Overview

Dataset statistics

Number of variables34
Number of observations21
Missing cells211
Missing cells (%)29.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory299.3 B

Variable types

Categorical12
Text5
Numeric7
Unsupported8
DateTime2

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-19741/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
문화체육업종명 is highly imbalanced (54.6%)Imbalance
공사립구분명 is highly imbalanced (54.6%)Imbalance
건축물동수 is highly imbalanced (54.4%)Imbalance
회원모집총인원 is highly imbalanced (72.4%)Imbalance
인허가취소일자 has 21 (100.0%) missing valuesMissing
폐업일자 has 13 (61.9%) missing valuesMissing
휴업시작일자 has 21 (100.0%) missing valuesMissing
휴업종료일자 has 21 (100.0%) missing valuesMissing
재개업일자 has 21 (100.0%) missing valuesMissing
전화번호 has 3 (14.3%) missing valuesMissing
소재지면적 has 21 (100.0%) missing valuesMissing
소재지우편번호 has 6 (28.6%) missing valuesMissing
도로명주소 has 1 (4.8%) missing valuesMissing
도로명우편번호 has 6 (28.6%) missing valuesMissing
업태구분명 has 21 (100.0%) missing valuesMissing
건축물연면적 has 14 (66.7%) missing valuesMissing
세부업종명 has 21 (100.0%) missing valuesMissing
법인명 has 21 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 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 1 (4.8%) zerosZeros

Reproduction

Analysis started2024-05-11 04:56:41.430858
Analysis finished2024-05-11 04:56:42.206852
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
3140000
21 

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 21
100.0%

Length

2024-05-11T04:56:42.410760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:42.732921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 21
100.0%

관리번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T04:56:43.198296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters420
Distinct characters13
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

Unique21 ?
Unique (%)100.0%

Sample

1st rowCDFH3301011989000001
2nd rowCDFH3301011989000002
3rd rowCDFH3301011990000001
4th rowCDFH3301011996000001
5th rowCDFH3301011997000001
ValueCountFrequency (%)
cdfh3301011989000001 1
 
4.8%
cdfh3301012013000001 1
 
4.8%
cdfh3301012019000001 1
 
4.8%
cdfh3301012017000001 1
 
4.8%
cdfh3301012016000002 1
 
4.8%
cdfh3301012016000001 1
 
4.8%
cdfh3301012014000003 1
 
4.8%
cdfh3301012014000002 1
 
4.8%
cdfh3301012014000001 1
 
4.8%
cdfh3301012013000002 1
 
4.8%
Other values (11) 11
52.4%
2024-05-11T04:56:44.081376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 165
39.3%
1 75
17.9%
3 45
 
10.7%
2 23
 
5.5%
C 21
 
5.0%
D 21
 
5.0%
F 21
 
5.0%
H 21
 
5.0%
9 17
 
4.0%
8 3
 
0.7%
Other values (3) 8
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 336
80.0%
Uppercase Letter 84
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 165
49.1%
1 75
22.3%
3 45
 
13.4%
2 23
 
6.8%
9 17
 
5.1%
8 3
 
0.9%
6 3
 
0.9%
4 3
 
0.9%
7 2
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 21
25.0%
D 21
25.0%
F 21
25.0%
H 21
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
80.0%
Latin 84
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 165
49.1%
1 75
22.3%
3 45
 
13.4%
2 23
 
6.8%
9 17
 
5.1%
8 3
 
0.9%
6 3
 
0.9%
4 3
 
0.9%
7 2
 
0.6%
Latin
ValueCountFrequency (%)
C 21
25.0%
D 21
25.0%
F 21
25.0%
H 21
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 165
39.3%
1 75
17.9%
3 45
 
10.7%
2 23
 
5.5%
C 21
 
5.0%
D 21
 
5.0%
F 21
 
5.0%
H 21
 
5.0%
9 17
 
4.0%
8 3
 
0.7%
Other values (3) 8
 
1.9%

인허가일자
Real number (ℝ)

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20071214
Minimum19891118
Maximum20200806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:44.476731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19891118
5-th percentile19891118
Q119990901
median20120608
Q320141224
95-th percentile20190730
Maximum20200806
Range309688
Interquartile range (IQR)150323

Descriptive statistics

Standard deviation103983.42
Coefficient of variation (CV)0.0051807239
Kurtosis-1.1303091
Mean20071214
Median Absolute Deviation (MAD)49799
Skewness-0.60540989
Sum4.214955 × 108
Variance1.0812551 × 1010
MonotonicityIncreasing
2024-05-11T04:56:44.872873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
19891118 2
 
9.5%
20130612 1
 
4.8%
20200806 1
 
4.8%
20190730 1
 
4.8%
20170407 1
 
4.8%
20160704 1
 
4.8%
20160113 1
 
4.8%
20141224 1
 
4.8%
20141208 1
 
4.8%
20140424 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
19891118 2
9.5%
19900507 1
4.8%
19960604 1
4.8%
19971106 1
4.8%
19990901 1
4.8%
19991118 1
4.8%
20010326 1
4.8%
20081027 1
4.8%
20120308 1
4.8%
20120608 1
4.8%
ValueCountFrequency (%)
20200806 1
4.8%
20190730 1
4.8%
20170407 1
4.8%
20160704 1
4.8%
20160113 1
4.8%
20141224 1
4.8%
20141208 1
4.8%
20140424 1
4.8%
20130612 1
4.8%
20130527 1
4.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
13 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 13
61.9%
3 8
38.1%

Length

2024-05-11T04:56:45.267757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:45.595025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 13
61.9%
3 8
38.1%

영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업/정상
13 
폐업
8 

Length

Max length5
Median length5
Mean length3.8571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 13
61.9%
폐업 8
38.1%

Length

2024-05-11T04:56:45.964484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:46.303997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 13
61.9%
폐업 8
38.1%

상세영업상태코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
13
13 
3
8 

Length

Max length2
Median length2
Mean length1.6190476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 13
61.9%
3 8
38.1%

Length

2024-05-11T04:56:46.532894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:46.834904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 13
61.9%
3 8
38.1%

상세영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업중
13 
폐업
8 

Length

Max length3
Median length3
Mean length2.6190476
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 13
61.9%
폐업 8
38.1%

Length

2024-05-11T04:56:47.059787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:47.363124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 13
61.9%
폐업 8
38.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing13
Missing (%)61.9%
Infinite0
Infinite (%)0.0%
Mean20118298
Minimum19980922
Maximum20221227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:47.638412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980922
5-th percentile20005495
Q120073477
median20130768
Q320162819
95-th percentile20213911
Maximum20221227
Range240305
Interquartile range (IQR)89342.25

Descriptive statistics

Standard deviation78775.554
Coefficient of variation (CV)0.0039156173
Kurtosis-0.11835264
Mean20118298
Median Absolute Deviation (MAD)59698.5
Skewness-0.49434421
Sum1.6094638 × 108
Variance6.205588 × 109
MonotonicityNot monotonic
2024-05-11T04:56:47.858963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20051130 1
 
4.8%
19980922 1
 
4.8%
20130826 1
 
4.8%
20150318 1
 
4.8%
20130709 1
 
4.8%
20080926 1
 
4.8%
20221227 1
 
4.8%
20200323 1
 
4.8%
(Missing) 13
61.9%
ValueCountFrequency (%)
19980922 1
4.8%
20051130 1
4.8%
20080926 1
4.8%
20130709 1
4.8%
20130826 1
4.8%
20150318 1
4.8%
20200323 1
4.8%
20221227 1
4.8%
ValueCountFrequency (%)
20221227 1
4.8%
20200323 1
4.8%
20150318 1
4.8%
20130826 1
4.8%
20130709 1
4.8%
20080926 1
4.8%
20051130 1
4.8%
19980922 1
4.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

전화번호
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing3
Missing (%)14.3%
Memory size300.0 B
2024-05-11T04:56:48.128244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.222222
Min length8

Characters and Unicode

Total characters184
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

Unique16 ?
Unique (%)88.9%

Sample

1st row2643-4771
2nd row2646-6819
3rd row02-2646-6096
4th row2647-9611
5th row2652-8083
ValueCountFrequency (%)
02-2607-8791 2
 
11.1%
0262138875 1
 
5.6%
2643-4771 1
 
5.6%
02-2163-3700 1
 
5.6%
02-2601-3456 1
 
5.6%
02-2607-1001 1
 
5.6%
6929-0079 1
 
5.6%
2653-4302 1
 
5.6%
2653-3738 1
 
5.6%
02-2646-6096 1
 
5.6%
Other values (7) 7
38.9%
2024-05-11T04:56:49.002765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30
16.3%
0 27
14.7%
6 27
14.7%
- 22
12.0%
3 15
8.2%
7 13
7.1%
1 13
7.1%
8 10
 
5.4%
4 10
 
5.4%
9 9
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
88.0%
Dash Punctuation 22
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
18.5%
0 27
16.7%
6 27
16.7%
3 15
9.3%
7 13
8.0%
1 13
8.0%
8 10
 
6.2%
4 10
 
6.2%
9 9
 
5.6%
5 8
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30
16.3%
0 27
14.7%
6 27
14.7%
- 22
12.0%
3 15
8.2%
7 13
7.1%
1 13
7.1%
8 10
 
5.4%
4 10
 
5.4%
9 9
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30
16.3%
0 27
14.7%
6 27
14.7%
- 22
12.0%
3 15
8.2%
7 13
7.1%
1 13
7.1%
8 10
 
5.4%
4 10
 
5.4%
9 9
 
4.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)73.3%
Missing6
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean158564.93
Minimum158050
Maximum158885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:49.431998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158050
5-th percentile158050
Q1158051.5
median158806
Q3158850
95-th percentile158885
Maximum158885
Range835
Interquartile range (IQR)798.5

Descriptive statistics

Standard deviation379.38135
Coefficient of variation (CV)0.002392593
Kurtosis-1.6220406
Mean158564.93
Median Absolute Deviation (MAD)79
Skewness-0.73611226
Sum2378474
Variance143930.21
MonotonicityNot monotonic
2024-05-11T04:56:49.892578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
158050 4
19.0%
158885 2
 
9.5%
158811 1
 
4.8%
158848 1
 
4.8%
158806 1
 
4.8%
158828 1
 
4.8%
158860 1
 
4.8%
158852 1
 
4.8%
158724 1
 
4.8%
158053 1
 
4.8%
(Missing) 6
28.6%
ValueCountFrequency (%)
158050 4
19.0%
158053 1
 
4.8%
158722 1
 
4.8%
158724 1
 
4.8%
158806 1
 
4.8%
158811 1
 
4.8%
158828 1
 
4.8%
158848 1
 
4.8%
158852 1
 
4.8%
158860 1
 
4.8%
ValueCountFrequency (%)
158885 2
9.5%
158860 1
4.8%
158852 1
4.8%
158848 1
4.8%
158828 1
4.8%
158811 1
4.8%
158806 1
4.8%
158724 1
4.8%
158722 1
4.8%
158053 1
4.8%

지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T04:56:50.390673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length28
Mean length26.380952
Min length19

Characters and Unicode

Total characters554
Distinct characters67
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동 610-23번지
2nd row서울특별시 양천구 목동 918번지 6블럭
3rd row서울특별시 양천구 신월동 1001-2번지
4th row서울특별시 양천구 신정동 88-5번지
5th row서울특별시 양천구 목동 405-25번지
ValueCountFrequency (%)
서울특별시 21
19.4%
양천구 21
19.4%
목동 10
 
9.3%
신정동 9
 
8.3%
지하1층 3
 
2.8%
신월동 3
 
2.8%
지하2층 2
 
1.9%
904번지 2
 
1.9%
4단지 2
 
1.9%
139-1 1
 
0.9%
Other values (34) 34
31.5%
2024-05-11T04:56:51.480878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
19.0%
지 24
 
4.3%
동 23
 
4.2%
1 23
 
4.2%
시 23
 
4.2%
울 22
 
4.0%
서 22
 
4.0%
천 21
 
3.8%
구 21
 
3.8%
양 21
 
3.8%
Other values (57) 249
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 322
58.1%
Decimal Number 106
 
19.1%
Space Separator 105
 
19.0%
Dash Punctuation 15
 
2.7%
Uppercase Letter 6
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 24
 
7.5%
동 23
 
7.1%
시 23
 
7.1%
울 22
 
6.8%
서 22
 
6.8%
천 21
 
6.5%
구 21
 
6.5%
양 21
 
6.5%
별 21
 
6.5%
특 21
 
6.5%
Other values (39) 103
32.0%
Decimal Number
ValueCountFrequency (%)
1 23
21.7%
2 17
16.0%
9 15
14.2%
0 14
13.2%
4 9
 
8.5%
5 7
 
6.6%
3 7
 
6.6%
6 7
 
6.6%
8 6
 
5.7%
7 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
X 1
16.7%
E 1
16.7%
L 1
16.7%
P 1
16.7%
U 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
58.1%
Common 226
40.8%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 24
 
7.5%
동 23
 
7.1%
시 23
 
7.1%
울 22
 
6.8%
서 22
 
6.8%
천 21
 
6.5%
구 21
 
6.5%
양 21
 
6.5%
별 21
 
6.5%
특 21
 
6.5%
Other values (39) 103
32.0%
Common
ValueCountFrequency (%)
105
46.5%
1 23
 
10.2%
2 17
 
7.5%
- 15
 
6.6%
9 15
 
6.6%
0 14
 
6.2%
4 9
 
4.0%
5 7
 
3.1%
3 7
 
3.1%
6 7
 
3.1%
Other values (2) 7
 
3.1%
Latin
ValueCountFrequency (%)
X 1
16.7%
E 1
16.7%
L 1
16.7%
P 1
16.7%
U 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 322
58.1%
ASCII 232
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
45.3%
1 23
 
9.9%
2 17
 
7.3%
- 15
 
6.5%
9 15
 
6.5%
0 14
 
6.0%
4 9
 
3.9%
5 7
 
3.0%
3 7
 
3.0%
6 7
 
3.0%
Other values (8) 13
 
5.6%
Hangul
ValueCountFrequency (%)
지 24
 
7.5%
동 23
 
7.1%
시 23
 
7.1%
울 22
 
6.8%
서 22
 
6.8%
천 21
 
6.5%
구 21
 
6.5%
양 21
 
6.5%
별 21
 
6.5%
특 21
 
6.5%
Other values (39) 103
32.0%

도로명주소
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2024-05-11T04:56:51.944312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length30.85
Min length23

Characters and Unicode

Total characters617
Distinct characters76
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

Unique20 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동중앙북로 19-1 (목동)
2nd row서울특별시 양천구 목동서로 143 (목동,6블럭)
3rd row서울특별시 양천구 신월로 134 (신월동)
4th row서울특별시 양천구 신목로 53 (신정동, 지하1층,지하2층)
5th row서울특별시 양천구 오목로 344 (목동)
ValueCountFrequency (%)
서울특별시 20
16.8%
양천구 20
16.8%
신정동 9
 
7.6%
목동 6
 
5.0%
목동서로 5
 
4.2%
지층 3
 
2.5%
신월동 3
 
2.5%
목동동로10길 2
 
1.7%
130 2
 
1.7%
371 2
 
1.7%
Other values (43) 47
39.5%
2024-05-11T04:56:53.131881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
17.0%
동 38
 
6.2%
서 28
 
4.5%
목 25
 
4.1%
시 23
 
3.7%
울 22
 
3.6%
별 21
 
3.4%
특 21
 
3.4%
양 20
 
3.2%
로 20
 
3.2%
Other values (66) 294
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
60.3%
Space Separator 105
 
17.0%
Decimal Number 78
 
12.6%
Open Punctuation 20
 
3.2%
Close Punctuation 20
 
3.2%
Other Punctuation 15
 
2.4%
Uppercase Letter 6
 
1.0%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 38
 
10.2%
서 28
 
7.5%
목 25
 
6.7%
시 23
 
6.2%
울 22
 
5.9%
별 21
 
5.6%
특 21
 
5.6%
양 20
 
5.4%
로 20
 
5.4%
천 20
 
5.4%
Other values (45) 134
36.0%
Decimal Number
ValueCountFrequency (%)
1 18
23.1%
3 12
15.4%
2 12
15.4%
4 10
12.8%
0 9
11.5%
7 5
 
6.4%
9 5
 
6.4%
5 3
 
3.8%
8 2
 
2.6%
6 2
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
X 1
16.7%
E 1
16.7%
L 1
16.7%
P 1
16.7%
U 1
16.7%
B 1
16.7%
Space Separator
ValueCountFrequency (%)
105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
60.3%
Common 239
38.7%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 38
 
10.2%
서 28
 
7.5%
목 25
 
6.7%
시 23
 
6.2%
울 22
 
5.9%
별 21
 
5.6%
특 21
 
5.6%
양 20
 
5.4%
로 20
 
5.4%
천 20
 
5.4%
Other values (45) 134
36.0%
Common
ValueCountFrequency (%)
105
43.9%
( 20
 
8.4%
) 20
 
8.4%
1 18
 
7.5%
, 15
 
6.3%
3 12
 
5.0%
2 12
 
5.0%
4 10
 
4.2%
0 9
 
3.8%
7 5
 
2.1%
Other values (5) 13
 
5.4%
Latin
ValueCountFrequency (%)
X 1
16.7%
E 1
16.7%
L 1
16.7%
P 1
16.7%
U 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
60.3%
ASCII 245
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
42.9%
( 20
 
8.2%
) 20
 
8.2%
1 18
 
7.3%
, 15
 
6.1%
3 12
 
4.9%
2 12
 
4.9%
4 10
 
4.1%
0 9
 
3.7%
7 5
 
2.0%
Other values (11) 19
 
7.8%
Hangul
ValueCountFrequency (%)
동 38
 
10.2%
서 28
 
7.5%
목 25
 
6.7%
시 23
 
6.2%
울 22
 
5.9%
별 21
 
5.6%
특 21
 
5.6%
양 20
 
5.4%
로 20
 
5.4%
천 20
 
5.4%
Other values (45) 134
36.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)80.0%
Missing6
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean8008.6
Minimum7920
Maximum8106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:53.490885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7920
5-th percentile7938.2
Q17994.5
median8013
Q38014
95-th percentile8082.9
Maximum8106
Range186
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation43.526347
Coefficient of variation (CV)0.0054349508
Kurtosis1.8785045
Mean8008.6
Median Absolute Deviation (MAD)9
Skewness0.23901093
Sum120129
Variance1894.5429
MonotonicityNot monotonic
2024-05-11T04:56:53.761955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8014 3
14.3%
8013 2
 
9.5%
7991 1
 
4.8%
8010 1
 
4.8%
7989 1
 
4.8%
8022 1
 
4.8%
7998 1
 
4.8%
7946 1
 
4.8%
8006 1
 
4.8%
7920 1
 
4.8%
Other values (2) 2
 
9.5%
(Missing) 6
28.6%
ValueCountFrequency (%)
7920 1
 
4.8%
7946 1
 
4.8%
7989 1
 
4.8%
7991 1
 
4.8%
7998 1
 
4.8%
8006 1
 
4.8%
8010 1
 
4.8%
8013 2
9.5%
8014 3
14.3%
8022 1
 
4.8%
ValueCountFrequency (%)
8106 1
 
4.8%
8073 1
 
4.8%
8022 1
 
4.8%
8014 3
14.3%
8013 2
9.5%
8010 1
 
4.8%
8006 1
 
4.8%
7998 1
 
4.8%
7991 1
 
4.8%
7989 1
 
4.8%

사업장명
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-05-11T04:56:54.091258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length9.1428571
Min length5

Characters and Unicode

Total characters192
Distinct characters93
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row자성수영장
2nd row목동청소년회관
3rd row영원스포츠센타
4th row미진수영장
5th row청학스포츠타운
ValueCountFrequency (%)
목동스포츠센터 2
 
6.9%
이노스베이 2
 
6.9%
블루라군수영장 2
 
6.9%
수상안전교육센타 1
 
3.4%
국가대표 1
 
3.4%
자성수영장 1
 
3.4%
휘트니스클럽아로마 1
 
3.4%
신기스포렉스 1
 
3.4%
엘리트 1
 
3.4%
키즈 1
 
3.4%
Other values (16) 16
55.2%
2024-05-11T04:56:54.732471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 10
 
5.2%
8
 
4.2%
센 7
 
3.6%
수 7
 
3.6%
영 7
 
3.6%
이 6
 
3.1%
포 5
 
2.6%
터 5
 
2.6%
서 5
 
2.6%
장 5
 
2.6%
Other values (83) 127
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
87.5%
Uppercase Letter 14
 
7.3%
Space Separator 8
 
4.2%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 10
 
6.0%
센 7
 
4.2%
수 7
 
4.2%
영 7
 
4.2%
이 6
 
3.6%
포 5
 
3.0%
터 5
 
3.0%
서 5
 
3.0%
장 5
 
3.0%
츠 4
 
2.4%
Other values (70) 107
63.7%
Uppercase Letter
ValueCountFrequency (%)
M 2
14.3%
E 2
14.3%
O 2
14.3%
P 2
14.3%
B 1
7.1%
R 1
7.1%
S 1
7.1%
H 1
7.1%
I 1
7.1%
L 1
7.1%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
87.5%
Latin 14
 
7.3%
Common 10
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 10
 
6.0%
센 7
 
4.2%
수 7
 
4.2%
영 7
 
4.2%
이 6
 
3.6%
포 5
 
3.0%
터 5
 
3.0%
서 5
 
3.0%
장 5
 
3.0%
츠 4
 
2.4%
Other values (70) 107
63.7%
Latin
ValueCountFrequency (%)
M 2
14.3%
E 2
14.3%
O 2
14.3%
P 2
14.3%
B 1
7.1%
R 1
7.1%
S 1
7.1%
H 1
7.1%
I 1
7.1%
L 1
7.1%
Common
ValueCountFrequency (%)
8
80.0%
) 1
 
10.0%
( 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
87.5%
ASCII 24
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 10
 
6.0%
센 7
 
4.2%
수 7
 
4.2%
영 7
 
4.2%
이 6
 
3.6%
포 5
 
3.0%
터 5
 
3.0%
서 5
 
3.0%
장 5
 
3.0%
츠 4
 
2.4%
Other values (70) 107
63.7%
ASCII
ValueCountFrequency (%)
8
33.3%
M 2
 
8.3%
E 2
 
8.3%
O 2
 
8.3%
P 2
 
8.3%
) 1
 
4.2%
B 1
 
4.2%
R 1
 
4.2%
S 1
 
4.2%
H 1
 
4.2%
Other values (3) 3
 
12.5%

최종수정일자
Date

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2002-10-22 17:59:13
Maximum2023-01-25 17:41:44
2024-05-11T04:56:55.021606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:56:55.301757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
I
12 
U
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 12
57.1%
U 9
42.9%

Length

2024-05-11T04:56:55.527561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:55.845785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 12
57.1%
u 9
42.9%

데이터갱신일자
Date

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2018-08-31 23:59:59
Maximum2022-12-01 00:07:00
2024-05-11T04:56:56.144142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:56:56.595386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

좌표정보(X)
Real number (ℝ)

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187951.76
Minimum184902.84
Maximum189659.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:56.953512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184902.84
5-th percentile184902.84
Q1187929.4
median188484.08
Q3188656.78
95-th percentile188924.25
Maximum189659.13
Range4756.2867
Interquartile range (IQR)727.38873

Descriptive statistics

Standard deviation1319.6738
Coefficient of variation (CV)0.0070213432
Kurtosis1.2528261
Mean187951.76
Median Absolute Deviation (MAD)420.49409
Skewness-1.4403771
Sum3946987
Variance1741539
MonotonicityNot monotonic
2024-05-11T04:56:57.391143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
188904.571764159 2
 
9.5%
184902.838587393 2
 
9.5%
188580.483661607 2
 
9.5%
188080.178399949 1
 
4.8%
188884.075622342 1
 
4.8%
188484.077672874 1
 
4.8%
187037.450703045 1
 
4.8%
186990.07041522 1
 
4.8%
188650.113584937 1
 
4.8%
188388.142161894 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
184902.838587393 2
9.5%
185681.509413991 1
4.8%
186990.07041522 1
4.8%
187037.450703045 1
4.8%
187929.395106977 1
4.8%
187954.571823191 1
4.8%
188080.178399949 1
4.8%
188335.8558965 1
4.8%
188388.142161894 1
4.8%
188484.077672874 1
4.8%
ValueCountFrequency (%)
189659.125277836 1
4.8%
188924.253025894 1
4.8%
188904.571764159 2
9.5%
188884.075622342 1
4.8%
188656.783840714 1
4.8%
188650.113584937 1
4.8%
188580.483661607 2
9.5%
188555.643850446 1
4.8%
188484.077672874 1
4.8%
188388.142161894 1
4.8%

좌표정보(Y)
Real number (ℝ)

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447198.39
Minimum445450.75
Maximum449783.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:56:57.745023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445450.75
5-th percentile446054.74
Q1446358.12
median446861.53
Q3447750.85
95-th percentile449596.3
Maximum449783.45
Range4332.6992
Interquartile range (IQR)1392.7246

Descriptive statistics

Standard deviation1140.5495
Coefficient of variation (CV)0.0025504328
Kurtosis0.38327169
Mean447198.39
Median Absolute Deviation (MAD)684.71497
Skewness0.90820013
Sum9391166.3
Variance1300853.1
MonotonicityNot monotonic
2024-05-11T04:56:58.066949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
446861.525362878 2
 
9.5%
448014.07913345 2
 
9.5%
447750.845210817 2
 
9.5%
449596.304559134 1
 
4.8%
447186.888604306 1
 
4.8%
446311.699743049 1
 
4.8%
445450.752690487 1
 
4.8%
446176.810389121 1
 
4.8%
446358.120598616 1
 
4.8%
446521.422307687 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
445450.752690487 1
4.8%
446054.738829512 1
4.8%
446176.810389121 1
4.8%
446305.287756674 1
4.8%
446311.699743049 1
4.8%
446358.120598616 1
4.8%
446479.058882981 1
4.8%
446489.674708003 1
4.8%
446521.422307687 1
4.8%
446861.525362878 2
9.5%
ValueCountFrequency (%)
449783.451870726 1
4.8%
449596.304559134 1
4.8%
448616.907017756 1
4.8%
448014.07913345 2
9.5%
447750.845210817 2
9.5%
447617.64711448 1
4.8%
447186.888604306 1
4.8%
446964.609090888 1
4.8%
446861.525362878 2
9.5%
446521.422307687 1
4.8%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
수영장업
19 
<NA>
2 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영장업 19
90.5%
<NA> 2
 
9.5%

Length

2024-05-11T04:56:58.325188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:58.561698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영장업 19
90.5%
na 2
 
9.5%

공사립구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
사립
19 
<NA>
2 

Length

Max length4
Median length2
Mean length2.1904762
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립 19
90.5%
<NA> 2
 
9.5%

Length

2024-05-11T04:56:58.951512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:59.202258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 19
90.5%
na 2
 
9.5%

보험가입여부코드
Categorical

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
13 
1
3 
0
3 
Y
2 

Length

Max length4
Median length4
Mean length2.8571429
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
61.9%
1 3
 
14.3%
0 3
 
14.3%
Y 2
 
9.5%

Length

2024-05-11T04:56:59.486549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:56:59.944154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
61.9%
1 3
 
14.3%
0 3
 
14.3%
y 2
 
9.5%

지도자수
Categorical

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
11 
2
3 
1
3 
4
2 
3
 
1

Length

Max length4
Median length4
Mean length2.5714286
Min length1

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row3
2nd row4
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 11
52.4%
2 3
 
14.3%
1 3
 
14.3%
4 2
 
9.5%
3 1
 
4.8%
0 1
 
4.8%

Length

2024-05-11T04:57:00.348956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:57:00.755591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 11
52.4%
2 3
 
14.3%
1 3
 
14.3%
4 2
 
9.5%
3 1
 
4.8%
0 1
 
4.8%

건축물동수
Categorical

IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
18 
0
2 
1
 
1

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
85.7%
0 2
 
9.5%
1 1
 
4.8%

Length

2024-05-11T04:57:01.413501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:57:01.779302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
85.7%
0 2
 
9.5%
1 1
 
4.8%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)100.0%
Missing14
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean998.54714
Minimum0
Maximum3400
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-05-11T04:57:02.090852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile135
Q1466
median748
Q3954.915
95-th percentile2714.5
Maximum3400
Range3400
Interquartile range (IQR)488.915

Descriptive statistics

Standard deviation1114.2735
Coefficient of variation (CV)1.1158948
Kurtosis5.0195223
Mean998.54714
Median Absolute Deviation (MAD)298
Skewness2.1129175
Sum6989.83
Variance1241605.5
MonotonicityNot monotonic
2024-05-11T04:57:02.469714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
748.0 1
 
4.8%
794.83 1
 
4.8%
0.0 1
 
4.8%
1115.0 1
 
4.8%
3400.0 1
 
4.8%
482.0 1
 
4.8%
450.0 1
 
4.8%
(Missing) 14
66.7%
ValueCountFrequency (%)
0.0 1
4.8%
450.0 1
4.8%
482.0 1
4.8%
748.0 1
4.8%
794.83 1
4.8%
1115.0 1
4.8%
3400.0 1
4.8%
ValueCountFrequency (%)
3400.0 1
4.8%
1115.0 1
4.8%
794.83 1
4.8%
748.0 1
4.8%
482.0 1
4.8%
450.0 1
4.8%
0.0 1
4.8%

회원모집총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
20 
50
 
1

Length

Max length4
Median length4
Mean length3.9047619
Min length2

Unique

Unique1 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
95.2%
50 1
 
4.8%

Length

2024-05-11T04:57:02.929531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:57:03.311958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
95.2%
50 1
 
4.8%

세부업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

법인명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
03140000CDFH330101198900000119891118<NA>3폐업3폐업20051130<NA><NA><NA>2643-4771<NA>158811서울특별시 양천구 목동 610-23번지서울특별시 양천구 목동중앙북로 19-1 (목동)<NA>자성수영장2006-08-18 13:18:47I2018-08-31 23:59:59.0<NA>188080.1784449596.304559수영장업사립13<NA>748.0<NA><NA><NA>
13140000CDFH330101198900000219891118<NA>1영업/정상13영업중<NA><NA><NA><NA>2646-6819<NA>158050서울특별시 양천구 목동 918번지 6블럭서울특별시 양천구 목동서로 143 (목동,6블럭)7991목동청소년회관2002-12-06 14:56:32I2018-08-31 23:59:59.0<NA>188924.253026447617.647114수영장업사립14<NA>794.83<NA><NA><NA>
23140000CDFH330101199000000119900507<NA>3폐업3폐업19980922<NA><NA><NA><NA><NA>158848서울특별시 양천구 신월동 1001-2번지서울특별시 양천구 신월로 134 (신월동)<NA>영원스포츠센타2002-10-22 17:59:13I2018-08-31 23:59:59.0<NA>185681.509414446054.73883수영장업사립<NA>000.0<NA><NA><NA>
33140000CDFH330101199600000119960604<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2646-6096<NA><NA>서울특별시 양천구 신정동 88-5번지서울특별시 양천구 신목로 53 (신정동, 지하1층,지하2층)8010미진수영장2017-06-08 16:40:31I2018-08-31 23:59:59.0<NA>188656.783841446479.058883수영장업사립Y<NA>01115.0<NA><NA><NA>
43140000CDFH330101199700000119971106<NA>3폐업3폐업20130826<NA><NA><NA>2647-9611<NA>158806서울특별시 양천구 목동 405-25번지서울특별시 양천구 오목로 344 (목동)<NA>청학스포츠타운2013-08-26 16:12:05I2018-08-31 23:59:59.0<NA>188904.571764446861.525363수영장업사립0<NA><NA><NA><NA><NA><NA>
53140000CDFH330101199900000119990901<NA>3폐업3폐업20150318<NA><NA><NA>2652-8083<NA>158050서울특별시 양천구 목동 900번지<NA><NA>양천주민편익시설2015-03-18 17:02:42I2018-08-31 23:59:59.0<NA>189659.125278448616.907018수영장업사립<NA><NA><NA><NA><NA><NA><NA>
63140000CDFH330101199900000219991118<NA>3폐업3폐업20130709<NA><NA><NA>02-2607-8791<NA>158828서울특별시 양천구 신월동 139-1번지서울특별시 양천구 남부순환로 371 (신월동)<NA>서울특별시서부여성발전센터2013-07-09 18:21:06I2018-08-31 23:59:59.0<NA>184902.838587448014.079133수영장업사립14<NA>3400.0<NA><NA><NA>
73140000CDFH330101200100000120010326<NA>3폐업3폐업20080926<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 904번지 4단지 복지시설서울특별시 양천구 목동서로 130 (목동,4단지 복지시설)<NA>목동스포츠센터2008-09-29 08:50:00I2018-08-31 23:59:59.0<NA>188580.483662447750.845211수영장업사립0<NA><NA><NA><NA><NA><NA>
83140000CDFH330101200800000120081027<NA>1영업/정상13영업중<NA><NA><NA><NA>2061-4561<NA>158050서울특별시 양천구 목동 904번지 복리시설 4단지 101호서울특별시 양천구 목동서로 130 (목동,복리시설 4단지 101호)7989목동스포츠센터2018-12-20 10:29:42U2018-12-22 02:40:00.0<NA>188580.483662447750.845211수영장업사립02<NA><NA><NA><NA><NA>
93140000CDFH330101201200000120120308<NA>1영업/정상13영업중<NA><NA><NA><NA>0226530302<NA>158885서울특별시 양천구 신정동 319-23번지 토피아빌딩 B02호서울특별시 양천구 목동서로 299, B02호 (신정동)8013블루라군수영장2015-01-02 12:23:39I2018-08-31 23:59:59.0<NA>188335.855896446489.674708수영장업사립<NA>1<NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명공사립구분명보험가입여부코드지도자수건축물동수건축물연면적회원모집총인원세부업종명법인명
113140000CDFH330101201300000120130527<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>158852서울특별시 양천구 신정동 294-58번지 지하1층서울특별시 양천구 목동동로10길 14, 지층 (신정동)8014MEMBERSHIP POOL(멤버십풀)2020-03-31 09:13:28U2020-04-02 02:40:00.0<NA>188555.64385446305.287757수영장업사립<NA><NA><NA><NA><NA><NA><NA>
123140000CDFH330101201300000220130612<NA>3폐업3폐업20221227<NA><NA><NA>02-2163-3700<NA>158724서울특별시 양천구 목동 916 현대백화점 목동점 UPLEX 8층서울특별시 양천구 목동동로 257 (목동, 현대백화점 목동점 UPLEX 8층)7998휘트니스클럽아로마2023-01-25 17:41:44U2022-11-30 22:07:00.0<NA>188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA>
133140000CDFH330101201400000120140424<NA>1영업/정상13영업중<NA><NA><NA><NA>2653-3738<NA>158053서울특별시 양천구 목동 606-9번지 지층서울특별시 양천구 목동중앙북로7가길 60, 지층 (목동)7946오션키즈강서센터2019-03-08 11:29:22U2019-03-12 02:40:00.0<NA>187954.571823449783.451871수영장업사립<NA><NA><NA><NA><NA><NA><NA>
143140000CDFH330101201400000220141208<NA>3폐업3폐업20200323<NA><NA><NA>0262138875<NA>158885서울특별시 양천구 신정동 319-26번지서울특별시 양천구 목동서로 293 (신정동)8013이노스베이 어린이 수상안전교육센타2020-03-23 13:11:57U2020-03-25 02:40:00.0<NA>188388.142162446521.422308수영장업사립Y<NA><NA><NA><NA><NA><NA>
153140000CDFH330101201400000320141224<NA>1영업/정상13영업중<NA><NA><NA><NA>2653-4302<NA>158722서울특별시 양천구 목동 405-25 지하2층서울특별시 양천구 오목로 344, 지하2층 (목동)8006블루라군 수영장2023-01-05 13:03:45U2022-12-01 00:07:00.0<NA>188904.571764446861.525363<NA><NA><NA><NA><NA><NA><NA><NA><NA>
163140000CDFH330101201600000120160113<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2607-8791<NA><NA>서울특별시 양천구 신월동 139-1서울특별시 양천구 남부순환로 371 (신월동, 서울특별시서부여성발전센터)7920서울특별시 서부여성발전센터2021-03-10 10:02:58U2021-03-12 02:40:00.0<NA>184902.838587448014.079133수영장업사립<NA><NA><NA><NA><NA><NA><NA>
173140000CDFH330101201600000220160704<NA>1영업/정상13영업중<NA><NA><NA><NA>6929-0079<NA><NA>서울특별시 양천구 신정동 296-24 지하1층서울특별시 양천구 목동동로10길 24 (신정동)8014키즈 엘리트2020-12-29 17:58:10U2020-12-31 02:40:00.0<NA>188650.113585446358.120599수영장업사립<NA>1<NA>482.0<NA><NA><NA>
183140000CDFH330101201700000120170407<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2607-1001<NA><NA>서울특별시 양천구 신정동 1182-11번지 상운맘모스 지하2층 201호 일부서울특별시 양천구 중앙로 237 (신정동, 지하2층201호일부)8073블루라군수영장2017-06-07 14:01:12I2018-08-31 23:59:59.0<NA>186990.070415446176.810389수영장업사립<NA>11450.050<NA><NA>
193140000CDFH330101201900000120190730<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2601-3456<NA><NA>서울특별시 양천구 신정동 1274 서울신기초등학교서울특별시 양천구 신정로 292, 서울신기초등학교 (신정동)8106신기스포렉스2021-01-26 14:20:22U2021-01-28 02:40:00.0<NA>187037.450703445450.75269수영장업사립<NA>2<NA><NA><NA><NA><NA>
203140000CDFH330101202000000120200806<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6346-3200<NA><NA>서울특별시 양천구 신정동 329-10 목동 블루스퀘어 지하1층서울특별시 양천구 목동동로 150, 목동 블루스퀘어 지하1층 (신정동)8014국가대표 어린이수영클럽2020-08-06 18:05:56I2020-08-08 00:23:14.0<NA>188484.077673446311.699743수영장업사립<NA>2<NA><NA><NA><NA><NA>