Overview

Dataset statistics

Number of variables6
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory55.7 B

Variable types

Categorical3
Numeric3

Dataset

Description새만금 방조제는 전라북도 군산시와 부안군을 이어주는 세계에서 가장 긴 방조제로 입니다. 2022년 1월 부터 도로 교통량 자료입니다. 출발지, 도착지, 대형차량, 소형차량 건수 입니다.
URLhttps://www.data.go.kr/data/15002284/fileData.do

Alerts

출발 is highly overall correlated with 대형 차량 and 2 other fieldsHigh correlation
도착지 is highly overall correlated with 대형 차량 and 2 other fieldsHigh correlation
대형 차량 is highly overall correlated with 소형 차량 and 2 other fieldsHigh correlation
소형 차량 is highly overall correlated with 대형 차량 and 2 other fieldsHigh correlation
대형 차량 has unique valuesUnique
소형 차량 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:40:10.512920
Analysis finished2023-12-12 09:40:12.076086
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조사일 년
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
2022
24 
2023
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 24
66.7%
2023 12
33.3%

Length

2023-12-12T18:40:12.170909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:40:12.287687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 24
66.7%
2023 12
33.3%

조사월
Real number (ℝ)

Distinct12
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:40:12.422717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile11.25
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.3509061
Coefficient of variation (CV)0.60925565
Kurtosis-0.84710482
Mean5.5
Median Absolute Deviation (MAD)2.5
Skewness0.46311758
Sum198
Variance11.228571
MonotonicityNot monotonic
2023-12-12T18:40:12.557374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 4
11.1%
2 4
11.1%
3 4
11.1%
4 4
11.1%
5 4
11.1%
6 4
11.1%
7 2
5.6%
8 2
5.6%
9 2
5.6%
10 2
5.6%
Other values (2) 4
11.1%
ValueCountFrequency (%)
1 4
11.1%
2 4
11.1%
3 4
11.1%
4 4
11.1%
5 4
11.1%
6 4
11.1%
7 2
5.6%
8 2
5.6%
9 2
5.6%
10 2
5.6%
ValueCountFrequency (%)
12 2
5.6%
11 2
5.6%
10 2
5.6%
9 2
5.6%
8 2
5.6%
7 2
5.6%
6 4
11.1%
5 4
11.1%
4 4
11.1%
3 4
11.1%

출발
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
부안
18 
군산
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부안 18
50.0%
군산 18
50.0%

Length

2023-12-12T18:40:12.707793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:40:12.830386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부안 18
50.0%
군산 18
50.0%

도착지
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
군산
18 
부안
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군산 18
50.0%
부안 18
50.0%

Length

2023-12-12T18:40:12.952905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:40:13.064742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군산 18
50.0%
부안 18
50.0%

대형 차량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3962.9444
Minimum837
Maximum29376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:40:13.188014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum837
5-th percentile945.5
Q11886
median2627.5
Q34851.75
95-th percentile7173.75
Maximum29376
Range28539
Interquartile range (IQR)2965.75

Descriptive statistics

Standard deviation4765.5413
Coefficient of variation (CV)1.2025254
Kurtosis24.229318
Mean3962.9444
Median Absolute Deviation (MAD)1552
Skewness4.5567874
Sum142666
Variance22710384
MonotonicityNot monotonic
2023-12-12T18:40:13.319407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1096 1
 
2.8%
4818 1
 
2.8%
6845 1
 
2.8%
4449 1
 
2.8%
3938 1
 
2.8%
837 1
 
2.8%
1055 1
 
2.8%
1475 1
 
2.8%
2424 1
 
2.8%
1994 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
837 1
2.8%
893 1
2.8%
963 1
2.8%
984 1
2.8%
1055 1
2.8%
1096 1
2.8%
1475 1
2.8%
1787 1
2.8%
1877 1
2.8%
1889 1
2.8%
ValueCountFrequency (%)
29376 1
2.8%
8160 1
2.8%
6845 1
2.8%
6790 1
2.8%
6062 1
2.8%
5710 1
2.8%
5420 1
2.8%
5027 1
2.8%
4953 1
2.8%
4818 1
2.8%

소형 차량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73143.25
Minimum21749
Maximum149697
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T18:40:13.452872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21749
5-th percentile27587.25
Q137758
median55259.5
Q3104470.25
95-th percentile140852.25
Maximum149697
Range127948
Interquartile range (IQR)66712.25

Descriptive statistics

Standard deviation42265.513
Coefficient of variation (CV)0.57784571
Kurtosis-1.1682931
Mean73143.25
Median Absolute Deviation (MAD)25381
Skewness0.58547174
Sum2633157
Variance1.7863736 × 109
MonotonicityNot monotonic
2023-12-12T18:40:13.904717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
32534 1
 
2.8%
139982 1
 
2.8%
136890 1
 
2.8%
91013 1
 
2.8%
57658 1
 
2.8%
28073 1
 
2.8%
27027 1
 
2.8%
30571 1
 
2.8%
48005 1
 
2.8%
37983 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
21749 1
2.8%
27027 1
2.8%
27774 1
2.8%
28073 1
2.8%
29186 1
2.8%
30571 1
2.8%
32534 1
2.8%
35277 1
2.8%
37083 1
2.8%
37983 1
2.8%
ValueCountFrequency (%)
149697 1
2.8%
143463 1
2.8%
139982 1
2.8%
139686 1
2.8%
139575 1
2.8%
136890 1
2.8%
131158 1
2.8%
127995 1
2.8%
114962 1
2.8%
100973 1
2.8%

Interactions

2023-12-12T18:40:11.389083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:10.792586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:11.080936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:11.514324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:10.886456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:11.177801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:11.646834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:10.978399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:40:11.280380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:40:14.002671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사일 년조사월출발도착지대형 차량소형 차량
조사일 년1.0000.0000.0000.0000.3350.438
조사월0.0001.0000.0000.0000.0000.000
출발0.0000.0001.0000.9960.9360.995
도착지0.0000.0000.9961.0000.9360.995
대형 차량0.3350.0000.9360.9361.0000.791
소형 차량0.4380.0000.9950.9950.7911.000
2023-12-12T18:40:14.107852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사일 년출발도착지
조사일 년1.0000.0000.000
출발0.0001.0000.943
도착지0.0000.9431.000
2023-12-12T18:40:14.193012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사월대형 차량소형 차량조사일 년출발도착지
조사월1.0000.2590.2120.0000.0000.000
대형 차량0.2591.0000.9070.1880.7530.753
소형 차량0.2120.9071.0000.2620.8200.820
조사일 년0.0000.1880.2621.0000.0000.000
출발0.0000.7530.8200.0001.0000.943
도착지0.0000.7530.8200.0000.9431.000

Missing values

2023-12-12T18:40:11.800037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:40:12.011529image/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

조사일 년조사월출발도착지대형 차량소형 차량
020221부안군산109632534
120222부안군산98429186
220223부안군산96327774
320224부안군산178742658
420225부안군산221044554
520226부안군산188935277
620227부안군산198742510
720228부안군산210852861
820229부안군산239251575
9202210부안군산279548277
조사일 년조사월출발도착지대형 차량소형 차량
2620233부안군산147530571
2720234부안군산242448005
2820235부안군산199437983
2920236부안군산187737083
3020231군산부안252865296
3120232군산부안2937672107
3220233군산부안4953114962
3320234군산부안8160139575
3420235군산부안6790131158
3520236군산부안6062127995