Overview

Dataset statistics

Number of variables10
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory85.5 B

Variable types

Numeric4
Categorical4
Text2

Dataset

Description울산광역시 북구에 설치 되어있는 그늘막의 현황과 그늘막의 위치(도로명주소, 지번주소, 경도,위도)를 알려주는 데이터입니다
URLhttps://www.data.go.kr/data/15042574/fileData.do

Alerts

시군구 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
도로명주소 is highly imbalanced (68.3%)Imbalance
연번 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:37:48.231687
Analysis finished2023-12-12 18:37:54.052377
Duration5.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.5
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:37:54.207413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.45
Q123.25
median45.5
Q367.75
95-th percentile85.55
Maximum90
Range89
Interquartile range (IQR)44.5

Descriptive statistics

Standard deviation26.124701
Coefficient of variation (CV)0.57416925
Kurtosis-1.2
Mean45.5
Median Absolute Deviation (MAD)22.5
Skewness0
Sum4095
Variance682.5
MonotonicityStrictly increasing
2023-12-13T03:37:54.501704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
69 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
울산광역시 북구
90 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산광역시 북구
2nd row울산광역시 북구
3rd row울산광역시 북구
4th row울산광역시 북구
5th row울산광역시 북구

Common Values

ValueCountFrequency (%)
울산광역시 북구 90
100.0%

Length

2023-12-13T03:37:54.749873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:37:54.968572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 90
50.0%
북구 90
50.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
송정동
19 
농소2동
18 
효문동
15 
농소1동
12 
강동동
10 
Other values (3)
16 

Length

Max length4
Median length3
Mean length3.4222222
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농소1동
2nd row농소1동
3rd row농소1동
4th row농소1동
5th row농소1동

Common Values

ValueCountFrequency (%)
송정동 19
21.1%
농소2동 18
20.0%
효문동 15
16.7%
농소1동 12
13.3%
강동동 10
11.1%
농소3동 8
8.9%
양정동 5
 
5.6%
염포동 3
 
3.3%

Length

2023-12-13T03:37:55.202898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:37:55.489100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송정동 19
21.1%
농소2동 18
20.0%
효문동 15
16.7%
농소1동 12
13.3%
강동동 10
11.1%
농소3동 8
8.9%
양정동 5
 
5.6%
염포동 3
 
3.3%

설치장소
Text

Distinct80
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T03:37:56.004331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.5111111
Min length4

Characters and Unicode

Total characters766
Distinct characters174
Distinct categories5 ?
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 (%)81.1%

Sample

1st row시장2리 사거리
2nd row농소초등학교 후문
3rd row에일린의뜰1차
4th row에일린의 뜰
5th row매산초교사거리
ValueCountFrequency (%)
앞 22
 
14.2%
사거리 7
 
4.5%
인근 6
 
3.9%
동아청구사거리 4
 
2.6%
송정 3
 
1.9%
정문 3
 
1.9%
맞은편 3
 
1.9%
금강펜테리움2차 3
 
1.9%
송정한라비발디 2
 
1.3%
고헌초등학교 2
 
1.3%
Other values (87) 100
64.5%
2023-12-13T03:37:57.607795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
8.6%
앞 32
 
4.2%
리 26
 
3.4%
교 26
 
3.4%
학 23
 
3.0%
거 21
 
2.7%
등 21
 
2.7%
사 19
 
2.5%
초 19
 
2.5%
차 17
 
2.2%
Other values (164) 496
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 672
87.7%
Space Separator 66
 
8.6%
Decimal Number 24
 
3.1%
Uppercase Letter 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 32
 
4.8%
리 26
 
3.9%
교 26
 
3.9%
학 23
 
3.4%
거 21
 
3.1%
등 21
 
3.1%
사 19
 
2.8%
초 19
 
2.8%
차 17
 
2.5%
동 15
 
2.2%
Other values (151) 453
67.4%
Decimal Number
ValueCountFrequency (%)
2 9
37.5%
1 7
29.2%
9 3
 
12.5%
4 1
 
4.2%
8 1
 
4.2%
3 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
C 1
33.3%
V 1
33.3%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 672
87.7%
Common 91
 
11.9%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 32
 
4.8%
리 26
 
3.9%
교 26
 
3.9%
학 23
 
3.4%
거 21
 
3.1%
등 21
 
3.1%
사 19
 
2.8%
초 19
 
2.8%
차 17
 
2.5%
동 15
 
2.2%
Other values (151) 453
67.4%
Common
ValueCountFrequency (%)
66
72.5%
2 9
 
9.9%
1 7
 
7.7%
9 3
 
3.3%
4 1
 
1.1%
8 1
 
1.1%
3 1
 
1.1%
- 1
 
1.1%
5 1
 
1.1%
7 1
 
1.1%
Latin
ValueCountFrequency (%)
G 1
33.3%
C 1
33.3%
V 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 672
87.7%
ASCII 94
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
70.2%
2 9
 
9.6%
1 7
 
7.4%
9 3
 
3.2%
G 1
 
1.1%
C 1
 
1.1%
V 1
 
1.1%
4 1
 
1.1%
8 1
 
1.1%
3 1
 
1.1%
Other values (3) 3
 
3.2%
Hangul
ValueCountFrequency (%)
앞 32
 
4.8%
리 26
 
3.9%
교 26
 
3.9%
학 23
 
3.4%
거 21
 
3.1%
등 21
 
3.1%
사 19
 
2.8%
초 19
 
2.8%
차 17
 
2.5%
동 15
 
2.2%
Other values (151) 453
67.4%

도로명주소
Categorical

IMBALANCE 

Distinct13
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
76 
울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차)
 
2
울산광역시 북구 산하중앙3로 142 (산하동, 울산블루마시티 서희스타힐스블루원아파트)
 
2
울산광역시 북구 제내5길 28 (신천동)
 
1
울산광역시 북구 동대중앙로 47 (호계동)
 
1
Other values (8)
8 

Length

Max length49
Median length1
Mean length5.7222222
Min length1

Unique

Unique10 ?
Unique (%)11.1%

Sample

1st row
2nd row
3rd row울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차)
4th row울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차)
5th row

Common Values

ValueCountFrequency (%)
76
84.4%
울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차) 2
 
2.2%
울산광역시 북구 산하중앙3로 142 (산하동, 울산블루마시티 서희스타힐스블루원아파트) 2
 
2.2%
울산광역시 북구 제내5길 28 (신천동) 1
 
1.1%
울산광역시 북구 동대중앙로 47 (호계동) 1
 
1.1%
울산광역시 북구 신기18길 22 (중산동) 1
 
1.1%
울산광역시 북구 신답로 26 (상안동) 1
 
1.1%
울산광역시 북구 산하중앙2로 150 (산하동) 1
 
1.1%
울산광역시 북구 산하중앙2로 171 (산하동) 1
 
1.1%
울산광역시 북구 진장로 2 (진장동) 1
 
1.1%
Other values (3) 3
 
3.3%

Length

2023-12-13T03:37:57.945527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울산광역시 14
 
17.3%
북구 14
 
17.3%
산하동 4
 
4.9%
산하중앙3로 2
 
2.5%
진장동 2
 
2.5%
서희스타힐스블루원아파트 2
 
2.5%
울산블루마시티 2
 
2.5%
142 2
 
2.5%
산하중앙2로 2
 
2.5%
1차 2
 
2.5%
Other values (30) 35
43.2%

지번주소
Text

Distinct88
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T03:37:58.565032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.755556
Min length16

Characters and Unicode

Total characters1688
Distinct characters47
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

Unique86 ?
Unique (%)95.6%

Sample

1st row울산광역시 북구 호계동 763-3
2nd row울산광역시 북구 호계동 877
3rd row울산광역시 북구 호계동 산 11-21
4th row울산광역시 북구 호계동 산 11-21
5th row울산광역시 북구 매곡동 산 91-9
ValueCountFrequency (%)
울산광역시 90
24.8%
북구 90
24.8%
송정동 10
 
2.8%
매곡동 10
 
2.8%
산하동 9
 
2.5%
화봉동 9
 
2.5%
호계동 7
 
1.9%
중산동 7
 
1.9%
신천동 6
 
1.7%
진장동 6
 
1.7%
Other values (97) 119
32.8%
2023-12-13T03:37:59.520915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
363
21.5%
산 109
 
6.5%
울 90
 
5.3%
광 90
 
5.3%
역 90
 
5.3%
시 90
 
5.3%
북 90
 
5.3%
구 90
 
5.3%
동 90
 
5.3%
1 72
 
4.3%
Other values (37) 514
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 903
53.5%
Space Separator 363
21.5%
Decimal Number 358
 
21.2%
Dash Punctuation 64
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 109
12.1%
울 90
10.0%
광 90
10.0%
역 90
10.0%
시 90
10.0%
북 90
10.0%
구 90
10.0%
동 90
10.0%
곡 15
 
1.7%
정 15
 
1.7%
Other values (25) 134
14.8%
Decimal Number
ValueCountFrequency (%)
1 72
20.1%
2 45
12.6%
4 40
11.2%
3 38
10.6%
7 36
10.1%
9 30
8.4%
5 28
 
7.8%
8 25
 
7.0%
6 23
 
6.4%
0 21
 
5.9%
Space Separator
ValueCountFrequency (%)
363
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 903
53.5%
Common 785
46.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 109
12.1%
울 90
10.0%
광 90
10.0%
역 90
10.0%
시 90
10.0%
북 90
10.0%
구 90
10.0%
동 90
10.0%
곡 15
 
1.7%
정 15
 
1.7%
Other values (25) 134
14.8%
Common
ValueCountFrequency (%)
363
46.2%
1 72
 
9.2%
- 64
 
8.2%
2 45
 
5.7%
4 40
 
5.1%
3 38
 
4.8%
7 36
 
4.6%
9 30
 
3.8%
5 28
 
3.6%
8 25
 
3.2%
Other values (2) 44
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 903
53.5%
ASCII 785
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
363
46.2%
1 72
 
9.2%
- 64
 
8.2%
2 45
 
5.7%
4 40
 
5.1%
3 38
 
4.8%
7 36
 
4.6%
9 30
 
3.8%
5 28
 
3.6%
8 25
 
3.2%
Other values (2) 44
 
5.6%
Hangul
ValueCountFrequency (%)
산 109
12.1%
울 90
10.0%
광 90
10.0%
역 90
10.0%
시 90
10.0%
북 90
10.0%
구 90
10.0%
동 90
10.0%
곡 15
 
1.7%
정 15
 
1.7%
Other values (25) 134
14.8%

설치연도
Real number (ℝ)

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.3
Minimum2018
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:37:59.830953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2018
5-th percentile2018.45
Q12019
median2020
Q32022
95-th percentile2023
Maximum2023
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5098925
Coefficient of variation (CV)0.00074736053
Kurtosis-1.2778889
Mean2020.3
Median Absolute Deviation (MAD)1
Skewness0.35373149
Sum181827
Variance2.2797753
MonotonicityNot monotonic
2023-12-13T03:38:00.149567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2019 35
38.9%
2022 21
23.3%
2020 13
 
14.4%
2021 9
 
10.0%
2023 7
 
7.8%
2018 5
 
5.6%
ValueCountFrequency (%)
2018 5
 
5.6%
2019 35
38.9%
2020 13
 
14.4%
2021 9
 
10.0%
2022 21
23.3%
2023 7
 
7.8%
ValueCountFrequency (%)
2023 7
 
7.8%
2022 21
23.3%
2021 9
 
10.0%
2020 13
 
14.4%
2019 35
38.9%
2018 5
 
5.6%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.36762
Minimum129.31691
Maximum129.4419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:38:00.491889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.31691
5-th percentile129.33369
Q1129.35212
median129.36144
Q3129.36779
95-th percentile129.43808
Maximum129.4419
Range0.1249871
Interquartile range (IQR)0.015665175

Descriptive statistics

Standard deviation0.028320034
Coefficient of variation (CV)0.00021891131
Kurtosis1.8298946
Mean129.36762
Median Absolute Deviation (MAD)0.0084395
Skewness1.4852517
Sum11643.085
Variance0.00080202432
MonotonicityNot monotonic
2023-12-13T03:38:00.875862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.3521858 1
 
1.1%
129.3655272 1
 
1.1%
129.3659304 1
 
1.1%
129.3658116 1
 
1.1%
129.360093 1
 
1.1%
129.3661922 1
 
1.1%
129.3672 1
 
1.1%
129.3677 1
 
1.1%
129.355437 1
 
1.1%
129.3615657 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
129.3169129 1
1.1%
129.3289388 1
1.1%
129.3302399 1
1.1%
129.3314861 1
1.1%
129.3325494 1
1.1%
129.3350775 1
1.1%
129.3353182 1
1.1%
129.3394389 1
1.1%
129.3396443 1
1.1%
129.3425733 1
1.1%
ValueCountFrequency (%)
129.4419 1
1.1%
129.4418435 1
1.1%
129.4396666 1
1.1%
129.4385321 1
1.1%
129.4382611 1
1.1%
129.4378535 1
1.1%
129.4376568 1
1.1%
129.4372659 1
1.1%
129.4369028 1
1.1%
129.4228 1
1.1%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.610102
Minimum35.524816
Maximum35.664898
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-13T03:38:01.235784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.524816
5-th percentile35.547665
Q135.58821
median35.625936
Q335.636465
95-th percentile35.649317
Maximum35.664898
Range0.1400821
Interquartile range (IQR)0.048254225

Descriptive statistics

Standard deviation0.034853409
Coefficient of variation (CV)0.0009787506
Kurtosis-0.61922501
Mean35.610102
Median Absolute Deviation (MAD)0.0218446
Skewness-0.64029468
Sum3204.9092
Variance0.0012147601
MonotonicityNot monotonic
2023-12-13T03:38:01.580551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.6261227 1
 
1.1%
35.6035043 1
 
1.1%
35.5943217 1
 
1.1%
35.58846 1
 
1.1%
35.5882417 1
 
1.1%
35.5884584 1
 
1.1%
35.5815 1
 
1.1%
35.5882 1
 
1.1%
35.5534327 1
 
1.1%
35.5804351 1
 
1.1%
Other values (80) 80
88.9%
ValueCountFrequency (%)
35.5248155 1
1.1%
35.5316056 1
1.1%
35.5354345 1
1.1%
35.5391136 1
1.1%
35.5429468 1
1.1%
35.5534327 1
1.1%
35.553554 1
1.1%
35.5539365 1
1.1%
35.5565008 1
1.1%
35.5592815 1
1.1%
ValueCountFrequency (%)
35.6648976 1
1.1%
35.6621327 1
1.1%
35.6618289 1
1.1%
35.651181 1
1.1%
35.6496284 1
1.1%
35.6489363 1
1.1%
35.6478 1
1.1%
35.6472423 1
1.1%
35.6459946 1
1.1%
35.6443861 1
1.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-07-15
90 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-15
2nd row2023-07-15
3rd row2023-07-15
4th row2023-07-15
5th row2023-07-15

Common Values

ValueCountFrequency (%)
2023-07-15 90
100.0%

Length

2023-12-13T03:38:01.895699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:38:02.131459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-15 90
100.0%

Interactions

2023-12-13T03:37:52.621145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:49.896251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:50.839638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:51.775011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:52.840649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:50.112804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:51.032485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:51.968200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:53.089192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:50.333560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:51.319782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:52.184448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:53.313108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:50.599553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:51.551715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:37:52.373742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:38:02.334019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동설치장소도로명주소지번주소설치연도경도위도
연번1.0000.9230.9740.3821.0000.4910.7410.878
읍면동0.9231.0000.9970.2751.0000.1860.8650.883
설치장소0.9740.9971.0000.9170.9840.9451.0001.000
도로명주소0.3820.2750.9171.0001.0000.0000.0000.000
지번주소1.0001.0000.9841.0001.0000.0001.0001.000
설치연도0.4910.1860.9450.0000.0001.0000.0000.278
경도0.7410.8651.0000.0001.0000.0001.0000.749
위도0.8780.8831.0000.0001.0000.2780.7491.000
2023-12-13T03:38:02.689471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명주소읍면동
도로명주소1.0000.117
읍면동0.1171.000
2023-12-13T03:38:02.927089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치연도경도위도읍면동도로명주소
연번1.0000.0030.525-0.7780.7690.160
설치연도0.0031.0000.0480.1770.0310.000
경도0.5250.0481.000-0.4350.6500.000
위도-0.7780.177-0.4351.0000.6810.000
읍면동0.7690.0310.6500.6811.0000.117
도로명주소0.1600.0000.0000.0000.1171.000

Missing values

2023-12-13T03:37:53.619564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:37:53.936142image/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

연번시군구읍면동설치장소도로명주소지번주소설치연도경도위도데이터기준일
01울산광역시 북구농소1동시장2리 사거리울산광역시 북구 호계동 763-32018129.35218635.6261232023-07-15
12울산광역시 북구농소1동농소초등학교 후문울산광역시 북구 호계동 8772019129.35742335.6213562023-07-15
23울산광역시 북구농소1동에일린의뜰1차울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차)울산광역시 북구 호계동 산 11-212019129.36361135.6354182023-07-15
34울산광역시 북구농소1동에일린의 뜰울산광역시 북구 호계매곡1로 31 (매곡동, 드림인시티 에일린의뜰 1차)울산광역시 북구 호계동 산 11-212020129.36376535.6355332023-07-15
45울산광역시 북구농소1동매산초교사거리울산광역시 북구 매곡동 산 91-92019129.35929135.6437652023-07-15
56울산광역시 북구농소1동매곡 월드메르디앙울산광역시 북구 매곡동 8662020129.36062935.6418172023-07-15
67울산광역시 북구농소1동매곡천 둔치울산광역시 북구 제내5길 28 (신천동)울산광역시 북구 신천동 2442022129.35132935.6352042023-07-15
78울산광역시 북구농소1동에일린의뜰2차아파트 앞울산광역시 북구 매곡동 912-12022129.3605835.6376542023-07-15
89울산광역시 북구농소1동은월초등학교 사거리울산광역시 북구 호계동 7-162022129.36349435.6341062023-07-15
910울산광역시 북구농소1동호계중학교 앞울산광역시 북구 동대중앙로 47 (호계동)울산광역시 북구 호계동 262-52022129.35553535.6303662023-07-15
연번시군구읍면동설치장소도로명주소지번주소설치연도경도위도데이터기준일
8081울산광역시 북구송정동새마을금고 화산지점울산광역시 북구 송정동 296-12022129.36483235.6046222023-07-15
8182울산광역시 북구송정동호반베르디움 앞울산광역시 북구 저수지길 33 (송정동)울산광역시 북구 송정동 2742022129.3605635.6042152023-07-15
8283울산광역시 북구양정동현대차 출고삼거리울산광역시 북구 양정동 779-142019129.37680635.5594052023-07-15
8384울산광역시 북구양정동현대차2공장앞울산광역시 북구 양정동 60-32019129.38138435.5535542023-07-15
8485울산광역시 북구양정동현대차정문울산광역시 북구 양정동 773-212019129.38523235.5429472023-07-15
8586울산광역시 북구양정동효정중학교 인근울산광역시 북구 양정동 213-192021129.37730435.5592812023-07-15
8687울산광역시 북구양정동현대자동차 4공장 앞울산광역시 북구 양정동 733-22021129.38680935.5391142023-07-15
8788울산광역시 북구염포동구암의원울산광역시 북구 염포동 204-22019129.38931835.5354352023-07-15
8889울산광역시 북구염포동성원상떼빌 정문울산광역시 북구 염포동 326-172019129.3925435.5316062023-07-15
8990울산광역시 북구염포동염포삼거리 삼포개항비울산광역시 북구 염포동 583-12019129.39988735.5248162023-07-15