Overview

Dataset statistics

Number of variables44
Number of observations8020
Missing cells72765
Missing cells (%)20.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 MiB
Average record size in memory376.0 B

Variable types

Categorical21
Text7
Unsupported7
DateTime3
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18451/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (58.8%)Imbalance
영업상태명 is highly imbalanced (58.8%)Imbalance
상세영업상태코드 is highly imbalanced (58.8%)Imbalance
상세영업상태명 is highly imbalanced (58.8%)Imbalance
업태구분명 is highly imbalanced (98.5%)Imbalance
위생업태명 is highly imbalanced (54.0%)Imbalance
남성종사자수 is highly imbalanced (76.1%)Imbalance
여성종사자수 is highly imbalanced (74.2%)Imbalance
영업장주변구분명 is highly imbalanced (74.0%)Imbalance
등급구분명 is highly imbalanced (76.9%)Imbalance
급수시설구분명 is highly imbalanced (70.0%)Imbalance
총인원 is highly imbalanced (66.1%)Imbalance
본사종업원수 is highly imbalanced (55.9%)Imbalance
공장판매직종업원수 is highly imbalanced (64.9%)Imbalance
공장생산직종업원수 is highly imbalanced (64.9%)Imbalance
인허가취소일자 has 8020 (100.0%) missing valuesMissing
폐업일자 has 664 (8.3%) missing valuesMissing
휴업시작일자 has 8020 (100.0%) missing valuesMissing
휴업종료일자 has 8020 (100.0%) missing valuesMissing
재개업일자 has 8020 (100.0%) missing valuesMissing
전화번호 has 4093 (51.0%) missing valuesMissing
소재지면적 has 4089 (51.0%) missing valuesMissing
도로명주소 has 2083 (26.0%) missing valuesMissing
도로명우편번호 has 2096 (26.1%) missing valuesMissing
좌표정보(X) has 224 (2.8%) missing valuesMissing
좌표정보(Y) has 224 (2.8%) missing valuesMissing
다중이용업소여부 has 1573 (19.6%) missing valuesMissing
시설총규모 has 1573 (19.6%) missing valuesMissing
전통업소지정번호 has 8020 (100.0%) missing valuesMissing
전통업소주된음식 has 8020 (100.0%) missing valuesMissing
홈페이지 has 8020 (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
소재지면적 has 412 (5.1%) zerosZeros
시설총규모 has 6183 (77.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:54:43.643739
Analysis finished2024-05-11 06:54:46.452083
Duration2.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
3240000
8020 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 8020
100.0%

Length

2024-05-11T15:54:46.582829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:46.775221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 8020
100.0%

관리번호
Text

UNIQUE 

Distinct8020
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
2024-05-11T15:54:47.099943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters176440
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

Unique8020 ?
Unique (%)100.0%

Sample

1st row3240000-107-1976-00001
2nd row3240000-107-1976-00002
3rd row3240000-107-1976-00003
4th row3240000-107-1976-00004
5th row3240000-107-1977-00001
ValueCountFrequency (%)
3240000-107-1976-00001 1
 
< 0.1%
3240000-107-2020-00169 1
 
< 0.1%
3240000-107-2020-00183 1
 
< 0.1%
3240000-107-2020-00182 1
 
< 0.1%
3240000-107-2020-00181 1
 
< 0.1%
3240000-107-2020-00180 1
 
< 0.1%
3240000-107-2020-00179 1
 
< 0.1%
3240000-107-2020-00178 1
 
< 0.1%
3240000-107-2020-00177 1
 
< 0.1%
3240000-107-2020-00176 1
 
< 0.1%
Other values (8010) 8010
99.9%
2024-05-11T15:54:47.682160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 69820
39.6%
- 24060
 
13.6%
2 21988
 
12.5%
1 16337
 
9.3%
3 11366
 
6.4%
4 10788
 
6.1%
7 10559
 
6.0%
9 3895
 
2.2%
8 2591
 
1.5%
6 2533
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 152380
86.4%
Dash Punctuation 24060
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 69820
45.8%
2 21988
 
14.4%
1 16337
 
10.7%
3 11366
 
7.5%
4 10788
 
7.1%
7 10559
 
6.9%
9 3895
 
2.6%
8 2591
 
1.7%
6 2533
 
1.7%
5 2503
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 24060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 69820
39.6%
- 24060
 
13.6%
2 21988
 
12.5%
1 16337
 
9.3%
3 11366
 
6.4%
4 10788
 
6.1%
7 10559
 
6.0%
9 3895
 
2.2%
8 2591
 
1.5%
6 2533
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 69820
39.6%
- 24060
 
13.6%
2 21988
 
12.5%
1 16337
 
9.3%
3 11366
 
6.4%
4 10788
 
6.1%
7 10559
 
6.0%
9 3895
 
2.2%
8 2591
 
1.5%
6 2533
 
1.4%
Distinct4035
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
2024-05-11T15:54:48.228679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2411471
Min length8

Characters and Unicode

Total characters66094
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2078 ?
Unique (%)25.9%

Sample

1st row19760501
2nd row19760501
3rd row19760501
4th row19760721
5th row19771115
ValueCountFrequency (%)
20180508 11
 
0.1%
20191029 10
 
0.1%
2024-05-08 9
 
0.1%
20200601 9
 
0.1%
20200818 9
 
0.1%
20190820 9
 
0.1%
2023-03-20 8
 
0.1%
20170131 8
 
0.1%
20210806 8
 
0.1%
20191112 8
 
0.1%
Other values (4025) 7931
98.9%
2024-05-11T15:54:48.998775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19794
29.9%
2 15768
23.9%
1 11596
17.5%
9 3668
 
5.5%
3 2752
 
4.2%
8 2593
 
3.9%
7 2345
 
3.5%
6 2001
 
3.0%
- 1934
 
2.9%
4 1911
 
2.9%
Other values (2) 1732
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64158
97.1%
Dash Punctuation 1934
 
2.9%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19794
30.9%
2 15768
24.6%
1 11596
18.1%
9 3668
 
5.7%
3 2752
 
4.3%
8 2593
 
4.0%
7 2345
 
3.7%
6 2001
 
3.1%
4 1911
 
3.0%
5 1730
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 1934
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66094
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19794
29.9%
2 15768
23.9%
1 11596
17.5%
9 3668
 
5.5%
3 2752
 
4.2%
8 2593
 
3.9%
7 2345
 
3.5%
6 2001
 
3.0%
- 1934
 
2.9%
4 1911
 
2.9%
Other values (2) 1732
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19794
29.9%
2 15768
23.9%
1 11596
17.5%
9 3668
 
5.5%
3 2752
 
4.2%
8 2593
 
3.9%
7 2345
 
3.5%
6 2001
 
3.0%
- 1934
 
2.9%
4 1911
 
2.9%
Other values (2) 1732
 
2.6%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
3
7356 
1
 
664

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 7356
91.7%
1 664
 
8.3%

Length

2024-05-11T15:54:49.222850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:49.359987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7356
91.7%
1 664
 
8.3%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
폐업
7356 
영업/정상
 
664

Length

Max length5
Median length2
Mean length2.2483791
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row영업/정상
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 7356
91.7%
영업/정상 664
 
8.3%

Length

2024-05-11T15:54:49.522708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:49.678503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7356
91.7%
영업/정상 664
 
8.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
2
7356 
1
 
664

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7356
91.7%
1 664
 
8.3%

Length

2024-05-11T15:54:49.813209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:49.936027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7356
91.7%
1 664
 
8.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
폐업
7356 
영업
 
664

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7356
91.7%
영업 664
 
8.3%

Length

2024-05-11T15:54:50.106875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:50.345525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7356
91.7%
영업 664
 
8.3%

폐업일자
Date

MISSING 

Distinct3545
Distinct (%)48.2%
Missing664
Missing (%)8.3%
Memory size62.8 KiB
Minimum1990-03-12 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:54:50.563993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:50.776892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

전화번호
Text

MISSING 

Distinct1818
Distinct (%)46.3%
Missing4093
Missing (%)51.0%
Memory size62.8 KiB
2024-05-11T15:54:51.509134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.79068
Min length2

Characters and Unicode

Total characters42375
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1534 ?
Unique (%)39.1%

Sample

1st row483 8380
2nd row483 6500
3rd row02 474 5500
4th row478 5974
5th row0334264572
ValueCountFrequency (%)
02 2009
 
21.8%
031 880
 
9.6%
070 230
 
2.5%
792 139
 
1.5%
858 108
 
1.2%
1226 104
 
1.1%
032 99
 
1.1%
062 88
 
1.0%
426 87
 
0.9%
055 82
 
0.9%
Other values (1976) 5371
58.4%
2024-05-11T15:54:52.137186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6515
15.4%
2 6282
14.8%
0 6168
14.6%
4 3615
8.5%
3 3367
7.9%
1 3249
7.7%
8 3099
7.3%
7 2969
7.0%
5 2720
6.4%
6 2260
 
5.3%
Other values (2) 2131
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35858
84.6%
Space Separator 6515
 
15.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6282
17.5%
0 6168
17.2%
4 3615
10.1%
3 3367
9.4%
1 3249
9.1%
8 3099
8.6%
7 2969
8.3%
5 2720
7.6%
6 2260
 
6.3%
9 2129
 
5.9%
Space Separator
ValueCountFrequency (%)
6515
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42375
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6515
15.4%
2 6282
14.8%
0 6168
14.6%
4 3615
8.5%
3 3367
7.9%
1 3249
7.7%
8 3099
7.3%
7 2969
7.0%
5 2720
6.4%
6 2260
 
5.3%
Other values (2) 2131
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6515
15.4%
2 6282
14.8%
0 6168
14.6%
4 3615
8.5%
3 3367
7.9%
1 3249
7.7%
8 3099
7.3%
7 2969
7.0%
5 2720
6.4%
6 2260
 
5.3%
Other values (2) 2131
 
5.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct913
Distinct (%)23.2%
Missing4089
Missing (%)51.0%
Infinite0
Infinite (%)0.0%
Mean17.486619
Minimum0
Maximum678
Zeros412
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size70.6 KiB
2024-05-11T15:54:52.374580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3
median10
Q325.5
95-th percentile49.5
Maximum678
Range678
Interquartile range (IQR)22.2

Descriptive statistics

Standard deviation24.672303
Coefficient of variation (CV)1.4109247
Kurtosis164.20901
Mean17.486619
Median Absolute Deviation (MAD)8
Skewness8.7216879
Sum68739.9
Variance608.72253
MonotonicityNot monotonic
2024-05-11T15:54:52.679312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 412
 
5.1%
3.3 323
 
4.0%
6.6 257
 
3.2%
33.0 149
 
1.9%
10.0 109
 
1.4%
5.0 106
 
1.3%
6.0 98
 
1.2%
3.0 81
 
1.0%
26.4 75
 
0.9%
9.9 72
 
0.9%
Other values (903) 2249
28.0%
(Missing) 4089
51.0%
ValueCountFrequency (%)
0.0 412
5.1%
0.3 1
 
< 0.1%
0.8 1
 
< 0.1%
0.82 1
 
< 0.1%
0.86 1
 
< 0.1%
0.9 2
 
< 0.1%
0.96 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 3
 
< 0.1%
1.12 1
 
< 0.1%
ValueCountFrequency (%)
678.0 1
< 0.1%
377.14 1
< 0.1%
300.0 1
< 0.1%
298.73 1
< 0.1%
295.56 1
< 0.1%
246.24 1
< 0.1%
244.71 1
< 0.1%
233.0 1
< 0.1%
210.0 1
< 0.1%
209.92 1
< 0.1%
Distinct180
Distinct (%)2.2%
Missing3
Missing (%)< 0.1%
Memory size62.8 KiB
2024-05-11T15:54:53.210649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1206187
Min length6

Characters and Unicode

Total characters49069
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

Unique32 ?
Unique (%)0.4%

Sample

1st row134873
2nd row134863
3rd row134870
4th row134864
5th row134873
ValueCountFrequency (%)
134779 1116
 
13.9%
134825 850
 
10.6%
134874 743
 
9.3%
134830 489
 
6.1%
134080 429
 
5.4%
134861 375
 
4.7%
134873 347
 
4.3%
134848 284
 
3.5%
134-779 208
 
2.6%
134819 171
 
2.1%
Other values (170) 3005
37.5%
2024-05-11T15:54:53.945663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 9652
19.7%
3 9277
18.9%
1 9178
18.7%
8 7127
14.5%
7 4354
8.9%
0 2656
 
5.4%
9 1956
 
4.0%
5 1573
 
3.2%
2 1414
 
2.9%
- 967
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48102
98.0%
Dash Punctuation 967
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9652
20.1%
3 9277
19.3%
1 9178
19.1%
8 7127
14.8%
7 4354
9.1%
0 2656
 
5.5%
9 1956
 
4.1%
5 1573
 
3.3%
2 1414
 
2.9%
6 915
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 967
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49069
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 9652
19.7%
3 9277
18.9%
1 9178
18.7%
8 7127
14.5%
7 4354
8.9%
0 2656
 
5.4%
9 1956
 
4.0%
5 1573
 
3.2%
2 1414
 
2.9%
- 967
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9652
19.7%
3 9277
18.9%
1 9178
18.7%
8 7127
14.5%
7 4354
8.9%
0 2656
 
5.4%
9 1956
 
4.0%
5 1573
 
3.2%
2 1414
 
2.9%
- 967
 
2.0%
Distinct3098
Distinct (%)38.6%
Missing3
Missing (%)< 0.1%
Memory size62.8 KiB
2024-05-11T15:54:54.437048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length48
Mean length26.176126
Min length15

Characters and Unicode

Total characters209854
Distinct characters355
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2551 ?
Unique (%)31.8%

Sample

1st row서울특별시 강동구 천호동 422-2 천호신시장 82호
2nd row서울특별시 강동구 천호동 395-7 1층
3rd row서울특별시 강동구 천호동 362-34
4th row서울특별시 강동구 천호동 166-102
5th row서울특별시 강동구 천호동 422-131
ValueCountFrequency (%)
서울특별시 8017
19.4%
강동구 8017
19.4%
천호동 3358
 
8.1%
명일동 1604
 
3.9%
현대백화점 1216
 
2.9%
572 926
 
2.2%
성내동 846
 
2.0%
46-4 789
 
1.9%
고덕동 717
 
1.7%
454-1 598
 
1.4%
Other values (2700) 15301
37.0%
2024-05-11T15:54:55.219073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39563
18.9%
16612
 
7.9%
8391
 
4.0%
8353
 
4.0%
8302
 
4.0%
8212
 
3.9%
8029
 
3.8%
8017
 
3.8%
8017
 
3.8%
4 6353
 
3.0%
Other values (345) 90005
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130218
62.1%
Space Separator 39563
 
18.9%
Decimal Number 33488
 
16.0%
Dash Punctuation 5035
 
2.4%
Uppercase Letter 964
 
0.5%
Open Punctuation 224
 
0.1%
Close Punctuation 224
 
0.1%
Other Punctuation 83
 
< 0.1%
Lowercase Letter 53
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16612
 
12.8%
8391
 
6.4%
8353
 
6.4%
8302
 
6.4%
8212
 
6.3%
8029
 
6.2%
8017
 
6.2%
8017
 
6.2%
4615
 
3.5%
4080
 
3.1%
Other values (300) 47590
36.5%
Uppercase Letter
ValueCountFrequency (%)
G 418
43.4%
S 395
41.0%
B 52
 
5.4%
L 30
 
3.1%
A 23
 
2.4%
D 15
 
1.6%
K 12
 
1.2%
C 8
 
0.8%
E 3
 
0.3%
M 2
 
0.2%
Other values (6) 6
 
0.6%
Decimal Number
ValueCountFrequency (%)
4 6353
19.0%
1 6104
18.2%
5 4512
13.5%
2 4346
13.0%
3 2567
7.7%
6 2454
 
7.3%
8 2242
 
6.7%
7 1807
 
5.4%
9 1619
 
4.8%
0 1484
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
g 18
34.0%
s 17
32.1%
i 4
 
7.5%
n 4
 
7.5%
r 2
 
3.8%
t 2
 
3.8%
a 2
 
3.8%
o 2
 
3.8%
b 1
 
1.9%
l 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 74
89.2%
. 6
 
7.2%
@ 2
 
2.4%
& 1
 
1.2%
Space Separator
ValueCountFrequency (%)
39563
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5035
100.0%
Open Punctuation
ValueCountFrequency (%)
( 224
100.0%
Close Punctuation
ValueCountFrequency (%)
) 224
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130218
62.1%
Common 78619
37.5%
Latin 1017
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16612
 
12.8%
8391
 
6.4%
8353
 
6.4%
8302
 
6.4%
8212
 
6.3%
8029
 
6.2%
8017
 
6.2%
8017
 
6.2%
4615
 
3.5%
4080
 
3.1%
Other values (300) 47590
36.5%
Latin
ValueCountFrequency (%)
G 418
41.1%
S 395
38.8%
B 52
 
5.1%
L 30
 
2.9%
A 23
 
2.3%
g 18
 
1.8%
s 17
 
1.7%
D 15
 
1.5%
K 12
 
1.2%
C 8
 
0.8%
Other values (16) 29
 
2.9%
Common
ValueCountFrequency (%)
39563
50.3%
4 6353
 
8.1%
1 6104
 
7.8%
- 5035
 
6.4%
5 4512
 
5.7%
2 4346
 
5.5%
3 2567
 
3.3%
6 2454
 
3.1%
8 2242
 
2.9%
7 1807
 
2.3%
Other values (9) 3636
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130215
62.1%
ASCII 79636
37.9%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39563
49.7%
4 6353
 
8.0%
1 6104
 
7.7%
- 5035
 
6.3%
5 4512
 
5.7%
2 4346
 
5.5%
3 2567
 
3.2%
6 2454
 
3.1%
8 2242
 
2.8%
7 1807
 
2.3%
Other values (35) 4653
 
5.8%
Hangul
ValueCountFrequency (%)
16612
 
12.8%
8391
 
6.4%
8353
 
6.4%
8302
 
6.4%
8212
 
6.3%
8029
 
6.2%
8017
 
6.2%
8017
 
6.2%
4615
 
3.5%
4080
 
3.1%
Other values (297) 47587
36.5%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

도로명주소
Text

MISSING 

Distinct2194
Distinct (%)37.0%
Missing2083
Missing (%)26.0%
Memory size62.8 KiB
2024-05-11T15:54:55.677202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length55
Mean length36.552636
Min length21

Characters and Unicode

Total characters217013
Distinct characters338
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1814 ?
Unique (%)30.6%

Sample

1st row서울특별시 강동구 구천면로34길 27, 1층 (천호동)
2nd row서울특별시 강동구 올림픽로80길 39, 101호 (천호동)
3rd row서울특별시 강동구 구천면로31길 14 (천호동)
4th row서울특별시 강동구 구천면로 356-1 (천호동)
5th row서울특별시 강동구 양재대로138길 21, 중앙상가 104호 (명일동)
ValueCountFrequency (%)
서울특별시 5937
 
14.6%
강동구 5937
 
14.6%
천호동 2686
 
6.6%
천호대로 1821
 
4.5%
1005 1289
 
3.2%
현대백화점 1184
 
2.9%
지하1층 1054
 
2.6%
명일동 1044
 
2.6%
고덕로 956
 
2.4%
1층 921
 
2.3%
Other values (1646) 17774
43.8%
2024-05-11T15:54:56.609586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34673
 
16.0%
12886
 
5.9%
1 8664
 
4.0%
, 6915
 
3.2%
6409
 
3.0%
6371
 
2.9%
6322
 
2.9%
6189
 
2.9%
6169
 
2.8%
6131
 
2.8%
Other values (328) 116284
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133987
61.7%
Space Separator 34673
 
16.0%
Decimal Number 28266
 
13.0%
Other Punctuation 6925
 
3.2%
Close Punctuation 6058
 
2.8%
Open Punctuation 6058
 
2.8%
Uppercase Letter 834
 
0.4%
Dash Punctuation 125
 
0.1%
Lowercase Letter 84
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12886
 
9.6%
6409
 
4.8%
6371
 
4.8%
6322
 
4.7%
6189
 
4.6%
6169
 
4.6%
6131
 
4.6%
6069
 
4.5%
5937
 
4.4%
5937
 
4.4%
Other values (282) 65567
48.9%
Uppercase Letter
ValueCountFrequency (%)
S 319
38.2%
G 316
37.9%
B 120
 
14.4%
A 19
 
2.3%
D 14
 
1.7%
K 12
 
1.4%
F 9
 
1.1%
C 6
 
0.7%
L 4
 
0.5%
E 3
 
0.4%
Other values (7) 12
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 8664
30.7%
0 5179
18.3%
5 3630
12.8%
2 3150
 
11.1%
7 2090
 
7.4%
3 1803
 
6.4%
6 1353
 
4.8%
8 995
 
3.5%
9 744
 
2.6%
4 658
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
s 29
34.5%
g 28
33.3%
b 11
 
13.1%
i 4
 
4.8%
n 4
 
4.8%
o 2
 
2.4%
a 2
 
2.4%
r 2
 
2.4%
t 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 6915
99.9%
. 6
 
0.1%
? 2
 
< 0.1%
@ 1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
34673
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6058
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6058
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133987
61.7%
Common 82108
37.8%
Latin 918
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12886
 
9.6%
6409
 
4.8%
6371
 
4.8%
6322
 
4.7%
6189
 
4.6%
6169
 
4.6%
6131
 
4.6%
6069
 
4.5%
5937
 
4.4%
5937
 
4.4%
Other values (282) 65567
48.9%
Latin
ValueCountFrequency (%)
S 319
34.7%
G 316
34.4%
B 120
 
13.1%
s 29
 
3.2%
g 28
 
3.1%
A 19
 
2.1%
D 14
 
1.5%
K 12
 
1.3%
b 11
 
1.2%
F 9
 
1.0%
Other values (16) 41
 
4.5%
Common
ValueCountFrequency (%)
34673
42.2%
1 8664
 
10.6%
, 6915
 
8.4%
) 6058
 
7.4%
( 6058
 
7.4%
0 5179
 
6.3%
5 3630
 
4.4%
2 3150
 
3.8%
7 2090
 
2.5%
3 1803
 
2.2%
Other values (10) 3888
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133985
61.7%
ASCII 83026
38.3%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34673
41.8%
1 8664
 
10.4%
, 6915
 
8.3%
) 6058
 
7.3%
( 6058
 
7.3%
0 5179
 
6.2%
5 3630
 
4.4%
2 3150
 
3.8%
7 2090
 
2.5%
3 1803
 
2.2%
Other values (36) 4806
 
5.8%
Hangul
ValueCountFrequency (%)
12886
 
9.6%
6409
 
4.8%
6371
 
4.8%
6322
 
4.7%
6189
 
4.6%
6169
 
4.6%
6131
 
4.6%
6069
 
4.5%
5937
 
4.4%
5937
 
4.4%
Other values (280) 65565
48.9%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct176
Distinct (%)3.0%
Missing2096
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean5306.3045
Minimum5210
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.6 KiB
2024-05-11T15:54:56.887094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5210
5-th percentile5229
Q15269
median5327
Q35328
95-th percentile5398
Maximum5415
Range205
Interquartile range (IQR)59

Descriptive statistics

Standard deviation49.474313
Coefficient of variation (CV)0.0093236853
Kurtosis-0.58518793
Mean5306.3045
Median Absolute Deviation (MAD)36
Skewness0.10314791
Sum31434548
Variance2447.7077
MonotonicityNot monotonic
2024-05-11T15:54:57.235740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328 1800
22.4%
5269 695
 
8.7%
5229 439
 
5.5%
5314 345
 
4.3%
5327 252
 
3.1%
5398 234
 
2.9%
5266 191
 
2.4%
5224 136
 
1.7%
5236 107
 
1.3%
5275 103
 
1.3%
Other values (166) 1622
20.2%
(Missing) 2096
26.1%
ValueCountFrequency (%)
5210 1
 
< 0.1%
5211 15
 
0.2%
5213 3
 
< 0.1%
5216 1
 
< 0.1%
5219 3
 
< 0.1%
5220 1
 
< 0.1%
5221 3
 
< 0.1%
5222 29
 
0.4%
5223 2
 
< 0.1%
5224 136
1.7%
ValueCountFrequency (%)
5415 48
0.6%
5414 1
 
< 0.1%
5412 8
 
0.1%
5411 15
 
0.2%
5409 6
 
0.1%
5408 10
 
0.1%
5407 4
 
< 0.1%
5406 7
 
0.1%
5405 17
 
0.2%
5404 81
1.0%
Distinct3771
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
2024-05-11T15:54:57.847956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length9.5411471
Min length1

Characters and Unicode

Total characters76520
Distinct characters801
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2959 ?
Unique (%)36.9%

Sample

1st row고소한기름
2nd row엄마기름집
3rd row동창기름
4th row희망
5th row천호기름
ValueCountFrequency (%)
한시적영업 4023
30.8%
주식회사 294
 
2.2%
월드푸드 159
 
1.2%
주)인네이처 110
 
0.8%
주)만구 99
 
0.8%
주)햇살드림 85
 
0.6%
주)동일 80
 
0.6%
남도장터(주 71
 
0.5%
주)참살이유통 70
 
0.5%
주)세연미트 61
 
0.5%
Other values (3823) 8025
61.4%
2024-05-11T15:54:58.539216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5067
 
6.6%
4478
 
5.9%
4454
 
5.8%
4305
 
5.6%
4272
 
5.6%
4153
 
5.4%
3055
 
4.0%
) 2694
 
3.5%
( 2615
 
3.4%
1474
 
1.9%
Other values (791) 39953
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65006
85.0%
Space Separator 5067
 
6.6%
Close Punctuation 2695
 
3.5%
Open Punctuation 2616
 
3.4%
Uppercase Letter 468
 
0.6%
Lowercase Letter 412
 
0.5%
Other Punctuation 143
 
0.2%
Decimal Number 81
 
0.1%
Dash Punctuation 31
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4478
 
6.9%
4454
 
6.9%
4305
 
6.6%
4272
 
6.6%
4153
 
6.4%
3055
 
4.7%
1474
 
2.3%
1061
 
1.6%
1000
 
1.5%
984
 
1.5%
Other values (717) 35770
55.0%
Uppercase Letter
ValueCountFrequency (%)
H 45
 
9.6%
D 43
 
9.2%
S 40
 
8.5%
F 37
 
7.9%
E 30
 
6.4%
O 27
 
5.8%
M 26
 
5.6%
B 25
 
5.3%
J 22
 
4.7%
C 21
 
4.5%
Other values (15) 152
32.5%
Lowercase Letter
ValueCountFrequency (%)
e 64
15.5%
a 42
 
10.2%
o 31
 
7.5%
l 28
 
6.8%
h 24
 
5.8%
i 24
 
5.8%
m 23
 
5.6%
n 22
 
5.3%
u 22
 
5.3%
r 19
 
4.6%
Other values (14) 113
27.4%
Decimal Number
ValueCountFrequency (%)
1 22
27.2%
0 17
21.0%
2 16
19.8%
9 7
 
8.6%
4 6
 
7.4%
3 5
 
6.2%
8 3
 
3.7%
5 2
 
2.5%
6 2
 
2.5%
7 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
& 87
60.8%
, 21
 
14.7%
. 16
 
11.2%
' 7
 
4.9%
? 5
 
3.5%
/ 3
 
2.1%
: 2
 
1.4%
! 2
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 2694
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2615
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5067
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64973
84.9%
Common 10634
 
13.9%
Latin 880
 
1.2%
Han 33
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4478
 
6.9%
4454
 
6.9%
4305
 
6.6%
4272
 
6.6%
4153
 
6.4%
3055
 
4.7%
1474
 
2.3%
1061
 
1.6%
1000
 
1.5%
984
 
1.5%
Other values (705) 35737
55.0%
Latin
ValueCountFrequency (%)
e 64
 
7.3%
H 45
 
5.1%
D 43
 
4.9%
a 42
 
4.8%
S 40
 
4.5%
F 37
 
4.2%
o 31
 
3.5%
E 30
 
3.4%
l 28
 
3.2%
O 27
 
3.1%
Other values (39) 493
56.0%
Common
ValueCountFrequency (%)
5067
47.6%
) 2694
25.3%
( 2615
24.6%
& 87
 
0.8%
- 31
 
0.3%
1 22
 
0.2%
, 21
 
0.2%
0 17
 
0.2%
2 16
 
0.2%
. 16
 
0.2%
Other values (15) 48
 
0.5%
Han
ValueCountFrequency (%)
21
63.6%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (2) 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64973
84.9%
ASCII 11514
 
15.0%
CJK Compat Ideographs 21
 
< 0.1%
CJK 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5067
44.0%
) 2694
23.4%
( 2615
22.7%
& 87
 
0.8%
e 64
 
0.6%
H 45
 
0.4%
D 43
 
0.4%
a 42
 
0.4%
S 40
 
0.3%
F 37
 
0.3%
Other values (64) 780
 
6.8%
Hangul
ValueCountFrequency (%)
4478
 
6.9%
4454
 
6.9%
4305
 
6.6%
4272
 
6.6%
4153
 
6.4%
3055
 
4.7%
1474
 
2.3%
1061
 
1.6%
1000
 
1.5%
984
 
1.5%
Other values (705) 35737
55.0%
CJK Compat Ideographs
ValueCountFrequency (%)
21
100.0%
CJK
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Distinct5029
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
Minimum1999-01-25 00:00:00
Maximum2024-05-09 11:13:48
2024-05-11T15:54:58.824033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:59.051905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
I
4110 
U
3910 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4110
51.2%
U 3910
48.8%

Length

2024-05-11T15:54:59.263689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:59.512893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4110
51.2%
u 3910
48.8%
Distinct1504
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:54:59.792523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:55:00.084059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
즉석판매제조가공업
8009 
기타
 
11

Length

Max length9
Median length9
Mean length8.990399
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 8009
99.9%
기타 11
 
0.1%

Length

2024-05-11T15:55:00.277411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:00.430414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 8009
99.9%
기타 11
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1371
Distinct (%)17.6%
Missing224
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean212060.84
Minimum210566.88
Maximum215984.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.6 KiB
2024-05-11T15:55:00.591587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile210929.92
Q1211005.82
median211861.99
Q3212871.58
95-th percentile213700.88
Maximum215984.38
Range5417.4995
Interquartile range (IQR)1865.7564

Descriptive statistics

Standard deviation1155.497
Coefficient of variation (CV)0.0054488935
Kurtosis-0.36554219
Mean212060.84
Median Absolute Deviation (MAD)900.30461
Skewness0.68377238
Sum1.6532263 × 109
Variance1335173.2
MonotonicityNot monotonic
2024-05-11T15:55:00.804744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210929.919693661 931
 
11.6%
213700.877714971 787
 
9.8%
211025.924972294 596
 
7.4%
210931.643485 564
 
7.0%
212926.089912845 415
 
5.2%
212501.369116329 403
 
5.0%
212676.162193508 354
 
4.4%
211055.486155787 291
 
3.6%
210566.875626134 268
 
3.3%
211979.520569314 156
 
1.9%
Other values (1361) 3031
37.8%
(Missing) 224
 
2.8%
ValueCountFrequency (%)
210566.875626134 268
3.3%
210613.801723814 1
 
< 0.1%
210621.633987432 1
 
< 0.1%
210630.209443525 1
 
< 0.1%
210644.063727145 1
 
< 0.1%
210646.543910513 1
 
< 0.1%
210656.192068858 1
 
< 0.1%
210667.826792159 1
 
< 0.1%
210669.90005838 1
 
< 0.1%
210671.486635695 1
 
< 0.1%
ValueCountFrequency (%)
215984.375136997 1
< 0.1%
215875.024969 1
< 0.1%
215682.604205044 1
< 0.1%
215672.146934322 1
< 0.1%
215661.222623 2
< 0.1%
215536.069244566 1
< 0.1%
215523.83400078 1
< 0.1%
215496.149626989 1
< 0.1%
215458.525218653 1
< 0.1%
215422.746119624 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1371
Distinct (%)17.6%
Missing224
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean449095.91
Minimum446598.59
Maximum452305.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.6 KiB
2024-05-11T15:55:01.028252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446598.59
5-th percentile447333.45
Q1448495.19
median448786.7
Q3450026.85
95-th percentile450751.52
Maximum452305.72
Range5707.1319
Interquartile range (IQR)1531.6632

Descriptive statistics

Standard deviation1063.1028
Coefficient of variation (CV)0.0023672065
Kurtosis-0.56907156
Mean449095.91
Median Absolute Deviation (MAD)820.47383
Skewness0.065616995
Sum3.5011517 × 109
Variance1130187.5
MonotonicityNot monotonic
2024-05-11T15:55:01.223056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448537.406728283 931
 
11.6%
450278.100930843 787
 
9.8%
448495.189151526 596
 
7.4%
448522.079827 564
 
7.0%
450751.524331915 415
 
5.2%
449282.31038379 403
 
5.0%
449910.881572138 354
 
4.4%
448786.697371515 291
 
3.6%
447402.629676369 268
 
3.3%
446932.653730601 156
 
1.9%
Other values (1361) 3031
37.8%
(Missing) 224
 
2.8%
ValueCountFrequency (%)
446598.591776331 3
< 0.1%
446680.303498539 2
 
< 0.1%
446742.800284862 1
 
< 0.1%
446748.493341691 1
 
< 0.1%
446761.604007505 3
< 0.1%
446766.631391106 1
 
< 0.1%
446846.089755545 6
0.1%
446857.032145865 1
 
< 0.1%
446862.234226426 1
 
< 0.1%
446889.128359606 1
 
< 0.1%
ValueCountFrequency (%)
452305.723682264 1
 
< 0.1%
452233.685440247 1
 
< 0.1%
452213.416817557 1
 
< 0.1%
452189.755118282 44
0.5%
452152.024544351 1
 
< 0.1%
452107.257532 1
 
< 0.1%
452052.025388385 1
 
< 0.1%
451848.368097629 1
 
< 0.1%
451774.813888 4
 
< 0.1%
451767.354930552 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
즉석판매제조가공업
6436 
<NA>
1573 
기타
 
11

Length

Max length9
Median length9
Mean length8.0097257
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 6436
80.2%
<NA> 1573
 
19.6%
기타 11
 
0.1%

Length

2024-05-11T15:55:01.404879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:01.543535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 6436
80.2%
na 1573
 
19.6%
기타 11
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
7087 
0
715 
1
 
209
2
 
5
3
 
3

Length

Max length4
Median length4
Mean length3.6511222
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7087
88.4%
0 715
 
8.9%
1 209
 
2.6%
2 5
 
0.1%
3 3
 
< 0.1%
11 1
 
< 0.1%

Length

2024-05-11T15:55:01.710222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:01.901867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7087
88.4%
0 715
 
8.9%
1 209
 
2.6%
2 5
 
0.1%
3 3
 
< 0.1%
11 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
7112 
0
725 
1
 
175
2
 
7
4
 
1

Length

Max length4
Median length4
Mean length3.6603491
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7112
88.7%
0 725
 
9.0%
1 175
 
2.2%
2 7
 
0.1%
4 1
 
< 0.1%

Length

2024-05-11T15:55:02.150546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:02.394047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7112
88.7%
0 725
 
9.0%
1 175
 
2.2%
2 7
 
0.1%
4 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
7263 
주택가주변
 
438
기타
 
151
아파트지역
 
102
유흥업소밀집지역
 
66

Length

Max length8
Median length4
Mean length4.0625935
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> 7263
90.6%
주택가주변 438
 
5.5%
기타 151
 
1.9%
아파트지역 102
 
1.3%
유흥업소밀집지역 66
 
0.8%

Length

2024-05-11T15:55:02.598243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:02.798482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7263
90.6%
주택가주변 438
 
5.5%
기타 151
 
1.9%
아파트지역 102
 
1.3%
유흥업소밀집지역 66
 
0.8%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
7263 
자율
 
545
기타
 
206
 
3
우수
 
3

Length

Max length4
Median length4
Mean length3.8108479
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> 7263
90.6%
자율 545
 
6.8%
기타 206
 
2.6%
3
 
< 0.1%
우수 3
 
< 0.1%

Length

2024-05-11T15:55:03.010621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:03.391788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7263
90.6%
자율 545
 
6.8%
기타 206
 
2.6%
3
 
< 0.1%
우수 3
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6859 
상수도전용
1158 
상수도(음용)지하수(주방용)겸용
 
2
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.1477556
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6859
85.5%
상수도전용 1158
 
14.4%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T15:55:04.019008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:04.248319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6859
85.5%
상수도전용 1158
 
14.4%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
7515 
0
 
505

Length

Max length4
Median length4
Mean length3.8110973
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> 7515
93.7%
0 505
 
6.3%

Length

2024-05-11T15:55:04.543616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:04.771386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7515
93.7%
0 505
 
6.3%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6510 
0
1509 
1
 
1

Length

Max length4
Median length4
Mean length3.4351621
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6510
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%

Length

2024-05-11T15:55:04.996866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:05.211244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6510
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6511 
0
1509 

Length

Max length4
Median length4
Mean length3.4355362
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6511
81.2%
0 1509
 
18.8%

Length

2024-05-11T15:55:05.421808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:05.611573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6511
81.2%
0 1509
 
18.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6509 
0
1509 
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.434788
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6509
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-05-11T15:55:05.816807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:06.029923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6509
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%
2 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6509 
0
1509 
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.434788
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6509
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-05-11T15:55:06.259210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:06.483844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6509
81.2%
0 1509
 
18.8%
1 1
 
< 0.1%
2 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
5542 
임대
1444 
자가
1034 

Length

Max length4
Median length4
Mean length3.3820449
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> 5542
69.1%
임대 1444
 
18.0%
자가 1034
 
12.9%

Length

2024-05-11T15:55:06.695955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:06.935301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5542
69.1%
임대 1444
 
18.0%
자가 1034
 
12.9%

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6970 
0
1050 

Length

Max length4
Median length4
Mean length3.6072319
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> 6970
86.9%
0 1050
 
13.1%

Length

2024-05-11T15:55:07.203259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:07.362870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6970
86.9%
0 1050
 
13.1%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size62.8 KiB
<NA>
6970 
0
1050 

Length

Max length4
Median length4
Mean length3.6072319
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> 6970
86.9%
0 1050
 
13.1%

Length

2024-05-11T15:55:07.537562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:55:07.750471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6970
86.9%
0 1050
 
13.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1573
Missing (%)19.6%
Memory size15.8 KiB
False
6447 
(Missing)
1573 
ValueCountFrequency (%)
False 6447
80.4%
(Missing) 1573
 
19.6%
2024-05-11T15:55:07.897259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct84
Distinct (%)1.3%
Missing1573
Missing (%)19.6%
Infinite0
Infinite (%)0.0%
Mean0.65105165
Minimum0
Maximum115
Zeros6183
Zeros (%)77.1%
Negative0
Negative (%)0.0%
Memory size70.6 KiB
2024-05-11T15:55:08.085346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum115
Range115
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.6378719
Coefficient of variation (CV)7.123662
Kurtosis162.89806
Mean0.65105165
Median Absolute Deviation (MAD)0
Skewness11.0596
Sum4197.33
Variance21.509856
MonotonicityNot monotonic
2024-05-11T15:55:08.341294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6183
77.1%
3.3 45
 
0.6%
6.6 25
 
0.3%
33.0 18
 
0.2%
10.0 14
 
0.2%
3.0 13
 
0.2%
6.0 9
 
0.1%
9.9 8
 
0.1%
16.5 7
 
0.1%
19.8 6
 
0.1%
Other values (74) 119
 
1.5%
(Missing) 1573
 
19.6%
ValueCountFrequency (%)
0.0 6183
77.1%
1.0 1
 
< 0.1%
1.2 1
 
< 0.1%
1.5 3
 
< 0.1%
1.8 1
 
< 0.1%
2.0 5
 
0.1%
2.25 1
 
< 0.1%
2.5 1
 
< 0.1%
2.73 1
 
< 0.1%
3.0 13
 
0.2%
ValueCountFrequency (%)
115.0 1
< 0.1%
90.0 1
< 0.1%
82.5 2
< 0.1%
74.84 1
< 0.1%
66.0 1
< 0.1%
59.4 2
< 0.1%
52.5 1
< 0.1%
50.0 1
< 0.1%
49.6 1
< 0.1%
49.5 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8020
Missing (%)100.0%
Memory size70.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-107-1976-0000119760501<NA>3폐업2폐업20061127<NA><NA><NA><NA>27.06134873서울특별시 강동구 천호동 422-2 천호신시장 82호<NA><NA>고소한기름2004-06-07 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업211252.735516448823.398751즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
132400003240000-107-1976-0000219760501<NA>1영업/정상1영업<NA><NA><NA><NA>483 838067.96134863서울특별시 강동구 천호동 395-7 1층서울특별시 강동구 구천면로34길 27, 1층 (천호동)5330엄마기름집2019-08-05 13:11:35U2019-08-07 02:40:00.0즉석판매제조가공업211660.643668448918.489579즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
232400003240000-107-1976-0000319760501<NA>1영업/정상1영업<NA><NA><NA><NA>483 650050.0134870서울특별시 강동구 천호동 362-34서울특별시 강동구 올림픽로80길 39, 101호 (천호동)5324동창기름2020-05-20 11:50:05U2020-05-22 02:40:00.0즉석판매제조가공업211195.374136448996.298655즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N50.0<NA><NA><NA>
332400003240000-107-1976-0000419760721<NA>3폐업2폐업20060322<NA><NA><NA><NA>24.85134864서울특별시 강동구 천호동 166-102<NA><NA>희망2006-04-10 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업211580.313697448479.374672즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
432400003240000-107-1977-0000119771115<NA>3폐업2폐업20021228<NA><NA><NA><NA>34.96134873서울특별시 강동구 천호동 422-131<NA><NA>천호기름2002-08-02 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
532400003240000-107-1977-0000219770713<NA>3폐업2폐업20191211<NA><NA><NA>02 474 550015.21134870서울특별시 강동구 천호동 399-7서울특별시 강동구 구천면로31길 14 (천호동)5326대구2019-12-11 11:09:37U2019-12-13 02:40:00.0즉석판매제조가공업211352.243626448812.194081즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
632400003240000-107-1977-0000319770905<NA>1영업/정상1영업<NA><NA><NA><NA>478 597417.56134866서울특별시 강동구 천호동 243-185서울특별시 강동구 구천면로 356-1 (천호동)5309신진2013-07-03 11:17:00I2018-08-31 23:59:59.0즉석판매제조가공업212147.705343449779.692272즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
732400003240000-107-1977-000041977-09-30<NA>1영업/정상1영업<NA><NA><NA><NA>033426457231.9134-830서울특별시 강동구 명일동 326-11 중앙상가서울특별시 강동구 양재대로138길 21, 중앙상가 104호 (명일동)5292동부기름2023-03-07 10:11:22U2022-12-02 23:00:00.0즉석판매제조가공업212738.875197449672.356959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
832400003240000-107-1978-0000119780905<NA>3폐업2폐업20021008<NA><NA><NA><NA>21.6134877서울특별시 강동구 암사동 538-1<NA><NA>제일2002-10-08 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-107-1979-0000119791109<NA>1영업/정상1영업<NA><NA><NA><NA>02477 431319.8134814서울특별시 강동구 길동 413-13서울특별시 강동구 진황도로 103 (길동)5353충북상회2021-07-15 13:38:14U2021-07-17 02:40:00.0즉석판매제조가공업212117.206943448171.400385즉석판매제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
801032400003240000-107-2024-002042024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>02 483 088918.0134-880서울특별시 강동구 길동 394-14서울특별시 강동구 양재대로112길 13, 1층 106호 (길동)5351신독도쭈꾸미2024-05-07 15:33:01I2023-12-05 00:09:00.0즉석판매제조가공업212355.213186448304.189002<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801132400003240000-107-2024-002052024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>031 984 5728<NA>134-861서울특별시 강동구 천호동 42 천호복합 상업시설서울특별시 강동구 양재대로 1571, 천호복합 상업시설 지하2층 (천호동)5314(주)동명에스티유 한시적영업2024-05-08 10:17:31I2023-12-04 23:00:00.0즉석판매제조가공업212501.369116449282.310384<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801232400003240000-107-2024-002062024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0134-779서울특별시 강동구 천호동 572 현대백화점서울특별시 강동구 천호대로 1005, 현대백화점 지하2층 (천호동)532831건어물 한시적영업2024-05-08 10:22:43I2023-12-04 23:00:00.0즉석판매제조가공업210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801332400003240000-107-2024-002072024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>134-779서울특별시 강동구 천호동 572 현대백화점서울특별시 강동구 천호대로 1005, 현대백화점 지하2층 (천호동)5328(주)팜덕 한시적영업2024-05-08 10:47:07I2023-12-04 23:00:00.0즉석판매제조가공업210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801432400003240000-107-2024-002082024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>062 381 0378<NA>134-825서울특별시 강동구 명일동 46-4 신세계이마트명일점서울특별시 강동구 고덕로 276, 신세계이마트명일점 지하1층 (명일동)5269남도장터(주) 한시적영업2024-05-08 11:29:12I2023-12-04 23:00:00.0즉석판매제조가공업213700.877715450278.100931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801532400003240000-107-2024-002092024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>062 381 03780.0134-874서울특별시 강동구 천호동 454-1 이마트서울특별시 강동구 천호대로 1017, 이마트 지하1층 (천호동)5328남도장터(주) 한시적영업2024-05-08 11:56:40I2023-12-04 23:00:00.0즉석판매제조가공업211025.924972448495.189152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801632400003240000-107-2024-002102024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>031 80760751<NA>134-080서울특별시 강동구 고덕동 693 고덕그라시움(제1상가)서울특별시 강동구 고덕로 353, 고덕그라시움(제1상가) GS더프레시 고덕그라시움점동 (고덕동)5224너울푸드 한시적영업2024-05-08 14:58:46I2023-12-04 23:00:00.0즉석판매제조가공업214299.644267450637.95476<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801732400003240000-107-2024-002112024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>041 935 0421<NA>134-825서울특별시 강동구 명일동 46-4 신세계이마트명일점서울특별시 강동구 고덕로 276, 신세계이마트명일점 지하1층 (명일동)5269(주)신성마린 한시적영업2024-05-08 15:59:14I2023-12-04 23:00:00.0즉석판매제조가공업213700.877715450278.100931<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801832400003240000-107-2024-002122024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>134-861서울특별시 강동구 천호동 42 천호복합 상업시설서울특별시 강동구 양재대로 1571, 천호복합 상업시설 지하2층 (천호동)5314주식회사팜덕 한시적영업2024-05-08 17:25:43I2023-12-04 23:00:00.0즉석판매제조가공업212501.369116449282.310384<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
801932400003240000-107-2024-002132024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA>031 297798840.0134-848서울특별시 강동구 성내동 451 농협서울지역본부서울특별시 강동구 올림픽로 528, 농협서울지역본부 1층 (성내동)5398(주)푸드뱅크코리아 한시적영업2024-05-08 18:03:58I2023-12-04 23:00:00.0즉석판매제조가공업210566.875626447402.629676<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>