Overview

Dataset statistics

Number of variables44
Number of observations3558
Missing cells35205
Missing cells (%)22.5%
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

Description24년03월_6270000_대구광역시_06_20_01_P_세탁업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000106497&dataSetDetailId=DDI_0000106544&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (86.9%)Imbalance
위생업태명 is highly imbalanced (86.9%)Imbalance
사용시작지하층 is highly imbalanced (58.5%)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 3558 (100.0%) missing valuesMissing
폐업일자 has 1062 (29.8%) missing valuesMissing
휴업시작일자 has 3558 (100.0%) missing valuesMissing
휴업종료일자 has 3558 (100.0%) missing valuesMissing
재개업일자 has 3558 (100.0%) missing valuesMissing
소재지전화 has 246 (6.9%) missing valuesMissing
소재지면적 has 88 (2.5%) missing valuesMissing
소재지우편번호 has 40 (1.1%) missing valuesMissing
도로명전체주소 has 1351 (38.0%) missing valuesMissing
도로명우편번호 has 1373 (38.6%) missing valuesMissing
좌표정보(X) has 202 (5.7%) missing valuesMissing
좌표정보(Y) has 202 (5.7%) missing valuesMissing
건물지상층수 has 807 (22.7%) missing valuesMissing
건물지하층수 has 1344 (37.8%) missing valuesMissing
사용끝지상층 has 1166 (32.8%) missing valuesMissing
조건부허가신고사유 has 3556 (99.9%) missing valuesMissing
세탁기수 has 1691 (47.5%) missing valuesMissing
여성종사자수 has 3067 (86.2%) missing valuesMissing
남성종사자수 has 2983 (83.8%) missing valuesMissing
회수건조기수 has 1787 (50.2%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 46.09658622)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 696 (19.6%) zerosZeros
건물지상층수 has 918 (25.8%) zerosZeros
건물지하층수 has 1746 (49.1%) zerosZeros
사용끝지상층 has 547 (15.4%) zerosZeros
세탁기수 has 624 (17.5%) zerosZeros
여성종사자수 has 350 (9.8%) zerosZeros
남성종사자수 has 329 (9.2%) zerosZeros
회수건조기수 has 1004 (28.2%) zerosZeros

Reproduction

Analysis started2024-04-29 12:09:17.233230
Analysis finished2024-04-29 12:09:18.778187
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3558
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1779.5
Minimum1
Maximum3558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:18.857102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile178.85
Q1890.25
median1779.5
Q32668.75
95-th percentile3380.15
Maximum3558
Range3557
Interquartile range (IQR)1778.5

Descriptive statistics

Standard deviation1027.2505
Coefficient of variation (CV)0.57726915
Kurtosis-1.2
Mean1779.5
Median Absolute Deviation (MAD)889.5
Skewness0
Sum6331461
Variance1055243.5
MonotonicityStrictly increasing
2024-04-29T21:09:18.999366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2378 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%
2374 1
 
< 0.1%
Other values (3548) 3548
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 (%)
3558 1
< 0.1%
3557 1
< 0.1%
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%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
세탁업
3558 

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 3558
100.0%

Length

2024-04-29T21:09:19.122264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:19.237254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 3558
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
06_20_01_P
3558 

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 3558
100.0%

Length

2024-04-29T21:09:19.336990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:19.422062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 3558
100.0%

개방자치단체코드
Real number (ℝ)

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3457394.3
Minimum3410000
Maximum5141000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:19.503003image/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 deviation125034.72
Coefficient of variation (CV)0.036164436
Kurtosis172.89005
Mean3457394.3
Median Absolute Deviation (MAD)20000
Skewness13.040699
Sum1.2301409 × 1010
Variance1.5633681 × 1010
MonotonicityIncreasing
2024-04-29T21:09:19.610877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3470000 745
20.9%
3460000 640
18.0%
3420000 519
14.6%
3450000 511
14.4%
3430000 400
11.2%
3440000 350
9.8%
3480000 213
 
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 640
18.0%
3470000 745
20.9%
3480000 213
 
6.0%
5141000 19
 
0.5%
ValueCountFrequency (%)
5141000 19
 
0.5%
3480000 213
 
6.0%
3470000 745
20.9%
3460000 640
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 

Distinct3558
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-29T21:09:19.794422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters78276
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

Unique3558 ?
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%
3460000-205-1992-00015 1
 
< 0.1%
3460000-205-2005-00027 1
 
< 0.1%
3460000-205-1992-00002 1
 
< 0.1%
3460000-205-2004-00020 1
 
< 0.1%
3460000-205-1996-00034 1
 
< 0.1%
3460000-205-1996-00036 1
 
< 0.1%
3460000-205-1996-00037 1
 
< 0.1%
3460000-205-1996-00043 1
 
< 0.1%
3460000-205-1994-00022 1
 
< 0.1%
Other values (3548) 3548
99.7%
2024-04-29T21:09:20.116781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34138
43.6%
- 10674
 
13.6%
2 7317
 
9.3%
3 5274
 
6.7%
5 4826
 
6.2%
4 4701
 
6.0%
1 3854
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1359
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67602
86.4%
Dash Punctuation 10674
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34138
50.5%
2 7317
 
10.8%
3 5274
 
7.8%
5 4826
 
7.1%
4 4701
 
7.0%
1 3854
 
5.7%
9 3255
 
4.8%
7 1603
 
2.4%
6 1359
 
2.0%
8 1275
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 10674
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34138
43.6%
- 10674
 
13.6%
2 7317
 
9.3%
3 5274
 
6.7%
5 4826
 
6.2%
4 4701
 
6.0%
1 3854
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1359
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34138
43.6%
- 10674
 
13.6%
2 7317
 
9.3%
3 5274
 
6.7%
5 4826
 
6.2%
4 4701
 
6.0%
1 3854
 
4.9%
9 3255
 
4.2%
7 1603
 
2.0%
6 1359
 
1.7%
Distinct2359
Distinct (%)66.5%
Missing8
Missing (%)0.2%
Memory size27.9 KiB
Minimum1971-03-01 00:00:00
Maximum2024-02-23 00:00:00
2024-04-29T21:09:20.252514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:09:20.382839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3558
Missing (%)100.0%
Memory size31.4 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
3
2496 
1
1062 

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 2496
70.2%
1 1062
29.8%

Length

2024-04-29T21:09:20.509991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:20.609005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2496
70.2%
1 1062
29.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
폐업
2496 
영업/정상
1062 

Length

Max length5
Median length2
Mean length2.8954469
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2496
70.2%
영업/정상 1062
29.8%

Length

2024-04-29T21:09:20.716923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:20.813968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2496
70.2%
영업/정상 1062
29.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2
2496 
1
1062 

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 2496
70.2%
1 1062
29.8%

Length

2024-04-29T21:09:20.916949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:21.007872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2496
70.2%
1 1062
29.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
폐업
2496 
영업
1062 

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 2496
70.2%
영업 1062
29.8%

Length

2024-04-29T21:09:21.097704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:21.184246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2496
70.2%
영업 1062
29.8%

폐업일자
Date

MISSING 

Distinct1696
Distinct (%)67.9%
Missing1062
Missing (%)29.8%
Memory size27.9 KiB
Minimum1997-01-10 00:00:00
Maximum2024-03-25 00:00:00
2024-04-29T21:09:21.303830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:09:21.428822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3558
Missing (%)100.0%
Memory size31.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3558
Missing (%)100.0%
Memory size31.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3558
Missing (%)100.0%
Memory size31.4 KiB

소재지전화
Text

MISSING 

Distinct3132
Distinct (%)94.6%
Missing246
Missing (%)6.9%
Memory size27.9 KiB
2024-04-29T21:09:21.675991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.233092
Min length7

Characters and Unicode

Total characters37204
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

Unique2958 ?
Unique (%)89.3%

Sample

1st row053 4214559
2nd row053 423 2033
3rd row053 2540763
4th row053 4259032
5th row053 4243594
ValueCountFrequency (%)
053 3031
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%
781 17
 
0.2%
765 17
 
0.2%
782 15
 
0.2%
Other values (3229) 4007
55.5%
2024-04-29T21:09:22.073554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6660
17.9%
3 5642
15.2%
0 5086
13.7%
3945
10.6%
6 2801
7.5%
2 2682
7.2%
7 2450
 
6.6%
4 2166
 
5.8%
1 1963
 
5.3%
8 1941
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33259
89.4%
Space Separator 3945
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6660
20.0%
3 5642
17.0%
0 5086
15.3%
6 2801
8.4%
2 2682
8.1%
7 2450
 
7.4%
4 2166
 
6.5%
1 1963
 
5.9%
8 1941
 
5.8%
9 1868
 
5.6%
Space Separator
ValueCountFrequency (%)
3945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6660
17.9%
3 5642
15.2%
0 5086
13.7%
3945
10.6%
6 2801
7.5%
2 2682
7.2%
7 2450
 
6.6%
4 2166
 
5.8%
1 1963
 
5.3%
8 1941
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6660
17.9%
3 5642
15.2%
0 5086
13.7%
3945
10.6%
6 2801
7.5%
2 2682
7.2%
7 2450
 
6.6%
4 2166
 
5.8%
1 1963
 
5.3%
8 1941
 
5.2%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1287
Distinct (%)37.1%
Missing88
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean33.045994
Minimum0
Maximum5601
Zeros696
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:22.198384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median26.25
Q336.99
95-th percentile80
Maximum5601
Range5601
Interquartile range (IQR)21.99

Descriptive statistics

Standard deviation102.86561
Coefficient of variation (CV)3.1128011
Kurtosis2477.2135
Mean33.045994
Median Absolute Deviation (MAD)11.25
Skewness46.096586
Sum114669.6
Variance10581.333
MonotonicityNot monotonic
2024-04-29T21:09:22.311324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 696
 
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 (1277) 2342
65.8%
(Missing) 88
 
2.5%
ValueCountFrequency (%)
0.0 696
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%
Missing40
Missing (%)1.1%
Memory size27.9 KiB
2024-04-29T21:09:22.627444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters24626
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%
706-838 23
 
0.7%
704-932 23
 
0.7%
711-812 22
 
0.6%
706-831 21
 
0.6%
711-852 20
 
0.6%
Other values (556) 3222
91.6%
2024-04-29T21:09:23.056234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4883
19.8%
7 4070
16.5%
- 3518
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1565
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1113
 
4.5%
5 892
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21108
85.7%
Dash Punctuation 3518
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4883
23.1%
7 4070
19.3%
8 3148
14.9%
1 1893
 
9.0%
4 1565
 
7.4%
2 1516
 
7.2%
3 1409
 
6.7%
6 1113
 
5.3%
5 892
 
4.2%
9 619
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 3518
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24626
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4883
19.8%
7 4070
16.5%
- 3518
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1565
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1113
 
4.5%
5 892
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4883
19.8%
7 4070
16.5%
- 3518
14.3%
8 3148
12.8%
1 1893
 
7.7%
4 1565
 
6.4%
2 1516
 
6.2%
3 1409
 
5.7%
6 1113
 
4.5%
5 892
 
3.6%
Distinct3405
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-29T21:09:23.377987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length51
Mean length25.194772
Min length16

Characters and Unicode

Total characters89643
Distinct characters361
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

Unique3262 ?
Unique (%)91.7%

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 3558
 
21.2%
달서구 745
 
4.4%
수성구 640
 
3.8%
동구 519
 
3.1%
북구 511
 
3.0%
서구 400
 
2.4%
남구 350
 
2.1%
대명동 231
 
1.4%
달성군 213
 
1.3%
중구 161
 
1.0%
Other values (4207) 9439
56.3%
2024-04-29T21:09:23.849923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16247
18.1%
6968
 
7.8%
1 4736
 
5.3%
4522
 
5.0%
3965
 
4.4%
3629
 
4.0%
3571
 
4.0%
3569
 
4.0%
3316
 
3.7%
2929
 
3.3%
Other values (351) 36191
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50529
56.4%
Decimal Number 19538
 
21.8%
Space Separator 16247
 
18.1%
Dash Punctuation 2848
 
3.2%
Open Punctuation 179
 
0.2%
Close Punctuation 179
 
0.2%
Uppercase Letter 76
 
0.1%
Other Punctuation 38
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6968
13.8%
4522
 
8.9%
3965
 
7.8%
3629
 
7.2%
3571
 
7.1%
3569
 
7.1%
3316
 
6.6%
2929
 
5.8%
1289
 
2.6%
1210
 
2.4%
Other values (316) 15561
30.8%
Uppercase Letter
ValueCountFrequency (%)
A 23
30.3%
B 17
22.4%
T 10
13.2%
P 10
13.2%
S 3
 
3.9%
K 2
 
2.6%
E 2
 
2.6%
L 2
 
2.6%
W 1
 
1.3%
H 1
 
1.3%
Other values (5) 5
 
6.6%
Decimal Number
ValueCountFrequency (%)
1 4736
24.2%
0 2448
12.5%
2 2422
12.4%
3 1896
9.7%
4 1595
 
8.2%
5 1499
 
7.7%
6 1352
 
6.9%
7 1257
 
6.4%
9 1176
 
6.0%
8 1157
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 25
65.8%
. 8
 
21.1%
/ 4
 
10.5%
@ 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
88.9%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
16247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2848
100.0%
Open Punctuation
ValueCountFrequency (%)
( 179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50529
56.4%
Common 39029
43.5%
Latin 85
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6968
13.8%
4522
 
8.9%
3965
 
7.8%
3629
 
7.2%
3571
 
7.1%
3569
 
7.1%
3316
 
6.6%
2929
 
5.8%
1289
 
2.6%
1210
 
2.4%
Other values (316) 15561
30.8%
Common
ValueCountFrequency (%)
16247
41.6%
1 4736
 
12.1%
- 2848
 
7.3%
0 2448
 
6.3%
2 2422
 
6.2%
3 1896
 
4.9%
4 1595
 
4.1%
5 1499
 
3.8%
6 1352
 
3.5%
7 1257
 
3.2%
Other values (8) 2729
 
7.0%
Latin
ValueCountFrequency (%)
A 23
27.1%
B 17
20.0%
T 10
11.8%
P 10
11.8%
e 8
 
9.4%
S 3
 
3.5%
K 2
 
2.4%
E 2
 
2.4%
L 2
 
2.4%
W 1
 
1.2%
Other values (7) 7
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50529
56.4%
ASCII 39114
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16247
41.5%
1 4736
 
12.1%
- 2848
 
7.3%
0 2448
 
6.3%
2 2422
 
6.2%
3 1896
 
4.8%
4 1595
 
4.1%
5 1499
 
3.8%
6 1352
 
3.5%
7 1257
 
3.2%
Other values (25) 2814
 
7.2%
Hangul
ValueCountFrequency (%)
6968
13.8%
4522
 
8.9%
3965
 
7.8%
3629
 
7.2%
3571
 
7.1%
3569
 
7.1%
3316
 
6.6%
2929
 
5.8%
1289
 
2.6%
1210
 
2.4%
Other values (316) 15561
30.8%

도로명전체주소
Text

MISSING 

Distinct2173
Distinct (%)98.5%
Missing1351
Missing (%)38.0%
Memory size27.9 KiB
2024-04-29T21:09:24.196820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length52
Mean length30.519257
Min length15

Characters and Unicode

Total characters67356
Distinct characters379
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

Unique2141 ?
Unique (%)97.0%

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 2207
 
16.8%
달서구 452
 
3.4%
수성구 401
 
3.1%
북구 364
 
2.8%
1층 335
 
2.6%
동구 283
 
2.2%
서구 226
 
1.7%
남구 222
 
1.7%
달성군 159
 
1.2%
대명동 148
 
1.1%
Other values (2797) 8336
63.5%
2024-04-29T21:09:24.648667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10931
 
16.2%
4496
 
6.7%
3239
 
4.8%
1 3044
 
4.5%
2808
 
4.2%
2294
 
3.4%
2231
 
3.3%
2213
 
3.3%
( 2173
 
3.2%
) 2173
 
3.2%
Other values (369) 31754
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38767
57.6%
Decimal Number 11277
 
16.7%
Space Separator 10931
 
16.2%
Open Punctuation 2173
 
3.2%
Close Punctuation 2173
 
3.2%
Other Punctuation 1550
 
2.3%
Dash Punctuation 396
 
0.6%
Uppercase Letter 81
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4496
 
11.6%
3239
 
8.4%
2808
 
7.2%
2294
 
5.9%
2231
 
5.8%
2213
 
5.7%
2081
 
5.4%
1471
 
3.8%
961
 
2.5%
950
 
2.5%
Other values (334) 16023
41.3%
Uppercase Letter
ValueCountFrequency (%)
A 28
34.6%
B 12
14.8%
T 11
 
13.6%
P 11
 
13.6%
K 3
 
3.7%
S 3
 
3.7%
D 3
 
3.7%
E 2
 
2.5%
C 2
 
2.5%
Q 1
 
1.2%
Other values (5) 5
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 3044
27.0%
2 1586
14.1%
0 1301
11.5%
3 1205
 
10.7%
4 905
 
8.0%
5 866
 
7.7%
6 718
 
6.4%
7 640
 
5.7%
8 535
 
4.7%
9 477
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 1534
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 (%)
10931
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2173
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 396
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38767
57.6%
Common 28500
42.3%
Latin 89
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4496
 
11.6%
3239
 
8.4%
2808
 
7.2%
2294
 
5.9%
2231
 
5.8%
2213
 
5.7%
2081
 
5.4%
1471
 
3.8%
961
 
2.5%
950
 
2.5%
Other values (334) 16023
41.3%
Common
ValueCountFrequency (%)
10931
38.4%
1 3044
 
10.7%
( 2173
 
7.6%
) 2173
 
7.6%
2 1586
 
5.6%
, 1534
 
5.4%
0 1301
 
4.6%
3 1205
 
4.2%
4 905
 
3.2%
5 866
 
3.0%
Other values (8) 2782
 
9.8%
Latin
ValueCountFrequency (%)
A 28
31.5%
B 12
13.5%
T 11
 
12.4%
P 11
 
12.4%
e 7
 
7.9%
K 3
 
3.4%
S 3
 
3.4%
D 3
 
3.4%
E 2
 
2.2%
C 2
 
2.2%
Other values (7) 7
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38767
57.6%
ASCII 28589
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10931
38.2%
1 3044
 
10.6%
( 2173
 
7.6%
) 2173
 
7.6%
2 1586
 
5.5%
, 1534
 
5.4%
0 1301
 
4.6%
3 1205
 
4.2%
4 905
 
3.2%
5 866
 
3.0%
Other values (25) 2871
 
10.0%
Hangul
ValueCountFrequency (%)
4496
 
11.6%
3239
 
8.4%
2808
 
7.2%
2294
 
5.9%
2231
 
5.8%
2213
 
5.7%
2081
 
5.4%
1471
 
3.8%
961
 
2.5%
950
 
2.5%
Other values (334) 16023
41.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1010
Distinct (%)46.2%
Missing1373
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean42082.167
Minimum41002
Maximum43149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:24.808515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41136
Q141552
median42132
Q342630
95-th percentile42941.2
Maximum43149
Range2147
Interquartile range (IQR)1078

Descriptive statistics

Standard deviation580.7744
Coefficient of variation (CV)0.013800962
Kurtosis-1.1895373
Mean42082.167
Median Absolute Deviation (MAD)537
Skewness-0.13412252
Sum91949535
Variance337298.91
MonotonicityNot monotonic
2024-04-29T21:09:25.132042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41569 9
 
0.3%
42970 7
 
0.2%
41534 7
 
0.2%
42769 7
 
0.2%
42679 7
 
0.2%
42644 7
 
0.2%
42915 7
 
0.2%
42452 7
 
0.2%
42819 7
 
0.2%
41450 7
 
0.2%
Other values (1000) 2113
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 3
0.1%
Distinct2285
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2024-04-29T21:09:25.334172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.1691962
Min length2

Characters and Unicode

Total characters18392
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%
세탁소 27
 
0.7%
제일세탁소 27
 
0.7%
보성세탁소 21
 
0.6%
우방세탁소 20
 
0.5%
백광세탁소 19
 
0.5%
백설세탁소 18
 
0.5%
삼성세탁소 16
 
0.4%
명성세탁소 16
 
0.4%
백조세탁소 16
 
0.4%
Other values (2286) 3460
94.3%
2024-04-29T21:09:25.675366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2551
 
13.9%
2512
 
13.7%
1669
 
9.1%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.1%
284
 
1.5%
252
 
1.4%
247
 
1.3%
Other values (484) 9080
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18050
98.1%
Space Separator 113
 
0.6%
Uppercase Letter 64
 
0.3%
Decimal Number 61
 
0.3%
Open Punctuation 35
 
0.2%
Close 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 (%)
2551
 
14.1%
2512
 
13.9%
1669
 
9.2%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
284
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8738
48.4%
Uppercase Letter
ValueCountFrequency (%)
C 7
10.9%
A 7
10.9%
K 6
 
9.4%
O 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%
9 3
 
4.9%
5 3
 
4.9%
6 2
 
3.3%
8 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 (%)
113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18050
98.1%
Common 264
 
1.4%
Latin 78
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2551
 
14.1%
2512
 
13.9%
1669
 
9.2%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
284
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8738
48.4%
Latin
ValueCountFrequency (%)
e 8
 
10.3%
C 7
 
9.0%
A 7
 
9.0%
K 6
 
7.7%
O 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 (%)
113
42.8%
( 35
 
13.3%
) 35
 
13.3%
1 18
 
6.8%
2 18
 
6.8%
. 11
 
4.2%
3 9
 
3.4%
4 6
 
2.3%
- 5
 
1.9%
9 3
 
1.1%
Other values (6) 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18050
98.1%
ASCII 342
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2551
 
14.1%
2512
 
13.9%
1669
 
9.2%
510
 
2.8%
488
 
2.7%
404
 
2.2%
395
 
2.2%
284
 
1.6%
252
 
1.4%
247
 
1.4%
Other values (445) 8738
48.4%
ASCII
ValueCountFrequency (%)
113
33.0%
( 35
 
10.2%
) 35
 
10.2%
1 18
 
5.3%
2 18
 
5.3%
. 11
 
3.2%
3 9
 
2.6%
e 8
 
2.3%
C 7
 
2.0%
A 7
 
2.0%
Other values (29) 81
23.7%
Distinct2700
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Minimum2001-09-10 00:00:00
Maximum2024-03-29 11:15:37
2024-04-29T21:09:25.802261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:09:25.937126image/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
2657 
U
901 

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 2657
74.7%
U 901
 
25.3%

Length

2024-04-29T21:09:26.064384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:26.168455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2657
74.7%
u 901
 
25.3%
Distinct546
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
Minimum2018-08-31 23:59:59
Maximum2024-03-31 02:40:00
2024-04-29T21:09:26.265681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:09:26.399885image/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
3432 
운동화전문세탁업
 
88
세탁업 기타
 
25
빨래방업
 
13

Length

Max length8
Median length5
Mean length5.0775717
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3432
96.5%
운동화전문세탁업 88
 
2.5%
세탁업 기타 25
 
0.7%
빨래방업 13
 
0.4%

Length

2024-04-29T21:09:26.550768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:26.655411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3432
95.8%
운동화전문세탁업 88
 
2.5%
세탁업 25
 
0.7%
기타 25
 
0.7%
빨래방업 13
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2887
Distinct (%)86.0%
Missing202
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean343041
Minimum327557.24
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:26.767331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327557.24
5-th percentile334975.44
Q1339748.29
median342478.42
Q3346389.96
95-th percentile353156.53
Maximum358060.65
Range30503.408
Interquartile range (IQR)6641.6674

Descriptive statistics

Standard deviation5095.0031
Coefficient of variation (CV)0.014852461
Kurtosis0.22022764
Mean343041
Median Absolute Deviation (MAD)3271.7676
Skewness0.10638899
Sum1.1512456 × 109
Variance25959057
MonotonicityNot monotonic
2024-04-29T21:09:26.899634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338969.480757299 5
 
0.1%
338692.161634264 5
 
0.1%
338962.151491269 5
 
0.1%
347296.208543798 5
 
0.1%
340630.056274461 4
 
0.1%
347913.021747973 4
 
0.1%
345038.837526749 4
 
0.1%
339393.012573076 4
 
0.1%
340425.612585211 4
 
0.1%
340792.592919538 4
 
0.1%
Other values (2877) 3312
93.1%
(Missing) 202
 
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 

Distinct2887
Distinct (%)86.0%
Missing202
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean263463.83
Minimum240358.72
Maximum307136.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:27.019791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257482.92
Q1261156.12
median263205.64
Q3265515.7
95-th percentile271099.35
Maximum307136.85
Range66778.124
Interquartile range (IQR)4359.5745

Descriptive statistics

Standard deviation5041.6897
Coefficient of variation (CV)0.019136174
Kurtosis20.883604
Mean263463.83
Median Absolute Deviation (MAD)2165.7899
Skewness2.0785457
Sum8.8418462 × 108
Variance25418635
MonotonicityNot monotonic
2024-04-29T21:09:27.153704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257548.491948507 5
 
0.1%
259135.243156101 5
 
0.1%
262515.182501563 5
 
0.1%
261275.08308428 5
 
0.1%
272309.461235988 4
 
0.1%
270429.169012283 4
 
0.1%
265537.218675911 4
 
0.1%
258572.019825526 4
 
0.1%
262761.163676007 4
 
0.1%
305196.555870712 4
 
0.1%
Other values (2877) 3312
93.1%
(Missing) 202
 
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
3432 
운동화전문세탁업
 
88
세탁업 기타
 
25
빨래방업
 
13

Length

Max length8
Median length5
Mean length5.0775717
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3432
96.5%
운동화전문세탁업 88
 
2.5%
세탁업 기타 25
 
0.7%
빨래방업 13
 
0.4%

Length

2024-04-29T21:09:27.304260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:27.408460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3432
95.8%
운동화전문세탁업 88
 
2.5%
세탁업 25
 
0.7%
기타 25
 
0.7%
빨래방업 13
 
0.4%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.8%
Missing807
Missing (%)22.7%
Infinite0
Infinite (%)0.0%
Mean1.6739368
Minimum0
Maximum57
Zeros918
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:27.498121image/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 deviation2.2918449
Coefficient of variation (CV)1.3691347
Kurtosis188.98367
Mean1.6739368
Median Absolute Deviation (MAD)1
Skewness10.216577
Sum4605
Variance5.2525532
MonotonicityNot monotonic
2024-04-29T21:09:27.590906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 918
25.8%
2 721
20.3%
3 530
14.9%
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) 807
22.7%
ValueCountFrequency (%)
0 918
25.8%
1 371
10.4%
2 721
20.3%
3 530
14.9%
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%
Missing1344
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean0.23125565
Minimum0
Maximum7
Zeros1746
Zeros (%)49.1%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:27.678705image/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 deviation0.50733308
Coefficient of variation (CV)2.1938192
Kurtosis30.113951
Mean0.23125565
Median Absolute Deviation (MAD)0
Skewness3.8219464
Sum512
Variance0.25738685
MonotonicityNot monotonic
2024-04-29T21:09:27.778985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1746
49.1%
1 446
 
12.5%
2 12
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 1344
37.8%
ValueCountFrequency (%)
0 1746
49.1%
1 446
 
12.5%
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%
1 446
 
12.5%
0 1746
49.1%
Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
1
1739 
<NA>
983 
0
778 
2
 
52
3
 
5

Length

Max length4
Median length1
Mean length1.8288364
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 1739
48.9%
<NA> 983
27.6%
0 778
21.9%
2 52
 
1.5%
3 5
 
0.1%
4 1
 
< 0.1%

Length

2024-04-29T21:09:27.898368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:27.999974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1739
48.9%
na 983
27.6%
0 778
21.9%
2 52
 
1.5%
3 5
 
0.1%
4 1
 
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing1166
Missing (%)32.8%
Infinite0
Infinite (%)0.0%
Mean0.81396321
Minimum0
Maximum10
Zeros547
Zeros (%)15.4%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:28.097759image/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 deviation0.58569795
Coefficient of variation (CV)0.71956317
Kurtosis77.791028
Mean0.81396321
Median Absolute Deviation (MAD)0
Skewness4.9337332
Sum1947
Variance0.34304209
MonotonicityNot monotonic
2024-04-29T21:09:28.200360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1779
50.0%
0 547
 
15.4%
2 55
 
1.5%
3 6
 
0.2%
10 3
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1166
32.8%
ValueCountFrequency (%)
0 547
 
15.4%
1 1779
50.0%
2 55
 
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 55
 
1.5%
1 1779
50.0%
0 547
 
15.4%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
0
1972 
<NA>
1547 
1
 
34
4
 
2
2
 
2

Length

Max length4
Median length1
Mean length2.3043845
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 1972
55.4%
<NA> 1547
43.5%
1 34
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2024-04-29T21:09:28.313879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:28.432906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1972
55.4%
na 1547
43.5%
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>
1827 
0
1691 
1
 
35
4
 
2
2
 
2

Length

Max length4
Median length4
Mean length2.5404722
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> 1827
51.3%
0 1691
47.5%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2024-04-29T21:09:28.556836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:28.660849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1827
51.3%
0 1691
47.5%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%
Distinct2
Distinct (%)100.0%
Missing3556
Missing (%)99.9%
Memory size27.9 KiB
2024-04-29T21:09:28.820182image/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%
2024-04-29T21:09:29.095730image/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>
3557 
20070213
 
1

Length

Max length8
Median length4
Mean length4.0011242
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> 3557
> 99.9%
20070213 1
 
< 0.1%

Length

2024-04-29T21:09:29.225222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:29.325927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3557
> 99.9%
20070213 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
3557 
20071130
 
1

Length

Max length8
Median length4
Mean length4.0011242
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> 3557
> 99.9%
20071130 1
 
< 0.1%

Length

2024-04-29T21:09:29.427844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:29.537318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3557
> 99.9%
20071130 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
<NA>
1869 
임대
1427 
자가
262 

Length

Max length4
Median length4
Mean length3.0505902
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
52.5%
임대 1427
40.1%
자가 262
 
7.4%

Length

2024-04-29T21:09:29.654810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:09:29.771685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1869
52.5%
임대 1427
40.1%
자가 262
 
7.4%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.5%
Missing1691
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean1.2394215
Minimum0
Maximum20
Zeros624
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:29.856205image/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 deviation1.2144138
Coefficient of variation (CV)0.97982309
Kurtosis31.514532
Mean1.2394215
Median Absolute Deviation (MAD)1
Skewness2.7296196
Sum2314
Variance1.474801
MonotonicityNot monotonic
2024-04-29T21:09:29.960194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 624
 
17.5%
2 595
 
16.7%
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) 1691
47.5%
ValueCountFrequency (%)
0 624
17.5%
1 462
13.0%
2 595
16.7%
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%
2 595
16.7%
1 462
13.0%
0 624
17.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.8%
Missing3067
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean0.39918534
Minimum0
Maximum20
Zeros350
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:30.082783image/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 deviation1.2220422
Coefficient of variation (CV)3.0613404
Kurtosis146.54571
Mean0.39918534
Median Absolute Deviation (MAD)0
Skewness10.418211
Sum196
Variance1.4933871
MonotonicityNot monotonic
2024-04-29T21:09:30.197361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 350
 
9.8%
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) 3067
86.2%
ValueCountFrequency (%)
0 350
9.8%
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%
0 350
9.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.2%
Missing2983
Missing (%)83.8%
Infinite0
Infinite (%)0.0%
Mean0.49565217
Minimum0
Maximum9
Zeros329
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:30.307254image/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 deviation0.75331917
Coefficient of variation (CV)1.5198545
Kurtosis38.208868
Mean0.49565217
Median Absolute Deviation (MAD)0
Skewness4.321004
Sum285
Variance0.56748977
MonotonicityNot monotonic
2024-04-29T21:09:30.406111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 329
 
9.2%
1 226
 
6.4%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 2983
83.8%
ValueCountFrequency (%)
0 329
9.2%
1 226
6.4%
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%
1 226
6.4%
0 329
9.2%

회수건조기수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing1787
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean0.46696781
Minimum0
Maximum10
Zeros1004
Zeros (%)28.2%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2024-04-29T21:09:30.751635image/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 deviation0.62834084
Coefficient of variation (CV)1.3455763
Kurtosis38.073777
Mean0.46696781
Median Absolute Deviation (MAD)0
Skewness3.4557456
Sum827
Variance0.39481221
MonotonicityNot monotonic
2024-04-29T21:09:30.860766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1004
28.2%
1 733
20.6%
2 23
 
0.6%
3 6
 
0.2%
4 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1787
50.2%
ValueCountFrequency (%)
0 1004
28.2%
1 733
20.6%
2 23
 
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 23
 
0.6%
1 733
20.6%
0 1004
28.2%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
False
3557 
True
 
1
ValueCountFrequency (%)
False 3557
> 99.9%
True 1
 
< 0.1%
2024-04-29T21:09:30.967915image/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
35483549세탁업06_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
35493550세탁업06_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
35503551세탁업06_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
35513552세탁업06_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
35523553세탁업06_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
35533554세탁업06_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
35543555세탁업06_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
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35563557세탁업06_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
35573558세탁업06_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