Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells132973
Missing cells (%)28.3%
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

Description22년10월_6270000_대구광역시_07_22_10_P_식품자동판매기업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096916&dataSetDetailId=DDI_0000096954&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
영업장주변구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (71.0%)Imbalance
여성종사자수 is highly imbalanced (81.6%)Imbalance
급수시설구분명 is highly imbalanced (72.6%)Imbalance
총직원수 is highly imbalanced (72.2%)Imbalance
본사직원수 is highly imbalanced (53.1%)Imbalance
공장생산직직원수 is highly imbalanced (54.0%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1245 (12.4%) 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 2394 (23.9%) missing valuesMissing
소재지면적 has 7959 (79.6%) missing valuesMissing
도로명전체주소 has 6461 (64.6%) missing valuesMissing
도로명우편번호 has 6535 (65.3%) missing valuesMissing
좌표정보(X) has 640 (6.4%) missing valuesMissing
좌표정보(Y) has 640 (6.4%) missing valuesMissing
영업장주변구분명 has 9999 (> 99.9%) missing valuesMissing
등급구분명 has 10000 (100.0%) missing valuesMissing
보증액 has 8510 (85.1%) missing valuesMissing
월세액 has 8510 (85.1%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -86.9138741)Skewed
보증액 is highly skewed (γ1 = 20.30234328)Skewed
월세액 is highly skewed (γ1 = 36.37279915)Skewed
시설총규모 is highly skewed (γ1 = 64.47778171)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 263 (2.6%) zerosZeros
보증액 has 1481 (14.8%) zerosZeros
월세액 has 1481 (14.8%) zerosZeros
시설총규모 has 9867 (98.7%) zerosZeros

Reproduction

Analysis started2023-12-10 20:31:21.329114
Analysis finished2023-12-10 20:31:25.653708
Duration4.32 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%
Mean5967.3432
Minimum1
Maximum11912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:25.850667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile602.95
Q12998.75
median5963.5
Q38948.25
95-th percentile11321.05
Maximum11912
Range11911
Interquartile range (IQR)5949.5

Descriptive statistics

Standard deviation3437.678
Coefficient of variation (CV)0.57608183
Kurtosis-1.1996712
Mean5967.3432
Median Absolute Deviation (MAD)2976.5
Skewness-0.00079007092
Sum59673432
Variance11817630
MonotonicityNot monotonic
2023-12-11T05:31:26.213547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3066 1
 
< 0.1%
2485 1
 
< 0.1%
8610 1
 
< 0.1%
11770 1
 
< 0.1%
2159 1
 
< 0.1%
8243 1
 
< 0.1%
3573 1
 
< 0.1%
227 1
 
< 0.1%
11098 1
 
< 0.1%
10633 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
11912 1
< 0.1%
11911 1
< 0.1%
11909 1
< 0.1%
11908 1
< 0.1%
11907 1
< 0.1%
11906 1
< 0.1%
11905 1
< 0.1%
11904 1
< 0.1%
11903 1
< 0.1%
11902 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

2023-12-11T05:31:26.438993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:26.587869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기업 10000
100.0%

개방서비스아이디
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

2023-12-11T05:31:26.765166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:26.972100image/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%
Mean3446317
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:27.161822image/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 deviation21130.787
Coefficient of variation (CV)0.0061314113
Kurtosis-1.1687969
Mean3446317
Median Absolute Deviation (MAD)20000
Skewness-0.23968164
Sum3.446317 × 1010
Variance4.4651016 × 108
MonotonicityNot monotonic
2023-12-11T05:31:27.392023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2064
20.6%
3450000 1701
17.0%
3460000 1445
14.4%
3420000 1298
13.0%
3430000 1097
11.0%
3440000 973
9.7%
3410000 923
9.2%
3480000 499
 
5.0%
ValueCountFrequency (%)
3410000 923
9.2%
3420000 1298
13.0%
3430000 1097
11.0%
3440000 973
9.7%
3450000 1701
17.0%
3460000 1445
14.4%
3470000 2064
20.6%
3480000 499
 
5.0%
ValueCountFrequency (%)
3480000 499
 
5.0%
3470000 2064
20.6%
3460000 1445
14.4%
3450000 1701
17.0%
3440000 973
9.7%
3430000 1097
11.0%
3420000 1298
13.0%
3410000 923
9.2%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T05:31:27.860584image/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 row3430000-112-2001-00143
2nd row3460000-112-2001-00007
3rd row3420000-112-2007-00052
4th row3460000-112-2001-00318
5th row3460000-112-2001-00444
ValueCountFrequency (%)
3430000-112-2001-00143 1
 
< 0.1%
3410000-112-2003-00021 1
 
< 0.1%
3450000-112-2010-00022 1
 
< 0.1%
3420000-112-2006-00068 1
 
< 0.1%
3460000-112-2001-00288 1
 
< 0.1%
3480000-112-1999-00013 1
 
< 0.1%
3420000-112-2001-00031 1
 
< 0.1%
3460000-112-2001-00659 1
 
< 0.1%
3430000-112-2003-00041 1
 
< 0.1%
3420000-112-2001-00287 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T05:31:28.479655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86378
39.3%
1 30586
 
13.9%
- 30000
 
13.6%
2 24164
 
11.0%
3 14403
 
6.5%
4 14070
 
6.4%
5 4779
 
2.2%
9 4768
 
2.2%
7 4307
 
2.0%
6 3871
 
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 86378
45.5%
1 30586
 
16.1%
2 24164
 
12.7%
3 14403
 
7.6%
4 14070
 
7.4%
5 4779
 
2.5%
9 4768
 
2.5%
7 4307
 
2.3%
6 3871
 
2.0%
8 2674
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86378
39.3%
1 30586
 
13.9%
- 30000
 
13.6%
2 24164
 
11.0%
3 14403
 
6.5%
4 14070
 
6.4%
5 4779
 
2.2%
9 4768
 
2.2%
7 4307
 
2.0%
6 3871
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86378
39.3%
1 30586
 
13.9%
- 30000
 
13.6%
2 24164
 
11.0%
3 14403
 
6.5%
4 14070
 
6.4%
5 4779
 
2.2%
9 4768
 
2.2%
7 4307
 
2.0%
6 3871
 
1.8%

인허가일자
Real number (ℝ)

SKEWED 

Distinct3516
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20040274
Minimum199908
Maximum20221024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:28.750337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199908
5-th percentile19960203
Q120010424
median20020818
Q320060418
95-th percentile20180619
Maximum20221024
Range20021116
Interquartile range (IQR)49993.5

Descriptive statistics

Standard deviation207896.31
Coefficient of variation (CV)0.010373925
Kurtosis8297.75
Mean20040274
Median Absolute Deviation (MAD)20186
Skewness-86.913874
Sum2.0040274 × 1011
Variance4.3220874 × 1010
MonotonicityNot monotonic
2023-12-11T05:31:29.007405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010214 136
 
1.4%
20010302 51
 
0.5%
20000904 46
 
0.5%
20010615 42
 
0.4%
20010303 41
 
0.4%
20010710 38
 
0.4%
20010709 38
 
0.4%
20010213 35
 
0.4%
20010706 34
 
0.3%
20010628 34
 
0.3%
Other values (3506) 9505
95.0%
ValueCountFrequency (%)
199908 1
< 0.1%
19841219 1
< 0.1%
19850116 1
< 0.1%
19850128 1
< 0.1%
19850328 1
< 0.1%
19850810 1
< 0.1%
19880718 1
< 0.1%
19881201 1
< 0.1%
19881202 1
< 0.1%
19881228 1
< 0.1%
ValueCountFrequency (%)
20221024 1
< 0.1%
20221021 1
< 0.1%
20221019 1
< 0.1%
20221017 1
< 0.1%
20220929 2
< 0.1%
20220926 1
< 0.1%
20220920 1
< 0.1%
20220901 1
< 0.1%
20220829 1
< 0.1%
20220823 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
8755 
1
1245 

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 8755
87.5%
1 1245
 
12.4%

Length

2023-12-11T05:31:29.243438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:29.417216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8755
87.5%
1 1245
 
12.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8755 
영업/정상
1245 

Length

Max length5
Median length2
Mean length2.3735
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8755
87.5%
영업/정상 1245
 
12.4%

Length

2023-12-11T05:31:29.613666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:29.811869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8755
87.5%
영업/정상 1245
 
12.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8755 
1
1245 

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 8755
87.5%
1 1245
 
12.4%

Length

2023-12-11T05:31:30.006815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:30.195630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8755
87.5%
1 1245
 
12.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8755 
영업
1245 

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 8755
87.5%
영업 1245
 
12.4%

Length

2023-12-11T05:31:30.398831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:30.562364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8755
87.5%
영업 1245
 
12.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct3439
Distinct (%)39.3%
Missing1245
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean20090905
Minimum19970109
Maximum20221028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:30.763300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970109
5-th percentile20030304
Q120050407
median20080121
Q320121005
95-th percentile20200525
Maximum20221028
Range250919
Interquartile range (IQR)70598

Descriptive statistics

Standard deviation52842.648
Coefficient of variation (CV)0.0026301776
Kurtosis-0.32074521
Mean20090905
Median Absolute Deviation (MAD)30884
Skewness0.81072009
Sum1.7589587 × 1011
Variance2.7923455 × 109
MonotonicityNot monotonic
2023-12-11T05:31:31.022583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040413 67
 
0.7%
20091209 48
 
0.5%
20090406 41
 
0.4%
20051229 37
 
0.4%
20091216 34
 
0.3%
20040723 32
 
0.3%
20050408 27
 
0.3%
20050310 27
 
0.3%
20191227 26
 
0.3%
20050308 24
 
0.2%
Other values (3429) 8392
83.9%
(Missing) 1245
 
12.4%
ValueCountFrequency (%)
19970109 1
< 0.1%
19971007 1
< 0.1%
19981021 1
< 0.1%
19990303 1
< 0.1%
19990629 1
< 0.1%
19991029 1
< 0.1%
19991102 1
< 0.1%
20000122 1
< 0.1%
20000210 1
< 0.1%
20000228 1
< 0.1%
ValueCountFrequency (%)
20221028 2
< 0.1%
20221026 1
< 0.1%
20221019 2
< 0.1%
20221018 1
< 0.1%
20221017 1
< 0.1%
20221013 1
< 0.1%
20221012 1
< 0.1%
20221011 2
< 0.1%
20220929 1
< 0.1%
20220920 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 

Distinct6966
Distinct (%)91.6%
Missing2394
Missing (%)23.9%
Memory size156.2 KiB
2023-12-11T05:31:32.028197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.302261
Min length3

Characters and Unicode

Total characters78359
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

Unique6700 ?
Unique (%)88.1%

Sample

1st row053 3533149
2nd row7649805
3rd row7840 734
4th row7633462
5th row053 9513079
ValueCountFrequency (%)
053 5673
39.3%
3829661 86
 
0.6%
943 43
 
0.3%
9661 38
 
0.3%
7439661 33
 
0.2%
9439661 32
 
0.2%
941 30
 
0.2%
322 18
 
0.1%
0019 18
 
0.1%
312 16
 
0.1%
Other values (7108) 8454
58.5%
2023-12-11T05:31:32.996325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13364
17.1%
3 11576
14.8%
0 10169
13.0%
6855
8.7%
6 6558
8.4%
2 5990
7.6%
7 5121
 
6.5%
1 5056
 
6.5%
4 4951
 
6.3%
9 4509
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71504
91.3%
Space Separator 6855
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13364
18.7%
3 11576
16.2%
0 10169
14.2%
6 6558
9.2%
2 5990
8.4%
7 5121
 
7.2%
1 5056
 
7.1%
4 4951
 
6.9%
9 4509
 
6.3%
8 4210
 
5.9%
Space Separator
ValueCountFrequency (%)
6855
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13364
17.1%
3 11576
14.8%
0 10169
13.0%
6855
8.7%
6 6558
8.4%
2 5990
7.6%
7 5121
 
6.5%
1 5056
 
6.5%
4 4951
 
6.3%
9 4509
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13364
17.1%
3 11576
14.8%
0 10169
13.0%
6855
8.7%
6 6558
8.4%
2 5990
7.6%
7 5121
 
6.5%
1 5056
 
6.5%
4 4951
 
6.3%
9 4509
 
5.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct67
Distinct (%)3.3%
Missing7959
Missing (%)79.6%
Infinite0
Infinite (%)0.0%
Mean2.6186673
Minimum0
Maximum496
Zeros263
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:33.313359image/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 deviation17.024536
Coefficient of variation (CV)6.5012215
Kurtosis467.43095
Mean2.6186673
Median Absolute Deviation (MAD)0
Skewness19.74264
Sum5344.7
Variance289.83483
MonotonicityNot monotonic
2023-12-11T05:31:33.580497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 1329
 
13.3%
0.0 263
 
2.6%
3.3 154
 
1.5%
2.0 77
 
0.8%
3.0 53
 
0.5%
1.5 46
 
0.5%
4.0 12
 
0.1%
1.44 12
 
0.1%
6.6 11
 
0.1%
1.2 6
 
0.1%
Other values (57) 78
 
0.8%
(Missing) 7959
79.6%
ValueCountFrequency (%)
0.0 263
 
2.6%
0.25 1
 
< 0.1%
0.3 2
 
< 0.1%
0.4 1
 
< 0.1%
0.5 5
 
0.1%
0.79 1
 
< 0.1%
1.0 1329
13.3%
1.03 1
 
< 0.1%
1.1 3
 
< 0.1%
1.2 6
 
0.1%
ValueCountFrequency (%)
496.0 1
< 0.1%
320.1 1
< 0.1%
303.0 1
< 0.1%
177.59 1
< 0.1%
165.3 1
< 0.1%
163.66 1
< 0.1%
117.39 1
< 0.1%
104.0 1
< 0.1%
100.0 2
< 0.1%
73.85 1
< 0.1%

소재지우편번호
Real number (ℝ)

Distinct685
Distinct (%)6.9%
Missing72
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean704211.64
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:33.818441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700531.35
Q1702701
median703850
Q3705811
95-th percentile706852
Maximum711891
Range11881
Interquartile range (IQR)3110

Descriptive statistics

Standard deviation2502.325
Coefficient of variation (CV)0.0035533707
Kurtosis1.5751162
Mean704211.64
Median Absolute Deviation (MAD)1952
Skewness0.94228146
Sum6.9914132 × 109
Variance6261630.4
MonotonicityNot monotonic
2023-12-11T05:31:34.043875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 149
 
1.5%
706170 95
 
0.9%
704060 90
 
0.9%
705802 86
 
0.9%
704919 78
 
0.8%
700412 76
 
0.8%
702040 72
 
0.7%
702845 65
 
0.7%
704834 59
 
0.6%
706140 55
 
0.5%
Other values (675) 9103
91.0%
(Missing) 72
 
0.7%
ValueCountFrequency (%)
700010 23
0.2%
700020 6
 
0.1%
700030 1
 
< 0.1%
700040 5
 
0.1%
700050 3
 
< 0.1%
700060 31
0.3%
700070 49
0.5%
700081 1
 
< 0.1%
700082 9
 
0.1%
700091 3
 
< 0.1%
ValueCountFrequency (%)
711891 10
 
0.1%
711874 20
0.2%
711873 18
0.2%
711872 24
0.2%
711871 1
 
< 0.1%
711864 29
0.3%
711863 6
 
0.1%
711862 5
 
0.1%
711861 11
 
0.1%
711860 1
 
< 0.1%

소재지전체주소
Text

Distinct8814
Distinct (%)88.2%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T05:31:34.729669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length51
Mean length22.115092
Min length14

Characters and Unicode

Total characters220974
Distinct characters460
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8031 ?
Unique (%)80.4%

Sample

1st row대구광역시 서구 원대동3가 1416-3
2nd row대구광역시 수성구 두산동 95-1
3rd row대구광역시 동구 방촌동 1084-507
4th row대구광역시 수성구 지산동 1204-3
5th row대구광역시 수성구 파동 196-8
ValueCountFrequency (%)
대구광역시 9992
22.7%
달서구 2064
 
4.7%
북구 1698
 
3.9%
수성구 1442
 
3.3%
동구 1299
 
3.0%
서구 1095
 
2.5%
남구 973
 
2.2%
중구 923
 
2.1%
대명동 718
 
1.6%
달성군 498
 
1.1%
Other values (8876) 23225
52.9%
2023-12-11T05:31:35.697788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43656
19.8%
구 19775
 
8.9%
동 11447
 
5.2%
1 11441
 
5.2%
대 11391
 
5.2%
시 10119
 
4.6%
역 10039
 
4.5%
광 10007
 
4.5%
- 7914
 
3.6%
0 7254
 
3.3%
Other values (450) 77931
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117604
53.2%
Decimal Number 50342
22.8%
Space Separator 43656
 
19.8%
Dash Punctuation 7914
 
3.6%
Open Punctuation 517
 
0.2%
Close Punctuation 505
 
0.2%
Other Punctuation 269
 
0.1%
Uppercase Letter 140
 
0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 19775
16.8%
동 11447
 
9.7%
대 11391
 
9.7%
시 10119
 
8.6%
역 10039
 
8.5%
광 10007
 
8.5%
서 3449
 
2.9%
성 2778
 
2.4%
달 2618
 
2.2%
북 1826
 
1.6%
Other values (402) 34155
29.0%
Uppercase Letter
ValueCountFrequency (%)
A 39
27.9%
B 17
12.1%
T 16
11.4%
P 15
 
10.7%
L 11
 
7.9%
C 9
 
6.4%
G 9
 
6.4%
E 4
 
2.9%
H 3
 
2.1%
M 3
 
2.1%
Other values (10) 14
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 11441
22.7%
0 7254
14.4%
2 6126
12.2%
3 4965
9.9%
4 3947
 
7.8%
5 3782
 
7.5%
6 3477
 
6.9%
7 3302
 
6.6%
8 3067
 
6.1%
9 2981
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
c 3
23.1%
e 3
23.1%
b 2
15.4%
t 1
 
7.7%
a 1
 
7.7%
p 1
 
7.7%
i 1
 
7.7%
m 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 237
88.1%
. 20
 
7.4%
/ 11
 
4.1%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
43656
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7914
100.0%
Open Punctuation
ValueCountFrequency (%)
( 517
100.0%
Close Punctuation
ValueCountFrequency (%)
) 505
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117598
53.2%
Common 103217
46.7%
Latin 153
 
0.1%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 19775
16.8%
동 11447
 
9.7%
대 11391
 
9.7%
시 10119
 
8.6%
역 10039
 
8.5%
광 10007
 
8.5%
서 3449
 
2.9%
성 2778
 
2.4%
달 2618
 
2.2%
북 1826
 
1.6%
Other values (401) 34149
29.0%
Latin
ValueCountFrequency (%)
A 39
25.5%
B 17
11.1%
T 16
10.5%
P 15
 
9.8%
L 11
 
7.2%
C 9
 
5.9%
G 9
 
5.9%
E 4
 
2.6%
H 3
 
2.0%
c 3
 
2.0%
Other values (18) 27
17.6%
Common
ValueCountFrequency (%)
43656
42.3%
1 11441
 
11.1%
- 7914
 
7.7%
0 7254
 
7.0%
2 6126
 
5.9%
3 4965
 
4.8%
4 3947
 
3.8%
5 3782
 
3.7%
6 3477
 
3.4%
7 3302
 
3.2%
Other values (10) 7353
 
7.1%
Han
ValueCountFrequency (%)
內 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117598
53.2%
ASCII 103370
46.8%
CJK 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43656
42.2%
1 11441
 
11.1%
- 7914
 
7.7%
0 7254
 
7.0%
2 6126
 
5.9%
3 4965
 
4.8%
4 3947
 
3.8%
5 3782
 
3.7%
6 3477
 
3.4%
7 3302
 
3.2%
Other values (38) 7506
 
7.3%
Hangul
ValueCountFrequency (%)
구 19775
16.8%
동 11447
 
9.7%
대 11391
 
9.7%
시 10119
 
8.6%
역 10039
 
8.5%
광 10007
 
8.5%
서 3449
 
2.9%
성 2778
 
2.4%
달 2618
 
2.2%
북 1826
 
1.6%
Other values (401) 34149
29.0%
CJK
ValueCountFrequency (%)
內 6
100.0%

도로명전체주소
Text

MISSING 

Distinct3291
Distinct (%)93.0%
Missing6461
Missing (%)64.6%
Memory size156.2 KiB
2023-12-11T05:31:36.350928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length58
Mean length27.983894
Min length19

Characters and Unicode

Total characters99035
Distinct characters458
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

Unique3154 ?
Unique (%)89.1%

Sample

1st row대구광역시 달성군 가창면 가창로 1100
2nd row대구광역시 달성군 유가읍 테크노북로 164, 상가동 1층 3,4호 (하나리움퀸즈파크)
3rd row대구광역시 북구 신천동로 148-37 (대현동)
4th row대구광역시 달성군 다사읍 다사역로 39, 1층
5th row대구광역시 달서구 구마로 212 (송현동)
ValueCountFrequency (%)
대구광역시 3539
 
17.6%
달서구 733
 
3.6%
1층 722
 
3.6%
북구 716
 
3.6%
동구 492
 
2.4%
수성구 401
 
2.0%
서구 339
 
1.7%
남구 320
 
1.6%
중구 287
 
1.4%
달성군 251
 
1.2%
Other values (3288) 12304
61.2%
2023-12-11T05:31:37.169829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16566
 
16.7%
구 7354
 
7.4%
대 4726
 
4.8%
동 4699
 
4.7%
1 4086
 
4.1%
시 3636
 
3.7%
역 3589
 
3.6%
광 3546
 
3.6%
로 3472
 
3.5%
( 3453
 
3.5%
Other values (448) 43908
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58574
59.1%
Space Separator 16566
 
16.7%
Decimal Number 14626
 
14.8%
Open Punctuation 3453
 
3.5%
Close Punctuation 3453
 
3.5%
Other Punctuation 1863
 
1.9%
Dash Punctuation 369
 
0.4%
Uppercase Letter 113
 
0.1%
Math Symbol 9
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 7354
 
12.6%
대 4726
 
8.1%
동 4699
 
8.0%
시 3636
 
6.2%
역 3589
 
6.1%
광 3546
 
6.1%
로 3472
 
5.9%
길 1513
 
2.6%
서 1453
 
2.5%
달 1317
 
2.2%
Other values (403) 23269
39.7%
Uppercase Letter
ValueCountFrequency (%)
A 29
25.7%
B 24
21.2%
G 9
 
8.0%
C 7
 
6.2%
T 7
 
6.2%
L 6
 
5.3%
S 4
 
3.5%
E 4
 
3.5%
P 3
 
2.7%
M 3
 
2.7%
Other values (10) 17
15.0%
Decimal Number
ValueCountFrequency (%)
1 4086
27.9%
2 2050
14.0%
3 1514
 
10.4%
0 1306
 
8.9%
4 1198
 
8.2%
5 1183
 
8.1%
6 931
 
6.4%
7 878
 
6.0%
9 757
 
5.2%
8 723
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
c 2
22.2%
e 2
22.2%
t 1
11.1%
p 1
11.1%
a 1
11.1%
b 1
11.1%
m 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1856
99.6%
. 6
 
0.3%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
16566
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3453
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3453
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 369
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58574
59.1%
Common 40339
40.7%
Latin 122
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 7354
 
12.6%
대 4726
 
8.1%
동 4699
 
8.0%
시 3636
 
6.2%
역 3589
 
6.1%
광 3546
 
6.1%
로 3472
 
5.9%
길 1513
 
2.6%
서 1453
 
2.5%
달 1317
 
2.2%
Other values (403) 23269
39.7%
Latin
ValueCountFrequency (%)
A 29
23.8%
B 24
19.7%
G 9
 
7.4%
C 7
 
5.7%
T 7
 
5.7%
L 6
 
4.9%
S 4
 
3.3%
E 4
 
3.3%
P 3
 
2.5%
M 3
 
2.5%
Other values (17) 26
21.3%
Common
ValueCountFrequency (%)
16566
41.1%
1 4086
 
10.1%
( 3453
 
8.6%
) 3453
 
8.6%
2 2050
 
5.1%
, 1856
 
4.6%
3 1514
 
3.8%
0 1306
 
3.2%
4 1198
 
3.0%
5 1183
 
2.9%
Other values (8) 3674
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58572
59.1%
ASCII 40461
40.9%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16566
40.9%
1 4086
 
10.1%
( 3453
 
8.5%
) 3453
 
8.5%
2 2050
 
5.1%
, 1856
 
4.6%
3 1514
 
3.7%
0 1306
 
3.2%
4 1198
 
3.0%
5 1183
 
2.9%
Other values (35) 3796
 
9.4%
Hangul
ValueCountFrequency (%)
구 7354
 
12.6%
대 4726
 
8.1%
동 4699
 
8.0%
시 3636
 
6.2%
역 3589
 
6.1%
광 3546
 
6.1%
로 3472
 
5.9%
길 1513
 
2.6%
서 1453
 
2.5%
달 1317
 
2.2%
Other values (401) 23267
39.7%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅊ 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1149
Distinct (%)33.2%
Missing6535
Missing (%)65.3%
Infinite0
Infinite (%)0.0%
Mean42029.86
Minimum41001
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:37.383598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41001
5-th percentile41118.2
Q141516
median41954
Q342620
95-th percentile42946.8
Maximum43023
Range2022
Interquartile range (IQR)1104

Descriptive statistics

Standard deviation591.06253
Coefficient of variation (CV)0.014062919
Kurtosis-1.2780044
Mean42029.86
Median Absolute Deviation (MAD)507
Skewness0.0057190704
Sum1.4563346 × 108
Variance349354.92
MonotonicityNot monotonic
2023-12-11T05:31:37.599344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42415 31
 
0.3%
42620 19
 
0.2%
41845 18
 
0.2%
41581 16
 
0.2%
41423 16
 
0.2%
41007 16
 
0.2%
41586 15
 
0.1%
41937 15
 
0.1%
41453 15
 
0.1%
42612 14
 
0.1%
Other values (1139) 3290
32.9%
(Missing) 6535
65.3%
ValueCountFrequency (%)
41001 2
 
< 0.1%
41002 4
 
< 0.1%
41005 2
 
< 0.1%
41007 16
0.2%
41008 7
0.1%
41017 1
 
< 0.1%
41020 1
 
< 0.1%
41021 2
 
< 0.1%
41022 1
 
< 0.1%
41024 1
 
< 0.1%
ValueCountFrequency (%)
43023 2
 
< 0.1%
43019 4
< 0.1%
43018 6
0.1%
43017 3
< 0.1%
43016 1
 
< 0.1%
43015 1
 
< 0.1%
43014 7
0.1%
43013 1
 
< 0.1%
43009 4
< 0.1%
43008 3
< 0.1%

사업장명
Text

Distinct8706
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T05:31:38.087920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length6.6205
Min length1

Characters and Unicode

Total characters66205
Distinct characters861
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

Unique8042 ?
Unique (%)80.4%

Sample

1st row대일슈퍼
2nd row부산할매손칼국수
3rd row명성유통
4th row에델만제라
5th row대교서점
ValueCountFrequency (%)
자판기 214
 
1.9%
세븐일레븐 88
 
0.8%
이마트24 58
 
0.5%
주)휘닉스벤딩서비스 51
 
0.5%
씨유 45
 
0.4%
신우유통 36
 
0.3%
gs25 35
 
0.3%
pc방 31
 
0.3%
영남대의료원 24
 
0.2%
지에스(gs)25 24
 
0.2%
Other values (8961) 10571
94.6%
2023-12-11T05:31:38.783843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 1970
 
3.0%
점 1687
 
2.5%
자 1538
 
2.3%
기 1512
 
2.3%
구 1483
 
2.2%
판 1362
 
2.1%
1190
 
1.8%
동 1020
 
1.5%
식 941
 
1.4%
마 911
 
1.4%
Other values (851) 52591
79.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60552
91.5%
Decimal Number 1439
 
2.2%
Uppercase Letter 1418
 
2.1%
Space Separator 1190
 
1.8%
Close Punctuation 684
 
1.0%
Open Punctuation 682
 
1.0%
Lowercase Letter 131
 
0.2%
Other Punctuation 84
 
0.1%
Dash Punctuation 24
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1970
 
3.3%
점 1687
 
2.8%
자 1538
 
2.5%
기 1512
 
2.5%
구 1483
 
2.4%
판 1362
 
2.2%
동 1020
 
1.7%
식 941
 
1.6%
마 911
 
1.5%
성 878
 
1.4%
Other values (786) 47250
78.0%
Uppercase Letter
ValueCountFrequency (%)
C 351
24.8%
P 209
14.7%
G 198
14.0%
S 190
13.4%
U 104
 
7.3%
K 45
 
3.2%
L 36
 
2.5%
E 33
 
2.3%
A 29
 
2.0%
T 25
 
1.8%
Other values (16) 198
14.0%
Lowercase Letter
ValueCountFrequency (%)
c 29
22.1%
p 21
16.0%
e 18
13.7%
o 11
 
8.4%
a 10
 
7.6%
i 7
 
5.3%
n 6
 
4.6%
f 5
 
3.8%
s 4
 
3.1%
k 4
 
3.1%
Other values (9) 16
12.2%
Decimal Number
ValueCountFrequency (%)
2 549
38.2%
4 258
17.9%
5 233
16.2%
1 157
 
10.9%
3 84
 
5.8%
0 57
 
4.0%
6 34
 
2.4%
7 30
 
2.1%
8 24
 
1.7%
9 13
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 56
66.7%
, 16
 
19.0%
& 7
 
8.3%
/ 3
 
3.6%
' 2
 
2.4%
Space Separator
ValueCountFrequency (%)
1190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 684
100.0%
Open Punctuation
ValueCountFrequency (%)
( 682
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60546
91.5%
Common 4103
 
6.2%
Latin 1550
 
2.3%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1970
 
3.3%
점 1687
 
2.8%
자 1538
 
2.5%
기 1512
 
2.5%
구 1483
 
2.4%
판 1362
 
2.2%
동 1020
 
1.7%
식 941
 
1.6%
마 911
 
1.5%
성 878
 
1.5%
Other values (784) 47244
78.0%
Latin
ValueCountFrequency (%)
C 351
22.6%
P 209
13.5%
G 198
12.8%
S 190
12.3%
U 104
 
6.7%
K 45
 
2.9%
L 36
 
2.3%
E 33
 
2.1%
A 29
 
1.9%
c 29
 
1.9%
Other values (36) 326
21.0%
Common
ValueCountFrequency (%)
1190
29.0%
) 684
16.7%
( 682
16.6%
2 549
13.4%
4 258
 
6.3%
5 233
 
5.7%
1 157
 
3.8%
3 84
 
2.0%
0 57
 
1.4%
. 56
 
1.4%
Other values (9) 153
 
3.7%
Han
ValueCountFrequency (%)
內 5
83.3%
無 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60544
91.4%
ASCII 5652
 
8.5%
CJK 6
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 1970
 
3.3%
점 1687
 
2.8%
자 1538
 
2.5%
기 1512
 
2.5%
구 1483
 
2.4%
판 1362
 
2.2%
동 1020
 
1.7%
식 941
 
1.6%
마 911
 
1.5%
성 878
 
1.5%
Other values (782) 47242
78.0%
ASCII
ValueCountFrequency (%)
1190
21.1%
) 684
12.1%
( 682
12.1%
2 549
9.7%
C 351
 
6.2%
4 258
 
4.6%
5 233
 
4.1%
P 209
 
3.7%
G 198
 
3.5%
S 190
 
3.4%
Other values (54) 1108
19.6%
CJK
ValueCountFrequency (%)
內 5
83.3%
無 1
 
16.7%
Compat Jamo
ValueCountFrequency (%)
ㅌ 1
50.0%
ㄱ 1
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct5405
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0084403 × 1013
Minimum2.0020116 × 1013
Maximum2.0221031 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:38.974580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020116 × 1013
5-th percentile2.0020327 × 1013
Q12.0021106 × 1013
median2.0060423 × 1013
Q32.0131102 × 1013
95-th percentile2.0210727 × 1013
Maximum2.0221031 × 1013
Range2.0091517 × 1011
Interquartile range (IQR)1.0999586 × 1011

Descriptive statistics

Standard deviation6.6192988 × 1010
Coefficient of variation (CV)0.0032957408
Kurtosis-0.8474228
Mean2.0084403 × 1013
Median Absolute Deviation (MAD)3.9809 × 1010
Skewness0.75944391
Sum2.0084403 × 1017
Variance4.3815117 × 1021
MonotonicityNot monotonic
2023-12-11T05:31:39.213591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031218000000 151
 
1.5%
20021107000000 92
 
0.9%
20020122000000 81
 
0.8%
20020117000000 80
 
0.8%
20020121000000 78
 
0.8%
20020522000000 67
 
0.7%
20020614000000 67
 
0.7%
20021030000000 65
 
0.7%
20020527000000 64
 
0.6%
20021028000000 63
 
0.6%
Other values (5395) 9192
91.9%
ValueCountFrequency (%)
20020116000000 12
 
0.1%
20020117000000 80
0.8%
20020118000000 40
0.4%
20020121000000 78
0.8%
20020122000000 81
0.8%
20020123000000 49
0.5%
20020125000000 1
 
< 0.1%
20020128000000 3
 
< 0.1%
20020129000000 10
 
0.1%
20020204000000 15
 
0.1%
ValueCountFrequency (%)
20221031172245 1
< 0.1%
20221031163805 1
< 0.1%
20221028173524 1
< 0.1%
20221028111755 1
< 0.1%
20221026150916 1
< 0.1%
20221026114415 1
< 0.1%
20221024160054 1
< 0.1%
20221024131313 1
< 0.1%
20221024110808 1
< 0.1%
20221021135545 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8678 
U
1322 

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 8678
86.8%
U 1322
 
13.2%

Length

2023-12-11T05:31:39.444110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:39.610092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8678
86.8%
u 1322
 
13.2%

데이터갱신일자
Date

Distinct791
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-11-02 02:40:00
2023-12-11T05:31:39.780563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:31:40.060322image/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

2023-12-11T05:31:40.316622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:40.461751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7457
Distinct (%)79.7%
Missing640
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean342962.71
Minimum325831.39
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:40.650277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325831.39
5-th percentile335062.58
Q1339812.05
median342810.78
Q3345997.3
95-th percentile353061.17
Maximum358060.65
Range32229.256
Interquartile range (IQR)6185.2434

Descriptive statistics

Standard deviation4908.0861
Coefficient of variation (CV)0.014310845
Kurtosis0.53686815
Mean342962.71
Median Absolute Deviation (MAD)3076.1499
Skewness0.08281049
Sum3.210131 × 109
Variance24089310
MonotonicityNot monotonic
2023-12-11T05:31:40.914040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343157.682044 55
 
0.5%
345141.357576 48
 
0.5%
344867.643963 38
 
0.4%
345549.11017 23
 
0.2%
339243.983122 18
 
0.2%
345032.238221 16
 
0.2%
343787.134091 15
 
0.1%
344047.164924 14
 
0.1%
339096.139718 13
 
0.1%
343705.561002 13
 
0.1%
Other values (7447) 9107
91.1%
(Missing) 640
 
6.4%
ValueCountFrequency (%)
325831.391262 1
< 0.1%
326269.666487 1
< 0.1%
326534.608033 1
< 0.1%
326610.275967 1
< 0.1%
326635.578062 1
< 0.1%
326660.851514 1
< 0.1%
326703.14585 1
< 0.1%
326755.194077 2
< 0.1%
326766.322228 1
< 0.1%
327085.648976 1
< 0.1%
ValueCountFrequency (%)
358060.647419 1
< 0.1%
356698.367083 1
< 0.1%
356668.763448 1
< 0.1%
356589.560791 2
< 0.1%
356533.072677 1
< 0.1%
356530.179947 1
< 0.1%
356521.273092 1
< 0.1%
356519.71742 1
< 0.1%
356508.020702 1
< 0.1%
356484.612255 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7458
Distinct (%)79.7%
Missing640
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean263540.91
Minimum238029.01
Maximum278909.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:41.164200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238029.01
5-th percentile257683.41
Q1261444.68
median263609.9
Q3265743.41
95-th percentile270815.92
Maximum278909.06
Range40880.052
Interquartile range (IQR)4298.728

Descriptive statistics

Standard deviation4293.6881
Coefficient of variation (CV)0.016292302
Kurtosis4.6697295
Mean263540.91
Median Absolute Deviation (MAD)2154.8294
Skewness-0.84819921
Sum2.4667429 × 109
Variance18435757
MonotonicityNot monotonic
2023-12-11T05:31:41.421359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261957.795169 55
 
0.5%
267096.362462 48
 
0.5%
264091.210417 38
 
0.4%
268620.845678 23
 
0.2%
268026.454531 18
 
0.2%
262949.871621 16
 
0.2%
264065.576741 15
 
0.1%
265132.987974 14
 
0.1%
263889.318703 13
 
0.1%
264310.975711 13
 
0.1%
Other values (7448) 9107
91.1%
(Missing) 640
 
6.4%
ValueCountFrequency (%)
238029.007127 1
< 0.1%
240209.547189 1
< 0.1%
240270.873923 1
< 0.1%
240405.052319 1
< 0.1%
240481.502376 1
< 0.1%
240550.011807 1
< 0.1%
240739.938523 1
< 0.1%
240757.761547 1
< 0.1%
242216.081731 1
< 0.1%
242311.21229 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 2
< 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

2023-12-11T05:31:41.640504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:41.792945image/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>
9492 
0
 
508

Length

Max length4
Median length4
Mean length3.8476
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> 9492
94.9%
0 508
 
5.1%

Length

2023-12-11T05:31:41.959181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:42.143519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9492
94.9%
0 508
 
5.1%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9491 
0
 
508
1
 
1

Length

Max length4
Median length4
Mean length3.8473
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> 9491
94.9%
0 508
 
5.1%
1 1
 
< 0.1%

Length

2023-12-11T05:31:42.353368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:42.560515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9491
94.9%
0 508
 
5.1%
1 1
 
< 0.1%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-11T05:31:42.798792image/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%
2023-12-11T05:31:43.715084image/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>
8147 
상수도전용
1836 
간이상수도
 
12
지하수전용
 
3
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length19
Median length4
Mean length4.1879
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8147
81.5%
상수도전용 1836
 
18.4%
간이상수도 12
 
0.1%
지하수전용 3
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
전용상수도(특정시설의 자가용 수도) 1
 
< 0.1%

Length

2023-12-11T05:31:43.962137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:44.158109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8147
81.5%
상수도전용 1836
 
18.4%
간이상수도 12
 
0.1%
지하수전용 3
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
전용상수도(특정시설의 1
 
< 0.1%
자가용 1
 
< 0.1%
수도 1
 
< 0.1%

총직원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9520 
0
 
480

Length

Max length4
Median length4
Mean length3.856
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> 9520
95.2%
0 480
 
4.8%

Length

2023-12-11T05:31:44.381649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:44.572645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9520
95.2%
0 480
 
4.8%

본사직원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6672 
<NA>
3306 
1
 
21
500
 
1

Length

Max length4
Median length1
Mean length1.992
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6672
66.7%
<NA> 3306
33.1%
1 21
 
0.2%
500 1
 
< 0.1%

Length

2023-12-11T05:31:44.786875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:45.104413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6672
66.7%
na 3306
33.1%
1 21
 
0.2%
500 1
 
< 0.1%

공장사무직직원수
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6688 
<NA>
3306 
1
 
6

Length

Max length4
Median length1
Mean length1.9918
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6688
66.9%
<NA> 3306
33.1%
1 6
 
0.1%

Length

2023-12-11T05:31:45.594712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:45.883657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6688
66.9%
na 3306
33.1%
1 6
 
0.1%

공장판매직직원수
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6532 
<NA>
3306 
1
 
157
2
 
5

Length

Max length4
Median length1
Mean length1.9918
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6532
65.3%
<NA> 3306
33.1%
1 157
 
1.6%
2 5
 
0.1%

Length

2023-12-11T05:31:46.139085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:46.390591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6532
65.3%
na 3306
33.1%
1 157
 
1.6%
2 5
 
< 0.1%

공장생산직직원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6691 
<NA>
3306 
1
 
2
2
 
1

Length

Max length4
Median length1
Mean length1.9918
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 6691
66.9%
<NA> 3306
33.1%
1 2
 
< 0.1%
2 1
 
< 0.1%

Length

2023-12-11T05:31:46.601571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:46.785709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6691
66.9%
na 3306
33.1%
1 2
 
< 0.1%
2 1
 
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7518 
자가
2042 
임대
 
440

Length

Max length4
Median length4
Mean length3.5036
Min length2

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> 7518
75.2%
자가 2042
 
20.4%
임대 440
 
4.4%

Length

2023-12-11T05:31:47.002747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:31:47.221247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7518
75.2%
자가 2042
 
20.4%
임대 440
 
4.4%

보증액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.5%
Missing8510
Missing (%)85.1%
Infinite0
Infinite (%)0.0%
Mean236916.11
Minimum0
Maximum1 × 108
Zeros1481
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:47.402333image/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 deviation4089772.3
Coefficient of variation (CV)17.262534
Kurtosis434.78662
Mean236916.11
Median Absolute Deviation (MAD)0
Skewness20.302343
Sum3.53005 × 108
Variance1.6726237 × 1013
MonotonicityNot monotonic
2023-12-11T05:31:47.645600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1481
 
14.8%
80000000 2
 
< 0.1%
30000000 2
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%
15000000 1
 
< 0.1%
5000 1
 
< 0.1%
100000000 1
 
< 0.1%
(Missing) 8510
85.1%
ValueCountFrequency (%)
0 1481
14.8%
5000 1
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%
15000000 1
 
< 0.1%
30000000 2
 
< 0.1%
80000000 2
 
< 0.1%
100000000 1
 
< 0.1%
ValueCountFrequency (%)
100000000 1
 
< 0.1%
80000000 2
 
< 0.1%
30000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 1
 
< 0.1%
8000000 1
 
< 0.1%
5000 1
 
< 0.1%
0 1481
14.8%

월세액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.5%
Missing8510
Missing (%)85.1%
Infinite0
Infinite (%)0.0%
Mean7986.7416
Minimum0
Maximum8000000
Zeros1481
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:47.849038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8000000
Range8000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation211640.68
Coefficient of variation (CV)26.499002
Kurtosis1368.8311
Mean7986.7416
Median Absolute Deviation (MAD)0
Skewness36.372799
Sum11900245
Variance4.4791777 × 1010
MonotonicityNot monotonic
2023-12-11T05:31:48.079895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1481
 
14.8%
200000 2
 
< 0.1%
500000 2
 
< 0.1%
600000 1
 
< 0.1%
800000 1
 
< 0.1%
8000000 1
 
< 0.1%
245 1
 
< 0.1%
1100000 1
 
< 0.1%
(Missing) 8510
85.1%
ValueCountFrequency (%)
0 1481
14.8%
245 1
 
< 0.1%
200000 2
 
< 0.1%
500000 2
 
< 0.1%
600000 1
 
< 0.1%
800000 1
 
< 0.1%
1100000 1
 
< 0.1%
8000000 1
 
< 0.1%
ValueCountFrequency (%)
8000000 1
 
< 0.1%
1100000 1
 
< 0.1%
800000 1
 
< 0.1%
600000 1
 
< 0.1%
500000 2
 
< 0.1%
200000 2
 
< 0.1%
245 1
 
< 0.1%
0 1481
14.8%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2023-12-11T05:31:48.294500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.064095
Minimum0
Maximum163.66
Zeros9867
Zeros (%)98.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T05:31:48.467930image/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 deviation1.9675659
Coefficient of variation (CV)30.69765
Kurtosis4961.7399
Mean0.064095
Median Absolute Deviation (MAD)0
Skewness64.477782
Sum640.95
Variance3.8713155
MonotonicityNot monotonic
2023-12-11T05:31:48.669791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 9867
98.7%
1.0 98
 
1.0%
2.0 9
 
0.1%
3.0 6
 
0.1%
1.5 2
 
< 0.1%
4.0 2
 
< 0.1%
16.6 1
 
< 0.1%
25.02 1
 
< 0.1%
9.66 1
 
< 0.1%
15.0 1
 
< 0.1%
Other values (12) 12
 
0.1%
ValueCountFrequency (%)
0.0 9867
98.7%
1.0 98
 
1.0%
1.5 2
 
< 0.1%
2.0 9
 
0.1%
3.0 6
 
0.1%
3.3 1
 
< 0.1%
4.0 2
 
< 0.1%
6.0 1
 
< 0.1%
7.0 1
 
< 0.1%
9.0 1
 
< 0.1%
ValueCountFrequency (%)
163.66 1
< 0.1%
62.42 1
< 0.1%
50.9 1
< 0.1%
44.22 1
< 0.1%
26.4 1
< 0.1%
26.17 1
< 0.1%
25.02 1
< 0.1%
20.4 1
< 0.1%
16.6 1
< 0.1%
15.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총직원수본사직원수공장사무직직원수공장판매직직원수공장생산직직원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
30653066식품자동판매기업07_22_10_P34300003430000-112-2001-0014320010417<NA>3폐업2폐업20081226<NA><NA><NA>053 3533149<NA>703851대구광역시 서구 원대동3가 1416-3<NA><NA>대일슈퍼20060912000000I2018-08-31 23:59:59.0식품자동판매기영업342016.936867266166.94399식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
82158216식품자동판매기업07_22_10_P34600003460000-112-2001-0000720010226<NA>3폐업2폐업20020121<NA><NA><NA>7649805<NA>706800대구광역시 수성구 두산동 95-1<NA><NA>부산할매손칼국수20020123000000I2018-08-31 23:59:59.0식품자동판매기영업346503.824132261144.58923식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
22012202식품자동판매기업07_22_10_P34200003420000-112-2007-0005220071129<NA>3폐업2폐업20090317<NA><NA><NA><NA><NA>701804대구광역시 동구 방촌동 1084-507<NA><NA>명성유통20071129153138I2018-08-31 23:59:59.0식품자동판매기영업350634.410914265305.56357식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
83418342식품자동판매기업07_22_10_P34600003460000-112-2001-0031820010228<NA>3폐업2폐업20041110<NA><NA><NA>7840 734<NA>706845대구광역시 수성구 지산동 1204-3<NA><NA>에델만제라20020118000000I2018-08-31 23:59:59.0식품자동판매기영업347560.969896259082.968276식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
77207721식품자동판매기업07_22_10_P34600003460000-112-2001-0044420010428<NA>3폐업2폐업20030320<NA><NA><NA>7633462<NA>706849대구광역시 수성구 파동 196-8<NA><NA>대교서점20020121000000I2018-08-31 23:59:59.0식품자동판매기영업346082.22788258239.225689식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
14341435식품자동판매기업07_22_10_P34200003420000-112-2003-0011520031206<NA>3폐업2폐업20061215<NA><NA><NA>053 95130791.0701815대구광역시 동구 신암동 216-18 궁전빌딩4층<NA><NA>스카이PC방자판기20061121000000I2018-08-31 23:59:59.0식품자동판매기영업346412.966097265928.264018식품자동판매기영업00<NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
11521153식품자동판매기업07_22_10_P34200003420000-112-2006-0004020060511<NA>3폐업2폐업20120417<NA><NA><NA>053 75557461.0701823대구광역시 동구 신천동 44-18<NA><NA>삼양유통자판기20060629000000I2018-08-31 23:59:59.0식품자동판매기영업346371.699945265207.03401식품자동판매기영업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
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