Overview

Dataset statistics

Number of variables9
Number of observations218
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory77.6 B

Variable types

Numeric5
Text3
DateTime1

Dataset

Description부산광역시_서구_공동주택현황_20200519
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3078634

Alerts

층수 is highly overall correlated with 세대수 and 1 other fieldsHigh correlation
동수 is highly overall correlated with 세대수 High correlation
세대수 is highly overall correlated with 층수 and 2 other fieldsHigh correlation
연면적 is highly overall correlated with 층수 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:25:31.950793
Analysis finished2023-12-10 16:25:35.438762
Duration3.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct218
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.5
Minimum1
Maximum218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:25:35.524465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.85
Q155.25
median109.5
Q3163.75
95-th percentile207.15
Maximum218
Range217
Interquartile range (IQR)108.5

Descriptive statistics

Standard deviation63.075352
Coefficient of variation (CV)0.57603061
Kurtosis-1.2
Mean109.5
Median Absolute Deviation (MAD)54.5
Skewness0
Sum23871
Variance3978.5
MonotonicityStrictly increasing
2023-12-11T01:25:35.746495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
151 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
146 1
 
0.5%
147 1
 
0.5%
Other values (208) 208
95.4%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
218 1
0.5%
217 1
0.5%
216 1
0.5%
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%
209 1
0.5%

단지명
Text

Distinct211
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:25:36.132294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length5.4587156
Min length2

Characters and Unicode

Total characters1190
Distinct characters230
Distinct categories7 ?
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 (%)94.0%

Sample

1st row창신아파트
2nd row토성아파트
3rd row시영아파트
4th row문화아파트
5th row문화아파트
ValueCountFrequency (%)
문화아파트 3
 
1.2%
봄여름가을겨울 3
 
1.2%
대신 3
 
1.2%
미소지음 2
 
0.8%
성원맨션 2
 
0.8%
부백자연애아파트 2
 
0.8%
에이스빌 2
 
0.8%
서원블루오션 2
 
0.8%
남부아파트 2
 
0.8%
서구 2
 
0.8%
Other values (221) 221
90.6%
2023-12-11T01:25:36.706042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 58
 
4.9%
트 52
 
4.4%
파 50
 
4.2%
스 48
 
4.0%
리 31
 
2.6%
빌 31
 
2.6%
대 29
 
2.4%
26
 
2.2%
타 26
 
2.2%
신 25
 
2.1%
Other values (220) 814
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1133
95.2%
Space Separator 26
 
2.2%
Uppercase Letter 15
 
1.3%
Decimal Number 13
 
1.1%
Letter Number 1
 
0.1%
Other Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 58
 
5.1%
트 52
 
4.6%
파 50
 
4.4%
스 48
 
4.2%
리 31
 
2.7%
빌 31
 
2.7%
대 29
 
2.6%
타 26
 
2.3%
신 25
 
2.2%
동 19
 
1.7%
Other values (199) 764
67.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
20.0%
L 2
13.3%
G 2
13.3%
R 1
 
6.7%
C 1
 
6.7%
H 1
 
6.7%
S 1
 
6.7%
N 1
 
6.7%
K 1
 
6.7%
J 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 5
38.5%
3 3
23.1%
6 2
 
15.4%
4 1
 
7.7%
1 1
 
7.7%
5 1
 
7.7%
Space Separator
ValueCountFrequency (%)
26
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1133
95.2%
Common 40
 
3.4%
Latin 17
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 58
 
5.1%
트 52
 
4.6%
파 50
 
4.4%
스 48
 
4.2%
리 31
 
2.7%
빌 31
 
2.7%
대 29
 
2.6%
타 26
 
2.3%
신 25
 
2.2%
동 19
 
1.7%
Other values (199) 764
67.4%
Latin
ValueCountFrequency (%)
B 3
17.6%
L 2
11.8%
G 2
11.8%
R 1
 
5.9%
C 1
 
5.9%
H 1
 
5.9%
Ⅲ 1
 
5.9%
S 1
 
5.9%
N 1
 
5.9%
K 1
 
5.9%
Other values (3) 3
17.6%
Common
ValueCountFrequency (%)
26
65.0%
2 5
 
12.5%
3 3
 
7.5%
6 2
 
5.0%
. 1
 
2.5%
4 1
 
2.5%
1 1
 
2.5%
5 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1133
95.2%
ASCII 56
 
4.7%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 58
 
5.1%
트 52
 
4.6%
파 50
 
4.4%
스 48
 
4.2%
리 31
 
2.7%
빌 31
 
2.7%
대 29
 
2.6%
타 26
 
2.3%
신 25
 
2.2%
동 19
 
1.7%
Other values (199) 764
67.4%
ASCII
ValueCountFrequency (%)
26
46.4%
2 5
 
8.9%
3 3
 
5.4%
B 3
 
5.4%
L 2
 
3.6%
G 2
 
3.6%
6 2
 
3.6%
R 1
 
1.8%
C 1
 
1.8%
H 1
 
1.8%
Other values (10) 10
 
17.9%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

소재지
Text

Distinct217
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:25:37.149627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length10.545872
Min length6

Characters and Unicode

Total characters2299
Distinct characters39
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

Unique216 ?
Unique (%)99.1%

Sample

1st row서대신동2가 88
2nd row토성동2가 19-9
3rd row남부민2동434-86
4th row동대신3가173
5th row토성동2가7-4
ValueCountFrequency (%)
서대신동3가 14
 
3.5%
동대신동3가 14
 
3.5%
암남동 13
 
3.3%
서구 12
 
3.0%
서대신동1가 12
 
3.0%
서대신동2가 11
 
2.8%
부산광역시 9
 
2.3%
토성동2가 8
 
2.0%
동대신동1가 7
 
1.8%
부민동1가 6
 
1.5%
Other values (244) 292
73.4%
2023-12-11T01:25:37.658750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 232
 
10.1%
1 227
 
9.9%
- 185
 
8.0%
180
 
7.8%
2 166
 
7.2%
3 165
 
7.2%
가 162
 
7.0%
대 90
 
3.9%
신 88
 
3.8%
5 76
 
3.3%
Other values (29) 728
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1005
43.7%
Decimal Number 929
40.4%
Dash Punctuation 185
 
8.0%
Space Separator 180
 
7.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 232
23.1%
가 162
16.1%
대 90
 
9.0%
신 88
 
8.8%
서 68
 
6.8%
남 55
 
5.5%
부 48
 
4.8%
암 40
 
4.0%
토 28
 
2.8%
성 28
 
2.8%
Other values (17) 166
16.5%
Decimal Number
ValueCountFrequency (%)
1 227
24.4%
2 166
17.9%
3 165
17.8%
5 76
 
8.2%
4 67
 
7.2%
6 67
 
7.2%
8 42
 
4.5%
0 41
 
4.4%
9 40
 
4.3%
7 38
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Space Separator
ValueCountFrequency (%)
180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1294
56.3%
Hangul 1005
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 232
23.1%
가 162
16.1%
대 90
 
9.0%
신 88
 
8.8%
서 68
 
6.8%
남 55
 
5.5%
부 48
 
4.8%
암 40
 
4.0%
토 28
 
2.8%
성 28
 
2.8%
Other values (17) 166
16.5%
Common
ValueCountFrequency (%)
1 227
17.5%
- 185
14.3%
180
13.9%
2 166
12.8%
3 165
12.8%
5 76
 
5.9%
4 67
 
5.2%
6 67
 
5.2%
8 42
 
3.2%
0 41
 
3.2%
Other values (2) 78
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1294
56.3%
Hangul 1005
43.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 232
23.1%
가 162
16.1%
대 90
 
9.0%
신 88
 
8.8%
서 68
 
6.8%
남 55
 
5.5%
부 48
 
4.8%
암 40
 
4.0%
토 28
 
2.8%
성 28
 
2.8%
Other values (17) 166
16.5%
ASCII
ValueCountFrequency (%)
1 227
17.5%
- 185
14.3%
180
13.9%
2 166
12.8%
3 165
12.8%
5 76
 
5.9%
4 67
 
5.2%
6 67
 
5.2%
8 42
 
3.2%
0 41
 
3.2%
Other values (2) 78
 
6.0%

새주소
Text

Distinct216
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:25:37.980636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.8302752
Min length5

Characters and Unicode

Total characters2143
Distinct characters66
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

Unique214 ?
Unique (%)98.2%

Sample

1st row구덕로 301번길 9
2nd row까치고개로 239번길 7-3
3rd row천해로 13번길 3
4th row구덕로 350
5th row구덕고 186번길 37
ValueCountFrequency (%)
구덕로 41
 
8.1%
충무대로 19
 
3.7%
보수대로 14
 
2.8%
까치고개로 13
 
2.6%
대영로 11
 
2.2%
천마로 11
 
2.2%
망양로 9
 
1.8%
10 7
 
1.4%
12 7
 
1.4%
감천로 7
 
1.4%
Other values (247) 369
72.6%
2023-12-11T01:25:38.650867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
13.5%
로 208
 
9.7%
1 160
 
7.5%
2 138
 
6.4%
길 116
 
5.4%
번 107
 
5.0%
3 105
 
4.9%
5 89
 
4.2%
7 65
 
3.0%
4 62
 
2.9%
Other values (56) 803
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 993
46.3%
Decimal Number 810
37.8%
Space Separator 290
 
13.5%
Dash Punctuation 50
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 208
20.9%
길 116
 
11.7%
번 107
 
10.8%
대 61
 
6.1%
구 57
 
5.7%
덕 56
 
5.6%
무 25
 
2.5%
충 25
 
2.5%
천 22
 
2.2%
수 17
 
1.7%
Other values (44) 299
30.1%
Decimal Number
ValueCountFrequency (%)
1 160
19.8%
2 138
17.0%
3 105
13.0%
5 89
11.0%
7 65
8.0%
4 62
 
7.7%
9 52
 
6.4%
8 49
 
6.0%
0 49
 
6.0%
6 41
 
5.1%
Space Separator
ValueCountFrequency (%)
290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1150
53.7%
Hangul 993
46.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 208
20.9%
길 116
 
11.7%
번 107
 
10.8%
대 61
 
6.1%
구 57
 
5.7%
덕 56
 
5.6%
무 25
 
2.5%
충 25
 
2.5%
천 22
 
2.2%
수 17
 
1.7%
Other values (44) 299
30.1%
Common
ValueCountFrequency (%)
290
25.2%
1 160
13.9%
2 138
12.0%
3 105
 
9.1%
5 89
 
7.7%
7 65
 
5.7%
4 62
 
5.4%
9 52
 
4.5%
- 50
 
4.3%
8 49
 
4.3%
Other values (2) 90
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1150
53.7%
Hangul 993
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
25.2%
1 160
13.9%
2 138
12.0%
3 105
 
9.1%
5 89
 
7.7%
7 65
 
5.7%
4 62
 
5.4%
9 52
 
4.5%
- 50
 
4.3%
8 49
 
4.3%
Other values (2) 90
 
7.8%
Hangul
ValueCountFrequency (%)
로 208
20.9%
길 116
 
11.7%
번 107
 
10.8%
대 61
 
6.1%
구 57
 
5.7%
덕 56
 
5.6%
무 25
 
2.5%
충 25
 
2.5%
천 22
 
2.2%
수 17
 
1.7%
Other values (44) 299
30.1%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.582569
Minimum3
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:25:38.841484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q15
median9.5
Q315
95-th percentile24.15
Maximum69
Range66
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.5186198
Coefficient of variation (CV)0.73546896
Kurtosis11.464485
Mean11.582569
Median Absolute Deviation (MAD)4.5
Skewness2.5807176
Sum2525
Variance72.566884
MonotonicityNot monotonic
2023-12-11T01:25:39.035988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
5 40
18.3%
15 24
11.0%
6 21
 
9.6%
14 13
 
6.0%
8 13
 
6.0%
4 11
 
5.0%
10 11
 
5.0%
3 10
 
4.6%
20 9
 
4.1%
13 9
 
4.1%
Other values (22) 57
26.1%
ValueCountFrequency (%)
3 10
 
4.6%
4 11
 
5.0%
5 40
18.3%
6 21
9.6%
7 6
 
2.8%
8 13
 
6.0%
9 8
 
3.7%
10 11
 
5.0%
11 5
 
2.3%
12 6
 
2.8%
ValueCountFrequency (%)
69 1
0.5%
49 1
0.5%
47 1
0.5%
38 1
0.5%
34 1
0.5%
33 1
0.5%
29 2
0.9%
28 1
0.5%
27 1
0.5%
25 1
0.5%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5458716
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:25:39.306870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5
Maximum12
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6489646
Coefficient of variation (CV)1.0666893
Kurtosis16.261149
Mean1.5458716
Median Absolute Deviation (MAD)0
Skewness3.9202896
Sum337
Variance2.7190843
MonotonicityNot monotonic
2023-12-11T01:25:39.477657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 179
82.1%
2 18
 
8.3%
3 7
 
3.2%
5 3
 
1.4%
8 3
 
1.4%
6 3
 
1.4%
9 2
 
0.9%
12 1
 
0.5%
4 1
 
0.5%
10 1
 
0.5%
ValueCountFrequency (%)
1 179
82.1%
2 18
 
8.3%
3 7
 
3.2%
4 1
 
0.5%
5 3
 
1.4%
6 3
 
1.4%
8 3
 
1.4%
9 2
 
0.9%
10 1
 
0.5%
12 1
 
0.5%
ValueCountFrequency (%)
12 1
 
0.5%
10 1
 
0.5%
9 2
 
0.9%
8 3
 
1.4%
6 3
 
1.4%
5 3
 
1.4%
4 1
 
0.5%
3 7
 
3.2%
2 18
 
8.3%
1 179
82.1%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.995413
Minimum8
Maximum1368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:25:39.822346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile20
Q124
median33
Q372
95-th percentile430.65
Maximum1368
Range1360
Interquartile range (IQR)48

Descriptive statistics

Standard deviation165.40796
Coefficient of variation (CV)1.8177615
Kurtosis22.670353
Mean90.995413
Median Absolute Deviation (MAD)13
Skewness4.2949207
Sum19837
Variance27359.793
MonotonicityNot monotonic
2023-12-11T01:25:40.071933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 25
 
11.5%
20 25
 
11.5%
28 9
 
4.1%
21 8
 
3.7%
23 7
 
3.2%
26 7
 
3.2%
48 6
 
2.8%
29 6
 
2.8%
36 5
 
2.3%
22 5
 
2.3%
Other values (80) 115
52.8%
ValueCountFrequency (%)
8 1
 
0.5%
18 1
 
0.5%
20 25
11.5%
21 8
 
3.7%
22 5
 
2.3%
23 7
 
3.2%
24 25
11.5%
25 4
 
1.8%
26 7
 
3.2%
27 4
 
1.8%
ValueCountFrequency (%)
1368 1
0.5%
959 1
0.5%
782 1
0.5%
753 1
0.5%
733 1
0.5%
613 1
0.5%
564 1
0.5%
503 1
0.5%
490 1
0.5%
452 1
0.5%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct205
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11874.431
Minimum486
Maximum391558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:25:40.287333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum486
5-th percentile652.85
Q1976
median3027
Q38702.25
95-th percentile49638.65
Maximum391558
Range391072
Interquartile range (IQR)7726.25

Descriptive statistics

Standard deviation32742.785
Coefficient of variation (CV)2.7574193
Kurtosis85.4813
Mean11874.431
Median Absolute Deviation (MAD)2245.5
Skewness8.0915505
Sum2588626
Variance1.07209 × 109
MonotonicityNot monotonic
2023-12-11T01:25:40.431927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
657 3
 
1.4%
660 3
 
1.4%
659 3
 
1.4%
920 2
 
0.9%
10668 2
 
0.9%
976 2
 
0.9%
1995 2
 
0.9%
613 2
 
0.9%
1564 2
 
0.9%
1361 2
 
0.9%
Other values (195) 195
89.4%
ValueCountFrequency (%)
486 1
0.5%
495 1
0.5%
501 1
0.5%
517 1
0.5%
539 1
0.5%
556 1
0.5%
613 2
0.9%
636 1
0.5%
651 1
0.5%
652 1
0.5%
ValueCountFrequency (%)
391558 1
0.5%
154045 1
0.5%
120505 1
0.5%
92720 1
0.5%
81507 1
0.5%
79835 1
0.5%
73926 1
0.5%
71907 1
0.5%
68384 1
0.5%
64987 1
0.5%

준공일자
Date

Distinct209
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1968-12-26 00:00:00
Maximum2022-11-29 00:00:00
2023-12-11T01:25:40.622209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:40.769990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T01:25:34.587662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.283413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.736413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.573319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.084389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.696013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.367755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.825051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.656187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.170719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.800103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.460970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.249387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.760833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.282213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.923956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.572481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.331814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.859268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.374274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:35.044687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:32.652787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.453617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:33.977615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:25:34.490702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:25:40.902267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적
연번1.0000.4090.0000.2080.000
층수0.4091.0000.5160.9030.819
동수0.0000.5161.0000.7890.783
세대수0.2080.9030.7891.0000.873
연면적0.0000.8190.7830.8731.000
2023-12-11T01:25:41.035359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번층수동수세대수연면적
연번1.0000.343-0.120-0.209-0.155
층수0.3431.0000.2300.6030.730
동수-0.1200.2301.0000.5300.489
세대수-0.2090.6030.5301.0000.890
연면적-0.1550.7300.4890.8901.000

Missing values

2023-12-11T01:25:35.209524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:25:35.378818image/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

연번단지명소재지새주소층수동수세대수연면적준공일자
01창신아파트서대신동2가 88구덕로 301번길 941259371968-12-26
12토성아파트토성동2가 19-9까치고개로 239번길 7-3414114551969-12-30
23시영아파트남부민2동434-86천해로 13번길 345288108161969-12-30
34문화아파트동대신3가173구덕로 350101180178181971-12-17
45문화아파트토성동2가7-4구덕고 186번길 37513416831974-01-11
56삼협아파트토성동1가12-1까치고개로 239번길 12412116311974-08-16
67충무아파트충무동2가29천마로 229413314861974-08-31
78동심아파트충무동2가20천마로 205번길 32512314081974-09-02
89문화아파트남부민1동30-1천마로 187번길 20514732771975-12-17
910충무제1아파트충무동2가34천마로 205번길 39526018651975-12-26
연번단지명소재지새주소층수동수세대수연면적준공일자
208209수현빌리지아미동1가 25-3번지구덕로165번길 21912310982020-04-24
209210서구 서대신동 주상복합 신축공사부산광역시 서구 서대신동2가 35-6구덕로315번길 51612519982020-08-03
210211대신엘리시움부산광역시 서구 서대신동3가 61-75대신공원로 37-1751286602020-08-21
211212에비뉴엘부산광역시 서구 동대신동3가 63-179망양로111번길 2251188202021-03-29
212213동대신역비스타동원아파트부산광역시 서구 동대신동1가 420보수대로154번길 29296503719072021-03-30
213214남명더라우부산광역시 서구 부용동1가 69-7구덕로 2341715354012021-11-10
214215한우리빌동대신동2가 29-3보동길 327번길 5-45186572021-12-29
215216힐스테이트이진베이시티암남동 123-15송도해변로 19269313683915582022-05-24
216217대신해모로센트럴서대신동2가 394-7서구 대티로 178298733294372022-07-30
217218에코펠리스6차충무동1가 29-8충무시장길 3420195141442022-11-29