Overview

Dataset statistics

Number of variables10
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory90.6 B

Variable types

Numeric8
Categorical1
DateTime1

Dataset

Description전북특별자치도 진안군 도시계획정보시스템 공공 문화체육시설 집행에 대한 데이터로 공간정보관리번호, X좌표 및 Y좌표 정보, 라벨명, 면적_도형, 길이_도형 등 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15119128/fileData.do

Alerts

X좌표최소값 is highly overall correlated with Y좌표최소값 and 1 other fieldsHigh correlation
Y좌표최소값 is highly overall correlated with X좌표최소값 and 2 other fieldsHigh correlation
X좌표최대값 is highly overall correlated with X좌표최소값 and 2 other fieldsHigh correlation
Y좌표최대값 is highly overall correlated with Y좌표최소값 and 1 other fieldsHigh correlation
면적_도형 is highly overall correlated with 길이_도형 and 1 other fieldsHigh correlation
길이_도형 is highly overall correlated with 면적_도형 and 1 other fieldsHigh correlation
라벨명 is highly overall correlated with 면적_도형 and 1 other fieldsHigh correlation
공간정보관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:01:36.689135
Analysis finished2024-03-14 12:01:51.932480
Duration15.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간정보관리번호
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85
Minimum61
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:52.064191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile63.4
Q173
median85
Q397
95-th percentile106.6
Maximum109
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.16810224
Kurtosis-1.2
Mean85
Median Absolute Deviation (MAD)12
Skewness0
Sum4165
Variance204.16667
MonotonicityStrictly increasing
2024-03-14T21:01:52.323272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
61 1
 
2.0%
98 1
 
2.0%
88 1
 
2.0%
89 1
 
2.0%
90 1
 
2.0%
91 1
 
2.0%
92 1
 
2.0%
93 1
 
2.0%
94 1
 
2.0%
95 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
61 1
2.0%
62 1
2.0%
63 1
2.0%
64 1
2.0%
65 1
2.0%
66 1
2.0%
67 1
2.0%
68 1
2.0%
69 1
2.0%
70 1
2.0%
ValueCountFrequency (%)
109 1
2.0%
108 1
2.0%
107 1
2.0%
106 1
2.0%
105 1
2.0%
104 1
2.0%
103 1
2.0%
102 1
2.0%
101 1
2.0%
100 1
2.0%

X좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23808149
Minimum22830318
Maximum25166566
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:52.731062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22830318
5-th percentile22912516
Q123350454
median23789695
Q323924365
95-th percentile25108392
Maximum25166566
Range2336248
Interquartile range (IQR)573911

Descriptive statistics

Standard deviation641233.41
Coefficient of variation (CV)0.026933359
Kurtosis-0.056390044
Mean23808149
Median Absolute Deviation (MAD)406983
Skewness0.73249534
Sum1.1665993 × 109
Variance4.1118029 × 1011
MonotonicityNot monotonic
2024-03-14T21:01:53.172347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
23815488 2
 
4.1%
24679113 1
 
2.0%
23755792 1
 
2.0%
22830318 1
 
2.0%
23382712 1
 
2.0%
23826266 1
 
2.0%
23815744 1
 
2.0%
23785488 1
 
2.0%
23326606 1
 
2.0%
23350454 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
22830318 1
2.0%
22890780 1
2.0%
22910224 1
2.0%
22915953 1
2.0%
22932876 1
2.0%
23006892 1
2.0%
23201837 1
2.0%
23244788 1
2.0%
23249338 1
2.0%
23291292 1
2.0%
ValueCountFrequency (%)
25166566 1
2.0%
25150014 1
2.0%
25114203 1
2.0%
25099676 1
2.0%
25043609 1
2.0%
24976922 1
2.0%
24679113 1
2.0%
24662934 1
2.0%
24444455 1
2.0%
24385675 1
2.0%

Y좌표최소값
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25612581
Minimum24113721
Maximum27537767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:53.589876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24113721
5-th percentile24322039
Q125128235
median25535922
Q325986493
95-th percentile27464382
Maximum27537767
Range3424046
Interquartile range (IQR)858258

Descriptive statistics

Standard deviation888466.63
Coefficient of variation (CV)0.034688681
Kurtosis0.054641131
Mean25612581
Median Absolute Deviation (MAD)450571
Skewness0.5308021
Sum1.2550165 × 109
Variance7.8937296 × 1011
MonotonicityNot monotonic
2024-03-14T21:01:54.045331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
25438859 2
 
4.1%
27406798 1
 
2.0%
25558381 1
 
2.0%
25922282 1
 
2.0%
24241511 1
 
2.0%
25464163 1
 
2.0%
25453682 1
 
2.0%
25565197 1
 
2.0%
24835691 1
 
2.0%
24807373 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
24113721 1
2.0%
24241511 1
2.0%
24319227 1
2.0%
24326257 1
2.0%
24351535 1
2.0%
24478319 1
2.0%
24517972 1
2.0%
24540714 1
2.0%
24799198 1
2.0%
24807373 1
2.0%
ValueCountFrequency (%)
27537767 1
2.0%
27512765 1
2.0%
27502772 1
2.0%
27406798 1
2.0%
27389828 1
2.0%
26671639 1
2.0%
26639557 1
2.0%
26367204 1
2.0%
26359505 1
2.0%
26019445 1
2.0%

X좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23829751
Minimum22911925
Maximum25200538
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:54.473463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22911925
5-th percentile22962966
Q123366970
median23805767
Q323943653
95-th percentile25122731
Maximum25200538
Range2288613
Interquartile range (IQR)576683

Descriptive statistics

Standard deviation633826.81
Coefficient of variation (CV)0.02659813
Kurtosis-0.022332682
Mean23829751
Median Absolute Deviation (MAD)392861
Skewness0.78163168
Sum1.1676578 × 109
Variance4.0173643 × 1011
MonotonicityNot monotonic
2024-03-14T21:01:54.920854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
23825268 2
 
4.1%
24690793 1
 
2.0%
23772448 1
 
2.0%
23019980 1
 
2.0%
23460612 1
 
2.0%
23839476 1
 
2.0%
23832567 1
 
2.0%
23805767 1
 
2.0%
23343565 1
 
2.0%
23366970 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
22911925 1
2.0%
22925934 1
2.0%
22946667 1
2.0%
22987415 1
2.0%
23019980 1
2.0%
23026133 1
2.0%
23212454 1
2.0%
23255292 1
2.0%
23267032 1
2.0%
23306156 1
2.0%
ValueCountFrequency (%)
25200538 1
2.0%
25165309 1
2.0%
25126434 1
2.0%
25117176 1
2.0%
25057133 1
2.0%
24988485 1
2.0%
24690793 1
2.0%
24674746 1
2.0%
24455609 1
2.0%
24398337 1
2.0%

Y좌표최대값
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25632291
Minimum24187928
Maximum27555377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:55.325380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24187928
5-th percentile24336490
Q125156054
median25555447
Q326009647
95-th percentile27477369
Maximum27555377
Range3367449
Interquartile range (IQR)853593

Descriptive statistics

Standard deviation885547.66
Coefficient of variation (CV)0.034548128
Kurtosis0.038388232
Mean25632291
Median Absolute Deviation (MAD)454200
Skewness0.53987375
Sum1.2559822 × 109
Variance7.8419467 × 1011
MonotonicityNot monotonic
2024-03-14T21:01:55.766277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
25448413 2
 
4.1%
27426880 1
 
2.0%
25584107 1
 
2.0%
26054386 1
 
2.0%
24294316 1
 
2.0%
25477503 1
 
2.0%
25470189 1
 
2.0%
25582772 1
 
2.0%
24850744 1
 
2.0%
24823386 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
24187928 1
2.0%
24294316 1
2.0%
24335676 1
2.0%
24337710 1
2.0%
24370881 1
2.0%
24506799 1
2.0%
24533533 1
2.0%
24551127 1
2.0%
24814211 1
2.0%
24823386 1
2.0%
ValueCountFrequency (%)
27555377 1
2.0%
27525081 1
2.0%
27511029 1
2.0%
27426880 1
2.0%
27406638 1
2.0%
26689022 1
2.0%
26650727 1
2.0%
26378531 1
2.0%
26368599 1
2.0%
26054386 1
2.0%

도면번호
Real number (ℝ)

Distinct19
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2653061
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:56.328676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q39
95-th percentile16.6
Maximum19
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.3881642
Coefficient of variation (CV)0.86000014
Kurtosis-0.36588485
Mean6.2653061
Median Absolute Deviation (MAD)3
Skewness0.91401623
Sum307
Variance29.032313
MonotonicityNot monotonic
2024-03-14T21:01:56.696122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 11
22.4%
3 5
10.2%
2 5
10.2%
4 4
 
8.2%
6 3
 
6.1%
5 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
14 2
 
4.1%
7 2
 
4.1%
Other values (9) 10
20.4%
ValueCountFrequency (%)
1 11
22.4%
2 5
10.2%
3 5
10.2%
4 4
 
8.2%
5 3
 
6.1%
6 3
 
6.1%
7 2
 
4.1%
8 2
 
4.1%
9 2
 
4.1%
10 1
 
2.0%
ValueCountFrequency (%)
19 1
2.0%
18 1
2.0%
17 1
2.0%
16 1
2.0%
15 2
4.1%
14 2
4.1%
13 1
2.0%
12 1
2.0%
11 1
2.0%
10 1
2.0%

라벨명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size520.0 B
청사(국가)
14 
초등학교
11 
중학교
고등학교
기타 공공청사시설
Other values (6)

Length

Max length9
Median length7
Mean length5.1632653
Min length3

Unique

Unique3 ?
Unique (%)6.1%

Sample

1st row청사(국가)
2nd row초등학교
3rd row지방자치단체
4th row초등학교
5th row중학교

Common Values

ValueCountFrequency (%)
청사(국가) 14
28.6%
초등학교 11
22.4%
중학교 8
16.3%
고등학교 4
 
8.2%
기타 공공청사시설 3
 
6.1%
기타 학교시설 2
 
4.1%
기타 문화시설 2
 
4.1%
기타 체육시설 2
 
4.1%
지방자치단체 1
 
2.0%
골프장 1
 
2.0%

Length

2024-03-14T21:01:57.116244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청사(국가 14
23.7%
초등학교 11
18.6%
기타 10
16.9%
중학교 8
13.6%
고등학교 4
 
6.8%
공공청사시설 3
 
5.1%
학교시설 2
 
3.4%
문화시설 2
 
3.4%
체육시설 2
 
3.4%
지방자치단체 1
 
1.7%
Other values (2) 2
 
3.4%

면적_도형
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53977.137
Minimum4090.22
Maximum1405821.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:57.495930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4090.22
5-th percentile4925.162
Q18492.89
median12512.63
Q318921.34
95-th percentile154372.65
Maximum1405821.8
Range1401731.6
Interquartile range (IQR)10428.45

Descriptive statistics

Standard deviation205721.12
Coefficient of variation (CV)3.811264
Kurtosis40.973528
Mean53977.137
Median Absolute Deviation (MAD)5050.97
Skewness6.2457519
Sum2644879.7
Variance4.2321177 × 1010
MonotonicityNot monotonic
2024-03-14T21:01:57.933434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
5702.27 2
 
4.1%
12512.63 1
 
2.0%
20252.66 1
 
2.0%
1405821.78 1
 
2.0%
199135.38 1
 
2.0%
9903.66 1
 
2.0%
14378.2 1
 
2.0%
19524.63 1
 
2.0%
14744.59 1
 
2.0%
14550.94 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
4090.22 1
2.0%
4123.05 1
2.0%
4407.09 1
2.0%
5702.27 2
4.1%
5736.8 1
2.0%
6028.69 1
2.0%
6360.63 1
2.0%
6595.86 1
2.0%
6630.13 1
2.0%
7461.66 1
2.0%
ValueCountFrequency (%)
1405821.78 1
2.0%
375963.15 1
2.0%
199135.38 1
2.0%
87228.56 1
2.0%
31280.96 1
2.0%
28231.3 1
2.0%
24544.15 1
2.0%
24331.28 1
2.0%
20304.61 1
2.0%
20252.66 1
2.0%

길이_도형
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean722.89347
Minimum272.89
Maximum6147.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-14T21:01:58.349900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum272.89
5-th percentile313.336
Q1400.22
median488.09
Q3640.95
95-th percentile2086.886
Maximum6147.12
Range5874.23
Interquartile range (IQR)240.73

Descriptive statistics

Standard deviation917.31663
Coefficient of variation (CV)1.2689513
Kurtosis26.563087
Mean722.89347
Median Absolute Deviation (MAD)111.77
Skewness4.854461
Sum35421.78
Variance841469.8
MonotonicityNot monotonic
2024-03-14T21:01:58.784582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
315.37 2
 
4.1%
599.86 1
 
2.0%
778.88 1
 
2.0%
6147.12 1
 
2.0%
2621.15 1
 
2.0%
400.22 1
 
2.0%
474.22 1
 
2.0%
655.09 1
 
2.0%
519.6 1
 
2.0%
525.68 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
272.89 1
2.0%
290.84 1
2.0%
311.98 1
2.0%
315.37 2
4.1%
328.8 1
2.0%
330.17 1
2.0%
336.12 1
2.0%
343.27 1
2.0%
361.4 1
2.0%
365.09 1
2.0%
ValueCountFrequency (%)
6147.12 1
2.0%
2636.69 1
2.0%
2621.15 1
2.0%
1285.49 1
2.0%
957.88 1
2.0%
841.29 1
2.0%
823.19 1
2.0%
817.66 1
2.0%
805.22 1
2.0%
778.88 1
2.0%
Distinct11
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size520.0 B
Minimum2013-01-02 00:00:00
Maximum2020-12-10 00:00:00
2024-03-14T21:01:59.150793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:59.505722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

Interactions

2024-03-14T21:01:49.902698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:37.082346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:38.820039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:40.804184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:42.380220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:44.351031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:46.372846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:48.399114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:50.101378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:37.308553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:39.063787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.051826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:42.619153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:44.596454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:46.625324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:48.652015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:50.348310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:37.448066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:39.299422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.200513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:42.864722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:44.837887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:46.867728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:48.901497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:50.609910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:37.610223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:39.560309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.366411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:43.122891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:45.099125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:47.336405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:49.121827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:50.815569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:37.806273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:39.791725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.515060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:43.357295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:45.341523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:47.476786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:49.271164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:50.970474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:38.060131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:40.041400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.672251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:43.604218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:45.597960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:47.638890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:49.429330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:51.122663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:38.309000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:40.290930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:41.881806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:43.850731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:45.853971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:47.888314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:49.585900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:51.371533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:38.572767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:40.548458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:42.123182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:44.103596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:46.119024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:48.149519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:49.746905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:01:59.764114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값도면번호라벨명면적_도형길이_도형현황도형 생성일지
공간정보관리번호1.0000.5450.6060.5170.5450.0000.3930.0000.0000.555
X좌표최소값0.5451.0000.8160.9920.7390.0000.0000.2980.0000.000
Y좌표최소값0.6060.8161.0000.7380.9950.5300.0000.0000.0000.000
X좌표최대값0.5170.9920.7381.0000.6900.0000.1630.3650.0000.000
Y좌표최대값0.5450.7390.9950.6901.0000.4650.0000.0000.4940.000
도면번호0.0000.0000.5300.0000.4651.0000.0000.0000.0000.000
라벨명0.3930.0000.0000.1630.0000.0001.0000.9240.9260.902
면적_도형0.0000.2980.0000.3650.0000.0000.9241.0001.0000.817
길이_도형0.0000.0000.0000.0000.4940.0000.9261.0001.0000.769
현황도형 생성일지0.5550.0000.0000.0000.0000.0000.9020.8170.7691.000
2024-03-14T21:02:00.092395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값도면번호면적_도형길이_도형라벨명
공간정보관리번호1.000-0.1870.070-0.1760.063-0.055-0.060-0.1700.161
X좌표최소값-0.1871.0000.5140.9980.492-0.193-0.183-0.1830.000
Y좌표최소값0.0700.5141.0000.5250.9960.097-0.229-0.1610.000
X좌표최대값-0.1760.9980.5251.0000.506-0.207-0.167-0.1670.000
Y좌표최대값0.0630.4920.9960.5061.0000.078-0.208-0.1410.000
도면번호-0.055-0.1930.097-0.2070.0781.000-0.025-0.0330.000
면적_도형-0.060-0.183-0.229-0.167-0.208-0.0251.0000.9540.776
길이_도형-0.170-0.183-0.161-0.167-0.141-0.0330.9541.0000.766
라벨명0.1610.0000.0000.0000.0000.0000.7760.7661.000

Missing values

2024-03-14T21:01:51.576289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:01:51.833007image/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

공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값도면번호라벨명면적_도형길이_도형현황도형 생성일지
061246791132740679824690793274268801청사(국가)12512.63599.862013-01-02
162239243652549948423943653255208315초등학교20304.61723.72013-01-02
263237056572537106323752824254017911지방자치단체87228.561285.492013-01-02
364244444552529734524455609253112641초등학교10591.7425.122013-01-02
465251500142596003725165309259772125중학교15586.09591.372013-01-02
566229328762451797222946667245335338초등학교11758.7509.952013-01-02
667228907802447831922911925245067999중학교24331.28817.662013-01-02
7682300689225535922230261332555544714초등학교12490.34823.192013-01-02
8692386845226359505238835852636859916초등학교8714.14421.192013-01-02
970243856752581102824398337258232083청사(국가)8234.58402.552013-01-02
공간정보관리번호X좌표최소값Y좌표최소값X좌표최대값Y좌표최대값도면번호라벨명면적_도형길이_도형현황도형 생성일지
39100229102242411372122987415241879281기타 연구시설375963.152636.692016-03-11
40101235673992566356723580528256745681기타 문화시설9400.73405.582019-08-22
41102251665662601944525200538260368772기타 체육시설28231.3841.292018-11-22
42103232018372594517223212454259582273기타 체육시설9860.76407.722017-08-28
431042324933825969616232670322598966513초등학교18921.34595.292013-01-02
44105232447882596741023255292259785147청사(국가)5736.8328.82018-11-22
45106251142032598649325126434259943172청사(국가)6630.13336.122020-03-04
46107239227312554702023934402255572543기타 공공청사시설6028.69343.272019-11-29
471082329129225996776233061562600964715중학교12933.2483.112013-01-02
48109238704432551229323882228255279054청사(국가)13046.93466.482020-12-10