Overview

Dataset statistics

Number of variables61
Number of observations4477
Missing cells107317
Missing cells (%)39.3%
Duplicate rows8
Duplicate rows (%)0.2%
Total size in memory2.2 MiB
Average record size in memory522.0 B

Variable types

Categorical22
Numeric8
Unsupported17
Text14

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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11455/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
Dataset has 8 (0.2%) duplicate rowsDuplicates
수거계획 is highly imbalanced (71.5%)Imbalance
수거사유코드 is highly imbalanced (57.5%)Imbalance
수거량(자유) is highly imbalanced (90.9%)Imbalance
제조일자(롯트) is highly imbalanced (99.6%)Imbalance
유통기한(제조일기준) is highly imbalanced (99.1%)Imbalance
바코드번호 is highly imbalanced (99.7%)Imbalance
어린이기호식품유형 is highly imbalanced (96.5%)Imbalance
국가명 is highly imbalanced (89.5%)Imbalance
판정구분 is highly imbalanced (55.9%)Imbalance
처리결과 is highly imbalanced (99.2%)Imbalance
계획구분명 has 4477 (100.0%) missing valuesMissing
수거증번호 has 861 (19.2%) missing valuesMissing
식품군 has 485 (10.8%) missing valuesMissing
품목명 has 108 (2.4%) missing valuesMissing
음식물명 has 4451 (99.4%) missing valuesMissing
원료명 has 4470 (99.8%) missing valuesMissing
생산업소 has 2937 (65.6%) missing valuesMissing
수거량(정량) has 247 (5.5%) missing valuesMissing
제품규격(정량) has 1101 (24.6%) missing valuesMissing
제조일자(일자) has 3333 (74.4%) missing valuesMissing
유통기한(일자) has 4477 (100.0%) missing valuesMissing
(구)제조사명 has 4379 (97.8%) missing valuesMissing
검사의뢰일자 has 3847 (85.9%) missing valuesMissing
결과회보일자 has 4043 (90.3%) missing valuesMissing
처리구분 has 4477 (100.0%) missing valuesMissing
수거검사구분코드 has 4477 (100.0%) missing valuesMissing
단속지역구분코드 has 4477 (100.0%) missing valuesMissing
수거장소구분코드 has 4477 (100.0%) missing valuesMissing
수거품처리 has 4477 (100.0%) missing valuesMissing
폐기일자 has 4477 (100.0%) missing valuesMissing
폐기량(kg) has 4477 (100.0%) missing valuesMissing
폐기금액(원) has 4477 (100.0%) missing valuesMissing
폐기장소 has 4477 (100.0%) missing valuesMissing
폐기방법 has 4477 (100.0%) missing valuesMissing
소재지(도로명) has 390 (8.7%) missing valuesMissing
업소전화번호 has 513 (11.5%) missing valuesMissing
점검내용 has 4477 (100.0%) missing valuesMissing
(구)제조유통기한 has 4477 (100.0%) missing valuesMissing
(구)제조회사주소 has 4477 (100.0%) missing valuesMissing
부적합항목 has 4477 (100.0%) missing valuesMissing
기준치부적합내용 has 4477 (100.0%) missing valuesMissing
수거일자 is highly skewed (γ1 = -58.06064689)Skewed
수거량(정량) is highly skewed (γ1 = 61.82692639)Skewed
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
유통기한(일자) is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조유통기한 is an unsupported type, check if it needs cleaning or further analysisUnsupported
(구)제조회사주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부적합항목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-04 02:49:06.030590
Analysis finished2024-05-04 02:49:11.467836
Duration5.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
3230000
4477 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 4477
100.0%

Length

2024-05-04T02:49:11.783443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:12.192021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 4477
100.0%

업종코드
Real number (ℝ)

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.31874
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:12.667170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation5.7470542
Coefficient of variation (CV)0.051627015
Kurtosis3.022187
Mean111.31874
Median Absolute Deviation (MAD)0
Skewness0.49355496
Sum498374
Variance33.028632
MonotonicityNot monotonic
2024-05-04T02:49:13.168368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
114 2893
64.6%
105 476
 
10.6%
101 418
 
9.3%
107 185
 
4.1%
106 167
 
3.7%
104 141
 
3.1%
134 86
 
1.9%
113 40
 
0.9%
109 25
 
0.6%
122 24
 
0.5%
Other values (3) 22
 
0.5%
ValueCountFrequency (%)
101 418
 
9.3%
104 141
 
3.1%
105 476
 
10.6%
106 167
 
3.7%
107 185
 
4.1%
109 25
 
0.6%
110 1
 
< 0.1%
112 15
 
0.3%
113 40
 
0.9%
114 2893
64.6%
ValueCountFrequency (%)
134 86
 
1.9%
122 24
 
0.5%
121 6
 
0.1%
114 2893
64.6%
113 40
 
0.9%
112 15
 
0.3%
110 1
 
< 0.1%
109 25
 
0.6%
107 185
 
4.1%
106 167
 
3.7%

업종명
Categorical

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
기타식품판매업
2893 
집단급식소
476 
일반음식점
418 
즉석판매제조가공업
 
185
식품제조가공업
 
167
Other values (8)
338 

Length

Max length11
Median length7
Mean length6.7064999
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 2893
64.6%
집단급식소 476
 
10.6%
일반음식점 418
 
9.3%
즉석판매제조가공업 185
 
4.1%
식품제조가공업 167
 
3.7%
휴게음식점 141
 
3.1%
건강기능식품일반판매업 86
 
1.9%
유통전문판매업 40
 
0.9%
식품소분업 25
 
0.6%
집단급식소식품판매업 24
 
0.5%
Other values (3) 22
 
0.5%

Length

2024-05-04T02:49:13.912819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 2893
64.6%
집단급식소 476
 
10.6%
일반음식점 418
 
9.3%
즉석판매제조가공업 185
 
4.1%
식품제조가공업 167
 
3.7%
휴게음식점 141
 
3.1%
건강기능식품일반판매업 86
 
1.9%
유통전문판매업 40
 
0.9%
식품소분업 25
 
0.6%
집단급식소식품판매업 24
 
0.5%
Other values (4) 23
 
0.5%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
999
2131 
<NA>
2080 
2
240 
3
 
18
7
 
8

Length

Max length4
Median length3
Mean length3.3457673
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 (%)
999 2131
47.6%
<NA> 2080
46.5%
2 240
 
5.4%
3 18
 
0.4%
7 8
 
0.2%

Length

2024-05-04T02:49:14.577215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:15.141713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999 2131
47.6%
na 2080
46.5%
2 240
 
5.4%
3 18
 
0.4%
7 8
 
0.2%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB
Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
2080 
2013 식품안전관리업무 추진계획
663 
2012년 유통식품 수거검사
365 
2015년도 식품수거검사 계획
338 
일상 수거검사
293 
Other values (26)
738 

Length

Max length28
Median length26
Mean length9.794952
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> 2080
46.5%
2013 식품안전관리업무 추진계획 663
 
14.8%
2012년 유통식품 수거검사 365
 
8.2%
2015년도 식품수거검사 계획 338
 
7.5%
일상 수거검사 293
 
6.5%
집단급식소 등 지도점검 149
 
3.3%
식품(소분)판매업 등 지도점검 110
 
2.5%
기타식품판매업소 일제점검 69
 
1.5%
식품수거검사 56
 
1.3%
식중독 의심 민원 신고 위생점검 52
 
1.2%
Other values (21) 302
 
6.7%

Length

2024-05-04T02:49:15.563081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2080
23.0%
추진계획 663
 
7.3%
2013 663
 
7.3%
식품안전관리업무 663
 
7.3%
수거검사 658
 
7.3%
지도점검 475
 
5.3%
식품수거검사 394
 
4.4%
계획 391
 
4.3%
유통식품 365
 
4.0%
2012년 365
 
4.0%
Other values (55) 2312
25.6%

수거계획
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3772 
2019 유통식품 수거검사 계획
 
231
2018년 유통가공식품 수거계획
 
164
조리식품 수거검사
 
144
유통식품 안전성 검사
 
126
Other values (6)
 
40

Length

Max length22
Median length4
Mean length5.6397141
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> 3772
84.3%
2019 유통식품 수거검사 계획 231
 
5.2%
2018년 유통가공식품 수거계획 164
 
3.7%
조리식품 수거검사 144
 
3.2%
유통식품 안전성 검사 126
 
2.8%
식음료 전문판매(프랜차이즈)업소 수거검사 19
 
0.4%
프랜차이즈 원료 제조가공업체 수거계획 10
 
0.2%
2020년 유통가공식품수거 6
 
0.1%
식품접객업소 수거관리 2
 
< 0.1%
집중관리업체 지도점검 계획 2
 
< 0.1%

Length

2024-05-04T02:49:16.143060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3772
63.1%
수거검사 394
 
6.6%
유통식품 357
 
6.0%
계획 233
 
3.9%
2019 231
 
3.9%
수거계획 174
 
2.9%
2018년 164
 
2.7%
유통가공식품 164
 
2.7%
조리식품 144
 
2.4%
안전성 126
 
2.1%
Other values (13) 215
 
3.6%

수거증번호
Text

MISSING 

Distinct3041
Distinct (%)84.1%
Missing861
Missing (%)19.2%
Memory size35.1 KiB
2024-05-04T02:49:16.920957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.3962942
Min length1

Characters and Unicode

Total characters30361
Distinct characters58
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

Unique2567 ?
Unique (%)71.0%

Sample

1st row124-3-14-1
2nd row124-3-14-2
3rd row124-3-14-3
4th row124-3-8
5th row124-03-04-02
ValueCountFrequency (%)
송파 64
 
1.7%
124-5-환경검체 17
 
0.5%
124 12
 
0.3%
124-4-27-1 11
 
0.3%
124-10-15 10
 
0.3%
124-4-27-2 10
 
0.3%
2017-6-22 9
 
0.2%
124-10-10 7
 
0.2%
124-11-30 7
 
0.2%
124-10-16 6
 
0.2%
Other values (3001) 3547
95.9%
2024-05-04T02:49:18.443184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6544
21.6%
1 6467
21.3%
2 5073
16.7%
4 3876
12.8%
0 1383
 
4.6%
3 1229
 
4.0%
6 1166
 
3.8%
5 1027
 
3.4%
9 919
 
3.0%
8 919
 
3.0%
Other values (48) 1758
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22887
75.4%
Dash Punctuation 6544
 
21.6%
Other Letter 586
 
1.9%
Uppercase Letter 125
 
0.4%
Space Separator 93
 
0.3%
Lowercase Letter 56
 
0.2%
Math Symbol 37
 
0.1%
Other Punctuation 33
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
103
17.6%
103
17.6%
62
10.6%
62
10.6%
43
7.3%
38
 
6.5%
38
 
6.5%
19
 
3.2%
15
 
2.6%
14
 
2.4%
Other values (22) 89
15.2%
Decimal Number
ValueCountFrequency (%)
1 6467
28.3%
2 5073
22.2%
4 3876
16.9%
0 1383
 
6.0%
3 1229
 
5.4%
6 1166
 
5.1%
5 1027
 
4.5%
9 919
 
4.0%
8 919
 
4.0%
7 828
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
a 22
39.3%
b 21
37.5%
c 8
 
14.3%
d 3
 
5.4%
f 1
 
1.8%
e 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 30
90.9%
, 1
 
3.0%
* 1
 
3.0%
1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
A 54
43.2%
B 47
37.6%
C 24
19.2%
Dash Punctuation
ValueCountFrequency (%)
- 6544
100.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Math Symbol
ValueCountFrequency (%)
~ 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29594
97.5%
Hangul 586
 
1.9%
Latin 181
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
103
17.6%
103
17.6%
62
10.6%
62
10.6%
43
7.3%
38
 
6.5%
38
 
6.5%
19
 
3.2%
15
 
2.6%
14
 
2.4%
Other values (22) 89
15.2%
Common
ValueCountFrequency (%)
- 6544
22.1%
1 6467
21.9%
2 5073
17.1%
4 3876
13.1%
0 1383
 
4.7%
3 1229
 
4.2%
6 1166
 
3.9%
5 1027
 
3.5%
9 919
 
3.1%
8 919
 
3.1%
Other values (7) 991
 
3.3%
Latin
ValueCountFrequency (%)
A 54
29.8%
B 47
26.0%
C 24
13.3%
a 22
12.2%
b 21
 
11.6%
c 8
 
4.4%
d 3
 
1.7%
f 1
 
0.6%
e 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29774
98.1%
Hangul 586
 
1.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6544
22.0%
1 6467
21.7%
2 5073
17.0%
4 3876
13.0%
0 1383
 
4.6%
3 1229
 
4.1%
6 1166
 
3.9%
5 1027
 
3.4%
9 919
 
3.1%
8 919
 
3.1%
Other values (15) 1171
 
3.9%
Hangul
ValueCountFrequency (%)
103
17.6%
103
17.6%
62
10.6%
62
10.6%
43
7.3%
38
 
6.5%
38
 
6.5%
19
 
3.2%
15
 
2.6%
14
 
2.4%
Other values (22) 89
15.2%
None
ValueCountFrequency (%)
1
100.0%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
검사용
3342 
<NA>
976 
기타
 
140
압류
 
15
증거용
 
4

Length

Max length4
Median length3
Mean length3.1833817
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 3342
74.6%
<NA> 976
 
21.8%
기타 140
 
3.1%
압류 15
 
0.3%
증거용 4
 
0.1%

Length

2024-05-04T02:49:18.902616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:19.354205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 3342
74.6%
na 976
 
21.8%
기타 140
 
3.1%
압류 15
 
0.3%
증거용 4
 
0.1%
Distinct396
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2024-05-04T02:49:20.003448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length8.4829127
Min length2

Characters and Unicode

Total characters37978
Distinct characters419
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

Unique181 ?
Unique (%)4.0%

Sample

1st row서울잠신초등학교
2nd row서울잠신초등학교
3rd row서울잠신초등학교
4th row나정식품
5th row대중음악박물관 카페
ValueCountFrequency (%)
잠실점 942
 
15.4%
롯데마트 928
 
15.2%
다농산업(주 595
 
9.7%
롯데마트월드점 205
 
3.3%
홈플러스(주 200
 
3.3%
롯데쇼핑(주 175
 
2.9%
이마트가든5점식품매장 151
 
2.5%
롯데쇼핑(주)롯데마트 141
 
2.3%
서울체육중,고등학교 109
 
1.8%
삼성테스코(주)홈플러스잠실점 109
 
1.8%
Other values (471) 2566
41.9%
2024-05-04T02:49:21.153633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2005
 
5.3%
) 1857
 
4.9%
( 1856
 
4.9%
1817
 
4.8%
1816
 
4.8%
1807
 
4.8%
1803
 
4.7%
1777
 
4.7%
1644
 
4.3%
1221
 
3.2%
Other values (409) 20375
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32110
84.5%
Close Punctuation 1857
 
4.9%
Open Punctuation 1856
 
4.9%
Space Separator 1644
 
4.3%
Decimal Number 193
 
0.5%
Uppercase Letter 143
 
0.4%
Other Punctuation 120
 
0.3%
Lowercase Letter 54
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2005
 
6.2%
1817
 
5.7%
1816
 
5.7%
1807
 
5.6%
1803
 
5.6%
1777
 
5.5%
1221
 
3.8%
1217
 
3.8%
726
 
2.3%
665
 
2.1%
Other values (368) 17256
53.7%
Uppercase Letter
ValueCountFrequency (%)
G 52
36.4%
S 36
25.2%
C 13
 
9.1%
N 11
 
7.7%
T 5
 
3.5%
P 5
 
3.5%
E 3
 
2.1%
D 3
 
2.1%
A 3
 
2.1%
L 2
 
1.4%
Other values (7) 10
 
7.0%
Lowercase Letter
ValueCountFrequency (%)
e 12
22.2%
r 11
20.4%
t 10
18.5%
a 6
11.1%
o 6
11.1%
u 6
11.1%
s 1
 
1.9%
h 1
 
1.9%
w 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
5 153
79.3%
2 20
 
10.4%
1 12
 
6.2%
0 3
 
1.6%
4 3
 
1.6%
8 1
 
0.5%
3 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 110
91.7%
/ 6
 
5.0%
: 3
 
2.5%
& 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 1857
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1856
100.0%
Space Separator
ValueCountFrequency (%)
1644
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32100
84.5%
Common 5671
 
14.9%
Latin 197
 
0.5%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2005
 
6.2%
1817
 
5.7%
1816
 
5.7%
1807
 
5.6%
1803
 
5.6%
1777
 
5.5%
1221
 
3.8%
1217
 
3.8%
726
 
2.3%
665
 
2.1%
Other values (366) 17246
53.7%
Latin
ValueCountFrequency (%)
G 52
26.4%
S 36
18.3%
C 13
 
6.6%
e 12
 
6.1%
r 11
 
5.6%
N 11
 
5.6%
t 10
 
5.1%
a 6
 
3.0%
o 6
 
3.0%
u 6
 
3.0%
Other values (16) 34
17.3%
Common
ValueCountFrequency (%)
) 1857
32.7%
( 1856
32.7%
1644
29.0%
5 153
 
2.7%
, 110
 
1.9%
2 20
 
0.4%
1 12
 
0.2%
/ 6
 
0.1%
0 3
 
0.1%
4 3
 
0.1%
Other values (5) 7
 
0.1%
Han
ValueCountFrequency (%)
9
90.0%
1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32100
84.5%
ASCII 5868
 
15.5%
CJK 10
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2005
 
6.2%
1817
 
5.7%
1816
 
5.7%
1807
 
5.6%
1803
 
5.6%
1777
 
5.5%
1221
 
3.8%
1217
 
3.8%
726
 
2.3%
665
 
2.1%
Other values (366) 17246
53.7%
ASCII
ValueCountFrequency (%)
) 1857
31.6%
( 1856
31.6%
1644
28.0%
5 153
 
2.6%
, 110
 
1.9%
G 52
 
0.9%
S 36
 
0.6%
2 20
 
0.3%
C 13
 
0.2%
e 12
 
0.2%
Other values (31) 115
 
2.0%
CJK
ValueCountFrequency (%)
9
90.0%
1
 
10.0%
Distinct302
Distinct (%)6.8%
Missing40
Missing (%)0.9%
Memory size35.1 KiB
2024-05-04T02:49:21.742635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.96732
Min length1

Characters and Unicode

Total characters48662
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

Unique90 ?
Unique (%)2.0%

Sample

1st rowG0300000300000
2nd rowG0300000300000
3rd rowG0100000100000
4th rowC0322020100000
5th rowG0200000200000
ValueCountFrequency (%)
g0100000100000 367
 
8.5%
c01000000 286
 
6.6%
802000000 201
 
4.7%
821000000 168
 
3.9%
g0300000300000 147
 
3.4%
801000000 130
 
3.0%
214000000 120
 
2.8%
818000000 112
 
2.6%
820000000 111
 
2.6%
x0100027900000 94
 
2.2%
Other values (290) 2571
59.7%
2024-05-04T02:49:23.016815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34397
70.7%
1 4387
 
9.0%
2 2373
 
4.9%
8 1962
 
4.0%
C 1336
 
2.7%
3 1033
 
2.1%
G 643
 
1.3%
9 534
 
1.1%
4 514
 
1.1%
354
 
0.7%
Other values (10) 1129
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46056
94.6%
Uppercase Letter 2252
 
4.6%
Space Separator 354
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34397
74.7%
1 4387
 
9.5%
2 2373
 
5.2%
8 1962
 
4.3%
3 1033
 
2.2%
9 534
 
1.2%
4 514
 
1.1%
5 310
 
0.7%
7 275
 
0.6%
6 271
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 1336
59.3%
G 643
28.6%
X 105
 
4.7%
E 66
 
2.9%
F 56
 
2.5%
A 21
 
0.9%
B 18
 
0.8%
Z 5
 
0.2%
D 2
 
0.1%
Space Separator
ValueCountFrequency (%)
354
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46410
95.4%
Latin 2252
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34397
74.1%
1 4387
 
9.5%
2 2373
 
5.1%
8 1962
 
4.2%
3 1033
 
2.2%
9 534
 
1.2%
4 514
 
1.1%
354
 
0.8%
5 310
 
0.7%
7 275
 
0.6%
Latin
ValueCountFrequency (%)
C 1336
59.3%
G 643
28.6%
X 105
 
4.7%
E 66
 
2.9%
F 56
 
2.5%
A 21
 
0.9%
B 18
 
0.8%
Z 5
 
0.2%
D 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34397
70.7%
1 4387
 
9.0%
2 2373
 
4.9%
8 1962
 
4.0%
C 1336
 
2.7%
3 1033
 
2.1%
G 643
 
1.3%
9 534
 
1.1%
4 514
 
1.1%
354
 
0.7%
Other values (10) 1129
 
2.3%

식품군
Text

MISSING 

Distinct231
Distinct (%)5.8%
Missing485
Missing (%)10.8%
Memory size35.1 KiB
2024-05-04T02:49:23.711660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length17
Mean length6.63001
Min length1

Characters and Unicode

Total characters26467
Distinct characters262
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)1.5%

Sample

1st row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
2nd row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
3rd row조리식품 등
4th row즉석섭취식품
5th row자가제조얼음
ValueCountFrequency (%)
593
 
8.7%
조리식품 412
 
6.1%
조미식품 288
 
4.2%
과자류 217
 
3.2%
빵또는떡류 201
 
3.0%
150
 
2.2%
중인 150
 
2.2%
제외한다 148
 
2.2%
것은 148
 
2.2%
147
 
2.2%
Other values (247) 4326
63.8%
2024-05-04T02:49:25.123338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2788
 
10.5%
1776
 
6.7%
1545
 
5.8%
1432
 
5.4%
934
 
3.5%
712
 
2.7%
661
 
2.5%
593
 
2.2%
525
 
2.0%
511
 
1.9%
Other values (252) 14990
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22598
85.4%
Space Separator 2788
 
10.5%
Other Punctuation 693
 
2.6%
Open Punctuation 182
 
0.7%
Close Punctuation 182
 
0.7%
Uppercase Letter 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1776
 
7.9%
1545
 
6.8%
1432
 
6.3%
934
 
4.1%
712
 
3.2%
661
 
2.9%
593
 
2.6%
525
 
2.3%
511
 
2.3%
462
 
2.0%
Other values (239) 13447
59.5%
Uppercase Letter
ValueCountFrequency (%)
C 8
33.3%
A 6
25.0%
D 4
16.7%
H 2
 
8.3%
E 2
 
8.3%
P 2
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 442
63.8%
. 219
31.6%
? 29
 
4.2%
/ 3
 
0.4%
Space Separator
ValueCountFrequency (%)
2788
100.0%
Open Punctuation
ValueCountFrequency (%)
( 182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22598
85.4%
Common 3845
 
14.5%
Latin 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1776
 
7.9%
1545
 
6.8%
1432
 
6.3%
934
 
4.1%
712
 
3.2%
661
 
2.9%
593
 
2.6%
525
 
2.3%
511
 
2.3%
462
 
2.0%
Other values (239) 13447
59.5%
Common
ValueCountFrequency (%)
2788
72.5%
, 442
 
11.5%
. 219
 
5.7%
( 182
 
4.7%
) 182
 
4.7%
? 29
 
0.8%
/ 3
 
0.1%
Latin
ValueCountFrequency (%)
C 8
33.3%
A 6
25.0%
D 4
16.7%
H 2
 
8.3%
E 2
 
8.3%
P 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22598
85.4%
ASCII 3869
 
14.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2788
72.1%
, 442
 
11.4%
. 219
 
5.7%
( 182
 
4.7%
) 182
 
4.7%
? 29
 
0.7%
C 8
 
0.2%
A 6
 
0.2%
D 4
 
0.1%
/ 3
 
0.1%
Other values (3) 6
 
0.2%
Hangul
ValueCountFrequency (%)
1776
 
7.9%
1545
 
6.8%
1432
 
6.3%
934
 
4.1%
712
 
3.2%
661
 
2.9%
593
 
2.6%
525
 
2.3%
511
 
2.3%
462
 
2.0%
Other values (239) 13447
59.5%

품목명
Text

MISSING 

Distinct321
Distinct (%)7.3%
Missing108
Missing (%)2.4%
Memory size35.1 KiB
2024-05-04T02:49:25.931950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length6.9029526
Min length1

Characters and Unicode

Total characters30159
Distinct characters314
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

Unique87 ?
Unique (%)2.0%

Sample

1st row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
2nd row칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)
3rd row조리식품 등
4th row즉석섭취식품
5th row자가제조얼음
ValueCountFrequency (%)
673
 
8.7%
조리식품 488
 
6.3%
소스류 227
 
2.9%
중인 189
 
2.4%
187
 
2.4%
제외한다 187
 
2.4%
것은 187
 
2.4%
칼.도마 185
 
2.4%
것(사용 185
 
2.4%
담는 185
 
2.4%
Other values (341) 5087
65.4%
2024-05-04T02:49:27.000119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3411
 
11.3%
1151
 
3.8%
1116
 
3.7%
1028
 
3.4%
910
 
3.0%
877
 
2.9%
853
 
2.8%
679
 
2.3%
614
 
2.0%
, 571
 
1.9%
Other values (304) 18949
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24934
82.7%
Space Separator 3411
 
11.3%
Other Punctuation 891
 
3.0%
Close Punctuation 418
 
1.4%
Open Punctuation 418
 
1.4%
Decimal Number 46
 
0.2%
Uppercase Letter 37
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1151
 
4.6%
1116
 
4.5%
1028
 
4.1%
910
 
3.6%
877
 
3.5%
853
 
3.4%
679
 
2.7%
614
 
2.5%
558
 
2.2%
505
 
2.0%
Other values (283) 16643
66.7%
Decimal Number
ValueCountFrequency (%)
0 18
39.1%
4 7
 
15.2%
3 7
 
15.2%
2 6
 
13.0%
5 5
 
10.9%
1 2
 
4.3%
6 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 20
54.1%
A 6
 
16.2%
D 5
 
13.5%
E 2
 
5.4%
P 2
 
5.4%
H 2
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 571
64.1%
. 308
34.6%
? 9
 
1.0%
/ 3
 
0.3%
Space Separator
ValueCountFrequency (%)
3411
100.0%
Close Punctuation
ValueCountFrequency (%)
) 418
100.0%
Open Punctuation
ValueCountFrequency (%)
( 418
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24934
82.7%
Common 5188
 
17.2%
Latin 37
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1151
 
4.6%
1116
 
4.5%
1028
 
4.1%
910
 
3.6%
877
 
3.5%
853
 
3.4%
679
 
2.7%
614
 
2.5%
558
 
2.2%
505
 
2.0%
Other values (283) 16643
66.7%
Common
ValueCountFrequency (%)
3411
65.7%
, 571
 
11.0%
) 418
 
8.1%
( 418
 
8.1%
. 308
 
5.9%
0 18
 
0.3%
? 9
 
0.2%
4 7
 
0.1%
3 7
 
0.1%
2 6
 
0.1%
Other values (5) 15
 
0.3%
Latin
ValueCountFrequency (%)
C 20
54.1%
A 6
 
16.2%
D 5
 
13.5%
E 2
 
5.4%
P 2
 
5.4%
H 2
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24934
82.7%
ASCII 5225
 
17.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3411
65.3%
, 571
 
10.9%
) 418
 
8.0%
( 418
 
8.0%
. 308
 
5.9%
C 20
 
0.4%
0 18
 
0.3%
? 9
 
0.2%
4 7
 
0.1%
3 7
 
0.1%
Other values (11) 38
 
0.7%
Hangul
ValueCountFrequency (%)
1151
 
4.6%
1116
 
4.5%
1028
 
4.1%
910
 
3.6%
877
 
3.5%
853
 
3.4%
679
 
2.7%
614
 
2.5%
558
 
2.2%
505
 
2.0%
Other values (283) 16643
66.7%
Distinct3639
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
2024-05-04T02:49:27.809587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length7.2421264
Min length1

Characters and Unicode

Total characters32423
Distinct characters879
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3209 ?
Unique (%)71.7%

Sample

1st row야채 칼
2nd row야채 도마
3rd row돈까스
4th row참치주먹밥
5th row식용얼음(제빙기 얼음)
ValueCountFrequency (%)
73
 
1.1%
도마 71
 
1.1%
청정원 34
 
0.5%
참기름 31
 
0.5%
석식 30
 
0.5%
초이스엘 26
 
0.4%
수족관물 25
 
0.4%
두부 25
 
0.4%
중식 25
 
0.4%
조식 25
 
0.4%
Other values (4121) 6076
94.3%
2024-05-04T02:49:29.150705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1974
 
6.1%
758
 
2.3%
579
 
1.8%
556
 
1.7%
494
 
1.5%
421
 
1.3%
382
 
1.2%
331
 
1.0%
313
 
1.0%
311
 
1.0%
Other values (869) 26304
81.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27856
85.9%
Space Separator 1974
 
6.1%
Decimal Number 1102
 
3.4%
Uppercase Letter 451
 
1.4%
Other Punctuation 301
 
0.9%
Close Punctuation 264
 
0.8%
Open Punctuation 263
 
0.8%
Lowercase Letter 124
 
0.4%
Dash Punctuation 78
 
0.2%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
758
 
2.7%
579
 
2.1%
556
 
2.0%
494
 
1.8%
421
 
1.5%
382
 
1.4%
331
 
1.2%
313
 
1.1%
311
 
1.1%
303
 
1.1%
Other values (793) 23408
84.0%
Uppercase Letter
ValueCountFrequency (%)
C 46
 
10.2%
I 40
 
8.9%
A 40
 
8.9%
E 36
 
8.0%
O 32
 
7.1%
T 26
 
5.8%
R 23
 
5.1%
M 22
 
4.9%
N 20
 
4.4%
L 19
 
4.2%
Other values (16) 147
32.6%
Lowercase Letter
ValueCountFrequency (%)
a 20
16.1%
m 15
12.1%
p 12
9.7%
e 11
8.9%
s 11
8.9%
c 9
 
7.3%
l 8
 
6.5%
o 5
 
4.0%
u 4
 
3.2%
i 4
 
3.2%
Other values (12) 25
20.2%
Other Punctuation
ValueCountFrequency (%)
. 189
62.8%
, 42
 
14.0%
& 18
 
6.0%
% 16
 
5.3%
/ 13
 
4.3%
; 11
 
3.7%
* 6
 
2.0%
? 2
 
0.7%
! 2
 
0.7%
1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 300
27.2%
0 204
18.5%
5 153
13.9%
2 142
12.9%
8 102
 
9.3%
3 62
 
5.6%
6 49
 
4.4%
4 45
 
4.1%
7 31
 
2.8%
9 14
 
1.3%
Math Symbol
ValueCountFrequency (%)
+ 8
80.0%
1
 
10.0%
~ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1974
100.0%
Close Punctuation
ValueCountFrequency (%)
) 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27849
85.9%
Common 3992
 
12.3%
Latin 575
 
1.8%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
758
 
2.7%
579
 
2.1%
556
 
2.0%
494
 
1.8%
421
 
1.5%
382
 
1.4%
331
 
1.2%
313
 
1.1%
311
 
1.1%
303
 
1.1%
Other values (786) 23401
84.0%
Latin
ValueCountFrequency (%)
C 46
 
8.0%
I 40
 
7.0%
A 40
 
7.0%
E 36
 
6.3%
O 32
 
5.6%
T 26
 
4.5%
R 23
 
4.0%
M 22
 
3.8%
a 20
 
3.5%
N 20
 
3.5%
Other values (38) 270
47.0%
Common
ValueCountFrequency (%)
1974
49.4%
1 300
 
7.5%
) 264
 
6.6%
( 263
 
6.6%
0 204
 
5.1%
. 189
 
4.7%
5 153
 
3.8%
2 142
 
3.6%
8 102
 
2.6%
- 78
 
2.0%
Other values (18) 323
 
8.1%
Han
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27849
85.9%
ASCII 4565
 
14.1%
CJK 6
 
< 0.1%
None 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1974
43.2%
1 300
 
6.6%
) 264
 
5.8%
( 263
 
5.8%
0 204
 
4.5%
. 189
 
4.1%
5 153
 
3.4%
2 142
 
3.1%
8 102
 
2.2%
- 78
 
1.7%
Other values (64) 896
19.6%
Hangul
ValueCountFrequency (%)
758
 
2.7%
579
 
2.1%
556
 
2.0%
494
 
1.8%
421
 
1.5%
382
 
1.4%
331
 
1.2%
313
 
1.1%
311
 
1.1%
303
 
1.1%
Other values (786) 23401
84.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

음식물명
Text

MISSING 

Distinct17
Distinct (%)65.4%
Missing4451
Missing (%)99.4%
Memory size35.1 KiB
2024-05-04T02:49:29.667294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9.5
Mean length4.4615385
Min length1

Characters and Unicode

Total characters116
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)57.7%

Sample

1st row광어회 (수산물)
2nd row광어회 (수산물)
3rd row광어회 (수산물)
4th row광어회 (수산물)
5th row짬뽕국
ValueCountFrequency (%)
7
22.6%
광어회 5
16.1%
수산물 4
12.9%
무채무침 1
 
3.2%
돼지고기 1
 
3.2%
짬뽕국 1
 
3.2%
차조밥 1
 
3.2%
닭갈비 1
 
3.2%
한식잡채 1
 
3.2%
애호박해물전 1
 
3.2%
Other values (8) 8
25.8%
2024-05-04T02:49:30.632703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
10.3%
9
 
7.8%
6
 
5.2%
6
 
5.2%
( 5
 
4.3%
5
 
4.3%
) 5
 
4.3%
5
 
4.3%
4
 
3.4%
3
 
2.6%
Other values (48) 56
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
82.8%
Space Separator 9
 
7.8%
Open Punctuation 5
 
4.3%
Close Punctuation 5
 
4.3%
Other Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
12.5%
6
 
6.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
2
 
2.1%
Other values (44) 48
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
82.8%
Common 20
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
12.5%
6
 
6.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
2
 
2.1%
Other values (44) 48
50.0%
Common
ValueCountFrequency (%)
9
45.0%
( 5
25.0%
) 5
25.0%
, 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
82.8%
ASCII 20
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12
 
12.5%
6
 
6.2%
6
 
6.2%
5
 
5.2%
5
 
5.2%
4
 
4.2%
3
 
3.1%
3
 
3.1%
2
 
2.1%
2
 
2.1%
Other values (44) 48
50.0%
ASCII
ValueCountFrequency (%)
9
45.0%
( 5
25.0%
) 5
25.0%
, 1
 
5.0%

원료명
Text

MISSING 

Distinct5
Distinct (%)71.4%
Missing4470
Missing (%)99.8%
Memory size35.1 KiB
2024-05-04T02:49:30.934836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5714286
Min length1

Characters and Unicode

Total characters18
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)57.1%

Sample

1st row
2nd row
3rd row
4th row갈치등
5th row돼지고기
ValueCountFrequency (%)
3
42.9%
갈치등 1
 
14.3%
돼지고기 1
 
14.3%
광어 1
 
14.3%
콩(콩가루 1
 
14.3%
2024-05-04T02:49:31.821664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
16.7%
2
 
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (5) 5
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
88.9%
Open Punctuation 1
 
5.6%
Close Punctuation 1
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
88.9%
ASCII 2
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

생산업소
Text

MISSING 

Distinct545
Distinct (%)35.4%
Missing2937
Missing (%)65.6%
Memory size35.1 KiB
2024-05-04T02:49:32.478387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length26
Mean length6.95
Min length2

Characters and Unicode

Total characters10703
Distinct characters358
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

Unique315 ?
Unique (%)20.5%

Sample

1st row마라사부 마라탕 / 서울시 송파구 올림픽로30길 9, 엘루이시티 102호 (방이동)
2nd row왕빈자 삼파전/서울시 송파구 풍성로26길 47, 상가동 1층 1,2호(풍납동, 송파해모로아파트)
3rd row왕빈자 삼파전/서울시 송파구 풍성로26길 47, 상가동 1층 1,2호(풍납동, 송파해모로아파트)
4th row신나루모듬전(서울시 송파구 올림픽로35길 94)
5th row신나루모듬전(서울시 송파구 올림픽로35길 94)
ValueCountFrequency (%)
대상(주 81
 
4.9%
씨제이제일제당(주 75
 
4.6%
주)오뚜기 37
 
2.3%
롯데제과(주 25
 
1.5%
자이소 24
 
1.5%
샘표식품(주 23
 
1.4%
주)동원f&amp;b 23
 
1.4%
동서식품 17
 
1.0%
뚜레반 16
 
1.0%
주)롯데제과 16
 
1.0%
Other values (581) 1302
79.4%
2024-05-04T02:49:33.554099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1130
 
10.6%
) 1106
 
10.3%
( 1101
 
10.3%
498
 
4.7%
348
 
3.3%
332
 
3.1%
195
 
1.8%
154
 
1.4%
150
 
1.4%
131
 
1.2%
Other values (348) 5558
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7900
73.8%
Close Punctuation 1106
 
10.3%
Open Punctuation 1101
 
10.3%
Uppercase Letter 181
 
1.7%
Lowercase Letter 155
 
1.4%
Other Punctuation 103
 
1.0%
Space Separator 99
 
0.9%
Decimal Number 46
 
0.4%
Dash Punctuation 9
 
0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1130
 
14.3%
498
 
6.3%
348
 
4.4%
332
 
4.2%
195
 
2.5%
154
 
1.9%
150
 
1.9%
131
 
1.7%
129
 
1.6%
128
 
1.6%
Other values (310) 4705
59.6%
Uppercase Letter
ValueCountFrequency (%)
F 69
38.1%
B 47
26.0%
J 16
 
8.8%
C 14
 
7.7%
S 9
 
5.0%
N 8
 
4.4%
O 5
 
2.8%
T 4
 
2.2%
E 2
 
1.1%
R 2
 
1.1%
Other values (4) 5
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 17
37.0%
2 7
15.2%
4 6
 
13.0%
9 3
 
6.5%
5 3
 
6.5%
3 3
 
6.5%
0 2
 
4.3%
6 2
 
4.3%
7 2
 
4.3%
8 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
p 49
31.6%
a 49
31.6%
m 49
31.6%
c 4
 
2.6%
k 4
 
2.6%
Other Punctuation
ValueCountFrequency (%)
; 49
47.6%
& 44
42.7%
, 7
 
6.8%
/ 3
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 1106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1101
100.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7900
73.8%
Common 2467
 
23.0%
Latin 336
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1130
 
14.3%
498
 
6.3%
348
 
4.4%
332
 
4.2%
195
 
2.5%
154
 
1.9%
150
 
1.9%
131
 
1.7%
129
 
1.6%
128
 
1.6%
Other values (310) 4705
59.6%
Common
ValueCountFrequency (%)
) 1106
44.8%
( 1101
44.6%
99
 
4.0%
; 49
 
2.0%
& 44
 
1.8%
1 17
 
0.7%
- 9
 
0.4%
2 7
 
0.3%
, 7
 
0.3%
4 6
 
0.2%
Other values (9) 22
 
0.9%
Latin
ValueCountFrequency (%)
F 69
20.5%
p 49
14.6%
a 49
14.6%
m 49
14.6%
B 47
14.0%
J 16
 
4.8%
C 14
 
4.2%
S 9
 
2.7%
N 8
 
2.4%
O 5
 
1.5%
Other values (9) 21
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7899
73.8%
ASCII 2803
 
26.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1130
 
14.3%
498
 
6.3%
348
 
4.4%
332
 
4.2%
195
 
2.5%
154
 
1.9%
150
 
1.9%
131
 
1.7%
129
 
1.6%
128
 
1.6%
Other values (309) 4704
59.6%
ASCII
ValueCountFrequency (%)
) 1106
39.5%
( 1101
39.3%
99
 
3.5%
F 69
 
2.5%
p 49
 
1.7%
a 49
 
1.7%
; 49
 
1.7%
m 49
 
1.7%
B 47
 
1.7%
& 44
 
1.6%
Other values (28) 141
 
5.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

수거일자
Real number (ℝ)

SKEWED 

Distinct308
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20146315
Minimum12011209
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:34.120469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12011209
5-th percentile20091086
Q120120427
median20151012
Q320180608
95-th percentile20211108
Maximum20240314
Range8229105
Interquartile range (IQR)60181

Descriptive statistics

Standard deviation127491.18
Coefficient of variation (CV)0.0063282628
Kurtosis3705.7399
Mean20146315
Median Absolute Deviation (MAD)29999
Skewness-58.060647
Sum9.0195054 × 1010
Variance1.6254001 × 1010
MonotonicityDecreasing
2024-05-04T02:49:34.659558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091102 179
 
4.0%
20131016 111
 
2.5%
20130724 109
 
2.4%
20180518 107
 
2.4%
20170926 106
 
2.4%
20130923 87
 
1.9%
20090903 76
 
1.7%
20151012 76
 
1.7%
20151105 74
 
1.7%
20131219 71
 
1.6%
Other values (298) 3481
77.8%
ValueCountFrequency (%)
12011209 1
 
< 0.1%
20090113 11
 
0.2%
20090518 5
 
0.1%
20090521 5
 
0.1%
20090603 1
 
< 0.1%
20090617 2
 
< 0.1%
20090715 2
 
< 0.1%
20090720 29
 
0.6%
20090903 76
1.7%
20090909 26
 
0.6%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240308 1
 
< 0.1%
20240304 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20240117 2
 
< 0.1%
20231206 1
 
< 0.1%
20231124 1
 
< 0.1%
20231116 14
0.3%
20231115 21
0.5%

수거량(정량)
Real number (ℝ)

MISSING  SKEWED 

Distinct176
Distinct (%)4.2%
Missing247
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean113.48915
Minimum1
Maximum110000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:35.079497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile617.75
Maximum110000
Range109999
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1719.3127
Coefficient of variation (CV)15.149578
Kurtosis3948.544
Mean113.48915
Median Absolute Deviation (MAD)1
Skewness61.826926
Sum480059.1
Variance2956036.3
MonotonicityNot monotonic
2024-05-04T02:49:35.629892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 1876
41.9%
2.0 722
 
16.1%
3.0 441
 
9.9%
6.0 258
 
5.8%
5.0 128
 
2.9%
4.0 126
 
2.8%
600.0 80
 
1.8%
7.0 59
 
1.3%
8.0 30
 
0.7%
10.0 21
 
0.5%
Other values (166) 489
 
10.9%
(Missing) 247
 
5.5%
ValueCountFrequency (%)
1.0 1876
41.9%
2.0 722
 
16.1%
3.0 441
 
9.9%
4.0 126
 
2.8%
5.0 128
 
2.9%
6.0 258
 
5.8%
7.0 59
 
1.3%
8.0 30
 
0.7%
9.0 14
 
0.3%
10.0 21
 
0.5%
ValueCountFrequency (%)
110000.0 1
< 0.1%
10000.0 1
< 0.1%
3480.0 1
< 0.1%
3000.0 1
< 0.1%
2850.0 1
< 0.1%
2700.0 1
< 0.1%
2508.0 2
< 0.1%
2460.0 1
< 0.1%
2400.0 1
< 0.1%
2040.0 1
< 0.1%

제품규격(정량)
Text

MISSING 

Distinct332
Distinct (%)9.8%
Missing1101
Missing (%)24.6%
Memory size35.1 KiB
2024-05-04T02:49:36.567993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.7138626
Min length1

Characters and Unicode

Total characters9162
Distinct characters17
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)4.2%

Sample

1st row1
2nd row1
3rd row600
4th row110
5th row600
ValueCountFrequency (%)
1 380
 
11.3%
200 310
 
9.2%
600 199
 
5.9%
300 198
 
5.9%
500 198
 
5.9%
100 186
 
5.5%
900 155
 
4.6%
400 147
 
4.4%
g 97
 
2.9%
350 61
 
1.8%
Other values (322) 1445
42.8%
2024-05-04T02:49:37.923552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3973
43.4%
1 1103
 
12.0%
2 857
 
9.4%
5 726
 
7.9%
3 615
 
6.7%
4 427
 
4.7%
6 414
 
4.5%
8 293
 
3.2%
9 279
 
3.0%
7 233
 
2.5%
Other values (7) 242
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8920
97.4%
Lowercase Letter 110
 
1.2%
Other Punctuation 104
 
1.1%
Other Letter 24
 
0.3%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3973
44.5%
1 1103
 
12.4%
2 857
 
9.6%
5 726
 
8.1%
3 615
 
6.9%
4 427
 
4.8%
6 414
 
4.6%
8 293
 
3.3%
9 279
 
3.1%
7 233
 
2.6%
Other Letter
ValueCountFrequency (%)
11
45.8%
11
45.8%
2
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 103
99.0%
, 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
g 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9028
98.5%
Latin 110
 
1.2%
Hangul 24
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3973
44.0%
1 1103
 
12.2%
2 857
 
9.5%
5 726
 
8.0%
3 615
 
6.8%
4 427
 
4.7%
6 414
 
4.6%
8 293
 
3.2%
9 279
 
3.1%
7 233
 
2.6%
Other values (3) 108
 
1.2%
Hangul
ValueCountFrequency (%)
11
45.8%
11
45.8%
2
 
8.3%
Latin
ValueCountFrequency (%)
g 110
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9138
99.7%
Hangul 22
 
0.2%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3973
43.5%
1 1103
 
12.1%
2 857
 
9.4%
5 726
 
7.9%
3 615
 
6.7%
4 427
 
4.7%
6 414
 
4.5%
8 293
 
3.2%
9 279
 
3.1%
7 233
 
2.5%
Other values (4) 218
 
2.4%
Hangul
ValueCountFrequency (%)
11
50.0%
11
50.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%

단위(정량)
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
g
2218 
<NA>
1221 
ML
560 
KG
323 
LT
 
97

Length

Max length4
Median length1
Mean length2.0370784
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 2218
49.5%
<NA> 1221
27.3%
ML 560
 
12.5%
KG 323
 
7.2%
LT 97
 
2.2%
58
 
1.3%

Length

2024-05-04T02:49:38.423447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:38.934029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 2218
49.5%
na 1221
27.3%
ml 560
 
12.5%
kg 323
 
7.2%
lt 97
 
2.2%
58
 
1.3%

수거량(자유)
Categorical

IMBALANCE 

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4237 
1개
 
108
1
 
51
스왑
 
29
환경검체1개
 
8
Other values (26)
 
44

Length

Max length16
Median length4
Mean length3.9425955
Min length1

Unique

Unique17 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4237
94.6%
1개 108
 
2.4%
1 51
 
1.1%
스왑 29
 
0.6%
환경검체1개 8
 
0.2%
스왑X1 6
 
0.1%
SWAB*2개 4
 
0.1%
환경검체 1개 4
 
0.1%
문고리 환경검체 1개 3
 
0.1%
세면대 환경검체 1개 2
 
< 0.1%
Other values (21) 25
 
0.6%

Length

2024-05-04T02:49:39.527275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4237
93.9%
1개 129
 
2.9%
1 51
 
1.1%
스왑 29
 
0.6%
환경검체 16
 
0.4%
환경검체1개 8
 
0.2%
스왑x1 6
 
0.1%
swab*2개 4
 
0.1%
문고리 4
 
0.1%
음용수대 3
 
0.1%
Other values (21) 25
 
0.6%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct268
Distinct (%)23.4%
Missing3333
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean20184399
Minimum20110616
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:40.231611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110616
5-th percentile20130614
Q120170622
median20181017
Q320200618
95-th percentile20230998
Maximum20240314
Range129698
Interquartile range (IQR)29996

Descriptive statistics

Standard deviation26807.944
Coefficient of variation (CV)0.0013281518
Kurtosis0.19601441
Mean20184399
Median Absolute Deviation (MAD)10395
Skewness-0.21757744
Sum2.3090952 × 1010
Variance7.1866588 × 108
MonotonicityNot monotonic
2024-05-04T02:49:40.870803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180518 72
 
1.6%
20181017 70
 
1.6%
20181205 55
 
1.2%
20190515 54
 
1.2%
20180517 43
 
1.0%
20190318 41
 
0.9%
20191119 28
 
0.6%
20190611 24
 
0.5%
20180516 22
 
0.5%
20230825 21
 
0.5%
Other values (258) 714
 
15.9%
(Missing) 3333
74.4%
ValueCountFrequency (%)
20110616 1
 
< 0.1%
20110824 1
 
< 0.1%
20111203 1
 
< 0.1%
20111207 1
 
< 0.1%
20111209 1
 
< 0.1%
20120112 3
0.1%
20120116 1
 
< 0.1%
20120117 1
 
< 0.1%
20120121 1
 
< 0.1%
20120216 1
 
< 0.1%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240307 1
 
< 0.1%
20240304 2
 
< 0.1%
20240226 1
 
< 0.1%
20240117 2
 
< 0.1%
20231206 1
 
< 0.1%
20231124 1
 
< 0.1%
20231116 14
0.3%
20231115 20
0.4%
20231114 1
 
< 0.1%

제조일자(롯트)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4475 
2211
 
1
2100195
 
1

Length

Max length7
Median length4
Mean length4.0006701
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> 4475
> 99.9%
2211 1
 
< 0.1%
2100195 1
 
< 0.1%

Length

2024-05-04T02:49:41.405362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:41.820873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4475
> 99.9%
2211 1
 
< 0.1%
2100195 1
 
< 0.1%

유통기한(일자)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

유통기한(제조일기준)
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4469 
180
 
4
3
 
1
365
 
1
720
 
1

Length

Max length4
Median length4
Mean length3.9979897
Min length1

Unique

Unique4 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4469
99.8%
180 4
 
0.1%
3 1
 
< 0.1%
365 1
 
< 0.1%
720 1
 
< 0.1%
1080 1
 
< 0.1%

Length

2024-05-04T02:49:42.238340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:42.628485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4469
99.8%
180 4
 
0.1%
3 1
 
< 0.1%
365 1
 
< 0.1%
720 1
 
< 0.1%
1080 1
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
실온
3043 
<NA>
983 
냉장
342 
냉동
 
101
기타
 
8

Length

Max length4
Median length2
Mean length2.4391333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 3043
68.0%
<NA> 983
 
22.0%
냉장 342
 
7.6%
냉동 101
 
2.3%
기타 8
 
0.2%

Length

2024-05-04T02:49:43.244735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:43.642948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3043
68.0%
na 983
 
22.0%
냉장 342
 
7.6%
냉동 101
 
2.3%
기타 8
 
0.2%

바코드번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4476 
4977042240922
 
1

Length

Max length13
Median length4
Mean length4.0020103
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> 4476
> 99.9%
4977042240922 1
 
< 0.1%

Length

2024-05-04T02:49:44.017418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:44.506740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4476
> 99.9%
4977042240922 1
 
< 0.1%

어린이기호식품유형
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4445 
과자(한과류제외)
 
18
빵류
 
11
캔디류
 
3

Length

Max length9
Median length4
Mean length4.0145187
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4445
99.3%
과자(한과류제외) 18
 
0.4%
빵류 11
 
0.2%
캔디류 3
 
0.1%

Length

2024-05-04T02:49:44.924855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:45.355451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4445
99.3%
과자(한과류제외 18
 
0.4%
빵류 11
 
0.2%
캔디류 3
 
0.1%

검사기관명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3345 
1
1132 

Length

Max length4
Median length4
Mean length3.2414563
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3345
74.7%
1 1132
 
25.3%

Length

2024-05-04T02:49:45.876046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:46.314799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3345
74.7%
1 1132
 
25.3%

(구)제조사명
Text

MISSING 

Distinct52
Distinct (%)53.1%
Missing4379
Missing (%)97.8%
Memory size35.1 KiB
2024-05-04T02:49:46.951834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.8061224
Min length2

Characters and Unicode

Total characters569
Distinct characters102
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)29.6%

Sample

1st row농협목우촌
2nd row씨제이제일제당
3rd row씨제이제일제당
4th row씨제이제일제당
5th row삼호햄
ValueCountFrequency (%)
씨제이제일제당 11
 
10.5%
5
 
4.8%
주)아워홈 5
 
4.8%
순창문옥례식품 4
 
3.8%
주)롯데햄 4
 
3.8%
롯데햄 4
 
3.8%
동원 4
 
3.8%
진보식품 3
 
2.9%
상촌식품 3
 
2.9%
한국맥꾸름 3
 
2.9%
Other values (42) 59
56.2%
2024-05-04T02:49:48.262532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
 
9.8%
) 31
 
5.4%
31
 
5.4%
( 30
 
5.3%
25
 
4.4%
25
 
4.4%
19
 
3.3%
17
 
3.0%
14
 
2.5%
14
 
2.5%
Other values (92) 307
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 500
87.9%
Close Punctuation 31
 
5.4%
Open Punctuation 30
 
5.3%
Space Separator 7
 
1.2%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
56
 
11.2%
31
 
6.2%
25
 
5.0%
25
 
5.0%
19
 
3.8%
17
 
3.4%
14
 
2.8%
14
 
2.8%
12
 
2.4%
10
 
2.0%
Other values (88) 277
55.4%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 500
87.9%
Common 69
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
56
 
11.2%
31
 
6.2%
25
 
5.0%
25
 
5.0%
19
 
3.8%
17
 
3.4%
14
 
2.8%
14
 
2.8%
12
 
2.4%
10
 
2.0%
Other values (88) 277
55.4%
Common
ValueCountFrequency (%)
) 31
44.9%
( 30
43.5%
7
 
10.1%
9 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 500
87.9%
ASCII 69
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
56
 
11.2%
31
 
6.2%
25
 
5.0%
25
 
5.0%
19
 
3.8%
17
 
3.4%
14
 
2.8%
14
 
2.8%
12
 
2.4%
10
 
2.0%
Other values (88) 277
55.4%
ASCII
ValueCountFrequency (%)
) 31
44.9%
( 30
43.5%
7
 
10.1%
9 1
 
1.4%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
국내
3357 
국외
1120 

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 3357
75.0%
국외 1120
 
25.0%

Length

2024-05-04T02:49:48.708935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:49.247573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 3357
75.0%
국외 1120
 
25.0%

국가명
Categorical

IMBALANCE 

Distinct29
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4218 
미국
 
83
일본
 
48
중국
 
37
태국
 
20
Other values (24)
 
71

Length

Max length6
Median length4
Mean length3.9075274
Min length2

Unique

Unique12 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4218
94.2%
미국 83
 
1.9%
일본 48
 
1.1%
중국 37
 
0.8%
태국 20
 
0.4%
이탈리아 10
 
0.2%
독일 9
 
0.2%
캐나다 8
 
0.2%
말레이지아 6
 
0.1%
중국 홍콩 5
 
0.1%
Other values (19) 33
 
0.7%

Length

2024-05-04T02:49:50.095496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4218
94.1%
미국 83
 
1.9%
일본 48
 
1.1%
중국 42
 
0.9%
태국 20
 
0.4%
이탈리아 10
 
0.2%
독일 9
 
0.2%
캐나다 8
 
0.2%
말레이지아 6
 
0.1%
홍콩 5
 
0.1%
Other values (20) 34
 
0.8%

검사구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
1
2579 
<NA>
952 
2
946 

Length

Max length4
Median length1
Mean length1.6379272
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2579
57.6%
<NA> 952
 
21.3%
2 946
 
21.1%

Length

2024-05-04T02:49:50.721595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:51.129358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2579
57.6%
na 952
 
21.3%
2 946
 
21.1%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)14.1%
Missing3847
Missing (%)85.9%
Infinite0
Infinite (%)0.0%
Mean20176594
Minimum20110112
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:51.641469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110112
5-th percentile20110324
Q120150827
median20160905
Q320230601
95-th percentile20231115
Maximum20240314
Range130202
Interquartile range (IQR)79774

Descriptive statistics

Standard deviation42952.348
Coefficient of variation (CV)0.0021288205
Kurtosis-1.2932826
Mean20176594
Median Absolute Deviation (MAD)49617.5
Skewness-0.0068435856
Sum1.2711254 × 1010
Variance1.8449042 × 109
MonotonicityNot monotonic
2024-05-04T02:49:52.281122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110324 62
 
1.4%
20151012 49
 
1.1%
20150827 47
 
1.0%
20160405 42
 
0.9%
20110426 26
 
0.6%
20230825 21
 
0.5%
20230601 21
 
0.5%
20231115 21
 
0.5%
20160830 18
 
0.4%
20210831 17
 
0.4%
Other values (79) 306
 
6.8%
(Missing) 3847
85.9%
ValueCountFrequency (%)
20110112 7
 
0.2%
20110222 3
 
0.1%
20110324 62
1.4%
20110426 26
0.6%
20130618 8
 
0.2%
20150302 4
 
0.1%
20150303 3
 
0.1%
20150827 47
1.0%
20150910 1
 
< 0.1%
20150917 1
 
< 0.1%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240308 1
 
< 0.1%
20240304 2
 
< 0.1%
20240226 1
 
< 0.1%
20240119 2
 
< 0.1%
20240117 2
 
< 0.1%
20231206 1
 
< 0.1%
20231124 1
 
< 0.1%
20231116 14
0.3%
20231115 21
0.5%

결과회보일자
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)11.5%
Missing4043
Missing (%)90.3%
Infinite0
Infinite (%)0.0%
Mean20148866
Minimum20100324
Maximum20211206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:53.110034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100324
5-th percentile20110131
Q120110426
median20151026
Q320160912
95-th percentile20201208
Maximum20211206
Range110882
Interquartile range (IQR)50486

Descriptive statistics

Standard deviation28433.336
Coefficient of variation (CV)0.001411163
Kurtosis-0.29076425
Mean20148866
Median Absolute Deviation (MAD)9900
Skewness0.087036707
Sum8.744608 × 109
Variance8.0845458 × 108
MonotonicityNot monotonic
2024-05-04T02:49:53.928977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110408 62
 
1.4%
20151026 49
 
1.1%
20150910 48
 
1.1%
20160420 42
 
0.9%
20110426 26
 
0.6%
20160912 18
 
0.4%
20160907 11
 
0.2%
20201208 11
 
0.2%
20161018 10
 
0.2%
20161021 9
 
0.2%
Other values (40) 148
 
3.3%
(Missing) 4043
90.3%
ValueCountFrequency (%)
20100324 1
 
< 0.1%
20100702 5
 
0.1%
20100727 6
 
0.1%
20100809 4
 
0.1%
20110131 7
 
0.2%
20110321 3
 
0.1%
20110408 62
1.4%
20110426 26
0.6%
20130628 8
 
0.2%
20150316 4
 
0.1%
ValueCountFrequency (%)
20211206 1
 
< 0.1%
20210916 6
0.1%
20210504 3
 
0.1%
20210415 2
 
< 0.1%
20210331 3
 
0.1%
20210205 3
 
0.1%
20201218 1
 
< 0.1%
20201208 11
0.2%
20201202 2
 
< 0.1%
20201124 8
0.2%

판정구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
3669 
1
798 
2
 
10

Length

Max length4
Median length4
Mean length3.458566
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> 3669
82.0%
1 798
 
17.8%
2 10
 
0.2%

Length

2024-05-04T02:49:54.391557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:54.766687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3669
82.0%
1 798
 
17.8%
2 10
 
0.2%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

처리결과
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
<NA>
4474 
적합
 
3

Length

Max length4
Median length4
Mean length3.9986598
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4474
99.9%
적합 3
 
0.1%

Length

2024-05-04T02:49:55.241414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:49:55.665448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4474
99.9%
적합 3
 
0.1%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

교부번호
Real number (ℝ)

Distinct396
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0023365 × 1010
Minimum1.9760114 × 1010
Maximum2.0230148 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:49:56.029923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9760114 × 1010
5-th percentile1.9908114 × 1010
Q11.9980115 × 1010
median1.9990116 × 1010
Q32.0080115 × 1010
95-th percentile2.0160115 × 1010
Maximum2.0230148 × 1010
Range4.7003433 × 108
Interquartile range (IQR)99999798

Descriptive statistics

Standard deviation75240480
Coefficient of variation (CV)0.0037576342
Kurtosis-0.53042417
Mean2.0023365 × 1010
Median Absolute Deviation (MAD)40002255
Skewness0.47920189
Sum8.9644604 × 1013
Variance5.6611299 × 1015
MonotonicityNot monotonic
2024-05-04T02:49:56.641948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19980115040 1109
24.8%
19950114057 555
 
12.4%
20070114920 281
 
6.3%
19900114514 167
 
3.7%
20110115006 151
 
3.4%
20070114378 117
 
2.6%
20000115428 109
 
2.4%
20140115393 76
 
1.7%
20010115978 71
 
1.6%
20000115167 70
 
1.6%
Other values (386) 1771
39.6%
ValueCountFrequency (%)
19760114003 1
 
< 0.1%
19810114011 1
 
< 0.1%
19850114058 2
 
< 0.1%
19850114117 6
0.1%
19860114063 3
 
0.1%
19870025212 13
0.3%
19870114108 3
 
0.1%
19870114148 3
 
0.1%
19880114024 5
 
0.1%
19880114493 6
0.1%
ValueCountFrequency (%)
20230148333 2
< 0.1%
20230147942 1
 
< 0.1%
20230147593 1
 
< 0.1%
20230147548 1
 
< 0.1%
20220141550 3
0.1%
20220140884 1
 
< 0.1%
20220140774 1
 
< 0.1%
20220140016 1
 
< 0.1%
20220139259 1
 
< 0.1%
20220139207 1
 
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

소재지(도로명)
Text

MISSING 

Distinct390
Distinct (%)9.5%
Missing390
Missing (%)8.7%
Memory size35.1 KiB
2024-05-04T02:49:57.292814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length62
Mean length33.762417
Min length23

Characters and Unicode

Total characters137987
Distinct characters255
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)4.4%

Sample

1st row서울특별시 송파구 잠실로 32, (잠실동)
2nd row서울특별시 송파구 잠실로 32, (잠실동)
3rd row서울특별시 송파구 잠실로 32, (잠실동)
4th row서울특별시 송파구 위례성대로6길 50, 지하1층 (방이동)
5th row서울특별시 송파구 올림픽로 300, 롯데월드몰 5층 (신천동)
ValueCountFrequency (%)
서울특별시 4087
16.0%
송파구 4087
16.0%
올림픽로 1584
 
6.2%
240 1415
 
5.5%
잠실동 1357
 
5.3%
지하1층 1269
 
5.0%
롯데마트 926
 
3.6%
가락동 635
 
2.5%
양재대로 598
 
2.3%
932 503
 
2.0%
Other values (602) 9137
35.7%
2024-05-04T02:49:58.498610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21546
 
15.6%
, 6580
 
4.8%
4782
 
3.5%
1 4602
 
3.3%
4467
 
3.2%
( 4397
 
3.2%
) 4397
 
3.2%
4383
 
3.2%
4329
 
3.1%
4090
 
3.0%
Other values (245) 74414
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82046
59.5%
Space Separator 21546
 
15.6%
Decimal Number 17909
 
13.0%
Other Punctuation 6676
 
4.8%
Open Punctuation 4397
 
3.2%
Close Punctuation 4397
 
3.2%
Dash Punctuation 422
 
0.3%
Math Symbol 300
 
0.2%
Uppercase Letter 254
 
0.2%
Lowercase Letter 40
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4782
 
5.8%
4467
 
5.4%
4383
 
5.3%
4329
 
5.3%
4090
 
5.0%
4090
 
5.0%
4090
 
5.0%
4087
 
5.0%
4087
 
5.0%
4086
 
5.0%
Other values (210) 39555
48.2%
Uppercase Letter
ValueCountFrequency (%)
B 102
40.2%
A 66
26.0%
E 16
 
6.3%
N 14
 
5.5%
H 14
 
5.5%
T 12
 
4.7%
C 11
 
4.3%
S 9
 
3.5%
F 3
 
1.2%
G 3
 
1.2%
Other values (2) 4
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 4602
25.7%
2 3874
21.6%
0 2253
12.6%
4 1877
10.5%
3 1865
10.4%
5 1121
 
6.3%
9 715
 
4.0%
6 713
 
4.0%
7 583
 
3.3%
8 306
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 6580
98.6%
/ 76
 
1.1%
. 18
 
0.3%
& 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
a 10
25.0%
e 10
25.0%
l 10
25.0%
b 10
25.0%
Space Separator
ValueCountFrequency (%)
21546
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4397
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 422
100.0%
Math Symbol
ValueCountFrequency (%)
~ 300
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82046
59.5%
Common 55647
40.3%
Latin 294
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4782
 
5.8%
4467
 
5.4%
4383
 
5.3%
4329
 
5.3%
4090
 
5.0%
4090
 
5.0%
4090
 
5.0%
4087
 
5.0%
4087
 
5.0%
4086
 
5.0%
Other values (210) 39555
48.2%
Common
ValueCountFrequency (%)
21546
38.7%
, 6580
 
11.8%
1 4602
 
8.3%
( 4397
 
7.9%
) 4397
 
7.9%
2 3874
 
7.0%
0 2253
 
4.0%
4 1877
 
3.4%
3 1865
 
3.4%
5 1121
 
2.0%
Other values (9) 3135
 
5.6%
Latin
ValueCountFrequency (%)
B 102
34.7%
A 66
22.4%
E 16
 
5.4%
N 14
 
4.8%
H 14
 
4.8%
T 12
 
4.1%
C 11
 
3.7%
a 10
 
3.4%
e 10
 
3.4%
l 10
 
3.4%
Other values (6) 29
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82046
59.5%
ASCII 55941
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21546
38.5%
, 6580
 
11.8%
1 4602
 
8.2%
( 4397
 
7.9%
) 4397
 
7.9%
2 3874
 
6.9%
0 2253
 
4.0%
4 1877
 
3.4%
3 1865
 
3.3%
5 1121
 
2.0%
Other values (25) 3429
 
6.1%
Hangul
ValueCountFrequency (%)
4782
 
5.8%
4467
 
5.4%
4383
 
5.3%
4329
 
5.3%
4090
 
5.0%
4090
 
5.0%
4090
 
5.0%
4087
 
5.0%
4087
 
5.0%
4086
 
5.0%
Other values (210) 39555
48.2%
Distinct325
Distinct (%)7.3%
Missing3
Missing (%)0.1%
Memory size35.1 KiB
2024-05-04T02:49:59.069412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length29.292803
Min length21

Characters and Unicode

Total characters131056
Distinct characters221
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)3.4%

Sample

1st row서울특별시 송파구 잠실동 22번지 10호
2nd row서울특별시 송파구 잠실동 22번지 10호
3rd row서울특별시 송파구 잠실동 22번지 10호
4th row서울특별시 송파구 방이동 146번지 4호
5th row서울특별시 송파구 신천동 29번지 롯데월드타워앤드롯데월드몰
ValueCountFrequency (%)
서울특별시 4474
16.9%
송파구 4474
16.9%
잠실동 1671
 
6.3%
1호 1477
 
5.6%
40번지 1409
 
5.3%
지하1층 1082
 
4.1%
가락동 983
 
3.7%
롯데마트 923
 
3.5%
600번지 782
 
3.0%
0호 630
 
2.4%
Other values (382) 8565
32.4%
2024-05-04T02:50:00.514597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32471
24.8%
6851
 
5.2%
1 5486
 
4.2%
4675
 
3.6%
4675
 
3.6%
4650
 
3.5%
4532
 
3.5%
4474
 
3.4%
4474
 
3.4%
4474
 
3.4%
Other values (211) 54294
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79083
60.3%
Space Separator 32471
24.8%
Decimal Number 18101
 
13.8%
Open Punctuation 311
 
0.2%
Close Punctuation 311
 
0.2%
Math Symbol 284
 
0.2%
Uppercase Letter 170
 
0.1%
Dash Punctuation 162
 
0.1%
Other Punctuation 123
 
0.1%
Lowercase Letter 40
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6851
 
8.7%
4675
 
5.9%
4675
 
5.9%
4650
 
5.9%
4532
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
Other values (170) 31330
39.6%
Uppercase Letter
ValueCountFrequency (%)
B 53
31.2%
A 22
12.9%
N 18
 
10.6%
H 14
 
8.2%
S 13
 
7.6%
T 13
 
7.6%
C 9
 
5.3%
G 5
 
2.9%
U 4
 
2.4%
F 4
 
2.4%
Other values (8) 15
 
8.8%
Decimal Number
ValueCountFrequency (%)
1 5486
30.3%
0 4203
23.2%
2 2155
 
11.9%
4 1851
 
10.2%
6 1195
 
6.6%
8 748
 
4.1%
3 720
 
4.0%
5 619
 
3.4%
9 589
 
3.3%
7 535
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/ 76
61.8%
, 42
34.1%
. 3
 
2.4%
& 2
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
e 10
25.0%
b 10
25.0%
l 10
25.0%
a 10
25.0%
Space Separator
ValueCountFrequency (%)
32471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 311
100.0%
Math Symbol
ValueCountFrequency (%)
~ 284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79083
60.3%
Common 51763
39.5%
Latin 210
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6851
 
8.7%
4675
 
5.9%
4675
 
5.9%
4650
 
5.9%
4532
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
Other values (170) 31330
39.6%
Latin
ValueCountFrequency (%)
B 53
25.2%
A 22
10.5%
N 18
 
8.6%
H 14
 
6.7%
S 13
 
6.2%
T 13
 
6.2%
e 10
 
4.8%
b 10
 
4.8%
l 10
 
4.8%
a 10
 
4.8%
Other values (12) 37
17.6%
Common
ValueCountFrequency (%)
32471
62.7%
1 5486
 
10.6%
0 4203
 
8.1%
2 2155
 
4.2%
4 1851
 
3.6%
6 1195
 
2.3%
8 748
 
1.4%
3 720
 
1.4%
5 619
 
1.2%
9 589
 
1.1%
Other values (9) 1726
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79083
60.3%
ASCII 51973
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32471
62.5%
1 5486
 
10.6%
0 4203
 
8.1%
2 2155
 
4.1%
4 1851
 
3.6%
6 1195
 
2.3%
8 748
 
1.4%
3 720
 
1.4%
5 619
 
1.2%
9 589
 
1.1%
Other values (31) 1936
 
3.7%
Hangul
ValueCountFrequency (%)
6851
 
8.7%
4675
 
5.9%
4675
 
5.9%
4650
 
5.9%
4532
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
4474
 
5.7%
Other values (170) 31330
39.6%

업소전화번호
Text

MISSING 

Distinct238
Distinct (%)6.0%
Missing513
Missing (%)11.5%
Memory size35.1 KiB
2024-05-04T02:50:01.375985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.622351
Min length2

Characters and Unicode

Total characters42107
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

Unique97 ?
Unique (%)2.4%

Sample

1st row02 412 3286
2nd row02 412 3286
3rd row02 412 3286
4th row02 32132730
5th row02 32132730
ValueCountFrequency (%)
02 3747
45.5%
4118800 1109
 
13.5%
4071171 595
 
7.2%
34688124 308
 
3.7%
4116084 167
 
2.0%
4111205 151
 
1.8%
412 138
 
1.7%
3230 117
 
1.4%
21409910 109
 
1.3%
407 82
 
1.0%
Other values (264) 1704
20.7%
2024-05-04T02:50:02.799426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9092
21.6%
1 6651
15.8%
2 6035
14.3%
5629
13.4%
4 4648
11.0%
8 3610
 
8.6%
7 2103
 
5.0%
3 1675
 
4.0%
6 1171
 
2.8%
5 753
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36478
86.6%
Space Separator 5629
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9092
24.9%
1 6651
18.2%
2 6035
16.5%
4 4648
12.7%
8 3610
 
9.9%
7 2103
 
5.8%
3 1675
 
4.6%
6 1171
 
3.2%
5 753
 
2.1%
9 740
 
2.0%
Space Separator
ValueCountFrequency (%)
5629
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9092
21.6%
1 6651
15.8%
2 6035
14.3%
5629
13.4%
4 4648
11.0%
8 3610
 
8.6%
7 2103
 
5.0%
3 1675
 
4.0%
6 1171
 
2.8%
5 753
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9092
21.6%
1 6651
15.8%
2 6035
14.3%
5629
13.4%
4 4648
11.0%
8 3610
 
8.6%
7 2103
 
5.0%
3 1675
 
4.0%
6 1171
 
2.8%
5 753
 
1.8%

점검목적
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
수거
2023 
<NA>
1805 
위생점검(전체)
623 
위생점검(부분)
 
26

Length

Max length8
Median length4
Mean length3.6761224
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수거 2023
45.2%
<NA> 1805
40.3%
위생점검(전체) 623
 
13.9%
위생점검(부분) 26
 
0.6%

Length

2024-05-04T02:50:03.473675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:50:03.968044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 2023
45.2%
na 1805
40.3%
위생점검(전체 623
 
13.9%
위생점검(부분 26
 
0.6%

점검일자
Real number (ℝ)

Distinct280
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20148129
Minimum20090113
Maximum20240314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.5 KiB
2024-05-04T02:50:04.383507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090113
5-th percentile20091102
Q120120427
median20150728
Q320180615
95-th percentile20211108
Maximum20240314
Range150201
Interquartile range (IQR)60188

Descriptive statistics

Standard deviation38261.592
Coefficient of variation (CV)0.0018990147
Kurtosis-0.82872759
Mean20148129
Median Absolute Deviation (MAD)30085
Skewness0.21146037
Sum9.0203172 × 1010
Variance1.4639494 × 109
MonotonicityNot monotonic
2024-05-04T02:50:04.845375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091102 179
 
4.0%
20091112 130
 
2.9%
20131016 111
 
2.5%
20130716 109
 
2.4%
20180518 108
 
2.4%
20170926 107
 
2.4%
20130923 91
 
2.0%
20090903 76
 
1.7%
20151012 76
 
1.7%
20181017 74
 
1.7%
Other values (270) 3416
76.3%
ValueCountFrequency (%)
20090113 15
 
0.3%
20090518 1
 
< 0.1%
20090521 5
 
0.1%
20090603 1
 
< 0.1%
20090617 2
 
< 0.1%
20090715 2
 
< 0.1%
20090720 29
 
0.6%
20090903 76
1.7%
20090909 26
 
0.6%
20091102 179
4.0%
ValueCountFrequency (%)
20240314 3
 
0.1%
20240308 1
 
< 0.1%
20240304 2
 
< 0.1%
20240226 1
 
< 0.1%
20240118 2
 
< 0.1%
20240117 2
 
< 0.1%
20231206 1
 
< 0.1%
20231124 1
 
< 0.1%
20231116 14
0.3%
20231115 21
0.5%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
수시
2172 
<NA>
1768 
기타
304 
일제
 
126
합동
 
107

Length

Max length4
Median length2
Mean length2.7898146
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수시 2172
48.5%
<NA> 1768
39.5%
기타 304
 
6.8%
일제 126
 
2.8%
합동 107
 
2.4%

Length

2024-05-04T02:50:05.385723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:50:05.834725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수시 2172
48.5%
na 1768
39.5%
기타 304
 
6.8%
일제 126
 
2.8%
합동 107
 
2.4%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size35.1 KiB
1
2656 
<NA>
1768 
2
 
53

Length

Max length4
Median length1
Mean length2.1847219
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2656
59.3%
<NA> 1768
39.5%
2 53
 
1.2%

Length

2024-05-04T02:50:06.248494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:50:06.635104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2656
59.3%
na 1768
39.5%
2 53
 
1.2%

(구)제조유통기한
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

(구)제조회사주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

부적합항목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4477
Missing (%)100.0%
Memory size39.5 KiB

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03230000105집단급식소<NA><NA><NA><NA>124-3-14-1기타서울잠신초등학교G0300000300000칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)야채 칼<NA><NA><NA>202403141.01<NA>20240314<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>20000115467<NA><NA><NA><NA><NA>서울특별시 송파구 잠실로 32, (잠실동)서울특별시 송파구 잠실동 22번지 10호02 412 3286<NA>20240314기타<NA>1<NA><NA><NA><NA>
13230000105집단급식소<NA><NA><NA><NA>124-3-14-2기타서울잠신초등학교G0300000300000칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)칼.도마 및 숟가락, 젓가락, 식기, 찬기 등 음식을 먹을 때 사용하거나 담는 것(사용 중인 것은 제외한다)야채 도마<NA><NA><NA>202403141.01<NA>20240314<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>20000115467<NA><NA><NA><NA><NA>서울특별시 송파구 잠실로 32, (잠실동)서울특별시 송파구 잠실동 22번지 10호02 412 3286<NA>20240314기타<NA>1<NA><NA><NA><NA>
23230000105집단급식소<NA><NA><NA><NA>124-3-14-3기타서울잠신초등학교G0100000100000조리식품 등조리식품 등돈까스<NA><NA><NA>202403141.0600g<NA>20240314<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240314<NA><NA><NA><NA><NA><NA><NA><NA>20000115467<NA><NA><NA><NA><NA>서울특별시 송파구 잠실로 32, (잠실동)서울특별시 송파구 잠실동 22번지 10호02 412 3286<NA>20240314기타<NA>1<NA><NA><NA><NA>
33230000106식품제조가공업<NA><NA><NA><NA>124-3-8검사용나정식품C0322020100000즉석섭취식품즉석섭취식품참치주먹밥<NA><NA><NA>202403086.0110g<NA>20240307<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240308<NA><NA><NA><NA><NA><NA><NA><NA>19940115343<NA><NA><NA><NA><NA>서울특별시 송파구 위례성대로6길 50, 지하1층 (방이동)서울특별시 송파구 방이동 146번지 4호<NA>수거20240308기타<NA>1<NA><NA><NA><NA>
43230000104휴게음식점<NA><NA><NA><NA>124-03-04-02검사용대중음악박물관 카페G0200000200000자가제조얼음자가제조얼음식용얼음(제빙기 얼음)<NA><NA><NA>202403041.0600g<NA>20240304<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240304<NA><NA><NA><NA><NA><NA><NA><NA>20180114257<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 300, 롯데월드몰 5층 (신천동)서울특별시 송파구 신천동 29번지 롯데월드타워앤드롯데월드몰<NA><NA>20240304<NA><NA><NA><NA><NA><NA><NA>
53230000101일반음식점<NA><NA><NA><NA>124-03-04-01검사용매트블랙커피(MATTE BLACK COFFEE)G0200000200000자가제조얼음자가제조얼음식용얼음(제빙기얼음)<NA><NA><NA>202403041.0600g<NA>20240304<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220240304<NA><NA><NA><NA><NA><NA><NA><NA>20230147942<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 300, 롯데월드타워앤드롯데월드몰 4층 (신천동)서울특별시 송파구 신천동 29번지 롯데월드타워앤드롯데월드몰<NA><NA>20240304<NA><NA><NA><NA><NA><NA><NA>
63230000101일반음식점<NA><NA><NA><NA>124-02-26-01검사용마라사부 마라탕F0100000300000폴리프로필렌폴리프로필렌포장용기<NA><NA>마라사부 마라탕 / 서울시 송파구 올림픽로30길 9, 엘루이시티 102호 (방이동)20240226<NA><NA><NA>포장용기 6EA20240226<NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120240226<NA><NA><NA><NA><NA><NA><NA><NA>20230147548<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로30길 9, 엘루이시티 102호 (방이동)서울특별시 송파구 방이동 28번지 2호 엘루이시티<NA>위생점검(전체)20240226기타<NA>1<NA><NA><NA><NA>
73230000114기타식품판매업<NA><NA><NA><NA>124-1-18-2검사용롯데쇼핑(주)롯데마트 월드타워점C0301010000000과자과자조청산자<NA><NA><NA>202401186.0220g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120240119<NA><NA><NA><NA><NA><NA><NA><NA>20140115393<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 300, (신천동, 엔터테인먼트동 지하2층 신선식품)서울특별시 송파구 신천동 29번지 엔터테인먼트동 지하2층 신선식품02 32132730위생점검(전체)20240118일제<NA>1<NA><NA><NA><NA>
83230000114기타식품판매업<NA><NA><NA><NA>124-1-18-1검사용롯데쇼핑(주)롯데마트 월드타워점C0301010000000과자과자호정가 조청유과<NA><NA><NA>202401186.0200g<NA><NA><NA><NA><NA>실온<NA><NA>1<NA>국내<NA>120240119<NA><NA><NA><NA><NA><NA><NA><NA>20140115393<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 300, (신천동, 엔터테인먼트동 지하2층 신선식품)서울특별시 송파구 신천동 29번지 엔터테인먼트동 지하2층 신선식품02 32132730위생점검(전체)20240118일제<NA>1<NA><NA><NA><NA>
93230000101일반음식점<NA><NA><NA><NA>124-01-17-02검사용왕빈자 삼파전G0100000100000조리식품 등조리식품 등해물파전<NA><NA>왕빈자 삼파전/서울시 송파구 풍성로26길 47, 상가동 1층 1,2호(풍납동, 송파해모로아파트)202401171.0600g<NA>20240117<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120240117<NA><NA><NA><NA><NA><NA><NA><NA>20180115418<NA><NA><NA><NA><NA>서울특별시 송파구 풍성로26길 47, 상가동 1층 1,2호 (풍납동, 송파해모로아파트)서울특별시 송파구 풍납동 512번지 송파해모로아파트<NA>위생점검(전체)20240117합동<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
44673230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과802000000빵또는떡류떡류절편<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44683230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과802000000빵또는떡류떡류무지개떡<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44693230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과201000000과자류강정(또는유과)매자과<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44703230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과802000000빵또는떡류떡류떡국떡<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44713230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과201000000과자류강정(또는유과)찹쌀유과<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44723230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과802000000빵또는떡류떡류기정떡<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44733230000114기타식품판매업<NA><NA><NA><NA><NA><NA>롯데쇼핑(주)롯데슈퍼잠실점205000000식육제품기타식육가공품잔치마을<NA><NA><NA>200901131.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20070115101<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 269, (신천동,잠실롯데캐슬내 상가B1)서울특별시 송파구 신천동 7번지 18호 잠실롯데캐슬내 상가B102 22035601수거20090113수시<NA>1<NA><NA><NA><NA>
44743230000114기타식품판매업<NA><NA><NA><NA><NA><NA>롯데쇼핑(주)롯데슈퍼잠실점801000000과자류과자한양종합선물세트<NA><NA><NA>200901131.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>20070115101<NA><NA><NA><NA><NA>서울특별시 송파구 올림픽로 269, (신천동,잠실롯데캐슬내 상가B1)서울특별시 송파구 신천동 7번지 18호 잠실롯데캐슬내 상가B102 22035601수거20090113수시<NA>1<NA><NA><NA><NA>
44753230000106식품제조가공업<NA><NA><NA><NA><NA><NA>전통한과802000000빵또는떡류떡류인절미<NA><NA><NA>200901133.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>19980114290<NA><NA><NA><NA><NA>서울특별시 송파구 송파대로40길 3-9, (송파동)서울특별시 송파구 송파동 90번지 4호02 4245746수거20090113수시<NA>1<NA><NA><NA><NA>
44763230000110식품등 수입판매업999<NA>2013 식품안전관리업무 추진계획<NA>124-12-9-1검사용(주)선명농수산829000000기타식품류땅콩또는견과류가공품튀김땅콩<NA><NA><NA>120112092.01.2KG<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>19990114211<NA><NA><NA><NA><NA>서울특별시 송파구 중대로 218, (가락동,신광빌딩 701호)서울특별시 송파구 가락동 160번지 8호 신광빌딩 701호0234018433위생점검(전체)20131209수시<NA>1<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드# duplicates
23230000112식품자동판매기영업<NA><NA><NA><NA><NA>경찰병원 상조회818000000음료류추출음료식품자동판매기물<NA><NA><NA>201007271.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA>20000115743서울특별시 송파구 송이로 123, (가락동)서울특별시 송파구 가락동 58번지 0호0234001120<NA>20100727<NA><NA>7
03230000104휴게음식점<NA><NA><NA><NA><NA>삼성테스코(주)홈플러스잠실점121000000식육류중육류<NA>한우등심<NA><NA><NA>201002043.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA><NA><NA>20070114936서울특별시 송파구 올림픽로35가길 16, (신천동,송파펀스타디움빌딩지하2층201호)서울특별시 송파구 신천동 7번지 12호 송파펀스타디움빌딩지하2층201호02 34688124<NA>20100204<NA><NA>2
13230000105집단급식소<NA><NA>2019 유통식품 수거검사 계획124-5-환경검체검사용서울버들초등학교X0100027900000환경오염도조사용환경오염도조사용6-신나라(박세연)의자<NA><NA><NA>20190515<NA><NA><NA>1개20190515<NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA>20070114978서울특별시 송파구 잠실로 62, (잠실동)서울특별시 송파구 잠실동 35번지02 22036416<NA>20190515<NA><NA>2
33230000114기타식품판매업<NA><NA><NA><NA><NA>다농산업(주)815000000면류국수남극곰표국수<NA><NA><NA>201010211.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA>19950114057<NA>서울특별시 송파구 가락동 산 600번지 0호02 4071171<NA>20101021<NA><NA>2
43230000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트월드점214000000조미식품고추가루하늘정성내리찬양념용고추가루<NA><NA><NA>20091102570.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980115040서울특별시 송파구 올림픽로 240, (잠실동,(롯데마그넷지하1층))서울특별시 송파구 잠실동 40번지 1호 (롯데마그넷지하1층)02 4118800수거20091102수시12
53230000114기타식품판매업<NA><NA><NA><NA><NA>롯데마트월드점214000000조미식품토마토케첩토마토케찹<NA><NA><NA>20091102900.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19980115040서울특별시 송파구 올림픽로 240, (잠실동,(롯데마그넷지하1층))서울특별시 송파구 잠실동 40번지 1호 (롯데마그넷지하1층)02 4118800수거20091102수시12
63230000114기타식품판매업<NA><NA><NA><NA><NA>엔씨송파점820000000장류된장마루코메 미소된장<NA><NA><NA>201012031.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA>20100114806<NA>서울특별시 송파구 문정동 516번지 라이프동1층02 21575000<NA>20101203<NA><NA>2
73230000114기타식품판매업<NA><NA><NA><NA><NA>엔씨송파점824000000젓갈류액젓까나리액젓<NA><NA><NA>201012031.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>국외<NA><NA><NA><NA>1<NA>20100114806<NA>서울특별시 송파구 문정동 516번지 라이프동1층02 21575000<NA>20101203<NA><NA>2