Overview

Dataset statistics

Number of variables45
Number of observations1803
Missing cells16100
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory676.3 KiB
Average record size in memory384.1 B

Variable types

Numeric11
Categorical16
Text7
DateTime4
Unsupported5
Boolean2

Dataset

Description2023-04-01
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 (51.4%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
여성종사자수 is highly imbalanced (73.8%)Imbalance
남성종사자수 is highly imbalanced (70.9%)Imbalance
다중이용업소여부 is highly imbalanced (84.9%)Imbalance
인허가취소일자 has 1803 (100.0%) missing valuesMissing
폐업일자 has 731 (40.5%) missing valuesMissing
휴업시작일자 has 1803 (100.0%) missing valuesMissing
휴업종료일자 has 1803 (100.0%) missing valuesMissing
재개업일자 has 1803 (100.0%) missing valuesMissing
소재지전화 has 154 (8.5%) missing valuesMissing
도로명전체주소 has 603 (33.4%) missing valuesMissing
도로명우편번호 has 661 (36.7%) missing valuesMissing
좌표정보(x) has 131 (7.3%) missing valuesMissing
좌표정보(y) has 131 (7.3%) missing valuesMissing
건물지상층수 has 403 (22.4%) missing valuesMissing
건물지하층수 has 628 (34.8%) missing valuesMissing
사용시작지상층 has 584 (32.4%) missing valuesMissing
사용끝지상층 has 672 (37.3%) missing valuesMissing
욕실수 has 568 (31.5%) missing valuesMissing
조건부허가신고사유 has 1802 (99.9%) missing valuesMissing
Unnamed: 44 has 1803 (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 371 (20.6%) zerosZeros
건물지하층수 has 573 (31.8%) zerosZeros
사용시작지상층 has 383 (21.2%) zerosZeros
사용끝지상층 has 268 (14.9%) zerosZeros
욕실수 has 646 (35.8%) zerosZeros

Reproduction

Analysis started2024-04-17 21:44:41.144279
Analysis finished2024-04-17 21:44:42.088591
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean902
Minimum1
Maximum1803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:42.148469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile91.1
Q1451.5
median902
Q31352.5
95-th percentile1712.9
Maximum1803
Range1802
Interquartile range (IQR)901

Descriptive statistics

Standard deviation520.62559
Coefficient of variation (CV)0.57719023
Kurtosis-1.2
Mean902
Median Absolute Deviation (MAD)451
Skewness0
Sum1626306
Variance271051
MonotonicityStrictly increasing
2024-04-18T06:44:42.273072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1241 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%
1204 1
 
0.1%
Other values (1793) 1793
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 (%)
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%
1794 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
목욕장업
1803 

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 1803
100.0%

Length

2024-04-18T06:44:42.402125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:42.485437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 1803
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
11_44_01_P
1803 

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 1803
100.0%

Length

2024-04-18T06:44:42.568276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:42.659321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 1803
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3323083.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:42.748548image/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 deviation40111.21
Coefficient of variation (CV)0.012070478
Kurtosis-0.91757699
Mean3323083.7
Median Absolute Deviation (MAD)30000
Skewness0.12502545
Sum5.99152 × 109
Variance1.6089092 × 109
MonotonicityNot monotonic
2024-04-18T06:44:42.858580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 223
12.4%
3340000 174
9.7%
3330000 159
8.8%
3310000 148
 
8.2%
3300000 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 223
12.4%
3300000 147
8.2%
3310000 148
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 148
8.2%

관리번호
Text

UNIQUE 

Distinct1803
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:44:43.021417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters39666
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

Unique1803 ?
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%
3320000-202-1983-01178 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%
3310000-202-1993-01171 1
 
0.1%
Other values (1793) 1793
99.4%
2024-04-18T06:44:43.290614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15316
38.6%
2 5637
 
14.2%
- 5409
 
13.6%
3 3909
 
9.9%
1 2715
 
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 34257
86.4%
Dash Punctuation 5409
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15316
44.7%
2 5637
 
16.5%
3 3909
 
11.4%
1 2715
 
7.9%
9 2500
 
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 (%)
- 5409
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15316
38.6%
2 5637
 
14.2%
- 5409
 
13.6%
3 3909
 
9.9%
1 2715
 
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 39666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15316
38.6%
2 5637
 
14.2%
- 5409
 
13.6%
3 3909
 
9.9%
1 2715
 
6.8%
9 2500
 
6.3%
8 1135
 
2.9%
4 936
 
2.4%
7 832
 
2.1%
5 684
 
1.7%
Distinct1535
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum1954-01-31 00:00:00
Maximum2023-02-20 00:00:00
2024-04-18T06:44:43.434005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:44:43.548127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1803
Missing (%)100.0%
Memory size16.0 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
3
1072 
1
731 

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 1072
59.5%
1 731
40.5%

Length

2024-04-18T06:44:43.678566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:43.761607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1072
59.5%
1 731
40.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1072 
영업/정상
731 

Length

Max length5
Median length2
Mean length3.2163062
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 1072
59.5%
영업/정상 731
40.5%

Length

2024-04-18T06:44:43.844985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:43.923633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1072
59.5%
영업/정상 731
40.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2
1072 
1
731 

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 1072
59.5%
1 731
40.5%

Length

2024-04-18T06:44:44.007172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:44.084125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1072
59.5%
1 731
40.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
폐업
1072 
영업
731 

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 1072
59.5%
영업 731
40.5%

Length

2024-04-18T06:44:44.183363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:44.280339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1072
59.5%
영업 731
40.5%

폐업일자
Date

MISSING 

Distinct903
Distinct (%)84.2%
Missing731
Missing (%)40.5%
Memory size14.2 KiB
Minimum1990-10-19 00:00:00
Maximum2023-02-27 00:00:00
2024-04-18T06:44:44.380797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:44:44.485228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1803
Missing (%)100.0%
Memory size16.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1803
Missing (%)100.0%
Memory size16.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1803
Missing (%)100.0%
Memory size16.0 KiB

소재지전화
Text

MISSING 

Distinct1611
Distinct (%)97.7%
Missing154
Missing (%)8.5%
Memory size14.2 KiB
2024-04-18T06:44:44.707418image/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%
261 5
 
0.1%
070 5
 
0.1%
802 5
 
0.1%
897 5
 
0.1%
816 5
 
0.1%
891 5
 
0.1%
646 4
 
0.1%
Other values (1773) 1916
53.8%
2024-04-18T06:44:45.072387image/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 (%)88.4%
Missing9
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean494.8371
Minimum0
Maximum8878.3
Zeros115
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:45.202298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1237.42
median347.81
Q3531.945
95-th percentile1379.1625
Maximum8878.3
Range8878.3
Interquartile range (IQR)294.525

Descriptive statistics

Standard deviation594.00253
Coefficient of variation (CV)1.2004001
Kurtosis49.990575
Mean494.8371
Median Absolute Deviation (MAD)137
Skewness5.5892537
Sum887737.76
Variance352839
MonotonicityNot monotonic
2024-04-18T06:44:45.319182image/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%
478.0 3
 
0.2%
93.73 3
 
0.2%
426.0 3
 
0.2%
798.24 3
 
0.2%
427.44 3
 
0.2%
506.24 3
 
0.2%
252.17 3
 
0.2%
348.0 3
 
0.2%
Other values (1575) 1650
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
2024-04-18T06:44:45.617149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters12579
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 (%)10.9%

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) 1690
94.0%
2024-04-18T06:44:46.028058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 2203
17.5%
8 1947
15.5%
- 1797
14.3%
0 1749
13.9%
1 1721
13.7%
2 837
 
6.7%
4 729
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10782
85.7%
Dash Punctuation 1797
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 2203
20.4%
8 1947
18.1%
0 1749
16.2%
1 1721
16.0%
2 837
 
7.8%
4 729
 
6.8%
3 571
 
5.3%
7 441
 
4.1%
9 322
 
3.0%
5 262
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12579
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 2203
17.5%
8 1947
15.5%
- 1797
14.3%
0 1749
13.9%
1 1721
13.7%
2 837
 
6.7%
4 729
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 2203
17.5%
8 1947
15.5%
- 1797
14.3%
0 1749
13.9%
1 1721
13.7%
2 837
 
6.7%
4 729
 
5.8%
3 571
 
4.5%
7 441
 
3.5%
9 322
 
2.6%
Distinct1746
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:44:46.331482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length23.189684
Min length16

Characters and Unicode

Total characters41811
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

Unique1695 ?
Unique (%)94.0%

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 1803
 
22.4%
t통b반 334
 
4.2%
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 (2199) 4691
58.3%
2024-04-18T06:44:46.760695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6245
 
14.9%
2155
 
5.2%
2146
 
5.1%
2085
 
5.0%
1 1899
 
4.5%
1874
 
4.5%
1824
 
4.4%
1815
 
4.3%
1807
 
4.3%
- 1676
 
4.0%
Other values (268) 18285
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24204
57.9%
Decimal Number 8759
 
20.9%
Space Separator 6245
 
14.9%
Dash Punctuation 1676
 
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 (%)
2155
 
8.9%
2146
 
8.9%
2085
 
8.6%
1874
 
7.7%
1824
 
7.5%
1815
 
7.5%
1807
 
7.5%
1286
 
5.3%
1217
 
5.0%
385
 
1.6%
Other values (242) 7610
31.4%
Decimal Number
ValueCountFrequency (%)
1 1899
21.7%
2 1133
12.9%
3 989
11.3%
4 881
10.1%
5 779
8.9%
6 676
 
7.7%
7 646
 
7.4%
0 609
 
7.0%
8 608
 
6.9%
9 539
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
B 342
50.1%
T 334
48.9%
W 2
 
0.3%
A 2
 
0.3%
L 1
 
0.1%
I 1
 
0.1%
G 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 112
98.2%
. 1
 
0.9%
@ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
6245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1676
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 24204
57.9%
Common 16923
40.5%
Latin 684
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2155
 
8.9%
2146
 
8.9%
2085
 
8.6%
1874
 
7.7%
1824
 
7.5%
1815
 
7.5%
1807
 
7.5%
1286
 
5.3%
1217
 
5.0%
385
 
1.6%
Other values (242) 7610
31.4%
Common
ValueCountFrequency (%)
6245
36.9%
1 1899
 
11.2%
- 1676
 
9.9%
2 1133
 
6.7%
3 989
 
5.8%
4 881
 
5.2%
5 779
 
4.6%
6 676
 
4.0%
7 646
 
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 24204
57.9%
ASCII 17606
42.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6245
35.5%
1 1899
 
10.8%
- 1676
 
9.5%
2 1133
 
6.4%
3 989
 
5.6%
4 881
 
5.0%
5 779
 
4.4%
6 676
 
3.8%
7 646
 
3.7%
0 609
 
3.5%
Other values (15) 2073
 
11.8%
Hangul
ValueCountFrequency (%)
2155
 
8.9%
2146
 
8.9%
2085
 
8.6%
1874
 
7.7%
1824
 
7.5%
1815
 
7.5%
1807
 
7.5%
1286
 
5.3%
1217
 
5.0%
385
 
1.6%
Other values (242) 7610
31.4%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1187
Distinct (%)98.9%
Missing603
Missing (%)33.4%
Memory size14.2 KiB
2024-04-18T06:44:47.093579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length27.588333
Min length20

Characters and Unicode

Total characters33106
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

Unique1174 ?
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 1200
 
19.0%
부산진구 155
 
2.5%
남구 104
 
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 (1737) 4237
67.2%
2024-04-18T06:44:47.590702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5107
 
15.4%
1520
 
4.6%
1455
 
4.4%
1455
 
4.4%
1268
 
3.8%
1256
 
3.8%
1230
 
3.7%
1205
 
3.6%
) 1185
 
3.6%
( 1185
 
3.6%
Other values (327) 16240
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19922
60.2%
Decimal Number 5113
 
15.4%
Space Separator 5107
 
15.4%
Close Punctuation 1186
 
3.6%
Open Punctuation 1186
 
3.6%
Other Punctuation 360
 
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 (%)
1520
 
7.6%
1455
 
7.3%
1455
 
7.3%
1268
 
6.4%
1256
 
6.3%
1230
 
6.2%
1205
 
6.0%
1143
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8008
40.2%
Decimal Number
ValueCountFrequency (%)
1 1157
22.6%
2 722
14.1%
3 639
12.5%
5 450
 
8.8%
4 440
 
8.6%
6 391
 
7.6%
0 383
 
7.5%
7 355
 
6.9%
9 291
 
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 (%)
, 355
98.6%
. 3
 
0.8%
* 1
 
0.3%
@ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1185
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1185
99.9%
[ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 12
92.3%
1
 
7.7%
Space Separator
ValueCountFrequency (%)
5107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19922
60.2%
Common 13168
39.8%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1520
 
7.6%
1455
 
7.3%
1455
 
7.3%
1268
 
6.4%
1256
 
6.3%
1230
 
6.2%
1205
 
6.0%
1143
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8008
40.2%
Common
ValueCountFrequency (%)
5107
38.8%
) 1185
 
9.0%
( 1185
 
9.0%
1 1157
 
8.8%
2 722
 
5.5%
3 639
 
4.9%
5 450
 
3.4%
4 440
 
3.3%
6 391
 
3.0%
0 383
 
2.9%
Other values (12) 1509
 
11.5%
Latin
ValueCountFrequency (%)
B 7
43.8%
A 4
25.0%
W 2
 
12.5%
I 1
 
6.2%
G 1
 
6.2%
1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19922
60.2%
ASCII 13182
39.8%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5107
38.7%
) 1185
 
9.0%
( 1185
 
9.0%
1 1157
 
8.8%
2 722
 
5.5%
3 639
 
4.8%
5 450
 
3.4%
4 440
 
3.3%
6 391
 
3.0%
0 383
 
2.9%
Other values (16) 1523
 
11.6%
Hangul
ValueCountFrequency (%)
1520
 
7.6%
1455
 
7.3%
1455
 
7.3%
1268
 
6.4%
1256
 
6.3%
1230
 
6.2%
1205
 
6.0%
1143
 
5.7%
712
 
3.6%
670
 
3.4%
Other values (299) 8008
40.2%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct876
Distinct (%)76.7%
Missing661
Missing (%)36.7%
Infinite0
Infinite (%)0.0%
Mean47882.813
Minimum46002
Maximum49523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:47.720484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46249
Q147142
median47879
Q348721.75
95-th percentile49395.9
Maximum49523
Range3521
Interquartile range (IQR)1579.75

Descriptive statistics

Standard deviation983.82005
Coefficient of variation (CV)0.020546413
Kurtosis-1.0491457
Mean47882.813
Median Absolute Deviation (MAD)759
Skewness-0.0832315
Sum54682172
Variance967901.89
MonotonicityNot monotonic
2024-04-18T06:44:47.835561image/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%
46308 4
 
0.2%
47712 4
 
0.2%
48052 4
 
0.2%
48053 4
 
0.2%
48095 4
 
0.2%
47142 4
 
0.2%
Other values (866) 1091
60.5%
(Missing) 661
36.7%
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%
Distinct1136
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
2024-04-18T06:44:48.122889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length3
Mean length4.1475319
Min length2

Characters and Unicode

Total characters7478
Distinct characters386
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

Unique897 ?
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%
천수탕 15
 
0.8%
산수탕 15
 
0.8%
장수탕 14
 
0.7%
평화탕 13
 
0.7%
제일탕 13
 
0.7%
Other values (1196) 1795
91.3%
2024-04-18T06:44:48.580826image/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 (376) 4512
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7196
96.2%
Space Separator 163
 
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%
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 (354) 4278
59.4%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
L 2
13.3%
W 2
13.3%
O 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 11
55.0%
4 9
45.0%
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 7195
96.2%
Common 260
 
3.5%
Latin 22
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1357
 
18.9%
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 (353) 4277
59.4%
Latin
ValueCountFrequency (%)
G 4
18.2%
L 2
9.1%
W 2
9.1%
O 2
9.1%
n 2
9.1%
o 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
62.7%
) 38
 
14.6%
( 35
 
13.5%
2 11
 
4.2%
4 9
 
3.5%
- 2
 
0.8%
. 1
 
0.4%
, 1
 
0.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7195
96.2%
ASCII 282
 
3.8%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1357
 
18.9%
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 (353) 4277
59.4%
ASCII
ValueCountFrequency (%)
163
57.8%
) 38
 
13.5%
( 35
 
12.4%
2 11
 
3.9%
4 9
 
3.2%
G 4
 
1.4%
L 2
 
0.7%
- 2
 
0.7%
W 2
 
0.7%
O 2
 
0.7%
Other values (12) 14
 
5.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1528
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum1999-02-10 00:00:00
Maximum2023-02-27 13:41:14
2024-04-18T06:44:48.710818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:44:48.828261image/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
1055 
U
748 

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 1055
58.5%
U 748
41.5%

Length

2024-04-18T06:44:48.960775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:49.050285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1055
58.5%
u 748
41.5%
Distinct376
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-03-01 02:40:00
2024-04-18T06:44:49.147163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:44:49.282927image/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
157 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.718802
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1525
84.6%
목욕장업 기타 157
 
8.7%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:44:49.415390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:49.512093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1525
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 

Distinct1509
Distinct (%)90.3%
Missing131
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean387829.17
Minimum366820.79
Maximum407878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:49.619990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366820.79
5-th percentile379636.68
Q1384052.77
median388143.76
Q3391170.37
95-th percentile397007.51
Maximum407878
Range41057.216
Interquartile range (IQR)7117.5968

Descriptive statistics

Standard deviation5316.9725
Coefficient of variation (CV)0.013709574
Kurtosis0.67058502
Mean387829.17
Median Absolute Deviation (MAD)3571.7977
Skewness0.28779931
Sum6.4845036 × 108
Variance28270196
MonotonicityNot monotonic
2024-04-18T06:44:49.759407image/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) 1640
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 1
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 (%)90.3%
Missing131
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean186606.96
Minimum173914.72
Maximum207205.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:49.904248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173914.72
5-th percentile177878.54
Q1182245.78
median186777.08
Q3190600.22
95-th percentile195665.78
Maximum207205.27
Range33290.55
Interquartile range (IQR)8354.4377

Descriptive statistics

Standard deviation5649.7615
Coefficient of variation (CV)0.030276263
Kurtosis0.053655969
Mean186606.96
Median Absolute Deviation (MAD)4099.6832
Skewness0.26019949
Sum3.1200684 × 108
Variance31919805
MonotonicityNot monotonic
2024-04-18T06:44:50.422709image/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) 1640
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
157 
공동탕업+찜질시설서비스영업
 
77
한증막업
 
33
찜질시설서비스영업
 
11

Length

Max length14
Median length4
Mean length4.718802
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 1525
84.6%
목욕장업 기타 157
 
8.7%
공동탕업+찜질시설서비스영업 77
 
4.3%
한증막업 33
 
1.8%
찜질시설서비스영업 11
 
0.6%

Length

2024-04-18T06:44:50.533880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:50.633297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 1525
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%
Missing403
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean3.7042857
Minimum0
Maximum42
Zeros371
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:50.748854image/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 deviation4.4319632
Coefficient of variation (CV)1.196442
Kurtosis16.260681
Mean3.7042857
Median Absolute Deviation (MAD)2
Skewness3.3006967
Sum5186
Variance19.642298
MonotonicityNot monotonic
2024-04-18T06:44:50.857326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 371
20.6%
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) 403
22.4%
ValueCountFrequency (%)
0 371
20.6%
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%
Missing628
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean0.74808511
Minimum0
Maximum7
Zeros573
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:50.937407image/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 deviation1.0406693
Coefficient of variation (CV)1.3911108
Kurtosis7.9938735
Mean0.74808511
Median Absolute Deviation (MAD)1
Skewness2.4299261
Sum879
Variance1.0829925
MonotonicityNot monotonic
2024-04-18T06:44:51.026650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 573
31.8%
1 459
25.5%
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) 628
34.8%
ValueCountFrequency (%)
0 573
31.8%
1 459
25.5%
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
25.5%
0 573
31.8%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.8%
Missing584
Missing (%)32.4%
Infinite0
Infinite (%)0.0%
Mean1.3412633
Minimum0
Maximum10
Zeros383
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:51.117266image/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 deviation1.4095716
Coefficient of variation (CV)1.0509283
Kurtosis5.5846598
Mean1.3412633
Median Absolute Deviation (MAD)1
Skewness1.8257922
Sum1635
Variance1.986892
MonotonicityNot monotonic
2024-04-18T06:44:51.205192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 383
21.2%
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) 584
32.4%
ValueCountFrequency (%)
0 383
21.2%
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%
0 383
21.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)1.1%
Missing672
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean2.1184792
Minimum0
Maximum11
Zeros268
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:51.293184image/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 deviation1.7544189
Coefficient of variation (CV)0.82815015
Kurtosis2.4627631
Mean2.1184792
Median Absolute Deviation (MAD)1
Skewness1.1179663
Sum2396
Variance3.0779856
MonotonicityNot monotonic
2024-04-18T06:44:51.380837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 382
21.2%
0 268
 
14.9%
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) 672
37.3%
ValueCountFrequency (%)
0 268
14.9%
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
<NA>
858 
0
852 
1
 
81
2
 
9
3
 
3

Length

Max length4
Median length1
Mean length2.4276206
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 858
47.6%
0 852
47.3%
1 81
 
4.5%
2 9
 
0.5%
3 3
 
0.2%

Length

2024-04-18T06:44:51.480765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:51.569357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 858
47.6%
0 852
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>
1060 
0
649 
1
 
69
2
 
21
3
 
3

Length

Max length4
Median length4
Mean length2.7637271
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1060
58.8%
0 649
36.0%
1 69
 
3.8%
2 21
 
1.2%
3 3
 
0.2%
4 1
 
0.1%

Length

2024-04-18T06:44:51.676033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:51.796942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1060
58.8%
0 649
36.0%
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%
Mean1.3060729
Minimum0
Maximum26
Zeros646
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size16.0 KiB
2024-04-18T06:44:51.908923image/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 deviation2.1402041
Coefficient of variation (CV)1.638656
Kurtosis31.634764
Mean1.3060729
Median Absolute Deviation (MAD)0
Skewness4.3415078
Sum1613
Variance4.5804736
MonotonicityNot monotonic
2024-04-18T06:44:52.012714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 646
35.8%
2 477
26.5%
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 (%)
0 646
35.8%
1 19
 
1.1%
2 477
26.5%
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
1343 
True
458 
(Missing)
 
2
ValueCountFrequency (%)
False 1343
74.5%
True 458
 
25.4%
(Missing) 2
 
0.1%
2024-04-18T06:44:52.110207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1802
Missing (%)99.9%
Memory size14.2 KiB
2024-04-18T06:44:52.251629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

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

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row건축과-16824(2019.4.15),가설건축물 존치기간연장 신고
ValueCountFrequency (%)
건축과-16824(2019.4.15),가설건축물 1
33.3%
존치기간연장 1
33.3%
신고 1
33.3%
2024-04-18T06:44:52.484944image/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>
1802 
20190501
 
1

Length

Max length8
Median length4
Mean length4.0022185
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> 1802
99.9%
20190501 1
 
0.1%

Length

2024-04-18T06:44:52.617367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:52.710302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1802
99.9%
20190501 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1802 
20210421
 
1

Length

Max length8
Median length4
Mean length4.0022185
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> 1802
99.9%
20210421 1
 
0.1%

Length

2024-04-18T06:44:52.807146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:52.907003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1802
99.9%
20210421 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.2 KiB
<NA>
1401 
자가
274 
임대
 
128

Length

Max length4
Median length4
Mean length3.5540765
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> 1401
77.7%
자가 274
 
15.2%
임대 128
 
7.1%

Length

2024-04-18T06:44:53.007137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:53.101310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1401
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>
1501 
0
297 
2
 
2
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.4975042
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> 1501
83.3%
0 297
 
16.5%
2 2
 
0.1%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:44:53.193678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:53.288558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1501
83.3%
0 297
 
16.5%
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>
1501 
0
297 
1
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.4975042
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> 1501
83.3%
0 297
 
16.5%
1 3
 
0.2%
4 1
 
0.1%
5 1
 
0.1%

Length

2024-04-18T06:44:53.393184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T06:44:53.503975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1501
83.3%
0 297
 
16.5%
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
1764 
True
 
39
ValueCountFrequency (%)
False 1764
97.8%
True 39
 
2.2%
2024-04-18T06:44:53.597812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 44
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1803
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
17931794목욕장업11_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>
17941795목욕장업11_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>
17951796목욕장업11_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>
17961797목욕장업11_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>
17971798목욕장업11_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>
17981799목욕장업11_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>
17991800목욕장업11_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>
18001801목욕장업11_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>
18011802목욕장업11_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>
18021803목욕장업11_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>