Overview

Dataset statistics

Number of variables44
Number of observations72
Missing cells839
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.7 KiB
Average record size in memory379.8 B

Variable types

Categorical19
Text6
DateTime3
Unsupported9
Numeric6
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18041/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (69.0%)Imbalance
여성종사자수 is highly imbalanced (69.0%)Imbalance
총인원 is highly imbalanced (69.0%)Imbalance
보증액 is highly imbalanced (61.1%)Imbalance
인허가취소일자 has 72 (100.0%) missing valuesMissing
폐업일자 has 23 (31.9%) missing valuesMissing
휴업시작일자 has 72 (100.0%) missing valuesMissing
휴업종료일자 has 72 (100.0%) missing valuesMissing
재개업일자 has 72 (100.0%) missing valuesMissing
전화번호 has 26 (36.1%) missing valuesMissing
소재지면적 has 1 (1.4%) missing valuesMissing
도로명주소 has 9 (12.5%) missing valuesMissing
도로명우편번호 has 13 (18.1%) missing valuesMissing
좌표정보(X) has 1 (1.4%) missing valuesMissing
좌표정보(Y) has 1 (1.4%) missing valuesMissing
영업장주변구분명 has 72 (100.0%) missing valuesMissing
등급구분명 has 72 (100.0%) missing valuesMissing
월세액 has 61 (84.7%) missing valuesMissing
다중이용업소여부 has 28 (38.9%) missing valuesMissing
시설총규모 has 28 (38.9%) missing valuesMissing
전통업소지정번호 has 72 (100.0%) missing valuesMissing
전통업소주된음식 has 72 (100.0%) missing valuesMissing
홈페이지 has 72 (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 (1.4%) zerosZeros
월세액 has 3 (4.2%) zerosZeros
시설총규모 has 36 (50.0%) zerosZeros

Reproduction

Analysis started2024-04-29 19:34:30.508057
Analysis finished2024-04-29 19:34:31.416614
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
3140000
72 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 72
100.0%

Length

2024-04-30T04:34:31.528027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:31.678352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 72
100.0%

관리번호
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-04-30T04:34:31.868081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1584
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

Unique72 ?
Unique (%)100.0%

Sample

1st row3140000-122-2008-00001
2nd row3140000-122-2008-00002
3rd row3140000-122-2008-00003
4th row3140000-122-2008-00004
5th row3140000-122-2008-00005
ValueCountFrequency (%)
3140000-122-2008-00001 1
 
1.4%
3140000-122-2008-00002 1
 
1.4%
3140000-122-2018-00002 1
 
1.4%
3140000-122-2018-00001 1
 
1.4%
3140000-122-2017-00003 1
 
1.4%
3140000-122-2017-00002 1
 
1.4%
3140000-122-2017-00001 1
 
1.4%
3140000-122-2016-00002 1
 
1.4%
3140000-122-2018-00003 1
 
1.4%
3140000-122-2016-00001 1
 
1.4%
Other values (62) 62
86.1%
2024-04-30T04:34:32.150950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 668
42.2%
2 254
 
16.0%
- 216
 
13.6%
1 213
 
13.4%
3 92
 
5.8%
4 83
 
5.2%
8 23
 
1.5%
5 13
 
0.8%
7 8
 
0.5%
6 7
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1368
86.4%
Dash Punctuation 216
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 668
48.8%
2 254
 
18.6%
1 213
 
15.6%
3 92
 
6.7%
4 83
 
6.1%
8 23
 
1.7%
5 13
 
1.0%
7 8
 
0.6%
6 7
 
0.5%
9 7
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1584
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 668
42.2%
2 254
 
16.0%
- 216
 
13.6%
1 213
 
13.4%
3 92
 
5.8%
4 83
 
5.2%
8 23
 
1.5%
5 13
 
0.8%
7 8
 
0.5%
6 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 668
42.2%
2 254
 
16.0%
- 216
 
13.6%
1 213
 
13.4%
3 92
 
5.8%
4 83
 
5.2%
8 23
 
1.5%
5 13
 
0.8%
7 8
 
0.5%
6 7
 
0.4%

인허가일자
Date

Distinct67
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum2008-03-19 00:00:00
Maximum2023-12-06 00:00:00
2024-04-30T04:34:32.268994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:34:32.396621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
3
49 
1
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 49
68.1%
1 23
31.9%

Length

2024-04-30T04:34:32.513827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:32.609461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 49
68.1%
1 23
31.9%

영업상태명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
폐업
49 
영업/정상
23 

Length

Max length5
Median length2
Mean length2.9583333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 49
68.1%
영업/정상 23
31.9%

Length

2024-04-30T04:34:32.708234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:32.796044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 49
68.1%
영업/정상 23
31.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
2
49 
1
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 49
68.1%
1 23
31.9%

Length

2024-04-30T04:34:32.888021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:32.976506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 49
68.1%
1 23
31.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
폐업
49 
영업
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 49
68.1%
영업 23
31.9%

Length

2024-04-30T04:34:33.057292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:33.137861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 49
68.1%
영업 23
31.9%

폐업일자
Date

MISSING 

Distinct48
Distinct (%)98.0%
Missing23
Missing (%)31.9%
Memory size708.0 B
Minimum2009-01-20 00:00:00
Maximum2023-12-28 00:00:00
2024-04-30T04:34:33.228550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:34:33.338988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

전화번호
Text

MISSING 

Distinct44
Distinct (%)95.7%
Missing26
Missing (%)36.1%
Memory size708.0 B
2024-04-30T04:34:33.523648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.347826
Min length10

Characters and Unicode

Total characters476
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

Unique42 ?
Unique (%)91.3%

Sample

1st row0226997792
2nd row02 26076307
3rd row02 20651695
4th row0226998240
5th row0226512662
ValueCountFrequency (%)
02 6
 
11.1%
0226816692 2
 
3.7%
0226083311 2
 
3.7%
0226021597 1
 
1.9%
3537652 1
 
1.9%
0226045755 1
 
1.9%
0226997792 1
 
1.9%
0226515142 1
 
1.9%
0226063111 1
 
1.9%
0226054185 1
 
1.9%
Other values (37) 37
68.5%
2024-04-30T04:34:33.819683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 104
21.8%
0 94
19.7%
6 67
14.1%
1 33
 
6.9%
5 32
 
6.7%
9 31
 
6.5%
7 27
 
5.7%
3 25
 
5.3%
4 25
 
5.3%
8 24
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 462
97.1%
Space Separator 14
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 104
22.5%
0 94
20.3%
6 67
14.5%
1 33
 
7.1%
5 32
 
6.9%
9 31
 
6.7%
7 27
 
5.8%
3 25
 
5.4%
4 25
 
5.4%
8 24
 
5.2%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 476
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 104
21.8%
0 94
19.7%
6 67
14.1%
1 33
 
6.9%
5 32
 
6.7%
9 31
 
6.5%
7 27
 
5.7%
3 25
 
5.3%
4 25
 
5.3%
8 24
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 476
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 104
21.8%
0 94
19.7%
6 67
14.1%
1 33
 
6.9%
5 32
 
6.7%
9 31
 
6.5%
7 27
 
5.7%
3 25
 
5.3%
4 25
 
5.3%
8 24
 
5.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct55
Distinct (%)77.5%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean57.97
Minimum0
Maximum324.8
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:33.958217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.95
Q126
median33
Q363.24
95-th percentile163
Maximum324.8
Range324.8
Interquartile range (IQR)37.24

Descriptive statistics

Standard deviation63.216699
Coefficient of variation (CV)1.0905071
Kurtosis8.5223267
Mean57.97
Median Absolute Deviation (MAD)13
Skewness2.7971694
Sum4115.87
Variance3996.351
MonotonicityNot monotonic
2024-04-30T04:34:34.073929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 7
 
9.7%
30.0 4
 
5.6%
26.0 3
 
4.2%
40.0 3
 
4.2%
20.0 2
 
2.8%
15.0 2
 
2.8%
9.9 2
 
2.8%
45.62 1
 
1.4%
306.9 1
 
1.4%
99.37 1
 
1.4%
Other values (45) 45
62.5%
ValueCountFrequency (%)
0.0 1
1.4%
3.0 1
1.4%
9.9 2
2.8%
10.0 1
1.4%
13.19 1
1.4%
15.0 2
2.8%
19.8 1
1.4%
20.0 2
2.8%
22.11 1
1.4%
23.0 1
1.4%
ValueCountFrequency (%)
324.8 1
1.4%
306.9 1
1.4%
284.0 1
1.4%
168.0 1
1.4%
158.0 1
1.4%
149.0 1
1.4%
130.0 1
1.4%
119.44 1
1.4%
100.0 1
1.4%
99.37 1
1.4%

소재지우편번호
Text

Distinct42
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-04-30T04:34:34.246713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3055556
Min length6

Characters and Unicode

Total characters454
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

Unique27 ?
Unique (%)37.5%

Sample

1st row158840
2nd row158825
3rd row158822
4th row158-830
5th row158881
ValueCountFrequency (%)
158840 4
 
5.6%
158847 4
 
5.6%
158859 4
 
5.6%
158822 4
 
5.6%
158856 4
 
5.6%
158846 4
 
5.6%
158841 3
 
4.2%
158-831 3
 
4.2%
158-829 3
 
4.2%
158864 2
 
2.8%
Other values (32) 37
51.4%
2024-04-30T04:34:34.517628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 146
32.2%
5 89
19.6%
1 86
18.9%
4 25
 
5.5%
- 22
 
4.8%
0 19
 
4.2%
2 19
 
4.2%
6 15
 
3.3%
9 12
 
2.6%
3 11
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 432
95.2%
Dash Punctuation 22
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 146
33.8%
5 89
20.6%
1 86
19.9%
4 25
 
5.8%
0 19
 
4.4%
2 19
 
4.4%
6 15
 
3.5%
9 12
 
2.8%
3 11
 
2.5%
7 10
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 454
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 146
32.2%
5 89
19.6%
1 86
18.9%
4 25
 
5.5%
- 22
 
4.8%
0 19
 
4.2%
2 19
 
4.2%
6 15
 
3.3%
9 12
 
2.6%
3 11
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 146
32.2%
5 89
19.6%
1 86
18.9%
4 25
 
5.5%
- 22
 
4.8%
0 19
 
4.2%
2 19
 
4.2%
6 15
 
3.3%
9 12
 
2.6%
3 11
 
2.4%

지번주소
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-04-30T04:34:34.748142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length31
Mean length24.333333
Min length19

Characters and Unicode

Total characters1752
Distinct characters78
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row서울특별시 양천구 신월동 547-7
2nd row서울특별시 양천구 신월동 81-10 2층
3rd row서울특별시 양천구 신월동 8-12
4th row서울특별시 양천구 신월동 199-6
5th row서울특별시 양천구 목동 929 한청상가 지층 1호
ValueCountFrequency (%)
서울특별시 72
19.8%
양천구 72
19.8%
신월동 43
 
11.8%
신정동 21
 
5.8%
1층 19
 
5.2%
지상1층 9
 
2.5%
목동 8
 
2.2%
2층 4
 
1.1%
220-7 3
 
0.8%
974-10 3
 
0.8%
Other values (99) 109
30.0%
2024-04-30T04:34:35.107626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
330
18.8%
1 100
 
5.7%
동 78
 
4.5%
시 75
 
4.3%
천 74
 
4.2%
양 74
 
4.2%
울 72
 
4.1%
서 72
 
4.1%
별 72
 
4.1%
특 72
 
4.1%
Other values (68) 733
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 955
54.5%
Decimal Number 382
 
21.8%
Space Separator 330
 
18.8%
Dash Punctuation 66
 
3.8%
Open Punctuation 7
 
0.4%
Close Punctuation 7
 
0.4%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 78
 
8.2%
시 75
 
7.9%
천 74
 
7.7%
양 74
 
7.7%
울 72
 
7.5%
서 72
 
7.5%
별 72
 
7.5%
특 72
 
7.5%
구 72
 
7.5%
신 65
 
6.8%
Other values (51) 229
24.0%
Decimal Number
ValueCountFrequency (%)
1 100
26.2%
2 49
12.8%
9 43
11.3%
7 36
 
9.4%
0 36
 
9.4%
4 34
 
8.9%
5 30
 
7.9%
8 22
 
5.8%
3 19
 
5.0%
6 13
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
@ 1
50.0%
Space Separator
ValueCountFrequency (%)
330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 955
54.5%
Common 794
45.3%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 78
 
8.2%
시 75
 
7.9%
천 74
 
7.7%
양 74
 
7.7%
울 72
 
7.5%
서 72
 
7.5%
별 72
 
7.5%
특 72
 
7.5%
구 72
 
7.5%
신 65
 
6.8%
Other values (51) 229
24.0%
Common
ValueCountFrequency (%)
330
41.6%
1 100
 
12.6%
- 66
 
8.3%
2 49
 
6.2%
9 43
 
5.4%
7 36
 
4.5%
0 36
 
4.5%
4 34
 
4.3%
5 30
 
3.8%
8 22
 
2.8%
Other values (6) 48
 
6.0%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 955
54.5%
ASCII 797
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
330
41.4%
1 100
 
12.5%
- 66
 
8.3%
2 49
 
6.1%
9 43
 
5.4%
7 36
 
4.5%
0 36
 
4.5%
4 34
 
4.3%
5 30
 
3.8%
8 22
 
2.8%
Other values (7) 51
 
6.4%
Hangul
ValueCountFrequency (%)
동 78
 
8.2%
시 75
 
7.9%
천 74
 
7.7%
양 74
 
7.7%
울 72
 
7.5%
서 72
 
7.5%
별 72
 
7.5%
특 72
 
7.5%
구 72
 
7.5%
신 65
 
6.8%
Other values (51) 229
24.0%

도로명주소
Text

MISSING 

Distinct61
Distinct (%)96.8%
Missing9
Missing (%)12.5%
Memory size708.0 B
2024-04-30T04:34:35.331489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length32.126984
Min length23

Characters and Unicode

Total characters2024
Distinct characters92
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)93.7%

Sample

1st row서울특별시 양천구 남부순환로 571 (신월동)
2nd row서울특별시 양천구 남부순환로58길 13 (신월동)
3rd row서울특별시 양천구 지양로11길 16-1 (신월동,명지 가동 B01호)
4th row서울특별시 양천구 목동로23길 34 (신정동,108호)
5th row서울특별시 양천구 남부순환로 589 (신월동)
ValueCountFrequency (%)
서울특별시 63
 
16.1%
양천구 63
 
16.1%
신월동 35
 
9.0%
1층 22
 
5.6%
신정동 17
 
4.3%
지상1층 9
 
2.3%
2층 7
 
1.8%
목동 7
 
1.8%
101호 4
 
1.0%
남부순환로 4
 
1.0%
Other values (125) 160
40.9%
2024-04-30T04:34:35.678192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
 
16.2%
1 108
 
5.3%
동 81
 
4.0%
양 69
 
3.4%
시 66
 
3.3%
서 65
 
3.2%
( 65
 
3.2%
) 65
 
3.2%
천 65
 
3.2%
구 63
 
3.1%
Other values (82) 1049
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1170
57.8%
Space Separator 328
 
16.2%
Decimal Number 319
 
15.8%
Open Punctuation 65
 
3.2%
Close Punctuation 65
 
3.2%
Other Punctuation 60
 
3.0%
Dash Punctuation 16
 
0.8%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 81
 
6.9%
양 69
 
5.9%
시 66
 
5.6%
서 65
 
5.6%
천 65
 
5.6%
구 63
 
5.4%
울 63
 
5.4%
특 63
 
5.4%
로 63
 
5.4%
신 63
 
5.4%
Other values (66) 509
43.5%
Decimal Number
ValueCountFrequency (%)
1 108
33.9%
2 35
 
11.0%
0 33
 
10.3%
4 31
 
9.7%
3 31
 
9.7%
6 24
 
7.5%
5 18
 
5.6%
7 17
 
5.3%
8 14
 
4.4%
9 8
 
2.5%
Space Separator
ValueCountFrequency (%)
328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Other Punctuation
ValueCountFrequency (%)
, 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1170
57.8%
Common 853
42.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 81
 
6.9%
양 69
 
5.9%
시 66
 
5.6%
서 65
 
5.6%
천 65
 
5.6%
구 63
 
5.4%
울 63
 
5.4%
특 63
 
5.4%
로 63
 
5.4%
신 63
 
5.4%
Other values (66) 509
43.5%
Common
ValueCountFrequency (%)
328
38.5%
1 108
 
12.7%
( 65
 
7.6%
) 65
 
7.6%
, 60
 
7.0%
2 35
 
4.1%
0 33
 
3.9%
4 31
 
3.6%
3 31
 
3.6%
6 24
 
2.8%
Other values (5) 73
 
8.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1170
57.8%
ASCII 854
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
38.4%
1 108
 
12.6%
( 65
 
7.6%
) 65
 
7.6%
, 60
 
7.0%
2 35
 
4.1%
0 33
 
3.9%
4 31
 
3.6%
3 31
 
3.6%
6 24
 
2.8%
Other values (6) 74
 
8.7%
Hangul
ValueCountFrequency (%)
동 81
 
6.9%
양 69
 
5.9%
시 66
 
5.6%
서 65
 
5.6%
천 65
 
5.6%
구 63
 
5.4%
울 63
 
5.4%
특 63
 
5.4%
로 63
 
5.4%
신 63
 
5.4%
Other values (66) 509
43.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)66.1%
Missing13
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean7975.5932
Minimum7900
Maximum8090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:35.793781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7904.5
Q17923
median7955
Q38031.5
95-th percentile8057.7
Maximum8090
Range190
Interquartile range (IQR)108.5

Descriptive statistics

Standard deviation57.839289
Coefficient of variation (CV)0.007252036
Kurtosis-1.5739706
Mean7975.5932
Median Absolute Deviation (MAD)50
Skewness0.21352889
Sum470560
Variance3345.3834
MonotonicityNot monotonic
2024-04-30T04:34:35.914491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7924 4
 
5.6%
7900 3
 
4.2%
7938 3
 
4.2%
8020 3
 
4.2%
8041 3
 
4.2%
7915 3
 
4.2%
8040 3
 
4.2%
7911 2
 
2.8%
7945 2
 
2.8%
8031 2
 
2.8%
Other values (29) 31
43.1%
(Missing) 13
18.1%
ValueCountFrequency (%)
7900 3
4.2%
7905 1
 
1.4%
7907 1
 
1.4%
7910 1
 
1.4%
7911 2
2.8%
7912 1
 
1.4%
7915 3
4.2%
7917 1
 
1.4%
7920 1
 
1.4%
7922 1
 
1.4%
ValueCountFrequency (%)
8090 1
 
1.4%
8065 1
 
1.4%
8064 1
 
1.4%
8057 2
2.8%
8041 3
4.2%
8040 3
4.2%
8039 1
 
1.4%
8037 1
 
1.4%
8032 2
2.8%
8031 2
2.8%

사업장명
Text

Distinct71
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-04-30T04:34:36.154096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length6.0694444
Min length2

Characters and Unicode

Total characters437
Distinct characters146
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)97.2%

Sample

1st row선경푸드
2nd row온고을FOOD
3rd row현유통
4th row가원푸드
5th row경기쌀상회
ValueCountFrequency (%)
태현 2
 
2.3%
주식회사 2
 
2.3%
농업회사법인 2
 
2.3%
신월점 1
 
1.1%
동원홈푸드이팜 1
 
1.1%
로데오 1
 
1.1%
농부아들마트 1
 
1.1%
주)케이알씨 1
 
1.1%
에이스유통 1
 
1.1%
봉푸드 1
 
1.1%
Other values (74) 74
85.1%
2024-04-30T04:34:36.500189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
드 20
 
4.6%
푸 20
 
4.6%
주 17
 
3.9%
( 15
 
3.4%
) 15
 
3.4%
15
 
3.4%
유 10
 
2.3%
농 9
 
2.1%
원 8
 
1.8%
점 8
 
1.8%
Other values (136) 300
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 378
86.5%
Open Punctuation 15
 
3.4%
Close Punctuation 15
 
3.4%
Space Separator 15
 
3.4%
Uppercase Letter 9
 
2.1%
Lowercase Letter 3
 
0.7%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 20
 
5.3%
푸 20
 
5.3%
주 17
 
4.5%
유 10
 
2.6%
농 9
 
2.4%
원 8
 
2.1%
점 8
 
2.1%
통 8
 
2.1%
스 8
 
2.1%
식 8
 
2.1%
Other values (124) 262
69.3%
Uppercase Letter
ValueCountFrequency (%)
F 3
33.3%
D 2
22.2%
O 2
22.2%
B 1
 
11.1%
G 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
66.7%
d 1
33.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
/ 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 378
86.5%
Common 47
 
10.8%
Latin 12
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 20
 
5.3%
푸 20
 
5.3%
주 17
 
4.5%
유 10
 
2.6%
농 9
 
2.4%
원 8
 
2.1%
점 8
 
2.1%
통 8
 
2.1%
스 8
 
2.1%
식 8
 
2.1%
Other values (124) 262
69.3%
Latin
ValueCountFrequency (%)
F 3
25.0%
o 2
16.7%
D 2
16.7%
O 2
16.7%
B 1
 
8.3%
d 1
 
8.3%
G 1
 
8.3%
Common
ValueCountFrequency (%)
( 15
31.9%
) 15
31.9%
15
31.9%
& 1
 
2.1%
/ 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 378
86.5%
ASCII 59
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
드 20
 
5.3%
푸 20
 
5.3%
주 17
 
4.5%
유 10
 
2.6%
농 9
 
2.4%
원 8
 
2.1%
점 8
 
2.1%
통 8
 
2.1%
스 8
 
2.1%
식 8
 
2.1%
Other values (124) 262
69.3%
ASCII
ValueCountFrequency (%)
( 15
25.4%
) 15
25.4%
15
25.4%
F 3
 
5.1%
o 2
 
3.4%
D 2
 
3.4%
O 2
 
3.4%
B 1
 
1.7%
& 1
 
1.7%
d 1
 
1.7%
Other values (2) 2
 
3.4%

최종수정일자
Date

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum2008-04-14 16:32:59
Maximum2024-02-26 11:14:08
2024-04-30T04:34:36.809211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:34:36.921706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
I
36 
U
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 36
50.0%
U 36
50.0%

Length

2024-04-30T04:34:37.044109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:37.146841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 36
50.0%
u 36
50.0%

데이터갱신일자
Categorical

Distinct27
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size708.0 B
2018-08-31 23:59:59.0
33 
2022-12-08 22:03:00.0
11 
2021-11-01 23:06:00.0
 
2
2022-12-02 22:04:00.0
 
2
2022-12-06 00:09:00.0
 
2
Other values (22)
22 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique22 ?
Unique (%)30.6%

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 row2023-12-01 22:08:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 33
45.8%
2022-12-08 22:03:00.0 11
 
15.3%
2021-11-01 23:06:00.0 2
 
2.8%
2022-12-02 22:04:00.0 2
 
2.8%
2022-12-06 00:09:00.0 2
 
2.8%
2022-02-16 02:40:00.0 1
 
1.4%
2022-12-04 22:08:00.0 1
 
1.4%
2019-12-01 02:40:00.0 1
 
1.4%
2022-11-01 21:00:00.0 1
 
1.4%
2018-12-28 02:40:00.0 1
 
1.4%
Other values (17) 17
23.6%

Length

2024-04-30T04:34:37.239695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 33
22.9%
23:59:59.0 33
22.9%
22:03:00.0 13
 
9.0%
2022-12-08 11
 
7.6%
02:40:00.0 10
 
6.9%
22:04:00.0 3
 
2.1%
00:09:00.0 2
 
1.4%
2022-12-07 2
 
1.4%
22:08:00.0 2
 
1.4%
2022-12-04 2
 
1.4%
Other values (29) 33
22.9%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
집단급식소 식품판매업
72 

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 72
100.0%

Length

2024-04-30T04:34:37.348539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:37.447315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 72
50.0%
식품판매업 72
50.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)87.3%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean186349.04
Minimum184503.79
Maximum189471.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:37.551976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184503.79
5-th percentile184632.87
Q1185345
median185814.94
Q3187470.96
95-th percentile188769.24
Maximum189471.31
Range4967.5153
Interquartile range (IQR)2125.964

Descriptive statistics

Standard deviation1347.6599
Coefficient of variation (CV)0.0072319124
Kurtosis-0.92996951
Mean186349.04
Median Absolute Deviation (MAD)890.85263
Skewness0.5296572
Sum13230782
Variance1816187.2
MonotonicityNot monotonic
2024-04-30T04:34:37.689118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185344.997632129 3
 
4.2%
187531.38903074 3
 
4.2%
185404.005193921 3
 
4.2%
184632.866121324 2
 
2.8%
185529.138798131 2
 
2.8%
185744.924947583 2
 
2.8%
185275.433537253 1
 
1.4%
184569.484666031 1
 
1.4%
187914.441912956 1
 
1.4%
185281.396053897 1
 
1.4%
Other values (52) 52
72.2%
ValueCountFrequency (%)
184503.790903959 1
1.4%
184569.484666031 1
1.4%
184581.783215705 1
1.4%
184632.866121324 2
2.8%
184730.131827127 1
1.4%
184758.604262927 1
1.4%
184900.542630793 1
1.4%
184924.090584079 1
1.4%
184929.382146282 1
1.4%
184972.561922366 1
1.4%
ValueCountFrequency (%)
189471.306217651 1
1.4%
189032.818409648 1
1.4%
188957.113121688 1
1.4%
188778.717365903 1
1.4%
188759.75407829 1
1.4%
188531.284850348 1
1.4%
188387.950363074 1
1.4%
188112.535073523 1
1.4%
188097.549555048 1
1.4%
187994.478131522 1
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)87.3%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean447212.95
Minimum444855.74
Maximum449735.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:37.815350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444855.74
5-th percentile445983.71
Q1446444.47
median446995.11
Q3447950.27
95-th percentile449139.46
Maximum449735.61
Range4879.8664
Interquartile range (IQR)1505.8067

Descriptive statistics

Standard deviation1024.4428
Coefficient of variation (CV)0.002290727
Kurtosis-0.25407782
Mean447212.95
Median Absolute Deviation (MAD)679.22484
Skewness0.45433183
Sum31752120
Variance1049483
MonotonicityNot monotonic
2024-04-30T04:34:37.946564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447358.551761155 3
 
4.2%
447310.609246804 3
 
4.2%
446558.739627264 3
 
4.2%
448693.308555722 2
 
2.8%
446315.885210727 2
 
2.8%
446190.192625377 2
 
2.8%
448189.097480124 1
 
1.4%
447955.375197522 1
 
1.4%
446872.675940057 1
 
1.4%
448338.776287268 1
 
1.4%
Other values (52) 52
72.2%
ValueCountFrequency (%)
444855.740951957 1
1.4%
445352.156222859 1
1.4%
445857.210637827 1
1.4%
445935.465515155 1
1.4%
446031.94974102 1
1.4%
446140.068718483 1
1.4%
446147.124980307 1
1.4%
446190.192625377 2
2.8%
446214.961412122 1
1.4%
446216.954241004 1
1.4%
ValueCountFrequency (%)
449735.607390575 1
1.4%
449325.917753825 1
1.4%
449319.26163953 1
1.4%
449296.04730161 1
1.4%
448982.864936069 1
1.4%
448806.969143828 1
1.4%
448693.308555722 2
2.8%
448692.51478741 1
1.4%
448450.878897551 1
1.4%
448338.776287268 1
1.4%

위생업태명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
집단급식소 식품판매업
44 
<NA>
28 

Length

Max length11
Median length11
Mean length8.2777778
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 44
61.1%
<NA> 28
38.9%

Length

2024-04-30T04:34:38.053519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:38.139517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 44
37.9%
식품판매업 44
37.9%
na 28
24.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
68 
0
 
4

Length

Max length4
Median length4
Mean length3.8333333
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> 68
94.4%
0 4
 
5.6%

Length

2024-04-30T04:34:38.236774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:38.333266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
94.4%
0 4
 
5.6%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
68 
0
 
4

Length

Max length4
Median length4
Mean length3.8333333
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> 68
94.4%
0 4
 
5.6%

Length

2024-04-30T04:34:38.420846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:38.506441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
94.4%
0 4
 
5.6%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

급수시설구분명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
59 
상수도전용
13 

Length

Max length5
Median length4
Mean length4.1805556
Min length4

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> 59
81.9%
상수도전용 13
 
18.1%

Length

2024-04-30T04:34:38.590802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:38.674316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
81.9%
상수도전용 13
 
18.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
68 
0
 
4

Length

Max length4
Median length4
Mean length3.8333333
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> 68
94.4%
0 4
 
5.6%

Length

2024-04-30T04:34:38.764399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:38.849236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
94.4%
0 4
 
5.6%

본사종업원수
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
50 
0
22 

Length

Max length4
Median length4
Mean length3.0833333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
69.4%
0 22
30.6%

Length

2024-04-30T04:34:38.943819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:39.032384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
69.4%
0 22
30.6%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
50 
0
22 

Length

Max length4
Median length4
Mean length3.0833333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
69.4%
0 22
30.6%

Length

2024-04-30T04:34:39.128284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:39.217509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
69.4%
0 22
30.6%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
50 
0
22 

Length

Max length4
Median length4
Mean length3.0833333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
69.4%
0 22
30.6%

Length

2024-04-30T04:34:39.317406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:39.410693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
69.4%
0 22
30.6%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
50 
0
22 

Length

Max length4
Median length4
Mean length3.0833333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
69.4%
0 22
30.6%

Length

2024-04-30T04:34:39.505950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:39.602339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
69.4%
0 22
30.6%

건물소유구분명
Categorical

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
32 
임대
27 
자가
13 

Length

Max length4
Median length2
Mean length2.8888889
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
44.4%
임대 27
37.5%
자가 13
18.1%

Length

2024-04-30T04:34:39.705685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:39.824136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
44.4%
임대 27
37.5%
자가 13
18.1%

보증액
Categorical

IMBALANCE 

Distinct6
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
60 
5000000
 
4
10000000
 
3
0
 
3
17000000
 
1

Length

Max length8
Median length4
Mean length4.3194444
Min length1

Unique

Unique2 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 60
83.3%
5000000 4
 
5.6%
10000000 3
 
4.2%
0 3
 
4.2%
17000000 1
 
1.4%
15000000 1
 
1.4%

Length

2024-04-30T04:34:39.930354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:34:40.048282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
83.3%
5000000 4
 
5.6%
10000000 3
 
4.2%
0 3
 
4.2%
17000000 1
 
1.4%
15000000 1
 
1.4%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)81.8%
Missing61
Missing (%)84.7%
Infinite0
Infinite (%)0.0%
Mean440909.09
Minimum0
Maximum1500000
Zeros3
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:40.147193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q150000
median400000
Q3575000
95-th percentile1250000
Maximum1500000
Range1500000
Interquartile range (IQR)525000

Descriptive statistics

Standard deviation472661.71
Coefficient of variation (CV)1.0720162
Kurtosis1.2949791
Mean440909.09
Median Absolute Deviation (MAD)300000
Skewness1.2239223
Sum4850000
Variance2.2340909 × 1011
MonotonicityNot monotonic
2024-04-30T04:34:40.239722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3
 
4.2%
100000 1
 
1.4%
400000 1
 
1.4%
500000 1
 
1.4%
550000 1
 
1.4%
600000 1
 
1.4%
1000000 1
 
1.4%
1500000 1
 
1.4%
200000 1
 
1.4%
(Missing) 61
84.7%
ValueCountFrequency (%)
0 3
4.2%
100000 1
 
1.4%
200000 1
 
1.4%
400000 1
 
1.4%
500000 1
 
1.4%
550000 1
 
1.4%
600000 1
 
1.4%
1000000 1
 
1.4%
1500000 1
 
1.4%
ValueCountFrequency (%)
1500000 1
 
1.4%
1000000 1
 
1.4%
600000 1
 
1.4%
550000 1
 
1.4%
500000 1
 
1.4%
400000 1
 
1.4%
200000 1
 
1.4%
100000 1
 
1.4%
0 3
4.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.3%
Missing28
Missing (%)38.9%
Memory size276.0 B
False
44 
(Missing)
28 
ValueCountFrequency (%)
False 44
61.1%
(Missing) 28
38.9%
2024-04-30T04:34:40.327948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)20.5%
Missing28
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean11.514318
Minimum0
Maximum158
Zeros36
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-04-30T04:34:40.397605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile72.45
Maximum158
Range158
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32.314008
Coefficient of variation (CV)2.8064196
Kurtosis11.933691
Mean11.514318
Median Absolute Deviation (MAD)0
Skewness3.4056485
Sum506.63
Variance1044.1951
MonotonicityNot monotonic
2024-04-30T04:34:40.502304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 36
50.0%
58.0 1
 
1.4%
24.0 1
 
1.4%
119.44 1
 
1.4%
75.0 1
 
1.4%
13.19 1
 
1.4%
33.0 1
 
1.4%
26.0 1
 
1.4%
158.0 1
 
1.4%
(Missing) 28
38.9%
ValueCountFrequency (%)
0.0 36
50.0%
13.19 1
 
1.4%
24.0 1
 
1.4%
26.0 1
 
1.4%
33.0 1
 
1.4%
58.0 1
 
1.4%
75.0 1
 
1.4%
119.44 1
 
1.4%
158.0 1
 
1.4%
ValueCountFrequency (%)
158.0 1
 
1.4%
119.44 1
 
1.4%
75.0 1
 
1.4%
58.0 1
 
1.4%
33.0 1
 
1.4%
26.0 1
 
1.4%
24.0 1
 
1.4%
13.19 1
 
1.4%
0.0 36
50.0%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
6231400003140000-122-2021-0000220210121<NA>3폐업2폐업20220721<NA><NA><NA><NA>49.44158847서울특별시 양천구 신월동 992-4서울특별시 양천구 지양로 26, 202호 (신월동)8041정원푸드2022-07-21 14:23:38U2021-12-06 22:03:00.0집단급식소 식품판매업185529.138798446315.885211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6331400003140000-122-2021-000032021-02-22<NA>3폐업2폐업2023-04-04<NA><NA><NA><NA>48.69158-830서울특별시 양천구 신월동 205-15서울특별시 양천구 남부순환로58길 27, 1층 (신월동)7915(주)더베스트유원2023-04-04 16:01:02U2022-12-04 00:06:00.0집단급식소 식품판매업185010.573971447509.236027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6431400003140000-122-2021-000042021-04-06<NA>1영업/정상1영업<NA><NA><NA><NA>022061513939.6158-814서울특별시 양천구 목동 728-21서울특별시 양천구 목동중앙남로5길 46, 1층 (목동)7959김치마켓2023-09-21 11:38:58U2022-12-08 22:03:00.0집단급식소 식품판매업187950.283555448306.36604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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6731400003140000-122-2021-000072021-12-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.0158-829서울특별시 양천구 신월동 166-3서울특별시 양천구 남부순환로40길 3, 2층 (신월동)7910한가람2023-08-21 14:17:16U2022-12-07 22:03:00.0집단급식소 식품판매업184758.604263448099.308173<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6831400003140000-122-2022-000012022-02-14<NA>1영업/정상1영업<NA><NA><NA><NA>0708862114530.0158-831서울특별시 양천구 신월동 220-7 1층 우측호서울특별시 양천구 곰달래로6길 16-11, 1층 우측호 (신월동)7924태현2023-09-21 11:36:40U2022-12-08 22:03:00.0집단급식소 식품판매업185344.997632447358.551761<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6931400003140000-122-2022-000022022-02-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>130.0158-846서울특별시 양천구 신월동 974-10서울특별시 양천구 남부순환로70길 11-10 (신월동)8040(주)정원푸드서비스2023-09-21 11:33:24U2022-12-08 22:03:00.0집단급식소 식품판매업185404.005194446558.739627<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7031400003140000-122-2022-000032022-12-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-840서울특별시 양천구 신월동 540-5서울특별시 양천구 신월로11길 14, 1층 (신월동)8031우유 신월점2023-09-21 11:32:05U2022-12-08 22:03:00.0집단급식소 식품판매업185814.943214446286.211801<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7131400003140000-122-2023-000012023-12-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0158-857서울특별시 양천구 신정동 905-2 해풍빌딩서울특별시 양천구 신정중앙로 68, 403호 (신정동, 해풍빌딩)7945동원홈푸드이팜 마포/서대문대리점2023-12-06 14:41:16I2022-11-02 00:08:00.0집단급식소 식품판매업187496.753603447163.623643<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>