Overview

Dataset statistics

Number of variables61
Number of observations5670
Missing cells149743
Missing cells (%)43.3%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory2.8 MiB
Average record size in memory520.0 B

Variable types

Categorical19
Numeric8
Unsupported18
Text16

Dataset

Description시군구코드,업종코드,업종명,계획구분코드,계획구분명,지도점검계획,수거계획,수거증번호,수거사유코드,업소명,식품군코드,식품군,품목명,제품명,음식물명,원료명,생산업소,수거일자,수거량(정량),제품규격(정량),단위(정량),수거량(자유),제조일자(일자),제조일자(롯트),유통기한(일자),유통기한(제조일기준),보관상태코드,바코드번호,어린이기호식품유형,검사기관명,(구)제조사명,내외국산,국가명,검사구분,검사의뢰일자,결과회보일자,판정구분,처리구분,수거검사구분코드,단속지역구분코드,수거장소구분코드,처리결과,수거품처리,교부번호,폐기일자,폐기량(kg),폐기금액(원),폐기장소,폐기방법,소재지(도로명),소재지(지번),업소전화번호,점검목적,점검일자,점검구분,점검내용,점검결과코드,(구)제조유통기한,(구)제조회사주소,부적합항목,기준치부적합내용
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-10223/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 4 (0.1%) duplicate rowsDuplicates
업종명 is highly imbalanced (68.5%)Imbalance
지도점검계획 is highly imbalanced (59.1%)Imbalance
수거계획 is highly imbalanced (56.5%)Imbalance
수거사유코드 is highly imbalanced (75.9%)Imbalance
수거량(자유) is highly imbalanced (94.8%)Imbalance
제조일자(롯트) is highly imbalanced (94.9%)Imbalance
유통기한(제조일기준) is highly imbalanced (96.3%)Imbalance
보관상태코드 is highly imbalanced (57.2%)Imbalance
국가명 is highly imbalanced (86.2%)Imbalance
계획구분명 has 5670 (100.0%) missing valuesMissing
수거증번호 has 616 (10.9%) missing valuesMissing
식품군코드 has 212 (3.7%) missing valuesMissing
식품군 has 846 (14.9%) missing valuesMissing
품목명 has 180 (3.2%) missing valuesMissing
음식물명 has 5619 (99.1%) missing valuesMissing
원료명 has 5668 (> 99.9%) missing valuesMissing
생산업소 has 5031 (88.7%) missing valuesMissing
수거량(정량) has 137 (2.4%) missing valuesMissing
제품규격(정량) has 753 (13.3%) missing valuesMissing
제조일자(일자) has 4820 (85.0%) missing valuesMissing
유통기한(일자) has 5670 (100.0%) missing valuesMissing
바코드번호 has 5670 (100.0%) missing valuesMissing
어린이기호식품유형 has 5670 (100.0%) missing valuesMissing
(구)제조사명 has 5670 (100.0%) missing valuesMissing
검사의뢰일자 has 2401 (42.3%) missing valuesMissing
결과회보일자 has 2719 (48.0%) missing valuesMissing
처리구분 has 5670 (100.0%) missing valuesMissing
수거검사구분코드 has 5670 (100.0%) missing valuesMissing
단속지역구분코드 has 5670 (100.0%) missing valuesMissing
수거장소구분코드 has 5670 (100.0%) missing valuesMissing
처리결과 has 5667 (99.9%) missing valuesMissing
수거품처리 has 5670 (100.0%) missing valuesMissing
폐기일자 has 5670 (100.0%) missing valuesMissing
폐기량(kg) has 5670 (100.0%) missing valuesMissing
폐기금액(원) has 5670 (100.0%) missing valuesMissing
폐기장소 has 5670 (100.0%) missing valuesMissing
폐기방법 has 5670 (100.0%) missing valuesMissing
소재지(도로명) has 808 (14.3%) missing valuesMissing
소재지(지번) has 568 (10.0%) missing valuesMissing
업소전화번호 has 307 (5.4%) missing valuesMissing
점검내용 has 5670 (100.0%) missing valuesMissing
(구)제조유통기한 has 5670 (100.0%) missing valuesMissing
(구)제조회사주소 has 5670 (100.0%) missing valuesMissing
부적합항목 has 5665 (99.9%) missing valuesMissing
기준치부적합내용 has 5666 (99.9%) missing valuesMissing
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
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
어린이기호식품유형 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조사명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조유통기한 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조회사주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 02:19:45.765769
Analysis finished2024-05-11 02:19:50.962419
Duration5.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
3010000
5670 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 5670
100.0%

Length

2024-05-11T02:19:51.101990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:19:51.389878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 5670
100.0%

업종코드
Real number (ℝ)

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.4231
Minimum101
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:19:51.686027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation4.8274143
Coefficient of variation (CV)0.0429397
Kurtosis4.9340152
Mean112.4231
Median Absolute Deviation (MAD)0
Skewness-0.34956651
Sum637439
Variance23.303929
MonotonicityNot monotonic
2024-05-11T02:19:52.095553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
114 4601
81.1%
101 504
 
8.9%
105 151
 
2.7%
104 132
 
2.3%
106 65
 
1.1%
134 64
 
1.1%
107 60
 
1.1%
109 34
 
0.6%
112 30
 
0.5%
121 21
 
0.4%
Other values (3) 8
 
0.1%
ValueCountFrequency (%)
101 504
 
8.9%
104 132
 
2.3%
105 151
 
2.7%
106 65
 
1.1%
107 60
 
1.1%
109 34
 
0.6%
110 1
 
< 0.1%
112 30
 
0.5%
113 5
 
0.1%
114 4601
81.1%
ValueCountFrequency (%)
135 2
 
< 0.1%
134 64
 
1.1%
121 21
 
0.4%
114 4601
81.1%
113 5
 
0.1%
112 30
 
0.5%
110 1
 
< 0.1%
109 34
 
0.6%
107 60
 
1.1%
106 65
 
1.1%

업종명
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
기타식품판매업
4601 
일반음식점
504 
집단급식소
 
151
휴게음식점
 
132
식품제조가공업
 
65
Other values (8)
 
217

Length

Max length13
Median length7
Mean length6.7823633
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 4601
81.1%
일반음식점 504
 
8.9%
집단급식소 151
 
2.7%
휴게음식점 132
 
2.3%
식품제조가공업 65
 
1.1%
건강기능식품일반판매업 64
 
1.1%
즉석판매제조가공업 60
 
1.1%
식품소분업 34
 
0.6%
식품자동판매기영업 30
 
0.5%
제과점영업 21
 
0.4%
Other values (3) 8
 
0.1%

Length

2024-05-11T02:19:52.725574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 4601
81.1%
일반음식점 504
 
8.9%
집단급식소 151
 
2.7%
휴게음식점 132
 
2.3%
식품제조가공업 65
 
1.1%
건강기능식품일반판매업 64
 
1.1%
즉석판매제조가공업 60
 
1.1%
식품소분업 34
 
0.6%
식품자동판매기영업 30
 
0.5%
제과점영업 21
 
0.4%
Other values (4) 9
 
0.2%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
4234 
999
1256 
7
 
180

Length

Max length4
Median length4
Mean length3.6832451
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> 4234
74.7%
999 1256
 
22.2%
7 180
 
3.2%

Length

2024-05-11T02:19:53.245551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:19:53.606043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4234
74.7%
999 1256
 
22.2%
7 180
 
3.2%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
4234 
2016년 가공식품 안전관리 계획
 
397
2020년 식품 제조, 유통 등 안전관리계획
 
356
2021년 식품 제조?유통?판매 등 안전관리계획
 
174
민원신고사항 위생점검
 
136
Other values (8)
 
373

Length

Max length28
Median length4
Mean length7.8469136
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> 4234
74.7%
2016년 가공식품 안전관리 계획 397
 
7.0%
2020년 식품 제조, 유통 등 안전관리계획 356
 
6.3%
2021년 식품 제조?유통?판매 등 안전관리계획 174
 
3.1%
민원신고사항 위생점검 136
 
2.4%
2023년 다소비식품 수거검사 124
 
2.2%
2017년 가공식품 안전관리 계획 104
 
1.8%
식품접객업소 지도점검 79
 
1.4%
2024년 다소비식품 수거검사 56
 
1.0%
2018년 가공식품 안전관리 계획 4
 
0.1%
Other values (3) 6
 
0.1%

Length

2024-05-11T02:19:54.135070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4234
41.3%
식품 531
 
5.2%
531
 
5.2%
안전관리계획 531
 
5.2%
가공식품 509
 
5.0%
안전관리 509
 
5.0%
계획 505
 
4.9%
2016년 397
 
3.9%
제조 357
 
3.5%
유통 357
 
3.5%
Other values (18) 1798
17.5%

수거계획
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
4167 
2013년 가공식품 안전관리 계획
645 
2018년 가공식품 안전관리 계획
487 
2017년 가공식품 안전관리계획
 
155
2015년 가공식품 안전관리 계획(서울특별시 중구)
 
95
Other values (4)
 
121

Length

Max length28
Median length4
Mean length8.0091711
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> 4167
73.5%
2013년 가공식품 안전관리 계획 645
 
11.4%
2018년 가공식품 안전관리 계획 487
 
8.6%
2017년 가공식품 안전관리계획 155
 
2.7%
2015년 가공식품 안전관리 계획(서울특별시 중구) 95
 
1.7%
2020년 식품 제조, 유통 등 안전관리 계획 75
 
1.3%
2014년 가공식품 안전관리 계획(서울특별시 중구) 28
 
0.5%
2013년 추석절 성수식품 수거계획 9
 
0.2%
식중독 예방을 위한 여름철 성수식품 수거검사 계획 9
 
0.2%

Length

2024-05-11T02:19:54.742397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:19:55.263705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4167
40.1%
가공식품 1410
 
13.6%
안전관리 1330
 
12.8%
계획 1216
 
11.7%
2013년 654
 
6.3%
2018년 487
 
4.7%
2017년 155
 
1.5%
안전관리계획 155
 
1.5%
계획(서울특별시 123
 
1.2%
중구 123
 
1.2%
Other values (15) 579
 
5.6%

수거증번호
Text

MISSING 

Distinct3375
Distinct (%)66.8%
Missing616
Missing (%)10.9%
Memory size44.4 KiB
2024-05-11T02:19:56.201391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.8462604
Min length2

Characters and Unicode

Total characters34601
Distinct characters121
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

Unique2335 ?
Unique (%)46.2%

Sample

1st row중구-어린이-2
2nd row중구-어린이-1
3rd row중구-어린이-3
4th row중구-어린이-4
5th row중구-어린이-5
ValueCountFrequency (%)
중구 167
 
3.2%
2-6-1 17
 
0.3%
세꼬시 12
 
0.2%
보원 12
 
0.2%
중구-방사능 11
 
0.2%
중구-2-1 9
 
0.2%
희락 8
 
0.2%
중구-2-2 8
 
0.2%
중구-2-3 7
 
0.1%
중구-2-6 7
 
0.1%
Other values (3294) 5019
95.1%
2024-05-11T02:19:57.602051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 9340
27.0%
1 4553
13.2%
2 4150
12.0%
2785
 
8.0%
2730
 
7.9%
3 1485
 
4.3%
4 1465
 
4.2%
7 1423
 
4.1%
5 1241
 
3.6%
9 1055
 
3.0%
Other values (111) 4374
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18149
52.5%
Dash Punctuation 9340
27.0%
Other Letter 6680
 
19.3%
Space Separator 223
 
0.6%
Uppercase Letter 105
 
0.3%
Open Punctuation 50
 
0.1%
Close Punctuation 50
 
0.1%
Math Symbol 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2785
41.7%
2730
40.9%
105
 
1.6%
68
 
1.0%
50
 
0.7%
46
 
0.7%
46
 
0.7%
46
 
0.7%
42
 
0.6%
34
 
0.5%
Other values (90) 728
 
10.9%
Decimal Number
ValueCountFrequency (%)
1 4553
25.1%
2 4150
22.9%
3 1485
 
8.2%
4 1465
 
8.1%
7 1423
 
7.8%
5 1241
 
6.8%
9 1055
 
5.8%
6 974
 
5.4%
0 974
 
5.4%
8 829
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
O 35
33.3%
G 35
33.3%
M 35
33.3%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 9340
100.0%
Space Separator
ValueCountFrequency (%)
223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27816
80.4%
Hangul 6680
 
19.3%
Latin 105
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2785
41.7%
2730
40.9%
105
 
1.6%
68
 
1.0%
50
 
0.7%
46
 
0.7%
46
 
0.7%
46
 
0.7%
42
 
0.6%
34
 
0.5%
Other values (90) 728
 
10.9%
Common
ValueCountFrequency (%)
- 9340
33.6%
1 4553
16.4%
2 4150
14.9%
3 1485
 
5.3%
4 1465
 
5.3%
7 1423
 
5.1%
5 1241
 
4.5%
9 1055
 
3.8%
6 974
 
3.5%
0 974
 
3.5%
Other values (8) 1156
 
4.2%
Latin
ValueCountFrequency (%)
O 35
33.3%
G 35
33.3%
M 35
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27920
80.7%
Hangul 6680
 
19.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 9340
33.5%
1 4553
16.3%
2 4150
14.9%
3 1485
 
5.3%
4 1465
 
5.2%
7 1423
 
5.1%
5 1241
 
4.4%
9 1055
 
3.8%
6 974
 
3.5%
0 974
 
3.5%
Other values (10) 1260
 
4.5%
Hangul
ValueCountFrequency (%)
2785
41.7%
2730
40.9%
105
 
1.6%
68
 
1.0%
50
 
0.7%
46
 
0.7%
46
 
0.7%
46
 
0.7%
42
 
0.6%
34
 
0.5%
Other values (90) 728
 
10.9%
None
ValueCountFrequency (%)
1
100.0%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
검사용
4983 
<NA>
666 
기타
 
18
증거용
 
2
압류
 
1

Length

Max length4
Median length3
Mean length3.1141093
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 4983
87.9%
<NA> 666
 
11.7%
기타 18
 
0.3%
증거용 2
 
< 0.1%
압류 1
 
< 0.1%

Length

2024-05-11T02:19:58.332600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:19:58.909570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 4983
87.9%
na 666
 
11.7%
기타 18
 
0.3%
증거용 2
 
< 0.1%
압류 1
 
< 0.1%
Distinct339
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-05-11T02:19:59.716016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length9.9552028
Min length2

Characters and Unicode

Total characters56446
Distinct characters412
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)2.9%

Sample

1st row지에스25 신당장충
2nd row지에스25 신당장충
3rd row지에스25 신당장충
4th row지에스25 신당장충
5th row지에스25 신당장충
ValueCountFrequency (%)
청계천점 1527
19.0%
주)이마트 1526
19.0%
롯데쇼핑(주)롯데마트서울역점 652
 
8.1%
신세계백화점 441
 
5.5%
롯데쇼핑(주 299
 
3.7%
태양마트 299
 
3.7%
gs수퍼(남산타운점 198
 
2.5%
상쾌한할인마트 149
 
1.9%
신당점 147
 
1.8%
롯데쇼핑(주)롯데슈퍼 143
 
1.8%
Other values (405) 2653
33.0%
2024-05-11T02:20:00.850651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3903
 
6.9%
3446
 
6.1%
3446
 
6.1%
( 3429
 
6.1%
) 3429
 
6.1%
3116
 
5.5%
2364
 
4.2%
2236
 
4.0%
2045
 
3.6%
2037
 
3.6%
Other values (402) 26995
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46585
82.5%
Open Punctuation 3429
 
6.1%
Close Punctuation 3429
 
6.1%
Space Separator 2364
 
4.2%
Uppercase Letter 513
 
0.9%
Lowercase Letter 56
 
0.1%
Other Punctuation 42
 
0.1%
Decimal Number 27
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3903
 
8.4%
3446
 
7.4%
3446
 
7.4%
3116
 
6.7%
2236
 
4.8%
2045
 
4.4%
2037
 
4.4%
1843
 
4.0%
1679
 
3.6%
1670
 
3.6%
Other values (364) 21164
45.4%
Uppercase Letter
ValueCountFrequency (%)
S 203
39.6%
G 202
39.4%
J 72
 
14.0%
L 14
 
2.7%
C 5
 
1.0%
N 3
 
0.6%
T 2
 
0.4%
R 2
 
0.4%
E 2
 
0.4%
P 2
 
0.4%
Other values (6) 6
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
a 14
25.0%
o 13
23.2%
k 13
23.2%
l 13
23.2%
n 1
 
1.8%
e 1
 
1.8%
h 1
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 9
33.3%
5 6
22.2%
1 5
18.5%
3 3
 
11.1%
0 2
 
7.4%
6 1
 
3.7%
4 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
@ 36
85.7%
/ 4
 
9.5%
, 1
 
2.4%
. 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 3429
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3429
100.0%
Space Separator
ValueCountFrequency (%)
2364
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46578
82.5%
Common 9292
 
16.5%
Latin 569
 
1.0%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3903
 
8.4%
3446
 
7.4%
3446
 
7.4%
3116
 
6.7%
2236
 
4.8%
2045
 
4.4%
2037
 
4.4%
1843
 
4.0%
1679
 
3.6%
1670
 
3.6%
Other values (363) 21157
45.4%
Latin
ValueCountFrequency (%)
S 203
35.7%
G 202
35.5%
J 72
 
12.7%
L 14
 
2.5%
a 14
 
2.5%
o 13
 
2.3%
k 13
 
2.3%
l 13
 
2.3%
C 5
 
0.9%
N 3
 
0.5%
Other values (13) 17
 
3.0%
Common
ValueCountFrequency (%)
( 3429
36.9%
) 3429
36.9%
2364
25.4%
@ 36
 
0.4%
2 9
 
0.1%
5 6
 
0.1%
1 5
 
0.1%
/ 4
 
< 0.1%
3 3
 
< 0.1%
0 2
 
< 0.1%
Other values (5) 5
 
0.1%
Han
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46578
82.5%
ASCII 9861
 
17.5%
CJK Compat Ideographs 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3903
 
8.4%
3446
 
7.4%
3446
 
7.4%
3116
 
6.7%
2236
 
4.8%
2045
 
4.4%
2037
 
4.4%
1843
 
4.0%
1679
 
3.6%
1670
 
3.6%
Other values (363) 21157
45.4%
ASCII
ValueCountFrequency (%)
( 3429
34.8%
) 3429
34.8%
2364
24.0%
S 203
 
2.1%
G 202
 
2.0%
J 72
 
0.7%
@ 36
 
0.4%
L 14
 
0.1%
a 14
 
0.1%
o 13
 
0.1%
Other values (28) 85
 
0.9%
CJK Compat Ideographs
ValueCountFrequency (%)
7
100.0%

식품군코드
Text

MISSING 

Distinct407
Distinct (%)7.5%
Missing212
Missing (%)3.7%
Memory size44.4 KiB
2024-05-11T02:20:01.573086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length12.230304
Min length1

Characters and Unicode

Total characters66753
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)2.1%

Sample

1st rowC0301020000000
2nd rowC0315070400000
3rd rowC0301020000000
4th rowC0301020000000
5th rowC0301020000000
ValueCountFrequency (%)
c01000000 380
 
7.2%
c0101010000000 213
 
4.0%
c0312020100000 134
 
2.5%
821000000 125
 
2.4%
816000000 115
 
2.2%
201000000 104
 
2.0%
g0100000100000 103
 
1.9%
c0121020000000 98
 
1.9%
801000000 91
 
1.7%
c0301010000000 88
 
1.7%
Other values (395) 3838
72.6%
2024-05-11T02:20:02.598918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44036
66.0%
1 7581
 
11.4%
C 3654
 
5.5%
2 3273
 
4.9%
3 2293
 
3.4%
8 1384
 
2.1%
1241
 
1.9%
6 666
 
1.0%
4 650
 
1.0%
9 645
 
1.0%
Other values (11) 1330
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61457
92.1%
Uppercase Letter 4055
 
6.1%
Space Separator 1241
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44036
71.7%
1 7581
 
12.3%
2 3273
 
5.3%
3 2293
 
3.7%
8 1384
 
2.3%
6 666
 
1.1%
4 650
 
1.1%
9 645
 
1.0%
5 549
 
0.9%
7 380
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 3654
90.1%
G 299
 
7.4%
X 28
 
0.7%
A 20
 
0.5%
D 17
 
0.4%
E 13
 
0.3%
F 11
 
0.3%
H 6
 
0.1%
B 5
 
0.1%
Z 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62698
93.9%
Latin 4055
 
6.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44036
70.2%
1 7581
 
12.1%
2 3273
 
5.2%
3 2293
 
3.7%
8 1384
 
2.2%
1241
 
2.0%
6 666
 
1.1%
4 650
 
1.0%
9 645
 
1.0%
5 549
 
0.9%
Latin
ValueCountFrequency (%)
C 3654
90.1%
G 299
 
7.4%
X 28
 
0.7%
A 20
 
0.5%
D 17
 
0.4%
E 13
 
0.3%
F 11
 
0.3%
H 6
 
0.1%
B 5
 
0.1%
Z 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44036
66.0%
1 7581
 
11.4%
C 3654
 
5.5%
2 3273
 
4.9%
3 2293
 
3.4%
8 1384
 
2.1%
1241
 
1.9%
6 666
 
1.0%
4 650
 
1.0%
9 645
 
1.0%
Other values (11) 1330
 
2.0%

식품군
Text

MISSING 

Distinct290
Distinct (%)6.0%
Missing846
Missing (%)14.9%
Memory size44.4 KiB
2024-05-11T02:20:03.292455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.7089552
Min length1

Characters and Unicode

Total characters22716
Distinct characters300
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

Unique83 ?
Unique (%)1.7%

Sample

1st row캔디류
2nd row서류가공품
3rd row캔디류
4th row캔디류
5th row캔디류
ValueCountFrequency (%)
과자 301
 
5.1%
209
 
3.6%
과자류 196
 
3.3%
조미식품 177
 
3.0%
조리식품 137
 
2.3%
소스 134
 
2.3%
다류 125
 
2.1%
즉석조리식품 108
 
1.8%
곡류가공품 105
 
1.8%
기타식품류 98
 
1.7%
Other values (307) 4267
72.9%
2024-05-11T02:20:04.702842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1458
 
6.4%
1450
 
6.4%
1046
 
4.6%
1033
 
4.5%
891
 
3.9%
714
 
3.1%
651
 
2.9%
621
 
2.7%
607
 
2.7%
507
 
2.2%
Other values (290) 13738
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21086
92.8%
Space Separator 1033
 
4.5%
Other Punctuation 298
 
1.3%
Open Punctuation 131
 
0.6%
Close Punctuation 131
 
0.6%
Uppercase Letter 19
 
0.1%
Decimal Number 12
 
0.1%
Dash Punctuation 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1458
 
6.9%
1450
 
6.9%
1046
 
5.0%
891
 
4.2%
714
 
3.4%
651
 
3.1%
621
 
2.9%
607
 
2.9%
507
 
2.4%
375
 
1.8%
Other values (269) 12766
60.5%
Uppercase Letter
ValueCountFrequency (%)
B 4
21.1%
L 4
21.1%
C 3
15.8%
D 2
10.5%
E 2
10.5%
A 2
10.5%
P 1
 
5.3%
H 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 139
46.6%
. 137
46.0%
/ 20
 
6.7%
? 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 7
58.3%
2 2
 
16.7%
6 2
 
16.7%
3 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1033
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21086
92.8%
Common 1610
 
7.1%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1458
 
6.9%
1450
 
6.9%
1046
 
5.0%
891
 
4.2%
714
 
3.4%
651
 
3.1%
621
 
2.9%
607
 
2.9%
507
 
2.4%
375
 
1.8%
Other values (269) 12766
60.5%
Common
ValueCountFrequency (%)
1033
64.2%
, 139
 
8.6%
. 137
 
8.5%
( 131
 
8.1%
) 131
 
8.1%
/ 20
 
1.2%
1 7
 
0.4%
- 5
 
0.3%
2 2
 
0.1%
6 2
 
0.1%
Other values (2) 3
 
0.2%
Latin
ValueCountFrequency (%)
B 4
20.0%
L 4
20.0%
C 3
15.0%
D 2
10.0%
E 2
10.0%
A 2
10.0%
c 1
 
5.0%
P 1
 
5.0%
H 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21086
92.8%
ASCII 1630
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1458
 
6.9%
1450
 
6.9%
1046
 
5.0%
891
 
4.2%
714
 
3.4%
651
 
3.1%
621
 
2.9%
607
 
2.9%
507
 
2.4%
375
 
1.8%
Other values (269) 12766
60.5%
ASCII
ValueCountFrequency (%)
1033
63.4%
, 139
 
8.5%
. 137
 
8.4%
( 131
 
8.0%
) 131
 
8.0%
/ 20
 
1.2%
1 7
 
0.4%
- 5
 
0.3%
B 4
 
0.2%
L 4
 
0.2%
Other values (11) 19
 
1.2%

품목명
Text

MISSING 

Distinct371
Distinct (%)6.8%
Missing180
Missing (%)3.2%
Memory size44.4 KiB
2024-05-11T02:20:05.646172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length21
Mean length5.2535519
Min length1

Characters and Unicode

Total characters28842
Distinct characters339
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

Unique128 ?
Unique (%)2.3%

Sample

1st row캔디류
2nd row서류가공품
3rd row캔디류
4th row캔디류
5th row캔디류
ValueCountFrequency (%)
433
 
5.7%
과자 341
 
4.5%
조리식품 341
 
4.5%
소스류 203
 
2.7%
침출차 155
 
2.0%
즉석조리식품 140
 
1.8%
소스 134
 
1.8%
캔디류 132
 
1.7%
기타가공품 131
 
1.7%
120
 
1.6%
Other values (398) 5459
71.9%
2024-05-11T02:20:07.025948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2099
 
7.3%
1351
 
4.7%
1106
 
3.8%
1047
 
3.6%
1024
 
3.6%
827
 
2.9%
796
 
2.8%
710
 
2.5%
638
 
2.2%
560
 
1.9%
Other values (329) 18684
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25602
88.8%
Space Separator 2099
 
7.3%
Other Punctuation 573
 
2.0%
Close Punctuation 265
 
0.9%
Open Punctuation 265
 
0.9%
Uppercase Letter 20
 
0.1%
Decimal Number 12
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1351
 
5.3%
1106
 
4.3%
1047
 
4.1%
1024
 
4.0%
827
 
3.2%
796
 
3.1%
710
 
2.8%
638
 
2.5%
560
 
2.2%
553
 
2.2%
Other values (308) 16990
66.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
20.0%
B 4
20.0%
L 4
20.0%
E 2
10.0%
A 2
10.0%
D 2
10.0%
P 1
 
5.0%
H 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 301
52.5%
. 248
43.3%
/ 20
 
3.5%
? 4
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 7
58.3%
6 2
 
16.7%
2 2
 
16.7%
3 1
 
8.3%
Space Separator
ValueCountFrequency (%)
2099
100.0%
Close Punctuation
ValueCountFrequency (%)
) 265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25602
88.8%
Common 3219
 
11.2%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1351
 
5.3%
1106
 
4.3%
1047
 
4.1%
1024
 
4.0%
827
 
3.2%
796
 
3.1%
710
 
2.8%
638
 
2.5%
560
 
2.2%
553
 
2.2%
Other values (308) 16990
66.4%
Common
ValueCountFrequency (%)
2099
65.2%
, 301
 
9.4%
) 265
 
8.2%
( 265
 
8.2%
. 248
 
7.7%
/ 20
 
0.6%
1 7
 
0.2%
- 5
 
0.2%
? 4
 
0.1%
6 2
 
0.1%
Other values (2) 3
 
0.1%
Latin
ValueCountFrequency (%)
C 4
19.0%
B 4
19.0%
L 4
19.0%
E 2
9.5%
A 2
9.5%
D 2
9.5%
P 1
 
4.8%
H 1
 
4.8%
c 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25602
88.8%
ASCII 3240
 
11.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2099
64.8%
, 301
 
9.3%
) 265
 
8.2%
( 265
 
8.2%
. 248
 
7.7%
/ 20
 
0.6%
1 7
 
0.2%
- 5
 
0.2%
C 4
 
0.1%
B 4
 
0.1%
Other values (11) 22
 
0.7%
Hangul
ValueCountFrequency (%)
1351
 
5.3%
1106
 
4.3%
1047
 
4.1%
1024
 
4.0%
827
 
3.2%
796
 
3.1%
710
 
2.8%
638
 
2.5%
560
 
2.2%
553
 
2.2%
Other values (308) 16990
66.4%
Distinct4204
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
2024-05-11T02:20:07.885288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length36
Mean length7.7068783
Min length1

Characters and Unicode

Total characters43698
Distinct characters922
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

Unique3509 ?
Unique (%)61.9%

Sample

1st rowHARIBO GOLDBEARS SOUR
2nd row촉촉꿀고구마스틱
3rd rowFRUTIPS 말랑 트로피칼믹스
4th rowLEGER NEON SOUR BEAR
5th rowVIDAL SOUR RED MIX
ValueCountFrequency (%)
청정원 98
 
1.1%
백설 69
 
0.8%
참기름 46
 
0.5%
유기농 44
 
0.5%
부침가루 35
 
0.4%
30
 
0.3%
도마 28
 
0.3%
오뚜기 28
 
0.3%
고춧가루 27
 
0.3%
냉면육수 26
 
0.3%
Other values (4854) 8212
95.0%
2024-05-11T02:20:09.400037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2978
 
6.8%
969
 
2.2%
811
 
1.9%
705
 
1.6%
644
 
1.5%
588
 
1.3%
520
 
1.2%
444
 
1.0%
426
 
1.0%
424
 
1.0%
Other values (912) 35189
80.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37499
85.8%
Space Separator 2978
 
6.8%
Uppercase Letter 1289
 
2.9%
Decimal Number 783
 
1.8%
Lowercase Letter 343
 
0.8%
Close Punctuation 285
 
0.7%
Open Punctuation 285
 
0.7%
Other Punctuation 207
 
0.5%
Dash Punctuation 13
 
< 0.1%
Math Symbol 11
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
969
 
2.6%
811
 
2.2%
705
 
1.9%
644
 
1.7%
588
 
1.6%
520
 
1.4%
444
 
1.2%
426
 
1.1%
424
 
1.1%
411
 
1.1%
Other values (829) 31557
84.2%
Uppercase Letter
ValueCountFrequency (%)
E 124
 
9.6%
A 117
 
9.1%
I 110
 
8.5%
O 107
 
8.3%
R 95
 
7.4%
C 93
 
7.2%
S 82
 
6.4%
N 68
 
5.3%
L 68
 
5.3%
T 56
 
4.3%
Other values (16) 369
28.6%
Lowercase Letter
ValueCountFrequency (%)
a 38
 
11.1%
i 35
 
10.2%
e 34
 
9.9%
m 29
 
8.5%
p 24
 
7.0%
n 19
 
5.5%
t 18
 
5.2%
c 17
 
5.0%
g 16
 
4.7%
u 16
 
4.7%
Other values (14) 97
28.3%
Other Punctuation
ValueCountFrequency (%)
% 50
24.2%
, 40
19.3%
& 33
15.9%
. 24
11.6%
; 19
 
9.2%
/ 16
 
7.7%
8
 
3.9%
? 8
 
3.9%
! 4
 
1.9%
' 4
 
1.9%
Decimal Number
ValueCountFrequency (%)
0 266
34.0%
1 184
23.5%
2 139
17.8%
3 49
 
6.3%
5 46
 
5.9%
6 35
 
4.5%
4 29
 
3.7%
7 19
 
2.4%
9 12
 
1.5%
8 4
 
0.5%
Letter Number
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 284
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 284
99.6%
[ 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 10
90.9%
~ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
2978
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37478
85.8%
Common 4563
 
10.4%
Latin 1636
 
3.7%
Han 21
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
969
 
2.6%
811
 
2.2%
705
 
1.9%
644
 
1.7%
588
 
1.6%
520
 
1.4%
444
 
1.2%
426
 
1.1%
424
 
1.1%
411
 
1.1%
Other values (821) 31536
84.1%
Latin
ValueCountFrequency (%)
E 124
 
7.6%
A 117
 
7.2%
I 110
 
6.7%
O 107
 
6.5%
R 95
 
5.8%
C 93
 
5.7%
S 82
 
5.0%
N 68
 
4.2%
L 68
 
4.2%
T 56
 
3.4%
Other values (43) 716
43.8%
Common
ValueCountFrequency (%)
2978
65.3%
) 284
 
6.2%
( 284
 
6.2%
0 266
 
5.8%
1 184
 
4.0%
2 139
 
3.0%
% 50
 
1.1%
3 49
 
1.1%
5 46
 
1.0%
, 40
 
0.9%
Other values (20) 243
 
5.3%
Han
ValueCountFrequency (%)
8
38.1%
3
 
14.3%
3
 
14.3%
2
 
9.5%
2
 
9.5%
1
 
4.8%
1
 
4.8%
1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37478
85.8%
ASCII 6185
 
14.2%
CJK 18
 
< 0.1%
None 9
 
< 0.1%
Number Forms 4
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2978
48.1%
) 284
 
4.6%
( 284
 
4.6%
0 266
 
4.3%
1 184
 
3.0%
2 139
 
2.2%
E 124
 
2.0%
A 117
 
1.9%
I 110
 
1.8%
O 107
 
1.7%
Other values (67) 1592
25.7%
Hangul
ValueCountFrequency (%)
969
 
2.6%
811
 
2.2%
705
 
1.9%
644
 
1.7%
588
 
1.6%
520
 
1.4%
444
 
1.2%
426
 
1.1%
424
 
1.1%
411
 
1.1%
Other values (821) 31536
84.1%
None
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
CJK
ValueCountFrequency (%)
8
44.4%
3
 
16.7%
2
 
11.1%
2
 
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
CJK Compat Ideographs
ValueCountFrequency (%)
3
100.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

음식물명
Text

MISSING 

Distinct41
Distinct (%)80.4%
Missing5619
Missing (%)99.1%
Memory size44.4 KiB
2024-05-11T02:20:10.189921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.627451
Min length1

Characters and Unicode

Total characters185
Distinct characters91
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

Unique36 ?
Unique (%)70.6%

Sample

1st row햄버거
2nd row패스츄리
3rd row생크림케?
4th row버터쿠키
5th row양념다대기
ValueCountFrequency (%)
정수기물 5
 
9.8%
수족관물 3
 
5.9%
조리용물 3
 
5.9%
알탕 2
 
3.9%
광어초밥 2
 
3.9%
초새우초밥 1
 
2.0%
학꽁치 1
 
2.0%
다슬기 1
 
2.0%
오징어순대 1
 
2.0%
쭈구미숙회 1
 
2.0%
Other values (31) 31
60.8%
2024-05-11T02:20:11.192768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
7.0%
9
 
4.9%
8
 
4.3%
6
 
3.2%
5
 
2.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
4
 
2.2%
4
 
2.2%
Other values (81) 121
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
99.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
7.1%
9
 
4.9%
8
 
4.3%
6
 
3.3%
5
 
2.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
4
 
2.2%
4
 
2.2%
Other values (80) 120
65.2%
Other Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
7.1%
9
 
4.9%
8
 
4.3%
6
 
3.3%
5
 
2.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
4
 
2.2%
4
 
2.2%
Other values (80) 120
65.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184
99.5%
None 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13
 
7.1%
9
 
4.9%
8
 
4.3%
6
 
3.3%
5
 
2.7%
5
 
2.7%
5
 
2.7%
5
 
2.7%
4
 
2.2%
4
 
2.2%
Other values (80) 120
65.2%
None
ValueCountFrequency (%)
1
100.0%

원료명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing5668
Missing (%)> 99.9%
Memory size44.4 KiB
2024-05-11T02:20:11.622082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row브라질너트
2nd row사차인치
ValueCountFrequency (%)
브라질너트 1
50.0%
사차인치 1
50.0%
2024-05-11T02:20:12.340220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%

생산업소
Text

MISSING 

Distinct265
Distinct (%)41.5%
Missing5031
Missing (%)88.7%
Memory size44.4 KiB
2024-05-11T02:20:12.919053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length17
Mean length7.0876369
Min length2

Characters and Unicode

Total characters4529
Distinct characters301
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

Unique164 ?
Unique (%)25.7%

Sample

1st row(주)가보팜스
2nd row300
3rd row(주)꽃샘식품
4th row대한다업(주)필동티카페연구소
5th row대한다업(주)필동티카페연구소
ValueCountFrequency (%)
48
 
6.6%
주)오뚜기 29
 
4.0%
주)아모레퍼시픽 27
 
3.7%
롯데칠성음료(주 19
 
2.6%
씨제이제일제당(주 17
 
2.3%
코카콜라음료(주 17
 
2.3%
대상(주 16
 
2.2%
주)시아스 13
 
1.8%
주)동원에프앤비 13
 
1.8%
호텔롯데 12
 
1.7%
Other values (273) 513
70.9%
2024-05-11T02:20:14.099766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
485
 
10.7%
) 473
 
10.4%
( 442
 
9.8%
132
 
2.9%
104
 
2.3%
97
 
2.1%
86
 
1.9%
63
 
1.4%
60
 
1.3%
58
 
1.3%
Other values (291) 2529
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3455
76.3%
Close Punctuation 473
 
10.4%
Open Punctuation 442
 
9.8%
Space Separator 86
 
1.9%
Uppercase Letter 35
 
0.8%
Lowercase Letter 26
 
0.6%
Decimal Number 7
 
0.2%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
485
 
14.0%
132
 
3.8%
104
 
3.0%
97
 
2.8%
63
 
1.8%
60
 
1.7%
58
 
1.7%
57
 
1.6%
56
 
1.6%
55
 
1.6%
Other values (245) 2288
66.2%
Lowercase Letter
ValueCountFrequency (%)
o 3
 
11.5%
i 3
 
11.5%
n 2
 
7.7%
s 2
 
7.7%
a 2
 
7.7%
m 2
 
7.7%
p 1
 
3.8%
h 1
 
3.8%
k 1
 
3.8%
e 1
 
3.8%
Other values (8) 8
30.8%
Uppercase Letter
ValueCountFrequency (%)
F 4
11.4%
S 4
11.4%
L 4
11.4%
O 4
11.4%
D 3
8.6%
N 2
 
5.7%
E 2
 
5.7%
T 2
 
5.7%
A 2
 
5.7%
Y 1
 
2.9%
Other values (7) 7
20.0%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
4 2
28.6%
3 1
14.3%
2 1
14.3%
1 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
& 1
 
20.0%
; 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 473
100.0%
Open Punctuation
ValueCountFrequency (%)
( 442
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3455
76.3%
Common 1013
 
22.4%
Latin 61
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
485
 
14.0%
132
 
3.8%
104
 
3.0%
97
 
2.8%
63
 
1.8%
60
 
1.7%
58
 
1.7%
57
 
1.6%
56
 
1.6%
55
 
1.6%
Other values (245) 2288
66.2%
Latin
ValueCountFrequency (%)
F 4
 
6.6%
S 4
 
6.6%
L 4
 
6.6%
O 4
 
6.6%
o 3
 
4.9%
i 3
 
4.9%
D 3
 
4.9%
n 2
 
3.3%
s 2
 
3.3%
a 2
 
3.3%
Other values (25) 30
49.2%
Common
ValueCountFrequency (%)
) 473
46.7%
( 442
43.6%
86
 
8.5%
. 3
 
0.3%
0 2
 
0.2%
4 2
 
0.2%
3 1
 
0.1%
& 1
 
0.1%
; 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3455
76.3%
ASCII 1074
 
23.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
485
 
14.0%
132
 
3.8%
104
 
3.0%
97
 
2.8%
63
 
1.8%
60
 
1.7%
58
 
1.7%
57
 
1.6%
56
 
1.6%
55
 
1.6%
Other values (245) 2288
66.2%
ASCII
ValueCountFrequency (%)
) 473
44.0%
( 442
41.2%
86
 
8.0%
F 4
 
0.4%
S 4
 
0.4%
L 4
 
0.4%
O 4
 
0.4%
o 3
 
0.3%
i 3
 
0.3%
. 3
 
0.3%
Other values (36) 48
 
4.5%

수거일자
Real number (ℝ)

Distinct259
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20163407
Minimum20000630
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:14.699202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000630
5-th percentile20090116
Q120143482
median20170117
Q320190616
95-th percentile20220107
Maximum20240314
Range239684
Interquartile range (IQR)47134.75

Descriptive statistics

Standard deviation37882.68
Coefficient of variation (CV)0.0018787837
Kurtosis-0.076720587
Mean20163407
Median Absolute Deviation (MAD)20503.5
Skewness-0.51213299
Sum1.1432652 × 1011
Variance1.4350974 × 109
MonotonicityDecreasing
2024-05-11T02:20:15.208548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151127 159
 
2.8%
20150324 109
 
1.9%
20130514 109
 
1.9%
20161219 101
 
1.8%
20161215 97
 
1.7%
20200702 96
 
1.7%
20190527 94
 
1.7%
20151204 94
 
1.7%
20150423 92
 
1.6%
20130418 88
 
1.6%
Other values (249) 4631
81.7%
ValueCountFrequency (%)
20000630 1
 
< 0.1%
20010907 1
 
< 0.1%
20011011 1
 
< 0.1%
20070816 1
 
< 0.1%
20071207 1
 
< 0.1%
20080130 65
1.1%
20080212 1
 
< 0.1%
20080215 2
 
< 0.1%
20080424 39
0.7%
20080428 3
 
0.1%
ValueCountFrequency (%)
20240314 5
 
0.1%
20240307 1
 
< 0.1%
20240226 4
 
0.1%
20240201 1
 
< 0.1%
20240131 55
1.0%
20240119 2
 
< 0.1%
20240117 2
 
< 0.1%
20231114 1
 
< 0.1%
20231107 1
 
< 0.1%
20231030 2
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)1.9%
Missing137
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean25.563871
Minimum0.2
Maximum3000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:15.700403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1
Q12
median3
Q35
95-th percentile35.4
Maximum3000
Range2999.8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation137.44973
Coefficient of variation (CV)5.3767179
Kurtosis127.13929
Mean25.563871
Median Absolute Deviation (MAD)1
Skewness9.5661409
Sum141444.9
Variance18892.427
MonotonicityNot monotonic
2024-05-11T02:20:16.909213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 1642
29.0%
3.0 1188
21.0%
1.0 961
16.9%
6.0 561
 
9.9%
4.0 260
 
4.6%
7.0 190
 
3.4%
5.0 152
 
2.7%
8.0 111
 
2.0%
10.0 66
 
1.2%
9.0 58
 
1.0%
Other values (97) 344
 
6.1%
(Missing) 137
 
2.4%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
1.0 961
16.9%
2.0 1642
29.0%
3.0 1188
21.0%
4.0 260
 
4.6%
5.0 152
 
2.7%
6.0 561
 
9.9%
7.0 190
 
3.4%
8.0 111
 
2.0%
9.0 58
 
1.0%
ValueCountFrequency (%)
3000.0 2
 
< 0.1%
1890.0 1
 
< 0.1%
1710.0 2
 
< 0.1%
1500.0 4
0.1%
1425.0 1
 
< 0.1%
1260.0 1
 
< 0.1%
1200.0 8
0.1%
1152.0 1
 
< 0.1%
1110.0 1
 
< 0.1%
1050.0 8
0.1%

제품규격(정량)
Text

MISSING 

Distinct426
Distinct (%)8.7%
Missing753
Missing (%)13.3%
Memory size44.4 KiB
2024-05-11T02:20:17.873644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8295709
Min length1

Characters and Unicode

Total characters13913
Distinct characters18
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)3.7%

Sample

1st row80
2nd row65
3rd row60
4th row70
5th row90
ValueCountFrequency (%)
500 526
 
10.7%
300 294
 
6.0%
100 282
 
5.7%
400 267
 
5.4%
1 258
 
5.2%
200 238
 
4.8%
600 198
 
4.0%
250 161
 
3.3%
350 118
 
2.4%
150 115
 
2.3%
Other values (416) 2460
50.0%
2024-05-11T02:20:19.555108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5854
42.1%
5 1607
 
11.6%
1 1489
 
10.7%
2 1356
 
9.7%
3 974
 
7.0%
4 827
 
5.9%
6 566
 
4.1%
8 417
 
3.0%
7 327
 
2.4%
9 314
 
2.3%
Other values (8) 182
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13731
98.7%
Other Punctuation 133
 
1.0%
Lowercase Letter 35
 
0.3%
Uppercase Letter 11
 
0.1%
Other Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5854
42.6%
5 1607
 
11.7%
1 1489
 
10.8%
2 1356
 
9.9%
3 974
 
7.1%
4 827
 
6.0%
6 566
 
4.1%
8 417
 
3.0%
7 327
 
2.4%
9 314
 
2.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 132
99.2%
, 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
g 33
94.3%
2
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
L 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13866
99.7%
Latin 44
 
0.3%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5854
42.2%
5 1607
 
11.6%
1 1489
 
10.7%
2 1356
 
9.8%
3 974
 
7.0%
4 827
 
6.0%
6 566
 
4.1%
8 417
 
3.0%
7 327
 
2.4%
9 314
 
2.3%
Other values (3) 135
 
1.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Latin
ValueCountFrequency (%)
g 33
75.0%
L 11
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13908
> 99.9%
Letterlike Symbols 2
 
< 0.1%
Hangul 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5854
42.1%
5 1607
 
11.6%
1 1489
 
10.7%
2 1356
 
9.7%
3 974
 
7.0%
4 827
 
5.9%
6 566
 
4.1%
8 417
 
3.0%
7 327
 
2.4%
9 314
 
2.3%
Other values (4) 177
 
1.3%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
g
3713 
<NA>
802 
ML
796 
KG
 
253
LT
 
102
Other values (2)
 
4

Length

Max length4
Median length1
Mean length1.6276896
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 3713
65.5%
<NA> 802
 
14.1%
ML 796
 
14.0%
KG 253
 
4.5%
LT 102
 
1.8%
mm 2
 
< 0.1%
2
 
< 0.1%

Length

2024-05-11T02:20:20.070001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:20.516647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3713
65.5%
na 802
 
14.1%
ml 796
 
14.0%
kg 253
 
4.5%
lt 102
 
1.8%
mm 2
 
< 0.1%
2
 
< 0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5533 
1
 
46
1개
 
35
1식
 
15
1건
 
13
Other values (18)
 
28

Length

Max length10
Median length4
Mean length3.9546737
Min length1

Unique

Unique12 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5533
97.6%
1 46
 
0.8%
1개 35
 
0.6%
1식 15
 
0.3%
1건 13
 
0.2%
2개 4
 
0.1%
2kg 3
 
0.1%
스왑 3
 
0.1%
2모 2
 
< 0.1%
2300g 2
 
< 0.1%
Other values (13) 14
 
0.2%

Length

2024-05-11T02:20:21.080523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5533
97.6%
1 46
 
0.8%
1개 35
 
0.6%
1식 15
 
0.3%
1건 13
 
0.2%
2개 4
 
0.1%
2kg 3
 
0.1%
스왑 3
 
0.1%
2100g 2
 
< 0.1%
2모 2
 
< 0.1%
Other values (14) 15
 
0.3%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct273
Distinct (%)32.1%
Missing4820
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean20177815
Minimum20111018
Maximum21060908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:21.664273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20111018
5-th percentile20130512
Q120151028
median20180409
Q320190784
95-th percentile20230711
Maximum21060908
Range949890
Interquartile range (IQR)39756.5

Descriptive statistics

Standard deviation42659.434
Coefficient of variation (CV)0.0021141751
Kurtosis215.3551
Mean20177815
Median Absolute Deviation (MAD)20309
Skewness10.496928
Sum1.7151143 × 1010
Variance1.8198273 × 109
MonotonicityNot monotonic
2024-05-11T02:20:22.202101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190502 21
 
0.4%
20131111 20
 
0.4%
20190501 15
 
0.3%
20190615 14
 
0.2%
20130512 14
 
0.2%
20141127 13
 
0.2%
20220106 13
 
0.2%
20131011 13
 
0.2%
20170822 13
 
0.2%
20230711 13
 
0.2%
Other values (263) 701
 
12.4%
(Missing) 4820
85.0%
ValueCountFrequency (%)
20111018 1
 
< 0.1%
20130114 2
 
< 0.1%
20130115 3
 
0.1%
20130116 8
0.1%
20130121 7
0.1%
20130124 7
0.1%
20130208 3
 
0.1%
20130311 2
 
< 0.1%
20130408 1
 
< 0.1%
20130512 14
0.2%
ValueCountFrequency (%)
21060908 1
 
< 0.1%
20240307 1
 
< 0.1%
20240226 4
0.1%
20240119 2
< 0.1%
20240117 2
< 0.1%
20240110 1
 
< 0.1%
20240105 1
 
< 0.1%
20231229 1
 
< 0.1%
20231122 1
 
< 0.1%
20231107 1
 
< 0.1%

제조일자(롯트)
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5590 
1
 
68
20180720
 
9
20180828
 
2
-
 
1

Length

Max length8
Median length4
Mean length3.9712522
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5590
98.6%
1 68
 
1.2%
20180720 9
 
0.2%
20180828 2
 
< 0.1%
- 1
 
< 0.1%

Length

2024-05-11T02:20:22.637029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:22.983489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5590
98.6%
1 68
 
1.2%
20180720 9
 
0.2%
20180828 2
 
< 0.1%
1
 
< 0.1%

유통기한(일자)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

유통기한(제조일기준)
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5614 
90
 
50
365
 
3
180
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.9809524
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5614
99.0%
90 50
 
0.9%
365 3
 
0.1%
180 2
 
< 0.1%
1 1
 
< 0.1%

Length

2024-05-11T02:20:23.359207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:23.692627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5614
99.0%
90 50
 
0.9%
365 3
 
0.1%
180 2
 
< 0.1%
1 1
 
< 0.1%

보관상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
실온
4557 
<NA>
666 
냉장
 
316
냉동
 
95
기타
 
36

Length

Max length4
Median length2
Mean length2.2349206
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 4557
80.4%
<NA> 666
 
11.7%
냉장 316
 
5.6%
냉동 95
 
1.7%
기타 36
 
0.6%

Length

2024-05-11T02:20:23.940189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:24.301634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 4557
80.4%
na 666
 
11.7%
냉장 316
 
5.6%
냉동 95
 
1.7%
기타 36
 
0.6%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

어린이기호식품유형
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

검사기관명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
001
3673 
<NA>
1930 
000
 
66
서울시보건환경연구원
 
1

Length

Max length10
Median length3
Mean length3.3416226
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
001 3673
64.8%
<NA> 1930
34.0%
000 66
 
1.2%
서울시보건환경연구원 1
 
< 0.1%

Length

2024-05-11T02:20:24.713799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:25.047346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 3673
64.8%
na 1930
34.0%
000 66
 
1.2%
서울시보건환경연구원 1
 
< 0.1%

(구)제조사명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
국내
4599 
국외
1071 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내 4599
81.1%
국외 1071
 
18.9%

Length

2024-05-11T02:20:25.397400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:25.700253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4599
81.1%
국외 1071
 
18.9%

국가명
Categorical

IMBALANCE 

Distinct42
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
5215 
미국
 
88
중국
 
57
일본
 
50
이탈리아
 
34
Other values (37)
 
226

Length

Max length9
Median length4
Mean length3.9003527
Min length2

Unique

Unique10 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5215
92.0%
미국 88
 
1.6%
중국 57
 
1.0%
일본 50
 
0.9%
이탈리아 34
 
0.6%
태국 25
 
0.4%
스페인 23
 
0.4%
독일 17
 
0.3%
베트남 16
 
0.3%
스리랑카 14
 
0.2%
Other values (32) 131
 
2.3%

Length

2024-05-11T02:20:26.063242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5215
91.8%
미국 88
 
1.5%
중국 60
 
1.1%
일본 50
 
0.9%
이탈리아 34
 
0.6%
태국 25
 
0.4%
스페인 23
 
0.4%
독일 17
 
0.3%
베트남 16
 
0.3%
스리랑카 14
 
0.2%
Other values (35) 138
 
2.4%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
3749 
<NA>
1195 
2
726 

Length

Max length4
Median length1
Mean length1.6322751
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3749
66.1%
<NA> 1195
 
21.1%
2 726
 
12.8%

Length

2024-05-11T02:20:26.654912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:27.164376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3749
66.1%
na 1195
 
21.1%
2 726
 
12.8%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)3.7%
Missing2401
Missing (%)42.3%
Infinite0
Infinite (%)0.0%
Mean20185414
Minimum20101023
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:27.567307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20101023
5-th percentile20160714
Q120170421
median20181123
Q320200706
95-th percentile20230719
Maximum20240314
Range139291
Interquartile range (IQR)30285

Descriptive statistics

Standard deviation22700.98
Coefficient of variation (CV)0.001124623
Kurtosis0.99453974
Mean20185414
Median Absolute Deviation (MAD)18992
Skewness0.046865392
Sum6.5986117 × 1010
Variance5.1533448 × 108
MonotonicityNot monotonic
2024-05-11T02:20:28.138624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161220 252
 
4.4%
20190529 100
 
1.8%
20200706 96
 
1.7%
20161014 90
 
1.6%
20190716 84
 
1.5%
20161118 80
 
1.4%
20171116 80
 
1.4%
20171215 75
 
1.3%
20190320 75
 
1.3%
20171030 73
 
1.3%
Other values (111) 2264
39.9%
(Missing) 2401
42.3%
ValueCountFrequency (%)
20101023 1
 
< 0.1%
20101223 5
0.1%
20110110 4
 
0.1%
20110127 10
0.2%
20110302 3
 
0.1%
20110517 9
0.2%
20111007 4
 
0.1%
20111011 11
0.2%
20111206 3
 
0.1%
20150804 1
 
< 0.1%
ValueCountFrequency (%)
20240314 5
 
0.1%
20240308 1
 
< 0.1%
20240226 4
 
0.1%
20240201 55
1.0%
20240131 1
 
< 0.1%
20240119 4
 
0.1%
20231115 1
 
< 0.1%
20231113 4
 
0.1%
20231107 1
 
< 0.1%
20231030 2
 
< 0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)3.6%
Missing2719
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean20182929
Minimum20111025
Maximum20220127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:28.741209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20111025
5-th percentile20160805
Q120170511
median20181001
Q320191217
95-th percentile20210510
Maximum20220127
Range109102
Interquartile range (IQR)20706

Descriptive statistics

Standard deviation16243.018
Coefficient of variation (CV)0.00080478993
Kurtosis0.56761343
Mean20182929
Median Absolute Deviation (MAD)10270
Skewness-0.10210378
Sum5.9559824 × 1010
Variance2.6383564 × 108
MonotonicityNot monotonic
2024-05-11T02:20:29.276350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170118 252
 
4.4%
20190516 100
 
1.8%
20200731 96
 
1.7%
20161101 90
 
1.6%
20171114 86
 
1.5%
20190807 84
 
1.5%
20181220 84
 
1.5%
20161216 80
 
1.4%
20171129 80
 
1.4%
20171227 75
 
1.3%
Other values (96) 1924
33.9%
(Missing) 2719
48.0%
ValueCountFrequency (%)
20111025 11
 
0.2%
20111223 3
 
0.1%
20150831 1
 
< 0.1%
20151218 1
 
< 0.1%
20160321 26
 
0.5%
20160525 1
 
< 0.1%
20160527 68
1.2%
20160613 1
 
< 0.1%
20160614 2
 
< 0.1%
20160805 57
1.0%
ValueCountFrequency (%)
20220127 2
 
< 0.1%
20220126 19
0.3%
20211202 12
0.2%
20211201 15
0.3%
20211130 4
 
0.1%
20211125 4
 
0.1%
20211119 12
0.2%
20211110 4
 
0.1%
20211029 1
 
< 0.1%
20211022 1
 
< 0.1%

판정구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
3786 
<NA>
1873 
2
 
11

Length

Max length4
Median length1
Mean length1.9910053
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 (%)
1 3786
66.8%
<NA> 1873
33.0%
2 11
 
0.2%

Length

2024-05-11T02:20:29.938097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:30.308888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3786
66.8%
na 1873
33.0%
2 11
 
0.2%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

처리결과
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing5667
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T02:20:30.593697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6666667
Min length9

Characters and Unicode

Total characters29
Distinct characters10
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowGMO정량검사 실시
2nd rowGMO정량검사실시
3rd rowGMO정량검사 실시
ValueCountFrequency (%)
gmo정량검사 2
40.0%
실시 2
40.0%
gmo정량검사실시 1
20.0%
2024-05-11T02:20:31.470631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 3
10.3%
M 3
10.3%
O 3
10.3%
3
10.3%
3
10.3%
3
10.3%
3
10.3%
3
10.3%
3
10.3%
2
6.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
62.1%
Uppercase Letter 9
31.0%
Space Separator 2
 
6.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
Uppercase Letter
ValueCountFrequency (%)
G 3
33.3%
M 3
33.3%
O 3
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
62.1%
Latin 9
31.0%
Common 2
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
Latin
ValueCountFrequency (%)
G 3
33.3%
M 3
33.3%
O 3
33.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
62.1%
ASCII 11
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 3
27.3%
M 3
27.3%
O 3
27.3%
2
18.2%
Hangul
ValueCountFrequency (%)
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%
3
16.7%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

교부번호
Real number (ℝ)

Distinct338
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0050112 × 1010
Minimum1.9670029 × 1010
Maximum2.0230041 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:31.903409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9670029 × 1010
5-th percentile1.9900029 × 1010
Q12.0040029 × 1010
median2.005003 × 1010
Q32.008003 × 1010
95-th percentile2.0150029 × 1010
Maximum2.0230041 × 1010
Range5.6001189 × 108
Interquartile range (IQR)40000013

Descriptive statistics

Standard deviation69036532
Coefficient of variation (CV)0.0034431992
Kurtosis3.1591476
Mean2.0050112 × 1010
Median Absolute Deviation (MAD)29999453
Skewness-1.1476421
Sum1.1368414 × 1014
Variance4.7660427 × 1015
MonotonicityNot monotonic
2024-05-11T02:20:32.486216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080029507 1580
27.9%
20040029494 708
12.5%
20050029760 438
 
7.7%
20000029690 436
 
7.7%
19900029237 296
 
5.2%
20110029738 246
 
4.3%
20050029608 219
 
3.9%
20140029255 163
 
2.9%
20080029267 143
 
2.5%
19990030240 111
 
2.0%
Other values (328) 1330
23.5%
ValueCountFrequency (%)
19670029056 1
 
< 0.1%
19680029016 2
 
< 0.1%
19680029040 1
 
< 0.1%
19720029071 14
0.2%
19730029077 8
0.1%
19750029003 2
 
< 0.1%
19760029049 2
 
< 0.1%
19770029132 6
0.1%
19800029026 1
 
< 0.1%
19800029091 2
 
< 0.1%
ValueCountFrequency (%)
20230040948 1
< 0.1%
20230040538 2
< 0.1%
20230040460 1
< 0.1%
20210030041 1
< 0.1%
20210029537 1
< 0.1%
20210029427 1
< 0.1%
20210029328 1
< 0.1%
20210029052 2
< 0.1%
20200030286 2
< 0.1%
20200030279 1
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

소재지(도로명)
Text

MISSING 

Distinct252
Distinct (%)5.2%
Missing808
Missing (%)14.3%
Memory size44.4 KiB
2024-05-11T02:20:33.119852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length51
Mean length33.827643
Min length21

Characters and Unicode

Total characters164470
Distinct characters194
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

Unique117 ?
Unique (%)2.4%

Sample

1st row서울특별시 중구 청구로17길 74, 1층 (신당동)
2nd row서울특별시 중구 청구로17길 74, 1층 (신당동)
3rd row서울특별시 중구 청구로17길 74, 1층 (신당동)
4th row서울특별시 중구 청구로17길 74, 1층 (신당동)
5th row서울특별시 중구 청구로17길 74, 1층 (신당동)
ValueCountFrequency (%)
서울특별시 4862
16.0%
중구 4862
16.0%
청계천로 1560
 
5.1%
400 1558
 
5.1%
청계천점 1554
 
5.1%
황학동 1202
 
4.0%
이마트 1162
 
3.8%
지하1층~지하2층 1162
 
3.8%
한강대로 732
 
2.4%
405 716
 
2.4%
Other values (455) 11026
36.3%
2024-05-11T02:20:34.476835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25534
 
15.5%
, 8297
 
5.0%
5443
 
3.3%
( 5374
 
3.3%
) 5374
 
3.3%
1 5257
 
3.2%
4913
 
3.0%
4893
 
3.0%
4883
 
3.0%
4883
 
3.0%
Other values (184) 89619
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96094
58.4%
Space Separator 25534
 
15.5%
Decimal Number 21964
 
13.4%
Other Punctuation 8303
 
5.0%
Open Punctuation 5374
 
3.3%
Close Punctuation 5374
 
3.3%
Math Symbol 1437
 
0.9%
Uppercase Letter 237
 
0.1%
Dash Punctuation 153
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5443
 
5.7%
4913
 
5.1%
4893
 
5.1%
4883
 
5.1%
4883
 
5.1%
4874
 
5.1%
4867
 
5.1%
4862
 
5.1%
4788
 
5.0%
4115
 
4.3%
Other values (160) 47573
49.5%
Decimal Number
ValueCountFrequency (%)
1 5257
23.9%
0 4858
22.1%
2 3451
15.7%
4 2549
11.6%
7 1573
 
7.2%
3 1440
 
6.6%
5 1268
 
5.8%
8 686
 
3.1%
6 680
 
3.1%
9 202
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
B 230
97.0%
O 2
 
0.8%
N 1
 
0.4%
S 1
 
0.4%
Y 1
 
0.4%
G 1
 
0.4%
A 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 8297
99.9%
. 6
 
0.1%
Space Separator
ValueCountFrequency (%)
25534
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5374
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5374
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1437
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96094
58.4%
Common 68139
41.4%
Latin 237
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5443
 
5.7%
4913
 
5.1%
4893
 
5.1%
4883
 
5.1%
4883
 
5.1%
4874
 
5.1%
4867
 
5.1%
4862
 
5.1%
4788
 
5.0%
4115
 
4.3%
Other values (160) 47573
49.5%
Common
ValueCountFrequency (%)
25534
37.5%
, 8297
 
12.2%
( 5374
 
7.9%
) 5374
 
7.9%
1 5257
 
7.7%
0 4858
 
7.1%
2 3451
 
5.1%
4 2549
 
3.7%
7 1573
 
2.3%
3 1440
 
2.1%
Other values (7) 4432
 
6.5%
Latin
ValueCountFrequency (%)
B 230
97.0%
O 2
 
0.8%
N 1
 
0.4%
S 1
 
0.4%
Y 1
 
0.4%
G 1
 
0.4%
A 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96094
58.4%
ASCII 68376
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25534
37.3%
, 8297
 
12.1%
( 5374
 
7.9%
) 5374
 
7.9%
1 5257
 
7.7%
0 4858
 
7.1%
2 3451
 
5.0%
4 2549
 
3.7%
7 1573
 
2.3%
3 1440
 
2.1%
Other values (14) 4669
 
6.8%
Hangul
ValueCountFrequency (%)
5443
 
5.7%
4913
 
5.1%
4893
 
5.1%
4883
 
5.1%
4883
 
5.1%
4874
 
5.1%
4867
 
5.1%
4862
 
5.1%
4788
 
5.0%
4115
 
4.3%
Other values (160) 47573
49.5%

소재지(지번)
Text

MISSING 

Distinct294
Distinct (%)5.8%
Missing568
Missing (%)10.0%
Memory size44.4 KiB
2024-05-11T02:20:35.321931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length54
Mean length30.915915
Min length19

Characters and Unicode

Total characters157733
Distinct characters177
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

Unique144 ?
Unique (%)2.8%

Sample

1st row서울특별시 중구 신당동 377번지 16호
2nd row서울특별시 중구 신당동 377번지 16호
3rd row서울특별시 중구 신당동 377번지 16호
4th row서울특별시 중구 신당동 377번지 16호
5th row서울특별시 중구 신당동 377번지 16호
ValueCountFrequency (%)
서울특별시 5102
16.9%
중구 5102
16.9%
황학동 1632
 
5.4%
2545번지 1578
 
5.2%
이마트 1520
 
5.0%
청계천점 1520
 
5.0%
신당동 1199
 
4.0%
지하1층~지하2층 1072
 
3.6%
봉래동2가 748
 
2.5%
122번지 748
 
2.5%
Other values (413) 9917
32.9%
2024-05-11T02:20:36.986926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37032
23.5%
8590
 
5.4%
1 7907
 
5.0%
2 6816
 
4.3%
5148
 
3.3%
5126
 
3.2%
5123
 
3.2%
5119
 
3.2%
5107
 
3.2%
5106
 
3.2%
Other values (167) 66659
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91000
57.7%
Space Separator 37032
23.5%
Decimal Number 26937
 
17.1%
Math Symbol 1270
 
0.8%
Open Punctuation 518
 
0.3%
Close Punctuation 518
 
0.3%
Uppercase Letter 252
 
0.2%
Other Punctuation 192
 
0.1%
Dash Punctuation 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8590
 
9.4%
5148
 
5.7%
5126
 
5.6%
5123
 
5.6%
5119
 
5.6%
5107
 
5.6%
5106
 
5.6%
5102
 
5.6%
5102
 
5.6%
4295
 
4.7%
Other values (143) 37182
40.9%
Decimal Number
ValueCountFrequency (%)
1 7907
29.4%
2 6816
25.3%
5 4353
16.2%
4 2674
 
9.9%
6 1453
 
5.4%
3 1128
 
4.2%
7 934
 
3.5%
9 702
 
2.6%
0 547
 
2.0%
8 423
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
B 245
97.2%
O 2
 
0.8%
G 1
 
0.4%
Y 1
 
0.4%
S 1
 
0.4%
N 1
 
0.4%
A 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 189
98.4%
. 3
 
1.6%
Space Separator
ValueCountFrequency (%)
37032
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 518
100.0%
Close Punctuation
ValueCountFrequency (%)
) 518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91000
57.7%
Common 66481
42.1%
Latin 252
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8590
 
9.4%
5148
 
5.7%
5126
 
5.6%
5123
 
5.6%
5119
 
5.6%
5107
 
5.6%
5106
 
5.6%
5102
 
5.6%
5102
 
5.6%
4295
 
4.7%
Other values (143) 37182
40.9%
Common
ValueCountFrequency (%)
37032
55.7%
1 7907
 
11.9%
2 6816
 
10.3%
5 4353
 
6.5%
4 2674
 
4.0%
6 1453
 
2.2%
~ 1270
 
1.9%
3 1128
 
1.7%
7 934
 
1.4%
9 702
 
1.1%
Other values (7) 2212
 
3.3%
Latin
ValueCountFrequency (%)
B 245
97.2%
O 2
 
0.8%
G 1
 
0.4%
Y 1
 
0.4%
S 1
 
0.4%
N 1
 
0.4%
A 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91000
57.7%
ASCII 66733
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37032
55.5%
1 7907
 
11.8%
2 6816
 
10.2%
5 4353
 
6.5%
4 2674
 
4.0%
6 1453
 
2.2%
~ 1270
 
1.9%
3 1128
 
1.7%
7 934
 
1.4%
9 702
 
1.1%
Other values (14) 2464
 
3.7%
Hangul
ValueCountFrequency (%)
8590
 
9.4%
5148
 
5.7%
5126
 
5.6%
5123
 
5.6%
5119
 
5.6%
5107
 
5.6%
5106
 
5.6%
5102
 
5.6%
5102
 
5.6%
4295
 
4.7%
Other values (143) 37182
40.9%

업소전화번호
Text

MISSING 

Distinct249
Distinct (%)4.6%
Missing307
Missing (%)5.4%
Memory size44.4 KiB
2024-05-11T02:20:37.722074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.738766
Min length2

Characters and Unicode

Total characters57592
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

Unique115 ?
Unique (%)2.1%

Sample

1st row0222348624
2nd row0234469383
3rd row02 390 2500
4th row02 390 2500
5th row02 390 2500
ValueCountFrequency (%)
02 2967
30.7%
0222901234 1219
12.6%
390 520
 
5.4%
2500 520
 
5.4%
727 446
 
4.6%
1234 446
 
4.6%
3101234 438
 
4.5%
22330101 436
 
4.5%
7723010 296
 
3.1%
22567300 246
 
2.5%
Other values (259) 2132
22.1%
2024-05-11T02:20:38.848802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15427
26.8%
0 12440
21.6%
6275
10.9%
3 5952
 
10.3%
1 4820
 
8.4%
7 2868
 
5.0%
9 2733
 
4.7%
4 2704
 
4.7%
5 1837
 
3.2%
6 1376
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51317
89.1%
Space Separator 6275
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15427
30.1%
0 12440
24.2%
3 5952
 
11.6%
1 4820
 
9.4%
7 2868
 
5.6%
9 2733
 
5.3%
4 2704
 
5.3%
5 1837
 
3.6%
6 1376
 
2.7%
8 1160
 
2.3%
Space Separator
ValueCountFrequency (%)
6275
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57592
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15427
26.8%
0 12440
21.6%
6275
10.9%
3 5952
 
10.3%
1 4820
 
8.4%
7 2868
 
5.0%
9 2733
 
4.7%
4 2704
 
4.7%
5 1837
 
3.2%
6 1376
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15427
26.8%
0 12440
21.6%
6275
10.9%
3 5952
 
10.3%
1 4820
 
8.4%
7 2868
 
5.0%
9 2733
 
4.7%
4 2704
 
4.7%
5 1837
 
3.2%
6 1376
 
2.4%

점검목적
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
<NA>
2345 
위생점검(전체)
1910 
수거
1292 
위생점검(부분)
 
74
시설점검
 
49

Length

Max length8
Median length4
Mean length4.9439153
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2345
41.4%
위생점검(전체) 1910
33.7%
수거 1292
22.8%
위생점검(부분) 74
 
1.3%
시설점검 49
 
0.9%

Length

2024-05-11T02:20:39.294958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:39.758298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2345
41.4%
위생점검(전체 1910
33.7%
수거 1292
22.8%
위생점검(부분 74
 
1.3%
시설점검 49
 
0.9%

점검일자
Real number (ℝ)

Distinct247
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20162940
Minimum20010907
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.0 KiB
2024-05-11T02:20:40.420398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010907
5-th percentile20090330
Q120143482
median20161215
Q320190622
95-th percentile20220106
Maximum20240314
Range229407
Interquartile range (IQR)47140

Descriptive statistics

Standard deviation37789.79
Coefficient of variation (CV)0.0018742202
Kurtosis-0.16053817
Mean20162940
Median Absolute Deviation (MAD)29312
Skewness-0.45579092
Sum1.1432387 × 1011
Variance1.4280682 × 109
MonotonicityNot monotonic
2024-05-11T02:20:41.358330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160303 226
 
4.0%
20151130 174
 
3.1%
20151203 123
 
2.2%
20180424 113
 
2.0%
20161219 102
 
1.8%
20161215 98
 
1.7%
20190527 94
 
1.7%
20200702 93
 
1.6%
20161013 90
 
1.6%
20130625 88
 
1.6%
Other values (237) 4469
78.8%
ValueCountFrequency (%)
20010907 1
 
< 0.1%
20011011 1
 
< 0.1%
20070816 1
 
< 0.1%
20080130 65
1.1%
20080214 3
 
0.1%
20080317 2
 
< 0.1%
20080428 3
 
0.1%
20080515 1
 
< 0.1%
20080724 48
0.8%
20080812 10
 
0.2%
ValueCountFrequency (%)
20240314 5
 
0.1%
20240305 1
 
< 0.1%
20240226 4
 
0.1%
20240131 56
1.0%
20240119 2
 
< 0.1%
20240117 2
 
< 0.1%
20231114 1
 
< 0.1%
20231107 1
 
< 0.1%
20231030 2
 
< 0.1%
20231019 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
수시
2586 
<NA>
2152 
기타
760 
합동
 
103
일제
 
69

Length

Max length4
Median length2
Mean length2.7590829
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 2586
45.6%
<NA> 2152
38.0%
기타 760
 
13.4%
합동 103
 
1.8%
일제 69
 
1.2%

Length

2024-05-11T02:20:41.826634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:42.217371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 2586
45.6%
na 2152
38.0%
기타 760
 
13.4%
합동 103
 
1.8%
일제 69
 
1.2%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.4 KiB
1
3494 
<NA>
2152 
2
 
24

Length

Max length4
Median length1
Mean length2.1386243
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3494
61.6%
<NA> 2152
38.0%
2 24
 
0.4%

Length

2024-05-11T02:20:42.748610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:43.215721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3494
61.6%
na 2152
38.0%
2 24
 
0.4%

(구)제조유통기한
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

(구)제조회사주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5670
Missing (%)100.0%
Memory size50.0 KiB

부적합항목
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing5665
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T02:20:43.520103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length8
Min length3

Characters and Unicode

Total characters40
Distinct characters17
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st row대장균
2nd row요오드가
3rd rowGMO성분(정성검사)
4th rowGMO성분(정성검사)
5th rowGMO성분(정성검사)
ValueCountFrequency (%)
gmo성분(정성검사 3
60.0%
대장균 1
 
20.0%
요오드가 1
 
20.0%
2024-05-11T02:20:44.509791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
15.0%
G 3
7.5%
3
7.5%
) 3
7.5%
M 3
7.5%
3
7.5%
3
7.5%
( 3
7.5%
3
7.5%
O 3
7.5%
Other values (7) 7
17.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
62.5%
Uppercase Letter 9
 
22.5%
Close Punctuation 3
 
7.5%
Open Punctuation 3
 
7.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
24.0%
3
12.0%
3
12.0%
3
12.0%
3
12.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (2) 2
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
G 3
33.3%
M 3
33.3%
O 3
33.3%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
62.5%
Latin 9
 
22.5%
Common 6
 
15.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
24.0%
3
12.0%
3
12.0%
3
12.0%
3
12.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (2) 2
 
8.0%
Latin
ValueCountFrequency (%)
G 3
33.3%
M 3
33.3%
O 3
33.3%
Common
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
62.5%
ASCII 15
37.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
24.0%
3
12.0%
3
12.0%
3
12.0%
3
12.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (2) 2
 
8.0%
ASCII
ValueCountFrequency (%)
G 3
20.0%
) 3
20.0%
M 3
20.0%
( 3
20.0%
O 3
20.0%
Distinct2
Distinct (%)50.0%
Missing5666
Missing (%)99.9%
Memory size44.4 KiB
2024-05-11T02:20:44.862171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.25
Min length3

Characters and Unicode

Total characters13
Distinct characters5
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

Unique1 ?
Unique (%)25.0%

Sample

1st row7~11
2nd rowRRS
3rd rowRRS
4th rowRRS
ValueCountFrequency (%)
rrs 3
75.0%
7~11 1
 
25.0%
2024-05-11T02:20:45.795195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 6
46.2%
S 3
23.1%
1 2
 
15.4%
7 1
 
7.7%
~ 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9
69.2%
Decimal Number 3
 
23.1%
Math Symbol 1
 
7.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 6
66.7%
S 3
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
7 1
33.3%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
69.2%
Common 4
30.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
7 1
25.0%
~ 1
25.0%
Latin
ValueCountFrequency (%)
R 6
66.7%
S 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 6
46.2%
S 3
23.1%
1 2
 
15.4%
7 1
 
7.7%
~ 1
 
7.7%

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
03010000104휴게음식점<NA><NA><NA><NA>중구-어린이-2검사용지에스25 신당장충C0301020000000캔디류캔디류HARIBO GOLDBEARS SOUR<NA><NA><NA>202403148.080g<NA>20230901<NA><NA><NA>실온<NA><NA>001<NA>국외터키120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200029545<NA><NA><NA><NA><NA>서울특별시 중구 청구로17길 74, 1층 (신당동)서울특별시 중구 신당동 377번지 16호<NA>수거20240314수시<NA>1<NA><NA><NA><NA>
13010000104휴게음식점<NA><NA><NA><NA>중구-어린이-1검사용지에스25 신당장충C0315070400000서류가공품서류가공품촉촉꿀고구마스틱<NA><NA><NA>2024031411.065g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200029545<NA><NA><NA><NA><NA>서울특별시 중구 청구로17길 74, 1층 (신당동)서울특별시 중구 신당동 377번지 16호<NA>수거20240314수시<NA>1<NA><NA><NA><NA>
23010000104휴게음식점<NA><NA><NA><NA>중구-어린이-3검사용지에스25 신당장충C0301020000000캔디류캔디류FRUTIPS 말랑 트로피칼믹스<NA><NA><NA>2024031410.060g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외중국120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200029545<NA><NA><NA><NA><NA>서울특별시 중구 청구로17길 74, 1층 (신당동)서울특별시 중구 신당동 377번지 16호<NA>수거20240314수시<NA>1<NA><NA><NA><NA>
33010000104휴게음식점<NA><NA><NA><NA>중구-어린이-4검사용지에스25 신당장충C0301020000000캔디류캔디류LEGER NEON SOUR BEAR<NA><NA><NA>202403149.070g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외터키120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200029545<NA><NA><NA><NA><NA>서울특별시 중구 청구로17길 74, 1층 (신당동)서울특별시 중구 신당동 377번지 16호<NA>수거20240314수시<NA>1<NA><NA><NA><NA>
43010000104휴게음식점<NA><NA><NA><NA>중구-어린이-5검사용지에스25 신당장충C0301020000000캔디류캔디류VIDAL SOUR RED MIX<NA><NA><NA>202403147.090g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외스페인120240314<NA><NA><NA><NA><NA><NA><NA><NA>20200029545<NA><NA><NA><NA><NA>서울특별시 중구 청구로17길 74, 1층 (신당동)서울특별시 중구 신당동 377번지 16호<NA>수거20240314수시<NA>1<NA><NA><NA><NA>
53010000106식품제조가공업<NA><NA><NA><NA>중구-가정-1검사용대영식품C0322020300000즉석조리식품즉석조리식품찰순대<NA><NA><NA>202403076.0120g<NA>20240307<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240308<NA><NA><NA><NA><NA><NA><NA><NA>20140029145<NA><NA><NA><NA><NA>서울특별시 중구 퇴계로87길 35-13, 1층 (황학동)서울특별시 중구 황학동 418번지 1층0222348624위생점검(전체)20240305기타<NA>1<NA><NA><NA><NA>
63010000104휴게음식점<NA><NA><NA><NA>24-3-1검사용(주)카키브라운 카페구름점G0200000200000자가제조얼음자가제조얼음식용얼음<NA><NA><NA>202402261.0600g<NA>20240226<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240226<NA><NA><NA><NA><NA><NA><NA><NA>20180030473<NA><NA><NA><NA><NA>서울특별시 중구 다산로 75, 3층 301호 (신당동)서울특별시 중구 신당동 353번지 24호 3층-301<NA>위생점검(전체)20240226수시<NA>1<NA><NA><NA><NA>
73010000112식품자동판매기영업<NA><NA><NA><NA>중구-무인-1검사용커피리드C0309020000000커피커피프리미엄 아메리카노<NA><NA><NA>202402265.0335g<NA>20240226<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240226<NA><NA><NA><NA><NA><NA><NA><NA>20210029328<NA><NA><NA><NA><NA>서울특별시 중구 다산로36길 69, 1층 (신당동)서울특별시 중구 신당동 47번지 14호<NA>위생점검(전체)20240226기타<NA>1<NA><NA><NA><NA>
83010000104휴게음식점<NA><NA><NA><NA>24-2-1검사용피어커피 광희문G0200000200000자가제조얼음자가제조얼음식용얼음<NA><NA><NA>202402261.0600g<NA>20240226<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240226<NA><NA><NA><NA><NA><NA><NA><NA>20200029340<NA><NA><NA><NA><NA>서울특별시 중구 청구로 123, 지하층 (신당동)서울특별시 중구 신당동 393번지 11호<NA>위생점검(전체)20240226수시<NA>1<NA><NA><NA><NA>
93010000101일반음식점<NA><NA><NA><NA>24-4-1검사용커피스미스 약수역점G0200000200000자가제조얼음자가제조얼음식용얼음<NA><NA><NA>202402261.0600g<NA>20240226<NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>220240226<NA><NA><NA><NA><NA><NA><NA><NA>20230040948<NA><NA><NA><NA><NA>서울특별시 중구 다산로 128-1, 1층,2층 (신당동)서울특별시 중구 신당동 369번지 101호0234469383위생점검(전체)20240226수시<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
56603010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장118000000과실류<NA>곳감<NA><NA><NA>200801301.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20080130수시<NA>1<NA><NA><NA><NA>
56613010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장11C000000버섯류<NA>유기재배표고버섯<NA><NA><NA>200801302.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20080130수시<NA>1<NA><NA><NA><NA>
56623010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장220000000기타식품류박력밀가루박력1등<NA><NA><NA>200801301.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20080130수시<NA>1<NA><NA><NA><NA>
56633010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장118000000과실류<NA>우리국산농산물(대추)<NA><NA><NA>200801302.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20080130수시<NA>1<NA><NA><NA><NA>
56643010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장119000000땅콩및견과류<NA>깐밤<NA><NA><NA>200801302.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20080130수시<NA>1<NA><NA><NA><NA>
56653010000114기타식품판매업<NA><NA><NA><NA><NA><NA>농협하나로클럽신촌점 서대문판매장801000000과자류과자엄마손파이<NA><NA><NA>20071207762.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20050029608<NA><NA><NA><NA><NA><NA>서울특별시 중구 충정로1가 75번지 1호0220806993수거20091207기타<NA>1<NA><NA><NA><NA>
56663010000107즉석판매제조가공업<NA><NA><NA><NA><NA><NA>대한기름집907000000<NA>식용유지류(압착식으로 착유하는 전품목)참기름<NA><NA><NA>200708161.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19890029673<NA><NA><NA><NA><NA><NA>서울특별시 중구 오장동 14번지 90호0222754049수거20070816수시<NA>1<NA><NA><NA><NA>
56673010000101일반음식점<NA><NA><NA><NA><NA><NA>미락식당<NA><NA>복어<NA><NA><NA>200110110.2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서울시보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>19940029595<NA><NA><NA><NA><NA><NA>서울특별시 중구 서소문동 47번지 2호0207716848<NA>20011011기타<NA>2<NA><NA><NA><NA>
56683010000101일반음식점<NA><NA><NA><NA><NA><NA>돌담길<NA><NA>스모크치킨<NA><NA><NA>20010907550.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>20010029522<NA><NA><NA><NA><NA><NA>서울특별시 중구 태평로2가 366번지 1호02 7781556<NA>20010907합동<NA>2<NA><NA><NA><NA>
56693010000106식품제조가공업<NA><NA><NA><NA><NA><NA>영림식품250000000식품별기준및규격외의일반가공식품기타가공품통째로갈아넣은홍삼유한뿌리<NA><NA><NA>200006306.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19720029071<NA><NA><NA><NA><NA><NA>서울특별시 중구 신당동 378번지 9호0222341237<NA>20080812<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(제조일기준)보관상태코드검사기관명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드부적합항목기준치부적합내용# duplicates
03010000106식품제조가공업<NA><NA><NA><NA><NA>영림식품250000000식품별기준및규격외의일반가공식품기타가공품통째로갈아넣은인삼유한뿌리<NA><NA><NA>200806306.0<NA><NA><NA><NA><NA><NA><NA>001국외<NA><NA><NA><NA><NA><NA>19720029071<NA>서울특별시 중구 신당동 378번지 9호0222341237<NA>20080812<NA><NA><NA><NA>3
23010000113유통전문판매업<NA><NA><NA><NA><NA>씨제이제일제당(주)216000000인삼제품류인삼음료통째로 갈아넣은 인삼유 한뿌리<NA><NA><NA>200806266.0<NA><NA><NA><NA><NA><NA><NA>001국외<NA><NA><NA><NA><NA><NA>20030030260<NA>서울특별시 중구 남대문로5가 500번지 ,4층02 7268058<NA>20080819<NA><NA><NA><NA>3
13010000109식품소분업<NA><NA><NA><NA><NA>동아물산119000000땅콩및견과류<NA>볶음땅콩(술친구)<NA><NA><NA>200804281.0<NA><NA><NA><NA><NA><NA><NA>001국외<NA><NA><NA><NA><NA><NA>19990029864<NA>서울특별시 중구 을지로5가 262번지 0호0222659766위생점검(전체)20080428기타2<NA><NA>2
33010000114기타식품판매업<NA><NA><NA><NA><NA>신세계백화점899000000축산물가공품햄류청정원 하이포크팜<NA><NA><NA>200903258.0<NA><NA><NA><NA><NA><NA><NA>001국외<NA><NA><NA><NA>1<NA>20050029760<NA>서울특별시 중구 충무로1가 52번지 20호02 3101234<NA>20090330<NA><NA><NA><NA>2