Overview

Dataset statistics

Number of variables25
Number of observations30
Missing cells46
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory217.4 B

Variable types

Categorical12
Text5
Numeric7
DateTime1

Dataset

Description부산광역시_기장군_건축신고현황_201712
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3082033

Alerts

용도지구 has constant value ""Constant
세대수 is highly imbalanced (53.1%)Imbalance
호수 is highly imbalanced (73.5%)Imbalance
부속용도 has 8 (26.7%) missing valuesMissing
용도지구 has 29 (96.7%) missing valuesMissing
총주차대수 has 9 (30.0%) missing valuesMissing
신고번호 has unique valuesUnique
대지면적(㎡) has unique valuesUnique
건폐율(%) has unique valuesUnique
용적률(%) has unique valuesUnique
총주차대수 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 16:56:33.650703
Analysis finished2023-12-10 16:56:34.370925
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
신축
17 
증축
8 
용도변경
5 

Length

Max length4
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 17
56.7%
증축 8
26.7%
용도변경 5
 
16.7%

Length

2023-12-11T01:56:34.563391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:34.793706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 17
56.7%
증축 8
26.7%
용도변경 5
 
16.7%

신고번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:56:35.171992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length19.266667
Min length18

Characters and Unicode

Total characters578
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row2017-창조건축과-신축신고-164
2nd row2017-창조건축과-용도변경신고-33
3rd row2017-창조건축과-신축신고-161
4th row2017-창조건축과-신축신고-162
5th row2017-창조건축과-신축신고-163
ValueCountFrequency (%)
2017-창조건축과-신축신고-164 1
 
3.2%
2017-창조건축과-용도변경신고-30 1
 
3.2%
2017-창조건축과-증축신고-81 1
 
3.2%
2017-창조건축과-용도변경신고-29 1
 
3.2%
2017-창조건축과-신축신고-150 1
 
3.2%
2017-창조건축과-신축신고-152 1
 
3.2%
2017-창조건축과-신축신고-151 1
 
3.2%
2017-창조건축과-신축신고-153 1
 
3.2%
2017-창조건축과-신축신고-154 1
 
3.2%
2017-창조건축과-신축신고-158 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T01:56:35.849446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 90
15.6%
축 54
 
9.3%
1 50
 
8.7%
신 46
 
8.0%
2 35
 
6.1%
0 33
 
5.7%
7 33
 
5.7%
건 31
 
5.4%
창 30
 
5.2%
조 30
 
5.2%
Other values (27) 146
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
50.3%
Decimal Number 194
33.6%
Dash Punctuation 90
 
15.6%
Open Punctuation 1
 
0.2%
Space Separator 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 54
18.6%
신 46
15.8%
건 31
10.7%
창 30
10.3%
조 30
10.3%
과 30
10.3%
고 30
10.3%
증 7
 
2.4%
경 6
 
2.1%
도 5
 
1.7%
Other values (13) 22
7.6%
Decimal Number
ValueCountFrequency (%)
1 50
25.8%
2 35
18.0%
0 33
17.0%
7 33
17.0%
5 12
 
6.2%
8 8
 
4.1%
3 8
 
4.1%
6 7
 
3.6%
9 4
 
2.1%
4 4
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
50.3%
Common 287
49.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 54
18.6%
신 46
15.8%
건 31
10.7%
창 30
10.3%
조 30
10.3%
과 30
10.3%
고 30
10.3%
증 7
 
2.4%
경 6
 
2.1%
도 5
 
1.7%
Other values (13) 22
7.6%
Common
ValueCountFrequency (%)
- 90
31.4%
1 50
17.4%
2 35
 
12.2%
0 33
 
11.5%
7 33
 
11.5%
5 12
 
4.2%
8 8
 
2.8%
3 8
 
2.8%
6 7
 
2.4%
9 4
 
1.4%
Other values (4) 7
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
50.3%
ASCII 287
49.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 90
31.4%
1 50
17.4%
2 35
 
12.2%
0 33
 
11.5%
7 33
 
11.5%
5 12
 
4.2%
8 8
 
2.8%
3 8
 
2.8%
6 7
 
2.4%
9 4
 
1.4%
Other values (4) 7
 
2.4%
Hangul
ValueCountFrequency (%)
축 54
18.6%
신 46
15.8%
건 31
10.7%
창 30
10.3%
조 30
10.3%
과 30
10.3%
고 30
10.3%
증 7
 
2.4%
경 6
 
2.1%
도 5
 
1.7%
Other values (13) 22
7.6%

대지위치
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:56:36.285802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length23.633333
Min length21

Characters and Unicode

Total characters709
Distinct characters63
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

Unique27 ?
Unique (%)90.0%

Sample

1st row부산광역시 기장군 장안읍 반룡리 387-9
2nd row부산광역시 기장군 기장읍 죽성리 30-19
3rd row부산광역시 기장군 기장읍 시랑리 684-2
4th row부산광역시 기장군 기장읍 죽성리 333-9
5th row부산광역시 기장군 기장읍 교리 328-5
ValueCountFrequency (%)
부산광역시 30
19.0%
기장군 30
19.0%
기장읍 11
 
7.0%
일광면 8
 
5.1%
장안읍 7
 
4.4%
외1필지 6
 
3.8%
동부리 3
 
1.9%
434-9 3
 
1.9%
정관읍 3
 
1.9%
이천리 3
 
1.9%
Other values (49) 54
34.2%
2023-12-11T01:56:37.008414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
18.1%
장 48
 
6.8%
기 41
 
5.8%
광 39
 
5.5%
부 34
 
4.8%
시 32
 
4.5%
산 31
 
4.4%
역 30
 
4.2%
군 30
 
4.2%
리 30
 
4.2%
Other values (53) 266
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
62.1%
Space Separator 128
 
18.1%
Decimal Number 119
 
16.8%
Dash Punctuation 22
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 48
10.9%
기 41
 
9.3%
광 39
 
8.9%
부 34
 
7.7%
시 32
 
7.3%
산 31
 
7.0%
역 30
 
6.8%
군 30
 
6.8%
리 30
 
6.8%
읍 21
 
4.8%
Other values (41) 104
23.6%
Decimal Number
ValueCountFrequency (%)
1 23
19.3%
3 21
17.6%
4 17
14.3%
9 12
10.1%
8 9
 
7.6%
7 9
 
7.6%
2 9
 
7.6%
5 8
 
6.7%
6 7
 
5.9%
0 4
 
3.4%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
62.1%
Common 269
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 48
10.9%
기 41
 
9.3%
광 39
 
8.9%
부 34
 
7.7%
시 32
 
7.3%
산 31
 
7.0%
역 30
 
6.8%
군 30
 
6.8%
리 30
 
6.8%
읍 21
 
4.8%
Other values (41) 104
23.6%
Common
ValueCountFrequency (%)
128
47.6%
1 23
 
8.6%
- 22
 
8.2%
3 21
 
7.8%
4 17
 
6.3%
9 12
 
4.5%
8 9
 
3.3%
7 9
 
3.3%
2 9
 
3.3%
5 8
 
3.0%
Other values (2) 11
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
62.1%
ASCII 269
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
47.6%
1 23
 
8.6%
- 22
 
8.2%
3 21
 
7.8%
4 17
 
6.3%
9 12
 
4.5%
8 9
 
3.3%
7 9
 
3.3%
2 9
 
3.3%
5 8
 
3.0%
Other values (2) 11
 
4.1%
Hangul
ValueCountFrequency (%)
장 48
10.9%
기 41
 
9.3%
광 39
 
8.9%
부 34
 
7.7%
시 32
 
7.3%
산 31
 
7.0%
역 30
 
6.8%
군 30
 
6.8%
리 30
 
6.8%
읍 21
 
4.8%
Other values (41) 104
23.6%

지목
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
대
22 
답
4 
전
3 
임야
 
1

Length

Max length2
Median length1
Mean length1.0333333
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
대 22
73.3%
답 4
 
13.3%
전 3
 
10.0%
임야 1
 
3.3%

Length

2023-12-11T01:56:37.309537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:37.502677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 22
73.3%
답 4
 
13.3%
전 3
 
10.0%
임야 1
 
3.3%

대지면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean847.17667
Minimum77
Maximum4191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:37.715324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum77
5-th percentile94.7
Q1273.925
median436.05
Q3968.15
95-th percentile3555.115
Maximum4191
Range4114
Interquartile range (IQR)694.225

Descriptive statistics

Standard deviation1053.8438
Coefficient of variation (CV)1.2439481
Kurtosis5.1121915
Mean847.17667
Median Absolute Deviation (MAD)293.5
Skewness2.3698458
Sum25415.3
Variance1110586.9
MonotonicityNot monotonic
2023-12-11T01:56:37.957582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
760.0 1
 
3.3%
433.0 1
 
3.3%
739.0 1
 
3.3%
400.0 1
 
3.3%
1005.0 1
 
3.3%
152.0 1
 
3.3%
109.0 1
 
3.3%
1118.0 1
 
3.3%
853.0 1
 
3.3%
978.0 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
77.0 1
3.3%
83.0 1
3.3%
109.0 1
3.3%
152.0 1
3.3%
180.0 1
3.3%
222.4 1
3.3%
238.0 1
3.3%
273.9 1
3.3%
274.0 1
3.3%
275.0 1
3.3%
ValueCountFrequency (%)
4191.0 1
3.3%
3964.3 1
3.3%
3055.0 1
3.3%
1465.0 1
3.3%
1118.0 1
3.3%
1054.0 1
3.3%
1005.0 1
3.3%
978.0 1
3.3%
938.6 1
3.3%
853.0 1
3.3%

건축면적(㎡)
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.43
Minimum26.82
Maximum3126.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:38.157423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.82
5-th percentile39.8265
Q173.4475
median87.315
Q3193.66
95-th percentile657.4395
Maximum3126.7
Range3099.88
Interquartile range (IQR)120.2125

Descriptive statistics

Standard deviation567.30673
Coefficient of variation (CV)2.1535388
Kurtosis24.225966
Mean263.43
Median Absolute Deviation (MAD)34.315
Skewness4.7497853
Sum7902.9
Variance321836.92
MonotonicityNot monotonic
2023-12-11T01:56:38.371492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
79.16 3
 
10.0%
54.0 1
 
3.3%
369.52 1
 
3.3%
97.2 1
 
3.3%
73.02 1
 
3.3%
456.24 1
 
3.3%
75.78 1
 
3.3%
58.1 1
 
3.3%
90.64 1
 
3.3%
101.26 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
26.82 1
3.3%
33.0 1
3.3%
48.17 1
3.3%
52.0 1
3.3%
54.0 1
3.3%
58.1 1
3.3%
60.0 1
3.3%
73.02 1
3.3%
74.73 1
3.3%
75.78 1
3.3%
ValueCountFrequency (%)
3126.7 1
3.3%
746.4 1
3.3%
548.71 1
3.3%
456.24 1
3.3%
369.52 1
3.3%
341.83 1
3.3%
333.4 1
3.3%
199.6 1
3.3%
175.84 1
3.3%
132.96 1
3.3%

연면적(㎡)
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.8797
Minimum26.82
Maximum54239.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:38.607183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.82
5-th percentile40.4385
Q176.94
median95.7
Q3285.2175
95-th percentile744.672
Maximum54239.03
Range54212.21
Interquartile range (IQR)208.2775

Descriptive statistics

Standard deviation9865.8775
Coefficient of variation (CV)4.8892298
Kurtosis29.961262
Mean2017.8797
Median Absolute Deviation (MAD)38.7
Skewness5.4721138
Sum60536.39
Variance97335538
MonotonicityNot monotonic
2023-12-11T01:56:38.805398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
79.16 3
 
10.0%
54.0 1
 
3.3%
663.13 1
 
3.3%
76.2 1
 
3.3%
193.49 1
 
3.3%
720.67 1
 
3.3%
49.53 1
 
3.3%
99.6 1
 
3.3%
85.14 1
 
3.3%
96.26 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
26.82 1
 
3.3%
33.0 1
 
3.3%
49.53 1
 
3.3%
52.0 1
 
3.3%
54.0 1
 
3.3%
60.0 1
 
3.3%
67.05 1
 
3.3%
76.2 1
 
3.3%
79.16 3
10.0%
84.63 1
 
3.3%
ValueCountFrequency (%)
54239.03 1
3.3%
764.31 1
3.3%
720.67 1
3.3%
705.0 1
3.3%
663.13 1
3.3%
595.4 1
3.3%
539.29 1
3.3%
292.69 1
3.3%
262.8 1
3.3%
193.49 1
3.3%

건폐율(%)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.201733
Minimum5.59
Maximum78.8714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:39.026178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.59
5-th percentile6.571
Q117.434025
median29.35
Q343.8925
95-th percentile58.9585
Maximum78.8714
Range73.2814
Interquartile range (IQR)26.458475

Descriptive statistics

Standard deviation18.549117
Coefficient of variation (CV)0.59448996
Kurtosis-0.076238335
Mean31.201733
Median Absolute Deviation (MAD)14.07065
Skewness0.54441147
Sum936.052
Variance344.06974
MonotonicityNot monotonic
2023-12-11T01:56:39.265850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7.11 1
 
3.3%
17.2587 1
 
3.3%
13.1529 1
 
3.3%
18.26 1
 
3.3%
45.4 1
 
3.3%
49.86 1
 
3.3%
53.3 1
 
3.3%
8.11 1
 
3.3%
11.87 1
 
3.3%
6.13 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
5.59 1
3.3%
6.13 1
3.3%
7.11 1
3.3%
8.11 1
3.3%
8.16 1
3.3%
11.87 1
3.3%
13.1529 1
3.3%
17.2587 1
3.3%
17.96 1
3.3%
18.26 1
3.3%
ValueCountFrequency (%)
78.8714 1
3.3%
59.71 1
3.3%
58.04 1
3.3%
53.3 1
3.3%
50.95 1
3.3%
50.0 1
3.3%
49.86 1
3.3%
45.4 1
3.3%
39.37 1
3.3%
35.56 1
3.3%

용적률(%)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.159927
Minimum5.59
Maximum920.8283
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:39.482586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.59
5-th percentile6.571
Q121.222675
median30.745
Q347.9125
95-th percentile123.522
Maximum920.8283
Range915.2383
Interquartile range (IQR)26.689825

Descriptive statistics

Standard deviation164.18466
Coefficient of variation (CV)2.481633
Kurtosis27.819311
Mean66.159927
Median Absolute Deviation (MAD)16.96
Skewness5.1990573
Sum1984.7978
Variance26956.602
MonotonicityNot monotonic
2023-12-11T01:56:39.701916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
7.11 1
 
3.3%
21.9723 1
 
3.3%
10.3112 1
 
3.3%
48.37 1
 
3.3%
71.71 1
 
3.3%
32.59 1
 
3.3%
91.38 1
 
3.3%
7.62 1
 
3.3%
11.28 1
 
3.3%
6.13 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
5.59 1
3.3%
6.13 1
3.3%
7.11 1
3.3%
7.62 1
3.3%
10.3112 1
3.3%
11.28 1
3.3%
12.87 1
3.3%
20.9728 1
3.3%
21.9723 1
3.3%
22.61 1
3.3%
ValueCountFrequency (%)
920.8283 1
3.3%
149.82 1
3.3%
91.38 1
3.3%
78.61 1
3.3%
71.71 1
3.3%
50.0 1
3.3%
48.37 1
3.3%
48.12 1
3.3%
47.29 1
3.3%
42.6847 1
3.3%

구조
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
경량철골구조
15 
철근콘크리트구조
7 
일반철골구조
4 
<NA>
2 
철골철근콘크리트구조
 
1

Length

Max length10
Median length6
Mean length6.4333333
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row경량철골구조
2nd row철근콘크리트구조
3rd row일반철골구조
4th row경량철골구조
5th row경량철골구조

Common Values

ValueCountFrequency (%)
경량철골구조 15
50.0%
철근콘크리트구조 7
23.3%
일반철골구조 4
 
13.3%
<NA> 2
 
6.7%
철골철근콘크리트구조 1
 
3.3%
일반목구조 1
 
3.3%

Length

2023-12-11T01:56:39.936544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:40.142409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경량철골구조 15
50.0%
철근콘크리트구조 7
23.3%
일반철골구조 4
 
13.3%
na 2
 
6.7%
철골철근콘크리트구조 1
 
3.3%
일반목구조 1
 
3.3%

신고일
Date

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-12-01 00:00:00
Maximum2017-12-29 00:00:00
2023-12-11T01:56:40.333434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:56:40.537328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

최대지상층수
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
20 
2
6 
3
3 
13
 
1

Length

Max length2
Median length1
Mean length1.0333333
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 20
66.7%
2 6
 
20.0%
3 3
 
10.0%
13 1
 
3.3%

Length

2023-12-11T01:56:40.820191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:41.008898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
66.7%
2 6
 
20.0%
3 3
 
10.0%
13 1
 
3.3%

최대지하층수
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
17 
<NA>
10 
1
2 
5
 
1

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 17
56.7%
<NA> 10
33.3%
1 2
 
6.7%
5 1
 
3.3%

Length

2023-12-11T01:56:41.211334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:41.405087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
56.7%
na 10
33.3%
1 2
 
6.7%
5 1
 
3.3%

최고높이(m)
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8443333
Minimum3.7
Maximum68.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:41.615983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.7
5-th percentile4.179
Q14.9125
median5.525
Q38.83
95-th percentile13.795
Maximum68.4
Range64.7
Interquartile range (IQR)3.9175

Descriptive statistics

Standard deviation11.577038
Coefficient of variation (CV)1.308978
Kurtosis26.384093
Mean8.8443333
Median Absolute Deviation (MAD)1.175
Skewness5.0095258
Sum265.33
Variance134.02781
MonotonicityNot monotonic
2023-12-11T01:56:41.866875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4.75 3
 
10.0%
9.4 2
 
6.7%
5.2 1
 
3.3%
4.4 1
 
3.3%
5.35 1
 
3.3%
13.3 1
 
3.3%
6.8 1
 
3.3%
7.6 1
 
3.3%
5.05 1
 
3.3%
4.9 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
3.7 1
 
3.3%
4.08 1
 
3.3%
4.3 1
 
3.3%
4.4 1
 
3.3%
4.75 3
10.0%
4.9 1
 
3.3%
4.95 1
 
3.3%
5.05 1
 
3.3%
5.2 1
 
3.3%
5.25 1
 
3.3%
ValueCountFrequency (%)
68.4 1
3.3%
14.2 1
3.3%
13.3 1
3.3%
11.9 1
3.3%
9.4 2
6.7%
9.38 1
3.3%
8.85 1
3.3%
8.77 1
3.3%
7.6 1
3.3%
7.3 1
3.3%

동수
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
22 
2
6 
0
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 22
73.3%
2 6
 
20.0%
0 2
 
6.7%

Length

2023-12-11T01:56:42.080631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:42.403783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
73.3%
2 6
 
20.0%
0 2
 
6.7%

주용도
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
단독주택
14 
제2종근린생활시설
12 
제1종근린생활시설
3 
창고시설
 
1

Length

Max length9
Median length6.5
Mean length6.5
Min length4

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row제2종근린생활시설
2nd row제2종근린생활시설
3rd row단독주택
4th row제2종근린생활시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 14
46.7%
제2종근린생활시설 12
40.0%
제1종근린생활시설 3
 
10.0%
창고시설 1
 
3.3%

Length

2023-12-11T01:56:42.669091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:42.891018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 14
46.7%
제2종근린생활시설 12
40.0%
제1종근린생활시설 3
 
10.0%
창고시설 1
 
3.3%

부속용도
Text

MISSING 

Distinct13
Distinct (%)59.1%
Missing8
Missing (%)26.7%
Memory size372.0 B
2023-12-11T01:56:43.150182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length9
Mean length5.1818182
Min length2

Characters and Unicode

Total characters114
Distinct characters45
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

Unique8 ?
Unique (%)36.4%

Sample

1st row사무소
2nd row단독주택
3rd row일반음식점
4th row사무소
5th row학원
ValueCountFrequency (%)
단독주택 6
25.0%
사무소 2
 
8.3%
일반음식점 2
 
8.3%
휴게음식점 2
 
8.3%
소매점 2
 
8.3%
학원 1
 
4.2%
창고시설 1
 
4.2%
판매시설,문화및 1
 
4.2%
집회시설,의료시설,업무시설 1
 
4.2%
외 1
 
4.2%
Other values (5) 5
20.8%
2023-12-11T01:56:43.792559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 7
 
6.1%
택 7
 
6.1%
소 7
 
6.1%
단 6
 
5.3%
독 6
 
5.3%
설 6
 
5.3%
시 6
 
5.3%
점 6
 
5.3%
식 4
 
3.5%
, 4
 
3.5%
Other values (35) 55
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106
93.0%
Other Punctuation 4
 
3.5%
Space Separator 2
 
1.8%
Decimal Number 2
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 7
 
6.6%
택 7
 
6.6%
소 7
 
6.6%
단 6
 
5.7%
독 6
 
5.7%
설 6
 
5.7%
시 6
 
5.7%
점 6
 
5.7%
식 4
 
3.8%
음 4
 
3.8%
Other values (31) 47
44.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106
93.0%
Common 8
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 7
 
6.6%
택 7
 
6.6%
소 7
 
6.6%
단 6
 
5.7%
독 6
 
5.7%
설 6
 
5.7%
시 6
 
5.7%
점 6
 
5.7%
식 4
 
3.8%
음 4
 
3.8%
Other values (31) 47
44.3%
Common
ValueCountFrequency (%)
, 4
50.0%
2
25.0%
2 1
 
12.5%
3 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106
93.0%
ASCII 8
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 7
 
6.6%
택 7
 
6.6%
소 7
 
6.6%
단 6
 
5.7%
독 6
 
5.7%
설 6
 
5.7%
시 6
 
5.7%
점 6
 
5.7%
식 4
 
3.8%
음 4
 
3.8%
Other values (31) 47
44.3%
ASCII
ValueCountFrequency (%)
, 4
50.0%
2
25.0%
2 1
 
12.5%
3 1
 
12.5%

용도지역
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
제1종일반주거지역
12 
자연녹지지역
6 
제2종일반주거지역
6 
제3종일반주거지역
4 
<NA>
 
1

Length

Max length9
Median length9
Mean length8.1333333
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row자연녹지지역
2nd row제1종일반주거지역
3rd row제1종일반주거지역
4th row제1종일반주거지역
5th row제2종일반주거지역

Common Values

ValueCountFrequency (%)
제1종일반주거지역 12
40.0%
자연녹지지역 6
20.0%
제2종일반주거지역 6
20.0%
제3종일반주거지역 4
 
13.3%
<NA> 1
 
3.3%
보전녹지지역 1
 
3.3%

Length

2023-12-11T01:56:44.066050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:44.272087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1종일반주거지역 12
40.0%
자연녹지지역 6
20.0%
제2종일반주거지역 6
20.0%
제3종일반주거지역 4
 
13.3%
na 1
 
3.3%
보전녹지지역 1
 
3.3%

용도지구
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-11T01:56:44.529390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row주거환경개선지구
ValueCountFrequency (%)
주거환경개선지구 1
100.0%
2023-12-11T01:56:45.034163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1
12.5%
거 1
12.5%
환 1
12.5%
경 1
12.5%
개 1
12.5%
선 1
12.5%
지 1
12.5%
구 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1
12.5%
거 1
12.5%
환 1
12.5%
경 1
12.5%
개 1
12.5%
선 1
12.5%
지 1
12.5%
구 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1
12.5%
거 1
12.5%
환 1
12.5%
경 1
12.5%
개 1
12.5%
선 1
12.5%
지 1
12.5%
구 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1
12.5%
거 1
12.5%
환 1
12.5%
경 1
12.5%
개 1
12.5%
선 1
12.5%
지 1
12.5%
구 1
12.5%

용도구역
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
제1종지구단위계획구역
13 
<NA>
8 
가축사육제한구역
7 
상대정화구역
 
1
개발제한구역
 
1

Length

Max length11
Median length8
Mean length8.1
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row<NA>
2nd row상대정화구역
3rd row가축사육제한구역
4th row제1종지구단위계획구역
5th row가축사육제한구역

Common Values

ValueCountFrequency (%)
제1종지구단위계획구역 13
43.3%
<NA> 8
26.7%
가축사육제한구역 7
23.3%
상대정화구역 1
 
3.3%
개발제한구역 1
 
3.3%

Length

2023-12-11T01:56:45.297788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:45.486220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1종지구단위계획구역 13
43.3%
na 8
26.7%
가축사육제한구역 7
23.3%
상대정화구역 1
 
3.3%
개발제한구역 1
 
3.3%

총주차대수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)38.1%
Missing9
Missing (%)30.0%
Infinite0
Infinite (%)0.0%
Mean25.47619
Minimum0
Maximum435
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:56:45.646409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q34
95-th percentile58
Maximum435
Range435
Interquartile range (IQR)3

Descriptive statistics

Standard deviation94.632246
Coefficient of variation (CV)3.7145367
Kurtosis20.185954
Mean25.47619
Median Absolute Deviation (MAD)1
Skewness4.4651424
Sum535
Variance8955.2619
MonotonicityNot monotonic
2023-12-11T01:56:45.866919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 8
26.7%
2 5
16.7%
4 2
 
6.7%
5 2
 
6.7%
6 1
 
3.3%
435 1
 
3.3%
58 1
 
3.3%
0 1
 
3.3%
(Missing) 9
30.0%
ValueCountFrequency (%)
0 1
 
3.3%
1 8
26.7%
2 5
16.7%
4 2
 
6.7%
5 2
 
6.7%
6 1
 
3.3%
58 1
 
3.3%
435 1
 
3.3%
ValueCountFrequency (%)
435 1
 
3.3%
58 1
 
3.3%
6 1
 
3.3%
5 2
 
6.7%
4 2
 
6.7%
2 5
16.7%
1 8
26.7%
0 1
 
3.3%

세대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
27 
1
3 

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
90.0%
1 3
 
10.0%

Length

2023-12-11T01:56:46.180084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:46.346056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
90.0%
1 3
 
10.0%

호수
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
28 
1
 
1
286
 
1

Length

Max length4
Median length4
Mean length3.8666667
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
93.3%
1 1
 
3.3%
286 1
 
3.3%

Length

2023-12-11T01:56:46.529192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:46.732438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
93.3%
1 1
 
3.3%
286 1
 
3.3%

가구수
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
18 
1
11 
2
 
1

Length

Max length4
Median length4
Mean length2.8
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
60.0%
1 11
36.7%
2 1
 
3.3%

Length

2023-12-11T01:56:46.921082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:47.532346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
60.0%
1 11
36.7%
2 1
 
3.3%

설계사무소명
Text

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:56:47.761094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.5666667
Min length8

Characters and Unicode

Total characters287
Distinct characters50
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)46.7%

Sample

1st row건보건축사사무소
2nd row건축사사무소 강건축
3rd row(주)해공A&E건축사사무소
4th row일탑 건축사사무소
5th row동림건축사사무소
ValueCountFrequency (%)
건축사사무소 15
31.2%
일탑 3
 
6.2%
선경 3
 
6.2%
주)해공a&e건축사사무소 2
 
4.2%
동림건축사사무소 2
 
4.2%
일산 2
 
4.2%
홍 2
 
4.2%
신한일종합건축사사무소 2
 
4.2%
해조 1
 
2.1%
건보건축사사무소 1
 
2.1%
Other values (15) 15
31.2%
2023-12-11T01:56:48.252733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 61
21.3%
건 32
11.1%
축 31
10.8%
무 30
10.5%
소 30
10.5%
18
 
6.3%
일 8
 
2.8%
주 4
 
1.4%
종 4
 
1.4%
합 4
 
1.4%
Other values (40) 65
22.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 257
89.5%
Space Separator 18
 
6.3%
Uppercase Letter 4
 
1.4%
Open Punctuation 3
 
1.0%
Close Punctuation 3
 
1.0%
Other Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 61
23.7%
건 32
12.5%
축 31
12.1%
무 30
11.7%
소 30
11.7%
일 8
 
3.1%
주 4
 
1.6%
종 4
 
1.6%
합 4
 
1.6%
선 4
 
1.6%
Other values (34) 49
19.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
E 2
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 257
89.5%
Common 26
 
9.1%
Latin 4
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 61
23.7%
건 32
12.5%
축 31
12.1%
무 30
11.7%
소 30
11.7%
일 8
 
3.1%
주 4
 
1.6%
종 4
 
1.6%
합 4
 
1.6%
선 4
 
1.6%
Other values (34) 49
19.1%
Common
ValueCountFrequency (%)
18
69.2%
( 3
 
11.5%
) 3
 
11.5%
& 2
 
7.7%
Latin
ValueCountFrequency (%)
A 2
50.0%
E 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 257
89.5%
ASCII 30
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 61
23.7%
건 32
12.5%
축 31
12.1%
무 30
11.7%
소 30
11.7%
일 8
 
3.1%
주 4
 
1.6%
종 4
 
1.6%
합 4
 
1.6%
선 4
 
1.6%
Other values (34) 49
19.1%
ASCII
ValueCountFrequency (%)
18
60.0%
( 3
 
10.0%
) 3
 
10.0%
& 2
 
6.7%
A 2
 
6.7%
E 2
 
6.7%

Sample

건축구분신고번호대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)건폐율(%)용적률(%)구조신고일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명
0신축2017-창조건축과-신축신고-164부산광역시 기장군 장안읍 반룡리 387-9대760.054.054.07.117.11경량철골구조2017-12-29105.21제2종근린생활시설사무소자연녹지지역<NA><NA><NA><NA><NA><NA>건보건축사사무소
1용도변경2017-창조건축과-용도변경신고-33부산광역시 기장군 기장읍 죽성리 30-19대83.048.17124.3558.04149.82철근콘크리트구조2017-12-283<NA>9.381제2종근린생활시설단독주택제1종일반주거지역<NA>상대정화구역<NA><NA>1<NA>건축사사무소 강건축
2신축2017-창조건축과-신축신고-161부산광역시 기장군 기장읍 시랑리 684-2대319.784.0367.0526.28420.9728일반철골구조2017-12-28104.951단독주택<NA>제1종일반주거지역<NA>가축사육제한구역2<NA><NA>1(주)해공A&E건축사사무소
3신축2017-창조건축과-신축신고-162부산광역시 기장군 기장읍 죽성리 333-9전77.026.8226.8234.8334.83경량철골구조2017-12-28103.71제2종근린생활시설일반음식점제1종일반주거지역<NA>제1종지구단위계획구역<NA><NA><NA><NA>일탑 건축사사무소
4신축2017-창조건축과-신축신고-163부산광역시 기장군 기장읍 교리 328-5대439.1130.8499.329.822.61경량철골구조2017-12-28106.532제2종근린생활시설사무소제2종일반주거지역<NA>가축사육제한구역1<NA><NA><NA>동림건축사사무소
5용도변경2017-창조건축과-용도변경신고-32부산광역시 기장군 일광면 이천리 755-2대1054.0333.4595.431.6347.29철근콘크리트구조2017-12-22219.41제2종근린생활시설학원자연녹지지역<NA>가축사육제한구역4<NA><NA><NA>일산 건축사사무소
6증축2017-창조건축과-증축신고-87부산광역시 기장군 정관읍 매학리 136-13대3055.0548.71764.3117.9625.02철근콘크리트구조2017-12-222<NA>11.91제2종근린생활시설휴게음식점자연녹지지역<NA>가축사육제한구역6<NA><NA><NA>백산종합건축사사무소
7신축2017-창조건축과-신축신고-160부산광역시 기장군 철마면 웅천리 377-4전238.084.6384.6335.5635.56경량철골구조2017-12-22105.421단독주택<NA>제1종일반주거지역<NA>제1종지구단위계획구역1<NA><NA>1일산 건축사사무소
8신축2017-창조건축과-개발제한구역내 건축신고-9부산광역시 기장군 정관읍 임곡리 131답180.090.090.050.050.0일반철골구조2017-12-21105.51창고시설창고시설자연녹지지역<NA>개발제한구역<NA><NA><NA><NA>건축사사무소 홍
9용도변경2017-창조건축과-용도변경신고-31부산광역시 기장군 정관읍 매학리 717-5 외1필지대3964.33126.754239.0378.8714920.8283철골철근콘크리트구조2017-12-2113568.41제2종근린생활시설판매시설,문화및 집회시설,의료시설,업무시설<NA><NA><NA>435<NA>286<NA>주식회사 목전 건축사사무소
건축구분신고번호대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)건폐율(%)용적률(%)구조신고일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명
20신축2017-창조건축과-신축신고-157부산광역시 기장군 기장읍 동부리 434-9대275.079.1679.1628.7928.79경량철골구조2017-12-12104.751단독주택단독주택제3종일반주거지역<NA><NA>1<NA><NA>1건축사사무소 선경
21신축2017-창조건축과-신축신고-158부산광역시 기장군 기장읍 청강리 291-11대222.452.052.023.3823.38경량철골구조2017-12-12105.551제2종근린생활시설제조업소제3종일반주거지역<NA>가축사육제한구역0<NA><NA><NA>이레건축사사무소
22신축2017-창조건축과-신축신고-154부산광역시 기장군 일광면 원리 산 6-10 외1필지임야978.060.060.06.136.13경량철골구조2017-12-11104.31단독주택<NA>보전녹지지역<NA>제1종지구단위계획구역1<NA><NA>1일 건축사 사무소
23신축2017-창조건축과-신축신고-153부산광역시 기장군 장안읍 덕선리 189 외1필지전853.0101.2696.2611.8711.28철근콘크리트구조2017-12-07104.91단독주택단독주택자연녹지지역<NA>제1종지구단위계획구역1<NA><NA>1신한일종합건축사사무소
24신축2017-창조건축과-신축신고-151부산광역시 기장군 기장읍 시랑리 184-4 외1필지대1118.090.6485.148.117.62철근콘크리트구조2017-12-06105.051단독주택<NA>제1종일반주거지역<NA>제1종지구단위계획구역2<NA><NA>1가야건축사사무소
25신축2017-창조건축과-신축신고-152부산광역시 기장군 일광면 이천리 395-4대109.058.199.653.391.38일반철골구조2017-12-06207.61제2종근린생활시설일반음식점제2종일반주거지역<NA>가축사육제한구역<NA><NA><NA><NA>신한일종합건축사사무소
26신축2017-창조건축과-신축신고-150부산광역시 기장군 장안읍 좌천리 287-3대152.075.7849.5349.8632.59철근콘크리트구조2017-12-05106.81단독주택단독주택제2종일반주거지역<NA>제1종지구단위계획구역<NA><NA><NA>1(주)종합건축사사무소로얄설계
27용도변경2017-창조건축과-용도변경신고-29부산광역시 기장군 장안읍 길천리 376-3대1005.0456.24720.6745.471.71<NA>2017-12-042<NA>13.31제2종근린생활시설제2종근린생활시설제1종일반주거지역<NA>제1종지구단위계획구역4<NA><NA><NA>건축사사무소 홍
28증축2017-창조건축과-증축신고-81부산광역시 기장군 일광면 화전리 530대400.073.02193.4918.2648.37철근콘크리트구조2017-12-043<NA>9.41단독주택다가구주택제1종일반주거지역<NA>가축사육제한구역2<NA><NA>2선우건축사사무소
29신축2017-창조건축과-신축신고-149부산광역시 기장군 일광면 문중리 188-1답739.097.276.213.152910.3112경량철골구조2017-12-01105.351단독주택<NA>제1종일반주거지역<NA>제1종지구단위계획구역11<NA><NA>(주)해공A&E건축사사무소