Overview

Dataset statistics

Number of variables45
Number of observations1801
Missing cells16039
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory680.8 KiB
Average record size in memory387.1 B

Variable types

Numeric14
Categorical16
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2022-11-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123185

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (63.1%)Imbalance
위생업태명 is highly imbalanced (63.1%)Imbalance
사용끝지하층 is highly imbalanced (51.8%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (76.6%)Imbalance
남성종사자수 is highly imbalanced (74.0%)Imbalance
다중이용업소여부 is highly imbalanced (85.2%)Imbalance
인허가취소일자 has 1801 (100.0%) missing valuesMissing
폐업일자 has 745 (41.4%) missing valuesMissing
휴업시작일자 has 1801 (100.0%) missing valuesMissing
휴업종료일자 has 1801 (100.0%) missing valuesMissing
재개업일자 has 1801 (100.0%) missing valuesMissing
소재지전화 has 109 (6.1%) missing valuesMissing
도로명전체주소 has 603 (33.5%) missing valuesMissing
도로명우편번호 has 658 (36.5%) missing valuesMissing
좌표정보(x) has 98 (5.4%) missing valuesMissing
좌표정보(y) has 98 (5.4%) missing valuesMissing
건물지상층수 has 411 (22.8%) missing valuesMissing
건물지하층수 has 639 (35.5%) missing valuesMissing
사용시작지상층 has 594 (33.0%) missing valuesMissing
사용끝지상층 has 685 (38.0%) missing valuesMissing
욕실수 has 577 (32.0%) missing valuesMissing
조건부허가신고사유 has 1800 (99.9%) missing valuesMissing
Unnamed: 44 has 1801 (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: 44 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 362 (20.1%) zerosZeros
건물지하층수 has 562 (31.2%) zerosZeros
사용시작지상층 has 373 (20.7%) zerosZeros
사용끝지상층 has 255 (14.2%) zerosZeros
욕실수 has 637 (35.4%) zerosZeros

Reproduction

Analysis started2024-04-17 21:43:22.960918
Analysis finished2024-04-17 21:43:23.930219
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1801
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean901
Minimum1
Maximum1801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:23.990078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91
Q1451
median901
Q31351
95-th percentile1711
Maximum1801
Range1800
Interquartile range (IQR)900

Descriptive statistics

Standard deviation520.04823
Coefficient of variation (CV)0.57719005
Kurtosis-1.2
Mean901
Median Absolute Deviation (MAD)450
Skewness0
Sum1622701
Variance270450.17
MonotonicityStrictly increasing
2024-04-18T06:43:24.109341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1239 1
 
0.1%
1209 1
 
0.1%
1208 1
 
0.1%
1207 1
 
0.1%
1206 1
 
0.1%
1205 1
 
0.1%
1204 1
 
0.1%
1203 1
 
0.1%
1202 1
 
0.1%
Other values (1791) 1791
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 (%)
1801 1
0.1%
1800 1
0.1%
1799 1
0.1%
1798 1
0.1%
1797 1
0.1%
1796 1
0.1%
1795 1
0.1%
1794 1
0.1%
1793 1
0.1%
1792 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
목욕장업
1801 

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 1801
100.0%

Length

2024-04-18T06:43:24.218142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:24.328535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1801
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
11_44_01_P
1801 

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 1801
100.0%

Length

2024-04-18T06:43:24.430574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:24.510188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1801
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3323109.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:24.589720image/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 deviation40124.718
Coefficient of variation (CV)0.01207445
Kurtosis-0.9186507
Mean3323109.4
Median Absolute Deviation (MAD)30000
Skewness0.12345046
Sum5.98492 × 109
Variance1.609993 × 109
MonotonicityNot monotonic
2024-04-18T06:43:24.686846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 222
12.3%
3340000 174
9.7%
3330000 159
8.8%
3300000 147
 
8.2%
3310000 147
 
8.2%
3370000 130
 
7.2%
3320000 125
 
6.9%
3350000 113
 
6.3%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 378
21.0%
ValueCountFrequency (%)
3250000 63
 
3.5%
3260000 74
 
4.1%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 222
12.3%
3300000 147
8.2%
3310000 147
8.2%
3320000 125
6.9%
3330000 159
8.8%
3340000 174
9.7%
ValueCountFrequency (%)
3400000 46
 
2.6%
3390000 94
5.2%
3380000 112
6.2%
3370000 130
7.2%
3360000 29
 
1.6%
3350000 113
6.3%
3340000 174
9.7%
3330000 159
8.8%
3320000 125
6.9%
3310000 147
8.2%

관리번호
Text

UNIQUE 

Distinct1801
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:43:24.885451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39622
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

Unique1801 ?
Unique (%)100.0%

Sample

1st row3250000-202-2022-00001
2nd row3250000-202-2005-00001
3rd row3250000-202-1984-00152
4th row3250000-202-1988-00159
5th row3250000-202-1960-00144
ValueCountFrequency (%)
3250000-202-2022-00001 1
 
0.1%
3320000-202-2006-00003 1
 
0.1%
3310000-202-2003-00001 1
 
0.1%
3310000-202-1982-00837 1
 
0.1%
3310000-202-1984-00253 1
 
0.1%
3310000-202-1970-00101 1
 
0.1%
3310000-202-1970-00043 1
 
0.1%
3310000-202-2002-00002 1
 
0.1%
3310000-202-1967-00412 1
 
0.1%
3310000-202-1963-00340 1
 
0.1%
Other values (1791) 1791
99.4%
2024-04-18T06:43:25.165887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15296
38.6%
2 5628
 
14.2%
- 5403
 
13.6%
3 3904
 
9.9%
1 2712
 
6.8%
9 2499
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34219
86.4%
Dash Punctuation 5403
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15296
44.7%
2 5628
 
16.4%
3 3904
 
11.4%
1 2712
 
7.9%
9 2499
 
7.3%
8 1135
 
3.3%
4 936
 
2.7%
7 832
 
2.4%
5 684
 
2.0%
6 593
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5403
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39622
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15296
38.6%
2 5628
 
14.2%
- 5403
 
13.6%
3 3904
 
9.9%
1 2712
 
6.8%
9 2499
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15296
38.6%
2 5628
 
14.2%
- 5403
 
13.6%
3 3904
 
9.9%
1 2712
 
6.8%
9 2499
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

인허가일자
Real number (ℝ)

Distinct1533
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19910480
Minimum19540131
Maximum20220803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:25.682128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19540131
5-th percentile19700422
Q119830304
median19901023
Q320010514
95-th percentile20110902
Maximum20220803
Range680672
Interquartile range (IQR)180210

Descriptive statistics

Standard deviation124718.17
Coefficient of variation (CV)0.0062639461
Kurtosis-0.34057457
Mean19910480
Median Absolute Deviation (MAD)89186
Skewness-0.017487709
Sum3.5858774 × 1010
Variance1.5554623 × 1010
MonotonicityNot monotonic
2024-04-18T06:43:25.804747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19630110 15
 
0.8%
20001130 9
 
0.5%
19830304 5
 
0.3%
19820928 5
 
0.3%
20000420 5
 
0.3%
20030115 5
 
0.3%
19630610 4
 
0.2%
19840908 4
 
0.2%
19880314 4
 
0.2%
19861217 4
 
0.2%
Other values (1523) 1741
96.7%
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 (%)
20220803 1
0.1%
20220610 1
0.1%
20220502 1
0.1%
20220328 1
0.1%
20220105 1
0.1%
20211115 1
0.1%
20211112 1
0.1%
20210914 1
0.1%
20210525 1
0.1%
20210401 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1801
Missing (%)100.0%
Memory size16.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
3
1056 
1
745 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1056
58.6%
1 745
41.4%

Length

2024-04-18T06:43:25.920442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:26.002055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1056
58.6%
1 745
41.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1056 
영업/정상
745 

Length

Max length5
Median length2
Mean length3.2409772
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1056
58.6%
영업/정상 745
41.4%

Length

2024-04-18T06:43:26.087486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:26.192425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1056
58.6%
영업/정상 745
41.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2
1056 
1
745 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1056
58.6%
1 745
41.4%

Length

2024-04-18T06:43:26.284889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:26.372171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1056
58.6%
1 745
41.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1056 
영업
745 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1056
58.6%
영업 745
41.4%

Length

2024-04-18T06:43:26.463080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:26.548064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1056
58.6%
영업 745
41.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct889
Distinct (%)84.2%
Missing745
Missing (%)41.4%
Infinite0
Infinite (%)0.0%
Mean20105421
Minimum19901019
Maximum20220927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:26.650462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19901019
5-th percentile20000310
Q120051230
median20110220
Q320160217
95-th percentile20210718
Maximum20220927
Range319908
Interquartile range (IQR)108987.5

Descriptive statistics

Standard deviation65148.522
Coefficient of variation (CV)0.0032403461
Kurtosis-0.64941807
Mean20105421
Median Absolute Deviation (MAD)50011.5
Skewness-0.12683922
Sum2.1231324 × 1010
Variance4.2443299 × 109
MonotonicityNot monotonic
2024-04-18T06:43:26.781935image/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%
20170310 5
 
0.3%
20030401 5
 
0.3%
20120621 4
 
0.2%
20190226 4
 
0.2%
20141030 4
 
0.2%
20030122 4
 
0.2%
20180102 3
 
0.2%
Other values (879) 1001
55.6%
(Missing) 745
41.4%
ValueCountFrequency (%)
19901019 1
0.1%
19921202 1
0.1%
19930607 1
0.1%
19930726 1
0.1%
19930924 1
0.1%
19931228 1
0.1%
19950309 1
0.1%
19950624 1
0.1%
19950709 1
0.1%
19950728 1
0.1%
ValueCountFrequency (%)
20220927 1
0.1%
20220922 2
0.1%
20220920 1
0.1%
20220919 1
0.1%
20220916 1
0.1%
20220914 1
0.1%
20220824 1
0.1%
20220809 2
0.1%
20220720 1
0.1%
20220706 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1801
Missing (%)100.0%
Memory size16.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1801
Missing (%)100.0%
Memory size16.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1801
Missing (%)100.0%
Memory size16.0 KiB

소재지전화
Text

MISSING 

Distinct1610
Distinct (%)95.2%
Missing109
Missing (%)6.1%
Memory size14.2 KiB
2024-04-18T06:43:26.997759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.911348
Min length3

Characters and Unicode

Total characters18462
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

Unique1572 ?
Unique (%)92.9%

Sample

1st row051 462 7616
2nd row051 4692777
3rd row051 4633803
4th row051 2472425
5th row051 2449501
ValueCountFrequency (%)
051 1638
45.5%
808 8
 
0.2%
893 7
 
0.2%
897 5
 
0.1%
816 5
 
0.1%
261 5
 
0.1%
070 5
 
0.1%
891 5
 
0.1%
802 5
 
0.1%
646 4
 
0.1%
Other values (1770) 1912
53.1%
2024-04-18T06:43:27.323882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3045
16.5%
0 2842
15.4%
1 2765
15.0%
1916
10.4%
2 1445
7.8%
3 1302
7.1%
6 1230
6.7%
4 1110
 
6.0%
7 1074
 
5.8%
8 1030
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16546
89.6%
Space Separator 1916
 
10.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3045
18.4%
0 2842
17.2%
1 2765
16.7%
2 1445
8.7%
3 1302
7.9%
6 1230
7.4%
4 1110
 
6.7%
7 1074
 
6.5%
8 1030
 
6.2%
9 703
 
4.2%
Space Separator
ValueCountFrequency (%)
1916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18462
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3045
16.5%
0 2842
15.4%
1 2765
15.0%
1916
10.4%
2 1445
7.8%
3 1302
7.1%
6 1230
6.7%
4 1110
 
6.0%
7 1074
 
5.8%
8 1030
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18462
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3045
16.5%
0 2842
15.4%
1 2765
15.0%
1916
10.4%
2 1445
7.8%
3 1302
7.1%
6 1230
6.7%
4 1110
 
6.0%
7 1074
 
5.8%
8 1030
 
5.6%
Distinct1582
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Memory size14.2 KiB
2024-04-18T06:43:27.589653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9720982
Min length3

Characters and Unicode

Total characters10702
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

Unique1498 ?
Unique (%)83.6%

Sample

1st row354.91
2nd row462.00
3rd row405.00
4th row338.97
5th row1,416.48
ValueCountFrequency (%)
00 116
 
6.5%
330.00 5
 
0.3%
427.44 3
 
0.2%
93.73 3
 
0.2%
252.17 3
 
0.2%
363.30 3
 
0.2%
478.00 3
 
0.2%
798.24 3
 
0.2%
348.00 3
 
0.2%
426.00 3
 
0.2%
Other values (1572) 1647
91.9%
2024-04-18T06:43:27.962444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1792
16.7%
0 1422
13.3%
2 1048
9.8%
3 998
9.3%
4 929
8.7%
1 904
8.4%
8 702
 
6.6%
6 701
 
6.6%
5 694
 
6.5%
7 680
 
6.4%
Other values (2) 832
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8751
81.8%
Other Punctuation 1951
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1422
16.2%
2 1048
12.0%
3 998
11.4%
4 929
10.6%
1 904
10.3%
8 702
8.0%
6 701
8.0%
5 694
7.9%
7 680
7.8%
9 673
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1792
91.9%
, 159
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Common 10702
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1792
16.7%
0 1422
13.3%
2 1048
9.8%
3 998
9.3%
4 929
8.7%
1 904
8.4%
8 702
 
6.6%
6 701
 
6.6%
5 694
 
6.5%
7 680
 
6.4%
Other values (2) 832
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10702
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1792
16.7%
0 1422
13.3%
2 1048
9.8%
3 998
9.3%
4 929
8.7%
1 904
8.4%
8 702
 
6.6%
6 701
 
6.6%
5 694
 
6.5%
7 680
 
6.4%
Other values (2) 832
7.8%

소재지우편번호
Real number (ℝ)

Distinct631
Distinct (%)35.2%
Missing6
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean610439.09
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:28.086292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601810.7
Q1606806
median611803
Q3614822
95-th percentile617834
Maximum619953
Range19942
Interquartile range (IQR)8016

Descriptive statistics

Standard deviation5192.9201
Coefficient of variation (CV)0.0085068604
Kurtosis-0.93198055
Mean610439.09
Median Absolute Deviation (MAD)3964
Skewness-0.21865462
Sum1.0957382 × 109
Variance26966419
MonotonicityNot monotonic
2024-04-18T06:43:28.207782image/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 11
 
0.6%
614822 10
 
0.6%
608828 10
 
0.6%
607833 9
 
0.5%
613832 9
 
0.5%
613805 9
 
0.5%
607826 9
 
0.5%
Other values (621) 1689
93.8%
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%
Distinct1742
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:43:28.516201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length23.233204
Min length16

Characters and Unicode

Total characters41843
Distinct characters278
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

Unique1689 ?
Unique (%)93.8%

Sample

1st row부산광역시 중구 대청동4가 24-1
2nd row부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)
3rd row부산광역시 중구 영주동 292-10
4th row부산광역시 중구 신창동2가 21-2
5th row부산광역시 중구 부평동3가 22-1 외 2필지
ValueCountFrequency (%)
부산광역시 1801
 
22.4%
t통b반 334
 
4.2%
부산진구 222
 
2.8%
사하구 174
 
2.2%
해운대구 159
 
2.0%
동래구 147
 
1.8%
남구 147
 
1.8%
연제구 130
 
1.6%
북구 125
 
1.6%
금정구 113
 
1.4%
Other values (2188) 4686
58.3%
2024-04-18T06:43:28.948931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6238
 
14.9%
2152
 
5.1%
2143
 
5.1%
2083
 
5.0%
1 1895
 
4.5%
1872
 
4.5%
1822
 
4.4%
1813
 
4.3%
1805
 
4.3%
- 1673
 
4.0%
Other values (268) 18347
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24259
58.0%
Decimal Number 8746
 
20.9%
Space Separator 6238
 
14.9%
Dash Punctuation 1673
 
4.0%
Uppercase Letter 683
 
1.6%
Other Punctuation 114
 
0.3%
Open Punctuation 61
 
0.1%
Close Punctuation 61
 
0.1%
Math Symbol 7
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2152
 
8.9%
2143
 
8.8%
2083
 
8.6%
1872
 
7.7%
1822
 
7.5%
1813
 
7.5%
1805
 
7.4%
1325
 
5.5%
1256
 
5.2%
385
 
1.6%
Other values (242) 7603
31.3%
Decimal Number
ValueCountFrequency (%)
1 1895
21.7%
2 1128
12.9%
3 988
11.3%
4 881
10.1%
5 779
8.9%
6 675
 
7.7%
7 645
 
7.4%
8 608
 
7.0%
0 608
 
7.0%
9 539
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 334
48.9%
A 2
 
0.3%
W 2
 
0.3%
G 1
 
0.1%
I 1
 
0.1%
L 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
. 1
 
0.9%
@ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
6238
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1673
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24259
58.0%
Common 16900
40.4%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2152
 
8.9%
2143
 
8.8%
2083
 
8.6%
1872
 
7.7%
1822
 
7.5%
1813
 
7.5%
1805
 
7.4%
1325
 
5.5%
1256
 
5.2%
385
 
1.6%
Other values (242) 7603
31.3%
Common
ValueCountFrequency (%)
6238
36.9%
1 1895
 
11.2%
- 1673
 
9.9%
2 1128
 
6.7%
3 988
 
5.8%
4 881
 
5.2%
5 779
 
4.6%
6 675
 
4.0%
7 645
 
3.8%
8 608
 
3.6%
Other values (8) 1390
 
8.2%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 334
48.8%
A 2
 
0.3%
W 2
 
0.3%
G 1
 
0.1%
I 1
 
0.1%
L 1
 
0.1%
1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24259
58.0%
ASCII 17583
42.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6238
35.5%
1 1895
 
10.8%
- 1673
 
9.5%
2 1128
 
6.4%
3 988
 
5.6%
4 881
 
5.0%
5 779
 
4.4%
6 675
 
3.8%
7 645
 
3.7%
8 608
 
3.5%
Other values (15) 2073
 
11.8%
Hangul
ValueCountFrequency (%)
2152
 
8.9%
2143
 
8.8%
2083
 
8.6%
1872
 
7.7%
1822
 
7.5%
1813
 
7.5%
1805
 
7.4%
1325
 
5.5%
1256
 
5.2%
385
 
1.6%
Other values (242) 7603
31.3%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1185
Distinct (%)98.9%
Missing603
Missing (%)33.5%
Memory size14.2 KiB
2024-04-18T06:43:29.295225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.573456
Min length20

Characters and Unicode

Total characters33033
Distinct characters337
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

Unique1172 ?
Unique (%)97.8%

Sample

1st row부산광역시 중구 대청북길 44, 1-3층 (대청동4가)
2nd row부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)
3rd row부산광역시 중구 영주로 20 (영주동)
4th row부산광역시 중구 광복로43번길 12 (신창동2가)
5th row부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)
ValueCountFrequency (%)
부산광역시 1198
 
19.0%
부산진구 154
 
2.4%
남구 103
 
1.6%
해운대구 103
 
1.6%
사하구 103
 
1.6%
동래구 96
 
1.5%
연제구 84
 
1.3%
북구 77
 
1.2%
금정구 75
 
1.2%
사상구 72
 
1.1%
Other values (1733) 4226
67.2%
2024-04-18T06:43:29.777183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5094
 
15.4%
1518
 
4.6%
1452
 
4.4%
1451
 
4.4%
1266
 
3.8%
1254
 
3.8%
1228
 
3.7%
1203
 
3.6%
( 1183
 
3.6%
) 1183
 
3.6%
Other values (327) 16201
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19884
60.2%
Decimal Number 5100
 
15.4%
Space Separator 5094
 
15.4%
Open Punctuation 1184
 
3.6%
Close Punctuation 1184
 
3.6%
Other Punctuation 356
 
1.1%
Dash Punctuation 202
 
0.6%
Uppercase Letter 15
 
< 0.1%
Math Symbol 13
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1518
 
7.6%
1452
 
7.3%
1451
 
7.3%
1266
 
6.4%
1254
 
6.3%
1228
 
6.2%
1203
 
6.1%
1141
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 7989
40.2%
Decimal Number
ValueCountFrequency (%)
1 1154
22.6%
2 722
14.2%
3 637
12.5%
5 450
 
8.8%
4 440
 
8.6%
6 388
 
7.6%
0 381
 
7.5%
7 353
 
6.9%
9 290
 
5.7%
8 285
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 7
46.7%
A 4
26.7%
W 2
 
13.3%
I 1
 
6.7%
G 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 351
98.6%
. 3
 
0.8%
@ 1
 
0.3%
* 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1183
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1183
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5094
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19884
60.2%
Common 13133
39.8%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1518
 
7.6%
1452
 
7.3%
1451
 
7.3%
1266
 
6.4%
1254
 
6.3%
1228
 
6.2%
1203
 
6.1%
1141
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 7989
40.2%
Common
ValueCountFrequency (%)
5094
38.8%
( 1183
 
9.0%
) 1183
 
9.0%
1 1154
 
8.8%
2 722
 
5.5%
3 637
 
4.9%
5 450
 
3.4%
4 440
 
3.4%
6 388
 
3.0%
0 381
 
2.9%
Other values (12) 1501
 
11.4%
Latin
ValueCountFrequency (%)
B 7
43.8%
A 4
25.0%
W 2
 
12.5%
1
 
6.2%
I 1
 
6.2%
G 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19884
60.2%
ASCII 13147
39.8%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5094
38.7%
( 1183
 
9.0%
) 1183
 
9.0%
1 1154
 
8.8%
2 722
 
5.5%
3 637
 
4.8%
5 450
 
3.4%
4 440
 
3.3%
6 388
 
3.0%
0 381
 
2.9%
Other values (16) 1515
 
11.5%
Hangul
ValueCountFrequency (%)
1518
 
7.6%
1452
 
7.3%
1451
 
7.3%
1266
 
6.4%
1254
 
6.3%
1228
 
6.2%
1203
 
6.1%
1141
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 7989
40.2%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct878
Distinct (%)76.8%
Missing658
Missing (%)36.5%
Infinite0
Infinite (%)0.0%
Mean47881.816
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:29.906426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147142
median47878
Q348721.5
95-th percentile49395.8
Maximum49523
Range3521
Interquartile range (IQR)1579.5

Descriptive statistics

Standard deviation983.60404
Coefficient of variation (CV)0.020542329
Kurtosis-1.0490673
Mean47881.816
Median Absolute Deviation (MAD)760
Skewness-0.080837271
Sum54728916
Variance967476.91
MonotonicityNot monotonic
2024-04-18T06:43:30.022668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47709 8
 
0.4%
48099 8
 
0.4%
47248 6
 
0.3%
46327 5
 
0.3%
48095 4
 
0.2%
48052 4
 
0.2%
47712 4
 
0.2%
47142 4
 
0.2%
48053 4
 
0.2%
46308 4
 
0.2%
Other values (868) 1092
60.6%
(Missing) 658
36.5%
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%
Distinct1134
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:43:30.290963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1426985
Min length2

Characters and Unicode

Total characters7461
Distinct characters384
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 (%)49.7%

Sample

1st row대청행복탕
2nd row마린목욕탕
3rd row거북탕
4th row녹수탕
5th row금강스파
ValueCountFrequency (%)
사우나 26
 
1.3%
청수탕 21
 
1.1%
현대탕 19
 
1.0%
옥천탕 19
 
1.0%
목욕탕 16
 
0.8%
산수탕 15
 
0.8%
천수탕 15
 
0.8%
장수탕 14
 
0.7%
평화탕 13
 
0.7%
약수탕 13
 
0.7%
Other values (1192) 1791
91.3%
2024-04-18T06:43:30.701018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1357
 
18.2%
299
 
4.0%
220
 
2.9%
181
 
2.4%
179
 
2.4%
168
 
2.3%
161
 
2.2%
159
 
2.1%
122
 
1.6%
117
 
1.6%
Other values (374) 4498
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7181
96.2%
Space Separator 161
 
2.2%
Close Punctuation 38
 
0.5%
Open Punctuation 35
 
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 (%)
1357
 
18.9%
299
 
4.2%
220
 
3.1%
181
 
2.5%
179
 
2.5%
168
 
2.3%
159
 
2.2%
122
 
1.7%
117
 
1.6%
115
 
1.6%
Other values (352) 4264
59.4%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
W 2
13.3%
O 2
13.3%
L 2
13.3%
F 1
 
6.7%
S 1
 
6.7%
M 1
 
6.7%
B 1
 
6.7%
J 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
n 2
28.6%
r 1
14.3%
u 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 (%)
161
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7180
96.2%
Common 258
 
3.5%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1357
 
18.9%
299
 
4.2%
220
 
3.1%
181
 
2.5%
179
 
2.5%
168
 
2.3%
159
 
2.2%
122
 
1.7%
117
 
1.6%
115
 
1.6%
Other values (351) 4263
59.4%
Latin
ValueCountFrequency (%)
G 4
18.2%
W 2
9.1%
O 2
9.1%
o 2
9.1%
L 2
9.1%
n 2
9.1%
F 1
 
4.5%
S 1
 
4.5%
M 1
 
4.5%
B 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
161
62.4%
) 38
 
14.7%
( 35
 
13.6%
2 11
 
4.3%
4 9
 
3.5%
- 2
 
0.8%
. 1
 
0.4%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7180
96.2%
ASCII 280
 
3.8%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1357
 
18.9%
299
 
4.2%
220
 
3.1%
181
 
2.5%
179
 
2.5%
168
 
2.3%
159
 
2.2%
122
 
1.7%
117
 
1.6%
115
 
1.6%
Other values (351) 4263
59.4%
ASCII
ValueCountFrequency (%)
161
57.5%
) 38
 
13.6%
( 35
 
12.5%
2 11
 
3.9%
4 9
 
3.2%
G 4
 
1.4%
W 2
 
0.7%
O 2
 
0.7%
- 2
 
0.7%
o 2
 
0.7%
Other values (12) 14
 
5.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1526
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0133027 × 1013
Minimum1.999021 × 1013
Maximum2.022093 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:30.833421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.999021 × 1013
5-th percentile2.0020424 × 1013
Q12.0050415 × 1013
median2.015093 × 1013
Q32.0200925 × 1013
95-th percentile2.0220408 × 1013
Maximum2.022093 × 1013
Range2.3072011 × 1011
Interquartile range (IQR)1.5051012 × 1011

Descriptive statistics

Standard deviation7.4332923 × 1010
Coefficient of variation (CV)0.0036920889
Kurtosis-1.414598
Mean2.0133027 × 1013
Median Absolute Deviation (MAD)5.9670979 × 1010
Skewness-0.39133126
Sum3.6259581 × 1016
Variance5.5253835 × 1021
MonotonicityNot monotonic
2024-04-18T06:43:30.954720image/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%
20030303000000 12
 
0.7%
20031217000000 10
 
0.6%
20041208000000 9
 
0.5%
20030722000000 8
 
0.4%
20040324000000 8
 
0.4%
19990421000000 7
 
0.4%
Other values (1516) 1670
92.7%
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 (%)
20220930105705 1
0.1%
20220928134502 1
0.1%
20220928111211 1
0.1%
20220927133858 1
0.1%
20220926135241 1
0.1%
20220926132024 1
0.1%
20220923100517 1
0.1%
20220923095056 1
0.1%
20220922110227 1
0.1%
20220922110212 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
I
1074 
U
727 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1074
59.6%
U 727
40.4%

Length

2024-04-18T06:43:31.084227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:31.171139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1074
59.6%
u 727
40.4%
Distinct361
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum2018-08-31 23:59:59
Maximum2022-10-02 02:40:00
2024-04-18T06:43:31.257957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:43:31.374319image/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 size14.2 KiB
공동탕업
1523 
목욕장업 기타
157 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7196002
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1523
84.6%
목욕장업 기타 157
 
8.7%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:43:31.483764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:31.573674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1523
77.8%
목욕장업 157
 
8.0%
기타 157
 
8.0%
공동탕업+찜질시설서비스영업 77
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1541
Distinct (%)90.5%
Missing98
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean387804.46
Minimum366820.79
Maximum407878.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:31.672166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379644.67
Q1384047.84
median388161.21
Q3391126.47
95-th percentile396841.07
Maximum407878.31
Range41057.525
Interquartile range (IQR)7078.6358

Descriptive statistics

Standard deviation5292.0951
Coefficient of variation (CV)0.013646298
Kurtosis0.71721219
Mean387804.46
Median Absolute Deviation (MAD)3552.2616
Skewness0.26587944
Sum6.60431 × 108
Variance28006271
MonotonicityNot monotonic
2024-04-18T06:43:31.800919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391834.082986499 4
 
0.2%
386026.75739607 4
 
0.2%
389415.20340442 3
 
0.2%
383300.306176121 3
 
0.2%
389322.400841052 3
 
0.2%
386428.823034759 3
 
0.2%
391103.422349355 3
 
0.2%
390285.068808765 3
 
0.2%
383091.957810087 3
 
0.2%
379618.460093644 3
 
0.2%
Other values (1531) 1671
92.8%
(Missing) 98
 
5.4%
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 

Distinct1541
Distinct (%)90.5%
Missing98
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean186621.15
Minimum173914.72
Maximum207205.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:31.919555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177919.86
Q1182281.53
median186777.67
Q3190626.48
95-th percentile195576.92
Maximum207205.17
Range33290.452
Interquartile range (IQR)8344.9487

Descriptive statistics

Standard deviation5631.0864
Coefficient of variation (CV)0.030173892
Kurtosis0.038918206
Mean186621.15
Median Absolute Deviation (MAD)4131.688
Skewness0.24954083
Sum3.1781581 × 108
Variance31709134
MonotonicityNot monotonic
2024-04-18T06:43:32.034909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189185.417047275 4
 
0.2%
181580.381775088 4
 
0.2%
193131.590860807 3
 
0.2%
193948.527977305 3
 
0.2%
193209.131530013 3
 
0.2%
189577.746954425 3
 
0.2%
182446.170472991 3
 
0.2%
184019.031918217 3
 
0.2%
179227.873327685 3
 
0.2%
174097.616386311 3
 
0.2%
Other values (1531) 1671
92.8%
(Missing) 98
 
5.4%
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 size14.2 KiB
공동탕업
1523 
목욕장업 기타
157 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7196002
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1523
84.6%
목욕장업 기타 157
 
8.7%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:43:32.173845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:32.270056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1523
77.8%
목욕장업 157
 
8.0%
기타 157
 
8.0%
공동탕업+찜질시설서비스영업 77
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.4%
Missing411
Missing (%)22.8%
Infinite0
Infinite (%)0.0%
Mean3.7230216
Minimum0
Maximum42
Zeros362
Zeros (%)20.1%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:32.369874image/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 deviation4.4335233
Coefficient of variation (CV)1.1908401
Kurtosis16.307969
Mean3.7230216
Median Absolute Deviation (MAD)2
Skewness3.3088614
Sum5175
Variance19.656129
MonotonicityNot monotonic
2024-04-18T06:43:32.466816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 362
20.1%
3 298
16.5%
4 208
11.5%
2 133
 
7.4%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.7%
8 29
 
1.6%
1 25
 
1.4%
9 20
 
1.1%
Other values (23) 84
 
4.7%
(Missing) 411
22.8%
ValueCountFrequency (%)
0 362
20.1%
1 25
 
1.4%
2 133
 
7.4%
3 298
16.5%
4 208
11.5%
5 132
 
7.3%
6 51
 
2.8%
7 48
 
2.7%
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%
Missing639
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean0.75215146
Minimum0
Maximum7
Zeros562
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:32.549709image/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 deviation1.0395369
Coefficient of variation (CV)1.3820846
Kurtosis8.0424415
Mean0.75215146
Median Absolute Deviation (MAD)1
Skewness2.4305763
Sum874
Variance1.0806371
MonotonicityNot monotonic
2024-04-18T06:43:32.656164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 562
31.2%
1 458
25.4%
2 78
 
4.3%
3 28
 
1.6%
4 16
 
0.9%
6 10
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 639
35.5%
ValueCountFrequency (%)
0 562
31.2%
1 458
25.4%
2 78
 
4.3%
3 28
 
1.6%
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
 
1.6%
2 78
 
4.3%
1 458
25.4%
0 562
31.2%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing594
Missing (%)33.0%
Infinite0
Infinite (%)0.0%
Mean1.3446562
Minimum0
Maximum10
Zeros373
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:32.777061image/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 deviation1.3984779
Coefficient of variation (CV)1.0400264
Kurtosis5.7190275
Mean1.3446562
Median Absolute Deviation (MAD)1
Skewness1.8268484
Sum1623
Variance1.9557405
MonotonicityNot monotonic
2024-04-18T06:43:32.867101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 374
20.8%
0 373
20.7%
2 300
16.7%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 12
 
0.7%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 594
33.0%
ValueCountFrequency (%)
0 373
20.7%
1 374
20.8%
2 300
16.7%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 12
 
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 12
 
0.7%
5 21
 
1.2%
4 42
 
2.3%
3 76
 
4.2%
2 300
16.7%
1 374
20.8%
0 373
20.7%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing685
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean2.1335125
Minimum0
Maximum11
Zeros255
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:32.953429image/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 deviation1.7351824
Coefficient of variation (CV)0.81329843
Kurtosis2.476246
Mean2.1335125
Median Absolute Deviation (MAD)1
Skewness1.1002525
Sum2381
Variance3.010858
MonotonicityNot monotonic
2024-04-18T06:43:33.036295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 382
21.2%
0 255
 
14.2%
3 211
 
11.7%
1 93
 
5.2%
4 82
 
4.6%
5 48
 
2.7%
6 20
 
1.1%
7 11
 
0.6%
9 5
 
0.3%
8 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 685
38.0%
ValueCountFrequency (%)
0 255
14.2%
1 93
 
5.2%
2 382
21.2%
3 211
11.7%
4 82
 
4.6%
5 48
 
2.7%
6 20
 
1.1%
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 20
 
1.1%
5 48
 
2.7%
4 82
 
4.6%
3 211
11.7%
2 382
21.2%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
881 
0
827 
1
 
81
2
 
9
3
 
3

Length

Max length4
Median length1
Mean length2.467518
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 881
48.9%
0 827
45.9%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:43:33.154107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:33.276041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 881
48.9%
0 827
45.9%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1087 
0
620 
1
 
69
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.8106607
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1087
60.4%
0 620
34.4%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:43:33.370037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:33.459846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1087
60.4%
0 620
34.4%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)1.4%
Missing577
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean1.3145425
Minimum0
Maximum26
Zeros637
Zeros (%)35.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:43:33.546144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1466857
Coefficient of variation (CV)1.6330287
Kurtosis31.457854
Mean1.3145425
Median Absolute Deviation (MAD)0
Skewness4.3308094
Sum1609
Variance4.6082593
MonotonicityNot monotonic
2024-04-18T06:43:33.653100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 637
35.4%
2 475
26.4%
6 30
 
1.7%
4 25
 
1.4%
1 19
 
1.1%
8 13
 
0.7%
10 6
 
0.3%
3 5
 
0.3%
5 3
 
0.2%
18 2
 
0.1%
Other values (7) 9
 
0.5%
(Missing) 577
32.0%
ValueCountFrequency (%)
0 637
35.4%
1 19
 
1.1%
2 475
26.4%
3 5
 
0.3%
4 25
 
1.4%
5 3
 
0.2%
6 30
 
1.7%
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 size3.6 KiB
False
1343 
True
456 
(Missing)
 
2
ValueCountFrequency (%)
False 1343
74.6%
True 456
 
25.3%
(Missing) 2
 
0.1%
2024-04-18T06:43:33.746480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1800
Missing (%)99.9%
Memory size14.2 KiB
2024-04-18T06:43:33.871933image/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%
2024-04-18T06:43:34.108274image/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 size14.2 KiB
<NA>
1800 
20190501
 
1

Length

Max length8
Median length4
Mean length4.002221
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> 1800
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:43:34.220254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:34.313158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1800
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1800 
20210421
 
1

Length

Max length8
Median length4
Mean length4.002221
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> 1800
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:43:34.416643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:34.503458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1800
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1400 
자가
273 
임대
 
128

Length

Max length4
Median length4
Mean length3.5546918
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1400
77.7%
자가 273
 
15.2%
임대 128
 
7.1%

Length

2024-04-18T06:43:35.068056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:35.173912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1400
77.7%
자가 273
 
15.2%
임대 128
 
7.1%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1552 
0
244 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.5852304
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1552
86.2%
0 244
 
13.5%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:43:35.289518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:35.407565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1552
86.2%
0 244
 
13.5%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1552 
0
244 
1
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.5852304
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1552
86.2%
0 244
 
13.5%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:43:35.534430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:43:35.637050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1552
86.2%
0 244
 
13.5%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
False
1763 
True
 
38
ValueCountFrequency (%)
False 1763
97.9%
True 38
 
2.1%
2024-04-18T06:43:35.729002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 44
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1801
Missing (%)100.0%
Memory size16.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
01목욕장업11_44_01_P32500003250000-202-2022-0000120220328<NA>1영업/정상1영업<NA><NA><NA><NA>051 462 7616354.91600800부산광역시 중구 대청동4가 24-1부산광역시 중구 대청북길 44, 1-3층 (대청동4가)48971대청행복탕20220418150347U2022-04-20 02:40:00.0공동탕업385153.11515180500.97525공동탕업4113002Y<NA><NA><NA>임대00N<NA>
12목욕장업11_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 02:40:00.0공동탕업385825.756708180869.292985공동탕업19300111N<NA><NA><NA><NA><NA><NA>N<NA>
23목욕장업11_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 02:40:00.0공동탕업385168.082468180838.190458공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
34목욕장업11_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 02:40:00.0공동탕업385015.385179808.355521공동탕업4124000N<NA><NA><NA>임대<NA><NA>N<NA>
45목욕장업11_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)48976금강스파20211018162024U2021-10-20 02:40:00.0공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업5155110N<NA><NA><NA><NA>00Y<NA>
56목욕장업11_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 02:40:00.0공동탕업384380.762746179907.143964공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
67목욕장업11_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 02:40:00.0공동탕업385598.846694180987.169146공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
78목욕장업11_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>N<NA><NA><NA><NA><NA><NA>N<NA>
89목욕장업11_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 02:40:00.0공동탕업385201.615276181101.034719공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
910목욕장업11_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)48956신수탕20220318105444U2022-03-20 02:40:00.0공동탕업385508.413955179934.600251공동탕업0000000N<NA><NA><NA><NA>00N<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
17911792목욕장업11_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 02:40:00.0공동탕업403211.411148198587.35393공동탕업3013004Y<NA><NA><NA>자가<NA><NA>N<NA>
17921793목욕장업11_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>2Y<NA><NA><NA>임대<NA><NA>N<NA>
17931794목욕장업11_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 02:40:00.0공동탕업401671.55937196027.51628공동탕업0044006N<NA><NA><NA><NA><NA><NA>N<NA>
17941795목욕장업11_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>0N<NA><NA><NA><NA><NA><NA>N<NA>
17951796목욕장업11_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>2Y<NA><NA><NA>자가<NA><NA>N<NA>
17961797목욕장업11_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>N<NA><NA><NA><NA><NA><NA>N<NA>
17971798목욕장업11_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>N<NA><NA><NA><NA><NA><NA>N<NA>
17981799목욕장업11_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>4Y<NA><NA><NA>자가<NA><NA>N<NA>
17991800목욕장업11_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>4Y<NA><NA><NA>임대<NA><NA>N<NA>
18001801목욕장업11_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>112N<NA><NA><NA>자가<NA><NA>N<NA>