Overview

Dataset statistics

Number of variables34
Number of observations220
Missing cells2129
Missing cells (%)28.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.2 KiB
Average record size in memory289.6 B

Variable types

Categorical13
Text7
DateTime4
Unsupported7
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19857/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (95.8%)Imbalance
보험가입여부코드 is highly imbalanced (55.3%)Imbalance
회원모집총인원 is highly imbalanced (56.1%)Imbalance
폐업일자 has 122 (55.5%) missing valuesMissing
휴업시작일자 has 220 (100.0%) missing valuesMissing
휴업종료일자 has 220 (100.0%) missing valuesMissing
재개업일자 has 220 (100.0%) missing valuesMissing
전화번호 has 112 (50.9%) missing valuesMissing
소재지면적 has 220 (100.0%) missing valuesMissing
소재지우편번호 has 110 (50.0%) missing valuesMissing
도로명주소 has 7 (3.2%) missing valuesMissing
도로명우편번호 has 83 (37.7%) missing valuesMissing
업태구분명 has 220 (100.0%) missing valuesMissing
좌표정보(X) has 6 (2.7%) missing valuesMissing
좌표정보(Y) has 6 (2.7%) missing valuesMissing
건축물연면적 has 143 (65.0%) missing valuesMissing
세부업종명 has 220 (100.0%) missing valuesMissing
법인명 has 220 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
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 46 (20.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:17:54.003286
Analysis finished2024-05-11 06:17:55.523181
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3050000
220 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 220
100.0%

Length

2024-05-11T06:17:55.717415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:17:56.014829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 220
100.0%

관리번호
Text

UNIQUE 

Distinct220
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T06:17:56.513330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters4400
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

Unique220 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061991000001
4th rowCDFH3301061992000001
5th rowCDFH3301061992000002
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.5%
cdfh3301062019000013 1
 
0.5%
cdfh3301062020000013 1
 
0.5%
cdfh3301062019000003 1
 
0.5%
cdfh3301062019000004 1
 
0.5%
cdfh3301062019000005 1
 
0.5%
cdfh3301062019000006 1
 
0.5%
cdfh3301062019000007 1
 
0.5%
cdfh3301062019000008 1
 
0.5%
cdfh3301062019000009 1
 
0.5%
Other values (210) 210
95.5%
2024-05-11T06:17:57.710295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1782
40.5%
3 504
 
11.5%
1 414
 
9.4%
2 336
 
7.6%
6 261
 
5.9%
C 220
 
5.0%
D 220
 
5.0%
F 220
 
5.0%
H 220
 
5.0%
9 83
 
1.9%
Other values (4) 140
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3520
80.0%
Uppercase Letter 880
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1782
50.6%
3 504
 
14.3%
1 414
 
11.8%
2 336
 
9.5%
6 261
 
7.4%
9 83
 
2.4%
4 53
 
1.5%
5 32
 
0.9%
8 28
 
0.8%
7 27
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 220
25.0%
D 220
25.0%
F 220
25.0%
H 220
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3520
80.0%
Latin 880
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1782
50.6%
3 504
 
14.3%
1 414
 
11.8%
2 336
 
9.5%
6 261
 
7.4%
9 83
 
2.4%
4 53
 
1.5%
5 32
 
0.9%
8 28
 
0.8%
7 27
 
0.8%
Latin
ValueCountFrequency (%)
C 220
25.0%
D 220
25.0%
F 220
25.0%
H 220
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1782
40.5%
3 504
 
11.5%
1 414
 
9.4%
2 336
 
7.6%
6 261
 
5.9%
C 220
 
5.0%
D 220
 
5.0%
F 220
 
5.0%
H 220
 
5.0%
9 83
 
1.9%
Other values (4) 140
 
3.2%

인허가일자
Date

Distinct212
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1989-12-26 00:00:00
Maximum2024-04-08 00:00:00
2024-05-11T06:17:58.286201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:17:58.936806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
219 
20150904
 
1

Length

Max length8
Median length4
Mean length4.0181818
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
99.5%
20150904 1
 
0.5%

Length

2024-05-11T06:17:59.448814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:17:59.929037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
99.5%
20150904 1
 
0.5%

영업상태코드
Categorical

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
1
121 
3
78 
4
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 121
55.0%
3 78
35.5%
4 21
 
9.5%

Length

2024-05-11T06:18:00.350936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:00.762374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 121
55.0%
3 78
35.5%
4 21
 
9.5%

영업상태명
Categorical

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
영업/정상
121 
폐업
78 
취소/말소/만료/정지/중지
21 

Length

Max length14
Median length5
Mean length4.7954545
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 121
55.0%
폐업 78
35.5%
취소/말소/만료/정지/중지 21
 
9.5%

Length

2024-05-11T06:18:01.191969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:01.597694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 121
55.0%
폐업 78
35.5%
취소/말소/만료/정지/중지 21
 
9.5%

상세영업상태코드
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
13
121 
3
78 
35
20 
32
 
1

Length

Max length2
Median length2
Mean length1.6454545
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
13 121
55.0%
3 78
35.5%
35 20
 
9.1%
32 1
 
0.5%

Length

2024-05-11T06:18:02.377303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:02.920651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 121
55.0%
3 78
35.5%
35 20
 
9.1%
32 1
 
0.5%

상세영업상태명
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
영업중
121 
폐업
78 
직권말소
20 
신고취소
 
1

Length

Max length4
Median length3
Mean length2.7409091
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 121
55.0%
폐업 78
35.5%
직권말소 20
 
9.1%
신고취소 1
 
0.5%

Length

2024-05-11T06:18:03.836279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:04.723111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 121
55.0%
폐업 78
35.5%
직권말소 20
 
9.1%
신고취소 1
 
0.5%

폐업일자
Date

MISSING 

Distinct76
Distinct (%)77.6%
Missing122
Missing (%)55.5%
Memory size1.8 KiB
Minimum1999-11-05 00:00:00
Maximum2024-03-22 00:00:00
2024-05-11T06:18:05.739281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:18:06.695989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

전화번호
Text

MISSING 

Distinct107
Distinct (%)99.1%
Missing112
Missing (%)50.9%
Memory size1.8 KiB
2024-05-11T06:18:07.791869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.4537037
Min length8

Characters and Unicode

Total characters1021
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

Unique106 ?
Unique (%)98.1%

Sample

1st row212-5440
2nd row924-2993
3rd row2213-2410
4th row2248-0869
5th row927-8888
ValueCountFrequency (%)
2247-3960 2
 
1.9%
02-2215-1080 1
 
0.9%
2217-8989 1
 
0.9%
02-2216-2858 1
 
0.9%
02-3394-5155 1
 
0.9%
02-2244-2450 1
 
0.9%
02-3394-7111 1
 
0.9%
2216-8296 1
 
0.9%
928-8278 1
 
0.9%
2232-2236 1
 
0.9%
Other values (97) 97
89.8%
2024-05-11T06:18:09.801059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 186
18.2%
- 142
13.9%
9 120
11.8%
0 106
10.4%
6 89
8.7%
4 77
7.5%
1 65
 
6.4%
3 63
 
6.2%
7 60
 
5.9%
8 60
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 879
86.1%
Dash Punctuation 142
 
13.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 186
21.2%
9 120
13.7%
0 106
12.1%
6 89
10.1%
4 77
8.8%
1 65
 
7.4%
3 63
 
7.2%
7 60
 
6.8%
8 60
 
6.8%
5 53
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1021
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 186
18.2%
- 142
13.9%
9 120
11.8%
0 106
10.4%
6 89
8.7%
4 77
7.5%
1 65
 
6.4%
3 63
 
6.2%
7 60
 
5.9%
8 60
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 186
18.2%
- 142
13.9%
9 120
11.8%
0 106
10.4%
6 89
8.7%
4 77
7.5%
1 65
 
6.4%
3 63
 
6.2%
7 60
 
5.9%
8 60
 
5.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

소재지우편번호
Text

MISSING 

Distinct53
Distinct (%)48.2%
Missing110
Missing (%)50.0%
Memory size1.8 KiB
2024-05-11T06:18:10.431120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0090909
Min length6

Characters and Unicode

Total characters661
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

Unique24 ?
Unique (%)21.8%

Sample

1st row130020
2nd row130821
3rd row130846
4th row130844
5th row130823
ValueCountFrequency (%)
130840 7
 
6.4%
130802 5
 
4.5%
130805 4
 
3.6%
130838 4
 
3.6%
130851 4
 
3.6%
130876 4
 
3.6%
130842 4
 
3.6%
130867 4
 
3.6%
130831 3
 
2.7%
130864 3
 
2.7%
Other values (43) 68
61.8%
2024-05-11T06:18:11.691769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 146
22.1%
3 132
20.0%
1 128
19.4%
8 109
16.5%
7 30
 
4.5%
4 29
 
4.4%
2 28
 
4.2%
6 24
 
3.6%
5 22
 
3.3%
9 12
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 660
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146
22.1%
3 132
20.0%
1 128
19.4%
8 109
16.5%
7 30
 
4.5%
4 29
 
4.4%
2 28
 
4.2%
6 24
 
3.6%
5 22
 
3.3%
9 12
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146
22.1%
3 132
20.0%
1 128
19.4%
8 109
16.5%
7 30
 
4.5%
4 29
 
4.4%
2 28
 
4.2%
6 24
 
3.6%
5 22
 
3.3%
9 12
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146
22.1%
3 132
20.0%
1 128
19.4%
8 109
16.5%
7 30
 
4.5%
4 29
 
4.4%
2 28
 
4.2%
6 24
 
3.6%
5 22
 
3.3%
9 12
 
1.8%

지번주소
Text

Distinct216
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T06:18:12.399179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33.5
Mean length24.663636
Min length18

Characters and Unicode

Total characters5426
Distinct characters152
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)96.8%

Sample

1st row서울특별시 동대문구 전농동 325-19번지
2nd row서울특별시 동대문구 용두동 127-16번지
3rd row서울특별시 동대문구 장안동 460-1번지
4th row서울특별시 동대문구 장안동 423-2번지
5th row서울특별시 동대문구 용두동 144-166번지
ValueCountFrequency (%)
서울특별시 220
22.0%
동대문구 220
22.0%
장안동 58
 
5.8%
전농동 29
 
2.9%
답십리동 26
 
2.6%
용두동 21
 
2.1%
이문동 20
 
2.0%
휘경동 20
 
2.0%
회기동 15
 
1.5%
제기동 15
 
1.5%
Other values (276) 355
35.5%
2024-05-11T06:18:13.485362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
934
17.2%
동 450
 
8.3%
문 241
 
4.4%
대 223
 
4.1%
서 221
 
4.1%
울 221
 
4.1%
시 221
 
4.1%
구 220
 
4.1%
별 220
 
4.1%
특 220
 
4.1%
Other values (142) 2255
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3251
59.9%
Decimal Number 977
 
18.0%
Space Separator 934
 
17.2%
Dash Punctuation 199
 
3.7%
Lowercase Letter 19
 
0.4%
Open Punctuation 14
 
0.3%
Close Punctuation 14
 
0.3%
Uppercase Letter 13
 
0.2%
Other Punctuation 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 450
13.8%
문 241
 
7.4%
대 223
 
6.9%
서 221
 
6.8%
울 221
 
6.8%
시 221
 
6.8%
구 220
 
6.8%
별 220
 
6.8%
특 220
 
6.8%
지 129
 
4.0%
Other values (108) 885
27.2%
Decimal Number
ValueCountFrequency (%)
1 182
18.6%
2 151
15.5%
3 131
13.4%
4 106
10.8%
6 88
9.0%
5 75
7.7%
7 67
 
6.9%
8 64
 
6.6%
0 63
 
6.4%
9 50
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
21.1%
s 3
15.8%
t 3
15.8%
a 2
10.5%
l 2
10.5%
r 1
 
5.3%
h 1
 
5.3%
o 1
 
5.3%
m 1
 
5.3%
w 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
23.1%
S 2
15.4%
O 2
15.4%
T 2
15.4%
A 2
15.4%
M 1
 
7.7%
G 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
@ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
934
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 199
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3251
59.9%
Common 2143
39.5%
Latin 32
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 450
13.8%
문 241
 
7.4%
대 223
 
6.9%
서 221
 
6.8%
울 221
 
6.8%
시 221
 
6.8%
구 220
 
6.8%
별 220
 
6.8%
특 220
 
6.8%
지 129
 
4.0%
Other values (108) 885
27.2%
Common
ValueCountFrequency (%)
934
43.6%
- 199
 
9.3%
1 182
 
8.5%
2 151
 
7.0%
3 131
 
6.1%
4 106
 
4.9%
6 88
 
4.1%
5 75
 
3.5%
7 67
 
3.1%
8 64
 
3.0%
Other values (7) 146
 
6.8%
Latin
ValueCountFrequency (%)
e 4
12.5%
K 3
9.4%
s 3
9.4%
t 3
9.4%
a 2
 
6.2%
S 2
 
6.2%
l 2
 
6.2%
O 2
 
6.2%
T 2
 
6.2%
A 2
 
6.2%
Other values (7) 7
21.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3251
59.9%
ASCII 2175
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
934
42.9%
- 199
 
9.1%
1 182
 
8.4%
2 151
 
6.9%
3 131
 
6.0%
4 106
 
4.9%
6 88
 
4.0%
5 75
 
3.4%
7 67
 
3.1%
8 64
 
2.9%
Other values (24) 178
 
8.2%
Hangul
ValueCountFrequency (%)
동 450
13.8%
문 241
 
7.4%
대 223
 
6.9%
서 221
 
6.8%
울 221
 
6.8%
시 221
 
6.8%
구 220
 
6.8%
별 220
 
6.8%
특 220
 
6.8%
지 129
 
4.0%
Other values (108) 885
27.2%

도로명주소
Text

MISSING 

Distinct211
Distinct (%)99.1%
Missing7
Missing (%)3.2%
Memory size1.8 KiB
2024-05-11T06:18:14.480714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length48
Mean length30.455399
Min length22

Characters and Unicode

Total characters6487
Distinct characters173
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique209 ?
Unique (%)98.1%

Sample

1st row서울특별시 동대문구 무학로 104 (용두동)
2nd row서울특별시 동대문구 천호대로85길 32 (장안동)
3rd row서울특별시 동대문구 장한로5길 17 (장안동)
4th row서울특별시 동대문구 이문로 93 (이문동)
5th row서울특별시 동대문구 장한로 115 (장안동)
ValueCountFrequency (%)
서울특별시 213
 
16.9%
동대문구 213
 
16.9%
장안동 44
 
3.5%
답십리동 24
 
1.9%
2층 24
 
1.9%
장한로 23
 
1.8%
지하1층 22
 
1.7%
전농동 21
 
1.7%
전농로 17
 
1.3%
휘경동 16
 
1.3%
Other values (338) 644
51.1%
2024-05-11T06:18:15.985080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1085
 
16.7%
동 442
 
6.8%
문 248
 
3.8%
대 237
 
3.7%
) 225
 
3.5%
( 225
 
3.5%
시 223
 
3.4%
서 219
 
3.4%
울 219
 
3.4%
로 215
 
3.3%
Other values (163) 3149
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3880
59.8%
Space Separator 1085
 
16.7%
Decimal Number 838
 
12.9%
Close Punctuation 225
 
3.5%
Open Punctuation 225
 
3.5%
Other Punctuation 183
 
2.8%
Lowercase Letter 19
 
0.3%
Dash Punctuation 18
 
0.3%
Uppercase Letter 11
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 442
 
11.4%
문 248
 
6.4%
대 237
 
6.1%
시 223
 
5.7%
서 219
 
5.6%
울 219
 
5.6%
로 215
 
5.5%
구 214
 
5.5%
특 213
 
5.5%
별 213
 
5.5%
Other values (132) 1437
37.0%
Decimal Number
ValueCountFrequency (%)
1 193
23.0%
2 162
19.3%
3 98
11.7%
4 92
11.0%
0 65
 
7.8%
6 64
 
7.6%
5 55
 
6.6%
7 39
 
4.7%
8 35
 
4.2%
9 35
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 4
21.1%
s 3
15.8%
t 3
15.8%
a 2
10.5%
l 2
10.5%
r 1
 
5.3%
h 1
 
5.3%
o 1
 
5.3%
m 1
 
5.3%
w 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 4
36.4%
A 2
18.2%
S 2
18.2%
K 2
18.2%
G 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1085
100.0%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 225
100.0%
Other Punctuation
ValueCountFrequency (%)
, 183
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3880
59.8%
Common 2577
39.7%
Latin 30
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 442
 
11.4%
문 248
 
6.4%
대 237
 
6.1%
시 223
 
5.7%
서 219
 
5.6%
울 219
 
5.6%
로 215
 
5.5%
구 214
 
5.5%
특 213
 
5.5%
별 213
 
5.5%
Other values (132) 1437
37.0%
Common
ValueCountFrequency (%)
1085
42.1%
) 225
 
8.7%
( 225
 
8.7%
1 193
 
7.5%
, 183
 
7.1%
2 162
 
6.3%
3 98
 
3.8%
4 92
 
3.6%
0 65
 
2.5%
6 64
 
2.5%
Other values (6) 185
 
7.2%
Latin
ValueCountFrequency (%)
e 4
13.3%
B 4
13.3%
s 3
10.0%
t 3
10.0%
A 2
 
6.7%
a 2
 
6.7%
S 2
 
6.7%
l 2
 
6.7%
K 2
 
6.7%
r 1
 
3.3%
Other values (5) 5
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3880
59.8%
ASCII 2607
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1085
41.6%
) 225
 
8.6%
( 225
 
8.6%
1 193
 
7.4%
, 183
 
7.0%
2 162
 
6.2%
3 98
 
3.8%
4 92
 
3.5%
0 65
 
2.5%
6 64
 
2.5%
Other values (21) 215
 
8.2%
Hangul
ValueCountFrequency (%)
동 442
 
11.4%
문 248
 
6.4%
대 237
 
6.1%
시 223
 
5.7%
서 219
 
5.6%
울 219
 
5.6%
로 215
 
5.5%
구 214
 
5.5%
특 213
 
5.5%
별 213
 
5.5%
Other values (132) 1437
37.0%

도로명우편번호
Text

MISSING 

Distinct84
Distinct (%)61.3%
Missing83
Missing (%)37.7%
Memory size1.8 KiB
2024-05-11T06:18:16.781841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0510949
Min length5

Characters and Unicode

Total characters692
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

Unique54 ?
Unique (%)39.4%

Sample

1st row130814
2nd row02589
3rd row02611
4th row02451
5th row02638
ValueCountFrequency (%)
02624 6
 
4.4%
02532 5
 
3.6%
02419 5
 
3.6%
02639 4
 
2.9%
02452 4
 
2.9%
02637 4
 
2.9%
02460 3
 
2.2%
02531 3
 
2.2%
02436 3
 
2.2%
02560 3
 
2.2%
Other values (74) 97
70.8%
2024-05-11T06:18:17.992636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 161
23.3%
0 157
22.7%
4 78
11.3%
5 76
11.0%
6 67
9.7%
3 47
 
6.8%
1 35
 
5.1%
9 30
 
4.3%
8 26
 
3.8%
7 14
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 691
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 161
23.3%
0 157
22.7%
4 78
11.3%
5 76
11.0%
6 67
9.7%
3 47
 
6.8%
1 35
 
5.1%
9 30
 
4.3%
8 26
 
3.8%
7 14
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 161
23.3%
0 157
22.7%
4 78
11.3%
5 76
11.0%
6 67
9.7%
3 47
 
6.8%
1 35
 
5.1%
9 30
 
4.3%
8 26
 
3.8%
7 14
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 161
23.3%
0 157
22.7%
4 78
11.3%
5 76
11.0%
6 67
9.7%
3 47
 
6.8%
1 35
 
5.1%
9 30
 
4.3%
8 26
 
3.8%
7 14
 
2.0%

사업장명
Text

Distinct212
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T06:18:18.514329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.2409091
Min length2

Characters and Unicode

Total characters1593
Distinct characters287
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

Unique205 ?
Unique (%)93.2%

Sample

1st row금온헬스크럽
2nd row미림헬스
3rd row중앙헬스
4th row뉴서울헬스클럽
5th row동양헬스
ValueCountFrequency (%)
휘트니스 16
 
4.9%
gym 8
 
2.5%
헬스클럽 5
 
1.5%
짐 5
 
1.5%
헬스 4
 
1.2%
크로스핏 3
 
0.9%
회기점 3
 
0.9%
에이치짐 3
 
0.9%
중앙헬스 3
 
0.9%
피티 2
 
0.6%
Other values (252) 273
84.0%
2024-05-11T06:18:19.605354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 157
 
9.9%
105
 
6.6%
헬 64
 
4.0%
트 51
 
3.2%
짐 46
 
2.9%
니 43
 
2.7%
휘 38
 
2.4%
이 33
 
2.1%
럽 25
 
1.6%
크 23
 
1.4%
Other values (277) 1008
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1226
77.0%
Uppercase Letter 139
 
8.7%
Space Separator 105
 
6.6%
Lowercase Letter 60
 
3.8%
Decimal Number 18
 
1.1%
Open Punctuation 15
 
0.9%
Close Punctuation 15
 
0.9%
Other Punctuation 13
 
0.8%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 157
 
12.8%
헬 64
 
5.2%
트 51
 
4.2%
짐 46
 
3.8%
니 43
 
3.5%
휘 38
 
3.1%
이 33
 
2.7%
럽 25
 
2.0%
크 23
 
1.9%
점 20
 
1.6%
Other values (220) 726
59.2%
Uppercase Letter
ValueCountFrequency (%)
T 20
14.4%
M 15
10.8%
Y 12
 
8.6%
G 12
 
8.6%
P 9
 
6.5%
H 9
 
6.5%
E 8
 
5.8%
S 7
 
5.0%
O 6
 
4.3%
A 6
 
4.3%
Other values (15) 35
25.2%
Lowercase Letter
ValueCountFrequency (%)
y 10
16.7%
i 6
10.0%
m 6
10.0%
e 5
8.3%
o 5
8.3%
t 5
8.3%
g 4
 
6.7%
f 3
 
5.0%
d 3
 
5.0%
p 2
 
3.3%
Other values (7) 11
18.3%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
2 3
 
16.7%
3 2
 
11.1%
0 2
 
11.1%
4 1
 
5.6%
5 1
 
5.6%
9 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
& 6
46.2%
. 4
30.8%
, 2
 
15.4%
! 1
 
7.7%
Space Separator
ValueCountFrequency (%)
105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1226
77.0%
Latin 199
 
12.5%
Common 168
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 157
 
12.8%
헬 64
 
5.2%
트 51
 
4.2%
짐 46
 
3.8%
니 43
 
3.5%
휘 38
 
3.1%
이 33
 
2.7%
럽 25
 
2.0%
크 23
 
1.9%
점 20
 
1.6%
Other values (220) 726
59.2%
Latin
ValueCountFrequency (%)
T 20
 
10.1%
M 15
 
7.5%
Y 12
 
6.0%
G 12
 
6.0%
y 10
 
5.0%
P 9
 
4.5%
H 9
 
4.5%
E 8
 
4.0%
S 7
 
3.5%
i 6
 
3.0%
Other values (32) 91
45.7%
Common
ValueCountFrequency (%)
105
62.5%
( 15
 
8.9%
) 15
 
8.9%
1 8
 
4.8%
& 6
 
3.6%
. 4
 
2.4%
2 3
 
1.8%
3 2
 
1.2%
, 2
 
1.2%
- 2
 
1.2%
Other values (5) 6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1226
77.0%
ASCII 367
 
23.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 157
 
12.8%
헬 64
 
5.2%
트 51
 
4.2%
짐 46
 
3.8%
니 43
 
3.5%
휘 38
 
3.1%
이 33
 
2.7%
럽 25
 
2.0%
크 23
 
1.9%
점 20
 
1.6%
Other values (220) 726
59.2%
ASCII
ValueCountFrequency (%)
105
28.6%
T 20
 
5.4%
( 15
 
4.1%
M 15
 
4.1%
) 15
 
4.1%
Y 12
 
3.3%
G 12
 
3.3%
y 10
 
2.7%
P 9
 
2.5%
H 9
 
2.5%
Other values (47) 145
39.5%

최종수정일자
Date

Distinct217
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2003-04-18 15:38:02
Maximum2024-04-30 21:29:32
2024-05-11T06:18:19.968143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:18:20.308477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
U
117 
I
103 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 117
53.2%
I 103
46.8%

Length

2024-05-11T06:18:20.775226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:21.132991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 117
53.2%
i 103
46.8%

데이터갱신일자
Date

Distinct109
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T06:18:21.517367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:18:21.974639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)84.6%
Missing6
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean204819.91
Minimum202023.92
Maximum206590.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T06:18:22.451710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202023.92
5-th percentile202629.67
Q1204082.11
median205001.51
Q3205741.54
95-th percentile206331.02
Maximum206590.05
Range4566.1245
Interquartile range (IQR)1659.4304

Descriptive statistics

Standard deviation1165.2651
Coefficient of variation (CV)0.0056892179
Kurtosis-0.41091852
Mean204819.91
Median Absolute Deviation (MAD)804.13943
Skewness-0.65293482
Sum43831460
Variance1357842.7
MonotonicityNot monotonic
2024-05-11T06:18:22.943273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205309.743378991 3
 
1.4%
206244.551036173 3
 
1.4%
205964.401655984 3
 
1.4%
205271.704936121 3
 
1.4%
204007.767059377 2
 
0.9%
206472.467412741 2
 
0.9%
204024.364989132 2
 
0.9%
202605.151275083 2
 
0.9%
205384.138316051 2
 
0.9%
203340.686374876 2
 
0.9%
Other values (171) 190
86.4%
(Missing) 6
 
2.7%
ValueCountFrequency (%)
202023.921749857 1
0.5%
202056.089579192 1
0.5%
202061.169089769 1
0.5%
202081.864808843 1
0.5%
202180.141420844 1
0.5%
202233.604900045 1
0.5%
202246.202799972 1
0.5%
202257.985695221 1
0.5%
202572.480304067 1
0.5%
202605.151275083 2
0.9%
ValueCountFrequency (%)
206590.046202018 1
0.5%
206543.156690365 2
0.9%
206521.405320134 1
0.5%
206472.467412741 2
0.9%
206464.060139046 1
0.5%
206460.770782597 1
0.5%
206401.188819875 1
0.5%
206377.880006898 1
0.5%
206341.538776724 1
0.5%
206325.349431713 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)84.6%
Missing6
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean452945.62
Minimum451065.32
Maximum455771.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T06:18:23.382929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451065.32
5-th percentile451389.36
Q1452170.45
median452756.58
Q3453774.01
95-th percentile454890.59
Maximum455771.62
Range4706.2984
Interquartile range (IQR)1603.5603

Descriptive statistics

Standard deviation1083.5608
Coefficient of variation (CV)0.0023922537
Kurtosis-0.70883691
Mean452945.62
Median Absolute Deviation (MAD)755.0599
Skewness0.44014773
Sum96930362
Variance1174104.1
MonotonicityNot monotonic
2024-05-11T06:18:23.958183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454890.591043526 3
 
1.4%
452354.914065855 3
 
1.4%
453559.086631839 3
 
1.4%
452706.897879436 3
 
1.4%
453209.916468264 2
 
0.9%
452115.49557391 2
 
0.9%
453631.24724885 2
 
0.9%
453325.299202188 2
 
0.9%
452834.663102195 2
 
0.9%
452607.843299182 2
 
0.9%
Other values (171) 190
86.4%
(Missing) 6
 
2.7%
ValueCountFrequency (%)
451065.321633611 1
0.5%
451103.146980087 1
0.5%
451126.481053284 1
0.5%
451152.275276839 1
0.5%
451194.768957792 1
0.5%
451232.226044039 2
0.9%
451252.386694413 1
0.5%
451284.080255576 1
0.5%
451335.469980245 1
0.5%
451373.15341337 1
0.5%
ValueCountFrequency (%)
455771.62005247 1
 
0.5%
455273.197096849 1
 
0.5%
455230.913336391 1
 
0.5%
455222.36542642 1
 
0.5%
455139.055232126 1
 
0.5%
455131.683241064 2
0.9%
455106.642149046 1
 
0.5%
454966.801905413 1
 
0.5%
454890.591043526 3
1.4%
454857.91144375 1
 
0.5%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
체력단련장업
158 
<NA>
62 

Length

Max length6
Median length6
Mean length5.4363636
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 158
71.8%
<NA> 62
 
28.2%

Length

2024-05-11T06:18:24.652418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:25.034529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 158
71.8%
na 62
 
28.2%

공사립구분명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
사립
158 
<NA>
62 

Length

Max length4
Median length2
Mean length2.5636364
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 158
71.8%
<NA> 62
 
28.2%

Length

2024-05-11T06:18:25.665011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:26.072740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 158
71.8%
na 62
 
28.2%

보험가입여부코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
188 
0
25 
Y
 
7

Length

Max length4
Median length4
Mean length3.5636364
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> 188
85.5%
0 25
 
11.4%
Y 7
 
3.2%

Length

2024-05-11T06:18:26.526947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:27.150251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 188
85.5%
0 25
 
11.4%
y 7
 
3.2%

지도자수
Categorical

Distinct5
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
138 
1
36 
0
34 
2
 
11
4
 
1

Length

Max length4
Median length4
Mean length2.8818182
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 138
62.7%
1 36
 
16.4%
0 34
 
15.5%
2 11
 
5.0%
4 1
 
0.5%

Length

2024-05-11T06:18:27.694884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:28.226169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 138
62.7%
1 36
 
16.4%
0 34
 
15.5%
2 11
 
5.0%
4 1
 
0.5%

건축물동수
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
160 
0
47 
1
 
12
3
 
1

Length

Max length4
Median length4
Mean length3.1818182
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
72.7%
0 47
 
21.4%
1 12
 
5.5%
3 1
 
0.5%

Length

2024-05-11T06:18:28.920965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:29.512168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 160
72.7%
0 47
 
21.4%
1 12
 
5.5%
3 1
 
0.5%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)40.3%
Missing143
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean4210.8913
Minimum0
Maximum75865.35
Zeros46
Zeros (%)20.9%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T06:18:29.983516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32204
95-th percentile21303.364
Maximum75865.35
Range75865.35
Interquartile range (IQR)2204

Descriptive statistics

Standard deviation11189.189
Coefficient of variation (CV)2.657202
Kurtosis23.241906
Mean4210.8913
Median Absolute Deviation (MAD)0
Skewness4.3687901
Sum324238.63
Variance1.2519794 × 108
MonotonicityNot monotonic
2024-05-11T06:18:30.553946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 46
 
20.9%
4930.88 2
 
0.9%
40755.44 1
 
0.5%
1531.6 1
 
0.5%
374.4 1
 
0.5%
947.29 1
 
0.5%
9664.65 1
 
0.5%
3048.0 1
 
0.5%
2204.0 1
 
0.5%
3435.0 1
 
0.5%
Other values (21) 21
 
9.5%
(Missing) 143
65.0%
ValueCountFrequency (%)
0.0 46
20.9%
374.4 1
 
0.5%
444.3 1
 
0.5%
467.9 1
 
0.5%
580.28 1
 
0.5%
591.43 1
 
0.5%
824.1 1
 
0.5%
947.29 1
 
0.5%
998.81 1
 
0.5%
1227.67 1
 
0.5%
ValueCountFrequency (%)
75865.35 1
0.5%
40755.44 1
0.5%
31390.55 1
0.5%
21359.42 1
0.5%
21289.35 1
0.5%
20155.49 1
0.5%
19804.64 1
0.5%
14042.22 1
0.5%
12845.19 1
0.5%
12122.56 1
0.5%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
200 
0
 
20

Length

Max length4
Median length4
Mean length3.7272727
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> 200
90.9%
0 20
 
9.1%

Length

2024-05-11T06:18:31.177600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:18:31.580414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
90.9%
0 20
 
9.1%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing220
Missing (%)100.0%
Memory size2.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03050000CDFH330106198900000119891226<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>212-5440<NA>130020서울특별시 동대문구 전농동 325-19번지<NA><NA>금온헬스크럽2020-05-22 11:13:13U2020-05-24 02:40:00.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
13050000CDFH330106198900000219891230<NA>3폐업3폐업20030407<NA><NA><NA>924-2993<NA>130821서울특별시 동대문구 용두동 127-16번지서울특별시 동대문구 무학로 104 (용두동)<NA>미림헬스2003-04-18 15:38:02I2018-08-31 23:59:59.0<NA>202660.986071452358.367218체력단련장업사립<NA>000.0<NA><NA><NA>
23050000CDFH330106199100000119910329<NA>3폐업3폐업19991105<NA><NA><NA>2213-2410<NA>130846서울특별시 동대문구 장안동 460-1번지서울특별시 동대문구 천호대로85길 32 (장안동)<NA>중앙헬스2018-11-09 11:09:47U2018-11-11 02:38:42.0<NA>205842.92994451232.226044체력단련장업사립<NA>000.0<NA><NA><NA>
33050000CDFH330106199200000119921106<NA>3폐업3폐업20120921<NA><NA><NA>2248-0869<NA>130844서울특별시 동대문구 장안동 423-2번지서울특별시 동대문구 장한로5길 17 (장안동)<NA>뉴서울헬스클럽2012-09-21 13:11:55I2018-08-31 23:59:59.0<NA>205702.932774451335.46998체력단련장업사립0<NA><NA><NA><NA><NA><NA>
43050000CDFH330106199200000219920817<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>927-8888<NA>130823서울특별시 동대문구 용두동 144-166번지<NA><NA>동양헬스2020-05-22 11:03:35U2020-05-24 02:40:00.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
53050000CDFH330106199300000219930225<NA>3폐업3폐업20100507<NA><NA><NA>960-0283<NA>130831서울특별시 동대문구 이문동 329-1번지서울특별시 동대문구 이문로 93 (이문동)<NA>뉴헬스크럽2010-05-11 16:34:16I2018-08-31 23:59:59.0<NA>205162.314842454785.731294체력단련장업사립<NA><NA>00.0<NA><NA><NA>
63050000CDFH330106199300000319930618<NA>3폐업3폐업20181227<NA><NA><NA>249-2035<NA>130842서울특별시 동대문구 장안동 372-1번지서울특별시 동대문구 장한로 115 (장안동)<NA>올림피아헬스2018-12-27 16:19:20U2018-12-29 02:40:00.0<NA>206158.609155452075.431032체력단련장업사립<NA>000.0<NA><NA><NA>
73050000CDFH330106199300000419931220<NA>3폐업3폐업20021118<NA><NA><NA>2246-3633<NA>130846서울특별시 동대문구 장안동 464-1번지서울특별시 동대문구 장한로 6 (장안동)<NA>장안헬스크럽2003-04-18 15:38:02I2018-08-31 23:59:59.0<NA>205711.263316451065.321634체력단련장업사립<NA>000.0<NA><NA><NA>
83050000CDFH330106199500000319950306<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>244-8878<NA>130802서울특별시 동대문구 답십리동 268-4번지서울특별시 동대문구 전농로 35 (답십리동)<NA>광동헬스크럽2020-05-22 13:08:49U2020-05-24 02:40:00.0<NA>204942.025768451779.594496체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
93050000CDFH330106199500000419950413<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>927-3222<NA>130812서울특별시 동대문구 신설동 101-7번지서울특별시 동대문구 왕산로 4 (신설동)<NA>삼성남여체육관2020-05-22 11:02:39U2020-05-24 02:40:00.0<NA>202056.089579452590.463014체력단련장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
2103050000CDFH33010620230000092023-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 회기동 71-1서울특별시 동대문구 이문로 9-1, 1~3층 (회기동)02460위아짐 회기점2023-09-06 13:12:16I2022-12-09 00:08:00.0<NA>204730.604506454092.324598<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2113050000CDFH33010620230000102023-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 102-172 홈-스타(home-star)서울특별시 동대문구 무학로36길 56, 3층 (용두동, 홈-스타(home-star))02585베일리 짐2023-09-06 13:14:03I2022-12-09 00:08:00.0<NA>202898.576711452784.25335<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2123050000CDFH33010620230000112023-11-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 150-4서울특별시 동대문구 서울시립대로 155, 면전빌딩 4층 (전농동)02492트리플에이스튜디오2023-11-08 17:40:34I2022-10-31 23:00:00.0<NA>204701.099623453511.635022<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2133050000CDFH33010620230000122023-12-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 신설동 98-24 맹그로브 신설서울특별시 동대문구 왕산로 22, 맹그로브 신설 지하1층 (신설동)02582업타운 휘트니스 신설점2023-12-26 18:10:23I2022-11-01 22:09:00.0<NA>202233.6049452654.526626<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2143050000CDFH33010620240000012024-01-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 휘경동 258 리브인서울특별시 동대문구 망우로21길 26, 리브인 101동 101, 201호 (휘경동)02436애프터짐2024-01-04 09:40:29I2023-12-01 00:06:00.0<NA>205381.840246454264.179611<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2153050000CDFH33010620240000022024-01-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 68-1서울특별시 동대문구 전농로 94, 한성빌딩 2층 (답십리동)02538헬스고 여성전용2024-01-08 14:27:13I2023-11-30 23:04:00.0<NA>205033.87404452322.301296<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2163050000CDFH33010620240000032024-01-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 39-1 청량리역한양수자인그라시엘서울특별시 동대문구 고산자로32길 78, 지하1층 (용두동, 청량리역한양수자인그라시엘)02561소울트레이닝 청량리2024-01-18 14:30:35I2023-11-30 22:00:00.0<NA>203728.022004452778.965235<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2173050000CDFH33010620240000042024-03-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 797 청량리역 해링턴플레이스서울특별시 동대문구 고산자로34길 70, 청량리역 해링턴플레이스 B동 B02호 (용두동)02560렛츠붐 스피닝2024-03-08 09:25:28I2023-12-02 23:00:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2183050000CDFH33010620240000052024-03-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 255-66 청계천 대성 스카이렉스2서울특별시 동대문구 청계천로 471, 2층 1,2,3호 (용두동, 청계천 대성 스카이렉스2)02587골든몽키짐 플래티넘 sky2024-03-19 14:08:27I2023-12-02 22:01:00.0<NA>202572.480304452006.054686<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2193050000CDFH33010620240000062024-04-08<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3390-9618<NA><NA>서울특별시 동대문구 답십리동 266-1서울특별시 동대문구 전농로 38, 지하1,2층 (답십리동)02615답십리점 스포애니 (주)케이디헬스케어2024-04-08 18:18:42I2023-12-03 23:00:00.0<NA>204992.502701451779.215427<NA><NA><NA><NA><NA><NA><NA><NA><NA>