Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows7
Duplicate rows (%)0.1%
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 7 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 20:05:28.114258
Analysis finished2023-12-11 20:05:29.794180
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

oid
Text

Distinct663
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T05:05:30.060746image/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

Unique50 ?
Unique (%)0.5%

Sample

1st row461017a7
2nd row461006e5
3rd row461003a7
4th row46100fb4
5th row461006e5
ValueCountFrequency (%)
461006e5 713
 
7.1%
46100734 419
 
4.2%
461002d7 410
 
4.1%
461005db 353
 
3.5%
46101334 338
 
3.4%
461010bb 333
 
3.3%
46100100 275
 
2.8%
46100283 226
 
2.3%
461002e1 217
 
2.2%
46100797 161
 
1.6%
Other values (653) 6555
65.5%
2023-12-12T05:05:30.558037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18122
22.7%
1 16753
20.9%
4 11814
14.8%
6 11659
14.6%
3 3034
 
3.8%
2 2805
 
3.5%
7 2614
 
3.3%
5 2287
 
2.9%
b 2018
 
2.5%
e 1836
 
2.3%
Other values (6) 7058
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71941
89.9%
Lowercase Letter 8059
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18122
25.2%
1 16753
23.3%
4 11814
16.4%
6 11659
16.2%
3 3034
 
4.2%
2 2805
 
3.9%
7 2614
 
3.6%
5 2287
 
3.2%
8 1709
 
2.4%
9 1144
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
b 2018
25.0%
e 1836
22.8%
d 1431
17.8%
f 976
12.1%
c 919
11.4%
a 879
10.9%

Most occurring scripts

ValueCountFrequency (%)
Common 71941
89.9%
Latin 8059
 
10.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18122
25.2%
1 16753
23.3%
4 11814
16.4%
6 11659
16.2%
3 3034
 
4.2%
2 2805
 
3.9%
7 2614
 
3.6%
5 2287
 
3.2%
8 1709
 
2.4%
9 1144
 
1.6%
Latin
ValueCountFrequency (%)
b 2018
25.0%
e 1836
22.8%
d 1431
17.8%
f 976
12.1%
c 919
11.4%
a 879
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18122
22.7%
1 16753
20.9%
4 11814
14.8%
6 11659
14.6%
3 3034
 
3.8%
2 2805
 
3.5%
7 2614
 
3.3%
5 2287
 
2.9%
b 2018
 
2.5%
e 1836
 
2.3%
Other values (6) 7058
 
8.8%

collection_dt
Real number (ℝ)

Distinct9061
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0211225 × 1016
Minimum2.0211212 × 1016
Maximum2.0211225 × 1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:30.730777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0211212 × 1016
5-th percentile2.0211225 × 1016
Q12.0211225 × 1016
median2.0211225 × 1016
Q32.0211225 × 1016
95-th percentile2.0211225 × 1016
Maximum2.0211225 × 1016
Range1.3212301 × 1010
Interquartile range (IQR)11300612

Descriptive statistics

Standard deviation2.7206064 × 109
Coefficient of variation (CV)1.3460868 × 10-7
Kurtosis17.477335
Mean2.0211225 × 1016
Median Absolute Deviation (MAD)7463640
Skewness-4.4128939
Sum-8.0193873 × 1017
Variance7.401699 × 1018
MonotonicityNot monotonic
2023-12-12T05:05:30.909353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211225185700661 6
 
0.1%
20211225190200512 5
 
0.1%
20211225185100411 5
 
0.1%
20211225185400481 5
 
0.1%
20211225185430938 4
 
< 0.1%
20211225192900658 4
 
< 0.1%
20211225185800387 4
 
< 0.1%
20211225191000589 4
 
< 0.1%
20211225192400807 4
 
< 0.1%
20211225190630140 4
 
< 0.1%
Other values (9051) 9955
99.6%
ValueCountFrequency (%)
20211212000030440 1
< 0.1%
20211212000100022 1
< 0.1%
20211212000100475 1
< 0.1%
20211212000100929 1
< 0.1%
20211212000121782 1
< 0.1%
20211212000130191 1
< 0.1%
20211212000130238 1
< 0.1%
20211212000200448 1
< 0.1%
20211212000330435 1
< 0.1%
20211212000400362 1
< 0.1%
ValueCountFrequency (%)
20211225212330968 1
< 0.1%
20211225212330671 1
< 0.1%
20211225212330655 1
< 0.1%
20211225212330483 1
< 0.1%
20211225212330468 1
< 0.1%
20211225212330233 1
< 0.1%
20211225212322732 1
< 0.1%
20211225212317653 1
< 0.1%
20211225212314606 1
< 0.1%
20211225212314169 1
< 0.1%

longitude
Real number (ℝ)

Distinct8596
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.81097
Minimum126.16564
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:31.319082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16564
5-th percentile126.27744
Q1126.44242
median126.49679
Q3126.56213
95-th percentile126.90971
Maximum180
Range53.83436
Interquartile range (IQR)0.119712

Descriptive statistics

Standard deviation8.2206551
Coefficient of variation (CV)0.064318856
Kurtosis36.337609
Mean127.81097
Median Absolute Deviation (MAD)0.064868
Skewness6.1899254
Sum1278109.7
Variance67.579171
MonotonicityNot monotonic
2023-12-12T05:05:31.461612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180.0000001 242
 
2.4%
126.562408 32
 
0.3%
126.528566 19
 
0.2%
126.482223 14
 
0.1%
126.492412 14
 
0.1%
126.492413 12
 
0.1%
126.347018 12
 
0.1%
126.492421 10
 
0.1%
126.492414 10
 
0.1%
126.324704 10
 
0.1%
Other values (8586) 9625
96.2%
ValueCountFrequency (%)
126.16564 1
< 0.1%
126.165774 1
< 0.1%
126.166704 1
< 0.1%
126.16912 1
< 0.1%
126.172969 1
< 0.1%
126.175276 1
< 0.1%
126.178932 1
< 0.1%
126.18162 1
< 0.1%
126.182036 1
< 0.1%
126.18215 1
< 0.1%
ValueCountFrequency (%)
180.0000001 242
2.4%
126.98217 1
 
< 0.1%
126.978624 1
 
< 0.1%
126.976887 1
 
< 0.1%
126.976717 1
 
< 0.1%
126.976341 1
 
< 0.1%
126.976167 1
 
< 0.1%
126.973685 1
 
< 0.1%
126.97123 1
 
< 0.1%
126.959161 1
 
< 0.1%

latitude
Real number (ℝ)

Distinct8248
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.789957
Minimum33.204246
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:05:31.602454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.204246
5-th percentile33.247528
Q133.304701
median33.47299
Q333.49609
95-th percentile33.528492
Maximum90
Range56.795754
Interquartile range (IQR)0.1913895

Descriptive statistics

Standard deviation8.6959507
Coefficient of variation (CV)0.24995578
Kurtosis36.3478
Mean34.789957
Median Absolute Deviation (MAD)0.0362365
Skewness6.1912128
Sum347899.57
Variance75.619558
MonotonicityNot monotonic
2023-12-12T05:05:31.743357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0000001 242
 
2.4%
33.245553 32
 
0.3%
33.49604 24
 
0.2%
33.496035 22
 
0.2%
33.247528 19
 
0.2%
33.496032 18
 
0.2%
33.496051 15
 
0.1%
33.496055 15
 
0.1%
33.496037 15
 
0.1%
33.485595 14
 
0.1%
Other values (8238) 9584
95.8%
ValueCountFrequency (%)
33.204246 1
< 0.1%
33.208374 1
< 0.1%
33.215723 1
< 0.1%
33.21611 1
< 0.1%
33.216272 1
< 0.1%
33.217248 1
< 0.1%
33.217335 1
< 0.1%
33.217556 1
< 0.1%
33.217701 1
< 0.1%
33.217706 1
< 0.1%
ValueCountFrequency (%)
90.0000001 242
2.4%
35.964547 1
 
< 0.1%
35.963552 1
 
< 0.1%
35.959791 1
 
< 0.1%
35.959433 1
 
< 0.1%
35.959216 1
 
< 0.1%
35.959071 1
 
< 0.1%
35.958993 1
 
< 0.1%
35.958964 1
 
< 0.1%
35.958604 1
 
< 0.1%

Interactions

2023-12-12T05:05:29.279114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:28.538369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:28.943610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:29.384711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:28.646352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:29.078628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:05:29.493042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/