Overview

Dataset statistics

Number of variables3
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows8
Duplicate rows (%)13.3%
Total size in memory1.6 KiB
Average record size in memory27.2 B

Variable types

Categorical2
Numeric1

Dataset

Description부산광역시 유량 시간당 적산값으로 수요예측에 사용되는 데이터를 제공 합니다. 순시차와 수집일자에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15081820/fileData.do

Alerts

수집일 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 8 (13.3%) duplicate rowsDuplicates
순시차 has 4 (6.7%) zerosZeros

Reproduction

Analysis started2023-12-12 02:24:29.129379
Analysis finished2023-12-12 02:24:29.418987
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수집일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-05-07
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-07
2nd row2023-05-07
3rd row2023-05-07
4th row2023-05-07
5th row2023-05-07

Common Values

ValueCountFrequency (%)
2023-05-07 60
100.0%

Length

2023-12-12T11:24:29.478896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:24:29.592298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-07 60
100.0%

순시차
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193.35811
Minimum0
Maximum896
Zeros4
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T11:24:29.727200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.5
median64.84
Q3245.3379
95-th percentile828.125
Maximum896
Range896
Interquartile range (IQR)218.8379

Descriptive statistics

Standard deviation256.27354
Coefficient of variation (CV)1.3253829
Kurtosis1.51872
Mean193.35811
Median Absolute Deviation (MAD)51.84
Skewness1.6515864
Sum11601.487
Variance65676.128
MonotonicityNot monotonic
2023-12-12T11:24:29.870090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 4
 
6.7%
828.125 4
 
6.7%
113.0 3
 
5.0%
23.0 2
 
3.3%
25.0 2
 
3.3%
47.0 2
 
3.3%
51.0 2
 
3.3%
48.0 2
 
3.3%
617.1875 1
 
1.7%
49.12 1
 
1.7%
Other values (37) 37
61.7%
ValueCountFrequency (%)
0.0 4
6.7%
5.12 1
 
1.7%
8.0 1
 
1.7%
12.0 1
 
1.7%
14.0 1
 
1.7%
16.0 1
 
1.7%
18.0 1
 
1.7%
23.0 2
3.3%
23.36 1
 
1.7%
25.0 2
3.3%
ValueCountFrequency (%)
896.0 1
 
1.7%
828.125 4
6.7%
684.0 1
 
1.7%
655.0 1
 
1.7%
617.1875 1
 
1.7%
558.5938 1
 
1.7%
441.1621 1
 
1.7%
327.1484 1
 
1.7%
303.0 1
 
1.7%
258.3008 1
 
1.7%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-05-07
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-07
2nd row2023-05-07
3rd row2023-05-07
4th row2023-05-07
5th row2023-05-07

Common Values

ValueCountFrequency (%)
2023-05-07 60
100.0%

Length

2023-12-12T11:24:29.996196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:24:30.092301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-07 60
100.0%

Interactions

2023-12-12T11:24:29.168726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T11:24:29.272579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:24:29.381298image/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

수집일순시차데이터기준일
02023-05-0723.02023-05-07
12023-05-0751.02023-05-07
22023-05-07113.02023-05-07
32023-05-07250.52023-05-07
42023-05-0748.02023-05-07
52023-05-0739.02023-05-07
62023-05-0712.02023-05-07
72023-05-0733.02023-05-07
82023-05-07186.02023-05-07
92023-05-07245.11722023-05-07
수집일순시차데이터기준일
502023-05-0749.122023-05-07
512023-05-07617.18752023-05-07
522023-05-07684.02023-05-07
532023-05-07167.02023-05-07
542023-05-070.02023-05-07
552023-05-07828.1252023-05-07
562023-05-070.02023-05-07
572023-05-07828.1252023-05-07
582023-05-07828.1252023-05-07
592023-05-07828.1252023-05-07

Duplicate rows

Most frequently occurring

수집일순시차데이터기준일# duplicates
02023-05-070.02023-05-074
72023-05-07828.1252023-05-074
62023-05-07113.02023-05-073
12023-05-0723.02023-05-072
22023-05-0725.02023-05-072
32023-05-0747.02023-05-072
42023-05-0748.02023-05-072
52023-05-0751.02023-05-072