Overview

Dataset statistics

Number of variables61
Number of observations7476
Missing cells174587
Missing cells (%)38.3%
Duplicate rows39
Duplicate rows (%)0.5%
Total size in memory3.7 MiB
Average record size in memory516.0 B

Variable types

Categorical22
Numeric12
Unsupported7
Text20

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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-2381/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
폐기장소 has constant value ""Constant
폐기방법 has constant value ""Constant
Dataset has 39 (0.5%) duplicate rowsDuplicates
업종명 is highly imbalanced (55.7%)Imbalance
지도점검계획 is highly imbalanced (61.1%)Imbalance
수거계획 is highly imbalanced (90.7%)Imbalance
수거사유코드 is highly imbalanced (58.2%)Imbalance
제조일자(롯트) is highly imbalanced (99.1%)Imbalance
바코드번호 is highly imbalanced (99.8%)Imbalance
어린이기호식품유형 is highly imbalanced (94.8%)Imbalance
검사기관명 is highly imbalanced (68.1%)Imbalance
국가명 is highly imbalanced (87.5%)Imbalance
수거품처리 is highly imbalanced (97.7%)Imbalance
폐기일자 is highly imbalanced (99.8%)Imbalance
폐기량(Kg) is highly imbalanced (99.8%)Imbalance
폐기금액(원) is highly imbalanced (99.8%)Imbalance
계획구분코드 has 5150 (68.9%) missing valuesMissing
계획구분명 has 7476 (100.0%) missing valuesMissing
수거증번호 has 1367 (18.3%) missing valuesMissing
식품군 has 1108 (14.8%) missing valuesMissing
품목명 has 323 (4.3%) missing valuesMissing
음식물명 has 6981 (93.4%) missing valuesMissing
원료명 has 7078 (94.7%) missing valuesMissing
생산업소 has 6963 (93.1%) missing valuesMissing
수거량(정량) has 520 (7.0%) missing valuesMissing
제품규격(정량) has 1887 (25.2%) missing valuesMissing
수거량(자유) has 6956 (93.0%) missing valuesMissing
제조일자(일자) has 5735 (76.7%) missing valuesMissing
유통기한(일자) has 7309 (97.8%) missing valuesMissing
유통기한(제조일기준) has 7464 (99.8%) missing valuesMissing
(구)제조사명 has 6887 (92.1%) missing valuesMissing
검사의뢰일자 has 3985 (53.3%) missing valuesMissing
결과회보일자 has 5527 (73.9%) missing valuesMissing
처리구분 has 7476 (100.0%) missing valuesMissing
수거검사구분코드 has 7476 (100.0%) missing valuesMissing
단속지역구분코드 has 7476 (100.0%) missing valuesMissing
수거장소구분코드 has 7476 (100.0%) missing valuesMissing
처리결과 has 7445 (99.6%) missing valuesMissing
폐기장소 has 7475 (> 99.9%) missing valuesMissing
폐기방법 has 7475 (> 99.9%) missing valuesMissing
소재지(도로명) has 778 (10.4%) missing valuesMissing
소재지(지번) has 599 (8.0%) missing valuesMissing
업소전화번호 has 520 (7.0%) missing valuesMissing
점검일자 has 457 (6.1%) missing valuesMissing
점검내용 has 7476 (100.0%) missing valuesMissing
(구)제조유통기한 has 7309 (97.8%) missing valuesMissing
(구)제조회사주소 has 7476 (100.0%) missing valuesMissing
부적합항목 has 7468 (99.9%) missing valuesMissing
기준치부적합내용 has 7469 (99.9%) missing valuesMissing
수거량(정량) is highly skewed (γ1 = 37.62848363)Skewed
계획구분명 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
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조회사주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-03 23:03:41.228323
Analysis finished2024-05-03 23:03:49.203813
Duration7.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
3160000
7476 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 7476
100.0%

Length

2024-05-03T23:03:49.413384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:03:49.774928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 7476
100.0%

업종코드
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.41239
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:03:50.079504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1107
median114
Q3114
95-th percentile114
Maximum134
Range33
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.29688
Coefficient of variation (CV)0.047543009
Kurtosis2.0840839
Mean111.41239
Median Absolute Deviation (MAD)0
Skewness-0.31349993
Sum832919
Variance28.056938
MonotonicityIncreasing
2024-05-03T23:03:50.428230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
114 5319
71.1%
101 848
 
11.3%
105 640
 
8.6%
104 241
 
3.2%
107 147
 
2.0%
112 108
 
1.4%
134 67
 
0.9%
106 65
 
0.9%
121 39
 
0.5%
111 1
 
< 0.1%
ValueCountFrequency (%)
101 848
 
11.3%
104 241
 
3.2%
105 640
 
8.6%
106 65
 
0.9%
107 147
 
2.0%
111 1
 
< 0.1%
112 108
 
1.4%
114 5319
71.1%
118 1
 
< 0.1%
121 39
 
0.5%
ValueCountFrequency (%)
134 67
 
0.9%
121 39
 
0.5%
118 1
 
< 0.1%
114 5319
71.1%
112 108
 
1.4%
111 1
 
< 0.1%
107 147
 
2.0%
106 65
 
0.9%
105 640
 
8.6%
104 241
 
3.2%

업종명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
기타식품판매업
5319 
일반음식점
848 
집단급식소
640 
휴게음식점
 
241
즉석판매제조가공업
 
147
Other values (6)
 
281

Length

Max length11
Median length7
Mean length6.6313537
Min length5

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 5319
71.1%
일반음식점 848
 
11.3%
집단급식소 640
 
8.6%
휴게음식점 241
 
3.2%
즉석판매제조가공업 147
 
2.0%
식품자동판매기영업 108
 
1.4%
건강기능식품일반판매업 67
 
0.9%
식품제조가공업 65
 
0.9%
제과점영업 39
 
0.5%
식용얼음판매업 1
 
< 0.1%

Length

2024-05-03T23:03:51.107295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 5319
71.1%
일반음식점 848
 
11.3%
집단급식소 640
 
8.6%
휴게음식점 241
 
3.2%
즉석판매제조가공업 147
 
2.0%
식품자동판매기영업 108
 
1.4%
건강기능식품일반판매업 67
 
0.9%
식품제조가공업 65
 
0.9%
제과점영업 39
 
0.5%
식용얼음판매업 1
 
< 0.1%

계획구분코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)0.3%
Missing5150
Missing (%)68.9%
Infinite0
Infinite (%)0.0%
Mean770.63929
Minimum1
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:03:51.588387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q1999
median999
Q3999
95-th percentile999
Maximum999
Range998
Interquartile range (IQR)0

Descriptive statistics

Standard deviation418.93063
Coefficient of variation (CV)0.54361442
Kurtosis-0.33684427
Mean770.63929
Median Absolute Deviation (MAD)0
Skewness-1.2897382
Sum1792507
Variance175502.88
MonotonicityNot monotonic
2024-05-03T23:03:52.148773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
999 1793
 
24.0%
2 366
 
4.9%
1 86
 
1.2%
7 46
 
0.6%
3 24
 
0.3%
8 11
 
0.1%
(Missing) 5150
68.9%
ValueCountFrequency (%)
1 86
 
1.2%
2 366
 
4.9%
3 24
 
0.3%
7 46
 
0.6%
8 11
 
0.1%
999 1793
24.0%
ValueCountFrequency (%)
999 1793
24.0%
8 11
 
0.1%
7 46
 
0.6%
3 24
 
0.3%
2 366
 
4.9%
1 86
 
1.2%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct44
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
5150 
2012년 식품수거검사 계획
 
514
2013년 유통식품 수거계획
 
434
수시 위생점검
 
173
2019 유통식품수거검사(지자체)
 
151
Other values (39)
1054 

Length

Max length36
Median length4
Mean length7.9208133
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row수시 위생점검
2nd row2013년 위생지도 및 원산지 지도서비스 실시
3rd row2013년 위생지도 및 원산지 지도서비스 실시
4th row2013년 위생지도 및 원산지 지도서비스 실시
5th row2012 원산지표시 지도점검

Common Values

ValueCountFrequency (%)
<NA> 5150
68.9%
2012년 식품수거검사 계획 514
 
6.9%
2013년 유통식품 수거계획 434
 
5.8%
수시 위생점검 173
 
2.3%
2019 유통식품수거검사(지자체) 151
 
2.0%
2020년 식품안전관리계획에 따른 지도점검 149
 
2.0%
23년 식품안전팀 지도점검 계획 97
 
1.3%
2015년 식품접객업소 위생 및 원산지 지도서비스 85
 
1.1%
2013년 위생지도 및 원산지 지도서비스 실시 81
 
1.1%
식중독 의심신고에 따른 점검 및 수거 74
 
1.0%
Other values (34) 568
 
7.6%

Length

2024-05-03T23:03:52.602754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5150
39.9%
계획 680
 
5.3%
2013년 544
 
4.2%
2012년 541
 
4.2%
지도점검 533
 
4.1%
식품수거검사 514
 
4.0%
수거계획 441
 
3.4%
유통식품 434
 
3.4%
및 295
 
2.3%
위생점검 267
 
2.1%
Other values (82) 3499
27.1%

수거계획
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7207 
2014 조리식품수거검사
 
88
2017년 접객업소 조리식품 수거계획(구로)
 
53
유통식품 수거검사
 
42
2015 조리식품수거검사
 
25
Other values (6)
 
61

Length

Max length26
Median length4
Mean length4.4427501
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7207
96.4%
2014 조리식품수거검사 88
 
1.2%
2017년 접객업소 조리식품 수거계획(구로) 53
 
0.7%
유통식품 수거검사 42
 
0.6%
2015 조리식품수거검사 25
 
0.3%
2021년 어린이 급식재료 방사능 안전관리 계획 23
 
0.3%
2017년 원산지관련 소고기수거 18
 
0.2%
2022년 일상수거검사 9
 
0.1%
2013년 식품접객업소 및 집단급식소 수거검사 7
 
0.1%
2015김밥취급업소 지도점검(수거) 3
 
< 0.1%

Length

2024-05-03T23:03:53.027008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7207
90.3%
조리식품수거검사 113
 
1.4%
2014 88
 
1.1%
2017년 72
 
0.9%
접객업소 53
 
0.7%
조리식품 53
 
0.7%
수거계획(구로 53
 
0.7%
수거검사 50
 
0.6%
유통식품 42
 
0.5%
2015 25
 
0.3%
Other values (17) 228
 
2.9%

수거증번호
Text

MISSING 

Distinct3290
Distinct (%)53.9%
Missing1367
Missing (%)18.3%
Memory size58.5 KiB
2024-05-03T23:03:53.908556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.2041251
Min length1

Characters and Unicode

Total characters50119
Distinct characters72
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

Unique2234 ?
Unique (%)36.6%

Sample

1st row117-06-06
2nd row2013-1
3rd row2013-2
4th row2013-3
5th row2012-31
ValueCountFrequency (%)
117-6-6 37
 
0.6%
117-11-3 11
 
0.2%
117-11-2 10
 
0.2%
117-11-1 10
 
0.2%
117-10-1 10
 
0.2%
117-10-6 9
 
0.1%
117-10-13 9
 
0.1%
117-10-14 9
 
0.1%
117-10-12 9
 
0.1%
117-10-11 9
 
0.1%
Other values (3261) 5995
98.0%
2024-05-03T23:03:55.141312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15544
31.0%
- 11239
22.4%
7 6199
 
12.4%
0 3112
 
6.2%
2 2896
 
5.8%
3 1937
 
3.9%
9 1579
 
3.2%
6 1465
 
2.9%
4 1463
 
2.9%
5 1463
 
2.9%
Other values (62) 3222
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36751
73.3%
Dash Punctuation 11239
 
22.4%
Other Letter 2013
 
4.0%
Uppercase Letter 87
 
0.2%
Space Separator 9
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Lowercase Letter 6
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 848
42.1%
로 848
42.1%
일 49
 
2.4%
반 40
 
2.0%
건 33
 
1.6%
기 30
 
1.5%
천 26
 
1.3%
방 23
 
1.1%
대 18
 
0.9%
음 9
 
0.4%
Other values (40) 89
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 15544
42.3%
7 6199
 
16.9%
0 3112
 
8.5%
2 2896
 
7.9%
3 1937
 
5.3%
9 1579
 
4.3%
6 1465
 
4.0%
4 1463
 
4.0%
5 1463
 
4.0%
8 1093
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
M 29
33.3%
G 29
33.3%
O 29
33.3%
Lowercase Letter
ValueCountFrequency (%)
o 2
33.3%
m 2
33.3%
g 2
33.3%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
, 1
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 11239
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48013
95.8%
Hangul 2013
 
4.0%
Latin 93
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 848
42.1%
로 848
42.1%
일 49
 
2.4%
반 40
 
2.0%
건 33
 
1.6%
기 30
 
1.5%
천 26
 
1.3%
방 23
 
1.1%
대 18
 
0.9%
음 9
 
0.4%
Other values (40) 89
 
4.4%
Common
ValueCountFrequency (%)
1 15544
32.4%
- 11239
23.4%
7 6199
 
12.9%
0 3112
 
6.5%
2 2896
 
6.0%
3 1937
 
4.0%
9 1579
 
3.3%
6 1465
 
3.1%
4 1463
 
3.0%
5 1463
 
3.0%
Other values (6) 1116
 
2.3%
Latin
ValueCountFrequency (%)
M 29
31.2%
G 29
31.2%
O 29
31.2%
o 2
 
2.2%
m 2
 
2.2%
g 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48106
96.0%
Hangul 2012
 
4.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15544
32.3%
- 11239
23.4%
7 6199
 
12.9%
0 3112
 
6.5%
2 2896
 
6.0%
3 1937
 
4.0%
9 1579
 
3.3%
6 1465
 
3.0%
4 1463
 
3.0%
5 1463
 
3.0%
Other values (12) 1209
 
2.5%
Hangul
ValueCountFrequency (%)
구 848
42.1%
로 848
42.1%
일 49
 
2.4%
반 40
 
2.0%
건 33
 
1.6%
기 30
 
1.5%
천 26
 
1.3%
방 23
 
1.1%
대 18
 
0.9%
음 9
 
0.4%
Other values (39) 88
 
4.4%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
검사용
4803 
<NA>
2651 
증거용
 
11
기타
 
8
압류
 
3

Length

Max length4
Median length3
Mean length3.35313
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 4803
64.2%
<NA> 2651
35.5%
증거용 11
 
0.1%
기타 8
 
0.1%
압류 3
 
< 0.1%

Length

2024-05-03T23:03:55.608469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:03:55.971163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 4803
64.2%
na 2651
35.5%
증거용 11
 
0.1%
기타 8
 
0.1%
압류 3
 
< 0.1%

업소명
Text

Distinct550
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
2024-05-03T23:03:56.470632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length9.515115
Min length2

Characters and Unicode

Total characters71135
Distinct characters460
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

Unique251 ?
Unique (%)3.4%

Sample

1st row평양면옥
2nd row육영토종정육전문점
3rd row육영토종정육전문점
4th row육영토종정육전문점
5th row육영토종정육전문점
ValueCountFrequency (%)
이마트신도림점 1346
 
14.4%
롯데쇼핑(주)롯데마트구로점 477
 
5.1%
주)이마트구로점 427
 
4.6%
하나로마트 344
 
3.7%
구로본점 344
 
3.7%
영등포농협 344
 
3.7%
에이케이플라자(ak 293
 
3.1%
plaza 293
 
3.1%
홈플러스테스코(주)신도림점 247
 
2.7%
주)세계로더블유스토어 197
 
2.1%
Other values (629) 5003
53.7%
2024-05-03T23:03:57.505812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 4147
 
5.8%
마 3789
 
5.3%
트 3664
 
5.2%
이 2948
 
4.1%
) 2925
 
4.1%
( 2923
 
4.1%
주 2621
 
3.7%
로 2536
 
3.6%
신 2296
 
3.2%
도 2238
 
3.1%
Other values (450) 41048
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60339
84.8%
Close Punctuation 2925
 
4.1%
Open Punctuation 2923
 
4.1%
Space Separator 1839
 
2.6%
Lowercase Letter 1617
 
2.3%
Uppercase Letter 1028
 
1.4%
Decimal Number 454
 
0.6%
Other Punctuation 7
 
< 0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 4147
 
6.9%
마 3789
 
6.3%
트 3664
 
6.1%
이 2948
 
4.9%
주 2621
 
4.3%
로 2536
 
4.2%
신 2296
 
3.8%
도 2238
 
3.7%
림 2131
 
3.5%
구 2104
 
3.5%
Other values (399) 31865
52.8%
Lowercase Letter
ValueCountFrequency (%)
a 616
38.1%
l 299
18.5%
z 293
18.1%
p 293
18.1%
e 30
 
1.9%
t 27
 
1.7%
s 20
 
1.2%
o 7
 
0.4%
r 7
 
0.4%
i 6
 
0.4%
Other values (10) 19
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
K 321
31.2%
A 302
29.4%
G 195
19.0%
S 115
 
11.2%
F 37
 
3.6%
C 25
 
2.4%
I 11
 
1.1%
N 6
 
0.6%
B 3
 
0.3%
L 3
 
0.3%
Other values (6) 10
 
1.0%
Decimal Number
ValueCountFrequency (%)
5 135
29.7%
2 117
25.8%
0 66
14.5%
1 64
14.1%
8 33
 
7.3%
4 30
 
6.6%
6 3
 
0.7%
3 3
 
0.7%
7 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
& 6
85.7%
. 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 2925
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2923
100.0%
Space Separator
ValueCountFrequency (%)
1839
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60337
84.8%
Common 8151
 
11.5%
Latin 2645
 
3.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 4147
 
6.9%
마 3789
 
6.3%
트 3664
 
6.1%
이 2948
 
4.9%
주 2621
 
4.3%
로 2536
 
4.2%
신 2296
 
3.8%
도 2238
 
3.7%
림 2131
 
3.5%
구 2104
 
3.5%
Other values (397) 31863
52.8%
Latin
ValueCountFrequency (%)
a 616
23.3%
K 321
12.1%
A 302
11.4%
l 299
11.3%
z 293
11.1%
p 293
11.1%
G 195
 
7.4%
S 115
 
4.3%
F 37
 
1.4%
e 30
 
1.1%
Other values (26) 144
 
5.4%
Common
ValueCountFrequency (%)
) 2925
35.9%
( 2923
35.9%
1839
22.6%
5 135
 
1.7%
2 117
 
1.4%
0 66
 
0.8%
1 64
 
0.8%
8 33
 
0.4%
4 30
 
0.4%
& 6
 
0.1%
Other values (5) 13
 
0.2%
Han
ValueCountFrequency (%)
情 1
50.0%
家 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60337
84.8%
ASCII 10796
 
15.2%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 4147
 
6.9%
마 3789
 
6.3%
트 3664
 
6.1%
이 2948
 
4.9%
주 2621
 
4.3%
로 2536
 
4.2%
신 2296
 
3.8%
도 2238
 
3.7%
림 2131
 
3.5%
구 2104
 
3.5%
Other values (397) 31863
52.8%
ASCII
ValueCountFrequency (%)
) 2925
27.1%
( 2923
27.1%
1839
17.0%
a 616
 
5.7%
K 321
 
3.0%
A 302
 
2.8%
l 299
 
2.8%
z 293
 
2.7%
p 293
 
2.7%
G 195
 
1.8%
Other values (41) 790
 
7.3%
CJK
ValueCountFrequency (%)
情 1
50.0%
家 1
50.0%

식품군코드
Text

Distinct363
Distinct (%)4.9%
Missing20
Missing (%)0.3%
Memory size58.5 KiB
2024-05-03T23:03:58.043644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.559549
Min length1

Characters and Unicode

Total characters78732
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)1.1%

Sample

1st row818000000
2nd row121000000
3rd row121000000
4th row121000000
5th row121000000
ValueCountFrequency (%)
c01000000 494
 
7.0%
g0100000100000 380
 
5.4%
801000000 372
 
5.2%
201000000 291
 
4.1%
829000000 240
 
3.4%
121000000 203
 
2.9%
214000000 179
 
2.5%
815000000 153
 
2.2%
830000000 150
 
2.1%
c0101010000000 146
 
2.1%
Other values (351) 4490
63.3%
2024-05-03T23:03:59.040320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53732
68.2%
1 7583
 
9.6%
2 3896
 
4.9%
8 2671
 
3.4%
2510
 
3.2%
C 2345
 
3.0%
3 1876
 
2.4%
9 805
 
1.0%
4 710
 
0.9%
5 666
 
0.8%
Other values (10) 1938
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72943
92.6%
Uppercase Letter 3279
 
4.2%
Space Separator 2510
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53732
73.7%
1 7583
 
10.4%
2 3896
 
5.3%
8 2671
 
3.7%
3 1876
 
2.6%
9 805
 
1.1%
4 710
 
1.0%
5 666
 
0.9%
6 506
 
0.7%
7 498
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 2345
71.5%
G 650
 
19.8%
B 138
 
4.2%
X 53
 
1.6%
F 37
 
1.1%
A 30
 
0.9%
E 14
 
0.4%
Z 6
 
0.2%
D 6
 
0.2%
Space Separator
ValueCountFrequency (%)
2510
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75453
95.8%
Latin 3279
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53732
71.2%
1 7583
 
10.0%
2 3896
 
5.2%
8 2671
 
3.5%
2510
 
3.3%
3 1876
 
2.5%
9 805
 
1.1%
4 710
 
0.9%
5 666
 
0.9%
6 506
 
0.7%
Latin
ValueCountFrequency (%)
C 2345
71.5%
G 650
 
19.8%
B 138
 
4.2%
X 53
 
1.6%
F 37
 
1.1%
A 30
 
0.9%
E 14
 
0.4%
Z 6
 
0.2%
D 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53732
68.2%
1 7583
 
9.6%
2 3896
 
4.9%
8 2671
 
3.4%
2510
 
3.2%
C 2345
 
3.0%
3 1876
 
2.4%
9 805
 
1.0%
4 710
 
0.9%
5 666
 
0.8%
Other values (10) 1938
 
2.5%

식품군
Text

MISSING 

Distinct264
Distinct (%)4.1%
Missing1108
Missing (%)14.8%
Memory size58.5 KiB
2024-05-03T23:03:59.672888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length60
Mean length5.2226759
Min length1

Characters and Unicode

Total characters33258
Distinct characters305
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

Unique55 ?
Unique (%)0.9%

Sample

1st row음료류
2nd row식육류중육류
3rd row식육류중육류
4th row식육류중육류
5th row식육류중육류
ValueCountFrequency (%)
과자류 673
 
8.6%
등 451
 
5.8%
조리식품 380
 
4.9%
조미식품 298
 
3.8%
기타식품류 288
 
3.7%
면류 225
 
2.9%
식육류중육류 203
 
2.6%
과자 189
 
2.4%
다류 175
 
2.2%
규격외일반가공식품 152
 
1.9%
Other values (281) 4783
61.2%
2024-05-03T23:04:00.920640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 3698
 
11.1%
품 2293
 
6.9%
식 2211
 
6.6%
1449
 
4.4%
과 1006
 
3.0%
가 971
 
2.9%
조 937
 
2.8%
자 879
 
2.6%
기 832
 
2.5%
공 811
 
2.4%
Other values (295) 18171
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30886
92.9%
Space Separator 1449
 
4.4%
Other Punctuation 523
 
1.6%
Uppercase Letter 116
 
0.3%
Close Punctuation 104
 
0.3%
Open Punctuation 104
 
0.3%
Decimal Number 61
 
0.2%
Lowercase Letter 13
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 3698
 
12.0%
품 2293
 
7.4%
식 2211
 
7.2%
과 1006
 
3.3%
가 971
 
3.1%
조 937
 
3.0%
자 879
 
2.8%
기 832
 
2.7%
공 811
 
2.6%
육 520
 
1.7%
Other values (262) 16728
54.2%
Lowercase Letter
ValueCountFrequency (%)
o 2
15.4%
e 2
15.4%
w 1
7.7%
r 1
7.7%
a 1
7.7%
c 1
7.7%
t 1
7.7%
u 1
7.7%
l 1
7.7%
s 1
7.7%
Uppercase Letter
ValueCountFrequency (%)
B 44
37.9%
A 19
16.4%
E 15
 
12.9%
D 14
 
12.1%
C 13
 
11.2%
P 5
 
4.3%
H 4
 
3.4%
L 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 23
37.7%
1 22
36.1%
6 11
18.0%
0 3
 
4.9%
4 1
 
1.6%
9 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 195
37.3%
, 182
34.8%
. 124
23.7%
? 22
 
4.2%
Space Separator
ValueCountFrequency (%)
1449
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30886
92.9%
Common 2243
 
6.7%
Latin 129
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 3698
 
12.0%
품 2293
 
7.4%
식 2211
 
7.2%
과 1006
 
3.3%
가 971
 
3.1%
조 937
 
3.0%
자 879
 
2.8%
기 832
 
2.7%
공 811
 
2.6%
육 520
 
1.7%
Other values (262) 16728
54.2%
Latin
ValueCountFrequency (%)
B 44
34.1%
A 19
14.7%
E 15
 
11.6%
D 14
 
10.9%
C 13
 
10.1%
P 5
 
3.9%
H 4
 
3.1%
o 2
 
1.6%
e 2
 
1.6%
L 2
 
1.6%
Other values (9) 9
 
7.0%
Common
ValueCountFrequency (%)
1449
64.6%
/ 195
 
8.7%
, 182
 
8.1%
. 124
 
5.5%
) 104
 
4.6%
( 104
 
4.6%
2 23
 
1.0%
1 22
 
1.0%
? 22
 
1.0%
6 11
 
0.5%
Other values (4) 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30886
92.9%
ASCII 2372
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 3698
 
12.0%
품 2293
 
7.4%
식 2211
 
7.2%
과 1006
 
3.3%
가 971
 
3.1%
조 937
 
3.0%
자 879
 
2.8%
기 832
 
2.7%
공 811
 
2.6%
육 520
 
1.7%
Other values (262) 16728
54.2%
ASCII
ValueCountFrequency (%)
1449
61.1%
/ 195
 
8.2%
, 182
 
7.7%
. 124
 
5.2%
) 104
 
4.4%
( 104
 
4.4%
B 44
 
1.9%
2 23
 
1.0%
1 22
 
0.9%
? 22
 
0.9%
Other values (23) 103
 
4.3%

품목명
Text

MISSING 

Distinct425
Distinct (%)5.9%
Missing323
Missing (%)4.3%
Memory size58.5 KiB
2024-05-03T23:04:01.656253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length60
Mean length5.3493639
Min length1

Characters and Unicode

Total characters38264
Distinct characters372
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

Unique110 ?
Unique (%)1.5%

Sample

1st row추출음료
2nd row소고기
3rd row소고기
4th row소고기
5th row소고기
ValueCountFrequency (%)
등 676
 
7.2%
조리식품 584
 
6.2%
과자 389
 
4.1%
소고기 265
 
2.8%
초콜릿가공품 217
 
2.3%
캔디류 178
 
1.9%
소스류 164
 
1.7%
수산물가공품 147
 
1.6%
유탕면류 143
 
1.5%
기타가공품 132
 
1.4%
Other values (444) 6555
69.4%
2024-05-03T23:04:03.302954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2297
 
6.0%
품 1834
 
4.8%
류 1803
 
4.7%
식 1239
 
3.2%
가 1225
 
3.2%
기 1171
 
3.1%
조 1145
 
3.0%
공 931
 
2.4%
과 870
 
2.3%
리 828
 
2.2%
Other values (362) 24921
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34050
89.0%
Space Separator 2297
 
6.0%
Other Punctuation 700
 
1.8%
Open Punctuation 482
 
1.3%
Close Punctuation 482
 
1.3%
Uppercase Letter 142
 
0.4%
Decimal Number 85
 
0.2%
Dash Punctuation 13
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 1834
 
5.4%
류 1803
 
5.3%
식 1239
 
3.6%
가 1225
 
3.6%
기 1171
 
3.4%
조 1145
 
3.4%
공 931
 
2.7%
과 870
 
2.6%
리 828
 
2.4%
등 680
 
2.0%
Other values (327) 22324
65.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
15.4%
o 2
15.4%
w 1
7.7%
r 1
7.7%
d 1
7.7%
s 1
7.7%
l 1
7.7%
t 1
7.7%
u 1
7.7%
c 1
7.7%
Uppercase Letter
ValueCountFrequency (%)
B 46
32.4%
A 28
19.7%
C 25
17.6%
E 15
 
10.6%
D 14
 
9.9%
P 5
 
3.5%
H 4
 
2.8%
L 3
 
2.1%
K 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 36
42.4%
2 23
27.1%
6 11
 
12.9%
3 10
 
11.8%
0 3
 
3.5%
4 1
 
1.2%
9 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 291
41.6%
. 209
29.9%
/ 195
27.9%
? 5
 
0.7%
Space Separator
ValueCountFrequency (%)
2297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 482
100.0%
Close Punctuation
ValueCountFrequency (%)
) 482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34050
89.0%
Common 4059
 
10.6%
Latin 155
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 1834
 
5.4%
류 1803
 
5.3%
식 1239
 
3.6%
가 1225
 
3.6%
기 1171
 
3.4%
조 1145
 
3.4%
공 931
 
2.7%
과 870
 
2.6%
리 828
 
2.4%
등 680
 
2.0%
Other values (327) 22324
65.6%
Latin
ValueCountFrequency (%)
B 46
29.7%
A 28
18.1%
C 25
16.1%
E 15
 
9.7%
D 14
 
9.0%
P 5
 
3.2%
H 4
 
2.6%
L 3
 
1.9%
e 2
 
1.3%
o 2
 
1.3%
Other values (10) 11
 
7.1%
Common
ValueCountFrequency (%)
2297
56.6%
( 482
 
11.9%
) 482
 
11.9%
, 291
 
7.2%
. 209
 
5.1%
/ 195
 
4.8%
1 36
 
0.9%
2 23
 
0.6%
- 13
 
0.3%
6 11
 
0.3%
Other values (5) 20
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34050
89.0%
ASCII 4214
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2297
54.5%
( 482
 
11.4%
) 482
 
11.4%
, 291
 
6.9%
. 209
 
5.0%
/ 195
 
4.6%
B 46
 
1.1%
1 36
 
0.9%
A 28
 
0.7%
C 25
 
0.6%
Other values (25) 123
 
2.9%
Hangul
ValueCountFrequency (%)
품 1834
 
5.4%
류 1803
 
5.3%
식 1239
 
3.6%
가 1225
 
3.6%
기 1171
 
3.4%
조 1145
 
3.4%
공 931
 
2.7%
과 870
 
2.6%
리 828
 
2.4%
등 680
 
2.0%
Other values (327) 22324
65.6%

제품명
Text

Distinct5399
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
2024-05-03T23:04:04.205249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length36
Mean length7.1577047
Min length1

Characters and Unicode

Total characters53511
Distinct characters954
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4516 ?
Unique (%)60.4%

Sample

1st row냉면육수
2nd row양지
3rd row치마살
4th row치마살
5th row갈비
ValueCountFrequency (%)
오뚜기 71
 
0.7%
청정원 65
 
0.6%
자판기커피 62
 
0.6%
등심 59
 
0.6%
음용수 57
 
0.5%
김밥 56
 
0.5%
도마 56
 
0.5%
칼 53
 
0.5%
수족관물 39
 
0.4%
한우등심 38
 
0.4%
Other values (6175) 10054
94.8%
2024-05-03T23:04:05.819483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3144
 
5.9%
스 1286
 
2.4%
이 1042
 
1.9%
리 949
 
1.8%
기 788
 
1.5%
치 657
 
1.2%
오 628
 
1.2%
드 612
 
1.1%
마 560
 
1.0%
고 534
 
1.0%
Other values (944) 43311
80.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46782
87.4%
Space Separator 3144
 
5.9%
Uppercase Letter 1246
 
2.3%
Decimal Number 1015
 
1.9%
Lowercase Letter 343
 
0.6%
Close Punctuation 317
 
0.6%
Open Punctuation 317
 
0.6%
Other Punctuation 257
 
0.5%
Dash Punctuation 65
 
0.1%
Math Symbol 13
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1286
 
2.7%
이 1042
 
2.2%
리 949
 
2.0%
기 788
 
1.7%
치 657
 
1.4%
오 628
 
1.3%
드 612
 
1.3%
마 560
 
1.2%
고 534
 
1.1%
수 510
 
1.1%
Other values (863) 39216
83.8%
Uppercase Letter
ValueCountFrequency (%)
E 133
 
10.7%
C 113
 
9.1%
A 100
 
8.0%
O 94
 
7.5%
I 79
 
6.3%
S 72
 
5.8%
R 69
 
5.5%
N 64
 
5.1%
L 63
 
5.1%
P 62
 
5.0%
Other values (16) 397
31.9%
Lowercase Letter
ValueCountFrequency (%)
a 53
15.5%
e 40
11.7%
p 26
 
7.6%
m 24
 
7.0%
s 22
 
6.4%
r 22
 
6.4%
i 19
 
5.5%
n 15
 
4.4%
t 14
 
4.1%
c 14
 
4.1%
Other values (13) 94
27.4%
Other Punctuation
ValueCountFrequency (%)
. 100
38.9%
% 30
 
11.7%
/ 27
 
10.5%
& 26
 
10.1%
？ 23
 
8.9%
, 21
 
8.2%
; 15
 
5.8%
? 7
 
2.7%
! 4
 
1.6%
' 3
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 321
31.6%
0 217
21.4%
2 120
 
11.8%
3 112
 
11.0%
5 52
 
5.1%
8 46
 
4.5%
6 44
 
4.3%
7 43
 
4.2%
9 35
 
3.4%
4 25
 
2.5%
Math Symbol
ValueCountFrequency (%)
+ 7
53.8%
~ 4
30.8%
± 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 315
99.4%
」 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 315
99.4%
「 2
 
0.6%
Space Separator
ValueCountFrequency (%)
3144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 10
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46764
87.4%
Common 5140
 
9.6%
Latin 1589
 
3.0%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1286
 
2.7%
이 1042
 
2.2%
리 949
 
2.0%
기 788
 
1.7%
치 657
 
1.4%
오 628
 
1.3%
드 612
 
1.3%
마 560
 
1.2%
고 534
 
1.1%
수 510
 
1.1%
Other values (854) 39198
83.8%
Latin
ValueCountFrequency (%)
E 133
 
8.4%
C 113
 
7.1%
A 100
 
6.3%
O 94
 
5.9%
I 79
 
5.0%
S 72
 
4.5%
R 69
 
4.3%
N 64
 
4.0%
L 63
 
4.0%
P 62
 
3.9%
Other values (39) 740
46.6%
Common
ValueCountFrequency (%)
3144
61.2%
1 321
 
6.2%
) 315
 
6.1%
( 315
 
6.1%
0 217
 
4.2%
2 120
 
2.3%
3 112
 
2.2%
. 100
 
1.9%
- 65
 
1.3%
5 52
 
1.0%
Other values (22) 379
 
7.4%
Han
ValueCountFrequency (%)
心 4
22.2%
茶 3
16.7%
蔘 2
11.1%
眞 2
11.1%
紅 2
11.1%
生 2
11.1%
秀 1
 
5.6%
美 1
 
5.6%
男 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46763
87.4%
ASCII 6698
 
12.5%
None 29
 
0.1%
CJK 15
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
CJK Compat 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3144
46.9%
1 321
 
4.8%
) 315
 
4.7%
( 315
 
4.7%
0 217
 
3.2%
E 133
 
2.0%
2 120
 
1.8%
C 113
 
1.7%
3 112
 
1.7%
A 100
 
1.5%
Other values (66) 1808
27.0%
Hangul
ValueCountFrequency (%)
스 1286
 
2.8%
이 1042
 
2.2%
리 949
 
2.0%
기 788
 
1.7%
치 657
 
1.4%
오 628
 
1.3%
드 612
 
1.3%
마 560
 
1.2%
고 534
 
1.1%
수 510
 
1.1%
Other values (853) 39197
83.8%
None
ValueCountFrequency (%)
？ 23
79.3%
」 2
 
6.9%
「 2
 
6.9%
± 2
 
6.9%
CJK
ValueCountFrequency (%)
心 4
26.7%
蔘 2
13.3%
眞 2
13.3%
紅 2
13.3%
生 2
13.3%
秀 1
 
6.7%
美 1
 
6.7%
男 1
 
6.7%
CJK Compat Ideographs
ValueCountFrequency (%)
茶 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎖ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 1
100.0%

음식물명
Text

MISSING 

Distinct213
Distinct (%)43.0%
Missing6981
Missing (%)93.4%
Memory size58.5 KiB
2024-05-03T23:04:06.760591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length4.0242424
Min length1

Characters and Unicode

Total characters1992
Distinct characters234
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

Unique159 ?
Unique (%)32.1%

Sample

1st row냉면육수
2nd row수족관물
3rd row칼
4th row도마
5th row수족관물
ValueCountFrequency (%)
자판기커피 43
 
7.8%
스웹 29
 
5.3%
정수기물 27
 
4.9%
음용수 26
 
4.7%
칼 24
 
4.4%
도마 23
 
4.2%
수족관물 20
 
3.6%
김밥 16
 
2.9%
급식면봉 15
 
2.7%
육회칼 9
 
1.6%
Other values (209) 318
57.8%
2024-05-03T23:04:08.404097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 94
 
4.7%
기 91
 
4.6%
물 60
 
3.0%
55
 
2.8%
자 53
 
2.7%
김 48
 
2.4%
커 47
 
2.4%
판 47
 
2.4%
음 47
 
2.4%
피 46
 
2.3%
Other values (224) 1404
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1886
94.7%
Space Separator 55
 
2.8%
Decimal Number 21
 
1.1%
Close Punctuation 14
 
0.7%
Open Punctuation 14
 
0.7%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 94
 
5.0%
기 91
 
4.8%
물 60
 
3.2%
자 53
 
2.8%
김 48
 
2.5%
커 47
 
2.5%
판 47
 
2.5%
음 47
 
2.5%
피 46
 
2.4%
도 45
 
2.4%
Other values (214) 1308
69.4%
Decimal Number
ValueCountFrequency (%)
2 9
42.9%
3 5
23.8%
5 2
 
9.5%
1 2
 
9.5%
4 2
 
9.5%
6 1
 
4.8%
Space Separator
ValueCountFrequency (%)
55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1886
94.7%
Common 106
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 94
 
5.0%
기 91
 
4.8%
물 60
 
3.2%
자 53
 
2.8%
김 48
 
2.5%
커 47
 
2.5%
판 47
 
2.5%
음 47
 
2.5%
피 46
 
2.4%
도 45
 
2.4%
Other values (214) 1308
69.4%
Common
ValueCountFrequency (%)
55
51.9%
) 14
 
13.2%
( 14
 
13.2%
2 9
 
8.5%
3 5
 
4.7%
5 2
 
1.9%
- 2
 
1.9%
1 2
 
1.9%
4 2
 
1.9%
6 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1886
94.7%
ASCII 106
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 94
 
5.0%
기 91
 
4.8%
물 60
 
3.2%
자 53
 
2.8%
김 48
 
2.5%
커 47
 
2.5%
판 47
 
2.5%
음 47
 
2.5%
피 46
 
2.4%
도 45
 
2.4%
Other values (214) 1308
69.4%
ASCII
ValueCountFrequency (%)
55
51.9%
) 14
 
13.2%
( 14
 
13.2%
2 9
 
8.5%
3 5
 
4.7%
5 2
 
1.9%
- 2
 
1.9%
1 2
 
1.9%
4 2
 
1.9%
6 1
 
0.9%

원료명
Text

MISSING 

Distinct201
Distinct (%)50.5%
Missing7078
Missing (%)94.7%
Memory size58.5 KiB
2024-05-03T23:04:09.415520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length3.6758794
Min length1

Characters and Unicode

Total characters1463
Distinct characters233
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

Unique156 ?
Unique (%)39.2%

Sample

1st row냉면육수
2nd row수족관물
3rd row칼
4th row수족관물
5th row칼
ValueCountFrequency (%)
스웹 29
 
6.4%
정수기물 26
 
5.8%
음용수 24
 
5.3%
도마 23
 
5.1%
칼 22
 
4.9%
쇠고기 19
 
4.2%
수족관물 19
 
4.2%
김밥 9
 
2.0%
김치 9
 
2.0%
닭 7
 
1.6%
Other values (200) 263
58.4%
2024-05-03T23:04:10.849646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 81
 
5.5%
기 67
 
4.6%
물 59
 
4.0%
52
 
3.6%
고 44
 
3.0%
김 42
 
2.9%
스 40
 
2.7%
치 39
 
2.7%
음 36
 
2.5%
웹 34
 
2.3%
Other values (223) 969
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1385
94.7%
Space Separator 52
 
3.6%
Uppercase Letter 12
 
0.8%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%
Dash Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%
Lowercase Letter 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 81
 
5.8%
기 67
 
4.8%
물 59
 
4.3%
고 44
 
3.2%
김 42
 
3.0%
스 40
 
2.9%
치 39
 
2.8%
음 36
 
2.6%
웹 34
 
2.5%
밥 32
 
2.3%
Other values (204) 911
65.8%
Uppercase Letter
ValueCountFrequency (%)
M 2
16.7%
C 1
8.3%
D 1
8.3%
T 1
8.3%
L 1
8.3%
E 1
8.3%
O 1
8.3%
K 1
8.3%
U 1
8.3%
R 1
8.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1385
94.7%
Common 65
 
4.4%
Latin 13
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 81
 
5.8%
기 67
 
4.8%
물 59
 
4.3%
고 44
 
3.2%
김 42
 
3.0%
스 40
 
2.9%
치 39
 
2.8%
음 36
 
2.6%
웹 34
 
2.5%
밥 32
 
2.3%
Other values (204) 911
65.8%
Latin
ValueCountFrequency (%)
M 2
15.4%
C 1
7.7%
D 1
7.7%
T 1
7.7%
L 1
7.7%
o 1
7.7%
E 1
7.7%
O 1
7.7%
K 1
7.7%
U 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
52
80.0%
( 4
 
6.2%
) 4
 
6.2%
- 2
 
3.1%
. 1
 
1.5%
, 1
 
1.5%
1 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1385
94.7%
ASCII 78
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 81
 
5.8%
기 67
 
4.8%
물 59
 
4.3%
고 44
 
3.2%
김 42
 
3.0%
스 40
 
2.9%
치 39
 
2.8%
음 36
 
2.6%
웹 34
 
2.5%
밥 32
 
2.3%
Other values (204) 911
65.8%
ASCII
ValueCountFrequency (%)
52
66.7%
( 4
 
5.1%
) 4
 
5.1%
- 2
 
2.6%
M 2
 
2.6%
C 1
 
1.3%
D 1
 
1.3%
T 1
 
1.3%
L 1
 
1.3%
. 1
 
1.3%
Other values (9) 9
 
11.5%

생산업소
Text

MISSING 

Distinct210
Distinct (%)40.9%
Missing6963
Missing (%)93.1%
Memory size58.5 KiB
2024-05-03T23:04:11.541145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length9.3840156
Min length2

Characters and Unicode

Total characters4814
Distinct characters263
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

Unique149 ?
Unique (%)29.0%

Sample

1st row평양면옥
2nd row대하
3rd row대하
4th row대하
5th row부산회집
ValueCountFrequency (%)
세종과학고등학교 107
 
13.8%
최우영 32
 
4.1%
스시 32
 
4.1%
co.ltd 18
 
2.3%
광명수산 16
 
2.1%
food 12
 
1.5%
foods 10
 
1.3%
어울림 9
 
1.2%
화원종합사회복지관 8
 
1.0%
신토불이 7
 
0.9%
Other values (336) 527
67.7%
2024-05-03T23:04:13.061485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
5.5%
학 225
 
4.7%
O 196
 
4.1%
A 170
 
3.5%
I 151
 
3.1%
종 132
 
2.7%
S 127
 
2.6%
T 126
 
2.6%
E 126
 
2.6%
N 125
 
2.6%
Other values (253) 3171
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2424
50.4%
Uppercase Letter 1831
38.0%
Space Separator 265
 
5.5%
Lowercase Letter 194
 
4.0%
Other Punctuation 71
 
1.5%
Close Punctuation 14
 
0.3%
Open Punctuation 14
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 225
 
9.3%
종 132
 
5.4%
등 115
 
4.7%
교 114
 
4.7%
고 113
 
4.7%
세 107
 
4.4%
과 107
 
4.4%
스 52
 
2.1%
우 49
 
2.0%
로 46
 
1.9%
Other values (200) 1364
56.3%
Uppercase Letter
ValueCountFrequency (%)
O 196
 
10.7%
A 170
 
9.3%
I 151
 
8.2%
S 127
 
6.9%
T 126
 
6.9%
E 126
 
6.9%
N 125
 
6.8%
C 115
 
6.3%
L 101
 
5.5%
R 97
 
5.3%
Other values (16) 497
27.1%
Lowercase Letter
ValueCountFrequency (%)
a 20
 
10.3%
o 18
 
9.3%
n 17
 
8.8%
r 17
 
8.8%
e 16
 
8.2%
l 13
 
6.7%
s 12
 
6.2%
i 11
 
5.7%
d 9
 
4.6%
u 9
 
4.6%
Other values (11) 52
26.8%
Other Punctuation
ValueCountFrequency (%)
. 68
95.8%
' 3
 
4.2%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2424
50.4%
Latin 2025
42.1%
Common 365
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 225
 
9.3%
종 132
 
5.4%
등 115
 
4.7%
교 114
 
4.7%
고 113
 
4.7%
세 107
 
4.4%
과 107
 
4.4%
스 52
 
2.1%
우 49
 
2.0%
로 46
 
1.9%
Other values (200) 1364
56.3%
Latin
ValueCountFrequency (%)
O 196
 
9.7%
A 170
 
8.4%
I 151
 
7.5%
S 127
 
6.3%
T 126
 
6.2%
E 126
 
6.2%
N 125
 
6.2%
C 115
 
5.7%
L 101
 
5.0%
R 97
 
4.8%
Other values (37) 691
34.1%
Common
ValueCountFrequency (%)
265
72.6%
. 68
 
18.6%
) 14
 
3.8%
( 14
 
3.8%
' 3
 
0.8%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2424
50.4%
ASCII 2390
49.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
 
11.1%
O 196
 
8.2%
A 170
 
7.1%
I 151
 
6.3%
S 127
 
5.3%
T 126
 
5.3%
E 126
 
5.3%
N 125
 
5.2%
C 115
 
4.8%
L 101
 
4.2%
Other values (43) 888
37.2%
Hangul
ValueCountFrequency (%)
학 225
 
9.3%
종 132
 
5.4%
등 115
 
4.7%
교 114
 
4.7%
고 113
 
4.7%
세 107
 
4.4%
과 107
 
4.4%
스 52
 
2.1%
우 49
 
2.0%
로 46
 
1.9%
Other values (200) 1364
56.3%

수거일자
Real number (ℝ)

Distinct409
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136750
Minimum20010910
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:13.645893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010910
5-th percentile20080326
Q120101118
median20130618
Q320170323
95-th percentile20210902
Maximum20240307
Range229397
Interquartile range (IQR)69205

Descriptive statistics

Standard deviation42030.968
Coefficient of variation (CV)0.0020872766
Kurtosis-0.56271742
Mean20136750
Median Absolute Deviation (MAD)30094
Skewness0.39832367
Sum1.5054235 × 1011
Variance1.7666023 × 109
MonotonicityNot monotonic
2024-05-03T23:04:14.396014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091216 182
 
2.4%
20210902 148
 
2.0%
20120709 105
 
1.4%
20151130 99
 
1.3%
20230911 91
 
1.2%
20120906 82
 
1.1%
20071024 78
 
1.0%
20170831 76
 
1.0%
20110412 70
 
0.9%
20170530 70
 
0.9%
Other values (399) 6475
86.6%
ValueCountFrequency (%)
20010910 1
 
< 0.1%
20010925 3
 
< 0.1%
20020718 1
 
< 0.1%
20020719 1
 
< 0.1%
20020910 1
 
< 0.1%
20070710 2
 
< 0.1%
20070719 1
 
< 0.1%
20070723 8
0.1%
20070726 18
0.2%
20070731 2
 
< 0.1%
ValueCountFrequency (%)
20240307 1
 
< 0.1%
20240227 3
 
< 0.1%
20240226 28
0.4%
20240122 1
 
< 0.1%
20240118 1
 
< 0.1%
20240117 17
0.2%
20240111 6
 
0.1%
20231129 31
0.4%
20231114 1
 
< 0.1%
20231026 2
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct43
Distinct (%)0.6%
Missing520
Missing (%)7.0%
Infinite0
Infinite (%)0.0%
Mean8.3578709
Minimum0.15
Maximum3900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:14.952274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum3900
Range3899.85
Interquartile range (IQR)3

Descriptive statistics

Standard deviation63.593363
Coefficient of variation (CV)7.6087994
Kurtosis2083.518
Mean8.3578709
Median Absolute Deviation (MAD)2
Skewness37.628484
Sum58137.35
Variance4044.1159
MonotonicityNot monotonic
2024-05-03T23:04:15.556604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1.0 2158
28.9%
3.0 1719
23.0%
2.0 1014
13.6%
6.0 890
11.9%
5.0 384
 
5.1%
4.0 351
 
4.7%
10.0 69
 
0.9%
7.0 67
 
0.9%
8.0 49
 
0.7%
300.0 48
 
0.6%
Other values (33) 207
 
2.8%
(Missing) 520
 
7.0%
ValueCountFrequency (%)
0.15 1
 
< 0.1%
0.3 4
 
0.1%
1.0 2158
28.9%
2.0 1014
13.6%
3.0 1719
23.0%
4.0 351
 
4.7%
5.0 384
 
5.1%
6.0 890
11.9%
7.0 67
 
0.9%
8.0 49
 
0.7%
ValueCountFrequency (%)
3900.0 1
 
< 0.1%
1380.0 1
 
< 0.1%
1200.0 1
 
< 0.1%
960.0 1
 
< 0.1%
600.0 6
 
0.1%
500.0 3
 
< 0.1%
400.0 1
 
< 0.1%
350.0 6
 
0.1%
320.0 1
 
< 0.1%
300.0 48
0.6%

제품규격(정량)
Text

MISSING 

Distinct641
Distinct (%)11.5%
Missing1887
Missing (%)25.2%
Memory size58.5 KiB
2024-05-03T23:04:16.837817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7822508
Min length1

Characters and Unicode

Total characters15550
Distinct characters171
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique301 ?
Unique (%)5.4%

Sample

1st row냉면육수
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 465
 
8.3%
1 339
 
6.1%
g 336
 
6.0%
600 314
 
5.6%
500 232
 
4.1%
300 212
 
3.8%
200 177
 
3.2%
400 155
 
2.8%
ml 123
 
2.2%
250 112
 
2.0%
Other values (628) 3126
55.9%
2024-05-03T23:04:18.072577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5649
36.3%
1 1778
 
11.4%
5 1290
 
8.3%
2 1221
 
7.9%
g 887
 
5.7%
3 885
 
5.7%
6 784
 
5.0%
4 668
 
4.3%
8 424
 
2.7%
7 364
 
2.3%
Other values (161) 1600
 
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13391
86.1%
Lowercase Letter 1417
 
9.1%
Other Letter 596
 
3.8%
Other Punctuation 107
 
0.7%
Uppercase Letter 36
 
0.2%
Space Separator 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 59
 
9.9%
물 46
 
7.7%
개 46
 
7.7%
기 28
 
4.7%
정 27
 
4.5%
김 17
 
2.9%
이 16
 
2.7%
족 15
 
2.5%
관 15
 
2.5%
치 15
 
2.5%
Other values (139) 312
52.3%
Decimal Number
ValueCountFrequency (%)
0 5649
42.2%
1 1778
 
13.3%
5 1290
 
9.6%
2 1221
 
9.1%
3 885
 
6.6%
6 784
 
5.9%
4 668
 
5.0%
8 424
 
3.2%
7 364
 
2.7%
9 328
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
g 887
62.6%
l 209
 
14.7%
m 201
 
14.2%
k 120
 
8.5%
Uppercase Letter
ValueCountFrequency (%)
L 26
72.2%
G 8
 
22.2%
K 1
 
2.8%
M 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 106
99.1%
, 1
 
0.9%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13501
86.8%
Latin 1453
 
9.3%
Hangul 596
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 59
 
9.9%
물 46
 
7.7%
개 46
 
7.7%
기 28
 
4.7%
정 27
 
4.5%
김 17
 
2.9%
이 16
 
2.7%
족 15
 
2.5%
관 15
 
2.5%
치 15
 
2.5%
Other values (139) 312
52.3%
Common
ValueCountFrequency (%)
0 5649
41.8%
1 1778
 
13.2%
5 1290
 
9.6%
2 1221
 
9.0%
3 885
 
6.6%
6 784
 
5.8%
4 668
 
4.9%
8 424
 
3.1%
7 364
 
2.7%
9 328
 
2.4%
Other values (4) 110
 
0.8%
Latin
ValueCountFrequency (%)
g 887
61.0%
l 209
 
14.4%
m 201
 
13.8%
k 120
 
8.3%
L 26
 
1.8%
G 8
 
0.6%
K 1
 
0.1%
M 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14953
96.2%
Hangul 594
 
3.8%
Compat Jamo 2
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5649
37.8%
1 1778
 
11.9%
5 1290
 
8.6%
2 1221
 
8.2%
g 887
 
5.9%
3 885
 
5.9%
6 784
 
5.2%
4 668
 
4.5%
8 424
 
2.8%
7 364
 
2.4%
Other values (11) 1003
 
6.7%
Hangul
ValueCountFrequency (%)
수 59
 
9.9%
물 46
 
7.7%
개 46
 
7.7%
기 28
 
4.7%
정 27
 
4.5%
김 17
 
2.9%
이 16
 
2.7%
족 15
 
2.5%
관 15
 
2.5%
치 15
 
2.5%
Other values (137) 310
52.2%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
50.0%
ㅔ 1
50.0%
CJK Compat
ValueCountFrequency (%)
㎖ 1
100.0%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
g
3219 
<NA>
3165 
ML
625 
KG
 
276
LT
 
188
Other values (2)
 
3

Length

Max length4
Median length2
Mean length2.4158641
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 3219
43.1%
<NA> 3165
42.3%
ML 625
 
8.4%
KG 276
 
3.7%
LT 188
 
2.5%
매 2
 
< 0.1%
mm 1
 
< 0.1%

Length

2024-05-03T23:04:18.525733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:19.047047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3219
43.1%
na 3165
42.3%
ml 625
 
8.4%
kg 276
 
3.7%
lt 188
 
2.5%
매 2
 
< 0.1%
mm 1
 
< 0.1%

수거량(자유)
Text

MISSING 

Distinct77
Distinct (%)14.8%
Missing6956
Missing (%)93.0%
Memory size58.5 KiB
2024-05-03T23:04:19.565325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length3.5692308
Min length1

Characters and Unicode

Total characters1856
Distinct characters70
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

Unique46 ?
Unique (%)8.8%

Sample

1st row칼 스웹 3개
2nd row도마스웹 3개
3rd row칼 스웹 3개
4th row도마스웹 3개
5th row1개
ValueCountFrequency (%)
1개 80
13.7%
3개 57
 
9.7%
1인분 56
 
9.6%
600g 48
 
8.2%
1 42
 
7.2%
200g 31
 
5.3%
400g 27
 
4.6%
2개 20
 
3.4%
150그램 19
 
3.2%
스웹 18
 
3.1%
Other values (64) 188
32.1%
2024-05-03T23:04:20.952296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 367
19.8%
1 257
13.8%
개 177
 
9.5%
g 146
 
7.9%
3 94
 
5.1%
6 69
 
3.7%
69
 
3.7%
2 68
 
3.7%
인 58
 
3.1%
분 57
 
3.1%
Other values (60) 494
26.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 952
51.3%
Other Letter 630
33.9%
Lowercase Letter 153
 
8.2%
Space Separator 69
 
3.7%
Uppercase Letter 22
 
1.2%
Other Punctuation 18
 
1.0%
Open Punctuation 6
 
0.3%
Close Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 177
28.1%
인 58
 
9.2%
분 57
 
9.0%
그 44
 
7.0%
램 44
 
7.0%
스 30
 
4.8%
웹 30
 
4.8%
줄 24
 
3.8%
마 17
 
2.7%
도 16
 
2.5%
Other values (37) 133
21.1%
Decimal Number
ValueCountFrequency (%)
0 367
38.6%
1 257
27.0%
3 94
 
9.9%
6 69
 
7.2%
2 68
 
7.1%
5 51
 
5.4%
4 41
 
4.3%
8 3
 
0.3%
9 1
 
0.1%
7 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
g 146
95.4%
l 3
 
2.0%
m 3
 
2.0%
k 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
E 8
36.4%
A 8
36.4%
G 5
22.7%
P 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
* 17
94.4%
？ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1051
56.6%
Hangul 630
33.9%
Latin 175
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 177
28.1%
인 58
 
9.2%
분 57
 
9.0%
그 44
 
7.0%
램 44
 
7.0%
스 30
 
4.8%
웹 30
 
4.8%
줄 24
 
3.8%
마 17
 
2.7%
도 16
 
2.5%
Other values (37) 133
21.1%
Common
ValueCountFrequency (%)
0 367
34.9%
1 257
24.5%
3 94
 
8.9%
6 69
 
6.6%
69
 
6.6%
2 68
 
6.5%
5 51
 
4.9%
4 41
 
3.9%
* 17
 
1.6%
( 6
 
0.6%
Other values (5) 12
 
1.1%
Latin
ValueCountFrequency (%)
g 146
83.4%
E 8
 
4.6%
A 8
 
4.6%
G 5
 
2.9%
l 3
 
1.7%
m 3
 
1.7%
k 1
 
0.6%
P 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1225
66.0%
Hangul 630
33.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 367
30.0%
1 257
21.0%
g 146
 
11.9%
3 94
 
7.7%
6 69
 
5.6%
69
 
5.6%
2 68
 
5.6%
5 51
 
4.2%
4 41
 
3.3%
* 17
 
1.4%
Other values (12) 46
 
3.8%
Hangul
ValueCountFrequency (%)
개 177
28.1%
인 58
 
9.2%
분 57
 
9.0%
그 44
 
7.0%
램 44
 
7.0%
스 30
 
4.8%
웹 30
 
4.8%
줄 24
 
3.8%
마 17
 
2.7%
도 16
 
2.5%
Other values (37) 133
21.1%
None
ValueCountFrequency (%)
？ 1
100.0%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct423
Distinct (%)24.3%
Missing5735
Missing (%)76.7%
Infinite0
Infinite (%)0.0%
Mean20123658
Minimum10000101
Maximum20261017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:21.663038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000101
5-th percentile20120605
Q120130701
median20160623
Q320181115
95-th percentile20240728
Maximum20261017
Range10260916
Interquartile range (IQR)50414

Descriptive statistics

Standard deviation644605.26
Coefficient of variation (CV)0.032032211
Kurtosis242.58092
Mean20123658
Median Absolute Deviation (MAD)29788
Skewness-15.600347
Sum3.5035288 × 1010
Variance4.1551594 × 1011
MonotonicityNot monotonic
2024-05-03T23:04:22.098302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120709 104
 
1.4%
20180621 48
 
0.6%
20151116 41
 
0.5%
20161201 41
 
0.5%
20121128 36
 
0.5%
20150713 32
 
0.4%
20130712 32
 
0.4%
20170831 29
 
0.4%
20140723 27
 
0.4%
20170622 23
 
0.3%
Other values (413) 1328
 
17.8%
(Missing) 5735
76.7%
ValueCountFrequency (%)
10000101 7
0.1%
20110713 1
 
< 0.1%
20110801 1
 
< 0.1%
20110812 1
 
< 0.1%
20110919 1
 
< 0.1%
20111201 1
 
< 0.1%
20111215 1
 
< 0.1%
20120115 1
 
< 0.1%
20120118 1
 
< 0.1%
20120207 4
0.1%
ValueCountFrequency (%)
20261017 1
< 0.1%
20260706 1
< 0.1%
20260109 1
< 0.1%
20251228 1
< 0.1%
20251221 2
< 0.1%
20251214 1
< 0.1%
20251108 1
< 0.1%
20251017 1
< 0.1%
20250903 1
< 0.1%
20250815 1
< 0.1%

제조일자(롯트)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7465 
0
 
9
11111
 
1
910901
 
1

Length

Max length6
Median length4
Mean length3.9967897
Min length1

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> 7465
99.9%
0 9
 
0.1%
11111 1
 
< 0.1%
910901 1
 
< 0.1%

Length

2024-05-03T23:04:22.702904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:23.118126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7465
99.9%
0 9
 
0.1%
11111 1
 
< 0.1%
910901 1
 
< 0.1%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)76.0%
Missing7309
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean20121269
Minimum20111014
Maximum20141023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:23.616148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20111014
5-th percentile20111028
Q120111128
median20120411
Q320121216
95-th percentile20140912
Maximum20141023
Range30009
Interquartile range (IQR)10088

Descriptive statistics

Standard deviation9575.5367
Coefficient of variation (CV)0.0004758913
Kurtosis-0.24560355
Mean20121269
Median Absolute Deviation (MAD)9283
Skewness0.81175725
Sum3.3602519 × 109
Variance91690903
MonotonicityNot monotonic
2024-05-03T23:04:24.238301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111123 4
 
0.1%
20111121 4
 
0.1%
20111119 3
 
< 0.1%
20111029 3
 
< 0.1%
20130405 3
 
< 0.1%
20111203 3
 
< 0.1%
20111114 3
 
< 0.1%
20120411 3
 
< 0.1%
20120828 2
 
< 0.1%
20130305 2
 
< 0.1%
Other values (117) 137
 
1.8%
(Missing) 7309
97.8%
ValueCountFrequency (%)
20111014 1
 
< 0.1%
20111016 1
 
< 0.1%
20111024 2
< 0.1%
20111025 2
< 0.1%
20111027 2
< 0.1%
20111028 2
< 0.1%
20111029 3
< 0.1%
20111031 2
< 0.1%
20111107 1
 
< 0.1%
20111113 1
 
< 0.1%
ValueCountFrequency (%)
20141023 1
< 0.1%
20141016 1
< 0.1%
20141006 1
< 0.1%
20141004 2
< 0.1%
20141003 1
< 0.1%
20140923 1
< 0.1%
20140920 1
< 0.1%
20140914 1
< 0.1%
20140908 2
< 0.1%
20140907 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)100.0%
Missing7464
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean10115450
Minimum0
Maximum20231113
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:25.034607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q1157.5
median10115444
Q320230736
95-th percentile20230947
Maximum20231113
Range20231113
Interquartile range (IQR)20230579

Descriptive statistics

Standard deviation10565085
Coefficient of variation (CV)1.0444503
Kurtosis-2.4444444
Mean10115450
Median Absolute Deviation (MAD)10115311
Skewness3.7760325 × 10-10
Sum1.213854 × 108
Variance1.1162102 × 1014
MonotonicityNot monotonic
2024-05-03T23:04:25.523946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20230523 1
 
< 0.1%
180 1
 
< 0.1%
20231113 1
 
< 0.1%
20230712 1
 
< 0.1%
20230522 1
 
< 0.1%
2 1
 
< 0.1%
90 1
 
< 0.1%
270 1
 
< 0.1%
20230811 1
 
< 0.1%
20230810 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 7464
99.8%
ValueCountFrequency (%)
0 1
< 0.1%
2 1
< 0.1%
90 1
< 0.1%
180 1
< 0.1%
270 1
< 0.1%
365 1
< 0.1%
20230522 1
< 0.1%
20230523 1
< 0.1%
20230712 1
< 0.1%
20230810 1
< 0.1%
ValueCountFrequency (%)
20231113 1
< 0.1%
20230811 1
< 0.1%
20230810 1
< 0.1%
20230712 1
< 0.1%
20230523 1
< 0.1%
20230522 1
< 0.1%
365 1
< 0.1%
270 1
< 0.1%
180 1
< 0.1%
90 1
< 0.1%

보관상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
실온
3607 
<NA>
2651 
냉장
642 
냉동
481 
기타
 
95

Length

Max length4
Median length2
Mean length2.7092028
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 3607
48.2%
<NA> 2651
35.5%
냉장 642
 
8.6%
냉동 481
 
6.4%
기타 95
 
1.3%

Length

2024-05-03T23:04:25.941942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:26.277051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3607
48.2%
na 2651
35.5%
냉장 642
 
8.6%
냉동 481
 
6.4%
기타 95
 
1.3%

바코드번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7474 
8809097859964
 
1
8801043015653
 
1

Length

Max length13
Median length4
Mean length4.0024077
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> 7474
> 99.9%
8809097859964 1
 
< 0.1%
8801043015653 1
 
< 0.1%

Length

2024-05-03T23:04:26.613757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:26.967271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7474
> 99.9%
8809097859964 1
 
< 0.1%
8801043015653 1
 
< 0.1%

어린이기호식품유형
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7361 
과자(한과류제외)
 
57
캔디류
 
24
초콜릿류
 
13
빵류
 
11
Other values (2)
 
10

Length

Max length9
Median length4
Mean length4.0321027
Min length2

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> 7361
98.5%
과자(한과류제외) 57
 
0.8%
캔디류 24
 
0.3%
초콜릿류 13
 
0.2%
빵류 11
 
0.1%
혼합음료 9
 
0.1%
과?채주스 1
 
< 0.1%

Length

2024-05-03T23:04:27.273410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:27.625349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7361
98.5%
과자(한과류제외 57
 
0.8%
캔디류 24
 
0.3%
초콜릿류 13
 
0.2%
빵류 11
 
0.1%
혼합음료 9
 
0.1%
과?채주스 1
 
< 0.1%

검사기관명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
001
4844 
<NA>
2618 
004
 
6
서울시보건환경연구원
 
3
서울특별시보건환경연구원
 
2
Other values (3)
 
3

Length

Max length12
Median length3
Mean length3.3560728
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
001 4844
64.8%
<NA> 2618
35.0%
004 6
 
0.1%
서울시보건환경연구원 3
 
< 0.1%
서울특별시보건환경연구원 2
 
< 0.1%
감시계 직원 1
 
< 0.1%
육안 식별 1
 
< 0.1%
000 1
 
< 0.1%

Length

2024-05-03T23:04:28.000473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:28.340544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
001 4844
64.8%
na 2618
35.0%
004 6
 
0.1%
서울시보건환경연구원 3
 
< 0.1%
서울특별시보건환경연구원 2
 
< 0.1%
감시계 1
 
< 0.1%
직원 1
 
< 0.1%
육안 1
 
< 0.1%
식별 1
 
< 0.1%
000 1
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct195
Distinct (%)33.1%
Missing6887
Missing (%)92.1%
Memory size58.5 KiB
2024-05-03T23:04:28.878944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length7.5704584
Min length2

Characters and Unicode

Total characters4459
Distinct characters259
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)18.7%

Sample

1st row바다목장
2nd row우동과 김밥
3rd row루이스치킨집
4th row버디버디
5th row약수터식당
ValueCountFrequency (%)
씨제이제일제당(주 32
 
4.9%
서서울과학고 30
 
4.6%
육회지존 20
 
3.1%
롯데칠성음료(주 19
 
2.9%
동서식품 15
 
2.3%
오뚜기라면주식회사 15
 
2.3%
주)오리온 14
 
2.1%
주)삼립식품 14
 
2.1%
해태제과식품(주 12
 
1.8%
주식회사 11
 
1.7%
Other values (214) 472
72.2%
2024-05-03T23:04:29.793411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 423
 
9.5%
) 339
 
7.6%
( 339
 
7.6%
식 177
 
4.0%
제 160
 
3.6%
품 108
 
2.4%
회 100
 
2.2%
서 90
 
2.0%
과 82
 
1.8%
사 78
 
1.7%
Other values (249) 2563
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3328
74.6%
Close Punctuation 339
 
7.6%
Open Punctuation 339
 
7.6%
Lowercase Letter 220
 
4.9%
Uppercase Letter 135
 
3.0%
Space Separator 65
 
1.5%
Other Punctuation 30
 
0.7%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 423
 
12.7%
식 177
 
5.3%
제 160
 
4.8%
품 108
 
3.2%
회 100
 
3.0%
서 90
 
2.7%
과 82
 
2.5%
사 78
 
2.3%
이 73
 
2.2%
오 68
 
2.0%
Other values (196) 1969
59.2%
Lowercase Letter
ValueCountFrequency (%)
o 34
15.5%
a 33
15.0%
n 19
 
8.6%
p 15
 
6.8%
i 12
 
5.5%
m 12
 
5.5%
s 11
 
5.0%
r 11
 
5.0%
d 10
 
4.5%
l 10
 
4.5%
Other values (13) 53
24.1%
Uppercase Letter
ValueCountFrequency (%)
F 32
23.7%
B 21
15.6%
S 14
10.4%
C 13
9.6%
D 10
 
7.4%
L 7
 
5.2%
P 6
 
4.4%
T 6
 
4.4%
M 4
 
3.0%
I 4
 
3.0%
Other values (10) 18
13.3%
Other Punctuation
ValueCountFrequency (%)
& 10
33.3%
; 10
33.3%
. 5
16.7%
？ 5
16.7%
Close Punctuation
ValueCountFrequency (%)
) 339
100.0%
Open Punctuation
ValueCountFrequency (%)
( 339
100.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3328
74.6%
Common 776
 
17.4%
Latin 355
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 423
 
12.7%
식 177
 
5.3%
제 160
 
4.8%
품 108
 
3.2%
회 100
 
3.0%
서 90
 
2.7%
과 82
 
2.5%
사 78
 
2.3%
이 73
 
2.2%
오 68
 
2.0%
Other values (196) 1969
59.2%
Latin
ValueCountFrequency (%)
o 34
 
9.6%
a 33
 
9.3%
F 32
 
9.0%
B 21
 
5.9%
n 19
 
5.4%
p 15
 
4.2%
S 14
 
3.9%
C 13
 
3.7%
i 12
 
3.4%
m 12
 
3.4%
Other values (33) 150
42.3%
Common
ValueCountFrequency (%)
) 339
43.7%
( 339
43.7%
65
 
8.4%
& 10
 
1.3%
; 10
 
1.3%
. 5
 
0.6%
？ 5
 
0.6%
~ 1
 
0.1%
- 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3328
74.6%
ASCII 1126
 
25.3%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 423
 
12.7%
식 177
 
5.3%
제 160
 
4.8%
품 108
 
3.2%
회 100
 
3.0%
서 90
 
2.7%
과 82
 
2.5%
사 78
 
2.3%
이 73
 
2.2%
오 68
 
2.0%
Other values (196) 1969
59.2%
ASCII
ValueCountFrequency (%)
) 339
30.1%
( 339
30.1%
65
 
5.8%
o 34
 
3.0%
a 33
 
2.9%
F 32
 
2.8%
B 21
 
1.9%
n 19
 
1.7%
p 15
 
1.3%
S 14
 
1.2%
Other values (42) 215
19.1%
None
ValueCountFrequency (%)
？ 5
100.0%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
국내
5555 
국외
1921 

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 5555
74.3%
국외 1921
 
25.7%

Length

2024-05-03T23:04:30.217560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:30.512886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 5555
74.3%
국외 1921
 
25.7%

국가명
Categorical

IMBALANCE 

Distinct49
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
6922 
미국
 
104
중국
 
62
이탈리아
 
41
일본
 
35
Other values (44)
 
312

Length

Max length9
Median length4
Mean length3.9066346
Min length2

Unique

Unique17 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6922
92.6%
미국 104
 
1.4%
중국 62
 
0.8%
이탈리아 41
 
0.5%
일본 35
 
0.5%
태국 34
 
0.5%
벨기에 32
 
0.4%
독일 30
 
0.4%
베트남 29
 
0.4%
스페인 17
 
0.2%
Other values (39) 170
 
2.3%

Length

2024-05-03T23:04:30.926798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6922
92.5%
미국 104
 
1.4%
중국 63
 
0.8%
이탈리아 41
 
0.5%
일본 35
 
0.5%
태국 34
 
0.5%
벨기에 32
 
0.4%
독일 30
 
0.4%
베트남 29
 
0.4%
스페인 17
 
0.2%
Other values (40) 174
 
2.3%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
3348 
1
2951 
2
1177 

Length

Max length4
Median length1
Mean length2.3434992
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 (%)
<NA> 3348
44.8%
1 2951
39.5%
2 1177
 
15.7%

Length

2024-05-03T23:04:31.637133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:32.064245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3348
44.8%
1 2951
39.5%
2 1177
 
15.7%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct185
Distinct (%)5.3%
Missing3985
Missing (%)53.3%
Infinite0
Infinite (%)0.0%
Mean20158376
Minimum20100119
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:32.547838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100119
5-th percentile20100618
Q120110816
median20170216
Q320181129
95-th percentile20230912
Maximum20240307
Range140188
Interquartile range (IQR)70313

Descriptive statistics

Standard deviation42827.8
Coefficient of variation (CV)0.002124566
Kurtosis-1.1761543
Mean20158376
Median Absolute Deviation (MAD)30907
Skewness0.013141175
Sum7.0372891 × 1010
Variance1.8342205 × 109
MonotonicityNot monotonic
2024-05-03T23:04:33.294359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210906 148
 
2.0%
20110809 104
 
1.4%
20230912 98
 
1.3%
20110413 69
 
0.9%
20100630 68
 
0.9%
20170831 62
 
0.8%
20101001 61
 
0.8%
20111101 61
 
0.8%
20110315 51
 
0.7%
20180621 48
 
0.6%
Other values (175) 2721
36.4%
(Missing) 3985
53.3%
ValueCountFrequency (%)
20100119 15
 
0.2%
20100225 20
0.3%
20100308 5
 
0.1%
20100323 6
 
0.1%
20100324 12
 
0.2%
20100325 12
 
0.2%
20100415 3
 
< 0.1%
20100426 39
0.5%
20100513 4
 
0.1%
20100530 15
 
0.2%
ValueCountFrequency (%)
20240307 1
 
< 0.1%
20240228 28
0.4%
20240227 3
 
< 0.1%
20240118 25
0.3%
20231129 31
0.4%
20231114 1
 
< 0.1%
20231026 2
 
< 0.1%
20231017 1
 
< 0.1%
20231012 1
 
< 0.1%
20230919 43
0.6%

결과회보일자
Real number (ℝ)

MISSING 

Distinct152
Distinct (%)7.8%
Missing5527
Missing (%)73.9%
Infinite0
Infinite (%)0.0%
Mean20172935
Minimum20100322
Maximum20210927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:34.021579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100322
5-th percentile20111109
Q120160913
median20170915
Q320181001
95-th percentile20210208
Maximum20210927
Range110605
Interquartile range (IQR)20088

Descriptive statistics

Standard deviation22186.304
Coefficient of variation (CV)0.0010998055
Kurtosis3.4614174
Mean20172935
Median Absolute Deviation (MAD)10002
Skewness-1.3432532
Sum3.931705 × 1010
Variance4.922321 × 108
MonotonicityNot monotonic
2024-05-03T23:04:34.784824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210927 93
 
1.2%
20160705 51
 
0.7%
20170508 51
 
0.7%
20160212 48
 
0.6%
20180705 48
 
0.6%
20160616 42
 
0.6%
20160308 41
 
0.5%
20160414 41
 
0.5%
20201027 38
 
0.5%
20160927 38
 
0.5%
Other values (142) 1458
 
19.5%
(Missing) 5527
73.9%
ValueCountFrequency (%)
20100322 5
 
0.1%
20100331 7
0.1%
20100524 1
 
< 0.1%
20100526 4
 
0.1%
20100527 15
0.2%
20100623 4
 
0.1%
20100707 1
 
< 0.1%
20100712 1
 
< 0.1%
20100727 17
0.2%
20101129 5
 
0.1%
ValueCountFrequency (%)
20210927 93
1.2%
20210427 2
 
< 0.1%
20210210 1
 
< 0.1%
20210208 3
 
< 0.1%
20201207 18
 
0.2%
20201204 15
 
0.2%
20201203 12
 
0.2%
20201202 4
 
0.1%
20201106 1
 
< 0.1%
20201104 37
 
0.5%

판정구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
3865 
1
3588 
2
 
23

Length

Max length4
Median length4
Mean length2.5509631
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> 3865
51.7%
1 3588
48.0%
2 23
 
0.3%

Length

2024-05-03T23:04:35.314963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:35.802057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3865
51.7%
1 3588
48.0%
2 23
 
0.3%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

처리결과
Text

MISSING 

Distinct19
Distinct (%)61.3%
Missing7445
Missing (%)99.6%
Memory size58.5 KiB
2024-05-03T23:04:36.358914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length13.516129
Min length4

Characters and Unicode

Total characters419
Distinct characters55
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

Unique13 ?
Unique (%)41.9%

Sample

1st row행정조치(당시 조리식품 현장에 없었음)
2nd row영업정지처분
3rd rowGMO정성검사
4th row기준이내(3%)
5th row행정처분
ValueCountFrequency (%)
트랜스 17
18.1%
지방 17
18.1%
70g당 13
13.8%
기준이내(3 5
 
5.3%
0g 4
 
4.3%
30g당 4
 
4.3%
0.01g 3
 
3.2%
0.03g 3
 
3.2%
gmo정성검사 3
 
3.2%
트랜스지방 2
 
2.1%
Other values (19) 23
24.5%
2024-05-03T23:04:37.396947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
15.3%
0 52
 
12.4%
g 38
 
9.1%
당 21
 
5.0%
지 20
 
4.8%
방 19
 
4.5%
스 19
 
4.5%
랜 19
 
4.5%
트 19
 
4.5%
7 15
 
3.6%
Other values (45) 133
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
43.9%
Decimal Number 92
22.0%
Space Separator 64
 
15.3%
Lowercase Letter 38
 
9.1%
Other Punctuation 20
 
4.8%
Uppercase Letter 9
 
2.1%
Close Punctuation 6
 
1.4%
Open Punctuation 6
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 21
11.4%
지 20
10.9%
방 19
10.3%
스 19
10.3%
랜 19
10.3%
트 19
10.3%
기 6
 
3.3%
정 6
 
3.3%
준 5
 
2.7%
이 5
 
2.7%
Other values (27) 45
24.5%
Decimal Number
ValueCountFrequency (%)
0 52
56.5%
7 15
 
16.3%
3 12
 
13.0%
1 6
 
6.5%
4 2
 
2.2%
9 2
 
2.2%
6 1
 
1.1%
2 1
 
1.1%
5 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
G 3
33.3%
M 3
33.3%
O 3
33.3%
Other Punctuation
ValueCountFrequency (%)
. 15
75.0%
% 5
 
25.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 188
44.9%
Hangul 184
43.9%
Latin 47
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 21
11.4%
지 20
10.9%
방 19
10.3%
스 19
10.3%
랜 19
10.3%
트 19
10.3%
기 6
 
3.3%
정 6
 
3.3%
준 5
 
2.7%
이 5
 
2.7%
Other values (27) 45
24.5%
Common
ValueCountFrequency (%)
64
34.0%
0 52
27.7%
7 15
 
8.0%
. 15
 
8.0%
3 12
 
6.4%
1 6
 
3.2%
) 6
 
3.2%
( 6
 
3.2%
% 5
 
2.7%
4 2
 
1.1%
Other values (4) 5
 
2.7%
Latin
ValueCountFrequency (%)
g 38
80.9%
G 3
 
6.4%
M 3
 
6.4%
O 3
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235
56.1%
Hangul 184
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
27.2%
0 52
22.1%
g 38
16.2%
7 15
 
6.4%
. 15
 
6.4%
3 12
 
5.1%
1 6
 
2.6%
) 6
 
2.6%
( 6
 
2.6%
% 5
 
2.1%
Other values (8) 16
 
6.8%
Hangul
ValueCountFrequency (%)
당 21
11.4%
지 20
10.9%
방 19
10.3%
스 19
10.3%
랜 19
10.3%
트 19
10.3%
기 6
 
3.3%
정 6
 
3.3%
준 5
 
2.7%
이 5
 
2.7%
Other values (27) 45
24.5%

수거품처리
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7443 
검사후 보환연 폐기처리
 
22
검사 후 보환연 폐기처리
 
10
검사후 폐기
 
1

Length

Max length13
Median length4
Mean length4.035848
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7443
99.6%
검사후 보환연 폐기처리 22
 
0.3%
검사 후 보환연 폐기처리 10
 
0.1%
검사후 폐기 1
 
< 0.1%

Length

2024-05-03T23:04:37.866875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:38.221644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7443
98.6%
보환연 32
 
0.4%
폐기처리 32
 
0.4%
검사후 23
 
0.3%
검사 10
 
0.1%
후 10
 
0.1%
폐기 1
 
< 0.1%

교부번호
Real number (ℝ)

Distinct555
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.006194 × 1010
Minimum1.979008 × 1010
Maximum2.0230107 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:38.822527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.979008 × 1010
5-th percentile1.9980081 × 1010
Q12.003008 × 1010
median2.0070081 × 1010
Q32.0090081 × 1010
95-th percentile2.015008 × 1010
Maximum2.0230107 × 1010
Range4.4002652 × 108
Interquartile range (IQR)60000287

Descriptive statistics

Standard deviation56295292
Coefficient of variation (CV)0.0028060742
Kurtosis1.2345221
Mean2.006194 × 1010
Median Absolute Deviation (MAD)29999877
Skewness-0.54987691
Sum1.4998306 × 1014
Variance3.16916 × 1015
MonotonicityNot monotonic
2024-05-03T23:04:39.365002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070080812 1346
 
18.0%
19990081058 537
 
7.2%
20070080905 491
 
6.6%
20050080410 477
 
6.4%
20130080031 344
 
4.6%
20090080207 293
 
3.9%
20160080207 197
 
2.6%
19990080638 163
 
2.2%
20000080390 130
 
1.7%
20110080313 116
 
1.6%
Other values (545) 3382
45.2%
ValueCountFrequency (%)
19790080033 1
 
< 0.1%
19800080013 6
 
0.1%
19810080094 1
 
< 0.1%
19820080132 16
0.2%
19830080083 1
 
< 0.1%
19830080111 6
 
0.1%
19830080254 3
 
< 0.1%
19840080269 3
 
< 0.1%
19850080059 3
 
< 0.1%
19850080208 1
 
< 0.1%
ValueCountFrequency (%)
20230106556 1
 
< 0.1%
20220099071 1
 
< 0.1%
20220098663 2
 
< 0.1%
20220098201 5
0.1%
20220098162 1
 
< 0.1%
20210081024 7
0.1%
20210080790 1
 
< 0.1%
20200081217 1
 
< 0.1%
20200081112 2
 
< 0.1%
20200081071 1
 
< 0.1%

폐기일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7474 
20080129
 
1
20200731
 
1

Length

Max length8
Median length4
Mean length4.0010701
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> 7474
> 99.9%
20080129 1
 
< 0.1%
20200731 1
 
< 0.1%

Length

2024-05-03T23:04:39.841681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:40.232450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7474
> 99.9%
20080129 1
 
< 0.1%
20200731 1
 
< 0.1%

폐기량(Kg)
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7474 
8
 
1
255000
 
1

Length

Max length6
Median length4
Mean length3.9998662
Min length1

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> 7474
> 99.9%
8 1
 
< 0.1%
255000 1
 
< 0.1%

Length

2024-05-03T23:04:40.645207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:40.963520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7474
> 99.9%
8 1
 
< 0.1%
255000 1
 
< 0.1%

폐기금액(원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
<NA>
7475 
64000
 
1

Length

Max length5
Median length4
Mean length4.0001338
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7475
> 99.9%
64000 1
 
< 0.1%

Length

2024-05-03T23:04:41.350945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:41.763687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7475
> 99.9%
64000 1
 
< 0.1%

폐기장소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing7475
Missing (%)> 99.9%
Memory size58.5 KiB
2024-05-03T23:04:42.051208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
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 row업소 자체
ValueCountFrequency (%)
업소 1
50.0%
자체 1
50.0%
2024-05-03T23:04:42.782623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 1
20.0%
소 1
20.0%
1
20.0%
자 1
20.0%
체 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
80.0%
Space Separator 1
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1
25.0%
소 1
25.0%
자 1
25.0%
체 1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
80.0%
Common 1
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1
25.0%
소 1
25.0%
자 1
25.0%
체 1
25.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
80.0%
ASCII 1
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 1
25.0%
소 1
25.0%
자 1
25.0%
체 1
25.0%
ASCII
ValueCountFrequency (%)
1
100.0%

폐기방법
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing7475
Missing (%)> 99.9%
Memory size58.5 KiB
2024-05-03T23:04:42.991296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자체폐기
ValueCountFrequency (%)
자체폐기 1
100.0%
2024-05-03T23:04:43.484873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 1
25.0%
체 1
25.0%
폐 1
25.0%
기 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 1
25.0%
체 1
25.0%
폐 1
25.0%
기 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 1
25.0%
체 1
25.0%
폐 1
25.0%
기 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 1
25.0%
체 1
25.0%
폐 1
25.0%
기 1
25.0%

소재지(도로명)
Text

MISSING 

Distinct336
Distinct (%)5.0%
Missing778
Missing (%)10.4%
Memory size58.5 KiB
2024-05-03T23:04:43.835942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length101
Median length56
Mean length35.096895
Min length23

Characters and Unicode

Total characters235079
Distinct characters233
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

Unique127 ?
Unique (%)1.9%

Sample

1st row서울특별시 구로구 가마산로 225, (구로동)
2nd row서울특별시 구로구 가마산로 225, (구로동)
3rd row서울특별시 구로구 구로중앙로19길 24, (구로동)
4th row서울특별시 구로구 구로중앙로19길 24, (구로동)
5th row서울특별시 구로구 디지털로32길 97-39, 2층 (구로동, 성민빌딩)
ValueCountFrequency (%)
서울특별시 6698
17.0%
구로구 6698
17.0%
구로동 2251
 
5.7%
지하2층 1434
 
3.6%
새말로 1418
 
3.6%
97 1397
 
3.5%
경인로 1369
 
3.5%
구로동,이마트신도림점 1346
 
3.4%
지하1층 747
 
1.9%
구로중앙로 688
 
1.7%
Other values (559) 15339
38.9%
2024-05-03T23:04:44.576305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32692
 
13.9%
로 19808
 
8.4%
구 19484
 
8.3%
, 12073
 
5.1%
) 7609
 
3.2%
( 7609
 
3.2%
동 7159
 
3.0%
시 6941
 
3.0%
서 6774
 
2.9%
1 6774
 
2.9%
Other values (223) 108156
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138470
58.9%
Decimal Number 34676
 
14.8%
Space Separator 32692
 
13.9%
Other Punctuation 12074
 
5.1%
Close Punctuation 7609
 
3.2%
Open Punctuation 7609
 
3.2%
Dash Punctuation 1511
 
0.6%
Uppercase Letter 432
 
0.2%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 19808
 
14.3%
구 19484
 
14.1%
동 7159
 
5.2%
시 6941
 
5.0%
서 6774
 
4.9%
울 6737
 
4.9%
별 6713
 
4.8%
특 6698
 
4.8%
지 4239
 
3.1%
층 3412
 
2.5%
Other values (193) 50505
36.5%
Uppercase Letter
ValueCountFrequency (%)
B 370
85.6%
A 22
 
5.1%
K 14
 
3.2%
S 9
 
2.1%
C 6
 
1.4%
N 4
 
0.9%
F 2
 
0.5%
G 1
 
0.2%
I 1
 
0.2%
T 1
 
0.2%
Other values (2) 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 6774
19.5%
2 5892
17.0%
4 4201
12.1%
3 3759
10.8%
6 3003
8.7%
7 2955
8.5%
9 2432
 
7.0%
8 2213
 
6.4%
0 1983
 
5.7%
5 1464
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 12073
> 99.9%
. 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 5
83.3%
+ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
32692
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7609
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7609
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1511
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138470
58.9%
Common 96177
40.9%
Latin 432
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 19808
 
14.3%
구 19484
 
14.1%
동 7159
 
5.2%
시 6941
 
5.0%
서 6774
 
4.9%
울 6737
 
4.9%
별 6713
 
4.8%
특 6698
 
4.8%
지 4239
 
3.1%
층 3412
 
2.5%
Other values (193) 50505
36.5%
Common
ValueCountFrequency (%)
32692
34.0%
, 12073
 
12.6%
) 7609
 
7.9%
( 7609
 
7.9%
1 6774
 
7.0%
2 5892
 
6.1%
4 4201
 
4.4%
3 3759
 
3.9%
6 3003
 
3.1%
7 2955
 
3.1%
Other values (8) 9610
 
10.0%
Latin
ValueCountFrequency (%)
B 370
85.6%
A 22
 
5.1%
K 14
 
3.2%
S 9
 
2.1%
C 6
 
1.4%
N 4
 
0.9%
F 2
 
0.5%
G 1
 
0.2%
I 1
 
0.2%
T 1
 
0.2%
Other values (2) 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138470
58.9%
ASCII 96609
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32692
33.8%
, 12073
 
12.5%
) 7609
 
7.9%
( 7609
 
7.9%
1 6774
 
7.0%
2 5892
 
6.1%
4 4201
 
4.3%
3 3759
 
3.9%
6 3003
 
3.1%
7 2955
 
3.1%
Other values (20) 10042
 
10.4%
Hangul
ValueCountFrequency (%)
로 19808
 
14.3%
구 19484
 
14.1%
동 7159
 
5.2%
시 6941
 
5.0%
서 6774
 
4.9%
울 6737
 
4.9%
별 6713
 
4.8%
특 6698
 
4.8%
지 4239
 
3.1%
층 3412
 
2.5%
Other values (193) 50505
36.5%

소재지(지번)
Text

MISSING 

Distinct513
Distinct (%)7.5%
Missing599
Missing (%)8.0%
Memory size58.5 KiB
2024-05-03T23:04:44.932946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length54
Mean length33.161553
Min length21

Characters and Unicode

Total characters228052
Distinct characters229
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

Unique237 ?
Unique (%)3.4%

Sample

1st row서울특별시 구로구 오류동 13번지 55호
2nd row서울특별시 구로구 구로동 600번지 6호
3rd row서울특별시 구로구 구로동 600번지 6호
4th row서울특별시 구로구 구로동 600번지 6호
5th row서울특별시 구로구 구로동 600번지 6호
ValueCountFrequency (%)
서울특별시 6877
16.6%
구로구 6877
16.6%
구로동 4427
 
10.7%
지하2층 1347
 
3.2%
25호 1334
 
3.2%
3번지 1323
 
3.2%
이마트신도림점 1253
 
3.0%
신도림동 898
 
2.2%
지하1층 835
 
2.0%
1호 709
 
1.7%
Other values (655) 15665
37.7%
2024-05-03T23:04:45.680394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50948
22.3%
구 18453
 
8.1%
로 12051
 
5.3%
지 10208
 
4.5%
1 8774
 
3.8%
동 7143
 
3.1%
시 7109
 
3.1%
서 6952
 
3.0%
울 6951
 
3.0%
별 6892
 
3.0%
Other values (219) 92571
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131979
57.9%
Space Separator 50948
 
22.3%
Decimal Number 40322
 
17.7%
Dash Punctuation 1357
 
0.6%
Other Punctuation 1293
 
0.6%
Open Punctuation 873
 
0.4%
Close Punctuation 873
 
0.4%
Uppercase Letter 406
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 18453
14.0%
로 12051
 
9.1%
지 10208
 
7.7%
동 7143
 
5.4%
시 7109
 
5.4%
서 6952
 
5.3%
울 6951
 
5.3%
별 6892
 
5.2%
번 6879
 
5.2%
특 6877
 
5.2%
Other values (194) 42464
32.2%
Decimal Number
ValueCountFrequency (%)
1 8774
21.8%
2 6520
16.2%
3 5164
12.8%
5 4014
10.0%
6 3445
 
8.5%
8 3019
 
7.5%
0 2969
 
7.4%
4 2830
 
7.0%
7 1979
 
4.9%
9 1608
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 348
85.7%
A 20
 
4.9%
K 15
 
3.7%
C 8
 
2.0%
F 6
 
1.5%
N 4
 
1.0%
S 4
 
1.0%
E 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1288
99.6%
. 5
 
0.4%
Space Separator
ValueCountFrequency (%)
50948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1357
100.0%
Open Punctuation
ValueCountFrequency (%)
( 873
100.0%
Close Punctuation
ValueCountFrequency (%)
) 873
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 131979
57.9%
Common 95667
41.9%
Latin 406
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 18453
14.0%
로 12051
 
9.1%
지 10208
 
7.7%
동 7143
 
5.4%
시 7109
 
5.4%
서 6952
 
5.3%
울 6951
 
5.3%
별 6892
 
5.2%
번 6879
 
5.2%
특 6877
 
5.2%
Other values (194) 42464
32.2%
Common
ValueCountFrequency (%)
50948
53.3%
1 8774
 
9.2%
2 6520
 
6.8%
3 5164
 
5.4%
5 4014
 
4.2%
6 3445
 
3.6%
8 3019
 
3.2%
0 2969
 
3.1%
4 2830
 
3.0%
7 1979
 
2.1%
Other values (7) 6005
 
6.3%
Latin
ValueCountFrequency (%)
B 348
85.7%
A 20
 
4.9%
K 15
 
3.7%
C 8
 
2.0%
F 6
 
1.5%
N 4
 
1.0%
S 4
 
1.0%
E 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131979
57.9%
ASCII 96073
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50948
53.0%
1 8774
 
9.1%
2 6520
 
6.8%
3 5164
 
5.4%
5 4014
 
4.2%
6 3445
 
3.6%
8 3019
 
3.1%
0 2969
 
3.1%
4 2830
 
2.9%
7 1979
 
2.1%
Other values (15) 6411
 
6.7%
Hangul
ValueCountFrequency (%)
구 18453
14.0%
로 12051
 
9.1%
지 10208
 
7.7%
동 7143
 
5.4%
시 7109
 
5.4%
서 6952
 
5.3%
울 6951
 
5.3%
별 6892
 
5.2%
번 6879
 
5.2%
특 6877
 
5.2%
Other values (194) 42464
32.2%

업소전화번호
Text

MISSING 

Distinct381
Distinct (%)5.5%
Missing520
Missing (%)7.0%
Memory size58.5 KiB
2024-05-03T23:04:46.198050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.905262
Min length2

Characters and Unicode

Total characters75857
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

Unique163 ?
Unique (%)2.3%

Sample

1st row0226142263
2nd row02 9771015
3rd row02 9771015
4th row02 9771015
5th row02 9771015
ValueCountFrequency (%)
02 4322
35.0%
67151052 1358
 
11.0%
0220091210 537
 
4.3%
0226392500 481
 
3.9%
838 345
 
2.8%
0553 344
 
2.8%
26349142 301
 
2.4%
818 295
 
2.4%
1145 293
 
2.4%
26182080 190
 
1.5%
Other values (405) 3897
31.5%
2024-05-03T23:04:47.268502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15249
20.1%
0 14517
19.1%
8798
11.6%
1 8117
10.7%
6 6538
8.6%
5 5949
 
7.8%
8 4547
 
6.0%
3 3694
 
4.9%
7 3235
 
4.3%
9 2819
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67059
88.4%
Space Separator 8798
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15249
22.7%
0 14517
21.6%
1 8117
12.1%
6 6538
9.7%
5 5949
 
8.9%
8 4547
 
6.8%
3 3694
 
5.5%
7 3235
 
4.8%
9 2819
 
4.2%
4 2394
 
3.6%
Space Separator
ValueCountFrequency (%)
8798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75857
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15249
20.1%
0 14517
19.1%
8798
11.6%
1 8117
10.7%
6 6538
8.6%
5 5949
 
7.8%
8 4547
 
6.0%
3 3694
 
4.9%
7 3235
 
4.3%
9 2819
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75857
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15249
20.1%
0 14517
19.1%
8798
11.6%
1 8117
10.7%
6 6538
8.6%
5 5949
 
7.8%
8 4547
 
6.0%
3 3694
 
4.9%
7 3235
 
4.3%
9 2819
 
3.7%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
수거
3012 
<NA>
2268 
위생점검(전체)
1592 
위생점검(부분)
604 

Length

Max length8
Median length4
Mean length4.3691814
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수거 3012
40.3%
<NA> 2268
30.3%
위생점검(전체) 1592
21.3%
위생점검(부분) 604
 
8.1%

Length

2024-05-03T23:04:47.759900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:48.106023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 3012
40.3%
na 2268
30.3%
위생점검(전체 1592
21.3%
위생점검(부분 604
 
8.1%

점검일자
Real number (ℝ)

MISSING 

Distinct381
Distinct (%)5.4%
Missing457
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean20135829
Minimum20010910
Maximum20240307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:48.527057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010910
5-th percentile20080118
Q120100706
median20121228
Q320170530
95-th percentile20211006
Maximum20240307
Range229397
Interquartile range (IQR)69824.5

Descriptive statistics

Standard deviation43213.327
Coefficient of variation (CV)0.0021460913
Kurtosis-0.63846246
Mean20135829
Median Absolute Deviation (MAD)30903
Skewness0.45116598
Sum1.4133338 × 1011
Variance1.8673916 × 109
MonotonicityNot monotonic
2024-05-03T23:04:49.239733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091216 182
 
2.4%
20210902 148
 
2.0%
20100426 144
 
1.9%
20120709 105
 
1.4%
20101001 103
 
1.4%
20230911 97
 
1.3%
20100630 95
 
1.3%
20120906 82
 
1.1%
20071024 78
 
1.0%
20180807 72
 
1.0%
Other values (371) 5913
79.1%
(Missing) 457
 
6.1%
ValueCountFrequency (%)
20010910 2
 
< 0.1%
20010925 3
 
< 0.1%
20020718 1
 
< 0.1%
20020719 1
 
< 0.1%
20070213 26
0.3%
20070710 1
 
< 0.1%
20070719 1
 
< 0.1%
20070723 8
 
0.1%
20070731 2
 
< 0.1%
20070809 3
 
< 0.1%
ValueCountFrequency (%)
20240307 1
 
< 0.1%
20240227 3
 
< 0.1%
20240226 28
0.4%
20240118 2
 
< 0.1%
20240117 17
0.2%
20240111 6
 
0.1%
20231129 31
0.4%
20231114 1
 
< 0.1%
20231026 2
 
< 0.1%
20231017 1
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
기타
2770 
<NA>
2239 
수시
1846 
합동
513 
일제
 
108

Length

Max length4
Median length2
Mean length2.5989834
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2770
37.1%
<NA> 2239
29.9%
수시 1846
24.7%
합동 513
 
6.9%
일제 108
 
1.4%

Length

2024-05-03T23:04:49.698534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:50.068512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2770
37.1%
na 2239
29.9%
수시 1846
24.7%
합동 513
 
6.9%
일제 108
 
1.4%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

점검결과코드
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.5 KiB
1
4979 
<NA>
2277 
2
 
220

Length

Max length4
Median length1
Mean length1.9137239
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4979
66.6%
<NA> 2277
30.5%
2 220
 
2.9%

Length

2024-05-03T23:04:50.499055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:04:50.851870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4979
66.6%
na 2277
30.5%
2 220
 
2.9%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct127
Distinct (%)76.0%
Missing7309
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean20121269
Minimum20111014
Maximum20141023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.8 KiB
2024-05-03T23:04:51.245685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20111014
5-th percentile20111028
Q120111128
median20120411
Q320121216
95-th percentile20140912
Maximum20141023
Range30009
Interquartile range (IQR)10088

Descriptive statistics

Standard deviation9575.5367
Coefficient of variation (CV)0.0004758913
Kurtosis-0.24560355
Mean20121269
Median Absolute Deviation (MAD)9283
Skewness0.81175725
Sum3.3602519 × 109
Variance91690903
MonotonicityNot monotonic
2024-05-03T23:04:51.718915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111123 4
 
0.1%
20111121 4
 
0.1%
20111119 3
 
< 0.1%
20111029 3
 
< 0.1%
20130405 3
 
< 0.1%
20111203 3
 
< 0.1%
20111114 3
 
< 0.1%
20120411 3
 
< 0.1%
20120828 2
 
< 0.1%
20130305 2
 
< 0.1%
Other values (117) 137
 
1.8%
(Missing) 7309
97.8%
ValueCountFrequency (%)
20111014 1
 
< 0.1%
20111016 1
 
< 0.1%
20111024 2
< 0.1%
20111025 2
< 0.1%
20111027 2
< 0.1%
20111028 2
< 0.1%
20111029 3
< 0.1%
20111031 2
< 0.1%
20111107 1
 
< 0.1%
20111113 1
 
< 0.1%
ValueCountFrequency (%)
20141023 1
< 0.1%
20141016 1
< 0.1%
20141006 1
< 0.1%
20141004 2
< 0.1%
20141003 1
< 0.1%
20140923 1
< 0.1%
20140920 1
< 0.1%
20140914 1
< 0.1%
20140908 2
< 0.1%
20140907 1
< 0.1%

(구)제조회사주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7476
Missing (%)100.0%
Memory size65.8 KiB

부적합항목
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing7468
Missing (%)99.9%
Memory size58.5 KiB
2024-05-03T23:04:52.161134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length4.625
Min length2

Characters and Unicode

Total characters37
Distinct characters24
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)50.0%

Sample

1st row대장균
2nd row식중독균 검출
3rd row대장균
4th row대장균
5th row대장균
ValueCountFrequency (%)
대장균 4
36.4%
식중독균 1
 
9.1%
검출 1
 
9.1%
일반세균수 1
 
9.1%
기준치 1
 
9.1%
초과 1
 
9.1%
산가 1
 
9.1%
n-헵탄 1
 
9.1%
2024-05-03T23:04:52.918673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
균 6
16.2%
대 4
 
10.8%
장 4
 
10.8%
3
 
8.1%
준 1
 
2.7%
헵 1
 
2.7%
- 1
 
2.7%
n 1
 
2.7%
가 1
 
2.7%
산 1
 
2.7%
Other values (14) 14
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
86.5%
Space Separator 3
 
8.1%
Dash Punctuation 1
 
2.7%
Lowercase Letter 1
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
균 6
18.8%
대 4
 
12.5%
장 4
 
12.5%
준 1
 
3.1%
헵 1
 
3.1%
가 1
 
3.1%
산 1
 
3.1%
과 1
 
3.1%
초 1
 
3.1%
치 1
 
3.1%
Other values (11) 11
34.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
86.5%
Common 4
 
10.8%
Latin 1
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
균 6
18.8%
대 4
 
12.5%
장 4
 
12.5%
준 1
 
3.1%
헵 1
 
3.1%
가 1
 
3.1%
산 1
 
3.1%
과 1
 
3.1%
초 1
 
3.1%
치 1
 
3.1%
Other values (11) 11
34.4%
Common
ValueCountFrequency (%)
3
75.0%
- 1
 
25.0%
Latin
ValueCountFrequency (%)
n 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32
86.5%
ASCII 5
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
균 6
18.8%
대 4
 
12.5%
장 4
 
12.5%
준 1
 
3.1%
헵 1
 
3.1%
가 1
 
3.1%
산 1
 
3.1%
과 1
 
3.1%
초 1
 
3.1%
치 1
 
3.1%
Other values (11) 11
34.4%
ASCII
ValueCountFrequency (%)
3
60.0%
- 1
 
20.0%
n 1
 
20.0%

기준치부적합내용
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing7469
Missing (%)99.9%
Memory size58.5 KiB
2024-05-03T23:04:53.208391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length8
Min length2

Characters and Unicode

Total characters56
Distinct characters35
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

Unique5 ?
Unique (%)71.4%

Sample

1st row대장균 양성
2nd row황색포도상구균 기준위반
3rd row양성
4th row대장균 양성
5th row세균수 180000
ValueCountFrequency (%)
양성 3
25.0%
대장균 2
16.7%
황색포도상구균 1
 
8.3%
기준위반 1
 
8.3%
세균수 1
 
8.3%
180000 1
 
8.3%
산가:14.3(규격 1
 
8.3%
2.0이하 1
 
8.3%
307 1
 
8.3%
2024-05-03T23:04:53.980642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
 
10.7%
5
 
8.9%
균 4
 
7.1%
양 3
 
5.4%
성 3
 
5.4%
3 2
 
3.6%
1 2
 
3.6%
장 2
 
3.6%
. 2
 
3.6%
대 2
 
3.6%
Other values (25) 25
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
57.1%
Decimal Number 14
25.0%
Space Separator 5
 
8.9%
Other Punctuation 3
 
5.4%
Open Punctuation 1
 
1.8%
Close Punctuation 1
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
균 4
 
12.5%
양 3
 
9.4%
성 3
 
9.4%
장 2
 
6.2%
대 2
 
6.2%
산 1
 
3.1%
규 1
 
3.1%
이 1
 
3.1%
하 1
 
3.1%
가 1
 
3.1%
Other values (13) 13
40.6%
Decimal Number
ValueCountFrequency (%)
0 6
42.9%
3 2
 
14.3%
1 2
 
14.3%
2 1
 
7.1%
4 1
 
7.1%
8 1
 
7.1%
7 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
57.1%
Common 24
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
균 4
 
12.5%
양 3
 
9.4%
성 3
 
9.4%
장 2
 
6.2%
대 2
 
6.2%
산 1
 
3.1%
규 1
 
3.1%
이 1
 
3.1%
하 1
 
3.1%
가 1
 
3.1%
Other values (13) 13
40.6%
Common
ValueCountFrequency (%)
0 6
25.0%
5
20.8%
3 2
 
8.3%
1 2
 
8.3%
. 2
 
8.3%
( 1
 
4.2%
2 1
 
4.2%
4 1
 
4.2%
: 1
 
4.2%
) 1
 
4.2%
Other values (2) 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32
57.1%
ASCII 24
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
25.0%
5
20.8%
3 2
 
8.3%
1 2
 
8.3%
. 2
 
8.3%
( 1
 
4.2%
2 1
 
4.2%
4 1
 
4.2%
: 1
 
4.2%
) 1
 
4.2%
Other values (2) 2
 
8.3%
Hangul
ValueCountFrequency (%)
균 4
 
12.5%
양 3
 
9.4%
성 3
 
9.4%
장 2
 
6.2%
대 2
 
6.2%
산 1
 
3.1%
규 1
 
3.1%
이 1
 
3.1%
하 1
 
3.1%
가 1
 
3.1%
Other values (13) 13
40.6%

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
03160000101일반음식점2<NA>수시 위생점검<NA>117-06-06검사용평양면옥818000000음료류추출음료냉면육수냉면육수냉면육수평양면옥201206051.0냉면육수LT<NA>20120605<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>19790080033<NA><NA><NA><NA><NA><NA>서울특별시 구로구 오류동 13번지 55호0226142263위생점검(전체)20120605수시<NA>2<NA><NA><NA><NA>
13160000101일반음식점2<NA>2013년 위생지도 및 원산지 지도서비스 실시<NA>2013-1검사용육영토종정육전문점121000000식육류중육류소고기양지<NA><NA><NA>201307011.0100g<NA>20130701<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20130701수시<NA>1<NA><NA><NA><NA>
23160000101일반음식점2<NA>2013년 위생지도 및 원산지 지도서비스 실시<NA>2013-2검사용육영토종정육전문점121000000식육류중육류소고기치마살<NA><NA><NA>201307011.0100g<NA>20130701<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20130701수시<NA>1<NA><NA><NA><NA>
33160000101일반음식점2<NA>2013년 위생지도 및 원산지 지도서비스 실시<NA>2013-3검사용육영토종정육전문점121000000식육류중육류소고기치마살<NA><NA><NA>201307011.0100g<NA>20130701<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20130701수시<NA>1<NA><NA><NA><NA>
43160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-31검사용육영토종정육전문점121000000식육류중육류소고기갈비<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<NA>1<NA><NA><NA><NA>
53160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-32검사용육영토종정육전문점121000000식육류중육류소고기등심<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<NA>1<NA><NA><NA><NA>
63160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-33검사용육영토종정육전문점121000000식육류중육류소고기설도<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<NA>1<NA><NA><NA><NA>
73160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-34검사용육영토종정육전문점121000000식육류중육류소고기양지<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<NA>1<NA><NA><NA><NA>
83160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-35검사용육영토종정육전문점121000000식육류중육류소고기차돌박이<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<NA>1<NA><NA><NA><NA>
93160000101일반음식점999<NA>2012 원산지표시 지도점검<NA>2012-60검사용육영토종정육전문점121000000식육류중육류소고기부채살<NA><NA><NA>201211281.0100g<NA>20121128<NA><NA><NA>냉동<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19820080132<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 600번지 6호02 9771015위생점검(전체)20121128수시<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
74663160000134건강기능식품일반판매업<NA><NA><NA><NA>117-4-10검사용(주)우리레인보우<NA>칼슘샤크 카트리지 칼슘<NA><NA><NA>201604203.090g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외호주120160420201606281<NA><NA><NA><NA><NA><NA>20150080584<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, (신도림동, 디큐브시티 지하2층)서울특별시 구로구 신도림동 692번지 디큐브시티 지하2층<NA><NA>20160504<NA><NA><NA><NA><NA><NA><NA>
74673160000134건강기능식품일반판매업<NA><NA><NA><NA>117-4-11검사용(주)우리레인보우E0101400000000비타민 C비타민 C레인보우 비타민C<NA><NA><NA>201604202.0120g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120160420201606281<NA><NA><NA><NA><NA><NA>20150080584<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, (신도림동, 디큐브시티 지하2층)서울특별시 구로구 신도림동 692번지 디큐브시티 지하2층<NA><NA>20160504<NA><NA><NA><NA><NA><NA><NA>
74683160000134건강기능식품일반판매업<NA><NA><NA><NA>117-4-12검사용동국제약(주) 네이처스비타민샵<NA>칼슘애니멀킹덤 갈슘마그네슘&amp;비타민D<NA><NA><NA>201604202.0105g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외캐나다120160420201606281<NA><NA><NA><NA><NA><NA>20150080591<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, (신도림동, 디큐브시티 지하2층)서울특별시 구로구 신도림동 692번지 디큐브시티 지하2층02 21919936<NA>20160504<NA><NA><NA><NA><NA><NA><NA>
74693160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-6검사용솔가비타민E0205100000000프로바이오틱스프로바이오틱스솔가멀티빌리언도필루스프로바이오틱스<NA><NA><NA>202109026.036g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외미국120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74703160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-7검사용솔가비타민E0202400000000공액리놀레산공액리놀레산다이어트엔 린바디<NA><NA><NA>202109022.0120g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74713160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-8검사용솔가비타민E0201400000000밀크씨슬(카르두스 마리아누스) 추출물밀크씨슬(카르두스 마리아누스) 추출물간 건강엔 밀크씨슬<NA><NA><NA>202109025.042g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74723160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-9검사용솔가비타민X0100026500000에이코사펜타엔산(EPA)및/또는도코사헥사엔산(DHA)함유제품에이코사펜타엔산(EPA)및/또는도코사헥사엔산(DHA)함유제품솔가오메가-3 700<NA><NA><NA>202109023.075g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국외미국120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74733160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-10검사용솔가비타민E0205700000000EPA 및 DHA 함유 유지EPA 및 DHA 함유 유지알티지 오메가3 1200<NA><NA><NA>202109025.048g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74743160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-11검사용솔가비타민E0307800000000락추로스 파우더(Lactulose Powder)(제2009-40호)락추로스 파우더(Lactulose Powder)(제2009-40호)장 건강엔 신바이오틱스<NA><NA><NA>202109024.060g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<NA>1<NA><NA><NA><NA>
74753160000134건강기능식품일반판매업<NA><NA><NA><NA>구로-건기-12검사용솔가비타민E0207000000000마리골드꽃추출물마리골드꽃추출물눈 건강엔 루테인 오메가3<NA><NA><NA>202109026.042g<NA><NA><NA><NA><NA>실온<NA><NA>001<NA>국내<NA>120210906<NA><NA><NA><NA><NA><NA><NA><NA>20210081024<NA><NA><NA><NA><NA>서울특별시 구로구 경인로 662, 지하2층 (신도림동, 디큐브시티)서울특별시 구로구 신도림동 692번지 디큐브시티02 26222233수거20210902수시<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)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과수거품처리교부번호폐기일자폐기량(Kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한부적합항목기준치부적합내용# duplicates
33160000105집단급식소<NA><NA><NA>117-6-6<NA>서서울생활과학고등학교<NA><NA>급식면봉급식면봉<NA><NA>201006281.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>001서서울과학고국내<NA>220100628<NA><NA><NA><NA>19990081420<NA><NA><NA><NA><NA><NA>서울특별시 구로구 궁동 35번지 0호0226115669위생점검(전체)20100628수시1<NA><NA><NA>14
233160000114기타식품판매업<NA><NA><NA><NA><NA>이마트신도림점214000000조미식품복합조미식품웰빙다시다 산들애 국내산 한우<NA><NA><NA>200912161.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>20070080812<NA><NA><NA><NA><NA>서울특별시 구로구 새말로 97, (구로동,이마트신도림점 지하2층)서울특별시 구로구 구로동 3번지 25호 이마트신도림점 지하2층02 67151052수거20091216기타1<NA><NA><NA>4
113160000114기타식품판매업<NA><NA><NA><NA><NA>구일쇼핑센터410000000기구류기구류중나무제나무젓가락<NA><NA><NA>200804163.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>19980080580<NA><NA><NA><NA><NA>서울특별시 구로구 구일로4길 33, (구로동,지하1층)서울특별시 구로구 구로동 685번지 215호 지하1층02 8672717수거20080416기타1<NA><NA><NA>3
253160000114기타식품판매업<NA><NA><NA><NA><NA>이마트신도림점219000000건포류조미건어포류맛진미오징어<NA><NA><NA>200912161.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>20070080812<NA><NA><NA><NA><NA>서울특별시 구로구 새말로 97, (구로동,이마트신도림점 지하2층)서울특별시 구로구 구로동 3번지 25호 이마트신도림점 지하2층02 67151052수거20091216기타1<NA><NA><NA>3
03160000101일반음식점<NA><NA><NA>6-2-9<NA>원조숯불 암소마을121000000식육류중육류<NA>한우등심<NA><NA><NA>20100615100.0g<NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국내<NA>120100615<NA><NA><NA><NA>20050080233<NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 184번지 1호 우림이비지센타 2차 104호<NA>수거20100615수시1<NA><NA><NA>2
13160000105집단급식소<NA><NA>2014 조리식품수거검사117-07-18검사용구로경찰서G01000000<NA>조리식품 등보존식(7.18 점심)<NA><NA><NA>201407231.0600g<NA>20140723<NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA>20010080656<NA><NA><NA><NA><NA>서울특별시 구로구 가마산로 235, (구로동)<NA>02 8623520<NA>20140723<NA><NA><NA><NA><NA>2
23160000105집단급식소<NA><NA><NA>117-6-6<NA>서서울생활과학고등학교<NA><NA>급식도마급식도마(2층실습실)<NA><NA>201006281.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>001서서울과학고국내<NA>220100628<NA><NA><NA><NA>19990081420<NA><NA><NA><NA><NA><NA>서울특별시 구로구 궁동 35번지 0호0226115669위생점검(전체)20100628수시1<NA><NA><NA>2
43160000105집단급식소<NA><NA><NA>117-6-6<NA>서서울생활과학고등학교<NA><NA>급식칼급식칼<NA><NA>201006281.0개<NA><NA><NA><NA><NA><NA><NA><NA><NA>001서서울과학고국내<NA>220100628<NA><NA><NA><NA>19990081420<NA><NA><NA><NA><NA><NA>서울특별시 구로구 궁동 35번지 0호0226115669위생점검(전체)20100628수시1<NA><NA><NA>2
53160000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계이마트구로점201000000과자류초콜릿가공품투유<NA><NA><NA>200902103.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA><NA><NA><NA>19990081058<NA><NA><NA><NA><NA>서울특별시 구로구 디지털로32길 43, (구로동)서울특별시 구로구 구로동 188번지 26호0220091210위생점검(부분)20090210합동1<NA><NA><NA>2
63160000114기타식품판매업<NA><NA><NA><NA><NA>(주)신세계이마트구로점209000000면류개량숙면류본고장유부생우동<NA><NA><NA>200712043.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>001<NA>국외<NA><NA><NA><NA>1<NA><NA>19990081058<NA><NA><NA><NA><NA>서울특별시 구로구 디지털로32길 43, (구로동)서울특별시 구로구 구로동 188번지 26호0220091210<NA>20071204<NA><NA><NA><NA><NA>2