Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory53.3 B

Variable types

Numeric3
DateTime1
Categorical2

Dataset

Description남동구 금연구역 단속 현황(연번,단속연월,장소,위반건수,과태료부과(천원),데이터기준일자)에 대한 데이터를 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087378&srcSe=7661IVAWM27C61E190

Alerts

장소 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 위반건수 and 1 other fieldsHigh correlation
위반건수 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
과태료부과(천원) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
단속연월 has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:04:27.352959
Analysis finished2024-01-28 06:04:28.389001
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-28T15:04:28.445618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2024-01-28T15:04:28.553305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

단속연월
Date

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2022-01-18 00:00:00
Maximum2023-04-30 00:00:00
2024-01-28T15:04:28.674227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:28.802050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

장소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
pc방, 복합건축물, 근린공원등
57 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpc방, 복합건축물, 근린공원등
2nd rowpc방, 복합건축물, 근린공원등
3rd rowpc방, 복합건축물, 근린공원등
4th rowpc방, 복합건축물, 근린공원등
5th rowpc방, 복합건축물, 근린공원등

Common Values

ValueCountFrequency (%)
pc방, 복합건축물, 근린공원등 57
100.0%

Length

2024-01-28T15:04:28.913575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:04:28.987494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pc방 57
33.3%
복합건축물 57
33.3%
근린공원등 57
33.3%

위반건수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.877193
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-28T15:04:29.072542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median18
Q336
95-th percentile62.4
Maximum71
Range70
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.947361
Coefficient of variation (CV)0.79353387
Kurtosis-0.11463058
Mean23.877193
Median Absolute Deviation (MAD)13
Skewness0.83333399
Sum1361
Variance359.00251
MonotonicityNot monotonic
2024-01-28T15:04:29.195954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2 4
 
7.0%
24 3
 
5.3%
18 3
 
5.3%
12 3
 
5.3%
9 2
 
3.5%
1 2
 
3.5%
52 2
 
3.5%
3 2
 
3.5%
31 2
 
3.5%
38 2
 
3.5%
Other values (26) 32
56.1%
ValueCountFrequency (%)
1 2
3.5%
2 4
7.0%
3 2
3.5%
4 1
 
1.8%
5 2
3.5%
6 1
 
1.8%
7 1
 
1.8%
9 2
3.5%
11 2
3.5%
12 3
5.3%
ValueCountFrequency (%)
71 1
1.8%
70 1
1.8%
64 1
1.8%
62 1
1.8%
52 2
3.5%
49 2
3.5%
48 1
1.8%
46 1
1.8%
42 1
1.8%
41 1
1.8%

과태료부과(천원)
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1955.7018
Minimum50
Maximum6800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-01-28T15:04:29.314312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile71
Q1560
median1350
Q32900
95-th percentile5110
Maximum6800
Range6750
Interquartile range (IQR)2340

Descriptive statistics

Standard deviation1771.5896
Coefficient of variation (CV)0.9058588
Kurtosis0.32454745
Mean1955.7018
Median Absolute Deviation (MAD)1030
Skewness1.0366334
Sum111475
Variance3138529.9
MonotonicityNot monotonic
2024-01-28T15:04:29.440646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1300 3
 
5.3%
150 3
 
5.3%
1100 3
 
5.3%
600 2
 
3.5%
50 2
 
3.5%
1350 2
 
3.5%
2950 1
 
1.8%
1665 1
 
1.8%
1940 1
 
1.8%
560 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
50 2
3.5%
55 1
 
1.8%
75 1
 
1.8%
80 1
 
1.8%
150 3
5.3%
250 1
 
1.8%
275 1
 
1.8%
320 1
 
1.8%
350 1
 
1.8%
450 1
 
1.8%
ValueCountFrequency (%)
6800 1
1.8%
6725 1
1.8%
5150 1
1.8%
5100 1
1.8%
4900 1
1.8%
4850 1
1.8%
4750 1
1.8%
4500 1
1.8%
4200 1
1.8%
3750 1
1.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-05-11
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-11
2nd row2023-05-11
3rd row2023-05-11
4th row2023-05-11
5th row2023-05-11

Common Values

ValueCountFrequency (%)
2023-05-11 57
100.0%

Length

2024-01-28T15:04:29.551744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:04:29.624519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-11 57
100.0%

Interactions

2024-01-28T15:04:27.966239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.452516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.684994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:28.051637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.532369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.755200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:28.135651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.608455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:04:27.849516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:04:29.670307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속연월위반건수과태료부과(천원)
연번1.0001.0000.6180.577
단속연월1.0001.0001.0001.000
위반건수0.6181.0001.0000.884
과태료부과(천원)0.5771.0000.8841.000
2024-01-28T15:04:29.766418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위반건수과태료부과(천원)
연번1.000-0.505-0.574
위반건수-0.5051.0000.978
과태료부과(천원)-0.5740.9781.000

Missing values

2024-01-28T15:04:28.251096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:04:28.346641image/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

연번단속연월장소위반건수과태료부과(천원)데이터기준일자
012022-01-18pc방, 복합건축물, 근린공원등1313002023-05-11
122022-02-18pc방, 복합건축물, 근린공원등4242002023-05-11
232022-03-18pc방, 복합건축물, 근린공원등4947502023-05-11
342022-04-18pc방, 복합건축물, 근린공원등7168002023-05-11
452022-05-18pc방, 복합건축물, 근린공원등7067252023-05-11
562022-06-18pc방, 복합건축물, 근린공원등4948502023-05-11
672022-07-18pc방, 복합건축물, 근린공원등3635502023-05-11
782022-08-18pc방, 복합건축물, 근린공원등1110502023-05-11
892022-09-18pc방, 복합건축물, 근린공원등1813002023-05-11
9102022-01-19pc방, 복합건축물, 근린공원등1311002023-05-11
연번단속연월장소위반건수과태료부과(천원)데이터기준일자
47482022-07-31pc방, 복합건축물, 근린공원등147002023-05-11
48492022-08-31pc방, 복합건축물, 근린공원등126002023-05-11
49502022-09-30pc방, 복합건축물, 근린공원등178502023-05-11
50512022-10-31pc방, 복합건축물, 근린공원등126002023-05-11
51522022-11-30pc방, 복합건축물, 근린공원등54502023-05-11
52532022-12-31pc방, 복합건축물, 근린공원등55002023-05-11
53542023-01-31pc방, 복합건축물, 근린공원등1502023-05-11
54552023-02-28pc방, 복합건축물, 근린공원등21502023-05-11
55562023-03-31pc방, 복합건축물, 근린공원등2111002023-05-11
56572023-04-30pc방, 복합건축물, 근린공원등11552023-05-11