Overview

Dataset statistics

Number of variables10
Number of observations120
Missing cells6
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory86.1 B

Variable types

Numeric5
Text3
DateTime2

Dataset

Description부산광역시_기장군_공동주택현황_20231011
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3071925

Alerts

연번 is highly overall correlated with 연면적High correlation
층수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
동수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
세대수 is highly overall correlated with 층수 and 2 other fieldsHigh correlation
연면적 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
관리사무소 has 6 (5.0%) missing valuesMissing
연번 has unique valuesUnique
단지명 has unique valuesUnique
연면적 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:22:00.969632
Analysis finished2023-12-10 16:22:05.112015
Duration4.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.5
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:22:05.219961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q130.75
median60.5
Q390.25
95-th percentile114.05
Maximum120
Range119
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation34.785054
Coefficient of variation (CV)0.57495957
Kurtosis-1.2
Mean60.5
Median Absolute Deviation (MAD)30
Skewness0
Sum7260
Variance1210
MonotonicityStrictly increasing
2023-12-11T01:22:05.473039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
62 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%

단지명
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:22:05.806884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length9.0083333
Min length4

Characters and Unicode

Total characters1081
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st rowS&T대우사원아파트
2nd row한빛아파트 3단지
3rd row양산기장주공아파트
4th row한얼주택
5th row삼보맨션
ValueCountFrequency (%)
정관 21
 
10.8%
일광 8
 
4.1%
1단지 5
 
2.6%
2단지 4
 
2.1%
부전타워 4
 
2.1%
가화만사성 3
 
1.5%
2차 3
 
1.5%
한신더휴 2
 
1.0%
비스타 2
 
1.0%
전원그린맨션 2
 
1.0%
Other values (131) 141
72.3%
2023-12-11T01:22:06.785788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
7.0%
트 39
 
3.6%
아 36
 
3.3%
파 32
 
3.0%
이 27
 
2.5%
스 27
 
2.5%
정 27
 
2.5%
관 25
 
2.3%
지 25
 
2.3%
차 24
 
2.2%
Other values (171) 743
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 900
83.3%
Space Separator 76
 
7.0%
Decimal Number 53
 
4.9%
Open Punctuation 16
 
1.5%
Close Punctuation 16
 
1.5%
Uppercase Letter 16
 
1.5%
Other Punctuation 3
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 39
 
4.3%
아 36
 
4.0%
파 32
 
3.6%
이 27
 
3.0%
스 27
 
3.0%
정 27
 
3.0%
관 25
 
2.8%
지 25
 
2.8%
차 24
 
2.7%
빌 22
 
2.4%
Other values (148) 616
68.4%
Uppercase Letter
ValueCountFrequency (%)
T 3
18.8%
A 3
18.8%
L 2
12.5%
H 2
12.5%
P 2
12.5%
N 1
 
6.2%
C 1
 
6.2%
S 1
 
6.2%
B 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 19
35.8%
2 15
28.3%
3 6
 
11.3%
5 4
 
7.5%
0 4
 
7.5%
4 3
 
5.7%
7 1
 
1.9%
6 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 900
83.3%
Common 164
 
15.2%
Latin 17
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 39
 
4.3%
아 36
 
4.0%
파 32
 
3.6%
이 27
 
3.0%
스 27
 
3.0%
정 27
 
3.0%
관 25
 
2.8%
지 25
 
2.8%
차 24
 
2.7%
빌 22
 
2.4%
Other values (148) 616
68.4%
Common
ValueCountFrequency (%)
76
46.3%
1 19
 
11.6%
( 16
 
9.8%
) 16
 
9.8%
2 15
 
9.1%
3 6
 
3.7%
5 4
 
2.4%
0 4
 
2.4%
4 3
 
1.8%
/ 2
 
1.2%
Other values (3) 3
 
1.8%
Latin
ValueCountFrequency (%)
T 3
17.6%
A 3
17.6%
L 2
11.8%
H 2
11.8%
P 2
11.8%
N 1
 
5.9%
C 1
 
5.9%
e 1
 
5.9%
S 1
 
5.9%
B 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 900
83.3%
ASCII 181
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
42.0%
1 19
 
10.5%
( 16
 
8.8%
) 16
 
8.8%
2 15
 
8.3%
3 6
 
3.3%
5 4
 
2.2%
0 4
 
2.2%
T 3
 
1.7%
4 3
 
1.7%
Other values (13) 19
 
10.5%
Hangul
ValueCountFrequency (%)
트 39
 
4.3%
아 36
 
4.0%
파 32
 
3.6%
이 27
 
3.0%
스 27
 
3.0%
정 27
 
3.0%
관 25
 
2.8%
지 25
 
2.8%
차 24
 
2.7%
빌 22
 
2.4%
Other values (148) 616
68.4%

소재지
Text

Distinct116
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:22:07.174956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length12.166667
Min length6

Characters and Unicode

Total characters1460
Distinct characters70
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

Unique114 ?
Unique (%)95.0%

Sample

1st row철마면 여락송정로 363
2nd row장안읍 천산로 28
3rd row기장읍 대청로35번길 49
4th row기장읍 무양2길 23-14
5th row일광읍 이천4길 16
ValueCountFrequency (%)
기장읍 55
 
15.3%
정관읍 34
 
9.5%
일광읍 20
 
5.6%
23 7
 
1.9%
28 6
 
1.7%
정관로 6
 
1.7%
장안읍 5
 
1.4%
천산로 4
 
1.1%
51 4
 
1.1%
7 4
 
1.1%
Other values (145) 214
59.6%
2023-12-11T01:22:07.740503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
16.4%
읍 114
 
7.8%
로 103
 
7.1%
1 79
 
5.4%
장 65
 
4.5%
기 60
 
4.1%
2 60
 
4.1%
정 56
 
3.8%
3 55
 
3.8%
4 55
 
3.8%
Other values (60) 574
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 803
55.0%
Decimal Number 397
27.2%
Space Separator 239
 
16.4%
Dash Punctuation 21
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
읍 114
14.2%
로 103
12.8%
장 65
 
8.1%
기 60
 
7.5%
정 56
 
7.0%
관 54
 
6.7%
길 37
 
4.6%
성 35
 
4.4%
차 35
 
4.4%
번 28
 
3.5%
Other values (48) 216
26.9%
Decimal Number
ValueCountFrequency (%)
1 79
19.9%
2 60
15.1%
3 55
13.9%
4 55
13.9%
6 40
10.1%
5 30
 
7.6%
8 25
 
6.3%
7 23
 
5.8%
0 16
 
4.0%
9 14
 
3.5%
Space Separator
ValueCountFrequency (%)
239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 803
55.0%
Common 657
45.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
읍 114
14.2%
로 103
12.8%
장 65
 
8.1%
기 60
 
7.5%
정 56
 
7.0%
관 54
 
6.7%
길 37
 
4.6%
성 35
 
4.4%
차 35
 
4.4%
번 28
 
3.5%
Other values (48) 216
26.9%
Common
ValueCountFrequency (%)
239
36.4%
1 79
 
12.0%
2 60
 
9.1%
3 55
 
8.4%
4 55
 
8.4%
6 40
 
6.1%
5 30
 
4.6%
8 25
 
3.8%
7 23
 
3.5%
- 21
 
3.2%
Other values (2) 30
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 803
55.0%
ASCII 657
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
36.4%
1 79
 
12.0%
2 60
 
9.1%
3 55
 
8.4%
4 55
 
8.4%
6 40
 
6.1%
5 30
 
4.6%
8 25
 
3.8%
7 23
 
3.5%
- 21
 
3.2%
Other values (2) 30
 
4.6%
Hangul
ValueCountFrequency (%)
읍 114
14.2%
로 103
12.8%
장 65
 
8.1%
기 60
 
7.5%
정 56
 
7.0%
관 54
 
6.7%
길 37
 
4.6%
성 35
 
4.4%
차 35
 
4.4%
번 28
 
3.5%
Other values (48) 216
26.9%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.058333
Minimum3
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:22:07.926936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q110.75
median15
Q320
95-th percentile29
Maximum31
Range28
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation7.0261167
Coefficient of variation (CV)0.46659325
Kurtosis-0.46067529
Mean15.058333
Median Absolute Deviation (MAD)5
Skewness0.19540241
Sum1807
Variance49.366317
MonotonicityNot monotonic
2023-12-11T01:22:08.098443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
15 39
32.5%
20 14
 
11.7%
6 9
 
7.5%
25 7
 
5.8%
5 7
 
5.8%
4 6
 
5.0%
29 5
 
4.2%
19 4
 
3.3%
11 4
 
3.3%
14 3
 
2.5%
Other values (13) 22
18.3%
ValueCountFrequency (%)
3 2
 
1.7%
4 6
5.0%
5 7
5.8%
6 9
7.5%
7 1
 
0.8%
8 1
 
0.8%
9 2
 
1.7%
10 2
 
1.7%
11 4
3.3%
12 2
 
1.7%
ValueCountFrequency (%)
31 2
 
1.7%
29 5
 
4.2%
26 3
 
2.5%
25 7
5.8%
23 1
 
0.8%
22 1
 
0.8%
20 14
11.7%
19 4
 
3.3%
18 2
 
1.7%
17 1
 
0.8%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.575
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:22:08.260727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q310.25
95-th percentile17
Maximum20
Range19
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation5.5951097
Coefficient of variation (CV)0.85096725
Kurtosis-0.70351894
Mean6.575
Median Absolute Deviation (MAD)5
Skewness0.67993069
Sum789
Variance31.305252
MonotonicityNot monotonic
2023-12-11T01:22:08.442366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 35
29.2%
2 13
 
10.8%
8 12
 
10.0%
6 6
 
5.0%
10 5
 
4.2%
12 5
 
4.2%
3 5
 
4.2%
5 4
 
3.3%
9 4
 
3.3%
11 4
 
3.3%
Other values (10) 27
22.5%
ValueCountFrequency (%)
1 35
29.2%
2 13
 
10.8%
3 5
 
4.2%
4 2
 
1.7%
5 4
 
3.3%
6 6
 
5.0%
7 4
 
3.3%
8 12
 
10.0%
9 4
 
3.3%
10 5
 
4.2%
ValueCountFrequency (%)
20 1
 
0.8%
19 3
2.5%
18 1
 
0.8%
17 3
2.5%
16 4
3.3%
15 3
2.5%
14 2
 
1.7%
13 4
3.3%
12 5
4.2%
11 4
3.3%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct112
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451.66667
Minimum28
Maximum1934
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:22:08.653339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile37
Q198
median278
Q3708.5
95-th percentile1251.6
Maximum1934
Range1906
Interquartile range (IQR)610.5

Descriptive statistics

Standard deviation428.63715
Coefficient of variation (CV)0.94901213
Kurtosis1.0548612
Mean451.66667
Median Absolute Deviation (MAD)218.5
Skewness1.2007764
Sum54200
Variance183729.8
MonotonicityNot monotonic
2023-12-11T01:22:08.877860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 3
 
2.5%
90 2
 
1.7%
45 2
 
1.7%
64 2
 
1.7%
228 2
 
1.7%
148 2
 
1.7%
98 2
 
1.7%
220 1
 
0.8%
1035 1
 
0.8%
182 1
 
0.8%
Other values (102) 102
85.0%
ValueCountFrequency (%)
28 1
 
0.8%
30 1
 
0.8%
31 1
 
0.8%
36 1
 
0.8%
37 3
2.5%
42 1
 
0.8%
44 1
 
0.8%
45 2
1.7%
46 1
 
0.8%
48 1
 
0.8%
ValueCountFrequency (%)
1934 1
0.8%
1758 1
0.8%
1638 1
0.8%
1533 1
0.8%
1500 1
0.8%
1301 1
0.8%
1249 1
0.8%
1131 1
0.8%
1128 1
0.8%
1084 1
0.8%

연면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55914.999
Minimum1577
Maximum239418.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:22:09.136769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1577
5-th percentile3394.453
Q19026.015
median31779.605
Q383438.25
95-th percentile162044.29
Maximum239418.48
Range237841.48
Interquartile range (IQR)74412.235

Descriptive statistics

Standard deviation57182.401
Coefficient of variation (CV)1.0226666
Kurtosis0.90917672
Mean55914.999
Median Absolute Deviation (MAD)28047.105
Skewness1.1903387
Sum6709799.9
Variance3.269827 × 109
MonotonicityNot monotonic
2023-12-11T01:22:09.356447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15272.0 1
 
0.8%
82981.0 1
 
0.8%
55089.0 1
 
0.8%
26721.1 1
 
0.8%
6806.37 1
 
0.8%
161679.99 1
 
0.8%
14346.66 1
 
0.8%
62775.7 1
 
0.8%
7015.82 1
 
0.8%
10274.78 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
1577.0 1
0.8%
1728.0 1
0.8%
1854.0 1
0.8%
2061.0 1
0.8%
3274.29 1
0.8%
3346.06 1
0.8%
3397.0 1
0.8%
3402.0 1
0.8%
3620.24 1
0.8%
3688.0 1
0.8%
ValueCountFrequency (%)
239418.48 1
0.8%
231690.53 1
0.8%
227783.42 1
0.8%
192454.62 1
0.8%
187026.0 1
0.8%
168966.06 1
0.8%
161679.99 1
0.8%
155550.31 1
0.8%
154009.0 1
0.8%
152713.0 1
0.8%

사업승인일
Date

Distinct112
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1970-01-01 00:00:00
Maximum2019-12-09 00:00:00
2023-12-11T01:22:09.600065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:09.846290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용검사일
Date

Distinct111
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1974-08-08 00:00:00
Maximum2023-03-24 00:00:00
2023-12-11T01:22:10.055734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:10.235622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리사무소
Text

MISSING 

Distinct108
Distinct (%)94.7%
Missing6
Missing (%)5.0%
Memory size1.1 KiB
2023-12-11T01:22:10.523013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008772
Min length12

Characters and Unicode

Total characters1369
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

Unique103 ?
Unique (%)90.4%

Sample

1st row051-509-2257
2nd row051-726-4712
3rd row051-721-5494
4th row051-721-7097
5th row051-721-3344
ValueCountFrequency (%)
051-726-4712 3
 
2.6%
051-722-6422 2
 
1.8%
051-721-7862 2
 
1.8%
051-714-3280 2
 
1.8%
051-721-0522 2
 
1.8%
051-724-5509 1
 
0.9%
051-724-7713 1
 
0.9%
051-728-6338 1
 
0.9%
051-723-2243 1
 
0.9%
051-721-5592 1
 
0.9%
Other values (98) 98
86.0%
2023-12-11T01:22:10.882354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 228
16.7%
7 191
14.0%
2 188
13.7%
1 180
13.1%
0 174
12.7%
5 149
10.9%
8 64
 
4.7%
4 61
 
4.5%
3 53
 
3.9%
6 44
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1141
83.3%
Dash Punctuation 228
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 191
16.7%
2 188
16.5%
1 180
15.8%
0 174
15.2%
5 149
13.1%
8 64
 
5.6%
4 61
 
5.3%
3 53
 
4.6%
6 44
 
3.9%
9 37
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 228
16.7%
7 191
14.0%
2 188
13.7%
1 180
13.1%
0 174
12.7%
5 149
10.9%
8 64
 
4.7%
4 61
 
4.5%
3 53
 
3.9%
6 44
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 228
16.7%
7 191
14.0%
2 188
13.7%
1 180
13.1%
0 174
12.7%
5 149
10.9%
8 64
 
4.7%
4 61
 
4.5%
3 53
 
3.9%
6 44
 
3.2%

Interactions

2023-12-11T01:22:04.208058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:01.468396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.161784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.861636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.524645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:04.298253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:01.604856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.305125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.987451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.678949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:04.394117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:01.731948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.435383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.116219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.792008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:04.510419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:01.867929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.604729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.264518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.954948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:04.637173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.015031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:02.739402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:03.400024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:04.076296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:22:10.968207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적
연번1.0000.7700.5510.4290.677
층수0.7701.0000.4350.3920.641
동수0.5510.4351.0000.8520.861
세대수0.4290.3920.8521.0000.919
연면적0.6770.6410.8610.9191.000
2023-12-11T01:22:11.061608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적
연번1.0000.4180.3780.4260.502
층수0.4181.0000.1880.5470.618
동수0.3780.1881.0000.8500.830
세대수0.4260.5470.8501.0000.950
연면적0.5020.6180.8300.9501.000

Missing values

2023-12-11T01:22:04.812528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:22:05.035208image/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.

Sample

연번단지명소재지층수동수세대수연면적사업승인일사용검사일관리사무소
01S&T대우사원아파트철마면 여락송정로 3634825615272.01970-01-011974-08-08051-509-2257
12한빛아파트 3단지장안읍 천산로 284121924916.01970-01-011979-01-01051-726-4712
23양산기장주공아파트기장읍 대청로35번길 49541406949.01970-01-011985-10-15051-721-5494
34한얼주택기장읍 무양2길 23-1432301728.01986-08-081986-12-23051-721-7097
45삼보맨션일광읍 이천4길 1651593397.01987-05-201988-02-05051-721-3344
56성림아파트정관읍 정관로 744-4152704190.01989-05-271989-12-12051-728-7370
67서린에코빌아파트기장읍 차성로326번길 1962966599.01989-04-251989-12-22051-722-7324
78금강로즈맨션기장읍 차성동로31번길 2661361577.01989-07-241990-04-21051-724-1540
89재흥아파트정관읍 정관로 750-24521709321.01989-05-311990-05-31051-727-6133
910대진로얄타운기장읍 차성로326번길 915111610546.01989-07-311990-08-20051-721-1190
연번단지명소재지층수동수세대수연면적사업승인일사용검사일관리사무소
110111일광 한신더휴 센트럴포레 2단지일광읍 해빛3로 62268748109002.882017-08-012020-06-19051-722-8772
111112일광 대성베르힐일광읍 해빛5로 1425751880786.212018-01-092020-09-23051-723-8533
112113일광신도시 비스타 동원 2차일광읍 해송1로 333111917192454.622018-03-072020-12-30051-724-6661
113114기장 유림노르웨이숲기장읍 차성로436번길 4615216517393.612019-03-222021-10-07051-724-1808
114115이지더원2차 포레온(임대)일광읍 해빛5로 2629878696786.272017-11-102022-05-26051-723-5009
115116이지더원3차 메르센포레(임대)일광읍 해빛3로 43-129541267591.572017-11-102022-05-26051-724-0117
116117부산청강 행복주택(임대)기장읍 대변로 43-11411308444.062018-12-272022-07-20051-724-1577
117118웨이브리즈(임대/일반 혼합)기장읍 대변로 43-125872894309.922019-09-302022-08-22051-723-4048
118119부산장안 LH 1단지장안읍 신좌천로 719342830016.212019-12-092022-10-19051-727-7890
119120금호 센트럴베이 행복주택 일광일광읍 해빛1로 6125899976623.592017-12-142023-03-24051-722-7007