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=9254db00-402e-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 12:27:12.818592
Analysis finished2023-12-10 12:27:14.087687
Duration1.27 second
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
64981
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row64981
2nd row64981
3rd row64981
4th row64981
5th row64981

Common Values

ValueCountFrequency (%)
64981 100
100.0%

Length

2023-12-10T21:27:14.189715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:27:14.329977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
64981 100
100.0%

데이터발생일시
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-10-19 11:26:00
Maximum2020-10-19 14:44:00
2023-12-10T21:27:14.483969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:27:14.690326image/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
36.730002
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row36.730002
2nd row36.730002
3rd row36.730002
4th row36.730002
5th row36.730002

Common Values

ValueCountFrequency (%)
36.730002 100
100.0%

Length

2023-12-10T21:27:14.891870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:27:15.044283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
36.730002 100
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
127.013929
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row127.013929
2nd row127.013929
3rd row127.013929
4th row127.013929
5th row127.013929

Common Values

ValueCountFrequency (%)
127.013929 100
100.0%

Length

2023-12-10T21:27:15.186982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:27:15.327045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
127.013929 100
100.0%

초미세먼지값(ug/m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.828
Minimum54.09
Maximum74.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:27:15.509362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54.09
5-th percentile58.0355
Q162.7
median66.615
Q369.18
95-th percentile71.793
Maximum74.98
Range20.89
Interquartile range (IQR)6.48

Descriptive statistics

Standard deviation4.4770434
Coefficient of variation (CV)0.068011232
Kurtosis-0.47762019
Mean65.828
Median Absolute Deviation (MAD)3.165
Skewness-0.47085274
Sum6582.8
Variance20.043917
MonotonicityNot monotonic
2023-12-10T21:27:15.784538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67.17 2
 
2.0%
66.04 2
 
2.0%
70.63 2
 
2.0%
63.45 2
 
2.0%
71.78 2
 
2.0%
66.93 1
 
1.0%
72.07 1
 
1.0%
69.15 1
 
1.0%
62.84 1
 
1.0%
66.62 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
54.09 1
1.0%
56.17 1
1.0%
56.3 1
1.0%
56.87 1
1.0%
57.0 1
1.0%
58.09 1
1.0%
58.38 1
1.0%
58.6 1
1.0%
58.93 1
1.0%
58.96 1
1.0%
ValueCountFrequency (%)
74.98 1
1.0%
72.36 1
1.0%
72.16 1
1.0%
72.07 1
1.0%
72.04 1
1.0%
71.78 2
2.0%
71.63 1
1.0%
71.58 1
1.0%
71.5 1
1.0%
71.16 1
1.0%

미세먼지값(ug/m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.6102
Minimum64.07
Maximum87.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:27:16.479038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum64.07
5-th percentile67.0155
Q172.4925
median77.445
Q381.1325
95-th percentile83.409
Maximum87.3
Range23.23
Interquartile range (IQR)8.64

Descriptive statistics

Standard deviation5.3923929
Coefficient of variation (CV)0.070387401
Kurtosis-0.68097677
Mean76.6102
Median Absolute Deviation (MAD)3.98
Skewness-0.4083925
Sum7661.02
Variance29.077901
MonotonicityNot monotonic
2023-12-10T21:27:16.837525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
81.12 2
 
2.0%
75.09 2
 
2.0%
76.65 1
 
1.0%
75.44 1
 
1.0%
73.44 1
 
1.0%
77.16 1
 
1.0%
83.96 1
 
1.0%
77.76 1
 
1.0%
82.53 1
 
1.0%
72.62 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
64.07 1
1.0%
65.23 1
1.0%
65.39 1
1.0%
65.4 1
1.0%
66.93 1
1.0%
67.02 1
1.0%
67.49 1
1.0%
68.4 1
1.0%
68.62 1
1.0%
68.85 1
1.0%
ValueCountFrequency (%)
87.3 1
1.0%
86.96 1
1.0%
84.57 1
1.0%
84.29 1
1.0%
83.96 1
1.0%
83.38 1
1.0%
83.2 1
1.0%
83.02 1
1.0%
82.86 1
1.0%
82.53 1
1.0%

Interactions

2023-12-10T21:27:13.361460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:27:13.112558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:27:13.528032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:27:13.239350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:27:17.023678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터발생일시초미세먼지값(ug/m3)미세먼지값(ug/m3)
데이터발생일시1.0001.0001.000
초미세먼지값(ug/m3)1.0001.0000.926
미세먼지값(ug/m3)1.0000.9261.000
2023-12-10T21:27:17.183893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
초미세먼지값(ug/m3)미세먼지값(ug/m3)
초미세먼지값(ug/m3)1.0000.945
미세먼지값(ug/m3)0.9451.000

Missing values

2023-12-10T21:27:13.722216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:27:13.953383image/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)
0649812020-10-19 11:2836.730002127.01392967.1776.65
1649812020-10-19 11:3036.730002127.01392966.2776.06
2649812020-10-19 11:3236.730002127.01392972.1681.93
3649812020-10-19 11:3436.730002127.01392972.3682.33
4649812020-10-19 11:3636.730002127.01392968.1379.37
5649812020-10-19 11:3836.730002127.01392971.1681.75
6649812020-10-19 11:4036.730002127.01392968.0778.61
7649812020-10-19 11:4236.730002127.01392966.576.95
8649812020-10-19 11:4436.730002127.01392970.1984.57
9649812020-10-19 11:4636.730002127.01392969.6883.02
장비ID데이터발생일시위도경도초미세먼지값(ug/m3)미세먼지값(ug/m3)
90649812020-10-19 14:2836.730002127.01392971.7880.24
91649812020-10-19 14:3036.730002127.01392971.5881.89
92649812020-10-19 14:3236.730002127.01392969.5677.32
93649812020-10-19 14:3436.730002127.01392967.8876.68
94649812020-10-19 14:3636.730002127.01392974.9886.96
95649812020-10-19 14:3836.730002127.01392967.1777.84
96649812020-10-19 14:4036.730002127.01392961.9369.73
97649812020-10-19 14:4236.730002127.01392960.8968.4
98649812020-10-19 14:4436.730002127.01392965.9675.09
99649812020-10-19 11:2636.730002127.01392965.1975.02