Overview

Dataset statistics

Number of variables26
Number of observations77
Missing cells325
Missing cells (%)16.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory218.7 B

Variable types

Categorical9
Text6
Numeric7
DateTime4

Dataset

Description부산광역시 동구 건축허가현황(신축, 개축, 증축, 대수선, 용도변경 등) - 허가번호, 대지위치, 면적, 건폐율, 용적율, 허가일, 높이, 층수, 용도, 건축관계자 등 정보 제공
Author부산광역시 동구
URLhttps://www.data.go.kr/data/3040089/fileData.do

Alerts

지목 is highly imbalanced (82.8%)Imbalance
동수 is highly imbalanced (85.0%)Imbalance
착공처리일 has 59 (76.6%) missing valuesMissing
착공예정일 has 59 (76.6%) missing valuesMissing
사용승인일 has 69 (89.6%) missing valuesMissing
부속용도 has 10 (13.0%) missing valuesMissing
설계사무소명 has 1 (1.3%) missing valuesMissing
감리사무소명 has 63 (81.8%) missing valuesMissing
시공자사무소명 has 64 (83.1%) missing valuesMissing
건축면적(제곱미터) has 1 (1.3%) zerosZeros
건폐율(퍼센트) has 1 (1.3%) zerosZeros
용적률(퍼센트) has 1 (1.3%) zerosZeros
최대지상층수 has 1 (1.3%) zerosZeros
최고높이(m) has 8 (10.4%) zerosZeros

Reproduction

Analysis started2023-12-12 08:12:27.240263
Analysis finished2023-12-12 08:12:27.832421
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
용도변경
46 
신축
21 
대수선
7 
증축
 
3

Length

Max length4
Median length4
Mean length3.2857143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용도변경 46
59.7%
신축 21
27.3%
대수선 7
 
9.1%
증축 3
 
3.9%

Length

2023-12-12T17:12:27.930111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:28.085129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용도변경 46
59.7%
신축 21
27.3%
대수선 7
 
9.1%
증축 3
 
3.9%

허가번호
Text

Distinct75
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-12T17:12:28.436050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.948052
Min length15

Characters and Unicode

Total characters1305
Distinct characters29
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

Unique73 ?
Unique (%)94.8%

Sample

1st row2023-건축과-용도변경허가-19
2nd row2023-건축과-공용건축물-3
3rd row2023-건축과-용도변경허가-18
4th row2023-건축과-용도변경허가-17
5th row2023-건축과-용도변경허가-16
ValueCountFrequency (%)
2022-건축과-용도변경허가-53 2
 
2.6%
2022-건축과-공용건축물-2 2
 
2.6%
2022-건축과-용도변경허가-42 1
 
1.3%
2022-건축과-용도변경허가-44 1
 
1.3%
2022-건축과-용도변경허가-55 1
 
1.3%
2022-건축과-대수선허가-6 1
 
1.3%
2022-건축과-대수선허가-7 1
 
1.3%
2022-건축과-대수선허가-8 1
 
1.3%
2022-건축과-용도변경허가-56 1
 
1.3%
2022-건축과-용도변경허가-57 1
 
1.3%
Other values (65) 65
84.4%
2023-12-12T17:12:28.995849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 231
17.7%
2 210
16.1%
축 102
 
7.8%
건 84
 
6.4%
0 81
 
6.2%
과 77
 
5.9%
허 70
 
5.4%
가 70
 
5.4%
용 52
 
4.0%
변 46
 
3.5%
Other values (19) 282
21.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
49.3%
Decimal Number 430
33.0%
Dash Punctuation 231
 
17.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 102
15.8%
건 84
13.0%
과 77
12.0%
허 70
10.9%
가 70
10.9%
용 52
8.1%
변 46
7.1%
경 46
7.1%
도 46
7.1%
신 17
 
2.6%
Other values (8) 34
 
5.3%
Decimal Number
ValueCountFrequency (%)
2 210
48.8%
0 81
 
18.8%
3 41
 
9.5%
1 27
 
6.3%
5 19
 
4.4%
6 16
 
3.7%
4 16
 
3.7%
8 7
 
1.6%
7 7
 
1.6%
9 6
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 661
50.7%
Hangul 644
49.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 102
15.8%
건 84
13.0%
과 77
12.0%
허 70
10.9%
가 70
10.9%
용 52
8.1%
변 46
7.1%
경 46
7.1%
도 46
7.1%
신 17
 
2.6%
Other values (8) 34
 
5.3%
Common
ValueCountFrequency (%)
- 231
34.9%
2 210
31.8%
0 81
 
12.3%
3 41
 
6.2%
1 27
 
4.1%
5 19
 
2.9%
6 16
 
2.4%
4 16
 
2.4%
8 7
 
1.1%
7 7
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661
50.7%
Hangul 644
49.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 231
34.9%
2 210
31.8%
0 81
 
12.3%
3 41
 
6.2%
1 27
 
4.1%
5 19
 
2.9%
6 16
 
2.4%
4 16
 
2.4%
8 7
 
1.1%
7 7
 
1.1%
Hangul
ValueCountFrequency (%)
축 102
15.8%
건 84
13.0%
과 77
12.0%
허 70
10.9%
가 70
10.9%
용 52
8.1%
변 46
7.1%
경 46
7.1%
도 46
7.1%
신 17
 
2.6%
Other values (8) 34
 
5.3%

대지위치
Text

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-12T17:12:29.375625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length27
Mean length20.454545
Min length15

Characters and Unicode

Total characters1575
Distinct characters46
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)87.0%

Sample

1st row부산광역시 동구 범일동 571-2
2nd row부산광역시 동구 수정동 1011-886
3rd row부산광역시 동구 범일동 1438-143
4th row부산광역시 동구 초량동 1030 외1필지
5th row부산광역시 동구 초량동 133-5
ValueCountFrequency (%)
부산광역시 77
23.4%
동구 77
23.4%
초량동 30
 
9.1%
수정동 21
 
6.4%
범일동 21
 
6.4%
외1필지 8
 
2.4%
좌천동 5
 
1.5%
830-140 3
 
0.9%
외3필지 3
 
0.9%
1163-10 3
 
0.9%
Other values (76) 81
24.6%
2023-12-12T17:12:29.854634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
16.0%
동 154
 
9.8%
1 115
 
7.3%
부 78
 
5.0%
구 78
 
5.0%
산 78
 
5.0%
광 77
 
4.9%
역 77
 
4.9%
시 77
 
4.9%
- 71
 
4.5%
Other values (36) 518
32.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 840
53.3%
Decimal Number 405
25.7%
Space Separator 252
 
16.0%
Dash Punctuation 71
 
4.5%
Uppercase Letter 5
 
0.3%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 154
18.3%
부 78
9.3%
구 78
9.3%
산 78
9.3%
광 77
9.2%
역 77
9.2%
시 77
9.2%
초 30
 
3.6%
량 30
 
3.6%
일 21
 
2.5%
Other values (18) 140
16.7%
Decimal Number
ValueCountFrequency (%)
1 115
28.4%
2 46
 
11.4%
3 45
 
11.1%
0 44
 
10.9%
4 35
 
8.6%
5 29
 
7.2%
7 26
 
6.4%
8 25
 
6.2%
6 21
 
5.2%
9 19
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
T 1
20.0%
I 1
20.0%
L 1
20.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 840
53.3%
Common 730
46.3%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 154
18.3%
부 78
9.3%
구 78
9.3%
산 78
9.3%
광 77
9.2%
역 77
9.2%
시 77
9.2%
초 30
 
3.6%
량 30
 
3.6%
일 21
 
2.5%
Other values (18) 140
16.7%
Common
ValueCountFrequency (%)
252
34.5%
1 115
15.8%
- 71
 
9.7%
2 46
 
6.3%
3 45
 
6.2%
0 44
 
6.0%
4 35
 
4.8%
5 29
 
4.0%
7 26
 
3.6%
8 25
 
3.4%
Other values (4) 42
 
5.8%
Latin
ValueCountFrequency (%)
B 2
40.0%
T 1
20.0%
I 1
20.0%
L 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 840
53.3%
ASCII 735
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
34.3%
1 115
15.6%
- 71
 
9.7%
2 46
 
6.3%
3 45
 
6.1%
0 44
 
6.0%
4 35
 
4.8%
5 29
 
3.9%
7 26
 
3.5%
8 25
 
3.4%
Other values (8) 47
 
6.4%
Hangul
ValueCountFrequency (%)
동 154
18.3%
부 78
9.3%
구 78
9.3%
산 78
9.3%
광 77
9.2%
역 77
9.2%
시 77
9.2%
초 30
 
3.6%
량 30
 
3.6%
일 21
 
2.5%
Other values (18) 140
16.7%

지목
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
대
73 
종교용지
 
1
도로
 
1
학교용지
 
1
주차장
 
1

Length

Max length4
Median length1
Mean length1.1168831
Min length1

Unique

Unique4 ?
Unique (%)5.2%

Sample

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

Common Values

ValueCountFrequency (%)
대 73
94.8%
종교용지 1
 
1.3%
도로 1
 
1.3%
학교용지 1
 
1.3%
주차장 1
 
1.3%

Length

2023-12-12T17:12:30.010047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:30.123880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 73
94.8%
종교용지 1
 
1.3%
도로 1
 
1.3%
학교용지 1
 
1.3%
주차장 1
 
1.3%

대지면적(제곱미터)
Real number (ℝ)

Distinct69
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1535.8343
Minimum28
Maximum24961.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:30.242584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile39.4
Q187
median244.1
Q3670
95-th percentile8222.56
Maximum24961.4
Range24933.4
Interquartile range (IQR)583

Descriptive statistics

Standard deviation4078.6675
Coefficient of variation (CV)2.655669
Kurtosis17.200058
Mean1535.8343
Median Absolute Deviation (MAD)175.1
Skewness3.9708871
Sum118259.24
Variance16635528
MonotonicityNot monotonic
2023-12-12T17:12:30.401316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6990.1 3
 
3.9%
375.2 3
 
3.9%
49.0 2
 
2.6%
189.74 2
 
2.6%
205.0 2
 
2.6%
40.0 2
 
2.6%
355.1 1
 
1.3%
283.0 1
 
1.3%
46.0 1
 
1.3%
32.7 1
 
1.3%
Other values (59) 59
76.6%
ValueCountFrequency (%)
28.0 1
1.3%
32.7 1
1.3%
33.1 1
1.3%
37.0 1
1.3%
40.0 2
2.6%
43.0 1
1.3%
46.0 1
1.3%
46.3 1
1.3%
49.0 2
2.6%
56.0 1
1.3%
ValueCountFrequency (%)
24961.4 1
 
1.3%
16715.0 1
 
1.3%
13369.9 1
 
1.3%
13152.4 1
 
1.3%
6990.1 3
3.9%
4010.7 1
 
1.3%
3897.8 1
 
1.3%
1268.4 1
 
1.3%
1254.9 1
 
1.3%
1201.87 1
 
1.3%

건축면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct72
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean765.20388
Minimum0
Maximum14346.93
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:30.538805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32.256
Q157.92
median149.6
Q3350.61
95-th percentile4857.51
Maximum14346.93
Range14346.93
Interquartile range (IQR)292.69

Descriptive statistics

Standard deviation2131.518
Coefficient of variation (CV)2.7855557
Kurtosis25.289148
Mean765.20388
Median Absolute Deviation (MAD)104.19
Skewness4.7609182
Sum58920.699
Variance4543369.1
MonotonicityNot monotonic
2023-12-12T17:12:30.702523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350.61 3
 
3.9%
4857.51 2
 
2.6%
149.6 2
 
2.6%
45.88 2
 
2.6%
60.23 1
 
1.3%
321.06 1
 
1.3%
30.78 1
 
1.3%
130.83 1
 
1.3%
562.04 1
 
1.3%
614.6 1
 
1.3%
Other values (62) 62
80.5%
ValueCountFrequency (%)
0.0 1
1.3%
23.94 1
1.3%
30.74 1
1.3%
30.78 1
1.3%
32.625 1
1.3%
34.51 1
1.3%
34.81 1
1.3%
35.34 1
1.3%
43.11 1
1.3%
43.64 1
1.3%
ValueCountFrequency (%)
14346.93 1
1.3%
9668.03 1
1.3%
4857.61 1
1.3%
4857.51 2
2.6%
2992.2839 1
1.3%
1950.55 1
1.3%
1004.38 1
1.3%
989.98 1
1.3%
975.83 1
1.3%
905.47 1
1.3%

연면적(제곱미터)
Real number (ℝ)

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9534.1592
Minimum34.81
Maximum152077.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:30.882113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.81
5-th percentile58.824
Q1127.32
median661.47
Q33227.11
95-th percentile77201.186
Maximum152077.05
Range152042.24
Interquartile range (IQR)3099.79

Descriptive statistics

Standard deviation28396.787
Coefficient of variation (CV)2.9784259
Kurtosis13.26318
Mean9534.1592
Median Absolute Deviation (MAD)581.97
Skewness3.7011095
Sum734130.26
Variance8.0637752 × 108
MonotonicityNot monotonic
2023-12-12T17:12:31.069057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3227.11 3
 
3.9%
111188.62 3
 
3.9%
670.2 2
 
2.6%
79.5 2
 
2.6%
91.23 1
 
1.3%
259.93 1
 
1.3%
61.56 1
 
1.3%
835.219 1
 
1.3%
5666.85 1
 
1.3%
9949.71 1
 
1.3%
Other values (61) 61
79.2%
ValueCountFrequency (%)
34.81 1
1.3%
35.34 1
1.3%
43.64 1
1.3%
47.88 1
1.3%
61.56 1
1.3%
65.125 1
1.3%
68.96 1
1.3%
69.02 1
1.3%
79.5 2
2.6%
80.15 1
1.3%
ValueCountFrequency (%)
152077.05 1
 
1.3%
111188.62 3
3.9%
68704.3277 1
 
1.3%
48985.1 1
 
1.3%
17060.6 1
 
1.3%
12780.01 1
 
1.3%
9949.71 1
 
1.3%
9918.8425 1
 
1.3%
7123.8 1
 
1.3%
6874.5 1
 
1.3%

건폐율(퍼센트)
Real number (ℝ)

ZEROS 

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.176462
Minimum0
Maximum112.23
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:31.268545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile44.716
Q158.89
median74.6075
Q380.72
95-th percentile97.478
Maximum112.23
Range112.23
Interquartile range (IQR)21.83

Descriptive statistics

Standard deviation19.850222
Coefficient of variation (CV)0.27888745
Kurtosis2.5758892
Mean71.176462
Median Absolute Deviation (MAD)10.0108
Skewness-1.0311021
Sum5480.5876
Variance394.03131
MonotonicityNot monotonic
2023-12-12T17:12:31.444282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93.4462 3
 
3.9%
69.49 3
 
3.9%
78.84 2
 
2.6%
93.6327 2
 
2.6%
76.85 1
 
1.3%
45.6314 1
 
1.3%
109.93 1
 
1.3%
86.27 1
 
1.3%
80.9 1
 
1.3%
59.29 1
 
1.3%
Other values (61) 61
79.2%
ValueCountFrequency (%)
0.0 1
1.3%
5.11 1
1.3%
23.4936 1
1.3%
42.57 1
1.3%
45.2525 1
1.3%
45.6314 1
1.3%
47.92 1
1.3%
49.46 1
1.3%
49.55 1
1.3%
50.0423 1
1.3%
ValueCountFrequency (%)
112.23 1
 
1.3%
109.93 1
 
1.3%
99.77 1
 
1.3%
98.95 1
 
1.3%
97.11 1
 
1.3%
96.6882 1
 
1.3%
95.51 1
 
1.3%
93.6327 2
2.6%
93.4462 3
3.9%
87.76 1
 
1.3%

용적률(퍼센트)
Real number (ℝ)

ZEROS 

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355.14657
Minimum0
Maximum1198.9812
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:31.637286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile52.27312
Q1136.7
median213.5319
Q3448.62
95-th percentile1109.02
Maximum1198.9812
Range1198.9812
Interquartile range (IQR)311.92

Descriptive statistics

Standard deviation324.94603
Coefficient of variation (CV)0.91496315
Kurtosis0.77240576
Mean355.14657
Median Absolute Deviation (MAD)118.5281
Skewness1.3362883
Sum27346.286
Variance105589.92
MonotonicityNot monotonic
2023-12-12T17:12:31.853112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
730.7729 3
 
3.9%
1109.02 3
 
3.9%
293.3 2
 
2.6%
162.2449 2
 
2.6%
228.07 1
 
1.3%
85.7 1
 
1.3%
219.86 1
 
1.3%
448.62 1
 
1.3%
671.99 1
 
1.3%
850.2306 1
 
1.3%
Other values (61) 61
79.2%
ValueCountFrequency (%)
0.0 1
1.3%
15.68 1
1.3%
23.4936 1
1.3%
42.57 1
1.3%
54.6989 1
1.3%
64.5967 1
1.3%
64.61 1
1.3%
75.67 1
1.3%
80.15 1
1.3%
85.7 1
1.3%
ValueCountFrequency (%)
1198.9812 1
 
1.3%
1196.7108 1
 
1.3%
1141.95 1
 
1.3%
1109.02 3
3.9%
1023.18 1
 
1.3%
1014.3591 1
 
1.3%
850.2306 1
 
1.3%
730.7729 3
3.9%
671.99 1
 
1.3%
641.4 1
 
1.3%

구조
Categorical

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size748.0 B
철근콘크리트구조
49 
블록구조
12 
<NA>
7 
일반철골구조
 
4
철골철근콘크리트구조
 
2
Other values (2)
 
3

Length

Max length10
Median length8
Mean length6.8181818
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 49
63.6%
블록구조 12
 
15.6%
<NA> 7
 
9.1%
일반철골구조 4
 
5.2%
철골철근콘크리트구조 2
 
2.6%
벽돌구조 2
 
2.6%
일반목구조 1
 
1.3%

Length

2023-12-12T17:12:32.068507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:32.238692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 49
63.6%
블록구조 12
 
15.6%
na 7
 
9.1%
일반철골구조 4
 
5.2%
철골철근콘크리트구조 2
 
2.6%
벽돌구조 2
 
2.6%
일반목구조 1
 
1.3%

허가일
Date

Distinct65
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size748.0 B
Minimum2022-07-01 00:00:00
Maximum2023-06-15 00:00:00
2023-12-12T17:12:32.418972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:12:32.583214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct17
Distinct (%)94.4%
Missing59
Missing (%)76.6%
Memory size748.0 B
Minimum2022-08-26 00:00:00
Maximum2023-07-05 00:00:00
2023-12-12T17:12:32.756032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:12:33.254251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

착공예정일
Date

MISSING 

Distinct16
Distinct (%)88.9%
Missing59
Missing (%)76.6%
Memory size748.0 B
Minimum2022-08-25 00:00:00
Maximum2023-06-27 00:00:00
2023-12-12T17:12:33.373726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:12:33.511468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

사용승인일
Date

MISSING 

Distinct7
Distinct (%)87.5%
Missing69
Missing (%)89.6%
Memory size748.0 B
Minimum2022-12-06 00:00:00
Maximum2023-07-13 00:00:00
2023-12-12T17:12:33.631591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:12:33.761077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

최대지상층수
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5584416
Minimum0
Maximum30
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:33.916828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q38
95-th percentile25.2
Maximum30
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.2773866
Coefficient of variation (CV)1.1096213
Kurtosis3.4788257
Mean6.5584416
Median Absolute Deviation (MAD)2
Skewness2.0199536
Sum505
Variance52.960355
MonotonicityNot monotonic
2023-12-12T17:12:34.089021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2 21
27.3%
1 8
 
10.4%
4 8
 
10.4%
5 7
 
9.1%
6 6
 
7.8%
8 5
 
6.5%
3 4
 
5.2%
10 3
 
3.9%
20 3
 
3.9%
30 3
 
3.9%
Other values (8) 9
11.7%
ValueCountFrequency (%)
0 1
 
1.3%
1 8
 
10.4%
2 21
27.3%
3 4
 
5.2%
4 8
 
10.4%
5 7
 
9.1%
6 6
 
7.8%
7 1
 
1.3%
8 5
 
6.5%
9 2
 
2.6%
ValueCountFrequency (%)
30 3
3.9%
26 1
 
1.3%
25 1
 
1.3%
20 3
3.9%
17 1
 
1.3%
15 1
 
1.3%
12 1
 
1.3%
10 3
3.9%
9 2
 
2.6%
8 5
6.5%

최대지하층수
Categorical

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size748.0 B
<NA>
25 
1
21 
0
14 
2
12 
6
4 

Length

Max length4
Median length1
Mean length1.974026
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
32.5%
1 21
27.3%
0 14
18.2%
2 12
15.6%
6 4
 
5.2%
4 1
 
1.3%

Length

2023-12-12T17:12:34.244774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:34.413356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
32.5%
1 21
27.3%
0 14
18.2%
2 12
15.6%
6 4
 
5.2%
4 1
 
1.3%

최고높이(m)
Real number (ℝ)

ZEROS 

Distinct57
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.042338
Minimum0
Maximum114.35
Zeros8
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-12T17:12:34.571582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median11
Q326.8
95-th percentile81.124
Maximum114.35
Range114.35
Interquartile range (IQR)19.8

Descriptive statistics

Standard deviation26.897369
Coefficient of variation (CV)1.2202594
Kurtosis4.1423587
Mean22.042338
Median Absolute Deviation (MAD)7.2
Skewness2.0838698
Sum1697.26
Variance723.46847
MonotonicityNot monotonic
2023-12-12T17:12:34.764975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
10.4%
114.35 3
 
3.9%
8.0 3
 
3.9%
35.0 3
 
3.9%
7.0 3
 
3.9%
7.2 2
 
2.6%
7.8 2
 
2.6%
5.5 2
 
2.6%
11.9 2
 
2.6%
3.0 2
 
2.6%
Other values (47) 47
61.0%
ValueCountFrequency (%)
0.0 8
10.4%
1.0 1
 
1.3%
2.7 1
 
1.3%
3.0 2
 
2.6%
4.02 1
 
1.3%
4.2 1
 
1.3%
4.5 1
 
1.3%
5.5 2
 
2.6%
6.0 1
 
1.3%
6.5 1
 
1.3%
ValueCountFrequency (%)
114.35 3
3.9%
85.7 1
 
1.3%
79.98 1
 
1.3%
76.4 1
 
1.3%
67.8 1
 
1.3%
59.75 1
 
1.3%
58.6 1
 
1.3%
45.75 1
 
1.3%
43.2 1
 
1.3%
38.85 1
 
1.3%

동수
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
1
74 
3
 
1
2
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)3.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 74
96.1%
3 1
 
1.3%
2 1
 
1.3%
5 1
 
1.3%

Length

2023-12-12T17:12:34.940618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:35.041267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 74
96.1%
3 1
 
1.3%
2 1
 
1.3%
5 1
 
1.3%

주용도
Categorical

Distinct13
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size748.0 B
제2종근린생활시설
27 
제1종근린생활시설
16 
업무시설
15 
단독주택
4 
숙박시설
3 
Other values (8)
12 

Length

Max length9
Median length9
Mean length6.8961039
Min length2

Unique

Unique5 ?
Unique (%)6.5%

Sample

1st row제2종근린생활시설
2nd row노유자시설
3rd row제2종근린생활시설
4th row숙박시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 27
35.1%
제1종근린생활시설 16
20.8%
업무시설 15
19.5%
단독주택 4
 
5.2%
숙박시설 3
 
3.9%
의료시설 3
 
3.9%
노유자시설 2
 
2.6%
공동주택 2
 
2.6%
교정및군사시설 1
 
1.3%
공장 1
 
1.3%
Other values (3) 3
 
3.9%

Length

2023-12-12T17:12:35.184143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 27
35.1%
제1종근린생활시설 16
20.8%
업무시설 15
19.5%
단독주택 4
 
5.2%
숙박시설 3
 
3.9%
의료시설 3
 
3.9%
노유자시설 2
 
2.6%
공동주택 2
 
2.6%
교정및군사시설 1
 
1.3%
공장 1
 
1.3%
Other values (3) 3
 
3.9%

부속용도
Text

MISSING 

Distinct45
Distinct (%)67.2%
Missing10
Missing (%)13.0%
Memory size748.0 B
2023-12-12T17:12:35.410730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length22
Mean length8.4179104
Min length2

Characters and Unicode

Total characters564
Distinct characters92
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

Unique37 ?
Unique (%)55.2%

Sample

1st row일반음식점
2nd row노유자시설(노인복지시설)
3rd row숙박시설,근린생활시설
4th row(일반음식점)
5th row일반음식점
ValueCountFrequency (%)
일반음식점 11
 
14.9%
사무소 7
 
9.5%
오피스텔 4
 
5.4%
판매시설,운동시설,문화및집회시설,제1종근린생활시설 3
 
4.1%
업무시설 3
 
4.1%
근린생활시설 2
 
2.7%
제1종근린생활시설 2
 
2.7%
단독주택 2
 
2.7%
미용원 2
 
2.7%
소매점 2
 
2.7%
Other values (34) 36
48.6%
2023-12-12T17:12:35.782594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 40
 
7.1%
설 39
 
6.9%
, 37
 
6.6%
점 19
 
3.4%
활 18
 
3.2%
생 18
 
3.2%
근 17
 
3.0%
식 16
 
2.8%
무 16
 
2.8%
소 16
 
2.8%
Other values (82) 328
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
85.8%
Other Punctuation 37
 
6.6%
Decimal Number 15
 
2.7%
Close Punctuation 10
 
1.8%
Open Punctuation 9
 
1.6%
Space Separator 8
 
1.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 40
 
8.3%
설 39
 
8.1%
점 19
 
3.9%
활 18
 
3.7%
생 18
 
3.7%
근 17
 
3.5%
식 16
 
3.3%
무 16
 
3.3%
소 16
 
3.3%
린 16
 
3.3%
Other values (75) 269
55.6%
Decimal Number
ValueCountFrequency (%)
1 11
73.3%
2 4
 
26.7%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 484
85.8%
Common 80
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 40
 
8.3%
설 39
 
8.1%
점 19
 
3.9%
활 18
 
3.7%
생 18
 
3.7%
근 17
 
3.5%
식 16
 
3.3%
무 16
 
3.3%
소 16
 
3.3%
린 16
 
3.3%
Other values (75) 269
55.6%
Common
ValueCountFrequency (%)
, 37
46.2%
1 11
 
13.8%
) 10
 
12.5%
( 9
 
11.2%
8
 
10.0%
2 4
 
5.0%
- 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
85.8%
ASCII 80
 
14.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 40
 
8.3%
설 39
 
8.1%
점 19
 
3.9%
활 18
 
3.7%
생 18
 
3.7%
근 17
 
3.5%
식 16
 
3.3%
무 16
 
3.3%
소 16
 
3.3%
린 16
 
3.3%
Other values (75) 269
55.6%
ASCII
ValueCountFrequency (%)
, 37
46.2%
1 11
 
13.8%
) 10
 
12.5%
( 9
 
11.2%
8
 
10.0%
2 4
 
5.0%
- 1
 
1.2%

용도지역
Categorical

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size748.0 B
일반상업지역
33 
가로구역별최고높이제한지역
15 
제2종일반주거지역
14 
제3종일반주거지역
11 
준주거지역
 
3

Length

Max length13
Median length9
Mean length8.2727273
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row일반상업지역
2nd row제2종일반주거지역
3rd row제3종일반주거지역
4th row가로구역별최고높이제한지역
5th row일반상업지역

Common Values

ValueCountFrequency (%)
일반상업지역 33
42.9%
가로구역별최고높이제한지역 15
19.5%
제2종일반주거지역 14
18.2%
제3종일반주거지역 11
 
14.3%
준주거지역 3
 
3.9%
도시지역 1
 
1.3%

Length

2023-12-12T17:12:35.939672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:36.062663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반상업지역 33
42.9%
가로구역별최고높이제한지역 15
19.5%
제2종일반주거지역 14
18.2%
제3종일반주거지역 11
 
14.3%
준주거지역 3
 
3.9%
도시지역 1
 
1.3%

용도지구
Categorical

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
방화지구
48 
<NA>
21 
주거환경개선지구
7 
고도지구
 
1

Length

Max length8
Median length4
Mean length4.3636364
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
방화지구 48
62.3%
<NA> 21
27.3%
주거환경개선지구 7
 
9.1%
고도지구 1
 
1.3%

Length

2023-12-12T17:12:36.204634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:36.336674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방화지구 48
62.3%
na 21
27.3%
주거환경개선지구 7
 
9.1%
고도지구 1
 
1.3%

용도구역
Categorical

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size748.0 B
<NA>
27 
상대보호구역
24 
중점경관관리구역
12 
가축사육제한구역
11 
지구단위계획구역
 
2

Length

Max length8
Median length6
Mean length5.9220779
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
35.1%
상대보호구역 24
31.2%
중점경관관리구역 12
15.6%
가축사육제한구역 11
14.3%
지구단위계획구역 2
 
2.6%
정비구역 1
 
1.3%

Length

2023-12-12T17:12:36.500151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:12:36.681134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
35.1%
상대보호구역 24
31.2%
중점경관관리구역 12
15.6%
가축사육제한구역 11
14.3%
지구단위계획구역 2
 
2.6%
정비구역 1
 
1.3%

설계사무소명
Text

MISSING 

Distinct48
Distinct (%)63.2%
Missing1
Missing (%)1.3%
Memory size748.0 B
2023-12-12T17:12:36.994839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length11.157895
Min length8

Characters and Unicode

Total characters848
Distinct characters102
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)51.3%

Sample

1st row종합건축사사무소그룹영남 주식회사
2nd row(주)가산 건축사사무소
3rd row건축사사무소 준우
4th row바우엔건축사사무소
5th row수만채 건축사사무소
ValueCountFrequency (%)
건축사사무소 33
25.4%
주식회사 13
 
10.0%
도운 10
 
7.7%
종합건축사사무소 8
 
6.2%
가원건축사사무소 7
 
5.4%
수만채 5
 
3.8%
바우엔건축사사무소 3
 
2.3%
재성종합건축사사무소 3
 
2.3%
하나 3
 
2.3%
종합건축사사무소그룹영남 2
 
1.5%
Other values (41) 43
33.1%
2023-12-12T17:12:37.429640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 166
19.6%
건 82
 
9.7%
축 80
 
9.4%
무 76
 
9.0%
소 76
 
9.0%
65
 
7.7%
주 25
 
2.9%
합 22
 
2.6%
종 22
 
2.6%
식 14
 
1.7%
Other values (92) 220
25.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 751
88.6%
Space Separator 65
 
7.7%
Open Punctuation 11
 
1.3%
Close Punctuation 11
 
1.3%
Uppercase Letter 6
 
0.7%
Decimal Number 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 166
22.1%
건 82
10.9%
축 80
10.7%
무 76
10.1%
소 76
10.1%
주 25
 
3.3%
합 22
 
2.9%
종 22
 
2.9%
식 14
 
1.9%
회 14
 
1.9%
Other values (81) 174
23.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
16.7%
T 1
16.7%
A 1
16.7%
I 1
16.7%
N 1
16.7%
U 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 751
88.6%
Common 91
 
10.7%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 166
22.1%
건 82
10.9%
축 80
10.7%
무 76
10.1%
소 76
10.1%
주 25
 
3.3%
합 22
 
2.9%
종 22
 
2.9%
식 14
 
1.9%
회 14
 
1.9%
Other values (81) 174
23.2%
Latin
ValueCountFrequency (%)
C 1
16.7%
T 1
16.7%
A 1
16.7%
I 1
16.7%
N 1
16.7%
U 1
16.7%
Common
ValueCountFrequency (%)
65
71.4%
( 11
 
12.1%
) 11
 
12.1%
2 2
 
2.2%
1 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 751
88.6%
ASCII 97
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 166
22.1%
건 82
10.9%
축 80
10.7%
무 76
10.1%
소 76
10.1%
주 25
 
3.3%
합 22
 
2.9%
종 22
 
2.9%
식 14
 
1.9%
회 14
 
1.9%
Other values (81) 174
23.2%
ASCII
ValueCountFrequency (%)
65
67.0%
( 11
 
11.3%
) 11
 
11.3%
2 2
 
2.1%
1 2
 
2.1%
C 1
 
1.0%
T 1
 
1.0%
A 1
 
1.0%
I 1
 
1.0%
N 1
 
1.0%

감리사무소명
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing63
Missing (%)81.8%
Memory size748.0 B
2023-12-12T17:12:37.657007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.428571
Min length9

Characters and Unicode

Total characters160
Distinct characters46
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

Unique14 ?
Unique (%)100.0%

Sample

1st row수만채 건축사사무소
2nd row대승종합건축사사무소
3rd row(주)인터건축사사무소
4th row(주)시공종합건축사사무소
5th row(주)공감대한이앤씨건축사사무소
ValueCountFrequency (%)
건축사사무소 4
20.0%
주식회사 2
 
10.0%
수만채 1
 
5.0%
대승종합건축사사무소 1
 
5.0%
주)인터건축사사무소 1
 
5.0%
주)시공종합건축사사무소 1
 
5.0%
주)공감대한이앤씨건축사사무소 1
 
5.0%
아키펌-수려건축사사무소 1
 
5.0%
건축사사무소엠.디 1
 
5.0%
바우엔건축사사무소 1
 
5.0%
Other values (6) 6
30.0%
2023-12-12T17:12:38.102480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 30
18.8%
건 14
 
8.8%
축 14
 
8.8%
무 14
 
8.8%
소 14
 
8.8%
6
 
3.8%
주 6
 
3.8%
인 4
 
2.5%
) 4
 
2.5%
( 4
 
2.5%
Other values (36) 50
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
90.0%
Space Separator 6
 
3.8%
Close Punctuation 4
 
2.5%
Open Punctuation 4
 
2.5%
Other Punctuation 1
 
0.6%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 30
20.8%
건 14
 
9.7%
축 14
 
9.7%
무 14
 
9.7%
소 14
 
9.7%
주 6
 
4.2%
인 4
 
2.8%
수 2
 
1.4%
씨 2
 
1.4%
식 2
 
1.4%
Other values (31) 42
29.2%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144
90.0%
Common 16
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 30
20.8%
건 14
 
9.7%
축 14
 
9.7%
무 14
 
9.7%
소 14
 
9.7%
주 6
 
4.2%
인 4
 
2.8%
수 2
 
1.4%
씨 2
 
1.4%
식 2
 
1.4%
Other values (31) 42
29.2%
Common
ValueCountFrequency (%)
6
37.5%
) 4
25.0%
( 4
25.0%
. 1
 
6.2%
- 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
90.0%
ASCII 16
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 30
20.8%
건 14
 
9.7%
축 14
 
9.7%
무 14
 
9.7%
소 14
 
9.7%
주 6
 
4.2%
인 4
 
2.8%
수 2
 
1.4%
씨 2
 
1.4%
식 2
 
1.4%
Other values (31) 42
29.2%
ASCII
ValueCountFrequency (%)
6
37.5%
) 4
25.0%
( 4
25.0%
. 1
 
6.2%
- 1
 
6.2%

시공자사무소명
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing64
Missing (%)83.1%
Memory size748.0 B
2023-12-12T17:12:38.365066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.3076923
Min length3

Characters and Unicode

Total characters121
Distinct characters46
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

Unique13 ?
Unique (%)100.0%

Sample

1st row반야사
2nd row(주)가온건설산업
3rd row화풍종합건설(주)
4th row(주)석포종합건설 하민수
5th row(주)금강고려하우징
ValueCountFrequency (%)
반야사 1
 
6.7%
주)가온건설산업 1
 
6.7%
화풍종합건설(주 1
 
6.7%
주)석포종합건설 1
 
6.7%
하민수 1
 
6.7%
주)금강고려하우징 1
 
6.7%
엠에이치종합건설주식회사 1
 
6.7%
우림건설주식회사 1
 
6.7%
중아건설주식회사 1
 
6.7%
주식회사 1
 
6.7%
Other values (5) 5
33.3%
2023-12-12T17:12:38.784647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 12
 
9.9%
건 11
 
9.1%
설 11
 
9.1%
종 7
 
5.8%
합 7
 
5.8%
( 7
 
5.8%
) 7
 
5.8%
사 6
 
5.0%
식 5
 
4.1%
회 5
 
4.1%
Other values (36) 43
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
86.8%
Open Punctuation 7
 
5.8%
Close Punctuation 7
 
5.8%
Space Separator 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
11.4%
건 11
 
10.5%
설 11
 
10.5%
종 7
 
6.7%
합 7
 
6.7%
사 6
 
5.7%
식 5
 
4.8%
회 5
 
4.8%
우 2
 
1.9%
민 2
 
1.9%
Other values (33) 37
35.2%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
86.8%
Common 16
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 12
 
11.4%
건 11
 
10.5%
설 11
 
10.5%
종 7
 
6.7%
합 7
 
6.7%
사 6
 
5.7%
식 5
 
4.8%
회 5
 
4.8%
우 2
 
1.9%
민 2
 
1.9%
Other values (33) 37
35.2%
Common
ValueCountFrequency (%)
( 7
43.8%
) 7
43.8%
2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
86.8%
ASCII 16
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 12
 
11.4%
건 11
 
10.5%
설 11
 
10.5%
종 7
 
6.7%
합 7
 
6.7%
사 6
 
5.7%
식 5
 
4.8%
회 5
 
4.8%
우 2
 
1.9%
민 2
 
1.9%
Other values (33) 37
35.2%
ASCII
ValueCountFrequency (%)
( 7
43.8%
) 7
43.8%
2
 
12.5%

Sample

건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역설계사무소명감리사무소명시공자사무소명
0용도변경2023-건축과-용도변경허가-19부산광역시 동구 범일동 571-2대40.030.7491.2376.85228.07철근콘크리트구조2023-06-15<NA><NA><NA>3<NA>9.01제2종근린생활시설일반음식점일반상업지역방화지구가축사육제한구역종합건축사사무소그룹영남 주식회사<NA><NA>
1증축2023-건축과-공용건축물-3부산광역시 동구 수정동 1011-886대705.0319.031623.0445.2525213.5319철근콘크리트구조2023-06-142023-07-052023-06-19<NA>611.01노유자시설노유자시설(노인복지시설)제2종일반주거지역<NA>중점경관관리구역(주)가산 건축사사무소<NA><NA>
2용도변경2023-건축과-용도변경허가-18부산광역시 동구 범일동 1438-143대64.045.9868.9671.84107.75<NA>2023-05-24<NA><NA><NA>2<NA>7.41제2종근린생활시설<NA>제3종일반주거지역주거환경개선지구상대보호구역건축사사무소 준우<NA><NA>
3용도변경2023-건축과-용도변경허가-17부산광역시 동구 초량동 1030 외1필지대200.58106.8477.953.25238.26철근콘크리트구조2023-05-23<NA><NA><NA>5<NA>9.21숙박시설숙박시설,근린생활시설가로구역별최고높이제한지역방화지구중점경관관리구역<NA><NA><NA>
4용도변경2023-건축과-용도변경허가-16부산광역시 동구 초량동 133-5대145.17107.25198.4573.88136.7철근콘크리트구조2023-05-17<NA><NA><NA>2<NA>9.71제2종근린생활시설(일반음식점)일반상업지역방화지구<NA>바우엔건축사사무소<NA><NA>
5대수선2023-건축과-대수선허가-2부산광역시 동구 수정동 207-9대138.8108.6661.4778.24402.75철근콘크리트구조2023-05-112023-06-272023-06-27<NA>6118.51제1종근린생활시설<NA>일반상업지역방화지구가축사육제한구역수만채 건축사사무소수만채 건축사사무소<NA>
6신축2023-건축과-신축허가-9부산광역시 동구 초량동 386-4 외1필지대197.1127.32127.3264.596764.5967일반철골구조2023-05-08<NA><NA><NA>105.51제2종근린생활시설일반음식점가로구역별최고높이제한지역방화지구중점경관관리구역재성종합건축사사무소<NA><NA>
7신축2023-건축과-공용건축물-1부산광역시 동구 수정동 522-3 외5필지대520.5257.451227.5649.46187.25철근콘크리트구조2023-05-02<NA><NA><NA>4116.771제1종근린생활시설지역자치센터제3종일반주거지역주거환경개선지구중점경관관리구역금상 건축사사무소<NA><NA>
8대수선2023-건축과-대수선허가-1부산광역시 동구 수정동 707-111대49.045.8879.593.6327162.2449블록구조2023-04-272023-05-022023-05-012023-06-222<NA>7.21제2종근린생활시설일반음식점제2종일반주거지역<NA>중점경관관리구역건축사사무소 도운<NA><NA>
9신축2023-건축과-신축허가-8부산광역시 동구 범일동 1383-1종교용지707.0166.1166.123.493623.4936철근콘크리트구조2023-04-252023-06-152023-06-01<NA>105.51제2종근린생활시설종교집회장제2종일반주거지역<NA>상대보호구역(주)옛터건축사사무소대승종합건축사사무소반야사
건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일최대지상층수최대지하층수최고높이(m)동수주용도부속용도용도지역용도지구용도구역설계사무소명감리사무소명시공자사무소명
67용도변경2022-건축과-용도변경허가-46부산광역시 동구 초량동 1164-2대326.3174.351023.7853.43260.32철근콘크리트구조2022-08-03<NA><NA><NA>5117.721제1종근린생활시설의원,사무소일반상업지역방화지구상대보호구역바론건축사사무소<NA><NA>
68용도변경2022-건축과-용도변경허가-45부산광역시 동구 초량동 1163-10대375.2350.613227.1193.4462730.7729철근콘크리트구조2022-08-01<NA><NA><NA>8235.01업무시설사무소일반상업지역방화지구상대보호구역건축사사무소 도운<NA><NA>
69신축2022-건축과-신축허가-16부산광역시 동구 초량동 1153-11대283.0215.663399.9176.21141.95철근콘크리트구조2022-07-292022-12-232022-12-01<NA>20159.751업무시설오피스텔가로구역별최고높이제한지역방화지구<NA>도리천 건축사사무소도리천 건축사사무소(주)다민건설
70신축2022-건축과-신축허가-15부산광역시 동구 수정동 312-6 외2필지대355.1197.85497.3355.72140.05철근콘크리트구조2022-07-272022-09-012022-08-25<NA>4014.761공동주택다세대주택가로구역별최고높이제한지역방화지구<NA>성호건축사사무소건축사사무소 아누광덕에이스종합건설(주)
71증축2022-건축과-공용건축물-2부산광역시 동구 초량동 238-9대60.345.41117.3975.31194.68일반철골구조2022-07-22<NA><NA><NA>3<NA>11.01제2종근린생활시설창고일반상업지역<NA><NA>미건 종합건축사사무소<NA><NA>
72신축2022-건축과-신축허가-14부산광역시 동구 초량동 1057-42 외5필지대255.04192.751740.7875.57599.65철근콘크리트구조2022-07-22<NA><NA><NA>9232.61제1종근린생활시설소매점가로구역별최고높이제한지역방화지구상대보호구역(주)다움건축종합건축사사무소<NA><NA>
73용도변경2022-건축과-용도변경허가-43부산광역시 동구 초량동 754-117대43.048.2696.52112.23224.47블록구조2022-07-11<NA><NA><NA>2<NA>7.01제2종근린생활시설일반음식점제3종일반주거지역<NA>가축사육제한구역수만채 건축사사무소<NA><NA>
74용도변경2022-건축과-용도변경허가-44부산광역시 동구 수정동 277-1대102.543.6443.6442.5742.57일반목구조2022-07-11<NA><NA><NA>1<NA>4.51제2종근린생활시설음식점일반상업지역방화지구<NA>종합건축사사무소 손길<NA><NA>
75용도변경2022-건축과-용도변경허가-42부산광역시 동구 범일동 95-2 외1필지대205.0152.911347.074.5902577.3463철근콘크리트구조2022-07-05<NA><NA><NA>8125.11제1종근린생활시설제2종근린생활시설,교육연구시설,노유자시설가로구역별최고높이제한지역방화지구상대보호구역원심 건축사사무소<NA><NA>
76용도변경2022-건축과-용도변경허가-41부산광역시 동구 수정동 327-8대189.74149.6670.278.84293.3철근콘크리트구조2022-07-01<NA><NA><NA>4111.91제2종근린생활시설(일반음식점, 제조업소,약국,학원,단독주택)일반상업지역방화지구상대보호구역바우엔건축사사무소<NA><NA>