Overview

Dataset statistics

Number of variables9
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory80.1 B

Variable types

Numeric5
Text3
DateTime1

Dataset

Description부산광역시 강서구 의무관리대상 공동주택 현황(아파트명, 주소, 세대수, 사용검사일자, 관리사무소전화번호)
Author부산광역시 강서구
URLhttps://www.data.go.kr/data/15026135/fileData.do

Alerts

동수 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 동수 and 1 other fieldsHigh correlation
세대수 is highly overall correlated with 연면적High correlation
연번 has unique valuesUnique
단지명 has unique valuesUnique
위치(새주소) has unique valuesUnique
연면적 has unique valuesUnique
세대수 has unique valuesUnique
관리사무소연락처 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:18:28.581149
Analysis finished2024-03-16 04:18:33.643298
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T13:18:33.742580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2024-03-16T13:18:33.965503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

단지명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-16T13:18:34.318347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length11.627907
Min length6

Characters and Unicode

Total characters500
Distinct characters132
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row퀸덤 1차 에디슨타운
2nd row퀸덤 1차 링컨타운
3rd row퀸덤 1차 아인슈타인
4th row명지 극동스타클래스
5th row명지 두산위브포세이돈
ValueCountFrequency (%)
명지 26
25.0%
1차 7
 
6.7%
금강펜테리움 4
 
3.8%
부산신호사랑으로부영 4
 
3.8%
2차 4
 
3.8%
지사 4
 
3.8%
센트럴파크 3
 
2.9%
퀸덤 3
 
2.9%
삼정그린코아 3
 
2.9%
3차 2
 
1.9%
Other values (40) 44
42.3%
2024-03-16T13:18:34.894357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
12.6%
지 35
 
7.0%
명 29
 
5.8%
차 14
 
2.8%
스 13
 
2.6%
사 8
 
1.6%
부 8
 
1.6%
더 7
 
1.4%
호 7
 
1.4%
리 7
 
1.4%
Other values (122) 309
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
79.4%
Space Separator 63
 
12.6%
Decimal Number 20
 
4.0%
Uppercase Letter 9
 
1.8%
Close Punctuation 5
 
1.0%
Open Punctuation 5
 
1.0%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 35
 
8.8%
명 29
 
7.3%
차 14
 
3.5%
스 13
 
3.3%
사 8
 
2.0%
부 8
 
2.0%
더 7
 
1.8%
호 7
 
1.8%
리 7
 
1.8%
움 7
 
1.8%
Other values (109) 262
66.0%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
2 6
30.0%
3 5
25.0%
4 1
 
5.0%
5 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S 4
44.4%
C 3
33.3%
D 1
 
11.1%
B 1
 
11.1%
Space Separator
ValueCountFrequency (%)
63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
79.4%
Common 93
 
18.6%
Latin 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 35
 
8.8%
명 29
 
7.3%
차 14
 
3.5%
스 13
 
3.3%
사 8
 
2.0%
부 8
 
2.0%
더 7
 
1.8%
호 7
 
1.8%
리 7
 
1.8%
움 7
 
1.8%
Other values (109) 262
66.0%
Common
ValueCountFrequency (%)
63
67.7%
1 7
 
7.5%
2 6
 
6.5%
) 5
 
5.4%
3 5
 
5.4%
( 5
 
5.4%
4 1
 
1.1%
5 1
 
1.1%
Latin
ValueCountFrequency (%)
S 4
40.0%
C 3
30.0%
e 1
 
10.0%
D 1
 
10.0%
B 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
79.4%
ASCII 103
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
61.2%
1 7
 
6.8%
2 6
 
5.8%
) 5
 
4.9%
3 5
 
4.9%
( 5
 
4.9%
S 4
 
3.9%
C 3
 
2.9%
4 1
 
1.0%
e 1
 
1.0%
Other values (3) 3
 
2.9%
Hangul
ValueCountFrequency (%)
지 35
 
8.8%
명 29
 
7.3%
차 14
 
3.5%
스 13
 
3.3%
사 8
 
2.0%
부 8
 
2.0%
더 7
 
1.8%
호 7
 
1.8%
리 7
 
1.8%
움 7
 
1.8%
Other values (109) 262
66.0%

위치(새주소)
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-16T13:18:35.421532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length38.744186
Min length26

Characters and Unicode

Total characters1666
Distinct characters145
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row부산광역시 강서구 명지오션시티10로 17 (명지동, 퀸덤1차아파트)
2nd row부산광역시 강서구 명지오션시티10로 16 (명지동, 퀸덤1차 링컨타운)
3rd row부산광역시 강서구 명지오션시티11로 51 (명지동, 퀸덤1차 아인슈타인타운)
4th row부산광역시 강서구 명지오션시티2로 71 (명지동, 극동스타클래스아파트)
5th row부산광역시 강서구 명지오션시티11로 22 (명지동, 명지두산위브포세이돈)
ValueCountFrequency (%)
부산광역시 43
 
15.5%
강서구 43
 
15.5%
명지동 29
 
10.5%
명지국제5로 11
 
4.0%
신호동 5
 
1.8%
명지국제7로 4
 
1.4%
더 3
 
1.1%
엘크루 3
 
1.1%
명지오션시티12로 3
 
1.1%
명지 3
 
1.1%
Other values (112) 130
46.9%
2024-03-16T13:18:36.146478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
253
 
15.2%
지 83
 
5.0%
명 73
 
4.4%
시 60
 
3.6%
산 59
 
3.5%
1 54
 
3.2%
부 52
 
3.1%
강 47
 
2.8%
로 46
 
2.8%
) 46
 
2.8%
Other values (135) 893
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1087
65.2%
Space Separator 253
 
15.2%
Decimal Number 181
 
10.9%
Close Punctuation 46
 
2.8%
Open Punctuation 46
 
2.8%
Other Punctuation 42
 
2.5%
Uppercase Letter 8
 
0.5%
Dash Punctuation 2
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 83
 
7.6%
명 73
 
6.7%
시 60
 
5.5%
산 59
 
5.4%
부 52
 
4.8%
강 47
 
4.3%
로 46
 
4.2%
동 44
 
4.0%
광 43
 
4.0%
역 43
 
4.0%
Other values (116) 537
49.4%
Decimal Number
ValueCountFrequency (%)
1 54
29.8%
2 27
14.9%
5 24
13.3%
3 20
 
11.0%
0 18
 
9.9%
7 11
 
6.1%
9 9
 
5.0%
4 8
 
4.4%
6 6
 
3.3%
8 4
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
50.0%
C 3
37.5%
D 1
 
12.5%
Space Separator
ValueCountFrequency (%)
253
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1087
65.2%
Common 570
34.2%
Latin 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 83
 
7.6%
명 73
 
6.7%
시 60
 
5.5%
산 59
 
5.4%
부 52
 
4.8%
강 47
 
4.3%
로 46
 
4.2%
동 44
 
4.0%
광 43
 
4.0%
역 43
 
4.0%
Other values (116) 537
49.4%
Common
ValueCountFrequency (%)
253
44.4%
1 54
 
9.5%
) 46
 
8.1%
( 46
 
8.1%
, 42
 
7.4%
2 27
 
4.7%
5 24
 
4.2%
3 20
 
3.5%
0 18
 
3.2%
7 11
 
1.9%
Other values (5) 29
 
5.1%
Latin
ValueCountFrequency (%)
S 4
44.4%
C 3
33.3%
e 1
 
11.1%
D 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1087
65.2%
ASCII 579
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
253
43.7%
1 54
 
9.3%
) 46
 
7.9%
( 46
 
7.9%
, 42
 
7.3%
2 27
 
4.7%
5 24
 
4.1%
3 20
 
3.5%
0 18
 
3.1%
7 11
 
1.9%
Other values (9) 38
 
6.6%
Hangul
ValueCountFrequency (%)
지 83
 
7.6%
명 73
 
6.7%
시 60
 
5.5%
산 59
 
5.4%
부 52
 
4.8%
강 47
 
4.3%
로 46
 
4.2%
동 44
 
4.0%
광 43
 
4.0%
역 43
 
4.0%
Other values (116) 537
49.4%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.813953
Minimum2
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T13:18:36.405194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q19
median13
Q316
95-th percentile20.9
Maximum29
Range27
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.7992439
Coefficient of variation (CV)0.45257257
Kurtosis1.1131107
Mean12.813953
Median Absolute Deviation (MAD)3
Skewness0.5447354
Sum551
Variance33.631229
MonotonicityNot monotonic
2024-03-16T13:18:36.780385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
16 6
14.0%
11 4
9.3%
13 4
9.3%
12 4
9.3%
8 4
9.3%
17 4
9.3%
14 3
 
7.0%
9 2
 
4.7%
2 2
 
4.7%
4 2
 
4.7%
Other values (7) 8
18.6%
ValueCountFrequency (%)
2 2
4.7%
4 2
4.7%
6 2
4.7%
8 4
9.3%
9 2
4.7%
10 1
 
2.3%
11 4
9.3%
12 4
9.3%
13 4
9.3%
14 3
7.0%
ValueCountFrequency (%)
29 1
 
2.3%
28 1
 
2.3%
21 1
 
2.3%
20 1
 
2.3%
19 1
 
2.3%
17 4
9.3%
16 6
14.0%
14 3
7.0%
13 4
9.3%
12 4
9.3%

층수
Real number (ℝ)

Distinct11
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.511628
Minimum4
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T13:18:37.013325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q115
median20
Q325
95-th percentile29.9
Maximum34
Range30
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.7307825
Coefficient of variation (CV)0.34496263
Kurtosis-0.3851845
Mean19.511628
Median Absolute Deviation (MAD)5
Skewness0.050588463
Sum839
Variance45.303433
MonotonicityNot monotonic
2024-03-16T13:18:37.254089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20 14
32.6%
15 9
20.9%
10 4
 
9.3%
25 4
 
9.3%
29 4
 
9.3%
11 2
 
4.7%
30 2
 
4.7%
21 1
 
2.3%
4 1
 
2.3%
27 1
 
2.3%
ValueCountFrequency (%)
4 1
 
2.3%
10 4
 
9.3%
11 2
 
4.7%
15 9
20.9%
20 14
32.6%
21 1
 
2.3%
25 4
 
9.3%
27 1
 
2.3%
29 4
 
9.3%
30 2
 
4.7%
ValueCountFrequency (%)
34 1
 
2.3%
30 2
 
4.7%
29 4
 
9.3%
27 1
 
2.3%
25 4
 
9.3%
21 1
 
2.3%
20 14
32.6%
15 9
20.9%
11 2
 
4.7%
10 4
 
9.3%

연면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137627.42
Minimum16771
Maximum291067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T13:18:37.477127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16771
5-th percentile48745.4
Q196790.5
median125631
Q3186185.5
95-th percentile240473.5
Maximum291067
Range274296
Interquartile range (IQR)89395

Descriptive statistics

Standard deviation59810.347
Coefficient of variation (CV)0.43458163
Kurtosis0.28914817
Mean137627.42
Median Absolute Deviation (MAD)36256
Skewness0.43117623
Sum5917979
Variance3.5772777 × 109
MonotonicityNot monotonic
2024-03-16T13:18:37.761363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
125631 1
 
2.3%
199392 1
 
2.3%
124866 1
 
2.3%
108526 1
 
2.3%
167134 1
 
2.3%
147792 1
 
2.3%
192716 1
 
2.3%
185079 1
 
2.3%
176136 1
 
2.3%
75729 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
16771 1
2.3%
25908 1
2.3%
45851 1
2.3%
74795 1
2.3%
75729 1
2.3%
76032 1
2.3%
90654 1
2.3%
92862 1
2.3%
93784 1
2.3%
94806 1
2.3%
ValueCountFrequency (%)
291067 1
2.3%
274224 1
2.3%
244670 1
2.3%
202705 1
2.3%
199392 1
2.3%
193776 1
2.3%
192716 1
2.3%
192500 1
2.3%
190251 1
2.3%
190077 1
2.3%

세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean882.97674
Minimum182
Maximum1664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T13:18:37.970628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182
5-th percentile255.2
Q1626
median908
Q31123
95-th percentile1504.1
Maximum1664
Range1482
Interquartile range (IQR)497

Descriptive statistics

Standard deviation385.5149
Coefficient of variation (CV)0.43660821
Kurtosis-0.80473008
Mean882.97674
Median Absolute Deviation (MAD)266
Skewness-0.053037653
Sum37968
Variance148621.74
MonotonicityNot monotonic
2024-03-16T13:18:38.150030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
652 1
 
2.3%
1102 1
 
2.3%
1013 1
 
2.3%
750 1
 
2.3%
1201 1
 
2.3%
1064 1
 
2.3%
1388 1
 
2.3%
1278 1
 
2.3%
1109 1
 
2.3%
961 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
182 1
2.3%
222 1
2.3%
252 1
2.3%
284 1
2.3%
375 1
2.3%
377 1
2.3%
414 1
2.3%
431 1
2.3%
480 1
2.3%
600 1
2.3%
ValueCountFrequency (%)
1664 1
2.3%
1530 1
2.3%
1515 1
2.3%
1406 1
2.3%
1388 1
2.3%
1278 1
2.3%
1277 1
2.3%
1256 1
2.3%
1210 1
2.3%
1201 1
2.3%

사용승인일
Date

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2005-11-07 00:00:00
Maximum2021-12-29 00:00:00
2024-03-16T13:18:38.389666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:38.654523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

관리사무소연락처
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-16T13:18:39.048192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters516
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

Unique43 ?
Unique (%)100.0%

Sample

1st row051-271-0541
2nd row051-271-7170
3rd row051-271-7781
4th row051-271-2142
5th row051-271-3787
ValueCountFrequency (%)
051-271-0541 1
 
2.3%
051-271-1202 1
 
2.3%
051-972-0555 1
 
2.3%
051-201-5923 1
 
2.3%
051-201-5976 1
 
2.3%
051-971-2563 1
 
2.3%
051-832-6111 1
 
2.3%
051-831-4560 1
 
2.3%
051-972-6996 1
 
2.3%
051-832-5121 1
 
2.3%
Other values (33) 33
76.7%
2024-03-16T13:18:39.714661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 91
17.6%
- 86
16.7%
0 69
13.4%
2 69
13.4%
5 64
12.4%
7 38
7.4%
9 23
 
4.5%
6 21
 
4.1%
8 20
 
3.9%
4 18
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 430
83.3%
Dash Punctuation 86
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91
21.2%
0 69
16.0%
2 69
16.0%
5 64
14.9%
7 38
8.8%
9 23
 
5.3%
6 21
 
4.9%
8 20
 
4.7%
4 18
 
4.2%
3 17
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 91
17.6%
- 86
16.7%
0 69
13.4%
2 69
13.4%
5 64
12.4%
7 38
7.4%
9 23
 
4.5%
6 21
 
4.1%
8 20
 
3.9%
4 18
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 91
17.6%
- 86
16.7%
0 69
13.4%
2 69
13.4%
5 64
12.4%
7 38
7.4%
9 23
 
4.5%
6 21
 
4.1%
8 20
 
3.9%
4 18
 
3.5%

Interactions

2024-03-16T13:18:32.232905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:29.309535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.054239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.772423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.522818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:32.383871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:29.453995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.190038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.897563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.662686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:32.522418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:29.578024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.325034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.058254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.783728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:32.693918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:29.759836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.491361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.210177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.972628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:32.831157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:29.875211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:30.615434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:31.349891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:18:32.099552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:18:39.895828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단지명위치(새주소)동수층수연면적세대수사용승인일관리사무소연락처
연번1.0001.0001.0000.5150.7300.5710.6800.9801.000
단지명1.0001.0001.0001.0001.0001.0001.0001.0001.000
위치(새주소)1.0001.0001.0001.0001.0001.0001.0001.0001.000
동수0.5151.0001.0001.0000.4230.3510.6290.9581.000
층수0.7301.0001.0000.4231.0000.6800.5050.8471.000
연면적0.5711.0001.0000.3510.6801.0000.6540.9791.000
세대수0.6801.0001.0000.6290.5050.6541.0000.8401.000
사용승인일0.9801.0001.0000.9580.8470.9790.8401.0001.000
관리사무소연락처1.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-16T13:18:40.165242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동수층수연면적세대수
연번1.000-0.4320.474-0.0460.067
동수-0.4321.000-0.4750.5310.480
층수0.474-0.4751.0000.2680.364
연면적-0.0460.5310.2681.0000.870
세대수0.0670.4800.3640.8701.000

Missing values

2024-03-16T13:18:33.403612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:18:33.582457image/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

연번단지명위치(새주소)동수층수연면적세대수사용승인일관리사무소연락처
01퀸덤 1차 에디슨타운부산광역시 강서구 명지오션시티10로 17 (명지동, 퀸덤1차아파트)11151256316522009-05-01051-271-0541
12퀸덤 1차 링컨타운부산광역시 강서구 명지오션시티10로 16 (명지동, 퀸덤1차 링컨타운)171519939211022009-05-01051-271-7170
23퀸덤 1차 아인슈타인부산광역시 강서구 명지오션시티11로 51 (명지동, 퀸덤1차 아인슈타인타운)171520270511122009-05-01051-271-7781
34명지 극동스타클래스부산광역시 강서구 명지오션시티2로 71 (명지동, 극동스타클래스아파트)211518729211242008-11-25051-271-2142
45명지 두산위브포세이돈부산광역시 강서구 명지오션시티11로 22 (명지동, 명지두산위브포세이돈)161519250012562013-03-15051-271-3787
56명지 엘크루솔마레(B3)부산광역시 강서구 명지오션시티12로 10 (명지동, 엘크루솔마레)1311747954802014-11-21051-271-3999
67명지 한신휴플러스부산광역시 강서구 명지오션시티1로 155 (명지동, 한신 휴플러스)29111269108412014-08-13051-271-2750
78명지 엘크루블루오션(C2)부산광역시 강서구 명지오션시티6로 33 (명지동, 엘크루 블루오션(C2))17101126644142012-06-29051-271-2262
89명지 엘크루블루오션(C3)부산광역시 강서구 명지오션시티12로 92 (명지동, 엘크루 블루오션(C3))14101076983752012-06-29051-271-2263
910명지 엘크루블루오션(C4)부산광역시 강서구 명지오션시티12로 120 (명지동, 엘크루 블루오션(C4))1310760322522012-06-29051-271-2264
연번단지명위치(새주소)동수층수연면적세대수사용승인일관리사무소연락처
3334명지 스위트팰리스부산광역시 강서구 명지국제5로 165 (명지동, 명지 스위트팰리스)12201244249082018-11-21051-201-0062
3435명지 중흥S클래스 더테라스부산광역시 강서구 명지국제13로38번길 11 (명지동, 중흥S클래스 더 테라스)164458512222019-01-25051-292-0573
3536명지 더 힐 시그니처부산광역시 강서구 명지국제7로 110 (명지동, 더 힐 시그니처)162024467012102019-01-28051-271-3577
3637명지 (대림)e편한세상부산광역시 강서구 명지국제2로 80 (명지동, e편한세상)427964733772019-02-25051-201-1231
3738명지 삼정그린코아 더 베스트부산광역시 강서구 명지국제3로 97 (명지동, 삼정그린코아 더 베스트)4301618874312019-09-17051-206-2920
3839화전 우방아이유쉘부산광역시 강서구 화전산단4로 74(화전동, 우방아이유쉘)162019025115152020-02-21051-974-1246
3940더샵 명지퍼스트월드 2단지부산광역시 강서구 명지국제7로 37(명지동, 더샵 명지퍼스트월드 2단지)113027422414062020-07-28051-293-2224
4041더샵 명지퍼스트월드3단지부산광역시 강서구 명지국제2로 41(명지동, 더샵 명지퍼스트월드 3단지)93429106715302020-07-28051-710-0802
4142공항마을 리베르하임부산광역시 강서구 공항앞길13번길 53 (대저2동)215259081822021-07-09051-984-0709
4243명지 행복주택부산광역시 강서구 르노삼성대로 255 (명지동)215167712842021-12-29051-294-8433