Overview

Dataset statistics

Number of variables34
Number of observations262
Missing cells2762
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory74.1 KiB
Average record size in memory289.5 B

Variable types

Categorical12
Text7
DateTime4
Unsupported8
Numeric3

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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-19872/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
보험가입여부코드 is highly imbalanced (74.3%)Imbalance
회원모집총인원 is highly imbalanced (68.4%)Imbalance
인허가취소일자 has 262 (100.0%) missing valuesMissing
폐업일자 has 167 (63.7%) missing valuesMissing
휴업시작일자 has 262 (100.0%) missing valuesMissing
휴업종료일자 has 262 (100.0%) missing valuesMissing
재개업일자 has 262 (100.0%) missing valuesMissing
전화번호 has 130 (49.6%) missing valuesMissing
소재지면적 has 262 (100.0%) missing valuesMissing
소재지우편번호 has 156 (59.5%) missing valuesMissing
도로명주소 has 4 (1.5%) missing valuesMissing
도로명우편번호 has 76 (29.0%) missing valuesMissing
업태구분명 has 262 (100.0%) missing valuesMissing
좌표정보(X) has 3 (1.1%) missing valuesMissing
좌표정보(Y) has 3 (1.1%) missing valuesMissing
건축물연면적 has 127 (48.5%) missing valuesMissing
세부업종명 has 262 (100.0%) missing valuesMissing
법인명 has 262 (100.0%) missing valuesMissing
관리번호 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
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 35 (13.4%) zerosZeros

Reproduction

Analysis started2024-04-29 20:02:16.580580
Analysis finished2024-04-29 20:02:17.483734
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3200000
262 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 262
100.0%

Length

2024-04-30T05:02:17.545669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:17.633627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 262
100.0%

관리번호
Text

UNIQUE 

Distinct262
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T05:02:17.784495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters5240
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

Unique262 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061989000003
4th rowCDFH3301061989000004
5th rowCDFH3301061989000005
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.4%
cdfh3301062019000010 1
 
0.4%
cdfh3301062020000001 1
 
0.4%
cdfh3301062020000002 1
 
0.4%
cdfh3301062020000003 1
 
0.4%
cdfh3301062020000004 1
 
0.4%
cdfh3301062020000005 1
 
0.4%
cdfh3301062020000006 1
 
0.4%
cdfh3301062020000007 1
 
0.4%
cdfh3301062020000008 1
 
0.4%
Other values (252) 252
96.2%
2024-04-30T05:02:18.068392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2082
39.7%
3 594
 
11.3%
1 499
 
9.5%
2 425
 
8.1%
6 306
 
5.8%
C 262
 
5.0%
D 262
 
5.0%
F 262
 
5.0%
H 262
 
5.0%
9 114
 
2.2%
Other values (4) 172
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4192
80.0%
Uppercase Letter 1048
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2082
49.7%
3 594
 
14.2%
1 499
 
11.9%
2 425
 
10.1%
6 306
 
7.3%
9 114
 
2.7%
4 52
 
1.2%
5 46
 
1.1%
7 42
 
1.0%
8 32
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 262
25.0%
D 262
25.0%
F 262
25.0%
H 262
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4192
80.0%
Latin 1048
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2082
49.7%
3 594
 
14.2%
1 499
 
11.9%
2 425
 
10.1%
6 306
 
7.3%
9 114
 
2.7%
4 52
 
1.2%
5 46
 
1.1%
7 42
 
1.0%
8 32
 
0.8%
Latin
ValueCountFrequency (%)
C 262
25.0%
D 262
25.0%
F 262
25.0%
H 262
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2082
39.7%
3 594
 
11.3%
1 499
 
9.5%
2 425
 
8.1%
6 306
 
5.8%
C 262
 
5.0%
D 262
 
5.0%
F 262
 
5.0%
H 262
 
5.0%
9 114
 
2.2%
Other values (4) 172
 
3.3%

인허가일자
Date

Distinct252
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1989-11-16 00:00:00
Maximum2024-04-03 00:00:00
2024-04-30T05:02:18.188423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:18.313923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
167 
3
66 
4
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 167
63.7%
3 66
 
25.2%
4 29
 
11.1%

Length

2024-04-30T05:02:18.416310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:18.502672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 167
63.7%
3 66
 
25.2%
4 29
 
11.1%

영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
영업/정상
167 
폐업
66 
취소/말소/만료/정지/중지
29 

Length

Max length14
Median length5
Mean length5.240458
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 167
63.7%
폐업 66
 
25.2%
취소/말소/만료/정지/중지 29
 
11.1%

Length

2024-04-30T05:02:18.601401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:18.697654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 167
63.7%
폐업 66
 
25.2%
취소/말소/만료/정지/중지 29
 
11.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
13
167 
3
66 
35
29 

Length

Max length2
Median length2
Mean length1.7480916
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 167
63.7%
3 66
 
25.2%
35 29
 
11.1%

Length

2024-04-30T05:02:18.781875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:18.868725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 167
63.7%
3 66
 
25.2%
35 29
 
11.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
영업중
167 
폐업
66 
직권말소
29 

Length

Max length4
Median length3
Mean length2.8587786
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 167
63.7%
폐업 66
 
25.2%
직권말소 29
 
11.1%

Length

2024-04-30T05:02:18.961317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:19.052466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 167
63.7%
폐업 66
 
25.2%
직권말소 29
 
11.1%

폐업일자
Date

MISSING 

Distinct76
Distinct (%)80.0%
Missing167
Missing (%)63.7%
Memory size2.2 KiB
Minimum1998-10-23 00:00:00
Maximum2024-01-15 00:00:00
2024-04-30T05:02:19.154203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:19.292156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

전화번호
Text

MISSING 

Distinct125
Distinct (%)94.7%
Missing130
Missing (%)49.6%
Memory size2.2 KiB
2024-04-30T05:02:19.506290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.106061
Min length8

Characters and Unicode

Total characters1466
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

Unique118 ?
Unique (%)89.4%

Sample

1st row02-877-6458
2nd row02-885-4100
3rd row02-871-1800
4th row885-8628
5th row02-859-5588
ValueCountFrequency (%)
070-8285-8296 2
 
1.5%
02-882-8296 2
 
1.5%
02-883-9682 2
 
1.5%
02-882-5046 2
 
1.5%
02-871-1800 2
 
1.5%
02-884-0440 2
 
1.5%
02-872-8470 2
 
1.5%
070-4076-0926 1
 
0.8%
02-6101-9945 1
 
0.8%
02-858-6703 1
 
0.8%
Other values (115) 115
87.1%
2024-04-30T05:02:19.826518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 255
17.4%
8 248
16.9%
0 222
15.1%
2 197
13.4%
7 104
7.1%
6 96
 
6.5%
5 79
 
5.4%
3 73
 
5.0%
1 67
 
4.6%
9 66
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1211
82.6%
Dash Punctuation 255
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 248
20.5%
0 222
18.3%
2 197
16.3%
7 104
8.6%
6 96
 
7.9%
5 79
 
6.5%
3 73
 
6.0%
1 67
 
5.5%
9 66
 
5.5%
4 59
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 255
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1466
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 255
17.4%
8 248
16.9%
0 222
15.1%
2 197
13.4%
7 104
7.1%
6 96
 
6.5%
5 79
 
5.4%
3 73
 
5.0%
1 67
 
4.6%
9 66
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1466
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 255
17.4%
8 248
16.9%
0 222
15.1%
2 197
13.4%
7 104
7.1%
6 96
 
6.5%
5 79
 
5.4%
3 73
 
5.0%
1 67
 
4.6%
9 66
 
4.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

소재지우편번호
Text

MISSING 

Distinct62
Distinct (%)58.5%
Missing156
Missing (%)59.5%
Memory size2.2 KiB
2024-04-30T05:02:20.044622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0849057
Min length6

Characters and Unicode

Total characters645
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

Unique40 ?
Unique (%)37.7%

Sample

1st row151888
2nd row151872
3rd row151825
4th row151880
5th row151930
ValueCountFrequency (%)
151015 8
 
7.5%
151050 4
 
3.8%
151812 4
 
3.8%
151890 4
 
3.8%
151895 4
 
3.8%
151930 4
 
3.8%
151836 4
 
3.8%
151825 3
 
2.8%
151903 3
 
2.8%
151880 3
 
2.8%
Other values (52) 65
61.3%
2024-04-30T05:02:20.387211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 236
36.6%
5 139
21.6%
8 86
 
13.3%
0 43
 
6.7%
9 30
 
4.7%
3 27
 
4.2%
2 23
 
3.6%
7 20
 
3.1%
6 17
 
2.6%
4 15
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 636
98.6%
Dash Punctuation 9
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 236
37.1%
5 139
21.9%
8 86
 
13.5%
0 43
 
6.8%
9 30
 
4.7%
3 27
 
4.2%
2 23
 
3.6%
7 20
 
3.1%
6 17
 
2.7%
4 15
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 236
36.6%
5 139
21.6%
8 86
 
13.3%
0 43
 
6.7%
9 30
 
4.7%
3 27
 
4.2%
2 23
 
3.6%
7 20
 
3.1%
6 17
 
2.6%
4 15
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 236
36.6%
5 139
21.6%
8 86
 
13.3%
0 43
 
6.7%
9 30
 
4.7%
3 27
 
4.2%
2 23
 
3.6%
7 20
 
3.1%
6 17
 
2.6%
4 15
 
2.3%

지번주소
Text

Distinct255
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T05:02:20.648275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length24.400763
Min length18

Characters and Unicode

Total characters6393
Distinct characters142
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

Unique248 ?
Unique (%)94.7%

Sample

1st row서울특별시 관악구 신림동 587-46번지
2nd row서울특별시 관악구 신림동 131-21
3rd row서울특별시 관악구 신림동 504-6번지
4th row서울특별시 관악구 봉천동 493-3번지
5th row서울특별시 관악구 신림동 613-10
ValueCountFrequency (%)
서울특별시 261
21.3%
관악구 261
21.3%
신림동 136
 
11.1%
봉천동 118
 
9.6%
3층 17
 
1.4%
지하1층 14
 
1.1%
4층 13
 
1.1%
2층 9
 
0.7%
남현동 7
 
0.6%
1층 4
 
0.3%
Other values (351) 385
31.4%
2024-04-30T05:02:21.066571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1125
17.6%
1 351
 
5.5%
동 271
 
4.2%
관 266
 
4.2%
악 265
 
4.1%
서 262
 
4.1%
시 262
 
4.1%
구 262
 
4.1%
특 261
 
4.1%
별 261
 
4.1%
Other values (132) 2807
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3539
55.4%
Decimal Number 1435
22.4%
Space Separator 1125
 
17.6%
Dash Punctuation 254
 
4.0%
Uppercase Letter 15
 
0.2%
Other Punctuation 14
 
0.2%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 271
 
7.7%
관 266
 
7.5%
악 265
 
7.5%
서 262
 
7.4%
시 262
 
7.4%
구 262
 
7.4%
특 261
 
7.4%
별 261
 
7.4%
울 261
 
7.4%
신 141
 
4.0%
Other values (109) 1027
29.0%
Decimal Number
ValueCountFrequency (%)
1 351
24.5%
6 156
10.9%
4 150
10.5%
3 144
10.0%
2 144
10.0%
5 142
9.9%
8 100
 
7.0%
7 93
 
6.5%
0 86
 
6.0%
9 69
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 7
46.7%
T 2
 
13.3%
G 2
 
13.3%
A 1
 
6.7%
S 1
 
6.7%
I 1
 
6.7%
Q 1
 
6.7%
Space Separator
ValueCountFrequency (%)
1125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 254
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3539
55.4%
Common 2839
44.4%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 271
 
7.7%
관 266
 
7.5%
악 265
 
7.5%
서 262
 
7.4%
시 262
 
7.4%
구 262
 
7.4%
특 261
 
7.4%
별 261
 
7.4%
울 261
 
7.4%
신 141
 
4.0%
Other values (109) 1027
29.0%
Common
ValueCountFrequency (%)
1125
39.6%
1 351
 
12.4%
- 254
 
8.9%
6 156
 
5.5%
4 150
 
5.3%
3 144
 
5.1%
2 144
 
5.1%
5 142
 
5.0%
8 100
 
3.5%
7 93
 
3.3%
Other values (6) 180
 
6.3%
Latin
ValueCountFrequency (%)
B 7
46.7%
T 2
 
13.3%
G 2
 
13.3%
A 1
 
6.7%
S 1
 
6.7%
I 1
 
6.7%
Q 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3539
55.4%
ASCII 2854
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1125
39.4%
1 351
 
12.3%
- 254
 
8.9%
6 156
 
5.5%
4 150
 
5.3%
3 144
 
5.0%
2 144
 
5.0%
5 142
 
5.0%
8 100
 
3.5%
7 93
 
3.3%
Other values (13) 195
 
6.8%
Hangul
ValueCountFrequency (%)
동 271
 
7.7%
관 266
 
7.5%
악 265
 
7.5%
서 262
 
7.4%
시 262
 
7.4%
구 262
 
7.4%
특 261
 
7.4%
별 261
 
7.4%
울 261
 
7.4%
신 141
 
4.0%
Other values (109) 1027
29.0%

도로명주소
Text

MISSING 

Distinct255
Distinct (%)98.8%
Missing4
Missing (%)1.5%
Memory size2.2 KiB
2024-04-30T05:02:21.303186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length30.124031
Min length21

Characters and Unicode

Total characters7772
Distinct characters178
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

Unique252 ?
Unique (%)97.7%

Sample

1st row서울특별시 관악구 난곡로 256 (신림동)
2nd row서울특별시 관악구 신림로 90, 5층 (신림동)
3rd row서울특별시 관악구 조원로 132 (신림동)
4th row서울특별시 관악구 양녕로 64 (봉천동)
5th row서울특별시 관악구 난우길 8 (신림동)
ValueCountFrequency (%)
서울특별시 258
16.5%
관악구 258
16.5%
신림동 125
 
8.0%
봉천동 109
 
7.0%
남부순환로 59
 
3.8%
지하1층 39
 
2.5%
3층 34
 
2.2%
신림로 27
 
1.7%
난곡로 20
 
1.3%
2층 19
 
1.2%
Other values (387) 615
39.3%
2024-04-30T05:02:21.660503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1332
 
17.1%
관 281
 
3.6%
악 280
 
3.6%
동 272
 
3.5%
1 267
 
3.4%
( 262
 
3.4%
시 262
 
3.4%
) 262
 
3.4%
서 260
 
3.3%
특 258
 
3.3%
Other values (168) 4036
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4520
58.2%
Space Separator 1332
 
17.1%
Decimal Number 1113
 
14.3%
Open Punctuation 262
 
3.4%
Close Punctuation 262
 
3.4%
Other Punctuation 243
 
3.1%
Uppercase Letter 21
 
0.3%
Dash Punctuation 13
 
0.2%
Math Symbol 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 281
 
6.2%
악 280
 
6.2%
동 272
 
6.0%
시 262
 
5.8%
서 260
 
5.8%
특 258
 
5.7%
별 258
 
5.7%
구 258
 
5.7%
울 258
 
5.7%
로 231
 
5.1%
Other values (145) 1902
42.1%
Decimal Number
ValueCountFrequency (%)
1 267
24.0%
2 158
14.2%
3 142
12.8%
4 94
 
8.4%
0 91
 
8.2%
6 89
 
8.0%
5 80
 
7.2%
7 67
 
6.0%
9 65
 
5.8%
8 60
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 12
57.1%
G 2
 
9.5%
A 2
 
9.5%
T 2
 
9.5%
I 1
 
4.8%
Q 1
 
4.8%
S 1
 
4.8%
Space Separator
ValueCountFrequency (%)
1332
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Close Punctuation
ValueCountFrequency (%)
) 262
100.0%
Other Punctuation
ValueCountFrequency (%)
, 243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4520
58.2%
Common 3231
41.6%
Latin 21
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 281
 
6.2%
악 280
 
6.2%
동 272
 
6.0%
시 262
 
5.8%
서 260
 
5.8%
특 258
 
5.7%
별 258
 
5.7%
구 258
 
5.7%
울 258
 
5.7%
로 231
 
5.1%
Other values (145) 1902
42.1%
Common
ValueCountFrequency (%)
1332
41.2%
1 267
 
8.3%
( 262
 
8.1%
) 262
 
8.1%
, 243
 
7.5%
2 158
 
4.9%
3 142
 
4.4%
4 94
 
2.9%
0 91
 
2.8%
6 89
 
2.8%
Other values (6) 291
 
9.0%
Latin
ValueCountFrequency (%)
B 12
57.1%
G 2
 
9.5%
A 2
 
9.5%
T 2
 
9.5%
I 1
 
4.8%
Q 1
 
4.8%
S 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4520
58.2%
ASCII 3252
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1332
41.0%
1 267
 
8.2%
( 262
 
8.1%
) 262
 
8.1%
, 243
 
7.5%
2 158
 
4.9%
3 142
 
4.4%
4 94
 
2.9%
0 91
 
2.8%
6 89
 
2.7%
Other values (13) 312
 
9.6%
Hangul
ValueCountFrequency (%)
관 281
 
6.2%
악 280
 
6.2%
동 272
 
6.0%
시 262
 
5.8%
서 260
 
5.8%
특 258
 
5.7%
별 258
 
5.7%
구 258
 
5.7%
울 258
 
5.7%
로 231
 
5.1%
Other values (145) 1902
42.1%

도로명우편번호
Text

MISSING 

Distinct81
Distinct (%)43.5%
Missing76
Missing (%)29.0%
Memory size2.2 KiB
2024-04-30T05:02:21.874971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0483871
Min length5

Characters and Unicode

Total characters939
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 (%)23.7%

Sample

1st row08839
2nd row08797
3rd row08812
4th row08854
5th row08742
ValueCountFrequency (%)
08786 10
 
5.4%
08793 9
 
4.8%
08787 9
 
4.8%
08813 8
 
4.3%
08754 7
 
3.8%
08814 6
 
3.2%
08801 6
 
3.2%
08742 5
 
2.7%
08708 5
 
2.7%
08812 5
 
2.7%
Other values (71) 116
62.4%
2024-04-30T05:02:22.227340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 292
31.1%
0 217
23.1%
7 162
17.3%
1 49
 
5.2%
5 41
 
4.4%
6 40
 
4.3%
3 37
 
3.9%
4 37
 
3.9%
2 31
 
3.3%
9 30
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
99.7%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 292
31.2%
0 217
23.2%
7 162
17.3%
1 49
 
5.2%
5 41
 
4.4%
6 40
 
4.3%
3 37
 
4.0%
4 37
 
4.0%
2 31
 
3.3%
9 30
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 939
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 292
31.1%
0 217
23.1%
7 162
17.3%
1 49
 
5.2%
5 41
 
4.4%
6 40
 
4.3%
3 37
 
3.9%
4 37
 
3.9%
2 31
 
3.3%
9 30
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 939
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 292
31.1%
0 217
23.1%
7 162
17.3%
1 49
 
5.2%
5 41
 
4.4%
6 40
 
4.3%
3 37
 
3.9%
4 37
 
3.9%
2 31
 
3.3%
9 30
 
3.2%

사업장명
Text

Distinct254
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T05:02:22.507007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length8.8206107
Min length2

Characters and Unicode

Total characters2311
Distinct characters304
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)93.9%

Sample

1st row거봉
2nd row짐박스 피트니스
3rd row파워플러스헬스클럽
4th row중앙헬스
5th row종합헬스
ValueCountFrequency (%)
gym 17
 
3.7%
휘트니스 14
 
3.0%
짐 12
 
2.6%
짐박스피트니스 9
 
1.9%
스포애니 8
 
1.7%
주)케이디헬스케어 8
 
1.7%
피트니스 7
 
1.5%
pt 7
 
1.5%
낙성대점 6
 
1.3%
더 6
 
1.3%
Other values (310) 369
79.7%
2024-04-30T05:02:22.931615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
201
 
8.7%
스 192
 
8.3%
짐 70
 
3.0%
트 70
 
3.0%
니 67
 
2.9%
헬 62
 
2.7%
점 57
 
2.5%
T 39
 
1.7%
휘 38
 
1.6%
이 38
 
1.6%
Other values (294) 1477
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1629
70.5%
Uppercase Letter 240
 
10.4%
Space Separator 201
 
8.7%
Lowercase Letter 155
 
6.7%
Open Punctuation 27
 
1.2%
Close Punctuation 27
 
1.2%
Decimal Number 20
 
0.9%
Other Punctuation 9
 
0.4%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 192
 
11.8%
짐 70
 
4.3%
트 70
 
4.3%
니 67
 
4.1%
헬 62
 
3.8%
점 57
 
3.5%
휘 38
 
2.3%
이 38
 
2.3%
럽 33
 
2.0%
대 30
 
1.8%
Other values (235) 972
59.7%
Uppercase Letter
ValueCountFrequency (%)
T 39
16.2%
P 30
12.5%
G 24
 
10.0%
M 18
 
7.5%
Y 17
 
7.1%
S 13
 
5.4%
I 12
 
5.0%
O 11
 
4.6%
F 8
 
3.3%
E 8
 
3.3%
Other values (15) 60
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 21
13.5%
t 16
10.3%
s 15
9.7%
i 14
9.0%
m 12
7.7%
o 12
7.7%
y 11
 
7.1%
l 10
 
6.5%
n 9
 
5.8%
h 7
 
4.5%
Other values (10) 28
18.1%
Decimal Number
ValueCountFrequency (%)
2 7
35.0%
4 4
20.0%
5 3
15.0%
3 2
 
10.0%
1 2
 
10.0%
6 1
 
5.0%
9 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
: 4
44.4%
& 3
33.3%
. 2
22.2%
Space Separator
ValueCountFrequency (%)
201
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1628
70.4%
Latin 395
 
17.1%
Common 287
 
12.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 192
 
11.8%
짐 70
 
4.3%
트 70
 
4.3%
니 67
 
4.1%
헬 62
 
3.8%
점 57
 
3.5%
휘 38
 
2.3%
이 38
 
2.3%
럽 33
 
2.0%
대 30
 
1.8%
Other values (234) 971
59.6%
Latin
ValueCountFrequency (%)
T 39
 
9.9%
P 30
 
7.6%
G 24
 
6.1%
e 21
 
5.3%
M 18
 
4.6%
Y 17
 
4.3%
t 16
 
4.1%
s 15
 
3.8%
i 14
 
3.5%
S 13
 
3.3%
Other values (35) 188
47.6%
Common
ValueCountFrequency (%)
201
70.0%
( 27
 
9.4%
) 27
 
9.4%
2 7
 
2.4%
: 4
 
1.4%
4 4
 
1.4%
- 3
 
1.0%
& 3
 
1.0%
5 3
 
1.0%
. 2
 
0.7%
Other values (4) 6
 
2.1%
Han
ValueCountFrequency (%)
魂 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1628
70.4%
ASCII 682
29.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
201
29.5%
T 39
 
5.7%
P 30
 
4.4%
( 27
 
4.0%
) 27
 
4.0%
G 24
 
3.5%
e 21
 
3.1%
M 18
 
2.6%
Y 17
 
2.5%
t 16
 
2.3%
Other values (49) 262
38.4%
Hangul
ValueCountFrequency (%)
스 192
 
11.8%
짐 70
 
4.3%
트 70
 
4.3%
니 67
 
4.1%
헬 62
 
3.8%
점 57
 
3.5%
휘 38
 
2.3%
이 38
 
2.3%
럽 33
 
2.0%
대 30
 
1.8%
Other values (234) 971
59.6%
CJK
ValueCountFrequency (%)
魂 1
100.0%

최종수정일자
Date

Distinct253
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2003-02-06 10:45:13
Maximum2024-04-17 09:06:44
2024-04-30T05:02:23.048439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:23.169597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
U
145 
I
117 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 145
55.3%
I 117
44.7%

Length

2024-04-30T05:02:23.312287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:23.409403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 145
55.3%
i 117
44.7%

데이터갱신일자
Date

Distinct148
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T05:02:23.512119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:23.638667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)88.0%
Missing3
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean194516.86
Minimum191182
Maximum198284.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T05:02:23.923061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191182
5-th percentile192264.92
Q1193556.99
median194395.38
Q3195692.09
95-th percentile196820.75
Maximum198284.08
Range7102.0781
Interquartile range (IQR)2135.0946

Descriptive statistics

Standard deviation1553.1336
Coefficient of variation (CV)0.0079845706
Kurtosis-0.57134022
Mean194516.86
Median Absolute Deviation (MAD)1117.9674
Skewness0.10357386
Sum50379867
Variance2412224
MonotonicityNot monotonic
2024-04-30T05:02:24.059875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196640.766100872 3
 
1.1%
196004.977409783 3
 
1.1%
193919.806951716 3
 
1.1%
195588.796492288 2
 
0.8%
192817.818457133 2
 
0.8%
195250.618292981 2
 
0.8%
194145.909561232 2
 
0.8%
196820.48357904 2
 
0.8%
195531.953701324 2
 
0.8%
196664.276957944 2
 
0.8%
Other values (218) 236
90.1%
(Missing) 3
 
1.1%
ValueCountFrequency (%)
191182.000480527 1
0.4%
191204.884621244 1
0.4%
191223.827173065 1
0.4%
191298.923231156 1
0.4%
191334.658955208 1
0.4%
191388.248354622 1
0.4%
191592.154183574 1
0.4%
191602.120217728 1
0.4%
191855.407522532 1
0.4%
191976.555027584 1
0.4%
ValueCountFrequency (%)
198284.078546351 1
0.4%
198215.79929384 1
0.4%
198097.13526738 1
0.4%
198081.693933879 1
0.4%
197989.550516662 1
0.4%
197965.134833373 1
0.4%
197626.942168938 1
0.4%
196982.09843076 1
0.4%
196978.243746073 1
0.4%
196955.001439946 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)88.0%
Missing3
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean441909.43
Minimum439809.67
Maximum443341.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T05:02:24.191290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439809.67
5-th percentile440777.99
Q1441492.68
median442004.18
Q3442468.11
95-th percentile442872.11
Maximum443341.38
Range3531.7098
Interquartile range (IQR)975.43362

Descriptive statistics

Standard deviation709.24671
Coefficient of variation (CV)0.0016049594
Kurtosis-0.31939659
Mean441909.43
Median Absolute Deviation (MAD)492.28332
Skewness-0.41429199
Sum1.1445454 × 108
Variance503030.9
MonotonicityNot monotonic
2024-04-30T05:02:24.325598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441722.030365358 3
 
1.1%
441952.163703792 3
 
1.1%
441887.736710799 3
 
1.1%
442098.372819317 2
 
0.8%
440263.768319604 2
 
0.8%
442790.674359138 2
 
0.8%
440956.752364675 2
 
0.8%
441635.55938456 2
 
0.8%
442060.794689435 2
 
0.8%
441702.736700471 2
 
0.8%
Other values (218) 236
90.1%
(Missing) 3
 
1.1%
ValueCountFrequency (%)
439809.669640911 1
0.4%
440080.722096024 1
0.4%
440178.60849927 1
0.4%
440205.2603058 1
0.4%
440263.768319604 2
0.8%
440293.901638173 1
0.4%
440299.376149385 1
0.4%
440545.946420334 1
0.4%
440707.623024621 1
0.4%
440722.050107279 1
0.4%
ValueCountFrequency (%)
443341.379446435 1
0.4%
443241.362831726 1
0.4%
443221.321009043 1
0.4%
443216.750634836 1
0.4%
443157.363464064 1
0.4%
443119.38369177 1
0.4%
443109.84937523 1
0.4%
443101.247145688 1
0.4%
443094.686592235 1
0.4%
443081.393439309 1
0.4%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
체력단련장업
168 
<NA>
94 

Length

Max length6
Median length6
Mean length5.2824427
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 168
64.1%
<NA> 94
35.9%

Length

2024-04-30T05:02:24.471813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:24.583701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 168
64.1%
na 94
35.9%

공사립구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
사립
168 
<NA>
94 

Length

Max length4
Median length2
Mean length2.7175573
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 168
64.1%
<NA> 94
35.9%

Length

2024-04-30T05:02:24.683533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:24.823266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 168
64.1%
na 94
35.9%

보험가입여부코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
245 
0
 
11
Y
 
6

Length

Max length4
Median length4
Mean length3.8053435
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> 245
93.5%
0 11
 
4.2%
Y 6
 
2.3%

Length

2024-04-30T05:02:24.945930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:25.072467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 245
93.5%
0 11
 
4.2%
y 6
 
2.3%

지도자수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
155 
1
73 
2
19 
0
 
15

Length

Max length4
Median length4
Mean length2.7748092
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> 155
59.2%
1 73
27.9%
2 19
 
7.3%
0 15
 
5.7%

Length

2024-04-30T05:02:25.171768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:25.256368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
59.2%
1 73
27.9%
2 19
 
7.3%
0 15
 
5.7%

건축물동수
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
189 
0
43 
1
30 

Length

Max length4
Median length4
Mean length3.1641221
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 189
72.1%
0 43
 
16.4%
1 30
 
11.5%

Length

2024-04-30T05:02:25.358978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:25.442223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 189
72.1%
0 43
 
16.4%
1 30
 
11.5%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct92
Distinct (%)68.1%
Missing127
Missing (%)48.5%
Infinite0
Infinite (%)0.0%
Mean11028.465
Minimum0
Maximum1231173
Zeros35
Zeros (%)13.4%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T05:02:25.543981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median829.87
Q32035.85
95-th percentile8645.364
Maximum1231173
Range1231173
Interquartile range (IQR)2035.85

Descriptive statistics

Standard deviation105862.26
Coefficient of variation (CV)9.5990019
Kurtosis134.65992
Mean11028.465
Median Absolute Deviation (MAD)829.87
Skewness11.597328
Sum1488842.8
Variance1.1206818 × 1010
MonotonicityNot monotonic
2024-04-30T05:02:25.677541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 35
 
13.4%
2346.34 2
 
0.8%
2875.95 2
 
0.8%
634.93 2
 
0.8%
4587.43 2
 
0.8%
2039.03 2
 
0.8%
684.35 2
 
0.8%
909.41 2
 
0.8%
974.28 2
 
0.8%
749.58 2
 
0.8%
Other values (82) 82
31.3%
(Missing) 127
48.5%
ValueCountFrequency (%)
0.0 35
13.4%
161.86 1
 
0.4%
249.93 1
 
0.4%
320.52 1
 
0.4%
394.51 1
 
0.4%
400.68 1
 
0.4%
425.76 1
 
0.4%
441.53 1
 
0.4%
444.96 1
 
0.4%
494.91 1
 
0.4%
ValueCountFrequency (%)
1231173.0 1
0.4%
23320.27 1
0.4%
22986.82 1
0.4%
17021.81 1
0.4%
14319.77 1
0.4%
13201.0 1
0.4%
12345.06 1
0.4%
7059.78 1
0.4%
6115.38 1
0.4%
5940.0 1
0.4%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
247 
0
 
15

Length

Max length4
Median length4
Mean length3.8282443
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> 247
94.3%
0 15
 
5.7%

Length

2024-04-30T05:02:25.804903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:25.890803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 247
94.3%
0 15
 
5.7%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing262
Missing (%)100.0%
Memory size2.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03200000CDFH330106198900000119891116<NA>3폐업3폐업20050308<NA><NA><NA><NA><NA>151888서울특별시 관악구 신림동 587-46번지서울특별시 관악구 난곡로 256 (신림동)<NA>거봉2009-09-01 15:22:32I2018-08-31 23:59:59.0<NA>192485.565227441648.942684체력단련장업사립<NA><NA>00.0<NA><NA><NA>
13200000CDFH330106198900000219891218<NA>1영업/정상13영업중<NA><NA><NA><NA>02-877-6458<NA><NA>서울특별시 관악구 신림동 131-21서울특별시 관악구 신림로 90, 5층 (신림동)08839짐박스 피트니스2022-08-23 14:53:49U2021-12-07 22:05:00.0<NA>194567.749823440976.482644<NA><NA><NA><NA><NA><NA><NA><NA><NA>
23200000CDFH330106198900000319891218<NA>3폐업3폐업20070604<NA><NA><NA><NA><NA>151872서울특별시 관악구 신림동 504-6번지서울특별시 관악구 조원로 132 (신림동)<NA>파워플러스헬스클럽2009-09-01 15:58:25I2018-08-31 23:59:59.0<NA>192582.733942442560.592626체력단련장업사립<NA><NA>00.0<NA><NA><NA>
33200000CDFH330106198900000419891218<NA>4취소/말소/만료/정지/중지35직권말소20141016<NA><NA><NA><NA><NA>151825서울특별시 관악구 봉천동 493-3번지서울특별시 관악구 양녕로 64 (봉천동)<NA>중앙헬스2014-11-19 09:59:42I2018-08-31 23:59:59.0<NA>195217.624373442839.032319체력단련장업사립<NA><NA>00.0<NA><NA><NA>
43200000CDFH330106198900000519891229<NA>4취소/말소/만료/정지/중지35직권말소20200911<NA><NA><NA><NA><NA>151880서울특별시 관악구 신림동 613-10서울특별시 관악구 난우길 8 (신림동)<NA>종합헬스2020-09-11 09:21:42U2020-09-13 02:40:00.0<NA>192765.201886441294.884932체력단련장업사립<NA><NA>01032.37<NA><NA><NA>
53200000CDFH330106198900000619891229<NA>4취소/말소/만료/정지/중지35직권말소20141107<NA><NA><NA><NA><NA>151930서울특별시 관악구 신림동 1640-48번지서울특별시 관악구 신림로 323 (신림동)<NA>신림헬스2014-11-21 10:07:18I2018-08-31 23:59:59.0<NA>193700.266889442335.340702체력단련장업사립<NA><NA>00.0<NA><NA><NA>
63200000CDFH330106199000000119900105<NA>4취소/말소/만료/정지/중지35직권말소20141028<NA><NA><NA><NA><NA>151862서울특별시 관악구 신림동 1513-3번지서울특별시 관악구 호암로 603 (신림동)<NA>화랑헬스2014-11-20 16:01:44I2018-08-31 23:59:59.0<NA>194048.078328441000.851294체력단련장업사립<NA><NA>00.0<NA><NA><NA>
73200000CDFH330106199000000219900807<NA>3폐업3폐업20000306<NA><NA><NA><NA><NA>151836서울특별시 관악구 봉천동 862-2번지 4층서울특별시 관악구 남부순환로 1820 (봉천동,4층)<NA>중앙헬스2003-02-06 10:45:13I2018-08-31 23:59:59.0<NA>195707.917935442075.680742체력단련장업사립<NA>000.0<NA><NA><NA>
83200000CDFH330106199200000119920422<NA>4취소/말소/만료/정지/중지35직권말소20141107<NA><NA><NA><NA><NA>151080서울특별시 관악구 남현동 1060-4번지 ,7서울특별시 관악구 남부순환로 2082-29 (남현동,,7)<NA>동일헬스크럽2014-11-21 09:58:33I2018-08-31 23:59:59.0<NA>198215.799294441548.607171체력단련장업사립<NA><NA>00.0<NA><NA><NA>
93200000CDFH330106199200000219921008<NA>3폐업3폐업19991028<NA><NA><NA><NA><NA>151848서울특별시 관악구 봉천동 857-14번지<NA><NA>한국헬스2003-02-06 10:45:13I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
2523200000CDFH33010620230000132023-09-17<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1566-3서울특별시 관악구 쑥고개로 97, 지층 (봉천동)08786GYM PRIVATE2023-09-17 14:45:20I2022-12-08 23:09:00.0<NA>195287.219195441902.697902<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2533200000CDFH33010620230000142023-10-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1566-8서울특별시 관악구 쑥고개로 103, 2층,3층 (봉천동)08786봉천동점 스포애니 (주)케이디헬스케어2024-03-20 10:52:50U2023-12-02 22:02:00.0<NA>195326.935558441899.463461<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2543200000CDFH33010620230000152023-10-18<NA>1영업/정상13영업중<NA><NA><NA><NA>02-883-6457<NA><NA>서울특별시 관악구 봉천동 463-4 메카플러스서울특별시 관악구 양녕로 46, 메카플러스 7층 (봉천동)08747짐박스피트니스 봉천현대시장점2023-10-18 09:34:27I2022-10-30 22:00:00.0<NA>195274.343266442663.498607<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2553200000CDFH33010620230000162023-11-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1632-9 진원빌딩서울특별시 관악구 봉천로 604, 진원빌딩 지층 (봉천동)08793운동하는날 낙성대점2023-11-08 09:09:47I2022-10-31 23:00:00.0<NA>196753.480707441530.298393<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2563200000CDFH33010620230000172023-12-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 478-25서울특별시 관악구 신사로20길 53, 지하1층 (신림동)08704프리원핏 신림점2024-04-16 19:36:09U2023-12-03 23:08:00.0<NA>192665.764771442740.319685<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2573200000CDFH33010620240000012024-01-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 876-1 그린피아 오피스텔서울특별시 관악구 관악로17길 25, 그린피아 오피스텔 B1층 101호 (봉천동)08786헤게모니짐PT 서울대입구점2024-04-09 11:55:39U2023-12-03 23:01:00.0<NA>195531.953701442060.794689<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2583200000CDFH33010620240000022024-02-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 704-67서울특별시 관악구 난곡로 173 (신림동)08858바디케이PT 난곡점2024-02-16 16:56:22U2023-12-01 23:08:00.0<NA>192820.524741440934.295564<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2593200000CDFH33010620240000032024-02-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 1514-1서울특별시 관악구 신림로 135, 지하1, 지상5,6층 (신림동)08812서울대벤처타운역점 스포애니 (주)케이디헬스케어2024-02-19 10:26:37U2023-12-01 22:01:00.0<NA>194120.792651440993.064166<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2603200000CDFH33010620240000042024-04-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-588-2998<NA><NA>서울특별시 관악구 남현동 1059-16서울특별시 관악구 남부순환로 2074 (남현동)08806짐박스피트니스 사당2호점2024-04-02 18:20:56I2023-12-04 00:04:00.0<NA>198081.693934441555.428706<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2613200000CDFH33010620240000052024-04-03<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8648-1400<NA><NA>서울특별시 관악구 신림동 118-3서울특별시 관악구 신림로 108, 지하1층 (신림동)08839원펀짐2024-04-03 11:12:25I2023-12-04 00:05:00.0<NA>194408.214484440998.894145<NA><NA><NA><NA><NA><NA><NA><NA><NA>