Overview

Dataset statistics

Number of variables29
Number of observations29
Missing cells183
Missing cells (%)21.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory248.6 B

Variable types

Categorical10
Text7
Numeric8
DateTime4

Dataset

Description부산광역시_수영구_건축허가현황_20230714
Author부산광역시 수영구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15014655

Alerts

지목 has constant value ""Constant
사용승인일 has constant value ""Constant
동수 has constant value ""Constant
지구 has constant value ""Constant
세대수 is highly imbalanced (63.2%)Imbalance
가구수 is highly imbalanced (57.2%)Imbalance
착공처리일 has 25 (86.2%) missing valuesMissing
착공예정일 has 25 (86.2%) missing valuesMissing
사용승인일 has 28 (96.6%) missing valuesMissing
부속용도 has 3 (10.3%) missing valuesMissing
지구 has 27 (93.1%) missing valuesMissing
호수 has 23 (79.3%) missing valuesMissing
감리사무소명 has 26 (89.7%) missing valuesMissing
시공자사무소명 has 26 (89.7%) missing valuesMissing
허가번호 has unique valuesUnique
호수 has 1 (3.4%) zerosZeros

Reproduction

Analysis started2023-12-10 16:30:51.426700
Analysis finished2023-12-10 16:30:51.832251
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
용도변경
15 
신축
7 
증축
4 
대수선
3 

Length

Max length4
Median length4
Mean length3.137931
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용도변경 15
51.7%
신축 7
24.1%
증축 4
 
13.8%
대수선 3
 
10.3%

Length

2023-12-11T01:30:51.903487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:52.016136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용도변경 15
51.7%
신축 7
24.1%
증축 4
 
13.8%
대수선 3
 
10.3%

허가번호
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T01:30:52.201288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16.37931
Min length15

Characters and Unicode

Total characters475
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

Unique29 ?
Unique (%)100.0%

Sample

1st row2023-건축과-용도변경허가-14
2nd row2023-건축과-용도변경허가-15
3rd row2023-건축과-증축허가-3
4th row2023-건축과-용도변경허가-11
5th row2023-건축과-용도변경허가-12
ValueCountFrequency (%)
2023-건축과-용도변경허가-14 1
 
3.4%
2023-건축과-대수선허가-2 1
 
3.4%
2023-건축과-신축허가-2 1
 
3.4%
2023-건축과-용도변경허가-1 1
 
3.4%
2023-건축과-용도변경허가-3 1
 
3.4%
2023-건축과-용도변경허가-2 1
 
3.4%
2023-건축과-신축허가-3 1
 
3.4%
2023-건축과-신축허가-4 1
 
3.4%
2023-건축과-용도변경허가-5 1
 
3.4%
2023-건축과-용도변경허가-4 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T01:30:52.530696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 87
18.3%
2 63
13.3%
축 40
8.4%
3 34
 
7.2%
0 30
 
6.3%
건 30
 
6.3%
과 29
 
6.1%
허 28
 
5.9%
가 28
 
5.9%
용 16
 
3.4%
Other values (17) 90
18.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 237
49.9%
Decimal Number 151
31.8%
Dash Punctuation 87
 
18.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 40
16.9%
건 30
12.7%
과 29
12.2%
허 28
11.8%
가 28
11.8%
용 16
 
6.8%
도 15
 
6.3%
변 15
 
6.3%
경 15
 
6.3%
신 7
 
3.0%
Other values (6) 14
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 63
41.7%
3 34
22.5%
0 30
19.9%
1 12
 
7.9%
4 3
 
2.0%
5 3
 
2.0%
7 2
 
1.3%
6 2
 
1.3%
9 1
 
0.7%
8 1
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 238
50.1%
Hangul 237
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 40
16.9%
건 30
12.7%
과 29
12.2%
허 28
11.8%
가 28
11.8%
용 16
 
6.8%
도 15
 
6.3%
변 15
 
6.3%
경 15
 
6.3%
신 7
 
3.0%
Other values (6) 14
 
5.9%
Common
ValueCountFrequency (%)
- 87
36.6%
2 63
26.5%
3 34
 
14.3%
0 30
 
12.6%
1 12
 
5.0%
4 3
 
1.3%
5 3
 
1.3%
7 2
 
0.8%
6 2
 
0.8%
9 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
50.1%
Hangul 237
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 87
36.6%
2 63
26.5%
3 34
 
14.3%
0 30
 
12.6%
1 12
 
5.0%
4 3
 
1.3%
5 3
 
1.3%
7 2
 
0.8%
6 2
 
0.8%
9 1
 
0.4%
Hangul
ValueCountFrequency (%)
축 40
16.9%
건 30
12.7%
과 29
12.2%
허 28
11.8%
가 28
11.8%
용 16
 
6.8%
도 15
 
6.3%
변 15
 
6.3%
경 15
 
6.3%
신 7
 
3.0%
Other values (6) 14
 
5.9%

대지위치
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T01:30:52.719870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.448276
Min length17

Characters and Unicode

Total characters564
Distinct characters31
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

Unique27 ?
Unique (%)93.1%

Sample

1st row부산광역시 수영구 민락동 164-16
2nd row부산광역시 수영구 민락동 15-10
3rd row부산광역시 수영구 남천동 52-3 외1필지
4th row부산광역시 수영구 민락동 18-31
5th row부산광역시 수영구 민락동 28-9
ValueCountFrequency (%)
부산광역시 29
24.6%
수영구 29
24.6%
민락동 11
 
9.3%
남천동 8
 
6.8%
망미동 5
 
4.2%
광안동 3
 
2.5%
외1필지 2
 
1.7%
수영동 2
 
1.7%
15-10 2
 
1.7%
164-17 1
 
0.8%
Other values (26) 26
22.0%
2023-12-11T01:30:53.010972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
15.8%
1 32
 
5.7%
광 32
 
5.7%
수 31
 
5.5%
영 31
 
5.5%
부 29
 
5.1%
역 29
 
5.1%
시 29
 
5.1%
구 29
 
5.1%
산 29
 
5.1%
Other values (21) 204
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 325
57.6%
Decimal Number 121
 
21.5%
Space Separator 89
 
15.8%
Dash Punctuation 29
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 32
9.8%
수 31
9.5%
영 31
9.5%
부 29
8.9%
역 29
8.9%
시 29
8.9%
구 29
8.9%
산 29
8.9%
동 29
8.9%
락 11
 
3.4%
Other values (9) 46
14.2%
Decimal Number
ValueCountFrequency (%)
1 32
26.4%
4 15
12.4%
2 14
11.6%
3 13
10.7%
5 11
 
9.1%
0 10
 
8.3%
7 9
 
7.4%
6 8
 
6.6%
8 6
 
5.0%
9 3
 
2.5%
Space Separator
ValueCountFrequency (%)
89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 325
57.6%
Common 239
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 32
9.8%
수 31
9.5%
영 31
9.5%
부 29
8.9%
역 29
8.9%
시 29
8.9%
구 29
8.9%
산 29
8.9%
동 29
8.9%
락 11
 
3.4%
Other values (9) 46
14.2%
Common
ValueCountFrequency (%)
89
37.2%
1 32
 
13.4%
- 29
 
12.1%
4 15
 
6.3%
2 14
 
5.9%
3 13
 
5.4%
5 11
 
4.6%
0 10
 
4.2%
7 9
 
3.8%
6 8
 
3.3%
Other values (2) 9
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 325
57.6%
ASCII 239
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
37.2%
1 32
 
13.4%
- 29
 
12.1%
4 15
 
6.3%
2 14
 
5.9%
3 13
 
5.4%
5 11
 
4.6%
0 10
 
4.2%
7 9
 
3.8%
6 8
 
3.3%
Other values (2) 9
 
3.8%
Hangul
ValueCountFrequency (%)
광 32
9.8%
수 31
9.5%
영 31
9.5%
부 29
8.9%
역 29
8.9%
시 29
8.9%
구 29
8.9%
산 29
8.9%
동 29
8.9%
락 11
 
3.4%
Other values (9) 46
14.2%

지목
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
대
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대 29
100.0%

Length

2023-12-11T01:30:53.150772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:53.271607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대 29
100.0%

대지면적
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean294.36379
Minimum39.85
Maximum873.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:53.417485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.85
5-th percentile98.14
Q1147.8
median238
Q3409.4
95-th percentile655.14
Maximum873.2
Range833.35
Interquartile range (IQR)261.6

Descriptive statistics

Standard deviation197.74972
Coefficient of variation (CV)0.67178684
Kurtosis1.4043835
Mean294.36379
Median Absolute Deviation (MAD)98.5
Skewness1.2612496
Sum8536.55
Variance39104.953
MonotonicityNot monotonic
2023-12-11T01:30:53.574173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
506.1 2
 
6.9%
139.5 1
 
3.4%
222.8 1
 
3.4%
135.0 1
 
3.4%
152.1 1
 
3.4%
249.0 1
 
3.4%
137.9 1
 
3.4%
97.5 1
 
3.4%
99.1 1
 
3.4%
302.8 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
39.85 1
3.4%
97.5 1
3.4%
99.1 1
3.4%
109.7 1
3.4%
135.0 1
3.4%
137.9 1
3.4%
139.5 1
3.4%
147.8 1
3.4%
152.1 1
3.4%
161.7 1
3.4%
ValueCountFrequency (%)
873.2 1
3.4%
700.5 1
3.4%
587.1 1
3.4%
506.1 2
6.9%
472.9 1
3.4%
446.9 1
3.4%
409.4 1
3.4%
336.3 1
3.4%
308.1 1
3.4%
302.8 1
3.4%

건축면적
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166.38586
Minimum33.78
Maximum479.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:53.764382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.78
5-th percentile58.662
Q182.38
median121.82
Q3244.2
95-th percentile372.44
Maximum479.9
Range446.12
Interquartile range (IQR)161.82

Descriptive statistics

Standard deviation113.65769
Coefficient of variation (CV)0.68309706
Kurtosis0.76518311
Mean166.38586
Median Absolute Deviation (MAD)58.09
Skewness1.1549808
Sum4825.19
Variance12918.071
MonotonicityNot monotonic
2023-12-11T01:30:53.892789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
274.38 2
 
6.9%
82.38 1
 
3.4%
130.05 1
 
3.4%
79.81 1
 
3.4%
84.43 1
 
3.4%
99.6 1
 
3.4%
69.85 1
 
3.4%
58.17 1
 
3.4%
59.4 1
 
3.4%
179.91 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
33.78 1
3.4%
58.17 1
3.4%
59.4 1
3.4%
62.42 1
3.4%
69.85 1
3.4%
78.38 1
3.4%
79.81 1
3.4%
82.38 1
3.4%
82.51 1
3.4%
84.43 1
3.4%
ValueCountFrequency (%)
479.9 1
3.4%
404.8 1
3.4%
323.9 1
3.4%
315.03 1
3.4%
274.38 2
6.9%
259.69 1
3.4%
244.2 1
3.4%
207.87 1
3.4%
200.96 1
3.4%
179.91 1
3.4%

연면적
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean753.68162
Minimum58.17
Maximum4104.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:54.031154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58.17
5-th percentile104.432
Q1178.2
median328.18
Q3992.27
95-th percentile2247.86
Maximum4104.44
Range4046.27
Interquartile range (IQR)814.07

Descriptive statistics

Standard deviation911.2811
Coefficient of variation (CV)1.2091062
Kurtosis5.729557
Mean753.68162
Median Absolute Deviation (MAD)197.1
Skewness2.2009329
Sum21856.767
Variance830433.24
MonotonicityNot monotonic
2023-12-11T01:30:54.203750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
908.43 2
 
6.9%
133.74 1
 
3.4%
488.72 1
 
3.4%
199.48 1
 
3.4%
328.18 1
 
3.4%
197.97 1
 
3.4%
131.08 1
 
3.4%
58.17 1
 
3.4%
178.2 1
 
3.4%
1555.637 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
58.17 1
3.4%
101.34 1
3.4%
109.07 1
3.4%
131.08 1
3.4%
131.96 1
3.4%
133.74 1
3.4%
172.56 1
3.4%
178.2 1
3.4%
195.47 1
3.4%
197.97 1
3.4%
ValueCountFrequency (%)
4104.44 1
3.4%
2573.14 1
3.4%
1759.94 1
3.4%
1724.15 1
3.4%
1555.637 1
3.4%
1469.86 1
3.4%
1119.52 1
3.4%
992.27 1
3.4%
908.43 2
6.9%
744.35 1
3.4%

건폐율
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.109603
Minimum40
Maximum84.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:54.350838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile44.6212
Q154.21
median58.37
Q359.65
95-th percentile69.29164
Maximum84.77
Range44.77
Interquartile range (IQR)5.44

Descriptive statistics

Standard deviation8.7017714
Coefficient of variation (CV)0.15236967
Kurtosis2.7891639
Mean57.109603
Median Absolute Deviation (MAD)2.86
Skewness0.8270509
Sum1656.1785
Variance75.720826
MonotonicityNot monotonic
2023-12-11T01:30:54.512501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
54.21 2
 
6.9%
59.0538 1
 
3.4%
58.37 1
 
3.4%
59.12 1
 
3.4%
55.51 1
 
3.4%
40.0 1
 
3.4%
50.6526 1
 
3.4%
59.6615 1
 
3.4%
59.94 1
 
3.4%
59.42 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
40.0 1
3.4%
44.502 1
3.4%
44.8 1
3.4%
46.2384 1
3.4%
48.47 1
3.4%
49.89 1
3.4%
50.6526 1
3.4%
54.21 2
6.9%
54.96 1
3.4%
55.51 1
3.4%
ValueCountFrequency (%)
84.77 1
3.4%
69.52 1
3.4%
68.9491 1
3.4%
66.62 1
3.4%
59.94 1
3.4%
59.76 1
3.4%
59.6615 1
3.4%
59.65 1
3.4%
59.6483 1
3.4%
59.42 1
3.4%

용적률
Real number (ℝ)

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194.74933
Minimum59.6615
Maximum713.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:54.660608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59.6615
5-th percentile78.29684
Q195.871
median162.64
Q3231.9775
95-th percentile507.704
Maximum713.5
Range653.8385
Interquartile range (IQR)136.1065

Descriptive statistics

Standard deviation148.36442
Coefficient of variation (CV)0.7618225
Kurtosis5.1353063
Mean194.74933
Median Absolute Deviation (MAD)67.5856
Skewness2.1861714
Sum5647.7307
Variance22012.002
MonotonicityNot monotonic
2023-12-11T01:30:54.809052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
162.64 2
 
6.9%
95.871 1
 
3.4%
163.57 1
 
3.4%
147.76 1
 
3.4%
215.77 1
 
3.4%
79.506 1
 
3.4%
95.0544 1
 
3.4%
59.6615 1
 
3.4%
179.82 1
 
3.4%
496.43 1
 
3.4%
Other values (18) 18
62.1%
ValueCountFrequency (%)
59.6615 1
3.4%
77.93 1
3.4%
78.8471 1
3.4%
79.506 1
3.4%
79.78 1
3.4%
84.58 1
3.4%
95.0544 1
3.4%
95.871 1
3.4%
99.43 1
3.4%
114.15 1
3.4%
ValueCountFrequency (%)
713.5 1
3.4%
515.22 1
3.4%
496.43 1
3.4%
265.01 1
3.4%
254.3 1
3.4%
236.11 1
3.4%
232.5281 1
3.4%
231.9775 1
3.4%
218.851 1
3.4%
215.77 1
3.4%

구조
Categorical

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
철근콘크리트구조
12 
<NA>
7 
일반철골구조
4 
블록구조
3 
벽돌구조
2 

Length

Max length8
Median length6
Mean length6
Min length4

Unique

Unique1 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 12
41.4%
<NA> 7
24.1%
일반철골구조 4
 
13.8%
블록구조 3
 
10.3%
벽돌구조 2
 
6.9%
시멘트블럭조 1
 
3.4%

Length

2023-12-11T01:30:54.946772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:55.080823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 12
41.4%
na 7
24.1%
일반철골구조 4
 
13.8%
블록구조 3
 
10.3%
벽돌구조 2
 
6.9%
시멘트블럭조 1
 
3.4%

허가일
Date

Distinct19
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2023-01-02 00:00:00
Maximum2023-02-24 00:00:00
2023-12-11T01:30:55.208508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:30:55.346712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

착공처리일
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing25
Missing (%)86.2%
Memory size364.0 B
Minimum2023-01-25 00:00:00
Maximum2023-03-13 00:00:00
2023-12-11T01:30:55.472106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:30:55.611868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

착공예정일
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing25
Missing (%)86.2%
Memory size364.0 B
Minimum2023-01-30 00:00:00
Maximum2023-03-13 00:00:00
2023-12-11T01:30:55.748239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:30:55.880145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

사용승인일
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing28
Missing (%)96.6%
Memory size364.0 B
Minimum2023-02-13 00:00:00
Maximum2023-02-13 00:00:00
2023-12-11T01:30:55.986346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:30:56.076701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

지상층수
Real number (ℝ)

Distinct9
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7931034
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:56.199661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q34
95-th percentile9.8
Maximum13
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7823334
Coefficient of variation (CV)0.73352427
Kurtosis4.3940171
Mean3.7931034
Median Absolute Deviation (MAD)1
Skewness2.0993632
Sum110
Variance7.7413793
MonotonicityNot monotonic
2023-12-11T01:30:56.391555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 11
37.9%
3 7
24.1%
4 3
 
10.3%
5 3
 
10.3%
8 1
 
3.4%
11 1
 
3.4%
7 1
 
3.4%
13 1
 
3.4%
1 1
 
3.4%
ValueCountFrequency (%)
1 1
 
3.4%
2 11
37.9%
3 7
24.1%
4 3
 
10.3%
5 3
 
10.3%
7 1
 
3.4%
8 1
 
3.4%
11 1
 
3.4%
13 1
 
3.4%
ValueCountFrequency (%)
13 1
 
3.4%
11 1
 
3.4%
8 1
 
3.4%
7 1
 
3.4%
5 3
 
10.3%
4 3
 
10.3%
3 7
24.1%
2 11
37.9%
1 1
 
3.4%

지하층수
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
11 
<NA>
9 
0
8 
3
 
1

Length

Max length4
Median length1
Mean length1.9310345
Min length1

Unique

Unique1 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 11
37.9%
<NA> 9
31.0%
0 8
27.6%
3 1
 
3.4%

Length

2023-12-11T01:30:56.578172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:56.699387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
37.9%
na 9
31.0%
0 8
27.6%
3 1
 
3.4%

최고높이
Real number (ℝ)

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.075172
Minimum3.9
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:30:56.869286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile6
Q17.6
median11.4
Q315.8
95-th percentile36.46
Maximum41
Range37.1
Interquartile range (IQR)8.2

Descriptive statistics

Standard deviation9.4242497
Coefficient of variation (CV)0.66956549
Kurtosis2.9157801
Mean14.075172
Median Absolute Deviation (MAD)4
Skewness1.7974354
Sum408.18
Variance88.816483
MonotonicityNot monotonic
2023-12-11T01:30:57.034997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11.4 2
 
6.9%
6.0 2
 
6.9%
7.3 1
 
3.4%
14.35 1
 
3.4%
16.55 1
 
3.4%
7.0 1
 
3.4%
7.8 1
 
3.4%
3.9 1
 
3.4%
9.95 1
 
3.4%
40.0 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
3.9 1
3.4%
6.0 2
6.9%
7.0 1
3.4%
7.2 1
3.4%
7.3 1
3.4%
7.4 1
3.4%
7.6 1
3.4%
7.8 1
3.4%
8.2 1
3.4%
8.8 1
3.4%
ValueCountFrequency (%)
41.0 1
3.4%
40.0 1
3.4%
31.15 1
3.4%
25.98 1
3.4%
17.5 1
3.4%
17.15 1
3.4%
16.55 1
3.4%
15.8 1
3.4%
15.0 1
3.4%
14.95 1
3.4%

동수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
1
29 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
100.0%

Length

2023-12-11T01:30:57.214190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:57.677142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
100.0%

주용도
Categorical

Distinct7
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
제2종근린생활시설
13 
제1종근린생활시설
8 
단독주택
2 
공동주택
2 
숙박시설
2 
Other values (2)
2 

Length

Max length9
Median length9
Mean length7.6206897
Min length4

Unique

Unique2 ?
Unique (%)6.9%

Sample

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

Common Values

ValueCountFrequency (%)
제2종근린생활시설 13
44.8%
제1종근린생활시설 8
27.6%
단독주택 2
 
6.9%
공동주택 2
 
6.9%
숙박시설 2
 
6.9%
업무시설 1
 
3.4%
창고시설 1
 
3.4%

Length

2023-12-11T01:30:57.799082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:57.935713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종근린생활시설 13
44.8%
제1종근린생활시설 8
27.6%
단독주택 2
 
6.9%
공동주택 2
 
6.9%
숙박시설 2
 
6.9%
업무시설 1
 
3.4%
창고시설 1
 
3.4%

부속용도
Text

MISSING 

Distinct22
Distinct (%)84.6%
Missing3
Missing (%)10.3%
Memory size364.0 B
2023-12-11T01:30:58.179436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length9.8461538
Min length2

Characters and Unicode

Total characters256
Distinct characters76
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

Unique20 ?
Unique (%)76.9%

Sample

1st row일반음식점
2nd row사무소
3rd row소매점
4th row사무소
5th row휴게음직점
ValueCountFrequency (%)
사무소 4
 
10.5%
일반음식점 3
 
7.9%
및 2
 
5.3%
제1종근린생활시설(소매점 2
 
5.3%
의원 2
 
5.3%
소매점 2
 
5.3%
사진관 1
 
2.6%
휴게음식점/미용원 1
 
2.6%
제2종근린생활시설 1
 
2.6%
목욕장 1
 
2.6%
Other values (19) 19
50.0%
2023-12-11T01:30:58.654047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 14
 
5.5%
소 12
 
4.7%
12
 
4.7%
시 11
 
4.3%
( 10
 
3.9%
) 10
 
3.9%
음 9
 
3.5%
, 9
 
3.5%
설 8
 
3.1%
식 7
 
2.7%
Other values (66) 154
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
81.2%
Space Separator 12
 
4.7%
Other Punctuation 12
 
4.7%
Open Punctuation 10
 
3.9%
Close Punctuation 10
 
3.9%
Decimal Number 3
 
1.2%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 14
 
6.7%
소 12
 
5.8%
시 11
 
5.3%
음 9
 
4.3%
설 8
 
3.8%
식 7
 
3.4%
택 7
 
3.4%
주 7
 
3.4%
활 6
 
2.9%
생 6
 
2.9%
Other values (56) 121
58.2%
Other Punctuation
ValueCountFrequency (%)
, 9
75.0%
. 1
 
8.3%
/ 1
 
8.3%
: 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
12
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 208
81.2%
Common 48
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 14
 
6.7%
소 12
 
5.8%
시 11
 
5.3%
음 9
 
4.3%
설 8
 
3.8%
식 7
 
3.4%
택 7
 
3.4%
주 7
 
3.4%
활 6
 
2.9%
생 6
 
2.9%
Other values (56) 121
58.2%
Common
ValueCountFrequency (%)
12
25.0%
( 10
20.8%
) 10
20.8%
, 9
18.8%
1 2
 
4.2%
2 1
 
2.1%
. 1
 
2.1%
/ 1
 
2.1%
: 1
 
2.1%
- 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
81.2%
ASCII 48
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 14
 
6.7%
소 12
 
5.8%
시 11
 
5.3%
음 9
 
4.3%
설 8
 
3.8%
식 7
 
3.4%
택 7
 
3.4%
주 7
 
3.4%
활 6
 
2.9%
생 6
 
2.9%
Other values (56) 121
58.2%
ASCII
ValueCountFrequency (%)
12
25.0%
( 10
20.8%
) 10
20.8%
, 9
18.8%
1 2
 
4.2%
2 1
 
2.1%
. 1
 
2.1%
/ 1
 
2.1%
: 1
 
2.1%
- 1
 
2.1%

지역
Categorical

Distinct6
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
도시지역
12 
제2종일반주거지역
11 
일반상업지역
2 
준주거지역
2 
가로구역별최고높이제한지역
 
1

Length

Max length13
Median length9
Mean length6.4482759
Min length4

Unique

Unique2 ?
Unique (%)6.9%

Sample

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

Common Values

ValueCountFrequency (%)
도시지역 12
41.4%
제2종일반주거지역 11
37.9%
일반상업지역 2
 
6.9%
준주거지역 2
 
6.9%
가로구역별최고높이제한지역 1
 
3.4%
준공업지역 1
 
3.4%

Length

2023-12-11T01:30:59.081208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:30:59.276091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시지역 12
41.4%
제2종일반주거지역 11
37.9%
일반상업지역 2
 
6.9%
준주거지역 2
 
6.9%
가로구역별최고높이제한지역 1
 
3.4%
준공업지역 1
 
3.4%

지구
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing27
Missing (%)93.1%
Memory size364.0 B
2023-12-11T01:30:59.479332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters8
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row방화지구
2nd row방화지구
ValueCountFrequency (%)
방화지구 2
100.0%
2023-12-11T01:30:59.841336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
방 2
25.0%
화 2
25.0%
지 2
25.0%
구 2
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 2
25.0%
화 2
25.0%
지 2
25.0%
구 2
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 2
25.0%
화 2
25.0%
지 2
25.0%
구 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
방 2
25.0%
화 2
25.0%
지 2
25.0%
구 2
25.0%

구역
Categorical

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
13 
상대보호구역
10 
중점경관관리구역
4 
문화재보존영향 검토대상구역
 
1
역사문화환경보존지역
 
1

Length

Max length14
Median length10
Mean length5.7931034
Min length4

Unique

Unique2 ?
Unique (%)6.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
44.8%
상대보호구역 10
34.5%
중점경관관리구역 4
 
13.8%
문화재보존영향 검토대상구역 1
 
3.4%
역사문화환경보존지역 1
 
3.4%

Length

2023-12-11T01:31:00.059922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:00.216439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
43.3%
상대보호구역 10
33.3%
중점경관관리구역 4
 
13.3%
문화재보존영향 1
 
3.3%
검토대상구역 1
 
3.3%
역사문화환경보존지역 1
 
3.3%

세대수
Categorical

IMBALANCE 

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
25 
0
 
1
16
 
1
2
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.6551724
Min length1

Unique

Unique4 ?
Unique (%)13.8%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
86.2%
0 1
 
3.4%
16 1
 
3.4%
2 1
 
3.4%
15 1
 
3.4%

Length

2023-12-11T01:31:00.414332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:00.571909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
86.2%
0 1
 
3.4%
16 1
 
3.4%
2 1
 
3.4%
15 1
 
3.4%

호수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)100.0%
Missing23
Missing (%)79.3%
Infinite0
Infinite (%)0.0%
Mean16.166667
Minimum0
Maximum46
Zeros1
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-11T01:31:00.705840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.25
Q12
median13
Q323.25
95-th percentile40.5
Maximum46
Range46
Interquartile range (IQR)21.25

Descriptive statistics

Standard deviation17.837227
Coefficient of variation (CV)1.1033336
Kurtosis0.20324371
Mean16.166667
Median Absolute Deviation (MAD)11.5
Skewness0.95359743
Sum97
Variance318.16667
MonotonicityNot monotonic
2023-12-11T01:31:00.852416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1
 
3.4%
21 1
 
3.4%
5 1
 
3.4%
1 1
 
3.4%
46 1
 
3.4%
24 1
 
3.4%
(Missing) 23
79.3%
ValueCountFrequency (%)
0 1
3.4%
1 1
3.4%
5 1
3.4%
21 1
3.4%
24 1
3.4%
46 1
3.4%
ValueCountFrequency (%)
46 1
3.4%
24 1
3.4%
21 1
3.4%
5 1
3.4%
1 1
3.4%
0 1
3.4%

가구수
Categorical

IMBALANCE 

Distinct5
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
<NA>
24 
1
 
2
0
 
1
11
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.5172414
Min length1

Unique

Unique3 ?
Unique (%)10.3%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 24
82.8%
1 2
 
6.9%
0 1
 
3.4%
11 1
 
3.4%
2 1
 
3.4%

Length

2023-12-11T01:31:01.034653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:01.193522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
82.8%
1 2
 
6.9%
0 1
 
3.4%
11 1
 
3.4%
2 1
 
3.4%

설계사무소명
Text

Distinct25
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-11T01:31:01.476907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.275862
Min length8

Characters and Unicode

Total characters298
Distinct characters62
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)72.4%

Sample

1st row대경 건축사사무소
2nd row건축사사무소 준우
3rd row주식회사 지을엔드종합건축사사무소
4th row에프엘엠(FLM)건축사사무소
5th row송지 종합건축사사무소
ValueCountFrequency (%)
건축사사무소 12
25.0%
종합건축사사무소 4
 
8.3%
대경 2
 
4.2%
이진건축사사무소 2
 
4.2%
준우 2
 
4.2%
메인 2
 
4.2%
그린건축사사무소 1
 
2.1%
주)종합건축사사무소 1
 
2.1%
동언 1
 
2.1%
바로건축사사무소 1
 
2.1%
Other values (20) 20
41.7%
2023-12-11T01:31:02.037998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 59
19.8%
건 30
 
10.1%
축 30
 
10.1%
무 29
 
9.7%
소 29
 
9.7%
19
 
6.4%
합 7
 
2.3%
종 7
 
2.3%
주 5
 
1.7%
) 5
 
1.7%
Other values (52) 78
26.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
89.3%
Space Separator 19
 
6.4%
Close Punctuation 5
 
1.7%
Open Punctuation 5
 
1.7%
Uppercase Letter 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 59
22.2%
건 30
11.3%
축 30
11.3%
무 29
10.9%
소 29
10.9%
합 7
 
2.6%
종 7
 
2.6%
주 5
 
1.9%
지 4
 
1.5%
우 4
 
1.5%
Other values (46) 62
23.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
F 1
33.3%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
89.3%
Common 29
 
9.7%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 59
22.2%
건 30
11.3%
축 30
11.3%
무 29
10.9%
소 29
10.9%
합 7
 
2.6%
종 7
 
2.6%
주 5
 
1.9%
지 4
 
1.5%
우 4
 
1.5%
Other values (46) 62
23.3%
Common
ValueCountFrequency (%)
19
65.5%
) 5
 
17.2%
( 5
 
17.2%
Latin
ValueCountFrequency (%)
L 1
33.3%
F 1
33.3%
M 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
89.3%
ASCII 32
 
10.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 59
22.2%
건 30
11.3%
축 30
11.3%
무 29
10.9%
소 29
10.9%
합 7
 
2.6%
종 7
 
2.6%
주 5
 
1.9%
지 4
 
1.5%
우 4
 
1.5%
Other values (46) 62
23.3%
ASCII
ValueCountFrequency (%)
19
59.4%
) 5
 
15.6%
( 5
 
15.6%
L 1
 
3.1%
F 1
 
3.1%
M 1
 
3.1%

감리사무소명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing26
Missing (%)89.7%
Memory size364.0 B
2023-12-11T01:31:02.267151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.6666667
Min length9

Characters and Unicode

Total characters29
Distinct characters15
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

Unique3 ?
Unique (%)100.0%

Sample

1st row건축사사무소 마온
2nd row평진 건축사사무소
3rd row(주)보고건축사사무소
ValueCountFrequency (%)
건축사사무소 2
40.0%
마온 1
20.0%
평진 1
20.0%
주)보고건축사사무소 1
20.0%
2023-12-11T01:31:02.743110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 6
20.7%
건 3
10.3%
축 3
10.3%
무 3
10.3%
소 3
10.3%
2
 
6.9%
마 1
 
3.4%
온 1
 
3.4%
평 1
 
3.4%
진 1
 
3.4%
Other values (5) 5
17.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
86.2%
Space Separator 2
 
6.9%
Open Punctuation 1
 
3.4%
Close Punctuation 1
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 6
24.0%
건 3
12.0%
축 3
12.0%
무 3
12.0%
소 3
12.0%
마 1
 
4.0%
온 1
 
4.0%
평 1
 
4.0%
진 1
 
4.0%
주 1
 
4.0%
Other values (2) 2
 
8.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
86.2%
Common 4
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 6
24.0%
건 3
12.0%
축 3
12.0%
무 3
12.0%
소 3
12.0%
마 1
 
4.0%
온 1
 
4.0%
평 1
 
4.0%
진 1
 
4.0%
주 1
 
4.0%
Other values (2) 2
 
8.0%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
86.2%
ASCII 4
 
13.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 6
24.0%
건 3
12.0%
축 3
12.0%
무 3
12.0%
소 3
12.0%
마 1
 
4.0%
온 1
 
4.0%
평 1
 
4.0%
진 1
 
4.0%
주 1
 
4.0%
Other values (2) 2
 
8.0%
ASCII
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

시공자사무소명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing26
Missing (%)89.7%
Memory size364.0 B
2023-12-11T01:31:02.950913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters27
Distinct characters13
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

Unique3 ?
Unique (%)100.0%

Sample

1st row동승종합건설(주)
2nd row(주)더한종합건설
3rd row고강종합건설(주)
ValueCountFrequency (%)
동승종합건설(주 1
33.3%
주)더한종합건설 1
33.3%
고강종합건설(주 1
33.3%
2023-12-11T01:31:03.369853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
종 3
11.1%
합 3
11.1%
건 3
11.1%
설 3
11.1%
( 3
11.1%
주 3
11.1%
) 3
11.1%
동 1
 
3.7%
승 1
 
3.7%
더 1
 
3.7%
Other values (3) 3
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21
77.8%
Open Punctuation 3
 
11.1%
Close Punctuation 3
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 3
14.3%
합 3
14.3%
건 3
14.3%
설 3
14.3%
주 3
14.3%
동 1
 
4.8%
승 1
 
4.8%
더 1
 
4.8%
한 1
 
4.8%
고 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21
77.8%
Common 6
 
22.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 3
14.3%
합 3
14.3%
건 3
14.3%
설 3
14.3%
주 3
14.3%
동 1
 
4.8%
승 1
 
4.8%
더 1
 
4.8%
한 1
 
4.8%
고 1
 
4.8%
Common
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21
77.8%
ASCII 6
 
22.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
종 3
14.3%
합 3
14.3%
건 3
14.3%
설 3
14.3%
주 3
14.3%
동 1
 
4.8%
승 1
 
4.8%
더 1
 
4.8%
한 1
 
4.8%
고 1
 
4.8%
ASCII
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Sample

건축구분허가번호대지위치지목대지면적건축면적연면적건폐율용적률구조허가일착공처리일착공예정일사용승인일지상층수지하층수최고높이동수주용도부속용도지역지구구역세대수호수가구수설계사무소명감리사무소명시공자사무소명
0용도변경2023-건축과-용도변경허가-14부산광역시 수영구 민락동 164-16대139.582.38133.7459.053895.871블록구조2023-02-24<NA><NA><NA>2<NA>7.31제2종근린생활시설일반음식점제2종일반주거지역<NA><NA><NA><NA><NA>대경 건축사사무소<NA><NA>
1용도변경2023-건축과-용도변경허가-15부산광역시 수영구 민락동 15-10대506.1274.38908.4354.21162.64<NA>2023-02-24<NA><NA><NA>3111.41제2종근린생활시설사무소도시지역<NA><NA>000건축사사무소 준우<NA><NA>
2증축2023-건축과-증축허가-3부산광역시 수영구 남천동 52-3 외1필지대700.5323.9992.2746.2384141.6517일반철골구조2023-02-23<NA><NA><NA>4<NA>17.151제1종근린생활시설소매점가로구역별최고높이제한지역<NA>중점경관관리구역<NA><NA><NA>주식회사 지을엔드종합건축사사무소<NA><NA>
3용도변경2023-건축과-용도변경허가-11부산광역시 수영구 민락동 18-31대147.886.28172.5658.3762116.7524철근콘크리트구조2023-02-23<NA><NA><NA>2<NA>7.41단독주택<NA>도시지역<NA>상대보호구역<NA><NA>1에프엘엠(FLM)건축사사무소<NA><NA>
4용도변경2023-건축과-용도변경허가-12부산광역시 수영구 민락동 28-9대206.7121.82262.9458.94114.15<NA>2023-02-23<NA><NA><NA>218.21제2종근린생활시설사무소제2종일반주거지역<NA>상대보호구역<NA><NA><NA>송지 종합건축사사무소<NA><NA>
5용도변경2023-건축과-용도변경허가-13부산광역시 수영구 광안동 152-31대165.482.51131.9649.8979.78<NA>2023-02-23<NA><NA><NA>2<NA>7.21제1종근린생활시설휴게음직점제2종일반주거지역<NA><NA><NA><NA><NA>건축사사무소현우<NA><NA>
6신축2023-건축과-신축허가-7부산광역시 수영구 민락동 718-3대109.762.42109.0756.999.43철근콘크리트구조2023-02-22<NA><NA><NA>208.81단독주택단독주택제2종일반주거지역<NA>상대보호구역<NA><NA>1건축사사무소 아키원<NA><NA>
7신축2023-건축과-신축허가-6부산광역시 수영구 망미동 884-30대238.0141.96497.1359.65208.88철근콘크리트구조2023-02-16<NA><NA><NA>5014.951공동주택다세대주택(도시형생활주택-소형주택)제2종일반주거지역<NA>상대보호구역16<NA><NA>(주)일영건축사사무소<NA><NA>
8용도변경2023-건축과-용도변경허가-9부산광역시 수영구 민락동 181-145대299.0207.871724.1569.52515.22철근콘크리트구조2023-02-16<NA><NA><NA>8131.151숙박시설관광숙박시설(소형호텔)도시지역<NA>중점경관관리구역<NA>21<NA>(주)루원건축사사무소<NA><NA>
9용도변경2023-건축과-용도변경허가-10부산광역시 수영구 광안동 741-11대587.1404.81759.9468.9491231.9775<NA>2023-02-16<NA><NA><NA>4114.41제1종근린생활시설의원일반상업지역방화지구<NA><NA><NA><NA>이진건축사사무소<NA><NA>
건축구분허가번호대지위치지목대지면적건축면적연면적건폐율용적률구조허가일착공처리일착공예정일사용승인일지상층수지하층수최고높이동수주용도부속용도지역지구구역세대수호수가구수설계사무소명감리사무소명시공자사무소명
19용도변경2023-건축과-용도변경허가-6부산광역시 수영구 민락동 715-1대39.8533.78101.3484.77254.3<NA>2023-01-16<NA><NA><NA>3<NA>9.71제2종근린생활시설일반음식점도시지역<NA>상대보호구역<NA><NA><NA>그린건축사사무소<NA><NA>
20용도변경2023-건축과-용도변경허가-4부산광역시 수영구 남천동 72-6대231.1103.54195.4744.884.58블록구조2023-01-13<NA><NA><NA>2<NA>6.01제2종근린생활시설<NA>도시지역<NA>중점경관관리구역<NA><NA><NA>건축사사무소 메인<NA><NA>
21용도변경2023-건축과-용도변경허가-5부산광역시 수영구 남천동 72-5대161.778.38207.6148.4777.93블록구조2023-01-13<NA><NA><NA>216.01제2종근린생활시설<NA>도시지역<NA>중점경관관리구역<NA><NA><NA>건축사사무소 메인<NA><NA>
22신축2023-건축과-신축허가-4부산광역시 수영구 망미동 431-2대302.8179.911555.63759.42496.43철근콘크리트구조2023-01-12<NA><NA><NA>13040.01공동주택(도시형생활주택:단지형다세대).업무시설(오피스텔)준주거지역<NA><NA>1524<NA>(주)종합건축사사무소 동언<NA><NA>
23신축2023-건축과-신축허가-3부산광역시 수영구 망미동 204-3대99.159.4178.259.94179.82일반철골구조2023-01-11<NA><NA><NA>309.951창고시설창고시설, 제2종근린생활시설준공업지역<NA>상대보호구역<NA><NA><NA>바로건축사사무소<NA><NA>
24용도변경2023-건축과-용도변경허가-2부산광역시 수영구 망미동 266-14대97.558.1758.1759.661559.6615시멘트블럭조2023-01-10<NA><NA><NA>1<NA>3.91제1종근린생활시설휴게음식점/미용원제2종일반주거지역<NA><NA><NA><NA><NA>선명건축사사무소<NA><NA>
25용도변경2023-건축과-용도변경허가-3부산광역시 수영구 민락동 164-17대137.969.85131.0850.652695.0544벽돌구조2023-01-10<NA><NA><NA>2<NA>7.81제2종근린생활시설일반음식점도시지역<NA><NA><NA><NA><NA>대경 건축사사무소<NA><NA>
26용도변경2023-건축과-용도변경허가-1부산광역시 수영구 민락동 1-22대249.099.6197.9740.079.506벽돌구조2023-01-06<NA><NA><NA>207.01제2종근린생활시설사진관제2종일반주거지역<NA>상대보호구역<NA><NA><NA>원심 건축사사무소<NA><NA>
27신축2023-건축과-신축허가-2부산광역시 수영구 망미동 452-10대152.184.43328.1855.51215.77철근콘크리트구조2023-01-04<NA><NA><NA>5016.551제2종근린생활시설단독주택(다가구주택)제2종일반주거지역<NA><NA><NA><NA>2종합건축사사무소 금문<NA><NA>
28신축2023-건축과-신축허가-1부산광역시 수영구 남천동 245-1대135.079.81199.4859.12147.76철근콘크리트구조2023-01-022023-01-252023-01-30<NA>3014.351제1종근린생활시설휴겡음식점, 소매점도시지역<NA><NA><NA><NA><NA>화산이엔지건축사사무소(주)보고건축사사무소고강종합건설(주)