Overview

Dataset statistics

Number of variables44
Number of observations23
Missing cells236
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory381.7 B

Variable types

Categorical20
Text8
DateTime3
Unsupported8
Numeric4
Boolean1

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),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18304/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
보증액 is highly imbalanced (74.2%)Imbalance
월세액 is highly imbalanced (74.2%)Imbalance
인허가취소일자 has 23 (100.0%) missing valuesMissing
폐업일자 has 10 (43.5%) missing valuesMissing
휴업시작일자 has 23 (100.0%) missing valuesMissing
휴업종료일자 has 23 (100.0%) missing valuesMissing
재개업일자 has 23 (100.0%) missing valuesMissing
전화번호 has 1 (4.3%) missing valuesMissing
도로명주소 has 8 (34.8%) missing valuesMissing
도로명우편번호 has 8 (34.8%) missing valuesMissing
좌표정보(X) has 1 (4.3%) missing valuesMissing
좌표정보(Y) has 1 (4.3%) missing valuesMissing
영업장주변구분명 has 15 (65.2%) missing valuesMissing
총인원 has 23 (100.0%) missing valuesMissing
다중이용업소여부 has 8 (34.8%) missing valuesMissing
전통업소지정번호 has 23 (100.0%) missing valuesMissing
전통업소주된음식 has 23 (100.0%) missing valuesMissing
홈페이지 has 23 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 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
총인원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 05:36:14.159304
Analysis finished2024-05-11 05:36:14.960837
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
3020000
23 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3020000 23
100.0%

Length

2024-05-11T14:36:15.103370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:15.295711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 23
100.0%

관리번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-11T14:36:15.577705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters506
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 row3020000-114-1996-00126
2nd row3020000-114-1996-00175
3rd row3020000-114-1996-00177
4th row3020000-114-1996-00189
5th row3020000-114-1996-00220
ValueCountFrequency (%)
3020000-114-1996-00126 1
 
4.3%
3020000-114-2005-00001 1
 
4.3%
3020000-114-2020-00001 1
 
4.3%
3020000-114-2016-00001 1
 
4.3%
3020000-114-2015-00001 1
 
4.3%
3020000-114-2013-00001 1
 
4.3%
3020000-114-2012-00001 1
 
4.3%
3020000-114-2011-00002 1
 
4.3%
3020000-114-2011-00001 1
 
4.3%
3020000-114-2010-00001 1
 
4.3%
Other values (13) 13
56.5%
2024-05-11T14:36:16.190666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 212
41.9%
1 83
 
16.4%
- 69
 
13.6%
2 49
 
9.7%
3 26
 
5.1%
4 26
 
5.1%
9 20
 
4.0%
6 9
 
1.8%
7 6
 
1.2%
5 4
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 437
86.4%
Dash Punctuation 69
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 212
48.5%
1 83
 
19.0%
2 49
 
11.2%
3 26
 
5.9%
4 26
 
5.9%
9 20
 
4.6%
6 9
 
2.1%
7 6
 
1.4%
5 4
 
0.9%
8 2
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 212
41.9%
1 83
 
16.4%
- 69
 
13.6%
2 49
 
9.7%
3 26
 
5.1%
4 26
 
5.1%
9 20
 
4.0%
6 9
 
1.8%
7 6
 
1.2%
5 4
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 212
41.9%
1 83
 
16.4%
- 69
 
13.6%
2 49
 
9.7%
3 26
 
5.1%
4 26
 
5.1%
9 20
 
4.0%
6 9
 
1.8%
7 6
 
1.2%
5 4
 
0.8%

인허가일자
Date

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum1996-06-28 00:00:00
Maximum2022-08-03 00:00:00
2024-05-11T14:36:16.422547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:16.634837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
3
13 
1
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 13
56.5%
1 10
43.5%

Length

2024-05-11T14:36:16.838775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:16.988353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 13
56.5%
1 10
43.5%

영업상태명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
폐업
13 
영업/정상
10 

Length

Max length5
Median length2
Mean length3.3043478
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 13
56.5%
영업/정상 10
43.5%

Length

2024-05-11T14:36:17.199405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:17.383093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 13
56.5%
영업/정상 10
43.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2
13 
1
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 13
56.5%
1 10
43.5%

Length

2024-05-11T14:36:17.618108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:17.911018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 13
56.5%
1 10
43.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
폐업
13 
영업
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 13
56.5%
영업 10
43.5%

Length

2024-05-11T14:36:18.090478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:18.598269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 13
56.5%
영업 10
43.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)100.0%
Missing10
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean20108446
Minimum20010731
Maximum20221011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-11T14:36:18.753442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010731
5-th percentile20016777
Q120060523
median20100603
Q320181123
95-th percentile20202478
Maximum20221011
Range210280
Interquartile range (IQR)120600

Descriptive statistics

Standard deviation70530.879
Coefficient of variation (CV)0.003507525
Kurtosis-1.4308982
Mean20108446
Median Absolute Deviation (MAD)60291
Skewness0.17509297
Sum2.614098 × 108
Variance4.9746048 × 109
MonotonicityNot monotonic
2024-05-11T14:36:18.924263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20060523 1
 
4.3%
20040312 1
 
4.3%
20221011 1
 
4.3%
20010731 1
 
4.3%
20100603 1
 
4.3%
20061103 1
 
4.3%
20020807 1
 
4.3%
20121022 1
 
4.3%
20071008 1
 
4.3%
20150210 1
 
4.3%
Other values (3) 3
 
13.0%
(Missing) 10
43.5%
ValueCountFrequency (%)
20010731 1
4.3%
20020807 1
4.3%
20040312 1
4.3%
20060523 1
4.3%
20061103 1
4.3%
20071008 1
4.3%
20100603 1
4.3%
20121022 1
4.3%
20150210 1
4.3%
20181123 1
4.3%
ValueCountFrequency (%)
20221011 1
4.3%
20190122 1
4.3%
20181226 1
4.3%
20181123 1
4.3%
20150210 1
4.3%
20121022 1
4.3%
20100603 1
4.3%
20071008 1
4.3%
20061103 1
4.3%
20060523 1
4.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

전화번호
Text

MISSING 

Distinct21
Distinct (%)95.5%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-05-11T14:36:19.153056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.545455
Min length10

Characters and Unicode

Total characters232
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

Unique20 ?
Unique (%)90.9%

Sample

1st row02 7969135
2nd row02 8208526
3rd row02 20772800
4th row02 7981652
5th row02 7922981
ValueCountFrequency (%)
02 19
44.2%
7044681 2
 
4.7%
796 1
 
2.3%
69054975 1
 
2.3%
0232739988 1
 
2.3%
3553 1
 
2.3%
755 1
 
2.3%
7928542 1
 
2.3%
7985601 1
 
2.3%
7979992 1
 
2.3%
Other values (14) 14
32.6%
2024-05-11T14:36:19.672123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
17.7%
2 39
16.8%
29
12.5%
7 25
10.8%
9 20
8.6%
5 17
7.3%
8 14
 
6.0%
1 14
 
6.0%
6 12
 
5.2%
3 12
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203
87.5%
Space Separator 29
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
20.2%
2 39
19.2%
7 25
12.3%
9 20
9.9%
5 17
8.4%
8 14
 
6.9%
1 14
 
6.9%
6 12
 
5.9%
3 12
 
5.9%
4 9
 
4.4%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
17.7%
2 39
16.8%
29
12.5%
7 25
10.8%
9 20
8.6%
5 17
7.3%
8 14
 
6.0%
1 14
 
6.0%
6 12
 
5.2%
3 12
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
17.7%
2 39
16.8%
29
12.5%
7 25
10.8%
9 20
8.6%
5 17
7.3%
8 14
 
6.0%
1 14
 
6.0%
6 12
 
5.2%
3 12
 
5.2%

소재지면적
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-11T14:36:19.991125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2173913
Min length6

Characters and Unicode

Total characters143
Distinct characters12
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

Unique21 ?
Unique (%)91.3%

Sample

1st row471.65
2nd row485.00
3rd row3300.00
4th row845.00
5th row646.00
ValueCountFrequency (%)
627.00 2
 
8.7%
471.65 1
 
4.3%
392.00 1
 
4.3%
808.49 1
 
4.3%
324.30 1
 
4.3%
464.70 1
 
4.3%
1088.19 1
 
4.3%
323.10 1
 
4.3%
377.00 1
 
4.3%
849.72 1
 
4.3%
Other values (12) 12
52.2%
2024-05-11T14:36:20.553729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
21.7%
. 23
16.1%
3 14
9.8%
7 13
9.1%
4 13
9.1%
2 11
 
7.7%
6 10
 
7.0%
8 9
 
6.3%
1 6
 
4.2%
5 6
 
4.2%
Other values (2) 7
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119
83.2%
Other Punctuation 24
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
26.1%
3 14
11.8%
7 13
10.9%
4 13
10.9%
2 11
 
9.2%
6 10
 
8.4%
8 9
 
7.6%
1 6
 
5.0%
5 6
 
5.0%
9 6
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 23
95.8%
, 1
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 143
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
21.7%
. 23
16.1%
3 14
9.8%
7 13
9.1%
4 13
9.1%
2 11
 
7.7%
6 10
 
7.0%
8 9
 
6.3%
1 6
 
4.2%
5 6
 
4.2%
Other values (2) 7
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
21.7%
. 23
16.1%
3 14
9.8%
7 13
9.1%
4 13
9.1%
2 11
 
7.7%
6 10
 
7.0%
8 9
 
6.3%
1 6
 
4.2%
5 6
 
4.2%
Other values (2) 7
 
4.9%

소재지우편번호
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-11T14:36:20.832585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3043478
Min length6

Characters and Unicode

Total characters145
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

Unique15 ?
Unique (%)65.2%

Sample

1st row140823
2nd row140860
3rd row140-873
4th row140026
5th row140865
ValueCountFrequency (%)
140823 2
 
8.7%
140899 2
 
8.7%
140865 2
 
8.7%
140860 2
 
8.7%
140210 1
 
4.3%
140-111 1
 
4.3%
140-210 1
 
4.3%
140850 1
 
4.3%
140-040 1
 
4.3%
140-884 1
 
4.3%
Other values (9) 9
39.1%
2024-05-11T14:36:21.377693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
23.4%
4 29
20.0%
1 28
19.3%
8 18
12.4%
6 7
 
4.8%
- 7
 
4.8%
2 6
 
4.1%
9 5
 
3.4%
5 5
 
3.4%
3 4
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138
95.2%
Dash Punctuation 7
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
24.6%
4 29
21.0%
1 28
20.3%
8 18
13.0%
6 7
 
5.1%
2 6
 
4.3%
9 5
 
3.6%
5 5
 
3.6%
3 4
 
2.9%
7 2
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 145
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
23.4%
4 29
20.0%
1 28
19.3%
8 18
12.4%
6 7
 
4.8%
- 7
 
4.8%
2 6
 
4.1%
9 5
 
3.4%
5 5
 
3.4%
3 4
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
23.4%
4 29
20.0%
1 28
19.3%
8 18
12.4%
6 7
 
4.8%
- 7
 
4.8%
2 6
 
4.1%
9 5
 
3.4%
5 5
 
3.4%
3 4
 
2.8%

지번주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-11T14:36:21.774781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length31
Mean length26.956522
Min length20

Characters and Unicode

Total characters620
Distinct characters65
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row서울특별시 용산구 보광동 260-6
2nd row서울특별시 용산구 이태원동 22-2 지하
3rd row서울특별시 용산구 한강로2가 15-19
4th row서울특별시 용산구 용산동6가 69-167 지하
5th row서울특별시 용산구 이태원동 128-4
ValueCountFrequency (%)
서울특별시 23
19.3%
용산구 23
19.3%
이태원동 5
 
4.2%
지하1층 4
 
3.4%
한남동 4
 
3.4%
지하 3
 
2.5%
128-4 2
 
1.7%
55-50 2
 
1.7%
후암동 2
 
1.7%
산천동 2
 
1.7%
Other values (45) 49
41.2%
2024-05-11T14:36:22.369467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111
 
17.9%
1 31
 
5.0%
산 28
 
4.5%
2 26
 
4.2%
용 26
 
4.2%
시 24
 
3.9%
서 23
 
3.7%
구 23
 
3.7%
울 23
 
3.7%
별 23
 
3.7%
Other values (55) 282
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 346
55.8%
Decimal Number 123
 
19.8%
Space Separator 111
 
17.9%
Dash Punctuation 21
 
3.4%
Close Punctuation 6
 
1.0%
Open Punctuation 6
 
1.0%
Other Punctuation 3
 
0.5%
Uppercase Letter 2
 
0.3%
Math Symbol 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 28
 
8.1%
용 26
 
7.5%
시 24
 
6.9%
서 23
 
6.6%
구 23
 
6.6%
울 23
 
6.6%
별 23
 
6.6%
특 23
 
6.6%
동 21
 
6.1%
지 20
 
5.8%
Other values (36) 112
32.4%
Decimal Number
ValueCountFrequency (%)
1 31
25.2%
2 26
21.1%
6 11
 
8.9%
0 11
 
8.9%
5 11
 
8.9%
8 9
 
7.3%
3 8
 
6.5%
9 6
 
4.9%
7 5
 
4.1%
4 5
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
55.8%
Common 271
43.7%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 28
 
8.1%
용 26
 
7.5%
시 24
 
6.9%
서 23
 
6.6%
구 23
 
6.6%
울 23
 
6.6%
별 23
 
6.6%
특 23
 
6.6%
동 21
 
6.1%
지 20
 
5.8%
Other values (36) 112
32.4%
Common
ValueCountFrequency (%)
111
41.0%
1 31
 
11.4%
2 26
 
9.6%
- 21
 
7.7%
6 11
 
4.1%
0 11
 
4.1%
5 11
 
4.1%
8 9
 
3.3%
3 8
 
3.0%
) 6
 
2.2%
Other values (6) 26
 
9.6%
Latin
ValueCountFrequency (%)
L 1
33.3%
a 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 346
55.8%
ASCII 274
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111
40.5%
1 31
 
11.3%
2 26
 
9.5%
- 21
 
7.7%
6 11
 
4.0%
0 11
 
4.0%
5 11
 
4.0%
8 9
 
3.3%
3 8
 
2.9%
) 6
 
2.2%
Other values (9) 29
 
10.6%
Hangul
ValueCountFrequency (%)
산 28
 
8.1%
용 26
 
7.5%
시 24
 
6.9%
서 23
 
6.6%
구 23
 
6.6%
울 23
 
6.6%
별 23
 
6.6%
특 23
 
6.6%
동 21
 
6.1%
지 20
 
5.8%
Other values (36) 112
32.4%

도로명주소
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing8
Missing (%)34.8%
Memory size316.0 B
2024-05-11T14:36:22.742645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length38
Mean length34.666667
Min length22

Characters and Unicode

Total characters520
Distinct characters69
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

Unique15 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 청파로 122 (한강로2가)
2nd row서울특별시 용산구 이촌로 352 (용산동6가,지하)
3rd row서울특별시 용산구 보광로 127 (이태원동,외1필지(128-5))
4th row서울특별시 용산구 한강대로23길 55 (한강로3가)
5th row서울특별시 용산구 보광로 30 (보광동)
ValueCountFrequency (%)
서울특별시 15
 
16.3%
용산구 15
 
16.3%
지하1층 3
 
3.3%
21 2
 
2.2%
후암동 2
 
2.2%
원효로 2
 
2.2%
보광로 2
 
2.2%
한남동 2
 
2.2%
이촌로 2
 
2.2%
후암로28길 2
 
2.2%
Other values (45) 45
48.9%
2024-05-11T14:36:23.324072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
14.8%
1 36
 
6.9%
) 20
 
3.8%
( 20
 
3.8%
지 19
 
3.7%
2 19
 
3.7%
산 18
 
3.5%
로 18
 
3.5%
, 17
 
3.3%
용 17
 
3.3%
Other values (59) 259
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
56.3%
Decimal Number 88
 
16.9%
Space Separator 77
 
14.8%
Close Punctuation 20
 
3.8%
Open Punctuation 20
 
3.8%
Other Punctuation 17
 
3.3%
Dash Punctuation 2
 
0.4%
Uppercase Letter 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 19
 
6.5%
산 18
 
6.1%
로 18
 
6.1%
용 17
 
5.8%
서 16
 
5.5%
시 16
 
5.5%
울 15
 
5.1%
구 15
 
5.1%
별 15
 
5.1%
특 15
 
5.1%
Other values (41) 129
44.0%
Decimal Number
ValueCountFrequency (%)
1 36
40.9%
2 19
21.6%
3 7
 
8.0%
5 7
 
8.0%
0 7
 
8.0%
6 4
 
4.5%
4 3
 
3.4%
8 3
 
3.4%
9 1
 
1.1%
7 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
56.3%
Common 225
43.3%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 19
 
6.5%
산 18
 
6.1%
로 18
 
6.1%
용 17
 
5.8%
서 16
 
5.5%
시 16
 
5.5%
울 15
 
5.1%
구 15
 
5.1%
별 15
 
5.1%
특 15
 
5.1%
Other values (41) 129
44.0%
Common
ValueCountFrequency (%)
77
34.2%
1 36
16.0%
) 20
 
8.9%
( 20
 
8.9%
2 19
 
8.4%
, 17
 
7.6%
3 7
 
3.1%
5 7
 
3.1%
0 7
 
3.1%
6 4
 
1.8%
Other values (6) 11
 
4.9%
Latin
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
56.3%
ASCII 227
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
33.9%
1 36
15.9%
) 20
 
8.8%
( 20
 
8.8%
2 19
 
8.4%
, 17
 
7.5%
3 7
 
3.1%
5 7
 
3.1%
0 7
 
3.1%
6 4
 
1.8%
Other values (8) 13
 
5.7%
Hangul
ValueCountFrequency (%)
지 19
 
6.5%
산 18
 
6.1%
로 18
 
6.1%
용 17
 
5.8%
서 16
 
5.5%
시 16
 
5.5%
울 15
 
5.1%
구 15
 
5.1%
별 15
 
5.1%
특 15
 
5.1%
Other values (41) 129
44.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)93.3%
Missing8
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean4379.9333
Minimum4315
Maximum4428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-11T14:36:23.535247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4315
5-th percentile4325.5
Q14355
median4377
Q34417
95-th percentile4427.3
Maximum4428
Range113
Interquartile range (IQR)62

Descriptive statistics

Standard deviation38.025305
Coefficient of variation (CV)0.0086817086
Kurtosis-1.2443956
Mean4379.9333
Median Absolute Deviation (MAD)38
Skewness-0.25056753
Sum65699
Variance1445.9238
MonotonicityNot monotonic
2024-05-11T14:36:23.725404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4330 2
 
8.7%
4371 1
 
4.3%
4428 1
 
4.3%
4391 1
 
4.3%
4377 1
 
4.3%
4415 1
 
4.3%
4315 1
 
4.3%
4351 1
 
4.3%
4419 1
 
4.3%
4420 1
 
4.3%
Other values (4) 4
17.4%
(Missing) 8
34.8%
ValueCountFrequency (%)
4315 1
4.3%
4330 2
8.7%
4351 1
4.3%
4359 1
4.3%
4365 1
4.3%
4371 1
4.3%
4377 1
4.3%
4391 1
4.3%
4401 1
4.3%
4415 1
4.3%
ValueCountFrequency (%)
4428 1
4.3%
4427 1
4.3%
4420 1
4.3%
4419 1
4.3%
4415 1
4.3%
4401 1
4.3%
4391 1
4.3%
4377 1
4.3%
4371 1
4.3%
4365 1
4.3%

사업장명
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-05-11T14:36:24.005388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length15
Mean length10.434783
Min length3

Characters and Unicode

Total characters240
Distinct characters83
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row(주)해태유통
2nd row(주)메가마트
3rd row(주)농협유통하나로클럽용산점
4th row롯데쇼핑(주)롯데수퍼신동아점
5th row해태유통이태원영업소
ValueCountFrequency (%)
홈마트 2
 
6.2%
원효로점 1
 
3.1%
fresh 1
 
3.1%
the 1
 
3.1%
지에스더프레시(gs 1
 
3.1%
럭키진흥마트 1
 
3.1%
고메이494한남점 1
 
3.1%
한화갤러리아(주 1
 
3.1%
소비자할인마트 1
 
3.1%
진흥마트 1
 
3.1%
Other values (21) 21
65.6%
2024-05-11T14:36:24.577132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 13
 
5.4%
점 12
 
5.0%
트 10
 
4.2%
( 10
 
4.2%
주 10
 
4.2%
) 10
 
4.2%
9
 
3.8%
스 6
 
2.5%
롯 6
 
2.5%
데 6
 
2.5%
Other values (73) 148
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
82.1%
Open Punctuation 10
 
4.2%
Close Punctuation 10
 
4.2%
Uppercase Letter 10
 
4.2%
Space Separator 9
 
3.8%
Decimal Number 3
 
1.2%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 13
 
6.6%
점 12
 
6.1%
트 10
 
5.1%
주 10
 
5.1%
스 6
 
3.0%
롯 6
 
3.0%
데 6
 
3.0%
한 5
 
2.5%
남 5
 
2.5%
이 5
 
2.5%
Other values (60) 119
60.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
R 1
10.0%
F 1
10.0%
T 1
10.0%
G 1
10.0%
Decimal Number
ValueCountFrequency (%)
4 2
66.7%
9 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
82.1%
Common 33
 
13.8%
Latin 10
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 13
 
6.6%
점 12
 
6.1%
트 10
 
5.1%
주 10
 
5.1%
스 6
 
3.0%
롯 6
 
3.0%
데 6
 
3.0%
한 5
 
2.5%
남 5
 
2.5%
이 5
 
2.5%
Other values (60) 119
60.4%
Latin
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
R 1
10.0%
F 1
10.0%
T 1
10.0%
G 1
10.0%
Common
ValueCountFrequency (%)
( 10
30.3%
) 10
30.3%
9
27.3%
4 2
 
6.1%
9 1
 
3.0%
- 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
82.1%
ASCII 43
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 13
 
6.6%
점 12
 
6.1%
트 10
 
5.1%
주 10
 
5.1%
스 6
 
3.0%
롯 6
 
3.0%
데 6
 
3.0%
한 5
 
2.5%
남 5
 
2.5%
이 5
 
2.5%
Other values (60) 119
60.4%
ASCII
ValueCountFrequency (%)
( 10
23.3%
) 10
23.3%
9
20.9%
E 2
 
4.7%
H 2
 
4.7%
4 2
 
4.7%
S 2
 
4.7%
R 1
 
2.3%
F 1
 
2.3%
T 1
 
2.3%
Other values (3) 3
 
7.0%

최종수정일자
Date

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2001-07-31 00:00:00
Maximum2024-04-22 13:42:36
2024-05-11T14:36:24.790605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:24.999452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

데이터갱신구분
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
U
12 
I
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 12
52.2%
I 11
47.8%

Length

2024-05-11T14:36:25.342001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:25.507838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 12
52.2%
i 11
47.8%

데이터갱신일자
Date

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-05-11T14:36:25.659425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:25.918277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
기타식품판매업
23 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 23
100.0%

Length

2024-05-11T14:36:26.119166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:26.265961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 23
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)81.8%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean198565.48
Minimum195544.61
Maximum200846.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-11T14:36:26.416217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195544.61
5-th percentile195607.89
Q1197221.44
median198918.82
Q3199792.55
95-th percentile200747.69
Maximum200846.6
Range5301.9983
Interquartile range (IQR)2571.1149

Descriptive statistics

Standard deviation1603.1634
Coefficient of variation (CV)0.0080737266
Kurtosis-0.83452005
Mean198565.48
Median Absolute Deviation (MAD)1174.6644
Skewness-0.43765821
Sum4368440.5
Variance2570132.9
MonotonicityNot monotonic
2024-05-11T14:36:26.631669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
199375.725957557 2
 
8.7%
197221.439324261 2
 
8.7%
199471.30974998 2
 
8.7%
198043.461924383 2
 
8.7%
199899.635730602 1
 
4.3%
199061.591994245 1
 
4.3%
200231.538140657 1
 
4.3%
195544.606275448 1
 
4.3%
195547.140326252 1
 
4.3%
200846.604536733 1
 
4.3%
Other values (8) 8
34.8%
ValueCountFrequency (%)
195544.606275448 1
4.3%
195547.140326252 1
4.3%
196762.077394917 1
4.3%
196813.258497258 1
4.3%
197045.849468346 1
4.3%
197221.439324261 2
8.7%
198043.461924383 2
8.7%
198622.89264988 1
4.3%
198776.047173222 1
4.3%
199061.591994245 1
4.3%
ValueCountFrequency (%)
200846.604536733 1
4.3%
200769.106350156 1
4.3%
200340.875562217 1
4.3%
200231.538140657 1
4.3%
199955.429742269 1
4.3%
199899.635730602 1
4.3%
199471.30974998 2
8.7%
199375.725957557 2
8.7%
199061.591994245 1
4.3%
198776.047173222 1
4.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)81.8%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean447890.33
Minimum446114.16
Maximum449732.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-05-11T14:36:26.965319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446114.16
5-th percentile446524.51
Q1447490.72
median447973.55
Q3448283.36
95-th percentile449676.62
Maximum449732.01
Range3617.8572
Interquartile range (IQR)792.6453

Descriptive statistics

Standard deviation889.74924
Coefficient of variation (CV)0.0019865337
Kurtosis0.66847329
Mean447890.33
Median Absolute Deviation (MAD)462.40597
Skewness0.16338583
Sum9853587.3
Variance791653.71
MonotonicityNot monotonic
2024-05-11T14:36:27.182189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
447994.259776162 2
 
8.7%
446524.508385914 2
 
8.7%
447522.747030786 2
 
8.7%
449732.012463716 2
 
8.7%
447307.171452429 1
 
4.3%
448038.185765556 1
 
4.3%
448226.481350525 1
 
4.3%
447831.138115911 1
 
4.3%
447976.775939762 1
 
4.3%
447970.331604571 1
 
4.3%
Other values (8) 8
34.8%
ValueCountFrequency (%)
446114.155238838 1
4.3%
446524.508385914 2
8.7%
447219.161582186 1
4.3%
447307.171452429 1
4.3%
447480.039577359 1
4.3%
447522.747030786 2
8.7%
447831.138115911 1
4.3%
447881.970772064 1
4.3%
447970.331604571 1
4.3%
447976.775939762 1
4.3%
ValueCountFrequency (%)
449732.012463716 2
8.7%
448624.224228815 1
4.3%
448620.768800874 1
4.3%
448447.558967085 1
4.3%
448302.321864858 1
4.3%
448226.481350525 1
4.3%
448038.185765556 1
4.3%
447994.259776162 2
8.7%
447976.775939762 1
4.3%
447970.331604571 1
4.3%

위생업태명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
기타식품판매업
15 
<NA>
8 

Length

Max length7
Median length7
Mean length5.9565217
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 15
65.2%
<NA> 8
34.8%

Length

2024-05-11T14:36:27.520221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:27.703108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 15
65.2%
na 8
34.8%

남성종사자수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
0
4 

Length

Max length4
Median length4
Mean length3.4782609
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
0 4
 
17.4%

Length

2024-05-11T14:36:27.906545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:28.066537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
0 4
 
17.4%

여성종사자수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
0
4 

Length

Max length4
Median length4
Mean length3.4782609
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
0 4
 
17.4%

Length

2024-05-11T14:36:28.254105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:28.445086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
0 4
 
17.4%

영업장주변구분명
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing15
Missing (%)65.2%
Memory size316.0 B
2024-05-11T14:36:28.633669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6.5
Mean length4.25
Min length2

Characters and Unicode

Total characters34
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)25.0%

Sample

1st row주택가주변
2nd row아파트지역
3rd row유흥업소밀집지역
4th row주택가주변
5th row기타
ValueCountFrequency (%)
주택가주변 3
37.5%
기타 3
37.5%
아파트지역 1
 
12.5%
유흥업소밀집지역 1
 
12.5%
2024-05-11T14:36:29.123229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6
17.6%
가 3
8.8%
변 3
8.8%
기 3
8.8%
타 3
8.8%
택 3
8.8%
지 2
 
5.9%
역 2
 
5.9%
흥 1
 
2.9%
밀 1
 
2.9%
Other values (7) 7
20.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6
17.6%
가 3
8.8%
변 3
8.8%
기 3
8.8%
타 3
8.8%
택 3
8.8%
지 2
 
5.9%
역 2
 
5.9%
흥 1
 
2.9%
밀 1
 
2.9%
Other values (7) 7
20.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6
17.6%
가 3
8.8%
변 3
8.8%
기 3
8.8%
타 3
8.8%
택 3
8.8%
지 2
 
5.9%
역 2
 
5.9%
흥 1
 
2.9%
밀 1
 
2.9%
Other values (7) 7
20.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6
17.6%
가 3
8.8%
변 3
8.8%
기 3
8.8%
타 3
8.8%
택 3
8.8%
지 2
 
5.9%
역 2
 
5.9%
흥 1
 
2.9%
밀 1
 
2.9%
Other values (7) 7
20.6%

등급구분명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
15 
기타
8 

Length

Max length4
Median length4
Mean length3.3043478
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 15
65.2%
기타 8
34.8%

Length

2024-05-11T14:36:29.418477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:29.630348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
65.2%
기타 8
34.8%

급수시설구분명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
상수도전용
4 

Length

Max length5
Median length4
Mean length4.173913
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
상수도전용 4
 
17.4%

Length

2024-05-11T14:36:29.835908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:30.013602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
상수도전용 4
 
17.4%

총인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

본사종업원수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
14 
0
9 

Length

Max length4
Median length4
Mean length2.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 14
60.9%
0 9
39.1%

Length

2024-05-11T14:36:30.190910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:30.373910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
60.9%
0 9
39.1%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
14 
0
9 

Length

Max length4
Median length4
Mean length2.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 14
60.9%
0 9
39.1%

Length

2024-05-11T14:36:30.563028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:30.703497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
60.9%
0 9
39.1%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
14 
0
9 

Length

Max length4
Median length4
Mean length2.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 14
60.9%
0 9
39.1%

Length

2024-05-11T14:36:30.842782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:30.996431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
60.9%
0 9
39.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
14 
0
9 

Length

Max length4
Median length4
Mean length2.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 14
60.9%
0 9
39.1%

Length

2024-05-11T14:36:31.160518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:31.321882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
60.9%
0 9
39.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
17 
자가
4 
임대
2 

Length

Max length4
Median length4
Mean length3.4782609
Min length2

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> 17
73.9%
자가 4
 
17.4%
임대 2
 
8.7%

Length

2024-05-11T14:36:31.535198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:31.704974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
73.9%
자가 4
 
17.4%
임대 2
 
8.7%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
22 
0
 
1

Length

Max length4
Median length4
Mean length3.8695652
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
95.7%
0 1
 
4.3%

Length

2024-05-11T14:36:31.889807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:32.073490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
95.7%
0 1
 
4.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
22 
0
 
1

Length

Max length4
Median length4
Mean length3.8695652
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
95.7%
0 1
 
4.3%

Length

2024-05-11T14:36:32.267211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:32.435006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
95.7%
0 1
 
4.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)6.7%
Missing8
Missing (%)34.8%
Memory size178.0 B
False
15 
(Missing)
8 
ValueCountFrequency (%)
False 15
65.2%
(Missing) 8
34.8%
2024-05-11T14:36:32.556790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
0.0
13 
<NA>
8 
464.7
 
1
324.3
 
1

Length

Max length5
Median length3
Mean length3.5217391
Min length3

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row0.0
2nd row0.0
3rd row<NA>
4th row<NA>
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 13
56.5%
<NA> 8
34.8%
464.7 1
 
4.3%
324.3 1
 
4.3%

Length

2024-05-11T14:36:32.696351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:32.845084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 13
56.5%
na 8
34.8%
464.7 1
 
4.3%
324.3 1
 
4.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030200003020000-114-1996-0012619960718<NA>3폐업2폐업20060523<NA><NA><NA>02 7969135471.65140823서울특별시 용산구 보광동 260-6<NA><NA>(주)해태유통2003-08-12 00:00:00I2018-08-31 23:59:59.0기타식품판매업199899.635731447307.171452기타식품판매업<NA><NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130200003020000-114-1996-0017519960628<NA>3폐업2폐업20040312<NA><NA><NA>02 8208526485.00140860서울특별시 용산구 이태원동 22-2 지하<NA><NA>(주)메가마트2004-10-13 00:00:00I2018-08-31 23:59:59.0기타식품판매업199471.30975447522.747031기타식품판매업00아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230200003020000-114-1996-001771996-07-18<NA>1영업/정상1영업<NA><NA><NA><NA>02 207728003300.00140-873서울특별시 용산구 한강로2가 15-19서울특별시 용산구 청파로 122 (한강로2가)4371(주)농협유통하나로클럽용산점2023-04-04 15:53:59U2022-12-04 00:06:00.0기타식품판매업196813.258497447881.970772<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
330200003020000-114-1996-0018919960718<NA>3폐업2폐업20221011<NA><NA><NA>02 7981652845.00140026서울특별시 용산구 용산동6가 69-167 지하서울특별시 용산구 이촌로 352 (용산동6가,지하)4428롯데쇼핑(주)롯데수퍼신동아점2022-10-11 11:46:28U2021-10-30 23:03:00.0기타식품판매업198622.89265446114.155239<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430200003020000-114-1996-0022019960718<NA>3폐업2폐업20010731<NA><NA><NA>02 7922981646.00140865서울특별시 용산구 이태원동 128-4<NA><NA>해태유통이태원영업소2001-07-31 00:00:00I2018-08-31 23:59:59.0기타식품판매업199375.725958447994.259776기타식품판매업<NA><NA>유흥업소밀집지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530200003020000-114-1996-0022119960718<NA>3폐업2폐업20100603<NA><NA><NA>02 7023313437.00140893서울특별시 용산구 한남동 726-173<NA><NA>한남슈퍼마켓2009-01-21 10:52:55I2018-08-31 23:59:59.0기타식품판매업200340.875562448624.224229기타식품판매업00주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630200003020000-114-1997-0017619971103<NA>3폐업2폐업20061103<NA><NA><NA>02 7951074744.00140842서울특별시 용산구 용산동2가 47-17<NA><NA>킴스클럽남산점2003-08-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업198776.047173448620.768801기타식품판매업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730200003020000-114-1999-0010919990517<NA>3폐업2폐업20020807<NA><NA><NA>02 7904162322.74140854서울특별시 용산구 이촌동 302-52 엘지프라자 지하동<NA><NA>럭키수퍼마켓2002-02-02 00:00:00I2018-08-31 23:59:59.0기타식품판매업197221.439324446524.508386기타식품판매업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830200003020000-114-2001-0034920010326<NA>3폐업2폐업20121022<NA><NA><NA>02 70446811,073.75140040서울특별시 용산구 산천동 6-0 삼성a단지상가 지하1<NA><NA>수협바다마트원효점2012-03-20 16:49:10I2018-08-31 23:59:59.0기타식품판매업<NA><NA>기타식품판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930200003020000-114-2001-0038520010806<NA>1영업/정상1영업<NA><NA><NA><NA>02 7971803627.00140865서울특별시 용산구 이태원동 128-4 외1필지(128-5)서울특별시 용산구 보광로 127 (이태원동,외1필지(128-5))4391홈마트2019-05-02 09:38:30U2019-05-04 02:40:00.0기타식품판매업199375.725958447994.259776기타식품판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1330200003020000-114-2007-0000120070912<NA>3폐업2폐업20150210<NA><NA><NA>0207553553392.00140899서울특별시 용산구 후암동 55-50서울특별시 용산구 후암로28길 21 (후암동)4330럭키진흥마트2009-02-05 15:48:47I2018-08-31 23:59:59.0기타식품판매업198043.461924449732.012464기타식품판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
1430200003020000-114-2010-000012010-10-18<NA>1영업/정상1영업<NA><NA><NA><NA>02 7115602782.68140-111서울특별시 용산구 원효로1가 133-3 리첸시아용산 에이동 지하1층(101~111, 126호)서울특별시 용산구 백범로 341 (원효로1가,리첸시아용산 에이동 지하1층(101~111, 126호))4315롯데쇼핑(주)롯데슈퍼 원효로점2023-05-25 10:33:23U2022-12-04 22:07:00.0기타식품판매업197045.849468448447.558967<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1530200003020000-114-2011-0000120110414<NA>3폐업2폐업20181226<NA><NA><NA>02 7979992849.72140866서울특별시 용산구 이태원동 181-8 외3필지 (지하1층)서울특별시 용산구 이태원로15길 1 (이태원동,외3필지 (지하1층))4351주-홈베이스마켓2018-12-26 16:17:25U2018-12-28 02:40:00.0기타식품판매업199061.591994448038.185766기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
1630200003020000-114-2011-0000220110523<NA>3폐업2폐업20181123<NA><NA><NA>02 7985601377.00140210서울특별시 용산구 한남동 810 (지하1층)서울특별시 용산구 독서당로 111 (한남동,(지하1층))4419롯데쇼핑(주)롯데슈퍼한남더힐점2018-11-23 16:50:53U2018-11-25 02:37:30.0기타식품판매업200769.10635448302.321865기타식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
1730200003020000-114-2012-000012012-01-06<NA>1영업/정상1영업<NA><NA><NA><NA>02 7928542323.10140-884서울특별시 용산구 한남동 26-5 (지하2층)서울특별시 용산구 유엔빌리지길 11 (한남동, 26-5 지하2층)4420홈플러스익스프레스한남점2024-03-19 16:08:23U2023-12-02 22:01:00.0기타식품판매업200846.604537447970.331605<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1830200003020000-114-2013-000012013-09-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 70446811088.19140-040서울특별시 용산구 산천동 202 외 2필지(지하1층)서울특별시 용산구 원효로 51 (산천동, 외 2필지(지하1층))4359수협바다마트 원효점2024-04-22 13:42:36U2023-12-03 22:04:00.0기타식품판매업195547.140326447976.77594<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1930200003020000-114-2015-0000120150210<NA>1영업/정상1영업<NA><NA><NA><NA>02 755 3553464.70140899서울특별시 용산구 후암동 55-50 지하1층, 지상1층서울특별시 용산구 후암로28길 21 (후암동, 지상1층, 지하1층)4330진흥마트2015-03-02 17:36:37I2018-08-31 23:59:59.0기타식품판매업198043.461924449732.012464기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N464.7<NA><NA><NA>
2030200003020000-114-2016-0000120160322<NA>3폐업2폐업20190122<NA><NA><NA>0232739988324.30140850서울특별시 용산구 원효로4가 118-16 외2필지, 지층서울특별시 용산구 원효로 64, 지층 (원효로4가)4365소비자할인마트2019-01-22 17:28:57U2019-01-24 02:40:00.0기타식품판매업195544.606275447831.138116기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N324.3<NA><NA><NA>
2130200003020000-114-2020-000012020-03-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 69054975808.49140-210서울특별시 용산구 한남동 829 나인원 한남서울특별시 용산구 한남대로 91, 지2층 (한남동, 나인원 한남)4401한화갤러리아(주) 고메이494한남점2023-11-16 15:15:46U2022-10-31 23:08:00.0기타식품판매업200231.538141448226.481351<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2230200003020000-114-2022-000012022-08-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>321.65140-854서울특별시 용산구 이촌동 302-52 LG프라자 지하1층서울특별시 용산구 이촌로 200, LG프라자 지하1층 지101호,지102호,지103호,지121호 (이촌동)4427지에스더프레시(GS THE FRESH) 용산이촌점2023-02-21 10:52:32U2022-12-01 22:03:00.0기타식품판매업197221.439324446524.508386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>