Overview

Dataset statistics

Number of variables51
Number of observations1812
Missing cells16320
Missing cells (%)17.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory780.5 KiB
Average record size in memory441.1 B

Variable types

Numeric14
Categorical22
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-11-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123185

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (63.5%)Imbalance
위생업태명 is highly imbalanced (63.5%)Imbalance
사용끝지하층 is highly imbalanced (53.2%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (85.6%)Imbalance
남성종사자수 is highly imbalanced (84.1%)Imbalance
다중이용업소여부 is highly imbalanced (86.6%)Imbalance
인허가취소일자 has 1812 (100.0%) missing valuesMissing
폐업일자 has 782 (43.2%) missing valuesMissing
휴업시작일자 has 1812 (100.0%) missing valuesMissing
휴업종료일자 has 1812 (100.0%) missing valuesMissing
재개업일자 has 1812 (100.0%) missing valuesMissing
소재지전화 has 118 (6.5%) missing valuesMissing
도로명전체주소 has 618 (34.1%) missing valuesMissing
도로명우편번호 has 670 (37.0%) missing valuesMissing
좌표정보(x) has 103 (5.7%) missing valuesMissing
좌표정보(y) has 103 (5.7%) missing valuesMissing
건물지상층수 has 428 (23.6%) missing valuesMissing
건물지하층수 has 664 (36.6%) missing valuesMissing
사용시작지상층 has 616 (34.0%) missing valuesMissing
사용끝지상층 has 729 (40.2%) missing valuesMissing
욕실수 has 602 (33.2%) missing valuesMissing
조건부허가신고사유 has 1811 (99.9%) missing valuesMissing
Unnamed: 50 has 1812 (100.0%) missing valuesMissing
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
Unnamed: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 357 (19.7%) zerosZeros
건물지하층수 has 548 (30.2%) zerosZeros
사용시작지상층 has 365 (20.1%) zerosZeros
사용끝지상층 has 225 (12.4%) zerosZeros
욕실수 has 629 (34.7%) zerosZeros

Reproduction

Analysis started2024-04-17 21:44:25.424903
Analysis finished2024-04-17 21:44:26.338352
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1812
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean906.5
Minimum1
Maximum1812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:26.398499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.55
Q1453.75
median906.5
Q31359.25
95-th percentile1721.45
Maximum1812
Range1811
Interquartile range (IQR)905.5

Descriptive statistics

Standard deviation523.22366
Coefficient of variation (CV)0.57719102
Kurtosis-1.2
Mean906.5
Median Absolute Deviation (MAD)453
Skewness0
Sum1642578
Variance273763
MonotonicityStrictly increasing
2024-04-18T06:44:26.513527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1192 1
 
0.1%
1218 1
 
0.1%
1217 1
 
0.1%
1216 1
 
0.1%
1215 1
 
0.1%
1214 1
 
0.1%
1213 1
 
0.1%
1212 1
 
0.1%
1211 1
 
0.1%
Other values (1802) 1802
99.4%
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 (%)
1812 1
0.1%
1811 1
0.1%
1810 1
0.1%
1809 1
0.1%
1808 1
0.1%
1807 1
0.1%
1806 1
0.1%
1805 1
0.1%
1804 1
0.1%
1803 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
목욕장업
1812 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목욕장업 1812
100.0%

Length

2024-04-18T06:44:26.633885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:26.722844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1812
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
11_44_01_P
1812 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 1812
100.0%

Length

2024-04-18T06:44:26.806782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:26.894774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1812
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3322902.9
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:26.968677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39930.44
Coefficient of variation (CV)0.012016734
Kurtosis-0.90851161
Mean3322902.9
Median Absolute Deviation (MAD)30000
Skewness0.13738707
Sum6.0211 × 109
Variance1.59444 × 109
MonotonicityNot monotonic
2024-04-18T06:44:27.065043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 222
12.3%
3340000 173
9.5%
3300000 164
9.1%
3330000 159
8.8%
3310000 146
 
8.1%
3370000 130
 
7.2%
3320000 124
 
6.8%
3350000 114
 
6.3%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 374
20.6%
ValueCountFrequency (%)
3250000 62
 
3.4%
3260000 73
 
4.0%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 222
12.3%
3300000 164
9.1%
3310000 146
8.1%
3320000 124
6.8%
3330000 159
8.8%
3340000 173
9.5%
ValueCountFrequency (%)
3400000 45
 
2.5%
3390000 93
5.1%
3380000 112
6.2%
3370000 130
7.2%
3360000 29
 
1.6%
3350000 114
6.3%
3340000 173
9.5%
3330000 159
8.8%
3320000 124
6.8%
3310000 146
8.1%

관리번호
Text

UNIQUE 

Distinct1812
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:44:27.227191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39864
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

Unique1812 ?
Unique (%)100.0%

Sample

1st row3400000-202-2003-00002
2nd row3400000-202-2000-00091
3rd row3400000-202-1992-00084
4th row3400000-202-1994-00408
5th row3400000-202-1994-00407
ValueCountFrequency (%)
3400000-202-2003-00002 1
 
0.1%
3370000-202-1984-00458 1
 
0.1%
3350000-202-2006-00001 1
 
0.1%
3350000-202-2013-00001 1
 
0.1%
3360000-202-2019-00003 1
 
0.1%
3360000-202-2019-00001 1
 
0.1%
3360000-202-2019-00002 1
 
0.1%
3360000-202-1992-00003 1
 
0.1%
3360000-202-1991-00003 1
 
0.1%
3360000-202-2006-00001 1
 
0.1%
Other values (1802) 1802
99.4%
2024-04-18T06:44:27.520713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15358
38.5%
2 5641
 
14.2%
- 5436
 
13.6%
3 3930
 
9.9%
1 2744
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34428
86.4%
Dash Punctuation 5436
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15358
44.6%
2 5641
 
16.4%
3 3930
 
11.4%
1 2744
 
8.0%
9 2539
 
7.4%
8 1141
 
3.3%
4 946
 
2.7%
7 837
 
2.4%
5 693
 
2.0%
6 599
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39864
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15358
38.5%
2 5641
 
14.2%
- 5436
 
13.6%
3 3930
 
9.9%
1 2744
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15358
38.5%
2 5641
 
14.2%
- 5436
 
13.6%
3 3930
 
9.9%
1 2744
 
6.9%
9 2539
 
6.4%
8 1141
 
2.9%
4 946
 
2.4%
7 837
 
2.1%
5 693
 
1.7%

인허가일자
Real number (ℝ)

Distinct1527
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19909689
Minimum19540131
Maximum20210914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:27.650611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700470
Q119830456
median19901122
Q320010312
95-th percentile20101063
Maximum20210914
Range670783
Interquartile range (IQR)179856.5

Descriptive statistics

Standard deviation122952.09
Coefficient of variation (CV)0.0061754906
Kurtosis-0.35411591
Mean19909689
Median Absolute Deviation (MAD)80816
Skewness-0.058444591
Sum3.6076356 × 1010
Variance1.5117217 × 1010
MonotonicityNot monotonic
2024-04-18T06:44:27.771838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.8%
20001130 9
 
0.5%
19921202 8
 
0.4%
19960710 6
 
0.3%
19971227 6
 
0.3%
20000420 5
 
0.3%
20030115 5
 
0.3%
19820928 5
 
0.3%
19830304 5
 
0.3%
19840908 4
 
0.2%
Other values (1517) 1744
96.2%
ValueCountFrequency (%)
19540131 1
 
0.1%
19601210 3
 
0.2%
19630108 1
 
0.1%
19630109 3
 
0.2%
19630110 15
0.8%
19630610 4
 
0.2%
19631001 1
 
0.1%
19640211 1
 
0.1%
19640915 1
 
0.1%
19641015 1
 
0.1%
ValueCountFrequency (%)
20210914 1
0.1%
20210525 1
0.1%
20210401 1
0.1%
20210316 1
0.1%
20201013 1
0.1%
20200924 1
0.1%
20200921 1
0.1%
20200908 1
0.1%
20200827 1
0.1%
20200708 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1812
Missing (%)100.0%
Memory size16.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
3
1030 
1
782 

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 1030
56.8%
1 782
43.2%

Length

2024-04-18T06:44:27.894881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:27.972441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1030
56.8%
1 782
43.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1030 
영업/정상
782 

Length

Max length5
Median length2
Mean length3.294702
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1030
56.8%
영업/정상 782
43.2%

Length

2024-04-18T06:44:28.057856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:28.141048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1030
56.8%
영업/정상 782
43.2%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2
1030 
1
782 

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 1030
56.8%
1 782
43.2%

Length

2024-04-18T06:44:28.223581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:28.303957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1030
56.8%
1 782
43.2%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
폐업
1030 
영업
782 

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 1030
56.8%
영업 782
43.2%

Length

2024-04-18T06:44:28.385704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:28.463806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1030
56.8%
영업 782
43.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct865
Distinct (%)84.0%
Missing782
Missing (%)43.2%
Infinite0
Infinite (%)0.0%
Mean20097323
Minimum19860612
Maximum20210928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:28.992889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19860612
5-th percentile19990462
Q120050950
median20100522
Q320150529
95-th percentile20200669
Maximum20210928
Range350316
Interquartile range (IQR)99579

Descriptive statistics

Standard deviation66353.826
Coefficient of variation (CV)0.003301625
Kurtosis-0.002280445
Mean20097323
Median Absolute Deviation (MAD)49884
Skewness-0.41002503
Sum2.0700243 × 1010
Variance4.4028302 × 109
MonotonicityNot monotonic
2024-04-18T06:44:29.124588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050121 12
 
0.7%
20001130 7
 
0.4%
20051017 7
 
0.4%
20030401 5
 
0.3%
20170310 5
 
0.3%
20030122 4
 
0.2%
20141030 4
 
0.2%
20190226 4
 
0.2%
20120621 4
 
0.2%
19991111 3
 
0.2%
Other values (855) 975
53.8%
(Missing) 782
43.2%
ValueCountFrequency (%)
19860612 1
0.1%
19870602 1
0.1%
19871229 1
0.1%
19890607 1
0.1%
19891016 1
0.1%
19900228 1
0.1%
19900705 1
0.1%
19901019 2
0.1%
19911220 1
0.1%
19920305 1
0.1%
ValueCountFrequency (%)
20210928 1
0.1%
20210924 1
0.1%
20210916 1
0.1%
20210824 1
0.1%
20210819 1
0.1%
20210806 1
0.1%
20210803 1
0.1%
20210730 1
0.1%
20210726 1
0.1%
20210715 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1812
Missing (%)100.0%
Memory size16.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1812
Missing (%)100.0%
Memory size16.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1812
Missing (%)100.0%
Memory size16.1 KiB

소재지전화
Text

MISSING 

Distinct1610
Distinct (%)95.0%
Missing118
Missing (%)6.5%
Memory size14.3 KiB
2024-04-18T06:44:29.386957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.904368
Min length3

Characters and Unicode

Total characters18472
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

Unique1571 ?
Unique (%)92.7%

Sample

1st row051 7243994
2nd row051 7222537
3rd row051 7221054
4th row051 7211997
5th row051 7273302
ValueCountFrequency (%)
051 1640
45.6%
893 7
 
0.2%
808 7
 
0.2%
070 6
 
0.2%
261 5
 
0.1%
802 5
 
0.1%
897 5
 
0.1%
891 5
 
0.1%
816 5
 
0.1%
208 4
 
0.1%
Other values (1765) 1908
53.0%
2024-04-18T06:44:29.736533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3050
16.5%
0 2842
15.4%
1 2766
15.0%
1912
10.4%
2 1449
7.8%
3 1301
7.0%
6 1229
6.7%
4 1109
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16560
89.6%
Space Separator 1912
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3050
18.4%
0 2842
17.2%
1 2766
16.7%
2 1449
8.8%
3 1301
7.9%
6 1229
7.4%
4 1109
 
6.7%
7 1074
 
6.5%
8 1036
 
6.3%
9 704
 
4.3%
Space Separator
ValueCountFrequency (%)
1912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18472
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3050
16.5%
0 2842
15.4%
1 2766
15.0%
1912
10.4%
2 1449
7.8%
3 1301
7.0%
6 1229
6.7%
4 1109
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3050
16.5%
0 2842
15.4%
1 2766
15.0%
1912
10.4%
2 1449
7.8%
3 1301
7.0%
6 1229
6.7%
4 1109
 
6.0%
7 1074
 
5.8%
8 1036
 
5.6%
Distinct1592
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Memory size14.3 KiB
2024-04-18T06:44:30.000756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9711592
Min length3

Characters and Unicode

Total characters10766
Distinct characters12
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

Unique1508 ?
Unique (%)83.6%

Sample

1st row348.16
2nd row384.00
3rd row609.82
4th row183.56
5th row395.22
ValueCountFrequency (%)
00 117
 
6.5%
330.00 5
 
0.3%
798.24 3
 
0.2%
284.00 3
 
0.2%
427.44 3
 
0.2%
363.30 3
 
0.2%
93.73 3
 
0.2%
426.00 3
 
0.2%
478.00 3
 
0.2%
506.24 3
 
0.2%
Other values (1582) 1657
91.9%
2024-04-18T06:44:30.354980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1803
16.7%
0 1439
13.4%
2 1064
9.9%
3 1008
9.4%
4 934
8.7%
1 905
8.4%
8 704
 
6.5%
6 700
 
6.5%
5 695
 
6.5%
7 678
 
6.3%
Other values (2) 836
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8803
81.8%
Other Punctuation 1963
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1439
16.3%
2 1064
12.1%
3 1008
11.5%
4 934
10.6%
1 905
10.3%
8 704
8.0%
6 700
8.0%
5 695
7.9%
7 678
7.7%
9 676
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1803
91.8%
, 160
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10766
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1803
16.7%
0 1439
13.4%
2 1064
9.9%
3 1008
9.4%
4 934
8.7%
1 905
8.4%
8 704
 
6.5%
6 700
 
6.5%
5 695
 
6.5%
7 678
 
6.3%
Other values (2) 836
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10766
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1803
16.7%
0 1439
13.4%
2 1064
9.9%
3 1008
9.4%
4 934
8.7%
1 905
8.4%
8 704
 
6.5%
6 700
 
6.5%
5 695
 
6.5%
7 678
 
6.3%
Other values (2) 836
7.8%

소재지우편번호
Real number (ℝ)

Distinct630
Distinct (%)34.9%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean610419.65
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:30.481489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601811
Q1606809
median611800
Q3614820.5
95-th percentile617833.7
Maximum619953
Range19942
Interquartile range (IQR)8011.5

Descriptive statistics

Standard deviation5167.1314
Coefficient of variation (CV)0.0084648839
Kurtosis-0.92056183
Mean610419.65
Median Absolute Deviation (MAD)3963
Skewness-0.20702164
Sum1.1030283 × 109
Variance26699247
MonotonicityNot monotonic
2024-04-18T06:44:30.606719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
604851 15
 
0.8%
612846 12
 
0.7%
612847 12
 
0.7%
608808 10
 
0.6%
608828 10
 
0.6%
614822 10
 
0.6%
607833 10
 
0.6%
607826 9
 
0.5%
613805 9
 
0.5%
613832 9
 
0.5%
Other values (620) 1701
93.9%
ValueCountFrequency (%)
600011 1
 
0.1%
600012 1
 
0.1%
600017 1
 
0.1%
600021 1
 
0.1%
600022 4
0.2%
600023 1
 
0.1%
600025 1
 
0.1%
600032 1
 
0.1%
600042 1
 
0.1%
600044 1
 
0.1%
ValueCountFrequency (%)
619953 2
 
0.1%
619952 3
0.2%
619951 4
0.2%
619913 1
 
0.1%
619912 2
 
0.1%
619911 2
 
0.1%
619906 3
0.2%
619905 5
0.3%
619904 3
0.2%
619903 7
0.4%
Distinct1741
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:44:30.915499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length23.335541
Min length16

Characters and Unicode

Total characters42284
Distinct characters276
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1681 ?
Unique (%)92.8%

Sample

1st row부산광역시 기장군 기장읍 서부리 422번지
2nd row부산광역시 기장군 기장읍 교리 352-8번지
3rd row부산광역시 기장군 기장읍 청강리 226-7번지
4th row부산광역시 기장군 철마면 장전리 366번지
5th row부산광역시 기장군 일광면 칠암리 158-5번지
ValueCountFrequency (%)
부산광역시 1812
 
22.4%
t통b반 334
 
4.1%
부산진구 222
 
2.7%
사하구 173
 
2.1%
동래구 164
 
2.0%
해운대구 159
 
2.0%
남구 146
 
1.8%
연제구 130
 
1.6%
북구 124
 
1.5%
금정구 114
 
1.4%
Other values (2176) 4697
58.2%
2024-04-18T06:44:31.426612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6264
 
14.8%
2163
 
5.1%
2154
 
5.1%
2111
 
5.0%
1 1907
 
4.5%
1882
 
4.5%
1833
 
4.3%
1824
 
4.3%
1816
 
4.3%
- 1684
 
4.0%
Other values (266) 18646
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24614
58.2%
Decimal Number 8795
 
20.8%
Space Separator 6264
 
14.8%
Dash Punctuation 1684
 
4.0%
Uppercase Letter 683
 
1.6%
Other Punctuation 114
 
0.3%
Close Punctuation 61
 
0.1%
Open Punctuation 61
 
0.1%
Math Symbol 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2163
 
8.8%
2154
 
8.8%
2111
 
8.6%
1882
 
7.6%
1833
 
7.4%
1824
 
7.4%
1816
 
7.4%
1456
 
5.9%
1388
 
5.6%
385
 
1.6%
Other values (240) 7602
30.9%
Decimal Number
ValueCountFrequency (%)
1 1907
21.7%
2 1135
12.9%
3 990
11.3%
4 893
10.2%
5 783
8.9%
6 679
 
7.7%
7 645
 
7.3%
8 612
 
7.0%
0 610
 
6.9%
9 541
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 334
48.9%
W 2
 
0.3%
A 2
 
0.3%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
@ 1
 
0.9%
. 1
 
0.9%
Space Separator
ValueCountFrequency (%)
6264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1684
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24614
58.2%
Common 16986
40.2%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2163
 
8.8%
2154
 
8.8%
2111
 
8.6%
1882
 
7.6%
1833
 
7.4%
1824
 
7.4%
1816
 
7.4%
1456
 
5.9%
1388
 
5.6%
385
 
1.6%
Other values (240) 7602
30.9%
Common
ValueCountFrequency (%)
6264
36.9%
1 1907
 
11.2%
- 1684
 
9.9%
2 1135
 
6.7%
3 990
 
5.8%
4 893
 
5.3%
5 783
 
4.6%
6 679
 
4.0%
7 645
 
3.8%
8 612
 
3.6%
Other values (8) 1394
 
8.2%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 334
48.8%
W 2
 
0.3%
A 2
 
0.3%
1
 
0.1%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24614
58.2%
ASCII 17669
41.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6264
35.5%
1 1907
 
10.8%
- 1684
 
9.5%
2 1135
 
6.4%
3 990
 
5.6%
4 893
 
5.1%
5 783
 
4.4%
6 679
 
3.8%
7 645
 
3.7%
8 612
 
3.5%
Other values (15) 2077
 
11.8%
Hangul
ValueCountFrequency (%)
2163
 
8.8%
2154
 
8.8%
2111
 
8.6%
1882
 
7.6%
1833
 
7.4%
1824
 
7.4%
1816
 
7.4%
1456
 
5.9%
1388
 
5.6%
385
 
1.6%
Other values (240) 7602
30.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1179
Distinct (%)98.7%
Missing618
Missing (%)34.1%
Memory size14.3 KiB
2024-04-18T06:44:31.775185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.505025
Min length20

Characters and Unicode

Total characters32841
Distinct characters336
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1166 ?
Unique (%)97.7%

Sample

1st row부산광역시 기장군 기장읍 반송로 1545
2nd row부산광역시 기장군 기장읍 차성동로 164-15
3rd row부산광역시 기장군 기장읍 차성동로 63
4th row부산광역시 기장군 일광면 삼성3길 55-1
5th row부산광역시 기장군 장안읍 길천길 1-2
ValueCountFrequency (%)
부산광역시 1194
 
19.1%
부산진구 154
 
2.5%
해운대구 103
 
1.6%
사하구 102
 
1.6%
남구 102
 
1.6%
동래구 99
 
1.6%
연제구 84
 
1.3%
북구 76
 
1.2%
금정구 75
 
1.2%
사상구 71
 
1.1%
Other values (1720) 4194
67.1%
2024-04-18T06:44:32.250922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5061
 
15.4%
1517
 
4.6%
1448
 
4.4%
1447
 
4.4%
1261
 
3.8%
1250
 
3.8%
1223
 
3.7%
1199
 
3.7%
( 1180
 
3.6%
) 1180
 
3.6%
Other values (326) 16075
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19784
60.2%
Decimal Number 5064
 
15.4%
Space Separator 5061
 
15.4%
Open Punctuation 1181
 
3.6%
Close Punctuation 1181
 
3.6%
Other Punctuation 343
 
1.0%
Dash Punctuation 199
 
0.6%
Uppercase Letter 14
 
< 0.1%
Math Symbol 13
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1517
 
7.7%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1223
 
6.2%
1199
 
6.1%
1138
 
5.8%
710
 
3.6%
669
 
3.4%
Other values (298) 7922
40.0%
Decimal Number
ValueCountFrequency (%)
1 1143
22.6%
2 721
14.2%
3 626
12.4%
5 443
 
8.7%
4 433
 
8.6%
6 390
 
7.7%
0 381
 
7.5%
7 353
 
7.0%
9 290
 
5.7%
8 284
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
A 4
28.6%
W 2
 
14.3%
I 1
 
7.1%
G 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 338
98.5%
. 3
 
0.9%
@ 1
 
0.3%
* 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1180
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1180
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5061
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19784
60.2%
Common 13042
39.7%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1517
 
7.7%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1223
 
6.2%
1199
 
6.1%
1138
 
5.8%
710
 
3.6%
669
 
3.4%
Other values (298) 7922
40.0%
Common
ValueCountFrequency (%)
5061
38.8%
( 1180
 
9.0%
) 1180
 
9.0%
1 1143
 
8.8%
2 721
 
5.5%
3 626
 
4.8%
5 443
 
3.4%
4 433
 
3.3%
6 390
 
3.0%
0 381
 
2.9%
Other values (12) 1484
 
11.4%
Latin
ValueCountFrequency (%)
B 6
40.0%
A 4
26.7%
W 2
 
13.3%
I 1
 
6.7%
G 1
 
6.7%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19784
60.2%
ASCII 13055
39.8%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5061
38.8%
( 1180
 
9.0%
) 1180
 
9.0%
1 1143
 
8.8%
2 721
 
5.5%
3 626
 
4.8%
5 443
 
3.4%
4 433
 
3.3%
6 390
 
3.0%
0 381
 
2.9%
Other values (16) 1497
 
11.5%
Hangul
ValueCountFrequency (%)
1517
 
7.7%
1448
 
7.3%
1447
 
7.3%
1261
 
6.4%
1250
 
6.3%
1223
 
6.2%
1199
 
6.1%
1138
 
5.8%
710
 
3.6%
669
 
3.4%
Other values (298) 7922
40.0%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct877
Distinct (%)76.8%
Missing670
Missing (%)37.0%
Infinite0
Infinite (%)0.0%
Mean47879.257
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:32.370085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147142
median47870
Q348717.25
95-th percentile49393.95
Maximum49523
Range3521
Interquartile range (IQR)1575.25

Descriptive statistics

Standard deviation980.89909
Coefficient of variation (CV)0.020486932
Kurtosis-1.039682
Mean47879.257
Median Absolute Deviation (MAD)745.5
Skewness-0.078621683
Sum54678111
Variance962163.03
MonotonicityNot monotonic
2024-04-18T06:44:32.491706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48099 8
 
0.4%
47709 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
46308 4
 
0.2%
48053 4
 
0.2%
47814 4
 
0.2%
48052 4
 
0.2%
47712 4
 
0.2%
48095 4
 
0.2%
Other values (867) 1091
60.2%
(Missing) 670
37.0%
ValueCountFrequency (%)
46002 1
0.1%
46008 1
0.1%
46015 1
0.1%
46017 1
0.1%
46020 1
0.1%
46032 1
0.1%
46033 1
0.1%
46036 2
0.1%
46037 2
0.1%
46040 1
0.1%
ValueCountFrequency (%)
49523 1
0.1%
49522 1
0.1%
49521 1
0.1%
49518 2
0.1%
49515 2
0.1%
49511 2
0.1%
49506 1
0.1%
49505 1
0.1%
49504 1
0.1%
49503 2
0.1%
Distinct1137
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
2024-04-18T06:44:32.766929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1181015
Min length2

Characters and Unicode

Total characters7462
Distinct characters381
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique895 ?
Unique (%)49.4%

Sample

1st row에쿠스목욕장
2nd row교리탕
3rd row보광탕
4th row철마목욕탕
5th row풍년탕
ValueCountFrequency (%)
사우나 23
 
1.2%
현대탕 21
 
1.1%
청수탕 21
 
1.1%
옥천탕 19
 
1.0%
산수탕 15
 
0.8%
천수탕 15
 
0.8%
목욕탕 15
 
0.8%
장수탕 14
 
0.7%
평화탕 13
 
0.7%
제일탕 13
 
0.7%
Other values (1192) 1794
91.4%
2024-04-18T06:44:33.173937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1370
 
18.4%
301
 
4.0%
224
 
3.0%
182
 
2.4%
180
 
2.4%
168
 
2.3%
158
 
2.1%
151
 
2.0%
123
 
1.6%
117
 
1.6%
Other values (371) 4488
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7194
96.4%
Space Separator 151
 
2.0%
Close Punctuation 37
 
0.5%
Open Punctuation 34
 
0.5%
Decimal Number 20
 
0.3%
Uppercase Letter 15
 
0.2%
Lowercase Letter 7
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1370
 
19.0%
301
 
4.2%
224
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
123
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (349) 4258
59.2%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
O 2
13.3%
L 2
13.3%
W 2
13.3%
J 1
 
6.7%
M 1
 
6.7%
B 1
 
6.7%
F 1
 
6.7%
S 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
n 2
28.6%
o 2
28.6%
u 1
14.3%
r 1
14.3%
d 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 11
55.0%
4 9
45.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7193
96.4%
Common 246
 
3.3%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1370
 
19.0%
301
 
4.2%
224
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
123
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (348) 4257
59.2%
Latin
ValueCountFrequency (%)
G 4
18.2%
n 2
9.1%
o 2
9.1%
O 2
9.1%
L 2
9.1%
W 2
9.1%
u 1
 
4.5%
r 1
 
4.5%
J 1
 
4.5%
M 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
151
61.4%
) 37
 
15.0%
( 34
 
13.8%
2 11
 
4.5%
4 9
 
3.7%
- 2
 
0.8%
. 1
 
0.4%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7193
96.4%
ASCII 268
 
3.6%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1370
 
19.0%
301
 
4.2%
224
 
3.1%
182
 
2.5%
180
 
2.5%
168
 
2.3%
158
 
2.2%
123
 
1.7%
117
 
1.6%
113
 
1.6%
Other values (348) 4257
59.2%
ASCII
ValueCountFrequency (%)
151
56.3%
) 37
 
13.8%
( 34
 
12.7%
2 11
 
4.1%
4 9
 
3.4%
G 4
 
1.5%
n 2
 
0.7%
o 2
 
0.7%
O 2
 
0.7%
L 2
 
0.7%
Other values (12) 14
 
5.2%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1517
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0127602 × 1013
Minimum1.999021 × 1013
Maximum2.021093 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:33.306364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020422 × 1013
Q12.0050211 × 1013
median2.0141018 × 1013
Q32.0200402 × 1013
95-th percentile2.0210618 × 1013
Maximum2.021093 × 1013
Range2.2072013 × 1011
Interquartile range (IQR)1.5019116 × 1011

Descriptive statistics

Standard deviation7.2042584 × 1010
Coefficient of variation (CV)0.003579293
Kurtosis-1.4337894
Mean2.0127602 × 1013
Median Absolute Deviation (MAD)5.9998098 × 1010
Skewness-0.35580604
Sum3.6471215 × 1016
Variance5.190134 × 1021
MonotonicityNot monotonic
2024-04-18T06:44:33.419199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020418000000 27
 
1.5%
20030409000000 25
 
1.4%
20040318000000 13
 
0.7%
20050415000000 12
 
0.7%
20031217000000 12
 
0.7%
20030303000000 12
 
0.7%
20020422000000 10
 
0.6%
20041208000000 9
 
0.5%
20030722000000 8
 
0.4%
20040324000000 8
 
0.4%
Other values (1507) 1676
92.5%
ValueCountFrequency (%)
19990210000000 2
 
0.1%
19990212000000 1
 
0.1%
19990302000000 7
0.4%
19990310000000 6
0.3%
19990315000000 1
 
0.1%
19990325000000 2
 
0.1%
19990420000000 2
 
0.1%
19990421000000 7
0.4%
19990422000000 1
 
0.1%
19990427000000 1
 
0.1%
ValueCountFrequency (%)
20210930132145 1
0.1%
20210928161956 1
0.1%
20210928132217 1
0.1%
20210928114007 1
0.1%
20210928113940 1
0.1%
20210928113913 1
0.1%
20210928113753 1
0.1%
20210928113736 1
0.1%
20210928113639 1
0.1%
20210928113401 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
I
1152 
U
660 

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 1152
63.6%
U 660
36.4%

Length

2024-04-18T06:44:33.523903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:33.605979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1152
63.6%
u 660
36.4%
Distinct284
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-10-02 02:40:00
2024-04-18T06:44:33.692667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:44:33.809575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
공동탕업
1537 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
76
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7064018
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1537
84.8%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 76
 
4.2%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:44:33.910770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:34.002462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1537
78.1%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 76
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1542
Distinct (%)90.2%
Missing103
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean387829.38
Minimum366820.79
Maximum407878.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:34.122624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379644.67
Q1384163.09
median388185.3
Q3391124.28
95-th percentile396841.07
Maximum407878.31
Range41057.525
Interquartile range (IQR)6961.1841

Descriptive statistics

Standard deviation5278.1238
Coefficient of variation (CV)0.013609396
Kurtosis0.7357759
Mean387829.38
Median Absolute Deviation (MAD)3521.3902
Skewness0.25606501
Sum6.6280042 × 108
Variance27858591
MonotonicityNot monotonic
2024-04-18T06:44:34.227232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
386026.75739607 4
 
0.2%
389655.360752282 4
 
0.2%
389322.400841052 4
 
0.2%
391834.082986499 4
 
0.2%
391103.422349355 3
 
0.2%
381700.609088258 3
 
0.2%
378594.286473542 3
 
0.2%
392683.749989177 3
 
0.2%
389415.20340442 3
 
0.2%
384510.802352823 3
 
0.2%
Other values (1532) 1675
92.4%
(Missing) 103
 
5.7%
ValueCountFrequency (%)
366820.787750249 1
0.1%
370674.351397752 1
0.1%
370718.68095386 1
0.1%
372902.66679319 1
0.1%
373056.59115396 1
0.1%
373088.087508096 2
0.1%
373178.636648911 1
0.1%
373368.868121279 1
0.1%
373512.89135141 1
0.1%
374901.846816548 2
0.1%
ValueCountFrequency (%)
407878.31227469 1
0.1%
407739.046710947 1
0.1%
407413.951209968 1
0.1%
407195.438344935 1
0.1%
406982.053033795 1
0.1%
405347.024248643 1
0.1%
405172.859381319 1
0.1%
404771.782281376 1
0.1%
404674.710704763 1
0.1%
403845.595330569 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1542
Distinct (%)90.2%
Missing103
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean186671.36
Minimum173914.72
Maximum207205.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:34.335391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177925.44
Q1182339.02
median186863.29
Q3190714.83
95-th percentile195569.29
Maximum207205.17
Range33290.452
Interquartile range (IQR)8375.8155

Descriptive statistics

Standard deviation5630.3931
Coefficient of variation (CV)0.030162062
Kurtosis0.022471828
Mean186671.36
Median Absolute Deviation (MAD)4093.9203
Skewness0.23155657
Sum3.1902135 × 108
Variance31701326
MonotonicityNot monotonic
2024-04-18T06:44:34.450054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181580.381775088 4
 
0.2%
191344.913457427 4
 
0.2%
193209.131530013 4
 
0.2%
189185.417047275 4
 
0.2%
182446.170472991 3
 
0.2%
179353.214511638 3
 
0.2%
180709.776059033 3
 
0.2%
185760.578634347 3
 
0.2%
193131.590860807 3
 
0.2%
186440.714011168 3
 
0.2%
Other values (1532) 1675
92.4%
(Missing) 103
 
5.7%
ValueCountFrequency (%)
173914.718015169 1
 
0.1%
174068.494334685 1
 
0.1%
174097.616386311 3
0.2%
174213.492106852 1
 
0.1%
174596.132939092 1
 
0.1%
174644.872274897 1
 
0.1%
174676.412428464 1
 
0.1%
174765.307900471 1
 
0.1%
174811.513941031 1
 
0.1%
174885.756922702 2
0.1%
ValueCountFrequency (%)
207205.169925653 1
0.1%
207141.911104602 1
0.1%
206164.575140106 1
0.1%
205671.36729929 1
0.1%
205652.426376355 1
0.1%
205455.066408843 1
0.1%
205405.879376804 1
0.1%
205366.770002161 1
0.1%
205061.202821882 1
0.1%
204747.884437376 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
공동탕업
1537 
목욕장업 기타
155 
공동탕업+찜질시설서비스영업
 
76
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7064018
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1537
84.8%
목욕장업 기타 155
 
8.6%
공동탕업+찜질시설서비스영업 76
 
4.2%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:44:34.559231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:34.648184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1537
78.1%
목욕장업 155
 
7.9%
기타 155
 
7.9%
공동탕업+찜질시설서비스영업 76
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.4%
Missing428
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean3.7362717
Minimum0
Maximum42
Zeros357
Zeros (%)19.7%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:34.741436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q35
95-th percentile10
Maximum42
Range42
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.4374612
Coefficient of variation (CV)1.1876709
Kurtosis16.281858
Mean3.7362717
Median Absolute Deviation (MAD)2
Skewness3.307565
Sum5171
Variance19.691062
MonotonicityNot monotonic
2024-04-18T06:44:34.837316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 357
19.7%
3 298
16.4%
4 207
11.4%
2 133
 
7.3%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.6%
8 29
 
1.6%
1 25
 
1.4%
9 20
 
1.1%
Other values (23) 84
 
4.6%
(Missing) 428
23.6%
ValueCountFrequency (%)
0 357
19.7%
1 25
 
1.4%
2 133
 
7.3%
3 298
16.4%
4 207
11.4%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.6%
8 29
 
1.6%
9 20
 
1.1%
ValueCountFrequency (%)
42 1
 
0.1%
37 1
 
0.1%
34 1
 
0.1%
33 1
 
0.1%
32 1
 
0.1%
30 1
 
0.1%
29 1
 
0.1%
28 3
0.2%
27 1
 
0.1%
25 2
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.7%
Missing664
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean0.76132404
Minimum0
Maximum7
Zeros548
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:34.918962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0425151
Coefficient of variation (CV)1.3693447
Kurtosis7.9614911
Mean0.76132404
Median Absolute Deviation (MAD)1
Skewness2.4174201
Sum874
Variance1.0868377
MonotonicityNot monotonic
2024-04-18T06:44:35.017926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 548
30.2%
1 458
25.3%
2 78
 
4.3%
3 28
 
1.5%
4 16
 
0.9%
6 10
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 664
36.6%
ValueCountFrequency (%)
0 548
30.2%
1 458
25.3%
2 78
 
4.3%
3 28
 
1.5%
4 16
 
0.9%
5 9
 
0.5%
6 10
 
0.6%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
6 10
 
0.6%
5 9
 
0.5%
4 16
 
0.9%
3 28
 
1.5%
2 78
 
4.3%
1 458
25.3%
0 548
30.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing616
Missing (%)34.0%
Infinite0
Infinite (%)0.0%
Mean1.3570234
Minimum0
Maximum10
Zeros365
Zeros (%)20.1%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:35.121974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4036864
Coefficient of variation (CV)1.0343863
Kurtosis5.6638995
Mean1.3570234
Median Absolute Deviation (MAD)1
Skewness1.8198631
Sum1623
Variance1.9703356
MonotonicityNot monotonic
2024-04-18T06:44:35.220012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 370
20.4%
0 365
20.1%
2 300
16.6%
3 77
 
4.2%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
0.7%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 616
34.0%
ValueCountFrequency (%)
0 365
20.1%
1 370
20.4%
2 300
16.6%
3 77
 
4.2%
4 42
 
2.3%
5 20
 
1.1%
6 13
 
0.7%
7 2
 
0.1%
8 4
 
0.2%
10 3
 
0.2%
ValueCountFrequency (%)
10 3
 
0.2%
8 4
 
0.2%
7 2
 
0.1%
6 13
 
0.7%
5 20
 
1.1%
4 42
 
2.3%
3 77
 
4.2%
2 300
16.6%
1 370
20.4%
0 365
20.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing729
Missing (%)40.2%
Infinite0
Infinite (%)0.0%
Mean2.1957525
Minimum0
Maximum11
Zeros225
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:35.306531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7273757
Coefficient of variation (CV)0.78668959
Kurtosis2.5377293
Mean2.1957525
Median Absolute Deviation (MAD)1
Skewness1.1037235
Sum2378
Variance2.9838267
MonotonicityNot monotonic
2024-04-18T06:44:35.389952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 381
21.0%
0 225
 
12.4%
3 209
 
11.5%
1 92
 
5.1%
4 82
 
4.5%
5 48
 
2.6%
6 21
 
1.2%
7 11
 
0.6%
8 5
 
0.3%
9 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 729
40.2%
ValueCountFrequency (%)
0 225
12.4%
1 92
 
5.1%
2 381
21.0%
3 209
11.5%
4 82
 
4.5%
5 48
 
2.6%
6 21
 
1.2%
7 11
 
0.6%
8 5
 
0.3%
9 5
 
0.3%
ValueCountFrequency (%)
11 1
 
0.1%
10 3
 
0.2%
9 5
 
0.3%
8 5
 
0.3%
7 11
 
0.6%
6 21
 
1.2%
5 48
 
2.6%
4 82
 
4.5%
3 209
11.5%
2 381
21.0%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
925 
0
795 
1
 
80
2
 
9
3
 
3

Length

Max length4
Median length4
Mean length2.531457
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 925
51.0%
0 795
43.9%
1 80
 
4.4%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:44:35.501871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:35.602760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 925
51.0%
0 795
43.9%
1 80
 
4.4%
2 9
 
0.5%
3 3
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1156 
0
564 
1
 
67
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.9139073
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1156
63.8%
0 564
31.1%
1 67
 
3.7%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:44:35.701636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:35.797607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1156
63.8%
0 564
31.1%
1 67
 
3.7%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
919 
0
893 

Length

Max length4
Median length4
Mean length2.5215232
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 919
50.7%
0 893
49.3%

Length

2024-04-18T06:44:35.921221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:36.006453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 919
50.7%
0 893
49.3%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
919 
0
893 

Length

Max length4
Median length4
Mean length2.5215232
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 919
50.7%
0 893
49.3%

Length

2024-04-18T06:44:36.094792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:36.179396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 919
50.7%
0 893
49.3%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)1.4%
Missing602
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean1.3140496
Minimum0
Maximum26
Zeros629
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size16.1 KiB
2024-04-18T06:44:36.255702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4.55
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1477018
Coefficient of variation (CV)1.6344146
Kurtosis31.758309
Mean1.3140496
Median Absolute Deviation (MAD)0
Skewness4.3597532
Sum1590
Variance4.612623
MonotonicityNot monotonic
2024-04-18T06:44:36.347220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 629
34.7%
2 472
26.0%
6 28
 
1.5%
4 25
 
1.4%
1 18
 
1.0%
8 13
 
0.7%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
12 2
 
0.1%
Other values (7) 9
 
0.5%
(Missing) 602
33.2%
ValueCountFrequency (%)
0 629
34.7%
1 18
 
1.0%
2 472
26.0%
3 5
 
0.3%
4 25
 
1.4%
5 3
 
0.2%
6 28
 
1.5%
8 13
 
0.7%
9 2
 
0.1%
10 6
 
0.3%
ValueCountFrequency (%)
26 1
 
0.1%
22 1
 
0.1%
18 2
 
0.1%
15 1
 
0.1%
14 1
 
0.1%
12 2
 
0.1%
11 1
 
0.1%
10 6
0.3%
9 2
 
0.1%
8 13
0.7%
Distinct2
Distinct (%)0.1%
Missing2
Missing (%)0.1%
Memory size3.7 KiB
False
1359 
True
451 
(Missing)
 
2
ValueCountFrequency (%)
False 1359
75.0%
True 451
 
24.9%
(Missing) 2
 
0.1%
2024-04-18T06:44:36.434580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
919 
0
892 
2
 
1

Length

Max length4
Median length4
Mean length2.5215232
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> 919
50.7%
0 892
49.2%
2 1
 
0.1%

Length

2024-04-18T06:44:36.523325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:36.613076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 919
50.7%
0 892
49.2%
2 1
 
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1811
Missing (%)99.9%
Memory size14.3 KiB
2024-04-18T06:44:36.764608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters36
Distinct characters28
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
ValueCountFrequency (%)
건축과-16824(2019.4.15),가설건축물 1
33.3%
존치기간연장 1
33.3%
신고 1
33.3%
2024-04-18T06:44:36.996961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
 
8.3%
2
 
5.6%
2 2
 
5.6%
4 2
 
5.6%
. 2
 
5.6%
2
 
5.6%
2
 
5.6%
1
 
2.8%
1
 
2.8%
1
 
2.8%
Other values (18) 18
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
44.4%
Decimal Number 12
33.3%
Other Punctuation 3
 
8.3%
Space Separator 2
 
5.6%
Close Punctuation 1
 
2.8%
Open Punctuation 1
 
2.8%
Dash Punctuation 1
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%
Decimal Number
ValueCountFrequency (%)
1 3
25.0%
2 2
16.7%
4 2
16.7%
5 1
 
8.3%
9 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
6 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
55.6%
Hangul 16
44.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
15.0%
2 2
10.0%
4 2
10.0%
. 2
10.0%
2
10.0%
) 1
 
5.0%
, 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
0 1
 
5.0%
Other values (4) 4
20.0%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
55.6%
Hangul 16
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
15.0%
2 2
10.0%
4 2
10.0%
. 2
10.0%
2
10.0%
) 1
 
5.0%
, 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
0 1
 
5.0%
Other values (4) 4
20.0%
Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1811 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022075
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> 1811
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:44:37.124870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:37.226326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1811
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1811 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022075
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> 1811
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:44:37.336822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:37.446528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1811
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1412 
자가
273 
임대
 
127

Length

Max length4
Median length4
Mean length3.5584989
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1412
77.9%
자가 273
 
15.1%
임대 127
 
7.0%

Length

2024-04-18T06:44:37.539699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:37.639149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1412
77.9%
자가 273
 
15.1%
임대 127
 
7.0%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1153 
0
659 

Length

Max length4
Median length4
Mean length2.9089404
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1153
63.6%
0 659
36.4%

Length

2024-04-18T06:44:37.730653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:37.823582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1153
63.6%
0 659
36.4%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1693 
0
 
114
2
 
2
5
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.8029801
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1693
93.4%
0 114
 
6.3%
2 2
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
1 1
 
0.1%

Length

2024-04-18T06:44:37.929283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:38.033300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1693
93.4%
0 114
 
6.3%
2 2
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
1 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1693 
0
 
114
1
 
3
5
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.8029801
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1693
93.4%
0 114
 
6.3%
1 3
 
0.2%
5 1
 
0.1%
4 1
 
0.1%

Length

2024-04-18T06:44:38.135699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:38.236660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1693
93.4%
0 114
 
6.3%
1 3
 
0.2%
5 1
 
0.1%
4 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1179 
0
633 

Length

Max length4
Median length4
Mean length2.9519868
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1179
65.1%
0 633
34.9%

Length

2024-04-18T06:44:38.332505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:38.422492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1179
65.1%
0 633
34.9%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.3 KiB
<NA>
1180 
0
632 

Length

Max length4
Median length4
Mean length2.9536424
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1180
65.1%
0 632
34.9%

Length

2024-04-18T06:44:38.939726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:39.034598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1180
65.1%
0 632
34.9%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1778 
True
 
34
ValueCountFrequency (%)
False 1778
98.1%
True 34
 
1.9%
2024-04-18T06:44:39.121867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1812
Missing (%)100.0%
Memory size16.1 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01목욕장업11_44_01_P34000003400000-202-2003-0000220031029<NA>3폐업2폐업20121220<NA><NA><NA>051 7243994348.16619905부산광역시 기장군 기장읍 서부리 422번지부산광역시 기장군 기장읍 반송로 154546058에쿠스목욕장20040531000000I2018-08-31 23:59:59.0공동탕업401037.499134196702.5529공동탕업52<NA><NA>11<NA><NA>2N<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>
12목욕장업11_44_01_P34000003400000-202-2000-0009120000330<NA>3폐업2폐업20161129<NA><NA><NA>051 7222537384.00619901부산광역시 기장군 기장읍 교리 352-8번지부산광역시 기장군 기장읍 차성동로 164-1546055교리탕20161130114519I2018-08-31 23:59:59.0공동탕업401804.176817197042.683118공동탕업3<NA>12<NA><NA><NA><NA>4Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
23목욕장업11_44_01_P34000003400000-202-1992-0008419920210<NA>3폐업2폐업20070829<NA><NA><NA>051 7221054609.82619906부산광역시 기장군 기장읍 청강리 226-7번지<NA><NA>보광탕20070814161709I2018-08-31 23:59:59.0공동탕업401913.079586195119.258755공동탕업4<NA>12<NA><NA><NA><NA>4Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>
34목욕장업11_44_01_P34000003400000-202-1994-0040819941125<NA>3폐업2폐업20090731<NA><NA><NA>051 7211997183.56619872부산광역시 기장군 철마면 장전리 366번지<NA><NA>철마목욕탕20030820000000I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
45목욕장업11_44_01_P34000003400000-202-1994-0040719940916<NA>3폐업2폐업20061107<NA><NA><NA>051 7273302395.22619911부산광역시 기장군 일광면 칠암리 158-5번지<NA><NA>풍년탕20031219000000I2018-08-31 23:59:59.0공동탕업405347.024249202354.011586공동탕업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
56목욕장업11_44_01_P34000003400000-202-1991-0008419911126<NA>3폐업2폐업20090817<NA><NA><NA>051 7220680322.38619905부산광역시 기장군 기장읍 동부리 152-8번지 6B 8-1L<NA><NA>제일탕20031219000000I2018-08-31 23:59:59.0공동탕업401672.154925196524.792797공동탕업3<NA>12<NA><NA><NA><NA>2Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N<NA>
67목욕장업11_44_01_P34000003400000-202-1984-0033719840922<NA>3폐업2폐업20041124<NA><NA><NA>051 7214512.00619913부산광역시 기장군 일광면 이천리 908번지<NA><NA>일광탕20020621000000I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
78목욕장업11_44_01_P34000003400000-202-2009-0000120091027<NA>3폐업2폐업20190718<NA><NA><NA>051 723 20931,500.00619903부산광역시 기장군 기장읍 대라리 57번지부산광역시 기장군 기장읍 차성동로 6346066석천탕20190718173053U2019-07-20 02:40:00.0공동탕업401671.55937196027.51628공동탕업004400006N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
89목욕장업11_44_01_P34000003400000-202-1998-0008819980819<NA>3폐업2폐업20090724<NA><NA><NA>051 7210905550.19619904부산광역시 기장군 기장읍 대변리 423번지<NA><NA>대변항해수탕20031219000000I2018-08-31 23:59:59.0공동탕업402750.992777194137.607656공동탕업3<NA>33<NA><NA><NA><NA>2Y<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
910목욕장업11_44_01_P34000003400000-202-1984-0033619840305<NA>3폐업2폐업20200710<NA><NA><NA>051 7215512722.19619912부산광역시 기장군 일광면 삼성리 33-6부산광역시 기장군 일광면 삼성3길 55-146044명성탕20200710154125U2020-07-12 02:40:00.0공동탕업403211.411148198587.35393공동탕업301300004Y0<NA><NA><NA>자가0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
18021803목욕장업11_44_01_P32500003250000-202-1990-0016419900905<NA>1영업/정상1영업<NA><NA><NA><NA>051 2486681526.00600023부산광역시 중구 동광동3가 9-1부산광역시 중구 대청로134번길 10 (동광동3가)48955득일탕20201204174232U2020-12-06 02:40:00.0공동탕업385446.727545180003.559095공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18031804목욕장업11_44_01_P32500003250000-202-1960-0014719601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 4848337.00600012부산광역시 중구 중앙동2가 21-1 , 6, 8부산광역시 중구 대청로138번길 15-1 (중앙동2가, 21-1, 6, 8)48956신수탕20200827153644U2020-08-29 02:40:00.0공동탕업385508.413955179934.600251공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18041805목욕장업11_44_01_P32500003250000-202-1970-0000419701228<NA>1영업/정상1영업<NA><NA><NA><NA>051 4698444156.00600110부산광역시 중구 영주동 277-16부산광역시 중구 동영로 77-1 (영주동)48915영주탕20201204173703U2020-12-06 02:40:00.0공동탕업385201.615276181101.034719공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18051806목욕장업11_44_01_P32500003250000-202-1969-0000119691201<NA>1영업/정상1영업<NA><NA><NA><NA>051 2451969233.00600806부산광역시 중구 부평동2가 68-6부산광역시 중구 중구로33번길 44 (부평동2가)48977청수탕20210118094352U2021-01-20 02:40:00.0공동탕업384626.918928179878.92302공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
18061807목욕장업11_44_01_P32500003250000-202-1982-0015119821112<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 3202232.00600811부산광역시 중구 영주동 636-2부산광역시 중구 중구로188번길 21 (영주동)48922청호탕20200814133434U2020-08-16 02:40:00.0공동탕업385598.846694180987.169146공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18071808목욕장업11_44_01_P32500003250000-202-1960-0014619601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 2443396517.00600074부산광역시 중구 부평동4가 28-3부산광역시 중구 흑교로21번길 21 (부평동4가)48974부천탕20210114133518U2021-01-16 02:40:00.0공동탕업384380.762746179907.143964공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18081809목욕장업11_44_01_P32500003250000-202-1960-0014419601210<NA>1영업/정상1영업<NA><NA><NA><NA>051 24495011,416.48600808부산광역시 중구 부평동3가 22-1 외 2필지부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)48976금강스파20200716105230U2020-07-18 02:40:00.0공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업515511000N0<NA><NA><NA><NA>0<NA><NA>00Y<NA>
18091810목욕장업11_44_01_P32500003250000-202-1988-0015919880913<NA>1영업/정상1영업<NA><NA><NA><NA>051 2472425338.97600062부산광역시 중구 신창동2가 21-2부산광역시 중구 광복로43번길 12 (신창동2가)48947녹수탕20201204174055U2020-12-06 02:40:00.0공동탕업385015.385179808.355521공동탕업412400000N0<NA><NA><NA>임대0<NA><NA>00N<NA>
18101811목욕장업11_44_01_P32500003250000-202-1984-0015219840217<NA>1영업/정상1영업<NA><NA><NA><NA>051 4633803405.00600110부산광역시 중구 영주동 292-10부산광역시 중구 영주로 20 (영주동)48916거북탕20201204173920U2020-12-06 02:40:00.0공동탕업385168.082468180838.190458공동탕업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
18111812목욕장업11_44_01_P32500003250000-202-2005-0000120050228<NA>1영업/정상1영업<NA><NA><NA><NA>051 4692777462.00600816부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)48936마린목욕탕20201204174358U2020-12-06 02:40:00.0공동탕업385825.756708180869.292985공동탕업1930011001N0<NA><NA><NA><NA>0<NA><NA>00N<NA>