Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells123139
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 MiB
Average record size in memory411.0 B

Variable types

Numeric10
Categorical17
Text6
DateTime4
Unsupported9
Boolean1

Dataset

Description23년05월_6270000_대구광역시_07_22_19_P_즉석판매제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098194&dataSetDetailId=DDI_0000098223&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (99.6%)Imbalance
위생업태명 is highly imbalanced (99.6%)Imbalance
급수시설구분명 is highly imbalanced (64.9%)Imbalance
본사직원수 is highly imbalanced (59.9%)Imbalance
공장사무직직원수 is highly imbalanced (57.2%)Imbalance
보증액 is highly imbalanced (70.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1703 (17.0%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
소재지전화 has 5705 (57.0%) missing valuesMissing
소재지면적 has 4297 (43.0%) missing valuesMissing
소재지우편번호 has 148 (1.5%) missing valuesMissing
도로명전체주소 has 2422 (24.2%) missing valuesMissing
도로명우편번호 has 2473 (24.7%) missing valuesMissing
좌표정보(X) has 214 (2.1%) missing valuesMissing
좌표정보(Y) has 214 (2.1%) missing valuesMissing
영업장주변구분명 has 10000 (100.0%) missing valuesMissing
등급구분명 has 10000 (100.0%) missing valuesMissing
공장판매직직원수 has 4029 (40.3%) missing valuesMissing
공장생산직직원수 has 4029 (40.3%) missing valuesMissing
월세액 has 7885 (78.8%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
공장판매직직원수 is highly skewed (γ1 = 24.91884894)Skewed
월세액 is highly skewed (γ1 = 22.81152066)Skewed
번호 has unique valuesUnique
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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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 426 (4.3%) zerosZeros
공장판매직직원수 has 5624 (56.2%) zerosZeros
공장생산직직원수 has 5503 (55.0%) zerosZeros
월세액 has 2108 (21.1%) zerosZeros
시설총규모 has 9607 (96.1%) zerosZeros

Reproduction

Analysis started2024-04-17 21:09:29.498754
Analysis finished2024-04-17 21:09:31.418334
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14024.042
Minimum3
Maximum28072
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:31.477573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1460.85
Q17001.75
median13927.5
Q320955.25
95-th percentile26730.1
Maximum28072
Range28069
Interquartile range (IQR)13953.5

Descriptive statistics

Standard deviation8085.83
Coefficient of variation (CV)0.57656916
Kurtosis-1.1983491
Mean14024.042
Median Absolute Deviation (MAD)6964
Skewness0.013849834
Sum1.4024042 × 108
Variance65380648
MonotonicityNot monotonic
2024-04-18T06:09:31.585626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17855 1
 
< 0.1%
24665 1
 
< 0.1%
8847 1
 
< 0.1%
22960 1
 
< 0.1%
12856 1
 
< 0.1%
6278 1
 
< 0.1%
7541 1
 
< 0.1%
7368 1
 
< 0.1%
17946 1
 
< 0.1%
17306 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
18 1
< 0.1%
24 1
< 0.1%
26 1
< 0.1%
ValueCountFrequency (%)
28072 1
< 0.1%
28069 1
< 0.1%
28068 1
< 0.1%
28063 1
< 0.1%
28057 1
< 0.1%
28055 1
< 0.1%
28053 1
< 0.1%
28048 1
< 0.1%
28046 1
< 0.1%
28045 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
10000 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

Length

2024-04-18T06:09:31.690188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:31.760985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_22_19_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_19_P
2nd row07_22_19_P
3rd row07_22_19_P
4th row07_22_19_P
5th row07_22_19_P

Common Values

ValueCountFrequency (%)
07_22_19_P 10000
100.0%

Length

2024-04-18T06:09:31.834069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:31.905368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_19_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3446455
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:31.972081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation22561.336
Coefficient of variation (CV)0.0065462441
Kurtosis-1.2862231
Mean3446455
Median Absolute Deviation (MAD)20000
Skewness-0.3150996
Sum3.446455 × 1010
Variance5.0901388 × 108
MonotonicityNot monotonic
2024-04-18T06:09:32.058342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2177
21.8%
3450000 1785
17.8%
3420000 1609
16.1%
3460000 1581
15.8%
3410000 1210
12.1%
3480000 593
 
5.9%
3430000 547
 
5.5%
3440000 498
 
5.0%
ValueCountFrequency (%)
3410000 1210
12.1%
3420000 1609
16.1%
3430000 547
 
5.5%
3440000 498
 
5.0%
3450000 1785
17.8%
3460000 1581
15.8%
3470000 2177
21.8%
3480000 593
 
5.9%
ValueCountFrequency (%)
3480000 593
 
5.9%
3470000 2177
21.8%
3460000 1581
15.8%
3450000 1785
17.8%
3440000 498
 
5.0%
3430000 547
 
5.5%
3420000 1609
16.1%
3410000 1210
12.1%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T06:09:32.227327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3460000-107-2015-00023
2nd row3430000-107-2014-00009
3rd row3470000-107-2003-00085
4th row3460000-107-2009-00091
5th row3470000-107-1996-00038
ValueCountFrequency (%)
3460000-107-2015-00023 1
 
< 0.1%
3420000-107-2005-00013 1
 
< 0.1%
3420000-107-2018-00217 1
 
< 0.1%
3460000-107-2023-00065 1
 
< 0.1%
3430000-107-2013-00019 1
 
< 0.1%
3470000-107-2009-00276 1
 
< 0.1%
3450000-107-2004-00156 1
 
< 0.1%
3420000-107-2021-00385 1
 
< 0.1%
3420000-107-2021-00166 1
 
< 0.1%
3470000-107-1999-00028 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-18T06:09:32.502771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91578
41.6%
- 30000
 
13.6%
1 22118
 
10.1%
2 18216
 
8.3%
7 15021
 
6.8%
3 14091
 
6.4%
4 13139
 
6.0%
6 4250
 
1.9%
5 4078
 
1.9%
9 4011
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91578
48.2%
1 22118
 
11.6%
2 18216
 
9.6%
7 15021
 
7.9%
3 14091
 
7.4%
4 13139
 
6.9%
6 4250
 
2.2%
5 4078
 
2.1%
9 4011
 
2.1%
8 3498
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 91578
41.6%
- 30000
 
13.6%
1 22118
 
10.1%
2 18216
 
8.3%
7 15021
 
6.8%
3 14091
 
6.4%
4 13139
 
6.0%
6 4250
 
1.9%
5 4078
 
1.9%
9 4011
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 91578
41.6%
- 30000
 
13.6%
1 22118
 
10.1%
2 18216
 
8.3%
7 15021
 
6.8%
3 14091
 
6.4%
4 13139
 
6.0%
6 4250
 
1.9%
5 4078
 
1.9%
9 4011
 
1.8%
Distinct4518
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1972-04-22 00:00:00
Maximum2023-05-31 00:00:00
2024-04-18T06:09:32.628273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:09:32.753082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8297 
1
1703 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 8297
83.0%
1 1703
 
17.0%

Length

2024-04-18T06:09:33.158725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:33.243773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8297
83.0%
1 1703
 
17.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8297 
영업/정상
1703 

Length

Max length5
Median length2
Mean length2.5109
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8297
83.0%
영업/정상 1703
 
17.0%

Length

2024-04-18T06:09:33.320648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:33.394355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8297
83.0%
영업/정상 1703
 
17.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8297 
1
1703 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8297
83.0%
1 1703
 
17.0%

Length

2024-04-18T06:09:33.468355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:33.539692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8297
83.0%
1 1703
 
17.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8297 
영업
1703 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8297
83.0%
영업 1703
 
17.0%

Length

2024-04-18T06:09:33.612046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:33.683258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8297
83.0%
영업 1703
 
17.0%

폐업일자
Date

MISSING 

Distinct3981
Distinct (%)48.0%
Missing1703
Missing (%)17.0%
Memory size156.2 KiB
Minimum2000-03-10 00:00:00
Maximum2023-05-31 00:00:00
2024-04-18T06:09:33.764654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:09:33.878416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지전화
Text

MISSING 

Distinct3436
Distinct (%)80.0%
Missing5705
Missing (%)57.0%
Memory size156.2 KiB
2024-04-18T06:09:34.159178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.849825
Min length6

Characters and Unicode

Total characters46600
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

Unique3137 ?
Unique (%)73.0%

Sample

1st row053 763 2988
2nd row053 6366891
3rd row02 847 9050
4th row053 6351768
5th row7840367
ValueCountFrequency (%)
053 2726
29.2%
031 229
 
2.5%
02 163
 
1.7%
055 106
 
1.1%
070 85
 
0.9%
051 69
 
0.7%
062 51
 
0.5%
1234 35
 
0.4%
325 33
 
0.4%
858 32
 
0.3%
Other values (3577) 5798
62.2%
2024-04-18T06:09:34.549477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 7122
15.3%
0 7019
15.1%
3 6238
13.4%
5198
11.2%
2 4087
8.8%
6 3310
7.1%
7 3076
6.6%
1 3034
6.5%
4 2638
 
5.7%
8 2548
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41402
88.8%
Space Separator 5198
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 7122
17.2%
0 7019
17.0%
3 6238
15.1%
2 4087
9.9%
6 3310
8.0%
7 3076
7.4%
1 3034
7.3%
4 2638
 
6.4%
8 2548
 
6.2%
9 2330
 
5.6%
Space Separator
ValueCountFrequency (%)
5198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 7122
15.3%
0 7019
15.1%
3 6238
13.4%
5198
11.2%
2 4087
8.8%
6 3310
7.1%
7 3076
6.6%
1 3034
6.5%
4 2638
 
5.7%
8 2548
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 7122
15.3%
0 7019
15.1%
3 6238
13.4%
5198
11.2%
2 4087
8.8%
6 3310
7.1%
7 3076
6.6%
1 3034
6.5%
4 2638
 
5.7%
8 2548
 
5.5%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct1975
Distinct (%)34.6%
Missing4297
Missing (%)43.0%
Infinite0
Infinite (%)0.0%
Mean22.468418
Minimum0
Maximum604.2
Zeros426
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:34.673781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median16.12
Q331.115
95-th percentile60.822
Maximum604.2
Range604.2
Interquartile range (IQR)25.115

Descriptive statistics

Standard deviation26.682605
Coefficient of variation (CV)1.1875604
Kurtosis68.65624
Mean22.468418
Median Absolute Deviation (MAD)11.83
Skewness5.5093022
Sum128137.39
Variance711.9614
MonotonicityNot monotonic
2024-04-18T06:09:34.787121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 426
 
4.3%
3.3 197
 
2.0%
6.0 164
 
1.6%
6.6 103
 
1.0%
10.0 92
 
0.9%
4.0 88
 
0.9%
3.0 77
 
0.8%
5.0 69
 
0.7%
2.0 66
 
0.7%
12.0 61
 
0.6%
Other values (1965) 4360
43.6%
(Missing) 4297
43.0%
ValueCountFrequency (%)
0.0 426
4.3%
0.2 1
 
< 0.1%
0.35 1
 
< 0.1%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
0.6 2
 
< 0.1%
0.7 1
 
< 0.1%
0.72 1
 
< 0.1%
0.75 2
 
< 0.1%
0.8 1
 
< 0.1%
ValueCountFrequency (%)
604.2 1
< 0.1%
396.0 1
< 0.1%
341.4 1
< 0.1%
337.0 1
< 0.1%
303.0 1
< 0.1%
301.2 1
< 0.1%
299.52 1
< 0.1%
292.0 1
< 0.1%
268.66 1
< 0.1%
246.13 1
< 0.1%

소재지우편번호
Text

MISSING 

Distinct592
Distinct (%)6.0%
Missing148
Missing (%)1.5%
Memory size156.2 KiB
2024-04-18T06:09:35.043562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters68964
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

Unique125 ?
Unique (%)1.3%

Sample

1st row706-838
2nd row703-060
3rd row704-818
4th row706-803
5th row704-828
ValueCountFrequency (%)
701-020 472
 
4.8%
704-923 338
 
3.4%
704-722 292
 
3.0%
700-082 291
 
3.0%
700-718 286
 
2.9%
706-803 285
 
2.9%
702-886 263
 
2.7%
704-800 256
 
2.6%
702-746 191
 
1.9%
701-868 189
 
1.9%
Other values (582) 6989
70.9%
2024-04-18T06:09:35.392864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15862
23.0%
7 11965
17.3%
- 9852
14.3%
8 7831
11.4%
2 5384
 
7.8%
1 4917
 
7.1%
4 3955
 
5.7%
6 3136
 
4.5%
3 2990
 
4.3%
5 1553
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59112
85.7%
Dash Punctuation 9852
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15862
26.8%
7 11965
20.2%
8 7831
13.2%
2 5384
 
9.1%
1 4917
 
8.3%
4 3955
 
6.7%
6 3136
 
5.3%
3 2990
 
5.1%
5 1553
 
2.6%
9 1519
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 9852
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15862
23.0%
7 11965
17.3%
- 9852
14.3%
8 7831
11.4%
2 5384
 
7.8%
1 4917
 
7.1%
4 3955
 
5.7%
6 3136
 
4.5%
3 2990
 
4.3%
5 1553
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15862
23.0%
7 11965
17.3%
- 9852
14.3%
8 7831
11.4%
2 5384
 
7.8%
1 4917
 
7.1%
4 3955
 
5.7%
6 3136
 
4.5%
3 2990
 
4.3%
5 1553
 
2.3%
Distinct5232
Distinct (%)52.4%
Missing20
Missing (%)0.2%
Memory size156.2 KiB
2024-04-18T06:09:35.652104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length49
Mean length25.41994
Min length16

Characters and Unicode

Total characters253691
Distinct characters413
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4626 ?
Unique (%)46.4%

Sample

1st row대구광역시 수성구 중동 417-46
2nd row대구광역시 서구 내당동 202-1 ,내당시영아파트 6동 점포5호
3rd row대구광역시 달서구 상인동 1529-3 (지상1층)
4th row대구광역시 수성구 만촌동 1356-5 이마트만촌점
5th row대구광역시 달서구 월성동 86 주공2단지상가 나동 104호
ValueCountFrequency (%)
대구광역시 9978
 
20.2%
달서구 2174
 
4.4%
북구 1771
 
3.6%
동구 1608
 
3.3%
수성구 1580
 
3.2%
중구 1210
 
2.4%
1층 665
 
1.3%
달성군 591
 
1.2%
상인동 575
 
1.2%
신천동 554
 
1.1%
Other values (5442) 28688
58.1%
2024-04-18T06:09:36.031806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49053
19.3%
20465
 
8.1%
12833
 
5.1%
12767
 
5.0%
1 12244
 
4.8%
10275
 
4.1%
10119
 
4.0%
9987
 
3.9%
0 7667
 
3.0%
2 6693
 
2.6%
Other values (403) 101588
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145773
57.5%
Decimal Number 50589
 
19.9%
Space Separator 49053
 
19.3%
Dash Punctuation 6395
 
2.5%
Open Punctuation 512
 
0.2%
Close Punctuation 507
 
0.2%
Uppercase Letter 381
 
0.2%
Lowercase Letter 238
 
0.1%
Other Punctuation 231
 
0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20465
 
14.0%
12833
 
8.8%
12767
 
8.8%
10275
 
7.0%
10119
 
6.9%
9987
 
6.9%
3806
 
2.6%
3216
 
2.2%
2840
 
1.9%
2279
 
1.6%
Other values (354) 57186
39.2%
Uppercase Letter
ValueCountFrequency (%)
B 90
23.6%
A 74
19.4%
S 72
18.9%
K 54
14.2%
H 34
 
8.9%
G 12
 
3.1%
M 8
 
2.1%
C 7
 
1.8%
P 6
 
1.6%
T 6
 
1.6%
Other values (9) 18
 
4.7%
Decimal Number
ValueCountFrequency (%)
1 12244
24.2%
0 7667
15.2%
2 6693
13.2%
5 5919
11.7%
3 4592
 
9.1%
6 3511
 
6.9%
4 3064
 
6.1%
9 2324
 
4.6%
7 2295
 
4.5%
8 2280
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 38
16.0%
o 34
14.3%
p 33
13.9%
m 33
13.9%
l 33
13.9%
u 33
13.9%
s 33
13.9%
k 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 191
82.7%
. 26
 
11.3%
/ 7
 
3.0%
@ 5
 
2.2%
: 1
 
0.4%
· 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 8
66.7%
+ 4
33.3%
Space Separator
ValueCountFrequency (%)
49053
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6395
100.0%
Open Punctuation
ValueCountFrequency (%)
( 512
100.0%
Close Punctuation
ValueCountFrequency (%)
) 507
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145769
57.5%
Common 107299
42.3%
Latin 619
 
0.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20465
 
14.0%
12833
 
8.8%
12767
 
8.8%
10275
 
7.0%
10119
 
6.9%
9987
 
6.9%
3806
 
2.6%
3216
 
2.2%
2840
 
1.9%
2279
 
1.6%
Other values (353) 57182
39.2%
Latin
ValueCountFrequency (%)
B 90
14.5%
A 74
12.0%
S 72
11.6%
K 54
8.7%
e 38
 
6.1%
o 34
 
5.5%
H 34
 
5.5%
p 33
 
5.3%
m 33
 
5.3%
l 33
 
5.3%
Other values (17) 124
20.0%
Common
ValueCountFrequency (%)
49053
45.7%
1 12244
 
11.4%
0 7667
 
7.1%
2 6693
 
6.2%
- 6395
 
6.0%
5 5919
 
5.5%
3 4592
 
4.3%
6 3511
 
3.3%
4 3064
 
2.9%
9 2324
 
2.2%
Other values (12) 5837
 
5.4%
Han
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145768
57.5%
ASCII 107917
42.5%
CJK 4
 
< 0.1%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49053
45.5%
1 12244
 
11.3%
0 7667
 
7.1%
2 6693
 
6.2%
- 6395
 
5.9%
5 5919
 
5.5%
3 4592
 
4.3%
6 3511
 
3.3%
4 3064
 
2.8%
9 2324
 
2.2%
Other values (38) 6455
 
6.0%
Hangul
ValueCountFrequency (%)
20465
 
14.0%
12833
 
8.8%
12767
 
8.8%
10275
 
7.0%
10119
 
6.9%
9987
 
6.9%
3806
 
2.6%
3216
 
2.2%
2840
 
1.9%
2279
 
1.6%
Other values (352) 57181
39.2%
CJK
ValueCountFrequency (%)
4
100.0%
None
ValueCountFrequency (%)
· 1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct4188
Distinct (%)55.3%
Missing2422
Missing (%)24.2%
Memory size156.2 KiB
2024-04-18T06:09:36.314456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length32.512536
Min length19

Characters and Unicode

Total characters246380
Distinct characters430
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

Unique3706 ?
Unique (%)48.9%

Sample

1st row대구광역시 수성구 청수로 27-3 (중동)
2nd row대구광역시 서구 서대구로8길 15, 6동 점포5호 (내당동)
3rd row대구광역시 달서구 상화북로 195-9 (상인동,(지상1층))
4th row대구광역시 달서구 월성로 77, 나동 104호 (월성동,주공2단지상가)
5th row대구광역시 수성구 용학로42길 13 (지산동,목련아파트 상가 8호)
ValueCountFrequency (%)
대구광역시 7576
 
15.5%
1층 2391
 
4.9%
달서구 1609
 
3.3%
동구 1391
 
2.8%
북구 1261
 
2.6%
지하1층 1216
 
2.5%
수성구 1196
 
2.4%
중구 931
 
1.9%
달구벌대로 717
 
1.5%
신천동 533
 
1.1%
Other values (3666) 30037
61.5%
2024-04-18T06:09:36.704580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41298
 
16.8%
16790
 
6.8%
11722
 
4.8%
11621
 
4.7%
1 10087
 
4.1%
7898
 
3.2%
7748
 
3.1%
7587
 
3.1%
7557
 
3.1%
) 7337
 
3.0%
Other values (420) 116735
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149410
60.6%
Space Separator 41298
 
16.8%
Decimal Number 32513
 
13.2%
Close Punctuation 7337
 
3.0%
Open Punctuation 7337
 
3.0%
Other Punctuation 6944
 
2.8%
Dash Punctuation 961
 
0.4%
Uppercase Letter 365
 
0.1%
Lowercase Letter 204
 
0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16790
 
11.2%
11722
 
7.8%
11621
 
7.8%
7898
 
5.3%
7748
 
5.2%
7587
 
5.1%
7557
 
5.1%
4439
 
3.0%
3485
 
2.3%
3109
 
2.1%
Other values (373) 67454
45.1%
Uppercase Letter
ValueCountFrequency (%)
B 85
23.3%
S 77
21.1%
K 65
17.8%
A 61
16.7%
H 29
 
7.9%
C 15
 
4.1%
G 7
 
1.9%
M 5
 
1.4%
D 4
 
1.1%
F 3
 
0.8%
Other values (8) 14
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 10087
31.0%
2 4921
15.1%
3 3646
 
11.2%
4 2468
 
7.6%
0 2353
 
7.2%
6 2036
 
6.3%
9 2031
 
6.2%
7 1871
 
5.8%
5 1591
 
4.9%
8 1509
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
e 32
15.7%
p 28
13.7%
u 28
13.7%
s 28
13.7%
l 28
13.7%
o 28
13.7%
m 28
13.7%
b 4
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 6933
99.8%
@ 4
 
0.1%
. 4
 
0.1%
/ 2
 
< 0.1%
· 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 8
72.7%
+ 3
 
27.3%
Space Separator
ValueCountFrequency (%)
41298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7337
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7337
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 961
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149410
60.6%
Common 96401
39.1%
Latin 569
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16790
 
11.2%
11722
 
7.8%
11621
 
7.8%
7898
 
5.3%
7748
 
5.2%
7587
 
5.1%
7557
 
5.1%
4439
 
3.0%
3485
 
2.3%
3109
 
2.1%
Other values (373) 67454
45.1%
Latin
ValueCountFrequency (%)
B 85
14.9%
S 77
13.5%
K 65
11.4%
A 61
10.7%
e 32
 
5.6%
H 29
 
5.1%
p 28
 
4.9%
u 28
 
4.9%
s 28
 
4.9%
l 28
 
4.9%
Other values (16) 108
19.0%
Common
ValueCountFrequency (%)
41298
42.8%
1 10087
 
10.5%
) 7337
 
7.6%
( 7337
 
7.6%
, 6933
 
7.2%
2 4921
 
5.1%
3 3646
 
3.8%
4 2468
 
2.6%
0 2353
 
2.4%
6 2036
 
2.1%
Other values (11) 7985
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149410
60.6%
ASCII 96969
39.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41298
42.6%
1 10087
 
10.4%
) 7337
 
7.6%
( 7337
 
7.6%
, 6933
 
7.1%
2 4921
 
5.1%
3 3646
 
3.8%
4 2468
 
2.5%
0 2353
 
2.4%
6 2036
 
2.1%
Other values (36) 8553
 
8.8%
Hangul
ValueCountFrequency (%)
16790
 
11.2%
11722
 
7.8%
11621
 
7.8%
7898
 
5.3%
7748
 
5.2%
7587
 
5.1%
7557
 
5.1%
4439
 
3.0%
3485
 
2.3%
3109
 
2.1%
Other values (373) 67454
45.1%
None
ValueCountFrequency (%)
· 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1014
Distinct (%)13.5%
Missing2473
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean42007.598
Minimum41000
Maximum59712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:36.827193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41097
Q141477
median41953
Q342620
95-th percentile42927
Maximum59712
Range18712
Interquartile range (IQR)1143

Descriptive statistics

Standard deviation633.47322
Coefficient of variation (CV)0.015079968
Kurtosis79.55984
Mean42007.598
Median Absolute Deviation (MAD)531
Skewness2.9205894
Sum3.1619119 × 108
Variance401288.32
MonotonicityNot monotonic
2024-04-18T06:09:36.944059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41229 489
 
4.9%
41936 394
 
3.9%
41953 261
 
2.6%
42037 251
 
2.5%
42637 246
 
2.5%
42809 239
 
2.4%
42778 225
 
2.2%
41084 167
 
1.7%
41581 159
 
1.6%
41422 144
 
1.4%
Other values (1004) 4952
49.5%
(Missing) 2473
24.7%
ValueCountFrequency (%)
41000 4
 
< 0.1%
41001 3
 
< 0.1%
41002 10
0.1%
41003 2
 
< 0.1%
41005 9
0.1%
41007 5
0.1%
41008 3
 
< 0.1%
41009 3
 
< 0.1%
41015 1
 
< 0.1%
41016 3
 
< 0.1%
ValueCountFrequency (%)
59712 1
 
< 0.1%
44220 1
 
< 0.1%
43024 6
 
0.1%
43022 1
 
< 0.1%
43020 1
 
< 0.1%
43018 28
0.3%
43017 7
 
0.1%
43015 2
 
< 0.1%
43014 15
0.1%
43013 1
 
< 0.1%
Distinct5582
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T06:09:37.156301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length6.1393
Min length1

Characters and Unicode

Total characters61393
Distinct characters866
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4595 ?
Unique (%)46.0%

Sample

1st row구지떡방앗간
2nd row산마니건강촌
3rd row새서울떡집
4th row바다채마
5th row주공참기름
ValueCountFrequency (%)
주식회사 331
 
3.0%
주)부촌푸드 97
 
0.9%
은호유통 97
 
0.9%
주)정성 78
 
0.7%
주)미트벨리 76
 
0.7%
주)인네이처 73
 
0.7%
제이수산 67
 
0.6%
수라원 64
 
0.6%
주)마켓인 63
 
0.6%
주경식품 61
 
0.6%
Other values (5784) 10003
90.9%
2024-04-18T06:09:37.494786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2500
 
4.1%
) 2144
 
3.5%
( 2090
 
3.4%
1458
 
2.4%
1269
 
2.1%
1010
 
1.6%
998
 
1.6%
973
 
1.6%
922
 
1.5%
888
 
1.4%
Other values (856) 47141
76.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54569
88.9%
Close Punctuation 2145
 
3.5%
Open Punctuation 2091
 
3.4%
Space Separator 1010
 
1.6%
Lowercase Letter 658
 
1.1%
Uppercase Letter 620
 
1.0%
Decimal Number 168
 
0.3%
Other Punctuation 108
 
0.2%
Dash Punctuation 18
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2500
 
4.6%
1458
 
2.7%
1269
 
2.3%
998
 
1.8%
973
 
1.8%
922
 
1.7%
888
 
1.6%
782
 
1.4%
780
 
1.4%
760
 
1.4%
Other values (777) 43239
79.2%
Uppercase Letter
ValueCountFrequency (%)
A 52
 
8.4%
S 48
 
7.7%
E 44
 
7.1%
O 44
 
7.1%
N 44
 
7.1%
F 42
 
6.8%
T 35
 
5.6%
C 34
 
5.5%
I 33
 
5.3%
D 30
 
4.8%
Other values (15) 214
34.5%
Lowercase Letter
ValueCountFrequency (%)
e 86
13.1%
o 71
 
10.8%
a 60
 
9.1%
i 49
 
7.4%
s 39
 
5.9%
n 37
 
5.6%
m 35
 
5.3%
t 33
 
5.0%
r 33
 
5.0%
l 32
 
4.9%
Other values (14) 183
27.8%
Decimal Number
ValueCountFrequency (%)
1 39
23.2%
2 26
15.5%
0 20
11.9%
5 17
10.1%
9 16
9.5%
8 13
 
7.7%
7 11
 
6.5%
6 10
 
6.0%
3 9
 
5.4%
4 7
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 34
31.5%
& 33
30.6%
' 14
13.0%
! 9
 
8.3%
, 9
 
8.3%
: 5
 
4.6%
/ 2
 
1.9%
; 1
 
0.9%
% 1
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 2144
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2090
> 99.9%
[ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1010
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54544
88.8%
Common 5543
 
9.0%
Latin 1280
 
2.1%
Han 26
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2500
 
4.6%
1458
 
2.7%
1269
 
2.3%
998
 
1.8%
973
 
1.8%
922
 
1.7%
888
 
1.6%
782
 
1.4%
780
 
1.4%
760
 
1.4%
Other values (768) 43214
79.2%
Latin
ValueCountFrequency (%)
e 86
 
6.7%
o 71
 
5.5%
a 60
 
4.7%
A 52
 
4.1%
i 49
 
3.8%
S 48
 
3.8%
E 44
 
3.4%
O 44
 
3.4%
N 44
 
3.4%
F 42
 
3.3%
Other values (41) 740
57.8%
Common
ValueCountFrequency (%)
) 2144
38.7%
( 2090
37.7%
1010
18.2%
1 39
 
0.7%
. 34
 
0.6%
& 33
 
0.6%
2 26
 
0.5%
0 20
 
0.4%
- 18
 
0.3%
5 17
 
0.3%
Other values (17) 112
 
2.0%
Han
ValueCountFrequency (%)
17
65.4%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54543
88.8%
ASCII 6821
 
11.1%
CJK 25
 
< 0.1%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2500
 
4.6%
1458
 
2.7%
1269
 
2.3%
998
 
1.8%
973
 
1.8%
922
 
1.7%
888
 
1.6%
782
 
1.4%
780
 
1.4%
760
 
1.4%
Other values (767) 43213
79.2%
ASCII
ValueCountFrequency (%)
) 2144
31.4%
( 2090
30.6%
1010
14.8%
e 86
 
1.3%
o 71
 
1.0%
a 60
 
0.9%
A 52
 
0.8%
i 49
 
0.7%
S 48
 
0.7%
E 44
 
0.6%
Other values (66) 1167
17.1%
CJK
ValueCountFrequency (%)
17
68.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct7807
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2001-08-21 00:00:00
Maximum2023-05-31 15:35:01
2024-04-18T06:09:37.606072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:09:37.717952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
5804 
U
4196 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5804
58.0%
U 4196
42.0%

Length

2024-04-18T06:09:37.816072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:37.884676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5804
58.0%
u 4196
42.0%
Distinct1579
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-06-02 02:40:00
2024-04-18T06:09:37.964094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:09:38.067242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9995 
기타
 
4
한식
 
1

Length

Max length9
Median length9
Mean length8.9965
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9995
> 99.9%
기타 4
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-18T06:09:38.174856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:38.251341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9995
> 99.9%
기타 4
 
< 0.1%
한식 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3756
Distinct (%)38.4%
Missing214
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean343269.69
Minimum264512.34
Maximum412704.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:38.338137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum264512.34
5-th percentile335086.71
Q1339324.36
median343588.74
Q3347037.24
95-th percentile353893.91
Maximum412704.63
Range148192.28
Interquartile range (IQR)7712.879

Descriptive statistics

Standard deviation5490.8179
Coefficient of variation (CV)0.015995639
Kurtosis6.8592913
Mean343269.69
Median Absolute Deviation (MAD)3707.473
Skewness0.051616278
Sum3.3592372 × 109
Variance30149081
MonotonicityNot monotonic
2024-04-18T06:09:38.442848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
347037.241970286 478
 
4.8%
339047.793378934 363
 
3.6%
345032.238220744 345
 
3.5%
347757.985568431 271
 
2.7%
343588.735554802 270
 
2.7%
337916.079938251 258
 
2.6%
337647.188646821 245
 
2.5%
340320.722709596 227
 
2.3%
355939.362329351 188
 
1.9%
344052.576927614 176
 
1.8%
Other values (3746) 6965
69.7%
(Missing) 214
 
2.1%
ValueCountFrequency (%)
264512.344650104 1
< 0.1%
326635.578062437 2
< 0.1%
326739.522357072 1
< 0.1%
326755.194077405 1
< 0.1%
326766.322228123 1
< 0.1%
327254.22982369 1
< 0.1%
327557.239553708 1
< 0.1%
327606.504993731 1
< 0.1%
327853.173808645 2
< 0.1%
327934.396590179 1
< 0.1%
ValueCountFrequency (%)
412704.62662297 1
< 0.1%
358070.673996722 1
< 0.1%
358026.99563512 1
< 0.1%
358012.428888704 1
< 0.1%
357990.643845118 1
< 0.1%
357987.298885612 1
< 0.1%
357881.329153021 1
< 0.1%
357870.136201308 2
< 0.1%
356965.555232748 1
< 0.1%
356643.050517102 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3756
Distinct (%)38.4%
Missing214
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean263242.4
Minimum139517.97
Maximum278333.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:38.571857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139517.97
5-th percentile257627.38
Q1261133.81
median263530.81
Q3265407.4
95-th percentile271557.94
Maximum278333.97
Range138816
Interquartile range (IQR)4273.5987

Descriptive statistics

Standard deviation4769.7239
Coefficient of variation (CV)0.018119132
Kurtosis50.035813
Mean263242.4
Median Absolute Deviation (MAD)1876.5944
Skewness-2.7251869
Sum2.5760901 × 109
Variance22750266
MonotonicityNot monotonic
2024-04-18T06:09:38.702226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
265407.404336831 478
 
4.8%
258741.902180368 363
 
3.6%
262949.871621315 345
 
3.5%
264692.744180043 271
 
2.7%
264119.010750105 270
 
2.7%
262111.061697986 258
 
2.6%
258512.316695219 245
 
2.5%
272735.675659876 227
 
2.3%
264777.243597576 188
 
1.9%
265131.653371228 176
 
1.8%
Other values (3746) 6965
69.7%
(Missing) 214
 
2.1%
ValueCountFrequency (%)
139517.968806039 1
< 0.1%
236978.764868043 1
< 0.1%
239193.193196123 1
< 0.1%
239523.935659457 1
< 0.1%
239755.102303496 1
< 0.1%
240281.048475686 1
< 0.1%
240330.145331269 1
< 0.1%
240358.722944009 2
< 0.1%
240649.764741954 2
< 0.1%
240737.702806251 1
< 0.1%
ValueCountFrequency (%)
278333.965932319 1
< 0.1%
278232.384480716 1
< 0.1%
278117.387967228 1
< 0.1%
278091.653532319 1
< 0.1%
278073.623285671 2
< 0.1%
277985.364429412 1
< 0.1%
277832.87261472 1
< 0.1%
277117.708906569 1
< 0.1%
277076.243491265 1
< 0.1%
276972.474723707 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9995 
기타
 
4
한식
 
1

Length

Max length9
Median length9
Mean length8.9965
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9995
> 99.9%
기타 4
 
< 0.1%
한식 1
 
< 0.1%

Length

2024-04-18T06:09:38.846970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:38.932655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9995
> 99.9%
기타 4
 
< 0.1%
한식 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8147 
0
1853 

Length

Max length4
Median length4
Mean length3.4441
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> 8147
81.5%
0 1853
 
18.5%

Length

2024-04-18T06:09:39.017055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.095717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8147
81.5%
0 1853
 
18.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8147 
0
1853 

Length

Max length4
Median length4
Mean length3.4441
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> 8147
81.5%
0 1853
 
18.5%

Length

2024-04-18T06:09:39.192727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.266069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8147
81.5%
0 1853
 
18.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7513 
상수도전용
2483 
전용상수도(특정시설의 자가용 수도)
 
2
지하수전용
 
1
간이상수도
 
1

Length

Max length19
Median length4
Mean length4.2515
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7513
75.1%
상수도전용 2483
 
24.8%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%
지하수전용 1
 
< 0.1%
간이상수도 1
 
< 0.1%

Length

2024-04-18T06:09:39.354151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.437707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7513
75.1%
상수도전용 2483
 
24.8%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%
지하수전용 1
 
< 0.1%
간이상수도 1
 
< 0.1%

총직원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8163 
0
1837 

Length

Max length4
Median length4
Mean length3.4489
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> 8163
81.6%
0 1837
 
18.4%

Length

2024-04-18T06:09:39.528829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.602200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8163
81.6%
0 1837
 
18.4%

본사직원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5892 
<NA>
4029 
1
 
71
2
 
6
4
 
1

Length

Max length4
Median length1
Mean length2.2087
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 5892
58.9%
<NA> 4029
40.3%
1 71
 
0.7%
2 6
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-18T06:09:39.683399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.768235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5892
58.9%
na 4029
40.3%
1 71
 
0.7%
2 6
 
0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

공장사무직직원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5951 
<NA>
4029 
1
 
17
2
 
2
10
 
1

Length

Max length4
Median length1
Mean length2.2088
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5951
59.5%
<NA> 4029
40.3%
1 17
 
0.2%
2 2
 
< 0.1%
10 1
 
< 0.1%

Length

2024-04-18T06:09:39.857899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:39.947541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5951
59.5%
na 4029
40.3%
1 17
 
0.2%
2 2
 
< 0.1%
10 1
 
< 0.1%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.1%
Missing4029
Missing (%)40.3%
Infinite0
Infinite (%)0.0%
Mean0.0701725
Minimum0
Maximum20
Zeros5624
Zeros (%)56.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:40.033637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3877517
Coefficient of variation (CV)5.525693
Kurtosis1178.9549
Mean0.0701725
Median Absolute Deviation (MAD)0
Skewness24.918849
Sum419
Variance0.15035138
MonotonicityNot monotonic
2024-04-18T06:09:40.118986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 5624
56.2%
1 302
 
3.0%
2 37
 
0.4%
3 5
 
0.1%
4 2
 
< 0.1%
20 1
 
< 0.1%
(Missing) 4029
40.3%
ValueCountFrequency (%)
0 5624
56.2%
1 302
 
3.0%
2 37
 
0.4%
3 5
 
0.1%
4 2
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
4 2
 
< 0.1%
3 5
 
0.1%
2 37
 
0.4%
1 302
 
3.0%
0 5624
56.2%

공장생산직직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.1%
Missing4029
Missing (%)40.3%
Infinite0
Infinite (%)0.0%
Mean0.10098811
Minimum0
Maximum10
Zeros5503
Zeros (%)55.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:40.212767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.39598153
Coefficient of variation (CV)3.9210708
Kurtosis86.119535
Mean0.10098811
Median Absolute Deviation (MAD)0
Skewness6.5124985
Sum603
Variance0.15680137
MonotonicityNot monotonic
2024-04-18T06:09:40.291580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 5503
55.0%
1 361
 
3.6%
2 91
 
0.9%
3 11
 
0.1%
4 3
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 4029
40.3%
ValueCountFrequency (%)
0 5503
55.0%
1 361
 
3.6%
2 91
 
0.9%
3 11
 
0.1%
4 3
 
< 0.1%
5 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
< 0.1%
3 11
 
0.1%
2 91
 
0.9%
1 361
 
3.6%
0 5503
55.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7078 
자가
1882 
임대
1040 

Length

Max length4
Median length4
Mean length3.4156
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7078
70.8%
자가 1882
 
18.8%
임대 1040
 
10.4%

Length

2024-04-18T06:09:40.414698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:40.520735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7078
70.8%
자가 1882
 
18.8%
임대 1040
 
10.4%

보증액
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7885 
0
2108 
10000000
 
3
5000000
 
2
15000000
 
1

Length

Max length8
Median length4
Mean length3.3701
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7885
78.8%
0 2108
 
21.1%
10000000 3
 
< 0.1%
5000000 2
 
< 0.1%
15000000 1
 
< 0.1%
2000000 1
 
< 0.1%

Length

2024-04-18T06:09:40.610527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:09:40.694431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7885
78.8%
0 2108
 
21.1%
10000000 3
 
< 0.1%
5000000 2
 
< 0.1%
15000000 1
 
< 0.1%
2000000 1
 
< 0.1%

월세액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.3%
Missing7885
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean1678.487
Minimum0
Maximum1000000
Zeros2108
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:40.773666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1000000
Range1000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32380.64
Coefficient of variation (CV)19.291564
Kurtosis583.57803
Mean1678.487
Median Absolute Deviation (MAD)0
Skewness22.811521
Sum3550000
Variance1.0485059 × 109
MonotonicityNot monotonic
2024-04-18T06:09:40.854516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 2108
 
21.1%
400000 2
 
< 0.1%
1000000 1
 
< 0.1%
350000 1
 
< 0.1%
700000 1
 
< 0.1%
200000 1
 
< 0.1%
500000 1
 
< 0.1%
(Missing) 7885
78.8%
ValueCountFrequency (%)
0 2108
21.1%
200000 1
 
< 0.1%
350000 1
 
< 0.1%
400000 2
 
< 0.1%
500000 1
 
< 0.1%
700000 1
 
< 0.1%
1000000 1
 
< 0.1%
ValueCountFrequency (%)
1000000 1
 
< 0.1%
700000 1
 
< 0.1%
500000 1
 
< 0.1%
400000 2
 
< 0.1%
350000 1
 
< 0.1%
200000 1
 
< 0.1%
0 2108
21.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2024-04-18T06:09:40.923223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct270
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.70922
Minimum0
Maximum172.7
Zeros9607
Zeros (%)96.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T06:09:41.388030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum172.7
Range172.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.4056688
Coefficient of variation (CV)7.6219914
Kurtosis240.04516
Mean0.70922
Median Absolute Deviation (MAD)0
Skewness13.053222
Sum7092.2
Variance29.221255
MonotonicityNot monotonic
2024-04-18T06:09:41.495368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9607
96.1%
3.0 16
 
0.2%
10.0 13
 
0.1%
3.3 9
 
0.1%
2.0 8
 
0.1%
1.0 7
 
0.1%
4.0 6
 
0.1%
6.0 6
 
0.1%
12.0 6
 
0.1%
5.0 5
 
0.1%
Other values (260) 317
 
3.2%
ValueCountFrequency (%)
0.0 9607
96.1%
0.42 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 7
 
0.1%
1.13 1
 
< 0.1%
1.14 1
 
< 0.1%
1.16 1
 
< 0.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.3 1
 
< 0.1%
ValueCountFrequency (%)
172.7 1
< 0.1%
132.2 1
< 0.1%
100.23 1
< 0.1%
99.3 1
< 0.1%
95.28 1
< 0.1%
94.89 1
< 0.1%
82.08 1
< 0.1%
82.0 1
< 0.1%
78.0 1
< 0.1%
77.68 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1785417855즉석판매제조가공업07_22_19_P34600003460000-107-2015-000232015-04-22<NA>3폐업2폐업2020-09-01<NA><NA><NA>053 763 298815.77706-838대구광역시 수성구 중동 417-46대구광역시 수성구 청수로 27-3 (중동)42154구지떡방앗간2020-09-01 14:22:38U2020-09-03 02:40:00즉석판매제조가공업345500.987047261307.534616즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
81048105즉석판매제조가공업07_22_19_P34300003430000-107-2014-000092014-05-27<NA>3폐업2폐업2020-02-05<NA><NA><NA><NA>30.0703-060대구광역시 서구 내당동 202-1 ,내당시영아파트 6동 점포5호대구광역시 서구 서대구로8길 15, 6동 점포5호 (내당동)41859산마니건강촌2020-02-04 14:00:30U2020-02-06 02:40:00즉석판매제조가공업340639.968381263582.844777즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
2140121402즉석판매제조가공업07_22_19_P34700003470000-107-2003-000852003-11-26<NA>3폐업2폐업2015-05-29<NA><NA><NA>053 636689129.26704-818대구광역시 달서구 상인동 1529-3 (지상1층)대구광역시 달서구 상화북로 195-9 (상인동,(지상1층))42812새서울떡집2003-11-26 00:00:00I2018-08-31 23:59:59즉석판매제조가공업339651.05814258226.541484즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>1000임대<NA><NA>N0.0<NA><NA><NA>
1804518046즉석판매제조가공업07_22_19_P34600003460000-107-2009-000912009-08-24<NA>3폐업2폐업2009-09-07<NA><NA><NA>02 847 90509.9706-803대구광역시 수성구 만촌동 1356-5 이마트만촌점<NA><NA>바다채마2009-09-01 11:11:21I2018-08-31 23:59:59즉석판매제조가공업347757.985568264692.74418즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
2624926250즉석판매제조가공업07_22_19_P34700003470000-107-1996-000381996-03-28<NA>1영업/정상1영업<NA><NA><NA><NA>053 635176834.22704-828대구광역시 달서구 월성동 86 주공2단지상가 나동 104호대구광역시 달서구 월성로 77, 나동 104호 (월성동,주공2단지상가)42732주공참기름2001-11-19 00:00:00I2018-08-31 23:59:59즉석판매제조가공업338085.062727259889.039763즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1733617337즉석판매제조가공업07_22_19_P34600003460000-107-2000-003132000-02-29<NA>3폐업2폐업2018-07-16<NA><NA><NA>784036729.16706-912대구광역시 수성구 지산동 1200 목련아파트 상가 8호대구광역시 수성구 용학로42길 13 (지산동,목련아파트 상가 8호)42220풍년2018-07-16 16:10:23I2018-08-31 23:59:59즉석판매제조가공업347435.764172258966.954321즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
2076820769즉석판매제조가공업07_22_19_P34700003470000-107-2021-000492021-02-15<NA>3폐업2폐업2021-03-03<NA><NA><NA>031557 0611<NA>704-928대구광역시 달서구 이곡동 1254대구광역시 달서구 이곡동로 24, 1층 (이곡동)42620주식회사 동광푸드2021-03-04 04:15:08U2021-03-06 02:40:00즉석판매제조가공업336343.945543262554.743801즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
77547755즉석판매제조가공업07_22_19_P34200003420000-107-2021-004572021-12-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>46.03701-805대구광역시 동구 불로동 1140-1대구광역시 동구 팔공로38길 10, 1층 (불로동)41030세웅컴퍼니2022-01-18 10:10:23U2022-01-20 02:40:00즉석판매제조가공업348114.59314269620.153174즉석판매제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
1326413265즉석판매제조가공업07_22_19_P34500003450000-107-2017-001322017-06-12<NA>3폐업2폐업2017-06-22<NA><NA><NA>031 571 0574<NA>702-852대구광역시 북구 칠성동2가 302-155대구광역시 북구 태평로 161, 지하2층 (칠성동2가, 롯데백화점 대구점)41581담은청2017-06-23 04:15:26I2018-08-31 23:59:59즉석판매제조가공업344052.576928265131.653371즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1642516426즉석판매제조가공업07_22_19_P34600003460000-107-2021-000592021-02-23<NA>3폐업2폐업2021-03-24<NA><NA><NA><NA><NA>706-800대구광역시 수성구 두산동 113 수성 SK리더스뷰 홈플러스수성점대구광역시 수성구 동대구로 95 (두산동, 수성 SK리더스뷰)42170덕유산유통2021-03-25 04:15:09U2021-03-27 02:40:00즉석판매제조가공업346586.097961261066.095208즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2717527176즉석판매제조가공업07_22_19_P34800003480000-107-2004-000252004-12-22<NA>3폐업2폐업2007-07-09<NA><NA><NA>053 614150633.0711-845대구광역시 달성군 옥포읍 본리리 2414-3<NA><NA>동의건강원2007-04-05 00:00:00I2018-08-31 23:59:59즉석판매제조가공업332212.762599255262.818338즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
15621563즉석판매제조가공업07_22_19_P34100003410000-107-2007-000172007-05-15<NA>3폐업2폐업2007-05-23<NA><NA><NA><NA>10.0700-718대구광역시 중구 대봉동 0214 대백프라자 지하1층<NA><NA>미고2007-05-15 00:00:00I2018-08-31 23:59:59즉석판매제조가공업345032.238221262949.871621즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
1463014631즉석판매제조가공업07_22_19_P34500003450000-107-2019-004342019-11-29<NA>3폐업2폐업2019-12-08<NA><NA><NA><NA><NA>702-845대구광역시 북구 산격동 1676 대구전시컨벤션센터대구광역시 북구 엑스코로 10, 대구전시컨벤션센터 (산격동)41515농업회사법인주식회사올릭2019-12-09 04:15:08U2019-12-11 02:40:00즉석판매제조가공업345549.11017268620.845678즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2607426075즉석판매제조가공업07_22_19_P34700003470000-107-2010-000952010-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.5704-808대구광역시 달서구 상인동 196-9 외 1필지대구광역시 달서구 월배로 207 (상인동,외 1필지)42781대구축산농협상인점하나로마트2015-04-20 16:07:41I2018-08-31 23:59:59즉석판매제조가공업338721.175606258736.994266즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1105011051즉석판매제조가공업07_22_19_P34500003450000-107-2021-000752021-03-30<NA>3폐업2폐업2022-12-30<NA><NA><NA><NA>17.75702-841대구광역시 북구 산격동 1258대구광역시 북구 대동로1길 34, 나동 110호 (산격동)41535김여사손맛1호점2022-12-30 09:08:09U2023-01-01 02:40:00즉석판매제조가공업345348.050145267644.219745즉석판매제조가공업00<NA><NA><NA>00000자가00N0.0<NA><NA><NA>
2773727738즉석판매제조가공업07_22_19_P34800003480000-107-2022-001082022-10-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0711-891대구광역시 달성군 구지면 응암리 1251 대구국가산단 반도유보라 아이비파크 2 131동 132호대구광역시 달성군 구지면 국가산단북로60길 59, 131동 132호 (대구국가산단 반도유보라 아이비파크 2)43008땅스부대찌개 구지점2022-10-14 17:36:00U2022-10-16 02:40:00즉석판매제조가공업328501.384301240739.938523즉석판매제조가공업00<NA><NA>상수도전용00000자가00N0.0<NA><NA><NA>
2255822559즉석판매제조가공업07_22_19_P34700003470000-107-2005-000022005-01-03<NA>3폐업2폐업2016-12-26<NA><NA><NA><NA>8.4704-834대구광역시 달서구 진천동 248-4 외5필지 A동대구광역시 달서구 월배로24길 40, A동 1층 (진천동)42801옛날맷돌식품2014-12-18 17:33:32I2018-08-31 23:59:59즉석판매제조가공업338016.853653258063.169811즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
1464414645즉석판매제조가공업07_22_19_P34500003450000-107-2019-004022019-11-07<NA>3폐업2폐업2019-11-20<NA><NA><NA><NA>50.0702-310대구광역시 북구 사수동 904대구광역시 북구 한강로 48, 1층 102호 (사수동)41598달달꽃2019-11-20 14:45:45U2019-11-22 02:40:00즉석판매제조가공업336704.960192267366.814076즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
20192020즉석판매제조가공업07_22_19_P34100003410000-107-2020-001802020-07-22<NA>3폐업2폐업2020-07-30<NA><NA><NA><NA><NA>700-718대구광역시 중구 대봉동 0214 대백프라자식품관대구광역시 중구 명덕로 333, 대백프라자식품관 (대봉동)41953은호유통2020-07-31 04:15:09U2020-08-02 02:40:00즉석판매제조가공업345032.238221262949.871621즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2677726778즉석판매제조가공업07_22_19_P34800003480000-107-2016-000882016-11-11<NA>3폐업2폐업2020-11-16<NA><NA><NA>053 759 112340.0711-851대구광역시 달성군 논공읍 금포리 1539-1대구광역시 달성군 논공읍 비슬로362길 1942974에이더블유2020-11-16 16:18:21U2020-11-18 02:40:00즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N13.3<NA><NA><NA>