Overview

Dataset statistics

Number of variables14
Number of observations147
Missing cells156
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.2 KiB
Average record size in memory119.9 B

Variable types

Numeric5
Categorical6
Text1
DateTime2

Dataset

Description서울특별시 성북구 관내 원룸 및 오피스텔 정보에 대한 데이터입니다. 파일은 연번, 시군구명, 법정동, 대지구분, 본번, 부번, 외필지수, 주용도, 부속용도, 세대수, 가구수, 호수, 사용승인일자, 데이터기준일자 로 구성되어 있습니다.
Author서울특별시 성북구
URLhttps://www.data.go.kr/data/15107846/fileData.do

Alerts

시군구명 has constant value ""Constant
대지구분 has constant value ""Constant
데이터기준일 has constant value ""Constant
외필지수 is highly overall correlated with 가구수High correlation
주용도 is highly overall correlated with 가구수High correlation
가구수 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 가구수High correlation
부번 is highly overall correlated with 가구수High correlation
주용도 is highly imbalanced (51.8%)Imbalance
가구수 is highly imbalanced (85.1%)Imbalance
부번 has 47 (32.0%) missing valuesMissing
세대수 has 39 (26.5%) missing valuesMissing
호수 has 70 (47.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:22:10.826539
Analysis finished2023-12-12 13:22:14.308857
Duration3.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:22:14.382606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.3
Q137.5
median74
Q3110.5
95-th percentile139.7
Maximum147
Range146
Interquartile range (IQR)73

Descriptive statistics

Standard deviation42.579338
Coefficient of variation (CV)0.57539646
Kurtosis-1.2
Mean74
Median Absolute Deviation (MAD)37
Skewness0
Sum10878
Variance1813
MonotonicityStrictly increasing
2023-12-12T22:22:14.879658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
Other values (137) 137
93.2%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울특별시 성북구
147 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 성북구
2nd row서울특별시 성북구
3rd row서울특별시 성북구
4th row서울특별시 성북구
5th row서울특별시 성북구

Common Values

ValueCountFrequency (%)
서울특별시 성북구 147
100.0%

Length

2023-12-12T22:22:15.045016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:15.178940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 147
50.0%
성북구 147
50.0%

법정동
Categorical

Distinct31
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
정릉동
20 
석관동
17 
하월곡동
16 
종암동
14 
안암동2가
9 
Other values (26)
71 

Length

Max length6
Median length5
Mean length4.1428571
Min length3

Unique

Unique9 ?
Unique (%)6.1%

Sample

1st row정릉동
2nd row동선동2가
3rd row정릉동
4th row정릉동
5th row동선동4가

Common Values

ValueCountFrequency (%)
정릉동 20
13.6%
석관동 17
 
11.6%
하월곡동 16
 
10.9%
종암동 14
 
9.5%
안암동2가 9
 
6.1%
동선동4가 8
 
5.4%
보문동2가 7
 
4.8%
안암동5가 5
 
3.4%
안암동1가 4
 
2.7%
동소문동6가 4
 
2.7%
Other values (21) 43
29.3%

Length

2023-12-12T22:22:15.334017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정릉동 20
13.6%
석관동 17
 
11.6%
하월곡동 16
 
10.9%
종암동 14
 
9.5%
안암동2가 9
 
6.1%
동선동4가 8
 
5.4%
보문동2가 7
 
4.8%
안암동5가 5
 
3.4%
안암동1가 4
 
2.7%
동소문동6가 4
 
2.7%
Other values (21) 43
29.3%

대지구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
대지
147 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대지
2nd row대지
3rd row대지
4th row대지
5th row대지

Common Values

ValueCountFrequency (%)
대지 147
100.0%

Length

2023-12-12T22:22:15.458951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:15.567076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대지 147
100.0%

본번
Real number (ℝ)

Distinct90
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.43537
Minimum1
Maximum916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:22:15.670780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q137.5
median119
Q3200
95-th percentile358.9
Maximum916
Range915
Interquartile range (IQR)162.5

Descriptive statistics

Standard deviation146.57249
Coefficient of variation (CV)1.0078187
Kurtosis9.0911963
Mean145.43537
Median Absolute Deviation (MAD)82
Skewness2.4332328
Sum21379
Variance21483.494
MonotonicityNot monotonic
2023-12-12T22:22:15.803675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 11
 
7.5%
3 8
 
5.4%
227 7
 
4.8%
10 5
 
3.4%
15 5
 
3.4%
13 3
 
2.0%
132 3
 
2.0%
30 3
 
2.0%
28 3
 
2.0%
120 3
 
2.0%
Other values (80) 96
65.3%
ValueCountFrequency (%)
1 1
 
0.7%
2 1
 
0.7%
3 8
5.4%
7 1
 
0.7%
8 1
 
0.7%
9 1
 
0.7%
10 5
3.4%
13 3
 
2.0%
15 5
3.4%
23 1
 
0.7%
ValueCountFrequency (%)
916 1
0.7%
882 1
0.7%
670 1
0.7%
488 2
1.4%
414 1
0.7%
402 1
0.7%
367 1
0.7%
340 1
0.7%
335 2
1.4%
332 2
1.4%

부번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct67
Distinct (%)67.0%
Missing47
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean209.59
Minimum1
Maximum1995
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:22:15.979777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median23
Q3113
95-th percentile1298.85
Maximum1995
Range1994
Interquartile range (IQR)107

Descriptive statistics

Standard deviation464.17537
Coefficient of variation (CV)2.2146828
Kurtosis6.3958299
Mean209.59
Median Absolute Deviation (MAD)21
Skewness2.7371052
Sum20959
Variance215458.77
MonotonicityNot monotonic
2023-12-12T22:22:16.143077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 9
 
6.1%
1 6
 
4.1%
5 6
 
4.1%
7 3
 
2.0%
8 3
 
2.0%
10 3
 
2.0%
6 3
 
2.0%
3 2
 
1.4%
9 2
 
1.4%
12 2
 
1.4%
Other values (57) 61
41.5%
(Missing) 47
32.0%
ValueCountFrequency (%)
1 6
4.1%
2 9
6.1%
3 2
 
1.4%
4 1
 
0.7%
5 6
4.1%
6 3
 
2.0%
7 3
 
2.0%
8 3
 
2.0%
9 2
 
1.4%
10 3
 
2.0%
ValueCountFrequency (%)
1995 1
0.7%
1817 1
0.7%
1815 1
0.7%
1814 1
0.7%
1714 1
0.7%
1277 1
0.7%
1266 1
0.7%
1264 1
0.7%
1261 1
0.7%
1123 1
0.7%

외필지수
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
104 
1
21 
2
 
10
3
 
6
5
 
3

Length

Max length4
Median length4
Mean length3.122449
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 104
70.7%
1 21
 
14.3%
2 10
 
6.8%
3 6
 
4.1%
5 3
 
2.0%
7 3
 
2.0%

Length

2023-12-12T22:22:16.276992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:16.402804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 104
70.7%
1 21
 
14.3%
2 10
 
6.8%
3 6
 
4.1%
5 3
 
2.0%
7 3
 
2.0%

주용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
공동주택
104 
업무시설
41 
제1종근린생활시설
 
1
의료시설
 
1

Length

Max length9
Median length4
Mean length4.0340136
Min length4

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row공동주택
2nd row공동주택
3rd row공동주택
4th row공동주택
5th row공동주택

Common Values

ValueCountFrequency (%)
공동주택 104
70.7%
업무시설 41
 
27.9%
제1종근린생활시설 1
 
0.7%
의료시설 1
 
0.7%

Length

2023-12-12T22:22:16.522125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:16.640719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 104
70.7%
업무시설 41
 
27.9%
제1종근린생활시설 1
 
0.7%
의료시설 1
 
0.7%

부속용도
Text

Distinct91
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T22:22:16.866100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length18.265306
Min length4

Characters and Unicode

Total characters2685
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)51.7%

Sample

1st row제2종근린생활시설및도시형생활주택(원룸형)
2nd row도시형생활주택(원룸형다세대)
3rd row도시형생활주택(원룸형)
4th row도시형생활주택(원룸형)
5th row업무시설(오피스텔)/도시형생활주택(원룸형주택)/제2종근린생활시설(사무소)
ValueCountFrequency (%)
업무시설(오피스텔 18
 
9.0%
도시형생활주택(원룸형 15
 
7.5%
도시형생활주택(원룸형다세대 13
 
6.5%
오피스텔 10
 
5.0%
공동주택(도시형생활주택(원룸형 8
 
4.0%
다세대주택 8
 
4.0%
및 8
 
4.0%
공동주택(도시형생활주택-원룸형다세대 5
 
2.5%
근린생활시설 4
 
2.0%
원룸형 4
 
2.0%
Other values (82) 107
53.5%
2023-12-12T22:22:17.259611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 193
 
7.2%
형 192
 
7.2%
택 189
 
7.0%
시 173
 
6.4%
( 163
 
6.1%
) 161
 
6.0%
생 131
 
4.9%
활 129
 
4.8%
도 99
 
3.7%
원 91
 
3.4%
Other values (54) 1164
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2167
80.7%
Open Punctuation 168
 
6.3%
Close Punctuation 166
 
6.2%
Other Punctuation 69
 
2.6%
Space Separator 53
 
2.0%
Decimal Number 39
 
1.5%
Dash Punctuation 19
 
0.7%
Connector Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 193
 
8.9%
형 192
 
8.9%
택 189
 
8.7%
시 173
 
8.0%
생 131
 
6.0%
활 129
 
6.0%
도 99
 
4.6%
원 91
 
4.2%
룸 91
 
4.2%
세 82
 
3.8%
Other values (36) 797
36.8%
Decimal Number
ValueCountFrequency (%)
1 18
46.2%
2 12
30.8%
4 3
 
7.7%
9 2
 
5.1%
8 1
 
2.6%
0 1
 
2.6%
3 1
 
2.6%
6 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 61
88.4%
/ 6
 
8.7%
: 2
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 163
97.0%
[ 5
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 161
97.0%
] 5
 
3.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2167
80.7%
Common 518
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 193
 
8.9%
형 192
 
8.9%
택 189
 
8.7%
시 173
 
8.0%
생 131
 
6.0%
활 129
 
6.0%
도 99
 
4.6%
원 91
 
4.2%
룸 91
 
4.2%
세 82
 
3.8%
Other values (36) 797
36.8%
Common
ValueCountFrequency (%)
( 163
31.5%
) 161
31.1%
, 61
 
11.8%
53
 
10.2%
- 19
 
3.7%
1 18
 
3.5%
2 12
 
2.3%
/ 6
 
1.2%
] 5
 
1.0%
[ 5
 
1.0%
Other values (8) 15
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2167
80.7%
ASCII 518
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 193
 
8.9%
형 192
 
8.9%
택 189
 
8.7%
시 173
 
8.0%
생 131
 
6.0%
활 129
 
6.0%
도 99
 
4.6%
원 91
 
4.2%
룸 91
 
4.2%
세 82
 
3.8%
Other values (36) 797
36.8%
ASCII
ValueCountFrequency (%)
( 163
31.5%
) 161
31.1%
, 61
 
11.8%
53
 
10.2%
- 19
 
3.7%
1 18
 
3.5%
2 12
 
2.3%
/ 6
 
1.2%
] 5
 
1.0%
[ 5
 
1.0%
Other values (8) 15
 
2.9%

세대수
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)28.7%
Missing39
Missing (%)26.5%
Infinite0
Infinite (%)0.0%
Mean20.509259
Minimum4
Maximum299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:22:17.396308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q111
median15
Q321
95-th percentile46.55
Maximum299
Range295
Interquartile range (IQR)10

Descriptive statistics

Standard deviation30.015727
Coefficient of variation (CV)1.4635208
Kurtosis70.554859
Mean20.509259
Median Absolute Deviation (MAD)5
Skewness7.786479
Sum2215
Variance900.94384
MonotonicityNot monotonic
2023-12-12T22:22:17.531684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
12 13
 
8.8%
8 10
 
6.8%
16 7
 
4.8%
13 6
 
4.1%
11 6
 
4.1%
19 6
 
4.1%
15 5
 
3.4%
21 5
 
3.4%
17 5
 
3.4%
20 4
 
2.7%
Other values (21) 41
27.9%
(Missing) 39
26.5%
ValueCountFrequency (%)
4 4
 
2.7%
5 3
 
2.0%
8 10
6.8%
9 3
 
2.0%
10 3
 
2.0%
11 6
4.1%
12 13
8.8%
13 6
4.1%
14 4
 
2.7%
15 5
 
3.4%
ValueCountFrequency (%)
299 1
 
0.7%
83 1
 
0.7%
72 1
 
0.7%
70 1
 
0.7%
57 1
 
0.7%
49 1
 
0.7%
42 1
 
0.7%
33 1
 
0.7%
29 4
2.7%
28 2
1.4%

가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
141 
1
 
4
23
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.8843537
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 141
95.9%
1 4
 
2.7%
23 1
 
0.7%
5 1
 
0.7%

Length

2023-12-12T22:22:17.664366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:22:17.765172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
95.9%
1 4
 
2.7%
23 1
 
0.7%
5 1
 
0.7%

호수
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)50.6%
Missing70
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean24.467532
Minimum1
Maximum260
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:22:17.887018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median12
Q328
95-th percentile81
Maximum260
Range259
Interquartile range (IQR)26

Descriptive statistics

Standard deviation39.584548
Coefficient of variation (CV)1.6178398
Kurtosis17.205735
Mean24.467532
Median Absolute Deviation (MAD)10
Skewness3.6315189
Sum1884
Variance1566.9364
MonotonicityNot monotonic
2023-12-12T22:22:18.033938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 10
 
6.8%
2 10
 
6.8%
4 8
 
5.4%
3 5
 
3.4%
18 3
 
2.0%
15 3
 
2.0%
24 2
 
1.4%
16 2
 
1.4%
5 2
 
1.4%
21 2
 
1.4%
Other values (29) 30
20.4%
(Missing) 70
47.6%
ValueCountFrequency (%)
1 10
6.8%
2 10
6.8%
3 5
3.4%
4 8
5.4%
5 2
 
1.4%
6 1
 
0.7%
7 1
 
0.7%
8 1
 
0.7%
12 1
 
0.7%
13 1
 
0.7%
ValueCountFrequency (%)
260 1
0.7%
144 1
0.7%
140 1
0.7%
85 1
0.7%
80 1
0.7%
72 1
0.7%
66 1
0.7%
60 1
0.7%
57 1
0.7%
56 1
0.7%

사용승인일
Date

Distinct136
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1972-10-26 00:00:00
Maximum2022-10-24 00:00:00
2023-12-12T22:22:18.168208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:18.295617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-11-01 00:00:00
Maximum2022-11-01 00:00:00
2023-12-12T22:22:18.421349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:18.502392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:22:13.452947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:11.490431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.011012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.502989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.011155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.533125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:11.586807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.109923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.597124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.114144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.607569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:11.684507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.220679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.686150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.188638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.695115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:11.800488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.349588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.804415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.277905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.795254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:11.904642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.429453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:12.918453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:22:13.362113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:22:18.570943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번법정동본번부번외필지수주용도부속용도세대수가구수호수
연번1.0000.0000.0860.2550.3030.6390.8220.000NaN0.000
법정동0.0001.0000.7670.0000.3380.4270.8650.4850.0000.395
본번0.0860.7671.0000.0000.1960.0000.4760.5330.0000.000
부번0.2550.0000.0001.0000.6700.2180.9460.000NaN0.000
외필지수0.3030.3380.1960.6701.0000.3130.8700.4031.0000.395
주용도0.6390.4270.0000.2180.3131.0001.0000.000NaN0.579
부속용도0.8220.8650.4760.9460.8701.0001.0000.9050.5980.508
세대수0.0000.4850.5330.0000.4030.0000.9051.000NaN0.798
가구수NaN0.0000.000NaN1.000NaN0.598NaN1.000NaN
호수0.0000.3950.0000.0000.3950.5790.5080.798NaN1.000
2023-12-12T22:22:18.704118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동외필지수주용도가구수
법정동1.0000.1050.2070.000
외필지수0.1051.0000.3651.000
주용도0.2070.3651.0001.000
가구수0.0001.0001.0001.000
2023-12-12T22:22:18.822781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번본번부번세대수호수법정동외필지수주용도가구수
연번1.000-0.082-0.022-0.1090.4950.0000.1560.4301.000
본번-0.0821.000-0.0650.1990.0530.3880.0550.0000.000
부번-0.022-0.0651.000-0.316-0.1730.0000.3010.2261.000
세대수-0.1090.199-0.3161.0000.4380.2380.3280.000NaN
호수0.4950.053-0.1730.4381.0000.1400.3130.281NaN
법정동0.0000.3880.0000.2380.1401.0000.1050.2070.000
외필지수0.1560.0550.3010.3280.3130.1051.0000.3651.000
주용도0.4300.0000.2260.0000.2810.2070.3651.0001.000
가구수1.0000.0001.000NaNNaN0.0001.0001.0001.000

Missing values

2023-12-12T22:22:13.921587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:22:14.103952image/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.
2023-12-12T22:22:14.243266image/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

연번시군구명법정동대지구분본번부번외필지수주용도부속용도세대수가구수호수사용승인일데이터기준일
01서울특별시 성북구정릉동대지22625<NA>공동주택제2종근린생활시설및도시형생활주택(원룸형)26<NA>22012-02-172022-11-01
12서울특별시 성북구동선동2가대지9<NA><NA>공동주택도시형생활주택(원룸형다세대)8<NA>22014-04-292022-11-01
23서울특별시 성북구정릉동대지192182<NA>공동주택도시형생활주택(원룸형)15<NA><NA>2014-07-012022-11-01
34서울특별시 성북구정릉동대지402122<NA>공동주택도시형생활주택(원룸형)16<NA><NA>2014-10-212022-11-01
45서울특별시 성북구동선동4가대지148<NA><NA>공동주택업무시설(오피스텔)/도시형생활주택(원룸형주택)/제2종근린생활시설(사무소)28<NA>122014-01-292022-11-01
56서울특별시 성북구보문동6가대지367<NA><NA>공동주택도시형생활주택(원룸형),제2종근린생활시설10<NA>12014-01-292022-11-01
67서울특별시 성북구종암동대지8435<NA>공동주택공동주택(도시형생활주택(원룸형 다세대))13<NA>12013-07-092022-11-01
78서울특별시 성북구종암동대지12533<NA>공동주택공동주택(다세대주택(도시형생활주택(원룸형)))14<NA><NA>2016-10-042022-11-01
89서울특별시 성북구정릉동대지91612공동주택도시형생활주택(원룸형)49<NA><NA>2015-12-172022-11-01
910서울특별시 성북구안암동2가대지13<NA><NA>공동주택도시형생활주택(원룸형)21<NA><NA>2013-07-092022-11-01
연번시군구명법정동대지구분본번부번외필지수주용도부속용도세대수가구수호수사용승인일데이터기준일
137138서울특별시 성북구석관동대지3352<NA>업무시설업무시설(오피스텔)<NA><NA>212002-03-152022-11-01
138139서울특별시 성북구석관동대지33516<NA>업무시설업무시설(오피스텔)<NA><NA>182004-06-292022-11-01
139140서울특별시 성북구동선동4가대지2954<NA>업무시설업무시설(오피스텔)<NA><NA>1442011-12-292022-11-01
140141서울특별시 성북구정릉동대지150277공동주택공동주택(도시형생활주택,근린생활시설, 오피스텔)72<NA>542022-08-092022-11-01
141142서울특별시 성북구종암동대지31266<NA>업무시설업무시설(오피스텔), 공동주택(다세대주택)8<NA>42021-05-122022-11-01
142143서울특별시 성북구정릉동대지4147<NA>공동주택공동주택(다세대주택),근린생활시설,오피스텔8<NA>22022-10-242022-11-01
143144서울특별시 성북구하월곡동대지28212업무시설업무시설(주거용오피스텔), 다세대주택20<NA>202022-02-152022-11-01
144145서울특별시 성북구장위동대지218122공동주택도시형생활주택(단지형다세대),업무시설(오피스텔),제1종근린생활시설(소매점)8<NA>52016-05-132022-11-01
145146서울특별시 성북구하월곡동대지90207<NA>업무시설(주거용오피스텔)및 다세대주택4<NA>42017-04-122022-11-01
146147서울특별시 성북구동소문동4가대지118<NA><NA>업무시설업무시설(오피스텔)<NA><NA>802019-03-262022-11-01