Overview

Dataset statistics

Number of variables34
Number of observations399
Missing cells4337
Missing cells (%)32.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory112.7 KiB
Average record size in memory289.3 B

Variable types

Categorical12
Text7
DateTime4
Unsupported8
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-19873/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
보험가입여부코드 is highly imbalanced (75.9%)Imbalance
회원모집총인원 is highly imbalanced (66.2%)Imbalance
인허가취소일자 has 399 (100.0%) missing valuesMissing
폐업일자 has 303 (75.9%) missing valuesMissing
휴업시작일자 has 399 (100.0%) missing valuesMissing
휴업종료일자 has 399 (100.0%) missing valuesMissing
재개업일자 has 399 (100.0%) missing valuesMissing
전화번호 has 165 (41.4%) missing valuesMissing
소재지면적 has 399 (100.0%) missing valuesMissing
소재지우편번호 has 232 (58.1%) missing valuesMissing
지번주소 has 14 (3.5%) missing valuesMissing
도로명주소 has 4 (1.0%) missing valuesMissing
도로명우편번호 has 110 (27.6%) missing valuesMissing
업태구분명 has 399 (100.0%) missing valuesMissing
좌표정보(X) has 4 (1.0%) missing valuesMissing
좌표정보(Y) has 4 (1.0%) missing valuesMissing
건축물연면적 has 309 (77.4%) missing valuesMissing
세부업종명 has 399 (100.0%) missing valuesMissing
법인명 has 399 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
세부업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법인명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축물연면적 has 36 (9.0%) zerosZeros

Reproduction

Analysis started2024-04-29 20:02:29.765507
Analysis finished2024-04-29 20:02:30.710460
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3210000
399 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 399
100.0%

Length

2024-04-30T05:02:30.772470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:30.849877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 399
100.0%

관리번호
Text

UNIQUE 

Distinct399
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-04-30T05:02:31.004276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7980
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

Unique399 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061990000001
4th rowCDFH3301061990000002
5th rowCDFH3301061991000001
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.3%
cdfh3301062019000003 1
 
0.3%
cdfh3301062020000008 1
 
0.3%
cdfh3301062020000007 1
 
0.3%
cdfh3301062020000006 1
 
0.3%
cdfh3301062020000005 1
 
0.3%
cdfh3301062020000004 1
 
0.3%
cdfh3301062020000003 1
 
0.3%
cdfh3301062020000002 1
 
0.3%
cdfh3301062020000001 1
 
0.3%
Other values (389) 389
97.5%
2024-04-30T05:02:31.264112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3138
39.3%
3 916
 
11.5%
1 793
 
9.9%
2 680
 
8.5%
6 461
 
5.8%
C 399
 
5.0%
D 399
 
5.0%
F 399
 
5.0%
H 399
 
5.0%
9 108
 
1.4%
Other values (4) 288
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6384
80.0%
Uppercase Letter 1596
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3138
49.2%
3 916
 
14.3%
1 793
 
12.4%
2 680
 
10.7%
6 461
 
7.2%
9 108
 
1.7%
4 83
 
1.3%
8 76
 
1.2%
5 69
 
1.1%
7 60
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 399
25.0%
D 399
25.0%
F 399
25.0%
H 399
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6384
80.0%
Latin 1596
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3138
49.2%
3 916
 
14.3%
1 793
 
12.4%
2 680
 
10.7%
6 461
 
7.2%
9 108
 
1.7%
4 83
 
1.3%
8 76
 
1.2%
5 69
 
1.1%
7 60
 
0.9%
Latin
ValueCountFrequency (%)
C 399
25.0%
D 399
25.0%
F 399
25.0%
H 399
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3138
39.3%
3 916
 
11.5%
1 793
 
9.9%
2 680
 
8.5%
6 461
 
5.8%
C 399
 
5.0%
D 399
 
5.0%
F 399
 
5.0%
H 399
 
5.0%
9 108
 
1.4%
Other values (4) 288
 
3.6%

인허가일자
Date

Distinct381
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1989-12-18 00:00:00
Maximum2024-04-12 00:00:00
2024-04-30T05:02:31.387010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:31.520674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
1
303 
3
96 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 303
75.9%
3 96
 
24.1%

Length

2024-04-30T05:02:31.629304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:31.714408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 303
75.9%
3 96
 
24.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
영업/정상
303 
폐업
96 

Length

Max length5
Median length5
Mean length4.2781955
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 303
75.9%
폐업 96
 
24.1%

Length

2024-04-30T05:02:31.804929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:31.904461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 303
75.9%
폐업 96
 
24.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
13
303 
3
96 

Length

Max length2
Median length2
Mean length1.7593985
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 303
75.9%
3 96
 
24.1%

Length

2024-04-30T05:02:31.990075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:32.069055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 303
75.9%
3 96
 
24.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
영업중
303 
폐업
96 

Length

Max length3
Median length3
Mean length2.7593985
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 303
75.9%
폐업 96
 
24.1%

Length

2024-04-30T05:02:32.151733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:32.236540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 303
75.9%
폐업 96
 
24.1%

폐업일자
Date

MISSING 

Distinct91
Distinct (%)94.8%
Missing303
Missing (%)75.9%
Memory size3.2 KiB
Minimum1998-06-08 00:00:00
Maximum2024-03-21 00:00:00
2024-04-30T05:02:32.319975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:32.432633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

전화번호
Text

MISSING 

Distinct229
Distinct (%)97.9%
Missing165
Missing (%)41.4%
Memory size3.2 KiB
2024-04-30T05:02:32.686572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.6452991
Min length1

Characters and Unicode

Total characters2257
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)95.7%

Sample

1st row503-5583
2nd row576-4891
3rd row532-0101
4th row507-4215
5th row562-1230
ValueCountFrequency (%)
2057-4035 2
 
0.9%
576-2747 2
 
0.9%
3474-8974 2
 
0.9%
533-1253 2
 
0.9%
02-537-3297 2
 
0.9%
02-511-0906 1
 
0.4%
02-525-9682 1
 
0.4%
02-521-5976 1
 
0.4%
02-2055-0077 1
 
0.4%
02-579-8485 1
 
0.4%
Other values (219) 219
93.6%
2024-04-30T05:02:33.075369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 320
14.2%
5 317
14.0%
0 281
12.5%
2 258
11.4%
3 191
8.5%
8 167
7.4%
7 164
7.3%
9 160
7.1%
1 149
6.6%
6 125
 
5.5%
Other values (5) 125
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1928
85.4%
Dash Punctuation 320
 
14.2%
Close Punctuation 6
 
0.3%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 317
16.4%
0 281
14.6%
2 258
13.4%
3 191
9.9%
8 167
8.7%
7 164
8.5%
9 160
8.3%
1 149
7.7%
6 125
 
6.5%
4 116
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 320
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2257
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 320
14.2%
5 317
14.0%
0 281
12.5%
2 258
11.4%
3 191
8.5%
8 167
7.4%
7 164
7.3%
9 160
7.1%
1 149
6.6%
6 125
 
5.5%
Other values (5) 125
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 320
14.2%
5 317
14.0%
0 281
12.5%
2 258
11.4%
3 191
8.5%
8 167
7.4%
7 164
7.3%
9 160
7.1%
1 149
6.6%
6 125
 
5.5%
Other values (5) 125
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

소재지우편번호
Text

MISSING 

Distinct85
Distinct (%)50.9%
Missing232
Missing (%)58.1%
Memory size3.2 KiB
2024-04-30T05:02:33.299195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0658683
Min length6

Characters and Unicode

Total characters1013
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

Unique45 ?
Unique (%)26.9%

Sample

1st row137040
2nd row137886
3rd row137804
4th row137860
5th row137859
ValueCountFrequency (%)
137803 7
 
4.2%
137806 7
 
4.2%
137828 5
 
3.0%
137909 5
 
3.0%
137865 4
 
2.4%
137856 4
 
2.4%
137867 4
 
2.4%
137882 4
 
2.4%
137873 4
 
2.4%
137860 4
 
2.4%
Other values (75) 119
71.3%
2024-04-30T05:02:33.634038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 209
20.6%
3 199
19.6%
1 191
18.9%
8 181
17.9%
0 56
 
5.5%
6 42
 
4.1%
9 39
 
3.8%
5 35
 
3.5%
2 31
 
3.1%
4 19
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1002
98.9%
Dash Punctuation 11
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 209
20.9%
3 199
19.9%
1 191
19.1%
8 181
18.1%
0 56
 
5.6%
6 42
 
4.2%
9 39
 
3.9%
5 35
 
3.5%
2 31
 
3.1%
4 19
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1013
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 209
20.6%
3 199
19.6%
1 191
18.9%
8 181
17.9%
0 56
 
5.5%
6 42
 
4.1%
9 39
 
3.8%
5 35
 
3.5%
2 31
 
3.1%
4 19
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1013
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 209
20.6%
3 199
19.6%
1 191
18.9%
8 181
17.9%
0 56
 
5.5%
6 42
 
4.1%
9 39
 
3.8%
5 35
 
3.5%
2 31
 
3.1%
4 19
 
1.9%

지번주소
Text

MISSING 

Distinct373
Distinct (%)96.9%
Missing14
Missing (%)3.5%
Memory size3.2 KiB
2024-04-30T05:02:33.889780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length26.47013
Min length16

Characters and Unicode

Total characters10191
Distinct characters269
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

Unique361 ?
Unique (%)93.8%

Sample

1st row서울특별시 서초구 반포동 0번지 경남상가 502호 번지동 불명호
2nd row서울특별시 서초구 양재동 4-5번지
3rd row서울특별시 서초구 반포동 63-1 4층
4th row서울특별시 서초구 서초동 1337-14번지
5th row서울특별시 서초구 서초동 1336-1번지
ValueCountFrequency (%)
서울특별시 385
20.2%
서초구 385
20.2%
서초동 166
 
8.7%
방배동 78
 
4.1%
반포동 67
 
3.5%
지하1층 40
 
2.1%
양재동 34
 
1.8%
잠원동 26
 
1.4%
2층 18
 
0.9%
3층 15
 
0.8%
Other values (589) 693
36.3%
2024-04-30T05:02:34.248884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1775
17.4%
서 964
 
9.5%
초 572
 
5.6%
1 474
 
4.7%
동 408
 
4.0%
시 393
 
3.9%
구 388
 
3.8%
울 387
 
3.8%
특 385
 
3.8%
별 385
 
3.8%
Other values (259) 4060
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5951
58.4%
Decimal Number 1940
 
19.0%
Space Separator 1775
 
17.4%
Dash Punctuation 356
 
3.5%
Open Punctuation 48
 
0.5%
Close Punctuation 48
 
0.5%
Uppercase Letter 41
 
0.4%
Other Punctuation 23
 
0.2%
Lowercase Letter 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 964
16.2%
초 572
 
9.6%
동 408
 
6.9%
시 393
 
6.6%
구 388
 
6.5%
울 387
 
6.5%
특 385
 
6.5%
별 385
 
6.5%
지 280
 
4.7%
번 194
 
3.3%
Other values (215) 1595
26.8%
Uppercase Letter
ValueCountFrequency (%)
B 9
22.0%
E 6
14.6%
R 4
9.8%
N 2
 
4.9%
K 2
 
4.9%
O 2
 
4.9%
A 2
 
4.9%
L 2
 
4.9%
G 2
 
4.9%
M 1
 
2.4%
Other values (9) 9
22.0%
Decimal Number
ValueCountFrequency (%)
1 474
24.4%
3 240
12.4%
2 231
11.9%
5 180
 
9.3%
7 158
 
8.1%
4 154
 
7.9%
0 137
 
7.1%
6 133
 
6.9%
9 127
 
6.5%
8 106
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
s 2
25.0%
r 1
12.5%
o 1
12.5%
v 1
12.5%
e 1
12.5%
i 1
12.5%
f 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 21
91.3%
& 1
 
4.3%
@ 1
 
4.3%
Space Separator
ValueCountFrequency (%)
1775
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5951
58.4%
Common 4191
41.1%
Latin 49
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 964
16.2%
초 572
 
9.6%
동 408
 
6.9%
시 393
 
6.6%
구 388
 
6.5%
울 387
 
6.5%
특 385
 
6.5%
별 385
 
6.5%
지 280
 
4.7%
번 194
 
3.3%
Other values (215) 1595
26.8%
Latin
ValueCountFrequency (%)
B 9
18.4%
E 6
 
12.2%
R 4
 
8.2%
N 2
 
4.1%
K 2
 
4.1%
O 2
 
4.1%
A 2
 
4.1%
L 2
 
4.1%
G 2
 
4.1%
s 2
 
4.1%
Other values (16) 16
32.7%
Common
ValueCountFrequency (%)
1775
42.4%
1 474
 
11.3%
- 356
 
8.5%
3 240
 
5.7%
2 231
 
5.5%
5 180
 
4.3%
7 158
 
3.8%
4 154
 
3.7%
0 137
 
3.3%
6 133
 
3.2%
Other values (8) 353
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5951
58.4%
ASCII 4240
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1775
41.9%
1 474
 
11.2%
- 356
 
8.4%
3 240
 
5.7%
2 231
 
5.4%
5 180
 
4.2%
7 158
 
3.7%
4 154
 
3.6%
0 137
 
3.2%
6 133
 
3.1%
Other values (34) 402
 
9.5%
Hangul
ValueCountFrequency (%)
서 964
16.2%
초 572
 
9.6%
동 408
 
6.9%
시 393
 
6.6%
구 388
 
6.5%
울 387
 
6.5%
특 385
 
6.5%
별 385
 
6.5%
지 280
 
4.7%
번 194
 
3.3%
Other values (215) 1595
26.8%

도로명주소
Text

MISSING 

Distinct386
Distinct (%)97.7%
Missing4
Missing (%)1.0%
Memory size3.2 KiB
2024-04-30T05:02:34.494393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length45
Mean length33.898734
Min length22

Characters and Unicode

Total characters13390
Distinct characters278
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

Unique377 ?
Unique (%)95.4%

Sample

1st row서울특별시 서초구 논현로31길 15 (양재동)
2nd row서울특별시 서초구 사평대로 160 (반포동, 4층)
3rd row서울특별시 서초구 사임당로 178 (서초동)
4th row서울특별시 서초구 강남대로30길 65 (양재동)
5th row서울특별시 서초구 고무래로10길 17 (반포동)
ValueCountFrequency (%)
서울특별시 395
 
15.6%
서초구 395
 
15.6%
서초동 130
 
5.1%
지하1층 67
 
2.7%
방배동 66
 
2.6%
반포동 54
 
2.1%
2층 47
 
1.9%
강남대로 29
 
1.1%
3층 28
 
1.1%
양재동 24
 
1.0%
Other values (676) 1290
51.1%
2024-04-30T05:02:34.870537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2207
 
16.5%
서 1098
 
8.2%
초 670
 
5.0%
1 468
 
3.5%
동 450
 
3.4%
) 442
 
3.3%
( 442
 
3.3%
, 437
 
3.3%
시 404
 
3.0%
구 400
 
3.0%
Other values (268) 6372
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7873
58.8%
Space Separator 2207
 
16.5%
Decimal Number 1868
 
14.0%
Other Punctuation 443
 
3.3%
Close Punctuation 442
 
3.3%
Open Punctuation 442
 
3.3%
Uppercase Letter 58
 
0.4%
Dash Punctuation 43
 
0.3%
Lowercase Letter 10
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1098
 
13.9%
초 670
 
8.5%
동 450
 
5.7%
시 404
 
5.1%
구 400
 
5.1%
울 397
 
5.0%
로 395
 
5.0%
특 395
 
5.0%
별 395
 
5.0%
층 322
 
4.1%
Other values (222) 2947
37.4%
Uppercase Letter
ValueCountFrequency (%)
B 15
25.9%
E 7
12.1%
R 6
 
10.3%
O 3
 
5.2%
A 3
 
5.2%
G 3
 
5.2%
L 2
 
3.4%
N 2
 
3.4%
K 2
 
3.4%
W 2
 
3.4%
Other values (9) 13
22.4%
Decimal Number
ValueCountFrequency (%)
1 468
25.1%
2 311
16.6%
3 262
14.0%
4 173
 
9.3%
0 147
 
7.9%
5 137
 
7.3%
6 120
 
6.4%
7 110
 
5.9%
9 73
 
3.9%
8 67
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
s 2
20.0%
b 2
20.0%
i 1
10.0%
o 1
10.0%
r 1
10.0%
v 1
10.0%
e 1
10.0%
f 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 437
98.6%
& 3
 
0.7%
/ 2
 
0.5%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2207
100.0%
Close Punctuation
ValueCountFrequency (%)
) 442
100.0%
Open Punctuation
ValueCountFrequency (%)
( 442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7873
58.8%
Common 5449
40.7%
Latin 68
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1098
 
13.9%
초 670
 
8.5%
동 450
 
5.7%
시 404
 
5.1%
구 400
 
5.1%
울 397
 
5.0%
로 395
 
5.0%
특 395
 
5.0%
별 395
 
5.0%
층 322
 
4.1%
Other values (222) 2947
37.4%
Latin
ValueCountFrequency (%)
B 15
22.1%
E 7
 
10.3%
R 6
 
8.8%
O 3
 
4.4%
A 3
 
4.4%
G 3
 
4.4%
L 2
 
2.9%
N 2
 
2.9%
s 2
 
2.9%
b 2
 
2.9%
Other values (17) 23
33.8%
Common
ValueCountFrequency (%)
2207
40.5%
1 468
 
8.6%
) 442
 
8.1%
( 442
 
8.1%
, 437
 
8.0%
2 311
 
5.7%
3 262
 
4.8%
4 173
 
3.2%
0 147
 
2.7%
5 137
 
2.5%
Other values (9) 423
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7873
58.8%
ASCII 5517
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2207
40.0%
1 468
 
8.5%
) 442
 
8.0%
( 442
 
8.0%
, 437
 
7.9%
2 311
 
5.6%
3 262
 
4.7%
4 173
 
3.1%
0 147
 
2.7%
5 137
 
2.5%
Other values (36) 491
 
8.9%
Hangul
ValueCountFrequency (%)
서 1098
 
13.9%
초 670
 
8.5%
동 450
 
5.7%
시 404
 
5.1%
구 400
 
5.1%
울 397
 
5.0%
로 395
 
5.0%
특 395
 
5.0%
별 395
 
5.0%
층 322
 
4.1%
Other values (222) 2947
37.4%

도로명우편번호
Text

MISSING 

Distinct150
Distinct (%)51.9%
Missing110
Missing (%)27.6%
Memory size3.2 KiB
2024-04-30T05:02:35.170747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0484429
Min length5

Characters and Unicode

Total characters1459
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 (%)28.4%

Sample

1st row06578
2nd row06524
3rd row06762
4th row137832
5th row06629
ValueCountFrequency (%)
06593 10
 
3.5%
06604 9
 
3.1%
06577 8
 
2.8%
06611 6
 
2.1%
06627 6
 
2.1%
06626 6
 
2.1%
06621 5
 
1.7%
06765 5
 
1.7%
06584 5
 
1.7%
06734 5
 
1.7%
Other values (140) 224
77.5%
2024-04-30T05:02:35.586257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 452
31.0%
0 321
22.0%
5 163
 
11.2%
7 135
 
9.3%
3 76
 
5.2%
4 72
 
4.9%
1 71
 
4.9%
2 68
 
4.7%
8 66
 
4.5%
9 34
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1458
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 452
31.0%
0 321
22.0%
5 163
 
11.2%
7 135
 
9.3%
3 76
 
5.2%
4 72
 
4.9%
1 71
 
4.9%
2 68
 
4.7%
8 66
 
4.5%
9 34
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1459
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 452
31.0%
0 321
22.0%
5 163
 
11.2%
7 135
 
9.3%
3 76
 
5.2%
4 72
 
4.9%
1 71
 
4.9%
2 68
 
4.7%
8 66
 
4.5%
9 34
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 452
31.0%
0 321
22.0%
5 163
 
11.2%
7 135
 
9.3%
3 76
 
5.2%
4 72
 
4.9%
1 71
 
4.9%
2 68
 
4.7%
8 66
 
4.5%
9 34
 
2.3%

사업장명
Text

Distinct387
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-04-30T05:02:35.788552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.4260652
Min length1

Characters and Unicode

Total characters3362
Distinct characters377
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

Unique376 ?
Unique (%)94.2%

Sample

1st row한덕헬스
2nd row경안헬스
3rd row팔라티움 헬스클럽
4th row한국헬스
5th row우성헬스크럽
ValueCountFrequency (%)
pt 17
 
2.6%
피트니스 12
 
1.8%
gym 12
 
1.8%
휘트니스 11
 
1.7%
studio 9
 
1.4%
주식회사 8
 
1.2%
fitness 8
 
1.2%
짐 7
 
1.1%
서초점 7
 
1.1%
스튜디오 6
 
0.9%
Other values (472) 554
85.1%
2024-04-30T05:02:36.139009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
 
7.5%
스 245
 
7.3%
트 110
 
3.3%
짐 93
 
2.8%
이 91
 
2.7%
니 89
 
2.6%
T 52
 
1.5%
피 50
 
1.5%
( 50
 
1.5%
) 50
 
1.5%
Other values (367) 2280
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2419
72.0%
Uppercase Letter 310
 
9.2%
Space Separator 252
 
7.5%
Lowercase Letter 241
 
7.2%
Open Punctuation 50
 
1.5%
Close Punctuation 50
 
1.5%
Decimal Number 22
 
0.7%
Other Punctuation 16
 
0.5%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 245
 
10.1%
트 110
 
4.5%
짐 93
 
3.8%
이 91
 
3.8%
니 89
 
3.7%
피 50
 
2.1%
디 49
 
2.0%
휘 48
 
2.0%
헬 46
 
1.9%
포 45
 
1.9%
Other values (303) 1553
64.2%
Uppercase Letter
ValueCountFrequency (%)
T 52
16.8%
P 32
 
10.3%
M 21
 
6.8%
G 21
 
6.8%
S 19
 
6.1%
O 16
 
5.2%
A 14
 
4.5%
F 14
 
4.5%
Y 13
 
4.2%
N 13
 
4.2%
Other values (13) 95
30.6%
Lowercase Letter
ValueCountFrequency (%)
e 29
12.0%
t 25
10.4%
i 24
10.0%
a 19
 
7.9%
s 18
 
7.5%
y 18
 
7.5%
m 14
 
5.8%
n 14
 
5.8%
o 13
 
5.4%
r 12
 
5.0%
Other values (13) 55
22.8%
Decimal Number
ValueCountFrequency (%)
2 5
22.7%
4 4
18.2%
3 3
13.6%
9 2
 
9.1%
6 2
 
9.1%
5 2
 
9.1%
0 2
 
9.1%
7 1
 
4.5%
1 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
& 10
62.5%
. 4
 
25.0%
, 1
 
6.2%
' 1
 
6.2%
Space Separator
ValueCountFrequency (%)
252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2419
72.0%
Latin 551
 
16.4%
Common 392
 
11.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 245
 
10.1%
트 110
 
4.5%
짐 93
 
3.8%
이 91
 
3.8%
니 89
 
3.7%
피 50
 
2.1%
디 49
 
2.0%
휘 48
 
2.0%
헬 46
 
1.9%
포 45
 
1.9%
Other values (303) 1553
64.2%
Latin
ValueCountFrequency (%)
T 52
 
9.4%
P 32
 
5.8%
e 29
 
5.3%
t 25
 
4.5%
i 24
 
4.4%
M 21
 
3.8%
G 21
 
3.8%
S 19
 
3.4%
a 19
 
3.4%
s 18
 
3.3%
Other values (36) 291
52.8%
Common
ValueCountFrequency (%)
252
64.3%
( 50
 
12.8%
) 50
 
12.8%
& 10
 
2.6%
2 5
 
1.3%
. 4
 
1.0%
4 4
 
1.0%
3 3
 
0.8%
9 2
 
0.5%
6 2
 
0.5%
Other values (8) 10
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2419
72.0%
ASCII 943
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
26.7%
T 52
 
5.5%
( 50
 
5.3%
) 50
 
5.3%
P 32
 
3.4%
e 29
 
3.1%
t 25
 
2.7%
i 24
 
2.5%
M 21
 
2.2%
G 21
 
2.2%
Other values (54) 387
41.0%
Hangul
ValueCountFrequency (%)
스 245
 
10.1%
트 110
 
4.5%
짐 93
 
3.8%
이 91
 
3.8%
니 89
 
3.7%
피 50
 
2.1%
디 49
 
2.0%
휘 48
 
2.0%
헬 46
 
1.9%
포 45
 
1.9%
Other values (303) 1553
64.2%

최종수정일자
Date

Distinct388
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2003-04-18 11:31:26
Maximum2024-04-12 14:40:56
2024-04-30T05:02:36.268473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:36.389208image/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 size3.2 KiB
I
262 
U
137 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 262
65.7%
U 137
34.3%

Length

2024-04-30T05:02:36.496664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:36.583803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 262
65.7%
u 137
34.3%

데이터갱신일자
Date

Distinct195
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:05:00
2024-04-30T05:02:36.681604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:36.792961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct339
Distinct (%)85.8%
Missing4
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean201108.38
Minimum198363.71
Maximum205120.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-04-30T05:02:36.926183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198363.71
5-th percentile198629.99
Q1199923.11
median201203.9
Q3202029.75
95-th percentile203424.23
Maximum205120.92
Range6757.2183
Interquartile range (IQR)2106.6372

Descriptive statistics

Standard deviation1419.9311
Coefficient of variation (CV)0.0070605266
Kurtosis-0.50821115
Mean201108.38
Median Absolute Deviation (MAD)971.11412
Skewness-0.064262876
Sum79437811
Variance2016204.3
MonotonicityNot monotonic
2024-04-30T05:02:37.227254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203384.79785484 4
 
1.0%
202463.85950988 3
 
0.8%
200826.536579375 3
 
0.8%
201111.079996085 3
 
0.8%
200554.74395758 3
 
0.8%
200975.310832194 3
 
0.8%
200852.048235135 3
 
0.8%
201600.394681612 2
 
0.5%
202144.075280951 2
 
0.5%
200982.169900218 2
 
0.5%
Other values (329) 367
92.0%
(Missing) 4
 
1.0%
ValueCountFrequency (%)
198363.705516537 1
0.3%
198367.956597525 1
0.3%
198381.147316283 1
0.3%
198397.235721331 1
0.3%
198410.072816565 1
0.3%
198416.687503983 1
0.3%
198420.529183765 1
0.3%
198426.66111184 1
0.3%
198432.354182494 2
0.5%
198448.680593311 1
0.3%
ValueCountFrequency (%)
205120.923862932 1
0.3%
204783.612470826 1
0.3%
204300.78 1
0.3%
203993.98 1
0.3%
203982.973731284 1
0.3%
203974.61962955 1
0.3%
203964.834475805 1
0.3%
203945.698700178 1
0.3%
203916.155701646 1
0.3%
203891.041008756 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct339
Distinct (%)85.8%
Missing4
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean443289.48
Minimum438520.18
Maximum446268.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-04-30T05:02:37.345152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438520.18
5-th percentile441018.14
Q1442567.51
median443343.53
Q3444034.12
95-th percentile445288.29
Maximum446268.29
Range7748.1123
Interquartile range (IQR)1466.6074

Descriptive statistics

Standard deviation1231.3103
Coefficient of variation (CV)0.0027776664
Kurtosis0.67290601
Mean443289.48
Median Absolute Deviation (MAD)741.44705
Skewness-0.35961423
Sum1.7509934 × 108
Variance1516125
MonotonicityNot monotonic
2024-04-30T05:02:37.461903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441844.122817435 4
 
1.0%
443356.365859457 3
 
0.8%
444530.367230862 3
 
0.8%
443819.491553551 3
 
0.8%
444811.364826199 3
 
0.8%
445119.999988057 3
 
0.8%
444335.617955668 3
 
0.8%
444038.762540109 2
 
0.5%
440208.843928869 2
 
0.5%
444468.719796887 2
 
0.5%
Other values (329) 367
92.0%
(Missing) 4
 
1.0%
ValueCountFrequency (%)
438520.182013694 1
0.3%
439363.863225029 1
0.3%
439432.045983233 1
0.3%
440136.781183797 1
0.3%
440208.843928869 2
0.5%
440329.694574605 1
0.3%
440383.505965875 2
0.5%
440481.666297089 1
0.3%
440511.561175378 1
0.3%
440538.66418347 1
0.3%
ValueCountFrequency (%)
446268.294338007 1
0.3%
446069.805589775 1
0.3%
445971.21278915 2
0.5%
445960.835289042 1
0.3%
445925.192925207 1
0.3%
445923.541778857 1
0.3%
445905.630636194 1
0.3%
445706.12537466 1
0.3%
445650.137597016 1
0.3%
445612.182605594 1
0.3%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
체력단련장업
267 
<NA>
132 

Length

Max length6
Median length6
Mean length5.3383459
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 267
66.9%
<NA> 132
33.1%

Length

2024-04-30T05:02:37.596578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:37.700328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 267
66.9%
na 132
33.1%

공사립구분명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
사립
267 
<NA>
132 

Length

Max length4
Median length2
Mean length2.6616541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 267
66.9%
<NA> 132
33.1%

Length

2024-04-30T05:02:37.797729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:37.885547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 267
66.9%
na 132
33.1%

보험가입여부코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
371 
0
 
27
Y
 
1

Length

Max length4
Median length4
Mean length3.7894737
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 371
93.0%
0 27
 
6.8%
Y 1
 
0.3%

Length

2024-04-30T05:02:37.992043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:38.090004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 371
93.0%
0 27
 
6.8%
y 1
 
0.3%

지도자수
Categorical

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
242 
1
96 
0
33 
2
28 

Length

Max length4
Median length4
Mean length2.8195489
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 242
60.7%
1 96
 
24.1%
0 33
 
8.3%
2 28
 
7.0%

Length

2024-04-30T05:02:38.194394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:38.283018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 242
60.7%
1 96
 
24.1%
0 33
 
8.3%
2 28
 
7.0%

건축물동수
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
325 
1
39 
0
35 

Length

Max length4
Median length4
Mean length3.443609
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 325
81.5%
1 39
 
9.8%
0 35
 
8.8%

Length

2024-04-30T05:02:38.377564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:38.466295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 325
81.5%
1 39
 
9.8%
0 35
 
8.8%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct53
Distinct (%)58.9%
Missing309
Missing (%)77.4%
Infinite0
Infinite (%)0.0%
Mean3856.904
Minimum0
Maximum104468
Zeros36
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-04-30T05:02:38.584709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median816.16
Q32964.585
95-th percentile10972.012
Maximum104468
Range104468
Interquartile range (IQR)2964.585

Descriptive statistics

Standard deviation12158.287
Coefficient of variation (CV)3.1523436
Kurtosis54.454846
Mean3856.904
Median Absolute Deviation (MAD)816.16
Skewness6.9209337
Sum347121.36
Variance1.4782394 × 108
MonotonicityNot monotonic
2024-04-30T05:02:38.708377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 36
 
9.0%
3526.38 3
 
0.8%
2569.76 1
 
0.3%
2865.3 1
 
0.3%
4572.68 1
 
0.3%
1579.36 1
 
0.3%
4172.11 1
 
0.3%
2678.56 1
 
0.3%
644.8 1
 
0.3%
8617.13 1
 
0.3%
Other values (43) 43
 
10.8%
(Missing) 309
77.4%
ValueCountFrequency (%)
0.0 36
9.0%
456.4 1
 
0.3%
501.56 1
 
0.3%
533.57 1
 
0.3%
604.8 1
 
0.3%
644.8 1
 
0.3%
653.0 1
 
0.3%
727.72 1
 
0.3%
805.6 1
 
0.3%
806.13 1
 
0.3%
ValueCountFrequency (%)
104468.0 1
0.3%
40043.8 1
0.3%
29482.62 1
0.3%
14317.77 1
0.3%
11405.79 1
0.3%
10441.84 1
0.3%
9665.14 1
0.3%
9662.41 1
0.3%
8617.13 1
0.3%
6809.5 1
0.3%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
374 
0
 
25

Length

Max length4
Median length4
Mean length3.8120301
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> 374
93.7%
0 25
 
6.3%

Length

2024-04-30T05:02:38.826476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:38.910051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 374
93.7%
0 25
 
6.3%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing399
Missing (%)100.0%
Memory size3.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03210000CDFH330106198900000119891218<NA>3폐업3폐업20001231<NA><NA><NA>503-5583<NA>137040서울특별시 서초구 반포동 0번지 경남상가 502호 번지동 불명호<NA><NA>한덕헬스2014-04-16 10:45:18I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립<NA>000.0<NA><NA><NA>
13210000CDFH330106198900000219891226<NA>3폐업3폐업20060504<NA><NA><NA>576-4891<NA>137886서울특별시 서초구 양재동 4-5번지서울특별시 서초구 논현로31길 15 (양재동)<NA>경안헬스2006-05-04 13:56:43I2018-08-31 23:59:59.0<NA>203659.766489442182.9184체력단련장업사립01<NA><NA><NA><NA><NA>
23210000CDFH330106199000000119900105<NA>3폐업3폐업20210303<NA><NA><NA>532-0101<NA>137804서울특별시 서초구 반포동 63-1 4층서울특별시 서초구 사평대로 160 (반포동, 4층)06578팔라티움 헬스클럽2021-03-03 14:15:15U2021-03-05 02:40:00.0<NA>200148.908813444359.607819체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
33210000CDFH330106199000000219900214<NA>3폐업3폐업20030521<NA><NA><NA>507-4215<NA>137860서울특별시 서초구 서초동 1337-14번지서울특별시 서초구 사임당로 178 (서초동)<NA>한국헬스2004-01-30 14:59:50I2018-08-31 23:59:59.0<NA>202503.871647443326.129565체력단련장업사립0<NA><NA><NA><NA><NA><NA>
43210000CDFH330106199100000119910708<NA>3폐업3폐업19990501<NA><NA><NA>562-1230<NA>137859서울특별시 서초구 서초동 1336-1번지<NA><NA>우성헬스크럽2014-04-16 10:45:18I2018-08-31 23:59:59.0<NA>202375.747328443293.000122체력단련장업사립<NA>000.0<NA><NA><NA>
53210000CDFH330106199100000219910809<NA>3폐업3폐업20000630<NA><NA><NA>573-3611<NA>137886서울특별시 서초구 양재동 7-61번지서울특별시 서초구 강남대로30길 65 (양재동)<NA>뉴보디2003-04-18 11:31:26I2018-08-31 23:59:59.0<NA>203531.794722442291.93105체력단련장업사립<NA>000.0<NA><NA><NA>
63210000CDFH330106199300000119930210<NA>1영업/정상13영업중<NA><NA><NA><NA>586-3558<NA>137875서울특별시 서초구 서초동 1577-49번지<NA><NA>금성헬스2017-11-01 11:20:46I2018-08-31 23:59:59.0<NA><NA><NA>체력단련장업사립<NA><NA><NA><NA><NA><NA><NA>
73210000CDFH330106199300000219930312<NA>3폐업3폐업19990501<NA><NA><NA>593-5900<NA>137803서울특별시 서초구 반포동 53-3번지서울특별시 서초구 고무래로10길 17 (반포동)<NA>(주)동호레포츠2003-04-18 11:31:26I2018-08-31 23:59:59.0<NA>200852.048235444335.617956체력단련장업사립<NA>000.0<NA><NA><NA>
83210000CDFH330106199400000119940120<NA>3폐업3폐업20000402<NA><NA><NA>576-0629<NA>137898서울특별시 서초구 양재동 365번지서울특별시 서초구 강남대로6길 108-4 (양재동)<NA>건희헬스2003-04-18 11:31:26I2018-08-31 23:59:59.0<NA>203982.973731440836.878317체력단련장업사립<NA>000.0<NA><NA><NA>
93210000CDFH330106199400000219940609<NA>3폐업3폐업19980608<NA><NA><NA><NA><NA>137876서울특별시 서초구 서초동 1599-11번지서울특별시 서초구 서초중앙로 63 (서초동)<NA>리더스헬스타운2003-04-18 11:31:26I2018-08-31 23:59:59.0<NA>201208.493843442790.939502체력단련장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
3893210000CDFH33010620230000272023-11-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1365-8서울특별시 서초구 남부순환로 2567, 지하2층 (서초동)06734휘트니스엠2023-11-24 10:23:57I2022-10-31 22:06:00.0<NA>202677.564388442497.656361<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3903210000CDFH33010620230000282023-11-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 97-10 97-10 트윈빌서울특별시 서초구 서래로1길 8, 97-10 트윈빌 지하2층 (반포동)06581아워피트니스2023-11-29 09:11:23I2022-11-02 00:01:00.0<NA>199732.294384443784.487525<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3913210000CDFH33010620230000292023-12-04<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8883-3338<NA><NA>서울특별시 서초구 잠원동 103 반포역서울특별시 서초구 신반포로 지하 241, 반포역 (잠원동)06521FIT.Covery핏커버리2023-12-04 09:45:27I2022-11-02 00:06:00.0<NA>200975.310832445119.999988<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3923210000CDFH33010620230000302023-12-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 913-8서울특별시 서초구 효령로27길 20, 2층 (방배동)06685모브핏(Mauve Fit)2023-12-06 10:31:07I2022-11-02 00:08:00.0<NA>199501.844241442176.570853<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3933210000CDFH33010620230000312023-12-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 577-39서울특별시 서초구 동광로46길 3, 1층 (반포동)06589바른길 PT STUDIO2023-12-15 09:05:02I2022-11-01 23:07:00.0<NA>200004.913741443559.71522<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3943210000CDFH33010620230000322023-12-22<NA>1영업/정상13영업중<NA><NA><NA><NA>02-596-9655<NA><NA>서울특별시 서초구 반포동 92-1서울특별시 서초구 서래로 48, 3층 (반포동)06577서래 퍼스널 트레이닝2023-12-22 09:59:43I2022-11-01 22:04:00.0<NA>199798.194419444116.167594<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3953210000CDFH33010620240000012024-02-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 723-1 도충빌딩서울특별시 서초구 강남대로 519, 도충빌딩 (반포동)06536아우라짐 논현역점2024-02-19 10:04:47I2023-12-01 22:01:00.0<NA>201881.527134445123.695283<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3963210000CDFH33010620240000022024-02-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 720-15서울특별시 서초구 사평대로53길 94 (반포동)06537AL피트니스2024-02-27 16:32:10I2023-12-01 22:09:00.0<NA>201722.926044445129.543833<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3973210000CDFH33010620240000032024-03-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 935-40 텔콤빌딩 내방서울특별시 서초구 방배로 141, 텔콤빌딩 내방 (방배동)06672아워피트니스 내방점2024-03-11 15:25:14U2023-12-02 23:03:00.0<NA>199409.926292442690.093729<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3983210000CDFH33010620240000042024-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 서초동 1364-39 지훈빌딩서울특별시 서초구 서운로6길 26, 지훈빌딩 지하1층 (서초동)06734인사이트 그룹PT 양재역점2024-04-12 14:40:56I2023-12-03 23:05:00.0<NA>202654.181046442602.079075<NA><NA><NA><NA><NA><NA><NA><NA><NA>