Overview

Dataset statistics

Number of variables10
Number of observations107
Missing cells8
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory86.2 B

Variable types

Numeric5
Text3
DateTime2

Dataset

Description부산광역시기장군_공동주택현황_20190131_cng
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3071925

Alerts

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 층수 and 2 other fieldsHigh correlation
관리사무소 has 8 (7.5%) missing valuesMissing
연번 has unique valuesUnique
단지명 has unique valuesUnique
연면적 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:21:51.039696
Analysis finished2023-12-10 16:21:54.723123
Duration3.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:21:54.808917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2023-12-11T01:21:54.961400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%

단지명
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T01:21:55.183291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.3084112
Min length4

Characters and Unicode

Total characters889
Distinct characters169
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

Unique107 ?
Unique (%)100.0%

Sample

1st rowS&T대우사원아파트
2nd row한빛아파트 3단지
3rd row양산기장주공아파트
4th row한얼주택
5th row삼보맨션
ValueCountFrequency (%)
정관 21
 
13.3%
부전타워 4
 
2.5%
가화만사성 3
 
1.9%
일광 3
 
1.9%
2단지 3
 
1.9%
1단지 3
 
1.9%
이진 2
 
1.3%
동부산 2
 
1.3%
테마빌 2
 
1.3%
전원그린맨션 2
 
1.3%
Other values (110) 113
71.5%
2023-12-11T01:21:55.513021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
5.7%
트 36
 
4.0%
아 36
 
4.0%
파 32
 
3.6%
정 27
 
3.0%
스 25
 
2.8%
관 25
 
2.8%
빌 21
 
2.4%
이 21
 
2.4%
지 19
 
2.1%
Other values (159) 596
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 758
85.3%
Space Separator 51
 
5.7%
Decimal Number 44
 
4.9%
Uppercase Letter 14
 
1.6%
Open Punctuation 10
 
1.1%
Close Punctuation 10
 
1.1%
Lowercase Letter 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 36
 
4.7%
아 36
 
4.7%
파 32
 
4.2%
정 27
 
3.6%
스 25
 
3.3%
관 25
 
3.3%
빌 21
 
2.8%
이 21
 
2.8%
지 19
 
2.5%
동 18
 
2.4%
Other values (137) 498
65.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
21.4%
T 3
21.4%
P 2
14.3%
H 1
 
7.1%
N 1
 
7.1%
C 1
 
7.1%
L 1
 
7.1%
S 1
 
7.1%
B 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 14
31.8%
2 12
27.3%
3 5
 
11.4%
5 4
 
9.1%
0 4
 
9.1%
4 3
 
6.8%
7 1
 
2.3%
6 1
 
2.3%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 758
85.3%
Common 116
 
13.0%
Latin 15
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 36
 
4.7%
아 36
 
4.7%
파 32
 
4.2%
정 27
 
3.6%
스 25
 
3.3%
관 25
 
3.3%
빌 21
 
2.8%
이 21
 
2.8%
지 19
 
2.5%
동 18
 
2.4%
Other values (137) 498
65.7%
Common
ValueCountFrequency (%)
51
44.0%
1 14
 
12.1%
2 12
 
10.3%
( 10
 
8.6%
) 10
 
8.6%
3 5
 
4.3%
5 4
 
3.4%
0 4
 
3.4%
4 3
 
2.6%
7 1
 
0.9%
Other values (2) 2
 
1.7%
Latin
ValueCountFrequency (%)
A 3
20.0%
T 3
20.0%
P 2
13.3%
e 1
 
6.7%
H 1
 
6.7%
N 1
 
6.7%
C 1
 
6.7%
L 1
 
6.7%
S 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 758
85.3%
ASCII 131
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
38.9%
1 14
 
10.7%
2 12
 
9.2%
( 10
 
7.6%
) 10
 
7.6%
3 5
 
3.8%
5 4
 
3.1%
0 4
 
3.1%
A 3
 
2.3%
T 3
 
2.3%
Other values (12) 15
 
11.5%
Hangul
ValueCountFrequency (%)
트 36
 
4.7%
아 36
 
4.7%
파 32
 
4.2%
정 27
 
3.6%
스 25
 
3.3%
관 25
 
3.3%
빌 21
 
2.8%
이 21
 
2.8%
지 19
 
2.5%
동 18
 
2.4%
Other values (137) 498
65.7%

소재지
Text

Distinct104
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T01:21:55.813822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length12.196262
Min length6

Characters and Unicode

Total characters1305
Distinct characters68
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

Unique103 ?
Unique (%)96.3%

Sample

1st row철마면 여락송정로 363
2nd row장안읍 천산로 28
3rd row기장읍 대청로35번길 49
4th row기장읍 무양2길 23-14
5th row일광면 이천4길 16
ValueCountFrequency (%)
기장읍 52
 
16.4%
정관읍 34
 
10.7%
일광면 9
 
2.8%
23 7
 
2.2%
28 6
 
1.9%
정관로 6
 
1.9%
장안읍 4
 
1.3%
철마면 4
 
1.3%
천산로 4
 
1.3%
차성서로 4
 
1.3%
Other values (133) 188
59.1%
2023-12-11T01:21:56.271595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
16.3%
읍 90
 
6.9%
로 90
 
6.9%
1 70
 
5.4%
장 61
 
4.7%
기 57
 
4.4%
정 56
 
4.3%
2 55
 
4.2%
관 54
 
4.1%
4 47
 
3.6%
Other values (58) 512
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 716
54.9%
Decimal Number 358
27.4%
Space Separator 213
 
16.3%
Dash Punctuation 18
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
읍 90
12.6%
로 90
12.6%
장 61
 
8.5%
기 57
 
8.0%
정 56
 
7.8%
관 54
 
7.5%
길 36
 
5.0%
차 34
 
4.7%
성 34
 
4.7%
번 27
 
3.8%
Other values (46) 177
24.7%
Decimal Number
ValueCountFrequency (%)
1 70
19.6%
2 55
15.4%
4 47
13.1%
3 47
13.1%
6 34
9.5%
5 28
 
7.8%
8 25
 
7.0%
7 22
 
6.1%
0 16
 
4.5%
9 14
 
3.9%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 716
54.9%
Common 589
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
읍 90
12.6%
로 90
12.6%
장 61
 
8.5%
기 57
 
8.0%
정 56
 
7.8%
관 54
 
7.5%
길 36
 
5.0%
차 34
 
4.7%
성 34
 
4.7%
번 27
 
3.8%
Other values (46) 177
24.7%
Common
ValueCountFrequency (%)
213
36.2%
1 70
 
11.9%
2 55
 
9.3%
4 47
 
8.0%
3 47
 
8.0%
6 34
 
5.8%
5 28
 
4.8%
8 25
 
4.2%
7 22
 
3.7%
- 18
 
3.1%
Other values (2) 30
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 716
54.9%
ASCII 589
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
36.2%
1 70
 
11.9%
2 55
 
9.3%
4 47
 
8.0%
3 47
 
8.0%
6 34
 
5.8%
5 28
 
4.8%
8 25
 
4.2%
7 22
 
3.7%
- 18
 
3.1%
Other values (2) 30
 
5.1%
Hangul
ValueCountFrequency (%)
읍 90
12.6%
로 90
12.6%
장 61
 
8.5%
기 57
 
8.0%
정 56
 
7.8%
관 54
 
7.5%
길 36
 
5.0%
차 34
 
4.7%
성 34
 
4.7%
번 27
 
3.8%
Other values (46) 177
24.7%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.88785
Minimum3
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:21:56.398933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q19
median15
Q318
95-th percentile25
Maximum29
Range26
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.2635922
Coefficient of variation (CV)0.45101236
Kurtosis-0.36050526
Mean13.88785
Median Absolute Deviation (MAD)4
Skewness0.087841001
Sum1486
Variance39.232587
MonotonicityNot monotonic
2023-12-11T01:21:56.560360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
15 38
35.5%
20 14
 
13.1%
6 9
 
8.4%
5 7
 
6.5%
4 6
 
5.6%
11 4
 
3.7%
25 4
 
3.7%
29 3
 
2.8%
19 3
 
2.8%
13 2
 
1.9%
Other values (11) 17
15.9%
ValueCountFrequency (%)
3 2
 
1.9%
4 6
5.6%
5 7
6.5%
6 9
8.4%
7 1
 
0.9%
8 1
 
0.9%
9 2
 
1.9%
10 2
 
1.9%
11 4
3.7%
12 2
 
1.9%
ValueCountFrequency (%)
29 3
 
2.8%
25 4
 
3.7%
23 1
 
0.9%
22 1
 
0.9%
20 14
 
13.1%
19 3
 
2.8%
18 2
 
1.9%
17 1
 
0.9%
15 38
35.5%
14 2
 
1.9%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6074766
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:21:56.724972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q311
95-th percentile17
Maximum20
Range19
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.8499428
Coefficient of variation (CV)0.88535202
Kurtosis-0.87544132
Mean6.6074766
Median Absolute Deviation (MAD)4
Skewness0.66269962
Sum707
Variance34.22183
MonotonicityNot monotonic
2023-12-11T01:21:56.867037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 34
31.8%
2 12
 
11.2%
8 7
 
6.5%
10 5
 
4.7%
12 5
 
4.7%
6 5
 
4.7%
16 4
 
3.7%
13 4
 
3.7%
3 4
 
3.7%
9 4
 
3.7%
Other values (10) 23
21.5%
ValueCountFrequency (%)
1 34
31.8%
2 12
 
11.2%
3 4
 
3.7%
4 2
 
1.9%
5 3
 
2.8%
6 5
 
4.7%
7 2
 
1.9%
8 7
 
6.5%
9 4
 
3.7%
10 5
 
4.7%
ValueCountFrequency (%)
20 1
 
0.9%
19 3
2.8%
18 1
 
0.9%
17 3
2.8%
16 4
3.7%
15 3
2.8%
14 2
 
1.9%
13 4
3.7%
12 5
4.7%
11 3
2.8%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean434.25234
Minimum28
Maximum1934
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:21:57.066822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile37
Q190
median239
Q3672.5
95-th percentile1285.4
Maximum1934
Range1906
Interquartile range (IQR)582.5

Descriptive statistics

Standard deviation442.27952
Coefficient of variation (CV)1.0184851
Kurtosis1.1876673
Mean434.25234
Median Absolute Deviation (MAD)194
Skewness1.3148243
Sum46465
Variance195611.17
MonotonicityNot monotonic
2023-12-11T01:21:57.548428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37 3
 
2.8%
45 2
 
1.9%
90 2
 
1.9%
98 2
 
1.9%
228 2
 
1.9%
64 2
 
1.9%
148 2
 
1.9%
1758 1
 
0.9%
756 1
 
0.9%
256 1
 
0.9%
Other values (89) 89
83.2%
ValueCountFrequency (%)
28 1
 
0.9%
30 1
 
0.9%
31 1
 
0.9%
36 1
 
0.9%
37 3
2.8%
42 1
 
0.9%
44 1
 
0.9%
45 2
1.9%
46 1
 
0.9%
48 1
 
0.9%
ValueCountFrequency (%)
1934 1
0.9%
1758 1
0.9%
1638 1
0.9%
1533 1
0.9%
1500 1
0.9%
1301 1
0.9%
1249 1
0.9%
1131 1
0.9%
1128 1
0.9%
1084 1
0.9%

연면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52609.048
Minimum1577
Maximum239418.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:21:57.748630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1577
5-th percentile3361.342
Q16982.41
median26721.1
Q382435.485
95-th percentile159841.09
Maximum239418.48
Range237841.48
Interquartile range (IQR)75453.075

Descriptive statistics

Standard deviation57334.784
Coefficient of variation (CV)1.0898274
Kurtosis1.264744
Mean52609.048
Median Absolute Deviation (MAD)23033.1
Skewness1.3305788
Sum5629168.1
Variance3.2872775 × 109
MonotonicityNot monotonic
2023-12-11T01:21:57.887143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15272.0 1
 
0.9%
129960.24 1
 
0.9%
70448.6 1
 
0.9%
93682.9 1
 
0.9%
95202.25 1
 
0.9%
231690.53 1
 
0.9%
168966.06 1
 
0.9%
133233.0 1
 
0.9%
187026.0 1
 
0.9%
239418.48 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1577.0 1
0.9%
1728.0 1
0.9%
1854.0 1
0.9%
2061.0 1
0.9%
3274.0 1
0.9%
3346.06 1
0.9%
3397.0 1
0.9%
3402.0 1
0.9%
3620.24 1
0.9%
3688.0 1
0.9%
ValueCountFrequency (%)
239418.48 1
0.9%
231690.53 1
0.9%
227783.42 1
0.9%
187026.0 1
0.9%
168966.06 1
0.9%
161679.99 1
0.9%
155550.3075 1
0.9%
154009.0 1
0.9%
152713.0 1
0.9%
144279.0 1
0.9%

사업승인일
Date

Distinct101
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size988.0 B
Minimum1970-01-01 00:00:00
Maximum2017-05-02 00:00:00
2023-12-11T01:21:58.077193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:58.227284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용검사일
Date

Distinct100
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size988.0 B
Minimum1974-08-08 00:00:00
Maximum2020-01-23 00:00:00
2023-12-11T01:21:58.369501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:58.549697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리사무소
Text

MISSING 

Distinct94
Distinct (%)94.9%
Missing8
Missing (%)7.5%
Memory size988.0 B
2023-12-11T01:21:58.860044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010101
Min length12

Characters and Unicode

Total characters1189
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

Unique90 ?
Unique (%)90.9%

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
 
3.0%
051-722-6422 2
 
2.0%
051-721-0522 2
 
2.0%
051-714-3280 2
 
2.0%
051-728-6993 1
 
1.0%
051-728-6771 1
 
1.0%
051-728-7831 1
 
1.0%
051-727-1028 1
 
1.0%
051-728-8612 1
 
1.0%
051-728-2910 1
 
1.0%
Other values (84) 84
84.8%
2023-12-11T01:21:59.287150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 198
16.7%
2 166
14.0%
7 164
13.8%
1 156
13.1%
0 148
12.4%
5 131
11.0%
4 53
 
4.5%
8 53
 
4.5%
3 48
 
4.0%
6 38
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 991
83.3%
Dash Punctuation 198
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 166
16.8%
7 164
16.5%
1 156
15.7%
0 148
14.9%
5 131
13.2%
4 53
 
5.3%
8 53
 
5.3%
3 48
 
4.8%
6 38
 
3.8%
9 34
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1189
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 198
16.7%
2 166
14.0%
7 164
13.8%
1 156
13.1%
0 148
12.4%
5 131
11.0%
4 53
 
4.5%
8 53
 
4.5%
3 48
 
4.0%
6 38
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1189
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 198
16.7%
2 166
14.0%
7 164
13.8%
1 156
13.1%
0 148
12.4%
5 131
11.0%
4 53
 
4.5%
8 53
 
4.5%
3 48
 
4.0%
6 38
 
3.2%

Interactions

2023-12-11T01:21:53.813157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:51.744795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.237200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.711218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.259006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.898060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:51.826896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.325627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.820901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.384427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.997893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:51.929322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.423476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.915035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.500120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:54.187958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.044773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.516362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.016362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.606069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:54.352759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.137720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:52.609155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.136968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:21:53.725359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:21:59.407544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적사용검사일관리사무소
연번1.0000.6910.2520.3730.3520.9970.985
층수0.6911.0000.0980.0000.4180.9720.948
동수0.2520.0981.0000.8390.7420.9020.886
세대수0.3730.0000.8391.0000.8350.8170.980
연면적0.3520.4180.7420.8351.0000.0000.917
사용검사일0.9970.9720.9020.8170.0001.0000.996
관리사무소0.9850.9480.8860.9800.9170.9961.000
2023-12-11T01:21:59.568455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적
연번1.0000.2600.4330.3970.487
층수0.2601.0000.1540.5060.574
동수0.4330.1541.0000.8530.834
세대수0.3970.5060.8531.0000.955
연면적0.4870.5740.8340.9551.000

Missing values

2023-12-11T01:21:54.514716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:21:54.655751image/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
45삼보맨션일광면 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
9798경보이리스힐아파트기장읍 교리 368111373787.02016-02-022017-10-11051-724-3383
9899경보그랜드비치기장읍 대변리 440-218211714257.02013-04-082018-01-25051-723-3500
99100파스텔라타운하우스정관읍 방곡리 437466614222.02014-01-162018-02-28<NA>
100101두산위브더테라스정관읍 달산리 124451627239475.02016-07-122018-05-31051-727-5212
101102가화테라스2차정관읍 방곡리 40561439666272.02015-10-282018-06-01051-727-7263
102103행복리치빌기장읍 대라리 90591373274.02017-04-282018-12-03<NA>
103104정관 행복주택기장군 정관읍 정관1로 5115585651015.632015-12-152018-12-18051-728-5851
104105일광 자이푸르지오 1단지해빛로 39-1529548874320.15982017-05-022020-01-22051-714-3280
105106일광 자이푸르지오 2단지해빛로 2929111059155550.30752017-05-022020-01-22051-714-3280
106107e편한세상 일광일광면 해빛2로 212910913133068.63282017-05-022020-01-23051-721-9885