Overview

Dataset statistics

Number of variables28
Number of observations122
Missing cells608
Missing cells (%)17.8%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory27.9 KiB
Average record size in memory234.1 B

Variable types

Categorical10
Text10
Numeric6
DateTime2

Dataset

Description부산광역시남구건축허가및착공현황_20221231
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15014623

Alerts

Dataset has 1 (0.8%) duplicate rowsDuplicates
지목 is highly imbalanced (84.8%)Imbalance
용도지구 is highly imbalanced (59.8%)Imbalance
가구수 is highly imbalanced (66.6%)Imbalance
주건축물수 is highly imbalanced (74.8%)Imbalance
증축연면적(제곱미터) has 110 (90.2%) missing valuesMissing
착공처리일 has 86 (70.5%) missing valuesMissing
부속용도 has 25 (20.5%) missing valuesMissing
세대수 has 102 (83.6%) missing valuesMissing
호수 has 103 (84.4%) missing valuesMissing
감리사무소명 has 87 (71.3%) missing valuesMissing
시공자사무소명 has 95 (77.9%) missing valuesMissing
최고높이(미터) has 12 (9.8%) zerosZeros
동수 has 3 (2.5%) zerosZeros

Reproduction

Analysis started2023-12-10 16:38:10.512076
Analysis finished2023-12-10 16:38:11.255715
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
용도변경
62 
신축
46 
증축
12 
대수선
 
2

Length

Max length4
Median length4
Mean length3.0327869
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용도변경 62
50.8%
신축 46
37.7%
증축 12
 
9.8%
대수선 2
 
1.6%

Length

2023-12-11T01:38:11.362414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:11.510474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용도변경 62
50.8%
신축 46
37.7%
증축 12
 
9.8%
대수선 2
 
1.6%
Distinct118
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:11.842265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19.663934
Min length16

Characters and Unicode

Total characters2399
Distinct characters34
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

Unique114 ?
Unique (%)93.4%

Sample

1st row부산광역시 남구 문현동 539-32 외1필지
2nd row부산광역시 남구 문현동 539-32 외1필지
3rd row부산광역시 남구 우암동 151-8
4th row부산광역시 남구 문현동 141-38
5th row부산광역시 남구 문현동 78-4
ValueCountFrequency (%)
부산광역시 122
23.7%
남구 122
23.7%
대연동 61
11.8%
문현동 27
 
5.2%
용호동 19
 
3.7%
외1필지 15
 
2.9%
우암동 6
 
1.2%
감만동 5
 
1.0%
용당동 4
 
0.8%
외3필지 3
 
0.6%
Other values (124) 131
25.4%
2023-12-11T01:38:12.411679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
393
16.4%
1 128
 
5.3%
123
 
5.1%
122
 
5.1%
122
 
5.1%
122
 
5.1%
122
 
5.1%
122
 
5.1%
122
 
5.1%
122
 
5.1%
Other values (24) 901
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1299
54.1%
Decimal Number 589
24.6%
Space Separator 393
 
16.4%
Dash Punctuation 118
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
123
9.5%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
61
 
4.7%
61
 
4.7%
Other values (12) 200
15.4%
Decimal Number
ValueCountFrequency (%)
1 128
21.7%
3 73
12.4%
5 71
12.1%
2 67
11.4%
7 50
 
8.5%
4 49
 
8.3%
8 43
 
7.3%
6 38
 
6.5%
9 38
 
6.5%
0 32
 
5.4%
Space Separator
ValueCountFrequency (%)
393
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1299
54.1%
Common 1100
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
123
9.5%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
61
 
4.7%
61
 
4.7%
Other values (12) 200
15.4%
Common
ValueCountFrequency (%)
393
35.7%
1 128
 
11.6%
- 118
 
10.7%
3 73
 
6.6%
5 71
 
6.5%
2 67
 
6.1%
7 50
 
4.5%
4 49
 
4.5%
8 43
 
3.9%
6 38
 
3.5%
Other values (2) 70
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1299
54.1%
ASCII 1100
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
393
35.7%
1 128
 
11.6%
- 118
 
10.7%
3 73
 
6.6%
5 71
 
6.5%
2 67
 
6.1%
7 50
 
4.5%
4 49
 
4.5%
8 43
 
3.9%
6 38
 
3.5%
Other values (2) 70
 
6.4%
Hangul
ValueCountFrequency (%)
123
9.5%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
122
9.4%
61
 
4.7%
61
 
4.7%
Other values (12) 200
15.4%

지목
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
116 
임야
 
2
잡종지
 
1
 
1
학교용지
 
1

Length

Max length5
Median length1
Mean length1.0901639
Min length1

Unique

Unique4 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
116
95.1%
임야 2
 
1.6%
잡종지 1
 
0.8%
1
 
0.8%
학교용지 1
 
0.8%
주유소용지 1
 
0.8%

Length

2023-12-11T01:38:12.624289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:12.742986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
116
95.1%
임야 2
 
1.6%
잡종지 1
 
0.8%
1
 
0.8%
학교용지 1
 
0.8%
주유소용지 1
 
0.8%
Distinct115
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:13.114077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.3852459
Min length2

Characters and Unicode

Total characters535
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)88.5%

Sample

1st row478.73
2nd row478.73
3rd row79
4th row188
5th row250
ValueCountFrequency (%)
478.73 2
 
1.6%
165.3 2
 
1.6%
123 2
 
1.6%
188 2
 
1.6%
245 2
 
1.6%
608.4 2
 
1.6%
77.5 2
 
1.6%
354,597 1
 
0.8%
233 1
 
0.8%
221.8 1
 
0.8%
Other values (105) 105
86.1%
2023-12-11T01:38:13.688015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 70
13.1%
3 60
11.2%
2 60
11.2%
1 57
10.7%
5 48
9.0%
6 47
8.8%
4 45
8.4%
8 40
7.5%
9 35
6.5%
7 33
6.2%
Other values (2) 40
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 452
84.5%
Other Punctuation 83
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 60
13.3%
2 60
13.3%
1 57
12.6%
5 48
10.6%
6 47
10.4%
4 45
10.0%
8 40
8.8%
9 35
7.7%
7 33
7.3%
0 27
6.0%
Other Punctuation
ValueCountFrequency (%)
. 70
84.3%
, 13
 
15.7%

Most occurring scripts

ValueCountFrequency (%)
Common 535
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 70
13.1%
3 60
11.2%
2 60
11.2%
1 57
10.7%
5 48
9.0%
6 47
8.8%
4 45
8.4%
8 40
7.5%
9 35
6.5%
7 33
6.2%
Other values (2) 40
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 535
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 70
13.1%
3 60
11.2%
2 60
11.2%
1 57
10.7%
5 48
9.0%
6 47
8.8%
4 45
8.4%
8 40
7.5%
9 35
6.5%
7 33
6.2%
Other values (2) 40
7.5%
Distinct119
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:14.034750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.6967213
Min length2

Characters and Unicode

Total characters695
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)95.1%

Sample

1st row382.44
2nd row382.44
3rd row44.17
4th row111.6
5th row130.62
ValueCountFrequency (%)
382.44 2
 
1.6%
339.47 2
 
1.6%
67.78 2
 
1.6%
117.69 1
 
0.8%
76.45 1
 
0.8%
354.46 1
 
0.8%
21.25 1
 
0.8%
262.03 1
 
0.8%
66,997.26 1
 
0.8%
291.35 1
 
0.8%
Other values (109) 109
89.3%
2023-12-11T01:38:14.702904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 119
17.1%
1 82
11.8%
2 71
10.2%
4 65
9.4%
3 60
8.6%
6 58
8.3%
7 55
7.9%
8 53
7.6%
5 49
7.1%
9 41
 
5.9%
Other values (2) 42
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 567
81.6%
Other Punctuation 128
 
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 82
14.5%
2 71
12.5%
4 65
11.5%
3 60
10.6%
6 58
10.2%
7 55
9.7%
8 53
9.3%
5 49
8.6%
9 41
7.2%
0 33
5.8%
Other Punctuation
ValueCountFrequency (%)
. 119
93.0%
, 9
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Common 695
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 119
17.1%
1 82
11.8%
2 71
10.2%
4 65
9.4%
3 60
8.6%
6 58
8.3%
7 55
7.9%
8 53
7.6%
5 49
7.1%
9 41
 
5.9%
Other values (2) 42
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 119
17.1%
1 82
11.8%
2 71
10.2%
4 65
9.4%
3 60
8.6%
6 58
8.3%
7 55
7.9%
8 53
7.6%
5 49
7.1%
9 41
 
5.9%
Other values (2) 42
 
6.0%
Distinct119
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:15.219415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.5901639
Min length3

Characters and Unicode

Total characters804
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)95.1%

Sample

1st row5,560.0579
2nd row5,560.0579
3rd row44.17
4th row412.355
5th row296.08
ValueCountFrequency (%)
5,560.0579 2
 
1.6%
1,540.43 2
 
1.6%
297.83 2
 
1.6%
188.1 1
 
0.8%
147.65 1
 
0.8%
4,946.65 1
 
0.8%
41.19 1
 
0.8%
3,334.87 1
 
0.8%
330,256.45 1
 
0.8%
314.75 1
 
0.8%
Other values (109) 109
89.3%
2023-12-11T01:38:16.038011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 120
14.9%
1 89
11.1%
5 77
9.6%
2 72
9.0%
4 68
8.5%
7 61
7.6%
3 61
7.6%
6 60
7.5%
9 58
7.2%
8 52
6.5%
Other values (2) 86
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 643
80.0%
Other Punctuation 161
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 89
13.8%
5 77
12.0%
2 72
11.2%
4 68
10.6%
7 61
9.5%
3 61
9.5%
6 60
9.3%
9 58
9.0%
8 52
8.1%
0 45
7.0%
Other Punctuation
ValueCountFrequency (%)
. 120
74.5%
, 41
 
25.5%

Most occurring scripts

ValueCountFrequency (%)
Common 804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 120
14.9%
1 89
11.1%
5 77
9.6%
2 72
9.0%
4 68
8.5%
7 61
7.6%
3 61
7.6%
6 60
7.5%
9 58
7.2%
8 52
6.5%
Other values (2) 86
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 120
14.9%
1 89
11.1%
5 77
9.6%
2 72
9.0%
4 68
8.5%
7 61
7.6%
3 61
7.6%
6 60
7.5%
9 58
7.2%
8 52
6.5%
Other values (2) 86
10.7%
Distinct11
Distinct (%)91.7%
Missing110
Missing (%)90.2%
Memory size1.1 KiB
2023-12-11T01:38:16.281976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4166667
Min length3

Characters and Unicode

Total characters65
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)83.3%

Sample

1st row123.67
2nd row89.76
3rd row764.72
4th row27.03
5th row27.03
ValueCountFrequency (%)
27.03 2
16.7%
123.67 1
8.3%
89.76 1
8.3%
764.72 1
8.3%
837.89 1
8.3%
60.32 1
8.3%
5.7 1
8.3%
765.24 1
8.3%
2,510.8 1
8.3%
102.93 1
8.3%
2023-12-11T01:38:16.723243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 11
16.9%
2 9
13.8%
7 9
13.8%
3 7
10.8%
0 6
9.2%
6 5
7.7%
8 4
 
6.2%
1 3
 
4.6%
9 3
 
4.6%
4 3
 
4.6%
Other values (2) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
80.0%
Other Punctuation 13
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
17.3%
7 9
17.3%
3 7
13.5%
0 6
11.5%
6 5
9.6%
8 4
7.7%
1 3
 
5.8%
9 3
 
5.8%
4 3
 
5.8%
5 3
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 11
84.6%
, 2
 
15.4%

Most occurring scripts

ValueCountFrequency (%)
Common 65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 11
16.9%
2 9
13.8%
7 9
13.8%
3 7
10.8%
0 6
9.2%
6 5
7.7%
8 4
 
6.2%
1 3
 
4.6%
9 3
 
4.6%
4 3
 
4.6%
Other values (2) 5
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 11
16.9%
2 9
13.8%
7 9
13.8%
3 7
10.8%
0 6
9.2%
6 5
7.7%
8 4
 
6.2%
1 3
 
4.6%
9 3
 
4.6%
4 3
 
4.6%
Other values (2) 5
7.7%

건폐율(퍼센트)
Real number (ℝ)

Distinct116
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.168777
Minimum2.49
Maximum89.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:16.942007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.49
5-th percentile32.6105
Q150.1275
median58.7342
Q359.9075
95-th percentile82.348145
Maximum89.75
Range87.26
Interquartile range (IQR)9.78

Descriptive statistics

Standard deviation15.422206
Coefficient of variation (CV)0.26976623
Kurtosis1.4263626
Mean57.168777
Median Absolute Deviation (MAD)6.4192
Skewness-0.50959373
Sum6974.5908
Variance237.84443
MonotonicityNot monotonic
2023-12-11T01:38:17.183394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79.89 2
 
1.6%
59.71 2
 
1.6%
55.8 2
 
1.6%
87.46 2
 
1.6%
59.64 2
 
1.6%
49.99 2
 
1.6%
59.19 1
 
0.8%
78.54 1
 
0.8%
77.99 1
 
0.8%
79.14 1
 
0.8%
Other values (106) 106
86.9%
ValueCountFrequency (%)
2.49 1
0.8%
16.28 1
0.8%
18.58 1
0.8%
18.8939 1
0.8%
19.2171 1
0.8%
25.01 1
0.8%
32.54 1
0.8%
33.95 1
0.8%
34.1796 1
0.8%
34.43 1
0.8%
ValueCountFrequency (%)
89.75 1
0.8%
87.46 2
1.6%
87.36 1
0.8%
85.26 1
0.8%
85.0499 1
0.8%
82.3691 1
0.8%
81.95 1
0.8%
79.91 1
0.8%
79.89 2
1.6%
79.33 1
0.8%
Distinct119
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:17.668913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0983607
Min length2

Characters and Unicode

Total characters744
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)95.1%

Sample

1st row1,070.18
2nd row1,070.18
3rd row55.91
4th row219.34
5th row100.95
ValueCountFrequency (%)
1,070.18 2
 
1.6%
253.19 2
 
1.6%
362.93 2
 
1.6%
92.84 1
 
0.8%
83.89 1
 
0.8%
992.34 1
 
0.8%
153.41 1
 
0.8%
819.82 1
 
0.8%
84.2576 1
 
0.8%
42.42 1
 
0.8%
Other values (109) 109
89.3%
2023-12-11T01:38:18.469805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 121
16.3%
1 102
13.7%
2 92
12.4%
9 62
8.3%
3 60
8.1%
7 58
7.8%
8 56
7.5%
4 54
7.3%
6 52
7.0%
5 46
 
6.2%
Other values (2) 41
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 621
83.5%
Other Punctuation 123
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 102
16.4%
2 92
14.8%
9 62
10.0%
3 60
9.7%
7 58
9.3%
8 56
9.0%
4 54
8.7%
6 52
8.4%
5 46
7.4%
0 39
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 121
98.4%
, 2
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 744
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 121
16.3%
1 102
13.7%
2 92
12.4%
9 62
8.3%
3 60
8.1%
7 58
7.8%
8 56
7.5%
4 54
7.3%
6 52
7.0%
5 46
 
6.2%
Other values (2) 41
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 744
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 121
16.3%
1 102
13.7%
2 92
12.4%
9 62
8.3%
3 60
8.1%
7 58
7.8%
8 56
7.5%
4 54
7.3%
6 52
7.0%
5 46
 
6.2%
Other values (2) 41
 
5.5%

구조
Categorical

Distinct9
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
철근콘크리트구조
73 
<NA>
14 
블록구조
13 
일반철골구조
10 
벽돌구조
 
7
Other values (4)
 
5

Length

Max length13
Median length8
Mean length6.7786885
Min length4

Unique

Unique3 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 73
59.8%
<NA> 14
 
11.5%
블록구조 13
 
10.7%
일반철골구조 10
 
8.2%
벽돌구조 7
 
5.7%
철골철근콘크리트구조 2
 
1.6%
철골콘크리트구조 1
 
0.8%
공업화박판강구조(PEB) 1
 
0.8%
경량철골구조 1
 
0.8%

Length

2023-12-11T01:38:18.698627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:18.876085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 73
59.8%
na 14
 
11.5%
블록구조 13
 
10.7%
일반철골구조 10
 
8.2%
벽돌구조 7
 
5.7%
철골철근콘크리트구조 2
 
1.6%
철골콘크리트구조 1
 
0.8%
공업화박판강구조(peb 1
 
0.8%
경량철골구조 1
 
0.8%
Distinct95
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2022-01-03 00:00:00
Maximum2022-12-30 00:00:00
2023-12-11T01:38:19.160999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:19.499778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct33
Distinct (%)91.7%
Missing86
Missing (%)70.5%
Memory size1.1 KiB
Minimum2022-01-12 00:00:00
Maximum2023-04-16 00:00:00
2023-12-11T01:38:19.722974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:38:20.318237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

최대지상층수
Real number (ℝ)

Distinct16
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6885246
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:20.509866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile15
Maximum23
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.0514908
Coefficient of variation (CV)0.86412916
Kurtosis5.6327929
Mean4.6885246
Median Absolute Deviation (MAD)1
Skewness2.3329869
Sum572
Variance16.414578
MonotonicityNot monotonic
2023-12-11T01:38:20.712277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 29
23.8%
2 27
22.1%
5 23
18.9%
4 10
 
8.2%
1 9
 
7.4%
7 6
 
4.9%
6 4
 
3.3%
17 3
 
2.5%
15 3
 
2.5%
10 2
 
1.6%
Other values (6) 6
 
4.9%
ValueCountFrequency (%)
1 9
 
7.4%
2 27
22.1%
3 29
23.8%
4 10
 
8.2%
5 23
18.9%
6 4
 
3.3%
7 6
 
4.9%
8 1
 
0.8%
9 1
 
0.8%
10 2
 
1.6%
ValueCountFrequency (%)
23 1
 
0.8%
18 1
 
0.8%
17 3
2.5%
16 1
 
0.8%
15 3
2.5%
11 1
 
0.8%
10 2
 
1.6%
9 1
 
0.8%
8 1
 
0.8%
7 6
4.9%
Distinct5
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
47 
1
40 
0
26 
2
3
 
2

Length

Max length4
Median length1
Mean length2.1557377
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row<NA>
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 47
38.5%
1 40
32.8%
0 26
21.3%
2 7
 
5.7%
3 2
 
1.6%

Length

2023-12-11T01:38:20.976099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:21.204791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
38.5%
1 40
32.8%
0 26
21.3%
2 7
 
5.7%
3 2
 
1.6%

최고높이(미터)
Real number (ℝ)

ZEROS 

Distinct95
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.900451
Minimum0
Maximum121.7
Zeros12
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:21.405488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median13.25
Q318.56
95-th percentile55.885
Maximum121.7
Range121.7
Interquartile range (IQR)10.56

Descriptive statistics

Standard deviation17.911979
Coefficient of variation (CV)1.0598521
Kurtosis11.979085
Mean16.900451
Median Absolute Deviation (MAD)5.34
Skewness3.0468108
Sum2061.855
Variance320.83898
MonotonicityNot monotonic
2023-12-11T01:38:21.713029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 12
 
9.8%
14.7 3
 
2.5%
83.02 2
 
1.6%
15.2 2
 
1.6%
12.3 2
 
1.6%
14.9 2
 
1.6%
8.1 2
 
1.6%
17.35 2
 
1.6%
7.2 2
 
1.6%
8.95 2
 
1.6%
Other values (85) 91
74.6%
ValueCountFrequency (%)
0.0 12
9.8%
2.7 1
 
0.8%
3.0 1
 
0.8%
3.2 1
 
0.8%
3.3 1
 
0.8%
4.45 1
 
0.8%
6.0 2
 
1.6%
6.5 1
 
0.8%
6.8 1
 
0.8%
7.0 1
 
0.8%
ValueCountFrequency (%)
121.7 1
0.8%
83.02 2
1.6%
63.7 1
0.8%
62.7 1
0.8%
59.8 1
0.8%
56.0 1
0.8%
53.7 1
0.8%
47.3 1
0.8%
40.1 1
0.8%
37.1 1
0.8%

동수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5819672
Minimum0
Maximum59
Zeros3
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:21.932469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum59
Range59
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.270909
Coefficient of variation (CV)3.33187
Kurtosis119.21974
Mean1.5819672
Median Absolute Deviation (MAD)0
Skewness10.862687
Sum193
Variance27.782482
MonotonicityNot monotonic
2023-12-11T01:38:22.116611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 108
88.5%
2 7
 
5.7%
0 3
 
2.5%
5 1
 
0.8%
3 1
 
0.8%
59 1
 
0.8%
4 1
 
0.8%
ValueCountFrequency (%)
0 3
 
2.5%
1 108
88.5%
2 7
 
5.7%
3 1
 
0.8%
4 1
 
0.8%
5 1
 
0.8%
59 1
 
0.8%
ValueCountFrequency (%)
59 1
 
0.8%
5 1
 
0.8%
4 1
 
0.8%
3 1
 
0.8%
2 7
 
5.7%
1 108
88.5%
0 3
 
2.5%

주용도
Categorical

Distinct12
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
제2종근린생활시설
54 
제1종근린생활시설
26 
공동주택
16 
업무시설
12 
창고시설
 
3
Other values (7)
11 

Length

Max length10
Median length9
Mean length7.3770492
Min length4

Unique

Unique4 ?
Unique (%)3.3%

Sample

1st row업무시설
2nd row업무시설
3rd row제2종근린생활시설
4th row제2종근린생활시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 54
44.3%
제1종근린생활시설 26
21.3%
공동주택 16
 
13.1%
업무시설 12
 
9.8%
창고시설 3
 
2.5%
단독주택 3
 
2.5%
숙박시설 2
 
1.6%
교육연구시설 2
 
1.6%
위험물저장및처리시설 1
 
0.8%
관광휴게시설 1
 
0.8%
Other values (2) 2
 
1.6%

Length

2023-12-11T01:38:22.388178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 54
44.3%
제1종근린생활시설 26
21.3%
공동주택 16
 
13.1%
업무시설 12
 
9.8%
창고시설 3
 
2.5%
단독주택 3
 
2.5%
숙박시설 2
 
1.6%
교육연구시설 2
 
1.6%
위험물저장및처리시설 1
 
0.8%
관광휴게시설 1
 
0.8%
Other values (2) 2
 
1.6%

부속용도
Text

MISSING 

Distinct70
Distinct (%)72.2%
Missing25
Missing (%)20.5%
Memory size1.1 KiB
2023-12-11T01:38:22.726378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length28
Mean length10.484536
Min length2

Characters and Unicode

Total characters1017
Distinct characters95
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

Unique59 ?
Unique (%)60.8%

Sample

1st row오피스텔
2nd row오피스텔
3rd row일반음식점
4th row사무소,부동산중개업소
5th row다세대주택
ValueCountFrequency (%)
사무소 13
 
9.4%
소매점 8
 
5.8%
휴게음식점 6
 
4.3%
제2종근린생활시설 5
 
3.6%
오피스텔 5
 
3.6%
제1,2종근린생활시설 5
 
3.6%
일반음식점 4
 
2.9%
4
 
2.9%
의원 4
 
2.9%
근린생활시설 3
 
2.2%
Other values (67) 81
58.7%
2023-12-11T01:38:23.311769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
 
5.3%
48
 
4.7%
, 44
 
4.3%
41
 
4.0%
40
 
3.9%
35
 
3.4%
( 34
 
3.3%
) 34
 
3.3%
34
 
3.3%
32
 
3.1%
Other values (85) 621
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 821
80.7%
Other Punctuation 50
 
4.9%
Space Separator 41
 
4.0%
Open Punctuation 34
 
3.3%
Close Punctuation 34
 
3.3%
Decimal Number 32
 
3.1%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
54
 
6.6%
48
 
5.8%
40
 
4.9%
35
 
4.3%
34
 
4.1%
32
 
3.9%
32
 
3.9%
32
 
3.9%
31
 
3.8%
30
 
3.7%
Other values (75) 453
55.2%
Other Punctuation
ValueCountFrequency (%)
, 44
88.0%
/ 3
 
6.0%
: 2
 
4.0%
. 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 18
56.2%
1 14
43.8%
Space Separator
ValueCountFrequency (%)
41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 821
80.7%
Common 196
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
54
 
6.6%
48
 
5.8%
40
 
4.9%
35
 
4.3%
34
 
4.1%
32
 
3.9%
32
 
3.9%
32
 
3.9%
31
 
3.8%
30
 
3.7%
Other values (75) 453
55.2%
Common
ValueCountFrequency (%)
, 44
22.4%
41
20.9%
( 34
17.3%
) 34
17.3%
2 18
9.2%
1 14
 
7.1%
- 5
 
2.6%
/ 3
 
1.5%
: 2
 
1.0%
. 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 821
80.7%
ASCII 196
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
54
 
6.6%
48
 
5.8%
40
 
4.9%
35
 
4.3%
34
 
4.1%
32
 
3.9%
32
 
3.9%
32
 
3.9%
31
 
3.8%
30
 
3.7%
Other values (75) 453
55.2%
ASCII
ValueCountFrequency (%)
, 44
22.4%
41
20.9%
( 34
17.3%
) 34
17.3%
2 18
9.2%
1 14
 
7.1%
- 5
 
2.6%
/ 3
 
1.5%
: 2
 
1.0%
. 1
 
0.5%

용도지역
Categorical

Distinct11
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
제2종일반주거지역
50 
일반상업지역
26 
가축사육제한구역
15 
제3종일반주거지역
11 
준주거지역
Other values (6)
14 

Length

Max length9
Median length9
Mean length7.795082
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
제2종일반주거지역 50
41.0%
일반상업지역 26
21.3%
가축사육제한구역 15
 
12.3%
제3종일반주거지역 11
 
9.0%
준주거지역 6
 
4.9%
제1종일반주거지역 5
 
4.1%
전용공업지역 2
 
1.6%
준공업지역 2
 
1.6%
자연녹지지역 2
 
1.6%
<NA> 2
 
1.6%

Length

2023-12-11T01:38:23.586567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 50
41.0%
일반상업지역 26
21.3%
가축사육제한구역 15
 
12.3%
제3종일반주거지역 11
 
9.0%
준주거지역 6
 
4.9%
제1종일반주거지역 5
 
4.1%
전용공업지역 2
 
1.6%
준공업지역 2
 
1.6%
자연녹지지역 2
 
1.6%
na 2
 
1.6%

용도지구
Categorical

IMBALANCE 

Distinct8
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
85 
방화지구
31 
항만시설보호지구
 
1
중요시설물보호지구(항만)
 
1
수변경관지구
 
1
Other values (3)
 
3

Length

Max length13
Median length4
Mean length4.1557377
Min length4

Unique

Unique6 ?
Unique (%)4.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
69.7%
방화지구 31
 
25.4%
항만시설보호지구 1
 
0.8%
중요시설물보호지구(항만) 1
 
0.8%
수변경관지구 1
 
0.8%
온천지구 1
 
0.8%
철도보호지구 1
 
0.8%
경관지구기타 1
 
0.8%

Length

2023-12-11T01:38:23.850413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:24.022480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
69.7%
방화지구 31
 
25.4%
항만시설보호지구 1
 
0.8%
중요시설물보호지구(항만 1
 
0.8%
수변경관지구 1
 
0.8%
온천지구 1
 
0.8%
철도보호지구 1
 
0.8%
경관지구기타 1
 
0.8%

용도구역
Categorical

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
60 
가축사육제한구역
37 
상대보호구역
22 
제1종지구단위계획구역
 
1
기타용지
 
1

Length

Max length11
Median length9.5
Mean length5.6639344
Min length4

Unique

Unique3 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 60
49.2%
가축사육제한구역 37
30.3%
상대보호구역 22
 
18.0%
제1종지구단위계획구역 1
 
0.8%
기타용지 1
 
0.8%
지역특화발전특구 1
 
0.8%

Length

2023-12-11T01:38:24.349094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:24.530180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
49.2%
가축사육제한구역 37
30.3%
상대보호구역 22
 
18.0%
제1종지구단위계획구역 1
 
0.8%
기타용지 1
 
0.8%
지역특화발전특구 1
 
0.8%

세대수
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)90.0%
Missing102
Missing (%)83.6%
Infinite0
Infinite (%)0.0%
Mean24.2
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:24.710433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q111.75
median21
Q325.75
95-th percentile45.9
Maximum120
Range119
Interquartile range (IQR)14

Descriptive statistics

Standard deviation24.917971
Coefficient of variation (CV)1.0296682
Kurtosis12.396971
Mean24.2
Median Absolute Deviation (MAD)8
Skewness3.2157395
Sum484
Variance620.90526
MonotonicityNot monotonic
2023-12-11T01:38:24.916671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
24 2
 
1.6%
23 2
 
1.6%
120 1
 
0.8%
11 1
 
0.8%
16 1
 
0.8%
28 1
 
0.8%
1 1
 
0.8%
25 1
 
0.8%
14 1
 
0.8%
12 1
 
0.8%
Other values (8) 8
 
6.6%
(Missing) 102
83.6%
ValueCountFrequency (%)
1 1
0.8%
3 1
0.8%
8 1
0.8%
9 1
0.8%
11 1
0.8%
12 1
0.8%
14 1
0.8%
15 1
0.8%
16 1
0.8%
19 1
0.8%
ValueCountFrequency (%)
120 1
0.8%
42 1
0.8%
37 1
0.8%
30 1
0.8%
28 1
0.8%
25 1
0.8%
24 2
1.6%
23 2
1.6%
19 1
0.8%
16 1
0.8%

호수
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)73.7%
Missing103
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean30.473684
Minimum1
Maximum128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:38:25.105583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.5
median7
Q332.5
95-th percentile120.8
Maximum128
Range127
Interquartile range (IQR)29

Descriptive statistics

Standard deviation44.234688
Coefficient of variation (CV)1.4515701
Kurtosis1.0260452
Mean30.473684
Median Absolute Deviation (MAD)5
Skewness1.5889436
Sum579
Variance1956.7076
MonotonicityNot monotonic
2023-12-11T01:38:25.317553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7 3
 
2.5%
120 2
 
1.6%
3 2
 
1.6%
1 2
 
1.6%
8 1
 
0.8%
31 1
 
0.8%
34 1
 
0.8%
70 1
 
0.8%
4 1
 
0.8%
11 1
 
0.8%
Other values (4) 4
 
3.3%
(Missing) 103
84.4%
ValueCountFrequency (%)
1 2
1.6%
2 1
 
0.8%
3 2
1.6%
4 1
 
0.8%
6 1
 
0.8%
7 3
2.5%
8 1
 
0.8%
11 1
 
0.8%
16 1
 
0.8%
31 1
 
0.8%
ValueCountFrequency (%)
128 1
 
0.8%
120 2
1.6%
70 1
 
0.8%
34 1
 
0.8%
31 1
 
0.8%
16 1
 
0.8%
11 1
 
0.8%
8 1
 
0.8%
7 3
2.5%
6 1
 
0.8%

가구수
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
107 
1
11 
2
 
3
5
 
1

Length

Max length4
Median length4
Mean length3.6311475
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 107
87.7%
1 11
 
9.0%
2 3
 
2.5%
5 1
 
0.8%

Length

2023-12-11T01:38:25.501746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:25.670385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 107
87.7%
1 11
 
9.0%
2 3
 
2.5%
5 1
 
0.8%

주건축물수
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
110 
2
 
6
<NA>
 
3
4
 
1
3
 
1

Length

Max length4
Median length1
Mean length1.0819672
Min length1

Unique

Unique3 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 110
90.2%
2 6
 
4.9%
<NA> 3
 
2.5%
4 1
 
0.8%
3 1
 
0.8%
59 1
 
0.8%

Length

2023-12-11T01:38:25.832191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:38:25.986616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 110
90.2%
2 6
 
4.9%
na 3
 
2.5%
4 1
 
0.8%
3 1
 
0.8%
59 1
 
0.8%
Distinct85
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T01:38:26.319055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.614754
Min length7

Characters and Unicode

Total characters1295
Distinct characters127
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

Unique64 ?
Unique (%)52.5%

Sample

1st row(주)서원건축사사무소
2nd row(주)서원건축사사무소
3rd row한솔 건축사사무소
4th row건축사사무소 한마루
5th row누마루건축사사무소
ValueCountFrequency (%)
건축사사무소 54
26.2%
주식회사 14
 
6.8%
한솔 9
 
4.4%
종합건축사사무소 8
 
3.9%
유승 6
 
2.9%
바로건축사사무소 4
 
1.9%
이진건축사사무소 3
 
1.5%
원탑 3
 
1.5%
대상 3
 
1.5%
지에이엠 2
 
1.0%
Other values (83) 100
48.5%
2023-12-11T01:38:26.845371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
20.1%
126
 
9.7%
124
 
9.6%
123
 
9.5%
122
 
9.4%
85
 
6.6%
38
 
2.9%
( 20
 
1.5%
) 20
 
1.5%
18
 
1.4%
Other values (117) 359
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1144
88.3%
Space Separator 85
 
6.6%
Open Punctuation 20
 
1.5%
Close Punctuation 20
 
1.5%
Uppercase Letter 12
 
0.9%
Other Punctuation 8
 
0.6%
Decimal Number 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
260
22.7%
126
11.0%
124
10.8%
123
10.8%
122
10.7%
38
 
3.3%
18
 
1.6%
18
 
1.6%
16
 
1.4%
15
 
1.3%
Other values (104) 284
24.8%
Uppercase Letter
ValueCountFrequency (%)
J 4
33.3%
A 3
25.0%
T 2
16.7%
M 2
16.7%
S 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
# 1
 
12.5%
& 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1144
88.3%
Common 139
 
10.7%
Latin 12
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
260
22.7%
126
11.0%
124
10.8%
123
10.8%
122
10.7%
38
 
3.3%
18
 
1.6%
18
 
1.6%
16
 
1.4%
15
 
1.3%
Other values (104) 284
24.8%
Common
ValueCountFrequency (%)
85
61.2%
( 20
 
14.4%
) 20
 
14.4%
. 6
 
4.3%
1 3
 
2.2%
2 3
 
2.2%
# 1
 
0.7%
& 1
 
0.7%
Latin
ValueCountFrequency (%)
J 4
33.3%
A 3
25.0%
T 2
16.7%
M 2
16.7%
S 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1144
88.3%
ASCII 151
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
260
22.7%
126
11.0%
124
10.8%
123
10.8%
122
10.7%
38
 
3.3%
18
 
1.6%
18
 
1.6%
16
 
1.4%
15
 
1.3%
Other values (104) 284
24.8%
ASCII
ValueCountFrequency (%)
85
56.3%
( 20
 
13.2%
) 20
 
13.2%
. 6
 
4.0%
J 4
 
2.6%
1 3
 
2.0%
2 3
 
2.0%
A 3
 
2.0%
T 2
 
1.3%
M 2
 
1.3%
Other values (3) 3
 
2.0%

감리사무소명
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing87
Missing (%)71.3%
Memory size1.1 KiB
2023-12-11T01:38:27.106573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.885714
Min length8

Characters and Unicode

Total characters381
Distinct characters79
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

Unique33 ?
Unique (%)94.3%

Sample

1st row건축사사무소엠디
2nd row원심 건축사사무소
3rd row예담종합건축사사무소
4th row유진이엔지 건축사사무소
5th row주식회사 인우건축사사무소
ValueCountFrequency (%)
건축사사무소 11
21.2%
주식회사 6
 
11.5%
유승 2
 
3.8%
주)상지엔지니어링건축사사무소 1
 
1.9%
주)제이비건축사사무소 1
 
1.9%
가원건축사사무소 1
 
1.9%
우인설계건축사사무소 1
 
1.9%
다우건축사사무소 1
 
1.9%
a&t한상준건축사사무소 1
 
1.9%
동림 1
 
1.9%
Other values (26) 26
50.0%
2023-12-11T01:38:27.584346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
19.9%
35
 
9.2%
35
 
9.2%
35
 
9.2%
35
 
9.2%
18
 
4.7%
15
 
3.9%
( 8
 
2.1%
) 8
 
2.1%
6
 
1.6%
Other values (69) 110
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
89.2%
Space Separator 18
 
4.7%
Open Punctuation 8
 
2.1%
Close Punctuation 8
 
2.1%
Uppercase Letter 4
 
1.0%
Decimal Number 2
 
0.5%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
76
22.4%
35
10.3%
35
10.3%
35
10.3%
35
10.3%
15
 
4.4%
6
 
1.8%
6
 
1.8%
5
 
1.5%
5
 
1.5%
Other values (59) 87
25.6%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
A 1
25.0%
M 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
89.2%
Common 37
 
9.7%
Latin 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
76
22.4%
35
10.3%
35
10.3%
35
10.3%
35
10.3%
15
 
4.4%
6
 
1.8%
6
 
1.8%
5
 
1.5%
5
 
1.5%
Other values (59) 87
25.6%
Common
ValueCountFrequency (%)
18
48.6%
( 8
21.6%
) 8
21.6%
& 1
 
2.7%
1 1
 
2.7%
2 1
 
2.7%
Latin
ValueCountFrequency (%)
T 1
25.0%
C 1
25.0%
A 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
89.2%
ASCII 41
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
76
22.4%
35
10.3%
35
10.3%
35
10.3%
35
10.3%
15
 
4.4%
6
 
1.8%
6
 
1.8%
5
 
1.5%
5
 
1.5%
Other values (59) 87
25.6%
ASCII
ValueCountFrequency (%)
18
43.9%
( 8
19.5%
) 8
19.5%
& 1
 
2.4%
T 1
 
2.4%
C 1
 
2.4%
A 1
 
2.4%
1 1
 
2.4%
2 1
 
2.4%
M 1
 
2.4%

시공자사무소명
Text

MISSING 

Distinct24
Distinct (%)88.9%
Missing95
Missing (%)77.9%
Memory size1.1 KiB
2023-12-11T01:38:27.851154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length8.7777778
Min length7

Characters and Unicode

Total characters237
Distinct characters62
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

Unique22 ?
Unique (%)81.5%

Sample

1st row(주)희종종합건설
2nd row나라종합건설(주)
3rd row(주)이카종합건설
4th row한목종합건설(주)
5th row디엠종합건설(주)
ValueCountFrequency (%)
주)이카종합건설 3
 
11.1%
주)디아이건설 2
 
7.4%
주)디알종합건설 1
 
3.7%
예린종합건설(주 1
 
3.7%
소도건설(주 1
 
3.7%
주식회사한유건설 1
 
3.7%
주)에스티모빅 1
 
3.7%
쿨스종합건설(주 1
 
3.7%
휘림건설(주 1
 
3.7%
주)이누테크 1
 
3.7%
Other values (14) 14
51.9%
2023-12-11T01:38:28.358027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
11.4%
( 25
 
10.5%
) 25
 
10.5%
23
 
9.7%
23
 
9.7%
19
 
8.0%
17
 
7.2%
7
 
3.0%
4
 
1.7%
3
 
1.3%
Other values (52) 64
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
78.9%
Open Punctuation 25
 
10.5%
Close Punctuation 25
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
14.4%
23
 
12.3%
23
 
12.3%
19
 
10.2%
17
 
9.1%
7
 
3.7%
4
 
2.1%
3
 
1.6%
2
 
1.1%
2
 
1.1%
Other values (50) 60
32.1%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
78.9%
Common 50
 
21.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
14.4%
23
 
12.3%
23
 
12.3%
19
 
10.2%
17
 
9.1%
7
 
3.7%
4
 
2.1%
3
 
1.6%
2
 
1.1%
2
 
1.1%
Other values (50) 60
32.1%
Common
ValueCountFrequency (%)
( 25
50.0%
) 25
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
78.9%
ASCII 50
 
21.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
27
14.4%
23
 
12.3%
23
 
12.3%
19
 
10.2%
17
 
9.1%
7
 
3.7%
4
 
2.1%
3
 
1.6%
2
 
1.1%
2
 
1.1%
Other values (50) 60
32.1%
ASCII
ValueCountFrequency (%)
( 25
50.0%
) 25
50.0%

Sample

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역세대수호수가구수주건축물수설계사무소명감리사무소명시공자사무소명
0신축부산광역시 남구 문현동 539-32 외1필지478.73382.445,560.0579<NA>79.891,070.18철근콘크리트구조2022-12-30<NA>17283.021업무시설오피스텔일반상업지역방화지구가축사육제한구역<NA>120<NA>1(주)서원건축사사무소<NA><NA>
1신축부산광역시 남구 문현동 539-32 외1필지478.73382.445,560.0579<NA>79.891,070.18철근콘크리트구조2022-12-30<NA>17283.021업무시설오피스텔일반상업지역방화지구가축사육제한구역<NA>120<NA>1(주)서원건축사사무소<NA><NA>
2용도변경부산광역시 남구 우암동 151-87944.1744.17<NA>55.9155.91<NA>2022-12-28<NA>1<NA>3.31제2종근린생활시설일반음식점제2종일반주거지역<NA>상대보호구역<NA><NA><NA>1한솔 건축사사무소<NA><NA>
3신축부산광역시 남구 문현동 141-38188111.6412.355<NA>59.36219.34철골콘크리트구조2022-12-21<NA>5016.351제2종근린생활시설<NA>제2종일반주거지역<NA>가축사육제한구역<NA><NA>11건축사사무소 한마루<NA><NA>
4용도변경부산광역시 남구 문현동 78-4250130.62296.08<NA>52.25100.95벽돌구조2022-12-20<NA>217.51제2종근린생활시설사무소,부동산중개업소제1종일반주거지역<NA><NA><NA><NA><NA>1누마루건축사사무소<NA><NA>
5신축부산광역시 남구 대연동 1281-50 외1필지245146.29425.354<NA>59.71173.61철근콘크리트구조2022-12-162023-02-135015.61공동주택다세대주택제2종일반주거지역<NA>가축사육제한구역12<NA><NA>1건축사사무소 원탑건축사사무소엠디(주)희종종합건설
6신축부산광역시 남구 용호동 366-1182.9109.25459.12<NA>59.73251.02철근콘크리트구조2022-12-162023-01-105017.061제1종근린생활시설한의원준주거지역<NA><NA><NA><NA><NA>1아담 종합건축사사무소원심 건축사사무소나라종합건설(주)
7신축부산광역시 남구 용호동 543-10761.9379.222,240.07<NA>49.77228.02철근콘크리트구조2022-12-15<NA>5119.781업무시설공공업무시설제3종일반주거지역<NA>제1종지구단위계획구역<NA><NA><NA>1도홍건축사사무소<NA><NA>
8신축부산광역시 남구 문현동 119-46597356.41,311.5<NA>59.7219.68철근콘크리트구조2022-12-152023-01-115016.751업무시설(오피스텔)및공동주택(다세대주택)제2종일반주거지역<NA>상대보호구역88<NA>1건축사사무소 원탑예담종합건축사사무소(주)이카종합건설
9증축부산광역시 남구 대연동 1500-12499.5235.08885.9123.6747.06177.36철근콘크리트구조2022-12-142023-01-124<NA>14.71제1종근린생활시설휴게음식점제2종일반주거지역<NA><NA><NA><NA><NA>1(주)제이비 건축사사무소<NA><NA>
건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역세대수호수가구수주건축물수설계사무소명감리사무소명시공자사무소명
112용도변경부산광역시 남구 문현동 141-3818884.79142.9<NA>45.168.52블록구조2022-01-26<NA>210.01제2종근린생활시설<NA>제2종전용주거지역<NA>가축사육제한구역<NA><NA><NA>1건축사사무소 한마루<NA><NA>
113용도변경부산광역시 남구 감만동 171-9505296.371,510.14<NA>58.6871213.2376<NA>2022-01-20<NA>4113.851제2종근린생활시설학원준주거지역<NA><NA><NA><NA><NA>1건축사사무소 건<NA><NA>
114용도변경부산광역시 남구 용당동 568-3039363.9763.97<NA>16.2816.28블록구조2022-01-19<NA>1<NA>0.01제2종근린생활시설제2종근린생활시설(사무소)제1종일반주거지역경관지구기타가축사육제한구역<NA><NA><NA>1바로건축사사무소<NA><NA>
115증축부산광역시 남구 대연동 243-2910,8534,283.8214,403.662,43039.4783.06일반철골구조2022-01-172022-06-072<NA>8.84업무시설공공업무시설(경찰서)제2종일반주거지역<NA>상대보호구역<NA><NA><NA>1대상 건축사사무소대상 건축사사무소제이티건설(주)
116용도변경부산광역시 남구 용당동 276306150.59246.06<NA>49.2180.41일반철골구조2022-01-10<NA>2<NA>8.951제2종근린생활시설제2종근린생활시설 및 공장제2종일반주거지역<NA>상대보호구역<NA><NA><NA>1한솔 건축사사무소<NA><NA>
117신축부산광역시 남구 대연동 1536-916088.41327.58<NA>55.26204.74철근콘크리트구조2022-01-06<NA>4013.651제2종근린생활시설<NA>제2종일반주거지역<NA><NA><NA><NA><NA>1건축사사무소 금강<NA><NA>
118용도변경부산광역시 남구 대연동 53-1231.5138.04494.82<NA>59.6285171.4989철근콘크리트구조2022-01-06<NA>310.01제1종근린생활시설<NA>제3종일반주거지역<NA>가축사육제한구역<NA><NA><NA>1건축사사무소 공감그룹<NA><NA>
119신축부산광역시 남구 문현동 119-50382228.68659.2175<NA>59.86172.57철근콘크리트구조2022-01-042022-01-125015.81공동주택공동주택(다세대주택)제2종일반주거지역<NA>상대보호구역11<NA><NA>1건축사사무소 원탑중앙CM건축사사무소(주)이카종합건설
120용도변경부산광역시 남구 용호동 517-20202.6117.69188.1<NA>58.0992.84<NA>2022-01-03<NA>2<NA>7.21제2종근린생활시설<NA>제2종일반주거지역<NA><NA><NA><NA>11건축사사무소준우<NA><NA>
121용도변경부산광역시 남구 대연동 731-11,624.82649.644,151.47<NA>39.98140.98철근콘크리트구조2022-01-03<NA>4214.61의료시설<NA><NA><NA><NA><NA><NA><NA>1화우 건축사사무소<NA><NA>

Duplicate rows

Most frequently occurring

건축구분대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역세대수호수가구수주건축물수설계사무소명감리사무소명시공자사무소명# duplicates
0신축부산광역시 남구 문현동 539-32 외1필지478.73382.445,560.0579<NA>79.891,070.18철근콘크리트구조2022-12-30<NA>17283.021업무시설오피스텔일반상업지역방화지구가축사육제한구역<NA>120<NA>1(주)서원건축사사무소<NA><NA>2