Overview

Dataset statistics

Number of variables9
Number of observations255
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.3 KiB
Average record size in memory77.5 B

Variable types

Numeric5
Text2
Categorical1
DateTime1

Dataset

Description부산광역시금정구_제설함설치현황_20230905
Author부산광역시 금정구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15025813

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
구분 is highly overall correlated with 위도High correlation
염화칼슘주머니수 is highly overall correlated with 모래주머니수High correlation
모래주머니수 is highly overall correlated with 염화칼슘주머니수High correlation
위도 is highly overall correlated with 구분High correlation
구분 has unique valuesUnique
염화칼슘주머니수 has 194 (76.1%) zerosZeros

Reproduction

Analysis started2023-12-10 16:17:57.037683
Analysis finished2023-12-10 16:18:01.235132
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct255
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128
Minimum1
Maximum255
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T01:18:01.340665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.7
Q164.5
median128
Q3191.5
95-th percentile242.3
Maximum255
Range254
Interquartile range (IQR)127

Descriptive statistics

Standard deviation73.756356
Coefficient of variation (CV)0.57622153
Kurtosis-1.2
Mean128
Median Absolute Deviation (MAD)64
Skewness0
Sum32640
Variance5440
MonotonicityStrictly increasing
2023-12-11T01:18:01.554997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
2 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
Other values (245) 245
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%

소재지주소
Text

Distinct189
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T01:18:01.938801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length18.32549
Min length14

Characters and Unicode

Total characters4673
Distinct characters87
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

Unique165 ?
Unique (%)64.7%

Sample

1st row부산광역시 금정구 서동 461-56
2nd row부산광역시 금정구 서동 505-17
3rd row부산광역시 금정구 서부로 77
4th row부산광역시 금정구 서동 산 73-5
5th row부산광역시 금정구 서부로 77
ValueCountFrequency (%)
부산광역시 255
23.8%
금정구 255
23.8%
산 46
 
4.3%
장전동 33
 
3.1%
금강로 25
 
2.3%
2-3 21
 
2.0%
청룡동 17
 
1.6%
금성동 15
 
1.4%
금샘로 14
 
1.3%
279 10
 
0.9%
Other values (231) 381
35.5%
2023-12-11T01:18:02.438960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
817
17.5%
산 342
 
7.3%
금 320
 
6.8%
부 266
 
5.7%
구 266
 
5.7%
정 261
 
5.6%
시 255
 
5.5%
역 255
 
5.5%
광 255
 
5.5%
로 151
 
3.2%
Other values (77) 1485
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2996
64.1%
Space Separator 817
 
17.5%
Decimal Number 769
 
16.5%
Dash Punctuation 91
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 342
11.4%
금 320
10.7%
부 266
8.9%
구 266
8.9%
정 261
8.7%
시 255
8.5%
역 255
8.5%
광 255
8.5%
로 151
 
5.0%
동 108
 
3.6%
Other values (65) 517
17.3%
Decimal Number
ValueCountFrequency (%)
2 143
18.6%
1 127
16.5%
3 88
11.4%
5 85
11.1%
4 71
9.2%
6 67
8.7%
7 66
8.6%
9 57
 
7.4%
0 39
 
5.1%
8 26
 
3.4%
Space Separator
ValueCountFrequency (%)
817
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2996
64.1%
Common 1677
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 342
11.4%
금 320
10.7%
부 266
8.9%
구 266
8.9%
정 261
8.7%
시 255
8.5%
역 255
8.5%
광 255
8.5%
로 151
 
5.0%
동 108
 
3.6%
Other values (65) 517
17.3%
Common
ValueCountFrequency (%)
817
48.7%
2 143
 
8.5%
1 127
 
7.6%
- 91
 
5.4%
3 88
 
5.2%
5 85
 
5.1%
4 71
 
4.2%
6 67
 
4.0%
7 66
 
3.9%
9 57
 
3.4%
Other values (2) 65
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2996
64.1%
ASCII 1677
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
817
48.7%
2 143
 
8.5%
1 127
 
7.6%
- 91
 
5.4%
3 88
 
5.2%
5 85
 
5.1%
4 71
 
4.2%
6 67
 
4.0%
7 66
 
3.9%
9 57
 
3.4%
Other values (2) 65
 
3.9%
Hangul
ValueCountFrequency (%)
산 342
11.4%
금 320
10.7%
부 266
8.9%
구 266
8.9%
정 261
8.7%
시 255
8.5%
역 255
8.5%
광 255
8.5%
로 151
 
5.0%
동 108
 
3.6%
Other values (65) 517
17.3%

상세위치
Text

Distinct252
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-11T01:18:02.780935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length11.137255
Min length3

Characters and Unicode

Total characters2840
Distinct characters267
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)97.6%

Sample

1st row윤산로 114
2nd row서부로2(서1동 제4공영주차장 앞)
3rd row서부로3~4(장애인복지관 위 삼거리)
4th row서부로5(금정여고 뒤 삼거리)
5th row서부로6(금정구장애인복지관)
ValueCountFrequency (%)
앞 26
 
5.5%
입구 18
 
3.8%
삼거리 9
 
1.9%
철마로 8
 
1.7%
구서동롯데캐슬 6
 
1.3%
정문 6
 
1.3%
뒤 6
 
1.3%
금성동 5
 
1.1%
구서 3
 
0.6%
산 3
 
0.6%
Other values (348) 379
80.8%
2023-12-11T01:18:03.306675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
7.6%
로 194
 
6.8%
( 115
 
4.0%
) 115
 
4.0%
1 106
 
3.7%
산 79
 
2.8%
동 77
 
2.7%
2 76
 
2.7%
구 66
 
2.3%
3 54
 
1.9%
Other values (257) 1743
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1914
67.4%
Decimal Number 420
 
14.8%
Space Separator 215
 
7.6%
Open Punctuation 115
 
4.0%
Close Punctuation 115
 
4.0%
Other Punctuation 31
 
1.1%
Uppercase Letter 16
 
0.6%
Dash Punctuation 7
 
0.2%
Math Symbol 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 194
 
10.1%
산 79
 
4.1%
동 77
 
4.0%
구 66
 
3.4%
성 52
 
2.7%
서 50
 
2.6%
사 46
 
2.4%
금 43
 
2.2%
정 39
 
2.0%
입 34
 
1.8%
Other values (232) 1234
64.5%
Decimal Number
ValueCountFrequency (%)
1 106
25.2%
2 76
18.1%
3 54
12.9%
5 39
 
9.3%
4 31
 
7.4%
0 29
 
6.9%
6 28
 
6.7%
7 22
 
5.2%
9 20
 
4.8%
8 15
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
S 6
37.5%
K 5
31.2%
G 1
 
6.2%
T 1
 
6.2%
O 1
 
6.2%
L 1
 
6.2%
I 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 26
83.9%
: 5
 
16.1%
Math Symbol
ValueCountFrequency (%)
~ 6
85.7%
→ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1914
67.4%
Common 910
32.0%
Latin 16
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 194
 
10.1%
산 79
 
4.1%
동 77
 
4.0%
구 66
 
3.4%
성 52
 
2.7%
서 50
 
2.6%
사 46
 
2.4%
금 43
 
2.2%
정 39
 
2.0%
입 34
 
1.8%
Other values (232) 1234
64.5%
Common
ValueCountFrequency (%)
215
23.6%
( 115
12.6%
) 115
12.6%
1 106
11.6%
2 76
 
8.4%
3 54
 
5.9%
5 39
 
4.3%
4 31
 
3.4%
0 29
 
3.2%
6 28
 
3.1%
Other values (8) 102
11.2%
Latin
ValueCountFrequency (%)
S 6
37.5%
K 5
31.2%
G 1
 
6.2%
T 1
 
6.2%
O 1
 
6.2%
L 1
 
6.2%
I 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1914
67.4%
ASCII 925
32.6%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
23.2%
( 115
12.4%
) 115
12.4%
1 106
11.5%
2 76
 
8.2%
3 54
 
5.8%
5 39
 
4.2%
4 31
 
3.4%
0 29
 
3.1%
6 28
 
3.0%
Other values (14) 117
12.6%
Hangul
ValueCountFrequency (%)
로 194
 
10.1%
산 79
 
4.1%
동 77
 
4.0%
구 66
 
3.4%
성 52
 
2.7%
서 50
 
2.6%
사 46
 
2.4%
금 43
 
2.2%
정 39
 
2.0%
입 34
 
1.8%
Other values (232) 1234
64.5%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

염화칼슘주머니수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.98039216
Minimum0
Maximum10
Zeros194
Zeros (%)76.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T01:18:03.467370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.3
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.1960074
Coefficient of variation (CV)2.2399276
Kurtosis6.4901869
Mean0.98039216
Median Absolute Deviation (MAD)0
Skewness2.6285461
Sum250
Variance4.8224487
MonotonicityNot monotonic
2023-12-11T01:18:03.602427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 194
76.1%
2 25
 
9.8%
3 9
 
3.5%
9 6
 
2.4%
4 6
 
2.4%
6 4
 
1.6%
7 3
 
1.2%
10 3
 
1.2%
1 2
 
0.8%
5 2
 
0.8%
ValueCountFrequency (%)
0 194
76.1%
1 2
 
0.8%
2 25
 
9.8%
3 9
 
3.5%
4 6
 
2.4%
5 2
 
0.8%
6 4
 
1.6%
7 3
 
1.2%
8 1
 
0.4%
9 6
 
2.4%
ValueCountFrequency (%)
10 3
 
1.2%
9 6
 
2.4%
8 1
 
0.4%
7 3
 
1.2%
6 4
 
1.6%
5 2
 
0.8%
4 6
 
2.4%
3 9
 
3.5%
2 25
9.8%
1 2
 
0.8%

모래주머니수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.745098
Minimum0
Maximum180
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T01:18:03.746972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38.5
Q160
median65
Q370
95-th percentile75
Maximum180
Range180
Interquartile range (IQR)10

Descriptive statistics

Standard deviation15.576637
Coefficient of variation (CV)0.24825265
Kurtosis17.52565
Mean62.745098
Median Absolute Deviation (MAD)5
Skewness1.460412
Sum16000
Variance242.63162
MonotonicityNot monotonic
2023-12-11T01:18:03.905097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
65 116
45.5%
70 46
 
18.0%
60 28
 
11.0%
40 15
 
5.9%
75 12
 
4.7%
45 8
 
3.1%
50 6
 
2.4%
35 5
 
2.0%
80 4
 
1.6%
30 4
 
1.6%
Other values (7) 11
 
4.3%
ValueCountFrequency (%)
0 2
 
0.8%
25 2
 
0.8%
30 4
 
1.6%
35 5
 
2.0%
40 15
 
5.9%
45 8
 
3.1%
50 6
 
2.4%
55 2
 
0.8%
60 28
 
11.0%
65 116
45.5%
ValueCountFrequency (%)
180 1
 
0.4%
150 1
 
0.4%
100 2
 
0.8%
95 1
 
0.4%
80 4
 
1.6%
75 12
 
4.7%
70 46
 
18.0%
65 116
45.5%
60 28
 
11.0%
55 2
 
0.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
부산광역시 금정구청 도시관리과
255 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 금정구청 도시관리과
2nd row부산광역시 금정구청 도시관리과
3rd row부산광역시 금정구청 도시관리과
4th row부산광역시 금정구청 도시관리과
5th row부산광역시 금정구청 도시관리과

Common Values

ValueCountFrequency (%)
부산광역시 금정구청 도시관리과 255
100.0%

Length

2023-12-11T01:18:04.059818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:18:04.148933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 255
33.3%
금정구청 255
33.3%
도시관리과 255
33.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2023-09-05 00:00:00
Maximum2023-09-05 00:00:00
2023-12-11T01:18:04.220515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:18:04.330387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.250188
Minimum35.209802
Maximum35.303632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T01:18:04.478428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.209802
5-th percentile35.21782
Q135.233615
median35.245694
Q335.268626
95-th percentile35.287487
Maximum35.303632
Range0.09383091
Interquartile range (IQR)0.03501097

Descriptive statistics

Standard deviation0.022647576
Coefficient of variation (CV)0.00064248098
Kurtosis-0.84163538
Mean35.250188
Median Absolute Deviation (MAD)0.01562821
Skewness0.33782473
Sum8988.798
Variance0.00051291269
MonotonicityNot monotonic
2023-12-11T01:18:04.654536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.24412537 21
 
8.2%
35.23640942 9
 
3.5%
35.23361548 6
 
2.4%
35.28195378 6
 
2.4%
35.25269064 5
 
2.0%
35.23510338 4
 
1.6%
35.23027221 3
 
1.2%
35.25964758 3
 
1.2%
35.25636618 3
 
1.2%
35.28930655 2
 
0.8%
Other values (181) 193
75.7%
ValueCountFrequency (%)
35.20980157 1
0.4%
35.21089709 1
0.4%
35.21164211 1
0.4%
35.21287828 1
0.4%
35.21406345 1
0.4%
35.21452677 1
0.4%
35.21555801 1
0.4%
35.21558562 1
0.4%
35.21615043 1
0.4%
35.21623227 1
0.4%
ValueCountFrequency (%)
35.30363248 1
0.4%
35.30327415 1
0.4%
35.29827862 1
0.4%
35.29807896 1
0.4%
35.29588642 2
0.8%
35.29334151 1
0.4%
35.2893581 1
0.4%
35.28930655 2
0.8%
35.28909082 1
0.4%
35.28829679 1
0.4%

경도
Real number (ℝ)

Distinct194
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08527
Minimum129.04567
Maximum129.12707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-11T01:18:04.812134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.04567
5-th percentile129.05631
Q1129.07347
median129.08578
Q3129.09533
95-th percentile129.11293
Maximum129.12707
Range0.0813953
Interquartile range (IQR)0.02186405

Descriptive statistics

Standard deviation0.017097282
Coefficient of variation (CV)0.00013244952
Kurtosis0.15999439
Mean129.08527
Median Absolute Deviation (MAD)0.0100368
Skewness0.12441877
Sum32916.745
Variance0.00029231705
MonotonicityNot monotonic
2023-12-11T01:18:05.051850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0695475 21
 
8.2%
129.0732976 9
 
3.5%
129.1270665 6
 
2.4%
129.075809 6
 
2.4%
129.0864949 5
 
2.0%
129.0947428 4
 
1.6%
129.0850293 3
 
1.2%
129.0819115 3
 
1.2%
129.0484863 3
 
1.2%
129.1242025 2
 
0.8%
Other values (184) 193
75.7%
ValueCountFrequency (%)
129.0456721 1
 
0.4%
129.0470896 1
 
0.4%
129.0484863 3
1.2%
129.0491767 1
 
0.4%
129.05091 1
 
0.4%
129.0514145 1
 
0.4%
129.054039 1
 
0.4%
129.0542017 1
 
0.4%
129.0554611 1
 
0.4%
129.0556553 1
 
0.4%
ValueCountFrequency (%)
129.1270674 1
 
0.4%
129.1270665 6
2.4%
129.1255271 1
 
0.4%
129.1242025 2
 
0.8%
129.1199615 1
 
0.4%
129.1151034 1
 
0.4%
129.1133307 1
 
0.4%
129.1127648 1
 
0.4%
129.1125764 1
 
0.4%
129.1119675 1
 
0.4%

Interactions

2023-12-11T01:17:59.862814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:57.550578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.198041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.771393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.338920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.997848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:57.672164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.320029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.882849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.433319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:18:00.146447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:57.814493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.426138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.996127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.543296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:18:00.638057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:57.949327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.557806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.092145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.652927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:18:00.759787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.075254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:58.662837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.207715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:17:59.756932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:18:05.197705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분염화칼슘주머니수모래주머니수위도경도
구분1.0000.4610.4050.9290.913
염화칼슘주머니수0.4611.0000.7340.3240.516
모래주머니수0.4050.7341.0000.2970.405
위도0.9290.3240.2971.0000.867
경도0.9130.5160.4050.8671.000
2023-12-11T01:18:05.321644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분염화칼슘주머니수모래주머니수위도경도
구분1.0000.144-0.1840.649-0.497
염화칼슘주머니수0.1441.000-0.517-0.157-0.369
모래주머니수-0.184-0.5171.000-0.0020.339
위도0.649-0.157-0.0021.000-0.112
경도-0.497-0.3690.339-0.1121.000

Missing values

2023-12-11T01:18:00.944692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:18:01.148196image/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

구분소재지주소상세위치염화칼슘주머니수모래주머니수관리기관명데이터기준일자위도경도
01부산광역시 금정구 서동 461-56윤산로 114060부산광역시 금정구청 도시관리과2023-09-0535.221044129.099796
12부산광역시 금정구 서동 505-17서부로2(서1동 제4공영주차장 앞)070부산광역시 금정구청 도시관리과2023-09-0535.219756129.096576
23부산광역시 금정구 서부로 77서부로3~4(장애인복지관 위 삼거리)865부산광역시 금정구청 도시관리과2023-09-0535.219555129.098975
34부산광역시 금정구 서동 산 73-5서부로5(금정여고 뒤 삼거리)060부산광역시 금정구청 도시관리과2023-09-0535.220754129.099438
45부산광역시 금정구 서부로 77서부로6(금정구장애인복지관)060부산광역시 금정구청 도시관리과2023-09-0535.219555129.098962
56부산광역시 금정구 서부로 58서부로7(제일요양병원 앞)060부산광역시 금정구청 도시관리과2023-09-0535.218452129.100762
67부산광역시 금정구 동현로 126동현로4(155종점입구, 서1치안센터 앞)060부산광역시 금정구청 도시관리과2023-09-0535.218093129.096447
78부산광역시 금정구 동현로 134동현로5(155종점→1동 행정복지센터 사이)060부산광역시 금정구청 도시관리과2023-09-0535.218058129.097467
89부산광역시 금정구 서동로 78서동로4~5(155종점삼거리, 새마을금고1~2)675부산광역시 금정구청 도시관리과2023-09-0535.217265129.095485
910부산광역시 금정구 명서로45번길 11-7명서로45번길240부산광역시 금정구청 도시관리과2023-09-0535.216232129.095327
구분소재지주소상세위치염화칼슘주머니수모래주머니수관리기관명데이터기준일자위도경도
245246부산광역시 금정구 북문로 178북문로5(학생교육원 앞, 북문로)255부산광역시 금정구청 도시관리과2023-09-0535.26057129.045672
246247부산광역시 금정구 남문로28금정산장 입구065부산광역시 금정구청 도시관리과2023-09-0535.240428129.058791
247248부산광역시 금정구 공해2길 32공해2길1(부일집 앞)345부산광역시 금정구청 도시관리과2023-09-0535.243248129.055461
248249부산광역시 금정구 공해2길 60공해2길2(토지산장)250부산광역시 금정구청 도시관리과2023-09-0535.241985129.055655
249250부산광역시 금정구 땅곡길 12땅곡길1(일반버스종점, 마산집 뒷편)065부산광역시 금정구청 도시관리과2023-09-0535.251779129.054039
250251부산광역시 금정구 중리1길 15중리1길(금성초등학교 앞)340부산광역시 금정구청 도시관리과2023-09-0535.250677129.05737
251252부산광역시 금정구 중리2길 9중리2길1060부산광역시 금정구청 도시관리과2023-09-0535.251536129.057237
252253부산광역시 금정구 중리2길 29중리2길2(금성빌라 앞)065부산광역시 금정구청 도시관리과2023-09-0535.252128129.057782
253254부산광역시 금정구 죽전1길 29죽전1길(킴스아트필드 뒤)250부산광역시 금정구청 도시관리과2023-09-0535.252414129.054202
254255부산광역시 금정구 산성로 452산성로 452075부산광역시 금정구청 도시관리과2023-09-0535.250332129.056142