Overview

Dataset statistics

Number of variables25
Number of observations31
Missing cells39
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory217.3 B

Variable types

Categorical11
Text5
Numeric9

Dataset

Description부산광역시_기장군_건축허가현황_201710
Author부산광역시 기장군
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3082033

Alerts

용도지구 has constant value ""Constant
세대수 is highly imbalanced (74.2%)Imbalance
호수 is highly imbalanced (79.4%)Imbalance
부속용도 has 7 (22.6%) missing valuesMissing
용도지구 has 30 (96.8%) missing valuesMissing
총주차대수 has 2 (6.5%) missing valuesMissing
허가번호 has unique valuesUnique
대지위치 has unique valuesUnique
대지면적(㎡) has unique valuesUnique
건축면적(㎡) has unique valuesUnique
연면적(㎡) has unique valuesUnique
건폐율(%) has unique valuesUnique
용적률(%) has unique valuesUnique
동수 has 3 (9.7%) zerosZeros

Reproduction

Analysis started2023-12-10 16:56:17.499654
Analysis finished2023-12-10 16:56:17.843674
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
신축
21 
증축
7 
용도변경
 
2
개축
 
1

Length

Max length4
Median length2
Mean length2.1290323
Min length2

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
신축 21
67.7%
증축 7
 
22.6%
용도변경 2
 
6.5%
개축 1
 
3.2%

Length

2023-12-11T01:56:17.921387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:18.031000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 21
67.7%
증축 7
 
22.6%
용도변경 2
 
6.5%
개축 1
 
3.2%

허가번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T01:56:18.230184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length19.032258
Min length18

Characters and Unicode

Total characters590
Distinct characters36
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

Unique31 ?
Unique (%)100.0%

Sample

1st row2017-창조건축과-신축허가-291
2nd row2017-창조건축과-신축허가-287
3rd row2017-창조건축과-신축허가-288
4th row2017-창조건축과-신축허가-289
5th row2017-창조건축과-신축허가-290
ValueCountFrequency (%)
2017-창조건축과-신축허가-291 1
 
3.1%
2017-창조건축과-신축허가-287 1
 
3.1%
2017-창조건축과-신축허가-272 1
 
3.1%
2017-창조건축과-신축허가-271 1
 
3.1%
2017-창조건축과-증축허가-45 1
 
3.1%
2017-창조건축과-용도변경허가-39 1
 
3.1%
2017-창조건축과-신축허가-274 1
 
3.1%
2017-창조건축과-신축허가-276 1
 
3.1%
2017-창조건축과-신축허가-275 1
 
3.1%
2017-창조건축과-신축허가-278 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T01:56:18.620658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 93
15.8%
축 60
10.2%
2 54
 
9.2%
7 44
 
7.5%
1 35
 
5.9%
0 35
 
5.9%
건 34
 
5.8%
창 31
 
5.3%
조 31
 
5.3%
과 31
 
5.3%
Other values (26) 142
24.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
49.5%
Decimal Number 204
34.6%
Dash Punctuation 93
 
15.8%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 60
20.5%
건 34
11.6%
창 31
10.6%
조 31
10.6%
과 31
10.6%
허 29
9.9%
가 29
9.9%
신 20
 
6.8%
증 6
 
2.1%
용 3
 
1.0%
Other values (14) 18
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 54
26.5%
7 44
21.6%
1 35
17.2%
0 35
17.2%
8 12
 
5.9%
4 8
 
3.9%
9 6
 
2.9%
5 4
 
2.0%
6 3
 
1.5%
3 3
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 298
50.5%
Hangul 292
49.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 60
20.5%
건 34
11.6%
창 31
10.6%
조 31
10.6%
과 31
10.6%
허 29
9.9%
가 29
9.9%
신 20
 
6.8%
증 6
 
2.1%
용 3
 
1.0%
Other values (14) 18
 
6.2%
Common
ValueCountFrequency (%)
- 93
31.2%
2 54
18.1%
7 44
14.8%
1 35
 
11.7%
0 35
 
11.7%
8 12
 
4.0%
4 8
 
2.7%
9 6
 
2.0%
5 4
 
1.3%
6 3
 
1.0%
Other values (2) 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298
50.5%
Hangul 292
49.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 93
31.2%
2 54
18.1%
7 44
14.8%
1 35
 
11.7%
0 35
 
11.7%
8 12
 
4.0%
4 8
 
2.7%
9 6
 
2.0%
5 4
 
1.3%
6 3
 
1.0%
Other values (2) 4
 
1.3%
Hangul
ValueCountFrequency (%)
축 60
20.5%
건 34
11.6%
창 31
10.6%
조 31
10.6%
과 31
10.6%
허 29
9.9%
가 29
9.9%
신 20
 
6.8%
증 6
 
2.1%
용 3
 
1.0%
Other values (14) 18
 
6.2%

대지위치
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T01:56:18.887403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length24.258065
Min length20

Characters and Unicode

Total characters752
Distinct characters71
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row부산광역시 기장군 기장읍 대라리 176-9
2nd row부산광역시 기장군 장안읍 좌천리 278-2
3rd row부산광역시 기장군 정관읍 달산리 1018-3
4th row부산광역시 기장군 정관읍 달산리 1018-4
5th row부산광역시 기장군 정관읍 병산리 266-5
ValueCountFrequency (%)
부산광역시 31
19.0%
기장군 31
19.0%
정관읍 11
 
6.7%
기장읍 7
 
4.3%
달산리 6
 
3.7%
장안읍 6
 
3.7%
일광면 5
 
3.1%
문동리 2
 
1.2%
반룡리 2
 
1.2%
철마면 2
 
1.2%
Other values (57) 60
36.8%
2023-12-11T01:56:19.299847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
17.6%
장 44
 
5.9%
산 41
 
5.5%
기 39
 
5.2%
광 37
 
4.9%
시 34
 
4.5%
부 32
 
4.3%
역 32
 
4.3%
군 31
 
4.1%
리 31
 
4.1%
Other values (61) 299
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
62.8%
Space Separator 132
 
17.6%
Decimal Number 121
 
16.1%
Dash Punctuation 26
 
3.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 44
 
9.3%
산 41
 
8.7%
기 39
 
8.3%
광 37
 
7.8%
시 34
 
7.2%
부 32
 
6.8%
역 32
 
6.8%
군 31
 
6.6%
리 31
 
6.6%
읍 24
 
5.1%
Other values (48) 127
26.9%
Decimal Number
ValueCountFrequency (%)
1 29
24.0%
4 15
12.4%
3 13
10.7%
7 12
9.9%
2 12
9.9%
6 10
 
8.3%
8 10
 
8.3%
0 8
 
6.6%
5 7
 
5.8%
9 5
 
4.1%
Space Separator
ValueCountFrequency (%)
132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
62.8%
Common 279
37.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 44
 
9.3%
산 41
 
8.7%
기 39
 
8.3%
광 37
 
7.8%
시 34
 
7.2%
부 32
 
6.8%
역 32
 
6.8%
군 31
 
6.6%
리 31
 
6.6%
읍 24
 
5.1%
Other values (48) 127
26.9%
Common
ValueCountFrequency (%)
132
47.3%
1 29
 
10.4%
- 26
 
9.3%
4 15
 
5.4%
3 13
 
4.7%
7 12
 
4.3%
2 12
 
4.3%
6 10
 
3.6%
8 10
 
3.6%
0 8
 
2.9%
Other values (2) 12
 
4.3%
Latin
ValueCountFrequency (%)
K 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
62.8%
ASCII 280
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
47.1%
1 29
 
10.4%
- 26
 
9.3%
4 15
 
5.4%
3 13
 
4.6%
7 12
 
4.3%
2 12
 
4.3%
6 10
 
3.6%
8 10
 
3.6%
0 8
 
2.9%
Other values (3) 13
 
4.6%
Hangul
ValueCountFrequency (%)
장 44
 
9.3%
산 41
 
8.7%
기 39
 
8.3%
광 37
 
7.8%
시 34
 
7.2%
부 32
 
6.8%
역 32
 
6.8%
군 31
 
6.6%
리 31
 
6.6%
읍 24
 
5.1%
Other values (48) 127
26.9%

지목
Categorical

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
대
16 
공장용지
7 
전
2 
임야
2 
주차장
 
1
Other values (3)
3 

Length

Max length5
Median length1
Mean length2.0967742
Min length1

Unique

Unique4 ?
Unique (%)12.9%

Sample

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

Common Values

ValueCountFrequency (%)
대 16
51.6%
공장용지 7
22.6%
전 2
 
6.5%
임야 2
 
6.5%
주차장 1
 
3.2%
주유소용지 1
 
3.2%
잡종지 1
 
3.2%
<NA> 1
 
3.2%

Length

2023-12-11T01:56:19.528364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:19.704410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 16
51.6%
공장용지 7
22.6%
전 2
 
6.5%
임야 2
 
6.5%
주차장 1
 
3.2%
주유소용지 1
 
3.2%
잡종지 1
 
3.2%
na 1
 
3.2%

대지면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39144.916
Minimum139
Maximum948613
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:19.853885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139
5-th percentile183.85
Q1247
median724
Q35476.5
95-th percentile100261.75
Maximum948613
Range948474
Interquartile range (IQR)5229.5

Descriptive statistics

Standard deviation171989.22
Coefficient of variation (CV)4.3936541
Kurtosis28.539104
Mean39144.916
Median Absolute Deviation (MAD)552.3
Skewness5.2804016
Sum1213492.4
Variance2.9580292 × 1010
MonotonicityNot monotonic
2023-12-11T01:56:19.984260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
396.0 1
 
3.2%
305.5 1
 
3.2%
227.0 1
 
3.2%
171.7 1
 
3.2%
1484.0 1
 
3.2%
8260.4 1
 
3.2%
139.0 1
 
3.2%
236.0 1
 
3.2%
5096.0 1
 
3.2%
205.4 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
139.0 1
3.2%
171.7 1
3.2%
196.0 1
3.2%
205.4 1
3.2%
208.4 1
3.2%
211.5 1
3.2%
227.0 1
3.2%
236.0 1
3.2%
258.0 1
3.2%
305.5 1
3.2%
ValueCountFrequency (%)
948613.0 1
3.2%
185310.0 1
3.2%
15213.5 1
3.2%
14995.0 1
3.2%
8260.4 1
3.2%
6858.0 1
3.2%
6840.9 1
3.2%
5857.0 1
3.2%
5096.0 1
3.2%
3248.2 1
3.2%

건축면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5379.2018
Minimum56.1
Maximum110572.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:20.109567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56.1
5-th percentile84.645
Q1125.1
median210.89
Q31364.35
95-th percentile14756.16
Maximum110572.57
Range110516.47
Interquartile range (IQR)1239.25

Descriptive statistics

Standard deviation19963.52
Coefficient of variation (CV)3.7112422
Kurtosis28.090992
Mean5379.2018
Median Absolute Deviation (MAD)154.79
Skewness5.2190908
Sum166755.26
Variance3.9854215 × 108
MonotonicityNot monotonic
2023-12-11T01:56:20.256901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
210.89 1
 
3.2%
179.23 1
 
3.2%
97.2 1
 
3.2%
99.17 1
 
3.2%
829.98 1
 
3.2%
5773.26 1
 
3.2%
56.1 1
 
3.2%
139.76 1
 
3.2%
2794.94 1
 
3.2%
123.04 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
56.1 1
3.2%
72.09 1
3.2%
97.2 1
3.2%
99.17 1
3.2%
103.1 1
3.2%
116.75 1
3.2%
123.04 1
3.2%
124.2 1
3.2%
126.0 1
3.2%
139.76 1
3.2%
ValueCountFrequency (%)
110572.57 1
3.2%
21792.61 1
3.2%
7719.71 1
3.2%
5773.26 1
3.2%
5367.06 1
3.2%
3952.57 1
3.2%
2794.94 1
3.2%
1552.96 1
3.2%
1175.74 1
3.2%
945.36 1
3.2%

연면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12399.817
Minimum56.1
Maximum235496.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:20.392863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum56.1
5-th percentile137.885
Q1204.445
median414
Q33434.18
95-th percentile51967.97
Maximum235496.83
Range235440.73
Interquartile range (IQR)3229.735

Descriptive statistics

Standard deviation43333.825
Coefficient of variation (CV)3.4947149
Kurtosis25.346188
Mean12399.817
Median Absolute Deviation (MAD)271.8
Skewness4.8992834
Sum384394.32
Variance1.8778204 × 109
MonotonicityNot monotonic
2023-12-11T01:56:20.531003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
210.89 1
 
3.2%
178.77 1
 
3.2%
142.2 1
 
3.2%
254.75 1
 
3.2%
939.96 1
 
3.2%
6725.62 1
 
3.2%
56.1 1
 
3.2%
353.27 1
 
3.2%
5100.44 1
 
3.2%
306.32 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
56.1 1
3.2%
133.57 1
3.2%
142.2 1
3.2%
147.84 1
3.2%
152.19 1
3.2%
178.77 1
3.2%
186.93 1
3.2%
198.0 1
3.2%
210.89 1
3.2%
229.69 1
3.2%
ValueCountFrequency (%)
235496.83 1
3.2%
53257.1 1
3.2%
50678.84 1
3.2%
8605.4 1
3.2%
7659.33 1
3.2%
6725.62 1
3.2%
5100.44 1
3.2%
4065.32 1
3.2%
2803.04 1
3.2%
2013.72 1
3.2%

건폐율(%)
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.603806
Minimum7.8409
Maximum78.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:20.699082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.8409
5-th percentile10.975
Q131.3
median51.55
Q359.23195
95-th percentile64.8963
Maximum78.46
Range70.6191
Interquartile range (IQR)27.93195

Descriptive statistics

Standard deviation20.263836
Coefficient of variation (CV)0.45430733
Kurtosis-0.75418155
Mean44.603806
Median Absolute Deviation (MAD)8.05
Skewness-0.7168635
Sum1382.718
Variance410.62306
MonotonicityNot monotonic
2023-12-11T01:56:20.888191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
53.26 1
 
3.2%
58.6678 1
 
3.2%
42.82 1
 
3.2%
57.7577 1
 
3.2%
55.93 1
 
3.2%
69.89 1
 
3.2%
40.36 1
 
3.2%
59.22 1
 
3.2%
54.85 1
 
3.2%
59.9026 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
7.8409 1
3.2%
10.45 1
3.2%
11.5 1
3.2%
11.65 1
3.2%
11.76 1
3.2%
12.6 1
3.2%
19.13 1
3.2%
22.64 1
3.2%
39.96 1
3.2%
40.36 1
3.2%
ValueCountFrequency (%)
78.46 1
3.2%
69.89 1
3.2%
59.9026 1
3.2%
59.886 1
3.2%
59.6 1
3.2%
59.57 1
3.2%
59.5663 1
3.2%
59.2439 1
3.2%
59.22 1
3.2%
58.6678 1
3.2%

용적률(%)
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.59762
Minimum6.8128
Maximum760.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:21.065758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8128
5-th percentile10.975
Q131.3985
median58.5172
Q3136.86
95-th percentile237.845
Maximum760.01
Range753.1972
Interquartile range (IQR)105.4615

Descriptive statistics

Standard deviation139.07431
Coefficient of variation (CV)1.3296126
Kurtosis17.087898
Mean104.59762
Median Absolute Deviation (MAD)41.5728
Skewness3.7875927
Sum3242.5262
Variance19341.665
MonotonicityNot monotonic
2023-12-11T01:56:21.238030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
53.26 1
 
3.2%
58.5172 1
 
3.2%
62.64 1
 
3.2%
148.3692 1
 
3.2%
55.93 1
 
3.2%
81.42 1
 
3.2%
40.36 1
 
3.2%
149.69 1
 
3.2%
100.09 1
 
3.2%
149.1334 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
6.8128 1
3.2%
10.45 1
3.2%
11.5 1
3.2%
17.23 1
3.2%
19.13 1
3.2%
21.02 1
3.2%
22.93 1
3.2%
23.9869 1
3.2%
38.8101 1
3.2%
40.36 1
3.2%
ValueCountFrequency (%)
760.01 1
3.2%
326.0 1
3.2%
149.69 1
3.2%
149.2152 1
3.2%
149.1334 1
3.2%
148.65 1
3.2%
148.3692 1
3.2%
136.87 1
3.2%
136.85 1
3.2%
123.4626 1
3.2%

구조
Categorical

Distinct8
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
철근콘크리트구조
12 
일반철골구조
9 
철골콘크리트구조
3 
경량철골구조
3 
벽돌구조
 
1
Other values (3)
3 

Length

Max length12
Median length8
Mean length7
Min length4

Unique

Unique4 ?
Unique (%)12.9%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 12
38.7%
일반철골구조 9
29.0%
철골콘크리트구조 3
 
9.7%
경량철골구조 3
 
9.7%
벽돌구조 1
 
3.2%
철골철근콘크리트합성구조 1
 
3.2%
일반목구조 1
 
3.2%
블록구조 1
 
3.2%

Length

2023-12-11T01:56:21.477240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:21.663411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 12
38.7%
일반철골구조 9
29.0%
철골콘크리트구조 3
 
9.7%
경량철골구조 3
 
9.7%
벽돌구조 1
 
3.2%
철골철근콘크리트합성구조 1
 
3.2%
일반목구조 1
 
3.2%
블록구조 1
 
3.2%

허가일
Categorical

Distinct12
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
2017-10-10
5 
2017-10-30
4 
2017-10-26
4 
2017-10-23
3 
2017-10-17
3 
Other values (7)
12 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row2017-10-31
2nd row2017-10-30
3rd row2017-10-30
4th row2017-10-30
5th row2017-10-30

Common Values

ValueCountFrequency (%)
2017-10-10 5
16.1%
2017-10-30 4
12.9%
2017-10-26 4
12.9%
2017-10-23 3
9.7%
2017-10-17 3
9.7%
2017-10-13 3
9.7%
2017-10-25 2
 
6.5%
2017-10-16 2
 
6.5%
2017-10-12 2
 
6.5%
2017-10-31 1
 
3.2%
Other values (2) 2
 
6.5%

Length

2023-12-11T01:56:21.851480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-10-10 5
16.1%
2017-10-30 4
12.9%
2017-10-26 4
12.9%
2017-10-23 3
9.7%
2017-10-17 3
9.7%
2017-10-13 3
9.7%
2017-10-25 2
 
6.5%
2017-10-16 2
 
6.5%
2017-10-12 2
 
6.5%
2017-10-31 1
 
3.2%
Other values (2) 2
 
6.5%

최대지상층수
Real number (ℝ)

Distinct7
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7419355
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:22.020180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.5
95-th percentile7
Maximum10
Range9
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation2.1751282
Coefficient of variation (CV)0.79328206
Kurtosis4.7715819
Mean2.7419355
Median Absolute Deviation (MAD)1
Skewness2.0373893
Sum85
Variance4.7311828
MonotonicityNot monotonic
2023-12-11T01:56:22.184397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 11
35.5%
2 6
19.4%
3 6
19.4%
4 5
16.1%
10 1
 
3.2%
5 1
 
3.2%
9 1
 
3.2%
ValueCountFrequency (%)
1 11
35.5%
2 6
19.4%
3 6
19.4%
4 5
16.1%
5 1
 
3.2%
9 1
 
3.2%
10 1
 
3.2%
ValueCountFrequency (%)
10 1
 
3.2%
9 1
 
3.2%
5 1
 
3.2%
4 5
16.1%
3 6
19.4%
2 6
19.4%
1 11
35.5%

최대지하층수
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
0
18 
1
6 
<NA>
6 
2
 
1

Length

Max length4
Median length1
Mean length1.5806452
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 18
58.1%
1 6
 
19.4%
<NA> 6
 
19.4%
2 1
 
3.2%

Length

2023-12-11T01:56:22.385906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:22.570472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
58.1%
1 6
 
19.4%
na 6
 
19.4%
2 1
 
3.2%

최고높이(m)
Real number (ℝ)

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.320645
Minimum4.13
Maximum40.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:22.724285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.13
5-th percentile4.7
Q17.365
median11.3
Q314.435
95-th percentile24.85
Maximum40.5
Range36.37
Interquartile range (IQR)7.07

Descriptive statistics

Standard deviation7.5553822
Coefficient of variation (CV)0.61322943
Kurtosis6.1643202
Mean12.320645
Median Absolute Deviation (MAD)3.47
Skewness2.1647351
Sum381.94
Variance57.0838
MonotonicityNot monotonic
2023-12-11T01:56:22.907999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11.3 2
 
6.5%
6.89 1
 
3.2%
18.0 1
 
3.2%
7.83 1
 
3.2%
14.75 1
 
3.2%
12.6 1
 
3.2%
16.8 1
 
3.2%
4.5 1
 
3.2%
9.4 1
 
3.2%
17.65 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
4.13 1
3.2%
4.5 1
3.2%
4.9 1
3.2%
5.25 1
3.2%
6.3 1
3.2%
6.4 1
3.2%
6.89 1
3.2%
6.9 1
3.2%
7.83 1
3.2%
7.85 1
3.2%
ValueCountFrequency (%)
40.5 1
3.2%
30.3 1
3.2%
19.4 1
3.2%
18.0 1
3.2%
17.65 1
3.2%
16.8 1
3.2%
16.0 1
3.2%
14.75 1
3.2%
14.12 1
3.2%
12.85 1
3.2%

동수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3225806
Minimum0
Maximum125
Zeros3
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:23.085067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile18
Maximum125
Range125
Interquartile range (IQR)1

Descriptive statistics

Standard deviation22.72207
Coefficient of variation (CV)3.5937968
Kurtosis27.049585
Mean6.3225806
Median Absolute Deviation (MAD)0
Skewness5.116413
Sum196
Variance516.29247
MonotonicityNot monotonic
2023-12-11T01:56:23.274351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 18
58.1%
2 5
 
16.1%
0 3
 
9.7%
4 2
 
6.5%
32 1
 
3.2%
125 1
 
3.2%
3 1
 
3.2%
ValueCountFrequency (%)
0 3
 
9.7%
1 18
58.1%
2 5
 
16.1%
3 1
 
3.2%
4 2
 
6.5%
32 1
 
3.2%
125 1
 
3.2%
ValueCountFrequency (%)
125 1
 
3.2%
32 1
 
3.2%
4 2
 
6.5%
3 1
 
3.2%
2 5
 
16.1%
1 18
58.1%
0 3
 
9.7%

주용도
Categorical

Distinct13
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
단독주택
11 
공장
6 
제2종근린생활시설
3 
창고시설
2 
제1종근린생활시설
 
1
Other values (8)
8 

Length

Max length10
Median length4
Mean length4.7419355
Min length2

Unique

Unique9 ?
Unique (%)29.0%

Sample

1st row창고시설
2nd row제1종근린생활시설
3rd row단독주택
4th row단독주택
5th row단독주택

Common Values

ValueCountFrequency (%)
단독주택 11
35.5%
공장 6
19.4%
제2종근린생활시설 3
 
9.7%
창고시설 2
 
6.5%
제1종근린생활시설 1
 
3.2%
교육연구시설 1
 
3.2%
숙박시설 1
 
3.2%
발전시설 1
 
3.2%
자동차관련시설 1
 
3.2%
위험물저장및처리시설 1
 
3.2%
Other values (3) 3
 
9.7%

Length

2023-12-11T01:56:23.505097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 11
35.5%
공장 6
19.4%
제2종근린생활시설 3
 
9.7%
창고시설 2
 
6.5%
제1종근린생활시설 1
 
3.2%
교육연구시설 1
 
3.2%
숙박시설 1
 
3.2%
발전시설 1
 
3.2%
자동차관련시설 1
 
3.2%
위험물저장및처리시설 1
 
3.2%
Other values (3) 3
 
9.7%

부속용도
Text

MISSING 

Distinct19
Distinct (%)79.2%
Missing7
Missing (%)22.6%
Memory size380.0 B
2023-12-11T01:56:23.786466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length9
Mean length8.3333333
Min length2

Characters and Unicode

Total characters200
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)66.7%

Sample

1st row창고
2nd row소매점
3rd row(다가구주택),제1종근린생활시설(소매점)
4th row(다가구주택),제1종근린생활시설(소매점)
5th row연구소
ValueCountFrequency (%)
다가구주택 4
 
13.8%
공장 2
 
6.9%
다가구주택),제1종근린생활시설(소매점 2
 
6.9%
제조업소 1
 
3.4%
창고 1
 
3.4%
요양병원 1
 
3.4%
공장,창고,경비실 1
 
3.4%
일반음식점 1
 
3.4%
단독주택 1
 
3.4%
처리시설 1
 
3.4%
Other values (14) 14
48.3%
2023-12-11T01:56:24.220394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 10
 
5.0%
설 10
 
5.0%
시 10
 
5.0%
주 9
 
4.5%
구 8
 
4.0%
( 8
 
4.0%
) 8
 
4.0%
소 7
 
3.5%
장 7
 
3.5%
택 7
 
3.5%
Other values (52) 116
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
82.5%
Other Punctuation 10
 
5.0%
Open Punctuation 8
 
4.0%
Close Punctuation 8
 
4.0%
Space Separator 5
 
2.5%
Decimal Number 4
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 10
 
6.1%
시 10
 
6.1%
주 9
 
5.5%
구 8
 
4.8%
소 7
 
4.2%
장 7
 
4.2%
택 7
 
4.2%
점 7
 
4.2%
다 6
 
3.6%
가 6
 
3.6%
Other values (46) 88
53.3%
Decimal Number
ValueCountFrequency (%)
1 3
75.0%
2 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
82.5%
Common 35
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 10
 
6.1%
시 10
 
6.1%
주 9
 
5.5%
구 8
 
4.8%
소 7
 
4.2%
장 7
 
4.2%
택 7
 
4.2%
점 7
 
4.2%
다 6
 
3.6%
가 6
 
3.6%
Other values (46) 88
53.3%
Common
ValueCountFrequency (%)
, 10
28.6%
( 8
22.9%
) 8
22.9%
5
14.3%
1 3
 
8.6%
2 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
82.5%
ASCII 35
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 10
28.6%
( 8
22.9%
) 8
22.9%
5
14.3%
1 3
 
8.6%
2 1
 
2.9%
Hangul
ValueCountFrequency (%)
설 10
 
6.1%
시 10
 
6.1%
주 9
 
5.5%
구 8
 
4.8%
소 7
 
4.2%
장 7
 
4.2%
택 7
 
4.2%
점 7
 
4.2%
다 6
 
3.6%
가 6
 
3.6%
Other values (46) 88
53.3%

용도지역
Categorical

Distinct7
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
제1종일반주거지역
11 
자연녹지지역
8 
일반공업지역
6 
제2종일반주거지역
3 
일반상업지역
 
1
Other values (2)
2 

Length

Max length9
Median length6
Mean length7.4193548
Min length5

Unique

Unique3 ?
Unique (%)9.7%

Sample

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

Common Values

ValueCountFrequency (%)
제1종일반주거지역 11
35.5%
자연녹지지역 8
25.8%
일반공업지역 6
19.4%
제2종일반주거지역 3
 
9.7%
일반상업지역 1
 
3.2%
제3종일반주거지역 1
 
3.2%
준주거지역 1
 
3.2%

Length

2023-12-11T01:56:24.494925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:24.695882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1종일반주거지역 11
35.5%
자연녹지지역 8
25.8%
일반공업지역 6
19.4%
제2종일반주거지역 3
 
9.7%
일반상업지역 1
 
3.2%
제3종일반주거지역 1
 
3.2%
준주거지역 1
 
3.2%

용도지구
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing30
Missing (%)96.8%
Memory size380.0 B
2023-12-11T01:56:24.913483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자연취락지구
ValueCountFrequency (%)
자연취락지구 1
100.0%
2023-12-11T01:56:25.314121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 1
16.7%
연 1
16.7%
취 1
16.7%
락 1
16.7%
지 1
16.7%
구 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 1
16.7%
연 1
16.7%
취 1
16.7%
락 1
16.7%
지 1
16.7%
구 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 1
16.7%
연 1
16.7%
취 1
16.7%
락 1
16.7%
지 1
16.7%
구 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 1
16.7%
연 1
16.7%
취 1
16.7%
락 1
16.7%
지 1
16.7%
구 1
16.7%

용도구역
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
제1종지구단위계획구역
15 
<NA>
10 
개발제한구역
2 
지구단위계획구역
2 
가축사육제한구역
 
1

Length

Max length11
Median length8
Mean length7.9677419
Min length4

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
제1종지구단위계획구역 15
48.4%
<NA> 10
32.3%
개발제한구역 2
 
6.5%
지구단위계획구역 2
 
6.5%
가축사육제한구역 1
 
3.2%
산업시설구역 1
 
3.2%

Length

2023-12-11T01:56:25.525830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:25.708690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1종지구단위계획구역 15
48.4%
na 10
32.3%
개발제한구역 2
 
6.5%
지구단위계획구역 2
 
6.5%
가축사육제한구역 1
 
3.2%
산업시설구역 1
 
3.2%

총주차대수
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)62.1%
Missing2
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean93.517241
Minimum1
Maximum1208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T01:56:25.874917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q320
95-th percentile691.8
Maximum1208
Range1207
Interquartile range (IQR)17

Descriptive statistics

Standard deviation280.62209
Coefficient of variation (CV)3.0007525
Kurtosis11.507962
Mean93.517241
Median Absolute Deviation (MAD)5
Skewness3.4784963
Sum2712
Variance78748.759
MonotonicityNot monotonic
2023-12-11T01:56:26.029354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 5
16.1%
3 3
 
9.7%
2 2
 
6.5%
5 2
 
6.5%
4 2
 
6.5%
30 2
 
6.5%
6 2
 
6.5%
1208 1
 
3.2%
949 1
 
3.2%
10 1
 
3.2%
Other values (8) 8
25.8%
(Missing) 2
 
6.5%
ValueCountFrequency (%)
1 5
16.1%
2 2
 
6.5%
3 3
9.7%
4 2
 
6.5%
5 2
 
6.5%
6 2
 
6.5%
7 1
 
3.2%
9 1
 
3.2%
10 1
 
3.2%
15 1
 
3.2%
ValueCountFrequency (%)
1208 1
3.2%
949 1
3.2%
306 1
3.2%
33 1
3.2%
30 2
6.5%
28 1
3.2%
20 1
3.2%
19 1
3.2%
15 1
3.2%
10 1
3.2%

세대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
29 
13
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.8387097
Min length1

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 29
93.5%
13 1
 
3.2%
1 1
 
3.2%

Length

2023-12-11T01:56:26.202878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:26.351709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
93.5%
13 1
 
3.2%
1 1
 
3.2%

호수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
30 
1
 
1

Length

Max length4
Median length4
Mean length3.9032258
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
96.8%
1 1
 
3.2%

Length

2023-12-11T01:56:26.509919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:26.650306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
96.8%
1 1
 
3.2%

가구수
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
20 
1
4 
8
 
2
4
 
2
3
 
2

Length

Max length4
Median length4
Mean length2.9354839
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row8
4th row8
5th row1

Common Values

ValueCountFrequency (%)
<NA> 20
64.5%
1 4
 
12.9%
8 2
 
6.5%
4 2
 
6.5%
3 2
 
6.5%
2 1
 
3.2%

Length

2023-12-11T01:56:26.835357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:56:27.035452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
64.5%
1 4
 
12.9%
8 2
 
6.5%
4 2
 
6.5%
3 2
 
6.5%
2 1
 
3.2%

설계사무소명
Text

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T01:56:27.313730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.9354839
Min length8

Characters and Unicode

Total characters308
Distinct characters58
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)74.2%

Sample

1st row동림건축사사무소
2nd row화우 건축사사무소
3rd row조형종합건축사사무소
4th row조형종합건축사사무소
5th row이지건축 건축사사무소
ValueCountFrequency (%)
건축사사무소 11
25.6%
jn건축사사무소 2
 
4.7%
한성건축사사무소 2
 
4.7%
조형종합건축사사무소 2
 
4.7%
신한일종합건축사사무소 2
 
4.7%
일우 1
 
2.3%
동림건축사사무소 1
 
2.3%
건일 1
 
2.3%
세화 1
 
2.3%
주식회사아키프로건축사사무소 1
 
2.3%
Other values (19) 19
44.2%
2023-12-11T01:56:28.257166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 63
20.5%
건 33
10.7%
축 33
10.7%
소 31
 
10.1%
무 30
 
9.7%
12
 
3.9%
합 7
 
2.3%
종 7
 
2.3%
주 6
 
1.9%
일 5
 
1.6%
Other values (48) 81
26.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
92.2%
Space Separator 12
 
3.9%
Open Punctuation 4
 
1.3%
Close Punctuation 4
 
1.3%
Uppercase Letter 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 63
22.2%
건 33
11.6%
축 33
11.6%
소 31
10.9%
무 30
10.6%
합 7
 
2.5%
종 7
 
2.5%
주 6
 
2.1%
일 5
 
1.8%
지 4
 
1.4%
Other values (43) 65
22.9%
Uppercase Letter
ValueCountFrequency (%)
N 2
50.0%
J 2
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
92.2%
Common 20
 
6.5%
Latin 4
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 63
22.2%
건 33
11.6%
축 33
11.6%
소 31
10.9%
무 30
10.6%
합 7
 
2.5%
종 7
 
2.5%
주 6
 
2.1%
일 5
 
1.8%
지 4
 
1.4%
Other values (43) 65
22.9%
Common
ValueCountFrequency (%)
12
60.0%
( 4
 
20.0%
) 4
 
20.0%
Latin
ValueCountFrequency (%)
N 2
50.0%
J 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
92.2%
ASCII 24
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 63
22.2%
건 33
11.6%
축 33
11.6%
소 31
10.9%
무 30
10.6%
합 7
 
2.5%
종 7
 
2.5%
주 6
 
2.1%
일 5
 
1.8%
지 4
 
1.4%
Other values (43) 65
22.9%
ASCII
ValueCountFrequency (%)
12
50.0%
( 4
 
16.7%
) 4
 
16.7%
N 2
 
8.3%
J 2
 
8.3%

Sample

건축구분허가번호대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)건폐율(%)용적률(%)구조허가일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명
0신축2017-창조건축과-신축허가-291부산광역시 기장군 기장읍 대라리 176-9대396.0210.89210.8953.2653.26일반철골구조2017-10-31106.891창고시설창고제2종일반주거지역<NA><NA>1<NA><NA><NA>동림건축사사무소
1신축2017-창조건축과-신축허가-287부산광역시 기장군 장안읍 좌천리 278-2대305.5179.23178.7758.667858.5172일반철골구조2017-10-30104.90제1종근린생활시설소매점제2종일반주거지역<NA>제1종지구단위계획구역2<NA><NA><NA>화우 건축사사무소
2신축2017-창조건축과-신축허가-288부산광역시 기장군 정관읍 달산리 1018-3대208.4124.2285.2459.6136.87철근콘크리트구조2017-10-304011.31단독주택(다가구주택),제1종근린생활시설(소매점)제1종일반주거지역<NA>제1종지구단위계획구역6<NA><NA>8조형종합건축사사무소
3신축2017-창조건축과-신축허가-289부산광역시 기장군 정관읍 달산리 1018-4대211.5126.0289.4459.57136.85철근콘크리트구조2017-10-304011.31단독주택(다가구주택),제1종근린생활시설(소매점)제1종일반주거지역<NA>제1종지구단위계획구역6<NA><NA>8조형종합건축사사무소
4신축2017-창조건축과-신축허가-290부산광역시 기장군 정관읍 병산리 266-5대258.0103.1133.5739.9651.77철근콘크리트구조2017-10-30206.91단독주택<NA>자연녹지지역자연취락지구<NA>1<NA><NA>1이지건축 건축사사무소
5증축2017-창조건축과-협의건축물-4부산광역시 기장군 기장읍 시랑리 408-1 외13필지대185310.021792.6150678.8411.7622.93철근콘크리트구조2017-10-26219.832교육연구시설연구소자연녹지지역<NA>개발제한구역306<NA><NA><NA>건축사사무소 맥
6증축2017-창조건축과-증축허가-49부산광역시 기장군 정관읍 달산리 1049-13대1578.6945.362013.7259.886123.4626철근콘크리트구조2017-10-263012.852숙박시설<NA>일반상업지역<NA>제1종지구단위계획구역20<NA><NA><NA>(주)사간건축사사무소
7증축2017-창조건축과-증축허가-50부산광역시 기장군 정관읍 달산리 44-5공장용지6858.03952.578605.457.63121.87일반철골구조2017-10-263111.14공장공장일반공업지역<NA><NA>30<NA><NA><NA>대영설계건축사사무소
8신축2017-창조건축과-신축허가-286부산광역시 기장군 일광면 칠암리 264전724.0163.89152.1922.6421.02벽돌구조2017-10-26105.252단독주택다가구주택제1종일반주거지역<NA>제1종지구단위계획구역2<NA><NA>1신한일종합건축사사무소
9증축2017-창조건축과-증축허가-48부산광역시 기장군 장안읍 고리 85-4공장용지948613.0110572.57235496.8311.6523.9869철골콘크리트구조2017-10-254119.4125발전시설업무시설,탁구장자연녹지지역<NA><NA>1208<NA><NA><NA>정영건축사사무소
건축구분허가번호대지위치지목대지면적(㎡)건축면적(㎡)연면적(㎡)건폐율(%)용적률(%)구조허가일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명
21신축2017-창조건축과-신축허가-277부산광역시 기장군 일광면 화전리 74전1415.0147.84147.8410.4510.45경량철골구조2017-10-13104.131단독주택<NA>자연녹지지역<NA><NA>1<NA><NA>1한성건축사사무소
22신축2017-창조건축과-신축허가-278부산광역시 기장군 철마면 임기리 468대572.072.09186.9312.617.23일반목구조2017-10-13217.851단독주택단독주택제1종일반주거지역<NA>제1종지구단위계획구역1<NA><NA>1아담 종합건축사사무소
23신축2017-창조건축과-신축허가-275부산광역시 기장군 정관읍 방곡리 413-7대205.4123.04306.3259.9026149.1334철근콘크리트구조2017-10-123011.921단독주택다가구주택제1종일반주거지역<NA>제1종지구단위계획구역4<NA><NA>3건축사사무소 소이
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