Overview

Dataset statistics

Number of variables29
Number of observations1253
Missing cells11339
Missing cells (%)31.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory303.6 KiB
Average record size in memory248.1 B

Variable types

Categorical7
Numeric9
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18772/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (83.0%)Imbalance
재개업일자 is highly imbalanced (98.6%)Imbalance
폐업일자 has 745 (59.5%) missing valuesMissing
휴업시작일자 has 1246 (99.4%) missing valuesMissing
휴업종료일자 has 1246 (99.4%) missing valuesMissing
전화번호 has 343 (27.4%) missing valuesMissing
소재지면적 has 1253 (100.0%) missing valuesMissing
소재지우편번호 has 538 (42.9%) missing valuesMissing
지번주소 has 14 (1.1%) missing valuesMissing
도로명주소 has 207 (16.5%) missing valuesMissing
도로명우편번호 has 607 (48.4%) missing valuesMissing
업태구분명 has 1253 (100.0%) missing valuesMissing
좌표정보(X) has 199 (15.9%) missing valuesMissing
좌표정보(Y) has 199 (15.9%) missing valuesMissing
자산규모 has 745 (59.5%) missing valuesMissing
부채총액 has 746 (59.5%) missing valuesMissing
자본금 has 745 (59.5%) missing valuesMissing
판매방식명 has 1253 (100.0%) missing valuesMissing
자산규모 is highly skewed (γ1 = 20.43897556)Skewed
부채총액 is highly skewed (γ1 = 20.19105761)Skewed
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 182 (14.5%) zerosZeros
부채총액 has 362 (28.9%) zerosZeros
자본금 has 136 (10.9%) zerosZeros

Reproduction

Analysis started2024-04-06 11:36:53.662115
Analysis finished2024-04-06 11:36:54.963756
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
3200000
1253 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 1253
100.0%

Length

2024-04-06T20:36:55.088858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:36:55.282769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 1253
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0116361 × 1018
Minimum1.99632 × 1018
Maximum2.02432 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:36:55.482194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.99632 × 1018
5-th percentile2.00432 × 1018
Q12.00732 × 1018
median2.01032 × 1018
Q32.01532 × 1018
95-th percentile2.02132 × 1018
Maximum2.02432 × 1018
Range2.8000012 × 1016
Interquartile range (IQR)8.0000105 × 1015

Descriptive statistics

Standard deviation5.2549159 × 1015
Coefficient of variation (CV)0.0026122598
Kurtosis-0.56002648
Mean2.0116361 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.34276407
Sum-6.6239578 × 1018
Variance2.7614141 × 1031
MonotonicityStrictly increasing
2024-04-06T20:36:55.721670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996320010623200039 1
 
0.1%
2013320019123200058 1
 
0.1%
2013320019123200066 1
 
0.1%
2013320019123200065 1
 
0.1%
2013320019123200064 1
 
0.1%
2013320019123200062 1
 
0.1%
2013320019123200061 1
 
0.1%
2013320019123200060 1
 
0.1%
2013320019123200059 1
 
0.1%
2013320019123200057 1
 
0.1%
Other values (1243) 1243
99.2%
ValueCountFrequency (%)
1996320010623200039 1
0.1%
1997320010623200081 1
0.1%
1998320010623200129 1
0.1%
1999320010623200131 1
0.1%
1999320010623200136 1
0.1%
1999320010623200137 1
0.1%
1999320010623200140 1
0.1%
1999320010623200170 1
0.1%
2000320010623200203 1
0.1%
2000320010623200244 1
0.1%
ValueCountFrequency (%)
2024320022523200003 1
0.1%
2024320022523200002 1
0.1%
2024320022523200001 1
0.1%
2023320022523200019 1
0.1%
2023320022523200018 1
0.1%
2023320022523200017 1
0.1%
2023320022523200016 1
0.1%
2023320022523200015 1
0.1%
2023320022523200014 1
0.1%
2023320022523200013 1
0.1%

인허가일자
Date

Distinct976
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
Minimum1997-01-01 00:00:00
Maximum2024-03-27 00:00:00
2024-04-06T20:36:55.956589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:36:56.221157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
<NA>
1179 
20080826
 
71
20080101
 
2
20131101
 
1

Length

Max length8
Median length4
Mean length4.236233
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1179
94.1%
20080826 71
 
5.7%
20080101 2
 
0.2%
20131101 1
 
0.1%

Length

2024-04-06T20:36:56.456168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:36:56.672078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1179
94.1%
20080826 71
 
5.7%
20080101 2
 
0.2%
20131101 1
 
0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
4
628 
3
499 
1
113 
5
 
9
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row4
3rd row3
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 628
50.1%
3 499
39.8%
1 113
 
9.0%
5 9
 
0.7%
2 4
 
0.3%

Length

2024-04-06T20:36:56.888501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:36:57.096301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 628
50.1%
3 499
39.8%
1 113
 
9.0%
5 9
 
0.7%
2 4
 
0.3%

영업상태명
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
취소/말소/만료/정지/중지
628 
폐업
499 
영업/정상
113 
제외/삭제/전출
 
9
휴업
 
4

Length

Max length14
Median length14
Mean length8.3280128
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 628
50.1%
폐업 499
39.8%
영업/정상 113
 
9.0%
제외/삭제/전출 9
 
0.7%
휴업 4
 
0.3%

Length

2024-04-06T20:36:57.328934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:36:57.518381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 628
50.1%
폐업 499
39.8%
영업/정상 113
 
9.0%
제외/삭제/전출 9
 
0.7%
휴업 4
 
0.3%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6584198
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:36:57.675708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.186183
Coefficient of variation (CV)0.46929711
Kurtosis-1.5707202
Mean4.6584198
Median Absolute Deviation (MAD)3
Skewness-0.060655931
Sum5837
Variance4.7793959
MonotonicityNot monotonic
2024-04-06T20:36:57.877939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
7 554
44.2%
3 499
39.8%
1 113
 
9.0%
4 74
 
5.9%
5 9
 
0.7%
2 4
 
0.3%
ValueCountFrequency (%)
1 113
 
9.0%
2 4
 
0.3%
3 499
39.8%
4 74
 
5.9%
5 9
 
0.7%
7 554
44.2%
ValueCountFrequency (%)
7 554
44.2%
5 9
 
0.7%
4 74
 
5.9%
3 499
39.8%
2 4
 
0.3%
1 113
 
9.0%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
직권말소
554 
폐업처리
499 
정상영업
113 
직권취소
74 
타시군구이관
 
9

Length

Max length6
Median length4
Mean length4.0143655
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
직권말소 554
44.2%
폐업처리 499
39.8%
정상영업 113
 
9.0%
직권취소 74
 
5.9%
타시군구이관 9
 
0.7%
휴업처리 4
 
0.3%

Length

2024-04-06T20:36:58.164692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:36:58.453744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직권말소 554
44.2%
폐업처리 499
39.8%
정상영업 113
 
9.0%
직권취소 74
 
5.9%
타시군구이관 9
 
0.7%
휴업처리 4
 
0.3%

폐업일자
Date

MISSING 

Distinct455
Distinct (%)89.6%
Missing745
Missing (%)59.5%
Memory size9.9 KiB
Minimum2007-07-23 00:00:00
Maximum2024-03-25 00:00:00
2024-04-06T20:36:58.807716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:36:59.084012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing1246
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20140620
Minimum20071231
Maximum20210805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:36:59.373027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071231
5-th percentile20076924
Q120090418
median20130627
Q320195419
95-th percentile20210780
Maximum20210805
Range139574
Interquartile range (IQR)105000.5

Descriptive statistics

Standard deviation59659.032
Coefficient of variation (CV)0.0029621249
Kurtosis-2.2045154
Mean20140620
Median Absolute Deviation (MAD)49491
Skewness0.17988038
Sum1.4098434 × 108
Variance3.5592 × 109
MonotonicityNot monotonic
2024-04-06T20:36:59.595126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20210805 1
 
0.1%
20071231 1
 
0.1%
20090207 1
 
0.1%
20090630 1
 
0.1%
20130627 1
 
0.1%
20180118 1
 
0.1%
20210720 1
 
0.1%
(Missing) 1246
99.4%
ValueCountFrequency (%)
20071231 1
0.1%
20090207 1
0.1%
20090630 1
0.1%
20130627 1
0.1%
20180118 1
0.1%
20210720 1
0.1%
20210805 1
0.1%
ValueCountFrequency (%)
20210805 1
0.1%
20210720 1
0.1%
20180118 1
0.1%
20130627 1
0.1%
20090630 1
0.1%
20090207 1
0.1%
20071231 1
0.1%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing1246
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean20146725
Minimum20080331
Maximum20220804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:36:59.798177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080331
5-th percentile20083598
Q120091226
median20151231
Q320196130
95-th percentile20217872
Maximum20220804
Range140473
Interquartile range (IQR)104905

Descriptive statistics

Standard deviation59724.858
Coefficient of variation (CV)0.0029644945
Kurtosis-2.2077179
Mean20146725
Median Absolute Deviation (MAD)60000
Skewness0.086532974
Sum1.4102708 × 108
Variance3.5670586 × 109
MonotonicityNot monotonic
2024-04-06T20:36:59.980197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20220804 1
 
0.1%
20080331 1
 
0.1%
20091231 1
 
0.1%
20091220 1
 
0.1%
20151231 1
 
0.1%
20181231 1
 
0.1%
20211030 1
 
0.1%
(Missing) 1246
99.4%
ValueCountFrequency (%)
20080331 1
0.1%
20091220 1
0.1%
20091231 1
0.1%
20151231 1
0.1%
20181231 1
0.1%
20211030 1
0.1%
20220804 1
0.1%
ValueCountFrequency (%)
20220804 1
0.1%
20211030 1
0.1%
20181231 1
0.1%
20151231 1
0.1%
20091231 1
0.1%
20091220 1
0.1%
20080331 1
0.1%

재개업일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
<NA>
1250 
20070809
 
1
20070608
 
1
20130214
 
1

Length

Max length8
Median length4
Mean length4.009577
Min length4

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1250
99.8%
20070809 1
 
0.1%
20070608 1
 
0.1%
20130214 1
 
0.1%

Length

2024-04-06T20:37:00.261945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:37:00.507695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1250
99.8%
20070809 1
 
0.1%
20070608 1
 
0.1%
20130214 1
 
0.1%

전화번호
Text

MISSING 

Distinct861
Distinct (%)94.6%
Missing343
Missing (%)27.4%
Memory size9.9 KiB
2024-04-06T20:37:00.853137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.854945
Min length1

Characters and Unicode

Total characters9878
Distinct characters17
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique833 ?
Unique (%)91.5%

Sample

1st row839-6111
2nd row886-8422
3rd row873-3420
4th row02 841 6110
5th row02 876 1212
ValueCountFrequency (%)
02 280
 
19.0%
0000 23
 
1.6%
000 23
 
1.6%
888 18
 
1.2%
871 17
 
1.2%
882 15
 
1.0%
877 14
 
1.0%
883 13
 
0.9%
887 12
 
0.8%
889 11
 
0.7%
Other values (932) 1046
71.1%
2024-04-06T20:37:01.536840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1443
14.6%
8 1380
14.0%
2 1165
11.8%
- 988
10.0%
932
9.4%
7 782
7.9%
5 678
6.9%
3 561
 
5.7%
1 540
 
5.5%
6 523
 
5.3%
Other values (7) 886
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7951
80.5%
Dash Punctuation 988
 
10.0%
Space Separator 932
 
9.4%
Other Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1443
18.1%
8 1380
17.4%
2 1165
14.7%
7 782
9.8%
5 678
8.5%
3 561
 
7.1%
1 540
 
6.8%
6 523
 
6.6%
4 451
 
5.7%
9 428
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 988
100.0%
Space Separator
ValueCountFrequency (%)
932
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9878
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1443
14.6%
8 1380
14.0%
2 1165
11.8%
- 988
10.0%
932
9.4%
7 782
7.9%
5 678
6.9%
3 561
 
5.7%
1 540
 
5.5%
6 523
 
5.3%
Other values (7) 886
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1443
14.6%
8 1380
14.0%
2 1165
11.8%
- 988
10.0%
932
9.4%
7 782
7.9%
5 678
6.9%
3 561
 
5.7%
1 540
 
5.5%
6 523
 
5.3%
Other values (7) 886
9.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1253
Missing (%)100.0%
Memory size11.1 KiB

소재지우편번호
Text

MISSING 

Distinct125
Distinct (%)17.5%
Missing538
Missing (%)42.9%
Memory size9.9 KiB
2024-04-06T20:37:02.144103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0083916
Min length6

Characters and Unicode

Total characters4296
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

Unique63 ?
Unique (%)8.8%

Sample

1st row151015
2nd row151050
3rd row151050
4th row151050
5th row151050
ValueCountFrequency (%)
151050 244
34.1%
151015 83
 
11.6%
151010 45
 
6.3%
151080 18
 
2.5%
151057 17
 
2.4%
151836 13
 
1.8%
151058 13
 
1.8%
151822 10
 
1.4%
151843 9
 
1.3%
151800 9
 
1.3%
Other values (115) 254
35.5%
2024-04-06T20:37:02.919534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1633
38.0%
5 1106
25.7%
0 871
20.3%
8 258
 
6.0%
2 89
 
2.1%
9 86
 
2.0%
7 72
 
1.7%
3 70
 
1.6%
4 57
 
1.3%
6 48
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4290
99.9%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1633
38.1%
5 1106
25.8%
0 871
20.3%
8 258
 
6.0%
2 89
 
2.1%
9 86
 
2.0%
7 72
 
1.7%
3 70
 
1.6%
4 57
 
1.3%
6 48
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1633
38.0%
5 1106
25.7%
0 871
20.3%
8 258
 
6.0%
2 89
 
2.1%
9 86
 
2.0%
7 72
 
1.7%
3 70
 
1.6%
4 57
 
1.3%
6 48
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1633
38.0%
5 1106
25.7%
0 871
20.3%
8 258
 
6.0%
2 89
 
2.1%
9 86
 
2.0%
7 72
 
1.7%
3 70
 
1.6%
4 57
 
1.3%
6 48
 
1.1%

지번주소
Text

MISSING 

Distinct763
Distinct (%)61.6%
Missing14
Missing (%)1.1%
Memory size9.9 KiB
2024-04-06T20:37:03.326298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length27.517353
Min length14

Characters and Unicode

Total characters34094
Distinct characters295
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

Unique634 ?
Unique (%)51.2%

Sample

1st row서울특별시 관악구 신림동 ***번지 *호
2nd row서울특별시 관악구 봉천동 ****번지 *호 원당빌딩*층 ***호
3rd row서울특별시 관악구 신림동 ****번지 **호 *층
4th row서울시 관악구 서원동 **-***
5th row서울특별시 관악구 봉천동 7번지 2호 1층
ValueCountFrequency (%)
관악구 1233
17.3%
호 1179
16.5%
서울특별시 1043
14.6%
번지 941
13.2%
봉천동 494
6.9%
층 355
 
5.0%
신림동 335
 
4.7%
222
 
3.1%
서울시 195
 
2.7%
봉천*동 69
 
1.0%
Other values (440) 1081
15.1%
2024-04-06T20:37:04.032050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8043
23.6%
5949
17.4%
동 1307
 
3.8%
서 1292
 
3.8%
관 1273
 
3.7%
악 1262
 
3.7%
시 1245
 
3.7%
구 1245
 
3.7%
울 1240
 
3.6%
호 1225
 
3.6%
Other values (285) 10013
29.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19665
57.7%
Other Punctuation 8054
23.6%
Space Separator 5949
 
17.4%
Dash Punctuation 297
 
0.9%
Uppercase Letter 53
 
0.2%
Close Punctuation 24
 
0.1%
Open Punctuation 24
 
0.1%
Decimal Number 21
 
0.1%
Lowercase Letter 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1307
 
6.6%
서 1292
 
6.6%
관 1273
 
6.5%
악 1262
 
6.4%
시 1245
 
6.3%
구 1245
 
6.3%
울 1240
 
6.3%
호 1225
 
6.2%
별 1044
 
5.3%
특 1043
 
5.3%
Other values (253) 7489
38.1%
Uppercase Letter
ValueCountFrequency (%)
B 22
41.5%
T 10
18.9%
K 9
17.0%
S 3
 
5.7%
G 2
 
3.8%
I 2
 
3.8%
D 2
 
3.8%
A 2
 
3.8%
C 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 7
33.3%
2 4
19.0%
7 3
14.3%
9 3
14.3%
8 1
 
4.8%
5 1
 
4.8%
4 1
 
4.8%
3 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
* 8043
99.9%
, 8
 
0.1%
. 1
 
< 0.1%
/ 1
 
< 0.1%
@ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
b 1
16.7%
c 1
16.7%
k 1
16.7%
w 1
16.7%
Space Separator
ValueCountFrequency (%)
5949
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19665
57.7%
Common 14370
42.1%
Latin 59
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1307
 
6.6%
서 1292
 
6.6%
관 1273
 
6.5%
악 1262
 
6.4%
시 1245
 
6.3%
구 1245
 
6.3%
울 1240
 
6.3%
호 1225
 
6.2%
별 1044
 
5.3%
특 1043
 
5.3%
Other values (253) 7489
38.1%
Common
ValueCountFrequency (%)
* 8043
56.0%
5949
41.4%
- 297
 
2.1%
) 24
 
0.2%
( 24
 
0.2%
, 8
 
0.1%
1 7
 
< 0.1%
2 4
 
< 0.1%
7 3
 
< 0.1%
9 3
 
< 0.1%
Other values (8) 8
 
0.1%
Latin
ValueCountFrequency (%)
B 22
37.3%
T 10
16.9%
K 9
15.3%
S 3
 
5.1%
s 2
 
3.4%
G 2
 
3.4%
I 2
 
3.4%
D 2
 
3.4%
A 2
 
3.4%
C 1
 
1.7%
Other values (4) 4
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19665
57.7%
ASCII 14429
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8043
55.7%
5949
41.2%
- 297
 
2.1%
) 24
 
0.2%
( 24
 
0.2%
B 22
 
0.2%
T 10
 
0.1%
K 9
 
0.1%
, 8
 
0.1%
1 7
 
< 0.1%
Other values (22) 36
 
0.2%
Hangul
ValueCountFrequency (%)
동 1307
 
6.6%
서 1292
 
6.6%
관 1273
 
6.5%
악 1262
 
6.4%
시 1245
 
6.3%
구 1245
 
6.3%
울 1240
 
6.3%
호 1225
 
6.2%
별 1044
 
5.3%
특 1043
 
5.3%
Other values (253) 7489
38.1%

도로명주소
Text

MISSING 

Distinct734
Distinct (%)70.2%
Missing207
Missing (%)16.5%
Memory size9.9 KiB
2024-04-06T20:37:04.569334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length44
Mean length32.325048
Min length17

Characters and Unicode

Total characters33812
Distinct characters300
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique620 ?
Unique (%)59.3%

Sample

1st row서울특별시 관악구 남부순환로 **** (신림동)
2nd row서울특별시 관악구 봉천로 ***, ***호 (봉천동, 원당빌딩)
3rd row서울특별시 관악구 신림로 *** (신림동,*층)
4th row서울특별시 관악구 관악로 300, 1층 (봉천동, 동보빌딩)
5th row서울특별시 관악구 남부순환로 ****-*, ***호 (봉천동)
ValueCountFrequency (%)
1068
16.7%
서울특별시 1046
16.3%
관악구 1039
16.2%
봉천동 441
 
6.9%
호 370
 
5.8%
층 352
 
5.5%
남부순환로 347
 
5.4%
신림동 276
 
4.3%
봉천로 80
 
1.2%
신림로**길 52
 
0.8%
Other values (534) 1337
20.9%
2024-04-06T20:37:05.464515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5618
16.6%
5362
 
15.9%
, 1173
 
3.5%
관 1152
 
3.4%
악 1133
 
3.4%
동 1124
 
3.3%
서 1067
 
3.2%
시 1065
 
3.1%
별 1047
 
3.1%
울 1046
 
3.1%
Other values (290) 14025
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19380
57.3%
Other Punctuation 6793
 
20.1%
Space Separator 5362
 
15.9%
Close Punctuation 1045
 
3.1%
Open Punctuation 1045
 
3.1%
Dash Punctuation 100
 
0.3%
Uppercase Letter 49
 
0.1%
Decimal Number 30
 
0.1%
Lowercase Letter 6
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 1152
 
5.9%
악 1133
 
5.8%
동 1124
 
5.8%
서 1067
 
5.5%
시 1065
 
5.5%
별 1047
 
5.4%
울 1046
 
5.4%
특 1046
 
5.4%
구 1045
 
5.4%
로 924
 
4.8%
Other values (257) 8731
45.1%
Uppercase Letter
ValueCountFrequency (%)
B 25
51.0%
T 6
 
12.2%
K 5
 
10.2%
S 3
 
6.1%
A 2
 
4.1%
G 2
 
4.1%
C 2
 
4.1%
D 2
 
4.1%
I 2
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 7
23.3%
2 4
13.3%
7 4
13.3%
0 4
13.3%
4 3
10.0%
3 3
10.0%
6 2
 
6.7%
5 2
 
6.7%
8 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
w 1
16.7%
c 1
16.7%
k 1
16.7%
b 1
16.7%
Other Punctuation
ValueCountFrequency (%)
* 5618
82.7%
, 1173
 
17.3%
/ 1
 
< 0.1%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5362
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1045
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1045
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19380
57.3%
Common 14376
42.5%
Latin 56
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 1152
 
5.9%
악 1133
 
5.8%
동 1124
 
5.8%
서 1067
 
5.5%
시 1065
 
5.5%
별 1047
 
5.4%
울 1046
 
5.4%
특 1046
 
5.4%
구 1045
 
5.4%
로 924
 
4.8%
Other values (257) 8731
45.1%
Common
ValueCountFrequency (%)
* 5618
39.1%
5362
37.3%
, 1173
 
8.2%
) 1045
 
7.3%
( 1045
 
7.3%
- 100
 
0.7%
1 7
 
< 0.1%
2 4
 
< 0.1%
7 4
 
< 0.1%
0 4
 
< 0.1%
Other values (8) 14
 
0.1%
Latin
ValueCountFrequency (%)
B 25
44.6%
T 6
 
10.7%
K 5
 
8.9%
S 3
 
5.4%
s 2
 
3.6%
A 2
 
3.6%
G 2
 
3.6%
C 2
 
3.6%
D 2
 
3.6%
I 2
 
3.6%
Other values (5) 5
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19380
57.3%
ASCII 14431
42.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5618
38.9%
5362
37.2%
, 1173
 
8.1%
) 1045
 
7.2%
( 1045
 
7.2%
- 100
 
0.7%
B 25
 
0.2%
1 7
 
< 0.1%
T 6
 
< 0.1%
K 5
 
< 0.1%
Other values (22) 45
 
0.3%
Hangul
ValueCountFrequency (%)
관 1152
 
5.9%
악 1133
 
5.8%
동 1124
 
5.8%
서 1067
 
5.5%
시 1065
 
5.5%
별 1047
 
5.4%
울 1046
 
5.4%
특 1046
 
5.4%
구 1045
 
5.4%
로 924
 
4.8%
Other values (257) 8731
45.1%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct185
Distinct (%)28.6%
Missing607
Missing (%)48.4%
Memory size9.9 KiB
2024-04-06T20:37:06.055766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length5.5092879
Min length5

Characters and Unicode

Total characters3559
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

Unique86 ?
Unique (%)13.3%

Sample

1st row151015
2nd row151050
3rd row151050
4th row151891
5th row151852
ValueCountFrequency (%)
151050 114
 
17.6%
151015 44
 
6.8%
08786 22
 
3.4%
08787 10
 
1.5%
151800 10
 
1.5%
08784 10
 
1.5%
08754 10
 
1.5%
08774 9
 
1.4%
08789 9
 
1.4%
08788 8
 
1.2%
Other values (175) 400
61.9%
2024-04-06T20:37:07.103664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 763
21.4%
0 738
20.7%
8 624
17.5%
5 576
16.2%
7 363
10.2%
4 115
 
3.2%
6 114
 
3.2%
9 104
 
2.9%
2 80
 
2.2%
3 76
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3553
99.8%
Dash Punctuation 6
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 763
21.5%
0 738
20.8%
8 624
17.6%
5 576
16.2%
7 363
10.2%
4 115
 
3.2%
6 114
 
3.2%
9 104
 
2.9%
2 80
 
2.3%
3 76
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3559
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 763
21.4%
0 738
20.7%
8 624
17.5%
5 576
16.2%
7 363
10.2%
4 115
 
3.2%
6 114
 
3.2%
9 104
 
2.9%
2 80
 
2.2%
3 76
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 763
21.4%
0 738
20.7%
8 624
17.5%
5 576
16.2%
7 363
10.2%
4 115
 
3.2%
6 114
 
3.2%
9 104
 
2.9%
2 80
 
2.2%
3 76
 
2.1%

사업장명
Text

Distinct1204
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
2024-04-06T20:37:07.657912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length7.5458899
Min length2

Characters and Unicode

Total characters9455
Distinct characters573
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1162 ?
Unique (%)92.7%

Sample

1st row기아자동차토리대리점
2nd row유니베라
3rd row마임신림중부지사
4th row일진인턴
5th row기아봉천대리점(주)
ValueCountFrequency (%)
주식회사 194
 
11.5%
인셀덤 17
 
1.0%
마임 16
 
0.9%
주 8
 
0.5%
관악지점 8
 
0.5%
관악지사 7
 
0.4%
코리아 6
 
0.4%
라이프 5
 
0.3%
유니베라 5
 
0.3%
케어 4
 
0.2%
Other values (1321) 1415
84.0%
2024-04-06T20:37:08.579146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
432
 
4.6%
주 431
 
4.6%
사 329
 
3.5%
이 326
 
3.4%
) 264
 
2.8%
( 262
 
2.8%
회 226
 
2.4%
스 225
 
2.4%
식 224
 
2.4%
리 192
 
2.0%
Other values (563) 6544
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7993
84.5%
Space Separator 432
 
4.6%
Close Punctuation 264
 
2.8%
Open Punctuation 262
 
2.8%
Uppercase Letter 235
 
2.5%
Lowercase Letter 121
 
1.3%
Other Symbol 60
 
0.6%
Decimal Number 50
 
0.5%
Other Punctuation 31
 
0.3%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 431
 
5.4%
사 329
 
4.1%
이 326
 
4.1%
회 226
 
2.8%
스 225
 
2.8%
식 224
 
2.8%
리 192
 
2.4%
아 174
 
2.2%
지 148
 
1.9%
에 140
 
1.8%
Other values (497) 5578
69.8%
Uppercase Letter
ValueCountFrequency (%)
S 29
 
12.3%
L 18
 
7.7%
T 17
 
7.2%
C 16
 
6.8%
M 15
 
6.4%
E 14
 
6.0%
B 13
 
5.5%
A 13
 
5.5%
O 12
 
5.1%
I 12
 
5.1%
Other values (13) 76
32.3%
Lowercase Letter
ValueCountFrequency (%)
e 16
13.2%
s 11
 
9.1%
a 11
 
9.1%
t 9
 
7.4%
i 9
 
7.4%
o 7
 
5.8%
n 7
 
5.8%
r 6
 
5.0%
m 6
 
5.0%
c 6
 
5.0%
Other values (13) 33
27.3%
Decimal Number
ValueCountFrequency (%)
0 10
20.0%
8 9
18.0%
1 7
14.0%
3 7
14.0%
5 6
12.0%
6 4
 
8.0%
7 3
 
6.0%
2 2
 
4.0%
4 2
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 16
51.6%
& 11
35.5%
/ 2
 
6.5%
' 1
 
3.2%
, 1
 
3.2%
Space Separator
ValueCountFrequency (%)
432
100.0%
Close Punctuation
ValueCountFrequency (%)
) 264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 262
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8053
85.2%
Common 1046
 
11.1%
Latin 356
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 431
 
5.4%
사 329
 
4.1%
이 326
 
4.0%
회 226
 
2.8%
스 225
 
2.8%
식 224
 
2.8%
리 192
 
2.4%
아 174
 
2.2%
지 148
 
1.8%
에 140
 
1.7%
Other values (498) 5638
70.0%
Latin
ValueCountFrequency (%)
S 29
 
8.1%
L 18
 
5.1%
T 17
 
4.8%
C 16
 
4.5%
e 16
 
4.5%
M 15
 
4.2%
E 14
 
3.9%
B 13
 
3.7%
A 13
 
3.7%
O 12
 
3.4%
Other values (36) 193
54.2%
Common
ValueCountFrequency (%)
432
41.3%
) 264
25.2%
( 262
25.0%
. 16
 
1.5%
& 11
 
1.1%
0 10
 
1.0%
8 9
 
0.9%
1 7
 
0.7%
3 7
 
0.7%
5 6
 
0.6%
Other values (9) 22
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7993
84.5%
ASCII 1402
 
14.8%
None 60
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
432
30.8%
) 264
18.8%
( 262
18.7%
S 29
 
2.1%
L 18
 
1.3%
T 17
 
1.2%
. 16
 
1.1%
C 16
 
1.1%
e 16
 
1.1%
M 15
 
1.1%
Other values (55) 317
22.6%
Hangul
ValueCountFrequency (%)
주 431
 
5.4%
사 329
 
4.1%
이 326
 
4.1%
회 226
 
2.8%
스 225
 
2.8%
식 224
 
2.8%
리 192
 
2.4%
아 174
 
2.2%
지 148
 
1.9%
에 140
 
1.8%
Other values (497) 5578
69.8%
None
ValueCountFrequency (%)
㈜ 60
100.0%

최종수정일자
Date

Distinct1250
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
Minimum2007-09-04 17:54:55
Maximum2024-03-27 13:45:58
2024-04-06T20:37:08.857036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:37:09.544649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
I
916 
U
337 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 916
73.1%
U 337
 
26.9%

Length

2024-04-06T20:37:09.803997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:37:10.012184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 916
73.1%
u 337
 
26.9%

데이터갱신일자
Date

Distinct203
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:09:00
2024-04-06T20:37:10.208544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:37:10.471202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1253
Missing (%)100.0%
Memory size11.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct638
Distinct (%)60.5%
Missing199
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean194795.27
Minimum186812.01
Maximum212882.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:37:10.733398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum186812.01
5-th percentile191709.72
Q1193723.26
median194863.01
Q3195935.55
95-th percentile197324.7
Maximum212882.26
Range26070.248
Interquartile range (IQR)2212.2929

Descriptive statistics

Standard deviation1770.9268
Coefficient of variation (CV)0.0090912207
Kurtosis10.539823
Mean194795.27
Median Absolute Deviation (MAD)1116.1755
Skewness0.94801568
Sum2.0531421 × 108
Variance3136181.6
MonotonicityNot monotonic
2024-04-06T20:37:10.955116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195588.796492288 26
 
2.1%
195445.432424349 23
 
1.8%
196104.971514365 15
 
1.2%
195635.738009117 11
 
0.9%
196492.988520778 10
 
0.8%
195519.229019438 10
 
0.8%
194889.614151264 10
 
0.8%
194879.596231677 9
 
0.7%
194548.651692342 8
 
0.6%
195935.552122359 8
 
0.6%
Other values (628) 924
73.7%
(Missing) 199
 
15.9%
ValueCountFrequency (%)
186812.009261555 1
0.1%
191036.011583196 1
0.1%
191076.428759797 1
0.1%
191084.937997691 1
0.1%
191131.049995846 1
0.1%
191161.849432287 1
0.1%
191164.635930111 1
0.1%
191204.884621244 2
0.2%
191210.00657717 1
0.1%
191210.078732513 2
0.2%
ValueCountFrequency (%)
212882.257399963 1
 
0.1%
204480.307828948 1
 
0.1%
198297.240031378 2
 
0.2%
198295.195735536 1
 
0.1%
198287.426869112 1
 
0.1%
198284.078546351 7
0.6%
198278.931088754 1
 
0.1%
198269.718342004 3
0.2%
198264.540439629 4
0.3%
198257.694991475 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct638
Distinct (%)60.5%
Missing199
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean442078.27
Minimum439663.59
Maximum453132.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:37:11.235236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439663.59
5-th percentile440980.38
Q1441753.56
median442165.38
Q3442430.65
95-th percentile442872.61
Maximum453132.43
Range13468.845
Interquartile range (IQR)677.09116

Descriptive statistics

Standard deviation720.80637
Coefficient of variation (CV)0.0016304949
Kurtosis56.130644
Mean442078.27
Median Absolute Deviation (MAD)314.53607
Skewness3.3973002
Sum4.659505 × 108
Variance519561.83
MonotonicityNot monotonic
2024-04-06T20:37:11.580993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442098.372819317 26
 
2.1%
442127.015243919 23
 
1.8%
441917.723076494 15
 
1.2%
442172.892032644 11
 
0.9%
441794.26194868 10
 
0.8%
442187.250439123 10
 
0.8%
442198.112113216 10
 
0.8%
442483.131081868 9
 
0.7%
442330.324311379 8
 
0.6%
441994.489322519 8
 
0.6%
Other values (628) 924
73.7%
(Missing) 199
 
15.9%
ValueCountFrequency (%)
439663.585570958 2
 
0.2%
439816.999224208 1
 
0.1%
439946.302906409 1
 
0.1%
439971.084406353 1
 
0.1%
440040.309820942 1
 
0.1%
440065.059366816 5
0.4%
440079.037787497 2
 
0.2%
440106.431628897 1
 
0.1%
440133.80598 2
 
0.2%
440167.803504363 1
 
0.1%
ValueCountFrequency (%)
453132.430838856 1
0.1%
447729.841653015 1
0.1%
445014.002982422 1
0.1%
444672.281771242 1
0.1%
443548.818562693 1
0.1%
443513.655954844 1
0.1%
443368.907638238 1
0.1%
443341.379446435 1
0.1%
443338.973622861 1
0.1%
443322.295671891 1
0.1%

자산규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct81
Distinct (%)15.9%
Missing745
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean2.1870219 × 109
Minimum0
Maximum7.6193133 × 1011
Zeros182
Zeros (%)14.5%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:37:11.861412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9
Q350000000
95-th percentile5.0949889 × 108
Maximum7.6193133 × 1011
Range7.6193133 × 1011
Interquartile range (IQR)50000000

Descriptive statistics

Standard deviation3.5110598 × 1010
Coefficient of variation (CV)16.054067
Kurtosis436.61394
Mean2.1870219 × 109
Median Absolute Deviation (MAD)9
Skewness20.438976
Sum1.1110071 × 1012
Variance1.2327541 × 1021
MonotonicityNot monotonic
2024-04-06T20:37:12.143960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 182
 
14.5%
9 75
 
6.0%
50000000 63
 
5.0%
100000000 29
 
2.3%
10000000 26
 
2.1%
20000000 12
 
1.0%
150000000 8
 
0.6%
200000000 7
 
0.6%
300000000 7
 
0.6%
30000000 7
 
0.6%
Other values (71) 92
 
7.3%
(Missing) 745
59.5%
ValueCountFrequency (%)
0 182
14.5%
1 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%
6 1
 
0.1%
9 75
6.0%
1000 1
 
0.1%
3000 1
 
0.1%
4400 1
 
0.1%
1000000 5
 
0.4%
ValueCountFrequency (%)
761931332656 1
0.1%
200000000000 1
0.1%
80636335148 1
0.1%
13550206439 1
0.1%
12700000000 1
0.1%
5000000000 1
0.1%
2000000000 1
0.1%
1611119230 1
0.1%
1610814437 1
0.1%
1410000000 1
0.1%

부채총액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct53
Distinct (%)10.5%
Missing746
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean1.9037342 × 108
Minimum0
Maximum6.0254239 × 1010
Zeros362
Zeros (%)28.9%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:37:12.429839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile1.4591957 × 108
Maximum6.0254239 × 1010
Range6.0254239 × 1010
Interquartile range (IQR)9

Descriptive statistics

Standard deviation2.7883073 × 109
Coefficient of variation (CV)14.646516
Kurtosis429.28611
Mean1.9037342 × 108
Median Absolute Deviation (MAD)0
Skewness20.191058
Sum9.6519324 × 1010
Variance7.7746577 × 1018
MonotonicityNot monotonic
2024-04-06T20:37:12.709922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 362
28.9%
9 78
 
6.2%
10000000 5
 
0.4%
100000000 4
 
0.3%
30000000 4
 
0.3%
50000000 3
 
0.2%
200000000 2
 
0.2%
150000000 2
 
0.2%
2000000 2
 
0.2%
40000000 2
 
0.2%
Other values (43) 43
 
3.4%
(Missing) 746
59.5%
ValueCountFrequency (%)
0 362
28.9%
1 1
 
0.1%
3 1
 
0.1%
6 1
 
0.1%
9 78
 
6.2%
5500 1
 
0.1%
997180 1
 
0.1%
2000000 2
 
0.2%
5000000 1
 
0.1%
6200000 1
 
0.1%
ValueCountFrequency (%)
60254238874 1
0.1%
14284197575 1
0.1%
10561889561 1
0.1%
1210541310 1
0.1%
951058695 1
0.1%
838351711 1
0.1%
800000000 1
0.1%
786091389 1
0.1%
580000000 1
0.1%
446000000 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct58
Distinct (%)11.4%
Missing745
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean2.4949413 × 108
Minimum0
Maximum5.6438298 × 1010
Zeros136
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size11.1 KiB
2024-04-06T20:37:12.951874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10000000
Q350000000
95-th percentile3 × 108
Maximum5.6438298 × 1010
Range5.6438298 × 1010
Interquartile range (IQR)50000000

Descriptive statistics

Standard deviation2.6835494 × 109
Coefficient of variation (CV)10.755962
Kurtosis383.52421
Mean2.4949413 × 108
Median Absolute Deviation (MAD)10000000
Skewness18.774678
Sum1.2674302 × 1011
Variance7.2014372 × 1018
MonotonicityNot monotonic
2024-04-06T20:37:13.237709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 136
 
10.9%
50000000 105
 
8.4%
9 57
 
4.5%
100000000 36
 
2.9%
10000000 36
 
2.9%
200000000 17
 
1.4%
20000000 12
 
1.0%
150000000 10
 
0.8%
30000000 10
 
0.8%
300000000 8
 
0.6%
Other values (48) 81
 
6.5%
(Missing) 745
59.5%
ValueCountFrequency (%)
0 136
10.9%
3 2
 
0.2%
5 1
 
0.1%
6 1
 
0.1%
9 57
4.5%
1000 1
 
0.1%
3000 1
 
0.1%
5000 1
 
0.1%
1000000 7
 
0.6%
2000000 3
 
0.2%
ValueCountFrequency (%)
56438298000 1
0.1%
14869685000 1
0.1%
12700000000 1
0.1%
9013055000 1
0.1%
5000000000 1
0.1%
1000000000 1
0.1%
999990000 1
0.1%
940000000 1
0.1%
830000000 1
0.1%
620000000 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1253
Missing (%)100.0%
Memory size11.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03200000199632001062320003920080527<NA>1영업/정상1정상영업<NA><NA><NA><NA>839-6111<NA>151015서울특별시 관악구 신림동 ***번지 *호서울특별시 관악구 남부순환로 **** (신림동)151015기아자동차토리대리점2016-12-15 19:22:18I2018-08-31 23:59:59.0<NA>191592.154184442041.324924<NA><NA><NA><NA>
13200000199732001062320008119970101<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>886-8422<NA>151050서울특별시 관악구 봉천동 ****번지 *호 원당빌딩*층 ***호서울특별시 관악구 봉천로 ***, ***호 (봉천동, 원당빌딩)151050유니베라2016-03-22 11:11:26I2018-08-31 23:59:59.0<NA>196753.480707441530.298393<NA><NA><NA><NA>
23200000199832001062320012919980101<NA>3폐업3폐업처리20130821<NA><NA><NA>873-3420<NA><NA>서울특별시 관악구 신림동 ****번지 **호 *층서울특별시 관악구 신림로 *** (신림동,*층)<NA>마임신림중부지사2013-08-21 15:14:44I2018-08-31 23:59:59.0<NA>193636.325447442867.66597450000000050000000<NA>
33200000199932001062320013119990104<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 841 6110<NA><NA>서울시 관악구 서원동 **-***<NA><NA>일진인턴2014-11-07 13:45:14I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43200000199932001062320013619990629<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 876 1212<NA>151050서울특별시 관악구 봉천동 7번지 2호 1층서울특별시 관악구 관악로 300, 1층 (봉천동, 동보빌딩)151050기아봉천대리점(주)2022-12-09 19:09:13U2021-11-01 23:01:00.0<NA>196131.90385443138.559097<NA><NA><NA><NA>
53200000199932001062320013719990101<NA>3폐업3폐업처리20130910<NA><NA><NA>02 852 4370<NA><NA>서울시 관악구 조원동 ***-** 정원빌딩*층<NA><NA>아모레신림특약점2014-01-24 17:05:28I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63200000199932001062320014019990320<NA>3폐업3폐업처리20130613<NA><NA><NA>02 873 2853<NA>151050서울특별시 관악구 봉천동 ****번지 **호 ***호서울특별시 관악구 남부순환로 ****-*, ***호 (봉천동)<NA>마임 사당지사2013-06-14 09:41:54I2018-08-31 23:59:59.0<NA>196653.908912441720.428446<NA><NA><NA><NA>
73200000199932001062320017019990104<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 871 8102<NA><NA>서울시 관악구 은천동 ***-**<NA><NA>현대봉천판매대리점2014-11-07 13:44:06I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
83200000200032001062320020320000101<NA>3폐업3폐업처리20130830<NA><NA><NA>02 879 1914<NA>151050서울특별시 관악구 봉천동 ****번지 *호 ***서울특별시 관악구 남부순환로 **** (봉천동,***)<NA>마임서울대지사2014-01-24 16:09:54I2018-08-31 23:59:59.0<NA>196193.652287441868.220355999<NA>
93200000200032001062320024420000102<NA>3폐업3폐업처리20130718<NA><NA><NA>02 592 3562<NA><NA>서울특별시 관악구 신림동 ***번지 **호 *층서울특별시 관악구 난곡로 *** (신림동,*층)<NA>윤선생영어교실2014-02-25 14:57:43I2018-08-31 23:59:59.0<NA>192688.341125441260.076331<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
1243320000020233200225232000132021-09-29<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 **-***서울특별시 관악구 남부순환로 ****, *층 (신림동)08780다이아린쇼핑2023-10-10 10:27:47U2022-10-30 23:02:00.0<NA>194413.568237442408.07554<NA><NA><NA><NA>
1244320000020233200225232000142022-08-30<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-887-7787<NA><NA>서울특별시 관악구 봉천동 ***-** 정암빌딩서울특별시 관악구 은천로 **, 정암빌딩 *층 (봉천동)08717라이프 케어2023-10-11 14:09:56I2022-10-30 23:03:00.0<NA>194497.191875442695.980426<NA><NA><NA><NA>
1245320000020233200225232000152023-10-12<NA>5제외/삭제/전출5타시군구이관2023-11-06<NA><NA><NA>02-882-4100<NA><NA>서울특별시 관악구 신림동 ****-* 르네상스 복합쇼핑몰서울특별시 관악구 신림로 ***, 르네상스 복합쇼핑몰 *층 씨 ***-*호 (신림동)08754피엘에이치엘 주식회사(PLHL)2023-11-06 13:26:55U2022-11-01 00:08:00.0<NA>193746.833838442510.775086<NA><NA><NA><NA>
1246320000020233200225232000162023-10-17<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ****-**서울특별시 관악구 장군봉*길 ** (봉천동)08784엘름미용실(엘름스타컴즈)2023-10-17 14:35:43I2022-10-30 23:09:00.0<NA>194727.122637441948.428613<NA><NA><NA><NA>
1247320000020233200225232000172023-10-25<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ***-*서울특별시 관악구 봉천로 ***, *층 (봉천동)08750주식회사 에벤에셀월드2023-10-25 13:19:07I2022-10-30 22:07:00.0<NA>194726.630865442408.540818<NA><NA><NA><NA>
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1249320000020233200225232000192020-02-11<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ***-* 대우디오슈페리움*단지서울특별시 관악구 관악로 ***, ***-**호 (봉천동, 대우디오슈페리움*단지)08788홍선생미술 관악지사2023-12-20 13:22:42I2022-11-01 22:03:00.0<NA>195785.625847442009.829042<NA><NA><NA><NA>
1250320000020243200225232000012024-01-11<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-4109-0072<NA><NA>서울특별시 관악구 신림동 ****-* 명륜당독서실서울특별시 관악구 호암로**가길 **, 명륜당독서실 *층 ***호 (신림동)08812주식회사 아토맘 코리아2024-01-11 13:49:38I2023-11-30 23:03:00.0<NA>194007.514747440756.136415<NA><NA><NA><NA>
1251320000020243200225232000022024-02-01<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ***-** 관악센츄리타워서울특별시 관악구 남부순환로 ****, 관악센츄리타워 제**층 제**호 (봉천동)08787주식회사 액츠4322024-02-01 09:49:56I2023-12-02 00:03:00.0<NA>195588.796492442098.372819<NA><NA><NA><NA>
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