Overview

Dataset statistics

Number of variables44
Number of observations45
Missing cells473
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory381.9 B

Variable types

Categorical21
Text6
DateTime2
Unsupported9
Numeric5
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18047/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신일자 is highly imbalanced (50.8%)Imbalance
남성종사자수 is highly imbalanced (84.6%)Imbalance
여성종사자수 is highly imbalanced (84.6%)Imbalance
급수시설구분명 is highly imbalanced (64.7%)Imbalance
총인원 is highly imbalanced (84.6%)Imbalance
보증액 is highly imbalanced (84.6%)Imbalance
월세액 is highly imbalanced (84.6%)Imbalance
시설총규모 is highly imbalanced (54.9%)Imbalance
인허가취소일자 has 45 (100.0%) missing valuesMissing
폐업일자 has 19 (42.2%) missing valuesMissing
휴업시작일자 has 45 (100.0%) missing valuesMissing
휴업종료일자 has 45 (100.0%) missing valuesMissing
재개업일자 has 45 (100.0%) missing valuesMissing
전화번호 has 17 (37.8%) missing valuesMissing
소재지면적 has 3 (6.7%) missing valuesMissing
소재지우편번호 has 3 (6.7%) missing valuesMissing
지번주소 has 3 (6.7%) missing valuesMissing
도로명주소 has 8 (17.8%) missing valuesMissing
도로명우편번호 has 9 (20.0%) missing valuesMissing
영업장주변구분명 has 45 (100.0%) missing valuesMissing
등급구분명 has 45 (100.0%) missing valuesMissing
다중이용업소여부 has 6 (13.3%) missing valuesMissing
전통업소지정번호 has 45 (100.0%) missing valuesMissing
전통업소주된음식 has 45 (100.0%) missing valuesMissing
홈페이지 has 45 (100.0%) missing valuesMissing
관리번호 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
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
소재지면적 has 1 (2.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:46:43.866120
Analysis finished2024-05-11 05:46:44.675415
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
3200000
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 45
100.0%

Length

2024-05-11T14:46:44.787581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:44.991143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 45
100.0%

관리번호
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-05-11T14:46:45.268589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters990
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

Unique45 ?
Unique (%)100.0%

Sample

1st row3200000-122-2008-00001
2nd row3200000-122-2008-00002
3rd row3200000-122-2008-00003
4th row3200000-122-2008-00004
5th row3200000-122-2009-00001
ValueCountFrequency (%)
3200000-122-2008-00001 1
 
2.2%
3200000-122-2015-00001 1
 
2.2%
3200000-122-2015-00003 1
 
2.2%
3200000-122-2015-00004 1
 
2.2%
3200000-122-2015-00005 1
 
2.2%
3200000-122-2015-00006 1
 
2.2%
3200000-122-2015-00007 1
 
2.2%
3200000-122-2015-00008 1
 
2.2%
3200000-122-2015-00009 1
 
2.2%
3200000-122-2015-00010 1
 
2.2%
Other values (35) 35
77.8%
2024-05-11T14:46:45.787792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 461
46.6%
2 203
20.5%
- 135
 
13.6%
1 97
 
9.8%
3 53
 
5.4%
5 15
 
1.5%
8 7
 
0.7%
9 6
 
0.6%
4 5
 
0.5%
7 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 855
86.4%
Dash Punctuation 135
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 461
53.9%
2 203
23.7%
1 97
 
11.3%
3 53
 
6.2%
5 15
 
1.8%
8 7
 
0.8%
9 6
 
0.7%
4 5
 
0.6%
7 5
 
0.6%
6 3
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 135
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 461
46.6%
2 203
20.5%
- 135
 
13.6%
1 97
 
9.8%
3 53
 
5.4%
5 15
 
1.5%
8 7
 
0.7%
9 6
 
0.6%
4 5
 
0.5%
7 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 461
46.6%
2 203
20.5%
- 135
 
13.6%
1 97
 
9.8%
3 53
 
5.4%
5 15
 
1.5%
8 7
 
0.7%
9 6
 
0.6%
4 5
 
0.5%
7 5
 
0.5%

인허가일자
Date

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2008-03-18 00:00:00
Maximum2023-03-13 00:00:00
2024-05-11T14:46:46.054522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:46.330099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
3
26 
1
19 

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 26
57.8%
1 19
42.2%

Length

2024-05-11T14:46:46.532748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:46.694846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 26
57.8%
1 19
42.2%

영업상태명
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
폐업
26 
영업/정상
19 

Length

Max length5
Median length2
Mean length3.2666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 26
57.8%
영업/정상 19
42.2%

Length

2024-05-11T14:46:46.882196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:47.066662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 26
57.8%
영업/정상 19
42.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2
26 
1
19 

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 26
57.8%
1 19
42.2%

Length

2024-05-11T14:46:47.220960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:47.377510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 26
57.8%
1 19
42.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
폐업
26 
영업
19 

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 26
57.8%
영업 19
42.2%

Length

2024-05-11T14:46:47.551404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:47.717113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 26
57.8%
영업 19
42.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)88.5%
Missing19
Missing (%)42.2%
Infinite0
Infinite (%)0.0%
Mean20142592
Minimum20090123
Maximum20190830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T14:46:47.916147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090123
5-th percentile20093309
Q120113552
median20150161
Q320167912
95-th percentile20181231
Maximum20190830
Range100707
Interquartile range (IQR)54359.75

Descriptive statistics

Standard deviation29434.252
Coefficient of variation (CV)0.0014612941
Kurtosis-0.94897271
Mean20142592
Median Absolute Deviation (MAD)20365.5
Skewness-0.23965562
Sum5.2370739 × 108
Variance8.6637518 × 108
MonotonicityNot monotonic
2024-05-11T14:46:48.161314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20150210 3
 
6.7%
20181231 2
 
4.4%
20140526 1
 
2.2%
20180731 1
 
2.2%
20160707 1
 
2.2%
20190830 1
 
2.2%
20150617 1
 
2.2%
20150911 1
 
2.2%
20170314 1
 
2.2%
20150112 1
 
2.2%
Other values (13) 13
28.9%
(Missing) 19
42.2%
ValueCountFrequency (%)
20090123 1
2.2%
20090709 1
2.2%
20101110 1
2.2%
20110208 1
2.2%
20110602 1
2.2%
20110704 1
2.2%
20111202 1
2.2%
20120604 1
2.2%
20130807 1
2.2%
20140526 1
2.2%
ValueCountFrequency (%)
20190830 1
 
2.2%
20181231 2
4.4%
20180731 1
 
2.2%
20170725 1
 
2.2%
20170328 1
 
2.2%
20170314 1
 
2.2%
20160707 1
 
2.2%
20150911 1
 
2.2%
20150617 1
 
2.2%
20150210 3
6.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

전화번호
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing17
Missing (%)37.8%
Memory size492.0 B
2024-05-11T14:46:48.469718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11.5
Mean length10.821429
Min length10

Characters and Unicode

Total characters303
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

Unique28 ?
Unique (%)100.0%

Sample

1st row02 8556275
2nd row02 8898174
3rd row02 883 9640
4th row02 837 3666
5th row02 8610026
ValueCountFrequency (%)
02 20
33.9%
070 2
 
3.4%
8886566 1
 
1.7%
7078 1
 
1.7%
07077570479 1
 
1.7%
032 1
 
1.7%
8228550 1
 
1.7%
07087676884 1
 
1.7%
8678245 1
 
1.7%
8751421 1
 
1.7%
Other values (29) 29
49.2%
2024-05-11T14:46:49.000584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
17.2%
8 46
15.2%
38
12.5%
2 34
11.2%
5 30
9.9%
7 28
9.2%
6 22
7.3%
4 16
 
5.3%
1 14
 
4.6%
3 13
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 265
87.5%
Space Separator 38
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
19.6%
8 46
17.4%
2 34
12.8%
5 30
11.3%
7 28
10.6%
6 22
8.3%
4 16
 
6.0%
1 14
 
5.3%
3 13
 
4.9%
9 10
 
3.8%
Space Separator
ValueCountFrequency (%)
38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
17.2%
8 46
15.2%
38
12.5%
2 34
11.2%
5 30
9.9%
7 28
9.2%
6 22
7.3%
4 16
 
5.3%
1 14
 
4.6%
3 13
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
17.2%
8 46
15.2%
38
12.5%
2 34
11.2%
5 30
9.9%
7 28
9.2%
6 22
7.3%
4 16
 
5.3%
1 14
 
4.6%
3 13
 
4.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)76.2%
Missing3
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean66.51119
Minimum0
Maximum466
Zeros1
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T14:46:49.221988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.675
Q122.08
median30.735
Q369
95-th percentile189.522
Maximum466
Range466
Interquartile range (IQR)46.92

Descriptive statistics

Standard deviation93.367475
Coefficient of variation (CV)1.403786
Kurtosis10.253057
Mean66.51119
Median Absolute Deviation (MAD)17.72
Skewness3.0595375
Sum2793.47
Variance8717.4854
MonotonicityNot monotonic
2024-05-11T14:46:49.430064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
22.08 7
 
15.6%
33.0 3
 
6.7%
27.0 2
 
4.4%
66.0 2
 
4.4%
6.6 1
 
2.2%
48.4 1
 
2.2%
6.54 1
 
2.2%
18.0 1
 
2.2%
8.1 1
 
2.2%
29.37 1
 
2.2%
Other values (22) 22
48.9%
(Missing) 3
 
6.7%
ValueCountFrequency (%)
0.0 1
 
2.2%
6.54 1
 
2.2%
6.6 1
 
2.2%
8.1 1
 
2.2%
12.55 1
 
2.2%
12.96 1
 
2.2%
13.1 1
 
2.2%
16.5 1
 
2.2%
18.0 1
 
2.2%
22.08 7
15.6%
ValueCountFrequency (%)
466.0 1
2.2%
385.0 1
2.2%
191.14 1
2.2%
158.78 1
2.2%
146.12 1
2.2%
141.0 1
2.2%
126.0 1
2.2%
100.0 1
2.2%
77.47 1
2.2%
76.12 1
2.2%

소재지우편번호
Text

MISSING 

Distinct27
Distinct (%)64.3%
Missing3
Missing (%)6.7%
Memory size492.0 B
2024-05-11T14:46:49.729434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0714286
Min length6

Characters and Unicode

Total characters255
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

Unique19 ?
Unique (%)45.2%

Sample

1st row151893
2nd row151015
3rd row151835
4th row151872
5th row151876
ValueCountFrequency (%)
151863 7
16.7%
151893 4
 
9.5%
151835 2
 
4.8%
151876 2
 
4.8%
151904 2
 
4.8%
151873 2
 
4.8%
151015 2
 
4.8%
151883 2
 
4.8%
151-804 1
 
2.4%
151830 1
 
2.4%
Other values (17) 17
40.5%
2024-05-11T14:46:50.245917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 92
36.1%
5 48
18.8%
8 38
14.9%
3 22
 
8.6%
0 13
 
5.1%
9 12
 
4.7%
6 11
 
4.3%
7 8
 
3.1%
2 5
 
2.0%
4 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
98.8%
Dash Punctuation 3
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 92
36.5%
5 48
19.0%
8 38
15.1%
3 22
 
8.7%
0 13
 
5.2%
9 12
 
4.8%
6 11
 
4.4%
7 8
 
3.2%
2 5
 
2.0%
4 3
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 255
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 92
36.1%
5 48
18.8%
8 38
14.9%
3 22
 
8.6%
0 13
 
5.1%
9 12
 
4.7%
6 11
 
4.3%
7 8
 
3.1%
2 5
 
2.0%
4 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 255
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 92
36.1%
5 48
18.8%
8 38
14.9%
3 22
 
8.6%
0 13
 
5.1%
9 12
 
4.7%
6 11
 
4.3%
7 8
 
3.1%
2 5
 
2.0%
4 3
 
1.2%

지번주소
Text

MISSING 

Distinct37
Distinct (%)88.1%
Missing3
Missing (%)6.7%
Memory size492.0 B
2024-05-11T14:46:51.031915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length23
Min length19

Characters and Unicode

Total characters966
Distinct characters59
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)83.3%

Sample

1st row서울특별시 관악구 신림동 468-17
2nd row서울특별시 관악구 신림동 산 56-1
3rd row서울특별시 관악구 봉천동 1596-1
4th row서울특별시 관악구 신림동 492-18
5th row서울특별시 관악구 신림동 540-2 지상2층
ValueCountFrequency (%)
서울특별시 42
23.0%
관악구 42
23.0%
신림동 29
15.8%
봉천동 12
 
6.6%
316-127 7
 
3.8%
1465-16 3
 
1.6%
511-15 2
 
1.1%
지상1층 2
 
1.1%
지상2층 2
 
1.1%
지상1,2층 2
 
1.1%
Other values (40) 40
21.9%
2024-05-11T14:46:51.642670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
18.2%
1 58
 
6.0%
관 44
 
4.6%
악 44
 
4.6%
서 42
 
4.3%
동 42
 
4.3%
특 42
 
4.3%
별 42
 
4.3%
시 42
 
4.3%
구 42
 
4.3%
Other values (49) 392
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 519
53.7%
Decimal Number 229
23.7%
Space Separator 176
 
18.2%
Dash Punctuation 40
 
4.1%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 44
8.5%
악 44
8.5%
서 42
 
8.1%
동 42
 
8.1%
특 42
 
8.1%
별 42
 
8.1%
시 42
 
8.1%
구 42
 
8.1%
울 42
 
8.1%
신 29
 
5.6%
Other values (36) 108
20.8%
Decimal Number
ValueCountFrequency (%)
1 58
25.3%
6 33
14.4%
2 29
12.7%
5 21
 
9.2%
4 20
 
8.7%
3 18
 
7.9%
7 17
 
7.4%
0 12
 
5.2%
9 11
 
4.8%
8 10
 
4.4%
Space Separator
ValueCountFrequency (%)
176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 519
53.7%
Common 447
46.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 44
8.5%
악 44
8.5%
서 42
 
8.1%
동 42
 
8.1%
특 42
 
8.1%
별 42
 
8.1%
시 42
 
8.1%
구 42
 
8.1%
울 42
 
8.1%
신 29
 
5.6%
Other values (36) 108
20.8%
Common
ValueCountFrequency (%)
176
39.4%
1 58
 
13.0%
- 40
 
8.9%
6 33
 
7.4%
2 29
 
6.5%
5 21
 
4.7%
4 20
 
4.5%
3 18
 
4.0%
7 17
 
3.8%
0 12
 
2.7%
Other values (3) 23
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 519
53.7%
ASCII 447
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
39.4%
1 58
 
13.0%
- 40
 
8.9%
6 33
 
7.4%
2 29
 
6.5%
5 21
 
4.7%
4 20
 
4.5%
3 18
 
4.0%
7 17
 
3.8%
0 12
 
2.7%
Other values (3) 23
 
5.1%
Hangul
ValueCountFrequency (%)
관 44
8.5%
악 44
8.5%
서 42
 
8.1%
동 42
 
8.1%
특 42
 
8.1%
별 42
 
8.1%
시 42
 
8.1%
구 42
 
8.1%
울 42
 
8.1%
신 29
 
5.6%
Other values (36) 108
20.8%

도로명주소
Text

MISSING 

Distinct31
Distinct (%)83.8%
Missing8
Missing (%)17.8%
Memory size492.0 B
2024-05-11T14:46:52.019552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length29.405405
Min length21

Characters and Unicode

Total characters1088
Distinct characters78
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)81.1%

Sample

1st row서울특별시 관악구 관악로 1 (신림동)
2nd row서울특별시 관악구 남부순환로 1369 (신림동, 관악농협하나로마트)
3rd row서울특별시 관악구 조원로16가길 35 (신림동)
4th row서울특별시 관악구 남부순환로228길 32 (봉천동)
5th row서울특별시 관악구 남부순환로161가길 65 (신림동)
ValueCountFrequency (%)
서울특별시 37
16.6%
관악구 37
16.6%
신림동 25
 
11.2%
봉천동 11
 
4.9%
1층 10
 
4.5%
호암로 9
 
4.0%
484 9
 
4.0%
3층 7
 
3.1%
101호 3
 
1.3%
지하1층 3
 
1.3%
Other values (67) 72
32.3%
2024-05-11T14:46:52.619237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
 
17.2%
1 46
 
4.2%
관 43
 
4.0%
악 41
 
3.8%
( 37
 
3.4%
울 37
 
3.4%
) 37
 
3.4%
동 37
 
3.4%
서 37
 
3.4%
시 37
 
3.4%
Other values (68) 549
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 623
57.3%
Space Separator 187
 
17.2%
Decimal Number 171
 
15.7%
Open Punctuation 37
 
3.4%
Close Punctuation 37
 
3.4%
Other Punctuation 30
 
2.8%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 43
 
6.9%
악 41
 
6.6%
울 37
 
5.9%
동 37
 
5.9%
서 37
 
5.9%
시 37
 
5.9%
별 37
 
5.9%
구 37
 
5.9%
특 37
 
5.9%
로 32
 
5.1%
Other values (53) 248
39.8%
Decimal Number
ValueCountFrequency (%)
1 46
26.9%
4 31
18.1%
2 22
12.9%
3 20
11.7%
8 15
 
8.8%
6 12
 
7.0%
0 10
 
5.8%
5 8
 
4.7%
9 4
 
2.3%
7 3
 
1.8%
Space Separator
ValueCountFrequency (%)
187
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 623
57.3%
Common 465
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 43
 
6.9%
악 41
 
6.6%
울 37
 
5.9%
동 37
 
5.9%
서 37
 
5.9%
시 37
 
5.9%
별 37
 
5.9%
구 37
 
5.9%
특 37
 
5.9%
로 32
 
5.1%
Other values (53) 248
39.8%
Common
ValueCountFrequency (%)
187
40.2%
1 46
 
9.9%
( 37
 
8.0%
) 37
 
8.0%
4 31
 
6.7%
, 30
 
6.5%
2 22
 
4.7%
3 20
 
4.3%
8 15
 
3.2%
6 12
 
2.6%
Other values (5) 28
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 623
57.3%
ASCII 465
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
40.2%
1 46
 
9.9%
( 37
 
8.0%
) 37
 
8.0%
4 31
 
6.7%
, 30
 
6.5%
2 22
 
4.7%
3 20
 
4.3%
8 15
 
3.2%
6 12
 
2.6%
Other values (5) 28
 
6.0%
Hangul
ValueCountFrequency (%)
관 43
 
6.9%
악 41
 
6.6%
울 37
 
5.9%
동 37
 
5.9%
서 37
 
5.9%
시 37
 
5.9%
별 37
 
5.9%
구 37
 
5.9%
특 37
 
5.9%
로 32
 
5.1%
Other values (53) 248
39.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)69.4%
Missing9
Missing (%)20.0%
Infinite0
Infinite (%)0.0%
Mean8792.3333
Minimum8706
Maximum8860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T14:46:52.856601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8706
5-th percentile8710
Q18760.5
median8800
Q38823
95-th percentile8856.25
Maximum8860
Range154
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation48.105836
Coefficient of variation (CV)0.0054713389
Kurtosis-1.0988682
Mean8792.3333
Median Absolute Deviation (MAD)34.5
Skewness-0.34620893
Sum316524
Variance2314.1714
MonotonicityNot monotonic
2024-05-11T14:46:53.110693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8823 9
20.0%
8710 2
 
4.4%
8856 2
 
4.4%
8846 2
 
4.4%
8762 1
 
2.2%
8769 1
 
2.2%
8717 1
 
2.2%
8722 1
 
2.2%
8706 1
 
2.2%
8754 1
 
2.2%
Other values (15) 15
33.3%
(Missing) 9
20.0%
ValueCountFrequency (%)
8706 1
2.2%
8710 2
4.4%
8717 1
2.2%
8722 1
2.2%
8729 1
2.2%
8737 1
2.2%
8754 1
2.2%
8756 1
2.2%
8762 1
2.2%
8764 1
2.2%
ValueCountFrequency (%)
8860 1
 
2.2%
8857 1
 
2.2%
8856 2
 
4.4%
8849 1
 
2.2%
8846 2
 
4.4%
8826 1
 
2.2%
8823 9
20.0%
8807 1
 
2.2%
8793 1
 
2.2%
8788 1
 
2.2%

사업장명
Text

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-05-11T14:46:53.473225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.4666667
Min length2

Characters and Unicode

Total characters381
Distinct characters132
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)91.1%

Sample

1st row남부상사
2nd row농업협동조합중앙회서울대학교지점
3rd row주식회사 아미가푸드
4th row농협식품전문점
5th row(주)오대양에프엔비
ValueCountFrequency (%)
서울지사 8
 
12.5%
주식회사 4
 
6.2%
주)동화수산 2
 
3.1%
동건 2
 
3.1%
봉천1.9동 1
 
1.6%
늘봄푸드 1
 
1.6%
관악농협하나로마트 1
 
1.6%
보라매점 1
 
1.6%
동작관악키즈 1
 
1.6%
주)화은 1
 
1.6%
Other values (42) 42
65.6%
2024-05-11T14:46:54.037164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 20
 
5.2%
19
 
5.0%
) 16
 
4.2%
( 16
 
4.2%
사 14
 
3.7%
드 12
 
3.1%
동 12
 
3.1%
울 11
 
2.9%
푸 11
 
2.9%
서 11
 
2.9%
Other values (122) 239
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
85.6%
Space Separator 19
 
5.0%
Close Punctuation 16
 
4.2%
Open Punctuation 16
 
4.2%
Decimal Number 2
 
0.5%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 20
 
6.1%
사 14
 
4.3%
드 12
 
3.7%
동 12
 
3.7%
울 11
 
3.4%
푸 11
 
3.4%
서 11
 
3.4%
식 10
 
3.1%
지 10
 
3.1%
수 6
 
1.8%
Other values (115) 209
64.1%
Decimal Number
ValueCountFrequency (%)
9 1
50.0%
1 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
85.6%
Common 55
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 20
 
6.1%
사 14
 
4.3%
드 12
 
3.7%
동 12
 
3.7%
울 11
 
3.4%
푸 11
 
3.4%
서 11
 
3.4%
식 10
 
3.1%
지 10
 
3.1%
수 6
 
1.8%
Other values (115) 209
64.1%
Common
ValueCountFrequency (%)
19
34.5%
) 16
29.1%
( 16
29.1%
9 1
 
1.8%
. 1
 
1.8%
1 1
 
1.8%
& 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
85.6%
ASCII 55
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 20
 
6.1%
사 14
 
4.3%
드 12
 
3.7%
동 12
 
3.7%
울 11
 
3.4%
푸 11
 
3.4%
서 11
 
3.4%
식 10
 
3.1%
지 10
 
3.1%
수 6
 
1.8%
Other values (115) 209
64.1%
ASCII
ValueCountFrequency (%)
19
34.5%
) 16
29.1%
( 16
29.1%
9 1
 
1.8%
. 1
 
1.8%
1 1
 
1.8%
& 1
 
1.8%

최종수정일자
Date

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum2008-03-18 14:58:08
Maximum2024-05-08 14:56:02
2024-05-11T14:46:54.254624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:46:54.484696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
I
36 
U
9 

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 36
80.0%
U 9
 
20.0%

Length

2024-05-11T14:46:54.668090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:54.844300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 36
80.0%
u 9
 
20.0%

데이터갱신일자
Categorical

IMBALANCE 

Distinct11
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2018-08-31 23:59:59.0
33 
2019-01-02 02:40:00.0
 
2
2021-11-01 22:04:00.0
 
2
2019-12-06 02:40:00.0
 
1
2023-12-04 23:00:00.0
 
1
Other values (6)
6 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique8 ?
Unique (%)17.8%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 33
73.3%
2019-01-02 02:40:00.0 2
 
4.4%
2021-11-01 22:04:00.0 2
 
4.4%
2019-12-06 02:40:00.0 1
 
2.2%
2023-12-04 23:00:00.0 1
 
2.2%
2019-08-31 02:40:00.0 1
 
2.2%
2022-12-03 23:05:00.0 1
 
2.2%
2020-08-07 00:23:15.0 1
 
2.2%
2022-03-19 02:40:00.0 1
 
2.2%
2021-11-01 22:03:00.0 1
 
2.2%

Length

2024-05-11T14:46:55.034798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 33
36.7%
23:59:59.0 33
36.7%
02:40:00.0 5
 
5.6%
2021-11-01 3
 
3.3%
23:05:00.0 2
 
2.2%
2019-01-02 2
 
2.2%
22:04:00.0 2
 
2.2%
22:03:00.0 1
 
1.1%
2022-03-19 1
 
1.1%
00:23:15.0 1
 
1.1%
Other values (7) 7
 
7.8%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
집단급식소 식품판매업
45 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 45
100.0%

Length

2024-05-11T14:46:55.293765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:55.486501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 45
50.0%
식품판매업 45
50.0%

좌표정보(X)
Real number (ℝ)

Distinct34
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193859.78
Minimum191334.66
Maximum198278.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T14:46:55.653871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191334.66
5-th percentile192114.4
Q1192983.99
median193719.54
Q3193910.16
95-th percentile196421.41
Maximum198278.93
Range6944.2721
Interquartile range (IQR)926.16845

Descriptive statistics

Standard deviation1448.6397
Coefficient of variation (CV)0.0074726157
Kurtosis1.0455351
Mean193859.78
Median Absolute Deviation (MAD)718.68555
Skewness0.97158707
Sum8723690.3
Variance2098556.9
MonotonicityNot monotonic
2024-05-11T14:46:55.837172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
193910.163334801 9
 
20.0%
193233.136629645 3
 
6.7%
192431.331182521 2
 
4.4%
194536.92447403 1
 
2.2%
193545.975733263 1
 
2.2%
193495.619701124 1
 
2.2%
193131.208565183 1
 
2.2%
193746.833837509 1
 
2.2%
194386.133620309 1
 
2.2%
193763.578031026 1
 
2.2%
Other values (24) 24
53.3%
ValueCountFrequency (%)
191334.658955208 1
2.2%
191499.702623466 1
2.2%
192091.636556737 1
2.2%
192205.473229729 1
2.2%
192431.331182521 2
4.4%
192491.9130359 1
2.2%
192674.885947244 1
2.2%
192691.713243421 1
2.2%
192817.818457133 1
2.2%
192971.550462789 1
2.2%
ValueCountFrequency (%)
198278.931088754 1
2.2%
196912.833572618 1
2.2%
196491.79948659 1
2.2%
196139.864969792 1
2.2%
196044.192957121 1
2.2%
195920.418422784 1
2.2%
195751.871898296 1
2.2%
195588.796492288 1
2.2%
195396.107343889 1
2.2%
194536.92447403 1
2.2%

좌표정보(Y)
Real number (ℝ)

Distinct34
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean441552.74
Minimum439023.17
Maximum443314.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-05-11T14:46:56.055448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile439858.51
Q1440529.26
median441993.85
Q3442525.51
95-th percentile443104.8
Maximum443314.94
Range4291.7744
Interquartile range (IQR)1996.2568

Descriptive statistics

Standard deviation1207.1442
Coefficient of variation (CV)0.0027338619
Kurtosis-1.1701876
Mean441552.74
Median Absolute Deviation (MAD)721.40995
Skewness-0.41574958
Sum19869873
Variance1457197.1
MonotonicityNot monotonic
2024-05-11T14:46:56.260480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
439858.509246791 9
 
20.0%
442525.514840337 3
 
6.7%
442476.630285209 2
 
4.4%
442715.263188428 1
 
2.2%
443148.827256697 1
 
2.2%
443314.941516933 1
 
2.2%
442928.668690781 1
 
2.2%
442510.775085572 1
 
2.2%
442492.51105354 1
 
2.2%
440807.902524025 1
 
2.2%
Other values (24) 24
53.3%
ValueCountFrequency (%)
439023.167125842 1
 
2.2%
439858.509246791 9
20.0%
440263.768319604 1
 
2.2%
440529.258018562 1
 
2.2%
440773.048162389 1
 
2.2%
440807.902524025 1
 
2.2%
440817.90186244 1
 
2.2%
440879.974793606 1
 
2.2%
441352.743493574 1
 
2.2%
441358.893188526 1
 
2.2%
ValueCountFrequency (%)
443314.941516933 1
 
2.2%
443288.592678371 1
 
2.2%
443148.827256697 1
 
2.2%
442928.668690781 1
 
2.2%
442915.87526241 1
 
2.2%
442874.278631397 1
 
2.2%
442715.263188428 1
 
2.2%
442633.361198822 1
 
2.2%
442562.567220785 1
 
2.2%
442525.514840337 3
6.7%

위생업태명
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
집단급식소 식품판매업
39 
<NA>
6 

Length

Max length11
Median length11
Mean length10.066667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 39
86.7%
<NA> 6
 
13.3%

Length

2024-05-11T14:46:56.545928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:56.754709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 39
46.4%
식품판매업 39
46.4%
na 6
 
7.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
44 
0
 
1

Length

Max length4
Median length4
Mean length3.9333333
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
97.8%
0 1
 
2.2%

Length

2024-05-11T14:46:56.941492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:57.135175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
97.8%
0 1
 
2.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
44 
0
 
1

Length

Max length4
Median length4
Mean length3.9333333
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
97.8%
0 1
 
2.2%

Length

2024-05-11T14:46:57.318455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:57.496873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
97.8%
0 1
 
2.2%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
42 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.0666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
93.3%
상수도전용 3
 
6.7%

Length

2024-05-11T14:46:57.678907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:57.857621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
93.3%
상수도전용 3
 
6.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
44 
0
 
1

Length

Max length4
Median length4
Mean length3.9333333
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
97.8%
0 1
 
2.2%

Length

2024-05-11T14:46:58.030324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:58.218948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
97.8%
0 1
 
2.2%

본사종업원수
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
40 
0
5 

Length

Max length4
Median length4
Mean length3.6666667
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> 40
88.9%
0 5
 
11.1%

Length

2024-05-11T14:46:58.420783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:58.602044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
88.9%
0 5
 
11.1%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
40 
0
5 

Length

Max length4
Median length4
Mean length3.6666667
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> 40
88.9%
0 5
 
11.1%

Length

2024-05-11T14:46:58.804047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:58.979109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
88.9%
0 5
 
11.1%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
40 
0
5 

Length

Max length4
Median length4
Mean length3.6666667
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> 40
88.9%
0 5
 
11.1%

Length

2024-05-11T14:46:59.164662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:59.344523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
88.9%
0 5
 
11.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
40 
0
5 

Length

Max length4
Median length4
Mean length3.6666667
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> 40
88.9%
0 5
 
11.1%

Length

2024-05-11T14:46:59.552841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:46:59.747398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
88.9%
0 5
 
11.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
20 
임대
18 
자가
7 

Length

Max length4
Median length2
Mean length2.8888889
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
44.4%
임대 18
40.0%
자가 7
 
15.6%

Length

2024-05-11T14:47:00.002450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:47:00.238949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
44.4%
임대 18
40.0%
자가 7
 
15.6%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
44 
75000000
 
1

Length

Max length8
Median length4
Mean length4.0888889
Min length4

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
97.8%
75000000 1
 
2.2%

Length

2024-05-11T14:47:00.447395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:47:00.625403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
97.8%
75000000 1
 
2.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
<NA>
44 
0
 
1

Length

Max length4
Median length4
Mean length3.9333333
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
97.8%
0 1
 
2.2%

Length

2024-05-11T14:47:00.828326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:47:01.010782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
97.8%
0 1
 
2.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.6%
Missing6
Missing (%)13.3%
Memory size222.0 B
False
39 
(Missing)
6 
ValueCountFrequency (%)
False 39
86.7%
(Missing) 6
 
13.3%
2024-05-11T14:47:01.148635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
0.0
38 
<NA>
6 
17.85
 
1

Length

Max length5
Median length3
Mean length3.1777778
Min length3

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 38
84.4%
<NA> 6
 
13.3%
17.85 1
 
2.2%

Length

2024-05-11T14:47:01.352013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:47:01.534212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 38
84.4%
na 6
 
13.3%
17.85 1
 
2.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032000003200000-122-2008-0000120080318<NA>3폐업2폐업20090123<NA><NA><NA>02 8556275385.0151893서울특별시 관악구 신림동 468-17<NA><NA>남부상사2008-03-18 14:58:08I2018-08-31 23:59:59.0집단급식소 식품판매업193000.85511442633.361199집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
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232000003200000-122-2008-0000320080922<NA>3폐업2폐업20110208<NA><NA><NA>02 883 9640126.0151835서울특별시 관악구 봉천동 1596-1<NA><NA>주식회사 아미가푸드2009-06-25 10:41:25I2018-08-31 23:59:59.0집단급식소 식품판매업195751.871898441610.455838집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
332000003200000-122-2008-0000420081119<NA>3폐업2폐업20090709<NA><NA><NA>02 837 366627.0151872서울특별시 관악구 신림동 492-18<NA><NA>농협식품전문점2008-11-19 10:35:30I2018-08-31 23:59:59.0집단급식소 식품판매업192691.713243442562.567221집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
432000003200000-122-2009-0000120090407<NA>3폐업2폐업20110704<NA><NA><NA>02 8610026<NA>151876서울특별시 관악구 신림동 540-2 지상2층<NA><NA>(주)오대양에프엔비2010-06-22 13:56:39I2018-08-31 23:59:59.0집단급식소 식품판매업192091.636557442282.244935집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532000003200000-122-2009-0000220090519<NA>1영업/정상1영업<NA><NA><NA><NA>02862 5885<NA>151904서울특별시 관악구 신림동 1668 관악농협하나로마트서울특별시 관악구 남부순환로 1369 (신림동, 관악농협하나로마트)8768관악농협농특산물백화점2014-02-25 11:26:23I2018-08-31 23:59:59.0집단급식소 식품판매업191334.658955441993.853242집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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832000003200000-122-2009-0000520090924<NA>3폐업2폐업20170725<NA><NA><NA>02 857088166.0151873서울특별시 관악구 신림동 511-15서울특별시 관악구 남부순환로161가길 65 (신림동)8762소담식품2017-07-25 12:54:56I2018-08-31 23:59:59.0집단급식소 식품판매업192431.331183442476.630285집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
932000003200000-122-2010-0000120100302<NA>3폐업2폐업20101110<NA><NA><NA><NA>70.0151893서울특별시 관악구 신림동 1465-16 지상1,2층<NA><NA>(주)천지인2010-04-15 17:23:44I2018-08-31 23:59:59.0집단급식소 식품판매업193233.13663442525.51484집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
3532000003200000-122-2017-0000120170303<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.37151862서울특별시 관악구 신림동 365-21서울특별시 관악구 양지8길 41, 1층 101호 (신림동)8846동아식품2022-12-22 10:40:52U2021-11-01 22:04:00.0집단급식소 식품판매업193719.540656440817.901862<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3632000003200000-122-2017-0000220170406<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.0151889서울특별시 관악구 신림동 654-33서울특별시 관악구 난곡로16길 15, 1층 (신림동)8857삼성식품2017-04-06 11:34:46I2018-08-31 23:59:59.0집단급식소 식품판매업192983.994881440529.258019집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3732000003200000-122-2017-0000320170925<NA>1영업/정상1영업<NA><NA><NA><NA>02 88865668.1151809서울특별시 관악구 봉천동 30-6서울특별시 관악구 행운1길 113, 지하1층 (봉천동)8737팔팔유통2017-09-25 13:50:46I2018-08-31 23:59:59.0집단급식소 식품판매업196044.192957442376.676371집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3832000003200000-122-2018-0000120180125<NA>1영업/정상1영업<NA><NA><NA><NA>0704006756633.0151883서울특별시 관악구 신림동 651-17서울특별시 관악구 난곡로24다길 2, 1층 101호 (신림동)8856천하식품2018-01-25 12:10:15I2018-08-31 23:59:59.0집단급식소 식품판매업192971.550463440773.048162집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
3932000003200000-122-2018-0000220180716<NA>1영업/정상1영업<NA><NA><NA><NA>070 4901937718.0151827서울특별시 관악구 봉천동 949-18 조은빌딩서울특별시 관악구 남부순환로 1679, 조은빌딩 314호 (봉천동)8756(주)웰푸드2018-07-16 14:09:45I2018-08-31 23:59:59.0집단급식소 식품판매업194386.13362442492.511054집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
4032000003200000-122-2020-0000220200805<NA>1영업/정상1영업<NA><NA><NA><NA>070 880714946.54151890서울특별시 관악구 신림동 1422-5 르네상스복합쇼핑몰서울특별시 관악구 신림로 340, 지하1층 65호 (신림동)8754웰푸드2020-08-05 17:52:02I2020-08-07 00:23:15.0집단급식소 식품판매업193746.833838442510.775086집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
4132000003200000-122-2022-0000120220215<NA>1영업/정상1영업<NA><NA><NA><NA>02 854 553448.4151891서울특별시 관악구 신림동 1449-29서울특별시 관악구 관천로22길 13, 1층 (신림동)8706청정푸드2022-03-17 16:15:24U2022-03-19 02:40:00.0집단급식소 식품판매업193131.208565442928.668691집단급식소 식품판매업00<NA><NA><NA>00000임대750000000N17.85<NA><NA><NA>
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