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.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15096119

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
노드링크 is highly skewed (γ1 = -20.79850592)Skewed
시작노드 is highly skewed (γ1 = -20.79598356)Skewed
끝노드 is highly skewed (γ1 = -20.81409159)Skewed
분류번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:24:01.109670
Analysis finished2023-12-10 23:24:06.875201
Duration5.77 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%
Mean17202.287
Minimum2
Maximum34472
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:06.942569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1723.85
Q18468.25
median17182.5
Q325841.25
95-th percentile32821.25
Maximum34472
Range34470
Interquartile range (IQR)17373

Descriptive statistics

Standard deviation9982.3487
Coefficient of variation (CV)0.58029195
Kurtosis-1.2033596
Mean17202.287
Median Absolute Deviation (MAD)8680
Skewness0.0064608558
Sum1.7202287 × 108
Variance99647286
MonotonicityNot monotonic
2023-12-11T08:24:07.090656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
431 1
 
< 0.1%
17904 1
 
< 0.1%
33480 1
 
< 0.1%
9617 1
 
< 0.1%
18519 1
 
< 0.1%
28666 1
 
< 0.1%
16618 1
 
< 0.1%
27286 1
 
< 0.1%
10926 1
 
< 0.1%
9826 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
18 1
< 0.1%
21 1
< 0.1%
28 1
< 0.1%
29 1
< 0.1%
33 1
< 0.1%
ValueCountFrequency (%)
34472 1
< 0.1%
34471 1
< 0.1%
34470 1
< 0.1%
34468 1
< 0.1%
34464 1
< 0.1%
34463 1
< 0.1%
34460 1
< 0.1%
34459 1
< 0.1%
34457 1
< 0.1%
34456 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

2023-12-11T08:24:07.237214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:07.329083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
현수막 10000
100.0%

수집날짜
Date

Distinct6530
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-21 02:54:00
Maximum2021-09-17 23:58:00
2023-12-11T08:24:07.424747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:07.557757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct7206
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.217798
Minimum35.036198
Maximum35.388357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:07.689935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.036198
5-th percentile35.174445
Q135.203983
median35.216101
Q335.233778
95-th percentile35.260471
Maximum35.388357
Range0.352159
Interquartile range (IQR)0.02979475

Descriptive statistics

Standard deviation0.026335965
Coefficient of variation (CV)0.00074780273
Kurtosis2.6322436
Mean35.217798
Median Absolute Deviation (MAD)0.013226
Skewness-0.10753639
Sum352177.98
Variance0.00069358307
MonotonicityNot monotonic
2023-12-11T08:24:07.824831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.218495 35
 
0.4%
35.218496 28
 
0.3%
35.206643 26
 
0.3%
35.218493 22
 
0.2%
35.218497 21
 
0.2%
35.265048 20
 
0.2%
35.206927 19
 
0.2%
35.218494 18
 
0.2%
35.21843 14
 
0.1%
35.202992 14
 
0.1%
Other values (7196) 9783
97.8%
ValueCountFrequency (%)
35.036198 1
< 0.1%
35.06832 2
< 0.1%
35.068569 1
< 0.1%
35.069341 1
< 0.1%
35.070778 1
< 0.1%
35.073058 1
< 0.1%
35.073235 1
< 0.1%
35.074423 1
< 0.1%
35.104074 1
< 0.1%
35.104401 1
< 0.1%
ValueCountFrequency (%)
35.388357 1
< 0.1%
35.388229 2
< 0.1%
35.378684 1
< 0.1%
35.37863 1
< 0.1%
35.354396 1
< 0.1%
35.34729 1
< 0.1%
35.347259 1
< 0.1%
35.33292 1
< 0.1%
35.319047 1
< 0.1%
35.318702 1
< 0.1%

경도
Real number (ℝ)

Distinct3812
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59355
Minimum127.90479
Maximum129.11566
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:07.977465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.90479
5-th percentile128.55756
Q1128.56523
median128.57542
Q3128.60619
95-th percentile128.68805
Maximum129.11566
Range1.210875
Interquartile range (IQR)0.04096

Descriptive statistics

Standard deviation0.053319185
Coefficient of variation (CV)0.00041463343
Kurtosis15.1731
Mean128.59355
Median Absolute Deviation (MAD)0.01191
Skewness2.3063284
Sum1285935.5
Variance0.0028429355
MonotonicityNot monotonic
2023-12-11T08:24:08.138941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.56265 43
 
0.4%
128.56967 39
 
0.4%
128.5649 34
 
0.3%
128.56966 33
 
0.3%
128.56264 30
 
0.3%
128.57057 30
 
0.3%
128.56963 29
 
0.3%
128.56487 28
 
0.3%
128.56485 28
 
0.3%
128.56267 28
 
0.3%
Other values (3802) 9678
96.8%
ValueCountFrequency (%)
127.904785 1
 
< 0.1%
128.26202 1
 
< 0.1%
128.34335 1
 
< 0.1%
128.34479 3
< 0.1%
128.3449 1
 
< 0.1%
128.34497 1
 
< 0.1%
128.34933 1
 
< 0.1%
128.34956 1
 
< 0.1%
128.38904 1
 
< 0.1%
128.41185 1
 
< 0.1%
ValueCountFrequency (%)
129.11566 1
< 0.1%
129.05946 1
< 0.1%
129.05933 2
< 0.1%
129.05731 1
< 0.1%
129.05464 2
< 0.1%
129.04643 1
< 0.1%
129.03564 1
< 0.1%
129.03514 1
< 0.1%
129.03297 1
< 0.1%
129.0286 1
< 0.1%

노드링크
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1411
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1483137 × 109
Minimum1.320019 × 109
Maximum4.1803769 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:08.289796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.320019 × 109
5-th percentile4.140091 × 109
Q14.1600232 × 109
median4.1601552 × 109
Q34.1700232 × 109
95-th percentile4.1700858 × 109
Maximum4.1803769 × 109
Range2.8603579 × 109
Interquartile range (IQR)10000025

Descriptive statistics

Standard deviation1.1185563 × 108
Coefficient of variation (CV)0.026964121
Kurtosis507.87559
Mean4.1483137 × 109
Median Absolute Deviation (MAD)9867400
Skewness-20.798506
Sum4.1483137 × 1013
Variance1.2511682 × 1016
MonotonicityNot monotonic
2023-12-11T08:24:08.466984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4170023200 230
 
2.3%
4160166000 192
 
1.9%
4160151900 173
 
1.7%
4160167100 166
 
1.7%
4160152000 124
 
1.2%
4160151000 122
 
1.2%
4160155300 120
 
1.2%
4160150600 117
 
1.2%
4170023900 106
 
1.1%
4160165900 102
 
1.0%
Other values (1401) 8548
85.5%
ValueCountFrequency (%)
1320019000 2
< 0.1%
1320021100 1
 
< 0.1%
1340013600 1
 
< 0.1%
1340040201 1
 
< 0.1%
1340044900 2
< 0.1%
1370002301 3
< 0.1%
1370002401 1
 
< 0.1%
1370004500 1
 
< 0.1%
1380004200 1
 
< 0.1%
3850000602 1
 
< 0.1%
ValueCountFrequency (%)
4180376900 2
 
< 0.1%
4180376300 4
< 0.1%
4180376200 8
0.1%
4180376000 1
 
< 0.1%
4180375300 1
 
< 0.1%
4180370600 4
< 0.1%
4180370500 1
 
< 0.1%
4180361400 1
 
< 0.1%
4180358600 5
0.1%
4180358500 2
 
< 0.1%

시작노드
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct953
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1481455 × 109
Minimum1.3200071 × 109
Maximum4.1801032 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:08.634687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3200071 × 109
5-th percentile4.140029 × 109
Q14.16001 × 109
median4.1600529 × 109
Q34.1700244 × 109
95-th percentile4.170037 × 109
Maximum4.1801032 × 109
Range2.8600961 × 109
Interquartile range (IQR)10014375

Descriptive statistics

Standard deviation1.118542 × 108
Coefficient of variation (CV)0.026964868
Kurtosis507.78612
Mean4.1481455 × 109
Median Absolute Deviation (MAD)9971100
Skewness-20.795984
Sum4.1481455 × 1013
Variance1.2511362 × 1016
MonotonicityNot monotonic
2023-12-11T08:24:08.772862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4160052900 392
 
3.9%
4170025800 268
 
2.7%
4170024700 235
 
2.4%
4160050500 193
 
1.9%
4160055900 151
 
1.5%
4160048400 139
 
1.4%
4160057200 139
 
1.4%
4160049900 128
 
1.3%
4160060700 123
 
1.2%
4160055800 122
 
1.2%
Other values (943) 8110
81.1%
ValueCountFrequency (%)
1320007100 3
< 0.1%
1340011200 1
 
< 0.1%
1340013100 1
 
< 0.1%
1340014000 2
< 0.1%
1370001200 1
 
< 0.1%
1370001400 3
< 0.1%
1370002300 1
 
< 0.1%
1380030900 1
 
< 0.1%
3850000200 1
 
< 0.1%
3850002400 1
 
< 0.1%
ValueCountFrequency (%)
4180103200 8
0.1%
4180103100 1
 
< 0.1%
4180093600 1
 
< 0.1%
4180077700 1
 
< 0.1%
4180076900 4
< 0.1%
4180075400 2
 
< 0.1%
4180075000 2
 
< 0.1%
4180074400 2
 
< 0.1%
4180074200 3
 
< 0.1%
4180073700 3
 
< 0.1%

끝노드
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct919
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1481496 × 109
Minimum1.3200065 × 109
Maximum4.1801062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:08.948847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3200065 × 109
5-th percentile4.1400273 × 109
Q14.1600103 × 109
median4.1600551 × 109
Q34.1700246 × 109
95-th percentile4.1700369 × 109
Maximum4.1801062 × 109
Range2.8600997 × 109
Interquartile range (IQR)10014325

Descriptive statistics

Standard deviation1.1181987 × 108
Coefficient of variation (CV)0.026956567
Kurtosis508.41014
Mean4.1481496 × 109
Median Absolute Deviation (MAD)9969200
Skewness-20.814092
Sum4.1481496 × 1013
Variance1.2503684 × 1016
MonotonicityNot monotonic
2023-12-11T08:24:09.096895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4170025000 338
 
3.4%
4160055900 256
 
2.6%
4160049900 252
 
2.5%
4160055100 246
 
2.5%
4160052900 222
 
2.2%
4160048400 173
 
1.7%
4170026400 144
 
1.4%
4160058400 131
 
1.3%
4160050500 130
 
1.3%
4170025800 130
 
1.3%
Other values (909) 7978
79.8%
ValueCountFrequency (%)
1320006500 2
< 0.1%
1320007300 1
 
< 0.1%
1340004300 1
 
< 0.1%
1340014600 2
< 0.1%
1340122000 1
 
< 0.1%
1370001200 3
< 0.1%
1370001400 1
 
< 0.1%
1370002100 1
 
< 0.1%
1380002000 1
 
< 0.1%
3850000401 1
 
< 0.1%
ValueCountFrequency (%)
4180106200 8
0.1%
4180103200 1
 
< 0.1%
4180096000 1
 
< 0.1%
4180078500 1
 
< 0.1%
4180078100 2
 
< 0.1%
4180077000 2
 
< 0.1%
4180076900 2
 
< 0.1%
4180076700 1
 
< 0.1%
4180075000 2
 
< 0.1%
4180074200 1
 
< 0.1%

도로명주소
Text

Distinct399
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:24:09.445705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length18.6666
Min length10

Characters and Unicode

Total characters186666
Distinct characters188
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

Unique86 ?
Unique (%)0.9%

Sample

1st row경상남도 창원시 마산회원구 회원남로
2nd row경상남도 창원시 의창구 팔용로
3rd row경상남도 창원시 마산회원구 -
4th row경상남도 창원시 마산회원구 3.15대로
5th row경상남도 창원시 성산구 정동로
ValueCountFrequency (%)
경상남도 9987
25.1%
창원시 9733
24.5%
마산합포구 4549
11.4%
마산회원구 2855
 
7.2%
의창구 1446
 
3.6%
3.15대로 896
 
2.3%
성산구 758
 
1.9%
노산서18길 579
 
1.5%
회원남로 449
 
1.1%
고운로 375
 
0.9%
Other values (377) 8105
20.4%
2023-12-11T08:24:09.914262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29732
15.9%
원 13768
 
7.4%
창 11755
 
6.3%
남 11251
 
6.0%
상 10184
 
5.5%
시 10154
 
5.4%
도 10055
 
5.4%
경 10027
 
5.4%
구 9813
 
5.3%
산 9623
 
5.2%
Other values (178) 60304
32.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150259
80.5%
Space Separator 29732
 
15.9%
Decimal Number 5674
 
3.0%
Other Punctuation 896
 
0.5%
Dash Punctuation 105
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 13768
 
9.2%
창 11755
 
7.8%
남 11251
 
7.5%
상 10184
 
6.8%
시 10154
 
6.8%
도 10055
 
6.7%
경 10027
 
6.7%
구 9813
 
6.5%
산 9623
 
6.4%
로 8307
 
5.5%
Other values (165) 45322
30.2%
Decimal Number
ValueCountFrequency (%)
1 2093
36.9%
3 1145
20.2%
5 1014
17.9%
8 710
 
12.5%
2 226
 
4.0%
7 147
 
2.6%
4 140
 
2.5%
9 96
 
1.7%
6 65
 
1.1%
0 38
 
0.7%
Space Separator
ValueCountFrequency (%)
29732
100.0%
Other Punctuation
ValueCountFrequency (%)
. 896
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150259
80.5%
Common 36407
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 13768
 
9.2%
창 11755
 
7.8%
남 11251
 
7.5%
상 10184
 
6.8%
시 10154
 
6.8%
도 10055
 
6.7%
경 10027
 
6.7%
구 9813
 
6.5%
산 9623
 
6.4%
로 8307
 
5.5%
Other values (165) 45322
30.2%
Common
ValueCountFrequency (%)
29732
81.7%
1 2093
 
5.7%
3 1145
 
3.1%
5 1014
 
2.8%
. 896
 
2.5%
8 710
 
2.0%
2 226
 
0.6%
7 147
 
0.4%
4 140
 
0.4%
- 105
 
0.3%
Other values (3) 199
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150259
80.5%
ASCII 36407
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29732
81.7%
1 2093
 
5.7%
3 1145
 
3.1%
5 1014
 
2.8%
. 896
 
2.5%
8 710
 
2.0%
2 226
 
0.6%
7 147
 
0.4%
4 140
 
0.4%
- 105
 
0.3%
Other values (3) 199
 
0.5%
Hangul
ValueCountFrequency (%)
원 13768
 
9.2%
창 11755
 
7.8%
남 11251
 
7.5%
상 10184
 
6.8%
시 10154
 
6.8%
도 10055
 
6.7%
경 10027
 
6.7%
구 9813
 
6.5%
산 9623
 
6.4%
로 8307
 
5.5%
Other values (165) 45322
30.2%

Interactions

2023-12-11T08:24:06.051903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.278463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.937390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.754780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.499320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.437075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:06.138551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.390253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.076237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.910861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.607875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.565325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:06.246539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.498320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.249801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.057591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.998803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.661940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:06.338231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.607288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.378711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.173288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.120499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.766791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:06.434320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.731765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.512223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.282981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.220179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.862366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:06.530929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:02.825744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:03.630848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:04.375439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.321926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:05.965106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:24:10.007751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류번호위도경도노드링크시작노드끝노드
분류번호1.0000.2040.1570.1500.1490.150
위도0.2041.0000.4840.3100.3070.310
경도0.1570.4841.0000.9990.9990.999
노드링크0.1500.3100.9991.0001.0001.000
시작노드0.1490.3070.9991.0001.0001.000
끝노드0.1500.3100.9991.0001.0001.000
2023-12-11T08:24:10.106862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류번호위도경도노드링크시작노드끝노드
분류번호1.0000.0360.076-0.066-0.048-0.046
위도0.0361.0000.4760.076-0.002-0.005
경도0.0760.4761.000-0.276-0.169-0.167
노드링크-0.0660.076-0.2761.0000.9390.933
시작노드-0.048-0.002-0.1690.9391.0000.973
끝노드-0.046-0.005-0.1670.9330.9731.000

Missing values

2023-12-11T08:24:06.675007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:24:06.815952image/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
430431현수막2021-08-21 09:0835.218631128.56741417002330041700250004170024700경상남도 창원시 마산회원구 회원남로
60396040현수막2021-08-26 21:2235.257006128.61456414013800041400340004140032500경상남도 창원시 의창구 팔용로
1724517246현수막2021-09-06 23:5135.247454128.59969417008190041700389004170039200경상남도 창원시 마산회원구 -
3084330844현수막2021-09-15 03:3435.233812128.57892417005110041700290004170028200경상남도 창원시 마산회원구 3.15대로
2531625317현수막2021-09-12 05:1935.199312128.68657415003590041500341004150026900경상남도 창원시 성산구 정동로
1117211173현수막2021-09-01 22:2535.154581128.67252418032990041800416004180042300경상남도 창원시 진해구 대야남로
2777327774현수막2021-09-13 23:3035.229026128.57675417004120041700279004170028400경상남도 창원시 마산회원구 양덕옛2길
2877428775현수막2021-09-14 05:1535.206008128.57317416015530041600575004160058400경상남도 창원시 마산합포구 3.15대로
2122621227현수막2021-09-09 23:0135.210836128.58372416016190041600641004160065200경상남도 창원시 마산합포구 허당로
95349535현수막2021-08-31 04:0935.206927128.57968416015630041600623004160063500경상남도 창원시 마산합포구 문화의길
분류번호위험물유형수집날짜위도경도노드링크시작노드끝노드도로명주소
62946295현수막2021-08-27 02:5435.239096128.58441417006870041700316004170030900경상남도 창원시 마산회원구 합성옛길
3273832739현수막2021-09-16 05:5035.206643128.5673416015190041600505004160048400경상남도 창원시 마산합포구 자산삼거리로
2188321884현수막2021-09-10 05:0835.199404128.7023415003740041500416004150045000경상남도 창원시 성산구 성주로
2610926110현수막2021-09-12 12:5335.235691128.64607414008750041400534004140054000경상남도 창원시 의창구 창이대로
1005710058현수막2021-08-31 13:2335.186096128.56032416013230041600459004160045100경상남도 창원시 마산합포구 고운로
2847928480현수막2021-09-14 03:3535.153029128.54842416009800041600380004160037500경상남도 창원시 마산합포구 남해안대로
1125611257현수막2021-09-02 00:1435.241939128.59065417007120041700347004170035700경상남도 창원시 마산회원구 팔용로
13941395현수막2021-09-15 10:3435.265048128.62225414015130041400407004140037900경상남도 창원시 의창구 읍성로
2058320584현수막2021-09-09 07:0235.2399128.58911417007180041700347004170032300경상남도 창원시 마산회원구 합성시장길
1599115992현수막2021-09-06 02:1235.203291128.57217416015030041600572004160057300경상남도 창원시 마산합포구 3.15대로