Overview

Dataset statistics

Number of variables26
Number of observations71
Missing cells155
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.4 KiB
Average record size in memory221.9 B

Variable types

Categorical13
Numeric5
DateTime2
Text6

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),점포구분명
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18724/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (89.3%)Imbalance
휴업시작일자 is highly imbalanced (89.3%)Imbalance
휴업종료일자 is highly imbalanced (89.3%)Imbalance
재개업일자 is highly imbalanced (89.3%)Imbalance
폐업일자 has 56 (78.9%) missing valuesMissing
소재지면적 has 4 (5.6%) missing valuesMissing
소재지우편번호 has 53 (74.6%) missing valuesMissing
지번주소 has 16 (22.5%) missing valuesMissing
도로명주소 has 11 (15.5%) missing valuesMissing
도로명우편번호 has 11 (15.5%) missing valuesMissing
좌표정보(X) has 2 (2.8%) missing valuesMissing
좌표정보(Y) has 2 (2.8%) missing valuesMissing
관리번호 has unique valuesUnique
소재지면적 has 21 (29.6%) zerosZeros

Reproduction

Analysis started2024-04-06 11:55:31.650701
Analysis finished2024-04-06 11:55:32.457838
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
3220000
71 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 71
100.0%

Length

2024-04-06T20:55:32.574187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:32.803709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 71
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0064865 × 1018
Minimum1.984322 × 1018
Maximum2.022322 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-04-06T20:55:33.088097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.984322 × 1018
5-th percentile2.001322 × 1018
Q12.001322 × 1018
median2.003322 × 1018
Q32.013322 × 1018
95-th percentile2.017322 × 1018
Maximum2.022322 × 1018
Range3.8000017 × 1016
Interquartile range (IQR)1.2000008 × 1016

Descriptive statistics

Standard deviation7.6015326 × 1015
Coefficient of variation (CV)0.0037884793
Kurtosis0.50027383
Mean2.0064865 × 1018
Median Absolute Deviation (MAD)2 × 1015
Skewness-0.18331028
Sum-5.1134117 × 1018
Variance5.7783298 × 1031
MonotonicityStrictly increasing
2024-04-06T20:55:33.409863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1984322008307500006 1
 
1.4%
1984322016207500001 1
 
1.4%
2013322016207500002 1
 
1.4%
2013322016207500001 1
 
1.4%
2012322016207500003 1
 
1.4%
2012322016207500002 1
 
1.4%
2012322016207500001 1
 
1.4%
2011322016207500003 1
 
1.4%
2011322016207500002 1
 
1.4%
2011322016207500001 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
1984322008307500006 1
1.4%
1984322016207500001 1
1.4%
1996322016207500001 1
1.4%
2001322008307500001 1
1.4%
2001322008307500002 1
1.4%
2001322008307500003 1
1.4%
2001322008307500004 1
1.4%
2001322008307500005 1
1.4%
2001322008307500006 1
1.4%
2001322008307500007 1
1.4%
ValueCountFrequency (%)
2022322024907500002 1
1.4%
2022322024907500001 1
1.4%
2021322024907500001 1
1.4%
2018322016207500001 1
1.4%
2016322016207500001 1
1.4%
2015322016207500001 1
1.4%
2014322016207500011 1
1.4%
2014322016207500010 1
1.4%
2014322016207500009 1
1.4%
2014322016207500008 1
1.4%

인허가일자
Date

Distinct62
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size700.0 B
Minimum1973-08-01 00:00:00
Maximum2022-09-15 00:00:00
2024-04-06T20:55:33.838816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:55:34.167110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
<NA>
70 
20100908
 
1

Length

Max length8
Median length4
Mean length4.056338
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
98.6%
20100908 1
 
1.4%

Length

2024-04-06T20:55:34.460344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:34.734153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
98.6%
20100908 1
 
1.4%

영업상태코드
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
1
50 
3
15 
2
 
5
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 50
70.4%
3 15
 
21.1%
2 5
 
7.0%
4 1
 
1.4%

Length

2024-04-06T20:55:34.978230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:35.242771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
70.4%
3 15
 
21.1%
2 5
 
7.0%
4 1
 
1.4%

영업상태명
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
영업/정상
50 
폐업
15 
휴업
 
5
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length4.2816901
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 50
70.4%
폐업 15
 
21.1%
휴업 5
 
7.0%
취소/말소/만료/정지/중지 1
 
1.4%

Length

2024-04-06T20:55:35.580412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:35.832302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 50
70.4%
폐업 15
 
21.1%
휴업 5
 
7.0%
취소/말소/만료/정지/중지 1
 
1.4%

상세영업상태코드
Categorical

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
1
49 
3
15 
2
5 
4
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.8%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 49
69.0%
3 15
 
21.1%
2 5
 
7.0%
4 1
 
1.4%
5 1
 
1.4%

Length

2024-04-06T20:55:36.099449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:36.405528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
69.0%
3 15
 
21.1%
2 5
 
7.0%
4 1
 
1.4%
5 1
 
1.4%

상세영업상태명
Categorical

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
정상영업
49 
폐업처리
15 
휴업처리
5 
직권취소
 
1
영업개시전
 
1

Length

Max length5
Median length4
Mean length4.0140845
Min length4

Unique

Unique2 ?
Unique (%)2.8%

Sample

1st row휴업처리
2nd row정상영업
3rd row정상영업
4th row정상영업
5th row폐업처리

Common Values

ValueCountFrequency (%)
정상영업 49
69.0%
폐업처리 15
 
21.1%
휴업처리 5
 
7.0%
직권취소 1
 
1.4%
영업개시전 1
 
1.4%

Length

2024-04-06T20:55:36.678052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:36.995754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 49
69.0%
폐업처리 15
 
21.1%
휴업처리 5
 
7.0%
직권취소 1
 
1.4%
영업개시전 1
 
1.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)86.7%
Missing56
Missing (%)78.9%
Infinite0
Infinite (%)0.0%
Mean20151981
Minimum20090922
Maximum20220819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-04-06T20:55:37.278775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090922
5-th percentile20097424
Q120125717
median20140324
Q320190831
95-th percentile20214107
Maximum20220819
Range129897
Interquartile range (IQR)65114

Descriptive statistics

Standard deviation43626.756
Coefficient of variation (CV)0.0021648867
Kurtosis-1.327076
Mean20151981
Median Absolute Deviation (MAD)39094
Skewness0.29575967
Sum3.0227971 × 108
Variance1.9032938 × 109
MonotonicityNot monotonic
2024-04-06T20:55:37.563515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20130220 2
 
2.8%
20190831 2
 
2.8%
20130214 1
 
1.4%
20140324 1
 
1.4%
20101230 1
 
1.4%
20210513 1
 
1.4%
20090922 1
 
1.4%
20121220 1
 
1.4%
20100210 1
 
1.4%
20170313 1
 
1.4%
Other values (3) 3
 
4.2%
(Missing) 56
78.9%
ValueCountFrequency (%)
20090922 1
1.4%
20100210 1
1.4%
20101230 1
1.4%
20121220 1
1.4%
20130214 1
1.4%
20130220 2
2.8%
20140324 1
1.4%
20140615 1
1.4%
20170313 1
1.4%
20190831 2
2.8%
ValueCountFrequency (%)
20220819 1
1.4%
20211230 1
1.4%
20210513 1
1.4%
20190831 2
2.8%
20170313 1
1.4%
20140615 1
1.4%
20140324 1
1.4%
20130220 2
2.8%
20130214 1
1.4%
20121220 1
1.4%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
<NA>
70 
20110415
 
1

Length

Max length8
Median length4
Mean length4.056338
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
98.6%
20110415 1
 
1.4%

Length

2024-04-06T20:55:37.963880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:38.289015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
98.6%
20110415 1
 
1.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
<NA>
70 
20140430
 
1

Length

Max length8
Median length4
Mean length4.056338
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
98.6%
20140430 1
 
1.4%

Length

2024-04-06T20:55:38.548165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:38.802446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
98.6%
20140430 1
 
1.4%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
<NA>
70 
20140326
 
1

Length

Max length8
Median length4
Mean length4.056338
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 70
98.6%
20140326 1
 
1.4%

Length

2024-04-06T20:55:39.078166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:39.316188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 70
98.6%
20140326 1
 
1.4%

전화번호
Text

Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-04-06T20:55:39.705657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.169014
Min length1

Characters and Unicode

Total characters722
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)93.0%

Sample

1st row02 5492233
2nd row02-561-4267
3rd row02-550-3090
4th row02 5420874
5th row02 5471151
ValueCountFrequency (%)
02 28
28.3%
5492233 3
 
3.0%
02-6908-1051 2
 
2.0%
025560604 1
 
1.0%
02-567-3424 1
 
1.0%
000269471234 1
 
1.0%
025168546 1
 
1.0%
545-9612 1
 
1.0%
025184089 1
 
1.0%
0221387230 1
 
1.0%
Other values (59) 59
59.6%
2024-04-06T20:55:40.400095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 123
17.0%
2 107
14.8%
5 92
12.7%
4 79
10.9%
6 57
7.9%
3 54
7.5%
1 45
 
6.2%
- 44
 
6.1%
9 40
 
5.5%
28
 
3.9%
Other values (3) 53
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 647
89.6%
Dash Punctuation 44
 
6.1%
Space Separator 28
 
3.9%
Close Punctuation 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 123
19.0%
2 107
16.5%
5 92
14.2%
4 79
12.2%
6 57
8.8%
3 54
8.3%
1 45
 
7.0%
9 40
 
6.2%
8 25
 
3.9%
7 25
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 123
17.0%
2 107
14.8%
5 92
12.7%
4 79
10.9%
6 57
7.9%
3 54
7.5%
1 45
 
6.2%
- 44
 
6.1%
9 40
 
5.5%
28
 
3.9%
Other values (3) 53
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 123
17.0%
2 107
14.8%
5 92
12.7%
4 79
10.9%
6 57
7.9%
3 54
7.5%
1 45
 
6.2%
- 44
 
6.1%
9 40
 
5.5%
28
 
3.9%
Other values (3) 53
7.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct46
Distinct (%)68.7%
Missing4
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean5405.4109
Minimum0
Maximum80038
Zeros21
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-04-06T20:55:40.680137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median503.8
Q34437.13
95-th percentile24943.722
Maximum80038
Range80038
Interquartile range (IQR)4437.13

Descriptive statistics

Standard deviation12579.656
Coefficient of variation (CV)2.3272339
Kurtosis20.156294
Mean5405.4109
Median Absolute Deviation (MAD)503.8
Skewness4.1322259
Sum362162.53
Variance1.5824773 × 108
MonotonicityNot monotonic
2024-04-06T20:55:40.955685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.0 21
29.6%
5174.0 2
 
2.8%
730.7 1
 
1.4%
231.0 1
 
1.4%
3041.01 1
 
1.4%
3246.51 1
 
1.4%
180.8 1
 
1.4%
177.7 1
 
1.4%
336.2 1
 
1.4%
177.8 1
 
1.4%
Other values (36) 36
50.7%
(Missing) 4
 
5.6%
ValueCountFrequency (%)
0.0 21
29.6%
120.07 1
 
1.4%
170.28 1
 
1.4%
177.7 1
 
1.4%
177.8 1
 
1.4%
180.8 1
 
1.4%
198.0 1
 
1.4%
223.0 1
 
1.4%
231.0 1
 
1.4%
272.02 1
 
1.4%
ValueCountFrequency (%)
80038.0 1
1.4%
46111.46 1
1.4%
37604.54 1
1.4%
26532.0 1
1.4%
21237.74 1
1.4%
15358.0 1
1.4%
13667.0 1
1.4%
12645.92 1
1.4%
12025.9 1
1.4%
11740.39 1
1.4%

소재지우편번호
Text

MISSING 

Distinct16
Distinct (%)88.9%
Missing53
Missing (%)74.6%
Memory size700.0 B
2024-04-06T20:55:41.302295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2222222
Min length6

Characters and Unicode

Total characters112
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

Unique14 ?
Unique (%)77.8%

Sample

1st row135926
2nd row135-724
3rd row135732
4th row135-731
5th row135-510
ValueCountFrequency (%)
135080 2
 
11.1%
135011 2
 
11.1%
135926 1
 
5.6%
135-724 1
 
5.6%
135732 1
 
5.6%
135-731 1
 
5.6%
135-510 1
 
5.6%
135280 1
 
5.6%
135509 1
 
5.6%
135820 1
 
5.6%
Other values (6) 6
33.3%
2024-04-06T20:55:41.819214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
21.4%
5 22
19.6%
3 21
18.8%
0 11
9.8%
8 9
 
8.0%
9 6
 
5.4%
2 6
 
5.4%
- 4
 
3.6%
7 4
 
3.6%
4 3
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
96.4%
Dash Punctuation 4
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
22.2%
5 22
20.4%
3 21
19.4%
0 11
10.2%
8 9
 
8.3%
9 6
 
5.6%
2 6
 
5.6%
7 4
 
3.7%
4 3
 
2.8%
6 2
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
21.4%
5 22
19.6%
3 21
18.8%
0 11
9.8%
8 9
 
8.0%
9 6
 
5.4%
2 6
 
5.4%
- 4
 
3.6%
7 4
 
3.6%
4 3
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
21.4%
5 22
19.6%
3 21
18.8%
0 11
9.8%
8 9
 
8.0%
9 6
 
5.4%
2 6
 
5.4%
- 4
 
3.6%
7 4
 
3.6%
4 3
 
2.7%

지번주소
Text

MISSING 

Distinct49
Distinct (%)89.1%
Missing16
Missing (%)22.5%
Memory size700.0 B
2024-04-06T20:55:42.244838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length28
Mean length22.545455
Min length17

Characters and Unicode

Total characters1240
Distinct characters85
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

Unique45 ?
Unique (%)81.8%

Sample

1st row서울특별시 강남구 압구정동 456호
2nd row서울특별시 강남구 대치동 511번지 한보미도맨션
3rd row서울특별시 강남구 역삼동 755번지
4th row서울특별시 강남구 신사동 510번지 11호
5th row서울특별시 강남구 논현동 122번지 8호
ValueCountFrequency (%)
서울특별시 55
20.8%
강남구 55
20.8%
역삼동 9
 
3.4%
압구정동 7
 
2.7%
대치동 7
 
2.7%
외 5
 
1.9%
논현동 5
 
1.9%
호 5
 
1.9%
신사동 4
 
1.5%
1호 4
 
1.5%
Other values (83) 108
40.9%
2024-04-06T20:55:42.881286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
18.5%
구 63
 
5.1%
동 56
 
4.5%
남 56
 
4.5%
강 56
 
4.5%
서 56
 
4.5%
시 55
 
4.4%
별 55
 
4.4%
울 55
 
4.4%
특 55
 
4.4%
Other values (75) 504
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 783
63.1%
Space Separator 229
 
18.5%
Decimal Number 217
 
17.5%
Dash Punctuation 3
 
0.2%
Uppercase Letter 3
 
0.2%
Other Punctuation 3
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 63
 
8.0%
동 56
 
7.2%
남 56
 
7.2%
강 56
 
7.2%
서 56
 
7.2%
시 55
 
7.0%
별 55
 
7.0%
울 55
 
7.0%
특 55
 
7.0%
호 42
 
5.4%
Other values (59) 234
29.9%
Decimal Number
ValueCountFrequency (%)
1 47
21.7%
2 28
12.9%
5 27
12.4%
4 25
11.5%
6 22
10.1%
7 21
9.7%
0 15
 
6.9%
9 13
 
6.0%
8 10
 
4.6%
3 9
 
4.1%
Space Separator
ValueCountFrequency (%)
229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 783
63.1%
Common 454
36.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 63
 
8.0%
동 56
 
7.2%
남 56
 
7.2%
강 56
 
7.2%
서 56
 
7.2%
시 55
 
7.0%
별 55
 
7.0%
울 55
 
7.0%
특 55
 
7.0%
호 42
 
5.4%
Other values (59) 234
29.9%
Common
ValueCountFrequency (%)
229
50.4%
1 47
 
10.4%
2 28
 
6.2%
5 27
 
5.9%
4 25
 
5.5%
6 22
 
4.8%
7 21
 
4.6%
0 15
 
3.3%
9 13
 
2.9%
8 10
 
2.2%
Other values (5) 17
 
3.7%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 783
63.1%
ASCII 457
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
50.1%
1 47
 
10.3%
2 28
 
6.1%
5 27
 
5.9%
4 25
 
5.5%
6 22
 
4.8%
7 21
 
4.6%
0 15
 
3.3%
9 13
 
2.8%
8 10
 
2.2%
Other values (6) 20
 
4.4%
Hangul
ValueCountFrequency (%)
구 63
 
8.0%
동 56
 
7.2%
남 56
 
7.2%
강 56
 
7.2%
서 56
 
7.2%
시 55
 
7.0%
별 55
 
7.0%
울 55
 
7.0%
특 55
 
7.0%
호 42
 
5.4%
Other values (59) 234
29.9%

도로명주소
Text

MISSING 

Distinct54
Distinct (%)90.0%
Missing11
Missing (%)15.5%
Memory size700.0 B
2024-04-06T20:55:43.362120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length36
Mean length28.666667
Min length23

Characters and Unicode

Total characters1720
Distinct characters112
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)81.7%

Sample

1st row서울특별시 강남구 삼성로 150 (대치동, 한보미도맨션)
2nd row서울특별시 강남구 역삼로 310 (역삼동)
3rd row서울특별시 강남구 압구정로2길 46 (신사동)
4th row서울특별시 강남구 학동로4길 15 (논현동)
5th row서울특별시 강남구 봉은사로33길 33 (논현동)
ValueCountFrequency (%)
서울특별시 60
 
18.2%
강남구 59
 
17.9%
역삼동 11
 
3.3%
논현동 10
 
3.0%
삼성동 10
 
3.0%
대치동 6
 
1.8%
신사동 6
 
1.8%
압구정로 5
 
1.5%
청담동 5
 
1.5%
1층 4
 
1.2%
Other values (117) 154
46.7%
2024-04-06T20:55:44.145905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
15.7%
구 74
 
4.3%
동 69
 
4.0%
남 66
 
3.8%
강 62
 
3.6%
서 61
 
3.5%
시 61
 
3.5%
( 60
 
3.5%
특 60
 
3.5%
별 60
 
3.5%
Other values (102) 877
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1050
61.0%
Space Separator 270
 
15.7%
Decimal Number 237
 
13.8%
Open Punctuation 60
 
3.5%
Close Punctuation 60
 
3.5%
Other Punctuation 30
 
1.7%
Dash Punctuation 13
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 74
 
7.0%
동 69
 
6.6%
남 66
 
6.3%
강 62
 
5.9%
서 61
 
5.8%
시 61
 
5.8%
특 60
 
5.7%
별 60
 
5.7%
울 60
 
5.7%
로 60
 
5.7%
Other values (87) 417
39.7%
Decimal Number
ValueCountFrequency (%)
1 48
20.3%
2 42
17.7%
3 31
13.1%
4 25
10.5%
0 23
9.7%
5 22
9.3%
6 16
 
6.8%
8 12
 
5.1%
9 10
 
4.2%
7 8
 
3.4%
Space Separator
ValueCountFrequency (%)
270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1050
61.0%
Common 670
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 74
 
7.0%
동 69
 
6.6%
남 66
 
6.3%
강 62
 
5.9%
서 61
 
5.8%
시 61
 
5.8%
특 60
 
5.7%
별 60
 
5.7%
울 60
 
5.7%
로 60
 
5.7%
Other values (87) 417
39.7%
Common
ValueCountFrequency (%)
270
40.3%
( 60
 
9.0%
) 60
 
9.0%
1 48
 
7.2%
2 42
 
6.3%
3 31
 
4.6%
, 30
 
4.5%
4 25
 
3.7%
0 23
 
3.4%
5 22
 
3.3%
Other values (5) 59
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1050
61.0%
ASCII 670
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
40.3%
( 60
 
9.0%
) 60
 
9.0%
1 48
 
7.2%
2 42
 
6.3%
3 31
 
4.6%
, 30
 
4.5%
4 25
 
3.7%
0 23
 
3.4%
5 22
 
3.3%
Other values (5) 59
 
8.8%
Hangul
ValueCountFrequency (%)
구 74
 
7.0%
동 69
 
6.6%
남 66
 
6.3%
강 62
 
5.9%
서 61
 
5.8%
시 61
 
5.8%
특 60
 
5.7%
별 60
 
5.7%
울 60
 
5.7%
로 60
 
5.7%
Other values (87) 417
39.7%

도로명우편번호
Text

MISSING 

Distinct50
Distinct (%)83.3%
Missing11
Missing (%)15.5%
Memory size700.0 B
2024-04-06T20:55:44.496200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9666667
Min length5

Characters and Unicode

Total characters358
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

Unique43 ?
Unique (%)71.7%

Sample

1st row06288
2nd row135926
3rd row135887
4th row135822
5th row135829
ValueCountFrequency (%)
135926 5
 
8.3%
135940 2
 
3.3%
135838 2
 
3.3%
135509 2
 
3.3%
135955 2
 
3.3%
135822 2
 
3.3%
135-902 2
 
3.3%
135569 1
 
1.7%
135897 1
 
1.7%
135823 1
 
1.7%
Other values (40) 40
66.7%
2024-04-06T20:55:45.520356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 67
18.7%
5 65
18.2%
1 62
17.3%
8 33
9.2%
9 29
8.1%
0 28
7.8%
2 25
 
7.0%
6 17
 
4.7%
7 14
 
3.9%
4 11
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 351
98.0%
Dash Punctuation 7
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 67
19.1%
5 65
18.5%
1 62
17.7%
8 33
9.4%
9 29
8.3%
0 28
8.0%
2 25
 
7.1%
6 17
 
4.8%
7 14
 
4.0%
4 11
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 358
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 67
18.7%
5 65
18.2%
1 62
17.3%
8 33
9.2%
9 29
8.1%
0 28
7.8%
2 25
 
7.0%
6 17
 
4.7%
7 14
 
3.9%
4 11
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 67
18.7%
5 65
18.2%
1 62
17.3%
8 33
9.2%
9 29
8.1%
0 28
7.8%
2 25
 
7.0%
6 17
 
4.7%
7 14
 
3.9%
4 11
 
3.1%

사업장명
Text

Distinct67
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-04-06T20:55:46.012403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length18
Mean length9.6338028
Min length4

Characters and Unicode

Total characters684
Distinct characters158
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

Unique63 ?
Unique (%)88.7%

Sample

1st row(주)금강개발산업
2nd row한보종합상가
3rd row한솔필리아
4th row강남시장
5th row영동시장
ValueCountFrequency (%)
롯데슈퍼 6
 
4.9%
역삼점 4
 
3.3%
압구정점 3
 
2.5%
논현점 3
 
2.5%
주)지에스리테일 3
 
2.5%
주)현대백화점 2
 
1.6%
삼성점 2
 
1.6%
이마트 2
 
1.6%
the 2
 
1.6%
코엑스 2
 
1.6%
Other values (84) 93
76.2%
2024-04-06T20:55:46.768277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
7.5%
점 33
 
4.8%
스 21
 
3.1%
( 18
 
2.6%
) 18
 
2.6%
상 17
 
2.5%
가 15
 
2.2%
삼 14
 
2.0%
주 13
 
1.9%
시 12
 
1.8%
Other values (148) 472
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 508
74.3%
Uppercase Letter 61
 
8.9%
Space Separator 51
 
7.5%
Open Punctuation 18
 
2.6%
Close Punctuation 18
 
2.6%
Lowercase Letter 16
 
2.3%
Decimal Number 10
 
1.5%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 33
 
6.5%
스 21
 
4.1%
상 17
 
3.3%
가 15
 
3.0%
삼 14
 
2.8%
주 13
 
2.6%
시 12
 
2.4%
장 11
 
2.2%
역 11
 
2.2%
데 11
 
2.2%
Other values (116) 350
68.9%
Uppercase Letter
ValueCountFrequency (%)
S 10
16.4%
A 6
9.8%
L 6
9.8%
E 6
9.8%
T 5
8.2%
M 4
 
6.6%
H 4
 
6.6%
G 4
 
6.6%
F 4
 
6.6%
R 3
 
4.9%
Other values (6) 9
14.8%
Lowercase Letter
ValueCountFrequency (%)
o 4
25.0%
e 2
12.5%
t 2
12.5%
k 2
12.5%
r 2
12.5%
a 2
12.5%
d 2
12.5%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
1 3
30.0%
0 1
 
10.0%
8 1
 
10.0%
6 1
 
10.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 508
74.3%
Common 99
 
14.5%
Latin 77
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 33
 
6.5%
스 21
 
4.1%
상 17
 
3.3%
가 15
 
3.0%
삼 14
 
2.8%
주 13
 
2.6%
시 12
 
2.4%
장 11
 
2.2%
역 11
 
2.2%
데 11
 
2.2%
Other values (116) 350
68.9%
Latin
ValueCountFrequency (%)
S 10
13.0%
A 6
 
7.8%
L 6
 
7.8%
E 6
 
7.8%
T 5
 
6.5%
M 4
 
5.2%
H 4
 
5.2%
G 4
 
5.2%
F 4
 
5.2%
o 4
 
5.2%
Other values (13) 24
31.2%
Common
ValueCountFrequency (%)
51
51.5%
( 18
 
18.2%
) 18
 
18.2%
2 4
 
4.0%
1 3
 
3.0%
- 2
 
2.0%
0 1
 
1.0%
8 1
 
1.0%
6 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 508
74.3%
ASCII 176
 
25.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
29.0%
( 18
 
10.2%
) 18
 
10.2%
S 10
 
5.7%
A 6
 
3.4%
L 6
 
3.4%
E 6
 
3.4%
T 5
 
2.8%
2 4
 
2.3%
M 4
 
2.3%
Other values (22) 48
27.3%
Hangul
ValueCountFrequency (%)
점 33
 
6.5%
스 21
 
4.1%
상 17
 
3.3%
가 15
 
3.0%
삼 14
 
2.8%
주 13
 
2.6%
시 12
 
2.4%
장 11
 
2.2%
역 11
 
2.2%
데 11
 
2.2%
Other values (116) 350
68.9%

최종수정일자
Date

Distinct67
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
Minimum2007-07-14 10:53:01
Maximum2024-04-03 09:54:25
2024-04-06T20:55:47.029392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:55:47.373221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
I
40 
U
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 40
56.3%
U 31
43.7%

Length

2024-04-06T20:55:47.670614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:47.853686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 40
56.3%
u 31
43.7%

데이터갱신일자
Categorical

Distinct25
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
2018-08-31 23:59:59.0
39 
2019-09-03 02:40:00.0
5 
2022-01-19 02:40:00.0
 
3
2022-12-02 21:00:00.0
 
2
2021-06-19 02:40:00.0
 
2
Other values (20)
20 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique20 ?
Unique (%)28.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2020-11-10 02:40:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 39
54.9%
2019-09-03 02:40:00.0 5
 
7.0%
2022-01-19 02:40:00.0 3
 
4.2%
2022-12-02 21:00:00.0 2
 
2.8%
2021-06-19 02:40:00.0 2
 
2.8%
2021-06-20 02:40:00.0 1
 
1.4%
2019-05-11 02:40:00.0 1
 
1.4%
2021-05-15 02:40:00.0 1
 
1.4%
2023-12-03 00:08:00.0 1
 
1.4%
2020-04-22 02:40:00.0 1
 
1.4%
Other values (15) 15
 
21.1%

Length

2024-04-06T20:55:48.035398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 39
27.5%
23:59:59.0 39
27.5%
02:40:00.0 21
14.8%
2019-09-03 5
 
3.5%
2022-01-19 3
 
2.1%
2022-12-02 2
 
1.4%
21:00:00.0 2
 
1.4%
2021-06-19 2
 
1.4%
2018-12-29 1
 
0.7%
22:01:00.0 1
 
0.7%
Other values (27) 27
19.0%

업태구분명
Categorical

Distinct8
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size700.0 B
그 밖의 대규모점포
34 
구분없음
17 
백화점
8 
대형마트
4 
쇼핑센터
 
3
Other values (3)
5 

Length

Max length10
Median length5
Mean length6.7323944
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row그 밖의 대규모점포
2nd row그 밖의 대규모점포
3rd row그 밖의 대규모점포
4th row복합쇼핑몰
5th row그 밖의 대규모점포

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 34
47.9%
구분없음 17
23.9%
백화점 8
 
11.3%
대형마트 4
 
5.6%
쇼핑센터 3
 
4.2%
복합쇼핑몰 2
 
2.8%
시장 2
 
2.8%
<NA> 1
 
1.4%

Length

2024-04-06T20:55:48.286059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:48.498285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 34
24.5%
밖의 34
24.5%
대규모점포 34
24.5%
구분없음 17
12.2%
백화점 8
 
5.8%
대형마트 4
 
2.9%
쇼핑센터 3
 
2.2%
복합쇼핑몰 2
 
1.4%
시장 2
 
1.4%
na 1
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)78.3%
Missing2
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean203988.8
Minimum201757.49
Maximum208789.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-04-06T20:55:48.722092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201757.49
5-th percentile202010.01
Q1202612.71
median203789.59
Q3204992.45
95-th percentile206815.27
Maximum208789.63
Range7032.1319
Interquartile range (IQR)2379.7432

Descriptive statistics

Standard deviation1527.3211
Coefficient of variation (CV)0.007487279
Kurtosis0.7296975
Mean203988.8
Median Absolute Deviation (MAD)1190.076
Skewness0.83072275
Sum14075227
Variance2332709.6
MonotonicityNot monotonic
2024-04-06T20:55:48.977158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202485.226490575 4
 
5.6%
204213.643236507 4
 
5.6%
204391.425431 2
 
2.8%
202023.395227792 2
 
2.8%
203789.588128352 2
 
2.8%
203292.307005445 2
 
2.8%
204254.782968629 2
 
2.8%
206581.787067095 2
 
2.8%
204170.278135097 2
 
2.8%
202010.0103397 2
 
2.8%
Other values (44) 45
63.4%
ValueCountFrequency (%)
201757.494098748 2
2.8%
201994.292033914 1
 
1.4%
202010.0103397 2
2.8%
202023.395227792 2
2.8%
202167.012989943 1
 
1.4%
202296.99602809 1
 
1.4%
202358.505687227 1
 
1.4%
202440.338882233 1
 
1.4%
202485.226490575 4
5.6%
202557.007830645 1
 
1.4%
ValueCountFrequency (%)
208789.626026494 1
1.4%
207748.487100942 1
1.4%
207614.091005038 1
1.4%
206970.919291372 1
1.4%
206581.787067095 2
2.8%
205886.286776047 1
1.4%
205558.159926896 1
1.4%
205359.898726792 1
1.4%
205340.631121567 1
1.4%
205314.159889285 1
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)78.3%
Missing2
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean445188.96
Minimum442286.23
Maximum447782.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-04-06T20:55:49.223523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442286.23
5-th percentile443039.14
Q1443854.9
median445302.92
Q3446316.51
95-th percentile447521.52
Maximum447782.51
Range5496.284
Interquartile range (IQR)2461.6172

Descriptive statistics

Standard deviation1541.1755
Coefficient of variation (CV)0.0034618458
Kurtosis-1.2170918
Mean445188.96
Median Absolute Deviation (MAD)1429.2947
Skewness0.065238683
Sum30718038
Variance2375222
MonotonicityNot monotonic
2024-04-06T20:55:49.517066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447521.520319158 4
 
5.6%
444113.028210915 4
 
5.6%
447439.752421 2
 
2.8%
445302.915908145 2
 
2.8%
446796.128299612 2
 
2.8%
446247.511537864 2
 
2.8%
442744.847670936 2
 
2.8%
443555.991242524 2
 
2.8%
444036.656041328 2
 
2.8%
445368.131754546 2
 
2.8%
Other values (44) 45
63.4%
ValueCountFrequency (%)
442286.229201457 1
1.4%
442744.847670936 2
2.8%
442942.853505354 1
1.4%
443183.576115254 1
1.4%
443219.258555294 1
1.4%
443240.945026406 1
1.4%
443297.031452896 1
1.4%
443422.779316247 1
1.4%
443437.682541522 1
1.4%
443439.981644506 1
1.4%
ValueCountFrequency (%)
447782.51322707 1
 
1.4%
447521.520319158 4
5.6%
447439.752421 2
2.8%
447391.130408384 1
 
1.4%
447369.579851952 1
 
1.4%
447316.222786487 1
 
1.4%
447312.903662969 1
 
1.4%
447232.955697694 1
 
1.4%
446808.075588622 1
 
1.4%
446806.733541327 1
 
1.4%

점포구분명
Categorical

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
대규모점포
36 
<NA>
20 
준대규모점포
15 

Length

Max length6
Median length5
Mean length4.9295775
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대규모점포 36
50.7%
<NA> 20
28.2%
준대규모점포 15
21.1%

Length

2024-04-06T20:55:49.811186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:55:49.995734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대규모점포 36
50.7%
na 20
28.2%
준대규모점포 15
21.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03220000198432200830750000619840307<NA>2휴업2휴업처리<NA><NA><NA><NA>02 5492233<NA><NA>서울특별시 강남구 압구정동 456호<NA><NA>(주)금강개발산업2007-07-14 10:53:01I2018-08-31 23:59:59.0그 밖의 대규모점포202485.226491447521.520319<NA>
13220000198432201620750000119840208<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-561-426711740.39<NA>서울특별시 강남구 대치동 511번지 한보미도맨션서울특별시 강남구 삼성로 150 (대치동, 한보미도맨션)06288한보종합상가2018-04-18 17:24:03I2018-08-31 23:59:59.0그 밖의 대규모점포205886.286776443467.611816대규모점포
23220000199632201620750000119961115<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-550-309012025.9135926서울특별시 강남구 역삼동 755번지서울특별시 강남구 역삼로 310 (역삼동)135926한솔필리아2018-04-18 16:09:06I2018-08-31 23:59:59.0그 밖의 대규모점포204213.643237444113.028211대규모점포
33220000200132200830750000119741110<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 54208743062.7<NA>서울특별시 강남구 신사동 510번지 11호서울특별시 강남구 압구정로2길 46 (신사동)135887강남시장2020-11-08 15:42:17U2020-11-10 02:40:00.0복합쇼핑몰201757.494099446282.454467대규모점포
43220000200132200830750000219730801<NA>3폐업3폐업처리20130214<NA><NA><NA>02 54711510.0<NA>서울특별시 강남구 논현동 122번지 8호서울특별시 강남구 학동로4길 15 (논현동)135822영동시장2013-12-30 09:11:02I2018-08-31 23:59:59.0그 밖의 대규모점포202010.01034445368.131755대규모점포
53220000200132200830750000319790117<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 54919400.0<NA>서울특별시 강남구 논현동 227번지 4호서울특별시 강남구 봉은사로33길 33 (논현동)135829논현종합시장2019-05-09 16:34:32U2019-05-11 02:40:00.0그 밖의 대규모점포203005.088002445311.309961대규모점포
63220000200132200830750000419870202<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 51031140.0<NA>서울특별시 강남구 논현동 105번지 7호서울특별시 강남구 언주로 726 (논현동, 두산빌딩)135714두산아케이드2013-12-30 13:52:36I2018-08-31 23:59:59.0그 밖의 대규모점포203050.78389446316.514036대규모점포
73220000200132200830750000519790410<NA>2휴업2휴업처리<NA><NA><NA><NA>02 5492233<NA><NA>서울특별시 강남구 압구정동 456호<NA><NA>금강상가2007-07-14 10:53:01I2018-08-31 23:59:59.0그 밖의 대규모점포202485.226491447521.520319<NA>
83220000200132200830750000619760807<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 54235162059.0<NA>서울특별시 강남구 압구정동 454호서울특별시 강남구 압구정로29길 72-1 (압구정동)135903신사상가2015-04-15 18:56:47I2018-08-31 23:59:59.0그 밖의 대규모점포202440.338882447782.513227대규모점포
9322000020013220083075000071985-07-08<NA>1영업/정상1정상영업<NA><NA><NA><NA>023449440610250.0<NA>서울특별시 강남구 압구정동 515호서울특별시 강남구 압구정로 407 (압구정동, 갤러리아백화점)135-902갤러리아백화점(동관)2023-03-28 11:23:26U2022-12-02 21:00:00.0백화점203604.761652447316.222786<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
61322000020143220162075000082012-07-02<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3446-5602294.9<NA><NA>서울특별시 강남구 봉은사로103길 5 (삼성동)135-873롯데슈퍼 코엑스점2023-05-09 15:26:03U2022-12-04 22:06:00.0구분없음205359.898727445864.805913<NA>
623220000201432201620750000920120702<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-547-5601503.8<NA><NA>서울특별시 강남구 언주로 123 (도곡동, 개포한신아파트)135855롯데슈퍼 도곡점2014-07-04 17:19:23I2018-08-31 23:59:59.0구분없음204254.782969442744.847671준대규모점포
633220000201432201620750001020140916<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2156510.88135011서울특별시 강남구 논현동 140번지서울특별시 강남구 강남대로128길 128-20, 1층 101,104,106호 (논현동, 영동프라자)135011(주)지에스리테일 GS슈퍼 강남 논현점2016-02-23 09:53:20I2018-08-31 23:59:59.0구분없음202023.395228445302.915908준대규모점포
643220000201432201620750001120141125<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-551-070513667.0<NA><NA>서울특별시 강남구 테헤란로87길 22-0 (삼성동)135728도심공항몰(CALT MALL)2019-04-11 14:04:06U2019-04-13 02:40:00.0쇼핑센터205170.959717445264.936337대규모점포
653220000201532201620750000120151211<NA>1영업/정상1정상영업<NA><NA><NA><NA>02)3446-71335155.7<NA><NA>서울특별시 강남구 강남대로 432 (역삼동, 점프밀라노)06129점프밀라노2022-02-15 15:34:37U2022-02-17 02:40:00.0그 밖의 대규모점포202296.996028444335.013666대규모점포
663220000201632201620750000120161229<NA>1영업/정상1정상영업<NA><NA><NA><NA>023809461358.71<NA><NA>서울특별시 강남구 삼성로 633, 1층 (삼성동, 삼광빌딩)06091노브랜드 삼성점2017-06-01 09:33:03I2018-08-31 23:59:59.0구분없음204447.069004446008.542809준대규모점포
673220000201832201620750000120180803<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-9461677.2135825서울특별시 강남구 논현동 164번지 5호 외 3필지<NA><NA>삐에로쇼핑 강남논현점2018-12-27 10:53:42U2018-12-29 02:40:00.0구분없음201994.292034445091.876704준대규모점포
683220000202132202490750000120210319<NA>1영업/정상5영업개시전<NA><NA><NA><NA>-7511.51<NA>서울특별시 강남구 역삼동 676 센터필드서울특별시 강남구 테헤란로 231, 센터필드 (역삼동)06142더 샵스 앳 센터필드 (THE SHOPS AT CENTERFIELD)2021-03-22 19:43:27U2021-03-24 02:40:00.0그 밖의 대규모점포203599.062772444556.062267대규모점포
693220000202232202490750000120220412<NA>1영업/정상1정상영업<NA><NA><NA><NA>023805042794.7<NA>서울특별시 강남구 신사동 510-11 강남상가아파트서울특별시 강남구 압구정로2길 46, 1층 (신사동, ---------)06034이마트에브리데이 강남시장점2022-04-26 10:07:26U2021-12-03 22:08:00.0구분없음201757.494099446282.454467<NA>
703220000202232202490750000220220915<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 2006-2678198.0<NA>서울특별시 강남구 신사동 638-6서울특별시 강남구 압구정로 312, 신사동동 1층 (신사동)06017GS THE FRESH 압구정점2022-09-15 18:50:39I2021-12-08 23:07:00.0구분없음203069.441212447391.130408<NA>