Overview

Dataset statistics

Number of variables34
Number of observations810
Missing cells8115
Missing cells (%)29.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory228.7 KiB
Average record size in memory289.2 B

Variable types

Categorical13
Text6
DateTime6
Unsupported6
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-19874/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (50.9%)Imbalance
영업상태명 is highly imbalanced (50.9%)Imbalance
상세영업상태코드 is highly imbalanced (50.9%)Imbalance
상세영업상태명 is highly imbalanced (50.9%)Imbalance
보험가입여부코드 is highly imbalanced (70.1%)Imbalance
지도자수 is highly imbalanced (52.3%)Imbalance
건축물동수 is highly imbalanced (66.6%)Imbalance
건축물연면적 is highly imbalanced (78.7%)Imbalance
회원모집총인원 is highly imbalanced (67.6%)Imbalance
인허가취소일자 has 810 (100.0%) missing valuesMissing
폐업일자 has 520 (64.2%) missing valuesMissing
휴업시작일자 has 808 (99.8%) missing valuesMissing
휴업종료일자 has 808 (99.8%) missing valuesMissing
재개업일자 has 810 (100.0%) missing valuesMissing
전화번호 has 376 (46.4%) missing valuesMissing
소재지면적 has 810 (100.0%) missing valuesMissing
소재지우편번호 has 470 (58.0%) missing valuesMissing
지번주소 has 10 (1.2%) missing valuesMissing
도로명우편번호 has 251 (31.0%) missing valuesMissing
업태구분명 has 810 (100.0%) missing valuesMissing
세부업종명 has 810 (100.0%) missing valuesMissing
법인명 has 810 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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

Reproduction

Analysis started2024-05-11 07:44:22.369997
Analysis finished2024-05-11 07:44:24.917310
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3220000
810 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 810
100.0%

Length

2024-05-11T07:44:25.255098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:25.706805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 810
100.0%

관리번호
Text

UNIQUE 

Distinct810
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-05-11T07:44:26.394189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters16200
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

Unique810 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061990000001
3rd rowCDFH3301061993000002
4th rowCDFH3301061994000001
5th rowCDFH3301061995000002
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.1%
cdfh3301062019000012 1
 
0.1%
cdfh3301062019000003 1
 
0.1%
cdfh3301062019000004 1
 
0.1%
cdfh3301062019000026 1
 
0.1%
cdfh3301062019000005 1
 
0.1%
cdfh3301062019000006 1
 
0.1%
cdfh3301062019000007 1
 
0.1%
cdfh3301062019000008 1
 
0.1%
cdfh3301062019000009 1
 
0.1%
Other values (800) 800
98.8%
2024-05-11T07:44:27.812146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6175
38.1%
3 1928
 
11.9%
1 1646
 
10.2%
2 1370
 
8.5%
6 956
 
5.9%
C 810
 
5.0%
D 810
 
5.0%
F 810
 
5.0%
H 810
 
5.0%
4 236
 
1.5%
Other values (4) 649
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12960
80.0%
Uppercase Letter 3240
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6175
47.6%
3 1928
 
14.9%
1 1646
 
12.7%
2 1370
 
10.6%
6 956
 
7.4%
4 236
 
1.8%
9 212
 
1.6%
5 165
 
1.3%
7 139
 
1.1%
8 133
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 810
25.0%
D 810
25.0%
F 810
25.0%
H 810
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12960
80.0%
Latin 3240
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6175
47.6%
3 1928
 
14.9%
1 1646
 
12.7%
2 1370
 
10.6%
6 956
 
7.4%
4 236
 
1.8%
9 212
 
1.6%
5 165
 
1.3%
7 139
 
1.1%
8 133
 
1.0%
Latin
ValueCountFrequency (%)
C 810
25.0%
D 810
25.0%
F 810
25.0%
H 810
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6175
38.1%
3 1928
 
11.9%
1 1646
 
10.2%
2 1370
 
8.5%
6 956
 
5.9%
C 810
 
5.0%
D 810
 
5.0%
F 810
 
5.0%
H 810
 
5.0%
4 236
 
1.5%
Other values (4) 649
 
4.0%

인허가일자
Date

Distinct711
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1989-12-28 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T07:44:28.354308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:28.946756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
1
512 
3
295 
2
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 512
63.2%
3 295
36.4%
2 2
 
0.2%
4 1
 
0.1%

Length

2024-05-11T07:44:29.320172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:29.776711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 512
63.2%
3 295
36.4%
2 2
 
0.2%
4 1
 
0.1%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
영업/정상
512 
폐업
295 
휴업
 
2
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length3.9111111
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 512
63.2%
폐업 295
36.4%
휴업 2
 
0.2%
취소/말소/만료/정지/중지 1
 
0.1%

Length

2024-05-11T07:44:30.403087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:30.908726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 512
63.2%
폐업 295
36.4%
휴업 2
 
0.2%
취소/말소/만료/정지/중지 1
 
0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
13
512 
3
295 
2
 
2
35
 
1

Length

Max length2
Median length2
Mean length1.6333333
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 512
63.2%
3 295
36.4%
2 2
 
0.2%
35 1
 
0.1%

Length

2024-05-11T07:44:31.390196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:31.841363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 512
63.2%
3 295
36.4%
2 2
 
0.2%
35 1
 
0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
영업중
512 
폐업
295 
휴업
 
2
직권말소
 
1

Length

Max length4
Median length3
Mean length2.6345679
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 512
63.2%
폐업 295
36.4%
휴업 2
 
0.2%
직권말소 1
 
0.1%

Length

2024-05-11T07:44:32.549614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:33.107741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 512
63.2%
폐업 295
36.4%
휴업 2
 
0.2%
직권말소 1
 
0.1%

폐업일자
Date

MISSING 

Distinct165
Distinct (%)56.9%
Missing520
Missing (%)64.2%
Memory size6.5 KiB
Minimum1996-04-03 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T07:44:33.725240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:34.155259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing808
Missing (%)99.8%
Memory size6.5 KiB
Minimum2019-10-10 00:00:00
Maximum2023-05-24 00:00:00
2024-05-11T07:44:34.872243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:35.316153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

휴업종료일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing808
Missing (%)99.8%
Memory size6.5 KiB
Minimum2020-10-09 00:00:00
Maximum2024-12-31 00:00:00
2024-05-11T07:44:35.829945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:36.290035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

전화번호
Text

MISSING 

Distinct416
Distinct (%)95.9%
Missing376
Missing (%)46.4%
Memory size6.5 KiB
2024-05-11T07:44:37.181934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.391705
Min length7

Characters and Unicode

Total characters4510
Distinct characters15
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)91.9%

Sample

1st row02-565-4778
2nd row3452-7676
3rd row544-7697
4th row3442-5573
5th row561-7497
ValueCountFrequency (%)
3452-3134 3
 
0.7%
02-538-9682 2
 
0.5%
518-3581 2
 
0.5%
02-3460-1333 2
 
0.5%
02-518-9744 2
 
0.5%
02-565-9618 2
 
0.5%
02-512-1202 2
 
0.5%
02-549-6868 2
 
0.5%
02-515-0455 2
 
0.5%
539-6300 2
 
0.5%
Other values (406) 413
95.2%
2024-05-11T07:44:38.760590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 694
15.4%
0 605
13.4%
5 592
13.1%
2 509
11.3%
4 357
7.9%
1 345
7.6%
6 321
7.1%
3 286
6.3%
7 281
6.2%
8 263
 
5.8%
Other values (5) 257
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3790
84.0%
Dash Punctuation 694
 
15.4%
Other Punctuation 23
 
0.5%
Math Symbol 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 605
16.0%
5 592
15.6%
2 509
13.4%
4 357
9.4%
1 345
9.1%
6 321
8.5%
3 286
7.5%
7 281
7.4%
8 263
6.9%
9 231
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 22
95.7%
/ 1
 
4.3%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
= 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 694
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 694
15.4%
0 605
13.4%
5 592
13.1%
2 509
11.3%
4 357
7.9%
1 345
7.6%
6 321
7.1%
3 286
6.3%
7 281
6.2%
8 263
 
5.8%
Other values (5) 257
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 694
15.4%
0 605
13.4%
5 592
13.1%
2 509
11.3%
4 357
7.9%
1 345
7.6%
6 321
7.1%
3 286
6.3%
7 281
6.2%
8 263
 
5.8%
Other values (5) 257
 
5.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

소재지우편번호
Text

MISSING 

Distinct152
Distinct (%)44.7%
Missing470
Missing (%)58.0%
Memory size6.5 KiB
2024-05-11T07:44:39.966591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0558824
Min length6

Characters and Unicode

Total characters2059
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

Unique71 ?
Unique (%)20.9%

Sample

1st row135822
2nd row135802
3rd row135897
4th row135514
5th row135937
ValueCountFrequency (%)
135897 8
 
2.4%
135957 7
 
2.1%
135816 7
 
2.1%
135500 7
 
2.1%
135847 6
 
1.8%
135830 6
 
1.8%
135896 6
 
1.8%
135954 6
 
1.8%
135860 5
 
1.5%
135894 5
 
1.5%
Other values (142) 277
81.5%
2024-05-11T07:44:41.823892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 458
22.2%
1 444
21.6%
3 406
19.7%
8 214
10.4%
9 182
 
8.8%
0 76
 
3.7%
7 75
 
3.6%
2 72
 
3.5%
4 62
 
3.0%
6 51
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2040
99.1%
Dash Punctuation 19
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 458
22.5%
1 444
21.8%
3 406
19.9%
8 214
10.5%
9 182
 
8.9%
0 76
 
3.7%
7 75
 
3.7%
2 72
 
3.5%
4 62
 
3.0%
6 51
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2059
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 458
22.2%
1 444
21.6%
3 406
19.7%
8 214
10.4%
9 182
 
8.8%
0 76
 
3.7%
7 75
 
3.6%
2 72
 
3.5%
4 62
 
3.0%
6 51
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 458
22.2%
1 444
21.6%
3 406
19.7%
8 214
10.4%
9 182
 
8.8%
0 76
 
3.7%
7 75
 
3.6%
2 72
 
3.5%
4 62
 
3.0%
6 51
 
2.5%

지번주소
Text

MISSING 

Distinct785
Distinct (%)98.1%
Missing10
Missing (%)1.2%
Memory size6.5 KiB
2024-05-11T07:44:42.420779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38.5
Mean length24.90875
Min length16

Characters and Unicode

Total characters19927
Distinct characters295
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique771 ?
Unique (%)96.4%

Sample

1st row서울특별시 강남구 논현동 121-1번지
2nd row서울특별시 강남구 개포동 168-4번지
3rd row서울특별시 강남구 신사동 662-5번지
4th row서울특별시 강남구 역삼동 734-22
5th row서울특별시 강남구 역삼동 837
ValueCountFrequency (%)
서울특별시 799
20.5%
강남구 799
20.5%
역삼동 177
 
4.5%
논현동 151
 
3.9%
대치동 110
 
2.8%
신사동 109
 
2.8%
청담동 97
 
2.5%
지하1층 88
 
2.3%
삼성동 67
 
1.7%
도곡동 46
 
1.2%
Other values (1132) 1463
37.5%
2024-05-11T07:44:43.842564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3664
18.4%
동 826
 
4.1%
서 813
 
4.1%
남 813
 
4.1%
1 809
 
4.1%
구 808
 
4.1%
강 807
 
4.0%
울 806
 
4.0%
시 805
 
4.0%
별 799
 
4.0%
Other values (285) 8977
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11519
57.8%
Decimal Number 3848
 
19.3%
Space Separator 3664
 
18.4%
Dash Punctuation 679
 
3.4%
Uppercase Letter 149
 
0.7%
Other Punctuation 43
 
0.2%
Math Symbol 7
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 826
 
7.2%
서 813
 
7.1%
남 813
 
7.1%
구 808
 
7.0%
강 807
 
7.0%
울 806
 
7.0%
시 805
 
7.0%
별 799
 
6.9%
특 799
 
6.9%
지 494
 
4.3%
Other values (242) 3749
32.5%
Uppercase Letter
ValueCountFrequency (%)
B 54
36.2%
S 11
 
7.4%
E 9
 
6.0%
O 8
 
5.4%
A 7
 
4.7%
T 6
 
4.0%
W 6
 
4.0%
R 6
 
4.0%
M 6
 
4.0%
F 5
 
3.4%
Other values (11) 31
20.8%
Decimal Number
ValueCountFrequency (%)
1 809
21.0%
2 565
14.7%
6 359
9.3%
4 343
8.9%
3 342
8.9%
5 337
8.8%
8 291
 
7.6%
7 290
 
7.5%
9 261
 
6.8%
0 251
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
l 2
33.3%
y 1
16.7%
r 1
16.7%
e 1
16.7%
a 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 35
81.4%
. 8
 
18.6%
Space Separator
ValueCountFrequency (%)
3664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 679
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11517
57.8%
Common 8253
41.4%
Latin 155
 
0.8%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 826
 
7.2%
서 813
 
7.1%
남 813
 
7.1%
구 808
 
7.0%
강 807
 
7.0%
울 806
 
7.0%
시 805
 
7.0%
별 799
 
6.9%
특 799
 
6.9%
지 494
 
4.3%
Other values (240) 3747
32.5%
Latin
ValueCountFrequency (%)
B 54
34.8%
S 11
 
7.1%
E 9
 
5.8%
O 8
 
5.2%
A 7
 
4.5%
T 6
 
3.9%
W 6
 
3.9%
R 6
 
3.9%
M 6
 
3.9%
F 5
 
3.2%
Other values (16) 37
23.9%
Common
ValueCountFrequency (%)
3664
44.4%
1 809
 
9.8%
- 679
 
8.2%
2 565
 
6.8%
6 359
 
4.3%
4 343
 
4.2%
3 342
 
4.1%
5 337
 
4.1%
8 291
 
3.5%
7 290
 
3.5%
Other values (7) 574
 
7.0%
Han
ValueCountFrequency (%)
巖 1
50.0%
如 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11517
57.8%
ASCII 8408
42.2%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3664
43.6%
1 809
 
9.6%
- 679
 
8.1%
2 565
 
6.7%
6 359
 
4.3%
4 343
 
4.1%
3 342
 
4.1%
5 337
 
4.0%
8 291
 
3.5%
7 290
 
3.4%
Other values (33) 729
 
8.7%
Hangul
ValueCountFrequency (%)
동 826
 
7.2%
서 813
 
7.1%
남 813
 
7.1%
구 808
 
7.0%
강 807
 
7.0%
울 806
 
7.0%
시 805
 
7.0%
별 799
 
6.9%
특 799
 
6.9%
지 494
 
4.3%
Other values (240) 3747
32.5%
CJK
ValueCountFrequency (%)
巖 1
50.0%
如 1
50.0%

도로명주소
Text

Distinct796
Distinct (%)98.8%
Missing4
Missing (%)0.5%
Memory size6.5 KiB
2024-05-11T07:44:44.576313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length31.944169
Min length22

Characters and Unicode

Total characters25747
Distinct characters313
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique786 ?
Unique (%)97.5%

Sample

1st row서울특별시 강남구 선릉로16길 4-10 (개포동)
2nd row서울특별시 강남구 언주로172길 53 (신사동)
3rd row서울특별시 강남구 역삼로 209 (역삼동)
4th row서울특별시 강남구 강남대로 318 (역삼동)
5th row서울특별시 강남구 학동로101길 15 (청담동)
ValueCountFrequency (%)
서울특별시 806
 
16.3%
강남구 806
 
16.3%
지하1층 172
 
3.5%
역삼동 145
 
2.9%
논현동 117
 
2.4%
신사동 88
 
1.8%
청담동 83
 
1.7%
대치동 75
 
1.5%
2층 61
 
1.2%
3층 54
 
1.1%
Other values (1121) 2533
51.3%
2024-05-11T07:44:45.889110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4223
 
16.4%
1 968
 
3.8%
동 915
 
3.6%
남 894
 
3.5%
구 868
 
3.4%
강 860
 
3.3%
로 820
 
3.2%
서 820
 
3.2%
) 812
 
3.2%
( 812
 
3.2%
Other values (303) 13755
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14952
58.1%
Space Separator 4223
 
16.4%
Decimal Number 3890
 
15.1%
Close Punctuation 812
 
3.2%
Open Punctuation 812
 
3.2%
Other Punctuation 804
 
3.1%
Uppercase Letter 195
 
0.8%
Dash Punctuation 43
 
0.2%
Math Symbol 8
 
< 0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 915
 
6.1%
남 894
 
6.0%
구 868
 
5.8%
강 860
 
5.8%
로 820
 
5.5%
서 820
 
5.5%
울 812
 
5.4%
시 811
 
5.4%
별 806
 
5.4%
특 806
 
5.4%
Other values (259) 6540
43.7%
Uppercase Letter
ValueCountFrequency (%)
B 94
48.2%
S 11
 
5.6%
E 10
 
5.1%
O 9
 
4.6%
A 9
 
4.6%
T 7
 
3.6%
W 6
 
3.1%
M 6
 
3.1%
G 6
 
3.1%
R 6
 
3.1%
Other values (11) 31
 
15.9%
Decimal Number
ValueCountFrequency (%)
1 968
24.9%
2 637
16.4%
3 475
12.2%
5 335
 
8.6%
4 328
 
8.4%
0 311
 
8.0%
6 246
 
6.3%
8 228
 
5.9%
7 208
 
5.3%
9 154
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
l 2
25.0%
b 2
25.0%
a 1
12.5%
y 1
12.5%
e 1
12.5%
r 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 793
98.6%
. 11
 
1.4%
Space Separator
ValueCountFrequency (%)
4223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 812
100.0%
Open Punctuation
ValueCountFrequency (%)
( 812
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14950
58.1%
Common 10592
41.1%
Latin 203
 
0.8%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 915
 
6.1%
남 894
 
6.0%
구 868
 
5.8%
강 860
 
5.8%
로 820
 
5.5%
서 820
 
5.5%
울 812
 
5.4%
시 811
 
5.4%
별 806
 
5.4%
특 806
 
5.4%
Other values (257) 6538
43.7%
Latin
ValueCountFrequency (%)
B 94
46.3%
S 11
 
5.4%
E 10
 
4.9%
O 9
 
4.4%
A 9
 
4.4%
T 7
 
3.4%
W 6
 
3.0%
M 6
 
3.0%
G 6
 
3.0%
R 6
 
3.0%
Other values (17) 39
19.2%
Common
ValueCountFrequency (%)
4223
39.9%
1 968
 
9.1%
) 812
 
7.7%
( 812
 
7.7%
, 793
 
7.5%
2 637
 
6.0%
3 475
 
4.5%
5 335
 
3.2%
4 328
 
3.1%
0 311
 
2.9%
Other values (7) 898
 
8.5%
Han
ValueCountFrequency (%)
如 1
50.0%
巖 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14950
58.1%
ASCII 10795
41.9%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4223
39.1%
1 968
 
9.0%
) 812
 
7.5%
( 812
 
7.5%
, 793
 
7.3%
2 637
 
5.9%
3 475
 
4.4%
5 335
 
3.1%
4 328
 
3.0%
0 311
 
2.9%
Other values (34) 1101
 
10.2%
Hangul
ValueCountFrequency (%)
동 915
 
6.1%
남 894
 
6.0%
구 868
 
5.8%
강 860
 
5.8%
로 820
 
5.5%
서 820
 
5.5%
울 812
 
5.4%
시 811
 
5.4%
별 806
 
5.4%
특 806
 
5.4%
Other values (257) 6538
43.7%
CJK
ValueCountFrequency (%)
如 1
50.0%
巖 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct238
Distinct (%)42.6%
Missing251
Missing (%)31.0%
Infinite0
Infinite (%)0.0%
Mean9848.966
Minimum6005
Maximum135969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T07:44:46.337224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6005
5-th percentile6015
Q16055
median6123
Q36225.5
95-th percentile6349
Maximum135969
Range129964
Interquartile range (IQR)170.5

Descriptive statistics

Standard deviation21639.252
Coefficient of variation (CV)2.1971091
Kurtosis30.246921
Mean9848.966
Median Absolute Deviation (MAD)85
Skewness5.6690223
Sum5505572
Variance4.6825725 × 108
MonotonicityNot monotonic
2024-05-11T07:44:46.860493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6018 11
 
1.4%
6099 11
 
1.4%
6017 11
 
1.4%
6059 10
 
1.2%
6014 8
 
1.0%
6022 7
 
0.9%
6109 7
 
0.9%
6055 7
 
0.9%
6016 7
 
0.9%
6062 7
 
0.9%
Other values (228) 473
58.4%
(Missing) 251
31.0%
ValueCountFrequency (%)
6005 1
 
0.1%
6006 2
 
0.2%
6010 2
 
0.2%
6011 5
0.6%
6012 3
 
0.4%
6013 5
0.6%
6014 8
1.0%
6015 3
 
0.4%
6016 7
0.9%
6017 11
1.4%
ValueCountFrequency (%)
135969 1
0.1%
135962 1
0.1%
135954 1
0.1%
135953 1
0.1%
135935 1
0.1%
135930 1
0.1%
135927 1
0.1%
135920 1
0.1%
135918 1
0.1%
135911 1
0.1%

사업장명
Text

Distinct802
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-05-11T07:44:47.719099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length26
Mean length10.265432
Min length2

Characters and Unicode

Total characters8315
Distinct characters468
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

Unique795 ?
Unique (%)98.1%

Sample

1st row파워짐
2nd row거성헬스
3rd row거산헬스클럽(28)
4th row알도요(22)
5th row강남헬스뱅크(25)
ValueCountFrequency (%)
gym 31
 
2.3%
휘트니스 18
 
1.3%
pt 16
 
1.2%
피트니스 15
 
1.1%
크로스핏 11
 
0.8%
주식회사 11
 
0.8%
짐 10
 
0.7%
스튜디오 10
 
0.7%
트레이닝 9
 
0.7%
스포애니 8
 
0.6%
Other values (1035) 1208
89.7%
2024-05-11T07:44:48.984594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
538
 
6.5%
스 443
 
5.3%
) 418
 
5.0%
( 414
 
5.0%
트 205
 
2.5%
짐 182
 
2.2%
이 160
 
1.9%
1 157
 
1.9%
2 156
 
1.9%
3 151
 
1.8%
Other values (458) 5491
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4474
53.8%
Decimal Number 1004
 
12.1%
Uppercase Letter 860
 
10.3%
Space Separator 538
 
6.5%
Lowercase Letter 520
 
6.3%
Close Punctuation 430
 
5.2%
Open Punctuation 426
 
5.1%
Other Punctuation 56
 
0.7%
Dash Punctuation 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 443
 
9.9%
트 205
 
4.6%
짐 182
 
4.1%
이 160
 
3.6%
니 147
 
3.3%
휘 94
 
2.1%
디 86
 
1.9%
피 72
 
1.6%
점 69
 
1.5%
라 69
 
1.5%
Other values (384) 2947
65.9%
Uppercase Letter
ValueCountFrequency (%)
T 99
 
11.5%
P 76
 
8.8%
G 71
 
8.3%
M 69
 
8.0%
Y 55
 
6.4%
A 51
 
5.9%
E 50
 
5.8%
S 47
 
5.5%
I 39
 
4.5%
O 38
 
4.4%
Other values (16) 265
30.8%
Lowercase Letter
ValueCountFrequency (%)
e 60
11.5%
i 54
10.4%
n 52
10.0%
t 49
9.4%
o 40
 
7.7%
s 39
 
7.5%
a 31
 
6.0%
y 28
 
5.4%
m 27
 
5.2%
r 26
 
5.0%
Other values (14) 114
21.9%
Decimal Number
ValueCountFrequency (%)
1 157
15.6%
2 156
15.5%
3 151
15.0%
4 133
13.2%
0 74
7.4%
6 70
7.0%
5 70
7.0%
7 68
6.8%
8 64
6.4%
9 61
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 22
39.3%
& 22
39.3%
, 6
 
10.7%
: 2
 
3.6%
? 2
 
3.6%
/ 1
 
1.8%
' 1
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 418
97.2%
] 12
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 414
97.2%
[ 12
 
2.8%
Space Separator
ValueCountFrequency (%)
538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4474
53.8%
Common 2461
29.6%
Latin 1380
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 443
 
9.9%
트 205
 
4.6%
짐 182
 
4.1%
이 160
 
3.6%
니 147
 
3.3%
휘 94
 
2.1%
디 86
 
1.9%
피 72
 
1.6%
점 69
 
1.5%
라 69
 
1.5%
Other values (384) 2947
65.9%
Latin
ValueCountFrequency (%)
T 99
 
7.2%
P 76
 
5.5%
G 71
 
5.1%
M 69
 
5.0%
e 60
 
4.3%
Y 55
 
4.0%
i 54
 
3.9%
n 52
 
3.8%
A 51
 
3.7%
E 50
 
3.6%
Other values (40) 743
53.8%
Common
ValueCountFrequency (%)
538
21.9%
) 418
17.0%
( 414
16.8%
1 157
 
6.4%
2 156
 
6.3%
3 151
 
6.1%
4 133
 
5.4%
0 74
 
3.0%
6 70
 
2.8%
5 70
 
2.8%
Other values (14) 280
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4474
53.8%
ASCII 3841
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
538
 
14.0%
) 418
 
10.9%
( 414
 
10.8%
1 157
 
4.1%
2 156
 
4.1%
3 151
 
3.9%
4 133
 
3.5%
T 99
 
2.6%
P 76
 
2.0%
0 74
 
1.9%
Other values (64) 1625
42.3%
Hangul
ValueCountFrequency (%)
스 443
 
9.9%
트 205
 
4.6%
짐 182
 
4.1%
이 160
 
3.6%
니 147
 
3.3%
휘 94
 
2.1%
디 86
 
1.9%
피 72
 
1.6%
점 69
 
1.5%
라 69
 
1.5%
Other values (384) 2947
65.9%

최종수정일자
Date

UNIQUE 

Distinct810
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2004-02-05 17:03:40
Maximum2024-05-09 12:05:44
2024-05-11T07:44:49.388275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:49.936799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
U
411 
I
399 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 411
50.7%
I 399
49.3%

Length

2024-05-11T07:44:50.367797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:50.961555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 411
50.7%
i 399
49.3%

데이터갱신일자
Date

Distinct380
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T07:44:51.397822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:44:51.933275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

좌표정보(X)
Real number (ℝ)

Distinct681
Distinct (%)84.5%
Missing4
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean203764.64
Minimum201646.06
Maximum212213.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T07:44:52.494864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201646.06
5-th percentile202024.62
Q1202882.94
median203532.41
Q3204490.54
95-th percentile205707.09
Maximum212213.69
Range10567.638
Interquartile range (IQR)1607.6018

Descriptive statistics

Standard deviation1287.8402
Coefficient of variation (CV)0.0063202339
Kurtosis4.7795839
Mean203764.64
Median Absolute Deviation (MAD)798.46013
Skewness1.4872139
Sum1.642343 × 108
Variance1658532.3
MonotonicityNot monotonic
2024-05-11T07:44:53.512563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202962.441804948 4
 
0.5%
205886.286776047 4
 
0.5%
205209.747122636 3
 
0.4%
204817.246059361 3
 
0.4%
202676.422809746 3
 
0.4%
203671.645686999 3
 
0.4%
203619.737329962 3
 
0.4%
205156.917414948 3
 
0.4%
202265.896799311 3
 
0.4%
203478.848090516 3
 
0.4%
Other values (671) 774
95.6%
(Missing) 4
 
0.5%
ValueCountFrequency (%)
201646.055864734 1
0.1%
201668.702125458 2
0.2%
201720.64812368 1
0.1%
201724.754920521 1
0.1%
201730.153319017 1
0.1%
201733.702293954 2
0.2%
201755.849621677 1
0.1%
201772.671195889 1
0.1%
201778.372432402 1
0.1%
201785.987184689 1
0.1%
ValueCountFrequency (%)
212213.694216827 1
0.1%
209568.78445268 1
0.1%
209421.920376653 1
0.1%
209110.791493694 1
0.1%
209062.201821883 1
0.1%
209052.072465426 1
0.1%
209009.86408188 1
0.1%
208992.862909059 1
0.1%
208955.31827 1
0.1%
208859.48 1
0.1%

좌표정보(Y)
Real number (ℝ)

Distinct681
Distinct (%)84.5%
Missing4
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean445140.85
Minimum440518.11
Maximum453696.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2024-05-11T07:44:54.165491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440518.11
5-th percentile442674.74
Q1444070.05
median445089.32
Q3446464.81
95-th percentile447181.72
Maximum453696.56
Range13178.453
Interquartile range (IQR)2394.7645

Descriptive statistics

Standard deviation1475.9735
Coefficient of variation (CV)0.0033157448
Kurtosis0.52024624
Mean445140.85
Median Absolute Deviation (MAD)1171.9141
Skewness-0.041102139
Sum3.5878353 × 108
Variance2178497.7
MonotonicityNot monotonic
2024-05-11T07:44:54.895576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447371.866295615 4
 
0.5%
443467.611815598 4
 
0.5%
443490.817333221 3
 
0.4%
443832.635074345 3
 
0.4%
444136.082630255 3
 
0.4%
444263.075193786 3
 
0.4%
445879.859319977 3
 
0.4%
444535.964228725 3
 
0.4%
444499.318499393 3
 
0.4%
446036.594200092 3
 
0.4%
Other values (671) 774
95.6%
(Missing) 4
 
0.5%
ValueCountFrequency (%)
440518.109999999 1
0.1%
440707.890762 1
0.1%
441103.672640686 1
0.1%
441108.499651602 1
0.1%
441298.325842647 1
0.1%
441457.423640678 1
0.1%
441675.495465839 1
0.1%
441753.907610029 1
0.1%
441819.460667918 1
0.1%
441875.546752218 1
0.1%
ValueCountFrequency (%)
453696.563171236 1
 
0.1%
447748.161018109 1
 
0.1%
447663.86257666 2
0.2%
447649.978394541 1
 
0.1%
447439.752421 1
 
0.1%
447393.51192286 1
 
0.1%
447371.866295615 4
0.5%
447362.10796179 2
0.2%
447334.651098516 1
 
0.1%
447329.953691113 1
 
0.1%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
체력단련장업
591 
<NA>
219 

Length

Max length6
Median length6
Mean length5.4592593
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 591
73.0%
<NA> 219
 
27.0%

Length

2024-05-11T07:44:55.384043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:55.714966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 591
73.0%
na 219
 
27.0%

공사립구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
사립
590 
<NA>
219 
공립
 
1

Length

Max length4
Median length2
Mean length2.5407407
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 590
72.8%
<NA> 219
 
27.0%
공립 1
 
0.1%

Length

2024-05-11T07:44:56.059782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:56.470380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 590
72.8%
na 219
 
27.0%
공립 1
 
0.1%

보험가입여부코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
767 
0
 
43

Length

Max length4
Median length4
Mean length3.8407407
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 767
94.7%
0 43
 
5.3%

Length

2024-05-11T07:44:56.836428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:57.169825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 767
94.7%
0 43
 
5.3%

지도자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
614 
1
126 
2
 
50
0
 
19
3
 
1

Length

Max length4
Median length4
Mean length3.2740741
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 614
75.8%
1 126
 
15.6%
2 50
 
6.2%
0 19
 
2.3%
3 1
 
0.1%

Length

2024-05-11T07:44:57.585533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:57.974963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 614
75.8%
1 126
 
15.6%
2 50
 
6.2%
0 19
 
2.3%
3 1
 
0.1%

건축물동수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
760 
0
 
50

Length

Max length4
Median length4
Mean length3.8148148
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> 760
93.8%
0 50
 
6.2%

Length

2024-05-11T07:44:58.393408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:58.744443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 760
93.8%
0 50
 
6.2%

건축물연면적
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
761 
0
 
48
490
 
1

Length

Max length4
Median length4
Mean length3.8209877
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 761
94.0%
0 48
 
5.9%
490 1
 
0.1%

Length

2024-05-11T07:44:59.127587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:44:59.486948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 761
94.0%
0 48
 
5.9%
490 1
 
0.1%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
762 
0
 
48

Length

Max length4
Median length4
Mean length3.8222222
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> 762
94.1%
0 48
 
5.9%

Length

2024-05-11T07:44:59.856617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:45:00.286849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 762
94.1%
0 48
 
5.9%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing810
Missing (%)100.0%
Memory size7.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03220000CDFH330106198900000119891228<NA>3폐업3폐업20040419<NA><NA><NA><NA><NA>135822서울특별시 강남구 논현동 121-1번지<NA><NA>파워짐2004-06-10 15:01:35I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립0<NA><NA><NA><NA><NA><NA>
13220000CDFH330106199000000119900202<NA>3폐업3폐업20050321<NA><NA><NA><NA><NA>135802서울특별시 강남구 개포동 168-4번지서울특별시 강남구 선릉로16길 4-10 (개포동)<NA>거성헬스2005-03-21 13:52:58I2018-08-31 23:59:59.0<NA>205269.83442351.96체력단련장업사립0<NA><NA><NA><NA><NA><NA>
23220000CDFH330106199300000219931210<NA>3폐업3폐업19960403<NA><NA><NA><NA><NA>135897서울특별시 강남구 신사동 662-5번지서울특별시 강남구 언주로172길 53 (신사동)<NA>거산헬스클럽(28)2006-04-03 10:42:18I2018-08-31 23:59:59.0<NA>203311.068042447204.468862체력단련장업사립0<NA><NA><NA><NA><NA><NA>
33220000CDFH330106199400000119940127<NA>3폐업3폐업20210311<NA><NA><NA>02-565-4778<NA>135514서울특별시 강남구 역삼동 734-22서울특별시 강남구 역삼로 209 (역삼동)<NA>알도요(22)2021-03-11 19:46:38U2021-03-13 02:40:00.0<NA>203473.846514443805.567264체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
43220000CDFH330106199500000219951005<NA>3폐업3폐업20210311<NA><NA><NA>3452-7676<NA>135937서울특별시 강남구 역삼동 837서울특별시 강남구 강남대로 318 (역삼동)<NA>강남헬스뱅크(25)2021-03-11 19:47:06U2021-03-13 02:40:00.0<NA>202688.511374443264.886254체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
53220000CDFH330106199500000319951019<NA>3폐업3폐업20210311<NA><NA><NA>544-7697<NA>135957서울특별시 강남구 청담동 132-16서울특별시 강남구 학동로101길 15 (청담동)<NA>청구(13)2021-03-11 19:47:55U2021-03-13 02:40:00.0<NA>205004.086673446564.659683체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
63220000CDFH330106199600000119960110<NA>3폐업3폐업20050622<NA><NA><NA><NA><NA>135917서울특별시 강남구 역삼동 697-45번지서울특별시 강남구 선릉로93길 22 (역삼동)<NA>오륜헬스(16)2006-04-03 10:45:30I2018-08-31 23:59:59.0<NA>204061.414991444757.531873체력단련장업사립0<NA><NA><NA><NA><NA><NA>
73220000CDFH330106199600000219960307<NA>3폐업3폐업20210311<NA><NA><NA>3442-5573<NA>135833서울특별시 강남구 논현동 278-22서울특별시 강남구 봉은사로 331 (논현동)<NA>강남헬스클럽(41)2021-03-11 19:48:39U2021-03-13 02:40:00.0<NA>203729.224187445341.453295체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
83220000CDFH330106199600000319960422<NA>3폐업3폐업20210311<NA><NA><NA>561-7497<NA>135911서울특별시 강남구 역삼동 648-15서울특별시 강남구 테헤란로13길 11 (역삼동)<NA>헬스렌드(42)2021-03-11 19:49:12U2021-03-13 02:40:00.0<NA>202774.114749444244.296155체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
93220000CDFH330106199600000419960502<NA>3폐업3폐업20210311<NA><NA><NA>557-9654<NA>135840서울특별시 강남구 대치동 893-4서울특별시 강남구 삼성로 427 (대치동)<NA>장수헬스(43)2021-03-11 19:49:41U2021-03-13 02:40:00.0<NA>204993.168008444750.10211체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
8003220000CDFH33010620240000052024-01-19<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4647-4906<NA><NA>서울특별시 강남구 대치동 897서울특별시 강남구 선릉로 424, 302호 (대치동)6198힙투게더 선릉점2024-01-19 13:29:38I2023-11-30 22:01:00.0<NA>204358.768922444520.576717<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8013220000CDFH33010620240000062024-02-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 728 지산빌딩서울특별시 강남구 역삼로25길 28, 지산빌딩 1층 (역삼동)6224하와이짐2024-05-09 12:05:44U2023-12-04 23:01:00.0<NA>203420.476058443985.277094<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8023220000CDFH33010620240000072024-02-23<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 압구정동 481 현대아파트서울특별시 강남구 압구정로 309, 지하층 (압구정동, 현대아파트)6006트레이브짐2024-02-23 13:19:42I2023-12-01 22:05:00.0<NA>203062.784523447663.862577<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8033220000CDFH33010620240000082024-03-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 708-20 금천빌딩서울특별시 강남구 테헤란로52길 15, 금천빌딩 B201호 (역삼동)6212휘트니스엠 선릉점2024-03-14 17:26:17I2023-12-02 23:06:00.0<NA>204170.084609444548.397487<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8043220000CDFH33010620240000092024-03-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 논현동 95-18서울특별시 강남구 도산대로50길 17, B1층 (논현동)6055피크짐(PEAK GYM)2024-03-22 17:11:49I2023-12-02 22:04:00.0<NA>203261.331008446567.741285<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8053220000CDFH33010620240000102024-04-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 45서울특별시 강남구 선릉로112길 64, 3층 (삼성동)6096유연바디랩2024-04-11 09:03:39I2023-12-03 23:03:00.0<NA>204242.905548445579.81976<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8063220000CDFH33010620240000112024-04-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 613-2서울특별시 강남구 논현로176길 22, B1층 (신사동)6022라이크짐 PT, 필라테스 2호점2024-04-11 09:07:32I2023-12-03 23:03:00.0<NA>202611.880761447226.439865<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8073220000CDFH33010620240000122024-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 논현동 242-31서울특별시 강남구 선릉로 663, 2층 (논현동)6099주식회사 닥터핏2024-04-12 14:09:24I2023-12-03 23:04:00.0<NA>203596.079927445965.838235<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8083220000CDFH33010620240000132024-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 논현동 147-10서울특별시 강남구 학동로20길 62, 2층 (논현동)6113논현PT 미라클 통증케어 체형교정2024-04-12 14:29:17I2023-12-03 23:04:00.0<NA>202287.215449445306.820699<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8093220000CDFH33010620240000142024-05-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 논현동 240-7 계풍빌딩서울특별시 강남구 학동로 332, 계풍빌딩 지하1층 (논현동)6099워터웍스 짐앤풀2024-05-09 10:48:03I2023-12-04 23:01:00.0<NA>203395.806596446013.259425<NA><NA><NA><NA><NA><NA><NA><NA><NA>