Overview

Dataset statistics

Number of variables47
Number of observations3776
Missing cells44388
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory406.0 B

Variable types

Numeric16
Categorical15
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description22년07월_6270000_대구광역시_07_22_11_P_식품제조가공업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094050&dataSetDetailId=DDI_0000094063&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
급수시설구분명 is highly imbalanced (55.8%)Imbalance
다중이용업소여부 is highly imbalanced (99.3%)Imbalance
홈페이지 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3776 (100.0%) missing valuesMissing
폐업일자 has 1030 (27.3%) missing valuesMissing
휴업시작일자 has 3776 (100.0%) missing valuesMissing
휴업종료일자 has 3776 (100.0%) missing valuesMissing
재개업일자 has 3776 (100.0%) missing valuesMissing
소재지전화 has 1056 (28.0%) missing valuesMissing
소재지면적 has 136 (3.6%) missing valuesMissing
소재지우편번호 has 82 (2.2%) missing valuesMissing
도로명전체주소 has 1370 (36.3%) missing valuesMissing
도로명우편번호 has 1398 (37.0%) missing valuesMissing
좌표정보(X) has 172 (4.6%) missing valuesMissing
좌표정보(Y) has 172 (4.6%) missing valuesMissing
영업장주변구분명 has 3776 (100.0%) missing valuesMissing
등급구분명 has 3776 (100.0%) missing valuesMissing
본사직원수 has 625 (16.6%) missing valuesMissing
공장사무직직원수 has 615 (16.3%) missing valuesMissing
공장판매직직원수 has 635 (16.8%) missing valuesMissing
공장생산직직원수 has 544 (14.4%) missing valuesMissing
보증액 has 3159 (83.7%) missing valuesMissing
월세액 has 3160 (83.7%) missing valuesMissing
전통업소지정번호 has 3776 (100.0%) missing valuesMissing
전통업소주된음식 has 3776 (100.0%) missing valuesMissing
공장사무직직원수 is highly skewed (γ1 = 22.25606666)Skewed
공장판매직직원수 is highly skewed (γ1 = 28.74015369)Skewed
공장생산직직원수 is highly skewed (γ1 = 34.64917244)Skewed
시설총규모 is highly skewed (γ1 = 28.77468733)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
본사직원수 has 3028 (80.2%) zerosZeros
공장사무직직원수 has 2765 (73.2%) zerosZeros
공장판매직직원수 has 2925 (77.5%) zerosZeros
공장생산직직원수 has 2309 (61.1%) zerosZeros
보증액 has 553 (14.6%) zerosZeros
월세액 has 552 (14.6%) zerosZeros
시설총규모 has 2994 (79.3%) zerosZeros

Reproduction

Analysis started2024-04-17 10:16:26.426215
Analysis finished2024-04-17 10:16:27.603035
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3776
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1888.5
Minimum1
Maximum3776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:27.656512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile189.75
Q1944.75
median1888.5
Q32832.25
95-th percentile3587.25
Maximum3776
Range3775
Interquartile range (IQR)1887.5

Descriptive statistics

Standard deviation1090.1816
Coefficient of variation (CV)0.57727383
Kurtosis-1.2
Mean1888.5
Median Absolute Deviation (MAD)944
Skewness0
Sum7130976
Variance1188496
MonotonicityStrictly increasing
2024-04-17T19:16:27.771236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2524 1
 
< 0.1%
2512 1
 
< 0.1%
2513 1
 
< 0.1%
2514 1
 
< 0.1%
2515 1
 
< 0.1%
2516 1
 
< 0.1%
2517 1
 
< 0.1%
2518 1
 
< 0.1%
2519 1
 
< 0.1%
Other values (3766) 3766
99.7%
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 (%)
3776 1
< 0.1%
3775 1
< 0.1%
3774 1
< 0.1%
3773 1
< 0.1%
3772 1
< 0.1%
3771 1
< 0.1%
3770 1
< 0.1%
3769 1
< 0.1%
3768 1
< 0.1%
3767 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
식품제조가공업
3776 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 3776
100.0%

Length

2024-04-17T19:16:27.882775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:27.959569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3776
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
07_22_11_P
3776 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_11_P
2nd row07_22_11_P
3rd row07_22_11_P
4th row07_22_11_P
5th row07_22_11_P

Common Values

ValueCountFrequency (%)
07_22_11_P 3776
100.0%

Length

2024-04-17T19:16:28.045521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:28.119508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_11_p 3776
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3449857
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:28.186082image/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 deviation20916.249
Coefficient of variation (CV)0.0060629322
Kurtosis-0.96056578
Mean3449857
Median Absolute Deviation (MAD)20000
Skewness-0.2995897
Sum1.302666 × 1010
Variance4.3748948 × 108
MonotonicityIncreasing
2024-04-17T19:16:28.427886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 952
25.2%
3470000 647
17.1%
3480000 471
12.5%
3420000 441
11.7%
3460000 433
11.5%
3430000 370
 
9.8%
3440000 239
 
6.3%
3410000 223
 
5.9%
ValueCountFrequency (%)
3410000 223
 
5.9%
3420000 441
11.7%
3430000 370
 
9.8%
3440000 239
 
6.3%
3450000 952
25.2%
3460000 433
11.5%
3470000 647
17.1%
3480000 471
12.5%
ValueCountFrequency (%)
3480000 471
12.5%
3470000 647
17.1%
3460000 433
11.5%
3450000 952
25.2%
3440000 239
 
6.3%
3430000 370
 
9.8%
3420000 441
11.7%
3410000 223
 
5.9%

관리번호
Text

UNIQUE 

Distinct3776
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
2024-04-17T19:16:28.584696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters83072
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

Unique3776 ?
Unique (%)100.0%

Sample

1st row3410000-106-2004-00002
2nd row3410000-106-2004-00003
3rd row3410000-106-2004-00004
4th row3410000-106-2004-00005
5th row3410000-106-2004-00006
ValueCountFrequency (%)
3410000-106-2004-00002 1
 
< 0.1%
3460000-106-2007-00019 1
 
< 0.1%
3460000-106-2013-00010 1
 
< 0.1%
3460000-106-2011-00003 1
 
< 0.1%
3460000-106-2011-00004 1
 
< 0.1%
3460000-106-2011-00005 1
 
< 0.1%
3460000-106-2011-00006 1
 
< 0.1%
3460000-106-2010-00007 1
 
< 0.1%
3460000-106-2010-00014 1
 
< 0.1%
3460000-106-2010-00015 1
 
< 0.1%
Other values (3766) 3766
99.7%
2024-04-17T19:16:28.846578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37868
45.6%
- 11328
 
13.6%
1 7962
 
9.6%
2 5602
 
6.7%
3 5138
 
6.2%
6 4950
 
6.0%
4 4839
 
5.8%
5 1701
 
2.0%
7 1362
 
1.6%
9 1175
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71744
86.4%
Dash Punctuation 11328
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37868
52.8%
1 7962
 
11.1%
2 5602
 
7.8%
3 5138
 
7.2%
6 4950
 
6.9%
4 4839
 
6.7%
5 1701
 
2.4%
7 1362
 
1.9%
9 1175
 
1.6%
8 1147
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 11328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37868
45.6%
- 11328
 
13.6%
1 7962
 
9.6%
2 5602
 
6.7%
3 5138
 
6.2%
6 4950
 
6.0%
4 4839
 
5.8%
5 1701
 
2.0%
7 1362
 
1.6%
9 1175
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37868
45.6%
- 11328
 
13.6%
1 7962
 
9.6%
2 5602
 
6.7%
3 5138
 
6.2%
6 4950
 
6.0%
4 4839
 
5.8%
5 1701
 
2.0%
7 1362
 
1.6%
9 1175
 
1.4%

인허가일자
Real number (ℝ)

Distinct2682
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20089201
Minimum19681218
Maximum20220725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:28.967051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19681218
5-th percentile19980382
Q120031030
median20091026
Q320150316
95-th percentile20200831
Maximum20220725
Range539507
Interquartile range (IQR)119287

Descriptive statistics

Standard deviation75095.081
Coefficient of variation (CV)0.0037380819
Kurtosis1.4043096
Mean20089201
Median Absolute Deviation (MAD)59584
Skewness-0.62152041
Sum7.5856825 × 1010
Variance5.6392712 × 109
MonotonicityNot monotonic
2024-04-17T19:16:29.084099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000302 28
 
0.7%
19960320 19
 
0.5%
19960516 7
 
0.2%
19930320 6
 
0.2%
20110520 6
 
0.2%
20130725 5
 
0.1%
20180706 5
 
0.1%
20160523 5
 
0.1%
20071108 5
 
0.1%
20160822 4
 
0.1%
Other values (2672) 3686
97.6%
ValueCountFrequency (%)
19681218 1
< 0.1%
19700224 1
< 0.1%
19710528 1
< 0.1%
19720522 1
< 0.1%
19720817 1
< 0.1%
19730502 1
< 0.1%
19740326 1
< 0.1%
19740803 1
< 0.1%
19741016 1
< 0.1%
19741220 1
< 0.1%
ValueCountFrequency (%)
20220725 1
< 0.1%
20220721 1
< 0.1%
20220715 1
< 0.1%
20220714 1
< 0.1%
20220708 1
< 0.1%
20220706 1
< 0.1%
20220704 2
0.1%
20220627 1
< 0.1%
20220620 2
0.1%
20220616 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
3
2746 
1
1030 

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 2746
72.7%
1 1030
 
27.3%

Length

2024-04-17T19:16:29.185913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:29.267933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2746
72.7%
1 1030
 
27.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
폐업
2746 
영업/정상
1030 

Length

Max length5
Median length2
Mean length2.8183263
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2746
72.7%
영업/정상 1030
 
27.3%

Length

2024-04-17T19:16:29.366843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:29.450623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2746
72.7%
영업/정상 1030
 
27.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
2
2746 
1
1030 

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 2746
72.7%
1 1030
 
27.3%

Length

2024-04-17T19:16:29.533911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:29.617342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2746
72.7%
1 1030
 
27.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
폐업
2746 
영업
1030 

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 2746
72.7%
영업 1030
 
27.3%

Length

2024-04-17T19:16:29.698863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:29.777669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2746
72.7%
영업 1030
 
27.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct2037
Distinct (%)74.2%
Missing1030
Missing (%)27.3%
Infinite0
Infinite (%)0.0%
Mean20117372
Minimum20000424
Maximum20220729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:29.872393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000424
5-th percentile20030306
Q120070102
median20120424
Q320170303
95-th percentile20210514
Maximum20220729
Range220305
Interquartile range (IQR)100200.5

Descriptive statistics

Standard deviation58470.692
Coefficient of variation (CV)0.0029064777
Kurtosis-1.1867134
Mean20117372
Median Absolute Deviation (MAD)50099
Skewness-0.013492469
Sum5.5242303 × 1010
Variance3.4188219 × 109
MonotonicityNot monotonic
2024-04-17T19:16:29.987980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20181226 6
 
0.2%
20101231 6
 
0.2%
20030711 5
 
0.1%
20181127 5
 
0.1%
20110607 4
 
0.1%
20180223 4
 
0.1%
20201229 4
 
0.1%
20161229 4
 
0.1%
20160114 4
 
0.1%
20140120 4
 
0.1%
Other values (2027) 2700
71.5%
(Missing) 1030
 
27.3%
ValueCountFrequency (%)
20000424 1
< 0.1%
20000512 1
< 0.1%
20000621 1
< 0.1%
20000905 1
< 0.1%
20000928 2
0.1%
20001106 1
< 0.1%
20001121 1
< 0.1%
20001217 1
< 0.1%
20010129 1
< 0.1%
20010212 1
< 0.1%
ValueCountFrequency (%)
20220729 1
< 0.1%
20220725 1
< 0.1%
20220721 1
< 0.1%
20220715 1
< 0.1%
20220713 1
< 0.1%
20220711 1
< 0.1%
20220706 1
< 0.1%
20220705 1
< 0.1%
20220629 1
< 0.1%
20220628 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

소재지전화
Text

MISSING 

Distinct2520
Distinct (%)92.6%
Missing1056
Missing (%)28.0%
Memory size29.6 KiB
2024-04-17T19:16:30.262971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.848529
Min length3

Characters and Unicode

Total characters29508
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

Unique2331 ?
Unique (%)85.7%

Sample

1st row053 4244979
2nd row053 2564337
3rd row053 4240540
4th row053 4223318
5th row053 4294238
ValueCountFrequency (%)
053 2004
34.9%
070 69
 
1.2%
311 21
 
0.4%
313 15
 
0.3%
314 13
 
0.2%
983 13
 
0.2%
621 13
 
0.2%
767 12
 
0.2%
611 12
 
0.2%
615 11
 
0.2%
Other values (2676) 3559
62.0%
2024-04-17T19:16:30.632742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4874
16.5%
3 4308
14.6%
0 4224
14.3%
3103
10.5%
2 2109
7.1%
6 2082
7.1%
1 2042
6.9%
7 1874
 
6.4%
8 1774
 
6.0%
4 1634
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26405
89.5%
Space Separator 3103
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4874
18.5%
3 4308
16.3%
0 4224
16.0%
2 2109
8.0%
6 2082
7.9%
1 2042
7.7%
7 1874
 
7.1%
8 1774
 
6.7%
4 1634
 
6.2%
9 1484
 
5.6%
Space Separator
ValueCountFrequency (%)
3103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29508
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4874
16.5%
3 4308
14.6%
0 4224
14.3%
3103
10.5%
2 2109
7.1%
6 2082
7.1%
1 2042
6.9%
7 1874
 
6.4%
8 1774
 
6.0%
4 1634
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4874
16.5%
3 4308
14.6%
0 4224
14.3%
3103
10.5%
2 2109
7.1%
6 2082
7.1%
1 2042
6.9%
7 1874
 
6.4%
8 1774
 
6.0%
4 1634
 
5.5%

소재지면적
Text

MISSING 

Distinct2631
Distinct (%)72.3%
Missing136
Missing (%)3.6%
Memory size29.6 KiB
2024-04-17T19:16:30.951807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3777473
Min length3

Characters and Unicode

Total characters19575
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

Unique2147 ?
Unique (%)59.0%

Sample

1st row14.70
2nd row41.85
3rd row120.60
4th row34.52
5th row25.23
ValueCountFrequency (%)
66.00 30
 
0.8%
33.00 25
 
0.7%
20.00 25
 
0.7%
00 17
 
0.5%
40.00 17
 
0.5%
26.40 14
 
0.4%
30.00 14
 
0.4%
132.00 12
 
0.3%
38.00 12
 
0.3%
15.00 12
 
0.3%
Other values (2621) 3462
95.1%
2024-04-17T19:16:31.366735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3640
18.6%
0 3388
17.3%
1 1790
9.1%
2 1732
8.8%
3 1440
 
7.4%
4 1436
 
7.3%
5 1378
 
7.0%
6 1359
 
6.9%
8 1180
 
6.0%
7 1109
 
5.7%
Other values (2) 1123
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15863
81.0%
Other Punctuation 3712
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3388
21.4%
1 1790
11.3%
2 1732
10.9%
3 1440
9.1%
4 1436
9.1%
5 1378
8.7%
6 1359
8.6%
8 1180
 
7.4%
7 1109
 
7.0%
9 1051
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 3640
98.1%
, 72
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 19575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3640
18.6%
0 3388
17.3%
1 1790
9.1%
2 1732
8.8%
3 1440
 
7.4%
4 1436
 
7.3%
5 1378
 
7.0%
6 1359
 
6.9%
8 1180
 
6.0%
7 1109
 
5.7%
Other values (2) 1123
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3640
18.6%
0 3388
17.3%
1 1790
9.1%
2 1732
8.8%
3 1440
 
7.4%
4 1436
 
7.3%
5 1378
 
7.0%
6 1359
 
6.9%
8 1180
 
6.0%
7 1109
 
5.7%
Other values (2) 1123
 
5.7%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct551
Distinct (%)14.9%
Missing82
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean704582.82
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:31.497299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700836.65
Q1702805
median703833
Q3705823
95-th percentile711850
Maximum711893
Range11883
Interquartile range (IQR)3018

Descriptive statistics

Standard deviation3086.2712
Coefficient of variation (CV)0.0043802816
Kurtosis0.77138008
Mean704582.82
Median Absolute Deviation (MAD)1761
Skewness1.1842134
Sum2.6027289 × 109
Variance9525069.7
MonotonicityNot monotonic
2024-04-17T19:16:31.611999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702825 90
 
2.4%
702061 80
 
2.1%
703830 57
 
1.5%
703833 48
 
1.3%
702816 46
 
1.2%
704080 43
 
1.1%
704900 36
 
1.0%
702903 36
 
1.0%
701140 34
 
0.9%
711851 34
 
0.9%
Other values (541) 3190
84.5%
(Missing) 82
 
2.2%
ValueCountFrequency (%)
700010 2
 
0.1%
700020 1
 
< 0.1%
700030 1
 
< 0.1%
700040 1
 
< 0.1%
700050 3
0.1%
700060 1
 
< 0.1%
700070 1
 
< 0.1%
700082 3
0.1%
700091 1
 
< 0.1%
700092 6
0.2%
ValueCountFrequency (%)
711893 8
 
0.2%
711892 9
0.2%
711891 9
0.2%
711874 3
 
0.1%
711871 9
0.2%
711864 12
0.3%
711863 21
0.6%
711862 3
 
0.1%
711861 2
 
0.1%
711858 11
0.3%
Distinct3512
Distinct (%)93.7%
Missing26
Missing (%)0.7%
Memory size29.6 KiB
2024-04-17T19:16:31.912479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length49
Mean length23.862133
Min length15

Characters and Unicode

Total characters89483
Distinct characters297
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

Unique3307 ?
Unique (%)88.2%

Sample

1st row대구광역시 중구 태평로1가 0001-0186번지
2nd row대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호
3rd row대구광역시 중구 봉산동 0165-0007번지
4th row대구광역시 중구 동인동3가 0302-0002번지
5th row대구광역시 중구 동인동1가 0196번지
ValueCountFrequency (%)
대구광역시 3750
22.3%
북구 945
 
5.6%
달서구 644
 
3.8%
달성군 467
 
2.8%
동구 441
 
2.6%
수성구 421
 
2.5%
서구 371
 
2.2%
남구 239
 
1.4%
중구 223
 
1.3%
지상1층 201
 
1.2%
Other values (3901) 9134
54.3%
2024-04-17T19:16:32.375204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16798
18.8%
7137
 
8.0%
1 4445
 
5.0%
4079
 
4.6%
3998
 
4.5%
3805
 
4.3%
3755
 
4.2%
3755
 
4.2%
3512
 
3.9%
- 3126
 
3.5%
Other values (287) 35073
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49991
55.9%
Decimal Number 18615
 
20.8%
Space Separator 16798
 
18.8%
Dash Punctuation 3126
 
3.5%
Open Punctuation 347
 
0.4%
Close Punctuation 347
 
0.4%
Other Punctuation 126
 
0.1%
Uppercase Letter 117
 
0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7137
14.3%
4079
 
8.2%
3998
 
8.0%
3805
 
7.6%
3755
 
7.5%
3755
 
7.5%
3512
 
7.0%
2998
 
6.0%
1188
 
2.4%
1179
 
2.4%
Other values (258) 14585
29.2%
Decimal Number
ValueCountFrequency (%)
1 4445
23.9%
2 2341
12.6%
0 2047
11.0%
3 1914
10.3%
4 1560
 
8.4%
5 1443
 
7.8%
6 1352
 
7.3%
7 1257
 
6.8%
8 1151
 
6.2%
9 1105
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 52
44.4%
A 49
41.9%
C 8
 
6.8%
T 2
 
1.7%
D 2
 
1.7%
E 2
 
1.7%
P 1
 
0.9%
J 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 116
92.1%
. 7
 
5.6%
/ 2
 
1.6%
: 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
16798
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 347
100.0%
Close Punctuation
ValueCountFrequency (%)
) 347
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49991
55.9%
Common 39372
44.0%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7137
14.3%
4079
 
8.2%
3998
 
8.0%
3805
 
7.6%
3755
 
7.5%
3755
 
7.5%
3512
 
7.0%
2998
 
6.0%
1188
 
2.4%
1179
 
2.4%
Other values (258) 14585
29.2%
Common
ValueCountFrequency (%)
16798
42.7%
1 4445
 
11.3%
- 3126
 
7.9%
2 2341
 
5.9%
0 2047
 
5.2%
3 1914
 
4.9%
4 1560
 
4.0%
5 1443
 
3.7%
6 1352
 
3.4%
7 1257
 
3.2%
Other values (9) 3089
 
7.8%
Latin
ValueCountFrequency (%)
B 52
43.3%
A 49
40.8%
C 8
 
6.7%
e 2
 
1.7%
T 2
 
1.7%
D 2
 
1.7%
E 2
 
1.7%
P 1
 
0.8%
J 1
 
0.8%
c 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49991
55.9%
ASCII 39492
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16798
42.5%
1 4445
 
11.3%
- 3126
 
7.9%
2 2341
 
5.9%
0 2047
 
5.2%
3 1914
 
4.8%
4 1560
 
4.0%
5 1443
 
3.7%
6 1352
 
3.4%
7 1257
 
3.2%
Other values (19) 3209
 
8.1%
Hangul
ValueCountFrequency (%)
7137
14.3%
4079
 
8.2%
3998
 
8.0%
3805
 
7.6%
3755
 
7.5%
3755
 
7.5%
3512
 
7.0%
2998
 
6.0%
1188
 
2.4%
1179
 
2.4%
Other values (258) 14585
29.2%

도로명전체주소
Text

MISSING 

Distinct2296
Distinct (%)95.4%
Missing1370
Missing (%)36.3%
Memory size29.6 KiB
2024-04-17T19:16:32.676998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length27.791355
Min length20

Characters and Unicode

Total characters66866
Distinct characters321
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

Unique2196 ?
Unique (%)91.3%

Sample

1st row대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)
2nd row대구광역시 중구 동덕로30길 139-24, 1층 (동인동4가)
3rd row대구광역시 중구 서성로14길 85 (대안동, 지상2층)
4th row대구광역시 중구 남산로 23-15, 1층 (남산동)
5th row대구광역시 중구 달성공원로6길 8, 지상 1층 (대신동)
ValueCountFrequency (%)
대구광역시 2406
 
17.9%
북구 615
 
4.6%
1층 555
 
4.1%
달서구 354
 
2.6%
달성군 313
 
2.3%
동구 300
 
2.2%
수성구 281
 
2.1%
서구 236
 
1.8%
남구 156
 
1.2%
중구 152
 
1.1%
Other values (2624) 8088
60.1%
2024-04-17T19:16:33.084843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11051
 
16.5%
4732
 
7.1%
1 2988
 
4.5%
2909
 
4.4%
2908
 
4.3%
2507
 
3.7%
2426
 
3.6%
2407
 
3.6%
) 2212
 
3.3%
( 2212
 
3.3%
Other values (311) 30514
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38291
57.3%
Space Separator 11051
 
16.5%
Decimal Number 10853
 
16.2%
Close Punctuation 2212
 
3.3%
Open Punctuation 2212
 
3.3%
Other Punctuation 1318
 
2.0%
Dash Punctuation 761
 
1.1%
Uppercase Letter 143
 
0.2%
Math Symbol 23
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4732
 
12.4%
2909
 
7.6%
2908
 
7.6%
2507
 
6.5%
2426
 
6.3%
2407
 
6.3%
2202
 
5.8%
1679
 
4.4%
1020
 
2.7%
996
 
2.6%
Other values (279) 14505
37.9%
Uppercase Letter
ValueCountFrequency (%)
B 61
42.7%
A 53
37.1%
C 11
 
7.7%
T 4
 
2.8%
D 3
 
2.1%
E 3
 
2.1%
P 2
 
1.4%
J 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (2) 2
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 2988
27.5%
2 1622
14.9%
3 1276
11.8%
4 919
 
8.5%
5 866
 
8.0%
6 772
 
7.1%
0 692
 
6.4%
7 665
 
6.1%
8 570
 
5.3%
9 483
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 1310
99.4%
. 4
 
0.3%
· 4
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
11051
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 761
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38291
57.3%
Common 28430
42.5%
Latin 145
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4732
 
12.4%
2909
 
7.6%
2908
 
7.6%
2507
 
6.5%
2426
 
6.3%
2407
 
6.3%
2202
 
5.8%
1679
 
4.4%
1020
 
2.7%
996
 
2.6%
Other values (279) 14505
37.9%
Common
ValueCountFrequency (%)
11051
38.9%
1 2988
 
10.5%
) 2212
 
7.8%
( 2212
 
7.8%
2 1622
 
5.7%
, 1310
 
4.6%
3 1276
 
4.5%
4 919
 
3.2%
5 866
 
3.0%
6 772
 
2.7%
Other values (8) 3202
 
11.3%
Latin
ValueCountFrequency (%)
B 61
42.1%
A 53
36.6%
C 11
 
7.6%
T 4
 
2.8%
D 3
 
2.1%
E 3
 
2.1%
P 2
 
1.4%
J 2
 
1.4%
G 1
 
0.7%
M 1
 
0.7%
Other values (4) 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38291
57.3%
ASCII 28571
42.7%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11051
38.7%
1 2988
 
10.5%
) 2212
 
7.7%
( 2212
 
7.7%
2 1622
 
5.7%
, 1310
 
4.6%
3 1276
 
4.5%
4 919
 
3.2%
5 866
 
3.0%
6 772
 
2.7%
Other values (21) 3343
 
11.7%
Hangul
ValueCountFrequency (%)
4732
 
12.4%
2909
 
7.6%
2908
 
7.6%
2507
 
6.5%
2426
 
6.3%
2407
 
6.3%
2202
 
5.8%
1679
 
4.4%
1020
 
2.7%
996
 
2.6%
Other values (279) 14505
37.9%
None
ValueCountFrequency (%)
· 4
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct817
Distinct (%)34.4%
Missing1398
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean42013.256
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:33.204318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41108.85
Q141489
median41929
Q342662
95-th percentile42972
Maximum43024
Range2024
Interquartile range (IQR)1173

Descriptive statistics

Standard deviation617.05937
Coefficient of variation (CV)0.014687254
Kurtosis-1.2976836
Mean42013.256
Median Absolute Deviation (MAD)488
Skewness0.17211041
Sum99907522
Variance380762.27
MonotonicityNot monotonic
2024-04-17T19:16:33.322086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41485 45
 
1.2%
41582 40
 
1.1%
41490 37
 
1.0%
41557 25
 
0.7%
41488 23
 
0.6%
41755 19
 
0.5%
42970 18
 
0.5%
42703 18
 
0.5%
42975 18
 
0.5%
41123 16
 
0.4%
Other values (807) 2119
56.1%
(Missing) 1398
37.0%
ValueCountFrequency (%)
41000 8
0.2%
41001 3
 
0.1%
41002 4
0.1%
41005 1
 
< 0.1%
41007 4
0.1%
41008 2
 
0.1%
41009 4
0.1%
41015 1
 
< 0.1%
41016 1
 
< 0.1%
41017 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43023 5
0.1%
43022 1
 
< 0.1%
43013 2
 
0.1%
43012 1
 
< 0.1%
43011 6
0.2%
43009 1
 
< 0.1%
43008 2
 
0.1%
43007 1
 
< 0.1%
43006 4
0.1%
Distinct3189
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
2024-04-17T19:16:33.554885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length5.9004237
Min length1

Characters and Unicode

Total characters22280
Distinct characters765
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2776 ?
Unique (%)73.5%

Sample

1st row동북상회
2nd row황실떡집
3rd row에프엔에스
4th row이유통
5th row불스푸드
ValueCountFrequency (%)
주식회사 97
 
2.3%
농업회사법인 15
 
0.4%
우리식품 14
 
0.3%
14
 
0.3%
커피 14
 
0.3%
푸드 12
 
0.3%
coffee 11
 
0.3%
제일식품 11
 
0.3%
food 9
 
0.2%
현대식품 9
 
0.2%
Other values (3371) 4024
95.1%
2024-04-17T19:16:33.910949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1249
 
5.6%
1092
 
4.9%
637
 
2.9%
) 602
 
2.7%
( 594
 
2.7%
472
 
2.1%
456
 
2.0%
443
 
2.0%
409
 
1.8%
360
 
1.6%
Other values (755) 15966
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19586
87.9%
Close Punctuation 602
 
2.7%
Open Punctuation 594
 
2.7%
Uppercase Letter 486
 
2.2%
Space Separator 456
 
2.0%
Lowercase Letter 433
 
1.9%
Decimal Number 61
 
0.3%
Other Punctuation 59
 
0.3%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1249
 
6.4%
1092
 
5.6%
637
 
3.3%
472
 
2.4%
443
 
2.3%
409
 
2.1%
360
 
1.8%
325
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (688) 13995
71.5%
Uppercase Letter
ValueCountFrequency (%)
F 48
 
9.9%
O 43
 
8.8%
C 38
 
7.8%
S 36
 
7.4%
B 35
 
7.2%
N 26
 
5.3%
T 25
 
5.1%
D 25
 
5.1%
M 24
 
4.9%
E 21
 
4.3%
Other values (14) 165
34.0%
Lowercase Letter
ValueCountFrequency (%)
e 80
18.5%
o 62
14.3%
f 36
8.3%
n 34
 
7.9%
a 31
 
7.2%
s 23
 
5.3%
c 23
 
5.3%
r 22
 
5.1%
t 18
 
4.2%
d 15
 
3.5%
Other values (13) 89
20.6%
Decimal Number
ValueCountFrequency (%)
2 14
23.0%
1 12
19.7%
3 9
14.8%
5 6
9.8%
6 5
 
8.2%
4 4
 
6.6%
0 3
 
4.9%
9 3
 
4.9%
8 3
 
4.9%
7 2
 
3.3%
Other Punctuation
ValueCountFrequency (%)
& 35
59.3%
. 15
25.4%
' 4
 
6.8%
, 3
 
5.1%
· 2
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 602
100.0%
Open Punctuation
ValueCountFrequency (%)
( 594
100.0%
Space Separator
ValueCountFrequency (%)
456
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19581
87.9%
Common 1775
 
8.0%
Latin 919
 
4.1%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1249
 
6.4%
1092
 
5.6%
637
 
3.3%
472
 
2.4%
443
 
2.3%
409
 
2.1%
360
 
1.8%
325
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (683) 13990
71.4%
Latin
ValueCountFrequency (%)
e 80
 
8.7%
o 62
 
6.7%
F 48
 
5.2%
O 43
 
4.7%
C 38
 
4.1%
f 36
 
3.9%
S 36
 
3.9%
B 35
 
3.8%
n 34
 
3.7%
a 31
 
3.4%
Other values (37) 476
51.8%
Common
ValueCountFrequency (%)
) 602
33.9%
( 594
33.5%
456
25.7%
& 35
 
2.0%
. 15
 
0.8%
2 14
 
0.8%
1 12
 
0.7%
3 9
 
0.5%
5 6
 
0.3%
6 5
 
0.3%
Other values (10) 27
 
1.5%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19581
87.9%
ASCII 2692
 
12.1%
CJK 5
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1249
 
6.4%
1092
 
5.6%
637
 
3.3%
472
 
2.4%
443
 
2.3%
409
 
2.1%
360
 
1.8%
325
 
1.7%
307
 
1.6%
297
 
1.5%
Other values (683) 13990
71.4%
ASCII
ValueCountFrequency (%)
) 602
22.4%
( 594
22.1%
456
16.9%
e 80
 
3.0%
o 62
 
2.3%
F 48
 
1.8%
O 43
 
1.6%
C 38
 
1.4%
f 36
 
1.3%
S 36
 
1.3%
Other values (56) 697
25.9%
None
ValueCountFrequency (%)
· 2
100.0%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

최종수정시점
Real number (ℝ)

Distinct3370
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.013234 × 1013
Minimum2.001082 × 1013
Maximum2.0220729 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:34.034300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001082 × 1013
5-th percentile2.002071 × 1013
Q12.0071009 × 1013
median2.0150825 × 1013
Q32.0191025 × 1013
95-th percentile2.0220207 × 1013
Maximum2.0220729 × 1013
Range2.0990911 × 1011
Interquartile range (IQR)1.2001607 × 1011

Descriptive statistics

Standard deviation6.7553802 × 1010
Coefficient of variation (CV)0.0033554868
Kurtosis-1.3154681
Mean2.013234 × 1013
Median Absolute Deviation (MAD)5.0495523 × 1010
Skewness-0.33184086
Sum7.6019716 × 1016
Variance4.5635161 × 1021
MonotonicityNot monotonic
2024-04-17T19:16:34.149066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020205000000 55
 
1.5%
20041011000000 23
 
0.6%
20020926000000 21
 
0.6%
20010821000000 18
 
0.5%
20030407000000 18
 
0.5%
20020508000000 14
 
0.4%
20020507000000 13
 
0.3%
20020509000000 13
 
0.3%
20031027000000 12
 
0.3%
20021108000000 12
 
0.3%
Other values (3360) 3577
94.7%
ValueCountFrequency (%)
20010820000000 4
 
0.1%
20010821000000 18
0.5%
20011108000000 2
 
0.1%
20011119000000 1
 
< 0.1%
20011122000000 1
 
< 0.1%
20011126000000 1
 
< 0.1%
20011128000000 3
 
0.1%
20011210000000 1
 
< 0.1%
20011226000000 1
 
< 0.1%
20011228000000 1
 
< 0.1%
ValueCountFrequency (%)
20220729114747 1
< 0.1%
20220728173938 1
< 0.1%
20220726105701 1
< 0.1%
20220726105642 1
< 0.1%
20220725185713 1
< 0.1%
20220725152742 1
< 0.1%
20220725101528 1
< 0.1%
20220722091353 1
< 0.1%
20220721171904 1
< 0.1%
20220719164012 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
I
2689 
U
1087 

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 2689
71.2%
U 1087
28.8%

Length

2024-04-17T19:16:34.263557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:34.351834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2689
71.2%
u 1087
28.8%
Distinct752
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
Minimum2018-08-31 23:59:59
Maximum2022-07-31 02:40:00
2024-04-17T19:16:34.438640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:16:34.769717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
식품제조가공업
2794 
기타 식품제조가공업
954 
도시락제조업
 
28

Length

Max length10
Median length7
Mean length7.7505297
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2794
74.0%
기타 식품제조가공업 954
 
25.3%
도시락제조업 28
 
0.7%

Length

2024-04-17T19:16:34.871061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:34.962029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3748
79.2%
기타 954
 
20.2%
도시락제조업 28
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3085
Distinct (%)85.6%
Missing172
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean341847.07
Minimum323038.14
Maximum356965.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:35.050422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum323038.14
5-th percentile331552.71
Q1338738.2
median341557.39
Q3345499.97
95-th percentile352940.44
Maximum356965.56
Range33927.418
Interquartile range (IQR)6761.7687

Descriptive statistics

Standard deviation5857.495
Coefficient of variation (CV)0.01713484
Kurtosis0.096934025
Mean341847.07
Median Absolute Deviation (MAD)3358.8759
Skewness-0.023519362
Sum1.2320168 × 109
Variance34310248
MonotonicityNot monotonic
2024-04-17T19:16:35.159154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339243.983122 27
 
0.7%
334406.500396 7
 
0.2%
348434.155718 5
 
0.1%
346004.036082 5
 
0.1%
344858.271847 4
 
0.1%
343260.899953 4
 
0.1%
338678.797273 4
 
0.1%
345484.223256 4
 
0.1%
334946.049344 4
 
0.1%
335619.487404 4
 
0.1%
Other values (3075) 3536
93.6%
(Missing) 172
 
4.6%
ValueCountFrequency (%)
323038.137302 1
 
< 0.1%
323583.427786 1
 
< 0.1%
325649.192591 1
 
< 0.1%
325694.253396 1
 
< 0.1%
326018.881016 1
 
< 0.1%
326032.481595 1
 
< 0.1%
326631.950345 1
 
< 0.1%
326739.522357 4
0.1%
326760.851184 1
 
< 0.1%
326950.230819 1
 
< 0.1%
ValueCountFrequency (%)
356965.555233 1
 
< 0.1%
356410.892344 1
 
< 0.1%
356388.525062 1
 
< 0.1%
356370.038499 1
 
< 0.1%
356353.91544 1
 
< 0.1%
356349.757069 3
0.1%
356345.316761 1
 
< 0.1%
356335.999166 1
 
< 0.1%
356331.110923 1
 
< 0.1%
356328.871819 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3084
Distinct (%)85.6%
Missing172
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean263385.72
Minimum236164.39
Maximum278073.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:35.274696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236164.39
5-th percentile253719.72
Q1261098.04
median263994.36
Q3266465.35
95-th percentile271932.41
Maximum278073.62
Range41909.231
Interquartile range (IQR)5367.3029

Descriptive statistics

Standard deviation5397.6367
Coefficient of variation (CV)0.020493277
Kurtosis3.2824077
Mean263385.72
Median Absolute Deviation (MAD)2702.6732
Skewness-1.1053542
Sum9.4924214 × 108
Variance29134482
MonotonicityNot monotonic
2024-04-17T19:16:35.378580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
268026.454531 27
 
0.7%
260208.38965 7
 
0.2%
269131.73002 5
 
0.1%
264017.165939 5
 
0.1%
260540.364298 4
 
0.1%
249198.891144 4
 
0.1%
250014.011622 4
 
0.1%
269356.648959 4
 
0.1%
242019.624632 4
 
0.1%
265012.3332 4
 
0.1%
Other values (3074) 3536
93.6%
(Missing) 172
 
4.6%
ValueCountFrequency (%)
236164.392418 1
< 0.1%
237999.437164 1
< 0.1%
238531.35408 1
< 0.1%
238772.106218 1
< 0.1%
238772.40735 1
< 0.1%
238824.505921 1
< 0.1%
238893.362765 1
< 0.1%
238893.829912 1
< 0.1%
239059.112588 1
< 0.1%
239098.142264 1
< 0.1%
ValueCountFrequency (%)
278073.623286 1
< 0.1%
278029.090204 1
< 0.1%
277860.926384 1
< 0.1%
277755.206408 2
0.1%
277749.024029 1
< 0.1%
277673.246368 1
< 0.1%
277500.515376 1
< 0.1%
277489.106534 1
< 0.1%
277348.717166 1
< 0.1%
277022.824657 1
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
식품제조가공업
2794 
기타 식품제조가공업
954 
도시락제조업
 
28

Length

Max length10
Median length7
Mean length7.7505297
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 2794
74.0%
기타 식품제조가공업 954
 
25.3%
도시락제조업 28
 
0.7%

Length

2024-04-17T19:16:35.486447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:35.572511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 3748
79.2%
기타 954
 
20.2%
도시락제조업 28
 
0.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
<NA>
3339 
0
437 

Length

Max length4
Median length4
Mean length3.6528072
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3339
88.4%
0 437
 
11.6%

Length

2024-04-17T19:16:35.663361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:35.746338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3339
88.4%
0 437
 
11.6%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
<NA>
3339 
0
437 

Length

Max length4
Median length4
Mean length3.6528072
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3339
88.4%
0 437
 
11.6%

Length

2024-04-17T19:16:35.836422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:35.925653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3339
88.4%
0 437
 
11.6%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
상수도전용
2204 
<NA>
1552 
지하수전용
 
16
간이상수도
 
3
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length5
Mean length4.592161
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 2204
58.4%
<NA> 1552
41.1%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-17T19:16:36.018945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:36.113153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 2204
58.4%
na 1552
41.1%
지하수전용 16
 
0.4%
간이상수도 3
 
0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총직원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
<NA>
3353 
0
423 

Length

Max length4
Median length4
Mean length3.6639301
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> 3353
88.8%
0 423
 
11.2%

Length

2024-04-17T19:16:36.228896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:36.329259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3353
88.8%
0 423
 
11.2%

본사직원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing625
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean0.068232307
Minimum0
Maximum12
Zeros3028
Zeros (%)80.2%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:36.400213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.45297256
Coefficient of variation (CV)6.6386816
Kurtosis213.19985
Mean0.068232307
Median Absolute Deviation (MAD)0
Skewness11.988686
Sum215
Variance0.20518414
MonotonicityNot monotonic
2024-04-17T19:16:36.492335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3028
80.2%
1 84
 
2.2%
3 15
 
0.4%
2 14
 
0.4%
5 5
 
0.1%
4 2
 
0.1%
12 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 625
 
16.6%
ValueCountFrequency (%)
0 3028
80.2%
1 84
 
2.2%
2 14
 
0.4%
3 15
 
0.4%
4 2
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 2
 
0.1%
3 15
 
0.4%
2 14
 
0.4%
1 84
 
2.2%
0 3028
80.2%

공장사무직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.3%
Missing615
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean0.20468206
Minimum0
Maximum40
Zeros2765
Zeros (%)73.2%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:36.580407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0226193
Coefficient of variation (CV)4.9961354
Kurtosis764.34922
Mean0.20468206
Median Absolute Deviation (MAD)0
Skewness22.256067
Sum647
Variance1.0457502
MonotonicityNot monotonic
2024-04-17T19:16:36.691485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 2765
73.2%
1 296
 
7.8%
2 58
 
1.5%
3 21
 
0.6%
4 8
 
0.2%
6 4
 
0.1%
5 3
 
0.1%
11 2
 
0.1%
15 2
 
0.1%
40 1
 
< 0.1%
(Missing) 615
 
16.3%
ValueCountFrequency (%)
0 2765
73.2%
1 296
 
7.8%
2 58
 
1.5%
3 21
 
0.6%
4 8
 
0.2%
5 3
 
0.1%
6 4
 
0.1%
9 1
 
< 0.1%
11 2
 
0.1%
15 2
 
0.1%
ValueCountFrequency (%)
40 1
 
< 0.1%
15 2
 
0.1%
11 2
 
0.1%
9 1
 
< 0.1%
6 4
 
0.1%
5 3
 
0.1%
4 8
 
0.2%
3 21
 
0.6%
2 58
 
1.5%
1 296
7.8%

공장판매직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct9
Distinct (%)0.3%
Missing635
Missing (%)16.8%
Infinite0
Infinite (%)0.0%
Mean0.10315186
Minimum0
Maximum30
Zeros2925
Zeros (%)77.5%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:36.778069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.68435166
Coefficient of variation (CV)6.6344092
Kurtosis1180.3503
Mean0.10315186
Median Absolute Deviation (MAD)0
Skewness28.740154
Sum324
Variance0.4683372
MonotonicityNot monotonic
2024-04-17T19:16:36.859594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 2925
77.5%
1 166
 
4.4%
2 36
 
1.0%
3 7
 
0.2%
5 2
 
0.1%
4 2
 
0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
30 1
 
< 0.1%
(Missing) 635
 
16.8%
ValueCountFrequency (%)
0 2925
77.5%
1 166
 
4.4%
2 36
 
1.0%
3 7
 
0.2%
4 2
 
0.1%
5 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
5 2
 
0.1%
4 2
 
0.1%
3 7
 
0.2%
2 36
 
1.0%
1 166
 
4.4%
0 2925
77.5%

공장생산직직원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct27
Distinct (%)0.8%
Missing544
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean0.82240099
Minimum0
Maximum220
Zeros2309
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:36.961392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum220
Range220
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.6727
Coefficient of variation (CV)5.6817782
Kurtosis1535.2484
Mean0.82240099
Median Absolute Deviation (MAD)0
Skewness34.649172
Sum2658
Variance21.834125
MonotonicityNot monotonic
2024-04-17T19:16:37.055804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2309
61.1%
1 458
 
12.1%
2 202
 
5.3%
3 107
 
2.8%
4 48
 
1.3%
5 30
 
0.8%
7 18
 
0.5%
6 13
 
0.3%
8 12
 
0.3%
10 7
 
0.2%
Other values (17) 28
 
0.7%
(Missing) 544
 
14.4%
ValueCountFrequency (%)
0 2309
61.1%
1 458
 
12.1%
2 202
 
5.3%
3 107
 
2.8%
4 48
 
1.3%
5 30
 
0.8%
6 13
 
0.3%
7 18
 
0.5%
8 12
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
220 1
< 0.1%
83 1
< 0.1%
50 1
< 0.1%
42 1
< 0.1%
32 1
< 0.1%
28 1
< 0.1%
25 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
20 2
0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
<NA>
1807 
임대
1145 
자가
824 

Length

Max length4
Median length2
Mean length2.9570975
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1807
47.9%
임대 1145
30.3%
자가 824
21.8%

Length

2024-04-17T19:16:37.153967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:37.246944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1807
47.9%
임대 1145
30.3%
자가 824
21.8%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)2.9%
Missing3159
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean1004703.1
Minimum0
Maximum50000000
Zeros553
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:37.345364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8400000
Maximum50000000
Range50000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4347673.1
Coefficient of variation (CV)4.3273213
Kurtosis68.714779
Mean1004703.1
Median Absolute Deviation (MAD)0
Skewness7.4168852
Sum6.199018 × 108
Variance1.8902261 × 1013
MonotonicityNot monotonic
2024-04-17T19:16:37.451370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 553
 
14.6%
10000000 24
 
0.6%
5000000 19
 
0.5%
3000000 3
 
0.1%
8000000 2
 
0.1%
30000000 2
 
0.1%
50000000 2
 
0.1%
2000000 2
 
0.1%
6000000 1
 
< 0.1%
18000000 1
 
< 0.1%
Other values (8) 8
 
0.2%
(Missing) 3159
83.7%
ValueCountFrequency (%)
0 553
14.6%
300 1
 
< 0.1%
500 1
 
< 0.1%
1000 1
 
< 0.1%
500000 1
 
< 0.1%
2000000 2
 
0.1%
3000000 3
 
0.1%
4400000 1
 
< 0.1%
5000000 19
 
0.5%
6000000 1
 
< 0.1%
ValueCountFrequency (%)
50000000 2
 
0.1%
40000000 1
 
< 0.1%
30000000 2
 
0.1%
20000000 1
 
< 0.1%
18000000 1
 
< 0.1%
10000000 24
0.6%
8000000 2
 
0.1%
7000000 1
 
< 0.1%
6000000 1
 
< 0.1%
5000000 19
0.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)4.2%
Missing3160
Missing (%)83.7%
Infinite0
Infinite (%)0.0%
Mean56396.412
Minimum0
Maximum2200000
Zeros552
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:37.547367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile462500
Maximum2200000
Range2200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation212894.79
Coefficient of variation (CV)3.7749705
Kurtosis39.954058
Mean56396.412
Median Absolute Deviation (MAD)0
Skewness5.5860369
Sum34740190
Variance4.5324192 × 1010
MonotonicityNot monotonic
2024-04-17T19:16:37.642807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 552
 
14.6%
300000 13
 
0.3%
500000 11
 
0.3%
400000 5
 
0.1%
600000 4
 
0.1%
350000 3
 
0.1%
200000 3
 
0.1%
800000 3
 
0.1%
250000 2
 
0.1%
700000 2
 
0.1%
Other values (16) 18
 
0.5%
(Missing) 3160
83.7%
ValueCountFrequency (%)
0 552
14.6%
10 1
 
< 0.1%
30 1
 
< 0.1%
150 1
 
< 0.1%
150000 1
 
< 0.1%
200000 3
 
0.1%
250000 2
 
0.1%
300000 13
 
0.3%
350000 3
 
0.1%
400000 5
 
0.1%
ValueCountFrequency (%)
2200000 1
 
< 0.1%
2000000 1
 
< 0.1%
1800000 1
 
< 0.1%
1300000 1
 
< 0.1%
1200000 1
 
< 0.1%
1100000 1
 
< 0.1%
900000 1
 
< 0.1%
850000 2
0.1%
800000 3
0.1%
750000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
False
3774 
True
 
2
ValueCountFrequency (%)
False 3774
99.9%
True 2
 
0.1%
2024-04-17T19:16:37.724019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct546
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.348927
Minimum0
Maximum4673.38
Zeros2994
Zeros (%)79.3%
Negative0
Negative (%)0.0%
Memory size33.3 KiB
2024-04-17T19:16:37.812434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile39.7825
Maximum4673.38
Range4673.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation124.97435
Coefficient of variation (CV)10.12026
Kurtosis975.43198
Mean12.348927
Median Absolute Deviation (MAD)0
Skewness28.774687
Sum46629.55
Variance15618.589
MonotonicityNot monotonic
2024-04-17T19:16:37.916811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2994
79.3%
3.0 23
 
0.6%
6.0 16
 
0.4%
1.0 15
 
0.4%
4.0 12
 
0.3%
2.0 12
 
0.3%
3.3 10
 
0.3%
4.5 8
 
0.2%
1.2 8
 
0.2%
9.0 7
 
0.2%
Other values (536) 671
 
17.8%
ValueCountFrequency (%)
0.0 2994
79.3%
1.0 15
 
0.4%
1.1 1
 
< 0.1%
1.2 8
 
0.2%
1.23 1
 
< 0.1%
1.3 1
 
< 0.1%
1.39 1
 
< 0.1%
1.5 5
 
0.1%
1.64 1
 
< 0.1%
1.7 1
 
< 0.1%
ValueCountFrequency (%)
4673.38 1
< 0.1%
4439.37 1
< 0.1%
2313.89 1
< 0.1%
1680.5 1
< 0.1%
1520.96 1
< 0.1%
943.03 1
< 0.1%
875.0 1
< 0.1%
802.0 1
< 0.1%
701.08 1
< 0.1%
695.92 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3776
Missing (%)100.0%
Memory size33.3 KiB

홈페이지
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.6 KiB
<NA>
3774 
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.998411
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> 3774
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-04-17T19:16:38.023834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:16:38.107476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3774
99.9%
4 1
 
< 0.1%
6 1
 
< 0.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
01식품제조가공업07_22_11_P34100003410000-106-2004-0000220040507<NA>3폐업2폐업20050324<NA><NA><NA>053 424497914.70700111대구광역시 중구 태평로1가 0001-0186번지<NA><NA>동북상회20041102000000I2018-08-31 23:59:59.0식품제조가공업344182.487426265065.535111식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0011<NA><NA><NA>N0.0<NA><NA><NA>
12식품제조가공업07_22_11_P34100003410000-106-2004-0000320040524<NA>3폐업2폐업20150424<NA><NA><NA>053 256433741.85700837대구광역시 중구 남산동 2466-0001번지 보성황실아파트 116동 105호대구광역시 중구 남산로13길 17, 1층 (남산동, 보성황실아파트 116동 105호)41978황실떡집20150304143402I2018-08-31 23:59:59.0식품제조가공업342754.486268263376.49575식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0002자가<NA><NA>N0.0<NA><NA><NA>
23식품제조가공업07_22_11_P34100003410000-106-2004-0000420040629<NA>3폐업2폐업20040908<NA><NA><NA>053 4240540120.60700823대구광역시 중구 봉산동 0165-0007번지<NA><NA>에프엔에스20040901000000I2018-08-31 23:59:59.0식품제조가공업344341.820223263777.999999식품제조가공업00<NA><NA>상수도전용<NA>0121임대<NA><NA>N0.0<NA><NA><NA>
34식품제조가공업07_22_11_P34100003410000-106-2004-0000520041101<NA>3폐업2폐업20080717<NA><NA><NA>053 422331834.52700845대구광역시 중구 동인동3가 0302-0002번지<NA><NA>이유통20071126103251I2018-08-31 23:59:59.0식품제조가공업345483.514708264655.185763식품제조가공업<NA><NA><NA><NA>상수도전용<NA>1000자가<NA><NA>N0.0<NA><NA><NA>
45식품제조가공업07_22_11_P34100003410000-106-2004-0000620041111<NA>3폐업2폐업20050906<NA><NA><NA><NA>25.23700421대구광역시 중구 동인동1가 0196번지<NA><NA>불스푸드20050321000000I2018-08-31 23:59:59.0식품제조가공업344696.914116264897.878354식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0111자가<NA><NA>N0.0<NA><NA><NA>
56식품제조가공업07_22_11_P34100003410000-106-2004-0000720041119<NA>3폐업2폐업20041120<NA><NA><NA>053 4294238<NA>700180대구광역시 중구 동문동 0020-0004번지<NA><NA>(사)농어촌특산단지전남연합회20041119000000I2018-08-31 23:59:59.0식품제조가공업344148.352033264812.35373식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
67식품제조가공업07_22_11_P34100003410000-106-2004-0000820041202<NA>3폐업2폐업20100621<NA><NA><NA>053 254013230.20700413대구광역시 중구 삼덕동3가 0042번지<NA><NA>교자춘20071113181224I2018-08-31 23:59:59.0식품제조가공업345042.851191263965.608979식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102자가<NA><NA>N0.0<NA><NA><NA>
78식품제조가공업07_22_11_P34100003410000-106-2005-0000220050623<NA>3폐업2폐업20050706<NA><NA><NA><NA><NA>700320대구광역시 중구 대신동 115-370번지 1층<NA><NA>경북농산20050623000000I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
89식품제조가공업07_22_11_P34100003410000-106-2005-0000420050908<NA>3폐업2폐업20070208<NA><NA><NA><NA>67.75700413대구광역시 중구 삼덕동3가 0227-0006번지<NA><NA>(주)승민식품20050908000000I2018-08-31 23:59:59.0식품제조가공업345171.417199263913.270601식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0202자가<NA><NA>N0.0<NA><NA><NA>
910식품제조가공업07_22_11_P34100003410000-106-2005-0000520050927<NA>3폐업2폐업20070918<NA><NA><NA><NA>58.84700812대구광역시 중구 대봉동 0166-0010번지<NA><NA>(주)엠빠나다20051028000000I2018-08-31 23:59:59.0식품제조가공업344440.147732263031.504086식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0101임대<NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
37663767식품제조가공업07_22_11_P34800003480000-106-2013-0001520131016<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.42711864대구광역시 달성군 가창면 용계리 233-16대구광역시 달성군 가창면 가창로213길 8-1, 1층42936보리채움20220207173857U2022-02-09 02:40:00.0식품제조가공업346565.952924256681.467415식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
37673768식품제조가공업07_22_11_P34800003480000-106-2021-0000620210430<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.00711852대구광역시 달성군 논공읍 남리 224-110대구광역시 달성군 논공읍 논공로 806-1, 1층42978네츄럴팩트20210430134728I2021-05-02 00:22:57.0기타 식품제조가공업330115.35775248516.530338기타 식품제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
37683769식품제조가공업07_22_11_P34800003480000-106-2008-0001720080104<NA>1영업/정상1영업<NA><NA><NA><NA>053 627 2557447.00711850대구광역시 달성군 논공읍 삼리리 632-1번지 외 1필지 A동대구광역시 달성군 논공읍 위천2길 6, A동 1층42976정통식품20160127164501I2018-08-31 23:59:59.0식품제조가공업327021.529591252397.401938식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
37693770식품제조가공업07_22_11_P34800003480000-106-2012-0001020120911<NA>1영업/정상1영업<NA><NA><NA><NA>070 75325543149.47711832대구광역시 달성군 화원읍 명곡리 105번지 2층대구광역시 달성군 화원읍 명곡로 12-11, 2층42960청원푸드20160128102651I2018-08-31 23:59:59.0식품제조가공업335094.531933256378.574073식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37703771식품제조가공업07_22_11_P34800003480000-106-2013-0000620130808<NA>1영업/정상1영업<NA><NA><NA><NA>053 639 5887159.30711839대구광역시 달성군 화원읍 성산리 536-6번지대구광역시 달성군 화원읍 성천로12길 1142946선미 푸드20160128164651I2018-08-31 23:59:59.0식품제조가공업334521.009928256794.676167식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37713772식품제조가공업07_22_11_P34800003480000-106-2012-0000520120615<NA>1영업/정상1영업<NA><NA><NA><NA>053 584 4884472.00711821대구광역시 달성군 하빈면 하산리 133-1번지대구광역시 달성군 하빈면 하산4길 7842900훈식품20170825094405I2018-08-31 23:59:59.0식품제조가공업327642.468368267180.710022식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
37723773식품제조가공업07_22_11_P34800003480000-106-2007-0001820071108<NA>1영업/정상1영업<NA><NA><NA><NA>053 6443684204.00711855대구광역시 달성군 논공읍 본리리 29-53번지대구광역시 달성군 논공읍 논공로71길 2742982미성20191011162442U2019-10-13 02:40:00.0식품제조가공업332803.386147250052.269534식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102임대<NA><NA>N8.0<NA><NA><NA>
37733774식품제조가공업07_22_11_P34800003480000-106-2007-0001920071113<NA>1영업/정상1영업<NA><NA><NA><NA>053 61196111,205.93711892대구광역시 달성군 구지면 내리 839-11번지대구광역시 달성군 구지면 달성2차로 2743011(주)푸름원20160127154201I2018-08-31 23:59:59.0식품제조가공업327415.835763238772.106218식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
37743775식품제조가공업07_22_11_P34800003480000-106-1997-0000819970924<NA>1영업/정상1영업<NA><NA><NA><NA><NA>837.90711823대구광역시 달성군 하빈면 봉촌리 1032-3번지대구광역시 달성군 하빈면 하빈남로 40742905연꽃마을20160127155832I2018-08-31 23:59:59.0식품제조가공업325649.192591263403.704757식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0102<NA><NA><NA>N0.0<NA><NA><NA>
37753776식품제조가공업07_22_11_P34800003480000-106-1997-0001019971006<NA>1영업/정상1영업<NA><NA><NA><NA>053 6153645225.00711842대구광역시 달성군 옥포면 강림리 263번지대구광역시 달성군 옥포면 시저로4길 1642968나진제과20160127155852I2018-08-31 23:59:59.0식품제조가공업329266.735737254748.099287식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0103<NA><NA><NA>N0.0<NA><NA><NA>