Overview

Dataset statistics

Number of variables47
Number of observations3639
Missing cells39931
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory405.0 B

Variable types

Categorical19
Text7
DateTime3
Unsupported7
Numeric9
Boolean2

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,건물지상층수,건물지하층수,사용시작지상층,사용끝지상층,사용시작지하층,사용끝지하층,한실수,양실수,욕실수,발한실여부,좌석수,조건부허가신고사유,조건부허가시작일자,조건부허가종료일자,건물소유구분명,세탁기수,여성종사자수,남성종사자수,회수건조수,침대수,다중이용업소여부
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-17909/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
발한실여부 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (50.7%)Imbalance
업태구분명 is highly imbalanced (61.6%)Imbalance
사용시작지하층 is highly imbalanced (57.7%)Imbalance
사용끝지하층 is highly imbalanced (78.7%)Imbalance
건물소유구분명 is highly imbalanced (89.0%)Imbalance
여성종사자수 is highly imbalanced (70.4%)Imbalance
남성종사자수 is highly imbalanced (58.2%)Imbalance
인허가취소일자 has 3639 (100.0%) missing valuesMissing
폐업일자 has 1192 (32.8%) missing valuesMissing
휴업시작일자 has 3639 (100.0%) missing valuesMissing
휴업종료일자 has 3639 (100.0%) missing valuesMissing
재개업일자 has 3639 (100.0%) missing valuesMissing
전화번호 has 1177 (32.3%) missing valuesMissing
도로명주소 has 1498 (41.2%) missing valuesMissing
도로명우편번호 has 1527 (42.0%) missing valuesMissing
좌표정보(X) has 262 (7.2%) missing valuesMissing
좌표정보(Y) has 262 (7.2%) missing valuesMissing
건물지상층수 has 874 (24.0%) missing valuesMissing
사용시작지상층 has 1222 (33.6%) missing valuesMissing
사용끝지상층 has 2270 (62.4%) missing valuesMissing
발한실여부 has 569 (15.6%) missing valuesMissing
좌석수 has 596 (16.4%) missing valuesMissing
조건부허가신고사유 has 3639 (100.0%) missing valuesMissing
조건부허가시작일자 has 3639 (100.0%) missing valuesMissing
조건부허가종료일자 has 3639 (100.0%) missing valuesMissing
침대수 has 2481 (68.2%) missing valuesMissing
다중이용업소여부 has 518 (14.2%) missing valuesMissing
좌석수 is highly skewed (γ1 = 29.92872919)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가신고사유 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 141 (3.9%) zerosZeros
건물지상층수 has 1569 (43.1%) zerosZeros
사용시작지상층 has 832 (22.9%) zerosZeros
사용끝지상층 has 177 (4.9%) zerosZeros
좌석수 has 251 (6.9%) zerosZeros
침대수 has 846 (23.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:39:43.797423
Analysis finished2024-05-11 05:39:46.041654
Duration2.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
3070000
3639 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3070000 3639
100.0%

Length

2024-05-11T14:39:46.171299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:46.353117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 3639
100.0%

관리번호
Text

UNIQUE 

Distinct3639
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2024-05-11T14:39:46.671634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters80058
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

Unique3639 ?
Unique (%)100.0%

Sample

1st row3070000-204-1964-00872
2nd row3070000-204-1965-01021
3rd row3070000-204-1965-01431
4th row3070000-204-1966-00909
5th row3070000-204-1967-01067
ValueCountFrequency (%)
3070000-204-1964-00872 1
 
< 0.1%
3070000-211-2017-00043 1
 
< 0.1%
3070000-211-2018-00041 1
 
< 0.1%
3070000-211-2018-00030 1
 
< 0.1%
3070000-211-2018-00031 1
 
< 0.1%
3070000-211-2018-00032 1
 
< 0.1%
3070000-211-2018-00033 1
 
< 0.1%
3070000-211-2018-00034 1
 
< 0.1%
3070000-211-2018-00035 1
 
< 0.1%
3070000-211-2018-00036 1
 
< 0.1%
Other values (3629) 3629
99.7%
2024-05-11T14:39:47.252713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33439
41.8%
- 10917
 
13.6%
2 8654
 
10.8%
1 8201
 
10.2%
3 5176
 
6.5%
7 4600
 
5.7%
9 3005
 
3.8%
4 2514
 
3.1%
8 1427
 
1.8%
5 1134
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69141
86.4%
Dash Punctuation 10917
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33439
48.4%
2 8654
 
12.5%
1 8201
 
11.9%
3 5176
 
7.5%
7 4600
 
6.7%
9 3005
 
4.3%
4 2514
 
3.6%
8 1427
 
2.1%
5 1134
 
1.6%
6 991
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 10917
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80058
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33439
41.8%
- 10917
 
13.6%
2 8654
 
10.8%
1 8201
 
10.2%
3 5176
 
6.5%
7 4600
 
5.7%
9 3005
 
3.8%
4 2514
 
3.1%
8 1427
 
1.8%
5 1134
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80058
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33439
41.8%
- 10917
 
13.6%
2 8654
 
10.8%
1 8201
 
10.2%
3 5176
 
6.5%
7 4600
 
5.7%
9 3005
 
3.8%
4 2514
 
3.1%
8 1427
 
1.8%
5 1134
 
1.4%
Distinct2782
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
Minimum1963-06-13 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:39:47.528666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:39:47.786463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
3
2447 
1
1192 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2447
67.2%
1 1192
32.8%

Length

2024-05-11T14:39:48.040531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:48.217047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2447
67.2%
1 1192
32.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
폐업
2447 
영업/정상
1192 

Length

Max length5
Median length2
Mean length2.9826876
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2447
67.2%
영업/정상 1192
32.8%

Length

2024-05-11T14:39:48.436131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:48.608567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2447
67.2%
영업/정상 1192
32.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2
2447 
1
1192 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2447
67.2%
1 1192
32.8%

Length

2024-05-11T14:39:48.783834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:49.000273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2447
67.2%
1 1192
32.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
폐업
2447 
영업
1192 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2447
67.2%
영업 1192
32.8%

Length

2024-05-11T14:39:49.184702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:49.342620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2447
67.2%
영업 1192
32.8%

폐업일자
Text

MISSING 

Distinct1849
Distinct (%)75.6%
Missing1192
Missing (%)32.8%
Memory size28.6 KiB
2024-05-11T14:39:49.691286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0858194
Min length8

Characters and Unicode

Total characters19786
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

Unique1551 ?
Unique (%)63.4%

Sample

1st row19940319
2nd row19981128
3rd row19980807
4th row19990209
5th row19970319
ValueCountFrequency (%)
20021102 77
 
3.1%
20030226 33
 
1.3%
20031231 28
 
1.1%
19950117 18
 
0.7%
20030624 17
 
0.7%
19940319 15
 
0.6%
20061127 14
 
0.6%
19951004 12
 
0.5%
19920331 10
 
0.4%
19970107 10
 
0.4%
Other values (1839) 2213
90.4%
2024-05-11T14:39:50.334343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5970
30.2%
2 4128
20.9%
1 3691
18.7%
9 1583
 
8.0%
3 1035
 
5.2%
7 696
 
3.5%
6 654
 
3.3%
4 649
 
3.3%
5 632
 
3.2%
8 537
 
2.7%
Other values (2) 211
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19575
98.9%
Dash Punctuation 210
 
1.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5970
30.5%
2 4128
21.1%
1 3691
18.9%
9 1583
 
8.1%
3 1035
 
5.3%
7 696
 
3.6%
6 654
 
3.3%
4 649
 
3.3%
5 632
 
3.2%
8 537
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5970
30.2%
2 4128
20.9%
1 3691
18.7%
9 1583
 
8.0%
3 1035
 
5.2%
7 696
 
3.5%
6 654
 
3.3%
4 649
 
3.3%
5 632
 
3.2%
8 537
 
2.7%
Other values (2) 211
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5970
30.2%
2 4128
20.9%
1 3691
18.7%
9 1583
 
8.0%
3 1035
 
5.2%
7 696
 
3.5%
6 654
 
3.3%
4 649
 
3.3%
5 632
 
3.2%
8 537
 
2.7%
Other values (2) 211
 
1.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

전화번호
Text

MISSING 

Distinct2236
Distinct (%)90.8%
Missing1177
Missing (%)32.3%
Memory size28.6 KiB
2024-05-11T14:39:50.820725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.391145
Min length2

Characters and Unicode

Total characters25583
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

Unique2080 ?
Unique (%)84.5%

Sample

1st row0209203364
2nd row02 9245694
3rd row0209075598
4th row0207422997
5th row02 9233038
ValueCountFrequency (%)
02 1727
36.9%
070 41
 
0.9%
909 28
 
0.6%
929 25
 
0.5%
941 23
 
0.5%
942 23
 
0.5%
921 21
 
0.4%
0200000000 21
 
0.4%
923 19
 
0.4%
943 17
 
0.4%
Other values (2299) 2736
58.4%
2024-05-11T14:39:51.611152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4589
17.9%
2 4391
17.2%
9 3372
13.2%
2783
10.9%
1 2047
8.0%
4 1515
 
5.9%
3 1491
 
5.8%
7 1445
 
5.6%
6 1411
 
5.5%
5 1323
 
5.2%
Other values (2) 1216
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22798
89.1%
Space Separator 2783
 
10.9%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4589
20.1%
2 4391
19.3%
9 3372
14.8%
1 2047
9.0%
4 1515
 
6.6%
3 1491
 
6.5%
7 1445
 
6.3%
6 1411
 
6.2%
5 1323
 
5.8%
8 1214
 
5.3%
Space Separator
ValueCountFrequency (%)
2783
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25583
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4589
17.9%
2 4391
17.2%
9 3372
13.2%
2783
10.9%
1 2047
8.0%
4 1515
 
5.9%
3 1491
 
5.8%
7 1445
 
5.6%
6 1411
 
5.5%
5 1323
 
5.2%
Other values (2) 1216
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4589
17.9%
2 4391
17.2%
9 3372
13.2%
2783
10.9%
1 2047
8.0%
4 1515
 
5.9%
3 1491
 
5.8%
7 1445
 
5.6%
6 1411
 
5.5%
5 1323
 
5.2%
Other values (2) 1216
 
4.8%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1682
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.015702
Minimum0
Maximum558.26
Zeros141
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:39:51.871461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q118.27
median26.45
Q345.315
95-th percentile106.498
Maximum558.26
Range558.26
Interquartile range (IQR)27.045

Descriptive statistics

Standard deviation35.546768
Coefficient of variation (CV)0.9350549
Kurtosis23.511454
Mean38.015702
Median Absolute Deviation (MAD)10.45
Skewness3.4538762
Sum138339.14
Variance1263.5727
MonotonicityNot monotonic
2024-05-11T14:39:52.105937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 141
 
3.9%
33.0 113
 
3.1%
26.4 81
 
2.2%
23.1 73
 
2.0%
19.8 71
 
2.0%
16.5 60
 
1.6%
30.0 50
 
1.4%
20.0 41
 
1.1%
49.5 37
 
1.0%
29.7 37
 
1.0%
Other values (1672) 2935
80.7%
ValueCountFrequency (%)
0.0 141
3.9%
3.2 1
 
< 0.1%
5.0 3
 
0.1%
5.07 1
 
< 0.1%
5.1 1
 
< 0.1%
5.28 1
 
< 0.1%
5.4 1
 
< 0.1%
5.69 1
 
< 0.1%
6.0 4
 
0.1%
6.1 1
 
< 0.1%
ValueCountFrequency (%)
558.26 1
< 0.1%
402.44 1
< 0.1%
348.7 1
< 0.1%
281.71 1
< 0.1%
281.7 1
< 0.1%
276.0 1
< 0.1%
257.72 1
< 0.1%
256.32 1
< 0.1%
243.56 1
< 0.1%
242.17 1
< 0.1%
Distinct223
Distinct (%)6.1%
Missing5
Missing (%)0.1%
Memory size28.6 KiB
2024-05-11T14:39:52.618695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0921849
Min length6

Characters and Unicode

Total characters22139
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

Unique42 ?
Unique (%)1.2%

Sample

1st row136034
2nd row136072
3rd row136873
4th row136032
5th row136891
ValueCountFrequency (%)
136051 135
 
3.7%
136865 107
 
2.9%
136833 106
 
2.9%
136800 84
 
2.3%
136818 79
 
2.2%
136075 77
 
2.1%
136052 75
 
2.1%
136110 72
 
2.0%
136858 68
 
1.9%
136042 64
 
1.8%
Other values (213) 2767
76.1%
2024-05-11T14:39:53.285287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4840
21.9%
3 4577
20.7%
6 4288
19.4%
8 2493
11.3%
0 2072
9.4%
5 1177
 
5.3%
4 837
 
3.8%
2 689
 
3.1%
7 611
 
2.8%
- 335
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21804
98.5%
Dash Punctuation 335
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4840
22.2%
3 4577
21.0%
6 4288
19.7%
8 2493
11.4%
0 2072
9.5%
5 1177
 
5.4%
4 837
 
3.8%
2 689
 
3.2%
7 611
 
2.8%
9 220
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 335
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4840
21.9%
3 4577
20.7%
6 4288
19.4%
8 2493
11.3%
0 2072
9.4%
5 1177
 
5.3%
4 837
 
3.8%
2 689
 
3.1%
7 611
 
2.8%
- 335
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4840
21.9%
3 4577
20.7%
6 4288
19.4%
8 2493
11.3%
0 2072
9.4%
5 1177
 
5.3%
4 837
 
3.8%
2 689
 
3.1%
7 611
 
2.8%
- 335
 
1.5%
Distinct3094
Distinct (%)85.1%
Missing5
Missing (%)0.1%
Memory size28.6 KiB
2024-05-11T14:39:53.638172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length25.058613
Min length17

Characters and Unicode

Total characters91063
Distinct characters304
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2675 ?
Unique (%)73.6%

Sample

1st row서울특별시 성북구 동소문동4가 278-80번지
2nd row서울특별시 성북구 안암동2가 81-0번지
3rd row서울특별시 성북구 하월곡동 88-0번지
4th row서울특별시 성북구 동소문동2가 291-0번지
5th row서울특별시 성북구 돈암동 538-13번지
ValueCountFrequency (%)
서울특별시 3634
21.8%
성북구 3633
21.8%
장위동 489
 
2.9%
정릉동 458
 
2.7%
하월곡동 395
 
2.4%
1층 357
 
2.1%
길음동 349
 
2.1%
석관동 318
 
1.9%
종암동 303
 
1.8%
동선동1가 161
 
1.0%
Other values (3082) 6599
39.5%
2024-05-11T14:39:54.470503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15990
 
17.6%
4469
 
4.9%
1 4282
 
4.7%
3761
 
4.1%
3718
 
4.1%
3664
 
4.0%
3647
 
4.0%
3639
 
4.0%
3635
 
4.0%
3634
 
4.0%
Other values (294) 40624
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53279
58.5%
Decimal Number 18205
 
20.0%
Space Separator 15990
 
17.6%
Dash Punctuation 2882
 
3.2%
Open Punctuation 273
 
0.3%
Close Punctuation 273
 
0.3%
Uppercase Letter 103
 
0.1%
Other Punctuation 45
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4469
 
8.4%
3761
 
7.1%
3718
 
7.0%
3664
 
6.9%
3647
 
6.8%
3639
 
6.8%
3635
 
6.8%
3634
 
6.8%
3634
 
6.8%
3011
 
5.7%
Other values (254) 16467
30.9%
Uppercase Letter
ValueCountFrequency (%)
B 27
26.2%
A 14
13.6%
S 12
11.7%
K 11
10.7%
P 5
 
4.9%
E 5
 
4.9%
I 5
 
4.9%
W 4
 
3.9%
V 4
 
3.9%
T 4
 
3.9%
Other values (7) 12
11.7%
Decimal Number
ValueCountFrequency (%)
1 4282
23.5%
2 2980
16.4%
3 2042
11.2%
0 1598
 
8.8%
5 1389
 
7.6%
4 1368
 
7.5%
6 1274
 
7.0%
8 1203
 
6.6%
7 1153
 
6.3%
9 916
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 37
82.2%
@ 3
 
6.7%
/ 2
 
4.4%
. 2
 
4.4%
? 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e 6
66.7%
a 2
 
22.2%
b 1
 
11.1%
Space Separator
ValueCountFrequency (%)
15990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2882
100.0%
Open Punctuation
ValueCountFrequency (%)
( 273
100.0%
Close Punctuation
ValueCountFrequency (%)
) 273
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53279
58.5%
Common 37672
41.4%
Latin 112
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4469
 
8.4%
3761
 
7.1%
3718
 
7.0%
3664
 
6.9%
3647
 
6.8%
3639
 
6.8%
3635
 
6.8%
3634
 
6.8%
3634
 
6.8%
3011
 
5.7%
Other values (254) 16467
30.9%
Common
ValueCountFrequency (%)
15990
42.4%
1 4282
 
11.4%
2 2980
 
7.9%
- 2882
 
7.7%
3 2042
 
5.4%
0 1598
 
4.2%
5 1389
 
3.7%
4 1368
 
3.6%
6 1274
 
3.4%
8 1203
 
3.2%
Other values (10) 2664
 
7.1%
Latin
ValueCountFrequency (%)
B 27
24.1%
A 14
12.5%
S 12
10.7%
K 11
9.8%
e 6
 
5.4%
P 5
 
4.5%
E 5
 
4.5%
I 5
 
4.5%
W 4
 
3.6%
V 4
 
3.6%
Other values (10) 19
17.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53279
58.5%
ASCII 37784
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15990
42.3%
1 4282
 
11.3%
2 2980
 
7.9%
- 2882
 
7.6%
3 2042
 
5.4%
0 1598
 
4.2%
5 1389
 
3.7%
4 1368
 
3.6%
6 1274
 
3.4%
8 1203
 
3.2%
Other values (30) 2776
 
7.3%
Hangul
ValueCountFrequency (%)
4469
 
8.4%
3761
 
7.1%
3718
 
7.0%
3664
 
6.9%
3647
 
6.8%
3639
 
6.8%
3635
 
6.8%
3634
 
6.8%
3634
 
6.8%
3011
 
5.7%
Other values (254) 16467
30.9%

도로명주소
Text

MISSING 

Distinct1969
Distinct (%)92.0%
Missing1498
Missing (%)41.2%
Memory size28.6 KiB
2024-05-11T14:39:54.882562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length54
Mean length32.421298
Min length21

Characters and Unicode

Total characters69414
Distinct characters309
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1827 ?
Unique (%)85.3%

Sample

1st row서울특별시 성북구 종암로 98-15, 1층 (종암동)
2nd row서울특별시 성북구 숭인로 4, 1층 (길음동)
3rd row서울특별시 성북구 정릉로36길 76 (정릉동)
4th row서울특별시 성북구 동소문로 248, 105동 210호 (길음동,삼부아파트상가)
5th row서울특별시 성북구 돌곶이로32길 34 (장위동)
ValueCountFrequency (%)
서울특별시 2141
 
16.1%
성북구 2140
 
16.1%
1층 631
 
4.8%
2층 259
 
2.0%
정릉동 221
 
1.7%
하월곡동 217
 
1.6%
장위동 216
 
1.6%
길음동 162
 
1.2%
석관동 146
 
1.1%
종암동 141
 
1.1%
Other values (1608) 6991
52.7%
2024-05-11T14:39:56.002251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11131
 
16.0%
3251
 
4.7%
1 3091
 
4.5%
( 2313
 
3.3%
) 2313
 
3.3%
2302
 
3.3%
2290
 
3.3%
2177
 
3.1%
2170
 
3.1%
2145
 
3.1%
Other values (299) 36231
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40007
57.6%
Decimal Number 11254
 
16.2%
Space Separator 11131
 
16.0%
Open Punctuation 2313
 
3.3%
Close Punctuation 2313
 
3.3%
Other Punctuation 1913
 
2.8%
Dash Punctuation 364
 
0.5%
Uppercase Letter 102
 
0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3251
 
8.1%
2302
 
5.8%
2290
 
5.7%
2177
 
5.4%
2170
 
5.4%
2145
 
5.4%
2141
 
5.4%
2141
 
5.4%
2141
 
5.4%
2134
 
5.3%
Other values (257) 17115
42.8%
Uppercase Letter
ValueCountFrequency (%)
B 41
40.2%
S 11
 
10.8%
A 11
 
10.8%
K 9
 
8.8%
E 5
 
4.9%
V 4
 
3.9%
I 4
 
3.9%
M 4
 
3.9%
W 4
 
3.9%
H 2
 
2.0%
Other values (6) 7
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 3091
27.5%
2 2141
19.0%
3 1125
 
10.0%
4 958
 
8.5%
0 942
 
8.4%
5 799
 
7.1%
6 687
 
6.1%
7 546
 
4.9%
8 520
 
4.6%
9 445
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
b 3
25.0%
e 3
25.0%
o 1
 
8.3%
x 1
 
8.3%
y 1
 
8.3%
a 1
 
8.3%
s 1
 
8.3%
k 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 1911
99.9%
? 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
11131
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40007
57.6%
Common 29293
42.2%
Latin 114
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3251
 
8.1%
2302
 
5.8%
2290
 
5.7%
2177
 
5.4%
2170
 
5.4%
2145
 
5.4%
2141
 
5.4%
2141
 
5.4%
2141
 
5.4%
2134
 
5.3%
Other values (257) 17115
42.8%
Latin
ValueCountFrequency (%)
B 41
36.0%
S 11
 
9.6%
A 11
 
9.6%
K 9
 
7.9%
E 5
 
4.4%
V 4
 
3.5%
I 4
 
3.5%
M 4
 
3.5%
W 4
 
3.5%
b 3
 
2.6%
Other values (14) 18
15.8%
Common
ValueCountFrequency (%)
11131
38.0%
1 3091
 
10.6%
( 2313
 
7.9%
) 2313
 
7.9%
2 2141
 
7.3%
, 1911
 
6.5%
3 1125
 
3.8%
4 958
 
3.3%
0 942
 
3.2%
5 799
 
2.7%
Other values (8) 2569
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40007
57.6%
ASCII 29407
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11131
37.9%
1 3091
 
10.5%
( 2313
 
7.9%
) 2313
 
7.9%
2 2141
 
7.3%
, 1911
 
6.5%
3 1125
 
3.8%
4 958
 
3.3%
0 942
 
3.2%
5 799
 
2.7%
Other values (32) 2683
 
9.1%
Hangul
ValueCountFrequency (%)
3251
 
8.1%
2302
 
5.8%
2290
 
5.7%
2177
 
5.4%
2170
 
5.4%
2145
 
5.4%
2141
 
5.4%
2141
 
5.4%
2141
 
5.4%
2134
 
5.3%
Other values (257) 17115
42.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct164
Distinct (%)7.8%
Missing1527
Missing (%)42.0%
Infinite0
Infinite (%)0.0%
Mean2791.4635
Minimum1215
Maximum2880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:39:56.285430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1215
5-th percentile2713
Q12749
median2797
Q32842
95-th percentile2865
Maximum2880
Range1665
Interquartile range (IQR)93

Descriptive statistics

Standard deviation61.33077
Coefficient of variation (CV)0.02197083
Kurtosis205.17896
Mean2791.4635
Median Absolute Deviation (MAD)47
Skewness-8.0866703
Sum5895571
Variance3761.4634
MonotonicityNot monotonic
2024-05-11T14:39:56.554959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2845 124
 
3.4%
2829 87
 
2.4%
2751 64
 
1.8%
2797 57
 
1.6%
2830 53
 
1.5%
2844 37
 
1.0%
2784 37
 
1.0%
2737 36
 
1.0%
2781 33
 
0.9%
2709 32
 
0.9%
Other values (154) 1552
42.6%
(Missing) 1527
42.0%
ValueCountFrequency (%)
1215 1
 
< 0.1%
2700 1
 
< 0.1%
2701 12
 
0.3%
2702 14
0.4%
2704 3
 
0.1%
2705 2
 
0.1%
2707 1
 
< 0.1%
2708 3
 
0.1%
2709 32
0.9%
2710 22
0.6%
ValueCountFrequency (%)
2880 19
0.5%
2879 2
 
0.1%
2877 1
 
< 0.1%
2874 1
 
< 0.1%
2873 14
0.4%
2872 30
0.8%
2871 13
0.4%
2870 1
 
< 0.1%
2869 2
 
0.1%
2868 2
 
0.1%
Distinct3085
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2024-05-11T14:39:57.020558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length5.6924979
Min length1

Characters and Unicode

Total characters20715
Distinct characters727
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2727 ?
Unique (%)74.9%

Sample

1st row아씨
2nd row희정
3rd row경아
4th row여로
5th row유진
ValueCountFrequency (%)
헤어 76
 
1.7%
네일 31
 
0.7%
hair 30
 
0.7%
미용실 28
 
0.6%
성신여대점 20
 
0.5%
에스테틱 17
 
0.4%
nail 15
 
0.3%
by 12
 
0.3%
12
 
0.3%
뷰티 12
 
0.3%
Other values (3292) 4120
94.2%
2024-05-11T14:39:57.716504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1341
 
6.5%
1286
 
6.2%
768
 
3.7%
736
 
3.6%
522
 
2.5%
498
 
2.4%
453
 
2.2%
443
 
2.1%
441
 
2.1%
) 269
 
1.3%
Other values (717) 13958
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17264
83.3%
Lowercase Letter 1067
 
5.2%
Uppercase Letter 783
 
3.8%
Space Separator 736
 
3.6%
Close Punctuation 270
 
1.3%
Open Punctuation 270
 
1.3%
Other Punctuation 175
 
0.8%
Decimal Number 133
 
0.6%
Math Symbol 7
 
< 0.1%
Dash Punctuation 6
 
< 0.1%
Other values (4) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1341
 
7.8%
1286
 
7.4%
768
 
4.4%
522
 
3.0%
498
 
2.9%
453
 
2.6%
443
 
2.6%
441
 
2.6%
253
 
1.5%
238
 
1.4%
Other values (633) 11021
63.8%
Uppercase Letter
ValueCountFrequency (%)
A 85
 
10.9%
S 68
 
8.7%
N 66
 
8.4%
H 57
 
7.3%
I 52
 
6.6%
L 49
 
6.3%
O 45
 
5.7%
T 42
 
5.4%
E 38
 
4.9%
J 32
 
4.1%
Other values (16) 249
31.8%
Lowercase Letter
ValueCountFrequency (%)
a 154
14.4%
e 109
10.2%
o 103
9.7%
i 99
9.3%
l 88
8.2%
n 78
 
7.3%
r 71
 
6.7%
h 54
 
5.1%
s 48
 
4.5%
t 47
 
4.4%
Other values (15) 216
20.2%
Other Punctuation
ValueCountFrequency (%)
? 47
26.9%
& 33
18.9%
. 26
14.9%
, 25
14.3%
# 20
11.4%
' 12
 
6.9%
: 5
 
2.9%
; 3
 
1.7%
! 2
 
1.1%
2
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 40
30.1%
2 34
25.6%
1 22
16.5%
7 10
 
7.5%
9 6
 
4.5%
3 6
 
4.5%
6 5
 
3.8%
4 5
 
3.8%
5 3
 
2.3%
8 2
 
1.5%
Math Symbol
ValueCountFrequency (%)
+ 5
71.4%
< 1
 
14.3%
> 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 269
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 269
99.6%
[ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17259
83.3%
Latin 1851
 
8.9%
Common 1600
 
7.7%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1341
 
7.8%
1286
 
7.5%
768
 
4.4%
522
 
3.0%
498
 
2.9%
453
 
2.6%
443
 
2.6%
441
 
2.6%
253
 
1.5%
238
 
1.4%
Other values (630) 11016
63.8%
Latin
ValueCountFrequency (%)
a 154
 
8.3%
e 109
 
5.9%
o 103
 
5.6%
i 99
 
5.3%
l 88
 
4.8%
A 85
 
4.6%
n 78
 
4.2%
r 71
 
3.8%
S 68
 
3.7%
N 66
 
3.6%
Other values (42) 930
50.2%
Common
ValueCountFrequency (%)
736
46.0%
) 269
 
16.8%
( 269
 
16.8%
? 47
 
2.9%
0 40
 
2.5%
2 34
 
2.1%
& 33
 
2.1%
. 26
 
1.6%
, 25
 
1.6%
1 22
 
1.4%
Other values (22) 99
 
6.2%
Han
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17259
83.3%
ASCII 3447
 
16.6%
CJK 5
 
< 0.1%
None 2
 
< 0.1%
Number Forms 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1341
 
7.8%
1286
 
7.5%
768
 
4.4%
522
 
3.0%
498
 
2.9%
453
 
2.6%
443
 
2.6%
441
 
2.6%
253
 
1.5%
238
 
1.4%
Other values (630) 11016
63.8%
ASCII
ValueCountFrequency (%)
736
21.4%
) 269
 
7.8%
( 269
 
7.8%
a 154
 
4.5%
e 109
 
3.2%
o 103
 
3.0%
i 99
 
2.9%
l 88
 
2.6%
A 85
 
2.5%
n 78
 
2.3%
Other values (71) 1457
42.3%
CJK
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
None
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
Distinct2586
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
Minimum1998-12-26 00:00:00
Maximum2024-05-09 13:30:20
2024-05-11T14:39:57.988471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:39:58.229770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
I
2859 
U
764 
D
 
16

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 2859
78.6%
U 764
 
21.0%
D 16
 
0.4%

Length

2024-05-11T14:39:58.465082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:58.654198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2859
78.6%
u 764
 
21.0%
d 16
 
0.4%
Distinct793
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:39:58.853146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:39:59.148277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
일반미용업
2912 
피부미용업
397 
네일아트업
 
267
메이크업업
 
58
기타
 
4

Length

Max length6
Median length5
Mean length4.9969772
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 2912
80.0%
피부미용업 397
 
10.9%
네일아트업 267
 
7.3%
메이크업업 58
 
1.6%
기타 4
 
0.1%
숙박업 기타 1
 
< 0.1%

Length

2024-05-11T14:39:59.395709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:59.602616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 2912
80.0%
피부미용업 397
 
10.9%
네일아트업 267
 
7.3%
메이크업업 58
 
1.6%
기타 5
 
0.1%
숙박업 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2017
Distinct (%)59.7%
Missing262
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean202528.5
Minimum199191.6
Maximum206112.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:39:59.808377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199191.6
5-th percentile200565.34
Q1201380.04
median202080.68
Q3203663.46
95-th percentile205344.64
Maximum206112.46
Range6920.8593
Interquartile range (IQR)2283.4207

Descriptive statistics

Standard deviation1528.1586
Coefficient of variation (CV)0.0075454002
Kurtosis-0.84921084
Mean202528.5
Median Absolute Deviation (MAD)1019.1382
Skewness0.46356448
Sum6.8393873 × 108
Variance2335268.6
MonotonicityNot monotonic
2024-05-11T14:40:00.062049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200841.726990037 37
 
1.0%
202029.981799661 24
 
0.7%
203318.127254872 22
 
0.6%
200575.420521471 17
 
0.5%
201648.204071174 16
 
0.4%
201989.271689499 15
 
0.4%
205996.717928956 15
 
0.4%
202667.468802014 12
 
0.3%
201964.531844396 10
 
0.3%
203649.811269449 9
 
0.2%
Other values (2007) 3200
87.9%
(Missing) 262
 
7.2%
ValueCountFrequency (%)
199191.598277675 1
< 0.1%
199264.515248477 1
< 0.1%
199288.277741946 1
< 0.1%
199342.361422027 1
< 0.1%
199361.181902605 1
< 0.1%
199488.829016125 1
< 0.1%
199516.48114411 2
0.1%
199549.679509335 1
< 0.1%
199606.464796251 1
< 0.1%
199621.266942781 1
< 0.1%
ValueCountFrequency (%)
206112.457605113 2
 
0.1%
205996.717928956 15
0.4%
205818.852385165 3
 
0.1%
205728.527460287 1
 
< 0.1%
205725.865213454 1
 
< 0.1%
205714.262098815 1
 
< 0.1%
205704.366298809 1
 
< 0.1%
205695.669320428 4
 
0.1%
205686.985960197 1
 
< 0.1%
205681.146401734 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2016
Distinct (%)59.7%
Missing262
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean455508.24
Minimum452955.23
Maximum457844.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:00.301724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452955.23
5-th percentile453668.43
Q1454513.15
median455713.24
Q3456365.33
95-th percentile457198.93
Maximum457844.35
Range4889.1191
Interquartile range (IQR)1852.1779

Descriptive statistics

Standard deviation1122.5067
Coefficient of variation (CV)0.0024642949
Kurtosis-1.0006484
Mean455508.24
Median Absolute Deviation (MAD)896.10897
Skewness-0.21444234
Sum1.5382513 × 109
Variance1260021.2
MonotonicityNot monotonic
2024-05-11T14:40:00.578301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
454721.505180141 37
 
1.0%
455605.716911266 24
 
0.7%
456078.982123486 23
 
0.6%
457360.617372111 17
 
0.5%
455717.855906877 16
 
0.4%
455190.095862939 15
 
0.4%
456704.522324447 15
 
0.4%
455858.920803881 12
 
0.3%
455825.760930114 10
 
0.3%
455662.299341418 9
 
0.2%
Other values (2006) 3199
87.9%
(Missing) 262
 
7.2%
ValueCountFrequency (%)
452955.228914632 1
< 0.1%
452977.8305465 1
< 0.1%
452992.513827755 1
< 0.1%
453013.952137832 1
< 0.1%
453031.449626 1
< 0.1%
453036.352333829 1
< 0.1%
453036.744985063 1
< 0.1%
453063.623811667 1
< 0.1%
453064.371196557 1
< 0.1%
453067.080511164 1
< 0.1%
ValueCountFrequency (%)
457844.348010616 7
0.2%
457803.264646008 6
0.2%
457789.390510766 1
 
< 0.1%
457681.833795388 2
 
0.1%
457679.079445295 1
 
< 0.1%
457678.401608072 1
 
< 0.1%
457667.199817772 1
 
< 0.1%
457664.624149181 1
 
< 0.1%
457651.875947833 1
 
< 0.1%
457584.166360937 1
 
< 0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
미용업
1390 
일반미용업
1060 
<NA>
518 
피부미용업
249 
종합미용업
216 
Other values (11)
206 

Length

Max length23
Median length16
Mean length4.4394064
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 1390
38.2%
일반미용업 1060
29.1%
<NA> 518
 
14.2%
피부미용업 249
 
6.8%
종합미용업 216
 
5.9%
네일미용업 81
 
2.2%
피부미용업, 네일미용업 30
 
0.8%
네일미용업, 화장ㆍ분장 미용업 25
 
0.7%
일반미용업, 화장ㆍ분장 미용업 17
 
0.5%
일반미용업, 네일미용업 11
 
0.3%
Other values (6) 42
 
1.2%

Length

2024-05-11T14:40:00.857454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 1470
38.2%
일반미용업 1100
28.5%
na 518
 
13.4%
피부미용업 305
 
7.9%
종합미용업 216
 
5.6%
네일미용업 164
 
4.3%
화장ㆍ분장 80
 
2.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.5%
Missing874
Missing (%)24.0%
Infinite0
Infinite (%)0.0%
Mean1.2792043
Minimum0
Maximum36
Zeros1569
Zeros (%)43.1%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:01.054714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum36
Range36
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9911576
Coefficient of variation (CV)1.5565594
Kurtosis38.026572
Mean1.2792043
Median Absolute Deviation (MAD)0
Skewness3.5907202
Sum3537
Variance3.9647085
MonotonicityNot monotonic
2024-05-11T14:40:01.224811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 1569
43.1%
3 318
 
8.7%
1 276
 
7.6%
2 240
 
6.6%
4 207
 
5.7%
5 96
 
2.6%
6 19
 
0.5%
9 15
 
0.4%
7 8
 
0.2%
8 4
 
0.1%
Other values (5) 13
 
0.4%
(Missing) 874
24.0%
ValueCountFrequency (%)
0 1569
43.1%
1 276
 
7.6%
2 240
 
6.6%
3 318
 
8.7%
4 207
 
5.7%
5 96
 
2.6%
6 19
 
0.5%
7 8
 
0.2%
8 4
 
0.1%
9 15
 
0.4%
ValueCountFrequency (%)
36 1
 
< 0.1%
15 4
 
0.1%
12 2
 
0.1%
11 2
 
0.1%
10 4
 
0.1%
9 15
 
0.4%
8 4
 
0.1%
7 8
 
0.2%
6 19
 
0.5%
5 96
2.6%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
0
1904 
<NA>
1586 
1
 
136
2
 
11
3
 
2

Length

Max length4
Median length1
Mean length2.3075021
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1904
52.3%
<NA> 1586
43.6%
1 136
 
3.7%
2 11
 
0.3%
3 2
 
0.1%

Length

2024-05-11T14:40:01.439536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:01.624882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1904
52.3%
na 1586
43.6%
1 136
 
3.7%
2 11
 
0.3%
3 2
 
0.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing1222
Missing (%)33.6%
Infinite0
Infinite (%)0.0%
Mean0.91228796
Minimum0
Maximum13
Zeros832
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:01.823302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum13
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.98905539
Coefficient of variation (CV)1.0841482
Kurtosis17.956386
Mean0.91228796
Median Absolute Deviation (MAD)1
Skewness2.8530211
Sum2205
Variance0.97823057
MonotonicityNot monotonic
2024-05-11T14:40:02.002590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1175
32.3%
0 832
22.9%
2 310
 
8.5%
3 56
 
1.5%
4 16
 
0.4%
7 10
 
0.3%
5 9
 
0.2%
6 7
 
0.2%
13 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 1222
33.6%
ValueCountFrequency (%)
0 832
22.9%
1 1175
32.3%
2 310
 
8.5%
3 56
 
1.5%
4 16
 
0.4%
5 9
 
0.2%
6 7
 
0.2%
7 10
 
0.3%
8 1
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
8 1
 
< 0.1%
7 10
 
0.3%
6 7
 
0.2%
5 9
 
0.2%
4 16
 
0.4%
3 56
 
1.5%
2 310
 
8.5%
1 1175
32.3%
0 832
22.9%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.7%
Missing2270
Missing (%)62.4%
Infinite0
Infinite (%)0.0%
Mean1.1563185
Minimum0
Maximum8
Zeros177
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:02.165360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.85777654
Coefficient of variation (CV)0.74181685
Kurtosis14.545605
Mean1.1563185
Median Absolute Deviation (MAD)0
Skewness2.7777015
Sum1583
Variance0.73578059
MonotonicityNot monotonic
2024-05-11T14:40:02.357840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 922
25.3%
2 206
 
5.7%
0 177
 
4.9%
3 40
 
1.1%
4 8
 
0.2%
5 6
 
0.2%
7 5
 
0.1%
6 4
 
0.1%
8 1
 
< 0.1%
(Missing) 2270
62.4%
ValueCountFrequency (%)
0 177
 
4.9%
1 922
25.3%
2 206
 
5.7%
3 40
 
1.1%
4 8
 
0.2%
5 6
 
0.2%
6 4
 
0.1%
7 5
 
0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
7 5
 
0.1%
6 4
 
0.1%
5 6
 
0.2%
4 8
 
0.2%
3 40
 
1.1%
2 206
 
5.7%
1 922
25.3%
0 177
 
4.9%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
2578 
0
998 
1
 
47
2
 
14
4
 
2

Length

Max length4
Median length4
Mean length3.1253092
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2578
70.8%
0 998
 
27.4%
1 47
 
1.3%
2 14
 
0.4%
4 2
 
0.1%

Length

2024-05-11T14:40:02.564005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:02.738903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2578
70.8%
0 998
 
27.4%
1 47
 
1.3%
2 14
 
0.4%
4 2
 
0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
3314 
0
 
281
1
 
35
2
 
8
4
 
1

Length

Max length4
Median length4
Mean length3.7320692
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3314
91.1%
0 281
 
7.7%
1 35
 
1.0%
2 8
 
0.2%
4 1
 
< 0.1%

Length

2024-05-11T14:40:02.954953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:03.155764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3314
91.1%
0 281
 
7.7%
1 35
 
1.0%
2 8
 
0.2%
4 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
0
1981 
<NA>
1658 

Length

Max length4
Median length1
Mean length2.366859
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1981
54.4%
<NA> 1658
45.6%

Length

2024-05-11T14:40:03.348573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:03.580395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1981
54.4%
na 1658
45.6%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
0
1981 
<NA>
1658 

Length

Max length4
Median length1
Mean length2.366859
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1981
54.4%
<NA> 1658
45.6%

Length

2024-05-11T14:40:03.830498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:04.026642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1981
54.4%
na 1658
45.6%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
0
1981 
<NA>
1658 

Length

Max length4
Median length1
Mean length2.366859
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1981
54.4%
<NA> 1658
45.6%

Length

2024-05-11T14:40:04.204394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:04.369465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1981
54.4%
na 1658
45.6%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing569
Missing (%)15.6%
Memory size7.2 KiB
False
3070 
(Missing)
569 
ValueCountFrequency (%)
False 3070
84.4%
(Missing) 569
 
15.6%
2024-05-11T14:40:04.497806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct25
Distinct (%)0.8%
Missing596
Missing (%)16.4%
Infinite0
Infinite (%)0.0%
Mean3.5882353
Minimum0
Maximum195
Zeros251
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:04.630172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum195
Range195
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.2899918
Coefficient of variation (CV)1.1955715
Kurtosis1306.192
Mean3.5882353
Median Absolute Deviation (MAD)1
Skewness29.928729
Sum10919
Variance18.40403
MonotonicityNot monotonic
2024-05-11T14:40:04.820176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3 1202
33.0%
2 496
13.6%
4 466
 
12.8%
0 251
 
6.9%
5 199
 
5.5%
6 151
 
4.1%
8 78
 
2.1%
7 50
 
1.4%
1 39
 
1.1%
10 37
 
1.0%
Other values (15) 74
 
2.0%
(Missing) 596
16.4%
ValueCountFrequency (%)
0 251
 
6.9%
1 39
 
1.1%
2 496
13.6%
3 1202
33.0%
4 466
 
12.8%
5 199
 
5.5%
6 151
 
4.1%
7 50
 
1.4%
8 78
 
2.1%
9 14
 
0.4%
ValueCountFrequency (%)
195 1
< 0.1%
36 1
< 0.1%
33 1
< 0.1%
30 2
0.1%
27 1
< 0.1%
22 1
< 0.1%
20 1
< 0.1%
19 1
< 0.1%
16 2
0.1%
15 2
0.1%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3639
Missing (%)100.0%
Memory size32.1 KiB

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
3546 
임대
 
92
자가
 
1

Length

Max length4
Median length4
Mean length3.9488871
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3546
97.4%
임대 92
 
2.5%
자가 1
 
< 0.1%

Length

2024-05-11T14:40:05.093135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:05.324276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3546
97.4%
임대 92
 
2.5%
자가 1
 
< 0.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
2379 
0
1260 

Length

Max length4
Median length4
Mean length2.9612531
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> 2379
65.4%
0 1260
34.6%

Length

2024-05-11T14:40:05.522208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:05.717847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2379
65.4%
0 1260
34.6%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
3023 
0
602 
1
 
10
2
 
3
4
 
1

Length

Max length4
Median length4
Mean length3.4921682
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3023
83.1%
0 602
 
16.5%
1 10
 
0.3%
2 3
 
0.1%
4 1
 
< 0.1%

Length

2024-05-11T14:40:05.984836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:06.199642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3023
83.1%
0 602
 
16.5%
1 10
 
0.3%
2 3
 
0.1%
4 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
3025 
0
611 
1
 
3

Length

Max length4
Median length4
Mean length3.493817
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> 3025
83.1%
0 611
 
16.8%
1 3
 
0.1%

Length

2024-05-11T14:40:06.410041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:06.988677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3025
83.1%
0 611
 
16.8%
1 3
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
<NA>
2476 
0
1163 

Length

Max length4
Median length4
Mean length3.0412201
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> 2476
68.0%
0 1163
32.0%

Length

2024-05-11T14:40:07.193825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:07.365550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2476
68.0%
0 1163
32.0%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.9%
Missing2481
Missing (%)68.2%
Infinite0
Infinite (%)0.0%
Mean0.78151986
Minimum0
Maximum9
Zeros846
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size32.1 KiB
2024-05-11T14:40:07.511456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5605676
Coefficient of variation (CV)1.9968368
Kurtosis5.4261464
Mean0.78151986
Median Absolute Deviation (MAD)0
Skewness2.3149717
Sum905
Variance2.4353712
MonotonicityNot monotonic
2024-05-11T14:40:07.710538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 846
 
23.2%
2 123
 
3.4%
1 51
 
1.4%
3 49
 
1.3%
4 37
 
1.0%
5 21
 
0.6%
6 17
 
0.5%
7 9
 
0.2%
9 3
 
0.1%
8 2
 
0.1%
(Missing) 2481
68.2%
ValueCountFrequency (%)
0 846
23.2%
1 51
 
1.4%
2 123
 
3.4%
3 49
 
1.3%
4 37
 
1.0%
5 21
 
0.6%
6 17
 
0.5%
7 9
 
0.2%
8 2
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
9 3
 
0.1%
8 2
 
0.1%
7 9
 
0.2%
6 17
 
0.5%
5 21
 
0.6%
4 37
 
1.0%
3 49
 
1.3%
2 123
 
3.4%
1 51
 
1.4%
0 846
23.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing518
Missing (%)14.2%
Memory size7.2 KiB
False
3121 
(Missing)
518 
ValueCountFrequency (%)
False 3121
85.8%
(Missing) 518
 
14.2%
2024-05-11T14:40:07.889600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
030700003070000-204-1964-0087219640914<NA>3폐업2폐업19940319<NA><NA><NA>020920336420.0136034서울특별시 성북구 동소문동4가 278-80번지<NA><NA>아씨2001-09-27 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
130700003070000-204-1965-0102119650529<NA>3폐업2폐업19981128<NA><NA><NA>02 924569418.79136072서울특별시 성북구 안암동2가 81-0번지<NA><NA>희정2001-09-27 00:00:00I2018-08-31 23:59:59.0일반미용업201860.984211453898.319249미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
230700003070000-204-1965-0143119650209<NA>3폐업2폐업19980807<NA><NA><NA>020907559820.3136873서울특별시 성북구 하월곡동 88-0번지<NA><NA>경아2001-09-27 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
330700003070000-204-1966-0090919661229<NA>3폐업2폐업19990209<NA><NA><NA>020742299720.1136032서울특별시 성북구 동소문동2가 291-0번지<NA><NA>여로1999-02-11 00:00:00I2018-08-31 23:59:59.0일반미용업200778.87496454118.53238미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
430700003070000-204-1967-0106719671104<NA>3폐업2폐업19970319<NA><NA><NA>02 923303821.82136891서울특별시 성북구 돈암동 538-13번지<NA><NA>유진2001-09-27 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
530700003070000-204-1967-0142219670414<NA>3폐업2폐업20021102<NA><NA><NA>020919235828.0136873서울특별시 성북구 하월곡동 88-427번지<NA><NA>2003-06-14 00:00:00I2018-08-31 23:59:59.0일반미용업202383.205659455932.109171미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
630700003070000-204-1967-0143019670610<NA>3폐업2폐업20021102<NA><NA><NA>020912869318.06136872서울특별시 성북구 하월곡동 82-12번지<NA><NA>한양2003-06-11 00:00:00I2018-08-31 23:59:59.0일반미용업203014.874306456082.118145미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
730700003070000-204-1968-0119219680619<NA>3폐업2폐업20010302<NA><NA><NA>020920362016.01136850서울특별시 성북구 정릉동 684-3번지<NA><NA>귀티나2001-03-05 00:00:00I2018-08-31 23:59:59.0일반미용업200445.672781456244.970591미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
830700003070000-204-1968-0126619680426<NA>3폐업2폐업19991208<NA><NA><NA>020919762113.7136804서울특별시 성북구 길음동 590-17번지<NA><NA>성희1999-12-15 00:00:00I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
930700003070000-204-1969-0117919690505<NA>3폐업2폐업19990730<NA><NA><NA>020919204316.03136850서울특별시 성북구 정릉동 685-76번지<NA><NA>이연희1999-08-05 00:00:00I2018-08-31 23:59:59.0일반미용업200509.875652456268.618559미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
362930700003070000-226-2019-0000120190403<NA>3폐업2폐업20220105<NA><NA><NA><NA>20.74136090서울특별시 성북구 종암동 130-2 102호서울특별시 성북구 종암로27길 26, 102호 (종암동)2802네일 더 행복(네일 THE 행복)2022-01-05 11:41:49U2022-01-07 02:40:00.0네일아트업202656.876553455605.03126피부미용업, 네일미용업, 화장ㆍ분장 미용업000000000N6<NA><NA><NA><NA>00001N
363030700003070000-226-2020-0000120200514<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.19136873서울특별시 성북구 하월곡동 175번지서울특별시 성북구 종암로40길 39, 1층 (하월곡동)2736봄꽃뷰티2020-05-14 15:41:30I2020-05-16 00:23:20.0피부미용업202770.841889456377.958651피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N3<NA><NA><NA><NA>00002N
363130700003070000-226-2021-0000120210224<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0136082서울특별시 성북구 보문동2가 125서울특별시 성북구 보문로23길 4, 1층 102호 (보문동2가)2872네일 오하이오2021-02-24 15:39:47I2021-02-26 00:23:01.0네일아트업201659.322646453550.189499피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N5<NA><NA><NA><NA>00000N
363230700003070000-226-2021-0000220210315<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.94136052서울특별시 성북구 동선동2가 12서울특별시 성북구 보문로34길 54, 3층 (동선동2가)2849또바네일2021-03-15 15:32:58I2021-03-17 00:22:59.0네일아트업201551.483299454273.783579피부미용업, 네일미용업, 화장ㆍ분장 미용업00<NA><NA><NA><NA>000N4<NA><NA><NA><NA>00002N
363330700003070000-226-2021-0000320210513<NA>1영업/정상1영업<NA><NA><NA><NA><NA>34.0136818서울특별시 성북구 석관동 300-28서울특별시 성북구 돌곶이로 52-10, 1층 (석관동)2784토티네2021-05-13 11:21:49I2021-05-15 00:22:56.0네일아트업205220.325454456269.143876피부미용업, 네일미용업, 화장ㆍ분장 미용업001<NA><NA><NA>000N6<NA><NA><NA><NA>00002N
363430700003070000-226-2021-000042021-06-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.2136-150서울특별시 성북구 석관동 10 두산아파트서울특별시 성북구 화랑로48길 16, 주상가동 211호 (석관동, 두산아파트)2780라온뷰티 석계역점2023-11-21 13:44:03U2022-10-31 22:03:00.0피부미용업205996.717929456704.522324<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
363530700003070000-226-2021-000052021-09-28<NA>3폐업2폐업2023-12-20<NA><NA><NA><NA>56.91136-100서울특별시 성북구 정릉동 1034 길음뉴타운10단지서울특별시 성북구 정릉로 307, 상가동 B218호 (정릉동, 길음뉴타운10단지)2719인주뷰티2023-12-20 09:44:51U2022-11-01 22:03:00.0네일아트업201548.495616455659.817852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
363630700003070000-226-2022-0000120220308<NA>1영업/정상1영업<NA><NA><NA><NA><NA>95.28136051서울특별시 성북구 동선동1가 2-4서울특별시 성북구 동소문로20나길 13, 4층 (동선동1가)2845구구네일 성신여대점2022-03-29 14:16:25U2021-12-02 21:01:00.0네일아트업201466.523319454434.811689<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
363730700003070000-226-2022-0000220220311<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.0136865서울특별시 성북구 하월곡동 64-11서울특별시 성북구 화랑로5길 5, 1층 (하월곡동)2751스네일('S nail)2022-03-11 13:31:24I2022-03-13 00:22:53.0네일아트업203364.199209455611.491119피부미용업, 네일미용업, 화장ㆍ분장 미용업001000000N3<NA><NA><NA><NA>00001N
363830700003070000-226-2022-0000320220617<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.13136844서울특별시 성북구 정릉동 111-36서울특별시 성북구 정릉로36길 81, 1층 (정릉동)2815티엘티(tlt)2022-06-17 13:37:08I2021-12-05 23:09:00.0네일아트업201176.977151455554.96297<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>