Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells65399
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory252.0 B

Variable types

Categorical10
Numeric5
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-18819/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (99.9%)Imbalance
자산규모 is highly imbalanced (68.5%)Imbalance
부채총액 is highly imbalanced (68.5%)Imbalance
자본금 is highly imbalanced (68.5%)Imbalance
판매방식명 is highly imbalanced (70.7%)Imbalance
폐업일자 has 7248 (72.5%) missing valuesMissing
휴업시작일자 has 9954 (99.5%) missing valuesMissing
휴업종료일자 has 9954 (99.5%) missing valuesMissing
재개업일자 has 9945 (99.5%) missing valuesMissing
전화번호 has 5494 (54.9%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 8287 (82.9%) missing valuesMissing
지번주소 has 1163 (11.6%) missing valuesMissing
도로명주소 has 555 (5.5%) missing valuesMissing
도로명우편번호 has 1587 (15.9%) missing valuesMissing
좌표정보(X) has 606 (6.1%) missing valuesMissing
좌표정보(Y) has 606 (6.1%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = 23.49456325)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 13:37:28.719556
Analysis finished2024-04-06 13:37:30.514625
Duration1.8 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
3170000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 10000
100.0%

Length

2024-04-06T22:37:30.565654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:30.641636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 10000
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0174839 × 1018
Minimum1.996317 × 1018
Maximum2.024317 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:37:30.739931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996317 × 1018
5-th percentile2.006317 × 1018
Q12.014317 × 1018
median2.019317 × 1018
Q32.021317 × 1018
95-th percentile2.023317 × 1018
Maximum2.024317 × 1018
Range2.8000015 × 1016
Interquartile range (IQR)7.0000093 × 1015

Descriptive statistics

Standard deviation5.461326 × 1015
Coefficient of variation (CV)0.0027069985
Kurtosis-0.063098542
Mean2.0174839 × 1018
Median Absolute Deviation (MAD)3.0000067 × 1015
Skewness-0.90510972
Sum-5.8988225 × 1018
Variance2.9826082 × 1031
MonotonicityNot monotonic
2024-04-06T22:37:30.868988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019317019030200059 1
 
< 0.1%
2010317010530200546 1
 
< 0.1%
2016317017430201375 1
 
< 0.1%
2010317010530200107 1
 
< 0.1%
2016317017430201191 1
 
< 0.1%
2015317017430200946 1
 
< 0.1%
2016317017430200343 1
 
< 0.1%
2006317010530201494 1
 
< 0.1%
2019317019030200849 1
 
< 0.1%
2023317025730202846 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1996317010530200042 1
< 0.1%
1997317010530201038 1
< 0.1%
1998317010530201499 1
< 0.1%
1998317010530201663 1
< 0.1%
2000317010530200030 1
< 0.1%
2000317010530200083 1
< 0.1%
2000317010530203149 1
< 0.1%
2000317010530203154 1
< 0.1%
2000317010530203259 1
< 0.1%
2000317010530203268 1
< 0.1%
ValueCountFrequency (%)
2024317025730200870 1
< 0.1%
2024317025730200869 1
< 0.1%
2024317025730200867 1
< 0.1%
2024317025730200865 1
< 0.1%
2024317025730200863 1
< 0.1%
2024317025730200861 1
< 0.1%
2024317025730200859 1
< 0.1%
2024317025730200857 1
< 0.1%
2024317025730200853 1
< 0.1%
2024317025730200848 1
< 0.1%

인허가일자
Date

Distinct3697
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1996-01-01 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T22:37:31.021186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:31.202093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
20150513
 
1

Length

Max length8
Median length4
Mean length4.0004
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
20150513 1
 
< 0.1%

Length

2024-04-06T22:37:31.333371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:31.423304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
20150513 1
 
< 0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
6199 
3
2071 
4
1011 
5
681 
2
 
38

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 6199
62.0%
3 2071
 
20.7%
4 1011
 
10.1%
5 681
 
6.8%
2 38
 
0.4%

Length

2024-04-06T22:37:31.509624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:31.594697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6199
62.0%
3 2071
 
20.7%
4 1011
 
10.1%
5 681
 
6.8%
2 38
 
0.4%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
6199 
폐업
2071 
취소/말소/만료/정지/중지
1011 
제외/삭제/전출
681 
휴업
 
38

Length

Max length14
Median length5
Mean length5.4815
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 6199
62.0%
폐업 2071
 
20.7%
취소/말소/만료/정지/중지 1011
 
10.1%
제외/삭제/전출 681
 
6.8%
휴업 38
 
0.4%

Length

2024-04-06T22:37:31.700674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:31.795971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 6199
62.0%
폐업 2071
 
20.7%
취소/말소/만료/정지/중지 1011
 
10.1%
제외/삭제/전출 681
 
6.8%
휴업 38
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.297
Minimum0
Maximum8
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:37:31.887249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q33
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9695631
Coefficient of variation (CV)0.85745021
Kurtosis0.65074039
Mean2.297
Median Absolute Deviation (MAD)0
Skewness1.3850229
Sum22970
Variance3.8791789
MonotonicityNot monotonic
2024-04-06T22:37:31.986308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 6197
62.0%
3 2071
 
20.7%
7 1009
 
10.1%
5 681
 
6.8%
2 38
 
0.4%
4 2
 
< 0.1%
0 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 6197
62.0%
2 38
 
0.4%
3 2071
 
20.7%
4 2
 
< 0.1%
5 681
 
6.8%
7 1009
 
10.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 1009
 
10.1%
5 681
 
6.8%
4 2
 
< 0.1%
3 2071
 
20.7%
2 38
 
0.4%
1 6197
62.0%
0 1
 
< 0.1%

상세영업상태명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상영업
6197 
폐업처리
2071 
직권말소
1009 
타시군구이관
681 
휴업처리
 
38
Other values (3)
 
4

Length

Max length6
Median length4
Mean length4.1362
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 6197
62.0%
폐업처리 2071
 
20.7%
직권말소 1009
 
10.1%
타시군구이관 681
 
6.8%
휴업처리 38
 
0.4%
직권취소 2
 
< 0.1%
<NA> 1
 
< 0.1%
영업재개 1
 
< 0.1%

Length

2024-04-06T22:37:32.108612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:32.218320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 6197
62.0%
폐업처리 2071
 
20.7%
직권말소 1009
 
10.1%
타시군구이관 681
 
6.8%
휴업처리 38
 
0.4%
직권취소 2
 
< 0.1%
na 1
 
< 0.1%
영업재개 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1642
Distinct (%)59.7%
Missing7248
Missing (%)72.5%
Memory size156.2 KiB
Minimum2003-09-19 00:00:00
Maximum2024-12-31 00:00:00
2024-04-06T22:37:32.331909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:32.509825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct44
Distinct (%)95.7%
Missing9954
Missing (%)99.5%
Memory size156.2 KiB
Minimum2006-08-09 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T22:37:32.635648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:32.794968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

휴업종료일자
Date

MISSING 

Distinct40
Distinct (%)87.0%
Missing9954
Missing (%)99.5%
Memory size156.2 KiB
Minimum2009-09-30 00:00:00
Maximum2099-01-01 00:00:00
2024-04-06T22:37:32.944257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:33.112778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

재개업일자
Date

MISSING 

Distinct50
Distinct (%)90.9%
Missing9945
Missing (%)99.5%
Memory size156.2 KiB
Minimum2006-12-04 00:00:00
Maximum2024-04-02 00:00:00
2024-04-06T22:37:33.233488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:33.352071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct4385
Distinct (%)97.3%
Missing5494
Missing (%)54.9%
Memory size156.2 KiB
2024-04-06T22:37:33.554816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length10.865513
Min length1

Characters and Unicode

Total characters48960
Distinct characters21
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4294 ?
Unique (%)95.3%

Sample

1st row02-2100-5831
2nd row070-7703-0555
3rd row888-8888
4th row02-3489-0024
5th row02-871-6278
ValueCountFrequency (%)
02 563
 
9.8%
99
 
1.7%
808 23
 
0.4%
2026 20
 
0.3%
802 19
 
0.3%
892 18
 
0.3%
070 18
 
0.3%
809 17
 
0.3%
896 16
 
0.3%
805 15
 
0.3%
Other values (4530) 4939
85.9%
2024-04-06T22:37:33.860697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7985
16.3%
- 6310
12.9%
2 5706
11.7%
8 4602
9.4%
7 3952
8.1%
6 3757
7.7%
1 3331
6.8%
5 3168
 
6.5%
3 2938
 
6.0%
4 2744
 
5.6%
Other values (11) 4467
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40697
83.1%
Dash Punctuation 6310
 
12.9%
Space Separator 1899
 
3.9%
Other Punctuation 39
 
0.1%
Math Symbol 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7985
19.6%
2 5706
14.0%
8 4602
11.3%
7 3952
9.7%
6 3757
9.2%
1 3331
8.2%
5 3168
 
7.8%
3 2938
 
7.2%
4 2744
 
6.7%
9 2514
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 27
69.2%
' 7
 
17.9%
/ 3
 
7.7%
, 2
 
5.1%
Other Letter
ValueCountFrequency (%)
이 1
33.3%
송 1
33.3%
욱 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 6310
100.0%
Space Separator
ValueCountFrequency (%)
1899
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48957
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7985
16.3%
- 6310
12.9%
2 5706
11.7%
8 4602
9.4%
7 3952
8.1%
6 3757
7.7%
1 3331
6.8%
5 3168
 
6.5%
3 2938
 
6.0%
4 2744
 
5.6%
Other values (8) 4464
9.1%
Hangul
ValueCountFrequency (%)
이 1
33.3%
송 1
33.3%
욱 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48957
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7985
16.3%
- 6310
12.9%
2 5706
11.7%
8 4602
9.4%
7 3952
8.1%
6 3757
7.7%
1 3331
6.8%
5 3168
 
6.5%
3 2938
 
6.0%
4 2744
 
5.6%
Other values (8) 4464
9.1%
Hangul
ValueCountFrequency (%)
이 1
33.3%
송 1
33.3%
욱 1
33.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct123
Distinct (%)7.2%
Missing8287
Missing (%)82.9%
Infinite0
Infinite (%)0.0%
Mean153638.15
Minimum120836
Maximum451822
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:37:33.991948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120836
5-th percentile153010
Q1153023
median153023
Q3153031
95-th percentile153830.4
Maximum451822
Range330986
Interquartile range (IQR)8

Descriptive statistics

Standard deviation12002.203
Coefficient of variation (CV)0.078119942
Kurtosis558.50072
Mean153638.15
Median Absolute Deviation (MAD)7
Skewness23.494563
Sum2.6318215 × 108
Variance1.4405289 × 108
MonotonicityNot monotonic
2024-04-06T22:37:34.343176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
153023 751
 
7.5%
153030 205
 
2.1%
153010 200
 
2.0%
153011 83
 
0.8%
153031 65
 
0.7%
153803 38
 
0.4%
153801 31
 
0.3%
153755 28
 
0.3%
153786 16
 
0.2%
153813 15
 
0.1%
Other values (113) 281
 
2.8%
(Missing) 8287
82.9%
ValueCountFrequency (%)
120836 1
 
< 0.1%
130060 1
 
< 0.1%
135896 1
 
< 0.1%
136072 1
 
< 0.1%
137070 1
 
< 0.1%
151010 1
 
< 0.1%
152050 1
 
< 0.1%
152842 1
 
< 0.1%
153010 200
2.0%
153011 83
0.8%
ValueCountFrequency (%)
451822 1
 
< 0.1%
437080 1
 
< 0.1%
426170 1
 
< 0.1%
158070 1
 
< 0.1%
157030 1
 
< 0.1%
156815 1
 
< 0.1%
153869 1
 
< 0.1%
153867 4
< 0.1%
153866 1
 
< 0.1%
153864 2
< 0.1%

지번주소
Text

MISSING 

Distinct2189
Distinct (%)24.8%
Missing1163
Missing (%)11.6%
Memory size156.2 KiB
2024-04-06T22:37:34.556590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length27.67059
Min length13

Characters and Unicode

Total characters244525
Distinct characters446
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1575 ?
Unique (%)17.8%

Sample

1st row서울특별시 금천구 시흥동 ***번지 *호 예일 센트럴
2nd row서울특별시 금천구 가산동 ***-** 에이스 K*타워
3rd row서울특별시 금천구 가산동 ***번지 *호 에이스테크노타워**차 ****호
4th row서울특별시 금천구 가산동 ***-** 에이스 비즈포레 지식산업센터
5th row서울특별시 금천구 가산동 ***번지 **호 에이스하이엔드타워*차
ValueCountFrequency (%)
서울특별시 8833
18.5%
금천구 8816
18.5%
가산동 5356
11.2%
5247
11.0%
호 3787
7.9%
번지 3735
7.8%
독산동 1779
 
3.7%
시흥동 1641
 
3.4%
가산 345
 
0.7%
차 281
 
0.6%
Other values (1441) 7944
16.6%
2024-04-06T22:37:34.906882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 45495
18.6%
38956
15.9%
시 10879
 
4.4%
동 9182
 
3.8%
금 8994
 
3.7%
천 8982
 
3.7%
서 8930
 
3.7%
울 8891
 
3.6%
구 8846
 
3.6%
별 8837
 
3.6%
Other values (436) 86533
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153020
62.6%
Other Punctuation 45567
 
18.6%
Space Separator 38956
 
15.9%
Dash Punctuation 4554
 
1.9%
Uppercase Letter 1489
 
0.6%
Decimal Number 647
 
0.3%
Lowercase Letter 207
 
0.1%
Open Punctuation 36
 
< 0.1%
Close Punctuation 35
 
< 0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10879
 
7.1%
동 9182
 
6.0%
금 8994
 
5.9%
천 8982
 
5.9%
서 8930
 
5.8%
울 8891
 
5.8%
구 8846
 
5.8%
별 8837
 
5.8%
특 8833
 
5.8%
산 8691
 
5.7%
Other values (370) 61955
40.5%
Uppercase Letter
ValueCountFrequency (%)
T 364
24.4%
I 333
22.4%
S 105
 
7.1%
B 103
 
6.9%
K 88
 
5.9%
C 67
 
4.5%
A 66
 
4.4%
G 51
 
3.4%
H 47
 
3.2%
Y 44
 
3.0%
Other values (13) 221
14.8%
Lowercase Letter
ValueCountFrequency (%)
e 55
26.6%
r 21
 
10.1%
t 16
 
7.7%
o 15
 
7.2%
b 13
 
6.3%
w 11
 
5.3%
u 11
 
5.3%
a 10
 
4.8%
s 10
 
4.8%
c 9
 
4.3%
Other values (10) 36
17.4%
Decimal Number
ValueCountFrequency (%)
1 131
20.2%
3 83
12.8%
5 77
11.9%
0 72
11.1%
4 58
9.0%
6 55
8.5%
2 55
8.5%
7 48
 
7.4%
8 37
 
5.7%
9 31
 
4.8%
Other Punctuation
ValueCountFrequency (%)
* 45495
99.8%
, 36
 
0.1%
@ 15
 
< 0.1%
/ 12
 
< 0.1%
. 8
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
38956
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153020
62.6%
Common 89806
36.7%
Latin 1699
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10879
 
7.1%
동 9182
 
6.0%
금 8994
 
5.9%
천 8982
 
5.9%
서 8930
 
5.8%
울 8891
 
5.8%
구 8846
 
5.8%
별 8837
 
5.8%
특 8833
 
5.8%
산 8691
 
5.7%
Other values (370) 61955
40.5%
Latin
ValueCountFrequency (%)
T 364
21.4%
I 333
19.6%
S 105
 
6.2%
B 103
 
6.1%
K 88
 
5.2%
C 67
 
3.9%
A 66
 
3.9%
e 55
 
3.2%
G 51
 
3.0%
H 47
 
2.8%
Other values (35) 420
24.7%
Common
ValueCountFrequency (%)
* 45495
50.7%
38956
43.4%
- 4554
 
5.1%
1 131
 
0.1%
3 83
 
0.1%
5 77
 
0.1%
0 72
 
0.1%
4 58
 
0.1%
6 55
 
0.1%
2 55
 
0.1%
Other values (11) 270
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 153020
62.6%
ASCII 91502
37.4%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 45495
49.7%
38956
42.6%
- 4554
 
5.0%
T 364
 
0.4%
I 333
 
0.4%
1 131
 
0.1%
S 105
 
0.1%
B 103
 
0.1%
K 88
 
0.1%
3 83
 
0.1%
Other values (54) 1290
 
1.4%
Hangul
ValueCountFrequency (%)
시 10879
 
7.1%
동 9182
 
6.0%
금 8994
 
5.9%
천 8982
 
5.9%
서 8930
 
5.8%
울 8891
 
5.8%
구 8846
 
5.8%
별 8837
 
5.8%
특 8833
 
5.8%
산 8691
 
5.7%
Other values (370) 61955
40.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%

도로명주소
Text

MISSING 

Distinct4798
Distinct (%)50.8%
Missing555
Missing (%)5.5%
Memory size156.2 KiB
2024-04-06T22:37:35.178244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length63
Mean length40.868184
Min length18

Characters and Unicode

Total characters386000
Distinct characters488
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3514 ?
Unique (%)37.2%

Sample

1st row서울특별시 금천구 독산로 ***, ***호 (시흥동, 예일 센트럴)
2nd row서울특별시 금천구 가산디지털*로 ***, ****-***호 (가산동, 월드메르디앙*차)
3rd row서울특별시 금천구 가산디지털*로 ***, 에이스 K*타워 ***호 (가산동)
4th row서울특별시 금천구 가산디지털*로 *** (가산동,에이스테크노타워**차 ****호)
5th row서울특별시 금천구 가산디지털*로 ***, 에이스 비즈포레 지식산업센터 **층 ****, ****호 (가산동)
ValueCountFrequency (%)
9615
14.0%
서울특별시 9442
13.8%
금천구 9405
13.7%
호 6875
 
10.0%
가산동 5454
 
7.9%
가산디지털*로 3396
 
4.9%
층 2440
 
3.6%
독산동 1689
 
2.5%
시흥동 1506
 
2.2%
동 1180
 
1.7%
Other values (2211) 17644
25.7%
2024-04-06T22:37:35.600280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 72314
18.7%
59223
 
15.3%
산 14375
 
3.7%
시 12991
 
3.4%
, 11904
 
3.1%
동 11778
 
3.1%
가 10710
 
2.8%
서 10088
 
2.6%
금 9962
 
2.6%
) 9585
 
2.5%
Other values (478) 163070
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216587
56.1%
Other Punctuation 84262
 
21.8%
Space Separator 59223
 
15.3%
Close Punctuation 9585
 
2.5%
Open Punctuation 9584
 
2.5%
Uppercase Letter 2805
 
0.7%
Dash Punctuation 2484
 
0.6%
Decimal Number 1189
 
0.3%
Lowercase Letter 226
 
0.1%
Math Symbol 52
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 14375
 
6.6%
시 12991
 
6.0%
동 11778
 
5.4%
가 10710
 
4.9%
서 10088
 
4.7%
금 9962
 
4.6%
천 9577
 
4.4%
울 9510
 
4.4%
별 9453
 
4.4%
특 9444
 
4.4%
Other values (408) 108699
50.2%
Uppercase Letter
ValueCountFrequency (%)
B 555
19.8%
A 465
16.6%
T 422
15.0%
I 389
13.9%
C 188
 
6.7%
S 141
 
5.0%
K 109
 
3.9%
G 78
 
2.8%
H 66
 
2.4%
Y 66
 
2.4%
Other values (15) 326
11.6%
Lowercase Letter
ValueCountFrequency (%)
e 59
26.1%
r 24
10.6%
t 17
 
7.5%
c 17
 
7.5%
o 16
 
7.1%
w 13
 
5.8%
a 13
 
5.8%
b 12
 
5.3%
u 12
 
5.3%
n 10
 
4.4%
Other values (10) 33
14.6%
Decimal Number
ValueCountFrequency (%)
1 360
30.3%
0 153
12.9%
2 137
 
11.5%
3 94
 
7.9%
6 87
 
7.3%
5 81
 
6.8%
8 76
 
6.4%
7 74
 
6.2%
9 70
 
5.9%
4 57
 
4.8%
Other Punctuation
ValueCountFrequency (%)
* 72314
85.8%
, 11904
 
14.1%
. 19
 
< 0.1%
/ 18
 
< 0.1%
@ 5
 
< 0.1%
& 1
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
33.3%
Ⅱ 1
33.3%
Ⅴ 1
33.3%
Space Separator
ValueCountFrequency (%)
59223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9585
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9584
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2484
100.0%
Math Symbol
ValueCountFrequency (%)
~ 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216587
56.1%
Common 166379
43.1%
Latin 3034
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 14375
 
6.6%
시 12991
 
6.0%
동 11778
 
5.4%
가 10710
 
4.9%
서 10088
 
4.7%
금 9962
 
4.6%
천 9577
 
4.4%
울 9510
 
4.4%
별 9453
 
4.4%
특 9444
 
4.4%
Other values (408) 108699
50.2%
Latin
ValueCountFrequency (%)
B 555
18.3%
A 465
15.3%
T 422
13.9%
I 389
12.8%
C 188
 
6.2%
S 141
 
4.6%
K 109
 
3.6%
G 78
 
2.6%
H 66
 
2.2%
Y 66
 
2.2%
Other values (38) 555
18.3%
Common
ValueCountFrequency (%)
* 72314
43.5%
59223
35.6%
, 11904
 
7.2%
) 9585
 
5.8%
( 9584
 
5.8%
- 2484
 
1.5%
1 360
 
0.2%
0 153
 
0.1%
2 137
 
0.1%
3 94
 
0.1%
Other values (12) 541
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216587
56.1%
ASCII 169410
43.9%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 72314
42.7%
59223
35.0%
, 11904
 
7.0%
) 9585
 
5.7%
( 9584
 
5.7%
- 2484
 
1.5%
B 555
 
0.3%
A 465
 
0.3%
T 422
 
0.2%
I 389
 
0.2%
Other values (57) 2485
 
1.5%
Hangul
ValueCountFrequency (%)
산 14375
 
6.6%
시 12991
 
6.0%
동 11778
 
5.4%
가 10710
 
4.9%
서 10088
 
4.7%
금 9962
 
4.6%
천 9577
 
4.4%
울 9510
 
4.4%
별 9453
 
4.4%
특 9444
 
4.4%
Other values (408) 108699
50.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
33.3%
Ⅱ 1
33.3%
Ⅴ 1
33.3%

도로명우편번호
Text

MISSING 

Distinct274
Distinct (%)3.3%
Missing1587
Missing (%)15.9%
Memory size156.2 KiB
2024-04-06T22:37:35.913033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1500059
Min length5

Characters and Unicode

Total characters43327
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

Unique47 ?
Unique (%)0.6%

Sample

1st row08625
2nd row08505
3rd row08503
4th row08500
5th row08506
ValueCountFrequency (%)
153023 463
 
5.5%
08506 418
 
5.0%
08504 408
 
4.8%
08503 366
 
4.4%
08511 342
 
4.1%
08507 284
 
3.4%
08501 244
 
2.9%
08505 221
 
2.6%
08589 221
 
2.6%
08512 218
 
2.6%
Other values (264) 5228
62.1%
2024-04-06T22:37:36.368073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11210
25.9%
8 8578
19.8%
5 8191
18.9%
1 3937
 
9.1%
3 3264
 
7.5%
6 2461
 
5.7%
2 1752
 
4.0%
9 1524
 
3.5%
4 1395
 
3.2%
7 982
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43294
99.9%
Dash Punctuation 33
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11210
25.9%
8 8578
19.8%
5 8191
18.9%
1 3937
 
9.1%
3 3264
 
7.5%
6 2461
 
5.7%
2 1752
 
4.0%
9 1524
 
3.5%
4 1395
 
3.2%
7 982
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43327
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11210
25.9%
8 8578
19.8%
5 8191
18.9%
1 3937
 
9.1%
3 3264
 
7.5%
6 2461
 
5.7%
2 1752
 
4.0%
9 1524
 
3.5%
4 1395
 
3.2%
7 982
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11210
25.9%
8 8578
19.8%
5 8191
18.9%
1 3937
 
9.1%
3 3264
 
7.5%
6 2461
 
5.7%
2 1752
 
4.0%
9 1524
 
3.5%
4 1395
 
3.2%
7 982
 
2.3%

사업장명
Text

Distinct9868
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T22:37:36.638947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length7.7499
Min length1

Characters and Unicode

Total characters77499
Distinct characters1051
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

Unique9738 ?
Unique (%)97.4%

Sample

1st row제이사이더
2nd row유림코리아
3rd row주식회사 모르제
4th row(주)케아이씨티
5th row주식회사 바름파이버
ValueCountFrequency (%)
주식회사 1989
 
14.4%
유한회사 192
 
1.4%
주 89
 
0.6%
co.,ltd 44
 
0.3%
co 34
 
0.2%
inc 33
 
0.2%
korea 31
 
0.2%
ltd 29
 
0.2%
컴퍼니 27
 
0.2%
company 24
 
0.2%
Other values (10637) 11312
81.9%
2024-04-06T22:37:37.019753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3845
 
5.0%
주 3319
 
4.3%
이 3087
 
4.0%
사 2569
 
3.3%
스 2429
 
3.1%
회 2326
 
3.0%
) 2236
 
2.9%
( 2233
 
2.9%
식 2087
 
2.7%
리 1113
 
1.4%
Other values (1041) 52255
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58967
76.1%
Lowercase Letter 4611
 
5.9%
Uppercase Letter 4341
 
5.6%
Space Separator 3845
 
5.0%
Close Punctuation 2236
 
2.9%
Open Punctuation 2233
 
2.9%
Other Punctuation 471
 
0.6%
Other Symbol 413
 
0.5%
Decimal Number 329
 
0.4%
Dash Punctuation 41
 
0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3319
 
5.6%
이 3087
 
5.2%
사 2569
 
4.4%
스 2429
 
4.1%
회 2326
 
3.9%
식 2087
 
3.5%
리 1113
 
1.9%
아 1077
 
1.8%
에 1054
 
1.8%
트 858
 
1.5%
Other values (960) 39048
66.2%
Lowercase Letter
ValueCountFrequency (%)
o 552
12.0%
e 474
 
10.3%
a 395
 
8.6%
n 384
 
8.3%
i 309
 
6.7%
t 308
 
6.7%
r 257
 
5.6%
l 249
 
5.4%
d 214
 
4.6%
c 192
 
4.2%
Other values (16) 1277
27.7%
Uppercase Letter
ValueCountFrequency (%)
A 317
 
7.3%
O 317
 
7.3%
C 299
 
6.9%
S 290
 
6.7%
E 285
 
6.6%
L 281
 
6.5%
I 262
 
6.0%
N 255
 
5.9%
T 228
 
5.3%
M 198
 
4.6%
Other values (16) 1609
37.1%
Other Punctuation
ValueCountFrequency (%)
. 254
53.9%
, 90
 
19.1%
& 78
 
16.6%
' 15
 
3.2%
/ 11
 
2.3%
? 7
 
1.5%
# 7
 
1.5%
: 5
 
1.1%
! 2
 
0.4%
@ 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 62
18.8%
2 61
18.5%
0 47
14.3%
3 43
13.1%
7 23
 
7.0%
8 21
 
6.4%
6 21
 
6.4%
4 19
 
5.8%
5 17
 
5.2%
9 15
 
4.6%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
3845
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2236
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2233
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 413
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59365
76.6%
Common 9167
 
11.8%
Latin 8952
 
11.6%
Han 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3319
 
5.6%
이 3087
 
5.2%
사 2569
 
4.3%
스 2429
 
4.1%
회 2326
 
3.9%
식 2087
 
3.5%
리 1113
 
1.9%
아 1077
 
1.8%
에 1054
 
1.8%
트 858
 
1.4%
Other values (946) 39446
66.4%
Latin
ValueCountFrequency (%)
o 552
 
6.2%
e 474
 
5.3%
a 395
 
4.4%
n 384
 
4.3%
A 317
 
3.5%
O 317
 
3.5%
i 309
 
3.5%
t 308
 
3.4%
C 299
 
3.3%
S 290
 
3.2%
Other values (42) 5307
59.3%
Common
ValueCountFrequency (%)
3845
41.9%
) 2236
24.4%
( 2233
24.4%
. 254
 
2.8%
, 90
 
1.0%
& 78
 
0.9%
1 62
 
0.7%
2 61
 
0.7%
0 47
 
0.5%
3 43
 
0.5%
Other values (18) 218
 
2.4%
Han
ValueCountFrequency (%)
館 1
 
6.7%
火 1
 
6.7%
中 1
 
6.7%
眞 1
 
6.7%
承 1
 
6.7%
明 1
 
6.7%
宏 1
 
6.7%
發 1
 
6.7%
溶 1
 
6.7%
昌 1
 
6.7%
Other values (5) 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58952
76.1%
ASCII 18119
 
23.4%
None 413
 
0.5%
CJK 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3845
21.2%
) 2236
 
12.3%
( 2233
 
12.3%
o 552
 
3.0%
e 474
 
2.6%
a 395
 
2.2%
n 384
 
2.1%
A 317
 
1.7%
O 317
 
1.7%
i 309
 
1.7%
Other values (70) 7057
38.9%
Hangul
ValueCountFrequency (%)
주 3319
 
5.6%
이 3087
 
5.2%
사 2569
 
4.4%
스 2429
 
4.1%
회 2326
 
3.9%
식 2087
 
3.5%
리 1113
 
1.9%
아 1077
 
1.8%
에 1054
 
1.8%
트 858
 
1.5%
Other values (945) 39033
66.2%
None
ValueCountFrequency (%)
㈜ 413
100.0%
CJK
ValueCountFrequency (%)
館 1
 
6.7%
火 1
 
6.7%
中 1
 
6.7%
眞 1
 
6.7%
承 1
 
6.7%
明 1
 
6.7%
宏 1
 
6.7%
發 1
 
6.7%
溶 1
 
6.7%
昌 1
 
6.7%
Other values (5) 5
33.3%

최종수정일자
Date

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-07-09 16:12:01
Maximum2024-04-04 13:18:27
2024-04-06T22:37:37.140113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:37.278548image/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
7233 
U
2767 

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 7233
72.3%
U 2767
 
27.7%

Length

2024-04-06T22:37:37.389997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:37.474171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7233
72.3%
u 2767
 
27.7%

데이터갱신일자
Date

Distinct1569
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T22:37:37.561308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:37:37.681621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

Distinct650
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T22:37:37.823818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length81
Mean length9.4639
Min length1

Characters and Unicode

Total characters94639
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

Unique424 ?
Unique (%)4.2%

Sample

1st row종합몰
2nd row종합몰
3rd row컴퓨터/사무용품
4th row종합몰
5th row기타
ValueCountFrequency (%)
종합몰 3892
25.5%
의류/패션/잡화/뷰티 3086
20.2%
기타 2575
16.9%
건강/식품 1067
 
7.0%
컴퓨터/사무용품 1039
 
6.8%
교육/도서/완구/오락 963
 
6.3%
가전 795
 
5.2%
가구/수납용품 579
 
3.8%
레져/여행/공연 442
 
2.9%
자동차/자동차용품 431
 
2.8%
Other values (3) 373
 
2.4%
2024-04-06T22:37:38.101331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 16254
 
17.2%
5242
 
5.5%
종 3892
 
4.1%
몰 3892
 
4.1%
합 3892
 
4.1%
품 3379
 
3.6%
잡 3086
 
3.3%
뷰 3086
 
3.3%
화 3086
 
3.3%
티 3086
 
3.3%
Other values (41) 45744
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73033
77.2%
Other Punctuation 16254
 
17.2%
Space Separator 5242
 
5.5%
Dash Punctuation 110
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 3892
 
5.3%
몰 3892
 
5.3%
합 3892
 
5.3%
품 3379
 
4.6%
잡 3086
 
4.2%
뷰 3086
 
4.2%
화 3086
 
4.2%
티 3086
 
4.2%
션 3086
 
4.2%
패 3086
 
4.2%
Other values (38) 39462
54.0%
Other Punctuation
ValueCountFrequency (%)
/ 16254
100.0%
Space Separator
ValueCountFrequency (%)
5242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73033
77.2%
Common 21606
 
22.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 3892
 
5.3%
몰 3892
 
5.3%
합 3892
 
5.3%
품 3379
 
4.6%
잡 3086
 
4.2%
뷰 3086
 
4.2%
화 3086
 
4.2%
티 3086
 
4.2%
션 3086
 
4.2%
패 3086
 
4.2%
Other values (38) 39462
54.0%
Common
ValueCountFrequency (%)
/ 16254
75.2%
5242
 
24.3%
- 110
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73033
77.2%
ASCII 21606
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 16254
75.2%
5242
 
24.3%
- 110
 
0.5%
Hangul
ValueCountFrequency (%)
종 3892
 
5.3%
몰 3892
 
5.3%
합 3892
 
5.3%
품 3379
 
4.6%
잡 3086
 
4.2%
뷰 3086
 
4.2%
화 3086
 
4.2%
티 3086
 
4.2%
션 3086
 
4.2%
패 3086
 
4.2%
Other values (38) 39462
54.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2293
Distinct (%)24.4%
Missing606
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean190212.16
Minimum177868.62
Maximum204072.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:37:38.222407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177868.62
5-th percentile189055.14
Q1189452.38
median189889.94
Q3191026.64
95-th percentile191866.53
Maximum204072.01
Range26203.386
Interquartile range (IQR)1574.2547

Descriptive statistics

Standard deviation1009.5023
Coefficient of variation (CV)0.0053072438
Kurtosis17.128677
Mean190212.16
Median Absolute Deviation (MAD)586.94944
Skewness1.6110052
Sum1.786853 × 109
Variance1019094.9
MonotonicityNot monotonic
2024-04-06T22:37:38.353148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189055.138252216 309
 
3.1%
191226.287379467 264
 
2.6%
189538.020935968 236
 
2.4%
189369.53962474 206
 
2.1%
190694.880295092 156
 
1.6%
189202.600232089 140
 
1.4%
189208.487613747 129
 
1.3%
189877.178943503 113
 
1.1%
189353.050637528 107
 
1.1%
189378.332493727 104
 
1.0%
Other values (2283) 7630
76.3%
(Missing) 606
 
6.1%
ValueCountFrequency (%)
177868.619228729 1
< 0.1%
184649.358818892 1
< 0.1%
185144.0 1
< 0.1%
185732.895750354 1
< 0.1%
185836.76129246 1
< 0.1%
185894.50946257 1
< 0.1%
186950.543605393 1
< 0.1%
187377.105857918 1
< 0.1%
187437.037841856 1
< 0.1%
188814.786669168 1
< 0.1%
ValueCountFrequency (%)
204072.005641837 1
< 0.1%
202929.726170786 1
< 0.1%
202731.25 1
< 0.1%
202245.377899369 1
< 0.1%
201780.083428886 1
< 0.1%
201646.385389914 1
< 0.1%
198083.675293253 1
< 0.1%
197802.054854046 1
< 0.1%
195682.646489277 1
< 0.1%
193793.109 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2290
Distinct (%)24.4%
Missing606
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean441002.08
Minimum387153.79
Maximum469558.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T22:37:38.475519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum387153.79
5-th percentile438410.52
Q1440412.74
median441475.31
Q3441958.33
95-th percentile442460.51
Maximum469558.22
Range82404.43
Interquartile range (IQR)1545.5966

Descriptive statistics

Standard deviation1468.6565
Coefficient of variation (CV)0.0033302711
Kurtosis212.40687
Mean441002.08
Median Absolute Deviation (MAD)618.33379
Skewness-5.1339695
Sum4.1427735 × 109
Variance2156951.9
MonotonicityNot monotonic
2024-04-06T22:37:38.580956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
441958.334400683 309
 
3.1%
437914.06299827 264
 
2.6%
441982.427934953 236
 
2.4%
441629.361414684 206
 
2.1%
440764.426277932 156
 
1.6%
441848.24299943 140
 
1.4%
442298.784420302 129
 
1.3%
442093.648596802 113
 
1.1%
442493.020182986 107
 
1.1%
442066.99866487 104
 
1.0%
Other values (2280) 7630
76.3%
(Missing) 606
 
6.1%
ValueCountFrequency (%)
387153.793172041 1
< 0.1%
421212.115511387 1
< 0.1%
431618.747992263 1
< 0.1%
436896.40836276 1
< 0.1%
436897.466167682 1
< 0.1%
436903.240679787 1
< 0.1%
436912.838835957 1
< 0.1%
436946.60407049 1
< 0.1%
436951.627619366 2
< 0.1%
436962.340703645 1
< 0.1%
ValueCountFrequency (%)
469558.223430873 1
< 0.1%
453831.497778732 1
< 0.1%
452956.947115296 1
< 0.1%
451570.248347401 1
< 0.1%
450938.0 1
< 0.1%
450780.850333333 1
< 0.1%
450644.919295783 1
< 0.1%
447611.552045596 1
< 0.1%
447380.297316673 1
< 0.1%
446919.002226231 1
< 0.1%

자산규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9431 
0
 
569

Length

Max length4
Median length4
Mean length3.8293
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9431
94.3%
0 569
 
5.7%

Length

2024-04-06T22:37:38.688691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:38.767174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9431
94.3%
0 569
 
5.7%

부채총액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9431 
0
 
569

Length

Max length4
Median length4
Mean length3.8293
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9431
94.3%
0 569
 
5.7%

Length

2024-04-06T22:37:38.850238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:38.932093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9431
94.3%
0 569
 
5.7%

자본금
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9431 
0
 
569

Length

Max length4
Median length4
Mean length3.8293
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9431
94.3%
0 569
 
5.7%

Length

2024-04-06T22:37:39.015594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:37:39.096299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9431
94.3%
0 569
 
5.7%

판매방식명
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5090 
인터넷
4441 
인터넷, 기타
 
136
기타
 
106
TV홈쇼핑, 인터넷
 
44
Other values (21)
 
183

Length

Max length26
Median length4
Mean length3.8257
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5090
50.9%
인터넷 4441
44.4%
인터넷, 기타 136
 
1.4%
기타 106
 
1.1%
TV홈쇼핑, 인터넷 44
 
0.4%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지, 기타 39
 
0.4%
인터넷, 카다로그 27
 
0.3%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지 19
 
0.2%
인터넷, 카다로그, 기타 18
 
0.2%
인터넷, 카다로그, 신문잡지 12
 
0.1%
Other values (16) 68
 
0.7%

Length

2024-04-06T22:37:39.182269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5090
48.1%
인터넷 4783
45.2%
기타 331
 
3.1%
카다로그 147
 
1.4%
tv홈쇼핑 144
 
1.4%
신문잡지 98
 
0.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
126273170000201931701903020005920190110<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2100-5831<NA><NA>서울특별시 금천구 시흥동 ***번지 *호 예일 센트럴서울특별시 금천구 독산로 ***, ***호 (시흥동, 예일 센트럴)08625제이사이더2019-01-10 18:03:38I2019-01-12 02:20:46.0종합몰191551.821908439405.220463<NA><NA><NA>인터넷
88623170000201631701743020033020160325<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-7703-0555<NA><NA><NA>서울특별시 금천구 가산디지털*로 ***, ****-***호 (가산동, 월드메르디앙*차)08505유림코리아2016-03-28 16:53:09I2018-08-31 23:59:59.0종합몰189202.600232441848.242999<NA><NA><NA>기타
202213170000202231702353020023820220201<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 ***-** 에이스 K*타워서울특별시 금천구 가산디지털*로 ***, 에이스 K*타워 ***호 (가산동)08503주식회사 모르제2022-02-01 12:42:14I2022-02-03 00:22:38.0컴퓨터/사무용품189158.740846442283.977343000인터넷
34693170000201031701053020027820081007<NA>3폐업3폐업처리20100414<NA><NA><NA>888-8888<NA>153023서울특별시 금천구 가산동 ***번지 *호 에이스테크노타워**차 ****호서울특별시 금천구 가산디지털*로 *** (가산동,에이스테크노타워**차 ****호)<NA>(주)케아이씨티2010-04-14 15:27:42I2018-08-31 23:59:59.0종합몰189417.708596442309.174988<NA><NA><NA>인터넷
168603170000202031702353020250120201103<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3489-0024<NA><NA>서울특별시 금천구 가산동 ***-** 에이스 비즈포레 지식산업센터서울특별시 금천구 가산디지털*로 ***, 에이스 비즈포레 지식산업센터 **층 ****, ****호 (가산동)08500주식회사 바름파이버2020-11-03 17:35:29I2020-11-05 00:23:23.0기타189065.818335442338.14413<NA><NA><NA>TV홈쇼핑, 인터넷, 기타
128373170000201931701903020030220181109<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-871-6278<NA><NA>서울특별시 금천구 가산동 ***번지 **호 에이스하이엔드타워*차서울특별시 금천구 가산디지털*로 ***, 에이스하이엔드타워*차 ****호 (가산동)08506싸다구2019-02-20 17:42:14I2019-02-22 02:21:29.0종합몰189467.124187441780.005399<NA><NA><NA>인터넷
175333170000202131702353020029320190103<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 ***-**서울특별시 금천구 가산디지털*로 ***, **층 ****호 (가산동)08503디오 코퍼레이션2021-01-28 18:02:14U2021-01-30 02:40:00.0종합몰189158.740846442283.977343<NA><NA><NA>인터넷
64143170000201331701423020094120131128<NA>3폐업3폐업처리20160114<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥대로 **, *동 ***호 (시흥동, 시흥산업용재유통센타)153862유씨코리아(UCKOREA)2016-01-14 17:44:41I2021-12-03 22:02:00.0종합몰 가전 컴퓨터/사무용품 의류/패션/잡화/뷰티 레져/여행/공연191226.287379437914.062998<NA><NA><NA><NA>
92993170000201631701743020084820160803<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 ***번지 **호서울특별시 금천구 시흥대로**길 **-* (시흥동)08624제이카2018-09-18 17:33:25U2018-09-18 23:59:59.0자동차/자동차용품191169.452002439548.810599<NA><NA><NA>인터넷
5843170000200431701053020050520040101<NA>1영업/정상1정상영업<NA><NA><NA><NA>2113- 8463<NA>153023서울특별시 금천구 가산동 **번지 **호 월드메르디앙벤처센타 ***서울특별시 금천구 벚꽃로 *** (가산동,월드메르디앙벤처센타 ***)<NA>이에이치라인(주)2011-06-22 11:38:59I2021-12-03 22:02:00.0가전 기타189788.849464441731.610479<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
23165317000020233170257302004812023-02-20<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 ****-** SD아크로타워서울특별시 금천구 시흥대로***길 *, SD아크로타워 ***호 (독산동)08579팝더태그2023-02-20 09:12:08I2022-12-01 22:02:00.0종합몰190963.721613440700.107645<NA><NA><NA><NA>
203653170000202231702353020038420220218<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 ***-* 롯데블르빌서울특별시 금천구 탑골로**길 *, ***호 (시흥동, 롯데블르빌)08656토라웨일(TORAWHALES)2022-02-18 13:59:08I2022-02-22 00:22:38.0종합몰 가구/수납용품 의류/패션/잡화/뷰티192347.400016438854.391375000인터넷
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11115317000020183170190302000222018-01-08<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 ***-* 가산 센트럴 푸르지오 시티서울특별시 금천구 디지털로**길 **, 가산 센트럴 푸르지오 시티 B동 **층 ****호 (가산동)08516맨디스코리아 주식회사2024-03-04 17:53:48U2023-12-03 00:06:00.0종합몰 의류/패션/잡화/뷰티190278.679729441481.431442<NA><NA><NA><NA>
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76533170000201531701743020025020150224<NA>1영업/정상1정상영업<NA><NA><NA><NA>894-8694<NA>153031서울특별시 금천구 시흥동 ****번지 벽산아파트 ***동 ***호서울특별시 금천구 금하로 ***, ***동 ***호 (시흥동, 벽산아파트)153031넥스트마켓2015-02-24 15:00:02I2018-08-31 23:59:59.0종합몰192754.346193438827.143733<NA><NA><NA>인터넷
39073170000201031701423020016220101108<NA>1영업/정상1정상영업<NA><NA><NA><NA>1599-1718<NA>153023서울특별시 금천구 가산동 ***번지 **호 백상스타타워*차 ****서울특별시 금천구 가산디지털*로 ***, ****호 (가산동)153023(주)인플로우2014-03-05 18:13:47I2018-08-31 23:59:59.0종합몰189092.729913442262.659278<NA><NA><NA>인터넷
155403170000202031702353020107120200515<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 ****번지 벽산아파트서울특별시 금천구 금하로 ***, ***동 ****호 (시흥동, 벽산아파트)08655유리빈2020-05-15 17:59:35I2021-12-03 22:02:00.0교육/도서/완구/오락 의류/패션/잡화/뷰티192754.346193438827.143733<NA><NA><NA><NA>
214533170000202231702353020148020220713<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 **** 벽산아파트서울특별시 금천구 금하로 ***, ***동 ***호 (시흥동, 벽산아파트)08655아워시즌2022-07-13 13:53:32I2021-12-06 23:06:00.0의류/패션/잡화/뷰티192754.346193438827.143733<NA><NA><NA><NA>
170483170000202031702353020270120201127<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 독산동 ***-**서울특별시 금천구 시흥대로***길 **-* (독산동)08546바분코리아(BABOON KOREA)2020-11-27 18:11:56I2020-11-29 00:23:08.0의류/패션/잡화/뷰티191146.309846441095.442929<NA><NA><NA>인터넷, 기타