Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory90.3 B

Variable types

Numeric1
Categorical8
DateTime1

Alerts

노드 아이디 has constant value ""Constant
co 측정값 has constant value ""Constant
PM1.0 측정값 has constant value ""Constant
온도 has constant value ""Constant
co2 측정값 is highly overall correlated with 시퀀스 and 3 other fieldsHigh correlation
습도 is highly overall correlated with 시퀀스 and 3 other fieldsHigh correlation
PM10 측정값 is highly overall correlated with 시퀀스 and 3 other fieldsHigh correlation
PM2.5 측정값 is highly overall correlated with 시퀀스 and 3 other fieldsHigh correlation
시퀀스 is highly overall correlated with co2 측정값 and 3 other fieldsHigh correlation
시퀀스 has unique valuesUnique
기록 시간 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:31:33.217891
Analysis finished2023-12-10 13:31:34.171697
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시퀀스
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2324319.9
Minimum2315013
Maximum2332487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:31:34.309716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2315013
5-th percentile2317252
Q12320380.5
median2324471
Q32328607
95-th percentile2331649.2
Maximum2332487
Range17474
Interquartile range (IQR)8226.5

Descriptive statistics

Standard deviation4780.1454
Coefficient of variation (CV)0.0020565781
Kurtosis-1.1585238
Mean2324319.9
Median Absolute Deviation (MAD)4117
Skewness-0.032220586
Sum2.3243199 × 108
Variance22849790
MonotonicityStrictly increasing
2023-12-10T22:31:34.578386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2315013 1
 
1.0%
2326722 1
 
1.0%
2328589 1
 
1.0%
2328556 1
 
1.0%
2327771 1
 
1.0%
2327568 1
 
1.0%
2327298 1
 
1.0%
2327195 1
 
1.0%
2327149 1
 
1.0%
2327026 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2315013 1
1.0%
2315624 1
1.0%
2316367 1
1.0%
2316619 1
1.0%
2316626 1
1.0%
2317285 1
1.0%
2317367 1
1.0%
2317699 1
1.0%
2317843 1
1.0%
2317961 1
1.0%
ValueCountFrequency (%)
2332487 1
1.0%
2332371 1
1.0%
2332187 1
1.0%
2331790 1
1.0%
2331653 1
1.0%
2331649 1
1.0%
2331357 1
1.0%
2331043 1
1.0%
2330744 1
1.0%
2330617 1
1.0%

노드 아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
201110
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201110
2nd row201110
3rd row201110
4th row201110
5th row201110

Common Values

ValueCountFrequency (%)
201110 100
100.0%

Length

2023-12-10T22:31:34.889753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:35.059227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201110 100
100.0%

co 측정값
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.5
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.5
2nd row0.5
3rd row0.5
4th row0.5
5th row0.5

Common Values

ValueCountFrequency (%)
0.5 100
100.0%

Length

2023-12-10T22:31:35.216664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:35.385015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.5 100
100.0%

co2 측정값
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
447
30 
446
21 
450
21 
442
19 
444
9 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row442
2nd row442
3rd row442
4th row442
5th row442

Common Values

ValueCountFrequency (%)
447 30
30.0%
446 21
21.0%
450 21
21.0%
442 19
19.0%
444 9
 
9.0%

Length

2023-12-10T22:31:35.540889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:35.768082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
447 30
30.0%
446 21
21.0%
450 21
21.0%
442 19
19.0%
444 9
 
9.0%

PM1.0 측정값
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 100
100.0%

Length

2023-12-10T22:31:35.959077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:36.110817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 100
100.0%

PM2.5 측정값
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
8
42 
7
39 
9
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
8 42
42.0%
7 39
39.0%
9 19
19.0%

Length

2023-12-10T22:31:36.264844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:36.442431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 42
42.0%
7 39
39.0%
9 19
19.0%

PM10 측정값
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
9
40 
7
39 
10
21 

Length

Max length2
Median length1
Mean length1.21
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 40
40.0%
7 39
39.0%
10 21
21.0%

Length

2023-12-10T22:31:36.606431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:36.788172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 40
40.0%
7 39
39.0%
10 21
21.0%

온도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
25.899999619
100 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row25.899999619
2nd row25.899999619
3rd row25.899999619
4th row25.899999619
5th row25.899999619

Common Values

ValueCountFrequency (%)
25.899999619 100
100.0%

Length

2023-12-10T22:31:36.946907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:37.106931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
25.899999619 100
100.0%

습도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
81.300003052
49 
80.900001526
30 
81.0
21 

Length

Max length12
Median length12
Mean length10.32
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row81.300003052
2nd row81.300003052
3rd row81.300003052
4th row81.300003052
5th row81.300003052

Common Values

ValueCountFrequency (%)
81.300003052 49
49.0%
80.900001526 30
30.0%
81.0 21
21.0%

Length

2023-12-10T22:31:37.366246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:37.548035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
81.300003052 49
49.0%
80.900001526 30
30.0%
81.0 21
21.0%

기록 시간
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2022-09-01 08:00:06
Maximum2022-09-01 08:03:48
2023-12-10T22:31:37.894970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:31:38.206501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-10T22:31:33.629650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:31:38.808991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시퀀스co2 측정값PM2.5 측정값PM10 측정값습도기록 시간
시퀀스1.0000.9790.8850.8400.9071.000
co2 측정값0.9791.0001.0001.0001.0001.000
PM2.5 측정값0.8851.0001.0000.9680.8991.000
PM10 측정값0.8401.0000.9681.0000.9321.000
습도0.9071.0000.8990.9321.0001.000
기록 시간1.0001.0001.0001.0001.0001.000
2023-12-10T22:31:39.016142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
co2 측정값습도PM10 측정값PM2.5 측정값
co2 측정값1.0000.9900.9900.990
습도0.9901.0000.6810.613
PM10 측정값0.9900.6811.0000.782
PM2.5 측정값0.9900.6130.7821.000
2023-12-10T22:31:39.181680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시퀀스co2 측정값PM2.5 측정값PM10 측정값습도
시퀀스1.0000.7740.7980.7260.833
co2 측정값0.7741.0000.9900.9900.990
PM2.5 측정값0.7980.9901.0000.7820.613
PM10 측정값0.7260.9900.7821.0000.681
습도0.8330.9900.6130.6811.000

Missing values

2023-12-10T22:31:33.842675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:31:34.079265image/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

시퀀스노드 아이디co 측정값co2 측정값PM1.0 측정값PM2.5 측정값PM10 측정값온도습도기록 시간
023150132011100.544259925.981.3000032022-09-01 08:00:12
123156242011100.544259925.981.3000032022-09-01 08:00:06
223163672011100.544259925.981.3000032022-09-01 08:00:10
323166192011100.544259925.981.3000032022-09-01 08:00:24
423166262011100.544259925.981.3000032022-09-01 08:00:08
523172852011100.544259925.981.3000032022-09-01 08:00:20
623173672011100.544259925.981.3000032022-09-01 08:00:30
723176992011100.544259925.981.3000032022-09-01 08:00:14
823178432011100.544259925.981.3000032022-09-01 08:00:26
923179612011100.544259925.981.3000032022-09-01 08:00:44
시퀀스노드 아이디co 측정값co2 측정값PM1.0 측정값PM2.5 측정값PM10 측정값온도습도기록 시간
9023306172011100.5450581025.980.9000022022-09-01 08:03:13
9123307442011100.5450581025.980.9000022022-09-01 08:03:11
9223310432011100.544457725.980.9000022022-09-01 08:03:31
9323313572011100.544457725.980.9000022022-09-01 08:03:37
9423316492011100.544457725.980.9000022022-09-01 08:03:35
9523316532011100.5450581025.980.9000022022-09-01 08:02:43
9623317902011100.544457725.980.9000022022-09-01 08:03:23
9723321872011100.544457725.980.9000022022-09-01 08:03:41
9823323712011100.544457725.980.9000022022-09-01 08:03:48
9923324872011100.544457725.980.9000022022-09-01 08:03:43