Overview

Dataset statistics

Number of variables34
Number of observations375
Missing cells3269
Missing cells (%)25.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory106.3 KiB
Average record size in memory290.4 B

Variable types

Categorical14
Text7
DateTime4
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-19639/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (56.0%)Imbalance
영업상태명 is highly imbalanced (56.0%)Imbalance
상세영업상태코드 is highly imbalanced (56.0%)Imbalance
상세영업상태명 is highly imbalanced (56.0%)Imbalance
휴업시작일자 is highly imbalanced (97.3%)Imbalance
휴업종료일자 is highly imbalanced (97.3%)Imbalance
문화체육업종명 is highly imbalanced (52.7%)Imbalance
공사립구분명 is highly imbalanced (52.7%)Imbalance
회원모집총인원 is highly imbalanced (95.2%)Imbalance
인허가취소일자 has 375 (100.0%) missing valuesMissing
폐업일자 has 62 (16.5%) missing valuesMissing
재개업일자 has 375 (100.0%) missing valuesMissing
전화번호 has 313 (83.5%) missing valuesMissing
소재지면적 has 375 (100.0%) missing valuesMissing
소재지우편번호 has 42 (11.2%) missing valuesMissing
지번주소 has 14 (3.7%) missing valuesMissing
도로명주소 has 44 (11.7%) missing valuesMissing
도로명우편번호 has 308 (82.1%) missing valuesMissing
업태구분명 has 375 (100.0%) missing valuesMissing
좌표정보(X) has 26 (6.9%) missing valuesMissing
좌표정보(Y) has 26 (6.9%) missing valuesMissing
건축물연면적 has 184 (49.1%) missing valuesMissing
세부업종명 has 375 (100.0%) missing valuesMissing
법인명 has 375 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 177 (47.2%) zerosZeros

Reproduction

Analysis started2024-04-29 19:59:21.325900
Analysis finished2024-04-29 19:59:22.159697
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3120000
375 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 375
100.0%

Length

2024-04-30T04:59:22.220404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:22.297164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 375
100.0%

관리번호
Text

UNIQUE 

Distinct375
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:22.431631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7500
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

Unique375 ?
Unique (%)100.0%

Sample

1st rowCDFH3301081989000003
2nd rowCDFH3301081990000001
3rd rowCDFH3301081990000002
4th rowCDFH3301081990000004
5th rowCDFH3301081991000003
ValueCountFrequency (%)
cdfh3301081989000003 1
 
0.3%
cdfh3301082002000011 1
 
0.3%
cdfh3301082005000008 1
 
0.3%
cdfh3301082005000007 1
 
0.3%
cdfh3301082005000006 1
 
0.3%
cdfh3301082005000004 1
 
0.3%
cdfh3301082005000003 1
 
0.3%
cdfh3301082005000002 1
 
0.3%
cdfh3301082005000001 1
 
0.3%
cdfh3301082004000004 1
 
0.3%
Other values (365) 365
97.3%
2024-04-30T04:59:22.699588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2762
36.8%
3 839
 
11.2%
1 808
 
10.8%
8 477
 
6.4%
9 463
 
6.2%
C 375
 
5.0%
D 375
 
5.0%
F 375
 
5.0%
H 375
 
5.0%
2 291
 
3.9%
Other values (4) 360
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6000
80.0%
Uppercase Letter 1500
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2762
46.0%
3 839
 
14.0%
1 808
 
13.5%
8 477
 
8.0%
9 463
 
7.7%
2 291
 
4.9%
7 100
 
1.7%
4 91
 
1.5%
6 88
 
1.5%
5 81
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
C 375
25.0%
D 375
25.0%
F 375
25.0%
H 375
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
80.0%
Latin 1500
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2762
46.0%
3 839
 
14.0%
1 808
 
13.5%
8 477
 
8.0%
9 463
 
7.7%
2 291
 
4.9%
7 100
 
1.7%
4 91
 
1.5%
6 88
 
1.5%
5 81
 
1.4%
Latin
ValueCountFrequency (%)
C 375
25.0%
D 375
25.0%
F 375
25.0%
H 375
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2762
36.8%
3 839
 
11.2%
1 808
 
10.8%
8 477
 
6.4%
9 463
 
6.2%
C 375
 
5.0%
D 375
 
5.0%
F 375
 
5.0%
H 375
 
5.0%
2 291
 
3.9%
Other values (4) 360
 
4.8%

인허가일자
Date

Distinct343
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum1989-12-31 00:00:00
Maximum2023-11-14 00:00:00
2024-04-30T04:59:22.824474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:22.943693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3
300 
1
60 
4
 
14
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
3 300
80.0%
1 60
 
16.0%
4 14
 
3.7%
2 1
 
0.3%

Length

2024-04-30T04:59:23.050963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:23.161592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 300
80.0%
1 60
 
16.0%
4 14
 
3.7%
2 1
 
0.3%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
300 
영업/정상
60 
취소/말소/만료/정지/중지
 
14
휴업
 
1

Length

Max length14
Median length2
Mean length2.928
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row폐업
2nd row폐업
3rd row영업/정상
4th row영업/정상
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 300
80.0%
영업/정상 60
 
16.0%
취소/말소/만료/정지/중지 14
 
3.7%
휴업 1
 
0.3%

Length

2024-04-30T04:59:23.268528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:23.357002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 300
80.0%
영업/정상 60
 
16.0%
취소/말소/만료/정지/중지 14
 
3.7%
휴업 1
 
0.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3
300 
13
60 
35
 
14
2
 
1

Length

Max length2
Median length1
Mean length1.1973333
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
3 300
80.0%
13 60
 
16.0%
35 14
 
3.7%
2 1
 
0.3%

Length

2024-04-30T04:59:23.453872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:23.543750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 300
80.0%
13 60
 
16.0%
35 14
 
3.7%
2 1
 
0.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
300 
영업중
60 
직권말소
 
14
휴업
 
1

Length

Max length4
Median length2
Mean length2.2346667
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 300
80.0%
영업중 60
 
16.0%
직권말소 14
 
3.7%
휴업 1
 
0.3%

Length

2024-04-30T04:59:23.647815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:23.737822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 300
80.0%
영업중 60
 
16.0%
직권말소 14
 
3.7%
휴업 1
 
0.3%

폐업일자
Date

MISSING 

Distinct217
Distinct (%)69.3%
Missing62
Missing (%)16.5%
Memory size3.1 KiB
Minimum1994-10-30 00:00:00
Maximum2023-12-13 00:00:00
2024-04-30T04:59:23.833762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:23.956703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
374 
20110501
 
1

Length

Max length8
Median length4
Mean length4.0106667
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 374
99.7%
20110501 1
 
0.3%

Length

2024-04-30T04:59:24.067003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:24.169888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 374
99.7%
20110501 1
 
0.3%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
374 
20120501
 
1

Length

Max length8
Median length4
Mean length4.0106667
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 374
99.7%
20120501 1
 
0.3%

Length

2024-04-30T04:59:24.274432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:24.373661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 374
99.7%
20120501 1
 
0.3%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

전화번호
Text

MISSING 

Distinct61
Distinct (%)98.4%
Missing313
Missing (%)83.5%
Memory size3.1 KiB
2024-04-30T04:59:24.548138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length9.1129032
Min length8

Characters and Unicode

Total characters565
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)96.8%

Sample

1st row396-2709
2nd row07048459314
3rd row02-324-3377
4th row336-9350
5th row308-9472
ValueCountFrequency (%)
02-374-7800 2
 
3.2%
02-374-1935 1
 
1.6%
304-7783 1
 
1.6%
395-0890 1
 
1.6%
362-8569 1
 
1.6%
302-0744 1
 
1.6%
394-5568 1
 
1.6%
02-395-9890 1
 
1.6%
307-2661 1
 
1.6%
365-4400 1
 
1.6%
Other values (51) 51
82.3%
2024-04-30T04:59:24.870652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 90
15.9%
0 81
14.3%
- 79
14.0%
2 65
11.5%
9 44
7.8%
7 41
7.3%
4 38
6.7%
5 38
6.7%
8 33
 
5.8%
6 33
 
5.8%
Other values (2) 23
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485
85.8%
Dash Punctuation 79
 
14.0%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 90
18.6%
0 81
16.7%
2 65
13.4%
9 44
9.1%
7 41
8.5%
4 38
7.8%
5 38
7.8%
8 33
 
6.8%
6 33
 
6.8%
1 22
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 565
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 90
15.9%
0 81
14.3%
- 79
14.0%
2 65
11.5%
9 44
7.8%
7 41
7.3%
4 38
6.7%
5 38
6.7%
8 33
 
5.8%
6 33
 
5.8%
Other values (2) 23
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 90
15.9%
0 81
14.3%
- 79
14.0%
2 65
11.5%
9 44
7.8%
7 41
7.3%
4 38
6.7%
5 38
6.7%
8 33
 
5.8%
6 33
 
5.8%
Other values (2) 23
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

소재지우편번호
Text

MISSING 

Distinct72
Distinct (%)21.6%
Missing42
Missing (%)11.2%
Memory size3.1 KiB
2024-04-30T04:59:25.077840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.012012
Min length6

Characters and Unicode

Total characters2002
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

Unique22 ?
Unique (%)6.6%

Sample

1st row120806
2nd row120070
3rd row120020
4th row120857
5th row120012
ValueCountFrequency (%)
120834 56
 
16.8%
120833 22
 
6.6%
120807 16
 
4.8%
120806 15
 
4.5%
120857 13
 
3.9%
120848 12
 
3.6%
120808 11
 
3.3%
120809 11
 
3.3%
120825 10
 
3.0%
120805 10
 
3.0%
Other values (62) 157
47.1%
2024-04-30T04:59:25.388664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 484
24.2%
1 402
20.1%
2 384
19.2%
8 322
16.1%
3 138
 
6.9%
4 91
 
4.5%
5 60
 
3.0%
7 51
 
2.5%
6 43
 
2.1%
9 23
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1998
99.8%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 484
24.2%
1 402
20.1%
2 384
19.2%
8 322
16.1%
3 138
 
6.9%
4 91
 
4.6%
5 60
 
3.0%
7 51
 
2.6%
6 43
 
2.2%
9 23
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 484
24.2%
1 402
20.1%
2 384
19.2%
8 322
16.1%
3 138
 
6.9%
4 91
 
4.5%
5 60
 
3.0%
7 51
 
2.5%
6 43
 
2.1%
9 23
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 484
24.2%
1 402
20.1%
2 384
19.2%
8 322
16.1%
3 138
 
6.9%
4 91
 
4.5%
5 60
 
3.0%
7 51
 
2.5%
6 43
 
2.1%
9 23
 
1.1%

지번주소
Text

MISSING 

Distinct340
Distinct (%)94.2%
Missing14
Missing (%)3.7%
Memory size3.1 KiB
2024-04-30T04:59:25.594924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length40
Mean length25.34349
Min length19

Characters and Unicode

Total characters9149
Distinct characters98
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

Unique323 ?
Unique (%)89.5%

Sample

1st row서울특별시 서대문구 남가좌동 324-30번지 (2층)
2nd row서울특별시 서대문구 영천동 320번지
3rd row서울특별시 서대문구 미근동 31-13번지
4th row서울특별시 서대문구 홍제동 294-50번지 2층
5th row서울특별시 서대문구 충정로2가 131번지
ValueCountFrequency (%)
서울특별시 361
22.2%
서대문구 361
22.2%
창천동 88
 
5.4%
남가좌동 60
 
3.7%
홍제동 42
 
2.6%
2층 41
 
2.5%
북가좌동 40
 
2.5%
3층 36
 
2.2%
홍은동 32
 
2.0%
연희동 28
 
1.7%
Other values (388) 536
33.0%
2024-04-30T04:59:25.911811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1587
17.3%
서 722
 
7.9%
대 385
 
4.2%
시 362
 
4.0%
구 361
 
3.9%
문 361
 
3.9%
울 361
 
3.9%
별 361
 
3.9%
특 361
 
3.9%
- 347
 
3.8%
Other values (88) 3941
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5394
59.0%
Decimal Number 1728
 
18.9%
Space Separator 1587
 
17.3%
Dash Punctuation 347
 
3.8%
Close Punctuation 38
 
0.4%
Open Punctuation 38
 
0.4%
Other Punctuation 15
 
0.2%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 722
13.4%
대 385
 
7.1%
시 362
 
6.7%
구 361
 
6.7%
문 361
 
6.7%
울 361
 
6.7%
별 361
 
6.7%
특 361
 
6.7%
동 345
 
6.4%
지 343
 
6.4%
Other values (71) 1432
26.5%
Decimal Number
ValueCountFrequency (%)
3 336
19.4%
1 311
18.0%
2 286
16.6%
4 169
9.8%
5 128
 
7.4%
0 120
 
6.9%
7 108
 
6.2%
9 99
 
5.7%
8 86
 
5.0%
6 85
 
4.9%
Space Separator
ValueCountFrequency (%)
1587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 347
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5394
59.0%
Common 3754
41.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 722
13.4%
대 385
 
7.1%
시 362
 
6.7%
구 361
 
6.7%
문 361
 
6.7%
울 361
 
6.7%
별 361
 
6.7%
특 361
 
6.7%
동 345
 
6.4%
지 343
 
6.4%
Other values (71) 1432
26.5%
Common
ValueCountFrequency (%)
1587
42.3%
- 347
 
9.2%
3 336
 
9.0%
1 311
 
8.3%
2 286
 
7.6%
4 169
 
4.5%
5 128
 
3.4%
0 120
 
3.2%
7 108
 
2.9%
9 99
 
2.6%
Other values (6) 263
 
7.0%
Latin
ValueCountFrequency (%)
a 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5394
59.0%
ASCII 3755
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1587
42.3%
- 347
 
9.2%
3 336
 
8.9%
1 311
 
8.3%
2 286
 
7.6%
4 169
 
4.5%
5 128
 
3.4%
0 120
 
3.2%
7 108
 
2.9%
9 99
 
2.6%
Other values (7) 264
 
7.0%
Hangul
ValueCountFrequency (%)
서 722
13.4%
대 385
 
7.1%
시 362
 
6.7%
구 361
 
6.7%
문 361
 
6.7%
울 361
 
6.7%
별 361
 
6.7%
특 361
 
6.7%
동 345
 
6.4%
지 343
 
6.4%
Other values (71) 1432
26.5%

도로명주소
Text

MISSING 

Distinct318
Distinct (%)96.1%
Missing44
Missing (%)11.7%
Memory size3.1 KiB
2024-04-30T04:59:26.150420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length43
Mean length28.217523
Min length22

Characters and Unicode

Total characters9340
Distinct characters134
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

Unique308 ?
Unique (%)93.1%

Sample

1st row서울특별시 서대문구 거북골로 35 (남가좌동,(2층))
2nd row서울특별시 서대문구 통일로 107-29 (미근동)
3rd row서울특별시 서대문구 통일로 479 (홍제동,2층)
4th row서울특별시 서대문구 세검정로 51-1 (홍제동)
5th row서울특별시 서대문구 응암로 113 (북가좌동,(3층))
ValueCountFrequency (%)
서울특별시 331
 
19.0%
서대문구 331
 
19.0%
창천동 53
 
3.0%
홍제동 34
 
1.9%
통일로 33
 
1.9%
응암로 26
 
1.5%
남가좌동 26
 
1.5%
거북골로 25
 
1.4%
북가좌동 25
 
1.4%
연세로 20
 
1.1%
Other values (353) 842
48.2%
2024-04-30T04:59:26.513296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1615
 
17.3%
서 667
 
7.1%
대 375
 
4.0%
( 359
 
3.8%
) 359
 
3.8%
시 335
 
3.6%
문 332
 
3.6%
특 331
 
3.5%
별 331
 
3.5%
구 331
 
3.5%
Other values (124) 4305
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5666
60.7%
Space Separator 1615
 
17.3%
Decimal Number 1109
 
11.9%
Open Punctuation 359
 
3.8%
Close Punctuation 359
 
3.8%
Other Punctuation 185
 
2.0%
Dash Punctuation 45
 
0.5%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 667
 
11.8%
대 375
 
6.6%
시 335
 
5.9%
문 332
 
5.9%
특 331
 
5.8%
별 331
 
5.8%
구 331
 
5.8%
울 331
 
5.8%
동 321
 
5.7%
로 301
 
5.3%
Other values (107) 2011
35.5%
Decimal Number
ValueCountFrequency (%)
1 228
20.6%
2 196
17.7%
3 165
14.9%
4 120
10.8%
5 80
 
7.2%
7 74
 
6.7%
0 70
 
6.3%
6 64
 
5.8%
8 56
 
5.0%
9 56
 
5.0%
Space Separator
ValueCountFrequency (%)
1615
100.0%
Open Punctuation
ValueCountFrequency (%)
( 359
100.0%
Close Punctuation
ValueCountFrequency (%)
) 359
100.0%
Other Punctuation
ValueCountFrequency (%)
, 185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5666
60.7%
Common 3673
39.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 667
 
11.8%
대 375
 
6.6%
시 335
 
5.9%
문 332
 
5.9%
특 331
 
5.8%
별 331
 
5.8%
구 331
 
5.8%
울 331
 
5.8%
동 321
 
5.7%
로 301
 
5.3%
Other values (107) 2011
35.5%
Common
ValueCountFrequency (%)
1615
44.0%
( 359
 
9.8%
) 359
 
9.8%
1 228
 
6.2%
2 196
 
5.3%
, 185
 
5.0%
3 165
 
4.5%
4 120
 
3.3%
5 80
 
2.2%
7 74
 
2.0%
Other values (6) 292
 
7.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5666
60.7%
ASCII 3674
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1615
44.0%
( 359
 
9.8%
) 359
 
9.8%
1 228
 
6.2%
2 196
 
5.3%
, 185
 
5.0%
3 165
 
4.5%
4 120
 
3.3%
5 80
 
2.2%
7 74
 
2.0%
Other values (7) 293
 
8.0%
Hangul
ValueCountFrequency (%)
서 667
 
11.8%
대 375
 
6.6%
시 335
 
5.9%
문 332
 
5.9%
특 331
 
5.8%
별 331
 
5.8%
구 331
 
5.8%
울 331
 
5.8%
동 321
 
5.7%
로 301
 
5.3%
Other values (107) 2011
35.5%

도로명우편번호
Text

MISSING 

Distinct46
Distinct (%)68.7%
Missing308
Missing (%)82.1%
Memory size3.1 KiB
2024-04-30T04:59:26.710128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1492537
Min length5

Characters and Unicode

Total characters345
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

Unique28 ?
Unique (%)41.8%

Sample

1st row120-839
2nd row03712
3rd row03681
4th row120050
5th row120834
ValueCountFrequency (%)
03668 4
 
6.0%
120834 3
 
4.5%
03766 2
 
3.0%
03758 2
 
3.0%
03691 2
 
3.0%
03708 2
 
3.0%
03629 2
 
3.0%
03666 2
 
3.0%
03678 2
 
3.0%
03789 2
 
3.0%
Other values (36) 44
65.7%
2024-04-30T04:59:27.056838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 80
23.2%
0 78
22.6%
6 57
16.5%
7 31
 
9.0%
8 26
 
7.5%
2 21
 
6.1%
1 19
 
5.5%
9 12
 
3.5%
5 11
 
3.2%
4 8
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 343
99.4%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 80
23.3%
0 78
22.7%
6 57
16.6%
7 31
 
9.0%
8 26
 
7.6%
2 21
 
6.1%
1 19
 
5.5%
9 12
 
3.5%
5 11
 
3.2%
4 8
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 345
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 80
23.2%
0 78
22.6%
6 57
16.5%
7 31
 
9.0%
8 26
 
7.5%
2 21
 
6.1%
1 19
 
5.5%
9 12
 
3.5%
5 11
 
3.2%
4 8
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 345
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 80
23.2%
0 78
22.6%
6 57
16.5%
7 31
 
9.0%
8 26
 
7.5%
2 21
 
6.1%
1 19
 
5.5%
9 12
 
3.5%
5 11
 
3.2%
4 8
 
2.3%

사업장명
Text

Distinct320
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:27.301296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length4.1973333
Min length1

Characters and Unicode

Total characters1574
Distinct characters297
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

Unique279 ?
Unique (%)74.4%

Sample

1st row정문
2nd row영천
3rd row동아
4th row로타리당구장
5th row한일
ValueCountFrequency (%)
당구장 27
 
6.4%
큐당구장 5
 
1.2%
제일 4
 
1.0%
동아 4
 
1.0%
킹당구장 3
 
0.7%
태양 3
 
0.7%
에이스 3
 
0.7%
승리당구장 3
 
0.7%
sbs당구클럽 3
 
0.7%
당구아카데미 3
 
0.7%
Other values (317) 363
86.2%
2024-04-30T04:59:27.684084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 183
 
11.6%
당 177
 
11.2%
장 146
 
9.3%
46
 
2.9%
클 30
 
1.9%
리 30
 
1.9%
럽 30
 
1.9%
스 29
 
1.8%
아 28
 
1.8%
이 20
 
1.3%
Other values (287) 855
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1402
89.1%
Uppercase Letter 75
 
4.8%
Space Separator 46
 
2.9%
Decimal Number 19
 
1.2%
Other Punctuation 12
 
0.8%
Lowercase Letter 9
 
0.6%
Dash Punctuation 4
 
0.3%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 183
 
13.1%
당 177
 
12.6%
장 146
 
10.4%
클 30
 
2.1%
리 30
 
2.1%
럽 30
 
2.1%
스 29
 
2.1%
아 28
 
2.0%
이 20
 
1.4%
대 17
 
1.2%
Other values (250) 712
50.8%
Uppercase Letter
ValueCountFrequency (%)
B 16
21.3%
S 14
18.7%
O 8
10.7%
K 4
 
5.3%
Q 4
 
5.3%
A 3
 
4.0%
M 3
 
4.0%
Y 3
 
4.0%
J 3
 
4.0%
G 2
 
2.7%
Other values (8) 15
20.0%
Lowercase Letter
ValueCountFrequency (%)
s 2
22.2%
e 2
22.2%
n 2
22.2%
b 1
11.1%
r 1
11.1%
o 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 9
47.4%
0 6
31.6%
1 2
 
10.5%
3 1
 
5.3%
9 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
& 3
 
25.0%
, 1
 
8.3%
Space Separator
ValueCountFrequency (%)
46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1402
89.1%
Common 88
 
5.6%
Latin 84
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 183
 
13.1%
당 177
 
12.6%
장 146
 
10.4%
클 30
 
2.1%
리 30
 
2.1%
럽 30
 
2.1%
스 29
 
2.1%
아 28
 
2.0%
이 20
 
1.4%
대 17
 
1.2%
Other values (250) 712
50.8%
Latin
ValueCountFrequency (%)
B 16
19.0%
S 14
16.7%
O 8
 
9.5%
K 4
 
4.8%
Q 4
 
4.8%
A 3
 
3.6%
M 3
 
3.6%
Y 3
 
3.6%
J 3
 
3.6%
G 2
 
2.4%
Other values (14) 24
28.6%
Common
ValueCountFrequency (%)
46
52.3%
2 9
 
10.2%
. 8
 
9.1%
0 6
 
6.8%
- 4
 
4.5%
( 3
 
3.4%
) 3
 
3.4%
& 3
 
3.4%
1 2
 
2.3%
+ 1
 
1.1%
Other values (3) 3
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1402
89.1%
ASCII 172
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 183
 
13.1%
당 177
 
12.6%
장 146
 
10.4%
클 30
 
2.1%
리 30
 
2.1%
럽 30
 
2.1%
스 29
 
2.1%
아 28
 
2.0%
이 20
 
1.4%
대 17
 
1.2%
Other values (250) 712
50.8%
ASCII
ValueCountFrequency (%)
46
26.7%
B 16
 
9.3%
S 14
 
8.1%
2 9
 
5.2%
O 8
 
4.7%
. 8
 
4.7%
0 6
 
3.5%
- 4
 
2.3%
K 4
 
2.3%
Q 4
 
2.3%
Other values (27) 53
30.8%

최종수정일자
Date

Distinct226
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2003-02-07 11:05:36
Maximum2024-03-29 11:15:18
2024-04-30T04:59:27.974263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:28.081496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
I
289 
U
86 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 289
77.1%
U 86
 
22.9%

Length

2024-04-30T04:59:28.202678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:28.291623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 289
77.1%
u 86
 
22.9%

데이터갱신일자
Date

Distinct61
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:09:00
2024-04-30T04:59:28.386944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:28.504684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct288
Distinct (%)82.5%
Missing26
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean194268.37
Minimum191500.39
Maximum197036.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-30T04:59:28.624234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191500.39
5-th percentile192219.45
Q1193310.57
median194332.05
Q3195070.97
95-th percentile196704.17
Maximum197036.03
Range5535.6412
Interquartile range (IQR)1760.4055

Descriptive statistics

Standard deviation1258.3741
Coefficient of variation (CV)0.0064775037
Kurtosis-0.37921486
Mean194268.37
Median Absolute Deviation (MAD)841.43471
Skewness0.12710164
Sum67799661
Variance1583505.3
MonotonicityNot monotonic
2024-04-30T04:59:28.739670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193318.985896441 4
 
1.1%
192794.825022354 4
 
1.1%
194472.002111027 3
 
0.8%
193388.346589852 3
 
0.8%
194997.451098631 3
 
0.8%
196079.049170663 3
 
0.8%
192042.945252338 3
 
0.8%
195079.145684427 3
 
0.8%
194334.618853084 3
 
0.8%
196578.410812324 3
 
0.8%
Other values (278) 317
84.5%
(Missing) 26
 
6.9%
ValueCountFrequency (%)
191500.393722857 1
 
0.3%
191559.918118738 1
 
0.3%
191586.918506689 1
 
0.3%
191624.443466756 1
 
0.3%
191993.934666673 1
 
0.3%
192008.587379083 1
 
0.3%
192026.493793732 1
 
0.3%
192042.945252338 3
0.8%
192093.826430125 2
0.5%
192110.634545006 1
 
0.3%
ValueCountFrequency (%)
197036.034948766 1
0.3%
197014.335044529 1
0.3%
196912.713362244 1
0.3%
196899.242661444 1
0.3%
196889.992166193 1
0.3%
196884.166631688 1
0.3%
196810.949114639 1
0.3%
196801.661639204 1
0.3%
196794.572693354 1
0.3%
196790.56276047 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct288
Distinct (%)82.5%
Missing26
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean452153.32
Minimum450388.33
Maximum455588.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-30T04:59:28.846227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450388.33
5-th percentile450515.52
Q1450693.86
median451917.13
Q3453261.48
95-th percentile454660.7
Maximum455588.32
Range5199.9877
Interquartile range (IQR)2567.6127

Descriptive statistics

Standard deviation1419.5274
Coefficient of variation (CV)0.0031394824
Kurtosis-1.1804147
Mean452153.32
Median Absolute Deviation (MAD)1248.3247
Skewness0.34178874
Sum1.5780151 × 108
Variance2015058.1
MonotonicityNot monotonic
2024-04-30T04:59:28.971540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452737.01809875 4
 
1.1%
453408.04831086 4
 
1.1%
450687.831429328 3
 
0.8%
453148.533867839 3
 
0.8%
450781.690034297 3
 
0.8%
450605.895857493 3
 
0.8%
452938.509891583 3
 
0.8%
454006.234109041 3
 
0.8%
450650.747799211 3
 
0.8%
451152.160773091 3
 
0.8%
Other values (278) 317
84.5%
(Missing) 26
 
6.9%
ValueCountFrequency (%)
450388.329359668 1
0.3%
450391.53849739 1
0.3%
450425.216941786 1
0.3%
450437.149123163 1
0.3%
450437.88111269 1
0.3%
450448.503514873 1
0.3%
450450.682916715 1
0.3%
450451.593376617 1
0.3%
450456.502909711 1
0.3%
450461.322132758 1
0.3%
ValueCountFrequency (%)
455588.317096857 1
0.3%
455220.88305506 1
0.3%
455193.014698844 2
0.5%
455058.235727032 2
0.5%
454885.429510931 1
0.3%
454864.181287808 2
0.5%
454817.095743814 1
0.3%
454808.0 1
0.3%
454763.633699865 1
0.3%
454692.683753267 2
0.5%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
당구장업
337 
<NA>
38 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 337
89.9%
<NA> 38
 
10.1%

Length

2024-04-30T04:59:29.071600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:29.166401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 337
89.9%
na 38
 
10.1%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
사립
337 
<NA>
38 

Length

Max length4
Median length2
Mean length2.2026667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 337
89.9%
<NA> 38
 
10.1%

Length

2024-04-30T04:59:29.263220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:29.362281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 337
89.9%
na 38
 
10.1%

보험가입여부코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
313 
0
62 

Length

Max length4
Median length4
Mean length3.504
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 313
83.5%
0 62
 
16.5%

Length

2024-04-30T04:59:29.458075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:29.540823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 313
83.5%
0 62
 
16.5%

지도자수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
207 
0
168 

Length

Max length4
Median length4
Mean length2.656
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 207
55.2%
0 168
44.8%

Length

2024-04-30T04:59:29.632344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:29.709943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 207
55.2%
0 168
44.8%

건축물동수
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
188 
0
184 
1
 
3

Length

Max length4
Median length4
Mean length2.504
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 188
50.1%
0 184
49.1%
1 3
 
0.8%

Length

2024-04-30T04:59:29.800501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:29.889718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 188
50.1%
0 184
49.1%
1 3
 
0.8%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)7.9%
Missing184
Missing (%)49.1%
Infinite0
Infinite (%)0.0%
Mean59.789948
Minimum0
Maximum1757.22
Zeros177
Zeros (%)47.2%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-30T04:59:29.964464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile624.165
Maximum1757.22
Range1757.22
Interquartile range (IQR)0

Descriptive statistics

Standard deviation247.47387
Coefficient of variation (CV)4.1390549
Kurtosis23.664551
Mean59.789948
Median Absolute Deviation (MAD)0
Skewness4.7021633
Sum11419.88
Variance61243.319
MonotonicityNot monotonic
2024-04-30T04:59:30.051575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 177
47.2%
661.78 1
 
0.3%
1114.47 1
 
0.3%
64.1 1
 
0.3%
123.97 1
 
0.3%
1757.22 1
 
0.3%
772.28 1
 
0.3%
1635.25 1
 
0.3%
881.2 1
 
0.3%
586.55 1
 
0.3%
Other values (5) 5
 
1.3%
(Missing) 184
49.1%
ValueCountFrequency (%)
0.0 177
47.2%
64.1 1
 
0.3%
123.97 1
 
0.3%
406.0 1
 
0.3%
586.55 1
 
0.3%
661.78 1
 
0.3%
695.52 1
 
0.3%
772.28 1
 
0.3%
787.14 1
 
0.3%
881.2 1
 
0.3%
ValueCountFrequency (%)
1757.22 1
0.3%
1635.25 1
0.3%
1114.47 1
0.3%
995.4 1
0.3%
939.0 1
0.3%
881.2 1
0.3%
787.14 1
0.3%
772.28 1
0.3%
695.52 1
0.3%
661.78 1
0.3%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
373 
0
 
2

Length

Max length4
Median length4
Mean length3.984
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> 373
99.5%
0 2
 
0.5%

Length

2024-04-30T04:59:30.172269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:30.263015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 373
99.5%
0 2
 
0.5%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing375
Missing (%)100.0%
Memory size3.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03120000CDFH330108198900000319891231<NA>3폐업3폐업20050518<NA><NA><NA><NA><NA>120806서울특별시 서대문구 남가좌동 324-30번지 (2층)서울특별시 서대문구 거북골로 35 (남가좌동,(2층))<NA>정문2005-05-18 15:43:23I2018-08-31 23:59:59.0<NA>193210.518647453008.44684당구장업사립0<NA><NA><NA><NA><NA><NA>
13120000CDFH330108199000000119900219<NA>3폐업3폐업19981218<NA><NA><NA><NA><NA>120070서울특별시 서대문구 영천동 320번지<NA><NA>영천2003-02-07 11:05:36I2018-08-31 23:59:59.0<NA>196547.056142452018.498894당구장업사립<NA>000.0<NA><NA><NA>
23120000CDFH330108199000000219901012<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>120020서울특별시 서대문구 미근동 31-13번지서울특별시 서대문구 통일로 107-29 (미근동)<NA>동아2003-02-07 11:05:36I2018-08-31 23:59:59.0<NA>197014.335045451350.816062당구장업사립<NA>000.0<NA><NA><NA>
33120000CDFH330108199000000419900101<NA>1영업/정상13영업중<NA><NA><NA><NA>396-2709<NA>120857서울특별시 서대문구 홍제동 294-50번지 2층서울특별시 서대문구 통일로 479 (홍제동,2층)<NA>로타리당구장2005-07-04 15:50:51I2018-08-31 23:59:59.0<NA>194772.418967454274.642833당구장업사립0<NA><NA><NA><NA><NA><NA>
43120000CDFH330108199100000319910515<NA>3폐업3폐업19991231<NA><NA><NA><NA><NA>120012서울특별시 서대문구 충정로2가 131번지<NA><NA>한일2003-02-07 11:05:36I2018-08-31 23:59:59.0<NA><NA><NA>당구장업사립<NA>000.0<NA><NA><NA>
53120000CDFH330108199100000419910516<NA>3폐업3폐업20000119<NA><NA><NA><NA><NA>120857서울특별시 서대문구 홍제동 266-233번지서울특별시 서대문구 세검정로 51-1 (홍제동)<NA>약속2003-02-07 11:05:36I2018-08-31 23:59:59.0<NA>195237.569772454495.601629당구장업사립<NA>000.0<NA><NA><NA>
63120000CDFH330108199100000519910724<NA>3폐업3폐업20220118<NA><NA><NA><NA><NA>120815서울특별시 서대문구 북가좌동 333-4 (3층)서울특별시 서대문구 응암로 113 (북가좌동,(3층))<NA>대경2022-01-18 13:47:49U2022-01-20 02:40:00.0<NA>192265.483983453388.30242당구장업사립<NA>000.00<NA><NA>
73120000CDFH330108199100000619911018<NA>3폐업3폐업20031126<NA><NA><NA><NA><NA>120838서울특별시 서대문구 충정로3가 128-10번지서울특별시 서대문구 경기대로 36 (충정로3가)<NA>우정2006-04-21 09:47:25I2018-08-31 23:59:59.0<NA>196578.410812451152.160773당구장업사립0<NA><NA><NA><NA><NA><NA>
83120000CDFH330108199100000719911125<NA>3폐업3폐업20010508<NA><NA><NA><NA><NA>120834서울특별시 서대문구 창천동 33-12번지서울특별시 서대문구 연세로 33 (창천동)<NA>상아2003-02-07 11:05:36I2018-08-31 23:59:59.0<NA>194336.396137450703.601033당구장업사립<NA>000.0<NA><NA><NA>
93120000CDFH330108199100000819911224<NA>3폐업3폐업20031229<NA><NA><NA><NA><NA>120819서울특별시 서대문구 북아현동 136-13번지서울특별시 서대문구 신촌로 265 (북아현동)<NA>성공2006-04-21 09:47:49I2018-08-31 23:59:59.0<NA>196008.202406450597.417544당구장업사립0<NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
3653120000CDFH33010820200000022020-04-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 327-2서울특별시 서대문구 응암로 105, 2층 (북가좌동)03678제우스 당구장2024-03-27 10:12:03U2023-12-02 22:09:00.0<NA>192226.158499453330.828953<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3663120000CDFH330108202000000320200423<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 122-4번지 엘리트빌딩서울특별시 서대문구 증가로 17, 엘리트빌딩 3층 (연희동)03703오태준 당구아카데미2020-04-23 21:37:09I2020-04-25 00:23:33.0<NA>193823.087716451944.584267당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3673120000CDFH330108202000000420200619<NA>1영업/정상13영업중<NA><NA><NA><NA>02-374-7800<NA><NA>서울특별시 서대문구 홍제동 330-61번지 경인주유소서울특별시 서대문구 통일로 455, 경인주유소 2층 (홍제동)03636제이스 빌리어드2020-06-19 14:15:51I2020-06-21 00:23:27.0<NA>194941.659192454077.940524당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3683120000CDFH330108202000000520200622<NA>1영업/정상13영업중<NA><NA><NA><NA>02-374-7800<NA><NA>서울특별시 서대문구 북가좌동 307-34번지 선산빌딩서울특별시 서대문구 응암로 61, 선산빌딩 2층 (북가좌동)03681현대당구장2020-06-22 20:06:46I2020-06-24 00:23:17.0<NA>191993.934667452947.074164당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3693120000CDFH330108202100000120210510<NA>1영업/정상13영업중<NA><NA><NA><NA>02-395-5958<NA><NA>서울특별시 서대문구 홍은동 426 연희127빌딩서울특별시 서대문구 연희로 286, 연희127빌딩 6층 (홍은동)03653최프로 빌리아드 클럽2021-05-10 09:40:00I2021-05-12 00:23:08.0<NA>194321.960265453368.123327당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3703120000CDFH330108202100000220211103<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 176-4서울특별시 서대문구 통일로 428, 지하1층 (홍제동)03630비바체2021-11-03 15:27:27I2021-11-05 00:22:45.0<NA>195166.648274453916.211199당구장업사립<NA>000.00<NA><NA>
3713120000CDFH330108202200000120220523<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 139-3 신양빌딩서울특별시 서대문구 통일로 408, 신양빌딩 2층 (홍제동)03632왕실당구장2022-05-23 16:09:04I2021-12-04 22:05:00.0<NA>195297.115525453758.055554<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3723120000CDFH33010820220000022022-06-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 306-20서울특별시 서대문구 응암로 64, 지층 (북가좌동)03691구슬당구장2024-03-29 11:15:18U2023-12-02 21:01:00.0<NA>192042.945252452938.509892<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3733120000CDFH33010820230000012023-06-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 188-3서울특별시 서대문구 연희로 95, 지하 1층 (연희동)03708아깝숑 당구장2023-06-28 10:20:43I2022-12-05 21:00:00.0<NA>193781.255306451595.122645<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3743120000CDFH33010820230000022023-11-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 719-17서울특별시 서대문구 홍연길 91, 2층 (연희동)03696연세당구장2023-11-14 17:56:17I2022-10-31 23:06:00.0<NA>193874.101692452744.934101<NA><NA><NA><NA><NA><NA><NA><NA><NA>