Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory781.2 KiB
Average record size in memory80.0 B

Variable types

Numeric8

Dataset

Description전북특별자치도 진안군 도시계획정보시스템 건축물 주제도 건폐율별에 대한 데이터로 공간정보관리번호, X좌표 및 Y좌표 정보, 건폐율, 건물군관리번호, 필지고유번호(PNU) 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15119141/fileData.do

Alerts

공간정보관리번호 is highly overall correlated with 필지고유번호(PNU)High correlation
X좌표최소값 is highly overall correlated with X좌표최대값High correlation
Y좌표최소값 is highly overall correlated with Y좌표최대값High correlation
X좌표최대값 is highly overall correlated with X좌표최소값High correlation
Y좌표최대값 is highly overall correlated with Y좌표최소값High correlation
필지고유번호(PNU) is highly overall correlated with 공간정보관리번호High correlation
공간정보관리번호 has unique valuesUnique
건물군관리번호 has unique valuesUnique
건폐율 has 2905 (29.0%) zerosZeros

Reproduction

Analysis started2024-03-15 01:39:27.759165
Analysis finished2024-03-15 01:39:48.598886
Duration20.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6086.9184
Minimum1
Maximum12145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:48.737193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile603.95
Q13083.75
median6099.5
Q39102.25
95-th percentile11528.05
Maximum12145
Range12144
Interquartile range (IQR)6018.5

Descriptive statistics

Standard deviation3495.7212
Coefficient of variation (CV)0.57430065
Kurtosis-1.1883685
Mean6086.9184
Median Absolute Deviation (MAD)3010
Skewness-0.0060194724
Sum60869184
Variance12220067
MonotonicityNot monotonic
2024-03-15T10:39:49.091699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7089 1
 
< 0.1%
5451 1
 
< 0.1%
6698 1
 
< 0.1%
9448 1
 
< 0.1%
8834 1
 
< 0.1%
2052 1
 
< 0.1%
3084 1
 
< 0.1%
10062 1
 
< 0.1%
3941 1
 
< 0.1%
6262 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
ValueCountFrequency (%)
12145 1
< 0.1%
12144 1
< 0.1%
12143 1
< 0.1%
12142 1
< 0.1%
12141 1
< 0.1%
12139 1
< 0.1%
12138 1
< 0.1%
12137 1
< 0.1%
12136 1
< 0.1%
12134 1
< 0.1%

X좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct9933
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23842493
Minimum22440102
Maximum25574377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:49.438723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22440102
5-th percentile22868974
Q123340978
median23815426
Q324164946
95-th percentile25129962
Maximum25574377
Range3134275
Interquartile range (IQR)823968.25

Descriptive statistics

Standard deviation670687.34
Coefficient of variation (CV)0.028129917
Kurtosis-0.3834673
Mean23842493
Median Absolute Deviation (MAD)460762
Skewness0.52848817
Sum2.3842493 × 1011
Variance4.4982151 × 1011
MonotonicityNot monotonic
2024-03-15T10:39:49.884542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23850660 3
 
< 0.1%
23846512 2
 
< 0.1%
25126290 2
 
< 0.1%
23908400 2
 
< 0.1%
22846272 2
 
< 0.1%
23437663 2
 
< 0.1%
23914978 2
 
< 0.1%
23979642 2
 
< 0.1%
23744700 2
 
< 0.1%
25126777 2
 
< 0.1%
Other values (9923) 9979
99.8%
ValueCountFrequency (%)
22440102 1
< 0.1%
22443254 1
< 0.1%
22444773 1
< 0.1%
22457198 1
< 0.1%
22458321 1
< 0.1%
22493316 1
< 0.1%
22540610 1
< 0.1%
22541794 1
< 0.1%
22542108 1
< 0.1%
22542336 1
< 0.1%
ValueCountFrequency (%)
25574377 1
< 0.1%
25573069 1
< 0.1%
25571786 1
< 0.1%
25568337 1
< 0.1%
25567808 1
< 0.1%
25566304 1
< 0.1%
25565980 1
< 0.1%
25563581 1
< 0.1%
25561643 1
< 0.1%
25559470 1
< 0.1%

Y좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct9960
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25678534
Minimum23670040
Maximum27979338
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:50.288273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23670040
5-th percentile24246969
Q124951387
median25496180
Q326247102
95-th percentile27484492
Maximum27979338
Range4309298
Interquartile range (IQR)1295715.2

Descriptive statistics

Standard deviation959254.96
Coefficient of variation (CV)0.037356298
Kurtosis-0.51635985
Mean25678534
Median Absolute Deviation (MAD)643733
Skewness0.41549199
Sum2.5678534 × 1011
Variance9.2017008 × 1011
MonotonicityNot monotonic
2024-03-15T10:39:50.756351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25482674 2
 
< 0.1%
25095354 2
 
< 0.1%
26612103 2
 
< 0.1%
25530893 2
 
< 0.1%
26050551 2
 
< 0.1%
25256751 2
 
< 0.1%
24038023 2
 
< 0.1%
25271968 2
 
< 0.1%
24617110 2
 
< 0.1%
26024018 2
 
< 0.1%
Other values (9950) 9980
99.8%
ValueCountFrequency (%)
23670040 1
< 0.1%
23696823 1
< 0.1%
23698721 1
< 0.1%
23699402 1
< 0.1%
23717424 1
< 0.1%
23723079 1
< 0.1%
23766729 1
< 0.1%
23774842 1
< 0.1%
23785596 1
< 0.1%
23810633 1
< 0.1%
ValueCountFrequency (%)
27979338 1
< 0.1%
27949950 1
< 0.1%
27942458 1
< 0.1%
27915388 1
< 0.1%
27914168 1
< 0.1%
27913281 1
< 0.1%
27911736 1
< 0.1%
27909557 1
< 0.1%
27909309 1
< 0.1%
27908657 1
< 0.1%

X좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct9939
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23846198
Minimum22443656
Maximum25577671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:51.057243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22443656
5-th percentile22871434
Q123343772
median23818823
Q324170791
95-th percentile25133130
Maximum25577671
Range3134015
Interquartile range (IQR)827018.75

Descriptive statistics

Standard deviation670531.4
Coefficient of variation (CV)0.028119007
Kurtosis-0.38385393
Mean23846198
Median Absolute Deviation (MAD)460230.5
Skewness0.52839109
Sum2.3846198 × 1011
Variance4.4961236 × 1011
MonotonicityNot monotonic
2024-03-15T10:39:51.522546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23298804 2
 
< 0.1%
25125093 2
 
< 0.1%
23961634 2
 
< 0.1%
23296591 2
 
< 0.1%
23845034 2
 
< 0.1%
23846914 2
 
< 0.1%
23806149 2
 
< 0.1%
23832155 2
 
< 0.1%
23303726 2
 
< 0.1%
23440310 2
 
< 0.1%
Other values (9929) 9980
99.8%
ValueCountFrequency (%)
22443656 1
< 0.1%
22446563 1
< 0.1%
22446913 1
< 0.1%
22461115 1
< 0.1%
22466092 1
< 0.1%
22494888 1
< 0.1%
22541514 1
< 0.1%
22543818 1
< 0.1%
22543967 1
< 0.1%
22544751 1
< 0.1%
ValueCountFrequency (%)
25577671 1
< 0.1%
25575603 1
< 0.1%
25574568 1
< 0.1%
25571693 1
< 0.1%
25571271 1
< 0.1%
25569378 1
< 0.1%
25568170 1
< 0.1%
25566036 1
< 0.1%
25565253 1
< 0.1%
25562750 1
< 0.1%

Y좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct9944
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25682331
Minimum23699341
Maximum28033127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:51.967663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23699341
5-th percentile24249970
Q124955191
median25499605
Q326250033
95-th percentile27489204
Maximum28033127
Range4333786
Interquartile range (IQR)1294841.8

Descriptive statistics

Standard deviation959349.57
Coefficient of variation (CV)0.037354459
Kurtosis-0.51629143
Mean25682331
Median Absolute Deviation (MAD)643390.5
Skewness0.41682589
Sum2.5682331 × 1011
Variance9.203516 × 1011
MonotonicityNot monotonic
2024-03-15T10:39:52.238793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25261839 3
 
< 0.1%
25838104 2
 
< 0.1%
25428043 2
 
< 0.1%
24721858 2
 
< 0.1%
25501331 2
 
< 0.1%
25219238 2
 
< 0.1%
24333955 2
 
< 0.1%
25497064 2
 
< 0.1%
24733024 2
 
< 0.1%
27381200 2
 
< 0.1%
Other values (9934) 9979
99.8%
ValueCountFrequency (%)
23699341 1
< 0.1%
23701398 1
< 0.1%
23702657 1
< 0.1%
23727531 1
< 0.1%
23764408 1
< 0.1%
23770182 1
< 0.1%
23777407 1
< 0.1%
23788274 1
< 0.1%
23822656 1
< 0.1%
23824569 1
< 0.1%
ValueCountFrequency (%)
28033127 1
< 0.1%
28025304 1
< 0.1%
27980978 1
< 0.1%
27959037 1
< 0.1%
27948330 1
< 0.1%
27924141 1
< 0.1%
27916980 1
< 0.1%
27916390 1
< 0.1%
27914378 1
< 0.1%
27911932 1
< 0.1%

건폐율
Real number (ℝ)

ZEROS 

Distinct3732
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.171545
Minimum0
Maximum222.49
Zeros2905
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:52.595925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16.075
Q327.5225
95-th percentile51.043
Maximum222.49
Range222.49
Interquartile range (IQR)27.5225

Descriptive statistics

Standard deviation18.383754
Coefficient of variation (CV)1.0116781
Kurtosis8.8479621
Mean18.171545
Median Absolute Deviation (MAD)14.33
Skewness1.877122
Sum181715.45
Variance337.96242
MonotonicityNot monotonic
2024-03-15T10:39:52.892677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2905
29.0%
15.0 15
 
0.1%
14.5 11
 
0.1%
24.5 10
 
0.1%
19.8 9
 
0.1%
10.0 9
 
0.1%
21.8 9
 
0.1%
24.0 9
 
0.1%
19.7 8
 
0.1%
15.5 8
 
0.1%
Other values (3722) 7007
70.1%
ValueCountFrequency (%)
0.0 2905
29.0%
0.02 1
 
< 0.1%
0.03 1
 
< 0.1%
0.04 2
 
< 0.1%
0.05 1
 
< 0.1%
0.066 1
 
< 0.1%
0.07 1
 
< 0.1%
0.08 1
 
< 0.1%
0.1 1
 
< 0.1%
0.15 1
 
< 0.1%
ValueCountFrequency (%)
222.49 1
< 0.1%
213.49 1
< 0.1%
200.28 1
< 0.1%
187.87 1
< 0.1%
176.88 1
< 0.1%
163.95 1
< 0.1%
162.58 1
< 0.1%
156.24 1
< 0.1%
149.95 1
< 0.1%
148.96 1
< 0.1%

건물군관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15526564
Minimum4
Maximum1.001869 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:53.409949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile2734.85
Q17883.75
median11890.5
Q315840.25
95-th percentile1.0018202 × 108
Maximum1.001869 × 108
Range1.001869 × 108
Interquartile range (IQR)7956.5

Descriptive statistics

Standard deviation36243843
Coefficient of variation (CV)2.3343118
Kurtosis1.6404899
Mean15526564
Median Absolute Deviation (MAD)3975
Skewness1.9079208
Sum1.5526564 × 1011
Variance1.3136162 × 1015
MonotonicityNot monotonic
2024-03-15T10:39:53.900830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13614 1
 
< 0.1%
12735 1
 
< 0.1%
16970 1
 
< 0.1%
6309 1
 
< 0.1%
17166 1
 
< 0.1%
9104 1
 
< 0.1%
14853 1
 
< 0.1%
16592 1
 
< 0.1%
100186161 1
 
< 0.1%
16210 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
20 1
< 0.1%
22 1
< 0.1%
40 1
< 0.1%
42 1
< 0.1%
43 1
< 0.1%
ValueCountFrequency (%)
100186900 1
< 0.1%
100186880 1
< 0.1%
100186860 1
< 0.1%
100186840 1
< 0.1%
100186819 1
< 0.1%
100186809 1
< 0.1%
100186808 1
< 0.1%
100186805 1
< 0.1%
100186804 1
< 0.1%
100186803 1
< 0.1%

필지고유번호(PNU)
Real number (ℝ)

HIGH CORRELATION 

Distinct7441
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5720332 × 1018
Minimum4.572025 × 1018
Maximum4.57204 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T10:39:54.217362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.572025 × 1018
5-th percentile4.572025 × 1018
Q14.572025 × 1018
median4.572035 × 1018
Q34.572038 × 1018
95-th percentile4.57204 × 1018
Maximum4.57204 × 1018
Range1.50051 × 1013
Interquartile range (IQR)1.2987991 × 1013

Descriptive statistics

Standard deviation5.3174158 × 1012
Coefficient of variation (CV)1.1630309 × 10-6
Kurtosis-1.1511129
Mean4.5720332 × 1018
Median Absolute Deviation (MAD)3.0019925 × 1012
Skewness-0.54349936
Sum-9.146689 × 1018
Variance2.8274911 × 1025
MonotonicityNot monotonic
2024-03-15T10:39:54.649196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4572025021104030000 28
 
0.3%
4572025021104060000 24
 
0.2%
4572025023100320000 24
 
0.2%
4572025023102840000 21
 
0.2%
4572031025110530000 18
 
0.2%
4572025021104790000 16
 
0.2%
4572025022101250000 16
 
0.2%
4572025021103660000 15
 
0.1%
4572037024104450000 15
 
0.1%
4572025021104020000 13
 
0.1%
Other values (7431) 9810
98.1%
ValueCountFrequency (%)
4572025021100280000 1
 
< 0.1%
4572025021100330000 1
 
< 0.1%
4572025021100450000 1
 
< 0.1%
4572025021100540000 1
 
< 0.1%
4572025021100560000 3
< 0.1%
4572025021100570000 1
 
< 0.1%
4572025021100600000 1
 
< 0.1%
4572025021100610000 1
 
< 0.1%
4572025021100630000 1
 
< 0.1%
4572025021100640000 1
 
< 0.1%
ValueCountFrequency (%)
4572040026200720000 1
< 0.1%
4572040026200520000 2
< 0.1%
4572040026200280000 1
< 0.1%
4572040026110540000 1
< 0.1%
4572040026110460000 1
< 0.1%
4572040026109900000 1
< 0.1%
4572040026109880000 1
< 0.1%
4572040026109800000 1
< 0.1%
4572040026109770000 1
< 0.1%
4572040026109360000 1
< 0.1%

Interactions

2024-03-15T10:39:46.074685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:30.370715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:32.674887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:34.943409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:36.947358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:39.261351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:41.831614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:43.942462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:46.269624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:30.790580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:32.968200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:35.211132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:37.221657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:39.576721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:42.111158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:44.217142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:46.502807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:31.047104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:33.247804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:35.480613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:37.499097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:39.888523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:42.414612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:44.483145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:46.740114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:31.312204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:33.578368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:35.738913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:37.774133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:40.161508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:42.693050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:44.744857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:46.961273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:31.594853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:33.853895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:35.962120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:38.051826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:40.584247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:43.021271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:45.027409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:47.241421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:31.857967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:34.120802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:36.146435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:38.318299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:40.852235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:43.217880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:45.513572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:47.462934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:32.118284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:34.382326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:36.397650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:38.581052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:41.123127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:43.374048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:45.672516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:47.701534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:32.389048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:34.656999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:36.665478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:38.854382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:41.403739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:43.665350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:39:45.887946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:39:54.945264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건폐율건물군관리번호필지고유번호(PNU)
공간정보관리번호1.0000.8490.8530.8490.8520.2200.3990.854
X좌표최소값0.8491.0000.7301.0000.7320.1380.0680.791
Y좌표최소값0.8530.7301.0000.7300.9980.1800.0830.829
X좌표최대값0.8491.0000.7301.0000.7320.1370.0690.791
Y좌표최대값0.8520.7320.9980.7321.0000.1820.0740.829
건폐율0.2200.1380.1800.1370.1821.0000.0950.091
건물군관리번호0.3990.0680.0830.0690.0740.0951.0000.071
필지고유번호(PNU)0.8540.7910.8290.7910.8290.0910.0711.000
2024-03-15T10:39:55.259641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건폐율건물군관리번호필지고유번호(PNU)
공간정보관리번호1.000-0.3060.160-0.3050.160-0.0330.0780.690
X좌표최소값-0.3061.0000.4511.0000.4510.0060.036-0.470
Y좌표최소값0.1600.4511.0000.4521.000-0.0690.0100.222
X좌표최대값-0.3051.0000.4521.0000.4510.0040.035-0.469
Y좌표최대값0.1600.4511.0000.4511.000-0.0700.0100.223
건폐율-0.0330.006-0.0690.004-0.0701.0000.102-0.031
건물군관리번호0.0780.0360.0100.0350.0100.1021.0000.006
필지고유번호(PNU)0.690-0.4700.222-0.4690.223-0.0310.0061.000

Missing values

2024-03-15T10:39:48.096728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:39:48.501123image/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

공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건폐율건물군관리번호필지고유번호(PNU)
705670892334683824811826233484382481360821.83136144572037021109780000
774274052317149624782689231746122478596019.4464714572037023111110000
559657992374816124322990237512692432585334.9963024572035027103290000
18081809241049942554973224108189255519260.080884572025028104440000
10748104192391347627895922239170882789842517.27118814572040025105880000
931493732393202626720721239351262672269626.54170144572039022114120000
658765872290697624809396229093072481225521.8794754572036026103690000
64326460232535282413939423255554241422570.051784572036024103840000
572359542356461424545709235667962454795832.1585514572035029107390000
84778225231706552579158723197512258240960.068904572038022200250000
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건폐율건물군관리번호필지고유번호(PNU)
518354092348919024457632234938022445985315.8667624572035023100250000
11086112102330722424800070233091032480233014.453074572037021109220000
58525630238288872402008923852859240432060.08128044572035026200300000
1083510506234375502789640123440354278989400.0155204572040026108870000
468147392474091325777088247451242577951214.962814572033026109420000
379438812487749826339856248796932634231014.01103924572032023107620000
567858812388045724663311238832732466531532.0688494572035028103640000
461942842533764326234446253417772623769018.23117124572033023105980000
1131411536238547542638018623858982263844568.221001825954572039021105400000
993395652502103026503867250238802650611338.4146774572032021105170000