Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory654.3 KiB
Average record size in memory67.0 B

Variable types

Numeric3
Categorical2
DateTime2

Dataset

Description창원시 무인대여 공영자전거 터미널현황 및 자전거 대여정보
Author창원레포츠파크
URLhttps://www.data.go.kr/data/15014737/fileData.do

Alerts

도착일 is highly overall correlated with 출발일High correlation
출발일 is highly overall correlated with 도착일High correlation

Reproduction

Analysis started2023-12-12 14:18:20.306692
Analysis finished2023-12-12 14:18:23.425354
Duration3.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자전거번호
Real number (ℝ)

Distinct2952
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6808.2908
Minimum3749
Maximum8829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:18:23.495250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3749
5-th percentile4968.95
Q15751.75
median6810
Q37902.25
95-th percentile8740
Maximum8829
Range5080
Interquartile range (IQR)2150.5

Descriptive statistics

Standard deviation1245.2109
Coefficient of variation (CV)0.18289626
Kurtosis-1.065258
Mean6808.2908
Median Absolute Deviation (MAD)1075
Skewness-0.056690268
Sum68082908
Variance1550550.3
MonotonicityNot monotonic
2023-12-12T23:18:23.638982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6297 17
 
0.2%
5761 17
 
0.2%
8740 16
 
0.2%
5455 15
 
0.1%
8745 15
 
0.1%
8757 14
 
0.1%
8810 14
 
0.1%
6748 14
 
0.1%
8809 14
 
0.1%
8739 13
 
0.1%
Other values (2942) 9851
98.5%
ValueCountFrequency (%)
3749 1
 
< 0.1%
3762 1
 
< 0.1%
3782 2
 
< 0.1%
3787 1
 
< 0.1%
3790 1
 
< 0.1%
3802 5
0.1%
3805 1
 
< 0.1%
3824 1
 
< 0.1%
3836 4
< 0.1%
3837 2
 
< 0.1%
ValueCountFrequency (%)
8829 7
0.1%
8828 2
 
< 0.1%
8827 5
0.1%
8826 3
 
< 0.1%
8825 7
0.1%
8824 4
 
< 0.1%
8823 11
0.1%
8822 9
0.1%
8821 4
 
< 0.1%
8820 9
0.1%

출발터미널
Real number (ℝ)

Distinct265
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.1105
Minimum8
Maximum295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:18:23.781306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile11
Q142
median93
Q3157
95-th percentile277
Maximum295
Range287
Interquartile range (IQR)115

Descriptive statistics

Standard deviation82.396824
Coefficient of variation (CV)0.73496081
Kurtosis-0.63193064
Mean112.1105
Median Absolute Deviation (MAD)56
Skewness0.70031402
Sum1121105
Variance6789.2366
MonotonicityNot monotonic
2023-12-12T23:18:23.923399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 253
 
2.5%
41 208
 
2.1%
11 198
 
2.0%
31 193
 
1.9%
286 190
 
1.9%
59 180
 
1.8%
9 153
 
1.5%
27 150
 
1.5%
140 134
 
1.3%
10 131
 
1.3%
Other values (255) 8210
82.1%
ValueCountFrequency (%)
8 99
1.0%
9 153
1.5%
10 131
1.3%
11 198
2.0%
12 42
 
0.4%
15 49
 
0.5%
16 31
 
0.3%
17 58
 
0.6%
18 35
 
0.4%
19 44
 
0.4%
ValueCountFrequency (%)
295 10
 
0.1%
294 16
 
0.2%
293 1
 
< 0.1%
292 52
 
0.5%
291 4
 
< 0.1%
290 6
 
0.1%
288 8
 
0.1%
287 30
 
0.3%
286 190
1.9%
285 10
 
0.1%

출발일
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-08-01
1643 
2018-08-02
1553 
2018-08-03
1546 
2018-08-06
1522 
2018-08-07
1336 
Other values (2)
2400 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-08-07
2nd row2018-08-05
3rd row2018-08-03
4th row2018-08-02
5th row2018-08-01

Common Values

ValueCountFrequency (%)
2018-08-01 1643
16.4%
2018-08-02 1553
15.5%
2018-08-03 1546
15.5%
2018-08-06 1522
15.2%
2018-08-07 1336
13.4%
2018-08-04 1286
12.9%
2018-08-05 1114
11.1%

Length

2023-12-12T23:18:24.086303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:18:24.231885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-01 1643
16.4%
2018-08-02 1553
15.5%
2018-08-03 1546
15.5%
2018-08-06 1522
15.2%
2018-08-07 1336
13.4%
2018-08-04 1286
12.9%
2018-08-05 1114
11.1%

출발시간
Date

Distinct9260
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-12 00:00:08
Maximum2023-12-12 23:59:56
2023-12-12T23:18:24.375749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:24.497718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

도착터미널
Real number (ℝ)

Distinct267
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.8039
Minimum8
Maximum295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:18:24.635745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile11
Q141
median88
Q3156
95-th percentile277
Maximum295
Range287
Interquartile range (IQR)115

Descriptive statistics

Standard deviation82.690233
Coefficient of variation (CV)0.75307191
Kurtosis-0.58910077
Mean109.8039
Median Absolute Deviation (MAD)54
Skewness0.74390782
Sum1098039
Variance6837.6746
MonotonicityNot monotonic
2023-12-12T23:18:24.831954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 323
 
3.2%
41 218
 
2.2%
286 215
 
2.1%
11 206
 
2.1%
9 171
 
1.7%
60 167
 
1.7%
53 167
 
1.7%
123 160
 
1.6%
31 148
 
1.5%
140 148
 
1.5%
Other values (257) 8077
80.8%
ValueCountFrequency (%)
8 106
1.1%
9 171
1.7%
10 120
1.2%
11 206
2.1%
12 75
 
0.8%
15 48
 
0.5%
16 26
 
0.3%
17 67
 
0.7%
18 34
 
0.3%
19 39
 
0.4%
ValueCountFrequency (%)
295 10
 
0.1%
294 29
 
0.3%
292 37
 
0.4%
291 7
 
0.1%
290 6
 
0.1%
289 1
 
< 0.1%
288 9
 
0.1%
287 11
 
0.1%
286 215
2.1%
285 9
 
0.1%

도착일
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2018-08-01
1626 
2018-08-02
1555 
2018-08-03
1549 
2018-08-06
1515 
2018-08-07
1358 
Other values (3)
2397 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-08-07
2nd row2018-08-05
3rd row2018-08-03
4th row2018-08-02
5th row2018-08-01

Common Values

ValueCountFrequency (%)
2018-08-01 1626
16.3%
2018-08-02 1555
15.6%
2018-08-03 1549
15.5%
2018-08-06 1515
15.2%
2018-08-07 1358
13.6%
2018-08-04 1285
12.8%
2018-08-05 1108
11.1%
2018-08-08 4
 
< 0.1%

Length

2023-12-12T23:18:25.030717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:18:25.427860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-01 1626
16.3%
2018-08-02 1555
15.6%
2018-08-03 1549
15.5%
2018-08-06 1515
15.2%
2018-08-07 1358
13.6%
2018-08-04 1285
12.8%
2018-08-05 1108
11.1%
2018-08-08 4
 
< 0.1%

도착시간
Date

Distinct9278
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-12 00:00:10
Maximum2023-12-12 23:59:36
2023-12-12T23:18:25.561316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:25.717275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T23:18:22.904339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.292164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.606735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:23.024299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.387247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.717963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:23.131311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.490197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:18:22.806521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:18:25.813508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거번호출발터미널출발일도착터미널도착일
자전거번호1.0000.0190.0000.0000.000
출발터미널0.0191.0000.0000.7390.000
출발일0.0000.0001.0000.0000.991
도착터미널0.0000.7390.0001.0000.000
도착일0.0000.0000.9910.0001.000
2023-12-12T23:18:25.917634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도착일출발일
도착일1.0000.988
출발일0.9881.000
2023-12-12T23:18:26.001057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자전거번호출발터미널도착터미널출발일도착일
자전거번호1.0000.0030.0010.0000.000
출발터미널0.0031.0000.3150.0000.000
도착터미널0.0010.3151.0000.0000.000
출발일0.0000.0000.0001.0000.988
도착일0.0000.0000.0000.9881.000

Missing values

2023-12-12T23:18:23.258985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:18:23.370833image/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

자전거번호출발터미널출발일출발시간도착터미널도착일도착시간
8546752631512018-08-0709:22:48612018-08-0709:39:07
59382606092018-08-0509:26:1482018-08-0509:32:27
384885199822018-08-0317:02:15572018-08-0317:23:23
1883886641322018-08-0209:23:31552018-08-0209:26:57
112585487342018-08-0119:19:22342018-08-0119:19:28
443945400432018-08-0322:21:53352018-08-0322:23:41
862656999102018-08-0710:39:272412018-08-0710:52:02
381048690152018-08-0316:34:34642018-08-0316:42:53
6325786301412018-08-0517:38:371402018-08-0517:44:49
4772385631162018-08-0409:21:012762018-08-0409:26:52
자전거번호출발터미널출발일출발시간도착터미널도착일도착시간
353405090942018-08-0312:17:34292018-08-0312:28:42
7666656021542018-08-0617:47:17922018-08-0617:52:43
21847206422018-08-0107:57:25422018-08-0107:57:51
7453776082192018-08-0615:33:042192018-08-0615:33:08
2375877921482018-08-0217:16:42422018-08-0217:21:44
155388286282018-08-0123:22:46522018-08-0123:27:13
4937951561402018-08-0412:41:46602018-08-0412:59:32
806026097592018-08-0621:57:231422018-08-0622:02:03
7270171502632018-08-0612:40:442412018-08-0612:44:04
2785468472382018-08-0220:49:241982018-08-0220:56:50