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 3 other fieldsHigh correlation
최고기온(℃) is highly overall correlated with 평균온도(℃) and 1 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 9 (9.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:23:22.157112
Analysis finished2023-12-10 13:23:35.014485
Duration12.86 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
31 
8000100
31 
8000101
31 
8000105
7 

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 31
31.0%
8000100 31
31.0%
8000101 31
31.0%
8000105 7
 
7.0%

Length

2023-12-10T22:23:35.153800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:35.346256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8000090 31
31.0%
8000100 31
31.0%
8000101 31
31.0%
8000105 7
 
7.0%

관측소명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
속초(기)
31 
대관령(기)
31 
춘천(기)
31 
강릉(기)
7 

Length

Max length6
Median length5
Mean length5.31
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) 31
31.0%
대관령(기) 31
31.0%
춘천(기) 31
31.0%
강릉(기) 7
 
7.0%

Length

2023-12-10T22:23:35.568844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:35.786280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
속초(기 31
31.0%
대관령(기 31
31.0%
춘천(기 31
31.0%
강릉(기 7
 
7.0%

위도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
128.56472
31 
128.758698
31 
127.7357
31 
128.89098
7 

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 31
31.0%
128.758698 31
31.0%
127.7357 31
31.0%
128.89098 7
 
7.0%

Length

2023-12-10T22:23:36.060219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:36.289234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
128.56472 31
31.0%
128.758698 31
31.0%
127.7357 31
31.0%
128.89098 7
 
7.0%

경도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
38.25085
31 
37.686924
31 
37.90256
31 
37.75147
7 

Length

Max length9
Median length8
Mean length8.31
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 31
31.0%
37.686924 31
31.0%
37.90256 31
31.0%
37.75147 7
 
7.0%

Length

2023-12-10T22:23:36.533406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:36.759322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.25085 31
31.0%
37.686924 31
31.0%
37.90256 31
31.0%
37.75147 7
 
7.0%

주소
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도 고성군 토성면 봉포리
31 
(산간)강원도 평창군 대관령면 횡계리
31 
강원도 춘천시 우두동
31 
강원도 강릉시 용강동
7 

Length

Max length20
Median length15
Mean length15.03
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 31
31.0%
(산간)강원도 평창군 대관령면 횡계리 31
31.0%
강원도 춘천시 우두동 31
31.0%
강원도 강릉시 용강동 7
 
7.0%

Length

2023-12-10T22:23:37.012030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:23:37.250454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 69
19.1%
고성군 31
8.6%
토성면 31
8.6%
봉포리 31
8.6%
산간)강원도 31
8.6%
평창군 31
8.6%
대관령면 31
8.6%
횡계리 31
8.6%
춘천시 31
8.6%
우두동 31
8.6%
Other values (2) 14
 
3.9%

관측일자
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200116
Minimum20200101
Maximum20200131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:37.479713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200101
5-th percentile20200102
Q120200108
median20200116
Q320200124
95-th percentile20200130
Maximum20200131
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.9735864
Coefficient of variation (CV)4.442344 × 10-7
Kurtosis-1.2002409
Mean20200116
Median Absolute Deviation (MAD)8
Skewness-0.03953974
Sum2.0200116 × 109
Variance80.525253
MonotonicityNot monotonic
2023-12-10T22:23:37.722947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20200124 4
 
4.0%
20200119 4
 
4.0%
20200123 4
 
4.0%
20200125 4
 
4.0%
20200101 4
 
4.0%
20200106 4
 
4.0%
20200114 4
 
4.0%
20200129 3
 
3.0%
20200127 3
 
3.0%
20200126 3
 
3.0%
Other values (21) 63
63.0%
ValueCountFrequency (%)
20200101 4
4.0%
20200102 3
3.0%
20200103 3
3.0%
20200104 3
3.0%
20200105 3
3.0%
20200106 4
4.0%
20200107 3
3.0%
20200108 3
3.0%
20200109 3
3.0%
20200110 3
3.0%
ValueCountFrequency (%)
20200131 3
3.0%
20200130 3
3.0%
20200129 3
3.0%
20200128 3
3.0%
20200127 3
3.0%
20200126 3
3.0%
20200125 4
4.0%
20200124 4
4.0%
20200123 4
4.0%
20200122 3
3.0%

평균습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.573
Minimum28.1
Maximum98.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:37.968570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.1
5-th percentile33.37
Q154.45
median67.7
Q378.925
95-th percentile94.315
Maximum98.8
Range70.7
Interquartile range (IQR)24.475

Descriptive statistics

Standard deviation18.151522
Coefficient of variation (CV)0.27681396
Kurtosis-0.65112587
Mean65.573
Median Absolute Deviation (MAD)12.35
Skewness-0.31811658
Sum6557.3
Variance329.47775
MonotonicityNot monotonic
2023-12-10T22:23:38.216504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.5 2
 
2.0%
68.3 2
 
2.0%
59.5 2
 
2.0%
79.0 2
 
2.0%
77.8 2
 
2.0%
69.1 2
 
2.0%
35.0 2
 
2.0%
76.4 2
 
2.0%
59.4 2
 
2.0%
45.6 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
28.1 1
1.0%
28.9 1
1.0%
30.1 1
1.0%
30.5 1
1.0%
32.8 1
1.0%
33.4 1
1.0%
33.6 1
1.0%
35.0 2
2.0%
36.1 1
1.0%
38.6 1
1.0%
ValueCountFrequency (%)
98.8 1
1.0%
96.9 1
1.0%
95.6 1
1.0%
95.5 1
1.0%
94.6 1
1.0%
94.3 1
1.0%
93.0 1
1.0%
92.5 1
1.0%
91.8 1
1.0%
91.6 1
1.0%

평균온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.359
Minimum-7.9
Maximum7.2
Zeros0
Zeros (%)0.0%
Negative47
Negative (%)47.0%
Memory size1.0 KiB
2023-12-10T22:23:38.882710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.9
5-th percentile-5.55
Q1-2.5
median0.25
Q33.15
95-th percentile6.1
Maximum7.2
Range15.1
Interquartile range (IQR)5.65

Descriptive statistics

Standard deviation3.8159446
Coefficient of variation (CV)10.629372
Kurtosis-0.94365076
Mean0.359
Median Absolute Deviation (MAD)2.85
Skewness-0.10041474
Sum35.9
Variance14.561433
MonotonicityNot monotonic
2023-12-10T22:23:39.247328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.3 6
 
6.0%
-0.6 4
 
4.0%
2.0 3
 
3.0%
6.1 3
 
3.0%
3.1 3
 
3.0%
-2.3 3
 
3.0%
-3.7 3
 
3.0%
-4.1 3
 
3.0%
2.8 3
 
3.0%
2.5 3
 
3.0%
Other values (56) 66
66.0%
ValueCountFrequency (%)
-7.9 1
 
1.0%
-7.3 1
 
1.0%
-6.9 1
 
1.0%
-6.7 1
 
1.0%
-6.5 1
 
1.0%
-5.5 1
 
1.0%
-4.9 1
 
1.0%
-4.4 1
 
1.0%
-4.3 6
6.0%
-4.2 1
 
1.0%
ValueCountFrequency (%)
7.2 1
 
1.0%
6.7 1
 
1.0%
6.5 1
 
1.0%
6.4 1
 
1.0%
6.1 3
3.0%
6.0 1
 
1.0%
5.9 1
 
1.0%
5.8 1
 
1.0%
5.7 1
 
1.0%
5.6 1
 
1.0%

평균풍속(m/s)
Real number (ℝ)

Distinct36
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.026
Minimum0.5
Maximum5.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:39.501617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.6
Q11.1
median1.75
Q32.4
95-th percentile5
Maximum5.8
Range5.3
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.2884585
Coefficient of variation (CV)0.63596174
Kurtosis0.84275133
Mean2.026
Median Absolute Deviation (MAD)0.65
Skewness1.1819952
Sum202.6
Variance1.6601253
MonotonicityNot monotonic
2023-12-10T22:23:39.744307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2.2 7
 
7.0%
1.8 7
 
7.0%
1.7 6
 
6.0%
0.7 6
 
6.0%
0.6 6
 
6.0%
1.4 6
 
6.0%
0.8 5
 
5.0%
1.2 5
 
5.0%
2.0 4
 
4.0%
2.3 4
 
4.0%
Other values (26) 44
44.0%
ValueCountFrequency (%)
0.5 3
3.0%
0.6 6
6.0%
0.7 6
6.0%
0.8 5
5.0%
0.9 1
 
1.0%
1.0 3
3.0%
1.1 2
 
2.0%
1.2 5
5.0%
1.3 3
3.0%
1.4 6
6.0%
ValueCountFrequency (%)
5.8 1
1.0%
5.7 1
1.0%
5.3 1
1.0%
5.1 1
1.0%
5.0 2
2.0%
4.6 1
1.0%
4.3 1
1.0%
4.2 2
2.0%
4.0 2
2.0%
3.8 2
2.0%

평균이슬점온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.214
Minimum-16.1
Maximum5.7
Zeros1
Zeros (%)1.0%
Negative88
Negative (%)88.0%
Memory size1.0 KiB
2023-12-10T22:23:40.033502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-16.1
5-th percentile-15.02
Q1-9.925
median-6.65
Q3-2.225
95-th percentile2.405
Maximum5.7
Range21.8
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation5.0204636
Coefficient of variation (CV)-0.80792784
Kurtosis-0.66356016
Mean-6.214
Median Absolute Deviation (MAD)3.6
Skewness0.064700336
Sum-621.4
Variance25.205055
MonotonicityNot monotonic
2023-12-10T22:23:40.301256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.2 3
 
3.0%
-10.0 3
 
3.0%
-7.8 3
 
3.0%
-1.5 3
 
3.0%
-8.0 2
 
2.0%
-7.4 2
 
2.0%
-3.7 2
 
2.0%
0.2 2
 
2.0%
-11.1 2
 
2.0%
-6.7 2
 
2.0%
Other values (64) 76
76.0%
ValueCountFrequency (%)
-16.1 1
1.0%
-15.7 1
1.0%
-15.6 1
1.0%
-15.5 1
1.0%
-15.4 1
1.0%
-15.0 1
1.0%
-14.5 1
1.0%
-13.8 1
1.0%
-12.7 1
1.0%
-12.6 2
2.0%
ValueCountFrequency (%)
5.7 1
1.0%
3.6 1
1.0%
2.8 1
1.0%
2.7 1
1.0%
2.5 1
1.0%
2.4 1
1.0%
1.2 1
1.0%
0.7 2
2.0%
0.2 2
2.0%
0.0 1
1.0%

최고기온(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.07
Minimum-3.6
Maximum12.5
Zeros0
Zeros (%)0.0%
Negative10
Negative (%)10.0%
Memory size1.0 KiB
2023-12-10T22:23:40.673280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.6
5-th percentile-0.71
Q12.575
median5.7
Q37.325
95-th percentile10.515
Maximum12.5
Range16.1
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.4897975
Coefficient of variation (CV)0.68832299
Kurtosis-0.48924463
Mean5.07
Median Absolute Deviation (MAD)2.6
Skewness-0.23042949
Sum507
Variance12.178687
MonotonicityNot monotonic
2023-12-10T22:23:40.975405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.6 3
 
3.0%
8.9 3
 
3.0%
5.9 3
 
3.0%
7.1 3
 
3.0%
3.1 3
 
3.0%
5.7 3
 
3.0%
6.4 3
 
3.0%
5.1 2
 
2.0%
11.2 2
 
2.0%
-0.3 2
 
2.0%
Other values (55) 73
73.0%
ValueCountFrequency (%)
-3.6 1
1.0%
-2.5 1
1.0%
-1.8 1
1.0%
-1.7 1
1.0%
-0.9 1
1.0%
-0.7 1
1.0%
-0.6 1
1.0%
-0.4 1
1.0%
-0.3 2
2.0%
0.3 1
1.0%
ValueCountFrequency (%)
12.5 1
1.0%
11.2 2
2.0%
10.9 1
1.0%
10.8 1
1.0%
10.5 1
1.0%
10.4 1
1.0%
10.2 1
1.0%
10.1 1
1.0%
9.3 2
2.0%
9.0 1
1.0%

최저기온(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.588
Minimum-14.2
Maximum5.1
Zeros0
Zeros (%)0.0%
Negative72
Negative (%)72.0%
Memory size1.0 KiB
2023-12-10T22:23:41.286902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-14.2
5-th percentile-12.265
Q1-7.4
median-3.15
Q30.1
95-th percentile3.715
Maximum5.1
Range19.3
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation4.8833107
Coefficient of variation (CV)-1.3610119
Kurtosis-0.6825295
Mean-3.588
Median Absolute Deviation (MAD)3.9
Skewness-0.30271607
Sum-358.8
Variance23.846723
MonotonicityNot monotonic
2023-12-10T22:23:41.585352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 5
 
5.0%
-2.1 3
 
3.0%
-6.1 3
 
3.0%
-3.1 3
 
3.0%
2.0 3
 
3.0%
-0.6 3
 
3.0%
-0.7 2
 
2.0%
-4.3 2
 
2.0%
-9.3 2
 
2.0%
-14.2 2
 
2.0%
Other values (65) 72
72.0%
ValueCountFrequency (%)
-14.2 2
2.0%
-13.9 1
1.0%
-13.6 1
1.0%
-13.5 1
1.0%
-12.2 1
1.0%
-11.5 1
1.0%
-11.2 1
1.0%
-10.4 1
1.0%
-9.9 1
1.0%
-9.7 1
1.0%
ValueCountFrequency (%)
5.1 1
1.0%
4.9 1
1.0%
4.3 1
1.0%
4.0 2
2.0%
3.7 1
1.0%
3.4 1
1.0%
3.3 1
1.0%
2.7 1
1.0%
2.5 1
1.0%
2.3 1
1.0%

일조량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.401
Minimum0
Maximum9.4
Zeros9
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:23:41.897932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.6
median6.95
Q38.625
95-th percentile9.2
Maximum9.4
Range9.4
Interquartile range (IQR)7.025

Descriptive statistics

Standard deviation3.5220086
Coefficient of variation (CV)0.65210305
Kurtosis-1.5224004
Mean5.401
Median Absolute Deviation (MAD)2.15
Skewness-0.41814988
Sum540.1
Variance12.404544
MonotonicityNot monotonic
2023-12-10T22:23:42.195783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
9.0%
8.9 7
 
7.0%
1.6 4
 
4.0%
4.7 4
 
4.0%
9.2 4
 
4.0%
8.8 4
 
4.0%
8.3 4
 
4.0%
9.1 3
 
3.0%
0.2 3
 
3.0%
9.0 3
 
3.0%
Other values (40) 55
55.0%
ValueCountFrequency (%)
0.0 9
9.0%
0.1 1
 
1.0%
0.2 3
 
3.0%
0.3 2
 
2.0%
0.5 1
 
1.0%
0.6 1
 
1.0%
0.7 1
 
1.0%
0.8 2
 
2.0%
1.1 1
 
1.0%
1.4 1
 
1.0%
ValueCountFrequency (%)
9.4 1
 
1.0%
9.3 1
 
1.0%
9.2 4
4.0%
9.1 3
3.0%
9.0 3
3.0%
8.9 7
7.0%
8.8 4
4.0%
8.7 2
 
2.0%
8.6 3
3.0%
8.5 2
 
2.0%

Interactions

2023-12-10T22:23:33.127498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.135176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.461875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.775437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.036639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:28.761655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.890361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.292061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:33.329844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.284186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.639491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.939748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.182521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:28.911673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.065716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.454446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:33.532246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.443856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.808655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.086664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.330973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.083117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.282317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.636132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:33.676522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.607583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.956154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.247362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.487816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.230893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.471502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.811240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:33.796390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.739265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.118088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.443259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.637345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.360409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.620400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.973051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:33.930422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:23.877259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.263882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.580745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:27.881779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.476384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.782895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:32.311138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:34.115074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.033372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.439711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.743330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:28.054907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.622107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:30.982454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:32.700542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:34.322985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:24.208623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:25.615220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:26.905890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:28.274147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:29.764597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:31.158435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:23:32.881464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:23:42.398924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
관측소코드1.0001.0001.0001.0001.0000.0000.6110.6280.6360.2630.6170.6560.375
관측소명1.0001.0001.0001.0001.0000.0000.6110.6280.6360.2630.6170.6560.375
위도1.0001.0001.0001.0001.0000.0000.6110.6280.6360.2630.6170.6560.375
경도1.0001.0001.0001.0001.0000.0000.6110.6280.6360.2630.6170.6560.375
주소1.0001.0001.0001.0001.0000.0000.6110.6280.6360.2630.6170.6560.375
관측일자0.0000.0000.0000.0000.0001.0000.5360.4940.4950.7860.4370.5590.576
평균습도(%)0.6110.6110.6110.6110.6110.5361.0000.4460.4960.6970.0000.1980.465
평균온도(℃)0.6280.6280.6280.6280.6280.4940.4461.0000.4510.5730.8050.8990.528
평균풍속(m/s)0.6360.6360.6360.6360.6360.4950.4960.4511.0000.4710.5460.6030.345
평균이슬점온도(℃)0.2630.2630.2630.2630.2630.7860.6970.5730.4711.0000.6060.7460.680
최고기온(℃)0.6170.6170.6170.6170.6170.4370.0000.8050.5460.6061.0000.6810.202
최저기온(℃)0.6560.6560.6560.6560.6560.5590.1980.8990.6030.7460.6811.0000.386
일조량0.3750.3750.3750.3750.3750.5760.4650.5280.3450.6800.2020.3861.000
2023-12-10T22:23:42.732287image/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
2023-12-10T22:23:42.938021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량관측소코드관측소명위도경도주소
관측일자1.0000.1740.264-0.0590.4160.1960.282-0.2600.0000.0000.0000.0000.000
평균습도(%)0.1741.000-0.176-0.1430.678-0.261-0.100-0.5570.4000.4000.4000.4000.400
평균온도(℃)0.264-0.1761.0000.1110.5570.8500.951-0.3970.4150.4150.4150.4150.415
평균풍속(m/s)-0.059-0.1430.1111.000-0.063-0.1880.2390.0990.4230.4230.4230.4230.423
평균이슬점온도(℃)0.4160.6780.557-0.0631.0000.3980.580-0.7620.1520.1520.1520.1520.152
최고기온(℃)0.196-0.2610.850-0.1880.3981.0000.698-0.1670.4050.4050.4050.4050.405
최저기온(℃)0.282-0.1000.9510.2390.5800.6981.000-0.4580.4420.4420.4420.4420.442
일조량-0.260-0.557-0.3970.099-0.762-0.167-0.4581.0000.2150.2150.2150.2150.215
관측소코드0.0000.4000.4150.4230.1520.4050.4420.2151.0001.0001.0001.0001.000
관측소명0.0000.4000.4150.4230.1520.4050.4420.2151.0001.0001.0001.0001.000
위도0.0000.4000.4150.4230.1520.4050.4420.2151.0001.0001.0001.0001.000
경도0.0000.4000.4150.4230.1520.4050.4420.2151.0001.0001.0001.0001.000
주소0.0000.4000.4150.4230.1520.4050.4420.2151.0001.0001.0001.0001.000

Missing values

2023-12-10T22:23:34.520423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:23:34.873757image/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 봉포리2020011245.62.01.7-8.65.1-0.33.6
18000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020011940.53.32.7-8.95.71.68.2
28000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020011878.92.41.7-1.36.90.13.3
38000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020011040.63.51.8-9.28.9-1.07.1
48000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020012140.51.21.7-10.95.9-3.59.2
58000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020012354.35.91.4-2.810.42.38.9
68000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020012579.04.71.61.27.70.94.1
78000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020010136.10.82.4-12.64.8-3.48.9
88000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020010648.95.31.2-4.78.10.90.2
98000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020011140.33.11.8-9.26.90.19.0
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
908000101춘천(기)127.735737.90256강원도 춘천시 우두동2020011563.8-4.30.9-11.12.6-9.58.3
918000101춘천(기)127.735737.90256강원도 춘천시 우두동2020012159.4-2.50.6-10.04.8-8.88.6
928000101춘천(기)127.735737.90256강원도 춘천시 우두동2020012667.64.12.2-2.010.5-2.17.4
938000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020010142.51.74.6-9.76.4-3.08.6
948000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020011945.84.13.6-6.76.12.74.7
958000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020010650.86.11.9-3.79.32.20.0
968000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020011435.01.22.5-12.75.9-2.19.0
978000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020012582.35.71.42.710.12.12.5
988000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020012476.44.41.40.27.22.50.2
998000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020012354.57.22.0-1.512.53.48.7