 0.1%
20240312 27
0.4%
20240308 1
 
< 0.1%
20240305 6
 
0.1%
20240304 22
 
0.4%
20240227 44
0.7%
20240119 3
 
< 0.1%
20240118 4
 
0.1%
20240115 59
1.0%
20240105 36
0.6%

결과회보일자
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)6.5%
Missing4717
Missing (%)78.3%
Infinite0
Infinite (%)0.0%
Mean20173899
Minimum20100308
Maximum20230905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:56.040957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100308
5-th percentile20151201
Q120160307
median20161012
Q320200130
95-th percentile20211012
Maximum20230905
Range130597
Interquartile range (IQR)39823

Descriptive statistics

Standard deviation22565.858
Coefficient of variation (CV)0.001118567
Kurtosis-0.59909154
Mean20173899
Median Absolute Deviation (MAD)9811
Skewness0.39762187
Sum2.6367287 × 1010
Variance5.0921795 × 108
MonotonicityNot monotonic
2024-05-10T22:31:56.453589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151201 115
 
1.9%
20151204 104
 
1.7%
20200709 68
 
1.1%
20160414 64
 
1.1%
20160420 54
 
0.9%
20160307 49
 
0.8%
20180417 44
 
0.7%
20160304 44
 
0.7%
20180626 41
 
0.7%
20180209 41
 
0.7%
Other values (75) 683
 
11.3%
(Missing) 4717
78.3%
ValueCountFrequency (%)
20100308 5
 
0.1%
20110720 2
 
< 0.1%
20110914 4
 
0.1%
20130911 1
 
< 0.1%
20151112 4
 
0.1%
20151123 2
 
< 0.1%
20151201 115
1.9%
20151204 104
1.7%
20151229 24
 
0.4%
20160304 44
 
0.7%
ValueCountFrequency (%)
20230905 1
 
< 0.1%
20220627 1
 
< 0.1%
20220322 9
 
0.1%
20220128 4
 
0.1%
20220124 2
 
< 0.1%
20211206 5
 
0.1%
20211125 12
0.2%
20211110 20
0.3%
20211013 1
 
< 0.1%
20211012 23
0.4%

판정구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
4601 
1
1401 
2
 
22

Length

Max length4
Median length4
Mean length3.2913347
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> 4601
76.4%
1 1401
 
23.3%
2 22
 
0.4%

Length

2024-05-10T22:31:56.955884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:57.217838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4601
76.4%
1 1401
 
23.3%
2 22
 
0.4%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

처리결과
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
6017 
시험을 확인함
 
5
서울특별시보건환경연구원 식품의약품부-15287(2016.12.13.)호
 
1
90/100(측정치/기준치)
 
1

Length

Max length39
Median length4
Mean length4.0101262
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> 6017
99.9%
시험을 확인함 5
 
0.1%
서울특별시보건환경연구원 식품의약품부-15287(2016.12.13.)호 1
 
< 0.1%
90/100(측정치/기준치) 1
 
< 0.1%

Length

2024-05-10T22:31:57.566775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:57.901606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6017
99.8%
시험을 5
 
0.1%
확인함 5
 
0.1%
서울특별시보건환경연구원 1
 
< 0.1%
식품의약품부-15287(2016.12.13.)호 1
 
< 0.1%
90/100(측정치/기준치 1
 
< 0.1%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

교부번호
Real number (ℝ)

Distinct384
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0053918 × 1010
Minimum1.9820046 × 1010
Maximum2.0230062 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:31:58.244201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9820046 × 1010
5-th percentile1.9990047 × 1010
Q12.0000046 × 1010
median2.0050047 × 1010
Q32.0100046 × 1010
95-th percentile2.0140046 × 1010
Maximum2.0230062 × 1010
Range4.1001639 × 108
Interquartile range (IQR)99999739

Descriptive statistics

Standard deviation59138634
Coefficient of variation (CV)0.0029489816
Kurtosis-0.64748752
Mean2.0053918 × 1010
Median Absolute Deviation (MAD)50000297
Skewness0.2823746
Sum1.208048 × 1014
Variance3.497378 × 1015
MonotonicityNot monotonic
2024-05-10T22:31:58.723037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19990047054 1025
17.0%
20060046520 647
 
10.7%
20000046318 614
 
10.2%
20130046624 463
 
7.7%
20100046055 415
 
6.9%
20110046018 306
 
5.1%
20050046352 249
 
4.1%
20140046147 188
 
3.1%
20010046240 186
 
3.1%
20050046615 161
 
2.7%
Other values (374) 1770
29.4%
ValueCountFrequency (%)
19820046007 1
 
< 0.1%
19830046041 5
0.1%
19880046124 7
0.1%
19890046369 1
 
< 0.1%
19910046079 1
 
< 0.1%
19910046388 1
 
< 0.1%
19910046658 1
 
< 0.1%
19930046217 2
 
< 0.1%
19930046233 1
 
< 0.1%
19930046285 1
 
< 0.1%
ValueCountFrequency (%)
20230062395 1
 
< 0.1%
20230062285 4
0.1%
20230062084 1
 
< 0.1%
20220055064 4
0.1%
20220054971 3
< 0.1%
20220054848 1
 
< 0.1%
20220054810 6
0.1%
20220054329 1
 
< 0.1%
20220054129 1
 
< 0.1%
20210047139 3
< 0.1%

폐기일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
6022 
20080131
 
2

Length

Max length8
Median length4
Mean length4.001328
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> 6022
> 99.9%
20080131 2
 
< 0.1%

Length

2024-05-10T22:31:59.100019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:31:59.398482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6022
> 99.9%
20080131 2
 
< 0.1%

폐기량(Kg)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
<NA>
6022 
26
 
2

Length

Max length4
Median length4
Mean length3.999336
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> 6022
> 99.9%
26 2
 
< 0.1%

Length

2024-05-10T22:31:59.871237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:32:00.208231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6022
> 99.9%
26 2
 
< 0.1%

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

소재지(도로명)
Text

MISSING 

Distinct331
Distinct (%)6.2%
Missing673
Missing (%)11.2%
Memory size47.2 KiB
2024-05-10T22:32:00.718850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length50
Mean length29.420295
Min length22

Characters and Unicode

Total characters157428
Distinct characters163
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

Unique160 ?
Unique (%)3.0%

Sample

1st row서울특별시 중랑구 신내로 74, (신내동,1층, 2층)
2nd row서울특별시 중랑구 신내로 74, (신내동,1층, 2층)
3rd row서울특별시 중랑구 신내로 74, (신내동,1층, 2층)
4th row서울특별시 중랑구 신내로 74, (신내동,1층, 2층)
5th row서울특별시 중랑구 신내로 74, (신내동,1층, 2층)
ValueCountFrequency (%)
서울특별시 5351
17.5%
중랑구 5351
17.5%
면목동 1146
 
3.7%
신내로 1129
 
3.7%
동일로 869
 
2.8%
상봉동 859
 
2.8%
망우동 837
 
2.7%
2층 752
 
2.5%
망우로 719
 
2.3%
상봉로 659
 
2.2%
Other values (437) 12958
42.3%
2024-05-10T22:32:01.752958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25280
 
16.1%
, 8429
 
5.4%
동 6394
 
4.1%
1 5835
 
3.7%
중 5727
 
3.6%
랑 5495
 
3.5%
시 5428
 
3.4%
구 5373
 
3.4%
) 5372
 
3.4%
( 5372
 
3.4%
Other values (153) 78723
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92451
58.7%
Space Separator 25280
 
16.1%
Decimal Number 20371
 
12.9%
Other Punctuation 8434
 
5.4%
Close Punctuation 5372
 
3.4%
Open Punctuation 5372
 
3.4%
Dash Punctuation 121
 
0.1%
Uppercase Letter 20
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6394
 
6.9%
중 5727
 
6.2%
랑 5495
 
5.9%
시 5428
 
5.9%
구 5373
 
5.8%
서 5352
 
5.8%
울 5352
 
5.8%
별 5351
 
5.8%
특 5351
 
5.8%
로 5331
 
5.8%
Other values (130) 37297
40.3%
Decimal Number
ValueCountFrequency (%)
1 5835
28.6%
2 2984
14.6%
3 2439
12.0%
4 1827
 
9.0%
5 1679
 
8.2%
6 1443
 
7.1%
7 1220
 
6.0%
0 1158
 
5.7%
8 1154
 
5.7%
9 632
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 13
65.0%
A 2
 
10.0%
S 2
 
10.0%
E 2
 
10.0%
C 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 8429
99.9%
@ 3
 
< 0.1%
? 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
25280
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92451
58.7%
Common 64957
41.3%
Latin 20
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6394
 
6.9%
중 5727
 
6.2%
랑 5495
 
5.9%
시 5428
 
5.9%
구 5373
 
5.8%
서 5352
 
5.8%
울 5352
 
5.8%
별 5351
 
5.8%
특 5351
 
5.8%
로 5331
 
5.8%
Other values (130) 37297
40.3%
Common
ValueCountFrequency (%)
25280
38.9%
, 8429
 
13.0%
1 5835
 
9.0%
) 5372
 
8.3%
( 5372
 
8.3%
2 2984
 
4.6%
3 2439
 
3.8%
4 1827
 
2.8%
5 1679
 
2.6%
6 1443
 
2.2%
Other values (8) 4297
 
6.6%
Latin
ValueCountFrequency (%)
B 13
65.0%
A 2
 
10.0%
S 2
 
10.0%
E 2
 
10.0%
C 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92451
58.7%
ASCII 64977
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25280
38.9%
, 8429
 
13.0%
1 5835
 
9.0%
) 5372
 
8.3%
( 5372
 
8.3%
2 2984
 
4.6%
3 2439
 
3.8%
4 1827
 
2.8%
5 1679
 
2.6%
6 1443
 
2.2%
Other values (13) 4317
 
6.6%
Hangul
ValueCountFrequency (%)
동 6394
 
6.9%
중 5727
 
6.2%
랑 5495
 
5.9%
시 5428
 
5.9%
구 5373
 
5.8%
서 5352
 
5.8%
울 5352
 
5.8%
별 5351
 
5.8%
특 5351
 
5.8%
로 5331
 
5.8%
Other values (130) 37297
40.3%

소재지(지번)
Text

MISSING 

Distinct375
Distinct (%)6.3%
Missing104
Missing (%)1.7%
Memory size47.2 KiB
2024-05-10T22:32:02.511142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length46
Mean length27.698649
Min length20

Characters and Unicode

Total characters163976
Distinct characters134
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

Unique188 ?
Unique (%)3.2%

Sample

1st row서울특별시 중랑구 신내동 562번지 1층, 2층
2nd row서울특별시 중랑구 신내동 562번지 1층, 2층
3rd row서울특별시 중랑구 신내동 562번지 1층, 2층
4th row서울특별시 중랑구 신내동 562번지 1층, 2층
5th row서울특별시 중랑구 신내동 562번지 1층, 2층
ValueCountFrequency (%)
서울특별시 5920
17.9%
중랑구 5920
17.9%
신내동 1727
 
5.2%
면목동 1654
 
5.0%
1호 1563
 
4.7%
2호 1112
 
3.4%
168번지 1032
 
3.1%
망우동 1026
 
3.1%
상봉동 790
 
2.4%
2층 766
 
2.3%
Other values (423) 11572
35.0%
2024-05-10T22:32:03.678194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42556
26.0%
지 7358
 
4.5%
1 7251
 
4.4%
중 6148
 
3.7%
시 6084
 
3.7%
동 6038
 
3.7%
구 5941
 
3.6%
서 5922
 
3.6%
울 5922
 
3.6%
랑 5920
 
3.6%
Other values (124) 64836
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94835
57.8%
Space Separator 42556
26.0%
Decimal Number 25580
 
15.6%
Other Punctuation 767
 
0.5%
Open Punctuation 99
 
0.1%
Close Punctuation 99
 
0.1%
Uppercase Letter 18
 
< 0.1%
Dash Punctuation 16
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 7358
 
7.8%
중 6148
 
6.5%
시 6084
 
6.4%
동 6038
 
6.4%
구 5941
 
6.3%
서 5922
 
6.2%
울 5922
 
6.2%
랑 5920
 
6.2%
별 5920
 
6.2%
번 5920
 
6.2%
Other values (103) 33662
35.5%
Decimal Number
ValueCountFrequency (%)
1 7251
28.3%
2 3390
13.3%
6 3302
12.9%
5 2664
 
10.4%
0 2555
 
10.0%
8 1750
 
6.8%
4 1553
 
6.1%
7 1518
 
5.9%
3 1132
 
4.4%
9 465
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
B 14
77.8%
A 2
 
11.1%
C 1
 
5.6%
S 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 763
99.5%
? 4
 
0.5%
Space Separator
ValueCountFrequency (%)
42556
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94835
57.8%
Common 69123
42.2%
Latin 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 7358
 
7.8%
중 6148
 
6.5%
시 6084
 
6.4%
동 6038
 
6.4%
구 5941
 
6.3%
서 5922
 
6.2%
울 5922
 
6.2%
랑 5920
 
6.2%
별 5920
 
6.2%
번 5920
 
6.2%
Other values (103) 33662
35.5%
Common
ValueCountFrequency (%)
42556
61.6%
1 7251
 
10.5%
2 3390
 
4.9%
6 3302
 
4.8%
5 2664
 
3.9%
0 2555
 
3.7%
8 1750
 
2.5%
4 1553
 
2.2%
7 1518
 
2.2%
3 1132
 
1.6%
Other values (7) 1452
 
2.1%
Latin
ValueCountFrequency (%)
B 14
77.8%
A 2
 
11.1%
C 1
 
5.6%
S 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94835
57.8%
ASCII 69141
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42556
61.5%
1 7251
 
10.5%
2 3390
 
4.9%
6 3302
 
4.8%
5 2664
 
3.9%
0 2555
 
3.7%
8 1750
 
2.5%
4 1553
 
2.2%
7 1518
 
2.2%
3 1132
 
1.6%
Other values (11) 1470
 
2.1%
Hangul
ValueCountFrequency (%)
지 7358
 
7.8%
중 6148
 
6.5%
시 6084
 
6.4%
동 6038
 
6.4%
구 5941
 
6.3%
서 5922
 
6.2%
울 5922
 
6.2%
랑 5920
 
6.2%
별 5920
 
6.2%
번 5920
 
6.2%
Other values (103) 33662
35.5%

업소전화번호
Text

MISSING 

Distinct335
Distinct (%)6.0%
Missing457
Missing (%)7.6%
Memory size47.2 KiB
2024-05-10T22:32:04.324223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.439555
Min length7

Characters and Unicode

Total characters58117
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)3.0%

Sample

1st row02 493 3080
2nd row02 493 3080
3rd row02 493 3080
4th row02 493 3080
5th row02 493 3080
ValueCountFrequency (%)
02 4055
38.1%
4917400 991
 
9.3%
0220248000 647
 
6.1%
4901053 616
 
5.8%
493 526
 
4.9%
3080 415
 
3.9%
4390600 249
 
2.3%
0269228100 219
 
2.1%
0220831052 202
 
1.9%
496 198
 
1.9%
Other values (355) 2537
23.8%
2024-05-10T22:32:05.594545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16303
28.1%
2 9015
15.5%
4 6444
 
11.1%
6374
 
11.0%
9 5220
 
9.0%
3 3964
 
6.8%
1 3279
 
5.6%
8 2690
 
4.6%
5 1987
 
3.4%
7 1623
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51743
89.0%
Space Separator 6374
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16303
31.5%
2 9015
17.4%
4 6444
 
12.5%
9 5220
 
10.1%
3 3964
 
7.7%
1 3279
 
6.3%
8 2690
 
5.2%
5 1987
 
3.8%
7 1623
 
3.1%
6 1218
 
2.4%
Space Separator
ValueCountFrequency (%)
6374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58117
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16303
28.1%
2 9015
15.5%
4 6444
 
11.1%
6374
 
11.0%
9 5220
 
9.0%
3 3964
 
6.8%
1 3279
 
5.6%
8 2690
 
4.6%
5 1987
 
3.4%
7 1623
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16303
28.1%
2 9015
15.5%
4 6444
 
11.1%
6374
 
11.0%
9 5220
 
9.0%
3 3964
 
6.8%
1 3279
 
5.6%
8 2690
 
4.6%
5 1987
 
3.4%
7 1623
 
2.8%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
위생점검(전체)
2617 
<NA>
2425 
수거
728 
위생점검(부분)
 
254

Length

Max length8
Median length4
Mean length5.6646746
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위생점검(전체) 2617
43.4%
<NA> 2425
40.3%
수거 728
 
12.1%
위생점검(부분) 254
 
4.2%

Length

2024-05-10T22:32:05.955921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:32:06.253737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위생점검(전체 2617
43.4%
na 2425
40.3%
수거 728
 
12.1%
위생점검(부분 254
 
4.2%

점검일자
Real number (ℝ)

Distinct298
Distinct (%)4.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean20148941
Minimum20011009
Maximum20240313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size53.1 KiB
2024-05-10T22:32:06.634682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011009
5-th percentile20090324
Q120110620
median20151110
Q320180914
95-th percentile20230829
Maximum20240313
Range229304
Interquartile range (IQR)70294

Descriptive statistics

Standard deviation43125.274
Coefficient of variation (CV)0.0021403246
Kurtosis-0.85357687
Mean20148941
Median Absolute Deviation (MAD)30697
Skewness0.27528209
Sum1.2135707 × 1011
Variance1.8597893 × 109
MonotonicityNot monotonic
2024-05-10T22:32:07.175061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151110 220
 
3.7%
20101130 173
 
2.9%
20090324 145
 
2.4%
20120413 129
 
2.1%
20121030 118
 
2.0%
20091211 111
 
1.8%
20100318 110
 
1.8%
20170915 102
 
1.7%
20130926 97
 
1.6%
20120501 91
 
1.5%
Other values (288) 4727
78.5%
ValueCountFrequency (%)
20011009 1
 
< 0.1%
20011129 2
< 0.1%
20050512 1
 
< 0.1%
20050610 1
 
< 0.1%
20050624 1
 
< 0.1%
20050726 1
 
< 0.1%
20050902 1
 
< 0.1%
20051006 3
< 0.1%
20060727 1
 
< 0.1%
20080123 4
0.1%
ValueCountFrequency (%)
20240313 28
0.5%
20240307 1
 
< 0.1%
20240305 26
0.4%
20240304 2
 
< 0.1%
20240227 44
0.7%
20240119 3
 
< 0.1%
20240118 4
 
0.1%
20240115 59
1.0%
20240105 36
0.6%
20231114 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
수시
2707 
<NA>
2368 
기타
400 
합동
394 
일제
 
155

Length

Max length4
Median length2
Mean length2.7861886
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 2707
44.9%
<NA> 2368
39.3%
기타 400
 
6.6%
합동 394
 
6.5%
일제 155
 
2.6%

Length

2024-05-10T22:32:07.656928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:32:08.025963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 2707
44.9%
na 2368
39.3%
기타 400
 
6.6%
합동 394
 
6.5%
일제 155
 
2.6%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

점검결과코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size47.2 KiB
1
3648 
<NA>
2368 
2
 
8

Length

Max length4
Median length1
Mean length2.1792829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3648
60.6%
<NA> 2368
39.3%
2 8
 
0.1%

Length

2024-05-10T22:32:08.438374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:32:08.844646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3648
60.6%
na 2368
39.3%
2 8
 
0.1%

(구)제조유통기한
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6024
Missing (%)100.0%
Memory size53.1 KiB

(구)제조회사주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing6023
Missing (%)> 99.9%
Memory size47.2 KiB
2024-05-10T22:32:09.156458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters21
Distinct characters17
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

Unique1 ?
Unique (%)100.0%

Sample

1st row충북 청원군 오창읍 과학산업3로 188
ValueCountFrequency (%)
충북 1
20.0%
청원군 1
20.0%
오창읍 1
20.0%
과학산업3로 1
20.0%
188 1
20.0%
2024-05-10T22:32:09.963004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
19.0%
8 2
 
9.5%
과 1
 
4.8%
1 1
 
4.8%
로 1
 
4.8%
3 1
 
4.8%
업 1
 
4.8%
산 1
 
4.8%
학 1
 
4.8%
충 1
 
4.8%
Other values (7) 7
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
61.9%
Space Separator 4
 
19.0%
Decimal Number 4
 
19.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 1
 
7.7%
로 1
 
7.7%
업 1
 
7.7%
산 1
 
7.7%
학 1
 
7.7%
충 1
 
7.7%
북 1
 
7.7%
창 1
 
7.7%
오 1
 
7.7%
군 1
 
7.7%
Other values (3) 3
23.1%
Decimal Number
ValueCountFrequency (%)
8 2
50.0%
1 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
61.9%
Common 8
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 1
 
7.7%
로 1
 
7.7%
업 1
 
7.7%
산 1
 
7.7%
학 1
 
7.7%
충 1
 
7.7%
북 1
 
7.7%
창 1
 
7.7%
오 1
 
7.7%
군 1
 
7.7%
Other values (3) 3
23.1%
Common
ValueCountFrequency (%)
4
50.0%
8 2
25.0%
1 1
 
12.5%
3 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
61.9%
ASCII 8
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
50.0%
8 2
25.0%
1 1
 
12.5%
3 1
 
12.5%
Hangul
ValueCountFrequency (%)
과 1
 
7.7%
로 1
 
7.7%
업 1
 
7.7%
산 1
 
7.7%
학 1
 
7.7%
충 1
 
7.7%
북 1
 
7.7%
창 1
 
7.7%
오 1
 
7.7%
군 1
 
7.7%
Other values (3) 3
23.1%

부적합항목
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing6022
Missing (%)> 99.9%
Memory size47.2 KiB
2024-05-10T22:32:10.330630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7
Min length2

Characters and Unicode

Total characters14
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row히드록시 메틸 푸르푸랄
2nd row성상
ValueCountFrequency (%)
히드록시 1
25.0%
메틸 1
25.0%
푸르푸랄 1
25.0%
성상 1
25.0%
2024-05-10T22:32:11.159125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
14.3%
푸 2
14.3%
히 1
7.1%
드 1
7.1%
록 1
7.1%
시 1
7.1%
메 1
7.1%
틸 1
7.1%
르 1
7.1%
랄 1
7.1%
Other values (2) 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
85.7%
Space Separator 2
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
푸 2
16.7%
히 1
8.3%
드 1
8.3%
록 1
8.3%
시 1
8.3%
메 1
8.3%
틸 1
8.3%
르 1
8.3%
랄 1
8.3%
성 1
8.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
85.7%
Common 2
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
푸 2
16.7%
히 1
8.3%
드 1
8.3%
록 1
8.3%
시 1
8.3%
메 1
8.3%
틸 1
8.3%
르 1
8.3%
랄 1
8.3%
성 1
8.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
85.7%
ASCII 2
 
14.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
푸 2
16.7%
히 1
8.3%
드 1
8.3%
록 1
8.3%
시 1
8.3%
메 1
8.3%
틸 1
8.3%
르 1
8.3%
랄 1
8.3%
성 1
8.3%

기준치부적합내용
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing6022
Missing (%)> 99.9%
Memory size47.2 KiB
2024-05-10T22:32:11.500409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12.5
Mean length12.5
Min length7

Characters and Unicode

Total characters25
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row109.5 / 기준 80.0 이하
2nd row적합하여야한다
ValueCountFrequency (%)
109.5 1
16.7%
1
16.7%
기준 1
16.7%
80.0 1
16.7%
이하 1
16.7%
적합하여야한다 1
16.7%
2024-05-10T22:32:12.322463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
16.0%
0 3
 
12.0%
하 2
 
8.0%
. 2
 
8.0%
1 1
 
4.0%
한 1
 
4.0%
야 1
 
4.0%
여 1
 
4.0%
합 1
 
4.0%
적 1
 
4.0%
Other values (8) 8
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
44.0%
Decimal Number 7
28.0%
Space Separator 4
 
16.0%
Other Punctuation 3
 
12.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
하 2
18.2%
한 1
9.1%
야 1
9.1%
여 1
9.1%
합 1
9.1%
적 1
9.1%
이 1
9.1%
준 1
9.1%
기 1
9.1%
다 1
9.1%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
1 1
 
14.3%
8 1
 
14.3%
5 1
 
14.3%
9 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
하 2
18.2%
한 1
9.1%
야 1
9.1%
여 1
9.1%
합 1
9.1%
적 1
9.1%
이 1
9.1%
준 1
9.1%
기 1
9.1%
다 1
9.1%
Common
ValueCountFrequency (%)
4
28.6%
0 3
21.4%
. 2
14.3%
1 1
 
7.1%
8 1
 
7.1%
/ 1
 
7.1%
5 1
 
7.1%
9 1
 
7.1%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
28.6%
0 3
21.4%
. 2
14.3%
1 1
 
7.1%
8 1
 
7.1%
/ 1
 
7.1%
5 1
 
7.1%
9 1
 
7.1%
Hangul
ValueCountFrequency (%)
하 2
18.2%
한 1
9.1%
야 1
9.1%
여 1
9.1%
합 1
9.1%
적 1
9.1%
이 1
9.1%
준 1
9.1%
기 1
9.1%
다 1
9.1%

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
03060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-47검사용동서울농업협동조합 하나로마트 신내점C0308040000000유탕면유탕면진라면(순한맛)<NA><NA><NA>202403122.0600g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
13060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-48검사용동서울농업협동조합 하나로마트 신내점C0308030000000건면건면오뚜기 옛날잡채<NA><NA><NA>202403122.0300g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
23060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-49검사용동서울농업협동조합 하나로마트 신내점C0308030000000건면건면멸치칼국수<NA><NA><NA>202403122.0490g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
33060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-50검사용동서울농업협동조합 하나로마트 신내점C0308040000000유탕면유탕면삼양라면 매운맛<NA><NA><NA>202403122.0600g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
43060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-51검사용동서울농업협동조합 하나로마트 신내점C0308040000000유탕면유탕면무파마탕면<NA><NA><NA>202403122.0488g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
53060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-52검사용동서울농업협동조합 하나로마트 신내점C0308030000000건면건면생면식감 매운맛<NA><NA><NA>202403122.0383.6g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
63060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-53검사용동서울농업협동조합 하나로마트 신내점C0308040000000유탕면유탕면일품해물라면 누룽지에디션<NA><NA><NA>202403122.0645g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
73060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-54검사용동서울농업협동조합 하나로마트 신내점C0308040000000유탕면유탕면짜슐랭<NA><NA><NA>202403122.0725g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
83060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-32검사용동서울농업협동조합 하나로마트 신내점C0304030200000올리고당가공품올리고당가공품요리올리고당<NA><NA><NA>202403121.01.2KG<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<NA>1<NA><NA><NA><NA>
93060000114기타식품판매업999<NA>식품제조판매업체 지도점검 계획<NA>107-3-31검사용동서울농업협동조합 하나로마트 신내점C0304060100000물엿물엿물엿<NA><NA><NA>202403121.01.2KG<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240312<NA><NA><NA><NA><NA><NA><NA><NA>20100046055<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로 74, (신내동,1층, 2층)서울특별시 중랑구 신내동 562번지 1층, 2층02 493 3080위생점검(전체)20240313수시<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
60143060000114기타식품판매업<NA><NA><NA><NA><NA><NA>먹골할인마트<NA><NA>서울연유외 48개품목<NA><NA><NA>2005100620.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20000046543<NA><NA><NA><NA><NA>서울특별시 중랑구 공릉로2길 7, (묵동,구산빌딩)서울특별시 중랑구 묵동 174번지 4호 구산빌딩02 9492333위생점검(전체)20051006수시<NA>1<NA><NA><NA><NA>
60153060000114기타식품판매업<NA><NA><NA><NA><NA><NA>진로마트<NA><NA>바몬드카레외 10건<NA><NA><NA>2005100610.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20040047145<NA><NA><NA><NA><NA>서울특별시 중랑구 중랑역로 262, (묵동)서울특별시 중랑구 묵동 165번지02 9797881위생점검(전체)20051006수시<NA>1<NA><NA><NA><NA>
60163060000114기타식품판매업<NA><NA><NA><NA><NA><NA>(주)코스트코코리아<NA><NA>종합선물세트외 37건<NA><NA><NA>2005090230.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20010046240<NA><NA><NA><NA><NA>서울특별시 중랑구 망우로 336, (상봉동)서울특별시 중랑구 상봉동 81번지 0호02 4391188수거20050902수시<NA>1<NA><NA><NA><NA>
60173060000114기타식품판매업<NA><NA><NA><NA><NA><NA>서울원예농업협동조합<NA><NA>콘?외 44건<NA><NA><NA>2005072645.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19990046695<NA><NA><NA><NA><NA>서울특별시 중랑구 동일로 842, (묵동)서울특별시 중랑구 묵동 188번지 10호02 9480570수거20050726수시<NA>1<NA><NA><NA><NA>
60183060000114기타식품판매업<NA><NA><NA><NA><NA><NA>수협바다마트신내점<NA><NA>고추참치외 35건<NA><NA><NA>2005062436.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20000046187<NA><NA><NA><NA><NA>서울특별시 중랑구 신내로14길 21, (신내동)서울특별시 중랑구 신내동 797번지 0호0234230100수거20050624수시<NA>1<NA><NA><NA><NA>
60193060000114기타식품판매업<NA><NA><NA><NA><NA><NA>(주)신세계이마트상봉점<NA><NA>'맛소금'외 52개품목<NA><NA><NA>2005061055.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20000046318<NA><NA><NA><NA><NA>서울특별시 중랑구 상봉로 118, (망우동)서울특별시 중랑구 망우동 506번지 1호02 4901053수거20050610수시<NA>1<NA><NA><NA><NA>
60203060000114기타식품판매업<NA><NA><NA><NA><NA><NA>한국까르푸(주)면목지점<NA><NA>'후디스하이키드'외 29개 품목<NA><NA><NA>2005051235.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19990047054<NA><NA><NA><NA><NA><NA>서울특별시 중랑구 면목동 168번지 2호02 4917400수거20050512수시<NA>1<NA><NA><NA><NA>
60213060000101일반음식점<NA><NA><NA><NA><NA><NA>랜드하우스<NA><NA>지하수<NA><NA><NA>200111296.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19970046409<NA><NA><NA><NA><NA><NA>서울특별시 중랑구 망우동 산 69번지 1호02 4952580<NA>20011129수시<NA>2<NA><NA><NA><NA>
60223060000101일반음식점<NA><NA><NA><NA><NA><NA>갓바위식당<NA><NA>먹는물<NA><NA><NA>200111296.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19930046233<NA><NA><NA><NA><NA><NA>서울특별시 중랑구 망우동 69번지 1호02 2085455<NA>20011129수시<NA>2<NA><NA><NA><NA>
60233060000101일반음식점<NA><NA><NA><NA><NA><NA>김밥천국<NA><NA>김밥<NA><NA><NA>200110090.3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>20010046361<NA><NA><NA><NA><NA><NA>서울특별시 중랑구 망우동 410번지 1호02 4947788<NA>20011009기타<NA>2<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호폐기일자폐기량(Kg)소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조회사주소부적합항목기준치부적합내용# duplicates
03060000101일반음식점<NA><NA><NA><NA><NA>영남식당<NA><NA>식용견(식육, 삶은 것)<NA><NA><NA>201006091.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19930046367<NA><NA><NA>서울특별시 중랑구 상봉동 106번지 5호02 4339667수거20100609수시1<NA><NA><NA>2
13060000101일반음식점<NA><NA><NA><NA><NA>육회본좌(묵동점)121000000식육류중육류<NA>원료식육<NA><NA><NA>201002261.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090046679<NA><NA><NA>서울특별시 중랑구 묵동 294번지 6호02 971 1582수거20100226수시1<NA><NA><NA>2
23060000101일반음식점<NA><NA><NA><NA><NA>육회본좌(묵동점)410000000기구류기구류중기타행주<NA><NA><NA>201002261.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090046679<NA><NA><NA>서울특별시 중랑구 묵동 294번지 6호02 971 1582수거20100226수시1<NA><NA><NA>2
33060000101일반음식점<NA><NA><NA><NA><NA>육회본좌(묵동점)829000000기타식품류즉석섭취식품육회<NA><NA><NA>201002261.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090046679<NA><NA><NA>서울특별시 중랑구 묵동 294번지 6호02 971 1582수거20100226수시1<NA><NA><NA>2
43060000101일반음식점<NA><NA><NA><NA><NA>치킨뱅이218000000주류맥주생맥주<NA><NA><NA>201007191.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19930046531<NA><NA><NA>서울특별시 중랑구 면목동 601번지 2호0204940753수거20100719수시1<NA><NA><NA>2
53060000112식품자동판매기영업<NA><NA><NA><NA><NA>코레일유통(주) 중랑역817000000커피액상커피자판기커피(중랑역상행)<NA><NA><NA>200907151.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20060046123<NA><NA>서울특별시 중랑구 중랑역로 9, (중화동)서울특별시 중랑구 중화동 73번지 7호02 9669856<NA>20090715<NA><NA><NA><NA><NA>2
63060000114기타식품판매업<NA><NA>가공식품 관리계획260-12-11검사용(주)이마트815000000면류유탕면류포장마차 우동<NA><NA><NA>201212145.0120g<NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA>20000046318<NA><NA>서울특별시 중랑구 상봉로 118, (망우동)서울특별시 중랑구 망우동 506번지 1호02 4901053<NA>20131214<NA><NA><NA><NA><NA>2
73060000114기타식품판매업<NA><NA>가공식품 관리계획260-12-44검사용(주)이마트827000000주류위스키맥캘란 싱글 몰트 위스키 12년<NA><NA><NA>201212141.0700ML<NA><NA><NA><NA>실온<NA><NA><NA><NA>국외영국<NA><NA><NA><NA><NA>20000046318<NA><NA>서울특별시 중랑구 상봉로 118, (망우동)서울특별시 중랑구 망우동 506번지 1호02 4901053<NA>20131214<NA><NA><NA><NA><NA>2
83060000114기타식품판매업<NA><NA><NA><NA><NA>삼성테스코(주)홈플러스신내점814000000식용유지류압착올리브유압착올리브유<NA><NA><NA>200905073.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20060046520<NA><NA>서울특별시 중랑구 신내로 201, (신내동,지하1층 삼성홈플러스신내점 내)서울특별시 중랑구 신내동 645번지 지하1층 삼성홈플러스신내점 내0220248000위생점검(전체)20090507기타1<NA><NA><NA>2
93060000114기타식품판매업<NA><NA><NA><NA><NA>홈플러스 테스코815000000면류국수홈플러스중면<NA><NA><NA>200912111.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19990047054<NA><NA><NA>서울특별시 중랑구 면목동 168번지 2호02 4917400<NA>20091211<NA><NA><NA><NA><NA>2