Overview

Dataset statistics

Number of variables29
Number of observations944
Missing cells9263
Missing cells (%)33.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory226.0 KiB
Average record size in memory245.1 B

Variable types

Categorical7
Text7
DateTime6
Numeric6
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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-18756/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has constant value ""Constant
휴업시작일자 is highly imbalanced (98.2%)Imbalance
휴업종료일자 is highly imbalanced (98.2%)Imbalance
인허가취소일자 has 943 (99.9%) missing valuesMissing
폐업일자 has 529 (56.0%) missing valuesMissing
재개업일자 has 940 (99.6%) missing valuesMissing
전화번호 has 157 (16.6%) missing valuesMissing
소재지면적 has 944 (100.0%) missing valuesMissing
소재지우편번호 has 521 (55.2%) missing valuesMissing
도로명주소 has 297 (31.5%) missing valuesMissing
도로명우편번호 has 542 (57.4%) missing valuesMissing
업태구분명 has 944 (100.0%) missing valuesMissing
좌표정보(X) has 286 (30.3%) missing valuesMissing
좌표정보(Y) has 286 (30.3%) missing valuesMissing
자산규모 has 640 (67.8%) missing valuesMissing
부채총액 has 642 (68.0%) missing valuesMissing
자본금 has 640 (67.8%) missing valuesMissing
판매방식명 has 944 (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 123 (13.0%) zerosZeros
부채총액 has 210 (22.2%) zerosZeros
자본금 has 112 (11.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:09:41.458579
Analysis finished2024-05-11 06:09:43.319022
Duration1.86 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
3040000
944 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 944
100.0%

Length

2024-05-11T15:09:43.444617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:43.601069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 944
100.0%

관리번호
Text

UNIQUE 

Distinct944
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T15:09:43.882112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length18.997881
Min length17

Characters and Unicode

Total characters17934
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

Unique944 ?
Unique (%)100.0%

Sample

1st row1996304010323200008
2nd row1996304010323200013
3rd row1996304010323200027
4th row1996304010323200028
5th row1997304010323200033
ValueCountFrequency (%)
1996304010323200008 1
 
0.1%
2013304016823200002 1
 
0.1%
2013304016823200018 1
 
0.1%
2012304016823200023 1
 
0.1%
2012304016823200024 1
 
0.1%
2012304016823200025 1
 
0.1%
2012304016823200026 1
 
0.1%
2012304016823200027 1
 
0.1%
2012304016823200028 1
 
0.1%
2012304016823200029 1
 
0.1%
Other values (934) 934
98.9%
2024-05-11T15:09:44.509788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6843
38.2%
2 3248
18.1%
3 2795
15.6%
1 1788
 
10.0%
4 1231
 
6.9%
9 491
 
2.7%
8 444
 
2.5%
6 438
 
2.4%
5 369
 
2.1%
7 286
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17933
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6843
38.2%
2 3248
18.1%
3 2795
15.6%
1 1788
 
10.0%
4 1231
 
6.9%
9 491
 
2.7%
8 444
 
2.5%
6 438
 
2.4%
5 369
 
2.1%
7 286
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6843
38.2%
2 3248
18.1%
3 2795
15.6%
1 1788
 
10.0%
4 1231
 
6.9%
9 491
 
2.7%
8 444
 
2.5%
6 438
 
2.4%
5 369
 
2.1%
7 286
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6843
38.2%
2 3248
18.1%
3 2795
15.6%
1 1788
 
10.0%
4 1231
 
6.9%
9 491
 
2.7%
8 444
 
2.5%
6 438
 
2.4%
5 369
 
2.1%
7 286
 
1.6%

인허가일자
Date

Distinct828
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Minimum1996-10-29 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T15:09:44.758246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:44.968235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing943
Missing (%)99.9%
Memory size7.5 KiB
Minimum2023-07-06 00:00:00
Maximum2023-07-06 00:00:00
2024-05-11T15:09:45.133396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:45.281511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

영업상태코드
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
4
420 
3
407 
1
107 
5
 
8
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 420
44.5%
3 407
43.1%
1 107
 
11.3%
5 8
 
0.8%
2 2
 
0.2%

Length

2024-05-11T15:09:45.482996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:45.630371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 420
44.5%
3 407
43.1%
1 107
 
11.3%
5 8
 
0.8%
2 2
 
0.2%

영업상태명
Categorical

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
취소/말소/만료/정지/중지
420 
폐업
407 
영업/정상
107 
제외/삭제/전출
 
8
휴업
 
2

Length

Max length14
Median length8
Mean length7.7298729
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 420
44.5%
폐업 407
43.1%
영업/정상 107
 
11.3%
제외/삭제/전출 8
 
0.8%
휴업 2
 
0.2%

Length

2024-05-11T15:09:45.832006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:46.000387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 420
44.5%
폐업 407
43.1%
영업/정상 107
 
11.3%
제외/삭제/전출 8
 
0.8%
휴업 2
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5646186
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-05-11T15:09:46.176202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.2692696
Coefficient of variation (CV)0.49714331
Kurtosis-1.6194726
Mean4.5646186
Median Absolute Deviation (MAD)2
Skewness-0.035137123
Sum4309
Variance5.1495846
MonotonicityNot monotonic
2024-05-11T15:09:46.362260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
7 419
44.4%
3 407
43.1%
1 107
 
11.3%
5 8
 
0.8%
2 2
 
0.2%
4 1
 
0.1%
ValueCountFrequency (%)
1 107
 
11.3%
2 2
 
0.2%
3 407
43.1%
4 1
 
0.1%
5 8
 
0.8%
7 419
44.4%
ValueCountFrequency (%)
7 419
44.4%
5 8
 
0.8%
4 1
 
0.1%
3 407
43.1%
2 2
 
0.2%
1 107
 
11.3%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
직권말소
419 
폐업처리
407 
정상영업
107 
타시군구이관
 
8
휴업처리
 
2

Length

Max length6
Median length4
Mean length4.0169492
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
직권말소 419
44.4%
폐업처리 407
43.1%
정상영업 107
 
11.3%
타시군구이관 8
 
0.8%
휴업처리 2
 
0.2%
직권취소 1
 
0.1%

Length

2024-05-11T15:09:46.624310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:46.817359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직권말소 419
44.4%
폐업처리 407
43.1%
정상영업 107
 
11.3%
타시군구이관 8
 
0.8%
휴업처리 2
 
0.2%
직권취소 1
 
0.1%

폐업일자
Date

MISSING 

Distinct353
Distinct (%)85.1%
Missing529
Missing (%)56.0%
Memory size7.5 KiB
Minimum1999-09-08 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:09:47.041302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:47.266137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
<NA>
941 
20221215
 
1
20200629
 
1
20221102
 
1

Length

Max length8
Median length4
Mean length4.0127119
Min length4

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 941
99.7%
20221215 1
 
0.1%
20200629 1
 
0.1%
20221102 1
 
0.1%

Length

2024-05-11T15:09:47.532273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:47.720503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 941
99.7%
20221215 1
 
0.1%
20200629 1
 
0.1%
20221102 1
 
0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
<NA>
941 
20230630
 
1
20210629
 
1
20230402
 
1

Length

Max length8
Median length4
Mean length4.0127119
Min length4

Unique

Unique3 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 941
99.7%
20230630 1
 
0.1%
20210629 1
 
0.1%
20230402 1
 
0.1%

Length

2024-05-11T15:09:47.911855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:48.089581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 941
99.7%
20230630 1
 
0.1%
20210629 1
 
0.1%
20230402 1
 
0.1%

재개업일자
Date

MISSING 

Distinct3
Distinct (%)75.0%
Missing940
Missing (%)99.6%
Memory size7.5 KiB
Minimum1999-05-31 00:00:00
Maximum2023-04-18 00:00:00
2024-05-11T15:09:48.207374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:48.364052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

전화번호
Text

MISSING 

Distinct676
Distinct (%)85.9%
Missing157
Missing (%)16.6%
Memory size7.5 KiB
2024-05-11T15:09:48.751711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length10.512071
Min length3

Characters and Unicode

Total characters8273
Distinct characters15
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

Unique635 ?
Unique (%)80.7%

Sample

1st row02)499 4889
2nd row02)461 0511
3rd row02)444 2255
4th row02)447 0071
5th row02)469 4062
ValueCountFrequency (%)
02 58
 
6.0%
02)455 15
 
1.6%
02)444 13
 
1.3%
02)452 13
 
1.3%
02)456 13
 
1.3%
02)454 12
 
1.2%
02)453 10
 
1.0%
02)446 9
 
0.9%
02)457 9
 
0.9%
02)447 9
 
0.9%
Other values (702) 805
83.3%
2024-05-11T15:09:49.301210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1261
15.2%
2 1161
14.0%
4 1027
12.4%
- 943
11.4%
5 660
8.0%
6 577
7.0%
1 515
6.2%
3 480
 
5.8%
8 429
 
5.2%
7 399
 
4.8%
Other values (5) 821
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6858
82.9%
Dash Punctuation 943
 
11.4%
Close Punctuation 288
 
3.5%
Space Separator 179
 
2.2%
Math Symbol 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1261
18.4%
2 1161
16.9%
4 1027
15.0%
5 660
9.6%
6 577
8.4%
1 515
7.5%
3 480
 
7.0%
8 429
 
6.3%
7 399
 
5.8%
9 349
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 943
100.0%
Close Punctuation
ValueCountFrequency (%)
) 288
100.0%
Space Separator
ValueCountFrequency (%)
179
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8273
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1261
15.2%
2 1161
14.0%
4 1027
12.4%
- 943
11.4%
5 660
8.0%
6 577
7.0%
1 515
6.2%
3 480
 
5.8%
8 429
 
5.2%
7 399
 
4.8%
Other values (5) 821
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1261
15.2%
2 1161
14.0%
4 1027
12.4%
- 943
11.4%
5 660
8.0%
6 577
7.0%
1 515
6.2%
3 480
 
5.8%
8 429
 
5.2%
7 399
 
4.8%
Other values (5) 821
9.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing944
Missing (%)100.0%
Memory size8.4 KiB

소재지우편번호
Text

MISSING 

Distinct85
Distinct (%)20.1%
Missing521
Missing (%)55.2%
Memory size7.5 KiB
2024-05-11T15:09:49.691849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0070922
Min length6

Characters and Unicode

Total characters2541
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

Unique42 ?
Unique (%)9.9%

Sample

1st row143190
2nd row143926
3rd row143815
4th row143190
5th row143848
ValueCountFrequency (%)
143200 66
15.6%
143220 58
13.7%
143190 54
 
12.8%
143150 35
 
8.3%
143180 25
 
5.9%
143210 14
 
3.3%
143130 10
 
2.4%
143838 9
 
2.1%
143904 6
 
1.4%
143898 6
 
1.4%
Other values (75) 140
33.1%
2024-05-11T15:09:50.200509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 599
23.6%
3 461
18.1%
4 453
17.8%
0 368
14.5%
2 235
 
9.2%
8 181
 
7.1%
9 116
 
4.6%
5 56
 
2.2%
7 39
 
1.5%
6 30
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2538
99.9%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 599
23.6%
3 461
18.2%
4 453
17.8%
0 368
14.5%
2 235
 
9.3%
8 181
 
7.1%
9 116
 
4.6%
5 56
 
2.2%
7 39
 
1.5%
6 30
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2541
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 599
23.6%
3 461
18.1%
4 453
17.8%
0 368
14.5%
2 235
 
9.2%
8 181
 
7.1%
9 116
 
4.6%
5 56
 
2.2%
7 39
 
1.5%
6 30
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 599
23.6%
3 461
18.1%
4 453
17.8%
0 368
14.5%
2 235
 
9.2%
8 181
 
7.1%
9 116
 
4.6%
5 56
 
2.2%
7 39
 
1.5%
6 30
 
1.2%

지번주소
Text

Distinct614
Distinct (%)65.6%
Missing8
Missing (%)0.8%
Memory size7.5 KiB
2024-05-11T15:09:50.527275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length45
Mean length26.482906
Min length15

Characters and Unicode

Total characters24788
Distinct characters258
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique497 ?
Unique (%)53.1%

Sample

1st row서울시 광진구 화양동**-**
2nd row서울시 광진구 자양동***-*
3rd row서울시 광진구 구의동**-*
4th row서울시 광진구 구의동**-*
5th row서울시 광진구 군자동**-*
ValueCountFrequency (%)
광진구 932
18.0%
호 706
13.6%
서울특별시 653
12.6%
번지 560
10.8%
층 331
 
6.4%
서울시 280
 
5.4%
구의동 250
 
4.8%
중곡동 218
 
4.2%
자양동 184
 
3.5%
166
 
3.2%
Other values (379) 911
17.5%
2024-05-11T15:09:51.150930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5539
22.3%
4381
17.7%
구 1202
 
4.8%
동 1031
 
4.2%
광 1025
 
4.1%
진 961
 
3.9%
서 943
 
3.8%
시 940
 
3.8%
울 937
 
3.8%
호 755
 
3.0%
Other values (248) 7074
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14281
57.6%
Other Punctuation 5570
 
22.5%
Space Separator 4381
 
17.7%
Dash Punctuation 401
 
1.6%
Decimal Number 76
 
0.3%
Uppercase Letter 70
 
0.3%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1202
 
8.4%
동 1031
 
7.2%
광 1025
 
7.2%
진 961
 
6.7%
서 943
 
6.6%
시 940
 
6.6%
울 937
 
6.6%
호 755
 
5.3%
특 653
 
4.6%
별 653
 
4.6%
Other values (214) 5181
36.3%
Uppercase Letter
ValueCountFrequency (%)
B 18
25.7%
A 17
24.3%
D 7
 
10.0%
K 4
 
5.7%
T 4
 
5.7%
C 4
 
5.7%
P 3
 
4.3%
M 3
 
4.3%
S 2
 
2.9%
I 2
 
2.9%
Other values (4) 6
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 16
21.1%
4 13
17.1%
2 11
14.5%
5 9
11.8%
6 8
10.5%
9 6
 
7.9%
7 4
 
5.3%
3 4
 
5.3%
0 3
 
3.9%
8 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
* 5539
99.4%
, 23
 
0.4%
/ 5
 
0.1%
@ 2
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4381
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 401
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14281
57.6%
Common 10437
42.1%
Latin 70
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1202
 
8.4%
동 1031
 
7.2%
광 1025
 
7.2%
진 961
 
6.7%
서 943
 
6.6%
시 940
 
6.6%
울 937
 
6.6%
호 755
 
5.3%
특 653
 
4.6%
별 653
 
4.6%
Other values (214) 5181
36.3%
Common
ValueCountFrequency (%)
* 5539
53.1%
4381
42.0%
- 401
 
3.8%
, 23
 
0.2%
1 16
 
0.2%
4 13
 
0.1%
2 11
 
0.1%
5 9
 
0.1%
6 8
 
0.1%
9 6
 
0.1%
Other values (10) 30
 
0.3%
Latin
ValueCountFrequency (%)
B 18
25.7%
A 17
24.3%
D 7
 
10.0%
K 4
 
5.7%
T 4
 
5.7%
C 4
 
5.7%
P 3
 
4.3%
M 3
 
4.3%
S 2
 
2.9%
I 2
 
2.9%
Other values (4) 6
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14281
57.6%
ASCII 10507
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5539
52.7%
4381
41.7%
- 401
 
3.8%
, 23
 
0.2%
B 18
 
0.2%
A 17
 
0.2%
1 16
 
0.2%
4 13
 
0.1%
2 11
 
0.1%
5 9
 
0.1%
Other values (24) 79
 
0.8%
Hangul
ValueCountFrequency (%)
구 1202
 
8.4%
동 1031
 
7.2%
광 1025
 
7.2%
진 961
 
6.7%
서 943
 
6.6%
시 940
 
6.6%
울 937
 
6.6%
호 755
 
5.3%
특 653
 
4.6%
별 653
 
4.6%
Other values (214) 5181
36.3%

도로명주소
Text

MISSING 

Distinct515
Distinct (%)79.6%
Missing297
Missing (%)31.5%
Memory size7.5 KiB
2024-05-11T15:09:51.495453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length32.502318
Min length22

Characters and Unicode

Total characters21029
Distinct characters245
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique440 ?
Unique (%)68.0%

Sample

1st row서울특별시 광진구 뚝섬로 ***, ***호 (자양동, 대양빌딩)
2nd row서울특별시 광진구 천호대로 ***, *층 동편, *층 ***-*(우측)호 (중곡동, 향림빌딩)
3rd row서울특별시 광진구 광나루로 ***, *층 (화양동)
4th row서울특별시 광진구 능동로 ***, ***호 ***호 (중곡동)
5th row서울특별시 광진구 아차산로 ***-**, *층 *,*호 (광장동, 청구아파트상가)
ValueCountFrequency (%)
673
16.6%
서울특별시 644
15.9%
광진구 642
15.9%
층 249
 
6.2%
호 200
 
4.9%
중곡동 125
 
3.1%
구의동 108
 
2.7%
자양동 106
 
2.6%
능동로 76
 
1.9%
천호대로 56
 
1.4%
Other values (384) 1164
28.8%
2024-05-11T15:09:52.039323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 3405
16.2%
3397
16.2%
동 867
 
4.1%
구 838
 
4.0%
광 763
 
3.6%
, 705
 
3.4%
진 662
 
3.1%
서 651
 
3.1%
시 650
 
3.1%
로 650
 
3.1%
Other values (235) 8441
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11967
56.9%
Other Punctuation 4117
 
19.6%
Space Separator 3397
 
16.2%
Close Punctuation 649
 
3.1%
Open Punctuation 649
 
3.1%
Dash Punctuation 113
 
0.5%
Decimal Number 74
 
0.4%
Uppercase Letter 62
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 867
 
7.2%
구 838
 
7.0%
광 763
 
6.4%
진 662
 
5.5%
서 651
 
5.4%
시 650
 
5.4%
로 650
 
5.4%
울 646
 
5.4%
특 644
 
5.4%
별 644
 
5.4%
Other values (202) 4952
41.4%
Uppercase Letter
ValueCountFrequency (%)
B 17
27.4%
A 17
27.4%
D 8
12.9%
C 6
 
9.7%
K 2
 
3.2%
F 2
 
3.2%
M 2
 
3.2%
S 2
 
3.2%
P 2
 
3.2%
T 1
 
1.6%
Other values (3) 3
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 10
13.5%
5 10
13.5%
2 10
13.5%
8 9
12.2%
6 8
10.8%
0 7
9.5%
3 7
9.5%
9 5
6.8%
4 5
6.8%
7 3
 
4.1%
Other Punctuation
ValueCountFrequency (%)
* 3405
82.7%
, 705
 
17.1%
/ 5
 
0.1%
& 1
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3397
100.0%
Close Punctuation
ValueCountFrequency (%)
) 649
100.0%
Open Punctuation
ValueCountFrequency (%)
( 649
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11967
56.9%
Common 9000
42.8%
Latin 62
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 867
 
7.2%
구 838
 
7.0%
광 763
 
6.4%
진 662
 
5.5%
서 651
 
5.4%
시 650
 
5.4%
로 650
 
5.4%
울 646
 
5.4%
특 644
 
5.4%
별 644
 
5.4%
Other values (202) 4952
41.4%
Common
ValueCountFrequency (%)
* 3405
37.8%
3397
37.7%
, 705
 
7.8%
) 649
 
7.2%
( 649
 
7.2%
- 113
 
1.3%
1 10
 
0.1%
5 10
 
0.1%
2 10
 
0.1%
8 9
 
0.1%
Other values (10) 43
 
0.5%
Latin
ValueCountFrequency (%)
B 17
27.4%
A 17
27.4%
D 8
12.9%
C 6
 
9.7%
K 2
 
3.2%
F 2
 
3.2%
M 2
 
3.2%
S 2
 
3.2%
P 2
 
3.2%
T 1
 
1.6%
Other values (3) 3
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11967
56.9%
ASCII 9062
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 3405
37.6%
3397
37.5%
, 705
 
7.8%
) 649
 
7.2%
( 649
 
7.2%
- 113
 
1.2%
B 17
 
0.2%
A 17
 
0.2%
1 10
 
0.1%
5 10
 
0.1%
Other values (23) 90
 
1.0%
Hangul
ValueCountFrequency (%)
동 867
 
7.2%
구 838
 
7.0%
광 763
 
6.4%
진 662
 
5.5%
서 651
 
5.4%
시 650
 
5.4%
로 650
 
5.4%
울 646
 
5.4%
특 644
 
5.4%
별 644
 
5.4%
Other values (202) 4952
41.4%

도로명우편번호
Text

MISSING 

Distinct175
Distinct (%)43.5%
Missing542
Missing (%)57.4%
Memory size7.5 KiB
2024-05-11T15:09:52.474494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4353234
Min length5

Characters and Unicode

Total characters2185
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

Unique91 ?
Unique (%)22.6%

Sample

1st row143862
2nd row04930
3rd row143926
4th row04937
5th row143815
ValueCountFrequency (%)
05116 22
 
5.5%
04969 12
 
3.0%
143838 9
 
2.2%
143898 9
 
2.2%
04928 8
 
2.0%
143899 8
 
2.0%
04930 7
 
1.7%
143874 7
 
1.7%
143867 6
 
1.5%
143847 6
 
1.5%
Other values (165) 308
76.6%
2024-05-11T15:09:53.127630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 395
18.1%
4 362
16.6%
1 291
13.3%
3 243
11.1%
9 234
10.7%
8 209
9.6%
5 185
8.5%
6 104
 
4.8%
7 84
 
3.8%
2 74
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2181
99.8%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 395
18.1%
4 362
16.6%
1 291
13.3%
3 243
11.1%
9 234
10.7%
8 209
9.6%
5 185
8.5%
6 104
 
4.8%
7 84
 
3.9%
2 74
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2185
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 395
18.1%
4 362
16.6%
1 291
13.3%
3 243
11.1%
9 234
10.7%
8 209
9.6%
5 185
8.5%
6 104
 
4.8%
7 84
 
3.8%
2 74
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 395
18.1%
4 362
16.6%
1 291
13.3%
3 243
11.1%
9 234
10.7%
8 209
9.6%
5 185
8.5%
6 104
 
4.8%
7 84
 
3.8%
2 74
 
3.4%

사업장명
Text

Distinct915
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-05-11T15:09:53.556878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length7.6991525
Min length1

Characters and Unicode

Total characters7268
Distinct characters539
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique887 ?
Unique (%)94.0%

Sample

1st row백옥화장품
2nd row끄레앙스
3rd row아시아자동차대공원영
4th row기아자동차대공원영업
5th row대우자동차동부판매
ValueCountFrequency (%)
주식회사 85
 
6.9%
주 14
 
1.1%
인셀덤 9
 
0.7%
윤선생영어교실 4
 
0.3%
광진 4
 
0.3%
광진센터 4
 
0.3%
쌍용자동차 4
 
0.3%
에치와이 3
 
0.2%
주)원전커머스 3
 
0.2%
주)유영교육 3
 
0.2%
Other values (1023) 1091
89.1%
2024-05-11T15:09:54.116974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 330
 
4.5%
281
 
3.9%
) 275
 
3.8%
( 275
 
3.8%
이 226
 
3.1%
스 210
 
2.9%
사 166
 
2.3%
리 119
 
1.6%
에 117
 
1.6%
식 100
 
1.4%
Other values (529) 5169
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5991
82.4%
Space Separator 281
 
3.9%
Close Punctuation 275
 
3.8%
Open Punctuation 275
 
3.8%
Uppercase Letter 259
 
3.6%
Lowercase Letter 133
 
1.8%
Other Punctuation 37
 
0.5%
Decimal Number 12
 
0.2%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 330
 
5.5%
이 226
 
3.8%
스 210
 
3.5%
사 166
 
2.8%
리 119
 
2.0%
에 117
 
2.0%
식 100
 
1.7%
회 99
 
1.7%
아 98
 
1.6%
지 93
 
1.6%
Other values (468) 4433
74.0%
Uppercase Letter
ValueCountFrequency (%)
C 25
 
9.7%
S 17
 
6.6%
T 17
 
6.6%
B 17
 
6.6%
A 17
 
6.6%
N 16
 
6.2%
L 15
 
5.8%
E 15
 
5.8%
M 15
 
5.8%
D 14
 
5.4%
Other values (13) 91
35.1%
Lowercase Letter
ValueCountFrequency (%)
o 18
13.5%
e 13
 
9.8%
i 12
 
9.0%
t 10
 
7.5%
n 10
 
7.5%
a 8
 
6.0%
r 8
 
6.0%
u 7
 
5.3%
l 6
 
4.5%
m 6
 
4.5%
Other values (11) 35
26.3%
Other Punctuation
ValueCountFrequency (%)
. 20
54.1%
& 9
24.3%
, 4
 
10.8%
/ 1
 
2.7%
' 1
 
2.7%
? 1
 
2.7%
# 1
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 4
33.3%
3 2
16.7%
2 2
16.7%
9 2
16.7%
4 1
 
8.3%
7 1
 
8.3%
Space Separator
ValueCountFrequency (%)
281
100.0%
Close Punctuation
ValueCountFrequency (%)
) 275
100.0%
Open Punctuation
ValueCountFrequency (%)
( 275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5991
82.4%
Common 885
 
12.2%
Latin 392
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 330
 
5.5%
이 226
 
3.8%
스 210
 
3.5%
사 166
 
2.8%
리 119
 
2.0%
에 117
 
2.0%
식 100
 
1.7%
회 99
 
1.7%
아 98
 
1.6%
지 93
 
1.6%
Other values (468) 4433
74.0%
Latin
ValueCountFrequency (%)
C 25
 
6.4%
o 18
 
4.6%
S 17
 
4.3%
T 17
 
4.3%
B 17
 
4.3%
A 17
 
4.3%
N 16
 
4.1%
L 15
 
3.8%
E 15
 
3.8%
M 15
 
3.8%
Other values (34) 220
56.1%
Common
ValueCountFrequency (%)
281
31.8%
) 275
31.1%
( 275
31.1%
. 20
 
2.3%
& 9
 
1.0%
- 5
 
0.6%
, 4
 
0.5%
1 4
 
0.5%
3 2
 
0.2%
2 2
 
0.2%
Other values (7) 8
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5991
82.4%
ASCII 1277
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 330
 
5.5%
이 226
 
3.8%
스 210
 
3.5%
사 166
 
2.8%
리 119
 
2.0%
에 117
 
2.0%
식 100
 
1.7%
회 99
 
1.7%
아 98
 
1.6%
지 93
 
1.6%
Other values (468) 4433
74.0%
ASCII
ValueCountFrequency (%)
281
22.0%
) 275
21.5%
( 275
21.5%
C 25
 
2.0%
. 20
 
1.6%
o 18
 
1.4%
S 17
 
1.3%
T 17
 
1.3%
B 17
 
1.3%
A 17
 
1.3%
Other values (51) 315
24.7%

최종수정일자
Date

Distinct939
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Minimum2007-07-04 13:20:23
Maximum2024-05-09 09:32:34
2024-05-11T15:09:54.323982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:54.538178image/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 size7.5 KiB
I
787 
U
157 

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 787
83.4%
U 157
 
16.6%

Length

2024-05-11T15:09:54.729681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:54.878124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 787
83.4%
u 157
 
16.6%

데이터갱신일자
Date

Distinct148
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:09:55.047752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:55.259493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing944
Missing (%)100.0%
Memory size8.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct449
Distinct (%)68.2%
Missing286
Missing (%)30.3%
Infinite0
Infinite (%)0.0%
Mean207273.21
Minimum180226.73
Maximum211346.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-05-11T15:09:55.473315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180226.73
5-th percentile205905.37
Q1206801.54
median207269.07
Q3207833.16
95-th percentile209028.39
Maximum211346.02
Range31119.288
Interquartile range (IQR)1031.6189

Descriptive statistics

Standard deviation1375.6487
Coefficient of variation (CV)0.0066368861
Kurtosis227.32131
Mean207273.21
Median Absolute Deviation (MAD)501.12823
Skewness-11.477778
Sum1.3638577 × 108
Variance1892409.3
MonotonicityNot monotonic
2024-05-11T15:09:56.041048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208394.416382167 23
 
2.4%
207388.308848516 11
 
1.2%
209637.078215509 11
 
1.2%
206801.538358961 9
 
1.0%
207050.741838142 8
 
0.8%
208124.549163942 8
 
0.8%
207295.535773115 7
 
0.7%
207147.398684407 6
 
0.6%
207380.881842195 5
 
0.5%
207072.800336685 5
 
0.5%
Other values (439) 565
59.9%
(Missing) 286
30.3%
ValueCountFrequency (%)
180226.735 1
0.1%
202834.695368091 1
0.1%
205333.847644836 1
0.1%
205421.250160702 1
0.1%
205491.674232141 1
0.1%
205525.535034662 1
0.1%
205561.045696547 1
0.1%
205582.273996432 1
0.1%
205586.123950156 1
0.1%
205604.282709629 1
0.1%
ValueCountFrequency (%)
211346.023277214 1
 
0.1%
209734.218553133 2
 
0.2%
209668.90120464 2
 
0.2%
209637.078215509 11
1.2%
209545.765272486 2
 
0.2%
209523.395129627 1
 
0.1%
209506.54940258 1
 
0.1%
209495.840303416 1
 
0.1%
209487.474614925 1
 
0.1%
209460.824569837 2
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct449
Distinct (%)68.2%
Missing286
Missing (%)30.3%
Infinite0
Infinite (%)0.0%
Mean449388.46
Minimum405131.57
Maximum461197.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-05-11T15:09:56.230953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum405131.57
5-th percentile447805.33
Q1448313.52
median449552.11
Q3450512.9
95-th percentile451122.47
Maximum461197.57
Range56065.998
Interquartile range (IQR)2199.3849

Descriptive statistics

Standard deviation2201.0865
Coefficient of variation (CV)0.0048979595
Kurtosis250.78553
Mean449388.46
Median Absolute Deviation (MAD)1083.5061
Skewness-12.38682
Sum2.9569761 × 108
Variance4844781.7
MonotonicityNot monotonic
2024-05-11T15:09:56.452765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448165.279999905 23
 
2.4%
448313.517465433 11
 
1.2%
449832.485937903 11
 
1.2%
450272.668534712 9
 
1.0%
450712.805909593 8
 
0.8%
447812.924832297 8
 
0.8%
450336.900913019 7
 
0.7%
450494.906098164 6
 
0.6%
448153.591228926 5
 
0.5%
450764.939696563 5
 
0.5%
Other values (439) 565
59.9%
(Missing) 286
30.3%
ValueCountFrequency (%)
405131.566931496 1
0.1%
437585.386881809 1
0.1%
444272.018760799 1
0.1%
447399.13287792 1
0.1%
447413.08579009 1
0.1%
447470.651402545 1
0.1%
447473.715631334 1
0.1%
447492.756850723 2
0.2%
447545.656504758 1
0.1%
447546.523504738 1
0.1%
ValueCountFrequency (%)
461197.565 1
0.1%
452123.458782283 1
0.1%
452101.652244219 1
0.1%
452034.440353727 1
0.1%
452022.542039327 1
0.1%
451995.653308863 1
0.1%
451992.328685625 1
0.1%
451991.900378929 2
0.2%
451970.554702384 1
0.1%
451931.671230146 1
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct100
Distinct (%)32.9%
Missing640
Missing (%)67.8%
Infinite0
Infinite (%)0.0%
Mean1.1216412 × 1010
Minimum0
Maximum1.421582 × 1012
Zeros123
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-05-11T15:09:56.666694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20000000
Q31 × 108
95-th percentile3.8719466 × 109
Maximum1.421582 × 1012
Range1.421582 × 1012
Interquartile range (IQR)1 × 108

Descriptive statistics

Standard deviation1.1726083 × 1011
Coefficient of variation (CV)10.454398
Kurtosis138.27986
Mean1.1216412 × 1010
Median Absolute Deviation (MAD)20000000
Skewness11.682422
Sum3.4097891 × 1012
Variance1.3750101 × 1022
MonotonicityNot monotonic
2024-05-11T15:09:56.907161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 123
 
13.0%
50000000 34
 
3.6%
100000000 14
 
1.5%
10000000 13
 
1.4%
30000000 7
 
0.7%
60000000 3
 
0.3%
1000000 3
 
0.3%
20000000 3
 
0.3%
5000000 3
 
0.3%
40000000 3
 
0.3%
Other values (90) 98
 
10.4%
(Missing) 640
67.8%
ValueCountFrequency (%)
0 123
13.0%
1 1
 
0.1%
100000 2
 
0.2%
1000000 3
 
0.3%
2562564 1
 
0.1%
3000000 1
 
0.1%
4633788 1
 
0.1%
5000000 3
 
0.3%
5100000 1
 
0.1%
10000000 13
 
1.4%
ValueCountFrequency (%)
1421582000000 2
0.2%
401358924666 1
0.1%
25086484000 1
0.1%
20915851680 1
0.1%
13510220588 1
0.1%
8098408879 1
0.1%
6438478903 1
0.1%
5813948367 2
0.2%
5254583890 1
0.1%
5000000000 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct85
Distinct (%)28.1%
Missing642
Missing (%)68.0%
Infinite0
Infinite (%)0.0%
Mean1.0525662 × 1010
Minimum0
Maximum1.341131 × 1012
Zeros210
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-05-11T15:09:57.128050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q322681425
95-th percentile2.5766281 × 109
Maximum1.341131 × 1012
Range1.341131 × 1012
Interquartile range (IQR)22681425

Descriptive statistics

Standard deviation1.1104482 × 1011
Coefficient of variation (CV)10.549913
Kurtosis137.14144
Mean1.0525662 × 1010
Median Absolute Deviation (MAD)0
Skewness11.633753
Sum3.1787499 × 1012
Variance1.2330951 × 1022
MonotonicityNot monotonic
2024-05-11T15:09:57.336762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 210
 
22.2%
10000000 5
 
0.5%
1341131000000 2
 
0.2%
5011231805 2
 
0.2%
150000000 2
 
0.2%
30000000 2
 
0.2%
4739984991 1
 
0.1%
332213502 1
 
0.1%
18536334607 1
 
0.1%
1161945657 1
 
0.1%
Other values (75) 75
 
7.9%
(Missing) 642
68.0%
ValueCountFrequency (%)
0 210
22.2%
1 1
 
0.1%
1765171 1
 
0.1%
1954246 1
 
0.1%
2000000 1
 
0.1%
3000000 1
 
0.1%
3600000 1
 
0.1%
5000000 1
 
0.1%
5312000 1
 
0.1%
10000000 5
 
0.5%
ValueCountFrequency (%)
1341131000000 2
0.2%
383272565102 1
0.1%
18536334607 1
0.1%
15912877330 1
0.1%
8749248771 1
0.1%
6983220052 1
0.1%
6185052489 1
0.1%
5011231805 2
0.2%
4739984991 1
0.1%
4000000000 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct57
Distinct (%)18.8%
Missing640
Missing (%)67.8%
Infinite0
Infinite (%)0.0%
Mean6.9387169 × 108
Minimum-1.3849613 × 1010
Maximum8.0451 × 1010
Zeros112
Zeros (%)11.9%
Negative3
Negative (%)0.3%
Memory size8.4 KiB
2024-05-11T15:09:57.560656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.3849613 × 1010
5-th percentile0
Q10
median20000000
Q362947834
95-th percentile4.8168091 × 108
Maximum8.0451 × 1010
Range9.4300613 × 1010
Interquartile range (IQR)62947834

Descriptive statistics

Standard deviation6.6627535 × 109
Coefficient of variation (CV)9.6022846
Kurtosis135.45234
Mean6.9387169 × 108
Median Absolute Deviation (MAD)20000000
Skewness11.425984
Sum2.1093699 × 1011
Variance4.4392284 × 1019
MonotonicityNot monotonic
2024-05-11T15:09:57.770500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 112
 
11.9%
50000000 53
 
5.6%
100000000 25
 
2.6%
10000000 16
 
1.7%
20000000 9
 
1.0%
300000000 8
 
0.8%
200000000 7
 
0.7%
30000000 7
 
0.7%
150000000 4
 
0.4%
5000000 4
 
0.4%
Other values (47) 59
 
6.2%
(Missing) 640
67.8%
ValueCountFrequency (%)
-13849612934 1
 
0.1%
-376481207 1
 
0.1%
-32240375 1
 
0.1%
0 112
11.9%
1 1
 
0.1%
10000 1
 
0.1%
100000 3
 
0.3%
852059 1
 
0.1%
1000000 3
 
0.3%
2000000 3
 
0.3%
ValueCountFrequency (%)
80451000000 2
0.2%
18086359564 1
0.1%
7000000000 1
0.1%
5455388784 1
0.1%
4760971817 1
0.1%
3000000000 1
0.1%
2779906796 1
0.1%
1913356390 1
0.1%
1720819039 1
0.1%
1618082559 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing944
Missing (%)100.0%
Memory size8.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03040000199630401032320000819961029<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)499 4889<NA><NA>서울시 광진구 화양동**-**<NA><NA>백옥화장품2016-08-09 13:03:42I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13040000199630401032320001319961113<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)461 0511<NA><NA>서울시 광진구 자양동***-*<NA><NA>끄레앙스2015-08-19 09:48:59I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23040000199630401032320002719961226<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)444 2255<NA><NA>서울시 광진구 구의동**-*<NA><NA>아시아자동차대공원영2015-08-19 09:44:27I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33040000199630401032320002819961226<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)447 0071<NA><NA>서울시 광진구 구의동**-*<NA><NA>기아자동차대공원영업2015-08-19 09:45:30I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
43040000199730401032320003319970501<NA>3폐업3폐업처리20160401<NA><NA><NA>02)469 4062<NA><NA>서울시 광진구 군자동**-*<NA><NA>대우자동차동부판매2016-04-04 09:26:43I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
53040000199730401032320003419970501<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)465 6400<NA><NA>서울시 광진구 군자동**-*<NA><NA>대우자동차판매회사2016-06-13 10:45:41I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63040000199730401032320004719970930<NA>3폐업3폐업처리20080630<NA><NA><NA>02)458 4978<NA><NA>서울시 광진구 구의동***-***<NA><NA>백옥생한방화장품동서울지사2008-07-01 18:39:53I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
73040000199730401032320005519980131<NA>3폐업3폐업처리20130916<NA><NA><NA>02-453-2033(~4)<NA><NA>서울시 광진구 자양동***-* 화성빌딩*층<NA><NA>아모레광진특약점2013-09-24 09:26:18I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
83040000199730401032320006819980318<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)447 5870<NA><NA>서울시 광진구 능동***-*<NA><NA>대경마트2016-06-13 10:42:05I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
93040000199730401032320007019980408<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)201 4664<NA><NA>서울시 광진구 구의동***-* 동서울터미널-***<NA><NA>고려물산2016-08-25 10:30:01I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
934304000020233040190232000142023-07-04<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 중곡동 ***-*서울특별시 광진구 면목로 ***, *층 (중곡동)04910천사마음2023-11-02 10:59:10I2022-11-01 00:04:00.0<NA>207014.648807451264.94796<NA><NA><NA><NA>
935304000020233040190232000152020-07-31<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 광장동 ***-* 대광빌딩서울특별시 광진구 아차산로**길 **, 대광빌딩 지하*층 (광장동)04968보광2023-11-24 15:50:28U2022-10-31 22:06:00.0<NA>209079.012519449367.798277<NA><NA><NA><NA>
936304000020233040190232000162023-12-12<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 구의동 **-**서울특별시 광진구 자양로 ***-*, *층 (구의동)04975수빈컴퍼니2023-12-14 17:22:28I2022-11-01 23:06:00.0<NA>207802.08508449538.078239<NA><NA><NA><NA>
937304000020233040190232000172023-12-14<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 자양동 ***-**서울특별시 광진구 뚝섬로**길 **, *층 (자양동)05078태양힐링센터2023-12-14 17:24:33I2022-11-01 23:06:00.0<NA>205642.888116448338.136856<NA><NA><NA><NA>
938304000020233040190232000182023-12-20<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-456-8802<NA><NA>서울특별시 광진구 구의동 ***-* 테크노-마트**서울특별시 광진구 광나루로**길 **, 테크노-마트** **층 *호 (구의동)05116주식회사 지음피앤브이2023-12-27 10:08:46I2022-11-01 22:09:00.0<NA>208394.416382448165.28<NA><NA><NA><NA>
939304000020243040190232000012024-01-10<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1544-2127<NA><NA>서울특별시 광진구 구의동 ***-**서울특별시 광진구 구의로**길 **, *층 ***호 (구의동)05033아이피119정보통신 주식회사2024-01-10 11:02:27I2023-11-30 23:02:00.0<NA>208143.339194448992.82262<NA><NA><NA><NA>
940304000020243040190232000022024-02-26<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1566-4668<NA><NA>서울특별시 광진구 구의동 ***-* 테크노-마트**서울특별시 광진구 광나루로**길 **, 테크노-마트** *층층 C-***호 (구의동)05116SM정보시스템2024-02-26 15:43:20I2023-12-01 22:08:00.0<NA>208394.416382448165.28<NA><NA><NA><NA>
941304000020243040190232000032019-05-28<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 자양동 ***-* 더샵스타시티서울특별시 광진구 아차산로 ***, C동 ****호 (자양동, 더샵스타시티)05065헬스웰2024-03-11 13:56:28I2023-12-02 23:03:00.0<NA>206349.675048448396.939704<NA><NA><NA><NA>
942304000020243040190232000041999-05-31<NA>1영업/정상1정상영업<NA><NA><NA>1999-05-3102-2244-7125<NA><NA>서울특별시 광진구 구의동 ***-** 성진프라자서울특별시 광진구 구의강변로 **, 성진프라자 *층 ***호 (구의동)05049고시포코2024-03-25 10:46:56I2023-12-02 22:07:00.0<NA>207995.957095448085.242459<NA><NA><NA><NA>
943304000020243040190232000052024-04-26<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-456-8986<NA><NA>서울특별시 광진구 구의동 ***-**서울특별시 광진구 구의로 **, 지층 (구의동)05033압토솔2024-04-26 16:20:55I2023-12-03 22:08:00.0<NA>207944.045277449081.590641<NA><NA><NA><NA>