Overview

Dataset statistics

Number of variables10
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory89.7 B

Variable types

Text4
Numeric3
DateTime2
Categorical1

Dataset

Description성남시내 주상복합건물현황(단지명,건축주,주소,대지위치,세대수,사용승인일,최대지상층수,최대지하층수,동수 등)입니다.
URLhttps://www.data.go.kr/data/15043663/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
세대수 is highly overall correlated with 최대지상층수High correlation
최대지상층수 is highly overall correlated with 세대수High correlation
단지명 has unique valuesUnique
도로명주소 has unique valuesUnique
대지위치 has unique valuesUnique
세대수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:01:08.501987
Analysis finished2023-12-12 09:01:10.158129
Duration1.66 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단지명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T18:01:10.343151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length8.6086957
Min length5

Characters and Unicode

Total characters198
Distinct characters87
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row분당로얄팰리스
2nd row분당아이파크 1
3rd row분당아이파크 2(공동관리)
4th row분당아이파크 3(공동관리)
5th row위브제니스
ValueCountFrequency (%)
분당아이파크 3
 
8.1%
푸르지오 2
 
5.4%
위례역 2
 
5.4%
알파리움 2
 
5.4%
분당로얄팰리스 1
 
2.7%
일성오퍼스원 1
 
2.7%
신세계쉐덴 1
 
2.7%
태평동 1
 
2.7%
신동아파라디움 1
 
2.7%
6단지 1
 
2.7%
Other values (22) 22
59.5%
2023-12-12T18:01:10.787447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
7.1%
분 8
 
4.0%
당 8
 
4.0%
리 8
 
4.0%
스 8
 
4.0%
파 8
 
4.0%
지 7
 
3.5%
아 7
 
3.5%
크 5
 
2.5%
움 4
 
2.0%
Other values (77) 121
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
83.3%
Space Separator 14
 
7.1%
Decimal Number 7
 
3.5%
Uppercase Letter 6
 
3.0%
Close Punctuation 3
 
1.5%
Open Punctuation 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
분 8
 
4.8%
당 8
 
4.8%
리 8
 
4.8%
스 8
 
4.8%
파 8
 
4.8%
지 7
 
4.2%
아 7
 
4.2%
크 5
 
3.0%
움 4
 
2.4%
위 4
 
2.4%
Other values (63) 98
59.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
16.7%
K 1
16.7%
V 1
16.7%
I 1
16.7%
E 1
16.7%
W 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
1 2
28.6%
4 1
14.3%
6 1
14.3%
3 1
14.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
83.3%
Common 27
 
13.6%
Latin 6
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
분 8
 
4.8%
당 8
 
4.8%
리 8
 
4.8%
스 8
 
4.8%
파 8
 
4.8%
지 7
 
4.2%
아 7
 
4.2%
크 5
 
3.0%
움 4
 
2.4%
위 4
 
2.4%
Other values (63) 98
59.4%
Common
ValueCountFrequency (%)
14
51.9%
) 3
 
11.1%
( 3
 
11.1%
2 2
 
7.4%
1 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%
3 1
 
3.7%
Latin
ValueCountFrequency (%)
S 1
16.7%
K 1
16.7%
V 1
16.7%
I 1
16.7%
E 1
16.7%
W 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
83.3%
ASCII 33
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
42.4%
) 3
 
9.1%
( 3
 
9.1%
2 2
 
6.1%
1 2
 
6.1%
4 1
 
3.0%
6 1
 
3.0%
S 1
 
3.0%
K 1
 
3.0%
V 1
 
3.0%
Other values (4) 4
 
12.1%
Hangul
ValueCountFrequency (%)
분 8
 
4.8%
당 8
 
4.8%
리 8
 
4.8%
스 8
 
4.8%
파 8
 
4.8%
지 7
 
4.2%
아 7
 
4.2%
크 5
 
3.0%
움 4
 
2.4%
위 4
 
2.4%
Other values (63) 98
59.4%

도로명주소
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T18:01:11.067988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.608696
Min length19

Characters and Unicode

Total characters474
Distinct characters43
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 분당구 성남대로 449
2nd row경기도 성남시 분당구 정자일로239
3rd row경기도 성남시 분당구 정자일로213번길 19
4th row경기도 성남시 분당구 정자일로213번길 5
5th row경기도 성남시 분당구 정자일로232번길 25
ValueCountFrequency (%)
경기도 23
20.0%
성남시 23
20.0%
분당구 17
14.8%
정자일로 7
 
6.1%
수정구 5
 
4.3%
성남대로 3
 
2.6%
정자일로213번길 2
 
1.7%
25 2
 
1.7%
위례광장로 2
 
1.7%
광명로 1
 
0.9%
Other values (30) 30
26.1%
2023-12-12T18:01:11.514494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
19.4%
성 26
 
5.5%
남 26
 
5.5%
경 23
 
4.9%
도 23
 
4.9%
시 23
 
4.9%
구 23
 
4.9%
기 23
 
4.9%
로 23
 
4.9%
정 17
 
3.6%
Other values (33) 175
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 308
65.0%
Space Separator 92
 
19.4%
Decimal Number 74
 
15.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 26
 
8.4%
남 26
 
8.4%
경 23
 
7.5%
도 23
 
7.5%
시 23
 
7.5%
구 23
 
7.5%
기 23
 
7.5%
로 23
 
7.5%
정 17
 
5.5%
분 17
 
5.5%
Other values (22) 84
27.3%
Decimal Number
ValueCountFrequency (%)
2 16
21.6%
1 16
21.6%
5 8
10.8%
0 8
10.8%
3 8
10.8%
4 5
 
6.8%
7 4
 
5.4%
6 4
 
5.4%
9 4
 
5.4%
8 1
 
1.4%
Space Separator
ValueCountFrequency (%)
92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 308
65.0%
Common 166
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 26
 
8.4%
남 26
 
8.4%
경 23
 
7.5%
도 23
 
7.5%
시 23
 
7.5%
구 23
 
7.5%
기 23
 
7.5%
로 23
 
7.5%
정 17
 
5.5%
분 17
 
5.5%
Other values (22) 84
27.3%
Common
ValueCountFrequency (%)
92
55.4%
2 16
 
9.6%
1 16
 
9.6%
5 8
 
4.8%
0 8
 
4.8%
3 8
 
4.8%
4 5
 
3.0%
7 4
 
2.4%
6 4
 
2.4%
9 4
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 308
65.0%
ASCII 166
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
55.4%
2 16
 
9.6%
1 16
 
9.6%
5 8
 
4.8%
0 8
 
4.8%
3 8
 
4.8%
4 5
 
3.0%
7 4
 
2.4%
6 4
 
2.4%
9 4
 
2.4%
Hangul
ValueCountFrequency (%)
성 26
 
8.4%
남 26
 
8.4%
경 23
 
7.5%
도 23
 
7.5%
시 23
 
7.5%
구 23
 
7.5%
기 23
 
7.5%
로 23
 
7.5%
정 17
 
5.5%
분 17
 
5.5%
Other values (22) 84
27.3%

대지위치
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T18:01:11.758277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.347826
Min length17

Characters and Unicode

Total characters491
Distinct characters43
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

Unique23 ?
Unique (%)100.0%

Sample

1st row경기도 성남시 분당구 정자동 28-1
2nd row경기도 성남시 분당구 정자동 9
3rd row경기도 성남시 분당구 정자동 10-1 외1필지
4th row경기도 성남시 분당구 정자동 11
5th row경기도 성남시 분당구 정자동 15-4 외2필지
ValueCountFrequency (%)
경기도 23
18.7%
성남시 23
18.7%
분당구 17
13.8%
정자동 10
 
8.1%
수정구 5
 
4.1%
외2필지 3
 
2.4%
금곡동 3
 
2.4%
창곡동 2
 
1.6%
태평동 2
 
1.6%
백현동 2
 
1.6%
Other values (33) 33
26.8%
2023-12-12T18:01:12.459798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
20.6%
성 24
 
4.9%
남 24
 
4.9%
경 23
 
4.7%
도 23
 
4.7%
시 23
 
4.7%
구 23
 
4.7%
동 23
 
4.7%
기 23
 
4.7%
1 21
 
4.3%
Other values (33) 183
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
61.3%
Space Separator 101
 
20.6%
Decimal Number 81
 
16.5%
Dash Punctuation 8
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 24
 
8.0%
남 24
 
8.0%
경 23
 
7.6%
도 23
 
7.6%
시 23
 
7.6%
구 23
 
7.6%
동 23
 
7.6%
기 23
 
7.6%
분 17
 
5.6%
당 17
 
5.6%
Other values (21) 81
26.9%
Decimal Number
ValueCountFrequency (%)
1 21
25.9%
2 11
13.6%
5 9
11.1%
0 8
 
9.9%
3 8
 
9.9%
6 6
 
7.4%
7 6
 
7.4%
8 5
 
6.2%
4 4
 
4.9%
9 3
 
3.7%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
61.3%
Common 190
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 24
 
8.0%
남 24
 
8.0%
경 23
 
7.6%
도 23
 
7.6%
시 23
 
7.6%
구 23
 
7.6%
동 23
 
7.6%
기 23
 
7.6%
분 17
 
5.6%
당 17
 
5.6%
Other values (21) 81
26.9%
Common
ValueCountFrequency (%)
101
53.2%
1 21
 
11.1%
2 11
 
5.8%
5 9
 
4.7%
0 8
 
4.2%
- 8
 
4.2%
3 8
 
4.2%
6 6
 
3.2%
7 6
 
3.2%
8 5
 
2.6%
Other values (2) 7
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
61.3%
ASCII 190
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
53.2%
1 21
 
11.1%
2 11
 
5.8%
5 9
 
4.7%
0 8
 
4.2%
- 8
 
4.2%
3 8
 
4.2%
6 6
 
3.2%
7 6
 
3.2%
8 5
 
2.6%
Other values (2) 7
 
3.7%
Hangul
ValueCountFrequency (%)
성 24
 
8.0%
남 24
 
8.0%
경 23
 
7.6%
도 23
 
7.6%
시 23
 
7.6%
구 23
 
7.6%
동 23
 
7.6%
기 23
 
7.6%
분 17
 
5.6%
당 17
 
5.6%
Other values (21) 81
26.9%

세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean386.21739
Minimum150
Maximum1834
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T18:01:12.625211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile157.4
Q1180
median259
Q3465.5
95-th percentile788.3
Maximum1834
Range1684
Interquartile range (IQR)285.5

Descriptive statistics

Standard deviation366.20957
Coefficient of variation (CV)0.94819545
Kurtosis11.337148
Mean386.21739
Median Absolute Deviation (MAD)95
Skewness3.0857225
Sum8883
Variance134109.45
MonotonicityNot monotonic
2023-12-12T18:01:12.759325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
624 1
 
4.3%
540 1
 
4.3%
150 1
 
4.3%
161 1
 
4.3%
182 1
 
4.3%
272 1
 
4.3%
265 1
 
4.3%
208 1
 
4.3%
417 1
 
4.3%
514 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
150 1
4.3%
157 1
4.3%
161 1
4.3%
164 1
4.3%
175 1
4.3%
178 1
4.3%
182 1
4.3%
203 1
4.3%
208 1
4.3%
212 1
4.3%
ValueCountFrequency (%)
1834 1
4.3%
803 1
4.3%
656 1
4.3%
624 1
4.3%
540 1
4.3%
514 1
4.3%
417 1
4.3%
378 1
4.3%
307 1
4.3%
272 1
4.3%

사용승인일
Date

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2003-02-07 00:00:00
Maximum2017-10-17 00:00:00
2023-12-12T18:01:12.882348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:12.998375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

최대지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.869565
Minimum12
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T18:01:13.154444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13.1
Q120
median20
Q332.5
95-th percentile35.9
Maximum39
Range27
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation8.1201453
Coefficient of variation (CV)0.32650934
Kurtosis-1.295477
Mean24.869565
Median Absolute Deviation (MAD)7
Skewness0.1501347
Sum572
Variance65.936759
MonotonicityNot monotonic
2023-12-12T18:01:13.349830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20 7
30.4%
34 2
 
8.7%
32 1
 
4.3%
36 1
 
4.3%
12 1
 
4.3%
13 1
 
4.3%
14 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
35 1
 
4.3%
Other values (6) 6
26.1%
ValueCountFrequency (%)
12 1
 
4.3%
13 1
 
4.3%
14 1
 
4.3%
18 1
 
4.3%
19 1
 
4.3%
20 7
30.4%
25 1
 
4.3%
27 1
 
4.3%
30 1
 
4.3%
31 1
 
4.3%
ValueCountFrequency (%)
39 1
4.3%
36 1
4.3%
35 1
4.3%
34 2
8.7%
33 1
4.3%
32 1
4.3%
31 1
4.3%
30 1
4.3%
27 1
4.3%
25 1
4.3%

최대지하층수
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
3
12 
2
8 
0
 
1
6
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)13.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
3 12
52.2%
2 8
34.8%
0 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

Length

2023-12-12T18:01:13.492029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:01:13.635536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 12
52.2%
2 8
34.8%
0 1
 
4.3%
6 1
 
4.3%
1 1
 
4.3%

동수
Real number (ℝ)

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5217391
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T18:01:13.769922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7286244
Coefficient of variation (CV)0.68548898
Kurtosis-1.1965662
Mean2.5217391
Median Absolute Deviation (MAD)1
Skewness0.59598506
Sum58
Variance2.9881423
MonotonicityNot monotonic
2023-12-12T18:01:13.907181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 11
47.8%
4 4
 
17.4%
5 3
 
13.0%
2 2
 
8.7%
3 2
 
8.7%
6 1
 
4.3%
ValueCountFrequency (%)
1 11
47.8%
2 2
 
8.7%
3 2
 
8.7%
4 4
 
17.4%
5 3
 
13.0%
6 1
 
4.3%
ValueCountFrequency (%)
6 1
 
4.3%
5 3
 
13.0%
4 4
 
17.4%
3 2
 
8.7%
2 2
 
8.7%
1 11
47.8%

관리사무실
Text

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T18:01:14.140355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.086957
Min length12

Characters and Unicode

Total characters278
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

Unique18 ?
Unique (%)78.3%

Sample

1st row031-785-5555
2nd row031-785-1900
3rd row031-785-1900
4th row031-785-1900
5th row031-719-1456
ValueCountFrequency (%)
031-785-1900 3
 
13.0%
031-759-9498 2
 
8.7%
031-785-5555 1
 
4.3%
031-759-1212 1
 
4.3%
031-759-4561 1
 
4.3%
031-742-0905 1
 
4.3%
031-705-7949 1
 
4.3%
031-709-9079 1
 
4.3%
031-8016-3938 1
 
4.3%
031-8022-5100 1
 
4.3%
Other values (10) 10
43.5%
2023-12-12T18:01:14.552166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
17.3%
- 46
16.5%
1 40
14.4%
3 33
11.9%
9 27
9.7%
7 26
9.4%
5 17
 
6.1%
8 15
 
5.4%
2 12
 
4.3%
4 9
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 232
83.5%
Dash Punctuation 46
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
20.7%
1 40
17.2%
3 33
14.2%
9 27
11.6%
7 26
11.2%
5 17
 
7.3%
8 15
 
6.5%
2 12
 
5.2%
4 9
 
3.9%
6 5
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 278
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
17.3%
- 46
16.5%
1 40
14.4%
3 33
11.9%
9 27
9.7%
7 26
9.4%
5 17
 
6.1%
8 15
 
5.4%
2 12
 
4.3%
4 9
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 278
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
17.3%
- 46
16.5%
1 40
14.4%
3 33
11.9%
9 27
9.7%
7 26
9.4%
5 17
 
6.1%
8 15
 
5.4%
2 12
 
4.3%
4 9
 
3.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2023-06-15 00:00:00
Maximum2023-06-15 00:00:00
2023-12-12T18:01:14.699960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:14.811713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:01:09.557728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:08.906137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.219393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.656418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.017113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.346862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.745184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.118292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:01:09.450901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:01:14.903941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명도로명주소대지위치세대수사용승인일최대지상층수최대지하층수동수관리사무실
단지명1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
대지위치1.0001.0001.0001.0001.0001.0001.0001.0001.000
세대수1.0001.0001.0001.0000.4410.0000.0000.2590.934
사용승인일1.0001.0001.0000.4411.0000.9671.0000.0000.996
최대지상층수1.0001.0001.0000.0000.9671.0000.0000.0000.967
최대지하층수1.0001.0001.0000.0001.0000.0001.0000.0000.760
동수1.0001.0001.0000.2590.0000.0000.0001.0000.876
관리사무실1.0001.0001.0000.9340.9960.9670.7600.8761.000
2023-12-12T18:01:15.062109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수최대지상층수동수최대지하층수
세대수1.0000.5260.2600.000
최대지상층수0.5261.0000.0470.000
동수0.2600.0471.0000.000
최대지하층수0.0000.0000.0001.000

Missing values

2023-12-12T18:01:09.889600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:01:10.088119image/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

단지명도로명주소대지위치세대수사용승인일최대지상층수최대지하층수동수관리사무실데이터기준일자
0분당로얄팰리스경기도 성남시 분당구 성남대로 449경기도 성남시 분당구 정자동 28-16242003-02-073234031-785-55552023-06-15
1분당아이파크 1경기도 성남시 분당구 정자일로239경기도 성남시 분당구 정자동 95402003-05-303434031-785-19002023-06-15
2분당아이파크 2(공동관리)경기도 성남시 분당구 정자일로213번길 19경기도 성남시 분당구 정자동 10-1 외1필지2242003-05-303132031-785-19002023-06-15
3분당아이파크 3(공동관리)경기도 성남시 분당구 정자일로213번길 5경기도 성남시 분당구 정자동 113072003-05-303432031-785-19002023-06-15
4위브제니스경기도 성남시 분당구 정자일로232번길 25경기도 성남시 분당구 정자동 15-4 외2필지1572003-03-293021031-719-14562023-06-15
5미켈란쉐르빌경기도 성남시 분당구 정자일로 100경기도 성남시 분당구 정자동 1808032003-09-173931031-782-03002023-06-15
6아데나팰리스경기도 성남시 분당구 성남대로 275경기도 성남시 분당구 정자동 169-1 외2필지2032003-04-302723031-719-76082023-06-15
7SK VIEW경기도 성남시 분당구 돌마로 906경기도 성남시 분당구 야탑동 1881752003-11-112034031-703-94002023-06-15
8코오롱 더 프라우경기도 성남시 분당구 정자일로 27경기도 성남시 분당구 금곡동 2011642004-03-263321031-726-38432023-06-15
9분당파크뷰경기도 성남시 분당구 정자일로 248경기도 성남시 분당구 정자동 618342004-07-013531031-783-20002023-06-15
단지명도로명주소대지위치세대수사용승인일최대지상층수최대지하층수동수관리사무실데이터기준일자
13분당더샾스타파크경기도 성남시 분당구 정자일로 121경기도 성남시 분당구 정자동 174-13782007-02-063634031-8022-51002023-06-15
14판교호반써밋플레이스경기도 성남시 분당구 동판교로177번길 25경기도 성남시 분당구 삼평동 740번지1782012-12-271821031-8016-39382023-06-15
15알파리움 2단지경기도 성남시 분당구 판교역로 145경기도 성남시 분당구 백현동 5305142015-11-242036031-709-90792023-06-15
16알파리움 1단지경기도 성남시 분당구 대왕판교로 606번길 10경기도 성남시 분당구 백현동 5314172015-11-241935031-705-79492023-06-15
17위례역 푸르지오 4단지경기도 성남시 수정구 위례광장로 36경기도 성남시 수정구 창곡동 5652082017-10-162005031-759-94982023-06-15
18위례역 푸르지오 6단지경기도 성남시 수정구 위례광장로 12경기도 성남시 수정구 창곡동 5632652017-10-172025031-759-94982023-06-15
19신동아파라디움경기도 성남시 수정구 공원로 322경기도 성남시 수정구 신흥동 2465-7 외2필지2722006-02-172031031-742-09052023-06-15
20태평동 신세계쉐덴경기도 성남시 수정구 수정로 201경기도 성남시 수정구 태평동 7336 외 3필지1822010-06-281461031-759-45612023-06-15
21일성오퍼스원경기도 성남시 수정구 성남대로 1330경기도 성남시 수정구 태평동 5113-7번지1612013-03-221331031-759-12122023-06-15
22보미리전빌경기도 성남시 중원구 광명로 114경기도 성남시 중원구 성남동 2508 외3필지1502003-05-131211031-721-79792023-06-15