Overview

Dataset statistics

Number of variables35
Number of observations94
Missing cells329
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.1 KiB
Average record size in memory295.4 B

Variable types

Categorical10
Text9
Numeric11
DateTime5

Dataset

Description부산광역시_동래구_건축물착공신고현황_20230111
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15026291

Alerts

지목 is highly imbalanced (81.9%)Imbalance
구조 is highly imbalanced (66.2%)Imbalance
동수 is highly imbalanced (73.6%)Imbalance
용도지구 is highly imbalanced (57.1%)Imbalance
가구수 is highly imbalanced (65.8%)Imbalance
증축연면적(제곱미터) has 72 (76.6%) missing valuesMissing
사용승인일 has 49 (52.1%) missing valuesMissing
부속용도 has 11 (11.7%) missing valuesMissing
총주차대수 has 10 (10.6%) missing valuesMissing
세대수 has 69 (73.4%) missing valuesMissing
호수 has 79 (84.0%) missing valuesMissing
감리사무소명 has 6 (6.4%) missing valuesMissing
감리자 도로명주소 has 6 (6.4%) missing valuesMissing
시공자사무소명 has 27 (28.7%) missing valuesMissing
허가번호 has unique valuesUnique
용적률(퍼센트) has unique valuesUnique
최고높이(미터) has 1 (1.1%) zerosZeros
총주차대수 has 3 (3.2%) zerosZeros
세대수 has 1 (1.1%) zerosZeros
호수 has 1 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:14:57.694752
Analysis finished2023-12-10 16:14:58.661495
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size884.0 B
신축
64 
증축
22 
대수선

Length

Max length3
Median length2
Mean length2.0851064
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 64
68.1%
증축 22
 
23.4%
대수선 8
 
8.5%

Length

2023-12-11T01:14:58.739785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:58.865898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 64
68.1%
증축 22
 
23.4%
대수선 8
 
8.5%

허가번호
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:14:59.174257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length15.861702
Min length15

Characters and Unicode

Total characters1491
Distinct characters26
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

Unique94 ?
Unique (%)100.0%

Sample

1st row2022-건축과-대수선허가-9
2nd row2022-건축과-신축허가-82
3rd row2022-건축과-대수선허가-7
4th row2022-건축과-신축허가-81
5th row2022-건축과-신축허가-76
ValueCountFrequency (%)
2022-건축과-대수선허가-9 1
 
1.1%
2022-건축과-증축허가-4 1
 
1.1%
2022-건축과-증축허가-2 1
 
1.1%
2022-건축과-신축허가-2 1
 
1.1%
2022-건축과-신축허가-3 1
 
1.1%
2022-건축과-증축허가-3 1
 
1.1%
2022-건축과-신축허가-6 1
 
1.1%
2022-건축과-신축허가-4 1
 
1.1%
2022-건축과-신축허가-7 1
 
1.1%
2022-건축과-신축허가-8 1
 
1.1%
Other values (84) 84
89.4%
2023-12-11T01:14:59.720092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 282
18.9%
2 274
18.4%
181
12.1%
0 102
 
6.8%
97
 
6.5%
94
 
6.3%
91
 
6.1%
91
 
6.1%
64
 
4.3%
1 53
 
3.6%
Other values (16) 162
10.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 668
44.8%
Decimal Number 541
36.3%
Dash Punctuation 282
18.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
181
27.1%
97
14.5%
94
14.1%
91
13.6%
91
13.6%
64
 
9.6%
20
 
3.0%
7
 
1.0%
7
 
1.0%
7
 
1.0%
Other values (5) 9
 
1.3%
Decimal Number
ValueCountFrequency (%)
2 274
50.6%
0 102
 
18.9%
1 53
 
9.8%
4 19
 
3.5%
8 17
 
3.1%
3 16
 
3.0%
5 16
 
3.0%
6 16
 
3.0%
9 15
 
2.8%
7 13
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 282
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 823
55.2%
Hangul 668
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
181
27.1%
97
14.5%
94
14.1%
91
13.6%
91
13.6%
64
 
9.6%
20
 
3.0%
7
 
1.0%
7
 
1.0%
7
 
1.0%
Other values (5) 9
 
1.3%
Common
ValueCountFrequency (%)
- 282
34.3%
2 274
33.3%
0 102
 
12.4%
1 53
 
6.4%
4 19
 
2.3%
8 17
 
2.1%
3 16
 
1.9%
5 16
 
1.9%
6 16
 
1.9%
9 15
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 823
55.2%
Hangul 668
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 282
34.3%
2 274
33.3%
0 102
 
12.4%
1 53
 
6.4%
4 19
 
2.3%
8 17
 
2.1%
3 16
 
1.9%
5 16
 
1.9%
6 16
 
1.9%
9 15
 
1.8%
Hangul
ValueCountFrequency (%)
181
27.1%
97
14.5%
94
14.1%
91
13.6%
91
13.6%
64
 
9.6%
20
 
3.0%
7
 
1.0%
7
 
1.0%
7
 
1.0%
Other values (5) 9
 
1.3%
Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:15:00.060339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length21.170213
Min length18

Characters and Unicode

Total characters1990
Distinct characters35
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

Unique90 ?
Unique (%)95.7%

Sample

1st row부산광역시 동래구 온천동 1426-15 외3필지
2nd row부산광역시 동래구 명륜동 696-67
3rd row부산광역시 동래구 안락동 465-26
4th row부산광역시 동래구 안락동 221-9
5th row부산광역시 동래구 사직동 75-35 외1필지
ValueCountFrequency (%)
부산광역시 94
22.9%
동래구 94
22.9%
온천동 29
 
7.1%
안락동 21
 
5.1%
외1필지 16
 
3.9%
사직동 14
 
3.4%
명륜동 12
 
2.9%
외2필지 7
 
1.7%
외3필지 7
 
1.7%
낙민동 6
 
1.5%
Other values (99) 111
27.0%
2023-12-11T01:15:00.541919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
15.9%
188
 
9.4%
1 105
 
5.3%
95
 
4.8%
94
 
4.7%
94
 
4.7%
94
 
4.7%
94
 
4.7%
94
 
4.7%
94
 
4.7%
Other values (25) 721
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1137
57.1%
Decimal Number 446
 
22.4%
Space Separator 317
 
15.9%
Dash Punctuation 90
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
188
16.5%
95
8.4%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
34
 
3.0%
34
 
3.0%
Other values (13) 222
19.5%
Decimal Number
ValueCountFrequency (%)
1 105
23.5%
4 59
13.2%
2 56
12.6%
5 45
10.1%
3 42
 
9.4%
6 40
 
9.0%
7 30
 
6.7%
9 27
 
6.1%
0 22
 
4.9%
8 20
 
4.5%
Space Separator
ValueCountFrequency (%)
317
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1137
57.1%
Common 853
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
188
16.5%
95
8.4%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
34
 
3.0%
34
 
3.0%
Other values (13) 222
19.5%
Common
ValueCountFrequency (%)
317
37.2%
1 105
 
12.3%
- 90
 
10.6%
4 59
 
6.9%
2 56
 
6.6%
5 45
 
5.3%
3 42
 
4.9%
6 40
 
4.7%
7 30
 
3.5%
9 27
 
3.2%
Other values (2) 42
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1137
57.1%
ASCII 853
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
37.2%
1 105
 
12.3%
- 90
 
10.6%
4 59
 
6.9%
2 56
 
6.6%
5 45
 
5.3%
3 42
 
4.9%
6 40
 
4.7%
7 30
 
3.5%
9 27
 
3.2%
Other values (2) 42
 
4.9%
Hangul
ValueCountFrequency (%)
188
16.5%
95
8.4%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
94
8.3%
34
 
3.0%
34
 
3.0%
Other values (13) 222
19.5%

지목
Categorical

IMBALANCE 

Distinct7
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
88 
 
1
임야
 
1
종교용지
 
1
수도용지
 
1
Other values (2)
 
2

Length

Max length4
Median length1
Mean length1.0957447
Min length1

Unique

Unique6 ?
Unique (%)6.4%

Sample

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

Common Values

ValueCountFrequency (%)
88
93.6%
1
 
1.1%
임야 1
 
1.1%
종교용지 1
 
1.1%
수도용지 1
 
1.1%
잡종지 1
 
1.1%
1
 
1.1%

Length

2023-12-11T01:15:00.687105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:00.802081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
88
93.6%
1
 
1.1%
임야 1
 
1.1%
종교용지 1
 
1.1%
수도용지 1
 
1.1%
잡종지 1
 
1.1%
1
 
1.1%
Distinct91
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1388.0288
Minimum104
Maximum75360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:00.958334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile123.6
Q1166.35
median348.6
Q3556.7
95-th percentile2591.25
Maximum75360
Range75256
Interquartile range (IQR)390.35

Descriptive statistics

Standard deviation7766.3888
Coefficient of variation (CV)5.5952648
Kurtosis91.294241
Mean1388.0288
Median Absolute Deviation (MAD)184.9
Skewness9.4940633
Sum130474.71
Variance60316796
MonotonicityNot monotonic
2023-12-11T01:15:01.164351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
558.0 2
 
2.1%
379.0 2
 
2.1%
193.0 2
 
2.1%
270.8 1
 
1.1%
131.6 1
 
1.1%
369.2 1
 
1.1%
356.7 1
 
1.1%
165.6 1
 
1.1%
261.0 1
 
1.1%
854.0 1
 
1.1%
Other values (81) 81
86.2%
ValueCountFrequency (%)
104.0 1
1.1%
109.0 1
1.1%
112.0 1
1.1%
112.83 1
1.1%
121.0 1
1.1%
125.0 1
1.1%
126.0 1
1.1%
127.7 1
1.1%
128.84 1
1.1%
131.6 1
1.1%
ValueCountFrequency (%)
75360.0 1
1.1%
5976.0 1
1.1%
4620.0 1
1.1%
3886.0 1
1.1%
3342.0 1
1.1%
2187.0 1
1.1%
1797.0 1
1.1%
1522.0 1
1.1%
1424.0 1
1.1%
1376.0 1
1.1%
Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean405.53697
Minimum59.06
Maximum13479.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:01.650676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59.06
5-th percentile70.54875
Q197.4725
median166.455
Q3317.7325
95-th percentile818.201
Maximum13479.44
Range13420.38
Interquartile range (IQR)220.26

Descriptive statistics

Standard deviation1398.6701
Coefficient of variation (CV)3.4489335
Kurtosis84.495056
Mean405.53697
Median Absolute Deviation (MAD)77.225
Skewness8.998542
Sum38120.475
Variance1956277.9
MonotonicityNot monotonic
2023-12-11T01:15:01.837993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119.6 2
 
2.1%
338.9 1
 
1.1%
158.49 1
 
1.1%
78.16 1
 
1.1%
163.56 1
 
1.1%
213.79 1
 
1.1%
97.66 1
 
1.1%
153.69 1
 
1.1%
426.81 1
 
1.1%
678.05 1
 
1.1%
Other values (83) 83
88.3%
ValueCountFrequency (%)
59.06 1
1.1%
64.18 1
1.1%
64.38 1
1.1%
65.67 1
1.1%
67.575 1
1.1%
72.15 1
1.1%
74.74 1
1.1%
74.78 1
1.1%
74.87 1
1.1%
75.66 1
1.1%
ValueCountFrequency (%)
13479.44 1
1.1%
1995.29 1
1.1%
1861.9 1
1.1%
1229.16 1
1.1%
931.08 1
1.1%
757.42 1
1.1%
678.05 1
1.1%
672.13 1
1.1%
495.85 1
1.1%
478.36 1
1.1%

연면적(제곱미터)
Real number (ℝ)

Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1462.4332
Minimum81.54
Maximum19916.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:01.993167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81.54
5-th percentile159.629
Q1275.4975
median542.63
Q31516.12
95-th percentile5829.4835
Maximum19916.77
Range19835.23
Interquartile range (IQR)1240.6225

Descriptive statistics

Standard deviation2745.7695
Coefficient of variation (CV)1.877535
Kurtosis24.108483
Mean1462.4332
Median Absolute Deviation (MAD)302.93
Skewness4.4204196
Sum137468.72
Variance7539250
MonotonicityNot monotonic
2023-12-11T01:15:02.158438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199.39 2
 
2.1%
998.5 1
 
1.1%
314.36 1
 
1.1%
268.8 1
 
1.1%
619.54 1
 
1.1%
585.68 1
 
1.1%
364.03 1
 
1.1%
573.51 1
 
1.1%
1527.09 1
 
1.1%
1307.11 1
 
1.1%
Other values (83) 83
88.3%
ValueCountFrequency (%)
81.54 1
1.1%
119.6 1
1.1%
128.76 1
1.1%
138.655 1
1.1%
158.68 1
1.1%
160.14 1
1.1%
164.13 1
1.1%
181.77 1
1.1%
183.525 1
1.1%
195.76 1
1.1%
ValueCountFrequency (%)
19916.77 1
1.1%
12054.32 1
1.1%
9550.38 1
1.1%
7042.14 1
1.1%
5996.28 1
1.1%
5739.67 1
1.1%
4105.9321 1
1.1%
4057.5595 1
1.1%
3710.405 1
1.1%
3369.78 1
1.1%

증축연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)100.0%
Missing72
Missing (%)76.6%
Infinite0
Infinite (%)0.0%
Mean334.18
Minimum-49.125
Maximum2605.26
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.1%
Memory size978.0 B
2023-12-11T01:15:02.292799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-49.125
5-th percentile5.43
Q134.895
median116.345
Q3355.0925
95-th percentile948.2035
Maximum2605.26
Range2654.385
Interquartile range (IQR)320.1975

Descriptive statistics

Standard deviation580.04395
Coefficient of variation (CV)1.7357231
Kurtosis11.592615
Mean334.18
Median Absolute Deviation (MAD)86.64255
Skewness3.1594552
Sum7351.9599
Variance336450.99
MonotonicityNot monotonic
2023-12-11T01:15:02.459091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
85.28 1
 
1.1%
2605.26 1
 
1.1%
169.32 1
 
1.1%
28.3349 1
 
1.1%
6.0 1
 
1.1%
160.08 1
 
1.1%
33.99 1
 
1.1%
679.35 1
 
1.1%
71.38 1
 
1.1%
958.17 1
 
1.1%
Other values (12) 12
 
12.8%
(Missing) 72
76.6%
ValueCountFrequency (%)
-49.125 1
1.1%
5.4 1
1.1%
6.0 1
1.1%
28.3349 1
1.1%
31.07 1
1.1%
33.99 1
1.1%
37.61 1
1.1%
38.15 1
1.1%
71.38 1
1.1%
85.28 1
1.1%
ValueCountFrequency (%)
2605.26 1
1.1%
958.17 1
1.1%
758.84 1
1.1%
679.35 1
1.1%
638.58 1
1.1%
362.71 1
1.1%
332.24 1
1.1%
169.32 1
1.1%
166.63 1
1.1%
160.08 1
1.1%

건폐율(퍼센트)
Real number (ℝ)

Distinct89
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.734586
Minimum17.45
Maximum79.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:02.603975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.45
5-th percentile26.95007
Q148.119525
median58.93
Q359.7275
95-th percentile74.06124
Maximum79.86
Range62.41
Interquartile range (IQR)11.607975

Descriptive statistics

Standard deviation13.194903
Coefficient of variation (CV)0.24555699
Kurtosis0.66267479
Mean53.734586
Median Absolute Deviation (MAD)3.0332
Skewness-0.87514282
Sum5051.0511
Variance174.10547
MonotonicityNot monotonic
2023-12-11T01:15:02.741458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39.42 2
 
2.1%
59.25 2
 
2.1%
49.98 2
 
2.1%
31.5567 2
 
2.1%
59.82 2
 
2.1%
58.53 1
 
1.1%
44.3 1
 
1.1%
59.9355 1
 
1.1%
58.97 1
 
1.1%
58.89 1
 
1.1%
Other values (79) 79
84.0%
ValueCountFrequency (%)
17.45 1
1.1%
17.89 1
1.1%
19.823 1
1.1%
26.6 1
1.1%
26.62 1
1.1%
27.1278 1
1.1%
29.88 1
1.1%
30.96 1
1.1%
31.5567 2
2.1%
33.39 1
1.1%
ValueCountFrequency (%)
79.86 1
1.1%
76.7812 1
1.1%
76.5962 1
1.1%
75.6 1
1.1%
74.64 1
1.1%
73.7496 1
1.1%
69.84 1
1.1%
69.64 1
1.1%
68.8884 1
1.1%
67.99 1
1.1%

용적률(퍼센트)
Real number (ℝ)

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.24024
Minimum21
Maximum1142.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:02.928441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile34.082
Q1109.2906
median180.185
Q3219.71
95-th percentile595.11377
Maximum1142.28
Range1121.28
Interquartile range (IQR)110.4194

Descriptive statistics

Standard deviation195.69643
Coefficient of variation (CV)0.89261184
Kurtosis8.1024681
Mean219.24024
Median Absolute Deviation (MAD)53.96975
Skewness2.6155163
Sum20608.582
Variance38297.093
MonotonicityNot monotonic
2023-12-11T01:15:03.109050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.63 1
 
1.1%
392.8346 1
 
1.1%
167.81 1
 
1.1%
164.19 1
 
1.1%
219.82 1
 
1.1%
219.74 1
 
1.1%
96.1 1
 
1.1%
33.64 1
 
1.1%
638.6446 1
 
1.1%
46.92 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
21.0 1
1.1%
22.17 1
1.1%
25.7989 1
1.1%
31.5567 1
1.1%
33.64 1
1.1%
34.32 1
1.1%
43.6903 1
1.1%
46.92 1
1.1%
53.7728 1
1.1%
54.9 1
1.1%
ValueCountFrequency (%)
1142.28 1
1.1%
975.6092 1
1.1%
916.58 1
1.1%
705.22 1
1.1%
638.6446 1
1.1%
571.6741 1
1.1%
497.85 1
1.1%
482.5612 1
1.1%
482.1771 1
1.1%
461.0593 1
1.1%

구조
Categorical

IMBALANCE 

Distinct8
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size884.0 B
철근콘크리트구조
78 
일반철골구조
경량철골구조
 
2
벽돌구조
 
1
블록구조
 
1
Other values (3)
 
3

Length

Max length10
Median length8
Mean length7.6702128
Min length4

Unique

Unique5 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 78
83.0%
일반철골구조 9
 
9.6%
경량철골구조 2
 
2.1%
벽돌구조 1
 
1.1%
블록구조 1
 
1.1%
철골콘크리트구조 1
 
1.1%
일반목구조 1
 
1.1%
철골철근콘크리트구조 1
 
1.1%

Length

2023-12-11T01:15:03.291066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:03.443917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 78
83.0%
일반철골구조 9
 
9.6%
경량철골구조 2
 
2.1%
벽돌구조 1
 
1.1%
블록구조 1
 
1.1%
철골콘크리트구조 1
 
1.1%
일반목구조 1
 
1.1%
철골철근콘크리트구조 1
 
1.1%
Distinct81
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2020-04-27 00:00:00
Maximum2022-12-15 00:00:00
2023-12-11T01:15:03.649010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:03.797143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct78
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2022-01-03 00:00:00
Maximum2022-12-22 00:00:00
2023-12-11T01:15:03.961495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:04.108024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct80
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2022-01-03 00:00:00
Maximum2022-12-22 00:00:00
2023-12-11T01:15:04.249397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:04.386759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct42
Distinct (%)93.3%
Missing49
Missing (%)52.1%
Memory size884.0 B
Minimum2022-01-12 00:00:00
Maximum2023-01-05 00:00:00
2023-12-11T01:15:04.532545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:04.662785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
Distinct83
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2019-08-12 00:00:00
Maximum2022-12-02 00:00:00
2023-12-11T01:15:04.815897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:04.960954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

Distinct16
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9787234
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:05.069347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile13.7
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.0267352
Coefficient of variation (CV)0.80878869
Kurtosis4.8783104
Mean4.9787234
Median Absolute Deviation (MAD)1
Skewness2.2036618
Sum468
Variance16.214596
MonotonicityNot monotonic
2023-12-11T01:15:05.183986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4 21
22.3%
3 17
18.1%
5 16
17.0%
2 15
16.0%
1 6
 
6.4%
12 3
 
3.2%
8 3
 
3.2%
6 3
 
3.2%
9 2
 
2.1%
19 2
 
2.1%
Other values (6) 6
 
6.4%
ValueCountFrequency (%)
1 6
 
6.4%
2 15
16.0%
3 17
18.1%
4 21
22.3%
5 16
17.0%
6 3
 
3.2%
7 1
 
1.1%
8 3
 
3.2%
9 2
 
2.1%
10 1
 
1.1%
ValueCountFrequency (%)
20 1
 
1.1%
19 2
2.1%
18 1
 
1.1%
15 1
 
1.1%
13 1
 
1.1%
12 3
3.2%
10 1
 
1.1%
9 2
2.1%
8 3
3.2%
7 1
 
1.1%
Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
0
52 
1
24 
<NA>
17 
2
 
1

Length

Max length4
Median length1
Mean length1.5425532
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 52
55.3%
1 24
25.5%
<NA> 17
 
18.1%
2 1
 
1.1%

Length

2023-12-11T01:15:05.315916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:05.467073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
55.3%
1 24
25.5%
na 17
 
18.1%
2 1
 
1.1%

최고높이(미터)
Real number (ℝ)

ZEROS 

Distinct86
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.076915
Minimum0
Maximum66
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:05.586929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.1375
Q110.1
median14.025
Q318.5625
95-th percentile47.729
Maximum66
Range66
Interquartile range (IQR)8.4625

Descriptive statistics

Standard deviation13.515329
Coefficient of variation (CV)0.74765682
Kurtosis3.6073184
Mean18.076915
Median Absolute Deviation (MAD)4.1
Skewness1.9340388
Sum1699.23
Variance182.66411
MonotonicityNot monotonic
2023-12-11T01:15:05.743075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 3
 
3.2%
12.6 2
 
2.1%
37.5 2
 
2.1%
10.3 2
 
2.1%
14.5 2
 
2.1%
10.1 2
 
2.1%
11.3 2
 
2.1%
5.2 1
 
1.1%
10.7 1
 
1.1%
16.5 1
 
1.1%
Other values (76) 76
80.9%
ValueCountFrequency (%)
0.0 1
 
1.1%
3.3 1
 
1.1%
4.0 1
 
1.1%
5.2 1
 
1.1%
5.65 1
 
1.1%
6.4 1
 
1.1%
6.7 1
 
1.1%
6.9 1
 
1.1%
7.0 1
 
1.1%
7.2 3
3.2%
ValueCountFrequency (%)
66.0 1
1.1%
63.3 1
1.1%
62.5 1
1.1%
58.5 1
1.1%
51.2 1
1.1%
45.86 1
1.1%
43.55 1
1.1%
38.9 1
1.1%
37.5 2
2.1%
36.6 1
1.1%

동수
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
1
85 
2
 
5
0
 
2
30
 
1
4
 
1

Length

Max length2
Median length1
Mean length1.0106383
Min length1

Unique

Unique2 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 85
90.4%
2 5
 
5.3%
0 2
 
2.1%
30 1
 
1.1%
4 1
 
1.1%

Length

2023-12-11T01:15:05.901160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:06.017773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 85
90.4%
2 5
 
5.3%
0 2
 
2.1%
30 1
 
1.1%
4 1
 
1.1%

주용도
Categorical

Distinct11
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size884.0 B
제2종근린생활시설
32 
제1종근린생활시설
22 
공동주택
18 
단독주택
업무시설
Other values (6)

Length

Max length9
Median length9
Mean length6.9680851
Min length4

Unique

Unique5 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
제2종근린생활시설 32
34.0%
제1종근린생활시설 22
23.4%
공동주택 18
19.1%
단독주택 7
 
7.4%
업무시설 7
 
7.4%
교육연구시설 3
 
3.2%
의료시설 1
 
1.1%
문화및집회시설 1
 
1.1%
종교시설 1
 
1.1%
창고시설 1
 
1.1%

Length

2023-12-11T01:15:06.128916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 32
34.0%
제1종근린생활시설 22
23.4%
공동주택 18
19.1%
단독주택 7
 
7.4%
업무시설 7
 
7.4%
교육연구시설 3
 
3.2%
의료시설 1
 
1.1%
문화및집회시설 1
 
1.1%
종교시설 1
 
1.1%
창고시설 1
 
1.1%

부속용도
Text

MISSING 

Distinct52
Distinct (%)62.7%
Missing11
Missing (%)11.7%
Memory size884.0 B
2023-12-11T01:15:06.307968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length24
Mean length8.626506
Min length2

Characters and Unicode

Total characters716
Distinct characters84
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

Unique40 ?
Unique (%)48.2%

Sample

1st row소매점
2nd row일반음식점
3rd row일반음식점
4th row다세대주택
5th row휴게음식점
ValueCountFrequency (%)
소매점 10
 
9.5%
사무소 9
 
8.6%
일반음식점 7
 
6.7%
휴게음식점 7
 
6.7%
다세대주택 7
 
6.7%
단독주택 6
 
5.7%
학원 4
 
3.8%
업무시설(오피스텔 3
 
2.9%
아파트 3
 
2.9%
의원 3
 
2.9%
Other values (37) 46
43.8%
2023-12-11T01:15:06.691843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 33
 
4.6%
32
 
4.5%
31
 
4.3%
31
 
4.3%
31
 
4.3%
29
 
4.1%
25
 
3.5%
22
 
3.1%
) 19
 
2.7%
( 19
 
2.7%
Other values (74) 444
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 606
84.6%
Other Punctuation 34
 
4.7%
Space Separator 22
 
3.1%
Close Punctuation 19
 
2.7%
Open Punctuation 19
 
2.7%
Decimal Number 10
 
1.4%
Dash Punctuation 6
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
32
 
5.3%
31
 
5.1%
31
 
5.1%
31
 
5.1%
29
 
4.8%
25
 
4.1%
19
 
3.1%
17
 
2.8%
17
 
2.8%
17
 
2.8%
Other values (66) 357
58.9%
Other Punctuation
ValueCountFrequency (%)
, 33
97.1%
/ 1
 
2.9%
Decimal Number
ValueCountFrequency (%)
2 6
60.0%
1 4
40.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 606
84.6%
Common 110
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
32
 
5.3%
31
 
5.1%
31
 
5.1%
31
 
5.1%
29
 
4.8%
25
 
4.1%
19
 
3.1%
17
 
2.8%
17
 
2.8%
17
 
2.8%
Other values (66) 357
58.9%
Common
ValueCountFrequency (%)
, 33
30.0%
22
20.0%
) 19
17.3%
( 19
17.3%
2 6
 
5.5%
- 6
 
5.5%
1 4
 
3.6%
/ 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 606
84.6%
ASCII 110
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 33
30.0%
22
20.0%
) 19
17.3%
( 19
17.3%
2 6
 
5.5%
- 6
 
5.5%
1 4
 
3.6%
/ 1
 
0.9%
Hangul
ValueCountFrequency (%)
32
 
5.3%
31
 
5.1%
31
 
5.1%
31
 
5.1%
29
 
4.8%
25
 
4.1%
19
 
3.1%
17
 
2.8%
17
 
2.8%
17
 
2.8%
Other values (66) 357
58.9%

용도지역
Categorical

Distinct7
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
제2종일반주거지역
45 
준주거지역
14 
일반상업지역
13 
제3종일반주거지역
12 
제1종일반주거지역
 
4
Other values (2)

Length

Max length13
Median length9
Mean length8.0957447
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제2종일반주거지역 45
47.9%
준주거지역 14
 
14.9%
일반상업지역 13
 
13.8%
제3종일반주거지역 12
 
12.8%
제1종일반주거지역 4
 
4.3%
가로구역별최고높이제한지역 4
 
4.3%
자연녹지지역 2
 
2.1%

Length

2023-12-11T01:15:07.104115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:07.230112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종일반주거지역 45
47.9%
준주거지역 14
 
14.9%
일반상업지역 13
 
13.8%
제3종일반주거지역 12
 
12.8%
제1종일반주거지역 4
 
4.3%
가로구역별최고높이제한지역 4
 
4.3%
자연녹지지역 2
 
2.1%

용도지구
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
<NA>
76 
방화지구
15 
철도보호지구
 
2
고도지구
 
1

Length

Max length6
Median length4
Mean length4.0425532
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 76
80.9%
방화지구 15
 
16.0%
철도보호지구 2
 
2.1%
고도지구 1
 
1.1%

Length

2023-12-11T01:15:07.362544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:07.462086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
80.9%
방화지구 15
 
16.0%
철도보호지구 2
 
2.1%
고도지구 1
 
1.1%

용도구역
Categorical

Distinct6
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
상대보호구역
50 
<NA>
34 
문화재보존영향 검토대상구역
 
4
제1종지구단위계획구역
 
2
용도구역기타
 
2

Length

Max length14
Median length6
Mean length5.7234043
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상대보호구역 50
53.2%
<NA> 34
36.2%
문화재보존영향 검토대상구역 4
 
4.3%
제1종지구단위계획구역 2
 
2.1%
용도구역기타 2
 
2.1%
절대정화구역 2
 
2.1%

Length

2023-12-11T01:15:07.601532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:07.766412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상대보호구역 50
51.0%
na 34
34.7%
문화재보존영향 4
 
4.1%
검토대상구역 4
 
4.1%
제1종지구단위계획구역 2
 
2.0%
용도구역기타 2
 
2.0%
절대정화구역 2
 
2.0%

총주차대수
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)31.0%
Missing10
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean11.880952
Minimum0
Maximum119
Zeros3
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:07.874796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4.5
Q310.25
95-th percentile38.95
Maximum119
Range119
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation20.166419
Coefficient of variation (CV)1.6973739
Kurtosis13.14191
Mean11.880952
Median Absolute Deviation (MAD)2.5
Skewness3.3788903
Sum998
Variance406.68445
MonotonicityNot monotonic
2023-12-11T01:15:07.987180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2 16
17.0%
4 11
11.7%
5 9
9.6%
1 8
8.5%
33 5
 
5.3%
6 5
 
5.3%
3 4
 
4.3%
7 3
 
3.2%
0 3
 
3.2%
18 2
 
2.1%
Other values (16) 18
19.1%
(Missing) 10
10.6%
ValueCountFrequency (%)
0 3
 
3.2%
1 8
8.5%
2 16
17.0%
3 4
 
4.3%
4 11
11.7%
5 9
9.6%
6 5
 
5.3%
7 3
 
3.2%
8 2
 
2.1%
9 1
 
1.1%
ValueCountFrequency (%)
119 1
 
1.1%
98 1
 
1.1%
71 1
 
1.1%
62 1
 
1.1%
40 1
 
1.1%
33 5
5.3%
31 1
 
1.1%
30 1
 
1.1%
28 1
 
1.1%
22 1
 
1.1%

세대수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)64.0%
Missing69
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean16.12
Minimum0
Maximum104
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:08.109173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median10
Q316
95-th percentile34
Maximum104
Range104
Interquartile range (IQR)8

Descriptive statistics

Standard deviation20.680748
Coefficient of variation (CV)1.2829248
Kurtosis14.189675
Mean16.12
Median Absolute Deviation (MAD)6
Skewness3.4399005
Sum403
Variance427.69333
MonotonicityNot monotonic
2023-12-11T01:15:08.220158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
8 4
 
4.3%
10 3
 
3.2%
16 3
 
3.2%
34 2
 
2.1%
1 2
 
2.1%
24 1
 
1.1%
2 1
 
1.1%
20 1
 
1.1%
12 1
 
1.1%
104 1
 
1.1%
Other values (6) 6
 
6.4%
(Missing) 69
73.4%
ValueCountFrequency (%)
0 1
 
1.1%
1 2
2.1%
2 1
 
1.1%
3 1
 
1.1%
4 1
 
1.1%
8 4
4.3%
10 3
3.2%
11 1
 
1.1%
12 1
 
1.1%
14 1
 
1.1%
ValueCountFrequency (%)
104 1
 
1.1%
34 2
2.1%
29 1
 
1.1%
24 1
 
1.1%
20 1
 
1.1%
16 3
3.2%
14 1
 
1.1%
12 1
 
1.1%
11 1
 
1.1%
10 3
3.2%

호수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)80.0%
Missing79
Missing (%)84.0%
Infinite0
Infinite (%)0.0%
Mean26.2
Minimum0
Maximum114
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-11T01:15:08.342653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.4
Q19
median12
Q333.5
95-th percentile72.7
Maximum114
Range114
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation29.7182
Coefficient of variation (CV)1.1342825
Kurtosis4.9552412
Mean26.2
Median Absolute Deviation (MAD)10
Skewness2.0603755
Sum393
Variance883.17143
MonotonicityNot monotonic
2023-12-11T01:15:08.455465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
12 3
 
3.2%
9 2
 
2.1%
0 1
 
1.1%
35 1
 
1.1%
28 1
 
1.1%
2 1
 
1.1%
17 1
 
1.1%
4 1
 
1.1%
55 1
 
1.1%
114 1
 
1.1%
Other values (2) 2
 
2.1%
(Missing) 79
84.0%
ValueCountFrequency (%)
0 1
 
1.1%
2 1
 
1.1%
4 1
 
1.1%
9 2
2.1%
12 3
3.2%
17 1
 
1.1%
28 1
 
1.1%
32 1
 
1.1%
35 1
 
1.1%
52 1
 
1.1%
ValueCountFrequency (%)
114 1
 
1.1%
55 1
 
1.1%
52 1
 
1.1%
35 1
 
1.1%
32 1
 
1.1%
28 1
 
1.1%
17 1
 
1.1%
12 3
3.2%
9 2
2.1%
4 1
 
1.1%

가구수
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size884.0 B
<NA>
82 
1
2
 
2
0
 
1

Length

Max length4
Median length4
Mean length3.6170213
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 82
87.2%
1 9
 
9.6%
2 2
 
2.1%
0 1
 
1.1%

Length

2023-12-11T01:15:08.592030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:08.700392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
87.2%
1 9
 
9.6%
2 2
 
2.1%
0 1
 
1.1%
Distinct80
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:15:08.900162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length10.904255
Min length7

Characters and Unicode

Total characters1025
Distinct characters126
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

Unique69 ?
Unique (%)73.4%

Sample

1st row건축사사무소 바림
2nd row가원엔지니어링건축사사무소
3rd row건축사사무소 가감승제
4th row진아트 건축사사무소
5th row에이텍건축사사무소
ValueCountFrequency (%)
건축사사무소 29
 
21.0%
종합건축사사무소 10
 
7.2%
주식회사 4
 
2.9%
주)에이앤티 3
 
2.2%
에이텍건축사사무소 3
 
2.2%
진아트 3
 
2.2%
선우건축사사무소 2
 
1.4%
미담 2
 
1.4%
주)해안건축사사무소 2
 
1.4%
네오종합건축사사무소 2
 
1.4%
Other values (74) 78
56.5%
2023-12-11T01:15:09.312912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
193
18.8%
101
 
9.9%
100
 
9.8%
96
 
9.4%
94
 
9.2%
45
 
4.4%
32
 
3.1%
( 25
 
2.4%
) 25
 
2.4%
21
 
2.0%
Other values (116) 293
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 899
87.7%
Space Separator 45
 
4.4%
Open Punctuation 25
 
2.4%
Close Punctuation 25
 
2.4%
Uppercase Letter 18
 
1.8%
Decimal Number 12
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
193
21.5%
101
11.2%
100
11.1%
96
10.7%
94
10.5%
32
 
3.6%
21
 
2.3%
21
 
2.3%
18
 
2.0%
11
 
1.2%
Other values (98) 212
23.6%
Uppercase Letter
ValueCountFrequency (%)
A 4
22.2%
C 3
16.7%
S 2
11.1%
P 2
11.1%
E 2
11.1%
T 2
11.1%
U 1
 
5.6%
N 1
 
5.6%
I 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 4
33.3%
4 1
 
8.3%
5 1
 
8.3%
8 1
 
8.3%
Space Separator
ValueCountFrequency (%)
45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 899
87.7%
Common 108
 
10.5%
Latin 18
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
193
21.5%
101
11.2%
100
11.1%
96
10.7%
94
10.5%
32
 
3.6%
21
 
2.3%
21
 
2.3%
18
 
2.0%
11
 
1.2%
Other values (98) 212
23.6%
Common
ValueCountFrequency (%)
45
41.7%
( 25
23.1%
) 25
23.1%
1 5
 
4.6%
2 4
 
3.7%
4 1
 
0.9%
5 1
 
0.9%
8 1
 
0.9%
& 1
 
0.9%
Latin
ValueCountFrequency (%)
A 4
22.2%
C 3
16.7%
S 2
11.1%
P 2
11.1%
E 2
11.1%
T 2
11.1%
U 1
 
5.6%
N 1
 
5.6%
I 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 899
87.7%
ASCII 126
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
193
21.5%
101
11.2%
100
11.1%
96
10.7%
94
10.5%
32
 
3.6%
21
 
2.3%
21
 
2.3%
18
 
2.0%
11
 
1.2%
Other values (98) 212
23.6%
ASCII
ValueCountFrequency (%)
45
35.7%
( 25
19.8%
) 25
19.8%
1 5
 
4.0%
2 4
 
3.2%
A 4
 
3.2%
C 3
 
2.4%
S 2
 
1.6%
P 2
 
1.6%
E 2
 
1.6%
Other values (8) 9
 
7.1%
Distinct84
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:15:09.613894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length30.776596
Min length16

Characters and Unicode

Total characters2893
Distinct characters173
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)78.7%

Sample

1st row부산광역시 수영구 남천동로 107, 4층
2nd row부산광역시 동래구 충렬대로237번길 104, 2층
3rd row부산광역시 남구 용소로46번길 4, 102호(대연동,아이노스오피스텔)
4th row부산광역시 수영구 연수로401번길 20, 704호 (수영동, 수영유건코아텔2차 )
5th row부산광역시 남구 수영로 312, 1140호,(대연동, 21 센츄리시티 오피스텔)
ValueCountFrequency (%)
부산광역시 86
 
16.1%
동래구 16
 
3.0%
연제구 12
 
2.3%
해운대구 12
 
2.3%
수영구 12
 
2.3%
부산진구 10
 
1.9%
2층 10
 
1.9%
3층 7
 
1.3%
충렬대로 7
 
1.3%
경상남도 7
 
1.3%
Other values (240) 354
66.4%
2023-12-11T01:15:10.051382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
 
15.3%
112
 
3.9%
1 111
 
3.8%
, 104
 
3.6%
104
 
3.6%
100
 
3.5%
93
 
3.2%
93
 
3.2%
2 92
 
3.2%
90
 
3.1%
Other values (163) 1552
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1703
58.9%
Decimal Number 532
 
18.4%
Space Separator 442
 
15.3%
Other Punctuation 104
 
3.6%
Open Punctuation 47
 
1.6%
Close Punctuation 46
 
1.6%
Dash Punctuation 13
 
0.4%
Lowercase Letter 3
 
0.1%
Uppercase Letter 2
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
112
 
6.6%
104
 
6.1%
100
 
5.9%
93
 
5.5%
93
 
5.5%
90
 
5.3%
88
 
5.2%
87
 
5.1%
52
 
3.1%
43
 
2.5%
Other values (144) 841
49.4%
Decimal Number
ValueCountFrequency (%)
1 111
20.9%
2 92
17.3%
0 74
13.9%
3 57
10.7%
4 46
8.6%
5 37
 
7.0%
6 34
 
6.4%
7 33
 
6.2%
9 26
 
4.9%
8 22
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
442
100.0%
Other Punctuation
ValueCountFrequency (%)
, 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1703
58.9%
Common 1185
41.0%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
112
 
6.6%
104
 
6.1%
100
 
5.9%
93
 
5.5%
93
 
5.5%
90
 
5.3%
88
 
5.2%
87
 
5.1%
52
 
3.1%
43
 
2.5%
Other values (144) 841
49.4%
Common
ValueCountFrequency (%)
442
37.3%
1 111
 
9.4%
, 104
 
8.8%
2 92
 
7.8%
0 74
 
6.2%
3 57
 
4.8%
( 47
 
4.0%
) 46
 
3.9%
4 46
 
3.9%
5 37
 
3.1%
Other values (6) 129
 
10.9%
Latin
ValueCountFrequency (%)
e 3
60.0%
A 1
 
20.0%
C 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1703
58.9%
ASCII 1190
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
37.1%
1 111
 
9.3%
, 104
 
8.7%
2 92
 
7.7%
0 74
 
6.2%
3 57
 
4.8%
( 47
 
3.9%
) 46
 
3.9%
4 46
 
3.9%
5 37
 
3.1%
Other values (9) 134
 
11.3%
Hangul
ValueCountFrequency (%)
112
 
6.6%
104
 
6.1%
100
 
5.9%
93
 
5.5%
93
 
5.5%
90
 
5.3%
88
 
5.2%
87
 
5.1%
52
 
3.1%
43
 
2.5%
Other values (144) 841
49.4%

감리사무소명
Text

MISSING 

Distinct86
Distinct (%)97.7%
Missing6
Missing (%)6.4%
Memory size884.0 B
2023-12-11T01:15:10.391614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.522727
Min length7

Characters and Unicode

Total characters926
Distinct characters133
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)95.5%

Sample

1st row건축사사무소 바림
2nd row고온건축사사무소
3rd row건축사사무소 가감승제
4th rowSL 건축사사무소
5th row동그라미건축사사무소
ValueCountFrequency (%)
건축사사무소 31
 
24.2%
종합건축사사무소 3
 
2.3%
유가건축사사무소 2
 
1.6%
어필 2
 
1.6%
가감승제 2
 
1.6%
주)종합건축사사무소 2
 
1.6%
성호건축사사무소 1
 
0.8%
누마루건축사사무소 1
 
0.8%
주식회사팀앤아키종합건축사사무소 1
 
0.8%
시안 1
 
0.8%
Other values (82) 82
64.1%
2023-12-11T01:15:10.864520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
19.2%
91
 
9.8%
90
 
9.7%
89
 
9.6%
88
 
9.5%
41
 
4.4%
24
 
2.6%
) 21
 
2.3%
( 21
 
2.3%
14
 
1.5%
Other values (123) 269
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 814
87.9%
Space Separator 41
 
4.4%
Close Punctuation 21
 
2.3%
Open Punctuation 21
 
2.3%
Uppercase Letter 18
 
1.9%
Decimal Number 6
 
0.6%
Other Punctuation 3
 
0.3%
Lowercase Letter 1
 
0.1%
Final Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
178
21.9%
91
11.2%
90
11.1%
89
10.9%
88
10.8%
24
 
2.9%
14
 
1.7%
14
 
1.7%
12
 
1.5%
10
 
1.2%
Other values (99) 204
25.1%
Uppercase Letter
ValueCountFrequency (%)
A 4
22.2%
N 3
16.7%
S 2
11.1%
U 2
11.1%
D 1
 
5.6%
I 1
 
5.6%
E 1
 
5.6%
K 1
 
5.6%
C 1
 
5.6%
L 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
5 1
16.7%
8 1
16.7%
2 1
16.7%
Other Punctuation
ValueCountFrequency (%)
# 1
33.3%
& 1
33.3%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 814
87.9%
Common 93
 
10.0%
Latin 19
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
178
21.9%
91
11.2%
90
11.1%
89
10.9%
88
10.8%
24
 
2.9%
14
 
1.7%
14
 
1.7%
12
 
1.5%
10
 
1.2%
Other values (99) 204
25.1%
Common
ValueCountFrequency (%)
41
44.1%
) 21
22.6%
( 21
22.6%
1 2
 
2.2%
# 1
 
1.1%
4 1
 
1.1%
5 1
 
1.1%
8 1
 
1.1%
& 1
 
1.1%
. 1
 
1.1%
Other values (2) 2
 
2.2%
Latin
ValueCountFrequency (%)
A 4
21.1%
N 3
15.8%
S 2
10.5%
U 2
10.5%
D 1
 
5.3%
I 1
 
5.3%
s 1
 
5.3%
E 1
 
5.3%
K 1
 
5.3%
C 1
 
5.3%
Other values (2) 2
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 814
87.9%
ASCII 111
 
12.0%
Punctuation 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
178
21.9%
91
11.2%
90
11.1%
89
10.9%
88
10.8%
24
 
2.9%
14
 
1.7%
14
 
1.7%
12
 
1.5%
10
 
1.2%
Other values (99) 204
25.1%
ASCII
ValueCountFrequency (%)
41
36.9%
) 21
18.9%
( 21
18.9%
A 4
 
3.6%
N 3
 
2.7%
1 2
 
1.8%
S 2
 
1.8%
U 2
 
1.8%
D 1
 
0.9%
# 1
 
0.9%
Other values (13) 13
 
11.7%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct87
Distinct (%)98.9%
Missing6
Missing (%)6.4%
Memory size884.0 B
2023-12-11T01:15:11.234404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length37
Mean length28.056818
Min length17

Characters and Unicode

Total characters2469
Distinct characters169
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)97.7%

Sample

1st row부산광역시 수영구 남천동로 107, 4층
2nd row부산광역시 동래구 우장춘로4번길 28, 1층
3rd row부산광역시 남구 용소로46번길 4, 102호(대연동,아이노스오피스텔)
4th row부산광역시 동래구 충렬대로237번길 90, 203호
5th row부산광역시 수영구 남천바다로10번길 69, 204호
ValueCountFrequency (%)
부산광역시 84
 
18.1%
연제구 12
 
2.6%
3층 11
 
2.4%
수영구 11
 
2.4%
동래구 10
 
2.2%
금정구 10
 
2.2%
2층 9
 
1.9%
해운대구 9
 
1.9%
부산진구 9
 
1.9%
강서구 6
 
1.3%
Other values (234) 294
63.2%
2023-12-11T01:15:11.708378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
 
15.4%
106
 
4.3%
99
 
4.0%
1 97
 
3.9%
90
 
3.6%
89
 
3.6%
89
 
3.6%
, 86
 
3.5%
86
 
3.5%
83
 
3.4%
Other values (159) 1265
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1429
57.9%
Decimal Number 497
 
20.1%
Space Separator 379
 
15.4%
Other Punctuation 87
 
3.5%
Open Punctuation 27
 
1.1%
Close Punctuation 27
 
1.1%
Dash Punctuation 21
 
0.9%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
106
 
7.4%
99
 
6.9%
90
 
6.3%
89
 
6.2%
89
 
6.2%
86
 
6.0%
83
 
5.8%
64
 
4.5%
46
 
3.2%
43
 
3.0%
Other values (141) 634
44.4%
Decimal Number
ValueCountFrequency (%)
1 97
19.5%
2 75
15.1%
3 61
12.3%
0 57
11.5%
6 42
8.5%
5 37
 
7.4%
7 36
 
7.2%
9 33
 
6.6%
4 31
 
6.2%
8 28
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 86
98.9%
. 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
g 1
50.0%
Space Separator
ValueCountFrequency (%)
379
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1429
57.9%
Common 1038
42.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
106
 
7.4%
99
 
6.9%
90
 
6.3%
89
 
6.2%
89
 
6.2%
86
 
6.0%
83
 
5.8%
64
 
4.5%
46
 
3.2%
43
 
3.0%
Other values (141) 634
44.4%
Common
ValueCountFrequency (%)
379
36.5%
1 97
 
9.3%
, 86
 
8.3%
2 75
 
7.2%
3 61
 
5.9%
0 57
 
5.5%
6 42
 
4.0%
5 37
 
3.6%
7 36
 
3.5%
9 33
 
3.2%
Other values (6) 135
 
13.0%
Latin
ValueCountFrequency (%)
h 1
50.0%
g 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1429
57.9%
ASCII 1040
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
36.4%
1 97
 
9.3%
, 86
 
8.3%
2 75
 
7.2%
3 61
 
5.9%
0 57
 
5.5%
6 42
 
4.0%
5 37
 
3.6%
7 36
 
3.5%
9 33
 
3.2%
Other values (8) 137
 
13.2%
Hangul
ValueCountFrequency (%)
106
 
7.4%
99
 
6.9%
90
 
6.3%
89
 
6.2%
89
 
6.2%
86
 
6.0%
83
 
5.8%
64
 
4.5%
46
 
3.2%
43
 
3.0%
Other values (141) 634
44.4%

시공자사무소명
Text

MISSING 

Distinct57
Distinct (%)85.1%
Missing27
Missing (%)28.7%
Memory size884.0 B
2023-12-11T01:15:11.961845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9.1044776
Min length5

Characters and Unicode

Total characters610
Distinct characters96
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

Unique48 ?
Unique (%)71.6%

Sample

1st row초우종합건설(주)
2nd row강한종합건설(주)
3rd row오송종합건설주식회사
4th row주식회사식스하우스
5th row석보건설(주)
ValueCountFrequency (%)
주식회사 5
 
6.9%
예린종합건설(주 3
 
4.2%
주)케이디개발 2
 
2.8%
동국종합건설(주 2
 
2.8%
주)케이탑종합건설 2
 
2.8%
주)태림이앤씨종합건설 2
 
2.8%
주)동인종합건설 2
 
2.8%
강한종합건설(주 2
 
2.8%
오송종합건설(주 2
 
2.8%
중아건설(주 2
 
2.8%
Other values (48) 48
66.7%
2023-12-11T01:15:12.426878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
67
 
11.0%
61
 
10.0%
( 59
 
9.7%
) 59
 
9.7%
58
 
9.5%
48
 
7.9%
47
 
7.7%
13
 
2.1%
9
 
1.5%
8
 
1.3%
Other values (86) 181
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
79.8%
Open Punctuation 59
 
9.7%
Close Punctuation 59
 
9.7%
Space Separator 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
67
13.8%
61
 
12.5%
58
 
11.9%
48
 
9.9%
47
 
9.7%
13
 
2.7%
9
 
1.8%
8
 
1.6%
8
 
1.6%
8
 
1.6%
Other values (83) 160
32.9%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
79.8%
Common 123
 
20.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
67
13.8%
61
 
12.5%
58
 
11.9%
48
 
9.9%
47
 
9.7%
13
 
2.7%
9
 
1.8%
8
 
1.6%
8
 
1.6%
8
 
1.6%
Other values (83) 160
32.9%
Common
ValueCountFrequency (%)
( 59
48.0%
) 59
48.0%
5
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
79.8%
ASCII 123
 
20.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
67
13.8%
61
 
12.5%
58
 
11.9%
48
 
9.9%
47
 
9.7%
13
 
2.7%
9
 
1.8%
8
 
1.6%
8
 
1.6%
8
 
1.6%
Other values (83) 160
32.9%
ASCII
ValueCountFrequency (%)
( 59
48.0%
) 59
48.0%
5
 
4.1%
Distinct90
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-11T01:15:12.756258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length39
Mean length30.010638
Min length16

Characters and Unicode

Total characters2821
Distinct characters192
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

Unique86 ?
Unique (%)91.5%

Sample

1st row부산광역시 동래구 금강공원로20번길 46, 503호
2nd row부산광역시 남구 진남로 201, 4층
3rd row부산광역시 수영구 망미로22번길 25
4th row부산광역시 해운대구 마린시티2로 47, 시동 2602호 (우동, 트럼프월드마린)
5th row부산광역시 해운대구 센텀1로 9, 에스동217호
ValueCountFrequency (%)
부산광역시 81
 
16.1%
동래구 23
 
4.6%
부산진구 11
 
2.2%
해운대구 10
 
2.0%
경상남도 9
 
1.8%
수영구 9
 
1.8%
4층 7
 
1.4%
금정구 7
 
1.4%
연제구 6
 
1.2%
2층 6
 
1.2%
Other values (255) 334
66.4%
2023-12-11T01:15:13.259996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
409
 
14.5%
1 120
 
4.3%
109
 
3.9%
106
 
3.8%
, 105
 
3.7%
102
 
3.6%
102
 
3.6%
91
 
3.2%
2 90
 
3.2%
87
 
3.1%
Other values (182) 1500
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1641
58.2%
Decimal Number 555
 
19.7%
Space Separator 409
 
14.5%
Other Punctuation 105
 
3.7%
Close Punctuation 47
 
1.7%
Open Punctuation 46
 
1.6%
Dash Punctuation 18
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
109
 
6.6%
106
 
6.5%
102
 
6.2%
102
 
6.2%
91
 
5.5%
87
 
5.3%
82
 
5.0%
82
 
5.0%
45
 
2.7%
43
 
2.6%
Other values (167) 792
48.3%
Decimal Number
ValueCountFrequency (%)
1 120
21.6%
2 90
16.2%
0 82
14.8%
4 60
10.8%
3 52
9.4%
7 41
 
7.4%
6 37
 
6.7%
8 31
 
5.6%
5 21
 
3.8%
9 21
 
3.8%
Space Separator
ValueCountFrequency (%)
409
100.0%
Other Punctuation
ValueCountFrequency (%)
, 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1641
58.2%
Common 1180
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
109
 
6.6%
106
 
6.5%
102
 
6.2%
102
 
6.2%
91
 
5.5%
87
 
5.3%
82
 
5.0%
82
 
5.0%
45
 
2.7%
43
 
2.6%
Other values (167) 792
48.3%
Common
ValueCountFrequency (%)
409
34.7%
1 120
 
10.2%
, 105
 
8.9%
2 90
 
7.6%
0 82
 
6.9%
4 60
 
5.1%
3 52
 
4.4%
) 47
 
4.0%
( 46
 
3.9%
7 41
 
3.5%
Other values (5) 128
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1641
58.2%
ASCII 1180
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
409
34.7%
1 120
 
10.2%
, 105
 
8.9%
2 90
 
7.6%
0 82
 
6.9%
4 60
 
5.1%
3 52
 
4.4%
) 47
 
4.0%
( 46
 
3.9%
7 41
 
3.5%
Other values (5) 128
 
10.8%
Hangul
ValueCountFrequency (%)
109
 
6.6%
106
 
6.5%
102
 
6.2%
102
 
6.2%
91
 
5.5%
87
 
5.3%
82
 
5.0%
82
 
5.0%
45
 
2.7%
43
 
2.6%
Other values (167) 792
48.3%

Sample

건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명설계자 도로명주소감리사무소명감리자 도로명주소시공자사무소명시공자 도로명주소
0대수선2022-건축과-대수선허가-9부산광역시 동래구 온천동 1426-15 외3필지552.8338.9998.5<NA>61.31180.63일반철골구조2022-12-152022-12-222022-12-222023-01-052022-12-023<NA>12.61제1종근린생활시설<NA>일반상업지역방화지구<NA>7<NA><NA><NA>건축사사무소 바림부산광역시 수영구 남천동로 107, 4층건축사사무소 바림부산광역시 수영구 남천동로 107, 4층<NA>부산광역시 동래구 금강공원로20번길 46, 503호
1신축2022-건축과-신축허가-82부산광역시 동래구 명륜동 696-67127.775.66279.36<NA>59.25218.76철근콘크리트구조2022-11-252022-12-132022-12-05<NA>2022-11-144015.751제1종근린생활시설소매점제2종일반주거지역<NA><NA>2<NA><NA><NA>가원엔지니어링건축사사무소부산광역시 동래구 충렬대로237번길 104, 2층고온건축사사무소부산광역시 동래구 우장춘로4번길 28, 1층초우종합건설(주)부산광역시 남구 진남로 201, 4층
2대수선2022-건축과-대수선허가-7부산광역시 동래구 안락동 465-26152.390.88421.9<NA>59.6717215.1149철근콘크리트구조2022-11-172022-11-282022-11-24<NA>2022-11-07410.01제2종근린생활시설일반음식점제2종일반주거지역<NA>상대보호구역0000건축사사무소 가감승제부산광역시 남구 용소로46번길 4, 102호(대연동,아이노스오피스텔)건축사사무소 가감승제부산광역시 남구 용소로46번길 4, 102호(대연동,아이노스오피스텔)강한종합건설(주)부산광역시 수영구 망미로22번길 25
3신축2022-건축과-신축허가-81부산광역시 동래구 안락동 221-9170.094.75158.68<NA>55.735393.3412철근콘크리트구조2022-11-152022-12-202022-12-19<NA>2022-10-25207.81제2종근린생활시설일반음식점제2종일반주거지역<NA>상대보호구역1<NA><NA><NA>진아트 건축사사무소부산광역시 수영구 연수로401번길 20, 704호 (수영동, 수영유건코아텔2차 )SL 건축사사무소부산광역시 동래구 충렬대로237번길 90, 203호<NA>부산광역시 해운대구 마린시티2로 47, 시동 2602호 (우동, 트럼프월드마린)
4신축2022-건축과-신축허가-76부산광역시 동래구 사직동 75-35 외1필지311.8184.24659.4<NA>59.09211.48철근콘크리트구조2022-10-192022-10-312022-10-28<NA>2022-10-055015.91공동주택다세대주택제2종일반주거지역<NA><NA>88<NA><NA>에이텍건축사사무소부산광역시 남구 수영로 312, 1140호,(대연동, 21 센츄리시티 오피스텔)동그라미건축사사무소부산광역시 수영구 남천바다로10번길 69, 204호오송종합건설주식회사부산광역시 해운대구 센텀1로 9, 에스동217호
5신축2022-건축과-신축허가-75부산광역시 동래구 명륜동 676-25126.074.78277.14<NA>59.35219.95철근콘크리트구조2022-10-172022-11-112022-11-10<NA>2022-09-265017.11제1종근린생활시설휴게음식점제2종일반주거지역<NA>제1종지구단위계획구역2<NA><NA><NA>(주)건축사사무소 넓은들부산광역시 수영구 광남로 121, 골드코스트 8층 (광안동)이에이치건축사사무소부산광역시 부산진구 동성로96번길 53-2, 1층(전포동)주식회사식스하우스부산광역시 수영구 광남로130번길 4 (광안동)
6증축2022-건축과-증축허가-18부산광역시 동래구 사직동 829-2379.0119.6235.35112.7531.556762.0976철근콘크리트구조2022-10-122022-11-152022-11-14<NA>2022-10-042<NA>7.01제2종근린생활시설사무소, 단독주택제2종일반주거지역<NA><NA>2<NA><NA>1진아트 건축사사무소부산광역시 수영구 연수로401번길 20, 수영동, 수영유건코아텔2차 704호주식회사 가원건축사사무소부산광역시 동구 고관로 99, 2층(수정동)<NA>부산광역시 동래구 종합운동장로40번길 8, 104동 402호 (사직동, 부산아시아드코오롱하늘채아파트)
7증축2022-건축과-증축허가-17부산광역시 동래구 온천동 1123-3300.0173.29532.5538.1557.76145.77철근콘크리트구조2022-10-052022-10-252022-10-172022-11-232022-09-274116.21제2종근린생활시설사무소제1종일반주거지역<NA><NA>4<NA><NA><NA>화우 건축사사무소부산광역시 수영구 남천동로108번길 9, 4층화우 건축사사무소부산광역시 수영구 남천동로108번길 9, 4층<NA>부산광역시 동래구 금정마을로 107
8증축2022-건축과-증축허가-16부산광역시 동래구 온천동 198-11 외1필지975.68672.137042.14332.2468.8884571.6741철근콘크리트구조2022-09-272022-10-072022-10-12<NA>2022-08-179229.91의료시설근린생활시설,노유자시설일반상업지역방화지구<NA><NA><NA><NA><NA>건축사사무소참경상남도 창원시 진해구 중원동로 49, 5층건축사사무소참경상남도 창원시 진해구 중원동로 49, 5층석보건설(주)경상남도 김해시 전하로 117-1
9신축2022-건축과-신축허가-71부산광역시 동래구 온천동 1579-5104.059.06222.68<NA>56.79183.83철근콘크리트구조2022-09-262022-10-252022-10-19<NA>2022-08-305014.21공동주택다세대주택제2종일반주거지역<NA>상대보호구역48<NA><NA>집터건축사사무소부산광역시 사상구 학감대로 230-10, 협성빌딩401호(감전동)건축사사무소 수공부산광역시 강서구 대저로 289-1, (대저동) 2층광덕에이스종합건설(주)부산광역시 금정구 중앙대로 2066, 6층(남산동, 우청빌딩)
건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(미터)동수주용도부속용도용도지역용도지구용도구역총주차대수세대수호수가구수설계사무소명설계자 도로명주소감리사무소명감리자 도로명주소시공자사무소명시공자 도로명주소
84신축2021-건축과-신축허가-76부산광역시 동래구 온천동 1250-16 외3필지620.9495.855996.28<NA>79.86916.58철근콘크리트구조2021-09-142022-03-082022-03-02<NA>2021-08-2718158.51공동주택아파트일반상업지역방화지구상대보호구역713452<NA>대로 건축사사무소부산광역시 부산진구 개금온정로 9, 석천오피스텔 1005호(개금동)(주)희건축사사무소부산광역시 부산진구 신천대로71번길 49, 2층(주)지음종합건설부산광역시 수영구 광서로30번길 29, 201호(광안동, 지음)
85신축2021-건축과-신축허가-70부산광역시 동래구 온천동 1249-3549.1420.595739.67<NA>76.5962975.6092철근콘크리트구조2021-07-262022-03-152022-02-08<NA>2021-07-1219166.01업무시설업무시설(오피스텔) 및 공동주택(아파트)일반상업지역방화지구<NA><NA>2932<NA>주식회사 이주 건축사사무소부산광역시 부산진구 서면문화로 27, 1602(부전동, 유원골든타워오피스텔)(주)에이엔종합건축사사무소부산광역시 금정구 중앙대로 1883원영종합건설 주식회사부산광역시 해운대구 센텀서로 30, 1803호(우동,케이엔엔타워)
86신축2021-건축과-신축허가-69부산광역시 동래구 명륜동 185 외1필지713.0412.2383.4<NA>57.812153.7728경량철골구조2021-07-232022-02-252022-02-25<NA>2021-06-24106.71제1종근린생활시설소매점제2종일반주거지역<NA>제1종지구단위계획구역3<NA><NA><NA>건축사사무소SPACE21부산광역시 연제구 월드컵대로111번길 6-8<NA><NA><NA>부산광역시 남구 용호로 164
87신축2021-건축과-신축허가-68부산광역시 동래구 온천동 353-1670.0309.641887.33<NA>46.21219.87철근콘크리트구조2021-07-192022-01-182022-01-152022-09-262021-06-226118.151공동주택도시형생활주택, 오피스텔제2종일반주거지역<NA>상대보호구역18812<NA>제이에스건축사사무소부산광역시 해운대구 해운대로61번가길 6, 상가동 111에이디프로건축사사무소부산광역시 해운대구 달맞이길117번나길 163, 101호강한종합건설(주)부산광역시 수영구 망미로22번길 25, , 2층 (망미동)
88신축2021-건축과-신축허가-46부산광역시 동래구 수안동 4-14 외2필지444.9238.83350.28<NA>53.67705.22철근콘크리트구조2021-05-202022-02-042022-01-27<NA>2021-04-0619162.51공동주택업무시설,제2종근린생활시설일반상업지역방화지구상대보호구역333412<NA>건축사사무소 화승부산광역시 해운대구 좌동순환로 5, 해운대이안103-2203A.N종합건축사사무소부산광역시 금정구 중앙대로 1883, 현대빌딩 4층(주)미도종합건설부산광역시 연제구 토곡로 46, 연산동
89신축2021-건축과-신축허가-44부산광역시 동래구 명륜동 49-1370.0198.94734.27<NA>53.77198.45철근콘크리트구조2021-05-172022-06-272022-06-27<NA>2021-05-074018.71제1종근린생활시설(소매점,의원,사무소)제2종일반주거지역<NA>상대보호구역5<NA><NA><NA>고딕 종합건축사사무소부산광역시 부산진구 동평로 350, 510호(양정동,양정현대프라자)바론건축사사무소부산광역시 부산진구 동평로 350 (양정동)(주)익수종합건설부산광역시 기장군 장안읍 해맞이로 430
90신축2021-건축과-신축허가-18부산광역시 동래구 온천동 300-51522.0471.2654057.5595<NA>30.96199.53철근콘크리트구조2021-03-152022-05-302022-06-01<NA>2021-02-2613145.861공동주택아파트, 업무시설(오피스텔), 근린생활시설제2종일반주거지역<NA><NA>40119<NA>(주)무이건축사사무소부산광역시 해운대구 해운대로394번길 23, 302호(우동)(주)루원건축사사무소부산광역시 해운대구 달맞이길117번라길 107, 2층(중동)(주)동오산업개발부산광역시 해운대구 좌동로 88, 507호(좌동, 울트라타워)
91증축2020-건축과-증축허가-16부산광역시 동래구 안락동 423-2262.1183.04366.08169.3269.84139.67경량철골구조2020-11-202022-05-112022-05-132022-07-202020-10-282<NA>7.21제2종근린생활시설외1일반상업지역고도지구<NA>2<NA><NA><NA>케이 건축사사무소부산광역시 금정구 중앙대로1793번길 42케이 건축사사무소부산광역시 금정구 중앙대로1793번길 42, 3층<NA>부산광역시 금정구 식물원로 47
92증축2020-건축과-공용건축물-4부산광역시 동래구 수안동 666-10 외1필지잡종지2187.0757.422946.262605.2634.6328134.717철골철근콘크리트구조2020-08-272022-05-102022-01-03<NA>2020-03-206<NA>28.61교육연구시설연구소제3종일반주거지역<NA>상대보호구역19<NA><NA><NA>(주)부산건축종합건축사사무소부산광역시 해운대구 센텀동로 99, 센텀 벽산e-클래스원 714호건축사사무소 주부산광역시 동구 중앙대로 357(주)신태원종합건설부산광역시 사상구 가야대로 81
93신축2020-건축과-신축허가-39부산광역시 동래구 온천동 1659-1452.089.6197.48<NA>19.82343.6903철근콘크리트구조2020-04-272022-01-042022-01-24<NA>2019-08-123012.11제2종근린생활시설일반음식점, 휴게음식점자연녹지지역<NA>상대보호구역2<NA><NA><NA>주식회사아키프로건축사사무소부산광역시 금정구 금단로 160, 101호건축사사무소유원부산광역시 남구 석포로126번길 5 (대연동. 2층)<NA>경상남도 김해시 김해대로 1784-14, 102동 306호(삼계동 동신아파트)