Overview

Dataset statistics

Number of variables11
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory100.0 B

Variable types

Categorical3
Numeric8

Dataset

Description2023 5 31 기준 인천시 의무 관리 대상 공동주택 현황 군구별 데이터이며 세대 숫자별 구분되어 있습니다.※ 의무관리대상 공동주택 산정기준공동주택관리법 시행령 제2조(의무관리대상 공동주택의 범위)에 따라, 분양세대를 기준으로1. 300세대 이상의 공동주택2. 150세대 이상으로서 승강기가 설치된 공동주택3. 150세대 이상으로서 중앙집중식 난방방식(지역난방방식을 포함한다)의 공동주택4. 「건축법」 제11조에 따른 건축허가를 받아 주택 외의 시설과 주택을 동일건축물로 건축한 건축물로서주택이 150세대 이상인 건축물
Author인천광역시
URLhttps://www.data.go.kr/data/15055214/fileData.do

Alerts

단지수 is highly overall correlated with 동수 and 7 other fieldsHigh correlation
동수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
세대수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 2000세대이상3000세대미만 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 1000세대이상2000세대미만 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 500세대이상1000세대미만 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 300세대이상 500세대미만 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 150세대이상300세대미만 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 3000세대이상 단지수 is highly overall correlated with 단지수 and 7 other fieldsHigh correlation
의무관리대상 공동주택 3000세대이상 단지수 is highly imbalanced (64.7%)Imbalance
단지수 has 26 (59.1%) zerosZeros
동수 has 26 (59.1%) zerosZeros
세대수 has 26 (59.1%) zerosZeros
의무관리대상 공동주택 2000세대이상3000세대미만 단지수 has 35 (79.5%) zerosZeros
의무관리대상 공동주택 1000세대이상2000세대미만 단지수 has 32 (72.7%) zerosZeros
의무관리대상 공동주택 500세대이상1000세대미만 단지수 has 28 (63.6%) zerosZeros
의무관리대상 공동주택 300세대이상 500세대미만 단지수 has 29 (65.9%) zerosZeros
의무관리대상 공동주택 150세대이상300세대미만 단지수 has 28 (63.6%) zerosZeros

Reproduction

Analysis started2023-12-11 23:23:19.266895
Analysis finished2023-12-11 23:23:26.792122
Duration7.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
인천광역시
4 
강화군
4 
옹진군
4 
중구
4 
동구
4 
Other values (6)
24 

Length

Max length6
Median length5
Mean length4.8181818
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시
2nd row인천광역시
3rd row인천광역시
4th row인천광역시
5th row 강화군

Common Values

ValueCountFrequency (%)
인천광역시 4
9.1%
강화군 4
9.1%
옹진군 4
9.1%
중구 4
9.1%
동구 4
9.1%
미추홀구 4
9.1%
연수구 4
9.1%
남동구 4
9.1%
부평구 4
9.1%
계양구 4
9.1%

Length

2023-12-12T08:23:26.904713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천광역시 4
9.1%
강화군 4
9.1%
옹진군 4
9.1%
중구 4
9.1%
동구 4
9.1%
미추홀구 4
9.1%
연수구 4
9.1%
남동구 4
9.1%
부평구 4
9.1%
계양구 4
9.1%

유형
Categorical

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
아파트
11 
주상복합
11 
연립
11 
다세대
11 

Length

Max length4
Median length3.5
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아파트
2nd row주상복합
3rd row연립
4th row다세대
5th row아파트

Common Values

ValueCountFrequency (%)
아파트 11
25.0%
주상복합 11
25.0%
연립 11
25.0%
다세대 11
25.0%

Length

2023-12-12T08:23:27.073355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:23:27.195462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 11
25.0%
주상복합 11
25.0%
연립 11
25.0%
다세대 11
25.0%

단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.818182
Minimum0
Maximum890
Zeros26
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:27.326147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38.5
95-th percentile142.55
Maximum890
Range890
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation139.58498
Coefficient of variation (CV)3.3379017
Kurtosis33.314817
Mean41.818182
Median Absolute Deviation (MAD)0
Skewness5.5139179
Sum1840
Variance19483.966
MonotonicityNot monotonic
2023-12-12T08:23:27.465269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 26
59.1%
8 2
 
4.5%
3 2
 
4.5%
890 1
 
2.3%
132 1
 
2.3%
5 1
 
2.3%
208 1
 
2.3%
1 1
 
2.3%
108 1
 
2.3%
140 1
 
2.3%
Other values (7) 7
 
15.9%
ValueCountFrequency (%)
0 26
59.1%
1 1
 
2.3%
3 2
 
4.5%
4 1
 
2.3%
5 1
 
2.3%
8 2
 
4.5%
10 1
 
2.3%
22 1
 
2.3%
23 1
 
2.3%
55 1
 
2.3%
ValueCountFrequency (%)
890 1
2.3%
208 1
2.3%
143 1
2.3%
140 1
2.3%
132 1
2.3%
108 1
2.3%
77 1
2.3%
55 1
2.3%
23 1
2.3%
22 1
2.3%

동수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean335
Minimum0
Maximum7111
Zeros26
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:27.614156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q393
95-th percentile1255.2
Maximum7111
Range7111
Interquartile range (IQR)93

Descriptive statistics

Standard deviation1116.9041
Coefficient of variation (CV)3.334042
Kurtosis33.087644
Mean335
Median Absolute Deviation (MAD)0
Skewness5.4923814
Sum14740
Variance1247474.7
MonotonicityNot monotonic
2023-12-12T08:23:27.799534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 26
59.1%
7111 1
 
2.3%
49 1
 
2.3%
117 1
 
2.3%
1634 1
 
2.3%
6 1
 
2.3%
654 1
 
2.3%
1072 1
 
2.3%
3 1
 
2.3%
1257 1
 
2.3%
Other values (9) 9
 
20.5%
ValueCountFrequency (%)
0 26
59.1%
3 1
 
2.3%
6 1
 
2.3%
23 1
 
2.3%
27 1
 
2.3%
49 1
 
2.3%
57 1
 
2.3%
85 1
 
2.3%
117 1
 
2.3%
174 1
 
2.3%
ValueCountFrequency (%)
7111 1
2.3%
1634 1
2.3%
1257 1
2.3%
1245 1
2.3%
1072 1
2.3%
654 1
2.3%
566 1
2.3%
471 1
2.3%
189 1
2.3%
174 1
2.3%

세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29593.364
Minimum0
Maximum632069
Zeros26
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:27.944326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35667.5
95-th percentile114191.95
Maximum632069
Range632069
Interquartile range (IQR)5667.5

Descriptive statistics

Standard deviation99249.336
Coefficient of variation (CV)3.35377
Kurtosis33.162081
Mean29593.364
Median Absolute Deviation (MAD)0
Skewness5.4967844
Sum1302108
Variance9.8504307 × 109
MonotonicityNot monotonic
2023-12-12T08:23:28.086516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 26
59.1%
632069 1
 
2.3%
9881 1
 
2.3%
1920 1
 
2.3%
135341 1
 
2.3%
724 1
 
2.3%
60714 1
 
2.3%
104245 1
 
2.3%
666 1
 
2.3%
115639 1
 
2.3%
Other values (9) 9
 
20.5%
ValueCountFrequency (%)
0 26
59.1%
666 1
 
2.3%
724 1
 
2.3%
795 1
 
2.3%
1472 1
 
2.3%
1920 1
 
2.3%
2715 1
 
2.3%
4263 1
 
2.3%
9881 1
 
2.3%
15534 1
 
2.3%
ValueCountFrequency (%)
632069 1
2.3%
135341 1
2.3%
115639 1
2.3%
105992 1
2.3%
104245 1
2.3%
60714 1
2.3%
54517 1
2.3%
38372 1
2.3%
17249 1
2.3%
15534 1
2.3%

의무관리대상 공동주택 3000세대이상 단지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size484.0 B
0
38 
1
 
3
8
 
1
2
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)6.8%

Sample

1st row8
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
86.4%
1 3
 
6.8%
8 1
 
2.3%
2 1
 
2.3%
3 1
 
2.3%

Length

2023-12-12T08:23:28.230818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:23:28.351704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
86.4%
1 3
 
6.8%
8 1
 
2.3%
2 1
 
2.3%
3 1
 
2.3%

의무관리대상 공동주택 2000세대이상3000세대미만 단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0454545
Minimum0
Maximum22
Zeros35
Zeros (%)79.5%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:28.462214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.85
Maximum22
Range22
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5170981
Coefficient of variation (CV)3.3641808
Kurtosis30.64317
Mean1.0454545
Median Absolute Deviation (MAD)0
Skewness5.2524202
Sum46
Variance12.369979
MonotonicityNot monotonic
2023-12-12T08:23:28.583777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 35
79.5%
1 2
 
4.5%
2 2
 
4.5%
22 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%
5 1
 
2.3%
3 1
 
2.3%
ValueCountFrequency (%)
0 35
79.5%
1 2
 
4.5%
2 2
 
4.5%
3 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
6 1
 
2.3%
22 1
 
2.3%
ValueCountFrequency (%)
22 1
 
2.3%
6 1
 
2.3%
5 1
 
2.3%
4 1
 
2.3%
3 1
 
2.3%
2 2
 
4.5%
1 2
 
4.5%
0 35
79.5%

의무관리대상 공동주택 1000세대이상2000세대미만 단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9090909
Minimum0
Maximum148
Zeros32
Zeros (%)72.7%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:28.682444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.5
95-th percentile29.25
Maximum148
Range148
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation23.285706
Coefficient of variation (CV)3.3702995
Kurtosis32.907834
Mean6.9090909
Median Absolute Deviation (MAD)0
Skewness5.4737446
Sum304
Variance542.2241
MonotonicityNot monotonic
2023-12-12T08:23:28.783848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 32
72.7%
4 2
 
4.5%
14 2
 
4.5%
148 1
 
2.3%
8 1
 
2.3%
1 1
 
2.3%
30 1
 
2.3%
3 1
 
2.3%
20 1
 
2.3%
25 1
 
2.3%
ValueCountFrequency (%)
0 32
72.7%
1 1
 
2.3%
3 1
 
2.3%
4 2
 
4.5%
8 1
 
2.3%
14 2
 
4.5%
20 1
 
2.3%
25 1
 
2.3%
30 1
 
2.3%
33 1
 
2.3%
ValueCountFrequency (%)
148 1
2.3%
33 1
2.3%
30 1
2.3%
25 1
2.3%
20 1
2.3%
14 2
4.5%
8 1
2.3%
4 2
4.5%
3 1
2.3%
1 1
2.3%

의무관리대상 공동주택 500세대이상1000세대미만 단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.363636
Minimum0
Maximum308
Zeros28
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:28.908485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.5
95-th percentile64.9
Maximum308
Range308
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation48.624375
Coefficient of variation (CV)3.3852413
Kurtosis32.447305
Mean14.363636
Median Absolute Deviation (MAD)0
Skewness5.4321259
Sum632
Variance2364.3298
MonotonicityNot monotonic
2023-12-12T08:23:29.024628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 28
63.6%
1 4
 
9.1%
308 1
 
2.3%
7 1
 
2.3%
17 1
 
2.3%
5 1
 
2.3%
24 1
 
2.3%
2 1
 
2.3%
53 1
 
2.3%
4 1
 
2.3%
Other values (4) 4
 
9.1%
ValueCountFrequency (%)
0 28
63.6%
1 4
 
9.1%
2 1
 
2.3%
4 1
 
2.3%
5 1
 
2.3%
7 1
 
2.3%
17 1
 
2.3%
24 1
 
2.3%
27 1
 
2.3%
43 1
 
2.3%
ValueCountFrequency (%)
308 1
2.3%
71 1
2.3%
67 1
2.3%
53 1
2.3%
43 1
2.3%
27 1
2.3%
24 1
2.3%
17 1
2.3%
7 1
2.3%
5 1
2.3%

의무관리대상 공동주택 300세대이상 500세대미만 단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.409091
Minimum0
Maximum248
Zeros29
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:29.155569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile42
Maximum248
Range248
Interquartile range (IQR)1

Descriptive statistics

Standard deviation38.991542
Coefficient of variation (CV)3.4175854
Kurtosis33.108555
Mean11.409091
Median Absolute Deviation (MAD)0
Skewness5.493953
Sum502
Variance1520.3404
MonotonicityNot monotonic
2023-12-12T08:23:29.330323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 29
65.9%
1 5
 
11.4%
42 2
 
4.5%
248 1
 
2.3%
2 1
 
2.3%
13 1
 
2.3%
7 1
 
2.3%
28 1
 
2.3%
21 1
 
2.3%
37 1
 
2.3%
ValueCountFrequency (%)
0 29
65.9%
1 5
 
11.4%
2 1
 
2.3%
7 1
 
2.3%
13 1
 
2.3%
21 1
 
2.3%
28 1
 
2.3%
37 1
 
2.3%
42 2
 
4.5%
57 1
 
2.3%
ValueCountFrequency (%)
248 1
 
2.3%
57 1
 
2.3%
42 2
 
4.5%
37 1
 
2.3%
28 1
 
2.3%
21 1
 
2.3%
13 1
 
2.3%
7 1
 
2.3%
2 1
 
2.3%
1 5
11.4%

의무관리대상 공동주택 150세대이상300세대미만 단지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7272727
Minimum0
Maximum156
Zeros28
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T08:23:29.460538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile28.4
Maximum156
Range156
Interquartile range (IQR)5

Descriptive statistics

Standard deviation24.663657
Coefficient of variation (CV)3.1917674
Kurtosis31.907873
Mean7.7272727
Median Absolute Deviation (MAD)0
Skewness5.3944927
Sum340
Variance608.29598
MonotonicityNot monotonic
2023-12-12T08:23:29.586002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 28
63.6%
5 2
 
4.5%
2 2
 
4.5%
11 2
 
4.5%
13 2
 
4.5%
3 2
 
4.5%
156 1
 
2.3%
9 1
 
2.3%
6 1
 
2.3%
29 1
 
2.3%
Other values (2) 2
 
4.5%
ValueCountFrequency (%)
0 28
63.6%
2 2
 
4.5%
3 2
 
4.5%
5 2
 
4.5%
6 1
 
2.3%
9 1
 
2.3%
11 2
 
4.5%
13 2
 
4.5%
25 1
 
2.3%
29 1
 
2.3%
ValueCountFrequency (%)
156 1
2.3%
47 1
2.3%
29 1
2.3%
25 1
2.3%
13 2
4.5%
11 2
4.5%
9 1
2.3%
6 1
2.3%
5 2
4.5%
3 2
4.5%

Interactions

2023-12-12T08:23:25.462047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:19.715600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.538285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.417876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.315668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.112173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.831807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.774154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.539307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:19.801895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.618153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.494704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.409737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.201445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.917181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.857202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.649182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:19.925637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.709357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.617972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.517703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.295125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.018695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.934993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.753570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.037827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.804795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.756540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.620973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.377760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.361967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.017247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.866469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.127326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.934500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.901905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.726963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.453963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.430990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.097770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:26.028009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.268066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.058507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.001959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.819250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.540127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.515582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.204017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:26.141402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.350266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.161762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.096342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.908777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.638217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.608174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.300083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:26.242926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:20.439246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:21.279674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:22.198786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.001886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:23.716429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:24.689292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:23:25.377824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:23:29.690304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분유형단지수동수세대수의무관리대상 공동주택 3000세대이상 단지수의무관리대상 공동주택 2000세대이상3000세대미만 단지수의무관리대상 공동주택 1000세대이상2000세대미만 단지수의무관리대상 공동주택 500세대이상1000세대미만 단지수의무관리대상 공동주택 300세대이상 500세대미만 단지수의무관리대상 공동주택 150세대이상300세대미만 단지수
구분1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
유형0.0001.0000.6580.5730.5730.3260.5730.5730.5730.6580.443
단지수0.0000.6581.0000.9990.9990.8090.9830.9830.9830.9960.995
동수0.0000.5730.9991.0001.0000.8450.9910.9910.9910.9900.985
세대수0.0000.5730.9991.0001.0000.8450.9910.9910.9910.9900.985
의무관리대상 공동주택 3000세대이상 단지수0.0000.3260.8090.8450.8451.0000.8780.8780.8780.8090.723
의무관리대상 공동주택 2000세대이상3000세대미만 단지수0.0000.5730.9830.9910.9910.8781.0001.0000.9790.9610.961
의무관리대상 공동주택 1000세대이상2000세대미만 단지수0.0000.5730.9830.9910.9910.8781.0001.0000.9790.9610.961
의무관리대상 공동주택 500세대이상1000세대미만 단지수0.0000.5730.9830.9910.9910.8780.9790.9791.0000.9770.961
의무관리대상 공동주택 300세대이상 500세대미만 단지수0.0000.6580.9960.9900.9900.8090.9610.9610.9771.0000.995
의무관리대상 공동주택 150세대이상300세대미만 단지수0.0000.4430.9950.9850.9850.7230.9610.9610.9610.9951.000
2023-12-12T08:23:29.860005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분유형의무관리대상 공동주택 3000세대이상 단지수
구분1.0000.0000.000
유형0.0001.0000.264
의무관리대상 공동주택 3000세대이상 단지수0.0000.2641.000
2023-12-12T08:23:29.960027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지수동수세대수의무관리대상 공동주택 2000세대이상3000세대미만 단지수의무관리대상 공동주택 1000세대이상2000세대미만 단지수의무관리대상 공동주택 500세대이상1000세대미만 단지수의무관리대상 공동주택 300세대이상 500세대미만 단지수의무관리대상 공동주택 150세대이상300세대미만 단지수구분유형의무관리대상 공동주택 3000세대이상 단지수
단지수1.0000.9950.9990.7520.8780.9590.9320.9500.0000.3080.762
동수0.9951.0000.9960.7380.8510.9490.9390.9460.0000.2510.810
세대수0.9990.9961.0000.7590.8800.9630.9280.9400.0000.2510.810
의무관리대상 공동주택 2000세대이상3000세대미만 단지수0.7520.7380.7591.0000.8560.7850.6890.6780.0000.2510.858
의무관리대상 공동주택 1000세대이상2000세대미만 단지수0.8780.8510.8800.8561.0000.9090.8410.8370.0000.2510.858
의무관리대상 공동주택 500세대이상1000세대미만 단지수0.9590.9490.9630.7850.9091.0000.9040.8850.0000.2510.858
의무관리대상 공동주택 300세대이상 500세대미만 단지수0.9320.9390.9280.6890.8410.9041.0000.9680.0000.3080.762
의무관리대상 공동주택 150세대이상300세대미만 단지수0.9500.9460.9400.6780.8370.8850.9681.0000.0000.1800.654
구분0.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.000
유형0.3080.2510.2510.2510.2510.2510.3080.1800.0001.0000.264
의무관리대상 공동주택 3000세대이상 단지수0.7620.8100.8100.8580.8580.8580.7620.6540.0000.2641.000

Missing values

2023-12-12T08:23:26.401914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:23:26.630610image/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

구분유형단지수동수세대수의무관리대상 공동주택 3000세대이상 단지수의무관리대상 공동주택 2000세대이상3000세대미만 단지수의무관리대상 공동주택 1000세대이상2000세대미만 단지수의무관리대상 공동주택 500세대이상1000세대미만 단지수의무관리대상 공동주택 300세대이상 500세대미만 단지수의무관리대상 공동주택 150세대이상300세대미만 단지수
0인천광역시아파트8907111632069822148308248156
1인천광역시주상복합228515534014719
2인천광역시연립81742715000125
3인천광역시다세대000000000
4강화군아파트4231472000112
5강화군주상복합000000000
6강화군연립000000000
7강화군다세대000000000
8옹진군아파트000000000
9옹진군주상복합000000000
구분유형단지수동수세대수의무관리대상 공동주택 3000세대이상 단지수의무관리대상 공동주택 2000세대이상3000세대미만 단지수의무관리대상 공동주택 1000세대이상2000세대미만 단지수의무관리대상 공동주택 500세대이상1000세대미만 단지수의무관리대상 공동주택 300세대이상 500세대미만 단지수의무관리대상 공동주택 150세대이상300세대미만 단지수
34부평구연립000000000
35부평구다세대000000000
36계양구아파트108654607140014274225
37계양구주상복합16724000100
38계양구연립000000000
39계양구다세대000000000
40서구아파트20816341353411333675747
41서구주상복합000000000
42서구연립51171920000113
43서구다세대000000000