Overview

Dataset statistics

Number of variables8
Number of observations75
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory67.8 B

Variable types

Categorical3
Text3
Numeric2

Dataset

Description충청남도 공주시 경로당 현황에 대한 데이터로 (경로당명, 도로명주소, 지번주소, 건축년도,데이터기준일자) 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=438&beforeMenuCd=DOM_000000201001001000&publicdatapk=15029444

Alerts

데이터기준일자 has constant value ""Constant
경로당명 has unique valuesUnique
면적(㎡) has unique valuesUnique

Reproduction

Analysis started2024-01-09 19:51:08.193047
Analysis finished2024-01-09 19:51:08.976252
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct4
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
신관동
25 
금학동
17 
월송동
17 
웅진동
16 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신관동 25
33.3%
금학동 17
22.7%
월송동 17
22.7%
웅진동 16
21.3%

Length

2024-01-10T04:51:09.027089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:51:09.105960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신관동 25
33.3%
금학동 17
22.7%
월송동 17
22.7%
웅진동 16
21.3%

경로당명
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T04:51:09.308159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.36
Min length2

Characters and Unicode

Total characters402
Distinct characters109
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

Unique75 ?
Unique (%)100.0%

Sample

1st row교동
2nd row교동1.5통
3rd row교동대우(아)
4th row금성2통
5th row금성3통비둘기(아)
ValueCountFrequency (%)
교동 1
 
1.3%
주공2단지(아 1
 
1.3%
한아름(아 1
 
1.3%
한빛아파트 1
 
1.3%
주공6단지(아 1
 
1.3%
주공5단지(아 1
 
1.3%
주공4차(아 1
 
1.3%
주공4단지(아)(남 1
 
1.3%
주공3단지(아 1
 
1.3%
주공1단지(아 1
 
1.3%
Other values (66) 66
86.8%
2024-01-10T04:51:09.624884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
통 28
 
7.0%
( 24
 
6.0%
아 24
 
6.0%
) 24
 
6.0%
동 18
 
4.5%
2 16
 
4.0%
1 11
 
2.7%
금 9
 
2.2%
성 9
 
2.2%
주 8
 
2.0%
Other values (99) 231
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
76.1%
Decimal Number 42
 
10.4%
Open Punctuation 24
 
6.0%
Close Punctuation 24
 
6.0%
Other Punctuation 3
 
0.7%
Space Separator 1
 
0.2%
Dash Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 28
 
9.2%
아 24
 
7.8%
동 18
 
5.9%
금 9
 
2.9%
성 9
 
2.9%
주 8
 
2.6%
대 8
 
2.6%
공 7
 
2.3%
현 7
 
2.3%
트 6
 
2.0%
Other values (86) 182
59.5%
Decimal Number
ValueCountFrequency (%)
2 16
38.1%
1 11
26.2%
4 6
 
14.3%
3 4
 
9.5%
5 3
 
7.1%
6 2
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
76.1%
Common 95
 
23.6%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 28
 
9.2%
아 24
 
7.8%
동 18
 
5.9%
금 9
 
2.9%
성 9
 
2.9%
주 8
 
2.6%
대 8
 
2.6%
공 7
 
2.3%
현 7
 
2.3%
트 6
 
2.0%
Other values (86) 182
59.5%
Common
ValueCountFrequency (%)
( 24
25.3%
) 24
25.3%
2 16
16.8%
1 11
11.6%
4 6
 
6.3%
3 4
 
4.2%
5 3
 
3.2%
6 2
 
2.1%
. 2
 
2.1%
1
 
1.1%
Other values (2) 2
 
2.1%
Latin
ValueCountFrequency (%)
E 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
76.1%
ASCII 96
 
23.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
통 28
 
9.2%
아 24
 
7.8%
동 18
 
5.9%
금 9
 
2.9%
성 9
 
2.9%
주 8
 
2.6%
대 8
 
2.6%
공 7
 
2.3%
현 7
 
2.3%
트 6
 
2.0%
Other values (86) 182
59.5%
ASCII
ValueCountFrequency (%)
( 24
25.0%
) 24
25.0%
2 16
16.7%
1 11
11.5%
4 6
 
6.2%
3 4
 
4.2%
5 3
 
3.1%
6 2
 
2.1%
. 2
 
2.1%
1
 
1.0%
Other values (3) 3
 
3.1%

도로명주소
Text

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T04:51:09.877706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length20.173333
Min length14

Characters and Unicode

Total characters1513
Distinct characters133
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)97.3%

Sample

1st row충청남도 공주시 향교1길 12-1
2nd row충청남도 공주시 교동1길 5, D-1004 교동(아))
3rd row충청남도 공주시 무령로 169-5, 104동 지하
4th row충청남도 공주시 정자방2길 12
5th row충청남도 공주시 정자방1길 30-3, A-106 (비둘기(아))
ValueCountFrequency (%)
충청남도 75
23.4%
공주시 75
23.4%
신금1길 5
 
1.6%
공주대학로 4
 
1.2%
신금2길 4
 
1.2%
관골2길 4
 
1.2%
월송동현로 3
 
0.9%
월미동길 2
 
0.6%
번영1로 2
 
0.6%
10 2
 
0.6%
Other values (131) 145
45.2%
2024-01-10T04:51:10.230505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
16.4%
공 84
 
5.6%
주 82
 
5.4%
시 78
 
5.2%
남 76
 
5.0%
청 76
 
5.0%
1 76
 
5.0%
충 75
 
5.0%
도 75
 
5.0%
길 58
 
3.8%
Other values (123) 585
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 878
58.0%
Decimal Number 287
 
19.0%
Space Separator 248
 
16.4%
Dash Punctuation 45
 
3.0%
Close Punctuation 20
 
1.3%
Open Punctuation 19
 
1.3%
Other Punctuation 12
 
0.8%
Uppercase Letter 3
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 84
 
9.6%
주 82
 
9.3%
시 78
 
8.9%
남 76
 
8.7%
청 76
 
8.7%
충 75
 
8.5%
도 75
 
8.5%
길 58
 
6.6%
로 17
 
1.9%
동 14
 
1.6%
Other values (104) 243
27.7%
Decimal Number
ValueCountFrequency (%)
1 76
26.5%
2 34
11.8%
4 34
11.8%
3 32
11.1%
0 29
 
10.1%
5 24
 
8.4%
8 18
 
6.3%
7 17
 
5.9%
9 12
 
4.2%
6 11
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
D 1
33.3%
E 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 878
58.0%
Common 631
41.7%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 84
 
9.6%
주 82
 
9.3%
시 78
 
8.9%
남 76
 
8.7%
청 76
 
8.7%
충 75
 
8.5%
도 75
 
8.5%
길 58
 
6.6%
로 17
 
1.9%
동 14
 
1.6%
Other values (104) 243
27.7%
Common
ValueCountFrequency (%)
248
39.3%
1 76
 
12.0%
- 45
 
7.1%
2 34
 
5.4%
4 34
 
5.4%
3 32
 
5.1%
0 29
 
4.6%
5 24
 
3.8%
) 20
 
3.2%
( 19
 
3.0%
Other values (5) 70
 
11.1%
Latin
ValueCountFrequency (%)
D 1
25.0%
E 1
25.0%
A 1
25.0%
a 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 878
58.0%
ASCII 635
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
39.1%
1 76
 
12.0%
- 45
 
7.1%
2 34
 
5.4%
4 34
 
5.4%
3 32
 
5.0%
0 29
 
4.6%
5 24
 
3.8%
) 20
 
3.1%
( 19
 
3.0%
Other values (9) 74
 
11.7%
Hangul
ValueCountFrequency (%)
공 84
 
9.6%
주 82
 
9.3%
시 78
 
8.9%
남 76
 
8.7%
청 76
 
8.7%
충 75
 
8.5%
도 75
 
8.5%
길 58
 
6.6%
로 17
 
1.9%
동 14
 
1.6%
Other values (104) 243
27.7%

지번주소
Text

Distinct74
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2024-01-10T04:51:10.444722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length20.96
Min length14

Characters and Unicode

Total characters1572
Distinct characters102
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

Unique73 ?
Unique (%)97.3%

Sample

1st row충청남도 공주시 교동 183-8
2nd row충청남도 공주시 교동 3-76 교동(아) D-1004
3rd row충청남도 공주시 교동 157-5 104동 지하
4th row충청남도 공주시 금성동 89-29
5th row충청남도 공주시 금성동 99-5
ValueCountFrequency (%)
충청남도 75
22.4%
공주시 75
22.4%
신관동 25
 
7.5%
금학동 6
 
1.8%
웅진동 5
 
1.5%
금흥동 4
 
1.2%
교동 4
 
1.2%
산성동 3
 
0.9%
오곡동 3
 
0.9%
태봉동 3
 
0.9%
Other values (127) 132
39.4%
2024-01-10T04:51:10.783659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
16.9%
동 80
 
5.1%
공 79
 
5.0%
주 79
 
5.0%
청 76
 
4.8%
남 76
 
4.8%
시 75
 
4.8%
충 75
 
4.8%
도 75
 
4.8%
1 74
 
4.7%
Other values (92) 618
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
57.0%
Decimal Number 331
 
21.1%
Space Separator 265
 
16.9%
Dash Punctuation 61
 
3.9%
Uppercase Letter 12
 
0.8%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 80
 
8.9%
공 79
 
8.8%
주 79
 
8.8%
청 76
 
8.5%
남 76
 
8.5%
시 75
 
8.4%
충 75
 
8.4%
도 75
 
8.4%
관 32
 
3.6%
신 26
 
2.9%
Other values (72) 223
24.9%
Decimal Number
ValueCountFrequency (%)
1 74
22.4%
2 45
13.6%
6 34
10.3%
4 33
10.0%
3 32
9.7%
0 28
 
8.5%
9 23
 
6.9%
5 22
 
6.6%
8 21
 
6.3%
7 19
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
A 6
50.0%
T 2
 
16.7%
P 2
 
16.7%
E 1
 
8.3%
D 1
 
8.3%
Space Separator
ValueCountFrequency (%)
265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
57.0%
Common 664
42.2%
Latin 12
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 80
 
8.9%
공 79
 
8.8%
주 79
 
8.8%
청 76
 
8.5%
남 76
 
8.5%
시 75
 
8.4%
충 75
 
8.4%
도 75
 
8.4%
관 32
 
3.6%
신 26
 
2.9%
Other values (72) 223
24.9%
Common
ValueCountFrequency (%)
265
39.9%
1 74
 
11.1%
- 61
 
9.2%
2 45
 
6.8%
6 34
 
5.1%
4 33
 
5.0%
3 32
 
4.8%
0 28
 
4.2%
9 23
 
3.5%
5 22
 
3.3%
Other values (5) 47
 
7.1%
Latin
ValueCountFrequency (%)
A 6
50.0%
T 2
 
16.7%
P 2
 
16.7%
E 1
 
8.3%
D 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
57.0%
ASCII 676
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
39.2%
1 74
 
10.9%
- 61
 
9.0%
2 45
 
6.7%
6 34
 
5.0%
4 33
 
4.9%
3 32
 
4.7%
0 28
 
4.1%
9 23
 
3.4%
5 22
 
3.3%
Other values (10) 59
 
8.7%
Hangul
ValueCountFrequency (%)
동 80
 
8.9%
공 79
 
8.8%
주 79
 
8.8%
청 76
 
8.5%
남 76
 
8.5%
시 75
 
8.4%
충 75
 
8.4%
도 75
 
8.4%
관 32
 
3.6%
신 26
 
2.9%
Other values (72) 223
24.9%

건축년도
Real number (ℝ)

Distinct27
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.9067
Minimum1974
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T04:51:11.093035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1974
5-th percentile1988.7
Q11994
median1998
Q32007
95-th percentile2014
Maximum2017
Range43
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.6120176
Coefficient of variation (CV)0.0043062097
Kurtosis-0.012722844
Mean1999.9067
Median Absolute Deviation (MAD)7
Skewness-0.099384204
Sum149993
Variance74.166847
MonotonicityNot monotonic
2024-01-10T04:51:11.174812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1998 6
 
8.0%
1997 6
 
8.0%
1996 5
 
6.7%
2009 5
 
6.7%
2007 5
 
6.7%
1989 4
 
5.3%
1992 4
 
5.3%
1999 4
 
5.3%
2006 4
 
5.3%
1994 4
 
5.3%
Other values (17) 28
37.3%
ValueCountFrequency (%)
1974 1
 
1.3%
1982 1
 
1.3%
1987 1
 
1.3%
1988 1
 
1.3%
1989 4
5.3%
1990 1
 
1.3%
1991 2
2.7%
1992 4
5.3%
1993 2
2.7%
1994 4
5.3%
ValueCountFrequency (%)
2017 3
4.0%
2014 2
 
2.7%
2012 2
 
2.7%
2010 2
 
2.7%
2009 5
6.7%
2008 2
 
2.7%
2007 5
6.7%
2006 4
5.3%
2005 2
 
2.7%
2004 1
 
1.3%

면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90.125333
Minimum21.33
Maximum222.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2024-01-10T04:51:11.269077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.33
5-th percentile45.988
Q170.08
median85.1
Q3100.95
95-th percentile149.817
Maximum222.41
Range201.08
Interquartile range (IQR)30.87

Descriptive statistics

Standard deviation34.202734
Coefficient of variation (CV)0.37950188
Kurtosis4.4606754
Mean90.125333
Median Absolute Deviation (MAD)16.46
Skewness1.5498432
Sum6759.4
Variance1169.827
MonotonicityNot monotonic
2024-01-10T04:51:11.375755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
183.96 1
 
1.3%
73.0 1
 
1.3%
89.04 1
 
1.3%
25.0 1
 
1.3%
89.38 1
 
1.3%
68.54 1
 
1.3%
84.6 1
 
1.3%
113.79 1
 
1.3%
59.99 1
 
1.3%
56.0 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
21.33 1
1.3%
25.0 1
1.3%
42.0 1
1.3%
44.0 1
1.3%
46.84 1
1.3%
53.34 1
1.3%
55.42 1
1.3%
56.0 1
1.3%
58.0 1
1.3%
59.99 1
1.3%
ValueCountFrequency (%)
222.41 1
1.3%
210.31 1
1.3%
183.96 1
1.3%
167.03 1
1.3%
142.44 1
1.3%
138.75 1
1.3%
122.29 1
1.3%
120.75 1
1.3%
113.94 1
1.3%
113.79 1
1.3%

소유자
Categorical

Distinct5
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
마을회
35 
아파트
26 
공주시
9 
노인회
4 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0133333
Min length3

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
마을회 35
46.7%
아파트 26
34.7%
공주시 9
 
12.0%
노인회 4
 
5.3%
<NA> 1
 
1.3%

Length

2024-01-10T04:51:11.479557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:51:11.560485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회 35
46.7%
아파트 26
34.7%
공주시 9
 
12.0%
노인회 4
 
5.3%
na 1
 
1.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
2018-05-09
75 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-05-09
2nd row2018-05-09
3rd row2018-05-09
4th row2018-05-09
5th row2018-05-09

Common Values

ValueCountFrequency (%)
2018-05-09 75
100.0%

Length

2024-01-10T04:51:11.647018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:51:11.720344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-05-09 75
100.0%

Interactions

2024-01-10T04:51:08.685527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:51:08.569367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:51:08.747217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:51:08.622186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T04:51:11.772397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동경로당명도로명주소지번주소건축년도면적(㎡)소유자
읍면동1.0001.0001.0001.0000.0230.0000.517
경로당명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0000.9741.000
지번주소1.0001.0001.0001.0001.0000.9741.000
건축년도0.0231.0001.0001.0001.0000.2130.522
면적(㎡)0.0001.0000.9740.9740.2131.0000.000
소유자0.5171.0001.0001.0000.5220.0001.000
2024-01-10T04:51:11.852007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동소유자
읍면동1.0000.221
소유자0.2211.000
2024-01-10T04:51:11.914326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축년도면적(㎡)읍면동소유자
건축년도1.0000.1730.0410.228
면적(㎡)0.1731.0000.0000.000
읍면동0.0410.0001.0000.221
소유자0.2280.0000.2211.000

Missing values

2024-01-10T04:51:08.847333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:51:08.940366image/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

읍면동경로당명도로명주소지번주소건축년도면적(㎡)소유자데이터기준일자
0웅진동교동충청남도 공주시 향교1길 12-1충청남도 공주시 교동 183-82017183.96<NA>2018-05-09
1웅진동교동1.5통충청남도 공주시 교동1길 5, D-1004 교동(아))충청남도 공주시 교동 3-76 교동(아) D-1004198279.9노인회2018-05-09
2웅진동교동대우(아)충청남도 공주시 무령로 169-5, 104동 지하충청남도 공주시 교동 157-5 104동 지하1999113.94아파트2018-05-09
3웅진동금성2통충청남도 공주시 정자방2길 12충청남도 공주시 금성동 89-29199681.47마을회2018-05-09
4웅진동금성3통비둘기(아)충청남도 공주시 정자방1길 30-3, A-106 (비둘기(아))충청남도 공주시 금성동 99-5200684.94아파트2018-05-09
5웅진동산성1통충청남도 공주시 남문길 13, 101-102 (덕성공원빌리지)충청남도 공주시 덕성공원빌리지 101동 지하층102호200199.45아파트2018-05-09
6웅진동산성2통충청남도 공주시 고개마을길 24충청남도 공주시 산성동 31-69199661.65마을회2018-05-09
7웅진동산성찬호길충청남도 공주시 산성찬호길 25-1충청남도 공주시 산성동 28-1200977.52공주시2018-05-09
8웅진동웅진1통충청남도 공주시 관광단지길 47충청남도 공주시 웅진동 354-1200698.4마을회2018-05-09
9웅진동웅진2통충청남도 공주시 장승배기길 3-1충청남도 공주시 웅진동 6641997102.23마을회2018-05-09
읍면동경로당명도로명주소지번주소건축년도면적(㎡)소유자데이터기준일자
65월송동석장리동(남)충청남도 공주시 석장리길 87충청남도 공주시 석장리 170-1199683.2마을회2018-05-09
66월송동석장리동(여)충청남도 공주시 석장리길 88-35충청남도 공주시 석장리동 126-11992103.23공주시2018-05-09
67월송동송선1통충청남도 공주시 장척로 43-28충청남도 공주시 송선1리 642-6199896.0마을회2018-05-09
68월송동송선2통충청남도 공주시 요동길 76충청남도 공주시 송선2통 489-1201465.7마을회2018-05-09
69월송동우남퍼스트빌실버충청남도 공주시 한적2길 51-14충청남도 공주시 금흥동 602 우남퍼스트빌 실버룸2010222.41아파트2018-05-09
70월송동월송동충청남도 공주시 월송동현로 109충청남도 공주시 월송동 430-32014138.75마을회2018-05-09
71월송동월송동사송정충청남도 공주시 명탄서원길 58충청남도 공주시 월송동242-1200999.06마을회2018-05-09
72월송동현대4차(아)충청남도 공주시 신금1길 98충청남도 공주시 금흥동 259 현대4차아파트199995.0아파트2018-05-09
73월송동현대힐스테이트충청남도 공주시 신금2길 17 현대5차아파트관리동충청남도 공주시 신관동 668 현대5차아파트관리동2007120.75아파트2018-05-09
74월송동금흥1통충청남도 공주시 한적2길 47-22충청남도 공주시 금흥동612-6201774.4공주시2018-05-09