Overview

Dataset statistics

Number of variables10
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory89.1 B

Variable types

Numeric6
Categorical3
Text1

Dataset

Description경기도 여주시의 창고시설현황 데이터입니다. 건축구분, 소재지지번주소, 대지면적, 건축면적, 연면적, 건폐율, 용적률, 주용도, 부속용도 데이터를 제공합니다.
Author경기도 여주시
URLhttps://www.data.go.kr/data/15107015/fileData.do

Alerts

주용도 has constant value ""Constant
대지면적 is highly overall correlated with 건축면적 and 1 other fieldsHigh correlation
건축면적 is highly overall correlated with 대지면적 and 2 other fieldsHigh correlation
연면적 is highly overall correlated with 대지면적 and 3 other fieldsHigh correlation
건폐율 is highly overall correlated with 건축면적 and 2 other fieldsHigh correlation
용적률 is highly overall correlated with 연면적 and 2 other fieldsHigh correlation
건축구분 is highly overall correlated with 용적률High correlation
번호 has unique valuesUnique
건축면적 has unique valuesUnique
건폐율 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:51:48.078335
Analysis finished2023-12-11 23:51:51.597451
Duration3.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:51.662022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2023-12-12T08:51:51.782141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

건축구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
신축
33 
증축
6 
대수선
4 

Length

Max length3
Median length2
Mean length2.0930233
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신축
2nd row신축
3rd row신축
4th row신축
5th row대수선

Common Values

ValueCountFrequency (%)
신축 33
76.7%
증축 6
 
14.0%
대수선 4
 
9.3%

Length

2023-12-12T08:51:51.909424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:51:52.013259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 33
76.7%
증축 6
 
14.0%
대수선 4
 
9.3%

소재지지번주소
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T08:51:52.242411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length23.302326
Min length17

Characters and Unicode

Total characters1002
Distinct characters67
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)95.3%

Sample

1st row경기도 여주시 가남읍 건장리 142-23 외1필지
2nd row경기도 여주시 가남읍 하귀리 303-1 외6필지
3rd row경기도 여주시 가남읍 양귀리 208-1 외2필지
4th row경기도 여주시 가남읍 양귀리 589
5th row경기도 여주시 가남읍 양귀리 627-1
ValueCountFrequency (%)
경기도 43
18.1%
여주시 43
18.1%
가남읍 21
 
8.9%
외1필지 6
 
2.5%
본두리 6
 
2.5%
외3필지 5
 
2.1%
심석리 5
 
2.1%
점봉동 5
 
2.1%
외6필지 4
 
1.7%
대신면 4
 
1.7%
Other values (76) 95
40.1%
2023-12-12T08:51:52.603485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
19.4%
경 43
 
4.3%
기 43
 
4.3%
도 43
 
4.3%
여 43
 
4.3%
주 43
 
4.3%
시 43
 
4.3%
1 39
 
3.9%
- 33
 
3.3%
리 32
 
3.2%
Other values (57) 446
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
57.9%
Decimal Number 195
 
19.5%
Space Separator 194
 
19.4%
Dash Punctuation 33
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 43
 
7.4%
기 43
 
7.4%
도 43
 
7.4%
여 43
 
7.4%
주 43
 
7.4%
시 43
 
7.4%
리 32
 
5.5%
지 32
 
5.5%
필 31
 
5.3%
외 31
 
5.3%
Other values (45) 196
33.8%
Decimal Number
ValueCountFrequency (%)
1 39
20.0%
2 30
15.4%
3 20
10.3%
7 20
10.3%
6 17
8.7%
5 17
8.7%
4 17
8.7%
8 13
 
6.7%
0 11
 
5.6%
9 11
 
5.6%
Space Separator
ValueCountFrequency (%)
194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
57.9%
Common 422
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 43
 
7.4%
기 43
 
7.4%
도 43
 
7.4%
여 43
 
7.4%
주 43
 
7.4%
시 43
 
7.4%
리 32
 
5.5%
지 32
 
5.5%
필 31
 
5.3%
외 31
 
5.3%
Other values (45) 196
33.8%
Common
ValueCountFrequency (%)
194
46.0%
1 39
 
9.2%
- 33
 
7.8%
2 30
 
7.1%
3 20
 
4.7%
7 20
 
4.7%
6 17
 
4.0%
5 17
 
4.0%
4 17
 
4.0%
8 13
 
3.1%
Other values (2) 22
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
57.9%
ASCII 422
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
46.0%
1 39
 
9.2%
- 33
 
7.8%
2 30
 
7.1%
3 20
 
4.7%
7 20
 
4.7%
6 17
 
4.0%
5 17
 
4.0%
4 17
 
4.0%
8 13
 
3.1%
Other values (2) 22
 
5.2%
Hangul
ValueCountFrequency (%)
경 43
 
7.4%
기 43
 
7.4%
도 43
 
7.4%
여 43
 
7.4%
주 43
 
7.4%
시 43
 
7.4%
리 32
 
5.5%
지 32
 
5.5%
필 31
 
5.3%
외 31
 
5.3%
Other values (45) 196
33.8%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36170.116
Minimum11306
Maximum148382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:52.708448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11306
5-th percentile13128.1
Q126069
median29120
Q329945
95-th percentile105731.55
Maximum148382
Range137076
Interquartile range (IQR)3876

Descriptive statistics

Standard deviation28394.31
Coefficient of variation (CV)0.78502126
Kurtosis6.2287168
Mean36170.116
Median Absolute Deviation (MAD)2231
Skewness2.4614728
Sum1555315
Variance8.0623686 × 108
MonotonicityNot monotonic
2023-12-12T08:51:52.811671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
107017.5 2
 
4.7%
14405.0 1
 
2.3%
15235.0 1
 
2.3%
29830.0 1
 
2.3%
50150.0 1
 
2.3%
29120.0 1
 
2.3%
29066.0 1
 
2.3%
11306.0 1
 
2.3%
27396.0 1
 
2.3%
17635.0 1
 
2.3%
Other values (32) 32
74.4%
ValueCountFrequency (%)
11306.0 1
2.3%
12442.0 1
2.3%
13090.0 1
2.3%
13471.0 1
2.3%
13892.0 1
2.3%
14405.0 1
2.3%
15235.0 1
2.3%
17635.0 1
2.3%
18443.0 1
2.3%
20486.0 1
2.3%
ValueCountFrequency (%)
148382.0 1
2.3%
107017.5 2
4.7%
94158.0 1
2.3%
65307.0 1
2.3%
61824.0 1
2.3%
51021.0 1
2.3%
50150.0 1
2.3%
30865.0 1
2.3%
30733.0 1
2.3%
29980.0 1
2.3%

건축면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13887.967
Minimum4354.55
Maximum52967.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:52.919297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4354.55
5-th percentile4483.565
Q17398.565
median10955.94
Q313827.39
95-th percentile32204.468
Maximum52967.79
Range48613.24
Interquartile range (IQR)6428.825

Descriptive statistics

Standard deviation11016.226
Coefficient of variation (CV)0.79322092
Kurtosis6.0487077
Mean13887.967
Median Absolute Deviation (MAD)3525.56
Skewness2.3729686
Sum597182.57
Variance1.2135723 × 108
MonotonicityNot monotonic
2023-12-12T08:51:53.024033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4852.1 1
 
2.3%
11007.35 1
 
2.3%
11825.26 1
 
2.3%
24929.59 1
 
2.3%
10844.87 1
 
2.3%
10935.83 1
 
2.3%
4431.55 1
 
2.3%
10955.94 1
 
2.3%
5546.74 1
 
2.3%
15414.08 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
4354.55 1
2.3%
4431.55 1
2.3%
4464.89 1
2.3%
4651.64 1
2.3%
4852.1 1
2.3%
5136.75 1
2.3%
5251.76 1
2.3%
5546.74 1
2.3%
5762.62 1
2.3%
7319.87 1
2.3%
ValueCountFrequency (%)
52967.79 1
2.3%
52946.4 1
2.3%
32381.84 1
2.3%
30608.12 1
2.3%
25831.66 1
2.3%
25369.63 1
2.3%
24929.59 1
2.3%
16814.71 1
2.3%
15995.89 1
2.3%
15414.08 1
2.3%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43760.389
Minimum6018.9
Maximum130989.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:53.125291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6018.9
5-th percentile9596.629
Q122243.765
median42408.58
Q350395.6
95-th percentile109762.99
Maximum130989.76
Range124970.86
Interquartile range (IQR)28151.835

Descriptive statistics

Standard deviation29751.237
Coefficient of variation (CV)0.67986682
Kurtosis1.8966443
Mean43760.389
Median Absolute Deviation (MAD)13443.8
Skewness1.3268522
Sum1881696.7
Variance8.8513609 × 108
MonotonicityNot monotonic
2023-12-12T08:51:53.230478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
50736.92 2
 
4.7%
11959.97 1
 
2.3%
9454.24 1
 
2.3%
49826.51 1
 
2.3%
122146.17 1
 
2.3%
19782.99 1
 
2.3%
35695.07 1
 
2.3%
13937.5 1
 
2.3%
59324.4 1
 
2.3%
10878.13 1
 
2.3%
Other values (32) 32
74.4%
ValueCountFrequency (%)
6018.9 1
2.3%
7898.61 1
2.3%
9454.24 1
2.3%
10878.13 1
2.3%
11959.97 1
2.3%
12083.51 1
2.3%
13802.68 1
2.3%
13937.5 1
2.3%
14263.88 1
2.3%
16413.38 1
2.3%
ValueCountFrequency (%)
130989.76 1
2.3%
122146.17 1
2.3%
109889.82 1
2.3%
108621.55 1
2.3%
75834.73 1
2.3%
72281.46 1
2.3%
59324.4 1
2.3%
55852.38 1
2.3%
53812.31 1
2.3%
50736.92 2
4.7%

건폐율
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.136719
Minimum10.39
Maximum59.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:53.341430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.39
5-th percentile20.57
Q136.5743
median39.3842
Q339.97415
95-th percentile54.00439
Maximum59.81
Range49.42
Interquartile range (IQR)3.39985

Descriptive statistics

Standard deviation9.279629
Coefficient of variation (CV)0.237108
Kurtosis2.2390363
Mean39.136719
Median Absolute Deviation (MAD)2.7956
Skewness-0.60877726
Sum1682.8789
Variance86.111514
MonotonicityNot monotonic
2023-12-12T08:51:53.459649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
33.6834 1
 
2.3%
39.76 1
 
2.3%
39.64 1
 
2.3%
49.71 1
 
2.3%
37.242 1
 
2.3%
37.62 1
 
2.3%
39.19 1
 
2.3%
39.991 1
 
2.3%
31.45 1
 
2.3%
10.39 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
10.39 1
2.3%
17.23 1
2.3%
19.68 1
2.3%
28.58 1
2.3%
31.45 1
2.3%
33.48 1
2.3%
33.6834 1
2.3%
34.391 1
2.3%
35.73 1
2.3%
35.89 1
2.3%
ValueCountFrequency (%)
59.81 1
2.3%
56.76 1
2.3%
54.48 1
2.3%
49.7239 1
2.3%
49.71 1
2.3%
49.51 1
2.3%
49.49 1
2.3%
49.47 1
2.3%
47.8413 1
2.3%
43.8 1
2.3%

용적률
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.197107
Minimum9.61
Maximum146.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T08:51:53.587852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.61
5-th percentile37.70107
Q168.17305
median91.997
Q399.0498
95-th percentile124.261
Maximum146.82
Range137.21
Interquartile range (IQR)30.87675

Descriptive statistics

Standard deviation29.306574
Coefficient of variation (CV)0.34398555
Kurtosis0.23896854
Mean85.197107
Median Absolute Deviation (MAD)15.787
Skewness-0.42865419
Sum3663.4756
Variance858.87529
MonotonicityNot monotonic
2023-12-12T08:51:53.717544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
47.41 2
 
4.7%
44.6419 1
 
2.3%
62.06 1
 
2.3%
98.08 1
 
2.3%
137.74 1
 
2.3%
67.9361 1
 
2.3%
76.21 1
 
2.3%
68.41 1
 
2.3%
95.5293 1
 
2.3%
61.68 1
 
2.3%
Other values (32) 32
74.4%
ValueCountFrequency (%)
9.61 1
2.3%
25.35 1
2.3%
37.0423 1
2.3%
43.63 1
2.3%
44.6419 1
2.3%
47.41 2
4.7%
54.57 1
2.3%
61.68 1
2.3%
62.06 1
2.3%
67.9361 1
2.3%
ValueCountFrequency (%)
146.82 1
2.3%
137.74 1
2.3%
124.53 1
2.3%
121.84 1
2.3%
120.98 1
2.3%
119.11 1
2.3%
116.57 1
2.3%
108.8262 1
2.3%
99.95 1
2.3%
99.8537 1
2.3%

주용도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
창고시설
43 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창고시설 43
100.0%

Length

2023-12-12T08:51:53.839315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:51:53.913447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창고시설 43
100.0%

부속용도
Categorical

Distinct14
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
14 
창고
10 
물류창고
6 
창고시설(물류창고)
2 
집배송시설
2 
Other values (9)
9 

Length

Max length11
Median length4
Mean length4.627907
Min length2

Unique

Unique9 ?
Unique (%)20.9%

Sample

1st row<NA>
2nd row물류창고
3rd row창고
4th row창고
5th row창고

Common Values

ValueCountFrequency (%)
<NA> 14
32.6%
창고 10
23.3%
물류창고 6
14.0%
창고시설(물류창고) 2
 
4.7%
집배송시설 2
 
4.7%
저온창고, 상온창고 1
 
2.3%
창고,사무소 1
 
2.3%
저온창고,상온창고 1
 
2.3%
창고시설(일반창고) 1
 
2.3%
및 근린생활시설 1
 
2.3%
Other values (4) 4
 
9.3%

Length

2023-12-12T08:51:54.006588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 14
30.4%
창고 10
21.7%
물류창고 6
13.0%
창고시설(물류창고 2
 
4.3%
집배송시설 2
 
4.3%
일반창고 2
 
4.3%
저온창고 1
 
2.2%
상온창고 1
 
2.2%
창고,사무소 1
 
2.2%
저온창고,상온창고 1
 
2.2%
Other values (6) 6
13.0%

Interactions

2023-12-12T08:51:50.833223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.381648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.811536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.464307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.896293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.393929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.933753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.446079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.876943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.527562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.967205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.463537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:51.047335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.517736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.951040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.613898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.042839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.540088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:51.136564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.579248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.017602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.674911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.127564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.609159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:51.214188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.646392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.099909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.742278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.224588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.687058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:51.287190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:48.744129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.392652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:49.811913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.314973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:51:50.757439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:51:54.075010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호건축구분소재지지번주소대지면적건축면적연면적건폐율용적률부속용도
번호1.0000.4920.9360.0000.0000.3810.3700.7790.623
건축구분0.4921.0000.0000.4300.6170.3370.7260.7820.757
소재지지번주소0.9360.0001.0001.0001.0001.0001.0001.0001.000
대지면적0.0000.4301.0001.0000.9640.6300.7700.7740.404
건축면적0.0000.6171.0000.9641.0000.7300.6820.7470.611
연면적0.3810.3371.0000.6300.7301.0000.4800.4500.000
건폐율0.3700.7261.0000.7700.6820.4801.0000.7950.110
용적률0.7790.7821.0000.7740.7470.4500.7951.0000.625
부속용도0.6230.7571.0000.4040.6110.0000.1100.6251.000
2023-12-12T08:51:54.167832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축구분부속용도
건축구분1.0000.458
부속용도0.4581.000
2023-12-12T08:51:54.488220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호대지면적건축면적연면적건폐율용적률건축구분부속용도
번호1.000-0.003-0.079-0.174-0.207-0.2130.2640.274
대지면적-0.0031.0000.8680.6050.2500.0860.1780.120
건축면적-0.0790.8681.0000.7910.5880.3050.3150.272
연면적-0.1740.6050.7911.0000.7530.6420.1740.000
건폐율-0.2070.2500.5880.7531.0000.5680.3930.000
용적률-0.2130.0860.3050.6420.5681.0000.6010.255
건축구분0.2640.1780.3150.1740.3930.6011.0000.458
부속용도0.2740.1200.2720.0000.0000.2550.4581.000

Missing values

2023-12-12T08:51:51.400989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:51:51.546204image/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

번호건축구분소재지지번주소대지면적건축면적연면적건폐율용적률주용도부속용도
01신축경기도 여주시 가남읍 건장리 142-23 외1필지14405.04852.111959.9733.683444.6419창고시설<NA>
12신축경기도 여주시 가남읍 하귀리 303-1 외6필지27687.011007.3541229.6539.7692.16창고시설물류창고
23신축경기도 여주시 가남읍 양귀리 208-1 외2필지29365.011660.6947868.4439.7196.96창고시설창고
34신축경기도 여주시 가남읍 양귀리 58913471.05251.766018.938.9943.63창고시설창고
45대수선경기도 여주시 가남읍 양귀리 627-120486.07319.8724781.1735.7399.95창고시설창고
56신축경기도 여주시 가남읍 심석리 67-1951021.025369.63109889.8249.7239124.53창고시설<NA>
67신축경기도 여주시 가남읍 심석리 67-129910.011919.972281.4639.8526120.98창고시설<NA>
78신축경기도 여주시 가남읍 심석리 84-2 외5필지29900.011879.042408.5839.7395.93창고시설창고시설(물류창고)
89신축경기도 여주시 가남읍 심석리 76-17 외1필지25631.010218.4543273.0439.8791.997창고시설<NA>
910신축경기도 여주시 가남읍 심석리 15-129980.011708.1547230.8339.0589.08창고시설물류창고
번호건축구분소재지지번주소대지면적건축면적연면적건폐율용적률주용도부속용도
3334신축경기도 여주시 흥천면 다대리 472-3 외1필지27112.09946.4828688.8736.6970.56창고시설물류센터
3435신축경기도 여주시 흥천면 신근리 275-22 외3필지27991.011184.4546056.8339.957398.7396창고시설<NA>
3536증축경기도 여주시 세종대왕면 신지리 32929286.05762.627898.6119.6825.35창고시설사무실,수위실
3637신축경기도 여주시 강천면 걸은리 877-3 외3필지26889.010674.9249989.139.788.3창고시설<NA>
3738대수선경기도 여주시 대신면 천남리 685 외2필지107017.552967.7950736.9249.4947.41창고시설일반창고
3839증축경기도 여주시 대신면 천남리 685 외2필지107017.552946.450736.9249.4747.41창고시설<NA>
3940신축경기도 여주시 대신면 천남리 81-29 외4필지29599.011376.7437750.8238.4484.91창고시설(일반창고, 사무실)
4041신축경기도 여주시 대신면 장풍리 46228852.010546.9838633.2936.5694.57창고시설창고시설(물류창고)
4142신축경기도 여주시 강천면 간매리 264-212442.04464.8912083.5135.8997.12창고시설<NA>
4243신축경기도 여주시 강천면 간매리 320-413892.04651.6413802.6833.4899.36창고시설창고