Overview

Dataset statistics

Number of variables34
Number of observations194
Missing cells1666
Missing cells (%)25.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory54.7 KiB
Average record size in memory288.7 B

Variable types

Categorical14
Text7
DateTime4
Unsupported6
Numeric3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,공사립구분명,보험가입여부코드,지도자수,건축물동수,건축물연면적,회원모집총인원,세부업종명,법인명
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-19832/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (91.8%)Imbalance
보험가입여부코드 is highly imbalanced (59.6%)Imbalance
회원모집총인원 is highly imbalanced (85.5%)Imbalance
폐업일자 has 84 (43.3%) missing valuesMissing
휴업시작일자 has 194 (100.0%) missing valuesMissing
휴업종료일자 has 194 (100.0%) missing valuesMissing
재개업일자 has 194 (100.0%) missing valuesMissing
전화번호 has 70 (36.1%) missing valuesMissing
소재지면적 has 194 (100.0%) missing valuesMissing
소재지우편번호 has 73 (37.6%) missing valuesMissing
도로명주소 has 14 (7.2%) missing valuesMissing
도로명우편번호 has 105 (54.1%) missing valuesMissing
좌표정보(X) has 11 (5.7%) missing valuesMissing
좌표정보(Y) has 11 (5.7%) missing valuesMissing
건축물연면적 has 134 (69.1%) missing valuesMissing
세부업종명 has 194 (100.0%) missing valuesMissing
법인명 has 194 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
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
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 45 (23.2%) zerosZeros

Reproduction

Analysis started2024-04-29 20:01:00.062949
Analysis finished2024-04-29 20:01:00.857267
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3050000
194 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 194
100.0%

Length

2024-04-30T05:01:00.928513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:01.014643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 194
100.0%

관리번호
Text

UNIQUE 

Distinct194
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:01:01.160093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters3880
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

Unique194 ?
Unique (%)100.0%

Sample

1st rowCDFH3301021982000001
2nd rowCDFH3301021982000002
3rd rowCDFH3301021982000003
4th rowCDFH3301021982000004
5th rowCDFH3301021984000001
ValueCountFrequency (%)
cdfh3301021982000001 1
 
0.5%
cdfh3301022012000001 1
 
0.5%
cdfh3301022008000002 1
 
0.5%
cdfh3301022009000001 1
 
0.5%
cdfh3301022008000003 1
 
0.5%
cdfh3301022008000004 1
 
0.5%
cdfh3301022008000005 1
 
0.5%
cdfh3301022008000006 1
 
0.5%
cdfh3301022008000007 1
 
0.5%
cdfh3301022008000008 1
 
0.5%
Other values (184) 184
94.8%
2024-04-30T05:01:01.422295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1599
41.2%
2 446
 
11.5%
3 441
 
11.4%
1 356
 
9.2%
C 194
 
5.0%
D 194
 
5.0%
F 194
 
5.0%
H 194
 
5.0%
9 107
 
2.8%
4 39
 
1.0%
Other values (4) 116
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3104
80.0%
Uppercase Letter 776
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1599
51.5%
2 446
 
14.4%
3 441
 
14.2%
1 356
 
11.5%
9 107
 
3.4%
4 39
 
1.3%
8 35
 
1.1%
5 31
 
1.0%
7 28
 
0.9%
6 22
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 194
25.0%
D 194
25.0%
F 194
25.0%
H 194
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3104
80.0%
Latin 776
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1599
51.5%
2 446
 
14.4%
3 441
 
14.2%
1 356
 
11.5%
9 107
 
3.4%
4 39
 
1.3%
8 35
 
1.1%
5 31
 
1.0%
7 28
 
0.9%
6 22
 
0.7%
Latin
ValueCountFrequency (%)
C 194
25.0%
D 194
25.0%
F 194
25.0%
H 194
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1599
41.2%
2 446
 
11.5%
3 441
 
11.4%
1 356
 
9.2%
C 194
 
5.0%
D 194
 
5.0%
F 194
 
5.0%
H 194
 
5.0%
9 107
 
2.8%
4 39
 
1.0%
Other values (4) 116
 
3.0%

인허가일자
Date

Distinct184
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1982-01-16 00:00:00
Maximum2024-04-05 00:00:00
2024-04-30T05:01:01.545701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:01:01.660684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
191 
20150904
 
2
20120523
 
1

Length

Max length8
Median length4
Mean length4.0618557
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 191
98.5%
20150904 2
 
1.0%
20120523 1
 
0.5%

Length

2024-04-30T05:01:01.798182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:01.897233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 191
98.5%
20150904 2
 
1.0%
20120523 1
 
0.5%

영업상태코드
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
93 
1
81 
4
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 93
47.9%
1 81
41.8%
4 20
 
10.3%

Length

2024-04-30T05:01:01.979424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:02.057691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 93
47.9%
1 81
41.8%
4 20
 
10.3%

영업상태명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
93 
영업/정상
81 
취소/말소/만료/정지/중지
20 

Length

Max length14
Median length5
Mean length4.4896907
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 93
47.9%
영업/정상 81
41.8%
취소/말소/만료/정지/중지 20
 
10.3%

Length

2024-04-30T05:01:02.150035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:02.251005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 93
47.9%
영업/정상 81
41.8%
취소/말소/만료/정지/중지 20
 
10.3%

상세영업상태코드
Categorical

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
93 
13
81 
35
17 
32
 
2
31
 
1

Length

Max length2
Median length2
Mean length1.5206186
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
3 93
47.9%
13 81
41.8%
35 17
 
8.8%
32 2
 
1.0%
31 1
 
0.5%

Length

2024-04-30T05:01:02.359393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:02.456207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 93
47.9%
13 81
41.8%
35 17
 
8.8%
32 2
 
1.0%
31 1
 
0.5%

상세영업상태명
Categorical

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
93 
영업중
81 
직권말소
17 
신고취소
 
2
등록취소
 
1

Length

Max length4
Median length3
Mean length2.6237113
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 93
47.9%
영업중 81
41.8%
직권말소 17
 
8.8%
신고취소 2
 
1.0%
등록취소 1
 
0.5%

Length

2024-04-30T05:01:02.552947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:02.660401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 93
47.9%
영업중 81
41.8%
직권말소 17
 
8.8%
신고취소 2
 
1.0%
등록취소 1
 
0.5%

폐업일자
Date

MISSING 

Distinct88
Distinct (%)80.0%
Missing84
Missing (%)43.3%
Memory size1.6 KiB
Minimum1997-07-03 00:00:00
Maximum2024-02-16 00:00:00
2024-04-30T05:01:02.772805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:01:02.891679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

전화번호
Text

MISSING 

Distinct116
Distinct (%)93.5%
Missing70
Missing (%)36.1%
Memory size1.6 KiB
2024-04-30T05:01:03.156285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.5322581
Min length8

Characters and Unicode

Total characters1182
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

Unique108 ?
Unique (%)87.1%

Sample

1st row962-7607
2nd row968-8911
3rd row966-1743
4th row02-966-0250
5th row2243-5786
ValueCountFrequency (%)
2246-1281 2
 
1.6%
2244-1216 2
 
1.6%
02-2212-3003 2
 
1.6%
02-2244-0012 2
 
1.6%
2217-0995 2
 
1.6%
968-5554 2
 
1.6%
2215-3240 2
 
1.6%
961-6469 2
 
1.6%
02-2236-6100 1
 
0.8%
02-2245-3352 1
 
0.8%
Other values (106) 106
85.5%
2024-04-30T05:01:03.681291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 261
22.1%
- 161
13.6%
4 107
9.1%
9 105
8.9%
0 101
 
8.5%
1 95
 
8.0%
3 89
 
7.5%
6 79
 
6.7%
5 78
 
6.6%
7 67
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1021
86.4%
Dash Punctuation 161
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 261
25.6%
4 107
10.5%
9 105
10.3%
0 101
 
9.9%
1 95
 
9.3%
3 89
 
8.7%
6 79
 
7.7%
5 78
 
7.6%
7 67
 
6.6%
8 39
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1182
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 261
22.1%
- 161
13.6%
4 107
9.1%
9 105
8.9%
0 101
 
8.5%
1 95
 
8.0%
3 89
 
7.5%
6 79
 
6.7%
5 78
 
6.6%
7 67
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 261
22.1%
- 161
13.6%
4 107
9.1%
9 105
8.9%
0 101
 
8.5%
1 95
 
8.0%
3 89
 
7.5%
6 79
 
6.7%
5 78
 
6.6%
7 67
 
5.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

소재지우편번호
Text

MISSING 

Distinct68
Distinct (%)56.2%
Missing73
Missing (%)37.6%
Memory size1.6 KiB
2024-04-30T05:01:03.941927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1652893
Min length6

Characters and Unicode

Total characters746
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

Unique35 ?
Unique (%)28.9%

Sample

1st row130817
2nd row130020
3rd row130080
4th row130-870
5th row130020
ValueCountFrequency (%)
130840 7
 
5.8%
130020 5
 
4.1%
130854 4
 
3.3%
130876 4
 
3.3%
130-840 4
 
3.3%
130835 3
 
2.5%
130859 3
 
2.5%
130867 3
 
2.5%
130875 3
 
2.5%
130817 3
 
2.5%
Other values (58) 82
67.8%
2024-04-30T05:01:04.260440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 182
24.4%
3 142
19.0%
1 137
18.4%
8 115
15.4%
4 31
 
4.2%
2 31
 
4.2%
7 30
 
4.0%
6 25
 
3.4%
5 21
 
2.8%
- 20
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 726
97.3%
Dash Punctuation 20
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 182
25.1%
3 142
19.6%
1 137
18.9%
8 115
15.8%
4 31
 
4.3%
2 31
 
4.3%
7 30
 
4.1%
6 25
 
3.4%
5 21
 
2.9%
9 12
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 182
24.4%
3 142
19.0%
1 137
18.4%
8 115
15.4%
4 31
 
4.2%
2 31
 
4.2%
7 30
 
4.0%
6 25
 
3.4%
5 21
 
2.8%
- 20
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 182
24.4%
3 142
19.0%
1 137
18.4%
8 115
15.4%
4 31
 
4.2%
2 31
 
4.2%
7 30
 
4.0%
6 25
 
3.4%
5 21
 
2.8%
- 20
 
2.7%

지번주소
Text

Distinct189
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:01:04.555254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length24.762887
Min length18

Characters and Unicode

Total characters4804
Distinct characters115
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

Unique184 ?
Unique (%)94.8%

Sample

1st row서울특별시 동대문구 용두동 39-62번지
2nd row서울특별시 동대문구 전농동 295-310번지
3rd row서울특별시 동대문구 이문동 산 339-4번지
4th row서울특별시 동대문구 청량리동 743-4
5th row서울특별시 동대문구 전농동 295-16번지
ValueCountFrequency (%)
동대문구 195
22.0%
서울특별시 194
21.9%
장안동 51
 
5.8%
답십리동 33
 
3.7%
전농동 27
 
3.0%
이문동 21
 
2.4%
휘경동 16
 
1.8%
용두동 16
 
1.8%
2층 16
 
1.8%
3층 15
 
1.7%
Other values (242) 302
34.1%
2024-04-30T05:01:04.974234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
812
16.9%
동 398
 
8.3%
문 218
 
4.5%
대 198
 
4.1%
서 197
 
4.1%
울 196
 
4.1%
시 196
 
4.1%
구 195
 
4.1%
별 194
 
4.0%
특 194
 
4.0%
Other values (105) 2006
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2887
60.1%
Decimal Number 883
 
18.4%
Space Separator 812
 
16.9%
Dash Punctuation 170
 
3.5%
Open Punctuation 20
 
0.4%
Close Punctuation 20
 
0.4%
Uppercase Letter 8
 
0.2%
Other Punctuation 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 398
13.8%
문 218
 
7.6%
대 198
 
6.9%
서 197
 
6.8%
울 196
 
6.8%
시 196
 
6.8%
구 195
 
6.8%
별 194
 
6.7%
특 194
 
6.7%
지 119
 
4.1%
Other values (83) 782
27.1%
Decimal Number
ValueCountFrequency (%)
3 152
17.2%
1 138
15.6%
2 133
15.1%
4 104
11.8%
5 76
8.6%
8 61
6.9%
0 61
6.9%
6 54
 
6.1%
9 53
 
6.0%
7 51
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
37.5%
S 2
25.0%
K 2
25.0%
B 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 1
33.3%
@ 1
33.3%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
812
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2887
60.1%
Common 1908
39.7%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 398
13.8%
문 218
 
7.6%
대 198
 
6.9%
서 197
 
6.8%
울 196
 
6.8%
시 196
 
6.8%
구 195
 
6.8%
별 194
 
6.7%
특 194
 
6.7%
지 119
 
4.1%
Other values (83) 782
27.1%
Common
ValueCountFrequency (%)
812
42.6%
- 170
 
8.9%
3 152
 
8.0%
1 138
 
7.2%
2 133
 
7.0%
4 104
 
5.5%
5 76
 
4.0%
8 61
 
3.2%
0 61
 
3.2%
6 54
 
2.8%
Other values (7) 147
 
7.7%
Latin
ValueCountFrequency (%)
A 3
33.3%
S 2
22.2%
K 2
22.2%
B 1
 
11.1%
e 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2887
60.1%
ASCII 1917
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
812
42.4%
- 170
 
8.9%
3 152
 
7.9%
1 138
 
7.2%
2 133
 
6.9%
4 104
 
5.4%
5 76
 
4.0%
8 61
 
3.2%
0 61
 
3.2%
6 54
 
2.8%
Other values (12) 156
 
8.1%
Hangul
ValueCountFrequency (%)
동 398
13.8%
문 218
 
7.6%
대 198
 
6.9%
서 197
 
6.8%
울 196
 
6.8%
시 196
 
6.8%
구 195
 
6.8%
별 194
 
6.7%
특 194
 
6.7%
지 119
 
4.1%
Other values (83) 782
27.1%

도로명주소
Text

MISSING 

Distinct175
Distinct (%)97.2%
Missing14
Missing (%)7.2%
Memory size1.6 KiB
2024-04-30T05:01:05.206565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length30.555556
Min length22

Characters and Unicode

Total characters5500
Distinct characters124
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

Unique171 ?
Unique (%)95.0%

Sample

1st row서울특별시 동대문구 천호대로45가길 34 (용두동)
2nd row서울특별시 동대문구 전농로15길 27 (전농동)
3rd row서울특별시 동대문구 홍릉로 3-1 (청량리동)
4th row서울특별시 동대문구 사가정로13길 3 (전농동)
5th row서울특별시 동대문구 신이문로 43 (이문동)
ValueCountFrequency (%)
서울특별시 180
 
17.1%
동대문구 180
 
17.1%
장안동 36
 
3.4%
3층 26
 
2.5%
전농동 23
 
2.2%
답십리동 22
 
2.1%
2층 17
 
1.6%
상가동 16
 
1.5%
이문동 13
 
1.2%
4층 13
 
1.2%
Other values (292) 524
49.9%
2024-04-30T05:01:05.551615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
915
 
16.6%
동 391
 
7.1%
문 213
 
3.9%
대 200
 
3.6%
) 199
 
3.6%
( 199
 
3.6%
시 191
 
3.5%
서 184
 
3.3%
울 184
 
3.3%
구 182
 
3.3%
Other values (114) 2642
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3294
59.9%
Space Separator 915
 
16.6%
Decimal Number 724
 
13.2%
Close Punctuation 199
 
3.6%
Open Punctuation 199
 
3.6%
Other Punctuation 136
 
2.5%
Dash Punctuation 24
 
0.4%
Uppercase Letter 8
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 391
 
11.9%
문 213
 
6.5%
대 200
 
6.1%
시 191
 
5.8%
서 184
 
5.6%
울 184
 
5.6%
구 182
 
5.5%
특 180
 
5.5%
별 180
 
5.5%
로 180
 
5.5%
Other values (92) 1209
36.7%
Decimal Number
ValueCountFrequency (%)
1 138
19.1%
2 136
18.8%
3 97
13.4%
4 82
11.3%
5 60
8.3%
6 58
8.0%
7 43
 
5.9%
0 42
 
5.8%
8 41
 
5.7%
9 27
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 4
50.0%
B 2
25.0%
S 1
 
12.5%
K 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 134
98.5%
@ 1
 
0.7%
. 1
 
0.7%
Space Separator
ValueCountFrequency (%)
915
100.0%
Close Punctuation
ValueCountFrequency (%)
) 199
100.0%
Open Punctuation
ValueCountFrequency (%)
( 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3294
59.9%
Common 2197
39.9%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 391
 
11.9%
문 213
 
6.5%
대 200
 
6.1%
시 191
 
5.8%
서 184
 
5.6%
울 184
 
5.6%
구 182
 
5.5%
특 180
 
5.5%
별 180
 
5.5%
로 180
 
5.5%
Other values (92) 1209
36.7%
Common
ValueCountFrequency (%)
915
41.6%
) 199
 
9.1%
( 199
 
9.1%
1 138
 
6.3%
2 136
 
6.2%
, 134
 
6.1%
3 97
 
4.4%
4 82
 
3.7%
5 60
 
2.7%
6 58
 
2.6%
Other values (7) 179
 
8.1%
Latin
ValueCountFrequency (%)
A 4
44.4%
B 2
22.2%
S 1
 
11.1%
K 1
 
11.1%
e 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3294
59.9%
ASCII 2206
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
915
41.5%
) 199
 
9.0%
( 199
 
9.0%
1 138
 
6.3%
2 136
 
6.2%
, 134
 
6.1%
3 97
 
4.4%
4 82
 
3.7%
5 60
 
2.7%
6 58
 
2.6%
Other values (12) 188
 
8.5%
Hangul
ValueCountFrequency (%)
동 391
 
11.9%
문 213
 
6.5%
대 200
 
6.1%
시 191
 
5.8%
서 184
 
5.6%
울 184
 
5.6%
구 182
 
5.5%
특 180
 
5.5%
별 180
 
5.5%
로 180
 
5.5%
Other values (92) 1209
36.7%

도로명우편번호
Text

MISSING 

Distinct71
Distinct (%)79.8%
Missing105
Missing (%)54.1%
Memory size1.6 KiB
2024-04-30T05:01:05.767346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0561798
Min length5

Characters and Unicode

Total characters450
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

Unique56 ?
Unique (%)62.9%

Sample

1st row02641
2nd row02641
3rd row02412
4th row130859
5th row02536
ValueCountFrequency (%)
02540 3
 
3.4%
02515 3
 
3.4%
02637 3
 
3.4%
02588 2
 
2.2%
02600 2
 
2.2%
02507 2
 
2.2%
02488 2
 
2.2%
02641 2
 
2.2%
02594 2
 
2.2%
02532 2
 
2.2%
Other values (61) 66
74.2%
2024-04-30T05:01:06.109081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112
24.9%
2 106
23.6%
5 56
12.4%
4 45
10.0%
6 32
 
7.1%
1 26
 
5.8%
3 25
 
5.6%
7 19
 
4.2%
8 17
 
3.8%
9 11
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 449
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 112
24.9%
2 106
23.6%
5 56
12.5%
4 45
10.0%
6 32
 
7.1%
1 26
 
5.8%
3 25
 
5.6%
7 19
 
4.2%
8 17
 
3.8%
9 11
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 450
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 112
24.9%
2 106
23.6%
5 56
12.4%
4 45
10.0%
6 32
 
7.1%
1 26
 
5.8%
3 25
 
5.6%
7 19
 
4.2%
8 17
 
3.8%
9 11
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 112
24.9%
2 106
23.6%
5 56
12.4%
4 45
10.0%
6 32
 
7.1%
1 26
 
5.8%
3 25
 
5.6%
7 19
 
4.2%
8 17
 
3.8%
9 11
 
2.4%

사업장명
Text

Distinct184
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-30T05:01:06.359874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.5360825
Min length3

Characters and Unicode

Total characters1462
Distinct characters210
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)90.2%

Sample

1st row최강태권도
2nd row비룡태권도
3rd row청도체육관(태권도)
4th row강덕무관(우슈)
5th row웅비용마(쿵후)
ValueCountFrequency (%)
태권도 6
 
2.3%
복싱 6
 
2.3%
복싱클럽 4
 
1.6%
장안체육관(태권도 3
 
1.2%
레전드 3
 
1.2%
용인대 3
 
1.2%
합기도 3
 
1.2%
클럽 3
 
1.2%
태권도장 3
 
1.2%
핫 2
 
0.8%
Other values (205) 220
85.9%
2024-04-30T05:01:06.723246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 124
 
8.5%
태 108
 
7.4%
권 99
 
6.8%
관 77
 
5.3%
체 70
 
4.8%
육 64
 
4.4%
62
 
4.2%
대 36
 
2.5%
장 36
 
2.5%
( 34
 
2.3%
Other values (200) 752
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1298
88.8%
Space Separator 62
 
4.2%
Open Punctuation 34
 
2.3%
Close Punctuation 34
 
2.3%
Uppercase Letter 29
 
2.0%
Decimal Number 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 124
 
9.6%
태 108
 
8.3%
권 99
 
7.6%
관 77
 
5.9%
체 70
 
5.4%
육 64
 
4.9%
대 36
 
2.8%
장 36
 
2.8%
복 30
 
2.3%
싱 29
 
2.2%
Other values (178) 625
48.2%
Uppercase Letter
ValueCountFrequency (%)
T 5
17.2%
K 3
10.3%
O 3
10.3%
M 3
10.3%
A 2
 
6.9%
P 2
 
6.9%
B 2
 
6.9%
R 2
 
6.9%
F 1
 
3.4%
C 1
 
3.4%
Other values (5) 5
17.2%
Decimal Number
ValueCountFrequency (%)
7 1
33.3%
9 1
33.3%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1298
88.8%
Common 135
 
9.2%
Latin 29
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 124
 
9.6%
태 108
 
8.3%
권 99
 
7.6%
관 77
 
5.9%
체 70
 
5.4%
육 64
 
4.9%
대 36
 
2.8%
장 36
 
2.8%
복 30
 
2.3%
싱 29
 
2.2%
Other values (178) 625
48.2%
Latin
ValueCountFrequency (%)
T 5
17.2%
K 3
10.3%
O 3
10.3%
M 3
10.3%
A 2
 
6.9%
P 2
 
6.9%
B 2
 
6.9%
R 2
 
6.9%
F 1
 
3.4%
C 1
 
3.4%
Other values (5) 5
17.2%
Common
ValueCountFrequency (%)
62
45.9%
( 34
25.2%
) 34
25.2%
& 2
 
1.5%
7 1
 
0.7%
9 1
 
0.7%
2 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1298
88.8%
ASCII 164
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 124
 
9.6%
태 108
 
8.3%
권 99
 
7.6%
관 77
 
5.9%
체 70
 
5.4%
육 64
 
4.9%
대 36
 
2.8%
장 36
 
2.8%
복 30
 
2.3%
싱 29
 
2.2%
Other values (178) 625
48.2%
ASCII
ValueCountFrequency (%)
62
37.8%
( 34
20.7%
) 34
20.7%
T 5
 
3.0%
K 3
 
1.8%
O 3
 
1.8%
M 3
 
1.8%
A 2
 
1.2%
P 2
 
1.2%
B 2
 
1.2%
Other values (12) 14
 
8.5%

최종수정일자
Date

Distinct189
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2003-04-18 15:38:02
Maximum2024-04-05 17:32:55
2024-04-30T05:01:06.839421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:01:06.965661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
U
115 
I
79 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 115
59.3%
I 79
40.7%

Length

2024-04-30T05:01:07.065394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:07.144861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 115
59.3%
i 79
40.7%

데이터갱신일자
Date

Distinct47
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T05:01:07.261245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:01:07.550887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

업태구분명
Categorical

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
102 
태권도
50 
권투
24 
합기도
 
8
검도
 
5
Other values (3)
 
5

Length

Max length4
Median length4
Mean length3.3556701
Min length2

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 102
52.6%
태권도 50
25.8%
권투 24
 
12.4%
합기도 8
 
4.1%
검도 5
 
2.6%
유도 3
 
1.5%
우슈 1
 
0.5%
레슬링 1
 
0.5%

Length

2024-04-30T05:01:07.660553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:07.760556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
52.6%
태권도 50
25.8%
권투 24
 
12.4%
합기도 8
 
4.1%
검도 5
 
2.6%
유도 3
 
1.5%
우슈 1
 
0.5%
레슬링 1
 
0.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct164
Distinct (%)89.6%
Missing11
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean204962.96
Minimum202114.76
Maximum206562.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:01:07.896999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202114.76
5-th percentile202679.84
Q1204230.32
median205048.14
Q3205850.76
95-th percentile206448.59
Maximum206562.65
Range4447.8894
Interquartile range (IQR)1620.4438

Descriptive statistics

Standard deviation1160.2058
Coefficient of variation (CV)0.0056605631
Kurtosis-0.3769394
Mean204962.96
Median Absolute Deviation (MAD)809.53264
Skewness-0.67741167
Sum37508221
Variance1346077.4
MonotonicityNot monotonic
2024-04-30T05:01:08.014336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204095.580966051 4
 
2.1%
204087.154871782 3
 
1.5%
206562.649224959 2
 
1.0%
202785.097798743 2
 
1.0%
205607.854744942 2
 
1.0%
204622.068292505 2
 
1.0%
205385.566057467 2
 
1.0%
204414.124968198 2
 
1.0%
206128.445460509 2
 
1.0%
204876.691450688 2
 
1.0%
Other values (154) 160
82.5%
(Missing) 11
 
5.7%
ValueCountFrequency (%)
202114.75984426 1
0.5%
202180.141420844 1
0.5%
202311.769333007 1
0.5%
202387.58821534 1
0.5%
202444.313840862 1
0.5%
202600.289971836 1
0.5%
202610.28584131 1
0.5%
202616.004256135 1
0.5%
202617.734894131 1
0.5%
202679.351741699 1
0.5%
ValueCountFrequency (%)
206562.649224959 2
1.0%
206521.405320134 1
0.5%
206502.751884821 1
0.5%
206488.078041774 1
0.5%
206464.060139046 2
1.0%
206453.802913626 1
0.5%
206450.432488236 1
0.5%
206449.764689744 1
0.5%
206438.049409217 1
0.5%
206429.136367187 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct164
Distinct (%)89.6%
Missing11
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean452996.67
Minimum451237.51
Maximum455801.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:01:08.127046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451237.51
5-th percentile451633.34
Q1452241.1
median452706.9
Q3453707.63
95-th percentile455253.43
Maximum455801.64
Range4564.1277
Interquartile range (IQR)1466.5289

Descriptive statistics

Standard deviation1091.4163
Coefficient of variation (CV)0.0024093252
Kurtosis-0.29613787
Mean452996.67
Median Absolute Deviation (MAD)682.71235
Skewness0.69537338
Sum82898390
Variance1191189.5
MonotonicityNot monotonic
2024-04-30T05:01:08.248495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452516.600098557 4
 
2.1%
452267.296291974 3
 
1.5%
452261.894728089 2
 
1.0%
452268.006218109 2
 
1.0%
454728.457426874 2
 
1.0%
454309.555044644 2
 
1.0%
451717.140632516 2
 
1.0%
453650.787929978 2
 
1.0%
451397.834814004 2
 
1.0%
452708.132578049 2
 
1.0%
Other values (154) 160
82.5%
(Missing) 11
 
5.7%
ValueCountFrequency (%)
451237.510868551 1
0.5%
451299.243507776 1
0.5%
451309.232677367 1
0.5%
451397.834814004 2
1.0%
451398.532298313 1
0.5%
451450.824165033 1
0.5%
451597.889972005 1
0.5%
451632.96031987 2
1.0%
451636.730116 1
0.5%
451653.626644161 1
0.5%
ValueCountFrequency (%)
455801.638525525 1
0.5%
455654.040807742 1
0.5%
455652.31748734 1
0.5%
455648.532126867 1
0.5%
455601.500196249 1
0.5%
455449.903263934 1
0.5%
455368.497123002 1
0.5%
455330.476532303 1
0.5%
455277.819225656 1
0.5%
455275.835949587 1
0.5%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
체육도장업
120 
<NA>
74 

Length

Max length5
Median length5
Mean length4.6185567
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 120
61.9%
<NA> 74
38.1%

Length

2024-04-30T05:01:08.360375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:08.451242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 120
61.9%
na 74
38.1%

공사립구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
사립
120 
<NA>
74 

Length

Max length4
Median length2
Mean length2.7628866
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 120
61.9%
<NA> 74
38.1%

Length

2024-04-30T05:01:08.566407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:08.675995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 120
61.9%
na 74
38.1%

보험가입여부코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
165 
0
28 
Y
 
1

Length

Max length4
Median length4
Mean length3.5515464
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 165
85.1%
0 28
 
14.4%
Y 1
 
0.5%

Length

2024-04-30T05:01:08.787643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:08.882934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 165
85.1%
0 28
 
14.4%
y 1
 
0.5%

지도자수
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
145 
0
27 
1
22 

Length

Max length4
Median length4
Mean length3.242268
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 145
74.7%
0 27
 
13.9%
1 22
 
11.3%

Length

2024-04-30T05:01:08.994274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:09.096127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 145
74.7%
0 27
 
13.9%
1 22
 
11.3%

건축물동수
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
144 
0
47 
1
 
3

Length

Max length4
Median length4
Mean length3.2268041
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 144
74.2%
0 47
 
24.2%
1 3
 
1.5%

Length

2024-04-30T05:01:09.188453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:09.278385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
74.2%
0 47
 
24.2%
1 3
 
1.5%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)26.7%
Missing134
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean260.805
Minimum0
Maximum4597.73
Zeros45
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-30T05:01:09.360098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3102.55
95-th percentile897.608
Maximum4597.73
Range4597.73
Interquartile range (IQR)102.55

Descriptive statistics

Standard deviation697.77541
Coefficient of variation (CV)2.6754679
Kurtosis26.19997
Mean260.805
Median Absolute Deviation (MAD)0
Skewness4.6708908
Sum15648.3
Variance486890.53
MonotonicityNot monotonic
2024-04-30T05:01:09.449617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 45
 
23.2%
2242.55 1
 
0.5%
609.72 1
 
0.5%
4597.73 1
 
0.5%
878.17 1
 
0.5%
493.01 1
 
0.5%
648.42 1
 
0.5%
452.7 1
 
0.5%
410.2 1
 
0.5%
427.77 1
 
0.5%
Other values (6) 6
 
3.1%
(Missing) 134
69.1%
ValueCountFrequency (%)
0.0 45
23.2%
410.2 1
 
0.5%
427.77 1
 
0.5%
452.7 1
 
0.5%
493.01 1
 
0.5%
591.25 1
 
0.5%
609.72 1
 
0.5%
635.04 1
 
0.5%
648.42 1
 
0.5%
741.7 1
 
0.5%
ValueCountFrequency (%)
4597.73 1
0.5%
2242.55 1
0.5%
1266.93 1
0.5%
878.17 1
0.5%
861.47 1
0.5%
791.64 1
0.5%
741.7 1
0.5%
648.42 1
0.5%
635.04 1
0.5%
609.72 1
0.5%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
190 
0
 
4

Length

Max length4
Median length4
Mean length3.9381443
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> 190
97.9%
0 4
 
2.1%

Length

2024-04-30T05:01:09.585356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:01:09.672637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 190
97.9%
0 4
 
2.1%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing194
Missing (%)100.0%
Memory size1.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03050000CDFH330102198200000119820206<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>962-7607<NA>130817서울특별시 동대문구 용두동 39-62번지서울특별시 동대문구 천호대로45가길 34 (용두동)<NA>최강태권도2020-05-22 10:24:24U2020-05-24 02:40:00.0<NA>203655.278471452644.194801체육도장업사립<NA><NA>0410.2<NA><NA><NA>
13050000CDFH330102198200000219820116<NA>3폐업3폐업20031014<NA><NA><NA>968-8911<NA>130020서울특별시 동대문구 전농동 295-310번지서울특별시 동대문구 전농로15길 27 (전농동)<NA>비룡태권도2003-10-14 16:52:41I2018-08-31 23:59:59.0<NA>204871.785109452817.102612체육도장업사립0<NA><NA><NA><NA><NA><NA>
23050000CDFH330102198200000319820624<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>966-1743<NA>130080서울특별시 동대문구 이문동 산 339-4번지<NA><NA>청도체육관(태권도)2020-05-22 10:37:42U2020-05-24 02:40:00.0<NA><NA><NA>체육도장업사립<NA>000.0<NA><NA><NA>
33050000CDFH33010219820000041982-12-15<NA>1영업/정상13영업중<NA><NA><NA><NA>02-966-0250<NA>130-870서울특별시 동대문구 청량리동 743-4서울특별시 동대문구 홍릉로 3-1 (청량리동)<NA>강덕무관(우슈)2024-01-15 10:28:36U2023-11-30 23:07:00.0우슈203888.935591453158.506653<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43050000CDFH330102198400000119841224<NA>3폐업3폐업20080528<NA><NA><NA>2243-5786<NA>130020서울특별시 동대문구 전농동 295-16번지서울특별시 동대문구 사가정로13길 3 (전농동)<NA>웅비용마(쿵후)2018-11-09 09:22:04U2018-11-11 02:38:42.0<NA>205048.138961452869.283154체육도장업사립<NA>000.0<NA><NA><NA>
53050000CDFH330102198600000119860114<NA>3폐업3폐업20050715<NA><NA><NA>967-7332<NA>130828서울특별시 동대문구 이문동 220-359번지서울특별시 동대문구 신이문로 43 (이문동)<NA>신이문체육관(태권도)2005-07-19 08:59:14I2018-08-31 23:59:59.0<NA>205843.852272455654.040808체육도장업사립0<NA><NA><NA><NA><NA><NA>
63050000CDFH330102198600000219860916<NA>3폐업3폐업20070410<NA><NA><NA>247-0477<NA>130837서울특별시 동대문구 장안동 192-75번지서울특별시 동대문구 한천로 60 (장안동)<NA>장안유도장2007-11-19 14:48:11I2018-08-31 23:59:59.0<NA>205456.377749451632.96032체육도장업사립0<NA><NA><NA><NA><NA><NA>
73050000CDFH330102198700000119870623<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>2247-0504<NA>130842서울특별시 동대문구 장안동 389-6번지서울특별시 동대문구 답십리로66길 25 (장안동)<NA>용인대태권도장2020-05-22 10:30:59U2020-05-24 02:40:00.0<NA>205936.783378452124.400835체육도장업사립<NA><NA>00.0<NA><NA><NA>
83050000CDFH330102199000000119900313<NA>3폐업3폐업20090623<NA><NA><NA>2213-7951<NA>130841서울특별시 동대문구 장안동 358-1번지서울특별시 동대문구 천호대로91길 90 (장안동)<NA>중앙체육관(태권도)2009-06-23 13:50:53I2018-08-31 23:59:59.0<NA>206197.196813451450.824165체육도장업사립<NA><NA>00.0<NA><NA><NA>
93050000CDFH330102199000000219900320<NA>4취소/말소/만료/정지/중지35직권말소20200522<NA><NA><NA>967-4240<NA>130876서울특별시 동대문구 휘경동 343-16번지서울특별시 동대문구 망우로 3 (휘경동)<NA>청림(유도)2020-05-22 11:01:36U2020-05-24 02:40:00.0<NA>204716.111048453996.733731체육도장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
1843050000CDFH33010220220000012022-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 542-4서울특별시 동대문구 황물로 54, 3층 1호 (답십리동)02593민앤마이노(답십리점)2023-07-27 16:58:32U2022-12-06 22:09:00.0유도204087.154872452267.296292<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1853050000CDFH330102202200000220220804<NA>1영업/정상13영업중<NA><NA><NA><NA>02-953-2022<NA><NA>서울특별시 동대문구 용두동 767-8 오션타워빌서울특별시 동대문구 한빛로 39, 2층 202호 (용두동, 오션타워빌)02578아리랑태권도2022-08-04 14:44:12I2021-12-08 00:06:00.0태권도202311.769333452931.087076<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1863050000CDFH33010220220000032022-11-01<NA>3폐업3폐업2023-10-31<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 431-2서울특별시 동대문구 장한로 27, 2층 1호 (장안동)02636히트플레이스PT2023-10-31 16:21:02U2022-11-01 00:02:00.0권투205751.349908451299.243508<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1873050000CDFH33010220230000012023-02-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 487-20서울특별시 동대문구 전농로 23, 2층 (답십리동)02605복싱트라이브2024-01-15 13:43:43U2023-11-30 23:07:00.0권투204921.103054451659.472207<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1883050000CDFH33010220230000022023-03-03<NA>3폐업3폐업2023-07-03<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 회기동 54-15서울특별시 동대문구 경희대로4길 60, B1층 (회기동)02452김영남 태권도장2023-07-03 16:01:49U2022-12-07 00:06:00.0태권도204828.974439454342.282888<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1893050000CDFH33010220230000032023-03-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 휘경동 319-13 두리빌딩서울특별시 동대문구 회기로 188, 두리빌딩 8층 (휘경동)02446히트앤핏 스카이라운지2023-03-24 17:03:10I2022-12-02 22:06:00.0권투204948.158924454162.585737<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1903050000CDFH33010220230000042023-07-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 192-75서울특별시 동대문구 한천로 60, 3층 (장안동)02631MTA 태권도2024-01-15 13:47:49U2023-11-30 23:07:00.0태권도205456.377749451632.96032<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1913050000CDFH33010220240000012024-02-21<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2244-0012<NA><NA>서울특별시 동대문구 답십리동 241-10서울특별시 동대문구 답십리로 145-1, 4층 (답십리동)02540레전드복싱체육관 답십리점2024-02-21 10:06:29I2023-12-01 22:03:00.0권투204906.34602452312.235535<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1923050000CDFH33010220240000022024-03-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 휘경동 34-48서울특별시 동대문구 망우로 120, 3층 (휘경동)02501렉스짐2024-03-08 10:44:20I2023-12-02 23:00:00.0권투205804.989007454312.287026<NA><NA><NA><NA><NA><NA><NA><NA><NA>
1933050000CDFH33010220240000032024-04-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 433-3서울특별시 동대문구 장한로 24, 호성빌딩 3층 (장안동)02644플렉스 복싱 PT2024-04-05 17:32:55I2023-12-04 00:07:00.0권투205782.949042451237.510869<NA><NA><NA><NA><NA><NA><NA><NA><NA>