Overview

Dataset statistics

Number of variables26
Number of observations10000
Missing cells85264
Missing cells (%)32.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory224.0 B

Variable types

Numeric3
Text9
Unsupported4
Categorical5
DateTime5

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),영업내용
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16060/S/1/datasetView.do

Alerts

상세영업상태코드 is highly imbalanced (68.8%)Imbalance
상세영업상태명 is highly imbalanced (66.8%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 3011 (30.1%) missing valuesMissing
휴업시작일자 has 9834 (98.3%) missing valuesMissing
휴업종료일자 has 9838 (98.4%) missing valuesMissing
재개업일자 has 9974 (99.7%) missing valuesMissing
전화번호 has 2409 (24.1%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 10000 (100.0%) missing valuesMissing
지번주소 has 108 (1.1%) missing valuesMissing
도로명주소 has 863 (8.6%) missing valuesMissing
도로명우편번호 has 6664 (66.6%) missing valuesMissing
업태구분명 has 10000 (100.0%) missing valuesMissing
좌표정보(X) has 550 (5.5%) missing valuesMissing
좌표정보(Y) has 550 (5.5%) missing valuesMissing
영업내용 has 1463 (14.6%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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
소재지우편번호 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

Reproduction

Analysis started2024-04-17 20:29:36.444452
Analysis finished2024-04-17 20:29:38.295596
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3141275
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T05:29:38.342711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13070000
median3160000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)140000

Descriptive statistics

Standard deviation78002.903
Coefficient of variation (CV)0.024831606
Kurtosis-1.177973
Mean3141275
Median Absolute Deviation (MAD)60000
Skewness-0.50708037
Sum3.141275 × 1010
Variance6.0844528 × 109
MonotonicityNot monotonic
2024-04-18T05:29:38.443272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3210000 1211
 
12.1%
3220000 1092
 
10.9%
3010000 718
 
7.2%
3180000 702
 
7.0%
3230000 692
 
6.9%
3130000 596
 
6.0%
3030000 389
 
3.9%
3170000 362
 
3.6%
3160000 361
 
3.6%
3000000 354
 
3.5%
Other values (15) 3523
35.2%
ValueCountFrequency (%)
3000000 354
3.5%
3010000 718
7.2%
3020000 210
 
2.1%
3030000 389
3.9%
3040000 261
 
2.6%
3050000 222
 
2.2%
3060000 324
3.2%
3070000 137
 
1.4%
3080000 187
 
1.9%
3090000 112
 
1.1%
ValueCountFrequency (%)
3240000 329
 
3.3%
3230000 692
6.9%
3220000 1092
10.9%
3210000 1211
12.1%
3200000 331
 
3.3%
3190000 245
 
2.5%
3180000 702
7.0%
3170000 362
 
3.6%
3160000 361
 
3.6%
3150000 297
 
3.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T05:29:38.602314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters190000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row2011323021108500003
2nd row2004318008508200022
3rd row2017308017408500001
4th row2001320002408200073
5th row2005321007808200008
ValueCountFrequency (%)
2011323021108500003 1
 
< 0.1%
2010322010408500017 1
 
< 0.1%
2005322010408200029 1
 
< 0.1%
2014320014708500002 1
 
< 0.1%
2014300014908500005 1
 
< 0.1%
2009313013708500014 1
 
< 0.1%
2002310009708111124 1
 
< 0.1%
2001323014008500413 1
 
< 0.1%
1989321007808200010 1
 
< 0.1%
2003313013408500541 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-18T05:29:38.886832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 74728
39.3%
1 23212
 
12.2%
2 22703
 
11.9%
3 16559
 
8.7%
8 16247
 
8.6%
5 10700
 
5.6%
9 8856
 
4.7%
4 6705
 
3.5%
7 6141
 
3.2%
6 4146
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189997
> 99.9%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 74728
39.3%
1 23212
 
12.2%
2 22703
 
11.9%
3 16559
 
8.7%
8 16247
 
8.6%
5 10700
 
5.6%
9 8856
 
4.7%
4 6705
 
3.5%
7 6141
 
3.2%
6 4146
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 74728
39.3%
1 23212
 
12.2%
2 22703
 
11.9%
3 16559
 
8.7%
8 16247
 
8.6%
5 10700
 
5.6%
9 8856
 
4.7%
4 6705
 
3.5%
7 6141
 
3.2%
6 4146
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 74728
39.3%
1 23212
 
12.2%
2 22703
 
11.9%
3 16559
 
8.7%
8 16247
 
8.6%
5 10700
 
5.6%
9 8856
 
4.7%
4 6705
 
3.5%
7 6141
 
3.2%
6 4146
 
2.2%
Distinct5526
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T05:29:39.118635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1458
Min length8

Characters and Unicode

Total characters81458
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3189 ?
Unique (%)31.9%

Sample

1st row20130820
2nd row20040709
3rd row20170727
4th row19880831
5th row20050131
ValueCountFrequency (%)
19880708 44
 
0.4%
19980801 30
 
0.3%
20121109 24
 
0.2%
19920831 24
 
0.2%
19910724 24
 
0.2%
20150807 24
 
0.2%
20080429 23
 
0.2%
19920420 23
 
0.2%
19960517 19
 
0.2%
19880714 19
 
0.2%
Other values (5516) 9746
97.5%
2024-04-18T05:29:39.447946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24273
29.8%
1 14702
18.0%
2 14423
17.7%
9 8483
 
10.4%
3 3423
 
4.2%
8 3308
 
4.1%
7 2908
 
3.6%
6 2870
 
3.5%
4 2857
 
3.5%
5 2752
 
3.4%
Other values (2) 1459
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79999
98.2%
Dash Punctuation 1458
 
1.8%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24273
30.3%
1 14702
18.4%
2 14423
18.0%
9 8483
 
10.6%
3 3423
 
4.3%
8 3308
 
4.1%
7 2908
 
3.6%
6 2870
 
3.6%
4 2857
 
3.6%
5 2752
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 1458
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24273
29.8%
1 14702
18.0%
2 14423
17.7%
9 8483
 
10.4%
3 3423
 
4.2%
8 3308
 
4.1%
7 2908
 
3.6%
6 2870
 
3.5%
4 2857
 
3.5%
5 2752
 
3.4%
Other values (2) 1459
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24273
29.8%
1 14702
18.0%
2 14423
17.7%
9 8483
 
10.4%
3 3423
 
4.2%
8 3308
 
4.1%
7 2908
 
3.6%
6 2870
 
3.5%
4 2857
 
3.5%
5 2752
 
3.4%
Other values (2) 1459
 
1.8%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7310 
1
2296 
4
 
309
2
 
85

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7310
73.1%
1 2296
 
23.0%
4 309
 
3.1%
2 85
 
0.9%

Length

2024-04-18T05:29:39.553319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:29:39.623132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7310
73.1%
1 2296
 
23.0%
4 309
 
3.1%
2 85
 
0.9%

영업상태명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7310 
영업/정상
2296 
취소/말소/만료/정지/중지
 
309
휴업
 
85

Length

Max length14
Median length2
Mean length3.0596
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7310
73.1%
영업/정상 2296
 
23.0%
취소/말소/만료/정지/중지 309
 
3.1%
휴업 85
 
0.9%

Length

2024-04-18T05:29:39.703905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:29:39.778580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7310
73.1%
영업/정상 2296
 
23.0%
취소/말소/만료/정지/중지 309
 
3.1%
휴업 85
 
0.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
40
7310 
20
2126 
70
 
297
01
 
99
30
 
85
Other values (8)
 
83

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row40
2nd row40
3rd row40
4th row01
5th row40

Common Values

ValueCountFrequency (%)
40 7310
73.1%
20 2126
 
21.3%
70 297
 
3.0%
01 99
 
1.0%
30 85
 
0.9%
90 31
 
0.3%
10 28
 
0.3%
50 8
 
0.1%
99 6
 
0.1%
% 6
 
0.1%
Other values (3) 4
 
< 0.1%

Length

2024-04-18T05:29:39.863578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
40 7310
73.1%
20 2126
 
21.3%
70 297
 
3.0%
01 99
 
1.0%
30 85
 
0.9%
90 31
 
0.3%
10 28
 
0.3%
50 8
 
0.1%
99 6
 
0.1%
6
 
0.1%
Other values (3) 4
 
< 0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7310 
정상
2126 
취소
 
297
<NA>
 
111
휴업
 
85
Other values (6)
 
71

Length

Max length9
Median length2
Mean length2.0381
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7310
73.1%
정상 2126
 
21.3%
취소 297
 
3.0%
<NA> 111
 
1.1%
휴업 85
 
0.9%
등록신청 31
 
0.3%
설립신청 28
 
0.3%
영업정지 8
 
0.1%
신청취소(반려) 2
 
< 0.1%
신청취소(취하) 1
 
< 0.1%

Length

2024-04-18T05:29:39.951928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐업 7310
73.1%
정상 2126
 
21.3%
취소 297
 
3.0%
na 111
 
1.1%
휴업 85
 
0.9%
등록신청 31
 
0.3%
설립신청 28
 
0.3%
영업정지 8
 
0.1%
신청취소(반려 2
 
< 0.1%
신청취소(취하 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct3127
Distinct (%)44.7%
Missing3011
Missing (%)30.1%
Memory size156.2 KiB
Minimum1991-06-22 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T05:29:40.055782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:29:40.162498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct143
Distinct (%)86.1%
Missing9834
Missing (%)98.3%
Memory size156.2 KiB
Minimum1998-10-26 00:00:00
Maximum2024-03-21 00:00:00
2024-04-18T05:29:40.268738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:29:40.370163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Text

MISSING 

Distinct135
Distinct (%)83.3%
Missing9838
Missing (%)98.4%
Memory size156.2 KiB
2024-04-18T05:29:40.586130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3333333
Min length8

Characters and Unicode

Total characters1350
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

Unique118 ?
Unique (%)72.8%

Sample

1st row20090420
2nd row2009-11-18
3rd row9999-12-31
4th row2024-11-26
5th row20080312
ValueCountFrequency (%)
19981231 7
 
4.3%
20211231 3
 
1.9%
9999-12-31 3
 
1.9%
20151231 3
 
1.9%
20221231 3
 
1.9%
20111231 3
 
1.9%
20081231 2
 
1.2%
20150217 2
 
1.2%
20061207 2
 
1.2%
20181231 2
 
1.2%
Other values (125) 132
81.5%
2024-04-18T05:29:40.915425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 346
25.6%
2 341
25.3%
1 249
18.4%
3 122
 
9.0%
9 63
 
4.7%
- 54
 
4.0%
6 47
 
3.5%
4 36
 
2.7%
5 34
 
2.5%
8 30
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1296
96.0%
Dash Punctuation 54
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 346
26.7%
2 341
26.3%
1 249
19.2%
3 122
 
9.4%
9 63
 
4.9%
6 47
 
3.6%
4 36
 
2.8%
5 34
 
2.6%
8 30
 
2.3%
7 28
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 346
25.6%
2 341
25.3%
1 249
18.4%
3 122
 
9.0%
9 63
 
4.7%
- 54
 
4.0%
6 47
 
3.5%
4 36
 
2.7%
5 34
 
2.5%
8 30
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 346
25.6%
2 341
25.3%
1 249
18.4%
3 122
 
9.0%
9 63
 
4.7%
- 54
 
4.0%
6 47
 
3.5%
4 36
 
2.7%
5 34
 
2.5%
8 30
 
2.2%

재개업일자
Date

MISSING 

Distinct24
Distinct (%)92.3%
Missing9974
Missing (%)99.7%
Memory size156.2 KiB
Minimum2005-10-31 00:00:00
Maximum2023-11-22 00:00:00
2024-04-18T05:29:41.015718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:29:41.093954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

전화번호
Text

MISSING 

Distinct6868
Distinct (%)90.5%
Missing2409
Missing (%)24.1%
Memory size156.2 KiB
2024-04-18T05:29:41.378656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.492425
Min length2

Characters and Unicode

Total characters79648
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6359 ?
Unique (%)83.8%

Sample

1st row02 26794282
2nd row02 713 4040
3rd row023946116
4th row0220009744
5th row02 5870104
ValueCountFrequency (%)
02 4827
32.6%
0000 56
 
0.4%
000 56
 
0.4%
070 38
 
0.3%
02-000-0000 37
 
0.2%
421 21
 
0.1%
358 20
 
0.1%
031 18
 
0.1%
585 18
 
0.1%
521 18
 
0.1%
Other values (7118) 9698
65.5%
2024-04-18T05:29:41.769869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13346
16.8%
0 12407
15.6%
10507
13.2%
4 6051
7.6%
3 6029
7.6%
5 5886
7.4%
7 5709
7.2%
6 5044
 
6.3%
1 4983
 
6.3%
8 4866
 
6.1%
Other values (2) 4820
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68382
85.9%
Space Separator 10507
 
13.2%
Dash Punctuation 759
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13346
19.5%
0 12407
18.1%
4 6051
8.8%
3 6029
8.8%
5 5886
8.6%
7 5709
8.3%
6 5044
 
7.4%
1 4983
 
7.3%
8 4866
 
7.1%
9 4061
 
5.9%
Space Separator
ValueCountFrequency (%)
10507
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 759
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13346
16.8%
0 12407
15.6%
10507
13.2%
4 6051
7.6%
3 6029
7.6%
5 5886
7.4%
7 5709
7.2%
6 5044
 
6.3%
1 4983
 
6.3%
8 4866
 
6.1%
Other values (2) 4820
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13346
16.8%
0 12407
15.6%
10507
13.2%
4 6051
7.6%
3 6029
7.6%
5 5886
7.4%
7 5709
7.2%
6 5044
 
6.3%
1 4983
 
6.3%
8 4866
 
6.1%
Other values (2) 4820
 
6.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

지번주소
Text

MISSING 

Distinct5626
Distinct (%)56.9%
Missing108
Missing (%)1.1%
Memory size156.2 KiB
2024-04-18T05:29:42.073857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length26.870501
Min length9

Characters and Unicode

Total characters265803
Distinct characters593
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4451 ?
Unique (%)45.0%

Sample

1st row서울특별시 송파구 가락동 ***-**번지
2nd row서울특별시 영등포구 양평동*가 ***번지
3rd row서울특별시 강북구 수유동 ***-**
4th row서울특별시 관악구 봉천동 ***-** 번지
5th row서울특별시 서초구 방배동 ***-*번지 남일예당빌딩*층
ValueCountFrequency (%)
서울특별시 9873
19.7%
번지 7739
 
15.4%
3125
 
6.2%
2033
 
4.1%
통*반 1782
 
3.6%
1208
 
2.4%
서초구 1204
 
2.4%
강남구 1079
 
2.2%
중구 711
 
1.4%
영등포구 692
 
1.4%
Other values (3033) 20739
41.3%
2024-04-18T05:29:42.489666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 56309
21.2%
47730
18.0%
12262
 
4.6%
11721
 
4.4%
10577
 
4.0%
10064
 
3.8%
9907
 
3.7%
9877
 
3.7%
9873
 
3.7%
- 8872
 
3.3%
Other values (583) 78611
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150265
56.5%
Other Punctuation 56787
 
21.4%
Space Separator 47730
 
18.0%
Dash Punctuation 8872
 
3.3%
Decimal Number 712
 
0.3%
Uppercase Letter 638
 
0.2%
Connector Punctuation 288
 
0.1%
Open Punctuation 197
 
0.1%
Close Punctuation 197
 
0.1%
Lowercase Letter 102
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12262
 
8.2%
11721
 
7.8%
10577
 
7.0%
10064
 
6.7%
9907
 
6.6%
9877
 
6.6%
9873
 
6.6%
8151
 
5.4%
7817
 
5.2%
2563
 
1.7%
Other values (514) 57453
38.2%
Uppercase Letter
ValueCountFrequency (%)
B 144
22.6%
A 71
11.1%
C 42
 
6.6%
S 41
 
6.4%
K 38
 
6.0%
T 32
 
5.0%
D 31
 
4.9%
M 27
 
4.2%
I 25
 
3.9%
E 25
 
3.9%
Other values (15) 162
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 20
19.6%
r 14
13.7%
o 10
9.8%
l 8
 
7.8%
t 8
 
7.8%
w 7
 
6.9%
n 7
 
6.9%
a 5
 
4.9%
i 4
 
3.9%
b 4
 
3.9%
Other values (8) 15
14.7%
Decimal Number
ValueCountFrequency (%)
1 148
20.8%
2 91
12.8%
0 77
10.8%
3 74
10.4%
5 68
9.6%
4 65
9.1%
7 59
 
8.3%
6 53
 
7.4%
9 39
 
5.5%
8 38
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 56309
99.2%
. 392
 
0.7%
, 64
 
0.1%
/ 14
 
< 0.1%
& 6
 
< 0.1%
: 1
 
< 0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
5
71.4%
1
 
14.3%
1
 
14.3%
Space Separator
ValueCountFrequency (%)
47730
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8872
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 288
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150265
56.5%
Common 114791
43.2%
Latin 747
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12262
 
8.2%
11721
 
7.8%
10577
 
7.0%
10064
 
6.7%
9907
 
6.6%
9877
 
6.6%
9873
 
6.6%
8151
 
5.4%
7817
 
5.2%
2563
 
1.7%
Other values (514) 57453
38.2%
Latin
ValueCountFrequency (%)
B 144
19.3%
A 71
 
9.5%
C 42
 
5.6%
S 41
 
5.5%
K 38
 
5.1%
T 32
 
4.3%
D 31
 
4.1%
M 27
 
3.6%
I 25
 
3.3%
E 25
 
3.3%
Other values (36) 271
36.3%
Common
ValueCountFrequency (%)
* 56309
49.1%
47730
41.6%
- 8872
 
7.7%
. 392
 
0.3%
_ 288
 
0.3%
( 197
 
0.2%
) 197
 
0.2%
1 148
 
0.1%
2 91
 
0.1%
0 77
 
0.1%
Other values (13) 490
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150265
56.5%
ASCII 115531
43.5%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 56309
48.7%
47730
41.3%
- 8872
 
7.7%
. 392
 
0.3%
_ 288
 
0.2%
( 197
 
0.2%
) 197
 
0.2%
1 148
 
0.1%
B 144
 
0.1%
2 91
 
0.1%
Other values (56) 1163
 
1.0%
Hangul
ValueCountFrequency (%)
12262
 
8.2%
11721
 
7.8%
10577
 
7.0%
10064
 
6.7%
9907
 
6.6%
9877
 
6.6%
9873
 
6.6%
8151
 
5.4%
7817
 
5.2%
2563
 
1.7%
Other values (514) 57453
38.2%
Number Forms
ValueCountFrequency (%)
5
71.4%
1
 
14.3%
1
 
14.3%

도로명주소
Text

MISSING 

Distinct7159
Distinct (%)78.4%
Missing863
Missing (%)8.6%
Memory size156.2 KiB
2024-04-18T05:29:42.716408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length54
Mean length30.698588
Min length16

Characters and Unicode

Total characters280493
Distinct characters621
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6064 ?
Unique (%)66.4%

Sample

1st row서울특별시 송파구 문정로**길 ** (가락동)
2nd row서울특별시 영등포구 선유로**길 ** (양평동*가, 신한하이빌)
3rd row서울특별시 강북구 인수봉로 *** (수유동)
4th row서울특별시 서초구 동광로 **-* (방배동,남일예당빌딩*층)
5th row서울특별시 영등포구 당산로**길 **-* (당산동*가)
ValueCountFrequency (%)
9230
 
17.7%
서울특별시 9126
 
17.5%
2260
 
4.3%
1213
 
2.3%
서초구 1160
 
2.2%
강남구 1057
 
2.0%
송파구 661
 
1.3%
영등포구 642
 
1.2%
615
 
1.2%
중구 599
 
1.1%
Other values (4870) 25686
49.2%
2024-04-18T05:29:43.331964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47279
16.9%
* 42995
 
15.3%
11859
 
4.2%
11590
 
4.1%
10203
 
3.6%
9913
 
3.5%
9430
 
3.4%
( 9294
 
3.3%
) 9294
 
3.3%
9183
 
3.3%
Other values (611) 109453
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161460
57.6%
Other Punctuation 49924
 
17.8%
Space Separator 47279
 
16.9%
Open Punctuation 9294
 
3.3%
Close Punctuation 9294
 
3.3%
Dash Punctuation 1428
 
0.5%
Uppercase Letter 727
 
0.3%
Decimal Number 671
 
0.2%
Connector Punctuation 267
 
0.1%
Lowercase Letter 126
 
< 0.1%
Other values (2) 23
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11859
 
7.3%
11590
 
7.2%
10203
 
6.3%
9913
 
6.1%
9430
 
5.8%
9183
 
5.7%
9131
 
5.7%
9126
 
5.7%
4918
 
3.0%
2982
 
1.8%
Other values (540) 73125
45.3%
Uppercase Letter
ValueCountFrequency (%)
B 169
23.2%
A 84
11.6%
S 51
 
7.0%
K 46
 
6.3%
C 43
 
5.9%
T 37
 
5.1%
D 34
 
4.7%
E 29
 
4.0%
I 28
 
3.9%
M 27
 
3.7%
Other values (15) 179
24.6%
Lowercase Letter
ValueCountFrequency (%)
e 27
21.4%
r 17
13.5%
o 12
9.5%
t 10
 
7.9%
n 9
 
7.1%
w 8
 
6.3%
l 8
 
6.3%
c 5
 
4.0%
a 5
 
4.0%
i 4
 
3.2%
Other values (10) 21
16.7%
Decimal Number
ValueCountFrequency (%)
1 150
22.4%
2 106
15.8%
3 83
12.4%
0 68
10.1%
4 60
 
8.9%
5 56
 
8.3%
6 56
 
8.3%
7 43
 
6.4%
8 27
 
4.0%
9 22
 
3.3%
Other Punctuation
ValueCountFrequency (%)
* 42995
86.1%
, 6610
 
13.2%
. 296
 
0.6%
/ 14
 
< 0.1%
& 7
 
< 0.1%
@ 1
 
< 0.1%
: 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
6
75.0%
1
 
12.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
47279
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9294
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1428
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 267
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161460
57.6%
Common 118172
42.1%
Latin 861
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11859
 
7.3%
11590
 
7.2%
10203
 
6.3%
9913
 
6.1%
9430
 
5.8%
9183
 
5.7%
9131
 
5.7%
9126
 
5.7%
4918
 
3.0%
2982
 
1.8%
Other values (540) 73125
45.3%
Latin
ValueCountFrequency (%)
B 169
19.6%
A 84
 
9.8%
S 51
 
5.9%
K 46
 
5.3%
C 43
 
5.0%
T 37
 
4.3%
D 34
 
3.9%
E 29
 
3.4%
I 28
 
3.3%
e 27
 
3.1%
Other values (38) 313
36.4%
Common
ValueCountFrequency (%)
47279
40.0%
* 42995
36.4%
( 9294
 
7.9%
) 9294
 
7.9%
, 6610
 
5.6%
- 1428
 
1.2%
. 296
 
0.3%
_ 267
 
0.2%
1 150
 
0.1%
2 106
 
0.1%
Other values (13) 453
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161460
57.6%
ASCII 119025
42.4%
Number Forms 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47279
39.7%
* 42995
36.1%
( 9294
 
7.8%
) 9294
 
7.8%
, 6610
 
5.6%
- 1428
 
1.2%
. 296
 
0.2%
_ 267
 
0.2%
B 169
 
0.1%
1 150
 
0.1%
Other values (58) 1243
 
1.0%
Hangul
ValueCountFrequency (%)
11859
 
7.3%
11590
 
7.2%
10203
 
6.3%
9913
 
6.1%
9430
 
5.8%
9183
 
5.7%
9131
 
5.7%
9126
 
5.7%
4918
 
3.0%
2982
 
1.8%
Other values (540) 73125
45.3%
Number Forms
ValueCountFrequency (%)
6
75.0%
1
 
12.5%
1
 
12.5%

도로명우편번호
Text

MISSING 

Distinct2101
Distinct (%)63.0%
Missing6664
Missing (%)66.6%
Memory size156.2 KiB
2024-04-18T05:29:43.595674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3297362
Min length5

Characters and Unicode

Total characters17780
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

Unique1428 ?
Unique (%)42.8%

Sample

1st row07206
2nd row01024
3rd row07266
4th row04319
5th row132854
ValueCountFrequency (%)
05854 16
 
0.5%
04793 14
 
0.4%
153803 13
 
0.4%
04410 11
 
0.3%
153801 11
 
0.3%
05836 11
 
0.3%
08501 11
 
0.3%
08503 11
 
0.3%
08504 10
 
0.3%
03192 10
 
0.3%
Other values (2091) 3218
96.5%
2024-04-18T05:29:43.982943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3725
21.0%
1 2321
13.1%
3 1833
10.3%
5 1684
9.5%
8 1664
9.4%
4 1521
8.6%
6 1386
 
7.8%
2 1360
 
7.6%
7 1356
 
7.6%
9 872
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17722
99.7%
Dash Punctuation 58
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3725
21.0%
1 2321
13.1%
3 1833
10.3%
5 1684
9.5%
8 1664
9.4%
4 1521
8.6%
6 1386
 
7.8%
2 1360
 
7.7%
7 1356
 
7.7%
9 872
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17780
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3725
21.0%
1 2321
13.1%
3 1833
10.3%
5 1684
9.5%
8 1664
9.4%
4 1521
8.6%
6 1386
 
7.8%
2 1360
 
7.6%
7 1356
 
7.6%
9 872
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3725
21.0%
1 2321
13.1%
3 1833
10.3%
5 1684
9.5%
8 1664
9.4%
4 1521
8.6%
6 1386
 
7.8%
2 1360
 
7.6%
7 1356
 
7.6%
9 872
 
4.9%
Distinct7723
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-18T05:29:44.246249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length6.1835
Min length1

Characters and Unicode

Total characters61835
Distinct characters769
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6324 ?
Unique (%)63.2%

Sample

1st row성림B2BC
2nd row한비콤
3rd row(주)모스테크
4th row삼성공사
5th row홍익애이디넷(주)
ValueCountFrequency (%)
주식회사 368
 
3.4%
디자인 66
 
0.6%
50
 
0.5%
기획 24
 
0.2%
광고 19
 
0.2%
서울광고 19
 
0.2%
현대광고 18
 
0.2%
제일광고 16
 
0.1%
미래광고 15
 
0.1%
애드 14
 
0.1%
Other values (7874) 10365
94.5%
2024-04-18T05:29:44.618063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3706
 
6.0%
) 3241
 
5.2%
( 3211
 
5.2%
2003
 
3.2%
1844
 
3.0%
1833
 
3.0%
1690
 
2.7%
1654
 
2.7%
1621
 
2.6%
1461
 
2.4%
Other values (759) 39571
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53016
85.7%
Close Punctuation 3241
 
5.2%
Open Punctuation 3211
 
5.2%
Space Separator 986
 
1.6%
Uppercase Letter 814
 
1.3%
Lowercase Letter 239
 
0.4%
Decimal Number 181
 
0.3%
Other Punctuation 78
 
0.1%
Dash Punctuation 61
 
0.1%
Other Symbol 5
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3706
 
7.0%
2003
 
3.8%
1844
 
3.5%
1833
 
3.5%
1690
 
3.2%
1654
 
3.1%
1621
 
3.1%
1461
 
2.8%
1408
 
2.7%
1320
 
2.5%
Other values (688) 34476
65.0%
Uppercase Letter
ValueCountFrequency (%)
S 98
12.0%
I 74
 
9.1%
C 64
 
7.9%
M 63
 
7.7%
N 54
 
6.6%
G 52
 
6.4%
D 49
 
6.0%
T 46
 
5.7%
E 41
 
5.0%
A 41
 
5.0%
Other values (15) 232
28.5%
Lowercase Letter
ValueCountFrequency (%)
o 27
11.3%
c 23
9.6%
e 22
 
9.2%
n 20
 
8.4%
i 19
 
7.9%
a 19
 
7.9%
m 16
 
6.7%
s 15
 
6.3%
g 12
 
5.0%
t 10
 
4.2%
Other values (13) 56
23.4%
Decimal Number
ValueCountFrequency (%)
2 52
28.7%
0 41
22.7%
1 39
21.5%
3 17
 
9.4%
4 8
 
4.4%
7 7
 
3.9%
8 6
 
3.3%
5 4
 
2.2%
9 4
 
2.2%
6 3
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 43
55.1%
& 22
28.2%
, 7
 
9.0%
3
 
3.8%
? 2
 
2.6%
* 1
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 3241
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3211
100.0%
Space Separator
ValueCountFrequency (%)
986
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53021
85.7%
Common 7761
 
12.6%
Latin 1053
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3706
 
7.0%
2003
 
3.8%
1844
 
3.5%
1833
 
3.5%
1690
 
3.2%
1654
 
3.1%
1621
 
3.1%
1461
 
2.8%
1408
 
2.7%
1320
 
2.5%
Other values (689) 34481
65.0%
Latin
ValueCountFrequency (%)
S 98
 
9.3%
I 74
 
7.0%
C 64
 
6.1%
M 63
 
6.0%
N 54
 
5.1%
G 52
 
4.9%
D 49
 
4.7%
T 46
 
4.4%
E 41
 
3.9%
A 41
 
3.9%
Other values (38) 471
44.7%
Common
ValueCountFrequency (%)
) 3241
41.8%
( 3211
41.4%
986
 
12.7%
- 61
 
0.8%
2 52
 
0.7%
. 43
 
0.6%
0 41
 
0.5%
1 39
 
0.5%
& 22
 
0.3%
3 17
 
0.2%
Other values (12) 48
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53014
85.7%
ASCII 8811
 
14.2%
None 8
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3706
 
7.0%
2003
 
3.8%
1844
 
3.5%
1833
 
3.5%
1690
 
3.2%
1654
 
3.1%
1621
 
3.1%
1461
 
2.8%
1408
 
2.7%
1320
 
2.5%
Other values (687) 34474
65.0%
ASCII
ValueCountFrequency (%)
) 3241
36.8%
( 3211
36.4%
986
 
11.2%
S 98
 
1.1%
I 74
 
0.8%
C 64
 
0.7%
M 63
 
0.7%
- 61
 
0.7%
N 54
 
0.6%
2 52
 
0.6%
Other values (59) 907
 
10.3%
None
ValueCountFrequency (%)
5
62.5%
3
37.5%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Distinct8414
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2024-04-16 20:44:28
2024-04-18T05:29:44.740358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:29:44.845827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7458 
U
2542 

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 7458
74.6%
U 2542
 
25.4%

Length

2024-04-18T05:29:44.943970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T05:29:45.010074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7458
74.6%
u 2542
 
25.4%
Distinct1084
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-18T05:29:45.096672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T05:29:45.201029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7525
Distinct (%)79.6%
Missing550
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean199551.03
Minimum178637.1
Maximum230326.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T05:29:45.305554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum178637.1
5-th percentile187839.4
Q1193096.23
median200859.29
Q3204372.9
95-th percentile210931.42
Maximum230326.31
Range51689.21
Interquartile range (IQR)11276.674

Descriptive statistics

Standard deviation7032.5878
Coefficient of variation (CV)0.035242053
Kurtosis-0.7795772
Mean199551.03
Median Absolute Deviation (MAD)5408.6153
Skewness-0.15211781
Sum1.8857572 × 109
Variance49457291
MonotonicityNot monotonic
2024-04-18T05:29:45.412839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191226.287379467 23
 
0.2%
201184.994931613 15
 
0.1%
202803.137561335 13
 
0.1%
201288.890133376 12
 
0.1%
188840.515865617 11
 
0.1%
200554.74395758 11
 
0.1%
193282.654266684 9
 
0.1%
202481.661169413 8
 
0.1%
198991.002784609 8
 
0.1%
203931.098064589 8
 
0.1%
Other values (7515) 9332
93.3%
(Missing) 550
 
5.5%
ValueCountFrequency (%)
178637.097769416 1
< 0.1%
181539.508264155 1
< 0.1%
182849.273281599 1
< 0.1%
182857.528466005 1
< 0.1%
182897.251870492 1
< 0.1%
182914.770762913 1
< 0.1%
182944.648231601 1
< 0.1%
182962.037203619 2
< 0.1%
182965.91468667 1
< 0.1%
182970.965516527 1
< 0.1%
ValueCountFrequency (%)
230326.307767 1
< 0.1%
218294.566609634 1
< 0.1%
217068.0 1
< 0.1%
215795.324533638 1
< 0.1%
215289.815449411 1
< 0.1%
215230.899404859 2
< 0.1%
215129.842193761 1
< 0.1%
215031.497171478 1
< 0.1%
215014.832595077 1
< 0.1%
214996.673945552 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7525
Distinct (%)79.6%
Missing550
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean447926.09
Minimum313897.18
Maximum476215.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-18T05:29:45.521276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum313897.18
5-th percentile441410.49
Q1443775.57
median447247.61
Q3451267.81
95-th percentile457320.78
Maximum476215.93
Range162318.74
Interquartile range (IQR)7492.2357

Descriptive statistics

Standard deviation5284.3882
Coefficient of variation (CV)0.011797456
Kurtosis43.602119
Mean447926.09
Median Absolute Deviation (MAD)3781.047
Skewness-1.1223483
Sum4.2329015 × 109
Variance27924758
MonotonicityNot monotonic
2024-04-18T05:29:45.641094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
437914.06299827 23
 
0.2%
442857.184989612 15
 
0.1%
443189.823482655 13
 
0.1%
442555.172193254 12
 
0.1%
444306.771104527 11
 
0.1%
444811.364826199 11
 
0.1%
447611.552045596 9
 
0.1%
442563.269271521 8
 
0.1%
451828.222399025 8
 
0.1%
444622.849264371 8
 
0.1%
Other values (7515) 9332
93.3%
(Missing) 550
 
5.5%
ValueCountFrequency (%)
313897.182607 1
 
< 0.1%
427922.324956665 1
 
< 0.1%
430985.004432136 1
 
< 0.1%
433767.565586245 1
 
< 0.1%
436660.024212789 1
 
< 0.1%
436962.340703645 1
 
< 0.1%
437280.574150819 4
< 0.1%
437626.290843064 2
< 0.1%
437753.206548839 1
 
< 0.1%
437811.811502379 1
 
< 0.1%
ValueCountFrequency (%)
476215.925309934 1
< 0.1%
474844.558950194 1
< 0.1%
466323.429501096 1
< 0.1%
465211.202003065 1
< 0.1%
464817.533653989 1
< 0.1%
464791.987958352 1
< 0.1%
464731.761130542 1
< 0.1%
464632.362897673 1
< 0.1%
464598.721765819 1
< 0.1%
464430.901378806 1
< 0.1%

영업내용
Text

MISSING 

Distinct1398
Distinct (%)16.4%
Missing1463
Missing (%)14.6%
Memory size156.2 KiB
2024-04-18T05:29:45.874593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length7.8480731
Min length1

Characters and Unicode

Total characters66999
Distinct characters348
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1073 ?
Unique (%)12.6%

Sample

1st row옥외광고업
2nd row광고물제작,광고대행,옥외광고
3rd row옥외광고물제작및대행
4th row옥외광고업
5th row간판및광고물제조
ValueCountFrequency (%)
옥외광고물 1958
12.8%
1712
 
11.2%
제작 1520
 
9.9%
옥외광고업 1421
 
9.3%
대행 975
 
6.4%
광고물제작 918
 
6.0%
광고대행 699
 
4.6%
간판제작 532
 
3.5%
설치 503
 
3.3%
옥외광고물제작 471
 
3.1%
Other values (1061) 4576
29.9%
2024-04-18T05:29:46.218337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7944
11.9%
7916
11.8%
6767
10.1%
5129
 
7.7%
5098
 
7.6%
4902
 
7.3%
4801
 
7.2%
4647
 
6.9%
2381
 
3.6%
2193
 
3.3%
Other values (338) 15221
22.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58185
86.8%
Space Separator 6767
 
10.1%
Other Punctuation 1209
 
1.8%
Decimal Number 415
 
0.6%
Open Punctuation 162
 
0.2%
Close Punctuation 162
 
0.2%
Uppercase Letter 68
 
0.1%
Lowercase Letter 17
 
< 0.1%
Dash Punctuation 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7944
13.7%
7916
13.6%
5129
8.8%
5098
8.8%
4902
8.4%
4801
8.3%
4647
8.0%
2381
 
4.1%
2193
 
3.8%
2191
 
3.8%
Other values (293) 10983
18.9%
Uppercase Letter
ValueCountFrequency (%)
L 19
27.9%
E 15
22.1%
D 14
20.6%
P 3
 
4.4%
I 3
 
4.4%
O 2
 
2.9%
T 2
 
2.9%
C 2
 
2.9%
M 1
 
1.5%
K 1
 
1.5%
Other values (6) 6
 
8.8%
Decimal Number
ValueCountFrequency (%)
0 275
66.3%
1 60
 
14.5%
2 26
 
6.3%
8 12
 
2.9%
7 11
 
2.7%
4 8
 
1.9%
3 8
 
1.9%
6 7
 
1.7%
9 5
 
1.2%
5 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 939
77.7%
. 152
 
12.6%
/ 95
 
7.9%
? 13
 
1.1%
: 6
 
0.5%
' 2
 
0.2%
1
 
0.1%
; 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
d 4
23.5%
e 4
23.5%
n 2
11.8%
g 2
11.8%
s 2
11.8%
i 2
11.8%
l 1
 
5.9%
Space Separator
ValueCountFrequency (%)
6767
100.0%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58184
86.8%
Common 8729
 
13.0%
Latin 85
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7944
13.7%
7916
13.6%
5129
8.8%
5098
8.8%
4902
8.4%
4801
8.3%
4647
8.0%
2381
 
4.1%
2193
 
3.8%
2191
 
3.8%
Other values (292) 10982
18.9%
Latin
ValueCountFrequency (%)
L 19
22.4%
E 15
17.6%
D 14
16.5%
d 4
 
4.7%
e 4
 
4.7%
P 3
 
3.5%
I 3
 
3.5%
n 2
 
2.4%
O 2
 
2.4%
T 2
 
2.4%
Other values (13) 17
20.0%
Common
ValueCountFrequency (%)
6767
77.5%
, 939
 
10.8%
0 275
 
3.2%
( 162
 
1.9%
) 162
 
1.9%
. 152
 
1.7%
/ 95
 
1.1%
1 60
 
0.7%
2 26
 
0.3%
- 14
 
0.2%
Other values (12) 77
 
0.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58153
86.8%
ASCII 8813
 
13.2%
Compat Jamo 31
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7944
13.7%
7916
13.6%
5129
8.8%
5098
8.8%
4902
8.4%
4801
8.3%
4647
8.0%
2381
 
4.1%
2193
 
3.8%
2191
 
3.8%
Other values (283) 10951
18.8%
ASCII
ValueCountFrequency (%)
6767
76.8%
, 939
 
10.7%
0 275
 
3.1%
( 162
 
1.8%
) 162
 
1.8%
. 152
 
1.7%
/ 95
 
1.1%
1 60
 
0.7%
2 26
 
0.3%
L 19
 
0.2%
Other values (34) 156
 
1.8%
Compat Jamo
ValueCountFrequency (%)
12
38.7%
4
 
12.9%
4
 
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
118833230000201132302110850000320130820<NA>3폐업40폐업20130820<NA><NA><NA><NA><NA><NA>서울특별시 송파구 가락동 ***-**번지서울특별시 송파구 문정로**길 ** (가락동)<NA>성림B2BC2013-08-26 10:57:42I2018-08-31 23:59:59.0<NA>211905.626471443595.267982옥외광고업
80013180000200431800850820002220040709<NA>3폐업40폐업20160212<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동*가 ***번지서울특별시 영등포구 선유로**길 ** (양평동*가, 신한하이빌)07206한비콤2016-02-16 10:23:09I2018-08-31 23:59:59.0<NA>190633.094922448463.575329광고물제작,광고대행,옥외광고
42933080000201730801740850000120170727<NA>3폐업40폐업20200630<NA><NA><NA><NA><NA><NA>서울특별시 강북구 수유동 ***-**서울특별시 강북구 인수봉로 *** (수유동)01024(주)모스테크2020-06-30 13:11:18U2020-07-02 02:40:00.0<NA>201072.909902459260.651108옥외광고물제작및대행
12953200000200132000240820007319880831<NA>1영업/정상01<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ***-** 번지<NA><NA>삼성공사1988-08-31 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA>
97853210000200532100780820000820050131<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 ***-*번지 남일예당빌딩*층서울특별시 서초구 동광로 **-* (방배동,남일예당빌딩*층)<NA>홍익애이디넷(주)2008-05-15 15:31:17I2018-08-31 23:59:59.0<NA>198921.649839443355.370371옥외광고업
7605318000020013180000082002532014-04-09<NA>1영업/정상20정상<NA><NA><NA><NA>02 26794282<NA><NA>서울특별시 영등포구 당산동*가 ***서울특별시 영등포구 당산로**길 **-* (당산동*가)07266서울기획2023-10-20 11:16:17U2022-10-30 22:02:00.0<NA>190985.250492446595.763575<NA>
57783130000201031301370850002020101119<NA>3폐업40폐업20150623<NA><NA><NA><NA><NA><NA>서울특별시 마포구 공덕동 ***번지 풍림브이아이피텔 ***호서울특별시 마포구 마포대로 ***, ***호 (공덕동,풍림브이아이피텔)<NA>(주)퍼블릭디자인컴퍼니2015-06-23 13:11:15I2018-08-31 23:59:59.0<NA>195703.425297449330.800718간판및광고물제조
24113020000200130200770820014720220615<NA>1영업/정상20정상<NA><NA><NA><NA>02 713 4040<NA><NA>서울특별시 용산구 효창동 *-***서울특별시 용산구 백범로**길 * (효창동)04319(주)태광싸인아트2022-06-15 17:11:28U2021-12-05 23:07:00.0<NA>196205.442371448755.748395<NA>
44603090000201430901160850000520141125<NA>1영업/정상20정상<NA><NA><NA><NA>023946116<NA><NA>서울특별시 도봉구 방학동 ***-*서울특별시 도봉구 도봉로***다길 **, ***호 (방학동)132854(주)서서도시개발2020-10-06 08:59:53U2020-10-08 02:40:00.0<NA>203860.326382462947.93146가로휴지통광고,현수막,벽보,전단,기타이와유사한것
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)영업내용
88993210000201932101400850000320190305<NA>3폐업40폐업20230120<NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 ***-*서울특별시 서초구 청두곶**길 * (방배동)06678하람디자인2023-01-20 14:02:06U2022-11-30 22:02:00.0<NA>198650.32902442145.531045<NA>
72693170000200031700710820014320000508<NA>3폐업40폐업20171123<NA><NA><NA>02 8037000<NA><NA>서울특별시 금천구 독산동 ****번지 보옥빌딩 *층*호서울특별시 금천구 시흥대로 ***, *층 *호 (독산동, 보옥빌딩)153867아이디애드2017-11-23 19:24:10I2018-08-31 23:59:59.0<NA>191006.637021439695.664433옥외광고물 제작 및 설치
5181312000020213120175085000072021-12-01<NA>1영업/정상20정상<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 ***-**서울특별시 서대문구 연희로**길 **-* (연희동)03724행운광고2023-03-14 11:17:42U2022-12-02 23:06:00.0<NA>193979.39591451609.360729<NA>
92503210000201932101530850000220080926<NA>3폐업40폐업20210927<NA><NA><NA>02 5013300<NA><NA>서울특별시 서초구 서초동 ****-* 부띠크 모나코서울특별시 서초구 서초대로 ***, 부띠크 모나코 ****호 (서초동)06616(주)모스트앤컴퍼니2021-09-27 10:19:06U2021-09-29 02:40:00.0<NA>202099.25278443921.619035광고물 제작 및 대행
92513210000201932101530850000320080617<NA>3폐업40폐업20190628<NA><NA><NA><NA><NA><NA>서울특별시 서초구 반포동 **-*번지 코웰빌딩서울특별시 서초구 사평대로 ***, 코웰빌딩 ***호 (반포동)06577주식회사앤드위2019-06-28 13:20:19U2019-06-30 02:40:00.0<NA>199898.194566444240.217111옥외광고물제작
110973220000199532201040820046419950812<NA>3폐업40폐업20120717<NA><NA><NA>0317952780<NA><NA>서울특별시 강남구 역삼동 ***-*번지 대건빌딩 ***호서울특별시 강남구 테헤란로 *** (역삼동,대건빌딩 ***호)<NA>(주)덕진에스아이2012-09-07 09:38:22I2018-08-31 23:59:59.0<NA>202518.374074444076.444984광고대행
94473210000200432100780850096920040702<NA>3폐업40폐업20130822<NA><NA><NA>02 523 9115<NA><NA>서울특별시 서초구 방배동 ***-**번지서울특별시 서초구 방배천로*안길 ** (방배동)<NA>(주)홍원아이디2013-08-22 14:57:28I2018-08-31 23:59:59.0<NA>198497.414273441840.718597옥외광고업(입간판제작)
98113210000200132100780820006920020423<NA>3폐업40폐업20040827<NA><NA><NA>02 5449909<NA><NA>서울특별시 서초구 잠원동 **-**번지서울특별시 서초구 신반포로**길 **-* (잠원동)<NA>명성인터프라이스(주)2007-12-21 12:42:40I2018-08-31 23:59:59.0<NA>201678.887678445477.637580
56683130000200531301340850061720050426<NA>3폐업40폐업20100329<NA><NA><NA>3238982<NA><NA>서울특별시 마포구 서교동 ***-***번지 *통*반 .서울특별시 마포구 양화로 **-** (서교동,.)<NA>(주)노카커뮤니케이션2010-03-29 18:11:57I2018-08-31 23:59:59.0<NA>192669.586859449857.487538광고대행및장치광고제조
12143000000201030001490850000920100818<NA>3폐업40폐업20160202<NA><NA><NA>027426600<NA><NA>서울특별시 종로구 낙원동 **-*번지 종로오피스텔 ****호서울특별시 종로구 삼일대로**길 **, ****호 (낙원동,종로오피스텔)<NA>(주)씨앤엠애드2016-02-02 09:38:39I2018-08-31 23:59:59.0<NA>198913.496136452416.17078옥외광고업 대행 및 제작