Overview

Dataset statistics

Number of variables61
Number of observations6291
Missing cells175105
Missing cells (%)45.6%
Duplicate rows10
Duplicate rows (%)0.2%
Total size in memory3.1 MiB
Average record size in memory520.0 B

Variable types

Categorical18
Numeric11
Unsupported15
Text17

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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-10993/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
부적합항목 has constant value ""Constant
Dataset has 10 (0.2%) duplicate rowsDuplicates
업종명 is highly imbalanced (61.1%)Imbalance
지도점검계획 is highly imbalanced (50.9%)Imbalance
수거계획 is highly imbalanced (89.6%)Imbalance
수거사유코드 is highly imbalanced (51.9%)Imbalance
수거량(자유) is highly imbalanced (94.7%)Imbalance
검사기관명 is highly imbalanced (51.7%)Imbalance
국가명 is highly imbalanced (85.7%)Imbalance
처리결과 is highly imbalanced (97.1%)Imbalance
계획구분명 has 6291 (100.0%) missing valuesMissing
수거증번호 has 831 (13.2%) missing valuesMissing
식품군 has 558 (8.9%) missing valuesMissing
품목명 has 124 (2.0%) missing valuesMissing
음식물명 has 6240 (99.2%) missing valuesMissing
원료명 has 6284 (99.9%) missing valuesMissing
생산업소 has 6123 (97.3%) missing valuesMissing
수거량(정량) has 256 (4.1%) missing valuesMissing
제품규격(정량) has 1032 (16.4%) missing valuesMissing
제조일자(일자) has 5321 (84.6%) missing valuesMissing
제조일자(롯트) has 6287 (99.9%) missing valuesMissing
유통기한(일자) has 6201 (98.6%) missing valuesMissing
유통기한(제조일기준) has 6242 (99.2%) missing valuesMissing
바코드번호 has 6291 (100.0%) missing valuesMissing
어린이기호식품유형 has 6291 (100.0%) missing valuesMissing
(구)제조사명 has 5470 (86.9%) missing valuesMissing
검사의뢰일자 has 3162 (50.3%) missing valuesMissing
결과회보일자 has 4690 (74.6%) missing valuesMissing
처리구분 has 6291 (100.0%) missing valuesMissing
수거검사구분코드 has 6291 (100.0%) missing valuesMissing
단속지역구분코드 has 6291 (100.0%) missing valuesMissing
수거장소구분코드 has 6291 (100.0%) missing valuesMissing
수거품처리 has 6291 (100.0%) missing valuesMissing
폐기일자 has 6291 (100.0%) missing valuesMissing
폐기량(kg) has 6291 (100.0%) missing valuesMissing
폐기금액(원) has 6291 (100.0%) missing valuesMissing
폐기장소 has 6291 (100.0%) missing valuesMissing
폐기방법 has 6291 (100.0%) missing valuesMissing
소재지(도로명) has 2902 (46.1%) missing valuesMissing
업소전화번호 has 427 (6.8%) missing valuesMissing
점검내용 has 6291 (100.0%) missing valuesMissing
(구)제조유통기한 has 6201 (98.6%) missing valuesMissing
(구)제조회사주소 has 6061 (96.3%) missing valuesMissing
부적합항목 has 6290 (> 99.9%) missing valuesMissing
기준치부적합내용 has 6291 (100.0%) missing valuesMissing
계획구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
바코드번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
어린이기호식품유형 is an unsupported type, check if it needs cleaning or further analysisUnsupported
처리구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거검사구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단속지역구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거장소구분코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수거품처리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기량(kg) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기금액(원) is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기장소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
점검내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기준치부적합내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:09:35.302532
Analysis finished2024-05-11 06:09:39.274949
Duration3.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
3100000
6291 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 6291
100.0%

Length

2024-05-11T15:09:39.418039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:39.626879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 6291
100.0%

업종코드
Real number (ℝ)

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.56144
Minimum101
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:39.793903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1114
median114
Q3114
95-th percentile114
Maximum134
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.5957574
Coefficient of variation (CV)0.04082888
Kurtosis5.4431841
Mean112.56144
Median Absolute Deviation (MAD)0
Skewness-0.091850728
Sum708124
Variance21.120986
MonotonicityIncreasing
2024-05-11T15:09:40.021450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
114 4934
78.4%
101 357
 
5.7%
105 288
 
4.6%
107 147
 
2.3%
106 134
 
2.1%
104 119
 
1.9%
112 91
 
1.4%
134 70
 
1.1%
109 67
 
1.1%
121 48
 
0.8%
Other values (2) 36
 
0.6%
ValueCountFrequency (%)
101 357
 
5.7%
104 119
 
1.9%
105 288
 
4.6%
106 134
 
2.1%
107 147
 
2.3%
109 67
 
1.1%
111 3
 
< 0.1%
112 91
 
1.4%
114 4934
78.4%
121 48
 
0.8%
ValueCountFrequency (%)
134 70
 
1.1%
122 33
 
0.5%
121 48
 
0.8%
114 4934
78.4%
112 91
 
1.4%
111 3
 
< 0.1%
109 67
 
1.1%
107 147
 
2.3%
106 134
 
2.1%
105 288
 
4.6%

업종명
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
기타식품판매업
4934 
일반음식점
 
357
집단급식소
 
288
즉석판매제조가공업
 
147
식품제조가공업
 
134
Other values (7)
 
431

Length

Max length11
Median length7
Mean length6.8564616
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 4934
78.4%
일반음식점 357
 
5.7%
집단급식소 288
 
4.6%
즉석판매제조가공업 147
 
2.3%
식품제조가공업 134
 
2.1%
휴게음식점 119
 
1.9%
식품자동판매기영업 91
 
1.4%
건강기능식품일반판매업 70
 
1.1%
식품소분업 67
 
1.1%
제과점영업 48
 
0.8%
Other values (2) 36
 
0.6%

Length

2024-05-11T15:09:40.250014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타식품판매업 4934
78.4%
일반음식점 357
 
5.7%
집단급식소 288
 
4.6%
즉석판매제조가공업 147
 
2.3%
식품제조가공업 134
 
2.1%
휴게음식점 119
 
1.9%
식품자동판매기영업 91
 
1.4%
건강기능식품일반판매업 70
 
1.1%
식품소분업 67
 
1.1%
제과점영업 48
 
0.8%
Other values (2) 36
 
0.6%
Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
3685 
999
1446 
2
972 
1
 
101
8
 
54

Length

Max length4
Median length4
Mean length3.2169766
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row7
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3685
58.6%
999 1446
 
23.0%
2 972
 
15.5%
1 101
 
1.6%
8 54
 
0.9%
7 33
 
0.5%

Length

2024-05-11T15:09:40.489248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:40.668438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3685
58.6%
999 1446
 
23.0%
2 972
 
15.5%
1 101
 
1.6%
8 54
 
0.9%
7 33
 
0.5%

계획구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

지도점검계획
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
3685 
부정불량식품관리
864 
시민다소비식품 수거검사
770 
시민다소비식품 수거
 
194
식품제조업소 등 지도점검
 
172
Other values (16)
606 

Length

Max length49
Median length4
Mean length6.5452233
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row서울시 민관 합동 위생점검
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3685
58.6%
부정불량식품관리 864
 
13.7%
시민다소비식품 수거검사 770
 
12.2%
시민다소비식품 수거 194
 
3.1%
식품제조업소 등 지도점검 172
 
2.7%
식중독 발생에 따른 원인조사 102
 
1.6%
민원업무처리 86
 
1.4%
집단급식소점검 81
 
1.3%
추석성수식품 수거검사 73
 
1.2%
원산지점검 56
 
0.9%
Other values (11) 208
 
3.3%

Length

2024-05-11T15:09:40.851057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3685
44.8%
시민다소비식품 964
 
11.7%
수거검사 871
 
10.6%
부정불량식품관리 864
 
10.5%
수거 194
 
2.4%
지도점검 174
 
2.1%
173
 
2.1%
식품제조업소 172
 
2.1%
식중독 103
 
1.3%
발생에 102
 
1.2%
Other values (33) 917
 
11.2%

수거계획
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
6039 
다소비식품 수거 검사
 
120
명절 성수식품 수거검사
 
63
2019년도 서울시 위생용품 지도점검 및 수거검사 계획
 
21
시민다소비식품수거검사
 
12
Other values (4)
 
36

Length

Max length30
Median length4
Mean length4.3476395
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6039
96.0%
다소비식품 수거 검사 120
 
1.9%
명절 성수식품 수거검사 63
 
1.0%
2019년도 서울시 위생용품 지도점검 및 수거검사 계획 21
 
0.3%
시민다소비식품수거검사 12
 
0.2%
식중독 원인조사 11
 
0.2%
다소비식품수거검사 11
 
0.2%
음식점 내 한우 수거검사 10
 
0.2%
다소비식품 수거검사 4
 
0.1%

Length

2024-05-11T15:09:41.043072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:41.223184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6039
88.4%
다소비식품 124
 
1.8%
수거 120
 
1.8%
검사 120
 
1.8%
수거검사 98
 
1.4%
명절 63
 
0.9%
성수식품 63
 
0.9%
계획 21
 
0.3%
21
 
0.3%
지도점검 21
 
0.3%
Other values (10) 138
 
2.0%

수거증번호
Text

MISSING 

Distinct2555
Distinct (%)46.8%
Missing831
Missing (%)13.2%
Memory size49.3 KiB
2024-05-11T15:09:41.916572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length7.8071429
Min length1

Characters and Unicode

Total characters42627
Distinct characters59
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1647 ?
Unique (%)30.2%

Sample

1st row7-7
2nd row110-6-5
3rd row6-19-2
4th row111-3-7
5th row111-3-8
ValueCountFrequency (%)
111-9-6 54
 
1.0%
111-6-41 20
 
0.4%
노원 16
 
0.3%
111-9-1 9
 
0.2%
111-9-3 9
 
0.2%
111-9-4 9
 
0.2%
111-9-2 9
 
0.2%
111-3-4 9
 
0.2%
111-9-19 8
 
0.1%
111-3-6 8
 
0.1%
Other values (2534) 5324
97.2%
2024-05-11T15:09:42.685869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17601
41.3%
- 10351
24.3%
2 2271
 
5.3%
0 1781
 
4.2%
3 1659
 
3.9%
4 1530
 
3.6%
6 1388
 
3.3%
7 1274
 
3.0%
9 1223
 
2.9%
5 1201
 
2.8%
Other values (49) 2348
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30956
72.6%
Dash Punctuation 10351
 
24.3%
Other Letter 1146
 
2.7%
Uppercase Letter 141
 
0.3%
Lowercase Letter 18
 
< 0.1%
Space Separator 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
350
30.5%
350
30.5%
76
 
6.6%
52
 
4.5%
39
 
3.4%
37
 
3.2%
27
 
2.4%
21
 
1.8%
21
 
1.8%
20
 
1.7%
Other values (28) 153
13.4%
Decimal Number
ValueCountFrequency (%)
1 17601
56.9%
2 2271
 
7.3%
0 1781
 
5.8%
3 1659
 
5.4%
4 1530
 
4.9%
6 1388
 
4.5%
7 1274
 
4.1%
9 1223
 
4.0%
5 1201
 
3.9%
8 1028
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
O 42
29.8%
I 33
23.4%
R 33
23.4%
L 15
 
10.6%
G 9
 
6.4%
M 9
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
o 6
33.3%
g 6
33.3%
m 6
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 10351
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41322
96.9%
Hangul 1146
 
2.7%
Latin 159
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
350
30.5%
350
30.5%
76
 
6.6%
52
 
4.5%
39
 
3.4%
37
 
3.2%
27
 
2.4%
21
 
1.8%
21
 
1.8%
20
 
1.7%
Other values (28) 153
13.4%
Common
ValueCountFrequency (%)
1 17601
42.6%
- 10351
25.0%
2 2271
 
5.5%
0 1781
 
4.3%
3 1659
 
4.0%
4 1530
 
3.7%
6 1388
 
3.4%
7 1274
 
3.1%
9 1223
 
3.0%
5 1201
 
2.9%
Other values (2) 1043
 
2.5%
Latin
ValueCountFrequency (%)
O 42
26.4%
I 33
20.8%
R 33
20.8%
L 15
 
9.4%
G 9
 
5.7%
M 9
 
5.7%
o 6
 
3.8%
g 6
 
3.8%
m 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41481
97.3%
Hangul 1138
 
2.7%
Compat Jamo 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17601
42.4%
- 10351
25.0%
2 2271
 
5.5%
0 1781
 
4.3%
3 1659
 
4.0%
4 1530
 
3.7%
6 1388
 
3.3%
7 1274
 
3.1%
9 1223
 
2.9%
5 1201
 
2.9%
Other values (11) 1202
 
2.9%
Hangul
ValueCountFrequency (%)
350
30.8%
350
30.8%
76
 
6.7%
52
 
4.6%
39
 
3.4%
37
 
3.3%
27
 
2.4%
21
 
1.8%
21
 
1.8%
20
 
1.8%
Other values (26) 145
12.7%
Compat Jamo
ValueCountFrequency (%)
6
75.0%
2
 
25.0%

수거사유코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
검사용
4056 
<NA>
1993 
기타
 
240
압류
 
1
증거용
 
1

Length

Max length4
Median length3
Mean length3.2784931
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
검사용 4056
64.5%
<NA> 1993
31.7%
기타 240
 
3.8%
압류 1
 
< 0.1%
증거용 1
 
< 0.1%

Length

2024-05-11T15:09:42.928392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:43.137891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사용 4056
64.5%
na 1993
31.7%
기타 240
 
3.8%
압류 1
 
< 0.1%
증거용 1
 
< 0.1%
Distinct461
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
2024-05-11T15:09:43.606762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length10.154189
Min length1

Characters and Unicode

Total characters63880
Distinct characters451
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)4.0%

Sample

1st row봉봉
2nd row제일콩집
3rd row제일콩집
4th row김가네
5th row김가네
ValueCountFrequency (%)
중계점 1129
 
13.2%
이마트월계점 1028
 
12.0%
롯데쇼핑(주)롯데마트 786
 
9.2%
홈플러스테스코(주)중계점 597
 
7.0%
홈플러스스토어즈(주)중계점 484
 
5.7%
주)gs리테일 354
 
4.1%
신세계이마트월계점 317
 
3.7%
상계점 297
 
3.5%
주)세이브존아이앤씨 198
 
2.3%
이천일아울렛 161
 
1.9%
Other values (519) 3189
37.3%
2024-05-11T15:09:44.382978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4666
 
7.3%
4656
 
7.3%
( 3077
 
4.8%
) 3077
 
4.8%
3045
 
4.8%
2780
 
4.4%
2779
 
4.4%
2723
 
4.3%
2620
 
4.1%
2491
 
3.9%
Other values (441) 31966
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54319
85.0%
Open Punctuation 3077
 
4.8%
Close Punctuation 3077
 
4.8%
Space Separator 2250
 
3.5%
Uppercase Letter 767
 
1.2%
Decimal Number 346
 
0.5%
Lowercase Letter 26
 
< 0.1%
Other Punctuation 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4666
 
8.6%
4656
 
8.6%
3045
 
5.6%
2780
 
5.1%
2779
 
5.1%
2723
 
5.0%
2620
 
4.8%
2491
 
4.6%
1901
 
3.5%
1778
 
3.3%
Other values (406) 24880
45.8%
Uppercase Letter
ValueCountFrequency (%)
G 371
48.4%
S 357
46.5%
C 16
 
2.1%
N 13
 
1.7%
F 3
 
0.4%
K 3
 
0.4%
M 1
 
0.1%
T 1
 
0.1%
A 1
 
0.1%
L 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
b 6
23.1%
m 4
15.4%
o 4
15.4%
u 3
11.5%
s 2
 
7.7%
e 2
 
7.7%
g 2
 
7.7%
a 1
 
3.8%
t 1
 
3.8%
r 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 129
37.3%
3 69
19.9%
5 69
19.9%
6 66
19.1%
2 4
 
1.2%
9 3
 
0.9%
0 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 11
61.1%
. 4
 
22.2%
& 3
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 3077
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3077
100.0%
Space Separator
ValueCountFrequency (%)
2250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54315
85.0%
Common 8768
 
13.7%
Latin 793
 
1.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4666
 
8.6%
4656
 
8.6%
3045
 
5.6%
2780
 
5.1%
2779
 
5.1%
2723
 
5.0%
2620
 
4.8%
2491
 
4.6%
1901
 
3.5%
1778
 
3.3%
Other values (402) 24876
45.8%
Latin
ValueCountFrequency (%)
G 371
46.8%
S 357
45.0%
C 16
 
2.0%
N 13
 
1.6%
b 6
 
0.8%
m 4
 
0.5%
o 4
 
0.5%
F 3
 
0.4%
u 3
 
0.4%
K 3
 
0.4%
Other values (10) 13
 
1.6%
Common
ValueCountFrequency (%)
( 3077
35.1%
) 3077
35.1%
2250
25.7%
1 129
 
1.5%
3 69
 
0.8%
5 69
 
0.8%
6 66
 
0.8%
, 11
 
0.1%
. 4
 
< 0.1%
2 4
 
< 0.1%
Other values (5) 12
 
0.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54315
85.0%
ASCII 9561
 
15.0%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4666
 
8.6%
4656
 
8.6%
3045
 
5.6%
2780
 
5.1%
2779
 
5.1%
2723
 
5.0%
2620
 
4.8%
2491
 
4.6%
1901
 
3.5%
1778
 
3.3%
Other values (402) 24876
45.8%
ASCII
ValueCountFrequency (%)
( 3077
32.2%
) 3077
32.2%
2250
23.5%
G 371
 
3.9%
S 357
 
3.7%
1 129
 
1.3%
3 69
 
0.7%
5 69
 
0.7%
6 66
 
0.7%
C 16
 
0.2%
Other values (25) 80
 
0.8%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct366
Distinct (%)5.9%
Missing37
Missing (%)0.6%
Memory size49.3 KiB
2024-05-11T15:09:44.744247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length10.753917
Min length1

Characters and Unicode

Total characters67255
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

Unique92 ?
Unique (%)1.5%

Sample

1st row827000000
2nd row600000000
3rd rowG0100000100000
4th row829000000
5th row829000000
ValueCountFrequency (%)
c01000000 414
 
6.7%
g0100000100000 325
 
5.3%
821000000 322
 
5.2%
829000000 312
 
5.1%
801000000 275
 
4.5%
803000000 208
 
3.4%
818000000 178
 
2.9%
816000000 173
 
2.8%
802000000 165
 
2.7%
830000000 151
 
2.5%
Other values (354) 3625
59.0%
2024-05-11T15:09:45.345095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46890
69.7%
1 6094
 
9.1%
8 3307
 
4.9%
2 3145
 
4.7%
C 2018
 
3.0%
3 1667
 
2.5%
9 740
 
1.1%
4 638
 
0.9%
6 568
 
0.8%
5 556
 
0.8%
Other values (10) 1632
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64007
95.2%
Uppercase Letter 2710
 
4.0%
Space Separator 538
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46890
73.3%
1 6094
 
9.5%
8 3307
 
5.2%
2 3145
 
4.9%
3 1667
 
2.6%
9 740
 
1.2%
4 638
 
1.0%
6 568
 
0.9%
5 556
 
0.9%
7 402
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 2018
74.5%
G 380
 
14.0%
B 96
 
3.5%
E 55
 
2.0%
H 42
 
1.5%
X 41
 
1.5%
A 40
 
1.5%
F 22
 
0.8%
Z 16
 
0.6%
Space Separator
ValueCountFrequency (%)
538
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64545
96.0%
Latin 2710
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46890
72.6%
1 6094
 
9.4%
8 3307
 
5.1%
2 3145
 
4.9%
3 1667
 
2.6%
9 740
 
1.1%
4 638
 
1.0%
6 568
 
0.9%
5 556
 
0.9%
538
 
0.8%
Latin
ValueCountFrequency (%)
C 2018
74.5%
G 380
 
14.0%
B 96
 
3.5%
E 55
 
2.0%
H 42
 
1.5%
X 41
 
1.5%
A 40
 
1.5%
F 22
 
0.8%
Z 16
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46890
69.7%
1 6094
 
9.1%
8 3307
 
4.9%
2 3145
 
4.7%
C 2018
 
3.0%
3 1667
 
2.5%
9 740
 
1.1%
4 638
 
0.9%
6 568
 
0.8%
5 556
 
0.8%
Other values (10) 1632
 
2.4%

식품군
Text

MISSING 

Distinct287
Distinct (%)5.0%
Missing558
Missing (%)8.9%
Memory size49.3 KiB
2024-05-11T15:09:45.934318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length20
Mean length4.8041165
Min length1

Characters and Unicode

Total characters27542
Distinct characters303
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

Unique72 ?
Unique (%)1.3%

Sample

1st row주류
2nd row식품접객업
3rd row조리식품 등
4th row기타식품류
5th row기타식품류
ValueCountFrequency (%)
과자류 429
 
6.5%
기타식품류 408
 
6.2%
조미식품 369
 
5.6%
356
 
5.4%
조리식품 325
 
4.9%
코코아가공품류또는초콜릿류 208
 
3.2%
다류 202
 
3.1%
음료류 191
 
2.9%
빵또는떡류 165
 
2.5%
커피 153
 
2.3%
Other values (306) 3786
57.4%
2024-05-11T15:09:46.801536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3019
 
11.0%
2248
 
8.2%
1877
 
6.8%
868
 
3.2%
859
 
3.1%
851
 
3.1%
847
 
3.1%
764
 
2.8%
691
 
2.5%
659
 
2.4%
Other values (293) 14859
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26178
95.0%
Space Separator 859
 
3.1%
Other Punctuation 187
 
0.7%
Open Punctuation 109
 
0.4%
Close Punctuation 109
 
0.4%
Uppercase Letter 58
 
0.2%
Decimal Number 25
 
0.1%
Dash Punctuation 10
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3019
 
11.5%
2248
 
8.6%
1877
 
7.2%
868
 
3.3%
851
 
3.3%
847
 
3.2%
764
 
2.9%
691
 
2.6%
659
 
2.5%
572
 
2.2%
Other values (264) 13782
52.6%
Uppercase Letter
ValueCountFrequency (%)
E 14
24.1%
A 11
19.0%
C 10
17.2%
D 9
15.5%
P 5
 
8.6%
H 5
 
8.6%
B 3
 
5.2%
S 1
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
l 1
14.3%
r 1
14.3%
i 1
14.3%
n 1
14.3%
e 1
14.3%
t 1
14.3%
o 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 9
36.0%
3 9
36.0%
2 4
16.0%
0 1
 
4.0%
9 1
 
4.0%
4 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 94
50.3%
, 73
39.0%
/ 15
 
8.0%
? 5
 
2.7%
Space Separator
ValueCountFrequency (%)
859
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26178
95.0%
Common 1299
 
4.7%
Latin 65
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3019
 
11.5%
2248
 
8.6%
1877
 
7.2%
868
 
3.3%
851
 
3.3%
847
 
3.2%
764
 
2.9%
691
 
2.6%
659
 
2.5%
572
 
2.2%
Other values (264) 13782
52.6%
Latin
ValueCountFrequency (%)
E 14
21.5%
A 11
16.9%
C 10
15.4%
D 9
13.8%
P 5
 
7.7%
H 5
 
7.7%
B 3
 
4.6%
l 1
 
1.5%
r 1
 
1.5%
S 1
 
1.5%
Other values (5) 5
 
7.7%
Common
ValueCountFrequency (%)
859
66.1%
( 109
 
8.4%
) 109
 
8.4%
. 94
 
7.2%
, 73
 
5.6%
/ 15
 
1.2%
- 10
 
0.8%
1 9
 
0.7%
3 9
 
0.7%
? 5
 
0.4%
Other values (4) 7
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26178
95.0%
ASCII 1364
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3019
 
11.5%
2248
 
8.6%
1877
 
7.2%
868
 
3.3%
851
 
3.3%
847
 
3.2%
764
 
2.9%
691
 
2.6%
659
 
2.5%
572
 
2.2%
Other values (264) 13782
52.6%
ASCII
ValueCountFrequency (%)
859
63.0%
( 109
 
8.0%
) 109
 
8.0%
. 94
 
6.9%
, 73
 
5.4%
/ 15
 
1.1%
E 14
 
1.0%
A 11
 
0.8%
- 10
 
0.7%
C 10
 
0.7%
Other values (19) 60
 
4.4%

품목명
Text

MISSING 

Distinct403
Distinct (%)6.5%
Missing124
Missing (%)2.0%
Memory size49.3 KiB
2024-05-11T15:09:47.250173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length22
Mean length4.7760662
Min length1

Characters and Unicode

Total characters29454
Distinct characters349
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

Unique106 ?
Unique (%)1.7%

Sample

1st row맥주
2nd row접객업소조리식품등
3rd row조리식품 등
4th row즉석섭취식품
5th row즉석섭취식품
ValueCountFrequency (%)
432
 
5.9%
조리식품 402
 
5.5%
소스류 225
 
3.1%
과자 220
 
3.0%
즉석조리식품 145
 
2.0%
초콜릿가공품 131
 
1.8%
기타가공품 131
 
1.8%
곡류가공품 130
 
1.8%
빵류 122
 
1.7%
고형차 111
 
1.5%
Other values (423) 5232
71.9%
2024-05-11T15:09:47.962605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1597
 
5.4%
1537
 
5.2%
1114
 
3.8%
1035
 
3.5%
992
 
3.4%
924
 
3.1%
863
 
2.9%
844
 
2.9%
745
 
2.5%
724
 
2.5%
Other values (339) 19079
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27077
91.9%
Space Separator 1114
 
3.8%
Other Punctuation 378
 
1.3%
Close Punctuation 377
 
1.3%
Open Punctuation 377
 
1.3%
Uppercase Letter 78
 
0.3%
Decimal Number 28
 
0.1%
Dash Punctuation 18
 
0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1597
 
5.9%
1537
 
5.7%
1035
 
3.8%
992
 
3.7%
924
 
3.4%
863
 
3.2%
844
 
3.1%
745
 
2.8%
724
 
2.7%
679
 
2.5%
Other values (309) 17137
63.3%
Uppercase Letter
ValueCountFrequency (%)
E 16
20.5%
C 15
19.2%
A 15
19.2%
D 11
14.1%
P 7
9.0%
H 7
9.0%
L 3
 
3.8%
B 3
 
3.8%
S 1
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
i 1
14.3%
n 1
14.3%
e 1
14.3%
t 1
14.3%
r 1
14.3%
o 1
14.3%
l 1
14.3%
Decimal Number
ValueCountFrequency (%)
3 11
39.3%
1 10
35.7%
2 4
 
14.3%
0 1
 
3.6%
9 1
 
3.6%
4 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 245
64.8%
, 106
28.0%
/ 15
 
4.0%
? 12
 
3.2%
Space Separator
ValueCountFrequency (%)
1114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 377
100.0%
Open Punctuation
ValueCountFrequency (%)
( 377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27077
91.9%
Common 2292
 
7.8%
Latin 85
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1597
 
5.9%
1537
 
5.7%
1035
 
3.8%
992
 
3.7%
924
 
3.4%
863
 
3.2%
844
 
3.1%
745
 
2.8%
724
 
2.7%
679
 
2.5%
Other values (309) 17137
63.3%
Latin
ValueCountFrequency (%)
E 16
18.8%
C 15
17.6%
A 15
17.6%
D 11
12.9%
P 7
8.2%
H 7
8.2%
L 3
 
3.5%
B 3
 
3.5%
S 1
 
1.2%
i 1
 
1.2%
Other values (6) 6
 
7.1%
Common
ValueCountFrequency (%)
1114
48.6%
) 377
 
16.4%
( 377
 
16.4%
. 245
 
10.7%
, 106
 
4.6%
- 18
 
0.8%
/ 15
 
0.7%
? 12
 
0.5%
3 11
 
0.5%
1 10
 
0.4%
Other values (4) 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27077
91.9%
ASCII 2377
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1597
 
5.9%
1537
 
5.7%
1035
 
3.8%
992
 
3.7%
924
 
3.4%
863
 
3.2%
844
 
3.1%
745
 
2.8%
724
 
2.7%
679
 
2.5%
Other values (309) 17137
63.3%
ASCII
ValueCountFrequency (%)
1114
46.9%
) 377
 
15.9%
( 377
 
15.9%
. 245
 
10.3%
, 106
 
4.5%
- 18
 
0.8%
E 16
 
0.7%
/ 15
 
0.6%
C 15
 
0.6%
A 15
 
0.6%
Other values (20) 79
 
3.3%
Distinct4883
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
2024-05-11T15:09:48.447924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length7.721189
Min length1

Characters and Unicode

Total characters48574
Distinct characters943
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4191 ?
Unique (%)66.6%

Sample

1st row맥주
2nd row콩국수육수
3rd row콩국물
4th row참치김밥
5th row쇠고기김밥
ValueCountFrequency (%)
청정원 89
 
0.9%
오뚜기 73
 
0.7%
백설 70
 
0.7%
부침가루 48
 
0.5%
커피 45
 
0.4%
등심 42
 
0.4%
홈플러스 42
 
0.4%
유기농 39
 
0.4%
초콜릿 35
 
0.3%
두부 34
 
0.3%
Other values (5423) 9605
94.9%
2024-05-11T15:09:49.495818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3853
 
7.9%
1094
 
2.3%
881
 
1.8%
872
 
1.8%
729
 
1.5%
493
 
1.0%
484
 
1.0%
481
 
1.0%
464
 
1.0%
451
 
0.9%
Other values (933) 38772
79.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41508
85.5%
Space Separator 3853
 
7.9%
Uppercase Letter 1051
 
2.2%
Decimal Number 845
 
1.7%
Lowercase Letter 450
 
0.9%
Open Punctuation 262
 
0.5%
Close Punctuation 260
 
0.5%
Other Punctuation 222
 
0.5%
Dash Punctuation 117
 
0.2%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1094
 
2.6%
881
 
2.1%
872
 
2.1%
729
 
1.8%
493
 
1.2%
484
 
1.2%
481
 
1.2%
464
 
1.1%
451
 
1.1%
413
 
1.0%
Other values (857) 35146
84.7%
Uppercase Letter
ValueCountFrequency (%)
E 94
 
8.9%
A 88
 
8.4%
R 72
 
6.9%
I 69
 
6.6%
O 69
 
6.6%
T 64
 
6.1%
C 62
 
5.9%
S 55
 
5.2%
N 54
 
5.1%
L 50
 
4.8%
Other values (16) 374
35.6%
Lowercase Letter
ValueCountFrequency (%)
p 54
12.0%
m 54
12.0%
a 51
11.3%
e 45
10.0%
s 39
8.7%
l 31
 
6.9%
i 28
 
6.2%
u 26
 
5.8%
o 23
 
5.1%
c 17
 
3.8%
Other values (12) 82
18.2%
Other Punctuation
ValueCountFrequency (%)
% 54
24.3%
& 45
20.3%
, 33
14.9%
; 22
9.9%
. 17
 
7.7%
/ 16
 
7.2%
13
 
5.9%
* 12
 
5.4%
? 7
 
3.2%
! 1
 
0.5%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 308
36.4%
0 228
27.0%
3 107
 
12.7%
2 70
 
8.3%
5 45
 
5.3%
4 26
 
3.1%
6 21
 
2.5%
7 17
 
2.0%
9 16
 
1.9%
8 7
 
0.8%
Space Separator
ValueCountFrequency (%)
3853
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Close Punctuation
ValueCountFrequency (%)
) 260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41493
85.4%
Common 5563
 
11.5%
Latin 1503
 
3.1%
Han 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1094
 
2.6%
881
 
2.1%
872
 
2.1%
729
 
1.8%
493
 
1.2%
484
 
1.2%
481
 
1.2%
464
 
1.1%
451
 
1.1%
413
 
1.0%
Other values (845) 35131
84.7%
Latin
ValueCountFrequency (%)
E 94
 
6.3%
A 88
 
5.9%
R 72
 
4.8%
I 69
 
4.6%
O 69
 
4.6%
T 64
 
4.3%
C 62
 
4.1%
S 55
 
3.7%
N 54
 
3.6%
p 54
 
3.6%
Other values (39) 822
54.7%
Common
ValueCountFrequency (%)
3853
69.3%
1 308
 
5.5%
( 262
 
4.7%
) 260
 
4.7%
0 228
 
4.1%
- 117
 
2.1%
3 107
 
1.9%
2 70
 
1.3%
% 54
 
1.0%
5 45
 
0.8%
Other values (17) 259
 
4.7%
Han
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41492
85.4%
ASCII 7050
 
14.5%
CJK 15
 
< 0.1%
None 14
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3853
54.7%
1 308
 
4.4%
( 262
 
3.7%
) 260
 
3.7%
0 228
 
3.2%
- 117
 
1.7%
3 107
 
1.5%
E 94
 
1.3%
A 88
 
1.2%
R 72
 
1.0%
Other values (63) 1661
23.6%
Hangul
ValueCountFrequency (%)
1094
 
2.6%
881
 
2.1%
872
 
2.1%
729
 
1.8%
493
 
1.2%
484
 
1.2%
481
 
1.2%
464
 
1.1%
451
 
1.1%
413
 
1.0%
Other values (844) 35130
84.7%
None
ValueCountFrequency (%)
13
92.9%
1
 
7.1%
CJK
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
Other values (2) 2
13.3%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

음식물명
Text

MISSING 

Distinct47
Distinct (%)92.2%
Missing6240
Missing (%)99.2%
Memory size49.3 KiB
2024-05-11T15:09:49.808030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.5686275
Min length1

Characters and Unicode

Total characters233
Distinct characters116
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

Unique43 ?
Unique (%)84.3%

Sample

1st row전(해물빈대떡)
2nd row전(파전)
3rd row전(해물파전)
4th row수육 (개고기)
5th row우엉김밥
ValueCountFrequency (%)
배추김치 2
 
3.8%
우유 2
 
3.8%
햄버거 2
 
3.8%
잡곡밥 2
 
3.8%
화장실수도꼭지4 1
 
1.9%
버섯국 1
 
1.9%
깍두기 1
 
1.9%
물미역무침 1
 
1.9%
청경채나물 1
 
1.9%
돈폭찹 1
 
1.9%
Other values (38) 38
73.1%
2024-05-11T15:09:50.317684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
3.0%
7
 
3.0%
7
 
3.0%
6
 
2.6%
6
 
2.6%
6
 
2.6%
6
 
2.6%
) 6
 
2.6%
( 6
 
2.6%
5
 
2.1%
Other values (106) 171
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215
92.3%
Close Punctuation 6
 
2.6%
Open Punctuation 6
 
2.6%
Decimal Number 5
 
2.1%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.8%
6
 
2.8%
6
 
2.8%
6
 
2.8%
5
 
2.3%
5
 
2.3%
5
 
2.3%
Other values (98) 155
72.1%
Decimal Number
ValueCountFrequency (%)
2 1
20.0%
1 1
20.0%
5 1
20.0%
3 1
20.0%
4 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215
92.3%
Common 18
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.8%
6
 
2.8%
6
 
2.8%
6
 
2.8%
5
 
2.3%
5
 
2.3%
5
 
2.3%
Other values (98) 155
72.1%
Common
ValueCountFrequency (%)
) 6
33.3%
( 6
33.3%
2 1
 
5.6%
1 1
 
5.6%
5 1
 
5.6%
3 1
 
5.6%
4 1
 
5.6%
1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215
92.3%
ASCII 18
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.8%
6
 
2.8%
6
 
2.8%
6
 
2.8%
5
 
2.3%
5
 
2.3%
5
 
2.3%
Other values (98) 155
72.1%
ASCII
ValueCountFrequency (%)
) 6
33.3%
( 6
33.3%
2 1
 
5.6%
1 1
 
5.6%
5 1
 
5.6%
3 1
 
5.6%
4 1
 
5.6%
1
 
5.6%

원료명
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing6284
Missing (%)99.9%
Memory size49.3 KiB
2024-05-11T15:09:50.543530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.4285714
Min length3

Characters and Unicode

Total characters24
Distinct characters19
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

Unique5 ?
Unique (%)71.4%

Sample

1st row개고기
2nd row수족관물
3rd row생선살
4th row닭고기
5th row식용유
ValueCountFrequency (%)
식용유 2
28.6%
개고기 1
14.3%
수족관물 1
14.3%
생선살 1
14.3%
닭고기 1
14.3%
콩(국산 1
14.3%
2024-05-11T15:09:51.043373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
( 1
 
4.2%
1
 
4.2%
Other values (9) 9
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
91.7%
Open Punctuation 1
 
4.2%
Close Punctuation 1
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (7) 7
31.8%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
91.7%
Common 2
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (7) 7
31.8%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
91.7%
ASCII 2
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (7) 7
31.8%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

생산업소
Text

MISSING 

Distinct83
Distinct (%)49.4%
Missing6123
Missing (%)97.3%
Memory size49.3 KiB
2024-05-11T15:09:51.460641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length14.130952
Min length2

Characters and Unicode

Total characters2374
Distinct characters207
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)34.5%

Sample

1st row풍운
2nd row새벽바다오징어축제
3rd row속초세꼬시
4th row호남영양탕
5th row양푼비빔밥
ValueCountFrequency (%)
공릉로34길 34
 
8.6%
62 34
 
8.6%
태강아파트 34
 
8.6%
광운로1길 29
 
7.3%
24(월계동 29
 
7.3%
2,3층(공릉동 29
 
7.3%
관리사무소 22
 
5.6%
관리사무소동 12
 
3.0%
롯데리아 6
 
1.5%
파스타가든 5
 
1.3%
Other values (115) 161
40.8%
2024-05-11T15:09:52.073016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
227
 
9.6%
2 110
 
4.6%
, 108
 
4.5%
98
 
4.1%
( 80
 
3.4%
) 80
 
3.4%
79
 
3.3%
3 77
 
3.2%
76
 
3.2%
74
 
3.1%
Other values (197) 1365
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1500
63.2%
Decimal Number 375
 
15.8%
Space Separator 227
 
9.6%
Other Punctuation 111
 
4.7%
Open Punctuation 80
 
3.4%
Close Punctuation 80
 
3.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
98
 
6.5%
79
 
5.3%
76
 
5.1%
74
 
4.9%
70
 
4.7%
48
 
3.2%
45
 
3.0%
43
 
2.9%
42
 
2.8%
40
 
2.7%
Other values (181) 885
59.0%
Decimal Number
ValueCountFrequency (%)
2 110
29.3%
3 77
20.5%
4 65
17.3%
1 54
14.4%
6 37
 
9.9%
8 12
 
3.2%
0 7
 
1.9%
7 6
 
1.6%
9 4
 
1.1%
5 3
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 108
97.3%
/ 3
 
2.7%
Space Separator
ValueCountFrequency (%)
227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1500
63.2%
Common 874
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
98
 
6.5%
79
 
5.3%
76
 
5.1%
74
 
4.9%
70
 
4.7%
48
 
3.2%
45
 
3.0%
43
 
2.9%
42
 
2.8%
40
 
2.7%
Other values (181) 885
59.0%
Common
ValueCountFrequency (%)
227
26.0%
2 110
12.6%
, 108
12.4%
( 80
 
9.2%
) 80
 
9.2%
3 77
 
8.8%
4 65
 
7.4%
1 54
 
6.2%
6 37
 
4.2%
8 12
 
1.4%
Other values (6) 24
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1500
63.2%
ASCII 874
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227
26.0%
2 110
12.6%
, 108
12.4%
( 80
 
9.2%
) 80
 
9.2%
3 77
 
8.8%
4 65
 
7.4%
1 54
 
6.2%
6 37
 
4.2%
8 12
 
1.4%
Other values (6) 24
 
2.7%
Hangul
ValueCountFrequency (%)
98
 
6.5%
79
 
5.3%
76
 
5.1%
74
 
4.9%
70
 
4.7%
48
 
3.2%
45
 
3.0%
43
 
2.9%
42
 
2.8%
40
 
2.7%
Other values (181) 885
59.0%

수거일자
Real number (ℝ)

Distinct330
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20140966
Minimum20011118
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:52.277198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011118
5-th percentile20080307
Q120110719
median20130829
Q320170912
95-th percentile20211027
Maximum20240315
Range229197
Interquartile range (IQR)60193

Descriptive statistics

Standard deviation41297.105
Coefficient of variation (CV)0.0020504034
Kurtosis-0.63072059
Mean20140966
Median Absolute Deviation (MAD)29798
Skewness0.3485298
Sum1.2670682 × 1011
Variance1.7054509 × 109
MonotonicityNot monotonic
2024-05-11T15:09:52.445669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160224 194
 
3.1%
20110719 97
 
1.5%
20130610 93
 
1.5%
20130212 92
 
1.5%
20110831 88
 
1.4%
20150831 86
 
1.4%
20111017 86
 
1.4%
20140324 86
 
1.4%
20130724 82
 
1.3%
20151110 82
 
1.3%
Other values (320) 5305
84.3%
ValueCountFrequency (%)
20011118 6
 
0.1%
20070517 12
 
0.2%
20070518 3
 
< 0.1%
20070709 7
 
0.1%
20070710 6
 
0.1%
20070711 5
 
0.1%
20070713 7
 
0.1%
20070912 63
1.0%
20070927 10
 
0.2%
20071004 8
 
0.1%
ValueCountFrequency (%)
20240315 29
0.5%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240111 2
 
< 0.1%
20231204 20
0.3%
20231127 34
0.5%
20231116 1
 
< 0.1%
20231107 1
 
< 0.1%
20231030 39
0.6%
20231026 3
 
< 0.1%

수거량(정량)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)0.7%
Missing256
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean9.365203
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:52.621447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q36
95-th percentile7
Maximum1000
Range999
Interquartile range (IQR)4

Descriptive statistics

Standard deviation54.454427
Coefficient of variation (CV)5.8145485
Kurtosis103.95457
Mean9.365203
Median Absolute Deviation (MAD)2
Skewness9.9514399
Sum56519
Variance2965.2846
MonotonicityNot monotonic
2024-05-11T15:09:52.807101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1463
23.3%
3 1353
21.5%
6 1176
18.7%
2 1028
16.3%
4 415
 
6.6%
5 233
 
3.7%
7 96
 
1.5%
10 60
 
1.0%
8 51
 
0.8%
500 29
 
0.5%
Other values (31) 131
 
2.1%
(Missing) 256
 
4.1%
ValueCountFrequency (%)
1 1463
23.3%
2 1028
16.3%
3 1353
21.5%
4 415
 
6.6%
5 233
 
3.7%
6 1176
18.7%
7 96
 
1.5%
8 51
 
0.8%
9 17
 
0.3%
10 60
 
1.0%
ValueCountFrequency (%)
1000 1
 
< 0.1%
600 24
0.4%
500 29
0.5%
350 4
 
0.1%
320 1
 
< 0.1%
300 5
 
0.1%
200 3
 
< 0.1%
150 1
 
< 0.1%
125 1
 
< 0.1%
100 21
0.3%

제품규격(정량)
Text

MISSING 

Distinct560
Distinct (%)10.6%
Missing1032
Missing (%)16.4%
Memory size49.3 KiB
2024-05-11T15:09:53.334754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0095075
Min length1

Characters and Unicode

Total characters15827
Distinct characters21
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

Unique255 ?
Unique (%)4.8%

Sample

1st rowl
2nd row1000
3rd row1
4th row100g
5th row100g
ValueCountFrequency (%)
1 377
 
7.2%
300 310
 
5.9%
100 280
 
5.3%
600 276
 
5.2%
500 260
 
4.9%
150 210
 
4.0%
200 173
 
3.3%
400 125
 
2.4%
900 89
 
1.7%
180 84
 
1.6%
Other values (549) 3075
58.5%
2024-05-11T15:09:54.054803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6015
38.0%
1 1894
 
12.0%
5 1588
 
10.0%
2 1276
 
8.1%
3 985
 
6.2%
g 883
 
5.6%
4 669
 
4.2%
6 663
 
4.2%
8 478
 
3.0%
7 377
 
2.4%
Other values (11) 999
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14290
90.3%
Lowercase Letter 1396
 
8.8%
Other Punctuation 124
 
0.8%
Other Letter 16
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6015
42.1%
1 1894
 
13.3%
5 1588
 
11.1%
2 1276
 
8.9%
3 985
 
6.9%
4 669
 
4.7%
6 663
 
4.6%
8 478
 
3.3%
7 377
 
2.6%
9 345
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
g 883
63.3%
l 252
 
18.1%
m 245
 
17.6%
k 14
 
1.0%
c 2
 
0.1%
Other Letter
ValueCountFrequency (%)
11
68.8%
2
 
12.5%
2
 
12.5%
1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 124
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14414
91.1%
Latin 1397
 
8.8%
Hangul 16
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6015
41.7%
1 1894
 
13.1%
5 1588
 
11.0%
2 1276
 
8.9%
3 985
 
6.8%
4 669
 
4.6%
6 663
 
4.6%
8 478
 
3.3%
7 377
 
2.6%
9 345
 
2.4%
Latin
ValueCountFrequency (%)
g 883
63.2%
l 252
 
18.0%
m 245
 
17.5%
k 14
 
1.0%
c 2
 
0.1%
L 1
 
0.1%
Hangul
ValueCountFrequency (%)
11
68.8%
2
 
12.5%
2
 
12.5%
1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15811
99.9%
Hangul 15
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6015
38.0%
1 1894
 
12.0%
5 1588
 
10.0%
2 1276
 
8.1%
3 985
 
6.2%
g 883
 
5.6%
4 669
 
4.2%
6 663
 
4.2%
8 478
 
3.0%
7 377
 
2.4%
Other values (7) 983
 
6.2%
Hangul
ValueCountFrequency (%)
11
73.3%
2
 
13.3%
2
 
13.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

단위(정량)
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
g
3127 
<NA>
2190 
ML
506 
KG
386 
LT
 
72
Other values (2)
 
10

Length

Max length4
Median length2
Mean length2.1977428
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
g 3127
49.7%
<NA> 2190
34.8%
ML 506
 
8.0%
KG 386
 
6.1%
LT 72
 
1.1%
9
 
0.1%
mm 1
 
< 0.1%

Length

2024-05-11T15:09:54.261141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:54.446998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 3127
49.7%
na 2190
34.8%
ml 506
 
8.0%
kg 386
 
6.1%
lt 72
 
1.1%
9
 
0.1%
mm 1
 
< 0.1%

수거량(자유)
Categorical

IMBALANCE 

Distinct39
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
6127 
1개
 
36
600g
 
24
6개
 
16
swap*2개
 
13
Other values (34)
 
75

Length

Max length16
Median length4
Mean length4.0082658
Min length1

Unique

Unique17 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6127
97.4%
1개 36
 
0.6%
600g 24
 
0.4%
6개 16
 
0.3%
swap*2개 13
 
0.2%
1 10
 
0.2%
1인분 9
 
0.1%
swap*1개 5
 
0.1%
600그램 4
 
0.1%
1L 3
 
< 0.1%
Other values (29) 44
 
0.7%

Length

2024-05-11T15:09:54.673743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6127
96.7%
1개 47
 
0.7%
600g 24
 
0.4%
6개 17
 
0.3%
x 16
 
0.3%
swap*2개 13
 
0.2%
1 10
 
0.2%
1인분 9
 
0.1%
swap*1개 5
 
0.1%
600그램 4
 
0.1%
Other values (39) 66
 
1.0%

제조일자(일자)
Real number (ℝ)

MISSING 

Distinct351
Distinct (%)36.2%
Missing5321
Missing (%)84.6%
Infinite0
Infinite (%)0.0%
Mean20183984
Minimum20110519
Maximum20260618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:54.908298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110519
5-th percentile20131113
Q120161011
median20190205
Q320200109
95-th percentile20231123
Maximum20260618
Range150099
Interquartile range (IQR)39097.75

Descriptive statistics

Standard deviation29112.504
Coefficient of variation (CV)0.0014423567
Kurtosis-0.19808929
Mean20183984
Median Absolute Deviation (MAD)19578
Skewness-0.026548646
Sum1.9578465 × 1010
Variance8.4753788 × 108
MonotonicityNot monotonic
2024-05-11T15:09:55.117491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180621 19
 
0.3%
20161006 19
 
0.3%
20190415 19
 
0.3%
20180417 17
 
0.3%
20170829 16
 
0.3%
20131113 16
 
0.3%
20170613 16
 
0.3%
20180827 15
 
0.2%
20231121 15
 
0.2%
20130925 14
 
0.2%
Other values (341) 804
 
12.8%
(Missing) 5321
84.6%
ValueCountFrequency (%)
20110519 1
< 0.1%
20110923 1
< 0.1%
20111021 1
< 0.1%
20111107 1
< 0.1%
20111110 1
< 0.1%
20111220 1
< 0.1%
20111222 1
< 0.1%
20120105 2
< 0.1%
20120108 1
< 0.1%
20120116 1
< 0.1%
ValueCountFrequency (%)
20260618 1
 
< 0.1%
20240613 3
 
< 0.1%
20240315 9
0.1%
20240314 6
0.1%
20240313 7
0.1%
20240312 6
0.1%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240111 2
 
< 0.1%
20231127 8
0.1%

제조일자(롯트)
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing6287
Missing (%)99.9%
Memory size49.3 KiB
2024-05-11T15:09:55.388388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.75
Min length17

Characters and Unicode

Total characters71
Distinct characters16
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

Unique4 ?
Unique (%)100.0%

Sample

1st row2015.08.21 제조(2년)
2nd row2014.10.31 제조 (3년)
3rd row2015.05.28 제조 (3년)
4th row2015.06.17 제조 (3년)
ValueCountFrequency (%)
제조 3
27.3%
3년 3
27.3%
2015.08.21 1
 
9.1%
제조(2년 1
 
9.1%
2014.10.31 1
 
9.1%
2015.05.28 1
 
9.1%
2015.06.17 1
 
9.1%
2024-05-11T15:09:55.850935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
11.3%
1 8
11.3%
. 8
11.3%
2 7
9.9%
7
9.9%
5 4
 
5.6%
4
 
5.6%
4
 
5.6%
( 4
 
5.6%
4
 
5.6%
Other values (6) 13
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 36
50.7%
Other Letter 12
 
16.9%
Other Punctuation 8
 
11.3%
Space Separator 7
 
9.9%
Open Punctuation 4
 
5.6%
Close Punctuation 4
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
22.2%
1 8
22.2%
2 7
19.4%
5 4
11.1%
3 4
11.1%
8 2
 
5.6%
4 1
 
2.8%
6 1
 
2.8%
7 1
 
2.8%
Other Letter
ValueCountFrequency (%)
4
33.3%
4
33.3%
4
33.3%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59
83.1%
Hangul 12
 
16.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
13.6%
1 8
13.6%
. 8
13.6%
2 7
11.9%
7
11.9%
5 4
6.8%
( 4
6.8%
) 4
6.8%
3 4
6.8%
8 2
 
3.4%
Other values (3) 3
 
5.1%
Hangul
ValueCountFrequency (%)
4
33.3%
4
33.3%
4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
83.1%
Hangul 12
 
16.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
13.6%
1 8
13.6%
. 8
13.6%
2 7
11.9%
7
11.9%
5 4
6.8%
( 4
6.8%
) 4
6.8%
3 4
6.8%
8 2
 
3.4%
Other values (3) 3
 
5.1%
Hangul
ValueCountFrequency (%)
4
33.3%
4
33.3%
4
33.3%

유통기한(일자)
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)80.0%
Missing6201
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean19675064
Minimum20123
Maximum20131003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:56.032267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20123
5-th percentile20120128
Q120120419
median20120604
Q320121009
95-th percentile20130767
Maximum20131003
Range20110880
Interquartile range (IQR)590

Descriptive statistics

Standard deviation2979695.8
Coefficient of variation (CV)0.15144529
Kurtosis42.408191
Mean19675064
Median Absolute Deviation (MAD)277.5
Skewness-6.5928738
Sum1.7707558 × 109
Variance8.8785872 × 1012
MonotonicityNot monotonic
2024-05-11T15:09:56.248170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120524 4
 
0.1%
20120419 3
 
< 0.1%
20120519 3
 
< 0.1%
20120128 3
 
< 0.1%
20120601 3
 
< 0.1%
20121009 2
 
< 0.1%
20120831 2
 
< 0.1%
20121024 2
 
< 0.1%
20120326 2
 
< 0.1%
20120403 2
 
< 0.1%
Other values (62) 64
 
1.0%
(Missing) 6201
98.6%
ValueCountFrequency (%)
20123 1
 
< 0.1%
20125 1
 
< 0.1%
20111219 1
 
< 0.1%
20120106 1
 
< 0.1%
20120128 3
< 0.1%
20120216 1
 
< 0.1%
20120219 1
 
< 0.1%
20120227 1
 
< 0.1%
20120301 1
 
< 0.1%
20120313 1
 
< 0.1%
ValueCountFrequency (%)
20131003 1
< 0.1%
20130927 1
< 0.1%
20130926 1
< 0.1%
20130908 1
< 0.1%
20130901 1
< 0.1%
20130603 1
< 0.1%
20130523 1
< 0.1%
20130512 1
< 0.1%
20130403 1
< 0.1%
20130305 1
< 0.1%

유통기한(제조일기준)
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)46.9%
Missing6242
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean16430062
Minimum2
Maximum20180208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:56.430163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile90
Q120110519
median20111103
Q320120431
95-th percentile20166905
Maximum20180208
Range20180206
Interquartile range (IQR)9912

Descriptive statistics

Standard deviation7874071
Coefficient of variation (CV)0.47924779
Kurtosis0.87629731
Mean16430062
Median Absolute Deviation (MAD)584
Skewness-1.6858666
Sum8.0507305 × 108
Variance6.2000993 × 1013
MonotonicityNot monotonic
2024-05-11T15:09:56.633344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20111201 9
 
0.1%
20110519 8
 
0.1%
20160425 5
 
0.1%
20111006 3
 
< 0.1%
90 2
 
< 0.1%
20120431 2
 
< 0.1%
180 2
 
< 0.1%
20180208 2
 
< 0.1%
20160424 2
 
< 0.1%
1825 1
 
< 0.1%
Other values (13) 13
 
0.2%
(Missing) 6242
99.2%
ValueCountFrequency (%)
2 1
 
< 0.1%
30 1
 
< 0.1%
90 2
 
< 0.1%
180 2
 
< 0.1%
365 1
 
< 0.1%
730 1
 
< 0.1%
1825 1
 
< 0.1%
20110519 8
0.1%
20110627 1
 
< 0.1%
20111006 3
 
< 0.1%
ValueCountFrequency (%)
20180208 2
 
< 0.1%
20171224 1
 
< 0.1%
20160426 1
 
< 0.1%
20160425 5
0.1%
20160424 2
 
< 0.1%
20120431 2
 
< 0.1%
20120429 1
 
< 0.1%
20120428 1
 
< 0.1%
20111201 9
0.1%
20111103 1
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
실온
3448 
<NA>
2109 
냉장
498 
냉동
 
202
기타
 
34

Length

Max length4
Median length2
Mean length2.6704816
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실온 3448
54.8%
<NA> 2109
33.5%
냉장 498
 
7.9%
냉동 202
 
3.2%
기타 34
 
0.5%

Length

2024-05-11T15:09:56.888186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:57.057061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실온 3448
54.8%
na 2109
33.5%
냉장 498
 
7.9%
냉동 202
 
3.2%
기타 34
 
0.5%

바코드번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

어린이기호식품유형
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

검사기관명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
1
3952 
<NA>
2331 
85
 
6
0
 
2

Length

Max length4
Median length1
Mean length2.1125417
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3952
62.8%
<NA> 2331
37.1%
85 6
 
0.1%
0 2
 
< 0.1%

Length

2024-05-11T15:09:57.231080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:57.404857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3952
62.8%
na 2331
37.1%
85 6
 
0.1%
0 2
 
< 0.1%

(구)제조사명
Text

MISSING 

Distinct307
Distinct (%)37.4%
Missing5470
Missing (%)86.9%
Memory size49.3 KiB
2024-05-11T15:09:57.742705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.043849
Min length2

Characters and Unicode

Total characters5783
Distinct characters274
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

Unique161 ?
Unique (%)19.6%

Sample

1st row티바두마리
2nd row동서상회
3rd row금강슈퍼
4th row씨제이제일제당(주)
5th row씨제이제일제당(주)
ValueCountFrequency (%)
씨제이제일제당(주 47
 
5.4%
대상(주 24
 
2.8%
동서식품 20
 
2.3%
주식회사오뚜기 18
 
2.1%
주식회사 16
 
1.8%
롯데칠성음료(주 15
 
1.7%
주)동원에프앤비 15
 
1.7%
주)오리온 13
 
1.5%
해태제과식품(주 13
 
1.5%
롯데제과(주 12
 
1.4%
Other values (315) 678
77.8%
2024-05-11T15:09:58.298379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
639
 
11.0%
) 566
 
9.8%
( 566
 
9.8%
276
 
4.8%
227
 
3.9%
172
 
3.0%
106
 
1.8%
94
 
1.6%
86
 
1.5%
79
 
1.4%
Other values (264) 2972
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4577
79.1%
Close Punctuation 566
 
9.8%
Open Punctuation 566
 
9.8%
Space Separator 50
 
0.9%
Uppercase Letter 9
 
0.2%
Other Punctuation 8
 
0.1%
Lowercase Letter 4
 
0.1%
Decimal Number 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
639
 
14.0%
276
 
6.0%
227
 
5.0%
172
 
3.8%
106
 
2.3%
94
 
2.1%
86
 
1.9%
79
 
1.7%
76
 
1.7%
74
 
1.6%
Other values (247) 2748
60.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
22.2%
H 2
22.2%
F 1
11.1%
G 1
11.1%
M 1
11.1%
Y 1
11.1%
N 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
f 1
25.0%
d 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
% 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 566
100.0%
Open Punctuation
ValueCountFrequency (%)
( 566
100.0%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4577
79.1%
Common 1193
 
20.6%
Latin 13
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
639
 
14.0%
276
 
6.0%
227
 
5.0%
172
 
3.8%
106
 
2.3%
94
 
2.1%
86
 
1.9%
79
 
1.7%
76
 
1.7%
74
 
1.6%
Other values (247) 2748
60.0%
Latin
ValueCountFrequency (%)
B 2
15.4%
o 2
15.4%
H 2
15.4%
f 1
7.7%
d 1
7.7%
F 1
7.7%
G 1
7.7%
M 1
7.7%
Y 1
7.7%
N 1
7.7%
Common
ValueCountFrequency (%)
) 566
47.4%
( 566
47.4%
50
 
4.2%
. 7
 
0.6%
2 2
 
0.2%
% 1
 
0.1%
1 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4577
79.1%
ASCII 1206
 
20.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
639
 
14.0%
276
 
6.0%
227
 
5.0%
172
 
3.8%
106
 
2.3%
94
 
2.1%
86
 
1.9%
79
 
1.7%
76
 
1.7%
74
 
1.6%
Other values (247) 2748
60.0%
ASCII
ValueCountFrequency (%)
) 566
46.9%
( 566
46.9%
50
 
4.1%
. 7
 
0.6%
2 2
 
0.2%
B 2
 
0.2%
o 2
 
0.2%
H 2
 
0.2%
f 1
 
0.1%
d 1
 
0.1%
Other values (7) 7
 
0.6%

내외국산
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
국내
4939 
국외
1352 

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 4939
78.5%
국외 1352
 
21.5%

Length

2024-05-11T15:09:58.457469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:58.598650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 4939
78.5%
국외 1352
 
21.5%

국가명
Categorical

IMBALANCE 

Distinct41
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
5770 
미국
 
92
중국
 
64
이탈리아
 
39
일본
 
37
Other values (36)
 
289

Length

Max length6
Median length4
Mean length3.8904785
Min length2

Unique

Unique9 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5770
91.7%
미국 92
 
1.5%
중국 64
 
1.0%
이탈리아 39
 
0.6%
일본 37
 
0.6%
태국 35
 
0.6%
캐나다 27
 
0.4%
스페인 26
 
0.4%
영국 24
 
0.4%
독일 20
 
0.3%
Other values (31) 157
 
2.5%

Length

2024-05-11T15:09:58.745990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5770
91.6%
미국 92
 
1.5%
중국 68
 
1.1%
이탈리아 39
 
0.6%
일본 37
 
0.6%
태국 35
 
0.6%
캐나다 27
 
0.4%
스페인 26
 
0.4%
영국 24
 
0.4%
독일 20
 
0.3%
Other values (32) 158
 
2.5%

검사구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
1
3311 
<NA>
2096 
2
884 

Length

Max length4
Median length1
Mean length1.9995231
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 3311
52.6%
<NA> 2096
33.3%
2 884
 
14.1%

Length

2024-05-11T15:09:58.916215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:59.027090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3311
52.6%
na 2096
33.3%
2 884
 
14.1%

검사의뢰일자
Real number (ℝ)

MISSING 

Distinct155
Distinct (%)5.0%
Missing3162
Missing (%)50.3%
Infinite0
Infinite (%)0.0%
Mean20152136
Minimum20100108
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:59.158002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100108
5-th percentile20100624
Q120110816
median20151130
Q320180321
95-th percentile20230919
Maximum20240315
Range140207
Interquartile range (IQR)69505

Descriptive statistics

Standard deviation41194.685
Coefficient of variation (CV)0.0020441845
Kurtosis-0.89138118
Mean20152136
Median Absolute Deviation (MAD)40020
Skewness0.35073278
Sum6.3056034 × 1010
Variance1.6970021 × 109
MonotonicityNot monotonic
2024-05-11T15:09:59.330241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160225 99
 
1.6%
20110720 97
 
1.5%
20151111 94
 
1.5%
20110901 88
 
1.4%
20150901 86
 
1.4%
20110922 82
 
1.3%
20111018 82
 
1.3%
20111110 77
 
1.2%
20160421 73
 
1.2%
20150922 72
 
1.1%
Other values (145) 2279
36.2%
(Missing) 3162
50.3%
ValueCountFrequency (%)
20100108 3
 
< 0.1%
20100121 46
0.7%
20100210 2
 
< 0.1%
20100212 10
 
0.2%
20100308 4
 
0.1%
20100309 13
 
0.2%
20100421 44
0.7%
20100615 2
 
< 0.1%
20100621 6
 
0.1%
20100624 65
1.0%
ValueCountFrequency (%)
20240315 28
0.4%
20240307 2
 
< 0.1%
20240228 3
 
< 0.1%
20240111 2
 
< 0.1%
20231205 20
0.3%
20231127 34
0.5%
20231116 1
 
< 0.1%
20231113 5
 
0.1%
20231107 1
 
< 0.1%
20231031 39
0.6%

결과회보일자
Real number (ℝ)

MISSING 

Distinct114
Distinct (%)7.1%
Missing4690
Missing (%)74.6%
Infinite0
Infinite (%)0.0%
Mean20168158
Minimum20130124
Maximum20220729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:09:59.510895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130124
5-th percentile20150805
Q120151215
median20161021
Q320180404
95-th percentile20210330
Maximum20220729
Range90605
Interquartile range (IQR)29189

Descriptive statistics

Standard deviation16237.038
Coefficient of variation (CV)0.00080508286
Kurtosis0.37220895
Mean20168158
Median Absolute Deviation (MAD)10007
Skewness0.92141625
Sum3.228922 × 1010
Variance2.636414 × 108
MonotonicityNot monotonic
2024-05-11T15:09:59.657981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160504 61
 
1.0%
20150916 56
 
0.9%
20180226 51
 
0.8%
20151215 50
 
0.8%
20151008 48
 
0.8%
20170717 47
 
0.7%
20161021 46
 
0.7%
20160921 46
 
0.7%
20150723 45
 
0.7%
20160310 42
 
0.7%
Other values (104) 1109
 
17.6%
(Missing) 4690
74.6%
ValueCountFrequency (%)
20130124 2
 
< 0.1%
20140916 1
 
< 0.1%
20150721 14
 
0.2%
20150723 45
0.7%
20150804 11
 
0.2%
20150805 15
 
0.2%
20150806 18
 
0.3%
20150807 21
0.3%
20150909 3
 
< 0.1%
20150915 27
0.4%
ValueCountFrequency (%)
20220729 2
 
< 0.1%
20211216 12
0.2%
20211214 6
 
0.1%
20211102 2
 
< 0.1%
20211027 3
 
< 0.1%
20210924 3
 
< 0.1%
20210923 28
0.4%
20210917 6
 
0.1%
20210831 2
 
< 0.1%
20210721 1
 
< 0.1%

판정구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
4318 
1
1962 
2
 
11

Length

Max length4
Median length4
Mean length3.0591321
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4318
68.6%
1 1962
31.2%
2 11
 
0.2%

Length

2024-05-11T15:09:59.789122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:00.297243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4318
68.6%
1 1962
31.2%
2 11
 
0.2%

처리구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

수거검사구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

단속지역구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

수거장소구분코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

처리결과
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
6263 
모든 시료(조리식품) 적합
 
16
모든 시료(조리식품) 적합 판정
 
12

Length

Max length17
Median length4
Mean length4.0502305
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6263
99.6%
모든 시료(조리식품) 적합 16
 
0.3%
모든 시료(조리식품) 적합 판정 12
 
0.2%

Length

2024-05-11T15:10:00.476035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:00.648691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6263
98.5%
모든 28
 
0.4%
시료(조리식품 28
 
0.4%
적합 28
 
0.4%
판정 12
 
0.2%

수거품처리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

교부번호
Real number (ℝ)

Distinct458
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0026284 × 1010
Minimum1.9670059 × 1010
Maximum2.023008 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:10:00.790448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9670059 × 1010
5-th percentile1.9930059 × 1010
Q12.0000059 × 1010
median2.002006 × 1010
Q32.004006 × 1010
95-th percentile2.012006 × 1010
Maximum2.023008 × 1010
Range5.6002075 × 108
Interquartile range (IQR)40000951

Descriptive statistics

Standard deviation53546986
Coefficient of variation (CV)0.0026738353
Kurtosis2.7265435
Mean2.0026284 × 1010
Median Absolute Deviation (MAD)20000891
Skewness0.52216034
Sum1.2598536 × 1014
Variance2.8672798 × 1015
MonotonicityNot monotonic
2024-05-11T15:10:00.968760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040060030 1331
21.2%
20000059079 1294
20.6%
20020059970 761
12.1%
20000059412 208
 
3.3%
19900059220 198
 
3.1%
19990059047 161
 
2.6%
20040060018 146
 
2.3%
20040060336 124
 
2.0%
20190059237 85
 
1.4%
20040059459 84
 
1.3%
Other values (448) 1899
30.2%
ValueCountFrequency (%)
19670059001 1
 
< 0.1%
19830059003 2
 
< 0.1%
19840059005 2
 
< 0.1%
19850059061 1
 
< 0.1%
19860059013 1
 
< 0.1%
19860059026 1
 
< 0.1%
19870059134 15
0.2%
19880059050 1
 
< 0.1%
19880059206 1
 
< 0.1%
19890059039 1
 
< 0.1%
ValueCountFrequency (%)
20230079747 2
< 0.1%
20230079583 1
< 0.1%
20230079354 1
< 0.1%
20230079196 1
< 0.1%
20230079141 2
< 0.1%
20220072215 1
< 0.1%
20220071555 1
< 0.1%
20220071541 1
< 0.1%
20220071373 1
< 0.1%
20210059824 1
< 0.1%

폐기일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

폐기량(kg)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

폐기금액(원)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

폐기장소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

폐기방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

소재지(도로명)
Text

MISSING 

Distinct249
Distinct (%)7.3%
Missing2902
Missing (%)46.1%
Memory size49.3 KiB
2024-05-11T15:10:01.406069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length61
Mean length34.555621
Min length23

Characters and Unicode

Total characters117109
Distinct characters186
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

Unique129 ?
Unique (%)3.8%

Sample

1st row서울특별시 노원구 동일로174길 37-8, 제일빌딩 1,2층 (공릉동)
2nd row서울특별시 노원구 동일로218길 25, (상계동,석창빌딩2층)
3rd row서울특별시 노원구 동일로 1530, (상계동, 다모아빌딩 114호)
4th row서울특별시 노원구 동일로 1350, 지하동 101-1호 (상계동,빌딩)
5th row서울특별시 노원구 노해로75길 14-22, (상계동)
ValueCountFrequency (%)
서울특별시 3389
15.4%
노원구 3389
15.4%
중계동 1734
 
7.9%
월계동 1023
 
4.6%
마들로3길 929
 
4.2%
15 922
 
4.2%
동일로204가길 774
 
3.5%
12 764
 
3.5%
333-1 692
 
3.1%
지하2층 656
 
3.0%
Other values (454) 7743
35.2%
2024-05-11T15:10:01.989976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18626
 
15.9%
, 6235
 
5.3%
3 5029
 
4.3%
4782
 
4.1%
1 4695
 
4.0%
4599
 
3.9%
4024
 
3.4%
3970
 
3.4%
2 3735
 
3.2%
) 3552
 
3.0%
Other values (176) 57862
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62705
53.5%
Decimal Number 21364
 
18.2%
Space Separator 18626
 
15.9%
Other Punctuation 6237
 
5.3%
Close Punctuation 3552
 
3.0%
Open Punctuation 3552
 
3.0%
Dash Punctuation 1020
 
0.9%
Uppercase Letter 52
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4782
 
7.6%
4599
 
7.3%
4024
 
6.4%
3970
 
6.3%
3395
 
5.4%
3392
 
5.4%
3390
 
5.4%
3389
 
5.4%
3389
 
5.4%
3389
 
5.4%
Other values (156) 24986
39.8%
Decimal Number
ValueCountFrequency (%)
3 5029
23.5%
1 4695
22.0%
2 3735
17.5%
0 2038
9.5%
5 2010
 
9.4%
4 1577
 
7.4%
7 1233
 
5.8%
8 369
 
1.7%
6 341
 
1.6%
9 337
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 6235
> 99.9%
. 1
 
< 0.1%
@ 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
B 45
86.5%
A 7
 
13.5%
Space Separator
ValueCountFrequency (%)
18626
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3552
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1020
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62705
53.5%
Common 54352
46.4%
Latin 52
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4782
 
7.6%
4599
 
7.3%
4024
 
6.4%
3970
 
6.3%
3395
 
5.4%
3392
 
5.4%
3390
 
5.4%
3389
 
5.4%
3389
 
5.4%
3389
 
5.4%
Other values (156) 24986
39.8%
Common
ValueCountFrequency (%)
18626
34.3%
, 6235
 
11.5%
3 5029
 
9.3%
1 4695
 
8.6%
2 3735
 
6.9%
) 3552
 
6.5%
( 3552
 
6.5%
0 2038
 
3.7%
5 2010
 
3.7%
4 1577
 
2.9%
Other values (8) 3303
 
6.1%
Latin
ValueCountFrequency (%)
B 45
86.5%
A 7
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62705
53.5%
ASCII 54404
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18626
34.2%
, 6235
 
11.5%
3 5029
 
9.2%
1 4695
 
8.6%
2 3735
 
6.9%
) 3552
 
6.5%
( 3552
 
6.5%
0 2038
 
3.7%
5 2010
 
3.7%
4 1577
 
2.9%
Other values (10) 3355
 
6.2%
Hangul
ValueCountFrequency (%)
4782
 
7.6%
4599
 
7.3%
4024
 
6.4%
3970
 
6.3%
3395
 
5.4%
3392
 
5.4%
3390
 
5.4%
3389
 
5.4%
3389
 
5.4%
3389
 
5.4%
Other values (156) 24986
39.8%
Distinct428
Distinct (%)6.8%
Missing1
Missing (%)< 0.1%
Memory size49.3 KiB
2024-05-11T15:10:02.548901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length57
Mean length26.865183
Min length22

Characters and Unicode

Total characters168982
Distinct characters204
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

Unique228 ?
Unique (%)3.6%

Sample

1st row서울특별시 노원구 공릉동 438번지 2호
2nd row서울특별시 노원구 공릉동 633번지 18호
3rd row서울특별시 노원구 공릉동 633번지 18호 제일빌딩 1,2층
4th row서울특별시 노원구 상계동 1132번지 107호
5th row서울특별시 노원구 상계동 1132번지 107호
ValueCountFrequency (%)
서울특별시 6290
18.9%
노원구 6290
18.9%
중계동 2766
 
8.3%
1호 1694
 
5.1%
월계동 1568
 
4.7%
2호 1481
 
4.4%
509번지 1474
 
4.4%
333번지 1452
 
4.4%
지하2층 1197
 
3.6%
상계동 1189
 
3.6%
Other values (553) 7959
23.9%
2024-05-11T15:10:03.203988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43129
25.5%
8081
 
4.8%
6376
 
3.8%
6326
 
3.7%
6311
 
3.7%
6303
 
3.7%
6296
 
3.7%
6295
 
3.7%
6290
 
3.7%
6290
 
3.7%
Other values (194) 67285
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97107
57.5%
Space Separator 43129
25.5%
Decimal Number 28006
 
16.6%
Other Punctuation 205
 
0.1%
Close Punctuation 163
 
0.1%
Open Punctuation 163
 
0.1%
Dash Punctuation 153
 
0.1%
Uppercase Letter 54
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8081
 
8.3%
6376
 
6.6%
6326
 
6.5%
6311
 
6.5%
6303
 
6.5%
6296
 
6.5%
6295
 
6.5%
6290
 
6.5%
6290
 
6.5%
6290
 
6.5%
Other values (173) 32249
33.2%
Decimal Number
ValueCountFrequency (%)
3 5652
20.2%
1 4941
17.6%
2 3611
12.9%
0 3259
11.6%
5 3099
11.1%
9 2025
 
7.2%
4 1600
 
5.7%
7 1464
 
5.2%
8 1284
 
4.6%
6 1071
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 45
83.3%
A 5
 
9.3%
P 2
 
3.7%
T 2
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 200
97.6%
@ 5
 
2.4%
Space Separator
ValueCountFrequency (%)
43129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 153
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97107
57.5%
Common 71821
42.5%
Latin 54
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8081
 
8.3%
6376
 
6.6%
6326
 
6.5%
6311
 
6.5%
6303
 
6.5%
6296
 
6.5%
6295
 
6.5%
6290
 
6.5%
6290
 
6.5%
6290
 
6.5%
Other values (173) 32249
33.2%
Common
ValueCountFrequency (%)
43129
60.1%
3 5652
 
7.9%
1 4941
 
6.9%
2 3611
 
5.0%
0 3259
 
4.5%
5 3099
 
4.3%
9 2025
 
2.8%
4 1600
 
2.2%
7 1464
 
2.0%
8 1284
 
1.8%
Other values (7) 1757
 
2.4%
Latin
ValueCountFrequency (%)
B 45
83.3%
A 5
 
9.3%
P 2
 
3.7%
T 2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97107
57.5%
ASCII 71875
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43129
60.0%
3 5652
 
7.9%
1 4941
 
6.9%
2 3611
 
5.0%
0 3259
 
4.5%
5 3099
 
4.3%
9 2025
 
2.8%
4 1600
 
2.2%
7 1464
 
2.0%
8 1284
 
1.8%
Other values (11) 1811
 
2.5%
Hangul
ValueCountFrequency (%)
8081
 
8.3%
6376
 
6.6%
6326
 
6.5%
6311
 
6.5%
6303
 
6.5%
6296
 
6.5%
6295
 
6.5%
6290
 
6.5%
6290
 
6.5%
6290
 
6.5%
Other values (173) 32249
33.2%

업소전화번호
Text

MISSING 

Distinct331
Distinct (%)5.6%
Missing427
Missing (%)6.8%
Memory size49.3 KiB
2024-05-11T15:10:03.577952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.278308
Min length7

Characters and Unicode

Total characters60272
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

Unique180 ?
Unique (%)3.1%

Sample

1st row02 9757523
2nd row02 9727016
3rd row02 9727016
4th row02 9022049
5th row02 9022049
ValueCountFrequency (%)
02 2767
28.8%
0220921234 1332
13.9%
0220922532 761
 
7.9%
986 671
 
7.0%
2080 671
 
7.0%
029862080 532
 
5.5%
0220910011 208
 
2.2%
9859000 198
 
2.1%
9482001 161
 
1.7%
9728793 146
 
1.5%
Other values (354) 2160
22.5%
2024-05-11T15:10:04.183586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15685
26.0%
0 13025
21.6%
9 7095
11.8%
5005
 
8.3%
3 4369
 
7.2%
8 3827
 
6.3%
1 3469
 
5.8%
4 2646
 
4.4%
5 2126
 
3.5%
6 1940
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55267
91.7%
Space Separator 5005
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15685
28.4%
0 13025
23.6%
9 7095
12.8%
3 4369
 
7.9%
8 3827
 
6.9%
1 3469
 
6.3%
4 2646
 
4.8%
5 2126
 
3.8%
6 1940
 
3.5%
7 1085
 
2.0%
Space Separator
ValueCountFrequency (%)
5005
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15685
26.0%
0 13025
21.6%
9 7095
11.8%
5005
 
8.3%
3 4369
 
7.2%
8 3827
 
6.3%
1 3469
 
5.8%
4 2646
 
4.4%
5 2126
 
3.5%
6 1940
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15685
26.0%
0 13025
21.6%
9 7095
11.8%
5005
 
8.3%
3 4369
 
7.2%
8 3827
 
6.3%
1 3469
 
5.8%
4 2646
 
4.4%
5 2126
 
3.5%
6 1940
 
3.2%

점검목적
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
수거
2736 
<NA>
2562 
위생점검(전체)
840 
위생점검(부분)
 
152
시설점검
 
1

Length

Max length8
Median length4
Mean length3.7609283
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수거 2736
43.5%
<NA> 2562
40.7%
위생점검(전체) 840
 
13.4%
위생점검(부분) 152
 
2.4%
시설점검 1
 
< 0.1%

Length

2024-05-11T15:10:04.392576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:04.602217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거 2736
43.5%
na 2562
40.7%
위생점검(전체 840
 
13.4%
위생점검(부분 152
 
2.4%
시설점검 1
 
< 0.1%

점검일자
Real number (ℝ)

Distinct325
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20140944
Minimum20070517
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:10:04.801281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070517
5-th percentile20080307
Q120110719
median20130829
Q320170829
95-th percentile20211130
Maximum20240315
Range169798
Interquartile range (IQR)60110

Descriptive statistics

Standard deviation41165.634
Coefficient of variation (CV)0.0020438781
Kurtosis-0.68873503
Mean20140944
Median Absolute Deviation (MAD)29798
Skewness0.37730335
Sum1.2670668 × 1011
Variance1.6946094 × 109
MonotonicityNot monotonic
2024-05-11T15:10:05.045216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160224 200
 
3.2%
20110719 97
 
1.5%
20130610 93
 
1.5%
20151110 90
 
1.4%
20120312 89
 
1.4%
20110831 88
 
1.4%
20111017 86
 
1.4%
20150831 86
 
1.4%
20140324 86
 
1.4%
20130724 82
 
1.3%
Other values (315) 5294
84.2%
ValueCountFrequency (%)
20070517 12
 
0.2%
20070518 3
 
< 0.1%
20070709 6
 
0.1%
20070710 8
 
0.1%
20070711 2
 
< 0.1%
20070713 7
 
0.1%
20070717 1
 
< 0.1%
20070827 1
 
< 0.1%
20070912 63
1.0%
20070927 10
 
0.2%
ValueCountFrequency (%)
20240315 29
0.5%
20240307 1
 
< 0.1%
20240228 3
 
< 0.1%
20240111 2
 
< 0.1%
20231204 20
0.3%
20231127 34
0.5%
20231116 1
 
< 0.1%
20231107 1
 
< 0.1%
20231030 39
0.6%
20231026 3
 
< 0.1%

점검구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
<NA>
2523 
수시
2073 
기타
1368 
합동
279 
일제
 
48

Length

Max length4
Median length2
Mean length2.8020982
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2523
40.1%
수시 2073
33.0%
기타 1368
21.7%
합동 279
 
4.4%
일제 48
 
0.8%

Length

2024-05-11T15:10:05.280727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:05.458441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2523
40.1%
수시 2073
33.0%
기타 1368
21.7%
합동 279
 
4.4%
일제 48
 
0.8%

점검내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size49.3 KiB
1
3676 
<NA>
2603 
2
 
12

Length

Max length4
Median length1
Mean length2.2412971
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3676
58.4%
<NA> 2603
41.4%
2 12
 
0.2%

Length

2024-05-11T15:10:05.627264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:10:05.787797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3676
58.4%
na 2603
41.4%
2 12
 
0.2%

(구)제조유통기한
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)80.0%
Missing6201
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean19675064
Minimum20123
Maximum20131003
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.4 KiB
2024-05-11T15:10:05.969676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20123
5-th percentile20120128
Q120120419
median20120604
Q320121009
95-th percentile20130767
Maximum20131003
Range20110880
Interquartile range (IQR)590

Descriptive statistics

Standard deviation2979695.8
Coefficient of variation (CV)0.15144529
Kurtosis42.408191
Mean19675064
Median Absolute Deviation (MAD)277.5
Skewness-6.5928738
Sum1.7707558 × 109
Variance8.8785872 × 1012
MonotonicityNot monotonic
2024-05-11T15:10:06.170847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120524 4
 
0.1%
20120419 3
 
< 0.1%
20120519 3
 
< 0.1%
20120128 3
 
< 0.1%
20120601 3
 
< 0.1%
20121009 2
 
< 0.1%
20120831 2
 
< 0.1%
20121024 2
 
< 0.1%
20120326 2
 
< 0.1%
20120403 2
 
< 0.1%
Other values (62) 64
 
1.0%
(Missing) 6201
98.6%
ValueCountFrequency (%)
20123 1
 
< 0.1%
20125 1
 
< 0.1%
20111219 1
 
< 0.1%
20120106 1
 
< 0.1%
20120128 3
< 0.1%
20120216 1
 
< 0.1%
20120219 1
 
< 0.1%
20120227 1
 
< 0.1%
20120301 1
 
< 0.1%
20120313 1
 
< 0.1%
ValueCountFrequency (%)
20131003 1
< 0.1%
20130927 1
< 0.1%
20130926 1
< 0.1%
20130908 1
< 0.1%
20130901 1
< 0.1%
20130603 1
< 0.1%
20130523 1
< 0.1%
20130512 1
< 0.1%
20130403 1
< 0.1%
20130305 1
< 0.1%
Distinct156
Distinct (%)67.8%
Missing6061
Missing (%)96.3%
Memory size49.3 KiB
2024-05-11T15:10:06.562437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length27
Mean length19.104348
Min length5

Characters and Unicode

Total characters4394
Distinct characters198
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)49.1%

Sample

1st row충남 천안시 서북구 성거읍 천홍리 321-4
2nd row경기도 용인시 처인구 고림동 709-1
3rd row서울 강남구 역삼동 701-2
4th row경기도 가평군 청평면 삼천리 1112-4
5th row경기도 용인시 처인구 고림동 709-1
ValueCountFrequency (%)
경기도 40
 
3.8%
충남 26
 
2.5%
충북 25
 
2.4%
경기 22
 
2.1%
천안시 17
 
1.6%
서울 15
 
1.4%
강남구 15
 
1.4%
고양시 13
 
1.2%
역삼동 11
 
1.1%
701-2 11
 
1.1%
Other values (380) 846
81.3%
2024-05-11T15:10:07.328547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
811
 
18.5%
1 176
 
4.0%
- 158
 
3.6%
153
 
3.5%
141
 
3.2%
2 126
 
2.9%
115
 
2.6%
3 105
 
2.4%
103
 
2.3%
102
 
2.3%
Other values (188) 2404
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2556
58.2%
Decimal Number 869
 
19.8%
Space Separator 811
 
18.5%
Dash Punctuation 158
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
153
 
6.0%
141
 
5.5%
115
 
4.5%
103
 
4.0%
102
 
4.0%
92
 
3.6%
70
 
2.7%
70
 
2.7%
68
 
2.7%
65
 
2.5%
Other values (176) 1577
61.7%
Decimal Number
ValueCountFrequency (%)
1 176
20.3%
2 126
14.5%
3 105
12.1%
4 100
11.5%
0 74
8.5%
5 73
8.4%
7 67
 
7.7%
6 61
 
7.0%
9 50
 
5.8%
8 37
 
4.3%
Space Separator
ValueCountFrequency (%)
811
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2556
58.2%
Common 1838
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
153
 
6.0%
141
 
5.5%
115
 
4.5%
103
 
4.0%
102
 
4.0%
92
 
3.6%
70
 
2.7%
70
 
2.7%
68
 
2.7%
65
 
2.5%
Other values (176) 1577
61.7%
Common
ValueCountFrequency (%)
811
44.1%
1 176
 
9.6%
- 158
 
8.6%
2 126
 
6.9%
3 105
 
5.7%
4 100
 
5.4%
0 74
 
4.0%
5 73
 
4.0%
7 67
 
3.6%
6 61
 
3.3%
Other values (2) 87
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2556
58.2%
ASCII 1838
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
811
44.1%
1 176
 
9.6%
- 158
 
8.6%
2 126
 
6.9%
3 105
 
5.7%
4 100
 
5.4%
0 74
 
4.0%
5 73
 
4.0%
7 67
 
3.6%
6 61
 
3.3%
Other values (2) 87
 
4.7%
Hangul
ValueCountFrequency (%)
153
 
6.0%
141
 
5.5%
115
 
4.5%
103
 
4.0%
102
 
4.0%
92
 
3.6%
70
 
2.7%
70
 
2.7%
68
 
2.7%
65
 
2.5%
Other values (176) 1577
61.7%

부적합항목
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing6290
Missing (%)> 99.9%
Memory size49.3 KiB
2024-05-11T15:10:07.540962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
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

Unique1 ?
Unique (%)100.0%

Sample

1st row위화물(전분)
ValueCountFrequency (%)
위화물(전분 1
100.0%
2024-05-11T15:10:07.875646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
( 1
14.3%
1
14.3%
1
14.3%
) 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
71.4%
Open Punctuation 1
 
14.3%
Close Punctuation 1
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
71.4%
Common 2
 
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
71.4%
ASCII 2
 
28.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

기준치부적합내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6291
Missing (%)100.0%
Memory size55.4 KiB

Sample

시군구코드업종코드업종명계획구분코드계획구분명지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드바코드번호어린이기호식품유형검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리구분수거검사구분코드단속지역구분코드수거장소구분코드처리결과수거품처리교부번호폐기일자폐기량(kg)폐기금액(원)폐기장소폐기방법소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검내용점검결과코드(구)제조유통기한(구)제조회사주소부적합항목기준치부적합내용
03100000101일반음식점<NA><NA><NA><NA>7-7<NA>봉봉827000000주류맥주맥주<NA><NA><NA>201007191l<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>120100719<NA><NA><NA><NA><NA><NA><NA><NA>19670059001<NA><NA><NA><NA><NA><NA>서울특별시 노원구 공릉동 438번지 2호02 9757523위생점검(전체)20100719기타<NA>1<NA><NA><NA><NA>
13100000101일반음식점<NA><NA><NA><NA>110-6-5검사용제일콩집600000000식품접객업접객업소조리식품등콩국수육수<NA><NA><NA>2012060811000ML<NA><NA><NA><NA><NA>냉장<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19830059003<NA><NA><NA><NA><NA><NA>서울특별시 노원구 공릉동 633번지 18호02 9727016수거20120608합동<NA>1<NA><NA><NA><NA>
23100000101일반음식점7<NA>서울시 민관 합동 위생점검<NA>6-19-2검사용제일콩집G0100000100000조리식품 등조리식품 등콩국물<NA><NA><NA>2018061911LT<NA>20180619<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220180619201807031<NA><NA><NA><NA><NA><NA>19830059003<NA><NA><NA><NA><NA>서울특별시 노원구 동일로174길 37-8, 제일빌딩 1,2층 (공릉동)서울특별시 노원구 공릉동 633번지 18호 제일빌딩 1,2층02 9727016위생점검(전체)20180619합동<NA>1<NA><NA><NA><NA>
33100000101일반음식점<NA><NA><NA><NA>111-3-7<NA>김가네829000000기타식품류즉석섭취식품참치김밥<NA><NA><NA>201003083100g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>120100308<NA><NA><NA><NA><NA><NA><NA><NA>19840059005<NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 1132번지 107호02 9022049<NA>20100308<NA><NA><NA><NA><NA><NA><NA>
43100000101일반음식점<NA><NA><NA><NA>111-3-8<NA>김가네829000000기타식품류즉석섭취식품쇠고기김밥<NA><NA><NA>201003083100g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>120100308<NA><NA><NA><NA><NA><NA><NA><NA>19840059005<NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 1132번지 107호02 9022049<NA>20100308<NA><NA><NA><NA><NA><NA><NA>
53100000101일반음식점<NA><NA><NA><NA>110-6-6검사용외백600000000식품접객업용수(지하수)지하수<NA><NA><NA>2012060811000ML<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19860059013<NA><NA><NA><NA><NA><NA>서울특별시 노원구 공릉동 644번지 49호0209753079수거20120608합동<NA>1<NA><NA><NA><NA>
63100000101일반음식점<NA><NA><NA><NA>7-8<NA>그날이후827000000주류맥주맥주<NA><NA><NA>201007191l<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>120100719<NA><NA><NA><NA><NA><NA><NA><NA>19860059026<NA><NA><NA><NA><NA><NA>서울특별시 노원구 공릉동 440번지 5호0209745312위생점검(전체)20100719기타<NA>1<NA><NA><NA><NA>
73100000101일반음식점<NA><NA><NA><NA>111-09-52검사용순두부와빈대떡마을G0100000100000조리식품 등조리식품 등전(해물빈대떡)전(해물빈대떡)<NA><NA>202109081600g<NA>20210908<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>120210908202109241<NA><NA><NA><NA><NA><NA>19890059039<NA><NA><NA><NA><NA>서울특별시 노원구 동일로218길 25, (상계동,석창빌딩2층)서울특별시 노원구 상계동 725번지 0호 석창빌딩2층02 9370409수거20210908일제<NA>1<NA><NA><NA><NA>
83100000101일반음식점<NA><NA><NA><NA>6-1<NA>고려식당121000000식육류중육류<NA>식육견<NA><NA><NA>20100615600g<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국내<NA>120100615<NA><NA><NA><NA><NA><NA><NA><NA>19890059224<NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 724번지 3호 고려빌딩 지하02 9384131위생점검(전체)20100615기타<NA>1<NA><NA><NA><NA>
93100000101일반음식점7<NA>배달전문음식점 지도점검<NA>111-산가-1검사용바몬드닭오리바베큐치킨G0100000100000조리식품 등조리식품 등통닭(후라이드)<NA><NA><NA>201510301800g<NA>20151030<NA><NA><NA>냉장<NA><NA>1<NA>국내<NA>220151030201511051<NA><NA><NA><NA><NA><NA>19890059195<NA><NA><NA><NA><NA>서울특별시 노원구 동일로 1530, (상계동, 다모아빌딩 114호)서울특별시 노원구 상계동 649번지 7호 다모아빌딩 114호02 9382375위생점검(전체)20151030수시<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
62813100000134건강기능식품일반판매업<NA><NA><NA><NA>111-2검사용트레이더스 월계점E0205700000000EPA 및 DHA 함유 유지EPA 및 DHA 함유 유지프로메가 더케어 900<NA><NA><NA>201904172115.7g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62823100000134건강기능식품일반판매업<NA><NA><NA><NA>111-5검사용트레이더스 월계점E0201600000000오메가-3 지방산 함유 유지오메가-3 지방산 함유 유지오메가3골드업플러스<NA><NA><NA>201904172216g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62833100000134건강기능식품일반판매업<NA><NA><NA><NA>111-4검사용트레이더스 월계점E0205700000000EPA 및 DHA 함유 유지EPA 및 DHA 함유 유지장용성 슈퍼오메가-3<NA><NA><NA>201904172180g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62843100000134건강기능식품일반판매업<NA><NA><NA><NA>111-8검사용트레이더스 월계점E0101400000000비타민 C비타민 C멀티비타민미네랄<NA><NA><NA>201904172135g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62853100000134건강기능식품일반판매업<NA><NA><NA><NA>111-9검사용트레이더스 월계점X0100026300000영양보충용제품영양보충용제품멀티비타민<NA><NA><NA>201904172210g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62863100000134건강기능식품일반판매업<NA><NA><NA><NA>111-10검사용트레이더스 월계점E0101400000000비타민 C비타민 C멀티비타민 포 우먼<NA><NA><NA>201904172130g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62873100000134건강기능식품일반판매업<NA><NA><NA><NA>111-1검사용트레이더스 월계점X0100026100000일반원료일반원료OMEGA 3 PLUS VITAMIN D 1200<NA><NA><NA>201904172144.2g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국외캐나다1<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62883100000134건강기능식품일반판매업<NA><NA><NA><NA>111-3검사용트레이더스 월계점E0205700000000EPA 및 DHA 함유 유지EPA 및 DHA 함유 유지츄어블오메가-3<NA><NA><NA>201904172105g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20190417<NA><NA><NA><NA><NA><NA><NA>
62893100000134건강기능식품일반판매업<NA><NA><NA><NA>111-5-8검사용트레이더스 월계점E0202500000000가르시니아캄보지아 추출물가르시니아캄보지아 추출물팻다운 컷 가르시니아<NA><NA><NA>20200514460g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국내<NA>2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190059242<NA><NA><NA><NA><NA>서울특별시 노원구 마들로3길 17, 월계트레이더스 1층 (월계동)서울특별시 노원구 월계동 333번지 1호 월계트레이더스 1층0263201234<NA>20200514<NA><NA><NA><NA><NA><NA><NA>
62903100000134건강기능식품일반판매업<NA><NA><NA><NA>111-5-1검사용호주프렌즈E0200500000000스피루리나스피루리나스피루리나 골드 100<NA><NA><NA>202005071261g<NA><NA><NA><NA><NA>실온<NA><NA><NA><NA>국외캐나다2<NA><NA><NA><NA><NA><NA><NA><NA><NA>20190060374<NA><NA><NA><NA><NA>서울특별시 노원구 동일로218길 17, 일신상가 1층 4호 (상계동)서울특별시 노원구 상계동 726번지 1호 일신상가<NA><NA>20200507<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드업종코드업종명계획구분코드지도점검계획수거계획수거증번호수거사유코드업소명식품군코드식품군품목명제품명음식물명원료명생산업소수거일자수거량(정량)제품규격(정량)단위(정량)수거량(자유)제조일자(일자)제조일자(롯트)유통기한(일자)유통기한(제조일기준)보관상태코드검사기관명(구)제조사명내외국산국가명검사구분검사의뢰일자결과회보일자판정구분처리결과교부번호소재지(도로명)소재지(지번)업소전화번호점검목적점검일자점검구분점검결과코드(구)제조유통기한(구)제조회사주소부적합항목# duplicates
03100000101일반음식점<NA><NA><NA><NA><NA>김밥천국<NA><NA>김밥<NA><NA><NA>200710053<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA>1<NA>19920059219<NA>서울특별시 노원구 공릉동 617번지 2호02 9746997위생점검(부분)20071005수시<NA><NA><NA><NA>2
13100000114기타식품판매업1추석성수식품 수거검사<NA>111-9-72검사용이마트월계점C0130010100000곡류가공품곡류가공품배대감 식혜만들기<NA><NA><NA>201509213240g<NA><NA><NA><NA><NA>실온1<NA>국내<NA>120150922201510141<NA>20040060030서울특별시 노원구 마들로3길 15, (월계동, 333-1)서울특별시 노원구 월계동 333번지 1호0220921234<NA>20150921<NA><NA><NA><NA><NA>2
23100000114기타식품판매업<NA><NA><NA>111-2-81검사용(주)이마트에브리데이 중계동점C0129120100000천일염천일염오천년의신비명품천일염<NA><NA><NA>2016022411KG<NA><NA><NA><NA><NA>실온<NA><NA>국내<NA>2<NA><NA><NA><NA>20040060336서울특별시 노원구 중계로12길 39, (중계동, 중계동 58번지 34호)서울특별시 노원구 중계동 58번지 34호02 9511641<NA>20160224<NA><NA><NA><NA><NA>2
33100000114기타식품판매업<NA><NA><NA>111-9-18검사용홈플러스스토어즈(주)중계점C0130080000000기타가공품기타가공품국산들깨가루<NA><NA><NA>201709215300g<NA><NA><NA><NA><NA>실온<NA><NA>국내<NA>2<NA><NA><NA><NA>20000059079서울특별시 노원구 동일로204가길 12, (중계동, 지하2층)서울특별시 노원구 중계동 509번지 2호 지하2층02 986 2080<NA>20170921<NA><NA><NA><NA><NA>2
43100000114기타식품판매업<NA><NA><NA><NA><NA>신세계이마트월계점220000000기타식품류크리미땅콩버터스키피땅콩버터<NA><NA><NA>200903113<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040060030<NA>서울특별시 노원구 월계동 333번지 1호0220921234<NA>20090312<NA><NA><NA><NA><NA>2
53100000114기타식품판매업<NA><NA><NA><NA><NA>신세계이마트월계점818000000음료류과.채음료아채라인썬몬드레드<NA><NA><NA>200907228<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040060030<NA>서울특별시 노원구 월계동 333번지 1호0220921234<NA>20090722<NA><NA><NA><NA><NA>2
63100000114기타식품판매업<NA><NA><NA><NA><NA>신세계이마트월계점827000000주류탁주쌀막걸리<NA><NA><NA>200907226<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040060030<NA>서울특별시 노원구 월계동 333번지 1호0220921234<NA>20090722<NA><NA><NA><NA><NA>2
73100000114기타식품판매업<NA><NA><NA><NA><NA>이천일아울렛 중계점821000000조미식품복합조미식품해물감치미<NA><NA><NA>200910146<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>19990059047<NA>서울특별시 노원구 중계동 509번지 0호02 9482001<NA>20091014<NA><NA><NA><NA><NA>2
83100000114기타식품판매업<NA><NA><NA><NA><NA>홈플러스테스코(주)중계점201000000과자류강정(또는유과)번데기형과자<NA><NA><NA>200909143<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20000059079<NA>서울특별시 노원구 중계동 509번지 2호 지하2층029862080<NA>20090914<NA><NA><NA><NA><NA>2
93100000121제과점영업<NA><NA><NA><NA><NA>케익하우스나리802000000빵또는떡류빵류패스추리<NA><NA><NA>201002181<NA><NA><NA><NA><NA><NA><NA><NA>1<NA>국외<NA><NA><NA><NA><NA><NA>20040059410<NA>서울특별시 노원구 상계동 396번지 6호02 9179970수거20100218수시1<NA><NA><NA>2