Overview

Dataset statistics

Number of variables44
Number of observations171
Missing cells1517
Missing cells (%)20.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.9 KiB
Average record size in memory376.8 B

Variable types

Categorical22
Text6
DateTime4
Unsupported7
Numeric4
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18184/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (71.0%)Imbalance
여성종사자수 is highly imbalanced (72.0%)Imbalance
영업장주변구분명 is highly imbalanced (77.0%)Imbalance
등급구분명 is highly imbalanced (74.7%)Imbalance
총인원 is highly imbalanced (80.9%)Imbalance
보증액 is highly imbalanced (71.8%)Imbalance
월세액 is highly imbalanced (69.8%)Imbalance
시설총규모 is highly imbalanced (65.8%)Imbalance
인허가취소일자 has 171 (100.0%) missing valuesMissing
폐업일자 has 30 (17.5%) missing valuesMissing
휴업시작일자 has 171 (100.0%) missing valuesMissing
휴업종료일자 has 171 (100.0%) missing valuesMissing
재개업일자 has 171 (100.0%) missing valuesMissing
전화번호 has 69 (40.4%) missing valuesMissing
소재지면적 has 11 (6.4%) missing valuesMissing
도로명주소 has 84 (49.1%) missing valuesMissing
도로명우편번호 has 87 (50.9%) missing valuesMissing
좌표정보(X) has 4 (2.3%) missing valuesMissing
좌표정보(Y) has 4 (2.3%) missing valuesMissing
다중이용업소여부 has 31 (18.1%) missing valuesMissing
전통업소지정번호 has 171 (100.0%) missing valuesMissing
전통업소주된음식 has 171 (100.0%) missing valuesMissing
홈페이지 has 171 (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 5 (2.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:37:55.626312
Analysis finished2024-04-29 19:37:56.472679
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3070000
171 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 171
100.0%

Length

2024-04-30T04:37:56.533071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:56.607310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 171
100.0%

관리번호
Text

UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:37:56.741110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3762
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

Unique171 ?
Unique (%)100.0%

Sample

1st row3070000-109-1988-00001
2nd row3070000-109-1990-00663
3rd row3070000-109-1994-00001
4th row3070000-109-1994-00002
5th row3070000-109-1995-00524
ValueCountFrequency (%)
3070000-109-1988-00001 1
 
0.6%
3070000-109-2013-00004 1
 
0.6%
3070000-109-2016-00004 1
 
0.6%
3070000-109-2011-00005 1
 
0.6%
3070000-109-2011-00006 1
 
0.6%
3070000-109-2012-00001 1
 
0.6%
3070000-109-2012-00002 1
 
0.6%
3070000-109-2013-00001 1
 
0.6%
3070000-109-2013-00002 1
 
0.6%
3070000-109-2013-00003 1
 
0.6%
Other values (161) 161
94.2%
2024-04-30T04:37:57.024844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1926
51.2%
- 513
 
13.6%
1 308
 
8.2%
2 230
 
6.1%
9 227
 
6.0%
3 215
 
5.7%
7 198
 
5.3%
5 41
 
1.1%
4 36
 
1.0%
8 35
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3249
86.4%
Dash Punctuation 513
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1926
59.3%
1 308
 
9.5%
2 230
 
7.1%
9 227
 
7.0%
3 215
 
6.6%
7 198
 
6.1%
5 41
 
1.3%
4 36
 
1.1%
8 35
 
1.1%
6 33
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 513
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1926
51.2%
- 513
 
13.6%
1 308
 
8.2%
2 230
 
6.1%
9 227
 
6.0%
3 215
 
5.7%
7 198
 
5.3%
5 41
 
1.1%
4 36
 
1.0%
8 35
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1926
51.2%
- 513
 
13.6%
1 308
 
8.2%
2 230
 
6.1%
9 227
 
6.0%
3 215
 
5.7%
7 198
 
5.3%
5 41
 
1.1%
4 36
 
1.0%
8 35
 
0.9%

인허가일자
Date

Distinct166
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1984-12-24 00:00:00
Maximum2024-04-23 00:00:00
2024-04-30T04:37:57.152143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:57.287091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
141 
1
30 

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 (%)
3 141
82.5%
1 30
 
17.5%

Length

2024-04-30T04:37:57.402706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:57.493704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 141
82.5%
1 30
 
17.5%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
141 
영업/정상
30 

Length

Max length5
Median length2
Mean length2.5263158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 141
82.5%
영업/정상 30
 
17.5%

Length

2024-04-30T04:37:57.600263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:57.700543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 141
82.5%
영업/정상 30
 
17.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2
141 
1
30 

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 (%)
2 141
82.5%
1 30
 
17.5%

Length

2024-04-30T04:37:57.793648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:57.876082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 141
82.5%
1 30
 
17.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
141 
영업
30 

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 141
82.5%
영업 30
 
17.5%

Length

2024-04-30T04:37:57.959502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:37:58.044169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 141
82.5%
영업 30
 
17.5%

폐업일자
Date

MISSING 

Distinct137
Distinct (%)97.2%
Missing30
Missing (%)17.5%
Memory size1.5 KiB
Minimum1996-11-15 00:00:00
Maximum2023-12-12 00:00:00
2024-04-30T04:37:58.134074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:37:58.235611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

전화번호
Text

MISSING 

Distinct97
Distinct (%)95.1%
Missing69
Missing (%)40.4%
Memory size1.5 KiB
2024-04-30T04:37:58.448871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8921569
Min length6

Characters and Unicode

Total characters1009
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

Unique93 ?
Unique (%)91.2%

Sample

1st row9841234
2nd row02 9130105
3rd row9131005
4th row02 9412286
5th row02 0
ValueCountFrequency (%)
02 72
38.1%
9441230 3
 
1.6%
9218053 3
 
1.6%
070 3
 
1.6%
9131581 2
 
1.1%
9252145 2
 
1.1%
909 2
 
1.1%
07088332023 1
 
0.5%
9630153 1
 
0.5%
9841234 1
 
0.5%
Other values (99) 99
52.4%
2024-04-30T04:37:58.796653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 180
17.8%
2 164
16.3%
9 124
12.3%
1 114
11.3%
99
9.8%
4 71
 
7.0%
7 59
 
5.8%
5 55
 
5.5%
8 49
 
4.9%
3 48
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 910
90.2%
Space Separator 99
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 180
19.8%
2 164
18.0%
9 124
13.6%
1 114
12.5%
4 71
 
7.8%
7 59
 
6.5%
5 55
 
6.0%
8 49
 
5.4%
3 48
 
5.3%
6 46
 
5.1%
Space Separator
ValueCountFrequency (%)
99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1009
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 180
17.8%
2 164
16.3%
9 124
12.3%
1 114
11.3%
99
9.8%
4 71
 
7.0%
7 59
 
5.8%
5 55
 
5.5%
8 49
 
4.9%
3 48
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 180
17.8%
2 164
16.3%
9 124
12.3%
1 114
11.3%
99
9.8%
4 71
 
7.0%
7 59
 
5.8%
5 55
 
5.5%
8 49
 
4.9%
3 48
 
4.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct125
Distinct (%)78.1%
Missing11
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean32.921937
Minimum0
Maximum596.42
Zeros5
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-30T04:37:58.920987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.916
Q16.925
median14.895
Q333.49
95-th percentile115.205
Maximum596.42
Range596.42
Interquartile range (IQR)26.565

Descriptive statistics

Standard deviation59.20621
Coefficient of variation (CV)1.7983817
Kurtosis52.37844
Mean32.921937
Median Absolute Deviation (MAD)10.57
Skewness6.137044
Sum5267.51
Variance3505.3753
MonotonicityNot monotonic
2024-04-30T04:37:59.048649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 11
 
6.4%
0.0 5
 
2.9%
8.0 4
 
2.3%
3.3 3
 
1.8%
6.0 3
 
1.8%
7.0 3
 
1.8%
20.0 3
 
1.8%
33.0 3
 
1.8%
5.0 3
 
1.8%
3.0 2
 
1.2%
Other values (115) 120
70.2%
(Missing) 11
 
6.4%
ValueCountFrequency (%)
0.0 5
2.9%
0.7 1
 
0.6%
1.5 1
 
0.6%
1.84 1
 
0.6%
1.92 1
 
0.6%
2.0 2
 
1.2%
2.25 2
 
1.2%
2.5 1
 
0.6%
2.54 1
 
0.6%
2.8 1
 
0.6%
ValueCountFrequency (%)
596.42 1
0.6%
240.9 1
0.6%
184.8 1
0.6%
157.14 1
0.6%
155.2 1
0.6%
139.24 1
0.6%
139.0 1
0.6%
138.48 1
0.6%
113.98 1
0.6%
113.09 1
0.6%

소재지우편번호
Text

Distinct85
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:37:59.272170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0994152
Min length6

Characters and Unicode

Total characters1043
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

Unique52 ?
Unique (%)30.4%

Sample

1st row136800
2nd row136871
3rd row136864
4th row136852
5th row136833
ValueCountFrequency (%)
136800 16
 
9.4%
136719 9
 
5.3%
136865 9
 
5.3%
136060 6
 
3.5%
136826 6
 
3.5%
136818 5
 
2.9%
136140 5
 
2.9%
136817 4
 
2.3%
136130 4
 
2.3%
136863 4
 
2.3%
Other values (75) 103
60.2%
2024-04-30T04:37:59.630363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 229
22.0%
3 212
20.3%
6 208
19.9%
8 124
11.9%
0 102
9.8%
4 36
 
3.5%
5 34
 
3.3%
7 34
 
3.3%
2 28
 
2.7%
9 19
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1026
98.4%
Dash Punctuation 17
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 229
22.3%
3 212
20.7%
6 208
20.3%
8 124
12.1%
0 102
9.9%
4 36
 
3.5%
5 34
 
3.3%
7 34
 
3.3%
2 28
 
2.7%
9 19
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1043
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 229
22.0%
3 212
20.3%
6 208
19.9%
8 124
11.9%
0 102
9.8%
4 36
 
3.5%
5 34
 
3.3%
7 34
 
3.3%
2 28
 
2.7%
9 19
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1043
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 229
22.0%
3 212
20.3%
6 208
19.9%
8 124
11.9%
0 102
9.8%
4 36
 
3.5%
5 34
 
3.3%
7 34
 
3.3%
2 28
 
2.7%
9 19
 
1.8%

지번주소
Text

Distinct157
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:37:59.803009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length26.175439
Min length17

Characters and Unicode

Total characters4476
Distinct characters146
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

Unique148 ?
Unique (%)86.5%

Sample

1st row서울특별시 성북구 길음동 25-2
2nd row서울특별시 성북구 하월곡동 77-333
3rd row서울특별시 성북구 종암동 3-991
4th row서울특별시 성북구 정릉동 716-53
5th row서울특별시 성북구 장위동 190-12
ValueCountFrequency (%)
서울특별시 171
20.1%
성북구 171
20.1%
길음동 32
 
3.8%
장위동 23
 
2.7%
하월곡동 21
 
2.5%
석관동 19
 
2.2%
지하1층 18
 
2.1%
정릉동 17
 
2.0%
지상1층 15
 
1.8%
종암동 13
 
1.5%
Other values (243) 349
41.1%
2024-04-30T04:38:00.073230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
810
 
18.1%
1 210
 
4.7%
동 195
 
4.4%
성 180
 
4.0%
북 178
 
4.0%
시 174
 
3.9%
서 172
 
3.8%
구 171
 
3.8%
울 171
 
3.8%
별 171
 
3.8%
Other values (136) 2044
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2634
58.8%
Space Separator 810
 
18.1%
Decimal Number 810
 
18.1%
Dash Punctuation 144
 
3.2%
Close Punctuation 35
 
0.8%
Open Punctuation 35
 
0.8%
Uppercase Letter 7
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 195
 
7.4%
성 180
 
6.8%
북 178
 
6.8%
시 174
 
6.6%
서 172
 
6.5%
구 171
 
6.5%
울 171
 
6.5%
별 171
 
6.5%
특 171
 
6.5%
하 50
 
1.9%
Other values (115) 1001
38.0%
Decimal Number
ValueCountFrequency (%)
1 210
25.9%
2 155
19.1%
0 87
10.7%
3 76
 
9.4%
4 54
 
6.7%
6 53
 
6.5%
5 52
 
6.4%
9 42
 
5.2%
8 42
 
5.2%
7 39
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
L 1
14.3%
A 1
14.3%
P 1
14.3%
T 1
14.3%
S 1
14.3%
Space Separator
ValueCountFrequency (%)
810
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2634
58.8%
Common 1835
41.0%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 195
 
7.4%
성 180
 
6.8%
북 178
 
6.8%
시 174
 
6.6%
서 172
 
6.5%
구 171
 
6.5%
울 171
 
6.5%
별 171
 
6.5%
특 171
 
6.5%
하 50
 
1.9%
Other values (115) 1001
38.0%
Common
ValueCountFrequency (%)
810
44.1%
1 210
 
11.4%
2 155
 
8.4%
- 144
 
7.8%
0 87
 
4.7%
3 76
 
4.1%
4 54
 
2.9%
6 53
 
2.9%
5 52
 
2.8%
9 42
 
2.3%
Other values (5) 152
 
8.3%
Latin
ValueCountFrequency (%)
G 2
28.6%
L 1
14.3%
A 1
14.3%
P 1
14.3%
T 1
14.3%
S 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2634
58.8%
ASCII 1842
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
810
44.0%
1 210
 
11.4%
2 155
 
8.4%
- 144
 
7.8%
0 87
 
4.7%
3 76
 
4.1%
4 54
 
2.9%
6 53
 
2.9%
5 52
 
2.8%
9 42
 
2.3%
Other values (11) 159
 
8.6%
Hangul
ValueCountFrequency (%)
동 195
 
7.4%
성 180
 
6.8%
북 178
 
6.8%
시 174
 
6.6%
서 172
 
6.5%
구 171
 
6.5%
울 171
 
6.5%
별 171
 
6.5%
특 171
 
6.5%
하 50
 
1.9%
Other values (115) 1001
38.0%

도로명주소
Text

MISSING 

Distinct86
Distinct (%)98.9%
Missing84
Missing (%)49.1%
Memory size1.5 KiB
2024-04-30T04:38:00.343625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length34.206897
Min length23

Characters and Unicode

Total characters2976
Distinct characters138
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

Unique85 ?
Unique (%)97.7%

Sample

1st row서울특별시 성북구 성북로4길 52 (돈암동,스카이프라자 동관4층)
2nd row서울특별시 성북구 동소문로 315 (길음동,외 11필지 현대백화점)
3rd row서울특별시 성북구 화랑로 202 (석관동,새석관시장 223호)
4th row서울특별시 성북구 장월로 165 (장위동)
5th row서울특별시 성북구 정릉로44길 7 (돈암동,현대상가 지하2층)
ValueCountFrequency (%)
서울특별시 87
 
15.7%
성북구 87
 
15.7%
1층 25
 
4.5%
지하1층 16
 
2.9%
장위동 9
 
1.6%
정릉동 9
 
1.6%
동소문로 8
 
1.4%
종암동 7
 
1.3%
석관동 7
 
1.3%
길음동 6
 
1.1%
Other values (216) 292
52.8%
2024-04-30T04:38:00.734077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
466
 
15.7%
1 139
 
4.7%
동 112
 
3.8%
성 104
 
3.5%
북 104
 
3.5%
, 99
 
3.3%
) 96
 
3.2%
( 96
 
3.2%
서 90
 
3.0%
시 89
 
3.0%
Other values (128) 1581
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1780
59.8%
Space Separator 466
 
15.7%
Decimal Number 427
 
14.3%
Other Punctuation 99
 
3.3%
Close Punctuation 96
 
3.2%
Open Punctuation 96
 
3.2%
Dash Punctuation 10
 
0.3%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 112
 
6.3%
성 104
 
5.8%
북 104
 
5.8%
서 90
 
5.1%
시 89
 
5.0%
로 89
 
5.0%
구 87
 
4.9%
울 87
 
4.9%
별 87
 
4.9%
특 87
 
4.9%
Other values (111) 844
47.4%
Decimal Number
ValueCountFrequency (%)
1 139
32.6%
2 63
14.8%
3 44
 
10.3%
5 39
 
9.1%
4 35
 
8.2%
0 34
 
8.0%
7 23
 
5.4%
9 19
 
4.4%
8 16
 
3.7%
6 15
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
466
100.0%
Other Punctuation
ValueCountFrequency (%)
, 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1780
59.8%
Common 1194
40.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 112
 
6.3%
성 104
 
5.8%
북 104
 
5.8%
서 90
 
5.1%
시 89
 
5.0%
로 89
 
5.0%
구 87
 
4.9%
울 87
 
4.9%
별 87
 
4.9%
특 87
 
4.9%
Other values (111) 844
47.4%
Common
ValueCountFrequency (%)
466
39.0%
1 139
 
11.6%
, 99
 
8.3%
) 96
 
8.0%
( 96
 
8.0%
2 63
 
5.3%
3 44
 
3.7%
5 39
 
3.3%
4 35
 
2.9%
0 34
 
2.8%
Other values (5) 83
 
7.0%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1780
59.8%
ASCII 1196
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
466
39.0%
1 139
 
11.6%
, 99
 
8.3%
) 96
 
8.0%
( 96
 
8.0%
2 63
 
5.3%
3 44
 
3.7%
5 39
 
3.3%
4 35
 
2.9%
0 34
 
2.8%
Other values (7) 85
 
7.1%
Hangul
ValueCountFrequency (%)
동 112
 
6.3%
성 104
 
5.8%
북 104
 
5.8%
서 90
 
5.1%
시 89
 
5.0%
로 89
 
5.0%
구 87
 
4.9%
울 87
 
4.9%
별 87
 
4.9%
특 87
 
4.9%
Other values (111) 844
47.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)67.9%
Missing87
Missing (%)50.9%
Infinite0
Infinite (%)0.0%
Mean2784.7381
Minimum2700
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-30T04:38:00.858243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2700
5-th percentile2711.75
Q12736.75
median2786
Q32827.5
95-th percentile2863.55
Maximum2880
Range180
Interquartile range (IQR)90.75

Descriptive statistics

Standard deviation49.773249
Coefficient of variation (CV)0.017873584
Kurtosis-0.9613384
Mean2784.7381
Median Absolute Deviation (MAD)43.5
Skewness0.14654208
Sum233918
Variance2477.3764
MonotonicityNot monotonic
2024-04-30T04:38:00.989268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2730 6
 
3.5%
2797 5
 
2.9%
2880 4
 
2.3%
2784 3
 
1.8%
2721 3
 
1.8%
2781 3
 
1.8%
2831 3
 
1.8%
2806 2
 
1.2%
2788 2
 
1.2%
2861 2
 
1.2%
Other values (47) 51
29.8%
(Missing) 87
50.9%
ValueCountFrequency (%)
2700 1
 
0.6%
2701 1
 
0.6%
2710 1
 
0.6%
2711 2
 
1.2%
2716 1
 
0.6%
2717 2
 
1.2%
2719 1
 
0.6%
2721 3
1.8%
2728 1
 
0.6%
2730 6
3.5%
ValueCountFrequency (%)
2880 4
2.3%
2864 1
 
0.6%
2861 2
1.2%
2859 1
 
0.6%
2858 1
 
0.6%
2853 1
 
0.6%
2846 1
 
0.6%
2845 1
 
0.6%
2840 1
 
0.6%
2837 1
 
0.6%

사업장명
Text

Distinct165
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-30T04:38:01.235973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length6.625731
Min length2

Characters and Unicode

Total characters1133
Distinct characters288
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)93.6%

Sample

1st row(주)신세계백화점 미아점
2nd row두두물산
3rd row영남식품
4th row대상물산
5th row(주)아남무역
ValueCountFrequency (%)
주식회사 6
 
3.1%
영우유통 3
 
1.5%
대성상회 2
 
1.0%
주)지에스리테일 2
 
1.0%
두두물산 2
 
1.0%
주)아남무역 2
 
1.0%
마트 2
 
1.0%
미아점 2
 
1.0%
해피필즈(happy 1
 
0.5%
루시카토캔디 1
 
0.5%
Other values (172) 172
88.2%
2024-04-30T04:38:01.617082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 54
 
4.8%
( 53
 
4.7%
주 49
 
4.3%
마 38
 
3.4%
이 33
 
2.9%
트 33
 
2.9%
24
 
2.1%
스 23
 
2.0%
통 21
 
1.9%
유 20
 
1.8%
Other values (278) 785
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 953
84.1%
Close Punctuation 54
 
4.8%
Open Punctuation 53
 
4.7%
Space Separator 24
 
2.1%
Lowercase Letter 23
 
2.0%
Uppercase Letter 18
 
1.6%
Other Punctuation 4
 
0.4%
Dash Punctuation 2
 
0.2%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
5.1%
마 38
 
4.0%
이 33
 
3.5%
트 33
 
3.5%
스 23
 
2.4%
통 21
 
2.2%
유 20
 
2.1%
식 20
 
2.1%
점 18
 
1.9%
사 17
 
1.8%
Other values (242) 681
71.5%
Uppercase Letter
ValueCountFrequency (%)
K 3
16.7%
N 3
16.7%
O 1
 
5.6%
M 1
 
5.6%
Y 1
 
5.6%
U 1
 
5.6%
B 1
 
5.6%
T 1
 
5.6%
A 1
 
5.6%
F 1
 
5.6%
Other values (4) 4
22.2%
Lowercase Letter
ValueCountFrequency (%)
l 5
21.7%
e 3
13.0%
p 3
13.0%
a 3
13.0%
s 2
 
8.7%
r 1
 
4.3%
k 1
 
4.3%
t 1
 
4.3%
i 1
 
4.3%
y 1
 
4.3%
Other values (2) 2
 
8.7%
Other Punctuation
ValueCountFrequency (%)
. 1
25.0%
? 1
25.0%
' 1
25.0%
& 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 953
84.1%
Common 139
 
12.3%
Latin 41
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
5.1%
마 38
 
4.0%
이 33
 
3.5%
트 33
 
3.5%
스 23
 
2.4%
통 21
 
2.2%
유 20
 
2.1%
식 20
 
2.1%
점 18
 
1.9%
사 17
 
1.8%
Other values (242) 681
71.5%
Latin
ValueCountFrequency (%)
l 5
 
12.2%
K 3
 
7.3%
N 3
 
7.3%
e 3
 
7.3%
p 3
 
7.3%
a 3
 
7.3%
s 2
 
4.9%
O 1
 
2.4%
M 1
 
2.4%
r 1
 
2.4%
Other values (16) 16
39.0%
Common
ValueCountFrequency (%)
) 54
38.8%
( 53
38.1%
24
17.3%
- 2
 
1.4%
. 1
 
0.7%
? 1
 
0.7%
' 1
 
0.7%
1 1
 
0.7%
2 1
 
0.7%
& 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 953
84.1%
ASCII 180
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 54
30.0%
( 53
29.4%
24
13.3%
l 5
 
2.8%
K 3
 
1.7%
N 3
 
1.7%
e 3
 
1.7%
p 3
 
1.7%
a 3
 
1.7%
s 2
 
1.1%
Other values (26) 27
15.0%
Hangul
ValueCountFrequency (%)
주 49
 
5.1%
마 38
 
4.0%
이 33
 
3.5%
트 33
 
3.5%
스 23
 
2.4%
통 21
 
2.2%
유 20
 
2.1%
식 20
 
2.1%
점 18
 
1.9%
사 17
 
1.8%
Other values (242) 681
71.5%

최종수정일자
Date

Distinct144
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2002-01-09 00:00:00
Maximum2024-04-23 14:06:28
2024-04-30T04:38:01.740922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:01.871014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
I
137 
U
34 

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 137
80.1%
U 34
 
19.9%

Length

2024-04-30T04:38:01.993348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:02.253694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 137
80.1%
u 34
 
19.9%

데이터갱신일자
Date

Distinct52
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:05:00
2024-04-30T04:38:02.343668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:02.453642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
식품소분업
171 

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 171
100.0%

Length

2024-04-30T04:38:02.560123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:02.641667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 171
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)72.5%
Missing4
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean202725.53
Minimum199325.64
Maximum205996.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-30T04:38:02.730778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199325.64
5-th percentile200390.35
Q1201472
median202555.3
Q3203928.16
95-th percentile205432
Maximum205996.72
Range6671.0764
Interquartile range (IQR)2456.1617

Descriptive statistics

Standard deviation1560.787
Coefficient of variation (CV)0.0076990153
Kurtosis-0.84607439
Mean202725.53
Median Absolute Deviation (MAD)1192.3148
Skewness0.19504996
Sum33855164
Variance2436056
MonotonicityNot monotonic
2024-04-30T04:38:02.856672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202466.801104742 13
 
7.6%
202555.30089577 11
 
6.4%
200841.726990037 7
 
4.1%
205020.608686581 4
 
2.3%
202124.690868117 3
 
1.8%
205449.027340692 3
 
1.8%
202819.871767584 3
 
1.8%
203353.798850162 3
 
1.8%
205254.262597746 3
 
1.8%
200771.40526517 2
 
1.2%
Other values (111) 115
67.3%
(Missing) 4
 
2.3%
ValueCountFrequency (%)
199325.641539235 1
0.6%
199887.379548552 1
0.6%
199933.916769915 1
0.6%
200082.088156596 1
0.6%
200114.522844816 1
0.6%
200142.840558768 1
0.6%
200320.001810002 1
0.6%
200357.047976682 1
0.6%
200384.086912862 1
0.6%
200404.958822888 1
0.6%
ValueCountFrequency (%)
205996.717928956 1
 
0.6%
205579.315116664 1
 
0.6%
205542.869987573 1
 
0.6%
205479.185255535 1
 
0.6%
205460.443873775 1
 
0.6%
205457.942128162 1
 
0.6%
205449.027340692 3
1.8%
205392.264342531 1
 
0.6%
205323.12640843 1
 
0.6%
205307.530477042 1
 
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)72.5%
Missing4
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean455754.94
Minimum453057.15
Maximum457844.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-30T04:38:02.980921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453057.15
5-th percentile453796.98
Q1455138.5
median455988.51
Q3456503.07
95-th percentile457221.6
Maximum457844.35
Range4787.2013
Interquartile range (IQR)1364.5679

Descriptive statistics

Standard deviation1047.0498
Coefficient of variation (CV)0.0022973965
Kurtosis-0.1672577
Mean455754.94
Median Absolute Deviation (MAD)577.70605
Skewness-0.61626586
Sum76111074
Variance1096313.3
MonotonicityNot monotonic
2024-04-30T04:38:03.107124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456227.571665528 13
 
7.6%
456503.066230481 11
 
6.4%
454721.505180141 7
 
4.1%
456783.766604012 4
 
2.3%
455479.322312286 3
 
1.8%
455919.701664294 3
 
1.8%
455458.024657239 3
 
1.8%
455765.417145198 3
 
1.8%
456319.556671704 3
 
1.8%
456645.212754152 2
 
1.2%
Other values (111) 115
67.3%
(Missing) 4
 
2.3%
ValueCountFrequency (%)
453057.146732852 1
0.6%
453134.35445784 1
0.6%
453158.83013214 1
0.6%
453170.305690883 1
0.6%
453387.031988555 1
0.6%
453432.818679924 1
0.6%
453524.189940782 1
0.6%
453593.837775363 1
0.6%
453795.988296364 1
0.6%
453799.297227934 1
0.6%
ValueCountFrequency (%)
457844.348010616 1
0.6%
457664.961911112 1
0.6%
457468.689811636 1
0.6%
457437.789670966 2
1.2%
457423.617145425 1
0.6%
457329.294441212 1
0.6%
457243.643633058 1
0.6%
457242.963167718 1
0.6%
457171.757965707 1
0.6%
457130.07705801 1
0.6%

위생업태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
식품소분업
140 
<NA>
31 

Length

Max length5
Median length5
Mean length4.8187135
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 140
81.9%
<NA> 31
 
18.1%

Length

2024-04-30T04:38:03.227442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:03.316467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 140
81.9%
na 31
 
18.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
155 
0
 
8
1
 
6
2
 
2

Length

Max length4
Median length4
Mean length3.7192982
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 155
90.6%
0 8
 
4.7%
1 6
 
3.5%
2 2
 
1.2%

Length

2024-04-30T04:38:03.466906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:03.648941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
90.6%
0 8
 
4.7%
1 6
 
3.5%
2 2
 
1.2%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
155 
0
 
10
1
 
5
3
 
1

Length

Max length4
Median length4
Mean length3.7192982
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 155
90.6%
0 10
 
5.8%
1 5
 
2.9%
3 1
 
0.6%

Length

2024-04-30T04:38:03.807449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:03.897526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
90.6%
0 10
 
5.8%
1 5
 
2.9%
3 1
 
0.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
157 
주택가주변
 
8
기타
 
4
학교정화(절대)
 
1
아파트지역
 
1

Length

Max length8
Median length4
Mean length4.0292398
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
91.8%
주택가주변 8
 
4.7%
기타 4
 
2.3%
학교정화(절대) 1
 
0.6%
아파트지역 1
 
0.6%

Length

2024-04-30T04:38:03.995428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:04.092152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
91.8%
주택가주변 8
 
4.7%
기타 4
 
2.3%
학교정화(절대 1
 
0.6%
아파트지역 1
 
0.6%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
157 
자율
 
9
기타
 
4
우수
 
1

Length

Max length4
Median length4
Mean length3.8362573
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 157
91.8%
자율 9
 
5.3%
기타 4
 
2.3%
우수 1
 
0.6%

Length

2024-04-30T04:38:04.206134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:04.302515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
91.8%
자율 9
 
5.3%
기타 4
 
2.3%
우수 1
 
0.6%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
148 
상수도전용
23 

Length

Max length5
Median length4
Mean length4.1345029
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 148
86.5%
상수도전용 23
 
13.5%

Length

2024-04-30T04:38:04.401756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:04.490466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
86.5%
상수도전용 23
 
13.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
166 
0
 
5

Length

Max length4
Median length4
Mean length3.9122807
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> 166
97.1%
0 5
 
2.9%

Length

2024-04-30T04:38:04.591539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:04.691154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 166
97.1%
0 5
 
2.9%

본사종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
107 
0
62 
1
 
2

Length

Max length4
Median length4
Mean length2.877193
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
62.6%
0 62
36.3%
1 2
 
1.2%

Length

2024-04-30T04:38:04.784343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:04.877159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
62.6%
0 62
36.3%
1 2
 
1.2%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
107 
0
63 
2
 
1

Length

Max length4
Median length4
Mean length2.877193
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
62.6%
0 63
36.8%
2 1
 
0.6%

Length

2024-04-30T04:38:04.969170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:05.059843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
62.6%
0 63
36.8%
2 1
 
0.6%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
107 
0
60 
1
 
4

Length

Max length4
Median length4
Mean length2.877193
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
62.6%
0 60
35.1%
1 4
 
2.3%

Length

2024-04-30T04:38:05.169857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:05.266431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
62.6%
0 60
35.1%
1 4
 
2.3%

공장생산직종업원수
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
105 
0
59 
1
 
5
3
 
2

Length

Max length4
Median length4
Mean length2.8421053
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 105
61.4%
0 59
34.5%
1 5
 
2.9%
3 2
 
1.2%

Length

2024-04-30T04:38:05.354714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:05.447317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 105
61.4%
0 59
34.5%
1 5
 
2.9%
3 2
 
1.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
81 
자가
51 
임대
39 

Length

Max length4
Median length2
Mean length2.9473684
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> 81
47.4%
자가 51
29.8%
임대 39
22.8%

Length

2024-04-30T04:38:05.566561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:05.686049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
47.4%
자가 51
29.8%
임대 39
22.8%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
149 
0
19 
520000
 
1
50000000
 
1
5000000
 
1

Length

Max length8
Median length4
Mean length3.7192982
Min length1

Unique

Unique3 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
87.1%
0 19
 
11.1%
520000 1
 
0.6%
50000000 1
 
0.6%
5000000 1
 
0.6%

Length

2024-04-30T04:38:05.799279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:05.899936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
87.1%
0 19
 
11.1%
520000 1
 
0.6%
50000000 1
 
0.6%
5000000 1
 
0.6%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
<NA>
150 
0
19 
120000
 
1
300000
 
1

Length

Max length6
Median length4
Mean length3.6900585
Min length1

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
87.7%
0 19
 
11.1%
120000 1
 
0.6%
300000 1
 
0.6%

Length

2024-04-30T04:38:06.006013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:06.105347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
87.7%
0 19
 
11.1%
120000 1
 
0.6%
300000 1
 
0.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.7%
Missing31
Missing (%)18.1%
Memory size474.0 B
False
140 
(Missing)
31 
ValueCountFrequency (%)
False 140
81.9%
(Missing) 31
 
18.1%
2024-04-30T04:38:06.184276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
0.0
136 
<NA>
31 
5.9
 
1
2.15
 
1
10.0
 
1

Length

Max length4
Median length3
Mean length3.1929825
Min length3

Unique

Unique4 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 136
79.5%
<NA> 31
 
18.1%
5.9 1
 
0.6%
2.15 1
 
0.6%
10.0 1
 
0.6%
5.0 1
 
0.6%

Length

2024-04-30T04:38:06.274010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:06.370100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 136
79.5%
na 31
 
18.1%
5.9 1
 
0.6%
2.15 1
 
0.6%
10.0 1
 
0.6%
5.0 1
 
0.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing171
Missing (%)100.0%
Memory size1.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-109-1988-0000119881226<NA>3폐업2폐업20070220<NA><NA><NA>9841234138.48136800서울특별시 성북구 길음동 25-2<NA><NA>(주)신세계백화점 미아점2004-03-31 00:00:00I2018-08-31 23:59:59.0식품소분업202555.300896456503.06623식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130700003070000-109-1990-0066319841224<NA>3폐업2폐업20040901<NA><NA><NA>02 913010588.81136871서울특별시 성북구 하월곡동 77-333<NA><NA>두두물산2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업00기타우수<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230700003070000-109-1994-0000119940122<NA>3폐업2폐업20130204<NA><NA><NA>913100527.44136864서울특별시 성북구 종암동 3-991<NA><NA>영남식품2003-04-01 00:00:00I2018-08-31 23:59:59.0식품소분업202847.710921455578.808805식품소분업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330700003070000-109-1994-0000219940311<NA>3폐업2폐업19961115<NA><NA><NA><NA><NA>136852서울특별시 성북구 정릉동 716-53<NA><NA>대상물산2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업200404.958823456404.385289식품소분업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430700003070000-109-1995-0052419951028<NA>3폐업2폐업19970812<NA><NA><NA>02 94122860.0136833서울특별시 성북구 장위동 190-12<NA><NA>(주)아남무역2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업204261.463759457423.617145식품소분업11주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530700003070000-109-1996-0052519960930<NA>3폐업2폐업20000925<NA><NA><NA><NA>10.88136871서울특별시 성북구 하월곡동 79-106<NA><NA>코사마트2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업203061.410685456592.677009식품소분업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630700003070000-109-1996-0052619961004<NA>3폐업2폐업19991028<NA><NA><NA>02 00.0136826서울특별시 성북구 장위동 100-3<NA><NA>서광상사2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업204826.995244456989.449536식품소분업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730700003070000-109-1997-0052719970425<NA>3폐업2폐업20050412<NA><NA><NA>02 913208662.7136804서울특별시 성북구 길음동 625-15<NA><NA>삼영상사2002-07-09 00:00:00I2018-08-31 23:59:59.0식품소분업<NA><NA>식품소분업10주택가주변자율<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830700003070000-109-1997-0052819971030<NA>3폐업2폐업19971104<NA><NA><NA>02 959623637.44136815서울특별시 성북구 석관동 330-1<NA><NA>참맛식품2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업205449.027341455919.701664식품소분업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930700003070000-109-1997-0052919971002<NA>3폐업2폐업19990730<NA><NA><NA>02 941228919.97136140서울특별시 성북구 장위동 148-29<NA><NA>(주)아남무역2002-02-04 00:00:00I2018-08-31 23:59:59.0식품소분업204752.802838457329.294441식품소분업21주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
16130700003070000-109-2022-0000420221222<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0136036서울특별시 성북구 동소문동6가 240서울특별시 성북구 아리랑로 27-5, 1층 (동소문동6가)2830산기가2022-12-22 18:08:19I2021-11-01 22:04:00.0식품소분업201299.737738454773.250995<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16230700003070000-109-2023-000012023-01-06<NA>3폐업2폐업2023-09-07<NA><NA><NA><NA>7.0136-074서울특별시 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>
16330700003070000-109-2023-000022023-02-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0136-832서울특별시 성북구 장위동 301 번동시장서울특별시 성북구 한천로101길 59, 번동시장 1층 (장위동)2758대명마트2023-02-07 11:39:42I2022-12-02 00:09:00.0식품소분업204162.777673457664.961911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16430700003070000-109-2023-000032023-04-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.5136-060서울특별시 성북구 돈암동 639 돈암 힐스테이트아파트서울특별시 성북구 아리랑로 68, 109,110호 (돈암동, 돈암 힐스테이트아파트)2827오케이(O.K) 식자재 마트2023-04-06 10:03:24I2022-12-04 00:08:00.0식품소분업201261.184858455148.159475<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16530700003070000-109-2023-000042023-07-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0136-859서울특별시 성북구 종암동 3-1110 창익빌딩서울특별시 성북구 종암로28길 72-9, 창익빌딩 1층 (종암동)2797포레스트푸드2023-07-28 11:01:18I2022-12-06 21:00:00.0식품소분업202993.726497455330.876004<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16630700003070000-109-2023-000052023-08-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0136-865서울특별시 성북구 하월곡동 62-11서울특별시 성북구 오패산로 20, 지하1층 1호 (하월곡동)2751컬럼버스서클2023-08-18 15:56:10I2022-12-07 22:00:00.0식품소분업203270.606648455745.782829<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16730700003070000-109-2024-000012024-03-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3136-054서울특별시 성북구 동선동4가 102-2서울특별시 성북구 동소문로 115-1, 1층 (동선동4가)2829바스켓 테이블2024-03-11 14:18:54I2023-12-02 23:03:00.0식품소분업201481.252427454587.297362<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16830700003070000-109-2024-000022024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0136-833서울특별시 성북구 장위동 238-103서울특별시 성북구 장월로 92, 1층 (장위동)2767엘스소사이어티2024-03-19 10:39:51I2023-12-02 22:01:00.0식품소분업204250.703782456860.666717<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16930700003070000-109-2024-000032024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.0136-035서울특별시 성북구 동소문동5가 75 메디컬센터빌서울특별시 성북구 동소문로 98, 지하1층 (동소문동5가)2846(주)대서양 식자재마트2024-03-29 14:26:09I2023-12-02 21:01:00.0식품소분업201358.89399454439.085102<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17030700003070000-109-2024-000042024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0136-834서울특별시 성북구 장위동 216-20서울특별시 성북구 돌곶이로41길 39, 1층 (장위동)2754푸드차이2024-04-23 14:06:28I2023-12-03 22:05:00.0식품소분업204045.968869457242.963168<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>