Overview

Dataset statistics

Number of variables17
Number of observations39
Missing cells5
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory145.4 B

Variable types

Categorical5
Text5
Numeric5
DateTime2

Dataset

Description부산광역시동구_건설현장시공정보_20221013
Author부산광역시 동구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15035722

Alerts

지목 is highly overall correlated with 대지면적(제곱미터) and 4 other fieldsHigh correlation
증축연면적(제곱미터) is highly overall correlated with 대지면적(제곱미터) and 8 other fieldsHigh correlation
주용도 is highly overall correlated with 대지면적(제곱미터) and 1 other fieldsHigh correlation
건축구분 is highly overall correlated with 증축연면적(제곱미터)High correlation
구조 is highly overall correlated with 대지면적(제곱미터) and 2 other fieldsHigh correlation
대지면적(제곱미터) is highly overall correlated with 건축면적(제곱미터) and 5 other fieldsHigh correlation
건축면적(제곱미터) is highly overall correlated with 대지면적(제곱미터) and 3 other fieldsHigh correlation
연면적(제곱미터) is highly overall correlated with 대지면적(제곱미터) and 2 other fieldsHigh correlation
건폐율 is highly overall correlated with 용적률 and 2 other fieldsHigh correlation
용적률 is highly overall correlated with 건폐율 and 1 other fieldsHigh correlation
건축구분 is highly imbalanced (64.7%)Imbalance
지목 is highly imbalanced (56.3%)Imbalance
증축연면적(제곱미터) is highly imbalanced (74.3%)Imbalance
구조 is highly imbalanced (57.3%)Imbalance
부속용도 has 1 (2.6%) missing valuesMissing
감리사무소명 has 1 (2.6%) missing valuesMissing
시공자사무소명 has 3 (7.7%) missing valuesMissing
대지위치 has unique valuesUnique
대지면적(제곱미터) has unique valuesUnique
건축면적(제곱미터) has unique valuesUnique
연면적(제곱미터) has unique valuesUnique
건폐율 has unique valuesUnique
용적률 has unique valuesUnique
허가일 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:42:22.208611
Analysis finished2023-12-10 16:42:27.019153
Duration4.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
신축
35 
증축
 
3
개축
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
신축 35
89.7%
증축 3
 
7.7%
개축 1
 
2.6%

Length

2023-12-11T01:42:27.078835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:42:27.200182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 35
89.7%
증축 3
 
7.7%
개축 1
 
2.6%

대지위치
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T01:42:27.423817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length21.666667
Min length16

Characters and Unicode

Total characters845
Distinct characters49
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

Unique39 ?
Unique (%)100.0%

Sample

1st row부산광역시 동구 범일동 1369
2nd row부산광역시 동구 범일동 830-239
3rd row부산광역시 동구 수정동 1043-163
4th row부산광역시 동구 범일동 828-9
5th row부산광역시 동구 수정동 342
ValueCountFrequency (%)
부산광역시 39
21.7%
동구 39
21.7%
초량동 14
 
7.8%
범일동 13
 
7.2%
수정동 8
 
4.4%
외1필지 6
 
3.3%
좌천동 4
 
2.2%
산 3
 
1.7%
외3필지 2
 
1.1%
외20필지 1
 
0.6%
Other values (51) 51
28.3%
2023-12-11T01:42:27.823953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141
16.7%
동 78
 
9.2%
산 44
 
5.2%
부 41
 
4.9%
역 40
 
4.7%
광 39
 
4.6%
시 39
 
4.6%
구 39
 
4.6%
1 38
 
4.5%
- 31
 
3.7%
Other values (39) 315
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 474
56.1%
Decimal Number 192
22.7%
Space Separator 141
 
16.7%
Dash Punctuation 31
 
3.7%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 78
16.5%
산 44
9.3%
부 41
8.6%
역 40
 
8.4%
광 39
 
8.2%
시 39
 
8.2%
구 39
 
8.2%
지 18
 
3.8%
필 17
 
3.6%
외 17
 
3.6%
Other values (24) 102
21.5%
Decimal Number
ValueCountFrequency (%)
1 38
19.8%
2 24
12.5%
9 20
10.4%
4 20
10.4%
3 20
10.4%
8 19
9.9%
6 15
 
7.8%
0 14
 
7.3%
5 12
 
6.2%
7 10
 
5.2%
Space Separator
ValueCountFrequency (%)
141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 474
56.1%
Common 370
43.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 78
16.5%
산 44
9.3%
부 41
8.6%
역 40
 
8.4%
광 39
 
8.2%
시 39
 
8.2%
구 39
 
8.2%
지 18
 
3.8%
필 17
 
3.6%
외 17
 
3.6%
Other values (24) 102
21.5%
Common
ValueCountFrequency (%)
141
38.1%
1 38
 
10.3%
- 31
 
8.4%
2 24
 
6.5%
9 20
 
5.4%
4 20
 
5.4%
3 20
 
5.4%
8 19
 
5.1%
6 15
 
4.1%
0 14
 
3.8%
Other values (4) 28
 
7.6%
Latin
ValueCountFrequency (%)
I 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 474
56.1%
ASCII 371
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141
38.0%
1 38
 
10.2%
- 31
 
8.4%
2 24
 
6.5%
9 20
 
5.4%
4 20
 
5.4%
3 20
 
5.4%
8 19
 
5.1%
6 15
 
4.0%
0 14
 
3.8%
Other values (5) 29
 
7.8%
Hangul
ValueCountFrequency (%)
동 78
16.5%
산 44
9.3%
부 41
8.6%
역 40
 
8.4%
광 39
 
8.2%
시 39
 
8.2%
구 39
 
8.2%
지 18
 
3.8%
필 17
 
3.6%
외 17
 
3.6%
Other values (24) 102
21.5%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
대
31 
임야
 
3
종교용지
 
1
공원
 
1
철도용지
 
1
Other values (2)
 
2

Length

Max length4
Median length1
Mean length1.3589744
Min length1

Unique

Unique5 ?
Unique (%)12.8%

Sample

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

Common Values

ValueCountFrequency (%)
대 31
79.5%
임야 3
 
7.7%
종교용지 1
 
2.6%
공원 1
 
2.6%
철도용지 1
 
2.6%
도로 1
 
2.6%
학교용지 1
 
2.6%

Length

2023-12-11T01:42:27.988826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:42:28.119971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 31
79.5%
임야 3
 
7.7%
종교용지 1
 
2.6%
공원 1
 
2.6%
철도용지 1
 
2.6%
도로 1
 
2.6%
학교용지 1
 
2.6%

대지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2878.4744
Minimum133.5
Maximum26466.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T01:42:28.246153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum133.5
5-th percentile158.2
Q1304.065
median572.26
Q31438.16
95-th percentile17283.91
Maximum26466.27
Range26332.77
Interquartile range (IQR)1134.095

Descriptive statistics

Standard deviation6051.642
Coefficient of variation (CV)2.1023783
Kurtosis8.452015
Mean2878.4744
Median Absolute Deviation (MAD)379.26
Skewness2.9756356
Sum112260.5
Variance36622371
MonotonicityNot monotonic
2023-12-11T01:42:28.356664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
350.0 1
 
2.6%
160.0 1
 
2.6%
850.0 1
 
2.6%
9466.0 1
 
2.6%
434.0 1
 
2.6%
1605.32 1
 
2.6%
1271.0 1
 
2.6%
142.0 1
 
2.6%
229.4 1
 
2.6%
193.0 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
133.5 1
2.6%
142.0 1
2.6%
160.0 1
2.6%
165.0 1
2.6%
176.17 1
2.6%
193.0 1
2.6%
229.4 1
2.6%
264.1 1
2.6%
281.3 1
2.6%
286.0 1
2.6%
ValueCountFrequency (%)
26466.27 1
2.6%
22873.0 1
2.6%
16662.9 1
2.6%
9466.0 1
2.6%
8384.8 1
2.6%
4146.5 1
2.6%
3178.2 1
2.6%
2818.0 1
2.6%
2471.5304 1
2.6%
1605.32 1
2.6%

건축면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean964.39985
Minimum61.82
Maximum12152.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T01:42:28.486071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.82
5-th percentile94.6935
Q1179.4699
median284.22
Q3938.85
95-th percentile3251.0958
Maximum12152.59
Range12090.77
Interquartile range (IQR)759.3801

Descriptive statistics

Standard deviation2045.656
Coefficient of variation (CV)2.1211699
Kurtosis24.553301
Mean964.39985
Median Absolute Deviation (MAD)144.56
Skewness4.6480981
Sum37611.594
Variance4184708.3
MonotonicityNot monotonic
2023-12-11T01:42:28.626191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
258.51 1
 
2.6%
109.05 1
 
2.6%
291.33 1
 
2.6%
1255.8 1
 
2.6%
206.35 1
 
2.6%
1000.67 1
 
2.6%
407.54 1
 
2.6%
63.9 1
 
2.6%
137.55 1
 
2.6%
114.99 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
61.82 1
2.6%
63.9 1
2.6%
98.115 1
2.6%
109.05 1
2.6%
114.99 1
2.6%
137.55 1
2.6%
139.66 1
2.6%
141.54 1
2.6%
160.16 1
2.6%
176.2598 1
2.6%
ValueCountFrequency (%)
12152.59 1
2.6%
4011.13 1
2.6%
3166.6475 1
2.6%
2762.28 1
2.6%
1817.698 1
2.6%
1538.95 1
2.6%
1318.3 1
2.6%
1255.8 1
2.6%
1000.67 1
2.6%
983.91 1
2.6%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5975.0918
Minimum111.48
Maximum56248.571
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T01:42:28.724608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111.48
5-th percentile124.065
Q1431.0908
median1009.85
Q35220.855
95-th percentile24752.632
Maximum56248.571
Range56137.091
Interquartile range (IQR)4789.7642

Descriptive statistics

Standard deviation11224.254
Coefficient of variation (CV)1.8785074
Kurtosis10.859316
Mean5975.0918
Median Absolute Deviation (MAD)884.6
Skewness3.1109545
Sum233028.58
Variance1.2598388 × 108
MonotonicityNot monotonic
2023-12-11T01:42:28.824408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3021.975 1
 
2.6%
252.3 1
 
2.6%
691.68 1
 
2.6%
23518.992 1
 
2.6%
486.38 1
 
2.6%
7677.46 1
 
2.6%
981.58 1
 
2.6%
125.25 1
 
2.6%
380.06 1
 
2.6%
111.48 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
111.48 1
2.6%
113.4 1
2.6%
125.25 1
2.6%
159.92 1
2.6%
248.49 1
2.6%
252.3 1
2.6%
352.53 1
2.6%
380.06 1
2.6%
396.88 1
2.6%
428.3816 1
2.6%
ValueCountFrequency (%)
56248.5708 1
2.6%
34440.7917 1
2.6%
23676.17 1
2.6%
23518.992 1
2.6%
15686.38 1
2.6%
11714.35 1
2.6%
9640.03 1
2.6%
7677.46 1
2.6%
5719.59 1
2.6%
5411.52 1
2.6%

증축연면적(제곱미터)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
<NA>
36 
2796.43
 
1
591.96
 
1
-30.18
 
1

Length

Max length7
Median length4
Mean length4.1794872
Min length4

Unique

Unique3 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
92.3%
2796.43 1
 
2.6%
591.96 1
 
2.6%
-30.18 1
 
2.6%

Length

2023-12-11T01:42:28.931135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:42:29.023192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
92.3%
2796.43 1
 
2.6%
591.96 1
 
2.6%
30.18 1
 
2.6%

건폐율
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.81171
Minimum4.3
Maximum80.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T01:42:29.115147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.3
5-th percentile22.99162
Q138.46
median56
Q368.98
95-th percentile78.527
Maximum80.34
Range76.04
Interquartile range (IQR)30.52

Descriptive statistics

Standard deviation18.961526
Coefficient of variation (CV)0.35904018
Kurtosis-0.23871575
Mean52.81171
Median Absolute Deviation (MAD)14.52
Skewness-0.54569807
Sum2059.6567
Variance359.53947
MonotonicityNot monotonic
2023-12-11T01:42:29.220700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
73.86 1
 
2.6%
68.16 1
 
2.6%
34.27 1
 
2.6%
13.2664 1
 
2.6%
47.55 1
 
2.6%
62.33 1
 
2.6%
32.06 1
 
2.6%
45.0 1
 
2.6%
59.96 1
 
2.6%
59.58 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
4.3 1
2.6%
13.2664 1
2.6%
24.0722 1
2.6%
29.54 1
2.6%
32.01 1
2.6%
32.06 1
2.6%
32.9439 1
2.6%
34.27 1
2.6%
35.37 1
2.6%
35.44 1
2.6%
ValueCountFrequency (%)
80.34 1
2.6%
79.85 1
2.6%
78.38 1
2.6%
76.37 1
2.6%
73.86 1
2.6%
73.55 1
2.6%
72.3 1
2.6%
71.34 1
2.6%
71.3 1
2.6%
69.17 1
2.6%

용적률
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean314.364
Minimum9.93
Maximum1222.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-11T01:42:29.327632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.93
5-th percentile24.89617
Q179.2555
median119.07
Q3503.605
95-th percentile1050.936
Maximum1222.2
Range1212.27
Interquartile range (IQR)424.3495

Descriptive statistics

Standard deviation372.22834
Coefficient of variation (CV)1.184068
Kurtosis0.08181108
Mean314.364
Median Absolute Deviation (MAD)50.91
Skewness1.2906054
Sum12260.196
Variance138553.94
MonotonicityNot monotonic
2023-12-11T01:42:29.459538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
806.66 1
 
2.6%
68.16 1
 
2.6%
81.37 1
 
2.6%
15.9193 1
 
2.6%
112.07 1
 
2.6%
338.33 1
 
2.6%
77.23 1
 
2.6%
88.2 1
 
2.6%
165.68 1
 
2.6%
57.76 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
9.93 1
2.6%
15.9193 1
2.6%
25.8936 1
2.6%
55.92 1
2.6%
57.76 1
2.6%
62.31 1
2.6%
65.49 1
2.6%
68.16 1
2.6%
77.23 1
2.6%
77.711 1
2.6%
ValueCountFrequency (%)
1222.2 1
2.6%
1132.08 1
2.6%
1041.92 1
2.6%
997.63 1
2.6%
898.88 1
2.6%
869.92 1
2.6%
830.7892 1
2.6%
806.66 1
2.6%
675.56 1
2.6%
668.88 1
2.6%

구조
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
철근콘크리트구조
34 
일반철골구조
 
3
철골철근콘크리트구조
 
2

Length

Max length10
Median length8
Mean length7.9487179
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 34
87.2%
일반철골구조 3
 
7.7%
철골철근콘크리트구조 2
 
5.1%

Length

2023-12-11T01:42:29.612010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:42:29.727221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 34
87.2%
일반철골구조 3
 
7.7%
철골철근콘크리트구조 2
 
5.1%

허가일
Date

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
Minimum2014-06-13 00:00:00
Maximum2022-05-03 00:00:00
2023-12-11T01:42:29.824013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:29.948734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

착공처리일
Date

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
Minimum2014-10-23 00:00:00
Maximum2022-05-17 00:00:00
2023-12-11T01:42:30.061507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:30.206789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

주용도
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
업무시설
8 
제1종근린생활시설
6 
공동주택
5 
문화및집회시설
5 
제2종근린생활시설
3 
Other values (7)
12 

Length

Max length9
Median length7
Mean length5.8974359
Min length4

Unique

Unique4 ?
Unique (%)10.3%

Sample

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

Common Values

ValueCountFrequency (%)
업무시설 8
20.5%
제1종근린생활시설 6
15.4%
공동주택 5
12.8%
문화및집회시설 5
12.8%
제2종근린생활시설 3
 
7.7%
자동차관련시설 3
 
7.7%
노유자시설 3
 
7.7%
단독주택 2
 
5.1%
종교시설 1
 
2.6%
운수시설 1
 
2.6%
Other values (2) 2
 
5.1%

Length

2023-12-11T01:42:30.389964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 8
20.5%
제1종근린생활시설 6
15.4%
공동주택 5
12.8%
문화및집회시설 5
12.8%
제2종근린생활시설 3
 
7.7%
자동차관련시설 3
 
7.7%
노유자시설 3
 
7.7%
단독주택 2
 
5.1%
종교시설 1
 
2.6%
운수시설 1
 
2.6%
Other values (2) 2
 
5.1%

부속용도
Text

MISSING 

Distinct31
Distinct (%)81.6%
Missing1
Missing (%)2.6%
Memory size444.0 B
2023-12-11T01:42:30.568279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length7.6052632
Min length3

Characters and Unicode

Total characters289
Distinct characters78
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

Unique26 ?
Unique (%)68.4%

Sample

1st row오피스텔
2nd row사무소,일반음식점
3rd row단독주택, 제1종근린생활시설
4th row업무시설(오피스텔),제2종근린생활시설
5th row아파트(도시형생활주택)/업무시설(오피스텔)
ValueCountFrequency (%)
주차장 3
 
7.3%
오피스텔 3
 
7.3%
전시장 3
 
7.3%
지구대 2
 
4.9%
종교집회장 2
 
4.9%
마을공동작업소 2
 
4.9%
제1종근린생활시설 2
 
4.9%
노인복지시설 1
 
2.4%
집회장 1
 
2.4%
노인여가복지시설 1
 
2.4%
Other values (21) 21
51.2%
2023-12-11T01:42:30.942608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 20
 
6.9%
설 14
 
4.8%
주 10
 
3.5%
생 10
 
3.5%
장 10
 
3.5%
활 10
 
3.5%
, 9
 
3.1%
텔 8
 
2.8%
스 8
 
2.8%
피 8
 
2.8%
Other values (68) 182
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
88.6%
Other Punctuation 10
 
3.5%
Open Punctuation 8
 
2.8%
Close Punctuation 8
 
2.8%
Decimal Number 4
 
1.4%
Space Separator 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
7.8%
설 14
 
5.5%
주 10
 
3.9%
생 10
 
3.9%
장 10
 
3.9%
활 10
 
3.9%
텔 8
 
3.1%
스 8
 
3.1%
피 8
 
3.1%
오 8
 
3.1%
Other values (61) 150
58.6%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
/ 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 3
75.0%
2 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
88.6%
Common 33
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
7.8%
설 14
 
5.5%
주 10
 
3.9%
생 10
 
3.9%
장 10
 
3.9%
활 10
 
3.9%
텔 8
 
3.1%
스 8
 
3.1%
피 8
 
3.1%
오 8
 
3.1%
Other values (61) 150
58.6%
Common
ValueCountFrequency (%)
, 9
27.3%
( 8
24.2%
) 8
24.2%
3
 
9.1%
1 3
 
9.1%
2 1
 
3.0%
/ 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
88.6%
ASCII 33
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 20
 
7.8%
설 14
 
5.5%
주 10
 
3.9%
생 10
 
3.9%
장 10
 
3.9%
활 10
 
3.9%
텔 8
 
3.1%
스 8
 
3.1%
피 8
 
3.1%
오 8
 
3.1%
Other values (61) 150
58.6%
ASCII
ValueCountFrequency (%)
, 9
27.3%
( 8
24.2%
) 8
24.2%
3
 
9.1%
1 3
 
9.1%
2 1
 
3.0%
/ 1
 
3.0%

설계사무소명
Text

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-11T01:42:31.165811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length12.589744
Min length8

Characters and Unicode

Total characters491
Distinct characters71
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

Unique30 ?
Unique (%)76.9%

Sample

1st row(주)아키신화종합건축사사무소
2nd row송지 종합건축사사무소
3rd row주식회사 디딤엔지니어링건축사사무소
4th row(주)상지엔지니어링건축사사무소
5th row주식회사 종합건축사사무소 세온
ValueCountFrequency (%)
종합건축사사무소 7
 
12.1%
건축사사무소 6
 
10.3%
주식회사 4
 
6.9%
주)지에스에이건축사사무소 3
 
5.2%
주)상지엔지니어링건축사사무소 2
 
3.4%
세온 2
 
3.4%
주)타오종합건축사사무소 2
 
3.4%
주)부산건축종합건축사사무소 2
 
3.4%
주)서현건축사사무소 1
 
1.7%
주)한국종합건축사사무소 1
 
1.7%
Other values (28) 28
48.3%
2023-12-11T01:42:31.553475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 82
16.7%
건 44
 
9.0%
축 43
 
8.8%
소 39
 
7.9%
무 39
 
7.9%
주 24
 
4.9%
20
 
4.1%
( 20
 
4.1%
) 20
 
4.1%
종 15
 
3.1%
Other values (61) 145
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
87.8%
Space Separator 20
 
4.1%
Open Punctuation 20
 
4.1%
Close Punctuation 20
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 82
19.0%
건 44
10.2%
축 43
 
10.0%
소 39
 
9.0%
무 39
 
9.0%
주 24
 
5.6%
종 15
 
3.5%
합 15
 
3.5%
지 14
 
3.2%
에 7
 
1.6%
Other values (58) 109
25.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
87.8%
Common 60
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 82
19.0%
건 44
10.2%
축 43
 
10.0%
소 39
 
9.0%
무 39
 
9.0%
주 24
 
5.6%
종 15
 
3.5%
합 15
 
3.5%
지 14
 
3.2%
에 7
 
1.6%
Other values (58) 109
25.3%
Common
ValueCountFrequency (%)
20
33.3%
( 20
33.3%
) 20
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
87.8%
ASCII 60
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 82
19.0%
건 44
10.2%
축 43
 
10.0%
소 39
 
9.0%
무 39
 
9.0%
주 24
 
5.6%
종 15
 
3.5%
합 15
 
3.5%
지 14
 
3.2%
에 7
 
1.6%
Other values (58) 109
25.3%
ASCII
ValueCountFrequency (%)
20
33.3%
( 20
33.3%
) 20
33.3%

감리사무소명
Text

MISSING 

Distinct33
Distinct (%)86.8%
Missing1
Missing (%)2.6%
Memory size444.0 B
2023-12-11T01:42:31.772055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length12.552632
Min length8

Characters and Unicode

Total characters477
Distinct characters72
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

Unique31 ?
Unique (%)81.6%

Sample

1st row(주)아키신화종합건축사사무소
2nd row(주)종합건축사사무소 노아
3rd row(주)상지엔지니어링건축사사무소
4th row주식회사 종합건축사사무소 세온
5th row성호건축사사무소
ValueCountFrequency (%)
건축사사무소 6
 
10.9%
주식회사 5
 
9.1%
주)상지엔지니어링건축사사무소 4
 
7.3%
종합건축사사무소 4
 
7.3%
건축사사무소에이플랜 3
 
5.5%
이에이 1
 
1.8%
경진 1
 
1.8%
금재건축사사무소 1
 
1.8%
남동건축사사무소 1
 
1.8%
가원엔지니어링건축사사무소 1
 
1.8%
Other values (28) 28
50.9%
2023-12-11T01:42:32.161051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 81
17.0%
축 41
 
8.6%
건 41
 
8.6%
소 38
 
8.0%
무 38
 
8.0%
주 19
 
4.0%
17
 
3.6%
( 14
 
2.9%
) 14
 
2.9%
합 13
 
2.7%
Other values (62) 161
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 427
89.5%
Space Separator 17
 
3.6%
Open Punctuation 14
 
2.9%
Close Punctuation 14
 
2.9%
Uppercase Letter 4
 
0.8%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 81
19.0%
축 41
 
9.6%
건 41
 
9.6%
소 38
 
8.9%
무 38
 
8.9%
주 19
 
4.4%
합 13
 
3.0%
종 13
 
3.0%
지 12
 
2.8%
이 8
 
1.9%
Other values (55) 123
28.8%
Uppercase Letter
ValueCountFrequency (%)
N 2
50.0%
A 1
25.0%
J 1
25.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 427
89.5%
Common 46
 
9.6%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 81
19.0%
축 41
 
9.6%
건 41
 
9.6%
소 38
 
8.9%
무 38
 
8.9%
주 19
 
4.4%
합 13
 
3.0%
종 13
 
3.0%
지 12
 
2.8%
이 8
 
1.9%
Other values (55) 123
28.8%
Common
ValueCountFrequency (%)
17
37.0%
( 14
30.4%
) 14
30.4%
. 1
 
2.2%
Latin
ValueCountFrequency (%)
N 2
50.0%
A 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 427
89.5%
ASCII 50
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 81
19.0%
축 41
 
9.6%
건 41
 
9.6%
소 38
 
8.9%
무 38
 
8.9%
주 19
 
4.4%
합 13
 
3.0%
종 13
 
3.0%
지 12
 
2.8%
이 8
 
1.9%
Other values (55) 123
28.8%
ASCII
ValueCountFrequency (%)
17
34.0%
( 14
28.0%
) 14
28.0%
N 2
 
4.0%
A 1
 
2.0%
. 1
 
2.0%
J 1
 
2.0%

시공자사무소명
Text

MISSING 

Distinct32
Distinct (%)88.9%
Missing3
Missing (%)7.7%
Memory size444.0 B
2023-12-11T01:42:32.385117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.4722222
Min length6

Characters and Unicode

Total characters305
Distinct characters72
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

Unique28 ?
Unique (%)77.8%

Sample

1st row진흥종합건설(주)
2nd row일성종합건설 주식회사
3rd row주식회사대성문
4th row용현건설(주)
5th row광덕에이스종합건설(주)
ValueCountFrequency (%)
주)금해종합건설 2
 
5.4%
주)우리종합건설 2
 
5.4%
주식회사대성문 2
 
5.4%
도우건설(주 2
 
5.4%
은우종합건설(주 1
 
2.7%
케이티건설(주 1
 
2.7%
씨엠종합건설 1
 
2.7%
주)해인산업개발 1
 
2.7%
건한종합건설(주 1
 
2.7%
시앤디종합건설(주 1
 
2.7%
Other values (23) 23
62.2%
2023-12-11T01:42:32.765152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 35
 
11.5%
건 32
 
10.5%
( 30
 
9.8%
) 30
 
9.8%
설 28
 
9.2%
종 21
 
6.9%
합 21
 
6.9%
우 5
 
1.6%
식 5
 
1.6%
회 5
 
1.6%
Other values (62) 93
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
80.0%
Open Punctuation 30
 
9.8%
Close Punctuation 30
 
9.8%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 35
14.3%
건 32
 
13.1%
설 28
 
11.5%
종 21
 
8.6%
합 21
 
8.6%
우 5
 
2.0%
식 5
 
2.0%
회 5
 
2.0%
사 5
 
2.0%
성 4
 
1.6%
Other values (59) 83
34.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
80.0%
Common 61
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 35
14.3%
건 32
 
13.1%
설 28
 
11.5%
종 21
 
8.6%
합 21
 
8.6%
우 5
 
2.0%
식 5
 
2.0%
회 5
 
2.0%
사 5
 
2.0%
성 4
 
1.6%
Other values (59) 83
34.0%
Common
ValueCountFrequency (%)
( 30
49.2%
) 30
49.2%
1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
80.0%
ASCII 61
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 35
14.3%
건 32
 
13.1%
설 28
 
11.5%
종 21
 
8.6%
합 21
 
8.6%
우 5
 
2.0%
식 5
 
2.0%
회 5
 
2.0%
사 5
 
2.0%
성 4
 
1.6%
Other values (59) 83
34.0%
ASCII
ValueCountFrequency (%)
( 30
49.2%
) 30
49.2%
1
 
1.6%

Interactions

2023-12-11T01:42:25.811849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.369161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.982031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.580153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.208369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.902237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.479793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.093185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.711090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.336153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:26.006647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.618392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.198649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.837097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.456439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:26.087090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.730244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.309742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.946117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.581236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:26.177435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:23.869279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:24.438893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.080799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:42:25.714449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:42:33.148027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율용적률구조허가일착공처리일주용도부속용도설계사무소명감리사무소명시공자사무소명
건축구분1.0001.0000.0000.4330.0000.000NaN0.3740.0000.0001.0001.0000.5570.0000.0000.7460.796
대지위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지목0.0001.0001.0000.8190.7380.3781.0000.8220.0000.8151.0000.8950.6640.0000.9750.0000.000
대지면적(제곱미터)0.4331.0000.8191.0000.8830.7801.0000.8560.0000.9421.0000.0000.9490.7930.0000.0000.856
건축면적(제곱미터)0.0001.0000.7380.8831.0000.681NaN0.7650.0000.2971.0000.0000.7630.7870.8300.0000.387
연면적(제곱미터)0.0001.0000.3780.7800.6811.000NaN0.3270.7310.6791.0000.0000.0000.8440.0000.0000.000
증축연면적(제곱미터)NaN1.0001.0001.000NaNNaN1.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
건폐율0.3741.0000.8220.8560.7650.3271.0001.0000.0000.5681.0001.0000.7140.8140.4830.0000.926
용적률0.0001.0000.0000.0000.0000.7311.0000.0001.0000.0001.0001.0000.0000.9790.9180.9110.920
구조0.0001.0000.8150.9420.2970.679NaN0.5680.0001.0001.0001.0000.6420.0001.0001.0000.383
허가일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
착공처리일1.0001.0000.8950.0000.0000.0001.0001.0001.0001.0001.0001.0000.0000.9670.9750.9740.974
주용도0.5571.0000.6640.9490.7630.0001.0000.7140.0000.6421.0000.0001.0000.9740.8360.0000.961
부속용도0.0001.0000.0000.7930.7870.8441.0000.8140.9790.0001.0000.9670.9741.0000.9360.8140.888
설계사무소명0.0001.0000.9750.0000.8300.0001.0000.4830.9181.0001.0000.9750.8360.9361.0000.9970.959
감리사무소명0.7461.0000.0000.0000.0000.0001.0000.0000.9111.0001.0000.9740.0000.8140.9971.0000.964
시공자사무소명0.7961.0000.0000.8560.3870.0001.0000.9260.9200.3831.0000.9740.9610.8880.9590.9641.000
2023-12-11T01:42:33.337175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목증축연면적(제곱미터)주용도건축구분구조
지목1.0001.0000.3590.0000.728
증축연면적(제곱미터)1.0001.0001.0001.0001.000
주용도0.3591.0001.0000.2470.309
건축구분0.0001.0000.2471.0000.000
구조0.7281.0000.3090.0001.000
2023-12-11T01:42:33.438576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)건폐율용적률건축구분지목증축연면적(제곱미터)구조주용도
대지면적(제곱미터)1.0000.9360.775-0.362-0.0970.1890.6521.0000.6560.620
건축면적(제곱미터)0.9361.0000.913-0.0790.1620.0000.5751.0000.2220.490
연면적(제곱미터)0.7750.9131.0000.1770.4450.0000.2231.0000.3440.000
건폐율-0.362-0.0790.1771.0000.8090.2030.5751.0000.3620.375
용적률-0.0970.1620.4450.8091.0000.0000.0001.0000.0000.000
건축구분0.1890.0000.0000.2030.0001.0000.0001.0000.0000.247
지목0.6520.5750.2230.5750.0000.0001.0001.0000.7280.359
증축연면적(제곱미터)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
구조0.6560.2220.3440.3620.0000.0000.7281.0001.0000.309
주용도0.6200.4900.0000.3750.0000.2470.3591.0000.3091.000

Missing values

2023-12-11T01:42:26.560557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:42:26.799944image/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.
2023-12-11T01:42:26.958249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율용적률구조허가일착공처리일주용도부속용도설계사무소명감리사무소명시공자사무소명
0신축부산광역시 동구 범일동 1369대350.0258.513021.975<NA>73.86806.66철근콘크리트구조2021-12-292022-05-17업무시설오피스텔(주)아키신화종합건축사사무소(주)아키신화종합건축사사무소진흥종합건설(주)
1신축부산광역시 동구 범일동 830-239대160.0109.05252.3<NA>68.1668.16철근콘크리트구조2022-05-032022-05-10제2종근린생활시설사무소,일반음식점송지 종합건축사사무소<NA><NA>
2신축부산광역시 동구 수정동 1043-163대165.098.115248.49<NA>59.46150.6철근콘크리트구조2022-03-102022-04-06단독주택단독주택, 제1종근린생활시설주식회사 디딤엔지니어링건축사사무소(주)종합건축사사무소 노아일성종합건설 주식회사
3신축부산광역시 동구 범일동 828-9대4146.53166.647556248.5708<NA>76.37997.63철근콘크리트구조2020-12-312022-03-03공동주택업무시설(오피스텔),제2종근린생활시설(주)상지엔지니어링건축사사무소(주)상지엔지니어링건축사사무소주식회사대성문
4신축부산광역시 동구 수정동 342대569.1406.04097.44<NA>71.34675.56철근콘크리트구조2018-09-212022-02-14공동주택아파트(도시형생활주택)/업무시설(오피스텔)주식회사 종합건축사사무소 세온주식회사 종합건축사사무소 세온용현건설(주)
5신축부산광역시 동구 수정동 997-2 외31필지종교용지3178.21318.34344.21<NA>41.48119.07일반철골구조2021-06-012021-11-26종교시설종교집회장성호건축사사무소성호건축사사무소광덕에이스종합건설(주)
6신축부산광역시 동구 초량동 984-3 외6필지대447.0221.87498.19<NA>49.64111.45철근콘크리트구조2021-04-222021-11-08제1종근린생활시설마을공동작업소루가 건축사사무소루가 건축사사무소(주)오현종합건설
7신축부산광역시 동구 초량동 359-1대426.82304.315030.19<NA>71.31132.08철근콘크리트구조2021-05-042021-08-11업무시설오피스텔, 제1종근린생활시설(소매점,의원)종합건축사사무소 삼우종합건축사사무소 삼우병산종합건설(주)
8신축부산광역시 동구 초량동 1159-2대281.3224.612626.67<NA>79.85869.92철근콘크리트구조2021-04-092021-08-02업무시설업무시설(오피스텔)주식회사 종합건축사사무소 세온주식회사 신일종합건축사사무소(주)지앤종합건설
9신축부산광역시 동구 범일동 321-45 외1필지대436.3139.66352.53<NA>32.0180.8철근콘크리트구조2021-02-242021-07-21문화및집회시설전시장(주)타오종합건축사사무소종합건축사사무소그룹영남 주식회사(주)영이건설
건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율용적률구조허가일착공처리일주용도부속용도설계사무소명감리사무소명시공자사무소명
29신축부산광역시 동구 초량동 906-57 외3필지대193.0114.99111.48<NA>59.5857.76철근콘크리트구조2018-01-242018-03-29노유자시설노인여가복지시설(주)서현건축사사무소건축사사무소동문건축(주)(주)국제종합건설
30증축부산광역시 동구 좌천동 498대322.13199.11660.29-30.1861.81144.89철근콘크리트구조2017-08-112017-08-28제1종근린생활시설마을공동작업소남동 건축사사무소남동건축사사무소은우종합건설(주)
31신축부산광역시 동구 초량동 1202 외4필지도로16662.94011.134790.25<NA>24.072225.8936철근콘크리트구조2016-12-232017-06-07문화및집회시설집회장(주)간삼건축종합건축사사무소(주)상지엔지니어링건축사사무소시앤디종합건설(주)
32신축부산광역시 동구 초량동 820-20대380.0189.71742.46<NA>49.9237147.5철근콘크리트구조2016-02-162016-04-28노유자시설노인복지시설건축사사무소서안금재건축사사무소건한종합건설(주)
33신축부산광역시 동구 초량동 970-20 외2필지대665.0235.26601.47<NA>35.3790.45철근콘크리트구조2016-03-022016-04-25제1종근린생활시설지구대우리 종합 건축사사무소종합건축사사무소 경진(주)해인산업개발
34신축부산광역시 동구 수정동 822 외20필지대2818.01538.955719.59<NA>54.6114169.307철근콘크리트구조2015-08-042016-03-07운동시설<NA>(주)부산건축종합건축사사무소(주)상지엔지니어링건축사사무소씨엠종합건설
35신축부산광역시 동구 수정동 487-84대606.0214.76396.88<NA>35.4465.49철근콘크리트구조2015-04-282015-07-02제1종근린생활시설지구대종합건축사사무소 지오이에이 건축사사무소마루종합건설주식회사
36신축부산광역시 동구 초량동 1167학교용지8384.82762.2811714.35<NA>32.9439106.7913철골철근콘크리트구조2014-06-132015-05-18문화및집회시설전시장(주)아이엔지엔지니어링건축사사무소주식회사 정림건축종합건축사사무소(주)우리종합건설
37신축부산광역시 동구 수정동 1164-12대133.561.82113.4<NA>46.3184.94일반철골구조2015-01-222015-01-27제2종근린생활시설종교집회장태림건축사사무소태림 건축사사무소<NA>
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