Overview

Dataset statistics

Number of variables34
Number of observations343
Missing cells3500
Missing cells (%)30.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.6 KiB
Average record size in memory291.4 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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-19641/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
문화체육업종명 is highly imbalanced (52.5%)Imbalance
공사립구분명 is highly imbalanced (52.5%)Imbalance
회원모집총인원 is highly imbalanced (90.8%)Imbalance
인허가취소일자 has 343 (100.0%) missing valuesMissing
폐업일자 has 90 (26.2%) missing valuesMissing
휴업시작일자 has 343 (100.0%) missing valuesMissing
휴업종료일자 has 343 (100.0%) missing valuesMissing
재개업일자 has 343 (100.0%) missing valuesMissing
전화번호 has 278 (81.0%) missing valuesMissing
소재지면적 has 343 (100.0%) missing valuesMissing
소재지우편번호 has 57 (16.6%) missing valuesMissing
도로명주소 has 8 (2.3%) missing valuesMissing
도로명우편번호 has 143 (41.7%) missing valuesMissing
업태구분명 has 343 (100.0%) missing valuesMissing
좌표정보(X) has 6 (1.7%) missing valuesMissing
좌표정보(Y) has 6 (1.7%) missing valuesMissing
건축물연면적 has 168 (49.0%) missing valuesMissing
세부업종명 has 343 (100.0%) missing valuesMissing
법인명 has 343 (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 134 (39.1%) zerosZeros

Reproduction

Analysis started2024-04-29 19:59:34.254556
Analysis finished2024-04-29 19:59:35.038065
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3140000
343 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 343
100.0%

Length

2024-04-30T04:59:35.099831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:35.189841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 343
100.0%

관리번호
Text

UNIQUE 

Distinct343
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:59:35.326477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters6860
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

Unique343 ?
Unique (%)100.0%

Sample

1st rowCDFH3301081980000001
2nd rowCDFH3301081982000001
3rd rowCDFH3301081982000002
4th rowCDFH3301081982000003
5th rowCDFH3301081983000001
ValueCountFrequency (%)
cdfh3301081980000001 1
 
0.3%
cdfh3301082007000006 1
 
0.3%
cdfh3301082007000024 1
 
0.3%
cdfh3301082007000023 1
 
0.3%
cdfh3301082007000022 1
 
0.3%
cdfh3301082007000021 1
 
0.3%
cdfh3301082007000020 1
 
0.3%
cdfh3301082007000019 1
 
0.3%
cdfh3301082007000018 1
 
0.3%
cdfh3301082007000017 1
 
0.3%
Other values (333) 333
97.1%
2024-04-30T04:59:35.636899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2696
39.3%
3 757
 
11.0%
1 721
 
10.5%
8 433
 
6.3%
C 343
 
5.0%
D 343
 
5.0%
F 343
 
5.0%
H 343
 
5.0%
9 313
 
4.6%
2 309
 
4.5%
Other values (4) 259
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5488
80.0%
Uppercase Letter 1372
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2696
49.1%
3 757
 
13.8%
1 721
 
13.1%
8 433
 
7.9%
9 313
 
5.7%
2 309
 
5.6%
7 72
 
1.3%
4 66
 
1.2%
5 64
 
1.2%
6 57
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 343
25.0%
D 343
25.0%
F 343
25.0%
H 343
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5488
80.0%
Latin 1372
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2696
49.1%
3 757
 
13.8%
1 721
 
13.1%
8 433
 
7.9%
9 313
 
5.7%
2 309
 
5.6%
7 72
 
1.3%
4 66
 
1.2%
5 64
 
1.2%
6 57
 
1.0%
Latin
ValueCountFrequency (%)
C 343
25.0%
D 343
25.0%
F 343
25.0%
H 343
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2696
39.3%
3 757
 
11.0%
1 721
 
10.5%
8 433
 
6.3%
C 343
 
5.0%
D 343
 
5.0%
F 343
 
5.0%
H 343
 
5.0%
9 313
 
4.6%
2 309
 
4.5%
Other values (4) 259
 
3.8%

인허가일자
Date

Distinct314
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1980-12-14 00:00:00
Maximum2023-10-30 00:00:00
2024-04-30T04:59:35.769971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:35.912144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
184 
1
90 
4
69 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 184
53.6%
1 90
26.2%
4 69
 
20.1%

Length

2024-04-30T04:59:36.027386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:36.120660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 184
53.6%
1 90
26.2%
4 69
 
20.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
184 
영업/정상
90 
취소/말소/만료/정지/중지
69 

Length

Max length14
Median length2
Mean length5.2011662
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 184
53.6%
영업/정상 90
26.2%
취소/말소/만료/정지/중지 69
 
20.1%

Length

2024-04-30T04:59:36.230644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:36.324132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 184
53.6%
영업/정상 90
26.2%
취소/말소/만료/정지/중지 69
 
20.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
184 
13
90 
35
69 

Length

Max length2
Median length1
Mean length1.4635569
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 184
53.6%
13 90
26.2%
35 69
 
20.1%

Length

2024-04-30T04:59:36.418236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:36.507638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 184
53.6%
13 90
26.2%
35 69
 
20.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
184 
영업중
90 
직권말소
69 

Length

Max length4
Median length2
Mean length2.664723
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 184
53.6%
영업중 90
26.2%
직권말소 69
 
20.1%

Length

2024-04-30T04:59:36.602169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:36.704316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 184
53.6%
영업중 90
26.2%
직권말소 69
 
20.1%

폐업일자
Date

MISSING 

Distinct185
Distinct (%)73.1%
Missing90
Missing (%)26.2%
Memory size2.8 KiB
Minimum1997-06-04 00:00:00
Maximum2024-02-02 00:00:00
2024-04-30T04:59:36.802570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:36.912189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

전화번호
Text

MISSING 

Distinct65
Distinct (%)100.0%
Missing278
Missing (%)81.0%
Memory size2.8 KiB
2024-04-30T04:59:37.148432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length10.076923
Min length8

Characters and Unicode

Total characters655
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

Unique65 ?
Unique (%)100.0%

Sample

1st row2693-3986
2nd row2604-9630
3rd row449-5451
4th row603-6671
5th row2695-0806
ValueCountFrequency (%)
2645-5592 1
 
1.5%
2605-2640 1
 
1.5%
2688-5068 1
 
1.5%
2066-3275 1
 
1.5%
2647-9346 1
 
1.5%
2601-3992 1
 
1.5%
2601-4939 1
 
1.5%
2695-4333 1
 
1.5%
2693-4841 1
 
1.5%
02-2644-0807 1
 
1.5%
Other values (55) 55
84.6%
2024-04-30T04:59:37.452651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 99
15.1%
6 92
14.0%
- 88
13.4%
0 75
11.5%
4 59
9.0%
5 55
8.4%
9 52
7.9%
3 39
 
6.0%
8 35
 
5.3%
1 34
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 567
86.6%
Dash Punctuation 88
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 99
17.5%
6 92
16.2%
0 75
13.2%
4 59
10.4%
5 55
9.7%
9 52
9.2%
3 39
 
6.9%
8 35
 
6.2%
1 34
 
6.0%
7 27
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 655
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 99
15.1%
6 92
14.0%
- 88
13.4%
0 75
11.5%
4 59
9.0%
5 55
8.4%
9 52
7.9%
3 39
 
6.0%
8 35
 
5.3%
1 34
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 655
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 99
15.1%
6 92
14.0%
- 88
13.4%
0 75
11.5%
4 59
9.0%
5 55
8.4%
9 52
7.9%
3 39
 
6.0%
8 35
 
5.3%
1 34
 
5.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

소재지우편번호
Text

MISSING 

Distinct67
Distinct (%)23.4%
Missing57
Missing (%)16.6%
Memory size2.8 KiB
2024-04-30T04:59:37.664823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0244755
Min length6

Characters and Unicode

Total characters1723
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

Unique24 ?
Unique (%)8.4%

Sample

1st row158808
2nd row158814
3rd row158851
4th row158824
5th row158822
ValueCountFrequency (%)
158857 18
 
6.3%
158806 15
 
5.2%
158811 12
 
4.2%
158827 11
 
3.8%
158819 11
 
3.8%
158070 11
 
3.8%
158808 11
 
3.8%
158849 10
 
3.5%
158838 9
 
3.1%
158840 9
 
3.1%
Other values (57) 169
59.1%
2024-04-30T04:59:37.996458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 594
34.5%
1 361
21.0%
5 356
20.7%
0 88
 
5.1%
4 73
 
4.2%
6 58
 
3.4%
2 58
 
3.4%
7 52
 
3.0%
3 39
 
2.3%
9 37
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1716
99.6%
Dash Punctuation 7
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 594
34.6%
1 361
21.0%
5 356
20.7%
0 88
 
5.1%
4 73
 
4.3%
6 58
 
3.4%
2 58
 
3.4%
7 52
 
3.0%
3 39
 
2.3%
9 37
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1723
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 594
34.5%
1 361
21.0%
5 356
20.7%
0 88
 
5.1%
4 73
 
4.2%
6 58
 
3.4%
2 58
 
3.4%
7 52
 
3.0%
3 39
 
2.3%
9 37
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1723
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 594
34.5%
1 361
21.0%
5 356
20.7%
0 88
 
5.1%
4 73
 
4.2%
6 58
 
3.4%
2 58
 
3.4%
7 52
 
3.0%
3 39
 
2.3%
9 37
 
2.1%

지번주소
Text

Distinct329
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:59:38.278799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length23.431487
Min length16

Characters and Unicode

Total characters8037
Distinct characters91
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

Unique316 ?
Unique (%)92.1%

Sample

1st row서울특별시 양천구 목동 513-11번지
2nd row서울특별시 양천구 목동 723-12번지
3rd row서울특별시 양천구 신정동 201-1번지
4th row서울특별시 양천구 신월동 54-1번지
5th row서울특별시 양천구 신월동 28-5번지
ValueCountFrequency (%)
양천구 344
22.8%
서울특별시 343
22.7%
신월동 128
 
8.5%
신정동 117
 
7.8%
목동 100
 
6.6%
3층 24
 
1.6%
2층 19
 
1.3%
지층 11
 
0.7%
지하1층 6
 
0.4%
201호 3
 
0.2%
Other values (375) 414
27.4%
2024-04-30T04:59:38.638075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1465
18.2%
1 356
 
4.4%
동 354
 
4.4%
서 344
 
4.3%
양 344
 
4.3%
천 344
 
4.3%
구 344
 
4.3%
특 343
 
4.3%
별 343
 
4.3%
시 343
 
4.3%
Other values (81) 3457
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4532
56.4%
Decimal Number 1681
 
20.9%
Space Separator 1465
 
18.2%
Dash Punctuation 333
 
4.1%
Other Punctuation 9
 
0.1%
Uppercase Letter 8
 
0.1%
Math Symbol 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 354
 
7.8%
서 344
 
7.6%
양 344
 
7.6%
천 344
 
7.6%
구 344
 
7.6%
특 343
 
7.6%
별 343
 
7.6%
시 343
 
7.6%
울 343
 
7.6%
지 298
 
6.6%
Other values (61) 1132
25.0%
Decimal Number
ValueCountFrequency (%)
1 356
21.2%
2 237
14.1%
3 169
10.1%
9 157
9.3%
4 156
9.3%
0 139
 
8.3%
5 130
 
7.7%
7 126
 
7.5%
6 117
 
7.0%
8 94
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
A 3
37.5%
T 1
 
12.5%
P 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1465
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 333
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4532
56.4%
Common 3497
43.5%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 354
 
7.8%
서 344
 
7.6%
양 344
 
7.6%
천 344
 
7.6%
구 344
 
7.6%
특 343
 
7.6%
별 343
 
7.6%
시 343
 
7.6%
울 343
 
7.6%
지 298
 
6.6%
Other values (61) 1132
25.0%
Common
ValueCountFrequency (%)
1465
41.9%
1 356
 
10.2%
- 333
 
9.5%
2 237
 
6.8%
3 169
 
4.8%
9 157
 
4.5%
4 156
 
4.5%
0 139
 
4.0%
5 130
 
3.7%
7 126
 
3.6%
Other values (6) 229
 
6.5%
Latin
ValueCountFrequency (%)
B 3
37.5%
A 3
37.5%
T 1
 
12.5%
P 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4532
56.4%
ASCII 3505
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1465
41.8%
1 356
 
10.2%
- 333
 
9.5%
2 237
 
6.8%
3 169
 
4.8%
9 157
 
4.5%
4 156
 
4.5%
0 139
 
4.0%
5 130
 
3.7%
7 126
 
3.6%
Other values (10) 237
 
6.8%
Hangul
ValueCountFrequency (%)
동 354
 
7.8%
서 344
 
7.6%
양 344
 
7.6%
천 344
 
7.6%
구 344
 
7.6%
특 343
 
7.6%
별 343
 
7.6%
시 343
 
7.6%
울 343
 
7.6%
지 298
 
6.6%
Other values (61) 1132
25.0%

도로명주소
Text

MISSING 

Distinct325
Distinct (%)97.0%
Missing8
Missing (%)2.3%
Memory size2.8 KiB
2024-04-30T04:59:38.852718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length26.698507
Min length22

Characters and Unicode

Total characters8944
Distinct characters118
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

Unique315 ?
Unique (%)94.0%

Sample

1st row서울특별시 양천구 공항대로 618 (목동)
2nd row서울특별시 양천구 목동중앙남로11길 3 (목동)
3rd row서울특별시 양천구 목동남로4길 2 (신정동)
4th row서울특별시 양천구 화곡로 50 (신월동)
5th row서울특별시 양천구 화곡로 43 (신월동)
ValueCountFrequency (%)
서울특별시 335
18.5%
양천구 335
18.5%
신월동 118
 
6.5%
신정동 101
 
5.6%
목동 80
 
4.4%
오목로 39
 
2.2%
3층 32
 
1.8%
신월로 31
 
1.7%
2층 22
 
1.2%
중앙로 20
 
1.1%
Other values (329) 700
38.6%
2024-04-30T04:59:39.185535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1634
 
18.3%
동 431
 
4.8%
서 351
 
3.9%
양 349
 
3.9%
로 349
 
3.9%
( 338
 
3.8%
) 338
 
3.8%
천 335
 
3.7%
구 335
 
3.7%
시 335
 
3.7%
Other values (108) 4149
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5321
59.5%
Space Separator 1634
 
18.3%
Decimal Number 1128
 
12.6%
Open Punctuation 338
 
3.8%
Close Punctuation 338
 
3.8%
Other Punctuation 149
 
1.7%
Dash Punctuation 23
 
0.3%
Uppercase Letter 9
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 431
 
8.1%
서 351
 
6.6%
양 349
 
6.6%
로 349
 
6.6%
천 335
 
6.3%
구 335
 
6.3%
시 335
 
6.3%
별 335
 
6.3%
울 335
 
6.3%
특 335
 
6.3%
Other values (88) 1831
34.4%
Decimal Number
ValueCountFrequency (%)
1 219
19.4%
2 197
17.5%
3 156
13.8%
5 101
9.0%
6 94
8.3%
4 93
8.2%
0 77
 
6.8%
7 68
 
6.0%
8 62
 
5.5%
9 61
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
44.4%
A 3
33.3%
P 1
 
11.1%
T 1
 
11.1%
Space Separator
ValueCountFrequency (%)
1634
100.0%
Open Punctuation
ValueCountFrequency (%)
( 338
100.0%
Close Punctuation
ValueCountFrequency (%)
) 338
100.0%
Other Punctuation
ValueCountFrequency (%)
, 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5321
59.5%
Common 3614
40.4%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 431
 
8.1%
서 351
 
6.6%
양 349
 
6.6%
로 349
 
6.6%
천 335
 
6.3%
구 335
 
6.3%
시 335
 
6.3%
별 335
 
6.3%
울 335
 
6.3%
특 335
 
6.3%
Other values (88) 1831
34.4%
Common
ValueCountFrequency (%)
1634
45.2%
( 338
 
9.4%
) 338
 
9.4%
1 219
 
6.1%
2 197
 
5.5%
3 156
 
4.3%
, 149
 
4.1%
5 101
 
2.8%
6 94
 
2.6%
4 93
 
2.6%
Other values (6) 295
 
8.2%
Latin
ValueCountFrequency (%)
B 4
44.4%
A 3
33.3%
P 1
 
11.1%
T 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5321
59.5%
ASCII 3623
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1634
45.1%
( 338
 
9.3%
) 338
 
9.3%
1 219
 
6.0%
2 197
 
5.4%
3 156
 
4.3%
, 149
 
4.1%
5 101
 
2.8%
6 94
 
2.6%
4 93
 
2.6%
Other values (10) 304
 
8.4%
Hangul
ValueCountFrequency (%)
동 431
 
8.1%
서 351
 
6.6%
양 349
 
6.6%
로 349
 
6.6%
천 335
 
6.3%
구 335
 
6.3%
시 335
 
6.3%
별 335
 
6.3%
울 335
 
6.3%
특 335
 
6.3%
Other values (88) 1831
34.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)42.5%
Missing143
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean14022.185
Minimum7903
Maximum158859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:39.298068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7903
5-th percentile7908.9
Q17942.25
median7991.5
Q38037.25
95-th percentile8104
Maximum158859
Range150956
Interquartile range (IQR)95

Descriptive statistics

Standard deviation29631.364
Coefficient of variation (CV)2.1131774
Kurtosis20.58233
Mean14022.185
Median Absolute Deviation (MAD)47.5
Skewness4.7303805
Sum2804437
Variance8.7801772 × 108
MonotonicityNot monotonic
2024-04-30T04:59:39.411358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7968 13
 
3.8%
7945 7
 
2.0%
7950 6
 
1.7%
8082 6
 
1.7%
7938 6
 
1.7%
8015 6
 
1.7%
7936 5
 
1.5%
8073 5
 
1.5%
8028 5
 
1.5%
7946 5
 
1.5%
Other values (75) 136
39.7%
(Missing) 143
41.7%
ValueCountFrequency (%)
7903 2
0.6%
7904 1
 
0.3%
7905 2
0.6%
7906 3
0.9%
7907 2
0.6%
7909 1
 
0.3%
7910 3
0.9%
7917 4
1.2%
7919 1
 
0.3%
7920 3
0.9%
ValueCountFrequency (%)
158859 1
 
0.3%
158857 1
 
0.3%
158846 1
 
0.3%
158840 1
 
0.3%
158833 1
 
0.3%
158810 1
 
0.3%
158808 1
 
0.3%
158723 1
 
0.3%
8104 4
1.2%
8093 2
0.6%

사업장명
Text

Distinct282
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-30T04:59:39.677996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length5.7259475
Min length2

Characters and Unicode

Total characters1964
Distinct characters270
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)70.3%

Sample

1st row초원당구장
2nd row지현당구장
3rd row금성당구장
4th row당구치러가자
5th row코끼리당구장
ValueCountFrequency (%)
당구장 31
 
7.8%
당구클럽 18
 
4.5%
큐당구장 6
 
1.5%
필당구장 4
 
1.0%
황제당구장 4
 
1.0%
스타당구장 4
 
1.0%
영당구장 4
 
1.0%
다모아당구장 3
 
0.8%
큐 3
 
0.8%
우성당구장 3
 
0.8%
Other values (278) 320
80.0%
2024-04-30T04:59:40.054893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 333
17.0%
당 332
16.9%
장 260
 
13.2%
럽 61
 
3.1%
클 59
 
3.0%
57
 
2.9%
스 36
 
1.8%
아 22
 
1.1%
이 22
 
1.1%
드 19
 
1.0%
Other values (260) 763
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1793
91.3%
Uppercase Letter 75
 
3.8%
Space Separator 57
 
2.9%
Decimal Number 18
 
0.9%
Close Punctuation 6
 
0.3%
Open Punctuation 6
 
0.3%
Other Punctuation 5
 
0.3%
Lowercase Letter 3
 
0.2%
Other Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 333
18.6%
당 332
18.5%
장 260
14.5%
럽 61
 
3.4%
클 59
 
3.3%
스 36
 
2.0%
아 22
 
1.2%
이 22
 
1.2%
드 19
 
1.1%
큐 17
 
0.9%
Other values (222) 632
35.2%
Uppercase Letter
ValueCountFrequency (%)
B 10
13.3%
S 9
12.0%
P 7
9.3%
C 6
 
8.0%
M 6
 
8.0%
U 5
 
6.7%
L 5
 
6.7%
J 5
 
6.7%
O 4
 
5.3%
I 3
 
4.0%
Other values (11) 15
20.0%
Decimal Number
ValueCountFrequency (%)
2 5
27.8%
4 3
16.7%
1 3
16.7%
0 2
 
11.1%
7 2
 
11.1%
9 1
 
5.6%
8 1
 
5.6%
5 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
& 1
 
20.0%
' 1
 
20.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
s 1
33.3%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1793
91.3%
Common 93
 
4.7%
Latin 78
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 333
18.6%
당 332
18.5%
장 260
14.5%
럽 61
 
3.4%
클 59
 
3.3%
스 36
 
2.0%
아 22
 
1.2%
이 22
 
1.2%
드 19
 
1.1%
큐 17
 
0.9%
Other values (222) 632
35.2%
Latin
ValueCountFrequency (%)
B 10
12.8%
S 9
11.5%
P 7
 
9.0%
C 6
 
7.7%
M 6
 
7.7%
U 5
 
6.4%
L 5
 
6.4%
J 5
 
6.4%
O 4
 
5.1%
I 3
 
3.8%
Other values (13) 18
23.1%
Common
ValueCountFrequency (%)
57
61.3%
) 6
 
6.5%
( 6
 
6.5%
2 5
 
5.4%
4 3
 
3.2%
. 3
 
3.2%
1 3
 
3.2%
0 2
 
2.2%
7 2
 
2.2%
9 1
 
1.1%
Other values (5) 5
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1793
91.3%
ASCII 170
 
8.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 333
18.6%
당 332
18.5%
장 260
14.5%
럽 61
 
3.4%
클 59
 
3.3%
스 36
 
2.0%
아 22
 
1.2%
이 22
 
1.2%
드 19
 
1.1%
큐 17
 
0.9%
Other values (222) 632
35.2%
ASCII
ValueCountFrequency (%)
57
33.5%
B 10
 
5.9%
S 9
 
5.3%
P 7
 
4.1%
C 6
 
3.5%
) 6
 
3.5%
( 6
 
3.5%
M 6
 
3.5%
U 5
 
2.9%
2 5
 
2.9%
Other values (27) 53
31.2%
None
ValueCountFrequency (%)
₂ 1
100.0%

최종수정일자
Date

Distinct276
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2002-10-22 17:59:13
Maximum2024-04-03 09:36:28
2024-04-30T04:59:40.187363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:40.319350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
I
187 
U
156 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 187
54.5%
U 156
45.5%

Length

2024-04-30T04:59:40.426537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:40.511261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 187
54.5%
u 156
45.5%

데이터갱신일자
Date

Distinct94
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T04:59:40.795689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:59:40.923300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct283
Distinct (%)84.0%
Missing6
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean187043.56
Minimum184613.51
Maximum189332.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:41.056125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184613.51
5-th percentile184867.74
Q1185810.07
median187209.34
Q3188111.42
95-th percentile188918.65
Maximum189332.77
Range4719.2599
Interquartile range (IQR)2301.3499

Descriptive statistics

Standard deviation1359.3999
Coefficient of variation (CV)0.0072678253
Kurtosis-1.2963887
Mean187043.56
Median Absolute Deviation (MAD)1237.1147
Skewness-0.15873279
Sum63033679
Variance1847968.1
MonotonicityNot monotonic
2024-04-30T04:59:41.191988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187781.177363335 4
 
1.2%
184867.739383378 4
 
1.2%
187244.552928692 3
 
0.9%
185692.551545586 3
 
0.9%
185952.141787723 3
 
0.9%
188918.557157522 2
 
0.6%
188788.809659247 2
 
0.6%
188494.598982992 2
 
0.6%
186887.779001601 2
 
0.6%
187959.175235751 2
 
0.6%
Other values (273) 310
90.4%
(Missing) 6
 
1.7%
ValueCountFrequency (%)
184613.513561026 1
0.3%
184619.809614881 1
0.3%
184631.002540554 1
0.3%
184678.753937033 1
0.3%
184727.875421797 1
0.3%
184745.326179726 1
0.3%
184758.160681476 1
0.3%
184761.561897631 1
0.3%
184769.91352489 1
0.3%
184825.763727278 1
0.3%
ValueCountFrequency (%)
189332.773428473 1
0.3%
189251.065 2
0.6%
189197.506088261 1
0.3%
189086.756192965 1
0.3%
189085.106666667 1
0.3%
189042.496526196 1
0.3%
189040.442771323 1
0.3%
189038.037681199 1
0.3%
189021.797866206 2
0.6%
188995.881881306 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct283
Distinct (%)84.0%
Missing6
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean447316.98
Minimum445039.93
Maximum449763.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:41.323933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445039.93
5-th percentile446059.82
Q1446575.5
median447032.24
Q3448068.57
95-th percentile449390.56
Maximum449763.35
Range4723.419
Interquartile range (IQR)1493.0661

Descriptive statistics

Standard deviation1074.0318
Coefficient of variation (CV)0.0024010531
Kurtosis-0.31894607
Mean447316.98
Median Absolute Deviation (MAD)663.57575
Skewness0.65261523
Sum1.5074582 × 108
Variance1153544.3
MonotonicityNot monotonic
2024-04-30T04:59:41.440396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447163.682028686 4
 
1.2%
448186.71968632 4
 
1.2%
446626.599997855 3
 
0.9%
447374.522041433 3
 
0.9%
446293.944517244 3
 
0.9%
447009.593471943 2
 
0.6%
449313.885409203 2
 
0.6%
447318.660520705 2
 
0.6%
446481.970675579 2
 
0.6%
447799.743285786 2
 
0.6%
Other values (273) 310
90.4%
(Missing) 6
 
1.7%
ValueCountFrequency (%)
445039.928375227 1
0.3%
445081.396522145 1
0.3%
445124.131588947 1
0.3%
445166.926423154 1
0.3%
445197.198550791 1
0.3%
445216.899831188 1
0.3%
445524.71062635 1
0.3%
445541.133178236 1
0.3%
445610.277402204 1
0.3%
445930.418572154 1
0.3%
ValueCountFrequency (%)
449763.347390512 1
0.3%
449722.378668012 2
0.6%
449683.219205227 1
0.3%
449679.651827505 1
0.3%
449654.079008626 1
0.3%
449605.761553476 1
0.3%
449596.162199226 1
0.3%
449595.827555769 1
0.3%
449583.899391857 1
0.3%
449578.800268858 1
0.3%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
당구장업
308 
<NA>
35 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 308
89.8%
<NA> 35
 
10.2%

Length

2024-04-30T04:59:41.549681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:41.628056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 308
89.8%
na 35
 
10.2%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
사립
308 
<NA>
35 

Length

Max length4
Median length2
Mean length2.2040816
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 308
89.8%
<NA> 35
 
10.2%

Length

2024-04-30T04:59:41.719585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:41.816152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 308
89.8%
na 35
 
10.2%

보험가입여부코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
269 
0
74 

Length

Max length4
Median length4
Mean length3.3527697
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 269
78.4%
0 74
 
21.6%

Length

2024-04-30T04:59:41.927239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:42.014528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 269
78.4%
0 74
 
21.6%

지도자수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
214 
0
129 

Length

Max length4
Median length4
Mean length2.8717201
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 214
62.4%
0 129
37.6%

Length

2024-04-30T04:59:42.105610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:42.193214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 214
62.4%
0 129
37.6%

건축물동수
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
198 
0
138 
1
 
7

Length

Max length4
Median length4
Mean length2.7317784
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
57.7%
0 138
40.2%
1 7
 
2.0%

Length

2024-04-30T04:59:42.278232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:42.366634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
57.7%
0 138
40.2%
1 7
 
2.0%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)20.6%
Missing168
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean87.190914
Minimum0
Maximum3094.01
Zeros134
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-30T04:59:42.452897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile268.936
Maximum3094.01
Range3094.01
Interquartile range (IQR)0

Descriptive statistics

Standard deviation311.20797
Coefficient of variation (CV)3.5692707
Kurtosis56.045091
Mean87.190914
Median Absolute Deviation (MAD)0
Skewness6.8265765
Sum15258.41
Variance96850.403
MonotonicityNot monotonic
2024-04-30T04:59:42.561204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0.0 134
39.1%
165.0 4
 
1.2%
132.0 3
 
0.9%
210.0 2
 
0.6%
237.6 1
 
0.3%
940.0 1
 
0.3%
195.73 1
 
0.3%
259.48 1
 
0.3%
1694.0 1
 
0.3%
652.0 1
 
0.3%
Other values (26) 26
 
7.6%
(Missing) 168
49.0%
ValueCountFrequency (%)
0.0 134
39.1%
96.0 1
 
0.3%
102.3 1
 
0.3%
109.44 1
 
0.3%
117.7 1
 
0.3%
125.0 1
 
0.3%
127.34 1
 
0.3%
130.0 1
 
0.3%
132.0 3
 
0.9%
135.3 1
 
0.3%
ValueCountFrequency (%)
3094.01 1
0.3%
1694.0 1
0.3%
1461.91 1
0.3%
941.7 1
0.3%
940.0 1
0.3%
652.0 1
0.3%
468.94 1
0.3%
402.0 1
0.3%
291.0 1
0.3%
259.48 1
0.3%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
339 
0
 
4

Length

Max length4
Median length4
Mean length3.9650146
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> 339
98.8%
0 4
 
1.2%

Length

2024-04-30T04:59:42.688870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:59:42.783364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 339
98.8%
0 4
 
1.2%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing343
Missing (%)100.0%
Memory size3.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03140000CDFH330108198000000119801214<NA>3폐업3폐업19980709<NA><NA><NA><NA><NA>158808서울특별시 양천구 목동 513-11번지서울특별시 양천구 공항대로 618 (목동)<NA>초원당구장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188753.288155449387.338524당구장업사립<NA>000.0<NA><NA><NA>
13140000CDFH330108198200000119820504<NA>3폐업3폐업20000607<NA><NA><NA><NA><NA>158814서울특별시 양천구 목동 723-12번지서울특별시 양천구 목동중앙남로11길 3 (목동)<NA>지현당구장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188065.613157448555.37926당구장업사립<NA>000.0<NA><NA><NA>
23140000CDFH330108198200000219820909<NA>4취소/말소/만료/정지/중지35직권말소20190806<NA><NA><NA><NA><NA>158851서울특별시 양천구 신정동 201-1번지서울특별시 양천구 목동남로4길 2 (신정동)8104금성당구장2019-08-06 18:07:38U2019-08-08 02:40:00.0<NA>187954.189632445124.131589당구장업사립<NA>000.0<NA><NA><NA>
33140000CDFH330108198200000319821019<NA>3폐업3폐업20040120<NA><NA><NA>2693-3986<NA>158824서울특별시 양천구 신월동 54-1번지서울특별시 양천구 화곡로 50 (신월동)<NA>당구치러가자2004-01-20 11:37:44I2018-08-31 23:59:59.0<NA>184678.753937448560.75034당구장업사립0<NA><NA>132.0<NA><NA><NA>
43140000CDFH330108198300000119830120<NA>3폐업3폐업20060609<NA><NA><NA><NA><NA>158822서울특별시 양천구 신월동 28-5번지서울특별시 양천구 화곡로 43 (신월동)<NA>코끼리당구장2006-06-09 14:52:33I2018-08-31 23:59:59.0<NA>184619.809615448605.087668당구장업사립0<NA><NA><NA><NA><NA><NA>
53140000CDFH330108198300000219830216<NA>3폐업3폐업20001230<NA><NA><NA><NA><NA>158841서울특별시 양천구 신월동 550-13번지서울특별시 양천구 남부순환로79길 21 (신월동)<NA>대우당구장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>185970.092965446138.930605당구장업사립<NA>000.0<NA><NA><NA>
63140000CDFH330108198300000319830312<NA>3폐업3폐업20000126<NA><NA><NA><NA><NA>158829서울특별시 양천구 신월동 147-4번지서울특별시 양천구 남부순환로 356 (신월동)<NA>샛별당구장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>184758.160681448125.6934당구장업사립<NA>000.0<NA><NA><NA>
73140000CDFH330108198300000419830408<NA>3폐업3폐업20180725<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1028-4번지 2층서울특별시 양천구 신월로 320, 2층 (신정동)8082삼성당구장2018-07-25 14:34:21I2018-08-31 23:59:59.0<NA>187241.641103446575.50162당구장업사립<NA><NA>0<NA><NA><NA><NA>
83140000CDFH330108198300000519830419<NA>3폐업3폐업20020205<NA><NA><NA><NA><NA>158807서울특별시 양천구 목동 506-17번지서울특별시 양천구 목동중앙북로 74 (목동)<NA>슈퍼당구장2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>188549.729779449364.309293당구장업사립<NA>000.0<NA><NA><NA>
93140000CDFH330108198300000619830721<NA>3폐업3폐업20080514<NA><NA><NA><NA><NA>158824서울특별시 양천구 신월동 64-4번지서울특별시 양천구 화곡로 104 (신월동)<NA>국일당구장2008-05-14 16:01:55I2018-08-31 23:59:59.0<NA>185227.352415448600.81406당구장업사립0<NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
3333140000CDFH330108202000000920201006<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2653-0896<NA><NA>서울특별시 양천구 신정동 1026-3 4층서울특별시 양천구 신월로 344, 4층 (신정동)8086브라보캐롬클럽 신정점2020-10-06 15:25:55I2020-10-08 00:23:10.0<NA>187488.563339446598.324632당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3343140000CDFH33010820200000102020-12-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 887-8 지층서울특별시 양천구 신정중앙로 95, 지층 (신정동)7938큐당구클럽2024-03-20 18:02:08U2023-12-02 22:02:00.0<NA>187781.177363447163.682029<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3353140000CDFH330108202100000120210304<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 794-1 3층서울특별시 양천구 목동중앙서로 6, 3층 (목동)7966별 당구장2022-01-23 15:48:02U2022-01-25 02:40:00.0<NA>187959.175236447799.743286당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3363140000CDFH33010820210000022021-03-31<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 89-77서울특별시 양천구 신목로 66, 2층 (신정동)8015셀프당구장2023-11-29 20:55:38U2022-11-02 00:01:00.0<NA>188750.790013446516.053427<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3373140000CDFH330108202100000320210610<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 115-17서울특별시 양천구 월정로 143, 3층 (신월동)7923신영 당구장2021-06-10 16:46:37I2021-06-12 00:22:54.0<NA>185530.34853447727.47782당구장업사립<NA><NA><NA><NA><NA><NA><NA>
3383140000CDFH330108202100000420210806<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 902-1서울특별시 양천구 신정중앙로 90, 3층 (신정동)7945JJ당구장2021-08-06 09:31:24I2021-08-08 00:22:51.0<NA>187700.179588447132.16554당구장업사립<NA>000.00<NA><NA>
3393140000CDFH330108202200000120221006<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 97-1서울특별시 양천구 가로공원로 122, 2층 (신월동)7917아까비당구장2022-10-06 13:58:37I2021-10-31 00:08:00.0<NA>184867.739383448186.719686<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3403140000CDFH33010820230000012023-03-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 514-16서울특별시 양천구 목동중앙북로 95, 4층 (목동)7968제이제이당구장2023-03-02 09:34:28I2022-12-03 00:04:00.0<NA>188783.842188449352.518037<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3413140000CDFH33010820230000022023-08-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 513-27 하쯔빌딩서울특별시 양천구 목동중앙북로 81, 하쯔빌딩 3층 (목동)7968큐당구장2023-08-14 11:01:48I2022-12-07 23:07:00.0<NA>188635.86327449373.174837<NA><NA><NA><NA><NA><NA><NA><NA><NA>
3423140000CDFH33010820230000032023-10-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 516서울특별시 양천구 공항대로 646, 2층 (목동)7968라이온 빌리어드2023-10-30 09:05:57I2022-11-01 00:01:00.0<NA>189038.037681449399.489127<NA><NA><NA><NA><NA><NA><NA><NA><NA>