Overview

Dataset statistics

Number of variables61
Number of observations7883
Missing cells212075
Missing cells (%)44.1%
Duplicate rows27
Duplicate rows (%)0.3%
Total size in memory3.9 MiB
Average record size in memory517.0 B

Variable types

Categorical19
Numeric11
Unsupported13
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-10455/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
폐기장소 has constant value ""Constant
폐기방법 has constant value ""Constant
Dataset has 27 (0.3%) duplicate rowsDuplicates
국가명 has a high cardinality: 51 distinct valuesHigh cardinality
업종명 is highly imbalanced (52.7%)Imbalance
계획구분코드 is highly imbalanced (63.8%)Imbalance
지도점검계획 is highly imbalanced (73.2%)Imbalance
수거계획 is highly imbalanced (59.3%)Imbalance
수거사유코드 is highly imbalanced (58.8%)Imbalance
수거량(자유) is highly imbalanced (96.0%)Imbalance
제조일자(롯트) is highly imbalanced (76.1%)Imbalance
검사기관명 is highly imbalanced (56.0%)Imbalance
국가명 is highly imbalanced (78.5%)Imbalance
판정구분 is highly imbalanced (72.4%)Imbalance
처리결과 is highly imbalanced (97.2%)Imbalance
계획구분명 has 7883 (100.0%) missing valuesMissing
수거증번호 has 1746 (22.1%) missing valuesMissing
식품군 has 589 (7.5%) missing valuesMissing
품목명 has 460 (5.8%) missing valuesMissing
음식물명 has 7580 (96.2%) missing valuesMissing
원료명 has 7861 (99.7%) missing valuesMissing
생산업소 has 7156 (90.8%) missing valuesMissing
수거량(정량) has 158 (2.0%) missing valuesMissing
제품규격(정량) has 1904 (24.2%) missing valuesMissing
제조일자(일자) has 6411 (81.3%) missing valuesMissing
유통기한(일자) has 7314 (92.8%) missing valuesMissing
유통기한(제조일기준) has 7831 (99.3%) missing valuesMissing
바코드번호 has 7883 (100.0%) missing valuesMissing
어린이기호식품유형 has 7879 (99.9%) missing valuesMissing
(구)제조사명 has 7023 (89.1%) missing valuesMissing
검사의뢰일자 has 5551 (70.4%) missing valuesMissing
결과회보일자 has 6891 (87.4%) missing valuesMissing
처리구분 has 7883 (100.0%) missing valuesMissing
수거검사구분코드 has 7883 (100.0%) missing valuesMissing
단속지역구분코드 has 7883 (100.0%) missing valuesMissing
수거장소구분코드 has 7883 (100.0%) missing valuesMissing
수거품처리 has 7883 (100.0%) missing valuesMissing
폐기일자 has 7883 (100.0%) missing valuesMissing
폐기량(Kg) has 7883 (100.0%) missing valuesMissing
폐기금액(원) has 7883 (100.0%) missing valuesMissing
폐기장소 has 7882 (> 99.9%) missing valuesMissing
폐기방법 has 7882 (> 99.9%) missing valuesMissing
소재지(도로명) has 815 (10.3%) missing valuesMissing
소재지(지번) has 857 (10.9%) missing valuesMissing
업소전화번호 has 1578 (20.0%) missing valuesMissing
점검내용 has 7883 (100.0%) missing valuesMissing
(구)제조유통기한 has 7314 (92.8%) missing valuesMissing
(구)제조회사주소 has 6874 (87.2%) missing valuesMissing
부적합항목 has 7883 (100.0%) missing valuesMissing
기준치부적합내용 has 7883 (100.0%) missing valuesMissing
제조일자(일자) is highly skewed (γ1 = -33.73330565)Skewed
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(Kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부적합항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:48:18.655502
Analysis finished2024-05-11 05:48:23.100472
Duration4.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
3180000
7883 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 7883
100.0%

Length

2024-05-11T14:48:23.198967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:23.334158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 7883
100.0%

업종코드
Real number (ℝ)

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.24039
Minimum101
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:23.481451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation5.7197009
Coefficient of variation (CV)0.051417483
Kurtosis2.5305282
Mean111.24039
Median Absolute Deviation (MAD)0
Skewness0.1734687
Sum876908
Variance32.714978
MonotonicityNot monotonic
2024-05-11T14:48:23.699172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
114 5127
65.0%
101 1002
 
12.7%
105 638
 
8.1%
106 332
 
4.2%
112 279
 
3.5%
104 174
 
2.2%
134 121
 
1.5%
107 104
 
1.3%
113 41
 
0.5%
121 32
 
0.4%
Other values (5) 33
 
0.4%
ValueCountFrequency (%)
101 1002
12.7%
104 174
 
2.2%
105 638
8.1%
106 332
 
4.2%
107 104
 
1.3%
109 3
 
< 0.1%
110 4
 
0.1%
111 10
 
0.1%
112 279
 
3.5%
113 41
 
0.5%
ValueCountFrequency (%)
135 2
 
< 0.1%
134 121
 
1.5%
122 14
 
0.2%
121 32
 
0.4%
114 5127
65.0%
113 41
 
0.5%
112 279
 
3.5%
111 10
 
0.1%
110 4
 
0.1%
109 3
 
< 0.1%

업종명
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
기타식품판매업
5127 
일반음식점
1002 
집단급식소
638 
식품제조가공업
 
332
식품자동판매기영업
 
279
Other values (10)
 
505

Length

Max length13
Median length7
Mean length6.6973234
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 5127
65.0%
일반음식점 1002
 
12.7%
집단급식소 638
 
8.1%
식품제조가공업 332
 
4.2%
식품자동판매기영업 279
 
3.5%
휴게음식점 174
 
2.2%
건강기능식품일반판매업 121
 
1.5%
즉석판매제조가공업 104
 
1.3%
유통전문판매업 41
 
0.5%
제과점영업 32
 
0.4%
Other values (5) 33
 
0.4%

Length

2024-05-11T14:48:23.992408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 5127
65.0%
일반음식점 1002
 
12.7%
집단급식소 638
 
8.1%
식품제조가공업 332
 
4.2%
식품자동판매기영업 279
 
3.5%
휴게음식점 174
 
2.2%
건강기능식품일반판매업 121
 
1.5%
즉석판매제조가공업 104
 
1.3%
유통전문판매업 41
 
0.5%
제과점영업 32
 
0.4%
Other values (6) 37
 
0.5%

계획구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
6531 
999
1263 
7
 
86
2
 
3

Length

Max length4
Median length4
Mean length3.8059115
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> 6531
82.8%
999 1263
 
16.0%
7 86
 
1.1%
2 3
 
< 0.1%

Length

2024-05-11T14:48:24.218549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:24.411856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6531
82.8%
999 1263
 
16.0%
7 86
 
1.1%
2 3
 
< 0.1%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
6531 
기타식품판매업 지도점검
735 
식품 판매업소 지도점검
 
194
식품제조가공업소 등 지도점검
 
129
2013 음식점 원산지 표시제 지도점검계획
 
83
Other values (10)
 
211

Length

Max length28
Median length4
Mean length5.8359762
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> 6531
82.8%
기타식품판매업 지도점검 735
 
9.3%
식품 판매업소 지도점검 194
 
2.5%
식품제조가공업소 등 지도점검 129
 
1.6%
2013 음식점 원산지 표시제 지도점검계획 83
 
1.1%
식품접객업소 지도점검계획(야간자체점검 및 민원신고) 76
 
1.0%
2012년도 음식점 원산지 표시제 지도점검계획 62
 
0.8%
건강기능식품에관한법률 지도점검 25
 
0.3%
식품접객업소 및 집단급식소지도점검 16
 
0.2%
식품제조업소 등 지도점검계획 16
 
0.2%
Other values (5) 16
 
0.2%

Length

2024-05-11T14:48:24.603752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6531
64.0%
지도점검 1084
 
10.6%
기타식품판매업 735
 
7.2%
식품 194
 
1.9%
판매업소 194
 
1.9%
지도점검계획 161
 
1.6%
표시제 145
 
1.4%
원산지 145
 
1.4%
음식점 145
 
1.4%
145
 
1.4%
Other values (24) 721
 
7.1%

수거계획
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
5983 
기타 일상수거검사
 
567
수거검사 계획
 
565
유통식품 수거검사
 
435
2012년 수거검사계획
 
115
Other values (5)
 
218

Length

Max length28
Median length4
Mean length5.3072434
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5983
75.9%
기타 일상수거검사 567
 
7.2%
수거검사 계획 565
 
7.2%
유통식품 수거검사 435
 
5.5%
2012년 수거검사계획 115
 
1.5%
2016~2017 소고기 유전자 수거검사 계획 107
 
1.4%
식중독 조사 89
 
1.1%
한우수거검사 12
 
0.2%
식중독 예방을 위한 여름철 성수식품 수거검사 계획 9
 
0.1%
코레일(지하철) 역사 내 식품접객업소 특별 위생점검 1
 
< 0.1%

Length

2024-05-11T14:48:24.790760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:25.006083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5983
59.0%
수거검사 1116
 
11.0%
계획 681
 
6.7%
기타 567
 
5.6%
일상수거검사 567
 
5.6%
유통식품 435
 
4.3%
2012년 115
 
1.1%
수거검사계획 115
 
1.1%
2016~2017 107
 
1.1%
소고기 107
 
1.1%
Other values (14) 348
 
3.4%

수거증번호
Text

MISSING 

Distinct5391
Distinct (%)87.8%
Missing1746
Missing (%)22.1%
Memory size61.7 KiB
2024-05-11T14:48:25.454079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.752159
Min length1

Characters and Unicode

Total characters53712
Distinct characters99
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

Unique4726 ?
Unique (%)77.0%

Sample

1st row2024-가정간편식-1
2nd row2024-가정간편식-2
3rd row2024-가정간편식-3
4th row2024-03-07
5th row2024-03-19
ValueCountFrequency (%)
119 331
 
5.1%
영등포 33
 
0.5%
119-1-4 5
 
0.1%
119-1-5 5
 
0.1%
119-5-20 4
 
0.1%
119-1-8 4
 
0.1%
119-5-25 4
 
0.1%
119-5-19 4
 
0.1%
119-1-1 4
 
0.1%
119-1-9 4
 
0.1%
Other values (5373) 6108
93.9%
2024-05-11T14:48:26.134044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15509
28.9%
- 11819
22.0%
9 5981
 
11.1%
2 4420
 
8.2%
0 2594
 
4.8%
3 2248
 
4.2%
4 2170
 
4.0%
6 1651
 
3.1%
5 1602
 
3.0%
7 1433
 
2.7%
Other values (89) 4285
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38934
72.5%
Dash Punctuation 11819
 
22.0%
Other Letter 2450
 
4.6%
Space Separator 370
 
0.7%
Uppercase Letter 134
 
0.2%
Other Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
574
23.4%
522
21.3%
473
19.3%
121
 
4.9%
120
 
4.9%
104
 
4.2%
67
 
2.7%
56
 
2.3%
39
 
1.6%
30
 
1.2%
Other values (68) 344
14.0%
Decimal Number
ValueCountFrequency (%)
1 15509
39.8%
9 5981
 
15.4%
2 4420
 
11.4%
0 2594
 
6.7%
3 2248
 
5.8%
4 2170
 
5.6%
6 1651
 
4.2%
5 1602
 
4.1%
7 1433
 
3.7%
8 1326
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
G 43
32.1%
M 43
32.1%
O 43
32.1%
L 5
 
3.7%
Other Punctuation
ValueCountFrequency (%)
* 1
33.3%
. 1
33.3%
, 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 11819
100.0%
Space Separator
ValueCountFrequency (%)
370
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51127
95.2%
Hangul 2450
 
4.6%
Latin 135
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
574
23.4%
522
21.3%
473
19.3%
121
 
4.9%
120
 
4.9%
104
 
4.2%
67
 
2.7%
56
 
2.3%
39
 
1.6%
30
 
1.2%
Other values (68) 344
14.0%
Common
ValueCountFrequency (%)
1 15509
30.3%
- 11819
23.1%
9 5981
 
11.7%
2 4420
 
8.6%
0 2594
 
5.1%
3 2248
 
4.4%
4 2170
 
4.2%
6 1651
 
3.2%
5 1602
 
3.1%
7 1433
 
2.8%
Other values (6) 1700
 
3.3%
Latin
ValueCountFrequency (%)
G 43
31.9%
M 43
31.9%
O 43
31.9%
L 5
 
3.7%
g 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51262
95.4%
Hangul 2450
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15509
30.3%
- 11819
23.1%
9 5981
 
11.7%
2 4420
 
8.6%
0 2594
 
5.1%
3 2248
 
4.4%
4 2170
 
4.2%
6 1651
 
3.2%
5 1602
 
3.1%
7 1433
 
2.8%
Other values (11) 1835
 
3.6%
Hangul
ValueCountFrequency (%)
574
23.4%
522
21.3%
473
19.3%
121
 
4.9%
120
 
4.9%
104
 
4.2%
67
 
2.7%
56
 
2.3%
39
 
1.6%
30
 
1.2%
Other values (68) 344
14.0%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
검사용
5115 
<NA>
2751 
기타
 
8
압류
 
5
증거용
 
4

Length

Max length4
Median length3
Mean length3.3473297
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 5115
64.9%
<NA> 2751
34.9%
기타 8
 
0.1%
압류 5
 
0.1%
증거용 4
 
0.1%

Length

2024-05-11T14:48:26.412347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:26.635024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 5115
64.9%
na 2751
34.9%
기타 8
 
0.1%
압류 5
 
0.1%
증거용 4
 
0.1%
Distinct817
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
2024-05-11T14:48:27.065419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length9.6588862
Min length2

Characters and Unicode

Total characters76141
Distinct characters547
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

Unique349 ?
Unique (%)4.4%

Sample

1st row(주)이코니크
2nd row(주)이마트 영등포점
3rd row(주)이마트 영등포점
4th row당서초등학교
5th row당서초등학교
ValueCountFrequency (%)
영등포점 1868
 
16.6%
주)이마트 1043
 
9.3%
홈플러스(주 581
 
5.2%
롯데백화점영등포점 306
 
2.7%
롯데쇼핑(주)롯데마트영등포점 286
 
2.5%
롯데마트 283
 
2.5%
서울양평점 283
 
2.5%
롯데쇼핑(주)빅마켓영등포점 282
 
2.5%
주)신세계 273
 
2.4%
삼성테스코(주)홈플러스영등포점 255
 
2.3%
Other values (887) 5791
51.5%
2024-05-11T14:48:27.759344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4753
 
6.2%
) 3989
 
5.2%
( 3985
 
5.2%
3890
 
5.1%
3368
 
4.4%
3327
 
4.4%
3229
 
4.2%
3224
 
4.2%
3193
 
4.2%
3167
 
4.2%
Other values (537) 40016
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62993
82.7%
Close Punctuation 3989
 
5.2%
Open Punctuation 3985
 
5.2%
Space Separator 3368
 
4.4%
Decimal Number 957
 
1.3%
Uppercase Letter 443
 
0.6%
Lowercase Letter 219
 
0.3%
Other Punctuation 98
 
0.1%
Dash Punctuation 89
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4753
 
7.5%
3890
 
6.2%
3327
 
5.3%
3229
 
5.1%
3224
 
5.1%
3193
 
5.1%
3167
 
5.0%
2253
 
3.6%
1746
 
2.8%
1734
 
2.8%
Other values (488) 32477
51.6%
Uppercase Letter
ValueCountFrequency (%)
S 90
20.3%
B 83
18.7%
K 80
18.1%
Z 34
 
7.7%
A 32
 
7.2%
F 20
 
4.5%
E 15
 
3.4%
G 14
 
3.2%
L 12
 
2.7%
T 11
 
2.5%
Other values (12) 52
11.7%
Lowercase Letter
ValueCountFrequency (%)
t 58
26.5%
r 30
13.7%
e 30
13.7%
o 29
13.2%
s 29
13.2%
i 29
13.2%
a 5
 
2.3%
p 4
 
1.8%
m 3
 
1.4%
k 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
2 277
28.9%
0 248
25.9%
4 152
15.9%
1 136
14.2%
3 124
13.0%
6 11
 
1.1%
5 9
 
0.9%
Other Punctuation
ValueCountFrequency (%)
& 68
69.4%
, 10
 
10.2%
/ 10
 
10.2%
. 6
 
6.1%
; 3
 
3.1%
# 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 3989
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3985
100.0%
Space Separator
ValueCountFrequency (%)
3368
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62990
82.7%
Common 12486
 
16.4%
Latin 662
 
0.9%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4753
 
7.5%
3890
 
6.2%
3327
 
5.3%
3229
 
5.1%
3224
 
5.1%
3193
 
5.1%
3167
 
5.0%
2253
 
3.6%
1746
 
2.8%
1734
 
2.8%
Other values (485) 32474
51.6%
Latin
ValueCountFrequency (%)
S 90
13.6%
B 83
12.5%
K 80
12.1%
t 58
 
8.8%
Z 34
 
5.1%
A 32
 
4.8%
r 30
 
4.5%
e 30
 
4.5%
o 29
 
4.4%
s 29
 
4.4%
Other values (22) 167
25.2%
Common
ValueCountFrequency (%)
) 3989
31.9%
( 3985
31.9%
3368
27.0%
2 277
 
2.2%
0 248
 
2.0%
4 152
 
1.2%
1 136
 
1.1%
3 124
 
1.0%
- 89
 
0.7%
& 68
 
0.5%
Other values (7) 50
 
0.4%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62990
82.7%
ASCII 13148
 
17.3%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4753
 
7.5%
3890
 
6.2%
3327
 
5.3%
3229
 
5.1%
3224
 
5.1%
3193
 
5.1%
3167
 
5.0%
2253
 
3.6%
1746
 
2.8%
1734
 
2.8%
Other values (485) 32474
51.6%
ASCII
ValueCountFrequency (%)
) 3989
30.3%
( 3985
30.3%
3368
25.6%
2 277
 
2.1%
0 248
 
1.9%
4 152
 
1.2%
1 136
 
1.0%
3 124
 
0.9%
S 90
 
0.7%
- 89
 
0.7%
Other values (39) 690
 
5.2%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct448
Distinct (%)5.7%
Missing40
Missing (%)0.5%
Memory size61.7 KiB
2024-05-11T14:48:28.115520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length11.216371
Min length1

Characters and Unicode

Total characters87970
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

Unique105 ?
Unique (%)1.3%

Sample

1st rowC0322020300000
2nd rowC0322020400000
3rd rowC0322020200000
4th rowG0100000100000
5th rowZ3800100000000
ValueCountFrequency (%)
801000000 672
 
8.9%
g0100000100000 541
 
7.2%
829000000 500
 
6.6%
803000000 315
 
4.2%
121000000 243
 
3.2%
600000000 208
 
2.8%
c01000000 199
 
2.6%
821000000 172
 
2.3%
830000000 154
 
2.0%
c0101010000000 147
 
1.9%
Other values (436) 4402
58.3%
2024-05-11T14:48:28.760799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59988
68.2%
1 8338
 
9.5%
2 3985
 
4.5%
8 3298
 
3.7%
C 2700
 
3.1%
3 2671
 
3.0%
2498
 
2.8%
9 965
 
1.1%
5 732
 
0.8%
G 666
 
0.8%
Other values (11) 2129
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81676
92.8%
Uppercase Letter 3796
 
4.3%
Space Separator 2498
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59988
73.4%
1 8338
 
10.2%
2 3985
 
4.9%
8 3298
 
4.0%
3 2671
 
3.3%
9 965
 
1.2%
5 732
 
0.9%
6 661
 
0.8%
4 559
 
0.7%
7 479
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 2700
71.1%
G 666
 
17.5%
E 132
 
3.5%
Z 120
 
3.2%
B 61
 
1.6%
X 51
 
1.3%
A 30
 
0.8%
F 27
 
0.7%
D 5
 
0.1%
H 4
 
0.1%
Space Separator
ValueCountFrequency (%)
2498
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84174
95.7%
Latin 3796
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59988
71.3%
1 8338
 
9.9%
2 3985
 
4.7%
8 3298
 
3.9%
3 2671
 
3.2%
2498
 
3.0%
9 965
 
1.1%
5 732
 
0.9%
6 661
 
0.8%
4 559
 
0.7%
Latin
ValueCountFrequency (%)
C 2700
71.1%
G 666
 
17.5%
E 132
 
3.5%
Z 120
 
3.2%
B 61
 
1.6%
X 51
 
1.3%
A 30
 
0.8%
F 27
 
0.7%
D 5
 
0.1%
H 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59988
68.2%
1 8338
 
9.5%
2 3985
 
4.5%
8 3298
 
3.7%
C 2700
 
3.1%
3 2671
 
3.0%
2498
 
2.8%
9 965
 
1.1%
5 732
 
0.8%
G 666
 
0.8%
Other values (11) 2129
 
2.4%

식품군
Text

MISSING 

Distinct339
Distinct (%)4.6%
Missing589
Missing (%)7.5%
Memory size61.7 KiB
2024-05-11T14:48:29.227000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length33
Mean length5.3079243
Min length1

Characters and Unicode

Total characters38716
Distinct characters307
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

Unique90 ?
Unique (%)1.2%

Sample

1st row즉석조리식품
2nd row간편조리세트
3rd row신선편의식품
4th row조리식품 등
5th row기타기준규격외
ValueCountFrequency (%)
과자류 829
 
9.4%
596
 
6.7%
조리식품 546
 
6.2%
기타식품류 526
 
5.9%
코코아가공품류또는초콜릿류 315
 
3.6%
식육류중육류 243
 
2.7%
조미식품 221
 
2.5%
식품접객업 208
 
2.3%
과자 185
 
2.1%
다류 172
 
1.9%
Other values (359) 5012
56.6%
2024-05-11T14:48:29.949082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4090
 
10.6%
3052
 
7.9%
2561
 
6.6%
1559
 
4.0%
1343
 
3.5%
1256
 
3.2%
1192
 
3.1%
1106
 
2.9%
1079
 
2.8%
1027
 
2.7%
Other values (297) 20451
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36445
94.1%
Space Separator 1559
 
4.0%
Other Punctuation 350
 
0.9%
Uppercase Letter 120
 
0.3%
Open Punctuation 107
 
0.3%
Close Punctuation 107
 
0.3%
Decimal Number 25
 
0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4090
 
11.2%
3052
 
8.4%
2561
 
7.0%
1343
 
3.7%
1256
 
3.4%
1192
 
3.3%
1106
 
3.0%
1079
 
3.0%
1027
 
2.8%
891
 
2.4%
Other values (277) 18848
51.7%
Uppercase Letter
ValueCountFrequency (%)
A 32
26.7%
B 19
15.8%
D 17
14.2%
E 14
11.7%
C 13
10.8%
P 12
 
10.0%
H 12
 
10.0%
Q 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
6 10
40.0%
1 9
36.0%
3 3
 
12.0%
2 2
 
8.0%
0 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 176
50.3%
, 143
40.9%
/ 31
 
8.9%
Space Separator
ValueCountFrequency (%)
1559
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36445
94.1%
Common 2151
 
5.6%
Latin 120
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4090
 
11.2%
3052
 
8.4%
2561
 
7.0%
1343
 
3.7%
1256
 
3.4%
1192
 
3.3%
1106
 
3.0%
1079
 
3.0%
1027
 
2.8%
891
 
2.4%
Other values (277) 18848
51.7%
Common
ValueCountFrequency (%)
1559
72.5%
. 176
 
8.2%
, 143
 
6.6%
( 107
 
5.0%
) 107
 
5.0%
/ 31
 
1.4%
6 10
 
0.5%
1 9
 
0.4%
3 3
 
0.1%
- 3
 
0.1%
Other values (2) 3
 
0.1%
Latin
ValueCountFrequency (%)
A 32
26.7%
B 19
15.8%
D 17
14.2%
E 14
11.7%
C 13
10.8%
P 12
 
10.0%
H 12
 
10.0%
Q 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36445
94.1%
ASCII 2271
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4090
 
11.2%
3052
 
8.4%
2561
 
7.0%
1343
 
3.7%
1256
 
3.4%
1192
 
3.3%
1106
 
3.0%
1079
 
3.0%
1027
 
2.8%
891
 
2.4%
Other values (277) 18848
51.7%
ASCII
ValueCountFrequency (%)
1559
68.6%
. 176
 
7.7%
, 143
 
6.3%
( 107
 
4.7%
) 107
 
4.7%
A 32
 
1.4%
/ 31
 
1.4%
B 19
 
0.8%
D 17
 
0.7%
E 14
 
0.6%
Other values (10) 66
 
2.9%

품목명
Text

MISSING 

Distinct413
Distinct (%)5.6%
Missing460
Missing (%)5.8%
Memory size61.7 KiB
2024-05-11T14:48:30.446895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length33
Mean length5.1912973
Min length1

Characters and Unicode

Total characters38535
Distinct characters349
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

Unique119 ?
Unique (%)1.6%

Sample

1st row즉석조리식품
2nd row간편조리세트
3rd row신선편의식품
4th row조리식품 등
5th row기타기준규격외
ValueCountFrequency (%)
조리식품 664
 
7.1%
641
 
6.9%
과자 442
 
4.7%
즉석섭취식품 326
 
3.5%
초콜릿가공품 297
 
3.2%
캔디류 249
 
2.7%
기타가공품 169
 
1.8%
즉석조리식품 159
 
1.7%
캔디류(사탕 153
 
1.6%
소고기 152
 
1.6%
Other values (433) 6084
65.2%
2024-05-11T14:48:31.290207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2580
 
6.7%
1913
 
5.0%
1689
 
4.4%
1425
 
3.7%
1388
 
3.6%
1264
 
3.3%
1202
 
3.1%
1024
 
2.7%
1023
 
2.7%
1021
 
2.6%
Other values (339) 24006
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34968
90.7%
Space Separator 1913
 
5.0%
Other Punctuation 495
 
1.3%
Open Punctuation 483
 
1.3%
Close Punctuation 483
 
1.3%
Uppercase Letter 152
 
0.4%
Decimal Number 34
 
0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2580
 
7.4%
1689
 
4.8%
1425
 
4.1%
1388
 
4.0%
1264
 
3.6%
1202
 
3.4%
1024
 
2.9%
1023
 
2.9%
1021
 
2.9%
717
 
2.1%
Other values (316) 21635
61.9%
Uppercase Letter
ValueCountFrequency (%)
C 42
27.6%
A 36
23.7%
B 19
12.5%
D 17
11.2%
E 16
 
10.5%
P 11
 
7.2%
H 10
 
6.6%
Q 1
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 10
29.4%
6 10
29.4%
3 6
17.6%
2 4
 
11.8%
0 2
 
5.9%
8 1
 
2.9%
5 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 287
58.0%
, 181
36.6%
/ 21
 
4.2%
? 6
 
1.2%
Space Separator
ValueCountFrequency (%)
1913
100.0%
Open Punctuation
ValueCountFrequency (%)
( 483
100.0%
Close Punctuation
ValueCountFrequency (%)
) 483
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34968
90.7%
Common 3415
 
8.9%
Latin 152
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2580
 
7.4%
1689
 
4.8%
1425
 
4.1%
1388
 
4.0%
1264
 
3.6%
1202
 
3.4%
1024
 
2.9%
1023
 
2.9%
1021
 
2.9%
717
 
2.1%
Other values (316) 21635
61.9%
Common
ValueCountFrequency (%)
1913
56.0%
( 483
 
14.1%
) 483
 
14.1%
. 287
 
8.4%
, 181
 
5.3%
/ 21
 
0.6%
1 10
 
0.3%
6 10
 
0.3%
- 7
 
0.2%
3 6
 
0.2%
Other values (5) 14
 
0.4%
Latin
ValueCountFrequency (%)
C 42
27.6%
A 36
23.7%
B 19
12.5%
D 17
11.2%
E 16
 
10.5%
P 11
 
7.2%
H 10
 
6.6%
Q 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34968
90.7%
ASCII 3567
 
9.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2580
 
7.4%
1689
 
4.8%
1425
 
4.1%
1388
 
4.0%
1264
 
3.6%
1202
 
3.4%
1024
 
2.9%
1023
 
2.9%
1021
 
2.9%
717
 
2.1%
Other values (316) 21635
61.9%
ASCII
ValueCountFrequency (%)
1913
53.6%
( 483
 
13.5%
) 483
 
13.5%
. 287
 
8.0%
, 181
 
5.1%
C 42
 
1.2%
A 36
 
1.0%
/ 21
 
0.6%
B 19
 
0.5%
D 17
 
0.5%
Other values (13) 85
 
2.4%
Distinct5877
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
2024-05-11T14:48:31.842044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length48
Mean length7.6470887
Min length1

Characters and Unicode

Total characters60282
Distinct characters978
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5065 ?
Unique (%)64.3%

Sample

1st row웜그레인샐러드오리엔탈
2nd row카덴 마제우동
3rd row델몬트 파인애플 (400)
4th row배추김치1
5th row식판
ValueCountFrequency (%)
커피 190
 
1.6%
한우 177
 
1.5%
등심 71
 
0.6%
청정원 54
 
0.5%
한우등심 52
 
0.4%
유기농 45
 
0.4%
도마 39
 
0.3%
자판기커피 37
 
0.3%
백설 36
 
0.3%
34
 
0.3%
Other values (6967) 11164
93.8%
2024-05-11T14:48:33.024388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4042
 
6.7%
1331
 
2.2%
1098
 
1.8%
1070
 
1.8%
736
 
1.2%
710
 
1.2%
619
 
1.0%
596
 
1.0%
E 592
 
1.0%
A 592
 
1.0%
Other values (968) 48896
81.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47929
79.5%
Uppercase Letter 5986
 
9.9%
Space Separator 4042
 
6.7%
Decimal Number 768
 
1.3%
Close Punctuation 446
 
0.7%
Open Punctuation 444
 
0.7%
Lowercase Letter 370
 
0.6%
Other Punctuation 201
 
0.3%
Dash Punctuation 79
 
0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1331
 
2.8%
1098
 
2.3%
1070
 
2.2%
736
 
1.5%
710
 
1.5%
619
 
1.3%
596
 
1.2%
560
 
1.2%
540
 
1.1%
515
 
1.1%
Other values (890) 40154
83.8%
Uppercase Letter
ValueCountFrequency (%)
E 592
 
9.9%
A 592
 
9.9%
I 475
 
7.9%
O 449
 
7.5%
R 396
 
6.6%
C 371
 
6.2%
N 363
 
6.1%
S 348
 
5.8%
T 317
 
5.3%
L 274
 
4.6%
Other values (16) 1809
30.2%
Lowercase Letter
ValueCountFrequency (%)
e 41
11.1%
a 40
10.8%
p 30
 
8.1%
m 29
 
7.8%
i 28
 
7.6%
o 27
 
7.3%
r 22
 
5.9%
s 20
 
5.4%
l 20
 
5.4%
n 19
 
5.1%
Other values (11) 94
25.4%
Other Punctuation
ValueCountFrequency (%)
, 40
19.9%
% 39
19.4%
& 32
15.9%
/ 28
13.9%
. 18
9.0%
; 16
 
8.0%
10
 
5.0%
: 4
 
2.0%
? 4
 
2.0%
' 4
 
2.0%
Other values (3) 6
 
3.0%
Decimal Number
ValueCountFrequency (%)
0 225
29.3%
1 198
25.8%
2 130
16.9%
3 63
 
8.2%
5 52
 
6.8%
9 29
 
3.8%
4 24
 
3.1%
6 17
 
2.2%
7 16
 
2.1%
8 14
 
1.8%
Math Symbol
ValueCountFrequency (%)
+ 14
93.3%
~ 1
 
6.7%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4042
100.0%
Close Punctuation
ValueCountFrequency (%)
) 446
100.0%
Open Punctuation
ValueCountFrequency (%)
( 444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47924
79.5%
Latin 6358
 
10.5%
Common 5995
 
9.9%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1331
 
2.8%
1098
 
2.3%
1070
 
2.2%
736
 
1.5%
710
 
1.5%
619
 
1.3%
596
 
1.2%
560
 
1.2%
540
 
1.1%
515
 
1.1%
Other values (885) 40149
83.8%
Latin
ValueCountFrequency (%)
E 592
 
9.3%
A 592
 
9.3%
I 475
 
7.5%
O 449
 
7.1%
R 396
 
6.2%
C 371
 
5.8%
N 363
 
5.7%
S 348
 
5.5%
T 317
 
5.0%
L 274
 
4.3%
Other values (39) 2181
34.3%
Common
ValueCountFrequency (%)
4042
67.4%
) 446
 
7.4%
( 444
 
7.4%
0 225
 
3.8%
1 198
 
3.3%
2 130
 
2.2%
- 79
 
1.3%
3 63
 
1.1%
5 52
 
0.9%
, 40
 
0.7%
Other values (19) 276
 
4.6%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47923
79.5%
ASCII 12338
 
20.5%
None 13
 
< 0.1%
CJK 5
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4042
32.8%
E 592
 
4.8%
A 592
 
4.8%
I 475
 
3.8%
O 449
 
3.6%
) 446
 
3.6%
( 444
 
3.6%
R 396
 
3.2%
C 371
 
3.0%
N 363
 
2.9%
Other values (64) 4168
33.8%
Hangul
ValueCountFrequency (%)
1331
 
2.8%
1098
 
2.3%
1070
 
2.2%
736
 
1.5%
710
 
1.5%
619
 
1.3%
596
 
1.2%
560
 
1.2%
540
 
1.1%
515
 
1.1%
Other values (884) 40148
83.8%
None
ValueCountFrequency (%)
10
76.9%
3
 
23.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

음식물명
Text

MISSING 

Distinct142
Distinct (%)46.9%
Missing7580
Missing (%)96.2%
Memory size61.7 KiB
2024-05-11T14:48:33.598059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length4.1551155
Min length1

Characters and Unicode

Total characters1259
Distinct characters240
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

Unique118 ?
Unique (%)38.9%

Sample

1st row타코야끼
2nd row김치
3rd row튀김
4th row튀김
5th row튀김
ValueCountFrequency (%)
커피 78
24.2%
자판기커피 37
 
11.5%
음용수 11
 
3.4%
정수기물 9
 
2.8%
도마 8
 
2.5%
7
 
2.2%
냉면육수 6
 
1.9%
이롬라바홍삼키즈튼튼딸기사과 6
 
1.9%
튀김 4
 
1.2%
김치 4
 
1.2%
Other values (135) 152
47.2%
2024-05-11T14:48:34.257277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
9.2%
116
 
9.2%
60
 
4.8%
46
 
3.7%
40
 
3.2%
37
 
2.9%
20
 
1.6%
19
 
1.5%
19
 
1.5%
19
 
1.5%
Other values (230) 767
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1185
94.1%
Decimal Number 21
 
1.7%
Space Separator 19
 
1.5%
Dash Punctuation 15
 
1.2%
Open Punctuation 8
 
0.6%
Close Punctuation 8
 
0.6%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
116
 
9.8%
116
 
9.8%
60
 
5.1%
46
 
3.9%
40
 
3.4%
37
 
3.1%
20
 
1.7%
19
 
1.6%
19
 
1.6%
17
 
1.4%
Other values (220) 695
58.6%
Decimal Number
ValueCountFrequency (%)
5 8
38.1%
4 6
28.6%
1 3
 
14.3%
3 2
 
9.5%
2 2
 
9.5%
Space Separator
ValueCountFrequency (%)
19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1185
94.1%
Common 74
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
116
 
9.8%
116
 
9.8%
60
 
5.1%
46
 
3.9%
40
 
3.4%
37
 
3.1%
20
 
1.7%
19
 
1.6%
19
 
1.6%
17
 
1.4%
Other values (220) 695
58.6%
Common
ValueCountFrequency (%)
19
25.7%
- 15
20.3%
5 8
10.8%
( 8
10.8%
) 8
10.8%
4 6
 
8.1%
1 3
 
4.1%
/ 3
 
4.1%
3 2
 
2.7%
2 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1185
94.1%
ASCII 74
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
116
 
9.8%
116
 
9.8%
60
 
5.1%
46
 
3.9%
40
 
3.4%
37
 
3.1%
20
 
1.7%
19
 
1.6%
19
 
1.6%
17
 
1.4%
Other values (220) 695
58.6%
ASCII
ValueCountFrequency (%)
19
25.7%
- 15
20.3%
5 8
10.8%
( 8
10.8%
) 8
10.8%
4 6
 
8.1%
1 3
 
4.1%
/ 3
 
4.1%
3 2
 
2.7%
2 2
 
2.7%

원료명
Text

MISSING 

Distinct16
Distinct (%)72.7%
Missing7861
Missing (%)99.7%
Memory size61.7 KiB
2024-05-11T14:48:34.513676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8.5
Mean length6.3181818
Min length2

Characters and Unicode

Total characters139
Distinct characters60
Distinct categories6 ?
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 (%)54.5%

Sample

1st row절임배추, 고춧가루
2nd row합성수지
3rd row금속
4th row돼지고기
5th row돼지고기소시지, 라면
ValueCountFrequency (%)
쇠고기(국내산한우 3
 
10.0%
쇠고기 3
 
10.0%
프로바이오틱스 2
 
6.7%
감마리놀렌산 2
 
6.7%
2
 
6.7%
dha 2
 
6.7%
함유 2
 
6.7%
고춧가루 1
 
3.3%
금속 1
 
3.3%
돼지고기 1
 
3.3%
Other values (11) 11
36.7%
2024-05-11T14:48:34.995529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
6.5%
8
 
5.8%
8
 
5.8%
6
 
4.3%
5
 
3.6%
A 4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.2%
3
 
2.2%
Other values (50) 85
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
79.9%
Uppercase Letter 12
 
8.6%
Space Separator 8
 
5.8%
Open Punctuation 3
 
2.2%
Close Punctuation 3
 
2.2%
Other Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9
 
8.1%
8
 
7.2%
6
 
5.4%
5
 
4.5%
4
 
3.6%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
Other values (41) 63
56.8%
Uppercase Letter
ValueCountFrequency (%)
A 4
33.3%
D 3
25.0%
H 2
16.7%
E 2
16.7%
P 1
 
8.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
79.9%
Common 16
 
11.5%
Latin 12
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9
 
8.1%
8
 
7.2%
6
 
5.4%
5
 
4.5%
4
 
3.6%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
Other values (41) 63
56.8%
Latin
ValueCountFrequency (%)
A 4
33.3%
D 3
25.0%
H 2
16.7%
E 2
16.7%
P 1
 
8.3%
Common
ValueCountFrequency (%)
8
50.0%
( 3
 
18.8%
) 3
 
18.8%
, 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
79.9%
ASCII 28
 
20.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9
 
8.1%
8
 
7.2%
6
 
5.4%
5
 
4.5%
4
 
3.6%
4
 
3.6%
3
 
2.7%
3
 
2.7%
3
 
2.7%
3
 
2.7%
Other values (41) 63
56.8%
ASCII
ValueCountFrequency (%)
8
28.6%
A 4
14.3%
( 3
 
10.7%
D 3
 
10.7%
) 3
 
10.7%
, 2
 
7.1%
H 2
 
7.1%
E 2
 
7.1%
P 1
 
3.6%

생산업소
Text

MISSING 

Distinct364
Distinct (%)50.1%
Missing7156
Missing (%)90.8%
Memory size61.7 KiB
2024-05-11T14:48:35.388129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length29
Mean length8.1898212
Min length2

Characters and Unicode

Total characters5954
Distinct characters374
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

Unique255 ?
Unique (%)35.1%

Sample

1st row피슈마라홍탕 영등포구청점
2nd row씨제이제일제당(주)
3rd row씨제이제일제당(주)
4th row대한제분(주)
5th row대한제분(주)
ValueCountFrequency (%)
롯데제과(주 60
 
6.7%
씨제이제일제당(주 40
 
4.5%
대상(주 23
 
2.6%
샘표식품(주)이천공장 15
 
1.7%
주)정식품 11
 
1.2%
대상에프앤에프(주 10
 
1.1%
10
 
1.1%
foods 10
 
1.1%
오뚜기(주 9
 
1.0%
ltd 9
 
1.0%
Other values (444) 699
78.0%
2024-05-11T14:48:36.096993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
 
8.2%
) 489
 
8.2%
( 488
 
8.2%
245
 
4.1%
169
 
2.8%
114
 
1.9%
113
 
1.9%
89
 
1.5%
86
 
1.4%
85
 
1.4%
Other values (364) 3587
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3750
63.0%
Uppercase Letter 699
 
11.7%
Close Punctuation 489
 
8.2%
Open Punctuation 488
 
8.2%
Lowercase Letter 288
 
4.8%
Space Separator 169
 
2.8%
Other Punctuation 48
 
0.8%
Decimal Number 22
 
0.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
489
 
13.0%
245
 
6.5%
114
 
3.0%
113
 
3.0%
89
 
2.4%
86
 
2.3%
85
 
2.3%
81
 
2.2%
77
 
2.1%
60
 
1.6%
Other values (299) 2311
61.6%
Uppercase Letter
ValueCountFrequency (%)
E 64
 
9.2%
O 63
 
9.0%
N 62
 
8.9%
T 62
 
8.9%
A 52
 
7.4%
S 51
 
7.3%
R 42
 
6.0%
I 36
 
5.2%
L 36
 
5.2%
C 32
 
4.6%
Other values (14) 199
28.5%
Lowercase Letter
ValueCountFrequency (%)
e 33
11.5%
a 30
10.4%
r 22
 
7.6%
o 22
 
7.6%
n 21
 
7.3%
t 21
 
7.3%
i 19
 
6.6%
l 18
 
6.2%
s 15
 
5.2%
c 15
 
5.2%
Other values (13) 72
25.0%
Decimal Number
ValueCountFrequency (%)
1 5
22.7%
0 4
18.2%
5 3
13.6%
8 2
 
9.1%
3 2
 
9.1%
2 2
 
9.1%
9 2
 
9.1%
4 1
 
4.5%
6 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 21
43.8%
, 9
18.8%
' 8
 
16.7%
& 5
 
10.4%
; 5
 
10.4%
Close Punctuation
ValueCountFrequency (%)
) 489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 488
100.0%
Space Separator
ValueCountFrequency (%)
169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3750
63.0%
Common 1217
 
20.4%
Latin 987
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
489
 
13.0%
245
 
6.5%
114
 
3.0%
113
 
3.0%
89
 
2.4%
86
 
2.3%
85
 
2.3%
81
 
2.2%
77
 
2.1%
60
 
1.6%
Other values (299) 2311
61.6%
Latin
ValueCountFrequency (%)
E 64
 
6.5%
O 63
 
6.4%
N 62
 
6.3%
T 62
 
6.3%
A 52
 
5.3%
S 51
 
5.2%
R 42
 
4.3%
I 36
 
3.6%
L 36
 
3.6%
e 33
 
3.3%
Other values (37) 486
49.2%
Common
ValueCountFrequency (%)
) 489
40.2%
( 488
40.1%
169
 
13.9%
. 21
 
1.7%
, 9
 
0.7%
' 8
 
0.7%
1 5
 
0.4%
& 5
 
0.4%
; 5
 
0.4%
0 4
 
0.3%
Other values (8) 14
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3750
63.0%
ASCII 2204
37.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
489
 
13.0%
245
 
6.5%
114
 
3.0%
113
 
3.0%
89
 
2.4%
86
 
2.3%
85
 
2.3%
81
 
2.2%
77
 
2.1%
60
 
1.6%
Other values (299) 2311
61.6%
ASCII
ValueCountFrequency (%)
) 489
22.2%
( 488
22.1%
169
 
7.7%
E 64
 
2.9%
O 63
 
2.9%
N 62
 
2.8%
T 62
 
2.8%
A 52
 
2.4%
S 51
 
2.3%
R 42
 
1.9%
Other values (55) 662
30.0%

수거일자
Real number (ℝ)

Distinct518
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20142962
Minimum20031030
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:36.328490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031030
5-th percentile20090916
Q120110113
median20131115
Q320170825
95-th percentile20211116
Maximum20240307
Range209277
Interquartile range (IQR)60712

Descriptive statistics

Standard deviation40744.533
Coefficient of variation (CV)0.0020227677
Kurtosis-0.85502323
Mean20142962
Median Absolute Deviation (MAD)30102
Skewness0.41993961
Sum1.5878697 × 1011
Variance1.660117 × 109
MonotonicityDecreasing
2024-05-11T14:48:36.562423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151118 134
 
1.7%
20151029 100
 
1.3%
20170414 94
 
1.2%
20111129 92
 
1.2%
20101207 91
 
1.2%
20130424 86
 
1.1%
20130115 72
 
0.9%
20091030 72
 
0.9%
20101202 70
 
0.9%
20240223 68
 
0.9%
Other values (508) 7004
88.8%
ValueCountFrequency (%)
20031030 1
 
< 0.1%
20060427 1
 
< 0.1%
20080131 5
 
0.1%
20080201 6
 
0.1%
20080827 8
 
0.1%
20080828 4
 
0.1%
20080926 9
 
0.1%
20080929 23
0.3%
20081209 4
 
0.1%
20090108 5
 
0.1%
ValueCountFrequency (%)
20240307 3
 
< 0.1%
20240306 21
 
0.3%
20240305 4
 
0.1%
20240304 1
 
< 0.1%
20240227 1
 
< 0.1%
20240223 68
0.9%
20240118 1
 
< 0.1%
20240117 8
 
0.1%
20231208 3
 
< 0.1%
20231123 6
 
0.1%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct99
Distinct (%)1.3%
Missing158
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean20.403392
Minimum1
Maximum2400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:36.781690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36
95-th percentile30
Maximum2400
Range2399
Interquartile range (IQR)5

Descriptive statistics

Standard deviation98.092296
Coefficient of variation (CV)4.8076466
Kurtosis126.59869
Mean20.403392
Median Absolute Deviation (MAD)2
Skewness9.1829542
Sum157616.2
Variance9622.0986
MonotonicityNot monotonic
2024-05-11T14:48:37.030664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 2364
30.0%
3.0 2030
25.8%
6.0 1140
14.5%
2.0 839
 
10.6%
4.0 230
 
2.9%
5.0 183
 
2.3%
300.0 125
 
1.6%
10.0 124
 
1.6%
7.0 109
 
1.4%
8.0 100
 
1.3%
Other values (89) 481
 
6.1%
(Missing) 158
 
2.0%
ValueCountFrequency (%)
1.0 2364
30.0%
1.2 1
 
< 0.1%
2.0 839
 
10.6%
3.0 2030
25.8%
4.0 230
 
2.9%
5.0 183
 
2.3%
6.0 1140
14.5%
7.0 109
 
1.4%
8.0 100
 
1.3%
9.0 45
 
0.6%
ValueCountFrequency (%)
2400.0 1
 
< 0.1%
2000.0 1
 
< 0.1%
1800.0 2
 
< 0.1%
1260.0 1
 
< 0.1%
1230.0 1
 
< 0.1%
1200.0 1
 
< 0.1%
1080.0 1
 
< 0.1%
1000.0 1
 
< 0.1%
900.0 6
0.1%
870.0 1
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct479
Distinct (%)8.0%
Missing1904
Missing (%)24.2%
Memory size61.7 KiB
2024-05-11T14:48:37.655246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7872554
Min length1

Characters and Unicode

Total characters16665
Distinct characters27
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

Unique201 ?
Unique (%)3.4%

Sample

1st row194
2nd row947.4
3rd row400
4th row100
5th row20
ValueCountFrequency (%)
100 468
 
7.8%
200 435
 
7.3%
500 366
 
6.1%
1 339
 
5.7%
300 300
 
5.0%
600 260
 
4.3%
400 237
 
4.0%
150 168
 
2.8%
250 148
 
2.5%
750 133
 
2.2%
Other values (469) 3125
52.3%
2024-05-11T14:48:38.643321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6816
40.9%
1 2092
 
12.6%
5 1638
 
9.8%
2 1630
 
9.8%
3 895
 
5.4%
4 742
 
4.5%
6 684
 
4.1%
8 537
 
3.2%
7 500
 
3.0%
9 316
 
1.9%
Other values (17) 815
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15850
95.1%
Lowercase Letter 526
 
3.2%
Other Punctuation 178
 
1.1%
Other Letter 108
 
0.6%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
24.1%
18
16.7%
18
16.7%
13
12.0%
13
12.0%
6
 
5.6%
6
 
5.6%
3
 
2.8%
2
 
1.9%
2
 
1.9%
Decimal Number
ValueCountFrequency (%)
0 6816
43.0%
1 2092
 
13.2%
5 1638
 
10.3%
2 1630
 
10.3%
3 895
 
5.6%
4 742
 
4.7%
6 684
 
4.3%
8 537
 
3.4%
7 500
 
3.2%
9 316
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
l 211
40.1%
m 185
35.2%
g 130
24.7%
Other Punctuation
ValueCountFrequency (%)
. 157
88.2%
, 21
 
11.8%
Uppercase Letter
ValueCountFrequency (%)
L 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16028
96.2%
Latin 529
 
3.2%
Hangul 108
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6816
42.5%
1 2092
 
13.1%
5 1638
 
10.2%
2 1630
 
10.2%
3 895
 
5.6%
4 742
 
4.6%
6 684
 
4.3%
8 537
 
3.4%
7 500
 
3.1%
9 316
 
2.0%
Other values (2) 178
 
1.1%
Hangul
ValueCountFrequency (%)
26
24.1%
18
16.7%
18
16.7%
13
12.0%
13
12.0%
6
 
5.6%
6
 
5.6%
3
 
2.8%
2
 
1.9%
2
 
1.9%
Latin
ValueCountFrequency (%)
l 211
39.9%
m 185
35.0%
g 130
24.6%
L 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16557
99.4%
Hangul 108
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6816
41.2%
1 2092
 
12.6%
5 1638
 
9.9%
2 1630
 
9.8%
3 895
 
5.4%
4 742
 
4.5%
6 684
 
4.1%
8 537
 
3.2%
7 500
 
3.0%
9 316
 
1.9%
Other values (6) 707
 
4.3%
Hangul
ValueCountFrequency (%)
26
24.1%
18
16.7%
18
16.7%
13
12.0%
13
12.0%
6
 
5.6%
6
 
5.6%
3
 
2.8%
2
 
1.9%
2
 
1.9%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
g
3835 
<NA>
2909 
ML
707 
KG
 
287
LT
 
140
Other values (2)
 
5

Length

Max length4
Median length2
Mean length2.2510466
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 3835
48.6%
<NA> 2909
36.9%
ML 707
 
9.0%
KG 287
 
3.6%
LT 140
 
1.8%
4
 
0.1%
mm 1
 
< 0.1%

Length

2024-05-11T14:48:38.862952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:39.175282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3835
48.6%
na 2909
36.9%
ml 707
 
9.0%
kg 287
 
3.6%
lt 140
 
1.8%
4
 
0.1%
mm 1
 
< 0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
7725 
1개
 
49
검체 2개
 
23
2개
 
16
2
 
9
Other values (39)
 
61

Length

Max length24
Median length4
Mean length4.0140809
Min length1

Unique

Unique30 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1개

Common Values

ValueCountFrequency (%)
<NA> 7725
98.0%
1개 49
 
0.6%
검체 2개 23
 
0.3%
2개 16
 
0.2%
2 9
 
0.1%
1스왓 6
 
0.1%
3개 5
 
0.1%
검체 5㎖×1 4
 
0.1%
1 4
 
0.1%
검체 5g*1 3
 
< 0.1%
Other values (34) 39
 
0.5%

Length

2024-05-11T14:48:39.404574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7725
97.3%
1개 49
 
0.6%
2개 45
 
0.6%
검체 31
 
0.4%
x 12
 
0.2%
2 9
 
0.1%
1스왓 6
 
0.1%
3개 6
 
0.1%
1 5
 
0.1%
5㎖×1 4
 
0.1%
Other values (37) 48
 
0.6%

제조일자(일자)
Real number (ℝ)

MISSING  SKEWED 

Distinct329
Distinct (%)22.4%
Missing6411
Missing (%)81.3%
Infinite0
Infinite (%)0.0%
Mean20131145
Minimum0
Maximum20240306
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:39.648332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20120424
Q120130619
median20170203
Q320180824
95-th percentile20240221
Maximum20240306
Range20240306
Interquartile range (IQR)50205.5

Descriptive statistics

Standard deviation548944.31
Coefficient of variation (CV)0.027268409
Kurtosis1231.907
Mean20131145
Median Absolute Deviation (MAD)20298
Skewness-33.733306
Sum2.9633046 × 1010
Variance3.0133985 × 1011
MonotonicityNot monotonic
2024-05-11T14:48:39.950244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170414 94
 
1.2%
20130308 43
 
0.5%
20120516 35
 
0.4%
20240223 29
 
0.4%
20190410 27
 
0.3%
19000101 27
 
0.3%
20121108 27
 
0.3%
20190613 26
 
0.3%
20160718 21
 
0.3%
20131113 20
 
0.3%
Other values (319) 1123
 
14.2%
(Missing) 6411
81.3%
ValueCountFrequency (%)
0 1
 
< 0.1%
19000101 27
0.3%
20100509 1
 
< 0.1%
20110701 1
 
< 0.1%
20110901 1
 
< 0.1%
20110920 1
 
< 0.1%
20111011 1
 
< 0.1%
20111013 1
 
< 0.1%
20111019 1
 
< 0.1%
20111020 1
 
< 0.1%
ValueCountFrequency (%)
20240306 5
 
0.1%
20240305 10
 
0.1%
20240304 11
 
0.1%
20240227 1
 
< 0.1%
20240223 29
0.4%
20240222 9
 
0.1%
20240221 11
 
0.1%
20240220 10
 
0.1%
20240219 9
 
0.1%
20240118 1
 
< 0.1%

제조일자(롯트)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
7114 
0
751 
0000-00-00
 
17
2022년 7월
 
1

Length

Max length10
Median length4
Mean length3.7276418
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> 7114
90.2%
0 751
 
9.5%
0000-00-00 17
 
0.2%
2022년 7월 1
 
< 0.1%

Length

2024-05-11T14:48:40.255642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:40.471192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7114
90.2%
0 751
 
9.5%
0000-00-00 17
 
0.2%
2022년 1
 
< 0.1%
7월 1
 
< 0.1%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct359
Distinct (%)63.1%
Missing7314
Missing (%)92.8%
Infinite0
Infinite (%)0.0%
Mean19908595
Minimum0
Maximum20150102
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:40.695575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20110725
Q120111229
median20120523
Q320121130
95-th percentile20131010
Maximum20150102
Range20150102
Interquartile range (IQR)9901

Descriptive statistics

Standard deviation2057059.5
Coefficient of variation (CV)0.1033252
Kurtosis90.646671
Mean19908595
Median Absolute Deviation (MAD)685
Skewness-9.6086836
Sum1.132799 × 1010
Variance4.2314937 × 1012
MonotonicityNot monotonic
2024-05-11T14:48:40.955318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110707 7
 
0.1%
20111214 6
 
0.1%
0 6
 
0.1%
20111222 6
 
0.1%
20111223 6
 
0.1%
20120126 5
 
0.1%
20111216 5
 
0.1%
20120414 5
 
0.1%
20120106 5
 
0.1%
20120612 5
 
0.1%
Other values (349) 513
 
6.5%
(Missing) 7314
92.8%
ValueCountFrequency (%)
0 6
0.1%
20110113 3
< 0.1%
20110116 1
 
< 0.1%
20110118 1
 
< 0.1%
20110119 1
 
< 0.1%
20110120 1
 
< 0.1%
20110121 1
 
< 0.1%
20110122 2
 
< 0.1%
20110125 1
 
< 0.1%
20110405 1
 
< 0.1%
ValueCountFrequency (%)
20150102 1
< 0.1%
20141023 1
< 0.1%
20140901 1
< 0.1%
20140831 1
< 0.1%
20140829 1
< 0.1%
20140729 1
< 0.1%
20140720 1
< 0.1%
20140704 1
< 0.1%
20140624 1
< 0.1%
20140527 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)28.8%
Missing7831
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean1164768.1
Minimum0
Maximum20220515
Zeros24
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:41.164316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q3360
95-th percentile9072766.9
Maximum20220515
Range20220515
Interquartile range (IQR)360

Descriptive statistics

Standard deviation4752784
Coefficient of variation (CV)4.0804552
Kurtosis13.799503
Mean1164768.1
Median Absolute Deviation (MAD)1
Skewness3.907663
Sum60567941
Variance2.2588956 × 1013
MonotonicityNot monotonic
2024-05-11T14:48:41.373691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 24
 
0.3%
1 4
 
0.1%
540 3
 
< 0.1%
7 3
 
< 0.1%
90 3
 
< 0.1%
360 3
 
< 0.1%
365 3
 
< 0.1%
180 2
 
< 0.1%
20220515 1
 
< 0.1%
450 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 7831
99.3%
ValueCountFrequency (%)
0 24
0.3%
1 4
 
0.1%
7 3
 
< 0.1%
80 1
 
< 0.1%
90 3
 
< 0.1%
180 2
 
< 0.1%
300 1
 
< 0.1%
360 3
 
< 0.1%
365 3
 
< 0.1%
450 1
 
< 0.1%
ValueCountFrequency (%)
20220515 1
 
< 0.1%
20180604 1
 
< 0.1%
20160812 1
 
< 0.1%
730 1
 
< 0.1%
540 3
< 0.1%
450 1
 
< 0.1%
365 3
< 0.1%
360 3
< 0.1%
300 1
 
< 0.1%
180 2
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
실온
4040 
<NA>
2752 
냉장
765 
냉동
 
240
기타
 
86

Length

Max length4
Median length2
Mean length2.6982113
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 4040
51.2%
<NA> 2752
34.9%
냉장 765
 
9.7%
냉동 240
 
3.0%
기타 86
 
1.1%

Length

2024-05-11T14:48:41.623921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:41.814573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 4040
51.2%
na 2752
34.9%
냉장 765
 
9.7%
냉동 240
 
3.0%
기타 86
 
1.1%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB
Distinct2
Distinct (%)50.0%
Missing7879
Missing (%)99.9%
Memory size61.7 KiB
2024-05-11T14:48:42.003456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.75
Min length3

Characters and Unicode

Total characters15
Distinct characters6
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

Unique1 ?
Unique (%)25.0%

Sample

1st row초콜릿류
2nd row초콜릿류
3rd row캔디류
4th row초콜릿류
ValueCountFrequency (%)
초콜릿류 3
75.0%
캔디류 1
 
25.0%
2024-05-11T14:48:42.415175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
26.7%
3
20.0%
3
20.0%
릿 3
20.0%
1
 
6.7%
1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
26.7%
3
20.0%
3
20.0%
릿 3
20.0%
1
 
6.7%
1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
26.7%
3
20.0%
3
20.0%
릿 3
20.0%
1
 
6.7%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
26.7%
3
20.0%
3
20.0%
릿 3
20.0%
1
 
6.7%
1
 
6.7%

검사기관명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
001
4060 
<NA>
3805 
002
 
15
000
 
2
부산광역시 보건환경연구원
 
1

Length

Max length13
Median length3
Mean length3.4839528
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
001 4060
51.5%
<NA> 3805
48.3%
002 15
 
0.2%
000 2
 
< 0.1%
부산광역시 보건환경연구원 1
 
< 0.1%

Length

2024-05-11T14:48:42.684446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:42.879676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 4060
51.5%
na 3805
48.3%
002 15
 
0.2%
000 2
 
< 0.1%
부산광역시 1
 
< 0.1%
보건환경연구원 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct335
Distinct (%)39.0%
Missing7023
Missing (%)89.1%
Memory size61.7 KiB
2024-05-11T14:48:43.283491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length15
Mean length7.3709302
Min length2

Characters and Unicode

Total characters6339
Distinct characters303
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)21.5%

Sample

1st row(주)보현산
2nd row(주)우천식품
3rd row해청식품(주)
4th row해청식품(주)
5th row해청식품(주)
ValueCountFrequency (%)
롯데제과(주 48
 
5.4%
주)코스트코코리아 43
 
4.9%
씨제이제일제당(주 30
 
3.4%
주)오뚜기 20
 
2.3%
주)크라운제과 18
 
2.0%
주)오리온 18
 
2.0%
대상(주 16
 
1.8%
해태제과식품(주 15
 
1.7%
주)청우식품 13
 
1.5%
성진식품 10
 
1.1%
Other values (334) 652
73.8%
2024-05-11T14:48:44.012764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
682
 
10.8%
( 679
 
10.7%
) 678
 
10.7%
258
 
4.1%
196
 
3.1%
155
 
2.4%
153
 
2.4%
135
 
2.1%
123
 
1.9%
119
 
1.9%
Other values (293) 3161
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4862
76.7%
Open Punctuation 679
 
10.7%
Close Punctuation 678
 
10.7%
Uppercase Letter 64
 
1.0%
Space Separator 23
 
0.4%
Other Punctuation 20
 
0.3%
Decimal Number 12
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
682
 
14.0%
258
 
5.3%
196
 
4.0%
155
 
3.2%
153
 
3.1%
135
 
2.8%
123
 
2.5%
119
 
2.4%
105
 
2.2%
98
 
2.0%
Other values (275) 2838
58.4%
Uppercase Letter
ValueCountFrequency (%)
F 36
56.2%
N 12
 
18.8%
B 9
 
14.1%
S 3
 
4.7%
C 2
 
3.1%
T 2
 
3.1%
Decimal Number
ValueCountFrequency (%)
2 4
33.3%
3 2
16.7%
9 2
16.7%
0 2
16.7%
8 1
 
8.3%
7 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 14
70.0%
6
30.0%
Open Punctuation
ValueCountFrequency (%)
( 679
100.0%
Close Punctuation
ValueCountFrequency (%)
) 678
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4862
76.7%
Common 1413
 
22.3%
Latin 64
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
682
 
14.0%
258
 
5.3%
196
 
4.0%
155
 
3.2%
153
 
3.1%
135
 
2.8%
123
 
2.5%
119
 
2.4%
105
 
2.2%
98
 
2.0%
Other values (275) 2838
58.4%
Common
ValueCountFrequency (%)
( 679
48.1%
) 678
48.0%
23
 
1.6%
/ 14
 
1.0%
6
 
0.4%
2 4
 
0.3%
3 2
 
0.1%
9 2
 
0.1%
0 2
 
0.1%
8 1
 
0.1%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
F 36
56.2%
N 12
 
18.8%
B 9
 
14.1%
S 3
 
4.7%
C 2
 
3.1%
T 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4862
76.7%
ASCII 1471
 
23.2%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
682
 
14.0%
258
 
5.3%
196
 
4.0%
155
 
3.2%
153
 
3.1%
135
 
2.8%
123
 
2.5%
119
 
2.4%
105
 
2.2%
98
 
2.0%
Other values (275) 2838
58.4%
ASCII
ValueCountFrequency (%)
( 679
46.2%
) 678
46.1%
F 36
 
2.4%
23
 
1.6%
/ 14
 
1.0%
N 12
 
0.8%
B 9
 
0.6%
2 4
 
0.3%
S 3
 
0.2%
3 2
 
0.1%
Other values (7) 11
 
0.7%
None
ValueCountFrequency (%)
6
100.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
국내
4990 
국외
2893 

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 4990
63.3%
국외 2893
36.7%

Length

2024-05-11T14:48:44.216621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:44.369162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4990
63.3%
국외 2893
36.7%

국가명
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct51
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
6736 
미국
 
230
일본
 
137
중국
 
111
이탈리아
 
83
Other values (46)
 
586

Length

Max length9
Median length4
Mean length3.8038818
Min length2

Unique

Unique11 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6736
85.4%
미국 230
 
2.9%
일본 137
 
1.7%
중국 111
 
1.4%
이탈리아 83
 
1.1%
프랑스 65
 
0.8%
태국 59
 
0.7%
독일 48
 
0.6%
베트남 46
 
0.6%
영국 44
 
0.6%
Other values (41) 324
 
4.1%

Length

2024-05-11T14:48:44.561275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6736
85.3%
미국 230
 
2.9%
일본 137
 
1.7%
중국 112
 
1.4%
이탈리아 83
 
1.1%
프랑스 65
 
0.8%
태국 59
 
0.7%
독일 48
 
0.6%
베트남 46
 
0.6%
영국 44
 
0.6%
Other values (41) 335
 
4.2%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
1
3337 
<NA>
3111 
2
1435 

Length

Max length4
Median length1
Mean length2.1839401
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3337
42.3%
<NA> 3111
39.5%
2 1435
18.2%

Length

2024-05-11T14:48:44.770520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:44.985596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3337
42.3%
na 3111
39.5%
2 1435
18.2%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct169
Distinct (%)7.2%
Missing5551
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean20162354
Minimum20100119
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:45.177454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100119
5-th percentile20100805
Q120111017
median20180620
Q320210615
95-th percentile20231121
Maximum20240307
Range140188
Interquartile range (IQR)99598

Descriptive statistics

Standard deviation48958.332
Coefficient of variation (CV)0.0024282052
Kurtosis-1.620563
Mean20162354
Median Absolute Deviation (MAD)50306
Skewness0.016577344
Sum4.7018609 × 1010
Variance2.3969183 × 109
MonotonicityNot monotonic
2024-05-11T14:48:45.420420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111129 92
 
1.2%
20240223 68
 
0.9%
20111207 67
 
0.8%
20190610 64
 
0.8%
20190322 60
 
0.8%
20111115 59
 
0.7%
20190430 53
 
0.7%
20111123 52
 
0.7%
20111101 52
 
0.7%
20210615 52
 
0.7%
Other values (159) 1713
 
21.7%
(Missing) 5551
70.4%
ValueCountFrequency (%)
20100119 3
 
< 0.1%
20100209 6
 
0.1%
20100217 4
 
0.1%
20100308 4
 
0.1%
20100323 1
 
< 0.1%
20100413 12
0.2%
20100414 12
0.2%
20100415 17
0.2%
20100416 19
0.2%
20100423 9
0.1%
ValueCountFrequency (%)
20240307 3
 
< 0.1%
20240306 24
 
0.3%
20240305 2
 
< 0.1%
20240223 68
0.9%
20240118 1
 
< 0.1%
20240117 9
 
0.1%
20231208 3
 
< 0.1%
20231123 6
 
0.1%
20231121 4
 
0.1%
20231115 13
 
0.2%

결과회보일자
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)10.7%
Missing6891
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean20185520
Minimum20100326
Maximum20220330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:46.009790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100326
5-th percentile20110928
Q120180712
median20190405
Q320201012
95-th percentile20211214
Maximum20220330
Range120004
Interquartile range (IQR)20300.5

Descriptive statistics

Standard deviation24924.228
Coefficient of variation (CV)0.0012347578
Kurtosis3.5533465
Mean20185520
Median Absolute Deviation (MAD)9990
Skewness-1.8631978
Sum2.0024036 × 1010
Variance6.2121714 × 108
MonotonicityNot monotonic
2024-05-11T14:48:46.324985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190628 63
 
0.8%
20180906 56
 
0.7%
20190514 53
 
0.7%
20210629 50
 
0.6%
20181214 42
 
0.5%
20200619 32
 
0.4%
20180705 31
 
0.4%
20201123 30
 
0.4%
20190410 30
 
0.4%
20190405 30
 
0.4%
Other values (96) 575
 
7.3%
(Missing) 6891
87.4%
ValueCountFrequency (%)
20100326 1
 
< 0.1%
20110415 4
 
0.1%
20110527 9
0.1%
20110610 2
 
< 0.1%
20110711 4
 
0.1%
20110725 1
 
< 0.1%
20110819 6
 
0.1%
20110901 3
 
< 0.1%
20110905 15
0.2%
20110922 1
 
< 0.1%
ValueCountFrequency (%)
20220330 1
 
< 0.1%
20220127 2
 
< 0.1%
20211223 4
 
0.1%
20211220 24
0.3%
20211215 15
0.2%
20211214 16
0.2%
20211202 1
 
< 0.1%
20211119 7
 
0.1%
20211118 15
0.2%
20211105 15
0.2%

판정구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
6890 
1
988 
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.6220982
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> 6890
87.4%
1 988
 
12.5%
2 4
 
0.1%
3 1
 
< 0.1%

Length

2024-05-11T14:48:46.558401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:46.754416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6890
87.4%
1 988
 
12.5%
2 4
 
0.1%
3 1
 
< 0.1%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

처리결과
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
7828 
원산지표시 관리철저 등 안내공문 발송
 
50
적합
 
3
유통기한 경과하여 판매중인 상품은 없음
 
1
대장균 양성
 
1

Length

Max length21
Median length4
Mean length4.1031333
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7828
99.3%
원산지표시 관리철저 등 안내공문 발송 50
 
0.6%
적합 3
 
< 0.1%
유통기한 경과하여 판매중인 상품은 없음 1
 
< 0.1%
대장균 양성 1
 
< 0.1%

Length

2024-05-11T14:48:46.960615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:47.360348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7828
96.8%
원산지표시 50
 
0.6%
관리철저 50
 
0.6%
50
 
0.6%
안내공문 50
 
0.6%
발송 50
 
0.6%
적합 3
 
< 0.1%
유통기한 1
 
< 0.1%
경과하여 1
 
< 0.1%
판매중인 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

교부번호
Real number (ℝ)

Distinct824
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0047905 × 1010
Minimum1.9670086 × 1010
Maximum2.0230116 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:47.593611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9670086 × 1010
5-th percentile1.9910086 × 1010
Q12.0010088 × 1010
median2.0070087 × 1010
Q32.0090087 × 1010
95-th percentile2.0170087 × 1010
Maximum2.0230116 × 1010
Range5.6002973 × 108
Interquartile range (IQR)79999642

Descriptive statistics

Standard deviation93674692
Coefficient of variation (CV)0.0046725426
Kurtosis3.187939
Mean2.0047905 × 1010
Median Absolute Deviation (MAD)59999139
Skewness-1.3006424
Sum1.5803764 × 1014
Variance8.774948 × 1015
MonotonicityNot monotonic
2024-05-11T14:48:47.857348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090087160 1007
 
12.8%
20010088221 795
 
10.1%
20010087651 550
 
7.0%
19910086175 306
 
3.9%
20090086930 300
 
3.8%
20170086501 283
 
3.6%
20080086467 225
 
2.9%
19940086955 205
 
2.6%
19690086003 176
 
2.2%
20150086704 133
 
1.7%
Other values (814) 3903
49.5%
ValueCountFrequency (%)
19670086001 2
 
< 0.1%
19690086003 176
2.2%
19700086012 2
 
< 0.1%
19720086039 1
 
< 0.1%
19730086037 1
 
< 0.1%
19760086001 3
 
< 0.1%
19780086050 6
 
0.1%
19780086062 2
 
< 0.1%
19790086051 3
 
< 0.1%
19800086108 1
 
< 0.1%
ValueCountFrequency (%)
20230115733 12
 
0.2%
20230114455 1
 
< 0.1%
20220108121 2
 
< 0.1%
20220107779 1
 
< 0.1%
20220107562 1
 
< 0.1%
20220107533 68
0.9%
20220107335 1
 
< 0.1%
20220106978 1
 
< 0.1%
20220106785 1
 
< 0.1%
20220106615 1
 
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

폐기량(Kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

폐기장소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing7882
Missing (%)> 99.9%
Memory size61.7 KiB
2024-05-11T14:48:48.132344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
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

Unique1 ?
Unique (%)100.0%

Sample

1st row삼성홈플러스 문래동지점
ValueCountFrequency (%)
삼성홈플러스 1
50.0%
문래동지점 1
50.0%
2024-05-11T14:48:48.548526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
91.7%
Space Separator 1
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
91.7%
Common 1
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
91.7%
ASCII 1
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
ASCII
ValueCountFrequency (%)
1
100.0%

폐기방법
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing7882
Missing (%)> 99.9%
Memory size61.7 KiB
2024-05-11T14:48:48.802088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row유통기한이 짧아 제고량이 남아 있지 않음
ValueCountFrequency (%)
유통기한이 1
16.7%
짧아 1
16.7%
제고량이 1
16.7%
남아 1
16.7%
있지 1
16.7%
않음 1
16.7%
2024-05-11T14:48:49.279600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
22.7%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17
77.3%
Space Separator 5
 
22.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17
77.3%
Common 5
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17
77.3%
ASCII 5
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
100.0%
Hangul
ValueCountFrequency (%)
2
 
11.8%
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (5) 5
29.4%

소재지(도로명)
Text

MISSING 

Distinct625
Distinct (%)8.8%
Missing815
Missing (%)10.3%
Memory size61.7 KiB
2024-05-11T14:48:49.906318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length58
Mean length31.690153
Min length23

Characters and Unicode

Total characters223986
Distinct characters287
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)3.8%

Sample

1st row서울특별시 영등포구 선유서로31길 3, 미디어 비즈 센타 5,6층 (양평동3가)
2nd row서울특별시 영등포구 영중로 15, (영등포동4가,지하1층,2층)
3rd row서울특별시 영등포구 영중로 15, (영등포동4가,지하1층,2층)
4th row서울특별시 영등포구 당산로 187, (당산동5가)
5th row서울특별시 영등포구 당산로 187, (당산동5가)
ValueCountFrequency (%)
서울특별시 7068
18.2%
영등포구 7068
18.2%
영중로 1920
 
5.0%
당산로 1146
 
3.0%
15 1032
 
2.7%
문래동3가 932
 
2.4%
영등포동4가,지하1층,2층 872
 
2.3%
42 870
 
2.2%
여의도동 751
 
1.9%
1층 701
 
1.8%
Other values (871) 16385
42.3%
2024-05-11T14:48:50.628094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31680
 
14.1%
12007
 
5.4%
, 11325
 
5.1%
9859
 
4.4%
9843
 
4.4%
1 8155
 
3.6%
7474
 
3.3%
( 7253
 
3.2%
) 7253
 
3.2%
7119
 
3.2%
Other values (277) 112018
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135520
60.5%
Space Separator 31680
 
14.1%
Decimal Number 30484
 
13.6%
Other Punctuation 11333
 
5.1%
Close Punctuation 7255
 
3.2%
Open Punctuation 7253
 
3.2%
Dash Punctuation 176
 
0.1%
Math Symbol 174
 
0.1%
Uppercase Letter 104
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12007
 
8.9%
9859
 
7.3%
9843
 
7.3%
7474
 
5.5%
7119
 
5.3%
7097
 
5.2%
7079
 
5.2%
7077
 
5.2%
7076
 
5.2%
7073
 
5.2%
Other values (241) 53816
39.7%
Uppercase Letter
ValueCountFrequency (%)
B 61
58.7%
C 8
 
7.7%
S 7
 
6.7%
K 7
 
6.7%
A 4
 
3.8%
F 4
 
3.8%
V 3
 
2.9%
E 3
 
2.9%
I 3
 
2.9%
M 2
 
1.9%
Other values (2) 2
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 8155
26.8%
2 5562
18.2%
3 4066
13.3%
4 3745
12.3%
5 3067
 
10.1%
8 1637
 
5.4%
6 1591
 
5.2%
0 1159
 
3.8%
9 862
 
2.8%
7 640
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
c 1
 
14.3%
n 1
 
14.3%
t 1
 
14.3%
r 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 11325
99.9%
5
 
< 0.1%
. 3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 7253
> 99.9%
] 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31680
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Math Symbol
ValueCountFrequency (%)
~ 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135519
60.5%
Common 88355
39.4%
Latin 111
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12007
 
8.9%
9859
 
7.3%
9843
 
7.3%
7474
 
5.5%
7119
 
5.3%
7097
 
5.2%
7079
 
5.2%
7077
 
5.2%
7076
 
5.2%
7073
 
5.2%
Other values (240) 53815
39.7%
Common
ValueCountFrequency (%)
31680
35.9%
, 11325
 
12.8%
1 8155
 
9.2%
( 7253
 
8.2%
) 7253
 
8.2%
2 5562
 
6.3%
3 4066
 
4.6%
4 3745
 
4.2%
5 3067
 
3.5%
8 1637
 
1.9%
Other values (9) 4612
 
5.2%
Latin
ValueCountFrequency (%)
B 61
55.0%
C 8
 
7.2%
S 7
 
6.3%
K 7
 
6.3%
A 4
 
3.6%
F 4
 
3.6%
V 3
 
2.7%
E 3
 
2.7%
e 3
 
2.7%
I 3
 
2.7%
Other values (7) 8
 
7.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135519
60.5%
ASCII 88461
39.5%
None 5
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31680
35.8%
, 11325
 
12.8%
1 8155
 
9.2%
( 7253
 
8.2%
) 7253
 
8.2%
2 5562
 
6.3%
3 4066
 
4.6%
4 3745
 
4.2%
5 3067
 
3.5%
8 1637
 
1.9%
Other values (25) 4718
 
5.3%
Hangul
ValueCountFrequency (%)
12007
 
8.9%
9859
 
7.3%
9843
 
7.3%
7474
 
5.5%
7119
 
5.3%
7097
 
5.2%
7079
 
5.2%
7077
 
5.2%
7076
 
5.2%
7073
 
5.2%
Other values (240) 53815
39.7%
None
ValueCountFrequency (%)
5
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

소재지(지번)
Text

MISSING 

Distinct778
Distinct (%)11.1%
Missing857
Missing (%)10.9%
Memory size61.7 KiB
2024-05-11T14:48:51.133348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length29.715485
Min length22

Characters and Unicode

Total characters208781
Distinct characters283
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique346 ?
Unique (%)4.9%

Sample

1st row서울특별시 영등포구 양평동3가 23번지 5호 미디어 비즈 센타
2nd row서울특별시 영등포구 영등포동4가 442번지 지하1층,2층
3rd row서울특별시 영등포구 영등포동4가 442번지 지하1층,2층
4th row서울특별시 영등포구 당산동5가 5번지 3호
5th row서울특별시 영등포구 당산동5가 5번지 3호
ValueCountFrequency (%)
서울특별시 7026
19.2%
영등포구 7026
19.2%
영등포동4가 1229
 
3.4%
3호 1068
 
2.9%
여의도동 1053
 
2.9%
문래동3가 922
 
2.5%
442번지 890
 
2.4%
55번지 836
 
2.3%
1호 804
 
2.2%
지하1층,2층 740
 
2.0%
Other values (824) 15034
41.0%
2024-05-11T14:48:51.914316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47778
22.9%
9557
 
4.6%
9540
 
4.6%
9524
 
4.6%
8780
 
4.2%
7121
 
3.4%
7057
 
3.4%
7043
 
3.4%
7040
 
3.4%
7037
 
3.4%
Other values (273) 88304
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125400
60.1%
Space Separator 47778
 
22.9%
Decimal Number 33588
 
16.1%
Other Punctuation 1192
 
0.6%
Close Punctuation 231
 
0.1%
Open Punctuation 229
 
0.1%
Math Symbol 183
 
0.1%
Uppercase Letter 98
 
< 0.1%
Dash Punctuation 75
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9557
 
7.6%
9540
 
7.6%
9524
 
7.6%
8780
 
7.0%
7121
 
5.7%
7057
 
5.6%
7043
 
5.6%
7040
 
5.6%
7037
 
5.6%
7034
 
5.6%
Other values (235) 45667
36.4%
Uppercase Letter
ValueCountFrequency (%)
B 29
29.6%
C 22
22.4%
M 10
 
10.2%
K 8
 
8.2%
S 8
 
8.2%
A 4
 
4.1%
F 4
 
4.1%
V 3
 
3.1%
I 3
 
3.1%
E 3
 
3.1%
Other values (2) 4
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 6386
19.0%
4 6031
18.0%
2 4913
14.6%
3 4815
14.3%
5 3512
10.5%
6 2603
7.7%
8 1477
 
4.4%
7 1454
 
4.3%
0 1349
 
4.0%
9 1048
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 1180
99.0%
5
 
0.4%
. 3
 
0.3%
@ 3
 
0.3%
? 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 3
42.9%
c 1
 
14.3%
n 1
 
14.3%
t 1
 
14.3%
r 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 229
99.1%
] 2
 
0.9%
Space Separator
ValueCountFrequency (%)
47778
100.0%
Open Punctuation
ValueCountFrequency (%)
( 229
100.0%
Math Symbol
ValueCountFrequency (%)
~ 183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125399
60.1%
Common 83276
39.9%
Latin 105
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9557
 
7.6%
9540
 
7.6%
9524
 
7.6%
8780
 
7.0%
7121
 
5.7%
7057
 
5.6%
7043
 
5.6%
7040
 
5.6%
7037
 
5.6%
7034
 
5.6%
Other values (234) 45666
36.4%
Common
ValueCountFrequency (%)
47778
57.4%
1 6386
 
7.7%
4 6031
 
7.2%
2 4913
 
5.9%
3 4815
 
5.8%
5 3512
 
4.2%
6 2603
 
3.1%
8 1477
 
1.8%
7 1454
 
1.7%
0 1349
 
1.6%
Other values (11) 2958
 
3.6%
Latin
ValueCountFrequency (%)
B 29
27.6%
C 22
21.0%
M 10
 
9.5%
K 8
 
7.6%
S 8
 
7.6%
A 4
 
3.8%
F 4
 
3.8%
e 3
 
2.9%
V 3
 
2.9%
I 3
 
2.9%
Other values (7) 11
 
10.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125399
60.1%
ASCII 83376
39.9%
None 5
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47778
57.3%
1 6386
 
7.7%
4 6031
 
7.2%
2 4913
 
5.9%
3 4815
 
5.8%
5 3512
 
4.2%
6 2603
 
3.1%
8 1477
 
1.8%
7 1454
 
1.7%
0 1349
 
1.6%
Other values (27) 3058
 
3.7%
Hangul
ValueCountFrequency (%)
9557
 
7.6%
9540
 
7.6%
9524
 
7.6%
8780
 
7.0%
7121
 
5.7%
7057
 
5.6%
7043
 
5.6%
7040
 
5.6%
7037
 
5.6%
7034
 
5.6%
Other values (234) 45666
36.4%
None
ValueCountFrequency (%)
5
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

업소전화번호
Text

MISSING 

Distinct587
Distinct (%)9.3%
Missing1578
Missing (%)20.0%
Memory size61.7 KiB
2024-05-11T14:48:52.464015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.3735131
Min length2

Characters and Unicode

Total characters59100
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

Unique254 ?
Unique (%)4.0%

Sample

1st row34680152
2nd row34680152
3rd row02 6754531
4th row02 6754531
5th row02 6754531
ValueCountFrequency (%)
02 2281
25.9%
34680152 1007
 
11.4%
21658115 795
 
9.0%
21652611 550
 
6.2%
26708010 306
 
3.5%
26391043 300
 
3.4%
0222801050 225
 
2.6%
26302653 209
 
2.4%
0226706653 176
 
2.0%
26778877 168
 
1.9%
Other values (608) 2797
31.7%
2024-05-11T14:48:53.182111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10847
18.4%
0 9574
16.2%
1 7195
12.2%
6 6893
11.7%
8 4969
8.4%
5 4966
8.4%
3 4390
7.4%
7 3309
 
5.6%
3195
 
5.4%
4 2611
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55905
94.6%
Space Separator 3195
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10847
19.4%
0 9574
17.1%
1 7195
12.9%
6 6893
12.3%
8 4969
8.9%
5 4966
8.9%
3 4390
7.9%
7 3309
 
5.9%
4 2611
 
4.7%
9 1151
 
2.1%
Space Separator
ValueCountFrequency (%)
3195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59100
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10847
18.4%
0 9574
16.2%
1 7195
12.2%
6 6893
11.7%
8 4969
8.4%
5 4966
8.4%
3 4390
7.4%
7 3309
 
5.6%
3195
 
5.4%
4 2611
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10847
18.4%
0 9574
16.2%
1 7195
12.2%
6 6893
11.7%
8 4969
8.4%
5 4966
8.4%
3 4390
7.4%
7 3309
 
5.6%
3195
 
5.4%
4 2611
 
4.4%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
3939 
수거
2115 
위생점검(전체)
1672 
위생점검(부분)
 
157

Length

Max length8
Median length4
Mean length4.3914753
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3939
50.0%
수거 2115
26.8%
위생점검(전체) 1672
21.2%
위생점검(부분) 157
 
2.0%

Length

2024-05-11T14:48:53.468131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:53.662133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3939
50.0%
수거 2115
26.8%
위생점검(전체 1672
21.2%
위생점검(부분 157
 
2.0%

점검일자
Real number (ℝ)

Distinct525
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20142853
Minimum20060427
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:53.876365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060427
5-th percentile20090401
Q120110113
median20131115
Q320170825
95-th percentile20211116
Maximum20240307
Range179880
Interquartile range (IQR)60712

Descriptive statistics

Standard deviation40858.985
Coefficient of variation (CV)0.0020284607
Kurtosis-0.85767735
Mean20142853
Median Absolute Deviation (MAD)30007
Skewness0.41458128
Sum1.5878611 × 1011
Variance1.6694567 × 109
MonotonicityNot monotonic
2024-05-11T14:48:54.195315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20101118 254
 
3.2%
20090401 199
 
2.5%
20100915 155
 
2.0%
20151103 132
 
1.7%
20101109 105
 
1.3%
20151118 100
 
1.3%
20170414 94
 
1.2%
20111129 92
 
1.2%
20130424 86
 
1.1%
20130115 72
 
0.9%
Other values (515) 6594
83.6%
ValueCountFrequency (%)
20060427 1
 
< 0.1%
20080129 35
0.4%
20080131 5
 
0.1%
20080201 6
 
0.1%
20080812 2
 
< 0.1%
20080821 5
 
0.1%
20080827 8
 
0.1%
20080828 4
 
0.1%
20080926 32
0.4%
20081020 3
 
< 0.1%
ValueCountFrequency (%)
20240307 2
 
< 0.1%
20240306 22
 
0.3%
20240305 4
 
0.1%
20240304 1
 
< 0.1%
20240227 1
 
< 0.1%
20240223 68
0.9%
20240118 1
 
< 0.1%
20240116 8
 
0.1%
20231208 3
 
< 0.1%
20231123 5
 
0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
<NA>
3661 
수시
2676 
기타
907 
합동
 
349
일제
 
290

Length

Max length4
Median length2
Mean length2.9288342
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3661
46.4%
수시 2676
33.9%
기타 907
 
11.5%
합동 349
 
4.4%
일제 290
 
3.7%

Length

2024-05-11T14:48:54.483219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:54.684575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3661
46.4%
수시 2676
33.9%
기타 907
 
11.5%
합동 349
 
4.4%
일제 290
 
3.7%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.7 KiB
1
4133 
<NA>
3661 
2
 
89

Length

Max length4
Median length1
Mean length2.3932513
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4133
52.4%
<NA> 3661
46.4%
2 89
 
1.1%

Length

2024-05-11T14:48:54.893723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:55.092319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4133
52.4%
na 3661
46.4%
2 89
 
1.1%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct359
Distinct (%)63.1%
Missing7314
Missing (%)92.8%
Infinite0
Infinite (%)0.0%
Mean19908595
Minimum0
Maximum20150102
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size69.4 KiB
2024-05-11T14:48:55.313315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20110725
Q120111229
median20120523
Q320121130
95-th percentile20131010
Maximum20150102
Range20150102
Interquartile range (IQR)9901

Descriptive statistics

Standard deviation2057059.5
Coefficient of variation (CV)0.1033252
Kurtosis90.646671
Mean19908595
Median Absolute Deviation (MAD)685
Skewness-9.6086836
Sum1.132799 × 1010
Variance4.2314937 × 1012
MonotonicityNot monotonic
2024-05-11T14:48:55.614121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110707 7
 
0.1%
20111214 6
 
0.1%
0 6
 
0.1%
20111222 6
 
0.1%
20111223 6
 
0.1%
20120126 5
 
0.1%
20111216 5
 
0.1%
20120414 5
 
0.1%
20120106 5
 
0.1%
20120612 5
 
0.1%
Other values (349) 513
 
6.5%
(Missing) 7314
92.8%
ValueCountFrequency (%)
0 6
0.1%
20110113 3
< 0.1%
20110116 1
 
< 0.1%
20110118 1
 
< 0.1%
20110119 1
 
< 0.1%
20110120 1
 
< 0.1%
20110121 1
 
< 0.1%
20110122 2
 
< 0.1%
20110125 1
 
< 0.1%
20110405 1
 
< 0.1%
ValueCountFrequency (%)
20150102 1
< 0.1%
20141023 1
< 0.1%
20140901 1
< 0.1%
20140831 1
< 0.1%
20140829 1
< 0.1%
20140729 1
< 0.1%
20140720 1
< 0.1%
20140704 1
< 0.1%
20140624 1
< 0.1%
20140527 1
< 0.1%
Distinct483
Distinct (%)47.9%
Missing6874
Missing (%)87.2%
Memory size61.7 KiB
2024-05-11T14:48:56.382891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length17.311199
Min length10

Characters and Unicode

Total characters17467
Distinct characters247
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

Unique292 ?
Unique (%)28.9%

Sample

1st row서울 은평구 응암동197-14
2nd row경북 구미시 옥계동 구미국가산업단지 제4단지601-7
3rd row경기 포천시 이동면 장암리151-17
4th row전남 여수시 망양로457
5th row전남 여수시 망양로457
ValueCountFrequency (%)
서울 175
 
4.6%
영등포구 170
 
4.4%
경기 136
 
3.6%
경기도 132
 
3.5%
충북 126
 
3.3%
양평동3가65 90
 
2.4%
서울시 84
 
2.2%
충남 79
 
2.1%
강남구 50
 
1.3%
음성군 48
 
1.3%
Other values (852) 2731
71.5%
2024-05-11T14:48:57.520414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2813
 
16.1%
1 697
 
4.0%
643
 
3.7%
- 601
 
3.4%
552
 
3.2%
540
 
3.1%
3 509
 
2.9%
2 487
 
2.8%
4 388
 
2.2%
5 382
 
2.2%
Other values (237) 9855
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10242
58.6%
Decimal Number 3792
 
21.7%
Space Separator 2813
 
16.1%
Dash Punctuation 601
 
3.4%
Uppercase Letter 7
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
643
 
6.3%
552
 
5.4%
540
 
5.3%
382
 
3.7%
362
 
3.5%
315
 
3.1%
284
 
2.8%
278
 
2.7%
273
 
2.7%
267
 
2.6%
Other values (219) 6346
62.0%
Decimal Number
ValueCountFrequency (%)
1 697
18.4%
3 509
13.4%
2 487
12.8%
4 388
10.2%
5 382
10.1%
6 347
9.2%
7 279
7.4%
0 277
 
7.3%
9 251
 
6.6%
8 175
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
71.4%
T 2
 
28.6%
Space Separator
ValueCountFrequency (%)
2813
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
; 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10242
58.6%
Common 7216
41.3%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
643
 
6.3%
552
 
5.4%
540
 
5.3%
382
 
3.7%
362
 
3.5%
315
 
3.1%
284
 
2.8%
278
 
2.7%
273
 
2.7%
267
 
2.6%
Other values (219) 6346
62.0%
Common
ValueCountFrequency (%)
2813
39.0%
1 697
 
9.7%
- 601
 
8.3%
3 509
 
7.1%
2 487
 
6.7%
4 388
 
5.4%
5 382
 
5.3%
6 347
 
4.8%
7 279
 
3.9%
0 277
 
3.8%
Other values (5) 436
 
6.0%
Latin
ValueCountFrequency (%)
B 5
55.6%
a 2
 
22.2%
T 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10240
58.6%
ASCII 7225
41.4%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2813
38.9%
1 697
 
9.6%
- 601
 
8.3%
3 509
 
7.0%
2 487
 
6.7%
4 388
 
5.4%
5 382
 
5.3%
6 347
 
4.8%
7 279
 
3.9%
0 277
 
3.8%
Other values (8) 445
 
6.2%
Hangul
ValueCountFrequency (%)
643
 
6.3%
552
 
5.4%
540
 
5.3%
382
 
3.7%
362
 
3.5%
315
 
3.1%
284
 
2.8%
278
 
2.7%
273
 
2.7%
267
 
2.6%
Other values (218) 6344
62.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%

부적합항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7883
Missing (%)100.0%
Memory size69.4 KiB

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(Kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03180000106식품제조가공업<NA><NA><NA><NA>2024-가정간편식-1검사용(주)이코니크C0322020300000즉석조리식품즉석조리식품웜그레인샐러드오리엔탈<NA><NA><NA>202403075.0194g<NA><NA><NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240307<NA><NA><NA><NA><NA><NA><NA><NA>20220108121<NA><NA><NA><NA><NA>서울특별시 영등포구 선유서로31길 3, 미디어 비즈 센타 5,6층 (양평동3가)서울특별시 영등포구 양평동3가 23번지 5호 미디어 비즈 센타<NA>위생점검(부분)20240306합동<NA>1<NA><NA><NA><NA>
13180000114기타식품판매업<NA><NA><NA><NA>2024-가정간편식-2검사용(주)이마트 영등포점C0322020400000간편조리세트간편조리세트카덴 마제우동<NA><NA><NA>202403075.0947.4g<NA><NA><NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240307<NA><NA><NA><NA><NA><NA><NA><NA>20090087160<NA><NA><NA><NA><NA>서울특별시 영등포구 영중로 15, (영등포동4가,지하1층,2층)서울특별시 영등포구 영등포동4가 442번지 지하1층,2층34680152<NA>20240307<NA><NA><NA><NA><NA><NA><NA>
23180000114기타식품판매업<NA><NA><NA><NA>2024-가정간편식-3검사용(주)이마트 영등포점C0322020200000신선편의식품신선편의식품델몬트 파인애플 (400)<NA><NA><NA>202403075.0400g<NA><NA><NA><NA><NA>냉장<NA><NA>001<NA>국내<NA>120240307<NA><NA><NA><NA><NA><NA><NA><NA>20090087160<NA><NA><NA><NA><NA>서울특별시 영등포구 영중로 15, (영등포동4가,지하1층,2층)서울특별시 영등포구 영등포동4가 442번지 지하1층,2층34680152<NA>20240307<NA><NA><NA><NA><NA><NA><NA>
33180000105집단급식소<NA><NA><NA>식중독 조사2024-03-07검사용당서초등학교G0100000100000조리식품 등조리식품 등배추김치1<NA><NA><NA>202403061.0100g<NA>20240304<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
43180000105집단급식소<NA><NA><NA>식중독 조사2024-03-19검사용당서초등학교Z3800100000000기타기준규격외기타기준규격외식판<NA><NA><NA>20240306<NA><NA><NA>1개20240306<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
53180000105집단급식소<NA><NA><NA>식중독 조사2024-03-06검사용당서초등학교G0100000100000조리식품 등조리식품 등김구이<NA><NA><NA>202403061.020g<NA>20240304<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
63180000105집단급식소<NA><NA><NA>식중독 조사2024-03-18검사용당서초등학교Z3800100000000기타기준규격외기타기준규격외도마<NA><NA><NA>20240306<NA><NA><NA>1개20240306<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
73180000105집단급식소<NA><NA><NA>식중독 조사2024-03-17검사용당서초등학교Z3800100000000기타기준규격외기타기준규격외<NA><NA><NA>20240306<NA><NA><NA>1개20240306<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
83180000105집단급식소<NA><NA><NA>식중독 조사2024-03-16검사용당서초등학교G0100000100000조리식품 등조리식품 등우유2<NA><NA><NA>202403061.0100g<NA>20240305<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><NA><NA><NA><NA>
93180000105집단급식소<NA><NA><NA>식중독 조사2024-03-15검사용당서초등학교G0100000100000조리식품 등조리식품 등새학기기념케이크<NA><NA><NA>202403061.0100g<NA>20240305<NA><NA><NA>냉동<NA><NA>001<NA>국내<NA>220240306<NA><NA><NA><NA><NA><NA><NA><NA>19990086262<NA><NA><NA><NA><NA>서울특별시 영등포구 당산로 187, (당산동5가)서울특별시 영등포구 당산동5가 5번지 3호02 6754531<NA>20240306<NA><NA><NA><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
78733180000106식품제조가공업<NA><NA><NA><NA><NA><NA>한흥유과201000000과자류강정(또는유과)찹살약과<NA><NA><NA>200802016.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19670086001<NA><NA><NA><NA><NA>서울특별시 영등포구 가마산로61길 14-13, (신길동)서울특별시 영등포구 신길동 310번지 3호02 8414341<NA>20080201<NA><NA><NA><NA><NA><NA><NA>
78743180000106식품제조가공업<NA><NA><NA><NA><NA><NA>고려웰빙216000000인삼제품류홍삼음료(홍삼사용제품)홍삼액플러스<NA><NA><NA>200802013.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20060087111<NA><NA><NA><NA><NA>서울특별시 영등포구 대방천로 168-7, (신길동,1층)서울특별시 영등포구 신길동 4590번지 1층02 8353903<NA>20080201<NA><NA><NA><NA><NA><NA><NA>
78753180000106식품제조가공업<NA><NA><NA><NA><NA><NA>좋은날201000000과자류강정(또는유과)개성약과<NA><NA><NA>200802013.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20020086126<NA><NA><NA><NA><NA>서울특별시 영등포구 신길로38길 11, (신길동)서울특별시 영등포구 신길동 4909번지 3호02 8486436<NA>20080201<NA><NA><NA><NA><NA><NA><NA>
78763180000106식품제조가공업<NA><NA><NA><NA><NA><NA>경북기름집208000000식용유지류압착참기름민속참기름<NA><NA><NA>200801313.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20060087049<NA><NA><NA><NA><NA>서울특별시 영등포구 영중로20길 23-6, (영등포동5가)서울특별시 영등포구 영등포동5가 33번지 98호0226769212<NA>20080131<NA><NA><NA><NA><NA><NA><NA>
78773180000106식품제조가공업<NA><NA><NA><NA><NA><NA>서신식품(주)207000000두부류또는묵류두부고소한무침두부<NA><NA><NA>20080131200.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19780086050<NA><NA><NA><NA><NA>서울특별시 영등포구 국회대로37길 8, (당산동4가)서울특별시 영등포구 당산동4가 1번지 143호0226720617<NA>20080131<NA><NA><NA><NA><NA><NA><NA>
78783180000106식품제조가공업<NA><NA><NA><NA><NA><NA>대성종합식품208000000식용유지류압착참기름참기름<NA><NA><NA>200801313.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20040086578<NA><NA><NA><NA><NA>서울특별시 영등포구 국회대로52길 8-1, (영등포동7가,외(142-9))서울특별시 영등포구 영등포동7가 81번지 2호 외(142-9)0220683101<NA>20080131<NA><NA><NA><NA><NA><NA><NA>
78793180000106식품제조가공업<NA><NA><NA><NA><NA><NA>제일식품208000000식용유지류압착참기름고소한참기름<NA><NA><NA>200801313.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20040087536<NA><NA><NA><NA><NA>서울특별시 영등포구 영등포로45길 24-2, (영등포동2가,지상1층)서울특별시 영등포구 영등포동2가 421번지 지상1층0226349036<NA>20080131<NA><NA><NA><NA><NA><NA><NA>
78803180000106식품제조가공업<NA><NA><NA><NA><NA><NA>초원종합식품207000000두부류또는묵류두부판두부<NA><NA><NA>200801313.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20000087042<NA><NA><NA><NA><NA>서울특별시 영등포구 양평로 158, (양평동5가)서울특별시 영등포구 양평동5가 51번지0226759240<NA>20080131<NA><NA><NA><NA><NA><NA><NA>
78813180000113유통전문판매업<NA><NA><NA><NA><NA><NA>삼성테스코(주)홈플러스영등포점<NA><NA>홈플러스 부산어묵 대봉<NA><NA><NA>200604271.2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 보건환경연구원<NA>국외<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>20010088222<NA><NA><NA>삼성홈플러스 문래동지점유통기한이 짧아 제고량이 남아 있지 않음서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호<NA>위생점검(부분)20060427합동<NA>2<NA><NA><NA><NA>
78823180000101일반음식점<NA><NA><NA><NA><NA><NA>씨제이푸드빌(주)빕스서여의도점829000000기타식품류즉석섭취식품양상추<NA><NA><NA>200310301.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20060086333<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 13번지 진미빌딩 지상1층, 지하1층<NA><NA>20090519합동<NA>1<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소# duplicates
203180000114기타식품판매업<NA><NA><NA><NA><NA>삼성테스코(주)홈플러스영등포점201000000과자류초콜릿가공품땅콩스니커즈<NA><NA><NA>200809293.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20010088221<NA><NA>서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호02 21658115수거20080926기타1<NA><NA>6
53180000112식품자동판매기영업<NA><NA><NA><NA><NA>서울대윤병원817000000커피인스턴트커피커피<NA><NA><NA>201004161.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20090087646<NA><NA>서울특별시 영등포구 영등포로 358, (신길동,1층)서울특별시 영등포구 신길동 103번지 21호 1층02 841 0101위생점검(전체)20101125기타1<NA><NA>4
13180000104휴게음식점<NA><NA><NA><NA><NA>바이더웨이 여의도공원점201000000과자류초콜릿초콜릿<NA><NA><NA>200902134.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20070086944<NA><NA><NA>서울특별시 영등포구 여의도동 2번지 여의공원길 7126718342<NA>20090319합동1<NA><NA>3
23180000104휴게음식점<NA><NA><NA><NA><NA>훼미리마트신길지점201000000과자류초콜릿초콜릿<NA><NA><NA>200902134.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19940086971<NA><NA>서울특별시 영등포구 신길로 164, (신길동)서울특별시 영등포구 신길동 4902번지 0호0208340753<NA>20090317합동1<NA><NA>3
63180000112식품자동판매기영업<NA><NA><NA><NA><NA>오렌지마트201000000과자류초콜릿초콜릿<NA><NA><NA>200902134.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19970086362<NA><NA>서울특별시 영등포구 경인로102길 4, (영등포동)서울특별시 영등포구 영등포동 618번지 91호02 6789479위생점검(전체)20090515일제1<NA><NA>3
193180000114기타식품판매업<NA><NA><NA><NA><NA>삼성테스코(주)홈플러스영등포점201000000과자류초콜릿가공품도브모카아몬드<NA><NA><NA>200809293.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20010088221<NA><NA>서울특별시 영등포구 당산로 42, (문래동3가)서울특별시 영등포구 문래동3가 55번지 3호02 21658115수거20080926기타1<NA><NA>3
03180000104휴게음식점<NA><NA>기타 일상수거검사조리19-7-30검사용코스트코코리아G0100000100000조리식품 등조리식품 등치킨덮밥<NA><NA><NA>201807311.0400g<NA>20180731<NA><NA><NA>냉장<NA><NA><NA>국내<NA>2<NA><NA><NA><NA>20040086131<NA><NA>서울특별시 영등포구 선유로 156, (양평동3가)서울특별시 영등포구 양평동3가 65번지0226301234<NA>20180731<NA><NA><NA><NA>2
33180000105집단급식소<NA><NA><NA><NA><NA>서울대윤병원829000000기타식품류즉석섭취식품고구마순볶음<NA><NA><NA>200910091.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>20080087041<NA><NA>서울특별시 영등포구 영등포로 358, (신길동,지하1층)서울특별시 영등포구 신길동 103번지 21호 지하1층<NA><NA>20090323합동1<NA><NA>2
43180000107즉석판매제조가공업<NA><NA><NA><NA><NA>영일기름집814000000식용유지류참기름참기름<NA><NA><NA>200901193.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA>19810086044<NA><NA>서울특별시 영등포구 경인로89길 2, (문래동3가)서울특별시 영등포구 문래동3가 8번지 5호0226336498위생점검(전체)20090119합동1<NA><NA>2
73180000114기타식품판매업999식품제조가공업소 등 지도점검<NA>119-5-64검사용롯데마트 서울양평점C0118010300000과.채음료과.채음료MOGU MOGU GRAPE JUICE 25% (WITH NATA DE COCO)<NA><NA><NA>201805303.0320ML<NA><NA><NA><NA><NA>실온<NA>002<NA>국외태국220180531201806151<NA>20170086501<NA><NA>서울특별시 영등포구 선유로 138, 지하1,2층 (양평동3가, 롯데마트 양평점)서울특별시 영등포구 양평동3가 45번지<NA>수거20180531수시1<NA><NA>2