Overview

Dataset statistics

Number of variables16
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.2 KiB
Average record size in memory144.2 B

Variable types

DateTime1
Numeric15

Dataset

Description광주교통공사 무료대여자전거대여수에 대한 데이터로 월별 , 역별(소태역, 학동증심사역 등) 자전거 대여수 정보를 제공합니다.
Author광주교통공사
URLhttps://www.data.go.kr/data/15046052/fileData.do

Alerts

소태역 is highly overall correlated with 학동증심사입구역 and 12 other fieldsHigh correlation
학동증심사입구역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
남광주역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
금남로5가역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
농성역 is highly overall correlated with 소태역 and 12 other fieldsHigh correlation
화정역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
쌍촌역 is highly overall correlated with 소태역 and 12 other fieldsHigh correlation
운천역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
상무역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
김대중컨벤션센터역 is highly overall correlated with 학동증심사입구역 and 12 other fieldsHigh correlation
공항역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
송정공원역 is highly overall correlated with 소태역 and 12 other fieldsHigh correlation
광주송정역 is highly overall correlated with 소태역 and 9 other fieldsHigh correlation
도산역 is highly overall correlated with 소태역 and 12 other fieldsHigh correlation
평동역 is highly overall correlated with 소태역 and 13 other fieldsHigh correlation
월별 대여수 has unique valuesUnique
소태역 has 12 (11.1%) zerosZeros
학동증심사입구역 has 14 (13.0%) zerosZeros
남광주역 has 10 (9.3%) zerosZeros
금남로5가역 has 10 (9.3%) zerosZeros
농성역 has 9 (8.3%) zerosZeros
화정역 has 11 (10.2%) zerosZeros
쌍촌역 has 13 (12.0%) zerosZeros
운천역 has 10 (9.3%) zerosZeros
상무역 has 11 (10.2%) zerosZeros
김대중컨벤션센터역 has 9 (8.3%) zerosZeros
공항역 has 12 (11.1%) zerosZeros
송정공원역 has 10 (9.3%) zerosZeros
광주송정역 has 29 (26.9%) zerosZeros
도산역 has 11 (10.2%) zerosZeros
평동역 has 9 (8.3%) zerosZeros

Reproduction

Analysis started2024-04-06 08:40:28.333108
Analysis finished2024-04-06 08:41:36.230107
Duration1 minute and 7.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

월별 대여수
Date

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
Minimum2015-01-01 00:00:00
Maximum2023-12-01 00:00:00
2024-04-06T17:41:36.480170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:36.937898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소태역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.453704
Minimum0
Maximum133
Zeros12
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:37.372579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.75
median12
Q326
95-th percentile41.3
Maximum133
Range133
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation17.881952
Coefficient of variation (CV)1.086804
Kurtosis15.772053
Mean16.453704
Median Absolute Deviation (MAD)10
Skewness2.9214395
Sum1777
Variance319.76419
MonotonicityNot monotonic
2024-04-06T17:41:37.800162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 12
 
11.1%
7 6
 
5.6%
1 5
 
4.6%
12 5
 
4.6%
3 5
 
4.6%
2 5
 
4.6%
29 4
 
3.7%
5 4
 
3.7%
4 4
 
3.7%
6 4
 
3.7%
Other values (30) 54
50.0%
ValueCountFrequency (%)
0 12
11.1%
1 5
4.6%
2 5
4.6%
3 5
4.6%
4 4
 
3.7%
5 4
 
3.7%
6 4
 
3.7%
7 6
5.6%
8 1
 
0.9%
9 2
 
1.9%
ValueCountFrequency (%)
133 1
0.9%
56 1
0.9%
54 1
0.9%
48 2
1.9%
42 1
0.9%
40 1
0.9%
39 1
0.9%
38 2
1.9%
36 2
1.9%
35 1
0.9%

학동증심사입구역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.907407
Minimum0
Maximum222
Zeros14
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:38.203268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median20
Q344
95-th percentile67.65
Maximum222
Range222
Interquartile range (IQR)41

Descriptive statistics

Standard deviation30.135686
Coefficient of variation (CV)1.1199773
Kurtosis15.037712
Mean26.907407
Median Absolute Deviation (MAD)19
Skewness2.7155555
Sum2906
Variance908.15957
MonotonicityNot monotonic
2024-04-06T17:41:39.222614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 14
 
13.0%
3 8
 
7.4%
2 6
 
5.6%
1 5
 
4.6%
42 4
 
3.7%
44 4
 
3.7%
45 4
 
3.7%
4 4
 
3.7%
5 3
 
2.8%
6 3
 
2.8%
Other values (36) 53
49.1%
ValueCountFrequency (%)
0 14
13.0%
1 5
 
4.6%
2 6
5.6%
3 8
7.4%
4 4
 
3.7%
5 3
 
2.8%
6 3
 
2.8%
7 2
 
1.9%
8 1
 
0.9%
10 1
 
0.9%
ValueCountFrequency (%)
222 1
0.9%
88 1
0.9%
77 1
0.9%
72 2
1.9%
68 1
0.9%
67 1
0.9%
65 1
0.9%
64 1
0.9%
62 1
0.9%
60 1
0.9%

남광주역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct70
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.601852
Minimum0
Maximum224
Zeros10
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:39.635021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median44
Q383.25
95-th percentile117.95
Maximum224
Range224
Interquartile range (IQR)64.25

Descriptive statistics

Standard deviation41.563585
Coefficient of variation (CV)0.7901544
Kurtosis1.249187
Mean52.601852
Median Absolute Deviation (MAD)29.5
Skewness0.90577806
Sum5681
Variance1727.5316
MonotonicityNot monotonic
2024-04-06T17:41:40.159657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
9.3%
31 6
 
5.6%
19 4
 
3.7%
23 4
 
3.7%
40 3
 
2.8%
10 3
 
2.8%
100 2
 
1.9%
103 2
 
1.9%
87 2
 
1.9%
84 2
 
1.9%
Other values (60) 70
64.8%
ValueCountFrequency (%)
0 10
9.3%
1 1
 
0.9%
2 1
 
0.9%
3 1
 
0.9%
8 1
 
0.9%
9 1
 
0.9%
10 3
 
2.8%
11 1
 
0.9%
12 1
 
0.9%
14 1
 
0.9%
ValueCountFrequency (%)
224 1
0.9%
140 1
0.9%
129 1
0.9%
126 1
0.9%
122 1
0.9%
119 1
0.9%
116 1
0.9%
114 1
0.9%
112 2
1.9%
109 1
0.9%

금남로5가역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.537037
Minimum0
Maximum114
Zeros10
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:40.632510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median32.5
Q351.75
95-th percentile88.3
Maximum114
Range114
Interquartile range (IQR)39.75

Descriptive statistics

Standard deviation29.004488
Coefficient of variation (CV)0.8161763
Kurtosis-0.42251202
Mean35.537037
Median Absolute Deviation (MAD)20.5
Skewness0.70387407
Sum3838
Variance841.2603
MonotonicityNot monotonic
2024-04-06T17:41:41.022728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
9.3%
6 6
 
5.6%
12 5
 
4.6%
13 4
 
3.7%
42 4
 
3.7%
33 4
 
3.7%
17 3
 
2.8%
1 3
 
2.8%
18 3
 
2.8%
26 3
 
2.8%
Other values (49) 63
58.3%
ValueCountFrequency (%)
0 10
9.3%
1 3
 
2.8%
4 1
 
0.9%
5 1
 
0.9%
6 6
5.6%
7 1
 
0.9%
8 1
 
0.9%
12 5
4.6%
13 4
 
3.7%
14 1
 
0.9%
ValueCountFrequency (%)
114 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%
92 1
0.9%
89 1
0.9%
87 1
0.9%
86 1
0.9%
85 1
0.9%
82 2
1.9%

농성역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.444444
Minimum0
Maximum114
Zeros9
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:41.542822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q128.5
median53.5
Q377.25
95-th percentile93.65
Maximum114
Range114
Interquartile range (IQR)48.75

Descriptive statistics

Standard deviation30.244899
Coefficient of variation (CV)0.59956848
Kurtosis-1.0704865
Mean50.444444
Median Absolute Deviation (MAD)24.5
Skewness-0.10012233
Sum5448
Variance914.75389
MonotonicityNot monotonic
2024-04-06T17:41:41.963991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
8.3%
79 4
 
3.7%
36 3
 
2.8%
38 3
 
2.8%
12 3
 
2.8%
63 3
 
2.8%
69 2
 
1.9%
92 2
 
1.9%
53 2
 
1.9%
78 2
 
1.9%
Other values (57) 75
69.4%
ValueCountFrequency (%)
0 9
8.3%
2 1
 
0.9%
8 1
 
0.9%
9 1
 
0.9%
10 1
 
0.9%
11 2
 
1.9%
12 3
 
2.8%
14 1
 
0.9%
15 1
 
0.9%
19 1
 
0.9%
ValueCountFrequency (%)
114 1
0.9%
103 1
0.9%
102 1
0.9%
98 1
0.9%
95 1
0.9%
94 1
0.9%
93 1
0.9%
92 2
1.9%
91 1
0.9%
90 2
1.9%

화정역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.657407
Minimum0
Maximum42
Zeros11
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:42.412620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median12
Q318
95-th percentile29.65
Maximum42
Range42
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.1316048
Coefficient of variation (CV)0.72144354
Kurtosis0.2508017
Mean12.657407
Median Absolute Deviation (MAD)6
Skewness0.69591168
Sum1367
Variance83.386206
MonotonicityNot monotonic
2024-04-06T17:41:42.931800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 11
 
10.2%
18 7
 
6.5%
5 7
 
6.5%
15 7
 
6.5%
13 6
 
5.6%
10 5
 
4.6%
14 5
 
4.6%
8 5
 
4.6%
4 5
 
4.6%
9 5
 
4.6%
Other values (22) 45
41.7%
ValueCountFrequency (%)
0 11
10.2%
1 2
 
1.9%
2 3
 
2.8%
4 5
4.6%
5 7
6.5%
6 4
 
3.7%
7 2
 
1.9%
8 5
4.6%
9 5
4.6%
10 5
4.6%
ValueCountFrequency (%)
42 1
 
0.9%
37 1
 
0.9%
32 1
 
0.9%
31 2
1.9%
30 1
 
0.9%
29 1
 
0.9%
28 1
 
0.9%
27 1
 
0.9%
26 4
3.7%
24 3
2.8%

쌍촌역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.703704
Minimum0
Maximum61
Zeros13
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:43.341525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.75
median14
Q325
95-th percentile43.95
Maximum61
Range61
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation13.530346
Coefficient of variation (CV)0.81002072
Kurtosis0.79209579
Mean16.703704
Median Absolute Deviation (MAD)8.5
Skewness0.99833748
Sum1804
Variance183.07027
MonotonicityNot monotonic
2024-04-06T17:41:43.860049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 13
 
12.0%
11 7
 
6.5%
17 7
 
6.5%
14 5
 
4.6%
10 5
 
4.6%
9 5
 
4.6%
28 4
 
3.7%
16 4
 
3.7%
15 4
 
3.7%
25 4
 
3.7%
Other values (32) 50
46.3%
ValueCountFrequency (%)
0 13
12.0%
1 2
 
1.9%
2 2
 
1.9%
3 2
 
1.9%
4 1
 
0.9%
5 4
 
3.7%
6 2
 
1.9%
7 1
 
0.9%
8 2
 
1.9%
9 5
 
4.6%
ValueCountFrequency (%)
61 1
0.9%
54 1
0.9%
53 1
0.9%
48 1
0.9%
45 2
1.9%
42 1
0.9%
41 1
0.9%
39 1
0.9%
38 2
1.9%
37 1
0.9%

운천역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct59
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.777778
Minimum0
Maximum129
Zeros10
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:44.277664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median35
Q354
95-th percentile85.65
Maximum129
Range129
Interquartile range (IQR)40

Descriptive statistics

Standard deviation28.102727
Coefficient of variation (CV)0.78547993
Kurtosis0.088503822
Mean35.777778
Median Absolute Deviation (MAD)20
Skewness0.69908108
Sum3864
Variance789.76324
MonotonicityNot monotonic
2024-04-06T17:41:44.734168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
9.3%
54 5
 
4.6%
19 5
 
4.6%
41 4
 
3.7%
2 3
 
2.8%
15 3
 
2.8%
18 3
 
2.8%
14 3
 
2.8%
44 3
 
2.8%
46 3
 
2.8%
Other values (49) 66
61.1%
ValueCountFrequency (%)
0 10
9.3%
1 2
 
1.9%
2 3
 
2.8%
4 1
 
0.9%
5 2
 
1.9%
6 2
 
1.9%
7 1
 
0.9%
11 2
 
1.9%
12 2
 
1.9%
14 3
 
2.8%
ValueCountFrequency (%)
129 1
0.9%
107 1
0.9%
96 1
0.9%
87 2
1.9%
86 1
0.9%
85 1
0.9%
82 1
0.9%
81 1
0.9%
80 1
0.9%
76 1
0.9%

상무역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct68
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.407407
Minimum0
Maximum164
Zeros11
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:45.216015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131
median76.5
Q3100
95-th percentile150.65
Maximum164
Range164
Interquartile range (IQR)69

Descriptive statistics

Standard deviation46.655436
Coefficient of variation (CV)0.65336969
Kurtosis-0.9117584
Mean71.407407
Median Absolute Deviation (MAD)36.5
Skewness0.15612037
Sum7712
Variance2176.7297
MonotonicityNot monotonic
2024-04-06T17:41:45.626756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
10.2%
20 4
 
3.7%
86 4
 
3.7%
98 3
 
2.8%
38 3
 
2.8%
151 3
 
2.8%
31 3
 
2.8%
76 3
 
2.8%
71 2
 
1.9%
36 2
 
1.9%
Other values (58) 70
64.8%
ValueCountFrequency (%)
0 11
10.2%
7 1
 
0.9%
15 2
 
1.9%
16 1
 
0.9%
17 1
 
0.9%
18 1
 
0.9%
20 4
 
3.7%
24 1
 
0.9%
25 1
 
0.9%
27 1
 
0.9%
ValueCountFrequency (%)
164 1
 
0.9%
161 1
 
0.9%
160 1
 
0.9%
151 3
2.8%
150 1
 
0.9%
149 2
1.9%
148 2
1.9%
145 1
 
0.9%
142 1
 
0.9%
133 1
 
0.9%

김대중컨벤션센터역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.814815
Minimum0
Maximum177
Zeros9
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:46.069120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.75
median29.5
Q346.25
95-th percentile94.25
Maximum177
Range177
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation31.37567
Coefficient of variation (CV)0.87605284
Kurtosis5.4859613
Mean35.814815
Median Absolute Deviation (MAD)15.5
Skewness1.9613502
Sum3868
Variance984.43268
MonotonicityNot monotonic
2024-04-06T17:41:46.479658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
8.3%
27 4
 
3.7%
14 4
 
3.7%
17 4
 
3.7%
30 4
 
3.7%
20 3
 
2.8%
18 3
 
2.8%
36 3
 
2.8%
38 3
 
2.8%
32 3
 
2.8%
Other values (48) 68
63.0%
ValueCountFrequency (%)
0 9
8.3%
1 1
 
0.9%
2 1
 
0.9%
6 1
 
0.9%
9 3
 
2.8%
10 3
 
2.8%
11 1
 
0.9%
12 1
 
0.9%
13 2
 
1.9%
14 4
3.7%
ValueCountFrequency (%)
177 1
0.9%
164 1
0.9%
118 1
0.9%
113 1
0.9%
108 1
0.9%
96 1
0.9%
91 1
0.9%
83 1
0.9%
75 1
0.9%
74 1
0.9%

공항역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct52
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.648148
Minimum0
Maximum115
Zeros12
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:47.006836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median19
Q337
95-th percentile78.9
Maximum115
Range115
Interquartile range (IQR)30

Descriptive statistics

Standard deviation24.917552
Coefficient of variation (CV)0.97151466
Kurtosis1.8850853
Mean25.648148
Median Absolute Deviation (MAD)14
Skewness1.3830003
Sum2770
Variance620.88439
MonotonicityNot monotonic
2024-04-06T17:41:47.531764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
11.1%
8 5
 
4.6%
9 4
 
3.7%
32 4
 
3.7%
7 4
 
3.7%
17 4
 
3.7%
23 3
 
2.8%
1 3
 
2.8%
10 3
 
2.8%
47 3
 
2.8%
Other values (42) 63
58.3%
ValueCountFrequency (%)
0 12
11.1%
1 3
 
2.8%
2 3
 
2.8%
3 1
 
0.9%
4 2
 
1.9%
5 2
 
1.9%
6 2
 
1.9%
7 4
 
3.7%
8 5
4.6%
9 4
 
3.7%
ValueCountFrequency (%)
115 1
0.9%
102 1
0.9%
96 1
0.9%
95 1
0.9%
82 1
0.9%
81 1
0.9%
75 1
0.9%
71 1
0.9%
65 1
0.9%
63 1
0.9%

송정공원역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.277778
Minimum0
Maximum87
Zeros10
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:47.981669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median33.5
Q347
95-th percentile67.65
Maximum87
Range87
Interquartile range (IQR)28

Descriptive statistics

Standard deviation20.174395
Coefficient of variation (CV)0.60624227
Kurtosis-0.41793649
Mean33.277778
Median Absolute Deviation (MAD)14
Skewness0.26057705
Sum3594
Variance407.00623
MonotonicityNot monotonic
2024-04-06T17:41:48.379419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10
 
9.3%
37 5
 
4.6%
26 4
 
3.7%
43 4
 
3.7%
20 4
 
3.7%
29 3
 
2.8%
35 3
 
2.8%
48 3
 
2.8%
22 3
 
2.8%
11 3
 
2.8%
Other values (44) 66
61.1%
ValueCountFrequency (%)
0 10
9.3%
6 1
 
0.9%
10 2
 
1.9%
11 3
 
2.8%
12 1
 
0.9%
13 2
 
1.9%
14 3
 
2.8%
15 2
 
1.9%
16 1
 
0.9%
18 1
 
0.9%
ValueCountFrequency (%)
87 1
0.9%
82 1
0.9%
71 1
0.9%
70 1
0.9%
69 1
0.9%
68 1
0.9%
67 1
0.9%
66 1
0.9%
64 1
0.9%
62 1
0.9%

광주송정역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.990741
Minimum0
Maximum190
Zeros29
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:48.772065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23
Q374.5
95-th percentile145
Maximum190
Range190
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation49.341551
Coefficient of variation (CV)1.1216349
Kurtosis0.078428926
Mean43.990741
Median Absolute Deviation (MAD)23
Skewness1.0313897
Sum4751
Variance2434.5887
MonotonicityNot monotonic
2024-04-06T17:41:49.231523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
26.9%
10 4
 
3.7%
3 3
 
2.8%
80 3
 
2.8%
14 3
 
2.8%
62 3
 
2.8%
37 3
 
2.8%
15 3
 
2.8%
26 2
 
1.9%
25 2
 
1.9%
Other values (47) 53
49.1%
ValueCountFrequency (%)
0 29
26.9%
1 1
 
0.9%
2 1
 
0.9%
3 3
 
2.8%
4 1
 
0.9%
5 2
 
1.9%
10 4
 
3.7%
11 1
 
0.9%
12 1
 
0.9%
14 3
 
2.8%
ValueCountFrequency (%)
190 1
0.9%
172 1
0.9%
158 1
0.9%
150 1
0.9%
146 1
0.9%
145 2
1.9%
139 1
0.9%
135 1
0.9%
133 1
0.9%
132 1
0.9%

도산역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.712963
Minimum0
Maximum112
Zeros11
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:49.685805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median24.5
Q344.25
95-th percentile77.65
Maximum112
Range112
Interquartile range (IQR)32.25

Descriptive statistics

Standard deviation24.800909
Coefficient of variation (CV)0.80750622
Kurtosis0.26281456
Mean30.712963
Median Absolute Deviation (MAD)14.5
Skewness0.85400215
Sum3317
Variance615.08506
MonotonicityNot monotonic
2024-04-06T17:41:50.702087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11
 
10.2%
15 6
 
5.6%
21 5
 
4.6%
12 5
 
4.6%
41 4
 
3.7%
10 4
 
3.7%
39 3
 
2.8%
34 3
 
2.8%
19 3
 
2.8%
38 3
 
2.8%
Other values (47) 61
56.5%
ValueCountFrequency (%)
0 11
10.2%
1 2
 
1.9%
2 1
 
0.9%
3 1
 
0.9%
4 1
 
0.9%
8 1
 
0.9%
9 2
 
1.9%
10 4
 
3.7%
11 3
 
2.8%
12 5
4.6%
ValueCountFrequency (%)
112 1
0.9%
97 1
0.9%
84 1
0.9%
83 1
0.9%
80 1
0.9%
78 1
0.9%
77 1
0.9%
75 1
0.9%
68 1
0.9%
67 1
0.9%

평동역
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct81
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.9537
Minimum0
Maximum513
Zeros9
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T17:41:51.073151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q158
median97.5
Q3174
95-th percentile363.25
Maximum513
Range513
Interquartile range (IQR)116

Descriptive statistics

Standard deviation110.89453
Coefficient of variation (CV)0.85995612
Kurtosis1.9515838
Mean128.9537
Median Absolute Deviation (MAD)47
Skewness1.4541989
Sum13927
Variance12297.596
MonotonicityNot monotonic
2024-04-06T17:41:51.497796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
8.3%
92 3
 
2.8%
73 3
 
2.8%
113 2
 
1.9%
108 2
 
1.9%
65 2
 
1.9%
16 2
 
1.9%
42 2
 
1.9%
84 2
 
1.9%
40 2
 
1.9%
Other values (71) 79
73.1%
ValueCountFrequency (%)
0 9
8.3%
5 1
 
0.9%
15 1
 
0.9%
16 2
 
1.9%
20 1
 
0.9%
33 1
 
0.9%
40 2
 
1.9%
41 1
 
0.9%
42 2
 
1.9%
46 1
 
0.9%
ValueCountFrequency (%)
513 1
0.9%
452 1
0.9%
450 1
0.9%
438 1
0.9%
411 1
0.9%
365 1
0.9%
360 2
1.9%
340 1
0.9%
323 1
0.9%
279 1
0.9%

Interactions

2024-04-06T17:41:30.569617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:29.649103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:33.755431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:37.650348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:41.397548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:45.690347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:49.976648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:54.023852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:58.364050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:02.869847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:07.563961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:12.010225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:16.041550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:19.817395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:25.099178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:30.790351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:29.925867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:33.996333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:37.914288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:41.640329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:45.949266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:50.309402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:54.268955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:58.750682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:03.780015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:07.887750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:12.350112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:16.297369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:20.679650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:25.419858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:31.252438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:30.158384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:34.222770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:38.129161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:41.903162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:46.210125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:50.568133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:54.510728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:59.018663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:04.032315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:08.229338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:12.575341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:16.524426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:20.942897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:25.844189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:31.582083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:30.432431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:34.493873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:38.347237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:42.154017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:46.440127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:50.798931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:54.741312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:59.383916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:04.319648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:08.534584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:12.825044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:16.745439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:21.201739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:26.215115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:31.905623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:30.673531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:34.851996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:38.549422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:42.393959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:46.717462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:51.143116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:55.014852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:59.677181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:04.585527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:08.864874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:13.165229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:16.976986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:21.516272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:26.513989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:32.199651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:30.962173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:35.099929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:38.766605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:42.608189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:47.013294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:51.443951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:55.253148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:59.927088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:04.848535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:09.145385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:13.468371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:17.196331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:21.821782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:26.931635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:32.452317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:31.184729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:35.338726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:39.069154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:42.847460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:47.253898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:51.670083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:55.564491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:00.199525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:05.081151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:09.419209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:13.680342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:17.414150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:22.237661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:27.332853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:32.766796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:31.410622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:35.568176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:39.404886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:43.063073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:47.514170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:51.903376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:55.800481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:00.481295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:05.320764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:09.708778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:13.956390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:17.635359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:22.553541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:27.695570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:33.063504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:31.660475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:35.799429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:39.688593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:43.288476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:47.766471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:52.335499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:56.125307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:00.778006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:05.569359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:10.041807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:14.212039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:17.869238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:23.059052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:28.347390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:33.355851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:31.963822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:36.075568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:39.966484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:43.566363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:48.072087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:52.613597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:56.458147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:01.134614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:05.807774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:10.431210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:14.465458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:18.178095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:23.419015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:28.835565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:33.681402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:32.386196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:36.325614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:40.205389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:43.801693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:48.426981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:52.849159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:56.770845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:01.455758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:06.115342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:10.726291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:14.716579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:18.434336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:23.704256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:29.194780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:34.022273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:32.625253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:36.595037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:40.406129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:44.058583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:48.785047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:53.091180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:57.059855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:01.730890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:06.363128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:11.011870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:14.960812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:18.695470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:23.941472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:29.514060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:34.286041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:32.846696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:36.939523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:40.665644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:44.263088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:49.077515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:53.325228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:57.385217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:01.979783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:06.597488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:11.252542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:15.253556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:18.960102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:24.183990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:29.769996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:34.561067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:33.226456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:37.200649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:40.940285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:44.535775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:49.437456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:53.569610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:57.727775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:02.333716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:06.911917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:11.544561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:15.561795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:19.307260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:24.474632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:30.028423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:34.821574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:33.518624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:37.428311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:41.190860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:44.740878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:49.729778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:53.817967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:40:57.996380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:02.610930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:07.237196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:11.780812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:15.799917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:19.579393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:24.779693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:41:30.335434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:41:51.845765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소태역학동증심사입구역남광주역금남로5가역농성역화정역쌍촌역운천역상무역김대중컨벤션센터역공항역송정공원역광주송정역도산역평동역
소태역1.0000.7660.5260.4530.5370.6160.6190.5840.6730.3270.5480.3020.6200.4850.568
학동증심사입구역0.7661.0000.6540.8530.6330.6090.8240.7900.8330.5530.8060.5540.8630.7230.845
남광주역0.5260.6541.0000.7020.5730.5590.5960.8460.6730.8060.7930.7110.7490.7620.795
금남로5가역0.4530.8530.7021.0000.7170.6520.6920.8570.7800.7270.8410.8430.7460.7260.860
농성역0.5370.6330.5730.7171.0000.5980.5840.7520.7910.4880.6070.7230.6150.6820.677
화정역0.6160.6090.5590.6520.5981.0000.5940.6220.6540.4490.6780.5720.6320.5530.562
쌍촌역0.6190.8240.5960.6920.5840.5941.0000.8330.6600.6520.7930.7190.7640.7510.692
운천역0.5840.7900.8460.8570.7520.6220.8331.0000.8340.7390.9060.8810.8690.8650.916
상무역0.6730.8330.6730.7800.7910.6540.6600.8341.0000.5440.7510.7600.6360.7590.784
김대중컨벤션센터역0.3270.5530.8060.7270.4880.4490.6520.7390.5441.0000.7430.6680.6550.5970.788
공항역0.5480.8060.7930.8410.6070.6780.7930.9060.7510.7431.0000.8110.8690.8900.874
송정공원역0.3020.5540.7110.8430.7230.5720.7190.8810.7600.6680.8111.0000.6900.8010.854
광주송정역0.6200.8630.7490.7460.6150.6320.7640.8690.6360.6550.8690.6901.0000.8620.821
도산역0.4850.7230.7620.7260.6820.5530.7510.8650.7590.5970.8900.8010.8621.0000.798
평동역0.5680.8450.7950.8600.6770.5620.6920.9160.7840.7880.8740.8540.8210.7981.000
2024-04-06T17:41:52.324533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소태역학동증심사입구역남광주역금남로5가역농성역화정역쌍촌역운천역상무역김대중컨벤션센터역공항역송정공원역광주송정역도산역평동역
소태역1.0000.7910.7950.6180.7940.6100.5460.7210.8280.4930.7250.5300.6430.6040.697
학동증심사입구역0.7911.0000.8800.8100.7660.5910.6330.8440.8550.6790.8400.5650.7800.7380.851
남광주역0.7950.8801.0000.8470.7680.6370.6300.8430.8310.6480.8290.6720.7230.7490.840
금남로5가역0.6180.8100.8471.0000.6830.6090.6050.8490.7270.7250.7670.7300.6770.7410.853
농성역0.7940.7660.7680.6831.0000.5030.5520.7410.7900.5160.6710.5430.4970.6840.663
화정역0.6100.5910.6370.6090.5031.0000.5290.6050.6000.5370.5750.5700.5630.5560.541
쌍촌역0.5460.6330.6300.6050.5520.5291.0000.6520.6650.5790.6130.5330.4640.6720.558
운천역0.7210.8440.8430.8490.7410.6050.6521.0000.8030.6620.8170.7440.6590.8050.848
상무역0.8280.8550.8310.7270.7900.6000.6650.8031.0000.6060.8120.6240.5930.7630.762
김대중컨벤션센터역0.4930.6790.6480.7250.5160.5370.5790.6620.6061.0000.6890.5700.5950.6680.728
공항역0.7250.8400.8290.7670.6710.5750.6130.8170.8120.6891.0000.6930.6460.7980.833
송정공원역0.5300.5650.6720.7300.5430.5700.5330.7440.6240.5700.6931.0000.3570.7080.659
광주송정역0.6430.7800.7230.6770.4970.5630.4640.6590.5930.5950.6460.3571.0000.4280.748
도산역0.6040.7380.7490.7410.6840.5560.6720.8050.7630.6680.7980.7080.4281.0000.703
평동역0.6970.8510.8400.8530.6630.5410.5580.8480.7620.7280.8330.6590.7480.7031.000

Missing values

2024-04-06T17:41:35.341119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:41:35.991460image/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

월별 대여수소태역학동증심사입구역남광주역금남로5가역농성역화정역쌍촌역운천역상무역김대중컨벤션센터역공항역송정공원역광주송정역도산역평동역
02015-01-01742624757101162982065456839221
12015-02-012042546151261036797346198039323
22015-03-01276510385723029741514082566365450
32015-04-01215712282661827821004695719777360
42015-05-0132882249898263212915111811582158112411
52015-06-011964112806031547697108102688080340
62015-07-012060878640285310712696757010163360
72015-08-0122688411455292587149113716414564438
82015-09-012772319961134585123177816113249452
92015-10-01134914010081152496133164968714675513
월별 대여수소태역학동증심사입구역남광주역금남로5가역농성역화정역쌍촌역운천역상무역김대중컨벤션센터역공항역송정공원역광주송정역도산역평동역
982023-03-01101121437141192818236151020
992023-04-0115325133911614363864211446
1002023-05-0182261738125162037735141078
1012023-06-01722216341361838391038151584
1022023-07-0131231836155173147723201592
1032023-08-01521162651173836934141486
1042023-09-011241613381991920381037161162
1052023-10-011151916401011212536835211258
1062023-11-01532518361614122045720141153
1072023-12-013230193150151720114101062