Overview

Dataset statistics

Number of variables28
Number of observations32
Missing cells139
Missing cells (%)15.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.7 KiB
Average record size in memory245.1 B

Variable types

Numeric9
Categorical10
Text5
Unsupported3
DateTime1

Dataset

Description22년10월_6270000_대구광역시_10_37_01_P_종합체육시설업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096817&dataSetDetailId=DDI_0000096846&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
인허가취소일자 is highly imbalanced (55.1%)Imbalance
휴업시작일자 is highly imbalanced (66.3%)Imbalance
휴업종료일자 is highly imbalanced (66.3%)Imbalance
폐업일자 has 20 (62.5%) missing valuesMissing
재개업일자 has 32 (100.0%) missing valuesMissing
소재지전화 has 2 (6.2%) missing valuesMissing
소재지면적 has 32 (100.0%) missing valuesMissing
소재지우편번호 has 10 (31.2%) missing valuesMissing
도로명전체주소 has 1 (3.1%) missing valuesMissing
도로명우편번호 has 10 (31.2%) missing valuesMissing
업태구분명 has 32 (100.0%) missing valuesMissing
번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정시점 has unique valuesUnique
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

Reproduction

Analysis started2024-04-18 02:07:15.050767
Analysis finished2024-04-18 02:07:15.379330
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:15.428905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-04-18T11:07:15.528954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
종합체육시설업
32 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종합체육시설업 32
100.0%

Length

2024-04-18T11:07:15.652598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:15.745895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합체육시설업 32
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
10_37_01_P
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10_37_01_P
2nd row10_37_01_P
3rd row10_37_01_P
4th row10_37_01_P
5th row10_37_01_P

Common Values

ValueCountFrequency (%)
10_37_01_P 32
100.0%

Length

2024-04-18T11:07:15.831463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:15.907844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_37_01_p 32
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3455937.5
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:15.971770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3420000
Q13450000
median3460000
Q33462500
95-th percentile3480000
Maximum3480000
Range60000
Interquartile range (IQR)12500

Descriptive statistics

Standard deviation16036.124
Coefficient of variation (CV)0.004640166
Kurtosis0.6202099
Mean3455937.5
Median Absolute Deviation (MAD)10000
Skewness-0.68167344
Sum1.1059 × 108
Variance2.5715726 × 108
MonotonicityIncreasing
2024-04-18T11:07:16.063428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3460000 10
31.2%
3450000 9
28.1%
3470000 4
 
12.5%
3480000 4
 
12.5%
3420000 3
 
9.4%
3440000 2
 
6.2%
ValueCountFrequency (%)
3420000 3
 
9.4%
3440000 2
 
6.2%
3450000 9
28.1%
3460000 10
31.2%
3470000 4
 
12.5%
3480000 4
 
12.5%
ValueCountFrequency (%)
3480000 4
 
12.5%
3470000 4
 
12.5%
3460000 10
31.2%
3450000 9
28.1%
3440000 2
 
6.2%
3420000 3
 
9.4%

관리번호
Text

Distinct22
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-18T11:07:16.221239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters640
Distinct characters13
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

Unique16 ?
Unique (%)50.0%

Sample

1st rowCDFH3301262021000001
2nd rowCDFH3301262013000001
3rd rowCDFH3301262020000001
4th rowCDFH3301261994000001
5th rowCDFH3301262008000001
ValueCountFrequency (%)
cdfh3301262021000001 3
 
9.4%
cdfh3301262006000001 3
 
9.4%
cdfh3301262014000001 3
 
9.4%
cdfh3301262013000001 3
 
9.4%
cdfh3301262008000001 2
 
6.2%
cdfh3301262010000001 2
 
6.2%
cdfh3301261996000001 1
 
3.1%
cdfh3301261998000002 1
 
3.1%
cdfh3301262007000001 1
 
3.1%
cdfh3301261997000001 1
 
3.1%
Other values (12) 12
37.5%
2024-04-18T11:07:16.484417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 229
35.8%
1 83
 
13.0%
2 71
 
11.1%
3 67
 
10.5%
6 38
 
5.9%
C 32
 
5.0%
D 32
 
5.0%
F 32
 
5.0%
H 32
 
5.0%
9 12
 
1.9%
Other values (3) 12
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 512
80.0%
Uppercase Letter 128
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 229
44.7%
1 83
 
16.2%
2 71
 
13.9%
3 67
 
13.1%
6 38
 
7.4%
9 12
 
2.3%
8 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 32
25.0%
D 32
25.0%
F 32
25.0%
H 32
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 512
80.0%
Latin 128
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 229
44.7%
1 83
 
16.2%
2 71
 
13.9%
3 67
 
13.1%
6 38
 
7.4%
9 12
 
2.3%
8 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
Latin
ValueCountFrequency (%)
C 32
25.0%
D 32
25.0%
F 32
25.0%
H 32
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 229
35.8%
1 83
 
13.0%
2 71
 
11.1%
3 67
 
10.5%
6 38
 
5.9%
C 32
 
5.0%
D 32
 
5.0%
F 32
 
5.0%
H 32
 
5.0%
9 12
 
1.9%
Other values (3) 12
 
1.9%

인허가일자
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20092939
Minimum19890825
Maximum20220901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:16.593066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19890825
5-th percentile19918353
Q120060483
median20105811
Q320145796
95-th percentile20215163
Maximum20220901
Range330076
Interquartile range (IQR)85313.5

Descriptive statistics

Standard deviation93425.989
Coefficient of variation (CV)0.0046496925
Kurtosis-0.26334429
Mean20092939
Median Absolute Deviation (MAD)45454.5
Skewness-0.6193506
Sum6.4297406 × 108
Variance8.7284153 × 109
MonotonicityNot monotonic
2024-04-18T11:07:16.693373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20210527 1
 
3.1%
19980530 1
 
3.1%
20131015 1
 
3.1%
20110715 1
 
3.1%
20061201 1
 
3.1%
20140619 1
 
3.1%
20080919 1
 
3.1%
20071227 1
 
3.1%
20060609 1
 
3.1%
19970228 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
19890825 1
3.1%
19891017 1
3.1%
19940719 1
3.1%
19960720 1
3.1%
19970228 1
3.1%
19980530 1
3.1%
20010614 1
3.1%
20060104 1
3.1%
20060609 1
3.1%
20060908 1
3.1%
ValueCountFrequency (%)
20220901 1
3.1%
20220830 1
3.1%
20210527 1
3.1%
20210524 1
3.1%
20210119 1
3.1%
20201228 1
3.1%
20171017 1
3.1%
20160704 1
3.1%
20140827 1
3.1%
20140619 1
3.1%

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
29 
20171204
3 

Length

Max length8
Median length4
Mean length4.375
Min length4

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> 29
90.6%
20171204 3
 
9.4%

Length

2024-04-18T11:07:16.801283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:16.891036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
90.6%
20171204 3
 
9.4%

영업상태구분코드
Categorical

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
1
15 
3
10 
4
5 
2
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 15
46.9%
3 10
31.2%
4 5
 
15.6%
2 2
 
6.2%

Length

2024-04-18T11:07:16.979304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:17.081329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 15
46.9%
3 10
31.2%
4 5
 
15.6%
2 2
 
6.2%

영업상태명
Categorical

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
영업/정상
15 
폐업
10 
취소/말소/만료/정지/중지
5 
휴업
2 

Length

Max length14
Median length5
Mean length5.28125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 15
46.9%
폐업 10
31.2%
취소/말소/만료/정지/중지 5
 
15.6%
휴업 2
 
6.2%

Length

2024-04-18T11:07:17.179099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:17.264531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 15
46.9%
폐업 10
31.2%
취소/말소/만료/정지/중지 5
 
15.6%
휴업 2
 
6.2%

상세영업상태코드
Categorical

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
13
15 
3
10 
32
3 
35
2 
2
2 

Length

Max length2
Median length2
Mean length1.625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row3
5th row3

Common Values

ValueCountFrequency (%)
13 15
46.9%
3 10
31.2%
32 3
 
9.4%
35 2
 
6.2%
2 2
 
6.2%

Length

2024-04-18T11:07:17.365846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:17.465891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 15
46.9%
3 10
31.2%
32 3
 
9.4%
35 2
 
6.2%
2 2
 
6.2%

상세영업상태명
Categorical

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
영업중
15 
폐업
10 
신고취소
3 
직권말소
2 
휴업
2 

Length

Max length4
Median length3
Mean length2.78125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 15
46.9%
폐업 10
31.2%
신고취소 3
 
9.4%
직권말소 2
 
6.2%
휴업 2
 
6.2%

Length

2024-04-18T11:07:17.600902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:17.695753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 15
46.9%
폐업 10
31.2%
신고취소 3
 
9.4%
직권말소 2
 
6.2%
휴업 2
 
6.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)100.0%
Missing20
Missing (%)62.5%
Infinite0
Infinite (%)0.0%
Mean20128908
Minimum20060619
Maximum20220816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:17.774137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060619
5-th percentile20066385
Q120090382
median20115318
Q320165800
95-th percentile20215034
Maximum20220816
Range160197
Interquartile range (IQR)75418.25

Descriptive statistics

Standard deviation56457.624
Coefficient of variation (CV)0.0028048031
Kurtosis-0.95468577
Mean20128908
Median Absolute Deviation (MAD)30359
Skewness0.71146079
Sum2.4154689 × 108
Variance3.1874633 × 109
MonotonicityNot monotonic
2024-04-18T11:07:17.868390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20090406 1
 
3.1%
20090311 1
 
3.1%
20210304 1
 
3.1%
20151029 1
 
3.1%
20220816 1
 
3.1%
20120523 1
 
3.1%
20210115 1
 
3.1%
20120529 1
 
3.1%
20110113 1
 
3.1%
20060619 1
 
3.1%
Other values (2) 2
 
6.2%
(Missing) 20
62.5%
ValueCountFrequency (%)
20060619 1
3.1%
20071102 1
3.1%
20090311 1
3.1%
20090406 1
3.1%
20091027 1
3.1%
20110113 1
3.1%
20120523 1
3.1%
20120529 1
3.1%
20151029 1
3.1%
20210115 1
3.1%
ValueCountFrequency (%)
20220816 1
3.1%
20210304 1
3.1%
20210115 1
3.1%
20151029 1
3.1%
20120529 1
3.1%
20120523 1
3.1%
20110113 1
3.1%
20091027 1
3.1%
20090406 1
3.1%
20090311 1
3.1%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
30 
20220101
 
2

Length

Max length8
Median length4
Mean length4.25
Min length4

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> 30
93.8%
20220101 2
 
6.2%

Length

2024-04-18T11:07:18.002828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:18.103705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
93.8%
20220101 2
 
6.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
<NA>
30 
20221231
 
2

Length

Max length8
Median length4
Mean length4.25
Min length4

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> 30
93.8%
20221231 2
 
6.2%

Length

2024-04-18T11:07:18.191551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:18.288054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
93.8%
20221231 2
 
6.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

소재지전화
Text

MISSING 

Distinct30
Distinct (%)100.0%
Missing2
Missing (%)6.2%
Memory size388.0 B
2024-04-18T11:07:18.430117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.4
Min length8

Characters and Unicode

Total characters312
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row053-247-7070
2nd row053-230-3310
3rd row053-327-7780
4th row623-0005
5th row476-0077
ValueCountFrequency (%)
053-230-3310 1
 
3.3%
053-327-7780 1
 
3.3%
053-780-2113 1
 
3.3%
715-1200 1
 
3.3%
053-635-0200 1
 
3.3%
053-623-0099 1
 
3.3%
627-5050 1
 
3.3%
053-627-5050 1
 
3.3%
053-761-9900 1
 
3.3%
053-740-7600 1
 
3.3%
Other values (20) 20
66.7%
2024-04-18T11:07:18.713349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86
27.6%
- 45
14.4%
3 35
11.2%
5 34
 
10.9%
7 31
 
9.9%
2 21
 
6.7%
6 21
 
6.7%
1 17
 
5.4%
4 9
 
2.9%
9 7
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 267
85.6%
Dash Punctuation 45
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86
32.2%
3 35
13.1%
5 34
 
12.7%
7 31
 
11.6%
2 21
 
7.9%
6 21
 
7.9%
1 17
 
6.4%
4 9
 
3.4%
9 7
 
2.6%
8 6
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86
27.6%
- 45
14.4%
3 35
11.2%
5 34
 
10.9%
7 31
 
9.9%
2 21
 
6.7%
6 21
 
6.7%
1 17
 
5.4%
4 9
 
2.9%
9 7
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86
27.6%
- 45
14.4%
3 35
11.2%
5 34
 
10.9%
7 31
 
9.9%
2 21
 
6.7%
6 21
 
6.7%
1 17
 
5.4%
4 9
 
2.9%
9 7
 
2.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)90.9%
Missing10
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean706038.64
Minimum701843
Maximum711873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:18.815839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum701843
5-th percentile702715.7
Q1703371.75
median705830
Q3706788.5
95-th percentile711870.05
Maximum711873
Range10030
Interquartile range (IQR)3416.75

Descriptive statistics

Standard deviation3180.4706
Coefficient of variation (CV)0.0045046693
Kurtosis-0.12474639
Mean706038.64
Median Absolute Deviation (MAD)1025
Skewness0.87305303
Sum15532850
Variance10115393
MonotonicityNot monotonic
2024-04-18T11:07:18.910509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
704805 3
 
9.4%
706822 1
 
3.1%
711872 1
 
3.1%
711812 1
 
3.1%
711833 1
 
3.1%
711873 1
 
3.1%
704828 1
 
3.1%
706745 1
 
3.1%
706803 1
 
3.1%
701843 1
 
3.1%
Other values (10) 10
31.2%
(Missing) 10
31.2%
ValueCountFrequency (%)
701843 1
 
3.1%
702714 1
 
3.1%
702748 1
 
3.1%
702851 1
 
3.1%
702864 1
 
3.1%
702894 1
 
3.1%
704805 3
9.4%
704828 1
 
3.1%
705828 1
 
3.1%
705832 1
 
3.1%
ValueCountFrequency (%)
711873 1
3.1%
711872 1
3.1%
711833 1
3.1%
711812 1
3.1%
706822 1
3.1%
706803 1
3.1%
706745 1
3.1%
706170 1
3.1%
706092 1
3.1%
706011 1
3.1%

소재지전체주소
Text

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-18T11:07:19.088226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length30
Mean length23.75
Min length17

Characters and Unicode

Total characters760
Distinct characters80
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

Unique27 ?
Unique (%)84.4%

Sample

1st row대구광역시 동구 서호동 108
2nd row대구광역시 동구 효목동 1084
3rd row대구광역시 동구 신천동 326-1
4th row대구광역시 남구 봉덕동 산 152-1번지
5th row대구광역시 남구 봉덕동 1071-6번지 3층
ValueCountFrequency (%)
대구광역시 32
21.8%
수성구 10
 
6.8%
북구 9
 
6.1%
범어동 5
 
3.4%
달서구 4
 
2.7%
달성군 4
 
2.7%
태전동 4
 
2.7%
본동 3
 
2.0%
225-7번지 3
 
2.0%
동구 3
 
2.0%
Other values (59) 70
47.6%
2024-04-18T11:07:20.070021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
19.2%
구 60
 
7.9%
1 33
 
4.3%
대 32
 
4.2%
광 32
 
4.2%
역 32
 
4.2%
시 32
 
4.2%
동 32
 
4.2%
2 24
 
3.2%
지 24
 
3.2%
Other values (70) 313
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
55.3%
Decimal Number 154
 
20.3%
Space Separator 146
 
19.2%
Dash Punctuation 21
 
2.8%
Other Punctuation 7
 
0.9%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%
Uppercase Letter 3
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 60
14.3%
대 32
 
7.6%
광 32
 
7.6%
역 32
 
7.6%
시 32
 
7.6%
동 32
 
7.6%
지 24
 
5.7%
성 19
 
4.5%
번 16
 
3.8%
수 11
 
2.6%
Other values (52) 130
31.0%
Decimal Number
ValueCountFrequency (%)
1 33
21.4%
2 24
15.6%
0 19
12.3%
7 17
11.0%
5 16
10.4%
3 15
9.7%
4 11
 
7.1%
9 8
 
5.2%
6 6
 
3.9%
8 5
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 5
71.4%
. 2
 
28.6%
Space Separator
ValueCountFrequency (%)
146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 420
55.3%
Common 337
44.3%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 60
14.3%
대 32
 
7.6%
광 32
 
7.6%
역 32
 
7.6%
시 32
 
7.6%
동 32
 
7.6%
지 24
 
5.7%
성 19
 
4.5%
번 16
 
3.8%
수 11
 
2.6%
Other values (52) 130
31.0%
Common
ValueCountFrequency (%)
146
43.3%
1 33
 
9.8%
2 24
 
7.1%
- 21
 
6.2%
0 19
 
5.6%
7 17
 
5.0%
5 16
 
4.7%
3 15
 
4.5%
4 11
 
3.3%
9 8
 
2.4%
Other values (7) 27
 
8.0%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
55.3%
ASCII 340
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
42.9%
1 33
 
9.7%
2 24
 
7.1%
- 21
 
6.2%
0 19
 
5.6%
7 17
 
5.0%
5 16
 
4.7%
3 15
 
4.4%
4 11
 
3.2%
9 8
 
2.4%
Other values (8) 30
 
8.8%
Hangul
ValueCountFrequency (%)
구 60
14.3%
대 32
 
7.6%
광 32
 
7.6%
역 32
 
7.6%
시 32
 
7.6%
동 32
 
7.6%
지 24
 
5.7%
성 19
 
4.5%
번 16
 
3.8%
수 11
 
2.6%
Other values (52) 130
31.0%

도로명전체주소
Text

MISSING 

Distinct28
Distinct (%)90.3%
Missing1
Missing (%)3.1%
Memory size388.0 B
2024-04-18T11:07:20.279596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length35
Mean length28.354839
Min length19

Characters and Unicode

Total characters879
Distinct characters110
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

Unique26 ?
Unique (%)83.9%

Sample

1st row대구광역시 동구 안심로41길 10 (서호동)
2nd row대구광역시 동구 효동로2길 24 (효목동)
3rd row대구광역시 동구 동부로26길 6, 5층 (신천동)
4th row대구광역시 남구 앞산순환로 574-114 (봉덕동)
5th row대구광역시 남구 대덕로40길 56 (봉덕동,3층)
ValueCountFrequency (%)
대구광역시 31
 
17.8%
수성구 10
 
5.7%
북구 9
 
5.2%
범어동 4
 
2.3%
달서구 4
 
2.3%
칠곡중앙대로 4
 
2.3%
태전동 4
 
2.3%
59 3
 
1.7%
309 3
 
1.7%
달성군 3
 
1.7%
Other values (78) 99
56.9%
2024-04-18T11:07:20.599114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
 
17.1%
구 66
 
7.5%
대 43
 
4.9%
동 38
 
4.3%
역 32
 
3.6%
시 32
 
3.6%
광 31
 
3.5%
로 30
 
3.4%
( 28
 
3.2%
) 28
 
3.2%
Other values (100) 401
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 515
58.6%
Space Separator 150
 
17.1%
Decimal Number 131
 
14.9%
Open Punctuation 28
 
3.2%
Close Punctuation 28
 
3.2%
Other Punctuation 20
 
2.3%
Uppercase Letter 5
 
0.6%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 66
 
12.8%
대 43
 
8.3%
동 38
 
7.4%
역 32
 
6.2%
시 32
 
6.2%
광 31
 
6.0%
로 30
 
5.8%
성 20
 
3.9%
수 11
 
2.1%
지 10
 
1.9%
Other values (81) 202
39.2%
Decimal Number
ValueCountFrequency (%)
1 26
19.8%
3 20
15.3%
2 19
14.5%
0 17
13.0%
4 12
9.2%
5 11
8.4%
8 10
 
7.6%
9 7
 
5.3%
6 5
 
3.8%
7 4
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 18
90.0%
. 2
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
80.0%
C 1
 
20.0%
Space Separator
ValueCountFrequency (%)
150
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 515
58.6%
Common 359
40.8%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 66
 
12.8%
대 43
 
8.3%
동 38
 
7.4%
역 32
 
6.2%
시 32
 
6.2%
광 31
 
6.0%
로 30
 
5.8%
성 20
 
3.9%
수 11
 
2.1%
지 10
 
1.9%
Other values (81) 202
39.2%
Common
ValueCountFrequency (%)
150
41.8%
( 28
 
7.8%
) 28
 
7.8%
1 26
 
7.2%
3 20
 
5.6%
2 19
 
5.3%
, 18
 
5.0%
0 17
 
4.7%
4 12
 
3.3%
5 11
 
3.1%
Other values (7) 30
 
8.4%
Latin
ValueCountFrequency (%)
B 4
80.0%
C 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 515
58.6%
ASCII 364
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
41.2%
( 28
 
7.7%
) 28
 
7.7%
1 26
 
7.1%
3 20
 
5.5%
2 19
 
5.2%
, 18
 
4.9%
0 17
 
4.7%
4 12
 
3.3%
5 11
 
3.0%
Other values (9) 35
 
9.6%
Hangul
ValueCountFrequency (%)
구 66
 
12.8%
대 43
 
8.3%
동 38
 
7.4%
역 32
 
6.2%
시 32
 
6.2%
광 31
 
6.0%
로 30
 
5.8%
성 20
 
3.9%
수 11
 
2.1%
지 10
 
1.9%
Other values (81) 202
39.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)81.8%
Missing10
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean71870.591
Minimum41117
Maximum702748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:20.697072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41117
5-th percentile41182.2
Q141457.75
median41801.5
Q342163
95-th percentile42985.85
Maximum702748
Range661631
Interquartile range (IQR)705.25

Descriptive statistics

Standard deviation140909.37
Coefficient of variation (CV)1.9605984
Kurtosis21.999339
Mean71870.591
Median Absolute Deviation (MAD)344.5
Skewness4.6903147
Sum1581153
Variance1.9855449 × 1010
MonotonicityNot monotonic
2024-04-18T11:07:20.778484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
41457 3
 
9.4%
41593 2
 
6.2%
42204 2
 
6.2%
42171 1
 
3.1%
42945 1
 
3.1%
42988 1
 
3.1%
42139 1
 
3.1%
42028 1
 
3.1%
42064 1
 
3.1%
42107 1
 
3.1%
Other values (8) 8
25.0%
(Missing) 10
31.2%
ValueCountFrequency (%)
41117 1
 
3.1%
41179 1
 
3.1%
41243 1
 
3.1%
41457 3
9.4%
41460 1
 
3.1%
41474 1
 
3.1%
41515 1
 
3.1%
41593 2
6.2%
42010 1
 
3.1%
42028 1
 
3.1%
ValueCountFrequency (%)
702748 1
3.1%
42988 1
3.1%
42945 1
3.1%
42204 2
6.2%
42171 1
3.1%
42139 1
3.1%
42107 1
3.1%
42064 1
3.1%
42028 1
3.1%
42010 1
3.1%

사업장명
Text

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-18T11:07:20.949797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length9.34375
Min length5

Characters and Unicode

Total characters299
Distinct characters101
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)87.5%

Sample

1st row우주스포츠센터
2nd row아양아트센터
3rd row어반 웰니스 (Urban Wellness)
4th row대원레포츠
5th row효성코아 헬스장
ValueCountFrequency (%)
스포츠센터 3
 
6.0%
송림스포츠센터 2
 
4.0%
제드 2
 
4.0%
휘트니스센터 2
 
4.0%
스포츠 2
 
4.0%
주)천명개발 1
 
2.0%
주)선영 1
 
2.0%
선 1
 
2.0%
스포츠프라자 1
 
2.0%
인터불고 1
 
2.0%
Other values (34) 34
68.0%
2024-04-18T11:07:21.245794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 24
 
8.0%
18
 
6.0%
센 18
 
6.0%
터 18
 
6.0%
포 17
 
5.7%
츠 17
 
5.7%
주 9
 
3.0%
( 8
 
2.7%
) 8
 
2.7%
트 8
 
2.7%
Other values (91) 154
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 247
82.6%
Space Separator 18
 
6.0%
Lowercase Letter 11
 
3.7%
Open Punctuation 8
 
2.7%
Close Punctuation 8
 
2.7%
Uppercase Letter 7
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 24
 
9.7%
센 18
 
7.3%
터 18
 
7.3%
포 17
 
6.9%
츠 17
 
6.9%
주 9
 
3.6%
트 8
 
3.2%
니 7
 
2.8%
아 7
 
2.8%
성 6
 
2.4%
Other values (74) 116
47.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
18.2%
s 2
18.2%
e 2
18.2%
l 2
18.2%
a 1
9.1%
b 1
9.1%
r 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
U 1
14.3%
G 1
14.3%
D 1
14.3%
T 1
14.3%
I 1
14.3%
S 1
14.3%
W 1
14.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
82.6%
Common 34
 
11.4%
Latin 18
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 24
 
9.7%
센 18
 
7.3%
터 18
 
7.3%
포 17
 
6.9%
츠 17
 
6.9%
주 9
 
3.6%
트 8
 
3.2%
니 7
 
2.8%
아 7
 
2.8%
성 6
 
2.4%
Other values (74) 116
47.0%
Latin
ValueCountFrequency (%)
n 2
11.1%
s 2
11.1%
e 2
11.1%
l 2
11.1%
U 1
 
5.6%
G 1
 
5.6%
D 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
S 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
18
52.9%
( 8
23.5%
) 8
23.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 247
82.6%
ASCII 52
 
17.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 24
 
9.7%
센 18
 
7.3%
터 18
 
7.3%
포 17
 
6.9%
츠 17
 
6.9%
주 9
 
3.6%
트 8
 
3.2%
니 7
 
2.8%
아 7
 
2.8%
성 6
 
2.4%
Other values (74) 116
47.0%
ASCII
ValueCountFrequency (%)
18
34.6%
( 8
15.4%
) 8
15.4%
n 2
 
3.8%
s 2
 
3.8%
e 2
 
3.8%
l 2
 
3.8%
U 1
 
1.9%
G 1
 
1.9%
D 1
 
1.9%
Other values (7) 7
 
13.5%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0174422 × 1013
Minimum2.0060609 × 1013
Maximum2.0221013 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:21.349444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0060609 × 1013
5-th percentile2.007695 × 1013
Q12.0143404 × 1013
median2.0200815 × 1013
Q32.0213501 × 1013
95-th percentile2.0220913 × 1013
Maximum2.0221013 × 1013
Range1.6040407 × 1011
Interquartile range (IQR)7.0097237 × 1010

Descriptive statistics

Standard deviation5.2117196 × 1010
Coefficient of variation (CV)0.0025833303
Kurtosis-0.34739082
Mean2.0174422 × 1013
Median Absolute Deviation (MAD)2.0107542 × 1010
Skewness-0.98266367
Sum6.4558151 × 1014
Variance2.7162021 × 1021
MonotonicityNot monotonic
2024-04-18T11:07:21.461886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20220420110408 1
 
3.1%
20120529165939 1
 
3.1%
20171204112204 1
 
3.1%
20171204112137 1
 
3.1%
20171204112027 1
 
3.1%
20220411083441 1
 
3.1%
20210509164125 1
 
3.1%
20091028100109 1
 
3.1%
20060609112009 1
 
3.1%
20060619165120 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
20060609112009 1
3.1%
20060619165120 1
3.1%
20090311193104 1
3.1%
20090406132244 1
3.1%
20091028100109 1
3.1%
20120523131249 1
3.1%
20120529140053 1
3.1%
20120529165939 1
3.1%
20151029163304 1
3.1%
20160203151132 1
3.1%
ValueCountFrequency (%)
20221013184251 1
3.1%
20221013184109 1
3.1%
20220831163605 1
3.1%
20220823185723 1
3.1%
20220729141340 1
3.1%
20220420110408 1
3.1%
20220411083441 1
3.1%
20220321171110 1
3.1%
20211228144302 1
3.1%
20211110161517 1
3.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
U
16 
I
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 16
50.0%
I 16
50.0%

Length

2024-04-18T11:07:21.567759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T11:07:21.650905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 16
50.0%
i 16
50.0%

데이터갱신일자
Date

Distinct16
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2018-08-31 23:59:59
Maximum2022-10-15 02:40:00
2024-04-18T11:07:21.724854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T11:07:21.815767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

좌표정보(X)
Real number (ℝ)

Distinct24
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343199.87
Minimum330240.33
Maximum354229.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:21.917323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330240.33
5-th percentile332136.2
Q1339651.84
median343843.04
Q3347067.23
95-th percentile351750.48
Maximum354229.47
Range23989.139
Interquartile range (IQR)7415.3815

Descriptive statistics

Standard deviation5844.7403
Coefficient of variation (CV)0.017030136
Kurtosis0.027874142
Mean343199.87
Median Absolute Deviation (MAD)4033.4381
Skewness-0.40972366
Sum10982396
Variance34160990
MonotonicityNot monotonic
2024-04-18T11:07:22.039625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
339486.330243 3
 
9.4%
343260.639405 3
 
9.4%
339783.989364 3
 
9.4%
347202.24792 2
 
6.2%
347067.226051 2
 
6.2%
354229.474254 1
 
3.1%
347850.865517 1
 
3.1%
330240.334923 1
 
3.1%
331919.96911 1
 
3.1%
334475.475586 1
 
3.1%
Other values (14) 14
43.8%
ValueCountFrequency (%)
330240.334923 1
 
3.1%
331919.96911 1
 
3.1%
332313.120088 1
 
3.1%
334475.475586 1
 
3.1%
338254.88849 1
 
3.1%
339486.330243 3
9.4%
339707.015975 1
 
3.1%
339783.989364 3
9.4%
343260.639405 3
9.4%
343550.446823 1
 
3.1%
ValueCountFrequency (%)
354229.474254 1
3.1%
353999.548196 1
3.1%
349910.333288 1
3.1%
349094.598043 1
3.1%
347850.865517 1
3.1%
347202.24792 2
6.2%
347067.226051 2
6.2%
346922.110876 1
3.1%
346571.168775 1
3.1%
346507.147444 1
3.1%

좌표정보(Y)
Real number (ℝ)

Distinct24
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262899.81
Minimum245630.33
Maximum271331.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-18T11:07:22.135548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245630.33
5-th percentile251898.8
Q1260733.9
median263458.52
Q3266077.82
95-th percentile270597.33
Maximum271331.09
Range25700.755
Interquartile range (IQR)5343.9211

Descriptive statistics

Standard deviation5867.2984
Coefficient of variation (CV)0.022317621
Kurtosis2.8162158
Mean262899.81
Median Absolute Deviation (MAD)2678.4163
Skewness-1.2677353
Sum8412794.1
Variance34425191
MonotonicityNot monotonic
2024-04-18T11:07:22.237958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
270340.317289 3
 
9.4%
266077.818455 3
 
9.4%
260733.89736 3
 
9.4%
259665.923686 2
 
6.2%
263458.521991 2
 
6.2%
264328.348009 1
 
3.1%
262414.596896 1
 
3.1%
245630.332878 1
 
3.1%
263810.755354 1
 
3.1%
256410.459464 1
 
3.1%
Other values (14) 14
43.8%
ValueCountFrequency (%)
245630.332878 1
 
3.1%
246384.553707 1
 
3.1%
256410.459464 1
 
3.1%
259122.373021 1
 
3.1%
259665.923686 2
6.2%
260132.20801 1
 
3.1%
260733.89736 3
9.4%
260826.314023 1
 
3.1%
260971.516963 1
 
3.1%
261412.731435 1
 
3.1%
ValueCountFrequency (%)
271331.088251 1
 
3.1%
270911.454654 1
 
3.1%
270340.317289 3
9.4%
268598.942833 1
 
3.1%
266077.818455 3
9.4%
265637.282898 1
 
3.1%
265123.315824 1
 
3.1%
265093.508874 1
 
3.1%
264328.348009 1
 
3.1%
264235.07481 1
 
3.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)
01종합체육시설업10_37_01_P3420000CDFH330126202100000120210527<NA>1영업/정상13영업중<NA><NA><NA><NA>053-247-7070<NA><NA>대구광역시 동구 서호동 108대구광역시 동구 안심로41길 10 (서호동)41117우주스포츠센터20220420110408U2022-04-22 02:40:00.0<NA>354229.474254264328.348009
12종합체육시설업10_37_01_P3420000CDFH330126201300000120130820<NA>1영업/정상13영업중<NA><NA><NA><NA>053-230-3310<NA>701843대구광역시 동구 효목동 1084대구광역시 동구 효동로2길 24 (효목동)41179아양아트센터20220729141340U2022-07-31 02:40:00.0<NA>349094.598043265637.282898
23종합체육시설업10_37_01_P3420000CDFH330126202000000120201228<NA>1영업/정상13영업중<NA><NA><NA><NA>053-327-7780<NA><NA>대구광역시 동구 신천동 326-1대구광역시 동구 동부로26길 6, 5층 (신천동)41243어반 웰니스 (Urban Wellness)20201228150939I2020-12-30 00:23:06.0<NA>346922.110876265123.315824
34종합체육시설업10_37_01_P3440000CDFH330126199400000119940719<NA>3폐업3폐업20090406<NA><NA><NA>623-0005<NA>705832대구광역시 남구 봉덕동 산 152-1번지대구광역시 남구 앞산순환로 574-114 (봉덕동)<NA>대원레포츠20090406132244I2018-08-31 23:59:59.0<NA>343550.446823259122.373021
45종합체육시설업10_37_01_P3440000CDFH330126200800000120080627<NA>3폐업3폐업20090311<NA><NA><NA>476-0077<NA>705828대구광역시 남구 봉덕동 1071-6번지 3층대구광역시 남구 대덕로40길 56 (봉덕동,3층)<NA>효성코아 헬스장20090311193104I2018-08-31 23:59:59.0<NA>344868.181814260971.516963
56종합체육시설업10_37_01_P3450000CDFH330126200600000220060908<NA>3폐업3폐업20210304<NA><NA><NA>312-6000<NA>702864대구광역시 북구 태전동 409-7 지하1,2층 지상3층대구광역시 북구 칠곡중앙대로 309 (태전동)41457송림스포츠센터20210304155824U2021-03-06 02:40:00.0<NA>339486.330243270340.317289
67종합체육시설업10_37_01_P3450000CDFH330126201300000120131014<NA>3폐업3폐업20151029<NA><NA><NA>721-7797<NA>702748대구광역시 북구 칠성동2가 2-5번지 비101호대구광역시 북구 옥산로 103, 비101호 (칠성동2가)41593해든 스포츠센터20151029163304I2018-08-31 23:59:59.0<NA>343260.639405266077.818455
78종합체육시설업10_37_01_P3450000CDFH330126202200000120220830<NA>1영업/정상13영업중<NA><NA><NA><NA>053-311-6600<NA><NA>대구광역시 북구 태전동 409-7대구광역시 북구 칠곡중앙대로 309, 지하 1,2층 (태전동)41457송림스포츠프라자20221013184251U2022-10-15 02:40:00.0<NA>339486.330243270340.317289
89종합체육시설업10_37_01_P3450000CDFH330126202200000220220901<NA>1영업/정상13영업중<NA><NA><NA><NA>053-380-0406<NA><NA>대구광역시 북구 산격동 1674대구광역시 북구 유통단지로 80, 2층 (산격동)41515(주)인터불고 엑스코20221013184109U2022-10-15 02:40:00.0<NA>345396.560356268598.942833
910종합체육시설업10_37_01_P3450000CDFH330126201000000120100907<NA>1영업/정상13영업중<NA><NA><NA><NA>950-0104<NA>702894대구광역시 북구 서변동 1724-1 지하1(수영장),지상2~4(골프연습장),5(체력단련장)대구광역시 북구 호국로57길 6, 지하1,지상2~5층 (서변동)41474유니버시아드레포츠센터20220321171110U2022-03-23 02:40:00.0<NA>344135.625387270911.454654
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)
2223종합체육시설업10_37_01_P3460000CDFH330126201200000120120618<NA>1영업/정상13영업중<NA><NA><NA><NA>053-740-7600<NA>706745대구광역시 수성구 범어동 179번지대구광역시 수성구 달구벌대로 2435 (범어동)42028휘트니스센터 제드20180817105105I2018-08-31 23:59:59.0<NA>347067.226051263458.521991
2324종합체육시설업10_37_01_P3460000CDFH330126201400000120140603<NA>1영업/정상13영업중<NA><NA><NA><NA>053-761-9900<NA><NA>대구광역시 수성구 범어동 805-4대구광역시 수성구 범어천로 73 (범어동, 호텔 라온제나)42139주식회사 라온베이20210114103732U2021-01-16 02:40:00.0<NA>346507.147444262714.226889
2425종합체육시설업10_37_01_P3470000CDFH330126199700000119970228<NA>3폐업3폐업20060619<NA><NA><NA>053-627-5050<NA>704805대구광역시 달서구 본동 225-7번지대구광역시 달서구 구마로 184 (본동)<NA>(주)천명개발20060619165120I2018-08-31 23:59:59.0<NA>339783.989364260733.89736
2526종합체육시설업10_37_01_P3470000CDFH330126200600000120060609<NA>3폐업3폐업20071102<NA><NA><NA>627-5050<NA>704805대구광역시 달서구 본동 225-7번지대구광역시 달서구 구마로 184 (본동)<NA>웰씨휘트니스(주)20060609112009I2018-08-31 23:59:59.0<NA>339783.989364260733.89736
2627종합체육시설업10_37_01_P3470000CDFH330126200700000120071227<NA>3폐업3폐업20091027<NA><NA><NA>053-623-0099<NA>704805대구광역시 달서구 본동 225-7번지대구광역시 달서구 구마로 184 (본동)<NA>도시안스포츠센타(주) 대구지점20091028100109I2018-08-31 23:59:59.0<NA>339783.989364260733.89736
2728종합체육시설업10_37_01_P3470000CDFH330126200800000120080919<NA>1영업/정상13영업중<NA><NA><NA><NA>053-635-0200<NA>704828대구광역시 달서구 월성동 273-4대구광역시 달서구 월성로 42 (월성동)<NA>센트로밸리휘트니스타20210509164125U2021-05-11 02:40:00.0<NA>338254.88849260132.20801
2829종합체육시설업10_37_01_P3480000CDFH330126201400000120140619<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>711873대구광역시 달성군 현풍읍 상리 50-1대구광역시 달성군 현풍읍 테크노중앙대로 33342988DGIST 스포츠센터20220411083441U2022-04-13 02:40:00.0<NA>332313.120088246384.553707
2930종합체육시설업10_37_01_P3480000CDFH330126200600000120061201201712044취소/말소/만료/정지/중지32신고취소<NA><NA><NA><NA><NA><NA>711833대구광역시 달성군 화원읍 설화리 553-3번지대구광역시 달성군 화원읍 성천로 542945달성군여성문화복지센터20171204112027I2018-08-31 23:59:59.0<NA>334475.475586256410.459464
3031종합체육시설업10_37_01_P3480000CDFH330126201100000120110715201712044취소/말소/만료/정지/중지32신고취소<NA><NA><NA><NA>715-1200<NA>711812대구광역시 달성군 다사읍 매곡리 1515-3번지대구광역시 달성군 다사읍 대실역북로2길 188<NA>달성문화센터20171204112137I2018-08-31 23:59:59.0<NA>331919.96911263810.755354
3132종합체육시설업10_37_01_P3480000CDFH330126201300000120131015201712044취소/말소/만료/정지/중지32신고취소<NA><NA><NA><NA>668-8000<NA>711872대구광역시 달성군 현풍면 성하리 227번지<NA><NA>달성국민체육센터20171204112204I2018-08-31 23:59:59.0<NA>330240.334923245630.332878