Overview

Dataset statistics

Number of variables44
Number of observations275
Missing cells2513
Missing cells (%)20.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory101.4 KiB
Average record size in memory377.5 B

Variable types

Categorical22
Text6
DateTime3
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18187/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (54.9%)Imbalance
남성종사자수 is highly imbalanced (60.0%)Imbalance
여성종사자수 is highly imbalanced (64.0%)Imbalance
영업장주변구분명 is highly imbalanced (73.6%)Imbalance
등급구분명 is highly imbalanced (72.7%)Imbalance
급수시설구분명 is highly imbalanced (56.1%)Imbalance
총인원 is highly imbalanced (74.1%)Imbalance
공장판매직종업원수 is highly imbalanced (69.3%)Imbalance
공장생산직종업원수 is highly imbalanced (69.3%)Imbalance
보증액 is highly imbalanced (74.1%)Imbalance
월세액 is highly imbalanced (74.1%)Imbalance
시설총규모 is highly imbalanced (54.9%)Imbalance
인허가취소일자 has 275 (100.0%) missing valuesMissing
폐업일자 has 57 (20.7%) missing valuesMissing
휴업시작일자 has 275 (100.0%) missing valuesMissing
휴업종료일자 has 275 (100.0%) missing valuesMissing
재개업일자 has 275 (100.0%) missing valuesMissing
전화번호 has 108 (39.3%) missing valuesMissing
소재지면적 has 78 (28.4%) missing valuesMissing
소재지우편번호 has 4 (1.5%) missing valuesMissing
지번주소 has 4 (1.5%) missing valuesMissing
도로명주소 has 149 (54.2%) missing valuesMissing
도로명우편번호 has 150 (54.5%) missing valuesMissing
좌표정보(X) has 6 (2.2%) missing valuesMissing
좌표정보(Y) has 6 (2.2%) missing valuesMissing
다중이용업소여부 has 26 (9.5%) missing valuesMissing
전통업소지정번호 has 275 (100.0%) missing valuesMissing
전통업소주된음식 has 275 (100.0%) missing valuesMissing
홈페이지 has 275 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:54:33.296148
Analysis finished2024-05-11 05:54:34.423516
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3100000
275 

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 275
100.0%

Length

2024-05-11T14:54:34.526474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:34.658055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 275
100.0%

관리번호
Text

UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:54:34.916283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6050
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

Unique275 ?
Unique (%)100.0%

Sample

1st row3100000-109-1991-00274
2nd row3100000-109-1992-00145
3rd row3100000-109-1992-00226
4th row3100000-109-1996-00146
5th row3100000-109-1996-00147
ValueCountFrequency (%)
3100000-109-1991-00274 1
 
0.4%
3100000-109-2011-00005 1
 
0.4%
3100000-109-2010-00006 1
 
0.4%
3100000-109-2011-00001 1
 
0.4%
3100000-109-2011-00002 1
 
0.4%
3100000-109-2011-00003 1
 
0.4%
3100000-109-2011-00004 1
 
0.4%
3100000-109-2015-00003 1
 
0.4%
3100000-109-2011-00007 1
 
0.4%
3100000-109-2008-00001 1
 
0.4%
Other values (265) 265
96.4%
2024-05-11T14:54:35.421177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3059
50.6%
- 825
 
13.6%
1 780
 
12.9%
2 375
 
6.2%
9 371
 
6.1%
3 345
 
5.7%
4 67
 
1.1%
5 66
 
1.1%
6 55
 
0.9%
8 54
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5225
86.4%
Dash Punctuation 825
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3059
58.5%
1 780
 
14.9%
2 375
 
7.2%
9 371
 
7.1%
3 345
 
6.6%
4 67
 
1.3%
5 66
 
1.3%
6 55
 
1.1%
8 54
 
1.0%
7 53
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6050
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3059
50.6%
- 825
 
13.6%
1 780
 
12.9%
2 375
 
6.2%
9 371
 
6.1%
3 345
 
5.7%
4 67
 
1.1%
5 66
 
1.1%
6 55
 
0.9%
8 54
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3059
50.6%
- 825
 
13.6%
1 780
 
12.9%
2 375
 
6.2%
9 371
 
6.1%
3 345
 
5.7%
4 67
 
1.1%
5 66
 
1.1%
6 55
 
0.9%
8 54
 
0.9%

인허가일자
Date

Distinct267
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1991-06-05 00:00:00
Maximum2024-03-13 00:00:00
2024-05-11T14:54:35.628259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:35.853489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3
218 
1
57 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 218
79.3%
1 57
 
20.7%

Length

2024-05-11T14:54:36.032941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:36.181241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 218
79.3%
1 57
 
20.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
218 
영업/정상
57 

Length

Max length5
Median length2
Mean length2.6218182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 218
79.3%
영업/정상 57
 
20.7%

Length

2024-05-11T14:54:36.328286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:36.474399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 218
79.3%
영업/정상 57
 
20.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2
218 
1
57 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 218
79.3%
1 57
 
20.7%

Length

2024-05-11T14:54:36.633321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:36.753795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 218
79.3%
1 57
 
20.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
폐업
218 
영업
57 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 218
79.3%
영업 57
 
20.7%

Length

2024-05-11T14:54:36.854946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:36.966910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 218
79.3%
영업 57
 
20.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)94.0%
Missing57
Missing (%)20.7%
Infinite0
Infinite (%)0.0%
Mean20102452
Minimum19971125
Maximum20230103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:37.114815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19971125
5-th percentile20020466
Q120050606
median20085769
Q320160463
95-th percentile20210753
Maximum20230103
Range258978
Interquartile range (IQR)109856.5

Descriptive statistics

Standard deviation65157.844
Coefficient of variation (CV)0.0032412884
Kurtosis-1.0613906
Mean20102452
Median Absolute Deviation (MAD)45065
Skewness0.32563592
Sum4.3823346 × 109
Variance4.2455447 × 109
MonotonicityNot monotonic
2024-05-11T14:54:37.296379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021227 5
 
1.8%
20210903 3
 
1.1%
20080102 3
 
1.1%
20200413 2
 
0.7%
20051011 2
 
0.7%
20091217 2
 
0.7%
20050616 2
 
0.7%
20030423 2
 
0.7%
20201228 1
 
0.4%
20141111 1
 
0.4%
Other values (195) 195
70.9%
(Missing) 57
 
20.7%
ValueCountFrequency (%)
19971125 1
0.4%
19971209 1
0.4%
19990323 1
0.4%
20000506 1
0.4%
20000720 1
0.4%
20010621 1
0.4%
20010622 1
0.4%
20011106 1
0.4%
20011112 1
0.4%
20020110 1
0.4%
ValueCountFrequency (%)
20230103 1
 
0.4%
20220729 1
 
0.4%
20220512 1
 
0.4%
20220427 1
 
0.4%
20220120 1
 
0.4%
20211122 1
 
0.4%
20211021 1
 
0.4%
20211001 1
 
0.4%
20210903 3
1.1%
20210727 1
 
0.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

전화번호
Text

MISSING 

Distinct150
Distinct (%)89.8%
Missing108
Missing (%)39.3%
Memory size2.3 KiB
2024-05-11T14:54:37.622585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.491018
Min length2

Characters and Unicode

Total characters1752
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

Unique139 ?
Unique (%)83.2%

Sample

1st row02 9719000
2nd row02 9392222
3rd row02 9491011
4th row02 9510438
5th row02 9346662
ValueCountFrequency (%)
02 131
37.6%
031 7
 
2.0%
9482001 5
 
1.4%
938 4
 
1.1%
9392222 4
 
1.1%
977 4
 
1.1%
070 3
 
0.9%
933 3
 
0.9%
9342315 3
 
0.9%
973 2
 
0.6%
Other values (168) 182
52.3%
2024-05-11T14:54:38.077401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 294
16.8%
2 279
15.9%
238
13.6%
9 216
12.3%
3 180
10.3%
1 128
7.3%
4 97
 
5.5%
7 91
 
5.2%
8 81
 
4.6%
5 77
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1514
86.4%
Space Separator 238
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 294
19.4%
2 279
18.4%
9 216
14.3%
3 180
11.9%
1 128
8.5%
4 97
 
6.4%
7 91
 
6.0%
8 81
 
5.4%
5 77
 
5.1%
6 71
 
4.7%
Space Separator
ValueCountFrequency (%)
238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1752
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 294
16.8%
2 279
15.9%
238
13.6%
9 216
12.3%
3 180
10.3%
1 128
7.3%
4 97
 
5.5%
7 91
 
5.2%
8 81
 
4.6%
5 77
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 294
16.8%
2 279
15.9%
238
13.6%
9 216
12.3%
3 180
10.3%
1 128
7.3%
4 97
 
5.5%
7 91
 
5.2%
8 81
 
4.6%
5 77
 
4.4%

소재지면적
Real number (ℝ)

MISSING 

Distinct147
Distinct (%)74.6%
Missing78
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean23.68802
Minimum0
Maximum138.38
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:38.598649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.024
Q16.6
median13
Q329.75
95-th percentile89.56
Maximum138.38
Range138.38
Interquartile range (IQR)23.15

Descriptive statistics

Standard deviation26.838259
Coefficient of variation (CV)1.1329887
Kurtosis3.7499135
Mean23.68802
Median Absolute Deviation (MAD)9
Skewness2.0083975
Sum4666.54
Variance720.29212
MonotonicityNot monotonic
2024-05-11T14:54:38.834244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 12
 
4.4%
10.0 7
 
2.5%
16.5 5
 
1.8%
2.0 5
 
1.8%
4.0 4
 
1.5%
23.1 4
 
1.5%
9.9 3
 
1.1%
13.0 2
 
0.7%
2.4 2
 
0.7%
23.0 2
 
0.7%
Other values (137) 151
54.9%
(Missing) 78
28.4%
ValueCountFrequency (%)
0.0 1
 
0.4%
1.0 2
 
0.7%
1.5 1
 
0.4%
1.82 1
 
0.4%
2.0 5
1.8%
2.03 1
 
0.4%
2.2 1
 
0.4%
2.4 2
 
0.7%
2.7 1
 
0.4%
2.8 2
 
0.7%
ValueCountFrequency (%)
138.38 1
0.4%
119.3 1
0.4%
117.23 1
0.4%
107.1 1
0.4%
100.95 1
0.4%
100.0 1
0.4%
99.0 1
0.4%
95.25 2
0.7%
91.4 1
0.4%
89.1 1
0.4%

소재지우편번호
Text

MISSING 

Distinct75
Distinct (%)27.7%
Missing4
Missing (%)1.5%
Memory size2.3 KiB
2024-05-11T14:54:39.204687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0627306
Min length6

Characters and Unicode

Total characters1643
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

Unique28 ?
Unique (%)10.3%

Sample

1st row139863
2nd row139200
3rd row139240
4th row139855
5th row139871
ValueCountFrequency (%)
139200 28
 
10.3%
139240 27
 
10.0%
139220 18
 
6.6%
139865 13
 
4.8%
139230 10
 
3.7%
139837 9
 
3.3%
139826 7
 
2.6%
139816 7
 
2.6%
139861 6
 
2.2%
139050 6
 
2.2%
Other values (65) 140
51.7%
2024-05-11T14:54:39.720353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 323
19.7%
3 315
19.2%
9 290
17.7%
0 176
10.7%
8 176
10.7%
2 153
9.3%
6 59
 
3.6%
4 54
 
3.3%
5 41
 
2.5%
7 39
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1626
99.0%
Dash Punctuation 17
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 323
19.9%
3 315
19.4%
9 290
17.8%
0 176
10.8%
8 176
10.8%
2 153
9.4%
6 59
 
3.6%
4 54
 
3.3%
5 41
 
2.5%
7 39
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1643
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 323
19.7%
3 315
19.2%
9 290
17.7%
0 176
10.7%
8 176
10.7%
2 153
9.3%
6 59
 
3.6%
4 54
 
3.3%
5 41
 
2.5%
7 39
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 323
19.7%
3 315
19.2%
9 290
17.7%
0 176
10.7%
8 176
10.7%
2 153
9.3%
6 59
 
3.6%
4 54
 
3.3%
5 41
 
2.5%
7 39
 
2.4%

지번주소
Text

MISSING 

Distinct219
Distinct (%)80.8%
Missing4
Missing (%)1.5%
Memory size2.3 KiB
2024-05-11T14:54:40.192243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length24.188192
Min length17

Characters and Unicode

Total characters6555
Distinct characters156
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

Unique202 ?
Unique (%)74.5%

Sample

1st row서울특별시 노원구 중계동 506-1
2nd row서울특별시 노원구 상계동 713-0 미도파 지하동
3rd row서울특별시 노원구 공릉동 383-2
4th row서울특별시 노원구 중계동 94-4
5th row서울특별시 노원구 하계동 164-2
ValueCountFrequency (%)
서울특별시 271
20.6%
노원구 271
20.6%
상계동 111
 
8.4%
중계동 71
 
5.4%
공릉동 50
 
3.8%
지하1층 26
 
2.0%
월계동 22
 
1.7%
하계동 17
 
1.3%
713 17
 
1.3%
517 14
 
1.1%
Other values (308) 446
33.9%
2024-05-11T14:54:40.942921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1282
19.6%
1 304
 
4.6%
동 282
 
4.3%
원 278
 
4.2%
구 278
 
4.2%
시 274
 
4.2%
노 274
 
4.2%
서 271
 
4.1%
특 271
 
4.1%
별 271
 
4.1%
Other values (146) 2770
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3776
57.6%
Space Separator 1282
 
19.6%
Decimal Number 1280
 
19.5%
Dash Punctuation 184
 
2.8%
Uppercase Letter 13
 
0.2%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 282
 
7.5%
원 278
 
7.4%
구 278
 
7.4%
시 274
 
7.3%
노 274
 
7.3%
서 271
 
7.2%
특 271
 
7.2%
별 271
 
7.2%
울 271
 
7.2%
계 229
 
6.1%
Other values (124) 1077
28.5%
Decimal Number
ValueCountFrequency (%)
1 304
23.8%
3 153
12.0%
5 123
9.6%
0 119
 
9.3%
6 119
 
9.3%
2 114
 
8.9%
7 101
 
7.9%
4 91
 
7.1%
8 81
 
6.3%
9 75
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
30.8%
E 3
23.1%
S 3
23.1%
A 2
15.4%
G 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
@ 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
1282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3776
57.6%
Common 2764
42.2%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 282
 
7.5%
원 278
 
7.4%
구 278
 
7.4%
시 274
 
7.3%
노 274
 
7.3%
서 271
 
7.2%
특 271
 
7.2%
별 271
 
7.2%
울 271
 
7.2%
계 229
 
6.1%
Other values (124) 1077
28.5%
Common
ValueCountFrequency (%)
1282
46.4%
1 304
 
11.0%
- 184
 
6.7%
3 153
 
5.5%
5 123
 
4.5%
0 119
 
4.3%
6 119
 
4.3%
2 114
 
4.1%
7 101
 
3.7%
4 91
 
3.3%
Other values (6) 174
 
6.3%
Latin
ValueCountFrequency (%)
B 4
26.7%
E 3
20.0%
S 3
20.0%
n 2
13.3%
A 2
13.3%
G 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3776
57.6%
ASCII 2779
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1282
46.1%
1 304
 
10.9%
- 184
 
6.6%
3 153
 
5.5%
5 123
 
4.4%
0 119
 
4.3%
6 119
 
4.3%
2 114
 
4.1%
7 101
 
3.6%
4 91
 
3.3%
Other values (12) 189
 
6.8%
Hangul
ValueCountFrequency (%)
동 282
 
7.5%
원 278
 
7.4%
구 278
 
7.4%
시 274
 
7.3%
노 274
 
7.3%
서 271
 
7.2%
특 271
 
7.2%
별 271
 
7.2%
울 271
 
7.2%
계 229
 
6.1%
Other values (124) 1077
28.5%

도로명주소
Text

MISSING 

Distinct125
Distinct (%)99.2%
Missing149
Missing (%)54.2%
Memory size2.3 KiB
2024-05-11T14:54:41.698878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length36
Min length23

Characters and Unicode

Total characters4536
Distinct characters156
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)98.4%

Sample

1st row서울특별시 노원구 동일로204가길 46 (중계동)
2nd row서울특별시 노원구 공릉로 183 (공릉동)
3rd row서울특별시 노원구 한글비석로 471 (상계동)
4th row서울특별시 노원구 한글비석로 57, 지하1층 (하계동, 세이브존)
5th row서울특별시 노원구 한글비석로 384 (중계동, (중계동 591))
ValueCountFrequency (%)
서울특별시 126
 
14.5%
노원구 126
 
14.5%
상계동 56
 
6.5%
공릉동 32
 
3.7%
1층 25
 
2.9%
중계동 21
 
2.4%
동일로 18
 
2.1%
한글비석로 15
 
1.7%
월계동 13
 
1.5%
지하1층 11
 
1.3%
Other values (295) 423
48.8%
2024-05-11T14:54:42.620886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
740
 
16.3%
1 223
 
4.9%
동 200
 
4.4%
, 141
 
3.1%
원 140
 
3.1%
노 137
 
3.0%
( 130
 
2.9%
) 130
 
2.9%
구 128
 
2.8%
시 127
 
2.8%
Other values (146) 2440
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2535
55.9%
Decimal Number 813
 
17.9%
Space Separator 740
 
16.3%
Other Punctuation 142
 
3.1%
Open Punctuation 130
 
2.9%
Close Punctuation 130
 
2.9%
Dash Punctuation 34
 
0.7%
Uppercase Letter 9
 
0.2%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 200
 
7.9%
원 140
 
5.5%
노 137
 
5.4%
구 128
 
5.0%
시 127
 
5.0%
서 126
 
5.0%
특 126
 
5.0%
별 126
 
5.0%
울 126
 
5.0%
로 126
 
5.0%
Other values (124) 1173
46.3%
Decimal Number
ValueCountFrequency (%)
1 223
27.4%
2 109
13.4%
3 92
11.3%
0 84
 
10.3%
4 69
 
8.5%
5 57
 
7.0%
6 50
 
6.2%
8 46
 
5.7%
9 42
 
5.2%
7 41
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
E 3
33.3%
S 2
22.2%
A 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 141
99.3%
@ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
740
100.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2535
55.9%
Common 1990
43.9%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 200
 
7.9%
원 140
 
5.5%
노 137
 
5.4%
구 128
 
5.0%
시 127
 
5.0%
서 126
 
5.0%
특 126
 
5.0%
별 126
 
5.0%
울 126
 
5.0%
로 126
 
5.0%
Other values (124) 1173
46.3%
Common
ValueCountFrequency (%)
740
37.2%
1 223
 
11.2%
, 141
 
7.1%
( 130
 
6.5%
) 130
 
6.5%
2 109
 
5.5%
3 92
 
4.6%
0 84
 
4.2%
4 69
 
3.5%
5 57
 
2.9%
Other values (7) 215
 
10.8%
Latin
ValueCountFrequency (%)
B 3
27.3%
E 3
27.3%
S 2
18.2%
n 2
18.2%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2535
55.9%
ASCII 2001
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
740
37.0%
1 223
 
11.1%
, 141
 
7.0%
( 130
 
6.5%
) 130
 
6.5%
2 109
 
5.4%
3 92
 
4.6%
0 84
 
4.2%
4 69
 
3.4%
5 57
 
2.8%
Other values (12) 226
 
11.3%
Hangul
ValueCountFrequency (%)
동 200
 
7.9%
원 140
 
5.5%
노 137
 
5.4%
구 128
 
5.0%
시 127
 
5.0%
서 126
 
5.0%
특 126
 
5.0%
별 126
 
5.0%
울 126
 
5.0%
로 126
 
5.0%
Other values (124) 1173
46.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)67.2%
Missing150
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean1749.52
Minimum1601
Maximum1913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:42.915689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1601
5-th percentile1610.2
Q11674
median1740
Q31846
95-th percentile1885
Maximum1913
Range312
Interquartile range (IQR)172

Descriptive statistics

Standard deviation93.58329
Coefficient of variation (CV)0.053490838
Kurtosis-1.3975106
Mean1749.52
Median Absolute Deviation (MAD)82
Skewness0.093005914
Sum218690
Variance8757.8323
MonotonicityNot monotonic
2024-05-11T14:54:43.211803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1695 7
 
2.5%
1857 5
 
1.8%
1617 3
 
1.1%
1848 3
 
1.1%
1746 3
 
1.1%
1845 3
 
1.1%
1663 3
 
1.1%
1779 3
 
1.1%
1808 2
 
0.7%
1885 2
 
0.7%
Other values (74) 91
33.1%
(Missing) 150
54.5%
ValueCountFrequency (%)
1601 1
 
0.4%
1604 1
 
0.4%
1606 1
 
0.4%
1607 1
 
0.4%
1609 2
0.7%
1610 1
 
0.4%
1611 1
 
0.4%
1617 3
1.1%
1620 1
 
0.4%
1630 1
 
0.4%
ValueCountFrequency (%)
1913 2
0.7%
1906 1
0.4%
1905 1
0.4%
1899 1
0.4%
1898 1
0.4%
1885 2
0.7%
1873 2
0.7%
1872 1
0.4%
1869 1
0.4%
1868 1
0.4%

사업장명
Text

Distinct257
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-05-11T14:54:43.670079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length5.9781818
Min length2

Characters and Unicode

Total characters1644
Distinct characters333
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

Unique242 ?
Unique (%)88.0%

Sample

1st row(주)씨마마트 중계점
2nd row(주)미도파
3rd row청구식품(주)
4th row(주)미동농산
5th row서방유통
ValueCountFrequency (%)
주식회사 5
 
1.5%
주)석보유통 3
 
0.9%
영우유통 3
 
0.9%
주)제이에프앤비 3
 
0.9%
유통 3
 
0.9%
두부집 2
 
0.6%
노원점 2
 
0.6%
식자재 2
 
0.6%
떡방 2
 
0.6%
강경젓갈 2
 
0.6%
Other values (286) 299
91.7%
2024-05-11T14:54:44.412880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 66
 
4.0%
( 64
 
3.9%
) 64
 
3.9%
51
 
3.1%
마 41
 
2.5%
식 39
 
2.4%
트 37
 
2.3%
통 37
 
2.3%
유 35
 
2.1%
이 34
 
2.1%
Other values (323) 1176
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1417
86.2%
Open Punctuation 64
 
3.9%
Close Punctuation 64
 
3.9%
Space Separator 51
 
3.1%
Uppercase Letter 23
 
1.4%
Lowercase Letter 12
 
0.7%
Decimal Number 6
 
0.4%
Other Punctuation 4
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 66
 
4.7%
마 41
 
2.9%
식 39
 
2.8%
트 37
 
2.6%
통 37
 
2.6%
유 35
 
2.5%
이 34
 
2.4%
스 28
 
2.0%
품 28
 
2.0%
원 22
 
1.6%
Other values (295) 1050
74.1%
Uppercase Letter
ValueCountFrequency (%)
S 5
21.7%
M 3
13.0%
K 3
13.0%
G 3
13.0%
L 1
 
4.3%
T 1
 
4.3%
N 1
 
4.3%
Y 1
 
4.3%
U 1
 
4.3%
C 1
 
4.3%
Other values (3) 3
13.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
25.0%
r 3
25.0%
t 3
25.0%
m 2
16.7%
s 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
5 2
33.3%
6 2
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
' 1
25.0%
& 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1417
86.2%
Common 192
 
11.7%
Latin 35
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 66
 
4.7%
마 41
 
2.9%
식 39
 
2.8%
트 37
 
2.6%
통 37
 
2.6%
유 35
 
2.5%
이 34
 
2.4%
스 28
 
2.0%
품 28
 
2.0%
원 22
 
1.6%
Other values (295) 1050
74.1%
Latin
ValueCountFrequency (%)
S 5
14.3%
M 3
 
8.6%
a 3
 
8.6%
r 3
 
8.6%
t 3
 
8.6%
K 3
 
8.6%
G 3
 
8.6%
m 2
 
5.7%
s 1
 
2.9%
L 1
 
2.9%
Other values (8) 8
22.9%
Common
ValueCountFrequency (%)
( 64
33.3%
) 64
33.3%
51
26.6%
- 3
 
1.6%
3 2
 
1.0%
5 2
 
1.0%
6 2
 
1.0%
. 2
 
1.0%
' 1
 
0.5%
& 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1417
86.2%
ASCII 227
 
13.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 66
 
4.7%
마 41
 
2.9%
식 39
 
2.8%
트 37
 
2.6%
통 37
 
2.6%
유 35
 
2.5%
이 34
 
2.4%
스 28
 
2.0%
품 28
 
2.0%
원 22
 
1.6%
Other values (295) 1050
74.1%
ASCII
ValueCountFrequency (%)
( 64
28.2%
) 64
28.2%
51
22.5%
S 5
 
2.2%
M 3
 
1.3%
a 3
 
1.3%
r 3
 
1.3%
t 3
 
1.3%
K 3
 
1.3%
- 3
 
1.3%
Other values (18) 25
 
11.0%

최종수정일자
Date

Distinct260
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1999-10-16 00:00:00
Maximum2024-05-03 15:20:35
2024-05-11T14:54:44.661206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:44.956292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
I
217 
U
58 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 217
78.9%
U 58
 
21.1%

Length

2024-05-11T14:54:45.184814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:45.330354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 217
78.9%
u 58
 
21.1%

데이터갱신일자
Date

Distinct78
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T14:54:45.528339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:45.755724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
식품소분업
275 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 275
100.0%

Length

2024-05-11T14:54:45.980959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:46.113137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 275
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct157
Distinct (%)58.4%
Missing6
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean205930.26
Minimum203904.66
Maximum208129.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:46.263324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203904.66
5-th percentile204661.69
Q1205320.28
median205994.81
Q3206415.55
95-th percentile207092.44
Maximum208129.13
Range4224.4715
Interquartile range (IQR)1095.2603

Descriptive statistics

Standard deviation740.69294
Coefficient of variation (CV)0.0035968146
Kurtosis-0.26091339
Mean205930.26
Median Absolute Deviation (MAD)603.74144
Skewness-0.14982337
Sum55395239
Variance548626.04
MonotonicityNot monotonic
2024-05-11T14:54:46.501139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205320.28476675 24
 
8.7%
206132.432496938 16
 
5.8%
205994.811815848 10
 
3.6%
205645.891969072 7
 
2.5%
205391.070378059 7
 
2.5%
205985.953324881 7
 
2.5%
205715.538939251 7
 
2.5%
205931.05327036 6
 
2.2%
206342.011931277 4
 
1.5%
205039.222100248 4
 
1.5%
Other values (147) 177
64.4%
(Missing) 6
 
2.2%
ValueCountFrequency (%)
203904.660962669 1
0.4%
203920.549325193 1
0.4%
203982.774049825 1
0.4%
204463.453552983 1
0.4%
204481.248686527 1
0.4%
204490.893862492 1
0.4%
204498.444678905 1
0.4%
204525.903979787 1
0.4%
204560.136414941 1
0.4%
204581.851473752 1
0.4%
ValueCountFrequency (%)
208129.13249453 1
0.4%
207577.515810212 1
0.4%
207447.636537089 1
0.4%
207334.879052168 1
0.4%
207313.112525229 1
0.4%
207311.175792021 1
0.4%
207308.302350224 1
0.4%
207274.300313358 1
0.4%
207224.076240442 1
0.4%
207176.887096655 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct157
Distinct (%)58.4%
Missing6
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean460514.14
Minimum457115.96
Maximum464849.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-05-11T14:54:46.760629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457115.96
5-th percentile457733.16
Q1458685.78
median460669.84
Q3461935.34
95-th percentile463328.46
Maximum464849.97
Range7734.008
Interquartile range (IQR)3249.5623

Descriptive statistics

Standard deviation1841.9863
Coefficient of variation (CV)0.0039998474
Kurtosis-1.0506632
Mean460514.14
Median Absolute Deviation (MAD)1430.4155
Skewness-0.081752384
Sum1.238783 × 108
Variance3392913.4
MonotonicityNot monotonic
2024-05-11T14:54:47.013036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461419.881795004 24
 
8.7%
460549.311157153 16
 
5.8%
459502.645279682 10
 
3.6%
459609.012509743 7
 
2.5%
458333.989216339 7
 
2.5%
459730.43776924 7
 
2.5%
462416.211580109 7
 
2.5%
459884.197207567 6
 
2.2%
461845.269709197 4
 
1.5%
462624.307076651 4
 
1.5%
Other values (147) 177
64.4%
(Missing) 6
 
2.2%
ValueCountFrequency (%)
457115.96094971 1
0.4%
457170.948044949 1
0.4%
457275.799282625 2
0.7%
457351.949998965 1
0.4%
457353.229350385 1
0.4%
457409.966707104 1
0.4%
457423.674667457 1
0.4%
457576.086812428 1
0.4%
457610.711998051 1
0.4%
457649.746511956 1
0.4%
ValueCountFrequency (%)
464849.968985063 1
0.4%
464080.593904719 1
0.4%
463966.29285643 1
0.4%
463801.619709388 1
0.4%
463780.370456798 1
0.4%
463777.629639984 1
0.4%
463742.831913572 1
0.4%
463701.187684051 1
0.4%
463631.765927204 2
0.7%
463554.778417158 1
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
식품소분업
249 
<NA>
26 

Length

Max length5
Median length5
Mean length4.9054545
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 249
90.5%
<NA> 26
 
9.5%

Length

2024-05-11T14:54:47.242164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:47.422370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 249
90.5%
na 26
 
9.5%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
240 
0
29 
1
 
6

Length

Max length4
Median length4
Mean length3.6181818
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 240
87.3%
0 29
 
10.5%
1 6
 
2.2%

Length

2024-05-11T14:54:47.614766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:47.781558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
87.3%
0 29
 
10.5%
1 6
 
2.2%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
243 
0
29 
1
 
3

Length

Max length4
Median length4
Mean length3.6509091
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row0
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 243
88.4%
0 29
 
10.5%
1 3
 
1.1%

Length

2024-05-11T14:54:47.953934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:48.129888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 243
88.4%
0 29
 
10.5%
1 3
 
1.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
249 
기타
 
11
주택가주변
 
8
아파트지역
 
6
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9854545
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row아파트지역
2nd row아파트지역
3rd row주택가주변
4th row주택가주변
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 249
90.5%
기타 11
 
4.0%
주택가주변 8
 
2.9%
아파트지역 6
 
2.2%
유흥업소밀집지역 1
 
0.4%

Length

2024-05-11T14:54:48.349624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:48.522668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
90.5%
기타 11
 
4.0%
주택가주변 8
 
2.9%
아파트지역 6
 
2.2%
유흥업소밀집지역 1
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
249 
기타
 
20
갑
 
4
자율
 
2

Length

Max length4
Median length4
Mean length3.7963636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 249
90.5%
기타 20
 
7.3%
갑 4
 
1.5%
자율 2
 
0.7%

Length

2024-05-11T14:54:48.714125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:48.895801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 249
90.5%
기타 20
 
7.3%
갑 4
 
1.5%
자율 2
 
0.7%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
250 
상수도전용
 
25

Length

Max length5
Median length4
Mean length4.0909091
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 250
90.9%
상수도전용 25
 
9.1%

Length

2024-05-11T14:54:49.093542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:49.259963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 250
90.9%
상수도전용 25
 
9.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
263 
0
 
12

Length

Max length4
Median length4
Mean length3.8690909
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 263
95.6%
0 12
 
4.4%

Length

2024-05-11T14:54:49.411918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:49.569591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 263
95.6%
0 12
 
4.4%

본사종업원수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
243 
0
32 

Length

Max length4
Median length4
Mean length3.6509091
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 243
88.4%
0 32
 
11.6%

Length

2024-05-11T14:54:49.768535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:49.953501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 243
88.4%
0 32
 
11.6%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
243 
0
32 

Length

Max length4
Median length4
Mean length3.6509091
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 243
88.4%
0 32
 
11.6%

Length

2024-05-11T14:54:50.495286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:50.679087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 243
88.4%
0 32
 
11.6%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
240 
0
32 
1
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.6181818
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
87.3%
0 32
 
11.6%
1 2
 
0.7%
2 1
 
0.4%

Length

2024-05-11T14:54:50.863437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:51.127043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
87.3%
0 32
 
11.6%
1 2
 
0.7%
2 1
 
0.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
240 
0
32 
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.6181818
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
87.3%
0 32
 
11.6%
1 2
 
0.7%
3 1
 
0.4%

Length

2024-05-11T14:54:51.356668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:51.528014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
87.3%
0 32
 
11.6%
1 2
 
0.7%
3 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
177 
자가
68 
임대
30 

Length

Max length4
Median length4
Mean length3.2872727
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 177
64.4%
자가 68
 
24.7%
임대 30
 
10.9%

Length

2024-05-11T14:54:51.722209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:51.920435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 177
64.4%
자가 68
 
24.7%
임대 30
 
10.9%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
263 
0
 
12

Length

Max length4
Median length4
Mean length3.8690909
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 263
95.6%
0 12
 
4.4%

Length

2024-05-11T14:54:52.107225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:52.298636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 263
95.6%
0 12
 
4.4%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
263 
0
 
12

Length

Max length4
Median length4
Mean length3.8690909
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 263
95.6%
0 12
 
4.4%

Length

2024-05-11T14:54:52.505986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:52.669104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 263
95.6%
0 12
 
4.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing26
Missing (%)9.5%
Memory size682.0 B
False
249 
(Missing)
26 
ValueCountFrequency (%)
False 249
90.5%
(Missing) 26
 
9.5%
2024-05-11T14:54:52.815173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
0
249 
<NA>
26 

Length

Max length4
Median length1
Mean length1.2836364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 249
90.5%
<NA> 26
 
9.5%

Length

2024-05-11T14:54:52.981007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:53.145925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 249
90.5%
na 26
 
9.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing275
Missing (%)100.0%
Memory size2.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-109-1991-0027419910605<NA>3폐업2폐업20040320<NA><NA><NA>02 971900091.4139863서울특별시 노원구 중계동 506-1<NA><NA>(주)씨마마트 중계점2002-10-05 00:00:00I2018-08-31 23:59:59.0식품소분업205645.891969459609.01251식품소분업00아파트지역갑<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
131000003100000-109-1992-0014519920831<NA>3폐업2폐업19971125<NA><NA><NA>02 939222288.4139200서울특별시 노원구 상계동 713-0 미도파 지하동<NA><NA>(주)미도파2001-09-29 00:00:00I2018-08-31 23:59:59.0식품소분업205320.284767461419.881795식품소분업<NA><NA>아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
231000003100000-109-1992-0022619920128<NA>3폐업2폐업20060411<NA><NA><NA>02 949101159.5139240서울특별시 노원구 공릉동 383-2<NA><NA>청구식품(주)2003-01-10 00:00:00I2018-08-31 23:59:59.0식품소분업206247.959836458163.060725식품소분업00주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
331000003100000-109-1996-0014619960829<NA>3폐업2폐업20080613<NA><NA><NA>02 951043820.93139855서울특별시 노원구 중계동 94-4<NA><NA>(주)미동농산2007-12-05 10:46:53I2018-08-31 23:59:59.0식품소분업207176.887097460962.56139식품소분업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
431000003100000-109-1996-0014719961118<NA>3폐업2폐업20050616<NA><NA><NA>02 934666218.0139871서울특별시 노원구 하계동 164-2<NA><NA>서방유통2001-09-29 00:00:00I2018-08-31 23:59:59.0식품소분업206414.974017459239.420954식품소분업<NA><NA>주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
531000003100000-109-1996-0014819961210<NA>3폐업2폐업20021227<NA><NA><NA>02 0000010.24139230서울특별시 노원구 하계동 산 61-7<NA><NA>(주)스위트드림2001-09-29 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업<NA><NA>주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
631000003100000-109-1996-0014919960112<NA>3폐업2폐업20030423<NA><NA><NA>02 9342315<NA>139860서울특별시 노원구 중계동 360-2 청구상가<NA><NA>(주)스파메트로 미도파슈퍼2003-04-01 00:00:00I2018-08-31 23:59:59.0식품소분업206490.247358460830.61536식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
731000003100000-109-1997-001491997-01-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 948200122.77139-865서울특별시 노원구 중계동 509-0서울특별시 노원구 동일로204가길 46 (중계동)1783(주)이랜드킴스클럽중계점2024-04-22 15:07:58U2023-12-03 22:04:00.0식품소분업205931.05327459884.197208<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831000003100000-109-1997-0015019970211<NA>3폐업2폐업20021116<NA><NA><NA>02 948119219.55139865서울특별시 노원구 중계동 512-0 시영2단지 상가 지하<NA><NA>홍진 에이전시1999-12-06 00:00:00I2018-08-31 23:59:59.0식품소분업205805.621561460041.339536식품소분업00아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
931000003100000-109-1997-0015119970217<NA>3폐업2폐업19990323<NA><NA><NA>023392089322.23139861서울특별시 노원구 중계동 364-17<NA><NA>그린벤츄어스2001-09-29 00:00:00I2018-08-31 23:59:59.0식품소분업206719.586259460669.836412식품소분업11아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
26531000003100000-109-2022-0000220221012<NA>1영업/정상1영업<NA><NA><NA><NA><NA>11.83139820서울특별시 노원구 상계동 450 교림노원프라자서울특별시 노원구 한글비석로 444, 교림노원프라자 407-1호 (상계동)1666김찬형생활건강2022-10-12 14:47:52I2021-10-30 23:04:00.0식품소분업205978.185784462367.006783<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26631000003100000-109-2023-0000120230102<NA>1영업/정상1영업<NA><NA><NA><NA>02 938808021.19139748서울특별시 노원구 상계동 173-1 벽산아파트서울특별시 노원구 한글비석로 396, 상가 109동 지층 19호 (상계동, 벽산아파트)1663고소미 선식2023-01-02 11:09:25I2022-12-01 00:04:00.0식품소분업206356.223148462123.478005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26731000003100000-109-2023-000022023-02-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.0139-240서울특별시 노원구 공릉동 571-16 연송빌딩서울특별시 노원구 동일로173가길 81, 연송빌딩 303호 (공릉동)1856주식회사 리얼리프이앤아이2023-02-08 15:19:00I2022-12-01 23:00:00.0식품소분업206321.030385457731.027184<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26831000003100000-109-2023-000032023-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.75139-863서울특별시 노원구 중계동 501-9서울특별시 노원구 동일로207길 50, 북부여성창업보육센터 2층 205호 (중계동)1771칠랙스2023-02-21 13:29:19I2022-12-01 22:03:00.0식품소분업205373.991036460072.170783<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26931000003100000-109-2023-000042023-03-13<NA>1영업/정상1영업<NA><NA><NA><NA>02 931 622211.36139-822서울특별시 노원구 상계동 649 12단지 종합상가서울특별시 노원구 동일로 1538, 12단지 종합상가 지하1층 4호중 일부 6호 (상계동)1674호정2023-03-13 17:52:05I2022-12-02 23:05:00.0식품소분업205039.2221462624.307077<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27031000003100000-109-2023-000052023-03-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.05139-200서울특별시 노원구 상계동 1313 수락리버시티4단지서울특별시 노원구 누원로 18, 상가동 2층 201호 (상계동, 수락리버시티4단지)1601다소니2023-03-14 14:38:17I2022-12-02 23:06:00.0식품소분업204655.7679464849.968985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27131000003100000-109-2023-000062023-09-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0139-803서울특별시 노원구 공릉동 392-4 EnS빌딩 E-1005호서울특별시 노원구 동일로190길 43-6, EnS빌딩 지하1층 E-1005호 (공릉동)1842루씨의 하루2023-09-01 15:28:53I2022-12-09 00:03:00.0식품소분업206597.645827458224.723279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27231000003100000-109-2023-000072023-09-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.79139-842서울특별시 노원구 월계동 321-2 희성프라자서울특별시 노원구 월계로 370, 희성프라자 508-2호 (월계동)1905베이빈2023-09-07 10:18:23I2022-12-09 00:09:00.0식품소분업205316.296327458732.958772<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27331000003100000-109-2024-000012024-01-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0139-050서울특별시 노원구 월계동 333-1서울특별시 노원구 마들로3길 17, 1층 (월계동)1906트레이더스 홀세일 클럽 월계점2024-04-08 15:09:02U2023-12-03 23:00:00.0식품소분업205391.070378458333.989216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27431000003100000-109-2024-000022024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0139-803서울특별시 노원구 공릉동 392-4 EnS빌딩서울특별시 노원구 동일로190길 43-6, EnS빌딩 지하1층 B-1004호 (공릉동)1842네오컨텐츠2024-03-13 11:16:09I2023-12-02 23:06:00.0식품소분업206597.645827458224.723279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>