Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.3 KiB
Average record size in memory85.3 B

Variable types

Numeric3
Categorical4
Text3

Dataset

Description충청남도 보령시에 설치된 폐농약용기 수거함에 대한 정보를 제공합니다. 수거함 설치 읍면동, 마을명, 도로명 주소, 지번주소, 위도, 경도를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=99&beforeMenuCd=DOM_000000201001001000&publicdatapk=15103992

Alerts

시군 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
위도 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
설치대수 is highly imbalanced (75.9%)Imbalance
도로명 주소 has 6 (6.0%) missing valuesMissing
연번 has unique valuesUnique
지번 주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:58:40.394061
Analysis finished2024-01-09 22:58:41.754034
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-10T07:58:41.824614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2024-01-10T07:58:41.950481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충청남도 보령시
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 보령시
2nd row충청남도 보령시
3rd row충청남도 보령시
4th row충청남도 보령시
5th row충청남도 보령시

Common Values

ValueCountFrequency (%)
충청남도 보령시 100
100.0%

Length

2024-01-10T07:58:42.071445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:42.150527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 100
50.0%
보령시 100
50.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
청소면
21 
주교면
15 
웅천읍
11 
주포면
9 
오천면
9 
Other values (8)
35 

Length

Max length4
Median length3
Mean length3.08
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
청소면 21
21.0%
주교면 15
15.0%
웅천읍 11
11.0%
주포면 9
9.0%
오천면 9
9.0%
청라면 7
 
7.0%
남포면 7
 
7.0%
미산면 6
 
6.0%
대천5동 5
 
5.0%
주산면 4
 
4.0%
Other values (3) 6
 
6.0%

Length

2024-01-10T07:58:42.233410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청소면 21
21.0%
주교면 15
15.0%
웅천읍 11
11.0%
주포면 9
9.0%
오천면 9
9.0%
청라면 7
 
7.0%
남포면 7
 
7.0%
미산면 6
 
6.0%
대천5동 5
 
5.0%
주산면 4
 
4.0%
Other values (3) 6
 
6.0%

마을명
Text

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-01-10T07:58:42.466073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length4.21
Min length3

Characters and Unicode

Total characters421
Distinct characters81
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)87.0%

Sample

1st row죽청1리
2nd row관당2리
3rd row관당3리
4th row두룡1리
5th row평1리
ValueCountFrequency (%)
연지리 3
 
3.0%
봉당2리 2
 
2.0%
도화담2리 2
 
2.0%
주교2리 2
 
2.0%
남곡3동 2
 
2.0%
성동2리 2
 
2.0%
죽림3리 1
 
1.0%
죽청1리 1
 
1.0%
신흥리 1
 
1.0%
음현리 1
 
1.0%
Other values (84) 84
83.2%
2024-01-10T07:58:42.831706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 92
21.9%
2 35
 
8.3%
1 29
 
6.9%
동 16
 
3.8%
3 13
 
3.1%
성 12
 
2.9%
신 9
 
2.1%
죽 9
 
2.1%
정 9
 
2.1%
현 8
 
1.9%
Other values (71) 189
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
78.1%
Decimal Number 84
 
20.0%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Other Punctuation 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 92
28.0%
동 16
 
4.9%
성 12
 
3.6%
신 9
 
2.7%
죽 9
 
2.7%
정 9
 
2.7%
현 8
 
2.4%
포 7
 
2.1%
주 7
 
2.1%
교 6
 
1.8%
Other values (61) 154
46.8%
Decimal Number
ValueCountFrequency (%)
2 35
41.7%
1 29
34.5%
3 13
 
15.5%
4 4
 
4.8%
6 2
 
2.4%
5 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 329
78.1%
Common 92
 
21.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 92
28.0%
동 16
 
4.9%
성 12
 
3.6%
신 9
 
2.7%
죽 9
 
2.7%
정 9
 
2.7%
현 8
 
2.4%
포 7
 
2.1%
주 7
 
2.1%
교 6
 
1.8%
Other values (61) 154
46.8%
Common
ValueCountFrequency (%)
2 35
38.0%
1 29
31.5%
3 13
 
14.1%
4 4
 
4.3%
) 3
 
3.3%
( 3
 
3.3%
6 2
 
2.2%
, 1
 
1.1%
1
 
1.1%
5 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
78.1%
ASCII 92
 
21.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 92
28.0%
동 16
 
4.9%
성 12
 
3.6%
신 9
 
2.7%
죽 9
 
2.7%
정 9
 
2.7%
현 8
 
2.4%
포 7
 
2.1%
주 7
 
2.1%
교 6
 
1.8%
Other values (61) 154
46.8%
ASCII
ValueCountFrequency (%)
2 35
38.0%
1 29
31.5%
3 13
 
14.1%
4 4
 
4.3%
) 3
 
3.3%
( 3
 
3.3%
6 2
 
2.2%
, 1
 
1.1%
1
 
1.1%
5 1
 
1.1%

설치대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
94 
2
 
4
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 94
94.0%
2 4
 
4.0%
3 2
 
2.0%

Length

2024-01-10T07:58:42.950633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:43.030971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 94
94.0%
2 4
 
4.0%
3 2
 
2.0%

도로명 주소
Text

MISSING 

Distinct94
Distinct (%)100.0%
Missing6
Missing (%)6.0%
Memory size932.0 B
2024-01-10T07:58:43.340292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length20.808511
Min length15

Characters and Unicode

Total characters1956
Distinct characters145
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

Unique94 ?
Unique (%)100.0%

Sample

1st row충청남도 보령시 웅천읍 죽청로 64
2nd row충청남도 보령시 웅천읍 무챙이2길 11
3rd row충청남도 보령시 웅천읍 간드리큰길 41
4th row충청남도 보령시 웅천읍 충서로 1284-5
5th row충청남도 보령시 웅천읍 평리큰길 78
ValueCountFrequency (%)
충청남도 94
20.1%
보령시 94
20.1%
청소면 21
 
4.5%
주교면 15
 
3.2%
웅천읍 11
 
2.4%
오천면 9
 
1.9%
주포면 9
 
1.9%
청라면 6
 
1.3%
미산면 5
 
1.1%
남포면 5
 
1.1%
Other values (170) 199
42.5%
2024-01-10T07:58:43.798575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
377
19.3%
청 123
 
6.3%
남 102
 
5.2%
도 99
 
5.1%
충 96
 
4.9%
보 96
 
4.9%
령 96
 
4.9%
시 94
 
4.8%
면 76
 
3.9%
길 69
 
3.5%
Other values (135) 728
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1280
65.4%
Space Separator 377
 
19.3%
Decimal Number 274
 
14.0%
Dash Punctuation 22
 
1.1%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 123
 
9.6%
남 102
 
8.0%
도 99
 
7.7%
충 96
 
7.5%
보 96
 
7.5%
령 96
 
7.5%
시 94
 
7.3%
면 76
 
5.9%
길 69
 
5.4%
주 31
 
2.4%
Other values (122) 398
31.1%
Decimal Number
ValueCountFrequency (%)
1 42
15.3%
2 36
13.1%
4 32
11.7%
6 30
10.9%
5 28
10.2%
3 26
9.5%
8 25
9.1%
9 23
8.4%
7 21
7.7%
0 11
 
4.0%
Space Separator
ValueCountFrequency (%)
377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1280
65.4%
Common 676
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 123
 
9.6%
남 102
 
8.0%
도 99
 
7.7%
충 96
 
7.5%
보 96
 
7.5%
령 96
 
7.5%
시 94
 
7.3%
면 76
 
5.9%
길 69
 
5.4%
주 31
 
2.4%
Other values (122) 398
31.1%
Common
ValueCountFrequency (%)
377
55.8%
1 42
 
6.2%
2 36
 
5.3%
4 32
 
4.7%
6 30
 
4.4%
5 28
 
4.1%
3 26
 
3.8%
8 25
 
3.7%
9 23
 
3.4%
- 22
 
3.3%
Other values (3) 35
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1280
65.4%
ASCII 676
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
377
55.8%
1 42
 
6.2%
2 36
 
5.3%
4 32
 
4.7%
6 30
 
4.4%
5 28
 
4.1%
3 26
 
3.8%
8 25
 
3.7%
9 23
 
3.4%
- 22
 
3.3%
Other values (3) 35
 
5.2%
Hangul
ValueCountFrequency (%)
청 123
 
9.6%
남 102
 
8.0%
도 99
 
7.7%
충 96
 
7.5%
보 96
 
7.5%
령 96
 
7.5%
시 94
 
7.3%
면 76
 
5.9%
길 69
 
5.4%
주 31
 
2.4%
Other values (122) 398
31.1%

지번 주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-01-10T07:58:44.114719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.36
Min length16

Characters and Unicode

Total characters2136
Distinct characters85
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

Unique100 ?
Unique (%)100.0%

Sample

1st row충청남도 보령시 웅천읍 죽청리 212-5
2nd row충청남도 보령시 웅천읍 관당리 777-8
3rd row충청남도 보령시 웅천읍 관당리 340-2
4th row충청남도 보령시 웅천읍 두룡리 129-5
5th row충청남도 보령시 웅천읍 평리 23
ValueCountFrequency (%)
충청남도 100
20.2%
보령시 100
20.2%
청소면 21
 
4.3%
주교면 15
 
3.0%
웅천읍 11
 
2.2%
오천면 9
 
1.8%
주포면 9
 
1.8%
청라면 7
 
1.4%
남포면 7
 
1.4%
미산면 6
 
1.2%
Other values (159) 209
42.3%
2024-01-10T07:58:44.833235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
394
18.4%
청 129
 
6.0%
남 110
 
5.1%
보 104
 
4.9%
도 103
 
4.8%
령 102
 
4.8%
충 100
 
4.7%
시 100
 
4.7%
리 92
 
4.3%
- 84
 
3.9%
Other values (75) 818
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1280
59.9%
Space Separator 394
 
18.4%
Decimal Number 378
 
17.7%
Dash Punctuation 84
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 129
 
10.1%
남 110
 
8.6%
보 104
 
8.1%
도 103
 
8.0%
령 102
 
8.0%
충 100
 
7.8%
시 100
 
7.8%
리 92
 
7.2%
면 81
 
6.3%
주 35
 
2.7%
Other values (63) 324
25.3%
Decimal Number
ValueCountFrequency (%)
1 77
20.4%
3 53
14.0%
2 45
11.9%
5 41
10.8%
4 36
9.5%
6 28
 
7.4%
7 27
 
7.1%
0 26
 
6.9%
8 25
 
6.6%
9 20
 
5.3%
Space Separator
ValueCountFrequency (%)
394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1280
59.9%
Common 856
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 129
 
10.1%
남 110
 
8.6%
보 104
 
8.1%
도 103
 
8.0%
령 102
 
8.0%
충 100
 
7.8%
시 100
 
7.8%
리 92
 
7.2%
면 81
 
6.3%
주 35
 
2.7%
Other values (63) 324
25.3%
Common
ValueCountFrequency (%)
394
46.0%
- 84
 
9.8%
1 77
 
9.0%
3 53
 
6.2%
2 45
 
5.3%
5 41
 
4.8%
4 36
 
4.2%
6 28
 
3.3%
7 27
 
3.2%
0 26
 
3.0%
Other values (2) 45
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1280
59.9%
ASCII 856
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
394
46.0%
- 84
 
9.8%
1 77
 
9.0%
3 53
 
6.2%
2 45
 
5.3%
5 41
 
4.8%
4 36
 
4.2%
6 28
 
3.3%
7 27
 
3.2%
0 26
 
3.0%
Other values (2) 45
 
5.3%
Hangul
ValueCountFrequency (%)
청 129
 
10.1%
남 110
 
8.6%
보 104
 
8.1%
도 103
 
8.0%
령 102
 
8.0%
충 100
 
7.8%
시 100
 
7.8%
리 92
 
7.2%
면 81
 
6.3%
주 35
 
2.7%
Other values (63) 324
25.3%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.365872
Minimum36.194761
Maximum36.483001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-10T07:58:44.979104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.194761
5-th percentile36.220186
Q136.304527
median36.383847
Q336.433429
95-th percentile36.463131
Maximum36.483001
Range0.28823981
Interquartile range (IQR)0.12890224

Descriptive statistics

Standard deviation0.07871844
Coefficient of variation (CV)0.002164624
Kurtosis-0.83875674
Mean36.365872
Median Absolute Deviation (MAD)0.05584305
Skewness-0.57961246
Sum3636.5872
Variance0.0061965928
MonotonicityNot monotonic
2024-01-10T07:58:45.101509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.24040445 1
 
1.0%
36.4332242 1
 
1.0%
36.2743004 1
 
1.0%
36.28234281 1
 
1.0%
36.40973372 1
 
1.0%
36.42719843 1
 
1.0%
36.43639508 1
 
1.0%
36.39859183 1
 
1.0%
36.37464562 1
 
1.0%
36.36869442 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
36.19476097 1
1.0%
36.20236198 1
1.0%
36.20533547 1
1.0%
36.21915739 1
1.0%
36.21964218 1
1.0%
36.22021412 1
1.0%
36.22335325 1
1.0%
36.22858999 1
1.0%
36.24040445 1
1.0%
36.24309905 1
1.0%
ValueCountFrequency (%)
36.48300078 1
1.0%
36.47430847 1
1.0%
36.46856026 1
1.0%
36.46748181 1
1.0%
36.46716222 1
1.0%
36.46291894 1
1.0%
36.459057 1
1.0%
36.45858858 1
1.0%
36.45855937 1
1.0%
36.45534825 1
1.0%

경도
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.59238
Minimum126.50295
Maximum126.70427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-01-10T07:58:45.228001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.50295
5-th percentile126.522
Q1126.55857
median126.58957
Q3126.62
95-th percentile126.67791
Maximum126.70427
Range0.2013115
Interquartile range (IQR)0.061427675

Descriptive statistics

Standard deviation0.04670471
Coefficient of variation (CV)0.00036893777
Kurtosis-0.38229265
Mean126.59238
Median Absolute Deviation (MAD)0.03103225
Skewness0.30345548
Sum12659.238
Variance0.0021813299
MonotonicityNot monotonic
2024-01-10T07:58:45.361598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5538812 1
 
1.0%
126.5760366 1
 
1.0%
126.5672669 1
 
1.0%
126.583242 1
 
1.0%
126.6778196 1
 
1.0%
126.6842996 1
 
1.0%
126.6747983 1
 
1.0%
126.6406793 1
 
1.0%
126.6368356 1
 
1.0%
126.6446147 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.5029545 1
1.0%
126.5044124 1
1.0%
126.5103241 1
1.0%
126.5134958 1
1.0%
126.5207572 1
1.0%
126.5220614 1
1.0%
126.5245907 1
1.0%
126.5247967 1
1.0%
126.5255907 1
1.0%
126.5319794 1
1.0%
ValueCountFrequency (%)
126.704266 1
1.0%
126.7006607 1
1.0%
126.6854527 1
1.0%
126.6842996 1
1.0%
126.6796084 1
1.0%
126.6778196 1
1.0%
126.6756253 1
1.0%
126.6747983 1
1.0%
126.674523 1
1.0%
126.6616081 1
1.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-08-14
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-14
2nd row2023-08-14
3rd row2023-08-14
4th row2023-08-14
5th row2023-08-14

Common Values

ValueCountFrequency (%)
2023-08-14 100
100.0%

Length

2024-01-10T07:58:45.488005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:45.567511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-14 100
100.0%

Interactions

2024-01-10T07:58:41.311843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:40.858593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.086641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.387789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:40.929973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.156648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.468338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.002238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:58:41.229992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:58:45.627348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동마을명설치대수도로명 주소지번 주소위도경도
연번1.0000.9441.0000.5051.0001.0000.9490.723
읍면동0.9441.0001.0000.6691.0001.0000.9110.753
마을명1.0001.0001.0001.0001.0001.0000.9880.995
설치대수0.5050.6691.0001.0001.0001.0000.5010.371
도로명 주소1.0001.0001.0001.0001.0001.0001.0001.000
지번 주소1.0001.0001.0001.0001.0001.0001.0001.000
위도0.9490.9110.9880.5011.0001.0001.0000.513
경도0.7230.7530.9950.3711.0001.0000.5131.000
2024-01-10T07:58:45.732075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치대수읍면동
설치대수1.0000.465
읍면동0.4651.000
2024-01-10T07:58:45.807860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면동설치대수
연번1.000-0.1100.4030.7770.338
위도-0.1101.000-0.1700.6850.334
경도0.403-0.1701.0000.4270.229
읍면동0.7770.6850.4271.0000.465
설치대수0.3380.3340.2290.4651.000

Missing values

2024-01-10T07:58:41.585968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:58:41.706655image/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

연번시군읍면동마을명설치대수도로명 주소지번 주소위도경도데이터기준일
01충청남도 보령시웅천읍죽청1리1충청남도 보령시 웅천읍 죽청로 64충청남도 보령시 웅천읍 죽청리 212-536.240404126.5538812023-08-14
12충청남도 보령시웅천읍관당2리1충청남도 보령시 웅천읍 무챙이2길 11충청남도 보령시 웅천읍 관당리 777-836.247844126.5402452023-08-14
23충청남도 보령시웅천읍관당3리1충청남도 보령시 웅천읍 간드리큰길 41충청남도 보령시 웅천읍 관당리 340-236.243099126.5417322023-08-14
34충청남도 보령시웅천읍두룡1리1충청남도 보령시 웅천읍 충서로 1284-5충청남도 보령시 웅천읍 두룡리 129-536.260267126.5861122023-08-14
45충청남도 보령시웅천읍평1리1충청남도 보령시 웅천읍 평리큰길 78충청남도 보령시 웅천읍 평리 2336.270389126.634482023-08-14
56충청남도 보령시웅천읍수부3리1충청남도 보령시 웅천읍 부당길 27충청남도 보령시 웅천읍 수부리 63336.264756126.6179482023-08-14
67충청남도 보령시웅천읍성동1리1충청남도 보령시 웅천읍 내성1길 42충청남도 보령시 웅천읍 성동리 199-136.247907126.6242052023-08-14
78충청남도 보령시웅천읍성동2리1충청남도 보령시 웅천읍 외성2길 42충청남도 보령시 웅천읍 성동리 92836.252932126.6112482023-08-14
89충청남도 보령시웅천읍성동2리1충청남도 보령시 웅천읍 성동큰길 273충청남도 보령시 웅천읍 성동리 384-336.251371126.619732023-08-14
910충청남도 보령시웅천읍성동2,3리1충청남도 보령시 웅천읍 성동큰길 239충청남도 보령시 웅천읍 성동리 782-136.250928126.6160822023-08-14
연번시군읍면동마을명설치대수도로명 주소지번 주소위도경도데이터기준일
9091충청남도 보령시성주면성주면행정복지센터(성주리)1충청남도 보령시 성주면 심원계곡로 6-7충청남도 보령시 성주면 성주리 191-136.336094126.651372023-08-14
9192충청남도 보령시성주면성주5리1충청남도 보령시 성주면 벌뜸길 9-80충청남도 보령시 성주면 성주리 92-236.341348126.6544942023-08-14
9293충청남도 보령시대천3동화산1동1충청남도 보령시 대청로 340충청남도 보령시 화산동 41536.367153126.6248792023-08-14
9394충청남도 보령시대천3동동대2동1충청남도 보령시 옥마로 200충청남도 보령시 동대동 4-136.349665126.6237222023-08-14
9495충청남도 보령시대천3동동대 16동1충청남도 보령시 동현로 47충청남도 보령시 동대동 575-4736.350159126.6119482023-08-14
9596충청남도 보령시대천5동남곡2동1충청남도 보령시 새태말길 38충청남도 보령시 남곡동 산 81-136.328829126.5643162023-08-14
9697충청남도 보령시대천5동남곡3동2충청남도 보령시 남서2길 117충청남도 보령시 남곡동 1030-236.337801126.5523472023-08-14
9798충청남도 보령시대천5동남곡3동2충청남도 보령시 남서2길 143충청남도 보령시 남곡동 산 107-136.336686126.5496282023-08-14
9899충청남도 보령시대천5동신흑2동2충청남도 보령시 흑포1길 33-22충청남도 보령시 신흑동 245-136.318746126.5352922023-08-14
99100충청남도 보령시대천5동신흑6동1<NA>충청남도 보령시 신흑동 163836.309298126.5207572023-08-14