Overview

Dataset statistics

Number of variables34
Number of observations273
Missing cells2948
Missing cells (%)31.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.2 KiB
Average record size in memory289.5 B

Variable types

Categorical12
Text7
DateTime4
Unsupported7
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-19837/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 273 (100.0%) missing valuesMissing
폐업일자 has 150 (54.9%) missing valuesMissing
휴업시작일자 has 273 (100.0%) missing valuesMissing
휴업종료일자 has 273 (100.0%) missing valuesMissing
재개업일자 has 273 (100.0%) missing valuesMissing
전화번호 has 192 (70.3%) missing valuesMissing
소재지면적 has 273 (100.0%) missing valuesMissing
소재지우편번호 has 83 (30.4%) missing valuesMissing
도로명주소 has 10 (3.7%) missing valuesMissing
도로명우편번호 has 135 (49.5%) missing valuesMissing
좌표정보(X) has 7 (2.6%) missing valuesMissing
좌표정보(Y) has 7 (2.6%) missing valuesMissing
건축물연면적 has 193 (70.7%) missing valuesMissing
회원모집총인원 has 260 (95.2%) missing valuesMissing
세부업종명 has 273 (100.0%) missing valuesMissing
법인명 has 273 (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
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 61 (22.3%) zerosZeros
회원모집총인원 has 6 (2.2%) zerosZeros

Reproduction

Analysis started2024-04-06 12:32:31.194649
Analysis finished2024-04-06 12:32:32.230854
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
3100000
273 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 273
100.0%

Length

2024-04-06T21:32:32.365168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:32.543249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 273
100.0%

관리번호
Text

UNIQUE 

Distinct273
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-06T21:32:32.843817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters5460
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

Unique273 ?
Unique (%)100.0%

Sample

1st rowCDFH3301021989000001
2nd rowCDFH3301021989000002
3rd rowCDFH3301021989000003
4th rowCDFH3301021990000001
5th rowCDFH3301021990000002
ValueCountFrequency (%)
cdfh3301021989000001 1
 
0.4%
cdfh3301022009000003 1
 
0.4%
cdfh3301022007000012 1
 
0.4%
cdfh3301022008000001 1
 
0.4%
cdfh3301022008000003 1
 
0.4%
cdfh3301022009000001 1
 
0.4%
cdfh3301022009000002 1
 
0.4%
cdfh3301022004000011 1
 
0.4%
cdfh3301022009000005 1
 
0.4%
cdfh3301022009000004 1
 
0.4%
Other values (263) 263
96.3%
2024-04-06T21:32:33.441650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2220
40.7%
3 607
 
11.1%
2 607
 
11.1%
1 526
 
9.6%
C 273
 
5.0%
D 273
 
5.0%
F 273
 
5.0%
H 273
 
5.0%
9 166
 
3.0%
4 61
 
1.1%
Other values (4) 181
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4368
80.0%
Uppercase Letter 1092
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2220
50.8%
3 607
 
13.9%
2 607
 
13.9%
1 526
 
12.0%
9 166
 
3.8%
4 61
 
1.4%
5 54
 
1.2%
7 50
 
1.1%
6 39
 
0.9%
8 38
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 273
25.0%
D 273
25.0%
F 273
25.0%
H 273
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4368
80.0%
Latin 1092
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2220
50.8%
3 607
 
13.9%
2 607
 
13.9%
1 526
 
12.0%
9 166
 
3.8%
4 61
 
1.4%
5 54
 
1.2%
7 50
 
1.1%
6 39
 
0.9%
8 38
 
0.9%
Latin
ValueCountFrequency (%)
C 273
25.0%
D 273
25.0%
F 273
25.0%
H 273
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2220
40.7%
3 607
 
11.1%
2 607
 
11.1%
1 526
 
9.6%
C 273
 
5.0%
D 273
 
5.0%
F 273
 
5.0%
H 273
 
5.0%
9 166
 
3.0%
4 61
 
1.1%
Other values (4) 181
 
3.3%

인허가일자
Date

Distinct255
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum1989-11-10 00:00:00
Maximum2024-01-24 00:00:00
2024-04-06T21:32:33.756018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:32:34.064266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
1
150 
3
100 
4
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 150
54.9%
3 100
36.6%
4 23
 
8.4%

Length

2024-04-06T21:32:34.361578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:34.573824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 150
54.9%
3 100
36.6%
4 23
 
8.4%

영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
영업/정상
150 
폐업
100 
취소/말소/만료/정지/중지
23 

Length

Max length14
Median length5
Mean length4.6593407
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 150
54.9%
폐업 100
36.6%
취소/말소/만료/정지/중지 23
 
8.4%

Length

2024-04-06T21:32:34.852321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:35.155627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 150
54.9%
폐업 100
36.6%
취소/말소/만료/정지/중지 23
 
8.4%

상세영업상태코드
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
13
150 
3
100 
35
23 

Length

Max length2
Median length2
Mean length1.6336996
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 150
54.9%
3 100
36.6%
35 23
 
8.4%

Length

2024-04-06T21:32:35.499997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:35.745988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 150
54.9%
3 100
36.6%
35 23
 
8.4%

상세영업상태명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
영업중
150 
폐업
100 
직권말소
23 

Length

Max length4
Median length3
Mean length2.7179487
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 150
54.9%
폐업 100
36.6%
직권말소 23
 
8.4%

Length

2024-04-06T21:32:36.043071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:36.376676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 150
54.9%
폐업 100
36.6%
직권말소 23
 
8.4%

폐업일자
Date

MISSING 

Distinct99
Distinct (%)80.5%
Missing150
Missing (%)54.9%
Memory size2.3 KiB
Minimum1995-10-17 00:00:00
Maximum2024-02-05 00:00:00
2024-04-06T21:32:36.699846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:32:37.087604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

전화번호
Text

MISSING 

Distinct78
Distinct (%)96.3%
Missing192
Missing (%)70.3%
Memory size2.3 KiB
2024-04-06T21:32:37.766012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.691358
Min length7

Characters and Unicode

Total characters785
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)92.6%

Sample

1st row02-971-7339
2nd row911-7971
3rd row02-937-3254
4th row932-5071
5th row932-2687
ValueCountFrequency (%)
932-2687 2
 
2.5%
02-935-9312 2
 
2.5%
930-7003 2
 
2.5%
02-977-0505 1
 
1.2%
02-930-8623 1
 
1.2%
975-2004 1
 
1.2%
9434777 1
 
1.2%
976-4500 1
 
1.2%
933-3466 1
 
1.2%
935-0227 1
 
1.2%
Other values (68) 68
84.0%
2024-04-06T21:32:38.688458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 121
15.4%
9 119
15.2%
0 102
13.0%
2 95
12.1%
3 91
11.6%
7 64
8.2%
1 48
 
6.1%
5 42
 
5.4%
8 38
 
4.8%
4 33
 
4.2%
Other values (2) 32
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 662
84.3%
Dash Punctuation 121
 
15.4%
Close Punctuation 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 119
18.0%
0 102
15.4%
2 95
14.4%
3 91
13.7%
7 64
9.7%
1 48
7.3%
5 42
 
6.3%
8 38
 
5.7%
4 33
 
5.0%
6 30
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 785
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 121
15.4%
9 119
15.2%
0 102
13.0%
2 95
12.1%
3 91
11.6%
7 64
8.2%
1 48
 
6.1%
5 42
 
5.4%
8 38
 
4.8%
4 33
 
4.2%
Other values (2) 32
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 785
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 121
15.4%
9 119
15.2%
0 102
13.0%
2 95
12.1%
3 91
11.6%
7 64
8.2%
1 48
 
6.1%
5 42
 
5.4%
8 38
 
4.8%
4 33
 
4.2%
Other values (2) 32
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

소재지우편번호
Text

MISSING 

Distinct77
Distinct (%)40.5%
Missing83
Missing (%)30.4%
Memory size2.3 KiB
2024-04-06T21:32:39.303333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0157895
Min length6

Characters and Unicode

Total characters1143
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

Unique28 ?
Unique (%)14.7%

Sample

1st row139802
2nd row139837
3rd row139845
4th row139822
5th row139836
ValueCountFrequency (%)
139837 8
 
4.2%
139816 7
 
3.7%
139800 6
 
3.2%
139852 6
 
3.2%
139820 5
 
2.6%
139818 5
 
2.6%
139854 5
 
2.6%
139859 5
 
2.6%
139848 4
 
2.1%
139815 4
 
2.1%
Other values (67) 135
71.1%
2024-04-06T21:32:40.086507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 240
21.0%
3 231
20.2%
9 206
18.0%
8 176
15.4%
0 68
 
5.9%
2 61
 
5.3%
5 49
 
4.3%
6 41
 
3.6%
7 38
 
3.3%
4 30
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1140
99.7%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 240
21.1%
3 231
20.3%
9 206
18.1%
8 176
15.4%
0 68
 
6.0%
2 61
 
5.4%
5 49
 
4.3%
6 41
 
3.6%
7 38
 
3.3%
4 30
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1143
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 240
21.0%
3 231
20.2%
9 206
18.0%
8 176
15.4%
0 68
 
5.9%
2 61
 
5.3%
5 49
 
4.3%
6 41
 
3.6%
7 38
 
3.3%
4 30
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 240
21.0%
3 231
20.2%
9 206
18.0%
8 176
15.4%
0 68
 
5.9%
2 61
 
5.3%
5 49
 
4.3%
6 41
 
3.6%
7 38
 
3.3%
4 30
 
2.6%

지번주소
Text

Distinct264
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-06T21:32:40.842754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length27.201465
Min length18

Characters and Unicode

Total characters7426
Distinct characters185
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

Unique255 ?
Unique (%)93.4%

Sample

1st row서울특별시 노원구 공릉동 333-15번지 5층
2nd row서울특별시 노원구 상계동 1007-3번지
3rd row서울특별시 노원구 월계동 391-1번지 2층동
4th row서울특별시 노원구 하계동 271-3 신한은행
5th row서울특별시 노원구 상계동 639-1
ValueCountFrequency (%)
서울특별시 273
19.5%
노원구 273
19.5%
상계동 129
 
9.2%
중계동 50
 
3.6%
월계동 41
 
2.9%
공릉동 37
 
2.6%
2층 34
 
2.4%
3층 23
 
1.6%
4층 16
 
1.1%
하계동 16
 
1.1%
Other values (418) 506
36.2%
2024-04-06T21:32:41.752236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1338
 
18.0%
동 300
 
4.0%
원 293
 
3.9%
구 277
 
3.7%
시 276
 
3.7%
서 274
 
3.7%
울 274
 
3.7%
특 273
 
3.7%
별 273
 
3.7%
노 273
 
3.7%
Other values (175) 3575
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4338
58.4%
Decimal Number 1464
 
19.7%
Space Separator 1338
 
18.0%
Dash Punctuation 218
 
2.9%
Close Punctuation 22
 
0.3%
Other Punctuation 21
 
0.3%
Open Punctuation 20
 
0.3%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 300
 
6.9%
원 293
 
6.8%
구 277
 
6.4%
시 276
 
6.4%
서 274
 
6.3%
울 274
 
6.3%
특 273
 
6.3%
별 273
 
6.3%
노 273
 
6.3%
계 252
 
5.8%
Other values (155) 1573
36.3%
Decimal Number
ValueCountFrequency (%)
1 226
15.4%
2 212
14.5%
3 204
13.9%
4 149
10.2%
6 146
10.0%
0 145
9.9%
5 109
7.4%
7 98
6.7%
8 88
 
6.0%
9 87
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
F 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 19
90.5%
@ 2
 
9.5%
Space Separator
ValueCountFrequency (%)
1338
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4338
58.4%
Common 3084
41.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 300
 
6.9%
원 293
 
6.8%
구 277
 
6.4%
시 276
 
6.4%
서 274
 
6.3%
울 274
 
6.3%
특 273
 
6.3%
별 273
 
6.3%
노 273
 
6.3%
계 252
 
5.8%
Other values (155) 1573
36.3%
Common
ValueCountFrequency (%)
1338
43.4%
1 226
 
7.3%
- 218
 
7.1%
2 212
 
6.9%
3 204
 
6.6%
4 149
 
4.8%
6 146
 
4.7%
0 145
 
4.7%
5 109
 
3.5%
7 98
 
3.2%
Other values (7) 239
 
7.7%
Latin
ValueCountFrequency (%)
A 2
50.0%
F 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4338
58.4%
ASCII 3088
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1338
43.3%
1 226
 
7.3%
- 218
 
7.1%
2 212
 
6.9%
3 204
 
6.6%
4 149
 
4.8%
6 146
 
4.7%
0 145
 
4.7%
5 109
 
3.5%
7 98
 
3.2%
Other values (10) 243
 
7.9%
Hangul
ValueCountFrequency (%)
동 300
 
6.9%
원 293
 
6.8%
구 277
 
6.4%
시 276
 
6.4%
서 274
 
6.3%
울 274
 
6.3%
특 273
 
6.3%
별 273
 
6.3%
노 273
 
6.3%
계 252
 
5.8%
Other values (155) 1573
36.3%

도로명주소
Text

MISSING 

Distinct261
Distinct (%)99.2%
Missing10
Missing (%)3.7%
Memory size2.3 KiB
2024-04-06T21:32:42.239486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length33.456274
Min length22

Characters and Unicode

Total characters8799
Distinct characters192
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

Unique259 ?
Unique (%)98.5%

Sample

1st row서울특별시 노원구 공릉로34길 4 (공릉동,5층)
2nd row서울특별시 노원구 광운로 53, 2층동 (월계동)
3rd row서울특별시 노원구 섬밭로 209, 벽산상가 4층 412, 412-1호 (하계동)
4th row서울특별시 노원구 한글비석로 474 (상계동)
5th row서울특별시 노원구 동일로 1593 (상계동)
ValueCountFrequency (%)
서울특별시 263
 
16.2%
노원구 263
 
16.2%
상계동 75
 
4.6%
3층 36
 
2.2%
2층 32
 
2.0%
중계동 30
 
1.8%
동일로 30
 
1.8%
한글비석로 26
 
1.6%
월계동 23
 
1.4%
공릉동 20
 
1.2%
Other values (495) 827
50.9%
2024-04-06T21:32:43.641925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1423
 
16.2%
동 366
 
4.2%
원 306
 
3.5%
, 297
 
3.4%
계 293
 
3.3%
노 282
 
3.2%
) 281
 
3.2%
( 279
 
3.2%
2 276
 
3.1%
시 266
 
3.0%
Other values (182) 4730
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5032
57.2%
Decimal Number 1450
 
16.5%
Space Separator 1423
 
16.2%
Other Punctuation 297
 
3.4%
Close Punctuation 281
 
3.2%
Open Punctuation 279
 
3.2%
Dash Punctuation 22
 
0.3%
Uppercase Letter 12
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 366
 
7.3%
원 306
 
6.1%
계 293
 
5.8%
노 282
 
5.6%
시 266
 
5.3%
구 265
 
5.3%
서 264
 
5.2%
울 264
 
5.2%
로 264
 
5.2%
특 263
 
5.2%
Other values (158) 2199
43.7%
Decimal Number
ValueCountFrequency (%)
2 276
19.0%
1 241
16.6%
3 220
15.2%
4 174
12.0%
0 138
9.5%
5 105
 
7.2%
6 91
 
6.3%
7 85
 
5.9%
9 63
 
4.3%
8 57
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 5
41.7%
S 2
 
16.7%
L 1
 
8.3%
A 1
 
8.3%
G 1
 
8.3%
Y 1
 
8.3%
K 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1423
100.0%
Other Punctuation
ValueCountFrequency (%)
, 297
100.0%
Close Punctuation
ValueCountFrequency (%)
) 281
100.0%
Open Punctuation
ValueCountFrequency (%)
( 279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5032
57.2%
Common 3753
42.7%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 366
 
7.3%
원 306
 
6.1%
계 293
 
5.8%
노 282
 
5.6%
시 266
 
5.3%
구 265
 
5.3%
서 264
 
5.2%
울 264
 
5.2%
로 264
 
5.2%
특 263
 
5.2%
Other values (158) 2199
43.7%
Common
ValueCountFrequency (%)
1423
37.9%
, 297
 
7.9%
) 281
 
7.5%
( 279
 
7.4%
2 276
 
7.4%
1 241
 
6.4%
3 220
 
5.9%
4 174
 
4.6%
0 138
 
3.7%
5 105
 
2.8%
Other values (6) 319
 
8.5%
Latin
ValueCountFrequency (%)
B 5
35.7%
b 2
 
14.3%
S 2
 
14.3%
L 1
 
7.1%
A 1
 
7.1%
G 1
 
7.1%
Y 1
 
7.1%
K 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5032
57.2%
ASCII 3767
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1423
37.8%
, 297
 
7.9%
) 281
 
7.5%
( 279
 
7.4%
2 276
 
7.3%
1 241
 
6.4%
3 220
 
5.8%
4 174
 
4.6%
0 138
 
3.7%
5 105
 
2.8%
Other values (14) 333
 
8.8%
Hangul
ValueCountFrequency (%)
동 366
 
7.3%
원 306
 
6.1%
계 293
 
5.8%
노 282
 
5.6%
시 266
 
5.3%
구 265
 
5.3%
서 264
 
5.2%
울 264
 
5.2%
로 264
 
5.2%
특 263
 
5.2%
Other values (158) 2199
43.7%

도로명우편번호
Text

MISSING 

Distinct98
Distinct (%)71.0%
Missing135
Missing (%)49.5%
Memory size2.3 KiB
2024-04-06T21:32:44.198236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1666667
Min length5

Characters and Unicode

Total characters713
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

Unique67 ?
Unique (%)48.6%

Sample

1st row01776
2nd row01673
3rd row139820
4th row139837
5th row01755
ValueCountFrequency (%)
01693 4
 
2.9%
01765 4
 
2.9%
01790 4
 
2.9%
01679 3
 
2.2%
01778 3
 
2.2%
01762 3
 
2.2%
01604 2
 
1.4%
01619 2
 
1.4%
139854 2
 
1.4%
01734 2
 
1.4%
Other values (88) 109
79.0%
2024-04-06T21:32:45.132018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 170
23.8%
0 152
21.3%
6 77
10.8%
9 64
 
9.0%
7 63
 
8.8%
8 59
 
8.3%
3 47
 
6.6%
5 30
 
4.2%
4 26
 
3.6%
2 24
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 712
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 170
23.9%
0 152
21.3%
6 77
10.8%
9 64
 
9.0%
7 63
 
8.8%
8 59
 
8.3%
3 47
 
6.6%
5 30
 
4.2%
4 26
 
3.7%
2 24
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 713
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 170
23.8%
0 152
21.3%
6 77
10.8%
9 64
 
9.0%
7 63
 
8.8%
8 59
 
8.3%
3 47
 
6.6%
5 30
 
4.2%
4 26
 
3.6%
2 24
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 713
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 170
23.8%
0 152
21.3%
6 77
10.8%
9 64
 
9.0%
7 63
 
8.8%
8 59
 
8.3%
3 47
 
6.6%
5 30
 
4.2%
4 26
 
3.6%
2 24
 
3.4%

사업장명
Text

Distinct263
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-04-06T21:32:45.669364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length7.7106227
Min length2

Characters and Unicode

Total characters2105
Distinct characters258
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)93.0%

Sample

1st row현대 태권도
2nd row구룡체육관
3rd row한국체육관
4th row탑태권도장(노원)
5th row경희대대한2태권도
ValueCountFrequency (%)
태권도 20
 
5.1%
용인대 11
 
2.8%
태권도장 9
 
2.3%
체육관 6
 
1.5%
한국체대 4
 
1.0%
노원점 4
 
1.0%
복싱 4
 
1.0%
경희대 4
 
1.0%
한국태권도장 3
 
0.8%
국가대표 3
 
0.8%
Other values (301) 325
82.7%
2024-04-06T21:32:46.582200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 173
 
8.2%
태 144
 
6.8%
권 144
 
6.8%
120
 
5.7%
관 105
 
5.0%
체 85
 
4.0%
육 78
 
3.7%
대 75
 
3.6%
장 59
 
2.8%
한 35
 
1.7%
Other values (248) 1087
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1899
90.2%
Space Separator 120
 
5.7%
Uppercase Letter 62
 
2.9%
Decimal Number 9
 
0.4%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Other Punctuation 4
 
0.2%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 173
 
9.1%
태 144
 
7.6%
권 144
 
7.6%
관 105
 
5.5%
체 85
 
4.5%
육 78
 
4.1%
대 75
 
3.9%
장 59
 
3.1%
한 35
 
1.8%
복 29
 
1.5%
Other values (217) 972
51.2%
Uppercase Letter
ValueCountFrequency (%)
T 11
17.7%
P 7
11.3%
O 5
 
8.1%
S 4
 
6.5%
I 4
 
6.5%
B 4
 
6.5%
Y 3
 
4.8%
M 3
 
4.8%
N 3
 
4.8%
G 3
 
4.8%
Other values (9) 15
24.2%
Decimal Number
ValueCountFrequency (%)
2 5
55.6%
3 3
33.3%
4 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
! 1
25.0%
' 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
i 1
33.3%
o 1
33.3%
Space Separator
ValueCountFrequency (%)
120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1899
90.2%
Common 141
 
6.7%
Latin 65
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 173
 
9.1%
태 144
 
7.6%
권 144
 
7.6%
관 105
 
5.5%
체 85
 
4.5%
육 78
 
4.1%
대 75
 
3.9%
장 59
 
3.1%
한 35
 
1.8%
복 29
 
1.5%
Other values (217) 972
51.2%
Latin
ValueCountFrequency (%)
T 11
16.9%
P 7
 
10.8%
O 5
 
7.7%
S 4
 
6.2%
I 4
 
6.2%
B 4
 
6.2%
Y 3
 
4.6%
M 3
 
4.6%
N 3
 
4.6%
G 3
 
4.6%
Other values (12) 18
27.7%
Common
ValueCountFrequency (%)
120
85.1%
2 5
 
3.5%
) 4
 
2.8%
( 4
 
2.8%
3 3
 
2.1%
& 2
 
1.4%
! 1
 
0.7%
' 1
 
0.7%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1899
90.2%
ASCII 206
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 173
 
9.1%
태 144
 
7.6%
권 144
 
7.6%
관 105
 
5.5%
체 85
 
4.5%
육 78
 
4.1%
대 75
 
3.9%
장 59
 
3.1%
한 35
 
1.8%
복 29
 
1.5%
Other values (217) 972
51.2%
ASCII
ValueCountFrequency (%)
120
58.3%
T 11
 
5.3%
P 7
 
3.4%
2 5
 
2.4%
O 5
 
2.4%
S 4
 
1.9%
I 4
 
1.9%
) 4
 
1.9%
( 4
 
1.9%
B 4
 
1.9%
Other values (21) 38
 
18.4%

최종수정일자
Date

Distinct251
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2003-02-21 10:29:10
Maximum2024-03-25 09:34:02
2024-04-06T21:32:47.008855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:32:47.380163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
U
158 
I
115 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 158
57.9%
I 115
42.1%

Length

2024-04-06T21:32:47.758388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:48.012052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 158
57.9%
i 115
42.1%

데이터갱신일자
Date

Distinct87
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:07:00
2024-04-06T21:32:48.261986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:32:48.620877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct7
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
태권도
117 
<NA>
102 
권투
32 
검도
 
7
합기도
 
7
Other values (2)
 
8

Length

Max length4
Median length3
Mean length3.2087912
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
태권도 117
42.9%
<NA> 102
37.4%
권투 32
 
11.7%
검도 7
 
2.6%
합기도 7
 
2.6%
유도 6
 
2.2%
레슬링 2
 
0.7%

Length

2024-04-06T21:32:48.998659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:49.302127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태권도 117
42.9%
na 102
37.4%
권투 32
 
11.7%
검도 7
 
2.6%
합기도 7
 
2.6%
유도 6
 
2.2%
레슬링 2
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct213
Distinct (%)80.1%
Missing7
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean205863.66
Minimum203737.41
Maximum207794.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-06T21:32:49.565660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203737.41
5-th percentile204593.15
Q1205172.5
median205894.76
Q3206563.34
95-th percentile207200.1
Maximum207794.26
Range4056.8496
Interquartile range (IQR)1390.8351

Descriptive statistics

Standard deviation867.47601
Coefficient of variation (CV)0.0042138375
Kurtosis-0.76362252
Mean205863.66
Median Absolute Deviation (MAD)705.82649
Skewness-0.073524969
Sum54759733
Variance752514.63
MonotonicityNot monotonic
2024-04-06T21:32:49.940609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205588.636016926 4
 
1.5%
205184.859621353 4
 
1.5%
205984.15211292 3
 
1.1%
206179.721259442 3
 
1.1%
205448.805750683 3
 
1.1%
206787.785139191 3
 
1.1%
206979.17849497 3
 
1.1%
205455.618698896 3
 
1.1%
204489.998187538 2
 
0.7%
206087.293296068 2
 
0.7%
Other values (203) 236
86.4%
(Missing) 7
 
2.6%
ValueCountFrequency (%)
203737.409404091 1
0.4%
203762.973030298 1
0.4%
203786.584663472 1
0.4%
203802.357238897 1
0.4%
203809.293429767 1
0.4%
204325.989587591 1
0.4%
204341.190263103 2
0.7%
204481.248686527 1
0.4%
204489.998187538 2
0.7%
204520.027934136 1
0.4%
ValueCountFrequency (%)
207794.259011921 1
0.4%
207642.144523897 1
0.4%
207602.35326675 1
0.4%
207416.586869686 2
0.7%
207345.508311081 1
0.4%
207274.300313358 1
0.4%
207272.357325927 1
0.4%
207265.771476959 1
0.4%
207261.781710467 1
0.4%
207254.060871726 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct213
Distinct (%)80.1%
Missing7
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean460674.87
Minimum457109.44
Maximum465253.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-06T21:32:50.405499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457109.44
5-th percentile457366.57
Q1458591.32
median461050.18
Q3462278.68
95-th percentile463590.81
Maximum465253.15
Range8143.707
Interquartile range (IQR)3687.3594

Descriptive statistics

Standard deviation2036.1302
Coefficient of variation (CV)0.0044198854
Kurtosis-1.1102416
Mean460674.87
Median Absolute Deviation (MAD)1556.3636
Skewness-0.17945268
Sum1.2253952 × 108
Variance4145826
MonotonicityNot monotonic
2024-04-06T21:32:50.726246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459964.099651861 4
 
1.5%
460543.29200918 4
 
1.5%
457275.799282625 3
 
1.1%
461730.955043154 3
 
1.1%
458564.347940661 3
 
1.1%
461559.743384567 3
 
1.1%
462665.966600711 3
 
1.1%
457358.731978332 3
 
1.1%
458912.083095685 2
 
0.7%
459625.877064728 2
 
0.7%
Other values (203) 236
86.4%
(Missing) 7
 
2.6%
ValueCountFrequency (%)
457109.444987681 2
0.7%
457132.041111567 1
 
0.4%
457170.948044949 1
 
0.4%
457182.860460769 1
 
0.4%
457194.378388243 1
 
0.4%
457205.957830975 1
 
0.4%
457275.799282625 3
1.1%
457353.229350385 1
 
0.4%
457358.731978332 3
1.1%
457390.078805111 1
 
0.4%
ValueCountFrequency (%)
465253.152004 1
0.4%
464959.058464501 1
0.4%
464356.527197506 1
0.4%
464208.305428933 1
0.4%
464174.158420444 2
0.7%
463982.914952977 1
0.4%
463805.802213944 1
0.4%
463801.64757776 2
0.7%
463778.901178769 1
0.4%
463710.871027012 1
0.4%

문화체육업종명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
체육도장업
231 
<NA>
42 

Length

Max length5
Median length5
Mean length4.8461538
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 231
84.6%
<NA> 42
 
15.4%

Length

2024-04-06T21:32:51.138950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:51.339305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 231
84.6%
na 42
 
15.4%

공사립구분명
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
사립
231 
<NA>
42 

Length

Max length4
Median length2
Mean length2.3076923
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 231
84.6%
<NA> 42
 
15.4%

Length

2024-04-06T21:32:51.671283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:52.087044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 231
84.6%
na 42
 
15.4%

보험가입여부코드
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
239 
0
34 

Length

Max length4
Median length4
Mean length3.6263736
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> 239
87.5%
0 34
 
12.5%

Length

2024-04-06T21:32:52.320982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:52.519759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 239
87.5%
0 34
 
12.5%

지도자수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
190 
0
55 
1
27 
2
 
1

Length

Max length4
Median length4
Mean length3.0879121
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 190
69.6%
0 55
 
20.1%
1 27
 
9.9%
2 1
 
0.4%

Length

2024-04-06T21:32:52.727212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:52.935007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 190
69.6%
0 55
 
20.1%
1 27
 
9.9%
2 1
 
0.4%

건축물동수
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
<NA>
190 
0
78 
1
 
5

Length

Max length4
Median length4
Mean length3.0879121
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 190
69.6%
0 78
28.6%
1 5
 
1.8%

Length

2024-04-06T21:32:53.183967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:32:53.457020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 190
69.6%
0 78
28.6%
1 5
 
1.8%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)25.0%
Missing193
Missing (%)70.7%
Infinite0
Infinite (%)0.0%
Mean249.34025
Minimum0
Maximum3067.76
Zeros61
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-06T21:32:53.648958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1681.0135
Maximum3067.76
Range3067.76
Interquartile range (IQR)0

Descriptive statistics

Standard deviation589.54116
Coefficient of variation (CV)2.3644043
Kurtosis8.062157
Mean249.34025
Median Absolute Deviation (MAD)0
Skewness2.7919638
Sum19947.22
Variance347558.78
MonotonicityNot monotonic
2024-04-06T21:32:53.899045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 61
 
22.3%
177.3 1
 
0.4%
555.98 1
 
0.4%
1681.0 1
 
0.4%
873.38 1
 
0.4%
900.32 1
 
0.4%
985.91 1
 
0.4%
343.48 1
 
0.4%
1559.06 1
 
0.4%
372.84 1
 
0.4%
Other values (10) 10
 
3.7%
(Missing) 193
70.7%
ValueCountFrequency (%)
0.0 61
22.3%
87.38 1
 
0.4%
133.92 1
 
0.4%
177.3 1
 
0.4%
343.48 1
 
0.4%
372.84 1
 
0.4%
525.78 1
 
0.4%
555.98 1
 
0.4%
638.73 1
 
0.4%
873.38 1
 
0.4%
ValueCountFrequency (%)
3067.76 1
0.4%
2258.35 1
0.4%
1720.0 1
0.4%
1681.27 1
0.4%
1681.0 1
0.4%
1559.06 1
0.4%
1493.66 1
0.4%
985.91 1
0.4%
900.32 1
0.4%
891.1 1
0.4%

회원모집총인원
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)46.2%
Missing260
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean75
Minimum0
Maximum500
Zeros6
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-06T21:32:54.135731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50
Q3100
95-th percentile260
Maximum500
Range500
Interquartile range (IQR)100

Descriptive statistics

Standard deviation134.53624
Coefficient of variation (CV)1.7938165
Kurtosis9.8841144
Mean75
Median Absolute Deviation (MAD)50
Skewness3.0034044
Sum975
Variance18100
MonotonicityNot monotonic
2024-04-06T21:32:54.362864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 6
 
2.2%
100 3
 
1.1%
65 1
 
0.4%
500 1
 
0.4%
60 1
 
0.4%
50 1
 
0.4%
(Missing) 260
95.2%
ValueCountFrequency (%)
0 6
2.2%
50 1
 
0.4%
60 1
 
0.4%
65 1
 
0.4%
100 3
1.1%
500 1
 
0.4%
ValueCountFrequency (%)
500 1
 
0.4%
100 3
1.1%
65 1
 
0.4%
60 1
 
0.4%
50 1
 
0.4%
0 6
2.2%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing273
Missing (%)100.0%
Memory size2.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03100000CDFH330102198900000119891110<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>139802서울특별시 노원구 공릉동 333-15번지 5층서울특별시 노원구 공릉로34길 4 (공릉동,5층)<NA>현대 태권도2020-04-16 18:09:02U2020-04-18 02:40:00.0태권도206953.275249457765.958555체육도장업사립<NA>000.0<NA><NA><NA>
13100000CDFH330102198900000219891122<NA>3폐업3폐업19990126<NA><NA><NA><NA><NA>139837서울특별시 노원구 상계동 1007-3번지<NA><NA>구룡체육관2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>205111.044964463551.35139체육도장업사립<NA>000.0<NA><NA><NA>
23100000CDFH330102198900000319891207<NA>3폐업3폐업19990628<NA><NA><NA><NA><NA>139845서울특별시 노원구 월계동 391-1번지 2층동서울특별시 노원구 광운로 53, 2층동 (월계동)<NA>한국체육관2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>205164.638884457785.012114체육도장업사립<NA>000.0<NA><NA><NA>
33100000CDFH330102199000000119900814<NA>1영업/정상13영업중<NA><NA><NA><NA>02-971-7339<NA><NA>서울특별시 노원구 하계동 271-3 신한은행서울특별시 노원구 섬밭로 209, 벽산상가 4층 412, 412-1호 (하계동)01776탑태권도장(노원)2022-09-29 10:21:00U2021-10-31 00:01:00.0태권도205601.066016459233.675552<NA><NA><NA><NA><NA><NA><NA><NA><NA>
43100000CDFH330102199000000219901127<NA>3폐업3폐업20210622<NA><NA><NA><NA><NA>139822서울특별시 노원구 상계동 639-1서울특별시 노원구 한글비석로 474 (상계동)<NA>경희대대한2태권도2021-06-22 15:42:34U2021-06-24 02:40:00.0태권도205707.281108462498.174061체육도장업사립<NA><NA>00.0<NA><NA><NA>
53100000CDFH330102199100000119910121<NA>3폐업3폐업19990204<NA><NA><NA><NA><NA>139836서울특별시 노원구 상계동 963-27번지서울특별시 노원구 동일로 1593 (상계동)<NA>충일태권도장2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>204848.859835463150.419641체육도장업사립<NA>000.0<NA><NA><NA>
63100000CDFH330102199100000219910430<NA>3폐업3폐업20090401<NA><NA><NA><NA><NA>139832서울특별시 노원구 상계동 749-8번지 삼양빌딩6층3호서울특별시 노원구 동일로 1350 (상계동,삼양빌딩6층3호)<NA>상계검도장2009-04-01 14:44:37I2018-08-31 23:59:59.0<NA>205437.99609460765.486013체육도장업사립<NA><NA>00.0<NA><NA><NA>
73100000CDFH330102199100000319910503<NA>3폐업3폐업19980615<NA><NA><NA><NA><NA>139848서울특별시 노원구 월계동 287-11번지서울특별시 노원구 월계로 337 (월계동)<NA>영재체육관2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>205025.704134458588.784835체육도장업사립<NA>000.0<NA><NA><NA>
83100000CDFH330102199200000119920625<NA>3폐업3폐업19951017<NA><NA><NA><NA><NA>139854서울특별시 노원구 중계동 62-6번지서울특별시 노원구 중계로10길 16 (중계동)<NA>한보체육관2003-02-21 10:29:10I2018-08-31 23:59:59.0<NA>207197.374022460438.981133체육도장업사립<NA>000.0<NA><NA><NA>
93100000CDFH330102199200000219921110<NA>3폐업3폐업19990820<NA><NA><NA><NA><NA>139827서울특별시 노원구 상계동 693-0번지 미도빌딩 5층동서울특별시 노원구 동일로 1426, 5층동 (상계동,미도빌딩)<NA>해동검도본관2019-08-30 15:44:40U2019-09-01 02:40:00.0<NA>205273.302427461515.158002체육도장업사립<NA>000.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
2633100000CDFH33010220230000022023-04-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 456-63 대명보습학원서울특별시 노원구 노원로34길 102, 대명보습학원 B1층 (상계동)01679리스펙다이어트PT 복싱체육관 노원점2023-10-24 10:22:10U2022-10-30 22:06:00.0권투205774.013876462345.354088<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2643100000CDFH33010220230000032023-04-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 730-3 다모아빌딩서울특별시 노원구 동일로 1379, 다모아빌딩 지층층 2호 (상계동)01762더뉴복싱2023-04-07 14:52:58I2022-12-04 00:09:00.0권투205302.900238461048.763789<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2653100000CDFH33010220230000042023-04-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 월계동 322-1 성원아파트서울특별시 노원구 마들로3길 37, 상가동 2층 201호 (월계동, 성원아파트)01907녹천태권도2023-04-07 15:46:48I2022-12-04 00:09:00.0태권도205448.805751458564.347941<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2663100000CDFH33010220230000052023-04-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 하계동 208-29 신흥약국서울특별시 노원구 공릉로 362, 신흥약국 3층 (하계동)01790한성태권도장2023-04-12 09:22:51I2022-12-03 23:04:00.0태권도206087.293296459625.877065<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2673100000CDFH33010220230000062023-06-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 중계동 503 동은유치원서울특별시 노원구 동일로207길 23, 동은유치원 4층 2호 (중계동)01778트리플 복싱 PT 다이어트 복싱 체육관(노원점)2023-06-09 14:17:34I2022-12-05 23:01:00.0권투205588.636017459964.099652<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2683100000CDFH33010220230000072023-06-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 중계동 58-64 득림빌딩서울특별시 노원구 중계로 120, 득림빌딩 4층 (중계동)01726국가태권도2023-06-09 13:35:46I2022-12-05 23:01:00.0태권도207149.521057460442.251692<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2693100000CDFH33010220230000082023-07-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 1023-1 유성상가서울특별시 노원구 동일로 1622, 유성상가 2층 1호 (상계동)01630수락주짓수파라에스트라 서울2023-07-19 15:13:26I2022-12-06 22:01:00.0권투204868.610895463402.191963<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2703100000CDFH33010220230000092023-08-21<NA>1영업/정상13영업중<NA><NA><NA><NA>02-935-9312<NA><NA>서울특별시 노원구 중계동 157-26 보고프라자서울특별시 노원구 덕릉로 680, 보고프라자 6층 601호 (중계동)01715위너스복싱PT다이어트복싱체육관 노원점2023-08-21 08:15:42I2022-12-07 22:03:00.0권투206589.201406461778.519083<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2713100000CDFH33010220230000102023-12-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 637-1 상계주공아파트(13단지)서울특별시 노원구 한글비석로54길 116, 상계주공아파트(13단지) 2층 206,207호 (상계동)01672나린태권도장2023-12-21 14:12:53I2022-11-01 22:03:00.0태권도205260.409756462881.259013<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2723100000CDFH33010220240000012024-01-24<NA>1영업/정상13영업중<NA><NA><NA><NA>02-4222-8237<NA><NA>서울특별시 노원구 상계동 693 미도빌딩서울특별시 노원구 동일로 1426, 미도빌딩 B1층 5호 (상계동)01694아율다 TK FIT2024-01-24 17:41:42I2023-11-30 22:06:00.0태권도205273.302427461515.158002<NA><NA><NA><NA><NA><NA><NA><NA><NA>