Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory948.0 B
Average record size in memory39.5 B

Variable types

DateTime1
Numeric2
Categorical1

Dataset

Description이 데이터는 서울특별시 동작구 흡연단속 현황에 관한 것입니다. 이 데이터에는 월별 흡연신고건수, 흡연단속건수 등이 포함되어 있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15049032/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 has unique valuesUnique
단속건수 has 5 (20.8%) zerosZeros

Reproduction

Analysis started2024-04-17 09:56:11.433965
Analysis finished2024-04-17 09:56:12.156415
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2021-07-01 00:00:00
Maximum2023-06-01 00:00:00
2024-04-17T18:56:12.197959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:56:12.289466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

흡연민원건수
Real number (ℝ)

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.166667
Minimum26
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-17T18:56:12.385432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile33.8
Q152.5
median65
Q377.75
95-th percentile84
Maximum110
Range84
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation18.65165
Coefficient of variation (CV)0.29067507
Kurtosis0.61850847
Mean64.166667
Median Absolute Deviation (MAD)13.5
Skewness0.093677453
Sum1540
Variance347.88406
MonotonicityNot monotonic
2024-04-17T18:56:12.483548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
84 2
 
8.3%
44 2
 
8.3%
63 2
 
8.3%
65 2
 
8.3%
68 1
 
4.2%
77 1
 
4.2%
110 1
 
4.2%
71 1
 
4.2%
54 1
 
4.2%
47 1
 
4.2%
Other values (10) 10
41.7%
ValueCountFrequency (%)
26 1
4.2%
32 1
4.2%
44 2
8.3%
47 1
4.2%
48 1
4.2%
54 1
4.2%
57 1
4.2%
62 1
4.2%
63 2
8.3%
65 2
8.3%
ValueCountFrequency (%)
110 1
4.2%
84 2
8.3%
82 1
4.2%
81 1
4.2%
80 1
4.2%
77 1
4.2%
71 1
4.2%
68 1
4.2%
67 1
4.2%
66 1
4.2%

단속건수
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.208333
Minimum0
Maximum112
Zeros5
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-17T18:56:12.575374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.75
median27.5
Q347.25
95-th percentile72.45
Maximum112
Range112
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation27.612189
Coefficient of variation (CV)0.91405866
Kurtosis1.9017066
Mean30.208333
Median Absolute Deviation (MAD)20
Skewness1.1638126
Sum725
Variance762.43297
MonotonicityNot monotonic
2024-04-17T18:56:12.679932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 5
20.8%
28 2
 
8.3%
15 1
 
4.2%
75 1
 
4.2%
37 1
 
4.2%
44 1
 
4.2%
53 1
 
4.2%
112 1
 
4.2%
47 1
 
4.2%
48 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
0 5
20.8%
4 1
 
4.2%
9 1
 
4.2%
15 1
 
4.2%
16 1
 
4.2%
19 1
 
4.2%
22 1
 
4.2%
27 1
 
4.2%
28 2
 
8.3%
34 1
 
4.2%
ValueCountFrequency (%)
112 1
4.2%
75 1
4.2%
58 1
4.2%
53 1
4.2%
49 1
4.2%
48 1
4.2%
47 1
4.2%
44 1
4.2%
37 1
4.2%
34 1
4.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-07-17
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-17
2nd row2023-07-17
3rd row2023-07-17
4th row2023-07-17
5th row2023-07-17

Common Values

ValueCountFrequency (%)
2023-07-17 24
100.0%

Length

2024-04-17T18:56:12.789711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:56:12.880883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-17 24
100.0%

Interactions

2024-04-17T18:56:11.906052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:56:11.502021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:56:11.962671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:56:11.846952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T18:56:12.933204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분흡연민원건수단속건수
구분1.0001.0001.000
흡연민원건수1.0001.0000.287
단속건수1.0000.2871.000
2024-04-17T18:56:13.020458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
흡연민원건수단속건수
흡연민원건수1.000-0.249
단속건수-0.2491.000

Missing values

2024-04-17T18:56:12.050152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:56:12.127280image/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

구분흡연민원건수단속건수데이터기준일자
02021-0768152023-07-17
12021-0867162023-07-17
22021-0984282023-07-17
32021-1057342023-07-17
42021-1144272023-07-17
52021-1281192023-07-17
62022-0148222023-07-17
72022-022642023-07-17
82022-036302023-07-17
92022-048002023-07-17
구분흡연민원건수단속건수데이터기준일자
142022-097792023-07-17
152022-1082492023-07-17
162022-1165752023-07-17
172022-1232582023-07-17
182023-0147482023-07-17
192023-0244472023-07-17
202023-03631122023-07-17
212023-0454532023-07-17
222023-0571442023-07-17
232023-06110372023-07-17