Overview

Dataset statistics

Number of variables28
Number of observations31
Missing cells134
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory245.3 B

Variable types

Numeric9
Categorical10
Text5
Unsupported3
DateTime1

Dataset

Description22년08월_6270000_대구광역시_10_37_01_P_종합체육시설업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094291&dataSetDetailId=DDI_0000094319&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
인허가취소일자 is highly imbalanced (54.1%)Imbalance
휴업시작일자 is highly imbalanced (65.5%)Imbalance
휴업종료일자 is highly imbalanced (65.5%)Imbalance
폐업일자 has 19 (61.3%) missing valuesMissing
재개업일자 has 31 (100.0%) missing valuesMissing
소재지전화 has 2 (6.5%) missing valuesMissing
소재지면적 has 31 (100.0%) missing valuesMissing
소재지우편번호 has 9 (29.0%) missing valuesMissing
도로명전체주소 has 1 (3.2%) missing valuesMissing
도로명우편번호 has 10 (32.3%) missing valuesMissing
업태구분명 has 31 (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 started2023-12-10 18:12:23.328588
Analysis finished2023-12-10 18:12:23.863300
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:23.943003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-11T03:12:24.147293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
종합체육시설업
31 

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 31
100.0%

Length

2023-12-11T03:12:24.323400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:24.444233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합체육시설업 31
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
10_37_01_P
31 

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 31
100.0%

Length

2023-12-11T03:12:24.601017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:24.733774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_37_01_p 31
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3456129
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:24.869789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3420000
Q13450000
median3460000
Q33465000
95-th percentile3480000
Maximum3480000
Range60000
Interquartile range (IQR)15000

Descriptive statistics

Standard deviation16263.952
Coefficient of variation (CV)0.0047058289
Kurtosis0.57855135
Mean3456129
Median Absolute Deviation (MAD)10000
Skewness-0.71269598
Sum1.0714 × 108
Variance2.6451613 × 108
MonotonicityIncreasing
2023-12-11T03:12:25.021092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3460000 10
32.3%
3450000 8
25.8%
3470000 4
 
12.9%
3480000 4
 
12.9%
3420000 3
 
9.7%
3440000 2
 
6.5%
ValueCountFrequency (%)
3420000 3
 
9.7%
3440000 2
 
6.5%
3450000 8
25.8%
3460000 10
32.3%
3470000 4
 
12.9%
3480000 4
 
12.9%
ValueCountFrequency (%)
3480000 4
 
12.9%
3470000 4
 
12.9%
3460000 10
32.3%
3450000 8
25.8%
3440000 2
 
6.5%
3420000 3
 
9.7%

관리번호
Text

Distinct21
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T03:12:25.249279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters620
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

Unique15 ?
Unique (%)48.4%

Sample

1st rowCDFH3301262021000001
2nd rowCDFH3301262013000001
3rd rowCDFH3301262020000001
4th rowCDFH3301261994000001
5th rowCDFH3301262008000001
ValueCountFrequency (%)
cdfh3301262021000001 3
 
9.7%
cdfh3301262006000001 3
 
9.7%
cdfh3301262014000001 3
 
9.7%
cdfh3301262013000001 3
 
9.7%
cdfh3301262008000001 2
 
6.5%
cdfh3301262010000001 2
 
6.5%
cdfh3301262001000001 1
 
3.2%
cdfh3301261998000002 1
 
3.2%
cdfh3301262007000001 1
 
3.2%
cdfh3301261997000001 1
 
3.2%
Other values (11) 11
35.5%
2023-12-11T03:12:25.684537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
35.8%
1 82
 
13.2%
2 66
 
10.6%
3 65
 
10.5%
6 37
 
6.0%
C 31
 
5.0%
D 31
 
5.0%
F 31
 
5.0%
H 31
 
5.0%
9 12
 
1.9%
Other values (3) 12
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 496
80.0%
Uppercase Letter 124
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
44.8%
1 82
 
16.5%
2 66
 
13.3%
3 65
 
13.1%
6 37
 
7.5%
9 12
 
2.4%
8 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 31
25.0%
D 31
25.0%
F 31
25.0%
H 31
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 496
80.0%
Latin 124
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
44.8%
1 82
 
16.5%
2 66
 
13.3%
3 65
 
13.1%
6 37
 
7.5%
9 12
 
2.4%
8 5
 
1.0%
4 4
 
0.8%
7 3
 
0.6%
Latin
ValueCountFrequency (%)
C 31
25.0%
D 31
25.0%
F 31
25.0%
H 31
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
35.8%
1 82
 
13.2%
2 66
 
10.6%
3 65
 
10.5%
6 37
 
6.0%
C 31
 
5.0%
D 31
 
5.0%
F 31
 
5.0%
H 31
 
5.0%
9 12
 
1.9%
Other values (3) 12
 
1.9%

인허가일자
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20088812
Minimum19890825
Maximum20220830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:25.877075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19890825
5-th percentile19915868
Q120060356
median20100907
Q320140723
95-th percentile20210526
Maximum20220830
Range330005
Interquartile range (IQR)80366.5

Descriptive statistics

Standard deviation91956.239
Coefficient of variation (CV)0.0045774853
Kurtosis-0.24041662
Mean20088812
Median Absolute Deviation (MAD)40298
Skewness-0.62458413
Sum6.2275316 × 108
Variance8.45595 × 109
MonotonicityNot monotonic
2023-12-11T03:12:26.076111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210527 1
 
3.2%
20130820 1
 
3.2%
20131015 1
 
3.2%
20110715 1
 
3.2%
20061201 1
 
3.2%
20140619 1
 
3.2%
20080919 1
 
3.2%
20071227 1
 
3.2%
20060609 1
 
3.2%
19970228 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
19890825 1
3.2%
19891017 1
3.2%
19940719 1
3.2%
19960720 1
3.2%
19970228 1
3.2%
19980530 1
3.2%
20010614 1
3.2%
20060104 1
3.2%
20060609 1
3.2%
20060908 1
3.2%
ValueCountFrequency (%)
20220830 1
3.2%
20210527 1
3.2%
20210524 1
3.2%
20210119 1
3.2%
20201228 1
3.2%
20171017 1
3.2%
20160704 1
3.2%
20140827 1
3.2%
20140619 1
3.2%
20140603 1
3.2%

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
28 
20171204
3 

Length

Max length8
Median length4
Mean length4.3870968
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> 28
90.3%
20171204 3
 
9.7%

Length

2023-12-11T03:12:26.274361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:26.430517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
90.3%
20171204 3
 
9.7%

영업상태구분코드
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
14 
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 14
45.2%
3 10
32.3%
4 5
 
16.1%
2 2
 
6.5%

Length

2023-12-11T03:12:26.595300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:26.758947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 14
45.2%
3 10
32.3%
4 5
 
16.1%
2 2
 
6.5%

영업상태명
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업/정상
14 
폐업
10 
취소/말소/만료/정지/중지
5 
휴업
2 

Length

Max length14
Median length5
Mean length5.2903226
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 14
45.2%
폐업 10
32.3%
취소/말소/만료/정지/중지 5
 
16.1%
휴업 2
 
6.5%

Length

2023-12-11T03:12:26.956799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:27.131117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 14
45.2%
폐업 10
32.3%
취소/말소/만료/정지/중지 5
 
16.1%
휴업 2
 
6.5%

상세영업상태코드
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
13
14 
3
10 
32
3 
35
2 
2
2 

Length

Max length2
Median length2
Mean length1.6129032
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 14
45.2%
3 10
32.3%
32 3
 
9.7%
35 2
 
6.5%
2 2
 
6.5%

Length

2023-12-11T03:12:27.331522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:27.525148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 14
45.2%
3 10
32.3%
32 3
 
9.7%
35 2
 
6.5%
2 2
 
6.5%

상세영업상태명
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업중
14 
폐업
10 
신고취소
3 
직권말소
2 
휴업
2 

Length

Max length4
Median length3
Mean length2.7741935
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 14
45.2%
폐업 10
32.3%
신고취소 3
 
9.7%
직권말소 2
 
6.5%
휴업 2
 
6.5%

Length

2023-12-11T03:12:27.732072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:27.925898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 14
45.2%
폐업 10
32.3%
신고취소 3
 
9.7%
직권말소 2
 
6.5%
휴업 2
 
6.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)100.0%
Missing19
Missing (%)61.3%
Infinite0
Infinite (%)0.0%
Mean20128908
Minimum20060619
Maximum20220816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:28.091341image/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
2023-12-11T03:12:28.275011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20090406 1
 
3.2%
20090311 1
 
3.2%
20210304 1
 
3.2%
20151029 1
 
3.2%
20220816 1
 
3.2%
20120523 1
 
3.2%
20210115 1
 
3.2%
20120529 1
 
3.2%
20110113 1
 
3.2%
20060619 1
 
3.2%
Other values (2) 2
 
6.5%
(Missing) 19
61.3%
ValueCountFrequency (%)
20060619 1
3.2%
20071102 1
3.2%
20090311 1
3.2%
20090406 1
3.2%
20091027 1
3.2%
20110113 1
3.2%
20120523 1
3.2%
20120529 1
3.2%
20151029 1
3.2%
20210115 1
3.2%
ValueCountFrequency (%)
20220816 1
3.2%
20210304 1
3.2%
20210115 1
3.2%
20151029 1
3.2%
20120529 1
3.2%
20120523 1
3.2%
20110113 1
3.2%
20091027 1
3.2%
20090406 1
3.2%
20090311 1
3.2%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
29 
20220101
 
2

Length

Max length8
Median length4
Mean length4.2580645
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
93.5%
20220101 2
 
6.5%

Length

2023-12-11T03:12:28.530531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:28.704670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
93.5%
20220101 2
 
6.5%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
29 
20221231
 
2

Length

Max length8
Median length4
Mean length4.2580645
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
93.5%
20221231 2
 
6.5%

Length

2023-12-11T03:12:28.893734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:29.073806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
93.5%
20221231 2
 
6.5%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

소재지전화
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing2
Missing (%)6.5%
Memory size380.0 B
2023-12-11T03:12:29.358586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.344828
Min length8

Characters and Unicode

Total characters300
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

Unique29 ?
Unique (%)100.0%

Sample

1st row053-247-7070
2nd row053-230-3310
3rd row053-327-7780
4th row623-0005
5th row476-0077
ValueCountFrequency (%)
053-247-7070 1
 
3.4%
0537926000 1
 
3.4%
053-230-3310 1
 
3.4%
715-1200 1
 
3.4%
053-635-0200 1
 
3.4%
053-623-0099 1
 
3.4%
627-5050 1
 
3.4%
053-627-5050 1
 
3.4%
053-761-9900 1
 
3.4%
053-740-7600 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T03:12:29.934710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 82
27.3%
- 43
14.3%
5 33
11.0%
3 33
11.0%
7 31
 
10.3%
2 21
 
7.0%
6 20
 
6.7%
1 17
 
5.7%
4 8
 
2.7%
9 7
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 257
85.7%
Dash Punctuation 43
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 82
31.9%
5 33
12.8%
3 33
12.8%
7 31
 
12.1%
2 21
 
8.2%
6 20
 
7.8%
1 17
 
6.6%
4 8
 
3.1%
9 7
 
2.7%
8 5
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 82
27.3%
- 43
14.3%
5 33
11.0%
3 33
11.0%
7 31
 
10.3%
2 21
 
7.0%
6 20
 
6.7%
1 17
 
5.7%
4 8
 
2.7%
9 7
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 82
27.3%
- 43
14.3%
5 33
11.0%
3 33
11.0%
7 31
 
10.3%
2 21
 
7.0%
6 20
 
6.7%
1 17
 
5.7%
4 8
 
2.7%
9 7
 
2.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)90.9%
Missing9
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean706038.64
Minimum701843
Maximum711873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:30.145363image/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
2023-12-11T03:12:30.342028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
704805 3
 
9.7%
706822 1
 
3.2%
711872 1
 
3.2%
711812 1
 
3.2%
711833 1
 
3.2%
711873 1
 
3.2%
704828 1
 
3.2%
706745 1
 
3.2%
706803 1
 
3.2%
701843 1
 
3.2%
Other values (10) 10
32.3%
(Missing) 9
29.0%
ValueCountFrequency (%)
701843 1
 
3.2%
702714 1
 
3.2%
702748 1
 
3.2%
702851 1
 
3.2%
702864 1
 
3.2%
702894 1
 
3.2%
704805 3
9.7%
704828 1
 
3.2%
705828 1
 
3.2%
705832 1
 
3.2%
ValueCountFrequency (%)
711873 1
3.2%
711872 1
3.2%
711833 1
3.2%
711812 1
3.2%
706822 1
3.2%
706803 1
3.2%
706745 1
3.2%
706170 1
3.2%
706092 1
3.2%
706011 1
3.2%

소재지전체주소
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T03:12:30.707261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length30
Mean length23.935484
Min length17

Characters and Unicode

Total characters742
Distinct characters79
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 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 31
21.7%
수성구 10
 
7.0%
북구 8
 
5.6%
범어동 5
 
3.5%
달서구 4
 
2.8%
달성군 4
 
2.8%
태전동 4
 
2.8%
409-7 3
 
2.1%
칠성동2가 3
 
2.1%
본동 3
 
2.1%
Other values (57) 68
47.6%
2023-12-11T03:12:31.335661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
19.1%
구 58
 
7.8%
1 32
 
4.3%
동 31
 
4.2%
대 31
 
4.2%
시 31
 
4.2%
광 31
 
4.2%
역 31
 
4.2%
2 24
 
3.2%
지 24
 
3.2%
Other values (69) 307
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 410
55.3%
Decimal Number 150
 
20.2%
Space Separator 142
 
19.1%
Dash Punctuation 21
 
2.8%
Other Punctuation 7
 
0.9%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%
Uppercase Letter 3
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 58
14.1%
동 31
 
7.6%
대 31
 
7.6%
시 31
 
7.6%
광 31
 
7.6%
역 31
 
7.6%
지 24
 
5.9%
성 19
 
4.6%
번 16
 
3.9%
수 11
 
2.7%
Other values (51) 127
31.0%
Decimal Number
ValueCountFrequency (%)
1 32
21.3%
2 24
16.0%
0 19
12.7%
7 16
10.7%
5 16
10.7%
3 15
10.0%
4 10
 
6.7%
9 8
 
5.3%
6 5
 
3.3%
8 5
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 5
71.4%
. 2
 
28.6%
Space Separator
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 410
55.3%
Common 329
44.3%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 58
14.1%
동 31
 
7.6%
대 31
 
7.6%
시 31
 
7.6%
광 31
 
7.6%
역 31
 
7.6%
지 24
 
5.9%
성 19
 
4.6%
번 16
 
3.9%
수 11
 
2.7%
Other values (51) 127
31.0%
Common
ValueCountFrequency (%)
142
43.2%
1 32
 
9.7%
2 24
 
7.3%
- 21
 
6.4%
0 19
 
5.8%
7 16
 
4.9%
5 16
 
4.9%
3 15
 
4.6%
4 10
 
3.0%
9 8
 
2.4%
Other values (7) 26
 
7.9%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 410
55.3%
ASCII 332
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
42.8%
1 32
 
9.6%
2 24
 
7.2%
- 21
 
6.3%
0 19
 
5.7%
7 16
 
4.8%
5 16
 
4.8%
3 15
 
4.5%
4 10
 
3.0%
9 8
 
2.4%
Other values (8) 29
 
8.7%
Hangul
ValueCountFrequency (%)
구 58
14.1%
동 31
 
7.6%
대 31
 
7.6%
시 31
 
7.6%
광 31
 
7.6%
역 31
 
7.6%
지 24
 
5.9%
성 19
 
4.6%
번 16
 
3.9%
수 11
 
2.7%
Other values (51) 127
31.0%

도로명전체주소
Text

MISSING 

Distinct27
Distinct (%)90.0%
Missing1
Missing (%)3.2%
Memory size380.0 B
2023-12-11T03:12:31.732565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length35
Mean length28.4
Min length19

Characters and Unicode

Total characters852
Distinct characters106
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

Unique25 ?
Unique (%)83.3%

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 30
 
17.9%
수성구 10
 
6.0%
북구 8
 
4.8%
범어동 4
 
2.4%
달서구 4
 
2.4%
태전동 4
 
2.4%
칠곡중앙대로 4
 
2.4%
달구벌대로 3
 
1.8%
달성군 3
 
1.8%
칠성동2가 3
 
1.8%
Other values (74) 95
56.5%
2023-12-11T03:12:32.329308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
17.0%
구 64
 
7.5%
대 42
 
4.9%
동 37
 
4.3%
역 31
 
3.6%
시 31
 
3.6%
광 30
 
3.5%
로 29
 
3.4%
( 27
 
3.2%
) 27
 
3.2%
Other values (96) 389
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 499
58.6%
Space Separator 145
 
17.0%
Decimal Number 128
 
15.0%
Open Punctuation 27
 
3.2%
Close Punctuation 27
 
3.2%
Other Punctuation 19
 
2.2%
Uppercase Letter 5
 
0.6%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 64
 
12.8%
대 42
 
8.4%
동 37
 
7.4%
역 31
 
6.2%
시 31
 
6.2%
광 30
 
6.0%
로 29
 
5.8%
성 20
 
4.0%
수 11
 
2.2%
달 10
 
2.0%
Other values (77) 194
38.9%
Decimal Number
ValueCountFrequency (%)
1 26
20.3%
3 20
15.6%
2 18
14.1%
0 16
12.5%
4 12
9.4%
5 11
8.6%
8 9
 
7.0%
9 7
 
5.5%
6 5
 
3.9%
7 4
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 17
89.5%
. 2
 
10.5%
Uppercase Letter
ValueCountFrequency (%)
B 4
80.0%
C 1
 
20.0%
Space Separator
ValueCountFrequency (%)
145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 499
58.6%
Common 348
40.8%
Latin 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 64
 
12.8%
대 42
 
8.4%
동 37
 
7.4%
역 31
 
6.2%
시 31
 
6.2%
광 30
 
6.0%
로 29
 
5.8%
성 20
 
4.0%
수 11
 
2.2%
달 10
 
2.0%
Other values (77) 194
38.9%
Common
ValueCountFrequency (%)
145
41.7%
( 27
 
7.8%
) 27
 
7.8%
1 26
 
7.5%
3 20
 
5.7%
2 18
 
5.2%
, 17
 
4.9%
0 16
 
4.6%
4 12
 
3.4%
5 11
 
3.2%
Other values (7) 29
 
8.3%
Latin
ValueCountFrequency (%)
B 4
80.0%
C 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 499
58.6%
ASCII 353
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
41.1%
( 27
 
7.6%
) 27
 
7.6%
1 26
 
7.4%
3 20
 
5.7%
2 18
 
5.1%
, 17
 
4.8%
0 16
 
4.5%
4 12
 
3.4%
5 11
 
3.1%
Other values (9) 34
 
9.6%
Hangul
ValueCountFrequency (%)
구 64
 
12.8%
대 42
 
8.4%
동 37
 
7.4%
역 31
 
6.2%
시 31
 
6.2%
광 30
 
6.0%
로 29
 
5.8%
성 20
 
4.0%
수 11
 
2.2%
달 10
 
2.0%
Other values (77) 194
38.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)81.0%
Missing10
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean73316.095
Minimum41117
Maximum702748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:32.526567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41117
5-th percentile41179
Q141457
median42010
Q342171
95-th percentile42988
Maximum702748
Range661631
Interquartile range (IQR)714

Descriptive statistics

Standard deviation144221.89
Coefficient of variation (CV)1.9671246
Kurtosis20.999375
Mean73316.095
Median Absolute Deviation (MAD)536
Skewness4.5824781
Sum1539638
Variance2.0799955 × 1010
MonotonicityNot monotonic
2023-12-11T03:12:32.690026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
41457 3
 
9.7%
41593 2
 
6.5%
42204 2
 
6.5%
41243 1
 
3.2%
41474 1
 
3.2%
41460 1
 
3.2%
702748 1
 
3.2%
42010 1
 
3.2%
41179 1
 
3.2%
42171 1
 
3.2%
Other values (7) 7
22.6%
(Missing) 10
32.3%
ValueCountFrequency (%)
41117 1
 
3.2%
41179 1
 
3.2%
41243 1
 
3.2%
41457 3
9.7%
41460 1
 
3.2%
41474 1
 
3.2%
41593 2
6.5%
42010 1
 
3.2%
42028 1
 
3.2%
42064 1
 
3.2%
ValueCountFrequency (%)
702748 1
3.2%
42988 1
3.2%
42945 1
3.2%
42204 2
6.5%
42171 1
3.2%
42139 1
3.2%
42107 1
3.2%
42064 1
3.2%
42028 1
3.2%
42010 1
3.2%

사업장명
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T03:12:33.015326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length9.2903226
Min length5

Characters and Unicode

Total characters288
Distinct characters100
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

Unique27 ?
Unique (%)87.1%

Sample

1st row우주스포츠센터
2nd row아양아트센터
3rd row어반 웰니스 (Urban Wellness)
4th row대원레포츠
5th row효성코아 헬스장
ValueCountFrequency (%)
스포츠센터 3
 
6.2%
송림스포츠센터 2
 
4.2%
제드 2
 
4.2%
휘트니스센터 2
 
4.2%
스포츠 2
 
4.2%
선 1
 
2.1%
스포츠프라자 1
 
2.1%
인터불고 1
 
2.1%
휘트니스 1
 
2.1%
주식회사 1
 
2.1%
Other values (32) 32
66.7%
2023-12-11T03:12:33.535726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 23
 
8.0%
센 18
 
6.2%
17
 
5.9%
포 17
 
5.9%
츠 17
 
5.9%
터 17
 
5.9%
주 8
 
2.8%
트 8
 
2.8%
( 7
 
2.4%
니 7
 
2.4%
Other values (90) 149
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
83.0%
Space Separator 17
 
5.9%
Lowercase Letter 11
 
3.8%
Open Punctuation 7
 
2.4%
Close Punctuation 7
 
2.4%
Uppercase Letter 7
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 23
 
9.6%
센 18
 
7.5%
포 17
 
7.1%
츠 17
 
7.1%
터 17
 
7.1%
주 8
 
3.3%
트 8
 
3.3%
니 7
 
2.9%
아 7
 
2.9%
성 6
 
2.5%
Other values (73) 111
46.4%
Lowercase Letter
ValueCountFrequency (%)
n 2
18.2%
s 2
18.2%
l 2
18.2%
e 2
18.2%
r 1
9.1%
b 1
9.1%
a 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
D 1
14.3%
G 1
14.3%
I 1
14.3%
S 1
14.3%
T 1
14.3%
U 1
14.3%
W 1
14.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
83.0%
Common 31
 
10.8%
Latin 18
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 23
 
9.6%
센 18
 
7.5%
포 17
 
7.1%
츠 17
 
7.1%
터 17
 
7.1%
주 8
 
3.3%
트 8
 
3.3%
니 7
 
2.9%
아 7
 
2.9%
성 6
 
2.5%
Other values (73) 111
46.4%
Latin
ValueCountFrequency (%)
n 2
11.1%
s 2
11.1%
l 2
11.1%
e 2
11.1%
D 1
 
5.6%
G 1
 
5.6%
I 1
 
5.6%
S 1
 
5.6%
T 1
 
5.6%
U 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
17
54.8%
( 7
22.6%
) 7
22.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
83.0%
ASCII 49
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 23
 
9.6%
센 18
 
7.5%
포 17
 
7.1%
츠 17
 
7.1%
터 17
 
7.1%
주 8
 
3.3%
트 8
 
3.3%
니 7
 
2.9%
아 7
 
2.9%
성 6
 
2.5%
Other values (73) 111
46.4%
ASCII
ValueCountFrequency (%)
17
34.7%
( 7
14.3%
) 7
14.3%
n 2
 
4.1%
s 2
 
4.1%
l 2
 
4.1%
e 2
 
4.1%
D 1
 
2.0%
G 1
 
2.0%
I 1
 
2.0%
Other values (7) 7
14.3%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0172913 × 1013
Minimum2.0060609 × 1013
Maximum2.0220831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:33.748008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0060609 × 1013
5-th percentile2.0075465 × 1013
Q12.0135779 × 1013
median2.0200401 × 1013
Q32.0211169 × 1013
95-th percentile2.0220827 × 1013
Maximum2.0220831 × 1013
Range1.6022205 × 1011
Interquartile range (IQR)7.5389988 × 1010

Descriptive statistics

Standard deviation5.226342 × 1010
Coefficient of variation (CV)0.002590772
Kurtosis-0.43087447
Mean2.0172913 × 1013
Median Absolute Deviation (MAD)2.0422072 × 1010
Skewness-0.94202093
Sum6.2536032 × 1014
Variance2.7314651 × 1021
MonotonicityNot monotonic
2023-12-11T03:12:34.268037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20220420110408 1
 
3.2%
20220729141340 1
 
3.2%
20171204112204 1
 
3.2%
20171204112137 1
 
3.2%
20171204112027 1
 
3.2%
20220411083441 1
 
3.2%
20210509164125 1
 
3.2%
20091028100109 1
 
3.2%
20060609112009 1
 
3.2%
20060619165120 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
20060609112009 1
3.2%
20060619165120 1
3.2%
20090311193104 1
3.2%
20090406132244 1
3.2%
20091028100109 1
3.2%
20120523131249 1
3.2%
20120529140053 1
3.2%
20120529165939 1
3.2%
20151029163304 1
3.2%
20160203151132 1
3.2%
ValueCountFrequency (%)
20220831163605 1
3.2%
20220830125607 1
3.2%
20220823185723 1
3.2%
20220729141340 1
3.2%
20220420110408 1
3.2%
20220411083441 1
3.2%
20220321171110 1
3.2%
20211228144302 1
3.2%
20211110161517 1
3.2%
20210509164125 1
3.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
I
17 
U
14 

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 (%)
I 17
54.8%
U 14
45.2%

Length

2023-12-11T03:12:34.616607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:12:34.823052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 17
54.8%
u 14
45.2%

데이터갱신일자
Date

Distinct16
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2018-08-31 23:59:59
Maximum2022-09-02 02:40:00
2023-12-11T03:12:34.992770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:12:35.194550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

좌표정보(X)
Real number (ℝ)

Distinct23
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343129
Minimum330240.33
Maximum354229.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:35.401695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum330240.33
5-th percentile332116.54
Q1339596.67
median343550.45
Q3347067.23
95-th percentile351954.94
Maximum354229.47
Range23989.139
Interquartile range (IQR)7470.5529

Descriptive statistics

Standard deviation5927.3647
Coefficient of variation (CV)0.017274449
Kurtosis-0.061466947
Mean343129
Median Absolute Deviation (MAD)3766.4575
Skewness-0.37027014
Sum10636999
Variance35133652
MonotonicityNot monotonic
2023-12-11T03:12:35.626462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
339486.330243 3
 
9.7%
343260.639405 3
 
9.7%
339783.989364 3
 
9.7%
347067.226051 2
 
6.5%
347202.24792 2
 
6.5%
347850.865517 1
 
3.2%
330240.334923 1
 
3.2%
331919.96911 1
 
3.2%
334475.475586 1
 
3.2%
332313.120088 1
 
3.2%
Other values (13) 13
41.9%
ValueCountFrequency (%)
330240.334923 1
 
3.2%
331919.96911 1
 
3.2%
332313.120088 1
 
3.2%
334475.475586 1
 
3.2%
338254.88849 1
 
3.2%
339486.330243 3
9.7%
339707.015975 1
 
3.2%
339783.989364 3
9.7%
343260.639405 3
9.7%
343550.446823 1
 
3.2%
ValueCountFrequency (%)
354229.474254 1
3.2%
353999.548196 1
3.2%
349910.333288 1
3.2%
349094.598043 1
3.2%
347850.865517 1
3.2%
347202.24792 2
6.5%
347067.226051 2
6.5%
346922.110876 1
3.2%
346571.168775 1
3.2%
346507.147444 1
3.2%

좌표정보(Y)
Real number (ℝ)

Distinct23
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262715.97
Minimum245630.33
Maximum271331.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T03:12:35.828013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245630.33
5-th percentile251397.51
Q1260733.9
median263458.52
Q3265857.55
95-th percentile270625.89
Maximum271331.09
Range25700.755
Interquartile range (IQR)5123.6533

Descriptive statistics

Standard deviation5869.847
Coefficient of variation (CV)0.022342939
Kurtosis2.8179034
Mean262715.97
Median Absolute Deviation (MAD)2632.208
Skewness-1.2432463
Sum8144195.1
Variance34455104
MonotonicityNot monotonic
2023-12-11T03:12:36.029497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
270340.317289 3
 
9.7%
266077.818455 3
 
9.7%
260733.89736 3
 
9.7%
263458.521991 2
 
6.5%
259665.923686 2
 
6.5%
262414.596896 1
 
3.2%
245630.332878 1
 
3.2%
263810.755354 1
 
3.2%
256410.459464 1
 
3.2%
246384.553707 1
 
3.2%
Other values (13) 13
41.9%
ValueCountFrequency (%)
245630.332878 1
 
3.2%
246384.553707 1
 
3.2%
256410.459464 1
 
3.2%
259122.373021 1
 
3.2%
259665.923686 2
6.5%
260132.20801 1
 
3.2%
260733.89736 3
9.7%
260826.314023 1
 
3.2%
260971.516963 1
 
3.2%
261412.731435 1
 
3.2%
ValueCountFrequency (%)
271331.088251 1
 
3.2%
270911.454654 1
 
3.2%
270340.317289 3
9.7%
266077.818455 3
9.7%
265637.282898 1
 
3.2%
265123.315824 1
 
3.2%
265093.508874 1
 
3.2%
264328.348009 1
 
3.2%
264235.07481 1
 
3.2%
263810.755354 1
 
3.2%

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)41457송림스포츠프라자20220830125607I2022-09-01 00:22:26.0<NA>339486.330243270340.317289
89종합체육시설업10_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
910종합체육시설업10_37_01_P3450000CDFH330126201400000120140827<NA>1영업/정상13영업중<NA><NA><NA><NA>053-473-2000<NA>702714대구광역시 북구 태전동 993번지 701호, 801호대구광역시 북구 칠곡중앙대로 412, 701호, 801호 (태전동)41460위더스 스포츠20200401113450U2020-04-03 02:40:00.0<NA>339707.015975271331.088251
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)
2122종합체육시설업10_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
2223종합체육시설업10_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
2324종합체육시설업10_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
2425종합체육시설업10_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
2526종합체육시설업10_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
2627종합체육시설업10_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
2728종합체육시설업10_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
2829종합체육시설업10_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
2930종합체육시설업10_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
3031종합체육시설업10_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