Overview

Dataset statistics

Number of variables37
Number of observations146
Missing cells938
Missing cells (%)17.4%
Duplicate rows3
Duplicate rows (%)2.1%
Total size in memory45.3 KiB
Average record size in memory317.9 B

Variable types

Categorical14
Text3
Numeric16
DateTime4

Dataset

Description경상남도 밀양시 건축허가 현황에 대한 자료로, 건축구분, 대지위치, 지목, 면적, 건폐율, 용적률, 구조, 허가 일 등에 대한 정보를 제공합니다.
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15035967

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 3 (2.1%) duplicate rowsDuplicates
승강기합 is highly imbalanced (56.2%)Imbalance
용도지구 is highly imbalanced (72.1%)Imbalance
인근자주식주차장(대) is highly imbalanced (92.5%)Imbalance
세대수 is highly imbalanced (88.9%)Imbalance
호수 is highly imbalanced (92.5%)Imbalance
가구수 is highly imbalanced (69.3%)Imbalance
증축연면적(제곱미터) has 110 (75.3%) missing valuesMissing
착공처리일 has 73 (50.0%) missing valuesMissing
사용승인일 has 121 (82.9%) missing valuesMissing
비상승강기합 has 143 (97.9%) missing valuesMissing
하수처리시설용량(세제곱미터) has 88 (60.3%) missing valuesMissing
부속용도 has 40 (27.4%) missing valuesMissing
자주식옥내주차장(대) has 133 (91.1%) missing valuesMissing
자주식옥외주차장(대) has 79 (54.1%) missing valuesMissing
총주차대수 has 20 (13.7%) missing valuesMissing
총주차장면적(제곱미터) has 20 (13.7%) missing valuesMissing
주건축물수 has 3 (2.1%) missing valuesMissing
부속건축물수 has 108 (74.0%) missing valuesMissing
동수 has 2 (1.4%) zerosZeros
총주차대수 has 53 (36.3%) zerosZeros
총주차장면적(제곱미터) has 61 (41.8%) zerosZeros
부속건축물수 has 3 (2.1%) zerosZeros

Reproduction

Analysis started2023-12-11 00:57:39.948030
Analysis finished2023-12-11 00:57:40.350261
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct5
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
신축
76 
증축
37 
용도변경
27 
대수선
 
3
가설건축물축조허가
 
3

Length

Max length9
Median length2
Mean length2.5342466
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신축
2nd row신축
3rd row증축
4th row용도변경
5th row증축

Common Values

ValueCountFrequency (%)
신축 76
52.1%
증축 37
25.3%
용도변경 27
 
18.5%
대수선 3
 
2.1%
가설건축물축조허가 3
 
2.1%

Length

2023-12-11T09:57:40.411653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:40.504293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 76
52.1%
증축 37
25.3%
용도변경 27
 
18.5%
대수선 3
 
2.1%
가설건축물축조허가 3
 
2.1%

대지위치
Text

Distinct136
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T09:57:40.764228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length22.342466
Min length16

Characters and Unicode

Total characters3262
Distinct characters103
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

Unique128 ?
Unique (%)87.7%

Sample

1st row경상남도 밀양시 삼문동 4-83
2nd row경상남도 밀양시 삼랑진읍 율동리 755
3rd row경상남도 밀양시 산외면 남기리 680
4th row경상남도 밀양시 상남면 기산리 1475-2
5th row경상남도 밀양시 삼랑진읍 미전리 636 외2필지
ValueCountFrequency (%)
경상남도 146
19.6%
밀양시 146
19.6%
외1필지 28
 
3.8%
삼랑진읍 19
 
2.6%
삼문동 15
 
2.0%
상남면 14
 
1.9%
내이동 13
 
1.7%
단장면 13
 
1.7%
하남읍 12
 
1.6%
무안면 12
 
1.6%
Other values (203) 326
43.8%
2023-12-11T09:57:41.151973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
598
18.3%
남 175
 
5.4%
상 163
 
5.0%
양 154
 
4.7%
경 146
 
4.5%
도 146
 
4.5%
밀 146
 
4.5%
시 146
 
4.5%
1 116
 
3.6%
리 104
 
3.2%
Other values (93) 1368
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1954
59.9%
Decimal Number 619
 
19.0%
Space Separator 598
 
18.3%
Dash Punctuation 91
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 175
 
9.0%
상 163
 
8.3%
양 154
 
7.9%
경 146
 
7.5%
도 146
 
7.5%
밀 146
 
7.5%
시 146
 
7.5%
리 104
 
5.3%
면 73
 
3.7%
동 64
 
3.3%
Other values (81) 637
32.6%
Decimal Number
ValueCountFrequency (%)
1 116
18.7%
2 86
13.9%
3 80
12.9%
7 66
10.7%
5 62
10.0%
4 61
9.9%
6 43
 
6.9%
9 43
 
6.9%
8 38
 
6.1%
0 24
 
3.9%
Space Separator
ValueCountFrequency (%)
598
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1954
59.9%
Common 1308
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 175
 
9.0%
상 163
 
8.3%
양 154
 
7.9%
경 146
 
7.5%
도 146
 
7.5%
밀 146
 
7.5%
시 146
 
7.5%
리 104
 
5.3%
면 73
 
3.7%
동 64
 
3.3%
Other values (81) 637
32.6%
Common
ValueCountFrequency (%)
598
45.7%
1 116
 
8.9%
- 91
 
7.0%
2 86
 
6.6%
3 80
 
6.1%
7 66
 
5.0%
5 62
 
4.7%
4 61
 
4.7%
6 43
 
3.3%
9 43
 
3.3%
Other values (2) 62
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1954
59.9%
ASCII 1308
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
598
45.7%
1 116
 
8.9%
- 91
 
7.0%
2 86
 
6.6%
3 80
 
6.1%
7 66
 
5.0%
5 62
 
4.7%
4 61
 
4.7%
6 43
 
3.3%
9 43
 
3.3%
Other values (2) 62
 
4.7%
Hangul
ValueCountFrequency (%)
남 175
 
9.0%
상 163
 
8.3%
양 154
 
7.9%
경 146
 
7.5%
도 146
 
7.5%
밀 146
 
7.5%
시 146
 
7.5%
리 104
 
5.3%
면 73
 
3.7%
동 64
 
3.3%
Other values (81) 637
32.6%

지목
Categorical

Distinct15
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
대
71 
답
22 
공장용지
18 
전
12 
임야
 
5
Other values (10)
18 

Length

Max length4
Median length1
Mean length1.7191781
Min length1

Unique

Unique6 ?
Unique (%)4.1%

Sample

1st row대
2nd row전
3rd row공장용지
4th row대
5th row대

Common Values

ValueCountFrequency (%)
대 71
48.6%
답 22
 
15.1%
공장용지 18
 
12.3%
전 12
 
8.2%
임야 5
 
3.4%
창고용지 5
 
3.4%
종교용지 3
 
2.1%
주차장 2
 
1.4%
목장용지 2
 
1.4%
잡종지 1
 
0.7%
Other values (5) 5
 
3.4%

Length

2023-12-11T09:57:41.263197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 71
48.6%
답 22
 
15.1%
공장용지 18
 
12.3%
전 12
 
8.2%
임야 5
 
3.4%
창고용지 5
 
3.4%
종교용지 3
 
2.1%
주차장 2
 
1.4%
목장용지 2
 
1.4%
잡종지 1
 
0.7%
Other values (5) 5
 
3.4%

대지면적(제곱미터)
Real number (ℝ)

Distinct136
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6622.5234
Minimum126
Maximum257511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:41.364907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126
5-th percentile195.75
Q1441.5
median1450.5
Q35008.7
95-th percentile24398.55
Maximum257511
Range257385
Interquartile range (IQR)4567.2

Descriptive statistics

Standard deviation22817.924
Coefficient of variation (CV)3.445503
Kurtosis102.31385
Mean6622.5234
Median Absolute Deviation (MAD)1195
Skewness9.468653
Sum966888.41
Variance5.2065766 × 108
MonotonicityNot monotonic
2023-12-11T09:57:41.475001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3182.0 3
 
2.1%
2291.0 3
 
2.1%
8945.0 2
 
1.4%
476.0 2
 
1.4%
202.5 2
 
1.4%
5008.7 2
 
1.4%
612.0 2
 
1.4%
16104.0 2
 
1.4%
362.0 1
 
0.7%
332.8 1
 
0.7%
Other values (126) 126
86.3%
ValueCountFrequency (%)
126.0 1
0.7%
128.0 1
0.7%
145.0 1
0.7%
145.7 1
0.7%
152.0 1
0.7%
168.0 1
0.7%
178.0 1
0.7%
195.0 1
0.7%
198.0 1
0.7%
202.0 1
0.7%
ValueCountFrequency (%)
257511.0 1
0.7%
51524.4 1
0.7%
51047.0 1
0.7%
44248.7 1
0.7%
37490.0 1
0.7%
33068.7 1
0.7%
29310.0 1
0.7%
24793.6 1
0.7%
23213.4 1
0.7%
22104.0 1
0.7%

건축면적(제곱미터)
Real number (ℝ)

Distinct137
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1572.0453
Minimum18
Maximum29204.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:41.578794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile75.705
Q1162.225
median335.305
Q31299.255
95-th percentile6997.8125
Maximum29204.06
Range29186.06
Interquartile range (IQR)1137.03

Descriptive statistics

Standard deviation3528.4248
Coefficient of variation (CV)2.2444804
Kurtosis29.422707
Mean1572.0453
Median Absolute Deviation (MAD)245.56
Skewness4.8276099
Sum229518.61
Variance12449781
MonotonicityNot monotonic
2023-12-11T09:57:41.685501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213.76 3
 
2.1%
655.64 3
 
2.1%
116.49 2
 
1.4%
61.78 2
 
1.4%
18.0 2
 
1.4%
1493.5 2
 
1.4%
491.4 2
 
1.4%
84.18 1
 
0.7%
574.64 1
 
0.7%
153.51 1
 
0.7%
Other values (127) 127
87.0%
ValueCountFrequency (%)
18.0 2
1.4%
54.14 1
0.7%
61.78 2
1.4%
68.74 1
0.7%
69.58 1
0.7%
74.94 1
0.7%
78.0 1
0.7%
82.64 1
0.7%
84.18 1
0.7%
85.8 1
0.7%
ValueCountFrequency (%)
29204.06 1
0.7%
17350.63 1
0.7%
13808.08 1
0.7%
12046.06 1
0.7%
11274.82 1
0.7%
10764.24 1
0.7%
8703.24 1
0.7%
7175.47 1
0.7%
6464.84 1
0.7%
5372.3 1
0.7%

연면적(제곱미터)
Real number (ℝ)

Distinct137
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3889.1671
Minimum18
Maximum180481.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:41.814349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile94.43
Q1198.575
median489.4
Q31804.2225
95-th percentile11722.218
Maximum180481.37
Range180463.37
Interquartile range (IQR)1605.6475

Descriptive statistics

Standard deviation17591.577
Coefficient of variation (CV)4.5232248
Kurtosis79.607801
Mean3889.1671
Median Absolute Deviation (MAD)362.21
Skewness8.6351179
Sum567818.39
Variance3.0946358 × 108
MonotonicityNot monotonic
2023-12-11T09:57:41.931952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
309.86 3
 
2.1%
1136.58 3
 
2.1%
200.67 2
 
1.4%
61.78 2
 
1.4%
18.0 2
 
1.4%
4937.6 2
 
1.4%
491.4 2
 
1.4%
84.18 1
 
0.7%
2703.76 1
 
0.7%
458.09 1
 
0.7%
Other values (127) 127
87.0%
ValueCountFrequency (%)
18.0 2
1.4%
54.14 1
0.7%
61.78 2
1.4%
84.18 1
0.7%
87.12 1
0.7%
92.85 1
0.7%
99.17 1
0.7%
115.82 1
0.7%
116.47 1
0.7%
117.3 1
0.7%
ValueCountFrequency (%)
180481.37 1
0.7%
110422.36 1
0.7%
18875.16 1
0.7%
18740.86 1
0.7%
15149.2 1
0.7%
13515.88 1
0.7%
13156.78 1
0.7%
11871.35 1
0.7%
11274.82 1
0.7%
10599.44 1
0.7%

증축연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)94.4%
Missing110
Missing (%)75.3%
Infinite0
Infinite (%)0.0%
Mean944.00278
Minimum0
Maximum10997.77
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:42.045172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50.31
Q1124.22
median349.875
Q3502.3975
95-th percentile3694.9975
Maximum10997.77
Range10997.77
Interquartile range (IQR)378.1775

Descriptive statistics

Standard deviation2251.8057
Coefficient of variation (CV)2.3853803
Kurtosis14.998019
Mean944.00278
Median Absolute Deviation (MAD)220.55
Skewness3.9048221
Sum33984.1
Variance5070628.7
MonotonicityNot monotonic
2023-12-11T09:57:42.159978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
120.98 3
 
2.1%
98.44 1
 
0.7%
430.03 1
 
0.7%
547.99 1
 
0.7%
134.75 1
 
0.7%
125.05 1
 
0.7%
843.25 1
 
0.7%
360.51 1
 
0.7%
487.2 1
 
0.7%
0.0 1
 
0.7%
Other values (24) 24
 
16.4%
(Missing) 110
75.3%
ValueCountFrequency (%)
0.0 1
 
0.7%
40.2 1
 
0.7%
53.68 1
 
0.7%
98.44 1
 
0.7%
106.8 1
 
0.7%
120.98 3
2.1%
121.73 1
 
0.7%
125.05 1
 
0.7%
133.6 1
 
0.7%
134.75 1
 
0.7%
ValueCountFrequency (%)
10997.77 1
0.7%
8703.07 1
0.7%
2025.64 1
0.7%
1630.73 1
0.7%
1065.0 1
0.7%
1053.96 1
0.7%
897.75 1
0.7%
843.25 1
0.7%
547.99 1
0.7%
487.2 1
0.7%

건폐율(퍼센트)
Real number (ℝ)

Distinct137
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.828187
Minimum0.0866
Maximum73.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:42.264297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0866
5-th percentile9.33
Q120.1875
median37.36975
Q350.6675
95-th percentile62.2875
Maximum73.75
Range73.6634
Interquartile range (IQR)30.48

Descriptive statistics

Standard deviation17.572925
Coefficient of variation (CV)0.49047765
Kurtosis-0.96992322
Mean35.828187
Median Absolute Deviation (MAD)15.67
Skewness0.019289363
Sum5230.9153
Variance308.80769
MonotonicityNot monotonic
2023-12-11T09:57:42.374999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.6 3
 
2.1%
9.33 3
 
2.1%
12.98 2
 
1.4%
25.9 2
 
1.4%
57.5259 2
 
1.4%
39.95 2
 
1.4%
16.6965 2
 
1.4%
58.28 1
 
0.7%
59.27 1
 
0.7%
53.04 1
 
0.7%
Other values (127) 127
87.0%
ValueCountFrequency (%)
0.0866 1
 
0.7%
1.8 1
 
0.7%
4.18 1
 
0.7%
4.58 1
 
0.7%
7.15 1
 
0.7%
7.55 1
 
0.7%
9.33 3
2.1%
10.43 1
 
0.7%
10.52 1
 
0.7%
11.0806 1
 
0.7%
ValueCountFrequency (%)
73.75 1
0.7%
69.98 1
0.7%
68.87 1
0.7%
68.84 1
0.7%
68.69 1
0.7%
68.61 1
0.7%
63.7 1
0.7%
63.15 1
0.7%
59.7 1
0.7%
59.69 1
0.7%

용적률(퍼센트)
Real number (ℝ)

Distinct138
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.782819
Minimum0.0866
Maximum323.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:42.511064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0866
5-th percentile10.7975
Q125.935
median41.0531
Q365.4425
95-th percentile187.3
Maximum323.17
Range323.0834
Interquartile range (IQR)39.5075

Descriptive statistics

Standard deviation58.326089
Coefficient of variation (CV)0.95958183
Kurtosis4.6289043
Mean60.782819
Median Absolute Deviation (MAD)19.8823
Skewness2.1204661
Sum8874.2916
Variance3401.9327
MonotonicityNot monotonic
2023-12-11T09:57:42.637785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.72 3
 
2.1%
13.53 3
 
2.1%
12.98 2
 
1.4%
99.0963 2
 
1.4%
39.95 2
 
1.4%
55.1996 2
 
1.4%
172.0 1
 
0.7%
176.87 1
 
0.7%
170.69 1
 
0.7%
7.33 1
 
0.7%
Other values (128) 128
87.7%
ValueCountFrequency (%)
0.0866 1
0.7%
1.8 1
0.7%
6.79 1
0.7%
7.15 1
0.7%
7.33 1
0.7%
7.55 1
0.7%
10.38 1
0.7%
10.43 1
0.7%
11.9 1
0.7%
12.1 1
0.7%
ValueCountFrequency (%)
323.17 1
0.7%
269.34 1
0.7%
263.88 1
0.7%
229.97 1
0.7%
219.36 1
0.7%
197.64 1
0.7%
196.89 1
0.7%
188.3 1
0.7%
184.3 1
0.7%
181.19 1
0.7%

구조
Categorical

Distinct10
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
일반철골구조
64 
철근콘크리트구조
43 
경량철골구조
13 
벽돌구조
7 
<NA>
7 
Other values (5)
12 

Length

Max length11
Median length6
Mean length6.4109589
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
일반철골구조 64
43.8%
철근콘크리트구조 43
29.5%
경량철골구조 13
 
8.9%
벽돌구조 7
 
4.8%
<NA> 7
 
4.8%
일반목구조 4
 
2.7%
블록구조 3
 
2.1%
컨테이너조 2
 
1.4%
프리케스트콘크리트구조 2
 
1.4%
철골철근콘크리트구조 1
 
0.7%

Length

2023-12-11T09:57:42.753091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:42.849945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반철골구조 64
43.8%
철근콘크리트구조 43
29.5%
경량철골구조 13
 
8.9%
벽돌구조 7
 
4.8%
na 7
 
4.8%
일반목구조 4
 
2.7%
블록구조 3
 
2.1%
컨테이너조 2
 
1.4%
프리케스트콘크리트구조 2
 
1.4%
철골철근콘크리트구조 1
 
0.7%

허가일
Date

Distinct108
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-08-01 00:00:00
Maximum2023-07-25 00:00:00
2023-12-11T09:57:42.966895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:57:43.071182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct58
Distinct (%)79.5%
Missing73
Missing (%)50.0%
Memory size1.3 KiB
Minimum2022-08-30 00:00:00
Maximum2023-08-28 00:00:00
2023-12-11T09:57:43.175638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:57:43.271468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct23
Distinct (%)92.0%
Missing121
Missing (%)82.9%
Memory size1.3 KiB
Minimum2022-10-07 00:00:00
Maximum2023-08-31 00:00:00
2023-12-11T09:57:43.363186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:57:43.463358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

최대지상층수
Real number (ℝ)

Distinct7
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0547945
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:43.548763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum10
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4984167
Coefficient of variation (CV)0.72922948
Kurtosis9.9378847
Mean2.0547945
Median Absolute Deviation (MAD)1
Skewness2.5989263
Sum300
Variance2.2452527
MonotonicityNot monotonic
2023-12-11T09:57:43.630926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 68
46.6%
2 42
28.8%
4 16
 
11.0%
3 14
 
9.6%
5 3
 
2.1%
10 2
 
1.4%
7 1
 
0.7%
ValueCountFrequency (%)
1 68
46.6%
2 42
28.8%
3 14
 
9.6%
4 16
 
11.0%
5 3
 
2.1%
7 1
 
0.7%
10 2
 
1.4%
ValueCountFrequency (%)
10 2
 
1.4%
7 1
 
0.7%
5 3
 
2.1%
4 16
 
11.0%
3 14
 
9.6%
2 42
28.8%
1 68
46.6%

최대지하층수
Categorical

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
74 
<NA>
59 
1
12 
2
 
1

Length

Max length4
Median length1
Mean length2.2123288
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row0
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
0 74
50.7%
<NA> 59
40.4%
1 12
 
8.2%
2 1
 
0.7%

Length

2023-12-11T09:57:43.736881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:43.842583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 74
50.7%
na 59
40.4%
1 12
 
8.2%
2 1
 
0.7%

최고높이(미터)
Real number (ℝ)

Distinct104
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.230932
Minimum0
Maximum72.6
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:43.958884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q16
median8.15
Q311.5375
95-th percentile23.1
Maximum72.6
Range72.6
Interquartile range (IQR)5.5375

Descriptive statistics

Standard deviation8.713266
Coefficient of variation (CV)0.85165911
Kurtosis26.544516
Mean10.230932
Median Absolute Deviation (MAD)2.575
Skewness4.4855596
Sum1493.716
Variance75.921005
MonotonicityNot monotonic
2023-12-11T09:57:44.321725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.0 6
 
4.1%
7.5 5
 
3.4%
4.8 5
 
3.4%
8.7 4
 
2.7%
5.4 3
 
2.1%
6.6 3
 
2.1%
15.1 3
 
2.1%
4.7 3
 
2.1%
7.9 3
 
2.1%
8.95 2
 
1.4%
Other values (94) 109
74.7%
ValueCountFrequency (%)
0.0 1
0.7%
2.4 1
0.7%
2.5 1
0.7%
3.5 2
1.4%
3.75 1
0.7%
3.9 1
0.7%
4.0 2
1.4%
4.2 1
0.7%
4.4 1
0.7%
4.6 1
0.7%
ValueCountFrequency (%)
72.6 1
0.7%
63.0 1
0.7%
33.3 1
0.7%
30.9 1
0.7%
29.7 1
0.7%
27.35 1
0.7%
24.15 2
1.4%
19.95 1
0.7%
19.1 1
0.7%
18.2 1
0.7%

동수
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2671233
Minimum0
Maximum16
Zeros2
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:44.421269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile7.75
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.6373736
Coefficient of variation (CV)1.1633128
Kurtosis10.784832
Mean2.2671233
Median Absolute Deviation (MAD)0
Skewness3.1133041
Sum331
Variance6.9557393
MonotonicityNot monotonic
2023-12-11T09:57:44.513431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 83
56.8%
2 33
 
22.6%
4 5
 
3.4%
5 5
 
3.4%
3 5
 
3.4%
6 4
 
2.7%
9 3
 
2.1%
0 2
 
1.4%
16 1
 
0.7%
15 1
 
0.7%
Other values (4) 4
 
2.7%
ValueCountFrequency (%)
0 2
 
1.4%
1 83
56.8%
2 33
 
22.6%
3 5
 
3.4%
4 5
 
3.4%
5 5
 
3.4%
6 4
 
2.7%
7 1
 
0.7%
8 1
 
0.7%
9 3
 
2.1%
ValueCountFrequency (%)
16 1
 
0.7%
15 1
 
0.7%
13 1
 
0.7%
12 1
 
0.7%
9 3
2.1%
8 1
 
0.7%
7 1
 
0.7%
6 4
2.7%
5 5
3.4%
4 5
3.4%

승강기합
Categorical

IMBALANCE 

Distinct8
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
107 
-
23 
1
 
9
4
 
2
3
 
2
Other values (3)
 
3

Length

Max length4
Median length4
Mean length3.2054795
Min length1

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row-
5th row4

Common Values

ValueCountFrequency (%)
<NA> 107
73.3%
- 23
 
15.8%
1 9
 
6.2%
4 2
 
1.4%
3 2
 
1.4%
5 1
 
0.7%
6 1
 
0.7%
12 1
 
0.7%

Length

2023-12-11T09:57:44.621598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:44.725391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
73.3%
23
 
15.8%
1 9
 
6.2%
4 2
 
1.4%
3 2
 
1.4%
5 1
 
0.7%
6 1
 
0.7%
12 1
 
0.7%

비상승강기합
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing143
Missing (%)97.9%
Memory size1.3 KiB
2023-12-11T09:57:44.801946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.3333333
Min length1

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row-
2nd row11
3rd row6
ValueCountFrequency (%)
1
33.3%
11 1
33.3%
6 1
33.3%
2023-12-11T09:57:44.983146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
- 1
25.0%
6 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
75.0%
Dash Punctuation 1
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
6 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
- 1
25.0%
6 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
- 1
25.0%
6 1
25.0%

하수처리시설명
Categorical

Distinct13
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
하수종말처리장연결
63 
<NA>
25 
기타오수처리시설
24 
접촉폭기방법
12 
부패탱크방법
 
5
Other values (8)
17 

Length

Max length13
Median length9
Mean length7.4931507
Min length4

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row하수종말처리장연결
2nd row하수종말처리장연결
3rd row기타오수처리시설
4th row하수종말처리장연결
5th row<NA>

Common Values

ValueCountFrequency (%)
하수종말처리장연결 63
43.2%
<NA> 25
 
17.1%
기타오수처리시설 24
 
16.4%
접촉폭기방법 12
 
8.2%
부패탱크방법 5
 
3.4%
마을하수처리장연결 3
 
2.1%
기타분뇨처리방법 3
 
2.1%
오수처리시설 3
 
2.1%
현수미생물접촉방법 3
 
2.1%
접촉산화방법 2
 
1.4%
Other values (3) 3
 
2.1%

Length

2023-12-11T09:57:45.109788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
하수종말처리장연결 63
43.2%
na 25
 
17.1%
기타오수처리시설 24
 
16.4%
접촉폭기방법 12
 
8.2%
부패탱크방법 5
 
3.4%
마을하수처리장연결 3
 
2.1%
기타분뇨처리방법 3
 
2.1%
오수처리시설 3
 
2.1%
현수미생물접촉방법 3
 
2.1%
접촉산화방법 2
 
1.4%
Other values (3) 3
 
2.1%

하수처리시설용량(세제곱미터)
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)36.2%
Missing88
Missing (%)60.3%
Infinite0
Infinite (%)0.0%
Mean23.637931
Minimum1
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:45.202277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q13.25
median7
Q315.5
95-th percentile153
Maximum215
Range214
Interquartile range (IQR)12.25

Descriptive statistics

Standard deviation45.012551
Coefficient of variation (CV)1.9042509
Kurtosis8.8526468
Mean23.637931
Median Absolute Deviation (MAD)4
Skewness3.0438967
Sum1371
Variance2026.1298
MonotonicityNot monotonic
2023-12-11T09:57:45.288363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 12
 
8.2%
6 7
 
4.8%
8 6
 
4.1%
10 5
 
3.4%
5 4
 
2.7%
1 3
 
2.1%
7 2
 
1.4%
170 2
 
1.4%
14 2
 
1.4%
30 2
 
1.4%
Other values (11) 13
 
8.9%
(Missing) 88
60.3%
ValueCountFrequency (%)
1 3
 
2.1%
3 12
8.2%
4 2
 
1.4%
5 4
 
2.7%
6 7
4.8%
7 2
 
1.4%
8 6
4.1%
10 5
3.4%
14 2
 
1.4%
16 2
 
1.4%
ValueCountFrequency (%)
215 1
0.7%
170 2
1.4%
150 1
0.7%
80 1
0.7%
57 1
0.7%
50 1
0.7%
45 1
0.7%
40 1
0.7%
30 2
1.4%
29 1
0.7%

주용도
Categorical

Distinct22
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
제2종근린생활시설
31 
제1종근린생활시설
30 
공장
18 
단독주택
16 
창고시설
14 
Other values (17)
37 

Length

Max length10
Median length9
Mean length6.2465753
Min length2

Unique

Unique7 ?
Unique (%)4.8%

Sample

1st row제1종근린생활시설
2nd row단독주택
3rd row공장
4th row단독주택
5th row노유자시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 31
21.2%
제1종근린생활시설 30
20.5%
공장 18
12.3%
단독주택 16
11.0%
창고시설 14
9.6%
문화및집회시설 5
 
3.4%
의료시설 4
 
2.7%
동물및식물관련시설 4
 
2.7%
종교시설 3
 
2.1%
교육연구시설 3
 
2.1%
Other values (12) 18
12.3%

Length

2023-12-11T09:57:45.397105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 31
21.2%
제1종근린생활시설 30
20.5%
공장 18
12.3%
단독주택 16
11.0%
창고시설 14
9.6%
문화및집회시설 5
 
3.4%
의료시설 4
 
2.7%
동물및식물관련시설 4
 
2.7%
종교시설 3
 
2.1%
교육연구시설 3
 
2.1%
Other values (12) 18
12.3%

부속용도
Text

MISSING 

Distinct75
Distinct (%)70.8%
Missing40
Missing (%)27.4%
Memory size1.3 KiB
2023-12-11T09:57:45.628630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length6.4528302
Min length2

Characters and Unicode

Total characters684
Distinct characters115
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)60.4%

Sample

1st row휴게음식점
2nd row사회복지시설
3rd row(단독주택)
4th row일반공장
5th row농산물제조업소
ValueCountFrequency (%)
및 12
 
9.4%
휴게음식점 11
 
8.6%
소매점 8
 
6.2%
사무소 7
 
5.5%
병원 4
 
3.1%
단독주택 4
 
3.1%
종교집회장 3
 
2.3%
일반음식점 3
 
2.3%
창고시설 3
 
2.3%
다세대주택 2
 
1.6%
Other values (66) 71
55.5%
2023-12-11T09:57:46.034312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 32
 
4.7%
소 32
 
4.7%
시 25
 
3.7%
사 24
 
3.5%
22
 
3.2%
설 22
 
3.2%
음 19
 
2.8%
식 19
 
2.8%
고 18
 
2.6%
창 17
 
2.5%
Other values (105) 454
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 599
87.6%
Space Separator 22
 
3.2%
Close Punctuation 16
 
2.3%
Open Punctuation 16
 
2.3%
Other Punctuation 16
 
2.3%
Decimal Number 12
 
1.8%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 32
 
5.3%
소 32
 
5.3%
시 25
 
4.2%
사 24
 
4.0%
설 22
 
3.7%
음 19
 
3.2%
식 19
 
3.2%
고 18
 
3.0%
창 17
 
2.8%
및 17
 
2.8%
Other values (95) 374
62.4%
Other Punctuation
ValueCountFrequency (%)
, 14
87.5%
/ 1
 
6.2%
. 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 6
50.0%
1 6
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
E 1
33.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 599
87.6%
Common 82
 
12.0%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 32
 
5.3%
소 32
 
5.3%
시 25
 
4.2%
사 24
 
4.0%
설 22
 
3.7%
음 19
 
3.2%
식 19
 
3.2%
고 18
 
3.0%
창 17
 
2.8%
및 17
 
2.8%
Other values (95) 374
62.4%
Common
ValueCountFrequency (%)
22
26.8%
) 16
19.5%
( 16
19.5%
, 14
17.1%
2 6
 
7.3%
1 6
 
7.3%
/ 1
 
1.2%
. 1
 
1.2%
Latin
ValueCountFrequency (%)
S 2
66.7%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 599
87.6%
ASCII 85
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 32
 
5.3%
소 32
 
5.3%
시 25
 
4.2%
사 24
 
4.0%
설 22
 
3.7%
음 19
 
3.2%
식 19
 
3.2%
고 18
 
3.0%
창 17
 
2.8%
및 17
 
2.8%
Other values (95) 374
62.4%
ASCII
ValueCountFrequency (%)
22
25.9%
) 16
18.8%
( 16
18.8%
, 14
16.5%
2 6
 
7.1%
1 6
 
7.1%
S 2
 
2.4%
/ 1
 
1.2%
. 1
 
1.2%
E 1
 
1.2%

용도지역
Categorical

Distinct14
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
계획관리지역
46 
제2종일반주거지역
31 
농림지역
13 
일반공업지역
11 
자연녹지지역
9 
Other values (9)
36 

Length

Max length9
Median length6
Mean length6.7260274
Min length4

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row일반상업지역
2nd row자연녹지지역
3rd row계획관리지역
4th row제1종일반주거지역
5th row계획관리지역

Common Values

ValueCountFrequency (%)
계획관리지역 46
31.5%
제2종일반주거지역 31
21.2%
농림지역 13
 
8.9%
일반공업지역 11
 
7.5%
자연녹지지역 9
 
6.2%
제1종일반주거지역 8
 
5.5%
가축사육제한구역 8
 
5.5%
일반상업지역 7
 
4.8%
생산녹지지역 5
 
3.4%
생산관리지역 3
 
2.1%
Other values (4) 5
 
3.4%

Length

2023-12-11T09:57:46.192030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계획관리지역 46
31.5%
제2종일반주거지역 31
21.2%
농림지역 13
 
8.9%
일반공업지역 11
 
7.5%
자연녹지지역 9
 
6.2%
제1종일반주거지역 8
 
5.5%
가축사육제한구역 8
 
5.5%
일반상업지역 7
 
4.8%
생산녹지지역 5
 
3.4%
생산관리지역 3
 
2.1%
Other values (4) 5
 
3.4%

용도지구
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
129 
자연취락지구
 
9
개발진흥지구
 
5
고도지구
 
1
주거개발진흥지구
 
1

Length

Max length11
Median length4
Mean length4.2671233
Min length4

Unique

Unique3 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
88.4%
자연취락지구 9
 
6.2%
개발진흥지구 5
 
3.4%
고도지구 1
 
0.7%
주거개발진흥지구 1
 
0.7%
산업ㆍ유통개발진흥지구 1
 
0.7%

Length

2023-12-11T09:57:46.316469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:46.485412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
88.4%
자연취락지구 9
 
6.2%
개발진흥지구 5
 
3.4%
고도지구 1
 
0.7%
주거개발진흥지구 1
 
0.7%
산업ㆍ유통개발진흥지구 1
 
0.7%

용도구역
Categorical

Distinct8
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
98 
지구단위계획구역
23 
가축사육제한구역
14 
농업진흥구역
 
6
가축사육제한구역미분류
 
2
Other values (3)
 
3

Length

Max length14
Median length4
Mean length5.2739726
Min length4

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row<NA>
3rd row가축사육제한구역
4th row지구단위계획구역
5th row가축사육제한구역

Common Values

ValueCountFrequency (%)
<NA> 98
67.1%
지구단위계획구역 23
 
15.8%
가축사육제한구역 14
 
9.6%
농업진흥구역 6
 
4.1%
가축사육제한구역미분류 2
 
1.4%
문화재보존영향 검토대상구역 1
 
0.7%
산림보호구역 1
 
0.7%
하천구역 1
 
0.7%

Length

2023-12-11T09:57:46.592748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:46.719682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 98
66.7%
지구단위계획구역 23
 
15.6%
가축사육제한구역 14
 
9.5%
농업진흥구역 6
 
4.1%
가축사육제한구역미분류 2
 
1.4%
문화재보존영향 1
 
0.7%
검토대상구역 1
 
0.7%
산림보호구역 1
 
0.7%
하천구역 1
 
0.7%

자주식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)84.6%
Missing133
Missing (%)91.1%
Infinite0
Infinite (%)0.0%
Mean73.461538
Minimum1
Maximum390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:46.858886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median16
Q349
95-th percentile310.8
Maximum390
Range389
Interquartile range (IQR)43

Descriptive statistics

Standard deviation121.45823
Coefficient of variation (CV)1.6533582
Kurtosis3.2941406
Mean73.461538
Median Absolute Deviation (MAD)15
Skewness1.9854287
Sum955
Variance14752.103
MonotonicityNot monotonic
2023-12-11T09:57:46.962543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 2
 
1.4%
6 2
 
1.4%
44 1
 
0.7%
153 1
 
0.7%
8 1
 
0.7%
390 1
 
0.7%
16 1
 
0.7%
4 1
 
0.7%
19 1
 
0.7%
49 1
 
0.7%
(Missing) 133
91.1%
ValueCountFrequency (%)
1 2
1.4%
4 1
0.7%
6 2
1.4%
8 1
0.7%
16 1
0.7%
19 1
0.7%
44 1
0.7%
49 1
0.7%
153 1
0.7%
258 1
0.7%
ValueCountFrequency (%)
390 1
0.7%
258 1
0.7%
153 1
0.7%
49 1
0.7%
44 1
0.7%
19 1
0.7%
16 1
0.7%
8 1
0.7%
6 2
1.4%
4 1
0.7%

자주식옥외주차장(대)
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)37.3%
Missing79
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean19.298507
Minimum1
Maximum235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:47.084452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q317
95-th percentile69
Maximum235
Range234
Interquartile range (IQR)15

Descriptive statistics

Standard deviation37.375253
Coefficient of variation (CV)1.9366914
Kurtosis18.917609
Mean19.298507
Median Absolute Deviation (MAD)5
Skewness3.98064
Sum1293
Variance1396.9095
MonotonicityNot monotonic
2023-12-11T09:57:47.187255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 13
 
8.9%
1 9
 
6.2%
3 7
 
4.8%
12 6
 
4.1%
6 5
 
3.4%
43 2
 
1.4%
8 2
 
1.4%
17 2
 
1.4%
4 2
 
1.4%
5 2
 
1.4%
Other values (15) 17
 
11.6%
(Missing) 79
54.1%
ValueCountFrequency (%)
1 9
6.2%
2 13
8.9%
3 7
4.8%
4 2
 
1.4%
5 2
 
1.4%
6 5
 
3.4%
7 2
 
1.4%
8 2
 
1.4%
12 6
4.1%
16 1
 
0.7%
ValueCountFrequency (%)
235 1
0.7%
160 1
0.7%
82 1
0.7%
69 2
1.4%
64 1
0.7%
55 1
0.7%
43 2
1.4%
39 1
0.7%
37 1
0.7%
33 1
0.7%

인근자주식주차장(대)
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
144 
4
 
1
12
 
1

Length

Max length4
Median length4
Mean length3.9657534
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 144
98.6%
4 1
 
0.7%
12 1
 
0.7%

Length

2023-12-11T09:57:47.327137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:47.430420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
98.6%
4 1
 
0.7%
12 1
 
0.7%

총주차대수
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)23.0%
Missing20
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean17.968254
Minimum0
Maximum625
Zeros53
Zeros (%)36.3%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:47.535592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q37.75
95-th percentile63.25
Maximum625
Range625
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation68.786619
Coefficient of variation (CV)3.8282306
Kurtosis57.576267
Mean17.968254
Median Absolute Deviation (MAD)2
Skewness7.2567526
Sum2264
Variance4731.599
MonotonicityNot monotonic
2023-12-11T09:57:47.643369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 53
36.3%
2 13
 
8.9%
1 7
 
4.8%
3 6
 
4.1%
12 6
 
4.1%
6 5
 
3.4%
4 4
 
2.7%
7 4
 
2.7%
69 2
 
1.4%
43 2
 
1.4%
Other values (19) 24
16.4%
(Missing) 20
 
13.7%
ValueCountFrequency (%)
0 53
36.3%
1 7
 
4.8%
2 13
 
8.9%
3 6
 
4.1%
4 4
 
2.7%
5 2
 
1.4%
6 5
 
3.4%
7 4
 
2.7%
8 2
 
1.4%
12 6
 
4.1%
ValueCountFrequency (%)
625 1
0.7%
418 1
0.7%
153 1
0.7%
82 1
0.7%
69 2
1.4%
64 1
0.7%
61 1
0.7%
55 1
0.7%
44 1
0.7%
43 2
1.4%

총주차장면적(제곱미터)
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)35.7%
Missing20
Missing (%)13.7%
Infinite0
Infinite (%)0.0%
Mean360.14714
Minimum0
Maximum17539.94
Zeros61
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:47.775043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12.25
Q380
95-th percentile663.695
Maximum17539.94
Range17539.94
Interquartile range (IQR)80

Descriptive statistics

Standard deviation2037.67
Coefficient of variation (CV)5.6578819
Kurtosis60.124316
Mean360.14714
Median Absolute Deviation (MAD)12.25
Skewness7.7292541
Sum45378.54
Variance4152099.1
MonotonicityNot monotonic
2023-12-11T09:57:47.902298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 61
41.8%
25.0 8
 
5.5%
12.5 5
 
3.4%
37.5 3
 
2.1%
80.0 3
 
2.1%
87.5 3
 
2.1%
138.0 2
 
1.4%
23.0 2
 
1.4%
75.0 2
 
1.4%
212.5 2
 
1.4%
Other values (35) 35
24.0%
(Missing) 20
 
13.7%
ValueCountFrequency (%)
0.0 61
41.8%
11.5 1
 
0.7%
12.0 1
 
0.7%
12.5 5
 
3.4%
23.0 2
 
1.4%
24.5 1
 
0.7%
24.67 1
 
0.7%
25.0 8
 
5.5%
35.5 1
 
0.7%
37.5 3
 
2.1%
ValueCountFrequency (%)
17539.94 1
0.7%
14733.22 1
0.7%
2405.06 1
0.7%
924.0 1
0.7%
795.6 1
0.7%
712.0 1
0.7%
687.5 1
0.7%
592.28 1
0.7%
541.5 1
0.7%
537.5 1
0.7%

세대수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
142 
1
 
2
2
 
1
8
 
1

Length

Max length4
Median length4
Mean length3.9178082
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 142
97.3%
1 2
 
1.4%
2 1
 
0.7%
8 1
 
0.7%

Length

2023-12-11T09:57:48.043324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:48.153691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 142
97.3%
1 2
 
1.4%
2 1
 
0.7%
8 1
 
0.7%

호수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
144 
2
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.9589041
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row2
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 144
98.6%
2 1
 
0.7%
1 1
 
0.7%

Length

2023-12-11T09:57:48.282813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:48.399509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 144
98.6%
2 1
 
0.7%
1 1
 
0.7%

가구수
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
124 
1
17 
9
 
2
2
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.5547945
Min length1

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 124
84.9%
1 17
 
11.6%
9 2
 
1.4%
2 1
 
0.7%
5 1
 
0.7%
11 1
 
0.7%

Length

2023-12-11T09:57:48.512671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:57:48.630590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
84.9%
1 17
 
11.6%
9 2
 
1.4%
2 1
 
0.7%
5 1
 
0.7%
11 1
 
0.7%

주건축물수
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)7.7%
Missing3
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean1.8251748
Minimum0
Maximum15
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:48.724774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.2496156
Coefficient of variation (CV)1.232548
Kurtosis20.164369
Mean1.8251748
Median Absolute Deviation (MAD)0
Skewness4.2563
Sum261
Variance5.0607702
MonotonicityNot monotonic
2023-12-11T09:57:48.840975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 101
69.2%
2 22
 
15.1%
3 7
 
4.8%
5 3
 
2.1%
15 2
 
1.4%
4 2
 
1.4%
6 2
 
1.4%
9 1
 
0.7%
0 1
 
0.7%
13 1
 
0.7%
(Missing) 3
 
2.1%
ValueCountFrequency (%)
0 1
 
0.7%
1 101
69.2%
2 22
 
15.1%
3 7
 
4.8%
4 2
 
1.4%
5 3
 
2.1%
6 2
 
1.4%
8 1
 
0.7%
9 1
 
0.7%
13 1
 
0.7%
ValueCountFrequency (%)
15 2
 
1.4%
13 1
 
0.7%
9 1
 
0.7%
8 1
 
0.7%
6 2
 
1.4%
5 3
 
2.1%
4 2
 
1.4%
3 7
 
4.8%
2 22
 
15.1%
1 101
69.2%

부속건축물수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)18.4%
Missing108
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean1.8421053
Minimum0
Maximum10
Zeros3
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T09:57:48.957456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4.15
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7937778
Coefficient of variation (CV)0.97376508
Kurtosis10.998285
Mean1.8421053
Median Absolute Deviation (MAD)0
Skewness2.8596248
Sum70
Variance3.2176387
MonotonicityNot monotonic
2023-12-11T09:57:49.053319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 20
 
13.7%
2 7
 
4.8%
3 3
 
2.1%
0 3
 
2.1%
4 3
 
2.1%
5 1
 
0.7%
10 1
 
0.7%
(Missing) 108
74.0%
ValueCountFrequency (%)
0 3
 
2.1%
1 20
13.7%
2 7
 
4.8%
3 3
 
2.1%
4 3
 
2.1%
5 1
 
0.7%
10 1
 
0.7%
ValueCountFrequency (%)
10 1
 
0.7%
5 1
 
0.7%
4 3
 
2.1%
3 3
 
2.1%
2 7
 
4.8%
1 20
13.7%
0 3
 
2.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-08-31 00:00:00
Maximum2023-08-31 00:00:00
2023-12-11T09:57:49.145084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:57:49.227612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수데이터기준일자
0신축경상남도 밀양시 삼문동 4-83대128.094.4188.8<NA>73.75147.5철근콘크리트구조2023-07-25<NA><NA>206.71<NA><NA>하수종말처리장연결<NA>제1종근린생활시설휴게음식점일반상업지역고도지구<NA><NA><NA><NA>00.0<NA>2<NA>1<NA>2023-08-31
1신축경상남도 밀양시 삼랑진읍 율동리 755전932.0169.68169.68<NA>18.2118.21일반목구조2023-07-24<NA><NA>104.872<NA><NA>하수종말처리장연결<NA>단독주택<NA>자연녹지지역<NA><NA><NA>1<NA>112.51<NA>1112023-08-31
2증축경상남도 밀양시 산외면 남기리 680공장용지16177.06464.8410599.448703.0739.9665.52일반철골구조2023-07-172023-08-11<NA>2<NA>14.74<NA><NA>기타오수처리시설30공장<NA>계획관리지역<NA>가축사육제한구역<NA><NA><NA>00.0<NA><NA><NA>132023-08-31
3용도변경경상남도 밀양시 상남면 기산리 1475-2대202.5116.49200.67<NA>57.525999.0963벽돌구조2023-07-14<NA><NA>1<NA>7.51-<NA>하수종말처리장연결<NA>단독주택<NA>제1종일반주거지역<NA>지구단위계획구역<NA>2<NA>225.0<NA><NA>11<NA>2023-08-31
4증축경상남도 밀양시 삼랑진읍 미전리 636 외2필지대11750.02824.417746.74233.6324.0461.66철근콘크리트구조2023-07-122023-08-28<NA>4116.994<NA><NA><NA>노유자시설사회복지시설계획관리지역<NA>가축사육제한구역<NA><NA><NA>00.0<NA><NA><NA>9<NA>2023-08-31
5신축경상남도 밀양시 가곡동 549-45대195.085.8130.85<NA>44.067.1철근콘크리트구조2023-07-102023-08-04<NA>208.651<NA><NA>하수종말처리장연결1단독주택(단독주택)제2종일반주거지역<NA><NA><NA>1<NA>112.0<NA><NA>11<NA>2023-08-31
6증축경상남도 밀양시 부북면 춘화리 848공장용지3248.01225.831336.43450.037.741141.1462일반철골구조2023-07-052023-07-18<NA>1<NA>11.882<NA><NA>하수종말처리장연결<NA>공장일반공장계획관리지역<NA>지구단위계획구역<NA>7<NA>782.5<NA><NA><NA>2<NA>2023-08-31
7신축경상남도 밀양시 내이동 1536-10대240.4165.14165.14<NA>68.6968.69경량철골구조2023-06-302023-07-11<NA>103.751<NA><NA>하수종말처리장연결<NA>위락시설<NA>일반상업지역<NA><NA><NA>2<NA>224.5<NA><NA><NA>1<NA>2023-08-31
8신축경상남도 밀양시 단장면 미촌리 375-1 외1필지대757.0297.0594.0<NA>39.2378.47일반철골구조2023-06-29<NA><NA>109.71<NA><NA>기타오수처리시설5공장농산물제조업소계획관리지역<NA><NA><NA><NA><NA>00.0<NA><NA><NA>1<NA>2023-08-31
9신축경상남도 밀양시 내이동 1196-4 외3필지대5443.01894.11938.45<NA>34.835.61일반철골구조2023-06-292023-08-09<NA>209.481<NA><NA>하수종말처리장연결29판매시설(소매점)제2종일반주거지역<NA>지구단위계획구역<NA>43<NA>43541.5<NA><NA><NA>1<NA>2023-08-31
건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수데이터기준일자
136신축경상남도 밀양시 초동면 금포리 251 외1필지전1861.0491.4491.4<NA>26.4126.41일반철골구조2022-08-232023-03-27<NA>109.61<NA><NA>기타오수처리시설8제1종근린생활시설소매점계획관리지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>2023-08-31
137신축경상남도 밀양시 초동면 금포리 251 외1필지전1660.0491.4491.4<NA>29.629.6일반철골구조2022-08-232023-03-27<NA>109.61<NA><NA>기타오수처리시설8제1종근린생활시설소매점계획관리지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>2023-08-31
138대수선경상남도 밀양시 부북면 전사포리 232공장용지20728.08703.2413515.88<NA>41.9965.21철근콘크리트구조2022-08-222022-08-302022-10-074<NA>19.956<NA><NA>현수미생물접촉방법<NA>공장및 제1종근린생활시설(소매점)일반공업지역<NA>가축사육제한구역<NA>39<NA>39458.5<NA><NA><NA>152023-08-31
139증축경상남도 밀양시 초동면 명성리 2462-1 외1필지공장용지23213.412046.0613156.78106.851.892756.6775일반철골구조2022-08-172022-09-062022-12-271<NA>6.012<NA><NA>현수미생물접촉방법<NA>공장<NA>계획관리지역산업ㆍ유통개발진흥지구지구단위계획구역<NA>82<NA>82924.0<NA><NA><NA>2102023-08-31
140용도변경경상남도 밀양시 삼랑진읍 용성리 327-1대519.054.1454.14<NA>10.4310.43경량철골구조2022-08-10<NA><NA>1<NA>4.41<NA><NA>기타오수처리시설3제1종근린생활시설소매점계획관리지역자연취락지구<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>2023-08-31
141용도변경경상남도 밀양시 부북면 퇴로리 334대1518.0510.65510.65<NA>33.6433.64일반목구조2022-08-05<NA><NA>1<NA>6.58<NA><NA>마을하수처리장연결<NA>단독주택및 음식점계획관리지역자연취락지구<NA><NA><NA><NA><NA><NA>1<NA><NA>8<NA>2023-08-31
142신축경상남도 밀양시 삼문동 525-7 외1필지대312.0186.26186.26<NA>59.759.7일반철골구조2022-08-04<NA><NA>105.71<NA><NA>하수종말처리장연결<NA>제1종근린생활시설휴게음식점제2종일반주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>2023-08-31
143신축경상남도 밀양시 상남면 기산리 1450-5대234.087.0142.11<NA>37.179560.7308철근콘크리트구조2022-08-042022-09-26<NA>208.91<NA><NA>하수종말처리장연결<NA>단독주택<NA>제1종일반주거지역<NA><NA><NA>2<NA>20.0<NA><NA>11<NA>2023-08-31
144신축경상남도 밀양시 부북면 제대리 118답553.0330.11453.05<NA>59.6981.93일반철골구조2022-08-022022-09-292023-02-07208.23<NA><NA>기타오수처리시설3제2종근린생활시설및제1종근생,창고시설계획관리지역개발진흥지구지구단위계획구역<NA>2<NA>225.0<NA><NA><NA>3<NA>2023-08-31
145용도변경경상남도 밀양시 무안면 웅동리 418대979.0116.47116.47<NA>11.911.9철근콘크리트구조2022-08-01<NA><NA>1<NA>4.82<NA><NA>현수미생물접촉방법3제2종근린생활시설사무소계획관리지역자연취락지구<NA><NA><NA><NA><NA><NA><NA><NA><NA>112023-08-31

Duplicate rows

Most frequently occurring

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수데이터기준일자# duplicates
0신축경상남도 밀양시 단장면 법흥리 347전2291.0213.76309.86<NA>9.3313.53철근콘크리트구조2022-12-09<NA><NA>208.71<NA><NA>접촉폭기방법6제2종근린생활시설종교집회장계획관리지역자연취락지구<NA><NA>6<NA>680.0<NA><NA><NA>1<NA>2023-08-312
1용도변경경상남도 밀양시 상남면 동산리 577대476.061.7861.78<NA>12.9812.98<NA>2022-10-14<NA><NA>1<NA>3.51<NA><NA>오수처리시설3제1종근린생활시설휴게음식점계획관리지역자연취락지구<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>2023-08-312
2증축경상남도 밀양시 무안면 무안리 766-1 외1필지종교용지3182.0655.641136.58120.9820.635.72경량철골구조2023-06-14<NA><NA>4<NA>6.65-<NA>부패탱크방법<NA>종교시설<NA>제2종일반주거지역<NA><NA><NA><NA><NA>00.0<NA><NA><NA>322023-08-312