Overview

Dataset statistics

Number of variables10
Number of observations215
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.0 KiB
Average record size in memory85.6 B

Variable types

Text3
Numeric5
DateTime1
Categorical1

Dataset

Description경상남도 거창군 관내 공동주택에 대한 데이터로 공동주택명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 동수, 층수, 세대수, 준공일을 제공합니다.
Author경상남도 거창군
URLhttps://www.data.go.kr/data/15006053/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
층수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 층수High correlation

Reproduction

Analysis started2023-12-12 10:24:44.348677
Analysis finished2023-12-12 10:24:47.428610
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공동주택명
Text

Distinct214
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T19:24:47.626202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length6.0651163
Min length2

Characters and Unicode

Total characters1304
Distinct characters205
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

Unique213 ?
Unique (%)99.1%

Sample

1st row상동연립가동
2nd row상동연립나동
3rd row상동연립다동
4th row상동연립라동
5th row비둘기아파트
ValueCountFrequency (%)
무지개맨션 5
 
2.0%
a 4
 
1.6%
상림빌라 4
 
1.6%
b동 3
 
1.2%
b 3
 
1.2%
거열빌라 3
 
1.2%
그린빌 3
 
1.2%
동원2차 3
 
1.2%
아림빌라 2
 
0.8%
늘푸른빌 2
 
0.8%
Other values (212) 217
87.1%
2023-12-12T19:24:48.049097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 90
 
6.9%
아 77
 
5.9%
동 60
 
4.6%
라 59
 
4.5%
트 58
 
4.4%
파 50
 
3.8%
34
 
2.6%
차 33
 
2.5%
주 27
 
2.1%
지 24
 
1.8%
Other values (195) 792
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1144
87.7%
Decimal Number 62
 
4.8%
Uppercase Letter 35
 
2.7%
Space Separator 34
 
2.6%
Close Punctuation 13
 
1.0%
Open Punctuation 13
 
1.0%
Dash Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 90
 
7.9%
아 77
 
6.7%
동 60
 
5.2%
라 59
 
5.2%
트 58
 
5.1%
파 50
 
4.4%
차 33
 
2.9%
주 27
 
2.4%
지 24
 
2.1%
대 23
 
2.0%
Other values (178) 643
56.2%
Decimal Number
ValueCountFrequency (%)
2 17
27.4%
1 16
25.8%
3 9
14.5%
0 8
12.9%
5 6
 
9.7%
4 4
 
6.5%
8 1
 
1.6%
7 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
B 14
40.0%
A 13
37.1%
C 6
17.1%
G 2
 
5.7%
Space Separator
ValueCountFrequency (%)
34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1144
87.7%
Common 125
 
9.6%
Latin 35
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 90
 
7.9%
아 77
 
6.7%
동 60
 
5.2%
라 59
 
5.2%
트 58
 
5.1%
파 50
 
4.4%
차 33
 
2.9%
주 27
 
2.4%
지 24
 
2.1%
대 23
 
2.0%
Other values (178) 643
56.2%
Common
ValueCountFrequency (%)
34
27.2%
2 17
13.6%
1 16
12.8%
) 13
 
10.4%
( 13
 
10.4%
3 9
 
7.2%
0 8
 
6.4%
5 6
 
4.8%
4 4
 
3.2%
- 2
 
1.6%
Other values (3) 3
 
2.4%
Latin
ValueCountFrequency (%)
B 14
40.0%
A 13
37.1%
C 6
17.1%
G 2
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1144
87.7%
ASCII 160
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 90
 
7.9%
아 77
 
6.7%
동 60
 
5.2%
라 59
 
5.2%
트 58
 
5.1%
파 50
 
4.4%
차 33
 
2.9%
주 27
 
2.4%
지 24
 
2.1%
대 23
 
2.0%
Other values (178) 643
56.2%
ASCII
ValueCountFrequency (%)
34
21.2%
2 17
10.6%
1 16
10.0%
B 14
8.8%
) 13
 
8.1%
( 13
 
8.1%
A 13
 
8.1%
3 9
 
5.6%
0 8
 
5.0%
C 6
 
3.8%
Other values (7) 17
10.6%

소재지도로명주소
Text

Distinct194
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T19:24:48.425235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length21.102326
Min length18

Characters and Unicode

Total characters4537
Distinct characters63
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

Unique179 ?
Unique (%)83.3%

Sample

1st row경상남도 거창군 거창읍 죽전길 24-17
2nd row경상남도 거창군 거창읍 죽전길 24-17
3rd row경상남도 거창군 거창읍 죽전길 24-17
4th row경상남도 거창군 거창읍 죽전길 24-17
5th row경상남도 거창군 거창읍 거열로1길 11
ValueCountFrequency (%)
경상남도 215
19.9%
거창군 215
19.9%
거창읍 208
19.3%
거열로4길 17
 
1.6%
거열로1길 13
 
1.2%
강변로 11
 
1.0%
거열로 11
 
1.0%
거열로2길 10
 
0.9%
죽전2길 8
 
0.7%
13 7
 
0.6%
Other values (220) 365
33.8%
2023-12-12T19:24:48.971312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
865
19.1%
거 496
 
10.9%
창 441
 
9.7%
남 230
 
5.1%
상 225
 
5.0%
군 215
 
4.7%
경 215
 
4.7%
도 215
 
4.7%
읍 208
 
4.6%
길 181
 
4.0%
Other values (53) 1246
27.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2891
63.7%
Space Separator 865
 
19.1%
Decimal Number 721
 
15.9%
Dash Punctuation 60
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 496
17.2%
창 441
15.3%
남 230
8.0%
상 225
7.8%
군 215
7.4%
경 215
7.4%
도 215
7.4%
읍 208
7.2%
길 181
 
6.3%
로 108
 
3.7%
Other values (41) 357
12.3%
Decimal Number
ValueCountFrequency (%)
1 156
21.6%
2 107
14.8%
4 101
14.0%
3 81
11.2%
5 61
 
8.5%
6 53
 
7.4%
7 51
 
7.1%
8 41
 
5.7%
9 38
 
5.3%
0 32
 
4.4%
Space Separator
ValueCountFrequency (%)
865
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2891
63.7%
Common 1646
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 496
17.2%
창 441
15.3%
남 230
8.0%
상 225
7.8%
군 215
7.4%
경 215
7.4%
도 215
7.4%
읍 208
7.2%
길 181
 
6.3%
로 108
 
3.7%
Other values (41) 357
12.3%
Common
ValueCountFrequency (%)
865
52.6%
1 156
 
9.5%
2 107
 
6.5%
4 101
 
6.1%
3 81
 
4.9%
5 61
 
3.7%
- 60
 
3.6%
6 53
 
3.2%
7 51
 
3.1%
8 41
 
2.5%
Other values (2) 70
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2891
63.7%
ASCII 1646
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
865
52.6%
1 156
 
9.5%
2 107
 
6.5%
4 101
 
6.1%
3 81
 
4.9%
5 61
 
3.7%
- 60
 
3.6%
6 53
 
3.2%
7 51
 
3.1%
8 41
 
2.5%
Other values (2) 70
 
4.3%
Hangul
ValueCountFrequency (%)
거 496
17.2%
창 441
15.3%
남 230
8.0%
상 225
7.8%
군 215
7.4%
경 215
7.4%
도 215
7.4%
읍 208
7.2%
길 181
 
6.3%
로 108
 
3.7%
Other values (41) 357
12.3%

소재지지번주소
Text

Distinct213
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T19:24:49.351349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length21.348837
Min length18

Characters and Unicode

Total characters4590
Distinct characters45
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

Unique211 ?
Unique (%)98.1%

Sample

1st row경상남도 거창군 거창읍 상림리 13-19
2nd row경상남도 거창군 거창읍 상림리 13-18
3rd row경상남도 거창군 거창읍 상림리 13-17
4th row경상남도 거창군 거창읍 상림리 13-13
5th row경상남도 거창군 거창읍 대동리 693-1
ValueCountFrequency (%)
경상남도 215
20.0%
거창군 215
20.0%
거창읍 208
19.3%
대동리 71
 
6.6%
상림리 48
 
4.5%
중앙리 35
 
3.3%
대평리 19
 
1.8%
김천리 18
 
1.7%
가지리 14
 
1.3%
가조면 6
 
0.6%
Other values (215) 226
21.0%
2023-12-12T19:24:49.865652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
860
18.7%
거 423
 
9.2%
창 423
 
9.2%
상 265
 
5.8%
경 215
 
4.7%
남 215
 
4.7%
도 215
 
4.7%
군 215
 
4.7%
리 214
 
4.7%
읍 208
 
4.5%
Other values (35) 1337
29.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2798
61.0%
Space Separator 860
 
18.7%
Decimal Number 774
 
16.9%
Dash Punctuation 158
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 423
15.1%
창 423
15.1%
상 265
9.5%
경 215
7.7%
남 215
7.7%
도 215
7.7%
군 215
7.7%
리 214
7.6%
읍 208
7.4%
대 90
 
3.2%
Other values (23) 315
11.3%
Decimal Number
ValueCountFrequency (%)
1 156
20.2%
2 103
13.3%
3 101
13.0%
5 77
9.9%
4 71
9.2%
6 69
8.9%
9 54
 
7.0%
8 52
 
6.7%
7 52
 
6.7%
0 39
 
5.0%
Space Separator
ValueCountFrequency (%)
860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2798
61.0%
Common 1792
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 423
15.1%
창 423
15.1%
상 265
9.5%
경 215
7.7%
남 215
7.7%
도 215
7.7%
군 215
7.7%
리 214
7.6%
읍 208
7.4%
대 90
 
3.2%
Other values (23) 315
11.3%
Common
ValueCountFrequency (%)
860
48.0%
- 158
 
8.8%
1 156
 
8.7%
2 103
 
5.7%
3 101
 
5.6%
5 77
 
4.3%
4 71
 
4.0%
6 69
 
3.9%
9 54
 
3.0%
8 52
 
2.9%
Other values (2) 91
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2798
61.0%
ASCII 1792
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
860
48.0%
- 158
 
8.8%
1 156
 
8.7%
2 103
 
5.7%
3 101
 
5.6%
5 77
 
4.3%
4 71
 
4.0%
6 69
 
3.9%
9 54
 
3.0%
8 52
 
2.9%
Other values (2) 91
 
5.1%
Hangul
ValueCountFrequency (%)
거 423
15.1%
창 423
15.1%
상 265
9.5%
경 215
7.7%
남 215
7.7%
도 215
7.7%
군 215
7.7%
리 214
7.6%
읍 208
7.4%
대 90
 
3.2%
Other values (23) 315
11.3%

위도
Real number (ℝ)

Distinct191
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.689927
Minimum35.673038
Maximum35.875126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T19:24:50.004730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.673038
5-th percentile35.678929
Q135.685459
median35.689447
Q335.69231
95-th percentile35.695265
Maximum35.875126
Range0.20208806
Interquartile range (IQR)0.00685044

Descriptive statistics

Standard deviation0.014010861
Coefficient of variation (CV)0.00039257185
Kurtosis143.89201
Mean35.689927
Median Absolute Deviation (MAD)0.00323864
Skewness10.929987
Sum7673.3343
Variance0.00019630422
MonotonicityNot monotonic
2023-12-12T19:24:50.156255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.68992534 4
 
1.9%
35.69310247 4
 
1.9%
35.68728568 3
 
1.4%
35.68352625 3
 
1.4%
35.6931808 2
 
0.9%
35.68945665 2
 
0.9%
35.68359021 2
 
0.9%
35.69011922 2
 
0.9%
35.69545691 2
 
0.9%
35.68739662 2
 
0.9%
Other values (181) 189
87.9%
ValueCountFrequency (%)
35.67303793 1
0.5%
35.6757868 1
0.5%
35.67579688 1
0.5%
35.67602241 1
0.5%
35.67644016 1
0.5%
35.67652596 1
0.5%
35.67670997 1
0.5%
35.6770135 1
0.5%
35.67715229 1
0.5%
35.67790883 1
0.5%
ValueCountFrequency (%)
35.87512599 1
0.5%
35.7125401 2
0.9%
35.71215841 1
0.5%
35.71140868 1
0.5%
35.71083457 1
0.5%
35.70886356 1
0.5%
35.69550212 1
0.5%
35.69545691 2
0.9%
35.69541269 1
0.5%
35.69520126 1
0.5%

경도
Real number (ℝ)

Distinct191
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.91548
Minimum127.89072
Maximum128.02015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T19:24:50.362262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.89072
5-th percentile127.90037
Q1127.90812
median127.91344
Q3127.91827
95-th percentile127.92493
Maximum128.02015
Range0.1294274
Interquartile range (IQR)0.0101536

Descriptive statistics

Standard deviation0.018857141
Coefficient of variation (CV)0.00014741876
Kurtosis22.524252
Mean127.91548
Median Absolute Deviation (MAD)0.005058
Skewness4.4907303
Sum27501.828
Variance0.00035559176
MonotonicityNot monotonic
2023-12-12T19:24:50.613701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.9081157 4
 
1.9%
127.9134433 4
 
1.9%
127.890722 3
 
1.4%
127.8993494 3
 
1.4%
127.9142603 2
 
0.9%
127.9075233 2
 
0.9%
127.9207651 2
 
0.9%
127.908328 2
 
0.9%
127.9065963 2
 
0.9%
127.9066347 2
 
0.9%
Other values (181) 189
87.9%
ValueCountFrequency (%)
127.890722 3
1.4%
127.8985443 1
 
0.5%
127.8991042 1
 
0.5%
127.8993176 1
 
0.5%
127.8993494 3
1.4%
127.8995973 1
 
0.5%
127.8999226 1
 
0.5%
127.9005546 1
 
0.5%
127.9006909 1
 
0.5%
127.9007139 1
 
0.5%
ValueCountFrequency (%)
128.0201494 2
0.9%
128.0185581 1
0.5%
128.0184054 1
0.5%
128.0169467 1
0.5%
128.0151892 1
0.5%
127.9278013 1
0.5%
127.9262892 1
0.5%
127.9255349 2
0.9%
127.9251893 1
0.5%
127.9248256 1
0.5%

동수
Real number (ℝ)

Distinct9
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3348837
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T19:24:50.841656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2.3
Maximum11
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2340352
Coefficient of variation (CV)0.92445145
Kurtosis28.777267
Mean1.3348837
Median Absolute Deviation (MAD)0
Skewness5.061337
Sum287
Variance1.5228429
MonotonicityNot monotonic
2023-12-12T19:24:51.040590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 187
87.0%
2 17
 
7.9%
6 4
 
1.9%
3 2
 
0.9%
4 1
 
0.5%
11 1
 
0.5%
5 1
 
0.5%
7 1
 
0.5%
9 1
 
0.5%
ValueCountFrequency (%)
1 187
87.0%
2 17
 
7.9%
3 2
 
0.9%
4 1
 
0.5%
5 1
 
0.5%
6 4
 
1.9%
7 1
 
0.5%
9 1
 
0.5%
11 1
 
0.5%
ValueCountFrequency (%)
11 1
 
0.5%
9 1
 
0.5%
7 1
 
0.5%
6 4
 
1.9%
5 1
 
0.5%
4 1
 
0.5%
3 2
 
0.9%
2 17
 
7.9%
1 187
87.0%

층수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1534884
Minimum2
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T19:24:51.195446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q14
median5
Q310
95-th percentile15
Maximum25
Range23
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.7191868
Coefficient of variation (CV)0.65970426
Kurtosis0.89754446
Mean7.1534884
Median Absolute Deviation (MAD)2
Skewness1.1954734
Sum1538
Variance22.270724
MonotonicityNot monotonic
2023-12-12T19:24:51.382280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4 52
24.2%
3 30
14.0%
5 27
12.6%
10 18
 
8.4%
15 16
 
7.4%
2 12
 
5.6%
6 11
 
5.1%
13 9
 
4.2%
12 8
 
3.7%
9 7
 
3.3%
Other values (9) 25
11.6%
ValueCountFrequency (%)
2 12
 
5.6%
3 30
14.0%
4 52
24.2%
5 27
12.6%
6 11
 
5.1%
7 7
 
3.3%
8 4
 
1.9%
9 7
 
3.3%
10 18
 
8.4%
11 2
 
0.9%
ValueCountFrequency (%)
25 1
 
0.5%
23 1
 
0.5%
22 1
 
0.5%
20 2
 
0.9%
18 2
 
0.9%
15 16
7.4%
14 5
 
2.3%
13 9
4.2%
12 8
3.7%
11 2
 
0.9%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)29.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.330233
Minimum2
Maximum677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T19:24:51.826085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q18.5
median17
Q329.5
95-th percentile191
Maximum677
Range675
Interquartile range (IQR)21

Descriptive statistics

Standard deviation93.684935
Coefficient of variation (CV)2.1133418
Kurtosis18.408389
Mean44.330233
Median Absolute Deviation (MAD)9
Skewness4.167545
Sum9531
Variance8776.8671
MonotonicityNot monotonic
2023-12-12T19:24:51.976763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 30
 
14.0%
19 23
 
10.7%
18 19
 
8.8%
16 13
 
6.0%
6 12
 
5.6%
12 11
 
5.1%
15 7
 
3.3%
9 6
 
2.8%
17 6
 
2.8%
29 6
 
2.8%
Other values (54) 82
38.1%
ValueCountFrequency (%)
2 1
 
0.5%
3 2
 
0.9%
4 5
 
2.3%
5 1
 
0.5%
6 12
 
5.6%
7 3
 
1.4%
8 30
14.0%
9 6
 
2.8%
10 5
 
2.3%
11 2
 
0.9%
ValueCountFrequency (%)
677 1
0.5%
501 1
0.5%
455 1
0.5%
450 1
0.5%
445 1
0.5%
404 1
0.5%
388 1
0.5%
373 1
0.5%
366 1
0.5%
284 1
0.5%

준공일
Date

Distinct205
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1982-08-27 00:00:00
Maximum2023-07-27 00:00:00
2023-12-12T19:24:52.171667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:52.344486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-09-27
215 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-27
2nd row2023-09-27
3rd row2023-09-27
4th row2023-09-27
5th row2023-09-27

Common Values

ValueCountFrequency (%)
2023-09-27 215
100.0%

Length

2023-12-12T19:24:52.509175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:24:52.617399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-27 215
100.0%

Interactions

2023-12-12T19:24:46.713820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:44.695269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.245850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.758235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.188955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.809174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:44.805628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.359213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.854509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.286020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.901598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:44.915397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.478086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.943491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.418624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.984201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.029510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.567801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.020254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.519261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:47.098804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.133842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:45.652270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.099173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:24:46.616086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:24:52.702788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동수층수세대수
위도1.0000.3430.0000.0000.000
경도0.3431.0000.2020.0000.199
동수0.0000.2021.0000.7160.978
층수0.0000.0000.7161.0000.811
세대수0.0000.1990.9780.8111.000
2023-12-12T19:24:52.837003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동수층수세대수
위도1.0000.1790.006-0.0280.001
경도0.1791.0000.0340.0790.054
동수0.0060.0341.0000.1550.306
층수-0.0280.0790.1551.0000.783
세대수0.0010.0540.3060.7831.000

Missing values

2023-12-12T19:24:47.229211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:24:47.375614image/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.

Sample

공동주택명소재지도로명주소소재지지번주소위도경도동수층수세대수준공일데이터기준일자
0상동연립가동경상남도 거창군 거창읍 죽전길 24-17경상남도 거창군 거창읍 상림리 13-1935.689925127.90811613181982-08-272023-09-27
1상동연립나동경상남도 거창군 거창읍 죽전길 24-17경상남도 거창군 거창읍 상림리 13-1835.689925127.90811613151982-08-272023-09-27
2상동연립다동경상남도 거창군 거창읍 죽전길 24-17경상남도 거창군 거창읍 상림리 13-1735.689925127.90811613121982-08-312023-09-27
3상동연립라동경상남도 거창군 거창읍 죽전길 24-17경상남도 거창군 거창읍 상림리 13-1335.689925127.90811613181982-08-312023-09-27
4비둘기아파트경상남도 거창군 거창읍 거열로1길 11경상남도 거창군 거창읍 대동리 693-135.691287127.91426313261983-10-172023-09-27
5송화아파트경상남도 거창군 거창읍 죽전4길 31경상남도 거창군 거창읍 중앙리 394-735.691269127.91043713181984-07-192023-09-27
6쌍용아파트경상남도 거창군 거창읍 거열로1길 17경상남도 거창군 거창읍 대동리 684-235.691407127.9139751381984-09-172023-09-27
7개나리아파트경상남도 거창군 거창읍 죽전2길 7경상남도 거창군 거창읍 중앙리 339-135.689825127.91013923171984-09-282023-09-27
8목화맨션아파트경상남도 거창군 거창읍 거열로 4길 24경상남도 거창군 거창읍 상림리 12-435.690003127.90771815301985-10-182023-09-27
9거창중앙아파트(흥국주택)경상남도 거창군 거창읍 중앙로1길 20-15경상남도 거창군 거창읍 대동리 844-1435.687885127.91468713181986-11-172023-09-27
공동주택명소재지도로명주소소재지지번주소위도경도동수층수세대수준공일데이터기준일자
205유빌리지3차경상남도 거창군 거창읍 강양5길 61-3경상남도 거창군 거창읍 대동리 5735.689447127.918453110182017-10-132023-09-27
206푸르지오경상남도 거창군 거창읍 송정2길 33경상남도 거창군 거창읍 송정리 109735.682102127.8995979256772018-01-102023-09-27
207지엔지5차경상남도 거창군 거창읍 거열로1길 100-24경상남도 거창군 거창읍 중앙리 2-2135.69421127.911771115292018-03-092023-09-27
208트윈빌경상남도 거창군 가조면 월포2길 31경상남도 거창군 가조면 수월리 491-635.711409128.01840525162018-05-102023-09-27
209나리안길 105동경상남도 거창군 거창읍 거열로1길 92경상남도 거창군 거창읍 중앙리 2-435.693692127.911919115292018-09-142023-09-27
210휴앤인더라움경상남도 거창군 거창읍 거열로4길 145경상남도 거창군 거창읍 가지리 28235.694776127.905577113682021-04-292023-09-27
211정은캐슬경상남도 거창군 거창읍 거열로4길 145-11경상남도 거창군 거창읍 가지리 27835.694228127.906474113292022-01-252023-09-27
212헤리티지경상남도 거창군 거창읍 하동3길 12경상남도 거창군 거창읍 중앙리 74-1외2필지35.688708127.914154113292023-06-142023-09-27
213나리안길 107동경상남도 거창군 거창읍 거열로1길 62-30경상남도 거창군 거창읍 대동리 57135.694439127.913736213482023-07-052023-09-27
214더센트럴캐슬경상남도 거창군 거창읍 강변로 149경상남도 거창군 거창읍 중앙리 21235.685565127.913192120942023-07-272023-09-27