Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows66
Duplicate rows (%)0.7%
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 66 (0.7%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 19:50:47.954913
Analysis finished2023-12-11 19:50:50.153600
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct927
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T04:50:50.479920image/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

Unique88 ?
Unique (%)0.9%

Sample

1st row461006dd
2nd row461004fc
3rd row4610072b
4th row4610037c
5th row46100bfa
ValueCountFrequency (%)
0c0000fd 121
 
1.2%
46100bd8 54
 
0.5%
461002a5 48
 
0.5%
46100bfa 42
 
0.4%
46100311 42
 
0.4%
4610054e 41
 
0.4%
461000e2 41
 
0.4%
46100472 40
 
0.4%
46100371 38
 
0.4%
461004fb 38
 
0.4%
Other values (917) 9495
95.0%
2023-12-12T04:50:51.126324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22475
28.1%
4 12582
15.7%
1 12459
15.6%
6 12030
15.0%
5 2554
 
3.2%
7 2476
 
3.1%
3 2446
 
3.1%
2 2116
 
2.6%
c 1552
 
1.9%
b 1476
 
1.8%
Other values (6) 7834
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71522
89.4%
Lowercase Letter 8478
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22475
31.4%
4 12582
17.6%
1 12459
17.4%
6 12030
16.8%
5 2554
 
3.6%
7 2476
 
3.5%
3 2446
 
3.4%
2 2116
 
3.0%
8 1215
 
1.7%
9 1169
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
c 1552
18.3%
b 1476
17.4%
d 1457
17.2%
e 1450
17.1%
f 1409
16.6%
a 1134
13.4%

Most occurring scripts

ValueCountFrequency (%)
Common 71522
89.4%
Latin 8478
 
10.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22475
31.4%
4 12582
17.6%
1 12459
17.4%
6 12030
16.8%
5 2554
 
3.6%
7 2476
 
3.5%
3 2446
 
3.4%
2 2116
 
3.0%
8 1215
 
1.7%
9 1169
 
1.6%
Latin
ValueCountFrequency (%)
c 1552
18.3%
b 1476
17.4%
d 1457
17.2%
e 1450
17.1%
f 1409
16.6%
a 1134
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22475
28.1%
4 12582
15.7%
1 12459
15.6%
6 12030
15.0%
5 2554
 
3.2%
7 2476
 
3.1%
3 2446
 
3.1%
2 2116
 
2.6%
c 1552
 
1.9%
b 1476
 
1.8%
Other values (6) 7834
 
9.8%

collection_dt
Real number (ℝ)

Distinct6940
Distinct (%)69.4%
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
2023-12-12T04:50:51.312207image/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
Range62752000
Interquartile range (IQR)17570000

Descriptive statistics

Standard deviation12699842
Coefficient of variation (CV)6.2870139 × 10-10
Kurtosis0.92168123
Mean2.0200118 × 1016
Median Absolute Deviation (MAD)8456500
Skewness-1.1372291
Sum-9.1300382 × 1017
Variance1.6128599 × 1014
MonotonicityNot monotonic
2023-12-12T04:50:51.477867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200118113103000 6
 
0.1%
20200118111746000 6
 
0.1%
20200118102920000 6
 
0.1%
20200118112909000 6
 
0.1%
20200118102829000 6
 
0.1%
20200118113139000 6
 
0.1%
20200118110555000 6
 
0.1%
20200118092651000 5
 
0.1%
20200118112152000 5
 
0.1%
20200118102314000 5
 
0.1%
Other values (6930) 9943
99.4%
ValueCountFrequency (%)
20200118051450000 1
< 0.1%
20200118051650000 1
< 0.1%
20200118051733000 1
< 0.1%
20200118051750000 1
< 0.1%
20200118051817000 1
< 0.1%
20200118052520000 1
< 0.1%
20200118052917000 1
< 0.1%
20200118053220000 1
< 0.1%
20200118053347000 1
< 0.1%
20200118053350000 1
< 0.1%
ValueCountFrequency (%)
20200118114202000 1
 
< 0.1%
20200118114157000 3
< 0.1%
20200118114156000 2
 
< 0.1%
20200118114154000 5
0.1%
20200118114152000 2
 
< 0.1%
20200118114151000 3
< 0.1%
20200118114150000 3
< 0.1%
20200118114149000 1
 
< 0.1%
20200118114148000 2
 
< 0.1%
20200118114147000 2
 
< 0.1%

longitude
Real number (ℝ)

Distinct9396
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.17389
Minimum126.16401
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:50:51.723044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16401
5-th percentile126.28446
Q1126.45656
median126.5066
Q3126.65284
95-th percentile126.95192
Maximum180
Range53.835994
Interquartile range (IQR)0.19627935

Descriptive statistics

Standard deviation11.575867
Coefficient of variation (CV)0.089614599
Kurtosis15.336858
Mean129.17389
Median Absolute Deviation (MAD)0.0897269
Skewness4.1628785
Sum1291738.9
Variance134.00069
MonotonicityNot monotonic
2023-12-12T04:50:51.960039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 493
 
4.9%
126.4915098 3
 
< 0.1%
126.496911 3
 
< 0.1%
126.506749 3
 
< 0.1%
126.455959 2
 
< 0.1%
126.502975 2
 
< 0.1%
126.4860846 2
 
< 0.1%
126.4565981 2
 
< 0.1%
126.4818238 2
 
< 0.1%
126.4953551 2
 
< 0.1%
Other values (9386) 9486
94.9%
ValueCountFrequency (%)
126.1640064 1
< 0.1%
126.1643078 1
< 0.1%
126.1646206 1
< 0.1%
126.1650428 1
< 0.1%
126.16572 1
< 0.1%
126.1665078 1
< 0.1%
126.1669915 1
< 0.1%
126.1670883 1
< 0.1%
126.167961 1
< 0.1%
126.1686236 1
< 0.1%
ValueCountFrequency (%)
180.0000001 493
4.9%
126.9686495 1
 
< 0.1%
126.9670076 1
 
< 0.1%
126.960565 1
 
< 0.1%
126.9566335 1
 
< 0.1%
126.9539566 1
 
< 0.1%
126.953672 1
 
< 0.1%
126.9535479 1
 
< 0.1%
126.9518376 1
 
< 0.1%
126.9515148 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct9355
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.209173
Minimum33.199174
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:50:52.177958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.199174
5-th percentile33.248996
Q133.337729
median33.470635
Q333.500739
95-th percentile33.562119
Maximum90
Range56.800826
Interquartile range (IQR)0.16300997

Descriptive statistics

Standard deviation12.250265
Coefficient of variation (CV)0.33831937
Kurtosis15.341789
Mean36.209173
Median Absolute Deviation (MAD)0.0441956
Skewness4.1638156
Sum362091.73
Variance150.06898
MonotonicityNot monotonic
2023-12-12T04:50:52.388806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 493
 
4.9%
33.493752 4
 
< 0.1%
33.4933933 3
 
< 0.1%
33.420337 2
 
< 0.1%
33.4021986 2
 
< 0.1%
33.4937428 2
 
< 0.1%
33.4971943 2
 
< 0.1%
33.4982653 2
 
< 0.1%
33.4713835 2
 
< 0.1%
33.4648786 2
 
< 0.1%
Other values (9345) 9486
94.9%
ValueCountFrequency (%)
33.199174 1
< 0.1%
33.201026 1
< 0.1%
33.2013951 1
< 0.1%
33.2046348 1
< 0.1%
33.2074983 1
< 0.1%
33.209639 1
< 0.1%
33.2104273 1
< 0.1%
33.2112263 1
< 0.1%
33.2118378 1
< 0.1%
33.2141788 1
< 0.1%
ValueCountFrequency (%)
90.0000001 493
4.9%
33.5645285 1
 
< 0.1%
33.5645066 1
 
< 0.1%
33.5641114 1
 
< 0.1%
33.5638285 1
 
< 0.1%
33.5633854 1
 
< 0.1%
33.563209 1
 
< 0.1%
33.5629233 1
 
< 0.1%
33.5620766 1
 
< 0.1%
33.5615905 1
 
< 0.1%

Interactions

2023-12-12T04:50:49.461684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:48.488533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:48.978169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:49.627176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:48.657083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:49.145019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:50:49.784163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/