Overview

Dataset statistics

Number of variables44
Number of observations8478
Missing cells117706
Missing cells (%)31.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 MiB
Average record size in memory375.0 B

Variable types

Numeric12
Text7
DateTime4
Unsupported7
Categorical13
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16075/S/1/datasetView.do

Alerts

업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (77.6%)Imbalance
등급구분명 is highly imbalanced (78.4%)Imbalance
급수시설구분명 is highly imbalanced (68.3%)Imbalance
공장사무직종업원수 is highly imbalanced (58.2%)Imbalance
다중이용업소여부 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 8478 (100.0%) missing valuesMissing
폐업일자 has 2113 (24.9%) missing valuesMissing
휴업시작일자 has 8478 (100.0%) missing valuesMissing
휴업종료일자 has 8478 (100.0%) missing valuesMissing
재개업일자 has 8478 (100.0%) missing valuesMissing
전화번호 has 3293 (38.8%) missing valuesMissing
소재지면적 has 1167 (13.8%) missing valuesMissing
도로명주소 has 3268 (38.5%) missing valuesMissing
도로명우편번호 has 3322 (39.2%) missing valuesMissing
좌표정보(X) has 274 (3.2%) missing valuesMissing
좌표정보(Y) has 274 (3.2%) missing valuesMissing
남성종사자수 has 6677 (78.8%) missing valuesMissing
여성종사자수 has 6688 (78.9%) missing valuesMissing
본사종업원수 has 5319 (62.7%) missing valuesMissing
공장판매직종업원수 has 5305 (62.6%) missing valuesMissing
공장생산직종업원수 has 5308 (62.6%) missing valuesMissing
보증액 has 6481 (76.4%) missing valuesMissing
월세액 has 6483 (76.5%) missing valuesMissing
다중이용업소여부 has 1161 (13.7%) missing valuesMissing
시설총규모 has 1161 (13.7%) missing valuesMissing
전통업소지정번호 has 8478 (100.0%) missing valuesMissing
전통업소주된음식 has 8478 (100.0%) missing valuesMissing
홈페이지 has 8478 (100.0%) missing valuesMissing
본사종업원수 is highly skewed (γ1 = 30.71556396)Skewed
보증액 is highly skewed (γ1 = 27.46214985)Skewed
월세액 is highly skewed (γ1 = 21.25370512)Skewed
시설총규모 is highly skewed (γ1 = 52.11821257)Skewed
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
남성종사자수 has 1600 (18.9%) zerosZeros
여성종사자수 has 1627 (19.2%) zerosZeros
본사종업원수 has 3130 (36.9%) zerosZeros
공장판매직종업원수 has 3024 (35.7%) zerosZeros
공장생산직종업원수 has 3096 (36.5%) zerosZeros
보증액 has 1971 (23.2%) zerosZeros
월세액 has 1971 (23.2%) zerosZeros
시설총규모 has 6359 (75.0%) zerosZeros

Reproduction

Analysis started2024-04-29 18:50:52.197043
Analysis finished2024-04-29 18:50:54.194694
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3138014.9
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:50:54.286113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13060000
median3150000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)160000

Descriptive statistics

Standard deviation79463.141
Coefficient of variation (CV)0.025322742
Kurtosis-1.3927771
Mean3138014.9
Median Absolute Deviation (MAD)70000
Skewness-0.27105806
Sum2.660409 × 1010
Variance6.3143907 × 109
MonotonicityNot monotonic
2024-04-30T03:50:54.414368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3230000 1149
 
13.6%
3220000 756
 
8.9%
3050000 679
 
8.0%
3010000 658
 
7.8%
3210000 569
 
6.7%
3150000 425
 
5.0%
3240000 387
 
4.6%
3180000 337
 
4.0%
3140000 310
 
3.7%
3100000 275
 
3.2%
Other values (15) 2933
34.6%
ValueCountFrequency (%)
3000000 133
 
1.6%
3010000 658
7.8%
3020000 172
 
2.0%
3030000 214
 
2.5%
3040000 200
 
2.4%
3050000 679
8.0%
3060000 264
 
3.1%
3070000 171
 
2.0%
3080000 165
 
1.9%
3090000 252
 
3.0%
ValueCountFrequency (%)
3240000 387
 
4.6%
3230000 1149
13.6%
3220000 756
8.9%
3210000 569
6.7%
3200000 217
 
2.6%
3190000 148
 
1.7%
3180000 337
 
4.0%
3170000 217
 
2.6%
3160000 188
 
2.2%
3150000 425
 
5.0%

관리번호
Text

UNIQUE 

Distinct8478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2024-04-30T03:50:54.602277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters186516
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

Unique8478 ?
Unique (%)100.0%

Sample

1st row3210000-109-2023-00004
2nd row3240000-109-2023-00002
3rd row3080000-109-2006-00005
4th row3240000-109-2023-00003
5th row3080000-109-2023-00001
ValueCountFrequency (%)
3210000-109-2023-00004 1
 
< 0.1%
3190000-109-2005-00003 1
 
< 0.1%
3200000-109-2001-00787 1
 
< 0.1%
3200000-109-2008-00007 1
 
< 0.1%
3200000-109-2003-00014 1
 
< 0.1%
3200000-109-2001-00794 1
 
< 0.1%
3200000-109-2011-00009 1
 
< 0.1%
3200000-109-2017-00005 1
 
< 0.1%
3200000-109-2016-00005 1
 
< 0.1%
3200000-109-2016-00002 1
 
< 0.1%
Other values (8468) 8468
99.9%
2024-04-30T03:50:55.019397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86981
46.6%
- 25434
 
13.6%
1 20398
 
10.9%
2 16219
 
8.7%
3 12691
 
6.8%
9 11925
 
6.4%
5 3156
 
1.7%
4 3128
 
1.7%
6 2360
 
1.3%
8 2144
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161082
86.4%
Dash Punctuation 25434
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86981
54.0%
1 20398
 
12.7%
2 16219
 
10.1%
3 12691
 
7.9%
9 11925
 
7.4%
5 3156
 
2.0%
4 3128
 
1.9%
6 2360
 
1.5%
8 2144
 
1.3%
7 2080
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 25434
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 186516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86981
46.6%
- 25434
 
13.6%
1 20398
 
10.9%
2 16219
 
8.7%
3 12691
 
6.8%
9 11925
 
6.4%
5 3156
 
1.7%
4 3128
 
1.7%
6 2360
 
1.3%
8 2144
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86981
46.6%
- 25434
 
13.6%
1 20398
 
10.9%
2 16219
 
8.7%
3 12691
 
6.8%
9 11925
 
6.4%
5 3156
 
1.7%
4 3128
 
1.7%
6 2360
 
1.3%
8 2144
 
1.1%
Distinct4819
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
Minimum1979-04-26 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T03:50:55.136482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:50:55.263040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
3
6365 
1
2113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 6365
75.1%
1 2113
 
24.9%

Length

2024-04-30T03:50:55.383704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:50:55.463802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6365
75.1%
1 2113
 
24.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
폐업
6365 
영업/정상
2113 

Length

Max length5
Median length2
Mean length2.7476999
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6365
75.1%
영업/정상 2113
 
24.9%

Length

2024-04-30T03:50:55.564922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:50:55.653428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6365
75.1%
영업/정상 2113
 
24.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2
6365 
1
2113 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6365
75.1%
1 2113
 
24.9%

Length

2024-04-30T03:50:55.750973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:50:55.835834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6365
75.1%
1 2113
 
24.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
폐업
6365 
영업
2113 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6365
75.1%
영업 2113
 
24.9%

Length

2024-04-30T03:50:55.930360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:50:56.012422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6365
75.1%
영업 2113
 
24.9%

폐업일자
Date

MISSING 

Distinct3571
Distinct (%)56.1%
Missing2113
Missing (%)24.9%
Memory size66.4 KiB
Minimum1991-06-03 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T03:50:56.124839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:50:56.238236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

전화번호
Text

MISSING 

Distinct4698
Distinct (%)90.6%
Missing3293
Missing (%)38.8%
Memory size66.4 KiB
2024-04-30T03:50:56.537610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.305689
Min length2

Characters and Unicode

Total characters53435
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4399 ?
Unique (%)84.8%

Sample

1st row02 34451446
2nd row02 865 0695
3rd row02 448 5372
4th row02 931 6222
5th row34462494
ValueCountFrequency (%)
02 3307
34.1%
070 152
 
1.6%
031 74
 
0.8%
407 45
 
0.5%
0 18
 
0.2%
032 17
 
0.2%
404 11
 
0.1%
587 10
 
0.1%
473 10
 
0.1%
754 9
 
0.1%
Other values (5038) 6051
62.4%
2024-04-30T03:50:56.937462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9172
17.2%
2 9006
16.9%
5951
11.1%
4 4227
7.9%
3 3960
7.4%
6 3743
7.0%
7 3740
7.0%
5 3671
6.9%
1 3526
 
6.6%
8 3289
 
6.2%
Other values (2) 3150
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47482
88.9%
Space Separator 5951
 
11.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9172
19.3%
2 9006
19.0%
4 4227
8.9%
3 3960
8.3%
6 3743
7.9%
7 3740
7.9%
5 3671
7.7%
1 3526
 
7.4%
8 3289
 
6.9%
9 3148
 
6.6%
Space Separator
ValueCountFrequency (%)
5951
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53435
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9172
17.2%
2 9006
16.9%
5951
11.1%
4 4227
7.9%
3 3960
7.4%
6 3743
7.0%
7 3740
7.0%
5 3671
6.9%
1 3526
 
6.6%
8 3289
 
6.2%
Other values (2) 3150
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9172
17.2%
2 9006
16.9%
5951
11.1%
4 4227
7.9%
3 3960
7.4%
6 3743
7.0%
7 3740
7.0%
5 3671
6.9%
1 3526
 
6.6%
8 3289
 
6.2%
Other values (2) 3150
 
5.9%

소재지면적
Text

MISSING 

Distinct2404
Distinct (%)32.9%
Missing1167
Missing (%)13.8%
Memory size66.4 KiB
2024-04-30T03:50:57.261124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8022158
Min length3

Characters and Unicode

Total characters35109
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1781 ?
Unique (%)24.4%

Sample

1st row38.51
2nd row15.00
3rd row4.20
4th row18.00
5th row7.40
ValueCountFrequency (%)
10.00 285
 
3.9%
6.60 270
 
3.7%
3.30 266
 
3.6%
33.00 233
 
3.2%
9.90 151
 
2.1%
16.50 137
 
1.9%
20.00 124
 
1.7%
15.00 123
 
1.7%
6.00 121
 
1.7%
30.00 119
 
1.6%
Other values (2394) 5482
75.0%
2024-04-30T03:50:57.691143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9517
27.1%
. 7311
20.8%
1 3069
 
8.7%
3 2816
 
8.0%
2 2424
 
6.9%
6 2337
 
6.7%
5 2091
 
6.0%
9 1628
 
4.6%
4 1614
 
4.6%
8 1294
 
3.7%
Other values (2) 1008
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27789
79.2%
Other Punctuation 7320
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9517
34.2%
1 3069
 
11.0%
3 2816
 
10.1%
2 2424
 
8.7%
6 2337
 
8.4%
5 2091
 
7.5%
9 1628
 
5.9%
4 1614
 
5.8%
8 1294
 
4.7%
7 999
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 7311
99.9%
, 9
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 35109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9517
27.1%
. 7311
20.8%
1 3069
 
8.7%
3 2816
 
8.0%
2 2424
 
6.9%
6 2337
 
6.7%
5 2091
 
6.0%
9 1628
 
4.6%
4 1614
 
4.6%
8 1294
 
3.7%
Other values (2) 1008
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9517
27.1%
. 7311
20.8%
1 3069
 
8.7%
3 2816
 
8.0%
2 2424
 
6.9%
6 2337
 
6.7%
5 2091
 
6.0%
9 1628
 
4.6%
4 1614
 
4.6%
8 1294
 
3.7%
Other values (2) 1008
 
2.9%
Distinct2358
Distinct (%)27.9%
Missing33
Missing (%)0.4%
Memory size66.4 KiB
2024-04-30T03:50:57.977682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.087389
Min length6

Characters and Unicode

Total characters51408
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

Unique1058 ?
Unique (%)12.5%

Sample

1st row137-787
2nd row134-856
3rd row142-868
4th row134-870
5th row142-874
ValueCountFrequency (%)
138881 261
 
3.1%
130864 256
 
3.0%
100310 128
 
1.5%
100804 71
 
0.8%
100070 63
 
0.7%
130865 62
 
0.7%
158050 56
 
0.7%
137893 55
 
0.7%
138200 54
 
0.6%
137713 51
 
0.6%
Other values (2348) 7388
87.5%
2024-04-30T03:50:58.349775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11542
22.5%
8 8872
17.3%
3 7046
13.7%
0 6216
12.1%
5 4169
 
8.1%
2 3181
 
6.2%
4 2769
 
5.4%
7 2422
 
4.7%
9 2361
 
4.6%
6 2092
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50670
98.6%
Dash Punctuation 738
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11542
22.8%
8 8872
17.5%
3 7046
13.9%
0 6216
12.3%
5 4169
 
8.2%
2 3181
 
6.3%
4 2769
 
5.5%
7 2422
 
4.8%
9 2361
 
4.7%
6 2092
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 738
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51408
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11542
22.5%
8 8872
17.3%
3 7046
13.7%
0 6216
12.1%
5 4169
 
8.1%
2 3181
 
6.2%
4 2769
 
5.4%
7 2422
 
4.7%
9 2361
 
4.6%
6 2092
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11542
22.5%
8 8872
17.3%
3 7046
13.7%
0 6216
12.1%
5 4169
 
8.1%
2 3181
 
6.2%
4 2769
 
5.4%
7 2422
 
4.7%
9 2361
 
4.6%
6 2092
 
4.1%
Distinct7501
Distinct (%)88.8%
Missing33
Missing (%)0.4%
Memory size66.4 KiB
2024-04-30T03:50:58.642524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length50
Mean length25.354529
Min length14

Characters and Unicode

Total characters214119
Distinct characters569
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7049 ?
Unique (%)83.5%

Sample

1st row서울특별시 서초구 양재동 232 AT센터 706호
2nd row서울특별시 강동구 암사동 487-36
3rd row서울특별시 강북구 번동 463-1 (번영1길 3)
4th row서울특별시 강동구 천호동 382-12
5th row서울특별시 강북구 수유동 50-75 수유대림쇼핑아파트
ValueCountFrequency (%)
서울특별시 8443
 
20.1%
송파구 1149
 
2.7%
1층 755
 
1.8%
강남구 755
 
1.8%
지하1층 681
 
1.6%
동대문구 677
 
1.6%
중구 656
 
1.6%
서초구 569
 
1.4%
가락동 499
 
1.2%
강서구 425
 
1.0%
Other values (8719) 27401
65.2%
2024-04-30T03:50:59.064889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40494
18.9%
1 10528
 
4.9%
10316
 
4.8%
9896
 
4.6%
8908
 
4.2%
8836
 
4.1%
8495
 
4.0%
8445
 
3.9%
8445
 
3.9%
- 7023
 
3.3%
Other values (559) 92733
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121835
56.9%
Decimal Number 42588
 
19.9%
Space Separator 40494
 
18.9%
Dash Punctuation 7023
 
3.3%
Open Punctuation 685
 
0.3%
Close Punctuation 683
 
0.3%
Uppercase Letter 520
 
0.2%
Other Punctuation 223
 
0.1%
Lowercase Letter 43
 
< 0.1%
Math Symbol 19
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10316
 
8.5%
9896
 
8.1%
8908
 
7.3%
8836
 
7.3%
8495
 
7.0%
8445
 
6.9%
8445
 
6.9%
3041
 
2.5%
2127
 
1.7%
1876
 
1.5%
Other values (493) 51450
42.2%
Uppercase Letter
ValueCountFrequency (%)
B 139
26.7%
A 65
12.5%
D 45
 
8.7%
C 32
 
6.2%
S 32
 
6.2%
G 32
 
6.2%
T 26
 
5.0%
E 20
 
3.8%
L 19
 
3.7%
H 17
 
3.3%
Other values (12) 93
17.9%
Lowercase Letter
ValueCountFrequency (%)
e 9
20.9%
n 5
11.6%
b 4
9.3%
r 4
9.3%
i 3
 
7.0%
s 3
 
7.0%
u 2
 
4.7%
w 2
 
4.7%
t 2
 
4.7%
o 2
 
4.7%
Other values (6) 7
16.3%
Decimal Number
ValueCountFrequency (%)
1 10528
24.7%
2 5726
13.4%
3 4300
10.1%
0 4152
 
9.7%
4 3770
 
8.9%
6 3282
 
7.7%
5 3214
 
7.5%
7 2709
 
6.4%
9 2595
 
6.1%
8 2312
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 184
82.5%
/ 26
 
11.7%
. 9
 
4.0%
@ 3
 
1.3%
: 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 15
78.9%
> 2
 
10.5%
< 2
 
10.5%
Letter Number
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 614
89.6%
[ 71
 
10.4%
Close Punctuation
ValueCountFrequency (%)
) 612
89.6%
] 71
 
10.4%
Space Separator
ValueCountFrequency (%)
40494
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7023
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121833
56.9%
Common 91716
42.8%
Latin 568
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10316
 
8.5%
9896
 
8.1%
8908
 
7.3%
8836
 
7.3%
8495
 
7.0%
8445
 
6.9%
8445
 
6.9%
3041
 
2.5%
2127
 
1.7%
1876
 
1.5%
Other values (492) 51448
42.2%
Latin
ValueCountFrequency (%)
B 139
24.5%
A 65
11.4%
D 45
 
7.9%
C 32
 
5.6%
S 32
 
5.6%
G 32
 
5.6%
T 26
 
4.6%
E 20
 
3.5%
L 19
 
3.3%
H 17
 
3.0%
Other values (31) 141
24.8%
Common
ValueCountFrequency (%)
40494
44.2%
1 10528
 
11.5%
- 7023
 
7.7%
2 5726
 
6.2%
3 4300
 
4.7%
0 4152
 
4.5%
4 3770
 
4.1%
6 3282
 
3.6%
5 3214
 
3.5%
7 2709
 
3.0%
Other values (15) 6518
 
7.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121832
56.9%
ASCII 92278
43.1%
Number Forms 5
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40494
43.9%
1 10528
 
11.4%
- 7023
 
7.6%
2 5726
 
6.2%
3 4300
 
4.7%
0 4152
 
4.5%
4 3770
 
4.1%
6 3282
 
3.6%
5 3214
 
3.5%
7 2709
 
2.9%
Other values (52) 7080
 
7.7%
Hangul
ValueCountFrequency (%)
10316
 
8.5%
9896
 
8.1%
8908
 
7.3%
8836
 
7.3%
8495
 
7.0%
8445
 
6.9%
8445
 
6.9%
3041
 
2.5%
2127
 
1.7%
1876
 
1.5%
Other values (491) 51447
42.2%
Number Forms
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
2
100.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct5079
Distinct (%)97.5%
Missing3268
Missing (%)38.5%
Memory size66.4 KiB
2024-04-30T03:50:59.354435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length59.5
Mean length34.31094
Min length20

Characters and Unicode

Total characters178760
Distinct characters577
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4979 ?
Unique (%)95.6%

Sample

1st row서울특별시 서초구 강남대로 27, AT센터 706호 (양재동)
2nd row서울특별시 강동구 구천면로 333, 1층 (암사동)
3rd row서울특별시 강북구 도봉로96길 12 (번동,(번영1길 3))
4th row서울특별시 강동구 구천면로33길 44, 1층 (천호동)
5th row서울특별시 강북구 도봉로71가길 11, 수유대림쇼핑아파트 323호 (수유동)
ValueCountFrequency (%)
서울특별시 5208
 
15.3%
1층 1214
 
3.6%
송파구 840
 
2.5%
지하1층 571
 
1.7%
동대문구 518
 
1.5%
2층 426
 
1.2%
강남구 421
 
1.2%
중구 387
 
1.1%
가락동 344
 
1.0%
제기동 318
 
0.9%
Other values (6721) 23847
69.9%
2024-04-30T03:50:59.804506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28917
 
16.2%
1 7876
 
4.4%
7338
 
4.1%
6251
 
3.5%
5724
 
3.2%
, 5643
 
3.2%
5575
 
3.1%
5432
 
3.0%
( 5395
 
3.0%
) 5393
 
3.0%
Other values (567) 95216
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103279
57.8%
Space Separator 28917
 
16.2%
Decimal Number 28419
 
15.9%
Other Punctuation 5661
 
3.2%
Open Punctuation 5426
 
3.0%
Close Punctuation 5424
 
3.0%
Dash Punctuation 1044
 
0.6%
Uppercase Letter 512
 
0.3%
Lowercase Letter 47
 
< 0.1%
Math Symbol 25
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7338
 
7.1%
6251
 
6.1%
5724
 
5.5%
5575
 
5.4%
5432
 
5.3%
5263
 
5.1%
5210
 
5.0%
5209
 
5.0%
3733
 
3.6%
2986
 
2.9%
Other values (501) 50558
49.0%
Uppercase Letter
ValueCountFrequency (%)
B 166
32.4%
A 68
13.3%
D 42
 
8.2%
C 36
 
7.0%
T 27
 
5.3%
S 20
 
3.9%
E 19
 
3.7%
L 17
 
3.3%
G 16
 
3.1%
H 14
 
2.7%
Other values (12) 87
17.0%
Lowercase Letter
ValueCountFrequency (%)
e 9
19.1%
b 7
14.9%
n 5
10.6%
c 5
10.6%
r 4
8.5%
t 2
 
4.3%
a 2
 
4.3%
i 2
 
4.3%
w 2
 
4.3%
o 2
 
4.3%
Other values (6) 7
14.9%
Decimal Number
ValueCountFrequency (%)
1 7876
27.7%
2 4581
16.1%
3 3354
11.8%
0 2524
 
8.9%
4 2331
 
8.2%
5 1938
 
6.8%
6 1725
 
6.1%
9 1403
 
4.9%
7 1390
 
4.9%
8 1297
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 5643
99.7%
/ 11
 
0.2%
. 6
 
0.1%
@ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 23
92.0%
> 1
 
4.0%
< 1
 
4.0%
Letter Number
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 5395
99.4%
[ 31
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 5393
99.4%
] 31
 
0.6%
Space Separator
ValueCountFrequency (%)
28917
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1044
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 103276
57.8%
Common 74918
41.9%
Latin 563
 
0.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7338
 
7.1%
6251
 
6.1%
5724
 
5.5%
5575
 
5.4%
5432
 
5.3%
5263
 
5.1%
5210
 
5.0%
5209
 
5.0%
3733
 
3.6%
2986
 
2.9%
Other values (500) 50555
49.0%
Latin
ValueCountFrequency (%)
B 166
29.5%
A 68
12.1%
D 42
 
7.5%
C 36
 
6.4%
T 27
 
4.8%
S 20
 
3.6%
E 19
 
3.4%
L 17
 
3.0%
G 16
 
2.8%
H 14
 
2.5%
Other values (31) 138
24.5%
Common
ValueCountFrequency (%)
28917
38.6%
1 7876
 
10.5%
, 5643
 
7.5%
( 5395
 
7.2%
) 5393
 
7.2%
2 4581
 
6.1%
3 3354
 
4.5%
0 2524
 
3.4%
4 2331
 
3.1%
5 1938
 
2.6%
Other values (15) 6966
 
9.3%
Han
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 103276
57.8%
ASCII 75477
42.2%
Number Forms 4
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28917
38.3%
1 7876
 
10.4%
, 5643
 
7.5%
( 5395
 
7.1%
) 5393
 
7.1%
2 4581
 
6.1%
3 3354
 
4.4%
0 2524
 
3.3%
4 2331
 
3.1%
5 1938
 
2.6%
Other values (53) 7525
 
10.0%
Hangul
ValueCountFrequency (%)
7338
 
7.1%
6251
 
6.1%
5724
 
5.5%
5575
 
5.4%
5432
 
5.3%
5263
 
5.1%
5210
 
5.0%
5209
 
5.0%
3733
 
3.6%
2986
 
2.9%
Other values (500) 50555
49.0%
CJK
ValueCountFrequency (%)
3
100.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct2280
Distinct (%)44.2%
Missing3322
Missing (%)39.2%
Infinite0
Infinite (%)0.0%
Mean5133.4986
Minimum1006
Maximum11159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:50:59.931157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1662.75
Q13496.5
median5537
Q36576
95-th percentile8504
Maximum11159
Range10153
Interquartile range (IQR)3079.5

Descriptive statistics

Standard deviation2040.5837
Coefficient of variation (CV)0.3975035
Kurtosis-0.83115332
Mean5133.4986
Median Absolute Deviation (MAD)1362.5
Skewness-0.16342998
Sum26468319
Variance4163981.7
MonotonicityNot monotonic
2024-04-30T03:51:00.051311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5699 269
 
3.2%
4547 129
 
1.5%
2570 107
 
1.3%
2478 80
 
0.9%
2571 60
 
0.7%
4529 55
 
0.6%
2569 54
 
0.6%
7644 43
 
0.5%
4546 32
 
0.4%
5838 25
 
0.3%
Other values (2270) 4302
50.7%
(Missing) 3322
39.2%
ValueCountFrequency (%)
1006 3
< 0.1%
1014 2
< 0.1%
1021 1
 
< 0.1%
1027 1
 
< 0.1%
1030 2
< 0.1%
1035 1
 
< 0.1%
1037 1
 
< 0.1%
1039 2
< 0.1%
1041 3
< 0.1%
1043 1
 
< 0.1%
ValueCountFrequency (%)
11159 1
 
< 0.1%
10252 1
 
< 0.1%
8863 2
 
< 0.1%
8861 1
 
< 0.1%
8860 2
 
< 0.1%
8857 2
 
< 0.1%
8856 2
 
< 0.1%
8854 1
 
< 0.1%
8849 5
0.1%
8848 2
 
< 0.1%
Distinct7154
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2024-04-30T03:51:00.235245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length6.4808917
Min length1

Characters and Unicode

Total characters54945
Distinct characters940
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6351 ?
Unique (%)74.9%

Sample

1st row(주)가파
2nd row농업법인(주)자연촌
3rd rowS-마트 번동점
4th row샬롬
5th row주식회사 이너스케어
ValueCountFrequency (%)
주식회사 288
 
2.9%
24
 
0.2%
유한회사 23
 
0.2%
위니비니 22
 
0.2%
주)지에스리테일 17
 
0.2%
주)교동씨엠 17
 
0.2%
영우유통 16
 
0.2%
주)제이에프앤비 15
 
0.2%
미래식품 15
 
0.2%
농업회사법인 14
 
0.1%
Other values (7589) 9328
95.4%
2024-04-30T03:51:00.555799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2653
 
4.8%
) 2517
 
4.6%
( 2494
 
4.5%
1303
 
2.4%
1242
 
2.3%
1213
 
2.2%
973
 
1.8%
936
 
1.7%
930
 
1.7%
865
 
1.6%
Other values (930) 39819
72.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46845
85.3%
Close Punctuation 2518
 
4.6%
Open Punctuation 2495
 
4.5%
Space Separator 1303
 
2.4%
Uppercase Letter 797
 
1.5%
Lowercase Letter 659
 
1.2%
Decimal Number 211
 
0.4%
Other Punctuation 84
 
0.2%
Dash Punctuation 29
 
0.1%
Math Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2653
 
5.7%
1242
 
2.7%
1213
 
2.6%
973
 
2.1%
936
 
2.0%
930
 
2.0%
865
 
1.8%
851
 
1.8%
822
 
1.8%
751
 
1.6%
Other values (852) 35609
76.0%
Uppercase Letter
ValueCountFrequency (%)
S 82
 
10.3%
A 57
 
7.2%
T 53
 
6.6%
E 53
 
6.6%
O 46
 
5.8%
C 45
 
5.6%
G 44
 
5.5%
F 41
 
5.1%
N 41
 
5.1%
B 40
 
5.0%
Other values (16) 295
37.0%
Lowercase Letter
ValueCountFrequency (%)
e 93
14.1%
o 74
11.2%
a 69
10.5%
t 49
 
7.4%
r 43
 
6.5%
l 43
 
6.5%
n 39
 
5.9%
i 36
 
5.5%
s 34
 
5.2%
p 22
 
3.3%
Other values (14) 157
23.8%
Decimal Number
ValueCountFrequency (%)
1 50
23.7%
2 28
13.3%
0 28
13.3%
3 27
12.8%
5 22
10.4%
4 15
 
7.1%
9 13
 
6.2%
6 12
 
5.7%
7 10
 
4.7%
8 6
 
2.8%
Other Punctuation
ValueCountFrequency (%)
& 37
44.0%
. 24
28.6%
? 9
 
10.7%
' 7
 
8.3%
, 3
 
3.6%
% 2
 
2.4%
: 1
 
1.2%
/ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 2517
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2494
> 99.9%
[ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
1303
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46833
85.2%
Common 6644
 
12.1%
Latin 1456
 
2.6%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2653
 
5.7%
1242
 
2.7%
1213
 
2.6%
973
 
2.1%
936
 
2.0%
930
 
2.0%
865
 
1.8%
851
 
1.8%
822
 
1.8%
751
 
1.6%
Other values (840) 35597
76.0%
Latin
ValueCountFrequency (%)
e 93
 
6.4%
S 82
 
5.6%
o 74
 
5.1%
a 69
 
4.7%
A 57
 
3.9%
T 53
 
3.6%
E 53
 
3.6%
t 49
 
3.4%
O 46
 
3.2%
C 45
 
3.1%
Other values (40) 835
57.3%
Common
ValueCountFrequency (%)
) 2517
37.9%
( 2494
37.5%
1303
19.6%
1 50
 
0.8%
& 37
 
0.6%
- 29
 
0.4%
2 28
 
0.4%
0 28
 
0.4%
3 27
 
0.4%
. 24
 
0.4%
Other values (18) 107
 
1.6%
Han
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46833
85.2%
ASCII 8100
 
14.7%
CJK 12
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2653
 
5.7%
1242
 
2.7%
1213
 
2.6%
973
 
2.1%
936
 
2.0%
930
 
2.0%
865
 
1.8%
851
 
1.8%
822
 
1.8%
751
 
1.6%
Other values (840) 35597
76.0%
ASCII
ValueCountFrequency (%)
) 2517
31.1%
( 2494
30.8%
1303
16.1%
e 93
 
1.1%
S 82
 
1.0%
o 74
 
0.9%
a 69
 
0.9%
A 57
 
0.7%
T 53
 
0.7%
E 53
 
0.7%
Other values (68) 1305
16.1%
CJK
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2) 2
16.7%
Distinct7118
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
Minimum1998-12-23 00:00:00
Maximum2024-04-25 17:26:18
2024-04-30T03:51:00.675465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:00.811838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
I
6457 
U
2020 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 6457
76.2%
U 2020
 
23.8%
D 1
 
< 0.1%

Length

2024-04-30T03:51:00.936761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:01.036994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6457
76.2%
u 2020
 
23.8%
d 1
 
< 0.1%
Distinct1393
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-30T03:51:01.353832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:51:01.473386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
식품소분업
8478 

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 8478
100.0%

Length

2024-04-30T03:51:01.590550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:01.665453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 8478
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct5564
Distinct (%)67.8%
Missing274
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean200802.56
Minimum182141.21
Maximum215984.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:01.751329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile186559.58
Q1194498.25
median202789.37
Q3206309.49
95-th percentile211627.84
Maximum215984.38
Range33843.17
Interquartile range (IQR)11811.239

Descriptive statistics

Standard deviation7712.7472
Coefficient of variation (CV)0.038409606
Kurtosis-0.70095947
Mean200802.56
Median Absolute Deviation (MAD)4984.8852
Skewness-0.46395636
Sum1.6473842 × 109
Variance59486469
MonotonicityNot monotonic
2024-04-30T03:51:01.872924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209790.959909032 280
 
3.3%
198259.65357739 64
 
0.8%
204413.616574592 57
 
0.7%
200250.447804795 52
 
0.6%
183914.938310002 48
 
0.6%
208589.363343145 47
 
0.6%
203811.366422118 41
 
0.5%
197936.261142268 41
 
0.5%
200015.499568016 38
 
0.4%
202358.505687227 34
 
0.4%
Other values (5554) 7502
88.5%
(Missing) 274
 
3.2%
ValueCountFrequency (%)
182141.205465089 2
 
< 0.1%
182293.357671337 1
 
< 0.1%
182438.570400174 1
 
< 0.1%
182524.823835629 6
0.1%
182846.406822134 1
 
< 0.1%
182876.367858149 1
 
< 0.1%
182895.668483962 1
 
< 0.1%
182912.435007001 2
 
< 0.1%
182933.115073744 1
 
< 0.1%
182944.731406147 1
 
< 0.1%
ValueCountFrequency (%)
215984.375136997 1
 
< 0.1%
215661.222623 1
 
< 0.1%
215254.0 1
 
< 0.1%
215206.101435737 1
 
< 0.1%
215203.799066155 1
 
< 0.1%
215195.884311721 2
< 0.1%
215178.170771585 1
 
< 0.1%
215177.804033096 3
< 0.1%
215172.159803867 1
 
< 0.1%
215167.502111577 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct5564
Distinct (%)67.8%
Missing274
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean448899.95
Minimum436961.57
Maximum485365.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:02.000953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436961.57
5-th percentile441618.52
Q1444265.94
median448311.69
Q3452322.47
95-th percentile460068.69
Maximum485365.54
Range48403.966
Interquartile range (IQR)8056.5266

Descriptive statistics

Standard deviation5504.519
Coefficient of variation (CV)0.01226224
Kurtosis-0.00086484296
Mean448899.95
Median Absolute Deviation (MAD)4030.2966
Skewness0.61484621
Sum3.6827752 × 109
Variance30299730
MonotonicityNot monotonic
2024-04-30T03:51:02.135124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443481.212174317 280
 
3.3%
451392.198218657 64
 
0.8%
461378.588676784 57
 
0.7%
444683.220506107 52
 
0.6%
450085.01457343 48
 
0.6%
445455.90405262 47
 
0.6%
440070.727589935 41
 
0.5%
450837.498547725 41
 
0.5%
451485.349952584 38
 
0.4%
447232.955697694 34
 
0.4%
Other values (5554) 7502
88.5%
(Missing) 274
 
3.2%
ValueCountFrequency (%)
436961.570793747 1
 
< 0.1%
437601.753603288 1
 
< 0.1%
437607.039565128 2
< 0.1%
437720.092885096 1
 
< 0.1%
437861.221701954 1
 
< 0.1%
437864.710924867 1
 
< 0.1%
437890.507732031 1
 
< 0.1%
437914.06299827 4
< 0.1%
437959.961132488 1
 
< 0.1%
438266.70898504 1
 
< 0.1%
ValueCountFrequency (%)
485365.536453517 1
< 0.1%
469091.224213731 1
< 0.1%
464907.896951126 1
< 0.1%
464849.968985063 1
< 0.1%
464814.717432497 1
< 0.1%
464788.847055332 2
< 0.1%
464664.845668554 1
< 0.1%
464633.761055876 1
< 0.1%
464552.486156478 2
< 0.1%
464215.186872943 1
< 0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
식품소분업
7317 
<NA>
1161 

Length

Max length5
Median length5
Mean length4.8630573
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 (%)
식품소분업 7317
86.3%
<NA> 1161
 
13.7%

Length

2024-04-30T03:51:02.272671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:02.377994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 7317
86.3%
na 1161
 
13.7%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.4%
Missing6677
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean0.17434758
Minimum0
Maximum7
Zeros1600
Zeros (%)18.9%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:02.462310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5779537
Coefficient of variation (CV)3.314951
Kurtosis27.165424
Mean0.17434758
Median Absolute Deviation (MAD)0
Skewness4.5172026
Sum314
Variance0.33403048
MonotonicityNot monotonic
2024-04-30T03:51:02.566207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1600
 
18.9%
1 124
 
1.5%
2 55
 
0.6%
3 13
 
0.2%
4 6
 
0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 6677
78.8%
ValueCountFrequency (%)
0 1600
18.9%
1 124
 
1.5%
2 55
 
0.6%
3 13
 
0.2%
4 6
 
0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
5 2
 
< 0.1%
4 6
 
0.1%
3 13
 
0.2%
2 55
 
0.6%
1 124
 
1.5%
0 1600
18.9%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.6%
Missing6688
Missing (%)78.9%
Infinite0
Infinite (%)0.0%
Mean0.16648045
Minimum0
Maximum12
Zeros1627
Zeros (%)19.2%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:02.657126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7462928
Coefficient of variation (CV)4.4827655
Kurtosis97.663678
Mean0.16648045
Median Absolute Deviation (MAD)0
Skewness8.4765521
Sum298
Variance0.55695295
MonotonicityNot monotonic
2024-04-30T03:51:02.759364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1627
 
19.2%
1 104
 
1.2%
2 33
 
0.4%
3 11
 
0.1%
4 6
 
0.1%
10 3
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
12 1
 
< 0.1%
(Missing) 6688
78.9%
ValueCountFrequency (%)
0 1627
19.2%
1 104
 
1.2%
2 33
 
0.4%
3 11
 
0.1%
4 6
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
10 3
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
10 3
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 6
 
0.1%
3 11
 
0.1%
2 33
 
0.4%
1 104
 
1.2%
0 1627
19.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7567 
기타
 
526
주택가주변
 
336
아파트지역
 
37
유흥업소밀집지역
 
8
Other values (2)
 
4

Length

Max length8
Median length4
Mean length3.9255721
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7567
89.3%
기타 526
 
6.2%
주택가주변 336
 
4.0%
아파트지역 37
 
0.4%
유흥업소밀집지역 8
 
0.1%
학교정화(상대) 3
 
< 0.1%
학교정화(절대) 1
 
< 0.1%

Length

2024-04-30T03:51:02.880548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:02.996982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7567
89.3%
기타 526
 
6.2%
주택가주변 336
 
4.0%
아파트지역 37
 
0.4%
유흥업소밀집지역 8
 
0.1%
학교정화(상대 3
 
< 0.1%
학교정화(절대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7567 
기타
 
581
자율
 
224
우수
 
61
 
26
Other values (3)
 
19

Length

Max length4
Median length4
Mean length3.7811984
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> 7567
89.3%
기타 581
 
6.9%
자율 224
 
2.6%
우수 61
 
0.7%
26
 
0.3%
관리 10
 
0.1%
7
 
0.1%
지도 2
 
< 0.1%

Length

2024-04-30T03:51:03.124506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:03.240526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7567
89.3%
기타 581
 
6.9%
자율 224
 
2.6%
우수 61
 
0.7%
26
 
0.3%
관리 10
 
0.1%
7
 
0.1%
지도 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7138 
상수도전용
1336 
지하수전용
 
2
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.160887
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> 7138
84.2%
상수도전용 1336
 
15.8%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

Length

2024-04-30T03:51:03.348381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:03.453107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7138
84.2%
상수도전용 1336
 
15.8%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%

총인원
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
7280 
0
1198 

Length

Max length4
Median length4
Mean length3.5760793
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> 7280
85.9%
0 1198
 
14.1%

Length

2024-04-30T03:51:03.553243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:03.657569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7280
85.9%
0 1198
 
14.1%

본사종업원수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct7
Distinct (%)0.2%
Missing5319
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean0.021525799
Minimum0
Maximum15
Zeros3130
Zeros (%)36.9%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:03.738617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.34253842
Coefficient of variation (CV)15.912924
Kurtosis1210.1644
Mean0.021525799
Median Absolute Deviation (MAD)0
Skewness30.715564
Sum68
Variance0.11733257
MonotonicityNot monotonic
2024-04-30T03:51:03.842723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3130
36.9%
1 15
 
0.2%
2 8
 
0.1%
5 3
 
< 0.1%
3 1
 
< 0.1%
15 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 5319
62.7%
ValueCountFrequency (%)
0 3130
36.9%
1 15
 
0.2%
2 8
 
0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 3
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
5 3
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 8
 
0.1%
1 15
 
0.2%
0 3130
36.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
5320 
0
3144 
1
 
11
2
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.8825195
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5320
62.8%
0 3144
37.1%
1 11
 
0.1%
2 2
 
< 0.1%
4 1
 
< 0.1%

Length

2024-04-30T03:51:03.953907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:04.053088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5320
62.8%
0 3144
37.1%
1 11
 
0.1%
2 2
 
< 0.1%
4 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.3%
Missing5305
Missing (%)62.6%
Infinite0
Infinite (%)0.0%
Mean0.083517176
Minimum0
Maximum10
Zeros3024
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:04.139214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.46466165
Coefficient of variation (CV)5.5636657
Kurtosis111.14809
Mean0.083517176
Median Absolute Deviation (MAD)0
Skewness8.7587512
Sum265
Variance0.21591045
MonotonicityNot monotonic
2024-04-30T03:51:04.241540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 3024
35.7%
1 81
 
1.0%
2 47
 
0.6%
3 8
 
0.1%
5 6
 
0.1%
4 5
 
0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
(Missing) 5305
62.6%
ValueCountFrequency (%)
0 3024
35.7%
1 81
 
1.0%
2 47
 
0.6%
3 8
 
0.1%
4 5
 
0.1%
5 6
 
0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
6 1
 
< 0.1%
5 6
 
0.1%
4 5
 
0.1%
3 8
 
0.1%
2 47
 
0.6%
1 81
 
1.0%
0 3024
35.7%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.3%
Missing5308
Missing (%)62.6%
Infinite0
Infinite (%)0.0%
Mean0.044479495
Minimum0
Maximum11
Zeros3096
Zeros (%)36.5%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:04.336251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.38867219
Coefficient of variation (CV)8.738233
Kurtosis332.97605
Mean0.044479495
Median Absolute Deviation (MAD)0
Skewness15.578512
Sum141
Variance0.15106607
MonotonicityNot monotonic
2024-04-30T03:51:04.438863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 3096
36.5%
1 43
 
0.5%
2 17
 
0.2%
3 7
 
0.1%
4 3
 
< 0.1%
11 1
 
< 0.1%
9 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 5308
62.6%
ValueCountFrequency (%)
0 3096
36.5%
1 43
 
0.5%
2 17
 
0.2%
3 7
 
0.1%
4 3
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
9 1
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
9 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
< 0.1%
3 7
 
0.1%
2 17
 
0.2%
1 43
 
0.5%
0 3096
36.5%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
<NA>
3692 
자가
2509 
임대
2277 

Length

Max length4
Median length2
Mean length2.8709601
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> 3692
43.5%
자가 2509
29.6%
임대 2277
26.9%

Length

2024-04-30T03:51:04.571463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:51:04.688476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3692
43.5%
자가 2509
29.6%
임대 2277
26.9%

보증액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct14
Distinct (%)0.7%
Missing6481
Missing (%)76.4%
Infinite0
Infinite (%)0.0%
Mean351286.93
Minimum0
Maximum2 × 108
Zeros1971
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:04.770462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2 × 108
Range2 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5480372.9
Coefficient of variation (CV)15.600845
Kurtosis918.02581
Mean351286.93
Median Absolute Deviation (MAD)0
Skewness27.46215
Sum7.0152 × 108
Variance3.0034487 × 1013
MonotonicityNot monotonic
2024-04-30T03:51:04.884262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 1971
 
23.2%
5000000 7
 
0.1%
10000000 4
 
< 0.1%
50000000 3
 
< 0.1%
20000000 2
 
< 0.1%
35000000 2
 
< 0.1%
520000 1
 
< 0.1%
15000000 1
 
< 0.1%
80000000 1
 
< 0.1%
2000000 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 6481
76.4%
ValueCountFrequency (%)
0 1971
23.2%
520000 1
 
< 0.1%
2000000 1
 
< 0.1%
4000000 1
 
< 0.1%
5000000 7
 
0.1%
10000000 4
 
< 0.1%
15000000 1
 
< 0.1%
20000000 2
 
< 0.1%
25000000 1
 
< 0.1%
35000000 2
 
< 0.1%
ValueCountFrequency (%)
200000000 1
 
< 0.1%
80000000 1
 
< 0.1%
50000000 3
< 0.1%
40000000 1
 
< 0.1%
35000000 2
 
< 0.1%
25000000 1
 
< 0.1%
20000000 2
 
< 0.1%
15000000 1
 
< 0.1%
10000000 4
< 0.1%
5000000 7
0.1%

월세액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)1.0%
Missing6483
Missing (%)76.5%
Infinite0
Infinite (%)0.0%
Mean19804.11
Minimum0
Maximum8000000
Zeros1971
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:04.990377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8000000
Range8000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation299515.2
Coefficient of variation (CV)15.12389
Kurtosis500.53391
Mean19804.11
Median Absolute Deviation (MAD)0
Skewness21.253705
Sum39509200
Variance8.9709352 × 1010
MonotonicityNot monotonic
2024-04-30T03:51:05.100016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 1971
 
23.2%
300000 3
 
< 0.1%
400000 3
 
< 0.1%
600000 2
 
< 0.1%
3200000 2
 
< 0.1%
450000 1
 
< 0.1%
1100000 1
 
< 0.1%
629200 1
 
< 0.1%
7500000 1
 
< 0.1%
500000 1
 
< 0.1%
Other values (9) 9
 
0.1%
(Missing) 6483
76.5%
ValueCountFrequency (%)
0 1971
23.2%
120000 1
 
< 0.1%
260000 1
 
< 0.1%
300000 3
 
< 0.1%
400000 3
 
< 0.1%
450000 1
 
< 0.1%
500000 1
 
< 0.1%
600000 2
 
< 0.1%
629200 1
 
< 0.1%
650000 1
 
< 0.1%
ValueCountFrequency (%)
8000000 1
< 0.1%
7500000 1
< 0.1%
5000000 1
< 0.1%
3200000 2
< 0.1%
2600000 1
< 0.1%
1300000 1
< 0.1%
1100000 1
< 0.1%
900000 1
< 0.1%
800000 1
< 0.1%
650000 1
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1161
Missing (%)13.7%
Memory size16.7 KiB
False
7314 
True
 
3
(Missing)
1161 
ValueCountFrequency (%)
False 7314
86.3%
True 3
 
< 0.1%
(Missing) 1161
 
13.7%
2024-04-30T03:51:05.200357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct460
Distinct (%)6.3%
Missing1161
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean5.587447
Minimum0
Maximum3372.7
Zeros6359
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size74.6 KiB
2024-04-30T03:51:05.305411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile30
Maximum3372.7
Range3372.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47.516231
Coefficient of variation (CV)8.5041041
Kurtosis3524.2027
Mean5.587447
Median Absolute Deviation (MAD)0
Skewness52.118213
Sum40883.35
Variance2257.7922
MonotonicityNot monotonic
2024-04-30T03:51:05.427442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6359
75.0%
10.0 50
 
0.6%
6.6 42
 
0.5%
33.0 41
 
0.5%
3.3 40
 
0.5%
9.9 30
 
0.4%
16.5 23
 
0.3%
30.0 19
 
0.2%
15.0 18
 
0.2%
20.0 16
 
0.2%
Other values (450) 679
 
8.0%
(Missing) 1161
 
13.7%
ValueCountFrequency (%)
0.0 6359
75.0%
0.3 1
 
< 0.1%
0.75 1
 
< 0.1%
0.87 1
 
< 0.1%
0.9 1
 
< 0.1%
1.0 2
 
< 0.1%
1.3 1
 
< 0.1%
1.39 1
 
< 0.1%
1.5 1
 
< 0.1%
1.65 1
 
< 0.1%
ValueCountFrequency (%)
3372.7 1
< 0.1%
1296.2 1
< 0.1%
330.0 1
< 0.1%
322.71 1
< 0.1%
311.17 1
< 0.1%
310.69 1
< 0.1%
295.28 1
< 0.1%
292.68 1
< 0.1%
286.94 1
< 0.1%
282.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8478
Missing (%)100.0%
Memory size74.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-109-2023-000042023-02-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 3445144638.51137-787서울특별시 서초구 양재동 232 AT센터 706호서울특별시 서초구 강남대로 27, AT센터 706호 (양재동)6774(주)가파2023-02-28 14:36:07I2022-12-03 00:03:00.0식품소분업203392.793461440676.37992<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
132400003240000-109-2023-000022023-02-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.00134-856서울특별시 강동구 암사동 487-36서울특별시 강동구 구천면로 333, 1층 (암사동)5259농업법인(주)자연촌2023-02-28 16:08:48I2022-12-03 00:03:00.0식품소분업211974.529997449663.797812<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230800003080000-109-2006-000052006-05-15<NA>3폐업2폐업2023-02-28<NA><NA><NA><NA>4.20142-868서울특별시 강북구 번동 463-1 (번영1길 3)서울특별시 강북구 도봉로96길 12 (번동,(번영1길 3))1056S-마트 번동점2023-02-28 11:25:56U2022-12-03 00:03:00.0식품소분업202520.512673459784.511653<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
332400003240000-109-2023-000032023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.00134-870서울특별시 강동구 천호동 382-12서울특별시 강동구 구천면로33길 44, 1층 (천호동)5325샬롬2023-03-08 13:57:00I2022-12-02 23:00:00.0식품소분업211301.209267448933.687561<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430800003080000-109-2023-000012023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 865 06957.40142-874서울특별시 강북구 수유동 50-75 수유대림쇼핑아파트서울특별시 강북구 도봉로71가길 11, 수유대림쇼핑아파트 323호 (수유동)1114주식회사 이너스케어2023-03-08 10:12:41I2022-12-02 23:00:00.0식품소분업201892.114537458840.846635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531400003140000-109-2023-000022023-03-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.52158-807서울특별시 양천구 목동 497-4 대명이튼캐슬 A동 103호서울특별시 양천구 목동중앙본로 107, 대명이튼캐슬 A동 103호 (목동, 대명이튼캐슬)7948뻥튀기하우스2023-03-10 14:46:17I2022-12-02 23:02:00.0식품소분업188509.227318449220.428989<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
631700003170000-109-2023-000032023-03-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00153-803서울특별시 금천구 가산동 481-10 벽산/경인디지털밸리2 112-2호서울특별시 금천구 가산디지털2로 184, 벽산/경인디지털밸리2 1층 112호 (가산동)8501시온하이텍2023-03-10 13:57:16I2022-12-02 23:02:00.0식품소분업189127.981105442460.505542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730300003030000-109-2023-000052023-03-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.26133-835서울특별시 성동구 성수동2가 302-8 블루스톤타워서울특별시 성동구 연무장5길 9-16, 블루스톤타워 1층 106,107호 (성수동2가)4782비엔에이치알커피2023-03-10 12:43:45I2022-12-02 23:02:00.0식품소분업204585.311977449123.994692<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830100003010000-109-2022-000052022-04-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.00100-866서울특별시 중구 필동1가 23-13서울특별시 중구 퇴계로30길 10, 201호 (필동1가)4627가까운빵2023-03-10 13:36:29U2022-12-02 23:02:00.0식품소분업199224.128503450933.385655<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
932300003230000-109-2008-000352008-11-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 448 537254.75138-801서울특별시 송파구 가락동 38-9서울특별시 송파구 양재대로64길 38 (가락동)5715(주)청해창2023-03-10 10:12:01U2022-12-02 23:02:00.0식품소분업210897.222377444124.519209<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
846831000003100000-109-2019-0000120190102<NA>3폐업2폐업20220512<NA><NA><NA>02 930440216.00139860서울특별시 노원구 중계동 360-15 건영아파트 상가동 지하1층 1호서울특별시 노원구 노원로22길 77, 건영아파트 상가동 지하1층 1호 (중계동)1744이온마트2022-05-12 13:28:38U2021-12-04 23:04:00.0식품소분업206487.136124460693.059405<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
846932200003220000-109-2005-0000220050117<NA>3폐업2폐업20220512<NA><NA><NA>574430766.11135240서울특별시 강남구 개포동 141-0 지상1층서울특별시 강남구 선릉로 7 (개포동,지상1층)<NA>한아름공판장2022-05-12 11:54:28U2021-12-04 23:04:00.0식품소분업205373.37109441814.602871<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847031900003190000-109-2018-0000120181106<NA>1영업/정상1영업<NA><NA><NA><NA><NA>100.00156060서울특별시 동작구 본동 485 경동윈츠리버아파트서울특별시 동작구 노량진로26길 62, 경동윈츠리버아파트 201호 (본동)6907디저트월드2023-01-05 09:33:22U2022-12-01 00:07:00.0식품소분업195975.975679445303.904437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847132200003220000-109-2021-0001620210331<NA>3폐업2폐업20220513<NA><NA><NA>02 1599599233.00135829서울특별시 강남구 논현동 216-2서울특별시 강남구 학동로30길 34, 4층 (논현동)6106주식회사 더그라운드컴퍼니2022-05-13 16:17:44U2021-12-04 23:05:00.0식품소분업202804.912119445524.907263<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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847331300003130000-109-2023-0000120230109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30121894서울특별시 마포구 서교동 375-1 코너호서울특별시 마포구 동교로22길 19, 1층 코너호 (서교동)4031누하우스2023-01-09 13:31:50I2022-11-30 23:01:00.0식품소분업192759.832764450268.93774<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847432300003230000-109-2023-0000120230106<NA>1영업/정상1영업<NA><NA><NA><NA><NA>160.00138846서울특별시 송파구 석촌동 256-3서울특별시 송파구 가락로 77, 1층 (석촌동)5690행복마트2023-01-06 16:12:47I2022-12-01 00:08:00.0식품소분업209195.817991444253.649435<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847530900003090000-109-2023-0000120230109<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.21132920서울특별시 도봉구 창동 621-52 1층서울특별시 도봉구 도봉로110라길 5, 1층 (창동)1458휴인(HUIN)2023-01-09 10:55:26I2022-11-30 23:01:00.0식품소분업203094.747268460389.538702<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847630700003070000-109-2023-000012023-01-06<NA>3폐업2폐업2023-09-07<NA><NA><NA><NA>7.00136-074서울특별시 성북구 안암동4가 14서울특별시 성북구 보문로14길 25, 1층 (안암동4가)2858데클렌2023-09-07 12:05:12U2022-12-09 00:09:00.0식품소분업202015.213035453158.830132<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
847731900003190000-109-2019-000012019-04-02<NA>3폐업2폐업2023-06-02<NA><NA><NA><NA>60.00156-060서울특별시 동작구 본동 485 경동윈츠리버아파트서울특별시 동작구 노량진로26길 62, 경동윈츠리버아파트 201-1,2호 (본동)6907디저트월드(주)2023-06-02 10:19:20U2022-12-06 00:04:00.0식품소분업195975.975679445303.904437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>