Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory53.3 B

Variable types

Categorical3
DateTime1
Numeric2

Dataset

Description샘플 데이터
Author순천향대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=a7b2c560-49a3-11eb-8ff3-e7c20661cf87

Alerts

기기 ID has constant value ""Constant
위도 has constant value ""Constant
경도 has constant value ""Constant
미세먼지 is highly overall correlated with 초미세먼지High correlation
초미세먼지 is highly overall correlated with 미세먼지High correlation
데이터 측정 일시 has unique valuesUnique
미세먼지 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:11:23.254140
Analysis finished2023-12-10 13:11:24.244143
Duration0.99 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
1911KT149
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1911KT149
2nd row1911KT149
3rd row1911KT149
4th row1911KT149
5th row1911KT149

Common Values

ValueCountFrequency (%)
1911KT149 100
100.0%

Length

2023-12-10T22:11:24.342999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:11:24.453779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1911kt149 100
100.0%

데이터 측정 일시
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-03-01 00:00:00
Maximum2020-03-05 03:00:00
2023-12-10T22:11:24.573227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:11:24.780474image/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
37.53785
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37.53785
2nd row37.53785
3rd row37.53785
4th row37.53785
5th row37.53785

Common Values

ValueCountFrequency (%)
37.53785 100
100.0%

Length

2023-12-10T22:11:24.986569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:11:25.144245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37.53785 100
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
126.986885
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row126.986885
2nd row126.986885
3rd row126.986885
4th row126.986885
5th row126.986885

Common Values

ValueCountFrequency (%)
126.986885 100
100.0%

Length

2023-12-10T22:11:25.289951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:11:25.778583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
126.986885 100
100.0%

미세먼지
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5476
Minimum13.45
Maximum75.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:11:25.954259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.45
5-th percentile17.495
Q127.9375
median40.305
Q348.1525
95-th percentile67.873
Maximum75.75
Range62.3
Interquartile range (IQR)20.215

Descriptive statistics

Standard deviation15.221748
Coefficient of variation (CV)0.37540442
Kurtosis-0.61299048
Mean40.5476
Median Absolute Deviation (MAD)11.505
Skewness0.33989372
Sum4054.76
Variance231.70162
MonotonicityNot monotonic
2023-12-10T22:11:26.262139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.0 1
 
1.0%
71.92 1
 
1.0%
18.69 1
 
1.0%
15.36 1
 
1.0%
17.54 1
 
1.0%
16.64 1
 
1.0%
14.13 1
 
1.0%
13.45 1
 
1.0%
16.32 1
 
1.0%
29.34 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
13.45 1
1.0%
14.13 1
1.0%
15.36 1
1.0%
16.32 1
1.0%
16.64 1
1.0%
17.54 1
1.0%
18.69 1
1.0%
22.13 1
1.0%
22.66 1
1.0%
23.0 1
1.0%
ValueCountFrequency (%)
75.75 1
1.0%
71.92 1
1.0%
70.37 1
1.0%
68.68 1
1.0%
67.93 1
1.0%
67.87 1
1.0%
67.31 1
1.0%
66.51 1
1.0%
65.74 1
1.0%
65.47 1
1.0%

초미세먼지
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.8943
Minimum17.04
Maximum94.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:11:26.550486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.04
5-th percentile21.9835
Q135.01
median50.48
Q360.47
95-th percentile85.007
Maximum94.65
Range77.61
Interquartile range (IQR)25.46

Descriptive statistics

Standard deviation19.076329
Coefficient of variation (CV)0.37482251
Kurtosis-0.61599821
Mean50.8943
Median Absolute Deviation (MAD)14.425
Skewness0.33882033
Sum5089.43
Variance363.90634
MonotonicityNot monotonic
2023-12-10T22:11:26.813223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54.54 2
 
2.0%
28.74 1
 
1.0%
62.95 1
 
1.0%
23.47 1
 
1.0%
19.28 1
 
1.0%
22.04 1
 
1.0%
20.91 1
 
1.0%
17.81 1
 
1.0%
17.04 1
 
1.0%
20.64 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
17.04 1
1.0%
17.81 1
1.0%
19.28 1
1.0%
20.64 1
1.0%
20.91 1
1.0%
22.04 1
1.0%
23.47 1
1.0%
27.9 1
1.0%
28.55 1
1.0%
28.74 1
1.0%
ValueCountFrequency (%)
94.65 1
1.0%
89.88 1
1.0%
88.53 1
1.0%
86.58 1
1.0%
85.14 1
1.0%
85.0 1
1.0%
84.71 1
1.0%
83.79 1
1.0%
82.75 1
1.0%
82.3 1
1.0%

Interactions

2023-12-10T22:11:23.714800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:11:23.457172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:11:23.853153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:11:23.590250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:11:26.987695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터 측정 일시미세먼지초미세먼지
데이터 측정 일시1.0001.0001.000
미세먼지1.0001.0001.000
초미세먼지1.0001.0001.000
2023-12-10T22:11:27.116910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지초미세먼지
미세먼지1.0001.000
초미세먼지1.0001.000

Missing values

2023-12-10T22:11:24.045623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:11:24.187605image/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 측정 일시위도경도미세먼지초미세먼지
01911KT1492020-03-01 01:00:0037.53785126.98688523.028.74
11911KT1492020-03-01 02:00:0037.53785126.98688524.0630.05
21911KT1492020-03-01 03:00:0037.53785126.98688528.5835.64
31911KT1492020-03-01 04:00:0037.53785126.98688535.9544.79
41911KT1492020-03-01 05:00:0037.53785126.98688540.3250.32
51911KT1492020-03-01 06:00:0037.53785126.98688547.9860.1
61911KT1492020-03-01 07:00:0037.53785126.98688570.3788.53
71911KT1492020-03-01 08:00:0037.53785126.98688565.7482.3
81911KT1492020-03-01 09:00:0037.53785126.98688547.0158.62
91911KT1492020-03-01 10:00:0037.53785126.98688543.0153.55
기기 ID데이터 측정 일시위도경도미세먼지초미세먼지
901911KT1492020-03-04 19:00:0037.53785126.98688554.4668.54
911911KT1492020-03-04 20:00:0037.53785126.98688553.3267.11
921911KT1492020-03-04 21:00:0037.53785126.98688554.9769.06
931911KT1492020-03-04 22:00:0037.53785126.98688554.7268.76
941911KT1492020-03-04 23:00:0037.53785126.98688545.2956.96
951911KT1492020-03-05 00:00:0037.53785126.98688542.1953.02
961911KT1492020-03-05 01:00:0037.53785126.98688540.9751.42
971911KT1492020-03-05 02:00:0037.53785126.98688539.7949.89
981911KT1492020-03-05 03:00:0037.53785126.98688542.0152.69
991911KT1492020-03-01 00:00:0037.53785126.98688523.7529.74