Overview

Dataset statistics

Number of variables38
Number of observations132
Missing cells1295
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.4 KiB
Average record size in memory329.0 B

Variable types

Numeric10
Categorical15
Text5
Unsupported8

Dataset

Description2021-02-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123172

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
문화체육업종명 has constant value ""Constant
공사립구분명 has constant value ""Constant
휴업시작일자 is highly imbalanced (93.6%)Imbalance
휴업종료일자 is highly imbalanced (93.6%)Imbalance
데이터갱신일자 is highly imbalanced (55.0%)Imbalance
지도자수 is highly imbalanced (88.7%)Imbalance
인허가취소일자 has 132 (100.0%) missing valuesMissing
폐업일자 has 46 (34.8%) missing valuesMissing
재개업일자 has 132 (100.0%) missing valuesMissing
소재지전화 has 27 (20.5%) missing valuesMissing
소재지면적 has 132 (100.0%) missing valuesMissing
소재지우편번호 has 28 (21.2%) missing valuesMissing
도로명전체주소 has 9 (6.8%) missing valuesMissing
도로명우편번호 has 67 (50.8%) missing valuesMissing
업태구분명 has 132 (100.0%) missing valuesMissing
좌표정보(x) has 2 (1.5%) missing valuesMissing
좌표정보(y) has 2 (1.5%) missing valuesMissing
건축물연면적 has 58 (43.9%) missing valuesMissing
회원모집총인원 has 132 (100.0%) missing valuesMissing
세부업종명 has 132 (100.0%) missing valuesMissing
법인명 has 132 (100.0%) missing valuesMissing
Unnamed: 37 has 132 (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
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 started2024-04-22 00:21:26.975484
Analysis finished2024-04-22 00:21:27.397545
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.5
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:27.467548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.55
Q133.75
median66.5
Q399.25
95-th percentile125.45
Maximum132
Range131
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation38.249183
Coefficient of variation (CV)0.57517568
Kurtosis-1.2
Mean66.5
Median Absolute Deviation (MAD)33
Skewness0
Sum8778
Variance1463
MonotonicityStrictly increasing
2024-04-22T09:21:27.618654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
85 1
 
0.8%
99 1
 
0.8%
98 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
Other values (122) 122
92.4%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
132 1
0.8%
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
무도학원업
132 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도학원업 132
100.0%

Length

2024-04-22T09:21:27.763586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:27.858639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도학원업 132
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
10_33_02_P
132 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10_33_02_P
2nd row10_33_02_P
3rd row10_33_02_P
4th row10_33_02_P
5th row10_33_02_P

Common Values

ValueCountFrequency (%)
10_33_02_P 132
100.0%

Length

2024-04-22T09:21:27.955743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:28.049955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_33_02_p 132
100.0%

개방자치단체코드
Real number (ℝ)

Distinct14
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3313409.1
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:28.155155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3300000
Q33340000
95-th percentile3380000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation37453.881
Coefficient of variation (CV)0.01130373
Kurtosis-0.70699857
Mean3313409.1
Median Absolute Deviation (MAD)30000
Skewness0.27474462
Sum4.3737 × 108
Variance1.4027932 × 109
MonotonicityNot monotonic
2024-04-22T09:21:28.275513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3300000 24
18.2%
3290000 21
15.9%
3350000 15
11.4%
3320000 12
9.1%
3270000 12
9.1%
3250000 10
7.6%
3340000 10
7.6%
3370000 7
 
5.3%
3380000 7
 
5.3%
3330000 5
 
3.8%
Other values (4) 9
 
6.8%
ValueCountFrequency (%)
3250000 10
7.6%
3270000 12
9.1%
3280000 3
 
2.3%
3290000 21
15.9%
3300000 24
18.2%
3310000 3
 
2.3%
3320000 12
9.1%
3330000 5
 
3.8%
3340000 10
7.6%
3350000 15
11.4%
ValueCountFrequency (%)
3400000 1
 
0.8%
3390000 2
 
1.5%
3380000 7
 
5.3%
3370000 7
 
5.3%
3350000 15
11.4%
3340000 10
7.6%
3330000 5
 
3.8%
3320000 12
9.1%
3310000 3
 
2.3%
3300000 24
18.2%

관리번호
Text

Distinct57
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:21:28.466710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2640
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)22.0%

Sample

1st rowCDFH3301111994000001
2nd rowCDFH3301112001000001
3rd rowCDFH3301112001000002
4th rowCDFH3301112008000001
5th rowCDFH3301111980000001
ValueCountFrequency (%)
cdfh3301112001000001 9
 
6.8%
cdfh3301112002000001 8
 
6.1%
cdfh3301111999000001 7
 
5.3%
cdfh3301112013000001 6
 
4.5%
cdfh3301112001000002 5
 
3.8%
cdfh3301111998000001 5
 
3.8%
cdfh3301112000000001 5
 
3.8%
cdfh3301112010000001 4
 
3.0%
cdfh3301112003000001 4
 
3.0%
cdfh3301112009000001 4
 
3.0%
Other values (47) 75
56.8%
2024-04-22T09:21:28.780200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 981
37.2%
1 572
21.7%
3 293
 
11.1%
2 144
 
5.5%
C 132
 
5.0%
D 132
 
5.0%
F 132
 
5.0%
H 132
 
5.0%
9 80
 
3.0%
8 15
 
0.6%
Other values (4) 27
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2112
80.0%
Uppercase Letter 528
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 981
46.4%
1 572
27.1%
3 293
 
13.9%
2 144
 
6.8%
9 80
 
3.8%
8 15
 
0.7%
5 9
 
0.4%
4 8
 
0.4%
6 6
 
0.3%
7 4
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
C 132
25.0%
D 132
25.0%
F 132
25.0%
H 132
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2112
80.0%
Latin 528
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 981
46.4%
1 572
27.1%
3 293
 
13.9%
2 144
 
6.8%
9 80
 
3.8%
8 15
 
0.7%
5 9
 
0.4%
4 8
 
0.4%
6 6
 
0.3%
7 4
 
0.2%
Latin
ValueCountFrequency (%)
C 132
25.0%
D 132
25.0%
F 132
25.0%
H 132
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 981
37.2%
1 572
21.7%
3 293
 
11.1%
2 144
 
5.5%
C 132
 
5.0%
D 132
 
5.0%
F 132
 
5.0%
H 132
 
5.0%
9 80
 
3.0%
8 15
 
0.6%
Other values (4) 27
 
1.0%

인허가일자
Real number (ℝ)

Distinct122
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20040933
Minimum19800102
Maximum20200929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:28.923026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19800102
5-th percentile19930586
Q120000600
median20020312
Q320093301
95-th percentile20164848
Maximum20200929
Range400827
Interquartile range (IQR)92701.25

Descriptive statistics

Standard deviation74236.37
Coefficient of variation (CV)0.0037042373
Kurtosis-0.0405284
Mean20040933
Median Absolute Deviation (MAD)39587.5
Skewness0.16940968
Sum2.6454031 × 109
Variance5.5110386 × 109
MonotonicityNot monotonic
2024-04-22T09:21:29.062915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010517 4
 
3.0%
20030210 4
 
3.0%
20010814 2
 
1.5%
20010207 2
 
1.5%
19990429 2
 
1.5%
19990902 2
 
1.5%
20160318 1
 
0.8%
20200417 1
 
0.8%
20000131 1
 
0.8%
20021106 1
 
0.8%
Other values (112) 112
84.8%
ValueCountFrequency (%)
19800102 1
0.8%
19910904 1
0.8%
19911125 1
0.8%
19920226 1
0.8%
19920521 1
0.8%
19930409 1
0.8%
19930426 1
0.8%
19930716 1
0.8%
19930804 1
0.8%
19931016 1
0.8%
ValueCountFrequency (%)
20200929 1
0.8%
20200921 1
0.8%
20200417 1
0.8%
20190311 1
0.8%
20181101 1
0.8%
20181018 1
0.8%
20170125 1
0.8%
20160531 1
0.8%
20160519 1
0.8%
20160512 1
0.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

영업상태구분코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
88 
1
42 
2
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 88
66.7%
1 42
31.8%
2 1
 
0.8%
4 1
 
0.8%

Length

2024-04-22T09:21:29.206548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:29.303812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 88
66.7%
1 42
31.8%
2 1
 
0.8%
4 1
 
0.8%

영업상태명
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
88 
영업/정상
42 
휴업
 
1
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length3.0454545
Min length2

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 88
66.7%
영업/정상 42
31.8%
휴업 1
 
0.8%
취소/말소/만료/정지/중지 1
 
0.8%

Length

2024-04-22T09:21:29.420302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:29.525058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
66.7%
영업/정상 42
31.8%
휴업 1
 
0.8%
취소/말소/만료/정지/중지 1
 
0.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
88 
13
42 
2
 
1
35
 
1

Length

Max length2
Median length1
Mean length1.3257576
Min length1

Unique

Unique2 ?
Unique (%)1.5%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 88
66.7%
13 42
31.8%
2 1
 
0.8%
35 1
 
0.8%

Length

2024-04-22T09:21:29.627445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:29.725608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 88
66.7%
13 42
31.8%
2 1
 
0.8%
35 1
 
0.8%

상세영업상태명
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
88 
영업중
42 
휴업
 
1
직권말소
 
1

Length

Max length4
Median length2
Mean length2.3333333
Min length2

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 88
66.7%
영업중 42
31.8%
휴업 1
 
0.8%
직권말소 1
 
0.8%

Length

2024-04-22T09:21:29.862487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:29.979107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 88
66.7%
영업중 42
31.8%
휴업 1
 
0.8%
직권말소 1
 
0.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct83
Distinct (%)96.5%
Missing46
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean20118548
Minimum19960426
Maximum20201224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:30.096192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19960426
5-th percentile20040374
Q120070578
median20115656
Q320178184
95-th percentile20200291
Maximum20201224
Range240798
Interquartile range (IQR)107607

Descriptive statistics

Standard deviation59201.539
Coefficient of variation (CV)0.0029426348
Kurtosis-0.99990659
Mean20118548
Median Absolute Deviation (MAD)54796
Skewness-0.21286755
Sum1.7301951 × 109
Variance3.5048222 × 109
MonotonicityNot monotonic
2024-04-22T09:21:30.250963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20091023 2
 
1.5%
20130603 2
 
1.5%
20070517 2
 
1.5%
20140225 1
 
0.8%
20070726 1
 
0.8%
20000509 1
 
0.8%
20180504 1
 
0.8%
20041101 1
 
0.8%
19960426 1
 
0.8%
20050712 1
 
0.8%
Other values (73) 73
55.3%
(Missing) 46
34.8%
ValueCountFrequency (%)
19960426 1
0.8%
20000509 1
0.8%
20020831 1
0.8%
20030324 1
0.8%
20040331 1
0.8%
20040504 1
0.8%
20040513 1
0.8%
20041101 1
0.8%
20041201 1
0.8%
20050103 1
0.8%
ValueCountFrequency (%)
20201224 1
0.8%
20200907 1
0.8%
20200720 1
0.8%
20200326 1
0.8%
20200320 1
0.8%
20200203 1
0.8%
20191112 1
0.8%
20190816 1
0.8%
20190711 1
0.8%
20190611 1
0.8%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
131 
20130318
 
1

Length

Max length8
Median length4
Mean length4.030303
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row20130318
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 131
99.2%
20130318 1
 
0.8%

Length

2024-04-22T09:21:30.380109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:30.482143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
99.2%
20130318 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
131 
20181229
 
1

Length

Max length8
Median length4
Mean length4.030303
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row20181229
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 131
99.2%
20181229 1
 
0.8%

Length

2024-04-22T09:21:30.591764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:30.709906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
99.2%
20181229 1
 
0.8%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

소재지전화
Text

MISSING 

Distinct102
Distinct (%)97.1%
Missing27
Missing (%)20.5%
Memory size1.2 KiB
2024-04-22T09:21:30.946110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.028571
Min length8

Characters and Unicode

Total characters1053
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)94.3%

Sample

1st row336-3150
2nd row051-245-8147
3rd row051-253-3372
4th row051-245-6984
5th row051-245-6984
ValueCountFrequency (%)
633-0588 2
 
1.9%
051-245-6984 2
 
1.9%
051-866-8018 2
 
1.9%
051-803-0502 1
 
1.0%
336-3150 1
 
1.0%
051-244-4200 1
 
1.0%
051-805-5550 1
 
1.0%
722-5511 1
 
1.0%
051-323-6677 1
 
1.0%
051-326-7675 1
 
1.0%
Other values (92) 92
87.6%
2024-04-22T09:21:31.322131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 170
16.1%
- 155
14.7%
0 115
10.9%
1 104
9.9%
7 88
8.4%
2 83
7.9%
8 77
7.3%
3 76
7.2%
6 69
6.6%
4 67
 
6.4%
Other values (2) 49
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 895
85.0%
Dash Punctuation 155
 
14.7%
Close Punctuation 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 170
19.0%
0 115
12.8%
1 104
11.6%
7 88
9.8%
2 83
9.3%
8 77
8.6%
3 76
8.5%
6 69
7.7%
4 67
 
7.5%
9 46
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1053
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 170
16.1%
- 155
14.7%
0 115
10.9%
1 104
9.9%
7 88
8.4%
2 83
7.9%
8 77
7.3%
3 76
7.2%
6 69
6.6%
4 67
 
6.4%
Other values (2) 49
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 170
16.1%
- 155
14.7%
0 115
10.9%
1 104
9.9%
7 88
8.4%
2 83
7.9%
8 77
7.3%
3 76
7.2%
6 69
6.6%
4 67
 
6.4%
Other values (2) 49
 
4.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)58.7%
Missing28
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean609847.89
Minimum600044
Maximum619903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:31.477942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600044
5-th percentile600958.1
Q1607804
median609830
Q3613880.25
95-th percentile616801
Maximum619903
Range19859
Interquartile range (IQR)6076.25

Descriptive statistics

Standard deviation5055.9849
Coefficient of variation (CV)0.0082905671
Kurtosis-0.86183426
Mean609847.89
Median Absolute Deviation (MAD)3979
Skewness-0.22080884
Sum63424181
Variance25562983
MonotonicityNot monotonic
2024-04-22T09:21:31.632600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
616801 10
 
7.6%
607824 6
 
4.5%
607804 4
 
3.0%
609830 4
 
3.0%
601803 4
 
3.0%
607831 4
 
3.0%
604815 3
 
2.3%
611822 3
 
2.3%
607833 3
 
2.3%
609842 2
 
1.5%
Other values (51) 61
46.2%
(Missing) 28
21.2%
ValueCountFrequency (%)
600044 2
1.5%
600046 1
 
0.8%
600805 1
 
0.8%
600807 1
 
0.8%
600809 1
 
0.8%
601803 4
3.0%
601807 1
 
0.8%
601827 2
1.5%
601838 1
 
0.8%
604021 1
 
0.8%
ValueCountFrequency (%)
619903 1
 
0.8%
617808 1
 
0.8%
617806 1
 
0.8%
616837 1
 
0.8%
616801 10
7.6%
614876 1
 
0.8%
614870 1
 
0.8%
614863 1
 
0.8%
614850 1
 
0.8%
614843 1
 
0.8%

소재지전체주소
Text

Distinct128
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:21:31.989175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length22.295455
Min length18

Characters and Unicode

Total characters2943
Distinct characters86
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)94.7%

Sample

1st row부산광역시 북구 구포동 599-5번지
2nd row부산광역시 중구 부평동2가 64-2번지
3rd row부산광역시 중구 부평동3가 79-14번지
4th row부산광역시 중구 부평동1가 39-18번지 4층
5th row부산광역시 중구 부평동1가 39-18번지
ValueCountFrequency (%)
부산광역시 132
23.1%
동래구 24
 
4.2%
부산진구 21
 
3.7%
3층 20
 
3.5%
금정구 15
 
2.6%
온천동 13
 
2.3%
북구 12
 
2.1%
구포동 12
 
2.1%
동구 12
 
2.1%
중구 10
 
1.7%
Other values (178) 301
52.6%
2024-04-22T09:21:32.463479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
440
 
15.0%
부 171
 
5.8%
동 167
 
5.7%
산 160
 
5.4%
구 146
 
5.0%
광 137
 
4.7%
역 132
 
4.5%
시 132
 
4.5%
지 124
 
4.2%
- 123
 
4.2%
Other values (76) 1211
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1738
59.1%
Decimal Number 630
 
21.4%
Space Separator 440
 
15.0%
Dash Punctuation 123
 
4.2%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 171
9.8%
동 167
9.6%
산 160
 
9.2%
구 146
 
8.4%
광 137
 
7.9%
역 132
 
7.6%
시 132
 
7.6%
지 124
 
7.1%
번 122
 
7.0%
층 41
 
2.4%
Other values (62) 406
23.4%
Decimal Number
ValueCountFrequency (%)
1 96
15.2%
2 94
14.9%
3 83
13.2%
4 68
10.8%
6 63
10.0%
7 52
8.3%
5 51
8.1%
0 46
7.3%
8 39
6.2%
9 38
 
6.0%
Space Separator
ValueCountFrequency (%)
440
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1738
59.1%
Common 1205
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 171
9.8%
동 167
9.6%
산 160
 
9.2%
구 146
 
8.4%
광 137
 
7.9%
역 132
 
7.6%
시 132
 
7.6%
지 124
 
7.1%
번 122
 
7.0%
층 41
 
2.4%
Other values (62) 406
23.4%
Common
ValueCountFrequency (%)
440
36.5%
- 123
 
10.2%
1 96
 
8.0%
2 94
 
7.8%
3 83
 
6.9%
4 68
 
5.6%
6 63
 
5.2%
7 52
 
4.3%
5 51
 
4.2%
0 46
 
3.8%
Other values (4) 89
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1738
59.1%
ASCII 1205
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
440
36.5%
- 123
 
10.2%
1 96
 
8.0%
2 94
 
7.8%
3 83
 
6.9%
4 68
 
5.6%
6 63
 
5.2%
7 52
 
4.3%
5 51
 
4.2%
0 46
 
3.8%
Other values (4) 89
 
7.4%
Hangul
ValueCountFrequency (%)
부 171
9.8%
동 167
9.6%
산 160
 
9.2%
구 146
 
8.4%
광 137
 
7.9%
역 132
 
7.6%
시 132
 
7.6%
지 124
 
7.1%
번 122
 
7.0%
층 41
 
2.4%
Other values (62) 406
23.4%

도로명전체주소
Text

MISSING 

Distinct121
Distinct (%)98.4%
Missing9
Missing (%)6.8%
Memory size1.2 KiB
2024-04-22T09:21:32.794097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length33
Mean length27.406504
Min length22

Characters and Unicode

Total characters3371
Distinct characters123
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

Unique119 ?
Unique (%)96.7%

Sample

1st row부산광역시 북구 구포시장길 1 (구포동)
2nd row부산광역시 중구 흑교로 10-1 (부평동2가)
3rd row부산광역시 중구 보수대로44번길 26 (부평동3가)
4th row부산광역시 중구 광복로 14-1 (부평동1가)
5th row부산광역시 중구 광복로 14-1 (부평동1가)
ValueCountFrequency (%)
부산광역시 123
 
18.8%
동래구 24
 
3.7%
부산진구 19
 
2.9%
3층 17
 
2.6%
금정구 15
 
2.3%
온천동 13
 
2.0%
동구 12
 
1.8%
북구 11
 
1.7%
구포동 11
 
1.7%
부전동 9
 
1.4%
Other values (230) 399
61.1%
2024-04-22T09:21:33.252594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
579
 
17.2%
동 187
 
5.5%
부 162
 
4.8%
산 149
 
4.4%
구 142
 
4.2%
광 131
 
3.9%
시 126
 
3.7%
( 125
 
3.7%
) 125
 
3.7%
역 123
 
3.6%
Other values (113) 1522
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1954
58.0%
Space Separator 579
 
17.2%
Decimal Number 513
 
15.2%
Open Punctuation 125
 
3.7%
Close Punctuation 125
 
3.7%
Other Punctuation 46
 
1.4%
Dash Punctuation 29
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 187
 
9.6%
부 162
 
8.3%
산 149
 
7.6%
구 142
 
7.3%
광 131
 
6.7%
시 126
 
6.4%
역 123
 
6.3%
로 120
 
6.1%
길 60
 
3.1%
번 57
 
2.9%
Other values (98) 697
35.7%
Decimal Number
ValueCountFrequency (%)
1 121
23.6%
2 67
13.1%
3 65
12.7%
4 53
10.3%
6 42
 
8.2%
5 42
 
8.2%
9 39
 
7.6%
7 37
 
7.2%
8 26
 
5.1%
0 21
 
4.1%
Space Separator
ValueCountFrequency (%)
579
100.0%
Open Punctuation
ValueCountFrequency (%)
( 125
100.0%
Close Punctuation
ValueCountFrequency (%)
) 125
100.0%
Other Punctuation
ValueCountFrequency (%)
, 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1954
58.0%
Common 1417
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 187
 
9.6%
부 162
 
8.3%
산 149
 
7.6%
구 142
 
7.3%
광 131
 
6.7%
시 126
 
6.4%
역 123
 
6.3%
로 120
 
6.1%
길 60
 
3.1%
번 57
 
2.9%
Other values (98) 697
35.7%
Common
ValueCountFrequency (%)
579
40.9%
( 125
 
8.8%
) 125
 
8.8%
1 121
 
8.5%
2 67
 
4.7%
3 65
 
4.6%
4 53
 
3.7%
, 46
 
3.2%
6 42
 
3.0%
5 42
 
3.0%
Other values (5) 152
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1954
58.0%
ASCII 1417
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
579
40.9%
( 125
 
8.8%
) 125
 
8.8%
1 121
 
8.5%
2 67
 
4.7%
3 65
 
4.6%
4 53
 
3.7%
, 46
 
3.2%
6 42
 
3.0%
5 42
 
3.0%
Other values (5) 152
 
10.7%
Hangul
ValueCountFrequency (%)
동 187
 
9.6%
부 162
 
8.3%
산 149
 
7.6%
구 142
 
7.3%
광 131
 
6.7%
시 126
 
6.4%
역 123
 
6.3%
로 120
 
6.1%
길 60
 
3.1%
번 57
 
2.9%
Other values (98) 697
35.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)73.8%
Missing67
Missing (%)50.8%
Infinite0
Infinite (%)0.0%
Mean134569.75
Minimum46243
Maximum616801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:33.386263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46243
5-th percentile46321
Q147254
median47813
Q348977
95-th percentile614856.4
Maximum616801
Range570558
Interquartile range (IQR)1723

Descriptive statistics

Standard deviation205225.22
Coefficient of variation (CV)1.5250472
Kurtosis1.9192304
Mean134569.75
Median Absolute Deviation (MAD)922
Skewness1.9647576
Sum8747034
Variance4.2117391 × 1010
MonotonicityNot monotonic
2024-04-22T09:21:33.513900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
46321 4
 
3.0%
47813 4
 
3.0%
616801 3
 
2.3%
47254 2
 
1.5%
47323 2
 
1.5%
47246 2
 
1.5%
47708 2
 
1.5%
47710 2
 
1.5%
48977 2
 
1.5%
48735 2
 
1.5%
Other values (38) 40
30.3%
(Missing) 67
50.8%
ValueCountFrequency (%)
46243 1
 
0.8%
46321 4
3.0%
46501 1
 
0.8%
46502 1
 
0.8%
46580 1
 
0.8%
46581 1
 
0.8%
47192 1
 
0.8%
47213 1
 
0.8%
47246 2
1.5%
47251 1
 
0.8%
ValueCountFrequency (%)
616801 3
2.3%
614863 1
 
0.8%
614830 1
 
0.8%
612847 1
 
0.8%
611822 1
 
0.8%
609830 1
 
0.8%
604815 1
 
0.8%
601827 1
 
0.8%
49311 1
 
0.8%
49053 1
 
0.8%

사업장명
Text

Distinct109
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-22T09:21:33.727752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.4924242
Min length3

Characters and Unicode

Total characters989
Distinct characters152
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)71.2%

Sample

1st row한국경기무도학원
2nd row황실무도학원
3rd row현대 무도학원
4th row중앙무도학원
5th row중앙무도학원
ValueCountFrequency (%)
댄스스포츠 19
 
11.0%
국제무도학원 5
 
2.9%
무도학원 5
 
2.9%
뉴욕무도학원 3
 
1.7%
제일무도학원 3
 
1.7%
현대무도학원 3
 
1.7%
한국댄스스포츠학원 3
 
1.7%
댄스 3
 
1.7%
부산무도학원 3
 
1.7%
현대 3
 
1.7%
Other values (113) 123
71.1%
2024-04-22T09:21:34.080156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 119
 
12.0%
원 88
 
8.9%
학 87
 
8.8%
도 76
 
7.7%
무 75
 
7.6%
포 54
 
5.5%
댄 54
 
5.5%
츠 51
 
5.2%
41
 
4.1%
대 15
 
1.5%
Other values (142) 329
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 942
95.2%
Space Separator 41
 
4.1%
Uppercase Letter 3
 
0.3%
Lowercase Letter 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 119
 
12.6%
원 88
 
9.3%
학 87
 
9.2%
도 76
 
8.1%
무 75
 
8.0%
포 54
 
5.7%
댄 54
 
5.7%
츠 51
 
5.4%
대 15
 
1.6%
국 12
 
1.3%
Other values (135) 311
33.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
C 1
33.3%
H 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
n 1
50.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 942
95.2%
Common 42
 
4.2%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 119
 
12.6%
원 88
 
9.3%
학 87
 
9.2%
도 76
 
8.1%
무 75
 
8.0%
포 54
 
5.7%
댄 54
 
5.7%
츠 51
 
5.4%
대 15
 
1.6%
국 12
 
1.3%
Other values (135) 311
33.0%
Latin
ValueCountFrequency (%)
K 1
20.0%
C 1
20.0%
H 1
20.0%
a 1
20.0%
n 1
20.0%
Common
ValueCountFrequency (%)
41
97.6%
& 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 942
95.2%
ASCII 47
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 119
 
12.6%
원 88
 
9.3%
학 87
 
9.2%
도 76
 
8.1%
무 75
 
8.0%
포 54
 
5.7%
댄 54
 
5.7%
츠 51
 
5.4%
대 15
 
1.6%
국 12
 
1.3%
Other values (135) 311
33.0%
ASCII
ValueCountFrequency (%)
41
87.2%
K 1
 
2.1%
& 1
 
2.1%
C 1
 
2.1%
H 1
 
2.1%
a 1
 
2.1%
n 1
 
2.1%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0139713 × 1013
Minimum2.0030211 × 1013
Maximum2.0201228 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:34.495975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030211 × 1013
5-th percentile2.0041204 × 1013
Q12.0107786 × 1013
median2.0151064 × 1013
Q32.0181153 × 1013
95-th percentile2.0200913 × 1013
Maximum2.0201228 × 1013
Range1.7101704 × 1011
Interquartile range (IQR)7.3367023 × 1010

Descriptive statistics

Standard deviation5.1041367 × 1010
Coefficient of variation (CV)0.0025343641
Kurtosis-0.92001609
Mean2.0139713 × 1013
Median Absolute Deviation (MAD)3.9750968 × 1010
Skewness-0.51910125
Sum2.6584421 × 1015
Variance2.6052211 × 1021
MonotonicityNot monotonic
2024-04-22T09:21:34.653121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171218085233 1
 
0.8%
20060106092442 1
 
0.8%
20180322154723 1
 
0.8%
20190924101239 1
 
0.8%
20191101173124 1
 
0.8%
20200929115730 1
 
0.8%
20190610133436 1
 
0.8%
20201114145353 1
 
0.8%
20201114145242 1
 
0.8%
20110111134616 1
 
0.8%
Other values (122) 122
92.4%
ValueCountFrequency (%)
20030211113618 1
0.8%
20030213101713 1
0.8%
20030324153829 1
0.8%
20030624095015 1
0.8%
20040505114457 1
0.8%
20040513133647 1
0.8%
20041201100418 1
0.8%
20041207140034 1
0.8%
20050712121944 1
0.8%
20060106092442 1
0.8%
ValueCountFrequency (%)
20201228151015 1
0.8%
20201119162739 1
0.8%
20201114145353 1
0.8%
20201114145242 1
0.8%
20201026085347 1
0.8%
20200929115730 1
0.8%
20200921112245 1
0.8%
20200907134812 1
0.8%
20200901205440 1
0.8%
20200720160706 1
0.8%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
97 
U
35 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 97
73.5%
U 35
 
26.5%

Length

2024-04-22T09:21:34.801642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:34.899226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 97
73.5%
u 35
 
26.5%

데이터갱신일자
Categorical

IMBALANCE 

Distinct38
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018-08-31 23:59:59.0
94 
2020-11-17 02:40:00.0
 
2
2018-10-25 02:37:47.0
 
1
2019-03-16 02:40:00.0
 
1
2020-03-22 02:40:00.0
 
1
Other values (33)
33 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique36 ?
Unique (%)27.3%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-11-29 02:40:00.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 94
71.2%
2020-11-17 02:40:00.0 2
 
1.5%
2018-10-25 02:37:47.0 1
 
0.8%
2019-03-16 02:40:00.0 1
 
0.8%
2020-03-22 02:40:00.0 1
 
0.8%
2020-07-22 02:40:00.0 1
 
0.8%
2020-09-09 02:40:00.0 1
 
0.8%
2019-03-22 02:40:00.0 1
 
0.8%
2019-11-14 02:40:00.0 1
 
0.8%
2019-08-18 02:40:00.0 1
 
0.8%
Other values (28) 28
 
21.2%

Length

2024-04-22T09:21:35.006585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 95
36.0%
2018-08-31 94
35.6%
02:40:00.0 32
 
12.1%
2020-11-17 2
 
0.8%
00:23:11.0 2
 
0.8%
2019-09-26 1
 
0.4%
2019-03-21 1
 
0.4%
2019-08-15 1
 
0.4%
2018-11-21 1
 
0.4%
04:00:00.0 1
 
0.4%
Other values (34) 34
 
12.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)90.8%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean387746.12
Minimum379146.46
Maximum401585.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:35.138629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum379146.46
5-th percentile380647.47
Q1384841.2
median387871.61
Q3389963.88
95-th percentile392685.44
Maximum401585.95
Range22439.495
Interquartile range (IQR)5122.679

Descriptive statistics

Standard deviation4083.2655
Coefficient of variation (CV)0.010530771
Kurtosis0.28608296
Mean387746.12
Median Absolute Deviation (MAD)2288.8869
Skewness-0.095178632
Sum50406996
Variance16673057
MonotonicityNot monotonic
2024-04-22T09:21:35.296194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391771.080138565 4
 
3.0%
387580.398935417 3
 
2.3%
389568.327459605 2
 
1.5%
384723.35613516 2
 
1.5%
382355.836275811 2
 
1.5%
391826.441352442 2
 
1.5%
381859.396768544 2
 
1.5%
387624.989707084 2
 
1.5%
387667.20808376 2
 
1.5%
387304.500984597 1
 
0.8%
Other values (108) 108
81.8%
(Missing) 2
 
1.5%
ValueCountFrequency (%)
379146.456410293 1
0.8%
379210.312595397 1
0.8%
379389.422681416 1
0.8%
379471.752047664 1
0.8%
379550.273389181 1
0.8%
379779.666846195 1
0.8%
380638.299765377 1
0.8%
380658.683422044 1
0.8%
381621.468580223 1
0.8%
381622.644225725 1
0.8%
ValueCountFrequency (%)
401585.951905544 1
0.8%
396886.146092074 1
0.8%
396641.87880435 1
0.8%
394793.311822588 1
0.8%
393281.146618383 1
0.8%
393191.489741171 1
0.8%
392711.416842625 1
0.8%
392653.680879591 1
0.8%
392637.790394465 1
0.8%
392531.362181258 1
0.8%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)90.8%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean187628.59
Minimum178539.55
Maximum197615.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:35.439970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178539.55
5-th percentile179638.95
Q1184100.27
median187365.3
Q3191778.2
95-th percentile193465.69
Maximum197615.56
Range19076.015
Interquartile range (IQR)7677.9253

Descriptive statistics

Standard deviation4922.5278
Coefficient of variation (CV)0.026235489
Kurtosis-0.99934205
Mean187628.59
Median Absolute Deviation (MAD)4238.6875
Skewness-0.2701463
Sum24391717
Variance24231280
MonotonicityNot monotonic
2024-04-22T09:21:35.625984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192637.074264478 4
 
3.0%
184100.273618128 3
 
2.3%
189526.220539494 2
 
1.5%
179684.637389432 2
 
1.5%
191840.120030345 2
 
1.5%
192681.076183986 2
 
1.5%
191549.285621544 2
 
1.5%
186442.636762676 2
 
1.5%
184016.952668961 2
 
1.5%
185840.662054236 1
 
0.8%
Other values (108) 108
81.8%
(Missing) 2
 
1.5%
ValueCountFrequency (%)
178539.547977792 1
0.8%
178628.749551099 1
0.8%
178982.210578747 1
0.8%
179365.804285634 1
0.8%
179452.209734125 1
0.8%
179528.531517589 1
0.8%
179629.424200445 1
0.8%
179650.592845187 1
0.8%
179660.148759733 1
0.8%
179684.637389432 2
1.5%
ValueCountFrequency (%)
197615.562523444 1
0.8%
197525.2001613 1
0.8%
196210.526021658 1
0.8%
196108.21407121 1
0.8%
193611.791707609 1
0.8%
193546.695320942 1
0.8%
193492.400999647 1
0.8%
193433.037073686 1
0.8%
193382.27892736 1
0.8%
193363.103984833 1
0.8%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
무도학원업
132 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
무도학원업 132
100.0%

Length

2024-04-22T09:21:35.771634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:35.876816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무도학원업 132
100.0%

공사립구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
사립
132 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 132
100.0%

Length

2024-04-22T09:21:35.980131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:36.087526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 132
100.0%

보험가입여부코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
53 
Y
45 
0
23 
1
11 

Length

Max length4
Median length1
Mean length2.2045455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 53
40.2%
Y 45
34.1%
0 23
17.4%
1 11
 
8.3%

Length

2024-04-22T09:21:36.188758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:36.294145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
40.2%
y 45
34.1%
0 23
17.4%
1 11
 
8.3%

지도자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
130 
1
 
2

Length

Max length4
Median length4
Mean length3.9545455
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> 130
98.5%
1 2
 
1.5%

Length

2024-04-22T09:21:36.409969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:36.510747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
98.5%
1 2
 
1.5%

건축물동수
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
105 
1
27 

Length

Max length4
Median length4
Mean length3.3863636
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> 105
79.5%
1 27
 
20.5%

Length

2024-04-22T09:21:36.632152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:21:36.738758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 105
79.5%
1 27
 
20.5%

건축물연면적
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)94.6%
Missing58
Missing (%)43.9%
Infinite0
Infinite (%)0.0%
Mean698.15905
Minimum68.3
Maximum5273.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-22T09:21:36.848185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum68.3
5-th percentile81.588
Q1133.995
median196.44
Q3717.58
95-th percentile2742.3275
Maximum5273.11
Range5204.81
Interquartile range (IQR)583.585

Descriptive statistics

Standard deviation1053.0566
Coefficient of variation (CV)1.5083333
Kurtosis7.3422236
Mean698.15905
Median Absolute Deviation (MAD)111.055
Skewness2.6128963
Sum51663.77
Variance1108928.1
MonotonicityNot monotonic
2024-04-22T09:21:36.981373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1405.93 2
 
1.5%
166.31 2
 
1.5%
480.02 2
 
1.5%
85.5 2
 
1.5%
202.1 1
 
0.8%
104.2 1
 
0.8%
81.7 1
 
0.8%
68.3 1
 
0.8%
144.1 1
 
0.8%
290.0 1
 
0.8%
Other values (60) 60
45.5%
(Missing) 58
43.9%
ValueCountFrequency (%)
68.3 1
0.8%
68.94 1
0.8%
77.16 1
0.8%
81.38 1
0.8%
81.7 1
0.8%
85.27 1
0.8%
85.5 2
1.5%
86.79 1
0.8%
87.0 1
0.8%
87.81 1
0.8%
ValueCountFrequency (%)
5273.11 1
0.8%
4746.17 1
0.8%
3861.84 1
0.8%
2942.95 1
0.8%
2634.3 1
0.8%
2213.48 1
0.8%
2176.3 1
0.8%
1833.28 1
0.8%
1712.56 1
0.8%
1686.46 1
0.8%

회원모집총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

Unnamed: 37
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing132
Missing (%)100.0%
Memory size1.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
01무도학원업10_33_02_P3320000CDFH330111199400000119940727<NA>2휴업2휴업<NA>2013031820181229<NA>336-3150<NA>616801부산광역시 북구 구포동 599-5번지부산광역시 북구 구포시장길 1 (구포동)<NA>한국경기무도학원20171218085233I2018-08-31 23:59:59.0<NA>382384.729355191844.412093무도학원업사립<NA><NA><NA><NA><NA><NA><NA><NA>
12무도학원업10_33_02_P3250000CDFH330111200100000120010829<NA>3폐업3폐업20181127<NA><NA><NA>051-245-8147<NA><NA>부산광역시 중구 부평동2가 64-2번지부산광역시 중구 흑교로 10-1 (부평동2가)48977황실무도학원20181127100122U2018-11-29 02:40:00.0<NA>384596.243459179800.252881무도학원업사립<NA><NA><NA><NA><NA><NA><NA><NA>
23무도학원업10_33_02_P3250000CDFH330111200100000220010920<NA>3폐업3폐업20111005<NA><NA><NA>051-253-3372<NA>600809부산광역시 중구 부평동3가 79-14번지부산광역시 중구 보수대로44번길 26 (부평동3가)<NA>현대 무도학원20111005154237I2018-08-31 23:59:59.0<NA>384474.391289180059.410132무도학원업사립<NA><NA><NA><NA><NA><NA><NA><NA>
34무도학원업10_33_02_P3250000CDFH330111200800000120080828<NA>3폐업3폐업20170613<NA><NA><NA>051-245-6984<NA><NA>부산광역시 중구 부평동1가 39-18번지 4층부산광역시 중구 광복로 14-1 (부평동1가)48980중앙무도학원20170613161439I2018-08-31 23:59:59.0<NA>384723.356135179684.637389무도학원업사립<NA><NA><NA>336.5<NA><NA><NA><NA>
45무도학원업10_33_02_P3250000CDFH330111198000000119800102<NA>3폐업3폐업20071011<NA><NA><NA>051-245-6984<NA>600805부산광역시 중구 부평동1가 39-18번지부산광역시 중구 광복로 14-1 (부평동1가)<NA>중앙무도학원20071011174605I2018-08-31 23:59:59.0<NA>384723.356135179684.637389무도학원업사립0<NA><NA><NA><NA><NA><NA><NA>
56무도학원업10_33_02_P3250000CDFH330111199800000119980624<NA>3폐업3폐업20030324<NA><NA><NA>051-255-0022<NA>600046부산광역시 중구 남포동6가 1155번지<NA><NA>동명무도학원20030324153829I2018-08-31 23:59:59.0<NA><NA><NA>무도학원업사립0<NA><NA>350.3<NA><NA><NA><NA>
67무도학원업10_33_02_P3250000CDFH330111199900000119990902<NA>3폐업3폐업20060530<NA><NA><NA>051-248-0856<NA>600044부산광역시 중구 남포동4가 7번지부산광역시 중구 자갈치로59번길 6 (남포동4가)<NA>남포무도학원20060620145245I2018-08-31 23:59:59.0<NA>385115.989447179528.531518무도학원업사립0<NA><NA>468.6<NA><NA><NA><NA>
78무도학원업10_33_02_P3250000CDFH330111200000000220000512<NA>3폐업3폐업20200320<NA><NA><NA>051-246-1043<NA><NA>부산광역시 중구 남포동6가 27-1번지부산광역시 중구 자갈치로 22-1 (남포동6가)48982현대 댄스스포츠20200320094908U2020-03-22 02:40:00.0<NA>384749.608488179365.804286무도학원업사립<NA><NA><NA>86.79<NA><NA><NA><NA>
89무도학원업10_33_02_P3250000CDFH330111200000000320001213<NA>3폐업3폐업20120709<NA><NA><NA>468-5582<NA>600044부산광역시 중구 남포동4가 30번지 3층<NA><NA>신동양무도학원20120709105828I2018-08-31 23:59:59.0<NA>385160.754397179452.209734무도학원업사립<NA><NA><NA>3861.84<NA><NA><NA><NA>
910무도학원업10_33_02_P3270000CDFH330111200200000320020906<NA>3폐업3폐업20070528<NA><NA><NA>464-7727<NA>601838부산광역시 동구 초량동 1200-1번지부산광역시 동구 중앙대로214번길 7-11 (초량동)<NA>파라댄스스포츠학원20070529173621I2018-08-31 23:59:59.0<NA>386055.563905181649.267916무도학원업사립1<NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명Unnamed: 37
122123무도학원업10_33_02_P3340000CDFH330111200900000220090806<NA>1영업/정상13영업중<NA><NA><NA><NA>291-9888<NA>604848부산광역시 사하구 하단동 618-43번지 4층부산광역시 사하구 낙동대로451번길 2 (하단동,4층)<NA>박용성댄스스포츠20120809155018I2018-08-31 23:59:59.0<NA>379471.752048180193.030622무도학원업사립Y<NA>11233.75<NA><NA><NA><NA>
123124무도학원업10_33_02_P3350000CDFH330111199400000119940725<NA>1영업/정상13영업중<NA><NA><NA><NA>051-524-4588<NA><NA>부산광역시 금정구 서동 207-15부산광역시 금정구 서동로 193 (서동)46321월드댄스스포츠학원20200901205440U2020-09-04 02:40:00.0<NA>391848.246677192598.042492무도학원업사립Y<NA>177.16<NA><NA><NA><NA>
124125무도학원업10_33_02_P3350000CDFH330111201800000120181101<NA>1영업/정상13영업중<NA><NA><NA><NA>051-521-8077<NA><NA>부산광역시 금정구 서동 205-15번지 3층부산광역시 금정구 서동로 187-7, 3층 (서동)46321주정희 댄스스포츠20190319155857U2019-03-21 02:40:00.0<NA>391771.080139192637.074264무도학원업사립Y<NA><NA>480.02<NA><NA><NA><NA>
125126무도학원업10_33_02_P3370000CDFH330111199300000119930804<NA>1영업/정상13영업중<NA><NA><NA><NA>051-865-6437<NA>611839부산광역시 연제구 연산동 708-2번지부산광역시 연제구 월드컵대로99번길 38 (연산동)47596뉴스타댄스스포츠20120224135339I2018-08-31 23:59:59.0<NA>389504.652643189203.58243무도학원업사립Y<NA><NA>197.19<NA><NA><NA><NA>
126127무도학원업10_33_02_P3370000CDFH330111201000000120100210<NA>1영업/정상13영업중<NA><NA><NA><NA>051-753-7732<NA>611822부산광역시 연제구 연산동 726-5번지 5층부산광역시 연제구 반송로 9-1 (연산동)47520동영무도학원20190725105531U2019-07-27 02:40:00.0<NA>389589.66909189503.879237무도학원업사립Y<NA><NA><NA><NA><NA><NA><NA>
127128무도학원업10_33_02_P3370000CDFH330111201000000220100401<NA>1영업/정상13영업중<NA><NA><NA><NA>051-853-9966<NA>611828부산광역시 연제구 연산동 1242-27번지부산광역시 연제구 중앙대로 1093 (연산동)47540김호경 인터내셔날 댄스스포츠20190813090251U2019-08-15 02:40:00.0<NA>389465.997157189353.18074무도학원업사립Y<NA><NA><NA><NA><NA><NA><NA>
128129무도학원업10_33_02_P3380000CDFH330111199900000119990429<NA>1영업/정상13영업중<NA><NA><NA><NA>752-3856<NA>613830부산광역시 수영구 수영동 446-5 3층부산광역시 수영구 수영로 691-5 (수영동)48228스타무도학원20201026085347U2020-10-28 02:40:00.0<NA>392637.790394187474.961978무도학원업사립Y<NA><NA><NA><NA><NA><NA><NA>
129130무도학원업10_33_02_P3380000CDFH330111199900000219990902<NA>1영업/정상13영업중<NA><NA><NA><NA>752-2268<NA>613800부산광역시 수영구 광안동 74-6번지 3층부산광역시 수영구 수영로 684 (광안동,3층)<NA>부산무도학원20140114132426I2018-08-31 23:59:59.0<NA>392653.68088187325.201255무도학원업사립Y<NA><NA><NA><NA><NA><NA><NA>
130131무도학원업10_33_02_P3380000CDFH330111200900000220090226<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>613809부산광역시 수영구 광안동 566-4번지 3층부산광역시 수영구 수영로 607 (광안동,3층)<NA>장미숙댄스스포츠학원20141029091052I2018-08-31 23:59:59.0<NA>392489.856606186576.421899무도학원업사립Y<NA><NA>576.88<NA><NA><NA><NA>
131132무도학원업10_33_02_P3380000CDFH330111201300000120130305<NA>1영업/정상13영업중<NA><NA><NA><NA>051-612-2204<NA>613815부산광역시 수영구 남천동 27-6번지 지상3층부산광역시 수영구 광남로 33, 지상동 3층 (남천동)48314K&C 댄스스포츠 스쿨20140114132002I2018-08-31 23:59:59.0<NA>392294.710671185004.189176무도학원업사립Y<NA><NA>5273.11<NA><NA><NA><NA>