Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells78766
Missing cells (%)27.2%
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18817/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
자산규모 is highly imbalanced (58.6%)Imbalance
부채총액 is highly imbalanced (58.6%)Imbalance
자본금 is highly imbalanced (58.6%)Imbalance
판매방식명 is highly imbalanced (70.5%)Imbalance
인허가취소일자 has 9700 (97.0%) missing valuesMissing
폐업일자 has 6112 (61.1%) missing valuesMissing
휴업시작일자 has 9943 (99.4%) missing valuesMissing
휴업종료일자 has 9943 (99.4%) missing valuesMissing
재개업일자 has 9983 (99.8%) missing valuesMissing
전화번호 has 5320 (53.2%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 8336 (83.4%) missing valuesMissing
지번주소 has 1843 (18.4%) missing valuesMissing
도로명주소 has 1220 (12.2%) missing valuesMissing
도로명우편번호 has 2466 (24.7%) missing valuesMissing
좌표정보(X) has 1950 (19.5%) missing valuesMissing
좌표정보(Y) has 1950 (19.5%) missing valuesMissing
소재지우편번호 is highly skewed (γ1 = 27.08334744)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 19:49:48.419209
Analysis finished2024-04-29 19:49:50.182226
Duration1.76 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
3150000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 10000
100.0%

Length

2024-04-30T04:49:50.265411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:50.360569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 10000
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0155587 × 1018
Minimum1.996315 × 1018
Maximum2.022315 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:50.454395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996315 × 1018
5-th percentile2.004315 × 1018
Q12.011315 × 1018
median2.017315 × 1018
Q32.020315 × 1018
95-th percentile2.021315 × 1018
Maximum2.022315 × 1018
Range2.600001 × 1016
Interquartile range (IQR)9.0000077 × 1015

Descriptive statistics

Standard deviation5.7520137 × 1015
Coefficient of variation (CV)0.002853806
Kurtosis-0.53178428
Mean2.0155587 × 1018
Median Absolute Deviation (MAD)4.0000021 × 1015
Skewness-0.79389668
Sum-6.7041088 × 1018
Variance3.3085661 × 1031
MonotonicityNot monotonic
2024-04-30T04:49:50.575605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2014315014530200398 1
 
< 0.1%
2003315010030200803 1
 
< 0.1%
2015315016630200066 1
 
< 0.1%
2021315020030202441 1
 
< 0.1%
2022315020030200728 1
 
< 0.1%
2019315020030200201 1
 
< 0.1%
2020315020030203429 1
 
< 0.1%
2011315012330200604 1
 
< 0.1%
2019315020030201405 1
 
< 0.1%
2021315020030200803 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1996315010030200261 1
< 0.1%
1996315010030200294 1
< 0.1%
1997315010030200499 1
< 0.1%
1997315010030200703 1
< 0.1%
1997315010030200795 1
< 0.1%
1997315010030200838 1
< 0.1%
1997315010030201035 1
< 0.1%
1998315010030201558 1
< 0.1%
1999315010030200132 1
< 0.1%
1999315010030201734 1
< 0.1%
ValueCountFrequency (%)
2022315020030201303 1
< 0.1%
2022315020030201300 1
< 0.1%
2022315020030201297 1
< 0.1%
2022315020030201293 1
< 0.1%
2022315020030201288 1
< 0.1%
2022315020030201287 1
< 0.1%
2022315020030201284 1
< 0.1%
2022315020030201280 1
< 0.1%
2022315020030201278 1
< 0.1%
2022315020030201275 1
< 0.1%

인허가일자
Date

Distinct3722
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1996-10-28 00:00:00
Maximum2022-04-21 00:00:00
2024-04-30T04:49:50.690847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:50.808587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)4.0%
Missing9700
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean20074667
Minimum20030923
Maximum20200928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:50.916297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030923
5-th percentile20030923
Q120061218
median20070928
Q320100108
95-th percentile20100108
Maximum20200928
Range170005
Interquartile range (IQR)38890

Descriptive statistics

Standard deviation24897.934
Coefficient of variation (CV)0.0012402664
Kurtosis0.93547249
Mean20074667
Median Absolute Deviation (MAD)29180
Skewness-0.026660938
Sum6.0224 × 109
Variance6.199071 × 108
MonotonicityNot monotonic
2024-04-30T04:49:51.030776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20100108 102
 
1.0%
20081215 46
 
0.5%
20041223 41
 
0.4%
20070904 39
 
0.4%
20070124 27
 
0.3%
20030923 26
 
0.3%
20061218 9
 
0.1%
20070928 5
 
0.1%
20041224 2
 
< 0.1%
20051031 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 9700
97.0%
ValueCountFrequency (%)
20030923 26
0.3%
20041223 41
0.4%
20041224 2
 
< 0.1%
20051031 1
 
< 0.1%
20060321 1
 
< 0.1%
20061218 9
 
0.1%
20070124 27
0.3%
20070904 39
0.4%
20070928 5
 
0.1%
20081215 46
0.5%
ValueCountFrequency (%)
20200928 1
 
< 0.1%
20100108 102
1.0%
20081215 46
0.5%
20070928 5
 
0.1%
20070904 39
 
0.4%
20070124 27
 
0.3%
20061218 9
 
0.1%
20060321 1
 
< 0.1%
20051031 1
 
< 0.1%
20041224 2
 
< 0.1%

영업상태코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5030 
3
3235 
4
1027 
5
665 
2
 
43

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5030
50.3%
3 3235
32.4%
4 1027
 
10.3%
5 665
 
6.7%
2 43
 
0.4%

Length

2024-04-30T04:49:51.132571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:51.348126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5030
50.3%
3 3235
32.4%
4 1027
 
10.3%
5 665
 
6.7%
2 43
 
0.4%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
5030 
폐업
3235 
취소/말소/만료/정지/중지
1027 
제외/삭제/전출
665 
휴업
 
43

Length

Max length14
Median length5
Mean length5.1404
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 5030
50.3%
폐업 3235
32.4%
취소/말소/만료/정지/중지 1027
 
10.3%
제외/삭제/전출 665
 
6.7%
휴업 43
 
0.4%

Length

2024-04-30T04:49:51.444742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:51.533431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 5030
50.3%
폐업 3235
32.4%
취소/말소/만료/정지/중지 1027
 
10.3%
제외/삭제/전출 665
 
6.7%
휴업 43
 
0.4%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4432
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:51.621544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7788452
Coefficient of variation (CV)0.72808005
Kurtosis0.65044716
Mean2.4432
Median Absolute Deviation (MAD)0
Skewness1.1796363
Sum24432
Variance3.1642902
MonotonicityNot monotonic
2024-04-30T04:49:51.702353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 5030
50.3%
3 3235
32.4%
7 726
 
7.3%
5 665
 
6.7%
4 301
 
3.0%
2 43
 
0.4%
ValueCountFrequency (%)
1 5030
50.3%
2 43
 
0.4%
3 3235
32.4%
4 301
 
3.0%
5 665
 
6.7%
7 726
 
7.3%
ValueCountFrequency (%)
7 726
 
7.3%
5 665
 
6.7%
4 301
 
3.0%
3 3235
32.4%
2 43
 
0.4%
1 5030
50.3%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
정상영업
5030 
폐업처리
3235 
직권말소
726 
타시군구이관
665 
직권취소
 
301

Length

Max length6
Median length4
Mean length4.133
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 5030
50.3%
폐업처리 3235
32.4%
직권말소 726
 
7.3%
타시군구이관 665
 
6.7%
직권취소 301
 
3.0%
휴업처리 43
 
0.4%

Length

2024-04-30T04:49:51.815215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:51.915501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 5030
50.3%
폐업처리 3235
32.4%
직권말소 726
 
7.3%
타시군구이관 665
 
6.7%
직권취소 301
 
3.0%
휴업처리 43
 
0.4%

폐업일자
Date

MISSING 

Distinct2312
Distinct (%)59.5%
Missing6112
Missing (%)61.1%
Memory size156.2 KiB
Minimum1998-01-20 00:00:00
Maximum2024-10-04 00:00:00
2024-04-30T04:49:52.026630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:52.134037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct54
Distinct (%)94.7%
Missing9943
Missing (%)99.4%
Memory size156.2 KiB
Minimum2007-11-15 00:00:00
Maximum2024-02-29 00:00:00
2024-04-30T04:49:52.246052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:52.378550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct44
Distinct (%)77.2%
Missing9943
Missing (%)99.4%
Memory size156.2 KiB
Minimum2008-05-14 00:00:00
Maximum2080-12-31 00:00:00
2024-04-30T04:49:52.481704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:52.596642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

재개업일자
Date

MISSING 

Distinct17
Distinct (%)100.0%
Missing9983
Missing (%)99.8%
Memory size156.2 KiB
Minimum2007-09-07 00:00:00
Maximum2024-04-17 00:00:00
2024-04-30T04:49:52.725764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:52.823555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

전화번호
Text

MISSING 

Distinct4470
Distinct (%)95.5%
Missing5320
Missing (%)53.2%
Memory size156.2 KiB
2024-04-30T04:49:53.053552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length12.182265
Min length1

Characters and Unicode

Total characters57013
Distinct characters18
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4399 ?
Unique (%)94.0%

Sample

1st row0505-440-8888
2nd row02 2690 9575
3rd row02 2664 6846
4th row02-6956-0006
5th row02-3664-8080
ValueCountFrequency (%)
02 1938
 
21.6%
259
 
2.9%
070 185
 
2.1%
3663 76
 
0.8%
3661 64
 
0.7%
3665 63
 
0.7%
3664 55
 
0.6%
2658 50
 
0.6%
2661 50
 
0.6%
2666 49
 
0.5%
Other values (4651) 6174
68.9%
2024-04-30T04:49:53.410475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8848
15.5%
2 8363
14.7%
6 6451
11.3%
6250
11.0%
- 5042
8.8%
7 3796
6.7%
3 3345
 
5.9%
5 3125
 
5.5%
8 3027
 
5.3%
1 2993
 
5.2%
Other values (8) 5773
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45651
80.1%
Space Separator 6250
 
11.0%
Dash Punctuation 5042
 
8.8%
Close Punctuation 37
 
0.1%
Other Punctuation 17
 
< 0.1%
Math Symbol 16
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8848
19.4%
2 8363
18.3%
6 6451
14.1%
7 3796
8.3%
3 3345
 
7.3%
5 3125
 
6.8%
8 3027
 
6.6%
1 2993
 
6.6%
4 2906
 
6.4%
9 2797
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 9
52.9%
, 3
 
17.6%
？ 3
 
17.6%
/ 2
 
11.8%
Space Separator
ValueCountFrequency (%)
6250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5042
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57013
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8848
15.5%
2 8363
14.7%
6 6451
11.3%
6250
11.0%
- 5042
8.8%
7 3796
6.7%
3 3345
 
5.9%
5 3125
 
5.5%
8 3027
 
5.3%
1 2993
 
5.2%
Other values (8) 5773
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57010
> 99.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8848
15.5%
2 8363
14.7%
6 6451
11.3%
6250
11.0%
- 5042
8.8%
7 3796
6.7%
3 3345
 
5.9%
5 3125
 
5.5%
8 3027
 
5.3%
1 2993
 
5.2%
Other values (7) 5770
10.1%
None
ValueCountFrequency (%)
？ 3
100.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

소재지우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct143
Distinct (%)8.6%
Missing8336
Missing (%)83.4%
Infinite0
Infinite (%)0.0%
Mean157449.16
Minimum110070
Maximum421170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:53.538635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110070
5-th percentile157010
Q1157011
median157040
Q3157240
95-th percentile157889
Maximum421170
Range311100
Interquartile range (IQR)229

Descriptive statistics

Standard deviation8998.9437
Coefficient of variation (CV)0.0571546
Kurtosis773.32301
Mean157449.16
Median Absolute Deviation (MAD)30
Skewness27.083347
Sum2.619954 × 108
Variance80980987
MonotonicityNot monotonic
2024-04-30T04:49:53.650073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
157010 391
 
3.9%
157030 160
 
1.6%
157220 108
 
1.1%
157040 92
 
0.9%
157240 82
 
0.8%
157200 74
 
0.7%
157280 52
 
0.5%
157031 37
 
0.4%
157011 35
 
0.4%
157221 34
 
0.3%
Other values (133) 599
 
6.0%
(Missing) 8336
83.4%
ValueCountFrequency (%)
110070 1
 
< 0.1%
110490 1
 
< 0.1%
135080 1
 
< 0.1%
152100 1
 
< 0.1%
157010 391
3.9%
157011 35
 
0.4%
157012 28
 
0.3%
157013 18
 
0.2%
157014 28
 
0.3%
157015 15
 
0.1%
ValueCountFrequency (%)
421170 1
 
< 0.1%
402208 1
 
< 0.1%
158070 1
 
< 0.1%
158050 1
 
< 0.1%
157935 3
< 0.1%
157934 2
 
< 0.1%
157931 3
< 0.1%
157930 1
 
< 0.1%
157928 6
0.1%
157927 1
 
< 0.1%

지번주소
Text

MISSING 

Distinct4080
Distinct (%)50.0%
Missing1843
Missing (%)18.4%
Memory size156.2 KiB
2024-04-30T04:49:53.826847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length27.966287
Min length6

Characters and Unicode

Total characters228121
Distinct characters503
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3246 ?
Unique (%)39.8%

Sample

1st row서울 강서구 화곡동 ***-** ***호
2nd row서울 강서구 공항동 **-** 스카이빌라 가동 ***호
3rd row서울특별시 강서구 마곡동 ***-**
4th row서울특별시 강서구 마곡동 ***번지 *호 이너매스 마곡 ***호
5th row서울특별시 강서구 등촌동 ***번지 *호 에이스테크노타워 ***호
ValueCountFrequency (%)
강서구 8149
17.7%
서울특별시 7013
15.3%
호 5282
11.5%
4215
9.2%
번지 4073
8.9%
화곡동 2865
 
6.2%
마곡동 1533
 
3.3%
등촌동 1146
 
2.5%
서울 1142
 
2.5%
방화동 794
 
1.7%
Other values (2469) 9765
21.2%
2024-04-30T04:49:54.122267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 47087
20.6%
38022
16.7%
서 16543
 
7.3%
동 9190
 
4.0%
강 8436
 
3.7%
울 8214
 
3.6%
구 8183
 
3.6%
시 7217
 
3.2%
별 7014
 
3.1%
특 7013
 
3.1%
Other values (493) 71202
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138023
60.5%
Other Punctuation 47217
 
20.7%
Space Separator 38022
 
16.7%
Dash Punctuation 3677
 
1.6%
Uppercase Letter 461
 
0.2%
Decimal Number 346
 
0.2%
Letter Number 205
 
0.1%
Lowercase Letter 93
 
< 0.1%
Open Punctuation 37
 
< 0.1%
Close Punctuation 37
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 16543
 
12.0%
동 9190
 
6.7%
강 8436
 
6.1%
울 8214
 
6.0%
구 8183
 
5.9%
시 7217
 
5.2%
별 7014
 
5.1%
특 7013
 
5.1%
호 5493
 
4.0%
곡 5170
 
3.7%
Other values (426) 55550
40.2%
Uppercase Letter
ValueCountFrequency (%)
B 137
29.7%
A 82
17.8%
W 29
 
6.3%
M 26
 
5.6%
I 23
 
5.0%
C 20
 
4.3%
P 19
 
4.1%
V 16
 
3.5%
S 16
 
3.5%
D 15
 
3.3%
Other values (13) 78
16.9%
Lowercase Letter
ValueCountFrequency (%)
l 13
14.0%
i 10
10.8%
e 10
10.8%
a 8
8.6%
c 7
 
7.5%
b 7
 
7.5%
o 5
 
5.4%
v 5
 
5.4%
s 5
 
5.4%
k 4
 
4.3%
Other values (7) 19
20.4%
Decimal Number
ValueCountFrequency (%)
1 52
15.0%
7 45
13.0%
2 38
11.0%
3 36
10.4%
0 35
10.1%
6 33
9.5%
8 30
8.7%
9 28
8.1%
5 26
7.5%
4 23
6.6%
Other Punctuation
ValueCountFrequency (%)
* 47087
99.7%
, 74
 
0.2%
@ 39
 
0.1%
/ 9
 
< 0.1%
. 7
 
< 0.1%
# 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 111
54.1%
Ⅰ 80
39.0%
Ⅲ 8
 
3.9%
Ⅳ 6
 
2.9%
Space Separator
ValueCountFrequency (%)
38022
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3677
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138021
60.5%
Common 89339
39.2%
Latin 759
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 16543
 
12.0%
동 9190
 
6.7%
강 8436
 
6.1%
울 8214
 
6.0%
구 8183
 
5.9%
시 7217
 
5.2%
별 7014
 
5.1%
특 7013
 
5.1%
호 5493
 
4.0%
곡 5170
 
3.7%
Other values (424) 55548
40.2%
Latin
ValueCountFrequency (%)
B 137
18.1%
Ⅱ 111
14.6%
A 82
 
10.8%
Ⅰ 80
 
10.5%
W 29
 
3.8%
M 26
 
3.4%
I 23
 
3.0%
C 20
 
2.6%
P 19
 
2.5%
V 16
 
2.1%
Other values (34) 216
28.5%
Common
ValueCountFrequency (%)
* 47087
52.7%
38022
42.6%
- 3677
 
4.1%
, 74
 
0.1%
1 52
 
0.1%
7 45
 
0.1%
@ 39
 
< 0.1%
2 38
 
< 0.1%
( 37
 
< 0.1%
) 37
 
< 0.1%
Other values (13) 231
 
0.3%
Han
ValueCountFrequency (%)
情 1
50.0%
內 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138021
60.5%
ASCII 89891
39.4%
Number Forms 205
 
0.1%
CJK 2
 
< 0.1%
None 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 47087
52.4%
38022
42.3%
- 3677
 
4.1%
B 137
 
0.2%
A 82
 
0.1%
, 74
 
0.1%
1 52
 
0.1%
7 45
 
0.1%
@ 39
 
< 0.1%
2 38
 
< 0.1%
Other values (51) 638
 
0.7%
Hangul
ValueCountFrequency (%)
서 16543
 
12.0%
동 9190
 
6.7%
강 8436
 
6.1%
울 8214
 
6.0%
구 8183
 
5.9%
시 7217
 
5.2%
별 7014
 
5.1%
특 7013
 
5.1%
호 5493
 
4.0%
곡 5170
 
3.7%
Other values (424) 55548
40.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 111
54.1%
Ⅰ 80
39.0%
Ⅲ 8
 
3.9%
Ⅳ 6
 
2.9%
CJK
ValueCountFrequency (%)
情 1
50.0%
內 1
50.0%
None
ValueCountFrequency (%)
Ａ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

도로명주소
Text

MISSING 

Distinct5814
Distinct (%)66.2%
Missing1220
Missing (%)12.2%
Memory size156.2 KiB
2024-04-30T04:49:54.327844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length38.731321
Min length20

Characters and Unicode

Total characters340061
Distinct characters518
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

Unique4606 ?
Unique (%)52.5%

Sample

1st row서울특별시 강서구 곰달래로**길 **, *층 (화곡동)
2nd row서울특별시 강서구 방화대로**나길 * (공항동)
3rd row서울특별시 강서구 곰달래로**길 **, *층 (화곡동)
4th row서울특별시 강서구 마곡중앙*로 **, *층 ***호 (마곡동)
5th row서울특별시 강서구 마곡중앙*로 **, 이너매스 마곡 ***호 (마곡동)
ValueCountFrequency (%)
서울특별시 8778
14.2%
강서구 8770
14.2%
8731
14.1%
호 6455
 
10.4%
화곡동 2733
 
4.4%
층 2434
 
3.9%
동 1775
 
2.9%
마곡동 1619
 
2.6%
등촌동 1080
 
1.7%
방화동 704
 
1.1%
Other values (3230) 18825
30.4%
2024-04-30T04:49:54.658214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 63949
18.8%
53199
 
15.6%
서 19362
 
5.7%
, 12377
 
3.6%
동 11903
 
3.5%
강 10480
 
3.1%
로 9057
 
2.7%
시 9001
 
2.6%
) 8853
 
2.6%
( 8852
 
2.6%
Other values (508) 133028
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 188917
55.6%
Other Punctuation 76360
22.5%
Space Separator 53199
 
15.6%
Close Punctuation 8853
 
2.6%
Open Punctuation 8852
 
2.6%
Dash Punctuation 2041
 
0.6%
Uppercase Letter 956
 
0.3%
Decimal Number 529
 
0.2%
Letter Number 209
 
0.1%
Lowercase Letter 112
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 19362
 
10.2%
동 11903
 
6.3%
강 10480
 
5.5%
로 9057
 
4.8%
시 9001
 
4.8%
울 8845
 
4.7%
구 8793
 
4.7%
별 8781
 
4.6%
특 8778
 
4.6%
곡 7400
 
3.9%
Other values (444) 86517
45.8%
Uppercase Letter
ValueCountFrequency (%)
B 338
35.4%
A 284
29.7%
C 50
 
5.2%
W 29
 
3.0%
I 28
 
2.9%
M 27
 
2.8%
D 26
 
2.7%
S 19
 
2.0%
P 19
 
2.0%
V 18
 
1.9%
Other values (12) 118
 
12.3%
Lowercase Letter
ValueCountFrequency (%)
b 23
20.5%
l 11
9.8%
a 10
8.9%
i 10
8.9%
e 10
8.9%
s 9
 
8.0%
o 7
 
6.2%
v 5
 
4.5%
c 5
 
4.5%
u 4
 
3.6%
Other values (8) 18
16.1%
Decimal Number
ValueCountFrequency (%)
1 135
25.5%
0 79
14.9%
2 56
10.6%
3 55
10.4%
4 42
 
7.9%
5 41
 
7.8%
6 41
 
7.8%
8 34
 
6.4%
7 31
 
5.9%
9 15
 
2.8%
Other Punctuation
ValueCountFrequency (%)
* 63949
83.7%
, 12377
 
16.2%
@ 19
 
< 0.1%
. 10
 
< 0.1%
/ 5
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 112
53.6%
Ⅰ 83
39.7%
Ⅲ 8
 
3.8%
Ⅳ 6
 
2.9%
Space Separator
ValueCountFrequency (%)
53199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8853
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8852
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2041
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 188915
55.6%
Common 149867
44.1%
Latin 1277
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 19362
 
10.2%
동 11903
 
6.3%
강 10480
 
5.5%
로 9057
 
4.8%
시 9001
 
4.8%
울 8845
 
4.7%
구 8793
 
4.7%
별 8781
 
4.6%
특 8778
 
4.6%
곡 7400
 
3.9%
Other values (442) 86515
45.8%
Latin
ValueCountFrequency (%)
B 338
26.5%
A 284
22.2%
Ⅱ 112
 
8.8%
Ⅰ 83
 
6.5%
C 50
 
3.9%
W 29
 
2.3%
I 28
 
2.2%
M 27
 
2.1%
D 26
 
2.0%
b 23
 
1.8%
Other values (34) 277
21.7%
Common
ValueCountFrequency (%)
* 63949
42.7%
53199
35.5%
, 12377
 
8.3%
) 8853
 
5.9%
( 8852
 
5.9%
- 2041
 
1.4%
1 135
 
0.1%
0 79
 
0.1%
2 56
 
< 0.1%
3 55
 
< 0.1%
Other values (10) 271
 
0.2%
Han
ValueCountFrequency (%)
內 1
50.0%
情 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 188915
55.6%
ASCII 150935
44.4%
Number Forms 209
 
0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 63949
42.4%
53199
35.2%
, 12377
 
8.2%
) 8853
 
5.9%
( 8852
 
5.9%
- 2041
 
1.4%
B 338
 
0.2%
A 284
 
0.2%
1 135
 
0.1%
0 79
 
0.1%
Other values (50) 828
 
0.5%
Hangul
ValueCountFrequency (%)
서 19362
 
10.2%
동 11903
 
6.3%
강 10480
 
5.5%
로 9057
 
4.8%
시 9001
 
4.8%
울 8845
 
4.7%
구 8793
 
4.7%
별 8781
 
4.6%
특 8778
 
4.6%
곡 7400
 
3.9%
Other values (442) 86515
45.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 112
53.6%
Ⅰ 83
39.7%
Ⅲ 8
 
3.8%
Ⅳ 6
 
2.9%
CJK
ValueCountFrequency (%)
內 1
50.0%
情 1
50.0%

도로명우편번호
Text

MISSING 

Distinct474
Distinct (%)6.3%
Missing2466
Missing (%)24.7%
Memory size156.2 KiB
2024-04-30T04:49:54.960846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1858243
Min length5

Characters and Unicode

Total characters39070
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

Unique57 ?
Unique (%)0.8%

Sample

1st row157904
2nd row07619
3rd row157880
4th row07807
5th row07801
ValueCountFrequency (%)
07788 306
 
4.1%
157010 225
 
3.0%
07631 218
 
2.9%
07802 205
 
2.7%
07803 183
 
2.4%
07806 131
 
1.7%
07801 120
 
1.6%
07807 104
 
1.4%
157030 77
 
1.0%
07573 72
 
1.0%
Other values (464) 5893
78.2%
2024-04-30T04:49:55.387578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 10868
27.8%
0 8820
22.6%
5 4170
 
10.7%
1 3223
 
8.2%
8 3074
 
7.9%
6 2921
 
7.5%
3 1788
 
4.6%
2 1684
 
4.3%
4 1291
 
3.3%
9 1204
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39043
99.9%
Dash Punctuation 27
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 10868
27.8%
0 8820
22.6%
5 4170
 
10.7%
1 3223
 
8.3%
8 3074
 
7.9%
6 2921
 
7.5%
3 1788
 
4.6%
2 1684
 
4.3%
4 1291
 
3.3%
9 1204
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39070
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 10868
27.8%
0 8820
22.6%
5 4170
 
10.7%
1 3223
 
8.2%
8 3074
 
7.9%
6 2921
 
7.5%
3 1788
 
4.6%
2 1684
 
4.3%
4 1291
 
3.3%
9 1204
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 10868
27.8%
0 8820
22.6%
5 4170
 
10.7%
1 3223
 
8.2%
8 3074
 
7.9%
6 2921
 
7.5%
3 1788
 
4.6%
2 1684
 
4.3%
4 1291
 
3.3%
9 1204
 
3.1%

사업장명
Text

Distinct9855
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T04:49:55.710995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length7.2828
Min length1

Characters and Unicode

Total characters72828
Distinct characters1102
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9718 ?
Unique (%)97.2%

Sample

1st row싸대요닷컴
2nd row마루테크 (Maroo tech)
3rd row호프만 골프
4th rowENFLEX
5th row리즈케이크
ValueCountFrequency (%)
주식회사 986
 
7.5%
주 71
 
0.5%
컴퍼니 34
 
0.3%
company 33
 
0.3%
korea 31
 
0.2%
co 28
 
0.2%
더 25
 
0.2%
co.,ltd 23
 
0.2%
㈜ 22
 
0.2%
ltd 21
 
0.2%
Other values (10980) 11855
90.3%
2024-04-30T04:49:56.172760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3136
 
4.3%
이 2609
 
3.6%
스 2170
 
3.0%
) 2162
 
3.0%
( 2161
 
3.0%
주 1809
 
2.5%
사 1402
 
1.9%
리 1173
 
1.6%
회 1097
 
1.5%
식 1058
 
1.5%
Other values (1092) 54051
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50718
69.6%
Lowercase Letter 7209
 
9.9%
Uppercase Letter 6349
 
8.7%
Space Separator 3136
 
4.3%
Close Punctuation 2163
 
3.0%
Open Punctuation 2162
 
3.0%
Decimal Number 474
 
0.7%
Other Punctuation 430
 
0.6%
Other Symbol 95
 
0.1%
Dash Punctuation 68
 
0.1%
Other values (5) 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2609
 
5.1%
스 2170
 
4.3%
주 1809
 
3.6%
사 1402
 
2.8%
리 1173
 
2.3%
회 1097
 
2.2%
식 1058
 
2.1%
아 955
 
1.9%
에 812
 
1.6%
트 731
 
1.4%
Other values (1005) 36902
72.8%
Lowercase Letter
ValueCountFrequency (%)
e 843
11.7%
o 772
 
10.7%
a 660
 
9.2%
n 533
 
7.4%
i 509
 
7.1%
r 471
 
6.5%
t 423
 
5.9%
l 393
 
5.5%
s 354
 
4.9%
m 290
 
4.0%
Other values (16) 1961
27.2%
Uppercase Letter
ValueCountFrequency (%)
A 479
 
7.5%
O 473
 
7.4%
E 471
 
7.4%
S 425
 
6.7%
N 388
 
6.1%
L 376
 
5.9%
C 370
 
5.8%
I 366
 
5.8%
T 362
 
5.7%
M 321
 
5.1%
Other values (16) 2318
36.5%
Other Punctuation
ValueCountFrequency (%)
. 231
53.7%
& 98
22.8%
, 60
 
14.0%
' 15
 
3.5%
: 7
 
1.6%
# 6
 
1.4%
? 5
 
1.2%
/ 4
 
0.9%
？ 2
 
0.5%
! 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 89
18.8%
1 82
17.3%
0 76
16.0%
3 51
10.8%
4 44
9.3%
5 36
7.6%
9 32
 
6.8%
6 24
 
5.1%
8 21
 
4.4%
7 19
 
4.0%
Close Punctuation
ValueCountFrequency (%)
) 2162
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2161
> 99.9%
[ 1
 
< 0.1%
Modifier Symbol
ValueCountFrequency (%)
` 2
66.7%
´ 1
33.3%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
3136
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50799
69.8%
Latin 13558
 
18.6%
Common 8457
 
11.6%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2609
 
5.1%
스 2170
 
4.3%
주 1809
 
3.6%
사 1402
 
2.8%
리 1173
 
2.3%
회 1097
 
2.2%
식 1058
 
2.1%
아 955
 
1.9%
에 812
 
1.6%
트 731
 
1.4%
Other values (992) 36983
72.8%
Latin
ValueCountFrequency (%)
e 843
 
6.2%
o 772
 
5.7%
a 660
 
4.9%
n 533
 
3.9%
i 509
 
3.8%
A 479
 
3.5%
O 473
 
3.5%
r 471
 
3.5%
E 471
 
3.5%
S 425
 
3.1%
Other values (42) 7922
58.4%
Common
ValueCountFrequency (%)
3136
37.1%
) 2162
25.6%
( 2161
25.6%
. 231
 
2.7%
& 98
 
1.2%
2 89
 
1.1%
1 82
 
1.0%
0 76
 
0.9%
- 68
 
0.8%
, 60
 
0.7%
Other values (24) 294
 
3.5%
Han
ValueCountFrequency (%)
蘭 1
 
7.1%
信 1
 
7.1%
星 1
 
7.1%
美 1
 
7.1%
嬅 1
 
7.1%
人 1
 
7.1%
珠 1
 
7.1%
家 1
 
7.1%
愛 1
 
7.1%
盛 1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50703
69.6%
ASCII 22007
30.2%
None 98
 
0.1%
CJK 14
 
< 0.1%
Punctuation 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3136
 
14.3%
) 2162
 
9.8%
( 2161
 
9.8%
e 843
 
3.8%
o 772
 
3.5%
a 660
 
3.0%
n 533
 
2.4%
i 509
 
2.3%
A 479
 
2.2%
O 473
 
2.1%
Other values (72) 10279
46.7%
Hangul
ValueCountFrequency (%)
이 2609
 
5.1%
스 2170
 
4.3%
주 1809
 
3.6%
사 1402
 
2.8%
리 1173
 
2.3%
회 1097
 
2.2%
식 1058
 
2.1%
아 955
 
1.9%
에 812
 
1.6%
트 731
 
1.4%
Other values (990) 36887
72.8%
None
ValueCountFrequency (%)
㈜ 95
96.9%
？ 2
 
2.0%
´ 1
 
1.0%
Punctuation
ValueCountFrequency (%)
’ 4
80.0%
‘ 1
 
20.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
CJK
ValueCountFrequency (%)
蘭 1
 
7.1%
信 1
 
7.1%
星 1
 
7.1%
美 1
 
7.1%
嬅 1
 
7.1%
人 1
 
7.1%
珠 1
 
7.1%
家 1
 
7.1%
愛 1
 
7.1%
盛 1
 
7.1%
Other values (4) 4
28.6%

최종수정일자
Date

Distinct9474
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-07-25 14:01:25
Maximum2024-04-25 14:31:11
2024-04-30T04:49:56.285831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:56.404818image/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 rowU
3rd rowI
4th rowI
5th rowI

Common Values

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

Length

2024-04-30T04:49:56.508950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:56.592411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7482
74.8%
u 2518
 
25.2%

데이터갱신일자
Date

Distinct1604
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T04:49:56.691684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:49:57.012858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

Distinct582
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-30T04:49:57.158267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length83
Mean length9.5353
Min length1

Characters and Unicode

Total characters95353
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

Unique356 ?
Unique (%)3.6%

Sample

1st row기타
2nd row컴퓨터/사무용품
3rd row레져/여행/공연
4th row-
5th row건강/식품 기타 교육/도서/완구/오락
ValueCountFrequency (%)
의류/패션/잡화/뷰티 3813
25.7%
종합몰 3081
20.8%
기타 2046
13.8%
건강/식품 1168
 
7.9%
883
 
6.0%
교육/도서/완구/오락 852
 
5.7%
컴퓨터/사무용품 728
 
4.9%
가전 648
 
4.4%
가구/수납용품 592
 
4.0%
레져/여행/공연 427
 
2.9%
Other values (3) 587
 
4.0%
2024-04-30T04:49:57.464696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 17820
18.7%
4825
 
5.1%
의 3813
 
4.0%
화 3813
 
4.0%
티 3813
 
4.0%
뷰 3813
 
4.0%
류 3813
 
4.0%
잡 3813
 
4.0%
션 3813
 
4.0%
패 3813
 
4.0%
Other values (41) 42204
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71825
75.3%
Other Punctuation 17820
 
18.7%
Space Separator 4825
 
5.1%
Dash Punctuation 883
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 3813
 
5.3%
화 3813
 
5.3%
티 3813
 
5.3%
뷰 3813
 
5.3%
류 3813
 
5.3%
잡 3813
 
5.3%
션 3813
 
5.3%
패 3813
 
5.3%
종 3081
 
4.3%
합 3081
 
4.3%
Other values (38) 35159
49.0%
Other Punctuation
ValueCountFrequency (%)
/ 17820
100.0%
Space Separator
ValueCountFrequency (%)
4825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 883
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71825
75.3%
Common 23528
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 3813
 
5.3%
화 3813
 
5.3%
티 3813
 
5.3%
뷰 3813
 
5.3%
류 3813
 
5.3%
잡 3813
 
5.3%
션 3813
 
5.3%
패 3813
 
5.3%
종 3081
 
4.3%
합 3081
 
4.3%
Other values (38) 35159
49.0%
Common
ValueCountFrequency (%)
/ 17820
75.7%
4825
 
20.5%
- 883
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71825
75.3%
ASCII 23528
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 17820
75.7%
4825
 
20.5%
- 883
 
3.8%
Hangul
ValueCountFrequency (%)
의 3813
 
5.3%
화 3813
 
5.3%
티 3813
 
5.3%
뷰 3813
 
5.3%
류 3813
 
5.3%
잡 3813
 
5.3%
션 3813
 
5.3%
패 3813
 
5.3%
종 3081
 
4.3%
합 3081
 
4.3%
Other values (38) 35159
49.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4253
Distinct (%)52.8%
Missing1950
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean185983.6
Minimum179428.03
Maximum203276.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:57.582666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179428.03
5-th percentile183246.89
Q1185078
median186156.57
Q3187087.08
95-th percentile188050.37
Maximum203276.33
Range23848.31
Interquartile range (IQR)2009.0789

Descriptive statistics

Standard deviation1529.2658
Coefficient of variation (CV)0.008222584
Kurtosis1.9378569
Mean185983.6
Median Absolute Deviation (MAD)990.05859
Skewness-0.16863786
Sum1.497168 × 109
Variance2338653.8
MonotonicityNot monotonic
2024-04-30T04:49:57.689780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187952.560027898 71
 
0.7%
186899.241516278 46
 
0.5%
186429.327795498 43
 
0.4%
187498.790852032 41
 
0.4%
186501.233192961 39
 
0.4%
185144.0 38
 
0.4%
185365.0 37
 
0.4%
184609.0 34
 
0.3%
185682.405797191 33
 
0.3%
185813.15048215 32
 
0.3%
Other values (4243) 7636
76.4%
(Missing) 1950
 
19.5%
ValueCountFrequency (%)
179428.025441079 2
< 0.1%
179453.408122513 1
< 0.1%
179532.459513003 1
< 0.1%
181644.858152609 1
< 0.1%
181880.787422473 1
< 0.1%
181881.234660314 2
< 0.1%
181925.508884437 1
< 0.1%
181936.092158088 1
< 0.1%
181987.838464305 1
< 0.1%
182019.210724441 1
< 0.1%
ValueCountFrequency (%)
203276.335 1
 
< 0.1%
197559.791065754 1
 
< 0.1%
192117.929167614 1
 
< 0.1%
189200.147733153 1
 
< 0.1%
189152.269637156 1
 
< 0.1%
189145.455894355 5
0.1%
189124.441211963 3
< 0.1%
189117.188848082 5
0.1%
189111.978786699 1
 
< 0.1%
189105.943058741 3
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4242
Distinct (%)52.7%
Missing1950
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean450018.58
Minimum443624.71
Maximum454021.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-30T04:49:57.801383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443624.71
5-th percentile447564.19
Q1448724.14
median450206.3
Q3451093.02
95-th percentile452292.81
Maximum454021.74
Range10397.03
Interquartile range (IQR)2368.8849

Descriptive statistics

Standard deviation1501.2599
Coefficient of variation (CV)0.0033359953
Kurtosis-0.8964985
Mean450018.58
Median Absolute Deviation (MAD)1123.8696
Skewness-0.12192176
Sum3.6226496 × 109
Variance2253781.2
MonotonicityNot monotonic
2024-04-30T04:49:57.927300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450562.020225978 71
 
0.7%
451093.022236256 46
 
0.5%
452034.27568352 43
 
0.4%
451226.066675277 41
 
0.4%
451485.251875922 39
 
0.4%
450938.0 39
 
0.4%
450789.0 37
 
0.4%
451839.0 34
 
0.3%
449689.106346042 33
 
0.3%
450434.088151226 32
 
0.3%
Other values (4232) 7635
76.3%
(Missing) 1950
 
19.5%
ValueCountFrequency (%)
443624.71 1
< 0.1%
443879.445960006 1
< 0.1%
446780.464037958 1
< 0.1%
447209.706639763 1
< 0.1%
447215.959475895 1
< 0.1%
447217.02586517 2
< 0.1%
447247.830982963 1
< 0.1%
447251.285621949 1
< 0.1%
447254.481538112 1
< 0.1%
447259.998758451 1
< 0.1%
ValueCountFrequency (%)
454021.739716432 1
< 0.1%
453985.638659523 1
< 0.1%
453942.332030606 1
< 0.1%
453888.720258506 1
< 0.1%
453853.986886879 1
< 0.1%
453830.690961043 1
< 0.1%
453794.949921909 1
< 0.1%
453667.289537405 1
< 0.1%
453663.10723513 1
< 0.1%
453644.164512267 1
< 0.1%

자산규모
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9167 
0
 
833

Length

Max length4
Median length4
Mean length3.7501
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> 9167
91.7%
0 833
 
8.3%

Length

2024-04-30T04:49:58.027841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:58.108700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9167
91.7%
0 833
 
8.3%

부채총액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9167 
0
 
833

Length

Max length4
Median length4
Mean length3.7501
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> 9167
91.7%
0 833
 
8.3%

Length

2024-04-30T04:49:58.209684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:58.287830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9167
91.7%
0 833
 
8.3%

자본금
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9167 
0
 
833

Length

Max length4
Median length4
Mean length3.7501
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> 9167
91.7%
0 833
 
8.3%

Length

2024-04-30T04:49:58.373169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:49:58.464635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9167
91.7%
0 833
 
8.3%

판매방식명
Categorical

IMBALANCE 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인터넷
5465 
<NA>
4035 
인터넷, 기타
 
168
기타
 
68
TV홈쇼핑, 인터넷
 
68
Other values (21)
 
196

Length

Max length26
Median length3
Mean length3.7498
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷 5465
54.6%
<NA> 4035
40.4%
인터넷, 기타 168
 
1.7%
기타 68
 
0.7%
TV홈쇼핑, 인터넷 68
 
0.7%
TV홈쇼핑, 인터넷, 카다로그, 신문잡지, 기타 41
 
0.4%
TV홈쇼핑 27
 
0.3%
인터넷, 카다로그 24
 
0.2%
인터넷, 카다로그, 기타 16
 
0.2%
TV홈쇼핑, 인터넷, 카다로그 14
 
0.1%
Other values (16) 74
 
0.7%

Length

2024-04-30T04:49:58.564596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인터넷 5854
55.0%
na 4035
37.9%
기타 331
 
3.1%
tv홈쇼핑 186
 
1.7%
카다로그 138
 
1.3%
신문잡지 94
 
0.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
98823150000201431501453020039820090309<NA>1영업/정상1정상영업<NA><NA><NA><NA>0505-440-8888<NA><NA><NA>서울특별시 강서구 곰달래로**길 **, *층 (화곡동)157904싸대요닷컴2014-04-22 09:29:29I2018-08-31 23:59:59.0기타187134.147214447523.958055<NA><NA><NA>인터넷
120753150000201631501663020042720160420<NA>5제외/삭제/전출5타시군구이관20220407<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화대로**나길 * (공항동)07619마루테크 (Maroo tech)2022-04-07 13:25:18U2021-12-04 00:09:00.0컴퓨터/사무용품183374.742372451251.816291<NA><NA><NA><NA>
13483150000200431501003020114620040214200812154취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 2690 9575<NA><NA>서울 강서구 화곡동 ***-** ***호<NA><NA>호프만 골프2008-12-22 13:22:16I2018-08-31 23:59:59.0레져/여행/공연<NA><NA><NA><NA><NA>인터넷
24403150000200531501003020227720050927<NA>3폐업3폐업처리20070820<NA><NA><NA>02 2664 6846<NA><NA>서울 강서구 공항동 **-** 스카이빌라 가동 ***호<NA><NA>ENFLEX2007-08-20 10:57:38I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>
100303150000201431501453020056920140619<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 곰달래로**길 **, *층 (화곡동)157880리즈케이크2014-06-19 11:18:43I2021-12-03 22:02:00.0건강/식품 기타 교육/도서/완구/오락186574.684213447752.400176<NA><NA><NA><NA>
180183150000201931502003020145520190814<NA>5제외/삭제/전출5타시군구이관20220510<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 ***-**서울특별시 강서구 마곡중앙*로 **, *층 ***호 (마곡동)07807더조은렌탈2022-05-10 15:56:13U2021-12-04 23:02:00.0기타<NA><NA><NA><NA><NA><NA>
203873150000202031502003020150920200427<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6956-0006<NA><NA>서울특별시 강서구 마곡동 ***번지 *호 이너매스 마곡 ***호서울특별시 강서구 마곡중앙*로 **, 이너매스 마곡 ***호 (마곡동)07801주식회사 티앤피퍼스널케어2020-04-28 16:40:56I2020-04-29 00:23:20.0의류/패션/잡화/뷰티<NA><NA><NA><NA><NA>인터넷
71553150000201131501233020061720110630<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3664-8080<NA>157030서울특별시 강서구 등촌동 ***번지 *호 에이스테크노타워 ***호서울특별시 강서구 강서로 ***, ***호 (등촌동,에이스테크노타워)<NA>(주)도고메디칼2014-05-20 17:53:26I2021-12-03 22:02:00.0의류/패션/잡화/뷰티 건강/식품 기타185931.619683451668.023529<NA><NA><NA><NA>
19624315000020203150200302007022019-11-13<NA>5제외/삭제/전출5타시군구이관2023-03-13<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 ***-* 보타닉파크타워*서울특별시 강서구 마곡중앙*로 **, 보타닉파크타워* *층 ***호 (마곡동)07801하다2023-03-13 14:16:57U2022-12-02 23:05:00.0종합몰184805.681473450977.857003<NA><NA><NA><NA>
259903150000202131502003020297620210818<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 **-***서울특별시 강서구 송정로*길 **, ***호 (공항동)07626주식회사 유앤티커머스2021-08-18 15:52:09I2021-12-03 22:02:00.0종합몰 가전 의류/패션/잡화/뷰티183372.33012450692.596757<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
1583150000200131501003020698420010903200309234취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>02 3664 4104<NA><NA>서울 강서구 내발산동 ***-*<NA><NA>테디하우스2008-02-21 00:00:00I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>
254423150000202131502003020240820210623<NA>3폐업3폐업처리20220509<NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 ***-***서울특별시 강서구 강서로**라길 *-**, ***호 (화곡동)07768헤이아로2022-05-11 08:56:49U2021-12-04 23:03:00.0의류/패션/잡화/뷰티185769.137827447855.547637<NA><NA><NA><NA>
253233150000202131502003020228520210611<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 ***-** 양지샤인아파트서울특별시 강서구 강서로*길 **-**, ***호 (화곡동, 양지샤인아파트)07777문바스켓2021-06-11 11:16:49I2021-06-13 00:22:54.0종합몰186324.037191447559.72818<NA><NA><NA>인터넷
80943150000201231501453020049820000704<NA>5제외/삭제/전출5타시군구이관20160707<NA><NA><NA>02-3429-9716<NA>157280서울특별시 강서구 내발산동 ***번지 *호서울특별시 강서구 강서로**길 ** (내발산동)157280(재) 새마을금고복지회2016-07-07 15:32:05I2021-12-03 22:02:00.0종합몰 기타185889.884865450633.386615<NA><NA><NA><NA>
121683150000201631501663020054620160519<NA>3폐업3폐업처리20170421<NA><NA><NA>070-8830-0077<NA><NA><NA>서울특별시 강서구 등촌로**나길 **, ***호 (등촌동, 예림홈타운)07669세진2017-04-21 10:45:15I2018-08-31 23:59:59.0종합몰187685.127766449363.462201<NA><NA><NA>인터넷
82383150000201231501453020066820120716<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 강서로**길 **, A동 ***호 (화곡동,새한아트빌)157922여우야2012-08-01 11:31:04I2018-08-31 23:59:59.0건강/식품185233.883648449015.424876<NA><NA><NA>인터넷
33123150000200731501003020319020070226<NA>3폐업3폐업처리20080531<NA><NA><NA>02 3446 1702<NA><NA>서울 강서구 등촌동 ***-* 인방빌딩 ***<NA><NA>(주)케이워드2008-06-18 18:28:02I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>
34933150000200731501003020338120070509<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA><NA>02 852 8266<NA><NA>서울 강서구 화곡동 ***-* 한백타운 ***<NA><NA>그린온2015-05-13 10:20:42I2021-12-03 22:02:00.0-<NA><NA><NA><NA><NA><NA>
18083150000200431501003020162520041019<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 2659 0928<NA><NA>서울 강서구 가양동 ****-* 대림경동@ ***-***<NA><NA>투칼라화장품2008-11-03 14:51:07I2018-08-31 23:59:59.0종합몰<NA><NA><NA><NA><NA>인터넷
151043150000201831501663020065620180417<NA>1영업/정상1정상영업<NA><NA><NA><NA>1588-6361<NA><NA>서울특별시 강서구 공항동 ****-**서울특별시 강서구 방화대로*길 **, *층 (공항동)07645지엘리빙2020-07-05 14:46:17I2021-12-03 22:02:00.0가구/수납용품 기타183814.20924450328.162579<NA><NA><NA><NA>