Overview

Dataset statistics

Number of variables45
Number of observations1804
Missing cells16101
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory676.6 KiB
Average record size in memory384.1 B

Variable types

Numeric11
Categorical16
Text7
DateTime4
Unsupported5
Boolean2

Dataset

Description2023-05-01
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 (51.3%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (73.4%)Imbalance
남성종사자수 is highly imbalanced (70.4%)Imbalance
다중이용업소여부 is highly imbalanced (85.0%)Imbalance
인허가취소일자 has 1804 (100.0%) missing valuesMissing
폐업일자 has 730 (40.5%) missing valuesMissing
휴업시작일자 has 1804 (100.0%) missing valuesMissing
휴업종료일자 has 1804 (100.0%) missing valuesMissing
재개업일자 has 1804 (100.0%) missing valuesMissing
소재지전화 has 155 (8.6%) missing valuesMissing
도로명전체주소 has 603 (33.4%) missing valuesMissing
도로명우편번호 has 661 (36.6%) missing valuesMissing
좌표정보(x) has 131 (7.3%) missing valuesMissing
좌표정보(y) has 131 (7.3%) missing valuesMissing
건물지상층수 has 402 (22.3%) missing valuesMissing
건물지하층수 has 627 (34.8%) missing valuesMissing
사용시작지상층 has 582 (32.3%) missing valuesMissing
사용끝지상층 has 671 (37.2%) missing valuesMissing
욕실수 has 568 (31.5%) missing valuesMissing
조건부허가신고사유 has 1803 (99.9%) missing valuesMissing
Unnamed: 44 has 1804 (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
소재지면적 has 115 (6.4%) zerosZeros
건물지상층수 has 373 (20.7%) zerosZeros
건물지하층수 has 575 (31.9%) zerosZeros
사용시작지상층 has 386 (21.4%) zerosZeros
사용끝지상층 has 270 (15.0%) zerosZeros
욕실수 has 647 (35.9%) zerosZeros

Reproduction

Analysis started2024-04-17 21:41:30.519313
Analysis finished2024-04-17 21:41:31.544799
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1804
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean902.5
Minimum1
Maximum1804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:31.598885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.15
Q1451.75
median902.5
Q31353.25
95-th percentile1713.85
Maximum1804
Range1803
Interquartile range (IQR)901.5

Descriptive statistics

Standard deviation520.91426
Coefficient of variation (CV)0.57719032
Kurtosis-1.2
Mean902.5
Median Absolute Deviation (MAD)451
Skewness0
Sum1628110
Variance271351.67
MonotonicityStrictly increasing
2024-04-18T06:41:31.711856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1242 1
 
0.1%
1212 1
 
0.1%
1211 1
 
0.1%
1210 1
 
0.1%
1209 1
 
0.1%
1208 1
 
0.1%
1207 1
 
0.1%
1206 1
 
0.1%
1205 1
 
0.1%
Other values (1794) 1794
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 (%)
1804 1
0.1%
1803 1
0.1%
1802 1
0.1%
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%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
목욕장업
1804 

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 1804
100.0%

Length

2024-04-18T06:41:31.820691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:31.898551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1804
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
11_44_01_P
1804 

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 1804
100.0%

Length

2024-04-18T06:41:31.977986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:32.077329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1804
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3323104.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:32.153466image/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 deviation40109.504
Coefficient of variation (CV)0.01206989
Kurtosis-0.9182363
Mean3323104.2
Median Absolute Deviation (MAD)30000
Skewness0.12387261
Sum5.99488 × 109
Variance1.6087723 × 109
MonotonicityNot monotonic
2024-04-18T06:41:32.249999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 223
12.4%
3340000 174
9.6%
3330000 159
8.8%
3310000 148
 
8.2%
3300000 147
 
8.1%
3370000 130
 
7.2%
3320000 125
 
6.9%
3350000 113
 
6.3%
3380000 112
 
6.2%
3270000 94
 
5.2%
Other values (6) 379
21.0%
ValueCountFrequency (%)
3250000 63
 
3.5%
3260000 74
 
4.1%
3270000 94
5.2%
3280000 72
 
4.0%
3290000 223
12.4%
3300000 147
8.1%
3310000 148
8.2%
3320000 125
6.9%
3330000 159
8.8%
3340000 174
9.6%
ValueCountFrequency (%)
3400000 46
 
2.5%
3390000 94
5.2%
3380000 112
6.2%
3370000 130
7.2%
3360000 30
 
1.7%
3350000 113
6.3%
3340000 174
9.6%
3330000 159
8.8%
3320000 125
6.9%
3310000 148
8.2%

관리번호
Text

UNIQUE 

Distinct1804
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:41:32.413657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39688
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

Unique1804 ?
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%
3320000-202-1983-01017 1
 
0.1%
3310000-202-1981-00044 1
 
0.1%
3310000-202-1981-00768 1
 
0.1%
3310000-202-1981-00836 1
 
0.1%
3310000-202-1998-00926 1
 
0.1%
3310000-202-1981-01098 1
 
0.1%
3310000-202-1997-01171 1
 
0.1%
3310000-202-1966-01168 1
 
0.1%
3310000-202-1993-01170 1
 
0.1%
Other values (1794) 1794
99.4%
2024-04-18T06:41:32.700357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15326
38.6%
2 5641
 
14.2%
- 5412
 
13.6%
3 3912
 
9.9%
1 2716
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34276
86.4%
Dash Punctuation 5412
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15326
44.7%
2 5641
 
16.5%
3 3912
 
11.4%
1 2716
 
7.9%
9 2500
 
7.3%
8 1135
 
3.3%
4 936
 
2.7%
7 832
 
2.4%
5 684
 
2.0%
6 594
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 5412
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15326
38.6%
2 5641
 
14.2%
- 5412
 
13.6%
3 3912
 
9.9%
1 2716
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15326
38.6%
2 5641
 
14.2%
- 5412
 
13.6%
3 3912
 
9.9%
1 2716
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%
Distinct1536
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum1954-01-31 00:00:00
Maximum2023-03-10 00:00:00
2024-04-18T06:41:32.870145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:41:32.981853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1804
Missing (%)100.0%
Memory size16.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
3
1074 
1
730 

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 1074
59.5%
1 730
40.5%

Length

2024-04-18T06:41:33.079691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:33.164905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1074
59.5%
1 730
40.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1074 
영업/정상
730 

Length

Max length5
Median length2
Mean length3.213969
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 1074
59.5%
영업/정상 730
40.5%

Length

2024-04-18T06:41:33.267703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:33.356567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1074
59.5%
영업/정상 730
40.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2
1074 
1
730 

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 1074
59.5%
1 730
40.5%

Length

2024-04-18T06:41:33.438545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:33.526302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1074
59.5%
1 730
40.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1074 
영업
730 

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 1074
59.5%
영업 730
40.5%

Length

2024-04-18T06:41:33.616635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:33.709631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1074
59.5%
영업 730
40.5%

폐업일자
Date

MISSING 

Distinct905
Distinct (%)84.3%
Missing730
Missing (%)40.5%
Memory size14.2 KiB
Minimum1990-10-19 00:00:00
Maximum2023-03-31 00:00:00
2024-04-18T06:41:33.814287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:41:33.940524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1804
Missing (%)100.0%
Memory size16.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1804
Missing (%)100.0%
Memory size16.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1804
Missing (%)100.0%
Memory size16.0 KiB

소재지전화
Text

MISSING 

Distinct1611
Distinct (%)97.7%
Missing155
Missing (%)8.6%
Memory size14.2 KiB
2024-04-18T06:41:34.161273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.128563
Min length7

Characters and Unicode

Total characters18351
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

Unique1574 ?
Unique (%)95.5%

Sample

1st row051 462 7616
2nd row051 4692777
3rd row051 4633803
4th row051 2472425
5th row051 2449501
ValueCountFrequency (%)
051 1595
44.8%
808 8
 
0.2%
893 7
 
0.2%
897 5
 
0.1%
261 5
 
0.1%
816 5
 
0.1%
802 5
 
0.1%
891 5
 
0.1%
070 5
 
0.1%
866 4
 
0.1%
Other values (1773) 1916
53.8%
2024-04-18T06:41:34.552437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3005
16.4%
0 2799
15.3%
1 2724
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1111
 
6.1%
7 1076
 
5.9%
8 1032
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16431
89.5%
Space Separator 1920
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3005
18.3%
0 2799
17.0%
1 2724
16.6%
2 1445
8.8%
3 1304
7.9%
6 1230
7.5%
4 1111
 
6.8%
7 1076
 
6.5%
8 1032
 
6.3%
9 705
 
4.3%
Space Separator
ValueCountFrequency (%)
1920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18351
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3005
16.4%
0 2799
15.3%
1 2724
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1111
 
6.1%
7 1076
 
5.9%
8 1032
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3005
16.4%
0 2799
15.3%
1 2724
14.8%
1920
10.5%
2 1445
7.9%
3 1304
7.1%
6 1230
6.7%
4 1111
 
6.1%
7 1076
 
5.9%
8 1032
 
5.6%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1585
Distinct (%)88.3%
Missing9
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean495.01766
Minimum0
Maximum8878.3
Zeros115
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:34.679097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1237.42
median348
Q3534.84
95-th percentile1379.055
Maximum8878.3
Range8878.3
Interquartile range (IQR)297.42

Descriptive statistics

Standard deviation593.88622
Coefficient of variation (CV)1.1997273
Kurtosis49.995679
Mean495.01766
Median Absolute Deviation (MAD)137.04
Skewness5.5885948
Sum888556.7
Variance352700.84
MonotonicityNot monotonic
2024-04-18T06:41:34.802109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 115
 
6.4%
330.0 5
 
0.3%
798.24 3
 
0.2%
252.17 3
 
0.2%
426.0 3
 
0.2%
506.24 3
 
0.2%
93.73 3
 
0.2%
478.0 3
 
0.2%
427.44 3
 
0.2%
348.0 3
 
0.2%
Other values (1575) 1651
91.5%
(Missing) 9
 
0.5%
ValueCountFrequency (%)
0.0 115
6.4%
16.65 1
 
0.1%
38.67 1
 
0.1%
60.9 1
 
0.1%
60.99 1
 
0.1%
66.0 1
 
0.1%
66.7 1
 
0.1%
72.39 1
 
0.1%
74.24 1
 
0.1%
80.99 1
 
0.1%
ValueCountFrequency (%)
8878.3 1
0.1%
7380.0 1
0.1%
6261.31 1
0.1%
6160.67 1
0.1%
4941.04 1
0.1%
4669.74 1
0.1%
4518.62 1
0.1%
4351.55 1
0.1%
3776.66 1
0.1%
3675.8 1
0.1%
Distinct631
Distinct (%)35.1%
Missing6
Missing (%)0.3%
Memory size14.2 KiB
2024-04-18T06:41:35.097938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters12586
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

Unique195 ?
Unique (%)10.8%

Sample

1st row600-800
2nd row600-816
3rd row600-110
4th row600-062
5th row600-808
ValueCountFrequency (%)
604-851 15
 
0.8%
612-846 12
 
0.7%
612-847 12
 
0.7%
608-808 11
 
0.6%
608-828 11
 
0.6%
614-822 10
 
0.6%
613-832 9
 
0.5%
613-805 9
 
0.5%
607-826 9
 
0.5%
607-833 9
 
0.5%
Other values (621) 1691
94.0%
2024-04-18T06:41:35.494091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2204
17.5%
8 1949
15.5%
- 1798
14.3%
0 1749
13.9%
1 1723
13.7%
2 837
 
6.7%
4 730
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10788
85.7%
Dash Punctuation 1798
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2204
20.4%
8 1949
18.1%
0 1749
16.2%
1 1723
16.0%
2 837
 
7.8%
4 730
 
6.8%
3 571
 
5.3%
7 441
 
4.1%
9 322
 
3.0%
5 262
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12586
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2204
17.5%
8 1949
15.5%
- 1798
14.3%
0 1749
13.9%
1 1723
13.7%
2 837
 
6.7%
4 730
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2204
17.5%
8 1949
15.5%
- 1798
14.3%
0 1749
13.9%
1 1723
13.7%
2 837
 
6.7%
4 730
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%
Distinct1748
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:41:35.816206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length23.166297
Min length16

Characters and Unicode

Total characters41792
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

Unique1698 ?
Unique (%)94.1%

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 1804
 
22.4%
t통b반 334
 
4.1%
부산진구 223
 
2.8%
사하구 174
 
2.2%
해운대구 159
 
2.0%
남구 148
 
1.8%
동래구 147
 
1.8%
연제구 130
 
1.6%
북구 125
 
1.6%
금정구 113
 
1.4%
Other values (2202) 4694
58.3%
2024-04-18T06:41:36.294467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6248
 
15.0%
2156
 
5.2%
2147
 
5.1%
2086
 
5.0%
1 1900
 
4.5%
1875
 
4.5%
1825
 
4.4%
1816
 
4.3%
1808
 
4.3%
- 1677
 
4.0%
Other values (268) 18254
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24175
57.8%
Decimal Number 8765
 
21.0%
Space Separator 6248
 
15.0%
Dash Punctuation 1677
 
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 (%)
2156
 
8.9%
2147
 
8.9%
2086
 
8.6%
1875
 
7.8%
1825
 
7.5%
1816
 
7.5%
1808
 
7.5%
1267
 
5.2%
1197
 
5.0%
385
 
1.6%
Other values (242) 7613
31.5%
Decimal Number
ValueCountFrequency (%)
1 1900
21.7%
2 1134
12.9%
3 992
11.3%
4 881
10.1%
5 779
8.9%
6 676
 
7.7%
7 647
 
7.4%
0 609
 
6.9%
8 608
 
6.9%
9 539
 
6.1%
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 (%)
6248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1677
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 24175
57.8%
Common 16933
40.5%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2156
 
8.9%
2147
 
8.9%
2086
 
8.6%
1875
 
7.8%
1825
 
7.5%
1816
 
7.5%
1808
 
7.5%
1267
 
5.2%
1197
 
5.0%
385
 
1.6%
Other values (242) 7613
31.5%
Common
ValueCountFrequency (%)
6248
36.9%
1 1900
 
11.2%
- 1677
 
9.9%
2 1134
 
6.7%
3 992
 
5.9%
4 881
 
5.2%
5 779
 
4.6%
6 676
 
4.0%
7 647
 
3.8%
0 609
 
3.6%
Other values (8) 1390
 
8.2%
Latin
ValueCountFrequency (%)
B 342
50.0%
T 334
48.8%
W 2
 
0.3%
A 2
 
0.3%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24175
57.8%
ASCII 17616
42.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6248
35.5%
1 1900
 
10.8%
- 1677
 
9.5%
2 1134
 
6.4%
3 992
 
5.6%
4 881
 
5.0%
5 779
 
4.4%
6 676
 
3.8%
7 647
 
3.7%
0 609
 
3.5%
Other values (15) 2073
 
11.8%
Hangul
ValueCountFrequency (%)
2156
 
8.9%
2147
 
8.9%
2086
 
8.6%
1875
 
7.8%
1825
 
7.5%
1816
 
7.5%
1808
 
7.5%
1267
 
5.2%
1197
 
5.0%
385
 
1.6%
Other values (242) 7613
31.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1188
Distinct (%)98.9%
Missing603
Missing (%)33.4%
Memory size14.2 KiB
2024-04-18T06:41:36.625071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.594505
Min length20

Characters and Unicode

Total characters33141
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

Unique1175 ?
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 1201
 
19.0%
부산진구 155
 
2.5%
남구 104
 
1.6%
사하구 103
 
1.6%
해운대구 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 (1737) 4243
67.2%
2024-04-18T06:41:37.080905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5113
 
15.4%
1521
 
4.6%
1456
 
4.4%
1456
 
4.4%
1269
 
3.8%
1258
 
3.8%
1231
 
3.7%
1206
 
3.6%
) 1186
 
3.6%
( 1186
 
3.6%
Other values (327) 16259
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19942
60.2%
Decimal Number 5118
 
15.4%
Space Separator 5113
 
15.4%
Close Punctuation 1187
 
3.6%
Open Punctuation 1187
 
3.6%
Other Punctuation 362
 
1.1%
Dash Punctuation 203
 
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 (%)
1521
 
7.6%
1456
 
7.3%
1456
 
7.3%
1269
 
6.4%
1258
 
6.3%
1231
 
6.2%
1206
 
6.0%
1144
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8019
40.2%
Decimal Number
ValueCountFrequency (%)
1 1157
22.6%
2 722
14.1%
3 639
12.5%
5 451
 
8.8%
4 442
 
8.6%
6 391
 
7.6%
0 384
 
7.5%
7 355
 
6.9%
9 292
 
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 (%)
, 357
98.6%
. 3
 
0.8%
@ 1
 
0.3%
* 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1186
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1186
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19942
60.2%
Common 13183
39.8%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1521
 
7.6%
1456
 
7.3%
1456
 
7.3%
1269
 
6.4%
1258
 
6.3%
1231
 
6.2%
1206
 
6.0%
1144
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8019
40.2%
Common
ValueCountFrequency (%)
5113
38.8%
) 1186
 
9.0%
( 1186
 
9.0%
1 1157
 
8.8%
2 722
 
5.5%
3 639
 
4.8%
5 451
 
3.4%
4 442
 
3.4%
6 391
 
3.0%
0 384
 
2.9%
Other values (12) 1512
 
11.5%
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 19942
60.2%
ASCII 13197
39.8%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5113
38.7%
) 1186
 
9.0%
( 1186
 
9.0%
1 1157
 
8.8%
2 722
 
5.5%
3 639
 
4.8%
5 451
 
3.4%
4 442
 
3.3%
6 391
 
3.0%
0 384
 
2.9%
Other values (16) 1526
 
11.6%
Hangul
ValueCountFrequency (%)
1521
 
7.6%
1456
 
7.3%
1456
 
7.3%
1269
 
6.4%
1258
 
6.3%
1231
 
6.2%
1206
 
6.0%
1144
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8019
40.2%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct876
Distinct (%)76.6%
Missing661
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean47881.835
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:37.205043image/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 deviation983.94488
Coefficient of variation (CV)0.02054944
Kurtosis-1.0507204
Mean47881.835
Median Absolute Deviation (MAD)760
Skewness-0.081425996
Sum54728937
Variance968147.53
MonotonicityNot monotonic
2024-04-18T06:41:37.335493image/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%
47712 4
 
0.2%
48052 4
 
0.2%
46308 4
 
0.2%
48053 4
 
0.2%
47142 4
 
0.2%
48095 4
 
0.2%
Other values (866) 1092
60.5%
(Missing) 661
36.6%
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 (%)63.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:41:37.613393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1491131
Min length2

Characters and Unicode

Total characters7485
Distinct characters389
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

Unique898 ?
Unique (%)49.8%

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%
약수탕 13
 
0.7%
제일탕 13
 
0.7%
Other values (1197) 1796
91.3%
2024-04-18T06:41:37.999998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1357
 
18.1%
299
 
4.0%
221
 
3.0%
181
 
2.4%
179
 
2.4%
168
 
2.2%
163
 
2.2%
159
 
2.1%
122
 
1.6%
117
 
1.6%
Other values (379) 4519
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7205
96.3%
Space Separator 163
 
2.2%
Close Punctuation 38
 
0.5%
Open Punctuation 35
 
0.5%
Decimal Number 18
 
0.2%
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
 
18.8%
299
 
4.1%
221
 
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 (357) 4287
59.5%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
O 2
13.3%
W 2
13.3%
L 2
13.3%
S 1
 
6.7%
F 1
 
6.7%
J 1
 
6.7%
M 1
 
6.7%
B 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
n 2
28.6%
o 2
28.6%
d 1
14.3%
u 1
14.3%
r 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 10
55.6%
4 8
44.4%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
163
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 7204
96.2%
Common 258
 
3.4%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1357
 
18.8%
299
 
4.2%
221
 
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 (356) 4286
59.5%
Latin
ValueCountFrequency (%)
G 4
18.2%
O 2
9.1%
W 2
9.1%
n 2
9.1%
o 2
9.1%
L 2
9.1%
S 1
 
4.5%
F 1
 
4.5%
d 1
 
4.5%
u 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
163
63.2%
) 38
 
14.7%
( 35
 
13.6%
2 10
 
3.9%
4 8
 
3.1%
- 2
 
0.8%
. 1
 
0.4%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7204
96.2%
ASCII 280
 
3.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1357
 
18.8%
299
 
4.2%
221
 
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 (356) 4286
59.5%
ASCII
ValueCountFrequency (%)
163
58.2%
) 38
 
13.6%
( 35
 
12.5%
2 10
 
3.6%
4 8
 
2.9%
G 4
 
1.4%
- 2
 
0.7%
O 2
 
0.7%
W 2
 
0.7%
n 2
 
0.7%
Other values (12) 14
 
5.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1529
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum1999-02-10 00:00:00
Maximum2023-03-31 15:30:29
2024-04-18T06:41:38.124608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:41:38.243496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
I
1051 
U
753 

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 1051
58.3%
U 753
41.7%

Length

2024-04-18T06:41:38.356493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:38.442908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1051
58.3%
u 753
41.7%
Distinct378
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-04-02 02:40:00
2024-04-18T06:41:38.532155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:41:38.644357image/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
1525 
목욕장업 기타
158 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7200665
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1525
84.5%
목욕장업 기타 158
 
8.8%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:41:38.755522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:38.841459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1525
77.7%
목욕장업 158
 
8.1%
기타 158
 
8.1%
공동탕업+찜질시설서비스영업 77
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct1509
Distinct (%)90.2%
Missing131
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean387820.61
Minimum366820.79
Maximum407878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:39.362044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379626.38
Q1384037.96
median388137.12
Q3391162.17
95-th percentile397006.31
Maximum407878
Range41057.216
Interquartile range (IQR)7124.2005

Descriptive statistics

Standard deviation5326.8937
Coefficient of variation (CV)0.013735458
Kurtosis0.67418648
Mean387820.61
Median Absolute Deviation (MAD)3576.3509
Skewness0.27922404
Sum6.4882388 × 108
Variance28375796
MonotonicityNot monotonic
2024-04-18T06:41:39.469037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
386026.75739607 4
 
0.2%
391834.082986499 4
 
0.2%
388552.977112094 3
 
0.2%
379052.480675244 3
 
0.2%
390285.068808765 3
 
0.2%
391103.422349355 3
 
0.2%
383300.306176121 3
 
0.2%
389680.677797295 3
 
0.2%
386428.823034759 3
 
0.2%
383091.957810087 3
 
0.2%
Other values (1499) 1641
91.0%
(Missing) 131
 
7.3%
ValueCountFrequency (%)
366820.787750492 1
0.1%
370718.68095413 1
0.1%
372902.666793487 1
0.1%
373056.591154247 1
0.1%
373088.08750839 2
0.1%
373178.636649203 1
0.1%
373368.868121567 1
0.1%
373512.891351707 2
0.1%
374901.846816856 2
0.1%
375279.393220432 1
0.1%
ValueCountFrequency (%)
407878.004041358 1
0.1%
407739.061113608 1
0.1%
407413.973711585 1
0.1%
407195.384771566 1
0.1%
406981.949996683 1
0.1%
405347.006280193 1
0.1%
405172.859382016 1
0.1%
404770.45246328 1
0.1%
404674.707509308 1
0.1%
403841.725234449 1
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct1509
Distinct (%)90.2%
Missing131
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean186601.47
Minimum173914.72
Maximum207205.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:39.606656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177840.87
Q1182195.57
median186776.49
Q3190600.22
95-th percentile195665.58
Maximum207205.27
Range33290.55
Interquartile range (IQR)8404.6466

Descriptive statistics

Standard deviation5652.5359
Coefficient of variation (CV)0.030292022
Kurtosis0.05102056
Mean186601.47
Median Absolute Deviation (MAD)4100.9049
Skewness0.26000812
Sum3.1218426 × 108
Variance31951162
MonotonicityNot monotonic
2024-04-18T06:41:39.762382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181580.381775088 4
 
0.2%
189185.417047275 4
 
0.2%
184433.515092005 3
 
0.2%
181034.181864204 3
 
0.2%
184019.031918217 3
 
0.2%
182446.170472991 3
 
0.2%
193948.527977305 3
 
0.2%
182339.017460953 3
 
0.2%
189577.746954425 3
 
0.2%
179227.873327685 3
 
0.2%
Other values (1499) 1641
91.0%
(Missing) 131
 
7.3%
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%
174676.412428457 1
 
0.1%
174765.307900471 1
 
0.1%
174811.513941025 1
 
0.1%
174885.756922702 2
0.1%
ValueCountFrequency (%)
207205.267789628 1
0.1%
207141.913579437 1
0.1%
206164.575140106 1
0.1%
205671.36699064 1
0.1%
205652.48759924 1
0.1%
205455.065758112 1
0.1%
205405.417865169 1
0.1%
205366.743408054 1
0.1%
205061.201316499 1
0.1%
204747.884437376 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
공동탕업
1525 
목욕장업 기타
158 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.7200665
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1525
84.5%
목욕장업 기타 158
 
8.8%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:41:39.898338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:39.992313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1525
77.7%
목욕장업 158
 
8.1%
기타 158
 
8.1%
공동탕업+찜질시설서비스영업 77
 
3.9%
한증막업 33
 
1.7%
찜질시설서비스영업 11
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)2.4%
Missing402
Missing (%)22.3%
Infinite0
Infinite (%)0.0%
Mean3.6990014
Minimum0
Maximum42
Zeros373
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:40.093299image/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 deviation4.4310064
Coefficient of variation (CV)1.1978926
Kurtosis16.266173
Mean3.6990014
Median Absolute Deviation (MAD)2
Skewness3.3008612
Sum5186
Variance19.633818
MonotonicityNot monotonic
2024-04-18T06:41:40.200712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 373
20.7%
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) 85
 
4.7%
(Missing) 402
22.3%
ValueCountFrequency (%)
0 373
20.7%
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%
Missing627
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean0.74681393
Minimum0
Maximum7
Zeros575
Zeros (%)31.9%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:40.292026image/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 deviation1.0402407
Coefficient of variation (CV)1.3929048
Kurtosis8.0055642
Mean0.74681393
Median Absolute Deviation (MAD)1
Skewness2.4318242
Sum879
Variance1.0821008
MonotonicityNot monotonic
2024-04-18T06:41:40.387218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 575
31.9%
1 459
25.4%
2 78
 
4.3%
3 28
 
1.6%
4 17
 
0.9%
6 10
 
0.6%
5 9
 
0.5%
7 1
 
0.1%
(Missing) 627
34.8%
ValueCountFrequency (%)
0 575
31.9%
1 459
25.4%
2 78
 
4.3%
3 28
 
1.6%
4 17
 
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 17
 
0.9%
3 28
 
1.6%
2 78
 
4.3%
1 459
25.4%
0 575
31.9%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing582
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean1.3379705
Minimum0
Maximum10
Zeros386
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:40.481458image/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 deviation1.4094039
Coefficient of variation (CV)1.0533894
Kurtosis5.5866623
Mean1.3379705
Median Absolute Deviation (MAD)1
Skewness1.8268481
Sum1635
Variance1.9864195
MonotonicityNot monotonic
2024-04-18T06:41:40.567911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 386
21.4%
1 374
20.7%
2 300
16.6%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 14
 
0.8%
8 4
 
0.2%
10 3
 
0.2%
7 2
 
0.1%
(Missing) 582
32.3%
ValueCountFrequency (%)
0 386
21.4%
1 374
20.7%
2 300
16.6%
3 76
 
4.2%
4 42
 
2.3%
5 21
 
1.2%
6 14
 
0.8%
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 14
 
0.8%
5 21
 
1.2%
4 42
 
2.3%
3 76
 
4.2%
2 300
16.6%
1 374
20.7%
0 386
21.4%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing671
Missing (%)37.2%
Infinite0
Infinite (%)0.0%
Mean2.1147396
Minimum0
Maximum11
Zeros270
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:40.653601image/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 deviation1.7551247
Coefficient of variation (CV)0.82994837
Kurtosis2.4575853
Mean2.1147396
Median Absolute Deviation (MAD)1
Skewness1.1179326
Sum2396
Variance3.0804628
MonotonicityNot monotonic
2024-04-18T06:41:40.746971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 382
21.2%
0 270
15.0%
3 211
 
11.7%
1 93
 
5.2%
4 82
 
4.5%
5 48
 
2.7%
6 21
 
1.2%
7 11
 
0.6%
9 6
 
0.3%
8 5
 
0.3%
Other values (2) 4
 
0.2%
(Missing) 671
37.2%
ValueCountFrequency (%)
0 270
15.0%
1 93
 
5.2%
2 382
21.2%
3 211
11.7%
4 82
 
4.5%
5 48
 
2.7%
6 21
 
1.2%
7 11
 
0.6%
8 5
 
0.3%
9 6
 
0.3%
ValueCountFrequency (%)
11 1
 
0.1%
10 3
 
0.2%
9 6
 
0.3%
8 5
 
0.3%
7 11
 
0.6%
6 21
 
1.2%
5 48
 
2.7%
4 82
 
4.5%
3 211
11.7%
2 382
21.2%
Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
0
858 
<NA>
853 
1
 
81
2
 
9
3
 
3

Length

Max length4
Median length1
Mean length2.4185144
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 858
47.6%
<NA> 853
47.3%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:41:40.852201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:40.947868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 858
47.6%
na 853
47.3%
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>
1055 
0
655 
1
 
69
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.7544346
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1055
58.5%
0 655
36.3%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:41:41.042783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:41.139469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1055
58.5%
0 655
36.3%
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%
Missing568
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean1.3050162
Minimum0
Maximum26
Zeros647
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:41:41.239804image/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 deviation2.13966
Coefficient of variation (CV)1.6395659
Kurtosis31.650525
Mean1.3050162
Median Absolute Deviation (MAD)0
Skewness4.3425965
Sum1613
Variance4.5781449
MonotonicityNot monotonic
2024-04-18T06:41:41.339414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 647
35.9%
2 477
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) 568
31.5%
ValueCountFrequency (%)
0 647
35.9%
1 19
 
1.1%
2 477
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 size3.7 KiB
False
1344 
True
458 
(Missing)
 
2
ValueCountFrequency (%)
False 1344
74.5%
True 458
 
25.4%
(Missing) 2
 
0.1%
2024-04-18T06:41:41.433963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1803
Missing (%)99.9%
Memory size14.2 KiB
2024-04-18T06:41:41.567235image/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%
2024-04-18T06:41:41.825221image/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>
1803 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022173
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> 1803
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:41:41.966467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:42.064342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1803
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1803 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022173
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> 1803
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:41:42.162133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:42.257272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1803
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1402 
자가
274 
임대
 
128

Length

Max length4
Median length4
Mean length3.5543237
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> 1402
77.7%
자가 274
 
15.2%
임대 128
 
7.1%

Length

2024-04-18T06:41:42.351009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:42.439934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1402
77.7%
자가 274
 
15.2%
임대 128
 
7.1%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1494 
0
305 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.4844789
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> 1494
82.8%
0 305
 
16.9%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:41:42.531375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:42.648659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1494
82.8%
0 305
 
16.9%
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>
1494 
0
305 
1
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.4844789
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> 1494
82.8%
0 305
 
16.9%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:41:42.766268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:41:42.866417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1494
82.8%
0 305
 
16.9%
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
1765 
True
 
39
ValueCountFrequency (%)
False 1765
97.8%
True 39
 
2.2%
2024-04-18T06:41:42.952802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 44
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1804
Missing (%)100.0%
Memory size16.0 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
01목욕장업11_44_01_P32500003250000-202-2022-000012022-03-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 462 7616354.91600-800부산광역시 중구 대청동4가 24-1부산광역시 중구 대청북길 44, 1-3층 (대청동4가)48971대청행복탕2022-04-18 15:03:47U2022-04-20 02:40:00공동탕업385153.11515180500.97525공동탕업4113002Y<NA><NA><NA>임대00N<NA>
12목욕장업11_44_01_P32500003250000-202-2005-000012005-02-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 4692777462.0600-816부산광역시 중구 중앙동4가 79-1 마린센터(지하1층)부산광역시 중구 충장대로9번길 52, 지하1층 (중앙동4가, 마린센터)48936마린목욕탕2020-12-04 17:43:58U2020-12-06 02:40:00공동탕업385825.756708180869.292985공동탕업19300111N<NA><NA><NA><NA><NA><NA>N<NA>
23목욕장업11_44_01_P32500003250000-202-1984-001521984-02-17<NA>1영업/정상1영업<NA><NA><NA><NA>051 4633803405.0600-110부산광역시 중구 영주동 292-10부산광역시 중구 영주로 20 (영주동)48916거북탕2020-12-04 17:39:20U2020-12-06 02:40:00공동탕업385168.082468180838.190458공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
34목욕장업11_44_01_P32500003250000-202-1988-001591988-09-13<NA>1영업/정상1영업<NA><NA><NA><NA>051 2472425338.97600-062부산광역시 중구 신창동2가 21-2부산광역시 중구 광복로43번길 12 (신창동2가)48947녹수탕2020-12-04 17:40:55U2020-12-06 02:40:00공동탕업385015.385179808.355521공동탕업4124000N<NA><NA><NA>임대<NA><NA>N<NA>
45목욕장업11_44_01_P32500003250000-202-1960-001441960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 24495011416.48600-808부산광역시 중구 부평동3가 22-1 외 2필지부산광역시 중구 흑교로31번길 3-1 (부평동3가, 외 2필지)48976금강스파2021-10-18 16:20:24U2021-10-20 02:40:00공동탕업+찜질시설서비스영업384542.121202179994.202104공동탕업+찜질시설서비스영업5155110N<NA><NA><NA><NA>00Y<NA>
56목욕장업11_44_01_P32500003250000-202-1960-001461960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 2443396517.0600-074부산광역시 중구 부평동4가 28-3부산광역시 중구 흑교로21번길 21 (부평동4가)48974부천탕2021-01-14 13:35:18U2021-01-16 02:40:00공동탕업384380.762746179907.143964공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
67목욕장업11_44_01_P32500003250000-202-1982-001511982-11-12<NA>1영업/정상1영업<NA><NA><NA><NA>051 469 3202232.0600-811부산광역시 중구 영주동 636-2부산광역시 중구 중구로188번길 21 (영주동)48922청호탕2020-08-14 13:34:34U2020-08-16 02:40:00공동탕업385598.846694180987.169146공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
78목욕장업11_44_01_P32500003250000-202-1969-000011969-12-01<NA>1영업/정상1영업<NA><NA><NA><NA>051 2451969233.0600-806부산광역시 중구 부평동2가 68-6부산광역시 중구 중구로33번길 44 (부평동2가)48977청수탕2021-01-18 09:43:52U2021-01-20 02:40:00공동탕업384626.918928179878.92302공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
89목욕장업11_44_01_P32500003250000-202-1970-000041970-12-28<NA>1영업/정상1영업<NA><NA><NA><NA>051 4698444156.0600-110부산광역시 중구 영주동 277-16부산광역시 중구 동영로 77-1 (영주동)48915영주탕2020-12-04 17:37:03U2020-12-06 02:40:00공동탕업385201.615276181101.034719공동탕업0000000N<NA><NA><NA><NA><NA><NA>N<NA>
910목욕장업11_44_01_P32500003250000-202-1960-001471960-12-10<NA>1영업/정상1영업<NA><NA><NA><NA>051 231 4848337.0600-012부산광역시 중구 중앙동2가 21-1 , 6, 8부산광역시 중구 대청로138번길 15-1 (중앙동2가, 21-1, 6, 8)48956신수탕2022-03-18 10:54:44U2022-03-20 02:40:00공동탕업385508.413955179934.600251공동탕업0000000N<NA><NA><NA><NA>00N<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부Unnamed: 44
17941795목욕장업11_44_01_P34000003400000-202-1984-003361984-03-05<NA>3폐업2폐업2020-07-10<NA><NA><NA>051 7215512722.19619-912부산광역시 기장군 일광면 삼성리 33-6부산광역시 기장군 일광면 삼성3길 55-146044명성탕2020-07-10 15:41:25U2020-07-12 02:40:00공동탕업403211.411795198587.35366공동탕업3013004Y<NA><NA><NA>자가<NA><NA>N<NA>
17951796목욕장업11_44_01_P34000003400000-202-1998-000881998-08-19<NA>3폐업2폐업2009-07-24<NA><NA><NA>051 7210905550.19619-904부산광역시 기장군 기장읍 대변리 423번지<NA><NA>대변항해수탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업402751.009587194137.606353공동탕업3<NA>33<NA><NA>2Y<NA><NA><NA>임대<NA><NA>N<NA>
17961797목욕장업11_44_01_P34000003400000-202-2009-000012009-10-27<NA>3폐업2폐업2019-07-18<NA><NA><NA>051 723 20931500.0619-903부산광역시 기장군 기장읍 대라리 57번지부산광역시 기장군 기장읍 차성동로 6346066석천탕2019-07-18 17:30:53U2019-07-20 02:40:00공동탕업401671.555424196027.510818공동탕업0044006N<NA><NA><NA><NA><NA><NA>N<NA>
17971798목욕장업11_44_01_P34000003400000-202-1984-003371984-09-22<NA>3폐업2폐업2004-11-24<NA><NA><NA>051 72145120.0619-913부산광역시 기장군 일광면 이천리 908번지<NA><NA>일광탕2002-06-21 00:00:00I2018-08-31 23:59:59공동탕업<NA><NA>공동탕업000<NA>0<NA>0N<NA><NA><NA><NA><NA><NA>N<NA>
17981799목욕장업11_44_01_P34000003400000-202-1991-000841991-11-26<NA>3폐업2폐업2009-08-17<NA><NA><NA>051 7220680322.38619-905부산광역시 기장군 기장읍 동부리 152-8번지 6B 8-1L<NA><NA>제일탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업401672.155429196524.791525공동탕업3<NA>12<NA><NA>2Y<NA><NA><NA>자가<NA><NA>N<NA>
17991800목욕장업11_44_01_P34000003400000-202-1994-004071994-09-16<NA>3폐업2폐업2006-11-07<NA><NA><NA>051 7273302395.22619-911부산광역시 기장군 일광면 칠암리 158-5번지<NA><NA>풍년탕2003-12-19 00:00:00I2018-08-31 23:59:59공동탕업405347.00628202354.026519공동탕업1<NA>11<NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
18001801목욕장업11_44_01_P34000003400000-202-1994-004081994-11-25<NA>3폐업2폐업2009-07-31<NA><NA><NA>051 7211997183.56619-872부산광역시 기장군 철마면 장전리 366번지<NA><NA>철마목욕탕2003-08-20 00:00:00I2018-08-31 23:59:59공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N<NA>
18011802목욕장업11_44_01_P34000003400000-202-1992-000841992-02-10<NA>3폐업2폐업2007-08-29<NA><NA><NA>051 7221054609.82619-906부산광역시 기장군 기장읍 청강리 226-7번지<NA><NA>보광탕2007-08-14 16:17:09I2018-08-31 23:59:59공동탕업401913.048724195119.251102공동탕업4<NA>12<NA><NA>4Y<NA><NA><NA>자가<NA><NA>N<NA>
18021803목욕장업11_44_01_P34000003400000-202-2000-000912000-03-30<NA>3폐업2폐업2016-11-29<NA><NA><NA>051 7222537384.0619-901부산광역시 기장군 기장읍 교리 352-8번지부산광역시 기장군 기장읍 차성동로 164-1546055교리탕2016-11-30 11:45:19I2018-08-31 23:59:59공동탕업401804.177755197042.680998공동탕업3<NA>12<NA><NA>4Y<NA><NA><NA>임대<NA><NA>N<NA>
18031804목욕장업11_44_01_P34000003400000-202-2003-000022003-10-29<NA>3폐업2폐업2012-12-20<NA><NA><NA>051 7243994348.16619-905부산광역시 기장군 기장읍 서부리 422번지부산광역시 기장군 기장읍 반송로 154546058에쿠스목욕장2004-05-31 00:00:00I2018-08-31 23:59:59공동탕업401037.499103196702.552856공동탕업52<NA><NA>112N<NA><NA><NA>자가<NA><NA>N<NA>