Overview

Dataset statistics

Number of variables5
Number of observations6950
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory292.0 KiB
Average record size in memory43.0 B

Variable types

Numeric3
Categorical2

Dataset

Description경기도 의왕시 보행안전지수 지도 시각화에 사용된 의왕시 전주 현황에 대한 정보를 담고 있는 csv형태의 데이터를 제공합니다.
Author경기도 의왕시
URLhttps://www.data.go.kr/data/15108968/fileData.do

Alerts

지형지물부호 is highly overall correlated with 전주구분High correlation
전주구분 is highly overall correlated with 지형지물부호High correlation
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation

Reproduction

Analysis started2023-12-12 04:44:35.143248
Analysis finished2023-12-12 04:44:36.763046
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간지리식별번호
Real number (ℝ)

Distinct5474
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2591.7906
Minimum1
Maximum5474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T13:44:36.830388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile249
Q11301
median2552.5
Q33816.75
95-th percentile5126.55
Maximum5474
Range5473
Interquartile range (IQR)2515.75

Descriptive statistics

Standard deviation1526.6068
Coefficient of variation (CV)0.58901625
Kurtosis-1.0860952
Mean2591.7906
Median Absolute Deviation (MAD)1257.5
Skewness0.11108655
Sum18012945
Variance2330528.4
MonotonicityNot monotonic
2023-12-12T13:44:36.953625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1228 2
 
< 0.1%
2750 2
 
< 0.1%
1059 2
 
< 0.1%
2753 2
 
< 0.1%
1054 2
 
< 0.1%
2757 2
 
< 0.1%
2760 2
 
< 0.1%
2761 2
 
< 0.1%
1047 2
 
< 0.1%
4850 2
 
< 0.1%
Other values (5464) 6930
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 2
< 0.1%
5 1
< 0.1%
6 2
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 2
< 0.1%
ValueCountFrequency (%)
5474 1
< 0.1%
5473 1
< 0.1%
5472 1
< 0.1%
5471 1
< 0.1%
5470 1
< 0.1%
5469 1
< 0.1%
5468 1
< 0.1%
5467 1
< 0.1%
5466 1
< 0.1%
5465 1
< 0.1%

지형지물부호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
AE170
5474 
AZ936
1476 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAE170
2nd rowAE170
3rd rowAE170
4th rowAE170
5th rowAE170

Common Values

ValueCountFrequency (%)
AE170 5474
78.8%
AZ936 1476
 
21.2%

Length

2023-12-12T13:44:37.099213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:44:37.212408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ae170 5474
78.8%
az936 1476
 
21.2%

전주구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size54.4 KiB
AEH002
2728 
AEH001
2441 
<NA>
1476 
AEH999
 
186
AEH000
 
89
Other values (2)
 
30

Length

Max length6
Median length6
Mean length5.5752518
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAEH001
2nd rowAEH001
3rd rowAEH001
4th rowAEH001
5th rowAEH001

Common Values

ValueCountFrequency (%)
AEH002 2728
39.3%
AEH001 2441
35.1%
<NA> 1476
21.2%
AEH999 186
 
2.7%
AEH000 89
 
1.3%
AEH004 24
 
0.3%
AEH003 6
 
0.1%

Length

2023-12-12T13:44:37.348567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:44:37.489961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aeh002 2728
39.3%
aeh001 2441
35.1%
na 1476
21.2%
aeh999 186
 
2.7%
aeh000 89
 
1.3%
aeh004 24
 
0.3%
aeh003 6
 
0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6923
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197924.09
Minimum193948.89
Maximum203475.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T13:44:37.664870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum193948.89
5-th percentile194572.85
Q1196216.43
median197891.45
Q3199519.83
95-th percentile201466.59
Maximum203475.22
Range9526.3326
Interquartile range (IQR)3303.4028

Descriptive statistics

Standard deviation2137.7929
Coefficient of variation (CV)0.010801075
Kurtosis-0.77575158
Mean197924.09
Median Absolute Deviation (MAD)1656.7613
Skewness0.20305118
Sum1.3755724 × 109
Variance4570158.5
MonotonicityNot monotonic
2023-12-12T13:44:37.856576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194542.5672 3
 
< 0.1%
195022.7754 3
 
< 0.1%
194108.1916 3
 
< 0.1%
198855.9703 2
 
< 0.1%
195587.652 2
 
< 0.1%
199509.5214 2
 
< 0.1%
194407.9524 2
 
< 0.1%
198664.27 2
 
< 0.1%
195456.3108 2
 
< 0.1%
201581.7943 2
 
< 0.1%
Other values (6913) 6927
99.7%
ValueCountFrequency (%)
193948.8903 1
< 0.1%
193953.7902 1
< 0.1%
193973.015 1
< 0.1%
193980.1494 1
< 0.1%
193982.7883 1
< 0.1%
193987.828 1
< 0.1%
193989.8468 1
< 0.1%
193995.3174 1
< 0.1%
194000.3172 1
< 0.1%
194003.4749 1
< 0.1%
ValueCountFrequency (%)
203475.2229 1
< 0.1%
203473.44 1
< 0.1%
203464.2206 1
< 0.1%
203436.186 1
< 0.1%
203426.484 1
< 0.1%
203401.302 1
< 0.1%
203396.097 1
< 0.1%
203367.501 1
< 0.1%
203361.672 1
< 0.1%
203321.2033 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct6922
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean528504.83
Minimum522357.61
Maximum534696.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.2 KiB
2023-12-12T13:44:38.021287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum522357.61
5-th percentile522993.89
Q1525362.09
median528578.68
Q3531807.53
95-th percentile533588.95
Maximum534696.55
Range12338.942
Interquartile range (IQR)6445.4431

Descriptive statistics

Standard deviation3474.7992
Coefficient of variation (CV)0.0065747729
Kurtosis-1.2431069
Mean528504.83
Median Absolute Deviation (MAD)3225.9611
Skewness-0.11769286
Sum3.6731086 × 109
Variance12074230
MonotonicityNot monotonic
2023-12-12T13:44:38.217336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
523006.7947 3
 
< 0.1%
524840.8296 3
 
< 0.1%
523490.5232 3
 
< 0.1%
533887.1515 2
 
< 0.1%
532479.8 2
 
< 0.1%
531614.1102 2
 
< 0.1%
530229.3996 2
 
< 0.1%
523009.1115 2
 
< 0.1%
526558.98 2
 
< 0.1%
526208.102 2
 
< 0.1%
Other values (6912) 6927
99.7%
ValueCountFrequency (%)
522357.6062 1
< 0.1%
522360.5875 1
< 0.1%
522360.953 1
< 0.1%
522361.7661 1
< 0.1%
522363.4205 1
< 0.1%
522366.3474 1
< 0.1%
522366.7651 1
< 0.1%
522370.0018 1
< 0.1%
522371.6737 1
< 0.1%
522372.7667 1
< 0.1%
ValueCountFrequency (%)
534696.5484 1
< 0.1%
534665.3183 1
< 0.1%
534650.4194 1
< 0.1%
534644.6783 1
< 0.1%
534639.838 1
< 0.1%
534622.7985 1
< 0.1%
534613.0905 1
< 0.1%
534609.3958 1
< 0.1%
534586.4686 1
< 0.1%
534586.0581 1
< 0.1%

Interactions

2023-12-12T13:44:36.184341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:35.521171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:35.813264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:36.310671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:35.617937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:35.930950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:36.466540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:35.707860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:44:36.045753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:44:38.350245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간지리식별번호지형지물부호전주구분위도경도
공간지리식별번호1.0000.3180.4000.5900.743
지형지물부호0.3181.000NaN0.4010.338
전주구분0.400NaN1.0000.2840.325
위도0.5900.4010.2841.0000.825
경도0.7430.3380.3250.8251.000
2023-12-12T13:44:38.784617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지형지물부호전주구분
지형지물부호1.0001.000
전주구분1.0001.000
2023-12-12T13:44:38.879749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간지리식별번호위도경도지형지물부호전주구분
공간지리식별번호1.000-0.181-0.2900.2440.223
위도-0.1811.0000.8220.3080.154
경도-0.2900.8221.0000.2590.177
지형지물부호0.2440.3080.2591.0001.000
전주구분0.2230.1540.1771.0001.000

Missing values

2023-12-12T13:44:36.622897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:44:36.721872image/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

공간지리식별번호지형지물부호전주구분위도경도
0195AE170AEH001197170.1458531390.3005
1196AE170AEH001200640.0139531387.2912
2197AE170AEH001200016.7092531383.7747
3198AE170AEH001197202.4358531377.7412
4199AE170AEH001200586.9747531376.2699
5200AE170AEH001200030.4494531367.4051
6201AE170AEH001200538.5153531366.4587
7202AE170AEH001197232.446531365.422
8203AE170AEH002200029.0395531364.755
9204AE170AEH002200055.2236531330.5402
공간지리식별번호지형지물부호전주구분위도경도
69404766AZ936<NA>198922.016532875.97
69414769AZ936<NA>198937.602532901.627
69424772AZ936<NA>198911.797532853.757
69434298AZ936<NA>200219.921530347.299
69444302AZ936<NA>200232.928530375.062
69454308AZ936<NA>200254.196530416.946
69464309AZ936<NA>200253.828530418.845
69474313AZ936<NA>200272.244530439.794
69484314AZ936<NA>200279.616530446.066
69494322AZ936<NA>200314.684530481.784