Overview

Dataset statistics

Number of variables47
Number of observations208
Missing cells2300
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory81.8 KiB
Average record size in memory402.6 B

Variable types

Categorical12
Text6
Numeric21
Unsupported1
DateTime7

Dataset

Description부산광역시부산진구_착공허가신고정보_20221003
Author부산광역시 부산진구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15014694

Alerts

지목 is highly imbalanced (90.2%)Imbalance
구조 is highly imbalanced (52.9%)Imbalance
비상승강기합 is highly imbalanced (72.2%)Imbalance
하수처리시설명 is highly imbalanced (55.7%)Imbalance
용도지구 is highly imbalanced (52.5%)Imbalance
기계식옥외주차장(대) is highly imbalanced (91.7%)Imbalance
인근자주식주차장(대) is highly imbalanced (92.4%)Imbalance
부속건축물수 is highly imbalanced (87.4%)Imbalance
증축연면적(제곱미터) has 169 (81.2%) missing valuesMissing
취소구분 has 208 (100.0%) missing valuesMissing
최종설계변경일 has 167 (80.3%) missing valuesMissing
실제착공일 has 90 (43.3%) missing valuesMissing
사용승인일 has 69 (33.2%) missing valuesMissing
최대지하층수 has 36 (17.3%) missing valuesMissing
승강기합 has 119 (57.2%) missing valuesMissing
하수처리시설용량(제곱미터) has 104 (50.0%) missing valuesMissing
부속용도 has 36 (17.3%) missing valuesMissing
자주식옥내주차장(대) has 142 (68.3%) missing valuesMissing
자주식옥외주차장(대) has 143 (68.8%) missing valuesMissing
기계식옥내주차장(대) has 182 (87.5%) missing valuesMissing
총주차대수 has 80 (38.5%) missing valuesMissing
총주차장면적(제곱미터) has 80 (38.5%) missing valuesMissing
세대수 has 192 (92.3%) missing valuesMissing
호수 has 161 (77.4%) missing valuesMissing
가구수 has 175 (84.1%) missing valuesMissing
주건축물수 has 5 (2.4%) missing valuesMissing
감리사무소명 has 46 (22.1%) missing valuesMissing
시공자사무소명 has 96 (46.2%) missing valuesMissing
허가번호 has unique valuesUnique
취소구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
최대지하층수 has 103 (49.5%) zerosZeros
동수 has 5 (2.4%) zerosZeros
승강기합 has 18 (8.7%) zerosZeros
총주차장면적(제곱미터) has 19 (9.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:12:49.576025
Analysis finished2023-12-10 16:12:51.108166
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
신축
138 
증축
39 
대수선
27 
용도변경
 
2
개축
 
2

Length

Max length4
Median length2
Mean length2.1490385
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 138
66.3%
증축 39
 
18.8%
대수선 27
 
13.0%
용도변경 2
 
1.0%
개축 2
 
1.0%

Length

2023-12-11T01:12:51.217156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:51.500106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 138
66.3%
증축 39
 
18.8%
대수선 27
 
13.0%
용도변경 2
 
1.0%
개축 2
 
1.0%

허가번호
Text

UNIQUE 

Distinct208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:12:51.929910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length15.903846
Min length15

Characters and Unicode

Total characters3308
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)100.0%

Sample

1st row2022-건축과-신축허가-38
2nd row2022-건축과-신축허가-37
3rd row2022-건축과-증축허가-8
4th row2022-건축과-대수선허가-9
5th row2022-건축과-신축허가-35
ValueCountFrequency (%)
2022-건축과-신축허가-38 1
 
0.5%
2022-건축과-신축허가-37 1
 
0.5%
2021-건축과-신축허가-14 1
 
0.5%
2021-건축과-증축허가-5 1
 
0.5%
2021-건축과-증축허가-6 1
 
0.5%
2021-건축과-신축허가-23 1
 
0.5%
2021-건축과-신축허가-22 1
 
0.5%
2021-건축과-신축허가-21 1
 
0.5%
2021-건축과-신축허가-19 1
 
0.5%
2021-건축과-대수선허가-3 1
 
0.5%
Other values (198) 198
95.2%
2023-12-11T01:12:52.740191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 624
18.9%
2 514
15.5%
387
11.7%
1 246
 
7.4%
0 224
 
6.8%
219
 
6.6%
208
 
6.3%
174
 
5.3%
153
 
4.6%
153
 
4.6%
Other values (20) 406
12.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1498
45.3%
Decimal Number 1186
35.9%
Dash Punctuation 624
18.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
387
25.8%
219
14.6%
208
13.9%
174
11.6%
153
 
10.2%
153
 
10.2%
44
 
2.9%
38
 
2.5%
27
 
1.8%
27
 
1.8%
Other values (9) 68
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 514
43.3%
1 246
20.7%
0 224
18.9%
3 36
 
3.0%
5 32
 
2.7%
4 31
 
2.6%
6 27
 
2.3%
9 26
 
2.2%
8 26
 
2.2%
7 24
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 624
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1810
54.7%
Hangul 1498
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
387
25.8%
219
14.6%
208
13.9%
174
11.6%
153
 
10.2%
153
 
10.2%
44
 
2.9%
38
 
2.5%
27
 
1.8%
27
 
1.8%
Other values (9) 68
 
4.5%
Common
ValueCountFrequency (%)
- 624
34.5%
2 514
28.4%
1 246
 
13.6%
0 224
 
12.4%
3 36
 
2.0%
5 32
 
1.8%
4 31
 
1.7%
6 27
 
1.5%
9 26
 
1.4%
8 26
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1810
54.7%
Hangul 1498
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 624
34.5%
2 514
28.4%
1 246
 
13.6%
0 224
 
12.4%
3 36
 
2.0%
5 32
 
1.8%
4 31
 
1.7%
6 27
 
1.5%
9 26
 
1.4%
8 26
 
1.4%
Hangul
ValueCountFrequency (%)
387
25.8%
219
14.6%
208
13.9%
174
11.6%
153
 
10.2%
153
 
10.2%
44
 
2.9%
38
 
2.5%
27
 
1.8%
27
 
1.8%
Other values (9) 68
 
4.5%
Distinct203
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:12:53.292657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.951923
Min length18

Characters and Unicode

Total characters4566
Distinct characters39
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

Unique198 ?
Unique (%)95.2%

Sample

1st row부산광역시 부산진구 가야동 646-2
2nd row부산광역시 부산진구 전포동 204-25
3rd row부산광역시 부산진구 전포동 164-42
4th row부산광역시 부산진구 양정동 273-1
5th row부산광역시 부산진구 당감동 663-10 외1필지
ValueCountFrequency (%)
부산광역시 208
23.4%
부산진구 208
23.4%
전포동 52
 
5.8%
부전동 37
 
4.2%
외1필지 35
 
3.9%
당감동 24
 
2.7%
개금동 20
 
2.2%
초읍동 17
 
1.9%
가야동 17
 
1.9%
양정동 16
 
1.8%
Other values (213) 256
28.8%
2023-12-11T01:12:53.973887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
682
14.9%
463
 
10.1%
416
 
9.1%
208
 
4.6%
208
 
4.6%
208
 
4.6%
208
 
4.6%
208
 
4.6%
208
 
4.6%
- 203
 
4.4%
Other values (29) 1554
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2670
58.5%
Decimal Number 1011
 
22.1%
Space Separator 682
 
14.9%
Dash Punctuation 203
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
463
17.3%
416
15.6%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
89
 
3.3%
63
 
2.4%
Other values (17) 391
14.6%
Decimal Number
ValueCountFrequency (%)
1 177
17.5%
3 133
13.2%
2 116
11.5%
5 109
10.8%
6 108
10.7%
4 96
9.5%
8 78
7.7%
7 75
7.4%
0 64
 
6.3%
9 55
 
5.4%
Space Separator
ValueCountFrequency (%)
682
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2670
58.5%
Common 1896
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
463
17.3%
416
15.6%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
89
 
3.3%
63
 
2.4%
Other values (17) 391
14.6%
Common
ValueCountFrequency (%)
682
36.0%
- 203
 
10.7%
1 177
 
9.3%
3 133
 
7.0%
2 116
 
6.1%
5 109
 
5.7%
6 108
 
5.7%
4 96
 
5.1%
8 78
 
4.1%
7 75
 
4.0%
Other values (2) 119
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2670
58.5%
ASCII 1896
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
682
36.0%
- 203
 
10.7%
1 177
 
9.3%
3 133
 
7.0%
2 116
 
6.1%
5 109
 
5.7%
6 108
 
5.7%
4 96
 
5.1%
8 78
 
4.1%
7 75
 
4.0%
Other values (2) 119
 
6.3%
Hangul
ValueCountFrequency (%)
463
17.3%
416
15.6%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
208
7.8%
89
 
3.3%
63
 
2.4%
Other values (17) 391
14.6%

지목
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
202 
창고용지
 
2
주차장
 
1
공장용지
 
1
 
1

Length

Max length4
Median length1
Mean length1.0625
Min length1

Unique

Unique4 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
202
97.1%
창고용지 2
 
1.0%
주차장 1
 
0.5%
공장용지 1
 
0.5%
1
 
0.5%
잡종지 1
 
0.5%

Length

2023-12-11T01:12:54.183629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:54.345761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202
97.1%
창고용지 2
 
1.0%
주차장 1
 
0.5%
공장용지 1
 
0.5%
1
 
0.5%
잡종지 1
 
0.5%
Distinct192
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3243.5288
Minimum20
Maximum462258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:54.526298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile54.7
Q1130.425
median226.25
Q3441.975
95-th percentile3008.2
Maximum462258
Range462238
Interquartile range (IQR)311.55

Descriptive statistics

Standard deviation32218.401
Coefficient of variation (CV)9.9331326
Kurtosis201.84997
Mean3243.5288
Median Absolute Deviation (MAD)114.55
Skewness14.115262
Sum674653.98
Variance1.0380254 × 109
MonotonicityNot monotonic
2023-12-11T01:12:54.728109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
228.1 3
 
1.4%
60.8 2
 
1.0%
149.0 2
 
1.0%
308.0 2
 
1.0%
111.0 2
 
1.0%
82.0 2
 
1.0%
257.5 2
 
1.0%
113.0 2
 
1.0%
229.2 2
 
1.0%
146.0 2
 
1.0%
Other values (182) 187
89.9%
ValueCountFrequency (%)
20.0 1
0.5%
27.0 1
0.5%
27.37 1
0.5%
28.2 1
0.5%
31.23 1
0.5%
38.4 1
0.5%
39.3 1
0.5%
44.6 1
0.5%
51.1 1
0.5%
52.9 1
0.5%
ValueCountFrequency (%)
462258.0 1
0.5%
35272.6 2
1.0%
16546.6 1
0.5%
15679.0 1
0.5%
12597.0 1
0.5%
7779.2 1
0.5%
6348.5 1
0.5%
4633.0 1
0.5%
3627.2 1
0.5%
3060.0 1
0.5%
Distinct203
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean860.40704
Minimum1.95
Maximum46431.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:54.910575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.95
5-th percentile27.3065
Q171.585
median132.035
Q3262.4425
95-th percentile1639.2455
Maximum46431.92
Range46429.97
Interquartile range (IQR)190.8575

Descriptive statistics

Standard deviation4186.6894
Coefficient of variation (CV)4.8659405
Kurtosis79.74022
Mean860.40704
Median Absolute Deviation (MAD)69.26
Skewness8.4837251
Sum178964.66
Variance17528368
MonotonicityNot monotonic
2023-12-11T01:12:55.135513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
159.32 2
 
1.0%
132.61 2
 
1.0%
153.84 2
 
1.0%
87.2 2
 
1.0%
25904.12 2
 
1.0%
68.64 1
 
0.5%
52.26 1
 
0.5%
78.27 1
 
0.5%
176.31 1
 
0.5%
305.04 1
 
0.5%
Other values (193) 193
92.8%
ValueCountFrequency (%)
1.95 1
0.5%
7.45 1
0.5%
13.61 1
0.5%
14.94 1
0.5%
15.82 1
0.5%
20.8 1
0.5%
21.36 1
0.5%
26.88 1
0.5%
26.91 1
0.5%
27.0 1
0.5%
ValueCountFrequency (%)
46431.92 1
0.5%
25904.12 2
1.0%
10911.47 1
0.5%
8994.81 1
0.5%
4428.77 1
0.5%
3807.19 1
0.5%
3426.06 1
0.5%
2772.46 1
0.5%
1922.4 1
0.5%
1725.02 1
0.5%

연면적(제곱미터)
Real number (ℝ)

Distinct205
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8898.1034
Minimum1.95
Maximum379412.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:55.334793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.95
5-th percentile47.6315
Q1176.07
median362.195
Q31032.6775
95-th percentile35722.593
Maximum379412.61
Range379410.66
Interquartile range (IQR)856.6075

Descriptive statistics

Standard deviation43059.06
Coefficient of variation (CV)4.8391279
Kurtosis58.483155
Mean8898.1034
Median Absolute Deviation (MAD)266.3
Skewness7.4302414
Sum1850805.5
Variance1.8540827 × 109
MonotonicityNot monotonic
2023-12-11T01:12:55.554895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133.86 2
 
1.0%
199.39 2
 
1.0%
465.04 2
 
1.0%
33716.81 1
 
0.5%
37898.81 1
 
0.5%
199.83 1
 
0.5%
104.52 1
 
0.5%
172.2 1
 
0.5%
726.63 1
 
0.5%
519.76 1
 
0.5%
Other values (195) 195
93.8%
ValueCountFrequency (%)
1.95 1
0.5%
7.45 1
0.5%
13.61 1
0.5%
26.91 1
0.5%
27.0 1
0.5%
27.1 1
0.5%
29.88 1
0.5%
33.76 1
0.5%
42.72 1
0.5%
45.0 1
0.5%
ValueCountFrequency (%)
379412.61 1
0.5%
379246.91 1
0.5%
270442.86 1
0.5%
117415.01 1
0.5%
84170.96 1
0.5%
65473.2 1
0.5%
61851.44 1
0.5%
39487.77 1
0.5%
37898.81 1
0.5%
37707.42 1
0.5%

증축연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)100.0%
Missing169
Missing (%)81.2%
Infinite0
Infinite (%)0.0%
Mean282.38077
Minimum-247.27
Maximum2434.33
Zeros1
Zeros (%)0.5%
Negative1
Negative (%)0.5%
Memory size2.0 KiB
2023-12-11T01:12:55.757135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-247.27
5-th percentile5.301
Q129.675
median60.04
Q3102.72
95-th percentile1640.131
Maximum2434.33
Range2681.6
Interquartile range (IQR)73.045

Descriptive statistics

Standard deviation598.44809
Coefficient of variation (CV)2.1192948
Kurtosis5.2973405
Mean282.38077
Median Absolute Deviation (MAD)33.33
Skewness2.4858296
Sum11012.85
Variance358140.11
MonotonicityNot monotonic
2023-12-11T01:12:55.967878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1328.74 1
 
0.5%
82.04 1
 
0.5%
15.64 1
 
0.5%
60.04 1
 
0.5%
5.89 1
 
0.5%
42.76 1
 
0.5%
0.0 1
 
0.5%
53.44 1
 
0.5%
78.23 1
 
0.5%
20.52 1
 
0.5%
Other values (29) 29
 
13.9%
(Missing) 169
81.2%
ValueCountFrequency (%)
-247.27 1
0.5%
0.0 1
0.5%
5.89 1
0.5%
15.64 1
0.5%
16.38 1
0.5%
16.63 1
0.5%
18.6 1
0.5%
20.52 1
0.5%
21.89 1
0.5%
26.71 1
0.5%
ValueCountFrequency (%)
2434.33 1
0.5%
1942.0 1
0.5%
1606.59 1
0.5%
1486.34 1
0.5%
1328.74 1
0.5%
346.11 1
0.5%
330.21 1
0.5%
240.61 1
0.5%
183.37 1
0.5%
123.4 1
0.5%

건폐율(백분율)
Real number (ℝ)

Distinct198
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.507328
Minimum0.68
Maximum92.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:56.127966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.68
5-th percentile37.081
Q149.7575
median59.485
Q371.66
95-th percentile79.8165
Maximum92.6
Range91.92
Interquartile range (IQR)21.9025

Descriptive statistics

Standard deviation14.982927
Coefficient of variation (CV)0.25178289
Kurtosis1.0857143
Mean59.507328
Median Absolute Deviation (MAD)9.93
Skewness-0.50594423
Sum12377.524
Variance224.4881
MonotonicityNot monotonic
2023-12-11T01:12:56.286824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.93 2
 
1.0%
59.74 2
 
1.0%
49.81 2
 
1.0%
59.41 2
 
1.0%
69.85 2
 
1.0%
59.24 2
 
1.0%
73.44 2
 
1.0%
59.47 2
 
1.0%
79.87 2
 
1.0%
43.06 2
 
1.0%
Other values (188) 188
90.4%
ValueCountFrequency (%)
0.68 1
0.5%
10.04 1
0.5%
17.55 1
0.5%
19.79 1
0.5%
19.83 1
0.5%
27.1974 1
0.5%
28.02 1
0.5%
29.03 1
0.5%
33.77 1
0.5%
36.2342 1
0.5%
ValueCountFrequency (%)
92.6 1
0.5%
89.76 1
0.5%
89.65 1
0.5%
88.73 1
0.5%
88.43 1
0.5%
80.45 1
0.5%
79.98 1
0.5%
79.95 1
0.5%
79.87 2
1.0%
79.82 1
0.5%

용적률(백분율)
Real number (ℝ)

Distinct207
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean274.83888
Minimum0.68
Maximum1246.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:56.448618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.68
5-th percentile40.560095
Q1114.215
median182.21
Q3296.93
95-th percentile977.66272
Maximum1246.67
Range1245.99
Interquartile range (IQR)182.715

Descriptive statistics

Standard deviation285.53258
Coefficient of variation (CV)1.038909
Kurtosis2.9223132
Mean274.83888
Median Absolute Deviation (MAD)74.315
Skewness1.9425735
Sum57166.487
Variance81528.853
MonotonicityNot monotonic
2023-12-11T01:12:56.623563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203.88 2
 
1.0%
135.73 1
 
0.5%
1199.45 1
 
0.5%
922.47 1
 
0.5%
221.05 1
 
0.5%
98.6 1
 
0.5%
114.3 1
 
0.5%
191.7228 1
 
0.5%
102.11 1
 
0.5%
226.16 1
 
0.5%
Other values (197) 197
94.7%
ValueCountFrequency (%)
0.68 1
0.5%
24.12 1
0.5%
29.03 1
0.5%
30.4144 1
0.5%
33.77 1
0.5%
34.46 1
0.5%
36.79 1
0.5%
37.25 1
0.5%
38.5725 1
0.5%
38.74 1
0.5%
ValueCountFrequency (%)
1246.67 1
0.5%
1213.71 1
0.5%
1199.45 1
0.5%
1198.81 1
0.5%
1189.7 1
0.5%
1142.72 1
0.5%
1112.2 1
0.5%
1099.99 1
0.5%
1063.0 1
0.5%
1038.85 1
0.5%

구조
Categorical

IMBALANCE 

Distinct10
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
철근콘크리트구조
145 
일반철골구조
31 
경량철골구조
 
13
철골철근콘크리트구조
 
7
블록구조
 
3
Other values (5)
 
9

Length

Max length10
Median length8
Mean length7.4903846
Min length4

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 145
69.7%
일반철골구조 31
 
14.9%
경량철골구조 13
 
6.2%
철골철근콘크리트구조 7
 
3.4%
블록구조 3
 
1.4%
벽돌구조 3
 
1.4%
철골콘크리트구조 2
 
1.0%
강파이프구조 2
 
1.0%
<NA> 1
 
0.5%
기타콘크리트구조 1
 
0.5%

Length

2023-12-11T01:12:56.774792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:56.974988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 145
69.7%
일반철골구조 31
 
14.9%
경량철골구조 13
 
6.2%
철골철근콘크리트구조 7
 
3.4%
블록구조 3
 
1.4%
벽돌구조 3
 
1.4%
철골콘크리트구조 2
 
1.0%
강파이프구조 2
 
1.0%
na 1
 
0.5%
기타콘크리트구조 1
 
0.5%

취소구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing208
Missing (%)100.0%
Memory size2.0 KiB
Distinct147
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-04 00:00:00
Maximum2022-05-25 00:00:00
2023-12-11T01:12:57.136813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:57.297152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종설계변경일
Date

MISSING 

Distinct40
Distinct (%)97.6%
Missing167
Missing (%)80.3%
Memory size1.8 KiB
Minimum2021-03-20 00:00:00
Maximum2022-07-07 00:00:00
2023-12-11T01:12:57.419242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:57.555638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
Distinct150
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2021-01-12 00:00:00
Maximum2022-07-06 00:00:00
2023-12-11T01:12:57.685857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:58.070723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct156
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2020-06-11 00:00:00
Maximum2022-07-05 00:00:00
2023-12-11T01:12:58.202802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:58.355808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실제착공일
Date

MISSING 

Distinct92
Distinct (%)78.0%
Missing90
Missing (%)43.3%
Memory size1.8 KiB
Minimum2021-01-10 00:00:00
Maximum2022-05-04 00:00:00
2023-12-11T01:12:58.490599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:58.620048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct105
Distinct (%)75.5%
Missing69
Missing (%)33.2%
Memory size1.8 KiB
Minimum2021-02-25 00:00:00
Maximum2022-07-06 00:00:00
2023-12-11T01:12:58.764113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:58.884399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct163
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2020-11-05 00:00:00
Maximum2022-05-11 00:00:00
2023-12-11T01:12:59.009150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:59.143692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

Distinct23
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8846154
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:59.297595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile20
Maximum42
Range41
Interquartile range (IQR)3

Descriptive statistics

Standard deviation7.0735374
Coefficient of variation (CV)1.202039
Kurtosis8.4689556
Mean5.8846154
Median Absolute Deviation (MAD)2
Skewness2.7777782
Sum1224
Variance50.034931
MonotonicityNot monotonic
2023-12-11T01:12:59.433734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2 42
20.2%
4 40
19.2%
5 29
13.9%
3 29
13.9%
1 24
11.5%
20 8
 
3.8%
6 6
 
2.9%
10 4
 
1.9%
7 4
 
1.9%
9 3
 
1.4%
Other values (13) 19
9.1%
ValueCountFrequency (%)
1 24
11.5%
2 42
20.2%
3 29
13.9%
4 40
19.2%
5 29
13.9%
6 6
 
2.9%
7 4
 
1.9%
8 1
 
0.5%
9 3
 
1.4%
10 4
 
1.9%
ValueCountFrequency (%)
42 2
 
1.0%
36 1
 
0.5%
30 1
 
0.5%
29 1
 
0.5%
26 1
 
0.5%
25 1
 
0.5%
23 1
 
0.5%
22 1
 
0.5%
20 8
3.8%
19 3
 
1.4%

최대지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)4.7%
Missing36
Missing (%)17.3%
Infinite0
Infinite (%)0.0%
Mean0.73837209
Minimum0
Maximum7
Zeros103
Zeros (%)49.5%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:59.538134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4.45
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3490884
Coefficient of variation (CV)1.8271118
Kurtosis7.420986
Mean0.73837209
Median Absolute Deviation (MAD)0
Skewness2.6852614
Sum127
Variance1.8200394
MonotonicityNot monotonic
2023-12-11T01:12:59.639672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 103
49.5%
1 48
23.1%
2 8
 
3.8%
5 5
 
2.4%
6 3
 
1.4%
3 3
 
1.4%
4 1
 
0.5%
7 1
 
0.5%
(Missing) 36
 
17.3%
ValueCountFrequency (%)
0 103
49.5%
1 48
23.1%
2 8
 
3.8%
3 3
 
1.4%
4 1
 
0.5%
5 5
 
2.4%
6 3
 
1.4%
7 1
 
0.5%
ValueCountFrequency (%)
7 1
 
0.5%
6 3
 
1.4%
5 5
 
2.4%
4 1
 
0.5%
3 3
 
1.4%
2 8
 
3.8%
1 48
23.1%
0 103
49.5%

최고높이(미터)
Real number (ℝ)

Distinct164
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.252937
Minimum2.2
Maximum171.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:12:59.788438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile4.57
Q18.675
median12.95
Q319.05
95-th percentile73.2025
Maximum171.66
Range169.46
Interquartile range (IQR)10.375

Descriptive statistics

Standard deviation25.109613
Coefficient of variation (CV)1.1814655
Kurtosis13.1317
Mean21.252937
Median Absolute Deviation (MAD)4.55
Skewness3.2425084
Sum4420.611
Variance630.49268
MonotonicityNot monotonic
2023-12-11T01:12:59.961864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.0 5
 
2.4%
8.4 4
 
1.9%
11.8 4
 
1.9%
9.3 3
 
1.4%
6.2 3
 
1.4%
7.3 3
 
1.4%
8.1 3
 
1.4%
14.6 3
 
1.4%
5.0 2
 
1.0%
12.9 2
 
1.0%
Other values (154) 176
84.6%
ValueCountFrequency (%)
2.2 1
0.5%
2.7 1
0.5%
2.8 1
0.5%
3.6 1
0.5%
3.8 2
1.0%
4.0 2
1.0%
4.24 1
0.5%
4.3 1
0.5%
4.5 1
0.5%
4.7 1
0.5%
ValueCountFrequency (%)
171.66 2
1.0%
111.2 1
0.5%
105.85 1
0.5%
90.5 1
0.5%
89.8 1
0.5%
87.1 1
0.5%
86.75 1
0.5%
79.9 1
0.5%
79.1 1
0.5%
73.85 1
0.5%

동수
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9567308
Minimum0
Maximum1580
Zeros5
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:00.117334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum1580
Range1580
Interquartile range (IQR)0

Descriptive statistics

Standard deviation109.51925
Coefficient of variation (CV)12.227592
Kurtosis207.53218
Mean8.9567308
Median Absolute Deviation (MAD)0
Skewness14.398469
Sum1863
Variance11994.467
MonotonicityNot monotonic
2023-12-11T01:13:00.268407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 190
91.3%
2 7
 
3.4%
0 5
 
2.4%
8 1
 
0.5%
1580 1
 
0.5%
52 1
 
0.5%
11 1
 
0.5%
3 1
 
0.5%
5 1
 
0.5%
ValueCountFrequency (%)
0 5
 
2.4%
1 190
91.3%
2 7
 
3.4%
3 1
 
0.5%
5 1
 
0.5%
8 1
 
0.5%
11 1
 
0.5%
52 1
 
0.5%
1580 1
 
0.5%
ValueCountFrequency (%)
1580 1
 
0.5%
52 1
 
0.5%
11 1
 
0.5%
8 1
 
0.5%
5 1
 
0.5%
3 1
 
0.5%
2 7
 
3.4%
1 190
91.3%
0 5
 
2.4%

승강기합
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)10.1%
Missing119
Missing (%)57.2%
Infinite0
Infinite (%)0.0%
Mean3.5168539
Minimum0
Maximum91
Zeros18
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:00.426378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile7.2
Maximum91
Range91
Interquartile range (IQR)1

Descriptive statistics

Standard deviation13.485777
Coefficient of variation (CV)3.834614
Kurtosis39.989358
Mean3.5168539
Median Absolute Deviation (MAD)0
Skewness6.3459406
Sum313
Variance181.86619
MonotonicityNot monotonic
2023-12-11T01:13:00.550136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 46
 
22.1%
0 18
 
8.7%
2 11
 
5.3%
3 5
 
2.4%
4 3
 
1.4%
8 2
 
1.0%
91 2
 
1.0%
14 1
 
0.5%
6 1
 
0.5%
(Missing) 119
57.2%
ValueCountFrequency (%)
0 18
 
8.7%
1 46
22.1%
2 11
 
5.3%
3 5
 
2.4%
4 3
 
1.4%
6 1
 
0.5%
8 2
 
1.0%
14 1
 
0.5%
91 2
 
1.0%
ValueCountFrequency (%)
91 2
 
1.0%
14 1
 
0.5%
8 2
 
1.0%
6 1
 
0.5%
4 3
 
1.4%
3 5
 
2.4%
2 11
 
5.3%
1 46
22.1%
0 18
 
8.7%

비상승강기합
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
186 
1
 
14
3
 
4
2
 
2
10
 
2

Length

Max length4
Median length4
Mean length3.6923077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row3
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 186
89.4%
1 14
 
6.7%
3 4
 
1.9%
2 2
 
1.0%
10 2
 
1.0%

Length

2023-12-11T01:13:00.669736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:00.809904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 186
89.4%
1 14
 
6.7%
3 4
 
1.9%
2 2
 
1.0%
10 2
 
1.0%

하수처리시설명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
하수종말처리장연결
163 
부패탱크방법
28 
<NA>
 
14
접촉산화방법
 
2
접촉폭기방법
 
1

Length

Max length9
Median length9
Mean length8.2163462
Min length4

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
하수종말처리장연결 163
78.4%
부패탱크방법 28
 
13.5%
<NA> 14
 
6.7%
접촉산화방법 2
 
1.0%
접촉폭기방법 1
 
0.5%

Length

2023-12-11T01:13:00.917654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:01.015275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하수종말처리장연결 163
78.4%
부패탱크방법 28
 
13.5%
na 14
 
6.7%
접촉산화방법 2
 
1.0%
접촉폭기방법 1
 
0.5%

하수처리시설용량(제곱미터)
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)97.1%
Missing104
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean21.279237
Minimum0.1
Maximum302.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:01.165037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile1.115
Q13.32975
median6.92
Q313.0025
95-th percentile87.2655
Maximum302.66
Range302.56
Interquartile range (IQR)9.67275

Descriptive statistics

Standard deviation48.081216
Coefficient of variation (CV)2.2595367
Kurtosis18.31501
Mean21.279237
Median Absolute Deviation (MAD)3.9245
Skewness4.1670811
Sum2213.0406
Variance2311.8033
MonotonicityNot monotonic
2023-12-11T01:13:01.299161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.96 2
 
1.0%
6.92 2
 
1.0%
8.49 2
 
1.0%
3.23 1
 
0.5%
7.84 1
 
0.5%
25.46 1
 
0.5%
227.69 1
 
0.5%
6.61 1
 
0.5%
20.0 1
 
0.5%
1.99 1
 
0.5%
Other values (91) 91
43.8%
(Missing) 104
50.0%
ValueCountFrequency (%)
0.1 1
0.5%
0.8856 1
0.5%
0.9 1
0.5%
1.0 1
0.5%
1.02 1
0.5%
1.1 1
0.5%
1.2 1
0.5%
1.373 1
0.5%
1.399 1
0.5%
1.48 1
0.5%
ValueCountFrequency (%)
302.66 1
0.5%
238.034 1
0.5%
227.69 1
0.5%
181.725 1
0.5%
126.47 1
0.5%
90.99 1
0.5%
66.16 1
0.5%
60.928 1
0.5%
57.18 1
0.5%
53.38 1
0.5%

주용도
Categorical

Distinct13
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
제2종근린생활시설
77 
제1종근린생활시설
42 
단독주택
21 
업무시설
19 
공동주택
15 
Other values (8)
34 

Length

Max length9
Median length9
Mean length6.9326923
Min length4

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row단독주택
2nd row제2종근린생활시설
3rd row제1종근린생활시설
4th row공동주택
5th row공동주택

Common Values

ValueCountFrequency (%)
제2종근린생활시설 77
37.0%
제1종근린생활시설 42
20.2%
단독주택 21
 
10.1%
업무시설 19
 
9.1%
공동주택 15
 
7.2%
창고시설 15
 
7.2%
숙박시설 5
 
2.4%
의료시설 4
 
1.9%
교육연구시설 3
 
1.4%
자동차관련시설 3
 
1.4%
Other values (3) 4
 
1.9%

Length

2023-12-11T01:13:01.453948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 77
37.0%
제1종근린생활시설 42
20.2%
단독주택 21
 
10.1%
업무시설 19
 
9.1%
공동주택 15
 
7.2%
창고시설 15
 
7.2%
숙박시설 5
 
2.4%
의료시설 4
 
1.9%
교육연구시설 3
 
1.4%
자동차관련시설 3
 
1.4%
Other values (3) 4
 
1.9%

부속용도
Text

MISSING 

Distinct101
Distinct (%)58.7%
Missing36
Missing (%)17.3%
Memory size1.8 KiB
2023-12-11T01:13:01.708504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length37
Mean length10.77907
Min length2

Characters and Unicode

Total characters1854
Distinct characters121
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)48.3%

Sample

1st row사무소
2nd row(소매점, 휴게음식점), 제2종근린생활시설(사무소)
3rd row공동주택(아파트)
4th row공동주택(도시형생활주택)
5th row교육연구시설,업무시설
ValueCountFrequency (%)
사무소 26
 
10.4%
일반음식점 20
 
8.0%
오피스텔 14
 
5.6%
13
 
5.2%
휴게음식점 11
 
4.4%
단독주택 9
 
3.6%
소매점 9
 
3.6%
7
 
2.8%
창고시설(창고 6
 
2.4%
제1종근린생활시설(휴게음식점 6
 
2.4%
Other values (85) 129
51.6%
2023-12-11T01:13:02.178675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
5.2%
89
 
4.8%
, 80
 
4.3%
78
 
4.2%
76
 
4.1%
( 71
 
3.8%
70
 
3.8%
) 70
 
3.8%
66
 
3.6%
60
 
3.2%
Other values (111) 1098
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1484
80.0%
Other Punctuation 93
 
5.0%
Space Separator 78
 
4.2%
Open Punctuation 73
 
3.9%
Close Punctuation 72
 
3.9%
Decimal Number 49
 
2.6%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
96
 
6.5%
89
 
6.0%
76
 
5.1%
70
 
4.7%
66
 
4.4%
60
 
4.0%
59
 
4.0%
58
 
3.9%
57
 
3.8%
55
 
3.7%
Other values (98) 798
53.8%
Other Punctuation
ValueCountFrequency (%)
, 80
86.0%
/ 12
 
12.9%
. 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 71
97.3%
{ 1
 
1.4%
[ 1
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 70
97.2%
} 1
 
1.4%
] 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 29
59.2%
1 20
40.8%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1484
80.0%
Common 370
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
96
 
6.5%
89
 
6.0%
76
 
5.1%
70
 
4.7%
66
 
4.4%
60
 
4.0%
59
 
4.0%
58
 
3.9%
57
 
3.8%
55
 
3.7%
Other values (98) 798
53.8%
Common
ValueCountFrequency (%)
, 80
21.6%
78
21.1%
( 71
19.2%
) 70
18.9%
2 29
 
7.8%
1 20
 
5.4%
/ 12
 
3.2%
- 5
 
1.4%
} 1
 
0.3%
. 1
 
0.3%
Other values (3) 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1484
80.0%
ASCII 370
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
96
 
6.5%
89
 
6.0%
76
 
5.1%
70
 
4.7%
66
 
4.4%
60
 
4.0%
59
 
4.0%
58
 
3.9%
57
 
3.8%
55
 
3.7%
Other values (98) 798
53.8%
ASCII
ValueCountFrequency (%)
, 80
21.6%
78
21.1%
( 71
19.2%
) 70
18.9%
2 29
 
7.8%
1 20
 
5.4%
/ 12
 
3.2%
- 5
 
1.4%
} 1
 
0.3%
. 1
 
0.3%
Other values (3) 3
 
0.8%

용도지역
Categorical

Distinct9
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
일반상업지역
59 
가로구역별최고높이제한지역
49 
제2종일반주거지역
44 
제3종일반주거지역
32 
준주거지역
15 
Other values (4)

Length

Max length13
Median length9
Mean length8.6057692
Min length4

Unique

Unique3 ?
Unique (%)1.4%

Sample

1st row가로구역별최고높이제한지역
2nd row가로구역별최고높이제한지역
3rd row일반상업지역
4th row일반상업지역
5th row제2종일반주거지역

Common Values

ValueCountFrequency (%)
일반상업지역 59
28.4%
가로구역별최고높이제한지역 49
23.6%
제2종일반주거지역 44
21.2%
제3종일반주거지역 32
15.4%
준주거지역 15
 
7.2%
<NA> 6
 
2.9%
근린상업지역 1
 
0.5%
상업지역 1
 
0.5%
자연녹지지역 1
 
0.5%

Length

2023-12-11T01:13:02.347203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:02.484493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반상업지역 59
28.4%
가로구역별최고높이제한지역 49
23.6%
제2종일반주거지역 44
21.2%
제3종일반주거지역 32
15.4%
준주거지역 15
 
7.2%
na 6
 
2.9%
근린상업지역 1
 
0.5%
상업지역 1
 
0.5%
자연녹지지역 1
 
0.5%

용도지구
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
110 
방화지구
91 
주거환경개선지구
 
4
철도보호지구
 
1
미관지구
 
1

Length

Max length9
Median length4
Mean length4.1105769
Min length4

Unique

Unique3 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 110
52.9%
방화지구 91
43.8%
주거환경개선지구 4
 
1.9%
철도보호지구 1
 
0.5%
미관지구 1
 
0.5%
지적재조사사업지구 1
 
0.5%

Length

2023-12-11T01:13:02.630318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:02.742730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 110
52.9%
방화지구 91
43.8%
주거환경개선지구 4
 
1.9%
철도보호지구 1
 
0.5%
미관지구 1
 
0.5%
지적재조사사업지구 1
 
0.5%

용도구역
Categorical

Distinct7
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
상대보호구역
100 
<NA>
92 
중점경관관리구역
 
7
제1종지구단위계획구역
 
5
지구단위계획구역
 
2
Other values (2)
 
2

Length

Max length11
Median length8
Mean length5.3173077
Min length4

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
상대보호구역 100
48.1%
<NA> 92
44.2%
중점경관관리구역 7
 
3.4%
제1종지구단위계획구역 5
 
2.4%
지구단위계획구역 2
 
1.0%
절대정화구역 1
 
0.5%
재개발구역 1
 
0.5%

Length

2023-12-11T01:13:02.866332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:02.981378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상대보호구역 100
48.1%
na 92
44.2%
중점경관관리구역 7
 
3.4%
제1종지구단위계획구역 5
 
2.4%
지구단위계획구역 2
 
1.0%
절대정화구역 1
 
0.5%
재개발구역 1
 
0.5%

자주식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)45.5%
Missing142
Missing (%)68.3%
Infinite0
Infinite (%)0.0%
Mean126.90909
Minimum1
Maximum2122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:03.164419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q323
95-th percentile745.75
Maximum2122
Range2121
Interquartile range (IQR)21

Descriptive statistics

Standard deviation402.02391
Coefficient of variation (CV)3.1678102
Kurtosis18.313801
Mean126.90909
Median Absolute Deviation (MAD)3
Skewness4.2431259
Sum8376
Variance161623.22
MonotonicityNot monotonic
2023-12-11T01:13:03.299760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2 18
 
8.7%
1 7
 
3.4%
4 5
 
2.4%
3 4
 
1.9%
5 3
 
1.4%
16 2
 
1.0%
6 2
 
1.0%
78 2
 
1.0%
2122 2
 
1.0%
158 1
 
0.5%
Other values (20) 20
 
9.6%
(Missing) 142
68.3%
ValueCountFrequency (%)
1 7
 
3.4%
2 18
8.7%
3 4
 
1.9%
4 5
 
2.4%
5 3
 
1.4%
6 2
 
1.0%
7 1
 
0.5%
8 1
 
0.5%
9 1
 
0.5%
10 1
 
0.5%
ValueCountFrequency (%)
2122 2
1.0%
1186 1
0.5%
831 1
0.5%
490 1
0.5%
268 1
0.5%
194 1
0.5%
176 1
0.5%
158 1
0.5%
139 1
0.5%
121 1
0.5%

자주식옥외주차장(대)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)23.1%
Missing143
Missing (%)68.8%
Infinite0
Infinite (%)0.0%
Mean5.4307692
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:03.420136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile23.8
Maximum70
Range69
Interquartile range (IQR)3

Descriptive statistics

Standard deviation10.139602
Coefficient of variation (CV)1.8670656
Kurtosis26.247158
Mean5.4307692
Median Absolute Deviation (MAD)1
Skewness4.6539091
Sum353
Variance102.81154
MonotonicityNot monotonic
2023-12-11T01:13:03.539228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 21
 
10.1%
2 14
 
6.7%
3 9
 
4.3%
4 6
 
2.9%
6 2
 
1.0%
8 2
 
1.0%
25 2
 
1.0%
5 2
 
1.0%
17 1
 
0.5%
70 1
 
0.5%
Other values (5) 5
 
2.4%
(Missing) 143
68.8%
ValueCountFrequency (%)
1 21
10.1%
2 14
6.7%
3 9
4.3%
4 6
 
2.9%
5 2
 
1.0%
6 2
 
1.0%
7 1
 
0.5%
8 2
 
1.0%
10 1
 
0.5%
12 1
 
0.5%
ValueCountFrequency (%)
70 1
0.5%
30 1
0.5%
25 2
1.0%
19 1
0.5%
17 1
0.5%
12 1
0.5%
10 1
0.5%
8 2
1.0%
7 1
0.5%
6 2
1.0%

기계식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)84.6%
Missing182
Missing (%)87.5%
Infinite0
Infinite (%)0.0%
Mean78
Minimum6
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:03.670390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile12
Q131
median63
Q3111
95-th percentile181
Maximum188
Range182
Interquartile range (IQR)80

Descriptive statistics

Standard deviation54.561525
Coefficient of variation (CV)0.69950673
Kurtosis-0.48955864
Mean78
Median Absolute Deviation (MAD)33
Skewness0.76222178
Sum2028
Variance2976.96
MonotonicityNot monotonic
2023-12-11T01:13:04.152089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
30 4
 
1.9%
66 2
 
1.0%
144 1
 
0.5%
8 1
 
0.5%
54 1
 
0.5%
108 1
 
0.5%
112 1
 
0.5%
76 1
 
0.5%
160 1
 
0.5%
188 1
 
0.5%
Other values (12) 12
 
5.8%
(Missing) 182
87.5%
ValueCountFrequency (%)
6 1
 
0.5%
8 1
 
0.5%
24 1
 
0.5%
30 4
1.9%
34 1
 
0.5%
46 1
 
0.5%
54 1
 
0.5%
56 1
 
0.5%
58 1
 
0.5%
60 1
 
0.5%
ValueCountFrequency (%)
188 1
0.5%
184 1
0.5%
172 1
0.5%
160 1
0.5%
144 1
0.5%
120 1
0.5%
112 1
0.5%
108 1
0.5%
88 1
0.5%
78 1
0.5%

기계식옥외주차장(대)
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
204 
100
 
2
3
 
1
112
 
1

Length

Max length4
Median length4
Mean length3.9711538
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 204
98.1%
100 2
 
1.0%
3 1
 
0.5%
112 1
 
0.5%

Length

2023-12-11T01:13:04.346971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:04.493251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 204
98.1%
100 2
 
1.0%
3 1
 
0.5%
112 1
 
0.5%

인근자주식주차장(대)
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
204 
4
 
1
1
 
1
227
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.9519231
Min length1

Unique

Unique4 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 204
98.1%
4 1
 
0.5%
1 1
 
0.5%
227 1
 
0.5%
3 1
 
0.5%

Length

2023-12-11T01:13:04.684984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:04.839746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 204
98.1%
4 1
 
0.5%
1 1
 
0.5%
227 1
 
0.5%
3 1
 
0.5%

총주차대수
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)33.6%
Missing80
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean88.335938
Minimum1
Maximum2247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:04.990613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q331
95-th percentile304.45
Maximum2247
Range2246
Interquartile range (IQR)29

Descriptive statistics

Standard deviation314.47678
Coefficient of variation (CV)3.5600095
Kurtosis35.389694
Mean88.335938
Median Absolute Deviation (MAD)3
Skewness5.7251596
Sum11307
Variance98895.642
MonotonicityNot monotonic
2023-12-11T01:13:05.177334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 23
 
11.1%
2 23
 
11.1%
3 12
 
5.8%
4 10
 
4.8%
6 5
 
2.4%
31 5
 
2.4%
8 5
 
2.4%
5 4
 
1.9%
68 2
 
1.0%
2247 2
 
1.0%
Other values (33) 37
17.8%
(Missing) 80
38.5%
ValueCountFrequency (%)
1 23
11.1%
2 23
11.1%
3 12
5.8%
4 10
4.8%
5 4
 
1.9%
6 5
 
2.4%
7 2
 
1.0%
8 5
 
2.4%
9 1
 
0.5%
10 2
 
1.0%
ValueCountFrequency (%)
2247 2
1.0%
1186 1
0.5%
975 1
0.5%
507 1
0.5%
500 1
0.5%
323 1
0.5%
270 2
1.0%
268 1
0.5%
212 1
0.5%
204 1
0.5%

총주차장면적(제곱미터)
Real number (ℝ)

MISSING  ZEROS 

Distinct69
Distinct (%)53.9%
Missing80
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean511.77662
Minimum0
Maximum26675.36
Zeros19
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:05.379544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.5
median37.5
Q384.85
95-th percentile1253.3425
Maximum26675.36
Range26675.36
Interquartile range (IQR)72.35

Descriptive statistics

Standard deviation2634.3631
Coefficient of variation (CV)5.1474861
Kurtosis78.967327
Mean511.77662
Median Absolute Deviation (MAD)25
Skewness8.3879205
Sum65507.407
Variance6939868.7
MonotonicityNot monotonic
2023-12-11T01:13:05.654722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 19
 
9.1%
12.5 15
 
7.2%
25.0 10
 
4.8%
37.5 6
 
2.9%
50.0 4
 
1.9%
46.0 3
 
1.4%
23.0 3
 
1.4%
12.0 3
 
1.4%
57.5 2
 
1.0%
34.5 2
 
1.0%
Other values (59) 61
29.3%
(Missing) 80
38.5%
ValueCountFrequency (%)
0.0 19
9.1%
11.5 1
 
0.5%
12.0 3
 
1.4%
12.5 15
7.2%
18.85 1
 
0.5%
22.81 1
 
0.5%
23.0 3
 
1.4%
24.5 2
 
1.0%
25.0 10
4.8%
28.57 1
 
0.5%
ValueCountFrequency (%)
26675.36 1
0.5%
9245.06 1
0.5%
8306.43 1
0.5%
4940.19 1
0.5%
4031.55 1
0.5%
1797.26 1
0.5%
1439.07 1
0.5%
908.42 1
0.5%
671.56 1
0.5%
599.85 1
0.5%

세대수
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)93.8%
Missing192
Missing (%)92.3%
Infinite0
Infinite (%)0.0%
Mean100
Minimum1
Maximum546
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:05.853444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.25
Q110.5
median36.5
Q3104
95-th percentile337.5
Maximum546
Range545
Interquartile range (IQR)93.5

Descriptive statistics

Standard deviation146.3325
Coefficient of variation (CV)1.463325
Kurtosis5.2742661
Mean100
Median Absolute Deviation (MAD)32
Skewness2.2143805
Sum1600
Variance21413.2
MonotonicityNot monotonic
2023-12-11T01:13:06.032311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
9 2
 
1.0%
268 1
 
0.5%
11 1
 
0.5%
38 1
 
0.5%
72 1
 
0.5%
80 1
 
0.5%
546 1
 
0.5%
76 1
 
0.5%
8 1
 
0.5%
35 1
 
0.5%
Other values (5) 5
 
2.4%
(Missing) 192
92.3%
ValueCountFrequency (%)
1 1
0.5%
8 1
0.5%
9 2
1.0%
11 1
0.5%
12 1
0.5%
15 1
0.5%
35 1
0.5%
38 1
0.5%
72 1
0.5%
76 1
0.5%
ValueCountFrequency (%)
546 1
0.5%
268 1
0.5%
244 1
0.5%
176 1
0.5%
80 1
0.5%
76 1
0.5%
72 1
0.5%
38 1
0.5%
35 1
0.5%
15 1
0.5%

호수
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)63.8%
Missing161
Missing (%)77.4%
Infinite0
Infinite (%)0.0%
Mean51.957447
Minimum1
Maximum409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:06.238877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q14
median13
Q358
95-th percentile253
Maximum409
Range408
Interquartile range (IQR)54

Descriptive statistics

Standard deviation88.607331
Coefficient of variation (CV)1.7053827
Kurtosis6.4425714
Mean51.957447
Median Absolute Deviation (MAD)11
Skewness2.5203238
Sum2442
Variance7851.259
MonotonicityNot monotonic
2023-12-11T01:13:06.439324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4 8
 
3.8%
2 4
 
1.9%
3 3
 
1.4%
1 3
 
1.4%
5 3
 
1.4%
132 2
 
1.0%
36 1
 
0.5%
38 1
 
0.5%
56 1
 
0.5%
409 1
 
0.5%
Other values (20) 20
 
9.6%
(Missing) 161
77.4%
ValueCountFrequency (%)
1 3
 
1.4%
2 4
1.9%
3 3
 
1.4%
4 8
3.8%
5 3
 
1.4%
6 1
 
0.5%
7 1
 
0.5%
13 1
 
0.5%
14 1
 
0.5%
16 1
 
0.5%
ValueCountFrequency (%)
409 1
0.5%
309 1
0.5%
259 1
0.5%
239 1
0.5%
154 1
0.5%
132 2
1.0%
98 1
0.5%
82 1
0.5%
73 1
0.5%
66 1
0.5%

가구수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)18.2%
Missing175
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean6.2121212
Minimum1
Maximum158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:06.598081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile5.4
Maximum158
Range157
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27.272648
Coefficient of variation (CV)4.3902312
Kurtosis32.872334
Mean6.2121212
Median Absolute Deviation (MAD)0
Skewness5.7286235
Sum205
Variance743.79735
MonotonicityNot monotonic
2023-12-11T01:13:06.763327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 25
 
12.0%
2 4
 
1.9%
6 1
 
0.5%
158 1
 
0.5%
5 1
 
0.5%
3 1
 
0.5%
(Missing) 175
84.1%
ValueCountFrequency (%)
1 25
12.0%
2 4
 
1.9%
3 1
 
0.5%
5 1
 
0.5%
6 1
 
0.5%
158 1
 
0.5%
ValueCountFrequency (%)
158 1
 
0.5%
6 1
 
0.5%
5 1
 
0.5%
3 1
 
0.5%
2 4
 
1.9%
1 25
12.0%

주건축물수
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)3.0%
Missing5
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean9.137931
Minimum1
Maximum1580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-11T01:13:06.932814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1580
Range1579
Interquartile range (IQR)0

Descriptive statistics

Standard deviation110.85938
Coefficient of variation (CV)12.131781
Kurtosis202.54942
Mean9.137931
Median Absolute Deviation (MAD)0
Skewness14.224674
Sum1855
Variance12289.803
MonotonicityNot monotonic
2023-12-11T01:13:07.089636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 193
92.8%
2 6
 
2.9%
7 1
 
0.5%
1580 1
 
0.5%
52 1
 
0.5%
11 1
 
0.5%
(Missing) 5
 
2.4%
ValueCountFrequency (%)
1 193
92.8%
2 6
 
2.9%
7 1
 
0.5%
11 1
 
0.5%
52 1
 
0.5%
1580 1
 
0.5%
ValueCountFrequency (%)
1580 1
 
0.5%
52 1
 
0.5%
11 1
 
0.5%
7 1
 
0.5%
2 6
 
2.9%
1 193
92.8%

부속건축물수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
<NA>
201 
1
 
5
0
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.8990385
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 201
96.6%
1 5
 
2.4%
0 1
 
0.5%
3 1
 
0.5%

Length

2023-12-11T01:13:07.286785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:07.461612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
96.6%
1 5
 
2.4%
0 1
 
0.5%
3 1
 
0.5%
Distinct138
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-11T01:13:07.825392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length10.947115
Min length8

Characters and Unicode

Total characters2277
Distinct characters159
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)53.8%

Sample

1st row루가 건축사사무소
2nd row(주)전원건축종합건축사사무소
3rd row조아 종합건축사사무소
4th row주식회사 제이에스종합건축사사무소
5th row경희건축사사무소
ValueCountFrequency (%)
건축사사무소 64
 
19.2%
종합건축사사무소 36
 
10.8%
조아 21
 
6.3%
주식회사 17
 
5.1%
아키21건축사사무소 11
 
3.3%
주)신흥 5
 
1.5%
대호 4
 
1.2%
포유종합건축사사무소 4
 
1.2%
진성 4
 
1.2%
주)건축사사무소 4
 
1.2%
Other values (134) 163
48.9%
2023-12-11T01:13:08.467963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
436
19.1%
216
 
9.5%
211
 
9.3%
209
 
9.2%
208
 
9.1%
127
 
5.6%
67
 
2.9%
67
 
2.9%
66
 
2.9%
( 43
 
1.9%
Other values (149) 627
27.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2015
88.5%
Space Separator 127
 
5.6%
Open Punctuation 43
 
1.9%
Close Punctuation 43
 
1.9%
Decimal Number 28
 
1.2%
Uppercase Letter 16
 
0.7%
Other Punctuation 4
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
436
21.6%
216
10.7%
211
10.5%
209
10.4%
208
10.3%
67
 
3.3%
67
 
3.3%
66
 
3.3%
37
 
1.8%
24
 
1.2%
Other values (131) 474
23.5%
Uppercase Letter
ValueCountFrequency (%)
A 4
25.0%
S 2
12.5%
C 2
12.5%
T 2
12.5%
E 1
 
6.2%
D 1
 
6.2%
M 1
 
6.2%
P 1
 
6.2%
L 1
 
6.2%
U 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 14
50.0%
1 14
50.0%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%
Space Separator
ValueCountFrequency (%)
127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2015
88.5%
Common 246
 
10.8%
Latin 16
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
436
21.6%
216
10.7%
211
10.5%
209
10.4%
208
10.3%
67
 
3.3%
67
 
3.3%
66
 
3.3%
37
 
1.8%
24
 
1.2%
Other values (131) 474
23.5%
Latin
ValueCountFrequency (%)
A 4
25.0%
S 2
12.5%
C 2
12.5%
T 2
12.5%
E 1
 
6.2%
D 1
 
6.2%
M 1
 
6.2%
P 1
 
6.2%
L 1
 
6.2%
U 1
 
6.2%
Common
ValueCountFrequency (%)
127
51.6%
( 43
 
17.5%
) 43
 
17.5%
2 14
 
5.7%
1 14
 
5.7%
& 3
 
1.2%
- 1
 
0.4%
. 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2015
88.5%
ASCII 262
 
11.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
436
21.6%
216
10.7%
211
10.5%
209
10.4%
208
10.3%
67
 
3.3%
67
 
3.3%
66
 
3.3%
37
 
1.8%
24
 
1.2%
Other values (131) 474
23.5%
ASCII
ValueCountFrequency (%)
127
48.5%
( 43
 
16.4%
) 43
 
16.4%
2 14
 
5.3%
1 14
 
5.3%
A 4
 
1.5%
& 3
 
1.1%
S 2
 
0.8%
C 2
 
0.8%
T 2
 
0.8%
Other values (8) 8
 
3.1%

감리사무소명
Text

MISSING 

Distinct135
Distinct (%)83.3%
Missing46
Missing (%)22.1%
Memory size1.8 KiB
2023-12-11T01:13:08.905114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length11.271605
Min length7

Characters and Unicode

Total characters1826
Distinct characters161
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

Unique118 ?
Unique (%)72.8%

Sample

1st row금영건축사사무소
2nd row건축사사무소 예천
3rd row조아 종합건축사사무소
4th row주식회사 제이에스종합건축사사무소
5th row(주)수가디자인 건축사사무소
ValueCountFrequency (%)
건축사사무소 44
 
17.7%
종합건축사사무소 16
 
6.5%
주식회사 15
 
6.0%
조아 6
 
2.4%
주)종합건축사사무소 6
 
2.4%
대호 4
 
1.6%
주)상지엔지니어링건축사사무소 3
 
1.2%
아키21건축사사무소 3
 
1.2%
미상건축사사무소 3
 
1.2%
주)삼현도시종합건축사사무소 3
 
1.2%
Other values (133) 145
58.5%
2023-12-11T01:13:09.608860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
339
18.6%
167
 
9.1%
164
 
9.0%
162
 
8.9%
162
 
8.9%
89
 
4.9%
64
 
3.5%
45
 
2.5%
( 44
 
2.4%
44
 
2.4%
Other values (151) 546
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1626
89.0%
Space Separator 89
 
4.9%
Open Punctuation 44
 
2.4%
Close Punctuation 44
 
2.4%
Decimal Number 13
 
0.7%
Uppercase Letter 8
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
339
20.8%
167
 
10.3%
164
 
10.1%
162
 
10.0%
162
 
10.0%
64
 
3.9%
45
 
2.8%
44
 
2.7%
26
 
1.6%
24
 
1.5%
Other values (136) 429
26.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
25.0%
G 1
12.5%
N 1
12.5%
C 1
12.5%
A 1
12.5%
L 1
12.5%
S 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
2 5
38.5%
5 1
 
7.7%
0 1
 
7.7%
Space Separator
ValueCountFrequency (%)
89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1626
89.0%
Common 192
 
10.5%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
339
20.8%
167
 
10.3%
164
 
10.1%
162
 
10.0%
162
 
10.0%
64
 
3.9%
45
 
2.8%
44
 
2.7%
26
 
1.6%
24
 
1.5%
Other values (136) 429
26.4%
Common
ValueCountFrequency (%)
89
46.4%
( 44
22.9%
) 44
22.9%
1 6
 
3.1%
2 5
 
2.6%
. 2
 
1.0%
5 1
 
0.5%
0 1
 
0.5%
Latin
ValueCountFrequency (%)
E 2
25.0%
G 1
12.5%
N 1
12.5%
C 1
12.5%
A 1
12.5%
L 1
12.5%
S 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1626
89.0%
ASCII 200
 
11.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
339
20.8%
167
 
10.3%
164
 
10.1%
162
 
10.0%
162
 
10.0%
64
 
3.9%
45
 
2.8%
44
 
2.7%
26
 
1.6%
24
 
1.5%
Other values (136) 429
26.4%
ASCII
ValueCountFrequency (%)
89
44.5%
( 44
22.0%
) 44
22.0%
1 6
 
3.0%
2 5
 
2.5%
. 2
 
1.0%
E 2
 
1.0%
G 1
 
0.5%
N 1
 
0.5%
C 1
 
0.5%
Other values (5) 5
 
2.5%

시공자사무소명
Text

MISSING 

Distinct97
Distinct (%)86.6%
Missing96
Missing (%)46.2%
Memory size1.8 KiB
2023-12-11T01:13:09.897608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length8.6607143
Min length5

Characters and Unicode

Total characters970
Distinct characters137
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

Unique86 ?
Unique (%)76.8%

Sample

1st row대신종합건설(주)
2nd row(주)태종종합건설
3rd row진보산업개발(주)
4th row(주)에스티모빅
5th row(주)진양종합건설
ValueCountFrequency (%)
주식회사 6
 
5.0%
강한종합건설(주 3
 
2.5%
성도종합건설(주 3
 
2.5%
주)디알종합건설 3
 
2.5%
유건 3
 
2.5%
지케이종합건설(주 2
 
1.7%
주식회사대성문 2
 
1.7%
교보종합건설(주 2
 
1.7%
대신종합건설(주 2
 
1.7%
건한종합건설(주 2
 
1.7%
Other values (89) 91
76.5%
2023-12-11T01:13:10.389800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
112
 
11.5%
95
 
9.8%
) 94
 
9.7%
( 94
 
9.7%
85
 
8.8%
66
 
6.8%
65
 
6.7%
18
 
1.9%
18
 
1.9%
18
 
1.9%
Other values (127) 305
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 775
79.9%
Close Punctuation 94
 
9.7%
Open Punctuation 94
 
9.7%
Space Separator 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
112
14.5%
95
 
12.3%
85
 
11.0%
66
 
8.5%
65
 
8.4%
18
 
2.3%
18
 
2.3%
18
 
2.3%
18
 
2.3%
9
 
1.2%
Other values (124) 271
35.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 775
79.9%
Common 195
 
20.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
112
14.5%
95
 
12.3%
85
 
11.0%
66
 
8.5%
65
 
8.4%
18
 
2.3%
18
 
2.3%
18
 
2.3%
18
 
2.3%
9
 
1.2%
Other values (124) 271
35.0%
Common
ValueCountFrequency (%)
) 94
48.2%
( 94
48.2%
7
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 775
79.9%
ASCII 195
 
20.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
112
14.5%
95
 
12.3%
85
 
11.0%
66
 
8.5%
65
 
8.4%
18
 
2.3%
18
 
2.3%
18
 
2.3%
18
 
2.3%
9
 
1.2%
Other values (124) 271
35.0%
ASCII
ValueCountFrequency (%)
) 94
48.2%
( 94
48.2%
7
 
3.6%

Sample

건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(백분율)용적률(백분율)구조취소구분허가일최종설계변경일착공처리일착공예정일실제착공일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수설계사무소명감리사무소명시공자사무소명
0신축2022-건축과-신축허가-38부산광역시 부산진구 가야동 646-2143.485.94194.64<NA>59.93135.73철근콘크리트구조<NA>2022-05-25<NA>2022-06-092022-06-07<NA><NA>2022-05-11309.31<NA><NA>하수종말처리장연결<NA>단독주택<NA>가로구역별최고높이제한지역<NA>상대보호구역<NA>2<NA><NA><NA>224.5<NA>121<NA>루가 건축사사무소금영건축사사무소<NA>
1신축2022-건축과-신축허가-37부산광역시 부산진구 전포동 204-25361.0177.59237.09<NA>49.1934.46철근콘크리트구조<NA>2022-05-24<NA>2022-06-022022-05-31<NA><NA>2022-05-09114.241<NA><NA>하수종말처리장연결3.556제2종근린생활시설사무소가로구역별최고높이제한지역<NA><NA><NA>2<NA><NA><NA>223.0<NA><NA><NA>1<NA>(주)전원건축종합건축사사무소건축사사무소 예천대신종합건설(주)
2증축2022-건축과-증축허가-8부산광역시 부산진구 전포동 164-42132.688.99240.61240.6167.11181.46블록구조<NA>2022-05-20<NA>2022-05-262022-05-27<NA><NA>2022-05-033<NA>12.310<NA>하수종말처리장연결8.49제1종근린생활시설(소매점, 휴게음식점), 제2종근린생활시설(사무소)일반상업지역방화지구상대보호구역<NA><NA><NA><NA><NA><NA><NA><NA>3<NA>1<NA>조아 종합건축사사무소조아 종합건축사사무소<NA>
3대수선2022-건축과-대수선허가-9부산광역시 부산진구 양정동 273-16348.53807.1961851.44<NA>59.9699622.7849철근콘크리트구조<NA>2022-05-18<NA>2022-05-242022-05-24<NA><NA>2022-04-1830590.5133접촉폭기방법<NA>공동주택공동주택(아파트)일반상업지역방화지구<NA>49017<NA><NA><NA>5070.026814<NA>1<NA>주식회사 제이에스종합건축사사무소주식회사 제이에스종합건축사사무소<NA>
4신축2022-건축과-신축허가-35부산광역시 부산진구 당감동 663-10 외1필지465.0241.02992.14<NA>51.83213.36철근콘크리트구조<NA>2022-05-18<NA>2022-06-232022-06-16<NA><NA>2022-04-066018.111<NA><NA><NA>공동주택공동주택(도시형생활주택)제2종일반주거지역<NA>상대보호구역11<NA><NA><NA><NA>110.0114<NA>1<NA>경희건축사사무소(주)수가디자인 건축사사무소(주)태종종합건설
5대수선2022-건축과-대수선허가-8부산광역시 부산진구 범천동 870-5430.4339.192069.63<NA>78.81406.89철근콘크리트구조<NA>2022-05-10<NA>2022-06-292022-07-01<NA><NA>2022-04-296120.911<NA>부패탱크방법<NA>제2종근린생활시설교육연구시설,업무시설가로구역별최고높이제한지역방화지구<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>(주)신흥 종합건축사사무소(주)신흥 종합건축사사무소진보산업개발(주)
6신축2022-건축과-신축허가-34부산광역시 부산진구 전포동 194-16 외1필지780.4288.7432.52<NA>36.9955.42철근콘크리트구조<NA>2022-05-09<NA>2022-07-062022-06-28<NA><NA>2022-04-252012.01<NA><NA>하수종말처리장연결13.97제2종근린생활시설휴게음식점일반상업지역방화지구상대보호구역<NA>6<NA><NA><NA>673.0<NA><NA><NA>1<NA>씨앤피건축사사무소씨앤피건축사사무소(주)에스티모빅
7신축2022-건축과-신축허가-33부산광역시 부산진구 부전동 398-17 외3필지346.1258.62334.72<NA>74.7296.71철근콘크리트구조<NA>2022-04-29<NA>2022-06-232022-06-23<NA><NA>2022-04-122010.31<NA><NA>하수종말처리장연결<NA>제2종근린생활시설<NA>일반상업지역방화지구<NA><NA>2<NA><NA><NA>225.0<NA><NA><NA>1<NA>도담 건축사사무소아이제이건축사사무소(주)진양종합건설
8신축2022-건축과-신축허가-31부산광역시 부산진구 전포동 671-12128.091.95267.3<NA>71.84208.83철근콘크리트구조<NA>2022-04-21<NA>2022-05-192022-05-20<NA><NA>2022-04-115015.71<NA><NA>하수종말처리장연결7.52창고시설(창고)/제1,2종근린생활시설(휴게음식점,일반음식점)가로구역별최고높이제한지역방화지구<NA><NA>1<NA><NA><NA>112.5<NA>4<NA>1<NA>조아 종합건축사사무소건축사사무소 대호(주)뉴동아건설
9신축2022-건축과-신축허가-30부산광역시 부산진구 개금동 467-11 외1필지229.2114.03335.79<NA>49.75146.51철근콘크리트구조<NA>2022-04-18<NA>2022-06-142022-06-15<NA><NA>2022-03-30309.01<NA><NA>부패탱크방법<NA>창고시설제2종 근린생활시설(사무소)제3종일반주거지역<NA>상대보호구역<NA>1<NA><NA><NA>112.5<NA><NA><NA>1<NA>수오재 건축사사무소밀리건축사사무소푸름담벼락종합건설 주식회사
건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(백분율)용적률(백분율)구조취소구분허가일최종설계변경일착공처리일착공예정일실제착공일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수설계사무소명감리사무소명시공자사무소명
198증축2021-건축과-증축신고-4부산광역시 부산진구 부전동 168-459200.1160.041300.1964.979.98584.84철근콘크리트구조<NA>2021-04-14<NA>2021-04-162021-04-192021-04-162021-05-122021-04-089136.0511<NA>하수종말처리장연결66.16제2종근린생활시설일반음식점일반상업지역방화지구<NA><NA><NA>8<NA><NA>898.87<NA><NA><NA>1<NA>우목엔지니어링건축사사무소우목엔지니어링건축사사무소주식회사우목산업개발
199증축2021-건축과-증축신고-3부산광역시 부산진구 부전동 198-3330.6261.6662.0359.9779.13200.25경량철골구조<NA>2021-03-24<NA>2021-05-172021-05-182021-05-172021-08-252021-03-164<NA>18.511<NA>하수종말처리장연결31.09제2종근린생활시설일반음식점일반상업지역방화지구<NA>4<NA><NA><NA><NA>446.0<NA><NA><NA>1<NA>건축사사무소 이림<NA><NA>
200증축2021-건축과-증축신고-2부산광역시 부산진구 전포동 687-8124.376.29199.4251.761.38160.43벽돌구조<NA>2021-03-11<NA>2021-04-132021-04-14<NA>2021-06-082021-03-043<NA>11.1310<NA>하수종말처리장연결6.34제2종근린생활시설제2종근린생활시설(일반음식점,사무소) 및 제1종근린생활시설일반상업지역방화지구<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>조아 종합건축사사무소<NA><NA>
201개축2021-건축과-공용건축물-4부산광역시 부산진구 양정동 503-15117.457.8449.58<NA>49.267542.2317철근콘크리트구조<NA>2021-03-11<NA>2021-08-182021-08-16<NA><NA>2021-02-221<NA>5.01<NA><NA>부패탱크방법<NA>제1종근린생활시설마을회관제3종일반주거지역<NA>상대보호구역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>건축사사무소 이가이룸건축사사무소(주)일성엔지니어링
202용도변경2021-건축과-용도변경신고-9부산광역시 부산진구 양정동 162-5 외1필지280.0131.46810.06<NA>46.95289.31철근콘크리트구조<NA>2021-02-18<NA>2021-03-112021-03-10<NA><NA>2021-01-267<NA>20.511<NA>부패탱크방법14.69공동주택<NA>준주거지역<NA>제1종지구단위계획구역42<NA><NA><NA>669.0153<NA>1<NA>건축사사무소 진성<NA><NA>
203신축2021-건축과-신축신고-3부산광역시 부산진구 부전동 560-1427.021.3642.72<NA>79.11158.22철근콘크리트구조<NA>2021-02-162021-04-262021-03-092021-03-082021-03-092021-06-112021-02-03308.51<NA><NA>하수종말처리장연결<NA>제1종근린생활시설<NA>일반상업지역방화지구<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>미상건축사사무소<NA><NA>
204증축2021-건축과-증축신고-1부산광역시 부산진구 전포동 355-4 외1필지141.765.94195.1361.8446.54137.71철근콘크리트구조<NA>2021-02-08<NA>2021-02-152021-02-15<NA>2021-03-112021-02-013<NA>11.551<NA><NA>하수종말처리장연결7.88제2종근린생활시설(일반음식점,사무소) 및 제1종 근린생활시설(휴게음식점)제3종일반주거지역<NA>상대보호구역<NA><NA><NA><NA><NA><NA><NA><NA>3<NA>1<NA>조아 종합건축사사무소<NA>진공종합건설(주)
205대수선2021-건축과-대수선신고-1부산광역시 부산진구 당감동 292-46142.047.9547.95<NA>33.7733.77블록구조<NA>2021-01-22<NA>2021-02-182021-02-16<NA>2021-03-252020-12-281<NA>3.810<NA>부패탱크방법<NA>단독주택<NA>가로구역별최고높이제한지역<NA>상대보호구역<NA><NA><NA><NA><NA><NA><NA><NA><NA>11<NA>건축사사무소 대호<NA><NA>
206신축2021-건축과-신축신고-2부산광역시 부산진구 전포동 356-3931.2320.862.4<NA>66.6026199.8079철근콘크리트구조<NA>2021-01-07<NA>2021-03-052021-03-03<NA>2021-07-232020-12-294011.251<NA><NA>하수종말처리장연결2.184제1종근린생활시설휴게음식점가로구역별최고높이제한지역방화지구상대보호구역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>이한건축사사무소<NA><NA>
207신축2021-건축과-신축신고-1부산광역시 부산진구 가야동 125-23111.040.2233.76<NA>36.234230.4144강파이프구조<NA>2021-01-05<NA>2021-01-182021-01-19<NA>2021-07-082020-12-17105.5661<NA><NA>하수종말처리장연결<NA>단독주택<NA>제3종일반주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11<NA>김정화건축사사무소<NA><NA>