Overview

Dataset statistics

Number of variables10
Number of observations96
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory89.4 B

Variable types

Categorical3
Numeric7

Dataset

Description서울도시고속도로 노선별 요일별 교통량- 노선별 대표구간 시간대별 교통량- 세부구간별 데이터가 상이하기 때문에 해당노선의 특성을 잘 반영하는 지점을 대표구간 자료료 사용함
Author서울시설공단
URLhttps://www.data.go.kr/data/15069979/fileData.do

Alerts

년도 has constant value ""Constant
일요일(휴일포함) is highly overall correlated with 월요일 and 6 other fieldsHigh correlation
월요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
화요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
수요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
목요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
금요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
토요일 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
도로명 is highly overall correlated with 일요일(휴일포함) and 6 other fieldsHigh correlation
일요일(휴일포함) has unique valuesUnique
월요일 has unique valuesUnique
화요일 has unique valuesUnique
수요일 has unique valuesUnique
목요일 has unique valuesUnique
금요일 has unique valuesUnique
토요일 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:38:23.607479
Analysis finished2024-04-21 01:38:30.271220
Duration6.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023
96 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 96
100.0%

Length

2024-04-21T10:38:30.339917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:38:30.423251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 96
100.0%

월
Categorical

Distinct12
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size900.0 B
2023-01
8 
2023-02
8 
2023-03
8 
2023-04
8 
2023-05
8 
Other values (7)
56 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01
2nd row2023-02
3rd row2023-03
4th row2023-04
5th row2023-05

Common Values

ValueCountFrequency (%)
2023-01 8
8.3%
2023-02 8
8.3%
2023-03 8
8.3%
2023-04 8
8.3%
2023-05 8
8.3%
2023-06 8
8.3%
2023-07 8
8.3%
2023-08 8
8.3%
2023-09 8
8.3%
2023-10 8
8.3%
Other values (2) 16
16.7%

Length

2024-04-21T10:38:30.507274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-01 8
8.3%
2023-02 8
8.3%
2023-03 8
8.3%
2023-04 8
8.3%
2023-05 8
8.3%
2023-06 8
8.3%
2023-07 8
8.3%
2023-08 8
8.3%
2023-09 8
8.3%
2023-10 8
8.3%
Other values (2) 16
16.7%

도로명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size900.0 B
강변북로
12 
경부고속도로
12 
내부순환로
12 
동부간선도로
12 
북부간선도로
12 
Other values (3)
36 

Length

Max length6
Median length5.5
Mean length5.25
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강변북로 12
12.5%
경부고속도로 12
12.5%
내부순환로 12
12.5%
동부간선도로 12
12.5%
북부간선도로 12
12.5%
분당수서로 12
12.5%
올림픽대로 12
12.5%
강남순환로 12
12.5%

Length

2024-04-21T10:38:30.630374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:38:30.739996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강변북로 12
12.5%
경부고속도로 12
12.5%
내부순환로 12
12.5%
동부간선도로 12
12.5%
북부간선도로 12
12.5%
분당수서로 12
12.5%
올림픽대로 12
12.5%
강남순환로 12
12.5%

일요일(휴일포함)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152940.75
Minimum92893
Maximum232140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:30.875450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum92893
5-th percentile100645.5
Q1120469.25
median129315.5
Q3190980
95-th percentile229231.5
Maximum232140
Range139247
Interquartile range (IQR)70510.75

Descriptive statistics

Standard deviation45249.678
Coefficient of variation (CV)0.29586411
Kurtosis-1.213662
Mean152940.75
Median Absolute Deviation (MAD)21650.5
Skewness0.60661544
Sum14682312
Variance2.0475334 × 109
MonotonicityNot monotonic
2024-04-21T10:38:31.002398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206723 1
 
1.0%
100360 1
 
1.0%
110596 1
 
1.0%
124607 1
 
1.0%
119614 1
 
1.0%
121046 1
 
1.0%
120041 1
 
1.0%
115725 1
 
1.0%
121995 1
 
1.0%
119281 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
92893 1
1.0%
93765 1
1.0%
97305 1
1.0%
100360 1
1.0%
100551 1
1.0%
100677 1
1.0%
101364 1
1.0%
102428 1
1.0%
103223 1
1.0%
104533 1
1.0%
ValueCountFrequency (%)
232140 1
1.0%
230490 1
1.0%
230168 1
1.0%
229644 1
1.0%
229329 1
1.0%
229199 1
1.0%
228527 1
1.0%
227444 1
1.0%
224076 1
1.0%
223790 1
1.0%

월요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166159.89
Minimum103644
Maximum248948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:31.126773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103644
5-th percentile107876.25
Q1132737.5
median145165.5
Q3201192.5
95-th percentile244589.25
Maximum248948
Range145304
Interquartile range (IQR)68455

Descriptive statistics

Standard deviation46470.029
Coefficient of variation (CV)0.27967056
Kurtosis-1.1440821
Mean166159.89
Median Absolute Deviation (MAD)27903
Skewness0.55105648
Sum15951349
Variance2.1594636 × 109
MonotonicityNot monotonic
2024-04-21T10:38:31.287910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
232545 1
 
1.0%
107661 1
 
1.0%
128694 1
 
1.0%
129853 1
 
1.0%
135631 1
 
1.0%
133875 1
 
1.0%
132120 1
 
1.0%
130788 1
 
1.0%
131625 1
 
1.0%
132427 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
103644 1
1.0%
105182 1
1.0%
105885 1
1.0%
107011 1
1.0%
107661 1
1.0%
107948 1
1.0%
108195 1
1.0%
108261 1
1.0%
109074 1
1.0%
109325 1
1.0%
ValueCountFrequency (%)
248948 1
1.0%
247053 1
1.0%
246786 1
1.0%
245554 1
1.0%
244692 1
1.0%
244555 1
1.0%
244074 1
1.0%
243929 1
1.0%
242721 1
1.0%
242665 1
1.0%

화요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166802.36
Minimum106032
Maximum251416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:31.434481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106032
5-th percentile106903.25
Q1132822.25
median146549
Q3202954
95-th percentile246055.25
Maximum251416
Range145384
Interquartile range (IQR)70131.75

Descriptive statistics

Standard deviation46192.219
Coefficient of variation (CV)0.27692784
Kurtosis-1.1032433
Mean166802.36
Median Absolute Deviation (MAD)30549.5
Skewness0.54347478
Sum16013027
Variance2.1337211 × 109
MonotonicityNot monotonic
2024-04-21T10:38:31.719682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
231738 1
 
1.0%
109135 1
 
1.0%
131142 1
 
1.0%
132907 1
 
1.0%
133502 1
 
1.0%
132112 1
 
1.0%
130436 1
 
1.0%
128517 1
 
1.0%
134678 1
 
1.0%
136548 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
106032 1
1.0%
106485 1
1.0%
106657 1
1.0%
106733 1
1.0%
106775 1
1.0%
106946 1
1.0%
109111 1
1.0%
109135 1
1.0%
109147 1
1.0%
109910 1
1.0%
ValueCountFrequency (%)
251416 1
1.0%
251128 1
1.0%
249682 1
1.0%
248543 1
1.0%
247487 1
1.0%
245578 1
1.0%
244877 1
1.0%
241259 1
1.0%
240759 1
1.0%
240747 1
1.0%

수요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167584.01
Minimum105173
Maximum254287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:31.873362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105173
5-th percentile108058.75
Q1133961
median147364.5
Q3202722.25
95-th percentile247337.5
Maximum254287
Range149114
Interquartile range (IQR)68761.25

Descriptive statistics

Standard deviation46670.568
Coefficient of variation (CV)0.27849058
Kurtosis-1.1151962
Mean167584.01
Median Absolute Deviation (MAD)29480
Skewness0.54420467
Sum16088065
Variance2.1781419 × 109
MonotonicityNot monotonic
2024-04-21T10:38:32.002308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
235951 1
 
1.0%
107998 1
 
1.0%
132097 1
 
1.0%
134126 1
 
1.0%
134109 1
 
1.0%
130888 1
 
1.0%
131394 1
 
1.0%
132885 1
 
1.0%
133298 1
 
1.0%
137227 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
105173 1
1.0%
106510 1
1.0%
107069 1
1.0%
107213 1
1.0%
107998 1
1.0%
108079 1
1.0%
108149 1
1.0%
109242 1
1.0%
109551 1
1.0%
109855 1
1.0%
ValueCountFrequency (%)
254287 1
1.0%
249546 1
1.0%
248741 1
1.0%
248510 1
1.0%
247519 1
1.0%
247277 1
1.0%
246893 1
1.0%
245343 1
1.0%
244945 1
1.0%
243913 1
1.0%

목요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167984.11
Minimum105396
Maximum252105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:32.190266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105396
5-th percentile108793.5
Q1134027
median146520.5
Q3204663.75
95-th percentile248449
Maximum252105
Range146709
Interquartile range (IQR)70636.75

Descriptive statistics

Standard deviation46775.995
Coefficient of variation (CV)0.27845487
Kurtosis-1.1218222
Mean167984.11
Median Absolute Deviation (MAD)30024
Skewness0.54054176
Sum16126475
Variance2.1879937 × 109
MonotonicityNot monotonic
2024-04-21T10:38:32.334970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
226718 1
 
1.0%
108345 1
 
1.0%
130627 1
 
1.0%
133195 1
 
1.0%
133264 1
 
1.0%
135380 1
 
1.0%
128575 1
 
1.0%
132620 1
 
1.0%
134425 1
 
1.0%
138430 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
105396 1
1.0%
106441 1
1.0%
107631 1
1.0%
107991 1
1.0%
108345 1
1.0%
108943 1
1.0%
109449 1
1.0%
109453 1
1.0%
109611 1
1.0%
110131 1
1.0%
ValueCountFrequency (%)
252105 1
1.0%
251826 1
1.0%
250220 1
1.0%
249947 1
1.0%
248887 1
1.0%
248303 1
1.0%
247086 1
1.0%
246487 1
1.0%
246233 1
1.0%
243819 1
1.0%

금요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170160.33
Minimum106337
Maximum254205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:32.519465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106337
5-th percentile110355.5
Q1137350.75
median151408.5
Q3205717.75
95-th percentile249306.25
Maximum254205
Range147868
Interquartile range (IQR)68367

Descriptive statistics

Standard deviation45672.352
Coefficient of variation (CV)0.26840775
Kurtosis-1.1090711
Mean170160.33
Median Absolute Deviation (MAD)28075
Skewness0.48884818
Sum16335392
Variance2.0859637 × 109
MonotonicityNot monotonic
2024-04-21T10:38:32.708903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
224022 1
 
1.0%
110665 1
 
1.0%
132156 1
 
1.0%
136193 1
 
1.0%
137881 1
 
1.0%
138426 1
 
1.0%
133452 1
 
1.0%
132564 1
 
1.0%
138891 1
 
1.0%
139512 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
106337 1
1.0%
107117 1
1.0%
108282 1
1.0%
109322 1
1.0%
109427 1
1.0%
110665 1
1.0%
111845 1
1.0%
112581 1
1.0%
112667 1
1.0%
113054 1
1.0%
ValueCountFrequency (%)
254205 1
1.0%
254138 1
1.0%
252897 1
1.0%
251426 1
1.0%
250591 1
1.0%
248878 1
1.0%
248571 1
1.0%
246990 1
1.0%
241494 1
1.0%
240663 1
1.0%

토요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct96
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167127.95
Minimum99213
Maximum250637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size996.0 B
2024-04-21T10:38:32.860540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum99213
5-th percentile106274.5
Q1133922.5
median146943.5
Q3203082
95-th percentile245849.5
Maximum250637
Range151424
Interquartile range (IQR)69159.5

Descriptive statistics

Standard deviation47091.333
Coefficient of variation (CV)0.28176815
Kurtosis-1.123634
Mean167127.95
Median Absolute Deviation (MAD)29369
Skewness0.52322705
Sum16044283
Variance2.2175936 × 109
MonotonicityNot monotonic
2024-04-21T10:38:32.990723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230175 1
 
1.0%
106168 1
 
1.0%
122206 1
 
1.0%
133846 1
 
1.0%
131516 1
 
1.0%
133948 1
 
1.0%
129993 1
 
1.0%
127321 1
 
1.0%
134368 1
 
1.0%
129720 1
 
1.0%
Other values (86) 86
89.6%
ValueCountFrequency (%)
99213 1
1.0%
100635 1
1.0%
101463 1
1.0%
103162 1
1.0%
106168 1
1.0%
106310 1
1.0%
108876 1
1.0%
108884 1
1.0%
109183 1
1.0%
109346 1
1.0%
ValueCountFrequency (%)
250637 1
1.0%
248881 1
1.0%
248815 1
1.0%
248243 1
1.0%
246748 1
1.0%
245550 1
1.0%
245445 1
1.0%
244433 1
1.0%
244400 1
1.0%
243458 1
1.0%

Interactions

2024-04-21T10:38:29.336776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.185444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.947956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.571077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.207739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.862592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.689475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.432257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.323986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.032231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.647884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.317694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.945445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.776781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.532481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.510666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.123562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.731016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.407476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.047545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.857684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.653092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.594621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.218746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.816011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.495149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.146688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.953601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.777631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.682026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.306777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.913162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.590019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.255903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.041240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.876567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.780650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.400562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.010026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.678184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.346038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.127645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.968381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:25.863982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:26.490765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.107039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:27.769562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:28.455221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:38:29.231741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:38:33.099097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월도로명일요일(휴일포함)월요일화요일수요일목요일금요일토요일
월1.0000.0000.0000.0000.0000.0000.0000.0000.000
도로명0.0001.0000.8830.9440.9550.9550.9410.9440.918
일요일(휴일포함)0.0000.8831.0000.8900.8590.8600.8890.8770.945
월요일0.0000.9440.8901.0000.9890.9910.9910.9860.966
화요일0.0000.9550.8590.9891.0000.9940.9930.9870.954
수요일0.0000.9550.8600.9910.9941.0000.9900.9900.959
목요일0.0000.9410.8890.9910.9930.9901.0000.9900.963
금요일0.0000.9440.8770.9860.9870.9900.9901.0000.963
토요일0.0000.9180.9450.9660.9540.9590.9630.9631.000
2024-04-21T10:38:33.203477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월도로명
월1.0000.000
도로명0.0001.000
2024-04-21T10:38:33.289918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일요일(휴일포함)월요일화요일수요일목요일금요일토요일월도로명
일요일(휴일포함)1.0000.8720.8690.8720.8780.8800.9360.0000.690
월요일0.8721.0000.9850.9840.9880.9880.9470.0000.822
화요일0.8690.9851.0000.9900.9850.9840.9420.0000.852
수요일0.8720.9840.9901.0000.9870.9860.9450.0000.852
목요일0.8780.9880.9850.9871.0000.9930.9490.0000.813
금요일0.8800.9880.9840.9860.9931.0000.9520.0000.821
토요일0.9360.9470.9420.9450.9490.9521.0000.0000.757
월0.0000.0000.0000.0000.0000.0000.0001.0000.000
도로명0.6900.8220.8520.8520.8130.8210.7570.0001.000

Missing values

2024-04-21T10:38:30.085953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:38:30.213780image/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

년도월도로명일요일(휴일포함)월요일화요일수요일목요일금요일토요일
020232023-01강변북로206723232545231738235951226718224022230175
120232023-02강변북로220635232485234954234612235183232944234274
220232023-03강변북로223581236329239361236910237818236109235410
320232023-04강변북로223473235383227797230837237249234978237442
420232023-05강변북로215797232175232150234790233294232265231804
520232023-06강변북로222077231078232086233958233206232005235406
620232023-07강변북로220337231077220639232571230673231064236397
720232023-08강변북로221466223073221156219412219225218560232580
820232023-09강변북로214942224430219253214000227390219913233469
920232023-10강변북로215545225032221318222151221621222277225895
년도월도로명일요일(휴일포함)월요일화요일수요일목요일금요일토요일
8620232023-03강남순환로122791165560168243168663169811176424158431
8720232023-04강남순환로127242159620168194163408166566172814157668
8820232023-05강남순환로128545148588158126158861164669168416146462
8920232023-06강남순환로121835156833158191158156158787167402154354
9020232023-07강남순환로112071152468153136154901157337163697145484
9120232023-08강남순환로118970152001158396158678150723162026146932
9220232023-09강남순환로128977158292160527160677161983167183163906
9320232023-10강남순환로122954152214155167153794155043161751150229
9420232023-11강남순환로119185151065153474152754154804161895152073
9520232023-12강남순환로109406149085151408153126153295157765135206