Overview

Dataset statistics

Number of variables14
Number of observations243
Missing cells350
Missing cells (%)10.3%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory30.0 KiB
Average record size in memory126.5 B

Variable types

Numeric12
Categorical2

Dataset

Description대구도시철도 중 2호선의 영업·비영업, 정기·임시 열차의 영업일수, 운행횟수, 운행키로 등의 데이터를 제공합니다.
Author대구교통공사
URLhttps://www.data.go.kr/data/15060893/fileData.do

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
호선 is highly overall correlated with 연도 and 12 other fieldsHigh correlation
영업일 is highly overall correlated with and 7 other fieldsHigh correlation
연도 is highly overall correlated with 영업열차운행횟수-정기(회) and 8 other fieldsHigh correlation
is highly overall correlated with 호선 and 1 other fieldsHigh correlation
영업열차운행횟수-정기(회) is highly overall correlated with 연도 and 6 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 6 other fieldsHigh correlation
비영업열차운행횟수-합계(회) is highly overall correlated with 연도 and 7 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 연도 and 6 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 연도 and 6 other fieldsHigh correlation
비영업열차운행키로-합계(Km) is highly overall correlated with 연도 and 7 other fieldsHigh correlation
전체열차운행키로-합계(Km) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
호선 is highly imbalanced (57.6%)Imbalance
연도 has 21 (8.6%) missing valuesMissing
has 21 (8.6%) missing valuesMissing
영업열차운행횟수-정기(회) has 21 (8.6%) missing valuesMissing
영업열차운행횟수-임시(회) has 70 (28.8%) missing valuesMissing
영업열차운행횟수-합계(회) has 21 (8.6%) missing valuesMissing
비영업열차운행횟수-합계(회) has 22 (9.1%) missing valuesMissing
전체열차운행횟수-합계(회) has 21 (8.6%) missing valuesMissing
영업열차운행키로-정기(Km) has 21 (8.6%) missing valuesMissing
영업열차운행키로-임시(Km) has 69 (28.4%) missing valuesMissing
영업열차운행키로-합계(Km) has 21 (8.6%) missing valuesMissing
비영업열차운행키로-합계(Km) has 21 (8.6%) missing valuesMissing
전체열차운행키로-합계(Km) has 21 (8.6%) missing valuesMissing
영업열차운행횟수-임시(회) has 78 (32.1%) zerosZeros
영업열차운행키로-임시(Km) has 79 (32.5%) zerosZeros

Reproduction

Analysis started2024-04-20 05:16:14.111407
Analysis finished2024-04-20 05:16:51.805468
Duration37.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)9.0%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean2014.5
Minimum2005
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:51.982351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2006
Q12010
median2014.5
Q32019
95-th percentile2023
Maximum2024
Range19
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.362641
Coefficient of variation (CV)0.0026620209
Kurtosis-1.1893243
Mean2014.5
Median Absolute Deviation (MAD)4.5
Skewness0
Sum447219
Variance28.757919
MonotonicityIncreasing
2024-04-20T05:16:52.436386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2006 12
 
4.9%
2023 12
 
4.9%
2022 12
 
4.9%
2021 12
 
4.9%
2020 12
 
4.9%
2019 12
 
4.9%
2018 12
 
4.9%
2017 12
 
4.9%
2016 12
 
4.9%
2015 12
 
4.9%
Other values (10) 102
42.0%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
2005 3
 
1.2%
2006 12
4.9%
2007 12
4.9%
2008 12
4.9%
2009 12
4.9%
2010 12
4.9%
2011 12
4.9%
2012 12
4.9%
2013 12
4.9%
2014 12
4.9%
ValueCountFrequency (%)
2024 3
 
1.2%
2023 12
4.9%
2022 12
4.9%
2021 12
4.9%
2020 12
4.9%
2019 12
4.9%
2018 12
4.9%
2017 12
4.9%
2016 12
4.9%
2015 12
4.9%


Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct12
Distinct (%)5.4%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:52.819076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6.5
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.4949867
Coefficient of variation (CV)0.53769026
Kurtosis-1.2447709
Mean6.5
Median Absolute Deviation (MAD)3.5
Skewness0
Sum1443
Variance12.214932
MonotonicityNot monotonic
2024-04-20T05:16:53.259096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
10 19
7.8%
11 19
7.8%
12 19
7.8%
1 19
7.8%
2 19
7.8%
3 19
7.8%
4 18
7.4%
5 18
7.4%
6 18
7.4%
7 18
7.4%
Other values (2) 36
14.8%
(Missing) 21
8.6%
ValueCountFrequency (%)
1 19
7.8%
2 19
7.8%
3 19
7.8%
4 18
7.4%
5 18
7.4%
6 18
7.4%
7 18
7.4%
8 18
7.4%
9 18
7.4%
10 19
7.8%
ValueCountFrequency (%)
12 19
7.8%
11 19
7.8%
10 19
7.8%
9 18
7.4%
8 18
7.4%
7 18
7.4%
6 18
7.4%
5 18
7.4%
4 18
7.4%
3 19
7.8%

호선
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2
222 
<NA>
 
21

Length

Max length4
Median length1
Mean length1.2592593
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 222
91.4%
<NA> 21
 
8.6%

Length

2024-04-20T05:16:53.662646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:16:53.958874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 222
91.4%
na 21
 
8.6%

영업일
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
31
129 
30
73 
<NA>
21 
28
14 
29
 
5

Length

Max length4
Median length2
Mean length2.1728395
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row14
2nd row30
3rd row31
4th row31
5th row28

Common Values

ValueCountFrequency (%)
31 129
53.1%
30 73
30.0%
<NA> 21
 
8.6%
28 14
 
5.8%
29 5
 
2.1%
14 1
 
0.4%

Length

2024-04-20T05:16:54.314080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T05:16:54.524360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31 129
53.1%
30 73
30.0%
na 21
 
8.6%
28 14
 
5.8%
29 5
 
2.1%
14 1
 
0.4%

영업열차운행횟수-정기(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct54
Distinct (%)24.3%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean9008.0856
Minimum8000
Maximum9576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:54.901253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8000
5-th percentile8384.4
Q18688
median8952
Q39264
95-th percentile9552
Maximum9576
Range1576
Interquartile range (IQR)576

Descriptive statistics

Standard deviation385.92222
Coefficient of variation (CV)0.042841758
Kurtosis-0.2934834
Mean9008.0856
Median Absolute Deviation (MAD)288
Skewness-0.25419658
Sum1999795
Variance148935.96
MonotonicityNot monotonic
2024-04-20T05:16:55.230744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9552 20
 
8.2%
8952 19
 
7.8%
9528 14
 
5.8%
8904 13
 
5.3%
8920 12
 
4.9%
8688 11
 
4.5%
9240 11
 
4.5%
8936 8
 
3.3%
9264 8
 
3.3%
9504 8
 
3.3%
Other values (44) 98
40.3%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
8000 2
0.8%
8016 2
0.8%
8032 1
0.4%
8080 1
0.4%
8096 2
0.8%
8260 1
0.4%
8296 1
0.4%
8312 1
0.4%
8376 1
0.4%
8544 2
0.8%
ValueCountFrequency (%)
9576 5
 
2.1%
9552 20
8.2%
9528 14
5.8%
9504 8
 
3.3%
9488 2
 
0.8%
9464 1
 
0.4%
9456 1
 
0.4%
9448 1
 
0.4%
9424 1
 
0.4%
9264 8
 
3.3%

영업열차운행횟수-임시(회)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct24
Distinct (%)13.9%
Missing70
Missing (%)28.8%
Infinite0
Infinite (%)0.0%
Mean5.9248555
Minimum0
Maximum132
Zeros78
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:55.560751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile20.2
Maximum132
Range132
Interquartile range (IQR)6

Descriptive statistics

Standard deviation16.694245
Coefficient of variation (CV)2.8176628
Kurtosis39.656174
Mean5.9248555
Median Absolute Deviation (MAD)1
Skewness6.0412315
Sum1025
Variance278.69781
MonotonicityNot monotonic
2024-04-20T05:16:55.818209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 78
32.1%
4 24
 
9.9%
1 11
 
4.5%
8 9
 
3.7%
2 9
 
3.7%
6 9
 
3.7%
9 5
 
2.1%
5 4
 
1.6%
10 3
 
1.2%
16 3
 
1.2%
Other values (14) 18
 
7.4%
(Missing) 70
28.8%
ValueCountFrequency (%)
0 78
32.1%
1 11
 
4.5%
2 9
 
3.7%
3 2
 
0.8%
4 24
 
9.9%
5 4
 
1.6%
6 9
 
3.7%
7 1
 
0.4%
8 9
 
3.7%
9 5
 
2.1%
ValueCountFrequency (%)
132 1
 
0.4%
118 1
 
0.4%
114 1
 
0.4%
47 1
 
0.4%
36 1
 
0.4%
24 1
 
0.4%
23 1
 
0.4%
22 2
0.8%
19 1
 
0.4%
16 3
1.2%

영업열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct112
Distinct (%)50.5%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean9012.7027
Minimum8000
Maximum9694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:56.093881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8000
5-th percentile8384.4
Q18692
median8952
Q39268
95-th percentile9552
Maximum9694
Range1694
Interquartile range (IQR)576

Descriptive statistics

Standard deviation386.30314
Coefficient of variation (CV)0.042862076
Kurtosis-0.27404106
Mean9012.7027
Median Absolute Deviation (MAD)292
Skewness-0.25829507
Sum2000820
Variance149230.12
MonotonicityNot monotonic
2024-04-20T05:16:56.487422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9552 16
 
6.6%
9528 11
 
4.5%
8952 7
 
2.9%
8920 7
 
2.9%
8904 6
 
2.5%
8592 6
 
2.5%
9504 5
 
2.1%
9264 5
 
2.1%
8936 5
 
2.1%
9240 4
 
1.6%
Other values (102) 150
61.7%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
8000 2
0.8%
8016 2
0.8%
8032 1
0.4%
8080 1
0.4%
8096 1
0.4%
8100 1
0.4%
8296 2
0.8%
8312 1
0.4%
8376 1
0.4%
8544 1
0.4%
ValueCountFrequency (%)
9694 1
 
0.4%
9584 1
 
0.4%
9576 3
 
1.2%
9568 1
 
0.4%
9560 2
 
0.8%
9556 1
 
0.4%
9552 16
6.6%
9537 1
 
0.4%
9536 1
 
0.4%
9530 1
 
0.4%

비영업열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct85
Distinct (%)38.5%
Missing22
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean126.80543
Minimum0
Maximum280
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:56.781423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q110
median167
Q3194
95-th percentile236
Maximum280
Range280
Interquartile range (IQR)184

Descriptive statistics

Standard deviation89.868152
Coefficient of variation (CV)0.70870902
Kurtosis-1.5047834
Mean126.80543
Median Absolute Deviation (MAD)60
Skewness-0.38041017
Sum28024
Variance8076.2847
MonotonicityNot monotonic
2024-04-20T05:16:57.018284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 24
 
9.9%
8 11
 
4.5%
172 10
 
4.1%
174 9
 
3.7%
2 7
 
2.9%
168 6
 
2.5%
232 5
 
2.1%
228 5
 
2.1%
10 5
 
2.1%
170 5
 
2.1%
Other values (75) 134
55.1%
(Missing) 22
 
9.1%
ValueCountFrequency (%)
0 2
 
0.8%
2 7
 
2.9%
3 1
 
0.4%
4 2
 
0.8%
5 2
 
0.8%
6 24
9.9%
7 3
 
1.2%
8 11
4.5%
10 5
 
2.1%
12 4
 
1.6%
ValueCountFrequency (%)
280 1
 
0.4%
246 2
 
0.8%
242 1
 
0.4%
239 1
 
0.4%
238 1
 
0.4%
237 3
1.2%
236 3
1.2%
234 4
1.6%
232 5
2.1%
231 1
 
0.4%

전체열차운행횟수-합계(회)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct179
Distinct (%)80.6%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean9143.4414
Minimum8152
Maximum9816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:57.344435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8152
5-th percentile8578.9
Q18919
median9140
Q39380.25
95-th percentile9582.95
Maximum9816
Range1664
Interquartile range (IQR)461.25

Descriptive statistics

Standard deviation335.59894
Coefficient of variation (CV)0.036703788
Kurtosis0.47984298
Mean9143.4414
Median Absolute Deviation (MAD)226
Skewness-0.60358536
Sum2029844
Variance112626.65
MonotonicityNot monotonic
2024-04-20T05:16:57.760348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9558 5
 
2.1%
9108 4
 
1.6%
9582 3
 
1.2%
8860 3
 
1.2%
9568 3
 
1.2%
9152 3
 
1.2%
9136 2
 
0.8%
8882 2
 
0.8%
9250 2
 
0.8%
9506 2
 
0.8%
Other values (169) 193
79.4%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
8152 1
0.4%
8156 1
0.4%
8168 1
0.4%
8226 2
0.8%
8238 1
0.4%
8254 1
0.4%
8293 1
0.4%
8458 1
0.4%
8498 1
0.4%
8529 1
0.4%
ValueCountFrequency (%)
9816 1
0.4%
9750 1
0.4%
9738 1
0.4%
9706 1
0.4%
9636 1
0.4%
9618 1
0.4%
9617 1
0.4%
9600 2
0.8%
9598 1
0.4%
9586 1
0.4%

영업열차운행키로-정기(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct86
Distinct (%)38.7%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean269957.5
Minimum238974.4
Maximum296683.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:58.108771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238974.4
5-th percentile250607.52
Q1265748.35
median270096
Q3278848
95-th percentile280933.6
Maximum296683.2
Range57708.8
Interquartile range (IQR)13099.65

Descriptive statistics

Standard deviation10684.353
Coefficient of variation (CV)0.039577907
Kurtosis0.44321734
Mean269957.5
Median Absolute Deviation (MAD)8249.6
Skewness-0.33781557
Sum59930564
Variance1.1415539 × 108
MonotonicityNot monotonic
2024-04-20T05:16:58.514254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266426.8 14
 
5.8%
279852.8 13
 
5.3%
278345.6 11
 
4.5%
271603.2 11
 
4.5%
265754.8 11
 
4.5%
278848.0 10
 
4.1%
258396.0 8
 
3.3%
279350.4 8
 
3.3%
270598.4 7
 
2.9%
257724.0 6
 
2.5%
Other values (76) 123
50.6%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
238974.4 1
0.4%
239646.4 2
0.8%
240990.4 2
0.8%
247169.7 1
0.4%
249693.2 1
0.4%
249903.5 1
0.4%
250080.0 2
0.8%
250582.4 2
0.8%
251084.8 1
0.4%
252592.0 1
0.4%
ValueCountFrequency (%)
296683.2 2
0.8%
295929.6 1
0.4%
295427.2 1
0.4%
294693.6 1
0.4%
292918.6 1
0.4%
288393.6 1
0.4%
287680.0 2
0.8%
285730.8 1
0.4%
285670.4 1
0.4%
280937.6 1
0.4%

영업열차운행키로-임시(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct47
Distinct (%)27.0%
Missing69
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean176.13506
Minimum0
Maximum4144.8
Zeros79
Zeros (%)32.5%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:58.864951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median31.4
Q3170.35
95-th percentile596.76
Maximum4144.8
Range4144.8
Interquartile range (IQR)170.35

Descriptive statistics

Standard deviation504.26525
Coefficient of variation (CV)2.8629465
Kurtosis41.452967
Mean176.13506
Median Absolute Deviation (MAD)31.4
Skewness6.1605881
Sum30647.5
Variance254283.44
MonotonicityNot monotonic
2024-04-20T05:16:59.254908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 79
32.5%
125.6 12
 
4.9%
112.0 9
 
3.7%
28.0 7
 
2.9%
224.0 6
 
2.5%
188.4 5
 
2.1%
62.8 4
 
1.6%
31.4 4
 
1.6%
59.4 2
 
0.8%
122.2 2
 
0.8%
Other values (37) 44
18.1%
(Missing) 69
28.4%
ValueCountFrequency (%)
0.0 79
32.5%
28.0 7
 
2.9%
31.4 4
 
1.6%
49.2 1
 
0.4%
56.0 2
 
0.8%
59.4 2
 
0.8%
62.8 4
 
1.6%
80.5 1
 
0.4%
94.2 2
 
0.8%
112.0 9
 
3.7%
ValueCountFrequency (%)
4144.8 1
0.4%
3579.6 1
0.4%
3304.0 1
0.4%
1316.0 1
0.4%
1130.4 1
0.4%
715.4 1
0.4%
690.8 1
0.4%
655.4 1
0.4%
616.0 1
0.4%
586.4 1
0.4%

영업열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct140
Distinct (%)63.1%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean270095.55
Minimum239086.4
Maximum296714.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:16:59.672623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239086.4
5-th percentile250607.52
Q1265748.35
median270370
Q3278848
95-th percentile281882.1
Maximum296714.6
Range57628.2
Interquartile range (IQR)13099.65

Descriptive statistics

Standard deviation10709.439
Coefficient of variation (CV)0.039650557
Kurtosis0.43534239
Mean270095.55
Median Absolute Deviation (MAD)8028.2
Skewness-0.34740264
Sum59961212
Variance1.1469208 × 108
MonotonicityNot monotonic
2024-04-20T05:17:00.047415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266426.8 14
 
5.8%
265754.8 9
 
3.7%
278848.0 7
 
2.9%
279852.8 6
 
2.5%
258396.0 5
 
2.1%
279350.4 5
 
2.1%
270598.4 4
 
1.6%
268588.8 4
 
1.6%
278345.6 4
 
1.6%
271603.2 4
 
1.6%
Other values (130) 160
65.8%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
239086.4 1
0.4%
239646.4 2
0.8%
240990.4 2
0.8%
247250.2 1
0.4%
249693.2 1
0.4%
250080.0 2
0.8%
250103.5 1
0.4%
250582.4 2
0.8%
251084.8 1
0.4%
252592.0 1
0.4%
ValueCountFrequency (%)
296714.6 1
0.4%
296683.2 1
0.4%
296023.8 1
0.4%
295427.2 1
0.4%
295070.4 1
0.4%
292918.6 1
0.4%
288393.6 1
0.4%
287805.6 1
0.4%
287680.0 1
0.4%
285730.8 1
0.4%

비영업열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct184
Distinct (%)82.9%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean650.84099
Minimum0
Maximum4873.1
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:17:00.358732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53.245
Q1154.875
median645.9
Q3958.925
95-th percentile1302.46
Maximum4873.1
Range4873.1
Interquartile range (IQR)804.05

Descriptive statistics

Standard deviation520.40534
Coefficient of variation (CV)0.79958907
Kurtosis18.495793
Mean650.84099
Median Absolute Deviation (MAD)441.45
Skewness2.5751211
Sum144486.7
Variance270821.72
MonotonicityNot monotonic
2024-04-20T05:17:00.925358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.1 16
 
6.6%
98.0 5
 
2.1%
148.2 4
 
1.6%
666.3 4
 
1.6%
21.0 4
 
1.6%
1178.5 3
 
1.2%
719.4 2
 
0.8%
638.5 2
 
0.8%
0.0 2
 
0.8%
1185.3 2
 
0.8%
Other values (174) 178
73.3%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
0.0 2
0.8%
17.4 1
 
0.4%
21.0 4
1.6%
23.2 1
 
0.4%
31.7 1
 
0.4%
38.7 1
 
0.4%
42.0 1
 
0.4%
53.1 1
 
0.4%
56.0 2
0.8%
74.1 1
 
0.4%
ValueCountFrequency (%)
4873.1 1
0.4%
2374.1 1
0.4%
1647.3 1
0.4%
1521.6 1
0.4%
1458.2 1
0.4%
1422.1 1
0.4%
1417.7 1
0.4%
1394.9 1
0.4%
1319.0 1
0.4%
1305.8 1
0.4%

전체열차운행키로-합계(Km)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct212
Distinct (%)95.5%
Missing21
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean270746.39
Minimum239184.4
Maximum297245.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-20T05:17:01.303789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239184.4
5-th percentile251687.15
Q1265784.55
median271182.9
Q3279659.05
95-th percentile283099.73
Maximum297245.6
Range58061.2
Interquartile range (IQR)13874.5

Descriptive statistics

Standard deviation10914.522
Coefficient of variation (CV)0.040312714
Kurtosis0.33218753
Mean270746.39
Median Absolute Deviation (MAD)8135.4
Skewness-0.35905195
Sum60105699
Variance1.1912678 × 108
MonotonicityNot monotonic
2024-04-20T05:17:01.570109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266521.9 4
 
1.6%
279514.3 2
 
0.8%
267193.9 2
 
0.8%
280026.5 2
 
0.8%
265103.8 2
 
0.8%
280016.7 2
 
0.8%
272367.3 2
 
0.8%
266575.0 2
 
0.8%
272427.2 1
 
0.4%
279147.7 1
 
0.4%
Other values (202) 202
83.1%
(Missing) 21
 
8.6%
ValueCountFrequency (%)
239184.4 1
0.4%
239669.6 1
0.4%
239741.5 1
0.4%
241007.8 1
0.4%
241413.6 1
0.4%
247324.3 1
0.4%
249788.3 1
0.4%
250461.7 1
0.4%
250664.1 1
0.4%
250834.1 1
0.4%
ValueCountFrequency (%)
297245.6 1
0.4%
297131.6 1
0.4%
296641.5 1
0.4%
296070.5 1
0.4%
295840.6 1
0.4%
293843.4 1
0.4%
289065.4 1
0.4%
288411.4 1
0.4%
288168.9 1
0.4%
286320.2 1
0.4%

Interactions

2024-04-20T05:16:47.380716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:15.202180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:18.030532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:20.673787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:23.915784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.567628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:29.489052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:32.371308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:35.542638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:39.330783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:42.261542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.948871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:47.569622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:15.408023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:18.285096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:20.945303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:24.161870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.766133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:29.757337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:32.639138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:35.836429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:39.581932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:42.528788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:45.165751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:47.732233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:15.662154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:18.532224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:21.292408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:24.404084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.968592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:29.922223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:32.978088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:36.094191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:39.852352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:42.774503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:45.335588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:47.907935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:15.843895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:18.799798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:21.569407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:24.668828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:27.261417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:30.168850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:33.234133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:36.434629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:40.163448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:43.118556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:45.528951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:48.115601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:16.012624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.015155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:21.830753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:24.823450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:27.489423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:30.361632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:33.520065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:36.754945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:40.427684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:43.364908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:45.727211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:48.380113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:16.185102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.175893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:22.132219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:25.028825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:27.705597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:30.528986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:33.782319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:37.136497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:40.641339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:43.628385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:46.078166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:48.639557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:16.541687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.326060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:22.408670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:25.277908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:27.978545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:30.677397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:34.013026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:37.401479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:40.814312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:43.871195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:46.296123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:48.897324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:16.806575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.549699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:22.676186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:25.488956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:28.275164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:30.956941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:34.213568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:37.783617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:41.040570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.098489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:46.522765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:49.116245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:17.062193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.736002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:22.992798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:25.805777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:28.469870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:31.348052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:34.407267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:38.161996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:41.285408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.301600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:46.706317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:49.352968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:17.311990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:19.936262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:23.174153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.036649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:28.726848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:31.591040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:34.583069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:38.404840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:41.545886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.467277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:46.851530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:49.605672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:17.567803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:20.182849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:23.378914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.255701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:28.975731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:31.841239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:34.977265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:38.661802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:41.755898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.618559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:47.004218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:49.855004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:17.826565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:20.424396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:23.646622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:26.404000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:29.228104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:32.095614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:35.267208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:39.026748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:41.988078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:44.787169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-20T05:16:47.162685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T05:17:01.926297image/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)
연도1.0000.0000.0000.6690.0000.6820.7630.6770.7050.0000.6970.9010.704
0.0001.0000.8660.7520.2440.7160.0930.6930.7060.2570.7040.0000.720
영업일0.0000.8661.0000.9460.0000.9430.1620.9230.9510.0000.9380.0000.954
영업열차운행횟수-정기(회)0.6690.7520.9461.0000.5020.9900.6330.9680.9730.4660.9630.5800.958
영업열차운행횟수-임시(회)0.0000.2440.0000.5021.0000.5960.0000.4190.0001.0000.0000.0000.000
영업열차운행횟수-합계(회)0.6820.7160.9430.9900.5961.0000.6450.9610.9640.6320.9580.5590.960
비영업열차운행횟수-합계(회)0.7630.0930.1620.6330.0000.6451.0000.6890.7260.0000.7210.9170.726
전체열차운행횟수-합계(회)0.6770.6930.9230.9680.4190.9610.6891.0000.9470.4840.9450.6640.952
영업열차운행키로-정기(Km)0.7050.7060.9510.9730.0000.9640.7260.9471.0000.0000.9990.6060.998
영업열차운행키로-임시(Km)0.0000.2570.0000.4661.0000.6320.0000.4840.0001.0000.0000.0000.000
영업열차운행키로-합계(Km)0.6970.7040.9380.9630.0000.9580.7210.9450.9990.0001.0000.5970.998
비영업열차운행키로-합계(Km)0.9010.0000.0000.5800.0000.5590.9170.6640.6060.0000.5971.0000.601
전체열차운행키로-합계(Km)0.7040.7200.9540.9580.0000.9600.7260.9520.9980.0000.9980.6011.000
2024-04-20T05:17:02.271025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호선영업일
호선1.0001.000
영업일1.0001.000
2024-04-20T05:17:02.463742image/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
연도1.000-0.060-0.6570.148-0.6530.881-0.5530.5350.1600.5390.8260.5531.0000.000
-0.0601.0000.1410.1800.1460.0620.1540.1780.1850.1730.0910.1691.0000.530
영업열차운행횟수-정기(회)-0.6570.1411.000-0.1440.997-0.5540.949-0.069-0.153-0.069-0.531-0.0701.0000.688
영업열차운행횟수-임시(회)0.1480.180-0.1441.000-0.0930.192-0.1170.2820.9970.3240.1870.3101.0000.000
영업열차운행횟수-합계(회)-0.6530.1460.997-0.0931.000-0.5470.953-0.069-0.102-0.064-0.523-0.0651.0000.681
비영업열차운행횟수-합계(회)0.8810.062-0.5540.192-0.5471.000-0.4500.6020.2090.6090.9510.6351.0000.092
전체열차운행횟수-합계(회)-0.5530.1540.949-0.1170.953-0.4501.0000.008-0.1240.013-0.4120.0221.0000.629
영업열차운행키로-정기(Km)0.5350.178-0.0690.282-0.0690.6020.0081.0000.2970.9970.5390.9941.0000.693
영업열차운행키로-임시(Km)0.1600.185-0.1530.997-0.1020.209-0.1240.2971.0000.3390.2030.3261.0000.000
영업열차운행키로-합계(Km)0.5390.173-0.0690.324-0.0640.6090.0130.9970.3391.0000.5470.9971.0000.660
비영업열차운행키로-합계(Km)0.8260.091-0.5310.187-0.5230.951-0.4120.5390.2030.5471.0000.5801.0000.000
전체열차운행키로-합계(Km)0.5530.169-0.0700.310-0.0650.6350.0220.9940.3260.9970.5801.0001.0000.700
호선1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업일0.0000.5300.6880.0000.6810.0920.6290.6930.0000.6600.0000.7001.0001.000

Missing values

2024-04-20T05:16:50.204469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T05:16:50.809219image/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.
2024-04-20T05:16:51.313974image/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)
0200510214896368969148983249903.5200.0250103.5358.2250461.7
1200511230926349267919358258363.6112.0258475.62374.1260849.7
220051223195524955659561266427.1112.0266539.138.7266577.8
32006123195040950409504265082.80.0265082.80.0265082.8
42006222886400864068646240990.40.0240990.417.4241007.8
520063231955209552319583266418.20.0266418.2617.2267035.4
620064230924009240189258257716.00.0257716.0144.6257860.6
72006523195280952829530265754.80.0265754.856.0265810.8
8200662309239249263109273257677.9655.4258333.3130.3258463.6
92006723195280952879535265746.20.0265746.2122.8265869.0
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)
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242<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>21