Overview

Dataset statistics

Number of variables38
Number of observations85
Missing cells1088
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.4 KiB
Average record size in memory329.6 B

Variable types

Numeric11
Categorical12
Unsupported10
Text4
DateTime1

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123174

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
문화체육업종명 has constant value ""Constant
공사립구분명 is highly imbalanced (90.8%)Imbalance
건축물동수 is highly imbalanced (61.3%)Imbalance
인허가취소일자 has 85 (100.0%) missing valuesMissing
폐업일자 has 49 (57.6%) missing valuesMissing
휴업시작일자 has 85 (100.0%) missing valuesMissing
휴업종료일자 has 85 (100.0%) missing valuesMissing
재개업일자 has 85 (100.0%) missing valuesMissing
소재지전화 has 7 (8.2%) missing valuesMissing
소재지면적 has 85 (100.0%) missing valuesMissing
소재지우편번호 has 38 (44.7%) missing valuesMissing
소재지전체주소 has 5 (5.9%) missing valuesMissing
도로명전체주소 has 9 (10.6%) missing valuesMissing
도로명우편번호 has 32 (37.6%) missing valuesMissing
업태구분명 has 85 (100.0%) missing valuesMissing
좌표정보(x) has 3 (3.5%) missing valuesMissing
좌표정보(y) has 3 (3.5%) missing valuesMissing
지도자수 has 53 (62.4%) missing valuesMissing
건축물연면적 has 39 (45.9%) missing valuesMissing
회원모집총인원 has 85 (100.0%) missing valuesMissing
세부업종명 has 85 (100.0%) missing valuesMissing
법인명 has 85 (100.0%) missing valuesMissing
Unnamed: 37 has 85 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
회원모집총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 37 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 21:20:00.187516
Analysis finished2024-04-16 21:20:00.607646
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:00.665212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.2
Q122
median43
Q364
95-th percentile80.8
Maximum85
Range84
Interquartile range (IQR)42

Descriptive statistics

Standard deviation24.681302
Coefficient of variation (CV)0.57398377
Kurtosis-1.2
Mean43
Median Absolute Deviation (MAD)21
Skewness0
Sum3655
Variance609.16667
MonotonicityStrictly increasing
2024-04-17T06:20:00.780736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
수영장업
85 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영장업 85
100.0%

Length

2024-04-17T06:20:00.885845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:00.956372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장업 85
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
10_35_01_P
85 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10_35_01_P
2nd row10_35_01_P
3rd row10_35_01_P
4th row10_35_01_P
5th row10_35_01_P

Common Values

ValueCountFrequency (%)
10_35_01_P 85
100.0%

Length

2024-04-17T06:20:01.033294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:01.109985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_35_01_p 85
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3332588.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:01.180880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3270000
Q13310000
median3330000
Q33350000
95-th percentile3398000
Maximum3400000
Range150000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation36421.898
Coefficient of variation (CV)0.010929012
Kurtosis-0.42800799
Mean3332588.2
Median Absolute Deviation (MAD)20000
Skewness-0.026923796
Sum2.8327 × 108
Variance1.3265546 × 109
MonotonicityNot monotonic
2024-04-17T06:20:01.274757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3330000 16
18.8%
3350000 8
9.4%
3340000 8
9.4%
3300000 7
8.2%
3320000 6
 
7.1%
3310000 6
 
7.1%
3370000 5
 
5.9%
3380000 5
 
5.9%
3290000 5
 
5.9%
3400000 5
 
5.9%
Other values (5) 14
16.5%
ValueCountFrequency (%)
3250000 2
 
2.4%
3270000 4
 
4.7%
3280000 2
 
2.4%
3290000 5
 
5.9%
3300000 7
8.2%
3310000 6
 
7.1%
3320000 6
 
7.1%
3330000 16
18.8%
3340000 8
9.4%
3350000 8
9.4%
ValueCountFrequency (%)
3400000 5
 
5.9%
3390000 3
 
3.5%
3380000 5
 
5.9%
3370000 5
 
5.9%
3360000 3
 
3.5%
3350000 8
9.4%
3340000 8
9.4%
3330000 16
18.8%
3320000 6
 
7.1%
3310000 6
 
7.1%

관리번호
Categorical

Distinct40
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size812.0 B
CDFH3301012017000001
10 
CDFH3301012020000001
7 
CDFH3301012000000001
6 
CDFH3301012017000002
 
4
CDFH3301011996000001
 
4
Other values (35)
54 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique22 ?
Unique (%)25.9%

Sample

1st rowCDFH3301012004000001
2nd rowCDFH3301011996000001
3rd rowCDFH3301011994000002
4th rowCDFH3301012007000001
5th rowCDFH3301012007000001

Common Values

ValueCountFrequency (%)
CDFH3301012017000001 10
 
11.8%
CDFH3301012020000001 7
 
8.2%
CDFH3301012000000001 6
 
7.1%
CDFH3301012017000002 4
 
4.7%
CDFH3301011996000001 4
 
4.7%
CDFH3301012018000001 4
 
4.7%
CDFH3301012015000001 3
 
3.5%
CDFH3301012003000001 3
 
3.5%
CDFH3301012002000001 3
 
3.5%
CDFH3301011999000001 3
 
3.5%
Other values (30) 38
44.7%

Length

2024-04-17T06:20:01.369064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cdfh3301012017000001 10
 
11.8%
cdfh3301012020000001 7
 
8.2%
cdfh3301012000000001 6
 
7.1%
cdfh3301012017000002 4
 
4.7%
cdfh3301011996000001 4
 
4.7%
cdfh3301012018000001 4
 
4.7%
cdfh3301012015000001 3
 
3.5%
cdfh3301012003000001 3
 
3.5%
cdfh3301012002000001 3
 
3.5%
cdfh3301011999000001 3
 
3.5%
Other values (30) 38
44.7%

인허가일자
Real number (ℝ)

Distinct81
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20068265
Minimum19730112
Maximum20201127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:01.467201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19730112
5-th percentile19892883
Q119991022
median20070201
Q320170713
95-th percentile20200416
Maximum20201127
Range471015
Interquartile range (IQR)179691

Descriptive statistics

Standard deviation111270.89
Coefficient of variation (CV)0.0055446193
Kurtosis-0.11365661
Mean20068265
Median Absolute Deviation (MAD)100113
Skewness-0.65670028
Sum1.7058025 × 109
Variance1.2381211 × 1010
MonotonicityNot monotonic
2024-04-17T06:20:01.612035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19800709 2
 
2.4%
20170627 2
 
2.4%
20030203 2
 
2.4%
19980324 2
 
2.4%
20040409 1
 
1.2%
20171026 1
 
1.2%
20171122 1
 
1.2%
20180618 1
 
1.2%
20200917 1
 
1.2%
20060216 1
 
1.2%
Other values (71) 71
83.5%
ValueCountFrequency (%)
19730112 1
1.2%
19800709 2
2.4%
19840519 1
1.2%
19890923 1
1.2%
19900724 1
1.2%
19930609 1
1.2%
19931221 1
1.2%
19940514 1
1.2%
19940915 1
1.2%
19950624 1
1.2%
ValueCountFrequency (%)
20201127 1
1.2%
20201023 1
1.2%
20200917 1
1.2%
20200602 1
1.2%
20200417 1
1.2%
20200413 1
1.2%
20200218 1
1.2%
20200205 1
1.2%
20190319 1
1.2%
20190219 1
1.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
1
49 
3
32 
4
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row3

Common Values

ValueCountFrequency (%)
1 49
57.6%
3 32
37.6%
4 4
 
4.7%

Length

2024-04-17T06:20:01.718848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:01.793952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
57.6%
3 32
37.6%
4 4
 
4.7%

영업상태명
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
영업/정상
49 
폐업
32 
취소/말소/만료/정지/중지
 
4

Length

Max length14
Median length5
Mean length4.2941176
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row취소/말소/만료/정지/중지
3rd row취소/말소/만료/정지/중지
4th row취소/말소/만료/정지/중지
5th row폐업

Common Values

ValueCountFrequency (%)
영업/정상 49
57.6%
폐업 32
37.6%
취소/말소/만료/정지/중지 4
 
4.7%

Length

2024-04-17T06:20:01.881822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:01.962119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 49
57.6%
폐업 32
37.6%
취소/말소/만료/정지/중지 4
 
4.7%

상세영업상태코드
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
13
49 
3
32 
35
 
4

Length

Max length2
Median length2
Mean length1.6235294
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35
2nd row35
3rd row35
4th row35
5th row3

Common Values

ValueCountFrequency (%)
13 49
57.6%
3 32
37.6%
35 4
 
4.7%

Length

2024-04-17T06:20:02.048988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:02.129983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 49
57.6%
3 32
37.6%
35 4
 
4.7%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
영업중
49 
폐업
32 
직권말소
 
4

Length

Max length4
Median length3
Mean length2.6705882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 49
57.6%
폐업 32
37.6%
직권말소 4
 
4.7%

Length

2024-04-17T06:20:02.221246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:02.307452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 49
57.6%
폐업 32
37.6%
직권말소 4
 
4.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)94.4%
Missing49
Missing (%)57.6%
Infinite0
Infinite (%)0.0%
Mean20102647
Minimum19951212
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:02.397968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19951212
5-th percentile19977974
Q120058047
median20105771
Q320170540
95-th percentile20191101
Maximum20191231
Range240019
Interquartile range (IQR)112492.5

Descriptive statistics

Standard deviation69326.199
Coefficient of variation (CV)0.0034486106
Kurtosis-0.67247861
Mean20102647
Median Absolute Deviation (MAD)55568.5
Skewness-0.41421954
Sum7.2369528 × 108
Variance4.8061219 × 109
MonotonicityNot monotonic
2024-04-17T06:20:02.502152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
20191101 2
 
2.4%
20050103 2
 
2.4%
19991211 1
 
1.2%
20170925 1
 
1.2%
20080709 1
 
1.2%
20100913 1
 
1.2%
20080828 1
 
1.2%
20111116 1
 
1.2%
19980531 1
 
1.2%
19951212 1
 
1.2%
Other values (24) 24
28.2%
(Missing) 49
57.6%
ValueCountFrequency (%)
19951212 1
1.2%
19970304 1
1.2%
19980531 1
1.2%
19991211 1
1.2%
20030102 1
1.2%
20031128 1
1.2%
20050103 2
2.4%
20050302 1
1.2%
20060629 1
1.2%
20061020 1
1.2%
ValueCountFrequency (%)
20191231 1
1.2%
20191101 2
2.4%
20190810 1
1.2%
20190203 1
1.2%
20190116 1
1.2%
20180820 1
1.2%
20170925 1
1.2%
20170614 1
1.2%
20170515 1
1.2%
20151001 1
1.2%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

소재지전화
Text

MISSING 

Distinct76
Distinct (%)97.4%
Missing7
Missing (%)8.2%
Memory size812.0 B
2024-04-17T06:20:02.713011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length10.679487
Min length8

Characters and Unicode

Total characters833
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)94.9%

Sample

1st row331-4186
2nd row051-333-5594
3rd row070-7431-0015
4th row051-863-8496~7
5th row051-704-8705
ValueCountFrequency (%)
051-740-0404 2
 
2.5%
622-0101 2
 
2.5%
051-604-7000 1
 
1.2%
051-509-1111 1
 
1.2%
465-1152 1
 
1.2%
051-604-7201 1
 
1.2%
331-4186 1
 
1.2%
051-559-4016 1
 
1.2%
051-514-9007 1
 
1.2%
051-967-5300 1
 
1.2%
Other values (68) 68
85.0%
2024-04-17T06:20:03.005679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 145
17.4%
1 124
14.9%
- 124
14.9%
5 105
12.6%
2 64
7.7%
7 57
 
6.8%
4 55
 
6.6%
6 50
 
6.0%
3 44
 
5.3%
9 40
 
4.8%
Other values (5) 25
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 703
84.4%
Dash Punctuation 124
 
14.9%
Close Punctuation 2
 
0.2%
Space Separator 2
 
0.2%
Other Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 145
20.6%
1 124
17.6%
5 105
14.9%
2 64
9.1%
7 57
 
8.1%
4 55
 
7.8%
6 50
 
7.1%
3 44
 
6.3%
9 40
 
5.7%
8 19
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 145
17.4%
1 124
14.9%
- 124
14.9%
5 105
12.6%
2 64
7.7%
7 57
 
6.8%
4 55
 
6.6%
6 50
 
6.0%
3 44
 
5.3%
9 40
 
4.8%
Other values (5) 25
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 145
17.4%
1 124
14.9%
- 124
14.9%
5 105
12.6%
2 64
7.7%
7 57
 
6.8%
4 55
 
6.6%
6 50
 
6.0%
3 44
 
5.3%
9 40
 
4.8%
Other values (5) 25
 
3.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)91.5%
Missing38
Missing (%)44.7%
Infinite0
Infinite (%)0.0%
Mean610471.77
Minimum600100
Maximum618814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:03.119086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600100
5-th percentile602723.9
Q1607808
median611817
Q3612846.5
95-th percentile616823.1
Maximum618814
Range18714
Interquartile range (IQR)5038.5

Descriptive statistics

Standard deviation4395.7021
Coefficient of variation (CV)0.0072005002
Kurtosis-0.34108198
Mean610471.77
Median Absolute Deviation (MAD)2983
Skewness-0.43325115
Sum28692173
Variance19322197
MonotonicityNot monotonic
2024-04-17T06:20:03.228779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
607808 2
 
2.4%
612846 2
 
2.4%
612821 2
 
2.4%
604813 2
 
2.4%
612020 1
 
1.2%
614822 1
 
1.2%
611839 1
 
1.2%
611812 1
 
1.2%
600100 1
 
1.2%
612848 1
 
1.2%
Other values (33) 33
38.8%
(Missing) 38
44.7%
ValueCountFrequency (%)
600100 1
1.2%
601812 1
1.2%
601829 1
1.2%
604812 1
1.2%
604813 2
2.4%
604827 1
1.2%
604845 1
1.2%
604868 1
1.2%
606080 1
1.2%
606081 1
1.2%
ValueCountFrequency (%)
618814 1
1.2%
617846 1
1.2%
616854 1
1.2%
616751 1
1.2%
616100 1
1.2%
614871 1
1.2%
614822 1
1.2%
613817 1
1.2%
613815 1
1.2%
613751 1
1.2%

소재지전체주소
Text

MISSING 

Distinct75
Distinct (%)93.8%
Missing5
Missing (%)5.9%
Memory size812.0 B
2024-04-17T06:20:03.469613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length23.6875
Min length17

Characters and Unicode

Total characters1895
Distinct characters125
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)87.5%

Sample

1st row부산광역시 북구 화명동 1130-15번지
2nd row부산광역시 북구 구포동 1103-2번지 구포현대아파트 상가 지하2층 1호
3rd row부산광역시 금정구 구서동 203-5번지 3층, 5층
4th row부산광역시 연제구 거제동 577-1번지 연제그린타워 101동 지하1층134호
5th row부산광역시 해운대구 좌동 1290번지
ValueCountFrequency (%)
부산광역시 80
 
21.9%
해운대구 16
 
4.4%
사하구 8
 
2.2%
동래구 7
 
1.9%
금정구 7
 
1.9%
우동 6
 
1.6%
남구 6
 
1.6%
연제구 5
 
1.4%
수영구 5
 
1.4%
부산진구 5
 
1.4%
Other values (159) 221
60.4%
2024-04-17T06:20:03.852702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
287
 
15.1%
동 94
 
5.0%
산 92
 
4.9%
1 90
 
4.7%
부 87
 
4.6%
시 83
 
4.4%
구 83
 
4.4%
역 80
 
4.2%
지 80
 
4.2%
광 80
 
4.2%
Other values (115) 839
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1142
60.3%
Decimal Number 380
 
20.1%
Space Separator 287
 
15.1%
Dash Punctuation 69
 
3.6%
Uppercase Letter 6
 
0.3%
Other Punctuation 5
 
0.3%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 94
 
8.2%
산 92
 
8.1%
부 87
 
7.6%
시 83
 
7.3%
구 83
 
7.3%
역 80
 
7.0%
지 80
 
7.0%
광 80
 
7.0%
번 68
 
6.0%
대 25
 
2.2%
Other values (95) 370
32.4%
Decimal Number
ValueCountFrequency (%)
1 90
23.7%
2 41
10.8%
3 40
10.5%
5 35
 
9.2%
4 34
 
8.9%
7 33
 
8.7%
0 30
 
7.9%
6 29
 
7.6%
9 25
 
6.6%
8 23
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
Z 2
33.3%
B 1
16.7%
O 1
16.7%
N 1
16.7%
E 1
16.7%
Space Separator
ValueCountFrequency (%)
287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1142
60.3%
Common 747
39.4%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 94
 
8.2%
산 92
 
8.1%
부 87
 
7.6%
시 83
 
7.3%
구 83
 
7.3%
역 80
 
7.0%
지 80
 
7.0%
광 80
 
7.0%
번 68
 
6.0%
대 25
 
2.2%
Other values (95) 370
32.4%
Common
ValueCountFrequency (%)
287
38.4%
1 90
 
12.0%
- 69
 
9.2%
2 41
 
5.5%
3 40
 
5.4%
5 35
 
4.7%
4 34
 
4.6%
7 33
 
4.4%
0 30
 
4.0%
6 29
 
3.9%
Other values (5) 59
 
7.9%
Latin
ValueCountFrequency (%)
Z 2
33.3%
B 1
16.7%
O 1
16.7%
N 1
16.7%
E 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1142
60.3%
ASCII 753
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
287
38.1%
1 90
 
12.0%
- 69
 
9.2%
2 41
 
5.4%
3 40
 
5.3%
5 35
 
4.6%
4 34
 
4.5%
7 33
 
4.4%
0 30
 
4.0%
6 29
 
3.9%
Other values (10) 65
 
8.6%
Hangul
ValueCountFrequency (%)
동 94
 
8.2%
산 92
 
8.1%
부 87
 
7.6%
시 83
 
7.3%
구 83
 
7.3%
역 80
 
7.0%
지 80
 
7.0%
광 80
 
7.0%
번 68
 
6.0%
대 25
 
2.2%
Other values (95) 370
32.4%

도로명전체주소
Text

MISSING 

Distinct72
Distinct (%)94.7%
Missing9
Missing (%)10.6%
Memory size812.0 B
2024-04-17T06:20:04.098693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length29.907895
Min length20

Characters and Unicode

Total characters2273
Distinct characters154
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)90.8%

Sample

1st row부산광역시 북구 금곡대로 230 (화명동)
2nd row부산광역시 북구 백양대로 1003, 상가동 지하2층 1호 (구포동)
3rd row부산광역시 금정구 구서중앙로15번길 20 (구서동,3층, 5층)
4th row부산광역시 연제구 거제천로87번길 30 (거제동)
5th row부산광역시 해운대구 세실로 137 (좌동, 지하1층)
ValueCountFrequency (%)
부산광역시 76
 
17.4%
해운대구 16
 
3.7%
지하1층 10
 
2.3%
금정구 8
 
1.8%
사하구 7
 
1.6%
해운대해변로 6
 
1.4%
우동 6
 
1.4%
남구 6
 
1.4%
북구 6
 
1.4%
부산진구 5
 
1.1%
Other values (202) 292
66.7%
2024-04-17T06:20:04.454157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
378
 
16.6%
부 89
 
3.9%
산 89
 
3.9%
동 88
 
3.9%
시 81
 
3.6%
1 80
 
3.5%
광 79
 
3.5%
구 79
 
3.5%
역 76
 
3.3%
로 75
 
3.3%
Other values (144) 1159
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1359
59.8%
Space Separator 378
 
16.6%
Decimal Number 320
 
14.1%
Close Punctuation 74
 
3.3%
Open Punctuation 74
 
3.3%
Other Punctuation 48
 
2.1%
Dash Punctuation 12
 
0.5%
Uppercase Letter 7
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 89
 
6.5%
산 89
 
6.5%
동 88
 
6.5%
시 81
 
6.0%
광 79
 
5.8%
구 79
 
5.8%
역 76
 
5.6%
로 75
 
5.5%
대 44
 
3.2%
해 37
 
2.7%
Other values (123) 622
45.8%
Decimal Number
ValueCountFrequency (%)
1 80
25.0%
2 61
19.1%
3 42
13.1%
0 31
 
9.7%
7 29
 
9.1%
8 20
 
6.2%
4 15
 
4.7%
9 14
 
4.4%
6 14
 
4.4%
5 14
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
Z 2
28.6%
B 2
28.6%
O 1
14.3%
N 1
14.3%
E 1
14.3%
Space Separator
ValueCountFrequency (%)
378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1359
59.8%
Common 907
39.9%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 89
 
6.5%
산 89
 
6.5%
동 88
 
6.5%
시 81
 
6.0%
광 79
 
5.8%
구 79
 
5.8%
역 76
 
5.6%
로 75
 
5.5%
대 44
 
3.2%
해 37
 
2.7%
Other values (123) 622
45.8%
Common
ValueCountFrequency (%)
378
41.7%
1 80
 
8.8%
) 74
 
8.2%
( 74
 
8.2%
2 61
 
6.7%
, 48
 
5.3%
3 42
 
4.6%
0 31
 
3.4%
7 29
 
3.2%
8 20
 
2.2%
Other values (6) 70
 
7.7%
Latin
ValueCountFrequency (%)
Z 2
28.6%
B 2
28.6%
O 1
14.3%
N 1
14.3%
E 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1359
59.8%
ASCII 914
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
378
41.4%
1 80
 
8.8%
) 74
 
8.1%
( 74
 
8.1%
2 61
 
6.7%
, 48
 
5.3%
3 42
 
4.6%
0 31
 
3.4%
7 29
 
3.2%
8 20
 
2.2%
Other values (11) 77
 
8.4%
Hangul
ValueCountFrequency (%)
부 89
 
6.5%
산 89
 
6.5%
동 88
 
6.5%
시 81
 
6.0%
광 79
 
5.8%
구 79
 
5.8%
역 76
 
5.6%
로 75
 
5.5%
대 44
 
3.2%
해 37
 
2.7%
Other values (123) 622
45.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)83.0%
Missing32
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean79562
Minimum46024
Maximum616100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:04.562717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46024
5-th percentile46083
Q146651
median47744
Q348106
95-th percentile275207
Maximum616100
Range570076
Interquartile range (IQR)1455

Descriptive statistics

Standard deviation132303.79
Coefficient of variation (CV)1.6629018
Kurtosis14.135279
Mean79562
Median Absolute Deviation (MAD)764
Skewness3.9499226
Sum4216786
Variance1.7504293 × 1010
MonotonicityNot monotonic
2024-04-17T06:20:04.891824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
46083 4
 
4.7%
48093 3
 
3.5%
47179 2
 
2.4%
47543 2
 
2.4%
46726 2
 
2.4%
46651 2
 
2.4%
613817 1
 
1.2%
47100 1
 
1.2%
48815 1
 
1.2%
47039 1
 
1.2%
Other values (34) 34
40.0%
(Missing) 32
37.6%
ValueCountFrequency (%)
46024 1
 
1.2%
46083 4
4.7%
46230 1
 
1.2%
46234 1
 
1.2%
46271 1
 
1.2%
46274 1
 
1.2%
46294 1
 
1.2%
46500 1
 
1.2%
46525 1
 
1.2%
46651 2
2.4%
ValueCountFrequency (%)
616100 1
1.2%
613817 1
1.2%
613751 1
1.2%
49511 1
1.2%
49449 1
1.2%
48912 1
1.2%
48815 1
1.2%
48584 1
1.2%
48528 1
1.2%
48508 1
1.2%

사업장명
Text

Distinct81
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size812.0 B
2024-04-17T06:20:05.073136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length8.9058824
Min length3

Characters and Unicode

Total characters757
Distinct characters177
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)91.8%

Sample

1st row금용레포츠타운 수영장
2nd row구포현대수영장
3rd row승산수영장
4th row연제그린수영장
5th row해운대 생활체육센타
ValueCountFrequency (%)
수영장 13
 
10.2%
망고키즈수영장 3
 
2.3%
아이올림픽 2
 
1.6%
시민 2
 
1.6%
해수온천 2
 
1.6%
구포현대수영장 2
 
1.6%
부산항 2
 
1.6%
힐튼호텔 2
 
1.6%
스포츠센터 2
 
1.6%
스포렉스 2
 
1.6%
Other values (96) 96
75.0%
2024-04-17T06:20:05.381300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 53
 
7.0%
영 50
 
6.6%
장 50
 
6.6%
43
 
5.7%
스 29
 
3.8%
포 23
 
3.0%
센 17
 
2.2%
츠 17
 
2.2%
즈 14
 
1.8%
터 14
 
1.8%
Other values (167) 447
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 676
89.3%
Space Separator 43
 
5.7%
Open Punctuation 13
 
1.7%
Close Punctuation 13
 
1.7%
Uppercase Letter 6
 
0.8%
Other Punctuation 2
 
0.3%
Decimal Number 2
 
0.3%
Lowercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 53
 
7.8%
영 50
 
7.4%
장 50
 
7.4%
스 29
 
4.3%
포 23
 
3.4%
센 17
 
2.5%
츠 17
 
2.5%
즈 14
 
2.1%
터 14
 
2.1%
키 13
 
1.9%
Other values (153) 396
58.6%
Uppercase Letter
ValueCountFrequency (%)
O 1
16.7%
L 1
16.7%
A 1
16.7%
P 1
16.7%
J 1
16.7%
T 1
16.7%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 676
89.3%
Common 73
 
9.6%
Latin 8
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 53
 
7.8%
영 50
 
7.4%
장 50
 
7.4%
스 29
 
4.3%
포 23
 
3.4%
센 17
 
2.5%
츠 17
 
2.5%
즈 14
 
2.1%
터 14
 
2.1%
키 13
 
1.9%
Other values (153) 396
58.6%
Latin
ValueCountFrequency (%)
O 1
12.5%
L 1
12.5%
A 1
12.5%
P 1
12.5%
J 1
12.5%
e 1
12.5%
h 1
12.5%
T 1
12.5%
Common
ValueCountFrequency (%)
43
58.9%
( 13
 
17.8%
) 13
 
17.8%
& 2
 
2.7%
5 1
 
1.4%
2 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 676
89.3%
ASCII 81
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 53
 
7.8%
영 50
 
7.4%
장 50
 
7.4%
스 29
 
4.3%
포 23
 
3.4%
센 17
 
2.5%
츠 17
 
2.5%
즈 14
 
2.1%
터 14
 
2.1%
키 13
 
1.9%
Other values (153) 396
58.6%
ASCII
ValueCountFrequency (%)
43
53.1%
( 13
 
16.0%
) 13
 
16.0%
& 2
 
2.5%
O 1
 
1.2%
L 1
 
1.2%
A 1
 
1.2%
5 1
 
1.2%
2 1
 
1.2%
P 1
 
1.2%
Other values (4) 4
 
4.9%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0158202 × 1013
Minimum2.003011 × 1013
Maximum2.0210121 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:05.492851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.003011 × 1013
5-th percentile2.0034943 × 1013
Q12.0140407 × 1013
median2.018083 × 1013
Q32.0200203 × 1013
95-th percentile2.0201095 × 1013
Maximum2.0210121 × 1013
Range1.8001099 × 1011
Interquartile range (IQR)5.9795988 × 1010

Descriptive statistics

Standard deviation5.3108318 × 1010
Coefficient of variation (CV)0.0026345762
Kurtosis0.297549
Mean2.0158202 × 1013
Median Absolute Deviation (MAD)1.9680967 × 1010
Skewness-1.2583793
Sum1.7134472 × 1015
Variance2.8204935 × 1021
MonotonicityNot monotonic
2024-04-17T06:20:05.603399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150831091038 1
 
1.2%
20190219130025 1
 
1.2%
20190531185503 1
 
1.2%
20200203101039 1
 
1.2%
20200917163731 1
 
1.2%
20150604162725 1
 
1.2%
20200408101646 1
 
1.2%
20201023174326 1
 
1.2%
20190903124425 1
 
1.2%
20200511110450 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
20030110102855 1
1.2%
20030110141521 1
1.2%
20030203105759 1
1.2%
20030203105946 1
1.2%
20031128163103 1
1.2%
20050202115804 1
1.2%
20050503102910 1
1.2%
20060803162125 1
1.2%
20070111131859 1
1.2%
20070326132920 1
1.2%
ValueCountFrequency (%)
20210121093306 1
1.2%
20201224085047 1
1.2%
20201202131504 1
1.2%
20201127111412 1
1.2%
20201113111308 1
1.2%
20201023174326 1
1.2%
20201019144743 1
1.2%
20201015144226 1
1.2%
20200917163731 1
1.2%
20200626154236 1
1.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
I
51 
U
34 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 51
60.0%
U 34
40.0%

Length

2024-04-17T06:20:05.704710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:05.778304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 51
60.0%
u 34
40.0%

데이터갱신일자
Date

Distinct38
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2018-08-31 23:59:59
Maximum2021-01-23 02:40:00
2024-04-17T06:20:05.858322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:20:05.970328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)85.4%
Missing3
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean389325.92
Minimum373088.09
Maximum402899.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:06.074587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum373088.09
5-th percentile379482.53
Q1385067.62
median390217.87
Q3393057.31
95-th percentile398170.89
Maximum402899.9
Range29811.816
Interquartile range (IQR)7989.6949

Descriptive statistics

Standard deviation6577.5208
Coefficient of variation (CV)0.016894639
Kurtosis-0.23142506
Mean389325.92
Median Absolute Deviation (MAD)3891.0177
Skewness-0.15770036
Sum31924726
Variance43263780
MonotonicityNot monotonic
2024-04-17T06:20:06.176938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
402771.0 3
 
3.5%
390057.531834683 2
 
2.4%
381886.710034792 2
 
2.4%
388720.828319509 2
 
2.4%
386466.092076382 2
 
2.4%
391202.373979842 2
 
2.4%
380242.229956273 2
 
2.4%
381432.330084105 2
 
2.4%
385030.729095916 2
 
2.4%
396311.478370083 2
 
2.4%
Other values (60) 61
71.8%
(Missing) 3
 
3.5%
ValueCountFrequency (%)
373088.087508096 1
1.2%
375459.538286912 1
1.2%
375497.314020354 1
1.2%
378889.964872659 1
1.2%
379461.562843903 1
1.2%
379880.819741946 1
1.2%
380187.188805154 1
1.2%
380242.229956273 2
2.4%
380540.836768886 1
1.2%
380924.606123329 1
1.2%
ValueCountFrequency (%)
402899.903247998 1
 
1.2%
402771.0 3
3.5%
398174.624215816 1
 
1.2%
398099.98527229 1
 
1.2%
398040.576128515 1
 
1.2%
397605.231632284 1
 
1.2%
397114.551436907 1
 
1.2%
397022.971550345 1
 
1.2%
396941.887444768 1
 
1.2%
396626.391770844 1
 
1.2%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)85.4%
Missing3
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean187062.72
Minimum174072.9
Maximum204435.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:06.287209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174072.9
5-th percentile176778.92
Q1183145.45
median186992.3
Q3190947
95-th percentile195926.91
Maximum204435.59
Range30362.694
Interquartile range (IQR)7801.5544

Descriptive statistics

Standard deviation5856.2315
Coefficient of variation (CV)0.031306246
Kurtosis0.1429359
Mean187062.72
Median Absolute Deviation (MAD)3954.7039
Skewness-0.0060051813
Sum15339143
Variance34295447
MonotonicityNot monotonic
2024-04-17T06:20:06.398977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190947.0 3
 
3.5%
196950.450593302 2
 
2.4%
192791.688242788 2
 
2.4%
189073.142540755 2
 
2.4%
181381.122678011 2
 
2.4%
191289.345957951 2
 
2.4%
176764.196253648 2
 
2.4%
190402.183262767 2
 
2.4%
186527.138977733 2
 
2.4%
186563.963573726 2
 
2.4%
Other values (60) 61
71.8%
(Missing) 3
 
3.5%
ValueCountFrequency (%)
174072.895685053 1
1.2%
175235.790940527 1
1.2%
175274.144961403 1
1.2%
176764.196253648 2
2.4%
177058.730875524 1
1.2%
177962.876339211 1
1.2%
178483.480105701 1
1.2%
179109.936617514 1
1.2%
179338.728162321 1
1.2%
180082.556995742 1
1.2%
ValueCountFrequency (%)
204435.59007753 1
1.2%
199014.86939962 1
1.2%
196950.450593302 2
2.4%
195986.908984448 1
1.2%
194786.946259107 1
1.2%
194178.256719389 1
1.2%
194117.297645474 1
1.2%
194017.963600245 1
1.2%
193622.839714278 1
1.2%
192791.688242788 2
2.4%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
수영장업
85 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영장업 85
100.0%

Length

2024-04-17T06:20:06.497135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:06.569578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장업 85
100.0%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
사립
84 
공립
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
사립 84
98.8%
공립 1
 
1.2%

Length

2024-04-17T06:20:06.652302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:06.729214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 84
98.8%
공립 1
 
1.2%

보험가입여부코드
Categorical

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
<NA>
42 
Y
26 
0
9 
1
8 

Length

Max length4
Median length1
Mean length2.4823529
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
49.4%
Y 26
30.6%
0 9
 
10.6%
1 8
 
9.4%

Length

2024-04-17T06:20:06.835651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:06.947308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
49.4%
y 26
30.6%
0 9
 
10.6%
1 8
 
9.4%

지도자수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)18.8%
Missing53
Missing (%)62.4%
Infinite0
Infinite (%)0.0%
Mean1.84375
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:07.034690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q32
95-th percentile4.45
Maximum7
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3224946
Coefficient of variation (CV)0.7172852
Kurtosis7.407735
Mean1.84375
Median Absolute Deviation (MAD)0.5
Skewness2.5369051
Sum59
Variance1.7489919
MonotonicityNot monotonic
2024-04-17T06:20:07.117858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 16
 
18.8%
2 12
 
14.1%
4 1
 
1.2%
5 1
 
1.2%
3 1
 
1.2%
7 1
 
1.2%
(Missing) 53
62.4%
ValueCountFrequency (%)
1 16
18.8%
2 12
14.1%
3 1
 
1.2%
4 1
 
1.2%
5 1
 
1.2%
7 1
 
1.2%
ValueCountFrequency (%)
7 1
 
1.2%
5 1
 
1.2%
4 1
 
1.2%
3 1
 
1.2%
2 12
14.1%
1 16
18.8%

건축물동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
<NA>
74 
1
10 
4
 
1

Length

Max length4
Median length4
Mean length3.6117647
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
87.1%
1 10
 
11.8%
4 1
 
1.2%

Length

2024-04-17T06:20:07.247694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:20:07.335705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
87.1%
1 10
 
11.8%
4 1
 
1.2%

건축물연면적
Real number (ℝ)

MISSING 

Distinct46
Distinct (%)100.0%
Missing39
Missing (%)45.9%
Infinite0
Infinite (%)0.0%
Mean5350.3307
Minimum0.1
Maximum53782.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-04-17T06:20:07.422240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile268.05
Q1676.57
median1244.44
Q34428.05
95-th percentile24562.365
Maximum53782.82
Range53782.72
Interquartile range (IQR)3751.48

Descriptive statistics

Standard deviation11186.112
Coefficient of variation (CV)2.0907329
Kurtosis12.437799
Mean5350.3307
Median Absolute Deviation (MAD)816.96
Skewness3.504413
Sum246115.21
Variance1.251291 × 108
MonotonicityNot monotonic
2024-04-17T06:20:07.523496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
4314.98 1
 
1.2%
449.54 1
 
1.2%
4465.74 1
 
1.2%
5672.04 1
 
1.2%
4981.48 1
 
1.2%
573.91 1
 
1.2%
3243.02 1
 
1.2%
979.17 1
 
1.2%
15067.3 1
 
1.2%
15589.38 1
 
1.2%
Other values (36) 36
42.4%
(Missing) 39
45.9%
ValueCountFrequency (%)
0.1 1
1.2%
105.0 1
1.2%
265.0 1
1.2%
277.2 1
1.2%
405.42 1
1.2%
449.54 1
1.2%
470.8 1
1.2%
544.0 1
1.2%
573.91 1
1.2%
587.08 1
1.2%
ValueCountFrequency (%)
53782.82 1
1.2%
49706.0 1
1.2%
27553.36 1
1.2%
15589.38 1
1.2%
15067.3 1
1.2%
8993.58 1
1.2%
7425.0 1
1.2%
5672.04 1
1.2%
5207.01 1
1.2%
4981.48 1
1.2%

회원모집총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

Unnamed: 37
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
01수영장업10_35_01_P3320000CDFH330101200400000120040409<NA>4취소/말소/만료/정지/중지35직권말소20150831<NA><NA><NA>331-4186<NA>616854부산광역시 북구 화명동 1130-15번지부산광역시 북구 금곡대로 230 (화명동)<NA>금용레포츠타운 수영장20150831091038I2018-08-31 23:59:59.0<NA>383196.567561194017.9636수영장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
12수영장업10_35_01_P3320000CDFH330101199600000119960511<NA>4취소/말소/만료/정지/중지35직권말소20190203<NA><NA><NA>051-333-5594<NA>616751부산광역시 북구 구포동 1103-2번지 구포현대아파트 상가 지하2층 1호부산광역시 북구 백양대로 1003, 상가동 지하2층 1호 (구포동)46651구포현대수영장20200203140257U2020-02-05 02:40:00.0<NA>381432.330084190402.183263수영장업사립<NA><NA><NA><NA><NA><NA><NA><NA>
23수영장업10_35_01_P3350000CDFH330101199400000219940514<NA>4취소/말소/만료/정지/중지35직권말소20140704<NA><NA><NA>070-7431-0015<NA>609804부산광역시 금정구 구서동 203-5번지 3층, 5층부산광역시 금정구 구서중앙로15번길 20 (구서동,3층, 5층)<NA>승산수영장20140704114014I2018-08-31 23:59:59.0<NA>390057.531835196950.450593수영장업사립<NA><NA>12595.0<NA><NA><NA><NA>
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67수영장업10_35_01_P3330000CDFH330101200200000120020430<NA>3폐업3폐업20190116<NA><NA><NA>051-743-1234<NA>612846부산광역시 해운대구 중동 1405-16번지부산광역시 해운대구 해운대해변로 292 (중동)<NA>노보텔엠배서더 부산수영장20190116095150U2019-01-18 02:40:00.0<NA>397022.97155186692.064622수영장업사립01<NA>803.0<NA><NA><NA><NA>
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89수영장업10_35_01_P3330000CDFH330101199800000319980324<NA>3폐업3폐업20191231<NA><NA><NA>051-740-0404<NA>612821부산광역시 해운대구 우동 651-2번지부산광역시 해운대구 해운대해변로 217 (우동)48093소수영장20191230174957U2020-01-01 02:40:00.0<NA>396311.47837186563.963574수영장업사립<NA><NA><NA>405.42<NA><NA><NA><NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
7576수영장업10_35_01_P3290000CDFH330101200000000120000426<NA>1영업/정상13영업중<NA><NA><NA><NA>605-5197<NA>614871부산광역시 부산진구 초읍동 43-1부산광역시 부산진구 성지곡로 15 (초읍동)47100시민생활체육센터20201224085047U2020-12-26 02:40:00.0<NA>386348.186505189119.367725수영장업사립Y<NA><NA>2782.57<NA><NA><NA><NA>
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7778수영장업10_35_01_P3370000CDFH330101200500000120050310<NA>1영업/정상13영업중<NA><NA><NA><NA>051-757-0101<NA>611817부산광역시 연제구 연산동 420-3번지 (6층)부산광역시 연제구 연안로 25 (연산동)47567대영 스포렉스20180803153701I2018-08-31 23:59:59.0<NA>391823.034521189881.981107수영장업사립Y<NA><NA><NA><NA><NA><NA><NA>
7879수영장업10_35_01_P3370000CDFH330101202000000120200417<NA>1영업/정상13영업중<NA><NA><NA><NA>051-852-1141<NA><NA>부산광역시 연제구 거제동 577-1번지 연제그린타워부산광역시 연제구 거제천로87번길 30, 지하1층 (거제동, 연제그린타워)47543더 퍼스트 수영장20200417131108I2020-04-19 00:23:21.0<NA>388720.82832189073.142541수영장업사립<NA>2<NA><NA><NA><NA><NA><NA>
7980수영장업10_35_01_P3300000CDFH330101202000000220201127<NA>1영업/정상13영업중<NA><NA><NA><NA>051-925-0909<NA><NA>부산광역시 동래구 온천동 1834 동래 지웰부산광역시 동래구 쇠미로 197, 104동 지하1층 101~103호 (온천동, 동래 지웰)47869지니키즈스윔스쿨20201127111412I2020-11-29 00:23:08.0<NA><NA><NA>수영장업사립<NA><NA><NA>844.72<NA><NA><NA><NA>
8081수영장업10_35_01_P3300000CDFH330101201500000120150807<NA>1영업/정상13영업중<NA><NA><NA><NA>051 524 0321<NA><NA>부산광역시 동래구 낙민동 84-8번지 보림프라자 지1층 108호부산광역시 동래구 안남로 23, 지1층 108호 (낙민동, 보림프라자)47892키즈스플래쉬(부산본점)20200409102229U2020-04-11 02:40:00.0<NA>390724.427857190387.205145수영장업사립<NA>118993.58<NA><NA><NA><NA>
8182수영장업10_35_01_P3300000CDFH330101201700000120170918<NA>1영업/정상13영업중<NA><NA><NA><NA>051-505-1212<NA><NA>부산광역시 동래구 사직동 74-18번지부산광역시 동래구 석사로18번길 41 (사직동)47867망고키즈수영장(사직점)20170918162726I2018-08-31 23:59:59.0<NA>387839.948218190632.136095수영장업사립Y1<NA><NA><NA><NA><NA><NA>
8283수영장업10_35_01_P3300000CDFH330101202000000120200413<NA>1영업/정상13영업중<NA><NA><NA><NA>051-525-7707<NA><NA>부산광역시 동래구 낙민동 90-4번지 B동부산광역시 동래구 안남로 32, B동 (낙민동)47903골드키즈20200413115148I2020-04-15 00:23:21.0<NA>390784.352952190320.060057수영장업사립<NA>1<NA><NA><NA><NA><NA><NA>
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