Overview

Dataset statistics

Number of variables47
Number of observations10000
Missing cells133030
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

Description22년08월_6270000_대구광역시_07_22_10_P_식품자동판매기업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094290&dataSetDetailId=DDI_0000094310&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 (72.4%)Imbalance
여성종사자수 is highly imbalanced (82.5%)Imbalance
급수시설구분명 is highly imbalanced (72.6%)Imbalance
총직원수 is highly imbalanced (74.0%)Imbalance
본사직원수 is highly imbalanced (53.2%)Imbalance
공장생산직직원수 is highly imbalanced (53.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1241 (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 2365 (23.6%) missing valuesMissing
소재지면적 has 7975 (79.8%) missing valuesMissing
도로명전체주소 has 6494 (64.9%) missing valuesMissing
도로명우편번호 has 6564 (65.6%) missing valuesMissing
좌표정보(X) has 632 (6.3%) missing valuesMissing
좌표정보(Y) has 632 (6.3%) missing valuesMissing
영업장주변구분명 has 9999 (> 99.9%) missing valuesMissing
등급구분명 has 10000 (100.0%) missing valuesMissing
보증액 has 8527 (85.3%) missing valuesMissing
월세액 has 8528 (85.3%) 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 = 20.07262049)Skewed
시설총규모 is highly skewed (γ1 = 64.70853036)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 252 (2.5%) zerosZeros
보증액 has 1464 (14.6%) zerosZeros
월세액 has 1464 (14.6%) zerosZeros
시설총규모 has 9869 (98.7%) zerosZeros

Reproduction

Analysis started2023-12-10 18:11:48.029303
Analysis finished2023-12-10 18:11:51.873944
Duration3.84 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%
Mean5943.4868
Minimum1
Maximum11901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:51.982682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile598.95
Q12976.75
median5935.5
Q38915.25
95-th percentile11305.05
Maximum11901
Range11900
Interquartile range (IQR)5938.5

Descriptive statistics

Standard deviation3434.1329
Coefficient of variation (CV)0.57779767
Kurtosis-1.1994517
Mean5943.4868
Median Absolute Deviation (MAD)2969.5
Skewness0.00093854583
Sum59434868
Variance11793268
MonotonicityNot monotonic
2023-12-11T03:11:52.228139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5646 1
 
< 0.1%
5157 1
 
< 0.1%
11633 1
 
< 0.1%
2484 1
 
< 0.1%
2677 1
 
< 0.1%
6109 1
 
< 0.1%
2416 1
 
< 0.1%
1246 1
 
< 0.1%
8848 1
 
< 0.1%
11423 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%
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 (%)
11901 1
< 0.1%
11899 1
< 0.1%
11898 1
< 0.1%
11897 1
< 0.1%
11896 1
< 0.1%
11895 1
< 0.1%
11892 1
< 0.1%
11891 1
< 0.1%
11890 1
< 0.1%
11889 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

2023-12-11T03:11:52.458457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:52.611360image/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

2023-12-11T03:11:52.760652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:52.905209image/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%
Mean3446205
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:53.030993image/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 deviation21159.696
Coefficient of variation (CV)0.0061399993
Kurtosis-1.1699819
Mean3446205
Median Absolute Deviation (MAD)20000
Skewness-0.23912
Sum3.446205 × 1010
Variance4.4773275 × 108
MonotonicityNot monotonic
2023-12-11T03:11:53.206288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 2049
20.5%
3450000 1706
17.1%
3460000 1451
14.5%
3420000 1292
12.9%
3430000 1087
10.9%
3440000 974
9.7%
3410000 949
9.5%
3480000 492
 
4.9%
ValueCountFrequency (%)
3410000 949
9.5%
3420000 1292
12.9%
3430000 1087
10.9%
3440000 974
9.7%
3450000 1706
17.1%
3460000 1451
14.5%
3470000 2049
20.5%
3480000 492
 
4.9%
ValueCountFrequency (%)
3480000 492
 
4.9%
3470000 2049
20.5%
3460000 1451
14.5%
3450000 1706
17.1%
3440000 974
9.7%
3430000 1087
10.9%
3420000 1292
12.9%
3410000 949
9.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T03:11:53.542717image/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 row3450000-112-2004-00194
2nd row3460000-112-2019-00003
3rd row3470000-112-2002-00021
4th row3470000-112-2001-00484
5th row3470000-112-2001-00423
ValueCountFrequency (%)
3450000-112-2004-00194 1
 
< 0.1%
3420000-112-2007-00045 1
 
< 0.1%
3450000-112-2004-00401 1
 
< 0.1%
3470000-112-2007-00040 1
 
< 0.1%
3480000-112-2000-00021 1
 
< 0.1%
3420000-112-2001-00269 1
 
< 0.1%
3430000-112-2015-00006 1
 
< 0.1%
3450000-112-2001-00363 1
 
< 0.1%
3420000-112-2022-00009 1
 
< 0.1%
3450000-112-2004-00148 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T03:11:54.085732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86383
39.3%
1 30547
 
13.9%
- 30000
 
13.6%
2 24200
 
11.0%
3 14413
 
6.6%
4 14073
 
6.4%
5 4750
 
2.2%
9 4725
 
2.1%
7 4321
 
2.0%
6 3910
 
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 86383
45.5%
1 30547
 
16.1%
2 24200
 
12.7%
3 14413
 
7.6%
4 14073
 
7.4%
5 4750
 
2.5%
9 4725
 
2.5%
7 4321
 
2.3%
6 3910
 
2.1%
8 2678
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86383
39.3%
1 30547
 
13.9%
- 30000
 
13.6%
2 24200
 
11.0%
3 14413
 
6.6%
4 14073
 
6.4%
5 4750
 
2.2%
9 4725
 
2.1%
7 4321
 
2.0%
6 3910
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86383
39.3%
1 30547
 
13.9%
- 30000
 
13.6%
2 24200
 
11.0%
3 14413
 
6.6%
4 14073
 
6.4%
5 4750
 
2.2%
9 4725
 
2.1%
7 4321
 
2.0%
6 3910
 
1.8%

인허가일자
Real number (ℝ)

Distinct3516
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20042069
Minimum19841124
Maximum20220829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:54.335325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19841124
5-th percentile19960529
Q120010426
median20020821
Q320060329
95-th percentile20180611
Maximum20220829
Range379705
Interquartile range (IQR)49903.25

Descriptive statistics

Standard deviation61589.779
Coefficient of variation (CV)0.0030730249
Kurtosis1.0176073
Mean20042069
Median Absolute Deviation (MAD)20087.5
Skewness1.0541968
Sum2.0042069 × 1011
Variance3.7933008 × 109
MonotonicityNot monotonic
2023-12-11T03:11:54.571784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010214 119
 
1.2%
20010302 49
 
0.5%
20000904 47
 
0.5%
20010303 45
 
0.4%
20010615 40
 
0.4%
20010710 39
 
0.4%
20010705 36
 
0.4%
20010628 36
 
0.4%
20010709 36
 
0.4%
20010706 36
 
0.4%
Other values (3506) 9517
95.2%
ValueCountFrequency (%)
19841124 1
< 0.1%
19850116 1
< 0.1%
19850128 1
< 0.1%
19850810 1
< 0.1%
19880718 1
< 0.1%
19881201 1
< 0.1%
19881202 1
< 0.1%
19881228 1
< 0.1%
19890803 1
< 0.1%
19900315 1
< 0.1%
ValueCountFrequency (%)
20220829 1
< 0.1%
20220823 1
< 0.1%
20220816 1
< 0.1%
20220812 1
< 0.1%
20220804 1
< 0.1%
20220801 1
< 0.1%
20220726 1
< 0.1%
20220725 1
< 0.1%
20220722 1
< 0.1%
20220715 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
8759 
1
1241 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 8759
87.6%
1 1241
 
12.4%

Length

2023-12-11T03:11:54.833041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:54.986739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8759
87.6%
1 1241
 
12.4%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8759 
영업/정상
1241 

Length

Max length5
Median length2
Mean length2.3723
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 8759
87.6%
영업/정상 1241
 
12.4%

Length

2023-12-11T03:11:55.184917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:55.368828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8759
87.6%
영업/정상 1241
 
12.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8759 
1
1241 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 8759
87.6%
1 1241
 
12.4%

Length

2023-12-11T03:11:55.566679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:55.758463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8759
87.6%
1 1241
 
12.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8759 
영업
1241 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8759
87.6%
영업 1241
 
12.4%

Length

2023-12-11T03:11:55.950786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:11:56.135157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8759
87.6%
영업 1241
 
12.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct3428
Distinct (%)39.1%
Missing1241
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean20089995
Minimum19970109
Maximum20220830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:56.352426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970109
5-th percentile20030306
Q120050401
median20071218
Q320120802
95-th percentile20200118
Maximum20220830
Range250721
Interquartile range (IQR)70400.5

Descriptive statistics

Standard deviation52349.741
Coefficient of variation (CV)0.0026057618
Kurtosis-0.29992074
Mean20089995
Median Absolute Deviation (MAD)30297
Skewness0.82055623
Sum1.7596827 × 1011
Variance2.7404954 × 109
MonotonicityNot monotonic
2023-12-11T03:11:56.616788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040413 68
 
0.7%
20091209 43
 
0.4%
20090406 42
 
0.4%
20051229 32
 
0.3%
20050408 31
 
0.3%
20040723 31
 
0.3%
20050310 30
 
0.3%
20091216 29
 
0.3%
20050915 25
 
0.2%
20050307 24
 
0.2%
Other values (3418) 8404
84.0%
(Missing) 1241
 
12.4%
ValueCountFrequency (%)
19970109 1
< 0.1%
19970709 1
< 0.1%
19971007 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%
20000211 1
< 0.1%
ValueCountFrequency (%)
20220830 1
< 0.1%
20220829 1
< 0.1%
20220822 1
< 0.1%
20220816 2
< 0.1%
20220808 1
< 0.1%
20220803 1
< 0.1%
20220801 1
< 0.1%
20220725 1
< 0.1%
20220722 1
< 0.1%
20220721 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 

Distinct6986
Distinct (%)91.5%
Missing2365
Missing (%)23.6%
Memory size156.2 KiB
2023-12-11T03:11:57.486072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.308055
Min length3

Characters and Unicode

Total characters78702
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

Unique6704 ?
Unique (%)87.8%

Sample

1st row053 3215264
2nd row053 5228530
3rd row053 5610739
4th row053 6217166
5th row7520210
ValueCountFrequency (%)
053 5702
39.3%
3829661 80
 
0.6%
943 42
 
0.3%
9661 38
 
0.3%
9439661 33
 
0.2%
7439661 29
 
0.2%
941 22
 
0.2%
322 17
 
0.1%
321 16
 
0.1%
070 16
 
0.1%
Other values (7115) 8499
58.6%
2023-12-11T03:11:58.348319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13392
17.0%
3 11646
14.8%
0 10218
13.0%
6883
8.7%
6 6578
8.4%
2 6008
7.6%
7 5202
 
6.6%
1 5018
 
6.4%
4 5015
 
6.4%
9 4528
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71819
91.3%
Space Separator 6883
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13392
18.6%
3 11646
16.2%
0 10218
14.2%
6 6578
9.2%
2 6008
8.4%
7 5202
 
7.2%
1 5018
 
7.0%
4 5015
 
7.0%
9 4528
 
6.3%
8 4214
 
5.9%
Space Separator
ValueCountFrequency (%)
6883
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78702
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13392
17.0%
3 11646
14.8%
0 10218
13.0%
6883
8.7%
6 6578
8.4%
2 6008
7.6%
7 5202
 
6.6%
1 5018
 
6.4%
4 5015
 
6.4%
9 4528
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78702
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13392
17.0%
3 11646
14.8%
0 10218
13.0%
6883
8.7%
6 6578
8.4%
2 6008
7.6%
7 5202
 
6.6%
1 5018
 
6.4%
4 5015
 
6.4%
9 4528
 
5.8%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct65
Distinct (%)3.2%
Missing7975
Missing (%)79.8%
Infinite0
Infinite (%)0.0%
Mean2.6054963
Minimum0
Maximum496
Zeros252
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:58.683176image/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 deviation16.945449
Coefficient of variation (CV)6.5037316
Kurtosis479.48967
Mean2.6054963
Median Absolute Deviation (MAD)0
Skewness20.07262
Sum5276.13
Variance287.14823
MonotonicityNot monotonic
2023-12-11T03:11:59.027186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 1331
 
13.3%
0.0 252
 
2.5%
3.3 158
 
1.6%
2.0 70
 
0.7%
3.0 52
 
0.5%
1.5 45
 
0.4%
1.44 13
 
0.1%
6.6 11
 
0.1%
4.0 10
 
0.1%
0.5 5
 
0.1%
Other values (55) 78
 
0.8%
(Missing) 7975
79.8%
ValueCountFrequency (%)
0.0 252
 
2.5%
0.3 2
 
< 0.1%
0.4 1
 
< 0.1%
0.5 5
 
0.1%
1.0 1331
13.3%
1.03 1
 
< 0.1%
1.1 3
 
< 0.1%
1.2 5
 
0.1%
1.3 2
 
< 0.1%
1.4 1
 
< 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%
100.0 2
< 0.1%
73.85 1
< 0.1%
52.9 1
< 0.1%

소재지우편번호
Real number (ℝ)

Distinct687
Distinct (%)6.9%
Missing66
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean704203.17
Minimum700010
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:11:59.277126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700701
Q1702701
median703849
Q3705811
95-th percentile706852
Maximum711893
Range11883
Interquartile range (IQR)3110

Descriptive statistics

Standard deviation2506.1032
Coefficient of variation (CV)0.0035587786
Kurtosis1.5496793
Mean704203.17
Median Absolute Deviation (MAD)1953
Skewness0.93761992
Sum6.9955543 × 109
Variance6280553
MonotonicityNot monotonic
2023-12-11T03:11:59.564357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 165
 
1.7%
704060 94
 
0.9%
706170 88
 
0.9%
705802 83
 
0.8%
702040 76
 
0.8%
700412 70
 
0.7%
704919 68
 
0.7%
702845 65
 
0.7%
704834 63
 
0.6%
700823 56
 
0.6%
Other values (677) 9106
91.1%
(Missing) 66
 
0.7%
ValueCountFrequency (%)
700010 22
0.2%
700020 8
 
0.1%
700030 3
 
< 0.1%
700040 4
 
< 0.1%
700050 4
 
< 0.1%
700060 34
0.3%
700070 46
0.5%
700081 1
 
< 0.1%
700082 8
 
0.1%
700091 5
 
0.1%
ValueCountFrequency (%)
711893 1
 
< 0.1%
711891 12
 
0.1%
711874 20
0.2%
711873 18
0.2%
711872 24
0.2%
711871 1
 
< 0.1%
711864 31
0.3%
711863 6
 
0.1%
711862 5
 
0.1%
711861 11
 
0.1%

소재지전체주소
Text

Distinct8828
Distinct (%)88.3%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T03:12:00.337886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length50
Mean length22.17122
Min length14

Characters and Unicode

Total characters221557
Distinct characters462
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

Unique8027 ?
Unique (%)80.3%

Sample

1st row대구광역시 북구 국우동 1108-4
2nd row대구광역시 수성구 수성동4가 1085-32 대구은행역, 지하1층
3rd row대구광역시 달서구 본리동 1199-8
4th row대구광역시 달서구 감삼동 22-19
5th row대구광역시 달서구 상인동 800-4
ValueCountFrequency (%)
대구광역시 9994
22.7%
달서구 2049
 
4.7%
북구 1703
 
3.9%
수성구 1449
 
3.3%
동구 1293
 
2.9%
서구 1085
 
2.5%
남구 974
 
2.2%
중구 949
 
2.2%
대명동 716
 
1.6%
달성군 491
 
1.1%
Other values (8893) 23287
52.9%
2023-12-11T03:12:01.438150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43720
19.7%
구 19801
 
8.9%
동 11483
 
5.2%
1 11453
 
5.2%
대 11402
 
5.1%
시 10112
 
4.6%
역 10045
 
4.5%
광 10008
 
4.5%
- 7960
 
3.6%
0 7345
 
3.3%
Other values (452) 78228
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117796
53.2%
Decimal Number 50591
22.8%
Space Separator 43720
 
19.7%
Dash Punctuation 7960
 
3.6%
Open Punctuation 521
 
0.2%
Close Punctuation 510
 
0.2%
Other Punctuation 301
 
0.1%
Uppercase Letter 139
 
0.1%
Lowercase Letter 10
 
< 0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 19801
16.8%
동 11483
 
9.7%
대 11402
 
9.7%
시 10112
 
8.6%
역 10045
 
8.5%
광 10008
 
8.5%
서 3433
 
2.9%
성 2791
 
2.4%
달 2592
 
2.2%
북 1828
 
1.6%
Other values (407) 34301
29.1%
Uppercase Letter
ValueCountFrequency (%)
A 40
28.8%
P 17
12.2%
T 16
 
11.5%
B 16
 
11.5%
L 12
 
8.6%
G 11
 
7.9%
C 9
 
6.5%
M 4
 
2.9%
H 2
 
1.4%
E 2
 
1.4%
Other values (8) 10
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 11453
22.6%
0 7345
14.5%
2 6137
12.1%
3 4980
9.8%
4 4065
 
8.0%
5 3788
 
7.5%
6 3410
 
6.7%
7 3364
 
6.6%
8 3035
 
6.0%
9 3014
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
30.0%
c 2
20.0%
i 1
 
10.0%
b 1
 
10.0%
t 1
 
10.0%
p 1
 
10.0%
a 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 262
87.0%
. 28
 
9.3%
/ 9
 
3.0%
& 1
 
0.3%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
43720
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7960
100.0%
Open Punctuation
ValueCountFrequency (%)
( 521
100.0%
Close Punctuation
ValueCountFrequency (%)
) 510
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117791
53.2%
Common 103612
46.8%
Latin 149
 
0.1%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 19801
16.8%
동 11483
 
9.7%
대 11402
 
9.7%
시 10112
 
8.6%
역 10045
 
8.5%
광 10008
 
8.5%
서 3433
 
2.9%
성 2791
 
2.4%
달 2592
 
2.2%
북 1828
 
1.6%
Other values (406) 34296
29.1%
Latin
ValueCountFrequency (%)
A 40
26.8%
P 17
11.4%
T 16
 
10.7%
B 16
 
10.7%
L 12
 
8.1%
G 11
 
7.4%
C 9
 
6.0%
M 4
 
2.7%
e 3
 
2.0%
H 2
 
1.3%
Other values (15) 19
12.8%
Common
ValueCountFrequency (%)
43720
42.2%
1 11453
 
11.1%
- 7960
 
7.7%
0 7345
 
7.1%
2 6137
 
5.9%
3 4980
 
4.8%
4 4065
 
3.9%
5 3788
 
3.7%
6 3410
 
3.3%
7 3364
 
3.2%
Other values (10) 7390
 
7.1%
Han
ValueCountFrequency (%)
內 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117791
53.2%
ASCII 103761
46.8%
CJK 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43720
42.1%
1 11453
 
11.0%
- 7960
 
7.7%
0 7345
 
7.1%
2 6137
 
5.9%
3 4980
 
4.8%
4 4065
 
3.9%
5 3788
 
3.7%
6 3410
 
3.3%
7 3364
 
3.2%
Other values (35) 7539
 
7.3%
Hangul
ValueCountFrequency (%)
구 19801
16.8%
동 11483
 
9.7%
대 11402
 
9.7%
시 10112
 
8.6%
역 10045
 
8.5%
광 10008
 
8.5%
서 3433
 
2.9%
성 2791
 
2.4%
달 2592
 
2.2%
북 1828
 
1.6%
Other values (406) 34296
29.1%
CJK
ValueCountFrequency (%)
內 5
100.0%

도로명전체주소
Text

MISSING 

Distinct3271
Distinct (%)93.3%
Missing6494
Missing (%)64.9%
Memory size156.2 KiB
2023-12-11T03:12:02.207575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length55
Mean length27.98089
Min length19

Characters and Unicode

Total characters98101
Distinct characters462
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3134 ?
Unique (%)89.4%

Sample

1st row대구광역시 수성구 달구벌대로 지하 2300, 대구은행역 지하1층 (수성동4가)
2nd row대구광역시 북구 칠성로17길 15 (칠성동2가)
3rd row대구광역시 중구 중앙대로 394, 8층 (남일동, LG증권8)
4th row대구광역시 달서구 월배로 227 (상인동)
5th row대구광역시 달서구 감삼남5길 35 (감삼동)
ValueCountFrequency (%)
대구광역시 3506
 
17.6%
1층 716
 
3.6%
달서구 714
 
3.6%
북구 700
 
3.5%
동구 476
 
2.4%
수성구 412
 
2.1%
서구 326
 
1.6%
남구 321
 
1.6%
중구 307
 
1.5%
달성군 250
 
1.3%
Other values (3280) 12209
61.2%
2023-12-11T03:12:03.329740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16431
 
16.7%
구 7286
 
7.4%
대 4704
 
4.8%
동 4664
 
4.8%
1 4054
 
4.1%
시 3595
 
3.7%
역 3563
 
3.6%
광 3512
 
3.6%
로 3437
 
3.5%
) 3416
 
3.5%
Other values (452) 43439
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58084
59.2%
Space Separator 16431
 
16.7%
Decimal Number 14434
 
14.7%
Close Punctuation 3416
 
3.5%
Open Punctuation 3416
 
3.5%
Other Punctuation 1850
 
1.9%
Dash Punctuation 360
 
0.4%
Uppercase Letter 98
 
0.1%
Math Symbol 6
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 7286
 
12.5%
대 4704
 
8.1%
동 4664
 
8.0%
시 3595
 
6.2%
역 3563
 
6.1%
광 3512
 
6.0%
로 3437
 
5.9%
길 1492
 
2.6%
서 1414
 
2.4%
달 1284
 
2.2%
Other values (411) 23133
39.8%
Uppercase Letter
ValueCountFrequency (%)
A 27
27.6%
B 25
25.5%
C 8
 
8.2%
G 7
 
7.1%
T 5
 
5.1%
L 4
 
4.1%
S 4
 
4.1%
M 4
 
4.1%
P 3
 
3.1%
E 2
 
2.0%
Other values (7) 9
 
9.2%
Decimal Number
ValueCountFrequency (%)
1 4054
28.1%
2 2007
13.9%
3 1517
 
10.5%
0 1275
 
8.8%
4 1165
 
8.1%
5 1155
 
8.0%
6 924
 
6.4%
7 844
 
5.8%
9 765
 
5.3%
8 728
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
c 1
16.7%
t 1
16.7%
p 1
16.7%
a 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 1844
99.7%
. 4
 
0.2%
/ 1
 
0.1%
@ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
16431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3416
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3416
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 360
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58083
59.2%
Common 39913
40.7%
Latin 104
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 7286
 
12.5%
대 4704
 
8.1%
동 4664
 
8.0%
시 3595
 
6.2%
역 3563
 
6.1%
광 3512
 
6.0%
로 3437
 
5.9%
길 1492
 
2.6%
서 1414
 
2.4%
달 1284
 
2.2%
Other values (410) 23132
39.8%
Latin
ValueCountFrequency (%)
A 27
26.0%
B 25
24.0%
C 8
 
7.7%
G 7
 
6.7%
T 5
 
4.8%
L 4
 
3.8%
S 4
 
3.8%
M 4
 
3.8%
P 3
 
2.9%
E 2
 
1.9%
Other values (12) 15
14.4%
Common
ValueCountFrequency (%)
16431
41.2%
1 4054
 
10.2%
) 3416
 
8.6%
( 3416
 
8.6%
2 2007
 
5.0%
, 1844
 
4.6%
3 1517
 
3.8%
0 1275
 
3.2%
4 1165
 
2.9%
5 1155
 
2.9%
Other values (9) 3633
 
9.1%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58081
59.2%
ASCII 40017
40.8%
Compat Jamo 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16431
41.1%
1 4054
 
10.1%
) 3416
 
8.5%
( 3416
 
8.5%
2 2007
 
5.0%
, 1844
 
4.6%
3 1517
 
3.8%
0 1275
 
3.2%
4 1165
 
2.9%
5 1155
 
2.9%
Other values (31) 3737
 
9.3%
Hangul
ValueCountFrequency (%)
구 7286
 
12.5%
대 4704
 
8.1%
동 4664
 
8.0%
시 3595
 
6.2%
역 3563
 
6.1%
광 3512
 
6.0%
로 3437
 
5.9%
길 1492
 
2.6%
서 1414
 
2.4%
달 1284
 
2.2%
Other values (408) 23130
39.8%
CJK
ValueCountFrequency (%)
內 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅊ 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1140
Distinct (%)33.2%
Missing6564
Missing (%)65.6%
Infinite0
Infinite (%)0.0%
Mean42034.82
Minimum41002
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:03.624465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41122
Q141520
median41961
Q342620
95-th percentile42947.25
Maximum43023
Range2021
Interquartile range (IQR)1100

Descriptive statistics

Standard deviation586.87466
Coefficient of variation (CV)0.013961631
Kurtosis-1.260124
Mean42034.82
Median Absolute Deviation (MAD)507
Skewness0.0028257334
Sum1.4443164 × 108
Variance344421.86
MonotonicityNot monotonic
2023-12-11T03:12:04.111403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42415 30
 
0.3%
41423 20
 
0.2%
41845 17
 
0.2%
42620 16
 
0.2%
41581 16
 
0.2%
41586 16
 
0.2%
42612 15
 
0.1%
42974 14
 
0.1%
41918 13
 
0.1%
41453 13
 
0.1%
Other values (1130) 3266
32.7%
(Missing) 6564
65.6%
ValueCountFrequency (%)
41002 4
 
< 0.1%
41005 2
 
< 0.1%
41007 12
0.1%
41008 7
0.1%
41021 2
 
< 0.1%
41022 1
 
< 0.1%
41024 1
 
< 0.1%
41025 1
 
< 0.1%
41026 3
 
< 0.1%
41028 1
 
< 0.1%
ValueCountFrequency (%)
43023 2
 
< 0.1%
43019 4
< 0.1%
43018 5
0.1%
43017 3
< 0.1%
43015 1
 
< 0.1%
43014 7
0.1%
43013 1
 
< 0.1%
43011 2
 
< 0.1%
43009 4
< 0.1%
43008 3
< 0.1%

사업장명
Text

Distinct8701
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T03:12:04.770018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length6.6002
Min length1

Characters and Unicode

Total characters66002
Distinct characters873
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

Unique8024 ?
Unique (%)80.2%

Sample

1st row놋그릇왕대포
2nd row이마트24에스대구은행역
3rd rowA할인마트
4th row조세빈헤어라인
5th row주공알뜰슈퍼
ValueCountFrequency (%)
자판기 222
 
2.0%
세븐일레븐 88
 
0.8%
이마트24 58
 
0.5%
주)휘닉스벤딩서비스 57
 
0.5%
신우유통 39
 
0.3%
gs25 38
 
0.3%
씨유 37
 
0.3%
pc방 29
 
0.3%
영남대학병원 23
 
0.2%
영남대의료원 23
 
0.2%
Other values (8943) 10557
94.5%
2023-12-11T03:12:05.530703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 1930
 
2.9%
점 1684
 
2.6%
자 1519
 
2.3%
기 1504
 
2.3%
구 1452
 
2.2%
판 1330
 
2.0%
1184
 
1.8%
동 990
 
1.5%
마 937
 
1.4%
식 933
 
1.4%
Other values (863) 52539
79.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60363
91.5%
Decimal Number 1416
 
2.1%
Uppercase Letter 1405
 
2.1%
Space Separator 1184
 
1.8%
Close Punctuation 667
 
1.0%
Open Punctuation 664
 
1.0%
Lowercase Letter 193
 
0.3%
Other Punctuation 85
 
0.1%
Dash Punctuation 24
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1930
 
3.2%
점 1684
 
2.8%
자 1519
 
2.5%
기 1504
 
2.5%
구 1452
 
2.4%
판 1330
 
2.2%
동 990
 
1.6%
마 937
 
1.6%
식 933
 
1.5%
트 859
 
1.4%
Other values (798) 47225
78.2%
Uppercase Letter
ValueCountFrequency (%)
C 349
24.8%
P 204
14.5%
G 193
13.7%
S 185
13.2%
U 104
 
7.4%
K 52
 
3.7%
L 34
 
2.4%
E 30
 
2.1%
A 29
 
2.1%
T 26
 
1.9%
Other values (16) 199
14.2%
Lowercase Letter
ValueCountFrequency (%)
c 35
18.1%
e 27
14.0%
p 22
11.4%
o 20
10.4%
a 14
 
7.3%
i 11
 
5.7%
f 9
 
4.7%
k 7
 
3.6%
t 7
 
3.6%
s 7
 
3.6%
Other values (10) 34
17.6%
Decimal Number
ValueCountFrequency (%)
2 538
38.0%
4 260
18.4%
5 226
16.0%
1 159
 
11.2%
3 81
 
5.7%
0 57
 
4.0%
7 30
 
2.1%
6 27
 
1.9%
8 26
 
1.8%
9 12
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 58
68.2%
, 19
 
22.4%
& 5
 
5.9%
/ 3
 
3.5%
Space Separator
ValueCountFrequency (%)
1184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 667
100.0%
Open Punctuation
ValueCountFrequency (%)
( 664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60358
91.4%
Common 4040
 
6.1%
Latin 1599
 
2.4%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1930
 
3.2%
점 1684
 
2.8%
자 1519
 
2.5%
기 1504
 
2.5%
구 1452
 
2.4%
판 1330
 
2.2%
동 990
 
1.6%
마 937
 
1.6%
식 933
 
1.5%
트 859
 
1.4%
Other values (796) 47220
78.2%
Latin
ValueCountFrequency (%)
C 349
21.8%
P 204
12.8%
G 193
12.1%
S 185
11.6%
U 104
 
6.5%
K 52
 
3.3%
c 35
 
2.2%
L 34
 
2.1%
E 30
 
1.9%
A 29
 
1.8%
Other values (37) 384
24.0%
Common
ValueCountFrequency (%)
1184
29.3%
) 667
16.5%
( 664
16.4%
2 538
13.3%
4 260
 
6.4%
5 226
 
5.6%
1 159
 
3.9%
3 81
 
2.0%
. 58
 
1.4%
0 57
 
1.4%
Other values (8) 146
 
3.6%
Han
ValueCountFrequency (%)
內 4
80.0%
無 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60356
91.4%
ASCII 5638
 
8.5%
CJK 5
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 1930
 
3.2%
점 1684
 
2.8%
자 1519
 
2.5%
기 1504
 
2.5%
구 1452
 
2.4%
판 1330
 
2.2%
동 990
 
1.6%
마 937
 
1.6%
식 933
 
1.5%
트 859
 
1.4%
Other values (794) 47218
78.2%
ASCII
ValueCountFrequency (%)
1184
21.0%
) 667
11.8%
( 664
11.8%
2 538
9.5%
C 349
 
6.2%
4 260
 
4.6%
5 226
 
4.0%
P 204
 
3.6%
G 193
 
3.4%
S 185
 
3.3%
Other values (54) 1168
20.7%
CJK
ValueCountFrequency (%)
內 4
80.0%
無 1
 
20.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
50.0%
ㅌ 1
50.0%

최종수정시점
Real number (ℝ)

Distinct5370
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0083687 × 1013
Minimum2.0020116 × 1013
Maximum2.0220831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:05.797249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020116 × 1013
5-th percentile2.0020327 × 1013
Q12.0021105 × 1013
median2.0060316 × 1013
Q32.0130926 × 1013
95-th percentile2.021061 × 1013
Maximum2.0220831 × 1013
Range2.0071512 × 1011
Interquartile range (IQR)1.0982111 × 1011

Descriptive statistics

Standard deviation6.5877402 × 1010
Coefficient of variation (CV)0.0032801447
Kurtosis-0.83002608
Mean2.0083687 × 1013
Median Absolute Deviation (MAD)3.97885 × 1010
Skewness0.77223841
Sum2.0083687 × 1017
Variance4.339832 × 1021
MonotonicityNot monotonic
2023-12-11T03:12:06.089494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031218000000 154
 
1.5%
20021107000000 90
 
0.9%
20020122000000 79
 
0.8%
20020121000000 75
 
0.8%
20021030000000 73
 
0.7%
20020614000000 72
 
0.7%
20020117000000 67
 
0.7%
20020522000000 64
 
0.6%
20020527000000 63
 
0.6%
20021028000000 61
 
0.6%
Other values (5360) 9202
92.0%
ValueCountFrequency (%)
20020116000000 14
 
0.1%
20020117000000 67
0.7%
20020118000000 39
0.4%
20020121000000 75
0.8%
20020122000000 79
0.8%
20020123000000 48
0.5%
20020125000000 1
 
< 0.1%
20020128000000 3
 
< 0.1%
20020129000000 10
 
0.1%
20020204000000 16
 
0.2%
ValueCountFrequency (%)
20220831115435 1
< 0.1%
20220831113510 1
< 0.1%
20220830153953 1
< 0.1%
20220830112816 1
< 0.1%
20220830112734 1
< 0.1%
20220830112549 1
< 0.1%
20220830112457 1
< 0.1%
20220830112444 1
< 0.1%
20220830110905 1
< 0.1%
20220830104239 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8695 
U
1305 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 8695
87.0%
U 1305
 
13.1%

Length

2023-12-11T03:12:06.352840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:06.540295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8695
87.0%
u 1305
 
13.1%

데이터갱신일자
Date

Distinct779
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-09-02 02:40:00
2023-12-11T03:12:06.757588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:12:07.041934image/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

2023-12-11T03:12:07.304437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:07.467261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 10000
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7465
Distinct (%)79.7%
Missing632
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean342965.33
Minimum325831.39
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:07.665291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325831.39
5-th percentile335118.01
Q1339872.27
median342891.9
Q3345967.47
95-th percentile352783.95
Maximum358060.65
Range32229.256
Interquartile range (IQR)6095.2025

Descriptive statistics

Standard deviation4858.7347
Coefficient of variation (CV)0.014166839
Kurtosis0.58663163
Mean342965.33
Median Absolute Deviation (MAD)3044.6847
Skewness0.061153988
Sum3.2128992 × 109
Variance23607303
MonotonicityNot monotonic
2023-12-11T03:12:07.916813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343157.682044 55
 
0.5%
345141.357576 45
 
0.4%
344867.643963 33
 
0.3%
345549.11017 24
 
0.2%
345032.238221 17
 
0.2%
342935.432334 15
 
0.1%
339243.983122 15
 
0.1%
344047.164924 14
 
0.1%
339096.139718 14
 
0.1%
343461.958736 13
 
0.1%
Other values (7455) 9123
91.2%
(Missing) 632
 
6.3%
ValueCountFrequency (%)
325831.391262 1
< 0.1%
326154.899807 1
< 0.1%
326269.666487 1
< 0.1%
326417.272694 1
< 0.1%
326534.608033 1
< 0.1%
326610.275967 1
< 0.1%
326660.851514 1
< 0.1%
326703.14585 1
< 0.1%
326766.322228 1
< 0.1%
327051.071404 1
< 0.1%
ValueCountFrequency (%)
358060.647419 1
< 0.1%
356698.367083 1
< 0.1%
356668.763448 1
< 0.1%
356589.560791 1
< 0.1%
356578.373419 1
< 0.1%
356533.072677 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 

Distinct7466
Distinct (%)79.7%
Missing632
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean263523.88
Minimum238029.01
Maximum278909.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:08.219645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238029.01
5-th percentile257677.46
Q1261442.96
median263600.89
Q3265743.41
95-th percentile270725.95
Maximum278909.06
Range40880.052
Interquartile range (IQR)4300.4548

Descriptive statistics

Standard deviation4266.5881
Coefficient of variation (CV)0.016190518
Kurtosis4.8807061
Mean263523.88
Median Absolute Deviation (MAD)2151.6569
Skewness-0.89528701
Sum2.4686918 × 109
Variance18203774
MonotonicityNot monotonic
2023-12-11T03:12:08.533684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261957.795169 55
 
0.5%
267096.362462 45
 
0.4%
264091.210417 33
 
0.3%
268620.845678 24
 
0.2%
262949.871621 17
 
0.2%
268026.454531 15
 
0.1%
264310.975711 15
 
0.1%
265132.987974 14
 
0.1%
262466.933945 13
 
0.1%
264065.576741 13
 
0.1%
Other values (7456) 9124
91.2%
(Missing) 632
 
6.3%
ValueCountFrequency (%)
238029.007127 1
< 0.1%
239380.163891 1
< 0.1%
239687.676988 1
< 0.1%
240209.547189 1
< 0.1%
240270.873923 1
< 0.1%
240405.052319 1
< 0.1%
240460.074049 1
< 0.1%
240481.502376 1
< 0.1%
240550.011807 1
< 0.1%
240739.938523 1
< 0.1%
ValueCountFrequency (%)
278909.058905 1
 
< 0.1%
278336.223852 4
< 0.1%
278318.296599 1
 
< 0.1%
278269.027313 1
 
< 0.1%
278149.556874 2
< 0.1%
278148.233339 1
 
< 0.1%
278117.387967 1
 
< 0.1%
278116.5272 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

2023-12-11T03:12:08.858904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:09.057607image/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>
9525 
0
 
475

Length

Max length4
Median length4
Mean length3.8575
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> 9525
95.2%
0 475
 
4.8%

Length

2023-12-11T03:12:09.246201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:09.421326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9525
95.2%
0 475
 
4.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9524 
0
 
475
1
 
1

Length

Max length4
Median length4
Mean length3.8572
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> 9524
95.2%
0 475
 
4.8%
1 1
 
< 0.1%

Length

2023-12-11T03:12:09.627642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:09.809902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9524
95.2%
0 475
 
4.8%
1 1
 
< 0.1%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-11T03:12:10.000040image/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%
2023-12-11T03:12:10.791743image/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>
8149 
상수도전용
1833 
간이상수도
 
13
지하수전용
 
3
전용상수도(특정시설의 자가용 수도)
 
1

Length

Max length19
Median length4
Mean length4.1877
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8149
81.5%
상수도전용 1833
 
18.3%
간이상수도 13
 
0.1%
지하수전용 3
 
< 0.1%
전용상수도(특정시설의 자가용 수도) 1
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2023-12-11T03:12:11.008951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:11.251640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8149
81.5%
상수도전용 1833
 
18.3%
간이상수도 13
 
0.1%
지하수전용 3
 
< 0.1%
전용상수도(특정시설의 1
 
< 0.1%
자가용 1
 
< 0.1%
수도 1
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총직원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9561 
0
 
439

Length

Max length4
Median length4
Mean length3.8683
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> 9561
95.6%
0 439
 
4.4%

Length

2023-12-11T03:12:11.491067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:11.676654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9561
95.6%
0 439
 
4.4%

본사직원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6665 
<NA>
3315 
1
 
19
500
 
1

Length

Max length4
Median length1
Mean length1.9947
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6665
66.6%
<NA> 3315
33.1%
1 19
 
0.2%
500 1
 
< 0.1%

Length

2023-12-11T03:12:11.889976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:12.087900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6665
66.6%
na 3315
33.1%
1 19
 
0.2%
500 1
 
< 0.1%

공장사무직직원수
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6678 
<NA>
3315 
1
 
7

Length

Max length4
Median length1
Mean length1.9945
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6678
66.8%
<NA> 3315
33.1%
1 7
 
0.1%

Length

2023-12-11T03:12:12.298728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:12.498419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6678
66.8%
na 3315
33.1%
1 7
 
0.1%

공장판매직직원수
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6531 
<NA>
3315 
1
 
149
2
 
5

Length

Max length4
Median length1
Mean length1.9945
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6531
65.3%
<NA> 3315
33.1%
1 149
 
1.5%
2 5
 
0.1%

Length

2023-12-11T03:12:12.700925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:12.882518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6531
65.3%
na 3315
33.1%
1 149
 
1.5%
2 5
 
< 0.1%

공장생산직직원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6680 
<NA>
3315 
1
 
4
2
 
1

Length

Max length4
Median length1
Mean length1.9945
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6680
66.8%
<NA> 3315
33.1%
1 4
 
< 0.1%
2 1
 
< 0.1%

Length

2023-12-11T03:12:13.088935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:13.287503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6680
66.8%
na 3315
33.1%
1 4
 
< 0.1%
2 1
 
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7500 
자가
2054 
임대
 
446

Length

Max length4
Median length4
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7500
75.0%
자가 2054
 
20.5%
임대 446
 
4.5%

Length

2023-12-11T03:12:13.529678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:13.752245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7500
75.0%
자가 2054
 
20.5%
임대 446
 
4.5%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.5%
Missing8527
Missing (%)85.3%
Infinite0
Infinite (%)0.0%
Mean302107.94
Minimum0
Maximum1 × 108
Zeros1464
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:13.939983image/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 deviation4861573
Coefficient of variation (CV)16.092172
Kurtosis338.77662
Mean302107.94
Median Absolute Deviation (MAD)0
Skewness18.062006
Sum4.45005 × 108
Variance2.3634892 × 1013
MonotonicityNot monotonic
2023-12-11T03:12:14.181768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1464
 
14.6%
100000000 2
 
< 0.1%
80000000 2
 
< 0.1%
30000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 1
 
< 0.1%
5000 1
 
< 0.1%
(Missing) 8527
85.3%
ValueCountFrequency (%)
0 1464
14.6%
5000 1
 
< 0.1%
10000000 1
 
< 0.1%
15000000 1
 
< 0.1%
30000000 2
 
< 0.1%
80000000 2
 
< 0.1%
100000000 2
 
< 0.1%
ValueCountFrequency (%)
100000000 2
 
< 0.1%
80000000 2
 
< 0.1%
30000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 1
 
< 0.1%
5000 1
 
< 0.1%
0 1464
14.6%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.5%
Missing8528
Missing (%)85.3%
Infinite0
Infinite (%)0.0%
Mean2649.623
Minimum0
Maximum1100000
Zeros1464
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:14.384002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1100000
Range1100000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation43470.032
Coefficient of variation (CV)16.40612
Kurtosis399.76512
Mean2649.623
Median Absolute Deviation (MAD)0
Skewness19.08441
Sum3900245
Variance1.8896437 × 109
MonotonicityNot monotonic
2023-12-11T03:12:14.597526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1464
 
14.6%
500000 2
 
< 0.1%
200000 2
 
< 0.1%
800000 1
 
< 0.1%
600000 1
 
< 0.1%
1100000 1
 
< 0.1%
245 1
 
< 0.1%
(Missing) 8528
85.3%
ValueCountFrequency (%)
0 1464
14.6%
245 1
 
< 0.1%
200000 2
 
< 0.1%
500000 2
 
< 0.1%
600000 1
 
< 0.1%
800000 1
 
< 0.1%
1100000 1
 
< 0.1%
ValueCountFrequency (%)
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 1464
14.6%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2023-12-11T03:12:14.766716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

SKEWED  ZEROS 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.062795
Minimum0
Maximum163.66
Zeros9869
Zeros (%)98.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T03:12:14.948775image/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 deviation1.9651411
Coefficient of variation (CV)31.294547
Kurtosis4986.4162
Mean0.062795
Median Absolute Deviation (MAD)0
Skewness64.70853
Sum627.95
Variance3.8617795
MonotonicityNot monotonic
2023-12-11T03:12:15.167775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 9869
98.7%
1.0 98
 
1.0%
2.0 9
 
0.1%
3.0 6
 
0.1%
1.5 2
 
< 0.1%
15.0 1
 
< 0.1%
3.3 1
 
< 0.1%
6.0 1
 
< 0.1%
16.6 1
 
< 0.1%
7.0 1
 
< 0.1%
Other values (11) 11
 
0.1%
ValueCountFrequency (%)
0.0 9869
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 1
 
< 0.1%
6.0 1
 
< 0.1%
7.0 1
 
< 0.1%
9.66 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
56455646식품자동판매기업07_22_10_P34500003450000-112-2004-0019420040914<NA>3폐업2폐업20060414<NA><NA><NA>053 3215264<NA>702877대구광역시 북구 국우동 1108-4<NA><NA>놋그릇왕대포20040914000000I2018-08-31 23:59:59.0식품자동판매기영업342011.265467273084.294496식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
88018802식품자동판매기업07_22_10_P34600003460000-112-2019-0000320190219<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3706836대구광역시 수성구 수성동4가 1085-32 대구은행역, 지하1층대구광역시 수성구 달구벌대로 지하 2300, 대구은행역 지하1층 (수성동4가)42123이마트24에스대구은행역20190413165951U2019-04-16 02:40:00.0식품자동판매기영업345996.651576263381.750739식품자동판매기영업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
88718872식품자동판매기업07_22_10_P34700003470000-112-2002-0002120020109<NA>3폐업2폐업20040323<NA><NA><NA>053 5228530<NA>704942대구광역시 달서구 본리동 1199-8<NA><NA>A할인마트20020522000000I2018-08-31 23:59:59.0식품자동판매기영업338196.362957261069.009421식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
94809481식품자동판매기업07_22_10_P34700003470000-112-2001-0048420010730<NA>3폐업2폐업20050407<NA><NA><NA>053 5610739<NA>704902대구광역시 달서구 감삼동 22-19<NA><NA>조세빈헤어라인20020520000000I2018-08-31 23:59:59.0식품자동판매기영업339202.091561262840.284583식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
96709671식품자동판매기업07_22_10_P34700003470000-112-2001-0042320010709<NA>3폐업2폐업20031104<NA><NA><NA>053 6217166<NA>704813대구광역시 달서구 상인동 800-4<NA><NA>주공알뜰슈퍼20020517000000I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
79837984식품자동판매기업07_22_10_P34600003460000-112-2001-0016020010214<NA>3폐업2폐업20110805<NA><NA><NA>7520210<NA>706803대구광역시 수성구 만촌동 1326-6<NA><NA>최가네 식당20020117000000I2018-08-31 23:59:59.0식품자동판매기영업347670.144233264730.731987식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
56065607식품자동판매기업07_22_10_P34500003450000-112-2004-0040920040617<NA>3폐업2폐업20201123<NA><NA><NA>063 641 8683<NA>702853대구광역시 북구 칠성동2가 385-19대구광역시 북구 칠성로17길 15 (칠성동2가)41579일신서점20201123160248U2020-11-25 02:40:00.0식품자동판매기영업344267.627207265576.039647식품자동판매기영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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