Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory54.3 B

Variable types

Categorical3
DateTime1
Numeric2

Dataset

Description샘플 데이터
Author순천향대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=92725bd0-4033-11eb-8ff3-e7c20661cf87

Alerts

장비ID has constant value ""Constant
위도 has constant value ""Constant
경도 has constant value ""Constant
초미세먼지값(ug/m3) is highly overall correlated with 미세먼지값(ug/m3)High correlation
미세먼지값(ug/m3) is highly overall correlated with 초미세먼지값(ug/m3)High correlation
데이터발생일시 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:36:57.640119
Analysis finished2023-12-10 12:36:58.585728
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

장비ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
47397
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47397
2nd row47397
3rd row47397
4th row47397
5th row47397

Common Values

ValueCountFrequency (%)
47397 100
100.0%

Length

2023-12-10T21:36:58.681209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:58.812160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47397 100
100.0%

데이터발생일시
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-11-03 17:51:00
Maximum2020-11-03 21:11:00
2023-12-10T21:36:58.960997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:59.172364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
35.171304
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35.171304
2nd row35.171304
3rd row35.171304
4th row35.171304
5th row35.171304

Common Values

ValueCountFrequency (%)
35.171304 100
100.0%

Length

2023-12-10T21:36:59.385430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:59.527709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35.171304 100
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
129.126606
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row129.126606
2nd row129.126606
3rd row129.126606
4th row129.126606
5th row129.126606

Common Values

ValueCountFrequency (%)
129.126606 100
100.0%

Length

2023-12-10T21:36:59.680717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:59.954336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
129.126606 100
100.0%

초미세먼지값(ug/m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.6366
Minimum9.55
Maximum14.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:00.122800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.55
5-th percentile9.7295
Q110.8975
median11.69
Q312.315
95-th percentile13.407
Maximum14.61
Range5.06
Interquartile range (IQR)1.4175

Descriptive statistics

Standard deviation1.0770866
Coefficient of variation (CV)0.092560252
Kurtosis-0.083013003
Mean11.6366
Median Absolute Deviation (MAD)0.71
Skewness0.13206699
Sum1163.66
Variance1.1601156
MonotonicityNot monotonic
2023-12-10T21:37:00.370630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12.14 3
 
3.0%
12.0 2
 
2.0%
11.89 2
 
2.0%
11.56 2
 
2.0%
10.68 1
 
1.0%
10.41 1
 
1.0%
11.77 1
 
1.0%
10.98 1
 
1.0%
10.24 1
 
1.0%
10.51 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
9.55 1
1.0%
9.58 1
1.0%
9.61 1
1.0%
9.62 1
1.0%
9.72 1
1.0%
9.73 1
1.0%
9.83 1
1.0%
9.92 1
1.0%
10.06 1
1.0%
10.23 1
1.0%
ValueCountFrequency (%)
14.61 1
1.0%
14.0 1
1.0%
13.97 1
1.0%
13.92 1
1.0%
13.54 1
1.0%
13.4 1
1.0%
13.36 1
1.0%
13.29 1
1.0%
12.98 1
1.0%
12.83 1
1.0%

미세먼지값(ug/m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.0419
Minimum9.88
Maximum15.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:00.907743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.88
5-th percentile11.019
Q112.2475
median12.96
Q313.98
95-th percentile15.0765
Maximum15.62
Range5.74
Interquartile range (IQR)1.7325

Descriptive statistics

Standard deviation1.2736718
Coefficient of variation (CV)0.097659986
Kurtosis-0.43267009
Mean13.0419
Median Absolute Deviation (MAD)0.815
Skewness-0.067261058
Sum1304.19
Variance1.6222398
MonotonicityNot monotonic
2023-12-10T21:37:01.095434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.61 3
 
3.0%
13.38 2
 
2.0%
14.26 2
 
2.0%
14.53 2
 
2.0%
14.21 2
 
2.0%
12.84 2
 
2.0%
13.63 2
 
2.0%
12.04 2
 
2.0%
13.1 1
 
1.0%
11.27 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
9.88 1
1.0%
10.23 1
1.0%
10.47 1
1.0%
10.71 1
1.0%
11.0 1
1.0%
11.02 1
1.0%
11.14 1
1.0%
11.2 1
1.0%
11.22 1
1.0%
11.27 1
1.0%
ValueCountFrequency (%)
15.62 1
1.0%
15.52 1
1.0%
15.34 1
1.0%
15.25 1
1.0%
15.2 1
1.0%
15.07 1
1.0%
15.06 1
1.0%
14.97 1
1.0%
14.95 1
1.0%
14.85 1
1.0%

Interactions

2023-12-10T21:36:58.064383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.822007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.190300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.948596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:37:01.225285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터발생일시초미세먼지값(ug/m3)미세먼지값(ug/m3)
데이터발생일시1.0001.0001.000
초미세먼지값(ug/m3)1.0001.0000.783
미세먼지값(ug/m3)1.0000.7831.000
2023-12-10T21:37:01.346981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
초미세먼지값(ug/m3)미세먼지값(ug/m3)
초미세먼지값(ug/m3)1.0000.856
미세먼지값(ug/m3)0.8561.000

Missing values

2023-12-10T21:36:58.367174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:58.521446image/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

장비ID데이터발생일시위도경도초미세먼지값(ug/m3)미세먼지값(ug/m3)
0473972020-11-03 17:5335.171304129.12660612.1413.1
1473972020-11-03 17:5535.171304129.12660611.5612.56
2473972020-11-03 17:5735.171304129.12660611.7312.21
3473972020-11-03 17:5935.171304129.12660611.4612.32
4473972020-11-03 18:0135.171304129.12660612.0214.16
5473972020-11-03 18:0335.171304129.12660612.3813.53
6473972020-11-03 18:0535.171304129.12660612.1313.09
7473972020-11-03 18:0735.171304129.12660614.014.66
8473972020-11-03 18:1135.171304129.12660612.7214.95
9473972020-11-03 18:1335.171304129.12660612.814.21
장비ID데이터발생일시위도경도초미세먼지값(ug/m3)미세먼지값(ug/m3)
90473972020-11-03 20:5535.171304129.1266069.7310.23
91473972020-11-03 20:5735.171304129.12660610.3910.71
92473972020-11-03 20:5935.171304129.1266069.8311.37
93473972020-11-03 21:0135.171304129.12660610.2912.78
94473972020-11-03 21:0335.171304129.12660610.711.3
95473972020-11-03 21:0535.171304129.12660611.012.34
96473972020-11-03 21:0735.171304129.1266069.5511.02
97473972020-11-03 21:0935.171304129.12660610.6812.05
98473972020-11-03 21:1135.171304129.12660610.5112.13
99473972020-11-03 17:5135.171304129.12660611.412.4