Overview

Dataset statistics

Number of variables47
Number of observations2123
Missing cells21330
Missing cells (%)21.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory841.9 KiB
Average record size in memory406.1 B

Variable types

Numeric11
Categorical20
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년05월_6270000_대구광역시_07_22_08_P_식품소분업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093418&dataSetDetailId=DDI_0000093467&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (99.4%)Imbalance
위생업태명 is highly imbalanced (99.4%)Imbalance
남성종사자수 is highly imbalanced (64.2%)Imbalance
여성종사자수 is highly imbalanced (64.2%)Imbalance
총종업원수 is highly imbalanced (65.7%)Imbalance
본사종업원수 is highly imbalanced (59.6%)Imbalance
공장사무직종업원수 is highly imbalanced (59.1%)Imbalance
공장판매직종업원수 is highly imbalanced (51.3%)Imbalance
보증액 is highly imbalanced (60.6%)Imbalance
월세액 is highly imbalanced (79.7%)Imbalance
홈페이지 is highly imbalanced (99.4%)Imbalance
인허가취소일자 has 2123 (100.0%) missing valuesMissing
폐업일자 has 547 (25.8%) missing valuesMissing
휴업시작일자 has 2123 (100.0%) missing valuesMissing
휴업종료일자 has 2123 (100.0%) missing valuesMissing
재개업일자 has 2123 (100.0%) missing valuesMissing
소재지전화 has 808 (38.1%) missing valuesMissing
소재지면적 has 351 (16.5%) missing valuesMissing
도로명전체주소 has 908 (42.8%) missing valuesMissing
도로명우편번호 has 919 (43.3%) missing valuesMissing
좌표정보(X) has 95 (4.5%) missing valuesMissing
좌표정보(Y) has 95 (4.5%) missing valuesMissing
영업장주변구분명 has 2123 (100.0%) missing valuesMissing
등급구분명 has 2123 (100.0%) missing valuesMissing
공장생산직종업원수 has 600 (28.3%) missing valuesMissing
전통업소지정번호 has 2123 (100.0%) missing valuesMissing
전통업소주된음식 has 2123 (100.0%) missing valuesMissing
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
공장생산직종업원수 has 1321 (62.2%) zerosZeros
시설총규모 has 2040 (96.1%) zerosZeros

Reproduction

Analysis started2024-04-16 22:10:35.668189
Analysis finished2024-04-16 22:10:36.611924
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct2123
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1062
Minimum1
Maximum2123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:36.671545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile107.1
Q1531.5
median1062
Q31592.5
95-th percentile2016.9
Maximum2123
Range2122
Interquartile range (IQR)1061

Descriptive statistics

Standard deviation613.00163
Coefficient of variation (CV)0.57721434
Kurtosis-1.2
Mean1062
Median Absolute Deviation (MAD)531
Skewness0
Sum2254626
Variance375771
MonotonicityStrictly increasing
2024-04-17T07:10:36.772559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1412 1
 
< 0.1%
1426 1
 
< 0.1%
1425 1
 
< 0.1%
1424 1
 
< 0.1%
1423 1
 
< 0.1%
1422 1
 
< 0.1%
1421 1
 
< 0.1%
1420 1
 
< 0.1%
1419 1
 
< 0.1%
Other values (2113) 2113
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2123 1
< 0.1%
2122 1
< 0.1%
2121 1
< 0.1%
2120 1
< 0.1%
2119 1
< 0.1%
2118 1
< 0.1%
2117 1
< 0.1%
2116 1
< 0.1%
2115 1
< 0.1%
2114 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
식품소분업
2123 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 2123
100.0%

Length

2024-04-17T07:10:36.863053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:36.940415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 2123
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
07_22_08_P
2123 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_08_P
2nd row07_22_08_P
3rd row07_22_08_P
4th row07_22_08_P
5th row07_22_08_P

Common Values

ValueCountFrequency (%)
07_22_08_P 2123
100.0%

Length

2024-04-17T07:10:37.014184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:37.083765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_08_p 2123
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3447974.6
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:37.149294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21532.811
Coefficient of variation (CV)0.0062450608
Kurtosis-1.0399184
Mean3447974.6
Median Absolute Deviation (MAD)20000
Skewness-0.35726864
Sum7.32005 × 109
Variance4.6366194 × 108
MonotonicityIncreasing
2024-04-17T07:10:37.230590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 468
22.0%
3470000 405
19.1%
3460000 314
14.8%
3420000 242
11.4%
3410000 213
10.0%
3430000 183
 
8.6%
3480000 172
 
8.1%
3440000 126
 
5.9%
ValueCountFrequency (%)
3410000 213
10.0%
3420000 242
11.4%
3430000 183
 
8.6%
3440000 126
 
5.9%
3450000 468
22.0%
3460000 314
14.8%
3470000 405
19.1%
3480000 172
 
8.1%
ValueCountFrequency (%)
3480000 172
 
8.1%
3470000 405
19.1%
3460000 314
14.8%
3450000 468
22.0%
3440000 126
 
5.9%
3430000 183
 
8.6%
3420000 242
11.4%
3410000 213
10.0%

관리번호
Text

UNIQUE 

Distinct2123
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
2024-04-17T07:10:37.390746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters46706
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

Unique2123 ?
Unique (%)100.0%

Sample

1st row3410000-109-2008-00011
2nd row3410000-109-2005-00003
3rd row3410000-109-2005-00004
4th row3410000-109-2005-00005
5th row3410000-109-2005-00006
ValueCountFrequency (%)
3410000-109-2008-00011 1
 
< 0.1%
3460000-109-2002-00012 1
 
< 0.1%
3460000-109-2017-00002 1
 
< 0.1%
3460000-109-2017-00001 1
 
< 0.1%
3460000-109-2016-00013 1
 
< 0.1%
3460000-109-2014-00011 1
 
< 0.1%
3460000-109-2014-00007 1
 
< 0.1%
3460000-109-2013-00012 1
 
< 0.1%
3460000-109-2001-00014 1
 
< 0.1%
3460000-109-2001-00012 1
 
< 0.1%
Other values (2113) 2113
99.5%
2024-04-17T07:10:37.638589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21817
46.7%
- 6369
 
13.6%
1 4345
 
9.3%
2 3092
 
6.6%
3 2825
 
6.0%
4 2748
 
5.9%
9 2658
 
5.7%
5 906
 
1.9%
7 736
 
1.6%
6 716
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40337
86.4%
Dash Punctuation 6369
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21817
54.1%
1 4345
 
10.8%
2 3092
 
7.7%
3 2825
 
7.0%
4 2748
 
6.8%
9 2658
 
6.6%
5 906
 
2.2%
7 736
 
1.8%
6 716
 
1.8%
8 494
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 6369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46706
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21817
46.7%
- 6369
 
13.6%
1 4345
 
9.3%
2 3092
 
6.6%
3 2825
 
6.0%
4 2748
 
5.9%
9 2658
 
5.7%
5 906
 
1.9%
7 736
 
1.6%
6 716
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21817
46.7%
- 6369
 
13.6%
1 4345
 
9.3%
2 3092
 
6.6%
3 2825
 
6.0%
4 2748
 
5.9%
9 2658
 
5.7%
5 906
 
1.9%
7 736
 
1.6%
6 716
 
1.5%

인허가일자
Real number (ℝ)

Distinct1713
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20090064
Minimum19790523
Maximum20220516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:37.756631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790523
5-th percentile20000111
Q120040112
median20081119
Q320141121
95-th percentile20209218
Maximum20220516
Range429993
Interquartile range (IQR)101009.5

Descriptive statistics

Standard deviation69348.886
Coefficient of variation (CV)0.0034518996
Kurtosis-0.38231211
Mean20090064
Median Absolute Deviation (MAD)50502
Skewness-0.022752351
Sum4.2651207 × 1010
Variance4.809268 × 109
MonotonicityNot monotonic
2024-04-17T07:10:37.875056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030219 6
 
0.3%
20040827 5
 
0.2%
20021127 5
 
0.2%
20091015 5
 
0.2%
20131126 5
 
0.2%
20110721 4
 
0.2%
20001124 4
 
0.2%
20040910 4
 
0.2%
20020404 4
 
0.2%
20091116 4
 
0.2%
Other values (1703) 2077
97.8%
ValueCountFrequency (%)
19790523 1
< 0.1%
19791213 1
< 0.1%
19810727 1
< 0.1%
19850905 1
< 0.1%
19870905 1
< 0.1%
19890315 1
< 0.1%
19890318 1
< 0.1%
19900707 1
< 0.1%
19900711 1
< 0.1%
19900818 1
< 0.1%
ValueCountFrequency (%)
20220516 1
< 0.1%
20220509 2
0.1%
20220429 2
0.1%
20220426 1
< 0.1%
20220422 1
< 0.1%
20220421 1
< 0.1%
20220420 1
< 0.1%
20220415 1
< 0.1%
20220414 1
< 0.1%
20220411 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
3
1576 
1
547 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1576
74.2%
1 547
 
25.8%

Length

2024-04-17T07:10:37.978056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:38.072250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1576
74.2%
1 547
 
25.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
폐업
1576 
영업/정상
547 

Length

Max length5
Median length2
Mean length2.7729628
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1576
74.2%
영업/정상 547
 
25.8%

Length

2024-04-17T07:10:38.179266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:38.284442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1576
74.2%
영업/정상 547
 
25.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
2
1576 
1
547 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1576
74.2%
1 547
 
25.8%

Length

2024-04-17T07:10:38.366438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:38.438612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1576
74.2%
1 547
 
25.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
폐업
1576 
영업
547 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1576
74.2%
영업 547
 
25.8%

Length

2024-04-17T07:10:38.515077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:38.587514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1576
74.2%
영업 547
 
25.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct1232
Distinct (%)78.2%
Missing547
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean20109338
Minimum20000919
Maximum20220527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:38.677096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000919
5-th percentile20030703
Q120060325
median20100708
Q320160411
95-th percentile20201229
Maximum20220527
Range219608
Interquartile range (IQR)100086.25

Descriptive statistics

Standard deviation56499.507
Coefficient of variation (CV)0.0028096154
Kurtosis-1.1409241
Mean20109338
Median Absolute Deviation (MAD)49714
Skewness0.26571547
Sum3.1692317 × 1010
Variance3.1921943 × 109
MonotonicityNot monotonic
2024-04-17T07:10:38.807092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20100512 8
 
0.4%
20080213 7
 
0.3%
20021224 6
 
0.3%
20181227 5
 
0.2%
20050331 5
 
0.2%
20050218 4
 
0.2%
20040302 4
 
0.2%
20050620 4
 
0.2%
20110620 4
 
0.2%
20121205 4
 
0.2%
Other values (1222) 1525
71.8%
(Missing) 547
 
25.8%
ValueCountFrequency (%)
20000919 1
< 0.1%
20010108 1
< 0.1%
20011017 1
< 0.1%
20020115 1
< 0.1%
20020128 1
< 0.1%
20020131 1
< 0.1%
20020219 1
< 0.1%
20020321 1
< 0.1%
20020403 1
< 0.1%
20020408 2
0.1%
ValueCountFrequency (%)
20220527 1
< 0.1%
20220519 1
< 0.1%
20220511 1
< 0.1%
20220509 1
< 0.1%
20220429 1
< 0.1%
20220426 1
< 0.1%
20220421 1
< 0.1%
20220413 1
< 0.1%
20220405 2
0.1%
20220401 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

소재지전화
Text

MISSING 

Distinct1198
Distinct (%)91.1%
Missing808
Missing (%)38.1%
Memory size16.7 KiB
2024-04-17T07:10:39.077942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.58327
Min length2

Characters and Unicode

Total characters13917
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

Unique1115 ?
Unique (%)84.8%

Sample

1st row053 4261355
2nd row053 2531258
3rd row053 2542877
4th row053 6366337
5th row053 2544506
ValueCountFrequency (%)
053 915
33.2%
070 28
 
1.0%
312 13
 
0.5%
1234 10
 
0.4%
313 9
 
0.3%
6602001 8
 
0.3%
031 7
 
0.3%
765 7
 
0.3%
322 7
 
0.3%
986 7
 
0.3%
Other values (1357) 1745
63.3%
2024-04-17T07:10:39.441855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2182
15.7%
5 2119
15.2%
3 1940
13.9%
1449
10.4%
2 1084
7.8%
6 1018
7.3%
1 916
6.6%
7 913
6.6%
8 819
 
5.9%
4 799
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12468
89.6%
Space Separator 1449
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2182
17.5%
5 2119
17.0%
3 1940
15.6%
2 1084
8.7%
6 1018
8.2%
1 916
7.3%
7 913
7.3%
8 819
 
6.6%
4 799
 
6.4%
9 678
 
5.4%
Space Separator
ValueCountFrequency (%)
1449
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13917
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2182
15.7%
5 2119
15.2%
3 1940
13.9%
1449
10.4%
2 1084
7.8%
6 1018
7.3%
1 916
6.6%
7 913
6.6%
8 819
 
5.9%
4 799
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2182
15.7%
5 2119
15.2%
3 1940
13.9%
1449
10.4%
2 1084
7.8%
6 1018
7.3%
1 916
6.6%
7 913
6.6%
8 819
 
5.9%
4 799
 
5.7%

소재지면적
Text

MISSING 

Distinct899
Distinct (%)50.7%
Missing351
Missing (%)16.5%
Memory size16.7 KiB
2024-04-17T07:10:39.771025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.7020316
Min length3

Characters and Unicode

Total characters8332
Distinct characters12
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

Unique693 ?
Unique (%)39.1%

Sample

1st row4.00
2nd row126.15
3rd row3.50
4th row8.17
5th row1.61
ValueCountFrequency (%)
00 46
 
2.6%
3.30 41
 
2.3%
4.00 37
 
2.1%
6.00 36
 
2.0%
6.60 32
 
1.8%
3.00 30
 
1.7%
12.00 26
 
1.5%
30.00 26
 
1.5%
33.00 26
 
1.5%
20.00 25
 
1.4%
Other values (889) 1447
81.7%
2024-04-17T07:10:40.185790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2056
24.7%
. 1772
21.3%
1 702
 
8.4%
2 645
 
7.7%
3 598
 
7.2%
6 546
 
6.6%
4 489
 
5.9%
5 487
 
5.8%
9 362
 
4.3%
7 342
 
4.1%
Other values (2) 333
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6559
78.7%
Other Punctuation 1773
 
21.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2056
31.3%
1 702
 
10.7%
2 645
 
9.8%
3 598
 
9.1%
6 546
 
8.3%
4 489
 
7.5%
5 487
 
7.4%
9 362
 
5.5%
7 342
 
5.2%
8 332
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 1772
99.9%
, 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 8332
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2056
24.7%
. 1772
21.3%
1 702
 
8.4%
2 645
 
7.7%
3 598
 
7.2%
6 546
 
6.6%
4 489
 
5.9%
5 487
 
5.8%
9 362
 
4.3%
7 342
 
4.1%
Other values (2) 333
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8332
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2056
24.7%
. 1772
21.3%
1 702
 
8.4%
2 645
 
7.7%
3 598
 
7.2%
6 546
 
6.6%
4 489
 
5.9%
5 487
 
5.8%
9 362
 
4.3%
7 342
 
4.1%
Other values (2) 333
 
4.0%

소재지우편번호
Real number (ℝ)

Distinct462
Distinct (%)22.0%
Missing19
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean704316.37
Minimum700040
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:40.300230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700040
5-th percentile700440
Q1702746
median703832.5
Q3705816
95-th percentile711832
Maximum711892
Range11852
Interquartile range (IQR)3070

Descriptive statistics

Standard deviation2847.6314
Coefficient of variation (CV)0.004043114
Kurtosis1.1562978
Mean704316.37
Median Absolute Deviation (MAD)1792.5
Skewness1.0826111
Sum1.4818816 × 109
Variance8109004.6
MonotonicityNot monotonic
2024-04-17T07:10:40.414271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 65
 
3.1%
704923 56
 
2.6%
702746 32
 
1.5%
704722 30
 
1.4%
700718 27
 
1.3%
700811 26
 
1.2%
700070 24
 
1.1%
702853 23
 
1.1%
711852 22
 
1.0%
706813 22
 
1.0%
Other values (452) 1777
83.7%
ValueCountFrequency (%)
700040 1
 
< 0.1%
700060 1
 
< 0.1%
700070 24
1.1%
700082 4
 
0.2%
700092 21
1.0%
700093 1
 
< 0.1%
700111 3
 
0.1%
700180 12
0.6%
700191 2
 
0.1%
700192 2
 
0.1%
ValueCountFrequency (%)
711892 4
0.2%
711891 3
0.1%
711874 3
0.1%
711873 1
 
< 0.1%
711872 1
 
< 0.1%
711864 3
0.1%
711863 1
 
< 0.1%
711861 1
 
< 0.1%
711858 2
0.1%
711856 2
0.1%
Distinct1795
Distinct (%)84.7%
Missing4
Missing (%)0.2%
Memory size16.7 KiB
2024-04-17T07:10:40.668963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length44
Mean length24.508731
Min length16

Characters and Unicode

Total characters51934
Distinct characters305
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1630 ?
Unique (%)76.9%

Sample

1st row대구광역시 중구 동성로2가 0174
2nd row대구광역시 중구 남산동 2109-0001
3rd row대구광역시 중구 대봉동 0214
4th row대구광역시 중구 동문동 0020-0004
5th row대구광역시 중구 대봉동 0214 대백프라자
ValueCountFrequency (%)
대구광역시 2119
 
20.9%
북구 468
 
4.6%
달서구 404
 
4.0%
수성구 313
 
3.1%
동구 243
 
2.4%
중구 213
 
2.1%
서구 183
 
1.8%
달성군 171
 
1.7%
남구 124
 
1.2%
1층 124
 
1.2%
Other values (2120) 5766
56.9%
2024-04-17T07:10:41.058262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10112
19.5%
4164
 
8.0%
1 2636
 
5.1%
2462
 
4.7%
2451
 
4.7%
2177
 
4.2%
2122
 
4.1%
2121
 
4.1%
0 1834
 
3.5%
- 1618
 
3.1%
Other values (295) 20237
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27984
53.9%
Decimal Number 11491
22.1%
Space Separator 10112
 
19.5%
Dash Punctuation 1618
 
3.1%
Open Punctuation 256
 
0.5%
Close Punctuation 252
 
0.5%
Other Punctuation 111
 
0.2%
Uppercase Letter 104
 
0.2%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4164
14.9%
2462
 
8.8%
2451
 
8.8%
2177
 
7.8%
2122
 
7.6%
2121
 
7.6%
786
 
2.8%
678
 
2.4%
613
 
2.2%
612
 
2.2%
Other values (264) 9798
35.0%
Uppercase Letter
ValueCountFrequency (%)
A 55
52.9%
B 34
32.7%
C 5
 
4.8%
T 2
 
1.9%
S 2
 
1.9%
E 1
 
1.0%
M 1
 
1.0%
L 1
 
1.0%
K 1
 
1.0%
G 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 2636
22.9%
0 1834
16.0%
2 1517
13.2%
3 1117
9.7%
5 982
 
8.5%
4 770
 
6.7%
7 714
 
6.2%
6 709
 
6.2%
8 632
 
5.5%
9 580
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 100
90.1%
. 10
 
9.0%
@ 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
10112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1618
100.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 252
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27982
53.9%
Common 23844
45.9%
Latin 106
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4164
14.9%
2462
 
8.8%
2451
 
8.8%
2177
 
7.8%
2122
 
7.6%
2121
 
7.6%
786
 
2.8%
678
 
2.4%
613
 
2.2%
612
 
2.2%
Other values (263) 9796
35.0%
Common
ValueCountFrequency (%)
10112
42.4%
1 2636
 
11.1%
0 1834
 
7.7%
- 1618
 
6.8%
2 1517
 
6.4%
3 1117
 
4.7%
5 982
 
4.1%
4 770
 
3.2%
7 714
 
3.0%
6 709
 
3.0%
Other values (8) 1835
 
7.7%
Latin
ValueCountFrequency (%)
A 55
51.9%
B 34
32.1%
C 5
 
4.7%
T 2
 
1.9%
S 2
 
1.9%
e 1
 
0.9%
E 1
 
0.9%
M 1
 
0.9%
L 1
 
0.9%
K 1
 
0.9%
Other values (3) 3
 
2.8%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27982
53.9%
ASCII 23950
46.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10112
42.2%
1 2636
 
11.0%
0 1834
 
7.7%
- 1618
 
6.8%
2 1517
 
6.3%
3 1117
 
4.7%
5 982
 
4.1%
4 770
 
3.2%
7 714
 
3.0%
6 709
 
3.0%
Other values (21) 1941
 
8.1%
Hangul
ValueCountFrequency (%)
4164
14.9%
2462
 
8.8%
2451
 
8.8%
2177
 
7.8%
2122
 
7.6%
2121
 
7.6%
786
 
2.8%
678
 
2.4%
613
 
2.2%
612
 
2.2%
Other values (263) 9796
35.0%
CJK
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct1175
Distinct (%)96.7%
Missing908
Missing (%)42.8%
Memory size16.7 KiB
2024-04-17T07:10:41.378715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length29.375309
Min length19

Characters and Unicode

Total characters35691
Distinct characters314
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1142 ?
Unique (%)94.0%

Sample

1st row대구광역시 중구 달구벌대로443길 40 (삼덕동3가)
2nd row대구광역시 중구 남성로 40-1, 2층 (남성로)
3rd row대구광역시 중구 동덕로 115 (삼덕동2가, 진석타워 902호(S7호))
4th row대구광역시 중구 큰장로26길 18 (대신동)
5th row대구광역시 중구 경상감영길 26, 2층 (서문로1가)
ValueCountFrequency (%)
대구광역시 1215
 
17.0%
1층 392
 
5.5%
북구 264
 
3.7%
달서구 236
 
3.3%
동구 173
 
2.4%
수성구 171
 
2.4%
달성군 108
 
1.5%
서구 94
 
1.3%
남구 91
 
1.3%
중구 78
 
1.1%
Other values (1662) 4342
60.6%
2024-04-17T07:10:41.782761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5951
 
16.7%
2472
 
6.9%
1 1616
 
4.5%
1582
 
4.4%
1555
 
4.4%
1273
 
3.6%
1222
 
3.4%
1217
 
3.4%
( 1186
 
3.3%
) 1186
 
3.3%
Other values (304) 16431
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20485
57.4%
Space Separator 5951
 
16.7%
Decimal Number 5589
 
15.7%
Open Punctuation 1186
 
3.3%
Close Punctuation 1186
 
3.3%
Other Punctuation 942
 
2.6%
Dash Punctuation 242
 
0.7%
Uppercase Letter 105
 
0.3%
Math Symbol 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2472
 
12.1%
1582
 
7.7%
1555
 
7.6%
1273
 
6.2%
1222
 
6.0%
1217
 
5.9%
1171
 
5.7%
694
 
3.4%
690
 
3.4%
512
 
2.5%
Other values (274) 8097
39.5%
Uppercase Letter
ValueCountFrequency (%)
A 49
46.7%
B 36
34.3%
C 6
 
5.7%
E 3
 
2.9%
T 3
 
2.9%
K 1
 
1.0%
R 1
 
1.0%
W 1
 
1.0%
O 1
 
1.0%
F 1
 
1.0%
Other values (3) 3
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 1616
28.9%
2 819
14.7%
3 615
 
11.0%
4 447
 
8.0%
5 413
 
7.4%
0 391
 
7.0%
6 367
 
6.6%
7 356
 
6.4%
8 300
 
5.4%
9 265
 
4.7%
Space Separator
ValueCountFrequency (%)
5951
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1186
100.0%
Other Punctuation
ValueCountFrequency (%)
, 942
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20485
57.4%
Common 15100
42.3%
Latin 106
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2472
 
12.1%
1582
 
7.7%
1555
 
7.6%
1273
 
6.2%
1222
 
6.0%
1217
 
5.9%
1171
 
5.7%
694
 
3.4%
690
 
3.4%
512
 
2.5%
Other values (274) 8097
39.5%
Common
ValueCountFrequency (%)
5951
39.4%
1 1616
 
10.7%
( 1186
 
7.9%
) 1186
 
7.9%
, 942
 
6.2%
2 819
 
5.4%
3 615
 
4.1%
4 447
 
3.0%
5 413
 
2.7%
0 391
 
2.6%
Other values (6) 1534
 
10.2%
Latin
ValueCountFrequency (%)
A 49
46.2%
B 36
34.0%
C 6
 
5.7%
E 3
 
2.8%
T 3
 
2.8%
K 1
 
0.9%
R 1
 
0.9%
e 1
 
0.9%
W 1
 
0.9%
O 1
 
0.9%
Other values (4) 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20485
57.4%
ASCII 15206
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5951
39.1%
1 1616
 
10.6%
( 1186
 
7.8%
) 1186
 
7.8%
, 942
 
6.2%
2 819
 
5.4%
3 615
 
4.0%
4 447
 
2.9%
5 413
 
2.7%
0 391
 
2.6%
Other values (20) 1640
 
10.8%
Hangul
ValueCountFrequency (%)
2472
 
12.1%
1582
 
7.7%
1555
 
7.6%
1273
 
6.2%
1222
 
6.0%
1217
 
5.9%
1171
 
5.7%
694
 
3.4%
690
 
3.4%
512
 
2.5%
Other values (274) 8097
39.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct625
Distinct (%)51.9%
Missing919
Missing (%)43.3%
Infinite0
Infinite (%)0.0%
Mean42025.768
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:41.896860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41091
Q141488
median41963.5
Q342637
95-th percentile42955.7
Maximum43024
Range2024
Interquartile range (IQR)1149

Descriptive statistics

Standard deviation607.69637
Coefficient of variation (CV)0.01446009
Kurtosis-1.3011978
Mean42025.768
Median Absolute Deviation (MAD)504.5
Skewness0.03103237
Sum50599025
Variance369294.88
MonotonicityNot monotonic
2024-04-17T07:10:42.004396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41488 27
 
1.3%
42637 24
 
1.1%
41485 23
 
1.1%
41490 18
 
0.8%
41557 12
 
0.6%
41582 10
 
0.5%
41936 8
 
0.4%
41927 8
 
0.4%
42945 7
 
0.3%
41581 7
 
0.3%
Other values (615) 1060
49.9%
(Missing) 919
43.3%
ValueCountFrequency (%)
41000 3
0.1%
41001 1
 
< 0.1%
41002 3
0.1%
41007 1
 
< 0.1%
41009 3
0.1%
41020 3
0.1%
41026 5
0.2%
41028 1
 
< 0.1%
41035 1
 
< 0.1%
41036 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43023 2
0.1%
43013 3
0.1%
43011 3
0.1%
43010 1
 
< 0.1%
43005 1
 
< 0.1%
43004 1
 
< 0.1%
43003 2
0.1%
42996 1
 
< 0.1%
42993 1
 
< 0.1%
Distinct1673
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
2024-04-17T07:10:42.242592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length6.029675
Min length2

Characters and Unicode

Total characters12801
Distinct characters589
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1449 ?
Unique (%)68.3%

Sample

1st row남경식품
2nd row한국물산
3rd row더네이쳐샵
4th row전남생연
5th row스위트존
ValueCountFrequency (%)
주식회사 34
 
1.5%
대백마트 21
 
0.9%
개미농특산 14
 
0.6%
궁전방식품 11
 
0.5%
조은식품 9
 
0.4%
일해식품(주 9
 
0.4%
서문떡방 9
 
0.4%
우리농수산 8
 
0.3%
주)바다누리 8
 
0.3%
영진식품 7
 
0.3%
Other values (1741) 2170
94.3%
2024-04-17T07:10:42.795229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
497
 
3.9%
) 425
 
3.3%
( 420
 
3.3%
415
 
3.2%
404
 
3.2%
381
 
3.0%
372
 
2.9%
231
 
1.8%
228
 
1.8%
221
 
1.7%
Other values (579) 9207
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11503
89.9%
Close Punctuation 425
 
3.3%
Open Punctuation 420
 
3.3%
Space Separator 177
 
1.4%
Uppercase Letter 136
 
1.1%
Lowercase Letter 65
 
0.5%
Decimal Number 54
 
0.4%
Other Punctuation 15
 
0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
497
 
4.3%
415
 
3.6%
404
 
3.5%
381
 
3.3%
372
 
3.2%
231
 
2.0%
228
 
2.0%
221
 
1.9%
212
 
1.8%
186
 
1.6%
Other values (522) 8356
72.6%
Uppercase Letter
ValueCountFrequency (%)
D 16
11.8%
O 16
11.8%
S 15
11.0%
K 13
 
9.6%
F 12
 
8.8%
G 7
 
5.1%
M 6
 
4.4%
N 5
 
3.7%
A 5
 
3.7%
H 5
 
3.7%
Other values (12) 36
26.5%
Lowercase Letter
ValueCountFrequency (%)
o 13
20.0%
e 8
12.3%
n 6
9.2%
a 5
 
7.7%
d 5
 
7.7%
y 5
 
7.7%
w 3
 
4.6%
s 3
 
4.6%
t 3
 
4.6%
l 3
 
4.6%
Other values (7) 11
16.9%
Decimal Number
ValueCountFrequency (%)
2 10
18.5%
1 10
18.5%
4 7
13.0%
0 7
13.0%
9 5
9.3%
7 5
9.3%
3 4
 
7.4%
5 3
 
5.6%
8 2
 
3.7%
6 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
& 8
53.3%
. 5
33.3%
, 1
 
6.7%
: 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 425
100.0%
Open Punctuation
ValueCountFrequency (%)
( 420
100.0%
Space Separator
ValueCountFrequency (%)
177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11502
89.9%
Common 1097
 
8.6%
Latin 201
 
1.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
497
 
4.3%
415
 
3.6%
404
 
3.5%
381
 
3.3%
372
 
3.2%
231
 
2.0%
228
 
2.0%
221
 
1.9%
212
 
1.8%
186
 
1.6%
Other values (521) 8355
72.6%
Latin
ValueCountFrequency (%)
D 16
 
8.0%
O 16
 
8.0%
S 15
 
7.5%
K 13
 
6.5%
o 13
 
6.5%
F 12
 
6.0%
e 8
 
4.0%
G 7
 
3.5%
M 6
 
3.0%
n 6
 
3.0%
Other values (29) 89
44.3%
Common
ValueCountFrequency (%)
) 425
38.7%
( 420
38.3%
177
16.1%
2 10
 
0.9%
1 10
 
0.9%
& 8
 
0.7%
4 7
 
0.6%
0 7
 
0.6%
- 6
 
0.5%
9 5
 
0.5%
Other values (8) 22
 
2.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11501
89.8%
ASCII 1298
 
10.1%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
497
 
4.3%
415
 
3.6%
404
 
3.5%
381
 
3.3%
372
 
3.2%
231
 
2.0%
228
 
2.0%
221
 
1.9%
212
 
1.8%
186
 
1.6%
Other values (520) 8354
72.6%
ASCII
ValueCountFrequency (%)
) 425
32.7%
( 420
32.4%
177
13.6%
D 16
 
1.2%
O 16
 
1.2%
S 15
 
1.2%
K 13
 
1.0%
o 13
 
1.0%
F 12
 
0.9%
2 10
 
0.8%
Other values (47) 181
13.9%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1806
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0117118 × 1013
Minimum2.0010823 × 1013
Maximum2.0220527 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:42.917203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0010823 × 1013
5-th percentile2.0020725 × 1013
Q12.0050701 × 1013
median2.012032 × 1013
Q32.0181002 × 1013
95-th percentile2.0211201 × 1013
Maximum2.0220527 × 1013
Range2.0970411 × 1011
Interquartile range (IQR)1.3030114 × 1011

Descriptive statistics

Standard deviation6.6578897 × 1010
Coefficient of variation (CV)0.0033095643
Kurtosis-1.4292955
Mean2.0117118 × 1013
Median Absolute Deviation (MAD)6.9204164 × 1010
Skewness0.032137611
Sum4.2708643 × 1016
Variance4.4327495 × 1021
MonotonicityNot monotonic
2024-04-17T07:10:43.019723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041011000000 33
 
1.6%
20020124000000 29
 
1.4%
20020725000000 13
 
0.6%
20050322000000 11
 
0.5%
20021012000000 10
 
0.5%
20030612000000 10
 
0.5%
20020527000000 10
 
0.5%
20020528000000 10
 
0.5%
20021121000000 10
 
0.5%
20010823000000 9
 
0.4%
Other values (1796) 1978
93.2%
ValueCountFrequency (%)
20010823000000 9
 
0.4%
20020124000000 29
1.4%
20020125000000 2
 
0.1%
20020207000000 1
 
< 0.1%
20020226000000 1
 
< 0.1%
20020228000000 1
 
< 0.1%
20020307000000 1
 
< 0.1%
20020320000000 1
 
< 0.1%
20020403000000 1
 
< 0.1%
20020413000000 2
 
0.1%
ValueCountFrequency (%)
20220527110756 1
< 0.1%
20220525182939 1
< 0.1%
20220520145720 1
< 0.1%
20220520101222 1
< 0.1%
20220519102834 1
< 0.1%
20220519102721 1
< 0.1%
20220518113353 1
< 0.1%
20220517164704 1
< 0.1%
20220516134400 1
< 0.1%
20220516121015 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
I
1667 
U
456 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1667
78.5%
U 456
 
21.5%

Length

2024-04-17T07:10:43.115180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:43.188245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1667
78.5%
u 456
 
21.5%
Distinct418
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
Minimum2018-08-31 23:59:59
Maximum2022-05-29 02:40:00
2024-04-17T07:10:43.272551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T07:10:43.380216image/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 size16.7 KiB
식품소분업
2122 
<NA>
 
1

Length

Max length5
Median length5
Mean length4.999529
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 2122
> 99.9%
<NA> 1
 
< 0.1%

Length

2024-04-17T07:10:43.482437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:43.574342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 2122
> 99.9%
na 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1375
Distinct (%)67.8%
Missing95
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean342527.1
Minimum326848.48
Maximum356477.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:43.659688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326848.48
5-th percentile333731.58
Q1339047.79
median342067.26
Q3345739.81
95-th percentile353467.46
Maximum356477.57
Range29629.088
Interquartile range (IQR)6692.0134

Descriptive statistics

Standard deviation5419.7436
Coefficient of variation (CV)0.015822817
Kurtosis0.24163564
Mean342527.1
Median Absolute Deviation (MAD)3198.6915
Skewness0.15233283
Sum6.9464497 × 108
Variance29373621
MonotonicityNot monotonic
2024-04-17T07:10:43.764821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
345032.238221 51
 
2.4%
339047.793379 47
 
2.2%
339243.983122 30
 
1.4%
338123.173581 29
 
1.4%
348194.499421 29
 
1.4%
337916.079938 25
 
1.2%
343705.561002 22
 
1.0%
345663.599839 19
 
0.9%
344047.164924 17
 
0.8%
340320.72271 16
 
0.8%
Other values (1365) 1743
82.1%
(Missing) 95
 
4.5%
ValueCountFrequency (%)
326848.481791 1
< 0.1%
327437.783351 1
< 0.1%
327489.324167 1
< 0.1%
327531.565421 1
< 0.1%
327605.063942 1
< 0.1%
327637.398011 1
< 0.1%
328014.79583 1
< 0.1%
328032.453545 1
< 0.1%
328213.561416 1
< 0.1%
328311.018298 1
< 0.1%
ValueCountFrequency (%)
356477.570168 1
 
< 0.1%
356370.489825 1
 
< 0.1%
356351.617491 1
 
< 0.1%
356347.076958 1
 
< 0.1%
356327.570046 1
 
< 0.1%
356325.339359 1
 
< 0.1%
356222.826617 1
 
< 0.1%
356082.08851 1
 
< 0.1%
355939.362329 7
0.3%
355907.185869 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1375
Distinct (%)67.8%
Missing95
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean263304.74
Minimum237972.41
Maximum277755.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:43.864739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237972.41
5-th percentile256717.62
Q1261135.84
median263514.08
Q3265607.66
95-th percentile270690.49
Maximum277755.21
Range39782.798
Interquartile range (IQR)4471.8219

Descriptive statistics

Standard deviation4629.2926
Coefficient of variation (CV)0.017581501
Kurtosis4.6865957
Mean263304.74
Median Absolute Deviation (MAD)2186.9507
Skewness-1.0789569
Sum5.3398202 × 108
Variance21430350
MonotonicityNot monotonic
2024-04-17T07:10:43.981290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262949.871621 51
 
2.4%
258741.90218 47
 
2.2%
268026.454531 30
 
1.4%
262253.34421 29
 
1.4%
259144.519321 29
 
1.4%
262111.061698 25
 
1.2%
264056.630949 22
 
1.0%
263506.50013 19
 
0.9%
265132.987974 17
 
0.8%
272735.67566 16
 
0.8%
Other values (1365) 1743
82.1%
(Missing) 95
 
4.5%
ValueCountFrequency (%)
237972.408064 1
< 0.1%
237999.437164 1
< 0.1%
238813.226712 1
< 0.1%
238824.505921 1
< 0.1%
238893.362765 1
< 0.1%
238893.829912 1
< 0.1%
239536.919741 1
< 0.1%
241150.870459 1
< 0.1%
242349.0 1
< 0.1%
243088.915629 2
0.1%
ValueCountFrequency (%)
277755.206408 1
< 0.1%
277673.246368 1
< 0.1%
277008.50814 1
< 0.1%
276811.276708 1
< 0.1%
275582.004218 1
< 0.1%
274822.293106 1
< 0.1%
274594.894588 1
< 0.1%
274508.218106 2
0.1%
274053.957157 1
< 0.1%
274035.207096 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
식품소분업
2122 
<NA>
 
1

Length

Max length5
Median length5
Mean length4.999529
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 2122
> 99.9%
<NA> 1
 
< 0.1%

Length

2024-04-17T07:10:44.083153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:44.157677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 2122
> 99.9%
na 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1979 
0
 
144

Length

Max length4
Median length4
Mean length3.7965144
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> 1979
93.2%
0 144
 
6.8%

Length

2024-04-17T07:10:44.236645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:44.312880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1979
93.2%
0 144
 
6.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1979 
0
 
144

Length

Max length4
Median length4
Mean length3.7965144
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> 1979
93.2%
0 144
 
6.8%

Length

2024-04-17T07:10:44.392615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:44.493391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1979
93.2%
0 144
 
6.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1413 
상수도전용
709 
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.3344324
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1413
66.6%
상수도전용 709
33.4%
지하수전용 1
 
< 0.1%

Length

2024-04-17T07:10:44.572129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:44.653312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1413
66.6%
상수도전용 709
33.4%
지하수전용 1
 
< 0.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1987 
0
 
136

Length

Max length4
Median length4
Mean length3.8078191
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> 1987
93.6%
0 136
 
6.4%

Length

2024-04-17T07:10:44.736833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:44.828806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1987
93.6%
0 136
 
6.4%

본사종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
1467 
<NA>
601 
1
 
45
2
 
6
3
 
3

Length

Max length4
Median length1
Mean length1.8492699
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1467
69.1%
<NA> 601
28.3%
1 45
 
2.1%
2 6
 
0.3%
3 3
 
0.1%
6 1
 
< 0.1%

Length

2024-04-17T07:10:44.937531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:45.035354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1467
69.1%
na 601
28.3%
1 45
 
2.1%
2 6
 
0.3%
3 3
 
0.1%
6 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
1498 
<NA>
601 
1
 
22
2
 
1
13
 
1

Length

Max length4
Median length1
Mean length1.8497409
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1498
70.6%
<NA> 601
28.3%
1 22
 
1.0%
2 1
 
< 0.1%
13 1
 
< 0.1%

Length

2024-04-17T07:10:45.129853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:45.222729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1498
70.6%
na 601
28.3%
1 22
 
1.0%
2 1
 
< 0.1%
13 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
1360 
<NA>
602 
1
141 
2
 
15
3
 
4

Length

Max length4
Median length1
Mean length1.850683
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1360
64.1%
<NA> 602
28.4%
1 141
 
6.6%
2 15
 
0.7%
3 4
 
0.2%
4 1
 
< 0.1%

Length

2024-04-17T07:10:45.315094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:45.406797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1360
64.1%
na 602
28.4%
1 141
 
6.6%
2 15
 
0.7%
3 4
 
0.2%
4 1
 
< 0.1%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.4%
Missing600
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean0.18778726
Minimum0
Maximum5
Zeros1321
Zeros (%)62.2%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:45.488688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.53907306
Coefficient of variation (CV)2.8706583
Kurtosis13.63177
Mean0.18778726
Median Absolute Deviation (MAD)0
Skewness3.413239
Sum286
Variance0.29059977
MonotonicityNot monotonic
2024-04-17T07:10:45.566722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1321
62.2%
1 135
 
6.4%
2 53
 
2.5%
3 12
 
0.6%
5 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 600
28.3%
ValueCountFrequency (%)
0 1321
62.2%
1 135
 
6.4%
2 53
 
2.5%
3 12
 
0.6%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 1
 
< 0.1%
3 12
 
0.6%
2 53
 
2.5%
1 135
 
6.4%
0 1321
62.2%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1378 
임대
417 
자가
328 

Length

Max length4
Median length4
Mean length3.298163
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1378
64.9%
임대 417
 
19.6%
자가 328
 
15.4%

Length

2024-04-17T07:10:45.706802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:45.823619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1378
64.9%
임대 417
 
19.6%
자가 328
 
15.4%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1958 
0
 
165

Length

Max length4
Median length4
Mean length3.7668394
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> 1958
92.2%
0 165
 
7.8%

Length

2024-04-17T07:10:45.910368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:45.990117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1958
92.2%
0 165
 
7.8%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
1956 
0
 
165
1000000
 
1
1200000
 
1

Length

Max length7
Median length4
Mean length3.7696656
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> 1956
92.1%
0 165
 
7.8%
1000000 1
 
< 0.1%
1200000 1
 
< 0.1%

Length

2024-04-17T07:10:46.072894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:46.155495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1956
92.1%
0 165
 
7.8%
1000000 1
 
< 0.1%
1200000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
False
2123 
ValueCountFrequency (%)
False 2123
100.0%
2024-04-17T07:10:46.235130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct74
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83421573
Minimum0
Maximum150.72
Zeros2040
Zeros (%)96.1%
Negative0
Negative (%)0.0%
Memory size18.8 KiB
2024-04-17T07:10:46.316272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum150.72
Range150.72
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.01303
Coefficient of variation (CV)8.4067343
Kurtosis222.81498
Mean0.83421573
Median Absolute Deviation (MAD)0
Skewness13.658264
Sum1771.04
Variance49.18259
MonotonicityNot monotonic
2024-04-17T07:10:46.417904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2040
96.1%
3.0 3
 
0.1%
3.3 3
 
0.1%
10.0 3
 
0.1%
3.8 2
 
0.1%
9.9 2
 
0.1%
6.0 2
 
0.1%
2.0 2
 
0.1%
76.57 1
 
< 0.1%
5.07 1
 
< 0.1%
Other values (64) 64
 
3.0%
ValueCountFrequency (%)
0.0 2040
96.1%
2.0 2
 
0.1%
2.02 1
 
< 0.1%
2.18 1
 
< 0.1%
2.53 1
 
< 0.1%
2.56 1
 
< 0.1%
2.7 1
 
< 0.1%
3.0 3
 
0.1%
3.3 3
 
0.1%
3.36 1
 
< 0.1%
ValueCountFrequency (%)
150.72 1
< 0.1%
122.56 1
< 0.1%
117.86 1
< 0.1%
104.92 1
< 0.1%
76.57 1
< 0.1%
72.46 1
< 0.1%
70.0 1
< 0.1%
66.0 1
< 0.1%
56.16 1
< 0.1%
53.22 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2123
Missing (%)100.0%
Memory size18.8 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
<NA>
2122 
53
 
1

Length

Max length4
Median length4
Mean length3.9990579
Min length2

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> 2122
> 99.9%
53 1
 
< 0.1%

Length

2024-04-17T07:10:46.551359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T07:10:46.657077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2122
> 99.9%
53 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품소분업07_22_08_P34100003410000-109-2008-0001120080923<NA>3폐업2폐업20090821<NA><NA><NA><NA>4.00700092대구광역시 중구 동성로2가 0174<NA><NA>남경식품20090107110549I2018-08-31 23:59:59.0식품소분업344066.98467264414.299416식품소분업<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
12식품소분업07_22_08_P34100003410000-109-2005-0000320050127<NA>3폐업2폐업20060609<NA><NA><NA><NA>126.15700826대구광역시 중구 남산동 2109-0001<NA><NA>한국물산20050127000000I2018-08-31 23:59:59.0식품소분업343639.465001263175.906103식품소분업<NA><NA><NA><NA><NA><NA>0002<NA><NA><NA>N0.0<NA><NA><NA>
23식품소분업07_22_08_P34100003410000-109-2005-0000420050225<NA>3폐업2폐업20050630<NA><NA><NA><NA>3.50700811대구광역시 중구 대봉동 0214<NA><NA>더네이쳐샵20050225000000I2018-08-31 23:59:59.0식품소분업345032.238221262949.871621식품소분업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
34식품소분업07_22_08_P34100003410000-109-2005-0000520050302<NA>3폐업2폐업20050315<NA><NA><NA><NA><NA>700180대구광역시 중구 동문동 0020-0004<NA><NA>전남생연20050302000000I2018-08-31 23:59:59.0식품소분업344148.352033264812.35373식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
45식품소분업07_22_08_P34100003410000-109-2005-0000620050303<NA>3폐업2폐업20070306<NA><NA><NA><NA>8.17700718대구광역시 중구 대봉동 0214 대백프라자<NA><NA>스위트존20050303000000I2018-08-31 23:59:59.0식품소분업345032.238221262949.871621식품소분업<NA><NA><NA><NA>상수도전용<NA>0001임대<NA><NA>N0.0<NA><NA><NA>
56식품소분업07_22_08_P34100003410000-109-2005-0000720050311<NA>3폐업2폐업20051027<NA><NA><NA><NA>1.61700180대구광역시 중구 동문동 0020-0011<NA><NA>동아백화점B1식품관20050311000000I2018-08-31 23:59:59.0식품소분업344138.507492264773.346334식품소분업<NA><NA><NA><NA>상수도전용<NA>0010임대<NA><NA>N0.0<NA><NA><NA>
67식품소분업07_22_08_P34100003410000-109-2005-0000820050315<NA>3폐업2폐업20050330<NA><NA><NA><NA><NA>700070대구광역시 중구 덕산동 0053-0003<NA><NA>전남생연20050315000000I2018-08-31 23:59:59.0식품소분업343705.561002264056.630949식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
78식품소분업07_22_08_P34100003410000-109-2011-0000420110825<NA>3폐업2폐업20110902<NA><NA><NA><NA><NA>700082대구광역시 중구 계산동2가 0200 외1필지 현대백화점 지하1층<NA><NA>(주)포항수산20110825120344I2018-08-31 23:59:59.0식품소분업343588.735555264119.01075식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
89식품소분업07_22_08_P34100003410000-109-2011-0000520110928<NA>3폐업2폐업20151231<NA><NA><NA>053 426135526.40700413대구광역시 중구 삼덕동3가 0258-0002 지상2층대구광역시 중구 달구벌대로443길 40 (삼덕동3가)41948천사로즈20120131153416I2018-08-31 23:59:59.0식품소분업344952.173512263909.065764식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
910식품소분업07_22_08_P34100003410000-109-2011-0000620110930<NA>3폐업2폐업20111010<NA><NA><NA><NA><NA>700092대구광역시 중구 동성로2가 0166-0001 지하1층<NA><NA>월드20110930173929I2018-08-31 23:59:59.0식품소분업344047.979265264405.128696식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
21132114식품소분업07_22_08_P34800003480000-109-2015-0000820150122<NA>1영업/정상1영업<NA><NA><NA><NA>053525 96339.30711892대구광역시 달성군 구지면 내리 851 1동 1층대구광역시 달성군 구지면 달성2차2로 6, 1동 1층43013(주)코레쉬텍20210507100902U2021-05-09 02:40:00.0식품소분업328213.561416237999.437164식품소분업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
21142115식품소분업07_22_08_P34800003480000-109-2020-0000920201228<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.36711831대구광역시 달성군 화원읍 구라리 973-3 1층대구광역시 달성군 화원읍 구라1길 27, 1층42942바다누리20210105122640U2021-01-07 02:40:00.0식품소분업334669.02493258079.96864식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
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