Overview

Dataset statistics

Number of variables37
Number of observations304
Missing cells2449
Missing cells (%)21.8%
Duplicate rows2
Duplicate rows (%)0.7%
Total size in memory94.2 KiB
Average record size in memory317.4 B

Variable types

Categorical12
Text4
Numeric18
DateTime3

Dataset

Description부천시 건축 허가에현황에 대한 데이터로 건축구분, 면적, 허가일, 승강기 정보, 하수처리 정보, 용도, 주차장정보, 세대수, 층수 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3038818/fileData.do

Alerts

Dataset has 2 (0.7%) duplicate rowsDuplicates
지목 is highly imbalanced (76.3%)Imbalance
구조 is highly imbalanced (56.7%)Imbalance
하수처리시설명 is highly imbalanced (55.5%)Imbalance
용도지구 is highly imbalanced (55.9%)Imbalance
인근자주식주차장(대) is highly imbalanced (96.8%)Imbalance
호수 is highly imbalanced (60.9%)Imbalance
주건축물수 is highly imbalanced (82.9%)Imbalance
부속건축물수 is highly imbalanced (75.0%)Imbalance
증축연면적(제곱미터) has 290 (95.4%) missing valuesMissing
착공처리일 has 173 (56.9%) missing valuesMissing
사용승인일 has 261 (85.9%) missing valuesMissing
최대지하층수 has 44 (14.5%) missing valuesMissing
승강기합 has 39 (12.8%) missing valuesMissing
비상승강기합 has 270 (88.8%) missing valuesMissing
하수처리시설용량(세제곱미터) has 278 (91.4%) missing valuesMissing
부속용도 has 31 (10.2%) missing valuesMissing
자주식옥내주차장(대) has 140 (46.1%) missing valuesMissing
자주식옥외주차장(대) has 127 (41.8%) missing valuesMissing
기계식옥내주차장(대) has 288 (94.7%) missing valuesMissing
총주차대수 has 27 (8.9%) missing valuesMissing
총주차장면적(제곱미터) has 27 (8.9%) missing valuesMissing
세대수 has 177 (58.2%) missing valuesMissing
가구수 has 277 (91.1%) missing valuesMissing
최대지하층수 has 103 (33.9%) zerosZeros
최고높이(미터) has 14 (4.6%) zerosZeros
동수 has 6 (2.0%) zerosZeros
승강기합 has 45 (14.8%) zerosZeros
비상승강기합 has 5 (1.6%) zerosZeros
총주차대수 has 17 (5.6%) zerosZeros
총주차장면적(제곱미터) has 67 (22.0%) zerosZeros

Reproduction

Analysis started2023-12-12 10:12:37.842905
Analysis finished2023-12-12 10:12:38.490290
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
신축
175 
용도변경
102 
증축
 
14
대수선
 
13

Length

Max length4
Median length2
Mean length2.7138158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 175
57.6%
용도변경 102
33.6%
증축 14
 
4.6%
대수선 13
 
4.3%

Length

2023-12-12T19:12:38.597042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:38.736687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 175
57.6%
용도변경 102
33.6%
증축 14
 
4.6%
대수선 13
 
4.3%

대지위치
Text

Distinct285
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T19:12:39.170208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length18.710526
Min length14

Characters and Unicode

Total characters5688
Distinct characters65
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

Unique273 ?
Unique (%)89.8%

Sample

1st row경기도 부천시 심곡동 176-14 외1필지
2nd row경기도 부천시 심곡동 194
3rd row경기도 부천시 심곡동 194
4th row경기도 부천시 송내동 388-9
5th row경기도 부천시 송내동 388-10
ValueCountFrequency (%)
경기도 304
22.9%
부천시 304
22.9%
외1필지 60
 
4.5%
소사본동 27
 
2.0%
심곡동 26
 
2.0%
도당동 22
 
1.7%
중동 21
 
1.6%
원종동 20
 
1.5%
심곡본동 20
 
1.5%
삼정동 17
 
1.3%
Other values (307) 505
38.1%
2023-12-12T19:12:39.821314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1022
18.0%
도 326
 
5.7%
1 313
 
5.5%
부 305
 
5.4%
경 304
 
5.3%
천 304
 
5.3%
시 304
 
5.3%
기 304
 
5.3%
동 304
 
5.3%
- 258
 
4.5%
Other values (55) 1944
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3073
54.0%
Decimal Number 1335
23.5%
Space Separator 1022
 
18.0%
Dash Punctuation 258
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 326
10.6%
부 305
9.9%
경 304
9.9%
천 304
9.9%
시 304
9.9%
기 304
9.9%
동 304
9.9%
지 108
 
3.5%
필 107
 
3.5%
외 107
 
3.5%
Other values (43) 600
19.5%
Decimal Number
ValueCountFrequency (%)
1 313
23.4%
2 203
15.2%
3 180
13.5%
5 120
 
9.0%
4 115
 
8.6%
6 91
 
6.8%
9 83
 
6.2%
7 81
 
6.1%
0 76
 
5.7%
8 73
 
5.5%
Space Separator
ValueCountFrequency (%)
1022
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3073
54.0%
Common 2615
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 326
10.6%
부 305
9.9%
경 304
9.9%
천 304
9.9%
시 304
9.9%
기 304
9.9%
동 304
9.9%
지 108
 
3.5%
필 107
 
3.5%
외 107
 
3.5%
Other values (43) 600
19.5%
Common
ValueCountFrequency (%)
1022
39.1%
1 313
 
12.0%
- 258
 
9.9%
2 203
 
7.8%
3 180
 
6.9%
5 120
 
4.6%
4 115
 
4.4%
6 91
 
3.5%
9 83
 
3.2%
7 81
 
3.1%
Other values (2) 149
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3073
54.0%
ASCII 2615
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1022
39.1%
1 313
 
12.0%
- 258
 
9.9%
2 203
 
7.8%
3 180
 
6.9%
5 120
 
4.6%
4 115
 
4.4%
6 91
 
3.5%
9 83
 
3.2%
7 81
 
3.1%
Other values (2) 149
 
5.7%
Hangul
ValueCountFrequency (%)
도 326
10.6%
부 305
9.9%
경 304
9.9%
천 304
9.9%
시 304
9.9%
기 304
9.9%
동 304
9.9%
지 108
 
3.5%
필 107
 
3.5%
외 107
 
3.5%
Other values (43) 600
19.5%

지목
Categorical

IMBALANCE 

Distinct10
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
대
264 
공장용지
28 
전
 
3
잡종지
 
3
주유소용지
 
1
Other values (5)
 
5

Length

Max length5
Median length1
Mean length1.3388158
Min length1

Unique

Unique6 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
대 264
86.8%
공장용지 28
 
9.2%
전 3
 
1.0%
잡종지 3
 
1.0%
주유소용지 1
 
0.3%
주차장 1
 
0.3%
창고용지 1
 
0.3%
답 1
 
0.3%
철도용지 1
 
0.3%
임야 1
 
0.3%

Length

2023-12-12T19:12:40.025396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:40.224391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 264
86.8%
공장용지 28
 
9.2%
전 3
 
1.0%
잡종지 3
 
1.0%
주유소용지 1
 
0.3%
주차장 1
 
0.3%
창고용지 1
 
0.3%
답 1
 
0.3%
철도용지 1
 
0.3%
임야 1
 
0.3%

대지면적(제곱미터)
Real number (ℝ)

Distinct283
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2029.0166
Minimum93
Maximum121065.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:40.705929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum93
5-th percentile132.405
Q1279.75
median497.15
Q31149.325
95-th percentile6317.9
Maximum121065.2
Range120972.2
Interquartile range (IQR)869.575

Descriptive statistics

Standard deviation8213.3401
Coefficient of variation (CV)4.0479414
Kurtosis152.29711
Mean2029.0166
Median Absolute Deviation (MAD)321.45
Skewness11.36641
Sum616821.04
Variance67458956
MonotonicityNot monotonic
2023-12-12T19:12:40.875801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6317.9 5
 
1.6%
4413.2 4
 
1.3%
9008.3 4
 
1.3%
1681.9 2
 
0.7%
107.7 2
 
0.7%
2737.7 2
 
0.7%
165.5 2
 
0.7%
300.0 2
 
0.7%
439.2 2
 
0.7%
308.0 2
 
0.7%
Other values (273) 277
91.1%
ValueCountFrequency (%)
93.0 1
0.3%
99.5 1
0.3%
101.3 1
0.3%
105.1 1
0.3%
107.7 2
0.7%
107.8 1
0.3%
115.9 1
0.3%
119.3 1
0.3%
123.1 1
0.3%
123.9 1
0.3%
ValueCountFrequency (%)
121065.2 1
 
0.3%
54029.9 1
 
0.3%
34555.6 1
 
0.3%
27194.6 1
 
0.3%
25604.7 1
 
0.3%
13976.6 1
 
0.3%
13387.0 1
 
0.3%
10634.5 1
 
0.3%
9008.3 4
1.3%
6317.9 5
1.6%

건축면적(제곱미터)
Real number (ℝ)

Distinct280
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1418.6688
Minimum53.04
Maximum72404.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:41.034325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53.04
5-th percentile72.541
Q1163.8475
median255.34
Q3686.84
95-th percentile4772.738
Maximum72404.91
Range72351.87
Interquartile range (IQR)522.9925

Descriptive statistics

Standard deviation5346.548
Coefficient of variation (CV)3.7687076
Kurtosis106.68964
Mean1418.6688
Median Absolute Deviation (MAD)146.625
Skewness9.1238528
Sum431275.33
Variance28585576
MonotonicityNot monotonic
2023-12-12T19:12:41.194189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3269.3 5
 
1.6%
22405.52 4
 
1.3%
6152.744 4
 
1.3%
996.38 2
 
0.7%
260.64 2
 
0.7%
1081.76 2
 
0.7%
122.57 2
 
0.7%
191.74 2
 
0.7%
1302.18 2
 
0.7%
93.64 2
 
0.7%
Other values (270) 277
91.1%
ValueCountFrequency (%)
53.04 1
0.3%
58.08 1
0.3%
58.63 1
0.3%
59.41 1
0.3%
61.37 1
0.3%
61.65 1
0.3%
62.66 1
0.3%
63.17 1
0.3%
63.84 1
0.3%
64.86 1
0.3%
ValueCountFrequency (%)
72404.91 1
 
0.3%
22405.52 4
1.3%
20965.72 1
 
0.3%
20894.43 1
 
0.3%
20557.42 1
 
0.3%
15142.26 1
 
0.3%
7952.67 1
 
0.3%
6932.74 1
 
0.3%
6152.744 4
1.3%
4859.63 1
 
0.3%

연면적(제곱미터)
Real number (ℝ)

Distinct284
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18859.849
Minimum106.08
Maximum2952017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:41.352381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106.08
5-th percentile150.0835
Q1509.8525
median1148.835
Q34535.68
95-th percentile50014.972
Maximum2952017
Range2951910.9
Interquartile range (IQR)4025.8275

Descriptive statistics

Standard deviation171262.68
Coefficient of variation (CV)9.0808085
Kurtosis286.63787
Mean18859.849
Median Absolute Deviation (MAD)925.905
Skewness16.714458
Sum5733394
Variance2.9330904 × 1010
MonotonicityNot monotonic
2023-12-12T19:12:41.491915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34107.01 5
 
1.6%
146028.45 4
 
1.3%
4535.68 4
 
1.3%
2409.86 2
 
0.7%
659.52 2
 
0.7%
1743.17 2
 
0.7%
513.17 2
 
0.7%
187.28 2
 
0.7%
658.86 2
 
0.7%
6847.43 2
 
0.7%
Other values (274) 277
91.1%
ValueCountFrequency (%)
106.08 1
0.3%
113.22 1
0.3%
118.81 1
0.3%
127.68 1
0.3%
128.16 1
0.3%
129.25 1
0.3%
130.86 1
0.3%
131.43 1
0.3%
134.57 1
0.3%
137.01 1
0.3%
ValueCountFrequency (%)
2952017.0 1
 
0.3%
305052.2 1
 
0.3%
198696.99 1
 
0.3%
146028.45 4
1.3%
106779.18 1
 
0.3%
86113.33 1
 
0.3%
76037.27 1
 
0.3%
73070.85 1
 
0.3%
64913.44 1
 
0.3%
62381.87 1
 
0.3%

증축연면적(제곱미터)
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing290
Missing (%)95.4%
Memory size2.5 KiB
2023-12-12T19:12:41.698622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.8571429
Min length3

Characters and Unicode

Total characters82
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row9,627.99
2nd row12,642.89
3rd row120
4th row41.41
5th row134.45
ValueCountFrequency (%)
9,627.99 1
 
7.1%
12,642.89 1
 
7.1%
120 1
 
7.1%
41.41 1
 
7.1%
134.45 1
 
7.1%
59.25 1
 
7.1%
88.59 1
 
7.1%
2,201.11 1
 
7.1%
51.46 1
 
7.1%
44.44 1
 
7.1%
Other values (4) 4
28.6%
2023-12-12T19:12:42.001319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.1%
. 13
15.9%
9 12
14.6%
4 11
13.4%
2 8
9.8%
5 7
8.5%
6 4
 
4.9%
, 3
 
3.7%
8 3
 
3.7%
0 3
 
3.7%
Other values (2) 4
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
80.5%
Other Punctuation 16
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.2%
9 12
18.2%
4 11
16.7%
2 8
12.1%
5 7
10.6%
6 4
 
6.1%
8 3
 
4.5%
0 3
 
4.5%
7 2
 
3.0%
3 2
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 13
81.2%
, 3
 
18.8%

Most occurring scripts

ValueCountFrequency (%)
Common 82
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.1%
. 13
15.9%
9 12
14.6%
4 11
13.4%
2 8
9.8%
5 7
8.5%
6 4
 
4.9%
, 3
 
3.7%
8 3
 
3.7%
0 3
 
3.7%
Other values (2) 4
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.1%
. 13
15.9%
9 12
14.6%
4 11
13.4%
2 8
9.8%
5 7
8.5%
6 4
 
4.9%
, 3
 
3.7%
8 3
 
3.7%
0 3
 
3.7%
Other values (2) 4
 
4.9%

건폐율(퍼센트)
Real number (ℝ)

Distinct267
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.154119
Minimum19.93
Maximum507.6933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:42.132384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19.93
5-th percentile33.490355
Q151.595
median58.725
Q360.5
95-th percentile77.055525
Maximum507.6933
Range487.7633
Interquartile range (IQR)8.905

Descriptive statistics

Standard deviation52.870404
Coefficient of variation (CV)0.85063396
Kurtosis64.893236
Mean62.154119
Median Absolute Deviation (MAD)5.7623
Skewness7.9266255
Sum18894.852
Variance2795.2796
MonotonicityNot monotonic
2023-12-12T19:12:42.292405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51.7466 5
 
1.6%
68.3 4
 
1.3%
59.88 4
 
1.3%
507.6933 4
 
1.3%
59.34 3
 
1.0%
59.2 3
 
1.0%
57.21 2
 
0.7%
59.67 2
 
0.7%
69.81 2
 
0.7%
59.78 2
 
0.7%
Other values (257) 273
89.8%
ValueCountFrequency (%)
19.93 1
0.3%
20.67 1
0.3%
22.15 1
0.3%
22.94 1
0.3%
23.98 1
0.3%
24.62 1
0.3%
25.9191 1
0.3%
27.4246 1
0.3%
28.0 1
0.3%
28.58 1
0.3%
ValueCountFrequency (%)
507.6933 4
1.3%
79.8 1
 
0.3%
79.66 1
 
0.3%
79.45 1
 
0.3%
79.34 1
 
0.3%
79.27 1
 
0.3%
79.15 1
 
0.3%
78.48 1
 
0.3%
77.89 1
 
0.3%
77.67 1
 
0.3%

용적률(퍼센트)
Text

Distinct286
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T19:12:42.759556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0394737
Min length2

Characters and Unicode

Total characters1836
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique275 ?
Unique (%)90.5%

Sample

1st row684.25
2nd row102.7753
3rd row102.7753
4th row156.45
5th row200.28
ValueCountFrequency (%)
285.1656 5
 
1.6%
102.7753 4
 
1.3%
988.42 4
 
1.3%
229.3 2
 
0.7%
117.38 2
 
0.7%
278.66 2
 
0.7%
150.16 2
 
0.7%
226.48 2
 
0.7%
113.16 2
 
0.7%
229.5 2
 
0.7%
Other values (276) 277
91.1%
2023-12-12T19:12:43.403708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 301
16.4%
2 254
13.8%
1 236
12.9%
9 180
9.8%
7 145
7.9%
3 135
7.4%
5 129
7.0%
4 127
6.9%
8 125
6.8%
6 125
6.8%
Other values (2) 79
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1533
83.5%
Other Punctuation 303
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 254
16.6%
1 236
15.4%
9 180
11.7%
7 145
9.5%
3 135
8.8%
5 129
8.4%
4 127
8.3%
8 125
8.2%
6 125
8.2%
0 77
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 301
99.3%
, 2
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 301
16.4%
2 254
13.8%
1 236
12.9%
9 180
9.8%
7 145
7.9%
3 135
7.4%
5 129
7.0%
4 127
6.9%
8 125
6.8%
6 125
6.8%
Other values (2) 79
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 301
16.4%
2 254
13.8%
1 236
12.9%
9 180
9.8%
7 145
7.9%
3 135
7.4%
5 129
7.0%
4 127
6.9%
8 125
6.8%
6 125
6.8%
Other values (2) 79
 
4.3%

구조
Categorical

IMBALANCE 

Distinct7
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
철근콘크리트구조
238 
벽돌구조
24 
일반철골구조
 
17
<NA>
 
14
철골철근콘크리트구조
 
8
Other values (2)
 
3

Length

Max length11
Median length8
Mean length7.4375
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 238
78.3%
벽돌구조 24
 
7.9%
일반철골구조 17
 
5.6%
<NA> 14
 
4.6%
철골철근콘크리트구조 8
 
2.6%
경량철골구조 2
 
0.7%
프리케스트콘크리트구조 1
 
0.3%

Length

2023-12-12T19:12:43.565464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:43.711442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 238
78.3%
벽돌구조 24
 
7.9%
일반철골구조 17
 
5.6%
na 14
 
4.6%
철골철근콘크리트구조 8
 
2.6%
경량철골구조 2
 
0.7%
프리케스트콘크리트구조 1
 
0.3%

허가일
Date

Distinct164
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum2022-04-08 00:00:00
Maximum2023-03-18 00:00:00
2023-12-12T19:12:43.870622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:44.054497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct89
Distinct (%)67.9%
Missing173
Missing (%)56.9%
Memory size2.5 KiB
Minimum2022-05-03 00:00:00
Maximum2023-03-20 00:00:00
2023-12-12T19:12:44.209511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:44.379329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct37
Distinct (%)86.0%
Missing261
Missing (%)85.9%
Memory size2.5 KiB
Minimum2022-05-25 00:00:00
Maximum2023-03-16 00:00:00
2023-12-12T19:12:44.505041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:44.642535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

최대지상층수
Real number (ℝ)

Distinct23
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9210526
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:44.773427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q37
95-th percentile17
Maximum49
Range48
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.7173253
Coefficient of variation (CV)0.97056412
Kurtosis19.678575
Mean6.9210526
Median Absolute Deviation (MAD)2
Skewness3.8522861
Sum2104
Variance45.12246
MonotonicityNot monotonic
2023-12-12T19:12:44.914596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
5 104
34.2%
2 42
13.8%
4 24
 
7.9%
3 21
 
6.9%
7 16
 
5.3%
6 15
 
4.9%
10 11
 
3.6%
11 11
 
3.6%
9 8
 
2.6%
1 7
 
2.3%
Other values (13) 45
14.8%
ValueCountFrequency (%)
1 7
 
2.3%
2 42
13.8%
3 21
 
6.9%
4 24
 
7.9%
5 104
34.2%
6 15
 
4.9%
7 16
 
5.3%
8 5
 
1.6%
9 8
 
2.6%
10 11
 
3.6%
ValueCountFrequency (%)
49 4
1.3%
35 1
 
0.3%
27 1
 
0.3%
22 2
 
0.7%
20 4
1.3%
19 3
1.0%
17 2
 
0.7%
16 1
 
0.3%
15 7
2.3%
14 5
1.6%

최대지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.1%
Missing44
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean1.1615385
Minimum0
Maximum7
Zeros103
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:45.023656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4746446
Coefficient of variation (CV)1.2695616
Kurtosis4.2894941
Mean1.1615385
Median Absolute Deviation (MAD)1
Skewness1.9534719
Sum302
Variance2.1745768
MonotonicityNot monotonic
2023-12-12T19:12:45.129273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 103
33.9%
1 89
29.3%
2 35
 
11.5%
3 12
 
3.9%
4 10
 
3.3%
7 5
 
1.6%
5 4
 
1.3%
6 2
 
0.7%
(Missing) 44
14.5%
ValueCountFrequency (%)
0 103
33.9%
1 89
29.3%
2 35
 
11.5%
3 12
 
3.9%
4 10
 
3.3%
5 4
 
1.3%
6 2
 
0.7%
7 5
 
1.6%
ValueCountFrequency (%)
7 5
 
1.6%
6 2
 
0.7%
5 4
 
1.3%
4 10
 
3.3%
3 12
 
3.9%
2 35
 
11.5%
1 89
29.3%
0 103
33.9%

최고높이(미터)
Real number (ℝ)

ZEROS 

Distinct183
Distinct (%)60.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.259082
Minimum0
Maximum160.3
Zeros14
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:45.269302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.26
Q114.375
median17.1
Q332.5
95-th percentile66.7075
Maximum160.3
Range160.3
Interquartile range (IQR)18.125

Descriptive statistics

Standard deviation22.99899
Coefficient of variation (CV)0.91052359
Kurtosis14.799791
Mean25.259082
Median Absolute Deviation (MAD)8.965
Skewness3.2082331
Sum7678.761
Variance528.95355
MonotonicityNot monotonic
2023-12-12T19:12:45.414415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.0 14
 
4.6%
0.0 14
 
4.6%
15.9 13
 
4.3%
15.8 8
 
2.6%
16.0 7
 
2.3%
16.1 6
 
2.0%
14.3 5
 
1.6%
17.0 5
 
1.6%
17.1 5
 
1.6%
42.35 5
 
1.6%
Other values (173) 222
73.0%
ValueCountFrequency (%)
0.0 14
4.6%
2.8 1
 
0.3%
5.2 1
 
0.3%
5.6 2
 
0.7%
5.7 1
 
0.3%
5.95 2
 
0.7%
6.0 1
 
0.3%
6.1 1
 
0.3%
6.4 3
 
1.0%
6.8 1
 
0.3%
ValueCountFrequency (%)
160.3 4
1.3%
113.22 1
 
0.3%
86.8 1
 
0.3%
83.1 1
 
0.3%
78.85 1
 
0.3%
75.9 1
 
0.3%
73.9 1
 
0.3%
71.15 1
 
0.3%
70.95 1
 
0.3%
70.4 2
0.7%

동수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1546053
Minimum0
Maximum21
Zeros6
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:45.543458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2970308
Coefficient of variation (CV)1.1233543
Kurtosis188.8163
Mean1.1546053
Median Absolute Deviation (MAD)0
Skewness12.983522
Sum351
Variance1.682289
MonotonicityNot monotonic
2023-12-12T19:12:45.670073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 275
90.5%
2 18
 
5.9%
0 6
 
2.0%
3 3
 
1.0%
21 1
 
0.3%
10 1
 
0.3%
ValueCountFrequency (%)
0 6
 
2.0%
1 275
90.5%
2 18
 
5.9%
3 3
 
1.0%
10 1
 
0.3%
21 1
 
0.3%
ValueCountFrequency (%)
21 1
 
0.3%
10 1
 
0.3%
3 3
 
1.0%
2 18
 
5.9%
1 275
90.5%
0 6
 
2.0%

승강기합
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)4.5%
Missing39
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean1.6641509
Minimum0
Maximum19
Zeros45
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:45.772266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile6
Maximum19
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8451909
Coefficient of variation (CV)1.7096952
Kurtosis25.372687
Mean1.6641509
Median Absolute Deviation (MAD)0
Skewness4.8089859
Sum441
Variance8.0951115
MonotonicityNot monotonic
2023-12-12T19:12:45.959555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 161
53.0%
0 45
 
14.8%
2 27
 
8.9%
3 11
 
3.6%
6 7
 
2.3%
4 4
 
1.3%
19 4
 
1.3%
5 2
 
0.7%
16 1
 
0.3%
7 1
 
0.3%
Other values (2) 2
 
0.7%
(Missing) 39
 
12.8%
ValueCountFrequency (%)
0 45
 
14.8%
1 161
53.0%
2 27
 
8.9%
3 11
 
3.6%
4 4
 
1.3%
5 2
 
0.7%
6 7
 
2.3%
7 1
 
0.3%
8 1
 
0.3%
16 1
 
0.3%
ValueCountFrequency (%)
19 4
 
1.3%
18 1
 
0.3%
16 1
 
0.3%
8 1
 
0.3%
7 1
 
0.3%
6 7
 
2.3%
5 2
 
0.7%
4 4
 
1.3%
3 11
3.6%
2 27
8.9%

비상승강기합
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)17.6%
Missing270
Missing (%)88.8%
Infinite0
Infinite (%)0.0%
Mean2.1764706
Minimum0
Maximum13
Zeros5
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:46.107553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q32
95-th percentile4.7
Maximum13
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.4054306
Coefficient of variation (CV)1.1051978
Kurtosis12.056819
Mean2.1764706
Median Absolute Deviation (MAD)1
Skewness2.9858693
Sum74
Variance5.7860963
MonotonicityNot monotonic
2023-12-12T19:12:46.220306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 11
 
3.6%
2 10
 
3.3%
4 6
 
2.0%
0 5
 
1.6%
13 1
 
0.3%
6 1
 
0.3%
(Missing) 270
88.8%
ValueCountFrequency (%)
0 5
1.6%
1 11
3.6%
2 10
3.3%
4 6
2.0%
6 1
 
0.3%
13 1
 
0.3%
ValueCountFrequency (%)
13 1
 
0.3%
6 1
 
0.3%
4 6
2.0%
2 10
3.3%
1 11
3.6%
0 5
1.6%

하수처리시설명
Categorical

IMBALANCE 

Distinct10
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
부패탱크방법
218 
하수종말처리장연결
44 
<NA>
 
16
접촉산화방법
 
8
기타단독정화조
 
7
Other values (5)
 
11

Length

Max length9
Median length6
Mean length6.3815789
Min length4

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
부패탱크방법 218
71.7%
하수종말처리장연결 44
 
14.5%
<NA> 16
 
5.3%
접촉산화방법 8
 
2.6%
기타단독정화조 7
 
2.3%
기타오수처리시설 5
 
1.6%
단독정화조 3
 
1.0%
임호프방식 1
 
0.3%
현수미생물접촉방법 1
 
0.3%
접촉폭기방법 1
 
0.3%

Length

2023-12-12T19:12:46.348049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:46.494682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부패탱크방법 218
71.7%
하수종말처리장연결 44
 
14.5%
na 16
 
5.3%
접촉산화방법 8
 
2.6%
기타단독정화조 7
 
2.3%
기타오수처리시설 5
 
1.6%
단독정화조 3
 
1.0%
임호프방식 1
 
0.3%
현수미생물접촉방법 1
 
0.3%
접촉폭기방법 1
 
0.3%

하수처리시설용량(세제곱미터)
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)92.3%
Missing278
Missing (%)91.4%
Infinite0
Infinite (%)0.0%
Mean52.617077
Minimum2.1
Maximum210.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:46.671734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.1
5-th percentile2.745
Q16.32
median20.105
Q368.79
95-th percentile187.5
Maximum210.33
Range208.23
Interquartile range (IQR)62.47

Descriptive statistics

Standard deviation64.388348
Coefficient of variation (CV)1.2237158
Kurtosis0.69290182
Mean52.617077
Median Absolute Deviation (MAD)16.51
Skewness1.3700536
Sum1368.044
Variance4145.8593
MonotonicityNot monotonic
2023-12-12T19:12:46.830843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
9.96 2
 
0.7%
2.1 2
 
0.7%
210.33 1
 
0.3%
129.24 1
 
0.3%
11.64 1
 
0.3%
136.017 1
 
0.3%
6.0 1
 
0.3%
20.0 1
 
0.3%
22.16 1
 
0.3%
4.68 1
 
0.3%
Other values (14) 14
 
4.6%
(Missing) 278
91.4%
ValueCountFrequency (%)
2.1 2
0.7%
4.68 1
0.3%
5.02 1
0.3%
5.129 1
0.3%
6.0 1
0.3%
6.14 1
0.3%
6.86 1
0.3%
9.96 2
0.7%
11.64 1
0.3%
14.019 1
0.3%
ValueCountFrequency (%)
210.33 1
0.3%
190.0 1
0.3%
180.0 1
0.3%
136.017 1
0.3%
129.24 1
0.3%
96.0 1
0.3%
71.0 1
0.3%
62.16 1
0.3%
62.0 1
0.3%
47.619 1
0.3%

주용도
Categorical

Distinct16
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
공동주택
112 
제1종근린생활시설
55 
제2종근린생활시설
40 
공장
31 
업무시설
27 
Other values (11)
39 

Length

Max length9
Median length4
Mean length5.4210526
Min length2

Unique

Unique6 ?
Unique (%)2.0%

Sample

1st row업무시설
2nd row제1종근린생활시설
3rd row제1종근린생활시설
4th row공동주택
5th row공동주택

Common Values

ValueCountFrequency (%)
공동주택 112
36.8%
제1종근린생활시설 55
18.1%
제2종근린생활시설 40
 
13.2%
공장 31
 
10.2%
업무시설 27
 
8.9%
단독주택 18
 
5.9%
의료시설 6
 
2.0%
자동차관련시설 4
 
1.3%
판매시설 3
 
1.0%
종교시설 2
 
0.7%
Other values (6) 6
 
2.0%

Length

2023-12-12T19:12:47.006951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 112
36.8%
제1종근린생활시설 55
18.1%
제2종근린생활시설 40
 
13.2%
공장 31
 
10.2%
업무시설 27
 
8.9%
단독주택 18
 
5.9%
의료시설 6
 
2.0%
자동차관련시설 4
 
1.3%
판매시설 3
 
1.0%
종교시설 2
 
0.7%
Other values (6) 6
 
2.0%

부속용도
Text

MISSING 

Distinct170
Distinct (%)62.3%
Missing31
Missing (%)10.2%
Memory size2.5 KiB
2023-12-12T19:12:47.215921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length33
Mean length13.395604
Min length2

Characters and Unicode

Total characters3657
Distinct characters131
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

Unique129 ?
Unique (%)47.3%

Sample

1st row오피스텔
2nd row사무실
3rd row사무실
4th row다세대주택-도시형생활주택단지형 다세대주택
5th row다세대주택-도시형생활주택 단지형다세대주택
ValueCountFrequency (%)
다세대주택 29
 
7.4%
및 24
 
6.1%
근린생활시설 16
 
4.1%
아파트 15
 
3.8%
제1종근린생활시설 11
 
2.8%
사무소 10
 
2.5%
제2종근린생활시설 10
 
2.5%
제1,2종근린생활시설 10
 
2.5%
공동주택(다세대주택 9
 
2.3%
8
 
2.0%
Other values (153) 252
64.0%
2023-12-12T19:12:47.661218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 243
 
6.6%
설 215
 
5.9%
, 168
 
4.6%
생 154
 
4.2%
주 153
 
4.2%
택 150
 
4.1%
활 143
 
3.9%
근 127
 
3.5%
121
 
3.3%
린 116
 
3.2%
Other values (121) 2067
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2940
80.4%
Other Punctuation 188
 
5.1%
Decimal Number 162
 
4.4%
Space Separator 121
 
3.3%
Close Punctuation 116
 
3.2%
Open Punctuation 114
 
3.1%
Dash Punctuation 16
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 243
 
8.3%
설 215
 
7.3%
생 154
 
5.2%
주 153
 
5.2%
택 150
 
5.1%
활 143
 
4.9%
근 127
 
4.3%
린 116
 
3.9%
종 106
 
3.6%
세 101
 
3.4%
Other values (106) 1432
48.7%
Decimal Number
ValueCountFrequency (%)
1 76
46.9%
2 73
45.1%
8 4
 
2.5%
9 3
 
1.9%
4 2
 
1.2%
7 2
 
1.2%
0 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 168
89.4%
/ 10
 
5.3%
. 7
 
3.7%
: 3
 
1.6%
Space Separator
ValueCountFrequency (%)
121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2940
80.4%
Common 717
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 243
 
8.3%
설 215
 
7.3%
생 154
 
5.2%
주 153
 
5.2%
택 150
 
5.1%
활 143
 
4.9%
근 127
 
4.3%
린 116
 
3.9%
종 106
 
3.6%
세 101
 
3.4%
Other values (106) 1432
48.7%
Common
ValueCountFrequency (%)
, 168
23.4%
121
16.9%
) 116
16.2%
( 114
15.9%
1 76
10.6%
2 73
10.2%
- 16
 
2.2%
/ 10
 
1.4%
. 7
 
1.0%
8 4
 
0.6%
Other values (5) 12
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2940
80.4%
ASCII 717
 
19.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 243
 
8.3%
설 215
 
7.3%
생 154
 
5.2%
주 153
 
5.2%
택 150
 
5.1%
활 143
 
4.9%
근 127
 
4.3%
린 116
 
3.9%
종 106
 
3.6%
세 101
 
3.4%
Other values (106) 1432
48.7%
ASCII
ValueCountFrequency (%)
, 168
23.4%
121
16.9%
) 116
16.2%
( 114
15.9%
1 76
10.6%
2 73
10.2%
- 16
 
2.2%
/ 10
 
1.4%
. 7
 
1.0%
8 4
 
0.6%
Other values (5) 12
 
1.7%

용도지역
Categorical

Distinct12
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
제2종일반주거지역
160 
일반상업지역
46 
일반공업지역
29 
제1종일반주거지역
18 
제3종일반주거지역
 
14
Other values (7)
37 

Length

Max length9
Median length9
Mean length7.8223684
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row일반상업지역
2nd row일반상업지역
3rd row일반상업지역
4th row준공업지역
5th row준공업지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 160
52.6%
일반상업지역 46
 
15.1%
일반공업지역 29
 
9.5%
제1종일반주거지역 18
 
5.9%
제3종일반주거지역 14
 
4.6%
준공업지역 12
 
3.9%
준주거지역 9
 
3.0%
중심상업지역 8
 
2.6%
유통상업지역 4
 
1.3%
<NA> 2
 
0.7%
Other values (2) 2
 
0.7%

Length

2023-12-12T19:12:47.842740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 160
52.6%
일반상업지역 46
 
15.1%
일반공업지역 29
 
9.5%
제1종일반주거지역 18
 
5.9%
제3종일반주거지역 14
 
4.6%
준공업지역 12
 
3.9%
준주거지역 9
 
3.0%
중심상업지역 8
 
2.6%
유통상업지역 4
 
1.3%
na 2
 
0.7%
Other values (2) 2
 
0.7%

용도지구
Categorical

IMBALANCE 

Distinct8
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
220 
방화지구
48 
시가지경관지구(일반)
 
21
최고고도지구
 
9
보금자리주택지구
 
2
Other values (3)
 
4

Length

Max length11
Median length4
Mean length4.6019737
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 220
72.4%
방화지구 48
 
15.8%
시가지경관지구(일반) 21
 
6.9%
최고고도지구 9
 
3.0%
보금자리주택지구 2
 
0.7%
시가지경관지구 2
 
0.7%
철도보호지구 1
 
0.3%
일반미관지구 1
 
0.3%

Length

2023-12-12T19:12:48.374503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:48.531102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
72.4%
방화지구 48
 
15.8%
시가지경관지구(일반 21
 
6.9%
최고고도지구 9
 
3.0%
보금자리주택지구 2
 
0.7%
시가지경관지구 2
 
0.7%
철도보호지구 1
 
0.3%
일반미관지구 1
 
0.3%

용도구역
Categorical

Distinct7
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
117 
항공표면
64 
지구단위계획구역
48 
상대보호구역
41 
중점경관관리구역
23 
Other values (2)
 
11

Length

Max length13
Median length4
Mean length5.4967105
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중점경관관리구역
2nd row지구단위계획구역
3rd row지구단위계획구역
4th row지구단위계획구역
5th row지구단위계획구역

Common Values

ValueCountFrequency (%)
<NA> 117
38.5%
항공표면 64
21.1%
지구단위계획구역 48
15.8%
상대보호구역 41
 
13.5%
중점경관관리구역 23
 
7.6%
토지거래계약에관한허가구역 6
 
2.0%
제1종지구단위계획구역 5
 
1.6%

Length

2023-12-12T19:12:48.720257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:48.873015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
38.5%
항공표면 64
21.1%
지구단위계획구역 48
15.8%
상대보호구역 41
 
13.5%
중점경관관리구역 23
 
7.6%
토지거래계약에관한허가구역 6
 
2.0%
제1종지구단위계획구역 5
 
1.6%

자주식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)45.1%
Missing140
Missing (%)46.1%
Infinite0
Infinite (%)0.0%
Mean109.90854
Minimum1
Maximum1716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:49.044373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16.75
median18
Q373.75
95-th percentile601.5
Maximum1716
Range1715
Interquartile range (IQR)67

Descriptive statistics

Standard deviation272.66782
Coefficient of variation (CV)2.4808612
Kurtosis17.132537
Mean109.90854
Median Absolute Deviation (MAD)14
Skewness4.0444246
Sum18025
Variance74347.74
MonotonicityNot monotonic
2023-12-12T19:12:49.238846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 12
 
3.9%
6 11
 
3.6%
3 9
 
3.0%
5 9
 
3.0%
7 8
 
2.6%
10 6
 
2.0%
4 5
 
1.6%
227 5
 
1.6%
2 5
 
1.6%
1201 4
 
1.3%
Other values (64) 90
29.6%
(Missing) 140
46.1%
ValueCountFrequency (%)
1 2
 
0.7%
2 5
1.6%
3 9
3.0%
4 5
1.6%
5 9
3.0%
6 11
3.6%
7 8
2.6%
8 12
3.9%
9 3
 
1.0%
10 6
2.0%
ValueCountFrequency (%)
1716 1
 
0.3%
1591 1
 
0.3%
1201 4
1.3%
721 1
 
0.3%
716 1
 
0.3%
615 1
 
0.3%
525 1
 
0.3%
415 1
 
0.3%
388 1
 
0.3%
316 1
 
0.3%

자주식옥외주차장(대)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)18.1%
Missing127
Missing (%)41.8%
Infinite0
Infinite (%)0.0%
Mean11.762712
Minimum1
Maximum256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:49.424095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q315
95-th percentile26
Maximum256
Range255
Interquartile range (IQR)11

Descriptive statistics

Standard deviation20.715337
Coefficient of variation (CV)1.7611021
Kurtosis111.11776
Mean11.762712
Median Absolute Deviation (MAD)5
Skewness9.6100077
Sum2082
Variance429.12519
MonotonicityNot monotonic
2023-12-12T19:12:49.608607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
2 19
 
6.2%
8 16
 
5.3%
12 13
 
4.3%
4 13
 
4.3%
3 12
 
3.9%
1 11
 
3.6%
5 10
 
3.3%
7 9
 
3.0%
9 7
 
2.3%
10 7
 
2.3%
Other values (22) 60
19.7%
(Missing) 127
41.8%
ValueCountFrequency (%)
1 11
3.6%
2 19
6.2%
3 12
3.9%
4 13
4.3%
5 10
3.3%
6 7
 
2.3%
7 9
3.0%
8 16
5.3%
9 7
 
2.3%
10 7
 
2.3%
ValueCountFrequency (%)
256 1
 
0.3%
74 1
 
0.3%
46 1
 
0.3%
33 1
 
0.3%
32 1
 
0.3%
30 1
 
0.3%
28 2
0.7%
26 4
1.3%
25 2
0.7%
24 3
1.0%

기계식옥내주차장(대)
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)75.0%
Missing288
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean140.1875
Minimum8
Maximum384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:49.770654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile17
Q148.5
median71
Q3182.25
95-th percentile384
Maximum384
Range376
Interquartile range (IQR)133.75

Descriptive statistics

Standard deviation148.16937
Coefficient of variation (CV)1.0569371
Kurtosis-0.57598554
Mean140.1875
Median Absolute Deviation (MAD)41.5
Skewness1.1380539
Sum2243
Variance21954.162
MonotonicityNot monotonic
2023-12-12T19:12:49.927938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
384 4
 
1.3%
70 2
 
0.7%
60 1
 
0.3%
54 1
 
0.3%
108 1
 
0.3%
20 1
 
0.3%
32 1
 
0.3%
115 1
 
0.3%
74 1
 
0.3%
24 1
 
0.3%
Other values (2) 2
 
0.7%
(Missing) 288
94.7%
ValueCountFrequency (%)
8 1
0.3%
20 1
0.3%
24 1
0.3%
32 1
0.3%
54 1
0.3%
60 1
0.3%
70 2
0.7%
72 1
0.3%
74 1
0.3%
108 1
0.3%
ValueCountFrequency (%)
384 4
1.3%
115 1
 
0.3%
108 1
 
0.3%
74 1
 
0.3%
72 1
 
0.3%
70 2
0.7%
60 1
 
0.3%
54 1
 
0.3%
32 1
 
0.3%
24 1
 
0.3%

인근자주식주차장(대)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
303 
270
 
1

Length

Max length4
Median length4
Mean length3.9967105
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 303
99.7%
270 1
 
0.3%

Length

2023-12-12T19:12:50.118938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:50.238803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 303
99.7%
270 1
 
0.3%

총주차대수
Real number (ℝ)

MISSING  ZEROS 

Distinct87
Distinct (%)31.4%
Missing27
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean81.66065
Minimum0
Maximum1972
Zeros17
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:50.401638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median12
Q336
95-th percentile282.4
Maximum1972
Range1972
Interquartile range (IQR)28

Descriptive statistics

Standard deviation254.55652
Coefficient of variation (CV)3.1172483
Kurtosis31.266833
Mean81.66065
Median Absolute Deviation (MAD)10
Skewness5.4473075
Sum22620
Variance64799.022
MonotonicityNot monotonic
2023-12-12T19:12:50.568857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 37
 
12.2%
0 17
 
5.6%
12 14
 
4.6%
10 11
 
3.6%
4 10
 
3.3%
2 10
 
3.3%
7 8
 
2.6%
9 6
 
2.0%
14 6
 
2.0%
1 6
 
2.0%
Other values (77) 152
50.0%
(Missing) 27
 
8.9%
ValueCountFrequency (%)
0 17
5.6%
1 6
 
2.0%
2 10
 
3.3%
3 6
 
2.0%
4 10
 
3.3%
5 6
 
2.0%
6 5
 
1.6%
7 8
 
2.6%
8 37
12.2%
9 6
 
2.0%
ValueCountFrequency (%)
1972 1
 
0.3%
1591 1
 
0.3%
1585 4
1.3%
736 1
 
0.3%
716 1
 
0.3%
615 1
 
0.3%
525 1
 
0.3%
415 1
 
0.3%
388 1
 
0.3%
341 1
 
0.3%

총주차장면적(제곱미터)
Real number (ℝ)

MISSING  ZEROS 

Distinct152
Distinct (%)54.9%
Missing27
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean1514.4563
Minimum0
Maximum47361.182
Zeros67
Zeros (%)22.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:50.738737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.5
median121.46
Q3336.96
95-th percentile3783.8
Maximum47361.182
Range47361.182
Interquartile range (IQR)324.46

Descriptive statistics

Standard deviation6489.5235
Coefficient of variation (CV)4.2850518
Kurtosis39.073597
Mean1514.4563
Median Absolute Deviation (MAD)121.46
Skewness6.1954673
Sum419504.38
Variance42113915
MonotonicityNot monotonic
2023-12-12T19:12:50.883534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 67
 
22.0%
100.0 11
 
3.6%
50.0 6
 
2.0%
25.0 5
 
1.6%
47361.182 4
 
1.3%
123.7 4
 
1.3%
148.7 3
 
1.0%
12.5 3
 
1.0%
318.4 3
 
1.0%
87.5 3
 
1.0%
Other values (142) 168
55.3%
(Missing) 27
 
8.9%
ValueCountFrequency (%)
0.0 67
22.0%
11.5 2
 
0.7%
12.5 3
 
1.0%
23.0 3
 
1.0%
25.0 5
 
1.6%
33.0 1
 
0.3%
34.5 1
 
0.3%
35.7 1
 
0.3%
37.0 2
 
0.7%
37.5 2
 
0.7%
ValueCountFrequency (%)
47361.182 4
1.3%
36258.02 1
 
0.3%
32593.29 1
 
0.3%
18736.8 1
 
0.3%
11906.83 1
 
0.3%
8692.9 1
 
0.3%
7043.78 1
 
0.3%
6753.11 1
 
0.3%
6201.43 1
 
0.3%
5816.28 1
 
0.3%

세대수
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)21.3%
Missing177
Missing (%)58.2%
Infinite0
Infinite (%)0.0%
Mean20.480315
Minimum0
Maximum172
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:51.031028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q18
median9
Q324
95-th percentile58.2
Maximum172
Range172
Interquartile range (IQR)16

Descriptive statistics

Standard deviation32.780862
Coefficient of variation (CV)1.6006034
Kurtosis16.033517
Mean20.480315
Median Absolute Deviation (MAD)3
Skewness4.0024599
Sum2601
Variance1074.5849
MonotonicityNot monotonic
2023-12-12T19:12:51.183744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
8 40
 
13.2%
12 11
 
3.6%
7 8
 
2.6%
10 8
 
2.6%
6 7
 
2.3%
29 6
 
2.0%
28 5
 
1.6%
172 5
 
1.6%
4 5
 
1.6%
20 5
 
1.6%
Other values (17) 27
 
8.9%
(Missing) 177
58.2%
ValueCountFrequency (%)
0 1
 
0.3%
1 2
 
0.7%
4 5
 
1.6%
6 7
 
2.3%
7 8
 
2.6%
8 40
13.2%
9 1
 
0.3%
10 8
 
2.6%
12 11
 
3.6%
15 1
 
0.3%
ValueCountFrequency (%)
172 5
1.6%
75 1
 
0.3%
60 1
 
0.3%
54 1
 
0.3%
36 1
 
0.3%
32 1
 
0.3%
29 6
2.0%
28 5
1.6%
27 1
 
0.3%
26 5
1.6%

호수
Categorical

IMBALANCE 

Distinct37
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
215 
1
30 
2
 
10
4
 
7
1,842
 
4
Other values (32)
38 

Length

Max length5
Median length4
Mean length3.3059211
Min length1

Unique

Unique28 ?
Unique (%)9.2%

Sample

1st row38
2nd row99
3rd row99
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 215
70.7%
1 30
 
9.9%
2 10
 
3.3%
4 7
 
2.3%
1,842 4
 
1.3%
99 4
 
1.3%
35 2
 
0.7%
25 2
 
0.7%
3 2
 
0.7%
24 1
 
0.3%
Other values (27) 27
 
8.9%

Length

2023-12-12T19:12:51.340307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 215
70.7%
1 30
 
9.9%
2 10
 
3.3%
4 7
 
2.3%
1,842 4
 
1.3%
99 4
 
1.3%
35 2
 
0.7%
25 2
 
0.7%
3 2
 
0.7%
84 1
 
0.3%
Other values (27) 27
 
8.9%

가구수
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)25.9%
Missing277
Missing (%)91.1%
Infinite0
Infinite (%)0.0%
Mean17.62963
Minimum1
Maximum414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T19:12:51.499535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile14.4
Maximum414
Range413
Interquartile range (IQR)2

Descriptive statistics

Standard deviation79.287766
Coefficient of variation (CV)4.4974153
Kurtosis26.889564
Mean17.62963
Median Absolute Deviation (MAD)0
Skewness5.1811239
Sum476
Variance6286.5499
MonotonicityNot monotonic
2023-12-12T19:12:51.654203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 17
 
5.6%
3 4
 
1.3%
2 2
 
0.7%
6 1
 
0.3%
18 1
 
0.3%
5 1
 
0.3%
414 1
 
0.3%
(Missing) 277
91.1%
ValueCountFrequency (%)
1 17
5.6%
2 2
 
0.7%
3 4
 
1.3%
5 1
 
0.3%
6 1
 
0.3%
18 1
 
0.3%
414 1
 
0.3%
ValueCountFrequency (%)
414 1
 
0.3%
18 1
 
0.3%
6 1
 
0.3%
5 1
 
0.3%
3 4
 
1.3%
2 2
 
0.7%
1 17
5.6%

주건축물수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
1
285 
2
 
10
<NA>
 
6
21
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.0657895
Min length1

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 285
93.8%
2 10
 
3.3%
<NA> 6
 
2.0%
21 1
 
0.3%
3 1
 
0.3%
10 1
 
0.3%

Length

2023-12-12T19:12:51.801928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:51.959542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 285
93.8%
2 10
 
3.3%
na 6
 
2.0%
21 1
 
0.3%
3 1
 
0.3%
10 1
 
0.3%

부속건축물수
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
285 
1
 
12
0
 
7

Length

Max length4
Median length4
Mean length3.8125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 285
93.8%
1 12
 
3.9%
0 7
 
2.3%

Length

2023-12-12T19:12:52.133670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:52.295635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 285
93.8%
1 12
 
3.9%
0 7
 
2.3%

Sample

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수
0신축경기도 부천시 심곡동 176-14 외1필지대471.7350.784185.0<NA>74.37684.25철근콘크리트구조2022-04-082022-08-19<NA>14143.111<NA>부패탱크방법<NA>업무시설오피스텔일반상업지역방화지구중점경관관리구역308<NA><NA>38463.1<NA>38<NA>1<NA>
1용도변경경기도 부천시 심곡동 194대4413.222405.524535.68<NA>507.6933102.7753철근콘크리트구조2022-04-08<NA><NA>2<NA>0.01<NA><NA><NA><NA>제1종근린생활시설사무실일반상업지역방화지구지구단위계획구역<NA><NA><NA><NA><NA><NA><NA>99<NA>1<NA>
2용도변경경기도 부천시 심곡동 194대4413.222405.524535.68<NA>507.6933102.7753철근콘크리트구조2022-04-08<NA><NA>2<NA>0.010<NA><NA><NA>제1종근린생활시설사무실일반상업지역방화지구지구단위계획구역<NA><NA><NA><NA><NA><NA><NA>99<NA>1<NA>
3신축경기도 부천시 송내동 388-9대306.0167.15478.74<NA>54.62156.45철근콘크리트구조2022-04-082022-05-032023-01-195015.911<NA>부패탱크방법<NA>공동주택다세대주택-도시형생활주택단지형 다세대주택준공업지역<NA>지구단위계획구역<NA>16<NA><NA>16198.28<NA><NA>1<NA>
4신축경기도 부천시 송내동 388-10대249.6166.17499.9<NA>66.57200.28철근콘크리트구조2022-04-082022-05-032023-01-195015.911<NA>부패탱크방법<NA>공동주택다세대주택-도시형생활주택 단지형다세대주택준공업지역<NA>지구단위계획구역<NA>16<NA><NA>16198.28<NA><NA>1<NA>
5용도변경경기도 부천시 심곡동 194대4413.222405.524535.68<NA>507.6933102.7753철근콘크리트구조2022-04-11<NA><NA>2<NA>0.01<NA><NA><NA><NA>제1종근린생활시설사무실일반상업지역방화지구지구단위계획구역<NA><NA><NA><NA><NA><NA><NA>99<NA>1<NA>
6용도변경경기도 부천시 중동 1033대1144.6801.286545.95<NA>70.0413.69<NA>2022-04-11<NA><NA>6223.5512<NA>기타오수처리시설<NA>업무시설제1,2종근린생활시설, 교육연구시설일반상업지역방화지구중점경관관리구역<NA>460<NA>64789.3<NA>28<NA>1<NA>
7용도변경경기도 부천시 심곡본동 736-14대158.6109.09327.27<NA>68.78206.35철근콘크리트구조2022-04-11<NA><NA>3<NA>12.01<NA><NA>부패탱크방법<NA>제1종근린생활시설및 제2종근린생활시설일반상업지역방화지구<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>
8신축경기도 부천시 송내동 577-2대1042.5746.8514219.73<NA>71.64899.71철근콘크리트구조2022-04-122022-10-13<NA>19368.2111부패탱크방법<NA>업무시설근린생활시설/업무시설/공동주택일반상업지역방화지구<NA>111<NA><NA><NA>1110.03263<NA>1<NA>
9신축경기도 부천시 역곡동 32-19대186.5110.2441.82<NA>59.09226.32철근콘크리트구조2022-04-122022-05-102022-11-285116.8511<NA>부패탱크방법<NA>공동주택다세대주택 및 1종근린생활시설-소매점제2종일반주거지역<NA>중점경관관리구역<NA>4<NA><NA>450.042<NA>1<NA>
건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수
294용도변경경기도 부천시 중동 1035-1대1374.01087.564041.6<NA>79.15294.15철근콘크리트구조2023-02-23<NA><NA>6<NA>26.111<NA>하수종말처리장연결<NA>제2종근린생활시설제1.2종근생,교육연구시설,운동시설일반상업지역<NA>지구단위계획구역<NA>32<NA><NA>320.0<NA><NA><NA>1<NA>
295증축경기도 부천시 춘의동 205-8 외1필지대1144.6296.67312.28196.5225.919127.2829일반철골구조2023-02-232023-03-16<NA>2<NA>5.951<NA><NA>부패탱크방법<NA>자동차관련시설세차장 / 제1종근린생활시설(소매점)준공업지역<NA>지구단위계획구역<NA>2<NA><NA>223.0<NA>1<NA>1<NA>
296증축경기도 부천시 도당동 222 외9필지공장용지54029.920894.4362381.87139.9938.67292.8651철근콘크리트구조2023-03-02<NA><NA>1<NA>5.6100<NA>부패탱크방법<NA>공장<NA>일반공업지역최고고도지구항공표면316<NA><NA><NA>3163634.0<NA><NA><NA>10<NA>
297용도변경경기도 부천시 심곡동 165대183.2128.38458.44<NA>70.08170.71철근콘크리트구조2023-03-03<NA><NA>310.010<NA>부패탱크방법<NA>제2종근린생활시설제1.2종근린생활시설준주거지역<NA><NA><NA><NA><NA><NA>00.0<NA><NA><NA>1<NA>
298용도변경경기도 부천시 상동 564-7대215.0128.19361.2<NA>59.62168철근콘크리트구조2023-03-07<NA><NA>3<NA>10.810<NA>하수종말처리장연결<NA>단독주택다가구 주택 및 제2종근린생활시설(수리점)제1종일반주거지역<NA>지구단위계획구역<NA>3<NA><NA>334.5<NA><NA>31<NA>
299신축경기도 부천시 옥길동 491-4 외1필지전645.4320.76495.61<NA>49.776.79일반철골구조2023-03-09<NA><NA>2011.71<NA><NA>부패탱크방법<NA>제1종근린생활시설<NA>제1종일반주거지역<NA>지구단위계획구역<NA>4<NA><NA>450.0<NA><NA><NA>1<NA>
300신축경기도 부천시 내동 19-1 외1필지대295.3170.1632.35<NA>57.6214.14철근콘크리트구조2023-03-09<NA><NA>5017.111<NA>부패탱크방법<NA>공동주택다세대주택--도시형생활주택 단지형다세대주택제2종일반주거지역<NA>항공표면8<NA><NA><NA>8100.08<NA><NA>1<NA>
301신축경기도 부천시 고강동 393-6 외5필지대982.8453.62298.186<NA>46.15229.33철근콘크리트구조2023-03-10<NA><NA>8124.911<NA>부패탱크방법<NA>공동주택공동주택(아파트)제2종일반주거지역<NA>항공표면624<NA><NA>30342.4261<NA>1<NA>
302신축경기도 부천시 중동 789-3 외6필지대860.1240.832051.41<NA>28.0229.9철근콘크리트구조2023-03-16<NA><NA>14141.311<NA>부패탱크방법<NA>공동주택아파트제2종일반주거지역<NA>상대보호구역<NA>26<NA><NA>26318.426<NA><NA>1<NA>
303용도변경경기도 부천시 중동 1125대930.5649.67276.64<NA>69.81605.32<NA>2023-03-18<NA><NA>9234.312<NA>하수종말처리장연결<NA>제1종근린생활시설제2종근린생활시설,업무시설,노유자시설중심상업지역방화지구지구단위계획구역44<NA><NA><NA>441554.54<NA><NA><NA>1<NA>

Duplicate rows

Most frequently occurring

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수최고높이(미터)동수승강기합비상승강기합하수처리시설명하수처리시설용량(세제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)인근자주식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수# duplicates
1용도변경경기도 부천시 범박동 155-2대6317.93269.334107.01<NA>51.7466285.1656철골철근콘크리트구조2022-07-22<NA><NA>7442.3516<NA>접촉산화방법<NA>제2종근린생활시설제1,2종근린생활시설,판매및영업시설,업무시설,교육연구및복지시설,노유자시설,운동시설제3종일반주거지역<NA>상대보호구역227<NA><NA><NA>2270.0172<NA><NA>103
0신축경기도 부천시 도당동 283-7대702.5271.071743.17<NA>38.59226.48철근콘크리트구조2022-09-30<NA><NA>11132.611<NA>부패탱크방법<NA>공동주택아파트제2종일반주거지역<NA>항공표면21<NA><NA><NA>21255.920<NA><NA>1<NA>2