Overview

Dataset statistics

Number of variables61
Number of observations5301
Missing cells145740
Missing cells (%)45.1%
Duplicate rows19
Duplicate rows (%)0.4%
Total size in memory2.6 MiB
Average record size in memory522.0 B

Variable types

Categorical19
Numeric10
Unsupported17
Text15

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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-10146/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 19 (0.4%) duplicate rowsDuplicates
업종명 is highly imbalanced (53.3%)Imbalance
지도점검계획 is highly imbalanced (50.6%)Imbalance
수거계획 is highly imbalanced (64.0%)Imbalance
수거사유코드 is highly imbalanced (58.0%)Imbalance
음식물명 is highly imbalanced (94.3%)Imbalance
수거량(자유) is highly imbalanced (89.0%)Imbalance
유통기한(제조일기준) is highly imbalanced (97.8%)Imbalance
국가명 is highly imbalanced (92.4%)Imbalance
계획구분명 has 5301 (100.0%) missing valuesMissing
수거증번호 has 1105 (20.8%) missing valuesMissing
식품군 has 624 (11.8%) missing valuesMissing
품목명 has 302 (5.7%) missing valuesMissing
원료명 has 5280 (99.6%) missing valuesMissing
생산업소 has 4868 (91.8%) missing valuesMissing
수거량(정량) has 385 (7.3%) missing valuesMissing
제품규격(정량) has 1490 (28.1%) missing valuesMissing
제조일자(일자) has 4139 (78.1%) missing valuesMissing
제조일자(롯트) has 5301 (100.0%) missing valuesMissing
유통기한(일자) has 5048 (95.2%) missing valuesMissing
바코드번호 has 5301 (100.0%) missing valuesMissing
어린이기호식품유형 has 5301 (100.0%) missing valuesMissing
(구)제조사명 has 4725 (89.1%) missing valuesMissing
검사의뢰일자 has 3930 (74.1%) missing valuesMissing
결과회보일자 has 4523 (85.3%) missing valuesMissing
처리구분 has 5301 (100.0%) missing valuesMissing
수거검사구분코드 has 5301 (100.0%) missing valuesMissing
단속지역구분코드 has 5301 (100.0%) missing valuesMissing
수거장소구분코드 has 5301 (100.0%) missing valuesMissing
처리결과 has 5301 (100.0%) missing valuesMissing
수거품처리 has 5301 (100.0%) missing valuesMissing
폐기일자 has 5301 (100.0%) missing valuesMissing
폐기량(kg) has 5301 (100.0%) missing valuesMissing
폐기금액(원) has 5301 (100.0%) missing valuesMissing
폐기장소 has 5301 (100.0%) missing valuesMissing
폐기방법 has 5301 (100.0%) missing valuesMissing
소재지(도로명) has 2563 (48.3%) missing valuesMissing
소재지(지번) has 740 (14.0%) missing valuesMissing
업소전화번호 has 448 (8.5%) missing valuesMissing
점검내용 has 5301 (100.0%) missing valuesMissing
(구)제조유통기한 has 5048 (95.2%) missing valuesMissing
(구)제조회사주소 has 5082 (95.9%) missing valuesMissing
부적합항목 has 5299 (> 99.9%) missing valuesMissing
기준치부적합내용 has 5301 (100.0%) missing valuesMissing
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제조일자(롯트) is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
어린이기호식품유형 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
처리결과 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:49:06.402760
Analysis finished2024-05-11 05:49:12.495079
Duration6.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
3170000
5301 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 5301
100.0%

Length

2024-05-11T05:49:12.772174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:13.076475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 5301
100.0%

업종코드
Real number (ℝ)

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.17261
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:13.396484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1106
median114
Q3114
95-th percentile114
Maximum134
Range33
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.4771405
Coefficient of variation (CV)0.049266997
Kurtosis1.1245172
Mean111.17261
Median Absolute Deviation (MAD)0
Skewness-0.45868317
Sum589326
Variance29.999068
MonotonicityIncreasing
2024-05-11T05:49:13.859721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
114 3630
68.5%
101 776
 
14.6%
105 229
 
4.3%
106 180
 
3.4%
104 176
 
3.3%
112 108
 
2.0%
107 92
 
1.7%
121 50
 
0.9%
134 34
 
0.6%
120 14
 
0.3%
Other values (2) 12
 
0.2%
ValueCountFrequency (%)
101 776
 
14.6%
104 176
 
3.3%
105 229
 
4.3%
106 180
 
3.4%
107 92
 
1.7%
112 108
 
2.0%
114 3630
68.5%
120 14
 
0.3%
121 50
 
0.9%
122 11
 
0.2%
ValueCountFrequency (%)
134 34
 
0.6%
133 1
 
< 0.1%
122 11
 
0.2%
121 50
 
0.9%
120 14
 
0.3%
114 3630
68.5%
112 108
 
2.0%
107 92
 
1.7%
106 180
 
3.4%
105 229
 
4.3%

업종명
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
기타식품판매업
3630 
일반음식점
776 
집단급식소
 
229
식품제조가공업
 
180
휴게음식점
 
176
Other values (7)
 
310

Length

Max length11
Median length7
Mean length6.6406338
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 3630
68.5%
일반음식점 776
 
14.6%
집단급식소 229
 
4.3%
식품제조가공업 180
 
3.4%
휴게음식점 176
 
3.3%
식품자동판매기영업 108
 
2.0%
즉석판매제조가공업 92
 
1.7%
제과점영업 50
 
0.9%
건강기능식품일반판매업 34
 
0.6%
위탁급식영업 14
 
0.3%
Other values (2) 12
 
0.2%

Length

2024-05-11T05:49:14.309459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 3630
68.5%
일반음식점 776
 
14.6%
집단급식소 229
 
4.3%
식품제조가공업 180
 
3.4%
휴게음식점 176
 
3.3%
식품자동판매기영업 108
 
2.0%
즉석판매제조가공업 92
 
1.7%
제과점영업 50
 
0.9%
건강기능식품일반판매업 34
 
0.6%
위탁급식영업 14
 
0.3%
Other values (2) 12
 
0.2%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
3774 
999
1229 
7
 
252
2
 
46

Length

Max length4
Median length4
Mean length3.5995095
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> 3774
71.2%
999 1229
 
23.2%
7 252
 
4.8%
2 46
 
0.9%

Length

2024-05-11T05:49:14.857041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:15.444385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3774
71.2%
999 1229
 
23.2%
7 252
 
4.8%
2 46
 
0.9%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
3774 
가공식품안전 업무계획
1000 
민원발생에 따른 지도점검
 
252
식품접객업소 지도점검 계획
 
220
집단급식소 등 식중독예방 지도점검
 
46

Length

Max length18
Median length4
Mean length6.2967365
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3774
71.2%
가공식품안전 업무계획 1000
 
18.9%
민원발생에 따른 지도점검 252
 
4.8%
식품접객업소 지도점검 계획 220
 
4.2%
집단급식소 등 식중독예방 지도점검 46
 
0.9%
식품접객업소 시설조사 9
 
0.2%

Length

2024-05-11T05:49:15.901398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:16.456758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3774
51.1%
가공식품안전 1000
 
13.5%
업무계획 1000
 
13.5%
지도점검 518
 
7.0%
민원발생에 252
 
3.4%
따른 252
 
3.4%
식품접객업소 229
 
3.1%
계획 220
 
3.0%
집단급식소 46
 
0.6%
46
 
0.6%
Other values (2) 55
 
0.7%

수거계획
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
4409 
시민다소비식품 수거검사
680 
기타 식품접객업소 수거검사
 
143
민원발생에 따른 수거검사
 
42
식중독 예방을 위한 수거검사
 
27

Length

Max length15
Median length4
Mean length5.4233164
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4409
83.2%
시민다소비식품 수거검사 680
 
12.8%
기타 식품접객업소 수거검사 143
 
2.7%
민원발생에 따른 수거검사 42
 
0.8%
식중독 예방을 위한 수거검사 27
 
0.5%

Length

2024-05-11T05:49:17.076722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:17.689264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4409
68.5%
수거검사 892
 
13.9%
시민다소비식품 680
 
10.6%
기타 143
 
2.2%
식품접객업소 143
 
2.2%
민원발생에 42
 
0.7%
따른 42
 
0.7%
식중독 27
 
0.4%
예방을 27
 
0.4%
위한 27
 
0.4%

수거증번호
Text

MISSING 

Distinct2053
Distinct (%)48.9%
Missing1105
Missing (%)20.8%
Memory size41.5 KiB
2024-05-11T05:49:18.771886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.07245
Min length3

Characters and Unicode

Total characters33872
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1323 ?
Unique (%)31.5%

Sample

1st row13-09-10
2nd row118-10-42
3rd row118-06-06
4th row118-06-07
5th row118-06-08
ValueCountFrequency (%)
118-3-1 9
 
0.2%
118-3-11 9
 
0.2%
118-3-6 9
 
0.2%
118-3-7 9
 
0.2%
118-11-10 9
 
0.2%
118-3-2 9
 
0.2%
118-3-4 8
 
0.2%
118-12-7 8
 
0.2%
118-3-9 8
 
0.2%
118-12-5 8
 
0.2%
Other values (2044) 4111
98.0%
2024-05-11T05:49:20.365957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11097
32.8%
- 8068
23.8%
8 4386
 
12.9%
2 1976
 
5.8%
3 1573
 
4.6%
0 1386
 
4.1%
6 1272
 
3.8%
7 1126
 
3.3%
5 1012
 
3.0%
4 1004
 
3.0%
Other values (24) 972
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25665
75.8%
Dash Punctuation 8068
 
23.8%
Other Letter 96
 
0.3%
Open Punctuation 22
 
0.1%
Close Punctuation 20
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
29.2%
14
14.6%
14
14.6%
7
 
7.3%
7
 
7.3%
4
 
4.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
Other values (10) 10
 
10.4%
Decimal Number
ValueCountFrequency (%)
1 11097
43.2%
8 4386
 
17.1%
2 1976
 
7.7%
3 1573
 
6.1%
0 1386
 
5.4%
6 1272
 
5.0%
7 1126
 
4.4%
5 1012
 
3.9%
4 1004
 
3.9%
9 833
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 8068
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33776
99.7%
Hangul 96
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
29.2%
14
14.6%
14
14.6%
7
 
7.3%
7
 
7.3%
4
 
4.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
Other values (10) 10
 
10.4%
Common
ValueCountFrequency (%)
1 11097
32.9%
- 8068
23.9%
8 4386
 
13.0%
2 1976
 
5.9%
3 1573
 
4.7%
0 1386
 
4.1%
6 1272
 
3.8%
7 1126
 
3.3%
5 1012
 
3.0%
4 1004
 
3.0%
Other values (4) 876
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33776
99.7%
Hangul 96
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11097
32.9%
- 8068
23.9%
8 4386
 
13.0%
2 1976
 
5.9%
3 1573
 
4.7%
0 1386
 
4.1%
6 1272
 
3.8%
7 1126
 
3.3%
5 1012
 
3.0%
4 1004
 
3.0%
Other values (4) 876
 
2.6%
Hangul
ValueCountFrequency (%)
28
29.2%
14
14.6%
14
14.6%
7
 
7.3%
7
 
7.3%
4
 
4.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
Other values (10) 10
 
10.4%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
검사용
3431 
<NA>
1847 
기타
 
17
증거용
 
4
압류
 
2

Length

Max length4
Median length3
Mean length3.3448406
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 3431
64.7%
<NA> 1847
34.8%
기타 17
 
0.3%
증거용 4
 
0.1%
압류 2
 
< 0.1%

Length

2024-05-11T05:49:20.867971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:21.233823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 3431
64.7%
na 1847
34.8%
기타 17
 
0.3%
증거용 4
 
0.1%
압류 2
 
< 0.1%
Distinct536
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2024-05-11T05:49:21.826470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length9.0673458
Min length1

Characters and Unicode

Total characters48066
Distinct characters460
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

Unique268 ?
Unique (%)5.1%

Sample

1st row원조마포갈비
2nd row삼미영양탕
3rd row쇠가리육회
4th row쇠가리육회
5th row쇠가리육회
ValueCountFrequency (%)
홈플러스(주)금천점 802
 
11.8%
금천점 553
 
8.2%
홈플러스테스코시흥점 403
 
6.0%
롯데마트금천점 375
 
5.5%
롯데쇼핑(주)롯데마트 374
 
5.5%
시흥점 369
 
5.5%
주)홈플러스테스코시흥점 324
 
4.8%
하모니마트 267
 
3.9%
은행나무마트 216
 
3.2%
삼성홈플러스 171
 
2.5%
Other values (604) 2914
43.1%
2024-05-11T05:49:23.139461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3246
 
6.8%
2884
 
6.0%
( 2190
 
4.6%
) 2190
 
4.6%
2110
 
4.4%
1935
 
4.0%
1925
 
4.0%
1924
 
4.0%
1907
 
4.0%
1879
 
3.9%
Other values (450) 25876
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41687
86.7%
Open Punctuation 2190
 
4.6%
Close Punctuation 2190
 
4.6%
Space Separator 1471
 
3.1%
Decimal Number 301
 
0.6%
Uppercase Letter 127
 
0.3%
Lowercase Letter 53
 
0.1%
Other Punctuation 47
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3246
 
7.8%
2884
 
6.9%
2110
 
5.1%
1935
 
4.6%
1925
 
4.6%
1924
 
4.6%
1907
 
4.6%
1879
 
4.5%
1675
 
4.0%
1568
 
3.8%
Other values (416) 20634
49.5%
Uppercase Letter
ValueCountFrequency (%)
B 21
16.5%
W 20
15.7%
F 19
15.0%
C 16
12.6%
K 15
11.8%
D 7
 
5.5%
T 7
 
5.5%
S 4
 
3.1%
G 4
 
3.1%
M 3
 
2.4%
Other values (5) 11
8.7%
Decimal Number
ValueCountFrequency (%)
5 69
22.9%
6 62
20.6%
3 60
19.9%
1 46
15.3%
7 35
11.6%
0 15
 
5.0%
2 13
 
4.3%
4 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
m 18
34.0%
a 17
32.1%
p 17
32.1%
i 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 17
36.2%
; 17
36.2%
12
25.5%
. 1
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 2190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2190
100.0%
Space Separator
ValueCountFrequency (%)
1471
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41687
86.7%
Common 6199
 
12.9%
Latin 180
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3246
 
7.8%
2884
 
6.9%
2110
 
5.1%
1935
 
4.6%
1925
 
4.6%
1924
 
4.6%
1907
 
4.6%
1879
 
4.5%
1675
 
4.0%
1568
 
3.8%
Other values (416) 20634
49.5%
Latin
ValueCountFrequency (%)
B 21
11.7%
W 20
11.1%
F 19
10.6%
m 18
10.0%
a 17
9.4%
p 17
9.4%
C 16
8.9%
K 15
8.3%
D 7
 
3.9%
T 7
 
3.9%
Other values (9) 23
12.8%
Common
ValueCountFrequency (%)
( 2190
35.3%
) 2190
35.3%
1471
23.7%
5 69
 
1.1%
6 62
 
1.0%
3 60
 
1.0%
1 46
 
0.7%
7 35
 
0.6%
& 17
 
0.3%
; 17
 
0.3%
Other values (5) 42
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41687
86.7%
ASCII 6367
 
13.2%
None 12
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3246
 
7.8%
2884
 
6.9%
2110
 
5.1%
1935
 
4.6%
1925
 
4.6%
1924
 
4.6%
1907
 
4.6%
1879
 
4.5%
1675
 
4.0%
1568
 
3.8%
Other values (416) 20634
49.5%
ASCII
ValueCountFrequency (%)
( 2190
34.4%
) 2190
34.4%
1471
23.1%
5 69
 
1.1%
6 62
 
1.0%
3 60
 
0.9%
1 46
 
0.7%
7 35
 
0.5%
B 21
 
0.3%
W 20
 
0.3%
Other values (23) 203
 
3.2%
None
ValueCountFrequency (%)
12
100.0%
Distinct327
Distinct (%)6.2%
Missing24
Missing (%)0.5%
Memory size41.5 KiB
2024-05-11T05:49:23.888205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.947129
Min length1

Characters and Unicode

Total characters57768
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

Unique107 ?
Unique (%)2.0%

Sample

1st row121000000
2nd rowG0100000100000
3rd row121000000
4th row121000000
5th row410000000
ValueCountFrequency (%)
g0100000100000 336
 
6.8%
821000000 197
 
4.0%
829000000 186
 
3.8%
830000000 171
 
3.5%
818000000 170
 
3.4%
816000000 161
 
3.3%
600000000 151
 
3.1%
801000000 144
 
2.9%
815000000 135
 
2.7%
899000000 123
 
2.5%
Other values (315) 3166
64.1%
2024-05-11T05:49:25.080631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38147
66.0%
1 5312
 
9.2%
8 2686
 
4.6%
2681
 
4.6%
2 2504
 
4.3%
C 1625
 
2.8%
3 1609
 
2.8%
9 667
 
1.2%
6 563
 
1.0%
G 533
 
0.9%
Other values (11) 1441
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52691
91.2%
Space Separator 2681
 
4.6%
Uppercase Letter 2396
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38147
72.4%
1 5312
 
10.1%
8 2686
 
5.1%
2 2504
 
4.8%
3 1609
 
3.1%
9 667
 
1.3%
6 563
 
1.1%
4 460
 
0.9%
5 420
 
0.8%
7 323
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 1625
67.8%
G 533
 
22.2%
B 159
 
6.6%
E 25
 
1.0%
X 16
 
0.7%
H 14
 
0.6%
Z 13
 
0.5%
A 8
 
0.3%
F 2
 
0.1%
L 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2681
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55372
95.9%
Latin 2396
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38147
68.9%
1 5312
 
9.6%
8 2686
 
4.9%
2681
 
4.8%
2 2504
 
4.5%
3 1609
 
2.9%
9 667
 
1.2%
6 563
 
1.0%
4 460
 
0.8%
5 420
 
0.8%
Latin
ValueCountFrequency (%)
C 1625
67.8%
G 533
 
22.2%
B 159
 
6.6%
E 25
 
1.0%
X 16
 
0.7%
H 14
 
0.6%
Z 13
 
0.5%
A 8
 
0.3%
F 2
 
0.1%
L 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57768
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38147
66.0%
1 5312
 
9.2%
8 2686
 
4.6%
2681
 
4.6%
2 2504
 
4.3%
C 1625
 
2.8%
3 1609
 
2.8%
9 667
 
1.2%
6 563
 
1.0%
G 533
 
0.9%
Other values (11) 1441
 
2.5%

식품군
Text

MISSING 

Distinct257
Distinct (%)5.5%
Missing624
Missing (%)11.8%
Memory size41.5 KiB
2024-05-11T05:49:25.954738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.9683558
Min length1

Characters and Unicode

Total characters23237
Distinct characters292
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st row식육류중육류
2nd row조리식품 등
3rd row식육류중육류
4th row식육류중육류
5th row기구류
ValueCountFrequency (%)
378
 
6.8%
조리식품 336
 
6.1%
조미식품 197
 
3.6%
기타식품류 187
 
3.4%
규격외일반가공식품 171
 
3.1%
음료류 170
 
3.1%
다류 161
 
2.9%
식품접객업 151
 
2.7%
과자류 144
 
2.6%
면류 136
 
2.5%
Other values (277) 3501
63.3%
2024-05-11T05:49:27.108748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2164
 
9.3%
1877
 
8.1%
1707
 
7.3%
855
 
3.7%
823
 
3.5%
753
 
3.2%
661
 
2.8%
611
 
2.6%
587
 
2.5%
441
 
1.9%
Other values (282) 12758
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22034
94.8%
Space Separator 855
 
3.7%
Other Punctuation 164
 
0.7%
Open Punctuation 86
 
0.4%
Close Punctuation 86
 
0.4%
Uppercase Letter 11
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2164
 
9.8%
1877
 
8.5%
1707
 
7.7%
823
 
3.7%
753
 
3.4%
661
 
3.0%
611
 
2.8%
587
 
2.7%
441
 
2.0%
380
 
1.7%
Other values (268) 12030
54.6%
Uppercase Letter
ValueCountFrequency (%)
C 4
36.4%
A 3
27.3%
H 1
 
9.1%
D 1
 
9.1%
P 1
 
9.1%
E 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 84
51.2%
. 72
43.9%
/ 7
 
4.3%
1
 
0.6%
Space Separator
ValueCountFrequency (%)
855
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22034
94.8%
Common 1192
 
5.1%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2164
 
9.8%
1877
 
8.5%
1707
 
7.7%
823
 
3.7%
753
 
3.4%
661
 
3.0%
611
 
2.8%
587
 
2.7%
441
 
2.0%
380
 
1.7%
Other values (268) 12030
54.6%
Common
ValueCountFrequency (%)
855
71.7%
( 86
 
7.2%
) 86
 
7.2%
, 84
 
7.0%
. 72
 
6.0%
/ 7
 
0.6%
1
 
0.1%
2 1
 
0.1%
Latin
ValueCountFrequency (%)
C 4
36.4%
A 3
27.3%
H 1
 
9.1%
D 1
 
9.1%
P 1
 
9.1%
E 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22034
94.8%
ASCII 1202
 
5.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2164
 
9.8%
1877
 
8.5%
1707
 
7.7%
823
 
3.7%
753
 
3.4%
661
 
3.0%
611
 
2.8%
587
 
2.7%
441
 
2.0%
380
 
1.7%
Other values (268) 12030
54.6%
ASCII
ValueCountFrequency (%)
855
71.1%
( 86
 
7.2%
) 86
 
7.2%
, 84
 
7.0%
. 72
 
6.0%
/ 7
 
0.6%
C 4
 
0.3%
A 3
 
0.2%
H 1
 
0.1%
D 1
 
0.1%
Other values (3) 3
 
0.2%
None
ValueCountFrequency (%)
1
100.0%

품목명
Text

MISSING 

Distinct318
Distinct (%)6.4%
Missing302
Missing (%)5.7%
Memory size41.5 KiB
2024-05-11T05:49:28.098388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length5.0868174
Min length1

Characters and Unicode

Total characters25429
Distinct characters336
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

Unique95 ?
Unique (%)1.9%

Sample

1st row소고기
2nd row조리식품 등
3rd row기구류중나무제
4th row기구류중금속제
5th row기구류중기타
ValueCountFrequency (%)
559
 
8.6%
조리식품 536
 
8.2%
즉석조리식품 157
 
2.4%
소고기 133
 
2.0%
소스류 133
 
2.0%
기타가공품 127
 
2.0%
과자 118
 
1.8%
유탕면류 112
 
1.7%
액상차 111
 
1.7%
빵류 102
 
1.6%
Other values (340) 4420
67.9%
2024-05-11T05:49:29.176938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1509
 
5.9%
1476
 
5.8%
1178
 
4.6%
1056
 
4.2%
970
 
3.8%
917
 
3.6%
842
 
3.3%
734
 
2.9%
634
 
2.5%
563
 
2.2%
Other values (326) 15550
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23125
90.9%
Space Separator 1509
 
5.9%
Other Punctuation 380
 
1.5%
Open Punctuation 167
 
0.7%
Close Punctuation 167
 
0.7%
Uppercase Letter 55
 
0.2%
Dash Punctuation 9
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Decimal Number 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1476
 
6.4%
1178
 
5.1%
1056
 
4.6%
970
 
4.2%
917
 
4.0%
842
 
3.6%
734
 
3.2%
634
 
2.7%
563
 
2.4%
552
 
2.4%
Other values (302) 14203
61.4%
Uppercase Letter
ValueCountFrequency (%)
C 46
83.6%
A 3
 
5.5%
L 2
 
3.6%
H 1
 
1.8%
E 1
 
1.8%
P 1
 
1.8%
D 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
r 3
33.3%
a 1
 
11.1%
s 1
 
11.1%
p 1
 
11.1%
b 1
 
11.1%
e 1
 
11.1%
y 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 204
53.7%
, 168
44.2%
/ 7
 
1.8%
1
 
0.3%
Decimal Number
ValueCountFrequency (%)
3 7
87.5%
2 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1509
100.0%
Open Punctuation
ValueCountFrequency (%)
( 167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23125
90.9%
Common 2240
 
8.8%
Latin 64
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1476
 
6.4%
1178
 
5.1%
1056
 
4.6%
970
 
4.2%
917
 
4.0%
842
 
3.6%
734
 
3.2%
634
 
2.7%
563
 
2.4%
552
 
2.4%
Other values (302) 14203
61.4%
Latin
ValueCountFrequency (%)
C 46
71.9%
r 3
 
4.7%
A 3
 
4.7%
L 2
 
3.1%
H 1
 
1.6%
E 1
 
1.6%
P 1
 
1.6%
D 1
 
1.6%
a 1
 
1.6%
s 1
 
1.6%
Other values (4) 4
 
6.2%
Common
ValueCountFrequency (%)
1509
67.4%
. 204
 
9.1%
, 168
 
7.5%
( 167
 
7.5%
) 167
 
7.5%
- 9
 
0.4%
/ 7
 
0.3%
3 7
 
0.3%
2 1
 
< 0.1%
1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23125
90.9%
ASCII 2303
 
9.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1509
65.5%
. 204
 
8.9%
, 168
 
7.3%
( 167
 
7.3%
) 167
 
7.3%
C 46
 
2.0%
- 9
 
0.4%
/ 7
 
0.3%
3 7
 
0.3%
r 3
 
0.1%
Other values (13) 16
 
0.7%
Hangul
ValueCountFrequency (%)
1476
 
6.4%
1178
 
5.1%
1056
 
4.6%
970
 
4.2%
917
 
4.0%
842
 
3.6%
734
 
3.2%
634
 
2.7%
563
 
2.4%
552
 
2.4%
Other values (302) 14203
61.4%
None
ValueCountFrequency (%)
1
100.0%
Distinct3871
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
2024-05-11T05:49:29.974207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length34
Mean length7.0288625
Min length1

Characters and Unicode

Total characters37260
Distinct characters889
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3310 ?
Unique (%)62.4%

Sample

1st row한우(등심)
2nd row수육
3rd row육회
4th row원료식육
5th row도마
ValueCountFrequency (%)
커피 93
 
1.3%
수족관물 55
 
0.8%
등심 49
 
0.7%
청정원 40
 
0.6%
김밥 38
 
0.5%
참기름 35
 
0.5%
한우(등심 33
 
0.5%
한우등심 32
 
0.4%
두부 32
 
0.4%
31
 
0.4%
Other values (4276) 6818
94.0%
2024-05-11T05:49:31.128111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1956
 
5.2%
1004
 
2.7%
709
 
1.9%
602
 
1.6%
518
 
1.4%
487
 
1.3%
453
 
1.2%
411
 
1.1%
404
 
1.1%
375
 
1.0%
Other values (879) 30341
81.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33205
89.1%
Space Separator 1956
 
5.2%
Uppercase Letter 660
 
1.8%
Decimal Number 438
 
1.2%
Close Punctuation 290
 
0.8%
Open Punctuation 288
 
0.8%
Lowercase Letter 273
 
0.7%
Other Punctuation 124
 
0.3%
Dash Punctuation 20
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1004
 
3.0%
709
 
2.1%
602
 
1.8%
518
 
1.6%
487
 
1.5%
453
 
1.4%
411
 
1.2%
404
 
1.2%
375
 
1.1%
374
 
1.1%
Other values (802) 27868
83.9%
Uppercase Letter
ValueCountFrequency (%)
E 61
 
9.2%
I 61
 
9.2%
A 60
 
9.1%
C 57
 
8.6%
N 45
 
6.8%
L 38
 
5.8%
S 37
 
5.6%
H 32
 
4.8%
M 32
 
4.8%
O 31
 
4.7%
Other values (16) 206
31.2%
Lowercase Letter
ValueCountFrequency (%)
e 33
12.1%
a 30
11.0%
p 28
10.3%
m 25
9.2%
s 19
 
7.0%
i 18
 
6.6%
t 17
 
6.2%
l 16
 
5.9%
u 14
 
5.1%
r 14
 
5.1%
Other values (12) 59
21.6%
Other Punctuation
ValueCountFrequency (%)
& 35
28.2%
% 20
16.1%
. 17
13.7%
; 14
 
11.3%
? 11
 
8.9%
/ 8
 
6.5%
, 7
 
5.6%
4
 
3.2%
! 3
 
2.4%
2
 
1.6%
Other values (2) 3
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 107
24.4%
0 102
23.3%
3 72
16.4%
2 50
11.4%
5 46
10.5%
4 21
 
4.8%
8 14
 
3.2%
9 12
 
2.7%
7 7
 
1.6%
6 7
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 289
99.7%
1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 287
99.7%
1
 
0.3%
Space Separator
ValueCountFrequency (%)
1956
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33185
89.1%
Common 3122
 
8.4%
Latin 933
 
2.5%
Han 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1004
 
3.0%
709
 
2.1%
602
 
1.8%
518
 
1.6%
487
 
1.5%
453
 
1.4%
411
 
1.2%
404
 
1.2%
375
 
1.1%
374
 
1.1%
Other values (787) 27848
83.9%
Latin
ValueCountFrequency (%)
E 61
 
6.5%
I 61
 
6.5%
A 60
 
6.4%
C 57
 
6.1%
N 45
 
4.8%
L 38
 
4.1%
S 37
 
4.0%
e 33
 
3.5%
H 32
 
3.4%
M 32
 
3.4%
Other values (38) 477
51.1%
Common
ValueCountFrequency (%)
1956
62.7%
) 289
 
9.3%
( 287
 
9.2%
1 107
 
3.4%
0 102
 
3.3%
3 72
 
2.3%
2 50
 
1.6%
5 46
 
1.5%
& 35
 
1.1%
4 21
 
0.7%
Other values (19) 157
 
5.0%
Han
ValueCountFrequency (%)
3
15.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (5) 5
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33184
89.1%
ASCII 4047
 
10.9%
CJK 17
 
< 0.1%
None 8
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1956
48.3%
) 289
 
7.1%
( 287
 
7.1%
1 107
 
2.6%
0 102
 
2.5%
3 72
 
1.8%
E 61
 
1.5%
I 61
 
1.5%
A 60
 
1.5%
C 57
 
1.4%
Other values (63) 995
24.6%
Hangul
ValueCountFrequency (%)
1004
 
3.0%
709
 
2.1%
602
 
1.8%
518
 
1.6%
487
 
1.5%
453
 
1.4%
411
 
1.2%
404
 
1.2%
375
 
1.1%
374
 
1.1%
Other values (786) 27847
83.9%
None
ValueCountFrequency (%)
4
50.0%
2
25.0%
1
 
12.5%
1
 
12.5%
CJK
ValueCountFrequency (%)
3
17.6%
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%
Other values (3) 3
17.6%
CJK Compat Ideographs
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

음식물명
Categorical

IMBALANCE 

Distinct47
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
5147 
커피
 
48
수족관물
 
11
생선회
 
8
김밥
 
7
Other values (42)
 
80

Length

Max length10
Median length4
Mean length3.9726467
Min length2

Unique

Unique23 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5147
97.1%
커피 48
 
0.9%
수족관물 11
 
0.2%
생선회 8
 
0.2%
김밥 7
 
0.1%
한우구이 6
 
0.1%
식빵 4
 
0.1%
냉면육수 4
 
0.1%
콩국물 4
 
0.1%
쿠키 4
 
0.1%
Other values (37) 58
 
1.1%

Length

2024-05-11T05:49:31.586938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5147
97.0%
커피 48
 
0.9%
수족관물 11
 
0.2%
생선회 8
 
0.2%
김밥 7
 
0.1%
한우구이 6
 
0.1%
냉면육수 5
 
0.1%
식빵 4
 
0.1%
콩국물 4
 
0.1%
쿠키 4
 
0.1%
Other values (41) 62
 
1.2%

원료명
Text

MISSING 

Distinct12
Distinct (%)57.1%
Missing5280
Missing (%)99.6%
Memory size41.5 KiB
2024-05-11T05:49:31.956132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.7142857
Min length2

Characters and Unicode

Total characters78
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st row한우
2nd row한우차돌박이
3rd row쇠고기
4th row쇠고기
5th row한우
ValueCountFrequency (%)
한우 7
33.3%
한우차돌박이 2
 
9.5%
쇠고기 2
 
9.5%
한우등심 2
 
9.5%
한우홍두깨 1
 
4.8%
광어회 1
 
4.8%
한우채끝 1
 
4.8%
한우갈비살 1
 
4.8%
한우살치살 1
 
4.8%
한우안심 1
 
4.8%
Other values (2) 2
 
9.5%
2024-05-11T05:49:32.690554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
23.1%
18
23.1%
4
 
5.1%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (18) 20
25.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
97.4%
Open Punctuation 1
 
1.3%
Close Punctuation 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
23.7%
18
23.7%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (16) 18
23.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
97.4%
Common 2
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
23.7%
18
23.7%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (16) 18
23.7%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
97.4%
ASCII 2
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
18
23.7%
18
23.7%
4
 
5.3%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
2
 
2.6%
2
 
2.6%
2
 
2.6%
Other values (16) 18
23.7%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

생산업소
Text

MISSING 

Distinct179
Distinct (%)41.3%
Missing4868
Missing (%)91.8%
Memory size41.5 KiB
2024-05-11T05:49:33.190271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.2355658
Min length2

Characters and Unicode

Total characters3133
Distinct characters274
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

Unique107 ?
Unique (%)24.7%

Sample

1st row이인성
2nd row한양축산물류쎈터
3rd row자연산활어회집
4th row강강술래 시흥점
5th row포장마차100호
ValueCountFrequency (%)
씨제이제일제당(주 39
 
8.8%
대상(주 30
 
6.8%
주)오뚜기 17
 
3.8%
주)진미식품 11
 
2.5%
롯데제과(주 11
 
2.5%
매일유업(주 7
 
1.6%
주)송학식품제1공장 7
 
1.6%
에스에취컴퍼니(주 6
 
1.4%
동서식품 6
 
1.4%
농협목우촌 6
 
1.4%
Other values (178) 302
68.3%
2024-05-11T05:49:34.140909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
335
 
10.7%
( 334
 
10.7%
) 334
 
10.7%
166
 
5.3%
75
 
2.4%
73
 
2.3%
72
 
2.3%
61
 
1.9%
52
 
1.7%
44
 
1.4%
Other values (264) 1587
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2371
75.7%
Open Punctuation 334
 
10.7%
Close Punctuation 334
 
10.7%
Uppercase Letter 31
 
1.0%
Decimal Number 24
 
0.8%
Lowercase Letter 15
 
0.5%
Other Punctuation 13
 
0.4%
Space Separator 9
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
335
 
14.1%
166
 
7.0%
75
 
3.2%
73
 
3.1%
72
 
3.0%
61
 
2.6%
52
 
2.2%
44
 
1.9%
43
 
1.8%
43
 
1.8%
Other values (243) 1407
59.3%
Uppercase Letter
ValueCountFrequency (%)
F 13
41.9%
C 4
 
12.9%
N 4
 
12.9%
B 4
 
12.9%
K 3
 
9.7%
M 2
 
6.5%
S 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 11
45.8%
0 6
25.0%
2 5
20.8%
3 2
 
8.3%
Other Punctuation
ValueCountFrequency (%)
& 5
38.5%
; 5
38.5%
3
23.1%
Lowercase Letter
ValueCountFrequency (%)
a 5
33.3%
p 5
33.3%
m 5
33.3%
Open Punctuation
ValueCountFrequency (%)
( 334
100.0%
Close Punctuation
ValueCountFrequency (%)
) 334
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2371
75.7%
Common 716
 
22.9%
Latin 46
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
335
 
14.1%
166
 
7.0%
75
 
3.2%
73
 
3.1%
72
 
3.0%
61
 
2.6%
52
 
2.2%
44
 
1.9%
43
 
1.8%
43
 
1.8%
Other values (243) 1407
59.3%
Common
ValueCountFrequency (%)
( 334
46.6%
) 334
46.6%
1 11
 
1.5%
9
 
1.3%
0 6
 
0.8%
2 5
 
0.7%
& 5
 
0.7%
; 5
 
0.7%
3
 
0.4%
- 2
 
0.3%
Latin
ValueCountFrequency (%)
F 13
28.3%
a 5
 
10.9%
p 5
 
10.9%
m 5
 
10.9%
C 4
 
8.7%
N 4
 
8.7%
B 4
 
8.7%
K 3
 
6.5%
M 2
 
4.3%
S 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2371
75.7%
ASCII 759
 
24.2%
None 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
335
 
14.1%
166
 
7.0%
75
 
3.2%
73
 
3.1%
72
 
3.0%
61
 
2.6%
52
 
2.2%
44
 
1.9%
43
 
1.8%
43
 
1.8%
Other values (243) 1407
59.3%
ASCII
ValueCountFrequency (%)
( 334
44.0%
) 334
44.0%
F 13
 
1.7%
1 11
 
1.4%
9
 
1.2%
0 6
 
0.8%
2 5
 
0.7%
& 5
 
0.7%
; 5
 
0.7%
a 5
 
0.7%
Other values (10) 32
 
4.2%
None
ValueCountFrequency (%)
3
100.0%

수거일자
Real number (ℝ)

Distinct330
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20140145
Minimum20070126
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:34.759714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070126
5-th percentile20090623
Q120110315
median20131203
Q320170405
95-th percentile20230601
Maximum20240311
Range170185
Interquartile range (IQR)60090

Descriptive statistics

Standard deviation38969.682
Coefficient of variation (CV)0.0019349256
Kurtosis-0.38231491
Mean20140145
Median Absolute Deviation (MAD)29990
Skewness0.59641539
Sum1.0676291 × 1011
Variance1.5186361 × 109
MonotonicityNot monotonic
2024-05-11T05:49:35.214287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150721 784
 
14.8%
20111129 130
 
2.5%
20230615 111
 
2.1%
20121211 95
 
1.8%
20131203 84
 
1.6%
20120216 81
 
1.5%
20120628 80
 
1.5%
20100607 72
 
1.4%
20200730 67
 
1.3%
20091111 66
 
1.2%
Other values (320) 3731
70.4%
ValueCountFrequency (%)
20070126 11
0.2%
20070201 11
0.2%
20070618 5
0.1%
20070620 6
0.1%
20070622 6
0.1%
20070625 3
 
0.1%
20070822 8
0.2%
20070823 9
0.2%
20080305 6
0.1%
20080307 3
 
0.1%
ValueCountFrequency (%)
20240311 22
0.4%
20240307 1
 
< 0.1%
20240305 2
 
< 0.1%
20240227 8
 
0.2%
20240130 6
 
0.1%
20240125 5
 
0.1%
20240118 2
 
< 0.1%
20240116 2
 
< 0.1%
20231122 5
 
0.1%
20231115 31
0.6%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)0.7%
Missing385
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean17.253458
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:35.678650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile8
Maximum1000
Range999
Interquartile range (IQR)3

Descriptive statistics

Standard deviation86.405404
Coefficient of variation (CV)5.008005
Kurtosis67.172495
Mean17.253458
Median Absolute Deviation (MAD)1
Skewness7.6773091
Sum84818
Variance7465.8938
MonotonicityNot monotonic
2024-05-11T05:49:36.090424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
3 1773
33.4%
1 859
16.2%
2 787
14.8%
6 691
 
13.0%
4 246
 
4.6%
5 210
 
4.0%
7 76
 
1.4%
300 62
 
1.2%
600 32
 
0.6%
8 32
 
0.6%
Other values (23) 148
 
2.8%
(Missing) 385
 
7.3%
ValueCountFrequency (%)
1 859
16.2%
2 787
14.8%
3 1773
33.4%
4 246
 
4.6%
5 210
 
4.0%
6 691
 
13.0%
7 76
 
1.4%
8 32
 
0.6%
9 9
 
0.2%
10 29
 
0.5%
ValueCountFrequency (%)
1000 14
 
0.3%
800 4
 
0.1%
600 32
0.6%
500 7
 
0.1%
350 9
 
0.2%
300 62
1.2%
250 20
 
0.4%
200 4
 
0.1%
150 1
 
< 0.1%
120 1
 
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct435
Distinct (%)11.4%
Missing1490
Missing (%)28.1%
Memory size41.5 KiB
2024-05-11T05:49:36.684666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9627394
Min length1

Characters and Unicode

Total characters11291
Distinct characters30
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique184 ?
Unique (%)4.8%

Sample

1st row100
2nd row400
3rd rowg
4th rowg
5th row
ValueCountFrequency (%)
100 402
 
10.5%
500 239
 
6.3%
300 212
 
5.6%
200 151
 
4.0%
400 132
 
3.5%
600 125
 
3.3%
250 107
 
2.8%
1 105
 
2.8%
ml 82
 
2.2%
g 69
 
1.8%
Other values (422) 2187
57.4%
2024-05-11T05:49:37.822458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4486
39.7%
1 1295
 
11.5%
5 1062
 
9.4%
2 966
 
8.6%
3 710
 
6.3%
4 553
 
4.9%
g 486
 
4.3%
6 392
 
3.5%
8 305
 
2.7%
7 247
 
2.2%
Other values (20) 789
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10233
90.6%
Lowercase Letter 935
 
8.3%
Other Punctuation 81
 
0.7%
Other Letter 26
 
0.2%
Uppercase Letter 16
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4486
43.8%
1 1295
 
12.7%
5 1062
 
10.4%
2 966
 
9.4%
3 710
 
6.9%
4 553
 
5.4%
6 392
 
3.8%
8 305
 
3.0%
7 247
 
2.4%
9 217
 
2.1%
Other Letter
ValueCountFrequency (%)
14
53.8%
4
 
15.4%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
g 486
52.0%
l 208
22.2%
m 197
21.1%
k 16
 
1.7%
a 14
 
1.5%
e 14
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
E 5
31.2%
A 5
31.2%
G 3
18.8%
L 3
18.8%
Other Punctuation
ValueCountFrequency (%)
. 80
98.8%
* 1
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10314
91.3%
Latin 951
 
8.4%
Hangul 26
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4486
43.5%
1 1295
 
12.6%
5 1062
 
10.3%
2 966
 
9.4%
3 710
 
6.9%
4 553
 
5.4%
6 392
 
3.8%
8 305
 
3.0%
7 247
 
2.4%
9 217
 
2.1%
Other values (2) 81
 
0.8%
Latin
ValueCountFrequency (%)
g 486
51.1%
l 208
21.9%
m 197
20.7%
k 16
 
1.7%
a 14
 
1.5%
e 14
 
1.5%
E 5
 
0.5%
A 5
 
0.5%
G 3
 
0.3%
L 3
 
0.3%
Hangul
ValueCountFrequency (%)
14
53.8%
4
 
15.4%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11265
99.8%
Hangul 25
 
0.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4486
39.8%
1 1295
 
11.5%
5 1062
 
9.4%
2 966
 
8.6%
3 710
 
6.3%
4 553
 
4.9%
g 486
 
4.3%
6 392
 
3.5%
8 305
 
2.7%
7 247
 
2.2%
Other values (12) 763
 
6.8%
Hangul
ValueCountFrequency (%)
14
56.0%
4
 
16.0%
2
 
8.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

단위(정량)
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
g
2395 
<NA>
2229 
ML
499 
KG
 
148
LT
 
25

Length

Max length4
Median length2
Mean length2.3882286
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 2395
45.2%
<NA> 2229
42.0%
ML 499
 
9.4%
KG 148
 
2.8%
LT 25
 
0.5%
5
 
0.1%

Length

2024-05-11T05:49:38.321267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:38.736656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 2395
45.2%
na 2229
42.0%
ml 499
 
9.4%
kg 148
 
2.8%
lt 25
 
0.5%
5
 
0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
4937 
600g
 
107
1인분
 
75
1개
 
53
2개
 
36
Other values (36)
 
93

Length

Max length9
Median length4
Mean length3.9475571
Min length1

Unique

Unique23 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4937
93.1%
600g 107
 
2.0%
1인분 75
 
1.4%
1개 53
 
1.0%
2개 36
 
0.7%
1 23
 
0.4%
환경검체 도말 11
 
0.2%
3개 5
 
0.1%
1L 5
 
0.1%
김밥 2개 4
 
0.1%
Other values (31) 45
 
0.8%

Length

2024-05-11T05:49:39.412585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4937
92.7%
600g 107
 
2.0%
1인분 75
 
1.4%
1개 54
 
1.0%
2개 41
 
0.8%
1 23
 
0.4%
도말 12
 
0.2%
환경검체 11
 
0.2%
3개 8
 
0.2%
김밥 5
 
0.1%
Other values (33) 54
 
1.0%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct277
Distinct (%)23.8%
Missing4139
Missing (%)78.1%
Infinite0
Infinite (%)0.0%
Mean20164992
Minimum20120207
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:39.963634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120207
5-th percentile20120622
Q120150147
median20170327
Q320181005
95-th percentile20230613
Maximum20240311
Range120104
Interquartile range (IQR)30857.75

Descriptive statistics

Standard deviation29181.857
Coefficient of variation (CV)0.0014471544
Kurtosis-0.045425913
Mean20164992
Median Absolute Deviation (MAD)19825.5
Skewness0.46298186
Sum2.3431721 × 1010
Variance8.515808 × 108
MonotonicityNot monotonic
2024-05-11T05:49:40.498831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150612 45
 
0.8%
20170601 27
 
0.5%
20170901 24
 
0.5%
20171208 22
 
0.4%
20131011 20
 
0.4%
20151105 19
 
0.4%
20151009 19
 
0.4%
20140922 18
 
0.3%
20190517 18
 
0.3%
20181211 17
 
0.3%
Other values (267) 933
 
17.6%
(Missing) 4139
78.1%
ValueCountFrequency (%)
20120207 4
0.1%
20120221 1
 
< 0.1%
20120327 4
0.1%
20120328 5
0.1%
20120406 1
 
< 0.1%
20120410 3
0.1%
20120412 6
0.1%
20120413 3
0.1%
20120418 4
0.1%
20120425 4
0.1%
ValueCountFrequency (%)
20240311 6
0.1%
20240310 1
 
< 0.1%
20240305 2
 
< 0.1%
20240227 8
0.2%
20240130 4
0.1%
20240118 2
 
< 0.1%
20231218 1
 
< 0.1%
20231111 1
 
< 0.1%
20231024 2
 
< 0.1%
20231018 1
 
< 0.1%

제조일자(롯트)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct173
Distinct (%)68.4%
Missing5048
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean20120307
Minimum20110101
Maximum20140829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:41.139992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110101
5-th percentile20110909
Q120120130
median20120515
Q320121027
95-th percentile20131008
Maximum20140829
Range30728
Interquartile range (IQR)897

Descriptive statistics

Standard deviation6474.982
Coefficient of variation (CV)0.00032181328
Kurtosis0.2449763
Mean20120307
Median Absolute Deviation (MAD)501
Skewness0.37988153
Sum5.0904376 × 109
Variance41925391
MonotonicityNot monotonic
2024-05-11T05:49:41.776715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120229 10
 
0.2%
20120430 7
 
0.1%
20111230 5
 
0.1%
20120328 4
 
0.1%
20121107 4
 
0.1%
20111002 4
 
0.1%
20110825 3
 
0.1%
20120901 3
 
0.1%
20120507 3
 
0.1%
20120214 3
 
0.1%
Other values (163) 207
 
3.9%
(Missing) 5048
95.2%
ValueCountFrequency (%)
20110101 1
 
< 0.1%
20110813 1
 
< 0.1%
20110820 1
 
< 0.1%
20110821 2
< 0.1%
20110824 3
0.1%
20110825 3
0.1%
20110829 1
 
< 0.1%
20110905 1
 
< 0.1%
20110911 1
 
< 0.1%
20110930 1
 
< 0.1%
ValueCountFrequency (%)
20140829 1
< 0.1%
20140703 1
< 0.1%
20140420 1
< 0.1%
20131108 2
< 0.1%
20131106 1
< 0.1%
20131103 1
< 0.1%
20131102 1
< 0.1%
20131101 1
< 0.1%
20131023 1
< 0.1%
20131013 1
< 0.1%

유통기한(제조일기준)
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
5274 
20180726
 
13
20181005
 
5
1
 
5
20120207
 
3

Length

Max length8
Median length4
Mean length4.013771
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> 5274
99.5%
20180726 13
 
0.2%
20181005 5
 
0.1%
1 5
 
0.1%
20120207 3
 
0.1%
20120107 1
 
< 0.1%

Length

2024-05-11T05:49:42.520172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:43.003872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5274
99.5%
20180726 13
 
0.2%
20181005 5
 
0.1%
1 5
 
0.1%
20120207 3
 
0.1%
20120107 1
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
실온
2479 
<NA>
1881 
냉장
541 
냉동
381 
기타
 
19

Length

Max length4
Median length2
Mean length2.7096774
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 2479
46.8%
<NA> 1881
35.5%
냉장 541
 
10.2%
냉동 381
 
7.2%
기타 19
 
0.4%

Length

2024-05-11T05:49:43.559236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:44.018199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 2479
46.8%
na 1881
35.5%
냉장 541
 
10.2%
냉동 381
 
7.2%
기타 19
 
0.4%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

어린이기호식품유형
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

검사기관명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
2825 
1
2440 
0
 
35
2
 
1

Length

Max length4
Median length4
Mean length2.598755
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2825
53.3%
1 2440
46.0%
0 35
 
0.7%
2 1
 
< 0.1%

Length

2024-05-11T05:49:44.532031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:44.918370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2825
53.3%
1 2440
46.0%
0 35
 
0.7%
2 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct239
Distinct (%)41.5%
Missing4725
Missing (%)89.1%
Memory size41.5 KiB
2024-05-11T05:49:45.593258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.8611111
Min length2

Characters and Unicode

Total characters3952
Distinct characters250
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)22.7%

Sample

1st row청일외식산업
2nd row찬푸드
3rd row찬푸드
4th row찬푸드
5th row윤가성신식품
ValueCountFrequency (%)
롯데칠성음료(주 29
 
4.7%
싱그람영농조합법인 25
 
4.1%
씨제이제일제당(주 17
 
2.8%
전원식품 16
 
2.6%
더블유 16
 
2.6%
에프엔비 16
 
2.6%
베이커리 15
 
2.5%
디초콜릿커리 9
 
1.5%
코카콜라음료(주 8
 
1.3%
주)삼립식품 8
 
1.3%
Other values (232) 453
74.0%
2024-05-11T05:49:46.974601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
330
 
8.4%
( 310
 
7.8%
) 310
 
7.8%
174
 
4.4%
154
 
3.9%
115
 
2.9%
59
 
1.5%
55
 
1.4%
54
 
1.4%
54
 
1.4%
Other values (240) 2337
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3259
82.5%
Open Punctuation 310
 
7.8%
Close Punctuation 310
 
7.8%
Space Separator 36
 
0.9%
Uppercase Letter 31
 
0.8%
Other Punctuation 5
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
330
 
10.1%
174
 
5.3%
154
 
4.7%
115
 
3.5%
59
 
1.8%
55
 
1.7%
54
 
1.7%
54
 
1.7%
49
 
1.5%
49
 
1.5%
Other values (228) 2166
66.5%
Uppercase Letter
ValueCountFrequency (%)
F 15
48.4%
B 6
 
19.4%
S 4
 
12.9%
N 4
 
12.9%
I 1
 
3.2%
W 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 310
100.0%
Close Punctuation
ValueCountFrequency (%)
) 310
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3259
82.5%
Common 662
 
16.8%
Latin 31
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
330
 
10.1%
174
 
5.3%
154
 
4.7%
115
 
3.5%
59
 
1.8%
55
 
1.7%
54
 
1.7%
54
 
1.7%
49
 
1.5%
49
 
1.5%
Other values (228) 2166
66.5%
Common
ValueCountFrequency (%)
( 310
46.8%
) 310
46.8%
36
 
5.4%
4
 
0.6%
1
 
0.2%
1 1
 
0.2%
Latin
ValueCountFrequency (%)
F 15
48.4%
B 6
 
19.4%
S 4
 
12.9%
N 4
 
12.9%
I 1
 
3.2%
W 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3259
82.5%
ASCII 688
 
17.4%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
330
 
10.1%
174
 
5.3%
154
 
4.7%
115
 
3.5%
59
 
1.8%
55
 
1.7%
54
 
1.7%
54
 
1.7%
49
 
1.5%
49
 
1.5%
Other values (228) 2166
66.5%
ASCII
ValueCountFrequency (%)
( 310
45.1%
) 310
45.1%
36
 
5.2%
F 15
 
2.2%
B 6
 
0.9%
S 4
 
0.6%
N 4
 
0.6%
1 1
 
0.1%
I 1
 
0.1%
W 1
 
0.1%
None
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
국내
4003 
국외
1298 

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 4003
75.5%
국외 1298
 
24.5%

Length

2024-05-11T05:49:47.667605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:48.156980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4003
75.5%
국외 1298
 
24.5%

국가명
Categorical

IMBALANCE 

Distinct31
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
5108 
미국
 
36
영국
 
21
태국
 
15
일본
 
15
Other values (26)
 
106

Length

Max length6
Median length4
Mean length3.9477457
Min length2

Unique

Unique10 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5108
96.4%
미국 36
 
0.7%
영국 21
 
0.4%
태국 15
 
0.3%
일본 15
 
0.3%
프랑스 14
 
0.3%
중국 10
 
0.2%
독일 10
 
0.2%
베트남 8
 
0.2%
이탈리아 8
 
0.2%
Other values (21) 56
 
1.1%

Length

2024-05-11T05:49:48.547966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5108
96.3%
미국 36
 
0.7%
영국 21
 
0.4%
태국 15
 
0.3%
일본 15
 
0.3%
프랑스 14
 
0.3%
중국 13
 
0.2%
독일 10
 
0.2%
이탈리아 8
 
0.2%
베트남 8
 
0.2%
Other values (22) 57
 
1.1%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
1
2743 
<NA>
1606 
2
952 

Length

Max length4
Median length1
Mean length1.9088851
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2743
51.7%
<NA> 1606
30.3%
2 952
 
18.0%

Length

2024-05-11T05:49:49.034786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:49.428593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2743
51.7%
na 1606
30.3%
2 952
 
18.0%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)8.2%
Missing3930
Missing (%)74.1%
Infinite0
Infinite (%)0.0%
Mean20155744
Minimum20100107
Maximum20240313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:49.931860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100107
5-th percentile20100623
Q120110720
median20111129
Q320201027
95-th percentile20231115
Maximum20240313
Range140206
Interquartile range (IQR)90307

Descriptive statistics

Standard deviation52481.458
Coefficient of variation (CV)0.0026037966
Kurtosis-1.6252288
Mean20155744
Median Absolute Deviation (MAD)10520
Skewness0.3532296
Sum2.7633525 × 1010
Variance2.7543034 × 109
MonotonicityNot monotonic
2024-05-11T05:49:50.456578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111129 130
 
2.5%
20230615 111
 
2.1%
20200730 67
 
1.3%
20190517 52
 
1.0%
20111019 50
 
0.9%
20110315 49
 
0.9%
20110720 44
 
0.8%
20230914 44
 
0.8%
20110519 42
 
0.8%
20180209 38
 
0.7%
Other values (103) 744
 
14.0%
(Missing) 3930
74.1%
ValueCountFrequency (%)
20100107 1
 
< 0.1%
20100310 23
0.4%
20100324 1
 
< 0.1%
20100421 10
0.2%
20100422 6
 
0.1%
20100429 4
 
0.1%
20100609 4
 
0.1%
20100617 7
 
0.1%
20100621 11
0.2%
20100623 3
 
0.1%
ValueCountFrequency (%)
20240313 21
0.4%
20240311 1
 
< 0.1%
20240307 1
 
< 0.1%
20240305 2
 
< 0.1%
20240227 8
 
0.2%
20240201 4
 
0.1%
20240131 2
 
< 0.1%
20240130 3
 
0.1%
20240126 2
 
< 0.1%
20240118 4
 
0.1%

결과회보일자
Real number (ℝ)

MISSING 

Distinct94
Distinct (%)12.1%
Missing4523
Missing (%)85.3%
Infinite0
Infinite (%)0.0%
Mean20141861
Minimum20100115
Maximum20210716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:51.050548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100115
5-th percentile20100506
Q120110331
median20110902
Q320190806
95-th percentile20210210
Maximum20210716
Range110601
Interquartile range (IQR)80475

Descriptive statistics

Standard deviation43037.963
Coefficient of variation (CV)0.0021367422
Kurtosis-1.5893165
Mean20141861
Median Absolute Deviation (MAD)9996
Skewness0.51731408
Sum1.5670368 × 1010
Variance1.8522663 × 109
MonotonicityNot monotonic
2024-05-11T05:49:51.556913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200813 66
 
1.2%
20180227 42
 
0.8%
20110601 42
 
0.8%
20110330 36
 
0.7%
20110725 27
 
0.5%
20111012 26
 
0.5%
20110810 24
 
0.5%
20110908 20
 
0.4%
20201214 18
 
0.3%
20181224 17
 
0.3%
Other values (84) 460
 
8.7%
(Missing) 4523
85.3%
ValueCountFrequency (%)
20100115 1
 
< 0.1%
20100317 7
0.1%
20100318 1
 
< 0.1%
20100324 13
0.2%
20100428 10
0.2%
20100429 6
0.1%
20100506 4
 
0.1%
20100609 1
 
< 0.1%
20100616 3
 
0.1%
20100617 2
 
< 0.1%
ValueCountFrequency (%)
20210716 1
 
< 0.1%
20210701 3
 
0.1%
20210624 2
 
< 0.1%
20210616 1
 
< 0.1%
20210330 9
0.2%
20210302 1
 
< 0.1%
20210215 17
0.3%
20210210 12
0.2%
20210209 6
 
0.1%
20201214 18
0.3%

판정구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
3061 
1
2234 
2
 
6

Length

Max length4
Median length4
Mean length2.7323147
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3061
57.7%
1 2234
42.1%
2 6
 
0.1%

Length

2024-05-11T05:49:52.073842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:52.545892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3061
57.7%
1 2234
42.1%
2 6
 
0.1%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

처리결과
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

교부번호
Real number (ℝ)

Distinct549
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0057115 × 1010
Minimum1.9690084 × 1010
Maximum2.0230111 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:49:53.057118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9690084 × 1010
5-th percentile1.9980084 × 1010
Q12.0010085 × 1010
median2.0030085 × 1010
Q32.0110084 × 1010
95-th percentile2.0180085 × 1010
Maximum2.0230111 × 1010
Range5.4002727 × 108
Interquartile range (IQR)99999840

Descriptive statistics

Standard deviation67986979
Coefficient of variation (CV)0.0033896689
Kurtosis1.0786621
Mean2.0057115 × 1010
Median Absolute Deviation (MAD)20000030
Skewness-0.12135701
Sum1.0632277 × 1014
Variance4.6222294 × 1015
MonotonicityNot monotonic
2024-05-11T05:49:53.647681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030084539 971
18.3%
20010084509 903
17.0%
20010084525 372
 
7.0%
20180084917 366
 
6.9%
20050084272 216
 
4.1%
20110084365 143
 
2.7%
20090084731 124
 
2.3%
20090084475 121
 
2.3%
20150084202 115
 
2.2%
20140084422 100
 
1.9%
Other values (539) 1870
35.3%
ValueCountFrequency (%)
19690084001 2
< 0.1%
19730084007 1
< 0.1%
19790084036 1
< 0.1%
19800084014 2
< 0.1%
19800084040 1
< 0.1%
19800084056 1
< 0.1%
19800084086 1
< 0.1%
19800084112 1
< 0.1%
19800084121 1
< 0.1%
19800084127 1
< 0.1%
ValueCountFrequency (%)
20230111270 1
< 0.1%
20220103768 1
< 0.1%
20220103645 1
< 0.1%
20220103276 2
< 0.1%
20210084217 1
< 0.1%
20210084072 1
< 0.1%
20200084933 2
< 0.1%
20200084803 1
< 0.1%
20200084741 1
< 0.1%
20200084222 1
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB

소재지(도로명)
Text

MISSING 

Distinct253
Distinct (%)9.2%
Missing2563
Missing (%)48.3%
Memory size41.5 KiB
2024-05-11T05:49:54.607306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length57
Mean length39.670562
Min length23

Characters and Unicode

Total characters108618
Distinct characters226
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

Unique100 ?
Unique (%)3.7%

Sample

1st row서울특별시 금천구 두산로13길 39, 지상1층 (독산동)
2nd row서울특별시 금천구 시흥대로 91, (시흥동,지상1층 (시흥대로 596))
3rd row서울특별시 금천구 시흥대로 91, (시흥동,지상1층 (시흥대로 596))
4th row서울특별시 금천구 시흥대로 91, (시흥동,지상1층 (시흥대로 596))
5th row서울특별시 금천구 시흥대로 91, (시흥동,지상1층 (시흥대로 596))
ValueCountFrequency (%)
서울특별시 2738
 
14.6%
금천구 2738
 
14.6%
시흥대로 1212
 
6.5%
독산동 758
 
4.0%
시흥동 721
 
3.8%
지상2층 553
 
2.9%
391 496
 
2.6%
지하1층 488
 
2.6%
독산동,홈플러스금천점 487
 
2.6%
금하로 485
 
2.6%
Other values (453) 8088
43.1%
2024-05-11T05:49:56.106127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16042
 
14.8%
, 5472
 
5.0%
5388
 
5.0%
1 5059
 
4.7%
4337
 
4.0%
3811
 
3.5%
3231
 
3.0%
) 3030
 
2.8%
( 3030
 
2.8%
3029
 
2.8%
Other values (216) 56189
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63655
58.6%
Space Separator 16042
 
14.8%
Decimal Number 15869
 
14.6%
Other Punctuation 5472
 
5.0%
Close Punctuation 3293
 
3.0%
Open Punctuation 3293
 
3.0%
Uppercase Letter 812
 
0.7%
Dash Punctuation 147
 
0.1%
Lowercase Letter 35
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5388
 
8.5%
4337
 
6.8%
3811
 
6.0%
3231
 
5.1%
3029
 
4.8%
2797
 
4.4%
2771
 
4.4%
2764
 
4.3%
2738
 
4.3%
2738
 
4.3%
Other values (177) 30051
47.2%
Uppercase Letter
ValueCountFrequency (%)
B 244
30.0%
C 112
13.8%
I 96
 
11.8%
Y 91
 
11.2%
H 90
 
11.1%
T 49
 
6.0%
G 47
 
5.8%
A 36
 
4.4%
D 11
 
1.4%
L 10
 
1.2%
Other values (7) 26
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 5059
31.9%
2 2358
14.9%
3 1935
 
12.2%
0 1794
 
11.3%
9 1629
 
10.3%
6 823
 
5.2%
7 691
 
4.4%
4 602
 
3.8%
5 507
 
3.2%
8 471
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
l 7
20.0%
o 7
20.0%
p 7
20.0%
i 7
20.0%
s 7
20.0%
Close Punctuation
ValueCountFrequency (%)
) 3030
92.0%
] 263
 
8.0%
Open Punctuation
ValueCountFrequency (%)
( 3030
92.0%
[ 263
 
8.0%
Space Separator
ValueCountFrequency (%)
16042
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5472
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63655
58.6%
Common 44116
40.6%
Latin 847
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5388
 
8.5%
4337
 
6.8%
3811
 
6.0%
3231
 
5.1%
3029
 
4.8%
2797
 
4.4%
2771
 
4.4%
2764
 
4.3%
2738
 
4.3%
2738
 
4.3%
Other values (177) 30051
47.2%
Latin
ValueCountFrequency (%)
B 244
28.8%
C 112
13.2%
I 96
 
11.3%
Y 91
 
10.7%
H 90
 
10.6%
T 49
 
5.8%
G 47
 
5.5%
A 36
 
4.3%
D 11
 
1.3%
L 10
 
1.2%
Other values (12) 61
 
7.2%
Common
ValueCountFrequency (%)
16042
36.4%
, 5472
 
12.4%
1 5059
 
11.5%
) 3030
 
6.9%
( 3030
 
6.9%
2 2358
 
5.3%
3 1935
 
4.4%
0 1794
 
4.1%
9 1629
 
3.7%
6 823
 
1.9%
Other values (7) 2944
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63655
58.6%
ASCII 44963
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16042
35.7%
, 5472
 
12.2%
1 5059
 
11.3%
) 3030
 
6.7%
( 3030
 
6.7%
2 2358
 
5.2%
3 1935
 
4.3%
0 1794
 
4.0%
9 1629
 
3.6%
6 823
 
1.8%
Other values (29) 3791
 
8.4%
Hangul
ValueCountFrequency (%)
5388
 
8.5%
4337
 
6.8%
3811
 
6.0%
3231
 
5.1%
3029
 
4.8%
2797
 
4.4%
2771
 
4.4%
2764
 
4.3%
2738
 
4.3%
2738
 
4.3%
Other values (177) 30051
47.2%

소재지(지번)
Text

MISSING 

Distinct533
Distinct (%)11.7%
Missing740
Missing (%)14.0%
Memory size41.5 KiB
2024-05-11T05:49:56.902332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length59
Mean length35.617189
Min length22

Characters and Unicode

Total characters162450
Distinct characters254
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

Unique287 ?
Unique (%)6.3%

Sample

1st row서울특별시 금천구 독산동 1037번지 0호 (독산역길3)
2nd row서울특별시 금천구 독산동 299번지 4호 지상1층
3rd row서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)
4th row서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)
5th row서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)
ValueCountFrequency (%)
서울특별시 4561
 
15.0%
금천구 4561
 
15.0%
독산동 2354
 
7.8%
시흥동 1664
 
5.5%
7호 991
 
3.3%
291번지 902
 
3.0%
992번지 883
 
2.9%
47호 882
 
2.9%
홈플러스금천점 878
 
2.9%
지상2층 876
 
2.9%
Other values (793) 11768
38.8%
2024-05-11T05:49:58.584505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35334
21.8%
7099
 
4.4%
6576
 
4.0%
1 6534
 
4.0%
6035
 
3.7%
6030
 
3.7%
4849
 
3.0%
2 4676
 
2.9%
4636
 
2.9%
4587
 
2.8%
Other values (244) 76094
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92064
56.7%
Space Separator 35334
 
21.8%
Decimal Number 29872
 
18.4%
Open Punctuation 2078
 
1.3%
Close Punctuation 2078
 
1.3%
Uppercase Letter 466
 
0.3%
Dash Punctuation 277
 
0.2%
Other Punctuation 264
 
0.2%
Math Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7099
 
7.7%
6576
 
7.1%
6035
 
6.6%
6030
 
6.5%
4849
 
5.3%
4636
 
5.0%
4587
 
5.0%
4564
 
5.0%
4563
 
5.0%
4563
 
5.0%
Other values (209) 38562
41.9%
Uppercase Letter
ValueCountFrequency (%)
B 231
49.6%
A 181
38.8%
C 20
 
4.3%
L 7
 
1.5%
K 6
 
1.3%
T 4
 
0.9%
S 3
 
0.6%
I 3
 
0.6%
W 2
 
0.4%
M 2
 
0.4%
Other values (5) 7
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 6534
21.9%
2 4676
15.7%
9 4181
14.0%
8 2972
9.9%
4 2606
 
8.7%
7 2396
 
8.0%
0 1911
 
6.4%
5 1899
 
6.4%
3 1760
 
5.9%
6 937
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 262
99.2%
: 1
 
0.4%
. 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
[ 1434
69.0%
( 644
31.0%
Close Punctuation
ValueCountFrequency (%)
] 1434
69.0%
) 644
31.0%
Space Separator
ValueCountFrequency (%)
35334
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 277
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92064
56.7%
Common 69920
43.0%
Latin 466
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7099
 
7.7%
6576
 
7.1%
6035
 
6.6%
6030
 
6.5%
4849
 
5.3%
4636
 
5.0%
4587
 
5.0%
4564
 
5.0%
4563
 
5.0%
4563
 
5.0%
Other values (209) 38562
41.9%
Common
ValueCountFrequency (%)
35334
50.5%
1 6534
 
9.3%
2 4676
 
6.7%
9 4181
 
6.0%
8 2972
 
4.3%
4 2606
 
3.7%
7 2396
 
3.4%
0 1911
 
2.7%
5 1899
 
2.7%
3 1760
 
2.5%
Other values (10) 5651
 
8.1%
Latin
ValueCountFrequency (%)
B 231
49.6%
A 181
38.8%
C 20
 
4.3%
L 7
 
1.5%
K 6
 
1.3%
T 4
 
0.9%
S 3
 
0.6%
I 3
 
0.6%
W 2
 
0.4%
M 2
 
0.4%
Other values (5) 7
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92064
56.7%
ASCII 70386
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35334
50.2%
1 6534
 
9.3%
2 4676
 
6.6%
9 4181
 
5.9%
8 2972
 
4.2%
4 2606
 
3.7%
7 2396
 
3.4%
0 1911
 
2.7%
5 1899
 
2.7%
3 1760
 
2.5%
Other values (25) 6117
 
8.7%
Hangul
ValueCountFrequency (%)
7099
 
7.7%
6576
 
7.1%
6035
 
6.6%
6030
 
6.5%
4849
 
5.3%
4636
 
5.0%
4587
 
5.0%
4564
 
5.0%
4563
 
5.0%
4563
 
5.0%
Other values (209) 38562
41.9%

업소전화번호
Text

MISSING 

Distinct424
Distinct (%)8.7%
Missing448
Missing (%)8.5%
Memory size41.5 KiB
2024-05-11T05:49:59.583586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.318566
Min length2

Characters and Unicode

Total characters50076
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

Unique207 ?
Unique (%)4.3%

Sample

1st row02 8054364
2nd row02 8635889
3rd row02 8389595
4th row02 8389595
5th row02 8389595
ValueCountFrequency (%)
02 4176
44.5%
8084900 903
 
9.6%
8908121 800
 
8.5%
69602500 374
 
4.0%
0221097531 322
 
3.4%
8914666 216
 
2.3%
8908125 173
 
1.8%
8539944 143
 
1.5%
8566969 124
 
1.3%
808 120
 
1.3%
Other values (442) 2034
21.7%
2024-05-11T05:50:01.418245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12080
24.1%
2 7604
15.2%
8 6823
13.6%
5508
11.0%
9 4427
 
8.8%
1 3679
 
7.3%
6 2740
 
5.5%
5 2615
 
5.2%
4 2103
 
4.2%
3 1373
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44568
89.0%
Space Separator 5508
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12080
27.1%
2 7604
17.1%
8 6823
15.3%
9 4427
 
9.9%
1 3679
 
8.3%
6 2740
 
6.1%
5 2615
 
5.9%
4 2103
 
4.7%
3 1373
 
3.1%
7 1124
 
2.5%
Space Separator
ValueCountFrequency (%)
5508
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50076
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12080
24.1%
2 7604
15.2%
8 6823
13.6%
5508
11.0%
9 4427
 
8.8%
1 3679
 
7.3%
6 2740
 
5.5%
5 2615
 
5.2%
4 2103
 
4.2%
3 1373
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50076
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12080
24.1%
2 7604
15.2%
8 6823
13.6%
5508
11.0%
9 4427
 
8.8%
1 3679
 
7.3%
6 2740
 
5.5%
5 2615
 
5.2%
4 2103
 
4.2%
3 1373
 
2.7%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
수거
2396 
<NA>
1882 
위생점검(전체)
915 
위생점검(부분)
 
108

Length

Max length8
Median length4
Mean length3.8679494
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수거 2396
45.2%
<NA> 1882
35.5%
위생점검(전체) 915
 
17.3%
위생점검(부분) 108
 
2.0%

Length

2024-05-11T05:50:02.184113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:50:02.576009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 2396
45.2%
na 1882
35.5%
위생점검(전체 915
 
17.3%
위생점검(부분 108
 
2.0%

점검일자
Real number (ℝ)

Distinct358
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20075036
Minimum2015109
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:50:03.154605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015109
5-th percentile20090623
Q120110315
median20131028
Q320170405
95-th percentile20230601
Maximum20240311
Range18225202
Interquartile range (IQR)60090

Descriptive statistics

Standard deviation1083966.8
Coefficient of variation (CV)0.053995759
Kurtosis273.54566
Mean20075036
Median Absolute Deviation (MAD)29825
Skewness-16.585524
Sum1.0641777 × 1011
Variance1.174984 × 1012
MonotonicityNot monotonic
2024-05-11T05:50:03.795119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121211 144
 
2.7%
20230614 117
 
2.2%
20131203 85
 
1.6%
20120216 81
 
1.5%
20120628 80
 
1.5%
20100607 72
 
1.4%
20200730 69
 
1.3%
20150602 68
 
1.3%
20091111 67
 
1.3%
20151124 67
 
1.3%
Other values (348) 4451
84.0%
ValueCountFrequency (%)
2015109 19
0.4%
20070126 11
0.2%
20070201 10
0.2%
20070618 5
 
0.1%
20070620 6
 
0.1%
20070622 6
 
0.1%
20070625 3
 
0.1%
20070727 1
 
< 0.1%
20070822 8
0.2%
20070823 9
0.2%
ValueCountFrequency (%)
20240311 22
0.4%
20240307 1
 
< 0.1%
20240306 2
 
< 0.1%
20240227 8
 
0.2%
20240130 6
 
0.1%
20240125 5
 
0.1%
20240118 2
 
< 0.1%
20240116 2
 
< 0.1%
20231122 5
 
0.1%
20231115 31
0.6%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
<NA>
1827 
수시
1826 
기타
932 
합동
508 
일제
208 

Length

Max length4
Median length2
Mean length2.6893039
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1827
34.5%
수시 1826
34.4%
기타 932
17.6%
합동 508
 
9.6%
일제 208
 
3.9%

Length

2024-05-11T05:50:04.435322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:50:04.933847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1827
34.5%
수시 1826
34.4%
기타 932
17.6%
합동 508
 
9.6%
일제 208
 
3.9%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.5 KiB
1
3419 
<NA>
1827 
2
 
55

Length

Max length4
Median length1
Mean length2.0339559
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3419
64.5%
<NA> 1827
34.5%
2 55
 
1.0%

Length

2024-05-11T05:50:05.351409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:50:05.760180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3419
64.5%
na 1827
34.5%
2 55
 
1.0%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct173
Distinct (%)68.4%
Missing5048
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean20120307
Minimum20110101
Maximum20140829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.7 KiB
2024-05-11T05:50:06.329946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110101
5-th percentile20110909
Q120120130
median20120515
Q320121027
95-th percentile20131008
Maximum20140829
Range30728
Interquartile range (IQR)897

Descriptive statistics

Standard deviation6474.982
Coefficient of variation (CV)0.00032181328
Kurtosis0.2449763
Mean20120307
Median Absolute Deviation (MAD)501
Skewness0.37988153
Sum5.0904376 × 109
Variance41925391
MonotonicityNot monotonic
2024-05-11T05:50:06.799621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120229 10
 
0.2%
20120430 7
 
0.1%
20111230 5
 
0.1%
20120328 4
 
0.1%
20121107 4
 
0.1%
20111002 4
 
0.1%
20110825 3
 
0.1%
20120901 3
 
0.1%
20120507 3
 
0.1%
20120214 3
 
0.1%
Other values (163) 207
 
3.9%
(Missing) 5048
95.2%
ValueCountFrequency (%)
20110101 1
 
< 0.1%
20110813 1
 
< 0.1%
20110820 1
 
< 0.1%
20110821 2
< 0.1%
20110824 3
0.1%
20110825 3
0.1%
20110829 1
 
< 0.1%
20110905 1
 
< 0.1%
20110911 1
 
< 0.1%
20110930 1
 
< 0.1%
ValueCountFrequency (%)
20140829 1
< 0.1%
20140703 1
< 0.1%
20140420 1
< 0.1%
20131108 2
< 0.1%
20131106 1
< 0.1%
20131103 1
< 0.1%
20131102 1
< 0.1%
20131101 1
< 0.1%
20131023 1
< 0.1%
20131013 1
< 0.1%
Distinct108
Distinct (%)49.3%
Missing5082
Missing (%)95.9%
Memory size41.5 KiB
2024-05-11T05:50:07.530184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length18.771689
Min length13

Characters and Unicode

Total characters4111
Distinct characters179
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

Unique56 ?
Unique (%)25.6%

Sample

1st row인천광역시 중구 신흥동3가 7-121
2nd row인천광역시 중구 신흥동3가 7-121
3rd row인천광역시 중구 신흥동 3가 7-121
4th row인천광역시 중구 북성동 1가 6-14
5th row경기도 오산시 궐동 415-1
ValueCountFrequency (%)
경기도 50
 
4.9%
충북 36
 
3.5%
경남 27
 
2.6%
충남 23
 
2.2%
경북 21
 
2.1%
광주시 15
 
1.5%
양산시 14
 
1.4%
문경시 12
 
1.2%
진천군 12
 
1.2%
1088 11
 
1.1%
Other values (322) 803
78.4%
2024-05-11T05:50:08.927028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
806
 
19.6%
1 195
 
4.7%
165
 
4.0%
- 138
 
3.4%
2 126
 
3.1%
123
 
3.0%
119
 
2.9%
105
 
2.6%
3 84
 
2.0%
5 76
 
1.8%
Other values (169) 2174
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2334
56.8%
Decimal Number 826
 
20.1%
Space Separator 806
 
19.6%
Dash Punctuation 138
 
3.4%
Other Punctuation 6
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
165
 
7.1%
123
 
5.3%
119
 
5.1%
105
 
4.5%
74
 
3.2%
72
 
3.1%
71
 
3.0%
69
 
3.0%
65
 
2.8%
64
 
2.7%
Other values (155) 1407
60.3%
Decimal Number
ValueCountFrequency (%)
1 195
23.6%
2 126
15.3%
3 84
10.2%
5 76
 
9.2%
8 71
 
8.6%
6 67
 
8.1%
0 66
 
8.0%
4 56
 
6.8%
9 48
 
5.8%
7 37
 
4.5%
Space Separator
ValueCountFrequency (%)
806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2334
56.8%
Common 1776
43.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
165
 
7.1%
123
 
5.3%
119
 
5.1%
105
 
4.5%
74
 
3.2%
72
 
3.1%
71
 
3.0%
69
 
3.0%
65
 
2.8%
64
 
2.7%
Other values (155) 1407
60.3%
Common
ValueCountFrequency (%)
806
45.4%
1 195
 
11.0%
- 138
 
7.8%
2 126
 
7.1%
3 84
 
4.7%
5 76
 
4.3%
8 71
 
4.0%
6 67
 
3.8%
0 66
 
3.7%
4 56
 
3.2%
Other values (3) 91
 
5.1%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2334
56.8%
ASCII 1777
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
806
45.4%
1 195
 
11.0%
- 138
 
7.8%
2 126
 
7.1%
3 84
 
4.7%
5 76
 
4.3%
8 71
 
4.0%
6 67
 
3.8%
0 66
 
3.7%
4 56
 
3.2%
Other values (4) 92
 
5.2%
Hangul
ValueCountFrequency (%)
165
 
7.1%
123
 
5.3%
119
 
5.1%
105
 
4.5%
74
 
3.2%
72
 
3.1%
71
 
3.0%
69
 
3.0%
65
 
2.8%
64
 
2.7%
Other values (155) 1407
60.3%

부적합항목
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing5299
Missing (%)> 99.9%
Memory size41.5 KiB
2024-05-11T05:50:09.339156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5
Min length3

Characters and Unicode

Total characters10
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row장염비브리오균
2nd row대장균
ValueCountFrequency (%)
장염비브리오균 1
50.0%
대장균 1
50.0%
2024-05-11T05:50:10.383137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5301
Missing (%)100.0%
Memory size46.7 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
03170000101일반음식점<NA><NA><NA>기타 식품접객업소 수거검사13-09-10검사용원조마포갈비121000000식육류중육류소고기한우(등심)<NA><NA><NA>201309252100g<NA>20130925<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19790084036<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 1037번지 0호 (독산역길3)02 8054364<NA>20130925<NA><NA><NA><NA><NA><NA><NA>
13170000101일반음식점<NA><NA><NA>기타 식품접객업소 수거검사118-10-42검사용삼미영양탕G0100000100000조리식품 등조리식품 등수육<NA><NA><NA>201710231400g<NA>20171023<NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>19800084453<NA><NA><NA><NA><NA>서울특별시 금천구 두산로13길 39, 지상1층 (독산동)서울특별시 금천구 독산동 299번지 4호 지상1층02 8635889<NA>20171023<NA><NA><NA><NA><NA><NA><NA>
23170000101일반음식점<NA><NA><NA><NA>118-06-06<NA>쇠가리육회121000000식육류중육류<NA>육회<NA><NA><NA>20110628350g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20110628201107061<NA><NA><NA><NA><NA><NA>19810084073<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)02 8389595수거20110628일제<NA>1<NA><NA><NA><NA>
33170000101일반음식점<NA><NA><NA><NA>118-06-07<NA>쇠가리육회121000000식육류중육류<NA>원료식육<NA><NA><NA>20110628100g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20110628201107061<NA><NA><NA><NA><NA><NA>19810084073<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)02 8389595수거20110628일제<NA>1<NA><NA><NA><NA>
43170000101일반음식점<NA><NA><NA><NA>118-06-08<NA>쇠가리육회410000000기구류기구류중나무제도마<NA><NA><NA>201106281<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20110628201107061<NA><NA><NA><NA><NA><NA>19810084073<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)02 8389595수거20110628일제<NA>1<NA><NA><NA><NA>
53170000101일반음식점<NA><NA><NA><NA>118-06-09<NA>쇠가리육회410000000기구류기구류중금속제<NA><NA><NA>201106281<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20110628201107061<NA><NA><NA><NA><NA><NA>19810084073<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)02 8389595수거20110628일제<NA>1<NA><NA><NA><NA>
63170000101일반음식점<NA><NA><NA><NA>118-06-10<NA>쇠가리육회410000000기구류기구류중기타행주<NA><NA><NA>201106281<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20110628201107061<NA><NA><NA><NA><NA><NA>19810084073<NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 146번지 1호 (시흥대로214-1)02 8389595수거20110628일제<NA>1<NA><NA><NA><NA>
73170000101일반음식점<NA><NA><NA><NA><NA><NA>장보고<NA><NA>수족관물<NA><NA><NA>200702011<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19810084032<NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 884번지 2호 (1층)<NA>위생점검(전체)20070201일제<NA>1<NA><NA><NA><NA>
83170000101일반음식점<NA><NA><NA><NA>118-8-25<NA>장보고<NA><NA>생선회생선회<NA><NA>20100805300g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20100805201008051<NA><NA><NA><NA><NA><NA>19810084032<NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 884번지 2호 지상1층 (금천로 199)<NA>위생점검(전체)20100805수시<NA>1<NA><NA><NA><NA>
93170000101일반음식점<NA><NA><NA><NA>118-8-26<NA>장보고<NA><NA>수족관물수족관물<NA><NA>201008051000l<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA><NA>20100805201008111<NA><NA><NA><NA><NA><NA>19810084032<NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 884번지 2호 지상1층 (금천로 199)<NA>위생점검(전체)20100805수시<NA>1<NA><NA><NA><NA>
시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
52913170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-5검사용롯데쇼핑(주)롯데마트 금천점E0200200000000홍삼홍삼황작홍삼스틱<NA><NA><NA>201908232300ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52923170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-6검사용롯데쇼핑(주)롯데마트 금천점C0116020000000액상차액상차홍삼정<NA><NA><NA>201908233240g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52933170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-7검사용롯데쇼핑(주)롯데마트 금천점E0201400000000밀크씨슬(카르두스 마리아누스) 추출물밀크씨슬(카르두스 마리아누스) 추출물퓨어 밀크씨슬<NA><NA><NA>20190823730g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52943170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-10검사용롯데쇼핑(주)롯데마트 금천점X0100026100000일반원료일반원료아이클리어 마스터<NA><NA><NA>20190823542g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52953170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-9검사용롯데쇼핑(주)롯데마트 금천점X0100026100000일반원료일반원료1등 오메가 프로메가 기억력오매가3<NA><NA><NA>20190823541.58g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52963170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-11검사용롯데쇼핑(주)롯데마트 금천점E0202800000000쏘팔메토 열매 추출물쏘팔메토 열매 추출물시원하다 전립쎈<NA><NA><NA>20190823636g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52973170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-8검사용롯데쇼핑(주)롯데마트 금천점X0100026100000일반원료일반원료리비케어 밀크씨슬<NA><NA><NA>20190823460g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084916<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 69602500<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52983170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-1검사용롯데쇼핑(주)롭스 롯데마트금천점E0201400000000밀크씨슬(카르두스 마리아누스) 추출물밀크씨슬(카르두스 마리아누스) 추출물헬씨칸 간 사랑 밀크씨슬<NA><NA><NA>201908238225g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084941<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 60704046<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
52993170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-2검사용롯데쇼핑(주)롭스 롯데마트금천점E0200200000000홍삼홍삼홍삼정스틱<NA><NA><NA>201908232300ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084941<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 60704046<NA>20190823<NA><NA><NA><NA><NA><NA><NA>
53003170000134건강기능식품일반판매업<NA><NA><NA>시민다소비식품 수거검사118-8-3검사용롯데쇼핑(주)롭스 롯데마트금천점E0200200000000홍삼홍삼홍삼정<NA><NA><NA>201908233240ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20180084941<NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 291, 309동 지하1층 (독산동, 금천롯데캐슬골드파크3차)서울특별시 금천구 독산동 1155번지 금천롯데캐슬골드파크3차02 60704046<NA>20190823<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)유통기한(일자)유통기한(제조일기준)보관상태코드검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목# duplicates
143170000114기타식품판매업<NA><NA><NA><NA><NA>홈플러스테스코시흥점803000000코코아가공품류또는초콜릿류초콜릿가공품오리온투유<NA><NA><NA>200902103<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA>20010084509<NA>서울특별시 금천구 시흥동 992번지 47호 [시흥대로 488]02 8084900수거20090210기타1<NA><NA><NA>3
183170000114기타식품판매업<NA><NA><NA><NA><NA>홈플러스테스코시흥점825000000절임식품당절임우리팥<NA><NA><NA>200906236<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA>20010084509<NA>서울특별시 금천구 시흥동 992번지 47호 [시흥대로 488]02 8084900수거20090623기타1<NA><NA><NA>3
03170000105집단급식소7민원발생에 따른 지도점검<NA>118-12-23검사용소망어린이집G0100000100000조리식품 등조리식품 등보리차<NA><NA><NA>20171208<NA><NA><NA>600g20171205<NA><NA>실온<NA><NA>국내<NA>2<NA><NA><NA>20050084336서울특별시 금천구 범안로 1187, (독산동, 지상1층)서울특별시 금천구 독산동 331번지 41호 지상1층02 8956942위생점검(전체)20171208수시1<NA><NA><NA>2
13170000112식품자동판매기영업<NA><NA><NA><NA><NA>한양식품<NA><NA>자판기커피<NA><NA><NA>200907151<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>119990084338<NA>서울특별시 금천구 독산동 1009번지 85호02위생점검(전체)20090715수시1<NA><NA><NA>2
23170000114기타식품판매업999가공식품안전 업무계획<NA>118-12-119검사용(주)홈플러스테스코시흥점813000000두부류또는묵류가공두부두부너비아니<NA><NA>(주)풀잎라인201212112216g<NA><NA><NA><NA>냉동<NA><NA>국내<NA>1<NA><NA><NA>20010084509<NA>서울특별시 금천구 시흥동 992번지 47호 [시흥대로 488]02 8084900수거20121211수시1<NA><NA><NA>2
33170000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트금천점816000000다류액상차순백차<NA><NA><NA>200906196<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA>20010084525<NA>서울특별시 금천구 독산동 295번지 10호 [두산길 18]0221097531수거20090619기타1<NA><NA><NA>2
43170000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트금천점816000000다류침출차동서 둥굴레차<NA><NA><NA>201012033<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>120010084525<NA>서울특별시 금천구 독산동 295번지 10호 [두산길 18]0221097531수거20101203합동1<NA><NA><NA>2
53170000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트금천점818000000음료류과.채음료트로피카나트위스터<NA><NA><NA>201004206<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>120010084525<NA>서울특별시 금천구 독산동 295번지 10호 [두산길 18]0221097531수거20100420수시1<NA><NA><NA>2
63170000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트금천점829000000기타식품류가공소금맛소금<NA><NA><NA>201006243<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>120010084525<NA>서울특별시 금천구 독산동 295번지 10호 [두산길 18]0221097531수거20100624수시1<NA><NA><NA>2
73170000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트금천점829000000기타식품류천일염3년묵은천일염<NA><NA><NA>201006243<NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>120010084525<NA>서울특별시 금천구 독산동 295번지 10호 [두산길 18]0221097531수거20100624수시1<NA><NA><NA>2