Overview

Dataset statistics

Number of variables34
Number of observations177
Missing cells1404
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.4 KiB
Average record size in memory291.7 B

Variable types

Categorical14
Text6
DateTime4
Unsupported6
Numeric4

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-19591/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (95.0%)Imbalance
휴업종료일자 is highly imbalanced (95.0%)Imbalance
지도자수 is highly imbalanced (63.5%)Imbalance
회원모집총인원 is highly imbalanced (95.0%)Imbalance
인허가취소일자 has 177 (100.0%) missing valuesMissing
폐업일자 has 60 (33.9%) missing valuesMissing
재개업일자 has 177 (100.0%) missing valuesMissing
전화번호 has 72 (40.7%) missing valuesMissing
소재지면적 has 177 (100.0%) missing valuesMissing
소재지우편번호 has 28 (15.8%) missing valuesMissing
도로명주소 has 4 (2.3%) missing valuesMissing
도로명우편번호 has 59 (33.3%) missing valuesMissing
업태구분명 has 177 (100.0%) missing valuesMissing
좌표정보(X) has 3 (1.7%) missing valuesMissing
좌표정보(Y) has 3 (1.7%) missing valuesMissing
건축물연면적 has 113 (63.8%) missing valuesMissing
세부업종명 has 177 (100.0%) missing valuesMissing
법인명 has 177 (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 19 (10.7%) zerosZeros

Reproduction

Analysis started2024-05-11 03:16:05.398142
Analysis finished2024-05-11 03:16:06.632560
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3140000
177 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 177
100.0%

Length

2024-05-11T03:16:06.754453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:06.939269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 177
100.0%

관리번호
Text

UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T03:16:07.264358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters3540
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

Unique177 ?
Unique (%)100.0%

Sample

1st rowCDFH3301051993000001
2nd rowCDFH3301051993000002
3rd rowCDFH3301051993000003
4th rowCDFH3301051993000004
5th rowCDFH3301051993000005
ValueCountFrequency (%)
cdfh3301051993000001 1
 
0.6%
cdfh3301052007000004 1
 
0.6%
cdfh3301052009000004 1
 
0.6%
cdfh3301052008000014 1
 
0.6%
cdfh3301052008000015 1
 
0.6%
cdfh3301052008000016 1
 
0.6%
cdfh3301052008000017 1
 
0.6%
cdfh3301052008000018 1
 
0.6%
cdfh3301052009000001 1
 
0.6%
cdfh3301052009000002 1
 
0.6%
Other values (167) 167
94.4%
2024-05-11T03:16:07.855242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1491
42.1%
3 400
 
11.3%
1 336
 
9.5%
5 204
 
5.8%
2 194
 
5.5%
C 177
 
5.0%
D 177
 
5.0%
F 177
 
5.0%
H 177
 
5.0%
9 79
 
2.2%
Other values (4) 128
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2832
80.0%
Uppercase Letter 708
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1491
52.6%
3 400
 
14.1%
1 336
 
11.9%
5 204
 
7.2%
2 194
 
6.9%
9 79
 
2.8%
4 35
 
1.2%
7 35
 
1.2%
8 30
 
1.1%
6 28
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 177
25.0%
D 177
25.0%
F 177
25.0%
H 177
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2832
80.0%
Latin 708
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1491
52.6%
3 400
 
14.1%
1 336
 
11.9%
5 204
 
7.2%
2 194
 
6.9%
9 79
 
2.8%
4 35
 
1.2%
7 35
 
1.2%
8 30
 
1.1%
6 28
 
1.0%
Latin
ValueCountFrequency (%)
C 177
25.0%
D 177
25.0%
F 177
25.0%
H 177
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3540
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1491
42.1%
3 400
 
11.3%
1 336
 
9.5%
5 204
 
5.8%
2 194
 
5.5%
C 177
 
5.0%
D 177
 
5.0%
F 177
 
5.0%
H 177
 
5.0%
9 79
 
2.2%
Other values (4) 128
 
3.6%

인허가일자
Date

Distinct173
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1993-01-27 00:00:00
Maximum2023-12-18 00:00:00
2024-05-11T03:16:08.432145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:16:08.844217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
86 
1
59 
4
31 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
3 86
48.6%
1 59
33.3%
4 31
 
17.5%
2 1
 
0.6%

Length

2024-05-11T03:16:09.144520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:09.489661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 86
48.6%
1 59
33.3%
4 31
 
17.5%
2 1
 
0.6%

영업상태명
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
86 
영업/정상
59 
취소/말소/만료/정지/중지
31 
휴업
 
1

Length

Max length14
Median length5
Mean length5.1016949
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 86
48.6%
영업/정상 59
33.3%
취소/말소/만료/정지/중지 31
 
17.5%
휴업 1
 
0.6%

Length

2024-05-11T03:16:09.894035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:10.249403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 86
48.6%
영업/정상 59
33.3%
취소/말소/만료/정지/중지 31
 
17.5%
휴업 1
 
0.6%

상세영업상태코드
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
86 
13
59 
35
31 
2
 
1

Length

Max length2
Median length2
Mean length1.5084746
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
3 86
48.6%
13 59
33.3%
35 31
 
17.5%
2 1
 
0.6%

Length

2024-05-11T03:16:10.636142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:10.982297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 86
48.6%
13 59
33.3%
35 31
 
17.5%
2 1
 
0.6%

상세영업상태명
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
86 
영업중
59 
직권말소
31 
휴업
 
1

Length

Max length4
Median length3
Mean length2.6836158
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 86
48.6%
영업중 59
33.3%
직권말소 31
 
17.5%
휴업 1
 
0.6%

Length

2024-05-11T03:16:11.331699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:11.681227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 86
48.6%
영업중 59
33.3%
직권말소 31
 
17.5%
휴업 1
 
0.6%

폐업일자
Date

MISSING 

Distinct89
Distinct (%)76.1%
Missing60
Missing (%)33.9%
Memory size1.5 KiB
Minimum1998-01-15 00:00:00
Maximum2023-11-30 00:00:00
2024-05-11T03:16:12.167486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:16:12.625451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
176 
20221226
 
1

Length

Max length8
Median length4
Mean length4.0225989
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
99.4%
20221226 1
 
0.6%

Length

2024-05-11T03:16:13.477678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:14.248345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
99.4%
20221226 1
 
0.6%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
176 
20230630
 
1

Length

Max length8
Median length4
Mean length4.0225989
Min length4

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
99.4%
20230630 1
 
0.6%

Length

2024-05-11T03:16:14.899858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:15.374642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
99.4%
20230630 1
 
0.6%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct97
Distinct (%)92.4%
Missing72
Missing (%)40.7%
Memory size1.5 KiB
2024-05-11T03:16:16.454421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.6761905
Min length8

Characters and Unicode

Total characters1016
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

Unique90 ?
Unique (%)85.7%

Sample

1st row02-2606-4477
2nd row2655-0770
3rd row2649-5032
4th row2697-3821
5th row2602-3220
ValueCountFrequency (%)
2693-0020 3
 
2.9%
2065-7272 2
 
1.9%
2643-0753 2
 
1.9%
2696-7979 2
 
1.9%
02-2653-9691 2
 
1.9%
2649-3080 2
 
1.9%
2602-3220 2
 
1.9%
02-2606-4477 1
 
1.0%
2642-0753 1
 
1.0%
2646-9075 1
 
1.0%
Other values (87) 87
82.9%
2024-05-11T03:16:17.803433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 202
19.9%
6 136
13.4%
- 124
12.2%
0 124
12.2%
7 83
8.2%
9 64
 
6.3%
4 64
 
6.3%
1 62
 
6.1%
5 60
 
5.9%
8 49
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 892
87.8%
Dash Punctuation 124
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 202
22.6%
6 136
15.2%
0 124
13.9%
7 83
9.3%
9 64
 
7.2%
4 64
 
7.2%
1 62
 
7.0%
5 60
 
6.7%
8 49
 
5.5%
3 48
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 202
19.9%
6 136
13.4%
- 124
12.2%
0 124
12.2%
7 83
8.2%
9 64
 
6.3%
4 64
 
6.3%
1 62
 
6.1%
5 60
 
5.9%
8 49
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 202
19.9%
6 136
13.4%
- 124
12.2%
0 124
12.2%
7 83
8.2%
9 64
 
6.3%
4 64
 
6.3%
1 62
 
6.1%
5 60
 
5.9%
8 49
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

소재지우편번호
Text

MISSING 

Distinct60
Distinct (%)40.3%
Missing28
Missing (%)15.8%
Memory size1.5 KiB
2024-05-11T03:16:18.431734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0536913
Min length6

Characters and Unicode

Total characters902
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

Unique29 ?
Unique (%)19.5%

Sample

1st row158-863
2nd row158818
3rd row158864
4th row158861
5th row158817
ValueCountFrequency (%)
158050 12
 
8.1%
158070 10
 
6.7%
158806 7
 
4.7%
158852 7
 
4.7%
158811 6
 
4.0%
158849 5
 
3.4%
158861 5
 
3.4%
158860 5
 
3.4%
158051 4
 
2.7%
158808 4
 
2.7%
Other values (50) 84
56.4%
2024-05-11T03:16:19.672696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 268
29.7%
1 192
21.3%
5 191
21.2%
0 86
 
9.5%
6 33
 
3.7%
7 32
 
3.5%
2 30
 
3.3%
4 30
 
3.3%
9 19
 
2.1%
3 13
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 894
99.1%
Dash Punctuation 8
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 268
30.0%
1 192
21.5%
5 191
21.4%
0 86
 
9.6%
6 33
 
3.7%
7 32
 
3.6%
2 30
 
3.4%
4 30
 
3.4%
9 19
 
2.1%
3 13
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 902
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 268
29.7%
1 192
21.3%
5 191
21.2%
0 86
 
9.5%
6 33
 
3.7%
7 32
 
3.5%
2 30
 
3.3%
4 30
 
3.3%
9 19
 
2.1%
3 13
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 268
29.7%
1 192
21.3%
5 191
21.2%
0 86
 
9.5%
6 33
 
3.7%
7 32
 
3.5%
2 30
 
3.3%
4 30
 
3.3%
9 19
 
2.1%
3 13
 
1.4%

지번주소
Text

Distinct167
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T03:16:20.321452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length44
Mean length27.463277
Min length18

Characters and Unicode

Total characters4861
Distinct characters144
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

Unique157 ?
Unique (%)88.7%

Sample

1st row서울특별시 양천구 신정동 1147-11
2nd row서울특별시 양천구 목동 773-3번지 지층
3rd row서울특별시 양천구 신정동 1182-11번지
4th row서울특별시 양천구 신정동 1023-12번지
5th row서울특별시 양천구 목동 762-6번지
ValueCountFrequency (%)
양천구 180
20.0%
서울특별시 177
19.7%
목동 75
 
8.3%
신정동 72
 
8.0%
신월동 31
 
3.4%
지층 14
 
1.6%
지하1층 14
 
1.6%
2층 7
 
0.8%
지하 6
 
0.7%
3층 5
 
0.6%
Other values (260) 318
35.4%
2024-05-11T03:16:21.657854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
867
 
17.8%
1 257
 
5.3%
동 203
 
4.2%
지 191
 
3.9%
천 180
 
3.7%
구 180
 
3.7%
서 180
 
3.7%
양 180
 
3.7%
시 179
 
3.7%
울 179
 
3.7%
Other values (134) 2265
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2774
57.1%
Decimal Number 1018
 
20.9%
Space Separator 867
 
17.8%
Dash Punctuation 162
 
3.3%
Uppercase Letter 13
 
0.3%
Other Punctuation 11
 
0.2%
Math Symbol 8
 
0.2%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 203
 
7.3%
지 191
 
6.9%
천 180
 
6.5%
구 180
 
6.5%
서 180
 
6.5%
양 180
 
6.5%
시 179
 
6.5%
울 179
 
6.5%
별 177
 
6.4%
특 177
 
6.4%
Other values (112) 948
34.2%
Decimal Number
ValueCountFrequency (%)
1 257
25.2%
2 146
14.3%
0 126
12.4%
3 84
 
8.3%
9 82
 
8.1%
5 81
 
8.0%
4 73
 
7.2%
7 67
 
6.6%
6 51
 
5.0%
8 51
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 9
69.2%
D 2
 
15.4%
E 1
 
7.7%
A 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
/ 2
 
18.2%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
867
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 162
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2774
57.1%
Common 2074
42.7%
Latin 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 203
 
7.3%
지 191
 
6.9%
천 180
 
6.5%
구 180
 
6.5%
서 180
 
6.5%
양 180
 
6.5%
시 179
 
6.5%
울 179
 
6.5%
별 177
 
6.4%
특 177
 
6.4%
Other values (112) 948
34.2%
Common
ValueCountFrequency (%)
867
41.8%
1 257
 
12.4%
- 162
 
7.8%
2 146
 
7.0%
0 126
 
6.1%
3 84
 
4.1%
9 82
 
4.0%
5 81
 
3.9%
4 73
 
3.5%
7 67
 
3.2%
Other values (8) 129
 
6.2%
Latin
ValueCountFrequency (%)
B 9
69.2%
D 2
 
15.4%
E 1
 
7.7%
A 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2774
57.1%
ASCII 2087
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
867
41.5%
1 257
 
12.3%
- 162
 
7.8%
2 146
 
7.0%
0 126
 
6.0%
3 84
 
4.0%
9 82
 
3.9%
5 81
 
3.9%
4 73
 
3.5%
7 67
 
3.2%
Other values (12) 142
 
6.8%
Hangul
ValueCountFrequency (%)
동 203
 
7.3%
지 191
 
6.9%
천 180
 
6.5%
구 180
 
6.5%
서 180
 
6.5%
양 180
 
6.5%
시 179
 
6.5%
울 179
 
6.5%
별 177
 
6.4%
특 177
 
6.4%
Other values (112) 948
34.2%

도로명주소
Text

MISSING 

Distinct169
Distinct (%)97.7%
Missing4
Missing (%)2.3%
Memory size1.5 KiB
2024-05-11T03:16:22.554659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46
Mean length31.271676
Min length22

Characters and Unicode

Total characters5410
Distinct characters166
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

Unique165 ?
Unique (%)95.4%

Sample

1st row서울특별시 양천구 중앙로 217 (신정동)
2nd row서울특별시 양천구 목동중앙로 43 (목동,지층)
3rd row서울특별시 양천구 중앙로 237 (신정동)
4th row서울특별시 양천구 은행정로 5 (신정동)
5th row서울특별시 양천구 목동중앙로 71 (목동)
ValueCountFrequency (%)
양천구 174
 
17.2%
서울특별시 173
 
17.1%
신정동 45
 
4.5%
목동 36
 
3.6%
신월로 19
 
1.9%
신월동 19
 
1.9%
목동서로 19
 
1.9%
지층 16
 
1.6%
오목로 16
 
1.6%
지하1층 15
 
1.5%
Other values (305) 479
47.4%
2024-05-11T03:16:23.942403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
914
 
16.9%
동 290
 
5.4%
서 200
 
3.7%
1 194
 
3.6%
목 186
 
3.4%
로 178
 
3.3%
양 177
 
3.3%
천 177
 
3.3%
구 176
 
3.3%
) 176
 
3.3%
Other values (156) 2742
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3200
59.1%
Space Separator 914
 
16.9%
Decimal Number 747
 
13.8%
Close Punctuation 176
 
3.3%
Open Punctuation 176
 
3.3%
Other Punctuation 160
 
3.0%
Uppercase Letter 16
 
0.3%
Dash Punctuation 13
 
0.2%
Math Symbol 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 290
 
9.1%
서 200
 
6.2%
목 186
 
5.8%
로 178
 
5.6%
양 177
 
5.5%
천 177
 
5.5%
구 176
 
5.5%
울 175
 
5.5%
시 175
 
5.5%
별 173
 
5.4%
Other values (135) 1293
40.4%
Decimal Number
ValueCountFrequency (%)
1 194
26.0%
2 105
14.1%
3 92
12.3%
0 78
10.4%
4 60
 
8.0%
5 54
 
7.2%
9 47
 
6.3%
7 42
 
5.6%
6 39
 
5.2%
8 36
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
75.0%
D 2
 
12.5%
E 1
 
6.2%
A 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 158
98.8%
/ 2
 
1.2%
Space Separator
ValueCountFrequency (%)
914
100.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3200
59.1%
Common 2194
40.6%
Latin 16
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 290
 
9.1%
서 200
 
6.2%
목 186
 
5.8%
로 178
 
5.6%
양 177
 
5.5%
천 177
 
5.5%
구 176
 
5.5%
울 175
 
5.5%
시 175
 
5.5%
별 173
 
5.4%
Other values (135) 1293
40.4%
Common
ValueCountFrequency (%)
914
41.7%
1 194
 
8.8%
) 176
 
8.0%
( 176
 
8.0%
, 158
 
7.2%
2 105
 
4.8%
3 92
 
4.2%
0 78
 
3.6%
4 60
 
2.7%
5 54
 
2.5%
Other values (7) 187
 
8.5%
Latin
ValueCountFrequency (%)
B 12
75.0%
D 2
 
12.5%
E 1
 
6.2%
A 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3200
59.1%
ASCII 2210
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
914
41.4%
1 194
 
8.8%
) 176
 
8.0%
( 176
 
8.0%
, 158
 
7.1%
2 105
 
4.8%
3 92
 
4.2%
0 78
 
3.5%
4 60
 
2.7%
5 54
 
2.4%
Other values (11) 203
 
9.2%
Hangul
ValueCountFrequency (%)
동 290
 
9.1%
서 200
 
6.2%
목 186
 
5.8%
로 178
 
5.6%
양 177
 
5.5%
천 177
 
5.5%
구 176
 
5.5%
울 175
 
5.5%
시 175
 
5.5%
별 173
 
5.4%
Other values (135) 1293
40.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)59.3%
Missing59
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean10557.407
Minimum7903
Maximum158859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T03:16:24.519926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7903
5-th percentile7909.85
Q17962
median8001
Q38031
95-th percentile8098.3
Maximum158859
Range150956
Interquartile range (IQR)69

Descriptive statistics

Standard deviation19555.408
Coefficient of variation (CV)1.8522928
Kurtosis56.42969
Mean10557.407
Median Absolute Deviation (MAD)38
Skewness7.581091
Sum1245774
Variance3.82414 × 108
MonotonicityNot monotonic
2024-05-11T03:16:25.288895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7938 4
 
2.3%
8017 4
 
2.3%
7946 4
 
2.3%
7993 4
 
2.3%
7988 3
 
1.7%
8001 3
 
1.7%
8028 3
 
1.7%
8011 3
 
1.7%
8086 3
 
1.7%
8077 3
 
1.7%
Other values (60) 84
47.5%
(Missing) 59
33.3%
ValueCountFrequency (%)
7903 2
1.1%
7904 3
1.7%
7909 1
 
0.6%
7910 2
1.1%
7915 1
 
0.6%
7925 2
1.1%
7938 4
2.3%
7945 1
 
0.6%
7946 4
2.3%
7947 2
1.1%
ValueCountFrequency (%)
158859 1
0.6%
158849 1
0.6%
8106 1
0.6%
8104 1
0.6%
8100 2
1.1%
8098 1
0.6%
8095 1
0.6%
8093 2
1.1%
8092 1
0.6%
8087 2
1.1%

사업장명
Text

Distinct165
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-05-11T03:16:26.515645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.9774011
Min length3

Characters and Unicode

Total characters1412
Distinct characters218
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

Unique156 ?
Unique (%)88.1%

Sample

1st row목동골프타운
2nd row88실내골프장
3rd rowNGF 골프스쿨
4th row에벤에셀골프연습장
5th row인더스트리골프스쿨
ValueCountFrequency (%)
스크린골프 14
 
5.7%
골프스쿨 5
 
2.0%
골프연습장 5
 
2.0%
아카데미 4
 
1.6%
스크린 4
 
1.6%
골프 4
 
1.6%
골프아카데미 4
 
1.6%
휘트니스 3
 
1.2%
실내골프연습장 3
 
1.2%
트라팰리스 3
 
1.2%
Other values (176) 195
79.9%
2024-05-11T03:16:28.306537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
프 157
 
11.1%
골 153
 
10.8%
스 112
 
7.9%
67
 
4.7%
린 52
 
3.7%
크 51
 
3.6%
아 30
 
2.1%
카 27
 
1.9%
동 26
 
1.8%
미 26
 
1.8%
Other values (208) 711
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1214
86.0%
Space Separator 67
 
4.7%
Uppercase Letter 66
 
4.7%
Lowercase Letter 38
 
2.7%
Decimal Number 17
 
1.2%
Other Punctuation 7
 
0.5%
Dash Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
프 157
 
12.9%
골 153
 
12.6%
스 112
 
9.2%
린 52
 
4.3%
크 51
 
4.2%
아 30
 
2.5%
카 27
 
2.2%
동 26
 
2.1%
미 26
 
2.1%
장 25
 
2.1%
Other values (156) 555
45.7%
Uppercase Letter
ValueCountFrequency (%)
S 8
12.1%
M 7
 
10.6%
K 6
 
9.1%
J 5
 
7.6%
G 5
 
7.6%
B 4
 
6.1%
D 4
 
6.1%
E 3
 
4.5%
A 3
 
4.5%
N 3
 
4.5%
Other values (11) 18
27.3%
Lowercase Letter
ValueCountFrequency (%)
o 5
13.2%
s 5
13.2%
f 3
 
7.9%
l 3
 
7.9%
c 3
 
7.9%
a 3
 
7.9%
k 2
 
5.3%
e 2
 
5.3%
h 2
 
5.3%
r 2
 
5.3%
Other values (7) 8
21.1%
Decimal Number
ValueCountFrequency (%)
1 4
23.5%
0 3
17.6%
2 2
11.8%
5 2
11.8%
4 2
11.8%
8 2
11.8%
6 1
 
5.9%
3 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
& 2
 
28.6%
Space Separator
ValueCountFrequency (%)
67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1214
86.0%
Latin 104
 
7.4%
Common 94
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
프 157
 
12.9%
골 153
 
12.6%
스 112
 
9.2%
린 52
 
4.3%
크 51
 
4.2%
아 30
 
2.5%
카 27
 
2.2%
동 26
 
2.1%
미 26
 
2.1%
장 25
 
2.1%
Other values (156) 555
45.7%
Latin
ValueCountFrequency (%)
S 8
 
7.7%
M 7
 
6.7%
K 6
 
5.8%
J 5
 
4.8%
o 5
 
4.8%
s 5
 
4.8%
G 5
 
4.8%
B 4
 
3.8%
D 4
 
3.8%
f 3
 
2.9%
Other values (28) 52
50.0%
Common
ValueCountFrequency (%)
67
71.3%
. 5
 
5.3%
1 4
 
4.3%
0 3
 
3.2%
2 2
 
2.1%
& 2
 
2.1%
5 2
 
2.1%
4 2
 
2.1%
8 2
 
2.1%
6 1
 
1.1%
Other values (4) 4
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1214
86.0%
ASCII 198
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
프 157
 
12.9%
골 153
 
12.6%
스 112
 
9.2%
린 52
 
4.3%
크 51
 
4.2%
아 30
 
2.5%
카 27
 
2.2%
동 26
 
2.1%
미 26
 
2.1%
장 25
 
2.1%
Other values (156) 555
45.7%
ASCII
ValueCountFrequency (%)
67
33.8%
S 8
 
4.0%
M 7
 
3.5%
K 6
 
3.0%
J 5
 
2.5%
o 5
 
2.5%
. 5
 
2.5%
s 5
 
2.5%
G 5
 
2.5%
B 4
 
2.0%
Other values (42) 81
40.9%

최종수정일자
Date

Distinct169
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2002-10-22 17:59:13
Maximum2024-04-08 17:17:05
2024-05-11T03:16:28.824190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:16:29.507182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
I
92 
U
85 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 92
52.0%
U 85
48.0%

Length

2024-05-11T03:16:29.913909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:30.265386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 92
52.0%
u 85
48.0%

데이터갱신일자
Date

Distinct56
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-11T03:16:30.627734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:16:31.051399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)77.6%
Missing3
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean187702.79
Minimum184413.38
Maximum189709.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T03:16:31.511516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184413.38
5-th percentile185066.84
Q1187078.94
median188008.81
Q3188571.14
95-th percentile189130.99
Maximum189709.8
Range5296.4197
Interquartile range (IQR)1492.1964

Descriptive statistics

Standard deviation1248.8782
Coefficient of variation (CV)0.006653488
Kurtosis-0.025012229
Mean187702.79
Median Absolute Deviation (MAD)592.15491
Skewness-0.96301379
Sum32660285
Variance1559696.9
MonotonicityNot monotonic
2024-05-11T03:16:32.016870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187520.306766633 4
 
2.3%
188571.139279196 4
 
2.3%
185566.058732924 3
 
1.7%
186127.16386564 3
 
1.7%
188904.571764159 3
 
1.7%
186908.412208034 2
 
1.1%
187907.527120319 2
 
1.1%
187978.068877411 2
 
1.1%
187518.093591416 2
 
1.1%
186404.624501079 2
 
1.1%
Other values (125) 147
83.1%
(Missing) 3
 
1.7%
ValueCountFrequency (%)
184413.383829302 1
0.6%
184546.86779406 2
1.1%
184806.911534822 1
0.6%
184896.641861544 1
0.6%
184898.574463951 1
0.6%
184941.672625889 1
0.6%
184973.69813136 1
0.6%
184985.026958259 1
0.6%
185110.894254328 1
0.6%
185170.791174761 1
0.6%
ValueCountFrequency (%)
189709.803505321 1
0.6%
189519.862506193 1
0.6%
189469.901305589 1
0.6%
189389.386306442 1
0.6%
189280.689807363 1
0.6%
189266.403688297 1
0.6%
189197.506088261 2
1.1%
189151.208015925 1
0.6%
189120.105048448 1
0.6%
189086.756192965 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct135
Distinct (%)77.6%
Missing3
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean447205.43
Minimum445197.2
Maximum449789.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T03:16:32.704548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445197.2
5-th percentile445620.56
Q1446275.32
median446904.57
Q3448133.31
95-th percentile449408.1
Maximum449789.61
Range4592.4148
Interquartile range (IQR)1857.9858

Descriptive statistics

Standard deviation1157.9331
Coefficient of variation (CV)0.0025892644
Kurtosis-0.61134973
Mean447205.43
Median Absolute Deviation (MAD)773.88456
Skewness0.60844477
Sum77813745
Variance1340809.1
MonotonicityNot monotonic
2024-05-11T03:16:33.255378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446450.347274241 4
 
2.3%
446130.682286882 4
 
2.3%
446070.262510721 3
 
1.7%
446341.584936103 3
 
1.7%
446861.525362878 3
 
1.7%
446899.767782806 2
 
1.1%
448520.184730399 2
 
1.1%
447379.54998456 2
 
1.1%
445920.374891605 2
 
1.1%
446729.087344494 2
 
1.1%
Other values (125) 147
83.1%
(Missing) 3
 
1.7%
ValueCountFrequency (%)
445197.198550791 1
0.6%
445478.395298097 2
1.1%
445479.209299057 1
0.6%
445546.556343923 1
0.6%
445569.639465968 1
0.6%
445597.867304429 1
0.6%
445613.501447784 2
1.1%
445624.366466149 1
0.6%
445768.146016485 2
1.1%
445876.969798744 1
0.6%
ValueCountFrequency (%)
449789.613381329 1
0.6%
449783.451870726 1
0.6%
449701.802558519 1
0.6%
449677.36412672 1
0.6%
449649.016215774 1
0.6%
449596.304559134 1
0.6%
449463.118569169 1
0.6%
449409.143621821 2
1.1%
449407.537608866 1
0.6%
449399.489126654 1
0.6%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
골프연습장업
157 
<NA>
20 

Length

Max length6
Median length6
Mean length5.7740113
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 157
88.7%
<NA> 20
 
11.3%

Length

2024-05-11T03:16:33.769574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:34.214527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 157
88.7%
na 20
 
11.3%

공사립구분명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
사립
157 
<NA>
20 

Length

Max length4
Median length2
Mean length2.2259887
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 157
88.7%
<NA> 20
 
11.3%

Length

2024-05-11T03:16:34.999739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:35.461140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 157
88.7%
na 20
 
11.3%

보험가입여부코드
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
129 
0
48 

Length

Max length4
Median length4
Mean length3.1864407
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
72.9%
0 48
 
27.1%

Length

2024-05-11T03:16:36.061503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:36.675157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
72.9%
0 48
 
27.1%

지도자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
156 
0
19 
1
 
2

Length

Max length4
Median length4
Mean length3.6440678
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 156
88.1%
0 19
 
10.7%
1 2
 
1.1%

Length

2024-05-11T03:16:37.141590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:37.550254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 156
88.1%
0 19
 
10.7%
1 2
 
1.1%

건축물동수
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
146 
0
20 
1
 
11

Length

Max length4
Median length4
Mean length3.4745763
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 146
82.5%
0 20
 
11.3%
1 11
 
6.2%

Length

2024-05-11T03:16:38.010747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:38.518912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
82.5%
0 20
 
11.3%
1 11
 
6.2%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct46
Distinct (%)71.9%
Missing113
Missing (%)63.8%
Infinite0
Infinite (%)0.0%
Mean1847.5002
Minimum0
Maximum59209
Zeros19
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T03:16:38.889466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median251.25
Q3400.175
95-th percentile3685.564
Maximum59209
Range59209
Interquartile range (IQR)400.175

Descriptive statistics

Standard deviation7930.9557
Coefficient of variation (CV)4.2928038
Kurtosis45.378393
Mean1847.5002
Median Absolute Deviation (MAD)245.9
Skewness6.4917206
Sum118240.01
Variance62900058
MonotonicityNot monotonic
2024-05-11T03:16:39.334198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.0 19
 
10.7%
383.0 1
 
0.6%
412.7 1
 
0.6%
119.9 1
 
0.6%
287.98 1
 
0.6%
339.7 1
 
0.6%
195.5 1
 
0.6%
184.08 1
 
0.6%
875.0 1
 
0.6%
3737.59 1
 
0.6%
Other values (36) 36
 
20.3%
(Missing) 113
63.8%
ValueCountFrequency (%)
0.0 19
10.7%
45.0 1
 
0.6%
91.96 1
 
0.6%
119.9 1
 
0.6%
136.0 1
 
0.6%
165.0 1
 
0.6%
184.08 1
 
0.6%
195.5 1
 
0.6%
198.0 1
 
0.6%
202.0 1
 
0.6%
ValueCountFrequency (%)
59209.0 1
0.6%
21681.0 1
0.6%
12895.2 1
0.6%
3737.59 1
0.6%
3390.75 1
0.6%
2076.79 1
0.6%
1360.27 1
0.6%
1081.0 1
0.6%
997.6 1
0.6%
875.6 1
0.6%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
176 
0
 
1

Length

Max length4
Median length4
Mean length3.9830508
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 176
99.4%
0 1
 
0.6%

Length

2024-05-11T03:16:39.831152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:16:40.272070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 176
99.4%
0 1
 
0.6%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing177
Missing (%)100.0%
Memory size1.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03140000CDFH33010519930000011993-01-27<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2606-4477<NA>158-863서울특별시 양천구 신정동 1147-11서울특별시 양천구 중앙로 217 (신정동)8077목동골프타운2024-04-08 17:17:05U2023-12-03 23:00:00.0<NA>187060.885933445963.585047<NA><NA><NA><NA><NA><NA><NA><NA><NA>
13140000CDFH330105199300000219930205<NA>3폐업3폐업20011218<NA><NA><NA><NA><NA>158818서울특별시 양천구 목동 773-3번지 지층서울특별시 양천구 목동중앙로 43 (목동,지층)<NA>88실내골프장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188394.976615447929.348133골프연습장업사립<NA>000.0<NA><NA><NA>
23140000CDFH330105199300000319930208<NA>3폐업3폐업20021213<NA><NA><NA><NA><NA>158864서울특별시 양천구 신정동 1182-11번지서울특별시 양천구 중앙로 237 (신정동)<NA>NGF 골프스쿨2002-12-13 16:38:39I2018-08-31 23:59:59.0<NA>186990.070415446176.810389골프연습장업사립0<NA><NA>255.0<NA><NA><NA>
33140000CDFH330105199300000419930412<NA>3폐업3폐업20000411<NA><NA><NA><NA><NA>158861서울특별시 양천구 신정동 1023-12번지서울특별시 양천구 은행정로 5 (신정동)<NA>에벤에셀골프연습장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>187520.306767446450.347274골프연습장업사립<NA>000.0<NA><NA><NA>
43140000CDFH330105199300000519930924<NA>3폐업3폐업20170522<NA><NA><NA>2655-0770<NA>158817서울특별시 양천구 목동 762-6번지서울특별시 양천구 목동중앙로 71 (목동)7961인더스트리골프스쿨2017-05-23 16:31:37I2018-08-31 23:59:59.0<NA>188454.414944448208.039743골프연습장업사립0<NA><NA>383.0<NA><NA><NA>
53140000CDFH330105199400000119940302<NA>3폐업3폐업20010120<NA><NA><NA><NA><NA>158806서울특별시 양천구 목동 405-70번지서울특별시 양천구 오목로54길 8 (목동)<NA>경인실내골프2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188713.039137446880.929734골프연습장업사립<NA>000.0<NA><NA><NA>
63140000CDFH330105199400000219940318<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA>2649-5032<NA>158808서울특별시 양천구 목동 516번지서울특별시 양천구 공항대로 646 (목동)7968슈퍼100골프스쿨2019-08-06 17:45:57U2019-08-08 02:40:00.0<NA>189038.037681449399.489127골프연습장업사립<NA><NA><NA>382.51<NA><NA><NA>
73140000CDFH330105199400000319940610<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA>2697-3821<NA>158840서울특별시 양천구 신월동 547-10번지서울특별시 양천구 남부순환로 577 (신월동)8032삼공스코어게임골프2019-08-06 19:25:47U2019-08-08 02:40:00.0<NA>185762.865323446144.142326골프연습장업사립<NA><NA><NA>262.16<NA><NA><NA>
83140000CDFH330105199400000419940701<NA>3폐업3폐업19980725<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 907-4번지서울특별시 양천구 목동서로 67 (목동)<NA>실내골프연습장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>189197.506088448244.523189골프연습장업사립<NA>000.0<NA><NA><NA>
93140000CDFH330105199400000519941026<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 228-1번지서울특별시 양천구 곰달래로 46, 2,3층 (신월동)7925비바골프클럽2019-08-01 10:09:58U2019-08-03 02:40:00.0<NA>185618.848964447519.079979골프연습장업사립<NA><NA><NA>997.6<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
1673140000CDFH330105201500000120151222<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2653-1872<NA><NA>서울특별시 양천구 신정동 294-71번지 지층서울특별시 양천구 신목로5길 23, 지층 (신정동)8017MD 골프카페2017-08-10 09:26:34I2018-08-31 23:59:59.0<NA>188571.139279446130.682287골프연습장업사립<NA><NA><NA>675.29<NA><NA><NA>
1683140000CDFH330105201600000120160727<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2653-9691<NA><NA>서울특별시 양천구 목동 405-25번지 청학빌딩서울특별시 양천구 오목로 344, 청학빌딩 지하1층 (목동)8006스포짐휘트니스2018-07-30 15:30:03I2018-08-31 23:59:59.0<NA>188904.571764446861.525363골프연습장업사립<NA><NA><NA>12895.2<NA><NA><NA>
1693140000CDFH330105201700000120170831<NA>3폐업3폐업20180119<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 995-1번지 지층서울특별시 양천구 목동로 185, 지층 (신정동)8022(주)짐사이어티2018-01-19 13:47:51I2018-08-31 23:59:59.0<NA>187924.072791446980.855231골프연습장업사립<NA><NA><NA>45.0<NA><NA><NA>
1703140000CDFH330105201700000220171020<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2653-9691<NA><NA>서울특별시 양천구 목동 962번지 목동트라팰리스서울특별시 양천구 오목로 299, 목동트라팰리스 지하층 102호 (목동)8001스포짐2018-03-16 19:05:11I2018-08-31 23:59:59.0<NA>188472.759197447091.855964골프연습장업사립<NA><NA><NA><NA><NA><NA><NA>
1713140000CDFH330105201700000320171113<NA>1영업/정상13영업중<NA><NA><NA><NA>2691-3233<NA><NA>서울특별시 양천구 신월동 546-25번지서울특별시 양천구 신월로 149, 2층 (신월동)8032강K골프아카데미2018-03-16 19:13:00I2018-08-31 23:59:59.0<NA>185810.065888446160.866333골프연습장업사립<NA><NA><NA><NA><NA><NA><NA>
1723140000CDFH330105201800000120180906<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 198-6번지서울특별시 양천구 남부순환로 396, 진보빌딩 4층 (신월동)7915준스크린골프2018-10-25 18:54:49U2018-10-27 02:37:55.0<NA>184941.672626447775.161982골프연습장업사립<NA><NA>12076.79<NA><NA><NA>
1733140000CDFH33010520190000012019-10-10<NA>3폐업3폐업2023-11-30<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 281-8 목동하나아이파크서울특별시 양천구 신목로5길 17-17, 지하1층 (신정동, 목동하나아이파크)8017하나스크린골프2023-11-30 13:48:27U2022-11-02 00:02:00.0<NA>188613.991434446129.318713<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1743140000CDFH330105201900000220191118<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2646-1030<NA><NA>서울특별시 양천구 목동 764-5번지서울특별시 양천구 목동중앙남로 12, 지하1층 (목동)7962목동골프아카데미2019-11-18 13:58:28I2019-11-20 00:23:19.0<NA>188345.484958448158.369459골프연습장업사립<NA><NA><NA>1360.27<NA><NA><NA>
1753140000CDFH330105201900000320191120<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2603-2280<NA><NA>서울특별시 양천구 신정동 1268 복합메디컬타운서울특별시 양천구 중앙로 181, 복합메디컬타운 지층 B202호 (신정동)8106갤러리 골프 아카데미 목동점2020-09-15 10:16:26U2020-09-17 02:40:00.0<NA>187181.284838445624.366466골프연습장업사립<NA><NA><NA><NA><NA><NA><NA>
1763140000CDFH33010520230000012023-12-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 150-5서울특별시 양천구 가로공원로 90, 3층 (신월동)7910챌린저 골프 아카데미2023-12-18 10:25:20I2022-11-01 22:00:00.0<NA>184546.867794448133.305549<NA><NA><NA><NA><NA><NA><NA><NA><NA>