Overview

Dataset statistics

Number of variables3
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory29.8 B

Variable types

Categorical1
Numeric2

Dataset

Description경상남도 진주시 관내 2019년, 2020년, 2021년, 2022년의 주정차 위반 연도별 월별건수 현황 자료입니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15077270

Alerts

월 is highly overall correlated with 건수High correlation
건수 is highly overall correlated with 월High correlation

Reproduction

Analysis started2023-12-10 23:59:17.234440
Analysis finished2023-12-10 23:59:17.770283
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
2022
12 
2021
12 
2020
12 
2019
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 12
25.0%
2021 12
25.0%
2020 12
25.0%
2019 12
25.0%

Length

2023-12-11T08:59:17.845379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:59:17.952135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 12
25.0%
2021 12
25.0%
2020 12
25.0%
2019 12
25.0%

월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T08:59:18.052456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.75
median6.5
Q39.25
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4885832
Coefficient of variation (CV)0.53670511
Kurtosis-1.2175129
Mean6.5
Median Absolute Deviation (MAD)3
Skewness0
Sum312
Variance12.170213
MonotonicityNot monotonic
2023-12-11T08:59:18.194504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 4
8.3%
2 4
8.3%
3 4
8.3%
4 4
8.3%
5 4
8.3%
6 4
8.3%
7 4
8.3%
8 4
8.3%
9 4
8.3%
10 4
8.3%
Other values (2) 8
16.7%
ValueCountFrequency (%)
1 4
8.3%
2 4
8.3%
3 4
8.3%
4 4
8.3%
5 4
8.3%
6 4
8.3%
7 4
8.3%
8 4
8.3%
9 4
8.3%
10 4
8.3%
ValueCountFrequency (%)
12 4
8.3%
11 4
8.3%
10 4
8.3%
9 4
8.3%
8 4
8.3%
7 4
8.3%
6 4
8.3%
5 4
8.3%
4 4
8.3%
3 4
8.3%

건수
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6267.3542
Minimum4426
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-11T08:59:18.308137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4426
5-th percentile4720
Q15485
median5815
Q37176.75
95-th percentile8146.3
Maximum9210
Range4784
Interquartile range (IQR)1691.75

Descriptive statistics

Standard deviation1156.7014
Coefficient of variation (CV)0.18455977
Kurtosis-0.55954955
Mean6267.3542
Median Absolute Deviation (MAD)654.5
Skewness0.55587392
Sum300833
Variance1337958.2
MonotonicityNot monotonic
2023-12-11T08:59:18.459033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
5502 2
 
4.2%
6455 1
 
2.1%
4921 1
 
2.1%
7064 1
 
2.1%
6824 1
 
2.1%
5744 1
 
2.1%
7515 1
 
2.1%
7353 1
 
2.1%
8147 1
 
2.1%
8385 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
4426 1
2.1%
4489 1
2.1%
4629 1
2.1%
4889 1
2.1%
4921 1
2.1%
5146 1
2.1%
5200 1
2.1%
5201 1
2.1%
5286 1
2.1%
5342 1
2.1%
ValueCountFrequency (%)
9210 1
2.1%
8385 1
2.1%
8147 1
2.1%
8145 1
2.1%
7974 1
2.1%
7860 1
2.1%
7668 1
2.1%
7527 1
2.1%
7515 1
2.1%
7481 1
2.1%

Interactions

2023-12-11T08:59:17.490452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:59:17.319033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:59:17.563337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:59:17.396713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:59:18.593415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도월건수
년도1.0000.0000.450
월0.0001.0000.316
건수0.4500.3161.000
2023-12-11T08:59:18.685286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월건수년도
월1.0000.5750.000
건수0.5751.0000.232
년도0.0000.2321.000

Missing values

2023-12-11T08:59:17.659205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:59:17.740128image/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

년도월건수
0202216455
1202225406
2202235200
3202245286
4202255812
5202265712
6202277481
7202289210
8202298145
92022107974
년도월건수
38201935502
39201945146
40201955201
41201964489
42201975760
43201985461
44201995619
452019105342
462019115818
472019125621