Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows48
Duplicate rows (%)0.5%
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 05:00:00부터 익일 04:59:59까지의 데이터를 추축 - 기간: 2020년 1월부터 2021년 12월 까지
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/1204

Alerts

Dataset has 48 (0.5%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 20:05:08.726016
Analysis finished2023-12-11 20:05:10.430820
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct967
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:05:10.553015image/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

Unique99 ?
Unique (%)1.0%

Sample

1st row461002d5
2nd row461000ec
3rd row461012f1
4th row461011fa
5th row46101244
ValueCountFrequency (%)
461002db 386
 
3.9%
461012cf 347
 
3.5%
461002e3 321
 
3.2%
461006ed 307
 
3.1%
461006da 280
 
2.8%
4610078d 273
 
2.7%
46100283 257
 
2.6%
461000ec 252
 
2.5%
461002d7 208
 
2.1%
461002e1 205
 
2.1%
Other values (957) 7164
71.6%
2023-12-12T05:05:10.869545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18094
22.6%
1 15741
19.7%
6 11802
14.8%
4 11781
14.7%
2 3526
 
4.4%
d 2660
 
3.3%
3 2542
 
3.2%
8 2233
 
2.8%
7 2013
 
2.5%
e 1807
 
2.3%
Other values (6) 7801
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70460
88.1%
Lowercase Letter 9540
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18094
25.7%
1 15741
22.3%
6 11802
16.7%
4 11781
16.7%
2 3526
 
5.0%
3 2542
 
3.6%
8 2233
 
3.2%
7 2013
 
2.9%
5 1549
 
2.2%
9 1179
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
d 2660
27.9%
e 1807
18.9%
c 1471
15.4%
b 1347
14.1%
f 1191
12.5%
a 1064
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
Common 70460
88.1%
Latin 9540
 
11.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18094
25.7%
1 15741
22.3%
6 11802
16.7%
4 11781
16.7%
2 3526
 
5.0%
3 2542
 
3.6%
8 2233
 
3.2%
7 2013
 
2.9%
5 1549
 
2.2%
9 1179
 
1.7%
Latin
ValueCountFrequency (%)
d 2660
27.9%
e 1807
18.9%
c 1471
15.4%
b 1347
14.1%
f 1191
12.5%
a 1064
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18094
22.6%
1 15741
19.7%
6 11802
14.8%
4 11781
14.7%
2 3526
 
4.4%
d 2660
 
3.3%
3 2542
 
3.2%
8 2233
 
2.8%
7 2013
 
2.5%
e 1807
 
2.3%
Other values (6) 7801
9.8%

collection_dt
Real number (ℝ)

Distinct7773
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0210814 × 1016
Minimum2.0210814 × 1016
Maximum2.0210814 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:11.005198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210814 × 1016
5-th percentile2.0210814 × 1016
Q12.0210814 × 1016
median2.0210814 × 1016
Q32.0210814 × 1016
95-th percentile2.0210814 × 1016
Maximum2.0210814 × 1016
Range8313386
Interquartile range (IQR)5954016

Descriptive statistics

Standard deviation2811871.5
Coefficient of variation (CV)1.3912708 × 10-10
Kurtosis-1.0169841
Mean2.0210814 × 1016
Median Absolute Deviation (MAD)1100668
Skewness0.80942396
Sum-8.0604315 × 1017
Variance7.9066213 × 1012
MonotonicityNot monotonic
2023-12-12T05:05:11.115619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210814165630406 7
 
0.1%
20210814164000345 6
 
0.1%
20210814164100894 6
 
0.1%
20210814164230734 6
 
0.1%
20210814163130739 6
 
0.1%
20210814171000431 6
 
0.1%
20210814163130583 6
 
0.1%
20210814163930305 6
 
0.1%
20210814164700407 6
 
0.1%
20210814165330602 6
 
0.1%
Other values (7763) 9939
99.4%
ValueCountFrequency (%)
20210814162935346 1
< 0.1%
20210814162936049 1
< 0.1%
20210814162937393 1
< 0.1%
20210814162937596 1
< 0.1%
20210814162939566 1
< 0.1%
20210814162940456 1
< 0.1%
20210814162941160 1
< 0.1%
20210814162941785 1
< 0.1%
20210814162942051 1
< 0.1%
20210814162942191 1
< 0.1%
ValueCountFrequency (%)
20210814171248732 1
< 0.1%
20210814171248561 1
< 0.1%
20210814171247545 1
< 0.1%
20210814171247029 1
< 0.1%
20210814171246888 1
< 0.1%
20210814171245982 1
< 0.1%
20210814171244309 1
< 0.1%
20210814171244059 1
< 0.1%
20210814171243293 1
< 0.1%
20210814171243043 1
< 0.1%

longitude
Real number (ℝ)

Distinct8671
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.72513
Minimum126.16325
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:11.222849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16325
5-th percentile126.27732
Q1126.37245
median126.49205
Q3126.62902
95-th percentile126.91796
Maximum180
Range53.836754
Interquartile range (IQR)0.25656175

Descriptive statistics

Standard deviation10.671155
Coefficient of variation (CV)0.082898772
Kurtosis19.138263
Mean128.72513
Median Absolute Deviation (MAD)0.1231525
Skewness4.5965091
Sum1287251.3
Variance113.87355
MonotonicityNot monotonic
2023-12-12T05:05:11.361465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 415
 
4.2%
126.492055 33
 
0.3%
126.492057 28
 
0.3%
126.492054 27
 
0.3%
126.492058 20
 
0.2%
126.492053 15
 
0.1%
126.492056 15
 
0.1%
126.49205 13
 
0.1%
126.49206 12
 
0.1%
126.492059 12
 
0.1%
Other values (8661) 9410
94.1%
ValueCountFrequency (%)
126.163246 1
< 0.1%
126.163305 1
< 0.1%
126.163316 1
< 0.1%
126.16436 1
< 0.1%
126.164577 1
< 0.1%
126.166522 1
< 0.1%
126.166863 1
< 0.1%
126.167018 1
< 0.1%
126.167397 1
< 0.1%
126.167442 1
< 0.1%
ValueCountFrequency (%)
180.0000001 415
4.2%
129.162782 1
 
< 0.1%
129.161926 1
 
< 0.1%
129.159378 1
 
< 0.1%
128.053044 1
 
< 0.1%
126.936004 1
 
< 0.1%
126.935827 1
 
< 0.1%
126.935731 1
 
< 0.1%
126.935624 1
 
< 0.1%
126.93562 2
 
< 0.1%

latitude
Real number (ℝ)

Distinct8550
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.760998
Minimum33.200868
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:11.498112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200868
5-th percentile33.245657
Q133.337223
median33.450662
Q333.495889
95-th percentile33.553283
Maximum90
Range56.799132
Interquartile range (IQR)0.158666

Descriptive statistics

Standard deviation11.287009
Coefficient of variation (CV)0.31562344
Kurtosis19.146309
Mean35.760998
Median Absolute Deviation (MAD)0.0568435
Skewness4.597876
Sum357609.98
Variance127.39658
MonotonicityNot monotonic
2023-12-12T05:05:11.618314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 415
 
4.2%
33.495889 26
 
0.3%
33.495898 19
 
0.2%
33.495888 17
 
0.2%
33.495896 17
 
0.2%
33.495899 16
 
0.2%
33.495897 16
 
0.2%
33.495895 16
 
0.2%
33.49589 14
 
0.1%
33.249952 14
 
0.1%
Other values (8540) 9430
94.3%
ValueCountFrequency (%)
33.200868 1
< 0.1%
33.206064 1
< 0.1%
33.20784 1
< 0.1%
33.208992 1
< 0.1%
33.209736 1
< 0.1%
33.21032 1
< 0.1%
33.211269 1
< 0.1%
33.211341 1
< 0.1%
33.212612 1
< 0.1%
33.212648 1
< 0.1%
ValueCountFrequency (%)
90.0000001 415
4.2%
35.166415 1
 
< 0.1%
35.165247 1
 
< 0.1%
35.162762 1
 
< 0.1%
34.769787 1
 
< 0.1%
33.564069 1
 
< 0.1%
33.560557 1
 
< 0.1%
33.560554 1
 
< 0.1%
33.560551 1
 
< 0.1%
33.560547 1
 
< 0.1%

Interactions

2023-12-12T05:05:10.017292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.085282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.635951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:10.108070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.460286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.730728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:10.198151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.543069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:09.860696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:05:11.705847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
collection_dtlongitudelatitude
collection_dt1.0000.0490.049
longitude0.0491.0001.000
latitude0.0491.0001.000
2023-12-12T05:05:11.786180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/