Overview

Dataset statistics

Number of variables13
Number of observations215
Missing cells14
Missing cells (%)0.5%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory22.8 KiB
Average record size in memory108.6 B

Variable types

Text4
Numeric4
Categorical3
DateTime2

Dataset

Description제주특별자치도 서귀포시 관내 공동주택 현황에 관한 데이터로 명칭, 도로명주소, 지번주소, 위도, 경도, 세대수 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/3083845/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates
세대수 is highly overall correlated with 동수High correlation
동수 is highly overall correlated with 세대수High correlation
명칭 has 6 (2.8%) missing valuesMissing
도로명주소 has 5 (2.3%) missing valuesMissing
승인년월일 has 3 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-03-16 04:17:59.853538
Analysis finished2024-03-16 04:18:05.475718
Duration5.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

MISSING 

Distinct207
Distinct (%)99.0%
Missing6
Missing (%)2.8%
Memory size1.8 KiB
2024-03-16T13:18:05.717690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length7.2727273
Min length3

Characters and Unicode

Total characters1520
Distinct characters246
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)98.1%

Sample

1st row천지연립주택
2nd row타운하우스
3rd row민우아파트
4th row남양맨션
5th row대일연립주택
ValueCountFrequency (%)
2차 3
 
1.2%
한빛테크놀즈 3
 
1.2%
제주영어교육도시캐논스빌리지 2
 
0.8%
파우제인제주 2
 
0.8%
공동주택 2
 
0.8%
휴마루 2
 
0.8%
호근동 2
 
0.8%
동홍 2
 
0.8%
타운하우스 2
 
0.8%
서강파인힐 2
 
0.8%
Other values (234) 235
91.4%
2024-03-16T13:18:06.373548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 80
 
5.3%
파 67
 
4.4%
트 64
 
4.2%
48
 
3.2%
주 45
 
3.0%
스 36
 
2.4%
빌 30
 
2.0%
리 29
 
1.9%
차 27
 
1.8%
동 25
 
1.6%
Other values (236) 1069
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1372
90.3%
Decimal Number 65
 
4.3%
Space Separator 48
 
3.2%
Uppercase Letter 9
 
0.6%
Open Punctuation 7
 
0.5%
Close Punctuation 7
 
0.5%
Dash Punctuation 4
 
0.3%
Lowercase Letter 4
 
0.3%
Letter Number 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 80
 
5.8%
파 67
 
4.9%
트 64
 
4.7%
주 45
 
3.3%
스 36
 
2.6%
빌 30
 
2.2%
리 29
 
2.1%
차 27
 
2.0%
동 25
 
1.8%
지 23
 
1.7%
Other values (210) 946
69.0%
Decimal Number
ValueCountFrequency (%)
2 19
29.2%
1 15
23.1%
3 8
12.3%
0 7
 
10.8%
5 5
 
7.7%
6 3
 
4.6%
8 3
 
4.6%
7 3
 
4.6%
4 2
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
L 2
22.2%
A 2
22.2%
P 1
11.1%
E 1
11.1%
H 1
11.1%
C 1
11.1%
G 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
u 1
25.0%
d 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1372
90.3%
Common 133
 
8.8%
Latin 15
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 80
 
5.8%
파 67
 
4.9%
트 64
 
4.7%
주 45
 
3.3%
스 36
 
2.6%
빌 30
 
2.2%
리 29
 
2.1%
차 27
 
2.0%
동 25
 
1.8%
지 23
 
1.7%
Other values (210) 946
69.0%
Common
ValueCountFrequency (%)
48
36.1%
2 19
 
14.3%
1 15
 
11.3%
3 8
 
6.0%
( 7
 
5.3%
0 7
 
5.3%
) 7
 
5.3%
5 5
 
3.8%
- 4
 
3.0%
6 3
 
2.3%
Other values (5) 10
 
7.5%
Latin
ValueCountFrequency (%)
L 2
13.3%
e 2
13.3%
A 2
13.3%
Ⅱ 2
13.3%
P 1
6.7%
E 1
6.7%
H 1
6.7%
C 1
6.7%
G 1
6.7%
u 1
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1372
90.3%
ASCII 146
 
9.6%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 80
 
5.8%
파 67
 
4.9%
트 64
 
4.7%
주 45
 
3.3%
스 36
 
2.6%
빌 30
 
2.2%
리 29
 
2.1%
차 27
 
2.0%
동 25
 
1.8%
지 23
 
1.7%
Other values (210) 946
69.0%
ASCII
ValueCountFrequency (%)
48
32.9%
2 19
 
13.0%
1 15
 
10.3%
3 8
 
5.5%
( 7
 
4.8%
0 7
 
4.8%
) 7
 
4.8%
5 5
 
3.4%
- 4
 
2.7%
6 3
 
2.1%
Other values (15) 23
15.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명주소
Text

MISSING 

Distinct208
Distinct (%)99.0%
Missing5
Missing (%)2.3%
Memory size1.8 KiB
2024-03-16T13:18:07.298084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length23.67619
Min length19

Characters and Unicode

Total characters4972
Distinct characters136
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)98.1%

Sample

1st row제주특별자치도 서귀포시 흙담솔로 17-6
2nd row제주특별자치도 서귀포시 천제연로208번길 16
3rd row제주특별자치도 서귀포시 홍중로 53-3
4th row제주특별자치도 서귀포시 동홍로72번길 8
5th row제주특별자치도 서귀포시 성산읍 고성중앙로 62-3
ValueCountFrequency (%)
제주특별자치도 210
23.3%
서귀포시 210
23.3%
대정읍 25
 
2.8%
안덕면 13
 
1.4%
성산읍 13
 
1.4%
홍중로 11
 
1.2%
10 8
 
0.9%
남원읍 6
 
0.7%
중산간동로 6
 
0.7%
표선면 5
 
0.6%
Other values (279) 394
43.7%
2024-03-16T13:18:08.208863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
691
 
13.9%
서 252
 
5.1%
시 219
 
4.4%
주 218
 
4.4%
제 217
 
4.4%
도 215
 
4.3%
귀 215
 
4.3%
포 213
 
4.3%
로 213
 
4.3%
치 210
 
4.2%
Other values (126) 2309
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3491
70.2%
Decimal Number 740
 
14.9%
Space Separator 691
 
13.9%
Dash Punctuation 50
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 252
 
7.2%
시 219
 
6.3%
주 218
 
6.2%
제 217
 
6.2%
도 215
 
6.2%
귀 215
 
6.2%
포 213
 
6.1%
로 213
 
6.1%
치 210
 
6.0%
자 210
 
6.0%
Other values (114) 1309
37.5%
Decimal Number
ValueCountFrequency (%)
1 145
19.6%
2 106
14.3%
5 74
10.0%
3 69
9.3%
6 64
8.6%
4 61
8.2%
8 60
8.1%
9 58
 
7.8%
0 56
 
7.6%
7 47
 
6.4%
Space Separator
ValueCountFrequency (%)
691
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3491
70.2%
Common 1481
29.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 252
 
7.2%
시 219
 
6.3%
주 218
 
6.2%
제 217
 
6.2%
도 215
 
6.2%
귀 215
 
6.2%
포 213
 
6.1%
로 213
 
6.1%
치 210
 
6.0%
자 210
 
6.0%
Other values (114) 1309
37.5%
Common
ValueCountFrequency (%)
691
46.7%
1 145
 
9.8%
2 106
 
7.2%
5 74
 
5.0%
3 69
 
4.7%
6 64
 
4.3%
4 61
 
4.1%
8 60
 
4.1%
9 58
 
3.9%
0 56
 
3.8%
Other values (2) 97
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3491
70.2%
ASCII 1481
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
691
46.7%
1 145
 
9.8%
2 106
 
7.2%
5 74
 
5.0%
3 69
 
4.7%
6 64
 
4.3%
4 61
 
4.1%
8 60
 
4.1%
9 58
 
3.9%
0 56
 
3.8%
Other values (2) 97
 
6.5%
Hangul
ValueCountFrequency (%)
서 252
 
7.2%
시 219
 
6.3%
주 218
 
6.2%
제 217
 
6.2%
도 215
 
6.2%
귀 215
 
6.2%
포 213
 
6.1%
로 213
 
6.1%
치 210
 
6.0%
자 210
 
6.0%
Other values (114) 1309
37.5%

지번주소
Text

Distinct213
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-16T13:18:08.824016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length22.8
Min length16

Characters and Unicode

Total characters4902
Distinct characters80
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)98.1%

Sample

1st row제주특별자치도 서귀포시 서홍동 327-1
2nd row제주특별자치도 서귀포시 중문동 2036
3rd row제주특별자치도 서귀포시 서홍동 349-2
4th row제주특별자치도 서귀포시 동홍동 482-1
5th row제주특별자치도 서귀포시 성산읍 고성리 1453
ValueCountFrequency (%)
제주특별자치도 215
23.2%
서귀포시 211
22.7%
동홍동 40
 
4.3%
서홍동 30
 
3.2%
대정읍 27
 
2.9%
강정동 17
 
1.8%
안덕면 14
 
1.5%
성산읍 14
 
1.5%
중문동 13
 
1.4%
보성리 9
 
1.0%
Other values (253) 338
36.4%
2024-03-16T13:18:09.961430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
713
 
14.5%
서 255
 
5.2%
도 216
 
4.4%
제 215
 
4.4%
포 215
 
4.4%
귀 215
 
4.4%
주 215
 
4.4%
치 215
 
4.4%
별 215
 
4.4%
특 215
 
4.4%
Other values (70) 2213
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3210
65.5%
Decimal Number 873
 
17.8%
Space Separator 713
 
14.5%
Dash Punctuation 106
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 255
 
7.9%
도 216
 
6.7%
제 215
 
6.7%
포 215
 
6.7%
귀 215
 
6.7%
주 215
 
6.7%
치 215
 
6.7%
별 215
 
6.7%
특 215
 
6.7%
자 215
 
6.7%
Other values (58) 1019
31.7%
Decimal Number
ValueCountFrequency (%)
1 204
23.4%
2 104
11.9%
5 86
9.9%
3 80
 
9.2%
4 76
 
8.7%
0 71
 
8.1%
9 71
 
8.1%
8 66
 
7.6%
7 64
 
7.3%
6 51
 
5.8%
Space Separator
ValueCountFrequency (%)
713
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3210
65.5%
Common 1692
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 255
 
7.9%
도 216
 
6.7%
제 215
 
6.7%
포 215
 
6.7%
귀 215
 
6.7%
주 215
 
6.7%
치 215
 
6.7%
별 215
 
6.7%
특 215
 
6.7%
자 215
 
6.7%
Other values (58) 1019
31.7%
Common
ValueCountFrequency (%)
713
42.1%
1 204
 
12.1%
- 106
 
6.3%
2 104
 
6.1%
5 86
 
5.1%
3 80
 
4.7%
4 76
 
4.5%
0 71
 
4.2%
9 71
 
4.2%
8 66
 
3.9%
Other values (2) 115
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3210
65.5%
ASCII 1692
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
713
42.1%
1 204
 
12.1%
- 106
 
6.3%
2 104
 
6.1%
5 86
 
5.1%
3 80
 
4.7%
4 76
 
4.5%
0 71
 
4.2%
9 71
 
4.2%
8 66
 
3.9%
Other values (2) 115
 
6.8%
Hangul
ValueCountFrequency (%)
서 255
 
7.9%
도 216
 
6.7%
제 215
 
6.7%
포 215
 
6.7%
귀 215
 
6.7%
주 215
 
6.7%
치 215
 
6.7%
별 215
 
6.7%
특 215
 
6.7%
자 215
 
6.7%
Other values (58) 1019
31.7%

위도
Real number (ℝ)

Distinct212
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.270075
Minimum33.216247
Maximum33.47211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-16T13:18:10.286702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.216247
5-th percentile33.227388
Q133.250832
median33.2575
Q333.265851
95-th percentile33.392089
Maximum33.47211
Range0.25586327
Interquartile range (IQR)0.015019855

Descriptive statistics

Standard deviation0.047261489
Coefficient of variation (CV)0.0014205405
Kurtosis8.543366
Mean33.270075
Median Absolute Deviation (MAD)0.00729446
Skewness2.9204945
Sum7153.0661
Variance0.0022336483
MonotonicityNot monotonic
2024-03-16T13:18:10.552342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.29548756 2
 
0.9%
33.22001692 2
 
0.9%
33.265716 2
 
0.9%
33.30276432 1
 
0.5%
33.2588436 1
 
0.5%
33.26237597 1
 
0.5%
33.28691522 1
 
0.5%
33.25132603 1
 
0.5%
33.381551 1
 
0.5%
33.24916474 1
 
0.5%
Other values (202) 202
94.0%
ValueCountFrequency (%)
33.21624671 1
0.5%
33.21975674 1
0.5%
33.22001692 2
0.9%
33.22021103 1
0.5%
33.22204804 1
0.5%
33.222745 1
0.5%
33.22284393 1
0.5%
33.22375305 1
0.5%
33.22409235 1
0.5%
33.22659808 1
0.5%
ValueCountFrequency (%)
33.47210998 1
0.5%
33.4637 1
0.5%
33.45032576 1
0.5%
33.450285 1
0.5%
33.44988625 1
0.5%
33.44985779 1
0.5%
33.44855999 1
0.5%
33.44711972 1
0.5%
33.445716 1
0.5%
33.44541927 1
0.5%

경도
Real number (ℝ)

Distinct212
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.51987
Minimum126.1768
Maximum126.9323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-16T13:18:10.800474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.1768
5-th percentile126.26006
Q1126.42961
median126.55471
Q3126.5721
95-th percentile126.85918
Maximum126.9323
Range0.7555
Interquartile range (IQR)0.1424919

Descriptive statistics

Standard deviation0.15963442
Coefficient of variation (CV)0.001261734
Kurtosis0.52009723
Mean126.51987
Median Absolute Deviation (MAD)0.0495454
Skewness0.41815995
Sum27201.772
Variance0.025483147
MonotonicityNot monotonic
2024-03-16T13:18:11.093646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.2884626 2
 
0.9%
126.2602703 2
 
0.9%
126.549222 2
 
0.9%
126.3358441 1
 
0.5%
126.5051661 1
 
0.5%
126.523882 1
 
0.5%
126.2803435 1
 
0.5%
126.5571821 1
 
0.5%
126.8787219 1
 
0.5%
126.3303696 1
 
0.5%
Other values (202) 202
94.0%
ValueCountFrequency (%)
126.1768 1
0.5%
126.2452133 1
0.5%
126.2470671 1
0.5%
126.2513411 1
0.5%
126.2523012 1
0.5%
126.255191 1
0.5%
126.2559324 1
0.5%
126.256613 1
0.5%
126.2576033 1
0.5%
126.2583464 1
0.5%
ValueCountFrequency (%)
126.9323 1
0.5%
126.915425 1
0.5%
126.9136208 1
0.5%
126.9130529 1
0.5%
126.9108039 1
0.5%
126.9092942 1
0.5%
126.9075361 1
0.5%
126.9051288 1
0.5%
126.8998541 1
0.5%
126.896875 1
0.5%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct110
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.56279
Minimum2
Maximum830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-16T13:18:11.354888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile14.8
Q140
median56
Q3100
95-th percentile429
Maximum830
Range828
Interquartile range (IQR)60

Descriptive statistics

Standard deviation139.26286
Coefficient of variation (CV)1.2827863
Kurtosis7.5779433
Mean108.56279
Median Absolute Deviation (MAD)24
Skewness2.6647454
Sum23341
Variance19394.144
MonotonicityNot monotonic
2024-03-16T13:18:11.710902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 9
 
4.2%
48 8
 
3.7%
64 8
 
3.7%
60 7
 
3.3%
32 7
 
3.3%
16 6
 
2.8%
46 6
 
2.8%
8 5
 
2.3%
72 5
 
2.3%
70 4
 
1.9%
Other values (100) 150
69.8%
ValueCountFrequency (%)
2 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
8 5
2.3%
9 1
 
0.5%
11 1
 
0.5%
12 1
 
0.5%
16 6
2.8%
18 4
1.9%
20 4
1.9%
ValueCountFrequency (%)
830 1
0.5%
716 1
0.5%
701 1
0.5%
602 1
0.5%
556 1
0.5%
548 2
0.9%
524 1
0.5%
499 1
0.5%
460 1
0.5%
450 1
0.5%

연면적(제곱미터)
Text

Distinct214
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-16T13:18:12.329428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.1302326
Min length4

Characters and Unicode

Total characters1533
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

Unique213 ?
Unique (%)99.1%

Sample

1st row1183.4
2nd row1625.54
3rd row5675.38
4th row6241.71
5th row1406.32
ValueCountFrequency (%)
6729.33 2
 
0.9%
8965.12 1
 
0.5%
6582.5233 1
 
0.5%
7808.5 1
 
0.5%
6060.17 1
 
0.5%
6199.44 1
 
0.5%
6165.4232 1
 
0.5%
57218 1
 
0.5%
2216.96 1
 
0.5%
2634.88 1
 
0.5%
Other values (204) 204
94.9%
2024-03-16T13:18:13.135680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 193
12.6%
4 163
10.6%
1 150
9.8%
6 147
9.6%
2 146
9.5%
3 144
9.4%
8 133
8.7%
9 125
8.2%
7 117
7.6%
5 116
7.6%
Other values (2) 99
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1326
86.5%
Other Punctuation 207
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 163
12.3%
1 150
11.3%
6 147
11.1%
2 146
11.0%
3 144
10.9%
8 133
10.0%
9 125
9.4%
7 117
8.8%
5 116
8.7%
0 85
6.4%
Other Punctuation
ValueCountFrequency (%)
. 193
93.2%
, 14
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1533
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 193
12.6%
4 163
10.6%
1 150
9.8%
6 147
9.6%
2 146
9.5%
3 144
9.4%
8 133
8.7%
9 125
8.2%
7 117
7.6%
5 116
7.6%
Other values (2) 99
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 193
12.6%
4 163
10.6%
1 150
9.8%
6 147
9.6%
2 146
9.5%
3 144
9.4%
8 133
8.7%
9 125
8.2%
7 117
7.6%
5 116
7.6%
Other values (2) 99
6.5%

층수
Categorical

Distinct30
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
지하1. 지상4
31 
지상4
30 
지하1. 지상7
25 
지상5
24 
지하1. 지상5
22 
Other values (25)
83 

Length

Max length9
Median length8
Mean length6.0790698
Min length3

Unique

Unique9 ?
Unique (%)4.2%

Sample

1st row지상2
2nd row지하1. 지상3
3rd row지하1. 지상5
4th row지하1. 지상5
5th row지상3

Common Values

ValueCountFrequency (%)
지하1. 지상4 31
14.4%
지상4 30
14.0%
지하1. 지상7 25
11.6%
지상5 24
11.2%
지하1. 지상5 22
10.2%
지하1.지상5 10
 
4.7%
지하1. 지상3 10
 
4.7%
지하1. 지상6 9
 
4.2%
지상7 8
 
3.7%
지하1. 지상9 7
 
3.3%
Other values (20) 39
18.1%

Length

2024-03-16T13:18:13.432499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지하1 114
34.0%
지상4 63
18.8%
지상5 46
13.7%
지상7 34
 
10.1%
지상3 14
 
4.2%
지하1.지상5 10
 
3.0%
지상9 10
 
3.0%
지상6 9
 
2.7%
지상10 8
 
2.4%
지하2 5
 
1.5%
Other values (11) 22
 
6.6%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6186047
Minimum0
Maximum47
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-16T13:18:13.659426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median3
Q36
95-th percentile14
Maximum47
Range47
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.6115392
Coefficient of variation (CV)1.2149858
Kurtosis21.09993
Mean4.6186047
Median Absolute Deviation (MAD)2
Skewness3.8331374
Sum993
Variance31.489372
MonotonicityNot monotonic
2024-03-16T13:18:13.896857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 56
26.0%
2 48
22.3%
4 23
10.7%
3 16
 
7.4%
6 12
 
5.6%
5 11
 
5.1%
9 9
 
4.2%
7 8
 
3.7%
8 8
 
3.7%
10 6
 
2.8%
Other values (14) 18
 
8.4%
ValueCountFrequency (%)
0 2
 
0.9%
1 56
26.0%
2 48
22.3%
3 16
 
7.4%
4 23
10.7%
5 11
 
5.1%
6 12
 
5.6%
7 8
 
3.7%
8 8
 
3.7%
9 9
 
4.2%
ValueCountFrequency (%)
47 1
 
0.5%
37 1
 
0.5%
29 1
 
0.5%
22 1
 
0.5%
20 1
 
0.5%
19 1
 
0.5%
17 1
 
0.5%
16 1
 
0.5%
15 1
 
0.5%
14 3
1.4%

승인년월일
Date

MISSING 

Distinct203
Distinct (%)95.8%
Missing3
Missing (%)1.4%
Memory size1.8 KiB
Minimum1983-12-02 00:00:00
Maximum2022-08-02 00:00:00
2024-03-16T13:18:14.141025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:14.378074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공년월일
Date

Distinct204
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1984-02-28 00:00:00
Maximum2023-12-20 00:00:00
2024-03-16T13:18:14.691141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:15.017143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

비고
Categorical

Distinct29
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
아파트
104 
연립
48 
단지형연립
15 
다세대주택
 
8
다세대
 
7
Other values (24)
33 

Length

Max length35
Median length3
Mean length3.9209302
Min length2

Unique

Unique20 ?
Unique (%)9.3%

Sample

1st row연립
2nd row연립
3rd row아파트
4th row연립
5th row연립

Common Values

ValueCountFrequency (%)
아파트 104
48.4%
연립 48
22.3%
단지형연립 15
 
7.0%
다세대주택 8
 
3.7%
다세대 7
 
3.3%
단지형다세대 5
 
2.3%
아파트30년임대 4
 
1.9%
연립.분양54.임대18 2
 
0.9%
연립주택 2
 
0.9%
아파트5년임대 1
 
0.5%
Other values (19) 19
 
8.8%

Length

2024-03-16T13:18:15.274639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아파트 104
47.3%
연립 49
22.3%
단지형연립 15
 
6.8%
다세대주택 9
 
4.1%
다세대 7
 
3.2%
단지형다세대 5
 
2.3%
아파트30년임대 4
 
1.8%
도시형생활주택(단지형다세대주택 2
 
0.9%
및 2
 
0.9%
연립주택 2
 
0.9%
Other values (20) 21
 
9.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-01-10
215 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-10
2nd row2024-01-10
3rd row2024-01-10
4th row2024-01-10
5th row2024-01-10

Common Values

ValueCountFrequency (%)
2024-01-10 215
100.0%

Length

2024-03-16T13:18:15.547181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:18:15.690368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-10 215
100.0%

Interactions

2024-03-16T13:18:03.976831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:01.915910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.575492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.229449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:04.126949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.061575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.693350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.377867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:04.360519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.292310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.833475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.555970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:04.589165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:02.436524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.025445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:03.685709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:18:15.814705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도세대수층수동수비고
위도1.0000.9130.0000.2490.3650.806
경도0.9131.0000.0000.2720.1070.536
세대수0.0000.0001.0000.6210.8240.760
층수0.2490.2720.6211.0000.0000.733
동수0.3650.1070.8240.0001.0000.714
비고0.8060.5360.7600.7330.7141.000
2024-03-16T13:18:16.031379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층수비고
층수1.0000.244
비고0.2441.000
2024-03-16T13:18:16.196619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도세대수동수층수비고
위도1.0000.412-0.0670.0510.0730.421
경도0.4121.000-0.036-0.1600.0810.209
세대수-0.067-0.0361.0000.6800.2330.369
동수0.051-0.1600.6801.0000.0000.359
층수0.0730.0810.2330.0001.0000.244
비고0.4210.2090.3690.3590.2441.000

Missing values

2024-03-16T13:18:04.780414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:18:05.085098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-16T13:18:05.343129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

명칭도로명주소지번주소위도경도세대수연면적(제곱미터)층수동수승인년월일준공년월일비고데이터기준일자
0천지연립주택제주특별자치도 서귀포시 흙담솔로 17-6제주특별자치도 서귀포시 서홍동 327-133.259807126.556809201183.4지상231983-12-021984-02-28연립2024-01-10
1타운하우스제주특별자치도 서귀포시 천제연로208번길 16제주특별자치도 서귀포시 중문동 203633.250323126.426495451625.54지하1. 지상321985-10-311986-07-30연립2024-01-10
2민우아파트제주특별자치도 서귀포시 홍중로 53-3제주특별자치도 서귀포시 서홍동 349-233.257227126.556234885675.38지하1. 지상531985-09-281986-09-03아파트2024-01-10
3남양맨션제주특별자치도 서귀포시 동홍로72번길 8제주특별자치도 서귀포시 동홍동 482-133.255459126.568399776241.71지하1. 지상531984-06-261987-04-21연립2024-01-10
4대일연립주택제주특별자치도 서귀포시 성산읍 고성중앙로 62-3제주특별자치도 서귀포시 성산읍 고성리 145333.44856126.909294241406.32지상34<NA>1987-12-28연립2024-01-10
5주공1차아파트제주특별자치도 서귀포시 동홍중앙로 10제주특별자치도 서귀포시 동홍동 14733.251609126.57211831014942지상591987-05-091988-10-14아파트2024-01-10
6신라호텔아파트제주특별자치도 서귀포시 홍중로 81제주특별자치도 서귀포시 서홍동 1592-233.259511126.555595604206.97지하1. 지상521989-01-251989-09-02아파트2024-01-10
7한라아파트제주특별자치도 서귀포시 동홍서로 82제주특별자치도 서귀포시 동홍동 49033.255694126.5705579810788.67지상541989-06-211990-03-03아파트2024-01-10
8세림아파트제주특별자치도 서귀포시 홍중로 75제주특별자치도 서귀포시 서홍동 344-333.259229126.555425606341.48지하1. 지상511989-07-041990-07-09아파트2024-01-10
9세기아파트(1차)제주특별자치도 서귀포시 태평로 549제주특별자치도 서귀포시 동홍동 139-133.25292126.57464917019473지하1. 지상561989-07-151990-09-22아파트2024-01-10
명칭도로명주소지번주소위도경도세대수연면적(제곱미터)층수동수승인년월일준공년월일비고데이터기준일자
205보목동 1087-5 임대주택 (보목마을회)제주특별자치도 서귀포시 마소물로 99제주특별자치도 서귀포시 보목동 1087-533.251103126.596359161,438.82지하1. 지상422021-06-042023-10-24다세대+창고시설2024-01-10
206더나인제주특별자치도 서귀포시 대정읍 글로벌에듀로 335제주특별자치도 서귀포시 대정읍 구억리 74833.281627126.28210593,342.32지하1. 지상422021-04-222023-12-20연립 및 다세대주택2024-01-10
207서홍빌리지제주특별자치도 서귀포시 서홍로 205-6제주특별자치도 서귀포시 서홍동 189133.265716126.549222181,383.65지상432021-04-212023-05-30도시형생활주택(단지형다세대주택)2024-01-10
208비바체빌제주특별자치도 서귀포시 일주동로 8355제주특별자치도 서귀포시 신효동 1476-133.259291126.595105161,668.15지하1. 지상412020-05-262023-08-14연립주택2024-01-10
209칸타빌 제주에듀제주특별자치도 서귀포시 대정읍 상모로 320제주특별자치도 서귀포시 대정읍 하모리 820-133.222745126.255191289,018.00지상1012019-12-102023-07-07아파트2024-01-10
210<NA>제주특별자치도 서귀포시 성산읍 풍천로192번길 37제주특별자치도 서귀포시 성산읍 신풍리 775-233.361237126.8383736457.51지상412019-07-192023-12-15다세대주택2024-01-10
211안덕면 서광리 1886-20 공동주택 (정정혜)제주특별자치도 서귀포시 안덕면 녹차분재로59번길 43-1제주특별자치도 서귀포시 안덕면 서광리 1886-2033.287635126.3009737777.48지하1. 지상412017-11-152023-09-05연립주택2024-01-10
212아이원캐슬제주특별자치도 서귀포시 중산간동로 8128-18제주특별자치도 서귀포시 서홍동 1870 외1필지33.265587126.54818404,824.83지하2. 지상462016-08-302023-10-30연립주택(도시형생활주택)2024-01-10
213호근동 1127-5 외2필지 공동주택제주특별자치도 서귀포시 중산간동로 8264제주특별자치도 서귀포시 호근동 1127-5 외2필지33.262423126.533739182,632.55지상432014-03-202023-10-06다세대주택1동+연립주택 2동2024-01-10
214이도PALACE주상복합제주특별자치도 서귀포시 서문로 59제주특별자치도 서귀포시 서귀동 323-15 외2필지33.248082126.557129366,944.70지하3. 지상712013-03-202023-10-30아파트2024-01-10

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0제주영어교육도시캐논스빌리지 2차제주특별자치도 서귀포시 대정읍 글로벌에듀로145번길 24제주특별자치도 서귀포시 대정읍 구억리 105833.295488126.288463726729.33지하1. 지상352011-08-252012-09-14연립.분양54.임대182024-01-102