Overview

Dataset statistics

Number of variables18
Number of observations43
Missing cells134
Missing cells (%)17.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory155.1 B

Variable types

Numeric3
Categorical8
DateTime3
Text3
Unsupported1

Dataset

Description경상남도 거창군의 2018년 ~ 2023년 8월 미준공 신축 건축물에 대한 데이터로 허가일, 착공일, 준공일, 대지위치, 연면적, 지상층수, 지하층수, 주용도, 부속용도, 총주차대수, 세대수, 가구수, 공사명(사업계획명), 시행사사무소명, 시공사사무소명을 제공합니다.
URLhttps://www.data.go.kr/data/15121982/fileData.do

Alerts

건축구분 has constant value ""Constant
데이터작성기준일 has constant value ""Constant
주용도 is highly overall correlated with 연면적(제곱미터) and 4 other fieldsHigh correlation
지상층수 is highly overall correlated with 연면적(제곱미터) and 2 other fieldsHigh correlation
시행사사무소명 is highly overall correlated with 연면적(제곱미터) and 4 other fieldsHigh correlation
지하층수 is highly overall correlated with 연면적(제곱미터) and 4 other fieldsHigh correlation
가구수 is highly overall correlated with 번호 and 6 other fieldsHigh correlation
번호 is highly overall correlated with 가구수High correlation
연면적(제곱미터) is highly overall correlated with 총주차대수 and 5 other fieldsHigh correlation
총주차대수 is highly overall correlated with 연면적(제곱미터) and 3 other fieldsHigh correlation
지하층수 is highly imbalanced (84.1%)Imbalance
주용도 is highly imbalanced (54.4%)Imbalance
세대수 is highly imbalanced (84.1%)Imbalance
착공일(착공예정일) has 19 (44.2%) missing valuesMissing
준공일(준공예정일) has 19 (44.2%) missing valuesMissing
부속용도 has 1 (2.3%) missing valuesMissing
총주차대수 has 19 (44.2%) missing valuesMissing
공사명(사업계획명) has 43 (100.0%) missing valuesMissing
시공사사무소명 has 33 (76.7%) missing valuesMissing
번호 has unique valuesUnique
공사명(사업계획명) is an unsupported type, check if it needs cleaning or further analysisUnsupported
총주차대수 has 8 (18.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:54:08.682395
Analysis finished2023-12-12 04:54:10.882309
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T13:54:10.960772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2023-12-12T13:54:11.221282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

건축구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
신축
43 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 43
100.0%

Length

2023-12-12T13:54:11.380415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:11.550720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 43
100.0%

허가일
Date

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2018-08-21 00:00:00
Maximum2023-08-25 00:00:00
2023-12-12T13:54:11.704037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:11.885250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

착공일(착공예정일)
Date

MISSING 

Distinct24
Distinct (%)100.0%
Missing19
Missing (%)44.2%
Memory size476.0 B
Minimum2018-09-19 00:00:00
Maximum2023-06-12 00:00:00
2023-12-12T13:54:12.041632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:12.204975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

준공일(준공예정일)
Date

MISSING 

Distinct21
Distinct (%)87.5%
Missing19
Missing (%)44.2%
Memory size476.0 B
Minimum2019-09-30 00:00:00
Maximum2121-12-25 00:00:00
2023-12-12T13:54:12.358238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:12.503947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

대지위치
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-12T13:54:12.849921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length23.232558
Min length19

Characters and Unicode

Total characters999
Distinct characters66
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

Unique41 ?
Unique (%)95.3%

Sample

1st row경상남도 거창군 마리면 말흘리 70
2nd row경상남도 거창군 마리면 말흘리 217-1 외2필지
3rd row경상남도 거창군 거창읍 장팔리 528-11
4th row경상남도 거창군 남상면 월평리 1383
5th row경상남도 거창군 웅양면 노현리 292-2 외4필지
ValueCountFrequency (%)
경상남도 43
18.5%
거창군 43
18.5%
거창읍 23
 
9.9%
대동리 5
 
2.2%
산 5
 
2.2%
가조면 5
 
2.2%
송정리 5
 
2.2%
마리면 4
 
1.7%
외2필지 4
 
1.7%
가지리 4
 
1.7%
Other values (74) 91
39.2%
2023-12-12T13:54:13.346353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
18.9%
거 66
 
6.6%
창 66
 
6.6%
상 51
 
5.1%
리 47
 
4.7%
남 45
 
4.5%
1 45
 
4.5%
경 43
 
4.3%
도 43
 
4.3%
군 43
 
4.3%
Other values (56) 361
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 599
60.0%
Space Separator 189
 
18.9%
Decimal Number 181
 
18.1%
Dash Punctuation 30
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 66
11.0%
창 66
11.0%
상 51
 
8.5%
리 47
 
7.8%
남 45
 
7.5%
경 43
 
7.2%
도 43
 
7.2%
군 43
 
7.2%
읍 23
 
3.8%
면 20
 
3.3%
Other values (44) 152
25.4%
Decimal Number
ValueCountFrequency (%)
1 45
24.9%
2 30
16.6%
3 21
11.6%
5 15
 
8.3%
4 14
 
7.7%
9 13
 
7.2%
6 12
 
6.6%
8 12
 
6.6%
0 10
 
5.5%
7 9
 
5.0%
Space Separator
ValueCountFrequency (%)
189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 599
60.0%
Common 400
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 66
11.0%
창 66
11.0%
상 51
 
8.5%
리 47
 
7.8%
남 45
 
7.5%
경 43
 
7.2%
도 43
 
7.2%
군 43
 
7.2%
읍 23
 
3.8%
면 20
 
3.3%
Other values (44) 152
25.4%
Common
ValueCountFrequency (%)
189
47.2%
1 45
 
11.2%
- 30
 
7.5%
2 30
 
7.5%
3 21
 
5.2%
5 15
 
3.8%
4 14
 
3.5%
9 13
 
3.2%
6 12
 
3.0%
8 12
 
3.0%
Other values (2) 19
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 599
60.0%
ASCII 400
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
47.2%
1 45
 
11.2%
- 30
 
7.5%
2 30
 
7.5%
3 21
 
5.2%
5 15
 
3.8%
4 14
 
3.5%
9 13
 
3.2%
6 12
 
3.0%
8 12
 
3.0%
Other values (2) 19
 
4.8%
Hangul
ValueCountFrequency (%)
거 66
11.0%
창 66
11.0%
상 51
 
8.5%
리 47
 
7.8%
남 45
 
7.5%
경 43
 
7.2%
도 43
 
7.2%
군 43
 
7.2%
읍 23
 
3.8%
면 20
 
3.3%
Other values (44) 152
25.4%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346.78465
Minimum32
Maximum2788.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T13:54:13.517019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile73.68
Q198.675
median165.6
Q3425.15
95-th percentile1023.753
Maximum2788.73
Range2756.73
Interquartile range (IQR)326.475

Descriptive statistics

Standard deviation476.1184
Coefficient of variation (CV)1.3729512
Kurtosis16.503431
Mean346.78465
Median Absolute Deviation (MAD)73.6
Skewness3.6520169
Sum14911.74
Variance226688.73
MonotonicityNot monotonic
2023-12-12T13:54:13.670551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
158.0 2
 
4.7%
235.6 1
 
2.3%
1315.55 1
 
2.3%
97.44 1
 
2.3%
291.33 1
 
2.3%
162.0 1
 
2.3%
98.01 1
 
2.3%
73.2 1
 
2.3%
78.0 1
 
2.3%
712.8 1
 
2.3%
Other values (32) 32
74.4%
ValueCountFrequency (%)
32.0 1
2.3%
38.0 1
2.3%
73.2 1
2.3%
78.0 1
2.3%
81.18 1
2.3%
90.45 1
2.3%
92.0 1
2.3%
94.88 1
2.3%
97.44 1
2.3%
98.01 1
2.3%
ValueCountFrequency (%)
2788.73 1
2.3%
1315.55 1
2.3%
1031.99 1
2.3%
949.62 1
2.3%
712.8 1
2.3%
698.45 1
2.3%
524.02 1
2.3%
510.95 1
2.3%
503.88 1
2.3%
479.3 1
2.3%

지상층수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
1
29 
2
10 
3
 
2
6
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 29
67.4%
2 10
 
23.3%
3 2
 
4.7%
6 1
 
2.3%
4 1
 
2.3%

Length

2023-12-12T13:54:13.790124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:13.897458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 29
67.4%
2 10
 
23.3%
3 2
 
4.7%
6 1
 
2.3%
4 1
 
2.3%

지하층수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
0
42 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 42
97.7%
1 1
 
2.3%

Length

2023-12-12T13:54:14.015557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:14.114960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
97.7%
1 1
 
2.3%

주용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
제2종근린생활시설
37 
숙박시설
 
3
운동시설
 
3

Length

Max length9
Median length9
Mean length8.3023256
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제2종근린생활시설 37
86.0%
숙박시설 3
 
7.0%
운동시설 3
 
7.0%

Length

2023-12-12T13:54:14.205844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:14.325103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종근린생활시설 37
86.0%
숙박시설 3
 
7.0%
운동시설 3
 
7.0%

부속용도
Text

MISSING 

Distinct26
Distinct (%)61.9%
Missing1
Missing (%)2.3%
Memory size476.0 B
2023-12-12T13:54:14.507667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length10
Mean length6.1190476
Min length2

Characters and Unicode

Total characters257
Distinct characters78
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)47.6%

Sample

1st row일반음식점+창고
2nd row기타운동시설
3rd row사무소
4th row제조업소
5th row게이트볼장
ValueCountFrequency (%)
일반음식점 6
 
12.0%
사무소 6
 
12.0%
제조업소 6
 
12.0%
게이트볼장 3
 
6.0%
일반숙박시설 2
 
4.0%
제조업소-커피가공 2
 
4.0%
단독주택 2
 
4.0%
가항목 1
 
2.0%
게이트볼장(건축법 1
 
2.0%
시행령 1
 
2.0%
Other values (20) 20
40.0%
2023-12-12T13:54:14.910594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 16
 
6.2%
사 11
 
4.3%
일 10
 
3.9%
반 10
 
3.9%
제 10
 
3.9%
무 10
 
3.9%
점 9
 
3.5%
조 9
 
3.5%
업 9
 
3.5%
9
 
3.5%
Other values (68) 154
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 236
91.8%
Space Separator 9
 
3.5%
Math Symbol 6
 
2.3%
Dash Punctuation 2
 
0.8%
Decimal Number 2
 
0.8%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 16
 
6.8%
사 11
 
4.7%
일 10
 
4.2%
반 10
 
4.2%
제 10
 
4.2%
무 10
 
4.2%
점 9
 
3.8%
조 9
 
3.8%
업 9
 
3.8%
음 8
 
3.4%
Other values (61) 134
56.8%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
91.8%
Common 21
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 16
 
6.8%
사 11
 
4.7%
일 10
 
4.2%
반 10
 
4.2%
제 10
 
4.2%
무 10
 
4.2%
점 9
 
3.8%
조 9
 
3.8%
업 9
 
3.8%
음 8
 
3.4%
Other values (61) 134
56.8%
Common
ValueCountFrequency (%)
9
42.9%
+ 6
28.6%
- 2
 
9.5%
1 1
 
4.8%
) 1
 
4.8%
2 1
 
4.8%
( 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 236
91.8%
ASCII 21
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 16
 
6.8%
사 11
 
4.7%
일 10
 
4.2%
반 10
 
4.2%
제 10
 
4.2%
무 10
 
4.2%
점 9
 
3.8%
조 9
 
3.8%
업 9
 
3.8%
음 8
 
3.4%
Other values (61) 134
56.8%
ASCII
ValueCountFrequency (%)
9
42.9%
+ 6
28.6%
- 2
 
9.5%
1 1
 
4.8%
) 1
 
4.8%
2 1
 
4.8%
( 1
 
4.8%

총주차대수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct11
Distinct (%)45.8%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean8.0833333
Minimum0
Maximum81
Zeros8
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T13:54:15.029910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q37
95-th percentile29.2
Maximum81
Range81
Interquartile range (IQR)7

Descriptive statistics

Standard deviation17.224645
Coefficient of variation (CV)2.130884
Kurtosis14.915238
Mean8.0833333
Median Absolute Deviation (MAD)2
Skewness3.6726196
Sum194
Variance296.68841
MonotonicityNot monotonic
2023-12-12T13:54:15.147313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 8
18.6%
2 4
 
9.3%
4 3
 
7.0%
7 2
 
4.7%
31 1
 
2.3%
1 1
 
2.3%
19 1
 
2.3%
81 1
 
2.3%
3 1
 
2.3%
9 1
 
2.3%
(Missing) 19
44.2%
ValueCountFrequency (%)
0 8
18.6%
1 1
 
2.3%
2 4
9.3%
3 1
 
2.3%
4 3
 
7.0%
7 2
 
4.7%
9 1
 
2.3%
16 1
 
2.3%
19 1
 
2.3%
31 1
 
2.3%
ValueCountFrequency (%)
81 1
 
2.3%
31 1
 
2.3%
19 1
 
2.3%
16 1
 
2.3%
9 1
 
2.3%
7 2
4.7%
4 3
7.0%
3 1
 
2.3%
2 4
9.3%
1 1
 
2.3%

세대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
42 
1
 
1

Length

Max length4
Median length4
Mean length3.9302326
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
97.7%
1 1
 
2.3%

Length

2023-12-12T13:54:15.578996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:15.693679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
97.7%
1 1
 
2.3%

가구수
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
38 
1
5 

Length

Max length4
Median length4
Mean length3.6511628
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 38
88.4%
1 5
 
11.6%

Length

2023-12-12T13:54:15.876058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:16.002886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
88.4%
1 5
 
11.6%

공사명(사업계획명)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size519.0 B

시행사사무소명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Memory size476.0 B
건축사(사)정건축
7 
가람종합건축사사무소
7 
거창종합건축사사무소
6 
동광 건축사사무소
5 
신건축사사무소
5 
Other values (12)
13 

Length

Max length15
Median length13
Mean length9.4418605
Min length7

Unique

Unique11 ?
Unique (%)25.6%

Sample

1st row건축사(사)정건축
2nd row(주)아키랜드건축사사무소
3rd row가람종합건축사사무소
4th row건축사(사)정건축
5th row우성종합건축사사무소

Common Values

ValueCountFrequency (%)
건축사(사)정건축 7
16.3%
가람종합건축사사무소 7
16.3%
거창종합건축사사무소 6
14.0%
동광 건축사사무소 5
11.6%
신건축사사무소 5
11.6%
도담터 건축사사무소 2
 
4.7%
(주)종합건축사사무소 인우제 1
 
2.3%
건축사사무소 모람 1
 
2.3%
(주)예빈종합건축사사무소 1
 
2.3%
우성종합건축사사무소 1
 
2.3%
Other values (7) 7
16.3%

Length

2023-12-12T13:54:16.153387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건축사사무소 8
15.4%
건축사(사)정건축 7
13.5%
가람종합건축사사무소 7
13.5%
거창종합건축사사무소 6
11.5%
동광 5
9.6%
신건축사사무소 5
9.6%
도담터 2
 
3.8%
주)아키랜드건축사사무소 1
 
1.9%
다솔건축사사무소 1
 
1.9%
건축사사무소그룹정 1
 
1.9%
Other values (9) 9
17.3%

시공사사무소명
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing33
Missing (%)76.7%
Memory size476.0 B
2023-12-12T13:54:16.340956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length8.7
Min length7

Characters and Unicode

Total characters87
Distinct characters28
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

Unique8 ?
Unique (%)80.0%

Sample

1st row(주)미라벨종합건설
2nd row범창종합건설(주)
3rd row정은종합건설(주)
4th row산상임업(주)
5th row수경종합건설(주)
ValueCountFrequency (%)
주)미라벨종합건설 2
20.0%
범창종합건설(주 1
10.0%
정은종합건설(주 1
10.0%
산상임업(주 1
10.0%
수경종합건설(주 1
10.0%
주)지안종합건설 1
10.0%
창희종합건설(주 1
10.0%
주식회사대경건설 1
10.0%
주)창동건설 1
10.0%
2023-12-12T13:54:16.661270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 10
11.5%
( 9
10.3%
건 9
10.3%
설 9
10.3%
) 9
10.3%
종 7
 
8.0%
합 7
 
8.0%
창 3
 
3.4%
라 2
 
2.3%
벨 2
 
2.3%
Other values (18) 20
23.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
79.3%
Open Punctuation 9
 
10.3%
Close Punctuation 9
 
10.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 10
14.5%
건 9
13.0%
설 9
13.0%
종 7
10.1%
합 7
10.1%
창 3
 
4.3%
라 2
 
2.9%
벨 2
 
2.9%
미 2
 
2.9%
경 2
 
2.9%
Other values (16) 16
23.2%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
79.3%
Common 18
 
20.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 10
14.5%
건 9
13.0%
설 9
13.0%
종 7
10.1%
합 7
10.1%
창 3
 
4.3%
라 2
 
2.9%
벨 2
 
2.9%
미 2
 
2.9%
경 2
 
2.9%
Other values (16) 16
23.2%
Common
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
79.3%
ASCII 18
 
20.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 10
14.5%
건 9
13.0%
설 9
13.0%
종 7
10.1%
합 7
10.1%
창 3
 
4.3%
라 2
 
2.9%
벨 2
 
2.9%
미 2
 
2.9%
경 2
 
2.9%
Other values (16) 16
23.2%
ASCII
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%

데이터작성기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-08-31
43 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-31
2nd row2023-08-31
3rd row2023-08-31
4th row2023-08-31
5th row2023-08-31

Common Values

ValueCountFrequency (%)
2023-08-31 43
100.0%

Length

2023-12-12T13:54:16.800833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:54:16.919311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-31 43
100.0%

Interactions

2023-12-12T13:54:09.993376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.416508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.698676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:10.079752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.495117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.778601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:10.172612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.601634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:54:09.860565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:54:17.004488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호허가일착공일(착공예정일)준공일(준공예정일)대지위치연면적(제곱미터)지상층수지하층수주용도부속용도총주차대수시행사사무소명시공사사무소명
번호1.0001.0001.0000.0001.0000.3720.3790.2220.4600.6430.8180.3310.641
허가일1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
착공일(착공예정일)1.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.000
준공일(준공예정일)0.0001.0001.0001.0001.0000.6460.000NaN0.0000.9240.0000.6061.000
대지위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연면적(제곱미터)0.3721.0001.0000.6461.0001.0000.6651.0000.9820.9490.7630.8560.576
지상층수0.3791.0001.0000.0001.0000.6651.0000.0000.6570.5570.7900.8240.000
지하층수0.2221.000NaNNaN1.0001.0000.0001.0000.3321.0001.0001.000NaN
주용도0.4601.0001.0000.0001.0000.9820.6570.3321.0001.0000.5300.8650.000
부속용도0.6431.0001.0000.9241.0000.9490.5571.0001.0001.0000.6590.7951.000
총주차대수0.8181.0001.0000.0001.0000.7630.7901.0000.5300.6591.0000.9500.000
시행사사무소명0.3311.0001.0000.6061.0000.8560.8241.0000.8650.7950.9501.0000.974
시공사사무소명0.6411.0001.0001.0001.0000.5760.000NaN0.0001.0000.0000.9741.000
2023-12-12T13:54:17.165265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수주용도지상층수시행사사무소명지하층수가구수
세대수1.000NaNNaNNaNNaNNaN
주용도NaN1.0000.6080.5830.5261.000
지상층수NaN0.6081.0000.4960.0001.000
시행사사무소명NaN0.5830.4961.0000.7961.000
지하층수NaN0.5260.0000.7961.0001.000
가구수NaN1.0001.0001.0001.0001.000
2023-12-12T13:54:17.306924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호연면적(제곱미터)총주차대수지상층수지하층수주용도세대수가구수시행사사무소명
번호1.000-0.047-0.4840.1260.0000.235NaN1.0000.000
연면적(제곱미터)-0.0471.0000.8110.5170.9500.805NaN1.0000.516
총주차대수-0.4840.8111.0000.4030.9290.439NaN1.0000.706
지상층수0.1260.5170.4031.0000.0000.608NaN1.0000.496
지하층수0.0000.9500.9290.0001.0000.526NaN1.0000.796
주용도0.2350.8050.4390.6080.5261.000NaN1.0000.583
세대수NaNNaNNaNNaNNaNNaN1.000NaNNaN
가구수1.0001.0001.0001.0001.0001.000NaN1.0001.000
시행사사무소명0.0000.5160.7060.4960.7960.583NaN1.0001.000

Missing values

2023-12-12T13:54:10.322504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:54:10.599405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T13:54:10.772893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호건축구분허가일착공일(착공예정일)준공일(준공예정일)대지위치연면적(제곱미터)지상층수지하층수주용도부속용도총주차대수세대수가구수공사명(사업계획명)시행사사무소명시공사사무소명데이터작성기준일
01신축2018-08-212018-09-192019-09-30경상남도 거창군 마리면 말흘리 70235.610제2종근린생활시설일반음식점+창고<NA><NA><NA><NA>건축사(사)정건축<NA>2023-08-31
12신축2019-11-08<NA><NA>경상남도 거창군 마리면 말흘리 217-1 외2필지510.9510제2종근린생활시설기타운동시설31<NA><NA><NA>(주)아키랜드건축사사무소<NA>2023-08-31
23신축2020-02-112020-02-212020-12-31경상남도 거창군 거창읍 장팔리 528-1132.010제2종근린생활시설사무소<NA><NA><NA><NA>가람종합건축사사무소<NA>2023-08-31
34신축2020-04-092020-05-252022-04-30경상남도 거창군 남상면 월평리 1383474.010제2종근린생활시설제조업소<NA><NA><NA><NA>건축사(사)정건축<NA>2023-08-31
45신축2020-04-14<NA><NA>경상남도 거창군 웅양면 노현리 292-2 외4필지524.0210제2종근린생활시설게이트볼장<NA><NA><NA><NA>우성종합건축사사무소<NA>2023-08-31
56신축2020-06-152022-11-182022-06-30경상남도 거창군 거창읍 학리 613137.4430제2종근린생활시설제조업소<NA><NA><NA><NA>건축사사무소그룹정<NA>2023-08-31
67신축2020-07-232020-09-252020-12-26경상남도 거창군 거창읍 서변리 551-2 외5필지479.310제2종근린생활시설게이트볼장4<NA><NA><NA>동광 건축사사무소(주)미라벨종합건설2023-08-31
78신축2020-09-162021-10-282022-10-26경상남도 거창군 거창읍 송정리 1128-190.4510제2종근린생활시설사무소+창고시설<NA><NA><NA><NA>다솔건축사사무소<NA>2023-08-31
89신축2020-09-21<NA><NA>경상남도 거창군 위천면 강천리 114-2503.8810제2종근린생활시설게이트볼장4<NA><NA><NA>동광 건축사사무소<NA>2023-08-31
910신축2020-10-262020-12-182021-12-15경상남도 거창군 거창읍 중앙리 333-1 외2필지125.7810제2종근린생활시설사무소<NA><NA><NA><NA>동광 건축사사무소범창종합건설(주)2023-08-31
번호건축구분허가일착공일(착공예정일)준공일(준공예정일)대지위치연면적(제곱미터)지상층수지하층수주용도부속용도총주차대수세대수가구수공사명(사업계획명)시행사사무소명시공사사무소명데이터작성기준일
3334신축2023-02-02<NA><NA>경상남도 거창군 북상면 갈계리 1011 외2필지1315.5520운동시설게이트볼장(건축법 시행령 별표1 가항목)7<NA><NA><NA>거창종합건축사사무소<NA>2023-08-31
3435신축2023-03-172023-03-272023-12-31경상남도 거창군 거창읍 대동리 684-6 외4필지99.3510제2종근린생활시설일반음식점0<NA><NA><NA>동광 건축사사무소<NA>2023-08-31
3536신축2023-03-28<NA><NA>경상남도 거창군 가조면 일부리 13741031.9940숙박시설일반숙박시설16<NA><NA><NA>거창종합건축사사무소<NA>2023-08-31
3637신축2023-03-302023-04-202024-03-30경상남도 거창군 거창읍 가지리 311300.620제2종근린생활시설제2종근린생활시설 및 단독주택211<NA>신건축사사무소주식회사대경건설2023-08-31
3738신축2023-04-112023-05-262023-09-30경상남도 거창군 거창읍 송정리 360-1161.5410제2종근린생활시설종교집회장2<NA><NA><NA>건축사사무소 모람(주)창동건설2023-08-31
3839신축2023-04-25<NA><NA>경상남도 거창군 남상면 월평리 산 156216.010제2종근린생활시설제조업소+ 부속창고0<NA><NA><NA>건축사(사)정건축<NA>2023-08-31
3940신축2023-05-18<NA><NA>경상남도 거창군 북상면 월성리 1678-299.210제2종근린생활시설일반음식점0<NA><NA><NA>아림신중광건축사사무소<NA>2023-08-31
4041신축2023-06-27<NA><NA>경상남도 거창군 웅양면 신촌리 1151-9 외1필지38.010제2종근린생활시설실내골프연습장0<NA><NA><NA>거창종합건축사사무소<NA>2023-08-31
4142신축2023-08-02<NA><NA>경상남도 거창군 거창읍 송정리 산 7-18376.320제2종근린생활시설일반음식점2<NA>1<NA>신건축사사무소<NA>2023-08-31
4243신축2023-08-25<NA><NA>경상남도 거창군 가조면 수월리 산 33-89165.610제2종근린생활시설일반음식점0<NA><NA><NA>가람종합건축사사무소<NA>2023-08-31