Overview

Dataset statistics

Number of variables34
Number of observations161
Missing cells1736
Missing cells (%)31.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.9 KiB
Average record size in memory291.8 B

Variable types

Categorical12
Text6
DateTime4
Unsupported8
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-19871/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
보험가입여부코드 is highly imbalanced (51.4%)Imbalance
건축물동수 is highly imbalanced (55.4%)Imbalance
회원모집총인원 is highly imbalanced (78.6%)Imbalance
인허가취소일자 has 161 (100.0%) missing valuesMissing
폐업일자 has 99 (61.5%) missing valuesMissing
휴업시작일자 has 161 (100.0%) missing valuesMissing
휴업종료일자 has 161 (100.0%) missing valuesMissing
재개업일자 has 161 (100.0%) missing valuesMissing
전화번호 has 57 (35.4%) missing valuesMissing
소재지면적 has 161 (100.0%) missing valuesMissing
소재지우편번호 has 118 (73.3%) missing valuesMissing
도로명주소 has 8 (5.0%) missing valuesMissing
도로명우편번호 has 31 (19.3%) missing valuesMissing
업태구분명 has 161 (100.0%) missing valuesMissing
좌표정보(X) has 3 (1.9%) missing valuesMissing
좌표정보(Y) has 3 (1.9%) missing valuesMissing
건축물연면적 has 128 (79.5%) missing valuesMissing
세부업종명 has 161 (100.0%) missing valuesMissing
법인명 has 161 (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 11 (6.8%) zerosZeros

Reproduction

Analysis started2024-04-29 20:02:04.210585
Analysis finished2024-04-29 20:02:04.966048
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3190000
161 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 161
100.0%

Length

2024-04-30T05:02:05.028787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:05.125429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 161
100.0%

관리번호
Text

UNIQUE 

Distinct161
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-30T05:02:05.268984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters3220
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

Unique161 ?
Unique (%)100.0%

Sample

1st rowCDFH3301061989000001
2nd rowCDFH3301061989000002
3rd rowCDFH3301061989000003
4th rowCDFH3301061993000001
5th rowCDFH3301061994000001
ValueCountFrequency (%)
cdfh3301061989000001 1
 
0.6%
cdfh3301062015000001 1
 
0.6%
cdfh3301062019000005 1
 
0.6%
cdfh3301062018000005 1
 
0.6%
cdfh3301062018000006 1
 
0.6%
cdfh3301062018000007 1
 
0.6%
cdfh3301062019000001 1
 
0.6%
cdfh3301062019000002 1
 
0.6%
cdfh3301062019000003 1
 
0.6%
cdfh3301062019000004 1
 
0.6%
Other values (151) 151
93.8%
2024-04-30T05:02:05.540884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1319
41.0%
3 365
 
11.3%
1 293
 
9.1%
2 245
 
7.6%
6 185
 
5.7%
C 161
 
5.0%
D 161
 
5.0%
F 161
 
5.0%
H 161
 
5.0%
9 61
 
1.9%
Other values (4) 108
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2576
80.0%
Uppercase Letter 644
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1319
51.2%
3 365
 
14.2%
1 293
 
11.4%
2 245
 
9.5%
6 185
 
7.2%
9 61
 
2.4%
4 41
 
1.6%
8 23
 
0.9%
5 23
 
0.9%
7 21
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 161
25.0%
D 161
25.0%
F 161
25.0%
H 161
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2576
80.0%
Latin 644
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1319
51.2%
3 365
 
14.2%
1 293
 
11.4%
2 245
 
9.5%
6 185
 
7.2%
9 61
 
2.4%
4 41
 
1.6%
8 23
 
0.9%
5 23
 
0.9%
7 21
 
0.8%
Latin
ValueCountFrequency (%)
C 161
25.0%
D 161
25.0%
F 161
25.0%
H 161
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1319
41.0%
3 365
 
11.3%
1 293
 
9.1%
2 245
 
7.6%
6 185
 
5.7%
C 161
 
5.0%
D 161
 
5.0%
F 161
 
5.0%
H 161
 
5.0%
9 61
 
1.9%
Other values (4) 108
 
3.4%

인허가일자
Date

Distinct157
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1989-12-13 00:00:00
Maximum2024-03-19 00:00:00
2024-04-30T05:02:05.681411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:05.824897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
1
99 
3
53 
4
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 99
61.5%
3 53
32.9%
4 9
 
5.6%

Length

2024-04-30T05:02:05.947507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:06.051780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 99
61.5%
3 53
32.9%
4 9
 
5.6%

영업상태명
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
영업/정상
99 
폐업
53 
취소/말소/만료/정지/중지
 
9

Length

Max length14
Median length5
Mean length4.515528
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 99
61.5%
폐업 53
32.9%
취소/말소/만료/정지/중지 9
 
5.6%

Length

2024-04-30T05:02:06.157117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:06.244906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 99
61.5%
폐업 53
32.9%
취소/말소/만료/정지/중지 9
 
5.6%

상세영업상태코드
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
13
99 
3
53 
35
 
9

Length

Max length2
Median length2
Mean length1.6708075
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 99
61.5%
3 53
32.9%
35 9
 
5.6%

Length

2024-04-30T05:02:06.336235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:06.432232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 99
61.5%
3 53
32.9%
35 9
 
5.6%

상세영업상태명
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
영업중
99 
폐업
53 
직권말소
 
9

Length

Max length4
Median length3
Mean length2.7267081
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 99
61.5%
폐업 53
32.9%
직권말소 9
 
5.6%

Length

2024-04-30T05:02:06.541426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:06.641541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 99
61.5%
폐업 53
32.9%
직권말소 9
 
5.6%

폐업일자
Date

MISSING 

Distinct57
Distinct (%)91.9%
Missing99
Missing (%)61.5%
Memory size1.4 KiB
Minimum1999-12-31 00:00:00
Maximum2024-02-14 00:00:00
2024-04-30T05:02:06.746689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:06.861693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct100
Distinct (%)96.2%
Missing57
Missing (%)35.4%
Memory size1.4 KiB
2024-04-30T05:02:07.111428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length9.25
Min length8

Characters and Unicode

Total characters962
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

Unique96 ?
Unique (%)92.3%

Sample

1st row815-7769
2nd row816-2547
3rd row821-3000
4th row595-8000
5th row583-0442
ValueCountFrequency (%)
596-0265 2
 
1.9%
02-814-9628 2
 
1.9%
821-7515 2
 
1.9%
904-8606 2
 
1.9%
02-848-8484 1
 
1.0%
02-3280-8296 1
 
1.0%
02-3280-1255 1
 
1.0%
02-848-9696 1
 
1.0%
3280-9998 1
 
1.0%
02-592-1555 1
 
1.0%
Other values (90) 90
86.5%
2024-04-30T05:02:07.465785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 138
14.3%
8 133
13.8%
2 131
13.6%
0 115
12.0%
5 91
9.5%
1 82
8.5%
4 59
6.1%
6 56
5.8%
9 55
 
5.7%
3 53
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 824
85.7%
Dash Punctuation 138
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 133
16.1%
2 131
15.9%
0 115
14.0%
5 91
11.0%
1 82
10.0%
4 59
7.2%
6 56
6.8%
9 55
6.7%
3 53
 
6.4%
7 49
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 962
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 138
14.3%
8 133
13.8%
2 131
13.6%
0 115
12.0%
5 91
9.5%
1 82
8.5%
4 59
6.1%
6 56
5.8%
9 55
 
5.7%
3 53
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 138
14.3%
8 133
13.8%
2 131
13.6%
0 115
12.0%
5 91
9.5%
1 82
8.5%
4 59
6.1%
6 56
5.8%
9 55
 
5.7%
3 53
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Text

MISSING 

Distinct30
Distinct (%)69.8%
Missing118
Missing (%)73.3%
Memory size1.4 KiB
2024-04-30T05:02:07.644218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0465116
Min length6

Characters and Unicode

Total characters260
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

Unique21 ?
Unique (%)48.8%

Sample

1st row156060
2nd row156811
3rd row156823
4th row156815
5th row156847
ValueCountFrequency (%)
156847 4
 
9.3%
156824 3
 
7.0%
156816 3
 
7.0%
156080 2
 
4.7%
156827 2
 
4.7%
156853 2
 
4.7%
156060 2
 
4.7%
156860 2
 
4.7%
156843 2
 
4.7%
156881 1
 
2.3%
Other values (20) 20
46.5%
2024-04-30T05:02:07.899755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 59
22.7%
6 53
20.4%
5 48
18.5%
8 41
15.8%
0 16
 
6.2%
4 10
 
3.8%
7 10
 
3.8%
3 9
 
3.5%
2 8
 
3.1%
9 4
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
99.2%
Dash Punctuation 2
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 59
22.9%
6 53
20.5%
5 48
18.6%
8 41
15.9%
0 16
 
6.2%
4 10
 
3.9%
7 10
 
3.9%
3 9
 
3.5%
2 8
 
3.1%
9 4
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 59
22.7%
6 53
20.4%
5 48
18.5%
8 41
15.8%
0 16
 
6.2%
4 10
 
3.8%
7 10
 
3.8%
3 9
 
3.5%
2 8
 
3.1%
9 4
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 59
22.7%
6 53
20.4%
5 48
18.5%
8 41
15.8%
0 16
 
6.2%
4 10
 
3.8%
7 10
 
3.8%
3 9
 
3.5%
2 8
 
3.1%
9 4
 
1.5%

지번주소
Text

Distinct157
Distinct (%)98.1%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2024-04-30T05:02:08.180937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length25.16875
Min length17

Characters and Unicode

Total characters4027
Distinct characters131
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

Unique154 ?
Unique (%)96.2%

Sample

1st row서울특별시 동작구 노량진동 312-43번지
2nd row서울특별시 동작구 본동 400-0번지
3rd row서울특별시 동작구 대방동 400-5번지
4th row서울특별시 동작구 사당동 136-1 7층
5th row서울특별시 동작구 사당동 318-13번지
ValueCountFrequency (%)
서울특별시 160
20.9%
동작구 160
20.9%
사당동 40
 
5.2%
상도동 30
 
3.9%
신대방동 24
 
3.1%
대방동 21
 
2.7%
노량진동 21
 
2.7%
흑석동 13
 
1.7%
3층 10
 
1.3%
2층 10
 
1.3%
Other values (230) 276
36.1%
2024-04-30T05:02:08.616183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
699
17.4%
동 336
 
8.3%
작 165
 
4.1%
1 162
 
4.0%
서 161
 
4.0%
시 161
 
4.0%
특 160
 
4.0%
구 160
 
4.0%
울 160
 
4.0%
별 160
 
4.0%
Other values (121) 1703
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2354
58.5%
Decimal Number 802
 
19.9%
Space Separator 699
 
17.4%
Dash Punctuation 139
 
3.5%
Uppercase Letter 11
 
0.3%
Close Punctuation 8
 
0.2%
Open Punctuation 8
 
0.2%
Other Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 336
14.3%
작 165
 
7.0%
서 161
 
6.8%
시 161
 
6.8%
특 160
 
6.8%
구 160
 
6.8%
울 160
 
6.8%
별 160
 
6.8%
지 100
 
4.2%
번 83
 
3.5%
Other values (100) 708
30.1%
Decimal Number
ValueCountFrequency (%)
1 162
20.2%
2 113
14.1%
3 101
12.6%
0 87
10.8%
5 77
9.6%
4 75
9.4%
7 52
 
6.5%
6 48
 
6.0%
8 47
 
5.9%
9 40
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
A 4
36.4%
P 1
 
9.1%
T 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
699
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2354
58.5%
Common 1662
41.3%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 336
14.3%
작 165
 
7.0%
서 161
 
6.8%
시 161
 
6.8%
특 160
 
6.8%
구 160
 
6.8%
울 160
 
6.8%
별 160
 
6.8%
지 100
 
4.2%
번 83
 
3.5%
Other values (100) 708
30.1%
Common
ValueCountFrequency (%)
699
42.1%
1 162
 
9.7%
- 139
 
8.4%
2 113
 
6.8%
3 101
 
6.1%
0 87
 
5.2%
5 77
 
4.6%
4 75
 
4.5%
7 52
 
3.1%
6 48
 
2.9%
Other values (7) 109
 
6.6%
Latin
ValueCountFrequency (%)
B 5
45.5%
A 4
36.4%
P 1
 
9.1%
T 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2354
58.5%
ASCII 1673
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
699
41.8%
1 162
 
9.7%
- 139
 
8.3%
2 113
 
6.8%
3 101
 
6.0%
0 87
 
5.2%
5 77
 
4.6%
4 75
 
4.5%
7 52
 
3.1%
6 48
 
2.9%
Other values (11) 120
 
7.2%
Hangul
ValueCountFrequency (%)
동 336
14.3%
작 165
 
7.0%
서 161
 
6.8%
시 161
 
6.8%
특 160
 
6.8%
구 160
 
6.8%
울 160
 
6.8%
별 160
 
6.8%
지 100
 
4.2%
번 83
 
3.5%
Other values (100) 708
30.1%

도로명주소
Text

MISSING 

Distinct150
Distinct (%)98.0%
Missing8
Missing (%)5.0%
Memory size1.4 KiB
2024-04-30T05:02:08.907918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length32.712418
Min length23

Characters and Unicode

Total characters5005
Distinct characters162
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

Unique147 ?
Unique (%)96.1%

Sample

1st row서울특별시 동작구 장승배기로17길 1 (노량진동)
2nd row서울특별시 동작구 노량진로 228 (본동)
3rd row서울특별시 동작구 동작대로 115, 7층 (사당동)
4th row서울특별시 동작구 사당로16길 7 (사당동)
5th row서울특별시 동작구 동작대로29길 69 (사당동,5층)
ValueCountFrequency (%)
서울특별시 153
 
15.9%
동작구 153
 
15.9%
사당동 33
 
3.4%
상도동 28
 
2.9%
상도로 24
 
2.5%
신대방동 20
 
2.1%
대방동 20
 
2.1%
노량진동 20
 
2.1%
3층 14
 
1.5%
2층 14
 
1.5%
Other values (279) 484
50.3%
2024-04-30T05:02:09.259184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
831
 
16.6%
동 352
 
7.0%
작 182
 
3.6%
, 166
 
3.3%
서 162
 
3.2%
1 159
 
3.2%
) 158
 
3.2%
( 158
 
3.2%
시 157
 
3.1%
울 153
 
3.1%
Other values (152) 2527
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2967
59.3%
Space Separator 831
 
16.6%
Decimal Number 695
 
13.9%
Other Punctuation 166
 
3.3%
Close Punctuation 158
 
3.2%
Open Punctuation 158
 
3.2%
Uppercase Letter 15
 
0.3%
Math Symbol 8
 
0.2%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 352
 
11.9%
작 182
 
6.1%
서 162
 
5.5%
시 157
 
5.3%
울 153
 
5.2%
구 153
 
5.2%
별 153
 
5.2%
특 153
 
5.2%
로 146
 
4.9%
층 103
 
3.5%
Other values (132) 1253
42.2%
Decimal Number
ValueCountFrequency (%)
1 159
22.9%
2 135
19.4%
3 83
11.9%
5 59
 
8.5%
0 54
 
7.8%
4 52
 
7.5%
6 48
 
6.9%
9 36
 
5.2%
7 36
 
5.2%
8 33
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 10
66.7%
A 3
 
20.0%
T 1
 
6.7%
P 1
 
6.7%
Space Separator
ValueCountFrequency (%)
831
100.0%
Other Punctuation
ValueCountFrequency (%)
, 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2967
59.3%
Common 2023
40.4%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 352
 
11.9%
작 182
 
6.1%
서 162
 
5.5%
시 157
 
5.3%
울 153
 
5.2%
구 153
 
5.2%
별 153
 
5.2%
특 153
 
5.2%
로 146
 
4.9%
층 103
 
3.5%
Other values (132) 1253
42.2%
Common
ValueCountFrequency (%)
831
41.1%
, 166
 
8.2%
1 159
 
7.9%
) 158
 
7.8%
( 158
 
7.8%
2 135
 
6.7%
3 83
 
4.1%
5 59
 
2.9%
0 54
 
2.7%
4 52
 
2.6%
Other values (6) 168
 
8.3%
Latin
ValueCountFrequency (%)
B 10
66.7%
A 3
 
20.0%
T 1
 
6.7%
P 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2967
59.3%
ASCII 2038
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
831
40.8%
, 166
 
8.1%
1 159
 
7.8%
) 158
 
7.8%
( 158
 
7.8%
2 135
 
6.6%
3 83
 
4.1%
5 59
 
2.9%
0 54
 
2.6%
4 52
 
2.6%
Other values (10) 183
 
9.0%
Hangul
ValueCountFrequency (%)
동 352
 
11.9%
작 182
 
6.1%
서 162
 
5.5%
시 157
 
5.3%
울 153
 
5.2%
구 153
 
5.2%
별 153
 
5.2%
특 153
 
5.2%
로 146
 
4.9%
층 103
 
3.5%
Other values (132) 1253
42.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)48.5%
Missing31
Missing (%)19.3%
Infinite0
Infinite (%)0.0%
Mean8143.9923
Minimum6904
Maximum156859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:02:09.378238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6904
5-th percentile6913
Q16942.25
median6999
Q37040
95-th percentile7071
Maximum156859
Range149955
Interquartile range (IQR)97.75

Descriptive statistics

Standard deviation13144.385
Coefficient of variation (CV)1.6139978
Kurtosis129.99569
Mean8143.9923
Median Absolute Deviation (MAD)46
Skewness11.401473
Sum1058719
Variance1.7277487 × 108
MonotonicityNot monotonic
2024-04-30T05:02:09.494625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7071 6
 
3.7%
7008 6
 
3.7%
6913 5
 
3.1%
7014 5
 
3.1%
7055 5
 
3.1%
6922 4
 
2.5%
7040 4
 
2.5%
7013 4
 
2.5%
7004 4
 
2.5%
6914 3
 
1.9%
Other values (53) 84
52.2%
(Missing) 31
 
19.3%
ValueCountFrequency (%)
6904 1
 
0.6%
6906 1
 
0.6%
6910 1
 
0.6%
6913 5
3.1%
6914 3
1.9%
6917 1
 
0.6%
6919 2
 
1.2%
6921 3
1.9%
6922 4
2.5%
6924 3
1.9%
ValueCountFrequency (%)
156859 1
 
0.6%
7072 3
1.9%
7071 6
3.7%
7069 3
1.9%
7065 3
1.9%
7064 1
 
0.6%
7061 1
 
0.6%
7060 1
 
0.6%
7059 1
 
0.6%
7055 5
3.1%

사업장명
Text

Distinct160
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-04-30T05:02:09.717845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length7.6149068
Min length2

Characters and Unicode

Total characters1226
Distinct characters249
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

Unique159 ?
Unique (%)98.8%

Sample

1st row강남
2nd row88헬스크럽
3rd row정우헬스
4th row태평
5th row국화
ValueCountFrequency (%)
휘트니스 18
 
6.7%
gym 7
 
2.6%
피트니스 7
 
2.6%
pt 6
 
2.2%
헬스 4
 
1.5%
studio 4
 
1.5%
스포츠 3
 
1.1%
상도점 3
 
1.1%
콩고 3
 
1.1%
신대방점 3
 
1.1%
Other values (200) 210
78.4%
2024-04-30T05:02:10.049971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 110
 
9.0%
107
 
8.7%
트 46
 
3.8%
니 38
 
3.1%
짐 37
 
3.0%
헬 35
 
2.9%
휘 27
 
2.2%
이 22
 
1.8%
T 19
 
1.5%
점 17
 
1.4%
Other values (239) 768
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 918
74.9%
Uppercase Letter 115
 
9.4%
Space Separator 107
 
8.7%
Lowercase Letter 34
 
2.8%
Decimal Number 15
 
1.2%
Close Punctuation 13
 
1.1%
Open Punctuation 13
 
1.1%
Other Punctuation 6
 
0.5%
Dash Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 110
 
12.0%
트 46
 
5.0%
니 38
 
4.1%
짐 37
 
4.0%
헬 35
 
3.8%
휘 27
 
2.9%
이 22
 
2.4%
점 17
 
1.9%
포 16
 
1.7%
피 15
 
1.6%
Other values (187) 555
60.5%
Uppercase Letter
ValueCountFrequency (%)
T 19
16.5%
P 13
11.3%
I 9
 
7.8%
S 9
 
7.8%
G 8
 
7.0%
M 6
 
5.2%
U 6
 
5.2%
O 5
 
4.3%
K 5
 
4.3%
Y 5
 
4.3%
Other values (13) 30
26.1%
Lowercase Letter
ValueCountFrequency (%)
e 5
14.7%
u 3
8.8%
m 3
8.8%
o 3
8.8%
t 3
8.8%
y 2
 
5.9%
a 2
 
5.9%
n 2
 
5.9%
r 2
 
5.9%
d 2
 
5.9%
Other values (5) 7
20.6%
Decimal Number
ValueCountFrequency (%)
1 5
33.3%
8 3
20.0%
2 3
20.0%
0 1
 
6.7%
9 1
 
6.7%
5 1
 
6.7%
4 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
& 2
33.3%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 918
74.9%
Common 159
 
13.0%
Latin 149
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 110
 
12.0%
트 46
 
5.0%
니 38
 
4.1%
짐 37
 
4.0%
헬 35
 
3.8%
휘 27
 
2.9%
이 22
 
2.4%
점 17
 
1.9%
포 16
 
1.7%
피 15
 
1.6%
Other values (187) 555
60.5%
Latin
ValueCountFrequency (%)
T 19
 
12.8%
P 13
 
8.7%
I 9
 
6.0%
S 9
 
6.0%
G 8
 
5.4%
M 6
 
4.0%
U 6
 
4.0%
O 5
 
3.4%
e 5
 
3.4%
K 5
 
3.4%
Other values (28) 64
43.0%
Common
ValueCountFrequency (%)
107
67.3%
) 13
 
8.2%
( 13
 
8.2%
- 5
 
3.1%
1 5
 
3.1%
8 3
 
1.9%
. 3
 
1.9%
2 3
 
1.9%
& 2
 
1.3%
0 1
 
0.6%
Other values (4) 4
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 918
74.9%
ASCII 308
 
25.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 110
 
12.0%
트 46
 
5.0%
니 38
 
4.1%
짐 37
 
4.0%
헬 35
 
3.8%
휘 27
 
2.9%
이 22
 
2.4%
점 17
 
1.9%
포 16
 
1.7%
피 15
 
1.6%
Other values (187) 555
60.5%
ASCII
ValueCountFrequency (%)
107
34.7%
T 19
 
6.2%
) 13
 
4.2%
P 13
 
4.2%
( 13
 
4.2%
I 9
 
2.9%
S 9
 
2.9%
G 8
 
2.6%
M 6
 
1.9%
U 6
 
1.9%
Other values (42) 105
34.1%

최종수정일자
Date

Distinct157
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2003-04-18 11:54:21
Maximum2024-04-01 08:47:12
2024-04-30T05:02:10.161190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:10.273402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
92 
U
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 92
57.1%
U 69
42.9%

Length

2024-04-30T05:02:10.577468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:10.668032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 92
57.1%
u 69
42.9%

데이터갱신일자
Date

Distinct88
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-04-30T05:02:10.753970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:02:10.867153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)84.8%
Missing3
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean195384.04
Minimum191691.68
Maximum198369.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:02:11.000351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191691.68
5-th percentile192090.69
Q1193747.16
median195128.96
Q3197238.44
95-th percentile198289.04
Maximum198369.27
Range6677.589
Interquartile range (IQR)3491.2817

Descriptive statistics

Standard deviation1961.5497
Coefficient of variation (CV)0.010039457
Kurtosis-1.0686682
Mean195384.04
Median Absolute Deviation (MAD)1544.3975
Skewness0.035903051
Sum30870679
Variance3847677.3
MonotonicityNot monotonic
2024-04-30T05:02:11.120425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197996.381794257 4
 
2.5%
198198.9077039 3
 
1.9%
191691.678396263 3
 
1.9%
195079.265528912 2
 
1.2%
195821.72598572 2
 
1.2%
196643.539904335 2
 
1.2%
193204.782207917 2
 
1.2%
194482.997889163 2
 
1.2%
194748.322941671 2
 
1.2%
193554.744988075 2
 
1.2%
Other values (124) 134
83.2%
(Missing) 3
 
1.9%
ValueCountFrequency (%)
191691.678396263 3
1.9%
191748.253117587 1
 
0.6%
191781.745330521 1
 
0.6%
191803.524952767 2
1.2%
191963.162407762 1
 
0.6%
192113.200600983 2
1.2%
192170.155815215 1
 
0.6%
192917.968628959 1
 
0.6%
192929.646582958 1
 
0.6%
192958.762593045 1
 
0.6%
ValueCountFrequency (%)
198369.267432933 1
0.6%
198354.350098982 1
0.6%
198310.468541102 1
0.6%
198303.527071078 1
0.6%
198297.907079009 1
0.6%
198295.843258378 1
0.6%
198293.498296993 1
0.6%
198289.039514074 2
1.2%
198284.656804106 1
0.6%
198282.786805929 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)84.8%
Missing3
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean443986.57
Minimum441588.86
Maximum445706.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:02:11.230823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441588.86
5-th percentile442193.2
Q1442926.7
median444094.26
Q3444955.54
95-th percentile445600.17
Maximum445706.96
Range4118.0975
Interquartile range (IQR)2028.8439

Descriptive statistics

Standard deviation1145.3115
Coefficient of variation (CV)0.0025796085
Kurtosis-1.1216892
Mean443986.57
Median Absolute Deviation (MAD)954.8165
Skewness-0.18331464
Sum70149878
Variance1311738.5
MonotonicityNot monotonic
2024-04-30T05:02:11.355836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442918.664628817 4
 
2.5%
442193.202544137 3
 
1.9%
442818.113681285 3
 
1.9%
445413.288375132 2
 
1.2%
443860.596515691 2
 
1.2%
445042.374578651 2
 
1.2%
443168.51356024 2
 
1.2%
444679.023067754 2
 
1.2%
445553.823752327 2
 
1.2%
444142.040717888 2
 
1.2%
Other values (124) 134
83.2%
(Missing) 3
 
1.9%
ValueCountFrequency (%)
441588.861462309 1
 
0.6%
441621.408468674 1
 
0.6%
441639.261005501 1
 
0.6%
441959.3027609 1
 
0.6%
442014.640731 1
 
0.6%
442017.925073828 1
 
0.6%
442193.202544137 3
1.9%
442211.512440311 2
1.2%
442277.270760751 1
 
0.6%
442303.756960284 1
 
0.6%
ValueCountFrequency (%)
445706.958977345 1
0.6%
445692.62623807 1
0.6%
445686.008483928 1
0.6%
445682.778340956 1
0.6%
445665.106836723 1
0.6%
445623.080168564 2
1.2%
445610.160717686 1
0.6%
445598.406998745 1
0.6%
445584.324293928 1
0.6%
445576.85723848 1
0.6%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
체력단련장업
103 
<NA>
58 

Length

Max length6
Median length6
Mean length5.2795031
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 103
64.0%
<NA> 58
36.0%

Length

2024-04-30T05:02:11.476550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:11.590848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 103
64.0%
na 58
36.0%

공사립구분명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
사립
103 
<NA>
58 

Length

Max length4
Median length2
Mean length2.7204969
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 103
64.0%
<NA> 58
36.0%

Length

2024-04-30T05:02:11.694730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:11.788394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 103
64.0%
na 58
36.0%

보험가입여부코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
144 
0
17 

Length

Max length4
Median length4
Mean length3.6832298
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 144
89.4%
0 17
 
10.6%

Length

2024-04-30T05:02:11.878747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:11.978093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
89.4%
0 17
 
10.6%

지도자수
Categorical

Distinct5
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
84 
1
57 
0
12 
2
 
7
22
 
1

Length

Max length4
Median length4
Mean length2.5714286
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
52.2%
1 57
35.4%
0 12
 
7.5%
2 7
 
4.3%
22 1
 
0.6%

Length

2024-04-30T05:02:12.079072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:12.170176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
52.2%
1 57
35.4%
0 12
 
7.5%
2 7
 
4.3%
22 1
 
0.6%

건축물동수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
132 
1
15 
0
 
13
105
 
1

Length

Max length4
Median length4
Mean length3.4720497
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
82.0%
1 15
 
9.3%
0 13
 
8.1%
105 1
 
0.6%

Length

2024-04-30T05:02:12.275656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:12.371783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 132
82.0%
1 15
 
9.3%
0 13
 
8.1%
105 1
 
0.6%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)69.7%
Missing128
Missing (%)79.5%
Infinite0
Infinite (%)0.0%
Mean5385.4624
Minimum0
Maximum81848.75
Zeros11
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T05:02:12.476137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1156.63
Q32075.48
95-th percentile23957.01
Maximum81848.75
Range81848.75
Interquartile range (IQR)2075.48

Descriptive statistics

Standard deviation16031.325
Coefficient of variation (CV)2.9767777
Kurtosis18.025149
Mean5385.4624
Median Absolute Deviation (MAD)1156.63
Skewness4.1933277
Sum177720.26
Variance2.5700337 × 108
MonotonicityNot monotonic
2024-04-30T05:02:12.579187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 11
 
6.8%
4673.25 1
 
0.6%
7982.13 1
 
0.6%
324.3 1
 
0.6%
1658.28 1
 
0.6%
1561.4 1
 
0.6%
601.02 1
 
0.6%
1475.77 1
 
0.6%
779.76 1
 
0.6%
1649.52 1
 
0.6%
Other values (13) 13
 
8.1%
(Missing) 128
79.5%
ValueCountFrequency (%)
0.0 11
6.8%
324.3 1
 
0.6%
601.02 1
 
0.6%
615.35 1
 
0.6%
631.73 1
 
0.6%
779.76 1
 
0.6%
1156.63 1
 
0.6%
1170.35 1
 
0.6%
1214.64 1
 
0.6%
1416.17 1
 
0.6%
ValueCountFrequency (%)
81848.75 1
0.6%
47575.98 1
0.6%
8211.03 1
0.6%
7982.13 1
0.6%
4673.25 1
0.6%
4585.14 1
0.6%
3918.43 1
0.6%
2595.15 1
0.6%
2075.48 1
0.6%
1658.28 1
0.6%

회원모집총인원
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
152 
0
 
8
30
 
1

Length

Max length4
Median length4
Mean length3.8385093
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> 152
94.4%
0 8
 
5.0%
30 1
 
0.6%

Length

2024-04-30T05:02:12.673102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:02:12.772279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
94.4%
0 8
 
5.0%
30 1
 
0.6%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing161
Missing (%)100.0%
Memory size1.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03190000CDFH330106198900000119891213<NA>4취소/말소/만료/정지/중지35직권말소20190322<NA><NA><NA>815-7769<NA><NA>서울특별시 동작구 노량진동 312-43번지서울특별시 동작구 장승배기로17길 1 (노량진동)6936강남2019-03-22 13:27:38U2019-03-24 02:40:00.0<NA>194593.427654444981.548906체력단련장업사립<NA>1<NA><NA><NA><NA><NA>
13190000CDFH330106198900000219891229<NA>3폐업3폐업20050216<NA><NA><NA>816-2547<NA>156060서울특별시 동작구 본동 400-0번지서울특별시 동작구 노량진로 228 (본동)<NA>88헬스크럽2005-02-16 15:21:26I2018-08-31 23:59:59.0<NA>195625.02384445584.324294체력단련장업사립0<NA><NA><NA><NA><NA><NA>
23190000CDFH330106198900000319891220<NA>3폐업3폐업20020118<NA><NA><NA>821-3000<NA>156811서울특별시 동작구 대방동 400-5번지<NA><NA>정우헬스2003-04-18 11:54:21I2018-08-31 23:59:59.0<NA>192929.646583444167.621807체력단련장업사립<NA>000.0<NA><NA><NA>
33190000CDFH330106199300000119930323<NA>3폐업3폐업20210319<NA><NA><NA>595-8000<NA><NA>서울특별시 동작구 사당동 136-1 7층서울특별시 동작구 동작대로 115, 7층 (사당동)7008태평2021-03-19 13:57:58U2021-03-21 02:40:00.0<NA>198303.527071442742.422888체력단련장업사립<NA>1<NA><NA><NA><NA><NA>
43190000CDFH330106199400000119941109<NA>3폐업3폐업20060705<NA><NA><NA>583-0442<NA>156823서울특별시 동작구 사당동 318-13번지서울특별시 동작구 사당로16길 7 (사당동)<NA>국화2006-07-05 17:31:51I2018-08-31 23:59:59.0<NA>197629.477544442303.75696체력단련장업사립0<NA><NA><NA><NA><NA><NA>
53190000CDFH330106199600000119960702<NA>3폐업3폐업20080521<NA><NA><NA>596-0265<NA>156815서울특별시 동작구 사당동 120-1번지 5층서울특별시 동작구 동작대로29길 69 (사당동,5층)<NA>두성2008-05-21 10:31:12I2018-08-31 23:59:59.0<NA>197996.381794442918.664629체력단련장업사립0<NA><NA><NA><NA><NA><NA>
63190000CDFH330106199700000119970513<NA>3폐업3폐업20080324<NA><NA><NA>821-7515<NA>156847서울특별시 동작구 신대방동 351-5번지 3층서울특별시 동작구 보라매로 105 (신대방동,3층)<NA>연세토탈휘트니스2008-03-24 11:32:42I2018-08-31 23:59:59.0<NA>193542.317495444054.924159체력단련장업사립0<NA><NA><NA><NA><NA><NA>
73190000CDFH330106199700000319970326<NA>3폐업3폐업19991231<NA><NA><NA>824-5219<NA>156839서울특별시 동작구 상도동 187-1번지<NA><NA>상도헬스클럽2003-05-01 14:21:26I2018-08-31 23:59:59.0<NA>194284.301857444582.34538체력단련장업사립0<NA><NA><NA><NA><NA><NA>
83190000CDFH330106199700000419970120<NA>3폐업3폐업20030701<NA><NA><NA>813-3267<NA>156861서울특별시 동작구 흑석동 184-14번지서울특별시 동작구 흑석로11길 4 (흑석동)<NA>중앙2003-07-01 15:57:13I2018-08-31 23:59:59.0<NA>196440.447611445074.072081체력단련장업사립0<NA><NA><NA><NA><NA><NA>
93190000CDFH330106199800000119980115<NA>1영업/정상13영업중<NA><NA><NA><NA>824-8688<NA><NA>서울특별시 동작구 흑석동 209-0번지서울특별시 동작구 흑석로6가길 21 (흑석동)6974헤라클레스2015-08-07 15:12:13I2018-08-31 23:59:59.0<NA>196024.949317444857.128278체력단련장업사립<NA>1<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
1513190000CDFH33010620230000102023-12-29<NA>1영업/정상13영업중<NA><NA><NA><NA>0232805227<NA><NA>서울특별시 동작구 대방동 335-16 대방빌딩서울특별시 동작구 상도로 83, 대방빌딩 2층 (대방동)6953어게인짐2023-12-29 09:29:24I2022-11-01 21:01:00.0<NA>193738.6678444191.10767<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1523190000CDFH33010620240000012024-01-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-848-6488<NA><NA>서울특별시 동작구 신대방동 395-69 보라매아카데미타워 B2호서울특별시 동작구 보라매로5가길 16, 보라매아카데미타워 B2호 (신대방동, 보라매아카데미타워)7071짐박스피트니스 보라매점2024-01-05 15:18:43I2023-12-01 00:07:00.0<NA>193218.36401443239.581054<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1533190000CDFH33010620240000022024-01-25<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 62-8 이도타워서울특별시 동작구 노량진로 134, 이도타워 지하3,4층 (노량진동)6922올데이스포츠2024-01-25 11:17:12I2023-11-30 22:07:00.0<NA>194703.281547445682.778341<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1543190000CDFH33010620240000032024-01-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 465서울특별시 동작구 상도로37길 53, 1층 101호 (상도동)6971피지컬리지PT2024-01-30 12:47:55I2023-12-02 00:01:00.0<NA>195666.984548444148.461388<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1553190000CDFH33010620240000042024-02-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 22-86서울특별시 동작구 상도로31길 83, 지하1층 (상도동)6921LIKE PT STUDIO 상도2호점2024-02-01 08:51:00I2023-12-02 00:03:00.0<NA>195161.017607444794.372397<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1563190000CDFH33010620240000052024-02-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 365-2 동서남북빌딩서울특별시 동작구 상도로 174, 동서남북빌딩 9층 (상도동)6956LIKE PT STUDIO 장승배기점2024-02-08 16:02:02I2023-12-01 23:01:00.0<NA>194482.997889444679.023068<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1573190000CDFH33010620240000062024-02-15<NA>1영업/정상13영업중<NA><NA><NA><NA>02-525-2022<NA><NA>서울특별시 동작구 사당동 1010-28 자매빌딩서울특별시 동작구 동작대로13길 12, 자매빌딩 지층 (사당동)7014얼티밋 트레이닝2024-02-15 12:00:52I2023-12-01 23:07:00.0<NA>198198.907704442193.202544<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1583190000CDFH33010620240000072024-03-13<NA>1영업/정상13영업중<NA><NA><NA><NA>02-522-6466<NA><NA>서울특별시 동작구 사당동 1030-20서울특별시 동작구 동작대로 43, 2,3층 (사당동)7015짐박스피트니스 사당1호점2024-03-13 14:50:41I2023-12-02 23:06:00.0<NA>198279.266223442017.925074<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1593190000CDFH33010620240000082024-03-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도1동 666-1 진영빌딩서울특별시 동작구 양녕로 268, 진영빌딩 5층 (상도1동)6968위드미짐2024-03-15 08:49:19I2023-12-02 23:07:00.0<NA>195407.072879444587.560882<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1603190000CDFH33010620240000092024-03-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 사당동 708-429서울특별시 동작구 사당로17길 21, 4층 (사당동)7004이안PT2024-03-19 08:54:10I2023-12-02 22:01:00.0<NA>197597.023515442439.403504<NA><NA><NA><NA><NA><NA><NA><NA><NA>