Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows78
Duplicate rows (%)0.8%
Total size in memory918.0 KiB
Average record size in memory94.0 B

Variable types

Text1
Categorical3
Numeric6

Dataset

Description부산광역시 도시공간정보시스템 내 도로 시설 정보입니다.(건축물 용도, 대지면적,높이,용적율,연면적,건축물면적 등)
URLhttps://www.data.go.kr/data/15084593/fileData.do

Alerts

Dataset has 78 (0.8%) duplicate rowsDuplicates
건축물면적 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 건축물면적 and 1 other fieldsHigh correlation
대지면적 is highly overall correlated with 높이 and 2 other fieldsHigh correlation
높이 is highly overall correlated with 연면적 and 3 other fieldsHigh correlation
건폐율 is highly overall correlated with 대지면적 and 2 other fieldsHigh correlation
용적율 is highly overall correlated with 대지면적 and 2 other fieldsHigh correlation
특수지구분명 is highly imbalanced (94.6%)Imbalance
건축물용도명 is highly imbalanced (54.7%)Imbalance
건축물면적 is highly skewed (γ1 = 41.79822687)Skewed
연면적 is highly skewed (γ1 = 44.90209665)Skewed
대지면적 is highly skewed (γ1 = 30.22917117)Skewed
높이 is highly skewed (γ1 = 99.99999959)Skewed
대지면적 has 4794 (47.9%) zerosZeros
높이 has 4557 (45.6%) zerosZeros
건폐율 has 4821 (48.2%) zerosZeros
용적율 has 4827 (48.3%) zerosZeros

Reproduction

Analysis started2023-12-12 10:28:07.728297
Analysis finished2023-12-12 10:28:14.746139
Duration7.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법정동명
Text

Distinct228
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T19:28:14.979108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length13.1736
Min length1

Characters and Unicode

Total characters131736
Distinct characters144
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row부산광역시 금정구 서동
2nd row부산광역시 해운대구 좌동
3rd row부산광역시 금정구 남산동
4th row부산광역시 사하구 하단동
5th row부산광역시 남구 우암동
ValueCountFrequency (%)
부산광역시 9910
32.9%
부산진구 1122
 
3.7%
금정구 788
 
2.6%
남구 754
 
2.5%
강서구 750
 
2.5%
동래구 739
 
2.5%
사상구 721
 
2.4%
해운대구 696
 
2.3%
서구 572
 
1.9%
연제구 562
 
1.9%
Other values (237) 13531
44.9%
2023-12-12T19:28:15.402224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20325
15.4%
산 11611
 
8.8%
부 11584
 
8.8%
동 11227
 
8.5%
광 10263
 
7.8%
시 9924
 
7.5%
역 9910
 
7.5%
구 9783
 
7.4%
대 1736
 
1.3%
서 1708
 
1.3%
Other values (134) 33665
25.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110314
83.7%
Space Separator 20325
 
15.4%
Decimal Number 1097
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 11611
 
10.5%
부 11584
 
10.5%
동 11227
 
10.2%
광 10263
 
9.3%
시 9924
 
9.0%
역 9910
 
9.0%
구 9783
 
8.9%
대 1736
 
1.6%
서 1708
 
1.5%
사 1460
 
1.3%
Other values (127) 31108
28.2%
Decimal Number
ValueCountFrequency (%)
2 414
37.7%
1 325
29.6%
3 207
18.9%
4 97
 
8.8%
5 51
 
4.6%
6 3
 
0.3%
Space Separator
ValueCountFrequency (%)
20325
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110314
83.7%
Common 21422
 
16.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 11611
 
10.5%
부 11584
 
10.5%
동 11227
 
10.2%
광 10263
 
9.3%
시 9924
 
9.0%
역 9910
 
9.0%
구 9783
 
8.9%
대 1736
 
1.6%
서 1708
 
1.5%
사 1460
 
1.3%
Other values (127) 31108
28.2%
Common
ValueCountFrequency (%)
20325
94.9%
2 414
 
1.9%
1 325
 
1.5%
3 207
 
1.0%
4 97
 
0.5%
5 51
 
0.2%
6 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110314
83.7%
ASCII 21422
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20325
94.9%
2 414
 
1.9%
1 325
 
1.5%
3 207
 
1.0%
4 97
 
0.5%
5 51
 
0.2%
6 3
 
< 0.1%
Hangul
ValueCountFrequency (%)
산 11611
 
10.5%
부 11584
 
10.5%
동 11227
 
10.2%
광 10263
 
9.3%
시 9924
 
9.0%
역 9910
 
9.0%
구 9783
 
8.9%
대 1736
 
1.6%
서 1708
 
1.5%
사 1460
 
1.3%
Other values (127) 31108
28.2%

특수지구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9938 
산
 
62

Length

Max length2
Median length2
Mean length1.9938
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 9938
99.4%
산 62
 
0.6%

Length

2023-12-12T19:28:15.550254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:28:15.762292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 9938
99.4%
산 62
 
0.6%

건축물용도명
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
5933 
제2종근린생활시설
993 
공동주택
976 
제1종근린생활시설
793 
공장
 
432
Other values (25)
873 

Length

Max length10
Median length4
Mean length4.9347
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row단독주택
2nd row공동주택
3rd row단독주택
4th row단독주택
5th row공동주택

Common Values

ValueCountFrequency (%)
단독주택 5933
59.3%
제2종근린생활시설 993
 
9.9%
공동주택 976
 
9.8%
제1종근린생활시설 793
 
7.9%
공장 432
 
4.3%
창고시설 165
 
1.7%
교육연구시설 120
 
1.2%
숙박시설 87
 
0.9%
업무시설 86
 
0.9%
동.식물 관련시설 82
 
0.8%
Other values (20) 333
 
3.3%

Length

2023-12-12T19:28:15.895195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 5933
58.9%
제2종근린생활시설 993
 
9.9%
공동주택 976
 
9.7%
제1종근린생활시설 793
 
7.9%
공장 432
 
4.3%
창고시설 165
 
1.6%
교육연구시설 120
 
1.2%
숙박시설 87
 
0.9%
업무시설 86
 
0.9%
동.식물 82
 
0.8%
Other values (20) 406
 
4.0%

건축물구조명
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
블록구조
3305 
철근콘크리트구조
3027 
벽돌구조
1894 
일반목구조
594 
일반철골구조
565 
Other values (13)
615 

Length

Max length11
Median length4
Mean length5.5075
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row벽돌구조
2nd row철근콘크리트구조
3rd row철근콘크리트구조
4th row철근콘크리트구조
5th row철근콘크리트구조

Common Values

ValueCountFrequency (%)
블록구조 3305
33.1%
철근콘크리트구조 3027
30.3%
벽돌구조 1894
18.9%
일반목구조 594
 
5.9%
일반철골구조 565
 
5.7%
기타조적구조 275
 
2.8%
경량철골구조 254
 
2.5%
조적구조 28
 
0.3%
철골철근콘크리트구조 16
 
0.2%
철골콘크리트구조 11
 
0.1%
Other values (8) 31
 
0.3%

Length

2023-12-12T19:28:16.032048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
블록구조 3305
33.1%
철근콘크리트구조 3027
30.3%
벽돌구조 1894
18.9%
일반목구조 594
 
5.9%
일반철골구조 565
 
5.7%
기타조적구조 275
 
2.8%
경량철골구조 254
 
2.5%
조적구조 28
 
0.3%
철골철근콘크리트구조 16
 
0.2%
철골콘크리트구조 11
 
0.1%
Other values (7) 29
 
0.3%

건축물면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6739
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196.37759
Minimum1.6
Maximum70343.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:16.188144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6
5-th percentile24
Q152.5525
median78.98
Q3127.34
95-th percentile517.5725
Maximum70343.5
Range70341.9
Interquartile range (IQR)74.7875

Descriptive statistics

Standard deviation1207.4358
Coefficient of variation (CV)6.1485416
Kurtosis2184.1834
Mean196.37759
Median Absolute Deviation (MAD)31.54
Skewness41.798227
Sum1963775.9
Variance1457901.1
MonotonicityNot monotonic
2023-12-12T19:28:16.367951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.45 44
 
0.4%
33.06 41
 
0.4%
39.67 41
 
0.4%
59.5 41
 
0.4%
66.12 39
 
0.4%
49.59 36
 
0.4%
42.98 26
 
0.3%
19.83 25
 
0.2%
29.75 25
 
0.2%
36.36 25
 
0.2%
Other values (6729) 9657
96.6%
ValueCountFrequency (%)
1.6 1
< 0.1%
1.65 1
< 0.1%
1.8 1
< 0.1%
1.98 1
< 0.1%
2.0 1
< 0.1%
2.2 1
< 0.1%
2.25 1
< 0.1%
2.4 1
< 0.1%
2.6 1
< 0.1%
2.64 1
< 0.1%
ValueCountFrequency (%)
70343.5 1
< 0.1%
66711.82 1
< 0.1%
37176.17 1
< 0.1%
24721.09 1
< 0.1%
19427.74 1
< 0.1%
18498.7701 1
< 0.1%
18107.55 1
< 0.1%
10005.006 1
< 0.1%
9615.9 1
< 0.1%
9589.85 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7931
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean685.43661
Minimum0
Maximum335653.91
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:16.539729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25.9095
Q171.07
median140.52
Q3319.7225
95-th percentile1873.22
Maximum335653.91
Range335653.91
Interquartile range (IQR)248.6525

Descriptive statistics

Standard deviation4550.6023
Coefficient of variation (CV)6.6389834
Kurtosis3015.7572
Mean685.43661
Median Absolute Deviation (MAD)84.305
Skewness44.902097
Sum6854366.1
Variance20707981
MonotonicityNot monotonic
2023-12-12T19:28:16.710612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.45 40
 
0.4%
33.06 40
 
0.4%
59.5 35
 
0.4%
66.12 31
 
0.3%
39.67 29
 
0.3%
49.59 29
 
0.3%
42.98 22
 
0.2%
46.28 22
 
0.2%
29.75 22
 
0.2%
36.36 21
 
0.2%
Other values (7921) 9709
97.1%
ValueCountFrequency (%)
0.0 3
< 0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 1
 
< 0.1%
2.2 1
 
< 0.1%
2.25 1
 
< 0.1%
2.4 1
 
< 0.1%
2.6 1
 
< 0.1%
2.64 1
 
< 0.1%
ValueCountFrequency (%)
335653.91 1
< 0.1%
101631.11 1
< 0.1%
100100.04 1
< 0.1%
83354.315 1
< 0.1%
74540.74 1
< 0.1%
64822.39 1
< 0.1%
54595.54 1
< 0.1%
47506.962 1
< 0.1%
46959.26 1
< 0.1%
46326.96 1
< 0.1%

대지면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2979
Distinct (%)29.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1083.4311
Minimum0
Maximum572538
Zeros4794
Zeros (%)47.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:16.889648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median46
Q3182
95-th percentile1093.335
Maximum572538
Range572538
Interquartile range (IQR)182

Descriptive statistics

Standard deviation12513.111
Coefficient of variation (CV)11.549522
Kurtosis1161.4488
Mean1083.4311
Median Absolute Deviation (MAD)46
Skewness30.229171
Sum10834311
Variance1.5657795 × 108
MonotonicityNot monotonic
2023-12-12T19:28:17.073082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4794
47.9%
50.0 49
 
0.5%
46.0 38
 
0.4%
132.0 32
 
0.3%
330.0 32
 
0.3%
53.0 26
 
0.3%
132.3 25
 
0.2%
129.0 23
 
0.2%
99.0 23
 
0.2%
66.0 22
 
0.2%
Other values (2969) 4936
49.4%
ValueCountFrequency (%)
0.0 4794
47.9%
7.9 1
 
< 0.1%
13.0 1
 
< 0.1%
15.0 1
 
< 0.1%
15.2 1
 
< 0.1%
16.0 2
 
< 0.1%
17.0 3
 
< 0.1%
19.8 1
 
< 0.1%
20.0 1
 
< 0.1%
22.0 2
 
< 0.1%
ValueCountFrequency (%)
572538.0 2
< 0.1%
455818.0 1
< 0.1%
325189.0 1
< 0.1%
280460.9 1
< 0.1%
254715.0 1
< 0.1%
211536.0 2
< 0.1%
170404.8 1
< 0.1%
166362.0 1
< 0.1%
152125.0 1
< 0.1%
132714.0 1
< 0.1%

높이
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct766
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1992.3311
Minimum0
Maximum19860821
Zeros4557
Zeros (%)45.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:17.252727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q39.25
95-th percentile18
Maximum19860821
Range19860821
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation198608.15
Coefficient of variation (CV)99.686318
Kurtosis9999.9999
Mean1992.3311
Median Absolute Deviation (MAD)4
Skewness100
Sum19923311
Variance3.9445196 × 1010
MonotonicityNot monotonic
2023-12-12T19:28:17.426959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4557
45.6%
4.0 487
 
4.9%
8.0 447
 
4.5%
7.3 163
 
1.6%
12.0 126
 
1.3%
7.5 109
 
1.1%
11.9 96
 
1.0%
7.4 93
 
0.9%
7.9 79
 
0.8%
6.9 75
 
0.8%
Other values (756) 3768
37.7%
ValueCountFrequency (%)
0.0 4557
45.6%
1.8 2
 
< 0.1%
2.0 1
 
< 0.1%
2.2 2
 
< 0.1%
2.3 1
 
< 0.1%
2.4 2
 
< 0.1%
2.5 7
 
0.1%
2.55 2
 
< 0.1%
2.6 5
 
0.1%
2.7 5
 
0.1%
ValueCountFrequency (%)
19860821.0 1
< 0.1%
208.5 1
< 0.1%
171.66 1
< 0.1%
157.55 1
< 0.1%
157.05 1
< 0.1%
134.0 1
< 0.1%
128.1 1
< 0.1%
124.15 1
< 0.1%
115.3 1
< 0.1%
111.7 1
< 0.1%

건폐율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3110
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.271441
Minimum0
Maximum167.26
Zeros4821
Zeros (%)48.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:17.600491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.26
Q358.7025
95-th percentile79.87
Maximum167.26
Range167.26
Interquartile range (IQR)58.7025

Descriptive statistics

Standard deviation31.009326
Coefficient of variation (CV)1.0968428
Kurtosis-1.3886386
Mean28.271441
Median Absolute Deviation (MAD)5.26
Skewness0.42815085
Sum282714.41
Variance961.5783
MonotonicityNot monotonic
2023-12-12T19:28:17.778231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4821
48.2%
59.62 20
 
0.2%
59.6 17
 
0.2%
59.64 16
 
0.2%
59.74 16
 
0.2%
59.58 16
 
0.2%
59.81 15
 
0.1%
59.4 15
 
0.1%
59.3 15
 
0.1%
59.76 15
 
0.1%
Other values (3100) 5034
50.3%
ValueCountFrequency (%)
0.0 4821
48.2%
0.01 1
 
< 0.1%
0.02 2
 
< 0.1%
0.03 2
 
< 0.1%
0.0564974 1
 
< 0.1%
0.06 2
 
< 0.1%
0.06275 1
 
< 0.1%
0.07 3
 
< 0.1%
0.0700531 1
 
< 0.1%
0.1 2
 
< 0.1%
ValueCountFrequency (%)
167.26 1
 
< 0.1%
147.33 1
 
< 0.1%
119.92 1
 
< 0.1%
100.0 3
< 0.1%
99.92 1
 
< 0.1%
99.85 1
 
< 0.1%
99.15 1
 
< 0.1%
99.0 2
< 0.1%
98.84 1
 
< 0.1%
98.6 1
 
< 0.1%

용적율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4644
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.975347
Minimum0
Maximum1216.14
Zeros4827
Zeros (%)48.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T19:28:17.941236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9.205
Q3111.32
95-th percentile286.089
Maximum1216.14
Range1216.14
Interquartile range (IQR)111.32

Descriptive statistics

Standard deviation109.62697
Coefficient of variation (CV)1.5022466
Kurtosis13.501684
Mean72.975347
Median Absolute Deviation (MAD)9.205
Skewness2.7076608
Sum729753.47
Variance12018.072
MonotonicityNot monotonic
2023-12-12T19:28:18.099777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4827
48.3%
50.0 13
 
0.1%
348.48 8
 
0.1%
152.92 4
 
< 0.1%
112.03 4
 
< 0.1%
58.84 4
 
< 0.1%
60.0 4
 
< 0.1%
59.02 4
 
< 0.1%
92.15 4
 
< 0.1%
98.85 4
 
< 0.1%
Other values (4634) 5124
51.2%
ValueCountFrequency (%)
0.0 4827
48.3%
0.01 1
 
< 0.1%
0.02 2
 
< 0.1%
0.03 2
 
< 0.1%
0.05 1
 
< 0.1%
0.0564974 1
 
< 0.1%
0.06 2
 
< 0.1%
0.06275 1
 
< 0.1%
0.07 3
 
< 0.1%
0.0700531 1
 
< 0.1%
ValueCountFrequency (%)
1216.14 1
< 0.1%
1184.37 1
< 0.1%
1118.45 1
< 0.1%
1081.89 1
< 0.1%
1042.6326 1
< 0.1%
1022.53 1
< 0.1%
1004.84 1
< 0.1%
1004.55 1
< 0.1%
998.58 1
< 0.1%
995.48 1
< 0.1%

Interactions

2023-12-12T19:28:13.914950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.672603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.465783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.271972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.041351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.890895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:14.019375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.803180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.623750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.402741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.197021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:13.023582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:14.125560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:09.933639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.751627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.530198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.330602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:13.161032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:14.217374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.060536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.864029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.627614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.464318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:13.272811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:14.324392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.206658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.989405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.771752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.623519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:13.418369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:14.418924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:10.333990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.142014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:11.901740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:12.765415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:28:13.525329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:28:18.197304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특수지구분명건축물용도명건축물구조명건축물면적연면적대지면적높이건폐율용적율
특수지구분명1.0000.2210.0400.0000.0000.2900.0000.0520.031
건축물용도명0.2211.0000.6920.0490.1720.4460.0000.2820.508
건축물구조명0.0400.6921.0000.3960.2510.1610.0000.4460.465
건축물면적0.0000.0490.3961.0000.5670.2190.0000.0660.111
연면적0.0000.1720.2510.5671.0000.0910.0000.0190.402
대지면적0.2900.4460.1610.2190.0911.0000.0000.0000.000
높이0.0000.0000.0000.0000.0000.0001.0000.0220.000
건폐율0.0520.2820.4460.0660.0190.0000.0221.0000.526
용적율0.0310.5080.4650.1110.4020.0000.0000.5261.000
2023-12-12T19:28:18.304612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물구조명건축물용도명특수지구분명
건축물구조명1.0000.2550.031
건축물용도명0.2551.0000.175
특수지구분명0.0310.1751.000
2023-12-12T19:28:18.416435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물면적연면적대지면적높이건폐율용적율특수지구분명건축물용도명건축물구조명
건축물면적1.0000.8860.4300.4220.1820.2470.0000.0200.169
연면적0.8861.0000.4460.5610.3340.4340.0000.0750.131
대지면적0.4300.4461.0000.7240.7480.7850.2180.1920.068
높이0.4220.5610.7241.0000.7350.7990.0000.0000.000
건폐율0.1820.3340.7480.7351.0000.9500.0520.1080.163
용적율0.2470.4340.7850.7990.9501.0000.0240.1850.197
특수지구분명0.0000.0000.2180.0000.0520.0241.0000.1750.031
건축물용도명0.0200.0750.1920.0000.1080.1850.1751.0000.255
건축물구조명0.1690.1310.0680.0000.1630.1970.0310.2551.000

Missing values

2023-12-12T19:28:14.541062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:28:14.682766image/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

법정동명특수지구분명건축물용도명건축물구조명건축물면적연면적대지면적높이건폐율용적율
86097부산광역시 금정구 서동일반단독주택벽돌구조44.64133.9250.010.389.28267.84
62637부산광역시 해운대구 좌동일반공동주택철근콘크리트구조4998.79312332.83526974.565.218.5342.19
29747부산광역시 금정구 남산동일반단독주택철근콘크리트구조93.4321.24164.112.056.92195.76
28811부산광역시 사하구 하단동일반단독주택철근콘크리트구조92.88427.32155.518.559.73274.8
42432부산광역시 남구 우암동일반공동주택철근콘크리트구조489.229943.4414923.065.218.78280.55
50931부산광역시 수영구 광안동일반단독주택벽돌구조134.37401.31192.810.169.69208.15
45278부산광역시 금정구 구서동일반공동주택철근콘크리트구조645.0213822.620.068.00.00.0
3954부산광역시 동래구 칠산동일반단독주택벽돌구조66.72126.39112.07.359.57112.85
20432부산광역시 동구 초량동일반단독주택블록구조25.1125.1150.04.050.2250.22
30603부산광역시 수영구 망미동일반단독주택블록구조66.2866.280.00.00.00.0
법정동명특수지구분명건축물용도명건축물구조명건축물면적연면적대지면적높이건폐율용적율
47972부산광역시 연제구 거제동일반단독주택블록구조28.128.10.00.00.00.0
8575부산광역시 해운대구 좌동일반공동주택철근콘크리트구조9615.911468.740.054.618.09256.76
61338부산광역시 해운대구 반송동일반단독주택기타조적구조40.96145.2846.011.689.04315.83
88977부산광역시 사상구 모라동일반단독주택벽돌구조96.98209.69162.070.059.84110.39
87265부산광역시 기장군 철마면 안평리일반동.식물 관련시설블록구조73.9273.920.04.50.00.0
8128부산광역시 남구 용당동일반제1종근린생활시설철근콘크리트구조66.88255.49112.010.459.71157.93
34972부산광역시 사상구 괘법동일반단독주택블록구조82.25164.230.07.70.00.0
37486부산광역시 기장군 일광면 이천리일반제2종근린생활시설철근콘크리트구조103.45248.34527.010.419.6347.12
24342부산광역시 남구 용호동일반제1종근린생활시설철근콘크리트구조67.99133.28113.98.059.69117.01
43816부산광역시 북구 구포동일반단독주택블록구조53.4886.8691.08.058.7795.45

Duplicate rows

Most frequently occurring

법정동명특수지구분명건축물용도명건축물구조명건축물면적연면적대지면적높이건폐율용적율# duplicates
24부산광역시 남구 용호동일반단독주택블록구조26.4526.450.00.00.00.015
55부산광역시 연제구 거제동일반단독주택블록구조59.559.50.00.00.00.06
69부산광역시 영도구 청학동일반단독주택블록구조23.1423.140.00.00.00.06
23부산광역시 남구 용호동일반공동주택철근콘크리트구조79.34158.680.00.00.00.05
64부산광역시 연제구 연산동일반단독주택블록구조66.1266.120.00.00.00.05
6부산광역시 강서구 명지동일반단독주택블록구조33.0633.060.00.00.00.04
42부산광역시 부산진구 전포동일반단독주택블록구조31.1131.110.00.00.00.04
59부산광역시 연제구 연산동일반단독주택블록구조42.9842.980.00.00.00.04
73부산광역시 해운대구 반송동일반단독주택기타조적구조43.56174.2450.011.987.12348.484
4부산광역시 강서구 대저2동일반동.식물 관련시설일반목구조2.982.980.00.00.00.03