Overview

Dataset statistics

Number of variables29
Number of observations1603
Missing cells17539
Missing cells (%)37.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory386.8 KiB
Average record size in memory247.1 B

Variable types

Categorical6
Numeric9
DateTime6
Text5
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-18770/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (73.5%)Imbalance
폐업일자 has 948 (59.1%) missing valuesMissing
휴업시작일자 has 1591 (99.3%) missing valuesMissing
휴업종료일자 has 1591 (99.3%) missing valuesMissing
재개업일자 has 1577 (98.4%) missing valuesMissing
전화번호 has 246 (15.3%) missing valuesMissing
소재지면적 has 1603 (100.0%) missing valuesMissing
소재지우편번호 has 1029 (64.2%) missing valuesMissing
지번주소 has 302 (18.8%) missing valuesMissing
도로명주소 has 473 (29.5%) missing valuesMissing
도로명우편번호 has 938 (58.5%) missing valuesMissing
업태구분명 has 1603 (100.0%) missing valuesMissing
좌표정보(X) has 455 (28.4%) missing valuesMissing
좌표정보(Y) has 455 (28.4%) missing valuesMissing
자산규모 has 1042 (65.0%) missing valuesMissing
부채총액 has 1042 (65.0%) missing valuesMissing
자본금 has 1041 (64.9%) missing valuesMissing
판매방식명 has 1603 (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 217 (13.5%) zerosZeros
부채총액 has 334 (20.8%) zerosZeros
자본금 has 144 (9.0%) zerosZeros

Reproduction

Analysis started2024-04-17 22:26:29.126224
Analysis finished2024-04-17 22:26:30.375429
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
3180000
1603 

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 1603
100.0%

Length

2024-04-18T07:26:30.425787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:30.504057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 1603
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct1603
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0106817 × 1018
Minimum1.996318 × 1018
Maximum2.024318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:30.589133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996318 × 1018
5-th percentile2.001318 × 1018
Q12.006318 × 1018
median2.009318 × 1018
Q32.015318 × 1018
95-th percentile2.021318 × 1018
Maximum2.024318 × 1018
Range2.8000014 × 1016
Interquartile range (IQR)9.0000046 × 1015

Descriptive statistics

Standard deviation5.8994399 × 1015
Coefficient of variation (CV)0.0029340496
Kurtosis-0.47451376
Mean2.0106817 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.21430267
Sum-5.0574354 × 1018
Variance3.4803392 × 1031
MonotonicityStrictly increasing
2024-04-18T07:26:30.703842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996318011723200019 1
 
0.1%
2013318016323200002 1
 
0.1%
2013318016323200015 1
 
0.1%
2013318016323200014 1
 
0.1%
2013318016323200013 1
 
0.1%
2013318016323200011 1
 
0.1%
2013318016323200010 1
 
0.1%
2013318016323200009 1
 
0.1%
2013318016323200008 1
 
0.1%
2013318016323200006 1
 
0.1%
Other values (1593) 1593
99.4%
ValueCountFrequency (%)
1996318011723200019 1
0.1%
1996318011723200045 1
0.1%
1996318011723200077 1
0.1%
1996318011723200082 1
0.1%
1996318011723200087 1
0.1%
1996318011723200090 1
0.1%
1996318011723200091 1
0.1%
1996318011723200119 1
0.1%
1996318011723200121 1
0.1%
1996318011723200131 1
0.1%
ValueCountFrequency (%)
2024318025423200008 1
0.1%
2024318025423200007 1
0.1%
2024318025423200006 1
0.1%
2024318025423200005 1
0.1%
2024318025423200004 1
0.1%
2024318025423200003 1
0.1%
2024318025423200002 1
0.1%
2024318025423200001 1
0.1%
2023318025423200030 1
0.1%
2023318025423200029 1
0.1%

인허가일자
Date

Distinct1259
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum1996-09-11 00:00:00
Maximum2024-03-28 00:00:00
2024-04-18T07:26:30.820052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:30.928796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
<NA>
1398 
20071022
142 
20080923
 
58
20071205
 
3
20071011
 
1

Length

Max length8
Median length4
Mean length4.5115409
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row20071022
3rd row20071022
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1398
87.2%
20071022 142
 
8.9%
20080923 58
 
3.6%
20071205 3
 
0.2%
20071011 1
 
0.1%
20080125 1
 
0.1%

Length

2024-04-18T07:26:31.069789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:31.176005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1398
87.2%
20071022 142
 
8.9%
20080923 58
 
3.6%
20071205 3
 
0.2%
20071011 1
 
0.1%
20080125 1
 
0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
4
723 
3
645 
1
213 
2
 
11
5
 
11

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 723
45.1%
3 645
40.2%
1 213
 
13.3%
2 11
 
0.7%
5 11
 
0.7%

Length

2024-04-18T07:26:31.312800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:31.433843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 723
45.1%
3 645
40.2%
1 213
 
13.3%
2 11
 
0.7%
5 11
 
0.7%

영업상태명
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
취소/말소/만료/정지/중지
723 
폐업
645 
영업/정상
213 
휴업
 
11
제외/삭제/전출
 
11

Length

Max length14
Median length8
Mean length7.8521522
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 723
45.1%
폐업 645
40.2%
영업/정상 213
 
13.3%
휴업 11
 
0.7%
제외/삭제/전출 11
 
0.7%

Length

2024-04-18T07:26:31.550848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:31.668458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 723
45.1%
폐업 645
40.2%
영업/정상 213
 
13.3%
휴업 11
 
0.7%
제외/삭제/전출 11
 
0.7%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1597006
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:31.753696image/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 deviation2.124278
Coefficient of variation (CV)0.51068052
Kurtosis-1.27364
Mean4.1597006
Median Absolute Deviation (MAD)1
Skewness0.26184127
Sum6668
Variance4.5125572
MonotonicityNot monotonic
2024-04-18T07:26:31.841942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 645
40.2%
7 517
32.3%
1 213
 
13.3%
4 206
 
12.9%
2 11
 
0.7%
5 11
 
0.7%
ValueCountFrequency (%)
1 213
 
13.3%
2 11
 
0.7%
3 645
40.2%
4 206
 
12.9%
5 11
 
0.7%
7 517
32.3%
ValueCountFrequency (%)
7 517
32.3%
5 11
 
0.7%
4 206
 
12.9%
3 645
40.2%
2 11
 
0.7%
1 213
 
13.3%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
폐업처리
645 
직권말소
517 
정상영업
213 
직권취소
206 
휴업처리
 
11

Length

Max length6
Median length4
Mean length4.0137243
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 645
40.2%
직권말소 517
32.3%
정상영업 213
 
13.3%
직권취소 206
 
12.9%
휴업처리 11
 
0.7%
타시군구이관 11
 
0.7%

Length

2024-04-18T07:26:31.971599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:32.088232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 645
40.2%
직권말소 517
32.3%
정상영업 213
 
13.3%
직권취소 206
 
12.9%
휴업처리 11
 
0.7%
타시군구이관 11
 
0.7%

폐업일자
Date

MISSING 

Distinct513
Distinct (%)78.3%
Missing948
Missing (%)59.1%
Memory size12.7 KiB
Minimum2007-07-07 00:00:00
Maximum2024-04-16 00:00:00
2024-04-18T07:26:32.197375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:32.320214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct12
Distinct (%)100.0%
Missing1591
Missing (%)99.3%
Memory size12.7 KiB
Minimum2009-03-12 00:00:00
Maximum2021-12-31 00:00:00
2024-04-18T07:26:32.424484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:32.521578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

휴업종료일자
Date

MISSING 

Distinct11
Distinct (%)91.7%
Missing1591
Missing (%)99.3%
Memory size12.7 KiB
Minimum2009-06-11 00:00:00
Maximum2030-07-27 00:00:00
2024-04-18T07:26:32.611837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:32.693520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

재개업일자
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)65.4%
Missing1577
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean20086411
Minimum20070525
Maximum20211220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:32.783779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070525
5-th percentile20070528
Q120070530
median20070610
Q320070626
95-th percentile20208331
Maximum20211220
Range140695
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation44703.906
Coefficient of variation (CV)0.0022255795
Kurtosis4.9640988
Mean20086411
Median Absolute Deviation (MAD)17
Skewness2.5639535
Sum5.2224669 × 108
Variance1.9984392 × 109
MonotonicityIncreasing
2024-04-18T07:26:32.873884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20070529 4
 
0.2%
20070626 3
 
0.2%
20070607 2
 
0.1%
20070608 2
 
0.1%
20070528 2
 
0.1%
20070625 2
 
0.1%
20070628 1
 
0.1%
20211220 1
 
0.1%
20210708 1
 
0.1%
20201201 1
 
0.1%
Other values (7) 7
 
0.4%
(Missing) 1577
98.4%
ValueCountFrequency (%)
20070525 1
 
0.1%
20070528 2
0.1%
20070529 4
0.2%
20070531 1
 
0.1%
20070601 1
 
0.1%
20070607 2
0.1%
20070608 2
0.1%
20070612 1
 
0.1%
20070615 1
 
0.1%
20070621 1
 
0.1%
ValueCountFrequency (%)
20211220 1
 
0.1%
20210708 1
 
0.1%
20201201 1
 
0.1%
20070702 1
 
0.1%
20070628 1
 
0.1%
20070626 3
0.2%
20070625 2
0.1%
20070621 1
 
0.1%
20070615 1
 
0.1%
20070612 1
 
0.1%

전화번호
Text

MISSING 

Distinct1179
Distinct (%)86.9%
Missing246
Missing (%)15.3%
Memory size12.7 KiB
2024-04-18T07:26:33.088458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length10.966102
Min length1

Characters and Unicode

Total characters14881
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

Unique1111 ?
Unique (%)81.9%

Sample

1st row02 834 7802
2nd row02 833 6801
3rd row02 843 5571
4th row02 834 6666
5th row02 849 4585
ValueCountFrequency (%)
02 459
 
21.0%
31
 
1.4%
2672 16
 
0.7%
834 15
 
0.7%
3667-1113 14
 
0.6%
2068 14
 
0.6%
3667 14
 
0.6%
2637 14
 
0.6%
2631 13
 
0.6%
849 13
 
0.6%
Other values (1265) 1585
72.4%
2024-04-18T07:26:33.436195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2098
14.1%
0 2035
13.7%
1439
9.7%
- 1429
9.6%
6 1273
8.6%
3 1159
7.8%
8 1146
7.7%
7 1082
7.3%
1 1006
6.8%
4 867
5.8%
Other values (6) 1347
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11928
80.2%
Space Separator 1439
 
9.7%
Dash Punctuation 1429
 
9.6%
Close Punctuation 48
 
0.3%
Other Punctuation 31
 
0.2%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2098
17.6%
0 2035
17.1%
6 1273
10.7%
3 1159
9.7%
8 1146
9.6%
7 1082
9.1%
1 1006
8.4%
4 867
7.3%
5 750
 
6.3%
9 512
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 30
96.8%
/ 1
 
3.2%
Space Separator
ValueCountFrequency (%)
1439
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1429
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14881
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2098
14.1%
0 2035
13.7%
1439
9.7%
- 1429
9.6%
6 1273
8.6%
3 1159
7.8%
8 1146
7.7%
7 1082
7.3%
1 1006
6.8%
4 867
5.8%
Other values (6) 1347
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2098
14.1%
0 2035
13.7%
1439
9.7%
- 1429
9.6%
6 1273
8.6%
3 1159
7.8%
8 1146
7.7%
7 1082
7.3%
1 1006
6.8%
4 867
5.8%
Other values (6) 1347
9.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1603
Missing (%)100.0%
Memory size14.2 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct91
Distinct (%)15.9%
Missing1029
Missing (%)64.2%
Infinite0
Infinite (%)0.0%
Mean150271.99
Minimum150010
Maximum157040
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:33.560833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150010
5-th percentile150010
Q1150041
median150050
Q3150800
95-th percentile150860
Maximum157040
Range7030
Interquartile range (IQR)759

Descriptive statistics

Standard deviation452.22825
Coefficient of variation (CV)0.0030093981
Kurtosis86.558704
Mean150271.99
Median Absolute Deviation (MAD)20
Skewness6.3893524
Sum86256124
Variance204510.39
MonotonicityNot monotonic
2024-04-18T07:26:33.684955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150041 85
 
5.3%
150070 69
 
4.3%
150010 42
 
2.6%
150050 38
 
2.4%
150800 35
 
2.2%
150033 25
 
1.6%
150043 16
 
1.0%
150035 11
 
0.7%
150837 11
 
0.7%
150803 10
 
0.6%
Other values (81) 232
 
14.5%
(Missing) 1029
64.2%
ValueCountFrequency (%)
150010 42
2.6%
150030 7
 
0.4%
150031 2
 
0.1%
150032 5
 
0.3%
150033 25
1.6%
150034 5
 
0.3%
150035 11
 
0.7%
150036 8
 
0.5%
150037 7
 
0.4%
150038 7
 
0.4%
ValueCountFrequency (%)
157040 1
 
0.1%
152050 1
 
0.1%
150997 1
 
0.1%
150992 1
 
0.1%
150975 1
 
0.1%
150972 3
0.2%
150958 3
0.2%
150903 1
 
0.1%
150899 1
 
0.1%
150888 1
 
0.1%

지번주소
Text

MISSING 

Distinct841
Distinct (%)64.6%
Missing302
Missing (%)18.8%
Memory size12.7 KiB
2024-04-18T07:26:33.897545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length42
Mean length28.200615
Min length14

Characters and Unicode

Total characters36689
Distinct characters326
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

Unique687 ?
Unique (%)52.8%

Sample

1st row서울특별시 영등포구 대림동***-**
2nd row서울특별시 영등포구 대림동****-* **
3rd row서울특별시 영등포구 대림동***-*
4th row서울특별시 영등포구 당산동*가 **-* 문래역 대우미래사랑*차
5th row서울특별시 영등포구 신길동***-*
ValueCountFrequency (%)
영등포구 1299
19.1%
서울특별시 1268
18.6%
호 739
10.9%
번지 709
10.4%
당산동*가 366
 
5.4%
276
 
4.1%
층 253
 
3.7%
대림동 215
 
3.2%
여의도동 160
 
2.4%
영등포동*가 130
 
1.9%
Other values (540) 1393
20.5%
2024-04-18T07:26:34.239479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 7188
19.6%
5571
15.2%
영 1497
 
4.1%
포 1470
 
4.0%
등 1466
 
4.0%
동 1361
 
3.7%
시 1323
 
3.6%
서 1316
 
3.6%
구 1305
 
3.6%
울 1305
 
3.6%
Other values (316) 12887
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23080
62.9%
Other Punctuation 7205
 
19.6%
Space Separator 5571
 
15.2%
Dash Punctuation 639
 
1.7%
Uppercase Letter 106
 
0.3%
Lowercase Letter 47
 
0.1%
Decimal Number 25
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1497
 
6.5%
포 1470
 
6.4%
등 1466
 
6.4%
동 1361
 
5.9%
시 1323
 
5.7%
서 1316
 
5.7%
구 1305
 
5.7%
울 1305
 
5.7%
특 1271
 
5.5%
별 1270
 
5.5%
Other values (272) 9496
41.1%
Uppercase Letter
ValueCountFrequency (%)
B 20
18.9%
K 17
16.0%
S 12
11.3%
V 9
8.5%
A 9
8.5%
T 6
 
5.7%
H 5
 
4.7%
I 5
 
4.7%
D 4
 
3.8%
M 3
 
2.8%
Other values (8) 16
15.1%
Decimal Number
ValueCountFrequency (%)
5 5
20.0%
1 5
20.0%
3 4
16.0%
2 3
12.0%
7 3
12.0%
4 2
 
8.0%
9 1
 
4.0%
6 1
 
4.0%
0 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 15
31.9%
n 9
19.1%
c 7
14.9%
t 7
14.9%
r 7
14.9%
i 1
 
2.1%
z 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
* 7188
99.8%
, 9
 
0.1%
/ 6
 
0.1%
@ 1
 
< 0.1%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 639
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23080
62.9%
Common 13456
36.7%
Latin 153
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1497
 
6.5%
포 1470
 
6.4%
등 1466
 
6.4%
동 1361
 
5.9%
시 1323
 
5.7%
서 1316
 
5.7%
구 1305
 
5.7%
울 1305
 
5.7%
특 1271
 
5.5%
별 1270
 
5.5%
Other values (272) 9496
41.1%
Latin
ValueCountFrequency (%)
B 20
13.1%
K 17
11.1%
e 15
 
9.8%
S 12
 
7.8%
n 9
 
5.9%
V 9
 
5.9%
A 9
 
5.9%
c 7
 
4.6%
t 7
 
4.6%
r 7
 
4.6%
Other values (15) 41
26.8%
Common
ValueCountFrequency (%)
* 7188
53.4%
5571
41.4%
- 639
 
4.7%
, 9
 
0.1%
( 7
 
0.1%
) 7
 
0.1%
/ 6
 
< 0.1%
5 5
 
< 0.1%
1 5
 
< 0.1%
3 4
 
< 0.1%
Other values (9) 15
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23080
62.9%
ASCII 13609
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 7188
52.8%
5571
40.9%
- 639
 
4.7%
B 20
 
0.1%
K 17
 
0.1%
e 15
 
0.1%
S 12
 
0.1%
, 9
 
0.1%
n 9
 
0.1%
V 9
 
0.1%
Other values (34) 120
 
0.9%
Hangul
ValueCountFrequency (%)
영 1497
 
6.5%
포 1470
 
6.4%
등 1466
 
6.4%
동 1361
 
5.9%
시 1323
 
5.7%
서 1316
 
5.7%
구 1305
 
5.7%
울 1305
 
5.7%
특 1271
 
5.5%
별 1270
 
5.5%
Other values (272) 9496
41.1%

도로명주소
Text

MISSING 

Distinct909
Distinct (%)80.4%
Missing473
Missing (%)29.5%
Memory size12.7 KiB
2024-04-18T07:26:34.465029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length53
Mean length36.557522
Min length23

Characters and Unicode

Total characters41310
Distinct characters344
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

Unique806 ?
Unique (%)71.3%

Sample

1st row서울특별시 영등포구 영등포로 ***, 문래역 대우미래사랑*차 ***동 ***호 (당산동*가)
2nd row서울특별시 영등포구 도림로 *** (대림동,*층 서쪽일부사무실*칸)
3rd row서울특별시 영등포구 선유동*로 **-* (양평동*가, *층)
4th row서울특별시 영등포구 가마산로 *** (대림동,*층)
5th row서울특별시 영등포구 도림로 ***, 남영빌딩 *층 ***호 (대림동)
ValueCountFrequency (%)
1163
16.1%
서울특별시 1130
15.6%
영등포구 1127
15.6%
호 461
 
6.4%
층 327
 
4.5%
영등포로 168
 
2.3%
당산동*가 163
 
2.3%
대림동 150
 
2.1%
신길동 98
 
1.4%
여의도동 93
 
1.3%
Other values (721) 2348
32.5%
2024-04-18T07:26:34.842125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 6880
 
16.7%
6125
 
14.8%
영 1634
 
4.0%
포 1494
 
3.6%
등 1490
 
3.6%
, 1323
 
3.2%
동 1285
 
3.1%
시 1193
 
2.9%
서 1155
 
2.8%
로 1137
 
2.8%
Other values (334) 17594
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24273
58.8%
Other Punctuation 8215
 
19.9%
Space Separator 6125
 
14.8%
Open Punctuation 1136
 
2.7%
Close Punctuation 1136
 
2.7%
Dash Punctuation 173
 
0.4%
Uppercase Letter 139
 
0.3%
Lowercase Letter 66
 
0.2%
Decimal Number 40
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1634
 
6.7%
포 1494
 
6.2%
등 1490
 
6.1%
동 1285
 
5.3%
시 1193
 
4.9%
서 1155
 
4.8%
로 1137
 
4.7%
울 1135
 
4.7%
구 1134
 
4.7%
특 1133
 
4.7%
Other values (290) 11483
47.3%
Uppercase Letter
ValueCountFrequency (%)
K 29
20.9%
B 27
19.4%
S 14
10.1%
E 11
 
7.9%
V 11
 
7.9%
T 9
 
6.5%
A 8
 
5.8%
I 7
 
5.0%
D 5
 
3.6%
H 4
 
2.9%
Other values (7) 14
10.1%
Decimal Number
ValueCountFrequency (%)
1 9
22.5%
3 7
17.5%
2 6
15.0%
5 5
12.5%
0 4
10.0%
4 3
 
7.5%
7 2
 
5.0%
9 2
 
5.0%
8 1
 
2.5%
6 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
* 6880
83.7%
, 1323
 
16.1%
/ 7
 
0.1%
. 3
 
< 0.1%
& 1
 
< 0.1%
@ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 20
30.3%
n 16
24.2%
t 10
15.2%
r 10
15.2%
c 10
15.2%
Space Separator
ValueCountFrequency (%)
6125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 173
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24273
58.8%
Common 16832
40.7%
Latin 205
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1634
 
6.7%
포 1494
 
6.2%
등 1490
 
6.1%
동 1285
 
5.3%
시 1193
 
4.9%
서 1155
 
4.8%
로 1137
 
4.7%
울 1135
 
4.7%
구 1134
 
4.7%
특 1133
 
4.7%
Other values (290) 11483
47.3%
Common
ValueCountFrequency (%)
* 6880
40.9%
6125
36.4%
, 1323
 
7.9%
( 1136
 
6.7%
) 1136
 
6.7%
- 173
 
1.0%
1 9
 
0.1%
3 7
 
< 0.1%
/ 7
 
< 0.1%
~ 6
 
< 0.1%
Other values (12) 30
 
0.2%
Latin
ValueCountFrequency (%)
K 29
14.1%
B 27
13.2%
e 20
9.8%
n 16
 
7.8%
S 14
 
6.8%
E 11
 
5.4%
V 11
 
5.4%
t 10
 
4.9%
r 10
 
4.9%
c 10
 
4.9%
Other values (12) 47
22.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24273
58.8%
ASCII 17037
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 6880
40.4%
6125
36.0%
, 1323
 
7.8%
( 1136
 
6.7%
) 1136
 
6.7%
- 173
 
1.0%
K 29
 
0.2%
B 27
 
0.2%
e 20
 
0.1%
n 16
 
0.1%
Other values (34) 172
 
1.0%
Hangul
ValueCountFrequency (%)
영 1634
 
6.7%
포 1494
 
6.2%
등 1490
 
6.1%
동 1285
 
5.3%
시 1193
 
4.9%
서 1155
 
4.8%
로 1137
 
4.7%
울 1135
 
4.7%
구 1134
 
4.7%
특 1133
 
4.7%
Other values (290) 11483
47.3%

도로명우편번호
Text

MISSING 

Distinct247
Distinct (%)37.1%
Missing938
Missing (%)58.5%
Memory size12.7 KiB
2024-04-18T07:26:35.105593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4105263
Min length5

Characters and Unicode

Total characters3598
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

Unique110 ?
Unique (%)16.5%

Sample

1st row07291
2nd row150862
3rd row07422
4th row150832
5th row150813
ValueCountFrequency (%)
07299 18
 
2.7%
07445 15
 
2.3%
07333 13
 
2.0%
150837 12
 
1.8%
07217 11
 
1.7%
150037 10
 
1.5%
07294 10
 
1.5%
07255 10
 
1.5%
150033 9
 
1.4%
150800 9
 
1.4%
Other values (237) 548
82.4%
2024-04-18T07:26:35.532126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 874
24.3%
7 552
15.3%
1 450
12.5%
5 408
11.3%
2 362
10.1%
3 297
 
8.3%
8 242
 
6.7%
4 172
 
4.8%
9 145
 
4.0%
6 94
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3596
99.9%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 874
24.3%
7 552
15.4%
1 450
12.5%
5 408
11.3%
2 362
10.1%
3 297
 
8.3%
8 242
 
6.7%
4 172
 
4.8%
9 145
 
4.0%
6 94
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3598
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 874
24.3%
7 552
15.3%
1 450
12.5%
5 408
11.3%
2 362
10.1%
3 297
 
8.3%
8 242
 
6.7%
4 172
 
4.8%
9 145
 
4.0%
6 94
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3598
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 874
24.3%
7 552
15.3%
1 450
12.5%
5 408
11.3%
2 362
10.1%
3 297
 
8.3%
8 242
 
6.7%
4 172
 
4.8%
9 145
 
4.0%
6 94
 
2.6%

사업장명
Text

Distinct1552
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
2024-04-18T07:26:35.810431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length7.3736744
Min length2

Characters and Unicode

Total characters11820
Distinct characters603
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

Unique1509 ?
Unique (%)94.1%

Sample

1st row현대영재시스템
2nd row한일상사
3rd row한성물산
4th row(주)생그린영등포지사
5th row영신대우자동차판매(주)
ValueCountFrequency (%)
주식회사 195
 
9.4%
주 39
 
1.9%
인셀덤 14
 
0.7%
유니베라 10
 
0.5%
마임 9
 
0.4%
한독화장품 9
 
0.4%
코리아 7
 
0.3%
영등포지사 7
 
0.3%
에치와이 5
 
0.2%
대운상사 4
 
0.2%
Other values (1673) 1770
85.5%
2024-04-18T07:26:36.225144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 598
 
5.1%
466
 
3.9%
) 443
 
3.7%
( 441
 
3.7%
이 399
 
3.4%
사 380
 
3.2%
스 330
 
2.8%
회 220
 
1.9%
식 215
 
1.8%
리 186
 
1.6%
Other values (593) 8142
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9907
83.8%
Space Separator 466
 
3.9%
Close Punctuation 443
 
3.7%
Open Punctuation 441
 
3.7%
Uppercase Letter 316
 
2.7%
Lowercase Letter 152
 
1.3%
Other Punctuation 60
 
0.5%
Decimal Number 26
 
0.2%
Dash Punctuation 7
 
0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 598
 
6.0%
이 399
 
4.0%
사 380
 
3.8%
스 330
 
3.3%
회 220
 
2.2%
식 215
 
2.2%
리 186
 
1.9%
아 177
 
1.8%
에 146
 
1.5%
상 144
 
1.5%
Other values (531) 7112
71.8%
Uppercase Letter
ValueCountFrequency (%)
S 38
 
12.0%
C 29
 
9.2%
O 20
 
6.3%
I 19
 
6.0%
L 18
 
5.7%
B 17
 
5.4%
N 16
 
5.1%
T 16
 
5.1%
E 15
 
4.7%
A 14
 
4.4%
Other values (14) 114
36.1%
Lowercase Letter
ValueCountFrequency (%)
e 25
16.4%
o 17
11.2%
r 13
 
8.6%
t 12
 
7.9%
a 11
 
7.2%
l 10
 
6.6%
s 8
 
5.3%
u 7
 
4.6%
d 7
 
4.6%
p 6
 
3.9%
Other values (11) 36
23.7%
Decimal Number
ValueCountFrequency (%)
2 7
26.9%
1 7
26.9%
9 5
19.2%
8 2
 
7.7%
4 2
 
7.7%
7 1
 
3.8%
6 1
 
3.8%
3 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 36
60.0%
& 16
26.7%
, 7
 
11.7%
? 1
 
1.7%
Space Separator
ValueCountFrequency (%)
466
100.0%
Close Punctuation
ValueCountFrequency (%)
) 443
100.0%
Open Punctuation
ValueCountFrequency (%)
( 441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9898
83.7%
Common 1443
 
12.2%
Latin 468
 
4.0%
Han 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 598
 
6.0%
이 399
 
4.0%
사 380
 
3.8%
스 330
 
3.3%
회 220
 
2.2%
식 215
 
2.2%
리 186
 
1.9%
아 177
 
1.8%
에 146
 
1.5%
상 144
 
1.5%
Other values (521) 7103
71.8%
Latin
ValueCountFrequency (%)
S 38
 
8.1%
C 29
 
6.2%
e 25
 
5.3%
O 20
 
4.3%
I 19
 
4.1%
L 18
 
3.8%
B 17
 
3.6%
o 17
 
3.6%
N 16
 
3.4%
T 16
 
3.4%
Other values (35) 253
54.1%
Common
ValueCountFrequency (%)
466
32.3%
) 443
30.7%
( 441
30.6%
. 36
 
2.5%
& 16
 
1.1%
2 7
 
0.5%
1 7
 
0.5%
- 7
 
0.5%
, 7
 
0.5%
9 5
 
0.3%
Other values (6) 8
 
0.6%
Han
ValueCountFrequency (%)
塡 1
9.1%
企 1
9.1%
業 1
9.1%
盛 1
9.1%
社 1
9.1%
孝 1
9.1%
秀 1
9.1%
韓 1
9.1%
光 1
9.1%
貿 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9896
83.7%
ASCII 1911
 
16.2%
CJK 11
 
0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 598
 
6.0%
이 399
 
4.0%
사 380
 
3.8%
스 330
 
3.3%
회 220
 
2.2%
식 215
 
2.2%
리 186
 
1.9%
아 177
 
1.8%
에 146
 
1.5%
상 144
 
1.5%
Other values (520) 7101
71.8%
ASCII
ValueCountFrequency (%)
466
24.4%
) 443
23.2%
( 441
23.1%
S 38
 
2.0%
. 36
 
1.9%
C 29
 
1.5%
e 25
 
1.3%
O 20
 
1.0%
I 19
 
1.0%
L 18
 
0.9%
Other values (51) 376
19.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%
CJK
ValueCountFrequency (%)
塡 1
9.1%
企 1
9.1%
業 1
9.1%
盛 1
9.1%
社 1
9.1%
孝 1
9.1%
秀 1
9.1%
韓 1
9.1%
光 1
9.1%
貿 1
9.1%

최종수정일자
Date

Distinct1458
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum2007-07-09 20:31:19
Maximum2024-04-16 16:01:33
2024-04-18T07:26:36.343763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:36.457820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
I
1179 
U
424 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1179
73.5%
U 424
 
26.5%

Length

2024-04-18T07:26:36.564314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:26:36.643171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1179
73.5%
u 424
 
26.5%

데이터갱신일자
Date

Distinct273
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size12.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-04-18T07:26:36.734437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:26:36.838551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1603
Missing (%)100.0%
Memory size14.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct630
Distinct (%)54.9%
Missing455
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean191419.2
Minimum189145.46
Maximum194561.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:36.951112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189145.46
5-th percentile190161.74
Q1190862.08
median191087.93
Q3191767.91
95-th percentile193490.7
Maximum194561.75
Range5416.2901
Interquartile range (IQR)905.82389

Descriptive statistics

Standard deviation980.74424
Coefficient of variation (CV)0.0051235415
Kurtosis0.59917038
Mean191419.2
Median Absolute Deviation (MAD)449.24608
Skewness1.0286053
Sum2.1974924 × 108
Variance961859.25
MonotonicityNot monotonic
2024-04-18T07:26:37.070429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190923.551317757 109
 
6.8%
191580.646388785 18
 
1.1%
191108.975924 14
 
0.9%
192654.926389121 13
 
0.8%
191285.015028707 11
 
0.7%
191015.887217843 10
 
0.6%
193469.554731741 10
 
0.6%
190555.768991595 9
 
0.6%
190941.054351896 9
 
0.6%
190401.596787693 8
 
0.5%
Other values (620) 937
58.5%
(Missing) 455
28.4%
ValueCountFrequency (%)
189145.455894355 1
 
0.1%
189549.847307536 1
 
0.1%
189682.022243843 3
0.2%
189700.355755718 2
0.1%
189734.544016734 1
 
0.1%
189737.063295458 1
 
0.1%
189740.94885729 2
0.1%
189749.797733542 1
 
0.1%
189785.752470051 2
0.1%
189812.521251622 1
 
0.1%
ValueCountFrequency (%)
194561.746032498 2
0.1%
194530.535390096 4
0.2%
194504.656267957 2
0.1%
194370.32715363 1
 
0.1%
194233.681125084 1
 
0.1%
194084.264051974 1
 
0.1%
194028.635844427 3
0.2%
193989.272586157 1
 
0.1%
193896.282065175 1
 
0.1%
193844.169062846 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct631
Distinct (%)55.0%
Missing455
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean446057.13
Minimum442649.87
Maximum449483.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:37.216512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442649.87
5-th percentile443407.26
Q1445160.71
median446480.95
Q3446978.64
95-th percentile448006.55
Maximum449483.69
Range6833.8148
Interquartile range (IQR)1817.9294

Descriptive statistics

Standard deviation1385.6736
Coefficient of variation (CV)0.0031064935
Kurtosis-0.33129093
Mean446057.13
Median Absolute Deviation (MAD)680.30793
Skewness-0.69120617
Sum5.1207359 × 108
Variance1920091.3
MonotonicityNot monotonic
2024-04-18T07:26:37.327971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446575.396546634 109
 
6.8%
446320.718339983 18
 
1.1%
446171.686827 14
 
0.9%
445917.021217324 13
 
0.8%
442649.873938101 11
 
0.7%
444422.848045604 10
 
0.6%
446508.068667777 10
 
0.6%
446698.814322782 9
 
0.6%
446449.917568696 8
 
0.5%
446339.064053872 8
 
0.5%
Other values (621) 938
58.5%
(Missing) 455
28.4%
ValueCountFrequency (%)
442649.873938101 11
0.7%
442663.748373343 2
 
0.1%
442704.061942942 1
 
0.1%
442710.662421803 2
 
0.1%
442744.165176674 1
 
0.1%
442844.492647284 1
 
0.1%
442854.148764609 1
 
0.1%
442905.116903156 1
 
0.1%
442919.522195885 3
 
0.2%
442935.312945877 1
 
0.1%
ValueCountFrequency (%)
449483.688743756 1
0.1%
448779.57454276 1
0.1%
448656.726986041 1
0.1%
448642.112414847 1
0.1%
448531.133666775 1
0.1%
448495.794800958 1
0.1%
448495.395437399 1
0.1%
448471.434635038 2
0.1%
448436.126322646 1
0.1%
448421.881545422 1
0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct238
Distinct (%)42.4%
Missing1042
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean2.2823889 × 1010
Minimum0
Maximum4.1363129 × 1012
Zeros217
Zeros (%)13.5%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:37.440431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16800000
Q32 × 108
95-th percentile5.3281404 × 109
Maximum4.1363129 × 1012
Range4.1363129 × 1012
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation2.6320572 × 1011
Coefficient of variation (CV)11.532028
Kurtosis215.36413
Mean2.2823889 × 1010
Median Absolute Deviation (MAD)16800000
Skewness14.359782
Sum1.2804202 × 1013
Variance6.9277253 × 1022
MonotonicityNot monotonic
2024-04-18T07:26:37.570266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 217
 
13.5%
50000000 29
 
1.8%
10000000 18
 
1.1%
1 14
 
0.9%
100000000 13
 
0.8%
5000000 9
 
0.6%
200000000 6
 
0.4%
300000000 6
 
0.4%
30000000 5
 
0.3%
20000000 5
 
0.3%
Other values (228) 239
 
14.9%
(Missing) 1042
65.0%
ValueCountFrequency (%)
0 217
13.5%
1 14
 
0.9%
111 1
 
0.1%
10000 1
 
0.1%
200000 1
 
0.1%
500000 2
 
0.1%
1000000 1
 
0.1%
2000000 3
 
0.2%
2071204 1
 
0.1%
3000000 2
 
0.1%
ValueCountFrequency (%)
4136312863585 1
0.1%
4111211369976 1
0.1%
1967055000000 1
0.1%
916153621668 1
0.1%
460800000000 1
0.1%
281567329664 1
0.1%
229246050186 1
0.1%
65108417946 1
0.1%
62121669111 1
0.1%
60592610105 1
0.1%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct207
Distinct (%)36.9%
Missing1042
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean1.975827 × 1010
Minimum0
Maximum3.9418009 × 1012
Zeros334
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-04-18T07:26:37.690313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q375442931
95-th percentile3.1235437 × 109
Maximum3.9418009 × 1012
Range3.9418009 × 1012
Interquartile range (IQR)75442931

Descriptive statistics

Standard deviation2.383267 × 1011
Coefficient of variation (CV)12.062124
Kurtosis217.78422
Mean1.975827 × 1010
Median Absolute Deviation (MAD)0
Skewness14.447343
Sum1.108439 × 1013
Variance5.6799616 × 1022
MonotonicityNot monotonic
2024-04-18T07:26:37.818711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 334
 
20.8%
1 14
 
0.9%
30000000 3
 
0.2%
100000000 3
 
0.2%
106633370 2
 
0.1%
151359863 2
 
0.1%
300000000 2
 
0.1%
50000000 2
 
0.1%
672084565 1
 
0.1%
6772125467 1
 
0.1%
Other values (197) 197
 
12.3%
(Missing) 1042
65.0%
ValueCountFrequency (%)
0 334
20.8%
1 14
 
0.9%
10 1
 
0.1%
111 1
 
0.1%
15315 1
 
0.1%
149180 1
 
0.1%
200000 1
 
0.1%
289803 1
 
0.1%
542000 1
 
0.1%
605000 1
 
0.1%
ValueCountFrequency (%)
3941800875811 1
0.1%
3496058346300 1
0.1%
1866855000000 1
0.1%
792291956975 1
0.1%
300700000000 1
0.1%
219715478808 1
0.1%
73860198399 1
0.1%
68996317309 1
0.1%
37468851717 1
0.1%
30839557154 1
0.1%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct152
Distinct (%)27.0%
Missing1041
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean2.5266406 × 109
Minimum-6.7541008 × 108
Maximum6.4025452 × 1011
Zeros144
Zeros (%)9.0%
Negative17
Negative (%)1.1%
Memory size14.2 KiB
2024-04-18T07:26:37.977191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6.7541008 × 108
5-th percentile0
Q10
median30684774
Q31 × 108
95-th percentile1.0971897 × 109
Maximum6.4025452 × 1011
Range6.4092993 × 1011
Interquartile range (IQR)1 × 108

Descriptive statistics

Standard deviation2.9547332 × 1010
Coefficient of variation (CV)11.694315
Kurtosis391.98901
Mean2.5266406 × 109
Median Absolute Deviation (MAD)30684774
Skewness18.774981
Sum1.419972 × 1012
Variance8.730448 × 1020
MonotonicityNot monotonic
2024-04-18T07:26:38.092942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 144
 
9.0%
50000000 86
 
5.4%
100000000 45
 
2.8%
10000000 35
 
2.2%
300000000 17
 
1.1%
30000000 15
 
0.9%
1 14
 
0.9%
20000000 11
 
0.7%
500000000 9
 
0.6%
200000000 9
 
0.6%
Other values (142) 177
 
11.0%
(Missing) 1041
64.9%
ValueCountFrequency (%)
-675410076 1
0.1%
-593058001 1
0.1%
-431018695 1
0.1%
-335778928 1
0.1%
-194574557 1
0.1%
-142548264 1
0.1%
-137474661 1
0.1%
-136984178 1
0.1%
-133512745 1
0.1%
-91541836 1
0.1%
ValueCountFrequency (%)
640254517285 1
0.1%
169410494165 1
0.1%
160100000000 1
0.1%
123861664693 1
0.1%
100200000000 1
0.1%
47946601741 1
0.1%
20705114726 1
0.1%
17401000000 1
0.1%
13411800000 1
0.1%
10157085000 1
0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1603
Missing (%)100.0%
Memory size14.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03180000199631801172320001919961205<NA>3폐업3폐업처리20110104<NA><NA><NA>02 834 7802<NA><NA>서울특별시 영등포구 대림동***-**<NA><NA>현대영재시스템2011-01-04 16:58:56I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
13180000199631801172320004519961025200710224취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 833 6801<NA><NA>서울특별시 영등포구 대림동****-* **<NA><NA>한일상사2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
23180000199631801172320007719961108200710224취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 843 5571<NA><NA>서울특별시 영등포구 대림동***-*<NA><NA>한성물산2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
33180000199631801172320008219961111<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 **-* 문래역 대우미래사랑*차서울특별시 영등포구 영등포로 ***, 문래역 대우미래사랑*차 ***동 ***호 (당산동*가)07291(주)생그린영등포지사2021-02-22 10:26:04U2021-02-24 02:40:00.0<NA>190526.232657446521.25266<NA><NA><NA><NA>
43180000199631801172320008719961113<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 834 6666<NA><NA>서울특별시 영등포구 신길동***-*<NA><NA>영신대우자동차판매(주)2012-08-23 22:18:21I2018-08-31 23:59:59.0<NA><NA><NA>111<NA>
53180000199631801172320009019961113<NA>3폐업3폐업처리20120523<NA><NA><NA>02 849 4585<NA><NA>서울특별시 영등포구 신길동***-**<NA><NA>대림대우자동차판매2012-05-23 16:29:39I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
63180000199631801172320009119961113200710224취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 675 1461<NA><NA>서울특별시 영등포구 당산동*가**-*<NA><NA>남구대우자동차판매주2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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