Overview

Dataset statistics

Number of variables13
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory116.3 B

Variable types

Categorical5
Numeric8

Alerts

관측소코드 is highly overall correlated with 관측소명 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 관측소코드 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 관측소코드 and 3 other fieldsHigh correlation
주소 is highly overall correlated with 관측소코드 and 3 other fieldsHigh correlation
관측소명 is highly overall correlated with 관측소코드 and 3 other fieldsHigh correlation
평균습도(%) is highly overall correlated with 평균이슬점온도(℃) and 1 other fieldsHigh correlation
평균온도(℃) is highly overall correlated with 평균이슬점온도(℃) and 2 other fieldsHigh correlation
평균이슬점온도(℃) is highly overall correlated with 평균습도(%) and 4 other fieldsHigh correlation
최고기온(℃) is highly overall correlated with 평균온도(℃) and 2 other fieldsHigh correlation
최저기온(℃) is highly overall correlated with 평균온도(℃) and 2 other fieldsHigh correlation
일조량 is highly overall correlated with 평균습도(%) and 1 other fieldsHigh correlation
일조량 has 8 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:23:01.982990
Analysis finished2023-12-10 13:23:13.414247
Duration11.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관측소코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
8000090
29 
8000100
29 
8000101
29 
8000105
13 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8000090
2nd row8000090
3rd row8000090
4th row8000090
5th row8000090

Common Values

ValueCountFrequency (%)
8000090 29
29.0%
8000100 29
29.0%
8000101 29
29.0%
8000105 13
13.0%

Length

2023-12-10T22:23:13.518393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:13.699992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8000090 29
29.0%
8000100 29
29.0%
8000101 29
29.0%
8000105 13
13.0%

관측소명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속초(기)
29 
대관령(기)
29 
춘천(기)
29 
강릉(기)
13 

Length

Max length6
Median length5
Mean length5.29
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row속초(기)
2nd row속초(기)
3rd row속초(기)
4th row속초(기)
5th row속초(기)

Common Values

ValueCountFrequency (%)
속초(기) 29
29.0%
대관령(기) 29
29.0%
춘천(기) 29
29.0%
강릉(기) 13
13.0%

Length

2023-12-10T22:23:13.955436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:14.143217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속초(기 29
29.0%
대관령(기 29
29.0%
춘천(기 29
29.0%
강릉(기 13
13.0%

위도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
128.56472
29 
128.758698
29 
127.7357
29 
128.89098
13 

Length

Max length10
Median length9
Mean length9
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row128.56472
2nd row128.56472
3rd row128.56472
4th row128.56472
5th row128.56472

Common Values

ValueCountFrequency (%)
128.56472 29
29.0%
128.758698 29
29.0%
127.7357 29
29.0%
128.89098 13
13.0%

Length

2023-12-10T22:23:14.377264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:14.576288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
128.56472 29
29.0%
128.758698 29
29.0%
127.7357 29
29.0%
128.89098 13
13.0%

경도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
38.25085
29 
37.686924
29 
37.90256
29 
37.75147
13 

Length

Max length9
Median length8
Mean length8.29
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38.25085
2nd row38.25085
3rd row38.25085
4th row38.25085
5th row38.25085

Common Values

ValueCountFrequency (%)
38.25085 29
29.0%
37.686924 29
29.0%
37.90256 29
29.0%
37.75147 13
13.0%

Length

2023-12-10T22:23:14.768646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:14.931314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.25085 29
29.0%
37.686924 29
29.0%
37.90256 29
29.0%
37.75147 13
13.0%

주소
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도 고성군 토성면 봉포리
29 
(산간)강원도 평창군 대관령면 횡계리
29 
강원도 춘천시 우두동
29 
강원도 강릉시 용강동
13 

Length

Max length20
Median length15
Mean length14.77
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 고성군 토성면 봉포리
2nd row강원도 고성군 토성면 봉포리
3rd row강원도 고성군 토성면 봉포리
4th row강원도 고성군 토성면 봉포리
5th row강원도 고성군 토성면 봉포리

Common Values

ValueCountFrequency (%)
강원도 고성군 토성면 봉포리 29
29.0%
(산간)강원도 평창군 대관령면 횡계리 29
29.0%
강원도 춘천시 우두동 29
29.0%
강원도 강릉시 용강동 13
13.0%

Length

2023-12-10T22:23:15.121336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:15.298784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 71
19.8%
고성군 29
8.1%
토성면 29
8.1%
봉포리 29
8.1%
산간)강원도 29
8.1%
평창군 29
8.1%
대관령면 29
8.1%
횡계리 29
8.1%
춘천시 29
8.1%
우두동 29
8.1%
Other values (2) 26
 
7.3%

관측일자
Real number (ℝ)

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200215
Minimum20200201
Maximum20200229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:15.507904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200201
5-th percentile20200202
Q120200207
median20200215
Q320200222
95-th percentile20200228
Maximum20200229
Range28
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.3698533
Coefficient of variation (CV)4.1434477 × 10-7
Kurtosis-1.202046
Mean20200215
Median Absolute Deviation (MAD)7
Skewness0.0055177894
Sum2.0200215 × 109
Variance70.054444
MonotonicityNot monotonic
2023-12-10T22:23:15.739913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20200216 4
 
4.0%
20200201 4
 
4.0%
20200206 4
 
4.0%
20200224 4
 
4.0%
20200218 4
 
4.0%
20200219 4
 
4.0%
20200204 4
 
4.0%
20200220 4
 
4.0%
20200223 4
 
4.0%
20200214 4
 
4.0%
Other values (19) 60
60.0%
ValueCountFrequency (%)
20200201 4
4.0%
20200202 3
3.0%
20200203 4
4.0%
20200204 4
4.0%
20200205 4
4.0%
20200206 4
4.0%
20200207 3
3.0%
20200208 3
3.0%
20200209 3
3.0%
20200210 3
3.0%
ValueCountFrequency (%)
20200229 3
3.0%
20200228 3
3.0%
20200227 3
3.0%
20200226 3
3.0%
20200225 3
3.0%
20200224 4
4.0%
20200223 4
4.0%
20200222 3
3.0%
20200221 3
3.0%
20200220 4
4.0%

평균습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.719
Minimum25.8
Maximum96.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:15.974962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.8
5-th percentile32.755
Q146.575
median62.7
Q376.425
95-th percentile90.67
Maximum96.9
Range71.1
Interquartile range (IQR)29.85

Descriptive statistics

Standard deviation17.931704
Coefficient of variation (CV)0.29053782
Kurtosis-0.80133074
Mean61.719
Median Absolute Deviation (MAD)14.1
Skewness-0.027500759
Sum6171.9
Variance321.546
MonotonicityNot monotonic
2023-12-10T22:23:16.214590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 3
 
3.0%
79.0 2
 
2.0%
54.9 2
 
2.0%
43.6 2
 
2.0%
65.4 2
 
2.0%
48.8 2
 
2.0%
43.0 2
 
2.0%
71.3 1
 
1.0%
84.6 1
 
1.0%
42.1 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
25.8 1
1.0%
26.3 1
1.0%
27.5 1
1.0%
30.5 1
1.0%
31.9 1
1.0%
32.8 1
1.0%
34.0 1
1.0%
34.6 1
1.0%
35.3 1
1.0%
37.6 1
1.0%
ValueCountFrequency (%)
96.9 1
1.0%
96.3 1
1.0%
94.3 1
1.0%
92.9 1
1.0%
92.0 1
1.0%
90.6 1
1.0%
89.3 1
1.0%
88.9 1
1.0%
87.8 1
1.0%
86.6 1
1.0%

평균온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.368
Minimum-12.8
Maximum11.3
Zeros1
Zeros (%)1.0%
Negative34
Negative (%)34.0%
Memory size1.0 KiB
2023-12-10T22:23:16.468120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-12.8
5-th percentile-7.215
Q1-2.15
median2.1
Q34.725
95-th percentile9.03
Maximum11.3
Range24.1
Interquartile range (IQR)6.875

Descriptive statistics

Standard deviation5.0013913
Coefficient of variation (CV)3.6559878
Kurtosis0.039737783
Mean1.368
Median Absolute Deviation (MAD)3.4
Skewness-0.42700707
Sum136.8
Variance25.013915
MonotonicityNot monotonic
2023-12-10T22:23:16.703362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.1 4
 
4.0%
6.0 3
 
3.0%
-4.0 3
 
3.0%
2.7 3
 
3.0%
4.4 2
 
2.0%
3.6 2
 
2.0%
-2.1 2
 
2.0%
3.1 2
 
2.0%
8.4 2
 
2.0%
4.8 2
 
2.0%
Other values (66) 75
75.0%
ValueCountFrequency (%)
-12.8 1
1.0%
-11.5 1
1.0%
-10.1 1
1.0%
-8.3 1
1.0%
-7.5 1
1.0%
-7.2 1
1.0%
-6.8 1
1.0%
-6.4 1
1.0%
-6.2 1
1.0%
-5.3 1
1.0%
ValueCountFrequency (%)
11.3 1
1.0%
10.9 1
1.0%
10.3 1
1.0%
9.9 1
1.0%
9.6 1
1.0%
9.0 1
1.0%
8.4 2
2.0%
8.1 1
1.0%
7.6 1
1.0%
7.3 1
1.0%

평균풍속(m/s)
Real number (ℝ)

Distinct41
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.278
Minimum0.5
Maximum7.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:16.926875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.7
Q11.2
median1.9
Q33
95-th percentile4.815
Maximum7.9
Range7.4
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.3730141
Coefficient of variation (CV)0.60272787
Kurtosis2.1525645
Mean2.278
Median Absolute Deviation (MAD)0.8
Skewness1.2933938
Sum227.8
Variance1.8851677
MonotonicityNot monotonic
2023-12-10T22:23:17.168644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1.2 7
 
7.0%
0.7 6
 
6.0%
1.0 5
 
5.0%
1.3 4
 
4.0%
3.7 4
 
4.0%
2.0 4
 
4.0%
1.1 4
 
4.0%
1.6 4
 
4.0%
1.9 4
 
4.0%
1.8 4
 
4.0%
Other values (31) 54
54.0%
ValueCountFrequency (%)
0.5 1
 
1.0%
0.6 2
 
2.0%
0.7 6
6.0%
0.8 1
 
1.0%
0.9 1
 
1.0%
1.0 5
5.0%
1.1 4
4.0%
1.2 7
7.0%
1.3 4
4.0%
1.4 3
3.0%
ValueCountFrequency (%)
7.9 1
 
1.0%
6.0 1
 
1.0%
5.4 2
2.0%
5.1 1
 
1.0%
4.8 2
2.0%
4.7 1
 
1.0%
4.2 1
 
1.0%
3.9 3
3.0%
3.8 1
 
1.0%
3.7 4
4.0%

평균이슬점온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.141
Minimum-20.9
Maximum6.1
Zeros0
Zeros (%)0.0%
Negative83
Negative (%)83.0%
Memory size1.0 KiB
2023-12-10T22:23:17.406489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20.9
5-th percentile-15.04
Q1-10.525
median-6.25
Q3-1.025
95-th percentile2.62
Maximum6.1
Range27
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.9809647
Coefficient of variation (CV)-0.97393986
Kurtosis-0.6243161
Mean-6.141
Median Absolute Deviation (MAD)4.4
Skewness-0.16871992
Sum-614.1
Variance35.771938
MonotonicityNot monotonic
2023-12-10T22:23:17.666668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.3 5
 
5.0%
-0.1 3
 
3.0%
-0.4 3
 
3.0%
-13.1 3
 
3.0%
-3.0 2
 
2.0%
-10.6 2
 
2.0%
-12.0 2
 
2.0%
-9.7 2
 
2.0%
-7.9 2
 
2.0%
-2.8 2
 
2.0%
Other values (71) 74
74.0%
ValueCountFrequency (%)
-20.9 1
1.0%
-20.7 1
1.0%
-17.9 1
1.0%
-16.9 1
1.0%
-15.8 1
1.0%
-15.0 1
1.0%
-14.7 1
1.0%
-14.4 1
1.0%
-13.6 1
1.0%
-13.3 2
2.0%
ValueCountFrequency (%)
6.1 1
1.0%
3.9 1
1.0%
3.8 1
1.0%
3.1 1
1.0%
3.0 1
1.0%
2.6 1
1.0%
2.5 1
1.0%
2.3 1
1.0%
2.2 1
1.0%
2.1 1
1.0%

최고기온(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.386
Minimum-8.2
Maximum16.6
Zeros1
Zeros (%)1.0%
Negative12
Negative (%)12.0%
Memory size1.0 KiB
2023-12-10T22:23:17.894536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.2
5-th percentile-1.715
Q13
median6.75
Q39.55
95-th percentile14.215
Maximum16.6
Range24.8
Interquartile range (IQR)6.55

Descriptive statistics

Standard deviation5.0533921
Coefficient of variation (CV)0.79132354
Kurtosis-0.1421103
Mean6.386
Median Absolute Deviation (MAD)3.5
Skewness-0.26946883
Sum638.6
Variance25.536772
MonotonicityNot monotonic
2023-12-10T22:23:18.555483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.5 3
 
3.0%
7.6 3
 
3.0%
4.4 3
 
3.0%
4.5 3
 
3.0%
9.1 2
 
2.0%
10.5 2
 
2.0%
8.8 2
 
2.0%
11.7 2
 
2.0%
6.7 2
 
2.0%
6.5 2
 
2.0%
Other values (68) 76
76.0%
ValueCountFrequency (%)
-8.2 1
1.0%
-4.7 1
1.0%
-4.0 1
1.0%
-2.7 1
1.0%
-2.0 1
1.0%
-1.7 2
2.0%
-1.4 1
1.0%
-1.3 1
1.0%
-0.9 1
1.0%
-0.7 1
1.0%
ValueCountFrequency (%)
16.6 1
1.0%
16.1 1
1.0%
15.8 1
1.0%
15.7 1
1.0%
14.5 1
1.0%
14.2 1
1.0%
13.7 1
1.0%
13.5 1
1.0%
13.4 1
1.0%
13.2 1
1.0%

최저기온(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.626
Minimum-24
Maximum7.4
Zeros1
Zeros (%)1.0%
Negative69
Negative (%)69.0%
Memory size1.0 KiB
2023-12-10T22:23:18.808445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-24
5-th percentile-13.045
Q1-7.15
median-2.75
Q30.4
95-th percentile5.03
Maximum7.4
Range31.4
Interquartile range (IQR)7.55

Descriptive statistics

Standard deviation5.8627504
Coefficient of variation (CV)-1.6168644
Kurtosis0.91463046
Mean-3.626
Median Absolute Deviation (MAD)3.5
Skewness-0.78030502
Sum-362.6
Variance34.371842
MonotonicityNot monotonic
2023-12-10T22:23:19.036155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4 4
 
4.0%
-0.7 3
 
3.0%
-9.7 3
 
3.0%
-1.8 2
 
2.0%
-2.5 2
 
2.0%
-7.3 2
 
2.0%
-3.0 2
 
2.0%
-5.2 2
 
2.0%
-1.7 2
 
2.0%
-4.1 2
 
2.0%
Other values (66) 76
76.0%
ValueCountFrequency (%)
-24.0 1
1.0%
-18.9 1
1.0%
-18.6 1
1.0%
-16.8 1
1.0%
-13.9 1
1.0%
-13.0 1
1.0%
-12.7 1
1.0%
-12.4 1
1.0%
-12.2 1
1.0%
-11.2 1
1.0%
ValueCountFrequency (%)
7.4 1
1.0%
6.6 1
1.0%
6.0 1
1.0%
5.8 1
1.0%
5.6 1
1.0%
5.0 1
1.0%
4.6 1
1.0%
4.0 1
1.0%
3.1 1
1.0%
2.7 1
1.0%

일조량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.002
Minimum0
Maximum10.6
Zeros8
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:19.298428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.075
median8.75
Q39.6
95-th percentile10.2
Maximum10.6
Range10.6
Interquartile range (IQR)4.525

Descriptive statistics

Standard deviation3.4776626
Coefficient of variation (CV)0.49666704
Kurtosis-0.45635169
Mean7.002
Median Absolute Deviation (MAD)1.15
Skewness-1.0220551
Sum700.2
Variance12.094137
MonotonicityNot monotonic
2023-12-10T22:23:19.536140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
8.0%
9.6 7
 
7.0%
9.7 7
 
7.0%
9.8 5
 
5.0%
9.3 4
 
4.0%
10.0 3
 
3.0%
8.9 3
 
3.0%
8.8 3
 
3.0%
9.4 3
 
3.0%
8.6 3
 
3.0%
Other values (40) 54
54.0%
ValueCountFrequency (%)
0.0 8
8.0%
0.1 2
 
2.0%
0.7 1
 
1.0%
1.1 1
 
1.0%
1.2 2
 
2.0%
1.4 3
 
3.0%
2.0 1
 
1.0%
2.8 1
 
1.0%
3.4 1
 
1.0%
3.6 1
 
1.0%
ValueCountFrequency (%)
10.6 1
 
1.0%
10.4 2
 
2.0%
10.3 1
 
1.0%
10.2 2
 
2.0%
10.1 1
 
1.0%
10.0 3
3.0%
9.9 2
 
2.0%
9.8 5
5.0%
9.7 7
7.0%
9.6 7
7.0%

Interactions

2023-12-10T22:23:11.831219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.105189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.397922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.684466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.900081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.192914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.338564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.662147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.986274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.290894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.544327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.823157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.159703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.348224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.483344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.783458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.135349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.467448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.703628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.959361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.315179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.497426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.620931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.917700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.260409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.654218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.820950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.080813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.445622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.620412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.720731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.046094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.408396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.807907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.957831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.250051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.591212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.770534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.836558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.201096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.544689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:03.956352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.200171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.380757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.725528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.911349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.266540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.331935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.694698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.109132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.405230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.499327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:07.854086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.036906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.373446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.469141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:12.827479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:04.251703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:05.548793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:06.632923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:08.025113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:09.190398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:10.500021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:11.692562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:23:19.713565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
관측소코드1.0001.0001.0001.0001.0000.0000.5060.3900.5610.0000.4140.4820.279
관측소명1.0001.0001.0001.0001.0000.0000.5060.3900.5610.0000.4140.4820.279
위도1.0001.0001.0001.0001.0000.0000.5060.3900.5610.0000.4140.4820.279
경도1.0001.0001.0001.0001.0000.0000.5060.3900.5610.0000.4140.4820.279
주소1.0001.0001.0001.0001.0000.0000.5060.3900.5610.0000.4140.4820.279
관측일자0.0000.0000.0000.0000.0001.0000.4090.5510.1830.7770.5640.3670.720
평균습도(%)0.5060.5060.5060.5060.5060.4091.0000.2350.2790.5880.0000.2300.333
평균온도(℃)0.3900.3900.3900.3900.3900.5510.2351.0000.2680.7540.9340.9450.295
평균풍속(m/s)0.5610.5610.5610.5610.5610.1830.2790.2681.0000.2530.4280.2630.265
평균이슬점온도(℃)0.0000.0000.0000.0000.0000.7770.5880.7540.2531.0000.6810.7620.500
최고기온(℃)0.4140.4140.4140.4140.4140.5640.0000.9340.4280.6811.0000.8540.000
최저기온(℃)0.4820.4820.4820.4820.4820.3670.2300.9450.2630.7620.8541.0000.000
일조량0.2790.2790.2790.2790.2790.7200.3330.2950.2650.5000.0000.0001.000
2023-12-10T22:23:19.953711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소코드경도위도주소관측소명
관측소코드1.0001.0001.0001.0001.000
경도1.0001.0001.0001.0001.000
위도1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
관측소명1.0001.0001.0001.0001.000
2023-12-10T22:23:20.172479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량관측소코드관측소명위도경도주소
관측일자1.0000.3350.352-0.1290.4910.3010.358-0.1800.0000.0000.0000.0000.000
평균습도(%)0.3351.000-0.066-0.2530.625-0.097-0.012-0.5390.3150.3150.3150.3150.315
평균온도(℃)0.352-0.0661.000-0.2780.7030.9280.946-0.1990.2330.2330.2330.2330.233
평균풍속(m/s)-0.129-0.253-0.2781.000-0.412-0.354-0.2280.2790.4010.4010.4010.4010.401
평균이슬점온도(℃)0.4910.6250.703-0.4121.0000.6330.699-0.5450.0000.0000.0000.0000.000
최고기온(℃)0.301-0.0970.928-0.3540.6331.0000.794-0.0630.2500.2500.2500.2500.250
최저기온(℃)0.358-0.0120.946-0.2280.6990.7941.000-0.2860.2970.2970.2970.2970.297
일조량-0.180-0.539-0.1990.279-0.545-0.063-0.2861.0000.1620.1620.1620.1620.162
관측소코드0.0000.3150.2330.4010.0000.2500.2970.1621.0001.0001.0001.0001.000
관측소명0.0000.3150.2330.4010.0000.2500.2970.1621.0001.0001.0001.0001.000
위도0.0000.3150.2330.4010.0000.2500.2970.1621.0001.0001.0001.0001.000
경도0.0000.3150.2330.4010.0000.2500.2970.1621.0001.0001.0001.0001.000
주소0.0000.3150.2330.4010.0000.2500.2970.1621.0001.0001.0001.0001.000

Missing values

2023-12-10T22:23:13.016534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:23:13.310610image/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

관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
08000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020022869.65.21.0-0.19.3-0.30.0
18000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020021838.50.01.6-12.95.4-6.110.2
28000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020020330.51.72.4-14.75.2-0.79.6
38000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020021150.07.01.8-2.912.60.19.6
48000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020022964.66.61.90.39.12.37.9
58000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020022582.06.31.93.110.84.60.0
68000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020021467.59.91.63.913.76.08.7
78000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020021046.64.01.5-6.78.1-0.19.9
88000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020022781.62.91.2-0.17.60.04.4
98000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020020734.01.12.6-13.35.3-5.98.8
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
908000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020022046.56.62.0-4.312.03.19.8
918000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020021941.64.72.5-7.49.40.79.8
928000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020022332.86.03.8-9.512.30.910.0
938000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020020658.4-2.62.5-10.02.1-7.17.3
948000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020021666.03.14.2-3.06.5-0.95.0
958000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020020152.34.82.9-4.39.10.49.3
968000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020021459.310.92.33.015.77.48.0
978000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020021143.68.11.8-3.916.6-0.29.6
988000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020021839.30.63.9-11.97.3-5.210.0
998000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020020531.9-2.13.0-16.93.8-5.39.6