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 20:05:21.235068
Analysis finished2023-12-11 20:05:22.796634
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct894
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:05:23.039179image/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

Unique111 ?
Unique (%)1.1%

Sample

1st row46100088
2nd row46100100
3rd row46100480
4th row461011b7
5th row4610045a
ValueCountFrequency (%)
4610078d 499
 
5.0%
461000e4 399
 
4.0%
46100351 331
 
3.3%
46100100 286
 
2.9%
46100366 271
 
2.7%
461002e3 229
 
2.3%
4610045a 228
 
2.3%
46101369 211
 
2.1%
461006e5 200
 
2.0%
46100088 196
 
2.0%
Other values (884) 7150
71.5%
2023-12-12T05:05:23.452346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19297
24.1%
1 15433
19.3%
6 12133
15.2%
4 12011
15.0%
3 2735
 
3.4%
2 2555
 
3.2%
7 2394
 
3.0%
8 2293
 
2.9%
d 2155
 
2.7%
5 1776
 
2.2%
Other values (6) 7218
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72080
90.1%
Lowercase Letter 7920
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19297
26.8%
1 15433
21.4%
6 12133
16.8%
4 12011
16.7%
3 2735
 
3.8%
2 2555
 
3.5%
7 2394
 
3.3%
8 2293
 
3.2%
5 1776
 
2.5%
9 1453
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
d 2155
27.2%
e 1741
22.0%
a 1215
15.3%
b 1101
13.9%
f 904
11.4%
c 804
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Common 72080
90.1%
Latin 7920
 
9.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19297
26.8%
1 15433
21.4%
6 12133
16.8%
4 12011
16.7%
3 2735
 
3.8%
2 2555
 
3.5%
7 2394
 
3.3%
8 2293
 
3.2%
5 1776
 
2.5%
9 1453
 
2.0%
Latin
ValueCountFrequency (%)
d 2155
27.2%
e 1741
22.0%
a 1215
15.3%
b 1101
13.9%
f 904
11.4%
c 804
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19297
24.1%
1 15433
19.3%
6 12133
15.2%
4 12011
15.0%
3 2735
 
3.4%
2 2555
 
3.2%
7 2394
 
3.0%
8 2293
 
2.9%
d 2155
 
2.7%
5 1776
 
2.2%
Other values (6) 7218
 
9.0%

collection_dt
Real number (ℝ)

Distinct8072
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.021103 × 1016
Minimum2.0211017 × 1016
Maximum2.021103 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:23.596983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0211017 × 1016
5-th percentile2.021103 × 1016
Q12.021103 × 1016
median2.021103 × 1016
Q32.021103 × 1016
95-th percentile2.021103 × 1016
Maximum2.021103 × 1016
Range1.3180323 × 1010
Interquartile range (IQR)2080300

Descriptive statistics

Standard deviation1.6808 × 109
Coefficient of variation (CV)8.3162512 × 10-8
Kurtosis55.286298
Mean2.021103 × 1016
Median Absolute Deviation (MAD)1026308
Skewness-7.5680287
Sum-8.0388525 × 1017
Variance2.8250887 × 1018
MonotonicityNot monotonic
2023-12-12T05:05:23.774911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211030174000651 7
 
0.1%
20211030174230078 6
 
0.1%
20211030175630876 6
 
0.1%
20211030174130538 6
 
0.1%
20211030175400107 5
 
0.1%
20211030175330181 5
 
0.1%
20211030173000510 5
 
0.1%
20211030173730522 5
 
0.1%
20211030173400510 5
 
0.1%
20211030174600105 5
 
0.1%
Other values (8062) 9945
99.5%
ValueCountFrequency (%)
20211017000030143 1
< 0.1%
20211017000130562 1
< 0.1%
20211017000300521 1
< 0.1%
20211017000400347 1
< 0.1%
20211017000430243 1
< 0.1%
20211017000530882 1
< 0.1%
20211017000630314 1
< 0.1%
20211017000700449 1
< 0.1%
20211017000700965 1
< 0.1%
20211017000730441 1
< 0.1%
ValueCountFrequency (%)
20211030180353312 1
< 0.1%
20211030180353093 1
< 0.1%
20211030180352734 1
< 0.1%
20211030180351265 1
< 0.1%
20211030180350765 1
< 0.1%
20211030180349718 1
< 0.1%
20211030180348077 1
< 0.1%
20211030180347921 1
< 0.1%
20211030180347577 1
< 0.1%
20211030180347483 1
< 0.1%

longitude
Real number (ℝ)

Distinct8567
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.2518
Minimum126.16326
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:23.927634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16326
5-th percentile126.27713
Q1126.4419
median126.50303
Q3126.60926
95-th percentile180
Maximum180
Range53.836738
Interquartile range (IQR)0.16735275

Descriptive statistics

Standard deviation11.778395
Coefficient of variation (CV)0.091127509
Kurtosis14.624233
Mean129.2518
Median Absolute Deviation (MAD)0.08366
Skewness4.0764235
Sum1292518
Variance138.73058
MonotonicityNot monotonic
2023-12-12T05:05:24.064781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 511
 
5.1%
126.410721 40
 
0.4%
126.565126 22
 
0.2%
126.462992 12
 
0.1%
126.482945 11
 
0.1%
126.916453 10
 
0.1%
126.493935 9
 
0.1%
126.27713 7
 
0.1%
126.455414 7
 
0.1%
126.478429 7
 
0.1%
Other values (8557) 9364
93.6%
ValueCountFrequency (%)
126.163262 1
< 0.1%
126.163297 1
< 0.1%
126.163359 1
< 0.1%
126.163554 1
< 0.1%
126.164169 1
< 0.1%
126.165308 1
< 0.1%
126.165355 1
< 0.1%
126.165546 1
< 0.1%
126.166272 1
< 0.1%
126.166522 1
< 0.1%
ValueCountFrequency (%)
180.0000001 511
5.1%
129.14372 1
 
< 0.1%
129.142113 1
 
< 0.1%
129.141899 1
 
< 0.1%
129.099787 1
 
< 0.1%
127.1160801 1
 
< 0.1%
127.1086008 1
 
< 0.1%
126.953667 1
 
< 0.1%
126.953617 1
 
< 0.1%
126.953614 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct8288
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.311456
Minimum33.200038
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:24.188364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.200038
5-th percentile33.249367
Q133.320048
median33.465944
Q333.496903
95-th percentile90
Maximum90
Range56.799962
Interquartile range (IQR)0.17685475

Descriptive statistics

Standard deviation12.460573
Coefficient of variation (CV)0.34315819
Kurtosis14.625677
Mean36.311456
Median Absolute Deviation (MAD)0.0462775
Skewness4.0767294
Sum363114.56
Variance155.26589
MonotonicityNot monotonic
2023-12-12T05:05:24.312327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 511
 
5.1%
33.249429 40
 
0.4%
33.250501 22
 
0.2%
33.47767 12
 
0.1%
33.484096 11
 
0.1%
33.433706 10
 
0.1%
33.448175 10
 
0.1%
33.477389 10
 
0.1%
33.423863 8
 
0.1%
33.49727 8
 
0.1%
Other values (8278) 9358
93.6%
ValueCountFrequency (%)
33.200038 1
< 0.1%
33.200622 1
< 0.1%
33.200696 1
< 0.1%
33.200797 1
< 0.1%
33.200883 1
< 0.1%
33.200902 1
< 0.1%
33.201152 1
< 0.1%
33.202053 1
< 0.1%
33.203301 1
< 0.1%
33.203413 1
< 0.1%
ValueCountFrequency (%)
90.0000001 511
5.1%
37.371373 1
 
< 0.1%
37.370848 1
 
< 0.1%
37.370333 1
 
< 0.1%
37.370321 1
 
< 0.1%
37.370293 1
 
< 0.1%
37.370287 1
 
< 0.1%
37.370185 1
 
< 0.1%
37.370159 1
 
< 0.1%
35.7941439 1
 
< 0.1%

Interactions

2023-12-12T05:05:22.316895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:21.663008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:21.981047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:22.429872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:21.769624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:22.101098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:22.532220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/