Overview

Dataset statistics

Number of variables14
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.8 KiB
Average record size in memory121.3 B

Variable types

DateTime1
Numeric5
Categorical3
Boolean5

Dataset

Description샘플 데이터
Author한국기상산업기술원
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=12dd5eb0-a066-11ee-b38e-6783ddae4cb6

Alerts

연월일 has constant value ""Constant
위도 has constant value ""Constant
경도 has constant value ""Constant
강수유무 has constant value ""Constant
기압QC has constant value ""Constant
기온QC has constant value ""Constant
습도QC has constant value ""Constant
PM2.5QC has constant value ""Constant
시 is highly overall correlated with 기압High correlation
기압 is highly overall correlated with 시High correlation
습도 is highly imbalanced (89.8%)Imbalance
시 has 11 (11.0%) zerosZeros
분 has 2 (2.0%) zerosZeros

Reproduction

Analysis started2024-03-13 11:43:20.966356
Analysis finished2024-03-13 11:43:24.919843
Duration3.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월일
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2023-12-08 00:00:00
Maximum2023-12-08 00:00:00
2024-03-13T20:43:24.973871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:25.056669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.82
Minimum0
Maximum8
Zeros11
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T20:43:25.169306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile8
Maximum8
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4959766
Coefficient of variation (CV)0.65339701
Kurtosis-1.1922646
Mean3.82
Median Absolute Deviation (MAD)2
Skewness0.04615684
Sum382
Variance6.229899
MonotonicityNot monotonic
2024-03-13T20:43:25.279462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 12
12.0%
2 12
12.0%
3 12
12.0%
5 12
12.0%
7 12
12.0%
0 11
11.0%
4 11
11.0%
6 11
11.0%
8 7
7.0%
ValueCountFrequency (%)
0 11
11.0%
1 12
12.0%
2 12
12.0%
3 12
12.0%
4 11
11.0%
5 12
12.0%
6 11
11.0%
7 12
12.0%
8 7
7.0%
ValueCountFrequency (%)
8 7
7.0%
7 12
12.0%
6 11
11.0%
5 12
12.0%
4 11
11.0%
3 12
12.0%
2 12
12.0%
1 12
12.0%
0 11
11.0%

분
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.16
Minimum0
Maximum59
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T20:43:25.406831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q113.75
median27.5
Q343
95-th percentile55
Maximum59
Range59
Interquartile range (IQR)29.25

Descriptive statistics

Standard deviation17.155098
Coefficient of variation (CV)0.60920091
Kurtosis-1.1695705
Mean28.16
Median Absolute Deviation (MAD)14.5
Skewness0.082753204
Sum2816
Variance294.29737
MonotonicityNot monotonic
2024-03-13T20:43:25.548990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55 4
 
4.0%
50 4
 
4.0%
2 3
 
3.0%
7 3
 
3.0%
38 3
 
3.0%
43 3
 
3.0%
27 2
 
2.0%
31 2
 
2.0%
17 2
 
2.0%
22 2
 
2.0%
Other values (50) 72
72.0%
ValueCountFrequency (%)
0 2
2.0%
1 1
 
1.0%
2 3
3.0%
3 2
2.0%
4 1
 
1.0%
5 2
2.0%
6 1
 
1.0%
7 3
3.0%
8 2
2.0%
9 1
 
1.0%
ValueCountFrequency (%)
59 1
 
1.0%
58 1
 
1.0%
57 1
 
1.0%
56 1
 
1.0%
55 4
4.0%
54 1
 
1.0%
53 1
 
1.0%
52 1
 
1.0%
51 1
 
1.0%
50 4
4.0%

위도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
37.466038
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37.466038
2nd row37.466038
3rd row37.466038
4th row37.466038
5th row37.466038

Common Values

ValueCountFrequency (%)
37.466038 100
100.0%

Length

2024-03-13T20:43:25.687638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:43:25.805079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37.466038 100
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
127.119338
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row127.119338
2nd row127.119338
3rd row127.119338
4th row127.119338
5th row127.119338

Common Values

ValueCountFrequency (%)
127.119338 100
100.0%

Length

2024-03-13T20:43:26.152299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:43:26.237337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
127.119338 100
100.0%

기압
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1012.968
Minimum1012.1
Maximum1013.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T20:43:26.323156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1012.1
5-th percentile1012.2
Q11012.4
median1013
Q31013.5
95-th percentile1013.7
Maximum1013.7
Range1.6
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation0.53783704
Coefficient of variation (CV)0.00053095166
Kurtosis-1.5587623
Mean1012.968
Median Absolute Deviation (MAD)0.5
Skewness-0.049522857
Sum101296.8
Variance0.28926869
MonotonicityNot monotonic
2024-03-13T20:43:26.441295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1013.6 13
13.0%
1013.0 13
13.0%
1013.5 13
13.0%
1012.4 12
12.0%
1012.2 9
9.0%
1012.5 8
8.0%
1013.7 8
8.0%
1012.3 5
 
5.0%
1013.4 4
 
4.0%
1013.1 4
 
4.0%
Other values (6) 11
11.0%
ValueCountFrequency (%)
1012.1 1
 
1.0%
1012.2 9
9.0%
1012.3 5
 
5.0%
1012.4 12
12.0%
1012.5 8
8.0%
1012.6 4
 
4.0%
1012.7 1
 
1.0%
1012.8 2
 
2.0%
1012.9 2
 
2.0%
1013.0 13
13.0%
ValueCountFrequency (%)
1013.7 8
8.0%
1013.6 13
13.0%
1013.5 13
13.0%
1013.4 4
 
4.0%
1013.2 1
 
1.0%
1013.1 4
 
4.0%
1013.0 13
13.0%
1012.9 2
 
2.0%
1012.8 2
 
2.0%
1012.7 1
 
1.0%

기온
Real number (ℝ)

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.536
Minimum5.8
Maximum8.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T20:43:26.597532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.8
5-th percentile6.195
Q17.075
median7.6
Q38.2
95-th percentile8.7
Maximum8.9
Range3.1
Interquartile range (IQR)1.125

Descriptive statistics

Standard deviation0.8133383
Coefficient of variation (CV)0.10792706
Kurtosis-0.81955729
Mean7.536
Median Absolute Deviation (MAD)0.6
Skewness-0.30558363
Sum753.6
Variance0.66151919
MonotonicityNot monotonic
2024-03-13T20:43:26.739205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
7.3 9
 
9.0%
7.7 7
 
7.0%
7.8 6
 
6.0%
8.5 5
 
5.0%
8.4 5
 
5.0%
6.5 5
 
5.0%
8.7 4
 
4.0%
7.9 4
 
4.0%
7.6 4
 
4.0%
7.5 4
 
4.0%
Other values (22) 47
47.0%
ValueCountFrequency (%)
5.8 1
 
1.0%
5.9 2
 
2.0%
6.0 1
 
1.0%
6.1 1
 
1.0%
6.2 3
3.0%
6.3 2
 
2.0%
6.4 3
3.0%
6.5 5
5.0%
6.6 2
 
2.0%
6.7 1
 
1.0%
ValueCountFrequency (%)
8.9 1
 
1.0%
8.8 3
3.0%
8.7 4
4.0%
8.6 3
3.0%
8.5 5
5.0%
8.4 5
5.0%
8.3 3
3.0%
8.2 3
3.0%
8.1 2
 
2.0%
8.0 3
3.0%

습도
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
100.0
98 
99.9
 
1
99.1
 
1

Length

Max length5
Median length5
Mean length4.98
Min length4

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row100.0
2nd row100.0
3rd row100.0
4th row100.0
5th row100.0

Common Values

ValueCountFrequency (%)
100.0 98
98.0%
99.9 1
 
1.0%
99.1 1
 
1.0%

Length

2024-03-13T20:43:26.881608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:43:26.980205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100.0 98
98.0%
99.9 1
 
1.0%
99.1 1
 
1.0%

강수유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
100 
ValueCountFrequency (%)
False 100
100.0%
2024-03-13T20:43:27.060653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

PM2.5
Real number (ℝ)

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.06971
Minimum4.804
Maximum10.365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-13T20:43:27.175297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.804
5-th percentile5.13185
Q16.19425
median7.128
Q37.792
95-th percentile8.871
Maximum10.365
Range5.561
Interquartile range (IQR)1.59775

Descriptive statistics

Standard deviation1.1747754
Coefficient of variation (CV)0.16617023
Kurtosis-0.31369696
Mean7.06971
Median Absolute Deviation (MAD)0.664
Skewness-0.0034780692
Sum706.971
Variance1.3800972
MonotonicityNot monotonic
2024-03-13T20:43:27.328043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
7.626 7
 
7.0%
6.713 6
 
6.0%
7.294 4
 
4.0%
5.219 4
 
4.0%
7.709 4
 
4.0%
6.132 4
 
4.0%
7.128 4
 
4.0%
7.377 3
 
3.0%
7.792 3
 
3.0%
7.045 3
 
3.0%
Other values (38) 58
58.0%
ValueCountFrequency (%)
4.804 1
 
1.0%
4.887 2
2.0%
5.053 2
2.0%
5.136 1
 
1.0%
5.219 4
4.0%
5.302 1
 
1.0%
5.385 3
3.0%
5.468 1
 
1.0%
5.634 1
 
1.0%
5.717 1
 
1.0%
ValueCountFrequency (%)
10.365 1
 
1.0%
9.452 1
 
1.0%
9.203 2
2.0%
8.871 3
3.0%
8.705 2
2.0%
8.539 1
 
1.0%
8.456 2
2.0%
8.373 2
2.0%
8.29 1
 
1.0%
8.207 2
2.0%

기압QC
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2024-03-13T20:43:27.432400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

기온QC
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2024-03-13T20:43:27.507087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

습도QC
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2024-03-13T20:43:27.579257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

PM2.5QC
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
True
100 
ValueCountFrequency (%)
True 100
100.0%
2024-03-13T20:43:27.668704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-13T20:43:24.094672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:21.891633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.566089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.037895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.557475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:24.186610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:21.990461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.657505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.144865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.701337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:24.268128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.086140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.744661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.233653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.796231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:24.388951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.375156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.834924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.316403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.904913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:24.487111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.476391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:22.928108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.426740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:43:23.994917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:43:27.745078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시분기압기온습도PM2.5
시1.0000.0000.9630.7740.4870.605
분0.0001.0000.0000.0000.0000.000
기압0.9630.0001.0000.7640.5400.482
기온0.7740.0000.7641.0000.0000.524
습도0.4870.0000.5400.0001.0000.000
PM2.50.6050.0000.4820.5240.0001.000
2024-03-13T20:43:27.862487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시분기압기온PM2.5습도
시1.000-0.084-0.902-0.0760.2240.236
분-0.0841.0000.013-0.129-0.1580.000
기압-0.9020.0131.0000.030-0.2190.273
기온-0.076-0.1290.0301.0000.4730.000
PM2.50.224-0.158-0.2190.4731.0000.000
습도0.2360.0000.2730.0000.0001.000

Missing values

2024-03-13T20:43:24.618826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:43:24.828915image/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

연월일시분위도경도기압기온습도강수유무PM2.5기압QC기온QC습도QCPM2.5QC
02023-12-080837.466038127.1193381013.68.8100.0N7.626YYYY
12023-12-0801337.466038127.1193381013.68.7100.0N6.879YYYY
22023-12-0801837.466038127.1193381013.68.7100.0N7.626YYYY
32023-12-0802337.466038127.1193381013.68.7100.0N7.128YYYY
42023-12-0802837.466038127.1193381013.58.6100.0N7.211YYYY
52023-12-0803337.466038127.1193381013.68.6100.0N9.203YYYY
62023-12-0803837.466038127.1193381013.78.5100.0N7.377YYYY
72023-12-0804337.466038127.1193381013.78.4100.0N7.294YYYY
82023-12-0805037.466038127.1193381013.78.4100.0N7.294YYYY
92023-12-0805537.466038127.1193381013.78.3100.0N8.373YYYY
연월일시분위도경도기압기온습도강수유무PM2.5기압QC기온QC습도QCPM2.5QC
902023-12-0875037.466038127.1193381012.47.8100.0N7.543YYYY
912023-12-0875537.466038127.1193381012.47.8100.0N7.875YYYY
922023-12-088237.466038127.1193381012.58.1100.0N8.705YYYY
932023-12-088737.466038127.1193381012.58.1100.0N9.203YYYY
942023-12-0881237.466038127.1193381012.58.2100.0N8.456YYYY
952023-12-0881737.466038127.1193381012.58.4100.0N7.294YYYY
962023-12-0882237.466038127.1193381012.58.5100.0N7.958YYYY
972023-12-0882737.466038127.1193381012.58.899.9N7.898YYYY
982023-12-0883237.466038127.1193381012.68.999.1N7.003YYYY
992023-12-080337.466038127.1193381013.68.8100.0N7.128YYYY