Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells77561
Missing cells (%)26.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory252.0 B

Variable types

Categorical9
Numeric6
DateTime7
Text6
Unsupported1

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-18820/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
판매방식명 is highly imbalanced (64.3%)Imbalance
인허가취소일자 has 9659 (96.6%) missing valuesMissing
폐업일자 has 7095 (71.0%) missing valuesMissing
휴업시작일자 has 9948 (99.5%) missing valuesMissing
휴업종료일자 has 9948 (99.5%) missing valuesMissing
재개업일자 has 9982 (99.8%) missing valuesMissing
전화번호 has 4514 (45.1%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 8279 (82.8%) missing valuesMissing
지번주소 has 2130 (21.3%) missing valuesMissing
도로명주소 has 1152 (11.5%) missing valuesMissing
도로명우편번호 has 2714 (27.1%) missing valuesMissing
좌표정보(X) has 1070 (10.7%) missing valuesMissing
좌표정보(Y) has 1070 (10.7%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = 40.08331999)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 19:50:06.057845
Analysis finished2024-04-29 19:50:07.845692
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3180000
10000 

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 10000
100.0%

Length

2024-04-30T04:50:07.908759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:07.982894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 10000
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0155125 × 1018
Minimum1.996318 × 1018
Maximum2.022318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:08.068216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996318 × 1018
5-th percentile2.005318 × 1018
Q12.011318 × 1018
median2.017318 × 1018
Q32.020318 × 1018
95-th percentile2.022318 × 1018
Maximum2.022318 × 1018
Range2.6000013 × 1016
Interquartile range (IQR)9.0000084 × 1015

Descriptive statistics

Standard deviation5.6430051 × 1015
Coefficient of variation (CV)0.0027997867
Kurtosis-0.85569626
Mean2.0155125 × 1018
Median Absolute Deviation (MAD)4.0000084 × 1015
Skewness-0.57077085
Sum-7.1660882 × 1018
Variance3.1843507 × 1031
MonotonicityNot monotonic
2024-04-30T04:50:08.179796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007318011730205435 1
 
< 0.1%
2007318011730205041 1
 
< 0.1%
2005318011730202673 1
 
< 0.1%
2021318024730200504 1
 
< 0.1%
2021318024730203251 1
 
< 0.1%
2021318024730202304 1
 
< 0.1%
2006318011730203897 1
 
< 0.1%
2012318016330200162 1
 
< 0.1%
2002318011730200567 1
 
< 0.1%
2019318022630201566 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1996318011730200116 1
< 0.1%
1997318011730200661 1
< 0.1%
1997318011730200741 1
< 0.1%
1997318011730200908 1
< 0.1%
1998318011730200186 1
< 0.1%
1998318011730201416 1
< 0.1%
1998318011730201502 1
< 0.1%
1999318011730201821 1
< 0.1%
1999318011730201939 1
< 0.1%
1999318011730202229 1
< 0.1%
ValueCountFrequency (%)
2022318024730202578 1
< 0.1%
2022318024730202577 1
< 0.1%
2022318024730202564 1
< 0.1%
2022318024730202559 1
< 0.1%
2022318024730202558 1
< 0.1%
2022318024730202554 1
< 0.1%
2022318024730202549 1
< 0.1%
2022318024730202547 1
< 0.1%
2022318024730202540 1
< 0.1%
2022318024730202539 1
< 0.1%

인허가일자
Date

Distinct3846
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1996-08-29 00:00:00
Maximum2022-09-14 00:00:00
2024-04-30T04:50:08.298148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:08.427128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)2.3%
Missing9659
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean20074557
Minimum20070905
Maximum20161209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:08.525593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070905
5-th percentile20070905
Q120070905
median20070905
Q320080710
95-th percentile20080710
Maximum20161209
Range90304
Interquartile range (IQR)9805

Descriptive statistics

Standard deviation7280.7193
Coefficient of variation (CV)0.00036268393
Kurtosis63.733583
Mean20074557
Median Absolute Deviation (MAD)0
Skewness6.1944172
Sum6.8454241 × 109
Variance53008873
MonotonicityNot monotonic
2024-04-30T04:50:08.620058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20070905 206
 
2.1%
20080710 108
 
1.1%
20071205 22
 
0.2%
20071001 1
 
< 0.1%
20110906 1
 
< 0.1%
20161209 1
 
< 0.1%
20071107 1
 
< 0.1%
20120221 1
 
< 0.1%
(Missing) 9659
96.6%
ValueCountFrequency (%)
20070905 206
2.1%
20071001 1
 
< 0.1%
20071107 1
 
< 0.1%
20071205 22
 
0.2%
20080710 108
1.1%
20110906 1
 
< 0.1%
20120221 1
 
< 0.1%
20161209 1
 
< 0.1%
ValueCountFrequency (%)
20161209 1
 
< 0.1%
20120221 1
 
< 0.1%
20110906 1
 
< 0.1%
20080710 108
1.1%
20071205 22
 
0.2%
20071107 1
 
< 0.1%
20071001 1
 
< 0.1%
20070905 206
2.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
4766 
3
2500 
4
2289 
5
 
405
2
 
40

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 4766
47.7%
3 2500
25.0%
4 2289
22.9%
5 405
 
4.0%
2 40
 
0.4%

Length

2024-04-30T04:50:08.711133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:08.943563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 4766
47.7%
3 2500
25.0%
4 2289
22.9%
5 405
 
4.0%
2 40
 
0.4%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
4766 
폐업
2500 
취소/말소/만료/정지/중지
2289 
제외/삭제/전출
 
405
휴업
 
40

Length

Max length14
Median length8
Mean length6.4196
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 4766
47.7%
폐업 2500
25.0%
취소/말소/만료/정지/중지 2289
22.9%
제외/삭제/전출 405
 
4.0%
휴업 40
 
0.4%

Length

2024-04-30T04:50:09.051023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:09.151799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 4766
47.7%
폐업 2500
25.0%
취소/말소/만료/정지/중지 2289
22.9%
제외/삭제/전출 405
 
4.0%
휴업 40
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9367
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:09.237033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation2.2838158
Coefficient of variation (CV)0.77768101
Kurtosis-0.77498674
Mean2.9367
Median Absolute Deviation (MAD)2
Skewness0.8383787
Sum29367
Variance5.2158147
MonotonicityNot monotonic
2024-04-30T04:50:09.320669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 4765
47.6%
3 2500
25.0%
7 1945
19.4%
5 405
 
4.0%
4 344
 
3.4%
2 40
 
0.4%
6 1
 
< 0.1%
ValueCountFrequency (%)
1 4765
47.6%
2 40
 
0.4%
3 2500
25.0%
4 344
 
3.4%
5 405
 
4.0%
6 1
 
< 0.1%
7 1945
19.4%
ValueCountFrequency (%)
7 1945
19.4%
6 1
 
< 0.1%
5 405
 
4.0%
4 344
 
3.4%
3 2500
25.0%
2 40
 
0.4%
1 4765
47.6%

상세영업상태명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상영업
4765 
폐업처리
2500 
직권말소
1945 
타시군구이관
 
405
직권취소
 
344
Other values (2)
 
41

Length

Max length6
Median length4
Mean length4.0812
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 4765
47.6%
폐업처리 2500
25.0%
직권말소 1945
19.4%
타시군구이관 405
 
4.0%
직권취소 344
 
3.4%
휴업처리 40
 
0.4%
타시군구전입 1
 
< 0.1%

Length

2024-04-30T04:50:09.446214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:09.546468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 4765
47.6%
폐업처리 2500
25.0%
직권말소 1945
19.4%
타시군구이관 405
 
4.0%
직권취소 344
 
3.4%
휴업처리 40
 
0.4%
타시군구전입 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1773
Distinct (%)61.0%
Missing7095
Missing (%)71.0%
Memory size156.2 KiB
Minimum2007-05-08 00:00:00
Maximum2024-04-25 00:00:00
2024-04-30T04:50:09.661615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:09.783890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct51
Distinct (%)98.1%
Missing9948
Missing (%)99.5%
Memory size156.2 KiB
Minimum2007-06-25 00:00:00
Maximum2024-07-28 00:00:00
2024-04-30T04:50:09.909267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:10.046835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct46
Distinct (%)88.5%
Missing9948
Missing (%)99.5%
Memory size156.2 KiB
Minimum2007-12-31 00:00:00
Maximum2030-12-31 00:00:00
2024-04-30T04:50:10.165066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:10.279998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

재개업일자
Date

MISSING 

Distinct16
Distinct (%)88.9%
Missing9982
Missing (%)99.8%
Memory size156.2 KiB
Minimum2008-01-02 00:00:00
Maximum2022-09-21 00:00:00
2024-04-30T04:50:10.380005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:10.470395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

전화번호
Text

MISSING 

Distinct5063
Distinct (%)92.3%
Missing4514
Missing (%)45.1%
Memory size156.2 KiB
2024-04-30T04:50:10.652643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length11.099708
Min length1

Characters and Unicode

Total characters60893
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

Unique4978 ?
Unique (%)90.7%

Sample

1st row02-2633-5569
2nd row02-761-9888
3rd row02-782-8369
4th row02-761-2464
5th row2672-2889
ValueCountFrequency (%)
02 1154
 
14.6%
476
 
6.0%
761 40
 
0.5%
780 38
 
0.5%
786 34
 
0.4%
785 34
 
0.4%
070 31
 
0.4%
783 27
 
0.3%
2068 26
 
0.3%
835 25
 
0.3%
Other values (5249) 6024
76.2%
2024-04-30T04:50:10.959921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9331
15.3%
2 8308
13.6%
- 7445
12.2%
7 5305
8.7%
6 4794
7.9%
8 4577
7.5%
3 4195
6.9%
3781
6.2%
1 3509
 
5.8%
5 3394
 
5.6%
Other values (7) 6254
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49195
80.8%
Dash Punctuation 7445
 
12.2%
Space Separator 3781
 
6.2%
Other Punctuation 240
 
0.4%
Close Punctuation 226
 
0.4%
Math Symbol 5
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9331
19.0%
2 8308
16.9%
7 5305
10.8%
6 4794
9.7%
8 4577
9.3%
3 4195
8.5%
1 3509
 
7.1%
5 3394
 
6.9%
4 3280
 
6.7%
9 2502
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 234
97.5%
/ 6
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 7445
100.0%
Space Separator
ValueCountFrequency (%)
3781
100.0%
Close Punctuation
ValueCountFrequency (%)
) 226
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60893
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9331
15.3%
2 8308
13.6%
- 7445
12.2%
7 5305
8.7%
6 4794
7.9%
8 4577
7.5%
3 4195
6.9%
3781
6.2%
1 3509
 
5.8%
5 3394
 
5.6%
Other values (7) 6254
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60893
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9331
15.3%
2 8308
13.6%
- 7445
12.2%
7 5305
8.7%
6 4794
7.9%
8 4577
7.5%
3 4195
6.9%
3781
6.2%
1 3509
 
5.8%
5 3394
 
5.6%
Other values (7) 6254
10.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct184
Distinct (%)10.7%
Missing8279
Missing (%)82.8%
Infinite0
Infinite (%)0.0%
Mean150438.65
Minimum121220
Maximum423010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:11.071808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum121220
5-th percentile150010
Q1150038
median150070
Q3150800
95-th percentile150899
Maximum423010
Range301790
Interquartile range (IQR)762

Descriptive statistics

Standard deviation6646.7581
Coefficient of variation (CV)0.044182517
Kurtosis1647.1734
Mean150438.65
Median Absolute Deviation (MAD)36
Skewness40.08332
Sum2.5890491 × 108
Variance44179393
MonotonicityNot monotonic
2024-04-30T04:50:11.177143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150010 217
 
2.2%
150050 136
 
1.4%
150070 116
 
1.2%
150723 66
 
0.7%
150042 42
 
0.4%
150103 41
 
0.4%
150037 38
 
0.4%
150033 36
 
0.4%
150035 33
 
0.3%
150043 33
 
0.3%
Other values (174) 963
 
9.6%
(Missing) 8279
82.8%
ValueCountFrequency (%)
121220 1
 
< 0.1%
136111 1
 
< 0.1%
140012 1
 
< 0.1%
140111 1
 
< 0.1%
150010 217
2.2%
150030 22
 
0.2%
150031 8
 
0.1%
150032 9
 
0.1%
150033 36
 
0.4%
150034 15
 
0.1%
ValueCountFrequency (%)
423010 1
 
< 0.1%
158090 1
 
< 0.1%
158050 1
 
< 0.1%
156030 1
 
< 0.1%
153030 1
 
< 0.1%
151913 1
 
< 0.1%
150997 1
 
< 0.1%
150993 1
 
< 0.1%
150992 3
< 0.1%
150989 2
< 0.1%

지번주소
Text

MISSING 

Distinct3386
Distinct (%)43.0%
Missing2130
Missing (%)21.3%
Memory size156.2 KiB
2024-04-30T04:50:11.409670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length58
Mean length28.750826
Min length15

Characters and Unicode

Total characters226269
Distinct characters482
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2500 ?
Unique (%)31.8%

Sample

1st row서울특별시 영등포구 당산동*가 ***번지 삼익아파트 *동 ***호
2nd row서울특별시 영등포구 영등포동4가 135번지 2호 401호
3rd row서울특별시 영등포구 문래동*가 ** 문래 SK V* center
4th row서울특별시 영등포구 대림동 ***-**
5th row서울특별시 영등포구 영등포동*가 **번지 **호
ValueCountFrequency (%)
서울특별시 7869
18.8%
영등포구 7860
18.7%
번지 3813
 
9.1%
호 3601
 
8.6%
3345
 
8.0%
당산동*가 1492
 
3.6%
여의도동 1395
 
3.3%
신길동 1020
 
2.4%
양평동*가 900
 
2.1%
문래동*가 882
 
2.1%
Other values (2058) 9764
23.3%
2024-04-30T04:50:11.764104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 39185
17.3%
36290
16.0%
영 9281
 
4.1%
포 9175
 
4.1%
등 9130
 
4.0%
동 8584
 
3.8%
시 8164
 
3.6%
서 7985
 
3.5%
울 7925
 
3.5%
구 7879
 
3.5%
Other values (472) 82671
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144480
63.9%
Other Punctuation 39303
 
17.4%
Space Separator 36290
 
16.0%
Dash Punctuation 3508
 
1.6%
Uppercase Letter 1092
 
0.5%
Decimal Number 957
 
0.4%
Lowercase Letter 572
 
0.3%
Close Punctuation 27
 
< 0.1%
Open Punctuation 27
 
< 0.1%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 9281
 
6.4%
포 9175
 
6.4%
등 9130
 
6.3%
동 8584
 
5.9%
시 8164
 
5.7%
서 7985
 
5.5%
울 7925
 
5.5%
구 7879
 
5.5%
별 7876
 
5.5%
특 7873
 
5.4%
Other values (407) 60608
41.9%
Uppercase Letter
ValueCountFrequency (%)
K 167
15.3%
S 165
15.1%
A 115
10.5%
V 97
8.9%
B 94
8.6%
E 76
 
7.0%
T 52
 
4.8%
I 38
 
3.5%
R 37
 
3.4%
L 35
 
3.2%
Other values (14) 216
19.8%
Lowercase Letter
ValueCountFrequency (%)
e 185
32.3%
n 107
18.7%
c 83
14.5%
t 82
14.3%
r 80
14.0%
i 10
 
1.7%
k 6
 
1.0%
v 4
 
0.7%
p 3
 
0.5%
b 3
 
0.5%
Other values (6) 9
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 198
20.7%
2 147
15.4%
3 124
13.0%
4 107
11.2%
0 99
10.3%
5 82
8.6%
6 69
 
7.2%
9 48
 
5.0%
7 44
 
4.6%
8 39
 
4.1%
Other Punctuation
ValueCountFrequency (%)
* 39185
99.7%
, 48
 
0.1%
/ 33
 
0.1%
. 28
 
0.1%
? 8
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
71.4%
Ⅲ 1
 
14.3%
Ⅰ 1
 
14.3%
Math Symbol
ValueCountFrequency (%)
~ 5
83.3%
= 1
 
16.7%
Space Separator
ValueCountFrequency (%)
36290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3508
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144473
63.9%
Common 80118
35.4%
Latin 1671
 
0.7%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 9281
 
6.4%
포 9175
 
6.4%
등 9130
 
6.3%
동 8584
 
5.9%
시 8164
 
5.7%
서 7985
 
5.5%
울 7925
 
5.5%
구 7879
 
5.5%
별 7876
 
5.5%
특 7873
 
5.4%
Other values (405) 60601
41.9%
Latin
ValueCountFrequency (%)
e 185
 
11.1%
K 167
 
10.0%
S 165
 
9.9%
A 115
 
6.9%
n 107
 
6.4%
V 97
 
5.8%
B 94
 
5.6%
c 83
 
5.0%
t 82
 
4.9%
r 80
 
4.8%
Other values (33) 496
29.7%
Common
ValueCountFrequency (%)
* 39185
48.9%
36290
45.3%
- 3508
 
4.4%
1 198
 
0.2%
2 147
 
0.2%
3 124
 
0.2%
4 107
 
0.1%
0 99
 
0.1%
5 82
 
0.1%
6 69
 
0.1%
Other values (12) 309
 
0.4%
Han
ValueCountFrequency (%)
新 5
71.4%
光 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144473
63.9%
ASCII 81782
36.1%
CJK 7
 
< 0.1%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 39185
47.9%
36290
44.4%
- 3508
 
4.3%
1 198
 
0.2%
e 185
 
0.2%
K 167
 
0.2%
S 165
 
0.2%
2 147
 
0.2%
3 124
 
0.2%
A 115
 
0.1%
Other values (52) 1698
 
2.1%
Hangul
ValueCountFrequency (%)
영 9281
 
6.4%
포 9175
 
6.4%
등 9130
 
6.3%
동 8584
 
5.9%
시 8164
 
5.7%
서 7985
 
5.5%
울 7925
 
5.5%
구 7879
 
5.5%
별 7876
 
5.5%
특 7873
 
5.4%
Other values (405) 60601
41.9%
CJK
ValueCountFrequency (%)
新 5
71.4%
光 2
 
28.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
71.4%
Ⅲ 1
 
14.3%
Ⅰ 1
 
14.3%

도로명주소
Text

MISSING 

Distinct5663
Distinct (%)64.0%
Missing1152
Missing (%)11.5%
Memory size156.2 KiB
2024-04-30T04:50:12.011374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length60
Mean length39.747627
Min length23

Characters and Unicode

Total characters351687
Distinct characters521
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4351 ?
Unique (%)49.2%

Sample

1st row서울특별시 영등포구 국회대로 ***, *동 ***호 (당산동*가,삼익아파트)
2nd row서울특별시 영등포구 **로 **, ***호 (여의도동, 콤비빌딩)
3rd row서울특별시 영등포구 은행로 **, ***호 (여의도동, 삼도오피스텔)
4th row서울특별시 영등포구 도신로**길 **-*, *층 *호 (신길동)
5th row서울특별시 영등포구 **로 **, ****호 (여의도동, 라이프오피스텔)
ValueCountFrequency (%)
8874
14.3%
서울특별시 8848
14.2%
영등포구 8843
14.2%
호 5475
 
8.8%
층 2862
 
4.6%
당산동*가 1466
 
2.4%
동 1465
 
2.4%
여의도동 1242
 
2.0%
신길동 1070
 
1.7%
양평동*가 967
 
1.6%
Other values (2878) 21054
33.9%
2024-04-30T04:50:12.366462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 63058
17.9%
53488
 
15.2%
영 12126
 
3.4%
동 11335
 
3.2%
포 11237
 
3.2%
등 11182
 
3.2%
, 11050
 
3.1%
시 9284
 
2.6%
서 9178
 
2.6%
) 8927
 
2.5%
Other values (511) 150822
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200963
57.1%
Other Punctuation 74171
 
21.1%
Space Separator 53488
 
15.2%
Close Punctuation 8927
 
2.5%
Open Punctuation 8926
 
2.5%
Dash Punctuation 1848
 
0.5%
Uppercase Letter 1711
 
0.5%
Decimal Number 846
 
0.2%
Lowercase Letter 766
 
0.2%
Math Symbol 30
 
< 0.1%
Other values (3) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 12126
 
6.0%
동 11335
 
5.6%
포 11237
 
5.6%
등 11182
 
5.6%
시 9284
 
4.6%
서 9178
 
4.6%
로 8926
 
4.4%
울 8912
 
4.4%
구 8857
 
4.4%
별 8854
 
4.4%
Other values (438) 101072
50.3%
Uppercase Letter
ValueCountFrequency (%)
B 315
18.4%
A 213
12.4%
K 210
12.3%
S 210
12.3%
V 132
7.7%
E 121
 
7.1%
T 61
 
3.6%
I 57
 
3.3%
R 51
 
3.0%
W 34
 
2.0%
Other values (15) 307
17.9%
Lowercase Letter
ValueCountFrequency (%)
e 235
30.7%
n 130
17.0%
c 108
14.1%
r 105
13.7%
t 101
13.2%
b 22
 
2.9%
a 11
 
1.4%
i 10
 
1.3%
k 7
 
0.9%
l 6
 
0.8%
Other values (11) 31
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 190
22.5%
2 120
14.2%
0 110
13.0%
3 96
11.3%
4 82
9.7%
7 61
 
7.2%
6 58
 
6.9%
5 49
 
5.8%
8 43
 
5.1%
9 37
 
4.4%
Other Punctuation
ValueCountFrequency (%)
* 63058
85.0%
, 11050
 
14.9%
/ 28
 
< 0.1%
. 27
 
< 0.1%
? 6
 
< 0.1%
& 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
71.4%
Ⅲ 1
 
14.3%
Ⅰ 1
 
14.3%
Math Symbol
ValueCountFrequency (%)
~ 29
96.7%
= 1
 
3.3%
Space Separator
ValueCountFrequency (%)
53488
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8927
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8926
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1848
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 200956
57.1%
Common 148240
42.2%
Latin 2484
 
0.7%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 12126
 
6.0%
동 11335
 
5.6%
포 11237
 
5.6%
등 11182
 
5.6%
시 9284
 
4.6%
서 9178
 
4.6%
로 8926
 
4.4%
울 8912
 
4.4%
구 8857
 
4.4%
별 8854
 
4.4%
Other values (436) 101065
50.3%
Latin
ValueCountFrequency (%)
B 315
12.7%
e 235
 
9.5%
A 213
 
8.6%
K 210
 
8.5%
S 210
 
8.5%
V 132
 
5.3%
n 130
 
5.2%
E 121
 
4.9%
c 108
 
4.3%
r 105
 
4.2%
Other values (39) 705
28.4%
Common
ValueCountFrequency (%)
* 63058
42.5%
53488
36.1%
, 11050
 
7.5%
) 8927
 
6.0%
( 8926
 
6.0%
- 1848
 
1.2%
1 190
 
0.1%
2 120
 
0.1%
0 110
 
0.1%
3 96
 
0.1%
Other values (14) 427
 
0.3%
Han
ValueCountFrequency (%)
新 5
71.4%
光 2
 
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200956
57.1%
ASCII 150717
42.9%
Number Forms 7
 
< 0.1%
CJK 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 63058
41.8%
53488
35.5%
, 11050
 
7.3%
) 8927
 
5.9%
( 8926
 
5.9%
- 1848
 
1.2%
B 315
 
0.2%
e 235
 
0.2%
A 213
 
0.1%
K 210
 
0.1%
Other values (60) 2447
 
1.6%
Hangul
ValueCountFrequency (%)
영 12126
 
6.0%
동 11335
 
5.6%
포 11237
 
5.6%
등 11182
 
5.6%
시 9284
 
4.6%
서 9178
 
4.6%
로 8926
 
4.4%
울 8912
 
4.4%
구 8857
 
4.4%
별 8854
 
4.4%
Other values (436) 101065
50.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
71.4%
Ⅲ 1
 
14.3%
Ⅰ 1
 
14.3%
CJK
ValueCountFrequency (%)
新 5
71.4%
光 2
 
28.6%

도로명우편번호
Text

MISSING 

Distinct467
Distinct (%)6.4%
Missing2714
Missing (%)27.1%
Memory size156.2 KiB
2024-04-30T04:50:12.659858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1966786
Min length5

Characters and Unicode

Total characters37863
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

Unique69 ?
Unique (%)0.9%

Sample

1st row07345
2nd row150869
3rd row150840
4th row150731
5th row07281
ValueCountFrequency (%)
07256 250
 
3.4%
07264 204
 
2.8%
07331 150
 
2.1%
07333 146
 
2.0%
07299 133
 
1.8%
07238 101
 
1.4%
07287 101
 
1.4%
07217 97
 
1.3%
07207 84
 
1.2%
07327 84
 
1.2%
Other values (457) 5936
81.5%
2024-04-30T04:50:13.061276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9074
24.0%
7 7586
20.0%
2 4858
12.8%
3 3672
9.7%
1 3061
 
8.1%
5 2996
 
7.9%
4 1841
 
4.9%
8 1793
 
4.7%
6 1584
 
4.2%
9 1360
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37825
99.9%
Dash Punctuation 38
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9074
24.0%
7 7586
20.1%
2 4858
12.8%
3 3672
9.7%
1 3061
 
8.1%
5 2996
 
7.9%
4 1841
 
4.9%
8 1793
 
4.7%
6 1584
 
4.2%
9 1360
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37863
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9074
24.0%
7 7586
20.0%
2 4858
12.8%
3 3672
9.7%
1 3061
 
8.1%
5 2996
 
7.9%
4 1841
 
4.9%
8 1793
 
4.7%
6 1584
 
4.2%
9 1360
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37863
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9074
24.0%
7 7586
20.0%
2 4858
12.8%
3 3672
9.7%
1 3061
 
8.1%
5 2996
 
7.9%
4 1841
 
4.9%
8 1793
 
4.7%
6 1584
 
4.2%
9 1360
 
3.6%

사업장명
Text

Distinct9893
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T04:50:13.339975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length7.6916
Min length1

Characters and Unicode

Total characters76916
Distinct characters1054
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9795 ?
Unique (%)98.0%

Sample

1st row더듀?
2nd row(주) 글로벌케이티티
3rd row(주)한국금융테크
4th row옹골찬 마켓
5th row(주)유목
ValueCountFrequency (%)
주식회사 1302
 
9.6%
주 231
 
1.7%
유한회사 38
 
0.3%
co 34
 
0.2%
ltd 32
 
0.2%
company 32
 
0.2%
컴퍼니 28
 
0.2%
korea 27
 
0.2%
스튜디오 26
 
0.2%
25
 
0.2%
Other values (10964) 11836
87.0%
2024-04-30T04:50:13.772209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3614
 
4.7%
주 2834
 
3.7%
이 2740
 
3.6%
) 2675
 
3.5%
( 2670
 
3.5%
스 2346
 
3.1%
사 1808
 
2.4%
회 1488
 
1.9%
식 1396
 
1.8%
리 1142
 
1.5%
Other values (1044) 54203
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55568
72.2%
Lowercase Letter 6052
 
7.9%
Uppercase Letter 5411
 
7.0%
Space Separator 3614
 
4.7%
Close Punctuation 2675
 
3.5%
Open Punctuation 2670
 
3.5%
Other Punctuation 460
 
0.6%
Decimal Number 406
 
0.5%
Dash Punctuation 41
 
0.1%
Other Symbol 10
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2834
 
5.1%
이 2740
 
4.9%
스 2346
 
4.2%
사 1808
 
3.3%
회 1488
 
2.7%
식 1396
 
2.5%
리 1142
 
2.1%
아 1009
 
1.8%
에 906
 
1.6%
트 775
 
1.4%
Other values (959) 39124
70.4%
Lowercase Letter
ValueCountFrequency (%)
e 712
11.8%
o 690
11.4%
a 534
 
8.8%
n 472
 
7.8%
i 418
 
6.9%
r 388
 
6.4%
t 381
 
6.3%
l 339
 
5.6%
s 279
 
4.6%
u 217
 
3.6%
Other values (22) 1622
26.8%
Uppercase Letter
ValueCountFrequency (%)
A 410
 
7.6%
O 394
 
7.3%
E 368
 
6.8%
L 355
 
6.6%
S 355
 
6.6%
C 341
 
6.3%
I 310
 
5.7%
N 303
 
5.6%
M 291
 
5.4%
T 289
 
5.3%
Other values (16) 1995
36.9%
Decimal Number
ValueCountFrequency (%)
1 79
19.5%
2 58
14.3%
4 54
13.3%
0 42
10.3%
3 42
10.3%
6 34
8.4%
9 32
7.9%
5 32
7.9%
7 22
 
5.4%
8 11
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 229
49.8%
& 106
23.0%
, 76
 
16.5%
' 15
 
3.3%
? 14
 
3.0%
: 7
 
1.5%
/ 6
 
1.3%
# 4
 
0.9%
! 3
 
0.7%
Other Symbol
ValueCountFrequency (%)
㈜ 9
90.0%
♡ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
3614
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2675
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2670
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55568
72.2%
Latin 11455
 
14.9%
Common 9876
 
12.8%
Han 9
 
< 0.1%
Greek 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2834
 
5.1%
이 2740
 
4.9%
스 2346
 
4.2%
사 1808
 
3.3%
회 1488
 
2.7%
식 1396
 
2.5%
리 1142
 
2.1%
아 1009
 
1.8%
에 906
 
1.6%
트 775
 
1.4%
Other values (951) 39124
70.4%
Latin
ValueCountFrequency (%)
e 712
 
6.2%
o 690
 
6.0%
a 534
 
4.7%
n 472
 
4.1%
i 418
 
3.6%
A 410
 
3.6%
O 394
 
3.4%
r 388
 
3.4%
t 381
 
3.3%
E 368
 
3.2%
Other values (42) 6688
58.4%
Common
ValueCountFrequency (%)
3614
36.6%
) 2675
27.1%
( 2670
27.0%
. 229
 
2.3%
& 106
 
1.1%
1 79
 
0.8%
, 76
 
0.8%
2 58
 
0.6%
4 54
 
0.5%
0 42
 
0.4%
Other values (16) 273
 
2.8%
Han
ValueCountFrequency (%)
垠 1
11.1%
妃 1
11.1%
孝 1
11.1%
禮 1
11.1%
至 1
11.1%
愛 1
11.1%
多 1
11.1%
甫 1
11.1%
宮 1
11.1%
Greek
ValueCountFrequency (%)
λ 3
37.5%
ω 1
 
12.5%
ε 1
 
12.5%
σ 1
 
12.5%
υ 1
 
12.5%
α 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55559
72.2%
ASCII 21330
 
27.7%
None 17
 
< 0.1%
CJK 8
 
< 0.1%
Misc Symbols 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3614
16.9%
) 2675
 
12.5%
( 2670
 
12.5%
e 712
 
3.3%
o 690
 
3.2%
a 534
 
2.5%
n 472
 
2.2%
i 418
 
2.0%
A 410
 
1.9%
O 394
 
1.8%
Other values (67) 8741
41.0%
Hangul
ValueCountFrequency (%)
주 2834
 
5.1%
이 2740
 
4.9%
스 2346
 
4.2%
사 1808
 
3.3%
회 1488
 
2.7%
식 1396
 
2.5%
리 1142
 
2.1%
아 1009
 
1.8%
에 906
 
1.6%
트 775
 
1.4%
Other values (950) 39115
70.4%
None
ValueCountFrequency (%)
㈜ 9
52.9%
λ 3
 
17.6%
ω 1
 
5.9%
ε 1
 
5.9%
σ 1
 
5.9%
υ 1
 
5.9%
α 1
 
5.9%
CJK
ValueCountFrequency (%)
垠 1
12.5%
妃 1
12.5%
孝 1
12.5%
至 1
12.5%
愛 1
12.5%
多 1
12.5%
甫 1
12.5%
宮 1
12.5%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
禮 1
100.0%

최종수정일자
Date

Distinct9680
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-07-10 10:51:43
Maximum2024-04-25 15:54:13
2024-04-30T04:50:13.893264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:14.012858image/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 size156.2 KiB
I
6834 
U
3166 

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 6834
68.3%
U 3166
31.7%

Length

2024-04-30T04:50:14.121865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:14.195610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6834
68.3%
u 3166
31.7%

데이터갱신일자
Date

Distinct1587
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T04:50:14.481010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:50:14.595850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

Distinct544
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T04:50:14.754483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length83
Mean length8.1807
Min length1

Characters and Unicode

Total characters81807
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique361 ?
Unique (%)3.6%

Sample

1st row-
2nd row의류/패션/잡화/뷰티 건강/식품
3rd row기타
4th row의류/패션/잡화/뷰티
5th row기타
ValueCountFrequency (%)
의류/패션/잡화/뷰티 2837
20.3%
종합몰 2676
19.1%
기타 2642
18.9%
1155
8.3%
건강/식품 1115
 
8.0%
교육/도서/완구/오락 826
 
5.9%
컴퓨터/사무용품 734
 
5.2%
가전 584
 
4.2%
가구/수납용품 475
 
3.4%
레져/여행/공연 395
 
2.8%
Other values (3) 547
 
3.9%
2024-04-30T04:50:15.025778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 14517
 
17.7%
3986
 
4.9%
품 2871
 
3.5%
의 2837
 
3.5%
류 2837
 
3.5%
패 2837
 
3.5%
션 2837
 
3.5%
잡 2837
 
3.5%
화 2837
 
3.5%
뷰 2837
 
3.5%
Other values (41) 40574
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62149
76.0%
Other Punctuation 14517
 
17.7%
Space Separator 3986
 
4.9%
Dash Punctuation 1155
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 2871
 
4.6%
의 2837
 
4.6%
류 2837
 
4.6%
패 2837
 
4.6%
션 2837
 
4.6%
잡 2837
 
4.6%
화 2837
 
4.6%
뷰 2837
 
4.6%
티 2837
 
4.6%
합 2676
 
4.3%
Other values (38) 33906
54.6%
Other Punctuation
ValueCountFrequency (%)
/ 14517
100.0%
Space Separator
ValueCountFrequency (%)
3986
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62149
76.0%
Common 19658
 
24.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 2871
 
4.6%
의 2837
 
4.6%
류 2837
 
4.6%
패 2837
 
4.6%
션 2837
 
4.6%
잡 2837
 
4.6%
화 2837
 
4.6%
뷰 2837
 
4.6%
티 2837
 
4.6%
합 2676
 
4.3%
Other values (38) 33906
54.6%
Common
ValueCountFrequency (%)
/ 14517
73.8%
3986
 
20.3%
- 1155
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62149
76.0%
ASCII 19658
 
24.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 14517
73.8%
3986
 
20.3%
- 1155
 
5.9%
Hangul
ValueCountFrequency (%)
품 2871
 
4.6%
의 2837
 
4.6%
류 2837
 
4.6%
패 2837
 
4.6%
션 2837
 
4.6%
잡 2837
 
4.6%
화 2837
 
4.6%
뷰 2837
 
4.6%
티 2837
 
4.6%
합 2676
 
4.3%
Other values (38) 33906
54.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3321
Distinct (%)37.2%
Missing1070
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean191499.86
Minimum183697.84
Maximum204415.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:15.147475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183697.84
5-th percentile189959.04
Q1190590.28
median191158.74
Q3192226.24
95-th percentile193730.45
Maximum204415.94
Range20718.104
Interquartile range (IQR)1635.9642

Descriptive statistics

Standard deviation1197.536
Coefficient of variation (CV)0.0062534561
Kurtosis1.9284849
Mean191499.86
Median Absolute Deviation (MAD)610.53221
Skewness0.84111028
Sum1.7100938 × 109
Variance1434092.4
MonotonicityNot monotonic
2024-04-30T04:50:15.280453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190555.768991595 332
 
3.3%
190586.062540107 224
 
2.2%
193469.554731741 159
 
1.6%
190996.357288859 118
 
1.2%
190079.219797466 90
 
0.9%
190941.054351896 84
 
0.8%
194561.746032498 65
 
0.7%
193282.654266684 59
 
0.6%
194530.535390096 49
 
0.5%
189959.044020878 45
 
0.4%
Other values (3311) 7705
77.0%
(Missing) 1070
 
10.7%
ValueCountFrequency (%)
183697.83985801 1
 
< 0.1%
185569.653333233 1
 
< 0.1%
185852.717246438 1
 
< 0.1%
187520.79689142 1
 
< 0.1%
187901.106351264 1
 
< 0.1%
188953.066831076 1
 
< 0.1%
189514.301323638 1
 
< 0.1%
189530.797549177 1
 
< 0.1%
189549.847307536 12
0.1%
189554.182520551 2
 
< 0.1%
ValueCountFrequency (%)
204415.943976695 1
 
< 0.1%
201356.035379848 1
 
< 0.1%
197167.128013565 1
 
< 0.1%
196873.001604976 1
 
< 0.1%
195083.648384079 1
 
< 0.1%
194632.526367463 2
 
< 0.1%
194592.276750438 15
 
0.1%
194561.746032498 65
0.7%
194530.535390096 49
0.5%
194522.497734512 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3319
Distinct (%)37.2%
Missing1070
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean446253.01
Minimum439286.68
Maximum465201.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:50:15.413259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439286.68
5-th percentile443645.76
Q1445548.8
median446508.07
Q3447144.28
95-th percentile448224.11
Maximum465201.67
Range25914.99
Interquartile range (IQR)1595.4782

Descriptive statistics

Standard deviation1340.562
Coefficient of variation (CV)0.0030040401
Kurtosis4.7367057
Mean446253.01
Median Absolute Deviation (MAD)708.85683
Skewness-0.23610831
Sum3.9850394 × 109
Variance1797106.4
MonotonicityNot monotonic
2024-04-30T04:50:15.552956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446698.814322782 332
 
3.3%
447216.925498911 224
 
2.2%
446508.068667777 159
 
1.6%
445841.377603245 118
 
1.2%
445778.895201988 90
 
0.9%
446364.318286465 65
 
0.7%
447611.552045596 59
 
0.6%
447628.862085473 58
 
0.6%
446306.787198089 49
 
0.5%
446192.884313355 45
 
0.4%
Other values (3309) 7731
77.3%
(Missing) 1070
 
10.7%
ValueCountFrequency (%)
439286.683964537 1
 
< 0.1%
442621.787911877 1
 
< 0.1%
442649.873938101 13
0.1%
442663.748373343 4
 
< 0.1%
442697.970107753 1
 
< 0.1%
442710.662421803 10
0.1%
442715.677609564 8
0.1%
442732.843958413 1
 
< 0.1%
442744.165176674 1
 
< 0.1%
442751.471769958 7
0.1%
ValueCountFrequency (%)
465201.674235863 1
 
< 0.1%
456606.133621913 1
 
< 0.1%
450124.593452761 1
 
< 0.1%
450011.542359184 1
 
< 0.1%
449107.834531278 1
 
< 0.1%
449039.941340036 1
 
< 0.1%
449025.246614702 1
 
< 0.1%
449024.656041802 2
< 0.1%
449021.440559054 1
 
< 0.1%
449020.276288934 3
< 0.1%

자산규모
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8216 
<NA>
1784 

Length

Max length4
Median length1
Mean length1.5352
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8216
82.2%
<NA> 1784
 
17.8%

Length

2024-04-30T04:50:15.676616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:15.763936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8216
82.2%
na 1784
 
17.8%

부채총액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8216 
<NA>
1784 

Length

Max length4
Median length1
Mean length1.5352
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8216
82.2%
<NA> 1784
 
17.8%

Length

2024-04-30T04:50:15.858999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:15.949974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8216
82.2%
na 1784
 
17.8%

자본금
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8216 
<NA>
1784 

Length

Max length4
Median length1
Mean length1.5352
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8216
82.2%
<NA> 1784
 
17.8%

Length

2024-04-30T04:50:16.045214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:50:16.127942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8216
82.2%
na 1784
 
17.8%

판매방식명
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인터넷
6028 
<NA>
2800 
기타
 
293
인터넷, 기타
 
259
TV홈쇼핑, 인터넷
 
131
Other values (23)
 
489

Length

Max length26
Median length3
Mean length4.0878
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row인터넷
2nd row인터넷
3rd row인터넷
4th row인터넷
5th rowTV홈쇼핑, 인터넷, 신문잡지

Common Values

ValueCountFrequency (%)
인터넷 6028
60.3%
<NA> 2800
28.0%
기타 293
 
2.9%
인터넷, 기타 259
 
2.6%
TV홈쇼핑, 인터넷 131
 
1.3%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지, 기타 103
 
1.0%
인터넷, 카다로그 61
 
0.6%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지 55
 
0.5%
인터넷, 카다로그, 신문잡지, 기타 34
 
0.3%
TV홈쇼핑 33
 
0.3%
Other values (18) 203
 
2.0%

Length

2024-04-30T04:50:16.220730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인터넷 6840
59.6%
na 2800
24.4%
기타 792
 
6.9%
tv홈쇼핑 410
 
3.6%
카다로그 361
 
3.1%
신문잡지 279
 
2.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
29893180000200731801173020543520070816<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-2633-5569<NA>150043서울특별시 영등포구 당산동*가 ***번지 삼익아파트 *동 ***호서울특별시 영등포구 국회대로 ***, *동 ***호 (당산동*가,삼익아파트)<NA>더듀?2013-03-27 20:56:38I2021-12-03 00:22:43.0-190679.328893447306.386643000인터넷
119733180000201531801633020112520150907<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-761-9888<NA><NA><NA>서울특별시 영등포구 **로 **, ***호 (여의도동, 콤비빌딩)07345(주) 글로벌케이티티2015-09-07 16:55:56I2021-12-03 00:22:43.0의류/패션/잡화/뷰티 건강/식품194530.53539446306.787198000인터넷
79633180000201231801633020002220120103<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-782-8369<NA><NA><NA>서울특별시 영등포구 은행로 **, ***호 (여의도동, 삼도오피스텔)150869(주)한국금융테크2014-12-22 15:04:36I2018-08-31 23:59:59.0기타193289.310384447527.152621000인터넷
115783180000201531801633020059220150513<NA>3폐업3폐업처리20160408<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 도신로**길 **-*, *층 *호 (신길동)150840옹골찬 마켓2016-04-08 15:09:59I2018-08-31 23:59:59.0의류/패션/잡화/뷰티192369.708958445341.153199000인터넷
79933180000201231801633020006120120109<NA>3폐업3폐업처리20170818<NA><NA><NA>02-761-2464<NA><NA><NA>서울특별시 영등포구 **로 **, ****호 (여의도동, 라이프오피스텔)150731(주)유목2017-08-18 15:26:48I2018-08-31 23:59:59.0기타194561.746032446364.318286000TV홈쇼핑, 인터넷, 신문잡지
54193180000200931801173020114120091117<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>2672-2889<NA><NA>서울특별시 영등포구 영등포동4가 135번지 2호 401호서울특별시 영등포구 영등포로36길 10-1 (영등포동4가,401호)<NA>앤앤몰2022-12-08 14:20:48U2021-11-01 23:00:00.0종합몰191391.977053446357.522388<NA><NA><NA><NA>
221073180000202131802473020043920210128<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동*가 ** 문래 SK V* center서울특별시 영등포구 선유로*길 **, 문래 SK V* center ***호 (문래동*가)07281주식회사 와이케이비파트너스2021-01-28 13:27:26I2021-01-30 00:23:03.0교육/도서/완구/오락189959.044021446192.884313000인터넷
204003180000202031802473020043020200811<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 ***-**서울특별시 영등포구 대림로**마길 **-*, ***호 (대림동)07401베코 컴퍼니(Beco Company)2020-08-11 12:53:26I2020-08-13 00:23:14.0종합몰191058.137884444249.944137000인터넷
78543180000201131801633020144620111122<NA>4취소/말소/만료/정지/중지7직권말소<NA>2013062420140624<NA><NA><NA>150037서울특별시 영등포구 영등포동*가 **번지 **호서울특별시 영등포구 양산로 ***, ***호 (영등포동*가)150037다원인터네셔널2014-12-19 15:26:52I2018-08-31 23:59:59.0의류/패션/잡화/뷰티191500.605636446752.019893000인터넷
153993180000201831801633020052120180405<NA>3폐업3폐업처리20200130<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동*가 **번지 문래힐스테이트서울특별시 영등포구 문래로 **, ***동 *층 *호 (문래동*가, 문래힐스테이트)07295에어오더2020-01-30 09:11:21U2020-02-01 02:40:00.0건강/식품190282.160798446242.316747000인터넷
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
847318000020043180117302021342004-07-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-781-9114<NA><NA>서울특별시 영등포구 여의도동**-* CCMM빌딩*층서울특별시 영등포구 여의공원로 ***, *층 (여의도동, CCMM빌딩)150-869국민일보 주식회사2024-04-03 11:24:31U2023-12-04 00:05:00.0기타193293.251953447448.342915<NA><NA><NA><NA>
188793180000202031802393020054420200227<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 **번지 여의도자이서울특별시 영등포구 여의동로*길 **, ***동 *층 ***호 (여의도동, 여의도자이)07324리오하2020-02-27 11:12:39I2020-02-29 00:23:35.0종합몰193393.096554446218.443828000인터넷, 기타
152933180000201831801633020037720161108<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-4408-1990<NA><NA>서울특별시 영등포구 문래동*가 ** 리버뷰 신안인스빌서울특별시 영등포구 경인로**길 **, ***동 *층 ***-***호 (문래동*가, 리버뷰 신안인스빌)07287㈜마노커머스2020-09-16 13:21:04I2021-12-03 00:22:43.0종합몰 의류/패션/잡화/뷰티190079.219797445778.895202000인터넷
177943180000201931802263020152920190910<NA>3폐업3폐업처리20200414<NA><NA><NA>02-2014-1111<NA><NA>서울특별시 영등포구 양평동*가 *번지 Citadines Han River서울특별시 영등포구 양평로**길 **, Citadines Han River (양평동*가)07202토브 호텔 앤 레지던스지점2020-04-14 15:57:41U2020-04-16 02:40:00.0기타190256.765819448739.129269000인터넷
90403180000201331801633020006420130114<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-8274-9543<NA><NA><NA>서울특별시 영등포구 경인로**길 *-*, 비동 ***호 (문래동*가, 유성연립)150091J몰2013-01-14 17:58:20I2021-12-03 00:22:43.0-190768.674959445507.634043000인터넷
7733180000200431801173020195420040507<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-835-2808<NA><NA><NA>서울특별시 영등포구 당산로**길 **, 더블유동 ****호 (당산동*가, 당산에스케이브이*센터)150806(주)다솜인터내셔널2015-04-15 09:48:01I2018-08-31 23:59:59.0가전190941.054352447684.468178000TV홈쇼핑, 인터넷
103033180000201431801633020039020060123<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02)727-8205<NA><NA><NA>서울특별시 영등포구 선유로 *** (양평동*가)150867주식회사 레임2022-01-27 16:15:16U2022-01-29 02:40:00.0종합몰 레져/여행/공연 기타190992.04317448226.05169000인터넷
225423180000202131802473020090320210312<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동*가 **-** 에이스하이테크시티서울특별시 영등포구 경인로 ***, 에이스하이테크시티 *동 **층 *호 (문래동*가)07299비엘텍코리아 주식회사2021-03-12 08:22:40I2021-03-14 00:23:00.0기타190996.357289445841.377603000인터넷, 기타
121203180000201531801633020130820151021<NA>3폐업3폐업처리20200604<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동*가 **번지 *호 영등포유통상가서울특별시 영등포구 영등포로 ***, 영등포유통상가 *층 마열**호 (당산동*가)07264제이투(J2)컴퍼니2020-06-04 09:18:12U2020-06-06 02:40:00.0기타190555.768992446698.814323000기타
79033180000201131801633020150620111207<NA>3폐업3폐업처리20141230<NA><NA><NA><NA><NA>150010서울특별시 영등포구 여의도동 **번지 **호 엘지여의도에클라트 ***호서울특별시 영등포구 국회대로 ***, ***호 (여의도동,엘지여의도에클라트)<NA>주식회사 한강엠엔씨2014-12-31 13:19:31I2018-08-31 23:59:59.0가구/수납용품192785.997964447523.116512000인터넷