Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells134038
Missing cells (%)28.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 MiB
Average record size in memory414.0 B

Variable types

Numeric13
Categorical18
Text6
Unsupported8
DateTime1
Boolean1

Dataset

Description6270000_대구광역시_07_22_10_P_식품자동판매기업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000090910&dataSetDetailId=DDI_0000090934&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
영업장주변구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (51.5%)Imbalance
남성종사자수 is highly imbalanced (93.3%)Imbalance
여성종사자수 is highly imbalanced (95.7%)Imbalance
급수시설구분명 is highly imbalanced (72.6%)Imbalance
총종업원수 is highly imbalanced (95.8%)Imbalance
본사종업원수 is highly imbalanced (52.4%)Imbalance
공장생산직종업원수 is highly imbalanced (53.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1351 (13.5%) 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 2357 (23.6%) missing valuesMissing
소재지면적 has 8058 (80.6%) missing valuesMissing
도로명전체주소 has 6527 (65.3%) missing valuesMissing
도로명우편번호 has 6592 (65.9%) missing valuesMissing
좌표정보(X) has 634 (6.3%) missing valuesMissing
좌표정보(Y) has 634 (6.3%) missing valuesMissing
영업장주변구분명 has 9999 (> 99.9%) missing valuesMissing
등급구분명 has 10000 (100.0%) missing valuesMissing
보증액 has 8912 (89.1%) missing valuesMissing
월세액 has 8913 (89.1%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 21.26090719)Skewed
시설총규모 is highly skewed (γ1 = 73.95936147)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
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 235 (2.4%) zerosZeros
보증액 has 1081 (10.8%) zerosZeros
월세액 has 1081 (10.8%) zerosZeros
시설총규모 has 9893 (98.9%) zerosZeros

Reproduction

Analysis started2024-04-21 19:57:59.373050
Analysis finished2024-04-21 19:58:02.415287
Duration3.04 seconds
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%
Mean5902.9841
Minimum1
Maximum11782
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:02.604286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile592.95
Q12972.5
median5904.5
Q38846.25
95-th percentile11193.05
Maximum11782
Range11781
Interquartile range (IQR)5873.75

Descriptive statistics

Standard deviation3397.7026
Coefficient of variation (CV)0.57559068
Kurtosis-1.1969654
Mean5902.9841
Median Absolute Deviation (MAD)2938
Skewness-0.005546781
Sum59029841
Variance11544383
MonotonicityNot monotonic
2024-04-22T04:58:03.039996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11453 1
 
< 0.1%
8185 1
 
< 0.1%
460 1
 
< 0.1%
8974 1
 
< 0.1%
7637 1
 
< 0.1%
7415 1
 
< 0.1%
2763 1
 
< 0.1%
1481 1
 
< 0.1%
2023 1
 
< 0.1%
4131 1
 
< 0.1%
Other values (9990) 9990
99.9%
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%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
11782 1
< 0.1%
11780 1
< 0.1%
11778 1
< 0.1%
11777 1
< 0.1%
11776 1
< 0.1%
11775 1
< 0.1%
11774 1
< 0.1%
11773 1
< 0.1%
11772 1
< 0.1%
11771 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기업 10000
100.0%

Length

2024-04-22T04:58:03.445763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:03.733403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기업 10000
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
07_22_10_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_10_P
2nd row07_22_10_P
3rd row07_22_10_P
4th row07_22_10_P
5th row07_22_10_P

Common Values

ValueCountFrequency (%)
07_22_10_P 10000
100.0%

Length

2024-04-22T04:58:04.035598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:04.323934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_10_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3446332
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:04.586293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33470000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21119.905
Coefficient of variation (CV)0.006128227
Kurtosis-1.1615399
Mean3446332
Median Absolute Deviation (MAD)20000
Skewness-0.24855309
Sum3.446332 × 1010
Variance4.4605038 × 108
MonotonicityNot monotonic
2024-04-22T04:58:04.949226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2067
20.7%
3450000 1726
17.3%
3460000 1450
14.5%
3420000 1279
12.8%
3430000 1083
10.8%
3440000 967
9.7%
3410000 938
9.4%
3480000 490
 
4.9%
ValueCountFrequency (%)
3410000 938
9.4%
3420000 1279
12.8%
3430000 1083
10.8%
3440000 967
9.7%
3450000 1726
17.3%
3460000 1450
14.5%
3470000 2067
20.7%
3480000 490
 
4.9%
ValueCountFrequency (%)
3480000 490
 
4.9%
3470000 2067
20.7%
3460000 1450
14.5%
3450000 1726
17.3%
3440000 967
9.7%
3430000 1083
10.8%
3420000 1279
12.8%
3410000 938
9.4%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-22T04:58:05.692341image/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 row3480000-112-2002-00004
2nd row3470000-112-2001-00566
3rd row3470000-112-2005-00202
4th row3440000-112-1996-00006
5th row3470000-112-1991-00008
ValueCountFrequency (%)
3480000-112-2002-00004 1
 
< 0.1%
3420000-112-2004-00024 1
 
< 0.1%
3470000-112-2001-00557 1
 
< 0.1%
3470000-112-2010-00012 1
 
< 0.1%
3410000-112-1997-00002 1
 
< 0.1%
3470000-112-2001-00303 1
 
< 0.1%
3460000-112-2002-00105 1
 
< 0.1%
3460000-112-2003-00037 1
 
< 0.1%
3430000-112-2001-00033 1
 
< 0.1%
3460000-112-2001-00064 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-22T04:58:06.785510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86373
39.3%
1 30541
 
13.9%
- 30000
 
13.6%
2 24000
 
10.9%
3 14491
 
6.6%
4 14076
 
6.4%
9 4813
 
2.2%
5 4760
 
2.2%
7 4391
 
2.0%
6 3908
 
1.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86373
45.5%
1 30541
 
16.1%
2 24000
 
12.6%
3 14491
 
7.6%
4 14076
 
7.4%
9 4813
 
2.5%
5 4760
 
2.5%
7 4391
 
2.3%
6 3908
 
2.1%
8 2647
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86373
39.3%
1 30541
 
13.9%
- 30000
 
13.6%
2 24000
 
10.9%
3 14491
 
6.6%
4 14076
 
6.4%
9 4813
 
2.2%
5 4760
 
2.2%
7 4391
 
2.0%
6 3908
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86373
39.3%
1 30541
 
13.9%
- 30000
 
13.6%
2 24000
 
10.9%
3 14491
 
6.6%
4 14076
 
6.4%
9 4813
 
2.2%
5 4760
 
2.2%
7 4391
 
2.0%
6 3908
 
1.8%

인허가일자
Real number (ℝ)

Distinct3446
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20040345
Minimum19841124
Maximum20210830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:07.201280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19841124
5-th percentile19960419
Q120010425
median20020718
Q320060215
95-th percentile20180105
Maximum20210830
Range369706
Interquartile range (IQR)49790

Descriptive statistics

Standard deviation59548.308
Coefficient of variation (CV)0.0029714213
Kurtosis1.0343817
Mean20040345
Median Absolute Deviation (MAD)20004.5
Skewness1.0029288
Sum2.0040345 × 1011
Variance3.5460009 × 109
MonotonicityNot monotonic
2024-04-22T04:58:07.658836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010214 134
 
1.3%
20010302 51
 
0.5%
20000904 47
 
0.5%
20010303 42
 
0.4%
20010710 39
 
0.4%
20010615 39
 
0.4%
20010625 38
 
0.4%
20010709 38
 
0.4%
20010705 37
 
0.4%
20010213 36
 
0.4%
Other values (3436) 9499
95.0%
ValueCountFrequency (%)
19841124 1
< 0.1%
19850116 1
< 0.1%
19850128 1
< 0.1%
19850810 1
< 0.1%
19860123 1
< 0.1%
19880718 1
< 0.1%
19881201 1
< 0.1%
19881202 1
< 0.1%
19881228 1
< 0.1%
19890803 1
< 0.1%
ValueCountFrequency (%)
20210830 1
< 0.1%
20210824 1
< 0.1%
20210819 1
< 0.1%
20210810 1
< 0.1%
20210809 1
< 0.1%
20210804 1
< 0.1%
20210803 1
< 0.1%
20210802 1
< 0.1%
20210730 1
< 0.1%
20210728 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8649 
1
1351 

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 8649
86.5%
1 1351
 
13.5%

Length

2024-04-22T04:58:08.075865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:08.371911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8649
86.5%
1 1351
 
13.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8649 
영업/정상
1351 

Length

Max length5
Median length2
Mean length2.4053
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8649
86.5%
영업/정상 1351
 
13.5%

Length

2024-04-22T04:58:08.730418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:09.047315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8649
86.5%
영업/정상 1351
 
13.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8649 
1
1351 

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 8649
86.5%
1 1351
 
13.5%

Length

2024-04-22T04:58:09.377435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:09.680651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8649
86.5%
1 1351
 
13.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8649 
영업
1351 

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 8649
86.5%
영업 1351
 
13.5%

Length

2024-04-22T04:58:10.004870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:10.305208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8649
86.5%
영업 1351
 
13.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct3334
Distinct (%)38.5%
Missing1351
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean20087627
Minimum19970109
Maximum20210830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:10.650632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970109
5-th percentile20030227
Q120050317
median20071121
Q320120321
95-th percentile20190813
Maximum20210830
Range240721
Interquartile range (IQR)70004

Descriptive statistics

Standard deviation49614.389
Coefficient of variation (CV)0.002469898
Kurtosis-0.33891446
Mean20087627
Median Absolute Deviation (MAD)30110
Skewness0.7796121
Sum1.7373789 × 1011
Variance2.4615876 × 109
MonotonicityNot monotonic
2024-04-22T04:58:11.092899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040413 69
 
0.7%
20091209 50
 
0.5%
20090406 41
 
0.4%
20051229 31
 
0.3%
20091216 30
 
0.3%
20050408 29
 
0.3%
20050310 28
 
0.3%
20040723 28
 
0.3%
20050407 27
 
0.3%
20050307 26
 
0.3%
Other values (3324) 8290
82.9%
(Missing) 1351
 
13.5%
ValueCountFrequency (%)
19970109 1
< 0.1%
19970709 1
< 0.1%
19971007 1
< 0.1%
19980411 1
< 0.1%
19981021 1
< 0.1%
19990629 1
< 0.1%
19990712 1
< 0.1%
19991029 1
< 0.1%
19991102 1
< 0.1%
20000104 1
< 0.1%
ValueCountFrequency (%)
20210830 1
< 0.1%
20210827 1
< 0.1%
20210825 1
< 0.1%
20210820 1
< 0.1%
20210817 2
< 0.1%
20210813 1
< 0.1%
20210810 2
< 0.1%
20210803 1
< 0.1%
20210730 2
< 0.1%
20210727 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 

Distinct6954
Distinct (%)91.0%
Missing2357
Missing (%)23.6%
Memory size156.2 KiB
2024-04-22T04:58:12.315400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.299228
Min length1

Characters and Unicode

Total characters78717
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

Unique6660 ?
Unique (%)87.1%

Sample

1st row05306144675
2nd row053 6336970
3rd row4768900
4th row053 6256205
5th row053 4261103
ValueCountFrequency (%)
053 5700
39.3%
3829661 81
 
0.6%
943 45
 
0.3%
9661 38
 
0.3%
9439661 37
 
0.3%
7439661 32
 
0.2%
941 29
 
0.2%
0019 20
 
0.1%
324 16
 
0.1%
323 16
 
0.1%
Other values (7092) 8472
58.5%
2024-04-22T04:58:13.938893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13409
17.0%
3 11594
14.7%
0 10217
13.0%
6861
8.7%
6 6595
8.4%
2 6056
7.7%
7 5167
 
6.6%
4 5026
 
6.4%
1 5005
 
6.4%
9 4542
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71856
91.3%
Space Separator 6861
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13409
18.7%
3 11594
16.1%
0 10217
14.2%
6 6595
9.2%
2 6056
8.4%
7 5167
 
7.2%
4 5026
 
7.0%
1 5005
 
7.0%
9 4542
 
6.3%
8 4245
 
5.9%
Space Separator
ValueCountFrequency (%)
6861
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78717
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13409
17.0%
3 11594
14.7%
0 10217
13.0%
6861
8.7%
6 6595
8.4%
2 6056
7.7%
7 5167
 
6.6%
4 5026
 
6.4%
1 5005
 
6.4%
9 4542
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78717
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13409
17.0%
3 11594
14.7%
0 10217
13.0%
6861
8.7%
6 6595
8.4%
2 6056
7.7%
7 5167
 
6.6%
4 5026
 
6.4%
1 5005
 
6.4%
9 4542
 
5.8%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct49
Distinct (%)2.5%
Missing8058
Missing (%)80.6%
Infinite0
Infinite (%)0.0%
Mean2.380757
Minimum0
Maximum496
Zeros235
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:14.357019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3.3
Maximum496
Range496
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.713658
Coefficient of variation (CV)7.0203126
Kurtosis523.76996
Mean2.380757
Median Absolute Deviation (MAD)0
Skewness21.260907
Sum4623.43
Variance279.34636
MonotonicityNot monotonic
2024-04-22T04:58:14.786160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1.0 1301
 
13.0%
0.0 235
 
2.4%
3.3 144
 
1.4%
2.0 68
 
0.7%
3.0 51
 
0.5%
1.5 43
 
0.4%
1.44 14
 
0.1%
6.6 10
 
0.1%
4.0 10
 
0.1%
1.2 6
 
0.1%
Other values (39) 60
 
0.6%
(Missing) 8058
80.6%
ValueCountFrequency (%)
0.0 235
 
2.4%
0.3 2
 
< 0.1%
0.5 4
 
< 0.1%
1.0 1301
13.0%
1.1 4
 
< 0.1%
1.2 6
 
0.1%
1.3 2
 
< 0.1%
1.4 2
 
< 0.1%
1.44 14
 
0.1%
1.5 43
 
0.4%
ValueCountFrequency (%)
496.0 1
< 0.1%
320.1 1
< 0.1%
303.0 1
< 0.1%
165.3 1
< 0.1%
163.66 1
< 0.1%
117.39 1
< 0.1%
100.0 2
< 0.1%
90.0 1
< 0.1%
57.01 1
< 0.1%
52.9 1
< 0.1%

소재지우편번호
Real number (ℝ)

Distinct683
Distinct (%)6.9%
Missing55
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean704214.36
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:15.191234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700492.2
Q1702701
median703850
Q3705811
95-th percentile706852
Maximum711891
Range11881
Interquartile range (IQR)3110

Descriptive statistics

Standard deviation2511.0678
Coefficient of variation (CV)0.003565772
Kurtosis1.556469
Mean704214.36
Median Absolute Deviation (MAD)1952
Skewness0.94389331
Sum7.0034118 × 109
Variance6305461.6
MonotonicityNot monotonic
2024-04-22T04:58:15.633408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 164
 
1.6%
704060 92
 
0.9%
706170 84
 
0.8%
705802 82
 
0.8%
704919 78
 
0.8%
702845 76
 
0.8%
700412 75
 
0.8%
702040 72
 
0.7%
704834 64
 
0.6%
706140 55
 
0.5%
Other values (673) 9103
91.0%
(Missing) 55
 
0.5%
ValueCountFrequency (%)
700010 22
0.2%
700020 7
 
0.1%
700030 3
 
< 0.1%
700040 3
 
< 0.1%
700050 5
 
0.1%
700060 38
0.4%
700070 48
0.5%
700081 1
 
< 0.1%
700082 7
 
0.1%
700091 4
 
< 0.1%
ValueCountFrequency (%)
711891 10
 
0.1%
711874 21
0.2%
711873 15
0.1%
711872 23
0.2%
711871 1
 
< 0.1%
711864 29
0.3%
711863 6
 
0.1%
711862 7
 
0.1%
711861 9
 
0.1%
711860 1
 
< 0.1%

소재지전체주소
Text

Distinct2668
Distinct (%)26.7%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2024-04-22T04:58:16.919676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length53
Mean length24.05013
Min length16

Characters and Unicode

Total characters240357
Distinct characters450
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1849 ?
Unique (%)18.5%

Sample

1st row대구광역시 달성군 옥포면 기세리 ***-*번지
2nd row대구광역시 달서구 상인동 ****-*번지
3rd row대구광역시 달서구 성당동 ***-*번지
4th row대구광역시 남구 대명동 ****-*번지
5th row대구광역시 달서구 유천동 ***번지
ValueCountFrequency (%)
대구광역시 9995
22.7%
번지 9577
21.8%
달서구 2067
 
4.7%
북구 1724
 
3.9%
수성구 1448
 
3.3%
동구 1280
 
2.9%
서구 1081
 
2.5%
남구 967
 
2.2%
중구 938
 
2.1%
대명동 715
 
1.6%
Other values (1465) 14144
32.2%
2024-04-22T04:58:18.887826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 50480
21.0%
43672
18.2%
구 19799
 
8.2%
동 11434
 
4.8%
대 11388
 
4.7%
지 10524
 
4.4%
시 10123
 
4.2%
역 10041
 
4.2%
광 10011
 
4.2%
번 9581
 
4.0%
Other values (440) 53304
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136756
56.9%
Other Punctuation 50771
 
21.1%
Space Separator 43672
 
18.2%
Dash Punctuation 7940
 
3.3%
Open Punctuation 525
 
0.2%
Close Punctuation 513
 
0.2%
Uppercase Letter 158
 
0.1%
Lowercase Letter 11
 
< 0.1%
Math Symbol 10
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 19799
14.5%
동 11434
 
8.4%
대 11388
 
8.3%
지 10524
 
7.7%
시 10123
 
7.4%
역 10041
 
7.3%
광 10011
 
7.3%
번 9581
 
7.0%
서 3449
 
2.5%
성 2773
 
2.0%
Other values (400) 37633
27.5%
Uppercase Letter
ValueCountFrequency (%)
A 39
24.7%
T 19
12.0%
P 18
11.4%
B 17
10.8%
L 15
 
9.5%
G 14
 
8.9%
C 11
 
7.0%
E 4
 
2.5%
O 3
 
1.9%
R 3
 
1.9%
Other values (10) 15
 
9.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
c 2
18.2%
a 2
18.2%
m 1
9.1%
i 1
9.1%
t 1
9.1%
p 1
9.1%
b 1
9.1%
Other Punctuation
ValueCountFrequency (%)
* 50480
99.4%
, 248
 
0.5%
. 31
 
0.1%
/ 10
 
< 0.1%
@ 1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
43672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7940
100.0%
Open Punctuation
ValueCountFrequency (%)
( 525
100.0%
Close Punctuation
ValueCountFrequency (%)
) 513
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136750
56.9%
Common 103432
43.0%
Latin 169
 
0.1%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 19799
14.5%
동 11434
 
8.4%
대 11388
 
8.3%
지 10524
 
7.7%
시 10123
 
7.4%
역 10041
 
7.3%
광 10011
 
7.3%
번 9581
 
7.0%
서 3449
 
2.5%
성 2773
 
2.0%
Other values (399) 37627
27.5%
Latin
ValueCountFrequency (%)
A 39
23.1%
T 19
11.2%
P 18
10.7%
B 17
10.1%
L 15
 
8.9%
G 14
 
8.3%
C 11
 
6.5%
E 4
 
2.4%
O 3
 
1.8%
R 3
 
1.8%
Other values (18) 26
15.4%
Common
ValueCountFrequency (%)
* 50480
48.8%
43672
42.2%
- 7940
 
7.7%
( 525
 
0.5%
) 513
 
0.5%
, 248
 
0.2%
. 31
 
< 0.1%
/ 10
 
< 0.1%
~ 10
 
< 0.1%
` 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
Han
ValueCountFrequency (%)
內 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136750
56.9%
ASCII 103601
43.1%
CJK 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 50480
48.7%
43672
42.2%
- 7940
 
7.7%
( 525
 
0.5%
) 513
 
0.5%
, 248
 
0.2%
A 39
 
< 0.1%
. 31
 
< 0.1%
T 19
 
< 0.1%
P 18
 
< 0.1%
Other values (30) 116
 
0.1%
Hangul
ValueCountFrequency (%)
구 19799
14.5%
동 11434
 
8.4%
대 11388
 
8.3%
지 10524
 
7.7%
시 10123
 
7.4%
역 10041
 
7.3%
광 10011
 
7.3%
번 9581
 
7.0%
서 3449
 
2.5%
성 2773
 
2.0%
Other values (399) 37627
27.5%
CJK
ValueCountFrequency (%)
內 6
100.0%

도로명전체주소
Text

MISSING 

Distinct2374
Distinct (%)68.4%
Missing6527
Missing (%)65.3%
Memory size156.2 KiB
2024-04-22T04:58:19.982052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length56
Mean length27.799597
Min length19

Characters and Unicode

Total characters96548
Distinct characters453
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1874 ?
Unique (%)54.0%

Sample

1st row대구광역시 달서구 월곡로**길 ** (상인동)
2nd row대구광역시 남구 중앙대로**길 * (대명동)
3rd row대구광역시 달서구 와룡로**길 ** (본동)
4th row대구광역시 수성구 동대구로 ***, *층 (범어동)
5th row대구광역시 달서구 월배로 ***, *층 (상인동, 세븐일레븐 상인역점)
ValueCountFrequency (%)
3482
17.8%
대구광역시 3473
17.7%
층 795
 
4.1%
달서구 725
 
3.7%
북구 715
 
3.6%
동구 464
 
2.4%
수성구 404
 
2.1%
서구 330
 
1.7%
남구 312
 
1.6%
호 310
 
1.6%
Other values (1588) 8597
43.8%
2024-04-22T04:58:21.252978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16135
16.7%
* 14156
14.7%
구 7226
 
7.5%
대 4641
 
4.8%
동 4540
 
4.7%
시 3566
 
3.7%
역 3526
 
3.7%
광 3481
 
3.6%
로 3403
 
3.5%
( 3397
 
3.5%
Other values (443) 32477
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57199
59.2%
Space Separator 16135
 
16.7%
Other Punctuation 15933
 
16.5%
Open Punctuation 3397
 
3.5%
Close Punctuation 3397
 
3.5%
Dash Punctuation 364
 
0.4%
Uppercase Letter 109
 
0.1%
Math Symbol 7
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 7226
 
12.6%
대 4641
 
8.1%
동 4540
 
7.9%
시 3566
 
6.2%
역 3526
 
6.2%
광 3481
 
6.1%
로 3403
 
5.9%
길 1471
 
2.6%
서 1427
 
2.5%
달 1288
 
2.3%
Other values (406) 22630
39.6%
Uppercase Letter
ValueCountFrequency (%)
A 27
24.8%
B 21
19.3%
G 9
 
8.3%
C 8
 
7.3%
T 8
 
7.3%
S 5
 
4.6%
L 4
 
3.7%
E 4
 
3.7%
P 4
 
3.7%
R 3
 
2.8%
Other values (10) 16
14.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
14.3%
m 1
14.3%
c 1
14.3%
b 1
14.3%
t 1
14.3%
p 1
14.3%
a 1
14.3%
Other Punctuation
ValueCountFrequency (%)
* 14156
88.8%
, 1769
 
11.1%
. 6
 
< 0.1%
/ 1
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
16135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3397
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57198
59.2%
Common 39233
40.6%
Latin 116
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 7226
 
12.6%
대 4641
 
8.1%
동 4540
 
7.9%
시 3566
 
6.2%
역 3526
 
6.2%
광 3481
 
6.1%
로 3403
 
5.9%
길 1471
 
2.6%
서 1427
 
2.5%
달 1288
 
2.3%
Other values (405) 22629
39.6%
Latin
ValueCountFrequency (%)
A 27
23.3%
B 21
18.1%
G 9
 
7.8%
C 8
 
6.9%
T 8
 
6.9%
S 5
 
4.3%
L 4
 
3.4%
E 4
 
3.4%
P 4
 
3.4%
R 3
 
2.6%
Other values (17) 23
19.8%
Common
ValueCountFrequency (%)
16135
41.1%
* 14156
36.1%
( 3397
 
8.7%
) 3397
 
8.7%
, 1769
 
4.5%
- 364
 
0.9%
~ 7
 
< 0.1%
. 6
 
< 0.1%
/ 1
 
< 0.1%
@ 1
 
< 0.1%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57196
59.2%
ASCII 39349
40.8%
Compat Jamo 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16135
41.0%
* 14156
36.0%
( 3397
 
8.6%
) 3397
 
8.6%
, 1769
 
4.5%
- 364
 
0.9%
A 27
 
0.1%
B 21
 
0.1%
G 9
 
< 0.1%
C 8
 
< 0.1%
Other values (27) 66
 
0.2%
Hangul
ValueCountFrequency (%)
구 7226
 
12.6%
대 4641
 
8.1%
동 4540
 
7.9%
시 3566
 
6.2%
역 3526
 
6.2%
광 3481
 
6.1%
로 3403
 
5.9%
길 1471
 
2.6%
서 1427
 
2.5%
달 1288
 
2.3%
Other values (403) 22627
39.6%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅊ 1
50.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1135
Distinct (%)33.3%
Missing6592
Missing (%)65.9%
Infinite0
Infinite (%)0.0%
Mean42031.877
Minimum41001
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:21.497709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41001
5-th percentile41121
Q141518.75
median41956.5
Q342620
95-th percentile42936
Maximum43023
Range2022
Interquartile range (IQR)1101.25

Descriptive statistics

Standard deviation586.45436
Coefficient of variation (CV)0.01395261
Kurtosis-1.270873
Mean42031.877
Median Absolute Deviation (MAD)504.5
Skewness0.0063379947
Sum1.4324464 × 108
Variance343928.72
MonotonicityNot monotonic
2024-04-22T04:58:21.767326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42415 29
 
0.3%
41581 19
 
0.2%
41453 18
 
0.2%
42620 17
 
0.2%
41586 16
 
0.2%
42612 16
 
0.2%
41423 15
 
0.1%
41845 15
 
0.1%
41518 15
 
0.1%
41505 14
 
0.1%
Other values (1125) 3234
32.3%
(Missing) 6592
65.9%
ValueCountFrequency (%)
41001 2
 
< 0.1%
41002 4
 
< 0.1%
41005 1
 
< 0.1%
41007 14
0.1%
41008 7
0.1%
41017 1
 
< 0.1%
41021 2
 
< 0.1%
41022 1
 
< 0.1%
41025 1
 
< 0.1%
41026 2
 
< 0.1%
ValueCountFrequency (%)
43023 2
 
< 0.1%
43019 4
< 0.1%
43018 5
0.1%
43017 2
 
< 0.1%
43016 1
 
< 0.1%
43015 1
 
< 0.1%
43014 4
< 0.1%
43013 1
 
< 0.1%
43011 1
 
< 0.1%
43009 4
< 0.1%

사업장명
Text

Distinct8669
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-22T04:58:22.590940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length6.5882
Min length1

Characters and Unicode

Total characters65882
Distinct characters868
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7993 ?
Unique (%)79.9%

Sample

1st row대영농기계수퍼
2nd row영신슈퍼
3rd row섬 실내포장
4th row하늘자판기
5th row대한방직구내매점
ValueCountFrequency (%)
자판기 224
 
2.0%
세븐일레븐 77
 
0.7%
주)휘닉스벤딩서비스 55
 
0.5%
이마트24 44
 
0.4%
씨유 41
 
0.4%
신우유통 33
 
0.3%
gs25 31
 
0.3%
pc방 28
 
0.3%
지에스(gs)25 23
 
0.2%
영남대학병원 21
 
0.2%
Other values (8918) 10560
94.8%
2024-04-22T04:58:23.628468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 1954
 
3.0%
점 1596
 
2.4%
자 1536
 
2.3%
기 1530
 
2.3%
구 1486
 
2.3%
판 1350
 
2.0%
1149
 
1.7%
동 987
 
1.5%
식 926
 
1.4%
마 919
 
1.4%
Other values (858) 52449
79.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60344
91.6%
Decimal Number 1394
 
2.1%
Uppercase Letter 1390
 
2.1%
Space Separator 1149
 
1.7%
Close Punctuation 675
 
1.0%
Open Punctuation 672
 
1.0%
Lowercase Letter 147
 
0.2%
Other Punctuation 87
 
0.1%
Dash Punctuation 23
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1954
 
3.2%
점 1596
 
2.6%
자 1536
 
2.5%
기 1530
 
2.5%
구 1486
 
2.5%
판 1350
 
2.2%
동 987
 
1.6%
식 926
 
1.5%
마 919
 
1.5%
성 875
 
1.5%
Other values (793) 47185
78.2%
Uppercase Letter
ValueCountFrequency (%)
C 347
25.0%
P 201
14.5%
G 195
14.0%
S 178
12.8%
U 108
 
7.8%
K 55
 
4.0%
L 40
 
2.9%
A 28
 
2.0%
O 28
 
2.0%
T 26
 
1.9%
Other values (16) 184
13.2%
Lowercase Letter
ValueCountFrequency (%)
c 33
22.4%
p 22
15.0%
e 19
12.9%
o 12
 
8.2%
a 10
 
6.8%
i 8
 
5.4%
n 6
 
4.1%
f 5
 
3.4%
k 5
 
3.4%
l 5
 
3.4%
Other values (10) 22
15.0%
Decimal Number
ValueCountFrequency (%)
2 519
37.2%
4 247
17.7%
5 225
16.1%
1 157
 
11.3%
3 90
 
6.5%
0 62
 
4.4%
6 30
 
2.2%
7 27
 
1.9%
8 25
 
1.8%
9 12
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 62
71.3%
, 20
 
23.0%
& 4
 
4.6%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
1149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 675
100.0%
Open Punctuation
ValueCountFrequency (%)
( 672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60338
91.6%
Common 4000
 
6.1%
Latin 1538
 
2.3%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1954
 
3.2%
점 1596
 
2.6%
자 1536
 
2.5%
기 1530
 
2.5%
구 1486
 
2.5%
판 1350
 
2.2%
동 987
 
1.6%
식 926
 
1.5%
마 919
 
1.5%
성 875
 
1.5%
Other values (791) 47179
78.2%
Latin
ValueCountFrequency (%)
C 347
22.6%
P 201
13.1%
G 195
12.7%
S 178
11.6%
U 108
 
7.0%
K 55
 
3.6%
L 40
 
2.6%
c 33
 
2.1%
A 28
 
1.8%
O 28
 
1.8%
Other values (37) 325
21.1%
Common
ValueCountFrequency (%)
1149
28.7%
) 675
16.9%
( 672
16.8%
2 519
13.0%
4 247
 
6.2%
5 225
 
5.6%
1 157
 
3.9%
3 90
 
2.2%
. 62
 
1.6%
0 62
 
1.6%
Other values (8) 142
 
3.5%
Han
ValueCountFrequency (%)
內 5
83.3%
無 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60336
91.6%
ASCII 5537
 
8.4%
CJK 6
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 1954
 
3.2%
점 1596
 
2.6%
자 1536
 
2.5%
기 1530
 
2.5%
구 1486
 
2.5%
판 1350
 
2.2%
동 987
 
1.6%
식 926
 
1.5%
마 919
 
1.5%
성 875
 
1.5%
Other values (789) 47177
78.2%
ASCII
ValueCountFrequency (%)
1149
20.8%
) 675
12.2%
( 672
12.1%
2 519
9.4%
C 347
 
6.3%
4 247
 
4.5%
5 225
 
4.1%
P 201
 
3.6%
G 195
 
3.5%
S 178
 
3.2%
Other values (54) 1129
20.4%
CJK
ValueCountFrequency (%)
內 5
83.3%
無 1
 
16.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
50.0%
ㅌ 1
50.0%

최종수정시점
Real number (ℝ)

Distinct5328
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0081026 × 1013
Minimum2.0020116 × 1013
Maximum2.0210831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:23.869809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020116 × 1013
5-th percentile2.0020327 × 1013
Q12.0021105 × 1013
median2.0060307 × 1013
Q32.0130226 × 1013
95-th percentile2.0200318 × 1013
Maximum2.0210831 × 1013
Range1.9071516 × 1011
Interquartile range (IQR)1.091209 × 1011

Descriptive statistics

Standard deviation6.2277783 × 1010
Coefficient of variation (CV)0.0031013247
Kurtosis-0.85975272
Mean2.0081026 × 1013
Median Absolute Deviation (MAD)3.9778 × 1010
Skewness0.74588558
Sum2.0081026 × 1017
Variance3.8785223 × 1021
MonotonicityNot monotonic
2024-04-22T04:58:24.133096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031218000000 152
 
1.5%
20021107000000 93
 
0.9%
20020121000000 85
 
0.9%
20020117000000 82
 
0.8%
20020122000000 77
 
0.8%
20021030000000 73
 
0.7%
20020614000000 71
 
0.7%
20021028000000 67
 
0.7%
20020517000000 63
 
0.6%
20020617000000 61
 
0.6%
Other values (5318) 9176
91.8%
ValueCountFrequency (%)
20020116000000 12
 
0.1%
20020117000000 82
0.8%
20020118000000 37
0.4%
20020121000000 85
0.9%
20020122000000 77
0.8%
20020123000000 50
0.5%
20020128000000 3
 
< 0.1%
20020129000000 9
 
0.1%
20020204000000 17
 
0.2%
20020205000000 3
 
< 0.1%
ValueCountFrequency (%)
20210831160024 1
< 0.1%
20210831131250 1
< 0.1%
20210830141700 1
< 0.1%
20210827131930 1
< 0.1%
20210825153251 1
< 0.1%
20210825095033 1
< 0.1%
20210820101738 1
< 0.1%
20210819171632 1
< 0.1%
20210817173519 1
< 0.1%
20210817172144 1
< 0.1%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8950 
U
1050 

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 8950
89.5%
U 1050
 
10.5%

Length

2024-04-22T04:58:24.375447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:24.535799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8950
89.5%
u 1050
 
10.5%

데이터갱신일자
Date

Distinct623
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-09-02 02:40:00
2024-04-22T04:58:24.729892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T04:58:24.969652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

Length

2024-04-22T04:58:25.187493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:25.346629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7491
Distinct (%)80.0%
Missing634
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean342949.36
Minimum325831.39
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:25.524277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325831.39
5-th percentile335132.51
Q1339858.54
median342823.36
Q3345945.38
95-th percentile352685.94
Maximum358060.65
Range32229.256
Interquartile range (IQR)6086.8381

Descriptive statistics

Standard deviation4850.7252
Coefficient of variation (CV)0.014144144
Kurtosis0.58255282
Mean342949.36
Median Absolute Deviation (MAD)3039.0693
Skewness0.063594752
Sum3.2120637 × 109
Variance23529535
MonotonicityNot monotonic
2024-04-22T04:58:25.781643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343157.682044 50
 
0.5%
345141.357576 48
 
0.5%
344867.643963 35
 
0.4%
345549.11017 29
 
0.3%
339243.983122 19
 
0.2%
342935.432334 16
 
0.2%
344047.164924 16
 
0.2%
345320.33229 15
 
0.1%
345032.238221 15
 
0.1%
339284.621293 14
 
0.1%
Other values (7481) 9109
91.1%
(Missing) 634
 
6.3%
ValueCountFrequency (%)
325831.391262 1
< 0.1%
326269.666487 1
< 0.1%
326417.272694 1
< 0.1%
326610.275967 1
< 0.1%
326635.578062 1
< 0.1%
326703.14585 1
< 0.1%
326755.194077 2
< 0.1%
326766.322228 1
< 0.1%
327051.071404 1
< 0.1%
327085.648976 1
< 0.1%
ValueCountFrequency (%)
358060.647419 1
< 0.1%
356668.763448 1
< 0.1%
356589.560791 2
< 0.1%
356578.373419 1
< 0.1%
356533.072677 1
< 0.1%
356530.179947 1
< 0.1%
356521.273092 1
< 0.1%
356508.020702 1
< 0.1%
356484.612255 1
< 0.1%
356431.884326 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7492
Distinct (%)80.0%
Missing634
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean263558.56
Minimum238029.01
Maximum278909.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:26.054471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238029.01
5-th percentile257708.2
Q1261445.31
median263638.99
Q3265759.48
95-th percentile270848.87
Maximum278909.06
Range40880.052
Interquartile range (IQR)4314.1626

Descriptive statistics

Standard deviation4261.0926
Coefficient of variation (CV)0.016167536
Kurtosis4.657226
Mean263558.56
Median Absolute Deviation (MAD)2156.7568
Skewness-0.82882601
Sum2.4684895 × 109
Variance18156910
MonotonicityNot monotonic
2024-04-22T04:58:26.319516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261957.795169 50
 
0.5%
267096.362462 48
 
0.5%
264091.210417 35
 
0.4%
268620.845678 29
 
0.3%
268026.454531 19
 
0.2%
264310.975711 16
 
0.2%
265132.987974 16
 
0.2%
268402.372721 15
 
0.1%
262949.871621 15
 
0.1%
270912.150061 14
 
0.1%
Other values (7482) 9109
91.1%
(Missing) 634
 
6.3%
ValueCountFrequency (%)
238029.007127 1
< 0.1%
239687.676988 1
< 0.1%
240209.547189 1
< 0.1%
240270.873923 1
< 0.1%
240460.074049 1
< 0.1%
240481.502376 1
< 0.1%
240550.011807 1
< 0.1%
240757.761547 1
< 0.1%
240930.669713 1
< 0.1%
242216.081731 1
< 0.1%
ValueCountFrequency (%)
278909.058905 1
 
< 0.1%
278336.223852 4
< 0.1%
278318.296599 1
 
< 0.1%
278149.556874 2
< 0.1%
278148.233339 1
 
< 0.1%
278117.387967 1
 
< 0.1%
278116.5272 1
 
< 0.1%
278081.466697 1
 
< 0.1%
278080.761551 1
 
< 0.1%
278068.782101 1
 
< 0.1%

위생업태명
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

Length

2024-04-22T04:58:26.561831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:26.718198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9920 
0
 
80

Length

Max length4
Median length4
Mean length3.976
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> 9920
99.2%
0 80
 
0.8%

Length

2024-04-22T04:58:26.891216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:27.065336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9920
99.2%
0 80
 
0.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9919 
0
 
80
1
 
1

Length

Max length4
Median length4
Mean length3.9757
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9919
99.2%
0 80
 
0.8%
1 1
 
< 0.1%

Length

2024-04-22T04:58:27.244189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:27.418890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9919
99.2%
0 80
 
0.8%
1 1
 
< 0.1%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-22T04:58:27.759647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row주택가주변
ValueCountFrequency (%)
주택가주변 1
100.0%
2024-04-22T04:58:28.325369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2
40.0%
택 1
20.0%
가 1
20.0%
변 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2
40.0%
택 1
20.0%
가 1
20.0%
변 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2
40.0%
택 1
20.0%
가 1
20.0%
변 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2
40.0%
택 1
20.0%
가 1
20.0%
변 1
20.0%

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8151 
상수도전용
1831 
간이상수도
 
12
지하수전용
 
3
전용상수도(특정시설의 자가용 수도)
 
2

Length

Max length19
Median length4
Mean length4.1889
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8151
81.5%
상수도전용 1831
 
18.3%
간이상수도 12
 
0.1%
지하수전용 3
 
< 0.1%
전용상수도(특정시설의 자가용 수도) 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-22T04:58:28.545573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:28.744420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8151
81.5%
상수도전용 1831
 
18.3%
간이상수도 12
 
0.1%
지하수전용 3
 
< 0.1%
전용상수도(특정시설의 2
 
< 0.1%
자가용 2
 
< 0.1%
수도 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9955 
0
 
45

Length

Max length4
Median length4
Mean length3.9865
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> 9955
99.6%
0 45
 
0.4%

Length

2024-04-22T04:58:28.958632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:29.136237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9955
99.6%
0 45
 
0.4%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6505 
<NA>
3474 
1
 
20
500
 
1

Length

Max length4
Median length1
Mean length2.0424
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6505
65.0%
<NA> 3474
34.7%
1 20
 
0.2%
500 1
 
< 0.1%

Length

2024-04-22T04:58:29.327198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:29.514090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6505
65.0%
na 3474
34.7%
1 20
 
0.2%
500 1
 
< 0.1%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6520 
<NA>
3474 
1
 
6

Length

Max length4
Median length1
Mean length2.0422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6520
65.2%
<NA> 3474
34.7%
1 6
 
0.1%

Length

2024-04-22T04:58:29.710479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:29.889351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6520
65.2%
na 3474
34.7%
1 6
 
0.1%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6375 
<NA>
3474 
1
 
146
2
 
5

Length

Max length4
Median length1
Mean length2.0422
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6375
63.7%
<NA> 3474
34.7%
1 146
 
1.5%
2 5
 
0.1%

Length

2024-04-22T04:58:30.083826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:30.267344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6375
63.7%
na 3474
34.7%
1 146
 
1.5%
2 5
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6522 
<NA>
3474 
1
 
3
2
 
1

Length

Max length4
Median length1
Mean length2.0422
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6522
65.2%
<NA> 3474
34.7%
1 3
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-22T04:58:30.468216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:30.657612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6522
65.2%
na 3474
34.7%
1 3
 
< 0.1%
2 1
 
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7556 
자가
2013 
임대
 
431

Length

Max length4
Median length4
Mean length3.5112
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7556
75.6%
자가 2013
 
20.1%
임대 431
 
4.3%

Length

2024-04-22T04:58:30.877383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T04:58:31.068580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7556
75.6%
자가 2013
 
20.1%
임대 431
 
4.3%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing8912
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean353864.89
Minimum0
Maximum1 × 108
Zeros1081
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:31.231457image/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 deviation5508942.3
Coefficient of variation (CV)15.567926
Kurtosis275.92492
Mean353864.89
Median Absolute Deviation (MAD)0
Skewness16.501217
Sum3.85005 × 108
Variance3.0348446 × 1013
MonotonicityNot monotonic
2024-04-22T04:58:31.418253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1081
 
10.8%
80000000 2
 
< 0.1%
100000000 2
 
< 0.1%
10000000 1
 
< 0.1%
5000 1
 
< 0.1%
15000000 1
 
< 0.1%
(Missing) 8912
89.1%
ValueCountFrequency (%)
0 1081
10.8%
5000 1
 
< 0.1%
10000000 1
 
< 0.1%
15000000 1
 
< 0.1%
80000000 2
 
< 0.1%
100000000 2
 
< 0.1%
ValueCountFrequency (%)
100000000 2
 
< 0.1%
80000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 1
 
< 0.1%
5000 1
 
< 0.1%
0 1081
10.8%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing8913
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean2116.1408
Minimum0
Maximum800000
Zeros1081
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:31.600862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum800000
Range800000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation34931.298
Coefficient of variation (CV)16.507077
Kurtosis368.61823
Mean2116.1408
Median Absolute Deviation (MAD)0
Skewness18.62583
Sum2300245
Variance1.2201956 × 109
MonotonicityNot monotonic
2024-04-22T04:58:31.799471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1081
 
10.8%
200000 2
 
< 0.1%
600000 1
 
< 0.1%
245 1
 
< 0.1%
800000 1
 
< 0.1%
500000 1
 
< 0.1%
(Missing) 8913
89.1%
ValueCountFrequency (%)
0 1081
10.8%
245 1
 
< 0.1%
200000 2
 
< 0.1%
500000 1
 
< 0.1%
600000 1
 
< 0.1%
800000 1
 
< 0.1%
ValueCountFrequency (%)
800000 1
 
< 0.1%
600000 1
 
< 0.1%
500000 1
 
< 0.1%
200000 2
 
< 0.1%
245 1
 
< 0.1%
0 1081
10.8%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2024-04-22T04:58:31.989986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.047931
Minimum0
Maximum163.66
Zeros9893
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-22T04:58:32.134722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum163.66
Range163.66
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8626935
Coefficient of variation (CV)38.86198
Kurtosis6139.5375
Mean0.047931
Median Absolute Deviation (MAD)0
Skewness73.959361
Sum479.31
Variance3.4696272
MonotonicityNot monotonic
2024-04-22T04:58:32.603263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 9893
98.9%
1.0 82
 
0.8%
2.0 7
 
0.1%
3.0 6
 
0.1%
4.0 2
 
< 0.1%
15.0 1
 
< 0.1%
3.3 1
 
< 0.1%
9.66 1
 
< 0.1%
26.17 1
 
< 0.1%
7.0 1
 
< 0.1%
Other values (5) 5
 
0.1%
ValueCountFrequency (%)
0.0 9893
98.9%
1.0 82
 
0.8%
2.0 7
 
0.1%
3.0 6
 
0.1%
3.3 1
 
< 0.1%
4.0 2
 
< 0.1%
7.0 1
 
< 0.1%
9.0 1
 
< 0.1%
9.66 1
 
< 0.1%
10.2 1
 
< 0.1%
ValueCountFrequency (%)
163.66 1
< 0.1%
62.42 1
< 0.1%
50.9 1
< 0.1%
26.17 1
< 0.1%
15.0 1
< 0.1%
10.2 1
< 0.1%
9.66 1
< 0.1%
9.0 1
< 0.1%
7.0 1
< 0.1%
4.0 2
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1145211453식품자동판매기업07_22_10_P34800003480000-112-2002-0000420020225<NA>3폐업2폐업20120118<NA><NA><NA>05306144675<NA>711843대구광역시 달성군 옥포면 기세리 ***-*번지<NA><NA>대영농기계수퍼20111010215613I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
95939594식품자동판매기업07_22_10_P34700003470000-112-2001-0056620010906<NA>3폐업2폐업20130527<NA><NA><NA>053 6336970<NA>704809대구광역시 달서구 상인동 ****-*번지대구광역시 달서구 월곡로**길 ** (상인동)42791영신슈퍼20100129114823I2018-08-31 23:59:59.0식품자동판매기영업338873.818845258185.020906식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1017110172식품자동판매기업07_22_10_P34700003470000-112-2005-0020220050609<NA>3폐업2폐업20060519<NA><NA><NA><NA><NA>704080대구광역시 달서구 성당동 ***-*번지<NA><NA>섬 실내포장20060831000000I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
41854186식품자동판매기업07_22_10_P34400003440000-112-1996-0000619960604<NA>3폐업2폐업20040610<NA><NA><NA>4768900<NA>705800대구광역시 남구 대명동 ****-*번지대구광역시 남구 중앙대로**길 * (대명동)42425하늘자판기20150714131454I2018-08-31 23:59:59.0식품자동판매기영업343667.093378262303.027809식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
88388839식품자동판매기업07_22_10_P34700003470000-112-1991-0000819911203<NA>3폐업2폐업20061229<NA><NA><NA>053 6256205<NA>704390대구광역시 달서구 유천동 ***번지<NA><NA>대한방직구내매점20020527000000I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
344345식품자동판매기업07_22_10_P34100003410000-112-2001-0011020010630<NA>3폐업2폐업20040705<NA><NA><NA>053 4261103<NA>700150대구광역시 중구 공평동 ****-****번지 삼화빌딩,*(지상*층)<NA><NA>반줄노래방20031218000000I2018-08-31 23:59:59.0식품자동판매기영업344202.539055264284.093343식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
71437144식품자동판매기업07_22_10_P34600003460000-112-2002-0018220020618<NA>3폐업2폐업20080306<NA><NA><NA>7821540<NA>706845대구광역시 수성구 지산동 ****-**번지<NA><NA>서이환카클리닉20020702000000I2018-08-31 23:59:59.0식품자동판매기영업347721.052173258989.680454식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
40744075식품자동판매기업07_22_10_P34400003440000-112-2004-0002920040408<NA>3폐업2폐업20050120<NA><NA><NA><NA><NA>705836대구광역시 남구 이천동 ***-***번지<NA><NA>동인상사20040408000000I2018-08-31 23:59:59.0식품자동판매기영업345030.048819262813.81977식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
87958796식품자동판매기업07_22_10_P34700003470000-112-2001-0067520011227<NA>3폐업2폐업20140917<NA><NA><NA>053 6256882<NA>704807대구광역시 달서구 본동 ***-*번지대구광역시 달서구 와룡로**길 ** (본동)42733통통치킨20100129115353I2018-08-31 23:59:59.0식품자동판매기영업338859.527081260684.492462식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
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