Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells82271
Missing cells (%)28.4%
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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18804/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
자산규모 is highly imbalanced (76.4%)Imbalance
부채총액 is highly imbalanced (76.4%)Imbalance
자본금 is highly imbalanced (76.4%)Imbalance
판매방식명 is highly imbalanced (74.1%)Imbalance
인허가취소일자 has 9766 (97.7%) missing valuesMissing
폐업일자 has 6336 (63.4%) missing valuesMissing
휴업시작일자 has 9959 (99.6%) missing valuesMissing
휴업종료일자 has 9959 (99.6%) missing valuesMissing
재개업일자 has 9948 (99.5%) missing valuesMissing
전화번호 has 3762 (37.6%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 8343 (83.4%) missing valuesMissing
지번주소 has 1776 (17.8%) missing valuesMissing
도로명주소 has 2971 (29.7%) missing valuesMissing
도로명우편번호 has 3824 (38.2%) missing valuesMissing
좌표정보(X) has 2813 (28.1%) missing valuesMissing
좌표정보(Y) has 2813 (28.1%) missing valuesMissing
좌표정보(Y) is highly skewed (γ1 = -35.22898781)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 11:06:04.023034
Analysis finished2024-04-06 11:06:07.151399
Duration3.13 seconds
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
3020000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 10000
100.0%

Length

2024-04-06T20:06:07.295528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:07.455284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 10000
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0134525 × 1018
Minimum1.996302 × 1018
Maximum2.023302 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:07.632029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996302 × 1018
5-th percentile2.003302 × 1018
Q12.007302 × 1018
median2.013302 × 1018
Q32.019552 × 1018
95-th percentile2.022302 × 1018
Maximum2.023302 × 1018
Range2.7000011 × 1016
Interquartile range (IQR)1.2250005 × 1016

Descriptive statistics

Standard deviation6.5585813 × 1015
Coefficient of variation (CV)0.0032573807
Kurtosis-1.3337272
Mean2.0134525 × 1018
Median Absolute Deviation (MAD)6.0000055 × 1015
Skewness-0.076751219
Sum9.1273386 × 1018
Variance4.3014988 × 1031
MonotonicityNot monotonic
2024-04-06T20:06:07.894152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2010302009530200887 1
 
< 0.1%
2011302009530200132 1
 
< 0.1%
2006302009530205872 1
 
< 0.1%
2017302015030201099 1
 
< 0.1%
2005302009530204127 1
 
< 0.1%
2005302009530200526 1
 
< 0.1%
2006302009530201115 1
 
< 0.1%
2018302015030200160 1
 
< 0.1%
2016302015030200696 1
 
< 0.1%
2008302009530200576 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1996302009530200168 1
< 0.1%
1996302009530200173 1
< 0.1%
1996302009530200437 1
< 0.1%
1997302009530200570 1
< 0.1%
1997302009530200596 1
< 0.1%
1997302009530200627 1
< 0.1%
1997302009530200647 1
< 0.1%
1997302009530200830 1
< 0.1%
1997302009530200928 1
< 0.1%
1997302009530200948 1
< 0.1%
ValueCountFrequency (%)
2023302020330201595 1
< 0.1%
2023302020330201594 1
< 0.1%
2023302020330201593 1
< 0.1%
2023302020330201592 1
< 0.1%
2023302020330201589 1
< 0.1%
2023302020330201587 1
< 0.1%
2023302020330201585 1
< 0.1%
2023302020330201584 1
< 0.1%
2023302020330201581 1
< 0.1%
2023302020330201576 1
< 0.1%

인허가일자
Date

Distinct4323
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1996-09-05 00:00:00
Maximum2024-03-21 00:00:00
2024-04-06T20:06:08.163072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:08.406343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)4.7%
Missing9766
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean20075770
Minimum20071224
Maximum20180419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:08.630826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071224
5-th percentile20071224
Q120071224
median20071231
Q320081218
95-th percentile20081218
Maximum20180419
Range109195
Interquartile range (IQR)9994

Descriptive statistics

Standard deviation12659.181
Coefficient of variation (CV)0.00063057012
Kurtosis43.229569
Mean20075770
Median Absolute Deviation (MAD)7
Skewness6.0203453
Sum4.6977302 × 109
Variance1.6025486 × 108
MonotonicityNot monotonic
2024-04-06T20:06:08.836026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20071231 93
 
0.9%
20071224 73
 
0.7%
20081218 60
 
0.6%
20130131 1
 
< 0.1%
20110422 1
 
< 0.1%
20100429 1
 
< 0.1%
20180419 1
 
< 0.1%
20180320 1
 
< 0.1%
20141205 1
 
< 0.1%
20080121 1
 
< 0.1%
(Missing) 9766
97.7%
ValueCountFrequency (%)
20071224 73
0.7%
20071231 93
0.9%
20080121 1
 
< 0.1%
20081218 60
0.6%
20100429 1
 
< 0.1%
20110225 1
 
< 0.1%
20110422 1
 
< 0.1%
20130131 1
 
< 0.1%
20141205 1
 
< 0.1%
20180320 1
 
< 0.1%
ValueCountFrequency (%)
20180419 1
 
< 0.1%
20180320 1
 
< 0.1%
20141205 1
 
< 0.1%
20130131 1
 
< 0.1%
20110422 1
 
< 0.1%
20110225 1
 
< 0.1%
20100429 1
 
< 0.1%
20081218 60
0.6%
20080121 1
 
< 0.1%
20071231 93
0.9%

영업상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
3156 
1
3142 
3
3089 
5
593 
2
 
20

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row1
4th row4
5th row5

Common Values

ValueCountFrequency (%)
4 3156
31.6%
1 3142
31.4%
3 3089
30.9%
5 593
 
5.9%
2 20
 
0.2%

Length

2024-04-06T20:06:09.059725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:09.217097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 3156
31.6%
1 3142
31.4%
3 3089
30.9%
5 593
 
5.9%
2 20
 
0.2%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
취소/말소/만료/정지/중지
3156 
영업/정상
3142 
폐업
3089 
제외/삭제/전출
593 
휴업
 
20

Length

Max length14
Median length8
Mean length7.0856
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취소/말소/만료/정지/중지 3156
31.6%
영업/정상 3142
31.4%
폐업 3089
30.9%
제외/삭제/전출 593
 
5.9%
휴업 20
 
0.2%

Length

2024-04-06T20:06:09.495849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:09.694357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취소/말소/만료/정지/중지 3156
31.6%
영업/정상 3142
31.4%
폐업 3089
30.9%
제외/삭제/전출 593
 
5.9%
휴업 20
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6789
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:09.866768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.3930665
Coefficient of variation (CV)0.65048426
Kurtosis-1.41633
Mean3.6789
Median Absolute Deviation (MAD)2
Skewness0.34130698
Sum36789
Variance5.7267675
MonotonicityNot monotonic
2024-04-06T20:06:10.038328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 3142
31.4%
3 3089
30.9%
7 2917
29.2%
5 593
 
5.9%
4 239
 
2.4%
2 20
 
0.2%
ValueCountFrequency (%)
1 3142
31.4%
2 20
 
0.2%
3 3089
30.9%
4 239
 
2.4%
5 593
 
5.9%
7 2917
29.2%
ValueCountFrequency (%)
7 2917
29.2%
5 593
 
5.9%
4 239
 
2.4%
3 3089
30.9%
2 20
 
0.2%
1 3142
31.4%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상영업
3142 
폐업처리
3089 
직권말소
2917 
타시군구이관
593 
직권취소
 
239

Length

Max length6
Median length4
Mean length4.1186
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 3142
31.4%
폐업처리 3089
30.9%
직권말소 2917
29.2%
타시군구이관 593
 
5.9%
직권취소 239
 
2.4%
휴업처리 20
 
0.2%

Length

2024-04-06T20:06:10.269515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:10.451921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 3142
31.4%
폐업처리 3089
30.9%
직권말소 2917
29.2%
타시군구이관 593
 
5.9%
직권취소 239
 
2.4%
휴업처리 20
 
0.2%

폐업일자
Date

MISSING 

Distinct2382
Distinct (%)65.0%
Missing6336
Missing (%)63.4%
Memory size156.2 KiB
Minimum1998-06-03 00:00:00
Maximum2024-04-02 00:00:00
2024-04-06T20:06:10.661891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:10.947534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct40
Distinct (%)97.6%
Missing9959
Missing (%)99.6%
Memory size156.2 KiB
Minimum2010-09-15 00:00:00
Maximum2024-01-12 00:00:00
2024-04-06T20:06:11.218897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:11.424541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

휴업종료일자
Date

MISSING 

Distinct38
Distinct (%)92.7%
Missing9959
Missing (%)99.6%
Memory size156.2 KiB
Minimum2011-09-15 00:00:00
Maximum2030-12-31 00:00:00
2024-04-06T20:06:11.625354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:11.862656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

재개업일자
Date

MISSING 

Distinct29
Distinct (%)55.8%
Missing9948
Missing (%)99.5%
Memory size156.2 KiB
Minimum2007-06-11 00:00:00
Maximum2022-07-01 00:00:00
2024-04-06T20:06:12.108236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:12.327923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

전화번호
Text

MISSING 

Distinct5939
Distinct (%)95.2%
Missing3762
Missing (%)37.6%
Memory size156.2 KiB
2024-04-06T20:06:13.040094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length11.360853
Min length1

Characters and Unicode

Total characters70869
Distinct characters16
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5764 ?
Unique (%)92.4%

Sample

1st row793-9728
2nd row02-1644-1828
3rd row070 7732 7919
4th row02-704-4586
5th row02 794 9132
ValueCountFrequency (%)
02 2454
 
22.3%
701 120
 
1.1%
711 116
 
1.1%
706 99
 
0.9%
703 96
 
0.9%
702 93
 
0.8%
704 85
 
0.8%
717 83
 
0.8%
719 82
 
0.7%
2120 77
 
0.7%
Other values (5825) 7685
69.9%
2024-04-06T20:06:13.741726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11940
16.8%
2 9787
13.8%
7 8409
11.9%
- 7019
9.9%
6543
9.2%
1 5553
7.8%
3 4299
 
6.1%
4 3582
 
5.1%
5 3489
 
4.9%
8 3445
 
4.9%
Other values (6) 6803
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57272
80.8%
Dash Punctuation 7019
 
9.9%
Space Separator 6543
 
9.2%
Other Punctuation 23
 
< 0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11940
20.8%
2 9787
17.1%
7 8409
14.7%
1 5553
9.7%
3 4299
 
7.5%
4 3582
 
6.3%
5 3489
 
6.1%
8 3445
 
6.0%
9 3435
 
6.0%
6 3333
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 21
91.3%
/ 1
 
4.3%
, 1
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 7019
100.0%
Space Separator
ValueCountFrequency (%)
6543
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70869
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11940
16.8%
2 9787
13.8%
7 8409
11.9%
- 7019
9.9%
6543
9.2%
1 5553
7.8%
3 4299
 
6.1%
4 3582
 
5.1%
5 3489
 
4.9%
8 3445
 
4.9%
Other values (6) 6803
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11940
16.8%
2 9787
13.8%
7 8409
11.9%
- 7019
9.9%
6543
9.2%
1 5553
7.8%
3 4299
 
6.1%
4 3582
 
5.1%
5 3489
 
4.9%
8 3445
 
4.9%
Other values (6) 6803
9.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING 

Distinct162
Distinct (%)9.8%
Missing8343
Missing (%)83.4%
Infinite0
Infinite (%)0.0%
Mean142090.03
Minimum100180
Maximum472908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:14.040277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100180
5-th percentile140012
Q1140080
median140210
Q3140847
95-th percentile140894
Maximum472908
Range372728
Interquartile range (IQR)767

Descriptive statistics

Standard deviation22656.871
Coefficient of variation (CV)0.15945432
Kurtosis170.33571
Mean142090.03
Median Absolute Deviation (MAD)198
Skewness12.949384
Sum2.3544319 × 108
Variance5.1333378 × 108
MonotonicityNot monotonic
2024-04-06T20:06:14.366283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140012 167
 
1.7%
140013 131
 
1.3%
140210 70
 
0.7%
140746 69
 
0.7%
140113 67
 
0.7%
140747 64
 
0.6%
140879 60
 
0.6%
140200 60
 
0.6%
140090 48
 
0.5%
140873 45
 
0.4%
Other values (152) 876
 
8.8%
(Missing) 8343
83.4%
ValueCountFrequency (%)
100180 1
< 0.1%
100450 1
< 0.1%
110822 1
< 0.1%
110836 1
< 0.1%
121230 1
< 0.1%
122851 1
< 0.1%
130872 1
< 0.1%
133120 1
< 0.1%
134020 2
< 0.1%
135010 1
< 0.1%
ValueCountFrequency (%)
472908 1
< 0.1%
471080 1
< 0.1%
471010 2
< 0.1%
421190 1
< 0.1%
420801 1
< 0.1%
412060 1
< 0.1%
405220 1
< 0.1%
403030 1
< 0.1%
336012 1
< 0.1%
157014 1
< 0.1%

지번주소
Text

MISSING 

Distinct4180
Distinct (%)50.8%
Missing1776
Missing (%)17.8%
Memory size156.2 KiB
2024-04-06T20:06:14.874529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length46
Mean length28.016294
Min length13

Characters and Unicode

Total characters230406
Distinct characters460
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3308 ?
Unique (%)40.2%

Sample

1st row서울특별시 용산구 이태원동 ***-** *층 *호,*호
2nd row서울특별시 용산구 후암동 ***번지 ***호
3rd row서울특별시 용산구 용산동*가 *-****
4th row서울특별시 용산구 한강로*가 ***번지 래미안용산 더 센트럴
5th row서울특별시 용산구 한강로*가 **-**
ValueCountFrequency (%)
서울특별시 8213
18.0%
용산구 8186
17.9%
5895
12.9%
호 3734
 
8.2%
한강로*가 2891
 
6.3%
번지 2720
 
5.9%
층 1062
 
2.3%
원효로*가 944
 
2.1%
한남동 720
 
1.6%
이태원동 622
 
1.4%
Other values (2253) 10765
23.5%
2024-04-06T20:06:15.707760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 46810
20.3%
39421
17.1%
용 9156
 
4.0%
산 9089
 
3.9%
서 8480
 
3.7%
시 8335
 
3.6%
구 8330
 
3.6%
울 8248
 
3.6%
특 8230
 
3.6%
별 8228
 
3.6%
Other values (450) 76079
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135567
58.8%
Other Punctuation 47095
 
20.4%
Space Separator 39421
 
17.1%
Dash Punctuation 5134
 
2.2%
Decimal Number 2257
 
1.0%
Uppercase Letter 540
 
0.2%
Lowercase Letter 190
 
0.1%
Close Punctuation 92
 
< 0.1%
Open Punctuation 91
 
< 0.1%
Math Symbol 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 9156
 
6.8%
산 9089
 
6.7%
서 8480
 
6.3%
시 8335
 
6.1%
구 8330
 
6.1%
울 8248
 
6.1%
특 8230
 
6.1%
별 8228
 
6.1%
가 6081
 
4.5%
동 5593
 
4.1%
Other values (384) 55797
41.2%
Uppercase Letter
ValueCountFrequency (%)
B 225
41.7%
A 77
 
14.3%
G 43
 
8.0%
S 40
 
7.4%
C 33
 
6.1%
D 26
 
4.8%
L 15
 
2.8%
P 12
 
2.2%
K 8
 
1.5%
E 8
 
1.5%
Other values (12) 53
 
9.8%
Lowercase Letter
ValueCountFrequency (%)
e 72
37.9%
c 24
 
12.6%
a 17
 
8.9%
s 14
 
7.4%
p 14
 
7.4%
b 11
 
5.8%
l 6
 
3.2%
i 6
 
3.2%
r 5
 
2.6%
d 4
 
2.1%
Other values (9) 17
 
8.9%
Decimal Number
ValueCountFrequency (%)
1 490
21.7%
2 409
18.1%
3 255
11.3%
4 219
9.7%
5 204
9.0%
6 173
 
7.7%
0 151
 
6.7%
9 122
 
5.4%
7 122
 
5.4%
8 112
 
5.0%
Other Punctuation
ValueCountFrequency (%)
* 46810
99.4%
, 110
 
0.2%
. 97
 
0.2%
/ 66
 
0.1%
& 6
 
< 0.1%
' 2
 
< 0.1%
: 2
 
< 0.1%
@ 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
39421
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135567
58.8%
Common 94107
40.8%
Latin 732
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 9156
 
6.8%
산 9089
 
6.7%
서 8480
 
6.3%
시 8335
 
6.1%
구 8330
 
6.1%
울 8248
 
6.1%
특 8230
 
6.1%
별 8228
 
6.1%
가 6081
 
4.5%
동 5593
 
4.1%
Other values (384) 55797
41.2%
Latin
ValueCountFrequency (%)
B 225
30.7%
A 77
 
10.5%
e 72
 
9.8%
G 43
 
5.9%
S 40
 
5.5%
C 33
 
4.5%
D 26
 
3.6%
c 24
 
3.3%
a 17
 
2.3%
L 15
 
2.0%
Other values (33) 160
21.9%
Common
ValueCountFrequency (%)
* 46810
49.7%
39421
41.9%
- 5134
 
5.5%
1 490
 
0.5%
2 409
 
0.4%
3 255
 
0.3%
4 219
 
0.2%
5 204
 
0.2%
6 173
 
0.2%
0 151
 
0.2%
Other values (13) 841
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135566
58.8%
ASCII 94837
41.2%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 46810
49.4%
39421
41.6%
- 5134
 
5.4%
1 490
 
0.5%
2 409
 
0.4%
3 255
 
0.3%
B 225
 
0.2%
4 219
 
0.2%
5 204
 
0.2%
6 173
 
0.2%
Other values (54) 1497
 
1.6%
Hangul
ValueCountFrequency (%)
용 9156
 
6.8%
산 9089
 
6.7%
서 8480
 
6.3%
시 8335
 
6.1%
구 8330
 
6.1%
울 8248
 
6.1%
특 8230
 
6.1%
별 8228
 
6.1%
가 6081
 
4.5%
동 5593
 
4.1%
Other values (383) 55796
41.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅈ 1
100.0%

도로명주소
Text

MISSING 

Distinct4714
Distinct (%)67.1%
Missing2971
Missing (%)29.7%
Memory size156.2 KiB
2024-04-06T20:06:16.122080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length57
Mean length36.787879
Min length21

Characters and Unicode

Total characters258582
Distinct characters492
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3848 ?
Unique (%)54.7%

Sample

1st row서울특별시 용산구 한강대로***길 **, *층, *층, 지층 (후암동)
2nd row서울특별시 용산구 신흥로 *** (용산동*가)
3rd row서울특별시 용산구 한남대로**길 **, 지층,*층 (한남동)
4th row서울특별시 용산구 한강대로 **, B동 ****호 (한강로*가, 래미안용산 더 센트럴)
5th row서울특별시 용산구 서빙고로 **, ***호 (한강로*가)
ValueCountFrequency (%)
서울특별시 7020
14.6%
용산구 6990
14.5%
6673
13.9%
호 3511
 
7.3%
층 2485
 
5.2%
한강로*가 1632
 
3.4%
동 1151
 
2.4%
청파로 897
 
1.9%
한남동 728
 
1.5%
원효로*가 685
 
1.4%
Other values (2659) 16360
34.0%
2024-04-06T20:06:16.950262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 45657
17.7%
41183
 
15.9%
로 9912
 
3.8%
, 8611
 
3.3%
용 7940
 
3.1%
산 7898
 
3.1%
서 7556
 
2.9%
시 7153
 
2.8%
구 7107
 
2.7%
( 7072
 
2.7%
Other values (482) 108493
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143090
55.3%
Other Punctuation 54319
 
21.0%
Space Separator 41183
 
15.9%
Open Punctuation 7072
 
2.7%
Close Punctuation 7072
 
2.7%
Decimal Number 3163
 
1.2%
Dash Punctuation 1877
 
0.7%
Uppercase Letter 625
 
0.2%
Lowercase Letter 150
 
0.1%
Math Symbol 28
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9912
 
6.9%
용 7940
 
5.5%
산 7898
 
5.5%
서 7556
 
5.3%
시 7153
 
5.0%
구 7107
 
5.0%
울 7054
 
4.9%
별 7034
 
4.9%
특 7031
 
4.9%
동 6219
 
4.3%
Other values (417) 68186
47.7%
Uppercase Letter
ValueCountFrequency (%)
B 271
43.4%
A 115
18.4%
C 54
 
8.6%
G 38
 
6.1%
S 34
 
5.4%
D 32
 
5.1%
L 10
 
1.6%
T 9
 
1.4%
K 8
 
1.3%
F 7
 
1.1%
Other values (11) 47
 
7.5%
Lowercase Letter
ValueCountFrequency (%)
e 68
45.3%
c 12
 
8.0%
a 7
 
4.7%
i 7
 
4.7%
l 7
 
4.7%
b 6
 
4.0%
s 6
 
4.0%
k 5
 
3.3%
o 5
 
3.3%
r 5
 
3.3%
Other values (10) 22
 
14.7%
Decimal Number
ValueCountFrequency (%)
1 748
23.6%
2 597
18.9%
0 415
13.1%
3 379
12.0%
4 281
 
8.9%
5 183
 
5.8%
7 163
 
5.2%
6 146
 
4.6%
8 140
 
4.4%
9 111
 
3.5%
Other Punctuation
ValueCountFrequency (%)
* 45657
84.1%
, 8611
 
15.9%
. 36
 
0.1%
& 6
 
< 0.1%
/ 6
 
< 0.1%
@ 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
41183
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7072
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7072
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1877
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143089
55.3%
Common 114715
44.4%
Latin 777
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9912
 
6.9%
용 7940
 
5.5%
산 7898
 
5.5%
서 7556
 
5.3%
시 7153
 
5.0%
구 7107
 
5.0%
울 7054
 
4.9%
별 7034
 
4.9%
특 7031
 
4.9%
동 6219
 
4.3%
Other values (416) 68185
47.7%
Latin
ValueCountFrequency (%)
B 271
34.9%
A 115
14.8%
e 68
 
8.8%
C 54
 
6.9%
G 38
 
4.9%
S 34
 
4.4%
D 32
 
4.1%
c 12
 
1.5%
L 10
 
1.3%
T 9
 
1.2%
Other values (33) 134
17.2%
Common
ValueCountFrequency (%)
* 45657
39.8%
41183
35.9%
, 8611
 
7.5%
( 7072
 
6.2%
) 7072
 
6.2%
- 1877
 
1.6%
1 748
 
0.7%
2 597
 
0.5%
0 415
 
0.4%
3 379
 
0.3%
Other values (12) 1104
 
1.0%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143089
55.3%
ASCII 115490
44.7%
Number Forms 2
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 45657
39.5%
41183
35.7%
, 8611
 
7.5%
( 7072
 
6.1%
) 7072
 
6.1%
- 1877
 
1.6%
1 748
 
0.6%
2 597
 
0.5%
0 415
 
0.4%
3 379
 
0.3%
Other values (53) 1879
 
1.6%
Hangul
ValueCountFrequency (%)
로 9912
 
6.9%
용 7940
 
5.5%
산 7898
 
5.5%
서 7556
 
5.3%
시 7153
 
5.0%
구 7107
 
5.0%
울 7054
 
4.9%
별 7034
 
4.9%
특 7031
 
4.9%
동 6219
 
4.3%
Other values (416) 68185
47.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

도로명우편번호
Text

MISSING 

Distinct347
Distinct (%)5.6%
Missing3824
Missing (%)38.2%
Memory size156.2 KiB
2024-04-06T20:06:17.589105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.267649
Min length5

Characters and Unicode

Total characters32533
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

Unique68 ?
Unique (%)1.1%

Sample

1st row04332
2nd row04337
3rd row140894
4th row04378
5th row04387
ValueCountFrequency (%)
04371 244
 
4.0%
04370 167
 
2.7%
04366 150
 
2.4%
04373 128
 
2.1%
04382 122
 
2.0%
140012 100
 
1.6%
140873 100
 
1.6%
04315 97
 
1.6%
04374 95
 
1.5%
04376 91
 
1.5%
Other values (337) 4882
79.0%
2024-04-06T20:06:18.455044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 8069
24.8%
0 7934
24.4%
3 4995
15.4%
1 3474
10.7%
7 1930
 
5.9%
8 1543
 
4.7%
2 1426
 
4.4%
6 1307
 
4.0%
9 932
 
2.9%
5 765
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32375
99.5%
Dash Punctuation 158
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 8069
24.9%
0 7934
24.5%
3 4995
15.4%
1 3474
10.7%
7 1930
 
6.0%
8 1543
 
4.8%
2 1426
 
4.4%
6 1307
 
4.0%
9 932
 
2.9%
5 765
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32533
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 8069
24.8%
0 7934
24.4%
3 4995
15.4%
1 3474
10.7%
7 1930
 
5.9%
8 1543
 
4.7%
2 1426
 
4.4%
6 1307
 
4.0%
9 932
 
2.9%
5 765
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 8069
24.8%
0 7934
24.4%
3 4995
15.4%
1 3474
10.7%
7 1930
 
5.9%
8 1543
 
4.7%
2 1426
 
4.4%
6 1307
 
4.0%
9 932
 
2.9%
5 765
 
2.4%

사업장명
Text

Distinct9849
Distinct (%)98.5%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-04-06T20:06:19.185777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length7.8151815
Min length1

Characters and Unicode

Total characters78144
Distinct characters1015
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9711 ?
Unique (%)97.1%

Sample

1st row인디언 26
2nd row주식회사 재클린
3rd row캔따개와고양이
4th row코든(CORDinat ion)
5th row커피인코나
ValueCountFrequency (%)
주식회사 938
 
7.0%
주 249
 
1.9%
company 31
 
0.2%
컴퍼니 28
 
0.2%
co 25
 
0.2%
korea 25
 
0.2%
24
 
0.2%
스튜디오 23
 
0.2%
더 22
 
0.2%
ltd 22
 
0.2%
Other values (11058) 12034
89.7%
2024-04-06T20:06:20.134237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3496
 
4.5%
) 3495
 
4.5%
3437
 
4.4%
주 3085
 
3.9%
이 2740
 
3.5%
스 2205
 
2.8%
사 1285
 
1.6%
아 1028
 
1.3%
회 1022
 
1.3%
리 1007
 
1.3%
Other values (1005) 55344
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52492
67.2%
Lowercase Letter 7689
 
9.8%
Uppercase Letter 6561
 
8.4%
Open Punctuation 3496
 
4.5%
Close Punctuation 3495
 
4.5%
Space Separator 3437
 
4.4%
Decimal Number 436
 
0.6%
Other Punctuation 414
 
0.5%
Dash Punctuation 68
 
0.1%
Other Symbol 40
 
0.1%
Other values (3) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3085
 
5.9%
이 2740
 
5.2%
스 2205
 
4.2%
사 1285
 
2.4%
아 1028
 
2.0%
회 1022
 
1.9%
리 1007
 
1.9%
식 1003
 
1.9%
트 859
 
1.6%
에 810
 
1.5%
Other values (923) 37448
71.3%
Lowercase Letter
ValueCountFrequency (%)
e 906
11.8%
o 790
 
10.3%
a 671
 
8.7%
n 598
 
7.8%
i 562
 
7.3%
t 485
 
6.3%
r 473
 
6.2%
l 445
 
5.8%
s 361
 
4.7%
c 285
 
3.7%
Other values (16) 2113
27.5%
Uppercase Letter
ValueCountFrequency (%)
A 499
 
7.6%
E 496
 
7.6%
O 491
 
7.5%
C 444
 
6.8%
T 400
 
6.1%
N 398
 
6.1%
L 387
 
5.9%
S 386
 
5.9%
I 357
 
5.4%
M 313
 
4.8%
Other values (16) 2390
36.4%
Other Punctuation
ValueCountFrequency (%)
. 227
54.8%
& 94
22.7%
, 52
 
12.6%
' 15
 
3.6%
? 7
 
1.7%
# 6
 
1.4%
: 6
 
1.4%
; 3
 
0.7%
/ 3
 
0.7%
% 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 94
21.6%
2 76
17.4%
9 48
11.0%
3 46
10.6%
0 42
9.6%
4 39
8.9%
5 28
 
6.4%
6 26
 
6.0%
8 22
 
5.0%
7 15
 
3.4%
Other Symbol
ValueCountFrequency (%)
㈜ 39
97.5%
ⓘ 1
 
2.5%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3496
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3495
100.0%
Space Separator
ValueCountFrequency (%)
3437
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52521
67.2%
Latin 14250
 
18.2%
Common 11363
 
14.5%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3085
 
5.9%
이 2740
 
5.2%
스 2205
 
4.2%
사 1285
 
2.4%
아 1028
 
2.0%
회 1022
 
1.9%
리 1007
 
1.9%
식 1003
 
1.9%
트 859
 
1.6%
에 810
 
1.5%
Other values (915) 37477
71.4%
Latin
ValueCountFrequency (%)
e 906
 
6.4%
o 790
 
5.5%
a 671
 
4.7%
n 598
 
4.2%
i 562
 
3.9%
A 499
 
3.5%
E 496
 
3.5%
O 491
 
3.4%
t 485
 
3.4%
r 473
 
3.3%
Other values (42) 8279
58.1%
Common
ValueCountFrequency (%)
( 3496
30.8%
) 3495
30.8%
3437
30.2%
. 227
 
2.0%
& 94
 
0.8%
1 94
 
0.8%
2 76
 
0.7%
- 68
 
0.6%
, 52
 
0.5%
9 48
 
0.4%
Other values (19) 276
 
2.4%
Han
ValueCountFrequency (%)
美 2
20.0%
海 1
10.0%
親 1
10.0%
友 1
10.0%
李 1
10.0%
本 1
10.0%
韓 1
10.0%
資 1
10.0%
云 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52482
67.2%
ASCII 25611
32.8%
None 39
 
< 0.1%
CJK 9
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3496
 
13.7%
) 3495
 
13.6%
3437
 
13.4%
e 906
 
3.5%
o 790
 
3.1%
a 671
 
2.6%
n 598
 
2.3%
i 562
 
2.2%
A 499
 
1.9%
E 496
 
1.9%
Other values (69) 10661
41.6%
Hangul
ValueCountFrequency (%)
주 3085
 
5.9%
이 2740
 
5.2%
스 2205
 
4.2%
사 1285
 
2.4%
아 1028
 
2.0%
회 1022
 
1.9%
리 1007
 
1.9%
식 1003
 
1.9%
트 859
 
1.6%
에 810
 
1.5%
Other values (914) 37438
71.3%
None
ValueCountFrequency (%)
㈜ 39
100.0%
CJK
ValueCountFrequency (%)
美 2
22.2%
海 1
11.1%
親 1
11.1%
友 1
11.1%
本 1
11.1%
韓 1
11.1%
資 1
11.1%
云 1
11.1%
Enclosed Alphanum
ValueCountFrequency (%)
ⓘ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

최종수정일자
Date

Distinct8987
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-07-23 13:41:42
Maximum2024-04-04 13:15:27
2024-04-06T20:06:20.518083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:20.838342image/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
7482 
U
2518 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7482
74.8%
U 2518
 
25.2%

Length

2024-04-06T20:06:21.060047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:21.233120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7482
74.8%
u 2518
 
25.2%

데이터갱신일자
Date

Distinct1213
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T20:06:21.430113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:06:21.708788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

Distinct478
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T20:06:22.014903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length80
Mean length8.7729
Min length1

Characters and Unicode

Total characters87729
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

Unique290 ?
Unique (%)2.9%

Sample

1st row의류/패션/잡화/뷰티
2nd row종합몰 의류/패션/잡화/뷰티
3rd row기타
4th row의류/패션/잡화/뷰티
5th row건강/식품
ValueCountFrequency (%)
의류/패션/잡화/뷰티 2846
20.1%
컴퓨터/사무용품 2489
17.6%
종합몰 2121
15.0%
1614
11.4%
기타 1579
11.2%
가전 988
 
7.0%
건강/식품 691
 
4.9%
교육/도서/완구/오락 649
 
4.6%
가구/수납용품 417
 
2.9%
레져/여행/공연 309
 
2.2%
Other values (3) 437
 
3.1%
2024-04-06T20:06:22.686270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 15048
 
17.2%
4140
 
4.7%
품 4034
 
4.6%
용 3254
 
3.7%
뷰 2846
 
3.2%
류 2846
 
3.2%
티 2846
 
3.2%
의 2846
 
3.2%
화 2846
 
3.2%
잡 2846
 
3.2%
Other values (41) 44177
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66927
76.3%
Other Punctuation 15048
 
17.2%
Space Separator 4140
 
4.7%
Dash Punctuation 1614
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 4034
 
6.0%
용 3254
 
4.9%
뷰 2846
 
4.3%
류 2846
 
4.3%
티 2846
 
4.3%
의 2846
 
4.3%
화 2846
 
4.3%
잡 2846
 
4.3%
션 2846
 
4.3%
패 2846
 
4.3%
Other values (38) 36871
55.1%
Other Punctuation
ValueCountFrequency (%)
/ 15048
100.0%
Space Separator
ValueCountFrequency (%)
4140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1614
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66927
76.3%
Common 20802
 
23.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 4034
 
6.0%
용 3254
 
4.9%
뷰 2846
 
4.3%
류 2846
 
4.3%
티 2846
 
4.3%
의 2846
 
4.3%
화 2846
 
4.3%
잡 2846
 
4.3%
션 2846
 
4.3%
패 2846
 
4.3%
Other values (38) 36871
55.1%
Common
ValueCountFrequency (%)
/ 15048
72.3%
4140
 
19.9%
- 1614
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66927
76.3%
ASCII 20802
 
23.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 15048
72.3%
4140
 
19.9%
- 1614
 
7.8%
Hangul
ValueCountFrequency (%)
품 4034
 
6.0%
용 3254
 
4.9%
뷰 2846
 
4.3%
류 2846
 
4.3%
티 2846
 
4.3%
의 2846
 
4.3%
화 2846
 
4.3%
잡 2846
 
4.3%
션 2846
 
4.3%
패 2846
 
4.3%
Other values (38) 36871
55.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3266
Distinct (%)45.4%
Missing2813
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean197672.67
Minimum173750.39
Maximum219238.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:22.954737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173750.39
5-th percentile196044.8
Q1196705.48
median197115.96
Q3198825.34
95-th percentile200357.54
Maximum219238.66
Range45488.273
Interquartile range (IQR)2119.8636

Descriptive statistics

Standard deviation1553.2975
Coefficient of variation (CV)0.0078579277
Kurtosis23.570852
Mean197672.67
Median Absolute Deviation (MAD)676.10346
Skewness0.45028704
Sum1.4206735 × 109
Variance2412733.2
MonotonicityNot monotonic
2024-04-06T20:06:23.244796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196839.641743356 193
 
1.9%
196893.277042114 186
 
1.9%
196370.746398773 125
 
1.2%
196762.077394917 114
 
1.1%
196873.001604976 111
 
1.1%
196118.749575977 81
 
0.8%
196775.639878418 69
 
0.7%
196060.559012563 65
 
0.7%
196385.232032928 64
 
0.6%
196189.205036161 59
 
0.6%
Other values (3256) 6120
61.2%
(Missing) 2813
28.1%
ValueCountFrequency (%)
173750.390635558 1
< 0.1%
175126.163890762 1
< 0.1%
186290.898350491 1
< 0.1%
189686.475000033 1
< 0.1%
190174.839618048 1
< 0.1%
190461.790473157 1
< 0.1%
190671.436719919 1
< 0.1%
190688.747501289 1
< 0.1%
190828.268143013 1
< 0.1%
191213.365899415 1
< 0.1%
ValueCountFrequency (%)
219238.663603894 1
< 0.1%
212432.197818938 1
< 0.1%
212127.268899208 1
< 0.1%
211027.8338921 1
< 0.1%
210970.75707265 1
< 0.1%
209717.866852267 1
< 0.1%
208394.416382167 1
< 0.1%
207236.605740857 1
< 0.1%
205379.194674158 1
< 0.1%
205098.400364657 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING  SKEWED 

Distinct3261
Distinct (%)45.4%
Missing2813
Missing (%)28.1%
Infinite0
Infinite (%)0.0%
Mean448148.38
Minimum363917.53
Maximum460494.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T20:06:23.471351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum363917.53
5-th percentile446855.74
Q1447760.16
median447982.92
Q3448588.9
95-th percentile449732.81
Maximum460494.43
Range96576.905
Interquartile range (IQR)828.74107

Descriptive statistics

Standard deviation1328.3943
Coefficient of variation (CV)0.0029641841
Kurtosis2252.4222
Mean448148.38
Median Absolute Deviation (MAD)355.50381
Skewness-35.228988
Sum3.2208424 × 109
Variance1764631.4
MonotonicityNot monotonic
2024-04-06T20:06:23.793607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447863.232025192 193
 
1.9%
447852.583272453 186
 
1.9%
447841.698787531 125
 
1.2%
447480.039577359 114
 
1.1%
447960.206197372 111
 
1.1%
447760.157527455 81
 
0.8%
447984.6345458 69
 
0.7%
447732.807254308 65
 
0.7%
447938.19246116 64
 
0.6%
447894.643407414 59
 
0.6%
Other values (3251) 6120
61.2%
(Missing) 2813
28.1%
ValueCountFrequency (%)
363917.525762 1
< 0.1%
438911.57492191 1
< 0.1%
440230.216008712 1
< 0.1%
440870.092608694 1
< 0.1%
441820.071591607 1
< 0.1%
442219.137493629 1
< 0.1%
442368.090413171 1
< 0.1%
442618.785745098 1
< 0.1%
443299.689335502 1
< 0.1%
443488.120892131 1
< 0.1%
ValueCountFrequency (%)
460494.430844782 1
< 0.1%
459591.06662434 1
< 0.1%
458043.001739156 1
< 0.1%
456108.627924468 1
< 0.1%
455843.387167702 1
< 0.1%
454056.59189241 1
< 0.1%
452844.465747665 1
< 0.1%
452139.237844695 1
< 0.1%
451972.610772923 1
< 0.1%
451720.217970577 1
< 0.1%

자산규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9613 
0
 
387

Length

Max length4
Median length4
Mean length3.8839
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9613
96.1%
0 387
 
3.9%

Length

2024-04-06T20:06:24.048445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:24.221374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9613
96.1%
0 387
 
3.9%

부채총액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9613 
0
 
387

Length

Max length4
Median length4
Mean length3.8839
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9613
96.1%
0 387
 
3.9%

Length

2024-04-06T20:06:24.433697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:24.617086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9613
96.1%
0 387
 
3.9%

자본금
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9613 
0
 
387

Length

Max length4
Median length4
Mean length3.8839
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9613
96.1%
0 387
 
3.9%

Length

2024-04-06T20:06:24.991861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:06:25.299068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9613
96.1%
0 387
 
3.9%

판매방식명
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5529 
인터넷
4297 
인터넷, 기타
 
53
기타
 
32
TV홈쇼핑, 인터넷
 
19
Other values (17)
 
70

Length

Max length26
Median length4
Mean length3.6803
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5529
55.3%
인터넷 4297
43.0%
인터넷, 기타 53
 
0.5%
기타 32
 
0.3%
TV홈쇼핑, 인터넷 19
 
0.2%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지, 기타 16
 
0.2%
TV홈쇼핑, 인터넷, 기타 7
 
0.1%
인터넷, 카다로그, 기타 6
 
0.1%
인터넷, 카다로그, 신문잡지, 기타 6
 
0.1%
인터넷, 카다로그, 신문잡지 5
 
0.1%
Other values (12) 30
 
0.3%

Length

2024-04-06T20:06:25.592515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5529
54.0%
인터넷 4431
43.3%
기타 127
 
1.2%
tv홈쇼핑 60
 
0.6%
카다로그 51
 
0.5%
신문잡지 40
 
0.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
114413020000201030200953020088720100902<NA>3폐업3폐업처리20101202<NA><NA><NA>793-9728<NA>140200서울특별시 용산구 이태원동 ***-** *층 *호,*호<NA><NA>인디언 262010-12-02 15:34:12I2018-08-31 23:59:59.0의류/패션/잡화/뷰티<NA><NA><NA><NA><NA>인터넷
178413020000201630201503020093720160926<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1644-1828<NA><NA>서울특별시 용산구 후암동 ***번지 ***호서울특별시 용산구 한강대로***길 **, *층, *층, 지층 (후암동)04332주식회사 재클린2018-01-16 10:22:49I2021-12-03 22:02:00.0종합몰 의류/패션/잡화/뷰티197897.030012449754.014242<NA><NA><NA><NA>
254313020000202130201503020125020210624<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 용산동*가 *-****서울특별시 용산구 신흥로 *** (용산동*가)04337캔따개와고양이2021-06-24 10:27:13I2021-06-26 00:22:54.0기타198318.315787449159.540446<NA><NA><NA>인터넷
160703020000201530201503020009120150115<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한남대로**길 **, 지층,*층 (한남동)140894코든(CORDinat ion)2018-05-21 13:26:15I2018-08-31 23:59:59.0의류/패션/잡화/뷰티200192.459424449052.166244<NA><NA><NA>인터넷
21382302000020193020150302008402016-01-27<NA>5제외/삭제/전출5타시군구이관2023-05-10<NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로*가 ***번지 래미안용산 더 센트럴서울특별시 용산구 한강대로 **, B동 ****호 (한강로*가, 래미안용산 더 센트럴)04378커피인코나2023-05-10 09:44:13U2022-12-04 23:02:00.0건강/식품197011.737529447430.100251<NA><NA><NA><NA>
239183020000202030201503020195920150429<NA>1영업/정상1정상영업<NA><NA><NA><NA>070 7732 7919<NA><NA>서울특별시 용산구 한강로*가 **-**서울특별시 용산구 서빙고로 **, ***호 (한강로*가)04387주식회사 뽀르띠골드2022-11-15 17:00:04U2021-10-31 23:07:00.0의류/패션/잡화/뷰티197071.403206447073.622842<NA><NA><NA><NA>
193253020000201830201503020007920180122<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-704-4586<NA><NA>서울특별시 용산구 원효로*가 **번지 *호서울특별시 용산구 원효로**길 **, *층 (원효로*가)04363디엔제이2020-03-18 18:33:14U2020-03-20 02:40:00.0컴퓨터/사무용품196455.434862448127.030157<NA><NA><NA>인터넷
63103020000200630200953020640320061128<NA>3폐업3폐업처리20110601<NA><NA><NA>02 794 9132<NA><NA>서울특별시 용산구 한강로*가 **-*** *층<NA><NA>폭스밀라노2011-06-01 10:56:42I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>
16198302000020153020150302002432015-02-24<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-790-2471<NA><NA><NA>서울특별시 용산구 한강대로 *** (한강로*가, 용산비즈텔**층 제*동****호)140-750퍼시픽 림 알리안스 코리아 유한책임회사 (영업소)2022-12-01 13:43:44U2022-12-04 22:06:00.0기타197117.418435447527.338271<NA><NA><NA><NA>
146523020000201330200953020080520050302<NA>1영업/정상1정상영업<NA><NA><NA><NA>028490011<NA>140140서울특별시 용산구 서계동 **번지 ***호 현대오피스 ***서울특별시 용산구 청파로**가길 **, ***호 (서계동, 현대오피스)140827아포코2013-08-08 16:49:37I2018-08-31 23:59:59.0종합몰197023.570766450007.904506<NA><NA><NA>인터넷
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
104963020000200930200953020117620091026<NA>4취소/말소/만료/정지/중지7직권말소<NA>2017080820201231<NA>02-711-4740<NA><NA>서울특별시 용산구 신계동 27번지 18호 2층서울특별시 용산구 새창로45길 22 (신계동,2층)<NA>사운드웨이브2022-12-13 16:45:06U2021-11-01 23:05:00.0기타196706.907886448037.504316<NA><NA><NA><NA>
143293020000201330200953020041420130419<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>070-4036-1319<NA><NA><NA>서울특별시 용산구 회나무로**길 **, 지층 (이태원동)140856KJ통신2018-05-21 11:31:53I2018-08-31 23:59:59.0기타199324.562319448690.910617<NA><NA><NA>인터넷
94363020000200930200953020002420090106<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-718-2260<NA>140747서울특별시 용산구 한강로*가 **번지 *호 선인상가**동*층****호<NA><NA>(주)영웅씨앤씨2013-12-27 09:49:43I2018-08-31 23:59:59.0컴퓨터/사무용품196893.277042447852.583272<NA><NA><NA>인터넷
26465302000020223020150302001232022-01-18<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 이태원동 ***-*서울특별시 용산구 이태원로 ***, 썬타운 B*층 (이태원동)04391빅사이즈토탈몰2023-12-23 15:51:47U2022-11-01 22:05:00.0의류/패션/잡화/뷰티199349.790763447999.806798<NA><NA><NA><NA>
249573020000202130201503020076320210404<NA>1영업/정상1정상영업<NA><NA><NA><NA>07047951674<NA><NA>서울특별시 용산구 도원동 *-**서울특별시 용산구 새창로**길 *, *층 (도원동)04356코티지로프2021-04-06 15:27:11I2021-12-03 22:02:00.0종합몰 건강/식품196200.514333448566.583898<NA><NA><NA><NA>
89283020000200830200953020076720080708<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02-702-4100<NA>140877서울특별시 용산구 한강로*가 *번지 *호 나진상가**동*층가열**호서울특별시 용산구 청파로 *** (한강로*가,나진상가**동*층가열**호)<NA>한진전기2012-06-29 17:52:56I2018-08-31 23:59:59.0기타196600.080247447900.639295<NA><NA><NA>인터넷
264003020000202230201503020005620220107<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로*가 **-*서울특별시 용산구 한강대로**가길 **, *층 (한강로*가)04382그?방2022-01-12 17:05:32I2022-01-14 00:22:40.0의류/패션/잡화/뷰티197426.528827447613.633912000기타
256433020000202130201503020147020180402<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-7777-5094<NA><NA>서울특별시 용산구 이태원동 *-**서울특별시 용산구 회나무로 **, ***동 ***호 (이태원동)04346(주)페이우2021-08-02 09:31:44U2021-08-04 02:40:00.0의류/패션/잡화/뷰티199472.58833448687.584666000인터넷, 기타
71633020000200730200953020676920070306<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 790 2503<NA><NA>서울특별시 용산구 보광동 *-** B***호<NA><NA>미스피기2010-12-23 11:32:04I2018-08-31 23:59:59.0의류/패션/잡화/뷰티<NA><NA><NA><NA><NA>인터넷
3013020000200130200953020758520011009<NA>3폐업3폐업처리<NA><NA><NA><NA>02 790 1491<NA><NA>서울특별시 용산구 한강로*가 **-* 삼화빌딩<NA><NA>대양상사2008-02-21 00:00:00I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>