Overview

Dataset statistics

Number of variables44
Number of observations68
Missing cells736
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.2 KiB
Average record size in memory379.9 B

Variable types

Categorical20
Text6
DateTime4
Unsupported9
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-18059/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (56.9%)Imbalance
여성종사자수 is highly imbalanced (56.9%)Imbalance
급수시설구분명 is highly imbalanced (56.9%)Imbalance
총인원 is highly imbalanced (56.9%)Imbalance
보증액 is highly imbalanced (61.1%)Imbalance
월세액 is highly imbalanced (61.1%)Imbalance
인허가취소일자 has 68 (100.0%) missing valuesMissing
폐업일자 has 24 (35.3%) missing valuesMissing
휴업시작일자 has 68 (100.0%) missing valuesMissing
휴업종료일자 has 68 (100.0%) missing valuesMissing
재개업일자 has 68 (100.0%) missing valuesMissing
전화번호 has 30 (44.1%) missing valuesMissing
소재지면적 has 19 (27.9%) missing valuesMissing
도로명주소 has 12 (17.6%) missing valuesMissing
도로명우편번호 has 16 (23.5%) missing valuesMissing
좌표정보(X) has 1 (1.5%) missing valuesMissing
좌표정보(Y) has 1 (1.5%) missing valuesMissing
영업장주변구분명 has 68 (100.0%) missing valuesMissing
등급구분명 has 68 (100.0%) missing valuesMissing
다중이용업소여부 has 21 (30.9%) missing valuesMissing
전통업소지정번호 has 68 (100.0%) missing valuesMissing
전통업소주된음식 has 68 (100.0%) missing valuesMissing
홈페이지 has 68 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 3 (4.4%) zerosZeros

Reproduction

Analysis started2024-04-29 19:34:59.854396
Analysis finished2024-04-29 19:35:00.695077
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
3070000
68 

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 68
100.0%

Length

2024-04-30T04:35:00.755497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:00.837337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 68
100.0%

관리번호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-04-30T04:35:00.981533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1496
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

Unique68 ?
Unique (%)100.0%

Sample

1st row3070000-135-2004-00001
2nd row3070000-135-2004-00002
3rd row3070000-135-2004-00003
4th row3070000-135-2004-00004
5th row3070000-135-2004-00005
ValueCountFrequency (%)
3070000-135-2004-00001 1
 
1.5%
3070000-135-2018-00001 1
 
1.5%
3070000-135-2016-00003 1
 
1.5%
3070000-135-2017-00001 1
 
1.5%
3070000-135-2017-00002 1
 
1.5%
3070000-135-2017-00003 1
 
1.5%
3070000-135-2017-00004 1
 
1.5%
3070000-135-2004-00002 1
 
1.5%
3070000-135-2018-00003 1
 
1.5%
3070000-135-2005-00002 1
 
1.5%
Other values (58) 58
85.3%
2024-04-30T04:35:01.289424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 705
47.1%
- 204
 
13.6%
3 160
 
10.7%
1 122
 
8.2%
2 111
 
7.4%
7 79
 
5.3%
5 75
 
5.0%
4 21
 
1.4%
6 7
 
0.5%
9 7
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1292
86.4%
Dash Punctuation 204
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 705
54.6%
3 160
 
12.4%
1 122
 
9.4%
2 111
 
8.6%
7 79
 
6.1%
5 75
 
5.8%
4 21
 
1.6%
6 7
 
0.5%
9 7
 
0.5%
8 5
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1496
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 705
47.1%
- 204
 
13.6%
3 160
 
10.7%
1 122
 
8.2%
2 111
 
7.4%
7 79
 
5.3%
5 75
 
5.0%
4 21
 
1.4%
6 7
 
0.5%
9 7
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 705
47.1%
- 204
 
13.6%
3 160
 
10.7%
1 122
 
8.2%
2 111
 
7.4%
7 79
 
5.3%
5 75
 
5.0%
4 21
 
1.4%
6 7
 
0.5%
9 7
 
0.5%

인허가일자
Date

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2004-06-01 00:00:00
Maximum2024-04-03 00:00:00
2024-04-30T04:35:01.417117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:01.539728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
3
44 
1
24 

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 44
64.7%
1 24
35.3%

Length

2024-04-30T04:35:01.666166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:01.743686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 44
64.7%
1 24
35.3%

영업상태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
폐업
44 
영업/정상
24 

Length

Max length5
Median length2
Mean length3.0588235
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 44
64.7%
영업/정상 24
35.3%

Length

2024-04-30T04:35:01.831611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:01.922250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 44
64.7%
영업/정상 24
35.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
2
44 
1
24 

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 44
64.7%
1 24
35.3%

Length

2024-04-30T04:35:02.007344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:02.087183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 44
64.7%
1 24
35.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
폐업
44 
영업
24 

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 44
64.7%
영업 24
35.3%

Length

2024-04-30T04:35:02.174397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:02.256384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 44
64.7%
영업 24
35.3%

폐업일자
Date

MISSING 

Distinct39
Distinct (%)88.6%
Missing24
Missing (%)35.3%
Memory size676.0 B
Minimum2006-04-25 00:00:00
Maximum2023-12-29 00:00:00
2024-04-30T04:35:02.344848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:02.454219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

전화번호
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing30
Missing (%)44.1%
Memory size676.0 B
2024-04-30T04:35:02.607249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.815789
Min length7

Characters and Unicode

Total characters411
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

Unique38 ?
Unique (%)100.0%

Sample

1st row02 9248885
2nd row02 9570720
3rd row02 9644510
4th row02 9092584
5th row02 9119600
ValueCountFrequency (%)
02 24
32.9%
070 4
 
5.5%
9248885 1
 
1.4%
07043242019 1
 
1.4%
21490501 1
 
1.4%
0262325448 1
 
1.4%
87874600 1
 
1.4%
07078453115 1
 
1.4%
22123598 1
 
1.4%
82382970 1
 
1.4%
Other values (37) 37
50.7%
2024-04-30T04:35:02.894085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 84
20.4%
2 71
17.3%
45
10.9%
9 40
9.7%
5 30
 
7.3%
1 27
 
6.6%
8 25
 
6.1%
3 25
 
6.1%
7 24
 
5.8%
4 24
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 366
89.1%
Space Separator 45
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 84
23.0%
2 71
19.4%
9 40
10.9%
5 30
 
8.2%
1 27
 
7.4%
8 25
 
6.8%
3 25
 
6.8%
7 24
 
6.6%
4 24
 
6.6%
6 16
 
4.4%
Space Separator
ValueCountFrequency (%)
45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 84
20.4%
2 71
17.3%
45
10.9%
9 40
9.7%
5 30
 
7.3%
1 27
 
6.6%
8 25
 
6.1%
3 25
 
6.1%
7 24
 
5.8%
4 24
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 84
20.4%
2 71
17.3%
45
10.9%
9 40
9.7%
5 30
 
7.3%
1 27
 
6.6%
8 25
 
6.1%
3 25
 
6.1%
7 24
 
5.8%
4 24
 
5.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct42
Distinct (%)85.7%
Missing19
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean77.526327
Minimum0
Maximum411.74
Zeros3
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-30T04:35:03.028734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.32
Q115
median60
Q3112
95-th percentile235.04
Maximum411.74
Range411.74
Interquartile range (IQR)97

Descriptive statistics

Standard deviation82.597295
Coefficient of variation (CV)1.0654096
Kurtosis5.1327447
Mean77.526327
Median Absolute Deviation (MAD)45
Skewness1.9859071
Sum3798.79
Variance6822.3132
MonotonicityNot monotonic
2024-04-30T04:35:03.126732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0.0 3
 
4.4%
4.0 2
 
2.9%
15.0 2
 
2.9%
87.42 2
 
2.9%
10.0 2
 
2.9%
112.0 2
 
2.9%
45.89 1
 
1.5%
60.0 1
 
1.5%
14.0 1
 
1.5%
6.6 1
 
1.5%
Other values (32) 32
47.1%
(Missing) 19
27.9%
ValueCountFrequency (%)
0.0 3
4.4%
3.3 1
 
1.5%
4.0 2
2.9%
6.6 1
 
1.5%
10.0 2
2.9%
11.88 1
 
1.5%
14.0 1
 
1.5%
15.0 2
2.9%
20.0 1
 
1.5%
21.24 1
 
1.5%
ValueCountFrequency (%)
411.74 1
1.5%
292.57 1
1.5%
255.0 1
1.5%
205.1 1
1.5%
162.27 1
1.5%
159.75 1
1.5%
157.42 1
1.5%
132.0 1
1.5%
130.0 1
1.5%
127.5 1
1.5%

소재지우편번호
Text

Distinct50
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-04-30T04:35:03.303588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2352941
Min length6

Characters and Unicode

Total characters424
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

Unique37 ?
Unique (%)54.4%

Sample

1st row136860
2nd row136865
3rd row136865
4th row136100
5th row136859
ValueCountFrequency (%)
136044 5
 
7.4%
136865 4
 
5.9%
136819 2
 
2.9%
136833 2
 
2.9%
136-865 2
 
2.9%
136702 2
 
2.9%
136815 2
 
2.9%
136045 2
 
2.9%
136085 2
 
2.9%
136-073 2
 
2.9%
Other values (40) 43
63.2%
2024-04-30T04:35:03.590713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 86
20.3%
3 82
19.3%
6 78
18.4%
0 41
9.7%
8 38
9.0%
7 23
 
5.4%
4 21
 
5.0%
5 21
 
5.0%
- 16
 
3.8%
9 10
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
96.2%
Dash Punctuation 16
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 86
21.1%
3 82
20.1%
6 78
19.1%
0 41
10.0%
8 38
9.3%
7 23
 
5.6%
4 21
 
5.1%
5 21
 
5.1%
9 10
 
2.5%
2 8
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 424
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 86
20.3%
3 82
19.3%
6 78
18.4%
0 41
9.7%
8 38
9.0%
7 23
 
5.4%
4 21
 
5.0%
5 21
 
5.0%
- 16
 
3.8%
9 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 86
20.3%
3 82
19.3%
6 78
18.4%
0 41
9.7%
8 38
9.0%
7 23
 
5.4%
4 21
 
5.0%
5 21
 
5.0%
- 16
 
3.8%
9 10
 
2.4%

지번주소
Text

Distinct65
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-04-30T04:35:03.799312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length27.661765
Min length18

Characters and Unicode

Total characters1881
Distinct characters139
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

Unique62 ?
Unique (%)91.2%

Sample

1st row서울특별시 성북구 종암동 **-**번지 백양빌딩 *층
2nd row서울특별시 성북구 하월곡동 **-*번지 H ***호
3rd row서울특별시 성북구 하월곡동 **-*번지
4th row서울특별시 성북구 정릉동 ****번지 우방아파트상가 B***호
5th row서울특별시 성북구 종암동 *-****번지 미아빌딩동 ***호
ValueCountFrequency (%)
서울특별시 68
19.4%
성북구 67
19.1%
번지 37
10.5%
30
 
8.5%
층 10
 
2.8%
정릉동 10
 
2.8%
호 10
 
2.8%
안암동*가 9
 
2.6%
종암동 9
 
2.6%
하월곡동 9
 
2.6%
Other values (63) 92
26.2%
2024-04-30T04:35:04.129180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 350
18.6%
321
17.1%
동 78
 
4.1%
성 74
 
3.9%
시 70
 
3.7%
북 70
 
3.7%
서 69
 
3.7%
특 68
 
3.6%
별 68
 
3.6%
구 68
 
3.6%
Other values (129) 645
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1133
60.2%
Other Punctuation 351
 
18.7%
Space Separator 321
 
17.1%
Dash Punctuation 51
 
2.7%
Lowercase Letter 8
 
0.4%
Uppercase Letter 6
 
0.3%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 78
 
6.9%
성 74
 
6.5%
시 70
 
6.2%
북 70
 
6.2%
서 69
 
6.1%
특 68
 
6.0%
별 68
 
6.0%
구 68
 
6.0%
울 68
 
6.0%
지 46
 
4.1%
Other values (116) 454
40.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
50.0%
e 2
25.0%
i 2
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
V 2
33.3%
H 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
* 350
99.7%
, 1
 
0.3%
Space Separator
ValueCountFrequency (%)
321
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Decimal Number
ValueCountFrequency (%)
4 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1133
60.2%
Common 734
39.0%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 78
 
6.9%
성 74
 
6.5%
시 70
 
6.2%
북 70
 
6.2%
서 69
 
6.1%
특 68
 
6.0%
별 68
 
6.0%
구 68
 
6.0%
울 68
 
6.0%
지 46
 
4.1%
Other values (116) 454
40.1%
Common
ValueCountFrequency (%)
* 350
47.7%
321
43.7%
- 51
 
6.9%
( 4
 
0.5%
) 4
 
0.5%
4 3
 
0.4%
, 1
 
0.1%
Latin
ValueCountFrequency (%)
l 4
28.6%
B 3
21.4%
V 2
14.3%
e 2
14.3%
i 2
14.3%
H 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1133
60.2%
ASCII 748
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 350
46.8%
321
42.9%
- 51
 
6.8%
( 4
 
0.5%
) 4
 
0.5%
l 4
 
0.5%
4 3
 
0.4%
B 3
 
0.4%
V 2
 
0.3%
e 2
 
0.3%
Other values (3) 4
 
0.5%
Hangul
ValueCountFrequency (%)
동 78
 
6.9%
성 74
 
6.5%
시 70
 
6.2%
북 70
 
6.2%
서 69
 
6.1%
특 68
 
6.0%
별 68
 
6.0%
구 68
 
6.0%
울 68
 
6.0%
지 46
 
4.1%
Other values (116) 454
40.1%

도로명주소
Text

MISSING 

Distinct54
Distinct (%)96.4%
Missing12
Missing (%)17.6%
Memory size676.0 B
2024-04-30T04:35:04.331297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length35.321429
Min length24

Characters and Unicode

Total characters1978
Distinct characters152
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

Unique52 ?
Unique (%)92.9%

Sample

1st row서울특별시 성북구 정릉로**길 * (정릉동)
2nd row서울특별시 성북구 화랑로**길 ** (석관동, B동)
3rd row서울특별시 성북구 보문로**길 **, *, *층 (안암동*가)
4th row서울특별시 성북구 월곡로*길 ** (종암동,*층)
5th row서울특별시 성북구 삼선교로 67-5, 101동 1001호 (삼선동4가, 공신아파트)
ValueCountFrequency (%)
59
15.4%
서울특별시 56
14.6%
성북구 55
14.3%
층 32
 
8.3%
호 16
 
4.2%
정릉동 9
 
2.3%
안암동*가 8
 
2.1%
삼선동*가 6
 
1.6%
하월곡동 6
 
1.6%
종암로 5
 
1.3%
Other values (96) 132
34.4%
2024-04-30T04:35:04.650570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
 
16.6%
* 311
 
15.7%
동 77
 
3.9%
, 68
 
3.4%
성 60
 
3.0%
북 60
 
3.0%
서 57
 
2.9%
( 57
 
2.9%
) 57
 
2.9%
시 57
 
2.9%
Other values (142) 846
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1123
56.8%
Other Punctuation 379
 
19.2%
Space Separator 328
 
16.6%
Open Punctuation 57
 
2.9%
Close Punctuation 57
 
2.9%
Decimal Number 11
 
0.6%
Dash Punctuation 9
 
0.5%
Lowercase Letter 8
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 77
 
6.9%
성 60
 
5.3%
북 60
 
5.3%
서 57
 
5.1%
시 57
 
5.1%
울 56
 
5.0%
로 56
 
5.0%
구 56
 
5.0%
별 56
 
5.0%
특 56
 
5.0%
Other values (124) 532
47.4%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
0 3
27.3%
6 1
 
9.1%
7 1
 
9.1%
4 1
 
9.1%
5 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
50.0%
e 2
25.0%
i 2
25.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
V 2
33.3%
N 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
* 311
82.1%
, 68
 
17.9%
Space Separator
ValueCountFrequency (%)
328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1123
56.8%
Common 841
42.5%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 77
 
6.9%
성 60
 
5.3%
북 60
 
5.3%
서 57
 
5.1%
시 57
 
5.1%
울 56
 
5.0%
로 56
 
5.0%
구 56
 
5.0%
별 56
 
5.0%
특 56
 
5.0%
Other values (124) 532
47.4%
Common
ValueCountFrequency (%)
328
39.0%
* 311
37.0%
, 68
 
8.1%
( 57
 
6.8%
) 57
 
6.8%
- 9
 
1.1%
1 4
 
0.5%
0 3
 
0.4%
6 1
 
0.1%
7 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
l 4
28.6%
B 3
21.4%
e 2
14.3%
i 2
14.3%
V 2
14.3%
N 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1123
56.8%
ASCII 855
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
38.4%
* 311
36.4%
, 68
 
8.0%
( 57
 
6.7%
) 57
 
6.7%
- 9
 
1.1%
1 4
 
0.5%
l 4
 
0.5%
0 3
 
0.4%
B 3
 
0.4%
Other values (8) 11
 
1.3%
Hangul
ValueCountFrequency (%)
동 77
 
6.9%
성 60
 
5.3%
북 60
 
5.3%
서 57
 
5.1%
시 57
 
5.1%
울 56
 
5.0%
로 56
 
5.0%
구 56
 
5.0%
별 56
 
5.0%
특 56
 
5.0%
Other values (124) 532
47.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)73.1%
Missing16
Missing (%)23.5%
Infinite0
Infinite (%)0.0%
Mean2832.1923
Minimum2707
Maximum4045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-30T04:35:04.760709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2707
5-th percentile2714.5
Q12778.5
median2820
Q32856.25
95-th percentile2873
Maximum4045
Range1338
Interquartile range (IQR)77.75

Descriptive statistics

Standard deviation178.88774
Coefficient of variation (CV)0.063162287
Kurtosis43.448909
Mean2832.1923
Median Absolute Deviation (MAD)37.5
Skewness6.3051267
Sum147274
Variance32000.825
MonotonicityNot monotonic
2024-04-30T04:35:04.896503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
2797 3
 
4.4%
2861 3
 
4.4%
2707 2
 
2.9%
2847 2
 
2.9%
2748 2
 
2.9%
2789 2
 
2.9%
2719 2
 
2.9%
2862 2
 
2.9%
2810 2
 
2.9%
2873 2
 
2.9%
Other values (28) 30
44.1%
(Missing) 16
23.5%
ValueCountFrequency (%)
2707 2
2.9%
2709 1
1.5%
2719 2
2.9%
2730 1
1.5%
2733 1
1.5%
2737 1
1.5%
2748 2
2.9%
2751 1
1.5%
2767 1
1.5%
2771 1
1.5%
ValueCountFrequency (%)
4045 1
 
1.5%
2880 1
 
1.5%
2873 2
2.9%
2872 1
 
1.5%
2862 2
2.9%
2861 3
4.4%
2858 2
2.9%
2857 1
 
1.5%
2856 1
 
1.5%
2853 1
 
1.5%

사업장명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-04-30T04:35:05.147669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length7.3088235
Min length2

Characters and Unicode

Total characters497
Distinct characters172
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row(주)쓰리지케어
2nd row(주)엔에스케이텍
3rd row(주)라이퍼바이오텍
4th row풀하우스
5th row포천약품상사
ValueCountFrequency (%)
주식회사 11
 
13.8%
주)쓰리지케어 1
 
1.2%
주)바디큐브 1
 
1.2%
웰니스라이프 1
 
1.2%
주)에이치더블유에이치 1
 
1.2%
꿀건달 1
 
1.2%
주식회사헬스하우스 1
 
1.2%
자이언츠오더 1
 
1.2%
주)엔에스케이텍 1
 
1.2%
주)예현마케팅 1
 
1.2%
Other values (60) 60
75.0%
2024-04-30T04:35:05.490807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 39
 
7.8%
( 28
 
5.6%
) 28
 
5.6%
이 25
 
5.0%
스 17
 
3.4%
사 16
 
3.2%
식 16
 
3.2%
회 14
 
2.8%
12
 
2.4%
에 10
 
2.0%
Other values (162) 292
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 414
83.3%
Open Punctuation 28
 
5.6%
Close Punctuation 28
 
5.6%
Space Separator 12
 
2.4%
Uppercase Letter 10
 
2.0%
Lowercase Letter 3
 
0.6%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 39
 
9.4%
이 25
 
6.0%
스 17
 
4.1%
사 16
 
3.9%
식 16
 
3.9%
회 14
 
3.4%
에 10
 
2.4%
라 8
 
1.9%
오 8
 
1.9%
케 8
 
1.9%
Other values (147) 253
61.1%
Uppercase Letter
ValueCountFrequency (%)
M 3
30.0%
O 2
20.0%
J 1
 
10.0%
N 1
 
10.0%
E 1
 
10.0%
H 1
 
10.0%
L 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
n 1
33.3%
i 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 414
83.3%
Common 70
 
14.1%
Latin 13
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 39
 
9.4%
이 25
 
6.0%
스 17
 
4.1%
사 16
 
3.9%
식 16
 
3.9%
회 14
 
3.4%
에 10
 
2.4%
라 8
 
1.9%
오 8
 
1.9%
케 8
 
1.9%
Other values (147) 253
61.1%
Latin
ValueCountFrequency (%)
M 3
23.1%
O 2
15.4%
J 1
 
7.7%
N 1
 
7.7%
E 1
 
7.7%
H 1
 
7.7%
e 1
 
7.7%
n 1
 
7.7%
i 1
 
7.7%
L 1
 
7.7%
Common
ValueCountFrequency (%)
( 28
40.0%
) 28
40.0%
12
17.1%
. 1
 
1.4%
& 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 414
83.3%
ASCII 83
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 39
 
9.4%
이 25
 
6.0%
스 17
 
4.1%
사 16
 
3.9%
식 16
 
3.9%
회 14
 
3.4%
에 10
 
2.4%
라 8
 
1.9%
오 8
 
1.9%
케 8
 
1.9%
Other values (147) 253
61.1%
ASCII
ValueCountFrequency (%)
( 28
33.7%
) 28
33.7%
12
14.5%
M 3
 
3.6%
O 2
 
2.4%
J 1
 
1.2%
N 1
 
1.2%
E 1
 
1.2%
. 1
 
1.2%
H 1
 
1.2%
Other values (5) 5
 
6.0%

최종수정일자
Date

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2004-06-14 00:00:00
Maximum2024-04-03 14:25:46
2024-04-30T04:35:05.802364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:05.903608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
I
46 
U
22 

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 46
67.6%
U 22
32.4%

Length

2024-04-30T04:35:06.004819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:06.078631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 46
67.6%
u 22
32.4%

데이터갱신일자
Date

Distinct35
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T04:35:06.160181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:06.270606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
건강기능식품유통전문판매업
68 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 68
100.0%

Length

2024-04-30T04:35:06.391255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:06.468611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 68
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)88.1%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean202228.17
Minimum192402.47
Maximum205674.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-30T04:35:06.563017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192402.47
5-th percentile200166.5
Q1201230.81
median202147.56
Q3203288.59
95-th percentile205050.87
Maximum205674.77
Range13272.302
Interquartile range (IQR)2057.788

Descriptive statistics

Standard deviation1931.1814
Coefficient of variation (CV)0.0095495175
Kurtosis9.0465708
Mean202228.17
Median Absolute Deviation (MAD)1079.6668
Skewness-1.7194517
Sum13549287
Variance3729461.7
MonotonicityNot monotonic
2024-04-30T04:35:06.708273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203934.360214315 3
 
4.4%
202959.015709751 2
 
2.9%
202959.293142996 2
 
2.9%
205050.874804615 2
 
2.9%
201907.499931509 2
 
2.9%
201236.356607708 2
 
2.9%
199628.172805473 2
 
2.9%
203104.711247782 1
 
1.5%
202147.563445871 1
 
1.5%
204746.21261151 1
 
1.5%
Other values (49) 49
72.1%
ValueCountFrequency (%)
192402.468624287 1
1.5%
199628.172805473 2
2.9%
200142.840558768 1
1.5%
200221.693270564 1
1.5%
200406.244476135 1
1.5%
200457.861914539 1
1.5%
200608.656831329 1
1.5%
200773.459670492 1
1.5%
200821.024024886 1
1.5%
200841.726990037 1
1.5%
ValueCountFrequency (%)
205674.770196402 1
 
1.5%
205632.34348067 1
 
1.5%
205619.709546648 1
 
1.5%
205050.874804615 2
2.9%
204994.676559846 1
 
1.5%
204746.21261151 1
 
1.5%
204237.51385208 1
 
1.5%
204215.082459126 1
 
1.5%
203934.360214315 3
4.4%
203699.905484172 1
 
1.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)88.1%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean454963.84
Minimum449701.63
Maximum457236.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-04-30T04:35:06.830906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449701.63
5-th percentile453200.35
Q1454102.26
median455128.84
Q3455834.88
95-th percentile456592.03
Maximum457236.26
Range7534.635
Interquartile range (IQR)1732.615

Descriptive statistics

Standard deviation1245.5297
Coefficient of variation (CV)0.0027376454
Kurtosis3.3268482
Mean454963.84
Median Absolute Deviation (MAD)928.25047
Skewness-1.0518966
Sum30482577
Variance1551344.2
MonotonicityNot monotonic
2024-04-30T04:35:06.947754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455417.925754463 3
 
4.4%
455400.037874011 2
 
2.9%
455081.24816279 2
 
2.9%
456089.086071008 2
 
2.9%
453519.140138977 2
 
2.9%
454263.493710962 2
 
2.9%
456534.7766001 2
 
2.9%
454508.901863913 1
 
1.5%
453152.39423341 1
 
1.5%
456616.565104138 1
 
1.5%
Other values (49) 49
72.1%
ValueCountFrequency (%)
449701.62502855 1
1.5%
453152.39423341 1
1.5%
453162.376311852 1
1.5%
453169.16269153 1
1.5%
453273.131287687 1
1.5%
453454.226068463 1
1.5%
453504.183306973 1
1.5%
453519.140138977 2
2.9%
453776.830069811 1
1.5%
453835.069325753 1
1.5%
ValueCountFrequency (%)
457236.260024904 1
1.5%
457045.067072887 1
1.5%
456820.592225852 1
1.5%
456616.565104138 1
1.5%
456534.7766001 2
2.9%
456416.307929309 1
1.5%
456366.752569552 1
1.5%
456308.902936869 1
1.5%
456227.571665528 1
1.5%
456158.998431472 1
1.5%

위생업태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
건강기능식품유통전문판매업
47 
<NA>
21 

Length

Max length13
Median length13
Mean length10.220588
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 47
69.1%
<NA> 21
30.9%

Length

2024-04-30T04:35:07.052226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:07.136168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 47
69.1%
na 21
30.9%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
62 
0
 
6

Length

Max length4
Median length4
Mean length3.7352941
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> 62
91.2%
0 6
 
8.8%

Length

2024-04-30T04:35:07.232563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:07.311165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
91.2%
0 6
 
8.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
62 
0
 
6

Length

Max length4
Median length4
Mean length3.7352941
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> 62
91.2%
0 6
 
8.8%

Length

2024-04-30T04:35:07.416610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:07.528528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
91.2%
0 6
 
8.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
62 
상수도전용
 
6

Length

Max length5
Median length4
Mean length4.0882353
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 62
91.2%
상수도전용 6
 
8.8%

Length

2024-04-30T04:35:07.630212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:07.713240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
91.2%
상수도전용 6
 
8.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
62 
0
 
6

Length

Max length4
Median length4
Mean length3.7352941
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> 62
91.2%
0 6
 
8.8%

Length

2024-04-30T04:35:07.801393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:07.900389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
91.2%
0 6
 
8.8%

본사종업원수
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
24 
4
 
1

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 24
35.3%
4 1
 
1.5%

Length

2024-04-30T04:35:07.995646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:08.086655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 24
35.3%
4 1
 
1.5%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
23 
1
 
2

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 23
33.8%
1 2
 
2.9%

Length

2024-04-30T04:35:08.186569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:08.275546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 23
33.8%
1 2
 
2.9%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
24 
3
 
1

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 24
35.3%
3 1
 
1.5%

Length

2024-04-30T04:35:08.360908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:08.443842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 24
35.3%
3 1
 
1.5%

공장생산직종업원수
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
24 
1
 
1

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 24
35.3%
1 1
 
1.5%

Length

2024-04-30T04:35:08.544900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:08.631176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 24
35.3%
1 1
 
1.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
40 
자가
20 
임대
8 

Length

Max length4
Median length4
Mean length3.1764706
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임대
2nd row임대
3rd row임대
4th row자가
5th row임대

Common Values

ValueCountFrequency (%)
<NA> 40
58.8%
자가 20
29.4%
임대 8
 
11.8%

Length

2024-04-30T04:35:08.736381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:08.843108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
58.8%
자가 20
29.4%
임대 8
 
11.8%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
57 
0
9 
6500000
 
1
8000000
 
1

Length

Max length7
Median length4
Mean length3.6911765
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

1st row<NA>
2nd row6500000
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
83.8%
0 9
 
13.2%
6500000 1
 
1.5%
8000000 1
 
1.5%

Length

2024-04-30T04:35:08.948673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:09.034631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
83.8%
0 9
 
13.2%
6500000 1
 
1.5%
8000000 1
 
1.5%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
57 
0
9 
800000
 
1
520000
 
1

Length

Max length6
Median length4
Mean length3.6617647
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

1st row<NA>
2nd row800000
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
83.8%
0 9
 
13.2%
800000 1
 
1.5%
520000 1
 
1.5%

Length

2024-04-30T04:35:09.125093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:09.214525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
83.8%
0 9
 
13.2%
800000 1
 
1.5%
520000 1
 
1.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.1%
Missing21
Missing (%)30.9%
Memory size268.0 B
False
47 
(Missing)
21 
ValueCountFrequency (%)
False 47
69.1%
(Missing) 21
30.9%
2024-04-30T04:35:09.295240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
0.0
45 
<NA>
21 
10.0
 
1
3.3
 
1

Length

Max length4
Median length3
Mean length3.3235294
Min length3

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 45
66.2%
<NA> 21
30.9%
10.0 1
 
1.5%
3.3 1
 
1.5%

Length

2024-04-30T04:35:09.376803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:09.466187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 45
66.2%
na 21
30.9%
10.0 1
 
1.5%
3.3 1
 
1.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030700003070000-135-2004-0000120040601<NA>3폐업2폐업20101228<NA><NA><NA>02 9248885100.0136860서울특별시 성북구 종암동 **-**번지 백양빌딩 *층<NA><NA>(주)쓰리지케어2005-12-19 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업203104.711248454508.901864건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
130700003070000-135-2004-0000220040614<NA>3폐업2폐업20100705<NA><NA><NA>02 957072042.9136865서울특별시 성북구 하월곡동 **-*번지 H ***호<NA><NA>(주)엔에스케이텍2004-06-14 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업203934.360214455417.925754건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0100임대6500000800000N0.0<NA><NA><NA>
230700003070000-135-2004-0000320040618<NA>3폐업2폐업20101125<NA><NA><NA>02 964451015.0136865서울특별시 성북구 하월곡동 **-*번지<NA><NA>(주)라이퍼바이오텍2006-04-04 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업203934.360214455417.925754건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
330700003070000-135-2004-0000420040625<NA>3폐업2폐업20060425<NA><NA><NA>02 909258463.0136100서울특별시 성북구 정릉동 ****번지 우방아파트상가 B***호<NA><NA>풀하우스2004-06-25 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업200821.024025455335.403146건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
430700003070000-135-2004-0000520040827<NA>3폐업2폐업20071108<NA><NA><NA>02 9119600292.57136859서울특별시 성북구 종암동 *-****번지 미아빌딩동 ***호<NA><NA>포천약품상사2004-08-27 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업202959.01571455400.037874건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
530700003070000-135-2004-0000620040924<NA>3폐업2폐업20171213<NA><NA><NA>02 942596927.0136841서울특별시 성북구 정릉동 **-***번지서울특별시 성북구 정릉로**길 * (정릉동)2816엠앤엠라인(M&M Line)2017-12-18 11:20:18I2018-08-31 23:59:59.0건강기능식품유통전문판매업201677.3223455497.554438건강기능식품유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0001자가<NA><NA>N0.0<NA><NA><NA>
630700003070000-135-2004-0000720040611<NA>1영업/정상1영업<NA><NA><NA><NA>080 990 338848.9136819서울특별시 성북구 석관동 ***번지 B동서울특별시 성북구 화랑로**길 ** (석관동, B동)2789(주)네츄럴라이프2012-03-20 09:43:53I2018-08-31 23:59:59.0건강기능식품유통전문판매업205050.874805456089.086071건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
730700003070000-135-2005-0000120050801<NA>3폐업2폐업20101125<NA><NA><NA>913200375.9136800서울특별시 성북구 길음동 ***-***번지 시대빌딩*층<NA><NA>주식회사 피앤피홀딩스2005-08-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업<NA><NA>건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>4130임대8000000520000N0.0<NA><NA><NA>
830700003070000-135-2005-0000220051012<NA>3폐업2폐업20101228<NA><NA><NA>02 9275904<NA>136075서울특별시 성북구 안암동*가 ***-*번지 노산빌딩***호<NA><NA>하나로2010-07-09 14:19:34I2018-08-31 23:59:59.0건강기능식품유통전문판매업202375.452279453273.131288건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930700003070000-135-2005-000032005-02-15<NA>3폐업2폐업2023-12-18<NA><NA><NA>02 9212031157.42136-073서울특별시 성북구 안암동*가 **서울특별시 성북구 보문로**길 **, *, *층 (안암동*가)2858(주)메디넥스2023-12-18 15:58:09U2022-11-01 22:00:00.0건강기능식품유통전문판매업201907.499932453519.140139<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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