Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells145840
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 MiB
Average record size in memory414.0 B

Variable types

Numeric15
Categorical14
Text7
Unsupported9
DateTime1
Boolean1

Dataset

Description22년04월_6270000_대구광역시_07_22_03_P_건강기능식품일반판매업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000092918&dataSetDetailId=DDI_0000092977&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (52.1%)Imbalance
여성종사자수 is highly imbalanced (52.1%)Imbalance
급수시설구분명 is highly imbalanced (68.9%)Imbalance
총종업원수 is highly imbalanced (52.6%)Imbalance
공장생산직종업원수 is highly imbalanced (58.4%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2697 (27.0%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
소재지전화 has 5170 (51.7%) missing valuesMissing
소재지면적 has 4051 (40.5%) missing valuesMissing
소재지우편번호 has 105 (1.1%) missing valuesMissing
도로명전체주소 has 1983 (19.8%) missing valuesMissing
도로명우편번호 has 2045 (20.4%) missing valuesMissing
업태구분명 has 10000 (100.0%) missing valuesMissing
좌표정보(X) has 222 (2.2%) missing valuesMissing
좌표정보(Y) has 222 (2.2%) missing valuesMissing
영업장주변구분명 has 10000 (100.0%) missing valuesMissing
등급구분명 has 10000 (100.0%) missing valuesMissing
본사종업원수 has 3828 (38.3%) missing valuesMissing
공장사무직종업원수 has 3827 (38.3%) missing valuesMissing
공장판매직종업원수 has 3826 (38.3%) missing valuesMissing
보증액 has 8942 (89.4%) missing valuesMissing
월세액 has 8941 (89.4%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 9973 (99.7%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = -63.13178791)Skewed
본사종업원수 is highly skewed (γ1 = 25.28310859)Skewed
공장사무직종업원수 is highly skewed (γ1 = 23.04982455)Skewed
공장판매직종업원수 is highly skewed (γ1 = 20.5080749)Skewed
보증액 is highly skewed (γ1 = 31.54738186)Skewed
시설총규모 is highly skewed (γ1 = 40.64775852)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
업태구분명 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
본사종업원수 has 6139 (61.4%) zerosZeros
공장사무직종업원수 has 5952 (59.5%) zerosZeros
공장판매직종업원수 has 5452 (54.5%) zerosZeros
보증액 has 1051 (10.5%) zerosZeros
월세액 has 1051 (10.5%) zerosZeros
시설총규모 has 9858 (98.6%) zerosZeros

Reproduction

Analysis started2024-04-18 02:12:53.205507
Analysis finished2024-04-18 02:12:54.917271
Duration1.71 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7819.7729
Minimum1
Maximum15620
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:12:54.972982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile783.9
Q13954.5
median7837.5
Q311706.5
95-th percentile14807.05
Maximum15620
Range15619
Interquartile range (IQR)7752

Descriptive statistics

Standard deviation4496.1889
Coefficient of variation (CV)0.57497692
Kurtosis-1.1993113
Mean7819.7729
Median Absolute Deviation (MAD)3875.5
Skewness-0.010585732
Sum78197729
Variance20215715
MonotonicityNot monotonic
2024-04-18T11:12:55.082336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3626 1
 
< 0.1%
2319 1
 
< 0.1%
15212 1
 
< 0.1%
10989 1
 
< 0.1%
11486 1
 
< 0.1%
4126 1
 
< 0.1%
7143 1
 
< 0.1%
13428 1
 
< 0.1%
6291 1
 
< 0.1%
6437 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
15620 1
< 0.1%
15618 1
< 0.1%
15617 1
< 0.1%
15616 1
< 0.1%
15613 1
< 0.1%
15612 1
< 0.1%
15611 1
< 0.1%
15608 1
< 0.1%
15607 1
< 0.1%
15606 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

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

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품일반판매업 10000
100.0%

Length

2024-04-18T11:12:55.190864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:55.261624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품일반판매업 10000
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_22_03_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_03_P
2nd row07_22_03_P
3rd row07_22_03_P
4th row07_22_03_P
5th row07_22_03_P

Common Values

ValueCountFrequency (%)
07_22_03_P 10000
100.0%

Length

2024-04-18T11:12:55.334887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:55.404848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_03_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3448417
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:12:55.472126image/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 deviation21219.075
Coefficient of variation (CV)0.0061532798
Kurtosis-1.0769372
Mean3448417
Median Absolute Deviation (MAD)20000
Skewness-0.4232135
Sum3.448417 × 1010
Variance4.5024914 × 108
MonotonicityNot monotonic
2024-04-18T11:12:55.560378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2215
22.1%
3460000 1857
18.6%
3450000 1699
17.0%
3420000 1386
13.9%
3410000 835
 
8.3%
3440000 739
 
7.4%
3430000 688
 
6.9%
3480000 581
 
5.8%
ValueCountFrequency (%)
3410000 835
 
8.3%
3420000 1386
13.9%
3430000 688
 
6.9%
3440000 739
 
7.4%
3450000 1699
17.0%
3460000 1857
18.6%
3470000 2215
22.1%
3480000 581
 
5.8%
ValueCountFrequency (%)
3480000 581
 
5.8%
3470000 2215
22.1%
3460000 1857
18.6%
3450000 1699
17.0%
3440000 739
 
7.4%
3430000 688
 
6.9%
3420000 1386
13.9%
3410000 835
 
8.3%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T11:12:55.724191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row3430000-134-2014-00047
2nd row3420000-134-2019-00008
3rd row3410000-134-2020-00030
4th row3440000-134-2005-00011
5th row3460000-134-2004-00333
ValueCountFrequency (%)
3430000-134-2014-00047 1
 
< 0.1%
3470000-134-2012-00069 1
 
< 0.1%
3460000-134-2004-00077 1
 
< 0.1%
3470000-134-2010-00073 1
 
< 0.1%
3480000-134-2004-00067 1
 
< 0.1%
3460000-134-2021-00087 1
 
< 0.1%
3470000-134-2018-00098 1
 
< 0.1%
3430000-134-2009-00079 1
 
< 0.1%
3450000-134-2004-00473 1
 
< 0.1%
3420000-134-2010-00027 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-18T11:12:55.982892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84114
38.2%
- 30000
 
13.6%
4 24818
 
11.3%
3 23658
 
10.8%
1 21830
 
9.9%
2 16519
 
7.5%
7 4596
 
2.1%
5 4441
 
2.0%
6 4308
 
2.0%
8 2891
 
1.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84114
44.3%
4 24818
 
13.1%
3 23658
 
12.5%
1 21830
 
11.5%
2 16519
 
8.7%
7 4596
 
2.4%
5 4441
 
2.3%
6 4308
 
2.3%
8 2891
 
1.5%
9 2825
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 84114
38.2%
- 30000
 
13.6%
4 24818
 
11.3%
3 23658
 
10.8%
1 21830
 
9.9%
2 16519
 
7.5%
7 4596
 
2.1%
5 4441
 
2.0%
6 4308
 
2.0%
8 2891
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 84114
38.2%
- 30000
 
13.6%
4 24818
 
11.3%
3 23658
 
10.8%
1 21830
 
9.9%
2 16519
 
7.5%
7 4596
 
2.1%
5 4441
 
2.0%
6 4308
 
2.0%
8 2891
 
1.3%

인허가일자
Real number (ℝ)

Distinct3429
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124049
Minimum20040204
Maximum20220428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:12:56.102116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040204
5-th percentile20040618
Q120081219
median20120508
Q320171206
95-th percentile20210722
Maximum20220428
Range180224
Interquartile range (IQR)89987

Descriptive statistics

Standard deviation56204.856
Coefficient of variation (CV)0.0027929198
Kurtosis-1.159356
Mean20124049
Median Absolute Deviation (MAD)49703.5
Skewness0.064958974
Sum2.0124049 × 1011
Variance3.1589858 × 109
MonotonicityNot monotonic
2024-04-18T11:12:56.238882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040618 221
 
2.2%
20040617 77
 
0.8%
20040616 35
 
0.4%
20040831 31
 
0.3%
20040615 30
 
0.3%
20131204 30
 
0.3%
20150423 28
 
0.3%
20040917 28
 
0.3%
20040621 26
 
0.3%
20040614 26
 
0.3%
Other values (3419) 9468
94.7%
ValueCountFrequency (%)
20040204 1
 
< 0.1%
20040214 1
 
< 0.1%
20040224 1
 
< 0.1%
20040304 2
< 0.1%
20040320 1
 
< 0.1%
20040326 2
< 0.1%
20040407 1
 
< 0.1%
20040408 3
< 0.1%
20040409 2
< 0.1%
20040412 2
< 0.1%
ValueCountFrequency (%)
20220428 1
 
< 0.1%
20220427 6
0.1%
20220426 3
 
< 0.1%
20220425 9
0.1%
20220422 1
 
< 0.1%
20220421 1
 
< 0.1%
20220420 2
 
< 0.1%
20220419 1
 
< 0.1%
20220418 8
0.1%
20220415 2
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7303 
1
2697 

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 7303
73.0%
1 2697
 
27.0%

Length

2024-04-18T11:12:56.346047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:56.419904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7303
73.0%
1 2697
 
27.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7303 
영업/정상
2697 

Length

Max length5
Median length2
Mean length2.8091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7303
73.0%
영업/정상 2697
 
27.0%

Length

2024-04-18T11:12:56.502929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:56.586123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7303
73.0%
영업/정상 2697
 
27.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7303 
1
2697 

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 7303
73.0%
1 2697
 
27.0%

Length

2024-04-18T11:12:56.689463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:56.759732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7303
73.0%
1 2697
 
27.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7303 
영업
2697 

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 7303
73.0%
영업 2697
 
27.0%

Length

2024-04-18T11:12:56.836036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:12:56.912523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7303
73.0%
영업 2697
 
27.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct2935
Distinct (%)40.2%
Missing2697
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean20148457
Minimum20040419
Maximum20220427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:12:57.002319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040419
5-th percentile20070108
Q120111207
median20160122
Q320190109
95-th percentile20210924
Maximum20220427
Range180008
Interquartile range (IQR)78902

Descriptive statistics

Standard deviation44663.849
Coefficient of variation (CV)0.0022167379
Kurtosis-0.77237929
Mean20148457
Median Absolute Deviation (MAD)30697
Skewness-0.46532818
Sum1.4714418 × 1011
Variance1.9948594 × 109
MonotonicityNot monotonic
2024-04-18T11:12:57.117576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171229 59
 
0.6%
20171228 34
 
0.3%
20171211 29
 
0.3%
20171205 27
 
0.3%
20190531 27
 
0.3%
20171227 25
 
0.2%
20181203 25
 
0.2%
20191231 24
 
0.2%
20211231 24
 
0.2%
20171206 23
 
0.2%
Other values (2925) 7006
70.1%
(Missing) 2697
 
27.0%
ValueCountFrequency (%)
20040419 1
< 0.1%
20040610 1
< 0.1%
20040624 1
< 0.1%
20040708 1
< 0.1%
20040713 1
< 0.1%
20040715 1
< 0.1%
20040722 1
< 0.1%
20040802 1
< 0.1%
20040809 1
< 0.1%
20040819 1
< 0.1%
ValueCountFrequency (%)
20220427 1
 
< 0.1%
20220425 3
< 0.1%
20220421 2
< 0.1%
20220418 2
< 0.1%
20220415 4
< 0.1%
20220411 3
< 0.1%
20220408 2
< 0.1%
20220404 1
 
< 0.1%
20220401 1
 
< 0.1%
20220330 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지전화
Text

MISSING 

Distinct4473
Distinct (%)92.6%
Missing5170
Missing (%)51.7%
Memory size156.2 KiB
2024-04-18T11:12:57.417062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.156522
Min length3

Characters and Unicode

Total characters53886
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

Unique4185 ?
Unique (%)86.6%

Sample

1st row053 4740898
2nd row053 7542204
3rd row053 2540481
4th row053 5840629
5th row3247686
ValueCountFrequency (%)
053 3905
34.6%
070 155
 
1.4%
02 44
 
0.4%
621 34
 
0.3%
741 31
 
0.3%
753 28
 
0.2%
791 28
 
0.2%
752 26
 
0.2%
781 24
 
0.2%
745 24
 
0.2%
Other values (4436) 7003
62.0%
2024-04-18T11:12:57.810153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 8753
16.2%
0 7627
14.2%
3 7575
14.1%
6532
12.1%
2 4241
7.9%
7 3894
7.2%
6 3627
6.7%
4 3099
 
5.8%
8 2972
 
5.5%
1 2940
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47354
87.9%
Space Separator 6532
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 8753
18.5%
0 7627
16.1%
3 7575
16.0%
2 4241
9.0%
7 3894
8.2%
6 3627
7.7%
4 3099
 
6.5%
8 2972
 
6.3%
1 2940
 
6.2%
9 2626
 
5.5%
Space Separator
ValueCountFrequency (%)
6532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 8753
16.2%
0 7627
14.2%
3 7575
14.1%
6532
12.1%
2 4241
7.9%
7 3894
7.2%
6 3627
6.7%
4 3099
 
5.8%
8 2972
 
5.5%
1 2940
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 8753
16.2%
0 7627
14.2%
3 7575
14.1%
6532
12.1%
2 4241
7.9%
7 3894
7.2%
6 3627
6.7%
4 3099
 
5.8%
8 2972
 
5.5%
1 2940
 
5.5%

소재지면적
Text

MISSING 

Distinct1752
Distinct (%)29.5%
Missing4051
Missing (%)40.5%
Memory size156.2 KiB
2024-04-18T11:12:58.125026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.4552026
Min length3

Characters and Unicode

Total characters26504
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

Unique1317 ?
Unique (%)22.1%

Sample

1st row100.00
2nd row150.48
3rd row77.40
4th row3.00
5th row23.14
ValueCountFrequency (%)
3.30 746
 
12.5%
00 508
 
8.5%
3.00 400
 
6.7%
1.00 307
 
5.2%
2.00 202
 
3.4%
6.00 135
 
2.3%
4.00 91
 
1.5%
6.60 87
 
1.5%
33.00 72
 
1.2%
30.00 65
 
1.1%
Other values (1742) 3336
56.1%
2024-04-18T11:12:58.541782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7961
30.0%
. 5949
22.4%
3 3048
 
11.5%
1 1850
 
7.0%
2 1762
 
6.6%
6 1298
 
4.9%
5 1209
 
4.6%
4 1083
 
4.1%
8 865
 
3.3%
9 775
 
2.9%
Other values (2) 704
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20551
77.5%
Other Punctuation 5953
 
22.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7961
38.7%
3 3048
 
14.8%
1 1850
 
9.0%
2 1762
 
8.6%
6 1298
 
6.3%
5 1209
 
5.9%
4 1083
 
5.3%
8 865
 
4.2%
9 775
 
3.8%
7 700
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 5949
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 26504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7961
30.0%
. 5949
22.4%
3 3048
 
11.5%
1 1850
 
7.0%
2 1762
 
6.6%
6 1298
 
4.9%
5 1209
 
4.6%
4 1083
 
4.1%
8 865
 
3.3%
9 775
 
2.9%
Other values (2) 704
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7961
30.0%
. 5949
22.4%
3 3048
 
11.5%
1 1850
 
7.0%
2 1762
 
6.6%
6 1298
 
4.9%
5 1209
 
4.6%
4 1083
 
4.1%
8 865
 
3.3%
9 775
 
2.9%
Other values (2) 704
 
2.7%

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct935
Distinct (%)9.4%
Missing105
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean704258.92
Minimum136821
Maximum718801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:12:58.659512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum136821
5-th percentile700802
Q1702746
median704722
Q3705829
95-th percentile706948
Maximum718801
Range581980
Interquartile range (IQR)3083

Descriptive statistics

Standard deviation6944.1465
Coefficient of variation (CV)0.009860218
Kurtosis4851.1237
Mean704258.92
Median Absolute Deviation (MAD)1887
Skewness-63.131788
Sum6.968642 × 109
Variance48221170
MonotonicityNot monotonic
2024-04-18T11:12:58.758934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
706170 145
 
1.5%
704080 109
 
1.1%
702886 97
 
1.0%
704060 88
 
0.9%
701847 77
 
0.8%
711812 69
 
0.7%
704834 69
 
0.7%
704808 63
 
0.6%
702807 62
 
0.6%
700412 62
 
0.6%
Other values (925) 9054
90.5%
(Missing) 105
 
1.1%
ValueCountFrequency (%)
136821 1
 
< 0.1%
405835 1
 
< 0.1%
700010 21
0.2%
700020 6
 
0.1%
700030 1
 
< 0.1%
700040 7
 
0.1%
700050 1
 
< 0.1%
700060 6
 
0.1%
700070 45
0.4%
700081 2
 
< 0.1%
ValueCountFrequency (%)
718801 1
 
< 0.1%
711892 1
 
< 0.1%
711891 26
0.3%
711874 8
 
0.1%
711873 4
 
< 0.1%
711872 5
 
0.1%
711871 3
 
< 0.1%
711864 11
0.1%
711863 2
 
< 0.1%
711862 5
 
0.1%
Distinct4799
Distinct (%)48.0%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-18T11:12:59.019732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length48
Mean length27.185674
Min length15

Characters and Unicode

Total characters271748
Distinct characters494
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3606 ?
Unique (%)36.1%

Sample

1st row대구광역시 서구 비산동 ***-*번지 ,*층
2nd row대구광역시 동구 봉무동 ****-*번지
3rd row대구광역시 중구 봉산동 ****-**** 메트로프라자 F***호
4th row대구광역시 남구 대명동 ****-**번지
5th row대구광역시 수성구 범어동 ***번지 장원맨션 ***동 ****호
ValueCountFrequency (%)
대구광역시 9993
19.7%
번지 7766
15.3%
2466
 
4.9%
달서구 2214
 
4.4%
2032
 
4.0%
수성구 1857
 
3.7%
북구 1695
 
3.3%
동구 1387
 
2.7%
1339
 
2.6%
1130
 
2.2%
Other values (2445) 18765
37.1%
2024-04-18T11:12:59.428768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 60943
22.4%
49048
18.0%
19835
 
7.3%
12915
 
4.8%
11345
 
4.2%
10282
 
3.8%
10071
 
3.7%
10048
 
3.7%
9757
 
3.6%
7769
 
2.9%
Other values (484) 69735
25.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151514
55.8%
Other Punctuation 61156
22.5%
Space Separator 49048
 
18.0%
Dash Punctuation 7587
 
2.8%
Open Punctuation 968
 
0.4%
Close Punctuation 968
 
0.4%
Uppercase Letter 432
 
0.2%
Lowercase Letter 59
 
< 0.1%
Math Symbol 14
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19835
 
13.1%
12915
 
8.5%
11345
 
7.5%
10282
 
6.8%
10071
 
6.6%
10048
 
6.6%
9757
 
6.4%
7769
 
5.1%
3817
 
2.5%
3386
 
2.2%
Other values (436) 52289
34.5%
Uppercase Letter
ValueCountFrequency (%)
A 139
32.2%
B 57
13.2%
P 33
 
7.6%
T 33
 
7.6%
C 30
 
6.9%
S 25
 
5.8%
K 16
 
3.7%
L 16
 
3.7%
H 15
 
3.5%
M 12
 
2.8%
Other values (14) 56
13.0%
Lowercase Letter
ValueCountFrequency (%)
e 47
79.7%
s 2
 
3.4%
a 2
 
3.4%
w 1
 
1.7%
m 1
 
1.7%
o 1
 
1.7%
p 1
 
1.7%
u 1
 
1.7%
l 1
 
1.7%
k 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
* 60943
99.7%
, 131
 
0.2%
. 46
 
0.1%
/ 29
 
< 0.1%
@ 6
 
< 0.1%
· 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
49048
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7587
100.0%
Open Punctuation
ValueCountFrequency (%)
( 968
100.0%
Close Punctuation
ValueCountFrequency (%)
) 968
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151515
55.8%
Common 119742
44.1%
Latin 491
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19835
 
13.1%
12915
 
8.5%
11345
 
7.5%
10282
 
6.8%
10071
 
6.6%
10048
 
6.6%
9757
 
6.4%
7769
 
5.1%
3817
 
2.5%
3386
 
2.2%
Other values (437) 52290
34.5%
Latin
ValueCountFrequency (%)
A 139
28.3%
B 57
11.6%
e 47
 
9.6%
P 33
 
6.7%
T 33
 
6.7%
C 30
 
6.1%
S 25
 
5.1%
K 16
 
3.3%
L 16
 
3.3%
H 15
 
3.1%
Other values (25) 80
16.3%
Common
ValueCountFrequency (%)
* 60943
50.9%
49048
41.0%
- 7587
 
6.3%
( 968
 
0.8%
) 968
 
0.8%
, 131
 
0.1%
. 46
 
< 0.1%
/ 29
 
< 0.1%
~ 14
 
< 0.1%
@ 6
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151514
55.8%
ASCII 120232
44.2%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 60943
50.7%
49048
40.8%
- 7587
 
6.3%
( 968
 
0.8%
) 968
 
0.8%
A 139
 
0.1%
, 131
 
0.1%
B 57
 
< 0.1%
e 47
 
< 0.1%
. 46
 
< 0.1%
Other values (36) 298
 
0.2%
Hangul
ValueCountFrequency (%)
19835
 
13.1%
12915
 
8.5%
11345
 
7.5%
10282
 
6.8%
10071
 
6.6%
10048
 
6.6%
9757
 
6.4%
7769
 
5.1%
3817
 
2.5%
3386
 
2.2%
Other values (436) 52289
34.5%
None
ValueCountFrequency (%)
1
50.0%
· 1
50.0%

도로명전체주소
Text

MISSING 

Distinct5869
Distinct (%)73.2%
Missing1983
Missing (%)19.8%
Memory size156.2 KiB
2024-04-18T11:12:59.677084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length54
Mean length32.814145
Min length20

Characters and Unicode

Total characters263071
Distinct characters514
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

Unique4741 ?
Unique (%)59.1%

Sample

1st row대구광역시 서구 북비산로**길 *, *층 (비산동)
2nd row대구광역시 동구 팔공로**길 **, *층 ***호 (봉무동)
3rd row대구광역시 중구 달구벌대로 지하 ****, 메트로프라자 F***호 (봉산동)
4th row대구광역시 남구 중앙대로**길 ** (대명동)
5th row대구광역시 남구 삼정*길 **-*, *층 (봉덕동)
ValueCountFrequency (%)
8072
 
15.7%
대구광역시 8014
 
15.6%
2966
 
5.8%
2736
 
5.3%
달서구 1770
 
3.4%
1681
 
3.3%
수성구 1484
 
2.9%
북구 1436
 
2.8%
동구 1148
 
2.2%
중구 651
 
1.3%
Other values (3268) 21453
41.7%
2024-04-18T11:13:00.062326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 46737
17.8%
43401
16.5%
16976
 
6.5%
12249
 
4.7%
10658
 
4.1%
8344
 
3.2%
, 8258
 
3.1%
( 8176
 
3.1%
) 8176
 
3.1%
8166
 
3.1%
Other values (504) 91930
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146358
55.6%
Other Punctuation 55032
 
20.9%
Space Separator 43401
 
16.5%
Open Punctuation 8176
 
3.1%
Close Punctuation 8176
 
3.1%
Dash Punctuation 1424
 
0.5%
Uppercase Letter 411
 
0.2%
Lowercase Letter 68
 
< 0.1%
Math Symbol 24
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16976
 
11.6%
12249
 
8.4%
10658
 
7.3%
8344
 
5.7%
8166
 
5.6%
8057
 
5.5%
7947
 
5.4%
4078
 
2.8%
3659
 
2.5%
3498
 
2.4%
Other values (455) 62726
42.9%
Uppercase Letter
ValueCountFrequency (%)
A 111
27.0%
B 64
15.6%
C 38
 
9.2%
S 29
 
7.1%
T 21
 
5.1%
P 19
 
4.6%
K 18
 
4.4%
L 15
 
3.6%
H 13
 
3.2%
E 13
 
3.2%
Other values (14) 70
17.0%
Lowercase Letter
ValueCountFrequency (%)
e 52
76.5%
s 2
 
2.9%
l 2
 
2.9%
p 2
 
2.9%
m 2
 
2.9%
o 2
 
2.9%
w 1
 
1.5%
u 1
 
1.5%
c 1
 
1.5%
a 1
 
1.5%
Other values (2) 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
* 46737
84.9%
, 8258
 
15.0%
. 19
 
< 0.1%
/ 12
 
< 0.1%
@ 3
 
< 0.1%
· 2
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
43401
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1424
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146359
55.6%
Common 116233
44.2%
Latin 479
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16976
 
11.6%
12249
 
8.4%
10658
 
7.3%
8344
 
5.7%
8166
 
5.6%
8057
 
5.5%
7947
 
5.4%
4078
 
2.8%
3659
 
2.5%
3498
 
2.4%
Other values (456) 62727
42.9%
Latin
ValueCountFrequency (%)
A 111
23.2%
B 64
13.4%
e 52
10.9%
C 38
 
7.9%
S 29
 
6.1%
T 21
 
4.4%
P 19
 
4.0%
K 18
 
3.8%
L 15
 
3.1%
H 13
 
2.7%
Other values (26) 99
20.7%
Common
ValueCountFrequency (%)
* 46737
40.2%
43401
37.3%
, 8258
 
7.1%
( 8176
 
7.0%
) 8176
 
7.0%
- 1424
 
1.2%
~ 24
 
< 0.1%
. 19
 
< 0.1%
/ 12
 
< 0.1%
@ 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146358
55.6%
ASCII 116710
44.4%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 46737
40.0%
43401
37.2%
, 8258
 
7.1%
( 8176
 
7.0%
) 8176
 
7.0%
- 1424
 
1.2%
A 111
 
0.1%
B 64
 
0.1%
e 52
 
< 0.1%
C 38
 
< 0.1%
Other values (37) 273
 
0.2%
Hangul
ValueCountFrequency (%)
16976
 
11.6%
12249
 
8.4%
10658
 
7.3%
8344
 
5.7%
8166
 
5.6%
8057
 
5.5%
7947
 
5.4%
4078
 
2.8%
3659
 
2.5%
3498
 
2.4%
Other values (455) 62726
42.9%
None
ValueCountFrequency (%)
· 2
66.7%
1
33.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1320
Distinct (%)16.6%
Missing2045
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean42038.196
Minimum2836
Maximum43020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:00.175815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2836
5-th percentile41114
Q141519
median42052
Q342627
95-th percentile42915
Maximum43020
Range40184
Interquartile range (IQR)1108

Descriptive statistics

Standard deviation766.06887
Coefficient of variation (CV)0.018223162
Kurtosis924.58878
Mean42038.196
Median Absolute Deviation (MAD)564
Skewness-19.27231
Sum3.3441385 × 108
Variance586861.52
MonotonicityNot monotonic
2024-04-18T11:13:00.289427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41940 48
 
0.5%
41423 44
 
0.4%
41936 37
 
0.4%
41438 34
 
0.3%
41519 31
 
0.3%
42612 30
 
0.3%
41229 30
 
0.3%
42781 30
 
0.3%
42028 28
 
0.3%
41535 28
 
0.3%
Other values (1310) 7615
76.1%
(Missing) 2045
 
20.4%
ValueCountFrequency (%)
2836 1
 
< 0.1%
21565 1
 
< 0.1%
39894 1
 
< 0.1%
41000 1
 
< 0.1%
41001 3
 
< 0.1%
41002 10
0.1%
41003 4
 
< 0.1%
41005 18
0.2%
41006 2
 
< 0.1%
41007 3
 
< 0.1%
ValueCountFrequency (%)
43020 1
 
< 0.1%
43019 9
0.1%
43018 10
0.1%
43017 11
0.1%
43016 12
0.1%
43015 6
0.1%
43014 5
0.1%
43013 4
 
< 0.1%
43012 1
 
< 0.1%
43010 1
 
< 0.1%
Distinct8403
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T11:13:01.038174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length27
Mean length6.9166
Min length1

Characters and Unicode

Total characters69166
Distinct characters906
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7722 ?
Unique (%)77.2%

Sample

1st row윤은정허브다이어트
2nd row핏앤다이어트
3rd row씨네손
4th row남부
5th rowJU 네트워크
ValueCountFrequency (%)
허브다이어트 115
 
1.0%
주식회사 78
 
0.7%
한국암웨이 64
 
0.6%
애터미 55
 
0.5%
아모레퍼시픽 54
 
0.5%
지에스(gs)25 46
 
0.4%
아리따움 45
 
0.4%
에이다넷 40
 
0.4%
아모레 38
 
0.3%
제이유네트워크 34
 
0.3%
Other values (8682) 10750
95.0%
2024-04-18T11:13:01.349334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2756
 
4.0%
1636
 
2.4%
1567
 
2.3%
) 1499
 
2.2%
( 1487
 
2.1%
1322
 
1.9%
1250
 
1.8%
1220
 
1.8%
1056
 
1.5%
1031
 
1.5%
Other values (896) 54342
78.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60497
87.5%
Uppercase Letter 1716
 
2.5%
Close Punctuation 1500
 
2.2%
Open Punctuation 1488
 
2.2%
Decimal Number 1354
 
2.0%
Space Separator 1322
 
1.9%
Lowercase Letter 1122
 
1.6%
Other Punctuation 121
 
0.2%
Dash Punctuation 40
 
0.1%
Other Symbol 2
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2756
 
4.6%
1636
 
2.7%
1567
 
2.6%
1250
 
2.1%
1220
 
2.0%
1056
 
1.7%
1031
 
1.7%
1013
 
1.7%
927
 
1.5%
917
 
1.5%
Other values (818) 47124
77.9%
Lowercase Letter
ValueCountFrequency (%)
e 145
12.9%
o 107
 
9.5%
a 75
 
6.7%
i 74
 
6.6%
n 73
 
6.5%
t 70
 
6.2%
r 69
 
6.1%
l 67
 
6.0%
h 48
 
4.3%
m 46
 
4.1%
Other values (16) 348
31.0%
Uppercase Letter
ValueCountFrequency (%)
S 282
16.4%
G 230
13.4%
O 127
 
7.4%
I 116
 
6.8%
C 110
 
6.4%
B 106
 
6.2%
N 78
 
4.5%
T 64
 
3.7%
E 64
 
3.7%
H 63
 
3.7%
Other values (15) 476
27.7%
Decimal Number
ValueCountFrequency (%)
4 571
42.2%
2 287
21.2%
5 257
19.0%
1 76
 
5.6%
3 47
 
3.5%
0 38
 
2.8%
8 33
 
2.4%
6 16
 
1.2%
9 16
 
1.2%
7 13
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 51
42.1%
& 42
34.7%
, 16
 
13.2%
/ 5
 
4.1%
' 4
 
3.3%
! 2
 
1.7%
: 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 1499
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1487
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60495
87.5%
Common 5827
 
8.4%
Latin 2840
 
4.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2756
 
4.6%
1636
 
2.7%
1567
 
2.6%
1250
 
2.1%
1220
 
2.0%
1056
 
1.7%
1031
 
1.7%
1013
 
1.7%
927
 
1.5%
917
 
1.5%
Other values (816) 47122
77.9%
Latin
ValueCountFrequency (%)
S 282
 
9.9%
G 230
 
8.1%
e 145
 
5.1%
O 127
 
4.5%
I 116
 
4.1%
C 110
 
3.9%
o 107
 
3.8%
B 106
 
3.7%
N 78
 
2.7%
a 75
 
2.6%
Other values (42) 1464
51.5%
Common
ValueCountFrequency (%)
) 1499
25.7%
( 1487
25.5%
1322
22.7%
4 571
 
9.8%
2 287
 
4.9%
5 257
 
4.4%
1 76
 
1.3%
. 51
 
0.9%
3 47
 
0.8%
& 42
 
0.7%
Other values (15) 188
 
3.2%
Han
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60493
87.5%
ASCII 8665
 
12.5%
CJK 4
 
< 0.1%
None 2
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2756
 
4.6%
1636
 
2.7%
1567
 
2.6%
1250
 
2.1%
1220
 
2.0%
1056
 
1.7%
1031
 
1.7%
1013
 
1.7%
927
 
1.5%
917
 
1.5%
Other values (815) 47120
77.9%
ASCII
ValueCountFrequency (%)
) 1499
17.3%
( 1487
17.2%
1322
15.3%
4 571
 
6.6%
2 287
 
3.3%
S 282
 
3.3%
5 257
 
3.0%
G 230
 
2.7%
e 145
 
1.7%
O 127
 
1.5%
Other values (66) 2458
28.4%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Number Forms
ValueCountFrequency (%)
2
100.0%

최종수정시점
Real number (ℝ)

Distinct9270
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0151711 × 1013
Minimum2.0040324 × 1013
Maximum2.0220428 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:01.467914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0040324 × 1013
5-th percentile2.0041008 × 1013
Q12.0110625 × 1013
median2.0171124 × 1013
Q32.0200222 × 1013
95-th percentile2.021123 × 1013
Maximum2.0220428 × 1013
Range1.8010417 × 1011
Interquartile range (IQR)8.9596753 × 1010

Descriptive statistics

Standard deviation5.4737209 × 1010
Coefficient of variation (CV)0.0027162561
Kurtosis-0.8210942
Mean2.0151711 × 1013
Median Absolute Deviation (MAD)3.9302015 × 1010
Skewness-0.64117884
Sum2.0151711 × 1017
Variance2.996162 × 1021
MonotonicityNot monotonic
2024-04-18T11:13:01.591396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041008000000 74
 
0.7%
20040618000000 26
 
0.3%
20040917000000 20
 
0.2%
20040617000000 19
 
0.2%
20040916000000 17
 
0.2%
20040715000000 15
 
0.1%
20040915000000 14
 
0.1%
20041005000000 14
 
0.1%
20060105000000 13
 
0.1%
20041103000000 12
 
0.1%
Other values (9260) 9776
97.8%
ValueCountFrequency (%)
20040324000000 2
< 0.1%
20040326000000 1
 
< 0.1%
20040401000000 1
 
< 0.1%
20040407000000 1
 
< 0.1%
20040408000000 2
< 0.1%
20040409000000 2
< 0.1%
20040426000000 2
< 0.1%
20040428000000 1
 
< 0.1%
20040429000000 3
< 0.1%
20040503000000 1
 
< 0.1%
ValueCountFrequency (%)
20220428172515 1
< 0.1%
20220428163125 1
< 0.1%
20220428154157 1
< 0.1%
20220428112751 1
< 0.1%
20220427170902 1
< 0.1%
20220427160511 1
< 0.1%
20220427155627 1
< 0.1%
20220427155201 1
< 0.1%
20220427140118 1
< 0.1%
20220427103807 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7066 
U
2934 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7066
70.7%
U 2934
29.3%

Length

2024-04-18T11:13:01.703732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:01.774514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7066
70.7%
u 2934
29.3%
Distinct1344
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-04-30 02:40:00
2024-04-18T11:13:01.855359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T11:13:01.963503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct6613
Distinct (%)67.6%
Missing222
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean343134.86
Minimum174169.07
Maximum358076.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:02.074173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174169.07
5-th percentile334931.57
Q1339628.32
median343223.45
Q3346523.63
95-th percentile353872.53
Maximum358076.66
Range183907.59
Interquartile range (IQR)6895.3079

Descriptive statistics

Standard deviation5746.0451
Coefficient of variation (CV)0.016745734
Kurtosis115.18784
Mean343134.86
Median Absolute Deviation (MAD)3488.3445
Skewness-4.0665085
Sum3.3551727 × 109
Variance33017034
MonotonicityNot monotonic
2024-04-18T11:13:02.184398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
344686.259338 37
 
0.4%
344047.164924 32
 
0.3%
347037.24197 26
 
0.3%
346916.265263 25
 
0.2%
339047.793379 23
 
0.2%
343588.735555 23
 
0.2%
343820.40768 20
 
0.2%
340548.96997 20
 
0.2%
345383.649328 18
 
0.2%
338560.694883 17
 
0.2%
Other values (6603) 9537
95.4%
(Missing) 222
 
2.2%
ValueCountFrequency (%)
174169.067539966 1
 
< 0.1%
200018.855604638 1
 
< 0.1%
325733.855686 1
 
< 0.1%
325937.566452 1
 
< 0.1%
326030.831594512 1
 
< 0.1%
326874.570932 1
 
< 0.1%
327201.005041 1
 
< 0.1%
327655.665337 1
 
< 0.1%
327851.659254 1
 
< 0.1%
327853.173809 5
0.1%
ValueCountFrequency (%)
358076.660234 1
 
< 0.1%
358060.647419 1
 
< 0.1%
357975.880928 1
 
< 0.1%
357934.27702 1
 
< 0.1%
357933.237729 1
 
< 0.1%
357916.122672 1
 
< 0.1%
357646.727978 3
< 0.1%
357073.974572 1
 
< 0.1%
356923.487472 1
 
< 0.1%
356698.367083 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct6611
Distinct (%)67.6%
Missing222
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean263389.46
Minimum237059.21
Maximum454580.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:02.297554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum237059.21
5-th percentile257612.35
Q1261213.05
median263314.57
Q3265337.33
95-th percentile271540.19
Maximum454580.8
Range217521.59
Interquartile range (IQR)4124.2748

Descriptive statistics

Standard deviation5135.3486
Coefficient of variation (CV)0.019497168
Kurtosis337.73744
Mean263389.46
Median Absolute Deviation (MAD)2069.1559
Skewness8.8184105
Sum2.5754221 × 109
Variance26371806
MonotonicityNot monotonic
2024-04-18T11:13:02.400594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263958.880864 37
 
0.4%
265132.987974 32
 
0.3%
265407.404337 26
 
0.3%
263443.713906 25
 
0.2%
264119.01075 23
 
0.2%
258741.90218 23
 
0.2%
264018.87607 20
 
0.2%
272470.830195 20
 
0.2%
267901.294823 18
 
0.2%
261656.240623 17
 
0.2%
Other values (6601) 9537
95.4%
(Missing) 222
 
2.2%
ValueCountFrequency (%)
237059.208299 1
 
< 0.1%
238029.007127 1
 
< 0.1%
238126.933814 2
 
< 0.1%
239311.580853 1
 
< 0.1%
240182.187266 1
 
< 0.1%
240204.92864 1
 
< 0.1%
240248.646376 1
 
< 0.1%
240270.873923 2
 
< 0.1%
240358.722944 5
0.1%
240365.71605 1
 
< 0.1%
ValueCountFrequency (%)
454580.797415934 1
< 0.1%
438974.350322758 1
< 0.1%
278042.64925 2
< 0.1%
277923.610317 1
< 0.1%
277799.708684 2
< 0.1%
277784.134758 1
< 0.1%
277759.213877 1
< 0.1%
277749.024029 1
< 0.1%
277718.159532176 1
< 0.1%
276945.373485 2
< 0.1%

위생업태명
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업장판매
4869 
전자상거래(통신판매업)
2029 
방문판매
1253 
통신판매
1124 
다단계판매
627 
Other values (5)
 
98

Length

Max length14
Median length5
Mean length6.2221
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업장판매
2nd row영업장판매
3rd row전자상거래(통신판매업)
4th row영업장판매
5th row다단계판매

Common Values

ValueCountFrequency (%)
영업장판매 4869
48.7%
전자상거래(통신판매업) 2029
20.3%
방문판매 1253
 
12.5%
통신판매 1124
 
11.2%
다단계판매 627
 
6.3%
기타(복합 등) 33
 
0.3%
도매업(유통) 27
 
0.3%
기타 건강기능식품일반판매업 26
 
0.3%
전화권유판매 10
 
0.1%
<NA> 2
 
< 0.1%

Length

2024-04-18T11:13:02.510599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:02.604761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업장판매 4869
48.4%
전자상거래(통신판매업 2029
20.2%
방문판매 1253
 
12.5%
통신판매 1124
 
11.2%
다단계판매 627
 
6.2%
기타(복합 33
 
0.3%
33
 
0.3%
도매업(유통 27
 
0.3%
기타 26
 
0.3%
건강기능식품일반판매업 26
 
0.3%
Other values (2) 12
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8969 
0
1031 

Length

Max length4
Median length4
Mean length3.6907
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> 8969
89.7%
0 1031
 
10.3%

Length

2024-04-18T11:13:02.717915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:02.794803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8969
89.7%
0 1031
 
10.3%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8969 
0
1031 

Length

Max length4
Median length4
Mean length3.6907
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> 8969
89.7%
0 1031
 
10.3%

Length

2024-04-18T11:13:02.885434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:02.964491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8969
89.7%
0 1031
 
10.3%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8483 
상수도전용
1510 
간이상수도
 
5
전용상수도(특정시설의 자가용 수도)
 
2

Length

Max length19
Median length4
Mean length4.1545
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8483
84.8%
상수도전용 1510
 
15.1%
간이상수도 5
 
0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%

Length

2024-04-18T11:13:03.048235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:03.146753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8483
84.8%
상수도전용 1510
 
15.1%
간이상수도 5
 
< 0.1%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8983 
0
1017 

Length

Max length4
Median length4
Mean length3.6949
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> 8983
89.8%
0 1017
 
10.2%

Length

2024-04-18T11:13:03.241907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:03.323011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8983
89.8%
0 1017
 
10.2%

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.1%
Missing3828
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.0082631238
Minimum0
Maximum6
Zeros6139
Zeros (%)61.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:03.387441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.13978395
Coefficient of variation (CV)16.916599
Kurtosis812.23392
Mean0.0082631238
Median Absolute Deviation (MAD)0
Skewness25.283109
Sum51
Variance0.019539553
MonotonicityNot monotonic
2024-04-18T11:13:03.466548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 6139
61.4%
1 25
 
0.2%
3 4
 
< 0.1%
2 2
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 3828
38.3%
ValueCountFrequency (%)
0 6139
61.4%
1 25
 
0.2%
2 2
 
< 0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
4 1
 
< 0.1%
3 4
 
< 0.1%
2 2
 
< 0.1%
1 25
 
0.2%
0 6139
61.4%

공장사무직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct13
Distinct (%)0.2%
Missing3827
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.071116151
Minimum0
Maximum23
Zeros5952
Zeros (%)59.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:03.553067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.73229591
Coefficient of variation (CV)10.297181
Kurtosis622.31367
Mean0.071116151
Median Absolute Deviation (MAD)0
Skewness23.049825
Sum439
Variance0.53625729
MonotonicityNot monotonic
2024-04-18T11:13:03.634838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 5952
59.5%
1 168
 
1.7%
2 25
 
0.2%
3 9
 
0.1%
4 7
 
0.1%
5 3
 
< 0.1%
21 2
 
< 0.1%
17 2
 
< 0.1%
22 1
 
< 0.1%
6 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 3827
38.3%
ValueCountFrequency (%)
0 5952
59.5%
1 168
 
1.7%
2 25
 
0.2%
3 9
 
0.1%
4 7
 
0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
14 1
 
< 0.1%
17 2
 
< 0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
21 2
 
< 0.1%
17 2
 
< 0.1%
14 1
 
< 0.1%
10 1
 
< 0.1%
6 1
 
< 0.1%
5 3
 
< 0.1%
4 7
0.1%
3 9
0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct28
Distinct (%)0.5%
Missing3826
Missing (%)38.3%
Infinite0
Infinite (%)0.0%
Mean0.37463557
Minimum0
Maximum100
Zeros5452
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:03.732328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.6236455
Coefficient of variation (CV)9.6724544
Kurtosis482.79645
Mean0.37463557
Median Absolute Deviation (MAD)0
Skewness20.508075
Sum2313
Variance13.130806
MonotonicityNot monotonic
2024-04-18T11:13:03.831654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 5452
54.5%
1 562
 
5.6%
2 57
 
0.6%
3 33
 
0.3%
5 10
 
0.1%
4 9
 
0.1%
7 7
 
0.1%
10 7
 
0.1%
6 5
 
0.1%
20 4
 
< 0.1%
Other values (18) 28
 
0.3%
(Missing) 3826
38.3%
ValueCountFrequency (%)
0 5452
54.5%
1 562
 
5.6%
2 57
 
0.6%
3 33
 
0.3%
4 9
 
0.1%
5 10
 
0.1%
6 5
 
0.1%
7 7
 
0.1%
9 1
 
< 0.1%
10 7
 
0.1%
ValueCountFrequency (%)
100 2
< 0.1%
94 3
< 0.1%
80 1
 
< 0.1%
58 1
 
< 0.1%
54 1
 
< 0.1%
52 1
 
< 0.1%
50 1
 
< 0.1%
45 2
< 0.1%
40 1
 
< 0.1%
36 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6168 
<NA>
3827 
1
 
3
9
 
1
30
 
1

Length

Max length4
Median length1
Mean length2.1482
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6168
61.7%
<NA> 3827
38.3%
1 3
 
< 0.1%
9 1
 
< 0.1%
30 1
 
< 0.1%

Length

2024-04-18T11:13:03.939233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:04.023045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6168
61.7%
na 3827
38.3%
1 3
 
< 0.1%
9 1
 
< 0.1%
30 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8281 
임대
884 
자가
835 

Length

Max length4
Median length4
Mean length3.6562
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8281
82.8%
임대 884
 
8.8%
자가 835
 
8.3%

Length

2024-04-18T11:13:04.120249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:13:04.202404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8281
82.8%
임대 884
 
8.8%
자가 835
 
8.3%

보증액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.7%
Missing8942
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean122873.82
Minimum0
Maximum1 × 108
Zeros1051
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:04.276116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1 × 108
Range1 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3106745.8
Coefficient of variation (CV)25.284034
Kurtosis1013.4621
Mean122873.82
Median Absolute Deviation (MAD)0
Skewness31.547382
Sum1.300005 × 108
Variance9.6518698 × 1012
MonotonicityNot monotonic
2024-04-18T11:13:04.364544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1051
 
10.5%
5000000 2
 
< 0.1%
500 1
 
< 0.1%
100000000 1
 
< 0.1%
2000000 1
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%
(Missing) 8942
89.4%
ValueCountFrequency (%)
0 1051
10.5%
500 1
 
< 0.1%
2000000 1
 
< 0.1%
5000000 2
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%
100000000 1
 
< 0.1%
ValueCountFrequency (%)
100000000 1
 
< 0.1%
10000000 1
 
< 0.1%
8000000 1
 
< 0.1%
5000000 2
 
< 0.1%
2000000 1
 
< 0.1%
500 1
 
< 0.1%
0 1051
10.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.7%
Missing8941
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean3238.9424
Minimum0
Maximum1000000
Zeros1051
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:04.452238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation48060.594
Coefficient of variation (CV)14.83836
Kurtosis317.8302
Mean3238.9424
Median Absolute Deviation (MAD)0
Skewness17.382124
Sum3430040
Variance2.3098207 × 109
MonotonicityNot monotonic
2024-04-18T11:13:04.546046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1051
 
10.5%
200000 2
 
< 0.1%
800000 2
 
< 0.1%
40 1
 
< 0.1%
1000000 1
 
< 0.1%
180000 1
 
< 0.1%
250000 1
 
< 0.1%
(Missing) 8941
89.4%
ValueCountFrequency (%)
0 1051
10.5%
40 1
 
< 0.1%
180000 1
 
< 0.1%
200000 2
 
< 0.1%
250000 1
 
< 0.1%
800000 2
 
< 0.1%
1000000 1
 
< 0.1%
ValueCountFrequency (%)
1000000 1
 
< 0.1%
800000 2
 
< 0.1%
250000 1
 
< 0.1%
200000 2
 
< 0.1%
180000 1
 
< 0.1%
40 1
 
< 0.1%
0 1051
10.5%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size97.7 KiB
False
9998 
(Missing)
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
(Missing) 2
 
< 0.1%
2024-04-18T11:13:04.634195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct113
Distinct (%)1.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.72869474
Minimum0
Maximum879.51
Zeros9858
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T11:13:04.734386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum879.51
Range879.51
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.936301
Coefficient of variation (CV)17.752703
Kurtosis2331.2996
Mean0.72869474
Median Absolute Deviation (MAD)0
Skewness40.647759
Sum7285.49
Variance167.34789
MonotonicityNot monotonic
2024-04-18T11:13:04.842650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9858
98.6%
10.0 8
 
0.1%
3.3 5
 
0.1%
15.0 3
 
< 0.1%
20.0 3
 
< 0.1%
30.0 3
 
< 0.1%
3.0 3
 
< 0.1%
0.9 2
 
< 0.1%
13.2 2
 
< 0.1%
8.64 2
 
< 0.1%
Other values (103) 109
 
1.1%
ValueCountFrequency (%)
0.0 9858
98.6%
0.9 2
 
< 0.1%
0.96 1
 
< 0.1%
1.0 2
 
< 0.1%
1.5 1
 
< 0.1%
2.0 1
 
< 0.1%
2.75 1
 
< 0.1%
3.0 3
 
< 0.1%
3.12 1
 
< 0.1%
3.18 1
 
< 0.1%
ValueCountFrequency (%)
879.51 1
< 0.1%
407.45 1
< 0.1%
312.0 1
< 0.1%
250.98 1
< 0.1%
243.96 1
< 0.1%
232.51 1
< 0.1%
232.4 1
< 0.1%
196.48 1
< 0.1%
190.0 1
< 0.1%
162.48 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Text

MISSING 

Distinct24
Distinct (%)88.9%
Missing9973
Missing (%)99.7%
Memory size156.2 KiB
2024-04-18T11:13:05.000386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length19
Mean length15.925926
Min length4

Characters and Unicode

Total characters430
Distinct characters50
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)81.5%

Sample

1st rowwww.44mycong.com
2nd row옥션 등 오픈마켓
3rd rowwww.herfamilly.co.kr
4th row오픈마켓(옥션, 지마켓)
5th rowwww.muse44.com
ValueCountFrequency (%)
오픈마켓 5
 
14.7%
옥션 2
 
5.9%
2
 
5.9%
www.muse44.com 2
 
5.9%
www.nalssin-girl.com 1
 
2.9%
https://smartstore.naver.com/beautysmile 1
 
2.9%
www.makelifebetter.co.kr 1
 
2.9%
www.ppeyo-kong.com 1
 
2.9%
운영 1
 
2.9%
위탁 1
 
2.9%
Other values (17) 17
50.0%
2024-04-18T11:13:05.292327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 54
 
12.6%
. 43
 
10.0%
o 35
 
8.1%
m 26
 
6.0%
c 24
 
5.6%
e 20
 
4.7%
l 17
 
4.0%
r 16
 
3.7%
a 14
 
3.3%
s 14
 
3.3%
Other values (40) 167
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 307
71.4%
Other Punctuation 52
 
12.1%
Other Letter 41
 
9.5%
Decimal Number 16
 
3.7%
Space Separator 7
 
1.6%
Dash Punctuation 5
 
1.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 54
17.6%
o 35
11.4%
m 26
 
8.5%
c 24
 
7.8%
e 20
 
6.5%
l 17
 
5.5%
r 16
 
5.2%
a 14
 
4.6%
s 14
 
4.6%
t 14
 
4.6%
Other values (15) 73
23.8%
Other Letter
ValueCountFrequency (%)
7
17.1%
7
17.1%
6
14.6%
6
14.6%
3
7.3%
3
7.3%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (4) 4
9.8%
Other Punctuation
ValueCountFrequency (%)
. 43
82.7%
/ 5
 
9.6%
: 2
 
3.8%
, 2
 
3.8%
Decimal Number
ValueCountFrequency (%)
4 11
68.8%
1 3
 
18.8%
0 2
 
12.5%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 307
71.4%
Common 82
 
19.1%
Hangul 41
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 54
17.6%
o 35
11.4%
m 26
 
8.5%
c 24
 
7.8%
e 20
 
6.5%
l 17
 
5.5%
r 16
 
5.2%
a 14
 
4.6%
s 14
 
4.6%
t 14
 
4.6%
Other values (15) 73
23.8%
Hangul
ValueCountFrequency (%)
7
17.1%
7
17.1%
6
14.6%
6
14.6%
3
7.3%
3
7.3%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (4) 4
9.8%
Common
ValueCountFrequency (%)
. 43
52.4%
4 11
 
13.4%
7
 
8.5%
/ 5
 
6.1%
- 5
 
6.1%
1 3
 
3.7%
: 2
 
2.4%
0 2
 
2.4%
, 2
 
2.4%
) 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 389
90.5%
Hangul 41
 
9.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 54
13.9%
. 43
 
11.1%
o 35
 
9.0%
m 26
 
6.7%
c 24
 
6.2%
e 20
 
5.1%
l 17
 
4.4%
r 16
 
4.1%
a 14
 
3.6%
s 14
 
3.6%
Other values (26) 126
32.4%
Hangul
ValueCountFrequency (%)
7
17.1%
7
17.1%
6
14.6%
6
14.6%
3
7.3%
3
7.3%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (4) 4
9.8%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
36253626건강기능식품일반판매업07_22_03_P34300003430000-134-2014-0004720140919<NA>3폐업2폐업20151118<NA><NA><NA><NA>100.00703040대구광역시 서구 비산동 ***-*번지 ,*층대구광역시 서구 북비산로**길 *, *층 (비산동)41745윤은정허브다이어트20140919101200I2018-08-31 23:59:59.0<NA>341590.309702265562.393356영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
27902791건강기능식품일반판매업07_22_03_P34200003420000-134-2019-0000820190122<NA>3폐업2폐업20190725<NA><NA><NA><NA>150.48701170대구광역시 동구 봉무동 ****-*번지대구광역시 동구 팔공로**길 **, *층 ***호 (봉무동)41026핏앤다이어트20190725154200U2019-07-27 02:40:00.0<NA>347834.127148270416.859763영업장판매<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N149.98<NA><NA><NA>
871872건강기능식품일반판매업07_22_03_P34100003410000-134-2020-0003020200529<NA>3폐업2폐업20201216<NA><NA><NA><NA><NA>700823대구광역시 중구 봉산동 ****-**** 메트로프라자 F***호대구광역시 중구 달구벌대로 지하 ****, 메트로프라자 F***호 (봉산동)41959씨네손20201216173051U2020-12-18 02:40:00.0<NA>344083.488663263931.205868전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
52025203건강기능식품일반판매업07_22_03_P34400003440000-134-2005-0001120050217<NA>3폐업2폐업20131024<NA><NA><NA>053 474089877.40705800대구광역시 남구 대명동 ****-**번지대구광역시 남구 중앙대로**길 ** (대명동)42425남부20111124092450I2018-08-31 23:59:59.0<NA>343753.647341262428.675574영업장판매<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
93379338건강기능식품일반판매업07_22_03_P34600003460000-134-2004-0033320040915<NA>3폐업2폐업20070126<NA><NA><NA>053 75422043.00706739대구광역시 수성구 범어동 ***번지 장원맨션 ***동 ****호<NA><NA>JU 네트워크20040915000000I2018-08-31 23:59:59.0<NA>347979.81887262472.171798다단계판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
48104811건강기능식품일반판매업07_22_03_P34400003440000-134-2012-0005220120830<NA>3폐업2폐업20130927<NA><NA><NA><NA>23.14705835대구광역시 남구 봉덕동 ****-*번지대구광역시 남구 삼정*길 **-*, *층 (봉덕동)42505보석콩20130207151926I2018-08-31 23:59:59.0<NA>344028.910576260987.704398영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
12411242건강기능식품일반판매업07_22_03_P34100003410000-134-2019-0001220190227<NA>1영업/정상1영업<NA><NA><NA><NA>053 25404811.00700818대구광역시 중구 대신동 ****번지 지상*층대구광역시 중구 달성로 *, 지상*층 (대신동)41927대한농산20190307170017U2019-03-09 02:40:00.0<NA>342823.541819263962.479035영업장판매<NA><NA><NA><NA><NA><NA>1000<NA><NA><NA>N0.0<NA><NA><NA>
1350013501건강기능식품일반판매업07_22_03_P34700003470000-134-2013-0005720130402<NA>3폐업2폐업20161227<NA><NA><NA>053 58406293.30704801대구광역시 달서구 대천동 ****번지대구광역시 달서구 월암로 ** (대천동)42724지에스(GS)25 달서대천점20130410140836I2018-08-31 23:59:59.0<NA>336689.553767259322.362085영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
18481849건강기능식품일반판매업07_22_03_P34200003420000-134-2012-0002220120307<NA>3폐업2폐업20131220<NA><NA><NA><NA>28.80701831대구광역시 동구 신천동 ***-**번지대구광역시 동구 신암로**길 **, ***동 *층 *호 (신천동, 신천가람타운 상가)41204건강한 아침20120613144118I2018-08-31 23:59:59.0<NA>345313.587319265221.214063영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
61456146건강기능식품일반판매업07_22_03_P34500003450000-134-2004-0035520040728<NA>1영업/정상1영업<NA><NA><NA><NA>32476863.00702847대구광역시 북구 읍내동 ***-*번지대구광역시 북구 동암로 * (읍내동)41433이춘희산부인과의원20140102110854I2018-08-31 23:59:59.0<NA>339950.713879272946.411516영업장판매<NA><NA><NA><NA><NA><NA>0010임대<NA><NA>N0.0<NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
89428943건강기능식품일반판매업07_22_03_P34600003460000-134-2010-0021820101216<NA>3폐업2폐업20110228<NA><NA><NA><NA>42.00706831대구광역시 수성구 수성동*가 ***-*번지 (지하*층)<NA><NA>국제팜코리아20110108123543I2018-08-31 23:59:59.0<NA>345487.625266262844.482035영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1225812259건강기능식품일반판매업07_22_03_P34700003470000-134-2004-0035020040831<NA>3폐업2폐업20070404<NA><NA><NA>053 28413002.00704928대구광역시 달서구 이곡동 ****-*번지 (지상*층)<NA><NA>연세의료기20050304000000I2018-08-31 23:59:59.0<NA>336450.120919262671.180355영업장판매<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
60096010건강기능식품일반판매업07_22_03_P34500003450000-134-2013-0002320130305<NA>1영업/정상1영업<NA><NA><NA><NA>053 355 62893.00702050대구광역시 북구 침산동 ***-*번지대구광역시 북구 침산로 ***, 엠브로타워 주건축물 제*동 *층 ***호 (침산동)41560(주)쿱스토어대구침산점20200422160527U2020-04-24 02:40:00.0<NA>343574.704111266803.737956영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
35753576건강기능식품일반판매업07_22_03_P34300003430000-134-2016-0001920160623<NA>3폐업2폐업20190823<NA><NA><NA><NA><NA>703844대구광역시 서구 평리동 ****-**번지 *층대구광역시 서구 통학로 ***, *층 (평리동)41813이롬황성주생식서구평리정20190823155901U2019-08-25 02:40:00.0<NA>341099.377809264603.402151방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
75647565건강기능식품일반판매업07_22_03_P34500003450000-134-2010-0009420100616<NA>3폐업2폐업20110406<NA><NA><NA><NA><NA>702809대구광역시 북구 노원동*가 *-*번지 *층<NA><NA>신선바이오테크20100616153838I2018-08-31 23:59:59.0<NA>342600.666042266658.982172영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
29432944건강기능식품일반판매업07_22_03_P34200003420000-134-2017-0003320170627<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>701837대구광역시 동구 율하동 ***-*대구광역시 동구 율하동로**길 **, *층 (율하동)41120애터미동구비젼센터20211231161643U2022-01-02 02:40:00.0<NA>353366.44675264669.008498전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
73207321건강기능식품일반판매업07_22_03_P34500003450000-134-2006-0001820060317<NA>3폐업2폐업20181122<NA><NA><NA>053 353964629.70702808대구광역시 북구 구암동 ***-*번지대구광역시 북구 팔거천동로*길 ** (구암동)41465웰빙하우스20181127155058U2018-11-29 02:40:00.0<NA>340003.675279270574.924926통신판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1450014501건강기능식품일반판매업07_22_03_P34700003470000-134-2022-0003920220304<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00704912대구광역시 달서구 본리동 ***-*대구광역시 달서구 당산로 **, 사동 *층 *호 (본리동)42676진안인삼사20220304170821I2022-03-10 13:22:36.0<NA><NA><NA>영업장판매00<NA><NA><NA>00000자가00N0.0<NA><NA><NA>
81788179건강기능식품일반판매업07_22_03_P34500003450000-134-2021-0012420210304<NA>3폐업2폐업20220119<NA><NA><NA><NA><NA>702828대구광역시 북구 복현동 ***-*대구광역시 북구 동북로**길 *, 채진 ***호 (복현동)41529시기20220119100319U2022-01-21 02:40:00.0<NA>346292.316425267185.277518전자상거래(통신판매업)00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
27412742건강기능식품일반판매업07_22_03_P34200003420000-134-2020-0006820200611<NA>3폐업2폐업20210924<NA><NA><NA><NA><NA>701847대구광역시 동구 율하동 **** 미라벨대구광역시 동구 율하동로**길 **-**, 미라벨 *층 (율하동)41102뚜바비앙(Tout va bien)20210924121138U2021-09-26 02:40:00.0<NA>353770.378869263883.874808전자상거래(통신판매업)00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>