Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory81.3 B

Variable types

Categorical3
DateTime1
Numeric5

Dataset

Description샘플 데이터
Author순천향대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=f84f1050-31ee-11ea-ad66-1b2f93f3f455

Alerts

기기 ID has constant value ""Constant
위도 has constant value ""Constant
경도 has constant value ""Constant
온도 is highly overall correlated with 이산화탄소 and 1 other fieldsHigh correlation
소음 is highly overall correlated with 이산화탄소 and 1 other fieldsHigh correlation
이산화탄소 is highly overall correlated with 온도 and 2 other fieldsHigh correlation
휘발성유기화학물질 is highly overall correlated with 온도 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 10:21:16.328635
Analysis finished2023-12-10 10:21:23.568149
Duration7.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기기 ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1060
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1060
2nd row1060
3rd row1060
4th row1060
5th row1060

Common Values

ValueCountFrequency (%)
1060 100
100.0%

Length

2023-12-10T19:21:23.672838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:21:23.836700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1060 100
100.0%

데이터 발생 일시
Date

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-09 10:27:00
Maximum2020-01-09 12:36:00
2023-12-10T19:21:24.123772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:24.353394image/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
37.53417
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37.53417
2nd row37.53417
3rd row37.53417
4th row37.53417
5th row37.53417

Common Values

ValueCountFrequency (%)
37.53417 100
100.0%

Length

2023-12-10T19:21:24.593821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:21:24.751266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37.53417 100
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
127.00438
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row127.00438
2nd row127.00438
3rd row127.00438
4th row127.00438
5th row127.00438

Common Values

ValueCountFrequency (%)
127.00438 100
100.0%

Length

2023-12-10T19:21:24.904043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:21:25.054665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
127.00438 100
100.0%

온도
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.711
Minimum14.1
Maximum21.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:21:25.295425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.1
5-th percentile15.475
Q117.3
median19.1
Q320.125
95-th percentile21
Maximum21.3
Range7.2
Interquartile range (IQR)2.825

Descriptive statistics

Standard deviation1.8403938
Coefficient of variation (CV)0.098358925
Kurtosis-0.41705234
Mean18.711
Median Absolute Deviation (MAD)1.5
Skewness-0.5697802
Sum1871.1
Variance3.3870495
MonotonicityNot monotonic
2023-12-10T19:21:25.575557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.0 7
 
7.0%
16.9 6
 
6.0%
20.9 4
 
4.0%
19.7 4
 
4.0%
20.1 4
 
4.0%
17.5 3
 
3.0%
21.1 3
 
3.0%
17.3 3
 
3.0%
19.1 3
 
3.0%
20.0 3
 
3.0%
Other values (40) 60
60.0%
ValueCountFrequency (%)
14.1 2
2.0%
14.4 1
1.0%
14.5 1
1.0%
15.0 1
1.0%
15.5 1
1.0%
15.6 1
1.0%
15.8 1
1.0%
16.0 1
1.0%
16.4 1
1.0%
16.6 1
1.0%
ValueCountFrequency (%)
21.3 1
 
1.0%
21.1 3
3.0%
21.0 7
7.0%
20.9 4
4.0%
20.8 2
 
2.0%
20.7 2
 
2.0%
20.6 1
 
1.0%
20.5 2
 
2.0%
20.4 1
 
1.0%
20.2 2
 
2.0%

습도
Real number (ℝ)

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.853
Minimum29.3
Maximum47.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:21:25.846103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29.3
5-th percentile29.7
Q136.4
median37.9
Q338.5
95-th percentile42.745
Maximum47.5
Range18.2
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation4.3229819
Coefficient of variation (CV)0.11730339
Kurtosis-0.099016954
Mean36.853
Median Absolute Deviation (MAD)0.95
Skewness-0.24943432
Sum3685.3
Variance18.688173
MonotonicityNot monotonic
2023-12-10T19:21:26.098413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.0 7
 
7.0%
37.9 7
 
7.0%
37.8 6
 
6.0%
37.7 4
 
4.0%
38.1 4
 
4.0%
30.2 3
 
3.0%
29.7 3
 
3.0%
38.4 3
 
3.0%
38.2 3
 
3.0%
38.5 3
 
3.0%
Other values (46) 57
57.0%
ValueCountFrequency (%)
29.3 1
 
1.0%
29.5 1
 
1.0%
29.6 2
2.0%
29.7 3
3.0%
29.8 2
2.0%
29.9 1
 
1.0%
30.0 1
 
1.0%
30.1 2
2.0%
30.2 3
3.0%
30.3 2
2.0%
ValueCountFrequency (%)
47.5 1
1.0%
47.1 1
1.0%
46.9 1
1.0%
45.5 1
1.0%
43.6 1
1.0%
42.7 1
1.0%
41.9 1
1.0%
41.8 1
1.0%
41.4 2
2.0%
41.1 1
1.0%

소음
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.154
Minimum51.3
Maximum68.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:21:26.338521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.3
5-th percentile52.495
Q156.075
median59.65
Q362.8
95-th percentile65.51
Maximum68.5
Range17.2
Interquartile range (IQR)6.725

Descriptive statistics

Standard deviation4.2571727
Coefficient of variation (CV)0.071967621
Kurtosis-0.97582287
Mean59.154
Median Absolute Deviation (MAD)3.4
Skewness-0.11436061
Sum5915.4
Variance18.123519
MonotonicityNot monotonic
2023-12-10T19:21:26.610566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52.7 6
 
6.0%
63.6 4
 
4.0%
62.4 4
 
4.0%
63.1 3
 
3.0%
56.2 3
 
3.0%
62.8 3
 
3.0%
55.6 3
 
3.0%
52.4 3
 
3.0%
58.1 3
 
3.0%
60.0 2
 
2.0%
Other values (51) 66
66.0%
ValueCountFrequency (%)
51.3 2
 
2.0%
52.4 3
3.0%
52.5 2
 
2.0%
52.7 6
6.0%
52.8 1
 
1.0%
53.1 2
 
2.0%
53.6 1
 
1.0%
55.3 1
 
1.0%
55.6 3
3.0%
55.7 2
 
2.0%
ValueCountFrequency (%)
68.5 1
1.0%
67.0 1
1.0%
66.5 1
1.0%
65.9 1
1.0%
65.7 1
1.0%
65.5 1
1.0%
65.4 1
1.0%
65.1 1
1.0%
64.2 2
2.0%
63.9 1
1.0%

이산화탄소
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean615.69
Minimum412
Maximum931
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:21:26.865976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum412
5-th percentile418.85
Q1543.5
median584.5
Q3692.75
95-th percentile894.25
Maximum931
Range519
Interquartile range (IQR)149.25

Descriptive statistics

Standard deviation136.92951
Coefficient of variation (CV)0.22240009
Kurtosis-0.32120271
Mean615.69
Median Absolute Deviation (MAD)72
Skewness0.56273322
Sum61569
Variance18749.691
MonotonicityNot monotonic
2023-12-10T19:21:27.100366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
561 7
 
7.0%
559 3
 
3.0%
751 2
 
2.0%
528 2
 
2.0%
563 2
 
2.0%
571 2
 
2.0%
552 2
 
2.0%
529 2
 
2.0%
554 2
 
2.0%
601 2
 
2.0%
Other values (72) 74
74.0%
ValueCountFrequency (%)
412 1
1.0%
413 1
1.0%
415 2
2.0%
416 1
1.0%
419 1
1.0%
420 1
1.0%
421 1
1.0%
426 1
1.0%
428 1
1.0%
434 2
2.0%
ValueCountFrequency (%)
931 1
1.0%
923 1
1.0%
919 1
1.0%
904 1
1.0%
899 1
1.0%
894 1
1.0%
868 1
1.0%
850 1
1.0%
847 1
1.0%
846 1
1.0%

휘발성유기화학물질
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.22
Minimum20
Maximum192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:21:27.585963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q120
median21
Q362
95-th percentile161.75
Maximum192
Range172
Interquartile range (IQR)42

Descriptive statistics

Standard deviation49.658751
Coefficient of variation (CV)0.95095271
Kurtosis1.3344983
Mean52.22
Median Absolute Deviation (MAD)1
Skewness1.5983269
Sum5222
Variance2465.9915
MonotonicityNot monotonic
2023-12-10T19:21:27.840269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
20 49
49.0%
21 3
 
3.0%
95 2
 
2.0%
56 2
 
2.0%
64 2
 
2.0%
62 2
 
2.0%
124 1
 
1.0%
57 1
 
1.0%
33 1
 
1.0%
39 1
 
1.0%
Other values (36) 36
36.0%
ValueCountFrequency (%)
20 49
49.0%
21 3
 
3.0%
22 1
 
1.0%
24 1
 
1.0%
31 1
 
1.0%
32 1
 
1.0%
33 1
 
1.0%
34 1
 
1.0%
36 1
 
1.0%
38 1
 
1.0%
ValueCountFrequency (%)
192 1
1.0%
188 1
1.0%
185 1
1.0%
183 1
1.0%
176 1
1.0%
161 1
1.0%
160 1
1.0%
157 1
1.0%
155 1
1.0%
151 1
1.0%

Interactions

2023-12-10T19:21:22.384008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:18.682638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:19.642490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.501107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:21.313831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:22.565013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:18.972783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:19.831238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.673290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:21.465484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:22.733942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:19.144987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.025826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.833293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:21.624287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:22.869765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:19.326699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.181944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:21.000156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:22.055669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:23.011920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:19.480138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:20.331022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:21.162733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:21:22.228436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:21:28.015759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터 발생 일시온도습도소음이산화탄소휘발성유기화학물질
데이터 발생 일시1.0000.9950.9800.9120.9990.764
온도0.9951.0000.8370.6600.8640.704
습도0.9800.8371.0000.6120.6820.480
소음0.9120.6600.6121.0000.7660.440
이산화탄소0.9990.8640.6820.7661.0000.873
휘발성유기화학물질0.7640.7040.4800.4400.8731.000
2023-12-10T19:21:28.186840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도습도소음이산화탄소휘발성유기화학물질
온도1.000-0.2730.3990.8460.874
습도-0.2731.0000.3910.184-0.010
소음0.3990.3911.0000.6210.513
이산화탄소0.8460.1840.6211.0000.908
휘발성유기화학물질0.874-0.0100.5130.9081.000

Missing values

2023-12-10T19:21:23.243797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:21:23.476514image/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

기기 ID데이터 발생 일시위도경도온도습도소음이산화탄소휘발성유기화학물질
010602020-01-09 11:5037.53417127.0043820.937.758.1786124
110602020-01-09 12:3437.53417127.0043816.930.155.641520
210602020-01-09 11:0737.53417127.0043819.138.560.659636
310602020-01-09 11:4837.53417127.0043820.737.664.2764104
410602020-01-09 12:1537.53417127.0043818.829.852.849920
510602020-01-09 12:3337.53417127.0043817.130.355.741320
610602020-01-09 10:4637.53417127.0043817.040.756.456120
710602020-01-09 11:0537.53417127.0043819.138.359.759124
810602020-01-09 11:2837.53417127.0043820.037.863.665659
910602020-01-09 11:4737.53417127.0043820.937.062.475795
기기 ID데이터 발생 일시위도경도온도습도소음이산화탄소휘발성유기화학물질
9010602020-01-09 11:3837.53417127.0043820.537.868.572460
9110602020-01-09 11:4037.53417127.0043820.737.163.175183
9210602020-01-09 11:4237.53417127.0043820.536.663.674776
9310602020-01-09 11:4337.53417127.0043820.636.165.574186
9410602020-01-09 11:5237.53417127.0043821.037.858.1808149
9510602020-01-09 11:5337.53417127.0043821.037.758.1821155
9610602020-01-09 11:5637.53417127.0043821.037.658.7846161
9710602020-01-09 11:5637.53417127.0043821.037.757.8847142
9810602020-01-09 12:3637.53417127.0043816.930.155.642020
9910602020-01-09 12:3537.53417127.0043816.930.255.741220