Overview

Dataset statistics

Number of variables44
Number of observations33
Missing cells360
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory380.0 B

Variable types

Categorical20
Text8
DateTime3
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18207/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 has constant value ""Constant
등급구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (56.1%)Imbalance
여성종사자수 is highly imbalanced (56.1%)Imbalance
급수시설구분명 is highly imbalanced (56.1%)Imbalance
총인원 is highly imbalanced (56.1%)Imbalance
인허가취소일자 has 33 (100.0%) missing valuesMissing
폐업일자 has 12 (36.4%) missing valuesMissing
휴업시작일자 has 33 (100.0%) missing valuesMissing
휴업종료일자 has 33 (100.0%) missing valuesMissing
재개업일자 has 33 (100.0%) missing valuesMissing
전화번호 has 16 (48.5%) missing valuesMissing
소재지면적 has 7 (21.2%) missing valuesMissing
도로명주소 has 10 (30.3%) missing valuesMissing
도로명우편번호 has 12 (36.4%) missing valuesMissing
영업장주변구분명 has 32 (97.0%) missing valuesMissing
등급구분명 has 32 (97.0%) missing valuesMissing
다중이용업소여부 has 4 (12.1%) missing valuesMissing
시설총규모 has 4 (12.1%) missing valuesMissing
전통업소지정번호 has 33 (100.0%) missing valuesMissing
전통업소주된음식 has 33 (100.0%) missing valuesMissing
홈페이지 has 33 (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
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
시설총규모 has 16 (48.5%) zerosZeros

Reproduction

Analysis started2024-04-29 19:38:57.063389
Analysis finished2024-04-29 19:38:57.801269
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
3050000
33 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 33
100.0%

Length

2024-04-30T04:38:57.861623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:57.943109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 33
100.0%

관리번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-04-30T04:38:58.080274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters726
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

Unique33 ?
Unique (%)100.0%

Sample

1st row3050000-117-1996-00276
2nd row3050000-117-2003-00001
3rd row3050000-117-2003-00002
4th row3050000-117-2003-00003
5th row3050000-117-2003-00004
ValueCountFrequency (%)
3050000-117-1996-00276 1
 
3.0%
3050000-117-2012-00001 1
 
3.0%
3050000-117-2021-00005 1
 
3.0%
3050000-117-2021-00004 1
 
3.0%
3050000-117-2021-00003 1
 
3.0%
3050000-117-2021-00002 1
 
3.0%
3050000-117-2021-00001 1
 
3.0%
3050000-117-2018-00001 1
 
3.0%
3050000-117-2017-00001 1
 
3.0%
3050000-117-2015-00001 1
 
3.0%
Other values (23) 23
69.7%
2024-04-30T04:38:58.351324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 343
47.2%
- 99
 
13.6%
1 97
 
13.4%
2 51
 
7.0%
3 44
 
6.1%
5 40
 
5.5%
7 36
 
5.0%
4 7
 
1.0%
6 4
 
0.6%
9 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 627
86.4%
Dash Punctuation 99
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 343
54.7%
1 97
 
15.5%
2 51
 
8.1%
3 44
 
7.0%
5 40
 
6.4%
7 36
 
5.7%
4 7
 
1.1%
6 4
 
0.6%
9 3
 
0.5%
8 2
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 726
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 343
47.2%
- 99
 
13.6%
1 97
 
13.4%
2 51
 
7.0%
3 44
 
6.1%
5 40
 
5.5%
7 36
 
5.0%
4 7
 
1.0%
6 4
 
0.6%
9 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 343
47.2%
- 99
 
13.6%
1 97
 
13.4%
2 51
 
7.0%
3 44
 
6.1%
5 40
 
5.5%
7 36
 
5.0%
4 7
 
1.0%
6 4
 
0.6%
9 3
 
0.4%

인허가일자
Date

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum1996-09-24 00:00:00
Maximum2022-10-05 00:00:00
2024-04-30T04:38:58.475189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:58.567063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
3
21 
1
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 21
63.6%
1 12
36.4%

Length

2024-04-30T04:38:58.661262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:58.742319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 21
63.6%
1 12
36.4%

영업상태명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
폐업
21 
영업/정상
12 

Length

Max length5
Median length2
Mean length3.0909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 21
63.6%
영업/정상 12
36.4%

Length

2024-04-30T04:38:58.823961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:58.911335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 21
63.6%
영업/정상 12
36.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
2
21 
1
12 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 21
63.6%
1 12
36.4%

Length

2024-04-30T04:38:58.994384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:59.070367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 21
63.6%
1 12
36.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
폐업
21 
영업
12 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 21
63.6%
영업 12
36.4%

Length

2024-04-30T04:38:59.151597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:38:59.232413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 21
63.6%
영업 12
36.4%

폐업일자
Date

MISSING 

Distinct20
Distinct (%)95.2%
Missing12
Missing (%)36.4%
Memory size396.0 B
Minimum1999-12-11 00:00:00
Maximum2024-04-09 00:00:00
2024-04-30T04:38:59.308827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:38:59.421560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

전화번호
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing16
Missing (%)48.5%
Memory size396.0 B
2024-04-30T04:38:59.551046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.117647
Min length6

Characters and Unicode

Total characters172
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

Unique15 ?
Unique (%)88.2%

Sample

1st row02 0
2nd row0222467293
3rd row0234119240
4th row02 9660484
5th row02 9276400
ValueCountFrequency (%)
02 8
30.8%
0222440011 2
 
7.7%
0222344409 1
 
3.8%
0264300300 1
 
3.8%
69592332 1
 
3.8%
8552 1
 
3.8%
967 1
 
3.8%
0222141212 1
 
3.8%
9292911 1
 
3.8%
0 1
 
3.8%
Other values (8) 8
30.8%
2024-04-30T04:38:59.778834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 42
24.4%
0 34
19.8%
4 19
11.0%
9 15
 
8.7%
14
 
8.1%
1 13
 
7.6%
6 9
 
5.2%
3 9
 
5.2%
7 7
 
4.1%
5 6
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 158
91.9%
Space Separator 14
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 42
26.6%
0 34
21.5%
4 19
12.0%
9 15
 
9.5%
1 13
 
8.2%
6 9
 
5.7%
3 9
 
5.7%
7 7
 
4.4%
5 6
 
3.8%
8 4
 
2.5%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 42
24.4%
0 34
19.8%
4 19
11.0%
9 15
 
8.7%
14
 
8.1%
1 13
 
7.6%
6 9
 
5.2%
3 9
 
5.2%
7 7
 
4.1%
5 6
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 42
24.4%
0 34
19.8%
4 19
11.0%
9 15
 
8.7%
14
 
8.1%
1 13
 
7.6%
6 9
 
5.2%
3 9
 
5.2%
7 7
 
4.1%
5 6
 
3.5%

소재지면적
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)88.5%
Missing7
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean78.925769
Minimum3.3
Maximum495.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-30T04:38:59.889431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile3.3
Q118.125
median44.395
Q373.8825
95-th percentile402.59
Maximum495.87
Range492.57
Interquartile range (IQR)55.7575

Descriptive statistics

Standard deviation126.38142
Coefficient of variation (CV)1.6012694
Kurtosis8.0199049
Mean78.925769
Median Absolute Deviation (MAD)27.4
Skewness2.9153151
Sum2052.07
Variance15972.264
MonotonicityNot monotonic
2024-04-30T04:38:59.988907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3.3 4
 
12.1%
18.0 1
 
3.0%
49.68 1
 
3.0%
32.24 1
 
3.0%
26.4 1
 
3.0%
48.79 1
 
3.0%
82.5 1
 
3.0%
15.99 1
 
3.0%
10.6 1
 
3.0%
29.99 1
 
3.0%
Other values (13) 13
39.4%
(Missing) 7
21.2%
ValueCountFrequency (%)
3.3 4
12.1%
10.6 1
 
3.0%
15.99 1
 
3.0%
18.0 1
 
3.0%
18.5 1
 
3.0%
26.4 1
 
3.0%
29.7 1
 
3.0%
29.99 1
 
3.0%
32.24 1
 
3.0%
40.0 1
 
3.0%
ValueCountFrequency (%)
495.87 1
3.0%
483.4 1
3.0%
160.16 1
3.0%
101.13 1
3.0%
99.0 1
3.0%
82.5 1
3.0%
76.51 1
3.0%
66.0 1
3.0%
54.91 1
3.0%
50.0 1
3.0%

소재지우편번호
Text

Distinct21
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-04-30T04:39:00.133264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0909091
Min length6

Characters and Unicode

Total characters201
Distinct characters10
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

Unique16 ?
Unique (%)48.5%

Sample

1st row130875
2nd row130805
3rd row130840
4th row130862
5th row130820
ValueCountFrequency (%)
130842 6
18.2%
130863 4
 
12.1%
130768 3
 
9.1%
130805 2
 
6.1%
130860 2
 
6.1%
130-827 1
 
3.0%
130875 1
 
3.0%
130814 1
 
3.0%
130-840 1
 
3.0%
130811 1
 
3.0%
Other values (11) 11
33.3%
2024-04-30T04:39:00.370596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43
21.4%
1 38
18.9%
3 37
18.4%
8 32
15.9%
2 12
 
6.0%
6 12
 
6.0%
4 11
 
5.5%
7 8
 
4.0%
5 5
 
2.5%
- 3
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
98.5%
Dash Punctuation 3
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
21.7%
1 38
19.2%
3 37
18.7%
8 32
16.2%
2 12
 
6.1%
6 12
 
6.1%
4 11
 
5.6%
7 8
 
4.0%
5 5
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43
21.4%
1 38
18.9%
3 37
18.4%
8 32
15.9%
2 12
 
6.0%
6 12
 
6.0%
4 11
 
5.5%
7 8
 
4.0%
5 5
 
2.5%
- 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43
21.4%
1 38
18.9%
3 37
18.4%
8 32
15.9%
2 12
 
6.0%
6 12
 
6.0%
4 11
 
5.5%
7 8
 
4.0%
5 5
 
2.5%
- 3
 
1.5%

지번주소
Text

Distinct31
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-04-30T04:39:00.545297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length33
Mean length30.272727
Min length18

Characters and Unicode

Total characters999
Distinct characters81
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)90.9%

Sample

1st row서울특별시 동대문구 휘경동 **-*번지
2nd row서울특별시 동대문구 답십리동 ***-**번지 (지하*층)
3rd row서울특별시 동대문구 장안동 ***-*번지 (지하*층)
4th row서울특별시 동대문구 제기동 ***-**번지 [홍릉로**길**-*]
5th row서울특별시 동대문구 용두동 ***-**번지 (*층)
ValueCountFrequency (%)
서울특별시 33
19.5%
동대문구 33
19.5%
번지 23
13.6%
12
 
7.1%
장안동 9
 
5.3%
제기동 9
 
5.3%
이문동 5
 
3.0%
지하*층 4
 
2.4%
층 3
 
1.8%
답십리동 3
 
1.8%
Other values (27) 35
20.7%
2024-04-30T04:39:00.866617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 191
19.1%
164
16.4%
동 71
 
7.1%
문 40
 
4.0%
대 35
 
3.5%
시 34
 
3.4%
울 33
 
3.3%
구 33
 
3.3%
서 33
 
3.3%
별 33
 
3.3%
Other values (71) 332
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
59.3%
Other Punctuation 192
 
19.2%
Space Separator 164
 
16.4%
Dash Punctuation 28
 
2.8%
Close Punctuation 11
 
1.1%
Open Punctuation 11
 
1.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 71
 
12.0%
문 40
 
6.8%
대 35
 
5.9%
시 34
 
5.7%
울 33
 
5.6%
구 33
 
5.6%
서 33
 
5.6%
별 33
 
5.6%
특 33
 
5.6%
지 30
 
5.1%
Other values (62) 217
36.7%
Other Punctuation
ValueCountFrequency (%)
* 191
99.5%
, 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 7
63.6%
] 4
36.4%
Open Punctuation
ValueCountFrequency (%)
( 7
63.6%
[ 4
36.4%
Space Separator
ValueCountFrequency (%)
164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
59.3%
Common 407
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 71
 
12.0%
문 40
 
6.8%
대 35
 
5.9%
시 34
 
5.7%
울 33
 
5.6%
구 33
 
5.6%
서 33
 
5.6%
별 33
 
5.6%
특 33
 
5.6%
지 30
 
5.1%
Other values (62) 217
36.7%
Common
ValueCountFrequency (%)
* 191
46.9%
164
40.3%
- 28
 
6.9%
) 7
 
1.7%
( 7
 
1.7%
[ 4
 
1.0%
] 4
 
1.0%
~ 1
 
0.2%
, 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
59.3%
ASCII 407
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 191
46.9%
164
40.3%
- 28
 
6.9%
) 7
 
1.7%
( 7
 
1.7%
[ 4
 
1.0%
] 4
 
1.0%
~ 1
 
0.2%
, 1
 
0.2%
Hangul
ValueCountFrequency (%)
동 71
 
12.0%
문 40
 
6.8%
대 35
 
5.9%
시 34
 
5.7%
울 33
 
5.6%
구 33
 
5.6%
서 33
 
5.6%
별 33
 
5.6%
특 33
 
5.6%
지 30
 
5.1%
Other values (62) 217
36.7%

도로명주소
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing10
Missing (%)30.3%
Memory size396.0 B
2024-04-30T04:39:01.045759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length45
Mean length39.086957
Min length27

Characters and Unicode

Total characters899
Distinct characters83
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row서울특별시 동대문구 홍릉로**길 **-* (제기동,[홍릉로**길**-*])
2nd row서울특별시 동대문구 정릉천동로 **, ***호 (용두동)
3rd row서울특별시 동대문구 천호대로 ***, *층 (답십리동, 부룡빌딩)
4th row서울특별시 동대문구 장한로**길 **-* (장안동,가야써니빌 ***호(장미공원*길**-*))
5th row서울특별시 동대문구 한천로**길 **-* (이문동,*층[한천로**길 **-*])
ValueCountFrequency (%)
25
15.6%
서울특별시 23
14.4%
동대문구 23
14.4%
층 10
 
6.2%
호 10
 
6.2%
장안동 7
 
4.4%
한천로**길 5
 
3.1%
장한로**길 4
 
2.5%
써니빌 4
 
2.5%
가야아파트 4
 
2.5%
Other values (34) 45
28.1%
2024-04-30T04:39:01.356202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 149
16.6%
137
 
15.2%
동 53
 
5.9%
, 32
 
3.6%
대 29
 
3.2%
문 29
 
3.2%
로 26
 
2.9%
) 25
 
2.8%
( 25
 
2.8%
시 25
 
2.8%
Other values (73) 369
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
57.6%
Other Punctuation 181
 
20.1%
Space Separator 137
 
15.2%
Close Punctuation 27
 
3.0%
Open Punctuation 27
 
3.0%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
10.2%
대 29
 
5.6%
문 29
 
5.6%
로 26
 
5.0%
시 25
 
4.8%
서 23
 
4.4%
울 23
 
4.4%
구 23
 
4.4%
별 23
 
4.4%
특 23
 
4.4%
Other values (65) 241
46.5%
Other Punctuation
ValueCountFrequency (%)
* 149
82.3%
, 32
 
17.7%
Close Punctuation
ValueCountFrequency (%)
) 25
92.6%
] 2
 
7.4%
Open Punctuation
ValueCountFrequency (%)
( 25
92.6%
[ 2
 
7.4%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
57.6%
Common 381
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
10.2%
대 29
 
5.6%
문 29
 
5.6%
로 26
 
5.0%
시 25
 
4.8%
서 23
 
4.4%
울 23
 
4.4%
구 23
 
4.4%
별 23
 
4.4%
특 23
 
4.4%
Other values (65) 241
46.5%
Common
ValueCountFrequency (%)
* 149
39.1%
137
36.0%
, 32
 
8.4%
) 25
 
6.6%
( 25
 
6.6%
- 9
 
2.4%
] 2
 
0.5%
[ 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
57.6%
ASCII 381
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 149
39.1%
137
36.0%
, 32
 
8.4%
) 25
 
6.6%
( 25
 
6.6%
- 9
 
2.4%
] 2
 
0.5%
[ 2
 
0.5%
Hangul
ValueCountFrequency (%)
동 53
 
10.2%
대 29
 
5.6%
문 29
 
5.6%
로 26
 
5.0%
시 25
 
4.8%
서 23
 
4.4%
울 23
 
4.4%
구 23
 
4.4%
별 23
 
4.4%
특 23
 
4.4%
Other values (65) 241
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)66.7%
Missing12
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean2551.4762
Minimum2423
Maximum2643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-30T04:39:01.518267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2423
5-th percentile2429
Q12480
median2582
Q32624
95-th percentile2638
Maximum2643
Range220
Interquartile range (IQR)144

Descriptive statistics

Standard deviation81.610428
Coefficient of variation (CV)0.031985573
Kurtosis-1.460443
Mean2551.4762
Median Absolute Deviation (MAD)43
Skewness-0.50697759
Sum53581
Variance6660.2619
MonotonicityNot monotonic
2024-04-30T04:39:01.672756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2624 4
 
12.1%
2429 3
 
9.1%
2480 2
 
6.1%
2625 2
 
6.1%
2566 1
 
3.0%
2603 1
 
3.0%
2423 1
 
3.0%
2586 1
 
3.0%
2475 1
 
3.0%
2643 1
 
3.0%
Other values (4) 4
 
12.1%
(Missing) 12
36.4%
ValueCountFrequency (%)
2423 1
 
3.0%
2429 3
9.1%
2475 1
 
3.0%
2480 2
6.1%
2501 1
 
3.0%
2566 1
 
3.0%
2571 1
 
3.0%
2582 1
 
3.0%
2586 1
 
3.0%
2603 1
 
3.0%
ValueCountFrequency (%)
2643 1
 
3.0%
2638 1
 
3.0%
2625 2
6.1%
2624 4
12.1%
2603 1
 
3.0%
2586 1
 
3.0%
2582 1
 
3.0%
2571 1
 
3.0%
2566 1
 
3.0%
2501 1
 
3.0%

사업장명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-04-30T04:39:01.972877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.7575758
Min length2

Characters and Unicode

Total characters190
Distinct characters91
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row하이델식품
2nd row제주축협유통
3rd row대진유통
4th row고려티알
5th row(주)거성특수
ValueCountFrequency (%)
하이델식품 1
 
3.0%
주식회사대한식품 1
 
3.0%
글로벌로지스 1
 
3.0%
주)이너스로지스틱스 1
 
3.0%
대중통운(주 1
 
3.0%
주)비아이로지스 1
 
3.0%
노다지로지스(주 1
 
3.0%
평원유통 1
 
3.0%
시현 1
 
3.0%
짐콜 1
 
3.0%
Other values (23) 23
69.7%
2024-04-30T04:39:02.292987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 14
 
7.4%
( 12
 
6.3%
) 12
 
6.3%
스 10
 
5.3%
통 8
 
4.2%
지 6
 
3.2%
유 6
 
3.2%
로 5
 
2.6%
이 5
 
2.6%
대 4
 
2.1%
Other values (81) 108
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
87.4%
Open Punctuation 12
 
6.3%
Close Punctuation 12
 
6.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
8.4%
스 10
 
6.0%
통 8
 
4.8%
지 6
 
3.6%
유 6
 
3.6%
로 5
 
3.0%
이 5
 
3.0%
대 4
 
2.4%
수 4
 
2.4%
드 3
 
1.8%
Other values (79) 101
60.8%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
87.4%
Common 24
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
8.4%
스 10
 
6.0%
통 8
 
4.8%
지 6
 
3.6%
유 6
 
3.6%
로 5
 
3.0%
이 5
 
3.0%
대 4
 
2.4%
수 4
 
2.4%
드 3
 
1.8%
Other values (79) 101
60.8%
Common
ValueCountFrequency (%)
( 12
50.0%
) 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
87.4%
ASCII 24
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 14
 
8.4%
스 10
 
6.0%
통 8
 
4.8%
지 6
 
3.6%
유 6
 
3.6%
로 5
 
3.0%
이 5
 
3.0%
대 4
 
2.4%
수 4
 
2.4%
드 3
 
1.8%
Other values (79) 101
60.8%
ASCII
ValueCountFrequency (%)
( 12
50.0%
) 12
50.0%

최종수정일자
Date

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2001-09-29 00:00:00
Maximum2024-04-09 14:26:42
2024-04-30T04:39:02.397551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:39:02.507291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
I
23 
U
10 

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 23
69.7%
U 10
30.3%

Length

2024-04-30T04:39:02.622253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:02.705851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 23
69.7%
u 10
30.3%

데이터갱신일자
Categorical

Distinct13
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Memory size396.0 B
2018-08-31 23:59:59.0
21 
2023-12-03 23:01:00.0
 
1
2021-12-12 02:40:00.0
 
1
2019-05-17 02:40:00.0
 
1
2020-08-05 02:40:00.0
 
1
Other values (8)
8 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique12 ?
Unique (%)36.4%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 21
63.6%
2023-12-03 23:01:00.0 1
 
3.0%
2021-12-12 02:40:00.0 1
 
3.0%
2019-05-17 02:40:00.0 1
 
3.0%
2020-08-05 02:40:00.0 1
 
3.0%
2019-04-11 02:40:00.0 1
 
3.0%
2021-01-17 02:40:00.0 1
 
3.0%
2021-02-11 00:23:11.0 1
 
3.0%
2021-12-07 00:03:00.0 1
 
3.0%
2021-10-10 02:40:00.0 1
 
3.0%
Other values (3) 3
 
9.1%

Length

2024-04-30T04:39:02.786336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 21
31.8%
23:59:59.0 21
31.8%
02:40:00.0 6
 
9.1%
2022-12-05 2
 
3.0%
2021-10-10 2
 
3.0%
00:23:11.0 1
 
1.5%
22:03:00.0 1
 
1.5%
00:22:47.0 1
 
1.5%
00:03:00.0 1
 
1.5%
2021-12-07 1
 
1.5%
Other values (9) 9
13.6%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
식품운반업
33 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 33
100.0%

Length

2024-04-30T04:39:02.875878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:02.949661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 33
100.0%

좌표정보(X)
Real number (ℝ)

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204677.08
Minimum202033.01
Maximum206521.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-30T04:39:03.032558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202033.01
5-th percentile202558.83
Q1203401.5
median204882.52
Q3205974.65
95-th percentile206106.54
Maximum206521.41
Range4488.3912
Interquartile range (IQR)2573.1503

Descriptive statistics

Standard deviation1418.8521
Coefficient of variation (CV)0.0069321495
Kurtosis-1.4968919
Mean204677.08
Median Absolute Deviation (MAD)1169.1255
Skewness-0.3606544
Sum6754343.8
Variance2013141.4
MonotonicityNot monotonic
2024-04-30T04:39:03.141117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
206051.643931827 4
 
12.1%
205896.640685441 3
 
9.1%
205754.942835775 1
 
3.0%
202033.014104401 1
 
3.0%
203569.594298733 1
 
3.0%
206521.405320134 1
 
3.0%
206009.495097994 1
 
3.0%
203457.157920253 1
 
3.0%
202257.985695221 1
 
3.0%
205785.838196003 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
202033.014104401 1
3.0%
202257.985695221 1
3.0%
202759.39842201 1
3.0%
202880.493384188 1
3.0%
203036.12956477 1
3.0%
203040.335263445 1
3.0%
203085.866786086 1
3.0%
203380.147760527 1
3.0%
203401.504209341 1
3.0%
203425.397336216 1
3.0%
ValueCountFrequency (%)
206521.405320134 1
 
3.0%
206160.909253161 1
 
3.0%
206070.29392676 1
 
3.0%
206051.643931827 4
12.1%
206009.495097994 1
 
3.0%
205974.654499441 1
 
3.0%
205918.871763774 1
 
3.0%
205896.640685441 3
9.1%
205785.838196003 1
 
3.0%
205754.942835775 1
 
3.0%

좌표정보(Y)
Real number (ℝ)

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean453085.99
Minimum451364.88
Maximum455364.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-30T04:39:03.243150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451364.88
5-th percentile451762.04
Q1451926.03
median453301.83
Q3453747.95
95-th percentile455037.91
Maximum455364.6
Range3999.7228
Interquartile range (IQR)1821.9234

Descriptive statistics

Standard deviation1182.4752
Coefficient of variation (CV)0.0026098251
Kurtosis-1.0037411
Mean453085.99
Median Absolute Deviation (MAD)1211.7878
Skewness0.39211589
Sum14951838
Variance1398247.6
MonotonicityNot monotonic
2024-04-30T04:39:03.525494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
451926.028056415 4
 
12.1%
454847.087355503 3
 
9.1%
454349.694317829 1
 
3.0%
452501.604674196 1
 
3.0%
453747.951485517 1
 
3.0%
451940.119059947 1
 
3.0%
451806.846262685 1
 
3.0%
453348.018436025 1
 
3.0%
452478.339896363 1
 
3.0%
454305.171471466 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
451364.877944047 1
 
3.0%
451699.765836365 1
 
3.0%
451803.558407339 1
 
3.0%
451806.846262685 1
 
3.0%
451828.732208665 1
 
3.0%
451858.754428857 1
 
3.0%
451926.028056415 4
12.1%
451940.119059947 1
 
3.0%
452090.037417385 1
 
3.0%
452478.339896363 1
 
3.0%
ValueCountFrequency (%)
455364.600730821 1
 
3.0%
455324.155870975 1
 
3.0%
454847.087355503 3
9.1%
454349.694317829 1
 
3.0%
454305.171471466 1
 
3.0%
453749.778934612 1
 
3.0%
453747.951485517 1
 
3.0%
453706.065304781 1
 
3.0%
453618.063367612 1
 
3.0%
453572.548827033 1
 
3.0%

위생업태명
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
식품운반업
29 
<NA>
4 

Length

Max length5
Median length5
Mean length4.8787879
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품운반업 29
87.9%
<NA> 4
 
12.1%

Length

2024-04-30T04:39:03.635145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:03.734147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품운반업 29
87.9%
na 4
 
12.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
30 
0
 
3

Length

Max length4
Median length4
Mean length3.7272727
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> 30
90.9%
0 3
 
9.1%

Length

2024-04-30T04:39:03.844283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:03.931015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
90.9%
0 3
 
9.1%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
30 
0
 
3

Length

Max length4
Median length4
Mean length3.7272727
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> 30
90.9%
0 3
 
9.1%

Length

2024-04-30T04:39:04.018984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:04.116874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
90.9%
0 3
 
9.1%

영업장주변구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2024-04-30T04:39:04.190650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타
ValueCountFrequency (%)
기타 1
100.0%
2024-04-30T04:39:04.386916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

등급구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2024-04-30T04:39:04.468529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자율
ValueCountFrequency (%)
자율 1
100.0%
2024-04-30T04:39:04.677598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 1
50.0%
율 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 1
50.0%
율 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 1
50.0%
율 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 1
50.0%
율 1
50.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
30 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.0909091
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
90.9%
상수도전용 3
 
9.1%

Length

2024-04-30T04:39:04.793154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:04.880277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
90.9%
상수도전용 3
 
9.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
30 
0
 
3

Length

Max length4
Median length4
Mean length3.7272727
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> 30
90.9%
0 3
 
9.1%

Length

2024-04-30T04:39:04.970614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:05.054486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
90.9%
0 3
 
9.1%

본사종업원수
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
0
18 
<NA>
15 

Length

Max length4
Median length1
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
54.5%
<NA> 15
45.5%

Length

2024-04-30T04:39:05.152555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:05.244637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
54.5%
na 15
45.5%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
0
18 
<NA>
15 

Length

Max length4
Median length1
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
54.5%
<NA> 15
45.5%

Length

2024-04-30T04:39:05.350575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:05.443986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
54.5%
na 15
45.5%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
0
18 
<NA>
15 

Length

Max length4
Median length1
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
54.5%
<NA> 15
45.5%

Length

2024-04-30T04:39:05.537470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:05.625155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
54.5%
na 15
45.5%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
0
18 
<NA>
15 

Length

Max length4
Median length1
Mean length2.3636364
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
54.5%
<NA> 15
45.5%

Length

2024-04-30T04:39:05.725899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:05.812382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
54.5%
na 15
45.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
자가
20 
<NA>
9 
임대
4 

Length

Max length4
Median length2
Mean length2.5454545
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자가 20
60.6%
<NA> 9
27.3%
임대 4
 
12.1%

Length

2024-04-30T04:39:05.911955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:06.021427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가 20
60.6%
na 9
27.3%
임대 4
 
12.1%

보증액
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
22 
0
11 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
66.7%
0 11
33.3%

Length

2024-04-30T04:39:06.129322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:06.212961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
66.7%
0 11
33.3%

월세액
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
22 
0
11 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 22
66.7%
0 11
33.3%

Length

2024-04-30T04:39:06.312611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:39:06.394278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
66.7%
0 11
33.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.4%
Missing4
Missing (%)12.1%
Memory size198.0 B
False
29 
(Missing)
4 
ValueCountFrequency (%)
False 29
87.9%
(Missing) 4
 
12.1%
2024-04-30T04:39:06.469083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)41.4%
Missing4
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean33.193103
Minimum0
Maximum495.87
Zeros16
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-04-30T04:39:06.537014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q326.4
95-th percentile93.678
Maximum495.87
Range495.87
Interquartile range (IQR)26.4

Descriptive statistics

Standard deviation93.525383
Coefficient of variation (CV)2.8176149
Kurtosis23.190808
Mean33.193103
Median Absolute Deviation (MAD)0
Skewness4.6371277
Sum962.6
Variance8746.9973
MonotonicityNot monotonic
2024-04-30T04:39:06.641326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 16
48.5%
3.3 3
 
9.1%
76.51 1
 
3.0%
495.87 1
 
3.0%
54.91 1
 
3.0%
101.13 1
 
3.0%
40.0 1
 
3.0%
10.6 1
 
3.0%
15.99 1
 
3.0%
82.5 1
 
3.0%
Other values (2) 2
 
6.1%
(Missing) 4
 
12.1%
ValueCountFrequency (%)
0.0 16
48.5%
3.3 3
 
9.1%
10.6 1
 
3.0%
15.99 1
 
3.0%
26.4 1
 
3.0%
40.0 1
 
3.0%
48.79 1
 
3.0%
54.91 1
 
3.0%
76.51 1
 
3.0%
82.5 1
 
3.0%
ValueCountFrequency (%)
495.87 1
3.0%
101.13 1
3.0%
82.5 1
3.0%
76.51 1
3.0%
54.91 1
3.0%
48.79 1
3.0%
40.0 1
3.0%
26.4 1
3.0%
15.99 1
3.0%
10.6 1
3.0%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing33
Missing (%)100.0%
Memory size429.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-117-1996-0027619960924<NA>3폐업2폐업19991211<NA><NA><NA>02 049.5130875서울특별시 동대문구 휘경동 **-*번지<NA><NA>하이델식품2001-09-29 00:00:00I2018-08-31 23:59:59.0식품운반업205754.942836454349.694318식품운반업<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130500003050000-117-2003-0000120031023<NA>3폐업2폐업20040806<NA><NA><NA>0222467293<NA>130805서울특별시 동대문구 답십리동 ***-**번지 (지하*층)<NA><NA>제주축협유통2003-10-23 00:00:00I2018-08-31 23:59:59.0식품운반업204638.486387451699.765836식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230500003050000-117-2003-0000220031105<NA>3폐업2폐업20040811<NA><NA><NA>023411924018.0130840서울특별시 동대문구 장안동 ***-*번지 (지하*층)<NA><NA>대진유통2003-11-05 00:00:00I2018-08-31 23:59:59.0식품운반업206160.909253451828.732209식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
330500003050000-117-2003-0000320031106<NA>1영업/정상1영업<NA><NA><NA><NA>02 966048450.0130862서울특별시 동대문구 제기동 ***-**번지 [홍릉로**길**-*]서울특별시 동대문구 홍릉로**길 **-* (제기동,[홍릉로**길**-*])2480고려티알2010-11-30 10:48:41I2018-08-31 23:59:59.0식품운반업203585.497022453749.778935식품운반업<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
430500003050000-117-2003-0000420031203<NA>3폐업2폐업20120214<NA><NA><NA>02 9276400<NA>130820서울특별시 동대문구 용두동 ***-**번지 (*층)<NA><NA>(주)거성특수2007-07-12 00:00:00I2018-08-31 23:59:59.0식품운반업202759.398422452746.095519식품운반업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530500003050000-117-2003-0000520031205<NA>3폐업2폐업20050727<NA><NA><NA>0222498473<NA>130802서울특별시 동대문구 답십리동 ***-*번지 (*층)<NA><NA>충남축산2003-12-05 00:00:00I2018-08-31 23:59:59.0식품운반업204882.51841452090.037417식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
630500003050000-117-2004-0000120041025<NA>3폐업2폐업20090120<NA><NA><NA>02 9579096<NA>130863서울특별시 동대문구 제기동 ***-*번지<NA><NA>사임당김치2004-10-25 00:00:00I2018-08-31 23:59:59.0식품운반업203380.147761453470.076457식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730500003050000-117-2004-0000220041217<NA>1영업/정상1영업<NA><NA><NA><NA>023785265776.51130070서울특별시 동대문구 용두동 ***번지 ***호서울특별시 동대문구 정릉천동로 **, ***호 (용두동)2566부림운수(주)2012-10-12 16:05:07I2018-08-31 23:59:59.0식품운반업203085.866786452766.014196식품운반업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N76.51<NA><NA><NA>
830500003050000-117-2005-0000120050518<NA>3폐업2폐업20130313<NA><NA><NA><NA><NA>130827서울특별시 동대문구 이문동 ***-***번지 **통*반<NA><NA>개별용달2005-05-18 00:00:00I2018-08-31 23:59:59.0식품운반업205642.162951455364.600731식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
930500003050000-117-2005-0000220050613<NA>3폐업2폐업20120224<NA><NA><NA><NA><NA>130863서울특별시 동대문구 제기동 ***번지 [경동시장로**길*]<NA><NA>천하유통2011-11-24 10:46:29I2018-08-31 23:59:59.0식품운반업203401.504209453502.538274식품운반업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
2330500003050000-117-2014-0000220140714<NA>1영업/정상1영업<NA><NA><NA><NA>02 6959233215.99130768서울특별시 동대문구 이문동 **번지 이문삼익아파트 상가동 ***호서울특별시 동대문구 한천로**길 *, 상가동 ***호 (이문동, 이문삼익아파트)2429(주)화성통운2014-11-13 13:44:10I2018-08-31 23:59:59.0식품운반업205896.640685454847.087356식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N15.99<NA><NA><NA>
2430500003050000-117-2015-0000120150731<NA>3폐업2폐업20200803<NA><NA><NA><NA>82.5130874서울특별시 동대문구 휘경동 **-**서울특별시 동대문구 망우로 ***, *층 (휘경동)2501짐콜2020-08-03 14:12:28U2020-08-05 02:40:00.0식품운반업205785.838196454305.171471식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N82.5<NA><NA><NA>
2530500003050000-117-2017-0000120170419<NA>3폐업2폐업20190409<NA><NA><NA><NA>48.79130811서울특별시 동대문구 신설동 **-*번지서울특별시 동대문구 천호대로 **, 지하*층 (신설동, 동광베르빌)2582시현2019-04-09 14:06:23U2019-04-11 02:40:00.0식품운반업202257.985695452478.339896식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N48.79<NA><NA><NA>
2630500003050000-117-2018-0000120180402<NA>3폐업2폐업20210118<NA><NA><NA><NA>26.4130863서울특별시 동대문구 제기동 ***서울특별시 동대문구 고산자로**길 **, *층 (제기동)2571평원유통2021-01-15 15:49:20U2021-01-17 02:40:00.0식품운반업203457.15792453348.018436식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N26.4<NA><NA><NA>
2730500003050000-117-2021-0000120210209<NA>1영업/정상1영업<NA><NA><NA><NA>02224400113.3130842서울특별시 동대문구 장안동 ***-* 써니빌 가야아파트서울특별시 동대문구 장한로**길 **-*, 써니빌 가야아파트 *층 ***호 (장안동, 써니빌 가야아파트)2624노다지로지스(주)2021-02-09 14:59:59I2021-02-11 00:23:11.0식품운반업206051.643932451926.028056식품운반업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N3.3<NA><NA><NA>
2830500003050000-117-2021-0000220210805<NA>1영업/정상1영업<NA><NA><NA><NA>02 2244001132.24130842서울특별시 동대문구 장안동 ***-* 장안현대벤처빌서울특별시 동대문구 장한로 **, 장안현대벤처빌 *층 ***호 (장안동)2625(주)비아이로지스2022-07-01 10:20:55U2021-12-07 00:03:00.0식품운반업206009.495098451806.846263<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2930500003050000-117-2021-0000320210907<NA>3폐업2폐업20211008<NA><NA><NA><NA>3.3130842서울특별시 동대문구 장안동 ***-* 써니빌 가야아파트서울특별시 동대문구 장한로**길 **-*, ***호 (장안동, 써니빌 가야아파트)2624대중통운(주)2021-10-08 11:14:10U2021-10-10 02:40:00.0식품운반업206051.643932451926.028056식품운반업00<NA><NA><NA>00000자가00N3.3<NA><NA><NA>
3030500003050000-117-2021-0000420211008<NA>1영업/정상1영업<NA><NA><NA><NA>02224400113.3130842서울특별시 동대문구 장안동 ***-* 써니빌 가야아파트서울특별시 동대문구 장한로**길 **-*, ***호 (장안동, 써니빌 가야아파트)2624(주)이너스로지스틱스2021-10-08 11:27:50I2021-10-10 00:22:47.0식품운반업206051.643932451926.028056식품운반업00<NA><NA><NA>00000자가00N3.3<NA><NA><NA>
3130500003050000-117-2021-000052021-10-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-840서울특별시 동대문구 장안동 *** 장안현대홈타운서울특별시 동대문구 장안벚꽃로 ***, ***동 ****호 (장안동, 장안현대홈타운)2638글로벌로지스2023-06-21 16:49:08U2022-12-05 22:03:00.0식품운반업206521.40532451940.11906<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3230500003050000-117-2022-000012022-10-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.68130-862서울특별시 동대문구 제기동 ***서울특별시 동대문구 홍릉로**길 **, *층 (제기동)2480푸드피아2023-06-07 12:00:48U2022-12-05 23:00:00.0식품운반업203569.594299453747.951486<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>