Overview

Dataset statistics

Number of variables34
Number of observations133
Missing cells1124
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.8 KiB
Average record size in memory291.0 B

Variable types

Categorical14
Text6
DateTime4
Unsupported6
Numeric4

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),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-19854/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (93.6%)Imbalance
휴업종료일자 is highly imbalanced (93.6%)Imbalance
보험가입여부코드 is highly imbalanced (77.2%)Imbalance
회원모집총인원 is highly imbalanced (67.2%)Imbalance
인허가취소일자 has 133 (100.0%) missing valuesMissing
폐업일자 has 81 (60.9%) missing valuesMissing
재개업일자 has 133 (100.0%) missing valuesMissing
전화번호 has 58 (43.6%) missing valuesMissing
소재지면적 has 133 (100.0%) missing valuesMissing
소재지우편번호 has 85 (63.9%) missing valuesMissing
도로명주소 has 7 (5.3%) missing valuesMissing
도로명우편번호 has 25 (18.8%) missing valuesMissing
업태구분명 has 133 (100.0%) missing valuesMissing
좌표정보(X) has 6 (4.5%) missing valuesMissing
좌표정보(Y) has 6 (4.5%) missing valuesMissing
건축물연면적 has 58 (43.6%) missing valuesMissing
세부업종명 has 133 (100.0%) missing valuesMissing
법인명 has 133 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
건축물연면적 has 23 (17.3%) zerosZeros

Reproduction

Analysis started2024-05-17 23:01:43.275313
Analysis finished2024-05-17 23:01:44.514394
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3020000
133 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 133
100.0%

Length

2024-05-18T08:01:44.727482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:45.028949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 133
100.0%

관리번호
Text

UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T08:01:45.489685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2660
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

Unique133 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061990000001
4th rowCDFH3301061990000002
5th rowCDFH3301061991000001
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.8%
cdfh3301062014000002 1
 
0.8%
cdfh3301062019000005 1
 
0.8%
cdfh3301062019000004 1
 
0.8%
cdfh3301062019000003 1
 
0.8%
cdfh3301062019000002 1
 
0.8%
cdfh3301062019000001 1
 
0.8%
cdfh3301062018000005 1
 
0.8%
cdfh3301062018000004 1
 
0.8%
cdfh3301062018000003 1
 
0.8%
Other values (123) 123
92.5%
2024-05-18T08:01:46.381536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1086
40.8%
3 305
 
11.5%
1 257
 
9.7%
2 188
 
7.1%
6 151
 
5.7%
C 133
 
5.0%
D 133
 
5.0%
F 133
 
5.0%
H 133
 
5.0%
9 57
 
2.1%
Other values (4) 84
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2128
80.0%
Uppercase Letter 532
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1086
51.0%
3 305
 
14.3%
1 257
 
12.1%
2 188
 
8.8%
6 151
 
7.1%
9 57
 
2.7%
4 30
 
1.4%
5 21
 
1.0%
7 21
 
1.0%
8 12
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 133
25.0%
D 133
25.0%
F 133
25.0%
H 133
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2128
80.0%
Latin 532
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1086
51.0%
3 305
 
14.3%
1 257
 
12.1%
2 188
 
8.8%
6 151
 
7.1%
9 57
 
2.7%
4 30
 
1.4%
5 21
 
1.0%
7 21
 
1.0%
8 12
 
0.6%
Latin
ValueCountFrequency (%)
C 133
25.0%
D 133
25.0%
F 133
25.0%
H 133
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1086
40.8%
3 305
 
11.5%
1 257
 
9.7%
2 188
 
7.1%
6 151
 
5.7%
C 133
 
5.0%
D 133
 
5.0%
F 133
 
5.0%
H 133
 
5.0%
9 57
 
2.1%
Other values (4) 84
 
3.2%

인허가일자
Date

Distinct127
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1989-12-22 00:00:00
Maximum2023-11-09 00:00:00
2024-05-18T08:01:46.947799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:01:47.307220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
80 
3
48 
4
 
4
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 80
60.2%
3 48
36.1%
4 4
 
3.0%
2 1
 
0.8%

Length

2024-05-18T08:01:47.717007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:48.037863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 80
60.2%
3 48
36.1%
4 4
 
3.0%
2 1
 
0.8%

영업상태명
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
80 
폐업
48 
취소/말소/만료/정지/중지
 
4
휴업
 
1

Length

Max length14
Median length5
Mean length4.1654135
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 80
60.2%
폐업 48
36.1%
취소/말소/만료/정지/중지 4
 
3.0%
휴업 1
 
0.8%

Length

2024-05-18T08:01:48.384626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:48.718206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 80
60.2%
폐업 48
36.1%
취소/말소/만료/정지/중지 4
 
3.0%
휴업 1
 
0.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
13
80 
3
48 
35
 
4
2
 
1

Length

Max length2
Median length2
Mean length1.6315789
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
13 80
60.2%
3 48
36.1%
35 4
 
3.0%
2 1
 
0.8%

Length

2024-05-18T08:01:49.115066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:49.447337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 80
60.2%
3 48
36.1%
35 4
 
3.0%
2 1
 
0.8%

상세영업상태명
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업중
80 
폐업
48 
직권말소
 
4
휴업
 
1

Length

Max length4
Median length3
Mean length2.6616541
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 80
60.2%
폐업 48
36.1%
직권말소 4
 
3.0%
휴업 1
 
0.8%

Length

2024-05-18T08:01:49.849128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:50.231071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 80
60.2%
폐업 48
36.1%
직권말소 4
 
3.0%
휴업 1
 
0.8%

폐업일자
Date

MISSING 

Distinct44
Distinct (%)84.6%
Missing81
Missing (%)60.9%
Memory size1.2 KiB
Minimum1996-10-02 00:00:00
Maximum2023-07-13 00:00:00
2024-05-18T08:01:50.876560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:01:51.357543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
132 
20221114
 
1

Length

Max length8
Median length4
Mean length4.0300752
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
99.2%
20221114 1
 
0.8%

Length

2024-05-18T08:01:51.945728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:52.294427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 132
99.2%
20221114 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
132 
20231113
 
1

Length

Max length8
Median length4
Mean length4.0300752
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
99.2%
20231113 1
 
0.8%

Length

2024-05-18T08:01:52.714544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:01:53.125784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 132
99.2%
20231113 1
 
0.8%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Text

MISSING 

Distinct75
Distinct (%)100.0%
Missing58
Missing (%)43.6%
Memory size1.2 KiB
2024-05-18T08:01:53.943574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.666667
Min length8

Characters and Unicode

Total characters800
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

Unique75 ?
Unique (%)100.0%

Sample

1st row796-0831
2nd row797-3402
3rd row796-6940
4th row02-777-3579
5th row02-795-9966
ValueCountFrequency (%)
795-9333 1
 
1.3%
02-790-8770 1
 
1.3%
02-797-7665 1
 
1.3%
02-794-8281 1
 
1.3%
02-792-1030 1
 
1.3%
02-794-7300 1
 
1.3%
02-714-8880 1
 
1.3%
02-2138-7011 1
 
1.3%
02-749-9880 1
 
1.3%
070-7630-1531 1
 
1.3%
Other values (65) 65
86.7%
2024-05-18T08:01:55.398813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 141
17.6%
- 133
16.6%
7 111
13.9%
2 100
12.5%
9 75
9.4%
1 47
 
5.9%
4 45
 
5.6%
8 40
 
5.0%
6 38
 
4.8%
3 37
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 667
83.4%
Dash Punctuation 133
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 141
21.1%
7 111
16.6%
2 100
15.0%
9 75
11.2%
1 47
 
7.0%
4 45
 
6.7%
8 40
 
6.0%
6 38
 
5.7%
3 37
 
5.5%
5 33
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 141
17.6%
- 133
16.6%
7 111
13.9%
2 100
12.5%
9 75
9.4%
1 47
 
5.9%
4 45
 
5.6%
8 40
 
5.0%
6 38
 
4.8%
3 37
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 141
17.6%
- 133
16.6%
7 111
13.9%
2 100
12.5%
9 75
9.4%
1 47
 
5.9%
4 45
 
5.6%
8 40
 
5.0%
6 38
 
4.8%
3 37
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

소재지우편번호
Text

MISSING 

Distinct31
Distinct (%)64.6%
Missing85
Missing (%)63.9%
Memory size1.2 KiB
2024-05-18T08:01:56.133822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0625
Min length6

Characters and Unicode

Total characters291
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

Unique21 ?
Unique (%)43.8%

Sample

1st row140887
2nd row140160
3rd row140887
4th row140819
5th row140879
ValueCountFrequency (%)
140887 6
 
12.5%
140901 5
 
10.4%
140893 2
 
4.2%
140160 2
 
4.2%
140892 2
 
4.2%
140884 2
 
4.2%
140871 2
 
4.2%
140900 2
 
4.2%
140132 2
 
4.2%
140133 2
 
4.2%
Other values (21) 21
43.8%
2024-05-18T08:01:57.945432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 69
23.7%
0 64
22.0%
4 54
18.6%
8 40
13.7%
9 16
 
5.5%
7 14
 
4.8%
3 13
 
4.5%
6 9
 
3.1%
2 7
 
2.4%
- 3
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 288
99.0%
Dash Punctuation 3
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 69
24.0%
0 64
22.2%
4 54
18.8%
8 40
13.9%
9 16
 
5.6%
7 14
 
4.9%
3 13
 
4.5%
6 9
 
3.1%
2 7
 
2.4%
5 2
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 69
23.7%
0 64
22.0%
4 54
18.6%
8 40
13.7%
9 16
 
5.5%
7 14
 
4.8%
3 13
 
4.5%
6 9
 
3.1%
2 7
 
2.4%
- 3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 69
23.7%
0 64
22.0%
4 54
18.6%
8 40
13.7%
9 16
 
5.5%
7 14
 
4.8%
3 13
 
4.5%
6 9
 
3.1%
2 7
 
2.4%
- 3
 
1.0%

지번주소
Text

Distinct130
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T08:01:59.079606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length25.368421
Min length16

Characters and Unicode

Total characters3374
Distinct characters129
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

Unique127 ?
Unique (%)95.5%

Sample

1st row서울특별시 용산구 한남동 657-70번지
2nd row서울특별시 용산구 남영동 182-3번지 지상5층
3rd row서울특별시 용산구 한남동 621-1번지
4th row서울특별시 용산구 동자동 14-27번지
5th row서울특별시 용산구 한강로3가 16-58번지 지하1층
ValueCountFrequency (%)
서울특별시 133
21.1%
용산구 133
21.1%
한남동 38
 
6.0%
이태원동 15
 
2.4%
지하1층 12
 
1.9%
이촌동 10
 
1.6%
남영동 9
 
1.4%
후암동 9
 
1.4%
한강로3가 9
 
1.4%
원효로1가 6
 
1.0%
Other values (197) 256
40.6%
2024-05-18T08:02:00.428504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
596
 
17.7%
1 148
 
4.4%
용 140
 
4.1%
산 139
 
4.1%
서 137
 
4.1%
시 137
 
4.1%
울 134
 
4.0%
특 133
 
3.9%
별 133
 
3.9%
구 133
 
3.9%
Other values (119) 1544
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1971
58.4%
Decimal Number 657
 
19.5%
Space Separator 596
 
17.7%
Dash Punctuation 123
 
3.6%
Uppercase Letter 15
 
0.4%
Other Punctuation 6
 
0.2%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 140
 
7.1%
산 139
 
7.1%
서 137
 
7.0%
시 137
 
7.0%
울 134
 
6.8%
특 133
 
6.7%
별 133
 
6.7%
구 133
 
6.7%
동 119
 
6.0%
지 114
 
5.8%
Other values (91) 652
33.1%
Uppercase Letter
ValueCountFrequency (%)
I 3
20.0%
B 2
13.3%
G 2
13.3%
V 1
 
6.7%
H 1
 
6.7%
A 1
 
6.7%
E 1
 
6.7%
T 1
 
6.7%
L 1
 
6.7%
S 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 148
22.5%
2 97
14.8%
3 93
14.2%
0 62
9.4%
4 60
9.1%
6 60
9.1%
7 43
 
6.5%
5 38
 
5.8%
8 32
 
4.9%
9 24
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
. 2
33.3%
: 1
 
16.7%
Space Separator
ValueCountFrequency (%)
596
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1971
58.4%
Common 1388
41.1%
Latin 15
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 140
 
7.1%
산 139
 
7.1%
서 137
 
7.0%
시 137
 
7.0%
울 134
 
6.8%
특 133
 
6.7%
별 133
 
6.7%
구 133
 
6.7%
동 119
 
6.0%
지 114
 
5.8%
Other values (91) 652
33.1%
Common
ValueCountFrequency (%)
596
42.9%
1 148
 
10.7%
- 123
 
8.9%
2 97
 
7.0%
3 93
 
6.7%
0 62
 
4.5%
4 60
 
4.3%
6 60
 
4.3%
7 43
 
3.1%
5 38
 
2.7%
Other values (7) 68
 
4.9%
Latin
ValueCountFrequency (%)
I 3
20.0%
B 2
13.3%
G 2
13.3%
V 1
 
6.7%
H 1
 
6.7%
A 1
 
6.7%
E 1
 
6.7%
T 1
 
6.7%
L 1
 
6.7%
S 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1971
58.4%
ASCII 1403
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
596
42.5%
1 148
 
10.5%
- 123
 
8.8%
2 97
 
6.9%
3 93
 
6.6%
0 62
 
4.4%
4 60
 
4.3%
6 60
 
4.3%
7 43
 
3.1%
5 38
 
2.7%
Other values (18) 83
 
5.9%
Hangul
ValueCountFrequency (%)
용 140
 
7.1%
산 139
 
7.1%
서 137
 
7.0%
시 137
 
7.0%
울 134
 
6.8%
특 133
 
6.7%
별 133
 
6.7%
구 133
 
6.7%
동 119
 
6.0%
지 114
 
5.8%
Other values (91) 652
33.1%

도로명주소
Text

MISSING 

Distinct123
Distinct (%)97.6%
Missing7
Missing (%)5.3%
Memory size1.2 KiB
2024-05-18T08:02:01.290679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length43
Mean length33.119048
Min length22

Characters and Unicode

Total characters4173
Distinct characters179
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

Unique120 ?
Unique (%)95.2%

Sample

1st row서울특별시 용산구 대사관로31길 19 (한남동)
2nd row서울특별시 용산구 청파로 48 (한강로3가,지하1층)
3rd row서울특별시 용산구 보광로 123 (이태원동)
4th row서울특별시 용산구 장문로 96, 지하 1층 (보광동)
5th row서울특별시 용산구 두텁바위로1길 110 (후암동,지하1층)
ValueCountFrequency (%)
서울특별시 126
 
15.8%
용산구 126
 
15.8%
한남동 34
 
4.2%
지하1층 15
 
1.9%
한강대로 14
 
1.8%
3층 14
 
1.8%
이태원동 14
 
1.8%
2층 12
 
1.5%
1층 10
 
1.2%
4층 10
 
1.2%
Other values (262) 425
53.1%
2024-05-18T08:02:02.634488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
690
 
16.5%
로 147
 
3.5%
서 145
 
3.5%
, 138
 
3.3%
산 136
 
3.3%
용 135
 
3.2%
시 132
 
3.2%
1 129
 
3.1%
) 128
 
3.1%
( 128
 
3.1%
Other values (169) 2265
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2442
58.5%
Space Separator 690
 
16.5%
Decimal Number 606
 
14.5%
Other Punctuation 140
 
3.4%
Close Punctuation 128
 
3.1%
Open Punctuation 128
 
3.1%
Uppercase Letter 22
 
0.5%
Dash Punctuation 16
 
0.4%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 147
 
6.0%
서 145
 
5.9%
산 136
 
5.6%
용 135
 
5.5%
시 132
 
5.4%
울 127
 
5.2%
별 127
 
5.2%
구 126
 
5.2%
특 126
 
5.2%
동 116
 
4.8%
Other values (140) 1125
46.1%
Uppercase Letter
ValueCountFrequency (%)
B 8
36.4%
I 3
 
13.6%
A 2
 
9.1%
G 2
 
9.1%
S 1
 
4.5%
E 1
 
4.5%
D 1
 
4.5%
V 1
 
4.5%
H 1
 
4.5%
L 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 129
21.3%
2 115
19.0%
4 72
11.9%
3 70
11.6%
7 53
8.7%
0 44
 
7.3%
5 34
 
5.6%
9 34
 
5.6%
6 28
 
4.6%
8 27
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 138
98.6%
. 1
 
0.7%
: 1
 
0.7%
Space Separator
ValueCountFrequency (%)
690
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2442
58.5%
Common 1709
41.0%
Latin 22
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 147
 
6.0%
서 145
 
5.9%
산 136
 
5.6%
용 135
 
5.5%
시 132
 
5.4%
울 127
 
5.2%
별 127
 
5.2%
구 126
 
5.2%
특 126
 
5.2%
동 116
 
4.8%
Other values (140) 1125
46.1%
Common
ValueCountFrequency (%)
690
40.4%
, 138
 
8.1%
1 129
 
7.5%
) 128
 
7.5%
( 128
 
7.5%
2 115
 
6.7%
4 72
 
4.2%
3 70
 
4.1%
7 53
 
3.1%
0 44
 
2.6%
Other values (8) 142
 
8.3%
Latin
ValueCountFrequency (%)
B 8
36.4%
I 3
 
13.6%
A 2
 
9.1%
G 2
 
9.1%
S 1
 
4.5%
E 1
 
4.5%
D 1
 
4.5%
V 1
 
4.5%
H 1
 
4.5%
L 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2442
58.5%
ASCII 1731
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
690
39.9%
, 138
 
8.0%
1 129
 
7.5%
) 128
 
7.4%
( 128
 
7.4%
2 115
 
6.6%
4 72
 
4.2%
3 70
 
4.0%
7 53
 
3.1%
0 44
 
2.5%
Other values (19) 164
 
9.5%
Hangul
ValueCountFrequency (%)
로 147
 
6.0%
서 145
 
5.9%
산 136
 
5.6%
용 135
 
5.5%
시 132
 
5.4%
울 127
 
5.2%
별 127
 
5.2%
구 126
 
5.2%
특 126
 
5.2%
동 116
 
4.8%
Other values (140) 1125
46.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)50.9%
Missing25
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean8167.2037
Minimum4301
Maximum140892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-18T08:02:03.172275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4301
5-th percentile4314
Q14349
median4387
Q34417
95-th percentile4427
Maximum140892
Range136591
Interquartile range (IQR)68

Descriptive statistics

Standard deviation22533.945
Coefficient of variation (CV)2.7590772
Kurtosis32.571973
Mean8167.2037
Median Absolute Deviation (MAD)35
Skewness5.8282859
Sum882058
Variance5.0777869 × 108
MonotonicityNot monotonic
2024-05-18T08:02:03.692461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4352 8
 
6.0%
4419 6
 
4.5%
4420 6
 
4.5%
4401 6
 
4.5%
4426 5
 
3.8%
4395 4
 
3.0%
4349 4
 
3.0%
4427 4
 
3.0%
4315 3
 
2.3%
4410 3
 
2.3%
Other values (45) 59
44.4%
(Missing) 25
18.8%
ValueCountFrequency (%)
4301 1
 
0.8%
4305 1
 
0.8%
4309 1
 
0.8%
4313 2
1.5%
4314 3
2.3%
4315 3
2.3%
4317 1
 
0.8%
4320 1
 
0.8%
4321 2
1.5%
4322 1
 
0.8%
ValueCountFrequency (%)
140892 1
 
0.8%
140884 1
 
0.8%
140807 1
 
0.8%
4428 1
 
0.8%
4427 4
3.0%
4426 5
3.8%
4420 6
4.5%
4419 6
4.5%
4418 1
 
0.8%
4417 2
 
1.5%

사업장명
Text

Distinct130
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T08:02:04.575663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length16
Mean length7.6466165
Min length1

Characters and Unicode

Total characters1017
Distinct characters222
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)95.5%

Sample

1st row한남헬스
2nd row영 헬스크럽
3rd row한미헬스크럽
4th row룡
5th row대영헬스
ValueCountFrequency (%)
스튜디오 4
 
2.0%
gym 4
 
2.0%
휘트니스 4
 
2.0%
트레이닝 3
 
1.5%
한남 3
 
1.5%
웰니스 3
 
1.5%
크로스핏 3
 
1.5%
헬스 2
 
1.0%
퍼스널트레이닝 2
 
1.0%
짐나우 2
 
1.0%
Other values (167) 175
85.4%
2024-05-18T08:02:05.616604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 84
 
8.3%
72
 
7.1%
트 33
 
3.2%
짐 30
 
2.9%
이 28
 
2.8%
헬 27
 
2.7%
니 21
 
2.1%
휘 15
 
1.5%
럽 14
 
1.4%
레 13
 
1.3%
Other values (212) 680
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 708
69.6%
Uppercase Letter 109
 
10.7%
Lowercase Letter 94
 
9.2%
Space Separator 72
 
7.1%
Close Punctuation 10
 
1.0%
Open Punctuation 10
 
1.0%
Decimal Number 8
 
0.8%
Other Punctuation 3
 
0.3%
Dash Punctuation 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 84
 
11.9%
트 33
 
4.7%
짐 30
 
4.2%
이 28
 
4.0%
헬 27
 
3.8%
니 21
 
3.0%
휘 15
 
2.1%
럽 14
 
2.0%
레 13
 
1.8%
센 11
 
1.6%
Other values (158) 432
61.0%
Uppercase Letter
ValueCountFrequency (%)
M 11
 
10.1%
E 9
 
8.3%
Y 8
 
7.3%
G 8
 
7.3%
C 7
 
6.4%
N 6
 
5.5%
S 6
 
5.5%
F 6
 
5.5%
B 5
 
4.6%
T 5
 
4.6%
Other values (13) 38
34.9%
Lowercase Letter
ValueCountFrequency (%)
n 12
12.8%
t 10
10.6%
e 9
9.6%
i 9
9.6%
a 8
8.5%
o 8
8.5%
u 6
 
6.4%
r 6
 
6.4%
s 6
 
6.4%
l 4
 
4.3%
Other values (9) 16
17.0%
Decimal Number
ValueCountFrequency (%)
4 2
25.0%
1 2
25.0%
2 2
25.0%
5 1
12.5%
3 1
12.5%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 707
69.5%
Latin 204
 
20.1%
Common 105
 
10.3%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 84
 
11.9%
트 33
 
4.7%
짐 30
 
4.2%
이 28
 
4.0%
헬 27
 
3.8%
니 21
 
3.0%
휘 15
 
2.1%
럽 14
 
2.0%
레 13
 
1.8%
센 11
 
1.6%
Other values (157) 431
61.0%
Latin
ValueCountFrequency (%)
n 12
 
5.9%
M 11
 
5.4%
t 10
 
4.9%
e 9
 
4.4%
i 9
 
4.4%
E 9
 
4.4%
Y 8
 
3.9%
G 8
 
3.9%
a 8
 
3.9%
o 8
 
3.9%
Other values (33) 112
54.9%
Common
ValueCountFrequency (%)
72
68.6%
) 10
 
9.5%
( 10
 
9.5%
- 2
 
1.9%
4 2
 
1.9%
1 2
 
1.9%
& 2
 
1.9%
2 2
 
1.9%
5 1
 
1.0%
' 1
 
1.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 707
69.5%
ASCII 308
30.3%
CJK 1
 
0.1%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 84
 
11.9%
트 33
 
4.7%
짐 30
 
4.2%
이 28
 
4.0%
헬 27
 
3.8%
니 21
 
3.0%
휘 15
 
2.1%
럽 14
 
2.0%
레 13
 
1.8%
센 11
 
1.6%
Other values (157) 431
61.0%
ASCII
ValueCountFrequency (%)
72
23.4%
n 12
 
3.9%
M 11
 
3.6%
t 10
 
3.2%
) 10
 
3.2%
( 10
 
3.2%
e 9
 
2.9%
i 9
 
2.9%
E 9
 
2.9%
Y 8
 
2.6%
Other values (43) 148
48.1%
CJK
ValueCountFrequency (%)
大 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct126
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2003-02-06 13:06:27
Maximum2024-05-08 14:08:27
2024-05-18T08:02:06.061886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:02:06.527665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
80 
U
53 

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 80
60.2%
U 53
39.8%

Length

2024-05-18T08:02:06.914154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:07.202534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 80
60.2%
u 53
39.8%

데이터갱신일자
Date

Distinct69
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:00:00
2024-05-18T08:02:07.589645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:02:08.270332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)89.0%
Missing6
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean198573.35
Minimum195556.85
Maximum200969.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-18T08:02:08.745942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195556.85
5-th percentile196566.12
Q1197260.52
median197974.14
Q3200051.26
95-th percentile200697.43
Maximum200969.97
Range5413.1177
Interquartile range (IQR)2790.7415

Descriptive statistics

Standard deviation1511.2753
Coefficient of variation (CV)0.0076106649
Kurtosis-1.3882462
Mean198573.35
Median Absolute Deviation (MAD)1180.1037
Skewness0.068292352
Sum25218816
Variance2283952.9
MonotonicityNot monotonic
2024-05-18T08:02:09.361249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200697.42588055 4
 
3.0%
200648.866223783 3
 
2.3%
197504.647924839 2
 
1.5%
197059.739243751 2
 
1.5%
197071.403205622 2
 
1.5%
197521.687731773 2
 
1.5%
197217.991619464 2
 
1.5%
197045.849468346 2
 
1.5%
196005.836412851 2
 
1.5%
200628.554655257 2
 
1.5%
Other values (103) 104
78.2%
(Missing) 6
 
4.5%
ValueCountFrequency (%)
195556.853873045 1
0.8%
195563.788982635 1
0.8%
196005.836412851 2
1.5%
196118.749575977 1
0.8%
196394.660344263 1
0.8%
196542.935666666 1
0.8%
196620.222371503 1
0.8%
196716.165873094 1
0.8%
196755.916741402 1
0.8%
196762.077394917 1
0.8%
ValueCountFrequency (%)
200969.971541614 1
 
0.8%
200890.057021973 1
 
0.8%
200864.256943225 1
 
0.8%
200791.255534892 1
 
0.8%
200697.42588055 4
3.0%
200648.866223783 3
2.3%
200628.554655257 2
1.5%
200559.36615505 1
 
0.8%
200550.758573376 1
 
0.8%
200524.309913718 2
1.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)89.0%
Missing6
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean448132.88
Minimum446221.69
Maximum450126.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-18T08:02:09.914620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446221.69
5-th percentile446428.92
Q1447699.76
median448075.52
Q3448813.97
95-th percentile449681.99
Maximum450126.95
Range3905.261
Interquartile range (IQR)1114.2083

Descriptive statistics

Standard deviation905.70047
Coefficient of variation (CV)0.0020210534
Kurtosis-0.31490587
Mean448132.88
Median Absolute Deviation (MAD)595.48246
Skewness-0.17078725
Sum56912876
Variance820293.34
MonotonicityNot monotonic
2024-05-18T08:02:10.471704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447925.577361706 4
 
3.0%
447953.839063087 3
 
2.3%
449160.021904876 2
 
1.5%
449146.256652348 2
 
1.5%
447073.62284187 2
 
1.5%
449024.318475909 2
 
1.5%
448723.232518462 2
 
1.5%
448447.558967085 2
 
1.5%
447699.758814725 2
 
1.5%
448024.720455877 2
 
1.5%
Other values (103) 104
78.2%
(Missing) 6
 
4.5%
ValueCountFrequency (%)
446221.69071399 1
0.8%
446243.198701013 1
0.8%
446246.110967125 1
0.8%
446248.255892098 1
0.8%
446270.376661762 1
0.8%
446302.326472725 1
0.8%
446425.373848781 1
0.8%
446437.197878548 1
0.8%
446524.508385914 1
0.8%
446530.658118817 1
0.8%
ValueCountFrequency (%)
450126.951675139 1
0.8%
449892.557718372 1
0.8%
449770.623370766 1
0.8%
449760.779873134 1
0.8%
449722.023318274 1
0.8%
449718.054471759 1
0.8%
449700.031317877 1
0.8%
449639.883505951 1
0.8%
449611.510104398 1
0.8%
449484.73780639 1
0.8%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
체력단련장업
103 
<NA>
30 

Length

Max length6
Median length6
Mean length5.5488722
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 103
77.4%
<NA> 30
 
22.6%

Length

2024-05-18T08:02:11.056902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:11.490736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 103
77.4%
na 30
 
22.6%

공사립구분명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
사립
103 
<NA>
30 

Length

Max length4
Median length2
Mean length2.4511278
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 103
77.4%
<NA> 30
 
22.6%

Length

2024-05-18T08:02:11.969944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:12.326016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 103
77.4%
na 30
 
22.6%

보험가입여부코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
125 
0
 
7
Y
 
1

Length

Max length4
Median length4
Mean length3.8195489
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
94.0%
0 7
 
5.3%
Y 1
 
0.8%

Length

2024-05-18T08:02:12.813595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:13.340007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
94.0%
0 7
 
5.3%
y 1
 
0.8%

지도자수
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
68 
1
41 
2
14 
0
10 

Length

Max length4
Median length4
Mean length2.5338346
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 68
51.1%
1 41
30.8%
2 14
 
10.5%
0 10
 
7.5%

Length

2024-05-18T08:02:13.880539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:14.446222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
51.1%
1 41
30.8%
2 14
 
10.5%
0 10
 
7.5%

건축물동수
Categorical

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
84 
0
28 
1
20 
3
 
1

Length

Max length4
Median length4
Mean length2.8947368
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
63.2%
0 28
 
21.1%
1 20
 
15.0%
3 1
 
0.8%

Length

2024-05-18T08:02:14.903943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:15.239691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
63.2%
0 28
 
21.1%
1 20
 
15.0%
3 1
 
0.8%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct48
Distinct (%)64.0%
Missing58
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean5212.854
Minimum0
Maximum151027.6
Zeros23
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-18T08:02:16.091702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median953.99
Q32211.61
95-th percentile26329.583
Maximum151027.6
Range151027.6
Interquartile range (IQR)2211.61

Descriptive statistics

Standard deviation18718.913
Coefficient of variation (CV)3.5909145
Kurtosis51.243153
Mean5212.854
Median Absolute Deviation (MAD)953.99
Skewness6.76771
Sum390964.05
Variance3.503977 × 108
MonotonicityNot monotonic
2024-05-18T08:02:16.741364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 23
 
17.3%
1106.5 3
 
2.3%
429.42 2
 
1.5%
2704.86 2
 
1.5%
4794.83 2
 
1.5%
1535.36 1
 
0.8%
1909.99 1
 
0.8%
997.58 1
 
0.8%
44414.27 1
 
0.8%
487.86 1
 
0.8%
Other values (38) 38
28.6%
(Missing) 58
43.6%
ValueCountFrequency (%)
0.0 23
17.3%
99.18 1
 
0.8%
246.51 1
 
0.8%
350.86 1
 
0.8%
429.42 2
 
1.5%
487.86 1
 
0.8%
494.1 1
 
0.8%
494.7 1
 
0.8%
499.5 1
 
0.8%
508.09 1
 
0.8%
ValueCountFrequency (%)
151027.6 1
0.8%
44414.27 1
0.8%
31143.52 1
0.8%
30966.46 1
0.8%
24342.35 1
0.8%
13267.62 1
0.8%
12761.02 1
0.8%
11260.72 1
0.8%
6267.19 1
0.8%
4794.83 2
1.5%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
125 
0
 
8

Length

Max length4
Median length4
Mean length3.8195489
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> 125
94.0%
0 8
 
6.0%

Length

2024-05-18T08:02:17.172958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:17.507468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
94.0%
0 8
 
6.0%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing133
Missing (%)100.0%
Memory size1.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03020000CDFH330106198900000119891222<NA>3폐업3폐업20040420<NA><NA><NA><NA><NA>140887서울특별시 용산구 한남동 657-70번지서울특별시 용산구 대사관로31길 19 (한남동)<NA>한남헬스2013-05-09 15:03:46I2018-08-31 23:59:59.0<NA>200439.150208447992.524198체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
13020000CDFH330106198900000219891222<NA>3폐업3폐업20101105<NA><NA><NA>796-0831<NA>140160서울특별시 용산구 남영동 182-3번지 지상5층<NA><NA>영 헬스크럽2010-11-05 17:32:51I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립0<NA><NA><NA><NA><NA><NA>
23020000CDFH330106199000000119901019<NA>3폐업3폐업20041118<NA><NA><NA><NA><NA>140887서울특별시 용산구 한남동 621-1번지<NA><NA>한미헬스크럽2013-05-09 15:02:32I2018-08-31 23:59:59.0<NA>200456.643967447739.382009체력단련장업사립<NA><NA>00.0<NA><NA><NA>
33020000CDFH330106199000000219901218<NA>3폐업3폐업19970809<NA><NA><NA><NA><NA>140819서울특별시 용산구 동자동 14-27번지<NA><NA>룡2003-02-06 13:06:27I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
43020000CDFH330106199100000119910419<NA>4취소/말소/만료/정지/중지35직권말소20090213<NA><NA><NA><NA><NA>140879서울특별시 용산구 한강로3가 16-58번지 지하1층서울특별시 용산구 청파로 48 (한강로3가,지하1층)<NA>대영헬스2009-02-13 17:03:32I2018-08-31 23:59:59.0<NA>196118.749576447760.157527체력단련장업사립0<NA><NA><NA><NA><NA><NA>
53020000CDFH330106199100000219910430<NA>3폐업3폐업20170323<NA><NA><NA>797-3402<NA><NA>서울특별시 용산구 이태원동 130-34번지 지하2층서울특별시 용산구 보광로 123 (이태원동)4391용헬스클럽2017-05-04 10:58:28I2018-08-31 23:59:59.0<NA>199399.509258447940.397729체력단련장업사립<NA><NA>00.0<NA><NA><NA>
63020000CDFH33010619910000031991-04-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 보광동 216-12 그린서적서울특별시 용산구 장문로 96, 지하 1층 (보광동)4395우노 휘트니스클럽2024-05-08 14:08:27U2023-12-04 23:00:00.0<NA>199940.114847447079.49999<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73020000CDFH330106199200000119921120<NA>3폐업3폐업19961002<NA><NA><NA><NA><NA>140900서울특별시 용산구 후암동 132-24번지 지하1층서울특별시 용산구 두텁바위로1길 110 (후암동,지하1층)<NA>밴 헬스타운2003-02-06 13:06:27I2018-08-31 23:59:59.0<NA>197827.066826449611.510104체력단련장업사립<NA>000.0<NA><NA><NA>
83020000CDFH330106199300000119930206<NA>3폐업3폐업20170323<NA><NA><NA>796-6940<NA>140871서울특별시 용산구 한강로2가 166-4번지서울특별시 용산구 한강대로38나길 25 (한강로2가)<NA>한강헬스2017-05-04 09:54:40I2018-08-31 23:59:59.0<NA>197176.930176447345.125176체력단련장업사립<NA><NA>00.0<NA><NA><NA>
93020000CDFH330106199300000219930720<NA>3폐업3폐업20061004<NA><NA><NA><NA><NA>140847서울특별시 용산구 원효로2가 72-3번지서울특별시 용산구 원효로 179 (원효로2가)<NA>원효헬스2013-05-09 14:52:30I2018-08-31 23:59:59.0<NA>196620.222372448210.523695체력단련장업사립<NA><NA>00.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
1233020000CDFH330106202200000520220602<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로3가 16-85 지에스 한강에클라트 104호서울특별시 용산구 이촌로 1, 1층 104호 (한강로3가, 지에스 한강에클라트)4373원(1)GYM2022-06-02 10:14:51I2021-12-06 00:04:00.0<NA>196005.836413447699.758815<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1243020000CDFH330106202200000620220616<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 남영동 114-15 17-17서울특별시 용산구 한강대로72길 11-18, 17-17 (남영동)4352크로스핏 남산2022-06-16 09:14:30I2021-12-05 23:08:00.0<NA>197633.100656448787.734716<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1253020000CDFH33010620220000072022-07-15<NA>1영업/정상13영업중<NA><NA><NA><NA>02-717-8437<NA><NA>서울특별시 용산구 원효로1가 133-3 리첸시아 용산 A동 210호서울특별시 용산구 백범로 341, A동 2층 210호 (원효로1가, 리첸시아 용산)4315바른핏2024-03-14 16:20:33U2023-12-02 23:06:00.0<NA>197045.849468448447.558967<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1263020000CDFH330106202200000820221102<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 후암동 358-17 대원정사 본관 201호서울특별시 용산구 두텁바위로60길 49, 대원정사 본관 201호 (후암동)4328텐세그리티2022-11-02 13:44:47I2021-11-01 00:04:00.0<NA>198470.128905449639.883506<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1273020000CDFH330106202200000920221212<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 청파동3가 80-6 지층 B01호서울특별시 용산구 청파로 251, 지층 B01호 (청파동3가)4313MCT GYM 용산2022-12-12 10:39:18I2021-11-01 23:04:00.0<NA>197311.684173448850.599823<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1283020000CDFH330106202300000120230126<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한남동 107-4서울특별시 용산구 독서당로11길 23, 지하1층 (한남동)4410드래곤짐2023-01-26 08:49:27I2022-11-30 22:08:00.0<NA>200550.758573447653.024719<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1293020000CDFH33010620230000022023-02-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 이촌동 302-81서울특별시 용산구 이촌로58길 3, 지하1층 (이촌동)4427상떼(Sante')2023-02-13 12:07:37I2022-12-01 23:05:00.0<NA>197173.660367446530.658119<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1303020000CDFH33010620230000032023-04-20<NA>1영업/정상13영업중<NA><NA><NA><NA>027497548<NA><NA>서울특별시 용산구 갈월동 92 용산빌딩서울특별시 용산구 한강대로 273, 용산빌딩 지하1층 (갈월동)4321스카이짐 GDR골프아카데미 헬스2023-04-20 17:02:24I2022-12-03 22:03:00.0<NA>197454.750647448937.796601<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1313020000CDFH33010620230000042023-07-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로3가 65-291서울특별시 용산구 서빙고로 52-4 (한강로3가)4388(주)비에프알 코리아2023-07-28 10:50:01I2022-12-06 21:00:00.0<NA>197265.93624446774.796917<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1323020000CDFH33010620230000052023-11-09<NA>1영업/정상13영업중<NA><NA><NA><NA>02-704-8884<NA><NA>서울특별시 용산구 갈월동 85-3 남영빌딩서울특별시 용산구 한강대로 295, 남영빌딩 지하1층 (갈월동)4321런앤리프트2024-03-26 08:26:24U2023-12-02 22:08:00.0<NA>197431.710876449143.721979<NA><NA><NA><NA><NA><NA><NA><NA><NA>