Overview

Dataset statistics

Number of variables14
Number of observations288
Missing cells232
Missing cells (%)5.8%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory35.6 KiB
Average record size in memory126.5 B

Variable types

Numeric12
Categorical2

Dataset

Description대구도시철도 1호선의 월별 정기 및 임시 열차운행횟수, 비영업 열차운행횟수와 월별 정기 및 임시 주행운행 km, 비영업 주행운행 km를 제공하고 있습니다.
Author대구교통공사
URLhttps://www.data.go.kr/data/15060890/fileData.do

Alerts

Dataset has 1 (0.3%) duplicate rowsDuplicates
호선 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
영업일 is highly overall correlated with and 1 other fieldsHigh correlation
연도 is highly overall correlated with 영업열차운행횟수-정기(회) and 4 other fieldsHigh correlation
is highly overall correlated with 호선 and 1 other fieldsHigh correlation
영업열차운행횟수-정기(회) is highly overall correlated with 연도 and 3 other fieldsHigh correlation
영업열차운행횟수-임시(회) is highly overall correlated with 영업열차운행키로-임시(Km) and 1 other fieldsHigh correlation
영업열차운행횟수-합계(회) is highly overall correlated with 연도 and 3 other fieldsHigh correlation
비영업열차운행횟수-합계(회) is highly overall correlated with 전체열차운행횟수-합계(회) and 1 other fieldsHigh correlation
전체열차운행횟수-합계(회) is highly overall correlated with 연도 and 4 other fieldsHigh correlation
영업열차운행키로-정기(Km) is highly overall correlated with 영업열차운행키로-합계(Km) and 2 other fieldsHigh correlation
영업열차운행키로-임시(Km) is highly overall correlated with 영업열차운행횟수-임시(회) and 1 other fieldsHigh correlation
영업열차운행키로-합계(Km) is highly overall correlated with 영업열차운행키로-정기(Km) and 2 other fieldsHigh correlation
비영업열차운행키로-합계(Km) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
전체열차운행키로-합계(Km) is highly overall correlated with 영업열차운행키로-정기(Km) and 3 other fieldsHigh correlation
호선 is highly imbalanced (79.9%)Imbalance
연도 has 9 (3.1%) missing valuesMissing
has 9 (3.1%) missing valuesMissing
영업열차운행횟수-정기(회) has 9 (3.1%) missing valuesMissing
영업열차운행횟수-임시(회) has 71 (24.7%) missing valuesMissing
영업열차운행횟수-합계(회) has 9 (3.1%) missing valuesMissing
비영업열차운행횟수-합계(회) has 9 (3.1%) missing valuesMissing
전체열차운행횟수-합계(회) has 9 (3.1%) missing valuesMissing
영업열차운행키로-정기(Km) has 9 (3.1%) missing valuesMissing
영업열차운행키로-임시(Km) has 71 (24.7%) missing valuesMissing
영업열차운행키로-합계(Km) has 9 (3.1%) missing valuesMissing
비영업열차운행키로-합계(Km) has 9 (3.1%) missing valuesMissing
전체열차운행키로-합계(Km) has 9 (3.1%) missing valuesMissing
영업열차운행횟수-임시(회) has 120 (41.7%) zerosZeros
영업열차운행키로-임시(Km) has 120 (41.7%) zerosZeros

Reproduction

Analysis started2024-04-20 05:10:20.676804
Analysis finished2024-04-20 05:11:00.925523
Duration40.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)8.6%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean2012.129
Minimum2001
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:01.067202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2002
Q12006
median2012
Q32018
95-th percentile2023
Maximum2024
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.7246339
Coefficient of variation (CV)0.003342049
Kurtosis-1.1989652
Mean2012.129
Median Absolute Deviation (MAD)6
Skewness0.0037777088
Sum561384
Variance45.220701
MonotonicityIncreasing
2024-04-20T05:11:01.461884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2001 12
 
4.2%
2002 12
 
4.2%
2023 12
 
4.2%
2022 12
 
4.2%
2021 12
 
4.2%
2020 12
 
4.2%
2019 12
 
4.2%
2018 12
 
4.2%
2017 12
 
4.2%
2016 12
 
4.2%
Other values (14) 159
55.2%
ValueCountFrequency (%)
2001 12
4.2%
2002 12
4.2%
2003 12
4.2%
2004 12
4.2%
2005 12
4.2%
2006 12
4.2%
2007 12
4.2%
2008 12
4.2%
2009 12
4.2%
2010 12
4.2%
ValueCountFrequency (%)
2024 3
 
1.0%
2023 12
4.2%
2022 12
4.2%
2021 12
4.2%
2020 12
4.2%
2019 12
4.2%
2018 12
4.2%
2017 12
4.2%
2016 12
4.2%
2015 12
4.2%


Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)4.3%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean6.4516129
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:01.833713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.471931
Coefficient of variation (CV)0.53814931
Kurtosis-1.2276739
Mean6.4516129
Median Absolute Deviation (MAD)3
Skewness0.01611117
Sum1800
Variance12.054305
MonotonicityNot monotonic
2024-04-20T05:11:02.341687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 24
8.3%
2 24
8.3%
3 24
8.3%
4 23
8.0%
5 23
8.0%
6 23
8.0%
7 23
8.0%
8 23
8.0%
9 23
8.0%
10 23
8.0%
Other values (2) 46
16.0%
ValueCountFrequency (%)
1 24
8.3%
2 24
8.3%
3 24
8.3%
4 23
8.0%
5 23
8.0%
6 23
8.0%
7 23
8.0%
8 23
8.0%
9 23
8.0%
10 23
8.0%
ValueCountFrequency (%)
12 23
8.0%
11 23
8.0%
10 23
8.0%
9 23
8.0%
8 23
8.0%
7 23
8.0%
6 23
8.0%
5 23
8.0%
4 23
8.0%
3 24
8.3%

호선
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
1
279 
<NA>
 
9

Length

Max length4
Median length1
Mean length1.09375
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 279
96.9%
<NA> 9
 
3.1%

Length

2024-04-20T05:11:02.727939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:11:03.019879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 279
96.9%
na 9
 
3.1%

영업일
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
31
163 
30
92 
28
18 
<NA>
 
9
29
 
6

Length

Max length4
Median length2
Mean length2.0625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31
2nd row28
3rd row31
4th row30
5th row31

Common Values

ValueCountFrequency (%)
31 163
56.6%
30 92
31.9%
28 18
 
6.2%
<NA> 9
 
3.1%
29 6
 
2.1%

Length

2024-04-20T05:11:03.366186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:11:03.727685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31 163
56.6%
30 92
31.9%
28 18
 
6.2%
na 9
 
3.1%
29 6
 
2.1%

영업열차운행횟수-정기(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)27.6%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean9370.0036
Minimum5700
Maximum18724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:04.106730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5700
5-th percentile8369.6
Q18872
median8984
Q39528
95-th percentile10162
Maximum18724
Range13024
Interquartile range (IQR)656

Descriptive statistics

Standard deviation1607.7741
Coefficient of variation (CV)0.17158735
Kurtosis23.975989
Mean9370.0036
Median Absolute Deviation (MAD)344
Skewness4.5865894
Sum2614231
Variance2584937.6
MonotonicityNot monotonic
2024-04-20T05:11:04.576093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9552 22
 
7.6%
8952 19
 
6.6%
9528 15
 
5.2%
8904 14
 
4.9%
9240 14
 
4.9%
8920 12
 
4.2%
8688 11
 
3.8%
9264 10
 
3.5%
8936 8
 
2.8%
9504 8
 
2.8%
Other values (67) 146
50.7%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
5700 1
0.3%
5710 1
0.3%
7184 1
0.3%
8000 2
0.7%
8016 2
0.7%
8032 1
0.3%
8080 1
0.3%
8096 2
0.7%
8260 1
0.3%
8296 1
0.3%
ValueCountFrequency (%)
18724 3
1.0%
18700 1
 
0.3%
18120 1
 
0.3%
18117 1
 
0.3%
18032 1
 
0.3%
14592 1
 
0.3%
11643 1
 
0.3%
10188 1
 
0.3%
10162 6
2.1%
10160 1
 
0.3%

영업열차운행횟수-임시(회)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct27
Distinct (%)12.4%
Missing71
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean7.3364055
Minimum0
Maximum134
Zeros120
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:04.924563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile28.4
Maximum134
Range134
Interquartile range (IQR)4

Descriptive statistics

Standard deviation20.101184
Coefficient of variation (CV)2.7399227
Kurtosis20.812477
Mean7.3364055
Median Absolute Deviation (MAD)0
Skewness4.4261048
Sum1592
Variance404.0576
MonotonicityNot monotonic
2024-04-20T05:11:05.366591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 120
41.7%
4 32
 
11.1%
8 17
 
5.9%
2 10
 
3.5%
10 4
 
1.4%
6 4
 
1.4%
88 3
 
1.0%
5 2
 
0.7%
13 2
 
0.7%
12 2
 
0.7%
Other values (17) 21
 
7.3%
(Missing) 71
24.7%
ValueCountFrequency (%)
0 120
41.7%
2 10
 
3.5%
3 1
 
0.3%
4 32
 
11.1%
5 2
 
0.7%
6 4
 
1.4%
7 1
 
0.3%
8 17
 
5.9%
10 4
 
1.4%
12 2
 
0.7%
ValueCountFrequency (%)
134 1
 
0.3%
132 1
 
0.3%
114 1
 
0.3%
88 3
1.0%
83 1
 
0.3%
72 1
 
0.3%
56 2
0.7%
30 1
 
0.3%
28 2
0.7%
26 1
 
0.3%

영업열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct135
Distinct (%)48.4%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean9375.7097
Minimum5700
Maximum18724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:05.919072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5700
5-th percentile8369.6
Q18872
median8984
Q39536
95-th percentile10162.8
Maximum18724
Range13024
Interquartile range (IQR)664

Descriptive statistics

Standard deviation1608.2615
Coefficient of variation (CV)0.17153491
Kurtosis23.907777
Mean9375.7097
Median Absolute Deviation (MAD)342
Skewness4.5771174
Sum2615823
Variance2586505
MonotonicityNot monotonic
2024-04-20T05:11:06.394694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9552 17
 
5.9%
8920 9
 
3.1%
8952 9
 
3.1%
9528 8
 
2.8%
8904 8
 
2.8%
9240 8
 
2.8%
9504 7
 
2.4%
8592 6
 
2.1%
8692 6
 
2.1%
8656 6
 
2.1%
Other values (125) 195
67.7%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
5700 1
0.3%
5713 1
0.3%
7184 1
0.3%
8000 2
0.7%
8016 1
0.3%
8020 1
0.3%
8032 1
0.3%
8080 1
0.3%
8096 1
0.3%
8100 1
0.3%
ValueCountFrequency (%)
18724 3
1.0%
18704 1
 
0.3%
18136 1
 
0.3%
18117 1
 
0.3%
18032 1
 
0.3%
14592 1
 
0.3%
11643 1
 
0.3%
10234 1
 
0.3%
10224 1
 
0.3%
10198 1
 
0.3%

비영업열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct157
Distinct (%)56.3%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean804.83871
Minimum2
Maximum1002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:06.809003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile187.1
Q1822.5
median856
Q3888
95-th percentile950.1
Maximum1002
Range1000
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation204.39669
Coefficient of variation (CV)0.25395981
Kurtosis9.1077006
Mean804.83871
Median Absolute Deviation (MAD)32
Skewness-3.0981316
Sum224550
Variance41778.006
MonotonicityNot monotonic
2024-04-20T05:11:07.158761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
866 6
 
2.1%
862 6
 
2.1%
868 5
 
1.7%
886 5
 
1.7%
884 4
 
1.4%
894 4
 
1.4%
864 4
 
1.4%
836 4
 
1.4%
848 4
 
1.4%
898 4
 
1.4%
Other values (147) 233
80.9%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
2 3
1.0%
3 1
 
0.3%
4 4
1.4%
8 4
1.4%
16 1
 
0.3%
143 1
 
0.3%
192 1
 
0.3%
363 1
 
0.3%
453 1
 
0.3%
486 1
 
0.3%
ValueCountFrequency (%)
1002 1
0.3%
1001 1
0.3%
988 1
0.3%
982 1
0.3%
980 1
0.3%
979 1
0.3%
972 1
0.3%
970 1
0.3%
957 1
0.3%
954 2
0.7%

전체열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct243
Distinct (%)87.1%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean10180.559
Minimum5843
Maximum19256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:07.539900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5843
5-th percentile9172.2
Q19678
median9890
Q310411
95-th percentile11068.5
Maximum19256
Range13413
Interquartile range (IQR)733

Descriptive statistics

Standard deviation1574.538
Coefficient of variation (CV)0.15466125
Kurtosis23.018808
Mean10180.559
Median Absolute Deviation (MAD)376
Skewness4.3722003
Sum2840376
Variance2479169.8
MonotonicityNot monotonic
2024-04-20T05:11:07.804242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9812 4
 
1.4%
10474 3
 
1.0%
10438 3
 
1.0%
9770 3
 
1.0%
9502 3
 
1.0%
9768 3
 
1.0%
9485 2
 
0.7%
9832 2
 
0.7%
9804 2
 
0.7%
9807 2
 
0.7%
Other values (233) 252
87.5%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
5843 1
0.3%
6076 1
0.3%
7637 1
0.3%
8726 1
0.3%
8763 1
0.3%
8766 1
0.3%
8782 1
0.3%
8797 1
0.3%
8844 1
0.3%
8871 1
0.3%
ValueCountFrequency (%)
19256 1
0.3%
19248 1
0.3%
19246 1
0.3%
19234 1
0.3%
18650 1
0.3%
18622 1
0.3%
18518 1
0.3%
15381 1
0.3%
12349 1
0.3%
11141 1
0.3%

영업열차운행키로-정기(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct135
Distinct (%)48.4%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean240511.81
Minimum147630
Maximum262791.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:08.211375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum147630
5-th percentile219781.8
Q1237356
median245210.8
Q3250994.8
95-th percentile254035.8
Maximum262791.4
Range115161.4
Interquartile range (IQR)13638.8

Descriptive statistics

Standard deviation16168.317
Coefficient of variation (CV)0.067224626
Kurtosis9.5208344
Mean240511.81
Median Absolute Deviation (MAD)6803.4
Skewness-2.5759181
Sum67102795
Variance2.6141446 × 108
MonotonicityNot monotonic
2024-04-20T05:11:08.613232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
246442.0 18
 
6.2%
245820.4 12
 
4.2%
238392.0 10
 
3.5%
239013.6 10
 
3.5%
253127.0 10
 
3.5%
251763.8 9
 
3.1%
245665.2 8
 
2.8%
245198.8 7
 
2.4%
244756.4 6
 
2.1%
252672.6 5
 
1.7%
Other values (125) 184
63.9%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
147630.0 1
 
0.3%
147889.0 1
 
0.3%
181221.6 1
 
0.3%
182078.7 1
 
0.3%
182106.0 1
 
0.3%
185726.8 1
 
0.3%
187957.8 1
 
0.3%
188176.2 3
1.0%
205461.2 1
 
0.3%
206337.6 1
 
0.3%
ValueCountFrequency (%)
262791.4 1
 
0.3%
262241.0 3
1.0%
262163.3 1
 
0.3%
261567.6 1
 
0.3%
261558.5 1
 
0.3%
260894.2 2
0.7%
260220.8 1
 
0.3%
258015.6 1
 
0.3%
254346.4 2
0.7%
254035.8 2
0.7%

영업열차운행키로-임시(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct47
Distinct (%)21.7%
Missing71
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean187.62719
Minimum0
Maximum3748.8
Zeros120
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:08.996048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3113.6
95-th percentile777.44
Maximum3748.8
Range3748.8
Interquartile range (IQR)113.6

Descriptive statistics

Standard deviation532.36986
Coefficient of variation (CV)2.8373812
Kurtosis23.081169
Mean187.62719
Median Absolute Deviation (MAD)0
Skewness4.6234885
Sum40715.1
Variance283417.67
MonotonicityNot monotonic
2024-04-20T05:11:09.347264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 120
41.7%
103.6 15
 
5.2%
113.6 8
 
2.8%
207.2 7
 
2.4%
51.8 6
 
2.1%
203.2 5
 
1.7%
14.0 4
 
1.4%
170.4 3
 
1.0%
99.6 3
 
1.0%
227.2 3
 
1.0%
Other values (37) 43
 
14.9%
(Missing) 71
24.7%
ValueCountFrequency (%)
0.0 120
41.7%
8.8 1
 
0.3%
14.0 4
 
1.4%
32.4 1
 
0.3%
51.8 6
 
2.1%
56.8 3
 
1.0%
65.9 1
 
0.3%
77.7 1
 
0.3%
99.6 3
 
1.0%
103.6 15
 
5.2%
ValueCountFrequency (%)
3748.8 1
0.3%
3470.6 1
0.3%
3237.6 1
0.3%
2279.2 1
0.3%
2191.2 2
0.7%
2130.1 1
0.3%
1792.8 1
0.3%
1422.1 1
0.3%
1394.4 1
0.3%
795.2 1
0.3%

영업열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct177
Distinct (%)63.4%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean240657.74
Minimum147630
Maximum263173.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:09.759466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum147630
5-th percentile219781.8
Q1237407.8
median245324.4
Q3251198.95
95-th percentile254356.76
Maximum263173.4
Range115543.4
Interquartile range (IQR)13791.15

Descriptive statistics

Standard deviation16225.688
Coefficient of variation (CV)0.067422256
Kurtosis9.427434
Mean240657.74
Median Absolute Deviation (MAD)6805.1
Skewness-2.5608495
Sum67143510
Variance2.6327295 × 108
MonotonicityNot monotonic
2024-04-20T05:11:10.200628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
246442.0 17
 
5.9%
238392.0 8
 
2.8%
245820.4 7
 
2.4%
245198.8 7
 
2.4%
244756.4 6
 
2.1%
253127.0 6
 
2.1%
251763.8 5
 
1.7%
239117.2 5
 
1.7%
245778.8 5
 
1.7%
237770.4 4
 
1.4%
Other values (167) 209
72.6%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
147630.0 1
 
0.3%
147966.7 1
 
0.3%
181221.6 1
 
0.3%
182078.7 1
 
0.3%
182251.6 1
 
0.3%
185726.8 1
 
0.3%
187990.2 1
 
0.3%
188176.2 3
1.0%
205461.2 1
 
0.3%
206337.6 1
 
0.3%
ValueCountFrequency (%)
263173.4 1
 
0.3%
262800.2 1
 
0.3%
262422.3 1
 
0.3%
262241.0 3
1.0%
261686.6 1
 
0.3%
261558.5 1
 
0.3%
260894.2 1
 
0.3%
260220.8 1
 
0.3%
258015.6 1
 
0.3%
255001.4 1
 
0.3%

비영업열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct254
Distinct (%)91.0%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1799.553
Minimum49.8
Maximum28207.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:10.588192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49.8
5-th percentile248.03
Q1925.6
median1039
Q33018.6
95-th percentile3420.53
Maximum28207.1
Range28157.3
Interquartile range (IQR)2093

Descriptive statistics

Standard deviation1938.0139
Coefficient of variation (CV)1.0769418
Kurtosis123.85279
Mean1799.553
Median Absolute Deviation (MAD)201.8
Skewness9.2243891
Sum502075.3
Variance3755897.9
MonotonicityNot monotonic
2024-04-20T05:11:11.013041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199.2 4
 
1.4%
99.6 4
 
1.4%
49.8 3
 
1.0%
933.8 3
 
1.0%
895.8 2
 
0.7%
1167.0 2
 
0.7%
3025.6 2
 
0.7%
911.8 2
 
0.7%
883.8 2
 
0.7%
989.6 2
 
0.7%
Other values (244) 253
87.8%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
49.8 3
1.0%
74.7 1
 
0.3%
99.6 4
1.4%
199.2 4
1.4%
207.2 1
 
0.3%
217.7 1
 
0.3%
251.4 1
 
0.3%
437.7 1
 
0.3%
530.6 1
 
0.3%
542.5 1
 
0.3%
ValueCountFrequency (%)
28207.1 1
0.3%
4270.3 1
0.3%
4132.4 1
0.3%
4100.5 1
0.3%
4031.6 1
0.3%
3799.5 1
0.3%
3749.0 1
0.3%
3626.3 1
0.3%
3614.6 1
0.3%
3611.5 1
0.3%

전체열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct274
Distinct (%)98.2%
Missing9
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean249537.21
Minimum147847.7
Maximum2248258.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-04-20T05:11:11.370573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum147847.7
5-th percentile220758.64
Q1238612.85
median246833.4
Q3253884.9
95-th percentile257419.79
Maximum2248258.6
Range2100410.9
Interquartile range (IQR)15272.05

Descriptive statistics

Standard deviation121237.53
Coefficient of variation (CV)0.48584952
Kurtosis268.48575
Mean249537.21
Median Absolute Deviation (MAD)7514.7
Skewness16.223955
Sum69620881
Variance1.4698539 × 1010
MonotonicityNot monotonic
2024-04-20T05:11:11.616702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
247375.8 3
 
1.0%
224755.8 2
 
0.7%
246750.2 2
 
0.7%
246060.8 2
 
0.7%
255929.0 1
 
0.3%
248888.8 1
 
0.3%
255908.0 1
 
0.3%
256637.8 1
 
0.3%
256317.0 1
 
0.3%
245975.1 1
 
0.3%
Other values (264) 264
91.7%
(Missing) 9
 
3.1%
ValueCountFrequency (%)
147847.7 1
0.3%
148404.4 1
0.3%
181752.2 1
0.3%
182621.2 1
0.3%
182796.0 1
0.3%
186507.0 1
0.3%
188550.6 1
0.3%
188728.6 1
0.3%
188808.6 1
0.3%
188928.4 1
0.3%
ValueCountFrequency (%)
2248258.6 1
0.3%
264179.9 1
0.3%
263833.2 1
0.3%
263726.0 1
0.3%
263373.1 1
0.3%
263192.8 1
0.3%
263186.8 1
0.3%
262683.8 1
0.3%
262550.1 1
0.3%
262460.8 1
0.3%

Interactions

2024-04-20T05:10:56.098199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:24.244193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:27.354761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:30.650079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.455405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:35.959969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:38.988858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:42.115147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:45.172427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:48.264701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:51.440654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:53.701954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:56.261052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:24.567123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:27.599805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:30.925113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.613779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:36.212707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:39.235414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:42.365507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:45.504981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:48.516010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:51.629208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:53.859409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:56.501947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:24.851902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:27.836319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:31.185441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.771465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:36.466828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:39.477745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:42.618270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:45.749571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:48.766717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:51.833745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.017902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:56.750220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:25.192426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:28.082561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:31.467503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.942079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:36.720152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:39.735078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:42.874361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:46.007772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:49.074000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.009803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.180335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.012748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:25.383188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:28.495369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:31.741257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:34.112917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:36.982540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:39.989588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:43.138223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:46.268167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:49.337112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.191119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.345773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.259978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:25.648667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:28.862206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:32.027317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:34.285535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:37.190382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:40.242393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:43.392634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:46.524514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:49.596192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.356792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.510224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.499855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:25.918640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:29.138834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:32.239472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:34.539493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:37.404543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:40.483813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:43.647617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:46.768174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:49.849308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.513942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.707902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.656534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:26.086585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:29.506870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:32.413293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:34.797003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:37.666909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:40.741580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:43.901551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:47.023866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:50.099675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.678160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:54.926528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.812019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:26.341800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:29.671002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:32.711610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:35.066079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:37.924394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:40.989202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:44.155064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:47.267829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:50.350106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:52.852905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:55.084755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:57.975950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:26.602380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:29.907545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:32.931802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:35.335143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:38.186115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:41.388819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:44.415757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:47.527953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:50.712356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:53.050115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:55.341422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:58.227491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:26.849979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:30.154186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.099624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:35.497743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:38.441296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:41.634566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:44.676269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:47.778209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:50.964508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:53.207122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:55.647358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:58.568659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:27.129075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:30.410158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:33.299696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:35.716271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:38.692744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:41.879555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:44.925429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:48.026185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:51.149079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:53.454509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:10:55.895845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T05:11:11.796643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도영업일영업열차운행횟수-정기(회)영업열차운행횟수-임시(회)영업열차운행횟수-합계(회)비영업열차운행횟수-합계(회)전체열차운행횟수-합계(회)영업열차운행키로-정기(Km)영업열차운행키로-임시(Km)영업열차운행키로-합계(Km)비영업열차운행키로-합계(Km)전체열차운행키로-합계(Km)
연도1.0000.0000.0000.5910.0000.5820.4950.6380.5230.0000.5210.7320.086
0.0001.0000.8010.1830.0990.1830.2450.0000.3320.1710.3220.0000.130
영업일0.0000.8011.0000.4530.0000.4530.4860.2330.8110.0000.8080.1060.000
영업열차운행횟수-정기(회)0.5910.1830.4531.0000.1341.0000.8440.9890.8380.0710.8360.2280.000
영업열차운행횟수-임시(회)0.0000.0990.0000.1341.0000.1400.0000.0000.0000.9830.0000.0000.000
영업열차운행횟수-합계(회)0.5820.1830.4531.0000.1401.0000.8430.9890.8370.0830.8360.2330.000
비영업열차운행횟수-합계(회)0.4950.2450.4860.8440.0000.8431.0000.8440.8100.0000.8100.4020.000
전체열차운행횟수-합계(회)0.6380.0000.2330.9890.0000.9890.8441.0000.8290.0000.8290.5430.000
영업열차운행키로-정기(Km)0.5230.3320.8110.8380.0000.8370.8100.8291.0000.0001.0000.4820.000
영업열차운행키로-임시(Km)0.0000.1710.0000.0710.9830.0830.0000.0000.0001.0000.0000.0000.000
영업열차운행키로-합계(Km)0.5210.3220.8080.8360.0000.8360.8100.8291.0000.0001.0000.4780.000
비영업열차운행키로-합계(Km)0.7320.0000.1060.2280.0000.2330.4020.5430.4820.0000.4781.0001.000
전체열차운행키로-합계(Km)0.0860.1300.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.000
2024-04-20T05:11:12.099869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선영업일
호선1.0001.000
영업일1.0001.000
2024-04-20T05:11:12.344231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도영업열차운행횟수-정기(회)영업열차운행횟수-임시(회)영업열차운행횟수-합계(회)비영업열차운행횟수-합계(회)전체열차운행횟수-합계(회)영업열차운행키로-정기(Km)영업열차운행키로-임시(Km)영업열차운행키로-합계(Km)비영업열차운행키로-합계(Km)전체열차운행키로-합계(Km)호선영업일
연도1.000-0.024-0.7320.050-0.730-0.133-0.6570.1130.0660.1010.7460.2311.0000.000
-0.0241.0000.0790.1670.0820.1340.0880.1120.1840.1120.1220.1241.0000.618
영업열차운행횟수-정기(회)-0.7320.0791.000-0.0380.9980.3630.9500.348-0.0520.355-0.4730.2151.0000.325
영업열차운행횟수-임시(회)0.0500.167-0.0381.0000.0060.062-0.0210.0270.9950.0800.0670.0561.0000.000
영업열차운행횟수-합계(회)-0.7300.0820.9980.0061.0000.3660.9510.349-0.0080.359-0.4700.2191.0000.325
비영업열차운행횟수-합계(회)-0.1330.1340.3630.0620.3661.0000.5420.3940.0700.3860.2520.3551.0000.329
전체열차운행횟수-합계(회)-0.6570.0880.950-0.0210.9510.5421.0000.351-0.0330.354-0.3540.2251.0000.160
영업열차운행키로-정기(Km)0.1130.1120.3480.0270.3490.3940.3511.0000.0380.9960.4050.9711.0000.475
영업열차운행키로-임시(Km)0.0660.184-0.0520.995-0.0080.070-0.0330.0381.0000.0900.0850.0711.0000.000
영업열차운행키로-합계(Km)0.1010.1120.3550.0800.3590.3860.3540.9960.0901.0000.3930.9711.0000.471
비영업열차운행키로-합계(Km)0.7460.122-0.4730.067-0.4700.252-0.3540.4050.0850.3931.0000.5281.0000.099
전체열차운행키로-합계(Km)0.2310.1240.2150.0560.2190.3550.2250.9710.0710.9710.5281.0001.0000.000
호선1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업일0.0000.6180.3250.0000.3250.3290.1600.4750.0000.4710.0990.0001.0001.000

Missing values

2024-04-20T05:10:58.936561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T05:10:59.825099image/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.
2024-04-20T05:11:00.519819image/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

연도호선영업일영업열차운행횟수-정기(회)영업열차운행횟수-임시(회)영업열차운행횟수-합계(회)비영업열차운행횟수-합계(회)전체열차운행횟수-합계(회)영업열차운행키로-정기(Km)영업열차운행키로-임시(Km)영업열차운행키로-합계(Km)비영업열차운행키로-합계(Km)전체열차운행키로-합계(Km)
02001113110084010084310087250198.80.0250198.874.7250273.5
12001212891924919649200228074.499.6228174.099.6228273.6
220013131101627210234810242252141.01792.8253933.8199.2254133.0
32001413098040980489812243255.60.0243255.6199.2243454.8
42001513110136010136810144251493.60.0251493.6199.2251692.8
520016130983056988649890243903.01394.4245297.499.6245397.0
62001713110136010136410140251493.60.0251493.699.6251593.2
72001813110162010162810170252141.00.0252141.0199.2252340.2
820019130983088991829920243903.02191.2246094.249.8246144.0
920011013110110010110210112250846.20.0250846.249.8250896.0
연도호선영업일영업열차운행횟수-정기(회)영업열차운행횟수-임시(회)영업열차운행횟수-합계(회)비영업열차운행횟수-합계(회)전체열차운행횟수-합계(회)영업열차운행키로-정기(Km)영업열차운행키로-임시(Km)영업열차운행키로-합계(Km)비영업열차운행키로-합계(Km)전체열차운행키로-합계(Km)
278202431318904089048669770251763.80.0251763.83071.6254835.4
279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
280<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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286<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연도호선영업일영업열차운행횟수-정기(회)영업열차운행횟수-임시(회)영업열차운행횟수-합계(회)비영업열차운행횟수-합계(회)전체열차운행횟수-합계(회)영업열차운행키로-정기(Km)영업열차운행키로-임시(Km)영업열차운행키로-합계(Km)비영업열차운행키로-합계(Km)전체열차운행키로-합계(Km)# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9