Overview

Dataset statistics

Number of variables27
Number of observations31
Missing cells198
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory236.3 B

Variable types

Categorical8
Numeric7
Unsupported4
Text6
DateTime2

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),취급제품명,담배공급업체명
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19895/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (79.4%)Imbalance
휴업종료일자 is highly imbalanced (79.4%)Imbalance
데이터갱신구분 is highly imbalanced (65.5%)Imbalance
인허가취소일자 has 31 (100.0%) missing valuesMissing
폐업일자 has 23 (74.2%) missing valuesMissing
재개업일자 has 31 (100.0%) missing valuesMissing
전화번호 has 8 (25.8%) missing valuesMissing
소재지면적 has 31 (100.0%) missing valuesMissing
소재지우편번호 has 15 (48.4%) missing valuesMissing
지번주소 has 13 (41.9%) missing valuesMissing
도로명우편번호 has 15 (48.4%) missing valuesMissing
업태구분명 has 31 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
도로명주소 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 12:24:53.737123
Analysis finished2024-04-06 12:24:54.587632
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
3180000
31 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 31
100.0%

Length

2024-04-06T21:24:54.710929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:54.883523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 31
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0116083 × 1018
Minimum2.002318 × 1018
Maximum2.022318 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:24:55.154516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002318 × 1018
5-th percentile2.005318 × 1018
Q12.008318 × 1018
median2.011318 × 1018
Q32.014818 × 1018
95-th percentile2.015818 × 1018
Maximum2.022318 × 1018
Range2.0000012 × 1016
Interquartile range (IQR)6.5000046 × 1015

Descriptive statistics

Standard deviation4.2284266 × 1015
Coefficient of variation (CV)0.0021020129
Kurtosis0.10900588
Mean2.0116083 × 1018
Median Absolute Deviation (MAD)3.0000046 × 1015
Skewness0.052347111
Sum7.0196262 × 1018
Variance1.7879592 × 1031
MonotonicityStrictly increasing
2024-04-06T21:24:55.423589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2002318011715500001 1
 
3.2%
2005318011715500001 1
 
3.2%
2022318023915500001 1
 
3.2%
2016318016315500001 1
 
3.2%
2015318016315500006 1
 
3.2%
2015318016315500005 1
 
3.2%
2015318016315500004 1
 
3.2%
2015318016315500003 1
 
3.2%
2015318016315500002 1
 
3.2%
2015318016315500001 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
2002318011715500001 1
3.2%
2005318011715500001 1
3.2%
2005318011715500002 1
3.2%
2007318011715500001 1
3.2%
2007318011715500002 1
3.2%
2008318011715500001 1
3.2%
2008318011715500002 1
3.2%
2008318011715500003 1
3.2%
2008318011715500004 1
3.2%
2009318011715500001 1
3.2%
ValueCountFrequency (%)
2022318023915500001 1
3.2%
2016318016315500001 1
3.2%
2015318016315500006 1
3.2%
2015318016315500005 1
3.2%
2015318016315500004 1
3.2%
2015318016315500003 1
3.2%
2015318016315500002 1
3.2%
2015318016315500001 1
3.2%
2014318016315500006 1
3.2%
2014318016315500005 1
3.2%

인허가일자
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20113625
Minimum20020528
Maximum20220214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:24:55.675339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020528
5-th percentile20050718
Q120080610
median20111011
Q320145710
95-th percentile20155915
Maximum20220214
Range199686
Interquartile range (IQR)65099.5

Descriptive statistics

Standard deviation42225.605
Coefficient of variation (CV)0.0020993533
Kurtosis0.10138729
Mean20113625
Median Absolute Deviation (MAD)30505
Skewness0.042644402
Sum6.2352237 × 108
Variance1.7830017 × 109
MonotonicityStrictly increasing
2024-04-06T21:24:55.925389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20020528 1
 
3.2%
20050707 1
 
3.2%
20220214 1
 
3.2%
20160628 1
 
3.2%
20151202 1
 
3.2%
20151002 1
 
3.2%
20150708 1
 
3.2%
20150508 1
 
3.2%
20150422 1
 
3.2%
20150205 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
20020528 1
3.2%
20050707 1
3.2%
20050728 1
3.2%
20071206 1
3.2%
20071220 1
3.2%
20080204 1
3.2%
20080317 1
3.2%
20080506 1
3.2%
20080715 1
3.2%
20090701 1
3.2%
ValueCountFrequency (%)
20220214 1
3.2%
20160628 1
3.2%
20151202 1
3.2%
20151002 1
3.2%
20150708 1
3.2%
20150508 1
3.2%
20150422 1
3.2%
20150205 1
3.2%
20141215 1
3.2%
20141204 1
3.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
23 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 23
74.2%
3 8
 
25.8%

Length

2024-04-06T21:24:56.184169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:56.407151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23
74.2%
3 8
 
25.8%

영업상태명
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업/정상
23 
폐업
8 

Length

Max length5
Median length5
Mean length4.2258065
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 23
74.2%
폐업 8
 
25.8%

Length

2024-04-06T21:24:56.636012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:56.842732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 23
74.2%
폐업 8
 
25.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
23 
3
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 23
74.2%
3 8
 
25.8%

Length

2024-04-06T21:24:57.028234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:57.236398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23
74.2%
3 8
 
25.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
정상영업
23 
폐업처리
8 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 23
74.2%
폐업처리 8
 
25.8%

Length

2024-04-06T21:24:57.421085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:57.615871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 23
74.2%
폐업처리 8
 
25.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing23
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean20142792
Minimum20100209
Maximum20200828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:24:57.949652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100209
5-th percentile20103680
Q120117614
median20135257
Q320170200
95-th percentile20190188
Maximum20200828
Range100619
Interquartile range (IQR)52585.75

Descriptive statistics

Standard deviation35525.521
Coefficient of variation (CV)0.001763684
Kurtosis-1.1468409
Mean20142792
Median Absolute Deviation (MAD)29999
Skewness0.43454741
Sum1.6114234 × 108
Variance1.2620626 × 109
MonotonicityNot monotonic
2024-04-06T21:24:58.221936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20170124 1
 
3.2%
20100209 1
 
3.2%
20120305 1
 
3.2%
20110126 1
 
3.2%
20120110 1
 
3.2%
20200828 1
 
3.2%
20150209 1
 
3.2%
20170427 1
 
3.2%
(Missing) 23
74.2%
ValueCountFrequency (%)
20100209 1
3.2%
20110126 1
3.2%
20120110 1
3.2%
20120305 1
3.2%
20150209 1
3.2%
20170124 1
3.2%
20170427 1
3.2%
20200828 1
3.2%
ValueCountFrequency (%)
20200828 1
3.2%
20170427 1
3.2%
20170124 1
3.2%
20150209 1
3.2%
20120305 1
3.2%
20120110 1
3.2%
20110126 1
3.2%
20100209 1
3.2%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
30 
20081029
 
1

Length

Max length8
Median length4
Mean length4.1290323
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row20081029
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
96.8%
20081029 1
 
3.2%

Length

2024-04-06T21:24:58.490996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:58.718419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
96.8%
20081029 1
 
3.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
30 
20081229
 
1

Length

Max length8
Median length4
Mean length4.1290323
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row20081229
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
96.8%
20081229 1
 
3.2%

Length

2024-04-06T21:24:58.947870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:24:59.187967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
96.8%
20081229 1
 
3.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

전화번호
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing8
Missing (%)25.8%
Memory size380.0 B
2024-04-06T21:24:59.517674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.8695652
Min length7

Characters and Unicode

Total characters227
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

Unique23 ?
Unique (%)100.0%

Sample

1st row2006-2077
2nd row3164-7222
3rd row785-8401
4th row3667-3627
5th row953-5000
ValueCountFrequency (%)
3164-7222 1
 
4.3%
02-2069-0382 1
 
4.3%
02-566-8888 1
 
4.3%
02-780-0034 1
 
4.3%
02-833-9982 1
 
4.3%
02-2068-4702 1
 
4.3%
070-4633-3566 1
 
4.3%
02-3667-1900 1
 
4.3%
3350900 1
 
4.3%
02-761-8980 1
 
4.3%
Other values (13) 13
56.5%
2024-04-06T21:25:00.263206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
17.6%
- 32
14.1%
2 25
11.0%
7 24
10.6%
6 22
9.7%
8 22
9.7%
3 20
8.8%
4 13
 
5.7%
5 10
 
4.4%
9 10
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
85.9%
Dash Punctuation 32
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
20.5%
2 25
12.8%
7 24
12.3%
6 22
11.3%
8 22
11.3%
3 20
10.3%
4 13
 
6.7%
5 10
 
5.1%
9 10
 
5.1%
1 9
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
17.6%
- 32
14.1%
2 25
11.0%
7 24
10.6%
6 22
9.7%
8 22
9.7%
3 20
8.8%
4 13
 
5.7%
5 10
 
4.4%
9 10
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
17.6%
- 32
14.1%
2 25
11.0%
7 24
10.6%
6 22
9.7%
8 22
9.7%
3 20
8.8%
4 13
 
5.7%
5 10
 
4.4%
9 10
 
4.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)62.5%
Missing15
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean150198.75
Minimum150010
Maximum150874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:25:01.066509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150010
5-th percentile150010
Q1150010
median150065.5
Q3150103
95-th percentile150844.75
Maximum150874
Range864
Interquartile range (IQR)93

Descriptive statistics

Standard deviation321.56544
Coefficient of variation (CV)0.0021409329
Kurtosis1.2085044
Mean150198.75
Median Absolute Deviation (MAD)46.5
Skewness1.7222148
Sum2403180
Variance103404.33
MonotonicityNot monotonic
2024-04-06T21:25:01.398468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
150010 5
 
16.1%
150103 2
 
6.5%
150038 2
 
6.5%
150096 1
 
3.2%
150095 1
 
3.2%
150037 1
 
3.2%
150093 1
 
3.2%
150874 1
 
3.2%
150818 1
 
3.2%
150835 1
 
3.2%
(Missing) 15
48.4%
ValueCountFrequency (%)
150010 5
16.1%
150037 1
 
3.2%
150038 2
 
6.5%
150093 1
 
3.2%
150095 1
 
3.2%
150096 1
 
3.2%
150103 2
 
6.5%
150818 1
 
3.2%
150835 1
 
3.2%
150874 1
 
3.2%
ValueCountFrequency (%)
150874 1
 
3.2%
150835 1
 
3.2%
150818 1
 
3.2%
150103 2
 
6.5%
150096 1
 
3.2%
150095 1
 
3.2%
150093 1
 
3.2%
150038 2
 
6.5%
150037 1
 
3.2%
150010 5
16.1%

지번주소
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing13
Missing (%)41.9%
Memory size380.0 B
2024-04-06T21:25:01.919120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length32.5
Mean length30.388889
Min length20

Characters and Unicode

Total characters547
Distinct characters69
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

Unique18 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 문래동6가 10번지
2nd row서울특별시 영등포구 문래동5가 9번지
3rd row서울특별시 영등포구 여의도동 44번지 24호 호성빌딩1102호
4th row서울특별시 영등포구 영등포동7가 44번지 1호 303호
5th row서울특별시 영등포구 여의도동 60번지 63빌딩 51층
ValueCountFrequency (%)
서울특별시 18
 
17.0%
영등포구 18
 
17.0%
여의도동 7
 
6.6%
44번지 3
 
2.8%
1호 3
 
2.8%
5호 2
 
1.9%
영등포동8가 2
 
1.9%
1층 2
 
1.9%
문래동3가 2
 
1.9%
양평동3가 2
 
1.9%
Other values (46) 47
44.3%
2024-04-06T21:25:02.709078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
16.3%
1 23
 
4.2%
호 22
 
4.0%
영 21
 
3.8%
포 21
 
3.8%
등 21
 
3.8%
서 19
 
3.5%
시 18
 
3.3%
별 18
 
3.3%
구 18
 
3.3%
Other values (59) 277
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
64.2%
Decimal Number 103
 
18.8%
Space Separator 89
 
16.3%
Dash Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 22
 
6.3%
영 21
 
6.0%
포 21
 
6.0%
등 21
 
6.0%
서 19
 
5.4%
시 18
 
5.1%
별 18
 
5.1%
구 18
 
5.1%
동 18
 
5.1%
특 18
 
5.1%
Other values (44) 157
44.7%
Decimal Number
ValueCountFrequency (%)
1 23
22.3%
3 14
13.6%
4 13
12.6%
5 11
10.7%
0 11
10.7%
6 10
9.7%
8 7
 
6.8%
2 6
 
5.8%
7 4
 
3.9%
9 4
 
3.9%
Space Separator
ValueCountFrequency (%)
89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
64.2%
Common 196
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 22
 
6.3%
영 21
 
6.0%
포 21
 
6.0%
등 21
 
6.0%
서 19
 
5.4%
시 18
 
5.1%
별 18
 
5.1%
구 18
 
5.1%
동 18
 
5.1%
특 18
 
5.1%
Other values (44) 157
44.7%
Common
ValueCountFrequency (%)
89
45.4%
1 23
 
11.7%
3 14
 
7.1%
4 13
 
6.6%
5 11
 
5.6%
0 11
 
5.6%
6 10
 
5.1%
8 7
 
3.6%
2 6
 
3.1%
7 4
 
2.0%
Other values (5) 8
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
64.2%
ASCII 196
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
45.4%
1 23
 
11.7%
3 14
 
7.1%
4 13
 
6.6%
5 11
 
5.6%
0 11
 
5.6%
6 10
 
5.1%
8 7
 
3.6%
2 6
 
3.1%
7 4
 
2.0%
Other values (5) 8
 
4.1%
Hangul
ValueCountFrequency (%)
호 22
 
6.3%
영 21
 
6.0%
포 21
 
6.0%
등 21
 
6.0%
서 19
 
5.4%
시 18
 
5.1%
별 18
 
5.1%
구 18
 
5.1%
동 18
 
5.1%
특 18
 
5.1%
Other values (44) 157
44.7%

도로명주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-06T21:25:03.249106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length35.580645
Min length25

Characters and Unicode

Total characters1103
Distinct characters99
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 선유로 75 (문래동6가)
2nd row서울특별시 영등포구 경인로71길 70 (문래동5가)
3rd row서울특별시 영등포구 여의대방로65길 20 (여의도동,호성빌딩1102호)
4th row서울특별시 영등포구 영중로 77 (영등포동7가,303호)
5th row서울특별시 영등포구 63로 50 (여의도동,63빌딩 51층)
ValueCountFrequency (%)
서울특별시 31
 
16.5%
영등포구 31
 
16.5%
선유로 4
 
2.1%
여의도동 4
 
2.1%
1층 3
 
1.6%
국회대로 3
 
1.6%
영중로 3
 
1.6%
63로 2
 
1.1%
5층 2
 
1.1%
당산로 2
 
1.1%
Other values (96) 103
54.8%
2024-04-06T21:25:04.132529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
14.2%
영 43
 
3.9%
1 39
 
3.5%
포 38
 
3.4%
등 38
 
3.4%
, 35
 
3.2%
서 35
 
3.2%
로 32
 
2.9%
( 32
 
2.9%
) 32
 
2.9%
Other values (89) 622
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 650
58.9%
Decimal Number 188
 
17.0%
Space Separator 157
 
14.2%
Other Punctuation 35
 
3.2%
Open Punctuation 32
 
2.9%
Close Punctuation 32
 
2.9%
Uppercase Letter 6
 
0.5%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 43
 
6.6%
포 38
 
5.8%
등 38
 
5.8%
서 35
 
5.4%
로 32
 
4.9%
울 32
 
4.9%
동 31
 
4.8%
별 31
 
4.8%
시 31
 
4.8%
구 31
 
4.8%
Other values (68) 308
47.4%
Decimal Number
ValueCountFrequency (%)
1 39
20.7%
3 25
13.3%
0 23
12.2%
2 23
12.2%
5 16
8.5%
6 16
8.5%
4 15
 
8.0%
7 12
 
6.4%
8 11
 
5.9%
9 8
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
16.7%
I 1
16.7%
F 1
16.7%
E 1
16.7%
N 1
16.7%
O 1
16.7%
Space Separator
ValueCountFrequency (%)
157
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 650
58.9%
Common 447
40.5%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 43
 
6.6%
포 38
 
5.8%
등 38
 
5.8%
서 35
 
5.4%
로 32
 
4.9%
울 32
 
4.9%
동 31
 
4.8%
별 31
 
4.8%
시 31
 
4.8%
구 31
 
4.8%
Other values (68) 308
47.4%
Common
ValueCountFrequency (%)
157
35.1%
1 39
 
8.7%
, 35
 
7.8%
( 32
 
7.2%
) 32
 
7.2%
3 25
 
5.6%
0 23
 
5.1%
2 23
 
5.1%
5 16
 
3.6%
6 16
 
3.6%
Other values (5) 49
 
11.0%
Latin
ValueCountFrequency (%)
C 1
16.7%
I 1
16.7%
F 1
16.7%
E 1
16.7%
N 1
16.7%
O 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 650
58.9%
ASCII 453
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
34.7%
1 39
 
8.6%
, 35
 
7.7%
( 32
 
7.1%
) 32
 
7.1%
3 25
 
5.5%
0 23
 
5.1%
2 23
 
5.1%
5 16
 
3.5%
6 16
 
3.5%
Other values (11) 55
 
12.1%
Hangul
ValueCountFrequency (%)
영 43
 
6.6%
포 38
 
5.8%
등 38
 
5.8%
서 35
 
5.4%
로 32
 
4.9%
울 32
 
4.9%
동 31
 
4.8%
별 31
 
4.8%
시 31
 
4.8%
구 31
 
4.8%
Other values (68) 308
47.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)100.0%
Missing15
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean105798.31
Minimum7238
Maximum150975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:25:04.384655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7238
5-th percentile7253
Q17402.75
median150037
Q3150809.5
95-th percentile150962.25
Maximum150975
Range143737
Interquartile range (IQR)143406.75

Descriptive statistics

Standard deviation68581.167
Coefficient of variation (CV)0.64822553
Kurtosis-1.3906263
Mean105798.31
Median Absolute Deviation (MAD)841
Skewness-0.89516515
Sum1692773
Variance4.7033764 × 109
MonotonicityNot monotonic
2024-04-06T21:25:04.600462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
150975 1
 
3.2%
7238 1
 
3.2%
7422 1
 
3.2%
7274 1
 
3.2%
7345 1
 
3.2%
150030 1
 
3.2%
150809 1
 
3.2%
7258 1
 
3.2%
150038 1
 
3.2%
150036 1
 
3.2%
Other values (6) 6
 
19.4%
(Missing) 15
48.4%
ValueCountFrequency (%)
7238 1
3.2%
7258 1
3.2%
7274 1
3.2%
7345 1
3.2%
7422 1
3.2%
150030 1
3.2%
150033 1
3.2%
150036 1
3.2%
150038 1
3.2%
150800 1
3.2%
ValueCountFrequency (%)
150975 1
3.2%
150958 1
3.2%
150945 1
3.2%
150811 1
3.2%
150809 1
3.2%
150801 1
3.2%
150800 1
3.2%
150038 1
3.2%
150036 1
3.2%
150033 1
3.2%

사업장명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-06T21:25:04.987269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.0967742
Min length2

Characters and Unicode

Total characters282
Distinct characters108
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row(주)지에스리테일
2nd row(주)바이더웨이
3rd row(주)티엔디인터내셔널
4th row주몽담배영등포대리점
5th row우리담배판매 주식회사
ValueCountFrequency (%)
주식회사 9
 
20.9%
주)지에스리테일 1
 
2.3%
파님 1
 
2.3%
스누스코리아영등포 1
 
2.3%
스톡홀름 1
 
2.3%
stklm 1
 
2.3%
아이큐브텍 1
 
2.3%
웰하우징하우스(주 1
 
2.3%
주)현대전자담배 1
 
2.3%
sm산업 1
 
2.3%
Other values (25) 25
58.1%
2024-04-06T21:25:05.674202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 19
 
6.7%
( 12
 
4.3%
) 12
 
4.3%
12
 
4.3%
리 11
 
3.9%
스 9
 
3.2%
식 9
 
3.2%
회 9
 
3.2%
사 9
 
3.2%
담 8
 
2.8%
Other values (98) 172
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
84.8%
Open Punctuation 12
 
4.3%
Close Punctuation 12
 
4.3%
Space Separator 12
 
4.3%
Uppercase Letter 7
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 19
 
7.9%
리 11
 
4.6%
스 9
 
3.8%
식 9
 
3.8%
회 9
 
3.8%
사 9
 
3.8%
담 8
 
3.3%
이 8
 
3.3%
배 8
 
3.3%
아 6
 
2.5%
Other values (90) 143
59.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
M 2
28.6%
K 1
14.3%
L 1
14.3%
T 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 239
84.8%
Common 36
 
12.8%
Latin 7
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 19
 
7.9%
리 11
 
4.6%
스 9
 
3.8%
식 9
 
3.8%
회 9
 
3.8%
사 9
 
3.8%
담 8
 
3.3%
이 8
 
3.3%
배 8
 
3.3%
아 6
 
2.5%
Other values (90) 143
59.8%
Latin
ValueCountFrequency (%)
S 2
28.6%
M 2
28.6%
K 1
14.3%
L 1
14.3%
T 1
14.3%
Common
ValueCountFrequency (%)
( 12
33.3%
) 12
33.3%
12
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
84.8%
ASCII 43
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 19
 
7.9%
리 11
 
4.6%
스 9
 
3.8%
식 9
 
3.8%
회 9
 
3.8%
사 9
 
3.8%
담 8
 
3.3%
이 8
 
3.3%
배 8
 
3.3%
아 6
 
2.5%
Other values (90) 143
59.8%
ASCII
ValueCountFrequency (%)
( 12
27.9%
) 12
27.9%
12
27.9%
S 2
 
4.7%
M 2
 
4.7%
K 1
 
2.3%
L 1
 
2.3%
T 1
 
2.3%

최종수정일자
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2007-12-20 10:18:50
Maximum2022-02-14 11:01:42
2024-04-06T21:25:05.980042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:25:06.252897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
I
29 
U
 
2

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 29
93.5%
U 2
 
6.5%

Length

2024-04-06T21:25:06.576946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:25:06.908028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 29
93.5%
u 2
 
6.5%

데이터갱신일자
Date

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2018-08-31 23:59:59
Maximum2022-02-16 00:22:49
2024-04-06T21:25:07.116105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:25:07.330369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

좌표정보(X)
Real number (ℝ)

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191765.31
Minimum189775.89
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:25:07.587196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189775.89
5-th percentile189941.28
Q1190812.97
median191356.19
Q3192946.98
95-th percentile194174.36
Maximum194632.53
Range4856.6403
Interquartile range (IQR)2134.0053

Descriptive statistics

Standard deviation1398.1617
Coefficient of variation (CV)0.007291004
Kurtosis-0.72150288
Mean191765.31
Median Absolute Deviation (MAD)991.5393
Skewness0.57429833
Sum5944724.7
Variance1954856
MonotonicityNot monotonic
2024-04-06T21:25:07.837857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
193694.665015597 2
 
6.5%
190364.652010662 2
 
6.5%
190119.734954633 1
 
3.2%
190854.486518255 1
 
3.2%
192959.271161366 1
 
3.2%
191172.482456967 1
 
3.2%
189775.886090625 1
 
3.2%
194530.535390096 1
 
3.2%
191864.617457296 1
 
3.2%
191290.122053654 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
189775.886090625 1
3.2%
189859.071768836 1
3.2%
190023.48828661 1
3.2%
190119.734954633 1
3.2%
190364.652010662 2
6.5%
190750.105695354 1
3.2%
190777.430587122 1
3.2%
190848.510008223 1
3.2%
190854.486518255 1
3.2%
190959.868921976 1
3.2%
ValueCountFrequency (%)
194632.526367463 1
3.2%
194530.535390096 1
3.2%
193818.18014 1
3.2%
193694.665015597 2
6.5%
193326.931018911 1
3.2%
193282.654266684 1
3.2%
192959.271161366 1
3.2%
192934.679988733 1
3.2%
192549.933121435 1
3.2%
191864.617457296 1
3.2%

좌표정보(Y)
Real number (ℝ)

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean446491.31
Minimum443404.43
Maximum448079.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T21:25:08.084709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443404.43
5-th percentile444153.87
Q1446293.64
median446522.74
Q3447158.95
95-th percentile447624.6
Maximum448079.62
Range4675.1891
Interquartile range (IQR)865.30273

Descriptive statistics

Standard deviation1044.7985
Coefficient of variation (CV)0.0023400199
Kurtosis3.1460371
Mean446491.31
Median Absolute Deviation (MAD)478.15738
Skewness-1.5716988
Sum13841231
Variance1091604
MonotonicityNot monotonic
2024-04-06T21:25:08.282866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
446449.546192539 2
 
6.5%
447158.946262059 2
 
6.5%
446513.394643464 1
 
3.2%
446522.737224053 1
 
3.2%
447637.656082358 1
 
3.2%
443535.679480495 1
 
3.2%
446943.6642314 1
 
3.2%
446306.787198089 1
 
3.2%
445723.280027991 1
 
3.2%
448079.622534069 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
443404.433481001 1
3.2%
443535.679480495 1
3.2%
444772.056169821 1
3.2%
445723.280027991 1
3.2%
445875.89672273 1
3.2%
446044.579840782 1
3.2%
446138.269919323 1
3.2%
446290.970687029 1
3.2%
446296.316384985 1
3.2%
446306.787198089 1
3.2%
ValueCountFrequency (%)
448079.622534069 1
3.2%
447637.656082358 1
3.2%
447611.552045596 1
3.2%
447522.605711768 1
3.2%
447397.380617328 1
3.2%
447340.688670594 1
3.2%
447262.153315855 1
3.2%
447158.946262059 2
6.5%
447064.885774633 1
3.2%
446973.914570276 1
3.2%

취급제품명
Text

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-06T21:25:08.626926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length21
Mean length10.451613
Min length2

Characters and Unicode

Total characters324
Distinct characters98
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)80.6%

Sample

1st row국산,수입산 전품목
2nd row국산 및 수입산 전품목
3rd rowme too
4th rowNEED JOOMONG
5th row위고(Wigo), 스윙(Swing) 등
ValueCountFrequency (%)
전자담배 11
 
17.2%
등 4
 
6.2%
액상 3
 
4.7%
및 2
 
3.1%
전품목 2
 
3.1%
시가 2
 
3.1%
yesmoke(예스모크 1
 
1.6%
하카 1
 
1.6%
락 1
 
1.6%
봉쥬르 1
 
1.6%
Other values (36) 36
56.2%
2024-04-06T21:25:09.323978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
10.2%
담 22
 
6.8%
배 22
 
6.8%
, 17
 
5.2%
전 14
 
4.3%
자 12
 
3.7%
스 8
 
2.5%
) 8
 
2.5%
( 8
 
2.5%
E 8
 
2.5%
Other values (88) 172
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
52.8%
Uppercase Letter 49
 
15.1%
Lowercase Letter 36
 
11.1%
Space Separator 33
 
10.2%
Other Punctuation 17
 
5.2%
Close Punctuation 8
 
2.5%
Open Punctuation 8
 
2.5%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
담 22
 
12.9%
배 22
 
12.9%
전 14
 
8.2%
자 12
 
7.0%
스 8
 
4.7%
산 7
 
4.1%
품 4
 
2.3%
고 4
 
2.3%
등 4
 
2.3%
위 3
 
1.8%
Other values (49) 71
41.5%
Uppercase Letter
ValueCountFrequency (%)
E 8
16.3%
R 6
12.2%
O 5
10.2%
S 5
10.2%
G 4
8.2%
W 3
 
6.1%
N 3
 
6.1%
A 2
 
4.1%
T 2
 
4.1%
U 2
 
4.1%
Other values (7) 9
18.4%
Lowercase Letter
ValueCountFrequency (%)
m 5
13.9%
o 5
13.9%
g 4
11.1%
i 4
11.1%
w 3
8.3%
a 2
 
5.6%
l 2
 
5.6%
d 2
 
5.6%
n 2
 
5.6%
t 1
 
2.8%
Other values (6) 6
16.7%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171
52.8%
Latin 85
26.2%
Common 68
 
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
담 22
 
12.9%
배 22
 
12.9%
전 14
 
8.2%
자 12
 
7.0%
스 8
 
4.7%
산 7
 
4.1%
품 4
 
2.3%
고 4
 
2.3%
등 4
 
2.3%
위 3
 
1.8%
Other values (49) 71
41.5%
Latin
ValueCountFrequency (%)
E 8
 
9.4%
R 6
 
7.1%
O 5
 
5.9%
m 5
 
5.9%
S 5
 
5.9%
o 5
 
5.9%
g 4
 
4.7%
i 4
 
4.7%
G 4
 
4.7%
W 3
 
3.5%
Other values (23) 36
42.4%
Common
ValueCountFrequency (%)
33
48.5%
, 17
25.0%
) 8
 
11.8%
( 8
 
11.8%
1 1
 
1.5%
5 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
52.8%
ASCII 153
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33
21.6%
, 17
 
11.1%
) 8
 
5.2%
( 8
 
5.2%
E 8
 
5.2%
R 6
 
3.9%
O 5
 
3.3%
m 5
 
3.3%
S 5
 
3.3%
o 5
 
3.3%
Other values (29) 53
34.6%
Hangul
ValueCountFrequency (%)
담 22
 
12.9%
배 22
 
12.9%
전 14
 
8.2%
자 12
 
7.0%
스 8
 
4.7%
산 7
 
4.1%
품 4
 
2.3%
고 4
 
2.3%
등 4
 
2.3%
위 3
 
1.8%
Other values (49) 71
41.5%

담배공급업체명
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-06T21:25:09.764253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length36
Mean length16
Min length6

Characters and Unicode

Total characters496
Distinct characters144
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)90.3%

Sample

1st row케이티앤지 외 수입업체
2nd row케이티엔지 외 수입공급업체
3rd row트리플나인(주)
4th row주몽담배(주)
5th row우리담배 주식회사
ValueCountFrequency (%)
우리담배판매(주 3
 
4.4%
주식회사 2
 
2.9%
korea 2
 
2.9%
케이티앤지 2
 
2.9%
외 2
 
2.9%
ltd 2
 
2.9%
co 2
 
2.9%
technology 2
 
2.9%
수입판매업체 1
 
1.5%
위 1
 
1.5%
Other values (49) 49
72.1%
2024-04-06T21:25:10.611551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
7.7%
주 24
 
4.8%
( 22
 
4.4%
) 22
 
4.4%
리 15
 
3.0%
이 10
 
2.0%
o 10
 
2.0%
담 9
 
1.8%
n 9
 
1.8%
배 8
 
1.6%
Other values (134) 329
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
52.8%
Lowercase Letter 61
 
12.3%
Uppercase Letter 61
 
12.3%
Space Separator 38
 
7.7%
Open Punctuation 22
 
4.4%
Close Punctuation 22
 
4.4%
Other Punctuation 16
 
3.2%
Decimal Number 13
 
2.6%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
9.2%
리 15
 
5.7%
이 10
 
3.8%
담 9
 
3.4%
배 8
 
3.1%
코 8
 
3.1%
업 7
 
2.7%
아 7
 
2.7%
스 6
 
2.3%
우 6
 
2.3%
Other values (83) 162
61.8%
Uppercase Letter
ValueCountFrequency (%)
A 7
11.5%
O 7
11.5%
T 7
11.5%
E 5
8.2%
C 5
8.2%
L 4
 
6.6%
R 4
 
6.6%
N 4
 
6.6%
I 4
 
6.6%
K 3
 
4.9%
Other values (8) 11
18.0%
Lowercase Letter
ValueCountFrequency (%)
o 10
16.4%
n 9
14.8%
e 6
9.8%
t 5
8.2%
r 4
 
6.6%
c 4
 
6.6%
y 4
 
6.6%
h 4
 
6.6%
a 3
 
4.9%
l 2
 
3.3%
Other values (7) 10
16.4%
Decimal Number
ValueCountFrequency (%)
1 4
30.8%
2 3
23.1%
0 2
15.4%
3 1
 
7.7%
8 1
 
7.7%
4 1
 
7.7%
7 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 6
37.5%
, 6
37.5%
: 2
 
12.5%
* 1
 
6.2%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
52.8%
Latin 122
24.6%
Common 112
22.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
9.2%
리 15
 
5.7%
이 10
 
3.8%
담 9
 
3.4%
배 8
 
3.1%
코 8
 
3.1%
업 7
 
2.7%
아 7
 
2.7%
스 6
 
2.3%
우 6
 
2.3%
Other values (83) 162
61.8%
Latin
ValueCountFrequency (%)
o 10
 
8.2%
n 9
 
7.4%
A 7
 
5.7%
O 7
 
5.7%
T 7
 
5.7%
e 6
 
4.9%
E 5
 
4.1%
t 5
 
4.1%
C 5
 
4.1%
r 4
 
3.3%
Other values (25) 57
46.7%
Common
ValueCountFrequency (%)
38
33.9%
( 22
19.6%
) 22
19.6%
. 6
 
5.4%
, 6
 
5.4%
1 4
 
3.6%
2 3
 
2.7%
0 2
 
1.8%
: 2
 
1.8%
- 1
 
0.9%
Other values (6) 6
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
52.8%
ASCII 234
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
 
16.2%
( 22
 
9.4%
) 22
 
9.4%
o 10
 
4.3%
n 9
 
3.8%
A 7
 
3.0%
O 7
 
3.0%
T 7
 
3.0%
. 6
 
2.6%
, 6
 
2.6%
Other values (41) 100
42.7%
Hangul
ValueCountFrequency (%)
주 24
 
9.2%
리 15
 
5.7%
이 10
 
3.8%
담 9
 
3.4%
배 8
 
3.1%
코 8
 
3.1%
업 7
 
2.7%
아 7
 
2.7%
스 6
 
2.3%
우 6
 
2.3%
Other values (83) 162
61.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)취급제품명담배공급업체명
03180000200231801171550000120020528<NA>3폐업3폐업처리20170124<NA><NA><NA>2006-2077<NA>150096서울특별시 영등포구 문래동6가 10번지서울특별시 영등포구 선유로 75 (문래동6가)<NA>(주)지에스리테일2017-02-06 15:53:11I2018-08-31 23:59:59.0<NA>190119.734955446513.394643국산,수입산 전품목케이티앤지 외 수입업체
13180000200531801171550000120050707<NA>1영업/정상1정상영업<NA>2008102920081229<NA>3164-7222<NA>150095서울특별시 영등포구 문래동5가 9번지서울특별시 영등포구 경인로71길 70 (문래동5가)<NA>(주)바이더웨이2008-10-29 17:28:00I2018-08-31 23:59:59.0<NA>189859.071769445875.896723국산 및 수입산 전품목케이티엔지 외 수입공급업체
23180000200531801171550000220050728<NA>1영업/정상1정상영업<NA><NA><NA><NA>785-8401<NA>150010서울특별시 영등포구 여의도동 44번지 24호 호성빌딩1102호서울특별시 영등포구 여의대방로65길 20 (여의도동,호성빌딩1102호)<NA>(주)티엔디인터내셔널2008-01-07 17:10:24I2018-08-31 23:59:59.0<NA>193694.665016446449.546193me too트리플나인(주)
33180000200731801171550000120071206<NA>3폐업3폐업처리20100209<NA><NA><NA>3667-3627<NA>150037서울특별시 영등포구 영등포동7가 44번지 1호 303호서울특별시 영등포구 영중로 77 (영등포동7가,303호)<NA>주몽담배영등포대리점2010-02-09 11:30:54I2018-08-31 23:59:59.0<NA>191521.990315446780.856819NEED JOOMONG주몽담배(주)
43180000200731801171550000220071220<NA>1영업/정상1정상영업<NA><NA><NA><NA>953-5000<NA>150010서울특별시 영등포구 여의도동 60번지 63빌딩 51층서울특별시 영등포구 63로 50 (여의도동,63빌딩 51층)<NA>우리담배판매 주식회사2007-12-20 10:18:50I2018-08-31 23:59:59.0<NA>194632.526367446401.926526위고(Wigo), 스윙(Swing) 등우리담배 주식회사
53180000200831801171550000120080204<NA>1영업/정상1정상영업<NA><NA><NA><NA>2678-4411<NA>150093서울특별시 영등포구 문래동3가 36번지 6호서울특별시 영등포구 문래로 149 (문래동3가)<NA>우리담배 관악양천점2008-02-04 13:38:10I2018-08-31 23:59:59.0<NA>190959.868922446290.970687WIGO, SWING우리담배판매(주)
63180000200831801171550000220080317<NA>3폐업3폐업처리20120305<NA><NA><NA>2628-5932<NA>150103서울특별시 영등포구 양평동3가 46번지 이엔씨드림타워 806,807호서울특별시 영등포구 선유로 146 (양평동3가,이엔씨드림타워 806,807호)<NA>(주)디에스디마케팅2012-03-06 13:50:28I2018-08-31 23:59:59.0<NA>190364.652011447158.946262위고(wigo),스윙(swing)우리담배판매(주)
73180000200831801171550000320080506<NA>1영업/정상1정상영업<NA><NA><NA><NA>2630-8800<NA><NA>서울특별시 영등포구 당산동3가 2번지 7호서울특별시 영등포구 국회대로 612 (당산동3가)7258코레일유통 주식회사2021-01-21 09:52:18U2021-01-23 02:40:00.0<NA>191272.120991447064.885775국산담배, 외산담배케이티앤지, 브리티쉬아메리칸토바코코리아주식회사, 한국필립모리스 (주), JT INTERNATIONAL KOREA INC.
83180000200831801171550000420080715<NA>1영업/정상1정상영업<NA><NA><NA><NA>3367-0661<NA>150038서울특별시 영등포구 영등포동8가 56번지 2호 청림빌딩 4층서울특별시 영등포구 국회대로53길 23 (영등포동8가,청림빌딩 4층)<NA>아이플랙스2008-07-15 17:24:01I2018-08-31 23:59:59.0<NA>191647.292795447262.153316위고,스윙 등우리담배판매(주)
93180000200931801171550000120090701<NA>1영업/정상1정상영업<NA><NA><NA><NA>784-9444<NA>150874서울특별시 영등포구 여의도동 17번지 1호 금산빌딩813호서울특별시 영등포구 국회대로 750 (여의도동,금산빌딩813호)<NA>이토바(전자담배)2011-03-16 17:40:45I2018-08-31 23:59:59.0<NA>192549.933121447340.688671전자담배(주)씨디이티아이
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