Overview

Dataset statistics

Number of variables13
Number of observations1477
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory164.6 KiB
Average record size in memory114.1 B

Variable types

Numeric10
Categorical2
Text1

Dataset

Description특별수송기간 도로별 집중률
Author경기도교통정보센터
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=PM4C8SLYP3CYVKUNL2C632757562&infSeq=1

Alerts

호선코드 is highly overall correlated with 호선명High correlation
설기간 is highly overall correlated with 설기간 최대 and 2 other fieldsHigh correlation
설기간 최대 is highly overall correlated with 설기간 and 3 other fieldsHigh correlation
휴가기간 is highly overall correlated with 휴가기간 최대 and 2 other fieldsHigh correlation
휴가기간 최대 is highly overall correlated with 설기간 최대 and 3 other fieldsHigh correlation
추석기간 is highly overall correlated with 설기간 and 4 other fieldsHigh correlation
추석기간 최대 is highly overall correlated with 설기간 and 4 other fieldsHigh correlation
연말기간 is highly overall correlated with 연말기간 최대High correlation
연말기간 최대 is highly overall correlated with 연말기간High correlation
호선명 is highly overall correlated with 호선코드 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 호선명High correlation
설기간 has 229 (15.5%) zerosZeros
설기간 최대 has 229 (15.5%) zerosZeros
휴가기간 has 257 (17.4%) zerosZeros
휴가기간 최대 has 257 (17.4%) zerosZeros
추석기간 has 267 (18.1%) zerosZeros
추석기간 최대 has 267 (18.1%) zerosZeros
연말기간 has 260 (17.6%) zerosZeros
연말기간 최대 has 260 (17.6%) zerosZeros

Reproduction

Analysis started2023-12-10 21:49:06.530802
Analysis finished2023-12-10 21:49:17.908153
Duration11.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct21
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.6858
Minimum2002
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:17.952707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2003
Q12007
median2012
Q32017
95-th percentile2021
Maximum2022
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.9429443
Coefficient of variation (CV)0.0029542109
Kurtosis-1.1589897
Mean2011.6858
Median Absolute Deviation (MAD)5
Skewness0.048883603
Sum2971260
Variance35.318587
MonotonicityDecreasing
2023-12-11T06:49:18.061429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2015 75
 
5.1%
2011 73
 
4.9%
2013 73
 
4.9%
2007 73
 
4.9%
2008 73
 
4.9%
2009 73
 
4.9%
2010 73
 
4.9%
2004 73
 
4.9%
2012 73
 
4.9%
2014 73
 
4.9%
Other values (11) 745
50.4%
ValueCountFrequency (%)
2002 73
4.9%
2003 73
4.9%
2004 73
4.9%
2005 73
4.9%
2006 73
4.9%
2007 73
4.9%
2008 73
4.9%
2009 73
4.9%
2010 73
4.9%
2011 73
4.9%
ValueCountFrequency (%)
2022 67
4.5%
2021 44
3.0%
2020 67
4.5%
2019 66
4.5%
2018 69
4.7%
2017 69
4.7%
2016 71
4.8%
2015 75
5.1%
2014 73
4.9%
2013 73
4.9%

호선명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
일반국도 43호선
198 
일반국도 37호선
187 
일반국도 38호선
151 
일반국도 39호선
137 
일반국도 45호선
132 
Other values (12)
672 

Length

Max length9
Median length9
Mean length8.6797563
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반국도 1호선
2nd row일반국도 1호선
3rd row일반국도 1호선
4th row일반국도 17호선
5th row일반국도 3호선

Common Values

ValueCountFrequency (%)
일반국도 43호선 198
13.4%
일반국도 37호선 187
12.7%
일반국도 38호선 151
10.2%
일반국도 39호선 137
9.3%
일반국도 45호선 132
8.9%
일반국도 3호선 131
8.9%
일반국도 42호선 110
7.4%
일반국도 1호선 90
6.1%
일반국도 6호선 77
 
5.2%
일반국도 47호선 62
 
4.2%
Other values (7) 202
13.7%

Length

2023-12-11T06:49:18.167668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반국도 1442
49.4%
43호선 198
 
6.8%
37호선 187
 
6.4%
38호선 151
 
5.2%
39호선 137
 
4.7%
45호선 132
 
4.5%
3호선 131
 
4.5%
42호선 110
 
3.8%
1호선 90
 
3.1%
6호선 77
 
2.6%
Other values (8) 264
 
9.0%

호선코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.565335
Minimum1
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:18.469738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q137
median39
Q344
95-th percentile75
Maximum87
Range86
Interquartile range (IQR)7

Descriptive statistics

Standard deviation19.087215
Coefficient of variation (CV)0.53668031
Kurtosis0.49225495
Mean35.565335
Median Absolute Deviation (MAD)4
Skewness-0.23503498
Sum52530
Variance364.32178
MonotonicityNot monotonic
2023-12-11T06:49:18.551083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
43 198
13.4%
37 187
12.7%
38 151
10.2%
39 137
9.3%
45 132
8.9%
3 131
8.9%
42 110
7.4%
1 90
6.1%
6 77
 
5.2%
47 62
 
4.2%
Other values (8) 202
13.7%
ValueCountFrequency (%)
1 90
6.1%
3 131
8.9%
6 77
 
5.2%
17 21
 
1.4%
37 187
12.7%
38 151
10.2%
39 137
9.3%
42 110
7.4%
43 198
13.4%
44 20
 
1.4%
ValueCountFrequency (%)
87 14
 
0.9%
82 28
 
1.9%
77 21
 
1.4%
75 21
 
1.4%
48 56
 
3.8%
47 62
 
4.2%
46 21
 
1.4%
45 132
8.9%
44 20
 
1.4%
43 198
13.4%
Distinct90
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T06:49:18.770738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters10339
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row0141-01
2nd row0142-00
3rd row0134-00
4th row1728-02
5th row0334-01
ValueCountFrequency (%)
0141-01 21
 
1.4%
0142-00 21
 
1.4%
4206-02 21
 
1.4%
4304-02 21
 
1.4%
4304-00 21
 
1.4%
4301-01 21
 
1.4%
0606-04 21
 
1.4%
4506-02 21
 
1.4%
4512-01 21
 
1.4%
0605-00 21
 
1.4%
Other values (80) 1267
85.8%
2023-12-11T06:49:19.104446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3226
31.2%
- 1477
14.3%
3 1099
 
10.6%
4 938
 
9.1%
1 919
 
8.9%
2 890
 
8.6%
8 482
 
4.7%
7 461
 
4.5%
5 299
 
2.9%
6 289
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8862
85.7%
Dash Punctuation 1477
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3226
36.4%
3 1099
 
12.4%
4 938
 
10.6%
1 919
 
10.4%
2 890
 
10.0%
8 482
 
5.4%
7 461
 
5.2%
5 299
 
3.4%
6 289
 
3.3%
9 259
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 1477
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3226
31.2%
- 1477
14.3%
3 1099
 
10.6%
4 938
 
9.1%
1 919
 
8.9%
2 890
 
8.6%
8 482
 
4.7%
7 461
 
4.5%
5 299
 
2.9%
6 289
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3226
31.2%
- 1477
14.3%
3 1099
 
10.6%
4 938
 
9.1%
1 919
 
8.9%
2 890
 
8.6%
8 482
 
4.7%
7 461
 
4.5%
5 299
 
2.9%
6 289
 
2.8%

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
포천
192 
평택
168 
광주
142 
용인
131 
여주
116 
Other values (16)
728 

Length

Max length3
Median length2
Mean length2.0020311
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row파주
2nd row파주
3rd row평택
4th row용인
5th row양주

Common Values

ValueCountFrequency (%)
포천 192
13.0%
평택 168
11.4%
광주 142
9.6%
용인 131
8.9%
여주 116
7.9%
가평 113
7.7%
화성 108
 
7.3%
파주 77
 
5.2%
양평 76
 
5.1%
안성 75
 
5.1%
Other values (11) 279
18.9%

Length

2023-12-11T06:49:19.221072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포천 192
13.0%
평택 168
11.4%
광주 142
9.6%
용인 131
8.9%
여주 116
7.9%
가평 113
7.7%
화성 108
 
7.3%
파주 77
 
5.2%
양평 76
 
5.1%
안성 75
 
5.1%
Other values (11) 279
18.9%

설기간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct128
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.74911307
Minimum0
Maximum2.51
Zeros229
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:19.321405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.7
median0.84
Q30.94
95-th percentile1.2
Maximum2.51
Range2.51
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.37280935
Coefficient of variation (CV)0.49766767
Kurtosis0.91072445
Mean0.74911307
Median Absolute Deviation (MAD)0.12
Skewness-0.7603052
Sum1106.44
Variance0.13898681
MonotonicityNot monotonic
2023-12-11T06:49:19.442465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 229
 
15.5%
0.91 42
 
2.8%
0.86 41
 
2.8%
0.94 40
 
2.7%
0.81 38
 
2.6%
0.82 38
 
2.6%
0.87 37
 
2.5%
0.84 37
 
2.5%
0.88 36
 
2.4%
0.85 35
 
2.4%
Other values (118) 904
61.2%
ValueCountFrequency (%)
0.0 229
15.5%
0.06 1
 
0.1%
0.13 1
 
0.1%
0.15 1
 
0.1%
0.16 1
 
0.1%
0.18 1
 
0.1%
0.21 1
 
0.1%
0.26 1
 
0.1%
0.29 1
 
0.1%
0.32 1
 
0.1%
ValueCountFrequency (%)
2.51 1
0.1%
2.49 1
0.1%
1.84 1
0.1%
1.79 2
0.1%
1.78 1
0.1%
1.76 1
0.1%
1.63 1
0.1%
1.61 1
0.1%
1.59 1
0.1%
1.57 1
0.1%

설기간 최대
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct167
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93320921
Minimum0
Maximum3.21
Zeros229
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:19.549596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.84
median0.99
Q31.18
95-th percentile1.6
Maximum3.21
Range3.21
Interquartile range (IQR)0.34

Descriptive statistics

Standard deviation0.4879824
Coefficient of variation (CV)0.52290783
Kurtosis0.92546835
Mean0.93320921
Median Absolute Deviation (MAD)0.17
Skewness-0.38555611
Sum1378.35
Variance0.23812682
MonotonicityNot monotonic
2023-12-11T06:49:19.657505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 229
 
15.5%
0.95 39
 
2.6%
0.96 37
 
2.5%
1.0 36
 
2.4%
1.02 35
 
2.4%
0.97 34
 
2.3%
1.03 34
 
2.3%
0.99 34
 
2.3%
0.98 34
 
2.3%
1.01 31
 
2.1%
Other values (157) 934
63.2%
ValueCountFrequency (%)
0.0 229
15.5%
0.1 1
 
0.1%
0.2 1
 
0.1%
0.21 1
 
0.1%
0.24 1
 
0.1%
0.25 1
 
0.1%
0.3 1
 
0.1%
0.33 1
 
0.1%
0.44 1
 
0.1%
0.46 1
 
0.1%
ValueCountFrequency (%)
3.21 1
0.1%
3.13 1
0.1%
2.7 1
0.1%
2.67 1
0.1%
2.58 1
0.1%
2.47 1
0.1%
2.33 1
0.1%
2.19 1
0.1%
2.13 2
0.1%
2.12 1
0.1%

휴가기간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct139
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.85
Minimum0
Maximum3.33
Zeros257
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:19.765660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.83
median0.96
Q31.04
95-th percentile1.41
Maximum3.33
Range3.33
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.4592537
Coefficient of variation (CV)0.54029847
Kurtosis2.0422581
Mean0.85
Median Absolute Deviation (MAD)0.1
Skewness-0.25826197
Sum1255.45
Variance0.21091396
MonotonicityNot monotonic
2023-12-11T06:49:19.870819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 257
 
17.4%
0.99 64
 
4.3%
0.97 63
 
4.3%
0.96 59
 
4.0%
0.98 58
 
3.9%
0.94 44
 
3.0%
1.01 43
 
2.9%
0.95 42
 
2.8%
1.0 41
 
2.8%
0.93 38
 
2.6%
Other values (129) 768
52.0%
ValueCountFrequency (%)
0.0 257
17.4%
0.16 1
 
0.1%
0.17 2
 
0.1%
0.19 2
 
0.1%
0.29 1
 
0.1%
0.33 2
 
0.1%
0.38 1
 
0.1%
0.44 1
 
0.1%
0.45 1
 
0.1%
0.48 4
 
0.3%
ValueCountFrequency (%)
3.33 1
0.1%
3.16 1
0.1%
3.03 1
0.1%
2.9 1
0.1%
2.85 1
0.1%
2.78 1
0.1%
2.64 1
0.1%
2.3 1
0.1%
2.18 1
0.1%
2.11 1
0.1%

휴가기간 최대
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct198
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0474949
Minimum0
Maximum4.88
Zeros257
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:19.990822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.95
median1.1
Q31.24
95-th percentile2.07
Maximum4.88
Range4.88
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.65266513
Coefficient of variation (CV)0.62307235
Kurtosis4.397915
Mean1.0474949
Median Absolute Deviation (MAD)0.14
Skewness0.87891259
Sum1547.15
Variance0.42597177
MonotonicityNot monotonic
2023-12-11T06:49:20.110983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 257
 
17.4%
1.11 48
 
3.2%
1.09 41
 
2.8%
1.1 41
 
2.8%
1.12 37
 
2.5%
1.15 36
 
2.4%
1.14 35
 
2.4%
1.07 32
 
2.2%
1.05 31
 
2.1%
1.13 31
 
2.1%
Other values (188) 888
60.1%
ValueCountFrequency (%)
0.0 257
17.4%
0.18 1
 
0.1%
0.22 1
 
0.1%
0.25 1
 
0.1%
0.26 1
 
0.1%
0.35 1
 
0.1%
0.37 1
 
0.1%
0.48 2
 
0.1%
0.53 1
 
0.1%
0.54 1
 
0.1%
ValueCountFrequency (%)
4.88 1
0.1%
4.66 1
0.1%
4.53 1
0.1%
4.5 1
0.1%
4.25 1
0.1%
4.08 1
0.1%
3.9 1
0.1%
3.79 1
0.1%
3.71 1
0.1%
3.63 1
0.1%

추석기간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct154
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86582261
Minimum0
Maximum3.04
Zeros267
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:20.228831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.77
median0.98
Q31.11
95-th percentile1.51
Maximum3.04
Range3.04
Interquartile range (IQR)0.34

Descriptive statistics

Standard deviation0.47359185
Coefficient of variation (CV)0.54698485
Kurtosis0.33218977
Mean0.86582261
Median Absolute Deviation (MAD)0.17
Skewness-0.55780616
Sum1278.82
Variance0.22428924
MonotonicityNot monotonic
2023-12-11T06:49:20.348551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 267
 
18.1%
0.98 39
 
2.6%
1.01 34
 
2.3%
1.07 33
 
2.2%
1.08 33
 
2.2%
1.03 32
 
2.2%
1.06 32
 
2.2%
1.02 31
 
2.1%
0.9 30
 
2.0%
0.96 28
 
1.9%
Other values (144) 918
62.2%
ValueCountFrequency (%)
0.0 267
18.1%
0.11 1
 
0.1%
0.17 1
 
0.1%
0.21 1
 
0.1%
0.22 1
 
0.1%
0.23 1
 
0.1%
0.25 1
 
0.1%
0.29 1
 
0.1%
0.35 1
 
0.1%
0.39 1
 
0.1%
ValueCountFrequency (%)
3.04 1
0.1%
2.83 1
0.1%
2.41 1
0.1%
2.26 1
0.1%
2.2 1
0.1%
2.14 1
0.1%
2.13 1
0.1%
2.0 1
0.1%
1.98 1
0.1%
1.96 1
0.1%

추석기간 최대
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct182
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.033629
Minimum0
Maximum3.71
Zeros267
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:20.471312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.9
median1.1
Q31.34
95-th percentile1.932
Maximum3.71
Range3.71
Interquartile range (IQR)0.44

Descriptive statistics

Standard deviation0.59807661
Coefficient of variation (CV)0.57861827
Kurtosis0.55827987
Mean1.033629
Median Absolute Deviation (MAD)0.22
Skewness-0.14597629
Sum1526.67
Variance0.35769563
MonotonicityNot monotonic
2023-12-11T06:49:20.597817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 267
 
18.1%
1.1 35
 
2.4%
1.15 33
 
2.2%
1.11 32
 
2.2%
1.08 31
 
2.1%
1.12 31
 
2.1%
1.13 31
 
2.1%
1.14 30
 
2.0%
1.07 28
 
1.9%
1.02 25
 
1.7%
Other values (172) 934
63.2%
ValueCountFrequency (%)
0.0 267
18.1%
0.17 1
 
0.1%
0.26 1
 
0.1%
0.29 1
 
0.1%
0.33 1
 
0.1%
0.38 1
 
0.1%
0.39 1
 
0.1%
0.43 1
 
0.1%
0.46 1
 
0.1%
0.52 2
 
0.1%
ValueCountFrequency (%)
3.71 1
 
0.1%
3.51 1
 
0.1%
3.38 1
 
0.1%
3.36 1
 
0.1%
2.8 1
 
0.1%
2.72 1
 
0.1%
2.63 1
 
0.1%
2.61 2
0.1%
2.55 3
0.2%
2.52 2
0.1%

연말기간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct159
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.80949898
Minimum0
Maximum3.32
Zeros260
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:20.744358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.76
median0.91
Q31
95-th percentile1.382
Maximum3.32
Range3.32
Interquartile range (IQR)0.24

Descriptive statistics

Standard deviation0.4515757
Coefficient of variation (CV)0.55784592
Kurtosis1.2503969
Mean0.80949898
Median Absolute Deviation (MAD)0.11
Skewness-0.21806924
Sum1195.63
Variance0.20392062
MonotonicityNot monotonic
2023-12-11T06:49:20.917067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 260
 
17.6%
0.94 53
 
3.6%
0.92 51
 
3.5%
0.91 49
 
3.3%
0.93 46
 
3.1%
0.89 46
 
3.1%
0.87 40
 
2.7%
0.96 39
 
2.6%
0.99 38
 
2.6%
0.88 36
 
2.4%
Other values (149) 819
55.5%
ValueCountFrequency (%)
0.0 260
17.6%
0.05 1
 
0.1%
0.12 1
 
0.1%
0.15 2
 
0.1%
0.17 2
 
0.1%
0.2 1
 
0.1%
0.21 1
 
0.1%
0.25 1
 
0.1%
0.26 1
 
0.1%
0.29 1
 
0.1%
ValueCountFrequency (%)
3.32 1
0.1%
2.62 1
0.1%
2.4 1
0.1%
2.36 1
0.1%
2.35 1
0.1%
2.24 1
0.1%
2.22 2
0.1%
2.21 1
0.1%
2.2 1
0.1%
2.18 1
0.1%

연말기간 최대
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct185
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93953961
Minimum0
Maximum3.66
Zeros260
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T06:49:21.130164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.89
median1.03
Q31.12
95-th percentile1.72
Maximum3.66
Range3.66
Interquartile range (IQR)0.23

Descriptive statistics

Standard deviation0.54890115
Coefficient of variation (CV)0.58422353
Kurtosis1.9532305
Mean0.93953961
Median Absolute Deviation (MAD)0.11
Skewness0.18823221
Sum1387.7
Variance0.30129247
MonotonicityNot monotonic
2023-12-11T06:49:21.338820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 260
 
17.6%
1.03 57
 
3.9%
1.07 56
 
3.8%
1.05 51
 
3.5%
1.06 49
 
3.3%
1.08 47
 
3.2%
1.02 46
 
3.1%
1.04 45
 
3.0%
1.09 39
 
2.6%
1.01 37
 
2.5%
Other values (175) 790
53.5%
ValueCountFrequency (%)
0.0 260
17.6%
0.06 1
 
0.1%
0.13 1
 
0.1%
0.16 1
 
0.1%
0.18 2
 
0.1%
0.21 1
 
0.1%
0.23 2
 
0.1%
0.29 2
 
0.1%
0.34 1
 
0.1%
0.36 2
 
0.1%
ValueCountFrequency (%)
3.66 1
0.1%
3.36 1
0.1%
3.22 1
0.1%
3.11 1
0.1%
3.07 1
0.1%
3.03 1
0.1%
3.02 1
0.1%
3.0 1
0.1%
2.93 1
0.1%
2.85 1
0.1%

Interactions

2023-12-11T06:49:16.705663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.362282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.400941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.361967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.320361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.316083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.343297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.598435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.575096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.712482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.814408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.461357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.538237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.457454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.428820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.431071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.459337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.702756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.695238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.849207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.952875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.558090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.632484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.539586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.548155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.530667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.548299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.795614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.792675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.946410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.064511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.669035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.702658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.624422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.634233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.642984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.637777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.878599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.903642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.049649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.181289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.770129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.808714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.734391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.734193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.731205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.993222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.968388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.021981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.152527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.269707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.859727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.896924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.831304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.819384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.821040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.074515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.065580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.136857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.249588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.350168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:07.962349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.986624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.913809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.901831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.916431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.156482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.159530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.225737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.348486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.435449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.054827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.077541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.010642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.004172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.031415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.252282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.266324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.327401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.441921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.517183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.168006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.181680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.121961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.117572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.155814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.349737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.370857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.464097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.532401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:17.594795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:08.265809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:09.273281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:10.214933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:11.211019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:12.245721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:13.459399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:14.470029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:15.589143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:49:16.619212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:49:21.478119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도호선명호선코드지점번호시군명설기간설기간 최대휴가기간휴가기간 최대추석기간추석기간 최대연말기간연말기간 최대
년도1.0000.0000.0000.0000.0000.3390.4140.5230.4570.3820.3350.5040.582
호선명0.0001.0001.0001.0000.9280.3730.3680.3730.4650.3520.3660.3250.324
호선코드0.0001.0001.0001.0000.7750.2810.1240.3340.3440.1730.1450.0430.089
지점번호0.0001.0001.0001.0000.9990.6880.6900.7680.8370.6740.7370.6300.598
시군명0.0000.9280.7750.9991.0000.4340.4330.4150.4700.4410.4230.4110.374
설기간0.3390.3730.2810.6880.4341.0000.9010.6810.5900.9250.8740.8340.652
설기간 최대0.4140.3680.1240.6900.4330.9011.0000.7970.7290.8180.7750.6880.772
휴가기간0.5230.3730.3340.7680.4150.6810.7971.0000.9550.7350.6880.7050.796
휴가기간 최대0.4570.4650.3440.8370.4700.5900.7290.9551.0000.6740.6730.6380.742
추석기간0.3820.3520.1730.6740.4410.9250.8180.7350.6741.0000.9560.8510.678
추석기간 최대0.3350.3660.1450.7370.4230.8740.7750.6880.6730.9561.0000.7880.615
연말기간0.5040.3250.0430.6300.4110.8340.6880.7050.6380.8510.7881.0000.921
연말기간 최대0.5820.3240.0890.5980.3740.6520.7720.7960.7420.6780.6150.9211.000
2023-12-11T06:49:21.611719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선명시군명
호선명1.0000.618
시군명0.6181.000
2023-12-11T06:49:21.700603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도호선코드설기간설기간 최대휴가기간휴가기간 최대추석기간추석기간 최대연말기간연말기간 최대호선명시군명
년도1.0000.033-0.0440.1700.3070.3830.0050.155-0.288-0.2580.0000.000
호선코드0.0331.000-0.160-0.118-0.034-0.005-0.108-0.073-0.068-0.0130.9970.482
설기간-0.044-0.1601.0000.8650.4150.4110.6170.5470.2980.2850.1630.182
설기간 최대0.170-0.1180.8651.0000.4620.5060.5950.6210.2300.2600.1530.174
휴가기간0.307-0.0340.4150.4621.0000.8460.6110.6250.1650.1780.1630.165
휴가기간 최대0.383-0.0050.4110.5060.8461.0000.6160.6870.1250.1900.2110.193
추석기간0.005-0.1080.6170.5950.6110.6161.0000.9340.3240.3270.1530.183
추석기간 최대0.155-0.0730.5470.6210.6250.6870.9341.0000.2410.2720.1590.176
연말기간-0.288-0.0680.2980.2300.1650.1250.3240.2411.0000.9290.1390.171
연말기간 최대-0.258-0.0130.2850.2600.1780.1900.3270.2720.9291.0000.1330.143
호선명0.0000.9970.1630.1530.1630.2110.1530.1590.1390.1331.0000.618
시군명0.0000.4820.1820.1740.1650.1930.1830.1760.1710.1430.6181.000

Missing values

2023-12-11T06:49:17.718206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:49:17.856016image/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

년도호선명호선코드지점번호시군명설기간설기간 최대휴가기간휴가기간 최대추석기간추석기간 최대연말기간연말기간 최대
02022일반국도 1호선10141-01파주0.730.890.971.110.820.890.991.05
12022일반국도 1호선10142-00파주0.790.890.971.281.321.730.870.97
22022일반국도 1호선10134-00평택0.780.950.961.090.771.160.981.07
32022일반국도 17호선171728-02용인0.661.110.981.180.861.170.941.08
42022일반국도 3호선30334-01양주0.730.850.971.140.860.930.991.09
52022일반국도 3호선30335-01연천0.840.941.031.211.061.221.01.06
62022일반국도 3호선30331-01광주0.891.020.00.00.00.00.00.0
72022일반국도 3호선30331-00광주0.931.181.061.331.152.040.91.01
82022일반국도 3호선30336-02연천0.760.851.021.161.051.140.941.04
92022일반국도 3호선30328-02여주0.91.881.031.411.42.610.911.07
년도호선명호선코드지점번호시군명설기간설기간 최대휴가기간휴가기간 최대추석기간추석기간 최대연말기간연말기간 최대
14672002일반국도 47호선474707-00남양0.890.960.971.010.941.041.031.16
14682002일반국도 48호선484802-03김포1.21.610.80.841.271.491.321.62
14692002일반국도 48호선484802-02김포0.881.050.941.00.961.071.061.17
14702002일반국도 48호선484803-02김포0.820.951.011.080.961.10.991.08
14712002일반국도 6호선60605-00남양0.00.00.00.00.00.00.00.0
14722002일반국도 6호선60606-04양평1.181.410.931.171.391.571.481.85
14732002일반국도 6호선60608-01양평1.441.951.121.281.611.711.992.48
14742002일반국도 6호선60608-02양평1.451.780.931.221.721.852.22.84
14752002일반국도 77호선777721-01평택0.60.790.951.130.640.720.840.95
14762002일반국도 82호선828201-04화성0.00.00.00.00.00.00.00.0