Overview

Dataset statistics

Number of variables44
Number of observations264
Missing cells2286
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.1 KiB
Average record size in memory376.5 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18183/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (50.1%)Imbalance
남성종사자수 is highly imbalanced (59.3%)Imbalance
여성종사자수 is highly imbalanced (63.2%)Imbalance
영업장주변구분명 is highly imbalanced (65.8%)Imbalance
등급구분명 is highly imbalanced (59.5%)Imbalance
총인원 is highly imbalanced (75.0%)Imbalance
인허가취소일자 has 264 (100.0%) missing valuesMissing
폐업일자 has 40 (15.2%) missing valuesMissing
휴업시작일자 has 264 (100.0%) missing valuesMissing
휴업종료일자 has 264 (100.0%) missing valuesMissing
재개업일자 has 264 (100.0%) missing valuesMissing
전화번호 has 90 (34.1%) missing valuesMissing
소재지면적 has 37 (14.0%) missing valuesMissing
도로명주소 has 99 (37.5%) missing valuesMissing
도로명우편번호 has 102 (38.6%) missing valuesMissing
좌표정보(X) has 6 (2.3%) missing valuesMissing
좌표정보(Y) has 6 (2.3%) missing valuesMissing
다중이용업소여부 has 29 (11.0%) missing valuesMissing
시설총규모 has 29 (11.0%) missing valuesMissing
전통업소지정번호 has 264 (100.0%) missing valuesMissing
전통업소주된음식 has 264 (100.0%) missing valuesMissing
홈페이지 has 264 (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
소재지면적 has 3 (1.1%) zerosZeros
시설총규모 has 219 (83.0%) zerosZeros

Reproduction

Analysis started2024-04-29 19:37:40.635113
Analysis finished2024-04-29 19:37:41.542465
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3060000
264 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 264
100.0%

Length

2024-04-30T04:37:41.599597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:41.672256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 264
100.0%

관리번호
Text

UNIQUE 

Distinct264
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T04:37:41.810561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5808
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

Unique264 ?
Unique (%)100.0%

Sample

1st row3060000-109-1985-00408
2nd row3060000-109-1988-00409
3rd row3060000-109-1990-00410
4th row3060000-109-1991-00411
5th row3060000-109-1994-00412
ValueCountFrequency (%)
3060000-109-1985-00408 1
 
0.4%
3060000-109-2013-00005 1
 
0.4%
3060000-109-2014-00007 1
 
0.4%
3060000-109-2012-00009 1
 
0.4%
3060000-109-2012-00010 1
 
0.4%
3060000-109-2012-00011 1
 
0.4%
3060000-109-2012-00012 1
 
0.4%
3060000-109-2012-00013 1
 
0.4%
3060000-109-2012-00014 1
 
0.4%
3060000-109-2012-00015 1
 
0.4%
Other values (254) 254
96.2%
2024-04-30T04:37:42.095312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2913
50.2%
- 792
 
13.6%
1 514
 
8.8%
2 359
 
6.2%
9 342
 
5.9%
3 339
 
5.8%
6 322
 
5.5%
5 68
 
1.2%
4 66
 
1.1%
7 52
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5016
86.4%
Dash Punctuation 792
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2913
58.1%
1 514
 
10.2%
2 359
 
7.2%
9 342
 
6.8%
3 339
 
6.8%
6 322
 
6.4%
5 68
 
1.4%
4 66
 
1.3%
7 52
 
1.0%
8 41
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 792
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5808
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2913
50.2%
- 792
 
13.6%
1 514
 
8.8%
2 359
 
6.2%
9 342
 
5.9%
3 339
 
5.8%
6 322
 
5.5%
5 68
 
1.2%
4 66
 
1.1%
7 52
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2913
50.2%
- 792
 
13.6%
1 514
 
8.8%
2 359
 
6.2%
9 342
 
5.9%
3 339
 
5.8%
6 322
 
5.5%
5 68
 
1.2%
4 66
 
1.1%
7 52
 
0.9%

인허가일자
Date

Distinct259
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1985-02-21 00:00:00
Maximum2024-02-08 00:00:00
2024-04-30T04:37:42.227682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:42.378880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
3
224 
1
40 

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 (%)
3 224
84.8%
1 40
 
15.2%

Length

2024-04-30T04:37:42.516036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:42.600034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 224
84.8%
1 40
 
15.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
224 
영업/정상
40 

Length

Max length5
Median length2
Mean length2.4545455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 224
84.8%
영업/정상 40
 
15.2%

Length

2024-04-30T04:37:42.686944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:42.775006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 224
84.8%
영업/정상 40
 
15.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2
224 
1
40 

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 (%)
2 224
84.8%
1 40
 
15.2%

Length

2024-04-30T04:37:42.857129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:42.938512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 224
84.8%
1 40
 
15.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
폐업
224 
영업
40 

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 224
84.8%
영업 40
 
15.2%

Length

2024-04-30T04:37:43.023180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:43.109868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 224
84.8%
영업 40
 
15.2%

폐업일자
Date

MISSING 

Distinct206
Distinct (%)92.0%
Missing40
Missing (%)15.2%
Memory size2.2 KiB
Minimum1996-06-27 00:00:00
Maximum2024-01-25 00:00:00
2024-04-30T04:37:43.197893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:43.316784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

전화번호
Text

MISSING 

Distinct163
Distinct (%)93.7%
Missing90
Missing (%)34.1%
Memory size2.2 KiB
2024-04-30T04:37:43.544282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.62069
Min length2

Characters and Unicode

Total characters1848
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

Unique153 ?
Unique (%)87.9%

Sample

1st row0204336290
2nd row0204941518
3rd row0204922213
4th row0234223161
5th row0200000000
ValueCountFrequency (%)
02 126
35.5%
433 8
 
2.3%
435 5
 
1.4%
438 4
 
1.1%
4917400 3
 
0.8%
437 3
 
0.8%
070 3
 
0.8%
491 3
 
0.8%
496 3
 
0.8%
4386440 2
 
0.6%
Other values (184) 195
54.9%
2024-04-30T04:37:43.902274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 336
18.2%
2 295
16.0%
241
13.0%
4 200
10.8%
3 168
9.1%
9 127
 
6.9%
1 105
 
5.7%
6 101
 
5.5%
7 96
 
5.2%
8 92
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1607
87.0%
Space Separator 241
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 336
20.9%
2 295
18.4%
4 200
12.4%
3 168
10.5%
9 127
 
7.9%
1 105
 
6.5%
6 101
 
6.3%
7 96
 
6.0%
8 92
 
5.7%
5 87
 
5.4%
Space Separator
ValueCountFrequency (%)
241
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1848
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 336
18.2%
2 295
16.0%
241
13.0%
4 200
10.8%
3 168
9.1%
9 127
 
6.9%
1 105
 
5.7%
6 101
 
5.5%
7 96
 
5.2%
8 92
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 336
18.2%
2 295
16.0%
241
13.0%
4 200
10.8%
3 168
9.1%
9 127
 
6.9%
1 105
 
5.7%
6 101
 
5.5%
7 96
 
5.2%
8 92
 
5.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct148
Distinct (%)65.2%
Missing37
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean41.602863
Minimum0
Maximum333.61
Zeros3
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T04:37:44.035105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.95
Q111.375
median27.49
Q349.5
95-th percentile122.279
Maximum333.61
Range333.61
Interquartile range (IQR)38.125

Descriptive statistics

Standard deviation47.276548
Coefficient of variation (CV)1.1363773
Kurtosis8.9136684
Mean41.602863
Median Absolute Deviation (MAD)17.51
Skewness2.583238
Sum9443.85
Variance2235.072
MonotonicityNot monotonic
2024-04-30T04:37:44.153061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 11
 
4.2%
6.6 8
 
3.0%
10.0 8
 
3.0%
16.5 7
 
2.7%
9.9 6
 
2.3%
30.0 5
 
1.9%
13.2 4
 
1.5%
19.8 4
 
1.5%
4.95 4
 
1.5%
40.0 3
 
1.1%
Other values (138) 167
63.3%
(Missing) 37
 
14.0%
ValueCountFrequency (%)
0.0 3
1.1%
1.0 1
 
0.4%
2.3 1
 
0.4%
3.0 1
 
0.4%
3.3 1
 
0.4%
3.73 1
 
0.4%
4.0 1
 
0.4%
4.3 1
 
0.4%
4.5 1
 
0.4%
4.95 4
1.5%
ValueCountFrequency (%)
333.61 1
0.4%
238.35 1
0.4%
217.8 1
0.4%
200.0 1
0.4%
198.0 1
0.4%
197.16 1
0.4%
173.88 1
0.4%
165.0 1
0.4%
164.71 1
0.4%
161.85 1
0.4%

소재지우편번호
Text

Distinct83
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T04:37:44.378415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0795455
Min length6

Characters and Unicode

Total characters1605
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

Unique29 ?
Unique (%)11.0%

Sample

1st row131825
2nd row131865
3rd row131818
4th row131863
5th row131805
ValueCountFrequency (%)
131809 20
 
7.6%
131848 13
 
4.9%
131865 12
 
4.5%
131822 11
 
4.2%
131872 9
 
3.4%
131875 8
 
3.0%
131810 8
 
3.0%
131816 7
 
2.7%
131877 6
 
2.3%
131811 6
 
2.3%
Other values (73) 164
62.1%
2024-04-30T04:37:44.715232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 594
37.0%
8 308
19.2%
3 287
17.9%
2 85
 
5.3%
0 76
 
4.7%
7 65
 
4.0%
6 58
 
3.6%
5 57
 
3.6%
9 32
 
2.0%
4 22
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1584
98.7%
Dash Punctuation 21
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 594
37.5%
8 308
19.4%
3 287
18.1%
2 85
 
5.4%
0 76
 
4.8%
7 65
 
4.1%
6 58
 
3.7%
5 57
 
3.6%
9 32
 
2.0%
4 22
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1605
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 594
37.0%
8 308
19.2%
3 287
17.9%
2 85
 
5.3%
0 76
 
4.7%
7 65
 
4.0%
6 58
 
3.6%
5 57
 
3.6%
9 32
 
2.0%
4 22
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1605
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 594
37.0%
8 308
19.2%
3 287
17.9%
2 85
 
5.3%
0 76
 
4.7%
7 65
 
4.0%
6 58
 
3.6%
5 57
 
3.6%
9 32
 
2.0%
4 22
 
1.4%

지번주소
Text

Distinct243
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T04:37:44.979634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length22.511364
Min length17

Characters and Unicode

Total characters5943
Distinct characters117
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

Unique229 ?
Unique (%)86.7%

Sample

1st row서울특별시 중랑구 면목동 341-6
2nd row서울특별시 중랑구 신내동 373-11
3rd row서울특별시 중랑구 면목동 547-30
4th row서울특별시 중랑구 상봉동 485-0 신내테크노타운 302호
5th row서울특별시 중랑구 망우동 402-59
ValueCountFrequency (%)
서울특별시 264
22.0%
중랑구 264
22.0%
면목동 83
 
6.9%
망우동 46
 
3.8%
중화동 42
 
3.5%
신내동 38
 
3.2%
묵동 30
 
2.5%
상봉동 25
 
2.1%
1층 22
 
1.8%
645 9
 
0.8%
Other values (284) 377
31.4%
2024-04-30T04:37:45.350694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1163
19.6%
중 309
 
5.2%
동 268
 
4.5%
랑 266
 
4.5%
구 266
 
4.5%
시 266
 
4.5%
서 265
 
4.5%
울 264
 
4.4%
별 264
 
4.4%
특 264
 
4.4%
Other values (107) 2348
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3301
55.5%
Decimal Number 1237
 
20.8%
Space Separator 1163
 
19.6%
Dash Punctuation 232
 
3.9%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Uppercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 309
 
9.4%
동 268
 
8.1%
랑 266
 
8.1%
구 266
 
8.1%
시 266
 
8.1%
서 265
 
8.0%
울 264
 
8.0%
별 264
 
8.0%
특 264
 
8.0%
면 86
 
2.6%
Other values (91) 783
23.7%
Decimal Number
ValueCountFrequency (%)
1 253
20.5%
2 167
13.5%
3 130
10.5%
4 127
10.3%
0 123
9.9%
6 114
9.2%
5 109
8.8%
8 80
 
6.5%
7 79
 
6.4%
9 55
 
4.4%
Space Separator
ValueCountFrequency (%)
1163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 232
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3301
55.5%
Common 2641
44.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 309
 
9.4%
동 268
 
8.1%
랑 266
 
8.1%
구 266
 
8.1%
시 266
 
8.1%
서 265
 
8.0%
울 264
 
8.0%
별 264
 
8.0%
특 264
 
8.0%
면 86
 
2.6%
Other values (91) 783
23.7%
Common
ValueCountFrequency (%)
1163
44.0%
1 253
 
9.6%
- 232
 
8.8%
2 167
 
6.3%
3 130
 
4.9%
4 127
 
4.8%
0 123
 
4.7%
6 114
 
4.3%
5 109
 
4.1%
8 80
 
3.0%
Other values (5) 143
 
5.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3301
55.5%
ASCII 2642
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1163
44.0%
1 253
 
9.6%
- 232
 
8.8%
2 167
 
6.3%
3 130
 
4.9%
4 127
 
4.8%
0 123
 
4.7%
6 114
 
4.3%
5 109
 
4.1%
8 80
 
3.0%
Other values (6) 144
 
5.5%
Hangul
ValueCountFrequency (%)
중 309
 
9.4%
동 268
 
8.1%
랑 266
 
8.1%
구 266
 
8.1%
시 266
 
8.1%
서 265
 
8.0%
울 264
 
8.0%
별 264
 
8.0%
특 264
 
8.0%
면 86
 
2.6%
Other values (91) 783
23.7%

도로명주소
Text

MISSING 

Distinct162
Distinct (%)98.2%
Missing99
Missing (%)37.5%
Memory size2.2 KiB
2024-04-30T04:37:45.583868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length30.89697
Min length22

Characters and Unicode

Total characters5098
Distinct characters134
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

Unique159 ?
Unique (%)96.4%

Sample

1st row서울특별시 중랑구 면목로33길 44 (면목동)
2nd row서울특별시 중랑구 봉화산로 123, 302호 (상봉동,신내테크노타운)
3rd row서울특별시 중랑구 봉화산로4길 16 (중화동)
4th row서울특별시 중랑구 사가정로 332, 홈플러스 지상1층 (면목동)
5th row서울특별시 중랑구 봉화산로56길 46 (신내동)
ValueCountFrequency (%)
서울특별시 165
 
16.6%
중랑구 165
 
16.6%
면목동 44
 
4.4%
1층 29
 
2.9%
중화동 26
 
2.6%
망우동 24
 
2.4%
묵동 17
 
1.7%
상봉동 16
 
1.6%
신내동 12
 
1.2%
망우로 11
 
1.1%
Other values (300) 483
48.7%
2024-04-30T04:37:45.939757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
827
 
16.2%
중 208
 
4.1%
1 206
 
4.0%
동 205
 
4.0%
랑 176
 
3.5%
구 168
 
3.3%
로 166
 
3.3%
서 165
 
3.2%
특 165
 
3.2%
별 165
 
3.2%
Other values (124) 2647
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2894
56.8%
Decimal Number 867
 
17.0%
Space Separator 827
 
16.2%
Close Punctuation 165
 
3.2%
Open Punctuation 165
 
3.2%
Other Punctuation 143
 
2.8%
Dash Punctuation 31
 
0.6%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 208
 
7.2%
동 205
 
7.1%
랑 176
 
6.1%
구 168
 
5.8%
로 166
 
5.7%
서 165
 
5.7%
특 165
 
5.7%
별 165
 
5.7%
시 165
 
5.7%
울 165
 
5.7%
Other values (107) 1146
39.6%
Decimal Number
ValueCountFrequency (%)
1 206
23.8%
2 135
15.6%
3 106
12.2%
4 97
11.2%
6 67
 
7.7%
5 65
 
7.5%
0 59
 
6.8%
7 47
 
5.4%
8 43
 
5.0%
9 42
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 5
83.3%
C 1
 
16.7%
Space Separator
ValueCountFrequency (%)
827
100.0%
Close Punctuation
ValueCountFrequency (%)
) 165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 165
100.0%
Other Punctuation
ValueCountFrequency (%)
, 143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2894
56.8%
Common 2198
43.1%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 208
 
7.2%
동 205
 
7.1%
랑 176
 
6.1%
구 168
 
5.8%
로 166
 
5.7%
서 165
 
5.7%
특 165
 
5.7%
별 165
 
5.7%
시 165
 
5.7%
울 165
 
5.7%
Other values (107) 1146
39.6%
Common
ValueCountFrequency (%)
827
37.6%
1 206
 
9.4%
) 165
 
7.5%
( 165
 
7.5%
, 143
 
6.5%
2 135
 
6.1%
3 106
 
4.8%
4 97
 
4.4%
6 67
 
3.0%
5 65
 
3.0%
Other values (5) 222
 
10.1%
Latin
ValueCountFrequency (%)
B 5
83.3%
C 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2894
56.8%
ASCII 2204
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
827
37.5%
1 206
 
9.3%
) 165
 
7.5%
( 165
 
7.5%
, 143
 
6.5%
2 135
 
6.1%
3 106
 
4.8%
4 97
 
4.4%
6 67
 
3.0%
5 65
 
2.9%
Other values (7) 228
 
10.3%
Hangul
ValueCountFrequency (%)
중 208
 
7.2%
동 205
 
7.1%
랑 176
 
6.1%
구 168
 
5.8%
로 166
 
5.7%
서 165
 
5.7%
특 165
 
5.7%
별 165
 
5.7%
시 165
 
5.7%
울 165
 
5.7%
Other values (107) 1146
39.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct92
Distinct (%)56.8%
Missing102
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean2120.5432
Minimum2004
Maximum2256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T04:37:46.063717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2015
Q12057
median2114.5
Q32169
95-th percentile2240.95
Maximum2256
Range252
Interquartile range (IQR)112

Descriptive statistics

Standard deviation71.917318
Coefficient of variation (CV)0.033914573
Kurtosis-1.1063813
Mean2120.5432
Median Absolute Deviation (MAD)55
Skewness0.20682865
Sum343528
Variance5172.1006
MonotonicityNot monotonic
2024-04-30T04:37:46.195660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2067 6
 
2.3%
2047 5
 
1.9%
2161 4
 
1.5%
2057 4
 
1.5%
2166 4
 
1.5%
2034 4
 
1.5%
2169 4
 
1.5%
2033 4
 
1.5%
2103 3
 
1.1%
2015 3
 
1.1%
Other values (82) 121
45.8%
(Missing) 102
38.6%
ValueCountFrequency (%)
2004 1
 
0.4%
2005 1
 
0.4%
2009 1
 
0.4%
2011 1
 
0.4%
2012 2
0.8%
2013 1
 
0.4%
2015 3
1.1%
2018 1
 
0.4%
2019 1
 
0.4%
2024 2
0.8%
ValueCountFrequency (%)
2256 1
0.4%
2253 1
0.4%
2248 2
0.8%
2246 1
0.4%
2245 1
0.4%
2244 1
0.4%
2241 2
0.8%
2240 2
0.8%
2239 2
0.8%
2237 2
0.8%

사업장명
Text

Distinct254
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T04:37:46.412964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length6.3977273
Min length2

Characters and Unicode

Total characters1689
Distinct characters310
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

Unique244 ?
Unique (%)92.4%

Sample

1st row송천식품
2nd row대한양봉진흥농원
3rd row진영상사
4th row(주)늘푸른마을
5th row진미유통
ValueCountFrequency (%)
주식회사 6
 
2.0%
신내점 3
 
1.0%
면목점 3
 
1.0%
주)후드피아 3
 
1.0%
한가네강정 2
 
0.7%
주)농업회사법인보아스농산 2
 
0.7%
홈플러스(주 2
 
0.7%
포인트컴퍼니 2
 
0.7%
동서울농업협동조합 2
 
0.7%
송천식품 2
 
0.7%
Other values (266) 272
91.0%
2024-04-30T04:37:46.764896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 74
 
4.4%
) 67
 
4.0%
( 65
 
3.8%
마 49
 
2.9%
식 44
 
2.6%
트 38
 
2.2%
이 35
 
2.1%
35
 
2.1%
품 33
 
2.0%
유 31
 
1.8%
Other values (300) 1218
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1492
88.3%
Close Punctuation 67
 
4.0%
Open Punctuation 65
 
3.8%
Space Separator 35
 
2.1%
Lowercase Letter 13
 
0.8%
Uppercase Letter 11
 
0.7%
Decimal Number 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 74
 
5.0%
마 49
 
3.3%
식 44
 
2.9%
트 38
 
2.5%
이 35
 
2.3%
품 33
 
2.2%
유 31
 
2.1%
스 31
 
2.1%
아 30
 
2.0%
사 28
 
1.9%
Other values (277) 1099
73.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
15.4%
n 2
15.4%
e 2
15.4%
a 2
15.4%
t 1
7.7%
i 1
7.7%
v 1
7.7%
c 1
7.7%
p 1
7.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
K 2
18.2%
F 2
18.2%
D 2
18.2%
P 1
 
9.1%
R 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
5 1
25.0%
6 1
25.0%
3 1
25.0%
7 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1492
88.3%
Common 173
 
10.2%
Latin 24
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 74
 
5.0%
마 49
 
3.3%
식 44
 
2.9%
트 38
 
2.5%
이 35
 
2.3%
품 33
 
2.2%
유 31
 
2.1%
스 31
 
2.1%
아 30
 
2.0%
사 28
 
1.9%
Other values (277) 1099
73.7%
Latin
ValueCountFrequency (%)
S 3
12.5%
K 2
 
8.3%
o 2
 
8.3%
n 2
 
8.3%
e 2
 
8.3%
a 2
 
8.3%
F 2
 
8.3%
D 2
 
8.3%
t 1
 
4.2%
P 1
 
4.2%
Other values (5) 5
20.8%
Common
ValueCountFrequency (%)
) 67
38.7%
( 65
37.6%
35
20.2%
& 2
 
1.2%
5 1
 
0.6%
6 1
 
0.6%
3 1
 
0.6%
7 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1492
88.3%
ASCII 197
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 74
 
5.0%
마 49
 
3.3%
식 44
 
2.9%
트 38
 
2.5%
이 35
 
2.3%
품 33
 
2.2%
유 31
 
2.1%
스 31
 
2.1%
아 30
 
2.0%
사 28
 
1.9%
Other values (277) 1099
73.7%
ASCII
ValueCountFrequency (%)
) 67
34.0%
( 65
33.0%
35
17.8%
S 3
 
1.5%
K 2
 
1.0%
o 2
 
1.0%
n 2
 
1.0%
e 2
 
1.0%
a 2
 
1.0%
F 2
 
1.0%
Other values (13) 15
 
7.6%

최종수정일자
Date

Distinct248
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1999-03-09 00:00:00
Maximum2024-04-17 14:30:03
2024-04-30T04:37:46.884766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:47.229794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
I
216 
U
48 

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 216
81.8%
U 48
 
18.2%

Length

2024-04-30T04:37:47.414752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:47.538875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 216
81.8%
u 48
 
18.2%

데이터갱신일자
Date

Distinct69
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-30T04:37:47.629764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:47.759070image/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 size2.2 KiB
식품소분업
264 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 264
100.0%

Length

2024-04-30T04:37:47.870490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:47.945404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 264
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct195
Distinct (%)75.6%
Missing6
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean207666.99
Minimum206266.6
Maximum209640.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T04:37:48.038082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206266.6
5-th percentile206521.5
Q1206980.57
median207594.08
Q3208295.1
95-th percentile208953.5
Maximum209640.29
Range3373.6816
Interquartile range (IQR)1314.5276

Descriptive statistics

Standard deviation800.74503
Coefficient of variation (CV)0.0038559091
Kurtosis-0.9739794
Mean207666.99
Median Absolute Deviation (MAD)639.53022
Skewness0.24915289
Sum53578083
Variance641192.61
MonotonicityNot monotonic
2024-04-30T04:37:48.158513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208208.786684767 9
 
3.4%
207089.21659098 9
 
3.4%
208183.558935157 6
 
2.3%
208295.099818379 5
 
1.9%
208658.077732594 5
 
1.9%
206788.048632489 3
 
1.1%
206774.874230196 3
 
1.1%
208628.324189314 3
 
1.1%
206859.21503478 3
 
1.1%
207923.745922676 3
 
1.1%
Other values (185) 209
79.2%
(Missing) 6
 
2.3%
ValueCountFrequency (%)
206266.603701754 1
0.4%
206310.371215011 1
0.4%
206346.045098344 1
0.4%
206377.995331013 1
0.4%
206417.240951707 1
0.4%
206438.692517058 1
0.4%
206448.314200373 1
0.4%
206472.224945227 1
0.4%
206479.265578579 1
0.4%
206514.495024064 1
0.4%
ValueCountFrequency (%)
209640.285276983 2
0.8%
209537.108569721 1
0.4%
209376.610753394 1
0.4%
209323.738296463 1
0.4%
209274.893741346 1
0.4%
209263.137025523 1
0.4%
209198.134045936 1
0.4%
209129.879364804 1
0.4%
209116.981356523 1
0.4%
209075.551726914 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct195
Distinct (%)75.6%
Missing6
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean454991.58
Minimum452074.06
Maximum457428.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T04:37:48.295563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452074.06
5-th percentile452711.88
Q1454174.69
median454984.41
Q3455849.02
95-th percentile457054.79
Maximum457428.66
Range5354.607
Interquartile range (IQR)1674.3325

Descriptive statistics

Standard deviation1280.086
Coefficient of variation (CV)0.0028134278
Kurtosis-0.59542771
Mean454991.58
Median Absolute Deviation (MAD)853.58956
Skewness-0.18876982
Sum1.1738783 × 108
Variance1638620.1
MonotonicityNot monotonic
2024-04-30T04:37:48.410285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457054.793655589 9
 
3.4%
453074.476763597 9
 
3.4%
454911.24852306 6
 
2.3%
456014.999180519 5
 
1.9%
454894.790220198 5
 
1.9%
455850.935638819 3
 
1.1%
457011.632629502 3
 
1.1%
455294.577026522 3
 
1.1%
456654.831186357 3
 
1.1%
455090.718335439 3
 
1.1%
Other values (185) 209
79.2%
(Missing) 6
 
2.3%
ValueCountFrequency (%)
452074.056304822 1
0.4%
452208.729385467 1
0.4%
452263.97241853 1
0.4%
452284.905148413 1
0.4%
452336.396167841 1
0.4%
452350.907653737 1
0.4%
452649.921914721 1
0.4%
452658.697048376 1
0.4%
452666.306495265 1
0.4%
452666.515244966 1
0.4%
ValueCountFrequency (%)
457428.663314438 1
 
0.4%
457345.712721801 1
 
0.4%
457302.240283913 1
 
0.4%
457282.566032636 1
 
0.4%
457273.035789206 1
 
0.4%
457236.317706626 1
 
0.4%
457156.039550731 1
 
0.4%
457097.848315 1
 
0.4%
457073.633385378 1
 
0.4%
457054.793655589 9
3.4%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
식품소분업
235 
<NA>
29 

Length

Max length5
Median length5
Mean length4.8901515
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 235
89.0%
<NA> 29
 
11.0%

Length

2024-04-30T04:37:48.520369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:48.594322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 235
89.0%
na 29
 
11.0%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
225 
0
 
21
1
 
12
2
 
6

Length

Max length4
Median length4
Mean length3.5568182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 225
85.2%
0 21
 
8.0%
1 12
 
4.5%
2 6
 
2.3%

Length

2024-04-30T04:37:48.679419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:48.771322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 225
85.2%
0 21
 
8.0%
1 12
 
4.5%
2 6
 
2.3%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
223 
0
24 
1
 
10
2
 
6
3
 
1

Length

Max length4
Median length4
Mean length3.5340909
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row3
4th row0
5th row2

Common Values

ValueCountFrequency (%)
<NA> 223
84.5%
0 24
 
9.1%
1 10
 
3.8%
2 6
 
2.3%
3 1
 
0.4%

Length

2024-04-30T04:37:48.869500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:48.967036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 223
84.5%
0 24
 
9.1%
1 10
 
3.8%
2 6
 
2.3%
3 1
 
0.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
232 
주택가주변
 
18
기타
 
12
아파트지역
 
2

Length

Max length5
Median length4
Mean length3.9848485
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 232
87.9%
주택가주변 18
 
6.8%
기타 12
 
4.5%
아파트지역 2
 
0.8%

Length

2024-04-30T04:37:49.061197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:49.150722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
87.9%
주택가주변 18
 
6.8%
기타 12
 
4.5%
아파트지역 2
 
0.8%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
232 
기타
 
22
자율
 
10

Length

Max length4
Median length4
Mean length3.7575758
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 232
87.9%
기타 22
 
8.3%
자율 10
 
3.8%

Length

2024-04-30T04:37:49.252835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:49.342103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 232
87.9%
기타 22
 
8.3%
자율 10
 
3.8%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
212 
상수도전용
52 

Length

Max length5
Median length4
Mean length4.1969697
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 212
80.3%
상수도전용 52
 
19.7%

Length

2024-04-30T04:37:49.437894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:49.517883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 212
80.3%
상수도전용 52
 
19.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
253 
0
 
11

Length

Max length4
Median length4
Mean length3.875
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> 253
95.8%
0 11
 
4.2%

Length

2024-04-30T04:37:49.602234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:49.689458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 253
95.8%
0 11
 
4.2%

본사종업원수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
170 
0
94 

Length

Max length4
Median length4
Mean length2.9318182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 170
64.4%
0 94
35.6%

Length

2024-04-30T04:37:49.788376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:49.872222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 170
64.4%
0 94
35.6%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
170 
0
94 

Length

Max length4
Median length4
Mean length2.9318182
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 170
64.4%
0 94
35.6%

Length

2024-04-30T04:37:49.967026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:50.062231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 170
64.4%
0 94
35.6%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
162 
0
88 
2
 
8
1
 
6

Length

Max length4
Median length4
Mean length2.8409091
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 162
61.4%
0 88
33.3%
2 8
 
3.0%
1 6
 
2.3%

Length

2024-04-30T04:37:50.158653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:50.257964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 162
61.4%
0 88
33.3%
2 8
 
3.0%
1 6
 
2.3%

공장생산직종업원수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
168 
0
94 
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.9090909
Min length1

Unique

Unique2 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 168
63.6%
0 94
35.6%
1 1
 
0.4%
2 1
 
0.4%

Length

2024-04-30T04:37:50.354597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:50.451380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 168
63.6%
0 94
35.6%
1 1
 
0.4%
2 1
 
0.4%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
105 
임대
105 
자가
54 

Length

Max length4
Median length2
Mean length2.7954545
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 105
39.8%
임대 105
39.8%
자가 54
20.5%

Length

2024-04-30T04:37:50.555272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:50.646869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 105
39.8%
임대 105
39.8%
자가 54
20.5%

보증액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
228 
0
36 

Length

Max length4
Median length4
Mean length3.5909091
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> 228
86.4%
0 36
 
13.6%

Length

2024-04-30T04:37:50.746278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:50.839279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
86.4%
0 36
 
13.6%

월세액
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
228 
0
36 

Length

Max length4
Median length4
Mean length3.5909091
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> 228
86.4%
0 36
 
13.6%

Length

2024-04-30T04:37:50.932194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:51.018804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
86.4%
0 36
 
13.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing29
Missing (%)11.0%
Memory size660.0 B
False
235 
(Missing)
29 
ValueCountFrequency (%)
False 235
89.0%
(Missing) 29
 
11.0%
2024-04-30T04:37:51.079124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)6.8%
Missing29
Missing (%)11.0%
Infinite0
Infinite (%)0.0%
Mean3.4820851
Minimum0
Maximum188.68
Zeros219
Zeros (%)83.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-04-30T04:37:51.147799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8.775
Maximum188.68
Range188.68
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.73425
Coefficient of variation (CV)5.6673657
Kurtosis59.759683
Mean3.4820851
Median Absolute Deviation (MAD)0
Skewness7.3913746
Sum818.29
Variance389.44061
MonotonicityNot monotonic
2024-04-30T04:37:51.233355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 219
83.0%
7.0 2
 
0.8%
92.0 1
 
0.4%
78.2 1
 
0.4%
188.68 1
 
0.4%
10.0 1
 
0.4%
173.88 1
 
0.4%
32.13 1
 
0.4%
0.75 1
 
0.4%
35.0 1
 
0.4%
Other values (6) 6
 
2.3%
(Missing) 29
 
11.0%
ValueCountFrequency (%)
0.0 219
83.0%
0.75 1
 
0.4%
7.0 2
 
0.8%
8.25 1
 
0.4%
10.0 1
 
0.4%
10.5 1
 
0.4%
11.9 1
 
0.4%
32.13 1
 
0.4%
33.0 1
 
0.4%
35.0 1
 
0.4%
ValueCountFrequency (%)
188.68 1
0.4%
173.88 1
0.4%
92.0 1
0.4%
90.0 1
0.4%
78.2 1
0.4%
40.0 1
0.4%
35.0 1
0.4%
33.0 1
0.4%
32.13 1
0.4%
11.9 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing264
Missing (%)100.0%
Memory size2.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-109-1985-0040819850221<NA>3폐업2폐업20150123<NA><NA><NA>0204336290122.6131825서울특별시 중랑구 면목동 341-6서울특별시 중랑구 면목로33길 44 (면목동)2241송천식품2011-10-30 14:07:44I2018-08-31 23:59:59.0식품소분업207301.5947452711.881844식품소분업21주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130600003060000-109-1988-0040919880210<NA>3폐업2폐업20080111<NA><NA><NA>020494151898.96131865서울특별시 중랑구 신내동 373-11<NA><NA>대한양봉진흥농원2004-07-29 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업21주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230600003060000-109-1990-0041019901123<NA>3폐업2폐업20061110<NA><NA><NA>0204922213121.53131818서울특별시 중랑구 면목동 547-30<NA><NA>진영상사2000-11-06 00:00:00I2018-08-31 23:59:59.0식품소분업207414.194332453778.711108식품소분업13주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330600003060000-109-1991-0041119910524<NA>3폐업2폐업20140402<NA><NA><NA>0234223161115.0131863서울특별시 중랑구 상봉동 485-0 신내테크노타운 302호서울특별시 중랑구 봉화산로 123, 302호 (상봉동,신내테크노타운)2048(주)늘푸른마을2011-05-09 15:43:11I2018-08-31 23:59:59.0식품소분업207681.184228455748.84875식품소분업20주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430600003060000-109-1994-0041219940906<NA>3폐업2폐업20031119<NA><NA><NA>020000000057.26131805서울특별시 중랑구 망우동 402-59<NA><NA>진미유통2000-11-06 00:00:00I2018-08-31 23:59:59.0식품소분업208844.712475454779.807166식품소분업22주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530600003060000-109-1995-0021919950223<NA>3폐업2폐업20070206<NA><NA><NA>02 439829338.7131875서울특별시 중랑구 중화동 10-20<NA><NA>용인농산2000-01-06 00:00:00I2018-08-31 23:59:59.0식품소분업207490.783678455558.564324식품소분업10주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630600003060000-109-1995-0022019950731<NA>3폐업2폐업19960627<NA><NA><NA>02 253712226.27131866서울특별시 중랑구 신내동 391-1<NA><NA>영창식품2001-10-04 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730600003060000-109-1996-0022119960306<NA>3폐업2폐업20190918<NA><NA><NA>02 434879029.2131882서울특별시 중랑구 중화동 329-17서울특별시 중랑구 봉화산로4길 16 (중화동)2100태능식품2019-09-18 15:04:51U2019-09-20 02:40:00.0식품소분업206646.148252455392.54534식품소분업11주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830600003060000-109-1996-0022219960820<NA>3폐업2폐업19980616<NA><NA><NA>02 433500037.72131809서울특별시 중랑구 망우동 572-0<NA><NA>진로하이퍼마트(용마점)2001-10-04 00:00:00I2018-08-31 23:59:59.0식품소분업208658.077733454894.79022식품소분업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930600003060000-109-1996-0022319961015<NA>3폐업2폐업19980807<NA><NA><NA>02 496500022.55131877서울특별시 중랑구 중화동 450-0<NA><NA>(주)진로종합유통진로하이퍼마트2001-10-04 00:00:00I2018-08-31 23:59:59.0식품소분업207163.791146454984.412729식품소분업22아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
25430600003060000-109-2023-000042023-06-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>48.0131-848서울특별시 중랑구 묵동 294-56서울특별시 중랑구 숙선옹주로 28, 1층 (묵동)2035주식회사 이디아이코리아2023-06-21 16:52:26I2022-12-05 22:03:00.0식품소분업206970.083435456891.43061<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25530600003060000-109-2023-000052023-06-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>96.96131-807서울특별시 중랑구 망우동 523-33 현대학원서울특별시 중랑구 상봉로 70, 현대학원 지층 (망우동)2175엠에스 컴퍼니2023-06-23 16:57:28I2022-12-05 22:05:00.0식품소분업208199.150901454415.366939<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25630600003060000-109-2023-000062023-07-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0131-859서울특별시 중랑구 상봉동 84-8서울특별시 중랑구 상봉로 97-1, 4층 402호 (상봉동)2152몸뚱이영양집합소2023-07-07 14:16:16I2022-12-07 00:09:00.0식품소분업208137.482423454701.034811<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25730600003060000-109-2023-000072023-07-19<NA>1영업/정상1영업<NA><NA><NA><NA>02 439 9593200.0131-875서울특별시 중랑구 중화동 282-12 서안유치원서울특별시 중랑구 동일로140길 15, 2층 (중화동)2047조은세상2024-04-04 16:26:02U2023-12-04 00:06:00.0식품소분업206993.031979455790.278886<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25830600003060000-109-2023-000082023-08-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.0131-853서울특별시 중랑구 묵동 250-34 명보빌딩서울특별시 중랑구 동일로143길 16, 명보빌딩 4층 402호 (묵동)2013(주)인피닛코리아2023-08-22 16:48:43I2022-12-07 22:04:00.0식품소분업206793.018169455902.640441<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25930600003060000-109-2023-000092023-08-31<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.0131-817서울특별시 중랑구 면목동 91-69 한성빌딩서울특별시 중랑구 면목로 456, 한성빌딩 5층 4호 (면목동)2155코코줌마2023-08-31 15:37:38I2022-12-09 00:02:00.0식품소분업207605.319631454476.402983<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26030600003060000-109-2023-000102023-10-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.0131-830서울특별시 중랑구 면목동 383-55 103호서울특별시 중랑구 답십리로75길 22, 103호 (면목동)2246위시아이2023-10-27 17:53:54I2022-10-30 22:09:00.0식품소분업207098.919659452263.972419<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26130600003060000-109-2023-000112023-12-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>115.71131-820서울특별시 중랑구 면목동 180-2서울특별시 중랑구 동일로 675, 302호 (면목동)2130(주)복음공조2023-12-06 10:45:52I2022-11-02 00:08:00.0식품소분업206975.9576454263.160609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26230600003060000-109-2023-000122023-12-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0131-778서울특별시 중랑구 상봉동 81-5 한일써너스빌서울특별시 중랑구 망우로 346, B109호 (상봉동, 한일써너스빌)2150울룰라2023-12-12 09:25:08I2022-11-01 23:04:00.0식품소분업207982.810825454980.023827<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26330600003060000-109-2024-000012024-02-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.9131-817서울특별시 중랑구 면목동 91-69 한성빌딩서울특별시 중랑구 면목로 456, 한성빌딩 5층 27호 (면목동)2155무지개마켓2024-02-08 11:34:49I2023-12-01 23:01:00.0식품소분업207605.319631454476.402983<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>