Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows60
Duplicate rows (%)0.6%
Total size in memory419.9 KiB
Average record size in memory43.0 B

Variable types

Text1
Numeric3

Dataset

Description- 월별 토요일의 렌터카 위치 정보 입니다. - 수집시각 기준 당일 05:00:00 부터 익일 04:59:59까지의 데이터를 추출 - 기간: 2020년 1월부터 2021년 12월 까지
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/1201

Alerts

Dataset has 60 (0.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 19:50:58.176648
Analysis finished2023-12-11 19:51:00.319043
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct936
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T04:51:00.579982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters80000
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)0.7%

Sample

1st row46100172
2nd row4610054e
3rd row461001a1
4th row461000b6
5th row4610014a
ValueCountFrequency (%)
0c0000fd 121
 
1.2%
46100311 42
 
0.4%
4610008c 42
 
0.4%
46100371 42
 
0.4%
461000e2 40
 
0.4%
461001a2 39
 
0.4%
461002a5 39
 
0.4%
46100bfa 38
 
0.4%
4610063c 37
 
0.4%
46100347 37
 
0.4%
Other values (926) 9523
95.2%
2023-12-12T04:51:01.091228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22363
28.0%
4 12632
15.8%
1 12503
15.6%
6 12040
15.0%
3 2605
 
3.3%
5 2548
 
3.2%
7 2472
 
3.1%
2 2016
 
2.5%
c 1584
 
2.0%
b 1499
 
1.9%
Other values (6) 7738
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71594
89.5%
Lowercase Letter 8406
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22363
31.2%
4 12632
17.6%
1 12503
17.5%
6 12040
16.8%
3 2605
 
3.6%
5 2548
 
3.6%
7 2472
 
3.5%
2 2016
 
2.8%
9 1247
 
1.7%
8 1168
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
c 1584
18.8%
b 1499
17.8%
d 1471
17.5%
e 1422
16.9%
f 1359
16.2%
a 1071
12.7%

Most occurring scripts

ValueCountFrequency (%)
Common 71594
89.5%
Latin 8406
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22363
31.2%
4 12632
17.6%
1 12503
17.5%
6 12040
16.8%
3 2605
 
3.6%
5 2548
 
3.6%
7 2472
 
3.5%
2 2016
 
2.8%
9 1247
 
1.7%
8 1168
 
1.6%
Latin
ValueCountFrequency (%)
c 1584
18.8%
b 1499
17.8%
d 1471
17.5%
e 1422
16.9%
f 1359
16.2%
a 1071
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22363
28.0%
4 12632
15.8%
1 12503
15.6%
6 12040
15.0%
3 2605
 
3.3%
5 2548
 
3.2%
7 2472
 
3.1%
2 2016
 
2.5%
c 1584
 
2.0%
b 1499
 
1.9%
Other values (6) 7738
 
9.7%

collection_dt
Real number (ℝ)

Distinct6979
Distinct (%)69.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0200118 × 1016
Minimum2.0200118 × 1016
Maximum2.0200118 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:51:01.260604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0200118 × 1016
5-th percentile2.0200118 × 1016
Q12.0200118 × 1016
median2.0200118 × 1016
Q32.0200118 × 1016
95-th percentile2.0200118 × 1016
Maximum2.0200118 × 1016
Range62353000
Interquartile range (IQR)17524748

Descriptive statistics

Standard deviation12775215
Coefficient of variation (CV)6.3243268 × 10-10
Kurtosis0.96102549
Mean2.0200118 × 1016
Median Absolute Deviation (MAD)8484000
Skewness-1.1431327
Sum-9.1300382 × 1017
Variance1.6320612 × 1014
MonotonicityNot monotonic
2023-12-12T04:51:01.431517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200118110432000 6
 
0.1%
20200118114001000 6
 
0.1%
20200118102008000 6
 
0.1%
20200118112213000 6
 
0.1%
20200118110559000 6
 
0.1%
20200118101854000 5
 
0.1%
20200118104251000 5
 
0.1%
20200118103746000 5
 
0.1%
20200118114003000 5
 
0.1%
20200118112117000 5
 
0.1%
Other values (6969) 9945
99.5%
ValueCountFrequency (%)
20200118051850000 1
< 0.1%
20200118052017000 1
< 0.1%
20200118052020000 1
< 0.1%
20200118052217000 1
< 0.1%
20200118052320000 1
< 0.1%
20200118052517000 1
< 0.1%
20200118052547000 1
< 0.1%
20200118052720000 1
< 0.1%
20200118052906000 1
< 0.1%
20200118052947000 1
< 0.1%
ValueCountFrequency (%)
20200118114203000 1
 
< 0.1%
20200118114201000 2
< 0.1%
20200118114159000 3
< 0.1%
20200118114157000 2
< 0.1%
20200118114155000 1
 
< 0.1%
20200118114154000 3
< 0.1%
20200118114153000 1
 
< 0.1%
20200118114150000 1
 
< 0.1%
20200118114148000 1
 
< 0.1%
20200118114147000 1
 
< 0.1%

longitude
Real number (ℝ)

Distinct9375
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.33665
Minimum126.1629
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:51:01.626385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.1629
5-th percentile126.28582
Q1126.45667
median126.50703
Q3126.66226
95-th percentile180
Maximum180
Range53.837096
Interquartile range (IQR)0.2055849

Descriptive statistics

Standard deviation11.903448
Coefficient of variation (CV)0.092034611
Kurtosis14.176796
Mean129.33665
Median Absolute Deviation (MAD)0.0927141
Skewness4.0212062
Sum1293366.5
Variance141.69207
MonotonicityNot monotonic
2023-12-12T04:51:01.798055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 523
 
5.2%
126.4969756 2
 
< 0.1%
126.3192988 2
 
< 0.1%
126.4865058 2
 
< 0.1%
126.305087 2
 
< 0.1%
126.4933493 2
 
< 0.1%
126.4918316 2
 
< 0.1%
126.4933665 2
 
< 0.1%
126.491628 2
 
< 0.1%
126.666205 2
 
< 0.1%
Other values (9365) 9459
94.6%
ValueCountFrequency (%)
126.162904 1
< 0.1%
126.1642704 1
< 0.1%
126.1643186 1
< 0.1%
126.1643356 1
< 0.1%
126.1644595 1
< 0.1%
126.1650996 1
< 0.1%
126.1653914 1
< 0.1%
126.1663898 1
< 0.1%
126.1668276 1
< 0.1%
126.1670976 1
< 0.1%
ValueCountFrequency (%)
180.0000001 523
5.2%
126.9701123 1
 
< 0.1%
126.9694733 1
 
< 0.1%
126.9686085 1
 
< 0.1%
126.9626185 1
 
< 0.1%
126.9605633 1
 
< 0.1%
126.9605591 1
 
< 0.1%
126.9605576 1
 
< 0.1%
126.9578381 1
 
< 0.1%
126.9537976 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct9326
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.381234
Minimum33.200212
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:51:01.947429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200212
5-th percentile33.249684
Q133.345456
median33.470917
Q333.501183
95-th percentile90
Maximum90
Range56.799788
Interquartile range (IQR)0.15572718

Descriptive statistics

Standard deviation12.596982
Coefficient of variation (CV)0.34624944
Kurtosis14.181367
Mean36.381234
Median Absolute Deviation (MAD)0.0426366
Skewness4.022109
Sum363812.34
Variance158.68395
MonotonicityNot monotonic
2023-12-12T04:51:02.101952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 523
 
5.2%
33.4938694 4
 
< 0.1%
33.4958759 3
 
< 0.1%
33.500185 3
 
< 0.1%
33.4937548 3
 
< 0.1%
33.4447256 2
 
< 0.1%
33.4458955 2
 
< 0.1%
33.2500853 2
 
< 0.1%
33.4954386 2
 
< 0.1%
33.4937443 2
 
< 0.1%
Other values (9316) 9454
94.5%
ValueCountFrequency (%)
33.2002118 1
< 0.1%
33.200636 1
< 0.1%
33.2008498 1
< 0.1%
33.2038711 1
< 0.1%
33.2041641 1
< 0.1%
33.2059753 1
< 0.1%
33.2062523 1
< 0.1%
33.2063196 1
< 0.1%
33.2075818 1
< 0.1%
33.2097326 1
< 0.1%
ValueCountFrequency (%)
90.0000001 523
5.2%
33.5647403 1
 
< 0.1%
33.563904 1
 
< 0.1%
33.563124 1
 
< 0.1%
33.5628156 1
 
< 0.1%
33.5614931 1
 
< 0.1%
33.5612836 1
 
< 0.1%
33.5611346 1
 
< 0.1%
33.5610456 1
 
< 0.1%
33.561045 1
 
< 0.1%

Interactions

2023-12-12T04:50:59.359169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:58.592004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:58.974818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:59.480262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:58.714585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:59.116264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:59.605590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/