Overview

Dataset statistics

Number of variables10
Number of observations52
Missing cells56
Missing cells (%)10.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory85.5 B

Variable types

Categorical5
DateTime1
Numeric2
Text1
Unsupported1

Dataset

Description경기도 화성시의 동탄신도시 내 도로별통행량 및 통행로 정보로 관리기관 / 소재지 주소 / 일자 / 시간 / 교통량(대) / 속도(km) / 구간정보 / 소통정보(소통판정) / 도로구분 으로 이루어져있습니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15094165/fileData.do

Alerts

소통정보(소통판정) is highly overall correlated with 속도(km) and 2 other fieldsHigh correlation
관리기관 is highly overall correlated with 교통량(대) and 5 other fieldsHigh correlation
도로구분 is highly overall correlated with 교통량(대) and 5 other fieldsHigh correlation
소재지 주소 is highly overall correlated with 관리기관 and 2 other fieldsHigh correlation
시간 is highly overall correlated with 관리기관 and 2 other fieldsHigh correlation
교통량(대) is highly overall correlated with 관리기관 and 1 other fieldsHigh correlation
속도(km) is highly overall correlated with 관리기관 and 2 other fieldsHigh correlation
관리기관 is highly imbalanced (86.3%)Imbalance
소통정보(소통판정) is highly imbalanced (70.6%)Imbalance
도로구분 is highly imbalanced (86.3%)Imbalance
일자 has 1 (1.9%) missing valuesMissing
교통량(대) has 1 (1.9%) missing valuesMissing
속도(km) has 1 (1.9%) missing valuesMissing
구간정보 has 1 (1.9%) missing valuesMissing
길이 has 52 (100.0%) missing valuesMissing
길이 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-21 12:53:25.159690
Analysis finished2024-04-21 12:53:27.702963
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size544.0 B
화성시
51 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0192308
Min length3

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
화성시 51
98.1%
<NA> 1
 
1.9%

Length

2024-04-21T21:53:27.919379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:53:28.225029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화성시 51
98.1%
na 1
 
1.9%

소재지 주소
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size544.0 B
화성시 석우동 632
4 
화성시 석우동 115
4 
화성시 반송동 290-2
4 
화성시 반송동 266
4 
화성시 반송동 78-2
4 
Other values (9)
32 

Length

Max length14
Median length11
Mean length11.653846
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row화성시 석우동 590-75
2nd row화성시 석우동 590-75
3rd row화성시 석우동 590-75
4th row화성시 석우동 632
5th row화성시 석우동 632

Common Values

ValueCountFrequency (%)
화성시 석우동 632 4
 
7.7%
화성시 석우동 115 4
 
7.7%
화성시 반송동 290-2 4
 
7.7%
화성시 반송동 266 4
 
7.7%
화성시 반송동 78-2 4
 
7.7%
화성시 반송동 248 4
 
7.7%
화성시 삼성1로 130 4
 
7.7%
화성시 능동 1081-1 4
 
7.7%
화성시 능동 1151-1 4
 
7.7%
화성시 반송동 301 4
 
7.7%
Other values (4) 12
23.1%

Length

2024-04-21T21:53:28.560753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 51
33.1%
반송동 20
 
13.0%
석우동 19
 
12.3%
능동 8
 
5.2%
130 4
 
2.6%
114 4
 
2.6%
106 4
 
2.6%
301 4
 
2.6%
1151-1 4
 
2.6%
1081-1 4
 
2.6%
Other values (9) 32
20.8%

일자
Date

MISSING 

Distinct8
Distinct (%)15.7%
Missing1
Missing (%)1.9%
Memory size544.0 B
Minimum2021-10-06 00:00:00
Maximum2021-10-13 00:00:00
2024-04-21T21:53:28.862270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:53:29.186867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

시간
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size544.0 B
10:00:00~11:00:00
4 
11:00:00~12:00:00
4 
12:00:00~13:00:00
4 
13:00:00~14:00:00
4 
14:00:00~15:00:00
4 
Other values (9)
32 

Length

Max length17
Median length17
Mean length16.75
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row09:00:00~10:00:00
2nd row09:00:00~10:00:00
3rd row09:00:00~10:00:00
4th row10:00:00~11:00:00
5th row10:00:00~11:00:00

Common Values

ValueCountFrequency (%)
10:00:00~11:00:00 4
 
7.7%
11:00:00~12:00:00 4
 
7.7%
12:00:00~13:00:00 4
 
7.7%
13:00:00~14:00:00 4
 
7.7%
14:00:00~15:00:00 4
 
7.7%
15:00:00~16:00:00 4
 
7.7%
16:00:00~17:00:00 4
 
7.7%
17:00:00~18:00:00 4
 
7.7%
18:00:00~19:00:00 4
 
7.7%
19:00:00~20:00:00 4
 
7.7%
Other values (4) 12
23.1%

Length

2024-04-21T21:53:29.584315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00:00~11:00:00 4
 
7.7%
11:00:00~12:00:00 4
 
7.7%
12:00:00~13:00:00 4
 
7.7%
13:00:00~14:00:00 4
 
7.7%
14:00:00~15:00:00 4
 
7.7%
15:00:00~16:00:00 4
 
7.7%
16:00:00~17:00:00 4
 
7.7%
17:00:00~18:00:00 4
 
7.7%
18:00:00~19:00:00 4
 
7.7%
19:00:00~20:00:00 4
 
7.7%
Other values (4) 12
23.1%

교통량(대)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)98.0%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean693.90196
Minimum3
Maximum2257
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size596.0 B
2024-04-21T21:53:29.971526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile155.5
Q1402
median580
Q3870.5
95-th percentile1340.5
Maximum2257
Range2254
Interquartile range (IQR)468.5

Descriptive statistics

Standard deviation437.96175
Coefficient of variation (CV)0.63115796
Kurtosis2.5255157
Mean693.90196
Median Absolute Deviation (MAD)241
Skewness1.2760381
Sum35389
Variance191810.49
MonotonicityNot monotonic
2024-04-21T21:53:30.400891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
503 2
 
3.8%
1277 1
 
1.9%
574 1
 
1.9%
834 1
 
1.9%
355 1
 
1.9%
714 1
 
1.9%
783 1
 
1.9%
2257 1
 
1.9%
364 1
 
1.9%
1852 1
 
1.9%
Other values (40) 40
76.9%
ValueCountFrequency (%)
3 1
1.9%
145 1
1.9%
155 1
1.9%
156 1
1.9%
171 1
1.9%
172 1
1.9%
223 1
1.9%
295 1
1.9%
304 1
1.9%
355 1
1.9%
ValueCountFrequency (%)
2257 1
1.9%
1852 1
1.9%
1347 1
1.9%
1334 1
1.9%
1321 1
1.9%
1277 1
1.9%
1190 1
1.9%
1144 1
1.9%
1093 1
1.9%
960 1
1.9%

속도(km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)35.3%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean14.313725
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size596.0 B
2024-04-21T21:53:30.773065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q111
median15
Q317
95-th percentile21.5
Maximum50
Range49
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.1791091
Coefficient of variation (CV)0.5015542
Kurtosis11.482111
Mean14.313725
Median Absolute Deviation (MAD)3
Skewness2.3352589
Sum730
Variance51.539608
MonotonicityNot monotonic
2024-04-21T21:53:31.158133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
16 7
13.5%
17 7
13.5%
13 6
11.5%
7 4
 
7.7%
6 4
 
7.7%
15 3
 
5.8%
12 3
 
5.8%
18 3
 
5.8%
11 2
 
3.8%
21 2
 
3.8%
Other values (8) 10
19.2%
ValueCountFrequency (%)
1 1
 
1.9%
5 1
 
1.9%
6 4
7.7%
7 4
7.7%
9 2
 
3.8%
11 2
 
3.8%
12 3
5.8%
13 6
11.5%
14 2
 
3.8%
15 3
5.8%
ValueCountFrequency (%)
50 1
 
1.9%
27 1
 
1.9%
22 1
 
1.9%
21 2
 
3.8%
19 1
 
1.9%
18 3
5.8%
17 7
13.5%
16 7
13.5%
15 3
5.8%
14 2
 
3.8%

구간정보
Text

MISSING 

Distinct50
Distinct (%)98.0%
Missing1
Missing (%)1.9%
Memory size544.0 B
2024-04-21T21:53:31.825876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.803922
Min length16

Characters and Unicode

Total characters1010
Distinct characters87
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)96.1%

Sample

1st row영내사거리 - 영천교삼거리 방면
2nd row영천교삼거리 - 한림대병원사거리 방면
3rd row한림대병원사거리 - 영천교삼거리 방면
4th row노작공원사거리 - 청계교사거리 방면
5th row동북교차로 - 청계교사거리 방면
ValueCountFrequency (%)
방면 51
24.8%
51
24.8%
한림대병원사거리 8
 
3.9%
잎새지하차도사거리 7
 
3.4%
노작공원사거리 7
 
3.4%
예당고교사거리 7
 
3.4%
청계교사거리 6
 
2.9%
반송마을사거리 5
 
2.4%
한빛마을사거리 5
 
2.4%
영천교삼거리 4
 
1.9%
Other values (31) 55
26.7%
2024-04-21T21:53:32.633399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
15.3%
거 97
 
9.6%
리 97
 
9.6%
사 89
 
8.8%
면 51
 
5.0%
- 51
 
5.0%
방 51
 
5.0%
교 34
 
3.4%
마 21
 
2.1%
원 21
 
2.1%
Other values (77) 343
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 800
79.2%
Space Separator 155
 
15.3%
Dash Punctuation 51
 
5.0%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 97
 
12.1%
리 97
 
12.1%
사 89
 
11.1%
면 51
 
6.4%
방 51
 
6.4%
교 34
 
4.2%
마 21
 
2.6%
원 21
 
2.6%
을 17
 
2.1%
한 13
 
1.6%
Other values (73) 309
38.6%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 800
79.2%
Common 206
 
20.4%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 97
 
12.1%
리 97
 
12.1%
사 89
 
11.1%
면 51
 
6.4%
방 51
 
6.4%
교 34
 
4.2%
마 21
 
2.6%
원 21
 
2.6%
을 17
 
2.1%
한 13
 
1.6%
Other values (73) 309
38.6%
Common
ValueCountFrequency (%)
155
75.2%
- 51
 
24.8%
Latin
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 800
79.2%
ASCII 210
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
73.8%
- 51
 
24.3%
T 2
 
1.0%
K 2
 
1.0%
Hangul
ValueCountFrequency (%)
거 97
 
12.1%
리 97
 
12.1%
사 89
 
11.1%
면 51
 
6.4%
방 51
 
6.4%
교 34
 
4.2%
마 21
 
2.6%
원 21
 
2.6%
을 17
 
2.1%
한 13
 
1.6%
Other values (73) 309
38.6%

소통정보(소통판정)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size544.0 B
정체
47 
서행
 
3
원활
 
1
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0384615
Min length2

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row원활
2nd row정체
3rd row정체
4th row정체
5th row정체

Common Values

ValueCountFrequency (%)
정체 47
90.4%
서행 3
 
5.8%
원활 1
 
1.9%
<NA> 1
 
1.9%

Length

2024-04-21T21:53:33.070358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:53:33.368645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정체 47
90.4%
서행 3
 
5.8%
원활 1
 
1.9%
na 1
 
1.9%

도로구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size544.0 B
일반도로
51 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
일반도로 51
98.1%
<NA> 1
 
1.9%

Length

2024-04-21T21:53:33.706133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:53:34.000909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반도로 51
98.1%
na 1
 
1.9%

길이
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size596.0 B

Interactions

2024-04-21T21:53:26.103813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:53:25.843629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:53:26.259619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:53:25.970501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:53:34.188624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지 주소일자시간교통량(대)속도(km)구간정보소통정보(소통판정)
소재지 주소1.0001.0001.0000.3610.4470.9320.307
일자1.0001.0001.0000.0000.0000.8990.000
시간1.0001.0001.0000.3610.4470.9320.307
교통량(대)0.3610.0000.3611.0000.4030.9310.000
속도(km)0.4470.0000.4470.4031.0000.0000.919
구간정보0.9320.8990.9320.9310.0001.0001.000
소통정보(소통판정)0.3070.0000.3070.0000.9191.0001.000
2024-04-21T21:53:34.473932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소통정보(소통판정)관리기관도로구분소재지 주소시간
소통정보(소통판정)1.0001.0001.0000.1470.147
관리기관1.0001.0001.0001.0001.000
도로구분1.0001.0001.0001.0001.000
소재지 주소0.1471.0001.0001.0001.000
시간0.1471.0001.0001.0001.000
2024-04-21T21:53:34.745713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교통량(대)속도(km)관리기관소재지 주소시간소통정보(소통판정)도로구분
교통량(대)1.0000.4911.0000.1440.1440.0001.000
속도(km)0.4911.0001.0000.1980.1980.8911.000
관리기관1.0001.0001.0001.0001.0001.0001.000
소재지 주소0.1440.1981.0001.0001.0000.1471.000
시간0.1440.1981.0001.0001.0000.1471.000
소통정보(소통판정)0.0000.8911.0000.1470.1471.0001.000
도로구분1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-04-21T21:53:26.603355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:53:27.071701image/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.
2024-04-21T21:53:27.455004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관리기관소재지 주소일자시간교통량(대)속도(km)구간정보소통정보(소통판정)도로구분길이
0화성시화성시 석우동 590-752021-10-0809:00:00~10:00:00127750영내사거리 - 영천교삼거리 방면원활일반도로<NA>
1화성시화성시 석우동 590-752021-10-0809:00:00~10:00:0031영천교삼거리 - 한림대병원사거리 방면정체일반도로<NA>
2화성시화성시 석우동 590-752021-10-0809:00:00~10:00:0079921한림대병원사거리 - 영천교삼거리 방면정체일반도로<NA>
3화성시화성시 석우동 6322021-10-1110:00:00~11:00:008767노작공원사거리 - 청계교사거리 방면정체일반도로<NA>
4화성시화성시 석우동 6322021-10-1110:00:00~11:00:0029516동북교차로 - 청계교사거리 방면정체일반도로<NA>
5화성시화성시 석우동 6322021-10-1110:00:00~11:00:0082916여울공원 - 청계교사거리 방면정체일반도로<NA>
6화성시화성시 석우동 6322021-10-1110:00:00~11:00:001726예당고교사거리 - 청계교사거리 방면정체일반도로<NA>
7화성시화성시 석우동 1152021-10-1211:00:00~12:00:00119017예당고교사거리 - 노작공원사거리 방면정체일반도로<NA>
8화성시화성시 석우동 1152021-10-1211:00:00~12:00:0052314청계교사거리 - 노작공원사거리 방면정체일반도로<NA>
9화성시화성시 석우동 1152021-10-1211:00:00~12:00:0078816KT삼거리 - 노작공원사거리 방면정체일반도로<NA>
관리기관소재지 주소일자시간교통량(대)속도(km)구간정보소통정보(소통판정)도로구분길이
42화성시화성시 반송동 3012021-10-0619:00:00~20:00:00133417교육지원청사거리 - 반송초교사거리 방면정체일반도로<NA>
43화성시화성시 석우동 1062021-10-0720:00:00~21:00:0086521한림대병원사거리 - 잎새지하차도사거리 방면서행일반도로<NA>
44화성시화성시 석우동 1062021-10-0720:00:00~21:00:001459노작공원사거리 - 잎새지하차도사거리 방면정체일반도로<NA>
45화성시화성시 석우동 1062021-10-0720:00:00~21:00:0050719한빛마을사거리 - 잎새지하차도사거리 방면정체일반도로<NA>
46화성시화성시 석우동 1062021-10-0720:00:00~21:00:00109313반송마을사거리 - 잎새지하차도사거리 방면정체일반도로<NA>
47화성시화성시 석우동 1142021-10-0821:00:00~22:00:0151217한림대병원사거리 - 예당고교사거리 방면정체일반도로<NA>
48화성시화성시 석우동 1142021-10-0821:00:00~22:00:0182117영천사거리 - 예당고교사거리 방면정체일반도로<NA>
49화성시화성시 석우동 1142021-10-0821:00:00~22:00:011566청계교사거리 - 예당고교사거리 방면정체일반도로<NA>
50화성시화성시 석우동 1142021-10-0821:00:00~22:00:015945노작공원사거리 - 예당고교사거리 방면정체일반도로<NA>
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