Overview

Dataset statistics

Number of variables11
Number of observations123
Missing cells44
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.2 KiB
Average record size in memory93.1 B

Variable types

Text4
Numeric4
DateTime2
Categorical1

Dataset

Description경기도 구리시 공동주택현황(공동주택명, 위치, 경위도, 동수, 세대수, 연락처, 사용검사일 등)을 제공합니다.
Author경기도 구리시
URLhttps://www.data.go.kr/data/3038641/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 동수High correlation
연락처1 has 22 (17.9%) missing valuesMissing
연락처2 has 22 (17.9%) missing valuesMissing
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:27:25.148096
Analysis finished2023-12-12 17:27:28.043323
Duration2.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공동주택 명칭
Text

Distinct117
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T02:27:28.227199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.7886179
Min length3

Characters and Unicode

Total characters958
Distinct characters174
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)91.1%

Sample

1st row기림주택
2nd row신일주택
3rd row복지빌라
4th row성림빌라
5th row태양파크
ValueCountFrequency (%)
원일아파트 3
 
2.3%
대명아파트 2
 
1.5%
아트빌멘션(동산빌라 2
 
1.5%
채움더힐 2
 
1.5%
원일주택 2
 
1.5%
아파트 2
 
1.5%
수택동 2
 
1.5%
무학율촌마을 1
 
0.8%
인창1차동문굿모닝힐아파트 1
 
0.8%
무학수누피마을 1
 
0.8%
Other values (115) 115
86.5%
2023-12-13T02:27:28.670467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 86
 
9.0%
트 80
 
8.4%
파 75
 
7.8%
빌 20
 
2.1%
인 19
 
2.0%
지 18
 
1.9%
창 16
 
1.7%
스 15
 
1.6%
동 14
 
1.5%
한 14
 
1.5%
Other values (164) 601
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 874
91.2%
Decimal Number 34
 
3.5%
Open Punctuation 12
 
1.3%
Space Separator 12
 
1.3%
Close Punctuation 12
 
1.3%
Lowercase Letter 6
 
0.6%
Uppercase Letter 6
 
0.6%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 86
 
9.8%
트 80
 
9.2%
파 75
 
8.6%
빌 20
 
2.3%
인 19
 
2.2%
지 18
 
2.1%
창 16
 
1.8%
스 15
 
1.7%
동 14
 
1.6%
한 14
 
1.6%
Other values (146) 517
59.2%
Decimal Number
ValueCountFrequency (%)
1 12
35.3%
2 9
26.5%
0 3
 
8.8%
4 3
 
8.8%
3 3
 
8.8%
6 2
 
5.9%
5 2
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
H 2
33.3%
L 2
33.3%
K 1
16.7%
S 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
83.3%
i 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 874
91.2%
Common 72
 
7.5%
Latin 12
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 86
 
9.8%
트 80
 
9.2%
파 75
 
8.6%
빌 20
 
2.3%
인 19
 
2.2%
지 18
 
2.1%
창 16
 
1.8%
스 15
 
1.7%
동 14
 
1.6%
한 14
 
1.6%
Other values (146) 517
59.2%
Common
ValueCountFrequency (%)
( 12
16.7%
12
16.7%
1 12
16.7%
) 12
16.7%
2 9
12.5%
0 3
 
4.2%
4 3
 
4.2%
3 3
 
4.2%
6 2
 
2.8%
5 2
 
2.8%
Other values (2) 2
 
2.8%
Latin
ValueCountFrequency (%)
e 5
41.7%
H 2
 
16.7%
L 2
 
16.7%
K 1
 
8.3%
S 1
 
8.3%
i 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 874
91.2%
ASCII 83
 
8.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 86
 
9.8%
트 80
 
9.2%
파 75
 
8.6%
빌 20
 
2.3%
인 19
 
2.2%
지 18
 
2.1%
창 16
 
1.8%
스 15
 
1.7%
동 14
 
1.6%
한 14
 
1.6%
Other values (146) 517
59.2%
ASCII
ValueCountFrequency (%)
( 12
14.5%
12
14.5%
1 12
14.5%
) 12
14.5%
2 9
10.8%
e 5
6.0%
0 3
 
3.6%
4 3
 
3.6%
3 3
 
3.6%
H 2
 
2.4%
Other values (7) 10
12.0%
None
ValueCountFrequency (%)
· 1
100.0%

위치
Text

UNIQUE 

Distinct123
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T02:27:29.028110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length16.99187
Min length14

Characters and Unicode

Total characters2090
Distinct characters53
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

Unique123 ?
Unique (%)100.0%

Sample

1st row경기도 구리시 수택동 326
2nd row경기도 구리시 수택동 328-1
3rd row경기도 구리시 수택동 276-64
4th row경기도 구리시 수택동 460(수택동 산35-10)
5th row경기도 구리시 수택동 544
ValueCountFrequency (%)
경기도 123
24.6%
구리시 123
24.6%
수택동 46
 
9.2%
인창동 37
 
7.4%
교문동 18
 
3.6%
토평동 9
 
1.8%
2필지 2
 
0.4%
704 2
 
0.4%
506-9 1
 
0.2%
707 1
 
0.2%
Other values (137) 137
27.5%
2023-12-13T02:27:29.593039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
377
18.0%
경 124
 
5.9%
구 124
 
5.9%
기 123
 
5.9%
도 123
 
5.9%
리 123
 
5.9%
시 123
 
5.9%
동 115
 
5.5%
1 71
 
3.4%
6 67
 
3.2%
Other values (43) 720
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1166
55.8%
Decimal Number 475
22.7%
Space Separator 377
 
18.0%
Dash Punctuation 58
 
2.8%
Other Punctuation 6
 
0.3%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 124
10.6%
구 124
10.6%
기 123
10.5%
도 123
10.5%
리 123
10.5%
시 123
10.5%
동 115
9.9%
택 50
 
4.3%
수 50
 
4.3%
인 37
 
3.2%
Other values (28) 174
14.9%
Decimal Number
ValueCountFrequency (%)
1 71
14.9%
6 67
14.1%
4 56
11.8%
8 52
10.9%
5 49
10.3%
2 43
9.1%
7 40
8.4%
0 40
8.4%
9 30
6.3%
3 27
 
5.7%
Space Separator
ValueCountFrequency (%)
377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1166
55.8%
Common 924
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 124
10.6%
구 124
10.6%
기 123
10.5%
도 123
10.5%
리 123
10.5%
시 123
10.5%
동 115
9.9%
택 50
 
4.3%
수 50
 
4.3%
인 37
 
3.2%
Other values (28) 174
14.9%
Common
ValueCountFrequency (%)
377
40.8%
1 71
 
7.7%
6 67
 
7.3%
- 58
 
6.3%
4 56
 
6.1%
8 52
 
5.6%
5 49
 
5.3%
2 43
 
4.7%
7 40
 
4.3%
0 40
 
4.3%
Other values (5) 71
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1166
55.8%
ASCII 924
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
377
40.8%
1 71
 
7.7%
6 67
 
7.3%
- 58
 
6.3%
4 56
 
6.1%
8 52
 
5.6%
5 49
 
5.3%
2 43
 
4.7%
7 40
 
4.3%
0 40
 
4.3%
Other values (5) 71
 
7.7%
Hangul
ValueCountFrequency (%)
경 124
10.6%
구 124
10.6%
기 123
10.5%
도 123
10.5%
리 123
10.5%
시 123
10.5%
동 115
9.9%
택 50
 
4.3%
수 50
 
4.3%
인 37
 
3.2%
Other values (28) 174
14.9%

위도
Real number (ℝ)

Distinct122
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.60149
Minimum37.585942
Maximum37.635666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:27:29.780248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.585942
5-th percentile37.588012
Q137.592579
median37.598767
Q337.607724
95-th percentile37.630063
Maximum37.635666
Range0.049724
Interquartile range (IQR)0.015145

Descriptive statistics

Standard deviation0.011960338
Coefficient of variation (CV)0.00031808148
Kurtosis1.0874898
Mean37.60149
Median Absolute Deviation (MAD)0.006775
Skewness1.2051129
Sum4624.9833
Variance0.00014304968
MonotonicityNot monotonic
2023-12-13T02:27:29.983699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.601447 2
 
1.6%
37.595503 1
 
0.8%
37.612421 1
 
0.8%
37.596505 1
 
0.8%
37.597171 1
 
0.8%
37.605142 1
 
0.8%
37.592641 1
 
0.8%
37.592415 1
 
0.8%
37.596682 1
 
0.8%
37.605732 1
 
0.8%
Other values (112) 112
91.1%
ValueCountFrequency (%)
37.585942 1
0.8%
37.586031 1
0.8%
37.586167 1
0.8%
37.586605 1
0.8%
37.587041 1
0.8%
37.587801 1
0.8%
37.588011 1
0.8%
37.588021 1
0.8%
37.588509 1
0.8%
37.588546 1
0.8%
ValueCountFrequency (%)
37.635666 1
0.8%
37.635619 1
0.8%
37.634826 1
0.8%
37.634798 1
0.8%
37.632153 1
0.8%
37.630539 1
0.8%
37.630151 1
0.8%
37.629269 1
0.8%
37.626023 1
0.8%
37.625473 1
0.8%

경도
Real number (ℝ)

Distinct122
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.1386
Minimum127.111
Maximum127.15452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:27:30.177789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.111
5-th percentile127.11841
Q1127.13383
median127.13879
Q3127.14532
95-th percentile127.14948
Maximum127.15452
Range0.043526
Interquartile range (IQR)0.0114855

Descriptive statistics

Standard deviation0.0089299326
Coefficient of variation (CV)7.0237778 × 10-5
Kurtosis0.90879281
Mean127.1386
Median Absolute Deviation (MAD)0.00574
Skewness-0.87990675
Sum15638.048
Variance7.9743696 × 10-5
MonotonicityNot monotonic
2023-12-13T02:27:30.381625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.148403 2
 
1.6%
127.150102 1
 
0.8%
127.139364 1
 
0.8%
127.142831 1
 
0.8%
127.145202 1
 
0.8%
127.138542 1
 
0.8%
127.141585 1
 
0.8%
127.140398 1
 
0.8%
127.142388 1
 
0.8%
127.132952 1
 
0.8%
Other values (112) 112
91.1%
ValueCountFrequency (%)
127.110995 1
0.8%
127.114692 1
0.8%
127.114994 1
0.8%
127.1156 1
0.8%
127.116855 1
0.8%
127.11714 1
0.8%
127.118292 1
0.8%
127.119519 1
0.8%
127.120878 1
0.8%
127.121078 1
0.8%
ValueCountFrequency (%)
127.154521 1
0.8%
127.153806 1
0.8%
127.153251 1
0.8%
127.152987 1
0.8%
127.152397 1
0.8%
127.150102 1
0.8%
127.149482 1
0.8%
127.149455 1
0.8%
127.149292 1
0.8%
127.149198 1
0.8%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0731707
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:27:30.575728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile13.9
Maximum20
Range19
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.0573163
Coefficient of variation (CV)0.79975946
Kurtosis1.2517857
Mean5.0731707
Median Absolute Deviation (MAD)2
Skewness1.253009
Sum624
Variance16.461815
MonotonicityNot monotonic
2023-12-13T02:27:30.703829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 23
18.7%
2 21
17.1%
5 14
11.4%
4 11
8.9%
3 11
8.9%
7 10
8.1%
6 7
 
5.7%
8 5
 
4.1%
10 4
 
3.3%
12 3
 
2.4%
Other values (7) 14
11.4%
ValueCountFrequency (%)
1 23
18.7%
2 21
17.1%
3 11
8.9%
4 11
8.9%
5 14
11.4%
6 7
 
5.7%
7 10
8.1%
8 5
 
4.1%
9 3
 
2.4%
10 4
 
3.3%
ValueCountFrequency (%)
20 1
 
0.8%
16 2
 
1.6%
15 1
 
0.8%
14 3
2.4%
13 2
 
1.6%
12 3
2.4%
11 2
 
1.6%
10 4
3.3%
9 3
2.4%
8 5
4.1%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean382.15447
Minimum20
Maximum1546
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:27:30.885290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile33.3
Q185
median251
Q3572.5
95-th percentile1076.8
Maximum1546
Range1526
Interquartile range (IQR)487.5

Descriptive statistics

Standard deviation364.74669
Coefficient of variation (CV)0.95444831
Kurtosis0.84913006
Mean382.15447
Median Absolute Deviation (MAD)195
Skewness1.2097399
Sum47005
Variance133040.15
MonotonicityNot monotonic
2023-12-13T02:27:31.092282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 3
 
2.4%
434 2
 
1.6%
1018 2
 
1.6%
85 2
 
1.6%
56 2
 
1.6%
90 2
 
1.6%
99 2
 
1.6%
60 2
 
1.6%
48 2
 
1.6%
299 2
 
1.6%
Other values (99) 102
82.9%
ValueCountFrequency (%)
20 1
0.8%
21 1
0.8%
24 1
0.8%
30 2
1.6%
32 1
0.8%
33 1
0.8%
36 2
1.6%
40 2
1.6%
44 1
0.8%
46 1
0.8%
ValueCountFrequency (%)
1546 1
0.8%
1444 1
0.8%
1408 1
0.8%
1344 1
0.8%
1229 1
0.8%
1196 1
0.8%
1077 1
0.8%
1075 1
0.8%
1033 1
0.8%
1018 2
1.6%

사용검사일
Date

Distinct112
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1979-12-05 00:00:00
Maximum2022-04-27 00:00:00
2023-12-13T02:27:31.283930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:31.476026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연락처1
Text

MISSING 

Distinct97
Distinct (%)96.0%
Missing22
Missing (%)17.9%
Memory size1.1 KiB
2023-12-13T02:27:31.802469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1212
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)93.1%

Sample

1st row031-562-7708
2nd row031-551-2145
3rd row031-563-6101
4th row031-563-6101
5th row031-569-2940
ValueCountFrequency (%)
031-556-6765 3
 
3.0%
031-555-4384 2
 
2.0%
031-563-6101 2
 
2.0%
031-551-9020 1
 
1.0%
031-568-7902 1
 
1.0%
031-562-3132 1
 
1.0%
031-555-4304 1
 
1.0%
031-555-0660 1
 
1.0%
031-554-5111 1
 
1.0%
031-563-1377 1
 
1.0%
Other values (87) 87
86.1%
2023-12-13T02:27:32.229019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 232
19.1%
- 202
16.7%
1 165
13.6%
0 150
12.4%
3 143
11.8%
6 82
 
6.8%
2 62
 
5.1%
4 57
 
4.7%
7 50
 
4.1%
9 37
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1010
83.3%
Dash Punctuation 202
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 232
23.0%
1 165
16.3%
0 150
14.9%
3 143
14.2%
6 82
 
8.1%
2 62
 
6.1%
4 57
 
5.6%
7 50
 
5.0%
9 37
 
3.7%
8 32
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 232
19.1%
- 202
16.7%
1 165
13.6%
0 150
12.4%
3 143
11.8%
6 82
 
6.8%
2 62
 
5.1%
4 57
 
4.7%
7 50
 
4.1%
9 37
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 232
19.1%
- 202
16.7%
1 165
13.6%
0 150
12.4%
3 143
11.8%
6 82
 
6.8%
2 62
 
5.1%
4 57
 
4.7%
7 50
 
4.1%
9 37
 
3.1%

연락처2
Text

MISSING 

Distinct97
Distinct (%)96.0%
Missing22
Missing (%)17.9%
Memory size1.1 KiB
2023-12-13T02:27:32.515297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1212
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)93.1%

Sample

1st row031-562-7709
2nd row031-551-2146
3rd row031-563-6102
4th row031-563-6102
5th row031-569-2941
ValueCountFrequency (%)
031-556-6766 3
 
3.0%
031-555-4385 2
 
2.0%
031-563-6102 2
 
2.0%
031-551-9021 1
 
1.0%
031-568-7903 1
 
1.0%
031-562-3133 1
 
1.0%
031-555-4305 1
 
1.0%
031-555-0661 1
 
1.0%
031-554-5112 1
 
1.0%
031-563-1378 1
 
1.0%
Other values (87) 87
86.1%
2023-12-13T02:27:32.882011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 231
19.1%
- 202
16.7%
1 162
13.4%
3 159
13.1%
0 139
11.5%
6 88
 
7.3%
2 59
 
4.9%
7 49
 
4.0%
4 47
 
3.9%
9 42
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1010
83.3%
Dash Punctuation 202
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 231
22.9%
1 162
16.0%
3 159
15.7%
0 139
13.8%
6 88
 
8.7%
2 59
 
5.8%
7 49
 
4.9%
4 47
 
4.7%
9 42
 
4.2%
8 34
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 231
19.1%
- 202
16.7%
1 162
13.4%
3 159
13.1%
0 139
11.5%
6 88
 
7.3%
2 59
 
4.9%
7 49
 
4.0%
4 47
 
3.9%
9 42
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 231
19.1%
- 202
16.7%
1 162
13.4%
3 159
13.1%
0 139
11.5%
6 88
 
7.3%
2 59
 
4.9%
7 49
 
4.0%
4 47
 
3.9%
9 42
 
3.5%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
경기도 구리시
123 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 구리시
2nd row경기도 구리시
3rd row경기도 구리시
4th row경기도 구리시
5th row경기도 구리시

Common Values

ValueCountFrequency (%)
경기도 구리시 123
100.0%

Length

2023-12-13T02:27:33.011991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:27:33.093790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 123
50.0%
구리시 123
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-01-05 00:00:00
Maximum2023-01-05 00:00:00
2023-12-13T02:27:33.167129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:33.256275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:27:26.949781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:25.560441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:25.952287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.346639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:27.083973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:25.668134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.038842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.455362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:27.167579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:25.750549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.141605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.595196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:27.269176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:25.851139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.244578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:27:26.781677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:27:33.323992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동수세대수연락처1연락처2
위도1.0000.7610.5060.7300.9890.989
경도0.7611.0000.6420.6791.0001.000
동수0.5060.6421.0000.7190.9940.994
세대수0.7300.6790.7191.0001.0001.000
연락처10.9891.0000.9941.0001.0001.000
연락처20.9891.0000.9941.0001.0001.000
2023-12-13T02:27:33.420573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도동수세대수
위도1.000-0.4940.2250.263
경도-0.4941.000-0.322-0.360
동수0.225-0.3221.0000.804
세대수0.263-0.3600.8041.000

Missing values

2023-12-13T02:27:27.406034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:27:27.552156image/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.
2023-12-13T02:27:27.977830image/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

공동주택 명칭위치위도경도동수세대수사용검사일연락처1연락처2관리기관명데이터기준일자
0기림주택경기도 구리시 수택동 32637.595503127.1501026441979-12-05<NA><NA>경기도 구리시2023-01-05
1신일주택경기도 구리시 수택동 328-137.595634127.1494554721983-01-26<NA><NA>경기도 구리시2023-01-05
2복지빌라경기도 구리시 수택동 276-6437.593075127.1482162361983-01-26<NA><NA>경기도 구리시2023-01-05
3성림빌라경기도 구리시 수택동 460(수택동 산35-10)37.594431127.1413383401985-12-13<NA><NA>경기도 구리시2023-01-05
4태양파크경기도 구리시 수택동 54437.600154127.1478072331985-12-18<NA><NA>경기도 구리시2023-01-05
5중앙잉꼬빌라경기도 구리시 수택동 661, 70437.592564127.1447565871985-12-28<NA><NA>경기도 구리시2023-01-05
6잉꼬빌라경기도 구리시 수택동 661-5외 2필지37.591591127.1447791211986-06-19<NA><NA>경기도 구리시2023-01-05
7아트빌멘션(동산빌라)경기도 구리시 수택동 454-17(수택동 산46-51)37.594127127.1453511241986-07-23<NA><NA>경기도 구리시2023-01-05
8아트빌멘션(동산빌라)경기도 구리시 수택동 454-18(수택동 597-2)37.593983127.1454312301986-12-24<NA><NA>경기도 구리시2023-01-05
9성우주택경기도 구리시 수택동 653-4, 660-137.592123127.1436062361986-12-29<NA><NA>경기도 구리시2023-01-05
공동주택 명칭위치위도경도동수세대수사용검사일연락처1연락처2관리기관명데이터기준일자
113푸른솔경기도 구리시 수택동 276-19337.592378127.1465482202020-03-17<NA><NA>경기도 구리시2023-01-05
114해담빌경기도 구리시 수택동 276-6237.592619127.1461371322020-06-01<NA><NA>경기도 구리시2023-01-05
115노블레스빌경기도 구리시 수택동 276-19237.592204127.1461534402020-05-22<NA><NA>경기도 구리시2023-01-05
116한양수자인구리역리버시티경기도 구리시 수택동 88937.602226127.14645874102021-06-30031-554-4785031-554-4786경기도 구리시2023-01-05
117유탑트윈팰리스경기도 구리시 수택동 48137.596236127.14427312992022-01-14031-554-4977031-554-4979경기도 구리시2023-01-05
118구리수택행복주택경기도 구리시 수택동 85237.591352127.14164533942021-08-12031-569-2223031-569-2224경기도 구리시2023-01-05
119클래시움더데라스하우스경기도 구리시 인창동 71537.61735127.14208361322017-06-20031-551-9020031-551-9021경기도 구리시2023-01-05
120동진뱅크빌경기도 구리시 수택동 847-137.592175127.1383521532011-08-11031-564-1136031-565-3133경기도 구리시2023-01-05
121채움더힐경기도 구리시 인창동 616-15외 3필지37.602529127.1306155482022-04-27<NA><NA>경기도 구리시2023-01-05
122채움더힐경기도 구리시 인창동 616-4외 1필지37.602771127.1298854492022-04-27<NA><NA>경기도 구리시2023-01-05