Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory585.9 KiB
Average record size in memory60.0 B

Variable types

Text1
Numeric4
DateTime1

Dataset

Description- 월별 토요일의 렌터카 체류 거점 위치정보 입니다. - 체류 거점은 수집시간 전로그와 후로그의 시각차이가 20분 이상인 경우, 전로그의 위치를 의미합니다. - 기간: 2020년 1월부터 2021년 12월 까지
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/1208

Reproduction

Analysis started2023-12-11 20:03:44.443646
Analysis finished2023-12-11 20:03:47.227907
Duration2.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct1531
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:03:47.497494image/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

Unique53 ?
Unique (%)0.5%

Sample

1st row461007de
2nd row461000b5
3rd row46101812
4th row46100538
5th row46101229
ValueCountFrequency (%)
461005ba 16
 
0.2%
46100525 16
 
0.2%
461005ac 16
 
0.2%
46100138 15
 
0.1%
46100438 15
 
0.1%
46101312 15
 
0.1%
461018e4 14
 
0.1%
4610194a 14
 
0.1%
4610129a 14
 
0.1%
4610054d 14
 
0.1%
Other values (1521) 9851
98.5%
2023-12-12T05:03:48.007693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18235
22.8%
0 17042
21.3%
4 11863
14.8%
6 11708
14.6%
2 2579
 
3.2%
7 2420
 
3.0%
8 2394
 
3.0%
3 2205
 
2.8%
5 1941
 
2.4%
9 1803
 
2.3%
Other values (6) 7810
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72190
90.2%
Lowercase Letter 7810
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18235
25.3%
0 17042
23.6%
4 11863
16.4%
6 11708
16.2%
2 2579
 
3.6%
7 2420
 
3.4%
8 2394
 
3.3%
3 2205
 
3.1%
5 1941
 
2.7%
9 1803
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
f 1520
19.5%
b 1405
18.0%
a 1328
17.0%
c 1237
15.8%
e 1179
15.1%
d 1141
14.6%

Most occurring scripts

ValueCountFrequency (%)
Common 72190
90.2%
Latin 7810
 
9.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18235
25.3%
0 17042
23.6%
4 11863
16.4%
6 11708
16.2%
2 2579
 
3.6%
7 2420
 
3.4%
8 2394
 
3.3%
3 2205
 
3.1%
5 1941
 
2.7%
9 1803
 
2.5%
Latin
ValueCountFrequency (%)
f 1520
19.5%
b 1405
18.0%
a 1328
17.0%
c 1237
15.8%
e 1179
15.1%
d 1141
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18235
22.8%
0 17042
21.3%
4 11863
14.8%
6 11708
14.6%
2 2579
 
3.2%
7 2420
 
3.0%
8 2394
 
3.0%
3 2205
 
2.8%
5 1941
 
2.4%
9 1803
 
2.3%
Other values (6) 7810
9.8%

collection_dt
Real number (ℝ)

Distinct5329
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0211213 × 1013
Minimum2.0211204 × 1013
Maximum2.0211225 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:03:48.251554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0211204 × 1013
5-th percentile2.0211204 × 1013
Q12.0211204 × 1013
median2.0211211 × 1013
Q32.0211218 × 1013
95-th percentile2.0211225 × 1013
Maximum2.0211225 × 1013
Range21169370
Interquartile range (IQR)13960218

Descriptive statistics

Standard deviation7860465.8
Coefficient of variation (CV)3.8891607 × 10-7
Kurtosis-1.287803
Mean2.0211213 × 1013
Median Absolute Deviation (MAD)6980200
Skewness0.29361435
Sum2.0211213 × 1017
Variance6.1786922 × 1013
MonotonicityNot monotonic
2023-12-12T05:03:48.460421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211204164530 8
 
0.1%
20211218145000 7
 
0.1%
20211211124530 7
 
0.1%
20211225161830 7
 
0.1%
20211204103330 7
 
0.1%
20211218132130 7
 
0.1%
20211218144030 7
 
0.1%
20211225155930 7
 
0.1%
20211225132700 7
 
0.1%
20211204112430 7
 
0.1%
Other values (5319) 9929
99.3%
ValueCountFrequency (%)
20211204055030 1
< 0.1%
20211204055930 1
< 0.1%
20211204060600 1
< 0.1%
20211204060730 1
< 0.1%
20211204060900 1
< 0.1%
20211204061030 1
< 0.1%
20211204061630 1
< 0.1%
20211204061700 1
< 0.1%
20211204062830 1
< 0.1%
20211204063030 1
< 0.1%
ValueCountFrequency (%)
20211225224400 1
< 0.1%
20211225220230 1
< 0.1%
20211225215930 1
< 0.1%
20211225215400 1
< 0.1%
20211225214430 1
< 0.1%
20211225213300 1
< 0.1%
20211225211430 1
< 0.1%
20211225205330 1
< 0.1%
20211225205030 1
< 0.1%
20211225204530 1
< 0.1%

longitude
Real number (ℝ)

Distinct9771
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.52939
Minimum126.16375
Maximum129.25619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:03:48.639285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16375
5-th percentile126.2557
Q1126.39256
median126.49999
Q3126.62287
95-th percentile126.91743
Maximum129.25619
Range3.092439
Interquartile range (IQR)0.230307

Descriptive statistics

Standard deviation0.21613185
Coefficient of variation (CV)0.0017081553
Kurtosis34.322359
Mean126.52939
Median Absolute Deviation (MAD)0.114893
Skewness3.331683
Sum1265293.9
Variance0.046712976
MonotonicityNot monotonic
2023-12-12T05:03:48.852589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.505608 3
 
< 0.1%
126.93575 3
 
< 0.1%
126.500546 3
 
< 0.1%
126.506514 3
 
< 0.1%
126.482504 3
 
< 0.1%
126.500542 3
 
< 0.1%
126.304019 2
 
< 0.1%
126.312118 2
 
< 0.1%
126.935154 2
 
< 0.1%
126.507664 2
 
< 0.1%
Other values (9761) 9974
99.7%
ValueCountFrequency (%)
126.163748 1
< 0.1%
126.163954 1
< 0.1%
126.163972 1
< 0.1%
126.164344 1
< 0.1%
126.164353 1
< 0.1%
126.164398 1
< 0.1%
126.164437 1
< 0.1%
126.165368 1
< 0.1%
126.165681 1
< 0.1%
126.165728 1
< 0.1%
ValueCountFrequency (%)
129.256187 1
< 0.1%
129.234385 1
< 0.1%
129.233981 1
< 0.1%
129.228164 1
< 0.1%
129.22099 1
< 0.1%
129.220628 1
< 0.1%
129.185311 1
< 0.1%
129.174454 1
< 0.1%
129.164684 1
< 0.1%
129.159703 1
< 0.1%

latitude
Real number (ℝ)

Distinct9567
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.411793
Minimum33.200051
Maximum35.958964
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:03:49.043594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200051
5-th percentile33.240013
Q133.29142
median33.452169
Q333.49674
95-th percentile33.531654
Maximum35.958964
Range2.758913
Interquartile range (IQR)0.20532025

Descriptive statistics

Standard deviation0.14113581
Coefficient of variation (CV)0.0042241317
Kurtosis88.097588
Mean33.411793
Median Absolute Deviation (MAD)0.060434
Skewness5.8688201
Sum334117.93
Variance0.019919317
MonotonicityNot monotonic
2023-12-12T05:03:49.223500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.496541 3
 
< 0.1%
33.508573 3
 
< 0.1%
33.502896 3
 
< 0.1%
33.518068 3
 
< 0.1%
33.49661 3
 
< 0.1%
33.502979 3
 
< 0.1%
33.250114 3
 
< 0.1%
33.29142 3
 
< 0.1%
33.496543 3
 
< 0.1%
33.489462 3
 
< 0.1%
Other values (9557) 9970
99.7%
ValueCountFrequency (%)
33.200051 1
< 0.1%
33.200057 1
< 0.1%
33.200124 1
< 0.1%
33.200137 1
< 0.1%
33.204111 1
< 0.1%
33.2043 1
< 0.1%
33.204492 1
< 0.1%
33.204604 1
< 0.1%
33.204751 1
< 0.1%
33.20507 1
< 0.1%
ValueCountFrequency (%)
35.958964 1
< 0.1%
35.862551 1
< 0.1%
35.833154 1
< 0.1%
35.8255971 1
< 0.1%
35.7941751 1
< 0.1%
35.7933924 1
< 0.1%
35.258562 1
< 0.1%
35.257941 1
< 0.1%
35.243426 1
< 0.1%
35.18984 1
< 0.1%

time
Date

Distinct5329
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-12-04 05:50:30
Maximum2021-12-25 22:44:00
2023-12-12T05:03:49.432516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:49.647876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Diff
Real number (ℝ)

Distinct6258
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107109.43
Minimum1200
Maximum1812806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:03:49.856031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1471.9
Q12491
median3886
Q39081
95-th percentile587580.25
Maximum1812806
Range1811606
Interquartile range (IQR)6590

Descriptive statistics

Standard deviation239342.07
Coefficient of variation (CV)2.2345564
Kurtosis6.2296141
Mean107109.43
Median Absolute Deviation (MAD)1843.5
Skewness2.3812597
Sum1.0710943 × 109
Variance5.7284624 × 1010
MonotonicityNot monotonic
2023-12-12T05:03:50.345655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2910 22
 
0.2%
1650 21
 
0.2%
2250 21
 
0.2%
2850 20
 
0.2%
2070 18
 
0.2%
3090 18
 
0.2%
2520 17
 
0.2%
2400 17
 
0.2%
1470 17
 
0.2%
1590 17
 
0.2%
Other values (6248) 9812
98.1%
ValueCountFrequency (%)
1200 8
0.1%
1201 3
 
< 0.1%
1202 2
 
< 0.1%
1203 2
 
< 0.1%
1204 4
< 0.1%
1205 2
 
< 0.1%
1208 2
 
< 0.1%
1209 1
 
< 0.1%
1211 1
 
< 0.1%
1212 3
 
< 0.1%
ValueCountFrequency (%)
1812806 1
< 0.1%
1806916 1
< 0.1%
1800570 1
< 0.1%
1800125 1
< 0.1%
1797060 1
< 0.1%
1797029 1
< 0.1%
1790562 1
< 0.1%
1790010 1
< 0.1%
1782361 1
< 0.1%
1782094 1
< 0.1%

Interactions

2023-12-12T05:03:46.521618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.134975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.574634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.061947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.621776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.232114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.685127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.189644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.744846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.344207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.791347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.323116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.877877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.449592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:45.919420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:03:46.416917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:03:50.456472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
collection_dtlongitudelatitudeDiff
collection_dt1.0000.0630.0150.201
longitude0.0631.0000.8350.018
latitude0.0150.8351.0000.067
Diff0.2010.0180.0671.000
2023-12-12T05:03:50.567458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
collection_dtlongitudelatitudeDiff
collection_dt1.000-0.007-0.020-0.021
longitude-0.0071.0000.2850.004
latitude-0.0200.2851.0000.045
Diff-0.0210.0040.0451.000

Missing values

2023-12-12T05:03:47.058340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:03:47.178257image/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

oidcollection_dtlongitudelatitudetimeDiff
9144461007de20211225095330126.77848833.4435642021-12-25 09:53:307304
96461000b520211218161508126.49613433.5039042021-12-18 16:15:08585534
194084610181220211211102130126.3094733.4639312021-12-11 10:21:304526
56524610053820211218144100126.42501333.241992021-12-18 14:41:00592089
156444610122920211211123230126.5207133.5135652021-12-11 12:32:302642
182684610179a20211218122900126.56553833.2476732021-12-18 12:29:004140
176824610135720211225151230126.3975433.4820672021-12-25 15:12:302906
137214610116420211225125330126.66828333.5439782021-12-25 12:53:303861
136794610116120211204181300126.483633.4967182021-12-04 18:13:00563949
13664610020020211211150600126.24748833.3996382021-12-11 15:06:003983
oidcollection_dtlongitudelatitudetimeDiff
73534610064320211204163430126.57343733.2667022021-12-04 16:34:301740
4983461004ac20211218121500126.42236933.4357032021-12-18 12:15:002938
197334610182c20211225141900126.63375133.3095032021-12-25 14:19:007020
28334610033e20211211131030126.79259833.3907462021-12-11 13:10:302656
219244610193d20211225160200126.526433.5115962021-12-25 16:02:001811
221284610195520211211115900126.52610233.5107792021-12-11 11:59:004290
6154610013d20211225112700126.33352433.2411262021-12-25 11:27:002655
173164610131220211211162830126.36508133.4100392021-12-11 16:28:301708
216064610191520211204191200126.26444933.4100772021-12-04 19:12:001348
2268461002b120211225133130126.32690433.4659972021-12-25 13:31:305100