Overview

Dataset statistics

Number of variables34
Number of observations41
Missing cells215
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.8 KiB
Average record size in memory295.2 B

Variable types

Categorical15
Text6
DateTime3
Unsupported3
Numeric7

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),의료유사업종별명,종업원수,자격증소유자수,보조종업원수,시설관리자수,기타종업원수,병상수,욕실면적,총면적
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-16373/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (83.5%)Imbalance
휴업종료일자 is highly imbalanced (83.5%)Imbalance
자격증소유자수 is highly imbalanced (71.9%)Imbalance
보조종업원수 is highly imbalanced (71.9%)Imbalance
시설관리자수 is highly imbalanced (71.9%)Imbalance
기타종업원수 is highly imbalanced (71.9%)Imbalance
인허가취소일자 has 41 (100.0%) missing valuesMissing
폐업일자 has 11 (26.8%) missing valuesMissing
재개업일자 has 41 (100.0%) missing valuesMissing
전화번호 has 2 (4.9%) missing valuesMissing
소재지면적 has 41 (100.0%) missing valuesMissing
소재지우편번호 has 14 (34.1%) missing valuesMissing
도로명주소 has 17 (41.5%) missing valuesMissing
도로명우편번호 has 17 (41.5%) missing valuesMissing
좌표정보(X) has 3 (7.3%) missing valuesMissing
좌표정보(Y) has 3 (7.3%) missing valuesMissing
종업원수 has 5 (12.2%) missing valuesMissing
병상수 has 16 (39.0%) missing valuesMissing
총면적 has 4 (9.8%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
병상수 has 1 (2.4%) zerosZeros

Reproduction

Analysis started2024-04-29 18:58:24.867162
Analysis finished2024-04-29 18:58:25.555394
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
3150000
41 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 41
100.0%

Length

2024-04-30T03:58:25.614466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:25.691209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 41
100.0%

관리번호
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-04-30T03:58:25.844582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1025
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

Unique41 ?
Unique (%)100.0%

Sample

1st rowPHMB419823150037042400001
2nd rowPHMB419893150037042400001
3rd rowPHMB419893150037042400002
4th rowPHMB419893150037042400003
5th rowPHMB419933150037042400001
ValueCountFrequency (%)
phmb419823150037042400001 1
 
2.4%
phmb420113150037042400002 1
 
2.4%
phmb420113150037042400004 1
 
2.4%
phmb420113150037042400005 1
 
2.4%
phmb420123150037042400001 1
 
2.4%
phmb420133150037042400001 1
 
2.4%
phmb420133150037042400002 1
 
2.4%
phmb420143150037042400001 1
 
2.4%
phmb420143150037042400002 1
 
2.4%
phmb420153150037042400001 1
 
2.4%
Other values (31) 31
75.6%
2024-04-30T03:58:26.133327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 318
31.0%
4 129
12.6%
1 103
 
10.0%
3 92
 
9.0%
2 84
 
8.2%
7 50
 
4.9%
5 43
 
4.2%
P 41
 
4.0%
H 41
 
4.0%
M 41
 
4.0%
Other values (4) 83
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 861
84.0%
Uppercase Letter 164
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 318
36.9%
4 129
15.0%
1 103
 
12.0%
3 92
 
10.7%
2 84
 
9.8%
7 50
 
5.8%
5 43
 
5.0%
9 33
 
3.8%
8 8
 
0.9%
6 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
P 41
25.0%
H 41
25.0%
M 41
25.0%
B 41
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 861
84.0%
Latin 164
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 318
36.9%
4 129
15.0%
1 103
 
12.0%
3 92
 
10.7%
2 84
 
9.8%
7 50
 
5.8%
5 43
 
5.0%
9 33
 
3.8%
8 8
 
0.9%
6 1
 
0.1%
Latin
ValueCountFrequency (%)
P 41
25.0%
H 41
25.0%
M 41
25.0%
B 41
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1025
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 318
31.0%
4 129
12.6%
1 103
 
10.0%
3 92
 
9.0%
2 84
 
8.2%
7 50
 
4.9%
5 43
 
4.2%
P 41
 
4.0%
H 41
 
4.0%
M 41
 
4.0%
Other values (4) 83
 
8.1%

인허가일자
Date

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum1982-06-16 00:00:00
Maximum2022-11-08 00:00:00
2024-04-30T03:58:26.266948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:58:26.372162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing41
Missing (%)100.0%
Memory size501.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
3
29 
1
10 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 29
70.7%
1 10
 
24.4%
4 2
 
4.9%

Length

2024-04-30T03:58:26.473790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:26.550716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 29
70.7%
1 10
 
24.4%
4 2
 
4.9%

영업상태명
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
폐업
29 
영업/정상
10 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length2
Mean length3.3170732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 29
70.7%
영업/정상 10
 
24.4%
취소/말소/만료/정지/중지 2
 
4.9%

Length

2024-04-30T03:58:26.649428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:26.750382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 29
70.7%
영업/정상 10
 
24.4%
취소/말소/만료/정지/중지 2
 
4.9%

상세영업상태코드
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
3
29 
13
10 
24
 
2

Length

Max length2
Median length1
Mean length1.2926829
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 29
70.7%
13 10
 
24.4%
24 2
 
4.9%

Length

2024-04-30T03:58:26.889354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:26.990694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 29
70.7%
13 10
 
24.4%
24 2
 
4.9%

상세영업상태명
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
폐업
29 
영업중
10 
직권폐업
 
2

Length

Max length4
Median length2
Mean length2.3414634
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 29
70.7%
영업중 10
 
24.4%
직권폐업 2
 
4.9%

Length

2024-04-30T03:58:27.083677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:27.177905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 29
70.7%
영업중 10
 
24.4%
직권폐업 2
 
4.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)96.7%
Missing11
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean20111327
Minimum19941026
Maximum20221228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:27.273521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19941026
5-th percentile19990444
Q120072840
median20125514
Q320161005
95-th percentile20210908
Maximum20221228
Range280202
Interquartile range (IQR)88164.75

Descriptive statistics

Standard deviation71461.567
Coefficient of variation (CV)0.0035532995
Kurtosis-0.1793978
Mean20111327
Median Absolute Deviation (MAD)44751
Skewness-0.53477101
Sum6.033398 × 108
Variance5.1067556 × 109
MonotonicityNot monotonic
2024-04-30T03:58:27.376686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20140528 2
 
4.9%
20081119 1
 
2.4%
20211216 1
 
2.4%
20210531 1
 
2.4%
20200824 1
 
2.4%
20170705 1
 
2.4%
20221228 1
 
2.4%
20161206 1
 
2.4%
20190502 1
 
2.4%
20170220 1
 
2.4%
Other values (19) 19
46.3%
(Missing) 11
26.8%
ValueCountFrequency (%)
19941026 1
2.4%
19990315 1
2.4%
19990601 1
2.4%
20001027 1
2.4%
20050331 1
2.4%
20050429 1
2.4%
20060508 1
2.4%
20070214 1
2.4%
20080718 1
2.4%
20081119 1
2.4%
ValueCountFrequency (%)
20221228 1
2.4%
20211216 1
2.4%
20210531 1
2.4%
20200824 1
2.4%
20190502 1
2.4%
20170705 1
2.4%
20170220 1
2.4%
20161206 1
2.4%
20160401 1
2.4%
20141008 1
2.4%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
40 
20140101
 
1

Length

Max length8
Median length4
Mean length4.097561
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 40
97.6%
20140101 1
 
2.4%

Length

2024-04-30T03:58:27.484626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:27.592070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
97.6%
20140101 1
 
2.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
40 
20140630
 
1

Length

Max length8
Median length4
Mean length4.097561
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 40
97.6%
20140630 1
 
2.4%

Length

2024-04-30T03:58:27.690845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:27.775926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
97.6%
20140630 1
 
2.4%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing41
Missing (%)100.0%
Memory size501.0 B

전화번호
Text

MISSING 

Distinct37
Distinct (%)94.9%
Missing2
Missing (%)4.9%
Memory size460.0 B
2024-04-30T03:58:27.937305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.769231
Min length8

Characters and Unicode

Total characters420
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

Unique35 ?
Unique (%)89.7%

Sample

1st row02-691-1055
2nd row02-2694-7063
3rd row02-696-6185
4th row02-696-7966
5th row02-2607-9922
ValueCountFrequency (%)
583-2222 2
 
5.1%
02-606-6093 2
 
5.1%
02-2664-7591 1
 
2.6%
02-2690-3382 1
 
2.6%
2602-8275 1
 
2.6%
0236638875 1
 
2.6%
0236652678 1
 
2.6%
3662-1575 1
 
2.6%
02-966-5236 1
 
2.6%
2606-2121 1
 
2.6%
Other values (27) 27
69.2%
2024-04-30T03:58:28.271046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 89
21.2%
6 67
16.0%
- 57
13.6%
0 54
12.9%
5 34
 
8.1%
3 28
 
6.7%
9 20
 
4.8%
7 20
 
4.8%
8 18
 
4.3%
1 18
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 363
86.4%
Dash Punctuation 57
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 89
24.5%
6 67
18.5%
0 54
14.9%
5 34
 
9.4%
3 28
 
7.7%
9 20
 
5.5%
7 20
 
5.5%
8 18
 
5.0%
1 18
 
5.0%
4 15
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 89
21.2%
6 67
16.0%
- 57
13.6%
0 54
12.9%
5 34
 
8.1%
3 28
 
6.7%
9 20
 
4.8%
7 20
 
4.8%
8 18
 
4.3%
1 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 89
21.2%
6 67
16.0%
- 57
13.6%
0 54
12.9%
5 34
 
8.1%
3 28
 
6.7%
9 20
 
4.8%
7 20
 
4.8%
8 18
 
4.3%
1 18
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing41
Missing (%)100.0%
Memory size501.0 B

소재지우편번호
Text

MISSING 

Distinct16
Distinct (%)59.3%
Missing14
Missing (%)34.1%
Memory size460.0 B
2024-04-30T03:58:28.405308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.037037
Min length6

Characters and Unicode

Total characters163
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

Unique12 ?
Unique (%)44.4%

Sample

1st row157016
2nd row157016
3rd row157019
4th row157011
5th row157016
ValueCountFrequency (%)
157016 7
25.9%
157019 4
14.8%
157011 2
 
7.4%
157033 2
 
7.4%
157930 1
 
3.7%
157040 1
 
3.7%
157222 1
 
3.7%
157924 1
 
3.7%
157280 1
 
3.7%
157-030 1
 
3.7%
Other values (6) 6
22.2%
2024-04-30T03:58:28.637923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 46
28.2%
5 28
17.2%
7 27
16.6%
0 23
14.1%
9 10
 
6.1%
6 8
 
4.9%
3 8
 
4.9%
2 6
 
3.7%
8 4
 
2.5%
4 2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
99.4%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 46
28.4%
5 28
17.3%
7 27
16.7%
0 23
14.2%
9 10
 
6.2%
6 8
 
4.9%
3 8
 
4.9%
2 6
 
3.7%
8 4
 
2.5%
4 2
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 163
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 46
28.2%
5 28
17.2%
7 27
16.6%
0 23
14.1%
9 10
 
6.1%
6 8
 
4.9%
3 8
 
4.9%
2 6
 
3.7%
8 4
 
2.5%
4 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 46
28.2%
5 28
17.2%
7 27
16.6%
0 23
14.1%
9 10
 
6.1%
6 8
 
4.9%
3 8
 
4.9%
2 6
 
3.7%
8 4
 
2.5%
4 2
 
1.2%

지번주소
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-04-30T03:58:28.861355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length26.658537
Min length21

Characters and Unicode

Total characters1093
Distinct characters81
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)90.2%

Sample

1st row서울특별시 강서구 화곡동 1133번지 10호
2nd row서울특별시 강서구 화곡동 1097번지 6호
3rd row서울특별시 강서구 화곡동 73번지 51호
4th row서울특별시 강서구 화곡동 924번지 14호
5th row서울특별시 강서구 화곡동 981번지 5호
ValueCountFrequency (%)
서울특별시 41
17.9%
강서구 41
17.9%
화곡동 18
 
7.9%
마곡동 8
 
3.5%
2호 5
 
2.2%
등촌동 4
 
1.7%
1호 4
 
1.7%
6호 3
 
1.3%
4호 3
 
1.3%
14호 3
 
1.3%
Other values (86) 99
43.2%
2024-04-30T03:58:29.200374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
17.2%
서 82
 
7.5%
1 51
 
4.7%
호 47
 
4.3%
시 42
 
3.8%
강 42
 
3.8%
특 41
 
3.8%
별 41
 
3.8%
구 41
 
3.8%
울 41
 
3.8%
Other values (71) 477
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 654
59.8%
Decimal Number 240
 
22.0%
Space Separator 188
 
17.2%
Other Punctuation 3
 
0.3%
Dash Punctuation 3
 
0.3%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 82
12.5%
호 47
 
7.2%
시 42
 
6.4%
강 42
 
6.4%
특 41
 
6.3%
별 41
 
6.3%
구 41
 
6.3%
울 41
 
6.3%
동 41
 
6.3%
지 40
 
6.1%
Other values (55) 196
30.0%
Decimal Number
ValueCountFrequency (%)
1 51
21.2%
2 30
12.5%
7 26
10.8%
0 25
10.4%
6 22
9.2%
9 20
 
8.3%
3 20
 
8.3%
4 18
 
7.5%
5 14
 
5.8%
8 14
 
5.8%
Space Separator
ValueCountFrequency (%)
188
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 654
59.8%
Common 438
40.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 82
12.5%
호 47
 
7.2%
시 42
 
6.4%
강 42
 
6.4%
특 41
 
6.3%
별 41
 
6.3%
구 41
 
6.3%
울 41
 
6.3%
동 41
 
6.3%
지 40
 
6.1%
Other values (55) 196
30.0%
Common
ValueCountFrequency (%)
188
42.9%
1 51
 
11.6%
2 30
 
6.8%
7 26
 
5.9%
0 25
 
5.7%
6 22
 
5.0%
9 20
 
4.6%
3 20
 
4.6%
4 18
 
4.1%
5 14
 
3.2%
Other values (5) 24
 
5.5%
Latin
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 654
59.8%
ASCII 438
40.1%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
42.9%
1 51
 
11.6%
2 30
 
6.8%
7 26
 
5.9%
0 25
 
5.7%
6 22
 
5.0%
9 20
 
4.6%
3 20
 
4.6%
4 18
 
4.1%
5 14
 
3.2%
Other values (5) 24
 
5.5%
Hangul
ValueCountFrequency (%)
서 82
12.5%
호 47
 
7.2%
시 42
 
6.4%
강 42
 
6.4%
특 41
 
6.3%
별 41
 
6.3%
구 41
 
6.3%
울 41
 
6.3%
동 41
 
6.3%
지 40
 
6.1%
Other values (55) 196
30.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct23
Distinct (%)95.8%
Missing17
Missing (%)41.5%
Memory size460.0 B
2024-04-30T03:58:29.423503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39.5
Mean length34.291667
Min length24

Characters and Unicode

Total characters823
Distinct characters98
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row서울특별시 강서구 강서로5가길 5 (화곡동)
2nd row서울특별시 강서구 화곡로 161 (화곡동, 대성빌딩703,704호)
3rd row서울특별시 강서구 화곡로 248-13 (화곡동)
4th row서울특별시 강서구 강서로 385, 1004호 (마곡동, 우성에스비타워)
5th row서울특별시 강서구 화곡로31길 67, 지층층 (화곡동)
ValueCountFrequency (%)
서울특별시 24
 
15.2%
강서구 24
 
15.2%
화곡동 9
 
5.7%
마곡동 8
 
5.1%
강서로 6
 
3.8%
공항대로 4
 
2.5%
화곡로 3
 
1.9%
등촌동 3
 
1.9%
지하1층 2
 
1.3%
13 2
 
1.3%
Other values (68) 73
46.2%
2024-04-30T03:58:29.742867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
16.3%
서 56
 
6.8%
강 32
 
3.9%
, 29
 
3.5%
곡 26
 
3.2%
로 25
 
3.0%
동 25
 
3.0%
시 25
 
3.0%
구 24
 
2.9%
) 24
 
2.9%
Other values (88) 423
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
57.4%
Space Separator 134
 
16.3%
Decimal Number 134
 
16.3%
Other Punctuation 29
 
3.5%
Close Punctuation 24
 
2.9%
Open Punctuation 24
 
2.9%
Dash Punctuation 4
 
0.5%
Letter Number 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 56
 
11.9%
강 32
 
6.8%
곡 26
 
5.5%
로 25
 
5.3%
동 25
 
5.3%
시 25
 
5.3%
구 24
 
5.1%
별 24
 
5.1%
울 24
 
5.1%
특 24
 
5.1%
Other values (71) 187
39.6%
Decimal Number
ValueCountFrequency (%)
1 21
15.7%
3 19
14.2%
0 19
14.2%
2 16
11.9%
6 15
11.2%
4 14
10.4%
5 14
10.4%
7 7
 
5.2%
8 6
 
4.5%
9 3
 
2.2%
Space Separator
ValueCountFrequency (%)
134
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
57.4%
Common 349
42.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 56
 
11.9%
강 32
 
6.8%
곡 26
 
5.5%
로 25
 
5.3%
동 25
 
5.3%
시 25
 
5.3%
구 24
 
5.1%
별 24
 
5.1%
울 24
 
5.1%
특 24
 
5.1%
Other values (71) 187
39.6%
Common
ValueCountFrequency (%)
134
38.4%
, 29
 
8.3%
) 24
 
6.9%
( 24
 
6.9%
1 21
 
6.0%
3 19
 
5.4%
0 19
 
5.4%
2 16
 
4.6%
6 15
 
4.3%
4 14
 
4.0%
Other values (5) 34
 
9.7%
Latin
ValueCountFrequency (%)
Ⅰ 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
57.4%
ASCII 350
42.5%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
38.3%
, 29
 
8.3%
) 24
 
6.9%
( 24
 
6.9%
1 21
 
6.0%
3 19
 
5.4%
0 19
 
5.4%
2 16
 
4.6%
6 15
 
4.3%
4 14
 
4.0%
Other values (6) 35
 
10.0%
Hangul
ValueCountFrequency (%)
서 56
 
11.9%
강 32
 
6.8%
곡 26
 
5.5%
로 25
 
5.3%
동 25
 
5.3%
시 25
 
5.3%
구 24
 
5.1%
별 24
 
5.1%
울 24
 
5.1%
특 24
 
5.1%
Other values (71) 187
39.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)87.5%
Missing17
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean32661.625
Minimum7510
Maximum157924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:29.860496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7510
5-th percentile7548.9
Q17631
median7733.5
Q37803
95-th percentile157779.8
Maximum157924
Range150414
Interquartile range (IQR)172

Descriptive statistics

Standard deviation57040.425
Coefficient of variation (CV)1.746405
Kurtosis1.7923991
Mean32661.625
Median Absolute Deviation (MAD)80
Skewness1.9104124
Sum783879
Variance3.2536101 × 109
MonotonicityNot monotonic
2024-04-30T03:58:29.973408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
7803 3
 
7.3%
7631 2
 
4.9%
157868 1
 
2.4%
7654 1
 
2.4%
7788 1
 
2.4%
7807 1
 
2.4%
7510 1
 
2.4%
7727 1
 
2.4%
7802 1
 
2.4%
7740 1
 
2.4%
Other values (11) 11
26.8%
(Missing) 17
41.5%
ValueCountFrequency (%)
7510 1
2.4%
7548 1
2.4%
7554 1
2.4%
7573 1
2.4%
7582 1
2.4%
7631 2
4.9%
7653 1
2.4%
7654 1
2.4%
7699 1
2.4%
7706 1
2.4%
ValueCountFrequency (%)
157924 1
 
2.4%
157868 1
 
2.4%
157280 1
 
2.4%
157015 1
 
2.4%
7807 1
 
2.4%
7803 3
7.3%
7802 1
 
2.4%
7788 1
 
2.4%
7778 1
 
2.4%
7740 1
 
2.4%

사업장명
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-04-30T03:58:30.162098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.1219512
Min length5

Characters and Unicode

Total characters292
Distinct characters84
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)90.2%

Sample

1st row강서안마시술소
2nd row현안마시술소
3rd row화성장안마시술소
4th row수성장안마시술소
5th row혜인안마시술소
ValueCountFrequency (%)
클린안마원서울6호점 2
 
4.9%
클린안마원 2
 
4.9%
약손지압원 1
 
2.4%
대명안마원 1
 
2.4%
강흥수안마원 1
 
2.4%
쾌압근통안마원 1
 
2.4%
강서안마시술소 1
 
2.4%
송인지압안마원 1
 
2.4%
등촌안마원 1
 
2.4%
지큐안마시술소 1
 
2.4%
Other values (29) 29
70.7%
2024-04-30T03:58:30.496780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 43
14.7%
안 40
 
13.7%
원 23
 
7.9%
시 18
 
6.2%
술 18
 
6.2%
소 18
 
6.2%
지 8
 
2.7%
압 7
 
2.4%
서 5
 
1.7%
성 5
 
1.7%
Other values (74) 107
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 283
96.9%
Decimal Number 6
 
2.1%
Uppercase Letter 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 43
15.2%
안 40
14.1%
원 23
 
8.1%
시 18
 
6.4%
술 18
 
6.4%
소 18
 
6.4%
지 8
 
2.8%
압 7
 
2.5%
서 5
 
1.8%
성 5
 
1.8%
Other values (67) 98
34.6%
Decimal Number
ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
8 1
16.7%
9 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
I 1
33.3%
P 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 283
96.9%
Common 6
 
2.1%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 43
15.2%
안 40
14.1%
원 23
 
8.1%
시 18
 
6.4%
술 18
 
6.4%
소 18
 
6.4%
지 8
 
2.8%
압 7
 
2.5%
서 5
 
1.8%
성 5
 
1.8%
Other values (67) 98
34.6%
Common
ValueCountFrequency (%)
6 2
33.3%
1 2
33.3%
8 1
16.7%
9 1
16.7%
Latin
ValueCountFrequency (%)
V 1
33.3%
I 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 283
96.9%
ASCII 9
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 43
15.2%
안 40
14.1%
원 23
 
8.1%
시 18
 
6.4%
술 18
 
6.4%
소 18
 
6.4%
지 8
 
2.8%
압 7
 
2.5%
서 5
 
1.8%
성 5
 
1.8%
Other values (67) 98
34.6%
ASCII
ValueCountFrequency (%)
6 2
22.2%
1 2
22.2%
8 1
11.1%
9 1
11.1%
V 1
11.1%
I 1
11.1%
P 1
11.1%

최종수정일자
Date

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum2008-12-16 15:18:18
Maximum2023-07-27 14:13:04
2024-04-30T03:58:30.606395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:58:30.714280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
I
31 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 31
75.6%
U 10
 
24.4%

Length

2024-04-30T03:58:30.816472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:30.903089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 31
75.6%
u 10
 
24.4%

데이터갱신일자
Date

Distinct14
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-06 21:00:00
2024-04-30T03:58:30.998740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:58:31.280281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

업태구분명
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
안마원
23 
안마시술소
18 

Length

Max length5
Median length3
Mean length3.8780488
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 23
56.1%
안마시술소 18
43.9%

Length

2024-04-30T03:58:31.390968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:31.503238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 23
56.1%
안마시술소 18
43.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)92.1%
Missing3
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean186175.46
Minimum183039.92
Maximum188907.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:31.593997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183039.92
5-th percentile184530.8
Q1185651.56
median186334.94
Q3186817.45
95-th percentile187649.27
Maximum188907.15
Range5867.2214
Interquartile range (IQR)1165.8901

Descriptive statistics

Standard deviation1095.7513
Coefficient of variation (CV)0.0058855842
Kurtosis2.3416105
Mean186175.46
Median Absolute Deviation (MAD)615.17654
Skewness-0.44704088
Sum7074667.4
Variance1200671
MonotonicityNot monotonic
2024-04-30T03:58:31.707352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
185520.437286264 2
 
4.9%
185882.668720873 2
 
4.9%
186335.414911828 2
 
4.9%
183366.101249557 1
 
2.4%
186036.670559053 1
 
2.4%
185573.0 1
 
2.4%
185163.0 1
 
2.4%
187511.664374039 1
 
2.4%
185318.0 1
 
2.4%
185920.208549725 1
 
2.4%
Other values (25) 25
61.0%
(Missing) 3
 
7.3%
ValueCountFrequency (%)
183039.924452506 1
2.4%
183366.101249557 1
2.4%
184736.337018716 1
2.4%
185163.0 1
2.4%
185318.0 1
2.4%
185520.437286264 2
4.9%
185559.921734415 1
2.4%
185573.0 1
2.4%
185648.751154822 1
2.4%
185660.0 1
2.4%
ValueCountFrequency (%)
188907.145870979 1
2.4%
188429.042609254 1
2.4%
187511.664374039 1
2.4%
187239.182172485 1
2.4%
187020.243445713 1
2.4%
187008.951755552 1
2.4%
186971.054506348 1
2.4%
186943.20540192 1
2.4%
186868.771611134 1
2.4%
186850.824018452 1
2.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)92.1%
Missing3
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean450019.9
Minimum447431.26
Maximum452817.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:31.823578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447431.26
5-th percentile447893.8
Q1449365.06
median450115.31
Q3450822.75
95-th percentile451537.11
Maximum452817.47
Range5386.2046
Interquartile range (IQR)1457.6919

Descriptive statistics

Standard deviation1116.1527
Coefficient of variation (CV)0.0024802297
Kurtosis0.74234553
Mean450019.9
Median Absolute Deviation (MAD)725.84776
Skewness-0.22348074
Sum17100756
Variance1245796.9
MonotonicityNot monotonic
2024-04-30T03:58:31.937119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
450132.710540539 2
 
4.9%
451525.065157834 2
 
4.9%
449470.119087541 2
 
4.9%
452817.469477897 1
 
2.4%
448909.28118647 1
 
2.4%
450813.0 1
 
2.4%
450826.0 1
 
2.4%
447972.86955028 1
 
2.4%
450914.0 1
 
2.4%
451605.394433274 1
 
2.4%
Other values (25) 25
61.0%
(Missing) 3
 
7.3%
ValueCountFrequency (%)
447431.264854637 1
2.4%
447445.743496067 1
2.4%
447972.86955028 1
2.4%
448856.181147257 1
2.4%
448909.28118647 1
2.4%
449131.455901655 1
2.4%
449137.594380745 1
2.4%
449141.845020499 1
2.4%
449259.642192635 1
2.4%
449330.037813924 1
2.4%
ValueCountFrequency (%)
452817.469477897 1
2.4%
451605.394433274 1
2.4%
451525.065157834 2
4.9%
451162.564814247 1
2.4%
450914.0 1
2.4%
450884.0 1
2.4%
450877.798368564 1
2.4%
450856.325 1
2.4%
450826.0 1
2.4%
450813.0 1
2.4%

의료유사업종별명
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
안마원
20 
안마시술소
17 
<NA>
4 

Length

Max length5
Median length4
Mean length3.9268293
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안마원 20
48.8%
안마시술소 17
41.5%
<NA> 4
 
9.8%

Length

2024-04-30T03:58:32.065162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:32.229037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안마원 20
48.8%
안마시술소 17
41.5%
na 4
 
9.8%

종업원수
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)19.4%
Missing5
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean2.4444444
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:32.335617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.25
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation1.8584855
Coefficient of variation (CV)0.76028951
Kurtosis0.13750932
Mean2.4444444
Median Absolute Deviation (MAD)1
Skewness1.1954194
Sum88
Variance3.4539683
MonotonicityNot monotonic
2024-04-30T03:58:32.449701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 16
39.0%
2 9
22.0%
6 4
 
9.8%
4 3
 
7.3%
3 2
 
4.9%
5 1
 
2.4%
7 1
 
2.4%
(Missing) 5
 
12.2%
ValueCountFrequency (%)
1 16
39.0%
2 9
22.0%
3 2
 
4.9%
4 3
 
7.3%
5 1
 
2.4%
6 4
 
9.8%
7 1
 
2.4%
ValueCountFrequency (%)
7 1
 
2.4%
6 4
 
9.8%
5 1
 
2.4%
4 3
 
7.3%
3 2
 
4.9%
2 9
22.0%
1 16
39.0%

자격증소유자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
39 
0
 
2

Length

Max length4
Median length4
Mean length3.8536585
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> 39
95.1%
0 2
 
4.9%

Length

2024-04-30T03:58:32.569168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:32.674274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
95.1%
0 2
 
4.9%

보조종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
39 
0
 
2

Length

Max length4
Median length4
Mean length3.8536585
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> 39
95.1%
0 2
 
4.9%

Length

2024-04-30T03:58:32.808668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:32.920380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
95.1%
0 2
 
4.9%

시설관리자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
39 
0
 
2

Length

Max length4
Median length4
Mean length3.8536585
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> 39
95.1%
0 2
 
4.9%

Length

2024-04-30T03:58:33.031669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:33.139281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
95.1%
0 2
 
4.9%

기타종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
39 
0
 
2

Length

Max length4
Median length4
Mean length3.8536585
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> 39
95.1%
0 2
 
4.9%

Length

2024-04-30T03:58:33.228093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:33.313474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 39
95.1%
0 2
 
4.9%

병상수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)64.0%
Missing16
Missing (%)39.0%
Infinite0
Infinite (%)0.0%
Mean12.88
Minimum0
Maximum28
Zeros1
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:33.383040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.2
Q14
median17
Q319
95-th percentile22.6
Maximum28
Range28
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.212389
Coefficient of variation (CV)0.63760784
Kurtosis-1.2549252
Mean12.88
Median Absolute Deviation (MAD)5
Skewness-0.22047125
Sum322
Variance67.443333
MonotonicityNot monotonic
2024-04-30T03:58:33.475332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
19 3
 
7.3%
18 3
 
7.3%
17 3
 
7.3%
21 2
 
4.9%
3 2
 
4.9%
2 2
 
4.9%
28 1
 
2.4%
9 1
 
2.4%
23 1
 
2.4%
12 1
 
2.4%
Other values (6) 6
 
14.6%
(Missing) 16
39.0%
ValueCountFrequency (%)
0 1
2.4%
1 1
2.4%
2 2
4.9%
3 2
4.9%
4 1
2.4%
5 1
2.4%
9 1
2.4%
10 1
2.4%
12 1
2.4%
16 1
2.4%
ValueCountFrequency (%)
28 1
 
2.4%
23 1
 
2.4%
21 2
4.9%
19 3
7.3%
18 3
7.3%
17 3
7.3%
16 1
 
2.4%
12 1
 
2.4%
10 1
 
2.4%
9 1
 
2.4%

욕실면적
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
<NA>
36 
0
5 

Length

Max length4
Median length4
Mean length3.6341463
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> 36
87.8%
0 5
 
12.2%

Length

2024-04-30T03:58:33.573891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:58:33.657988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
87.8%
0 5
 
12.2%

총면적
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)94.6%
Missing4
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean277.19973
Minimum33.95
Maximum804.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-30T03:58:33.750959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.95
5-th percentile41.312
Q161.42
median90.09
Q3458.06
95-th percentile765.528
Maximum804.72
Range770.77
Interquartile range (IQR)396.64

Descriptive statistics

Standard deviation260.71004
Coefficient of variation (CV)0.94051331
Kurtosis-0.84658028
Mean277.19973
Median Absolute Deviation (MAD)49.53
Skewness0.77304166
Sum10256.39
Variance67969.723
MonotonicityNot monotonic
2024-04-30T03:58:33.861012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
804.72 2
 
4.9%
84.0 2
 
4.9%
67.86 1
 
2.4%
82.76 1
 
2.4%
59.28 1
 
2.4%
46.23 1
 
2.4%
33.95 1
 
2.4%
53.55 1
 
2.4%
103.08 1
 
2.4%
61.42 1
 
2.4%
Other values (25) 25
61.0%
(Missing) 4
 
9.8%
ValueCountFrequency (%)
33.95 1
2.4%
40.56 1
2.4%
41.5 1
2.4%
46.23 1
2.4%
47.61 1
2.4%
52.92 1
2.4%
53.55 1
2.4%
56.0 1
2.4%
59.28 1
2.4%
61.42 1
2.4%
ValueCountFrequency (%)
804.72 2
4.9%
755.73 1
2.4%
735.84 1
2.4%
643.96 1
2.4%
631.24 1
2.4%
568.45 1
2.4%
498.37 1
2.4%
486.61 1
2.4%
458.06 1
2.4%
447.81 1
2.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
03150000PHMB41982315003704240000119820616<NA>3폐업3폐업20001027<NA><NA><NA>02-691-1055<NA>157016서울특별시 강서구 화곡동 1133번지 10호<NA><NA>강서안마시술소2008-12-16 15:18:18I2018-08-31 23:59:59.0안마시술소186943.205402449954.580881안마시술소6<NA><NA><NA><NA>17<NA>274.71
13150000PHMB41989315003704240000119890518<NA>3폐업3폐업20081119<NA><NA><NA>02-2694-7063<NA>157016서울특별시 강서구 화곡동 1097번지 6호<NA><NA>현안마시술소2008-12-16 15:36:00I2018-08-31 23:59:59.0안마시술소186717.341727450157.356071안마시술소5<NA><NA><NA><NA>18<NA>486.61
23150000PHMB41989315003704240000219890630<NA>3폐업3폐업19941026<NA><NA><NA>02-696-6185<NA>157019서울특별시 강서구 화곡동 73번지 51호<NA><NA>화성장안마시술소2008-12-16 15:38:08I2018-08-31 23:59:59.0안마시술소186335.414912449470.119088안마시술소6<NA><NA><NA><NA>18<NA>498.37
33150000PHMB41989315003704240000319890808<NA>3폐업3폐업19990601<NA><NA><NA>02-696-7966<NA>157011서울특별시 강서구 화곡동 924번지 14호<NA><NA>수성장안마시술소2008-12-16 15:40:11I2018-08-31 23:59:59.0안마시술소185942.421105447445.743496안마시술소4<NA><NA><NA><NA>12<NA>447.81
43150000PHMB41993315003704240000119930630<NA>3폐업3폐업20080718<NA><NA><NA>02-2607-9922<NA>157016서울특별시 강서구 화곡동 981번지 5호<NA><NA>혜인안마시술소2008-12-16 15:42:16I2018-08-31 23:59:59.0안마시술소186554.679916449751.875759안마시술소2<NA><NA><NA><NA>21<NA>735.84
53150000PHMB41993315003704240000219931011<NA>3폐업3폐업19990315<NA><NA><NA>02-606-6093<NA>157016서울특별시 강서구 화곡동 29번지 65호<NA><NA>명성안마시술소2008-12-16 15:44:05I2018-08-31 23:59:59.0안마시술소186516.527278449330.037814안마시술소6<NA><NA><NA><NA>19<NA>804.72
63150000PHMB41994315003704240000119940121<NA>3폐업3폐업20070214<NA><NA><NA>02-2690-5562<NA>157016서울특별시 강서구 화곡동 1107번지 3호<NA><NA>화곡온천안마시술소2008-12-16 15:49:30I2018-08-31 23:59:59.0안마시술소187020.243446450286.461903안마시술소4<NA><NA><NA><NA>28<NA>643.96
73150000PHMB41994315003704240000219941129<NA>3폐업3폐업20081219<NA><NA><NA>02-2604-1400<NA>157019서울특별시 강서구 화곡동 73번지 51호<NA><NA>화성안마시술소2010-03-17 16:02:25I2018-08-31 23:59:59.0안마시술소186335.414912449470.119088안마시술소2<NA><NA><NA><NA>17<NA>411.27
83150000PHMB41996315003704240000119960916<NA>3폐업3폐업20091125<NA><NA><NA>02-2604-9365<NA>157016서울특별시 강서구 화곡동 987번지 11호<NA><NA>신라안마시술소2010-01-19 16:25:50I2018-08-31 23:59:59.0안마시술소186499.299693449823.419295안마시술소4<NA><NA><NA><NA>9<NA>458.06
93150000PHMB41997315003704240000119970328<NA>3폐업3폐업20090108<NA><NA><NA>02-3665-3546<NA>157040서울특별시 강서구 염창동 252번지 16호<NA><NA>VIP안마시술소2009-01-08 16:32:45I2018-08-31 23:59:59.0안마시술소188907.145871449738.825007안마시술소2<NA><NA><NA><NA>23<NA>631.24
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)의료유사업종별명종업원수자격증소유자수보조종업원수시설관리자수기타종업원수병상수욕실면적총면적
313150000PHMB42017315003704240000120170322<NA>1영업/정상13영업중<NA><NA><NA><NA>0236652678<NA><NA>서울특별시 강서구 등촌동 684번지 3호 2층203호서울특별시 강서구 강서로 462, 2층 203호 (등촌동, 대룡드림타워-1)7573마곡지압안마원2017-03-23 09:33:57I2018-08-31 23:59:59.0안마원185920.20855451605.394433안마원1<NA><NA><NA><NA><NA><NA>67.86
323150000PHMB42017315003704240000220170526<NA>3폐업3폐업<NA><NA><NA><NA>0226587588<NA><NA>서울특별시 강서구 마곡동 796번지 6호 403호서울특별시 강서구 마곡중앙6로 65, 403호 (마곡동, 지투프라자)7803리커버리마사지안마원2022-07-19 15:11:54U2021-12-06 22:01:00.0안마원185318.0450914.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>
333150000PHMB42017315003704240000320171215<NA>1영업/정상13영업중<NA><NA><NA><NA>0220615515<NA><NA>서울특별시 강서구 화곡동 828번지 23호서울특별시 강서구 곰달래로53가길 13, 지층 (화곡동)77408복안마원2017-12-18 17:33:40I2018-08-31 23:59:59.0안마원187511.664374447972.86955안마원<NA><NA><NA><NA><NA><NA><NA>61.42
343150000PHMB42018315003704240000120181001<NA>1영업/정상13영업중<NA><NA><NA><NA>0236647572<NA><NA>서울특별시 강서구 마곡동 774번지 4호 마곡센트럴타워Ⅰ 406호서울특별시 강서구 공항대로 227, 마곡센트럴타워Ⅰ 406호 (마곡동)7802바른척추안마원2020-10-16 18:01:10U2020-10-18 02:40:00.0안마원185163.0450826.0안마원2<NA><NA><NA><NA>3<NA>76.67
353150000PHMB42018315003704240000220181203<NA>1영업/정상13영업중<NA><NA><NA><NA>15448538<NA><NA>서울특별시 강서구 마곡동 797번지 14호 힐스테이트에코마곡 318호서울특별시 강서구 공항대로 269-15, 힐스테이트에코마곡 318호 (마곡동)7803참손길지압힐링안마원2019-08-29 17:45:57U2019-08-31 02:40:00.0안마원185573.0450813.0안마원1<NA><NA><NA><NA>5090.09
363150000PHMB42018315003704240000320181130<NA>1영업/정상13영업중<NA><NA><NA><NA>0226032354<NA><NA>서울특별시 강서구 화곡동 107번지 6호 주병빌딩(3층)서울특별시 강서구 까치산로 23-9, 주병빌딩 3층 (화곡동)7727대명안마원2018-12-10 13:25:58I2018-12-12 02:20:14.0안마원186036.670559448909.281186안마원1<NA><NA><NA><NA>3056.0
373150000PHMB42019315003704240000120190820<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2664-7591<NA><NA>서울특별시 강서구 방화동 829번지 4호 금강프라자빌딩서울특별시 강서구 금낭화로 135, 금강프라자빌딩 6층 610호 (방화동)7510약손지압원2019-08-20 17:39:07I2019-08-22 02:22:07.0안마원183366.10125452817.469478안마원1<NA><NA><NA><NA>2<NA>40.56
383150000PHMB42019315003704240000220191002<NA>3폐업3폐업20210531<NA><NA><NA>02-2662-7333<NA><NA>서울특별시 강서구 마곡동 798번지 2호 류마타워서울특별시 강서구 공항대로 164, 류마타워 509호 (마곡동)7807쾌압근통안마원2021-05-31 11:38:35U2021-06-02 02:40:00.0안마원<NA><NA>안마원1<NA><NA><NA><NA>2<NA>52.92
393150000PHMB42019315003704240000320191128<NA>3폐업3폐업20211216<NA><NA><NA>02-852-5588<NA><NA>서울특별시 강서구 마곡동 759번지 1호 두산더랜드타워서울특별시 강서구 마곡서로 152, 두산더랜드타워 304호 (마곡동)7788강흥수안마원2021-12-16 17:20:05U2021-12-18 02:40:00.0안마원<NA><NA>안마원100004041.5
403150000PHMB42022315003704240000120221108<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 799-11 파인스퀘어서울특별시 강서구 마곡중앙4로 22, 파인스퀘어 A동 307호 (마곡동)7631두손안마원2022-11-11 10:07:02I2021-10-31 23:03:00.0안마원<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>