Overview

Dataset statistics

Number of variables9
Number of observations895
Missing cells803
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.7 KiB
Average record size in memory75.1 B

Variable types

Text4
Numeric2
Categorical3

Dataset

Description경상남도 거창군 내 신축 건축물 인허가 정보에 대한 데이터로 허가번호, 건축지역, 연면적, 지상층수, 지하층수, 주용도, 부속용도, 시공사명을 제공합니다.
URLhttps://www.data.go.kr/data/15118769/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
지상층수 is highly overall correlated with 지하층수High correlation
지하층수 is highly overall correlated with 지상층수 and 1 other fieldsHigh correlation
주용도 is highly overall correlated with 지하층수High correlation
지하층수 is highly imbalanced (77.8%)Imbalance
부속용도 has 186 (20.8%) missing valuesMissing
시공사명 has 617 (68.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:56:47.668827
Analysis finished2023-12-12 10:56:49.668063
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Text

Distinct888
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-12T19:56:49.900863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length18.039106
Min length17

Characters and Unicode

Total characters16145
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique881 ?
Unique (%)98.4%

Sample

1st row2023-도시건축과-신축허가-27
2nd row2023-도시건축과-신축허가-26
3rd row2023-도시건축과-협의건축물-6
4th row2023-도시건축과-공용건축물-20
5th row2023-도시건축과-공용건축물-19
ValueCountFrequency (%)
2023-도시건축과-신축허가-4 2
 
0.2%
2023-도시건축과-신축허가-5 2
 
0.2%
2023-도시건축과-신축허가-6 2
 
0.2%
2021-도시건축과-신축허가-2 2
 
0.2%
2023-도시건축과-신축허가-3 2
 
0.2%
2021-도시건축과-신축허가-1 2
 
0.2%
2023-도시건축과-신축허가-2 2
 
0.2%
2017-도시건축과-신축허가-39 1
 
0.1%
2017-도시건축과-신축허가-59 1
 
0.1%
2017-도시건축과-신축허가-60 1
 
0.1%
Other values (878) 878
98.1%
2023-12-12T19:56:50.468497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2685
16.6%
축 1791
11.1%
2 1560
9.7%
0 1122
 
6.9%
1 963
 
6.0%
건 952
 
5.9%
도 895
 
5.5%
시 895
 
5.5%
과 895
 
5.5%
신 839
 
5.2%
Other values (18) 3548
22.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8114
50.3%
Decimal Number 5344
33.1%
Dash Punctuation 2685
 
16.6%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 1791
22.1%
건 952
11.7%
도 895
11.0%
시 895
11.0%
과 895
11.0%
신 839
10.3%
허 838
10.3%
가 838
10.3%
물 57
 
0.7%
협 29
 
0.4%
Other values (5) 85
 
1.0%
Decimal Number
ValueCountFrequency (%)
2 1560
29.2%
0 1122
21.0%
1 963
18.0%
5 283
 
5.3%
6 276
 
5.2%
7 270
 
5.1%
8 259
 
4.8%
3 223
 
4.2%
9 222
 
4.2%
4 166
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 2685
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8114
50.3%
Common 8031
49.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 1791
22.1%
건 952
11.7%
도 895
11.0%
시 895
11.0%
과 895
11.0%
신 839
10.3%
허 838
10.3%
가 838
10.3%
물 57
 
0.7%
협 29
 
0.4%
Other values (5) 85
 
1.0%
Common
ValueCountFrequency (%)
- 2685
33.4%
2 1560
19.4%
0 1122
14.0%
1 963
 
12.0%
5 283
 
3.5%
6 276
 
3.4%
7 270
 
3.4%
8 259
 
3.2%
3 223
 
2.8%
9 222
 
2.8%
Other values (3) 168
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8114
50.3%
ASCII 8031
49.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2685
33.4%
2 1560
19.4%
0 1122
14.0%
1 963
 
12.0%
5 283
 
3.5%
6 276
 
3.4%
7 270
 
3.4%
8 259
 
3.2%
3 223
 
2.8%
9 222
 
2.8%
Other values (3) 168
 
2.1%
Hangul
ValueCountFrequency (%)
축 1791
22.1%
건 952
11.7%
도 895
11.0%
시 895
11.0%
과 895
11.0%
신 839
10.3%
허 838
10.3%
가 838
10.3%
물 57
 
0.7%
협 29
 
0.4%
Other values (5) 85
 
1.0%

건축지역
Text

Distinct894
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-12T19:56:50.881433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length23.22905
Min length18

Characters and Unicode

Total characters20790
Distinct characters114
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

Unique893 ?
Unique (%)99.8%

Sample

1st row경상남도 거창군 거창읍 송정리 산 7-18
2nd row경상남도 거창군 주상면 연교리 404-4
3rd row경상남도 거창군 거창읍 대평리 1362-7
4th row경상남도 거창군 거창읍 대평리 1497-3
5th row경상남도 거창군 웅양면 노현리 217-10
ValueCountFrequency (%)
경상남도 895
18.9%
거창군 895
18.9%
거창읍 556
 
11.7%
송정리 158
 
3.3%
외1필지 131
 
2.8%
가지리 85
 
1.8%
남상면 80
 
1.7%
상림리 77
 
1.6%
가조면 72
 
1.5%
대동리 72
 
1.5%
Other values (966) 1714
36.2%
2023-12-12T19:56:51.591114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3840
18.5%
거 1454
 
7.0%
창 1451
 
7.0%
상 1116
 
5.4%
1 1092
 
5.3%
남 1004
 
4.8%
리 922
 
4.4%
도 908
 
4.4%
군 896
 
4.3%
경 895
 
4.3%
Other values (104) 7212
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12358
59.4%
Decimal Number 3929
 
18.9%
Space Separator 3840
 
18.5%
Dash Punctuation 660
 
3.2%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 1454
11.8%
창 1451
11.7%
상 1116
 
9.0%
남 1004
 
8.1%
리 922
 
7.5%
도 908
 
7.3%
군 896
 
7.3%
경 895
 
7.2%
읍 556
 
4.5%
면 339
 
2.7%
Other values (89) 2817
22.8%
Decimal Number
ValueCountFrequency (%)
1 1092
27.8%
2 443
11.3%
3 358
 
9.1%
4 349
 
8.9%
5 331
 
8.4%
6 328
 
8.3%
8 277
 
7.1%
9 260
 
6.6%
0 252
 
6.4%
7 239
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
3840
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 660
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12358
59.4%
Common 8429
40.5%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 1454
11.8%
창 1451
11.7%
상 1116
 
9.0%
남 1004
 
8.1%
리 922
 
7.5%
도 908
 
7.3%
군 896
 
7.3%
경 895
 
7.2%
읍 556
 
4.5%
면 339
 
2.7%
Other values (89) 2817
22.8%
Common
ValueCountFrequency (%)
3840
45.6%
1 1092
 
13.0%
- 660
 
7.8%
2 443
 
5.3%
3 358
 
4.2%
4 349
 
4.1%
5 331
 
3.9%
6 328
 
3.9%
8 277
 
3.3%
9 260
 
3.1%
Other values (2) 491
 
5.8%
Latin
ValueCountFrequency (%)
A 1
33.3%
B 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12358
59.4%
ASCII 8432
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3840
45.5%
1 1092
 
13.0%
- 660
 
7.8%
2 443
 
5.3%
3 358
 
4.2%
4 349
 
4.1%
5 331
 
3.9%
6 328
 
3.9%
8 277
 
3.3%
9 260
 
3.1%
Other values (5) 494
 
5.9%
Hangul
ValueCountFrequency (%)
거 1454
11.8%
창 1451
11.7%
상 1116
 
9.0%
남 1004
 
8.1%
리 922
 
7.5%
도 908
 
7.3%
군 896
 
7.3%
경 895
 
7.2%
읍 556
 
4.5%
면 339
 
2.7%
Other values (89) 2817
22.8%

연면적(제곱미터)
Real number (ℝ)

Distinct830
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean771.85005
Minimum104.67
Maximum17472.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-12T19:56:51.869520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104.67
5-th percentile140
Q1199.84
median428.36
Q3907.16
95-th percentile2309.143
Maximum17472.19
Range17367.52
Interquartile range (IQR)707.32

Descriptive statistics

Standard deviation1139.4137
Coefficient of variation (CV)1.4762111
Kurtosis77.925083
Mean771.85005
Median Absolute Deviation (MAD)248.51
Skewness6.8906516
Sum690805.8
Variance1298263.5
MonotonicityNot monotonic
2023-12-12T19:56:52.154650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
152.422 13
 
1.5%
152.07 8
 
0.9%
167.24 5
 
0.6%
129.38 5
 
0.6%
500.44 4
 
0.4%
1375.0 3
 
0.3%
199.84 3
 
0.3%
1500.0 3
 
0.3%
1250.0 3
 
0.3%
492.8 2
 
0.2%
Other values (820) 846
94.5%
ValueCountFrequency (%)
104.67 1
0.1%
105.57 1
0.1%
106.75 1
0.1%
112.43 1
0.1%
113.1 1
0.1%
113.22 1
0.1%
113.81 1
0.1%
115.39 1
0.1%
116.05 1
0.1%
117.0 1
0.1%
ValueCountFrequency (%)
17472.1902 1
0.1%
14308.2745 1
0.1%
8153.82 1
0.1%
7744.44 1
0.1%
6198.1221 1
0.1%
5478.07 1
0.1%
4848.08 1
0.1%
4782.74 1
0.1%
4532.09 1
0.1%
4395.2835 1
0.1%

지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1117318
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-12T19:56:52.387514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6167561
Coefficient of variation (CV)0.76560672
Kurtosis46.5331
Mean2.1117318
Median Absolute Deviation (MAD)1
Skewness5.4083354
Sum1890
Variance2.6139002
MonotonicityNot monotonic
2023-12-12T19:56:53.104615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 342
38.2%
2 304
34.0%
3 168
18.8%
4 58
 
6.5%
5 9
 
1.0%
6 3
 
0.3%
13 2
 
0.2%
20 2
 
0.2%
14 1
 
0.1%
12 1
 
0.1%
Other values (5) 5
 
0.6%
ValueCountFrequency (%)
1 342
38.2%
2 304
34.0%
3 168
18.8%
4 58
 
6.5%
5 9
 
1.0%
6 3
 
0.3%
7 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
10 1
 
0.1%
ValueCountFrequency (%)
20 2
0.2%
15 1
 
0.1%
14 1
 
0.1%
13 2
0.2%
12 1
 
0.1%
10 1
 
0.1%
9 1
 
0.1%
8 1
 
0.1%
7 1
 
0.1%
6 3
0.3%

지하층수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
0
863 
1
 
32

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 863
96.4%
1 32
 
3.6%

Length

2023-12-12T19:56:53.320549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:53.494971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 863
96.4%
1 32
 
3.6%

주용도
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
단독주택
338 
동물및식물관련시설
186 
제2종근린생활시설
117 
제1종근린생활시설
110 
창고시설
45 
Other values (13)
99 

Length

Max length9
Median length7
Mean length6.2815642
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row제2종근린생활시설
2nd row동물및식물관련시설
3rd row교육연구시설
4th row단독주택
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 338
37.8%
동물및식물관련시설 186
20.8%
제2종근린생활시설 117
 
13.1%
제1종근린생활시설 110
 
12.3%
창고시설 45
 
5.0%
공장 35
 
3.9%
공동주택 13
 
1.5%
숙박시설 11
 
1.2%
노유자시설 10
 
1.1%
업무시설 7
 
0.8%
Other values (8) 23
 
2.6%

Length

2023-12-12T19:56:53.725847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 338
37.8%
동물및식물관련시설 186
20.8%
제2종근린생활시설 117
 
13.1%
제1종근린생활시설 110
 
12.3%
창고시설 45
 
5.0%
공장 35
 
3.9%
공동주택 13
 
1.5%
숙박시설 11
 
1.2%
노유자시설 10
 
1.1%
자동차관련시설 7
 
0.8%
Other values (8) 23
 
2.6%

부속용도
Text

MISSING 

Distinct295
Distinct (%)41.6%
Missing186
Missing (%)20.8%
Memory size7.1 KiB
2023-12-12T19:56:54.031546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length31
Mean length7.0662906
Min length2

Characters and Unicode

Total characters5010
Distinct characters189
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique237 ?
Unique (%)33.4%

Sample

1st row일반음식점
2nd row우사
3rd row연구소
4th row다가구주택, 근린생활시설
5th row우체국
ValueCountFrequency (%)
다가구주택 109
 
13.0%
단독주택 84
 
10.0%
우사 49
 
5.8%
축사 39
 
4.6%
및 36
 
4.3%
축사-우사 32
 
3.8%
소매점 29
 
3.4%
일반음식점 18
 
2.1%
다가구 18
 
2.1%
축사(우사 15
 
1.8%
Other values (263) 412
49.0%
2023-12-12T19:56:54.609947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 332
 
6.6%
주 288
 
5.7%
택 276
 
5.5%
, 207
 
4.1%
가 183
 
3.7%
구 177
 
3.5%
다 173
 
3.5%
소 166
 
3.3%
점 144
 
2.9%
단 134
 
2.7%
Other values (179) 2930
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4284
85.5%
Other Punctuation 221
 
4.4%
Space Separator 134
 
2.7%
Open Punctuation 116
 
2.3%
Close Punctuation 115
 
2.3%
Decimal Number 86
 
1.7%
Dash Punctuation 43
 
0.9%
Uppercase Letter 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 332
 
7.7%
주 288
 
6.7%
택 276
 
6.4%
가 183
 
4.3%
구 177
 
4.1%
다 173
 
4.0%
소 166
 
3.9%
점 144
 
3.4%
단 134
 
3.1%
독 133
 
3.1%
Other values (158) 2278
53.2%
Uppercase Letter
ValueCountFrequency (%)
E 3
27.3%
T 3
27.3%
S 1
 
9.1%
O 1
 
9.1%
W 1
 
9.1%
R 1
 
9.1%
A 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 42
48.8%
2 37
43.0%
0 3
 
3.5%
3 2
 
2.3%
8 1
 
1.2%
5 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 207
93.7%
/ 8
 
3.6%
: 4
 
1.8%
. 2
 
0.9%
Space Separator
ValueCountFrequency (%)
134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4284
85.5%
Common 715
 
14.3%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 332
 
7.7%
주 288
 
6.7%
택 276
 
6.4%
가 183
 
4.3%
구 177
 
4.1%
다 173
 
4.0%
소 166
 
3.9%
점 144
 
3.4%
단 134
 
3.1%
독 133
 
3.1%
Other values (158) 2278
53.2%
Common
ValueCountFrequency (%)
, 207
29.0%
134
18.7%
( 116
16.2%
) 115
16.1%
- 43
 
6.0%
1 42
 
5.9%
2 37
 
5.2%
/ 8
 
1.1%
: 4
 
0.6%
0 3
 
0.4%
Other values (4) 6
 
0.8%
Latin
ValueCountFrequency (%)
E 3
27.3%
T 3
27.3%
S 1
 
9.1%
O 1
 
9.1%
W 1
 
9.1%
R 1
 
9.1%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4284
85.5%
ASCII 726
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 332
 
7.7%
주 288
 
6.7%
택 276
 
6.4%
가 183
 
4.3%
구 177
 
4.1%
다 173
 
4.0%
소 166
 
3.9%
점 144
 
3.4%
단 134
 
3.1%
독 133
 
3.1%
Other values (158) 2278
53.2%
ASCII
ValueCountFrequency (%)
, 207
28.5%
134
18.5%
( 116
16.0%
) 115
15.8%
- 43
 
5.9%
1 42
 
5.8%
2 37
 
5.1%
/ 8
 
1.1%
: 4
 
0.6%
E 3
 
0.4%
Other values (11) 17
 
2.3%

시공사명
Text

MISSING 

Distinct144
Distinct (%)51.8%
Missing617
Missing (%)68.9%
Memory size7.1 KiB
2023-12-12T19:56:55.000835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length9
Mean length8.5431655
Min length4

Characters and Unicode

Total characters2375
Distinct characters143
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

Unique106 ?
Unique (%)38.1%

Sample

1st row(주)동하산업개발
2nd row주식회사 태영개발공사
3rd row(주)창동건설
4th row(주)한반도건설
5th row주식회사대경건설
ValueCountFrequency (%)
주)산양종합개발 26
 
8.8%
주)유림종합건설 26
 
8.8%
주식회사 15
 
5.1%
창희종합건설(주 10
 
3.4%
주)진성 8
 
2.7%
부경종합건설(주 8
 
2.7%
정은종합건설(주 8
 
2.7%
주식회사오주건설 6
 
2.0%
주)만경종합건설 5
 
1.7%
주)강산 4
 
1.4%
Other values (138) 180
60.8%
2023-12-12T19:56:55.564604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 280
 
11.8%
) 225
 
9.5%
( 225
 
9.5%
건 212
 
8.9%
설 191
 
8.0%
종 170
 
7.2%
합 170
 
7.2%
회 48
 
2.0%
사 48
 
2.0%
식 46
 
1.9%
Other values (133) 760
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1895
79.8%
Close Punctuation 225
 
9.5%
Open Punctuation 225
 
9.5%
Space Separator 18
 
0.8%
Lowercase Letter 6
 
0.3%
Other Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 280
14.8%
건 212
 
11.2%
설 191
 
10.1%
종 170
 
9.0%
합 170
 
9.0%
회 48
 
2.5%
사 48
 
2.5%
식 46
 
2.4%
산 41
 
2.2%
개 36
 
1.9%
Other values (121) 653
34.5%
Lowercase Letter
ValueCountFrequency (%)
d 2
33.3%
o 2
33.3%
t 1
16.7%
i 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
L 1
33.3%
Y 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 225
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1895
79.8%
Common 471
 
19.8%
Latin 9
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 280
14.8%
건 212
 
11.2%
설 191
 
10.1%
종 170
 
9.0%
합 170
 
9.0%
회 48
 
2.5%
사 48
 
2.5%
식 46
 
2.4%
산 41
 
2.2%
개 36
 
1.9%
Other values (121) 653
34.5%
Latin
ValueCountFrequency (%)
d 2
22.2%
o 2
22.2%
C 1
11.1%
L 1
11.1%
t 1
11.1%
Y 1
11.1%
i 1
11.1%
Common
ValueCountFrequency (%)
) 225
47.8%
( 225
47.8%
18
 
3.8%
. 2
 
0.4%
, 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1895
79.8%
ASCII 480
 
20.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 280
14.8%
건 212
 
11.2%
설 191
 
10.1%
종 170
 
9.0%
합 170
 
9.0%
회 48
 
2.5%
사 48
 
2.5%
식 46
 
2.4%
산 41
 
2.2%
개 36
 
1.9%
Other values (121) 653
34.5%
ASCII
ValueCountFrequency (%)
) 225
46.9%
( 225
46.9%
18
 
3.8%
d 2
 
0.4%
o 2
 
0.4%
. 2
 
0.4%
C 1
 
0.2%
, 1
 
0.2%
L 1
 
0.2%
t 1
 
0.2%
Other values (2) 2
 
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-08-16
895 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-16
2nd row2023-08-16
3rd row2023-08-16
4th row2023-08-16
5th row2023-08-16

Common Values

ValueCountFrequency (%)
2023-08-16 895
100.0%

Length

2023-12-12T19:56:55.782552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:55.941829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-16 895
100.0%

Interactions

2023-12-12T19:56:48.801561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:48.394889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:48.980320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:48.566702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:56:56.067963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(제곱미터)지상층수지하층수주용도
연면적(제곱미터)1.0000.7120.4470.589
지상층수0.7121.0000.5030.765
지하층수0.4470.5031.0000.685
주용도0.5890.7650.6851.000
2023-12-12T19:56:56.215901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도지하층수
주용도1.0000.545
지하층수0.5451.000
2023-12-12T19:56:56.358767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(제곱미터)지상층수지하층수주용도
연면적(제곱미터)1.000-0.1360.4770.309
지상층수-0.1361.0000.5030.363
지하층수0.4770.5031.0000.545
주용도0.3090.3630.5451.000

Missing values

2023-12-12T19:56:49.220341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:56:49.415326image/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.
2023-12-12T19:56:49.570452image/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

허가번호건축지역연면적(제곱미터)지상층수지하층수주용도부속용도시공사명데이터기준일자
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12023-도시건축과-신축허가-26경상남도 거창군 주상면 연교리 404-41370.010동물및식물관련시설우사<NA>2023-08-16
22023-도시건축과-협의건축물-6경상남도 거창군 거창읍 대평리 1362-7117.010교육연구시설연구소<NA>2023-08-16
32023-도시건축과-공용건축물-20경상남도 거창군 거창읍 대평리 1497-3969.5840단독주택다가구주택, 근린생활시설<NA>2023-08-16
42023-도시건축과-공용건축물-19경상남도 거창군 웅양면 노현리 217-10255.110제1종근린생활시설우체국(주)동하산업개발2023-08-16
52023-도시건축과-신축허가-24경상남도 거창군 거창읍 대평리 1189168.7720단독주택단독주택<NA>2023-08-16
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72023-도시건축과-신축허가-22경상남도 거창군 거창읍 대동리 679-24166.6520단독주택단독주택<NA>2023-08-16
82023-도시건축과-공용건축물-18경상남도 거창군 거창읍 상림리 92 외2필지1127.3940제1종근린생활시설노유자시설주식회사 태영개발공사2023-08-16
92023-도시건축과-신축허가-21경상남도 거창군 거창읍 양평리 796 외1필지239.9520단독주택<NA><NA>2023-08-16
허가번호건축지역연면적(제곱미터)지상층수지하층수주용도부속용도시공사명데이터기준일자
8852015-도시건축과-신축허가-11경상남도 거창군 마리면 말흘리 217-15489.4430제2종근린생활시설<NA><NA>2023-08-16
8862015-도시건축과-신축허가-10경상남도 거창군 거창읍 대평리 1000-1 외6필지693.3820운수시설여객자동처터미널주식회사환웅종합건설2023-08-16
8872015-도시건축과-신축허가-9경상남도 거창군 남상면 대산리 1599-41848.7610공장사무실,저온창고주식회사유림종합건설2023-08-16
8882015-도시건축과-신축허가-8경상남도 거창군 주상면 도평리 750-3223.1820제2종근린생활시설일반음식점<NA>2023-08-16
8892015-도시건축과-신축허가-7경상남도 거창군 거창읍 대동리 95-16184.8920제2종근린생활시설일반음식점 및 단독주택<NA>2023-08-16
8902015-도시건축과-신축허가-5경상남도 거창군 남상면 대산리 1596 외1필지1992.010공장<NA>해드림종합건설(주)2023-08-16
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