Overview

Dataset statistics

Number of variables44
Number of observations224
Missing cells1899
Missing cells (%)19.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory82.4 KiB
Average record size in memory376.6 B

Variable types

Categorical22
Text7
DateTime3
Unsupported7
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18225/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (53.7%)Imbalance
남성종사자수 is highly imbalanced (85.4%)Imbalance
여성종사자수 is highly imbalanced (85.4%)Imbalance
영업장주변구분명 is highly imbalanced (89.2%)Imbalance
등급구분명 is highly imbalanced (88.9%)Imbalance
급수시설구분명 is highly imbalanced (50.9%)Imbalance
총인원 is highly imbalanced (89.7%)Imbalance
공장사무직종업원수 is highly imbalanced (53.3%)Imbalance
시설총규모 is highly imbalanced (68.2%)Imbalance
인허가취소일자 has 224 (100.0%) missing valuesMissing
폐업일자 has 100 (44.6%) missing valuesMissing
휴업시작일자 has 224 (100.0%) missing valuesMissing
휴업종료일자 has 224 (100.0%) missing valuesMissing
재개업일자 has 224 (100.0%) missing valuesMissing
전화번호 has 77 (34.4%) missing valuesMissing
소재지면적 has 8 (3.6%) missing valuesMissing
도로명주소 has 55 (24.6%) missing valuesMissing
도로명우편번호 has 57 (25.4%) missing valuesMissing
좌표정보(X) has 6 (2.7%) missing valuesMissing
좌표정보(Y) has 6 (2.7%) missing valuesMissing
다중이용업소여부 has 22 (9.8%) missing valuesMissing
전통업소지정번호 has 224 (100.0%) missing valuesMissing
전통업소주된음식 has 224 (100.0%) missing valuesMissing
홈페이지 has 224 (100.0%) missing valuesMissing
관리번호 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
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 08:32:37.155014
Analysis finished2024-05-11 08:32:38.714633
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3230000
224 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 224
100.0%

Length

2024-05-11T08:32:38.947901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:39.492456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 224
100.0%

관리번호
Text

UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:32:39.925101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4928
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

Unique224 ?
Unique (%)100.0%

Sample

1st row3230000-117-1990-00239
2nd row3230000-117-1991-00240
3rd row3230000-117-1991-00241
4th row3230000-117-1992-00242
5th row3230000-117-1997-00243
ValueCountFrequency (%)
3230000-117-1990-00239 1
 
0.4%
3230000-117-1991-00240 1
 
0.4%
3230000-117-2013-00006 1
 
0.4%
3230000-117-2012-00011 1
 
0.4%
3230000-117-2012-00012 1
 
0.4%
3230000-117-2012-00013 1
 
0.4%
3230000-117-2012-00014 1
 
0.4%
3230000-117-2012-00015 1
 
0.4%
3230000-117-2012-00016 1
 
0.4%
3230000-117-2013-00001 1
 
0.4%
Other values (214) 214
95.5%
2024-05-11T08:32:40.861696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2074
42.1%
- 672
 
13.6%
1 639
 
13.0%
2 539
 
10.9%
3 510
 
10.3%
7 273
 
5.5%
4 64
 
1.3%
5 43
 
0.9%
6 43
 
0.9%
8 36
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4256
86.4%
Dash Punctuation 672
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2074
48.7%
1 639
 
15.0%
2 539
 
12.7%
3 510
 
12.0%
7 273
 
6.4%
4 64
 
1.5%
5 43
 
1.0%
6 43
 
1.0%
8 36
 
0.8%
9 35
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4928
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2074
42.1%
- 672
 
13.6%
1 639
 
13.0%
2 539
 
10.9%
3 510
 
10.3%
7 273
 
5.5%
4 64
 
1.3%
5 43
 
0.9%
6 43
 
0.9%
8 36
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4928
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2074
42.1%
- 672
 
13.6%
1 639
 
13.0%
2 539
 
10.9%
3 510
 
10.3%
7 273
 
5.5%
4 64
 
1.3%
5 43
 
0.9%
6 43
 
0.9%
8 36
 
0.7%

인허가일자
Date

Distinct210
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1990-12-20 00:00:00
Maximum2024-04-17 00:00:00
2024-05-11T08:32:41.299928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:32:41.724957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
124 
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 124
55.4%
1 100
44.6%

Length

2024-05-11T08:32:42.120053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:42.511384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 124
55.4%
1 100
44.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
124 
영업/정상
100 

Length

Max length5
Median length2
Mean length3.3392857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 124
55.4%
영업/정상 100
44.6%

Length

2024-05-11T08:32:42.753262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:43.095818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 124
55.4%
영업/정상 100
44.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2
124 
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 124
55.4%
1 100
44.6%

Length

2024-05-11T08:32:43.442222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:43.758888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 124
55.4%
1 100
44.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
124 
영업
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 124
55.4%
영업 100
44.6%

Length

2024-05-11T08:32:44.125375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:32:44.472380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 124
55.4%
영업 100
44.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)75.0%
Missing100
Missing (%)44.6%
Infinite0
Infinite (%)0.0%
Mean20129492
Minimum19970329
Maximum20221006
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:32:44.843002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970329
5-th percentile20050320
Q120080778
median20140771
Q320163452
95-th percentile20201027
Maximum20221006
Range250677
Interquartile range (IQR)82673.75

Descriptive statistics

Standard deviation57510.751
Coefficient of variation (CV)0.0028570394
Kurtosis0.087595259
Mean20129492
Median Absolute Deviation (MAD)39850
Skewness-0.72070358
Sum2.496057 × 109
Variance3.3074865 × 109
MonotonicityNot monotonic
2024-05-11T08:32:45.451425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161223 18
 
8.0%
20060831 6
 
2.7%
20050905 4
 
1.8%
19980701 3
 
1.3%
20151202 2
 
0.9%
20140919 2
 
0.9%
20061117 2
 
0.9%
20070720 2
 
0.9%
20120117 1
 
0.4%
20160108 1
 
0.4%
Other values (83) 83
37.1%
(Missing) 100
44.6%
ValueCountFrequency (%)
19970329 1
 
0.4%
19971107 1
 
0.4%
19980701 3
1.3%
20041101 1
 
0.4%
20050217 1
 
0.4%
20050905 4
1.8%
20051215 1
 
0.4%
20060316 1
 
0.4%
20060831 6
2.7%
20061110 1
 
0.4%
ValueCountFrequency (%)
20221006 1
0.4%
20220927 1
0.4%
20220103 1
0.4%
20210511 1
0.4%
20210416 1
0.4%
20201229 1
0.4%
20201029 1
0.4%
20201013 1
0.4%
20200904 1
0.4%
20200828 1
0.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

전화번호
Text

MISSING 

Distinct140
Distinct (%)95.2%
Missing77
Missing (%)34.4%
Memory size1.9 KiB
2024-05-11T08:32:46.068723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.959184
Min length8

Characters and Unicode

Total characters1611
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

Unique134 ?
Unique (%)91.2%

Sample

1st row02 4092104
2nd row02 4829223
3rd row02 4751940
4th row02 4249811
5th row02 4086200
ValueCountFrequency (%)
02 113
35.4%
031 5
 
1.6%
070 5
 
1.6%
401 5
 
1.6%
26310160 3
 
0.9%
425 2
 
0.6%
449 2
 
0.6%
430 2
 
0.6%
418 2
 
0.6%
400 2
 
0.6%
Other values (167) 178
55.8%
2024-05-11T08:32:47.034391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 316
19.6%
2 251
15.6%
233
14.5%
4 193
12.0%
3 119
 
7.4%
1 117
 
7.3%
5 83
 
5.2%
7 82
 
5.1%
9 78
 
4.8%
8 74
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1378
85.5%
Space Separator 233
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 316
22.9%
2 251
18.2%
4 193
14.0%
3 119
 
8.6%
1 117
 
8.5%
5 83
 
6.0%
7 82
 
6.0%
9 78
 
5.7%
8 74
 
5.4%
6 65
 
4.7%
Space Separator
ValueCountFrequency (%)
233
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1611
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 316
19.6%
2 251
15.6%
233
14.5%
4 193
12.0%
3 119
 
7.4%
1 117
 
7.3%
5 83
 
5.2%
7 82
 
5.1%
9 78
 
4.8%
8 74
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1611
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 316
19.6%
2 251
15.6%
233
14.5%
4 193
12.0%
3 119
 
7.4%
1 117
 
7.3%
5 83
 
5.2%
7 82
 
5.1%
9 78
 
4.8%
8 74
 
4.6%

소재지면적
Text

MISSING 

Distinct134
Distinct (%)62.0%
Missing8
Missing (%)3.6%
Memory size1.9 KiB
2024-05-11T08:32:47.783095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0694444
Min length3

Characters and Unicode

Total characters1095
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

Unique102 ?
Unique (%)47.2%

Sample

1st row5.40
2nd row27.30
3rd row27.30
4th row79.80
5th row15.00
ValueCountFrequency (%)
33.00 12
 
5.6%
66.00 11
 
5.1%
10.00 11
 
5.1%
60.00 6
 
2.8%
3.30 5
 
2.3%
24.00 4
 
1.9%
15.00 4
 
1.9%
90.00 4
 
1.9%
20.00 3
 
1.4%
45.00 3
 
1.4%
Other values (124) 153
70.8%
2024-05-11T08:32:48.913685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 360
32.9%
. 216
19.7%
3 85
 
7.8%
1 80
 
7.3%
6 73
 
6.7%
2 60
 
5.5%
9 53
 
4.8%
4 50
 
4.6%
5 49
 
4.5%
7 34
 
3.1%
Other values (2) 35
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 878
80.2%
Other Punctuation 217
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 360
41.0%
3 85
 
9.7%
1 80
 
9.1%
6 73
 
8.3%
2 60
 
6.8%
9 53
 
6.0%
4 50
 
5.7%
5 49
 
5.6%
7 34
 
3.9%
8 34
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 216
99.5%
, 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 1095
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 360
32.9%
. 216
19.7%
3 85
 
7.8%
1 80
 
7.3%
6 73
 
6.7%
2 60
 
5.5%
9 53
 
4.8%
4 50
 
4.6%
5 49
 
4.5%
7 34
 
3.1%
Other values (2) 35
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 360
32.9%
. 216
19.7%
3 85
 
7.8%
1 80
 
7.3%
6 73
 
6.7%
2 60
 
5.5%
9 53
 
4.8%
4 50
 
4.6%
5 49
 
4.5%
7 34
 
3.1%
Other values (2) 35
 
3.2%

소재지우편번호
Text

Distinct68
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:32:49.455485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0401786
Min length6

Characters and Unicode

Total characters1353
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

Unique32 ?
Unique (%)14.3%

Sample

1st row138160
2nd row138874
3rd row138874
4th row138160
5th row138160
ValueCountFrequency (%)
138881 32
 
14.3%
138200 13
 
5.8%
138888 13
 
5.8%
138806 10
 
4.5%
138858 7
 
3.1%
138802 6
 
2.7%
138828 6
 
2.7%
138857 6
 
2.7%
138803 6
 
2.7%
138805 6
 
2.7%
Other values (58) 119
53.1%
2024-05-11T08:32:50.508106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 505
37.3%
1 284
21.0%
3 247
18.3%
0 98
 
7.2%
2 48
 
3.5%
5 43
 
3.2%
4 39
 
2.9%
6 30
 
2.2%
7 27
 
2.0%
9 23
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1344
99.3%
Dash Punctuation 9
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 505
37.6%
1 284
21.1%
3 247
18.4%
0 98
 
7.3%
2 48
 
3.6%
5 43
 
3.2%
4 39
 
2.9%
6 30
 
2.2%
7 27
 
2.0%
9 23
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1353
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 505
37.3%
1 284
21.0%
3 247
18.3%
0 98
 
7.2%
2 48
 
3.5%
5 43
 
3.2%
4 39
 
2.9%
6 30
 
2.2%
7 27
 
2.0%
9 23
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1353
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 505
37.3%
1 284
21.0%
3 247
18.3%
0 98
 
7.2%
2 48
 
3.5%
5 43
 
3.2%
4 39
 
2.9%
6 30
 
2.2%
7 27
 
2.0%
9 23
 
1.7%

지번주소
Text

Distinct175
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:32:51.280174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length26.620536
Min length18

Characters and Unicode

Total characters5963
Distinct characters164
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

Unique141 ?
Unique (%)62.9%

Sample

1st row서울특별시 송파구 가락동 산 ***-*번지 가락유통쎈
2nd row서울특별시 송파구 풍납동 ***-*번지
3rd row서울특별시 송파구 풍납동 ***-*번지
4th row서울특별시 송파구 가락동 산 ***-*번지 축산시장 *층호
5th row서울특별시 송파구 가락동 산 ***-*번지
ValueCountFrequency (%)
서울특별시 223
19.5%
송파구 223
19.5%
번지 173
15.1%
가락동 97
8.5%
61
 
5.3%
층 44
 
3.8%
호 38
 
3.3%
문정동 37
 
3.2%
지상*층 26
 
2.3%
오금동 22
 
1.9%
Other values (106) 200
17.5%
2024-05-11T08:32:52.803578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1106
18.5%
* 1073
18.0%
동 254
 
4.3%
파 246
 
4.1%
송 239
 
4.0%
시 238
 
4.0%
서 228
 
3.8%
울 227
 
3.8%
구 225
 
3.8%
별 223
 
3.7%
Other values (154) 1904
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3567
59.8%
Space Separator 1106
 
18.5%
Other Punctuation 1082
 
18.1%
Dash Punctuation 182
 
3.1%
Uppercase Letter 8
 
0.1%
Decimal Number 7
 
0.1%
Close Punctuation 5
 
0.1%
Open Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 254
 
7.1%
파 246
 
6.9%
송 239
 
6.7%
시 238
 
6.7%
서 228
 
6.4%
울 227
 
6.4%
구 225
 
6.3%
별 223
 
6.3%
특 223
 
6.3%
지 217
 
6.1%
Other values (137) 1247
35.0%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
4 2
28.6%
7 1
14.3%
9 1
14.3%
3 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
25.0%
B 2
25.0%
A 2
25.0%
K 1
12.5%
L 1
12.5%
Other Punctuation
ValueCountFrequency (%)
* 1073
99.2%
, 9
 
0.8%
Space Separator
ValueCountFrequency (%)
1106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3567
59.8%
Common 2388
40.0%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 254
 
7.1%
파 246
 
6.9%
송 239
 
6.7%
시 238
 
6.7%
서 228
 
6.4%
울 227
 
6.4%
구 225
 
6.3%
별 223
 
6.3%
특 223
 
6.3%
지 217
 
6.1%
Other values (137) 1247
35.0%
Common
ValueCountFrequency (%)
1106
46.3%
* 1073
44.9%
- 182
 
7.6%
, 9
 
0.4%
) 5
 
0.2%
( 5
 
0.2%
1 2
 
0.1%
4 2
 
0.1%
~ 1
 
< 0.1%
7 1
 
< 0.1%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
C 2
25.0%
B 2
25.0%
A 2
25.0%
K 1
12.5%
L 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3567
59.8%
ASCII 2396
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1106
46.2%
* 1073
44.8%
- 182
 
7.6%
, 9
 
0.4%
) 5
 
0.2%
( 5
 
0.2%
1 2
 
0.1%
4 2
 
0.1%
C 2
 
0.1%
B 2
 
0.1%
Other values (7) 8
 
0.3%
Hangul
ValueCountFrequency (%)
동 254
 
7.1%
파 246
 
6.9%
송 239
 
6.7%
시 238
 
6.7%
서 228
 
6.4%
울 227
 
6.4%
구 225
 
6.3%
별 223
 
6.3%
특 223
 
6.3%
지 217
 
6.1%
Other values (137) 1247
35.0%

도로명주소
Text

MISSING 

Distinct160
Distinct (%)94.7%
Missing55
Missing (%)24.6%
Memory size1.9 KiB
2024-05-11T08:32:53.543948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length35.213018
Min length23

Characters and Unicode

Total characters5951
Distinct characters173
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

Unique153 ?
Unique (%)90.5%

Sample

1st row서울특별시 송파구 양재대로 *** (가락동,주차건물동 *-*)
2nd row서울특별시 송파구 삼학사로 **, ***호 (석촌동, 보라빌딩)
3rd row서울특별시 송파구 중대로 ***-* (오금동,*층)
4th row서울특별시 송파구 송파대로 *** (석촌동,(***호))
5th row서울특별시 송파구 양재대로 *** (가락동,청과물시장동 *층 ***-*)
ValueCountFrequency (%)
173
15.4%
서울특별시 169
15.0%
송파구 169
15.0%
호 73
 
6.5%
층 51
 
4.5%
가락동 44
 
3.9%
지상*층 32
 
2.8%
문정동 29
 
2.6%
양재대로 25
 
2.2%
송파대로**길 14
 
1.2%
Other values (158) 346
30.8%
2024-05-11T08:32:54.918640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1008
16.9%
957
 
16.1%
동 225
 
3.8%
송 211
 
3.5%
파 208
 
3.5%
, 191
 
3.2%
시 185
 
3.1%
울 173
 
2.9%
서 173
 
2.9%
) 171
 
2.9%
Other values (163) 2449
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3363
56.5%
Other Punctuation 1199
 
20.1%
Space Separator 957
 
16.1%
Close Punctuation 171
 
2.9%
Open Punctuation 171
 
2.9%
Dash Punctuation 51
 
0.9%
Uppercase Letter 26
 
0.4%
Decimal Number 11
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 225
 
6.7%
송 211
 
6.3%
파 208
 
6.2%
시 185
 
5.5%
울 173
 
5.1%
서 173
 
5.1%
구 170
 
5.1%
별 169
 
5.0%
특 169
 
5.0%
로 169
 
5.0%
Other values (143) 1511
44.9%
Decimal Number
ValueCountFrequency (%)
2 4
36.4%
7 2
18.2%
5 1
 
9.1%
3 1
 
9.1%
4 1
 
9.1%
6 1
 
9.1%
1 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
A 14
53.8%
C 5
 
19.2%
B 4
 
15.4%
D 1
 
3.8%
L 1
 
3.8%
K 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
* 1008
84.1%
, 191
 
15.9%
Space Separator
ValueCountFrequency (%)
957
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3363
56.5%
Common 2562
43.1%
Latin 26
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 225
 
6.7%
송 211
 
6.3%
파 208
 
6.2%
시 185
 
5.5%
울 173
 
5.1%
서 173
 
5.1%
구 170
 
5.1%
별 169
 
5.0%
특 169
 
5.0%
로 169
 
5.0%
Other values (143) 1511
44.9%
Common
ValueCountFrequency (%)
* 1008
39.3%
957
37.4%
, 191
 
7.5%
) 171
 
6.7%
( 171
 
6.7%
- 51
 
2.0%
2 4
 
0.2%
7 2
 
0.1%
~ 2
 
0.1%
5 1
 
< 0.1%
Other values (4) 4
 
0.2%
Latin
ValueCountFrequency (%)
A 14
53.8%
C 5
 
19.2%
B 4
 
15.4%
D 1
 
3.8%
L 1
 
3.8%
K 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3363
56.5%
ASCII 2588
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1008
38.9%
957
37.0%
, 191
 
7.4%
) 171
 
6.6%
( 171
 
6.6%
- 51
 
2.0%
A 14
 
0.5%
C 5
 
0.2%
2 4
 
0.2%
B 4
 
0.2%
Other values (10) 12
 
0.5%
Hangul
ValueCountFrequency (%)
동 225
 
6.7%
송 211
 
6.3%
파 208
 
6.2%
시 185
 
5.5%
울 173
 
5.1%
서 173
 
5.1%
구 170
 
5.1%
별 169
 
5.0%
특 169
 
5.0%
로 169
 
5.0%
Other values (143) 1511
44.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct94
Distinct (%)56.3%
Missing57
Missing (%)25.4%
Infinite0
Infinite (%)0.0%
Mean5720.2874
Minimum5501
Maximum5855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:32:55.577235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5501
5-th percentile5548
Q15682.5
median5715
Q35803.5
95-th percentile5854
Maximum5855
Range354
Interquartile range (IQR)121

Descriptive statistics

Standard deviation87.889244
Coefficient of variation (CV)0.01536448
Kurtosis-0.3742131
Mean5720.2874
Median Absolute Deviation (MAD)59
Skewness-0.34293039
Sum955288
Variance7724.5193
MonotonicityNot monotonic
2024-05-11T08:32:56.114048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5699 24
 
10.7%
5854 10
 
4.5%
5719 6
 
2.7%
5548 4
 
1.8%
5744 3
 
1.3%
5722 3
 
1.3%
5829 3
 
1.3%
5686 3
 
1.3%
5842 3
 
1.3%
5806 3
 
1.3%
Other values (84) 105
46.9%
(Missing) 57
25.4%
ValueCountFrequency (%)
5501 1
 
0.4%
5510 1
 
0.4%
5526 1
 
0.4%
5533 1
 
0.4%
5537 1
 
0.4%
5544 1
 
0.4%
5545 1
 
0.4%
5548 4
1.8%
5549 2
0.9%
5573 1
 
0.4%
ValueCountFrequency (%)
5855 1
 
0.4%
5854 10
4.5%
5842 3
 
1.3%
5841 2
 
0.9%
5838 1
 
0.4%
5836 2
 
0.9%
5832 2
 
0.9%
5831 2
 
0.9%
5829 3
 
1.3%
5826 2
 
0.9%

사업장명
Text

Distinct217
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T08:32:56.980531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.2053571
Min length2

Characters and Unicode

Total characters1614
Distinct characters234
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique210 ?
Unique (%)93.8%

Sample

1st row정육백화점
2nd row펑안화물
3rd row평안화물
4th row우주특수산업(주)
5th row한국축산유통
ValueCountFrequency (%)
주식회사 11
 
4.4%
농업회사법인 4
 
1.6%
혜인푸드라인(주 2
 
0.8%
주)코리아넷운수 2
 
0.8%
주 2
 
0.8%
푸드월드 2
 
0.8%
혜영푸드 2
 
0.8%
서울유통 2
 
0.8%
남양로지스 2
 
0.8%
올후드 2
 
0.8%
Other values (220) 221
87.7%
2024-05-11T08:32:58.238968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 134
 
8.3%
) 122
 
7.6%
( 120
 
7.4%
드 53
 
3.3%
스 49
 
3.0%
푸 43
 
2.7%
유 38
 
2.4%
이 34
 
2.1%
통 33
 
2.0%
산 32
 
2.0%
Other values (224) 956
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1339
83.0%
Close Punctuation 122
 
7.6%
Open Punctuation 120
 
7.4%
Space Separator 28
 
1.7%
Uppercase Letter 4
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 134
 
10.0%
드 53
 
4.0%
스 49
 
3.7%
푸 43
 
3.2%
유 38
 
2.8%
이 34
 
2.5%
통 33
 
2.5%
산 32
 
2.4%
지 30
 
2.2%
식 29
 
2.2%
Other values (216) 864
64.5%
Uppercase Letter
ValueCountFrequency (%)
J 1
25.0%
H 1
25.0%
F 1
25.0%
G 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1339
83.0%
Common 271
 
16.8%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 134
 
10.0%
드 53
 
4.0%
스 49
 
3.7%
푸 43
 
3.2%
유 38
 
2.8%
이 34
 
2.5%
통 33
 
2.5%
산 32
 
2.4%
지 30
 
2.2%
식 29
 
2.2%
Other values (216) 864
64.5%
Common
ValueCountFrequency (%)
) 122
45.0%
( 120
44.3%
28
 
10.3%
1 1
 
0.4%
Latin
ValueCountFrequency (%)
J 1
25.0%
H 1
25.0%
F 1
25.0%
G 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1339
83.0%
ASCII 275
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 134
 
10.0%
드 53
 
4.0%
스 49
 
3.7%
푸 43
 
3.2%
유 38
 
2.8%
이 34
 
2.5%
통 33
 
2.5%
산 32
 
2.4%
지 30
 
2.2%
식 29
 
2.2%
Other values (216) 864
64.5%
ASCII
ValueCountFrequency (%)
) 122
44.4%
( 120
43.6%
28
 
10.2%
1 1
 
0.4%
J 1
 
0.4%
H 1
 
0.4%
F 1
 
0.4%
G 1
 
0.4%

최종수정일자
Date

Distinct209
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2002-09-04 00:00:00
Maximum2024-04-17 10:58:43
2024-05-11T08:32:58.672686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:32:59.170226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
I
170 
U
54 

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 170
75.9%
U 54
 
24.1%

Length

2024-05-11T08:32:59.665139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:00.130739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 170
75.9%
u 54
 
24.1%

데이터갱신일자
Date

Distinct71
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-05-11T08:33:00.663338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:33:01.259049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
식품운반업
224 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 224
100.0%

Length

2024-05-11T08:33:01.874650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:02.357300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 224
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)68.8%
Missing6
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean210585.22
Minimum206835.85
Maximum213877.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:33:02.986579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206835.85
5-th percentile209238.13
Q1209790.96
median210558
Q3211184.39
95-th percentile212513.17
Maximum213877.92
Range7042.0659
Interquartile range (IQR)1393.4301

Descriptive statistics

Standard deviation1082.3097
Coefficient of variation (CV)0.0051395331
Kurtosis1.0076277
Mean210585.22
Median Absolute Deviation (MAD)767.04009
Skewness0.036331669
Sum45907578
Variance1171394.3
MonotonicityNot monotonic
2024-05-11T08:33:03.688543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.959909032 33
 
14.7%
210558.0 6
 
2.7%
210491.321883503 4
 
1.8%
210857.0 3
 
1.3%
209509.155143836 3
 
1.3%
210663.629938729 3
 
1.3%
212076.099510353 2
 
0.9%
210969.894988622 2
 
0.9%
209659.734134742 2
 
0.9%
210414.919309988 2
 
0.9%
Other values (140) 158
70.5%
(Missing) 6
 
2.7%
ValueCountFrequency (%)
206835.849181736 1
0.4%
207227.601437566 1
0.4%
207373.50021477 1
0.4%
207901.982417098 1
0.4%
208442.334997138 1
0.4%
208516.391912451 1
0.4%
208538.456869611 1
0.4%
208650.639642801 1
0.4%
208678.389125238 1
0.4%
209077.957661492 1
0.4%
ValueCountFrequency (%)
213877.915058256 1
0.4%
213228.378235527 1
0.4%
213212.586749809 2
0.9%
213143.588011 1
0.4%
212806.540625753 1
0.4%
212733.273968195 1
0.4%
212645.539631084 1
0.4%
212617.339496289 1
0.4%
212613.538466293 1
0.4%
212548.84493652 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct150
Distinct (%)68.8%
Missing6
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean443991.78
Minimum441446
Maximum447967.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T08:33:04.233130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441446
5-th percentile442225.25
Q1443438.83
median443787.69
Q3444593.24
95-th percentile445753.25
Maximum447967.68
Range6521.68
Interquartile range (IQR)1154.4143

Descriptive statistics

Standard deviation1204.2834
Coefficient of variation (CV)0.0027124002
Kurtosis1.5022768
Mean443991.78
Median Absolute Deviation (MAD)632.74928
Skewness0.78061574
Sum96790207
Variance1450298.4
MonotonicityNot monotonic
2024-05-11T08:33:04.857774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443481.212174317 33
 
14.7%
442587.0 6
 
2.7%
443569.763243482 4
 
1.8%
441446.0 3
 
1.3%
445702.432655116 3
 
1.3%
443227.768393636 3
 
1.3%
444516.528609397 2
 
0.9%
444593.375332437 2
 
0.9%
445534.533151158 2
 
0.9%
444081.432070039 2
 
0.9%
Other values (140) 158
70.5%
(Missing) 6
 
2.7%
ValueCountFrequency (%)
441446.0 3
1.3%
441537.243988221 1
 
0.4%
441621.092 1
 
0.4%
441725.293491662 1
 
0.4%
441996.227705236 2
0.9%
442106.154785377 1
 
0.4%
442163.308563343 2
0.9%
442236.177915237 1
 
0.4%
442338.115571068 1
 
0.4%
442352.745053247 1
 
0.4%
ValueCountFrequency (%)
447967.680010779 2
0.9%
447961.830409897 1
0.4%
447855.177758717 1
0.4%
447646.739364029 1
0.4%
447370.765004276 1
0.4%
447341.670834952 1
0.4%
446156.529775445 1
0.4%
446083.728440268 1
0.4%
445960.615515654 1
0.4%
445935.092530909 1
0.4%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
식품운반업
202 
<NA>
22 

Length

Max length5
Median length5
Mean length4.9017857
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 202
90.2%
<NA> 22
 
9.8%

Length

2024-05-11T08:33:05.533153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:06.004053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 202
90.2%
na 22
 
9.8%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
217 
0
 
4
1
 
3

Length

Max length4
Median length4
Mean length3.90625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 217
96.9%
0 4
 
1.8%
1 3
 
1.3%

Length

2024-05-11T08:33:06.484540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:06.978924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
96.9%
0 4
 
1.8%
1 3
 
1.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
217 
0
 
4
1
 
3

Length

Max length4
Median length4
Mean length3.90625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 217
96.9%
0 4
 
1.8%
1 3
 
1.3%

Length

2024-05-11T08:33:07.395697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:07.830097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
96.9%
0 4
 
1.8%
1 3
 
1.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
219 
주택가주변
 
4
기타
 
1

Length

Max length5
Median length4
Mean length4.0089286
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row기타
2nd row주택가주변
3rd row주택가주변
4th row주택가주변
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 219
97.8%
주택가주변 4
 
1.8%
기타 1
 
0.4%

Length

2024-05-11T08:33:08.239700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:08.700760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
97.8%
주택가주변 4
 
1.8%
기타 1
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
219 
을
 
3
우수
 
2

Length

Max length4
Median length4
Mean length3.9419643
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row을
2nd row을
3rd row을
4th row우수
5th row우수

Common Values

ValueCountFrequency (%)
<NA> 219
97.8%
을 3
 
1.3%
우수 2
 
0.9%

Length

2024-05-11T08:33:09.006008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:09.407546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
97.8%
을 3
 
1.3%
우수 2
 
0.9%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
200 
상수도전용
24 

Length

Max length5
Median length4
Mean length4.1071429
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 200
89.3%
상수도전용 24
 
10.7%

Length

2024-05-11T08:33:09.878485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:10.369061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
89.3%
상수도전용 24
 
10.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
221 
0
 
3

Length

Max length4
Median length4
Mean length3.9598214
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> 221
98.7%
0 3
 
1.3%

Length

2024-05-11T08:33:10.718013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:11.075038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 221
98.7%
0 3
 
1.3%

본사종업원수
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
131 
0
91 
8
 
1
5
 
1

Length

Max length4
Median length4
Mean length2.7544643
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 131
58.5%
0 91
40.6%
8 1
 
0.4%
5 1
 
0.4%

Length

2024-05-11T08:33:11.609443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:12.068391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
58.5%
0 91
40.6%
8 1
 
0.4%
5 1
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
132 
0
89 
1
 
1
18
 
1
130
 
1

Length

Max length4
Median length4
Mean length2.78125
Min length1

Unique

Unique3 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
58.9%
0 89
39.7%
1 1
 
0.4%
18 1
 
0.4%
130 1
 
0.4%

Length

2024-05-11T08:33:12.723815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:13.241790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 132
58.9%
0 89
39.7%
1 1
 
0.4%
18 1
 
0.4%
130 1
 
0.4%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
133 
0
91 

Length

Max length4
Median length4
Mean length2.78125
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> 133
59.4%
0 91
40.6%

Length

2024-05-11T08:33:13.754577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:14.083010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 133
59.4%
0 91
40.6%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
133 
0
91 

Length

Max length4
Median length4
Mean length2.78125
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> 133
59.4%
0 91
40.6%

Length

2024-05-11T08:33:14.562063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:14.967695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 133
59.4%
0 91
40.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
임대
105 
자가
74 
<NA>
45 

Length

Max length4
Median length2
Mean length2.4017857
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 (%)
임대 105
46.9%
자가 74
33.0%
<NA> 45
20.1%

Length

2024-05-11T08:33:15.620979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:16.079728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 105
46.9%
자가 74
33.0%
na 45
20.1%

보증액
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
147 
0
76 
10000000
 
1

Length

Max length8
Median length4
Mean length3
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
65.6%
0 76
33.9%
10000000 1
 
0.4%

Length

2024-05-11T08:33:16.502228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:17.167759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
65.6%
0 76
33.9%
10000000 1
 
0.4%

월세액
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
147 
0
76 
500000
 
1

Length

Max length6
Median length4
Mean length2.9910714
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
65.6%
0 76
33.9%
500000 1
 
0.4%

Length

2024-05-11T08:33:17.608994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:18.032925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
65.6%
0 76
33.9%
500000 1
 
0.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing22
Missing (%)9.8%
Memory size580.0 B
False
202 
(Missing)
22 
ValueCountFrequency (%)
False 202
90.2%
(Missing) 22
 
9.8%
2024-05-11T08:33:18.470517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
0.0
201 
<NA>
22 
10.6
 
1

Length

Max length4
Median length3
Mean length3.1026786
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 201
89.7%
<NA> 22
 
9.8%
10.6 1
 
0.4%

Length

2024-05-11T08:33:18.835425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:33:19.202435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 201
89.7%
na 22
 
9.8%
10.6 1
 
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing224
Missing (%)100.0%
Memory size2.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032300003230000-117-1990-0023919901220<NA>3폐업2폐업19971107<NA><NA><NA>02 40921045.40138160서울특별시 송파구 가락동 산 ***-*번지 가락유통쎈<NA><NA>정육백화점2002-09-04 00:00:00I2018-08-31 23:59:59.0식품운반업<NA><NA>식품운반업<NA><NA>기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132300003230000-117-1991-0024019911224<NA>3폐업2폐업19970329<NA><NA><NA>02 482922327.30138874서울특별시 송파구 풍납동 ***-*번지<NA><NA>펑안화물2002-09-04 00:00:00I2018-08-31 23:59:59.0식품운반업210318.643338447967.680011식품운반업11주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232300003230000-117-1991-0024119911224<NA>3폐업2폐업19980701<NA><NA><NA>02 475194027.30138874서울특별시 송파구 풍납동 ***-*번지<NA><NA>평안화물2002-09-04 00:00:00I2018-08-31 23:59:59.0식품운반업210318.643338447967.680011식품운반업11주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332300003230000-117-1992-0024219921208<NA>3폐업2폐업19980701<NA><NA><NA>02 424981179.80138160서울특별시 송파구 가락동 산 ***-*번지 축산시장 *층호<NA><NA>우주특수산업(주)2002-09-04 00:00:00I2018-08-31 23:59:59.0식품운반업<NA><NA>식품운반업11주택가주변우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432300003230000-117-1997-0024319970804<NA>3폐업2폐업19980701<NA><NA><NA>02 408620015.00138160서울특별시 송파구 가락동 산 ***-*번지<NA><NA>한국축산유통2002-09-04 00:00:00I2018-08-31 23:59:59.0식품운반업<NA><NA>식품운반업<NA><NA>주택가주변우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532300003230000-117-1997-0024419970617<NA>1영업/정상1영업<NA><NA><NA><NA>0234020011<NA>138881서울특별시 송파구 가락동 ***번지 주차건물동 *-*서울특별시 송파구 양재대로 *** (가락동,주차건물동 *-*)5699(주)성한유통2006-08-14 00:00:00I2018-08-31 23:59:59.0식품운반업209790.959909443481.212174식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
632300003230000-117-2003-0000120030808<NA>3폐업2폐업20130401<NA><NA><NA>023401643650.00138857서울특별시 송파구 오금동 **-*번지<NA><NA>(주)대영에이앤지2003-08-08 00:00:00I2018-08-31 23:59:59.0식품운반업211902.402445444554.819769식품운반업<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
732300003230000-117-2003-0000220030827<NA>3폐업2폐업20060316<NA><NA><NA>02 4001531180.00138804서울특별시 송파구 가락동 **-*번지 한서제약*층<NA><NA>혜인푸드라인(주)2003-08-27 00:00:00I2018-08-31 23:59:59.0식품운반업210310.209196444051.533056식품운반업<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
832300003230000-117-2003-0000320030919<NA>3폐업2폐업20080804<NA><NA><NA>02 473003450.00138874서울특별시 송파구 풍납동 ***-**번지<NA><NA>삼원식품2003-09-19 00:00:00I2018-08-31 23:59:59.0식품운반업209886.805202447646.739364식품운반업<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
932300003230000-117-2003-0000420031002<NA>3폐업2폐업20050217<NA><NA><NA><NA>120.00138826서울특별시 송파구 문정동 **번지 지하*층<NA><NA>(주)푸드랜드2003-10-02 00:00:00I2018-08-31 23:59:59.0식품운반업210972.819748442577.449769식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
21432300003230000-117-2022-0000220220525<NA>1영업/정상1영업<NA><NA><NA><NA>02 2631016034.50138888서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 A동 *층 ***호 (문정동)5854(주)우정로지텍2022-05-25 12:15:59I2021-12-04 22:07:00.0식품운반업210558.0442587.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21532300003230000-117-2022-0000320220525<NA>1영업/정상1영업<NA><NA><NA><NA>02 2631016034.50138888서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 A동 *층 ***호 (문정동)5854(주)다성제이앤제이2022-05-25 12:25:22I2021-12-04 22:07:00.0식품운반업210558.0442587.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21632300003230000-117-2022-0000420220525<NA>1영업/정상1영업<NA><NA><NA><NA>02 2361016034.50138888서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 A동 *층 ***호 (문정동)5854(주)청현운수2022-05-25 13:26:23I2021-12-04 22:07:00.0식품운반업210558.0442587.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21732300003230000-117-2022-0000520220603<NA>1영업/정상1영업<NA><NA><NA><NA>02 6080363933.00138807서울특별시 송파구 가락동 ***-*서울특별시 송파구 동남로 ***, *층 ***호 (가락동)5826(주)월드유니온코포레애션2022-06-03 17:49:05I2021-12-06 00:08:00.0식품운반업211286.216815443423.838214<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21832300003230000-117-2022-0000620221116<NA>1영업/정상1영업<NA><NA><NA><NA>02 69250515129.60138865서울특별시 송파구 잠실동 ***-** 애드버스서울특별시 송파구 도곡로**길 **, 애드버스 *층 (잠실동)5573히어로지스틱2022-11-16 16:02:56I2021-10-31 23:08:00.0식품운반업206835.849182444653.645158<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21932300003230000-117-2022-0000720221209<NA>1영업/정상1영업<NA><NA><NA><NA>15883047393.16138842서울특별시 송파구 석촌동 14-7서울특별시 송파구 백제고분로 275, 7층 (석촌동)5613(주)고고밴코리아2022-12-09 11:14:47I2021-11-01 23:01:00.0식품운반업208538.45687444516.687666<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22032300003230000-117-2023-000012023-04-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-849서울특별시 송파구 송파동 **-* 현대레이크빌서울특별시 송파구 석촌호수로 ***, *층 ***호 (송파동, 현대레이크빌)5623개별화물2023-04-14 14:00:05I2022-12-03 23:06:00.0식품운반업209389.696217445393.711557<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22132300003230000-117-2023-000022023-05-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 416 098411.89138-908서울특별시 송파구 잠실동 **-* 잠실파인애플상가서울특별시 송파구 올림픽로 ***, 잠실파인애플상가 지하*층 A***호 (잠실동)5501(주)대화로지스2023-05-12 15:40:20I2022-12-04 23:04:00.0식품운반업207373.500215445545.656024<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22232300003230000-117-2023-000032023-05-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 406 710674.52138-888서울특별시 송파구 문정동 ***-* 엠스테이트서울특별시 송파구 법원로 ***, 엠스테이트 A동 *층 ***호 (문정동)5854(주)엘제이로지스틱스2023-05-30 14:55:11I2022-12-06 00:01:00.0식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22332300003230000-117-2024-000012024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.50138-830서울특별시 송파구 방이동 ***-* 금천빌딩서울특별시 송파구 오금로 ***, 금천빌딩 *층 (방이동)5642주식회사 태성상사2024-04-17 10:58:43I2023-12-03 23:09:00.0식품운반업210092.736423445214.179934<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>