Overview

Dataset statistics

Number of variables37
Number of observations56
Missing cells628
Missing cells (%)30.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory321.4 B

Variable types

Numeric10
Categorical13
Text5
Unsupported9

Dataset

Description6270000_대구광역시_10_35_01_P_수영장업_6월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000090373&dataSetDetailId=DDI_0000090406&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
문화체육업종명 has constant value ""Constant
공사립구분명 has constant value ""Constant
건축물동수 is highly imbalanced (69.9%)Imbalance
인허가취소일자 has 56 (100.0%) missing valuesMissing
폐업일자 has 29 (51.8%) missing valuesMissing
휴업시작일자 has 56 (100.0%) missing valuesMissing
휴업종료일자 has 56 (100.0%) missing valuesMissing
재개업일자 has 56 (100.0%) missing valuesMissing
소재지전화 has 10 (17.9%) missing valuesMissing
소재지면적 has 56 (100.0%) missing valuesMissing
소재지우편번호 has 23 (41.1%) missing valuesMissing
소재지전체주소 has 2 (3.6%) missing valuesMissing
도로명전체주소 has 5 (8.9%) missing valuesMissing
도로명우편번호 has 16 (28.6%) missing valuesMissing
업태구분명 has 56 (100.0%) missing valuesMissing
건축물연면적 has 39 (69.6%) missing valuesMissing
회원모집총인원 has 56 (100.0%) missing valuesMissing
세부업종명 has 56 (100.0%) missing valuesMissing
법인명 has 56 (100.0%) missing valuesMissing
번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
회원모집총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 20:50:31.397888
Analysis finished2023-12-10 20:50:32.193314
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:50:32.320890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.75
Q114.75
median28.5
Q342.25
95-th percentile53.25
Maximum56
Range55
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation16.309506
Coefficient of variation (CV)0.57226338
Kurtosis-1.2
Mean28.5
Median Absolute Deviation (MAD)14
Skewness0
Sum1596
Variance266
MonotonicityStrictly increasing
2023-12-11T05:50:32.634558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
30 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
수영장업
56 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영장업 56
100.0%

Length

2023-12-11T05:50:32.892044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:33.053077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장업 56
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
10_35_01_P
56 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10_35_01_P 56
100.0%

Length

2023-12-11T05:50:33.279191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:33.502805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10_35_01_p 56
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3455535.7
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:50:33.688948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13440000
median3460000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation18676.153
Coefficient of variation (CV)0.0054047056
Kurtosis-0.12896613
Mean3455535.7
Median Absolute Deviation (MAD)10000
Skewness-0.80781785
Sum1.9351 × 108
Variance3.487987 × 108
MonotonicityIncreasing
2023-12-11T05:50:33.903940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 15
26.8%
3460000 14
25.0%
3440000 6
 
10.7%
3450000 6
 
10.7%
3480000 6
 
10.7%
3430000 4
 
7.1%
3420000 3
 
5.4%
3410000 2
 
3.6%
ValueCountFrequency (%)
3410000 2
 
3.6%
3420000 3
 
5.4%
3430000 4
 
7.1%
3440000 6
 
10.7%
3450000 6
 
10.7%
3460000 14
25.0%
3470000 15
26.8%
3480000 6
 
10.7%
ValueCountFrequency (%)
3480000 6
 
10.7%
3470000 15
26.8%
3460000 14
25.0%
3450000 6
 
10.7%
3440000 6
 
10.7%
3430000 4
 
7.1%
3420000 3
 
5.4%
3410000 2
 
3.6%

관리번호
Text

Distinct29
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-11T05:50:34.312562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1120
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

Unique14 ?
Unique (%)25.0%

Sample

1st rowCDFH3301011996000001
2nd rowCDFH3301012002000001
3rd rowCDFH3301012016000001
4th rowCDFH3301012011000001
5th rowCDFH3301012002000001
ValueCountFrequency (%)
cdfh3301012003000001 5
 
8.9%
cdfh3301012002000001 5
 
8.9%
cdfh3301012019000001 4
 
7.1%
cdfh3301012004000001 3
 
5.4%
cdfh3301012015000001 3
 
5.4%
cdfh3301012017000001 3
 
5.4%
cdfh3301012010000001 3
 
5.4%
cdfh3301012012000001 2
 
3.6%
cdfh3301012007000001 2
 
3.6%
cdfh3301012009000001 2
 
3.6%
Other values (19) 24
42.9%
2023-12-11T05:50:34.917505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 472
42.1%
1 199
17.8%
3 119
 
10.6%
2 68
 
6.1%
C 56
 
5.0%
D 56
 
5.0%
F 56
 
5.0%
H 56
 
5.0%
9 14
 
1.2%
5 7
 
0.6%
Other values (4) 17
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 896
80.0%
Uppercase Letter 224
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 472
52.7%
1 199
22.2%
3 119
 
13.3%
2 68
 
7.6%
9 14
 
1.6%
5 7
 
0.8%
7 6
 
0.7%
4 5
 
0.6%
6 4
 
0.4%
8 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
C 56
25.0%
D 56
25.0%
F 56
25.0%
H 56
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 896
80.0%
Latin 224
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 472
52.7%
1 199
22.2%
3 119
 
13.3%
2 68
 
7.6%
9 14
 
1.6%
5 7
 
0.8%
7 6
 
0.7%
4 5
 
0.6%
6 4
 
0.4%
8 2
 
0.2%
Latin
ValueCountFrequency (%)
C 56
25.0%
D 56
25.0%
F 56
25.0%
H 56
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 472
42.1%
1 199
17.8%
3 119
 
10.6%
2 68
 
6.1%
C 56
 
5.0%
D 56
 
5.0%
F 56
 
5.0%
H 56
 
5.0%
9 14
 
1.2%
5 7
 
0.6%
Other values (4) 17
 
1.5%

인허가일자
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20098566
Minimum19960701
Maximum20210416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:50:35.200663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19960701
5-th percentile20005297
Q120031227
median20101162
Q320153249
95-th percentile20193280
Maximum20210416
Range249715
Interquartile range (IQR)122021.75

Descriptive statistics

Standard deviation67891.525
Coefficient of variation (CV)0.0033779289
Kurtosis-1.2353296
Mean20098566
Median Absolute Deviation (MAD)60696.5
Skewness-0.052549143
Sum1.1255197 × 109
Variance4.6092591 × 109
MonotonicityNot monotonic
2023-12-11T05:50:35.449937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960701 1
 
1.8%
20120402 1
 
1.8%
20050620 1
 
1.8%
20020503 1
 
1.8%
20111006 1
 
1.8%
20110630 1
 
1.8%
20070221 1
 
1.8%
20170726 1
 
1.8%
20210416 1
 
1.8%
20170630 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
19960701 1
1.8%
19990218 1
1.8%
19990818 1
1.8%
20010123 1
1.8%
20010913 1
1.8%
20020409 1
1.8%
20020503 1
1.8%
20020827 1
1.8%
20020902 1
1.8%
20021214 1
1.8%
ValueCountFrequency (%)
20210416 1
1.8%
20210406 1
1.8%
20200115 1
1.8%
20191001 1
1.8%
20190920 1
1.8%
20190528 1
1.8%
20190404 1
1.8%
20181215 1
1.8%
20171219 1
1.8%
20170726 1
1.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
1
29 
3
23 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row4
5th row1

Common Values

ValueCountFrequency (%)
1 29
51.8%
3 23
41.1%
4 4
 
7.1%

Length

2023-12-11T05:50:35.714541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:35.922640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
51.8%
3 23
41.1%
4 4
 
7.1%

영업상태명
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
영업/정상
29 
폐업
23 
취소/말소/만료/정지/중지
4 

Length

Max length14
Median length5
Mean length4.4107143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 29
51.8%
폐업 23
41.1%
취소/말소/만료/정지/중지 4
 
7.1%

Length

2023-12-11T05:50:36.179156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:36.391326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 29
51.8%
폐업 23
41.1%
취소/말소/만료/정지/중지 4
 
7.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
13
29 
3
23 
35
4 

Length

Max length2
Median length2
Mean length1.5892857
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row13
4th row35
5th row13

Common Values

ValueCountFrequency (%)
13 29
51.8%
3 23
41.1%
35 4
 
7.1%

Length

2023-12-11T05:50:36.630598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:36.855335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 29
51.8%
3 23
41.1%
35 4
 
7.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
영업중
29 
폐업
23 
직권말소
4 

Length

Max length4
Median length3
Mean length2.6607143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 29
51.8%
폐업 23
41.1%
직권말소 4
 
7.1%

Length

2023-12-11T05:50:37.106116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:50:37.367706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 29
51.8%
폐업 23
41.1%
직권말소 4
 
7.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)96.3%
Missing29
Missing (%)51.8%
Infinite0
Infinite (%)0.0%
Mean20126444
Minimum20030108
Maximum20210408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:50:37.601678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030108
5-th percentile20033239
Q120085312
median20140827
Q320170521
95-th percentile20204339
Maximum20210408
Range180300
Interquartile range (IQR)85209

Descriptive statistics

Standard deviation53692.449
Coefficient of variation (CV)0.0026677563
Kurtosis-0.95325858
Mean20126444
Median Absolute Deviation (MAD)39276
Skewness-0.3081416
Sum5.4341399 × 108
Variance2.8828791 × 109
MonotonicityNot monotonic
2023-12-11T05:50:37.919919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
20150102 2
 
3.6%
20070221 1
 
1.8%
20110616 1
 
1.8%
20040524 1
 
1.8%
20170727 1
 
1.8%
20180103 1
 
1.8%
20061024 1
 
1.8%
20210408 1
 
1.8%
20101109 1
 
1.8%
20150305 1
 
1.8%
Other values (16) 16
28.6%
(Missing) 29
51.8%
ValueCountFrequency (%)
20030108 1
1.8%
20030117 1
1.8%
20040524 1
1.8%
20061024 1
1.8%
20070221 1
1.8%
20071126 1
1.8%
20080313 1
1.8%
20090311 1
1.8%
20100907 1
1.8%
20101109 1
1.8%
ValueCountFrequency (%)
20210408 1
1.8%
20210223 1
1.8%
20190611 1
1.8%
20180103 1
1.8%
20171013 1
1.8%
20170727 1
1.8%
20170524 1
1.8%
20170518 1
1.8%
20170405 1
1.8%
20150305 1
1.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

소재지전화
Text

MISSING 

Distinct45
Distinct (%)97.8%
Missing10
Missing (%)17.9%
Memory size580.0 B
2023-12-11T05:50:38.431583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.608696
Min length8

Characters and Unicode

Total characters488
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

Unique44 ?
Unique (%)95.7%

Sample

1st row253-9800
2nd row250-6813
3rd row053-793-6452
4th row053-951-6400
5th row986-5012
ValueCountFrequency (%)
053-213-2211 2
 
4.3%
588-8003 1
 
2.2%
253-9800 1
 
2.2%
053-621-0468 1
 
2.2%
764-0235 1
 
2.2%
742-6868 1
 
2.2%
761-4200 1
 
2.2%
053-602-7114 1
 
2.2%
053-592-1956 1
 
2.2%
053-721-7942 1
 
2.2%
Other values (35) 35
76.1%
2023-12-11T05:50:39.220526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76
15.6%
- 75
15.4%
5 65
13.3%
3 54
11.1%
2 42
8.6%
1 35
7.2%
7 33
6.8%
6 33
6.8%
8 28
 
5.7%
4 27
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 413
84.6%
Dash Punctuation 75
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
18.4%
5 65
15.7%
3 54
13.1%
2 42
10.2%
1 35
8.5%
7 33
8.0%
6 33
8.0%
8 28
 
6.8%
4 27
 
6.5%
9 20
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76
15.6%
- 75
15.4%
5 65
13.3%
3 54
11.1%
2 42
8.6%
1 35
7.2%
7 33
6.8%
6 33
6.8%
8 28
 
5.7%
4 27
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76
15.6%
- 75
15.4%
5 65
13.3%
3 54
11.1%
2 42
8.6%
1 35
7.2%
7 33
6.8%
6 33
6.8%
8 28
 
5.7%
4 27
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)81.8%
Missing23
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean705159.03
Minimum700070
Maximum711839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:50:39.554926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700070
5-th percentile701133.8
Q1703815
median704923
Q3705837
95-th percentile711821.2
Maximum711839
Range11769
Interquartile range (IQR)2022

Descriptive statistics

Standard deviation2726.6194
Coefficient of variation (CV)0.003866673
Kurtosis1.8508387
Mean705159.03
Median Absolute Deviation (MAD)1108
Skewness0.89892413
Sum23270248
Variance7434453.2
MonotonicityNot monotonic
2023-12-11T05:51:36.256493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
705837 3
 
5.4%
704945 2
 
3.6%
704915 2
 
3.6%
700070 2
 
3.6%
703815 2
 
3.6%
705828 1
 
1.8%
704130 1
 
1.8%
711839 1
 
1.8%
711835 1
 
1.8%
711812 1
 
1.8%
Other values (17) 17
30.4%
(Missing) 23
41.1%
ValueCountFrequency (%)
700070 2
3.6%
701843 1
1.8%
702714 1
1.8%
702835 1
1.8%
702845 1
1.8%
702894 1
1.8%
703815 2
3.6%
703830 1
1.8%
704130 1
1.8%
704735 1
1.8%
ValueCountFrequency (%)
711839 1
 
1.8%
711835 1
 
1.8%
711812 1
 
1.8%
706841 1
 
1.8%
706828 1
 
1.8%
706808 1
 
1.8%
706170 1
 
1.8%
706160 1
 
1.8%
705837 3
5.4%
705828 1
 
1.8%

소재지전체주소
Text

MISSING 

Distinct51
Distinct (%)94.4%
Missing2
Missing (%)3.6%
Memory size580.0 B
2023-12-11T05:51:36.735419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length23.962963
Min length18

Characters and Unicode

Total characters1294
Distinct characters124
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

Unique48 ?
Unique (%)88.9%

Sample

1st row대구광역시 중구 덕산동 110번지
2nd row대구광역시 중구 덕산동 110번지
3rd row대구광역시 동구 동호동 107-13번지
4th row대구광역시 동구 효목동 1084번지 동구문화체육회관
5th row대구광역시 동구 방촌동 1047번지
ValueCountFrequency (%)
대구광역시 54
 
21.7%
수성구 14
 
5.6%
달서구 13
 
5.2%
북구 6
 
2.4%
남구 6
 
2.4%
달성군 6
 
2.4%
서구 4
 
1.6%
89-2번지 3
 
1.2%
만촌동 3
 
1.2%
다사읍 3
 
1.2%
Other values (111) 137
55.0%
2023-12-11T05:51:37.533758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
19.2%
구 105
 
8.1%
대 58
 
4.5%
시 56
 
4.3%
동 55
 
4.3%
광 54
 
4.2%
역 54
 
4.2%
1 49
 
3.8%
지 47
 
3.6%
번 43
 
3.3%
Other values (114) 525
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 785
60.7%
Space Separator 248
 
19.2%
Decimal Number 221
 
17.1%
Dash Punctuation 36
 
2.8%
Other Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 105
 
13.4%
대 58
 
7.4%
시 56
 
7.1%
동 55
 
7.0%
광 54
 
6.9%
역 54
 
6.9%
지 47
 
6.0%
번 43
 
5.5%
성 28
 
3.6%
수 20
 
2.5%
Other values (99) 265
33.8%
Decimal Number
ValueCountFrequency (%)
1 49
22.2%
2 29
13.1%
7 26
11.8%
3 26
11.8%
0 23
10.4%
5 17
 
7.7%
4 17
 
7.7%
9 16
 
7.2%
8 11
 
5.0%
6 7
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 785
60.7%
Common 507
39.2%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 105
 
13.4%
대 58
 
7.4%
시 56
 
7.1%
동 55
 
7.0%
광 54
 
6.9%
역 54
 
6.9%
지 47
 
6.0%
번 43
 
5.5%
성 28
 
3.6%
수 20
 
2.5%
Other values (99) 265
33.8%
Common
ValueCountFrequency (%)
248
48.9%
1 49
 
9.7%
- 36
 
7.1%
2 29
 
5.7%
7 26
 
5.1%
3 26
 
5.1%
0 23
 
4.5%
5 17
 
3.4%
4 17
 
3.4%
9 16
 
3.2%
Other values (3) 20
 
3.9%
Latin
ValueCountFrequency (%)
C 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 785
60.7%
ASCII 509
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
48.7%
1 49
 
9.6%
- 36
 
7.1%
2 29
 
5.7%
7 26
 
5.1%
3 26
 
5.1%
0 23
 
4.5%
5 17
 
3.3%
4 17
 
3.3%
9 16
 
3.1%
Other values (5) 22
 
4.3%
Hangul
ValueCountFrequency (%)
구 105
 
13.4%
대 58
 
7.4%
시 56
 
7.1%
동 55
 
7.0%
광 54
 
6.9%
역 54
 
6.9%
지 47
 
6.0%
번 43
 
5.5%
성 28
 
3.6%
수 20
 
2.5%
Other values (99) 265
33.8%

도로명전체주소
Text

MISSING 

Distinct51
Distinct (%)100.0%
Missing5
Missing (%)8.9%
Memory size580.0 B
2023-12-11T05:51:38.000968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length29.392157
Min length21

Characters and Unicode

Total characters1499
Distinct characters154
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row대구광역시 동구 경안로 722, B1층 (동호동)
2nd row대구광역시 동구 효동로2길 24 (효목동,동구문화체육회관)
3rd row대구광역시 동구 동촌로 168 (방촌동, 대구동촌초등학교)
4th row대구광역시 서구 문화로 322 (비산동)
5th row대구광역시 서구 문화로 322, 5층 (비산동)
ValueCountFrequency (%)
대구광역시 51
 
17.4%
달서구 14
 
4.8%
수성구 14
 
4.8%
남구 6
 
2.0%
달구벌대로 5
 
1.7%
달성군 5
 
1.7%
북구 5
 
1.7%
40 4
 
1.4%
지하1층 4
 
1.4%
서구 4
 
1.4%
Other values (147) 181
61.8%
2023-12-11T05:51:38.694886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
249
 
16.6%
구 112
 
7.5%
대 72
 
4.8%
동 63
 
4.2%
시 52
 
3.5%
광 51
 
3.4%
역 51
 
3.4%
( 48
 
3.2%
) 48
 
3.2%
로 46
 
3.1%
Other values (144) 707
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 925
61.7%
Space Separator 249
 
16.6%
Decimal Number 193
 
12.9%
Open Punctuation 48
 
3.2%
Close Punctuation 48
 
3.2%
Other Punctuation 31
 
2.1%
Uppercase Letter 4
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 112
 
12.1%
대 72
 
7.8%
동 63
 
6.8%
시 52
 
5.6%
광 51
 
5.5%
역 51
 
5.5%
로 46
 
5.0%
성 30
 
3.2%
달 26
 
2.8%
수 22
 
2.4%
Other values (127) 400
43.2%
Decimal Number
ValueCountFrequency (%)
1 39
20.2%
2 31
16.1%
3 24
12.4%
0 20
10.4%
4 17
8.8%
5 17
8.8%
6 16
8.3%
7 14
 
7.3%
8 9
 
4.7%
9 6
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
C 1
 
25.0%
Space Separator
ValueCountFrequency (%)
249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 925
61.7%
Common 570
38.0%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 112
 
12.1%
대 72
 
7.8%
동 63
 
6.8%
시 52
 
5.6%
광 51
 
5.5%
역 51
 
5.5%
로 46
 
5.0%
성 30
 
3.2%
달 26
 
2.8%
수 22
 
2.4%
Other values (127) 400
43.2%
Common
ValueCountFrequency (%)
249
43.7%
( 48
 
8.4%
) 48
 
8.4%
1 39
 
6.8%
2 31
 
5.4%
, 31
 
5.4%
3 24
 
4.2%
0 20
 
3.5%
4 17
 
3.0%
5 17
 
3.0%
Other values (5) 46
 
8.1%
Latin
ValueCountFrequency (%)
B 3
75.0%
C 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 925
61.7%
ASCII 574
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
43.4%
( 48
 
8.4%
) 48
 
8.4%
1 39
 
6.8%
2 31
 
5.4%
, 31
 
5.4%
3 24
 
4.2%
0 20
 
3.5%
4 17
 
3.0%
5 17
 
3.0%
Other values (7) 50
 
8.7%
Hangul
ValueCountFrequency (%)
구 112
 
12.1%
대 72
 
7.8%
동 63
 
6.8%
시 52
 
5.6%
광 51
 
5.5%
역 51
 
5.5%
로 46
 
5.0%
성 30
 
3.2%
달 26
 
2.8%
수 22
 
2.4%
Other values (127) 400
43.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)97.5%
Missing16
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean141549.48
Minimum41078
Maximum705837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:51:38.912048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41078
5-th percentile41409.8
Q142057.75
median42281
Q342754.25
95-th percentile704924.1
Maximum705837
Range664759
Interquartile range (IQR)696.5

Descriptive statistics

Standard deviation239454.88
Coefficient of variation (CV)1.6916691
Kurtosis2.2626083
Mean141549.48
Median Absolute Deviation (MAD)466.5
Skewness2.0376079
Sum5661979
Variance5.7338639 × 1010
MonotonicityNot monotonic
2023-12-11T05:51:39.126853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
42157 2
 
3.6%
42029 1
 
1.8%
42171 1
 
1.8%
42064 1
 
1.8%
42758 1
 
1.8%
42699 1
 
1.8%
42753 1
 
1.8%
42746 1
 
1.8%
704130 1
 
1.8%
704945 1
 
1.8%
Other values (29) 29
51.8%
(Missing) 16
28.6%
ValueCountFrequency (%)
41078 1
1.8%
41159 1
1.8%
41423 1
1.8%
41515 1
1.8%
41559 1
1.8%
41759 1
1.8%
41775 1
1.8%
41789 1
1.8%
42029 1
1.8%
42039 1
1.8%
ValueCountFrequency (%)
705837 1
1.8%
704945 1
1.8%
704923 1
1.8%
704130 1
1.8%
703815 1
1.8%
702714 1
1.8%
42938 1
1.8%
42929 1
1.8%
42915 1
1.8%
42758 1
1.8%

사업장명
Text

Distinct51
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-11T05:51:39.430724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length8.9464286
Min length4

Characters and Unicode

Total characters501
Distinct characters143
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

Unique46 ?
Unique (%)82.1%

Sample

1st row삼성수영장
2nd row삼성수영장
3rd row월드스포츠스쿨 아쿠아센터
4th row동구스포츠 수영센타
5th row동촌아쿠아수영장
ValueCountFrequency (%)
수영장 11
 
13.6%
삼성수영장 2
 
2.5%
웃는얼굴아트센터수영장 2
 
2.5%
수성수영장 2
 
2.5%
실외수영장 2
 
2.5%
아쿠아센터 2
 
2.5%
월드스포츠스쿨 2
 
2.5%
짐스아쿠아 2
 
2.5%
p&s 1
 
1.2%
삼산스포츠 1
 
1.2%
Other values (54) 54
66.7%
2023-12-11T05:51:40.010964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 32
 
6.4%
수 31
 
6.2%
영 27
 
5.4%
장 27
 
5.4%
25
 
5.0%
아 21
 
4.2%
포 15
 
3.0%
터 13
 
2.6%
센 13
 
2.6%
츠 12
 
2.4%
Other values (133) 285
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
90.4%
Space Separator 25
 
5.0%
Open Punctuation 10
 
2.0%
Close Punctuation 10
 
2.0%
Uppercase Letter 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 32
 
7.1%
수 31
 
6.8%
영 27
 
6.0%
장 27
 
6.0%
아 21
 
4.6%
포 15
 
3.3%
터 13
 
2.9%
센 13
 
2.9%
츠 12
 
2.6%
주 10
 
2.2%
Other values (127) 252
55.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
90.4%
Common 46
 
9.2%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 32
 
7.1%
수 31
 
6.8%
영 27
 
6.0%
장 27
 
6.0%
아 21
 
4.6%
포 15
 
3.3%
터 13
 
2.9%
센 13
 
2.9%
츠 12
 
2.6%
주 10
 
2.2%
Other values (127) 252
55.6%
Common
ValueCountFrequency (%)
25
54.3%
( 10
 
21.7%
) 10
 
21.7%
& 1
 
2.2%
Latin
ValueCountFrequency (%)
S 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
90.4%
ASCII 48
 
9.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 32
 
7.1%
수 31
 
6.8%
영 27
 
6.0%
장 27
 
6.0%
아 21
 
4.6%
포 15
 
3.3%
터 13
 
2.9%
센 13
 
2.9%
츠 12
 
2.6%
주 10
 
2.2%
Other values (127) 252
55.6%
ASCII
ValueCountFrequency (%)
25
52.1%
( 10
 
20.8%
) 10
 
20.8%
S 1
 
2.1%
& 1
 
2.1%
P 1
 
2.1%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.016222 × 1013
Minimum2.0030117 × 1013
Maximum2.0210624 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:51:40.257374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030117 × 1013
5-th percentile2.0068061 × 1013
Q12.014098 × 1013
median2.0185808 × 1013
Q32.0200424 × 1013
95-th percentile2.0210515 × 1013
Maximum2.0210624 × 1013
Range1.8050702 × 1011
Interquartile range (IQR)5.9443463 × 1010

Descriptive statistics

Standard deviation5.0327195 × 1010
Coefficient of variation (CV)0.0024961138
Kurtosis0.33333476
Mean2.016222 × 1013
Median Absolute Deviation (MAD)1.5398519 × 1010
Skewness-1.1782417
Sum1.1290843 × 1015
Variance2.5328266 × 1021
MonotonicityNot monotonic
2023-12-11T05:51:40.478589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030120094828 1
 
1.8%
20190808172507 1
 
1.8%
20070406170343 1
 
1.8%
20170405124436 1
 
1.8%
20171013142916 1
 
1.8%
20170518171046 1
 
1.8%
20200727170448 1
 
1.8%
20210624160855 1
 
1.8%
20210509155131 1
 
1.8%
20210624111643 1
 
1.8%
Other values (46) 46
82.1%
ValueCountFrequency (%)
20030117143036 1
1.8%
20030120094828 1
1.8%
20061026185828 1
1.8%
20070406170343 1
1.8%
20071029150300 1
1.8%
20071116150014 1
1.8%
20080313135031 1
1.8%
20090311193051 1
1.8%
20100914095132 1
1.8%
20101109094234 1
1.8%
ValueCountFrequency (%)
20210624160855 1
1.8%
20210624111643 1
1.8%
20210531162058 1
1.8%
20210509155131 1
1.8%
20210409093651 1
1.8%
20210325155225 1
1.8%
20210312162117 1
1.8%
20210223164544 1
1.8%
20201202161645 1
1.8%
20201118160243 1
1.8%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
I
29 
U
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 29
51.8%
U 27
48.2%

Length

2023-12-11T05:51:40.688891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:40.831042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 29
51.8%
u 27
48.2%

데이터갱신일자
Categorical

Distinct26
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
2018-08-31 23:59:59.0
27 
2019-04-24 02:40:00.0
3 
2019-07-12 02:40:00.0
 
2
2021-06-26 02:40:00.0
 
2
2019-09-28 02:40:00.0
 
1
Other values (21)
21 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique22 ?
Unique (%)39.3%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2019-07-17 02:40:00.0
4th row2018-08-31 23:59:59.0
5th row2020-04-24 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 27
48.2%
2019-04-24 02:40:00.0 3
 
5.4%
2019-07-12 02:40:00.0 2
 
3.6%
2021-06-26 02:40:00.0 2
 
3.6%
2019-09-28 02:40:00.0 1
 
1.8%
2020-04-24 02:40:00.0 1
 
1.8%
2021-02-25 02:40:00.0 1
 
1.8%
2021-03-27 02:40:00.0 1
 
1.8%
2020-11-20 02:40:00.0 1
 
1.8%
2020-01-05 02:40:00.0 1
 
1.8%
Other values (16) 16
28.6%

Length

2023-12-11T05:51:41.030697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 27
24.1%
02:40:00.0 27
24.1%
23:59:59.0 27
24.1%
2019-04-24 3
 
2.7%
2019-07-12 2
 
1.8%
2021-06-26 2
 
1.8%
2018-12-18 1
 
0.9%
2020-07-29 1
 
0.9%
2021-05-11 1
 
0.9%
2021-04-11 1
 
0.9%
Other values (20) 20
17.9%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

좌표정보(X)
Real number (ℝ)

Distinct46
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343009.81
Minimum331685.39
Maximum355472.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:51:41.204217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331685.39
5-th percentile334191.13
Q1338590.45
median343540.3
Q3346337.97
95-th percentile354036.69
Maximum355472.43
Range23787.037
Interquartile range (IQR)7747.5219

Descriptive statistics

Standard deviation5735.9077
Coefficient of variation (CV)0.016722285
Kurtosis-0.27369241
Mean343009.81
Median Absolute Deviation (MAD)4046.1383
Skewness0.2364739
Sum19208549
Variance32900637
MonotonicityNot monotonic
2023-12-11T05:51:41.403335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
344928.975006 3
 
5.4%
345417.083514 3
 
5.4%
337497.848974 3
 
5.4%
343787.134091 2
 
3.6%
341042.349189 2
 
3.6%
341510.862642 2
 
3.6%
331685.390023 2
 
3.6%
346571.168775 1
 
1.8%
349910.333288 1
 
1.8%
334303.395884 1
 
1.8%
Other values (36) 36
64.3%
ValueCountFrequency (%)
331685.390023 2
3.6%
333854.317766 1
 
1.8%
334303.395884 1
 
1.8%
334580.0 1
 
1.8%
336455.611689 1
 
1.8%
337497.848974 3
5.4%
337679.419373 1
 
1.8%
337807.0 1
 
1.8%
338012.0 1
 
1.8%
338088.341393 1
 
1.8%
ValueCountFrequency (%)
355472.42694 1
1.8%
354740.350322 1
1.8%
354148.12465 1
1.8%
353999.548196 1
1.8%
353740.640174 1
1.8%
349910.333288 1
1.8%
349670.669719 1
1.8%
349094.598043 1
1.8%
348665.873375 1
1.8%
347783.240397 1
1.8%

좌표정보(Y)
Real number (ℝ)

Distinct46
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262786.03
Minimum255360.48
Maximum272441.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:51:41.606024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum255360.48
5-th percentile258832.5
Q1260826.05
median262233.8
Q3264308.24
95-th percentile269177.07
Maximum272441.47
Range17080.997
Interquartile range (IQR)3482.1945

Descriptive statistics

Standard deviation3267.7109
Coefficient of variation (CV)0.012434873
Kurtosis1.5523416
Mean262786.03
Median Absolute Deviation (MAD)1665.0617
Skewness0.83504488
Sum14716018
Variance10677934
MonotonicityNot monotonic
2023-12-11T05:51:41.900911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
262392.127882 3
 
5.4%
260825.254495 3
 
5.4%
261409.692978 3
 
5.4%
264065.576741 2
 
3.6%
261843.246105 2
 
3.6%
265077.849795 2
 
3.6%
263366.296869 2
 
3.6%
260826.314023 1
 
1.8%
264894.753601 1
 
1.8%
261431.686003 1
 
1.8%
Other values (36) 36
64.3%
ValueCountFrequency (%)
255360.475912 1
1.8%
256588.430623 1
1.8%
258064.058453 1
1.8%
259088.64231 1
1.8%
259384.0 1
1.8%
259416.0 1
1.8%
259794.008602 1
1.8%
259925.20324 1
1.8%
260393.619602 1
1.8%
260632.745332 1
1.8%
ValueCountFrequency (%)
272441.47305 1
1.8%
271331.088251 1
1.8%
270911.454654 1
1.8%
268598.942833 1
1.8%
267901.294823 1
1.8%
266758.595001 1
1.8%
265952.52682 1
1.8%
265637.282898 1
1.8%
265077.849795 2
3.6%
264894.753601 1
1.8%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
수영장업
56 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영장업 56
100.0%

Length

2023-12-11T05:51:42.127755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:42.282698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장업 56
100.0%

공사립구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
사립
56 

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 56
100.0%

Length

2023-12-11T05:51:42.478519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:42.692581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 56
100.0%

보험가입여부코드
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
26 
Y
20 
0
10 

Length

Max length4
Median length1
Mean length2.3928571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 26
46.4%
Y 20
35.7%
0 10
 
17.9%

Length

2023-12-11T05:51:42.888607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:43.059128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
46.4%
y 20
35.7%
0 10
 
17.9%

지도자수
Categorical

Distinct4
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
35 
2
12 
1
8 
3
 
1

Length

Max length4
Median length4
Mean length2.875
Min length1

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row<NA>
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
<NA> 35
62.5%
2 12
 
21.4%
1 8
 
14.3%
3 1
 
1.8%

Length

2023-12-11T05:51:43.250632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:43.427764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
62.5%
2 12
 
21.4%
1 8
 
14.3%
3 1
 
1.8%

건축물동수
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size580.0 B
<NA>
53 
1
 
3

Length

Max length4
Median length4
Mean length3.8392857
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> 53
94.6%
1 3
 
5.4%

Length

2023-12-11T05:51:43.591499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:51:43.735303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
94.6%
1 3
 
5.4%

건축물연면적
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)88.2%
Missing39
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean23090.261
Minimum999.33
Maximum116479
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T05:51:43.865477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum999.33
5-th percentile1306.194
Q11988.01
median8677.87
Q319532.53
95-th percentile116479
Maximum116479
Range115479.67
Interquartile range (IQR)17544.52

Descriptive statistics

Standard deviation37496.695
Coefficient of variation (CV)1.6239182
Kurtosis3.4713468
Mean23090.261
Median Absolute Deviation (MAD)6703.01
Skewness2.1256175
Sum392534.43
Variance1.4060021 × 109
MonotonicityNot monotonic
2023-12-11T05:51:44.034271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
116479.0 2
 
3.6%
8677.87 2
 
3.6%
1974.86 1
 
1.8%
11680.42 1
 
1.8%
4884.0 1
 
1.8%
2913.0 1
 
1.8%
3961.98 1
 
1.8%
14899.0 1
 
1.8%
54874.56 1
 
1.8%
21489.27 1
 
1.8%
Other values (5) 5
 
8.9%
(Missing) 39
69.6%
ValueCountFrequency (%)
999.33 1
1.8%
1382.91 1
1.8%
1640.82 1
1.8%
1974.86 1
1.8%
1988.01 1
1.8%
2913.0 1
1.8%
3961.98 1
1.8%
4884.0 1
1.8%
8677.87 2
3.6%
11680.42 1
1.8%
ValueCountFrequency (%)
116479.0 2
3.6%
54874.56 1
1.8%
21489.27 1
1.8%
19532.53 1
1.8%
14899.0 1
1.8%
11680.42 1
1.8%
8677.87 2
3.6%
4884.0 1
1.8%
3961.98 1
1.8%
2913.0 1
1.8%

회원모집총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
01수영장업10_35_01_P3410000CDFH330101199600000119960701<NA>3폐업3폐업20030108<NA><NA><NA>253-9800<NA>700070대구광역시 중구 덕산동 110번지<NA><NA>삼성수영장20030120094828I2018-08-31 23:59:59.0<NA>343787.134091264065.576741수영장업사립0<NA><NA>116479.0<NA><NA><NA>
12수영장업10_35_01_P3410000CDFH330101200200000120021214<NA>3폐업3폐업20030117<NA><NA><NA>250-6813<NA>700070대구광역시 중구 덕산동 110번지<NA><NA>삼성수영장20030117143036I2018-08-31 23:59:59.0<NA>343787.134091264065.576741수영장업사립01<NA>116479.0<NA><NA><NA>
23수영장업10_35_01_P3420000CDFH330101201600000120161202<NA>1영업/정상13영업중<NA><NA><NA><NA>053-793-6452<NA><NA>대구광역시 동구 동호동 107-13번지대구광역시 동구 경안로 722, B1층 (동호동)41078월드스포츠스쿨 아쿠아센터20190715173351U2019-07-17 02:40:00.0<NA>354740.350322264308.47143수영장업사립<NA>2<NA>1974.86<NA><NA><NA>
34수영장업10_35_01_P3420000CDFH330101201100000120110715<NA>4취소/말소/만료/정지/중지35직권말소20130404<NA><NA><NA>053-951-6400<NA>701843대구광역시 동구 효목동 1084번지 동구문화체육회관대구광역시 동구 효동로2길 24 (효목동,동구문화체육회관)<NA>동구스포츠 수영센타20130404093709I2018-08-31 23:59:59.0<NA>349094.598043265637.282898수영장업사립<NA>2<NA>11680.42<NA><NA><NA>
45수영장업10_35_01_P3420000CDFH330101200200000120020827<NA>1영업/정상13영업중<NA><NA><NA><NA>986-5012<NA><NA>대구광역시 동구 방촌동 1047번지대구광역시 동구 동촌로 168 (방촌동, 대구동촌초등학교)41159동촌아쿠아수영장20200422132657U2020-04-24 02:40:00.0<NA>349670.669719265952.52682수영장업사립<NA>2<NA><NA><NA><NA><NA>
56수영장업10_35_01_P3430000CDFH330101200500000120050330<NA>3폐업3폐업20150112<NA><NA><NA><NA><NA>703815대구광역시 서구 비산동 475-2번지대구광역시 서구 문화로 322 (비산동)703815나인스포츠20150112165711I2018-08-31 23:59:59.0<NA>341510.862642265077.849795수영장업사립<NA><NA><NA><NA><NA><NA><NA>
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