Overview

Dataset statistics

Number of variables10
Number of observations65
Missing cells60
Missing cells (%)9.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory85.0 B

Variable types

Text3
Categorical3
Numeric3
DateTime1

Dataset

Description대전광역시 대덕구 소재 도시공원 내의 야외등 설치 현황 데이터로 공원명, 공원종류, 소재지지번주소, 위도, 경도, 야외등 개수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15081492/fileData.do

Alerts

관리청 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 행정동High correlation
야외등 개수 is highly overall correlated with 공원종류High correlation
공원종류 is highly overall correlated with 야외등 개수High correlation
행정동 is highly overall correlated with 위도High correlation
비고 has 60 (92.3%) missing valuesMissing
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:45:08.299989
Analysis finished2023-12-11 22:45:09.507269
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공원명
Text

Distinct62
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T07:45:09.678386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.4461538
Min length4

Characters and Unicode

Total characters289
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)90.8%

Sample

1st row오정공원
2nd row통매바위공원
3rd row노촌공원
4th row봉촌공원
5th row새말공원
ValueCountFrequency (%)
오정공원 2
 
3.1%
목상공원 2
 
3.1%
송촌공원 2
 
3.1%
새일공원 1
 
1.5%
증척골공원 1
 
1.5%
중앙공원 1
 
1.5%
범바위공원 1
 
1.5%
효심공원 1
 
1.5%
나래공원 1
 
1.5%
만남공원 1
 
1.5%
Other values (52) 52
80.0%
2023-12-12T07:45:10.004527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 67
23.2%
공 65
22.5%
골 7
 
2.4%
촌 6
 
2.1%
정 5
 
1.7%
봉 4
 
1.4%
새 4
 
1.4%
래 4
 
1.4%
바 4
 
1.4%
위 3
 
1.0%
Other values (88) 120
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 67
23.2%
공 65
22.5%
골 7
 
2.4%
촌 6
 
2.1%
정 5
 
1.7%
봉 4
 
1.4%
새 4
 
1.4%
래 4
 
1.4%
바 4
 
1.4%
위 3
 
1.0%
Other values (88) 120
41.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 67
23.2%
공 65
22.5%
골 7
 
2.4%
촌 6
 
2.1%
정 5
 
1.7%
봉 4
 
1.4%
새 4
 
1.4%
래 4
 
1.4%
바 4
 
1.4%
위 3
 
1.0%
Other values (88) 120
41.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 67
23.2%
공 65
22.5%
골 7
 
2.4%
촌 6
 
2.1%
정 5
 
1.7%
봉 4
 
1.4%
새 4
 
1.4%
래 4
 
1.4%
바 4
 
1.4%
위 3
 
1.0%
Other values (88) 120
41.5%

공원종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size652.0 B
어린이공원
45 
근린공원
11 
체육공원
 
4
소공원
 
3
역사공원
 
1

Length

Max length5
Median length5
Mean length4.6461538
Min length3

Unique

Unique2 ?
Unique (%)3.1%

Sample

1st row근린공원
2nd row어린이공원
3rd row어린이공원
4th row어린이공원
5th row어린이공원

Common Values

ValueCountFrequency (%)
어린이공원 45
69.2%
근린공원 11
 
16.9%
체육공원 4
 
6.2%
소공원 3
 
4.6%
역사공원 1
 
1.5%
문화공원 1
 
1.5%

Length

2023-12-12T07:45:10.127680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:45:10.228742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이공원 45
69.2%
근린공원 11
 
16.9%
체육공원 4
 
6.2%
소공원 3
 
4.6%
역사공원 1
 
1.5%
문화공원 1
 
1.5%

관리청
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
대덕구
65 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대덕구 65
100.0%

Length

2023-12-12T07:45:10.321147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:45:10.400819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대덕구 65
100.0%

행정동
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
중리동
13 
송촌동
12 
오정동
6 
법2동
6 
법1동
5 
Other values (7)
23 

Length

Max length4
Median length3
Mean length3.0461538
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중리동 13
20.0%
송촌동 12
18.5%
오정동 6
9.2%
법2동 6
9.2%
법1동 5
 
7.7%
목상동 5
 
7.7%
비래동 4
 
6.2%
석봉동 4
 
6.2%
신탄진동 3
 
4.6%
덕암동 3
 
4.6%
Other values (2) 4
 
6.2%

Length

2023-12-12T07:45:10.479382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중리동 13
20.0%
송촌동 12
18.5%
오정동 6
9.2%
법2동 6
9.2%
법1동 5
 
7.7%
목상동 5
 
7.7%
비래동 4
 
6.2%
석봉동 4
 
6.2%
신탄진동 3
 
4.6%
덕암동 3
 
4.6%
Other values (2) 4
 
6.2%

소재지지번주소
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T07:45:10.683736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length19.076923
Min length17

Characters and Unicode

Total characters1240
Distinct characters46
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

Unique65 ?
Unique (%)100.0%

Sample

1st row대전광역시 대덕구 대화동 산32-23일원
2nd row대전광역시 대덕구 오정동 274-1
3rd row대전광역시 대덕구 오정동 311-6
4th row대전광역시 대덕구 오정동 382-3
5th row대전광역시 대덕구 오정동 453-1
ValueCountFrequency (%)
대전광역시 65
24.9%
대덕구 65
24.9%
중리동 13
 
5.0%
송촌동 12
 
4.6%
법2동 6
 
2.3%
오정동 5
 
1.9%
법1동 5
 
1.9%
비래동 4
 
1.5%
석봉동 4
 
1.5%
대화동 3
 
1.1%
Other values (73) 79
30.3%
2023-12-12T07:45:11.024795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
196
15.8%
대 133
 
10.7%
덕 67
 
5.4%
광 65
 
5.2%
역 65
 
5.2%
시 65
 
5.2%
구 65
 
5.2%
전 65
 
5.2%
동 65
 
5.2%
1 60
 
4.8%
Other values (36) 394
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 719
58.0%
Decimal Number 267
 
21.5%
Space Separator 196
 
15.8%
Dash Punctuation 57
 
4.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 133
18.5%
덕 67
9.3%
광 65
9.0%
역 65
9.0%
시 65
9.0%
구 65
9.0%
전 65
9.0%
동 65
9.0%
리 13
 
1.8%
중 13
 
1.8%
Other values (23) 103
14.3%
Decimal Number
ValueCountFrequency (%)
1 60
22.5%
2 44
16.5%
4 32
12.0%
3 28
10.5%
5 26
9.7%
8 23
 
8.6%
7 15
 
5.6%
6 13
 
4.9%
9 13
 
4.9%
0 13
 
4.9%
Space Separator
ValueCountFrequency (%)
196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 719
58.0%
Common 521
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 133
18.5%
덕 67
9.3%
광 65
9.0%
역 65
9.0%
시 65
9.0%
구 65
9.0%
전 65
9.0%
동 65
9.0%
리 13
 
1.8%
중 13
 
1.8%
Other values (23) 103
14.3%
Common
ValueCountFrequency (%)
196
37.6%
1 60
 
11.5%
- 57
 
10.9%
2 44
 
8.4%
4 32
 
6.1%
3 28
 
5.4%
5 26
 
5.0%
8 23
 
4.4%
7 15
 
2.9%
6 13
 
2.5%
Other values (3) 27
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 719
58.0%
ASCII 521
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
196
37.6%
1 60
 
11.5%
- 57
 
10.9%
2 44
 
8.4%
4 32
 
6.1%
3 28
 
5.4%
5 26
 
5.0%
8 23
 
4.4%
7 15
 
2.9%
6 13
 
2.5%
Other values (3) 27
 
5.2%
Hangul
ValueCountFrequency (%)
대 133
18.5%
덕 67
9.3%
광 65
9.0%
역 65
9.0%
시 65
9.0%
구 65
9.0%
전 65
9.0%
동 65
9.0%
리 13
 
1.8%
중 13
 
1.8%
Other values (23) 103
14.3%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.382426
Minimum36.346106
Maximum36.45388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T07:45:11.145389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.346106
5-th percentile36.352804
Q136.361346
median36.365367
Q336.377711
95-th percentile36.449757
Maximum36.45388
Range0.10777391
Interquartile range (IQR)0.01636439

Descriptive statistics

Standard deviation0.035860819
Coefficient of variation (CV)0.00098566322
Kurtosis-0.3361651
Mean36.382426
Median Absolute Deviation (MAD)0.00576169
Skewness1.2250051
Sum2364.8577
Variance0.0012859983
MonotonicityNot monotonic
2023-12-12T07:45:11.262137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.36932902 2
 
3.1%
36.36188283 1
 
1.5%
36.37002731 1
 
1.5%
36.35744341 1
 
1.5%
36.3614647 1
 
1.5%
36.36334086 1
 
1.5%
36.36739529 1
 
1.5%
36.36823684 1
 
1.5%
36.37072009 1
 
1.5%
36.37255168 1
 
1.5%
Other values (54) 54
83.1%
ValueCountFrequency (%)
36.34610646 1
1.5%
36.34900338 1
1.5%
36.3516813 1
1.5%
36.35246425 1
1.5%
36.35416298 1
1.5%
36.35591435 1
1.5%
36.35591818 1
1.5%
36.35670385 1
1.5%
36.35715256 1
1.5%
36.35744341 1
1.5%
ValueCountFrequency (%)
36.45388037 1
1.5%
36.45155552 1
1.5%
36.4500395 1
1.5%
36.44982721 1
1.5%
36.44947686 1
1.5%
36.44902382 1
1.5%
36.44804093 1
1.5%
36.44717334 1
1.5%
36.44637557 1
1.5%
36.44445234 1
1.5%

경도
Real number (ℝ)

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.42901
Minimum127.39795
Maximum127.45799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T07:45:11.384069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.39795
5-th percentile127.41061
Q1127.42178
median127.42888
Q3127.43657
95-th percentile127.44665
Maximum127.45799
Range0.0600383
Interquartile range (IQR)0.0147845

Descriptive statistics

Standard deviation0.012086402
Coefficient of variation (CV)9.4848121 × 10-5
Kurtosis-0.047965459
Mean127.42901
Median Absolute Deviation (MAD)0.0073199
Skewness-0.15143644
Sum8282.8854
Variance0.00014608111
MonotonicityNot monotonic
2023-12-12T07:45:11.536211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4428211 2
 
3.1%
127.4104258 1
 
1.5%
127.4322292 1
 
1.5%
127.4298134 1
 
1.5%
127.4301741 1
 
1.5%
127.4324003 1
 
1.5%
127.4264759 1
 
1.5%
127.4271829 1
 
1.5%
127.4263067 1
 
1.5%
127.4248556 1
 
1.5%
Other values (54) 54
83.1%
ValueCountFrequency (%)
127.397949 1
1.5%
127.4030161 1
1.5%
127.4084912 1
1.5%
127.4104258 1
1.5%
127.4113221 1
1.5%
127.4117776 1
1.5%
127.4125105 1
1.5%
127.4130465 1
1.5%
127.4142238 1
1.5%
127.415023 1
1.5%
ValueCountFrequency (%)
127.4579873 1
1.5%
127.4517076 1
1.5%
127.4472236 1
1.5%
127.4466602 1
1.5%
127.4465951 1
1.5%
127.4464903 1
1.5%
127.4456319 1
1.5%
127.4431114 1
1.5%
127.4428211 2
3.1%
127.4411228 1
1.5%

야외등 개수
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.523077
Minimum1
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T07:45:11.670044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q14
median6
Q312
95-th percentile70.6
Maximum259
Range258
Interquartile range (IQR)8

Descriptive statistics

Standard deviation37.697027
Coefficient of variation (CV)2.151279
Kurtosis27.582772
Mean17.523077
Median Absolute Deviation (MAD)3
Skewness4.8690555
Sum1139
Variance1421.0659
MonotonicityNot monotonic
2023-12-12T07:45:11.773934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3 9
13.8%
5 7
 
10.8%
6 7
 
10.8%
4 7
 
10.8%
8 4
 
6.2%
9 4
 
6.2%
2 2
 
3.1%
7 2
 
3.1%
17 2
 
3.1%
13 2
 
3.1%
Other values (15) 19
29.2%
ValueCountFrequency (%)
1 2
 
3.1%
2 2
 
3.1%
3 9
13.8%
4 7
10.8%
5 7
10.8%
6 7
10.8%
7 2
 
3.1%
8 4
6.2%
9 4
6.2%
10 1
 
1.5%
ValueCountFrequency (%)
259 1
1.5%
132 1
1.5%
90 1
1.5%
72 1
1.5%
65 1
1.5%
50 1
1.5%
36 1
1.5%
34 1
1.5%
21 1
1.5%
17 2
3.1%

비고
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing60
Missing (%)92.3%
Memory size652.0 B
2023-12-12T07:45:11.929723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length9.2
Min length8

Characters and Unicode

Total characters46
Distinct characters15
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

Unique5 ?
Unique (%)100.0%

Sample

1st row잔디등 18 포함
2nd row잔디등 49, 가로등1
3rd row잔디등 10 포함
4th row잔디등11 포함
5th row잔디등21 포함
ValueCountFrequency (%)
포함 4
30.8%
잔디등 3
23.1%
18 1
 
7.7%
49 1
 
7.7%
가로등1 1
 
7.7%
10 1
 
7.7%
잔디등11 1
 
7.7%
잔디등21 1
 
7.7%
2023-12-12T07:45:12.246229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
17.4%
등 6
13.0%
1 6
13.0%
잔 5
10.9%
디 5
10.9%
포 4
8.7%
함 4
8.7%
8 1
 
2.2%
4 1
 
2.2%
9 1
 
2.2%
Other values (5) 5
10.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
56.5%
Decimal Number 11
23.9%
Space Separator 8
 
17.4%
Other Punctuation 1
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 6
23.1%
잔 5
19.2%
디 5
19.2%
포 4
15.4%
함 4
15.4%
가 1
 
3.8%
로 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 6
54.5%
8 1
 
9.1%
4 1
 
9.1%
9 1
 
9.1%
0 1
 
9.1%
2 1
 
9.1%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
56.5%
Common 20
43.5%

Most frequent character per script

Common
ValueCountFrequency (%)
8
40.0%
1 6
30.0%
8 1
 
5.0%
4 1
 
5.0%
9 1
 
5.0%
, 1
 
5.0%
0 1
 
5.0%
2 1
 
5.0%
Hangul
ValueCountFrequency (%)
등 6
23.1%
잔 5
19.2%
디 5
19.2%
포 4
15.4%
함 4
15.4%
가 1
 
3.8%
로 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
56.5%
ASCII 20
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
40.0%
1 6
30.0%
8 1
 
5.0%
4 1
 
5.0%
9 1
 
5.0%
, 1
 
5.0%
0 1
 
5.0%
2 1
 
5.0%
Hangul
ValueCountFrequency (%)
등 6
23.1%
잔 5
19.2%
디 5
19.2%
포 4
15.4%
함 4
15.4%
가 1
 
3.8%
로 1
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
Minimum2023-06-30 00:00:00
Maximum2023-06-30 00:00:00
2023-12-12T07:45:12.382796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:12.784537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T07:45:09.056786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.632579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.847164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:09.131372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.700650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.916229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:09.221358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.780186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:45:08.990228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:45:12.861303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공원명공원종류행정동소재지지번주소위도경도야외등 개수비고
공원명1.0000.7541.0001.0000.8980.9860.0001.000
공원종류0.7541.0000.7371.0000.1550.1030.9041.000
행정동1.0000.7371.0001.0000.8910.7890.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
위도0.8980.1550.8911.0001.0000.4510.0001.000
경도0.9860.1030.7891.0000.4511.0000.5131.000
야외등 개수0.0000.9040.0001.0000.0000.5131.0001.000
비고1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T07:45:12.979274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동공원종류
행정동1.0000.359
공원종류0.3591.000
2023-12-12T07:45:13.095135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도야외등 개수공원종류행정동
위도1.000-0.1780.2290.0980.714
경도-0.1781.0000.1160.0190.474
야외등 개수0.2290.1161.0000.5600.000
공원종류0.0980.0190.5601.0000.359
행정동0.7140.4740.0000.3591.000

Missing values

2023-12-12T07:45:09.309690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:45:09.443971image/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

공원명공원종류관리청행정동소재지지번주소위도경도야외등 개수비고데이터기준일자
0오정공원근린공원대덕구오정동대전광역시 대덕구 대화동 산32-23일원36.361883127.41042611<NA>2023-06-30
1통매바위공원어린이공원대덕구오정동대전광역시 대덕구 오정동 274-136.354163127.4130463<NA>2023-06-30
2노촌공원어린이공원대덕구오정동대전광역시 대덕구 오정동 311-636.352464127.4084915<NA>2023-06-30
3봉촌공원어린이공원대덕구오정동대전광역시 대덕구 오정동 382-336.351681127.4142245<NA>2023-06-30
4새말공원어린이공원대덕구오정동대전광역시 대덕구 오정동 453-136.349003127.4176751<NA>2023-06-30
5오정공원어린이공원대덕구오정동대전광역시 대덕구 오정동 496-136.346106127.4150236<NA>2023-06-30
6대화쌈지공원어린이공원대덕구대화동대전광역시 대덕구 대화동 35-139일원36.363943127.4150913<NA>2023-06-30
7대화공원어린이공원대덕구대화동대전광역시 대덕구 대화동 35-936일원36.365367127.4151914<NA>2023-06-30
8후곡공원소공원대덕구회덕동대전광역시 대덕구 읍내동 574-136.377711127.4275486<NA>2023-06-30
9임천마당공원소공원대덕구회덕동대전광역시 대덕구 읍내동 517-7336.377726127.428939<NA>2023-06-30
공원명공원종류관리청행정동소재지지번주소위도경도야외등 개수비고데이터기준일자
55산호빛공원체육공원대덕구석봉동대전광역시 대덕구 석봉동 78036.45388127.421245132<NA>2023-06-30
56등마루공원어린이공원대덕구석봉동대전광역시 대덕구 석봉동 202-136.451556127.4250553<NA>2023-06-30
57무지개공원어린이공원대덕구덕암동대전광역시 대덕구 평촌동 537-136.435557127.4228643<NA>2023-06-30
58새뜸공원어린이공원대덕구덕암동대전광역시 대덕구 덕암동 22-536.44294127.4214389<NA>2023-06-30
59덕암공원어린이공원대덕구덕암동대전광역시 대덕구 덕암동 16-136.442449127.42614817<NA>2023-06-30
60새일공원근린공원대덕구목상동대전광역시 대덕구 문평동 78-536.448041127.40301614<NA>2023-06-30
61문평공원근린공원대덕구목상동대전광역시 대덕구 문평동 42-436.442581127.39794911<NA>2023-06-30
62목상공원근린공원대덕구목상동대전광역시 대덕구 목상동 87536.444452127.41177834잔디등21 포함2023-06-30
63목상공원어린이공원대덕구목상동대전광역시 대덕구 목상동 185-336.446376127.412514<NA>2023-06-30
64을미기공원체육공원대덕구목상동대전광역시 대덕구 신일동 1682-836.442729127.41132265<NA>2023-06-30