Overview

Dataset statistics

Number of variables14
Number of observations108
Missing cells117
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 KiB
Average record size in memory117.2 B

Variable types

Numeric4
Categorical4
Text3
DateTime3

Dataset

Description경상남도 사천시 관내 건축허가 현황자료(2023년도)로 건축구분, 대지위치 , 대지면적, 건축면적, 연면적, 구조, 허가일, 착공처리일, 사용승인일, 주용도, 설계사무소 설계자 도로명주소, 데이터기준일을 포함하고 있습니다.
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15053245

Alerts

데이터기준일 has constant value ""Constant
대지면적(제곱미터) is highly overall correlated with 건축면적(제곱미터) and 1 other fieldsHigh correlation
건축면적(제곱미터) is highly overall correlated with 대지면적(제곱미터) and 1 other fieldsHigh correlation
연면적(제곱미터) is highly overall correlated with 대지면적(제곱미터) and 1 other fieldsHigh correlation
착공처리일 has 41 (38.0%) missing valuesMissing
사용승인일 has 76 (70.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:04:19.296692
Analysis finished2023-12-10 23:04:22.267105
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:04:22.358425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2023-12-11T08:04:22.516797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

건축구분
Categorical

Distinct4
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size996.0 B
신축
63 
증축
34 
용도변경
9 
대수선
 
2

Length

Max length4
Median length2
Mean length2.1851852
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 63
58.3%
증축 34
31.5%
용도변경 9
 
8.3%
대수선 2
 
1.9%

Length

2023-12-11T08:04:22.695083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:22.823674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 63
58.3%
증축 34
31.5%
용도변경 9
 
8.3%
대수선 2
 
1.9%

대지위치
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:04:23.255969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length21.87037
Min length15

Characters and Unicode

Total characters2362
Distinct characters99
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row경상남도 사천시 벌리동 54-11
2nd row경상남도 사천시 백천동 108-1 외2필지
3rd row경상남도 사천시 동금동 330-9 외1필지
4th row경상남도 사천시 곤양면 환덕리 1360-1 외2필지
5th row경상남도 사천시 사천읍 정의리 1-11
ValueCountFrequency (%)
경상남도 108
20.0%
사천시 108
20.0%
사천읍 20
 
3.7%
외1필지 15
 
2.8%
사남면 13
 
2.4%
축동면 10
 
1.8%
곤양면 10
 
1.8%
외2필지 8
 
1.5%
유천리 8
 
1.5%
향촌동 6
 
1.1%
Other values (167) 235
43.4%
2023-12-11T08:04:23.880256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
433
18.3%
사 148
 
6.3%
천 141
 
6.0%
남 123
 
5.2%
1 111
 
4.7%
경 108
 
4.6%
도 108
 
4.6%
시 108
 
4.6%
상 108
 
4.6%
- 78
 
3.3%
Other values (89) 896
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1401
59.3%
Decimal Number 448
 
19.0%
Space Separator 433
 
18.3%
Dash Punctuation 78
 
3.3%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 148
 
10.6%
천 141
 
10.1%
남 123
 
8.8%
경 108
 
7.7%
도 108
 
7.7%
시 108
 
7.7%
상 108
 
7.7%
리 71
 
5.1%
동 62
 
4.4%
면 45
 
3.2%
Other values (75) 379
27.1%
Decimal Number
ValueCountFrequency (%)
1 111
24.8%
4 54
12.1%
2 49
10.9%
3 44
 
9.8%
5 40
 
8.9%
7 35
 
7.8%
8 35
 
7.8%
0 32
 
7.1%
6 24
 
5.4%
9 24
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
433
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1401
59.3%
Common 959
40.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 148
 
10.6%
천 141
 
10.1%
남 123
 
8.8%
경 108
 
7.7%
도 108
 
7.7%
시 108
 
7.7%
상 108
 
7.7%
리 71
 
5.1%
동 62
 
4.4%
면 45
 
3.2%
Other values (75) 379
27.1%
Common
ValueCountFrequency (%)
433
45.2%
1 111
 
11.6%
- 78
 
8.1%
4 54
 
5.6%
2 49
 
5.1%
3 44
 
4.6%
5 40
 
4.2%
7 35
 
3.6%
8 35
 
3.6%
0 32
 
3.3%
Other values (2) 48
 
5.0%
Latin
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1401
59.3%
ASCII 961
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
433
45.1%
1 111
 
11.6%
- 78
 
8.1%
4 54
 
5.6%
2 49
 
5.1%
3 44
 
4.6%
5 40
 
4.2%
7 35
 
3.6%
8 35
 
3.6%
0 32
 
3.3%
Other values (4) 50
 
5.2%
Hangul
ValueCountFrequency (%)
사 148
 
10.6%
천 141
 
10.1%
남 123
 
8.8%
경 108
 
7.7%
도 108
 
7.7%
시 108
 
7.7%
상 108
 
7.7%
리 71
 
5.1%
동 62
 
4.4%
면 45
 
3.2%
Other values (75) 379
27.1%

대지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13449.895
Minimum82.7
Maximum670815.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:04:24.058325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82.7
5-th percentile196.545
Q1501.25
median1640.55
Q35723.325
95-th percentile30406.775
Maximum670815.3
Range670732.6
Interquartile range (IQR)5222.075

Descriptive statistics

Standard deviation67078.968
Coefficient of variation (CV)4.9873227
Kurtosis88.428924
Mean13449.895
Median Absolute Deviation (MAD)1301
Skewness9.1107908
Sum1452588.7
Variance4.4995879 × 109
MonotonicityNot monotonic
2023-12-11T08:04:24.244346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
496.0 2
 
1.9%
151.4 2
 
1.9%
376.0 2
 
1.9%
260.4 1
 
0.9%
4925.0 1
 
0.9%
10672.0 1
 
0.9%
493.0 1
 
0.9%
559.0 1
 
0.9%
8183.0 1
 
0.9%
976.0 1
 
0.9%
Other values (95) 95
88.0%
ValueCountFrequency (%)
82.7 1
0.9%
83.0 1
0.9%
86.0 1
0.9%
151.4 2
1.9%
182.3 1
0.9%
223.0 1
0.9%
260.4 1
0.9%
272.0 1
0.9%
276.5 1
0.9%
279.4 1
0.9%
ValueCountFrequency (%)
670815.3 1
0.9%
171649.2 1
0.9%
106047.6 1
0.9%
52893.0 1
0.9%
49243.6 1
0.9%
31713.5 1
0.9%
27980.0 1
0.9%
20597.0 1
0.9%
18489.0 1
0.9%
16760.3 1
0.9%

건축면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct106
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4593.1615
Minimum32.6
Maximum207884.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:04:24.429893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32.6
5-th percentile79.3357
Q1176.2425
median421.5
Q31316.6475
95-th percentile10453.451
Maximum207884.28
Range207851.68
Interquartile range (IQR)1140.405

Descriptive statistics

Standard deviation21994.179
Coefficient of variation (CV)4.788462
Kurtosis70.852612
Mean4593.1615
Median Absolute Deviation (MAD)310
Skewness8.042112
Sum496061.44
Variance4.8374392 × 108
MonotonicityNot monotonic
2023-12-11T08:04:24.610828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77.158 2
 
1.9%
992.0 2
 
1.9%
128.8 1
 
0.9%
685.3 1
 
0.9%
1821.46 1
 
0.9%
407.91 1
 
0.9%
643.98 1
 
0.9%
1324.95 1
 
0.9%
231.64 1
 
0.9%
111.1 1
 
0.9%
Other values (96) 96
88.9%
ValueCountFrequency (%)
32.6 1
0.9%
49.5 1
0.9%
51.94 1
0.9%
56.2 1
0.9%
77.158 2
1.9%
83.38 1
0.9%
88.31 1
0.9%
88.44 1
0.9%
111.1 1
0.9%
111.9 1
0.9%
ValueCountFrequency (%)
207884.282 1
0.9%
82855.0 1
0.9%
51146.96 1
0.9%
24876.3 1
0.9%
16577.76 1
0.9%
11025.04 1
0.9%
9391.93 1
0.9%
6499.46 1
0.9%
4993.37 1
0.9%
4535.757 1
0.9%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6510.6316
Minimum51.94
Maximum302614.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:04:24.780847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.94
5-th percentile130.3335
Q1196.085
median695.005
Q32559.9525
95-th percentile11280.096
Maximum302614.19
Range302562.25
Interquartile range (IQR)2363.8675

Descriptive statistics

Standard deviation31596.645
Coefficient of variation (CV)4.8530845
Kurtosis74.129227
Mean6510.6316
Median Absolute Deviation (MAD)551.185
Skewness8.2057994
Sum703148.21
Variance9.9834797 × 108
MonotonicityNot monotonic
2023-12-11T08:04:24.965844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
139.309 2
 
1.9%
198.35 1
 
0.9%
395.33 1
 
0.9%
3757.81 1
 
0.9%
587.25 1
 
0.9%
2026.564 1
 
0.9%
1983.15 1
 
0.9%
922.04 1
 
0.9%
552.77 1
 
0.9%
2447.44 1
 
0.9%
Other values (97) 97
89.8%
ValueCountFrequency (%)
51.94 1
0.9%
56.2 1
0.9%
83.38 1
0.9%
92.23 1
0.9%
114.16 1
0.9%
130.05 1
0.9%
130.86 1
0.9%
132.36 1
0.9%
139.309 2
1.9%
140.85 1
0.9%
ValueCountFrequency (%)
302614.191 1
0.9%
91790.02 1
0.9%
85714.83 1
0.9%
55968.8 1
0.9%
17599.71 1
0.9%
12018.04 1
0.9%
9909.63 1
0.9%
6679.44 1
0.9%
5870.47 1
0.9%
4760.102 1
0.9%

구조
Categorical

Distinct8
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
일반철골구조
41 
철근콘크리트구조
38 
경량철골구조
17 
강파이프구조
5 
일반목구조
 
3
Other values (3)
 
4

Length

Max length11
Median length6
Mean length6.6666667
Min length4

Unique

Unique2 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
일반철골구조 41
38.0%
철근콘크리트구조 38
35.2%
경량철골구조 17
15.7%
강파이프구조 5
 
4.6%
일반목구조 3
 
2.8%
<NA> 2
 
1.9%
벽돌구조 1
 
0.9%
프리케스트콘크리트구조 1
 
0.9%

Length

2023-12-11T08:04:25.150340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:25.294370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반철골구조 41
38.0%
철근콘크리트구조 38
35.2%
경량철골구조 17
15.7%
강파이프구조 5
 
4.6%
일반목구조 3
 
2.8%
na 2
 
1.9%
벽돌구조 1
 
0.9%
프리케스트콘크리트구조 1
 
0.9%

허가일
Date

Distinct79
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum2023-01-03 00:00:00
Maximum2023-10-31 00:00:00
2023-12-11T08:04:25.454006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:25.632528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct46
Distinct (%)68.7%
Missing41
Missing (%)38.0%
Memory size996.0 B
Minimum2023-01-25 00:00:00
Maximum2023-10-26 00:00:00
2023-12-11T08:04:25.789643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:25.951527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

사용승인일
Date

MISSING 

Distinct30
Distinct (%)93.8%
Missing76
Missing (%)70.4%
Memory size996.0 B
Minimum2023-02-03 00:00:00
Maximum2023-10-23 00:00:00
2023-12-11T08:04:26.104475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:26.236931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

주용도
Categorical

Distinct13
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
제2종근린생활시설
24 
공장
22 
제1종근린생활시설
19 
단독주택
14 
창고시설
8 
Other values (8)
21 

Length

Max length9
Median length7
Mean length6.037037
Min length2

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st row제2종근린생활시설
2nd row창고시설
3rd row제2종근린생활시설
4th row동물및식물관련시설
5th row노유자시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 24
22.2%
공장 22
20.4%
제1종근린생활시설 19
17.6%
단독주택 14
13.0%
창고시설 8
 
7.4%
동물및식물관련시설 8
 
7.4%
노유자시설 3
 
2.8%
숙박시설 3
 
2.8%
종교시설 2
 
1.9%
업무시설 2
 
1.9%
Other values (3) 3
 
2.8%

Length

2023-12-11T08:04:26.400984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종근린생활시설 24
22.2%
공장 22
20.4%
제1종근린생활시설 19
17.6%
단독주택 14
13.0%
창고시설 8
 
7.4%
동물및식물관련시설 8
 
7.4%
노유자시설 3
 
2.8%
숙박시설 3
 
2.8%
종교시설 2
 
1.9%
업무시설 2
 
1.9%
Other values (3) 3
 
2.8%

설계사무소명
Text

Distinct63
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:04:26.621272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length9.9444444
Min length7

Characters and Unicode

Total characters1074
Distinct characters103
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)37.0%

Sample

1st row에이플러스건축사사무소
2nd row건축사사무소 강현
3rd row주식회사에이원건축사사무소
4th row기담건축사사무소
5th row우미건축사(사)
ValueCountFrequency (%)
건축사사무소 22
 
16.5%
예림 7
 
5.3%
주)수안건축사사무소 6
 
4.5%
강현 5
 
3.8%
이가건축사사무소 5
 
3.8%
우미건축사(사 4
 
3.0%
에이플러스건축사사무소 3
 
2.3%
으뜸건축사사무소 3
 
2.3%
건축사사무소이건설계 3
 
2.3%
누보건축사사무소 3
 
2.3%
Other values (56) 72
54.1%
2023-12-11T08:04:26.980938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 220
20.5%
건 116
 
10.8%
축 112
 
10.4%
소 104
 
9.7%
무 102
 
9.5%
( 27
 
2.5%
) 27
 
2.5%
25
 
2.3%
주 24
 
2.2%
이 19
 
1.8%
Other values (93) 298
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 992
92.4%
Open Punctuation 27
 
2.5%
Close Punctuation 27
 
2.5%
Space Separator 25
 
2.3%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 220
22.2%
건 116
11.7%
축 112
11.3%
소 104
10.5%
무 102
 
10.3%
주 24
 
2.4%
이 19
 
1.9%
가 13
 
1.3%
우 13
 
1.3%
인 11
 
1.1%
Other values (87) 258
26.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
E 1
33.3%
H 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 992
92.4%
Common 79
 
7.4%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 220
22.2%
건 116
11.7%
축 112
11.3%
소 104
10.5%
무 102
 
10.3%
주 24
 
2.4%
이 19
 
1.9%
가 13
 
1.3%
우 13
 
1.3%
인 11
 
1.1%
Other values (87) 258
26.0%
Common
ValueCountFrequency (%)
( 27
34.2%
) 27
34.2%
25
31.6%
Latin
ValueCountFrequency (%)
M 1
33.3%
E 1
33.3%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 992
92.4%
ASCII 82
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 220
22.2%
건 116
11.7%
축 112
11.3%
소 104
10.5%
무 102
 
10.3%
주 24
 
2.4%
이 19
 
1.9%
가 13
 
1.3%
우 13
 
1.3%
인 11
 
1.1%
Other values (87) 258
26.0%
ASCII
ValueCountFrequency (%)
( 27
32.9%
) 27
32.9%
25
30.5%
M 1
 
1.2%
E 1
 
1.2%
H 1
 
1.2%

설계자 도로명주소
Text

Distinct64
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-11T08:04:27.310224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length27.435185
Min length15

Characters and Unicode

Total characters2963
Distinct characters178
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

Unique42 ?
Unique (%)38.9%

Sample

1st row경상남도 사천시 벌리로 10
2nd row경상남도 사천시 사천읍 서재농청길 49 1층
3rd row부산광역시 수영구 망미번영로38번길 3 5층(광안동)
4th row경상남도 사천시 사천읍 동문로 45 100호 기담건축사사무소
5th row경상남도 사천시 사천읍 구암두문로 15 1층
ValueCountFrequency (%)
경상남도 88
 
13.9%
사천시 55
 
8.7%
진주시 19
 
3.0%
사천읍 17
 
2.7%
2층 14
 
2.2%
1층 14
 
2.2%
부산광역시 13
 
2.0%
용현면 11
 
1.7%
3층 11
 
1.7%
21 9
 
1.4%
Other values (201) 384
60.5%
2023-12-11T08:04:27.814849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
527
 
17.8%
시 120
 
4.0%
1 113
 
3.8%
상 104
 
3.5%
2 100
 
3.4%
사 97
 
3.3%
남 95
 
3.2%
도 93
 
3.1%
경 91
 
3.1%
천 81
 
2.7%
Other values (168) 1542
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1814
61.2%
Space Separator 527
 
17.8%
Decimal Number 522
 
17.6%
Open Punctuation 38
 
1.3%
Close Punctuation 38
 
1.3%
Dash Punctuation 18
 
0.6%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 120
 
6.6%
상 104
 
5.7%
사 97
 
5.3%
남 95
 
5.2%
도 93
 
5.1%
경 91
 
5.0%
천 81
 
4.5%
로 73
 
4.0%
층 57
 
3.1%
길 55
 
3.0%
Other values (150) 948
52.3%
Decimal Number
ValueCountFrequency (%)
1 113
21.6%
2 100
19.2%
3 59
11.3%
0 52
10.0%
4 46
8.8%
5 44
 
8.4%
6 30
 
5.7%
7 26
 
5.0%
9 26
 
5.0%
8 26
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
I 2
33.3%
K 2
33.3%
A 1
16.7%
F 1
16.7%
Space Separator
ValueCountFrequency (%)
527
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1814
61.2%
Common 1143
38.6%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 120
 
6.6%
상 104
 
5.7%
사 97
 
5.3%
남 95
 
5.2%
도 93
 
5.1%
경 91
 
5.0%
천 81
 
4.5%
로 73
 
4.0%
층 57
 
3.1%
길 55
 
3.0%
Other values (150) 948
52.3%
Common
ValueCountFrequency (%)
527
46.1%
1 113
 
9.9%
2 100
 
8.7%
3 59
 
5.2%
0 52
 
4.5%
4 46
 
4.0%
5 44
 
3.8%
( 38
 
3.3%
) 38
 
3.3%
6 30
 
2.6%
Other values (4) 96
 
8.4%
Latin
ValueCountFrequency (%)
I 2
33.3%
K 2
33.3%
A 1
16.7%
F 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1814
61.2%
ASCII 1149
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
527
45.9%
1 113
 
9.8%
2 100
 
8.7%
3 59
 
5.1%
0 52
 
4.5%
4 46
 
4.0%
5 44
 
3.8%
( 38
 
3.3%
) 38
 
3.3%
6 30
 
2.6%
Other values (8) 102
 
8.9%
Hangul
ValueCountFrequency (%)
시 120
 
6.6%
상 104
 
5.7%
사 97
 
5.3%
남 95
 
5.2%
도 93
 
5.1%
경 91
 
5.0%
천 81
 
4.5%
로 73
 
4.0%
층 57
 
3.1%
길 55
 
3.0%
Other values (150) 948
52.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-10-30
108 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-30
2nd row2023-10-30
3rd row2023-10-30
4th row2023-10-30
5th row2023-10-30

Common Values

ValueCountFrequency (%)
2023-10-30 108
100.0%

Length

2023-12-11T08:04:27.974054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:04:28.079273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-30 108
100.0%

Interactions

2023-12-11T08:04:21.148842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.137078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.465410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.826646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:21.239652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.214749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.555706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.902952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:21.329831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.302853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.654081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.984184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:21.410986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.377166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:20.746942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:04:21.064480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:04:28.163581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축구분대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)구조허가일착공처리일사용승인일주용도설계사무소명설계자 도로명주소
연번1.0000.1970.1310.1560.1560.2390.9990.9541.0000.3530.7510.758
건축구분0.1971.0000.0000.0000.0000.3110.7590.9710.9650.6950.7080.726
대지면적(제곱미터)0.1310.0001.0001.0001.0000.0000.7160.000NaN0.0001.0001.000
건축면적(제곱미터)0.1560.0001.0001.0001.0000.6250.8830.000NaN0.0000.9220.920
연면적(제곱미터)0.1560.0001.0001.0001.0000.6250.8830.000NaN0.0000.9220.920
구조0.2390.3110.0000.6250.6251.0000.9250.0001.0000.6900.0000.000
허가일0.9990.7590.7160.8830.8830.9251.0000.9560.9880.6120.9780.978
착공처리일0.9540.9710.0000.0000.0000.0000.9561.0000.9920.9360.8700.851
사용승인일1.0000.965NaNNaNNaN1.0000.9880.9921.0000.9950.9660.966
주용도0.3530.6950.0000.0000.0000.6900.6120.9360.9951.0000.8300.823
설계사무소명0.7510.7081.0000.9220.9220.0000.9780.8700.9660.8301.0001.000
설계자 도로명주소0.7580.7261.0000.9200.9200.0000.9780.8510.9660.8231.0001.000
2023-12-11T08:04:28.314208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도건축구분구조
주용도1.0000.4660.414
건축구분0.4661.0000.214
구조0.4140.2141.000
2023-12-11T08:04:28.403316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)건축구분구조주용도
연번1.000-0.084-0.005-0.0210.1120.1170.148
대지면적(제곱미터)-0.0841.0000.8950.7980.0000.0000.000
건축면적(제곱미터)-0.0050.8951.0000.9390.0000.4610.000
연면적(제곱미터)-0.0210.7980.9391.0000.0000.4610.000
건축구분0.1120.0000.0000.0001.0000.2140.466
구조0.1170.0000.4610.4610.2141.0000.414
주용도0.1480.0000.0000.0000.4660.4141.000

Missing values

2023-12-11T08:04:21.543599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:04:22.076554image/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.
2023-12-11T08:04:22.205900image/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

연번건축구분대지위치대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)구조허가일착공처리일사용승인일주용도설계사무소명설계자 도로명주소데이터기준일
01신축경상남도 사천시 벌리동 54-11260.4128.8198.35철근콘크리트구조2023-10-31<NA><NA>제2종근린생활시설에이플러스건축사사무소경상남도 사천시 벌리로 102023-10-30
12증축경상남도 사천시 백천동 108-1 외2필지12781.01774.952583.15철근콘크리트구조2023-10-30<NA><NA>창고시설건축사사무소 강현경상남도 사천시 사천읍 서재농청길 49 1층2023-10-30
23신축경상남도 사천시 동금동 330-9 외1필지1627.0423.0423.0일반철골구조2023-10-30<NA><NA>제2종근린생활시설주식회사에이원건축사사무소부산광역시 수영구 망미번영로38번길 3 5층(광안동)2023-10-30
34증축경상남도 사천시 곤양면 환덕리 1360-1 외2필지7288.94357.03937.0강파이프구조2023-10-27<NA><NA>동물및식물관련시설기담건축사사무소경상남도 사천시 사천읍 동문로 45 100호 기담건축사사무소2023-10-30
45신축경상남도 사천시 사천읍 정의리 1-11800.0126.94114.16철근콘크리트구조2023-10-25<NA><NA>노유자시설우미건축사(사)경상남도 사천시 사천읍 구암두문로 15 1층2023-10-30
56신축경상남도 사천시 서포면 비토리 14-136504.8263.39479.35철근콘크리트구조2023-10-25<NA><NA>제1종근린생활시설(주)제이유건축사사무소서울특별시 서초구 양재천로 125 한국빌딩 3층2023-10-30
67증축경상남도 사천시 사천읍 장전리 산 73-6 외1필지6967.02109.932109.93경량철골구조2023-10-12<NA><NA>동물및식물관련시설동광 건축사사무소경상남도 거창군 거창읍 거열로 162-1 2층2023-10-30
78신축경상남도 사천시 사천읍 정의리 209-1 외2필지507.0208.35820.17철근콘크리트구조2023-10-11<NA><NA>제1종근린생활시설건축사사무소 예공부산광역시 연제구 과정로 274 3층2023-10-30
89증축경상남도 사천시 용현면 신촌리 588-116588.09391.939909.63일반철골구조2023-09-262023-10-20<NA>공장가원종합건축사사무소경상남도 사천시 사천읍 역사길 11-22 3층(수석리IK타운 )2023-10-30
910용도변경경상남도 사천시 축동면 가산리 405-1297.051.9451.94경량철골구조2023-09-21<NA><NA>단독주택정원씨엠건축사사무소부산광역시 동구 고관로 9 남산빌딩 3F2023-10-30
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