Overview

Dataset statistics

Number of variables13
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory121.3 B

Variable types

Categorical7
Numeric6

Dataset

Description2014년 9월 기준 건축허가 통계 자료입니다.
Author경상남도
URLhttps://www.data.go.kr/data/15071389/fileData.do

Alerts

건축주 주택조합 has constant value ""Constant
건축주 주택공사 has constant value ""Constant
건축주 정부투자기관 is highly overall correlated with 건축주 지방공사 and 1 other fieldsHigh correlation
건축주 국가기관 is highly overall correlated with 건축주 계 and 5 other fieldsHigh correlation
건축주 지방공사 is highly overall correlated with 건축주 계 and 5 other fieldsHigh correlation
건축주 계 is highly overall correlated with 건축주 개인 and 4 other fieldsHigh correlation
건축주 개인 is highly overall correlated with 건축주 계 and 5 other fieldsHigh correlation
일반법인 is highly overall correlated with 건축주 계 and 2 other fieldsHigh correlation
건축주 주택업체 is highly overall correlated with 건축주 개인 and 1 other fieldsHigh correlation
건축주 지방자치단체 is highly overall correlated with 건축주 지방공사 and 1 other fieldsHigh correlation
건축주 기타 is highly overall correlated with 건축주 계 and 5 other fieldsHigh correlation
건축주 지방공사 is highly imbalanced (54.4%)Imbalance
건축주 정부투자기관 is highly imbalanced (59.1%)Imbalance
건축주 국가기관 is highly imbalanced (54.4%)Imbalance
건축주 계 has unique valuesUnique
건축주 개인 has 3 (14.3%) zerosZeros
건축주 주택업체 has 16 (76.2%) zerosZeros
건축주 지방자치단체 has 3 (14.3%) zerosZeros
건축주 기타 has 6 (28.6%) zerosZeros

Reproduction

Analysis started2023-12-12 07:54:22.290884
Analysis finished2023-12-12 07:54:27.123079
Duration4.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분1
Categorical

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
주거용
3 
상업용
3 
농수산용
3 
공업용
3 
공공용
3 
Other values (2)
6 

Length

Max length6
Median length3
Mean length3.4285714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주거용
2nd row주거용
3rd row주거용
4th row상업용
5th row상업용

Common Values

ValueCountFrequency (%)
주거용 3
14.3%
상업용 3
14.3%
농수산용 3
14.3%
공업용 3
14.3%
공공용 3
14.3%
문교/사회용 3
14.3%
기타 3
14.3%

Length

2023-12-12T16:54:27.221205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:27.384172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거용 3
14.3%
상업용 3
14.3%
농수산용 3
14.3%
공업용 3
14.3%
공공용 3
14.3%
문교/사회용 3
14.3%
기타 3
14.3%

구분2
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
건 수
7 
동 수
7 
연면적
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건 수
2nd row동 수
3rd row연면적
4th row건 수
5th row동 수

Common Values

ValueCountFrequency (%)
건 수 7
33.3%
동 수 7
33.3%
연면적 7
33.3%

Length

2023-12-12T16:54:27.545003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:27.653693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수 14
40.0%
건 7
20.0%
동 7
20.0%
연면적 7
20.0%

건축주 계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36631.381
Minimum4
Maximum400149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:27.811122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q197
median316
Q316329
95-th percentile169089
Maximum400149
Range400145
Interquartile range (IQR)16232

Descriptive statistics

Standard deviation94367.508
Coefficient of variation (CV)2.5761384
Kurtosis11.702706
Mean36631.381
Median Absolute Deviation (MAD)311
Skewness3.3107564
Sum769259
Variance8.9052265 × 109
MonotonicityNot monotonic
2023-12-12T16:54:27.961143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
651 1
 
4.8%
811 1
 
4.8%
16831 1
 
4.8%
139 1
 
4.8%
99 1
 
4.8%
16329 1
 
4.8%
46 1
 
4.8%
33 1
 
4.8%
4093 1
 
4.8%
5 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
4 1
4.8%
5 1
4.8%
33 1
4.8%
34 1
4.8%
46 1
4.8%
97 1
4.8%
99 1
4.8%
101 1
4.8%
139 1
4.8%
180 1
4.8%
ValueCountFrequency (%)
400149 1
4.8%
169089 1
4.8%
125905 1
4.8%
33957 1
4.8%
16831 1
4.8%
16329 1
4.8%
4093 1
4.8%
811 1
4.8%
651 1
4.8%
390 1
4.8%

건축주 개인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11419.952
Minimum0
Maximum111329
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:28.121745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q127
median96
Q32425
95-th percentile65413
Maximum111329
Range111329
Interquartile range (IQR)2398

Descriptive statistics

Standard deviation27689.736
Coefficient of variation (CV)2.4246805
Kurtosis8.9644674
Mean11419.952
Median Absolute Deviation (MAD)96
Skewness2.9704178
Sum239819
Variance7.6672147 × 108
MonotonicityNot monotonic
2023-12-12T16:54:28.266864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 3
 
14.3%
610 1
 
4.8%
729 1
 
4.8%
9681 1
 
4.8%
96 1
 
4.8%
77 1
 
4.8%
2425 1
 
4.8%
14 1
 
4.8%
11 1
 
4.8%
31853 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
0 3
14.3%
11 1
 
4.8%
14 1
 
4.8%
27 1
 
4.8%
40 1
 
4.8%
61 1
 
4.8%
63 1
 
4.8%
77 1
 
4.8%
96 1
 
4.8%
231 1
 
4.8%
ValueCountFrequency (%)
111329 1
4.8%
65413 1
4.8%
31853 1
4.8%
16878 1
4.8%
9681 1
4.8%
2425 1
4.8%
729 1
4.8%
610 1
4.8%
281 1
4.8%
231 1
4.8%

일반법인
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22548.905
Minimum1
Maximum260565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:28.405185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113
median48
Q36189
95-th percentile92295
Maximum260565
Range260564
Interquartile range (IQR)6176

Descriptive statistics

Standard deviation61020.887
Coefficient of variation (CV)2.7061575
Kurtosis12.373144
Mean22548.905
Median Absolute Deviation (MAD)42
Skewness3.3995085
Sum473527
Variance3.7235486 × 109
MonotonicityNot monotonic
2023-12-12T16:54:28.554931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
13 2
 
9.5%
1 2
 
9.5%
22 1
 
4.8%
55 1
 
4.8%
6189 1
 
4.8%
31 1
 
4.8%
6955 1
 
4.8%
10 1
 
4.8%
636 1
 
4.8%
91848 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
1 2
9.5%
6 1
4.8%
10 1
4.8%
13 2
9.5%
22 1
4.8%
31 1
4.8%
32 1
4.8%
41 1
4.8%
48 1
4.8%
55 1
4.8%
ValueCountFrequency (%)
260565 1
4.8%
92295 1
4.8%
91848 1
4.8%
14589 1
4.8%
6955 1
4.8%
6189 1
4.8%
636 1
4.8%
117 1
4.8%
60 1
4.8%
55 1
4.8%

건축주 주택조합
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 21
100.0%

Length

2023-12-12T16:54:28.702067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:28.828462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

건축주 주택업체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1204.4762
Minimum0
Maximum24928
Zeros16
Zeros (%)76.2%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:28.929146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile355
Maximum24928
Range24928
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5436.2912
Coefficient of variation (CV)4.513407
Kurtosis20.990165
Mean1204.4762
Median Absolute Deviation (MAD)0
Skewness4.5810543
Sum25294
Variance29553262
MonotonicityNot monotonic
2023-12-12T16:54:29.046172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 16
76.2%
3 1
 
4.8%
7 1
 
4.8%
24928 1
 
4.8%
1 1
 
4.8%
355 1
 
4.8%
ValueCountFrequency (%)
0 16
76.2%
1 1
 
4.8%
3 1
 
4.8%
7 1
 
4.8%
355 1
 
4.8%
24928 1
 
4.8%
ValueCountFrequency (%)
24928 1
 
4.8%
355 1
 
4.8%
7 1
 
4.8%
3 1
 
4.8%
1 1
 
4.8%
0 16
76.2%

건축주 주택공사
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 21
100.0%

Length

2023-12-12T16:54:29.170946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:29.273465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

건축주 지방공사
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
18 
1
2 
361
 
1

Length

Max length3
Median length1
Mean length1.0952381
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 18
85.7%
1 2
 
9.5%
361 1
 
4.8%

Length

2023-12-12T16:54:29.422983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:29.554134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
85.7%
1 2
 
9.5%
361 1
 
4.8%

건축주 정부투자기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
18 
1
 
1
2
 
1
91
 
1

Length

Max length2
Median length1
Mean length1.047619
Min length1

Unique

Unique3 ?
Unique (%)14.3%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row2

Common Values

ValueCountFrequency (%)
0 18
85.7%
1 1
 
4.8%
2 1
 
4.8%
91 1
 
4.8%

Length

2023-12-12T16:54:29.691288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:29.818985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
85.7%
1 1
 
4.8%
2 1
 
4.8%
91 1
 
4.8%

건축주 지방자치단체
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean599.14286
Minimum0
Maximum3844
Zeros3
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:29.919912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q3127
95-th percentile3457
Maximum3844
Range3844
Interquartile range (IQR)126

Descriptive statistics

Standard deviation1251.4147
Coefficient of variation (CV)2.088675
Kurtosis2.0949294
Mean599.14286
Median Absolute Deviation (MAD)4
Skewness1.8904764
Sum12582
Variance1566038.7
MonotonicityNot monotonic
2023-12-12T16:54:30.064009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 3
14.3%
0 3
14.3%
3 2
 
9.5%
4 2
 
9.5%
156 1
 
4.8%
18 1
 
4.8%
21 1
 
4.8%
3844 1
 
4.8%
2 1
 
4.8%
2490 1
 
4.8%
Other values (5) 5
23.8%
ValueCountFrequency (%)
0 3
14.3%
1 3
14.3%
2 1
 
4.8%
3 2
9.5%
4 2
9.5%
8 1
 
4.8%
15 1
 
4.8%
18 1
 
4.8%
21 1
 
4.8%
127 1
 
4.8%
ValueCountFrequency (%)
3844 1
4.8%
3457 1
4.8%
2490 1
4.8%
2427 1
4.8%
156 1
4.8%
127 1
4.8%
21 1
4.8%
18 1
4.8%
15 1
4.8%
8 1
4.8%

건축주 국가기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
18 
2
2 
641
 
1

Length

Max length3
Median length1
Mean length1.0952381
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row0
2nd row0
3rd row0
4th row2
5th row2

Common Values

ValueCountFrequency (%)
0 18
85.7%
2 2
 
9.5%
641 1
 
4.8%

Length

2023-12-12T16:54:30.519222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:54:30.628568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
85.7%
2 2
 
9.5%
641 1
 
4.8%

건축주 기타
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean806.42857
Minimum0
Maximum6089
Zeros6
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T16:54:30.728781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q334
95-th percentile4522
Maximum6089
Range6089
Interquartile range (IQR)34

Descriptive statistics

Standard deviation1724.5045
Coefficient of variation (CV)2.1384466
Kurtosis4.2117458
Mean806.42857
Median Absolute Deviation (MAD)6
Skewness2.2250226
Sum16935
Variance2973915.7
MonotonicityNot monotonic
2023-12-12T16:54:30.857817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 6
28.6%
4 2
 
9.5%
15 1
 
4.8%
19 1
 
4.8%
3171 1
 
4.8%
22 1
 
4.8%
34 1
 
4.8%
6089 1
 
4.8%
1 1
 
4.8%
2 1
 
4.8%
Other values (5) 5
23.8%
ValueCountFrequency (%)
0 6
28.6%
1 1
 
4.8%
2 1
 
4.8%
4 2
 
9.5%
6 1
 
4.8%
8 1
 
4.8%
15 1
 
4.8%
19 1
 
4.8%
22 1
 
4.8%
34 1
 
4.8%
ValueCountFrequency (%)
6089 1
4.8%
4522 1
4.8%
3171 1
4.8%
2204 1
4.8%
834 1
4.8%
34 1
4.8%
22 1
4.8%
19 1
4.8%
15 1
4.8%
8 1
4.8%

Interactions

2023-12-12T16:54:26.202528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:22.759767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.601351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.167922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.920202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.529935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.310560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:22.874594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.682548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.319555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.043877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.663023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.407614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:22.953650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.754320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.456627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.153807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.765126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.520500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.030417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.833623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.574591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.249591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.877520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.615295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.431544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.915265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.678046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.342899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.979851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.703525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:23.520469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.025924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:24.821226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:25.433570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:54:26.099044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:54:30.958602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분1구분2건축주 계건축주 개인일반법인건축주 주택업체건축주 지방공사건축주 정부투자기관건축주 지방자치단체건축주 국가기관건축주 기타
구분11.0000.0000.1760.1690.0000.1320.6460.3650.0000.6460.153
구분20.0001.0000.1760.2980.6120.0440.0000.0000.3400.0000.612
건축주 계0.1760.1761.0001.0001.0001.0000.6310.8290.8320.6311.000
건축주 개인0.1690.2981.0001.0001.0001.0000.6590.5010.6800.6590.888
일반법인0.0000.6121.0001.0001.0001.0000.7460.3510.3560.7461.000
건축주 주택업체0.1320.0441.0001.0001.0001.0000.0000.0000.0000.0001.000
건축주 지방공사0.6460.0000.6310.6590.7460.0001.0001.0000.6331.0000.888
건축주 정부투자기관0.3650.0000.8290.5010.3510.0001.0001.0000.8321.0000.531
건축주 지방자치단체0.0000.3400.8320.6800.3560.0000.6330.8321.0000.6330.746
건축주 국가기관0.6460.0000.6310.6590.7460.0001.0001.0000.6331.0000.888
건축주 기타0.1530.6121.0000.8881.0001.0000.8880.5310.7460.8881.000
2023-12-12T16:54:31.114670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분2건축주 정부투자기관구분1건축주 국가기관건축주 지방공사
구분21.0000.0000.0000.0000.000
건축주 정부투자기관0.0001.0000.1980.9720.972
구분10.0000.1981.0000.4710.471
건축주 국가기관0.0000.9720.4711.0001.000
건축주 지방공사0.0000.9720.4711.0001.000
2023-12-12T16:54:31.241330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축주 계건축주 개인일반법인건축주 주택업체건축주 지방자치단체건축주 기타구분1구분2건축주 지방공사건축주 정부투자기관건축주 국가기관
건축주 계1.0000.8660.9350.5000.4270.6690.0000.1360.6290.4700.629
건축주 개인0.8661.0000.7740.5500.2590.7710.0000.1980.5870.4060.587
일반법인0.9350.7741.0000.3500.3760.5720.0000.2720.3980.3200.398
건축주 주택업체0.5000.5500.3501.0000.1810.5420.0000.0000.0000.0000.000
건축주 지방자치단체0.4270.2590.3760.1811.0000.2740.0000.3080.6320.4730.632
건축주 기타0.6690.7710.5720.5420.2741.0000.0000.2640.5410.3300.541
구분10.0000.0000.0000.0000.0000.0001.0000.0000.4710.1980.471
구분20.1360.1980.2720.0000.3080.2640.0001.0000.0000.0000.000
건축주 지방공사0.6290.5870.3980.0000.6320.5410.4710.0001.0000.9721.000
건축주 정부투자기관0.4700.4060.3200.0000.4730.3300.1980.0000.9721.0000.972
건축주 국가기관0.6290.5870.3980.0000.6320.5410.4710.0001.0000.9721.000

Missing values

2023-12-12T16:54:26.826062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:54:27.042707image/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

구분1구분2건축주 계건축주 개인일반법인건축주 주택조합건축주 주택업체건축주 주택공사건축주 지방공사건축주 정부투자기관건축주 지방자치단체건축주 국가기관건축주 기타
0주거용건 수65161022030001015
1주거용동 수81172955070001019
2주거용연면적40014911132926056502492800015603171
3상업용건 수316231410001118222
4상업용동 수390281480101221234
5상업용연면적1690896541392295035503619138446416089
6농수산용건 수3427600000100
7농수산용동 수97633200000200
8농수산용연면적33957168781458900000249000
9공업용건 수101406000000001
구분1구분2건축주 계건축주 개인일반법인건축주 주택조합건축주 주택업체건축주 주택공사건축주 지방공사건축주 정부투자기관건축주 지방자치단체건축주 국가기관건축주 기타
11공업용연면적125905318539184800000002204
12공공용건 수40100000300
13공공용동 수50100000400
14공공용연면적4093063600000345700
15문교/사회용건 수33111000000804
16문교/사회용동 수461413000001504
17문교/사회용연면적163292425695500000242704522
18기타건 수99771300000306
19기타동 수139963100000408
20기타연면적1683196816189000001270834