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 층수별에 대한 데이터로 공간정보관리번호, X좌표 및 Y좌표 정보, 건물군관리번호, 필지고유번호(PNU), 층수 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15119146/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
층수 has 379 (3.8%) zerosZeros

Reproduction

Analysis started2024-03-14 15:01:56.489661
Analysis finished2024-03-14 15:02:12.227485
Duration15.74 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%
Mean6075.4275
Minimum1
Maximum12147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:12.358854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile620.9
Q13036.5
median6072.5
Q39104.5
95-th percentile11541.05
Maximum12147
Range12146
Interquartile range (IQR)6068

Descriptive statistics

Standard deviation3503.5186
Coefficient of variation (CV)0.5766703
Kurtosis-1.2000519
Mean6075.4275
Median Absolute Deviation (MAD)3034.5
Skewness0.00023588011
Sum60754275
Variance12274642
MonotonicityNot monotonic
2024-03-15T00:02:12.619576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10771 1
 
< 0.1%
5839 1
 
< 0.1%
11621 1
 
< 0.1%
5474 1
 
< 0.1%
1624 1
 
< 0.1%
6618 1
 
< 0.1%
1280 1
 
< 0.1%
6788 1
 
< 0.1%
11025 1
 
< 0.1%
1142 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
ValueCountFrequency (%)
12147 1
< 0.1%
12146 1
< 0.1%
12145 1
< 0.1%
12142 1
< 0.1%
12141 1
< 0.1%
12140 1
< 0.1%
12139 1
< 0.1%
12135 1
< 0.1%
12134 1
< 0.1%
12133 1
< 0.1%

X좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct9929
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23844430
Minimum22440102
Maximum25574377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:13.017139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22440102
5-th percentile22869022
Q123343141
median23815768
Q324180717
95-th percentile25131875
Maximum25574377
Range3134275
Interquartile range (IQR)837576

Descriptive statistics

Standard deviation670088.86
Coefficient of variation (CV)0.028102531
Kurtosis-0.37934149
Mean23844430
Median Absolute Deviation (MAD)458740
Skewness0.53373817
Sum2.384443 × 1011
Variance4.4901907 × 1011
MonotonicityNot monotonic
2024-03-15T00:02:13.451511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23962676 2
 
< 0.1%
23291099 2
 
< 0.1%
23908260 2
 
< 0.1%
23151813 2
 
< 0.1%
23326143 2
 
< 0.1%
23867182 2
 
< 0.1%
23437456 2
 
< 0.1%
23855069 2
 
< 0.1%
23567369 2
 
< 0.1%
24987580 2
 
< 0.1%
Other values (9919) 9980
99.8%
ValueCountFrequency (%)
22440102 1
< 0.1%
22443254 1
< 0.1%
22444773 1
< 0.1%
22458321 1
< 0.1%
22483910 1
< 0.1%
22493316 1
< 0.1%
22540610 1
< 0.1%
22542108 1
< 0.1%
22542336 1
< 0.1%
22542768 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%
25561643 1
< 0.1%
25559470 1
< 0.1%
25555237 1
< 0.1%

Y좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct9963
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25678659
Minimum23670040
Maximum27979338
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:13.884019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23670040
5-th percentile24250727
Q124956238
median25495198
Q326242617
95-th percentile27487517
Maximum27979338
Range4309298
Interquartile range (IQR)1286378.8

Descriptive statistics

Standard deviation956808.79
Coefficient of variation (CV)0.037260855
Kurtosis-0.50607447
Mean25678659
Median Absolute Deviation (MAD)640871
Skewness0.4212093
Sum2.5678659 × 1011
Variance9.1548305 × 1011
MonotonicityNot monotonic
2024-03-15T00:02:14.329595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25250862 3
 
< 0.1%
27204893 2
 
< 0.1%
25697925 2
 
< 0.1%
25477345 2
 
< 0.1%
27198605 2
 
< 0.1%
26024018 2
 
< 0.1%
25482674 2
 
< 0.1%
27482024 2
 
< 0.1%
25530893 2
 
< 0.1%
24347097 2
 
< 0.1%
Other values (9953) 9979
99.8%
ValueCountFrequency (%)
23670040 1
< 0.1%
23694144 1
< 0.1%
23696823 1
< 0.1%
23698721 1
< 0.1%
23699402 1
< 0.1%
23717424 1
< 0.1%
23723079 1
< 0.1%
23744380 1
< 0.1%
23766729 1
< 0.1%
23768390 1
< 0.1%
ValueCountFrequency (%)
27979338 1
< 0.1%
27949950 1
< 0.1%
27942458 1
< 0.1%
27931609 1
< 0.1%
27925980 1
< 0.1%
27915388 1
< 0.1%
27915110 1
< 0.1%
27914168 1
< 0.1%
27913281 1
< 0.1%
27912130 1
< 0.1%

X좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct9941
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23848130
Minimum22443656
Maximum25577671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:14.731445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22443656
5-th percentile22871434
Q123346067
median23819271
Q324187954
95-th percentile25134374
Maximum25577671
Range3134015
Interquartile range (IQR)841886.5

Descriptive statistics

Standard deviation669952.89
Coefficient of variation (CV)0.028092471
Kurtosis-0.37960874
Mean23848130
Median Absolute Deviation (MAD)459024
Skewness0.53380822
Sum2.384813 × 1011
Variance4.4883688 × 1011
MonotonicityNot monotonic
2024-03-15T00:02:15.173737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24743734 2
 
< 0.1%
23903175 2
 
< 0.1%
23898359 2
 
< 0.1%
24954205 2
 
< 0.1%
23297472 2
 
< 0.1%
23469508 2
 
< 0.1%
23296591 2
 
< 0.1%
24010987 2
 
< 0.1%
23010164 2
 
< 0.1%
23480409 2
 
< 0.1%
Other values (9931) 9980
99.8%
ValueCountFrequency (%)
22443656 1
< 0.1%
22446563 1
< 0.1%
22446913 1
< 0.1%
22466092 1
< 0.1%
22486390 1
< 0.1%
22494888 1
< 0.1%
22541514 1
< 0.1%
22543818 1
< 0.1%
22543967 1
< 0.1%
22546089 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%
25565253 1
< 0.1%
25562750 1
< 0.1%
25558714 1
< 0.1%

Y좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct9947
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25682439
Minimum23696544
Maximum28025304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:15.611616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23696544
5-th percentile24254482
Q124960478
median25498256
Q326246240
95-th percentile27492121
Maximum28025304
Range4328760
Interquartile range (IQR)1285761.5

Descriptive statistics

Standard deviation956763.02
Coefficient of variation (CV)0.037253588
Kurtosis-0.5063829
Mean25682439
Median Absolute Deviation (MAD)640556
Skewness0.42242835
Sum2.5682439 × 1011
Variance9.1539547 × 1011
MonotonicityNot monotonic
2024-03-15T00:02:16.044643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25261839 3
 
< 0.1%
25462739 2
 
< 0.1%
25191257 2
 
< 0.1%
24773517 2
 
< 0.1%
25249640 2
 
< 0.1%
25475342 2
 
< 0.1%
24333955 2
 
< 0.1%
24824915 2
 
< 0.1%
25473994 2
 
< 0.1%
25244202 2
 
< 0.1%
Other values (9937) 9979
99.8%
ValueCountFrequency (%)
23696544 1
< 0.1%
23699341 1
< 0.1%
23701398 1
< 0.1%
23702657 1
< 0.1%
23727531 1
< 0.1%
23749731 1
< 0.1%
23764408 1
< 0.1%
23770182 1
< 0.1%
23772950 1
< 0.1%
23777407 1
< 0.1%
ValueCountFrequency (%)
28025304 1
< 0.1%
27980978 1
< 0.1%
27959037 1
< 0.1%
27948330 1
< 0.1%
27933757 1
< 0.1%
27928969 1
< 0.1%
27924141 1
< 0.1%
27916980 1
< 0.1%
27916390 1
< 0.1%
27916249 1
< 0.1%

건물군관리번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15175944
Minimum4
Maximum1.001869 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:16.436450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile2707.85
Q17805.75
median11790
Q315801.25
95-th percentile1.0018181 × 108
Maximum1.001869 × 108
Range1.001869 × 108
Interquartile range (IQR)7995.5

Descriptive statistics

Standard deviation35906158
Coefficient of variation (CV)2.3659917
Kurtosis1.7849235
Mean15175944
Median Absolute Deviation (MAD)3997
Skewness1.9453962
Sum1.5175944 × 1011
Variance1.2892522 × 1015
MonotonicityNot monotonic
2024-03-15T00:02:16.853868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6073 1
 
< 0.1%
12776 1
 
< 0.1%
100171844 1
 
< 0.1%
16131 1
 
< 0.1%
15696 1
 
< 0.1%
9641 1
 
< 0.1%
870 1
 
< 0.1%
14727 1
 
< 0.1%
1886 1
 
< 0.1%
5284 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%
40 1
< 0.1%
43 1
< 0.1%
48 1
< 0.1%
53 1
< 0.1%
ValueCountFrequency (%)
100186900 1
< 0.1%
100186880 1
< 0.1%
100186861 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%

필지고유번호(PNU)
Real number (ℝ)

HIGH CORRELATION 

Distinct7461
Distinct (%)74.6%
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
2024-03-15T00:02:17.301423image/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)1.2987999 × 1013

Descriptive statistics

Standard deviation5.3406382 × 1012
Coefficient of variation (CV)1.1681101 × 10-6
Kurtosis-1.1757228
Mean4.5720332 × 1018
Median Absolute Deviation (MAD)3.0019962 × 1012
Skewness-0.52995714
Sum-9.1470545 × 1018
Variance2.8522417 × 1025
MonotonicityNot monotonic
2024-03-15T00:02:17.849309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4572025021104030000 29
 
0.3%
4572025023100320000 26
 
0.3%
4572025021104060000 26
 
0.3%
4572025023102840000 24
 
0.2%
4572025021104790000 17
 
0.2%
4572031025110530000 16
 
0.2%
4572037024104450000 16
 
0.2%
4572025021103660000 13
 
0.1%
4572038029105030000 13
 
0.1%
4572040024109060000 12
 
0.1%
Other values (7451) 9808
98.1%
ValueCountFrequency (%)
4572025021100280000 1
 
< 0.1%
4572025021100330000 1
 
< 0.1%
4572025021100450000 1
 
< 0.1%
4572025021100540000 1
 
< 0.1%
4572025021100560000 4
< 0.1%
4572025021100570000 1
 
< 0.1%
4572025021100600000 1
 
< 0.1%
4572025021100610000 1
 
< 0.1%
4572025021100620000 1
 
< 0.1%
4572025021100630000 1
 
< 0.1%
ValueCountFrequency (%)
4572040026200520000 2
< 0.1%
4572040026200400000 1
< 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%
4572040026109760000 1
< 0.1%

층수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0292
Minimum0
Maximum5
Zeros379
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T00:02:18.443903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3660065
Coefficient of variation (CV)0.35562233
Kurtosis22.428958
Mean1.0292
Median Absolute Deviation (MAD)0
Skewness2.6693702
Sum10292
Variance0.13396076
MonotonicityNot monotonic
2024-03-15T00:02:18.889367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 9065
90.6%
2 469
 
4.7%
0 379
 
3.8%
3 65
 
0.7%
4 16
 
0.2%
5 6
 
0.1%
ValueCountFrequency (%)
0 379
 
3.8%
1 9065
90.6%
2 469
 
4.7%
3 65
 
0.7%
4 16
 
0.2%
5 6
 
0.1%
ValueCountFrequency (%)
5 6
 
0.1%
4 16
 
0.2%
3 65
 
0.7%
2 469
 
4.7%
1 9065
90.6%
0 379
 
3.8%

Interactions

2024-03-15T00:02:10.435180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:57.302999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:59.247417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.760741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:02.762252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:04.689572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:06.809849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:08.665135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:10.616441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:57.598770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:59.422619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.940213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:02.939231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:04.955290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:07.081273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:08.844950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:10.786679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:57.843943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:59.600324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:01.213371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:03.114221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:05.228763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:07.357281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:09.029652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:10.942683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:58.106695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:59.777895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:01.468392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:03.313901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:05.483968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:07.618733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:09.470695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:11.114461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:58.381789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.063174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:01.736394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:03.591125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:05.757812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:07.904457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:09.654666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:11.270305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:58.648299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.230746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:01.991543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:03.857682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:06.009836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:08.155796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:09.825117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:11.432349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:58.871954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.401990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:02.259968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:04.129526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:06.273156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:08.318937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:10.003496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:11.697425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:01:59.070686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:00.595278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:02.538167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:04.418666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:06.548523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:08.503521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:02:10.199370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:02:19.103743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건물군관리번호필지고유번호(PNU)층수
공간정보관리번호1.0000.8490.8520.8490.8510.3880.8530.177
X좌표최소값0.8491.0000.7301.0000.7290.0640.7880.100
Y좌표최소값0.8520.7301.0000.7300.9980.0740.8290.115
X좌표최대값0.8491.0000.7301.0000.7290.0650.7880.101
Y좌표최대값0.8510.7290.9980.7291.0000.0730.8290.110
건물군관리번호0.3880.0640.0740.0650.0731.0000.0670.095
필지고유번호(PNU)0.8530.7880.8290.7880.8290.0671.0000.093
층수0.1770.1000.1150.1010.1100.0950.0931.000
2024-03-15T00:02:19.416353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건물군관리번호필지고유번호(PNU)층수
공간정보관리번호1.000-0.3040.160-0.3030.1610.0670.694-0.061
X좌표최소값-0.3041.0000.4471.0000.4470.026-0.4650.034
Y좌표최소값0.1600.4471.0000.4471.0000.0250.2280.039
X좌표최대값-0.3031.0000.4471.0000.4470.026-0.4640.034
Y좌표최대값0.1610.4471.0000.4471.0000.0250.2280.039
건물군관리번호0.0670.0260.0250.0260.0251.0000.0060.127
필지고유번호(PNU)0.694-0.4650.228-0.4640.2280.0061.000-0.071
층수-0.0610.0340.0390.0340.0390.127-0.0711.000

Missing values

2024-03-15T00:02:11.905621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:02:12.131688image/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

공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건물군관리번호필지고유번호(PNU)층수
107121077123191239241124202319382724117671607345720360241063400001
33553442249488982666392824951721266667351506945720320211163800001
17472004243524722532080124354820253232141399145720250281009500001
8000777123100842251041182310362425106894746445720370241049600001
921892772393056026843055239450952686303710018544345720400231082400001
65456546226635552457328222666249245762881215245720360251039000001
67356736228516822493816622854189249395931361845720360271052200001
54151323887516254720372389118325476748222045720250211040300001
679651238233342547275323826467254755391599245720250221010500001
3162323824684016273305272468797527344054661445720310251105300001
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값건물군관리번호필지고유번호(PNU)층수
727368972268394025219557226867912522211411745720360281029000000
84335238506602548685723852634254891051319345720250211051700001
45254304253200382622475025323074262268271667445720330231064800001
7628740523171496247826892317461224785960647145720370231111100001
6168227870812523630022790042252388671245245720370241152600001
8054782523183843249600362318698624961830698645720370251055000001
11591111239062512530674023908577253088291550945720250231003200001
5244536323667405245648122366922624567249998645720350221063600001
62559723860916254670642386700525471285374245720250211036400001
120891177723372807261459712337518126151003836445720380211029400001