Overview

Dataset statistics

Number of variables36
Number of observations340
Missing cells2768
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory101.1 KiB
Average record size in memory304.4 B

Variable types

Categorical9
Text4
Numeric14
Unsupported1
DateTime8

Dataset

Description경상남도 사천시 관내 건축허가 현황자료(2015년 , 2023년)입니다. (건축구분, 대지위치 , 대지면적, 건축면적, 연면적 등)
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15053245

Alerts

건축구분 is highly imbalanced (54.1%)Imbalance
취소구분 is highly imbalanced (90.1%)Imbalance
용도지구 is highly imbalanced (72.4%)Imbalance
증축연면적(제곱미터) has 285 (83.8%) missing valuesMissing
철거멸실구분 has 340 (100.0%) missing valuesMissing
허가취소일 has 333 (97.9%) missing valuesMissing
최종설계변경일 has 241 (70.9%) missing valuesMissing
착공처리일 has 53 (15.6%) missing valuesMissing
착공예정일 has 53 (15.6%) missing valuesMissing
실제착공일 has 114 (33.5%) missing valuesMissing
사용승인일 has 108 (31.8%) missing valuesMissing
부속용도 has 95 (27.9%) missing valuesMissing
세대수 has 315 (92.6%) missing valuesMissing
호수 has 330 (97.1%) missing valuesMissing
가구수 has 178 (52.4%) missing valuesMissing
주건축물수 has 21 (6.2%) missing valuesMissing
부속건축물수 has 300 (88.2%) missing valuesMissing
허가번호 has unique valuesUnique
철거멸실구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
동수 has 21 (6.2%) zerosZeros

Reproduction

Analysis started2023-12-10 23:04:07.221053
Analysis finished2023-12-10 23:04:07.976063
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
신축
259 
증축
55 
용도변경
 
22
가설건축물축조허가
 
3
대수선
 
1

Length

Max length9
Median length2
Mean length2.1941176
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
신축 259
76.2%
증축 55
 
16.2%
용도변경 22
 
6.5%
가설건축물축조허가 3
 
0.9%
대수선 1
 
0.3%

Length

2023-12-11T08:04:08.070062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:08.213056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 259
76.2%
증축 55
 
16.2%
용도변경 22
 
6.5%
가설건축물축조허가 3
 
0.9%
대수선 1
 
0.3%

허가번호
Text

UNIQUE 

Distinct340
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T08:04:08.439827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length18.332353
Min length15

Characters and Unicode

Total characters6233
Distinct characters34
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

Unique340 ?
Unique (%)100.0%

Sample

1st row2015-민원봉사과-신축허가-233
2nd row2015-민원봉사과-신축허가-234
3rd row2015-민원봉사과-협의건축물-11
4th row2015-건축과-신축허가-21
5th row2015-민원봉사과-신축허가-232
ValueCountFrequency (%)
2015-민원봉사과-신축허가-233 1
 
0.3%
2015-민원봉사과-신축허가-90 1
 
0.3%
2015-민원봉사과-신축허가-79 1
 
0.3%
2015-민원봉사과-신축허가-78 1
 
0.3%
2015-민원봉사과-증축허가-16 1
 
0.3%
2015-민원봉사과-신축허가-80 1
 
0.3%
2015-민원봉사과-신축허가-81 1
 
0.3%
2015-민원봉사과-용도변경허가-6 1
 
0.3%
2015-민원봉사과-신축허가-82 1
 
0.3%
2015-민원봉사과-신축허가-83 1
 
0.3%
Other values (330) 330
97.1%
2023-12-11T08:04:08.857805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1020
16.4%
1 542
 
8.7%
2 455
 
7.3%
0 393
 
6.3%
5 391
 
6.3%
축 342
 
5.5%
과 340
 
5.5%
가 337
 
5.4%
허 334
 
5.4%
사 319
 
5.1%
Other values (24) 1760
28.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3082
49.4%
Decimal Number 2131
34.2%
Dash Punctuation 1020
 
16.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 342
11.1%
과 340
11.0%
가 337
10.9%
허 334
10.8%
사 319
10.4%
봉 319
10.4%
민 319
10.4%
원 319
10.4%
신 258
8.4%
증 51
 
1.7%
Other values (13) 144
4.7%
Decimal Number
ValueCountFrequency (%)
1 542
25.4%
2 455
21.4%
0 393
18.4%
5 391
18.3%
3 71
 
3.3%
4 64
 
3.0%
6 58
 
2.7%
7 53
 
2.5%
8 52
 
2.4%
9 52
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1020
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3151
50.6%
Hangul 3082
49.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 342
11.1%
과 340
11.0%
가 337
10.9%
허 334
10.8%
사 319
10.4%
봉 319
10.4%
민 319
10.4%
원 319
10.4%
신 258
8.4%
증 51
 
1.7%
Other values (13) 144
4.7%
Common
ValueCountFrequency (%)
- 1020
32.4%
1 542
17.2%
2 455
14.4%
0 393
 
12.5%
5 391
 
12.4%
3 71
 
2.3%
4 64
 
2.0%
6 58
 
1.8%
7 53
 
1.7%
8 52
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3151
50.6%
Hangul 3082
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1020
32.4%
1 542
17.2%
2 455
14.4%
0 393
 
12.5%
5 391
 
12.4%
3 71
 
2.3%
4 64
 
2.0%
6 58
 
1.8%
7 53
 
1.7%
8 52
 
1.7%
Hangul
ValueCountFrequency (%)
축 342
11.1%
과 340
11.0%
가 337
10.9%
허 334
10.8%
사 319
10.4%
봉 319
10.4%
민 319
10.4%
원 319
10.4%
신 258
8.4%
증 51
 
1.7%
Other values (13) 144
4.7%

건축주명
Text

Distinct312
Distinct (%)92.3%
Missing2
Missing (%)0.6%
Memory size2.8 KiB
2023-12-11T08:04:09.060960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length3
Mean length4.6213018
Min length3

Characters and Unicode

Total characters1562
Distinct characters226
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

Unique286 ?
Unique (%)84.6%

Sample

1st row강철원 외 1
2nd row심점화
3rd row사천시
4th row(주)우용주택건설
5th row주식회사다인
ValueCountFrequency (%)
외 49
 
11.2%
1 44
 
10.1%
3 3
 
0.7%
정은미 2
 
0.5%
이영구 2
 
0.5%
강경희 2
 
0.5%
2 2
 
0.5%
이경자 2
 
0.5%
문순금 2
 
0.5%
심가령 2
 
0.5%
Other values (306) 326
74.8%
2023-12-11T08:04:09.414732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
 
6.3%
주 60
 
3.8%
김 53
 
3.4%
이 51
 
3.3%
외 51
 
3.3%
1 45
 
2.9%
정 36
 
2.3%
사 34
 
2.2%
영 31
 
2.0%
강 26
 
1.7%
Other values (216) 1077
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1364
87.3%
Space Separator 98
 
6.3%
Decimal Number 50
 
3.2%
Close Punctuation 22
 
1.4%
Open Punctuation 22
 
1.4%
Other Punctuation 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 60
 
4.4%
김 53
 
3.9%
이 51
 
3.7%
외 51
 
3.7%
정 36
 
2.6%
사 34
 
2.5%
영 31
 
2.3%
강 26
 
1.9%
회 26
 
1.9%
식 25
 
1.8%
Other values (205) 971
71.2%
Decimal Number
ValueCountFrequency (%)
1 45
90.0%
3 3
 
6.0%
2 2
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
T 1
33.3%
J 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1364
87.3%
Common 195
 
12.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 60
 
4.4%
김 53
 
3.9%
이 51
 
3.7%
외 51
 
3.7%
정 36
 
2.6%
사 34
 
2.5%
영 31
 
2.3%
강 26
 
1.9%
회 26
 
1.9%
식 25
 
1.8%
Other values (205) 971
71.2%
Common
ValueCountFrequency (%)
98
50.3%
1 45
23.1%
) 22
 
11.3%
( 22
 
11.3%
3 3
 
1.5%
2 2
 
1.0%
. 2
 
1.0%
: 1
 
0.5%
Latin
ValueCountFrequency (%)
C 1
33.3%
T 1
33.3%
J 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1364
87.3%
ASCII 198
 
12.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
49.5%
1 45
22.7%
) 22
 
11.1%
( 22
 
11.1%
3 3
 
1.5%
2 2
 
1.0%
. 2
 
1.0%
: 1
 
0.5%
C 1
 
0.5%
T 1
 
0.5%
Hangul
ValueCountFrequency (%)
주 60
 
4.4%
김 53
 
3.9%
이 51
 
3.7%
외 51
 
3.7%
정 36
 
2.6%
사 34
 
2.5%
영 31
 
2.3%
강 26
 
1.9%
회 26
 
1.9%
식 25
 
1.8%
Other values (205) 971
71.2%

대지위치
Text

Distinct328
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-11T08:04:09.644449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length21.314706
Min length14

Characters and Unicode

Total characters7247
Distinct characters105
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

Unique316 ?
Unique (%)92.9%

Sample

1st row경상남도 사천시 향촌동 336-6 외1필지
2nd row경상남도 사천시 사천읍 선인리 215-37
3rd row경상남도 사천시 사등동 114-1 외5필지
4th row경상남도 사천시 향촌동 977-17
5th row경상남도 사천시 사남면 월성리 산 2-11 외1필지
ValueCountFrequency (%)
경상남도 340
20.4%
사천시 340
20.4%
사천읍 88
 
5.3%
사남면 60
 
3.6%
외1필지 58
 
3.5%
벌리동 33
 
2.0%
향촌동 28
 
1.7%
월성리 24
 
1.4%
선인리 23
 
1.4%
사주리 21
 
1.3%
Other values (404) 651
39.1%
2023-12-11T08:04:10.023215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1326
18.3%
사 512
 
7.1%
천 447
 
6.2%
남 406
 
5.6%
경 340
 
4.7%
도 340
 
4.7%
시 340
 
4.7%
상 340
 
4.7%
1 299
 
4.1%
- 263
 
3.6%
Other values (95) 2634
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4288
59.2%
Decimal Number 1370
 
18.9%
Space Separator 1326
 
18.3%
Dash Punctuation 263
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 512
11.9%
천 447
10.4%
남 406
 
9.5%
경 340
 
7.9%
도 340
 
7.9%
시 340
 
7.9%
상 340
 
7.9%
리 244
 
5.7%
동 164
 
3.8%
면 123
 
2.9%
Other values (83) 1032
24.1%
Decimal Number
ValueCountFrequency (%)
1 299
21.8%
2 178
13.0%
3 149
10.9%
4 139
10.1%
5 127
9.3%
6 116
 
8.5%
0 103
 
7.5%
7 96
 
7.0%
8 86
 
6.3%
9 77
 
5.6%
Space Separator
ValueCountFrequency (%)
1326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 263
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4288
59.2%
Common 2959
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 512
11.9%
천 447
10.4%
남 406
 
9.5%
경 340
 
7.9%
도 340
 
7.9%
시 340
 
7.9%
상 340
 
7.9%
리 244
 
5.7%
동 164
 
3.8%
면 123
 
2.9%
Other values (83) 1032
24.1%
Common
ValueCountFrequency (%)
1326
44.8%
1 299
 
10.1%
- 263
 
8.9%
2 178
 
6.0%
3 149
 
5.0%
4 139
 
4.7%
5 127
 
4.3%
6 116
 
3.9%
0 103
 
3.5%
7 96
 
3.2%
Other values (2) 163
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4288
59.2%
ASCII 2959
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1326
44.8%
1 299
 
10.1%
- 263
 
8.9%
2 178
 
6.0%
3 149
 
5.0%
4 139
 
4.7%
5 127
 
4.3%
6 116
 
3.9%
0 103
 
3.5%
7 96
 
3.2%
Other values (2) 163
 
5.5%
Hangul
ValueCountFrequency (%)
사 512
11.9%
천 447
10.4%
남 406
 
9.5%
경 340
 
7.9%
도 340
 
7.9%
시 340
 
7.9%
상 340
 
7.9%
리 244
 
5.7%
동 164
 
3.8%
면 123
 
2.9%
Other values (83) 1032
24.1%

지목
Categorical

Distinct11
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
대
170 
답
71 
전
38 
공장용지
29 
임야
 
16
Other values (6)
 
16

Length

Max length5
Median length1
Mean length1.4147059
Min length1

Unique

Unique4 ?
Unique (%)1.2%

Sample

1st row전
2nd row대
3rd row잡종지
4th row대
5th row임야

Common Values

ValueCountFrequency (%)
대 170
50.0%
답 71
20.9%
전 38
 
11.2%
공장용지 29
 
8.5%
임야 16
 
4.7%
잡종지 9
 
2.6%
창고용지 3
 
0.9%
주유소용지 1
 
0.3%
공원 1
 
0.3%
목장용지 1
 
0.3%

Length

2023-12-11T08:04:10.424598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 170
50.0%
답 71
20.9%
전 38
 
11.2%
공장용지 29
 
8.5%
임야 16
 
4.7%
잡종지 9
 
2.6%
창고용지 3
 
0.9%
주유소용지 1
 
0.3%
공원 1
 
0.3%
목장용지 1
 
0.3%

대지면적(제곱미터)
Real number (ℝ)

Distinct303
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3412.8968
Minimum50
Maximum171649.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:10.563451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile198.475
Q1330
median532.5
Q31274
95-th percentile10056.26
Maximum171649.2
Range171599.2
Interquartile range (IQR)944

Descriptive statistics

Standard deviation14823.486
Coefficient of variation (CV)4.3433737
Kurtosis80.230261
Mean3412.8968
Median Absolute Deviation (MAD)281
Skewness8.5241299
Sum1160384.9
Variance2.1973574 × 108
MonotonicityNot monotonic
2023-12-11T08:04:10.741436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
315.0 3
 
0.9%
331.0 3
 
0.9%
500.0 2
 
0.6%
573.0 2
 
0.6%
1138.0 2
 
0.6%
258.0 2
 
0.6%
358.0 2
 
0.6%
336.0 2
 
0.6%
513.0 2
 
0.6%
330.6 2
 
0.6%
Other values (293) 318
93.5%
ValueCountFrequency (%)
50.0 1
0.3%
98.0 1
0.3%
119.0 2
0.6%
153.3 1
0.3%
153.6 1
0.3%
157.5 1
0.3%
162.0 1
0.3%
165.4 1
0.3%
166.4 1
0.3%
167.0 2
0.6%
ValueCountFrequency (%)
171649.2 1
0.3%
141414.9 1
0.3%
106047.6 1
0.3%
84567.0 1
0.3%
69432.0 1
0.3%
33259.1 1
0.3%
30750.7 1
0.3%
24650.0 1
0.3%
18663.7 1
0.3%
18169.0 1
0.3%

건축면적(제곱미터)
Real number (ℝ)

Distinct329
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1031.6468
Minimum18
Maximum67268.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:10.860263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile94.9155
Q1160.6625
median224.295
Q3446.63
95-th percentile3397.314
Maximum67268.3
Range67250.3
Interquartile range (IQR)285.9675

Descriptive statistics

Standard deviation4423.4864
Coefficient of variation (CV)4.2877915
Kurtosis156.65284
Mean1031.6468
Median Absolute Deviation (MAD)91.055
Skewness11.435082
Sum350759.91
Variance19567232
MonotonicityNot monotonic
2023-12-11T08:04:10.991692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000.0 3
 
0.9%
198.0 3
 
0.9%
226.56 2
 
0.6%
95.08 2
 
0.6%
229.73 2
 
0.6%
175.01 2
 
0.6%
236.17 2
 
0.6%
1136.11 2
 
0.6%
237.7 2
 
0.6%
199.66 1
 
0.3%
Other values (319) 319
93.8%
ValueCountFrequency (%)
18.0 1
0.3%
35.42 1
0.3%
39.98 1
0.3%
55.18 1
0.3%
60.9 1
0.3%
65.48 1
0.3%
71.6 1
0.3%
72.36 1
0.3%
81.94 1
0.3%
85.94 1
0.3%
ValueCountFrequency (%)
67268.3 1
0.3%
32083.55 1
0.3%
18847.88 1
0.3%
14515.55 1
0.3%
13942.64 1
0.3%
10421.89 1
0.3%
9990.635 1
0.3%
8389.92 1
0.3%
8157.95 1
0.3%
6036.541 1
0.3%

연면적(제곱미터)
Real number (ℝ)

Distinct328
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1486.4881
Minimum18
Maximum66253.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:11.111578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile134.3505
Q1296.13438
median494.585
Q3861.8075
95-th percentile4583.018
Maximum66253.15
Range66235.15
Interquartile range (IQR)565.67313

Descriptive statistics

Standard deviation4625.5918
Coefficient of variation (CV)3.1117583
Kurtosis122.4548
Mean1486.4881
Median Absolute Deviation (MAD)232.91
Skewness9.8863115
Sum505405.96
Variance21396099
MonotonicityNot monotonic
2023-12-11T08:04:11.220202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 3
 
0.9%
1000.0 3
 
0.9%
237.7 2
 
0.6%
658.01 2
 
0.6%
297.0 2
 
0.6%
493.55 2
 
0.6%
3133.96 2
 
0.6%
186.1 2
 
0.6%
607.25 2
 
0.6%
657.76 2
 
0.6%
Other values (318) 318
93.5%
ValueCountFrequency (%)
18.0 1
0.3%
60.9 1
0.3%
63.62 1
0.3%
72.36 1
0.3%
81.72 1
0.3%
90.88 1
0.3%
108.72 1
0.3%
114.96 1
0.3%
118.91 1
0.3%
121.78 1
0.3%
ValueCountFrequency (%)
66253.15 1
0.3%
34284.23 1
0.3%
21659.26 1
0.3%
20135.43 1
0.3%
15634.87 1
0.3%
13427.125 1
0.3%
12712.37 1
0.3%
9577.22 1
0.3%
9221.3 1
0.3%
8808.0 1
0.3%

증축연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)100.0%
Missing285
Missing (%)83.8%
Infinite0
Infinite (%)0.0%
Mean774.08808
Minimum25.6
Maximum4619.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:11.333522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.6
5-th percentile95.913
Q1173.8
median315
Q3749.49
95-th percentile3462.942
Maximum4619.99
Range4594.39
Interquartile range (IQR)575.69

Descriptive statistics

Standard deviation1084.3841
Coefficient of variation (CV)1.4008536
Kurtosis4.5688584
Mean774.08808
Median Absolute Deviation (MAD)166.43
Skewness2.2900049
Sum42574.844
Variance1175888.9
MonotonicityNot monotonic
2023-12-11T08:04:11.440030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1615.471 1
 
0.3%
494.81 1
 
0.3%
462.0 1
 
0.3%
358.8 1
 
0.3%
300.0 1
 
0.3%
527.0375 1
 
0.3%
3292.64 1
 
0.3%
787.38 1
 
0.3%
711.6 1
 
0.3%
315.0 1
 
0.3%
Other values (45) 45
 
13.2%
(Missing) 285
83.8%
ValueCountFrequency (%)
25.6 1
0.3%
42.3 1
0.3%
95.71 1
0.3%
96.0 1
0.3%
98.96 1
0.3%
111.8 1
0.3%
143.6365 1
0.3%
144.2425 1
0.3%
148.57 1
0.3%
155.88 1
0.3%
ValueCountFrequency (%)
4619.99 1
0.3%
4145.83 1
0.3%
3731.35 1
0.3%
3347.91 1
0.3%
3292.64 1
0.3%
2131.2 1
0.3%
1628.86 1
0.3%
1615.471 1
0.3%
1430.0 1
0.3%
1354.0 1
0.3%

건폐율(퍼센트)
Real number (ℝ)

Distinct329
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.972168
Minimum1.4435
Maximum79.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:11.555197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.4435
5-th percentile15.72943
Q130.0925
median48.46
Q358.516375
95-th percentile66.6465
Maximum79.96
Range78.5165
Interquartile range (IQR)28.423875

Descriptive statistics

Standard deviation17.09558
Coefficient of variation (CV)0.38878182
Kurtosis-0.8737102
Mean43.972168
Median Absolute Deviation (MAD)10.95555
Skewness-0.36388795
Sum14950.537
Variance292.25884
MonotonicityNot monotonic
2023-12-11T08:04:11.679125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.16 3
 
0.9%
55.0 2
 
0.6%
32.17 2
 
0.6%
59.51 2
 
0.6%
39.6 2
 
0.6%
52.4278 2
 
0.6%
79.9 2
 
0.6%
48.89 2
 
0.6%
58.0566 2
 
0.6%
59.71 2
 
0.6%
Other values (319) 319
93.8%
ValueCountFrequency (%)
1.4435 1
0.3%
6.27 1
0.3%
7.5748 1
0.3%
8.1239 1
0.3%
9.4257 1
0.3%
9.86 1
0.3%
10.36 1
0.3%
11.065 1
0.3%
11.78 1
0.3%
12.02 1
0.3%
ValueCountFrequency (%)
79.96 1
0.3%
79.9 2
0.6%
77.94 1
0.3%
76.96 1
0.3%
74.35 1
0.3%
73.68 1
0.3%
73.63 1
0.3%
71.23 1
0.3%
71.16 1
0.3%
70.87 1
0.3%

용적률(퍼센트)
Real number (ℝ)

Distinct334
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.810108
Minimum1.4435
Maximum453.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:11.810000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.4435
5-th percentile17.49963
Q137.23975
median89.2213
Q3158.44485
95-th percentile197.7185
Maximum453.25
Range451.8065
Interquartile range (IQR)121.2051

Descriptive statistics

Standard deviation69.542285
Coefficient of variation (CV)0.69674592
Kurtosis1.7653921
Mean99.810108
Median Absolute Deviation (MAD)57.82675
Skewness0.91549619
Sum33935.437
Variance4836.1295
MonotonicityNot monotonic
2023-12-11T08:04:11.945080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.71 2
 
0.6%
32.17 2
 
0.6%
39.6 2
 
0.6%
144.6221 2
 
0.6%
169.62 2
 
0.6%
166.2269 2
 
0.6%
35.0392 1
 
0.3%
113.8 1
 
0.3%
40.12 1
 
0.3%
26.79 1
 
0.3%
Other values (324) 324
95.3%
ValueCountFrequency (%)
1.4435 1
0.3%
8.14 1
0.3%
10.9829 1
0.3%
11.06 1
0.3%
11.78 1
0.3%
11.92 1
0.3%
12.3656 1
0.3%
12.5365 1
0.3%
12.6136 1
0.3%
12.73 1
0.3%
ValueCountFrequency (%)
453.25 1
0.3%
399.3872 1
0.3%
327.0 1
0.3%
288.2 1
0.3%
268.15 1
0.3%
262.97 1
0.3%
261.8897 1
0.3%
239.16 1
0.3%
228.41 1
0.3%
226.35 1
0.3%

구조
Categorical

Distinct10
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
철근콘크리트구조
201 
일반철골구조
85 
경량철골구조
34 
<NA>
 
5
일반목구조
 
5
Other values (5)
 
10

Length

Max length8
Median length8
Mean length7.1264706
Min length4

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 201
59.1%
일반철골구조 85
25.0%
경량철골구조 34
 
10.0%
<NA> 5
 
1.5%
일반목구조 5
 
1.5%
벽돌구조 3
 
0.9%
강파이프구조 3
 
0.9%
철골콘크리트구조 2
 
0.6%
기타조적구조 1
 
0.3%
블록구조 1
 
0.3%

Length

2023-12-11T08:04:12.063724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:12.172997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트구조 201
59.1%
일반철골구조 85
25.0%
경량철골구조 34
 
10.0%
na 5
 
1.5%
일반목구조 5
 
1.5%
벽돌구조 3
 
0.9%
강파이프구조 3
 
0.9%
철골콘크리트구조 2
 
0.6%
기타조적구조 1
 
0.3%
블록구조 1
 
0.3%

취소구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
333 
취소
 
6
전환
 
1

Length

Max length4
Median length4
Mean length3.9588235
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 333
97.9%
취소 6
 
1.8%
전환 1
 
0.3%

Length

2023-12-11T08:04:12.322648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:12.433297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 333
97.9%
취소 6
 
1.8%
전환 1
 
0.3%

철거멸실구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing340
Missing (%)100.0%
Memory size3.1 KiB

허가취소일
Date

MISSING 

Distinct7
Distinct (%)100.0%
Missing333
Missing (%)97.9%
Memory size2.8 KiB
Minimum2015-04-08 00:00:00
Maximum2016-05-04 00:00:00
2023-12-11T08:04:12.509904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:12.602273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

허가일
Date

Distinct183
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2015-01-06 00:00:00
Maximum2015-12-31 00:00:00
2023-12-11T08:04:12.710667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:12.830739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종설계변경일
Date

MISSING 

Distinct79
Distinct (%)79.8%
Missing241
Missing (%)70.9%
Memory size2.8 KiB
Minimum2015-03-12 00:00:00
Maximum2016-06-07 00:00:00
2023-12-11T08:04:12.959164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:13.099760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct172
Distinct (%)59.9%
Missing53
Missing (%)15.6%
Memory size2.8 KiB
Minimum2015-01-09 00:00:00
Maximum2016-05-16 00:00:00
2023-12-11T08:04:13.225161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:13.371466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공예정일
Date

MISSING 

Distinct185
Distinct (%)64.5%
Missing53
Missing (%)15.6%
Memory size2.8 KiB
Minimum1995-03-20 00:00:00
Maximum2016-05-16 00:00:00
2023-12-11T08:04:13.488192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:13.611579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실제착공일
Date

MISSING 

Distinct156
Distinct (%)69.0%
Missing114
Missing (%)33.5%
Memory size2.8 KiB
Minimum1995-03-20 00:00:00
Maximum2016-03-15 00:00:00
2023-12-11T08:04:13.738806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:14.128700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct155
Distinct (%)66.8%
Missing108
Missing (%)31.8%
Memory size2.8 KiB
Minimum2015-03-13 00:00:00
Maximum2016-06-14 00:00:00
2023-12-11T08:04:14.289310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:14.415923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건축허가최초접수일
Date

Distinct182
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2014-11-28 00:00:00
Maximum2015-12-21 00:00:00
2023-12-11T08:04:14.542359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:14.698009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

Distinct12
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8176471
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:14.829622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum20
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9693029
Coefficient of variation (CV)0.69891751
Kurtosis19.321376
Mean2.8176471
Median Absolute Deviation (MAD)1
Skewness3.132828
Sum958
Variance3.8781537
MonotonicityNot monotonic
2023-12-11T08:04:14.939937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2 96
28.2%
4 91
26.8%
1 86
25.3%
3 41
12.1%
5 12
 
3.5%
10 4
 
1.2%
8 3
 
0.9%
9 2
 
0.6%
6 2
 
0.6%
20 1
 
0.3%
Other values (2) 2
 
0.6%
ValueCountFrequency (%)
1 86
25.3%
2 96
28.2%
3 41
12.1%
4 91
26.8%
5 12
 
3.5%
6 2
 
0.6%
7 1
 
0.3%
8 3
 
0.9%
9 2
 
0.6%
10 4
 
1.2%
ValueCountFrequency (%)
20 1
 
0.3%
12 1
 
0.3%
10 4
 
1.2%
9 2
 
0.6%
8 3
 
0.9%
7 1
 
0.3%
6 2
 
0.6%
5 12
 
3.5%
4 91
26.8%
3 41
12.1%

최대지하층수
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
252 
<NA>
71 
1
 
17

Length

Max length4
Median length1
Mean length1.6264706
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 252
74.1%
<NA> 71
 
20.9%
1 17
 
5.0%

Length

2023-12-11T08:04:15.091922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:15.216445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 252
74.1%
na 71
 
20.9%
1 17
 
5.0%

최고높이(제곱미터)
Real number (ℝ)

Distinct193
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.308994
Minimum0
Maximum65.5
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:15.342660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.9285
Q17.9
median10.8
Q313.3
95-th percentile18.8
Maximum65.5
Range65.5
Interquartile range (IQR)5.4

Descriptive statistics

Standard deviation5.8082114
Coefficient of variation (CV)0.51359222
Kurtosis24.4015
Mean11.308994
Median Absolute Deviation (MAD)2.7
Skewness3.4552068
Sum3845.058
Variance33.73532
MonotonicityNot monotonic
2023-12-11T08:04:15.490291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.7 7
 
2.1%
12.8 6
 
1.8%
8.6 6
 
1.8%
13.0 5
 
1.5%
8.1 5
 
1.5%
7.7 5
 
1.5%
7.5 5
 
1.5%
14.7 5
 
1.5%
8.5 5
 
1.5%
13.3 4
 
1.2%
Other values (183) 287
84.4%
ValueCountFrequency (%)
0.0 2
0.6%
2.8 1
 
0.3%
4.2 2
0.6%
4.3 1
 
0.3%
4.5 2
0.6%
4.6 3
0.9%
4.65 1
 
0.3%
4.8 4
1.2%
4.9 1
 
0.3%
4.93 1
 
0.3%
ValueCountFrequency (%)
65.5 1
0.3%
39.1 1
0.3%
31.41 1
0.3%
30.6 1
0.3%
30.5 1
0.3%
30.43 1
0.3%
29.95 1
0.3%
28.75 1
0.3%
27.7 1
0.3%
26.0 1
0.3%

동수
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5794118
Minimum0
Maximum21
Zeros21
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:15.618537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile5
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2386099
Coefficient of variation (CV)1.4173694
Kurtosis40.596785
Mean1.5794118
Median Absolute Deviation (MAD)0
Skewness5.8015251
Sum537
Variance5.0113743
MonotonicityNot monotonic
2023-12-11T08:04:15.713450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 249
73.2%
2 37
 
10.9%
0 21
 
6.2%
3 9
 
2.6%
5 7
 
2.1%
4 6
 
1.8%
7 2
 
0.6%
8 2
 
0.6%
18 1
 
0.3%
21 1
 
0.3%
Other values (5) 5
 
1.5%
ValueCountFrequency (%)
0 21
 
6.2%
1 249
73.2%
2 37
 
10.9%
3 9
 
2.6%
4 6
 
1.8%
5 7
 
2.1%
6 1
 
0.3%
7 2
 
0.6%
8 2
 
0.6%
9 1
 
0.3%
ValueCountFrequency (%)
21 1
 
0.3%
20 1
 
0.3%
18 1
 
0.3%
13 1
 
0.3%
11 1
 
0.3%
9 1
 
0.3%
8 2
 
0.6%
7 2
 
0.6%
6 1
 
0.3%
5 7
2.1%

주용도
Categorical

Distinct19
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
단독주택
118 
제2종근린생활시설
64 
제1종근린생활시설
46 
공장
37 
공동주택
22 
Other values (14)
53 

Length

Max length10
Median length4
Mean length5.5676471
Min length2

Unique

Unique6 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 118
34.7%
제2종근린생활시설 64
18.8%
제1종근린생활시설 46
 
13.5%
공장 37
 
10.9%
공동주택 22
 
6.5%
창고시설 15
 
4.4%
업무시설 7
 
2.1%
숙박시설 6
 
1.8%
동.식물관련시설 6
 
1.8%
노유자시설 5
 
1.5%
Other values (9) 14
 
4.1%

Length

2023-12-11T08:04:15.832810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 118
34.7%
제2종근린생활시설 64
18.8%
제1종근린생활시설 46
 
13.5%
공장 37
 
10.9%
공동주택 22
 
6.5%
창고시설 15
 
4.4%
업무시설 7
 
2.1%
숙박시설 6
 
1.8%
동.식물관련시설 6
 
1.8%
노유자시설 5
 
1.5%
Other values (9) 14
 
4.1%

부속용도
Text

MISSING 

Distinct111
Distinct (%)45.3%
Missing95
Missing (%)27.9%
Memory size2.8 KiB
2023-12-11T08:04:15.999582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length6.9877551
Min length2

Characters and Unicode

Total characters1712
Distinct characters130
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

Unique87 ?
Unique (%)35.5%

Sample

1st row소매점 및 단독주택
2nd row다가구주택
3rd row하수 등 처리시설
4th row다세대주택
5th row목욕탕
ValueCountFrequency (%)
다가구주택 55
17.6%
단독주택 33
 
10.5%
소매점 21
 
6.7%
및 21
 
6.7%
일반음식점 16
 
5.1%
다가구 15
 
4.8%
사무소 14
 
4.5%
제2종근린생활시설 7
 
2.2%
근린생활시설 5
 
1.6%
창고 4
 
1.3%
Other values (93) 122
39.0%
2023-12-11T08:04:16.302857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 117
 
6.8%
택 115
 
6.7%
다 84
 
4.9%
가 84
 
4.9%
구 78
 
4.6%
68
 
4.0%
점 57
 
3.3%
시 56
 
3.3%
소 55
 
3.2%
설 52
 
3.0%
Other values (120) 946
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1497
87.4%
Space Separator 68
 
4.0%
Close Punctuation 37
 
2.2%
Open Punctuation 37
 
2.2%
Other Punctuation 37
 
2.2%
Decimal Number 35
 
2.0%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 117
 
7.8%
택 115
 
7.7%
다 84
 
5.6%
가 84
 
5.6%
구 78
 
5.2%
점 57
 
3.8%
시 56
 
3.7%
소 55
 
3.7%
설 52
 
3.5%
단 41
 
2.7%
Other values (108) 758
50.6%
Other Punctuation
ValueCountFrequency (%)
, 30
81.1%
/ 5
 
13.5%
. 1
 
2.7%
: 1
 
2.7%
Decimal Number
ValueCountFrequency (%)
2 24
68.6%
1 9
 
25.7%
8 1
 
2.9%
3 1
 
2.9%
Space Separator
ValueCountFrequency (%)
68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1497
87.4%
Common 215
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 117
 
7.8%
택 115
 
7.7%
다 84
 
5.6%
가 84
 
5.6%
구 78
 
5.2%
점 57
 
3.8%
시 56
 
3.7%
소 55
 
3.7%
설 52
 
3.5%
단 41
 
2.7%
Other values (108) 758
50.6%
Common
ValueCountFrequency (%)
68
31.6%
) 37
17.2%
( 37
17.2%
, 30
14.0%
2 24
 
11.2%
1 9
 
4.2%
/ 5
 
2.3%
. 1
 
0.5%
8 1
 
0.5%
3 1
 
0.5%
Other values (2) 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1497
87.4%
ASCII 215
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 117
 
7.8%
택 115
 
7.7%
다 84
 
5.6%
가 84
 
5.6%
구 78
 
5.2%
점 57
 
3.8%
시 56
 
3.7%
소 55
 
3.7%
설 52
 
3.5%
단 41
 
2.7%
Other values (108) 758
50.6%
ASCII
ValueCountFrequency (%)
68
31.6%
) 37
17.2%
( 37
17.2%
, 30
14.0%
2 24
 
11.2%
1 9
 
4.2%
/ 5
 
2.3%
. 1
 
0.5%
8 1
 
0.5%
3 1
 
0.5%
Other values (2) 2
 
0.9%

용도지역
Categorical

Distinct17
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
제2종일반주거지역
103 
제1종일반주거지역
72 
계획관리지역
42 
자연녹지지역
30 
일반상업지역
25 
Other values (12)
68 

Length

Max length9
Median length9
Mean length7.4411765
Min length4

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row생산녹지지역
2nd row제2종일반주거지역
3rd row일반공업지역
4th row제2종일반주거지역
5th row제2종일반주거지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 103
30.3%
제1종일반주거지역 72
21.2%
계획관리지역 42
12.4%
자연녹지지역 30
 
8.8%
일반상업지역 25
 
7.4%
일반공업지역 12
 
3.5%
준공업지역 12
 
3.5%
준주거지역 9
 
2.6%
생산녹지지역 8
 
2.4%
생산관리지역 7
 
2.1%
Other values (7) 20
 
5.9%

Length

2023-12-11T08:04:16.421555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 103
30.3%
제1종일반주거지역 72
21.2%
계획관리지역 42
12.4%
자연녹지지역 30
 
8.8%
일반상업지역 25
 
7.4%
일반공업지역 12
 
3.5%
준공업지역 12
 
3.5%
준주거지역 9
 
2.6%
생산녹지지역 8
 
2.4%
생산관리지역 7
 
2.1%
Other values (7) 20
 
5.9%

용도지구
Categorical

IMBALANCE 

Distinct10
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
294 
비행안전제5구역(전술)
 
17
자연취락지구
 
8
최고고도지구
 
7
산업개발진흥지구
 
6
Other values (5)
 
8

Length

Max length12
Median length4
Mean length4.7058824
Min length4

Unique

Unique4 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 294
86.5%
비행안전제5구역(전술) 17
 
5.0%
자연취락지구 8
 
2.4%
최고고도지구 7
 
2.1%
산업개발진흥지구 6
 
1.8%
비행안전제6구역(전술) 4
 
1.2%
비행안전제2구역(전술) 1
 
0.3%
취락지구 1
 
0.3%
비행안전제4구역(전술) 1
 
0.3%
제한보호구역 1
 
0.3%

Length

2023-12-11T08:04:16.540159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:16.670051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 294
86.5%
비행안전제5구역(전술 17
 
5.0%
자연취락지구 8
 
2.4%
최고고도지구 7
 
2.1%
산업개발진흥지구 6
 
1.8%
비행안전제6구역(전술 4
 
1.2%
비행안전제2구역(전술 1
 
0.3%
취락지구 1
 
0.3%
비행안전제4구역(전술 1
 
0.3%
제한보호구역 1
 
0.3%

용도구역
Categorical

Distinct15
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
208 
전술항공작전기지의비행안전제5구역
42 
상대정화구역
38 
전술항공작전기지의비행안전제6구역
21 
제1종지구단위계획구역
 
7
Other values (10)
24 

Length

Max length17
Median length4
Mean length7.1941176
Min length4

Unique

Unique3 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 208
61.2%
전술항공작전기지의비행안전제5구역 42
 
12.4%
상대정화구역 38
 
11.2%
전술항공작전기지의비행안전제6구역 21
 
6.2%
제1종지구단위계획구역 7
 
2.1%
제2종지구단위계획구역 6
 
1.8%
수산자원보호구역 4
 
1.2%
전술항공작전기지의비행안전제4구역 3
 
0.9%
절대정화구역 2
 
0.6%
접도구역 2
 
0.6%
Other values (5) 7
 
2.1%

Length

2023-12-11T08:04:16.799745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 208
60.6%
전술항공작전기지의비행안전제5구역 42
 
12.2%
상대정화구역 38
 
11.1%
전술항공작전기지의비행안전제6구역 21
 
6.1%
제1종지구단위계획구역 7
 
2.0%
제2종지구단위계획구역 6
 
1.7%
수산자원보호구역 4
 
1.2%
전술항공작전기지의비행안전제4구역 3
 
0.9%
대상구역 2
 
0.6%
농업진흥구역 2
 
0.6%
Other values (7) 10
 
2.9%

세대수
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)56.0%
Missing315
Missing (%)92.6%
Infinite0
Infinite (%)0.0%
Mean16.6
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:16.906787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median16
Q324
95-th percentile45.6
Maximum48
Range47
Interquartile range (IQR)16

Descriptive statistics

Standard deviation13.12123
Coefficient of variation (CV)0.79043552
Kurtosis0.90090205
Mean16.6
Median Absolute Deviation (MAD)8
Skewness1.0755105
Sum415
Variance172.16667
MonotonicityNot monotonic
2023-12-11T08:04:17.008333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
8 4
 
1.2%
1 4
 
1.2%
16 4
 
1.2%
48 2
 
0.6%
24 2
 
0.6%
19 1
 
0.3%
36 1
 
0.3%
12 1
 
0.3%
15 1
 
0.3%
28 1
 
0.3%
Other values (4) 4
 
1.2%
(Missing) 315
92.6%
ValueCountFrequency (%)
1 4
1.2%
7 1
 
0.3%
8 4
1.2%
10 1
 
0.3%
12 1
 
0.3%
15 1
 
0.3%
16 4
1.2%
17 1
 
0.3%
19 1
 
0.3%
24 2
0.6%
ValueCountFrequency (%)
48 2
0.6%
36 1
 
0.3%
28 1
 
0.3%
27 1
 
0.3%
24 2
0.6%
19 1
 
0.3%
17 1
 
0.3%
16 4
1.2%
15 1
 
0.3%
12 1
 
0.3%

호수
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)80.0%
Missing330
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean9
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:17.108451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.25
median5.5
Q38
95-th percentile28.8
Maximum36
Range35
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation11.005049
Coefficient of variation (CV)1.2227833
Kurtosis3.9681995
Mean9
Median Absolute Deviation (MAD)3
Skewness2.01513
Sum90
Variance121.11111
MonotonicityNot monotonic
2023-12-11T08:04:17.249382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
8 2
 
0.6%
1 2
 
0.6%
36 1
 
0.3%
2 1
 
0.3%
6 1
 
0.3%
5 1
 
0.3%
20 1
 
0.3%
3 1
 
0.3%
(Missing) 330
97.1%
ValueCountFrequency (%)
1 2
0.6%
2 1
0.3%
3 1
0.3%
5 1
0.3%
6 1
0.3%
8 2
0.6%
20 1
0.3%
36 1
0.3%
ValueCountFrequency (%)
36 1
0.3%
20 1
0.3%
8 2
0.6%
6 1
0.3%
5 1
0.3%
3 1
0.3%
2 1
0.3%
1 2
0.6%

가구수
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)11.7%
Missing178
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean7.3024691
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:17.374565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q312.75
95-th percentile18
Maximum19
Range18
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation6.345233
Coefficient of variation (CV)0.8689161
Kurtosis-1.3820841
Mean7.3024691
Median Absolute Deviation (MAD)5
Skewness0.38255382
Sum1183
Variance40.261981
MonotonicityNot monotonic
2023-12-11T08:04:17.510173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 63
 
18.5%
11 16
 
4.7%
14 10
 
2.9%
18 10
 
2.9%
2 8
 
2.4%
15 8
 
2.4%
10 6
 
1.8%
5 5
 
1.5%
12 5
 
1.5%
9 5
 
1.5%
Other values (9) 26
 
7.6%
(Missing) 178
52.4%
ValueCountFrequency (%)
1 63
18.5%
2 8
 
2.4%
3 1
 
0.3%
4 3
 
0.9%
5 5
 
1.5%
6 3
 
0.9%
7 1
 
0.3%
8 5
 
1.5%
9 5
 
1.5%
10 6
 
1.8%
ValueCountFrequency (%)
19 4
 
1.2%
18 10
2.9%
17 4
 
1.2%
16 3
 
0.9%
15 8
2.4%
14 10
2.9%
13 2
 
0.6%
12 5
 
1.5%
11 16
4.7%
10 6
 
1.8%

주건축물수
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)2.5%
Missing21
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean1.3260188
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:17.606895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum18
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2714747
Coefficient of variation (CV)0.95886627
Kurtosis98.503079
Mean1.3260188
Median Absolute Deviation (MAD)0
Skewness8.6060381
Sum423
Variance1.6166479
MonotonicityNot monotonic
2023-12-11T08:04:17.702281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 268
78.8%
2 36
 
10.6%
4 4
 
1.2%
3 4
 
1.2%
6 3
 
0.9%
5 2
 
0.6%
18 1
 
0.3%
9 1
 
0.3%
(Missing) 21
 
6.2%
ValueCountFrequency (%)
1 268
78.8%
2 36
 
10.6%
3 4
 
1.2%
4 4
 
1.2%
5 2
 
0.6%
6 3
 
0.9%
9 1
 
0.3%
18 1
 
0.3%
ValueCountFrequency (%)
18 1
 
0.3%
9 1
 
0.3%
6 3
 
0.9%
5 2
 
0.6%
4 4
 
1.2%
3 4
 
1.2%
2 36
 
10.6%
1 268
78.8%

부속건축물수
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)17.5%
Missing300
Missing (%)88.2%
Infinite0
Infinite (%)0.0%
Mean2.85
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-11T08:04:17.805301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile6.45
Maximum19
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.591657
Coefficient of variation (CV)1.2602305
Kurtosis12.975097
Mean2.85
Median Absolute Deviation (MAD)1
Skewness3.4664335
Sum114
Variance12.9
MonotonicityNot monotonic
2023-12-11T08:04:17.927126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 19
 
5.6%
3 7
 
2.1%
2 6
 
1.8%
4 4
 
1.2%
6 2
 
0.6%
15 1
 
0.3%
19 1
 
0.3%
(Missing) 300
88.2%
ValueCountFrequency (%)
1 19
5.6%
2 6
 
1.8%
3 7
 
2.1%
4 4
 
1.2%
6 2
 
0.6%
15 1
 
0.3%
19 1
 
0.3%
ValueCountFrequency (%)
19 1
 
0.3%
15 1
 
0.3%
6 2
 
0.6%
4 4
 
1.2%
3 7
 
2.1%
2 6
 
1.8%
1 19
5.6%

Sample

건축구분허가번호건축주명대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조취소구분철거멸실구분허가취소일허가일최종설계변경일착공처리일착공예정일실제착공일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(제곱미터)동수주용도부속용도용도지역용도지구용도구역세대수호수가구수주건축물수부속건축물수
0신축2015-민원봉사과-신축허가-233강철원 외 1경상남도 사천시 향촌동 336-6 외1필지전536.0105.91187.81<NA>19.759335.0392일반철골구조<NA><NA><NA>2015-12-31<NA>2016-01-072016-01-112016-01-112016-05-232015-12-21208.91제1종근린생활시설소매점 및 단독주택생산녹지지역<NA><NA><NA><NA>11<NA>
1신축2015-민원봉사과-신축허가-234심점화경상남도 사천시 사천읍 선인리 215-37대497.0291.21655.99<NA>58.59131.99철근콘크리트구조<NA><NA><NA>2015-12-31<NA>2016-01-142016-01-14<NA><NA>2015-12-214013.21단독주택다가구주택제2종일반주거지역<NA><NA><NA><NA>181<NA>
2증축2015-민원봉사과-협의건축물-11사천시경상남도 사천시 사등동 114-1 외5필지잡종지84567.05300.059221.3943.976.278.14철근콘크리트구조<NA><NA><NA>2015-12-30<NA><NA><NA><NA><NA>2015-12-02119.118자원순환관련시설하수 등 처리시설일반공업지역<NA><NA><NA><NA><NA>18<NA>
3신축2015-건축과-신축허가-21(주)우용주택건설경상남도 사천시 향촌동 977-17대549.6215.1658.0<NA>39.1376119.7234철근콘크리트구조<NA><NA><NA>2015-12-30<NA>2016-01-152016-01-15<NA><NA>2015-12-115014.71공동주택다세대주택제2종일반주거지역<NA><NA>8<NA><NA>1<NA>
4신축2015-민원봉사과-신축허가-232주식회사다인경상남도 사천시 사남면 월성리 산 2-11 외1필지임야1087.0598.912604.66<NA>55.1228.41철근콘크리트구조<NA><NA><NA>2015-12-30<NA>2016-01-252016-01-22<NA><NA>2015-12-085121.650제2종근린생활시설목욕탕제2종일반주거지역<NA><NA>1<NA><NA><NA><NA>
5증축2015-민원봉사과-증축허가-50주식회사명천공업경상남도 사천시 사남면 월성리 415공장용지9886.56036.5416559.5941615.47161.0666.35일반철골구조<NA><NA><NA>2015-12-28<NA>2016-01-142016-01-112016-01-112016-05-262015-12-212<NA>8.25공장<NA>계획관리지역산업개발진흥지구제2종지구단위계획구역<NA><NA><NA>41
6신축2015-민원봉사과-신축허가-230주세영경상남도 사천시 사남면 월성리 548-6대334.7200.67493.55<NA>59.96147.46철근콘크리트구조<NA><NA><NA>2015-12-28<NA>2015-12-302015-12-30<NA><NA>2015-12-214016.91단독주택제2종 근린생활시설제2종일반주거지역비행안전제5구역(전술)<NA><NA><NA>51<NA>
7신축2015-민원봉사과-신축허가-231양영희경상남도 사천시 벌리동 245-14대448.7255.51655.52<NA>56.9445146.0932철근콘크리트구조<NA><NA><NA>2015-12-28<NA>2015-12-302015-12-31<NA><NA>2015-12-174013.31단독주택다가구주택제2종일반주거지역<NA><NA><NA><NA>171<NA>
8신축2015-민원봉사과-신축허가-229주식회사석영경상남도 사천시 사천읍 평화리 165-11대1049.0583.67583.67<NA>55.6455.64일반철골구조<NA><NA><NA>2015-12-242016-02-222016-01-112016-01-112016-01-112016-06-142015-12-14106.52제1종근린생활시설소매점, 사무소제2종일반주거지역<NA>상대정화구역<NA><NA>22<NA>
9신축2015-민원봉사과-신축허가-227구명수 외 1경상남도 사천시 동금동 329-5 외1필지대801.0424.78746.98<NA>53.0393.26일반철골구조<NA><NA><NA>2015-12-222016-06-072016-01-072016-01-08<NA><NA>2015-11-24207.71제2종근린생활시설일반음식점,위락시설(유흥주점)일반상업지역<NA>상대정화구역<NA><NA><NA>1<NA>
건축구분허가번호건축주명대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조취소구분철거멸실구분허가취소일허가일최종설계변경일착공처리일착공예정일실제착공일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(제곱미터)동수주용도부속용도용도지역용도지구용도구역세대수호수가구수주건축물수부속건축물수
330신축2015-민원봉사과-신축허가-7문선환 외 1경상남도 사천시 향촌동 943-2대278.2166.17468.24<NA>59.7304168.3106철근콘크리트구조<NA><NA><NA>2015-01-19<NA>2015-02-092015-02-102015-02-102015-08-072015-01-134013.11단독주택<NA>제2종일반주거지역<NA><NA><NA><NA>111<NA>
331증축2015-민원봉사과-증축허가-2이칠문경상남도 사천시 송포동 1399 외2필지전907.0173.8266.98226.9819.162129.4355철근콘크리트구조<NA><NA><NA>2015-01-16<NA>2015-01-272015-01-282015-01-282015-06-042015-01-022<NA>7.82단독주택다가구주택자연녹지지역최고고도지구<NA><NA><NA>62<NA>
332신축2015-민원봉사과-신축허가-6이주봉경상남도 사천시 봉남동 583-4전628.0139.51240.27<NA>22.2238.26일반철골구조<NA><NA><NA>2015-01-16<NA>2015-01-302015-01-302015-01-302015-11-052015-01-072010.01제2종근린생활시설단독주택자연녹지지역자연취락지구상대정화구역<NA><NA>11<NA>
333신축2015-민원봉사과-신축허가-5하덕근경상남도 사천시 용현면 송지리 1252대347.6175.14316.26<NA>50.3990.98일반목구조<NA><NA><NA>2015-01-142015-06-232015-01-162015-01-192015-01-192015-08-042014-12-232010.991단독주택근.생(일반음식점)제1종일반주거지역<NA>제1종지구단위계획구역<NA><NA>11<NA>
334신축2015-민원봉사과-신축허가-4김환갑경상남도 사천시 사남면 월성리 18-2 외1필지답989.0590.55590.55<NA>59.7159.71경량철골구조<NA><NA><NA>2015-01-132015-04-162015-02-112015-02-232015-02-232015-04-292014-12-26106.652제2종근린생활시설일반음식점제2종일반주거지역<NA>전술항공작전기지의비행안전제5구역<NA><NA><NA>2<NA>
335증축2015-민원봉사과-증축허가-1서강유업(주)경상남도 사천시 사남면 월성리 421공장용지18663.79990.63513427.125345.9553.529871.9425일반철골구조<NA><NA><NA>2015-01-12<NA>2015-01-212015-01-192015-01-192015-04-062014-12-311<NA>10.58공장공장계획관리지역산업개발진흥지구제2종지구단위계획구역<NA><NA><NA>26
336신축2015-민원봉사과-신축허가-1성성호 외 1경상남도 사천시 서동 308-1대119.095.08186.1<NA>79.9139.45철근콘크리트구조<NA><NA><NA>2015-01-07<NA>2015-01-092015-01-092015-01-092015-04-282014-12-29208.51단독주택및 제1종근린생활시설상업지역<NA><NA><NA><NA>11<NA>
337신축2015-민원봉사과-신축허가-2배강효 외 1경상남도 사천시 사천읍 구암리 1620-8전662.0128.27183.88<NA>19.376125.3897철근콘크리트구조<NA><NA><NA>2015-01-07<NA>2015-01-202015-01-232015-01-232015-07-242014-12-22207.71제1종근린생활시설단독주택자연녹지지역<NA>전술항공작전기지의비행안전제5구역<NA><NA>11<NA>
338신축2015-민원봉사과-신축허가-3김우진 외 1경상남도 사천시 동금동 65-9대545.8267.72489.9<NA>49.0589.76철근콘크리트구조<NA><NA><NA>2015-01-072015-06-082015-05-082015-05-112015-05-112015-11-262014-12-30208.51제2종근린생활시설(사무소)단독주택(다가구)제2종일반주거지역<NA><NA><NA><NA>21<NA>
339신축2015-건축과-신축허가-1이정옥경상남도 사천시 향촌동 1027전605.0266.311629.1<NA>44.02268.15철근콘크리트구조<NA><NA><NA>2015-01-06<NA>2015-03-092015-03-092015-03-092016-03-252014-12-1810130.61공동주택아파트,업무시설(오피스텔)근린상업지역<NA>상대정화구역17<NA><NA>1<NA>