Overview

Dataset statistics

Number of variables29
Number of observations680
Missing cells5393
Missing cells (%)27.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory164.8 KiB
Average record size in memory248.2 B

Variable types

Categorical8
Numeric8
DateTime4
Text6
Unsupported3

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),자산규모,부채총액,자본금,판매방식명
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18795/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (83.2%)Imbalance
휴업시작일자 is highly imbalanced (97.3%)Imbalance
휴업종료일자 is highly imbalanced (97.3%)Imbalance
폐업일자 has 200 (29.4%) missing valuesMissing
재개업일자 has 590 (86.8%) missing valuesMissing
전화번호 has 94 (13.8%) missing valuesMissing
소재지면적 has 680 (100.0%) missing valuesMissing
소재지우편번호 has 431 (63.4%) missing valuesMissing
지번주소 has 148 (21.8%) missing valuesMissing
도로명주소 has 110 (16.2%) missing valuesMissing
도로명우편번호 has 323 (47.5%) missing valuesMissing
업태구분명 has 680 (100.0%) missing valuesMissing
좌표정보(X) has 105 (15.4%) missing valuesMissing
좌표정보(Y) has 105 (15.4%) missing valuesMissing
자산규모 has 416 (61.2%) missing valuesMissing
부채총액 has 416 (61.2%) missing valuesMissing
자본금 has 415 (61.0%) missing valuesMissing
판매방식명 has 680 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
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
판매방식명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자산규모 has 89 (13.1%) zerosZeros
부채총액 has 130 (19.1%) zerosZeros
자본금 has 67 (9.9%) zerosZeros

Reproduction

Analysis started2024-04-17 17:52:38.279296
Analysis finished2024-04-17 17:52:38.933525
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
3180000
680 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 680
100.0%

Length

2024-04-18T02:52:38.982152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:39.050687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 680
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct680
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.012693 × 1018
Minimum2.002318 × 1018
Maximum2.024318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:39.131517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002318 × 1018
5-th percentile2.003318 × 1018
Q12.007318 × 1018
median2.012318 × 1018
Q32.018318 × 1018
95-th percentile2.022318 × 1018
Maximum2.024318 × 1018
Range2.2000014 × 1016
Interquartile range (IQR)1.1000005 × 1016

Descriptive statistics

Standard deviation6.1146884 × 1015
Coefficient of variation (CV)0.0030380631
Kurtosis-1.2422097
Mean2.012693 × 1018
Median Absolute Deviation (MAD)5.0000046 × 1015
Skewness0.17093011
Sum3.5721895 × 1018
Variance3.7389414 × 1031
MonotonicityStrictly increasing
2024-04-18T02:52:39.237455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002318011724290001 1
 
0.1%
2016318016324200027 1
 
0.1%
2016318016324200016 1
 
0.1%
2016318016324200017 1
 
0.1%
2016318016324200018 1
 
0.1%
2016318016324200019 1
 
0.1%
2016318016324200020 1
 
0.1%
2016318016324200021 1
 
0.1%
2016318016324200022 1
 
0.1%
2016318016324200023 1
 
0.1%
Other values (670) 670
98.5%
ValueCountFrequency (%)
2002318011724290001 1
0.1%
2002318011724290002 1
0.1%
2002318011724290003 1
0.1%
2002318011724290005 1
0.1%
2002318011724290006 1
0.1%
2002318011724290007 1
0.1%
2002318011724290008 1
0.1%
2002318011724290009 1
0.1%
2002318011724290011 1
0.1%
2002318011724290015 1
0.1%
ValueCountFrequency (%)
2024318025424200003 1
0.1%
2024318025424200002 1
0.1%
2024318025424200001 1
0.1%
2023318025424200020 1
0.1%
2023318025424200019 1
0.1%
2023318025424200018 1
0.1%
2023318025424200017 1
0.1%
2023318025424200016 1
0.1%
2023318025424200015 1
0.1%
2023318025424200014 1
0.1%

인허가일자
Date

Distinct580
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2002-08-26 00:00:00
Maximum2024-03-28 00:00:00
2024-04-18T02:52:39.335807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:52:39.444907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
<NA>
641 
20071022
 
22
20080923
 
15
20071205
 
1
20190430
 
1

Length

Max length8
Median length4
Mean length4.2294118
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 641
94.3%
20071022 22
 
3.2%
20080923 15
 
2.2%
20071205 1
 
0.1%
20190430 1
 
0.1%

Length

2024-04-18T02:52:39.552191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:39.642968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 641
94.3%
20071022 22
 
3.2%
20080923 15
 
2.2%
20071205 1
 
0.1%
20190430 1
 
0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
3
294 
1
195 
4
174 
5
 
14
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 294
43.2%
1 195
28.7%
4 174
25.6%
5 14
 
2.1%
2 3
 
0.4%

Length

2024-04-18T02:52:39.732177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:39.808934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 294
43.2%
1 195
28.7%
4 174
25.6%
5 14
 
2.1%
2 3
 
0.4%

영업상태명
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
폐업
294 
영업/정상
195 
취소/말소/만료/정지/중지
174 
제외/삭제/전출
 
14
휴업
 
3

Length

Max length14
Median length8
Mean length6.0544118
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 294
43.2%
영업/정상 195
28.7%
취소/말소/만료/정지/중지 174
25.6%
제외/삭제/전출 14
 
2.1%
휴업 3
 
0.4%

Length

2024-04-18T02:52:39.905130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:39.987618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 294
43.2%
영업/정상 195
28.7%
취소/말소/만료/정지/중지 174
25.6%
제외/삭제/전출 14
 
2.1%
휴업 3
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3147059
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:40.059945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0916599
Coefficient of variation (CV)0.63102428
Kurtosis-0.63544094
Mean3.3147059
Median Absolute Deviation (MAD)2
Skewness0.71056206
Sum2254
Variance4.3750412
MonotonicityNot monotonic
2024-04-18T02:52:40.145669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 294
43.2%
1 195
28.7%
7 135
19.9%
4 39
 
5.7%
5 14
 
2.1%
2 3
 
0.4%
ValueCountFrequency (%)
1 195
28.7%
2 3
 
0.4%
3 294
43.2%
4 39
 
5.7%
5 14
 
2.1%
7 135
19.9%
ValueCountFrequency (%)
7 135
19.9%
5 14
 
2.1%
4 39
 
5.7%
3 294
43.2%
2 3
 
0.4%
1 195
28.7%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
폐업처리
294 
정상영업
195 
직권말소
135 
직권취소
39 
타시군구이관
 
14

Length

Max length6
Median length4
Mean length4.0411765
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 294
43.2%
정상영업 195
28.7%
직권말소 135
19.9%
직권취소 39
 
5.7%
타시군구이관 14
 
2.1%
휴업처리 3
 
0.4%

Length

2024-04-18T02:52:40.272820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:40.380967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 294
43.2%
정상영업 195
28.7%
직권말소 135
19.9%
직권취소 39
 
5.7%
타시군구이관 14
 
2.1%
휴업처리 3
 
0.4%

폐업일자
Date

MISSING 

Distinct266
Distinct (%)55.4%
Missing200
Missing (%)29.4%
Memory size5.4 KiB
Minimum2002-12-21 00:00:00
Maximum2024-04-04 00:00:00
2024-04-18T02:52:40.470173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:52:40.594217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
<NA>
676 
20140630
 
1
20100101
 
1
20191220
 
1
20150924
 
1

Length

Max length8
Median length4
Mean length4.0235294
Min length4

Unique

Unique4 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 676
99.4%
20140630 1
 
0.1%
20100101 1
 
0.1%
20191220 1
 
0.1%
20150924 1
 
0.1%

Length

2024-04-18T02:52:40.730773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:40.814342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 676
99.4%
20140630 1
 
0.1%
20100101 1
 
0.1%
20191220 1
 
0.1%
20150924 1
 
0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
<NA>
676 
20150624
 
1
20121231
 
1
20201231
 
1
20250924
 
1

Length

Max length8
Median length4
Mean length4.0235294
Min length4

Unique

Unique4 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 676
99.4%
20150624 1
 
0.1%
20121231 1
 
0.1%
20201231 1
 
0.1%
20250924 1
 
0.1%

Length

2024-04-18T02:52:40.924524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:41.241313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 676
99.4%
20150624 1
 
0.1%
20121231 1
 
0.1%
20201231 1
 
0.1%
20250924 1
 
0.1%

재개업일자
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)84.4%
Missing590
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean20038170
Minimum20020831
Maximum20060515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:41.338889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020831
5-th percentile20020959
Q120030410
median20040223
Q320050328
95-th percentile20051172
Maximum20060515
Range39684
Interquartile range (IQR)19918.25

Descriptive statistics

Standard deviation10792.067
Coefficient of variation (CV)0.00053857547
Kurtosis-0.89241815
Mean20038170
Median Absolute Deviation (MAD)9967
Skewness0.19632223
Sum1.8034353 × 109
Variance1.164687 × 108
MonotonicityNot monotonic
2024-04-18T02:52:41.471665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030123 3
 
0.4%
20030124 3
 
0.4%
20030920 2
 
0.3%
20040624 2
 
0.3%
20021015 2
 
0.3%
20040621 2
 
0.3%
20040528 2
 
0.3%
20020902 2
 
0.3%
20031118 2
 
0.3%
20030530 2
 
0.3%
Other values (66) 68
 
10.0%
(Missing) 590
86.8%
ValueCountFrequency (%)
20020831 1
0.1%
20020902 2
0.3%
20020912 1
0.1%
20020914 1
0.1%
20021015 2
0.3%
20021017 1
0.1%
20021023 1
0.1%
20021127 1
0.1%
20030107 1
0.1%
20030117 1
0.1%
ValueCountFrequency (%)
20060515 1
0.1%
20060421 1
0.1%
20060406 1
0.1%
20060223 1
0.1%
20051219 1
0.1%
20051115 1
0.1%
20051110 1
0.1%
20051025 1
0.1%
20051005 1
0.1%
20050926 1
0.1%

전화번호
Text

MISSING 

Distinct549
Distinct (%)93.7%
Missing94
Missing (%)13.8%
Memory size5.4 KiB
2024-04-18T02:52:41.652846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.496587
Min length1

Characters and Unicode

Total characters6151
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique527 ?
Unique (%)89.9%

Sample

1st row02 676 5340
2nd row02 676 5096
3rd row02 676 4122
4th row02 6674 4200
5th row02
ValueCountFrequency (%)
02 94
 
12.2%
9
 
1.2%
670 9
 
1.2%
2633 6
 
0.8%
832 5
 
0.6%
3418 4
 
0.5%
02)777-6762 3
 
0.4%
753-2415 3
 
0.4%
843-2330 3
 
0.4%
02-1522-8471 3
 
0.4%
Other values (597) 631
81.9%
2024-04-18T02:52:41.946805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 895
14.6%
2 837
13.6%
- 730
11.9%
6 555
9.0%
1 507
8.2%
7 500
8.1%
3 472
7.7%
8 427
6.9%
4 386
6.3%
5 345
 
5.6%
Other values (6) 497
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5177
84.2%
Dash Punctuation 730
 
11.9%
Space Separator 206
 
3.3%
Close Punctuation 28
 
0.5%
Other Punctuation 9
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 895
17.3%
2 837
16.2%
6 555
10.7%
1 507
9.8%
7 500
9.7%
3 472
9.1%
8 427
8.2%
4 386
7.5%
5 345
 
6.7%
9 253
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 7
77.8%
/ 2
 
22.2%
Dash Punctuation
ValueCountFrequency (%)
- 730
100.0%
Space Separator
ValueCountFrequency (%)
206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6151
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 895
14.6%
2 837
13.6%
- 730
11.9%
6 555
9.0%
1 507
8.2%
7 500
8.1%
3 472
7.7%
8 427
6.9%
4 386
6.3%
5 345
 
5.6%
Other values (6) 497
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 895
14.6%
2 837
13.6%
- 730
11.9%
6 555
9.0%
1 507
8.2%
7 500
8.1%
3 472
7.7%
8 427
6.9%
4 386
6.3%
5 345
 
5.6%
Other values (6) 497
8.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing680
Missing (%)100.0%
Memory size6.1 KiB

소재지우편번호
Text

MISSING 

Distinct60
Distinct (%)24.1%
Missing431
Missing (%)63.4%
Memory size5.4 KiB
2024-04-18T02:52:42.120212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0040161
Min length6

Characters and Unicode

Total characters1495
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

Unique21 ?
Unique (%)8.4%

Sample

1st row150-010
2nd row150010
3rd row150010
4th row150808
5th row150046
ValueCountFrequency (%)
150070 51
20.5%
150010 32
 
12.9%
150046 8
 
3.2%
150033 8
 
3.2%
150038 7
 
2.8%
150050 7
 
2.8%
150043 7
 
2.8%
150103 7
 
2.8%
150045 7
 
2.8%
150803 6
 
2.4%
Other values (50) 109
43.8%
2024-04-18T02:52:42.382025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 568
38.0%
1 311
20.8%
5 275
18.4%
7 83
 
5.6%
3 78
 
5.2%
8 66
 
4.4%
4 42
 
2.8%
2 30
 
2.0%
6 24
 
1.6%
9 17
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1494
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 568
38.0%
1 311
20.8%
5 275
18.4%
7 83
 
5.6%
3 78
 
5.2%
8 66
 
4.4%
4 42
 
2.8%
2 30
 
2.0%
6 24
 
1.6%
9 17
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 568
38.0%
1 311
20.8%
5 275
18.4%
7 83
 
5.6%
3 78
 
5.2%
8 66
 
4.4%
4 42
 
2.8%
2 30
 
2.0%
6 24
 
1.6%
9 17
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 568
38.0%
1 311
20.8%
5 275
18.4%
7 83
 
5.6%
3 78
 
5.2%
8 66
 
4.4%
4 42
 
2.8%
2 30
 
2.0%
6 24
 
1.6%
9 17
 
1.1%

지번주소
Text

MISSING 

Distinct393
Distinct (%)73.9%
Missing148
Missing (%)21.8%
Memory size5.4 KiB
2024-04-18T02:52:42.543901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length38
Mean length29.911654
Min length18

Characters and Unicode

Total characters15913
Distinct characters265
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique323 ?
Unique (%)60.7%

Sample

1st row서울특별시 영등포구 영등포동*가 일반번지 ***-*
2nd row서울특별시 영등포구 양평동*가 일반번지 **-*
3rd row서울특별시 영등포구 양평동*가 일반번지 ***-*
4th row서울특별시 노원구 일반 **-**
5th row서울특별시 영등포구 영등포동*가 일반 *-*
ValueCountFrequency (%)
서울특별시 530
17.5%
영등포구 528
17.4%
호 358
11.8%
번지 324
10.7%
241
8.0%
여의도동 137
 
4.5%
당산동*가 117
 
3.9%
대림동 79
 
2.6%
영등포동*가 67
 
2.2%
층 55
 
1.8%
Other values (278) 594
19.6%
2024-04-18T02:52:42.804765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2996
18.8%
* 2716
17.1%
영 619
 
3.9%
포 611
 
3.8%
등 608
 
3.8%
동 559
 
3.5%
시 542
 
3.4%
서 535
 
3.4%
별 533
 
3.3%
울 531
 
3.3%
Other values (255) 5663
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9900
62.2%
Space Separator 2996
 
18.8%
Other Punctuation 2720
 
17.1%
Dash Punctuation 175
 
1.1%
Uppercase Letter 53
 
0.3%
Decimal Number 33
 
0.2%
Lowercase Letter 29
 
0.2%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 619
 
6.3%
포 611
 
6.2%
등 608
 
6.1%
동 559
 
5.6%
시 542
 
5.5%
서 535
 
5.4%
별 533
 
5.4%
울 531
 
5.4%
특 531
 
5.4%
구 531
 
5.4%
Other values (217) 4300
43.4%
Uppercase Letter
ValueCountFrequency (%)
K 11
20.8%
T 10
18.9%
S 7
13.2%
E 5
9.4%
V 4
 
7.5%
A 4
 
7.5%
I 3
 
5.7%
U 2
 
3.8%
M 2
 
3.8%
R 1
 
1.9%
Other values (4) 4
 
7.5%
Decimal Number
ValueCountFrequency (%)
3 7
21.2%
5 6
18.2%
1 6
18.2%
7 5
15.2%
2 2
 
6.1%
0 2
 
6.1%
4 2
 
6.1%
6 2
 
6.1%
8 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
27.6%
c 6
20.7%
n 5
17.2%
r 4
13.8%
t 4
13.8%
m 2
 
6.9%
Other Punctuation
ValueCountFrequency (%)
* 2716
99.9%
, 2
 
0.1%
. 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2996
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9900
62.2%
Common 5931
37.3%
Latin 82
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 619
 
6.3%
포 611
 
6.2%
등 608
 
6.1%
동 559
 
5.6%
시 542
 
5.5%
서 535
 
5.4%
별 533
 
5.4%
울 531
 
5.4%
특 531
 
5.4%
구 531
 
5.4%
Other values (217) 4300
43.4%
Latin
ValueCountFrequency (%)
K 11
13.4%
T 10
12.2%
e 8
9.8%
S 7
 
8.5%
c 6
 
7.3%
E 5
 
6.1%
n 5
 
6.1%
V 4
 
4.9%
r 4
 
4.9%
A 4
 
4.9%
Other values (10) 18
22.0%
Common
ValueCountFrequency (%)
2996
50.5%
* 2716
45.8%
- 175
 
3.0%
3 7
 
0.1%
5 6
 
0.1%
1 6
 
0.1%
7 5
 
0.1%
( 3
 
0.1%
) 3
 
0.1%
2 2
 
< 0.1%
Other values (8) 12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9900
62.2%
ASCII 6013
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2996
49.8%
* 2716
45.2%
- 175
 
2.9%
K 11
 
0.2%
T 10
 
0.2%
e 8
 
0.1%
S 7
 
0.1%
3 7
 
0.1%
c 6
 
0.1%
5 6
 
0.1%
Other values (28) 71
 
1.2%
Hangul
ValueCountFrequency (%)
영 619
 
6.3%
포 611
 
6.2%
등 608
 
6.1%
동 559
 
5.6%
시 542
 
5.5%
서 535
 
5.4%
별 533
 
5.4%
울 531
 
5.4%
특 531
 
5.4%
구 531
 
5.4%
Other values (217) 4300
43.4%

도로명주소
Text

MISSING 

Distinct502
Distinct (%)88.1%
Missing110
Missing (%)16.2%
Memory size5.4 KiB
2024-04-18T02:52:43.004564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length52
Mean length38.147368
Min length24

Characters and Unicode

Total characters21744
Distinct characters288
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique456 ?
Unique (%)80.0%

Sample

1st row서울특별시 영등포구 의사당대로 * (여의도동)
2nd row서울특별시 영등포구 국회대로**길 **, ***호 (여의도동,오성빌딩)
3rd row서울특별시 영등포구 국제금융로*길 **, ***호 (여의도동,여의도백화점빌딩)
4th row서울특별시 영등포구 의사당대로 ** (여의도동)
5th row서울특별시 영등포구 국제금융로*길 ** (여의도동,대한빌딩 *층)
ValueCountFrequency (%)
580
15.3%
서울특별시 570
15.1%
영등포구 570
15.1%
호 300
 
7.9%
층 186
 
4.9%
여의도동 105
 
2.8%
당산동*가 66
 
1.7%
양평동*가 53
 
1.4%
문래동*가 52
 
1.4%
국회대로**길 46
 
1.2%
Other values (481) 1255
33.2%
2024-04-18T02:52:43.330677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 3598
 
16.5%
3229
 
14.9%
영 755
 
3.5%
, 730
 
3.4%
포 696
 
3.2%
등 692
 
3.2%
동 642
 
3.0%
시 598
 
2.8%
서 579
 
2.7%
) 574
 
2.6%
Other values (278) 9651
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12779
58.8%
Other Punctuation 4332
 
19.9%
Space Separator 3229
 
14.9%
Close Punctuation 574
 
2.6%
Open Punctuation 574
 
2.6%
Dash Punctuation 85
 
0.4%
Uppercase Letter 85
 
0.4%
Lowercase Letter 45
 
0.2%
Decimal Number 38
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 755
 
5.9%
포 696
 
5.4%
등 692
 
5.4%
동 642
 
5.0%
시 598
 
4.7%
서 579
 
4.5%
별 573
 
4.5%
특 572
 
4.5%
구 571
 
4.5%
로 571
 
4.5%
Other values (232) 6530
51.1%
Uppercase Letter
ValueCountFrequency (%)
K 19
22.4%
T 12
14.1%
S 10
11.8%
E 9
10.6%
A 6
 
7.1%
B 6
 
7.1%
V 5
 
5.9%
I 4
 
4.7%
D 3
 
3.5%
U 2
 
2.4%
Other values (8) 9
10.6%
Decimal Number
ValueCountFrequency (%)
2 7
18.4%
1 7
18.4%
3 6
15.8%
0 5
13.2%
9 4
10.5%
7 3
7.9%
4 3
7.9%
5 1
 
2.6%
8 1
 
2.6%
6 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 10
22.2%
n 8
17.8%
d 8
17.8%
c 7
15.6%
r 5
11.1%
t 5
11.1%
m 2
 
4.4%
Other Punctuation
ValueCountFrequency (%)
* 3598
83.1%
, 730
 
16.9%
/ 2
 
< 0.1%
. 1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3229
100.0%
Close Punctuation
ValueCountFrequency (%)
) 574
100.0%
Open Punctuation
ValueCountFrequency (%)
( 574
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12779
58.8%
Common 8835
40.6%
Latin 130
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 755
 
5.9%
포 696
 
5.4%
등 692
 
5.4%
동 642
 
5.0%
시 598
 
4.7%
서 579
 
4.5%
별 573
 
4.5%
특 572
 
4.5%
구 571
 
4.5%
로 571
 
4.5%
Other values (232) 6530
51.1%
Latin
ValueCountFrequency (%)
K 19
14.6%
T 12
 
9.2%
e 10
 
7.7%
S 10
 
7.7%
E 9
 
6.9%
n 8
 
6.2%
d 8
 
6.2%
c 7
 
5.4%
A 6
 
4.6%
B 6
 
4.6%
Other values (15) 35
26.9%
Common
ValueCountFrequency (%)
* 3598
40.7%
3229
36.5%
, 730
 
8.3%
) 574
 
6.5%
( 574
 
6.5%
- 85
 
1.0%
2 7
 
0.1%
1 7
 
0.1%
3 6
 
0.1%
0 5
 
0.1%
Other values (11) 20
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12779
58.8%
ASCII 8965
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 3598
40.1%
3229
36.0%
, 730
 
8.1%
) 574
 
6.4%
( 574
 
6.4%
- 85
 
0.9%
K 19
 
0.2%
T 12
 
0.1%
e 10
 
0.1%
S 10
 
0.1%
Other values (36) 124
 
1.4%
Hangul
ValueCountFrequency (%)
영 755
 
5.9%
포 696
 
5.4%
등 692
 
5.4%
동 642
 
5.0%
시 598
 
4.7%
서 579
 
4.5%
별 573
 
4.5%
특 572
 
4.5%
구 571
 
4.5%
로 571
 
4.5%
Other values (232) 6530
51.1%

도로명우편번호
Text

MISSING 

Distinct145
Distinct (%)40.6%
Missing323
Missing (%)47.5%
Memory size5.4 KiB
2024-04-18T02:52:43.590442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2773109
Min length5

Characters and Unicode

Total characters1884
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

Unique72 ?
Unique (%)20.2%

Sample

1st row150899
2nd row150866
3rd row07237
4th row07328
5th row07254
ValueCountFrequency (%)
07333 22
 
6.2%
07299 18
 
5.0%
07327 10
 
2.8%
07257 10
 
2.8%
07217 8
 
2.2%
07237 7
 
2.0%
07255 7
 
2.0%
07331 7
 
2.0%
07212 6
 
1.7%
150103 6
 
1.7%
Other values (135) 256
71.7%
2024-04-18T02:52:43.970865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 452
24.0%
7 348
18.5%
2 251
13.3%
3 205
10.9%
1 180
 
9.6%
5 173
 
9.2%
8 88
 
4.7%
9 87
 
4.6%
4 51
 
2.7%
6 44
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1879
99.7%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 452
24.1%
7 348
18.5%
2 251
13.4%
3 205
10.9%
1 180
 
9.6%
5 173
 
9.2%
8 88
 
4.7%
9 87
 
4.6%
4 51
 
2.7%
6 44
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1884
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 452
24.0%
7 348
18.5%
2 251
13.3%
3 205
10.9%
1 180
 
9.6%
5 173
 
9.2%
8 88
 
4.7%
9 87
 
4.6%
4 51
 
2.7%
6 44
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1884
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 452
24.0%
7 348
18.5%
2 251
13.3%
3 205
10.9%
1 180
 
9.6%
5 173
 
9.2%
8 88
 
4.7%
9 87
 
4.6%
4 51
 
2.7%
6 44
 
2.3%

사업장명
Text

Distinct660
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2024-04-18T02:52:44.250821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length27
Mean length8.8867647
Min length2

Characters and Unicode

Total characters6043
Distinct characters458
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique641 ?
Unique (%)94.3%

Sample

1st row미성미디어텍
2nd row라이센스114.
3rd row21C PASS
4th row매일넷
5th row수림통상
ValueCountFrequency (%)
주식회사 142
 
15.0%
주 24
 
2.5%
푸시 7
 
0.7%
대운상사 3
 
0.3%
한국신문방송기자회 2
 
0.2%
ltd 2
 
0.2%
이플레이스 2
 
0.2%
세종 2
 
0.2%
corporation 2
 
0.2%
국제결혼 2
 
0.2%
Other values (734) 756
80.1%
2024-04-18T02:52:44.669761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 354
 
5.9%
265
 
4.4%
) 234
 
3.9%
( 234
 
3.9%
이 212
 
3.5%
사 197
 
3.3%
회 185
 
3.1%
스 178
 
2.9%
식 151
 
2.5%
한 89
 
1.5%
Other values (448) 3944
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4888
80.9%
Space Separator 265
 
4.4%
Close Punctuation 234
 
3.9%
Open Punctuation 234
 
3.9%
Uppercase Letter 204
 
3.4%
Lowercase Letter 160
 
2.6%
Other Punctuation 35
 
0.6%
Decimal Number 18
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 354
 
7.2%
이 212
 
4.3%
사 197
 
4.0%
회 185
 
3.8%
스 178
 
3.6%
식 151
 
3.1%
한 89
 
1.8%
아 82
 
1.7%
에 79
 
1.6%
리 77
 
1.6%
Other values (388) 3284
67.2%
Uppercase Letter
ValueCountFrequency (%)
C 18
 
8.8%
S 17
 
8.3%
E 16
 
7.8%
T 16
 
7.8%
M 14
 
6.9%
L 13
 
6.4%
I 12
 
5.9%
N 10
 
4.9%
H 9
 
4.4%
J 9
 
4.4%
Other values (14) 70
34.3%
Lowercase Letter
ValueCountFrequency (%)
o 22
13.8%
e 16
10.0%
t 15
 
9.4%
r 15
 
9.4%
a 14
 
8.8%
i 10
 
6.2%
n 9
 
5.6%
p 7
 
4.4%
m 7
 
4.4%
d 7
 
4.4%
Other values (11) 38
23.8%
Decimal Number
ValueCountFrequency (%)
1 5
27.8%
9 5
27.8%
4 3
16.7%
8 2
 
11.1%
2 1
 
5.6%
5 1
 
5.6%
7 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 24
68.6%
& 7
 
20.0%
, 4
 
11.4%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Open Punctuation
ValueCountFrequency (%)
( 234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4889
80.9%
Common 789
 
13.1%
Latin 364
 
6.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 354
 
7.2%
이 212
 
4.3%
사 197
 
4.0%
회 185
 
3.8%
스 178
 
3.6%
식 151
 
3.1%
한 89
 
1.8%
아 82
 
1.7%
에 79
 
1.6%
리 77
 
1.6%
Other values (388) 3285
67.2%
Latin
ValueCountFrequency (%)
o 22
 
6.0%
C 18
 
4.9%
S 17
 
4.7%
E 16
 
4.4%
e 16
 
4.4%
T 16
 
4.4%
t 15
 
4.1%
r 15
 
4.1%
a 14
 
3.8%
M 14
 
3.8%
Other values (35) 201
55.2%
Common
ValueCountFrequency (%)
265
33.6%
) 234
29.7%
( 234
29.7%
. 24
 
3.0%
& 7
 
0.9%
1 5
 
0.6%
9 5
 
0.6%
, 4
 
0.5%
4 3
 
0.4%
- 3
 
0.4%
Other values (4) 5
 
0.6%
Han
ValueCountFrequency (%)
秀 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4887
80.9%
ASCII 1153
 
19.1%
None 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 354
 
7.2%
이 212
 
4.3%
사 197
 
4.0%
회 185
 
3.8%
스 178
 
3.6%
식 151
 
3.1%
한 89
 
1.8%
아 82
 
1.7%
에 79
 
1.6%
리 77
 
1.6%
Other values (387) 3283
67.2%
ASCII
ValueCountFrequency (%)
265
23.0%
) 234
20.3%
( 234
20.3%
. 24
 
2.1%
o 22
 
1.9%
C 18
 
1.6%
S 17
 
1.5%
E 16
 
1.4%
e 16
 
1.4%
T 16
 
1.4%
Other values (49) 291
25.2%
None
ValueCountFrequency (%)
㈜ 2
100.0%
CJK
ValueCountFrequency (%)
秀 1
100.0%

최종수정일자
Date

Distinct594
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2007-07-10 22:02:12
Maximum2024-04-14 15:58:14
2024-04-18T02:52:44.823400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:52:44.940922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
I
525 
U
155 

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 525
77.2%
U 155
 
22.8%

Length

2024-04-18T02:52:45.066506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:52:45.156142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 525
77.2%
u 155
 
22.8%

데이터갱신일자
Date

Distinct192
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-18T02:52:45.240916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T02:52:45.370931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing680
Missing (%)100.0%
Memory size6.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct330
Distinct (%)57.4%
Missing105
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean191611.38
Minimum189607.6
Maximum194592.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:45.481764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189607.6
5-th percentile190120.84
Q1190757.02
median191143.82
Q3192671.15
95-th percentile193745.64
Maximum194592.28
Range4984.6779
Interquartile range (IQR)1914.1316

Descriptive statistics

Standard deviation1192.9047
Coefficient of variation (CV)0.0062256465
Kurtosis-0.61888595
Mean191611.38
Median Absolute Deviation (MAD)556.24825
Skewness0.72723179
Sum1.1017655 × 108
Variance1423021.7
MonotonicityNot monotonic
2024-04-18T02:52:45.579431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191108.975924 12
 
1.8%
193469.554731741 10
 
1.5%
190684.216398175 10
 
1.5%
193694.665015597 9
 
1.3%
190911.095889611 8
 
1.2%
190555.768991595 8
 
1.2%
190217.705071932 7
 
1.0%
190941.054351896 7
 
1.0%
190401.596787693 7
 
1.0%
191892.606363416 6
 
0.9%
Other values (320) 491
72.2%
(Missing) 105
 
15.4%
ValueCountFrequency (%)
189607.598899153 1
0.1%
189649.045363359 1
0.1%
189682.022243843 1
0.1%
189700.355755718 1
0.1%
189737.063295458 1
0.1%
189739.200412131 1
0.1%
189785.752470051 1
0.1%
189849.410292461 2
0.3%
189862.670939789 1
0.1%
189880.0 1
0.1%
ValueCountFrequency (%)
194592.276750438 1
 
0.1%
194561.746032498 3
0.4%
194530.535390096 6
0.9%
194028.635844427 2
 
0.3%
193861.272368256 1
 
0.1%
193818.18014 4
0.6%
193798.948251805 1
 
0.1%
193785.813402517 2
 
0.3%
193767.231404334 6
0.9%
193749.233907174 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct331
Distinct (%)57.6%
Missing105
Missing (%)15.4%
Infinite0
Infinite (%)0.0%
Mean446402.05
Minimum442649.87
Maximum448642.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:45.674442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442649.87
5-th percentile443663.38
Q1446171.69
median446640.41
Q3447201.87
95-th percentile448090.98
Maximum448642.11
Range5992.2385
Interquartile range (IQR)1030.1825

Descriptive statistics

Standard deviation1305.3228
Coefficient of variation (CV)0.0029240969
Kurtosis0.37640699
Mean446402.05
Median Absolute Deviation (MAD)538.60093
Skewness-1.0353547
Sum2.5668118 × 108
Variance1703867.7
MonotonicityNot monotonic
2024-04-18T02:52:45.771994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446171.686827 12
 
1.8%
446508.068667777 10
 
1.5%
445883.474973877 10
 
1.5%
446449.546192539 9
 
1.3%
447178.670382264 8
 
1.2%
446698.814322782 8
 
1.2%
446339.064053872 7
 
1.0%
446449.917568696 7
 
1.0%
446320.718339983 6
 
0.9%
446306.787198089 6
 
0.9%
Other values (321) 492
72.4%
(Missing) 105
 
15.4%
ValueCountFrequency (%)
442649.873938101 1
 
0.1%
442704.061942942 1
 
0.1%
442744.165176674 1
 
0.1%
442905.116903156 3
0.4%
443079.668086593 1
 
0.1%
443147.062605365 1
 
0.1%
443221.362840852 1
 
0.1%
443325.375451909 1
 
0.1%
443328.179258251 1
 
0.1%
443395.289736462 1
 
0.1%
ValueCountFrequency (%)
448642.112414847 3
0.4%
448548.48004759 1
 
0.1%
448495.395437399 2
0.3%
448436.126322646 1
 
0.1%
448399.365382151 1
 
0.1%
448352.840608043 1
 
0.1%
448289.617887109 3
0.4%
448279.993287223 1
 
0.1%
448279.594119232 1
 
0.1%
448270.380896893 1
 
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct146
Distinct (%)55.3%
Missing416
Missing (%)61.2%
Infinite0
Infinite (%)0.0%
Mean4.1494872 × 1010
Minimum0
Maximum4.1363129 × 1012
Zeros89
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:45.901525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median45109940
Q37.3353806 × 108
95-th percentile4.7908032 × 1010
Maximum4.1363129 × 1012
Range4.1363129 × 1012
Interquartile range (IQR)7.3353806 × 108

Descriptive statistics

Standard deviation3.1630669 × 1011
Coefficient of variation (CV)7.6227899
Kurtosis127.91822
Mean4.1494872 × 1010
Median Absolute Deviation (MAD)45109940
Skewness10.898326
Sum1.0954646 × 1013
Variance1.0004992 × 1023
MonotonicityNot monotonic
2024-04-18T02:52:46.002672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 89
 
13.1%
50000000 14
 
2.1%
10000000 8
 
1.2%
20000000 5
 
0.7%
100000000 4
 
0.6%
30000000 3
 
0.4%
5000000 2
 
0.3%
39828967781 1
 
0.1%
1474558883 1
 
0.1%
23916716 1
 
0.1%
Other values (136) 136
 
20.0%
(Missing) 416
61.2%
ValueCountFrequency (%)
0 89
13.1%
390400 1
 
0.1%
480748 1
 
0.1%
487522 1
 
0.1%
516400 1
 
0.1%
590400 1
 
0.1%
2071204 1
 
0.1%
4995600 1
 
0.1%
5000000 2
 
0.3%
6000000 1
 
0.1%
ValueCountFrequency (%)
4136312863585 1
0.1%
2763667250808 1
0.1%
916153621668 1
0.1%
746490262063 1
0.1%
505404006080 1
0.1%
460800000000 1
0.1%
229246050186 1
0.1%
181576270301 1
0.1%
145391144749 1
0.1%
114351776000 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct132
Distinct (%)50.0%
Missing416
Missing (%)61.2%
Infinite0
Infinite (%)0.0%
Mean2.7588341 × 1010
Minimum0
Maximum3.4960583 × 1012
Zeros130
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-04-18T02:52:46.102460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median224900
Q34.3435765 × 108
95-th percentile2.9260015 × 1010
Maximum3.4960583 × 1012
Range3.4960583 × 1012
Interquartile range (IQR)4.3435765 × 108

Descriptive statistics

Standard deviation2.3575032 × 1011
Coefficient of variation (CV)8.5452882
Kurtosis182.63952
Mean2.7588341 × 1010
Median Absolute Deviation (MAD)224900
Skewness12.909703
Sum7.2833219 × 1012
Variance5.5578214 × 1022
MonotonicityNot monotonic
2024-04-18T02:52:46.208117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 130
 
19.1%
30000000 3
 
0.4%
224900 2
 
0.3%
462263839 1
 
0.1%
2721000000 1
 
0.1%
1737201986 1
 
0.1%
3496058346300 1
 
0.1%
23769534219 1
 
0.1%
773344152 1
 
0.1%
4880250 1
 
0.1%
Other values (122) 122
 
17.9%
(Missing) 416
61.2%
ValueCountFrequency (%)
0 130
19.1%
70400 1
 
0.1%
224900 2
 
0.3%
508732 1
 
0.1%
605000 1
 
0.1%
626060 1
 
0.1%
2869610 1
 
0.1%
3289480 1
 
0.1%
4155000 1
 
0.1%
4880250 1
 
0.1%
ValueCountFrequency (%)
3496058346300 1
0.1%
1264394970334 1
0.1%
792291956975 1
0.1%
375933130692 1
0.1%
321305529547 1
0.1%
300700000000 1
0.1%
104425287840 1
0.1%
73860198399 1
0.1%
68996317309 1
0.1%
49975253753 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct110
Distinct (%)41.5%
Missing415
Missing (%)61.0%
Infinite0
Infinite (%)0.0%
Mean1.2171616 × 1010
Minimum-8.0411771 × 1010
Maximum1.4992723 × 1012
Zeros67
Zeros (%)9.9%
Negative7
Negative (%)1.0%
Memory size6.1 KiB
2024-04-18T02:52:46.320425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.0411771 × 1010
5-th percentile0
Q10
median45998025
Q32.7350391 × 108
95-th percentile9.595346 × 109
Maximum1.4992723 × 1012
Range1.5796841 × 1012
Interquartile range (IQR)2.7350391 × 108

Descriptive statistics

Standard deviation1.0434071 × 1011
Coefficient of variation (CV)8.5724619
Kurtosis162.92179
Mean1.2171616 × 1010
Median Absolute Deviation (MAD)45998025
Skewness12.13676
Sum3.2254781 × 1012
Variance1.0886984 × 1022
MonotonicityNot monotonic
2024-04-18T02:52:46.426254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67
 
9.9%
50000000 26
 
3.8%
10000000 18
 
2.6%
100000000 12
 
1.8%
20000000 9
 
1.3%
30000000 7
 
1.0%
1000000 6
 
0.9%
300000000 5
 
0.7%
5000000 5
 
0.7%
200000000 5
 
0.7%
Other values (100) 105
 
15.4%
(Missing) 415
61.0%
ValueCountFrequency (%)
-80411771000 1
 
0.1%
-2465069908 1
 
0.1%
-194574557 1
 
0.1%
-135124807 1
 
0.1%
-79010623 1
 
0.1%
-28031326 1
 
0.1%
-9329608 1
 
0.1%
0 67
9.9%
100000 1
 
0.1%
1000000 6
 
0.9%
ValueCountFrequency (%)
1499272280474 1
0.1%
640254517285 1
0.1%
425184732516 1
0.1%
160100000000 1
0.1%
131601016548 1
0.1%
123861664693 1
0.1%
69200003000 1
0.1%
42611601000 1
0.1%
36154467833 1
0.1%
30357410000 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing680
Missing (%)100.0%
Memory size6.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03180000200231801172429000120020831<NA>3폐업3폐업처리20050309<NA><NA>2002083102 676 5340<NA><NA>서울특별시 영등포구 영등포동*가 일반번지 ***-*<NA><NA>미성미디어텍2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13180000200231801172429000220020902<NA>3폐업3폐업처리20050309<NA><NA>2002090202 676 5096<NA><NA>서울특별시 영등포구 양평동*가 일반번지 **-*<NA><NA>라이센스114.2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23180000200231801172429000320020902<NA>3폐업3폐업처리20030221<NA><NA>2002090202 676 4122<NA><NA>서울특별시 영등포구 양평동*가 일반번지 ***-*<NA><NA>21C PASS2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33180000200231801172429000520020912<NA>3폐업3폐업처리20021221<NA><NA>2002091202 6674 4200<NA><NA>서울특별시 노원구 일반 **-**<NA><NA>매일넷2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43180000200231801172429000620020914<NA>3폐업3폐업처리20040909<NA><NA>2002091402<NA><NA>서울특별시 영등포구 영등포동*가 일반 *-*<NA><NA>수림통상2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53180000200231801172429000720021015<NA>3폐업3폐업처리20041115<NA><NA>2002101502 670 3365<NA><NA>경기도 고양시일산동구 마두동 일반 **-*<NA><NA>TV 영상미디어2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63180000200231801172429000820021017<NA>3폐업3폐업처리20050309<NA><NA>2002101702 679 0386<NA><NA>서울특별시 영등포구 영등포동*가 ***-*<NA><NA>권훈통상2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73180000200231801172429000920021024<NA>3폐업3폐업처리20050309<NA><NA>2002102302 6332 6699<NA><NA>서울특별시 영등포구 대림동 일반번지 ***-*<NA><NA>청인에스티엔2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
83180000200231801172429001120021015<NA>3폐업3폐업처리20050309<NA><NA>2002101502 784 8884<NA><NA>서울특별시 영등포구 여의도동 일반번지 **-*<NA><NA>(주)클럽스카이2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
93180000200231801172429001520021127<NA>3폐업3폐업처리20050309<NA><NA>2002112702 795 5400<NA><NA>서울특별시 영등포구 영등포동*가 *-*<NA><NA>(주)에이스포유2008-02-01 13:17:51I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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672318000020233180254242000162023-09-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1544-0797<NA><NA>서울특별시 영등포구 양평동*가 ***-* TS빌딩서울특별시 영등포구 양평로 **, TS빌딩 *층,*층,*층 (양평동*가)07206주식회사 TS트릴리온2023-12-19 15:44:58U2022-11-01 22:01:00.0<NA>190807.871452448279.993287<NA><NA><NA><NA>
673318000020233180254242000172023-03-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1644-2448<NA><NA>서울특별시 영등포구 여의도동 ** 파크원서울특별시 영등포구 여의대로 ***, 파크원타워* **층 (여의도동)07335㈜티오더2023-11-07 14:35:30I2022-11-01 00:09:00.0<NA>193592.00038447092.629433<NA><NA><NA><NA>
674318000020233180254242000182023-12-11<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동*가 ** 송호빌딩서울특별시 영등포구 영등포로**길 *, 송호빌딩 *층 ***호 (영등포동*가)07301엔잡플렛폼2023-12-08 16:35:48I2022-11-01 23:00:00.0<NA>191420.294465446326.118899<NA><NA><NA><NA>
675318000020233180254242000192020-04-02<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-4055-5823<NA><NA>서울특별시 영등포구 영등포동*가 ***서울특별시 영등포구 영신로 ***, 영등포반도아이비밸리 *층 ***호 (영등포동*가)07251주식회사 미래비즈코리아2023-12-26 17:21:37I2022-11-01 22:08:00.0<NA>191287.220817446748.752489<NA><NA><NA><NA>
676318000020233180254242000202020-01-23<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-4632-5550<NA><NA>서울특별시 영등포구 양평동*가 ***-* 양평자이비즈타워서울특별시 영등포구 선유로 ***, **층 ****호, ****호 (양평동*가)07262주식회사 한국건강데이터 (Korea Health Data Corp.)2023-12-29 16:25:45I2022-11-01 21:01:00.0<NA>190280.387552446874.553138<NA><NA><NA><NA>
677318000020243180254242000012024-02-01<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2678-4455<NA><NA>서울특별시 영등포구 양평동*가 **-* 에이스테크노타워서울특별시 영등포구 선유로**길 **, 에이스테크노타워 ***호 (양평동*가)07271(주) 한강기전2024-01-31 16:14:01I2023-12-02 00:02:00.0<NA>190121.883535447160.550414<NA><NA><NA><NA>
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