Overview

Dataset statistics

Number of variables34
Number of observations241
Missing cells2103
Missing cells (%)25.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.6 KiB
Average record size in memory291.5 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-19866/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (96.1%)Imbalance
휴업종료일자 is highly imbalanced (96.1%)Imbalance
보험가입여부코드 is highly imbalanced (55.9%)Imbalance
건축물동수 is highly imbalanced (60.5%)Imbalance
회원모집총인원 is highly imbalanced (69.7%)Imbalance
인허가취소일자 has 241 (100.0%) missing valuesMissing
폐업일자 has 152 (63.1%) missing valuesMissing
재개업일자 has 241 (100.0%) missing valuesMissing
전화번호 has 157 (65.1%) missing valuesMissing
소재지면적 has 241 (100.0%) missing valuesMissing
소재지우편번호 has 129 (53.5%) missing valuesMissing
도로명주소 has 8 (3.3%) missing valuesMissing
도로명우편번호 has 42 (17.4%) missing valuesMissing
업태구분명 has 241 (100.0%) missing valuesMissing
좌표정보(X) has 3 (1.2%) missing valuesMissing
좌표정보(Y) has 3 (1.2%) missing valuesMissing
건축물연면적 has 163 (67.6%) missing valuesMissing
세부업종명 has 241 (100.0%) missing valuesMissing
법인명 has 241 (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 42 (17.4%) zerosZeros

Reproduction

Analysis started2024-05-17 23:17:42.891889
Analysis finished2024-05-17 23:17:44.138389
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3140000
241 

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 241
100.0%

Length

2024-05-18T08:17:44.329839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:44.634076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 241
100.0%

관리번호
Text

UNIQUE 

Distinct241
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-18T08:17:45.029520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters4820
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

Unique241 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061989000003
4th rowCDFH3301061989000004
5th rowCDFH3301061989000005
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.4%
cdfh3301062014000003 1
 
0.4%
cdfh3301062019000007 1
 
0.4%
cdfh3301062018000003 1
 
0.4%
cdfh3301062018000004 1
 
0.4%
cdfh3301062018000005 1
 
0.4%
cdfh3301062018000006 1
 
0.4%
cdfh3301062018000007 1
 
0.4%
cdfh3301062018000008 1
 
0.4%
cdfh3301062019000001 1
 
0.4%
Other values (231) 231
95.9%
2024-05-18T08:17:45.863515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1945
40.4%
3 553
 
11.5%
1 463
 
9.6%
2 335
 
7.0%
6 283
 
5.9%
C 241
 
5.0%
D 241
 
5.0%
F 241
 
5.0%
H 241
 
5.0%
9 114
 
2.4%
Other values (4) 163
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3856
80.0%
Uppercase Letter 964
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1945
50.4%
3 553
 
14.3%
1 463
 
12.0%
2 335
 
8.7%
6 283
 
7.3%
9 114
 
3.0%
4 45
 
1.2%
5 42
 
1.1%
7 39
 
1.0%
8 37
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 241
25.0%
D 241
25.0%
F 241
25.0%
H 241
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3856
80.0%
Latin 964
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1945
50.4%
3 553
 
14.3%
1 463
 
12.0%
2 335
 
8.7%
6 283
 
7.3%
9 114
 
3.0%
4 45
 
1.2%
5 42
 
1.1%
7 39
 
1.0%
8 37
 
1.0%
Latin
ValueCountFrequency (%)
C 241
25.0%
D 241
25.0%
F 241
25.0%
H 241
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1945
40.4%
3 553
 
11.5%
1 463
 
9.6%
2 335
 
7.0%
6 283
 
5.9%
C 241
 
5.0%
D 241
 
5.0%
F 241
 
5.0%
H 241
 
5.0%
9 114
 
2.4%
Other values (4) 163
 
3.4%

인허가일자
Date

Distinct231
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1989-11-27 00:00:00
Maximum2024-05-14 00:00:00
2024-05-18T08:17:46.305443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:17:46.837992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1
150 
3
61 
4
29 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 150
62.2%
3 61
25.3%
4 29
 
12.0%
2 1
 
0.4%

Length

2024-05-18T08:17:47.350082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:47.863016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 150
62.2%
3 61
25.3%
4 29
 
12.0%
2 1
 
0.4%

영업상태명
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
영업/정상
150 
폐업
61 
취소/말소/만료/정지/중지
29 
휴업
 
1

Length

Max length14
Median length5
Mean length5.3112033
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 150
62.2%
폐업 61
25.3%
취소/말소/만료/정지/중지 29
 
12.0%
휴업 1
 
0.4%

Length

2024-05-18T08:17:48.306525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:48.789935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 150
62.2%
폐업 61
25.3%
취소/말소/만료/정지/중지 29
 
12.0%
휴업 1
 
0.4%

상세영업상태코드
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
13
150 
3
61 
35
29 
2
 
1

Length

Max length2
Median length2
Mean length1.7427386
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
13 150
62.2%
3 61
25.3%
35 29
 
12.0%
2 1
 
0.4%

Length

2024-05-18T08:17:49.400330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:49.793097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 150
62.2%
3 61
25.3%
35 29
 
12.0%
2 1
 
0.4%

상세영업상태명
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
영업중
150 
폐업
61 
직권말소
29 
휴업
 
1

Length

Max length4
Median length3
Mean length2.8630705
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 150
62.2%
폐업 61
25.3%
직권말소 29
 
12.0%
휴업 1
 
0.4%

Length

2024-05-18T08:17:50.157439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:50.604318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 150
62.2%
폐업 61
25.3%
직권말소 29
 
12.0%
휴업 1
 
0.4%

폐업일자
Date

MISSING 

Distinct63
Distinct (%)70.8%
Missing152
Missing (%)63.1%
Memory size2.0 KiB
Minimum1998-07-07 00:00:00
Maximum2024-05-01 00:00:00
2024-05-18T08:17:51.040529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:17:51.623163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
240 
20221222
 
1

Length

Max length8
Median length4
Mean length4.0165975
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
99.6%
20221222 1
 
0.4%

Length

2024-05-18T08:17:52.143246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:52.680735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
99.6%
20221222 1
 
0.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
240 
20230630
 
1

Length

Max length8
Median length4
Mean length4.0165975
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 240
99.6%
20230630 1
 
0.4%

Length

2024-05-18T08:17:53.191793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:17:53.634197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 240
99.6%
20230630 1
 
0.4%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct83
Distinct (%)98.8%
Missing157
Missing (%)65.1%
Memory size2.0 KiB
2024-05-18T08:17:54.303960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.654762
Min length8

Characters and Unicode

Total characters895
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

Unique82 ?
Unique (%)97.6%

Sample

1st row2601-2554
2nd row02-2648-7017
3rd row2691-5575
4th row2693-6873
5th row692-8264
ValueCountFrequency (%)
050-7556-1842 2
 
2.4%
02-2646-0201 1
 
1.2%
02-2653-9691 1
 
1.2%
02-2065-1123 1
 
1.2%
02-3477-0609 1
 
1.2%
02-2061-0202 1
 
1.2%
02-2695-1007 1
 
1.2%
02-2065-8594 1
 
1.2%
02-2652-0887 1
 
1.2%
02-2647-7727 1
 
1.2%
Other values (73) 73
86.9%
2024-05-18T08:17:55.694912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 158
17.7%
0 129
14.4%
6 123
13.7%
- 122
13.6%
8 66
7.4%
5 59
 
6.6%
9 58
 
6.5%
4 57
 
6.4%
1 49
 
5.5%
7 37
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 773
86.4%
Dash Punctuation 122
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 158
20.4%
0 129
16.7%
6 123
15.9%
8 66
8.5%
5 59
 
7.6%
9 58
 
7.5%
4 57
 
7.4%
1 49
 
6.3%
7 37
 
4.8%
3 37
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 895
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 158
17.7%
0 129
14.4%
6 123
13.7%
- 122
13.6%
8 66
7.4%
5 59
 
6.6%
9 58
 
6.5%
4 57
 
6.4%
1 49
 
5.5%
7 37
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 895
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 158
17.7%
0 129
14.4%
6 123
13.7%
- 122
13.6%
8 66
7.4%
5 59
 
6.6%
9 58
 
6.5%
4 57
 
6.4%
1 49
 
5.5%
7 37
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

소재지우편번호
Text

MISSING 

Distinct54
Distinct (%)48.2%
Missing129
Missing (%)53.5%
Memory size2.0 KiB
2024-05-18T08:17:56.278847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0535714
Min length6

Characters and Unicode

Total characters678
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 (%)25.9%

Sample

1st row158812
2nd row158840
3rd row158816
4th row158859
5th row158811
ValueCountFrequency (%)
158050 11
 
9.8%
158806 8
 
7.1%
158860 6
 
5.4%
158070 6
 
5.4%
158859 5
 
4.5%
158811 4
 
3.6%
158827 3
 
2.7%
158848 3
 
2.7%
158824 3
 
2.7%
158831 3
 
2.7%
Other values (44) 60
53.6%
2024-05-18T08:17:57.399384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 203
29.9%
5 150
22.1%
1 141
20.8%
0 66
 
9.7%
7 27
 
4.0%
6 24
 
3.5%
4 23
 
3.4%
2 19
 
2.8%
3 10
 
1.5%
9 9
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 672
99.1%
Dash Punctuation 6
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 203
30.2%
5 150
22.3%
1 141
21.0%
0 66
 
9.8%
7 27
 
4.0%
6 24
 
3.6%
4 23
 
3.4%
2 19
 
2.8%
3 10
 
1.5%
9 9
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 678
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 203
29.9%
5 150
22.1%
1 141
20.8%
0 66
 
9.7%
7 27
 
4.0%
6 24
 
3.5%
4 23
 
3.4%
2 19
 
2.8%
3 10
 
1.5%
9 9
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 678
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 203
29.9%
5 150
22.1%
1 141
20.8%
0 66
 
9.7%
7 27
 
4.0%
6 24
 
3.5%
4 23
 
3.4%
2 19
 
2.8%
3 10
 
1.5%
9 9
 
1.3%

지번주소
Text

Distinct237
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-18T08:17:58.123122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length33
Mean length25.352697
Min length18

Characters and Unicode

Total characters6110
Distinct characters164
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

Unique233 ?
Unique (%)96.7%

Sample

1st row서울특별시 양천구 목동 657-22번지
2nd row서울특별시 양천구 신월동 537-7번지 4층
3rd row서울특별시 양천구 목동 752-8번지
4th row서울특별시 양천구 신정동 952-5번지
5th row서울특별시 양천구 목동 613-9번지
ValueCountFrequency (%)
서울특별시 241
20.5%
양천구 241
20.5%
목동 109
 
9.3%
신정동 95
 
8.1%
신월동 38
 
3.2%
3층 13
 
1.1%
2층 10
 
0.9%
4층 8
 
0.7%
지하1층 7
 
0.6%
지층 6
 
0.5%
Other values (350) 408
34.7%
2024-05-18T08:17:59.476182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1092
 
17.9%
동 261
 
4.3%
양 243
 
4.0%
울 241
 
3.9%
구 241
 
3.9%
천 241
 
3.9%
서 241
 
3.9%
시 241
 
3.9%
별 241
 
3.9%
특 241
 
3.9%
Other values (154) 2827
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3486
57.1%
Decimal Number 1275
 
20.9%
Space Separator 1092
 
17.9%
Dash Punctuation 215
 
3.5%
Uppercase Letter 24
 
0.4%
Other Punctuation 8
 
0.1%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 261
 
7.5%
양 243
 
7.0%
울 241
 
6.9%
구 241
 
6.9%
천 241
 
6.9%
서 241
 
6.9%
시 241
 
6.9%
별 241
 
6.9%
특 241
 
6.9%
지 156
 
4.5%
Other values (129) 1139
32.7%
Decimal Number
ValueCountFrequency (%)
1 236
18.5%
2 189
14.8%
0 153
12.0%
3 138
10.8%
9 119
9.3%
4 113
8.9%
5 92
 
7.2%
7 81
 
6.4%
6 79
 
6.2%
8 75
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
B 14
58.3%
I 2
 
8.3%
D 2
 
8.3%
M 1
 
4.2%
A 1
 
4.2%
U 1
 
4.2%
L 1
 
4.2%
N 1
 
4.2%
G 1
 
4.2%
Space Separator
ValueCountFrequency (%)
1092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3486
57.1%
Common 2600
42.6%
Latin 24
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 261
 
7.5%
양 243
 
7.0%
울 241
 
6.9%
구 241
 
6.9%
천 241
 
6.9%
서 241
 
6.9%
시 241
 
6.9%
별 241
 
6.9%
특 241
 
6.9%
지 156
 
4.5%
Other values (129) 1139
32.7%
Common
ValueCountFrequency (%)
1092
42.0%
1 236
 
9.1%
- 215
 
8.3%
2 189
 
7.3%
0 153
 
5.9%
3 138
 
5.3%
9 119
 
4.6%
4 113
 
4.3%
5 92
 
3.5%
7 81
 
3.1%
Other values (6) 172
 
6.6%
Latin
ValueCountFrequency (%)
B 14
58.3%
I 2
 
8.3%
D 2
 
8.3%
M 1
 
4.2%
A 1
 
4.2%
U 1
 
4.2%
L 1
 
4.2%
N 1
 
4.2%
G 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3486
57.1%
ASCII 2624
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1092
41.6%
1 236
 
9.0%
- 215
 
8.2%
2 189
 
7.2%
0 153
 
5.8%
3 138
 
5.3%
9 119
 
4.5%
4 113
 
4.3%
5 92
 
3.5%
7 81
 
3.1%
Other values (15) 196
 
7.5%
Hangul
ValueCountFrequency (%)
동 261
 
7.5%
양 243
 
7.0%
울 241
 
6.9%
구 241
 
6.9%
천 241
 
6.9%
서 241
 
6.9%
시 241
 
6.9%
별 241
 
6.9%
특 241
 
6.9%
지 156
 
4.5%
Other values (129) 1139
32.7%

도로명주소
Text

MISSING 

Distinct229
Distinct (%)98.3%
Missing8
Missing (%)3.3%
Memory size2.0 KiB
2024-05-18T08:18:00.378069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length31.416309
Min length21

Characters and Unicode

Total characters7320
Distinct characters183
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

Unique225 ?
Unique (%)96.6%

Sample

1st row서울특별시 양천구 신월로 173, 4층 (신월동)
2nd row서울특별시 양천구 목동중앙로 101 (목동)
3rd row서울특별시 양천구 오목로 178 (신정동)
4th row서울특별시 양천구 등촌로 224 (목동)
5th row서울특별시 양천구 중앙로 269 (신정동)
ValueCountFrequency (%)
서울특별시 233
 
16.1%
양천구 233
 
16.1%
목동 84
 
5.8%
신정동 82
 
5.7%
오목로 37
 
2.6%
신월동 32
 
2.2%
목동서로 25
 
1.7%
2층 24
 
1.7%
3층 22
 
1.5%
목동동로 19
 
1.3%
Other values (378) 654
45.3%
2024-05-18T08:18:02.010119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1252
 
17.1%
동 378
 
5.2%
서 263
 
3.6%
목 256
 
3.5%
양 240
 
3.3%
, 238
 
3.3%
( 238
 
3.3%
) 238
 
3.3%
로 237
 
3.2%
천 234
 
3.2%
Other values (173) 3746
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4202
57.4%
Space Separator 1252
 
17.1%
Decimal Number 1090
 
14.9%
Other Punctuation 244
 
3.3%
Open Punctuation 238
 
3.3%
Close Punctuation 238
 
3.3%
Uppercase Letter 33
 
0.5%
Dash Punctuation 18
 
0.2%
Math Symbol 4
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 378
 
9.0%
서 263
 
6.3%
목 256
 
6.1%
양 240
 
5.7%
로 237
 
5.6%
천 234
 
5.6%
구 233
 
5.5%
울 233
 
5.5%
시 233
 
5.5%
별 233
 
5.5%
Other values (146) 1662
39.6%
Decimal Number
ValueCountFrequency (%)
1 216
19.8%
2 185
17.0%
3 153
14.0%
0 123
11.3%
4 87
8.0%
5 81
 
7.4%
6 64
 
5.9%
9 62
 
5.7%
7 60
 
5.5%
8 59
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 21
63.6%
A 3
 
9.1%
I 2
 
6.1%
D 2
 
6.1%
M 1
 
3.0%
U 1
 
3.0%
L 1
 
3.0%
G 1
 
3.0%
N 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 238
97.5%
. 6
 
2.5%
Space Separator
ValueCountFrequency (%)
1252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 238
100.0%
Close Punctuation
ValueCountFrequency (%)
) 238
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4202
57.4%
Common 3084
42.1%
Latin 34
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 378
 
9.0%
서 263
 
6.3%
목 256
 
6.1%
양 240
 
5.7%
로 237
 
5.6%
천 234
 
5.6%
구 233
 
5.5%
울 233
 
5.5%
시 233
 
5.5%
별 233
 
5.5%
Other values (146) 1662
39.6%
Common
ValueCountFrequency (%)
1252
40.6%
, 238
 
7.7%
( 238
 
7.7%
) 238
 
7.7%
1 216
 
7.0%
2 185
 
6.0%
3 153
 
5.0%
0 123
 
4.0%
4 87
 
2.8%
5 81
 
2.6%
Other values (7) 273
 
8.9%
Latin
ValueCountFrequency (%)
B 21
61.8%
A 3
 
8.8%
I 2
 
5.9%
D 2
 
5.9%
b 1
 
2.9%
M 1
 
2.9%
U 1
 
2.9%
L 1
 
2.9%
G 1
 
2.9%
N 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4202
57.4%
ASCII 3118
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1252
40.2%
, 238
 
7.6%
( 238
 
7.6%
) 238
 
7.6%
1 216
 
6.9%
2 185
 
5.9%
3 153
 
4.9%
0 123
 
3.9%
4 87
 
2.8%
5 81
 
2.6%
Other values (17) 307
 
9.8%
Hangul
ValueCountFrequency (%)
동 378
 
9.0%
서 263
 
6.3%
목 256
 
6.1%
양 240
 
5.7%
로 237
 
5.6%
천 234
 
5.6%
구 233
 
5.5%
울 233
 
5.5%
시 233
 
5.5%
별 233
 
5.5%
Other values (146) 1662
39.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct78
Distinct (%)39.2%
Missing42
Missing (%)17.4%
Infinite0
Infinite (%)0.0%
Mean9520.191
Minimum7905
Maximum158855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T08:18:02.592949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7905
5-th percentile7935.4
Q17965
median8005
Q38029.5
95-th percentile8095
Maximum158855
Range150950
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation15083.579
Coefficient of variation (CV)1.5843778
Kurtosis96.957005
Mean9520.191
Median Absolute Deviation (MAD)36
Skewness9.8985592
Sum1894518
Variance2.2751436 × 108
MonotonicityNot monotonic
2024-05-18T08:18:03.165469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7946 13
 
5.4%
7983 9
 
3.7%
8093 8
 
3.3%
7993 7
 
2.9%
8020 7
 
2.9%
8007 6
 
2.5%
8006 5
 
2.1%
7995 5
 
2.1%
7967 5
 
2.1%
7988 5
 
2.1%
Other values (68) 129
53.5%
(Missing) 42
 
17.4%
ValueCountFrequency (%)
7905 3
1.2%
7907 1
 
0.4%
7909 1
 
0.4%
7920 1
 
0.4%
7921 1
 
0.4%
7923 1
 
0.4%
7924 1
 
0.4%
7930 1
 
0.4%
7936 2
0.8%
7937 2
0.8%
ValueCountFrequency (%)
158855 1
 
0.4%
158831 1
 
0.4%
8106 4
1.7%
8104 2
 
0.8%
8102 1
 
0.4%
8095 2
 
0.8%
8093 8
3.3%
8087 2
 
0.8%
8086 4
1.7%
8082 3
 
1.2%

사업장명
Text

Distinct236
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-18T08:18:03.884557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length7.8506224
Min length1

Characters and Unicode

Total characters1892
Distinct characters308
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)95.9%

Sample

1st row백마헬스크럽
2nd row라이프헬스클럽
3rd row양천헬스크럽
4th row정우헬스
5th row국제헬스
ValueCountFrequency (%)
휘트니스 16
 
4.3%
피트니스 7
 
1.9%
짐 6
 
1.6%
pt 5
 
1.3%
목동점 5
 
1.3%
gym 5
 
1.3%
fit 4
 
1.1%
3
 
0.8%
studio 3
 
0.8%
등촌역점 3
 
0.8%
Other values (288) 317
84.8%
2024-05-18T08:18:05.177221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 166
 
8.8%
134
 
7.1%
트 62
 
3.3%
니 56
 
3.0%
헬 55
 
2.9%
짐 54
 
2.9%
이 49
 
2.6%
휘 37
 
2.0%
T 28
 
1.5%
점 27
 
1.4%
Other values (298) 1224
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1381
73.0%
Uppercase Letter 192
 
10.1%
Space Separator 134
 
7.1%
Lowercase Letter 93
 
4.9%
Decimal Number 28
 
1.5%
Other Punctuation 23
 
1.2%
Open Punctuation 19
 
1.0%
Close Punctuation 19
 
1.0%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 166
 
12.0%
트 62
 
4.5%
니 56
 
4.1%
헬 55
 
4.0%
짐 54
 
3.9%
이 49
 
3.5%
휘 37
 
2.7%
점 27
 
2.0%
럽 22
 
1.6%
리 21
 
1.5%
Other values (233) 832
60.2%
Uppercase Letter
ValueCountFrequency (%)
T 28
14.6%
P 20
10.4%
S 18
 
9.4%
M 16
 
8.3%
F 14
 
7.3%
B 12
 
6.2%
G 11
 
5.7%
I 10
 
5.2%
Y 9
 
4.7%
E 9
 
4.7%
Other values (15) 45
23.4%
Lowercase Letter
ValueCountFrequency (%)
o 11
11.8%
s 9
 
9.7%
t 8
 
8.6%
e 8
 
8.6%
i 8
 
8.6%
y 7
 
7.5%
m 5
 
5.4%
n 5
 
5.4%
d 5
 
5.4%
a 4
 
4.3%
Other values (10) 23
24.7%
Decimal Number
ValueCountFrequency (%)
1 6
21.4%
2 6
21.4%
4 4
14.3%
3 2
 
7.1%
0 2
 
7.1%
5 2
 
7.1%
9 2
 
7.1%
6 2
 
7.1%
8 1
 
3.6%
7 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 14
60.9%
& 5
 
21.7%
＆ 1
 
4.3%
/ 1
 
4.3%
: 1
 
4.3%
' 1
 
4.3%
Space Separator
ValueCountFrequency (%)
134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1381
73.0%
Latin 285
 
15.1%
Common 226
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 166
 
12.0%
트 62
 
4.5%
니 56
 
4.1%
헬 55
 
4.0%
짐 54
 
3.9%
이 49
 
3.5%
휘 37
 
2.7%
점 27
 
2.0%
럽 22
 
1.6%
리 21
 
1.5%
Other values (233) 832
60.2%
Latin
ValueCountFrequency (%)
T 28
 
9.8%
P 20
 
7.0%
S 18
 
6.3%
M 16
 
5.6%
F 14
 
4.9%
B 12
 
4.2%
o 11
 
3.9%
G 11
 
3.9%
I 10
 
3.5%
s 9
 
3.2%
Other values (35) 136
47.7%
Common
ValueCountFrequency (%)
134
59.3%
( 19
 
8.4%
) 19
 
8.4%
. 14
 
6.2%
1 6
 
2.7%
2 6
 
2.7%
& 5
 
2.2%
4 4
 
1.8%
- 3
 
1.3%
3 2
 
0.9%
Other values (10) 14
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1381
73.0%
ASCII 510
 
27.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 166
 
12.0%
트 62
 
4.5%
니 56
 
4.1%
헬 55
 
4.0%
짐 54
 
3.9%
이 49
 
3.5%
휘 37
 
2.7%
점 27
 
2.0%
럽 22
 
1.6%
리 21
 
1.5%
Other values (233) 832
60.2%
ASCII
ValueCountFrequency (%)
134
26.3%
T 28
 
5.5%
P 20
 
3.9%
( 19
 
3.7%
) 19
 
3.7%
S 18
 
3.5%
M 16
 
3.1%
. 14
 
2.7%
F 14
 
2.7%
B 12
 
2.4%
Other values (54) 216
42.4%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정일자
Date

Distinct231
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2002-10-22 17:59:13
Maximum2024-05-14 17:58:08
2024-05-18T08:18:05.631332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:18:06.026948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
I
124 
U
117 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 124
51.5%
U 117
48.5%

Length

2024-05-18T08:18:06.683814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:07.057110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 124
51.5%
u 117
48.5%

데이터갱신일자
Date

Distinct137
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-18T08:18:07.535187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:18:08.013631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)80.3%
Missing3
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean187685
Minimum184413.38
Maximum189659.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T08:18:08.699774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184413.38
5-th percentile185159.56
Q1187158.47
median187936.5
Q3188550.73
95-th percentile189151.21
Maximum189659.13
Range5245.7414
Interquartile range (IQR)1392.2619

Descriptive statistics

Standard deviation1207.0328
Coefficient of variation (CV)0.0064311627
Kurtosis-0.05644465
Mean187685
Median Absolute Deviation (MAD)653.44898
Skewness-0.90027602
Sum44669029
Variance1456928.1
MonotonicityNot monotonic
2024-05-18T08:18:09.207363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188494.598982992 4
 
1.7%
189151.208015925 3
 
1.2%
188967.445733675 3
 
1.2%
189042.496526196 3
 
1.2%
187909.577234823 3
 
1.2%
187734.983111761 3
 
1.2%
187309.190268085 3
 
1.2%
187774.076185179 2
 
0.8%
188301.080556007 2
 
0.8%
187520.306766633 2
 
0.8%
Other values (181) 210
87.1%
(Missing) 3
 
1.2%
ValueCountFrequency (%)
184413.383829302 1
0.4%
184748.532781957 1
0.4%
184757.482019275 1
0.4%
184829.306182525 1
0.4%
184849.685333553 1
0.4%
185018.889951411 1
0.4%
185077.934512008 1
0.4%
185099.82674039 1
0.4%
185104.517731789 1
0.4%
185116.090844072 1
0.4%
ValueCountFrequency (%)
189659.125277836 2
0.8%
189519.862506193 1
 
0.4%
189469.901305589 1
 
0.4%
189348.372526225 1
 
0.4%
189280.689807363 2
0.8%
189251.065 2
0.8%
189224.684682604 1
 
0.4%
189197.506088261 1
 
0.4%
189151.208015925 3
1.2%
189086.756192965 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)80.3%
Missing3
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean447281.47
Minimum445081.4
Maximum449821.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T08:18:09.626956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445081.4
5-th percentile445670.49
Q1446566.4
median446986.41
Q3448085.38
95-th percentile449643.83
Maximum449821.72
Range4740.3232
Interquartile range (IQR)1518.9797

Descriptive statistics

Standard deviation1129.6176
Coefficient of variation (CV)0.0025255184
Kurtosis-0.31648043
Mean447281.47
Median Absolute Deviation (MAD)729.92312
Skewness0.58608187
Sum1.0645299 × 108
Variance1276035.9
MonotonicityNot monotonic
2024-05-18T08:18:10.298910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447318.660520705 4
 
1.7%
448200.067716589 3
 
1.2%
447716.332636357 3
 
1.2%
447777.835760268 3
 
1.2%
448552.886115153 3
 
1.2%
446030.714521005 3
 
1.2%
446979.598892559 3
 
1.2%
449099.406847977 2
 
0.8%
447086.727980803 2
 
0.8%
446450.347274241 2
 
0.8%
Other values (181) 210
87.1%
(Missing) 3
 
1.2%
ValueCountFrequency (%)
445081.396522145 1
0.4%
445124.131588947 1
0.4%
445180.40867328 1
0.4%
445197.198550791 1
0.4%
445235.902836259 1
0.4%
445479.209299057 1
0.4%
445516.57883261 1
0.4%
445562.576452316 1
0.4%
445595.680081302 1
0.4%
445624.366466149 2
0.8%
ValueCountFrequency (%)
449821.719712552 1
0.4%
449783.944486969 1
0.4%
449783.451870726 1
0.4%
449753.158413664 1
0.4%
449728.279227887 1
0.4%
449706.807437882 1
0.4%
449701.802558519 2
0.8%
449679.651827505 2
0.8%
449668.428997479 2
0.8%
449639.484816091 1
0.4%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
체력단련장업
177 
<NA>
64 

Length

Max length6
Median length6
Mean length5.4688797
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 177
73.4%
<NA> 64
 
26.6%

Length

2024-05-18T08:18:10.796373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:11.200872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 177
73.4%
na 64
 
26.6%

공사립구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
사립
177 
<NA>
64 

Length

Max length4
Median length2
Mean length2.5311203
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 177
73.4%
<NA> 64
 
26.6%

Length

2024-05-18T08:18:11.642739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:12.097364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 177
73.4%
na 64
 
26.6%

보험가입여부코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
219 
0
22 

Length

Max length4
Median length4
Mean length3.7261411
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> 219
90.9%
0 22
 
9.1%

Length

2024-05-18T08:18:12.478772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:13.072917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
90.9%
0 22
 
9.1%

지도자수
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
145 
1
53 
0
27 
2
16 

Length

Max length4
Median length4
Mean length2.8049793
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 145
60.2%
1 53
 
22.0%
0 27
 
11.2%
2 16
 
6.6%

Length

2024-05-18T08:18:13.438305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:13.755913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
60.2%
1 53
 
22.0%
0 27
 
11.2%
2 16
 
6.6%

건축물동수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
194 
0
44 
1
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.4149378
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 194
80.5%
0 44
 
18.3%
1 2
 
0.8%
2 1
 
0.4%

Length

2024-05-18T08:18:14.182389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:14.577431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 194
80.5%
0 44
 
18.3%
1 2
 
0.8%
2 1
 
0.4%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)47.4%
Missing163
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean371.80846
Minimum0
Maximum12895.2
Zeros42
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-18T08:18:14.965270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3237.75
95-th percentile745.5575
Maximum12895.2
Range12895.2
Interquartile range (IQR)237.75

Descriptive statistics

Standard deviation1545.9446
Coefficient of variation (CV)4.1579058
Kurtosis57.848288
Mean371.80846
Median Absolute Deviation (MAD)0
Skewness7.3097274
Sum29001.06
Variance2389944.6
MonotonicityNot monotonic
2024-05-18T08:18:15.420417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 42
 
17.4%
204.6 1
 
0.4%
115.5 1
 
0.4%
212.0 1
 
0.4%
732.56 1
 
0.4%
96.0 1
 
0.4%
71.0 1
 
0.4%
202.0 1
 
0.4%
165.0 1
 
0.4%
242.98 1
 
0.4%
Other values (27) 27
 
11.2%
(Missing) 163
67.6%
ValueCountFrequency (%)
0.0 42
17.4%
71.0 1
 
0.4%
96.0 1
 
0.4%
100.0 1
 
0.4%
115.5 1
 
0.4%
119.0 1
 
0.4%
163.68 1
 
0.4%
165.0 1
 
0.4%
171.0 1
 
0.4%
180.0 1
 
0.4%
ValueCountFrequency (%)
12895.2 1
0.4%
3737.56 1
0.4%
3341.33 1
0.4%
819.21 1
0.4%
732.56 1
0.4%
658.52 1
0.4%
390.4 1
0.4%
350.31 1
0.4%
332.75 1
0.4%
332.24 1
0.4%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
228 
0
 
13

Length

Max length4
Median length4
Mean length3.8381743
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> 228
94.6%
0 13
 
5.4%

Length

2024-05-18T08:18:15.792756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:18:16.108005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
94.6%
0 13
 
5.4%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing241
Missing (%)100.0%
Memory size2.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03140000CDFH330106198900000119891127<NA>3폐업3폐업20000801<NA><NA><NA><NA><NA>158812서울특별시 양천구 목동 657-22번지<NA><NA>백마헬스크럽2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>187778.18928449202.438648체력단련장업사립<NA>000.0<NA><NA><NA>
13140000CDFH330106198900000219891206<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>158840서울특별시 양천구 신월동 537-7번지 4층서울특별시 양천구 신월로 173, 4층 (신월동)8030라이프헬스클럽2016-07-27 16:19:12I2018-08-31 23:59:59.0<NA>185987.773852446289.261283체력단련장업사립<NA><NA>0<NA><NA><NA><NA>
23140000CDFH330106198900000319891206<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA><NA><NA>158816서울특별시 양천구 목동 752-8번지서울특별시 양천구 목동중앙로 101 (목동)7976양천헬스크럽2019-08-06 17:17:59U2019-08-08 02:40:00.0<NA>188683.524275448423.22837체력단련장업사립<NA>000.0<NA><NA><NA>
33140000CDFH330106198900000419891218<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA>2601-2554<NA>158859서울특별시 양천구 신정동 952-5번지서울특별시 양천구 오목로 178 (신정동)8020정우헬스2019-08-06 18:12:31U2019-08-08 02:40:00.0<NA>187309.190268446979.598893체력단련장업사립<NA><NA><NA>171.0<NA><NA><NA>
43140000CDFH330106198900000519891218<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA>02-2648-7017<NA>158811서울특별시 양천구 목동 613-9번지서울특별시 양천구 등촌로 224 (목동)7946국제헬스2019-08-06 17:21:41U2019-08-08 02:40:00.0<NA>187922.211865449706.807438체력단련장업사립<NA><NA><NA>204.6<NA><NA><NA>
53140000CDFH330106198900000619891218<NA>3폐업3폐업19990504<NA><NA><NA><NA><NA>158864서울특별시 양천구 신정동 1190-6번지서울특별시 양천구 중앙로 269 (신정동)<NA>강서헬스크럽2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>186887.779002446481.970676체력단련장업사립<NA>000.0<NA><NA><NA>
63140000CDFH330106199200000119920611<NA>3폐업3폐업20041209<NA><NA><NA><NA><NA>158828서울특별시 양천구 신월동 132-4번지서울특별시 양천구 남부순환로59길 10 (신월동)<NA>룡헬스크럽2004-12-09 10:07:20I2018-08-31 23:59:59.0<NA>185116.090844447779.905137체력단련장업사립0<NA><NA><NA><NA><NA><NA>
73140000CDFH330106199300000119930107<NA>3폐업3폐업20070615<NA><NA><NA>2691-5575<NA>158844서울특별시 양천구 신월동 913-1번지서울특별시 양천구 지양로 96 (신월동)<NA>역산헬스2007-06-15 16:41:08I2018-08-31 23:59:59.0<NA>185077.934512446815.49327체력단련장업사립0<NA><NA>115.5<NA><NA><NA>
83140000CDFH330106199300000219930601<NA>3폐업3폐업19980707<NA><NA><NA><NA><NA>158070서울특별시 양천구 신정동 319-18번지서울특별시 양천구 목동서로 301-13 (신정동)<NA>무2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188374.060947446369.138672체력단련장업사립<NA>000.0<NA><NA><NA>
93140000CDFH330106199300000319930604<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA><NA><NA>158806서울특별시 양천구 목동 404-151번지서울특별시 양천구 신목로 90 (목동)8007영헬스2019-08-06 17:24:21U2019-08-08 02:40:00.0<NA>188892.040933446732.277349체력단련장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
2313140000CDFH33010620230000182023-12-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 406-183서울특별시 양천구 오목로 287, 4층 (목동)7993루티니2024-04-09 09:23:46U2023-12-03 23:01:00.0<NA>188389.335315447053.287593<NA><NA><NA><NA><NA><NA><NA><NA><NA>
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2333140000CDFH33010620240000012024-01-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 296-28 목동캐슬아파트서울특별시 양천구 목동동로10길 22, 지층1호 (신정동, 목동캐슬아파트)8014(주)테이스트피트니스PT 목동점2024-01-13 10:57:28I2023-11-30 23:05:00.0<NA>188619.344914446340.894581<NA><NA><NA><NA><NA><NA><NA><NA><NA>
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2353140000CDFH33010620240000032024-03-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 797-9서울특별시 양천구 목동중앙서로 32, 2층 (목동)7967오오핏2024-03-14 09:05:31I2023-12-02 23:06:00.0<NA>188199.619596447838.73735<NA><NA><NA><NA><NA><NA><NA><NA><NA>
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2373140000CDFH33010620240000052024-03-27<NA>1영업/정상13영업중<NA><NA><NA><NA>0507-1446-3694<NA><NA>서울특별시 양천구 신월동 546-25서울특별시 양천구 신월로 149, 2층 (신월동)8032본투비짐2024-03-27 09:03:22I2023-12-02 22:09:00.0<NA>185810.065888446160.866333<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2383140000CDFH33010620240000062016-05-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1014-3 법정빌딩서울특별시 양천구 신월로 376, 법정빌딩 지층 (신정동)8087머슬팜짐2024-04-09 09:26:36U2023-12-03 23:01:00.0<NA>187791.46182446647.027913<NA><NA><NA><NA><NA><NA><NA><NA><NA>
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