Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells111124
Missing cells (%)25.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Categorical18
Text8
DateTime3
Unsupported8
Numeric6
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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18665/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (50.2%)Imbalance
급수시설구분명 is highly imbalanced (50.4%)Imbalance
총인원 is highly imbalanced (70.9%)Imbalance
본사종업원수 is highly imbalanced (70.9%)Imbalance
공장사무직종업원수 is highly imbalanced (70.9%)Imbalance
공장판매직종업원수 is highly imbalanced (70.9%)Imbalance
공장생산직종업원수 is highly imbalanced (70.9%)Imbalance
보증액 is highly imbalanced (70.9%)Imbalance
월세액 is highly imbalanced (70.9%)Imbalance
다중이용업소여부 is highly imbalanced (88.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2618 (26.2%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 5016 (50.2%) missing valuesMissing
소재지면적 has 142 (1.4%) missing valuesMissing
도로명주소 has 3914 (39.1%) missing valuesMissing
도로명우편번호 has 3975 (39.8%) missing valuesMissing
좌표정보(X) has 530 (5.3%) missing valuesMissing
좌표정보(Y) has 530 (5.3%) missing valuesMissing
남성종사자수 has 5682 (56.8%) missing valuesMissing
여성종사자수 has 5437 (54.4%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1621 (16.2%) missing valuesMissing
시설총규모 has 1621 (16.2%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (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
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 2921 (29.2%) zerosZeros
여성종사자수 has 2310 (23.1%) zerosZeros
시설총규모 has 138 (1.4%) zerosZeros

Reproduction

Analysis started2024-05-11 08:34:43.990852
Analysis finished2024-05-11 08:34:49.762849
Duration5.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3130000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 10000
100.0%

Length

2024-05-11T08:34:50.235970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:34:50.573349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:34:51.065476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3130000-101-2004-00444
2nd row3130000-101-2015-00436
3rd row3130000-101-1998-03542
4th row3130000-101-2020-00851
5th row3130000-101-2020-00727
ValueCountFrequency (%)
3130000-101-2004-00444 1
 
< 0.1%
3130000-101-2012-00655 1
 
< 0.1%
3130000-101-1999-07774 1
 
< 0.1%
3130000-101-2008-00247 1
 
< 0.1%
3130000-101-2018-00689 1
 
< 0.1%
3130000-101-2022-00170 1
 
< 0.1%
3130000-101-1982-07085 1
 
< 0.1%
3130000-101-1996-01854 1
 
< 0.1%
3130000-101-1997-01766 1
 
< 0.1%
3130000-101-2018-00327 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T08:34:51.975687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81328
37.0%
1 41122
18.7%
- 30000
 
13.6%
3 24289
 
11.0%
2 13086
 
5.9%
9 8767
 
4.0%
4 4510
 
2.1%
8 4296
 
2.0%
7 4258
 
1.9%
5 4241
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81328
42.8%
1 41122
21.6%
3 24289
 
12.8%
2 13086
 
6.9%
9 8767
 
4.6%
4 4510
 
2.4%
8 4296
 
2.3%
7 4258
 
2.2%
5 4241
 
2.2%
6 4103
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81328
37.0%
1 41122
18.7%
- 30000
 
13.6%
3 24289
 
11.0%
2 13086
 
5.9%
9 8767
 
4.0%
4 4510
 
2.1%
8 4296
 
2.0%
7 4258
 
1.9%
5 4241
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81328
37.0%
1 41122
18.7%
- 30000
 
13.6%
3 24289
 
11.0%
2 13086
 
5.9%
9 8767
 
4.0%
4 4510
 
2.1%
8 4296
 
2.0%
7 4258
 
1.9%
5 4241
 
1.9%
Distinct5716
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1968-04-26 00:00:00
Maximum2022-10-14 00:00:00
2024-05-11T08:34:52.426952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:34:52.960314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7382 
1
2618 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7382
73.8%
1 2618
 
26.2%

Length

2024-05-11T08:34:53.585309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:34:53.987460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7382
73.8%
1 2618
 
26.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7382 
영업/정상
2618 

Length

Max length5
Median length2
Mean length2.7854
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7382
73.8%
영업/정상 2618
 
26.2%

Length

2024-05-11T08:34:54.318916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:34:54.728465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7382
73.8%
영업/정상 2618
 
26.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7382 
1
2618 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7382
73.8%
1 2618
 
26.2%

Length

2024-05-11T08:34:55.381061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:34:55.904092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7382
73.8%
1 2618
 
26.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7382 
영업
2618 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7382
73.8%
영업 2618
 
26.2%

Length

2024-05-11T08:34:56.270063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:34:56.579786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7382
73.8%
영업 2618
 
26.2%

폐업일자
Text

MISSING 

Distinct4088
Distinct (%)55.4%
Missing2618
Missing (%)26.2%
Memory size156.2 KiB
2024-05-11T08:34:57.683201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1232728
Min length8

Characters and Unicode

Total characters59966
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2419 ?
Unique (%)32.8%

Sample

1st row20070803
2nd row20010201
3rd row19960123
4th row20210915
5th row2023-07-28
ValueCountFrequency (%)
20220208 129
 
1.7%
20190614 85
 
1.2%
20020820 74
 
1.0%
19961128 47
 
0.6%
2024-04-17 42
 
0.6%
20020604 39
 
0.5%
20130605 36
 
0.5%
20130718 32
 
0.4%
20130812 32
 
0.4%
20130726 27
 
0.4%
Other values (4078) 6839
92.6%
2024-05-11T08:34:58.918892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18541
30.9%
2 13551
22.6%
1 10655
17.8%
9 3684
 
6.1%
3 2713
 
4.5%
8 2247
 
3.7%
6 2082
 
3.5%
4 1978
 
3.3%
7 1912
 
3.2%
5 1692
 
2.8%
Other values (2) 911
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59055
98.5%
Dash Punctuation 910
 
1.5%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18541
31.4%
2 13551
22.9%
1 10655
18.0%
9 3684
 
6.2%
3 2713
 
4.6%
8 2247
 
3.8%
6 2082
 
3.5%
4 1978
 
3.3%
7 1912
 
3.2%
5 1692
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 910
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59966
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18541
30.9%
2 13551
22.6%
1 10655
17.8%
9 3684
 
6.1%
3 2713
 
4.5%
8 2247
 
3.7%
6 2082
 
3.5%
4 1978
 
3.3%
7 1912
 
3.2%
5 1692
 
2.8%
Other values (2) 911
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59966
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18541
30.9%
2 13551
22.6%
1 10655
17.8%
9 3684
 
6.1%
3 2713
 
4.5%
8 2247
 
3.7%
6 2082
 
3.5%
4 1978
 
3.3%
7 1912
 
3.2%
5 1692
 
2.8%
Other values (2) 911
 
1.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct4370
Distinct (%)87.7%
Missing5016
Missing (%)50.2%
Memory size156.2 KiB
2024-05-11T08:34:59.854769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.0623997
Min length2

Characters and Unicode

Total characters45167
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

Unique4291 ?
Unique (%)86.1%

Sample

1st row3354567
2nd row02
3rd row02 3338050
4th row02 714 4936
5th row02 7147709
ValueCountFrequency (%)
02 3625
41.2%
322 48
 
0.5%
0 36
 
0.4%
332 31
 
0.4%
337 31
 
0.4%
070 26
 
0.3%
325 26
 
0.3%
333 25
 
0.3%
338 25
 
0.3%
323 24
 
0.3%
Other values (4396) 4893
55.7%
2024-05-11T08:35:01.326146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7836
17.3%
0 7305
16.2%
3 6764
15.0%
4522
10.0%
7 3788
8.4%
1 3390
7.5%
4 2554
 
5.7%
6 2436
 
5.4%
5 2315
 
5.1%
8 2213
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40645
90.0%
Space Separator 4522
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7836
19.3%
0 7305
18.0%
3 6764
16.6%
7 3788
9.3%
1 3390
8.3%
4 2554
 
6.3%
6 2436
 
6.0%
5 2315
 
5.7%
8 2213
 
5.4%
9 2044
 
5.0%
Space Separator
ValueCountFrequency (%)
4522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 7836
17.3%
0 7305
16.2%
3 6764
15.0%
4522
10.0%
7 3788
8.4%
1 3390
7.5%
4 2554
 
5.7%
6 2436
 
5.4%
5 2315
 
5.1%
8 2213
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7836
17.3%
0 7305
16.2%
3 6764
15.0%
4522
10.0%
7 3788
8.4%
1 3390
7.5%
4 2554
 
5.7%
6 2436
 
5.4%
5 2315
 
5.1%
8 2213
 
4.9%

소재지면적
Text

MISSING 

Distinct5369
Distinct (%)54.5%
Missing142
Missing (%)1.4%
Memory size156.2 KiB
2024-05-11T08:35:02.573441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1553053
Min length4

Characters and Unicode

Total characters50821
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3661 ?
Unique (%)37.1%

Sample

1st row29.00
2nd row52.72
3rd row16.10
4th row33.33
5th row20.00
ValueCountFrequency (%)
33.00 117
 
1.2%
30.00 79
 
0.8%
50.00 64
 
0.6%
40.00 63
 
0.6%
26.00 48
 
0.5%
20.00 48
 
0.5%
26.40 43
 
0.4%
60.00 43
 
0.4%
27.00 41
 
0.4%
66.00 39
 
0.4%
Other values (5359) 9273
94.1%
2024-05-11T08:35:04.594160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9858
19.4%
0 7534
14.8%
2 4755
9.4%
1 4364
8.6%
3 3872
 
7.6%
4 3842
 
7.6%
6 3730
 
7.3%
5 3624
 
7.1%
8 3180
 
6.3%
9 3096
 
6.1%
Other values (2) 2966
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40948
80.6%
Other Punctuation 9873
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7534
18.4%
2 4755
11.6%
1 4364
10.7%
3 3872
9.5%
4 3842
9.4%
6 3730
9.1%
5 3624
8.9%
8 3180
7.8%
9 3096
7.6%
7 2951
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 9858
99.8%
, 15
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 50821
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9858
19.4%
0 7534
14.8%
2 4755
9.4%
1 4364
8.6%
3 3872
 
7.6%
4 3842
 
7.6%
6 3730
 
7.3%
5 3624
 
7.1%
8 3180
 
6.3%
9 3096
 
6.1%
Other values (2) 2966
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9858
19.4%
0 7534
14.8%
2 4755
9.4%
1 4364
8.6%
3 3872
 
7.6%
4 3842
 
7.6%
6 3730
 
7.3%
5 3624
 
7.1%
8 3180
 
6.3%
9 3096
 
6.1%
Other values (2) 2966
 
5.8%
Distinct267
Distinct (%)2.7%
Missing19
Missing (%)0.2%
Memory size156.2 KiB
2024-05-11T08:35:06.086430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1012925
Min length6

Characters and Unicode

Total characters60897
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

Unique27 ?
Unique (%)0.3%

Sample

1st row121885
2nd row121830
3rd row121893
4th row121892
5th row121838
ValueCountFrequency (%)
121837 435
 
4.4%
121895 313
 
3.1%
121836 283
 
2.8%
121838 273
 
2.7%
121893 250
 
2.5%
121812 238
 
2.4%
121865 232
 
2.3%
121807 211
 
2.1%
121829 208
 
2.1%
121830 179
 
1.8%
Other values (257) 7359
73.7%
2024-05-11T08:35:08.183848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21928
36.0%
2 11816
19.4%
8 11070
18.2%
0 2659
 
4.4%
3 2564
 
4.2%
9 2339
 
3.8%
5 2222
 
3.6%
7 2089
 
3.4%
6 1797
 
3.0%
4 1402
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59886
98.3%
Dash Punctuation 1011
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21928
36.6%
2 11816
19.7%
8 11070
18.5%
0 2659
 
4.4%
3 2564
 
4.3%
9 2339
 
3.9%
5 2222
 
3.7%
7 2089
 
3.5%
6 1797
 
3.0%
4 1402
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1011
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60897
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21928
36.0%
2 11816
19.4%
8 11070
18.2%
0 2659
 
4.4%
3 2564
 
4.2%
9 2339
 
3.8%
5 2222
 
3.6%
7 2089
 
3.4%
6 1797
 
3.0%
4 1402
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21928
36.0%
2 11816
19.4%
8 11070
18.2%
0 2659
 
4.4%
3 2564
 
4.2%
9 2339
 
3.8%
5 2222
 
3.6%
7 2089
 
3.4%
6 1797
 
3.0%
4 1402
 
2.3%
Distinct8407
Distinct (%)84.2%
Missing19
Missing (%)0.2%
Memory size156.2 KiB
2024-05-11T08:35:08.879751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length56
Mean length24.712754
Min length16

Characters and Unicode

Total characters246658
Distinct characters458
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7349 ?
Unique (%)73.6%

Sample

1st row서울특별시 마포구 합정동 383-14번지 1층
2nd row서울특별시 마포구 상암동 34-9번지 1층
3rd row서울특별시 마포구 서교동 365-17번지
4th row서울특별시 마포구 창전동 442 서강한화오벨리스크
5th row서울특별시 마포구 서교동 358-42
ValueCountFrequency (%)
서울특별시 9981
21.5%
마포구 9980
21.4%
서교동 2348
 
5.0%
1층 1599
 
3.4%
망원동 765
 
1.6%
동교동 669
 
1.4%
상암동 648
 
1.4%
합정동 629
 
1.4%
도화동 628
 
1.3%
연남동 618
 
1.3%
Other values (7464) 18663
40.1%
2024-05-11T08:35:09.982669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44680
18.1%
12431
 
5.0%
1 11429
 
4.6%
11122
 
4.5%
10198
 
4.1%
10186
 
4.1%
10082
 
4.1%
10058
 
4.1%
9994
 
4.1%
9984
 
4.0%
Other values (448) 106494
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140909
57.1%
Decimal Number 50036
 
20.3%
Space Separator 44680
 
18.1%
Dash Punctuation 9011
 
3.7%
Uppercase Letter 996
 
0.4%
Other Punctuation 367
 
0.1%
Lowercase Letter 218
 
0.1%
Open Punctuation 204
 
0.1%
Close Punctuation 202
 
0.1%
Math Symbol 24
 
< 0.1%
Other values (3) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12431
 
8.8%
11122
 
7.9%
10198
 
7.2%
10186
 
7.2%
10082
 
7.2%
10058
 
7.1%
9994
 
7.1%
9984
 
7.1%
9981
 
7.1%
8311
 
5.9%
Other values (376) 38562
27.4%
Uppercase Letter
ValueCountFrequency (%)
B 216
21.7%
C 111
11.1%
M 85
 
8.5%
D 85
 
8.5%
T 69
 
6.9%
F 57
 
5.7%
I 52
 
5.2%
K 47
 
4.7%
S 39
 
3.9%
G 37
 
3.7%
Other values (14) 198
19.9%
Lowercase Letter
ValueCountFrequency (%)
e 27
12.4%
i 26
11.9%
y 22
10.1%
t 22
10.1%
o 20
9.2%
r 16
7.3%
w 14
 
6.4%
a 12
 
5.5%
n 11
 
5.0%
s 9
 
4.1%
Other values (11) 39
17.9%
Decimal Number
ValueCountFrequency (%)
1 11429
22.8%
3 7043
14.1%
2 6230
12.5%
4 5469
10.9%
5 4313
 
8.6%
6 3683
 
7.4%
0 3583
 
7.2%
8 2900
 
5.8%
7 2857
 
5.7%
9 2529
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 287
78.2%
. 49
 
13.4%
@ 17
 
4.6%
& 6
 
1.6%
/ 5
 
1.4%
? 2
 
0.5%
' 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 23
95.8%
+ 1
 
4.2%
Letter Number
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
44680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9011
100.0%
Open Punctuation
ValueCountFrequency (%)
( 204
100.0%
Close Punctuation
ValueCountFrequency (%)
) 202
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140905
57.1%
Common 104527
42.4%
Latin 1222
 
0.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12431
 
8.8%
11122
 
7.9%
10198
 
7.2%
10186
 
7.2%
10082
 
7.2%
10058
 
7.1%
9994
 
7.1%
9984
 
7.1%
9981
 
7.1%
8311
 
5.9%
Other values (372) 38558
27.4%
Latin
ValueCountFrequency (%)
B 216
17.7%
C 111
 
9.1%
M 85
 
7.0%
D 85
 
7.0%
T 69
 
5.6%
F 57
 
4.7%
I 52
 
4.3%
K 47
 
3.8%
S 39
 
3.2%
G 37
 
3.0%
Other values (37) 424
34.7%
Common
ValueCountFrequency (%)
44680
42.7%
1 11429
 
10.9%
- 9011
 
8.6%
3 7043
 
6.7%
2 6230
 
6.0%
4 5469
 
5.2%
5 4313
 
4.1%
6 3683
 
3.5%
0 3583
 
3.4%
8 2900
 
2.8%
Other values (15) 6186
 
5.9%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140905
57.1%
ASCII 105739
42.9%
Number Forms 8
 
< 0.1%
CJK 4
 
< 0.1%
CJK Compat 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44680
42.3%
1 11429
 
10.8%
- 9011
 
8.5%
3 7043
 
6.7%
2 6230
 
5.9%
4 5469
 
5.2%
5 4313
 
4.1%
6 3683
 
3.5%
0 3583
 
3.4%
8 2900
 
2.7%
Other values (59) 7398
 
7.0%
Hangul
ValueCountFrequency (%)
12431
 
8.8%
11122
 
7.9%
10198
 
7.2%
10186
 
7.2%
10082
 
7.2%
10058
 
7.1%
9994
 
7.1%
9984
 
7.1%
9981
 
7.1%
8311
 
5.9%
Other values (372) 38558
27.4%
Number Forms
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
CJK Compat
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

도로명주소
Text

MISSING 

Distinct5847
Distinct (%)96.1%
Missing3914
Missing (%)39.1%
Memory size156.2 KiB
2024-05-11T08:35:10.681550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length63
Mean length32.27933
Min length21

Characters and Unicode

Total characters196452
Distinct characters460
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5635 ?
Unique (%)92.6%

Sample

1st row서울특별시 마포구 월드컵북로44길 35-6, 1층 (상암동)
2nd row서울특별시 마포구 창전로 45, 103동 1층 107호 (창전동, 서강한화오벨리스크)
3rd row서울특별시 마포구 와우산로21길 28-12, 지1층 (서교동)
4th row서울특별시 마포구 토정로 275 (용강동,1.2층)
5th row서울특별시 마포구 마포대로11길 92, 1층 우측호 (염리동)
ValueCountFrequency (%)
서울특별시 6086
 
15.7%
마포구 6085
 
15.7%
1층 2184
 
5.6%
서교동 1415
 
3.6%
2층 587
 
1.5%
상암동 491
 
1.3%
연남동 484
 
1.2%
동교동 419
 
1.1%
망원동 418
 
1.1%
지하1층 356
 
0.9%
Other values (3125) 20262
52.2%
2024-05-11T08:35:11.825711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32725
 
16.7%
1 10471
 
5.3%
7868
 
4.0%
7374
 
3.8%
6847
 
3.5%
6725
 
3.4%
, 6613
 
3.4%
6361
 
3.2%
6177
 
3.1%
( 6176
 
3.1%
Other values (450) 99115
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111904
57.0%
Space Separator 32725
 
16.7%
Decimal Number 30256
 
15.4%
Other Punctuation 6646
 
3.4%
Open Punctuation 6176
 
3.1%
Close Punctuation 6176
 
3.1%
Dash Punctuation 1250
 
0.6%
Uppercase Letter 1051
 
0.5%
Lowercase Letter 195
 
0.1%
Math Symbol 65
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7868
 
7.0%
7374
 
6.6%
6847
 
6.1%
6725
 
6.0%
6361
 
5.7%
6177
 
5.5%
6117
 
5.5%
6088
 
5.4%
6087
 
5.4%
5868
 
5.2%
Other values (379) 46392
41.5%
Uppercase Letter
ValueCountFrequency (%)
B 351
33.4%
C 106
 
10.1%
M 74
 
7.0%
D 72
 
6.9%
T 63
 
6.0%
I 48
 
4.6%
K 47
 
4.5%
A 41
 
3.9%
S 35
 
3.3%
G 33
 
3.1%
Other values (15) 181
17.2%
Lowercase Letter
ValueCountFrequency (%)
e 25
12.8%
i 24
12.3%
y 22
11.3%
t 20
10.3%
o 16
8.2%
r 14
7.2%
a 11
 
5.6%
w 11
 
5.6%
h 10
 
5.1%
s 9
 
4.6%
Other values (11) 33
16.9%
Decimal Number
ValueCountFrequency (%)
1 10471
34.6%
2 4801
15.9%
3 2879
 
9.5%
0 2199
 
7.3%
4 2136
 
7.1%
5 1872
 
6.2%
6 1661
 
5.5%
9 1544
 
5.1%
7 1411
 
4.7%
8 1282
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 6613
99.5%
. 12
 
0.2%
& 7
 
0.1%
@ 7
 
0.1%
/ 3
 
< 0.1%
? 3
 
< 0.1%
' 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 64
98.5%
+ 1
 
1.5%
Letter Number
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
32725
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111900
57.0%
Common 83294
42.4%
Latin 1254
 
0.6%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7868
 
7.0%
7374
 
6.6%
6847
 
6.1%
6725
 
6.0%
6361
 
5.7%
6177
 
5.5%
6117
 
5.5%
6088
 
5.4%
6087
 
5.4%
5868
 
5.2%
Other values (375) 46388
41.5%
Latin
ValueCountFrequency (%)
B 351
28.0%
C 106
 
8.5%
M 74
 
5.9%
D 72
 
5.7%
T 63
 
5.0%
I 48
 
3.8%
K 47
 
3.7%
A 41
 
3.3%
S 35
 
2.8%
G 33
 
2.6%
Other values (38) 384
30.6%
Common
ValueCountFrequency (%)
32725
39.3%
1 10471
 
12.6%
, 6613
 
7.9%
( 6176
 
7.4%
) 6176
 
7.4%
2 4801
 
5.8%
3 2879
 
3.5%
0 2199
 
2.6%
4 2136
 
2.6%
5 1872
 
2.2%
Other values (13) 7246
 
8.7%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111900
57.0%
ASCII 84540
43.0%
Number Forms 8
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32725
38.7%
1 10471
 
12.4%
, 6613
 
7.8%
( 6176
 
7.3%
) 6176
 
7.3%
2 4801
 
5.7%
3 2879
 
3.4%
0 2199
 
2.6%
4 2136
 
2.5%
5 1872
 
2.2%
Other values (59) 8492
 
10.0%
Hangul
ValueCountFrequency (%)
7868
 
7.0%
7374
 
6.6%
6847
 
6.1%
6725
 
6.0%
6361
 
5.7%
6177
 
5.5%
6117
 
5.5%
6088
 
5.4%
6087
 
5.4%
5868
 
5.2%
Other values (375) 46388
41.5%
Number Forms
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct277
Distinct (%)4.6%
Missing3975
Missing (%)39.8%
Infinite0
Infinite (%)0.0%
Mean4043.7711
Minimum3705
Maximum4214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:12.290626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3705
5-th percentile3925
Q13990
median4047
Q34074
95-th percentile4173
Maximum4214
Range509
Interquartile range (IQR)84

Descriptive statistics

Standard deviation73.636395
Coefficient of variation (CV)0.018209832
Kurtosis-0.2710637
Mean4043.7711
Median Absolute Deviation (MAD)49
Skewness0.37082307
Sum24363721
Variance5422.3186
MonotonicityNot monotonic
2024-05-11T08:35:12.707673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4049 284
 
2.8%
3982 217
 
2.2%
4053 172
 
1.7%
4047 148
 
1.5%
4048 146
 
1.5%
3925 133
 
1.3%
4055 116
 
1.2%
3927 112
 
1.1%
3930 100
 
1.0%
4039 99
 
1.0%
Other values (267) 4498
45.0%
(Missing) 3975
39.8%
ValueCountFrequency (%)
3705 1
 
< 0.1%
3900 1
 
< 0.1%
3901 11
0.1%
3902 2
 
< 0.1%
3905 13
0.1%
3907 10
0.1%
3908 16
0.2%
3909 6
 
0.1%
3911 2
 
< 0.1%
3912 2
 
< 0.1%
ValueCountFrequency (%)
4214 26
0.3%
4213 4
 
< 0.1%
4212 9
 
0.1%
4211 51
0.5%
4210 18
 
0.2%
4209 18
 
0.2%
4208 11
 
0.1%
4207 21
0.2%
4206 12
 
0.1%
4205 7
 
0.1%
Distinct9126
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:35:13.287859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length5.7812
Min length1

Characters and Unicode

Total characters57812
Distinct characters1176
Distinct categories14 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8528 ?
Unique (%)85.3%

Sample

1st row피자팸
2nd row도담
3rd row다정활어센타
4th row열정국밥
5th row청춘부추소곱창
ValueCountFrequency (%)
홍대점 91
 
0.8%
마포점 40
 
0.3%
카페 38
 
0.3%
상암점 30
 
0.3%
공덕점 26
 
0.2%
연남점 23
 
0.2%
합정점 21
 
0.2%
망원점 20
 
0.2%
전주식당 20
 
0.2%
coffee 19
 
0.2%
Other values (9966) 11553
97.2%
2024-05-11T08:35:14.358732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1889
 
3.3%
1327
 
2.3%
1131
 
2.0%
968
 
1.7%
) 933
 
1.6%
( 932
 
1.6%
852
 
1.5%
848
 
1.5%
737
 
1.3%
646
 
1.1%
Other values (1166) 47549
82.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47409
82.0%
Lowercase Letter 2993
 
5.2%
Uppercase Letter 2744
 
4.7%
Space Separator 1889
 
3.3%
Close Punctuation 935
 
1.6%
Open Punctuation 934
 
1.6%
Decimal Number 682
 
1.2%
Other Punctuation 191
 
0.3%
Dash Punctuation 27
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other values (4) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1327
 
2.8%
1131
 
2.4%
968
 
2.0%
852
 
1.8%
848
 
1.8%
737
 
1.6%
646
 
1.4%
634
 
1.3%
520
 
1.1%
477
 
1.0%
Other values (1081) 39269
82.8%
Lowercase Letter
ValueCountFrequency (%)
e 407
13.6%
a 308
 
10.3%
o 289
 
9.7%
n 208
 
6.9%
r 198
 
6.6%
i 196
 
6.5%
l 149
 
5.0%
t 148
 
4.9%
s 139
 
4.6%
u 127
 
4.2%
Other values (16) 824
27.5%
Uppercase Letter
ValueCountFrequency (%)
A 230
 
8.4%
E 215
 
7.8%
O 196
 
7.1%
C 182
 
6.6%
B 157
 
5.7%
T 152
 
5.5%
S 141
 
5.1%
N 140
 
5.1%
R 140
 
5.1%
M 138
 
5.0%
Other values (16) 1053
38.4%
Other Punctuation
ValueCountFrequency (%)
& 58
30.4%
. 47
24.6%
, 28
14.7%
? 19
 
9.9%
' 19
 
9.9%
: 8
 
4.2%
! 6
 
3.1%
# 2
 
1.0%
/ 2
 
1.0%
% 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 150
22.0%
1 140
20.5%
0 77
11.3%
4 61
8.9%
3 51
 
7.5%
5 47
 
6.9%
7 46
 
6.7%
9 41
 
6.0%
8 36
 
5.3%
6 33
 
4.8%
Close Punctuation
ValueCountFrequency (%)
) 933
99.8%
] 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 932
99.8%
[ 2
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
` 1
50.0%
˚ 1
50.0%
Space Separator
ValueCountFrequency (%)
1889
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
× 2
100.0%
Modifier Letter
ValueCountFrequency (%)
ː 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47359
81.9%
Latin 5738
 
9.9%
Common 4665
 
8.1%
Han 47
 
0.1%
Hiragana 2
 
< 0.1%
Katakana 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1327
 
2.8%
1131
 
2.4%
968
 
2.0%
852
 
1.8%
848
 
1.8%
737
 
1.6%
646
 
1.4%
634
 
1.3%
520
 
1.1%
477
 
1.0%
Other values (1042) 39219
82.8%
Latin
ValueCountFrequency (%)
e 407
 
7.1%
a 308
 
5.4%
o 289
 
5.0%
A 230
 
4.0%
E 215
 
3.7%
n 208
 
3.6%
r 198
 
3.5%
i 196
 
3.4%
O 196
 
3.4%
C 182
 
3.2%
Other values (43) 3309
57.7%
Han
ValueCountFrequency (%)
5
 
10.6%
5
 
10.6%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
1
 
2.1%
1
 
2.1%
1
 
2.1%
Other values (26) 26
55.3%
Common
ValueCountFrequency (%)
1889
40.5%
) 933
20.0%
( 932
20.0%
2 150
 
3.2%
1 140
 
3.0%
0 77
 
1.7%
4 61
 
1.3%
& 58
 
1.2%
3 51
 
1.1%
. 47
 
1.0%
Other values (22) 327
 
7.0%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Katakana
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47353
81.9%
ASCII 10397
 
18.0%
CJK 46
 
0.1%
Compat Jamo 6
 
< 0.1%
None 3
 
< 0.1%
Modifier Letters 2
 
< 0.1%
Hiragana 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Katakana 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1889
 
18.2%
) 933
 
9.0%
( 932
 
9.0%
e 407
 
3.9%
a 308
 
3.0%
o 289
 
2.8%
A 230
 
2.2%
E 215
 
2.1%
n 208
 
2.0%
r 198
 
1.9%
Other values (70) 4788
46.1%
Hangul
ValueCountFrequency (%)
1327
 
2.8%
1131
 
2.4%
968
 
2.0%
852
 
1.8%
848
 
1.8%
737
 
1.6%
646
 
1.4%
634
 
1.3%
520
 
1.1%
477
 
1.0%
Other values (1039) 39213
82.8%
CJK
ValueCountFrequency (%)
5
 
10.9%
5
 
10.9%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
1
 
2.2%
Other values (25) 25
54.3%
Compat Jamo
ValueCountFrequency (%)
4
66.7%
1
 
16.7%
1
 
16.7%
None
ValueCountFrequency (%)
× 2
66.7%
1
33.3%
Modifier Letters
ValueCountFrequency (%)
ː 1
50.0%
˚ 1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
100.0%
Hiragana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct8153
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-26 00:00:00
Maximum2024-05-08 13:29:41
2024-05-11T08:35:14.779716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:35:15.302858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
6245 
U
3755 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6245
62.5%
U 3755
37.5%

Length

2024-05-11T08:35:15.905042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:16.238303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6245
62.5%
u 3755
37.5%
Distinct1450
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:35:16.615355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:35:17.417926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3496 
기타
1558 
분식
1238 
호프/통닭
973 
경양식
815 
Other values (19)
1920 

Length

Max length15
Median length2
Mean length2.6293
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row패스트푸드
2nd row한식
3rd row일식
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
한식 3496
35.0%
기타 1558
15.6%
분식 1238
 
12.4%
호프/통닭 973
 
9.7%
경양식 815
 
8.2%
까페 765
 
7.6%
일식 477
 
4.8%
중국식 261
 
2.6%
통닭(치킨) 108
 
1.1%
외국음식전문점(인도,태국등) 78
 
0.8%
Other values (14) 231
 
2.3%

Length

2024-05-11T08:35:17.969326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3496
35.0%
기타 1558
15.6%
분식 1238
 
12.4%
호프/통닭 973
 
9.7%
경양식 815
 
8.2%
까페 765
 
7.6%
일식 477
 
4.8%
중국식 261
 
2.6%
통닭(치킨 108
 
1.1%
외국음식전문점(인도,태국등 78
 
0.8%
Other values (14) 231
 
2.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4652
Distinct (%)49.1%
Missing530
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean193295.76
Minimum189192.41
Maximum196723.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:18.504638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189192.41
5-th percentile190681.55
Q1192366.79
median193142.9
Q3194436.09
95-th percentile195849.73
Maximum196723.03
Range7530.6211
Interquartile range (IQR)2069.3013

Descriptive statistics

Standard deviation1514.838
Coefficient of variation (CV)0.0078368921
Kurtosis-0.49923104
Mean193295.76
Median Absolute Deviation (MAD)994.49415
Skewness0.042879266
Sum1.8305108 × 109
Variance2294734.2
MonotonicityNot monotonic
2024-05-11T08:35:19.033916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190250.875091908 76
 
0.8%
193187.802952358 56
 
0.6%
190125.564768858 50
 
0.5%
193166.430144679 40
 
0.4%
195324.793653981 35
 
0.4%
192311.642580307 34
 
0.3%
190086.625449279 33
 
0.3%
195277.885388974 32
 
0.3%
195184.335899857 32
 
0.3%
189857.566447564 26
 
0.3%
Other values (4642) 9056
90.6%
(Missing) 530
 
5.3%
ValueCountFrequency (%)
189192.411433557 2
 
< 0.1%
189212.737535822 1
 
< 0.1%
189282.58640148 1
 
< 0.1%
189286.651086068 1
 
< 0.1%
189315.370584751 6
0.1%
189392.975995366 8
0.1%
189520.410979113 3
 
< 0.1%
189520.465145926 1
 
< 0.1%
189592.30107511 3
 
< 0.1%
189640.477184701 1
 
< 0.1%
ValueCountFrequency (%)
196723.032487763 1
< 0.1%
196721.001826384 1
< 0.1%
196719.262874995 1
< 0.1%
196717.946323293 1
< 0.1%
196713.991377586 2
< 0.1%
196697.874709656 1
< 0.1%
196697.275054441 1
< 0.1%
196693.578355085 1
< 0.1%
196691.898084567 1
< 0.1%
196686.57570924 2
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4652
Distinct (%)49.1%
Missing530
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean450232.12
Minimum448116.64
Maximum453685.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:19.663529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448116.64
5-th percentile448753.04
Q1449592.69
median450164.51
Q3450581.78
95-th percentile452758.64
Maximum453685.55
Range5568.9059
Interquartile range (IQR)989.0917

Descriptive statistics

Standard deviation1016.8629
Coefficient of variation (CV)0.0022585302
Kurtosis1.3514735
Mean450232.12
Median Absolute Deviation (MAD)524.23039
Skewness1.0193344
Sum4.2636982 × 109
Variance1034010.1
MonotonicityNot monotonic
2024-05-11T08:35:20.141282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453017.867202928 76
 
0.8%
450172.178899424 56
 
0.6%
453090.149821248 50
 
0.5%
450425.852790862 40
 
0.4%
448885.430093289 35
 
0.4%
449855.643910445 34
 
0.3%
453231.427685063 33
 
0.3%
448919.647035291 32
 
0.3%
448780.26877488 32
 
0.3%
453271.198852486 26
 
0.3%
Other values (4642) 9056
90.6%
(Missing) 530
 
5.3%
ValueCountFrequency (%)
448116.639953919 2
 
< 0.1%
448161.548233627 1
 
< 0.1%
448209.438670234 1
 
< 0.1%
448220.880197432 1
 
< 0.1%
448229.063825491 6
0.1%
448236.655548283 6
0.1%
448238.164063251 1
 
< 0.1%
448276.965250949 2
 
< 0.1%
448294.181304771 1
 
< 0.1%
448306.174934976 1
 
< 0.1%
ValueCountFrequency (%)
453685.545865753 3
 
< 0.1%
453685.460423342 1
 
< 0.1%
453647.349314742 6
 
0.1%
453614.583448105 5
 
0.1%
453577.133041615 1
 
< 0.1%
453468.379147545 1
 
< 0.1%
453407.67377 1
 
< 0.1%
453360.240306636 1
 
< 0.1%
453345.947683972 3
 
< 0.1%
453302.04990022 20
0.2%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3061 
<NA>
1621 
분식
1167 
기타
947 
호프/통닭
855 
Other values (20)
2349 

Length

Max length15
Median length2
Mean length2.8483
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row패스트푸드
2nd row한식
3rd row일식
4th row<NA>
5th row기타

Common Values

ValueCountFrequency (%)
한식 3061
30.6%
<NA> 1621
16.2%
분식 1167
 
11.7%
기타 947
 
9.5%
호프/통닭 855
 
8.6%
까페 707
 
7.1%
경양식 691
 
6.9%
일식 395
 
4.0%
중국식 214
 
2.1%
통닭(치킨) 102
 
1.0%
Other values (15) 240
 
2.4%

Length

2024-05-11T08:35:20.724848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3061
30.6%
na 1621
16.2%
분식 1167
 
11.7%
기타 947
 
9.5%
호프/통닭 855
 
8.6%
까페 707
 
7.1%
경양식 691
 
6.9%
일식 395
 
4.0%
중국식 214
 
2.1%
통닭(치킨 102
 
1.0%
Other values (15) 240
 
2.4%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.4%
Missing5682
Missing (%)56.8%
Infinite0
Infinite (%)0.0%
Mean0.49559981
Minimum0
Maximum20
Zeros2921
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:21.203055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0213628
Coefficient of variation (CV)2.0608619
Kurtosis72.332489
Mean0.49559981
Median Absolute Deviation (MAD)0
Skewness5.9329524
Sum2140
Variance1.0431819
MonotonicityNot monotonic
2024-05-11T08:35:21.727379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 2921
29.2%
1 971
 
9.7%
2 279
 
2.8%
3 86
 
0.9%
4 31
 
0.3%
5 13
 
0.1%
7 5
 
0.1%
6 4
 
< 0.1%
9 1
 
< 0.1%
15 1
 
< 0.1%
Other values (6) 6
 
0.1%
(Missing) 5682
56.8%
ValueCountFrequency (%)
0 2921
29.2%
1 971
 
9.7%
2 279
 
2.8%
3 86
 
0.9%
4 31
 
0.3%
5 13
 
0.1%
6 4
 
< 0.1%
7 5
 
0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
17 1
 
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
7 5
0.1%
6 4
< 0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.3%
Missing5437
Missing (%)54.4%
Infinite0
Infinite (%)0.0%
Mean0.82248521
Minimum0
Maximum18
Zeros2310
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:22.149493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1953267
Coefficient of variation (CV)1.4533109
Kurtosis29.182473
Mean0.82248521
Median Absolute Deviation (MAD)0
Skewness3.6100201
Sum3753
Variance1.428806
MonotonicityNot monotonic
2024-05-11T08:35:22.610584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 2310
23.1%
1 1318
 
13.2%
2 656
 
6.6%
3 167
 
1.7%
4 53
 
0.5%
5 28
 
0.3%
7 7
 
0.1%
6 6
 
0.1%
10 6
 
0.1%
8 5
 
0.1%
Other values (3) 7
 
0.1%
(Missing) 5437
54.4%
ValueCountFrequency (%)
0 2310
23.1%
1 1318
13.2%
2 656
 
6.6%
3 167
 
1.7%
4 53
 
0.5%
5 28
 
0.3%
6 6
 
0.1%
7 7
 
0.1%
8 5
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
18 2
 
< 0.1%
11 2
 
< 0.1%
10 6
 
0.1%
9 3
 
< 0.1%
8 5
 
0.1%
7 7
 
0.1%
6 6
 
0.1%
5 28
 
0.3%
4 53
 
0.5%
3 167
1.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6347 
기타
1715 
주택가주변
1605 
유흥업소밀집지역
 
211
아파트지역
 
53
Other values (3)
 
69

Length

Max length8
Median length4
Mean length3.9331
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6347
63.5%
기타 1715
 
17.2%
주택가주변 1605
 
16.1%
유흥업소밀집지역 211
 
2.1%
아파트지역 53
 
0.5%
학교정화(상대) 30
 
0.3%
학교정화(절대) 22
 
0.2%
결혼예식장주변 17
 
0.2%

Length

2024-05-11T08:35:23.189637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:23.566585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6347
63.5%
기타 1715
 
17.2%
주택가주변 1605
 
16.1%
유흥업소밀집지역 211
 
2.1%
아파트지역 53
 
0.5%
학교정화(상대 30
 
0.3%
학교정화(절대 22
 
0.2%
결혼예식장주변 17
 
0.2%

등급구분명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6577 
기타
1793 
자율
1075 
지도
 
303
 
226
Other values (2)
 
26

Length

Max length4
Median length4
Mean length3.2911
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6577
65.8%
기타 1793
 
17.9%
자율 1075
 
10.8%
지도 303
 
3.0%
226
 
2.3%
17
 
0.2%
우수 9
 
0.1%

Length

2024-05-11T08:35:24.327400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:24.810983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6577
65.8%
기타 1793
 
17.9%
자율 1075
 
10.8%
지도 303
 
3.0%
226
 
2.3%
17
 
0.2%
우수 9
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5868 
상수도전용
4117 
상수도(음용)지하수(주방용)겸용
 
14
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.43
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5868
58.7%
상수도전용 4117
41.2%
상수도(음용)지하수(주방용)겸용 14
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T08:35:25.332944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:25.783616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5868
58.7%
상수도전용 4117
41.2%
상수도(음용)지하수(주방용)겸용 14
 
0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:26.259578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:26.639256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:27.072878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:27.599832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:28.342973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:28.908231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:29.460216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:29.877476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:30.517401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:31.108590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:31.694427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:32.182303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9490 
0
 
510

Length

Max length4
Median length4
Mean length3.847
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> 9490
94.9%
0 510
 
5.1%

Length

2024-05-11T08:35:32.574687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:35:33.027949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9490
94.9%
0 510
 
5.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1621
Missing (%)16.2%
Memory size97.7 KiB
False
8246 
True
 
133
(Missing)
1621 
ValueCountFrequency (%)
False 8246
82.5%
True 133
 
1.3%
(Missing) 1621
 
16.2%
2024-05-11T08:35:33.338568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct4732
Distinct (%)56.5%
Missing1621
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean69.523292
Minimum0
Maximum2973.17
Zeros138
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:35:33.760157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.5
Q127.525
median47
Q380.115
95-th percentile190.876
Maximum2973.17
Range2973.17
Interquartile range (IQR)52.59

Descriptive statistics

Standard deviation95.01949
Coefficient of variation (CV)1.3667289
Kurtosis170.51375
Mean69.523292
Median Absolute Deviation (MAD)22.3
Skewness9.4214915
Sum582535.66
Variance9028.7035
MonotonicityNot monotonic
2024-05-11T08:35:34.253996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 138
 
1.4%
33.0 92
 
0.9%
30.0 67
 
0.7%
40.0 54
 
0.5%
50.0 49
 
0.5%
26.0 42
 
0.4%
26.4 38
 
0.4%
27.0 37
 
0.4%
20.0 34
 
0.3%
21.0 34
 
0.3%
Other values (4722) 7794
77.9%
(Missing) 1621
 
16.2%
ValueCountFrequency (%)
0.0 138
1.4%
1.0 12
 
0.1%
3.52 1
 
< 0.1%
4.0 1
 
< 0.1%
4.15 1
 
< 0.1%
4.2 1
 
< 0.1%
4.5 1
 
< 0.1%
4.93 1
 
< 0.1%
4.95 1
 
< 0.1%
4.96 1
 
< 0.1%
ValueCountFrequency (%)
2973.17 1
< 0.1%
1704.0 1
< 0.1%
1690.3 1
< 0.1%
1520.39 1
< 0.1%
1510.77 1
< 0.1%
1489.53 1
< 0.1%
1414.72 1
< 0.1%
1237.94 1
< 0.1%
1134.0 1
< 0.1%
1107.44 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
967731300003130000-101-2004-0044420040813<NA>3폐업2폐업20070803<NA><NA><NA>335456729.00121885서울특별시 마포구 합정동 383-14번지 1층<NA><NA>피자팸2005-08-30 00:00:00I2018-08-31 23:59:59.0패스트푸드192175.869468449657.793069패스트푸드01<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.0<NA><NA><NA>
1775431300003130000-101-2015-0043620150604<NA>1영업/정상1영업<NA><NA><NA><NA><NA>52.72121830서울특별시 마포구 상암동 34-9번지 1층서울특별시 마포구 월드컵북로44길 35-6, 1층 (상암동)3930도담2017-09-28 10:36:09I2018-08-31 23:59:59.0한식190668.065746452657.378304한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N52.72<NA><NA><NA>
540731300003130000-101-1998-0354219980416<NA>3폐업2폐업20010201<NA><NA><NA>0216.10121893서울특별시 마포구 서교동 365-17번지<NA><NA>다정활어센타2001-02-01 00:00:00I2018-08-31 23:59:59.0일식193008.271033450061.494176일식<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.1<NA><NA><NA>
2355731300003130000-101-2020-0085120201019<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.33121892서울특별시 마포구 창전동 442 서강한화오벨리스크서울특별시 마포구 창전로 45, 103동 1층 107호 (창전동, 서강한화오벨리스크)4086열정국밥2022-10-31 13:05:45U2021-11-01 00:02:00.0기타193905.437192449372.4965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2343331300003130000-101-2020-0072720200907<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.00121838서울특별시 마포구 서교동 358-42서울특별시 마포구 와우산로21길 28-12, 지1층 (서교동)4040청춘부추소곱창2020-09-07 09:51:40I2020-09-09 00:23:12.0기타193079.134083450062.228834기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N20.0<NA><NA><NA>
161631300003130000-101-1992-0346619920625<NA>3폐업2폐업19960123<NA><NA><NA>02 333805059.50121840서울특별시 마포구 서교동 395-17번지<NA><NA>가미2001-10-04 00:00:00I2018-08-31 23:59:59.0일식192878.727777449832.766257일식00주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N59.5<NA><NA><NA>
1073531300003130000-101-2006-0019220060427<NA>3폐업2폐업20210915<NA><NA><NA>02 714 4936160.00121875서울특별시 마포구 용강동 115-24 1.2층서울특별시 마포구 토정로 275 (용강동,1.2층)4159왕경(旺京)2021-09-15 17:36:34U2021-09-17 02:40:00.0한식194677.846483448887.563517한식00<NA><NA><NA>00000<NA>00N160.0<NA><NA><NA>
2490231300003130000-101-2022-000482022-01-21<NA>3폐업2폐업2023-07-28<NA><NA><NA>02 714770938.23121-871서울특별시 마포구 염리동 27-110서울특별시 마포구 마포대로11길 92, 1층 우측호 (염리동)4134집밥한끼2023-07-31 13:27:24U2022-12-08 00:02:00.0일식195449.061227449628.805089<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1510731300003130000-101-2012-0042620120723<NA>3폐업2폐업20171130<NA><NA><NA>02 323090820.70121821서울특별시 마포구 망원동 395-17번지서울특별시 마포구 포은로 71, 1층 (망원동)4017보물섬2017-11-30 12:41:12I2018-08-31 23:59:59.0분식191617.307102450139.870775분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N20.7<NA><NA><NA>
1187231300003130000-101-2008-0014320080408<NA>3폐업2폐업20130605<NA><NA><NA><NA>193.01121818서울특별시 마포구 동교동 173-14번지 1층<NA><NA>애녹수산2013-09-24 09:51:23I2018-08-31 23:59:59.0한식193414.676814450675.003556한식56<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N193.01<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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1740531300003130000-101-2015-0008620150210<NA>3폐업2폐업20220208<NA><NA><NA><NA>24.64121870서울특별시 마포구 염리동 9-117 1층일부서울특별시 마포구 대흥로30길 20 (염리동, 1층일부)4113주유포차2022-02-23 10:24:34U2022-02-25 02:40:00.0호프/통닭195263.312818450444.510277호프/통닭00<NA><NA><NA>00000<NA>00N24.64<NA><NA><NA>
996431300003130000-101-2004-0074520041224<NA>3폐업2폐업20060331<NA><NA><NA>706875629.00121779서울특별시 마포구 도화동 555번지 한화오벨리스크 지하1층132호<NA><NA>두부다2005-04-28 00:00:00I2018-08-31 23:59:59.0한식195111.088139448644.311299한식01<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.0<NA><NA><NA>
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557731300003130000-101-1998-0519119980625<NA>3폐업2폐업20020702<NA><NA><NA>023141304017.42121823서울특별시 마포구 망원동 422-19번지<NA><NA>원샷주점2000-04-25 00:00:00I2018-08-31 23:59:59.0분식191468.588237450593.675112분식1<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.42<NA><NA><NA>
740331300003130000-101-2001-0909520010619<NA>3폐업2폐업20101216<NA><NA><NA>02 712135010.15121804서울특별시 마포구 공덕동 371-0번지 삼성상가지하127호<NA><NA>공덕추어탕2001-09-10 00:00:00I2018-08-31 23:59:59.0한식195614.865104449366.926257한식<NA>1주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N10.15<NA><NA><NA>
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303231300003130000-101-1994-0459319941109<NA>3폐업2폐업20050801<NA><NA><NA>02 333806213.86121839서울특별시 마포구 서교동 481-8번지 1층동<NA><NA>형제분식2000-04-19 00:00:00I2018-08-31 23:59:59.0분식192336.540548450250.605928분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N13.86<NA><NA><NA>
499631300003130000-101-1997-0510319970321<NA>3폐업2폐업20020820<NA><NA><NA>02 332653921.78121821서울특별시 마포구 망원동 397-17번지<NA><NA>둘리소주방2002-08-21 00:00:00I2018-08-31 23:59:59.0분식191374.493719450133.076372분식<NA>1주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N21.78<NA><NA><NA>
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