Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory839.8 KiB
Average record size in memory86.0 B

Variable types

Numeric6
Categorical1
DateTime1
Text1

Dataset

Description8월 21일부터 9월 17일까지 수집된 창원시 주요도로 주변 (불법)현수막 게시 현황 데이터입니다. 각 데이터의 유형, 위치 정보, 해당 도로정보가 있습니다.
Author경상남도 창원시
URLhttps://www.data.go.kr/data/15096119/fileData.do

Alerts

위험물유형 has constant value ""Constant
노드링크 is highly overall correlated with 시작노드 and 1 other fieldsHigh correlation
시작노드 is highly overall correlated with 노드링크 and 1 other fieldsHigh correlation
끝노드 is highly overall correlated with 노드링크 and 1 other fieldsHigh correlation
분류번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:28:03.413423
Analysis finished2023-12-12 02:28:09.431226
Duration6.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17221.804
Minimum3
Maximum34476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:09.508700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1759.6
Q18631.5
median17055.5
Q325914.5
95-th percentile32747.1
Maximum34476
Range34473
Interquartile range (IQR)17283

Descriptive statistics

Standard deviation9954.4127
Coefficient of variation (CV)0.57801219
Kurtosis-1.2042455
Mean17221.804
Median Absolute Deviation (MAD)8650.5
Skewness0.0046403107
Sum1.7221804 × 108
Variance99090332
MonotonicityNot monotonic
2023-12-12T11:28:09.656562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18123 1
 
< 0.1%
12629 1
 
< 0.1%
15545 1
 
< 0.1%
30008 1
 
< 0.1%
23051 1
 
< 0.1%
23092 1
 
< 0.1%
7135 1
 
< 0.1%
33681 1
 
< 0.1%
16223 1
 
< 0.1%
34246 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
22 1
< 0.1%
23 1
< 0.1%
26 1
< 0.1%
ValueCountFrequency (%)
34476 1
< 0.1%
34472 1
< 0.1%
34468 1
< 0.1%
34467 1
< 0.1%
34462 1
< 0.1%
34461 1
< 0.1%
34448 1
< 0.1%
34440 1
< 0.1%
34435 1
< 0.1%
34434 1
< 0.1%

위험물유형
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
현수막
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
현수막 10000
100.0%

Length

2023-12-12T11:28:09.840356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:28:09.959296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
현수막 10000
100.0%

수집날짜
Date

Distinct6587
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-21 02:54:00
Maximum2021-09-17 23:58:00
2023-12-12T11:28:10.092001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:10.295737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct7174
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.217826
Minimum34.893191
Maximum35.388363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:10.510975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.893191
5-th percentile35.174444
Q135.2034
median35.215523
Q335.234195
95-th percentile35.260503
Maximum35.388363
Range0.495172
Interquartile range (IQR)0.03079525

Descriptive statistics

Standard deviation0.026706678
Coefficient of variation (CV)0.00075832842
Kurtosis4.3357518
Mean35.217826
Median Absolute Deviation (MAD)0.013652
Skewness-0.35509175
Sum352178.26
Variance0.00071324667
MonotonicityNot monotonic
2023-12-12T11:28:10.717968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.218496 24
 
0.2%
35.218495 24
 
0.2%
35.206643 22
 
0.2%
35.218493 20
 
0.2%
35.218492 18
 
0.2%
35.21843 17
 
0.2%
35.218497 17
 
0.2%
35.265048 16
 
0.2%
35.210816 16
 
0.2%
35.218431 16
 
0.2%
Other values (7164) 9810
98.1%
ValueCountFrequency (%)
34.893191 1
< 0.1%
35.036639 1
< 0.1%
35.064313 1
< 0.1%
35.06832 2
< 0.1%
35.068749 1
< 0.1%
35.070554 1
< 0.1%
35.070778 1
< 0.1%
35.074277 1
< 0.1%
35.074433 1
< 0.1%
35.074436 1
< 0.1%
ValueCountFrequency (%)
35.388363 1
< 0.1%
35.378684 1
< 0.1%
35.354306 1
< 0.1%
35.34729 1
< 0.1%
35.33292 1
< 0.1%
35.330537 1
< 0.1%
35.330445 1
< 0.1%
35.319047 2
< 0.1%
35.318702 1
< 0.1%
35.318555 1
< 0.1%

경도
Real number (ℝ)

Distinct3817
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59306
Minimum127.90465
Maximum129.05946
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:10.908630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.90465
5-th percentile128.55748
Q1128.565
median128.57476
Q3128.6071
95-th percentile128.68456
Maximum129.05946
Range1.15481
Interquartile range (IQR)0.042105

Descriptive statistics

Standard deviation0.05295083
Coefficient of variation (CV)0.00041177052
Kurtosis18.0167
Mean128.59306
Median Absolute Deviation (MAD)0.01159
Skewness2.5407934
Sum1285930.6
Variance0.0028037904
MonotonicityNot monotonic
2023-12-12T11:28:11.084294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.56966 44
 
0.4%
128.56967 36
 
0.4%
128.5649 35
 
0.4%
128.56487 34
 
0.3%
128.57057 34
 
0.3%
128.56969 33
 
0.3%
128.56488 33
 
0.3%
128.56485 32
 
0.3%
128.56963 30
 
0.3%
128.56265 30
 
0.3%
Other values (3807) 9659
96.6%
ValueCountFrequency (%)
127.90465 1
 
< 0.1%
128.26202 2
 
< 0.1%
128.34428 1
 
< 0.1%
128.34479 2
 
< 0.1%
128.34491 1
 
< 0.1%
128.35962 1
 
< 0.1%
128.37413 1
 
< 0.1%
128.4465 1
 
< 0.1%
128.44788 1
 
< 0.1%
128.44826 5
0.1%
ValueCountFrequency (%)
129.05946 1
< 0.1%
129.05945 1
< 0.1%
129.05943 1
< 0.1%
129.05936 2
< 0.1%
129.05934 1
< 0.1%
129.05931 1
< 0.1%
129.05748 1
< 0.1%
129.05731 1
< 0.1%
129.05724 1
< 0.1%
129.0571 1
< 0.1%

노드링크
Real number (ℝ)

HIGH CORRELATION 

Distinct1426
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1471355 × 109
Minimum1.320019 × 109
Maximum4.1803769 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:11.257662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.320019 × 109
5-th percentile4.1400913 × 109
Q14.1600199 × 109
median4.1601532 × 109
Q34.1700209 × 109
95-th percentile4.1700819 × 109
Maximum4.1803769 × 109
Range2.8603579 × 109
Interquartile range (IQR)10001000

Descriptive statistics

Standard deviation1.3078764 × 108
Coefficient of variation (CV)0.031536863
Kurtosis399.91481
Mean4.1471355 × 109
Median Absolute Deviation (MAD)9867400
Skewness-18.996648
Sum4.1471355 × 1013
Variance1.7105408 × 1016
MonotonicityNot monotonic
2023-12-12T11:28:11.441070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4170023200 215
 
2.1%
4160151900 209
 
2.1%
4160166000 195
 
1.9%
4160167100 151
 
1.5%
4160165900 142
 
1.4%
4160151000 135
 
1.4%
4160155300 123
 
1.2%
4160150600 112
 
1.1%
4160152000 104
 
1.0%
4170023900 99
 
1.0%
Other values (1416) 8515
85.2%
ValueCountFrequency (%)
1320019000 1
 
< 0.1%
1320021000 1
 
< 0.1%
1320021100 2
< 0.1%
1340005100 3
< 0.1%
1340013600 4
< 0.1%
1340029800 1
 
< 0.1%
1340040201 1
 
< 0.1%
1340044900 2
< 0.1%
1370002301 3
< 0.1%
1370002401 1
 
< 0.1%
ValueCountFrequency (%)
4180376900 1
 
< 0.1%
4180376300 4
< 0.1%
4180376200 7
0.1%
4180376000 2
 
< 0.1%
4180370600 3
< 0.1%
4180370500 2
 
< 0.1%
4180362000 1
 
< 0.1%
4180361500 1
 
< 0.1%
4180361400 1
 
< 0.1%
4180361300 1
 
< 0.1%

시작노드
Real number (ℝ)

HIGH CORRELATION 

Distinct955
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1469702 × 109
Minimum1.3200071 × 109
Maximum4.1801032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:11.591403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3200071 × 109
5-th percentile4.140029 × 109
Q14.1600094 × 109
median4.1600529 × 109
Q34.1700239 × 109
95-th percentile4.1700369 × 109
Maximum4.1801032 × 109
Range2.8600961 × 109
Interquartile range (IQR)10014500

Descriptive statistics

Standard deviation1.3078547 × 108
Coefficient of variation (CV)0.031537597
Kurtosis399.8526
Mean4.1469702 × 109
Median Absolute Deviation (MAD)9970900
Skewness-18.99457
Sum4.1469702 × 1013
Variance1.710484 × 1016
MonotonicityNot monotonic
2023-12-12T11:28:11.750085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4160052900 375
 
3.8%
4170025800 267
 
2.7%
4170024700 226
 
2.3%
4160050500 226
 
2.3%
4160049900 166
 
1.7%
4160055900 149
 
1.5%
4160055800 135
 
1.4%
4160057200 134
 
1.3%
4160060700 126
 
1.3%
4160057500 123
 
1.2%
Other values (945) 8073
80.7%
ValueCountFrequency (%)
1320007100 3
< 0.1%
1320007200 1
 
< 0.1%
1340002100 3
< 0.1%
1340011200 5
0.1%
1340013100 1
 
< 0.1%
1340014000 2
 
< 0.1%
1370001200 1
 
< 0.1%
1370001400 3
< 0.1%
3830010401 1
 
< 0.1%
3850002400 2
 
< 0.1%
ValueCountFrequency (%)
4180103200 5
0.1%
4180103100 1
 
< 0.1%
4180093600 2
 
< 0.1%
4180077700 1
 
< 0.1%
4180076700 1
 
< 0.1%
4180075800 1
 
< 0.1%
4180075400 2
 
< 0.1%
4180074300 1
 
< 0.1%
4180074200 3
< 0.1%
4180073900 1
 
< 0.1%

끝노드
Real number (ℝ)

HIGH CORRELATION 

Distinct914
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1469754 × 109
Minimum1.3200065 × 109
Maximum4.1801062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:28:11.945470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3200065 × 109
5-th percentile4.1400273 × 109
Q14.1600102 × 109
median4.1600529 × 109
Q34.1700243 × 109
95-th percentile4.1700366 × 109
Maximum4.1801062 × 109
Range2.8600997 × 109
Interquartile range (IQR)10014100

Descriptive statistics

Standard deviation1.3075448 × 108
Coefficient of variation (CV)0.031530084
Kurtosis400.23418
Mean4.1469754 × 109
Median Absolute Deviation (MAD)9970900
Skewness-19.007467
Sum4.1469754 × 1013
Variance1.7096734 × 1016
MonotonicityNot monotonic
2023-12-12T11:28:12.135718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4170025000 315
 
3.1%
4160052900 264
 
2.6%
4160055100 251
 
2.5%
4160049900 243
 
2.4%
4160055900 242
 
2.4%
4160048400 211
 
2.1%
4170026400 148
 
1.5%
4160058400 128
 
1.3%
4170025800 121
 
1.2%
4170028200 115
 
1.1%
Other values (904) 7962
79.6%
ValueCountFrequency (%)
1320006500 1
 
< 0.1%
1320007100 1
 
< 0.1%
1320007300 2
< 0.1%
1340000100 3
< 0.1%
1340004300 4
< 0.1%
1340009500 1
 
< 0.1%
1340014600 2
< 0.1%
1340122000 1
 
< 0.1%
1370001200 3
< 0.1%
1370001400 1
 
< 0.1%
ValueCountFrequency (%)
4180106200 5
0.1%
4180103200 1
 
< 0.1%
4180096000 2
 
< 0.1%
4180078500 1
 
< 0.1%
4180076900 2
 
< 0.1%
4180075000 1
 
< 0.1%
4180074400 1
 
< 0.1%
4180074200 1
 
< 0.1%
4180073700 1
 
< 0.1%
4180073600 4
< 0.1%

도로명주소
Text

Distinct406
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:28:12.579118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.6771
Min length12

Characters and Unicode

Total characters186771
Distinct characters186
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

Unique88 ?
Unique (%)0.9%

Sample

1st row경상남도 창원시 마산합포구 아구찜길
2nd row경상남도 창원시 마산회원구 3.15대로
3rd row경상남도 창원시 마산합포구 3.15대로
4th row경상남도 창원시 의창구 우곡로
5th row경상남도 창원시 마산회원구 무학로
ValueCountFrequency (%)
경상남도 9981
25.1%
창원시 9751
24.5%
마산합포구 4592
11.6%
마산회원구 2802
 
7.0%
의창구 1525
 
3.8%
3.15대로 935
 
2.4%
성산구 711
 
1.8%
노산서18길 593
 
1.5%
회원남로 428
 
1.1%
고운로 383
 
1.0%
Other values (385) 8050
20.3%
2023-12-12T11:28:13.176021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29751
15.9%
원 13696
 
7.3%
창 11852
 
6.3%
남 11259
 
6.0%
상 10183
 
5.5%
시 10159
 
5.4%
도 10066
 
5.4%
경 10007
 
5.4%
구 9835
 
5.3%
산 9558
 
5.1%
Other values (176) 60405
32.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150159
80.4%
Space Separator 29751
 
15.9%
Decimal Number 5837
 
3.1%
Other Punctuation 935
 
0.5%
Dash Punctuation 89
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 13696
 
9.1%
창 11852
 
7.9%
남 11259
 
7.5%
상 10183
 
6.8%
시 10159
 
6.8%
도 10066
 
6.7%
경 10007
 
6.7%
구 9835
 
6.5%
산 9558
 
6.4%
로 8306
 
5.5%
Other values (163) 45238
30.1%
Decimal Number
ValueCountFrequency (%)
1 2159
37.0%
3 1168
20.0%
5 1030
17.6%
8 739
 
12.7%
2 231
 
4.0%
4 167
 
2.9%
7 138
 
2.4%
9 96
 
1.6%
6 69
 
1.2%
0 40
 
0.7%
Space Separator
ValueCountFrequency (%)
29751
100.0%
Other Punctuation
ValueCountFrequency (%)
. 935
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150159
80.4%
Common 36612
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 13696
 
9.1%
창 11852
 
7.9%
남 11259
 
7.5%
상 10183
 
6.8%
시 10159
 
6.8%
도 10066
 
6.7%
경 10007
 
6.7%
구 9835
 
6.5%
산 9558
 
6.4%
로 8306
 
5.5%
Other values (163) 45238
30.1%
Common
ValueCountFrequency (%)
29751
81.3%
1 2159
 
5.9%
3 1168
 
3.2%
5 1030
 
2.8%
. 935
 
2.6%
8 739
 
2.0%
2 231
 
0.6%
4 167
 
0.5%
7 138
 
0.4%
9 96
 
0.3%
Other values (3) 198
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150159
80.4%
ASCII 36612
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29751
81.3%
1 2159
 
5.9%
3 1168
 
3.2%
5 1030
 
2.8%
. 935
 
2.6%
8 739
 
2.0%
2 231
 
0.6%
4 167
 
0.5%
7 138
 
0.4%
9 96
 
0.3%
Other values (3) 198
 
0.5%
Hangul
ValueCountFrequency (%)
원 13696
 
9.1%
창 11852
 
7.9%
남 11259
 
7.5%
상 10183
 
6.8%
시 10159
 
6.8%
도 10066
 
6.7%
경 10007
 
6.7%
구 9835
 
6.5%
산 9558
 
6.4%
로 8306
 
5.5%
Other values (163) 45238
30.1%

Interactions

2023-12-12T11:28:08.264094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:04.536233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.251076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.953609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.673442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.589837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.416158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:04.642804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.365352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.082037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.785693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.697547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.560273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:04.786048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.458838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.197681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.878626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.799023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.686940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:04.882678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.591546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.318155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.285910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.923376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.819937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:04.978619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.724715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.442427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.394228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.032698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.949769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.080353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:05.845681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:06.559075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:07.496595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:28:08.147527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:28:13.314229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류번호위도경도노드링크시작노드끝노드
분류번호1.0000.1360.1780.1680.1610.168
위도0.1361.0000.7750.4310.4120.431
경도0.1780.7751.0000.9650.9650.965
노드링크0.1680.4310.9651.0001.0001.000
시작노드0.1610.4120.9651.0001.0001.000
끝노드0.1680.4310.9651.0001.0001.000
2023-12-12T11:28:13.430970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류번호위도경도노드링크시작노드끝노드
분류번호1.0000.0490.072-0.048-0.031-0.034
위도0.0491.0000.4960.060-0.020-0.022
경도0.0720.4961.000-0.283-0.174-0.172
노드링크-0.0480.060-0.2831.0000.9370.932
시작노드-0.031-0.020-0.1740.9371.0000.974
끝노드-0.034-0.022-0.1720.9320.9741.000

Missing values

2023-12-12T11:28:09.139536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:28:09.337574image/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

분류번호위험물유형수집날짜위도경도노드링크시작노드끝노드도로명주소
1812218123현수막2021-09-07 08:5435.209155128.5784416015680041600621004160062300경상남도 창원시 마산합포구 아구찜길
38723873현수막2021-08-23 02:5835.231309128.57695417005110041700290004170028200경상남도 창원시 마산회원구 3.15대로
1023210233현수막2021-08-31 21:4735.202986128.57005416015060041600572004160055100경상남도 창원시 마산합포구 3.15대로
98529853현수막2021-08-31 07:2635.245826128.63947414001520041400485004140048700경상남도 창원시 의창구 우곡로
46404641현수막2021-08-24 07:2935.220511128.5618417002550041700239004170023400경상남도 창원시 마산회원구 무학로
2080720808현수막2021-09-09 09:0535.244689128.65916414011150041400609004140060200경상남도 창원시 의창구 창이대로
83928393현수막2021-08-29 23:4435.213376128.5623416016090041600488004160046000경상남도 창원시 마산합포구 무학로
2943129432현수막2021-09-14 08:4135.204633128.57921416015320041600625004160063100경상남도 창원시 마산합포구 복요리로
1409614097현수막2021-09-04 09:2135.203196128.57964416015110041600629004160063400경상남도 창원시 마산합포구 해안대로
96309631현수막2021-08-31 05:1635.205184128.56483416015190041600505004160048400경상남도 창원시 마산합포구 자산삼거리로
분류번호위험물유형수집날짜위도경도노드링크시작노드끝노드도로명주소
93939394현수막2021-08-31 01:5535.215391128.56969416016710041600529004160055900경상남도 창원시 마산합포구 노산서18길
13441345현수막2021-09-14 08:5635.237246128.5884417006650041700346004170034500경상남도 창원시 마산회원구 팔용로
1390313904현수막2021-09-04 07:3435.211826128.57552416016400041600607004160059800경상남도 창원시 마산합포구 3.15대로
96249625현수막2021-08-31 05:1035.205189128.56485416015190041600505004160048400경상남도 창원시 마산합포구 자산삼거리로
1018410185현수막2021-08-31 21:2335.210815128.58908417001520041700341004170035800경상남도 창원시 마산회원구 무역로
32743275현수막2021-08-22 22:1535.198691128.56242416014190041600473004160047500경상남도 창원시 마산합포구 고운로
2252222523현수막2021-09-10 13:0635.204001128.56433416015200041600484004160050500경상남도 창원시 마산합포구 자산삼거리로
3021730218현수막2021-09-14 21:2835.257138128.60742414014200041400290004140027300경상남도 창원시 의창구 의창대로
2865628657현수막2021-09-14 04:4735.210946128.59605417001580041700370004170039900경상남도 창원시 마산회원구 무역로
1846118462현수막2021-09-07 23:3535.229426128.57574417004460041700275004170028200경상남도 창원시 마산회원구 3.15대로