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

Categorical4
Numeric5

Dataset

Description샘플 데이터
Author세종대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=7989edb0-31dc-11ea-923b-5be5436fc479

Alerts

그리드 번호 has constant value ""Constant
국가 코드 has constant value ""Constant
위도(°) has constant value ""Constant
경도(°) has constant value ""Constant
전망 일 is highly overall correlated with 최대 온도(℃) and 1 other fieldsHigh correlation
최대 온도(℃) is highly overall correlated with 전망 일 and 1 other fieldsHigh correlation
최저 온도(℃) is highly overall correlated with 전망 일 and 1 other fieldsHigh correlation
전망 일 has unique valuesUnique
강수 량(mm) has 34 (34.0%) zerosZeros

Reproduction

Analysis started2023-12-10 11:37:52.566678
Analysis finished2023-12-10 11:37:57.406472
Duration4.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

그리드 번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
10137
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10137
2nd row10137
3rd row10137
4th row10137
5th row10137

Common Values

ValueCountFrequency (%)
10137 100
100.0%

Length

2023-12-10T20:37:57.523056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:37:57.677121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10137 100
100.0%

전망 일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20050235
Minimum20050101
Maximum20050410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:37:57.859435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050101
5-th percentile20050106
Q120050126
median20050220
Q320050316
95-th percentile20050405
Maximum20050410
Range309
Interquartile range (IQR)190.5

Descriptive statistics

Standard deviation98.046521
Coefficient of variation (CV)4.8900436 × 10-6
Kurtosis-1.1930186
Mean20050235
Median Absolute Deviation (MAD)95.5
Skewness0.15908349
Sum2.0050235 × 109
Variance9613.1203
MonotonicityStrictly increasing
2023-12-10T20:37:58.115809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050101 1
 
1.0%
20050306 1
 
1.0%
20050316 1
 
1.0%
20050315 1
 
1.0%
20050314 1
 
1.0%
20050313 1
 
1.0%
20050312 1
 
1.0%
20050311 1
 
1.0%
20050310 1
 
1.0%
20050309 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
20050101 1
1.0%
20050102 1
1.0%
20050103 1
1.0%
20050104 1
1.0%
20050105 1
1.0%
20050106 1
1.0%
20050107 1
1.0%
20050108 1
1.0%
20050109 1
1.0%
20050110 1
1.0%
ValueCountFrequency (%)
20050410 1
1.0%
20050409 1
1.0%
20050408 1
1.0%
20050407 1
1.0%
20050406 1
1.0%
20050405 1
1.0%
20050404 1
1.0%
20050403 1
1.0%
20050402 1
1.0%
20050401 1
1.0%

국가 코드
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BG 100
100.0%

Length

2023-12-10T20:37:58.330238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:37:58.486320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bg 100
100.0%

위도(°)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
26.75
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26.75
2nd row26.75
3rd row26.75
4th row26.75
5th row26.75

Common Values

ValueCountFrequency (%)
26.75 100
100.0%

Length

2023-12-10T20:37:58.637657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:37:58.848962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26.75 100
100.0%

경도(°)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
88.25
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row88.25
2nd row88.25
3rd row88.25
4th row88.25
5th row88.25

Common Values

ValueCountFrequency (%)
88.25 100
100.0%

Length

2023-12-10T20:37:59.007612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:37:59.138393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
88.25 100
100.0%

강수 량(mm)
Real number (ℝ)

ZEROS 

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2539
Minimum0
Maximum19.78
Zeros34
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:37:59.356467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.07
Q30.49
95-th percentile7.625
Maximum19.78
Range19.78
Interquartile range (IQR)0.49

Descriptive statistics

Standard deviation3.0622161
Coefficient of variation (CV)2.4421534
Kurtosis15.39996
Mean1.2539
Median Absolute Deviation (MAD)0.07
Skewness3.6203894
Sum125.39
Variance9.3771675
MonotonicityNot monotonic
2023-12-10T20:37:59.624818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
34.0%
0.01 8
 
8.0%
0.22 2
 
2.0%
0.19 2
 
2.0%
0.04 2
 
2.0%
0.24 2
 
2.0%
0.16 2
 
2.0%
0.12 2
 
2.0%
0.05 2
 
2.0%
0.26 2
 
2.0%
Other values (41) 42
42.0%
ValueCountFrequency (%)
0.0 34
34.0%
0.01 8
 
8.0%
0.02 1
 
1.0%
0.03 2
 
2.0%
0.04 2
 
2.0%
0.05 2
 
2.0%
0.06 1
 
1.0%
0.08 1
 
1.0%
0.09 1
 
1.0%
0.12 2
 
2.0%
ValueCountFrequency (%)
19.78 1
1.0%
11.88 1
1.0%
11.07 1
1.0%
9.37 1
1.0%
8.48 1
1.0%
7.58 1
1.0%
7.39 1
1.0%
6.53 1
1.0%
6.14 1
1.0%
3.89 1
1.0%

최대 온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.1327
Minimum16.8
Maximum32.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:37:59.907988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.8
5-th percentile19.162
Q120.96
median23.155
Q327.715
95-th percentile29.6585
Maximum32.73
Range15.93
Interquartile range (IQR)6.755

Descriptive statistics

Standard deviation3.7490305
Coefficient of variation (CV)0.15535065
Kurtosis-1.1624156
Mean24.1327
Median Absolute Deviation (MAD)3
Skewness0.27346261
Sum2413.27
Variance14.05523
MonotonicityNot monotonic
2023-12-10T20:38:00.175050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.55 2
 
2.0%
20.2 2
 
2.0%
25.29 1
 
1.0%
29.19 1
 
1.0%
31.54 1
 
1.0%
28.83 1
 
1.0%
30.11 1
 
1.0%
25.91 1
 
1.0%
29.6 1
 
1.0%
29.2 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
16.8 1
1.0%
18.42 1
1.0%
18.47 1
1.0%
18.86 1
1.0%
19.01 1
1.0%
19.17 1
1.0%
19.25 1
1.0%
19.58 1
1.0%
19.67 1
1.0%
19.81 1
1.0%
ValueCountFrequency (%)
32.73 1
1.0%
31.54 1
1.0%
30.11 1
1.0%
30.02 1
1.0%
30.01 1
1.0%
29.64 1
1.0%
29.6 1
1.0%
29.34 1
1.0%
29.33 1
1.0%
29.21 1
1.0%

최저 온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.0175
Minimum3.74
Maximum19.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:38:00.418755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.74
5-th percentile6.409
Q18.195
median12.365
Q315.015
95-th percentile18.195
Maximum19.11
Range15.37
Interquartile range (IQR)6.82

Descriptive statistics

Standard deviation3.9331347
Coefficient of variation (CV)0.32728393
Kurtosis-1.0057698
Mean12.0175
Median Absolute Deviation (MAD)3.22
Skewness-0.064239552
Sum1201.75
Variance15.469548
MonotonicityNot monotonic
2023-12-10T20:38:00.655302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.97 2
 
2.0%
14.97 2
 
2.0%
13.43 2
 
2.0%
13.06 1
 
1.0%
13.07 1
 
1.0%
12.75 1
 
1.0%
18.1 1
 
1.0%
18.35 1
 
1.0%
17.13 1
 
1.0%
18.29 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
3.74 1
1.0%
3.99 1
1.0%
4.63 1
1.0%
5.38 1
1.0%
6.2 1
1.0%
6.42 1
1.0%
6.48 1
1.0%
6.49 1
1.0%
6.65 1
1.0%
7.01 1
1.0%
ValueCountFrequency (%)
19.11 1
1.0%
18.83 1
1.0%
18.36 1
1.0%
18.35 1
1.0%
18.29 1
1.0%
18.19 1
1.0%
18.1 1
1.0%
17.92 1
1.0%
17.55 1
1.0%
17.3 1
1.0%

평균 바람 속도(m/s)
Real number (ℝ)

Distinct80
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4472
Minimum0.44
Maximum3.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:38:00.920120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.44
5-th percentile0.6095
Q10.9975
median1.36
Q31.825
95-th percentile2.3345
Maximum3.08
Range2.64
Interquartile range (IQR)0.8275

Descriptive statistics

Standard deviation0.58691641
Coefficient of variation (CV)0.40555307
Kurtosis-0.20891443
Mean1.4472
Median Absolute Deviation (MAD)0.41
Skewness0.54735274
Sum144.72
Variance0.34447087
MonotonicityNot monotonic
2023-12-10T20:38:01.182945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.65 3
 
3.0%
1.39 2
 
2.0%
0.9 2
 
2.0%
1.77 2
 
2.0%
1.02 2
 
2.0%
0.52 2
 
2.0%
1.12 2
 
2.0%
2.12 2
 
2.0%
2.2 2
 
2.0%
2.21 2
 
2.0%
Other values (70) 79
79.0%
ValueCountFrequency (%)
0.44 1
1.0%
0.52 2
2.0%
0.56 1
1.0%
0.6 1
1.0%
0.61 1
1.0%
0.68 1
1.0%
0.69 1
1.0%
0.72 1
1.0%
0.73 1
1.0%
0.77 1
1.0%
ValueCountFrequency (%)
3.08 1
1.0%
2.96 1
1.0%
2.87 1
1.0%
2.65 1
1.0%
2.42 1
1.0%
2.33 1
1.0%
2.29 2
2.0%
2.27 1
1.0%
2.24 1
1.0%
2.21 2
2.0%

Interactions

2023-12-10T20:37:56.247034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:52.834686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.663538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:54.396880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.448501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:56.409585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:52.974414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.821637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:54.886512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.595875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:56.578242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.143845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.964078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.015773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.754783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:56.745929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.301310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:54.128210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.153471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.916969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:56.884477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:53.510873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:54.277441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:55.297653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:37:56.087221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:38:01.357289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전망 일강수 량(mm)최대 온도(℃)최저 온도(℃)평균 바람 속도(m/s)
전망 일1.0000.2520.6990.6480.089
강수 량(mm)0.2521.0000.0000.1490.000
최대 온도(℃)0.6990.0001.0000.7790.484
최저 온도(℃)0.6480.1490.7791.0000.000
평균 바람 속도(m/s)0.0890.0000.4840.0001.000
2023-12-10T20:38:01.535507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전망 일강수 량(mm)최대 온도(℃)최저 온도(℃)평균 바람 속도(m/s)
전망 일1.0000.4520.7820.7610.109
강수 량(mm)0.4521.0000.2700.3370.019
최대 온도(℃)0.7820.2701.0000.7390.104
최저 온도(℃)0.7610.3370.7391.0000.163
평균 바람 속도(m/s)0.1090.0190.1040.1631.000

Missing values

2023-12-10T20:37:57.087415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:37:57.321056image/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

그리드 번호전망 일국가 코드위도(°)경도(°)강수 량(mm)최대 온도(℃)최저 온도(℃)평균 바람 속도(m/s)
01013720050101BG26.7588.250.023.713.061.07
11013720050102BG26.7588.250.021.7612.071.02
21013720050103BG26.7588.250.022.59.40.83
31013720050104BG26.7588.250.023.569.411.65
41013720050105BG26.7588.250.022.3111.441.26
51013720050106BG26.7588.250.021.957.970.82
61013720050107BG26.7588.250.022.077.681.56
71013720050108BG26.7588.250.021.468.20.8
81013720050109BG26.7588.250.2920.28.481.58
91013720050110BG26.7588.250.2618.473.991.14
그리드 번호전망 일국가 코드위도(°)경도(°)강수 량(mm)최대 온도(℃)최저 온도(℃)평균 바람 속도(m/s)
901013720050401BG26.7588.250.1928.3816.281.38
911013720050402BG26.7588.250.1928.813.432.2
921013720050403BG26.7588.253.8928.4417.041.72
931013720050404BG26.7588.257.5827.317.01.65
941013720050405BG26.7588.250.0129.2119.112.1
951013720050406BG26.7588.252.0726.8116.881.19
961013720050407BG26.7588.253.4428.8616.261.18
971013720050408BG26.7588.250.2429.6417.551.32
981013720050409BG26.7588.250.3228.1918.191.18
991013720050410BG26.7588.2511.8827.0715.520.9