Overview

Dataset statistics

Number of variables35
Number of observations49
Missing cells49
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.2 KiB
Average record size in memory296.6 B

Variable types

Categorical10
Text9
Numeric11
DateTime5

Dataset

Description부산광역시 동래구 건축물 착공신고 현황에 관한 데이터로 대지위치, 대지면적, 건축면적, 연면적, 건폐율, 용적률, 착공일, 용도 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/15026291/fileData.do

Alerts

지목 is highly imbalanced (68.6%)Imbalance
동수 is highly imbalanced (64.2%)Imbalance
가구수 is highly imbalanced (59.2%)Imbalance
사용승인일 has 19 (38.8%) missing valuesMissing
건축허가최초접수일 has 1 (2.0%) missing valuesMissing
부속용도 has 7 (14.3%) missing valuesMissing
감리사무소명 has 1 (2.0%) missing valuesMissing
감리자 도로명주소 has 1 (2.0%) missing valuesMissing
시공자사무소명 has 18 (36.7%) missing valuesMissing
시공자 도로명주소 has 2 (4.1%) missing valuesMissing
허가번호 has unique valuesUnique
대지위치 has unique valuesUnique
증축연면적(제곱미터) has 42 (85.7%) zerosZeros
총주차대수 has 9 (18.4%) zerosZeros
세대수 has 44 (89.8%) zerosZeros
호수 has 44 (89.8%) zerosZeros

Reproduction

Analysis started2024-03-14 19:45:07.996986
Analysis finished2024-03-14 19:45:09.448026
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
신축
29 
대수선
10 
증축
용도변경
 
2
가설건축물축조허가
 
1

Length

Max length9
Median length2
Mean length2.4285714
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 29
59.2%
대수선 10
 
20.4%
증축 7
 
14.3%
용도변경 2
 
4.1%
가설건축물축조허가 1
 
2.0%

Length

2024-03-15T04:45:09.723380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:10.131485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 29
59.2%
대수선 10
 
20.4%
증축 7
 
14.3%
용도변경 2
 
4.1%
가설건축물축조허가 1
 
2.0%

허가번호
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-03-15T04:45:11.361596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length15.897959
Min length15

Characters and Unicode

Total characters779
Distinct characters27
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

Unique49 ?
Unique (%)100.0%

Sample

1st row2023-건축과-신축허가-30
2nd row2023-건축과-공용건축물-2
3rd row2023-건축과-증축허가-5
4th row2023-건축과-신축허가-28
5th row2023-건축과-대수선허가-7
ValueCountFrequency (%)
2023-건축과-신축허가-30 1
 
2.0%
2023-건축과-대수선허가-2 1
 
2.0%
2023-건축과-대수선허가-1 1
 
2.0%
2023-건축과-신축허가-3 1
 
2.0%
2023-건축과-신축허가-2 1
 
2.0%
2023-건축과-신축허가-1 1
 
2.0%
2022-건축과-대수선허가-10 1
 
2.0%
2022-건축과-신축허가-84 1
 
2.0%
2022-건축과-증축허가-20 1
 
2.0%
2022-건축과-신축허가-83 1
 
2.0%
Other values (39) 39
79.6%
2024-03-15T04:45:12.677140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 147
18.9%
2 130
16.7%
86
11.0%
0 55
 
7.1%
50
 
6.4%
49
 
6.3%
48
 
6.2%
48
 
6.2%
3 40
 
5.1%
29
 
3.7%
Other values (17) 97
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
46.0%
Decimal Number 274
35.2%
Dash Punctuation 147
18.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
86
24.0%
50
14.0%
49
13.7%
48
13.4%
48
13.4%
29
 
8.1%
10
 
2.8%
10
 
2.8%
10
 
2.8%
7
 
2.0%
Other values (6) 11
 
3.1%
Decimal Number
ValueCountFrequency (%)
2 130
47.4%
0 55
20.1%
3 40
 
14.6%
1 19
 
6.9%
4 8
 
2.9%
8 6
 
2.2%
6 6
 
2.2%
7 5
 
1.8%
9 3
 
1.1%
5 2
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 421
54.0%
Hangul 358
46.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
86
24.0%
50
14.0%
49
13.7%
48
13.4%
48
13.4%
29
 
8.1%
10
 
2.8%
10
 
2.8%
10
 
2.8%
7
 
2.0%
Other values (6) 11
 
3.1%
Common
ValueCountFrequency (%)
- 147
34.9%
2 130
30.9%
0 55
 
13.1%
3 40
 
9.5%
1 19
 
4.5%
4 8
 
1.9%
8 6
 
1.4%
6 6
 
1.4%
7 5
 
1.2%
9 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 421
54.0%
Hangul 358
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 147
34.9%
2 130
30.9%
0 55
 
13.1%
3 40
 
9.5%
1 19
 
4.5%
4 8
 
1.9%
8 6
 
1.4%
6 6
 
1.4%
7 5
 
1.2%
9 3
 
0.7%
Hangul
ValueCountFrequency (%)
86
24.0%
50
14.0%
49
13.7%
48
13.4%
48
13.4%
29
 
8.1%
10
 
2.8%
10
 
2.8%
10
 
2.8%
7
 
2.0%
Other values (6) 11
 
3.1%

대지위치
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-03-15T04:45:13.483469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length21.122449
Min length18

Characters and Unicode

Total characters1035
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

Unique49 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 안락동 419-11
2nd row부산광역시 동래구 안락동 107-2 외5필지
3rd row부산광역시 동래구 복천동 327-1
4th row부산광역시 동래구 명륜동 451-11 외1필지
5th row부산광역시 동래구 낙민동 23-3
ValueCountFrequency (%)
부산광역시 49
23.2%
동래구 49
23.2%
온천동 27
12.8%
외1필지 9
 
4.3%
안락동 7
 
3.3%
사직동 4
 
1.9%
명륜동 3
 
1.4%
낙민동 3
 
1.4%
명장동 3
 
1.4%
외2필지 2
 
0.9%
Other values (55) 55
26.1%
2024-03-15T04:45:14.791931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
15.7%
98
 
9.5%
1 62
 
6.0%
49
 
4.7%
49
 
4.7%
49
 
4.7%
49
 
4.7%
49
 
4.7%
49
 
4.7%
49
 
4.7%
Other values (26) 370
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
56.4%
Decimal Number 241
23.3%
Space Separator 162
 
15.7%
Dash Punctuation 48
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
98
16.8%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
28
 
4.8%
27
 
4.6%
Other values (14) 88
15.1%
Decimal Number
ValueCountFrequency (%)
1 62
25.7%
2 33
13.7%
4 33
13.7%
5 21
 
8.7%
7 19
 
7.9%
3 18
 
7.5%
6 17
 
7.1%
0 16
 
6.6%
9 13
 
5.4%
8 9
 
3.7%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 584
56.4%
Common 451
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
98
16.8%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
28
 
4.8%
27
 
4.6%
Other values (14) 88
15.1%
Common
ValueCountFrequency (%)
162
35.9%
1 62
 
13.7%
- 48
 
10.6%
2 33
 
7.3%
4 33
 
7.3%
5 21
 
4.7%
7 19
 
4.2%
3 18
 
4.0%
6 17
 
3.8%
0 16
 
3.5%
Other values (2) 22
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 584
56.4%
ASCII 451
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
35.9%
1 62
 
13.7%
- 48
 
10.6%
2 33
 
7.3%
4 33
 
7.3%
5 21
 
4.7%
7 19
 
4.2%
3 18
 
4.0%
6 17
 
3.8%
0 16
 
3.5%
Other values (2) 22
 
4.9%
Hangul
ValueCountFrequency (%)
98
16.8%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
49
8.4%
28
 
4.8%
27
 
4.6%
Other values (14) 88
15.1%

지목
Categorical

IMBALANCE 

Distinct6
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
43 
주유소용지
 
2
도로
 
1
잡종지
 
1
종교용지
 
1

Length

Max length5
Median length1
Mean length1.2857143
Min length1

Unique

Unique4 ?
Unique (%)8.2%

Sample

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

Common Values

ValueCountFrequency (%)
43
87.8%
주유소용지 2
 
4.1%
도로 1
 
2.0%
잡종지 1
 
2.0%
종교용지 1
 
2.0%
1
 
2.0%

Length

2024-03-15T04:45:15.136577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:15.341502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
43
87.8%
주유소용지 2
 
4.1%
도로 1
 
2.0%
잡종지 1
 
2.0%
종교용지 1
 
2.0%
1
 
2.0%
Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1495
Minimum57
Maximum26299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:15.797942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57
5-th percentile129.2
Q1235
median428
Q3748
95-th percentile3170.8
Maximum26299
Range26242
Interquartile range (IQR)513

Descriptive statistics

Standard deviation4020.4485
Coefficient of variation (CV)2.6892632
Kurtosis31.964898
Mean1495
Median Absolute Deviation (MAD)250
Skewness5.4330706
Sum73255
Variance16164006
MonotonicityNot monotonic
2024-03-15T04:45:16.338451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
165 2
 
4.1%
393 1
 
2.0%
57 1
 
2.0%
140 1
 
2.0%
251 1
 
2.0%
428 1
 
2.0%
661 1
 
2.0%
26299 1
 
2.0%
2914 1
 
2.0%
231 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
57 1
2.0%
86 1
2.0%
122 1
2.0%
140 1
2.0%
146 1
2.0%
153 1
2.0%
165 2
4.1%
170 1
2.0%
178 1
2.0%
220 1
2.0%
ValueCountFrequency (%)
26299 1
2.0%
11624 1
2.0%
3342 1
2.0%
2914 1
2.0%
2811 1
2.0%
2781 1
2.0%
2156 1
2.0%
1984 1
2.0%
1654 1
2.0%
1647 1
2.0%
Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean723.67347
Minimum42
Maximum15819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:16.766169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile67.2
Q1136
median208
Q3417
95-th percentile1675.8
Maximum15819
Range15777
Interquartile range (IQR)281

Descriptive statistics

Standard deviation2265.8216
Coefficient of variation (CV)3.131
Kurtosis43.339572
Mean723.67347
Median Absolute Deviation (MAD)112
Skewness6.4361669
Sum35460
Variance5133947.5
MonotonicityNot monotonic
2024-03-15T04:45:17.242865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
42 2
 
4.1%
223 2
 
4.1%
447 2
 
4.1%
377 1
 
2.0%
594 1
 
2.0%
84 1
 
2.0%
188 1
 
2.0%
255 1
 
2.0%
390 1
 
2.0%
15819 1
 
2.0%
Other values (36) 36
73.5%
ValueCountFrequency (%)
42 2
4.1%
66 1
2.0%
69 1
2.0%
76 1
2.0%
84 1
2.0%
89 1
2.0%
96 1
2.0%
107 1
2.0%
109 1
2.0%
117 1
2.0%
ValueCountFrequency (%)
15819 1
2.0%
2969 1
2.0%
1701 1
2.0%
1638 1
2.0%
1455 1
2.0%
1122 1
2.0%
825 1
2.0%
779 1
2.0%
594 1
2.0%
515 1
2.0%

연면적(제곱미터)
Real number (ℝ)

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5768.0816
Minimum42
Maximum158588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:17.787446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile127.8
Q1334
median704
Q31981
95-th percentile17264.8
Maximum158588
Range158546
Interquartile range (IQR)1647

Descriptive statistics

Standard deviation22864.461
Coefficient of variation (CV)3.9639628
Kurtosis43.935742
Mean5768.0816
Median Absolute Deviation (MAD)505
Skewness6.4956029
Sum282636
Variance5.2278357 × 108
MonotonicityNot monotonic
2024-03-15T04:45:18.249941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
597 2
 
4.1%
471 1
 
2.0%
191 1
 
2.0%
2000 1
 
2.0%
924 1
 
2.0%
1981 1
 
2.0%
158588 1
 
2.0%
12913 1
 
2.0%
872 1
 
2.0%
1460 1
 
2.0%
Other values (38) 38
77.6%
ValueCountFrequency (%)
42 1
2.0%
117 1
2.0%
125 1
2.0%
132 1
2.0%
149 1
2.0%
154 1
2.0%
174 1
2.0%
191 1
2.0%
197 1
2.0%
199 1
2.0%
ValueCountFrequency (%)
158588 1
2.0%
25403 1
2.0%
20166 1
2.0%
12913 1
2.0%
11165 1
2.0%
10183 1
2.0%
7975 1
2.0%
4238 1
2.0%
2916 1
2.0%
2573 1
2.0%

증축연면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.55102
Minimum0
Maximum293
Zeros42
Zeros (%)85.7%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:18.750836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile147
Maximum293
Range293
Interquartile range (IQR)0

Descriptive statistics

Standard deviation57.310943
Coefficient of variation (CV)3.0893688
Kurtosis12.099014
Mean18.55102
Median Absolute Deviation (MAD)0
Skewness3.4248869
Sum909
Variance3284.5442
MonotonicityNot monotonic
2024-03-15T04:45:19.023925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 42
85.7%
117 1
 
2.0%
159 1
 
2.0%
129 1
 
2.0%
6 1
 
2.0%
180 1
 
2.0%
25 1
 
2.0%
293 1
 
2.0%
ValueCountFrequency (%)
0 42
85.7%
6 1
 
2.0%
25 1
 
2.0%
117 1
 
2.0%
129 1
 
2.0%
159 1
 
2.0%
180 1
 
2.0%
293 1
 
2.0%
ValueCountFrequency (%)
293 1
 
2.0%
180 1
 
2.0%
159 1
 
2.0%
129 1
 
2.0%
117 1
 
2.0%
25 1
 
2.0%
6 1
 
2.0%
0 42
85.7%

건폐율(퍼센트)
Real number (ℝ)

Distinct26
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.77551
Minimum2
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:19.663175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile20.6
Q150
median59
Q367
95-th percentile79.6
Maximum87
Range85
Interquartile range (IQR)17

Descriptive statistics

Standard deviation18.39414
Coefficient of variation (CV)0.32978883
Kurtosis0.7707429
Mean55.77551
Median Absolute Deviation (MAD)9
Skewness-0.84480718
Sum2733
Variance338.34439
MonotonicityNot monotonic
2024-03-15T04:45:20.041943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
60 9
18.4%
50 5
 
10.2%
79 4
 
8.2%
58 4
 
8.2%
59 3
 
6.1%
26 2
 
4.1%
80 2
 
4.1%
57 2
 
4.1%
71 1
 
2.0%
16 1
 
2.0%
Other values (16) 16
32.7%
ValueCountFrequency (%)
2 1
2.0%
16 1
2.0%
17 1
2.0%
26 2
4.1%
28 1
2.0%
31 1
2.0%
36 1
2.0%
39 1
2.0%
48 1
2.0%
49 1
2.0%
ValueCountFrequency (%)
87 1
 
2.0%
80 2
 
4.1%
79 4
8.2%
77 1
 
2.0%
75 1
 
2.0%
73 1
 
2.0%
71 1
 
2.0%
68 1
 
2.0%
67 1
 
2.0%
60 9
18.4%

용적률(퍼센트)
Real number (ℝ)

Distinct42
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239
Minimum2
Maximum1300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:20.424047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile30.4
Q1105
median178
Q3291
95-th percentile740
Maximum1300
Range1298
Interquartile range (IQR)186

Descriptive statistics

Standard deviation246.19818
Coefficient of variation (CV)1.0301179
Kurtosis8.0074955
Mean239
Median Absolute Deviation (MAD)78
Skewness2.6094014
Sum11711
Variance60613.542
MonotonicityNot monotonic
2024-03-15T04:45:20.897921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
220 4
 
8.2%
116 3
 
6.1%
114 2
 
4.1%
291 2
 
4.1%
120 1
 
2.0%
34 1
 
2.0%
106 1
 
2.0%
744 1
 
2.0%
216 1
 
2.0%
357 1
 
2.0%
Other values (32) 32
65.3%
ValueCountFrequency (%)
2 1
2.0%
26 1
2.0%
30 1
2.0%
31 1
2.0%
34 1
2.0%
36 1
2.0%
39 1
2.0%
71 1
2.0%
72 1
2.0%
90 1
2.0%
ValueCountFrequency (%)
1300 1
2.0%
997 1
2.0%
744 1
2.0%
734 1
2.0%
394 1
2.0%
392 1
2.0%
378 1
2.0%
362 1
2.0%
357 1
2.0%
350 1
2.0%

구조
Categorical

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size520.0 B
철근콘크리트구조
33 
일반철골구조
경량철골구조
 
3
데이터미집계
 
2
조립식판넬조
 
1
Other values (4)

Length

Max length10
Median length8
Mean length7.3469388
Min length4

Unique

Unique5 ?
Unique (%)10.2%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 33
67.3%
일반철골구조 6
 
12.2%
경량철골구조 3
 
6.1%
데이터미집계 2
 
4.1%
조립식판넬조 1
 
2.0%
벽돌구조 1
 
2.0%
블록구조 1
 
2.0%
철골철근콘크리트구조 1
 
2.0%
스틸하우스조 1
 
2.0%

Length

2024-03-15T04:45:21.362244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:21.723253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 33
67.3%
일반철골구조 6
 
12.2%
경량철골구조 3
 
6.1%
데이터미집계 2
 
4.1%
조립식판넬조 1
 
2.0%
벽돌구조 1
 
2.0%
블록구조 1
 
2.0%
철골철근콘크리트구조 1
 
2.0%
스틸하우스조 1
 
2.0%
Distinct47
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size520.0 B
Minimum2020-06-22 00:00:00
Maximum2023-11-21 00:00:00
2024-03-15T04:45:22.138715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:45:22.583901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size520.0 B
Minimum2023-01-26 00:00:00
Maximum2023-12-28 00:00:00
2024-03-15T04:45:22.887199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:45:23.132588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Memory size520.0 B
Minimum2023-01-25 00:00:00
Maximum2023-12-25 00:00:00
2024-03-15T04:45:23.412112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:45:23.678787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

사용승인일
Date

MISSING 

Distinct27
Distinct (%)90.0%
Missing19
Missing (%)38.8%
Memory size520.0 B
Minimum2023-03-17 00:00:00
Maximum2024-01-12 00:00:00
2024-03-15T04:45:24.122934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:45:24.413011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
Distinct47
Distinct (%)97.9%
Missing1
Missing (%)2.0%
Memory size520.0 B
Minimum2021-06-04 00:00:00
Maximum2023-11-02 00:00:00
2024-03-15T04:45:24.762478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:45:25.024600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

최대지상층수
Real number (ℝ)

Distinct14
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5306122
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:25.256103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile14.6
Maximum38
Range37
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.9760008
Coefficient of variation (CV)1.0805315
Kurtosis17.897814
Mean5.5306122
Median Absolute Deviation (MAD)2
Skewness3.6694583
Sum271
Variance35.712585
MonotonicityNot monotonic
2024-03-15T04:45:25.457918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 12
24.5%
4 7
14.3%
3 7
14.3%
1 4
 
8.2%
6 4
 
8.2%
7 3
 
6.1%
5 2
 
4.1%
15 2
 
4.1%
9 2
 
4.1%
8 2
 
4.1%
Other values (4) 4
 
8.2%
ValueCountFrequency (%)
1 4
 
8.2%
2 12
24.5%
3 7
14.3%
4 7
14.3%
5 2
 
4.1%
6 4
 
8.2%
7 3
 
6.1%
8 2
 
4.1%
9 2
 
4.1%
11 1
 
2.0%
ValueCountFrequency (%)
38 1
 
2.0%
15 2
4.1%
14 1
 
2.0%
12 1
 
2.0%
11 1
 
2.0%
9 2
4.1%
8 2
4.1%
7 3
6.1%
6 4
8.2%
5 2
4.1%
Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
0
27 
1
15 
2
3
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0612245
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 27
55.1%
1 15
30.6%
2 3
 
6.1%
3 3
 
6.1%
<NA> 1
 
2.0%

Length

2024-03-15T04:45:25.711360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:25.986471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
55.1%
1 15
30.6%
2 3
 
6.1%
3 3
 
6.1%
na 1
 
2.0%

최고높이(미터)
Real number (ℝ)

Distinct47
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.879633
Minimum3.1
Maximum127.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:26.199487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile4.48
Q18.8
median13.8
Q324.4
95-th percentile55.94
Maximum127.15
Range124.05
Interquartile range (IQR)15.6

Descriptive statistics

Standard deviation22.152766
Coefficient of variation (CV)1.0124834
Kurtosis10.07662
Mean21.879633
Median Absolute Deviation (MAD)5.9
Skewness2.7578244
Sum1072.102
Variance490.74504
MonotonicityNot monotonic
2024-03-15T04:45:26.453718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
8.4 2
 
4.1%
11.65 2
 
4.1%
59.1 1
 
2.0%
44.4 1
 
2.0%
17.6 1
 
2.0%
45.34 1
 
2.0%
74.8 1
 
2.0%
37.0 1
 
2.0%
18.64 1
 
2.0%
17.4 1
 
2.0%
Other values (37) 37
75.5%
ValueCountFrequency (%)
3.1 1
2.0%
3.9 1
2.0%
4.0 1
2.0%
5.2 1
2.0%
6.3 1
2.0%
6.5 1
2.0%
7.4 1
2.0%
7.5 1
2.0%
7.9 1
2.0%
8.0 1
2.0%
ValueCountFrequency (%)
127.15 1
2.0%
74.8 1
2.0%
59.1 1
2.0%
51.2 1
2.0%
45.34 1
2.0%
45.3 1
2.0%
44.4 1
2.0%
40.25 1
2.0%
37.5 1
2.0%
37.0 1
2.0%

동수
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
1
43 
3
 
3
4
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 43
87.8%
3 3
 
6.1%
4 2
 
4.1%
2 1
 
2.0%

Length

2024-03-15T04:45:26.799097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:27.195781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 43
87.8%
3 3
 
6.1%
4 2
 
4.1%
2 1
 
2.0%

주용도
Categorical

Distinct14
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size520.0 B
제2종근린생활시설
20 
제1종근린생활시설
의료시설
단독주택
공동주택
Other values (9)
11 

Length

Max length10
Median length9
Mean length7.4693878
Min length4

Unique

Unique7 ?
Unique (%)14.3%

Sample

1st row제2종근린생활시설
2nd row제1종근린생활시설
3rd row제2종근린생활시설
4th row제2종근린생활시설
5th row의료시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 20
40.8%
제1종근린생활시설 9
18.4%
의료시설 3
 
6.1%
단독주택 3
 
6.1%
공동주택 3
 
6.1%
숙박시설 2
 
4.1%
위험물저장및처리시설 2
 
4.1%
창고시설 1
 
2.0%
자동차관련시설 1
 
2.0%
문화및집회시설 1
 
2.0%
Other values (4) 4
 
8.2%

Length

2024-03-15T04:45:27.590698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 20
40.8%
제1종근린생활시설 9
18.4%
의료시설 3
 
6.1%
단독주택 3
 
6.1%
공동주택 3
 
6.1%
숙박시설 2
 
4.1%
위험물저장및처리시설 2
 
4.1%
창고시설 1
 
2.0%
자동차관련시설 1
 
2.0%
문화및집회시설 1
 
2.0%
Other values (4) 4
 
8.2%

부속용도
Text

MISSING 

Distinct35
Distinct (%)83.3%
Missing7
Missing (%)14.3%
Memory size520.0 B
2024-03-15T04:45:28.541908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length23
Mean length8.9047619
Min length2

Characters and Unicode

Total characters374
Distinct characters85
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

Unique31 ?
Unique (%)73.8%

Sample

1st row자동차영업소
2nd row휴게음식점
3rd row사무소
4th row일반음식점
5th row종합병원,교육연구및복지시설
ValueCountFrequency (%)
사무소 5
 
8.9%
일반음식점 4
 
7.1%
의원 3
 
5.4%
제2종근린생활시설 2
 
3.6%
학원 2
 
3.6%
소매점 2
 
3.6%
근린생활시설 2
 
3.6%
업무시설(오피스텔 2
 
3.6%
호텔 2
 
3.6%
문화집회시설 1
 
1.8%
Other values (31) 31
55.4%
2024-03-15T04:45:29.942018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 24
 
6.4%
18
 
4.8%
17
 
4.5%
17
 
4.5%
16
 
4.3%
13
 
3.5%
12
 
3.2%
11
 
2.9%
( 10
 
2.7%
) 10
 
2.7%
Other values (75) 226
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
82.6%
Other Punctuation 25
 
6.7%
Space Separator 16
 
4.3%
Open Punctuation 10
 
2.7%
Close Punctuation 10
 
2.7%
Decimal Number 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
5.8%
17
 
5.5%
17
 
5.5%
13
 
4.2%
12
 
3.9%
11
 
3.6%
10
 
3.2%
9
 
2.9%
8
 
2.6%
8
 
2.6%
Other values (68) 186
60.2%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
: 1
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
82.6%
Common 65
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
5.8%
17
 
5.5%
17
 
5.5%
13
 
4.2%
12
 
3.9%
11
 
3.6%
10
 
3.2%
9
 
2.9%
8
 
2.6%
8
 
2.6%
Other values (68) 186
60.2%
Common
ValueCountFrequency (%)
, 24
36.9%
16
24.6%
( 10
15.4%
) 10
15.4%
1 2
 
3.1%
2 2
 
3.1%
: 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
82.6%
ASCII 65
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 24
36.9%
16
24.6%
( 10
15.4%
) 10
15.4%
1 2
 
3.1%
2 2
 
3.1%
: 1
 
1.5%
Hangul
ValueCountFrequency (%)
18
 
5.8%
17
 
5.5%
17
 
5.5%
13
 
4.2%
12
 
3.9%
11
 
3.6%
10
 
3.2%
9
 
2.9%
8
 
2.6%
8
 
2.6%
Other values (68) 186
60.2%

용도지역
Categorical

Distinct7
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size520.0 B
제2종일반주거지역
16 
일반상업지역
11 
가로구역별최고높이제한지역
준주거지역
제3종일반주거지역
Other values (2)

Length

Max length13
Median length9
Mean length8.2857143
Min length5

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row준주거지역
2nd row자연녹지지역
3rd row일반상업지역
4th row준주거지역
5th row제3종일반주거지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 16
32.7%
일반상업지역 11
22.4%
가로구역별최고높이제한지역 7
14.3%
준주거지역 6
 
12.2%
제3종일반주거지역 6
 
12.2%
자연녹지지역 2
 
4.1%
제1종일반주거지역 1
 
2.0%

Length

2024-03-15T04:45:30.404979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:30.773130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종일반주거지역 16
32.7%
일반상업지역 11
22.4%
가로구역별최고높이제한지역 7
14.3%
준주거지역 6
 
12.2%
제3종일반주거지역 6
 
12.2%
자연녹지지역 2
 
4.1%
제1종일반주거지역 1
 
2.0%

용도지구
Categorical

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
<NA>
30 
방화지구
17 
역사문화특화경관지구
 
1
철도보호지구
 
1

Length

Max length10
Median length4
Mean length4.1632653
Min length4

Unique

Unique2 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
61.2%
방화지구 17
34.7%
역사문화특화경관지구 1
 
2.0%
철도보호지구 1
 
2.0%

Length

2024-03-15T04:45:31.121353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:31.498029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
61.2%
방화지구 17
34.7%
역사문화특화경관지구 1
 
2.0%
철도보호지구 1
 
2.0%

용도구역
Categorical

Distinct8
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size520.0 B
데이터미집계
25 
상대보호구역
18 
역사문화환경보존지역
 
1
준주거지역
 
1
절대정화구역
 
1
Other values (3)

Length

Max length14
Median length6
Mean length6.2857143
Min length4

Unique

Unique6 ?
Unique (%)12.2%

Sample

1st row역사문화환경보존지역
2nd row데이터미집계
3rd row준주거지역
4th row데이터미집계
5th row데이터미집계

Common Values

ValueCountFrequency (%)
데이터미집계 25
51.0%
상대보호구역 18
36.7%
역사문화환경보존지역 1
 
2.0%
준주거지역 1
 
2.0%
절대정화구역 1
 
2.0%
제1종지구단위계획구역 1
 
2.0%
<NA> 1
 
2.0%
문화재보존영향 검토대상구역 1
 
2.0%

Length

2024-03-15T04:45:31.732689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:32.070468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
데이터미집계 25
50.0%
상대보호구역 18
36.0%
역사문화환경보존지역 1
 
2.0%
준주거지역 1
 
2.0%
절대정화구역 1
 
2.0%
제1종지구단위계획구역 1
 
2.0%
na 1
 
2.0%
문화재보존영향 1
 
2.0%
검토대상구역 1
 
2.0%

총주차대수
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.44898
Minimum0
Maximum1571
Zeros9
Zeros (%)18.4%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:32.284591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q323
95-th percentile129.2
Maximum1571
Range1571
Interquartile range (IQR)22

Descriptive statistics

Standard deviation224.80659
Coefficient of variation (CV)4.2060034
Kurtosis45.832593
Mean53.44898
Median Absolute Deviation (MAD)4
Skewness6.6791938
Sum2619
Variance50538.003
MonotonicityNot monotonic
2024-03-15T04:45:32.514262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 9
18.4%
4 7
14.3%
2 5
 
10.2%
1 4
 
8.2%
5 4
 
8.2%
9 2
 
4.1%
14 2
 
4.1%
25 1
 
2.0%
11 1
 
2.0%
35 1
 
2.0%
Other values (13) 13
26.5%
ValueCountFrequency (%)
0 9
18.4%
1 4
8.2%
2 5
10.2%
4 7
14.3%
5 4
8.2%
8 1
 
2.0%
9 2
 
4.1%
11 1
 
2.0%
13 1
 
2.0%
14 2
 
4.1%
ValueCountFrequency (%)
1571 1
2.0%
190 1
2.0%
134 1
2.0%
122 1
2.0%
85 1
2.0%
75 1
2.0%
68 1
2.0%
62 1
2.0%
48 1
2.0%
41 1
2.0%

세대수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3265306
Minimum0
Maximum160
Zeros44
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:32.819978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12.8
Maximum160
Range160
Interquartile range (IQR)0

Descriptive statistics

Standard deviation23.241833
Coefficient of variation (CV)5.3719332
Kurtosis44.355762
Mean4.3265306
Median Absolute Deviation (MAD)0
Skewness6.5530364
Sum212
Variance540.18282
MonotonicityNot monotonic
2024-03-15T04:45:33.188627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 44
89.8%
1 1
 
2.0%
160 1
 
2.0%
20 1
 
2.0%
29 1
 
2.0%
2 1
 
2.0%
ValueCountFrequency (%)
0 44
89.8%
1 1
 
2.0%
2 1
 
2.0%
20 1
 
2.0%
29 1
 
2.0%
160 1
 
2.0%
ValueCountFrequency (%)
160 1
 
2.0%
29 1
 
2.0%
20 1
 
2.0%
2 1
 
2.0%
1 1
 
2.0%
0 44
89.8%

호수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3877551
Minimum0
Maximum43
Zeros44
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size569.0 B
2024-03-15T04:45:33.548896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.6
Maximum43
Range43
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.3927574
Coefficient of variation (CV)4.6065458
Kurtosis39.330256
Mean1.3877551
Median Absolute Deviation (MAD)0
Skewness6.0773066
Sum68
Variance40.867347
MonotonicityNot monotonic
2024-03-15T04:45:33.892266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 44
89.8%
6 1
 
2.0%
43 1
 
2.0%
7 1
 
2.0%
1 1
 
2.0%
11 1
 
2.0%
ValueCountFrequency (%)
0 44
89.8%
1 1
 
2.0%
6 1
 
2.0%
7 1
 
2.0%
11 1
 
2.0%
43 1
 
2.0%
ValueCountFrequency (%)
43 1
 
2.0%
11 1
 
2.0%
7 1
 
2.0%
6 1
 
2.0%
1 1
 
2.0%
0 44
89.8%

가구수
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size520.0 B
0
41 
1
5
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 41
83.7%
1 6
 
12.2%
5 1
 
2.0%
2 1
 
2.0%

Length

2024-03-15T04:45:34.416735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:45:34.733704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
83.7%
1 6
 
12.2%
5 1
 
2.0%
2 1
 
2.0%
Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-03-15T04:45:35.577575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length11.040816
Min length8

Characters and Unicode

Total characters541
Distinct characters102
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

Unique43 ?
Unique (%)87.8%

Sample

1st row주식회사 중앙건축사사무소
2nd row자우건축사사무소
3rd row(주)해안건축사사무소
4th row건축사사무소임건축
5th row건축사사무소 가전건축
ValueCountFrequency (%)
건축사사무소 19
22.4%
종합건축사사무소 7
 
8.2%
주식회사 3
 
3.5%
다솜건축사사무소 2
 
2.4%
주)종합건축사사무소 2
 
2.4%
2
 
2.4%
주)다인종합건축사사무소 2
 
2.4%
금강 1
 
1.2%
1
 
1.2%
동언 1
 
1.2%
Other values (45) 45
52.9%
2024-03-15T04:45:36.989780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
18.7%
52
 
9.6%
52
 
9.6%
49
 
9.1%
49
 
9.1%
37
 
6.8%
14
 
2.6%
13
 
2.4%
13
 
2.4%
( 10
 
1.8%
Other values (92) 151
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 448
82.8%
Space Separator 37
 
6.8%
Uppercase Letter 16
 
3.0%
Open Punctuation 10
 
1.8%
Close Punctuation 10
 
1.8%
Lowercase Letter 10
 
1.8%
Other Punctuation 9
 
1.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
101
22.5%
52
11.6%
52
11.6%
49
10.9%
49
10.9%
14
 
3.1%
13
 
2.9%
13
 
2.9%
5
 
1.1%
4
 
0.9%
Other values (64) 96
21.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
18.8%
E 2
12.5%
N 2
12.5%
D 1
 
6.2%
K 1
 
6.2%
U 1
 
6.2%
I 1
 
6.2%
Y 1
 
6.2%
H 1
 
6.2%
S 1
 
6.2%
Other values (2) 2
12.5%
Lowercase Letter
ValueCountFrequency (%)
s 2
20.0%
o 1
10.0%
u 1
10.0%
q 1
10.0%
r 1
10.0%
p 1
10.0%
l 1
10.0%
a 1
10.0%
n 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
& 2
 
22.2%
; 1
 
11.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
82.8%
Common 67
 
12.4%
Latin 26
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
101
22.5%
52
11.6%
52
11.6%
49
10.9%
49
10.9%
14
 
3.1%
13
 
2.9%
13
 
2.9%
5
 
1.1%
4
 
0.9%
Other values (64) 96
21.4%
Latin
ValueCountFrequency (%)
A 3
 
11.5%
E 2
 
7.7%
N 2
 
7.7%
s 2
 
7.7%
o 1
 
3.8%
D 1
 
3.8%
K 1
 
3.8%
u 1
 
3.8%
q 1
 
3.8%
r 1
 
3.8%
Other values (11) 11
42.3%
Common
ValueCountFrequency (%)
37
55.2%
( 10
 
14.9%
) 10
 
14.9%
. 6
 
9.0%
& 2
 
3.0%
; 1
 
1.5%
- 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 448
82.8%
ASCII 93
 
17.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
101
22.5%
52
11.6%
52
11.6%
49
10.9%
49
10.9%
14
 
3.1%
13
 
2.9%
13
 
2.9%
5
 
1.1%
4
 
0.9%
Other values (64) 96
21.4%
ASCII
ValueCountFrequency (%)
37
39.8%
( 10
 
10.8%
) 10
 
10.8%
. 6
 
6.5%
A 3
 
3.2%
& 2
 
2.2%
E 2
 
2.2%
N 2
 
2.2%
s 2
 
2.2%
o 1
 
1.1%
Other values (18) 18
19.4%
Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size520.0 B
2024-03-15T04:45:38.152797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length30.183673
Min length15

Characters and Unicode

Total characters1479
Distinct characters153
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)87.8%

Sample

1st row부산광역시 동래구 아시아드대로 111-1, 3층,사직동
2nd row부산광역시 해운대구 좌동로14번길 2, 3층
3rd row부산광역시 연제구 연수로11번길 114, 연산동연동빌딩 3층
4th row경상남도 창녕군 창녕읍 창녕대로 27, 2층 건축사사무소임건축
5th row부산광역시 동래구 충렬대로237번길 104 (명륜동,조광빌딩3층)
ValueCountFrequency (%)
부산광역시 44
 
15.8%
2층 9
 
3.2%
동래구 6
 
2.2%
북구 6
 
2.2%
3층 6
 
2.2%
해운대구 5
 
1.8%
연제구 5
 
1.8%
금정구 5
 
1.8%
부산진구 5
 
1.8%
사상로 4
 
1.4%
Other values (145) 183
65.8%
2024-03-15T04:45:39.402655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
 
15.5%
, 54
 
3.7%
52
 
3.5%
1 51
 
3.4%
2 51
 
3.4%
50
 
3.4%
50
 
3.4%
50
 
3.4%
49
 
3.3%
49
 
3.3%
Other values (143) 794
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 872
59.0%
Decimal Number 269
 
18.2%
Space Separator 229
 
15.5%
Other Punctuation 54
 
3.7%
Close Punctuation 23
 
1.6%
Open Punctuation 23
 
1.6%
Dash Punctuation 6
 
0.4%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
6.0%
50
 
5.7%
50
 
5.7%
50
 
5.7%
49
 
5.6%
49
 
5.6%
45
 
5.2%
44
 
5.0%
32
 
3.7%
26
 
3.0%
Other values (126) 425
48.7%
Decimal Number
ValueCountFrequency (%)
1 51
19.0%
2 51
19.0%
3 36
13.4%
0 28
10.4%
7 23
8.6%
6 20
 
7.4%
4 18
 
6.7%
5 18
 
6.7%
8 13
 
4.8%
9 11
 
4.1%
Space Separator
ValueCountFrequency (%)
229
100.0%
Other Punctuation
ValueCountFrequency (%)
, 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 872
59.0%
Common 604
40.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
6.0%
50
 
5.7%
50
 
5.7%
50
 
5.7%
49
 
5.6%
49
 
5.6%
45
 
5.2%
44
 
5.0%
32
 
3.7%
26
 
3.0%
Other values (126) 425
48.7%
Common
ValueCountFrequency (%)
229
37.9%
, 54
 
8.9%
1 51
 
8.4%
2 51
 
8.4%
3 36
 
6.0%
0 28
 
4.6%
7 23
 
3.8%
) 23
 
3.8%
( 23
 
3.8%
6 20
 
3.3%
Other values (5) 66
 
10.9%
Latin
ValueCountFrequency (%)
C 2
66.7%
e 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 872
59.0%
ASCII 607
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
37.7%
, 54
 
8.9%
1 51
 
8.4%
2 51
 
8.4%
3 36
 
5.9%
0 28
 
4.6%
7 23
 
3.8%
) 23
 
3.8%
( 23
 
3.8%
6 20
 
3.3%
Other values (7) 69
 
11.4%
Hangul
ValueCountFrequency (%)
52
 
6.0%
50
 
5.7%
50
 
5.7%
50
 
5.7%
49
 
5.6%
49
 
5.6%
45
 
5.2%
44
 
5.0%
32
 
3.7%
26
 
3.0%
Other values (126) 425
48.7%

감리사무소명
Text

MISSING 

Distinct47
Distinct (%)97.9%
Missing1
Missing (%)2.0%
Memory size520.0 B
2024-03-15T04:45:40.288877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.583333
Min length7

Characters and Unicode

Total characters508
Distinct characters99
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

Unique46 ?
Unique (%)95.8%

Sample

1st row로운건축사사무소
2nd row자우건축사사무소
3rd row(주)해안건축사사무소
4th row건축사사무소 에이피
5th row건축사사무소 가전건축
ValueCountFrequency (%)
건축사사무소 22
26.5%
종합건축사사무소 6
 
7.2%
주식회사 3
 
3.6%
삼주건축 2
 
2.4%
젬마 1
 
1.2%
서우 1
 
1.2%
주)이담종합건축사사무소 1
 
1.2%
준건축사사무소 1
 
1.2%
도반건축사사무소 1
 
1.2%
로얄 1
 
1.2%
Other values (44) 44
53.0%
2024-03-15T04:45:41.295689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
19.5%
55
10.8%
51
 
10.0%
50
 
9.8%
48
 
9.4%
35
 
6.9%
12
 
2.4%
10
 
2.0%
10
 
2.0%
8
 
1.6%
Other values (89) 130
25.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 442
87.0%
Space Separator 35
 
6.9%
Uppercase Letter 9
 
1.8%
Close Punctuation 7
 
1.4%
Open Punctuation 7
 
1.4%
Lowercase Letter 5
 
1.0%
Other Punctuation 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
99
22.4%
55
12.4%
51
11.5%
50
11.3%
48
10.9%
12
 
2.7%
10
 
2.3%
10
 
2.3%
8
 
1.8%
3
 
0.7%
Other values (70) 96
21.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
22.2%
D 1
11.1%
U 1
11.1%
K 1
11.1%
E 1
11.1%
N 1
11.1%
H 1
11.1%
Y 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
20.0%
p 1
20.0%
l 1
20.0%
a 1
20.0%
n 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 442
87.0%
Common 52
 
10.2%
Latin 14
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
99
22.4%
55
12.4%
51
11.5%
50
11.3%
48
10.9%
12
 
2.7%
10
 
2.3%
10
 
2.3%
8
 
1.8%
3
 
0.7%
Other values (70) 96
21.7%
Latin
ValueCountFrequency (%)
A 2
14.3%
D 1
 
7.1%
U 1
 
7.1%
K 1
 
7.1%
E 1
 
7.1%
N 1
 
7.1%
s 1
 
7.1%
H 1
 
7.1%
Y 1
 
7.1%
p 1
 
7.1%
Other values (3) 3
21.4%
Common
ValueCountFrequency (%)
35
67.3%
) 7
 
13.5%
( 7
 
13.5%
. 1
 
1.9%
& 1
 
1.9%
- 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 442
87.0%
ASCII 66
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
99
22.4%
55
12.4%
51
11.5%
50
11.3%
48
10.9%
12
 
2.7%
10
 
2.3%
10
 
2.3%
8
 
1.8%
3
 
0.7%
Other values (70) 96
21.7%
ASCII
ValueCountFrequency (%)
35
53.0%
) 7
 
10.6%
( 7
 
10.6%
A 2
 
3.0%
. 1
 
1.5%
D 1
 
1.5%
U 1
 
1.5%
K 1
 
1.5%
E 1
 
1.5%
N 1
 
1.5%
Other values (9) 9
 
13.6%
Distinct47
Distinct (%)97.9%
Missing1
Missing (%)2.0%
Memory size520.0 B
2024-03-15T04:45:42.477891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length28.520833
Min length15

Characters and Unicode

Total characters1369
Distinct characters140
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

Unique46 ?
Unique (%)95.8%

Sample

1st row부산광역시 연제구 과정로 226, 202호
2nd row부산광역시 해운대구 좌동로14번길 2, 3층
3rd row부산광역시 연제구 연수로11번길 114, 연산동연동빌딩 3층
4th row부산광역시 수영구 망미배산로70번다길 9, 4층
5th row부산광역시 동래구 충렬대로237번길 104 (명륜동,조광빌딩3층)
ValueCountFrequency (%)
부산광역시 47
 
17.6%
2층 9
 
3.4%
3층 7
 
2.6%
연제구 6
 
2.2%
북구 6
 
2.2%
수영구 5
 
1.9%
금정구 5
 
1.9%
동구 5
 
1.9%
동래구 5
 
1.9%
해운대구 4
 
1.5%
Other values (140) 168
62.9%
2024-03-15T04:45:43.956297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
16.0%
56
 
4.1%
53
 
3.9%
52
 
3.8%
51
 
3.7%
50
 
3.7%
2 49
 
3.6%
, 48
 
3.5%
48
 
3.5%
47
 
3.4%
Other values (130) 696
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 806
58.9%
Decimal Number 252
 
18.4%
Space Separator 219
 
16.0%
Other Punctuation 48
 
3.5%
Open Punctuation 19
 
1.4%
Close Punctuation 19
 
1.4%
Dash Punctuation 5
 
0.4%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
56
 
6.9%
53
 
6.6%
52
 
6.5%
51
 
6.3%
50
 
6.2%
48
 
6.0%
47
 
5.8%
43
 
5.3%
26
 
3.2%
23
 
2.9%
Other values (114) 357
44.3%
Decimal Number
ValueCountFrequency (%)
2 49
19.4%
1 38
15.1%
3 31
12.3%
0 30
11.9%
6 26
10.3%
7 20
7.9%
5 19
 
7.5%
4 16
 
6.3%
8 14
 
5.6%
9 9
 
3.6%
Space Separator
ValueCountFrequency (%)
219
100.0%
Other Punctuation
ValueCountFrequency (%)
, 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 806
58.9%
Common 562
41.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
56
 
6.9%
53
 
6.6%
52
 
6.5%
51
 
6.3%
50
 
6.2%
48
 
6.0%
47
 
5.8%
43
 
5.3%
26
 
3.2%
23
 
2.9%
Other values (114) 357
44.3%
Common
ValueCountFrequency (%)
219
39.0%
2 49
 
8.7%
, 48
 
8.5%
1 38
 
6.8%
3 31
 
5.5%
0 30
 
5.3%
6 26
 
4.6%
7 20
 
3.6%
( 19
 
3.4%
) 19
 
3.4%
Other values (5) 63
 
11.2%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 806
58.9%
ASCII 563
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
38.9%
2 49
 
8.7%
, 48
 
8.5%
1 38
 
6.7%
3 31
 
5.5%
0 30
 
5.3%
6 26
 
4.6%
7 20
 
3.6%
( 19
 
3.4%
) 19
 
3.4%
Other values (6) 64
 
11.4%
Hangul
ValueCountFrequency (%)
56
 
6.9%
53
 
6.6%
52
 
6.5%
51
 
6.3%
50
 
6.2%
48
 
6.0%
47
 
5.8%
43
 
5.3%
26
 
3.2%
23
 
2.9%
Other values (114) 357
44.3%

시공자사무소명
Text

MISSING 

Distinct28
Distinct (%)90.3%
Missing18
Missing (%)36.7%
Memory size520.0 B
2024-03-15T04:45:44.968053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.7419355
Min length5

Characters and Unicode

Total characters271
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)80.6%

Sample

1st row부경종합건설주식회사
2nd row주식회사대보건설
3rd row계림종합건설(주)
4th row(주)유안
5th row(주)토백종합건설
ValueCountFrequency (%)
주식회사 3
 
8.8%
주)장한이앤씨 2
 
5.9%
초우종합건설(주 2
 
5.9%
주)원우종합건설 2
 
5.9%
모아종합건설(주 1
 
2.9%
부경종합건설주식회사 1
 
2.9%
성무건설주식회사 1
 
2.9%
지안종합건설 1
 
2.9%
에스에이치시종합건설(주 1
 
2.9%
태흥종합건설(주 1
 
2.9%
Other values (19) 19
55.9%
2024-03-15T04:45:45.979020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
10.7%
28
 
10.3%
27
 
10.0%
( 23
 
8.5%
) 23
 
8.5%
22
 
8.1%
21
 
7.7%
7
 
2.6%
6
 
2.2%
6
 
2.2%
Other values (53) 79
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
81.9%
Open Punctuation 23
 
8.5%
Close Punctuation 23
 
8.5%
Space Separator 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
13.1%
28
12.6%
27
12.2%
22
 
9.9%
21
 
9.5%
7
 
3.2%
6
 
2.7%
6
 
2.7%
6
 
2.7%
5
 
2.3%
Other values (50) 65
29.3%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
81.9%
Common 49
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
13.1%
28
12.6%
27
12.2%
22
 
9.9%
21
 
9.5%
7
 
3.2%
6
 
2.7%
6
 
2.7%
6
 
2.7%
5
 
2.3%
Other values (50) 65
29.3%
Common
ValueCountFrequency (%)
( 23
46.9%
) 23
46.9%
3
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
81.9%
ASCII 49
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
29
13.1%
28
12.6%
27
12.2%
22
 
9.9%
21
 
9.5%
7
 
3.2%
6
 
2.7%
6
 
2.7%
6
 
2.7%
5
 
2.3%
Other values (50) 65
29.3%
ASCII
ValueCountFrequency (%)
( 23
46.9%
) 23
46.9%
3
 
6.1%
Distinct45
Distinct (%)95.7%
Missing2
Missing (%)4.1%
Memory size520.0 B
2024-03-15T04:45:47.082444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length36
Mean length28.957447
Min length15

Characters and Unicode

Total characters1361
Distinct characters160
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)91.5%

Sample

1st row부산광역시 기장군 기장읍 차성로277번길 21, 3층
2nd row부산광역시 연제구 연안로 5, 4층(연산동)
3rd row부산광역시 동래구 동래로136번길 25, 5층
4th row부산광역시 강서구 낙동남로 133
5th row부산광역시 남구 유엔평화로125번길 11-1
ValueCountFrequency (%)
부산광역시 37
 
14.6%
동래구 9
 
3.5%
금정구 7
 
2.8%
경상남도 7
 
2.8%
연제구 5
 
2.0%
온천동 4
 
1.6%
남구 4
 
1.6%
부산진구 4
 
1.6%
수영구 4
 
1.6%
54 3
 
1.2%
Other values (142) 170
66.9%
2024-03-15T04:45:48.647183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
207
 
15.2%
1 57
 
4.2%
49
 
3.6%
48
 
3.5%
47
 
3.5%
, 45
 
3.3%
44
 
3.2%
43
 
3.2%
41
 
3.0%
41
 
3.0%
Other values (150) 739
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
57.4%
Decimal Number 271
 
19.9%
Space Separator 207
 
15.2%
Other Punctuation 45
 
3.3%
Open Punctuation 20
 
1.5%
Close Punctuation 19
 
1.4%
Dash Punctuation 11
 
0.8%
Uppercase Letter 5
 
0.4%
Connector Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
49
 
6.3%
48
 
6.1%
47
 
6.0%
44
 
5.6%
43
 
5.5%
41
 
5.2%
41
 
5.2%
38
 
4.9%
21
 
2.7%
20
 
2.6%
Other values (128) 389
49.8%
Decimal Number
ValueCountFrequency (%)
1 57
21.0%
2 38
14.0%
0 29
10.7%
3 28
10.3%
4 28
10.3%
6 27
10.0%
5 25
9.2%
7 17
 
6.3%
9 13
 
4.8%
8 9
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
Y 1
20.0%
G 1
20.0%
T 1
20.0%
S 1
20.0%
K 1
20.0%
Space Separator
ValueCountFrequency (%)
207
100.0%
Other Punctuation
ValueCountFrequency (%)
, 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 781
57.4%
Common 574
42.2%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
49
 
6.3%
48
 
6.1%
47
 
6.0%
44
 
5.6%
43
 
5.5%
41
 
5.2%
41
 
5.2%
38
 
4.9%
21
 
2.7%
20
 
2.6%
Other values (128) 389
49.8%
Common
ValueCountFrequency (%)
207
36.1%
1 57
 
9.9%
, 45
 
7.8%
2 38
 
6.6%
0 29
 
5.1%
3 28
 
4.9%
4 28
 
4.9%
6 27
 
4.7%
5 25
 
4.4%
( 20
 
3.5%
Other values (6) 70
 
12.2%
Latin
ValueCountFrequency (%)
Y 1
16.7%
G 1
16.7%
T 1
16.7%
b 1
16.7%
S 1
16.7%
K 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
57.4%
ASCII 580
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
207
35.7%
1 57
 
9.8%
, 45
 
7.8%
2 38
 
6.6%
0 29
 
5.0%
3 28
 
4.8%
4 28
 
4.8%
6 27
 
4.7%
5 25
 
4.3%
( 20
 
3.4%
Other values (12) 76
 
13.1%
Hangul
ValueCountFrequency (%)
49
 
6.3%
48
 
6.1%
47
 
6.0%
44
 
5.6%
43
 
5.5%
41
 
5.2%
41
 
5.2%
38
 
4.9%
21
 
2.7%
20
 
2.6%
Other values (128) 389
49.8%

Sample

건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명설계자 도로명주소감리사무소명감리자 도로명주소시공자사무소명시공자 도로명주소
0신축2023-건축과-신축허가-30부산광역시 동래구 안락동 419-11393235471060120일반철골구조2023-11-212023-12-062023-12-06<NA>2023-11-01208.41제2종근린생활시설자동차영업소준주거지역역사문화특화경관지구역사문화환경보존지역4000주식회사 중앙건축사사무소부산광역시 동래구 아시아드대로 111-1, 3층,사직동로운건축사사무소부산광역시 연제구 과정로 226, 202호부경종합건설주식회사부산광역시 기장군 기장읍 차성로277번길 21, 3층
1가설건축물축조허가2023-건축과-공용건축물-2부산광역시 동래구 안락동 107-2 외5필지도로27814242022조립식판넬조2023-11-092023-11-132023-11-13<NA>2023-11-02103.11제1종근린생활시설휴게음식점자연녹지지역<NA>데이터미집계0000자우건축사사무소부산광역시 해운대구 좌동로14번길 2, 3층자우건축사사무소부산광역시 해운대구 좌동로14번길 2, 3층주식회사대보건설부산광역시 연제구 연안로 5, 4층(연산동)
2증축2023-건축과-증축허가-5부산광역시 동래구 복천동 327-133015896811748235철근콘크리트구조2023-11-032023-12-062023-11-302023-12-282023-09-255116.381제2종근린생활시설사무소일반상업지역방화지구준주거지역2000(주)해안건축사사무소부산광역시 연제구 연수로11번길 114, 연산동연동빌딩 3층(주)해안건축사사무소부산광역시 연제구 연수로11번길 114, 연산동연동빌딩 3층<NA>부산광역시 동래구 동래로136번길 25, 5층
3신축2023-건축과-신축허가-28부산광역시 동래구 명륜동 451-11 외1필지293175334060114일반철골구조2023-11-032023-12-152023-12-25<NA>2023-10-132010.11제2종근린생활시설일반음식점준주거지역<NA>데이터미집계2000건축사사무소임건축경상남도 창녕군 창녕읍 창녕대로 27, 2층 건축사사무소임건축건축사사무소 에이피부산광역시 수영구 망미배산로70번다길 9, 4층계림종합건설(주)부산광역시 강서구 낙동남로 133
4대수선2023-건축과-대수선허가-7부산광역시 동래구 낙민동 23-33342163811165049314철근콘크리트구조2023-10-162023-12-082023-12-062023-12-182023-09-1315151.21의료시설종합병원,교육연구및복지시설제3종일반주거지역철도보호지구데이터미집계85000건축사사무소 가전건축부산광역시 동래구 충렬대로237번길 104 (명륜동,조광빌딩3층)건축사사무소 가전건축부산광역시 동래구 충렬대로237번길 104 (명륜동,조광빌딩3층)(주)유안부산광역시 남구 유엔평화로125번길 11-1
5증축2023-건축과-증축허가-4부산광역시 동래구 온천동 137-71162429692016615926116철근콘크리트구조2023-10-102023-10-302023-10-312024-01-122023-09-229240.253숙박시설호텔일반상업지역방화지구데이터미집계75000종합건축사사무소 상록부산광역시 남구 유엔로 98종합건축사사무소 상록부산광역시 남구 유엔로 98(주)토백종합건설부산광역시 수영구 광안해변로344번길 17-17, 9층
6신축2023-건축과-신축허가-27부산광역시 동래구 온천동 781-2 외2필지3901931136050291철근콘크리트구조2023-09-152023-11-012023-10-30<NA>2023-08-297023.641제1종근린생활시설소매점,의원 (제2종근린생활시설 학원,사무소)제3종일반주거지역<NA>상대보호구역8000가공 건축사사무소부산광역시 사하구 낙동남로1353번길 32, 골드빌 301호종합건축사사무소 삼원부산광역시 사하구 하신번영로 210, 3층 (하단동)(주)태건종합건설부산광역시 동래구 아시아드대로181번길 12, 사직동 56-14
7대수선2023-건축과-대수선허가-6부산광역시 동래구 사직동 159-7잡종지69421227203139경량철골구조2023-08-082023-08-242023-08-232023-09-272023-07-31207.41위험물저장및처리시설자동차관련시설제2종일반주거지역<NA>상대보호구역1000올리브 건축사사무소부산광역시 북구 사상로 579, (구포동)C동 2층 204호올리브 건축사사무소부산광역시 북구 사상로 579, (구포동)C동 2층 204호<NA>경상남도 창원시 진해구 안골로 359, 107동 1004호(용원동, 일신님아파트)
8신축2023-건축과-신축허가-22부산광역시 동래구 온천동 210-835244174238080734철근콘크리트구조2023-07-312023-10-122023-09-05<NA>2023-07-1111145.31제1종근린생활시설제2종근린생활시설가로구역별최고높이제한지역방화지구데이터미집계41000삼주건축 건축사사무소부산광역시 수영구 수영로652번길 6, 광안동, 정원센텀뷰 202호삼주건축 건축사사무소부산광역시 수영구 수영로652번길 6, 광안동, 정원센텀뷰 202호(주)동인종합건설부산광역시 부산진구 백양대로18번길 54, 4층 (부암동, 다온빌딩)
9용도변경2023-건축과-용도변경허가-43부산광역시 동래구 안락동 631-621467613205290데이터미집계2023-07-252023-08-282023-08-142023-11-132023-07-19206.51단독주택다가구주택제2종일반주거지역<NA>절대정화구역0105HY건축사사무소부산광역시 금정구 금강로279번길 3, 지하1층HY건축사사무소부산광역시 금정구 금강로279번길 3, 지하1층<NA>부산광역시 연제구 중앙대로 1164, 923호
건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명설계자 도로명주소감리사무소명감리자 도로명주소시공자사무소명시공자 도로명주소
39신축2022-건축과-신축허가-61부산광역시 동래구 온천동 1026 외2필지117420339801734일반철골구조2022-08-242023-06-232023-06-12<NA>2022-07-13208.01동물및식물관련시설온실제1종일반주거지역<NA>데이터미집계9000탄탄건축사사무소부산광역시 부산진구 중앙대로 984, 5층와이건축사사무소부산광역시 동래구 충렬대로446번길 67, 상가 2층 209호(주)성운종합건설경상남도 김해시 해반천로 6
40신축2022-건축과-신축허가-56부산광역시 동래구 온천동 1447-12 외1필지562447999080175철근콘크리트구조2022-07-192023-07-172023-07-11<NA>2022-06-074120.21제2종근린생활시설일반음식점일반상업지역방화지구데이터미집계9200건축사사무소 마온부산광역시 해운대구 재반로11번길 76, 재정빌딩 401호건축사사무소 건일부산광역시 해운대구 마린시티3로 1, 626호 (우동, 선프라자)태흥종합건설(주)부산광역시 부산진구 동평로 396, 4층
41신축2022-건축과-신축허가-40부산광역시 동래구 온천동 154-144873862098079392철근콘크리트구조2022-05-172023-02-132023-02-01<NA>2022-04-227137.51제1종근린생활시설소매점, 일반음식점, 의원일반상업지역방화지구데이터미집계35000(주)종합건축사사무소 디엔지부산광역시 연제구 법원남로9번길 6, 6층 (거제동, 석천빌딩)(주)무명건축사사무소부산광역시 금정구 금강로 320 (장전동)에스에이치시종합건설(주)부산광역시 해운대구 마린시티3로 1, 531호(우동, 선프라자오피스텔)
42신축2022-건축과-신축허가-33부산광역시 동래구 온천동 707-516548251911050116철근콘크리트구조2022-04-222023-02-092023-02-012023-11-062022-03-243014.43제2종근린생활시설<NA>제3종일반주거지역<NA>데이터미집계14000다솜건축사사무소부산광역시 동래구 충렬대로237번길 90, 2층 203호건축사사무소 왕건부산광역시 부산진구 부전로152번길 40 (부전동)초우종합건설(주)부산광역시 남구 진남로 201, 4층(문현동)
43대수선2022-건축과-대수선허가-2부산광역시 동래구 온천동 1464-46704472916067362철근콘크리트구조2022-03-312023-07-262023-07-24<NA>2022-03-108124.41숙박시설(호텔)가로구역별최고높이제한지역방화지구상대보호구역11000더 KEUN&rsquo;s 건축사사무소부산광역시 연제구 쌍미천로 70, 연산삼성타워맨션 상가 2층더 KEUNs 건축사사무소부산광역시 연제구 쌍미천로 70, 연산삼성타워맨션 상가 2층<NA><NA>
44신축2022-건축과-신축허가-21부산광역시 동래구 온천동 707-1640319638050100철근콘크리트구조2022-03-292023-02-062023-02-062023-10-162022-03-23208.81제2종근린생활시설<NA>제3종일반주거지역<NA>데이터미집계5000다솜건축사사무소부산광역시 동래구 충렬대로237번길 90, 2층 203호서우 건축사사무소부산광역시 금정구 범어천로38번길 10, 남산동초우종합건설(주)부산광역시 남구 진남로 201, 4층
45신축2022-건축과-신축허가-20부산광역시 동래구 명장동 24-1712269199057163철근콘크리트구조2022-03-282023-04-142023-04-202023-09-222022-03-143010.151제2종근린생활시설<NA>제2종일반주거지역<NA>상대보호구역1000건축사사무소 금강부산광역시 금정구 중앙대로1793번길 70, 201(부곡동,위클라우드4차2층)건축사사무소 젬마부산광역시 연제구 중앙대로 1131, 1102호<NA>부산광역시 금정구 중앙대로1629번길 16, 105동 604호(부곡동,삼한골든뷰에듀스테이션)
46신축2021-건축과-신축허가-91부산광역시 동래구 온천동 1218-5372223594060105철근콘크리트구조2021-12-172023-07-102023-07-10<NA>2021-12-032111.651제2종근린생활시설제조업소,단독주택제2종일반주거지역<NA>데이터미집계4001아이제이건축사사무소부산광역시 해운대구 해운대로 785, 1520호(좌동,까르띠움)아이제이건축사사무소부산광역시 해운대구 해운대로 785, 1520(좌동,까르띠움)주식회사 지안종합건설경상남도 양산시 동면 금오로 247, 3층 306호 지안종합건설
47대수선2021-건축과-대수선허가-6부산광역시 동래구 명륜동 624-1 외1필지170149704087350철근콘크리트구조2021-06-182023-05-232023-05-292023-08-022021-06-044114.51제1종근린생활시설사무소,소매점,다방일반상업지역방화지구데이터미집계0000세정건축사사무소부산광역시 동구 중앙대로308번길 3-6, 초량동 향군빌딩 2층세정건축사사무소부산광역시 동구 중앙대로308번길 3-6, 향군회관 2층제이와이건설부산광역시 금정구 중앙대로 1893, 3층 304호
48증축2022-건축과-증축허가-19부산광역시 동래구 온천동 1666-2 외1필지11751904872931626철근콘크리트구조2020-06-222023-03-092023-03-132023-11-30<NA>216.34제2종근린생활시설<NA>자연녹지지역<NA>상대보호구역2000대상 건축사사무소부산광역시 부산진구 성지로 118, 유성빌딩4층대상 건축사사무소부산광역시 부산진구 성지로 118, 유성빌딩4층<NA>부산광역시 동래구 쇠미로129번길 102-27 (온천동)