Overview

Dataset statistics

Number of variables4
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory36.6 B

Variable types

Categorical2
Numeric1
DateTime1

Dataset

Description대전광역시 중구 내의 불법추자위반단속 현황에 대한 데이터로, 행정동별, 연도별로 구분되어 있는 데이터를 제공합니다. 대전광역시 중구청 교통과에서 제공하는 데이터입니다.
URLhttps://www.data.go.kr/data/15113254/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
단속건수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:13:46.107162
Analysis finished2023-12-12 20:13:46.432771
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
2021
17 
2022
17 
2023
17 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 17
33.3%
2022 17
33.3%
2023 17
33.3%

Length

2023-12-13T05:13:46.488682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:13:46.574583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 17
33.3%
2022 17
33.3%
2023 17
33.3%

행정동
Categorical

Distinct17
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size540.0 B
중촌동
 
3
용두동
 
3
은행선화동
 
3
대흥동
 
3
문창동
 
3
Other values (12)
36 

Length

Max length5
Median length3
Mean length3.4117647
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중촌동
2nd row용두동
3rd row은행선화동
4th row대흥동
5th row문창동

Common Values

ValueCountFrequency (%)
중촌동 3
 
5.9%
용두동 3
 
5.9%
은행선화동 3
 
5.9%
대흥동 3
 
5.9%
문창동 3
 
5.9%
부사동 3
 
5.9%
대사동 3
 
5.9%
석교동 3
 
5.9%
목동 3
 
5.9%
오류동 3
 
5.9%
Other values (7) 21
41.2%

Length

2023-12-13T05:13:46.685812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중촌동 3
 
5.9%
오류동 3
 
5.9%
문화2동 3
 
5.9%
문화1동 3
 
5.9%
유천2동 3
 
5.9%
유천1동 3
 
5.9%
태평2동 3
 
5.9%
태평1동 3
 
5.9%
목동 3
 
5.9%
용두동 3
 
5.9%
Other values (7) 21
41.2%

단속건수
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1520.9804
Minimum42
Maximum10732
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-13T05:13:46.851506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile87
Q1278
median941
Q31565
95-th percentile4850.5
Maximum10732
Range10690
Interquartile range (IQR)1287

Descriptive statistics

Standard deviation2048.0735
Coefficient of variation (CV)1.3465482
Kurtosis9.6300086
Mean1520.9804
Median Absolute Deviation (MAD)665
Skewness2.889754
Sum77570
Variance4194605
MonotonicityNot monotonic
2023-12-13T05:13:47.004039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1300 1
 
2.0%
370 1
 
2.0%
851 1
 
2.0%
379 1
 
2.0%
205 1
 
2.0%
1076 1
 
2.0%
234 1
 
2.0%
2503 1
 
2.0%
941 1
 
2.0%
147 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
42 1
2.0%
52 1
2.0%
59 1
2.0%
115 1
2.0%
147 1
2.0%
205 1
2.0%
221 1
2.0%
234 1
2.0%
238 1
2.0%
245 1
2.0%
ValueCountFrequency (%)
10732 1
2.0%
8534 1
2.0%
5179 1
2.0%
4522 1
2.0%
4141 1
2.0%
3251 1
2.0%
3210 1
2.0%
2915 1
2.0%
2503 1
2.0%
2452 1
2.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
Minimum2023-04-04 00:00:00
Maximum2023-04-04 00:00:00
2023-12-13T05:13:47.209462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:13:47.306776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:13:46.229604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:13:47.686698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도행정동단속건수
연도1.0000.0000.140
행정동0.0001.0000.636
단속건수0.1400.6361.000
2023-12-13T05:13:47.773482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동연도
행정동1.0000.000
연도0.0001.000
2023-12-13T05:13:47.856206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속건수연도행정동
단속건수1.0000.0760.298
연도0.0761.0000.000
행정동0.2980.0001.000

Missing values

2023-12-13T05:13:46.328411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:13:46.402471image/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

연도행정동단속건수데이터기준일자
02021중촌동13002023-04-04
12021용두동3702023-04-04
22021은행선화동45222023-04-04
32021대흥동85342023-04-04
42021문창동11522023-04-04
52021부사동7982023-04-04
62021대사동11162023-04-04
72021석교동8762023-04-04
82021목동29152023-04-04
92021오류동16852023-04-04
연도행정동단속건수데이터기준일자
412023석교동2642023-04-04
422023목동11842023-04-04
432023오류동10312023-04-04
442023태평1동1152023-04-04
452023태평2동2382023-04-04
462023유천1동522023-04-04
472023유천2동422023-04-04
482023문화1동2452023-04-04
492023문화2동592023-04-04
502023산성동7502023-04-04