Overview

Dataset statistics

Number of variables9
Number of observations596
Missing cells566
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.4 KiB
Average record size in memory76.2 B

Variable types

Numeric4
Boolean3
Categorical2

Dataset

Description생활안전융합데이터를 구축하기 위해 정비한 데이터입니다. 300셀 격자단위로 의왕시 교통생활안전 관련 대상물 통계정보를 표현한 데이터입니다. 도로터널, 교량, 자전거도로, 철도 등의 정보를 제공합니다.
Author경기도 의왕시
URLhttps://www.data.go.kr/data/15108860/fileData.do

Alerts

데이터 생성일자 has constant value ""Constant
격자 ID is highly overall correlated with 격자 X축좌표 and 1 other fieldsHigh correlation
격자 X축좌표 is highly overall correlated with 격자 ID and 1 other fieldsHigh correlation
격자 Y축좌표 is highly overall correlated with 격자 ID and 2 other fieldsHigh correlation
철도 수 is highly overall correlated with 도로터널 여부 and 1 other fieldsHigh correlation
도로터널 여부 is highly overall correlated with 철도 수High correlation
행정동명 is highly overall correlated with 격자 Y축좌표 and 1 other fieldsHigh correlation
도로터널 여부 is highly imbalanced (69.1%)Imbalance
철도 수 has 566 (95.0%) missing valuesMissing
격자 ID has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:51:53.744908
Analysis finished2023-12-12 01:51:56.066744
Duration2.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

격자 ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct596
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31073113
Minimum30545233
Maximum31565350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T10:51:56.164348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30545233
5-th percentile30665241
Q130905274
median31085292
Q331265282
95-th percentile31445330
Maximum31565350
Range1020117
Interquartile range (IQR)360007.5

Descriptive statistics

Standard deviation234529.51
Coefficient of variation (CV)0.007547667
Kurtosis-0.73120697
Mean31073113
Median Absolute Deviation (MAD)180004.5
Skewness-0.15071067
Sum1.8519575 × 1010
Variance5.5004091 × 1010
MonotonicityNot monotonic
2023-12-12T10:51:56.342954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30635227 1
 
0.2%
30995314 1
 
0.2%
31055314 1
 
0.2%
31085314 1
 
0.2%
31115314 1
 
0.2%
31145314 1
 
0.2%
31175314 1
 
0.2%
31205314 1
 
0.2%
31235314 1
 
0.2%
31265314 1
 
0.2%
Other values (586) 586
98.3%
ValueCountFrequency (%)
30545233 1
0.2%
30545239 1
0.2%
30545242 1
0.2%
30545245 1
0.2%
30575230 1
0.2%
30575233 1
0.2%
30575236 1
0.2%
30575239 1
0.2%
30575242 1
0.2%
30575245 1
0.2%
ValueCountFrequency (%)
31565350 1
0.2%
31565347 1
0.2%
31535350 1
0.2%
31535347 1
0.2%
31535344 1
0.2%
31535341 1
0.2%
31505350 1
0.2%
31505347 1
0.2%
31505344 1
0.2%
31505341 1
0.2%

격자 X축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310721.19
Minimum305443
Maximum315643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T10:51:56.486290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum305443
5-th percentile306643
Q1309043
median310843
Q3312643
95-th percentile314443
Maximum315643
Range10200
Interquartile range (IQR)3600

Descriptive statistics

Standard deviation2345.0346
Coefficient of variation (CV)0.0075470702
Kurtosis-0.73124664
Mean310721.19
Median Absolute Deviation (MAD)1800
Skewness-0.15065577
Sum1.8518983 × 108
Variance5499187.3
MonotonicityNot monotonic
2023-12-12T10:51:56.652034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
310543 29
 
4.9%
310843 28
 
4.7%
310243 28
 
4.7%
312343 27
 
4.5%
311143 26
 
4.4%
312643 25
 
4.2%
312043 25
 
4.2%
311743 25
 
4.2%
311443 25
 
4.2%
309943 25
 
4.2%
Other values (25) 333
55.9%
ValueCountFrequency (%)
305443 4
 
0.7%
305743 6
 
1.0%
306043 7
 
1.2%
306343 8
1.3%
306643 7
 
1.2%
306943 10
1.7%
307243 15
2.5%
307543 14
2.3%
307843 15
2.5%
308143 18
3.0%
ValueCountFrequency (%)
315643 2
 
0.3%
315343 4
 
0.7%
315043 7
 
1.2%
314743 11
1.8%
314443 12
2.0%
314143 12
2.0%
313843 17
2.9%
313543 18
3.0%
313243 20
3.4%
312943 24
4.0%

격자 Y축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean529443.35
Minimum522716
Maximum535016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T10:51:56.806167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum522716
5-th percentile523616
Q1526916
median529616
Q3532316
95-th percentile534416
Maximum535016
Range12300
Interquartile range (IQR)5400

Descriptive statistics

Standard deviation3291.8908
Coefficient of variation (CV)0.006217645
Kurtosis-0.95285719
Mean529443.35
Median Absolute Deviation (MAD)2700
Skewness-0.23965475
Sum3.1554824 × 108
Variance10836545
MonotonicityIncreasing
2023-12-12T10:51:56.987855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
532016 19
 
3.2%
531716 18
 
3.0%
529916 18
 
3.0%
530216 18
 
3.0%
530516 18
 
3.0%
526916 18
 
3.0%
532616 18
 
3.0%
532316 18
 
3.0%
530816 18
 
3.0%
531416 18
 
3.0%
Other values (32) 415
69.6%
ValueCountFrequency (%)
522716 4
 
0.7%
523016 9
1.5%
523316 11
1.8%
523616 10
1.7%
523916 11
1.8%
524216 11
1.8%
524516 11
1.8%
524816 9
1.5%
525116 6
1.0%
525416 7
1.2%
ValueCountFrequency (%)
535016 6
 
1.0%
534716 12
2.0%
534416 13
2.2%
534116 16
2.7%
533816 17
2.9%
533516 16
2.7%
533216 17
2.9%
532916 17
2.9%
532616 18
3.0%
532316 18
3.0%

도로터널 여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size728.0 B
False
563 
True
 
33
ValueCountFrequency (%)
False 563
94.5%
True 33
 
5.5%
2023-12-12T10:51:57.125585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

교량 여부
Boolean

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size728.0 B
False
447 
True
149 
ValueCountFrequency (%)
False 447
75.0%
True 149
 
25.0%
2023-12-12T10:51:57.219162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

자전거도로 여부
Boolean

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size728.0 B
False
391 
True
205 
ValueCountFrequency (%)
False 391
65.6%
True 205
34.4%
2023-12-12T10:51:57.300866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

철도 수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)76.7%
Missing566
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean21.166667
Minimum1
Maximum66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T10:51:57.398758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16.5
median15
Q333.5
95-th percentile57.55
Maximum66
Range65
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.928328
Coefficient of variation (CV)0.89425173
Kurtosis-0.20333291
Mean21.166667
Median Absolute Deviation (MAD)12
Skewness0.92809069
Sum635
Variance358.28161
MonotonicityNot monotonic
2023-12-12T10:51:57.544192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2 4
 
0.7%
10 2
 
0.3%
6 2
 
0.3%
18 2
 
0.3%
8 2
 
0.3%
11 1
 
0.2%
14 1
 
0.2%
16 1
 
0.2%
9 1
 
0.2%
40 1
 
0.2%
Other values (13) 13
 
2.2%
(Missing) 566
95.0%
ValueCountFrequency (%)
1 1
 
0.2%
2 4
0.7%
4 1
 
0.2%
6 2
0.3%
8 2
0.3%
9 1
 
0.2%
10 2
0.3%
11 1
 
0.2%
14 1
 
0.2%
16 1
 
0.2%
ValueCountFrequency (%)
66 1
0.2%
58 1
0.2%
57 1
0.2%
47 1
0.2%
43 1
0.2%
40 1
0.2%
38 1
0.2%
34 1
0.2%
32 1
0.2%
31 1
0.2%

행정동명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
청계동
265 
부곡동
122 
고천동
96 
오전동
74 
내손1동
 
22
Other values (2)
 
17

Length

Max length4
Median length3
Mean length3.0654362
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
청계동 265
44.5%
부곡동 122
20.5%
고천동 96
 
16.1%
오전동 74
 
12.4%
내손1동 22
 
3.7%
내손2동 16
 
2.7%
군포1동 1
 
0.2%

Length

2023-12-12T10:51:57.750919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:51:57.918384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청계동 265
44.5%
부곡동 122
20.5%
고천동 96
 
16.1%
오전동 74
 
12.4%
내손1동 22
 
3.7%
내손2동 16
 
2.7%
군포1동 1
 
0.2%

데이터 생성일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2022-10-19
596 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-19
2nd row2022-10-19
3rd row2022-10-19
4th row2022-10-19
5th row2022-10-19

Common Values

ValueCountFrequency (%)
2022-10-19 596
100.0%

Length

2023-12-12T10:51:58.067475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:51:58.200221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-19 596
100.0%

Interactions

2023-12-12T10:51:55.330732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.117002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.493030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.891824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:55.449485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.198461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.585387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.995208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:55.550269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.298434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.678350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:55.116446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:55.668529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.398214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:54.791061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:55.227330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:51:58.290399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자 ID격자 X축좌표격자 Y축좌표도로터널 여부교량 여부자전거도로 여부철도 수행정동명
격자 ID1.0001.0000.7780.2120.1980.4430.0000.725
격자 X축좌표1.0001.0000.7720.1900.2000.4430.0000.727
격자 Y축좌표0.7780.7721.0000.3970.2080.3000.5250.811
도로터널 여부0.2120.1900.3971.0000.0760.204NaN0.139
교량 여부0.1980.2000.2080.0761.0000.5560.0000.088
자전거도로 여부0.4430.4430.3000.2040.5561.0000.0000.164
철도 수0.0000.0000.525NaN0.0000.0001.000NaN
행정동명0.7250.7270.8110.1390.0880.164NaN1.000
2023-12-12T10:51:58.443042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로터널 여부교량 여부자전거도로 여부행정동명
도로터널 여부1.0000.0490.1310.148
교량 여부0.0491.0000.3750.094
자전거도로 여부0.1310.3751.0000.175
행정동명0.1480.0940.1751.000
2023-12-12T10:51:58.553543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자 ID격자 X축좌표격자 Y축좌표철도 수도로터널 여부교량 여부자전거도로 여부행정동명
격자 ID1.0000.9990.783-0.1260.1620.1520.3400.478
격자 X축좌표0.9991.0000.762-0.1950.1460.1560.3430.481
격자 Y축좌표0.7830.7621.0000.1060.3030.1580.2280.591
철도 수-0.126-0.1950.1061.0001.0000.0980.0001.000
도로터널 여부0.1620.1460.3031.0001.0000.0490.1310.148
교량 여부0.1520.1560.1580.0980.0491.0000.3750.094
자전거도로 여부0.3400.3430.2280.0000.1310.3751.0000.175
행정동명0.4780.4810.5911.0000.1480.0940.1751.000

Missing values

2023-12-12T10:51:55.817931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:51:56.002677image/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

격자 ID격자 X축좌표격자 Y축좌표도로터널 여부교량 여부자전거도로 여부철도 수행정동명데이터 생성일자
030635227306343522716NNN<NA>부곡동2022-10-19
130665227306643522716NYY<NA>부곡동2022-10-19
230695227306943522716NNN<NA>부곡동2022-10-19
330725227307243522716NNN<NA>부곡동2022-10-19
430575230305743523016NNN<NA>부곡동2022-10-19
530605230306043523016NNN<NA>부곡동2022-10-19
630635230306343523016NYY<NA>부곡동2022-10-19
730665230306643523016NNY<NA>부곡동2022-10-19
830695230306943523016NNN<NA>부곡동2022-10-19
930725230307243523016NNN<NA>부곡동2022-10-19
격자 ID격자 X축좌표격자 Y축좌표도로터널 여부교량 여부자전거도로 여부철도 수행정동명데이터 생성일자
58631475347314743534716NYN<NA>청계동2022-10-19
58731505347315043534716NNN<NA>청계동2022-10-19
58831535347315343534716NNN<NA>청계동2022-10-19
58931565347315643534716NNN<NA>청계동2022-10-19
59031295350312943535016NNN<NA>청계동2022-10-19
59131325350313243535016NNN<NA>청계동2022-10-19
59231475350314743535016NNN<NA>청계동2022-10-19
59331505350315043535016NNN<NA>청계동2022-10-19
59431535350315343535016NNN<NA>청계동2022-10-19
59531565350315643535016NNN<NA>청계동2022-10-19