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 20:05:13.807066
Analysis finished2023-12-11 20:05:15.427235
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct1011
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:05:15.749657image/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

Unique118 ?
Unique (%)1.2%

Sample

1st row461012cf
2nd row46100ff1
3rd row46101247
4th row461012f9
5th row4610053e
ValueCountFrequency (%)
461002e3 389
 
3.9%
461006ba 366
 
3.7%
46101334 326
 
3.3%
461012cf 298
 
3.0%
46100283 278
 
2.8%
46100103 278
 
2.8%
461007cc 223
 
2.2%
4610078d 198
 
2.0%
461000e4 184
 
1.8%
461006c9 169
 
1.7%
Other values (1001) 7291
72.9%
2023-12-12T05:05:16.338187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18212
22.8%
1 16064
20.1%
6 12106
15.1%
4 11816
14.8%
3 3241
 
4.1%
2 3017
 
3.8%
7 2508
 
3.1%
8 2066
 
2.6%
c 1703
 
2.1%
e 1678
 
2.1%
Other values (6) 7589
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71748
89.7%
Lowercase Letter 8252
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18212
25.4%
1 16064
22.4%
6 12106
16.9%
4 11816
16.5%
3 3241
 
4.5%
2 3017
 
4.2%
7 2508
 
3.5%
8 2066
 
2.9%
5 1371
 
1.9%
9 1347
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
c 1703
20.6%
e 1678
20.3%
d 1293
15.7%
f 1290
15.6%
a 1148
13.9%
b 1140
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 71748
89.7%
Latin 8252
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18212
25.4%
1 16064
22.4%
6 12106
16.9%
4 11816
16.5%
3 3241
 
4.5%
2 3017
 
4.2%
7 2508
 
3.5%
8 2066
 
2.9%
5 1371
 
1.9%
9 1347
 
1.9%
Latin
ValueCountFrequency (%)
c 1703
20.6%
e 1678
20.3%
d 1293
15.7%
f 1290
15.6%
a 1148
13.9%
b 1140
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18212
22.8%
1 16064
20.1%
6 12106
15.1%
4 11816
14.8%
3 3241
 
4.1%
2 3017
 
3.8%
7 2508
 
3.1%
8 2066
 
2.6%
c 1703
 
2.1%
e 1678
 
2.1%
Other values (6) 7589
9.5%

collection_dt
Real number (ℝ)

Distinct7832
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0210925 × 1016
Minimum2.0210925 × 1016
Maximum2.0210925 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:16.564293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210925 × 1016
5-th percentile2.0210925 × 1016
Q12.0210925 × 1016
median2.0210925 × 1016
Q32.0210925 × 1016
95-th percentile2.0210925 × 1016
Maximum2.0210925 × 1016
Range8929661
Interquartile range (IQR)6521724

Descriptive statistics

Standard deviation3001510.6
Coefficient of variation (CV)1.4850931 × 10-10
Kurtosis-0.94842766
Mean2.0210925 × 1016
Median Absolute Deviation (MAD)1301428
Skewness-0.8045334
Sum-8.0493351 × 1017
Variance9.0090656 × 1012
MonotonicityNot monotonic
2023-12-12T05:05:16.768935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210925131030362 6
 
0.1%
20210925130930251 6
 
0.1%
20210925132100508 6
 
0.1%
20210925132630467 6
 
0.1%
20210925130600218 5
 
0.1%
20210925133630679 5
 
0.1%
20210925130830123 5
 
0.1%
20210925125500332 5
 
0.1%
20210925131630487 5
 
0.1%
20210925125630453 5
 
0.1%
Other values (7822) 9946
99.5%
ValueCountFrequency (%)
20210925124701268 1
< 0.1%
20210925124701283 1
< 0.1%
20210925124701674 1
< 0.1%
20210925124702674 1
< 0.1%
20210925124703190 1
< 0.1%
20210925124703409 1
< 0.1%
20210925124703612 1
< 0.1%
20210925124704347 1
< 0.1%
20210925124705300 1
< 0.1%
20210925124706848 1
< 0.1%
ValueCountFrequency (%)
20210925133630929 1
 
< 0.1%
20210925133630913 1
 
< 0.1%
20210925133630898 1
 
< 0.1%
20210925133630882 1
 
< 0.1%
20210925133630866 1
 
< 0.1%
20210925133630819 2
 
< 0.1%
20210925133630757 1
 
< 0.1%
20210925133630726 1
 
< 0.1%
20210925133630694 1
 
< 0.1%
20210925133630679 5
0.1%

longitude
Real number (ℝ)

Distinct8591
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.24298
Minimum126.16317
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:16.960978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16317
5-th percentile126.24144
Q1126.36794
median126.50282
Q3126.6734
95-th percentile126.93537
Maximum180
Range53.836834
Interquartile range (IQR)0.30545625

Descriptive statistics

Standard deviation9.4287103
Coefficient of variation (CV)0.073522233
Kurtosis26.16626
Mean128.24298
Median Absolute Deviation (MAD)0.151112
Skewness5.3050101
Sum1282429.8
Variance88.900577
MonotonicityNot monotonic
2023-12-12T05:05:17.132618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 321
 
3.2%
126.345312 23
 
0.2%
126.241438 23
 
0.2%
126.34531 18
 
0.2%
126.345309 17
 
0.2%
126.241431 14
 
0.1%
126.935378 14
 
0.1%
126.345311 13
 
0.1%
126.482298 13
 
0.1%
126.241445 13
 
0.1%
Other values (8581) 9531
95.3%
ValueCountFrequency (%)
126.163166 1
< 0.1%
126.163171 1
< 0.1%
126.163189 1
< 0.1%
126.163198 1
< 0.1%
126.163223 1
< 0.1%
126.163284 1
< 0.1%
126.163298 1
< 0.1%
126.163307 1
< 0.1%
126.163334 1
< 0.1%
126.163473 1
< 0.1%
ValueCountFrequency (%)
180.0000001 321
3.2%
129.046715 1
 
< 0.1%
129.043433 1
 
< 0.1%
129.043343 1
 
< 0.1%
129.043029 1
 
< 0.1%
129.038595 1
 
< 0.1%
129.03856 1
 
< 0.1%
129.038542 1
 
< 0.1%
129.035254 1
 
< 0.1%
129.033976 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct8426
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.238661
Minimum33.200633
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:17.303210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200633
5-th percentile33.247396
Q133.328565
median33.461389
Q333.49979
95-th percentile33.554183
Maximum90
Range56.799367
Interquartile range (IQR)0.17122525

Descriptive statistics

Standard deviation9.973958
Coefficient of variation (CV)0.28304021
Kurtosis26.190262
Mean35.238661
Median Absolute Deviation (MAD)0.0562235
Skewness5.3084858
Sum352386.61
Variance99.479839
MonotonicityNot monotonic
2023-12-12T05:05:17.467222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 321
 
3.2%
33.394863 16
 
0.2%
33.394862 16
 
0.2%
33.318586 15
 
0.1%
33.318584 15
 
0.1%
33.394872 15
 
0.1%
33.394869 13
 
0.1%
33.485804 13
 
0.1%
33.462452 12
 
0.1%
33.39486 12
 
0.1%
Other values (8416) 9552
95.5%
ValueCountFrequency (%)
33.200633 1
< 0.1%
33.200928 1
< 0.1%
33.201188 1
< 0.1%
33.204979 1
< 0.1%
33.205367 1
< 0.1%
33.205368 1
< 0.1%
33.205426 1
< 0.1%
33.20605 1
< 0.1%
33.206138 1
< 0.1%
33.206139 1
< 0.1%
ValueCountFrequency (%)
90.0000001 321
3.2%
35.116585 1
 
< 0.1%
35.115995 1
 
< 0.1%
35.115993 1
 
< 0.1%
35.115881 1
 
< 0.1%
35.114214 1
 
< 0.1%
35.112298 1
 
< 0.1%
35.112173 1
 
< 0.1%
35.112074 1
 
< 0.1%
35.112013 1
 
< 0.1%

Interactions

2023-12-12T05:05:14.817162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:14.130379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:14.475825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:14.960588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:14.237849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:14.592788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:15.090475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/