Overview

Dataset statistics

Number of variables44
Number of observations3556
Missing cells35317
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory376.0 B

Variable types

Numeric13
Categorical15
Text7
DateTime4
Unsupported4
Boolean1

Dataset

Description23년11월_6270000_대구광역시_06_20_01_P_세탁업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000101292&dataSetDetailId=DDI_0000101307&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (87.0%)Imbalance
위생업태명 is highly imbalanced (87.0%)Imbalance
사용시작지하층 is highly imbalanced (58.4%)Imbalance
사용끝지하층 is highly imbalanced (58.0%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3556 (100.0%) missing valuesMissing
폐업일자 has 1084 (30.5%) missing valuesMissing
휴업시작일자 has 3556 (100.0%) missing valuesMissing
휴업종료일자 has 3556 (100.0%) missing valuesMissing
재개업일자 has 3556 (100.0%) missing valuesMissing
소재지전화 has 245 (6.9%) missing valuesMissing
소재지면적 has 88 (2.5%) missing valuesMissing
소재지우편번호 has 39 (1.1%) missing valuesMissing
도로명전체주소 has 1351 (38.0%) missing valuesMissing
도로명우편번호 has 1373 (38.6%) missing valuesMissing
좌표정보(X) has 201 (5.7%) missing valuesMissing
좌표정보(Y) has 201 (5.7%) missing valuesMissing
건물지상층수 has 816 (22.9%) missing valuesMissing
건물지하층수 has 1355 (38.1%) missing valuesMissing
사용끝지상층 has 1176 (33.1%) missing valuesMissing
조건부허가신고사유 has 3554 (99.9%) missing valuesMissing
세탁기수 has 1702 (47.9%) missing valuesMissing
여성종사자수 has 3093 (87.0%) missing valuesMissing
남성종사자수 has 3009 (84.6%) missing valuesMissing
회수건조기수 has 1798 (50.6%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 46.09400196)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
소재지면적 has 698 (19.6%) zerosZeros
건물지상층수 has 910 (25.6%) zerosZeros
건물지하층수 has 1732 (48.7%) zerosZeros
사용끝지상층 has 538 (15.1%) zerosZeros
세탁기수 has 614 (17.3%) zerosZeros
여성종사자수 has 322 (9.1%) zerosZeros
남성종사자수 has 302 (8.5%) zerosZeros
회수건조기수 has 995 (28.0%) zerosZeros

Reproduction

Analysis started2023-12-16 05:08:11.635233
Analysis finished2023-12-16 05:08:16.169606
Duration4.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3556
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1778.5
Minimum1
Maximum3556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:08:16.526793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile178.75
Q1889.75
median1778.5
Q32667.25
95-th percentile3378.25
Maximum3556
Range3555
Interquartile range (IQR)1777.5

Descriptive statistics

Standard deviation1026.6731
Coefficient of variation (CV)0.57726911
Kurtosis-1.2
Mean1778.5
Median Absolute Deviation (MAD)889
Skewness0
Sum6324346
Variance1054057.7
MonotonicityStrictly increasing
2023-12-16T05:08:17.769455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2377 1
 
< 0.1%
2366 1
 
< 0.1%
2367 1
 
< 0.1%
2368 1
 
< 0.1%
2369 1
 
< 0.1%
2370 1
 
< 0.1%
2371 1
 
< 0.1%
2372 1
 
< 0.1%
2373 1
 
< 0.1%
Other values (3546) 3546
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3556 1
< 0.1%
3555 1
< 0.1%
3554 1
< 0.1%
3553 1
< 0.1%
3552 1
< 0.1%
3551 1
< 0.1%
3550 1
< 0.1%
3549 1
< 0.1%
3548 1
< 0.1%
3547 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
세탁업
3556 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 3556
100.0%

Length

2023-12-16T05:08:18.556407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:19.134135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 3556
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
06_20_01_P
3556 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row06_20_01_P
2nd row06_20_01_P
3rd row06_20_01_P
4th row06_20_01_P
5th row06_20_01_P

Common Values

ValueCountFrequency (%)
06_20_01_P 3556
100.0%

Length

2023-12-16T05:08:19.806419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:20.383821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 3556
100.0%

개방자치단체코드
Real number (ℝ)

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3457387.2
Minimum3410000
Maximum5141000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:08:20.824879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum5141000
Range1731000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation125069.3
Coefficient of variation (CV)0.036174514
Kurtosis172.79755
Mean3457387.2
Median Absolute Deviation (MAD)20000
Skewness13.037387
Sum1.2294469 × 1010
Variance1.564233 × 1010
MonotonicityIncreasing
2023-12-16T05:08:21.513790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3470000 745
21.0%
3460000 639
18.0%
3420000 519
14.6%
3450000 511
14.4%
3430000 400
11.2%
3440000 350
9.8%
3480000 212
 
6.0%
3410000 161
 
4.5%
5141000 19
 
0.5%
ValueCountFrequency (%)
3410000 161
 
4.5%
3420000 519
14.6%
3430000 400
11.2%
3440000 350
9.8%
3450000 511
14.4%
3460000 639
18.0%
3470000 745
21.0%
3480000 212
 
6.0%
5141000 19
 
0.5%
ValueCountFrequency (%)
5141000 19
 
0.5%
3480000 212
 
6.0%
3470000 745
21.0%
3460000 639
18.0%
3450000 511
14.4%
3440000 350
9.8%
3430000 400
11.2%
3420000 519
14.6%
3410000 161
 
4.5%

관리번호
Text

UNIQUE 

Distinct3556
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-16T05:08:22.298001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters78232
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

Unique3556 ?
Unique (%)100.0%

Sample

1st row3410000-205-2003-00002
2nd row3410000-205-2008-00002
3rd row3410000-205-2003-00017
4th row3410000-205-1987-00026
5th row3410000-205-1999-00003
ValueCountFrequency (%)
3410000-205-2003-00002 1
 
< 0.1%
3460000-205-2010-00006 1
 
< 0.1%
3460000-205-2008-00007 1
 
< 0.1%
3460000-205-1997-00028 1
 
< 0.1%
3460000-205-1999-00023 1
 
< 0.1%
3460000-205-1992-00017 1
 
< 0.1%
3460000-205-2014-00004 1
 
< 0.1%
3460000-205-2002-00014 1
 
< 0.1%
3460000-205-1996-00012 1
 
< 0.1%
3460000-205-1996-00033 1
 
< 0.1%
Other values (3546) 3546
99.7%
2023-12-16T05:08:24.595862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34118
43.6%
- 10668
 
13.6%
2 7311
 
9.3%
3 5271
 
6.7%
5 4824
 
6.2%
4 4698
 
6.0%
1 3852
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1358
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67564
86.4%
Dash Punctuation 10668
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34118
50.5%
2 7311
 
10.8%
3 5271
 
7.8%
5 4824
 
7.1%
4 4698
 
7.0%
1 3852
 
5.7%
9 3255
 
4.8%
7 1603
 
2.4%
6 1358
 
2.0%
8 1274
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 10668
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34118
43.6%
- 10668
 
13.6%
2 7311
 
9.3%
3 5271
 
6.7%
5 4824
 
6.2%
4 4698
 
6.0%
1 3852
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1358
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34118
43.6%
- 10668
 
13.6%
2 7311
 
9.3%
3 5271
 
6.7%
5 4824
 
6.2%
4 4698
 
6.0%
1 3852
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1358
 
1.7%
Distinct2357
Distinct (%)66.4%
Missing8
Missing (%)0.2%
Memory size27.9 KiB
Minimum1971-03-01 00:00:00
Maximum2023-09-06 00:00:00
2023-12-16T05:08:25.537203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:08:26.703043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3556
Missing (%)100.0%
Memory size31.4 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
3
2472 
1
1084 

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 2472
69.5%
1 1084
30.5%

Length

2023-12-16T05:08:27.663775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:28.385795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2472
69.5%
1 1084
30.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
폐업
2472 
영업/정상
1084 

Length

Max length5
Median length2
Mean length2.9145107
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2472
69.5%
영업/정상 1084
30.5%

Length

2023-12-16T05:08:29.622430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:30.508198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2472
69.5%
영업/정상 1084
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2
2472 
1
1084 

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 2472
69.5%
1 1084
30.5%

Length

2023-12-16T05:08:31.156430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:31.805600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2472
69.5%
1 1084
30.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
폐업
2472 
영업
1084 

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 2472
69.5%
영업 1084
30.5%

Length

2023-12-16T05:08:32.329725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:08:33.104416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2472
69.5%
영업 1084
30.5%

폐업일자
Date

MISSING 

Distinct1680
Distinct (%)68.0%
Missing1084
Missing (%)30.5%
Memory size27.9 KiB
Minimum1997-01-10 00:00:00
Maximum2023-11-29 00:00:00
2023-12-16T05:08:33.936851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:08:34.749206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3556
Missing (%)100.0%
Memory size31.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3556
Missing (%)100.0%
Memory size31.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3556
Missing (%)100.0%
Memory size31.4 KiB

소재지전화
Text

MISSING 

Distinct3131
Distinct (%)94.6%
Missing245
Missing (%)6.9%
Memory size27.9 KiB
2023-12-16T05:08:36.051941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.233162
Min length7

Characters and Unicode

Total characters37193
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

Unique2957 ?
Unique (%)89.3%

Sample

1st row053 4214559
2nd row053 423 2033
3rd row053 2540763
4th row053 4259032
5th row053 4243594
ValueCountFrequency (%)
053 3030
42.0%
764 28
 
0.4%
791 25
 
0.3%
763 21
 
0.3%
762 19
 
0.3%
754 19
 
0.3%
792 18
 
0.2%
765 17
 
0.2%
781 17
 
0.2%
752 15
 
0.2%
Other values (3228) 4006
55.5%
2023-12-16T05:08:39.286717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6657
17.9%
3 5641
15.2%
0 5085
13.7%
3944
10.6%
6 2801
7.5%
2 2681
7.2%
7 2449
 
6.6%
4 2164
 
5.8%
1 1962
 
5.3%
8 1941
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33249
89.4%
Space Separator 3944
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6657
20.0%
3 5641
17.0%
0 5085
15.3%
6 2801
8.4%
2 2681
8.1%
7 2449
 
7.4%
4 2164
 
6.5%
1 1962
 
5.9%
8 1941
 
5.8%
9 1868
 
5.6%
Space Separator
ValueCountFrequency (%)
3944
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6657
17.9%
3 5641
15.2%
0 5085
13.7%
3944
10.6%
6 2801
7.5%
2 2681
7.2%
7 2449
 
6.6%
4 2164
 
5.8%
1 1962
 
5.3%
8 1941
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6657
17.9%
3 5641
15.2%
0 5085
13.7%
3944
10.6%
6 2801
7.5%
2 2681
7.2%
7 2449
 
6.6%
4 2164
 
5.8%
1 1962
 
5.3%
8 1941
 
5.2%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1284
Distinct (%)37.0%
Missing88
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean32.991646
Minimum0
Maximum5601
Zeros698
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:08:40.319639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.91
median26.235
Q336.885
95-th percentile79.79
Maximum5601
Range5601
Interquartile range (IQR)21.975

Descriptive statistics

Standard deviation102.88841
Coefficient of variation (CV)3.11862
Kurtosis2476.5451
Mean32.991646
Median Absolute Deviation (MAD)11.235
Skewness46.094002
Sum114415.03
Variance10586.024
MonotonicityNot monotonic
2023-12-16T05:08:40.888820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 698
 
19.6%
33.0 84
 
2.4%
30.0 59
 
1.7%
26.4 49
 
1.4%
16.5 45
 
1.3%
20.0 43
 
1.2%
19.8 42
 
1.2%
36.0 38
 
1.1%
23.1 37
 
1.0%
24.0 35
 
1.0%
Other values (1274) 2338
65.7%
(Missing) 88
 
2.5%
ValueCountFrequency (%)
0.0 698
19.6%
5.0 1
 
< 0.1%
7.0 2
 
0.1%
8.0 2
 
0.1%
8.56 1
 
< 0.1%
9.0 1
 
< 0.1%
9.5 1
 
< 0.1%
9.9 6
 
0.2%
9.92 1
 
< 0.1%
10.0 4
 
0.1%
ValueCountFrequency (%)
5601.0 1
< 0.1%
673.34 1
< 0.1%
522.92 1
< 0.1%
489.0 1
< 0.1%
486.0 1
< 0.1%
450.0 1
< 0.1%
415.74 1
< 0.1%
409.53 1
< 0.1%
389.94 1
< 0.1%
363.0 1
< 0.1%

소재지우편번호
Text

MISSING 

Distinct566
Distinct (%)16.1%
Missing39
Missing (%)1.1%
Memory size27.9 KiB
2023-12-16T05:08:41.813218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters24619
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

Unique133 ?
Unique (%)3.8%

Sample

1st row700-413
2nd row700-421
3rd row700-340
4th row700-809
5th row700-100
ValueCountFrequency (%)
704-080 49
 
1.4%
702-040 40
 
1.1%
706-170 36
 
1.0%
701-804 32
 
0.9%
704-060 30
 
0.9%
704-932 23
 
0.7%
706-838 23
 
0.7%
711-812 22
 
0.6%
706-831 22
 
0.6%
704-936 20
 
0.6%
Other values (556) 3220
91.6%
2023-12-16T05:08:43.900021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4880
19.8%
7 4069
16.5%
- 3517
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1564
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1112
 
4.5%
5 892
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21102
85.7%
Dash Punctuation 3517
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4880
23.1%
7 4069
19.3%
8 3148
14.9%
1 1893
 
9.0%
4 1564
 
7.4%
2 1516
 
7.2%
3 1409
 
6.7%
6 1112
 
5.3%
5 892
 
4.2%
9 619
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 3517
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24619
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4880
19.8%
7 4069
16.5%
- 3517
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1564
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1112
 
4.5%
5 892
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24619
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4880
19.8%
7 4069
16.5%
- 3517
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1564
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1112
 
4.5%
5 892
 
3.6%
Distinct3400
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-16T05:08:45.462098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length51
Mean length25.206974
Min length16

Characters and Unicode

Total characters89636
Distinct characters357
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3254 ?
Unique (%)91.5%

Sample

1st row대구광역시 중구 삼덕동3가 300-0001번지
2nd row대구광역시 중구 동인동1가 0233-0001번지
3rd row대구광역시 중구 북내동 0031-0001번지
4th row대구광역시 중구 대봉동 10-1번지
5th row대구광역시 중구 화전동 28번지
ValueCountFrequency (%)
대구광역시 3556
 
21.2%
달서구 745
 
4.4%
수성구 639
 
3.8%
동구 519
 
3.1%
북구 511
 
3.1%
서구 400
 
2.4%
남구 350
 
2.1%
대명동 231
 
1.4%
달성군 212
 
1.3%
중구 161
 
1.0%
Other values (4193) 9428
56.3%
2023-12-16T05:08:48.555344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16232
18.1%
6965
 
7.8%
1 4735
 
5.3%
4520
 
5.0%
3963
 
4.4%
3627
 
4.0%
3569
 
4.0%
3567
 
4.0%
3346
 
3.7%
2959
 
3.3%
Other values (347) 36153
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50557
56.4%
Decimal Number 19527
 
21.8%
Space Separator 16232
 
18.1%
Dash Punctuation 2847
 
3.2%
Close Punctuation 179
 
0.2%
Open Punctuation 179
 
0.2%
Uppercase Letter 69
 
0.1%
Other Punctuation 37
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6965
13.8%
4520
 
8.9%
3963
 
7.8%
3627
 
7.2%
3569
 
7.1%
3567
 
7.1%
3346
 
6.6%
2959
 
5.9%
1289
 
2.5%
1207
 
2.4%
Other values (316) 15545
30.7%
Uppercase Letter
ValueCountFrequency (%)
A 22
31.9%
B 17
24.6%
P 10
14.5%
T 10
14.5%
S 2
 
2.9%
K 2
 
2.9%
L 2
 
2.9%
C 1
 
1.4%
H 1
 
1.4%
D 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 4735
24.2%
0 2449
12.5%
2 2418
12.4%
3 1892
 
9.7%
4 1596
 
8.2%
5 1498
 
7.7%
6 1353
 
6.9%
7 1256
 
6.4%
9 1174
 
6.0%
8 1156
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 24
64.9%
. 8
 
21.6%
/ 4
 
10.8%
@ 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
e 8
88.9%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
16232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2847
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50557
56.4%
Common 39001
43.5%
Latin 78
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6965
13.8%
4520
 
8.9%
3963
 
7.8%
3627
 
7.2%
3569
 
7.1%
3567
 
7.1%
3346
 
6.6%
2959
 
5.9%
1289
 
2.5%
1207
 
2.4%
Other values (316) 15545
30.7%
Common
ValueCountFrequency (%)
16232
41.6%
1 4735
 
12.1%
- 2847
 
7.3%
0 2449
 
6.3%
2 2418
 
6.2%
3 1892
 
4.9%
4 1596
 
4.1%
5 1498
 
3.8%
6 1353
 
3.5%
7 1256
 
3.2%
Other values (8) 2725
 
7.0%
Latin
ValueCountFrequency (%)
A 22
28.2%
B 17
21.8%
P 10
12.8%
T 10
12.8%
e 8
 
10.3%
S 2
 
2.6%
K 2
 
2.6%
L 2
 
2.6%
C 1
 
1.3%
s 1
 
1.3%
Other values (3) 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50557
56.4%
ASCII 39079
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16232
41.5%
1 4735
 
12.1%
- 2847
 
7.3%
0 2449
 
6.3%
2 2418
 
6.2%
3 1892
 
4.8%
4 1596
 
4.1%
5 1498
 
3.8%
6 1353
 
3.5%
7 1256
 
3.2%
Other values (21) 2803
 
7.2%
Hangul
ValueCountFrequency (%)
6965
13.8%
4520
 
8.9%
3963
 
7.8%
3627
 
7.2%
3569
 
7.1%
3567
 
7.1%
3346
 
6.6%
2959
 
5.9%
1289
 
2.5%
1207
 
2.4%
Other values (316) 15545
30.7%

도로명전체주소
Text

MISSING 

Distinct2170
Distinct (%)98.4%
Missing1351
Missing (%)38.0%
Memory size27.9 KiB
2023-12-16T05:08:49.887633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length52
Mean length30.506576
Min length15

Characters and Unicode

Total characters67267
Distinct characters375
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2137 ?
Unique (%)96.9%

Sample

1st row대구광역시 중구 서성로16길 28 (북내동)
2nd row대구광역시 중구 중앙대로66길 44 (남산동)
3rd row대구광역시 중구 국채보상로131길 55 (동인동1가, 시티타운상가 15호)
4th row대구광역시 중구 관덕정길 56 (남산동)
5th row대구광역시 중구 국채보상로93길 25 (대신동)
ValueCountFrequency (%)
대구광역시 2205
 
16.8%
달서구 452
 
3.4%
수성구 400
 
3.0%
북구 364
 
2.8%
1층 332
 
2.5%
동구 283
 
2.2%
서구 226
 
1.7%
남구 222
 
1.7%
달성군 158
 
1.2%
대명동 148
 
1.1%
Other values (2793) 8325
63.5%
2023-12-16T05:08:52.406296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10915
 
16.2%
4492
 
6.7%
3238
 
4.8%
1 3041
 
4.5%
2804
 
4.2%
2292
 
3.4%
2229
 
3.3%
2211
 
3.3%
) 2172
 
3.2%
( 2172
 
3.2%
Other values (365) 31701
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38724
57.6%
Decimal Number 11262
 
16.7%
Space Separator 10915
 
16.2%
Close Punctuation 2172
 
3.2%
Open Punctuation 2172
 
3.2%
Other Punctuation 1545
 
2.3%
Dash Punctuation 395
 
0.6%
Uppercase Letter 74
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4492
 
11.6%
3238
 
8.4%
2804
 
7.2%
2292
 
5.9%
2229
 
5.8%
2211
 
5.7%
2079
 
5.4%
1471
 
3.8%
958
 
2.5%
950
 
2.5%
Other values (334) 16000
41.3%
Uppercase Letter
ValueCountFrequency (%)
A 27
36.5%
B 12
16.2%
T 11
14.9%
P 11
14.9%
D 3
 
4.1%
K 3
 
4.1%
S 2
 
2.7%
C 2
 
2.7%
H 1
 
1.4%
L 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 3041
27.0%
2 1582
14.0%
0 1301
11.6%
3 1203
 
10.7%
4 905
 
8.0%
5 864
 
7.7%
6 716
 
6.4%
7 640
 
5.7%
8 534
 
4.7%
9 476
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 1529
99.0%
@ 10
 
0.6%
. 4
 
0.3%
/ 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 7
87.5%
s 1
 
12.5%
Space Separator
ValueCountFrequency (%)
10915
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2172
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 395
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38724
57.6%
Common 28461
42.3%
Latin 82
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4492
 
11.6%
3238
 
8.4%
2804
 
7.2%
2292
 
5.9%
2229
 
5.8%
2211
 
5.7%
2079
 
5.4%
1471
 
3.8%
958
 
2.5%
950
 
2.5%
Other values (334) 16000
41.3%
Common
ValueCountFrequency (%)
10915
38.4%
1 3041
 
10.7%
) 2172
 
7.6%
( 2172
 
7.6%
2 1582
 
5.6%
, 1529
 
5.4%
0 1301
 
4.6%
3 1203
 
4.2%
4 905
 
3.2%
5 864
 
3.0%
Other values (8) 2777
 
9.8%
Latin
ValueCountFrequency (%)
A 27
32.9%
B 12
14.6%
T 11
13.4%
P 11
13.4%
e 7
 
8.5%
D 3
 
3.7%
K 3
 
3.7%
S 2
 
2.4%
C 2
 
2.4%
s 1
 
1.2%
Other values (3) 3
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38724
57.6%
ASCII 28543
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10915
38.2%
1 3041
 
10.7%
) 2172
 
7.6%
( 2172
 
7.6%
2 1582
 
5.5%
, 1529
 
5.4%
0 1301
 
4.6%
3 1203
 
4.2%
4 905
 
3.2%
5 864
 
3.0%
Other values (21) 2859
 
10.0%
Hangul
ValueCountFrequency (%)
4492
 
11.6%
3238
 
8.4%
2804
 
7.2%
2292
 
5.9%
2229
 
5.8%
2211
 
5.7%
2079
 
5.4%
1471
 
3.8%
958
 
2.5%
950
 
2.5%
Other values (334) 16000
41.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1011
Distinct (%)46.3%
Missing1373
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean42081.735
Minimum41002
Maximum43149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:08:53.228821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41136
Q141551.5
median42132
Q342630
95-th percentile42938
Maximum43149
Range2147
Interquartile range (IQR)1078.5

Descriptive statistics

Standard deviation580.69748
Coefficient of variation (CV)0.013799276
Kurtosis-1.1903604
Mean42081.735
Median Absolute Deviation (MAD)537
Skewness-0.13396159
Sum91864428
Variance337209.56
MonotonicityNot monotonic
2023-12-16T05:08:54.068789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41569 9
 
0.3%
42644 7
 
0.2%
42446 7
 
0.2%
42769 7
 
0.2%
42970 7
 
0.2%
41534 7
 
0.2%
41450 7
 
0.2%
42679 7
 
0.2%
42452 7
 
0.2%
42915 7
 
0.2%
Other values (1001) 2111
59.4%
(Missing) 1373
38.6%
ValueCountFrequency (%)
41002 3
0.1%
41005 3
0.1%
41020 1
 
< 0.1%
41022 2
 
0.1%
41024 1
 
< 0.1%
41025 1
 
< 0.1%
41026 5
0.1%
41029 1
 
< 0.1%
41033 1
 
< 0.1%
41034 2
 
0.1%
ValueCountFrequency (%)
43149 2
 
0.1%
43129 1
 
< 0.1%
43119 1
 
< 0.1%
43117 1
 
< 0.1%
43115 5
0.1%
43114 1
 
< 0.1%
43102 1
 
< 0.1%
43022 1
 
< 0.1%
43018 1
 
< 0.1%
43014 2
 
0.1%
Distinct2284
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-16T05:08:55.466139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length5.1656355
Min length2

Characters and Unicode

Total characters18369
Distinct characters494
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1757 ?
Unique (%)49.4%

Sample

1st row진아
2nd row(주) 유니코
3rd row성주사
4th row백광
5th row백구세탁소
ValueCountFrequency (%)
현대세탁소 29
 
0.8%
제일세탁소 27
 
0.7%
세탁소 27
 
0.7%
보성세탁소 21
 
0.6%
우방세탁소 20
 
0.5%
백광세탁소 19
 
0.5%
백설세탁소 18
 
0.5%
백조세탁소 16
 
0.4%
명성세탁소 16
 
0.4%
백양세탁소 16
 
0.4%
Other values (2283) 3455
94.3%
2023-12-16T05:08:57.998206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2549
 
13.9%
2509
 
13.7%
1669
 
9.1%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
283
 
1.5%
252
 
1.4%
247
 
1.3%
Other values (484) 9063
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18030
98.2%
Space Separator 110
 
0.6%
Uppercase Letter 64
 
0.3%
Decimal Number 61
 
0.3%
Close Punctuation 35
 
0.2%
Open Punctuation 35
 
0.2%
Other Punctuation 15
 
0.1%
Lowercase Letter 14
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2549
 
14.1%
2509
 
13.9%
1669
 
9.3%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
283
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8724
48.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
10.9%
C 7
10.9%
O 6
 
9.4%
K 6
 
9.4%
G 4
 
6.2%
I 4
 
6.2%
D 4
 
6.2%
E 4
 
6.2%
L 4
 
6.2%
P 3
 
4.7%
Other values (8) 15
23.4%
Decimal Number
ValueCountFrequency (%)
1 18
29.5%
2 18
29.5%
3 9
14.8%
4 6
 
9.8%
5 3
 
4.9%
9 3
 
4.9%
8 2
 
3.3%
6 2
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
57.1%
r 2
 
14.3%
k 2
 
14.3%
a 1
 
7.1%
p 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 11
73.3%
, 2
 
13.3%
/ 1
 
6.7%
& 1
 
6.7%
Space Separator
ValueCountFrequency (%)
110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18030
98.2%
Common 261
 
1.4%
Latin 78
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2549
 
14.1%
2509
 
13.9%
1669
 
9.3%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
283
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8724
48.4%
Latin
ValueCountFrequency (%)
e 8
 
10.3%
A 7
 
9.0%
C 7
 
9.0%
O 6
 
7.7%
K 6
 
7.7%
G 4
 
5.1%
I 4
 
5.1%
D 4
 
5.1%
E 4
 
5.1%
L 4
 
5.1%
Other values (13) 24
30.8%
Common
ValueCountFrequency (%)
110
42.1%
) 35
 
13.4%
( 35
 
13.4%
1 18
 
6.9%
2 18
 
6.9%
. 11
 
4.2%
3 9
 
3.4%
4 6
 
2.3%
- 5
 
1.9%
5 3
 
1.1%
Other values (6) 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18030
98.2%
ASCII 339
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2549
 
14.1%
2509
 
13.9%
1669
 
9.3%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
283
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8724
48.4%
ASCII
ValueCountFrequency (%)
110
32.4%
) 35
 
10.3%
( 35
 
10.3%
1 18
 
5.3%
2 18
 
5.3%
. 11
 
3.2%
3 9
 
2.7%
e 8
 
2.4%
A 7
 
2.1%
C 7
 
2.1%
Other values (29) 81
23.9%
Distinct2696
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Minimum2001-09-10 00:00:00
Maximum2023-11-29 11:09:31
2023-12-16T05:08:58.916790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:09:00.517711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
I
2685 
U
871 

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 2685
75.5%
U 871
 
24.5%

Length

2023-12-16T05:09:01.410774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:02.073663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2685
75.5%
u 871
 
24.5%
Distinct523
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-01 02:40:00
2023-12-16T05:09:02.558810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T05:09:03.138523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
일반세탁업
3431 
운동화전문세탁업
 
88
세탁업 기타
 
24
빨래방업
 
13

Length

Max length8
Median length5
Mean length5.0773341
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3431
96.5%
운동화전문세탁업 88
 
2.5%
세탁업 기타 24
 
0.7%
빨래방업 13
 
0.4%

Length

2023-12-16T05:09:03.940903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:04.579906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3431
95.8%
운동화전문세탁업 88
 
2.5%
세탁업 24
 
0.7%
기타 24
 
0.7%
빨래방업 13
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2885
Distinct (%)86.0%
Missing201
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean343044.2
Minimum327557.24
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:05.161603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327557.24
5-th percentile334975.61
Q1339749.12
median342478.46
Q3346391.68
95-th percentile353156.53
Maximum358060.65
Range30503.408
Interquartile range (IQR)6642.5553

Descriptive statistics

Standard deviation5091.7308
Coefficient of variation (CV)0.014842784
Kurtosis0.22130514
Mean343044.2
Median Absolute Deviation (MAD)3268.4213
Skewness0.1081665
Sum1.1509133 × 109
Variance25925722
MonotonicityNot monotonic
2023-12-16T05:09:06.283786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
347296.208543798 5
 
0.1%
338969.480757299 5
 
0.1%
338962.151491269 5
 
0.1%
338692.161634264 5
 
0.1%
341420.593871095 4
 
0.1%
337885.924275265 4
 
0.1%
339201.745044261 4
 
0.1%
340425.612585211 4
 
0.1%
339393.012573076 4
 
0.1%
345038.837526749 4
 
0.1%
Other values (2875) 3311
93.1%
(Missing) 201
 
5.7%
ValueCountFrequency (%)
327557.239553708 1
< 0.1%
327770.336985265 1
< 0.1%
327811.761116979 1
< 0.1%
327853.173808645 1
< 0.1%
328223.184090209 1
< 0.1%
328342.10797327 1
< 0.1%
328420.408085296 1
< 0.1%
328446.299883876 1
< 0.1%
328896.964041988 1
< 0.1%
329116.875999959 1
< 0.1%
ValueCountFrequency (%)
358060.647418873 1
 
< 0.1%
356610.086476575 1
 
< 0.1%
356468.087524666 1
 
< 0.1%
356388.525061719 1
 
< 0.1%
356353.404987598 1
 
< 0.1%
356310.91765893 3
0.1%
356270.185688667 1
 
< 0.1%
356267.166058634 1
 
< 0.1%
356258.185380378 1
 
< 0.1%
356175.418160422 2
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2885
Distinct (%)86.0%
Missing201
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean263469.29
Minimum240358.72
Maximum307136.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:07.485179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257491.7
Q1261160.01
median263206.05
Q3265516.55
95-th percentile271099.35
Maximum307136.85
Range66778.124
Interquartile range (IQR)4356.5386

Descriptive statistics

Standard deviation5032.7059
Coefficient of variation (CV)0.019101679
Kurtosis21.002373
Mean263469.29
Median Absolute Deviation (MAD)2164.8543
Skewness2.1010092
Sum8.8393948 × 108
Variance25328129
MonotonicityNot monotonic
2023-12-16T05:09:08.312432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261275.08308428 5
 
0.1%
257548.491948507 5
 
0.1%
262515.182501563 5
 
0.1%
259135.243156101 5
 
0.1%
272763.955160132 4
 
0.1%
259679.933296511 4
 
0.1%
269601.265680049 4
 
0.1%
262761.163676007 4
 
0.1%
258572.019825526 4
 
0.1%
265537.218675911 4
 
0.1%
Other values (2875) 3311
93.1%
(Missing) 201
 
5.7%
ValueCountFrequency (%)
240358.722944009 1
< 0.1%
240622.56148125 1
< 0.1%
240649.764741954 1
< 0.1%
240755.21422067 1
< 0.1%
240854.426297061 1
< 0.1%
240894.621331233 1
< 0.1%
240899.421415258 1
< 0.1%
242471.306039654 1
< 0.1%
242492.351659569 1
< 0.1%
244642.33521458 1
< 0.1%
ValueCountFrequency (%)
307136.847106877 1
 
< 0.1%
305386.49674584 1
 
< 0.1%
305237.853638047 1
 
< 0.1%
305196.555870712 4
0.1%
305096.17721367 1
 
< 0.1%
304977.460110106 1
 
< 0.1%
304809.326510287 1
 
< 0.1%
304733.543504807 1
 
< 0.1%
300899.770702594 1
 
< 0.1%
300704.369610462 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
일반세탁업
3431 
운동화전문세탁업
 
88
세탁업 기타
 
24
빨래방업
 
13

Length

Max length8
Median length5
Mean length5.0773341
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3431
96.5%
운동화전문세탁업 88
 
2.5%
세탁업 기타 24
 
0.7%
빨래방업 13
 
0.4%

Length

2023-12-16T05:09:09.436072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:09.973344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3431
95.8%
운동화전문세탁업 88
 
2.5%
세탁업 24
 
0.7%
기타 24
 
0.7%
빨래방업 13
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.8%
Missing816
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean1.6777372
Minimum0
Maximum57
Zeros910
Zeros (%)25.6%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:10.456729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum57
Range57
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2943684
Coefficient of variation (CV)1.3675374
Kurtosis188.84101
Mean1.6777372
Median Absolute Deviation (MAD)1
Skewness10.219849
Sum4597
Variance5.2641263
MonotonicityNot monotonic
2023-12-16T05:09:10.777979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 910
25.6%
2 720
20.2%
3 528
14.8%
1 371
10.4%
4 146
 
4.1%
5 37
 
1.0%
6 7
 
0.2%
11 3
 
0.1%
20 3
 
0.1%
7 2
 
0.1%
Other values (11) 13
 
0.4%
(Missing) 816
22.9%
ValueCountFrequency (%)
0 910
25.6%
1 371
10.4%
2 720
20.2%
3 528
14.8%
4 146
 
4.1%
5 37
 
1.0%
6 7
 
0.2%
7 2
 
0.1%
8 1
 
< 0.1%
9 2
 
0.1%
ValueCountFrequency (%)
57 1
 
< 0.1%
40 1
 
< 0.1%
36 1
 
< 0.1%
32 1
 
< 0.1%
24 1
 
< 0.1%
20 3
0.1%
17 1
 
< 0.1%
15 2
0.1%
12 1
 
< 0.1%
11 3
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing1355
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean0.23307587
Minimum0
Maximum7
Zeros1732
Zeros (%)48.7%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:11.194591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50875609
Coefficient of variation (CV)2.1827917
Kurtosis29.886484
Mean0.23307587
Median Absolute Deviation (MAD)0
Skewness3.8038058
Sum513
Variance0.25883276
MonotonicityNot monotonic
2023-12-16T05:09:11.792048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1732
48.7%
1 447
 
12.6%
2 12
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1355
38.1%
ValueCountFrequency (%)
0 1732
48.7%
1 447
 
12.6%
2 12
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 4
 
0.1%
2 12
 
0.3%
1 447
 
12.6%
0 1732
48.7%
Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
1
1737 
<NA>
992 
0
770 
2
 
51
3
 
5

Length

Max length4
Median length1
Mean length1.8368954
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 (%)
1 1737
48.8%
<NA> 992
27.9%
0 770
21.7%
2 51
 
1.4%
3 5
 
0.1%
4 1
 
< 0.1%

Length

2023-12-16T05:09:12.582041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:13.340903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1737
48.8%
na 992
27.9%
0 770
21.7%
2 51
 
1.4%
3 5
 
0.1%
4 1
 
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing1176
Missing (%)33.1%
Infinite0
Infinite (%)0.0%
Mean0.81638655
Minimum0
Maximum10
Zeros538
Zeros (%)15.1%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:14.035708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58449956
Coefficient of variation (CV)0.71595931
Kurtosis78.763284
Mean0.81638655
Median Absolute Deviation (MAD)0
Skewness4.9834376
Sum1943
Variance0.34163973
MonotonicityNot monotonic
2023-12-16T05:09:14.725694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1777
50.0%
0 538
 
15.1%
2 54
 
1.5%
3 6
 
0.2%
10 3
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1176
33.1%
ValueCountFrequency (%)
0 538
 
15.1%
1 1777
50.0%
2 54
 
1.5%
3 6
 
0.2%
4 1
 
< 0.1%
6 1
 
< 0.1%
10 3
 
0.1%
ValueCountFrequency (%)
10 3
 
0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
3 6
 
0.2%
2 54
 
1.5%
1 1777
50.0%
0 538
 
15.1%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
0
1959 
<NA>
1558 
1
 
34
4
 
2
2
 
2

Length

Max length4
Median length1
Mean length2.3143982
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 (%)
0 1959
55.1%
<NA> 1558
43.8%
1 34
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2023-12-16T05:09:15.614705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:16.273124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1959
55.1%
na 1558
43.8%
1 34
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
1838 
0
1678 
1
 
35
4
 
2
2
 
2

Length

Max length4
Median length4
Mean length2.5506187
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> 1838
51.7%
0 1678
47.2%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2023-12-16T05:09:17.241989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:17.961795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1838
51.7%
0 1678
47.2%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%
Distinct2
Distinct (%)100.0%
Missing3554
Missing (%)99.9%
Memory size27.9 KiB
2023-12-16T05:09:18.810901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length70
Mean length70
Min length58

Characters and Unicode

Total characters140
Distinct characters75
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row폐업,지위승계등 금지(과태료50만원체납),'05,'07년 위생교육미필 2007.05.07현재행정처분진행중
2nd row가설건축물 존치기간(2007.11.30까지)만료시 존치기간 연장, 이전 또는 자진폐업을 하여야 하며 이를 이행하지 않을시 영업신고의 효력이 소멸됨.
ValueCountFrequency (%)
폐업,지위승계등 1
 
5.3%
자진폐업을 1
 
5.3%
효력이 1
 
5.3%
영업신고의 1
 
5.3%
않을시 1
 
5.3%
이행하지 1
 
5.3%
이를 1
 
5.3%
하며 1
 
5.3%
하여야 1
 
5.3%
또는 1
 
5.3%
Other values (9) 9
47.4%
2023-12-16T05:09:20.590727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
12.1%
0 10
 
7.1%
. 5
 
3.6%
7 4
 
2.9%
, 4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
3
 
2.1%
3
 
2.1%
Other values (65) 83
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
61.4%
Decimal Number 22
 
15.7%
Space Separator 17
 
12.1%
Other Punctuation 11
 
7.9%
Close Punctuation 2
 
1.4%
Open Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Decimal Number
ValueCountFrequency (%)
0 10
45.5%
7 4
 
18.2%
5 3
 
13.6%
2 2
 
9.1%
1 2
 
9.1%
3 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 5
45.5%
, 4
36.4%
' 2
 
18.2%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
61.4%
Common 54
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Common
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
61.4%
ASCII 54
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%
Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
3555 
20070213
 
1

Length

Max length8
Median length4
Mean length4.0011249
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3555
> 99.9%
20070213 1
 
< 0.1%

Length

2023-12-16T05:09:21.539945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:22.329434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3555
> 99.9%
20070213 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
3555 
20071130
 
1

Length

Max length8
Median length4
Mean length4.0011249
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3555
> 99.9%
20071130 1
 
< 0.1%

Length

2023-12-16T05:09:23.057575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:23.737363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3555
> 99.9%
20071130 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
1869 
임대
1425 
자가
262 

Length

Max length4
Median length4
Mean length3.0511811
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> 1869
52.6%
임대 1425
40.1%
자가 262
 
7.4%

Length

2023-12-16T05:09:24.452448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T05:09:25.123650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1869
52.6%
임대 1425
40.1%
자가 262
 
7.4%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.5%
Missing1702
Missing (%)47.9%
Infinite0
Infinite (%)0.0%
Mean1.2448759
Minimum0
Maximum20
Zeros614
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:25.770539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2148626
Coefficient of variation (CV)0.9758905
Kurtosis31.650613
Mean1.2448759
Median Absolute Deviation (MAD)1
Skewness2.7376005
Sum2308
Variance1.4758912
MonotonicityNot monotonic
2023-12-16T05:09:26.439466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 614
 
17.3%
2 592
 
16.6%
1 462
 
13.0%
3 127
 
3.6%
4 43
 
1.2%
5 7
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
20 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 1702
47.9%
ValueCountFrequency (%)
0 614
17.3%
1 462
13.0%
2 592
16.6%
3 127
 
3.6%
4 43
 
1.2%
5 7
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
9 1
 
< 0.1%
7 3
 
0.1%
6 4
 
0.1%
5 7
 
0.2%
4 43
 
1.2%
3 127
 
3.6%
2 592
16.6%
1 462
13.0%
0 614
17.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.9%
Missing3093
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean0.42332613
Minimum0
Maximum20
Zeros322
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:27.050153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2544536
Coefficient of variation (CV)2.9633266
Kurtosis139.15373
Mean0.42332613
Median Absolute Deviation (MAD)0
Skewness10.161584
Sum196
Variance1.5736538
MonotonicityNot monotonic
2023-12-16T05:09:27.651540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 322
 
9.1%
1 130
 
3.7%
2 3
 
0.1%
3 2
 
0.1%
5 2
 
0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 3093
87.0%
ValueCountFrequency (%)
0 322
9.1%
1 130
3.7%
2 3
 
0.1%
3 2
 
0.1%
5 2
 
0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
5 2
 
0.1%
3 2
 
0.1%
2 3
 
0.1%
1 130
3.7%
0 322
9.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.3%
Missing3009
Missing (%)84.6%
Infinite0
Infinite (%)0.0%
Mean0.51919561
Minimum0
Maximum9
Zeros302
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:28.470840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7638207
Coefficient of variation (CV)1.4711617
Kurtosis37.463028
Mean0.51919561
Median Absolute Deviation (MAD)0
Skewness4.2787669
Sum284
Variance0.58342206
MonotonicityNot monotonic
2023-12-16T05:09:29.058859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 302
 
8.5%
1 225
 
6.3%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 3009
84.6%
ValueCountFrequency (%)
0 302
8.5%
1 225
6.3%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 1
 
< 0.1%
4 2
 
0.1%
3 3
 
0.1%
2 13
 
0.4%
1 225
6.3%
0 302
8.5%

회수건조기수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing1798
Missing (%)50.6%
Infinite0
Infinite (%)0.0%
Mean0.46700796
Minimum0
Maximum10
Zeros995
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-16T05:09:30.174744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.62738967
Coefficient of variation (CV)1.3434239
Kurtosis38.586471
Mean0.46700796
Median Absolute Deviation (MAD)0
Skewness3.4817989
Sum821
Variance0.39361779
MonotonicityNot monotonic
2023-12-16T05:09:30.845024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 995
28.0%
1 731
20.6%
2 21
 
0.6%
3 6
 
0.2%
4 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1798
50.6%
ValueCountFrequency (%)
0 995
28.0%
1 731
20.6%
2 21
 
0.6%
3 6
 
0.2%
4 2
 
0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
0.1%
3 6
 
0.2%
2 21
 
0.6%
1 731
20.6%
0 995
28.0%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
False
3555 
True
 
1
ValueCountFrequency (%)
False 3555
> 99.9%
True 1
 
< 0.1%
2023-12-16T05:09:31.602557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조기수다중이용업소여부
01세탁업06_20_01_P34100003410000-205-2003-000021992-10-14<NA>3폐업2폐업2009-01-21<NA><NA><NA>053 4214559<NA>700-413대구광역시 중구 삼덕동3가 300-0001번지<NA><NA>진아2007-09-10 10:38:00I2018-08-31 23:59:59일반세탁업344952.904168263899.71513일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
12세탁업06_20_01_P34100003410000-205-2008-000022008-08-07<NA>3폐업2폐업2008-08-20<NA><NA><NA>053 423 20330.0700-421대구광역시 중구 동인동1가 0233-0001번지<NA><NA>(주) 유니코2008-08-07 11:11:17I2018-08-31 23:59:59일반세탁업344637.632881264667.618454일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
23세탁업06_20_01_P34100003410000-205-2003-000172003-09-08<NA>3폐업2폐업2016-03-22<NA><NA><NA>053 254076333.0700-340대구광역시 중구 북내동 0031-0001번지대구광역시 중구 서성로16길 28 (북내동)41919성주사2012-02-23 14:36:32I2018-08-31 23:59:59일반세탁업343440.170776264831.180532일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
34세탁업06_20_01_P34100003410000-205-1987-000261987-11-27<NA>3폐업2폐업2006-05-26<NA><NA><NA>053 425903226.64700-809대구광역시 중구 대봉동 10-1번지<NA><NA>백광2004-02-14 00:00:00I2018-08-31 23:59:59일반세탁업344983.552432263576.591255일반세탁업1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
45세탁업06_20_01_P34100003410000-205-1999-000031999-08-27<NA>3폐업2폐업2008-12-12<NA><NA><NA>053 42435940.0700-100대구광역시 중구 화전동 28번지<NA><NA>백구세탁소2007-08-28 13:38:13I2018-08-31 23:59:59일반세탁업343995.332261264874.973286일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
56세탁업06_20_01_P34100003410000-205-1987-000131987-08-19<NA>3폐업2폐업2009-01-08<NA><NA><NA>053 257190023.4700-360대구광역시 중구 도원동 3번지<NA><NA>고속사2007-08-28 10:38:54I2018-08-31 23:59:59일반세탁업<NA><NA>일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
67세탁업06_20_01_P34100003410000-205-1987-000141987-08-19<NA>3폐업2폐업2006-01-25<NA><NA><NA>053 254069024.6700-252대구광역시 중구 서문로2가 38-3번지<NA><NA>은성2004-02-13 00:00:00I2018-08-31 23:59:59일반세탁업343110.028589264537.556467일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
78세탁업06_20_01_P34100003410000-205-1988-000111988-06-20<NA>3폐업2폐업2009-01-19<NA><NA><NA>053 255055823.62700-330대구광역시 중구 서야동 28번지<NA><NA>제일사2007-08-28 10:42:05I2018-08-31 23:59:59일반세탁업343055.831616264767.125282일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
89세탁업06_20_01_P34100003410000-205-1987-000151987-08-19<NA>3폐업2폐업2009-01-08<NA><NA><NA>053 257347622.57700-819대구광역시 중구 대신동 1082번지<NA><NA>재건2009-02-05 17:04:30I2018-08-31 23:59:59일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
910세탁업06_20_01_P34100003410000-205-1987-000181987-08-19<NA>3폐업2폐업2009-01-20<NA><NA><NA>0530423312010.42700-803대구광역시 중구 남산동 659-9번지<NA><NA>광명2004-02-16 00:00:00I2018-08-31 23:59:59일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조기수다중이용업소여부
35463547세탁업06_20_01_P51410005141000-205-1987-000031987-05-09<NA>3폐업2폐업2014-09-11<NA><NA><NA>054 382782413.2<NA>대구광역시 군위군 의흥면 읍내리 577-4대구광역시 군위군 의흥면 읍내길 48-143149형제세탁소2012-05-23 11:02:00I2023-07-01 16:42:10일반세탁업354280.256756298511.42267일반세탁업000000<NA><NA><NA><NA>0000N
35473548세탁업06_20_01_P51410005141000-205-1987-000041987-05-09<NA>3폐업2폐업2002-05-31<NA><NA><NA><NA>0.0<NA>대구광역시 군위군 의흥면 읍내리 757<NA><NA>동아세탁소2002-07-10 00:00:00I2023-07-01 16:42:10일반세탁업353668.759048298647.358659일반세탁업000000<NA><NA><NA><NA>0000N
35483549세탁업06_20_01_P51410005141000-205-1994-000031994-07-28<NA>3폐업2폐업2013-09-04<NA><NA><NA>054 383023217.6<NA>대구광역시 군위군 군위읍 서부리 36-4대구광역시 군위군 군위읍 중앙길 9943115대백크리닝타운2011-10-21 10:56:47I2023-07-01 16:42:10일반세탁업340792.59292305196.555871일반세탁업000000<NA><NA><NA><NA>0000N
35493550세탁업06_20_01_P51410005141000-205-1997-000011997-11-10<NA>3폐업2폐업2011-07-11<NA><NA><NA>054 383787228.86<NA>대구광역시 군위군 군위읍 서부리 406<NA><NA>제일세탁소2009-12-03 16:45:33I2023-07-01 15:23:19일반세탁업<NA><NA>일반세탁업100000<NA><NA><NA>임대0000N
35503551세탁업06_20_01_P51410005141000-205-2000-000012000-03-15<NA>3폐업2폐업2005-01-29<NA><NA><NA>38247940.0<NA>대구광역시 군위군 우보면 이화리 1107-8<NA><NA>우일세탁소2005-01-29 00:00:00I2023-07-01 16:42:10일반세탁업349840.137032300899.770703일반세탁업000000<NA><NA><NA><NA>0000N
35513552세탁업06_20_01_P51410005141000-205-1987-000071987-05-07<NA>3폐업2폐업2008-05-07<NA><NA><NA>38299450.0<NA>대구광역시 군위군 우보면 이화리 1292-1<NA><NA>달구벌세탁소2003-03-06 00:00:00I2023-07-01 16:42:10일반세탁업349677.643879300704.36961일반세탁업000000<NA><NA><NA><NA>0000N
35523553세탁업06_20_01_P51410005141000-205-2002-000012002-10-10<NA>3폐업2폐업2005-09-26<NA><NA><NA>054 38366630.0<NA>대구광역시 군위군 군위읍 서부리 262-1<NA><NA>화이트212005-10-17 00:00:00I2023-07-01 16:42:10일반세탁업340742.666737304977.46011일반세탁업000000<NA><NA><NA><NA>0000N
35533554세탁업06_20_01_P51410005141000-205-1994-000041994-10-29<NA>3폐업2폐업2021-08-30<NA><NA><NA>054 38270459.9<NA>대구광역시 군위군 의흥면 읍내리 262-5대구광역시 군위군 의흥면 읍내길 6343149달구벌세탁소2021-08-30 15:59:19I2023-07-01 16:42:10일반세탁업354431.053741298454.611198일반세탁업000000<NA><NA><NA><NA>0000N
35543555세탁업06_20_01_P51410005141000-205-2009-000012009-10-26<NA>3폐업2폐업2023-08-18<NA><NA><NA>054 382320022.08<NA>대구광역시 군위군 군위읍 동부리 396-6대구광역시 군위군 군위읍 중앙길 12043114서울크리닝2023-08-18 15:50:09U2023-08-20 02:40:00일반세탁업340876.847131305386.496746일반세탁업000000<NA><NA><NA><NA>1000N
35553556세탁업06_20_01_P51410005141000-205-1987-000051987-08-31<NA>1영업/정상1영업<NA><NA><NA><NA>054 382075016.5<NA>대구광역시 군위군 군위읍 서부리 406-2대구광역시 군위군 군위읍 중앙길 8943115현대세탁소2009-04-24 15:04:24I2023-07-01 16:42:10일반세탁업340756.851659305096.177214일반세탁업000000<NA><NA><NA><NA>0000N