Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows64
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 05:00:00부터 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 64 (0.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 20:05:01.980736
Analysis finished2023-12-11 20:05:03.815665
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct621
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:05:04.124980image/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

Unique61 ?
Unique (%)0.6%

Sample

1st row46101818
2nd row46101826
3rd row461012f7
4th row46101072
5th row461000db
ValueCountFrequency (%)
461002db 1082
 
10.8%
461002e3 608
 
6.1%
461002e2 546
 
5.5%
461006ed 387
 
3.9%
461000ec 372
 
3.7%
46100103 360
 
3.6%
461012cf 297
 
3.0%
461005db 186
 
1.9%
461002e1 157
 
1.6%
46100283 150
 
1.5%
Other values (611) 5855
58.6%
2023-12-12T05:05:04.596067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18967
23.7%
1 15528
19.4%
6 11263
14.1%
4 11260
14.1%
2 4931
 
6.2%
e 2685
 
3.4%
d 2548
 
3.2%
3 2392
 
3.0%
b 1982
 
2.5%
5 1401
 
1.8%
Other values (6) 7043
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69591
87.0%
Lowercase Letter 10409
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18967
27.3%
1 15528
22.3%
6 11263
16.2%
4 11260
16.2%
2 4931
 
7.1%
3 2392
 
3.4%
5 1401
 
2.0%
8 1362
 
2.0%
7 1249
 
1.8%
9 1238
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 2685
25.8%
d 2548
24.5%
b 1982
19.0%
c 1321
12.7%
f 1249
12.0%
a 624
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69591
87.0%
Latin 10409
 
13.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18967
27.3%
1 15528
22.3%
6 11263
16.2%
4 11260
16.2%
2 4931
 
7.1%
3 2392
 
3.4%
5 1401
 
2.0%
8 1362
 
2.0%
7 1249
 
1.8%
9 1238
 
1.8%
Latin
ValueCountFrequency (%)
e 2685
25.8%
d 2548
24.5%
b 1982
19.0%
c 1321
12.7%
f 1249
12.0%
a 624
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18967
23.7%
1 15528
19.4%
6 11263
14.1%
4 11260
14.1%
2 4931
 
6.2%
e 2685
 
3.4%
d 2548
 
3.2%
3 2392
 
3.0%
b 1982
 
2.5%
5 1401
 
1.8%
Other values (6) 7043
 
8.8%

collection_dt
Real number (ℝ)

Distinct9248
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0210703 × 1016
Minimum2.0210703 × 1016
Maximum2.0210703 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:04.791496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210703 × 1016
5-th percentile2.0210703 × 1016
Q12.0210703 × 1016
median2.0210703 × 1016
Q32.0210703 × 1016
95-th percentile2.0210703 × 1016
Maximum2.0210703 × 1016
Range45099964
Interquartile range (IQR)18392512

Descriptive statistics

Standard deviation10983803
Coefficient of variation (CV)5.4346466 × 10-10
Kurtosis-0.49028377
Mean2.0210703 × 1016
Median Absolute Deviation (MAD)9000016
Skewness-0.67985432
Sum-8.0715399 × 1017
Variance1.2064392 × 1014
MonotonicityNot monotonic
2023-12-12T05:05:04.977682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210703082730051 5
 
0.1%
20210703093630627 4
 
< 0.1%
20210703094100410 4
 
< 0.1%
20210703091730700 4
 
< 0.1%
20210703091900510 4
 
< 0.1%
20210703085930259 3
 
< 0.1%
20210703094800946 3
 
< 0.1%
20210703092800501 3
 
< 0.1%
20210703093230006 3
 
< 0.1%
20210703092430251 3
 
< 0.1%
Other values (9238) 9964
99.6%
ValueCountFrequency (%)
20210703050000319 1
< 0.1%
20210703050100333 1
< 0.1%
20210703050100349 1
< 0.1%
20210703050153407 1
< 0.1%
20210703050330146 1
< 0.1%
20210703050400934 1
< 0.1%
20210703050430547 1
< 0.1%
20210703050530499 1
< 0.1%
20210703050530609 1
< 0.1%
20210703050800006 1
< 0.1%
ValueCountFrequency (%)
20210703095100283 1
< 0.1%
20210703095100268 1
< 0.1%
20210703095100158 2
< 0.1%
20210703095100143 1
< 0.1%
20210703095100127 1
< 0.1%
20210703095100064 1
< 0.1%
20210703095100002 1
< 0.1%
20210703095058658 1
< 0.1%
20210703095057642 1
< 0.1%
20210703095057517 1
< 0.1%

longitude
Real number (ℝ)

Distinct8764
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.00621
Minimum126.16976
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:05.188309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16976
5-th percentile126.27215
Q1126.38824
median126.49103
Q3126.54542
95-th percentile126.91019
Maximum180
Range53.830236
Interquartile range (IQR)0.15718725

Descriptive statistics

Standard deviation8.875297
Coefficient of variation (CV)0.069334896
Kurtosis30.355282
Mean128.00621
Median Absolute Deviation (MAD)0.0795325
Skewness5.6864586
Sum1280062.1
Variance78.770896
MonotonicityNot monotonic
2023-12-12T05:05:05.393388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 283
 
2.8%
126.327047 15
 
0.1%
126.327048 13
 
0.1%
126.479117 10
 
0.1%
126.52936 8
 
0.1%
126.454718 8
 
0.1%
126.415426 8
 
0.1%
126.49624 6
 
0.1%
126.529359 6
 
0.1%
126.289101 6
 
0.1%
Other values (8754) 9637
96.4%
ValueCountFrequency (%)
126.169764 1
< 0.1%
126.171196 1
< 0.1%
126.171204 1
< 0.1%
126.171205 1
< 0.1%
126.177089 1
< 0.1%
126.17724 1
< 0.1%
126.179237 1
< 0.1%
126.180617 1
< 0.1%
126.181727 1
< 0.1%
126.182128 1
< 0.1%
ValueCountFrequency (%)
180.0000001 283
2.8%
129.185549 1
 
< 0.1%
129.184941 1
 
< 0.1%
129.183671 1
 
< 0.1%
129.160634 1
 
< 0.1%
129.151906 1
 
< 0.1%
129.01117 1
 
< 0.1%
129.011157 1
 
< 0.1%
129.006524 1
 
< 0.1%
128.976241 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct8596
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.037779
Minimum33.200802
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:05.580086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200802
5-th percentile33.256144
Q133.383427
median33.472835
Q333.500903
95-th percentile33.523177
Maximum90
Range56.799198
Interquartile range (IQR)0.11747675

Descriptive statistics

Standard deviation9.3807935
Coefficient of variation (CV)0.26773368
Kurtosis30.372483
Mean35.037779
Median Absolute Deviation (MAD)0.0350345
Skewness5.6887668
Sum350377.79
Variance87.999287
MonotonicityNot monotonic
2023-12-12T05:05:05.745468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 283
 
2.8%
33.503889 14
 
0.1%
33.465642 11
 
0.1%
33.305205 9
 
0.1%
33.505194 9
 
0.1%
33.505192 8
 
0.1%
33.481045 7
 
0.1%
33.465643 7
 
0.1%
33.305208 7
 
0.1%
33.50519 6
 
0.1%
Other values (8586) 9639
96.4%
ValueCountFrequency (%)
33.200802 1
< 0.1%
33.20115 1
< 0.1%
33.202463 1
< 0.1%
33.205784 1
< 0.1%
33.205787 1
< 0.1%
33.205788 1
< 0.1%
33.209784 1
< 0.1%
33.210654 1
< 0.1%
33.211541 1
< 0.1%
33.211605 1
< 0.1%
ValueCountFrequency (%)
90.0000001 283
2.8%
35.218389 1
 
< 0.1%
35.214907 1
 
< 0.1%
35.212307 1
 
< 0.1%
35.212294 1
 
< 0.1%
35.202973 1
 
< 0.1%
35.193758 1
 
< 0.1%
35.187937 1
 
< 0.1%
35.168943 1
 
< 0.1%
35.164727 1
 
< 0.1%

Interactions

2023-12-12T05:05:03.216261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:02.407739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:02.800672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:03.346823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:02.530034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:02.943928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/