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
관측일자 is highly overall correlated with 최고기온(℃)High correlation
평균습도(%) is highly overall correlated with 평균이슬점온도(℃)High correlation
평균온도(℃) is highly overall correlated with 최고기온(℃) and 1 other fieldsHigh correlation
평균이슬점온도(℃) is highly overall correlated with 평균습도(%) and 1 other fieldsHigh correlation
최고기온(℃) is highly overall correlated with 관측일자 and 2 other fieldsHigh correlation
최저기온(℃) is highly overall correlated with 평균온도(℃) and 2 other fieldsHigh correlation
최저기온(℃) has 4 (4.0%) zerosZeros
일조량 has 6 (6.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:22:40.288791
Analysis finished2023-12-10 13:22:53.284440
Duration13 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

2023-12-10T22:22:53.432054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:53.590266image/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

2023-12-10T22:22:53.805922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:53.995551image/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

2023-12-10T22:22:54.197679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:54.368256image/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

2023-12-10T22:22:54.545135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:54.733870image/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

2023-12-10T22:22:54.957953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:55.115978image/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)

HIGH CORRELATION 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200316
Minimum20200301
Maximum20200331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:55.297720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200301
5-th percentile20200302
Q120200308
median20200316
Q320200324
95-th percentile20200330
Maximum20200331
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.9735864
Coefficient of variation (CV)4.4423 × 10-7
Kurtosis-1.2002409
Mean20200316
Median Absolute Deviation (MAD)8
Skewness-0.03953974
Sum2.0200316 × 109
Variance80.525253
MonotonicityNot monotonic
2023-12-10T22:22:55.514377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20200324 4
 
4.0%
20200319 4
 
4.0%
20200323 4
 
4.0%
20200325 4
 
4.0%
20200301 4
 
4.0%
20200306 4
 
4.0%
20200314 4
 
4.0%
20200329 3
 
3.0%
20200327 3
 
3.0%
20200326 3
 
3.0%
Other values (21) 63
63.0%
ValueCountFrequency (%)
20200301 4
4.0%
20200302 3
3.0%
20200303 3
3.0%
20200304 3
3.0%
20200305 3
3.0%
20200306 4
4.0%
20200307 3
3.0%
20200308 3
3.0%
20200309 3
3.0%
20200310 3
3.0%
ValueCountFrequency (%)
20200331 3
3.0%
20200330 3
3.0%
20200329 3
3.0%
20200328 3
3.0%
20200327 3
3.0%
20200326 3
3.0%
20200325 4
4.0%
20200324 4
4.0%
20200323 4
4.0%
20200322 3
3.0%

평균습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.846
Minimum25.4
Maximum98.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:55.850317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.4
5-th percentile34.97
Q147.225
median58
Q372.65
95-th percentile86.45
Maximum98.9
Range73.5
Interquartile range (IQR)25.425

Descriptive statistics

Standard deviation16.35081
Coefficient of variation (CV)0.27321474
Kurtosis-0.68941603
Mean59.846
Median Absolute Deviation (MAD)12.35
Skewness0.15026201
Sum5984.6
Variance267.34897
MonotonicityNot monotonic
2023-12-10T22:22:56.105355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.6 3
 
3.0%
45.3 3
 
3.0%
57.1 3
 
3.0%
57.5 2
 
2.0%
79.5 2
 
2.0%
49.5 2
 
2.0%
66.5 2
 
2.0%
53.0 2
 
2.0%
47.0 2
 
2.0%
65.4 2
 
2.0%
Other values (74) 77
77.0%
ValueCountFrequency (%)
25.4 1
1.0%
28.6 1
1.0%
33.1 1
1.0%
34.0 1
1.0%
34.4 1
1.0%
35.0 2
2.0%
35.8 1
1.0%
36.1 1
1.0%
36.3 1
1.0%
39.4 1
1.0%
ValueCountFrequency (%)
98.9 1
1.0%
95.0 1
1.0%
90.3 1
1.0%
87.5 1
1.0%
87.4 1
1.0%
86.4 1
1.0%
86.3 1
1.0%
84.3 1
1.0%
81.6 1
1.0%
80.5 1
1.0%

평균온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.872
Minimum-2.8
Maximum14
Zeros0
Zeros (%)0.0%
Negative9
Negative (%)9.0%
Memory size1.0 KiB
2023-12-10T22:22:56.284839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.8
5-th percentile-1
Q13.275
median6
Q38.825
95-th percentile12.2
Maximum14
Range16.8
Interquartile range (IQR)5.55

Descriptive statistics

Standard deviation3.9856074
Coefficient of variation (CV)0.67874786
Kurtosis-0.63138509
Mean5.872
Median Absolute Deviation (MAD)2.8
Skewness-0.12985954
Sum587.2
Variance15.885067
MonotonicityNot monotonic
2023-12-10T22:22:56.500780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.2 3
 
3.0%
7.6 3
 
3.0%
6.8 3
 
3.0%
5.2 3
 
3.0%
3.8 3
 
3.0%
10.8 2
 
2.0%
8.6 2
 
2.0%
9.0 2
 
2.0%
6.5 2
 
2.0%
4.3 2
 
2.0%
Other values (63) 75
75.0%
ValueCountFrequency (%)
-2.8 1
1.0%
-2.5 1
1.0%
-1.6 1
1.0%
-1.2 1
1.0%
-1.0 2
2.0%
-0.8 2
2.0%
-0.1 1
1.0%
0.1 1
1.0%
0.3 1
1.0%
0.4 1
1.0%
ValueCountFrequency (%)
14.0 1
1.0%
13.2 1
1.0%
13.1 1
1.0%
12.9 1
1.0%
12.2 2
2.0%
11.8 1
1.0%
11.6 1
1.0%
11.5 1
1.0%
11.3 1
1.0%
11.2 1
1.0%

평균풍속(m/s)
Real number (ℝ)

Distinct42
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.454
Minimum0.6
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:56.693069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1
Q11.4
median2.05
Q32.725
95-th percentile6.415
Maximum9
Range8.4
Interquartile range (IQR)1.325

Descriptive statistics

Standard deviation1.6100329
Coefficient of variation (CV)0.65608514
Kurtosis3.7231584
Mean2.454
Median Absolute Deviation (MAD)0.65
Skewness1.8744218
Sum245.4
Variance2.5922061
MonotonicityNot monotonic
2023-12-10T22:22:56.896030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1.4 7
 
7.0%
1.3 6
 
6.0%
2.1 6
 
6.0%
1.5 5
 
5.0%
2.5 5
 
5.0%
1.9 5
 
5.0%
1.2 5
 
5.0%
1.0 4
 
4.0%
1.1 4
 
4.0%
2.3 4
 
4.0%
Other values (32) 49
49.0%
ValueCountFrequency (%)
0.6 1
 
1.0%
0.7 2
 
2.0%
0.8 1
 
1.0%
1.0 4
4.0%
1.1 4
4.0%
1.2 5
5.0%
1.3 6
6.0%
1.4 7
7.0%
1.5 5
5.0%
1.6 2
 
2.0%
ValueCountFrequency (%)
9.0 1
1.0%
7.6 1
1.0%
7.1 1
1.0%
6.8 1
1.0%
6.7 1
1.0%
6.4 1
1.0%
5.3 1
1.0%
5.2 1
1.0%
4.6 1
1.0%
4.5 2
2.0%

평균이슬점온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.566
Minimum-10.6
Maximum9.2
Zeros0
Zeros (%)0.0%
Negative72
Negative (%)72.0%
Memory size1.0 KiB
2023-12-10T22:22:57.115230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10.6
5-th percentile-9.03
Q1-6.4
median-2.85
Q30.675
95-th percentile5.205
Maximum9.2
Range19.8
Interquartile range (IQR)7.075

Descriptive statistics

Standard deviation4.5960286
Coefficient of variation (CV)-1.7911257
Kurtosis-0.68300889
Mean-2.566
Median Absolute Deviation (MAD)3.55
Skewness0.30577327
Sum-256.6
Variance21.123479
MonotonicityNot monotonic
2023-12-10T22:22:57.463894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.0 3
 
3.0%
-1.5 3
 
3.0%
-5.5 3
 
3.0%
-1.2 3
 
3.0%
-6.8 3
 
3.0%
-1.9 3
 
3.0%
-4.4 2
 
2.0%
-8.2 2
 
2.0%
-7.8 2
 
2.0%
2.9 2
 
2.0%
Other values (58) 74
74.0%
ValueCountFrequency (%)
-10.6 1
1.0%
-10.0 2
2.0%
-9.7 1
1.0%
-9.6 1
1.0%
-9.0 1
1.0%
-8.9 2
2.0%
-8.7 1
1.0%
-8.4 1
1.0%
-8.3 2
2.0%
-8.2 2
2.0%
ValueCountFrequency (%)
9.2 1
1.0%
6.5 1
1.0%
6.0 1
1.0%
5.6 1
1.0%
5.3 1
1.0%
5.2 1
1.0%
5.1 2
2.0%
4.9 1
1.0%
4.6 1
1.0%
3.6 2
2.0%

최고기온(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.842
Minimum1.7
Maximum21.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:57.733066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile3.685
Q18.875
median11.55
Q315.425
95-th percentile19.31
Maximum21.5
Range19.8
Interquartile range (IQR)6.55

Descriptive statistics

Standard deviation4.7680583
Coefficient of variation (CV)0.40263961
Kurtosis-0.67781055
Mean11.842
Median Absolute Deviation (MAD)2.95
Skewness0.003815583
Sum1184.2
Variance22.73438
MonotonicityNot monotonic
2023-12-10T22:22:57.991714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.8 2
 
2.0%
11.8 2
 
2.0%
10.6 2
 
2.0%
2.9 2
 
2.0%
11.5 2
 
2.0%
8.9 2
 
2.0%
3.7 2
 
2.0%
6.4 2
 
2.0%
19.1 2
 
2.0%
13.0 2
 
2.0%
Other values (71) 80
80.0%
ValueCountFrequency (%)
1.7 1
1.0%
2.9 2
2.0%
3.2 1
1.0%
3.4 1
1.0%
3.7 2
2.0%
4.2 1
1.0%
4.5 1
1.0%
4.6 1
1.0%
6.3 1
1.0%
6.4 2
2.0%
ValueCountFrequency (%)
21.5 1
1.0%
20.6 1
1.0%
20.5 1
1.0%
20.4 1
1.0%
19.5 1
1.0%
19.3 1
1.0%
19.1 2
2.0%
18.9 1
1.0%
18.6 1
1.0%
18.3 2
2.0%

최저기온(℃)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.212
Minimum-8.9
Maximum8.7
Zeros4
Zeros (%)4.0%
Negative45
Negative (%)45.0%
Memory size1.0 KiB
2023-12-10T22:22:58.202352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.9
5-th percentile-6.915
Q1-3.6
median0.35
Q32.625
95-th percentile5.645
Maximum8.7
Range17.6
Interquartile range (IQR)6.225

Descriptive statistics

Standard deviation4.0532636
Coefficient of variation (CV)-19.119168
Kurtosis-0.61451936
Mean-0.212
Median Absolute Deviation (MAD)3.05
Skewness-0.19097153
Sum-21.2
Variance16.428945
MonotonicityNot monotonic
2023-12-10T22:22:58.414163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4
 
4.0%
-3.6 4
 
4.0%
0.7 3
 
3.0%
4.0 3
 
3.0%
2.2 3
 
3.0%
0.5 3
 
3.0%
-4.4 2
 
2.0%
-8.9 2
 
2.0%
-6.1 2
 
2.0%
1.2 2
 
2.0%
Other values (66) 72
72.0%
ValueCountFrequency (%)
-8.9 2
2.0%
-8.7 1
1.0%
-8.2 1
1.0%
-7.2 1
1.0%
-6.9 1
1.0%
-6.4 1
1.0%
-6.1 2
2.0%
-6.0 1
1.0%
-5.6 1
1.0%
-5.5 1
1.0%
ValueCountFrequency (%)
8.7 1
1.0%
7.4 1
1.0%
6.9 1
1.0%
6.8 1
1.0%
6.5 1
1.0%
5.6 1
1.0%
5.5 1
1.0%
5.1 1
1.0%
5.0 1
1.0%
4.9 1
1.0%

일조량
Real number (ℝ)

ZEROS 

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.359
Minimum0
Maximum11.8
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:59.009830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.4
median9.9
Q310.8
95-th percentile11.4
Maximum11.8
Range11.8
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation3.3343058
Coefficient of variation (CV)0.39888812
Kurtosis0.70831541
Mean8.359
Median Absolute Deviation (MAD)1.25
Skewness-1.2909334
Sum835.9
Variance11.117595
MonotonicityNot monotonic
2023-12-10T22:22:59.324379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.5 7
 
7.0%
0.0 6
 
6.0%
10.9 6
 
6.0%
10.6 5
 
5.0%
11.4 4
 
4.0%
9.4 3
 
3.0%
10.8 3
 
3.0%
11.2 3
 
3.0%
11.3 3
 
3.0%
10.0 3
 
3.0%
Other values (43) 57
57.0%
ValueCountFrequency (%)
0.0 6
6.0%
0.3 1
 
1.0%
0.8 1
 
1.0%
1.6 1
 
1.0%
2.9 1
 
1.0%
3.5 1
 
1.0%
4.6 2
 
2.0%
4.9 2
 
2.0%
5.2 1
 
1.0%
5.3 1
 
1.0%
ValueCountFrequency (%)
11.8 1
 
1.0%
11.7 1
 
1.0%
11.6 1
 
1.0%
11.5 1
 
1.0%
11.4 4
4.0%
11.3 3
3.0%
11.2 3
3.0%
11.1 2
 
2.0%
11.0 1
 
1.0%
10.9 6
6.0%

Interactions

2023-12-10T22:22:51.417189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:41.326240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:43.411823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.667495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.823647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.929454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.157760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.409400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:51.575490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:41.929964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:43.582088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.815064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.968431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.089234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.322866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.567629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:51.730227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:42.145866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:43.733456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.977985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.101470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.249592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.480294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.717516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:51.864882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:42.324591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:43.897034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.124587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.222456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.393333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.647193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.939722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:52.005416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:42.467087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.017711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.261857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.325748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.524864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.783892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:50.133105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:52.176728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:42.769727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.189734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.415695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.492203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.678616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:48.959630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:50.325304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:52.394916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:42.992282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.366429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.556648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.680950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.839204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.117453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:50.593791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:52.552431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:43.255776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:44.520213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:45.693053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:46.808546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:47.993917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:49.268343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:22:50.785593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:22:59.507473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
관측소코드1.0001.0001.0001.0001.0000.0000.3680.5430.4660.2840.4800.6010.096
관측소명1.0001.0001.0001.0001.0000.0000.3680.5430.4660.2840.4800.6010.096
위도1.0001.0001.0001.0001.0000.0000.3680.5430.4660.2840.4800.6010.096
경도1.0001.0001.0001.0001.0000.0000.3680.5430.4660.2840.4800.6010.096
주소1.0001.0001.0001.0001.0000.0000.3680.5430.4660.2840.4800.6010.096
관측일자0.0000.0000.0000.0000.0001.0000.4590.5470.5820.6400.5030.4340.378
평균습도(%)0.3680.3680.3680.3680.3680.4591.0000.4890.0000.6680.4310.5660.595
평균온도(℃)0.5430.5430.5430.5430.5430.5470.4891.0000.5080.5580.8670.8540.000
평균풍속(m/s)0.4660.4660.4660.4660.4660.5820.0000.5081.0000.2780.5900.4210.000
평균이슬점온도(℃)0.2840.2840.2840.2840.2840.6400.6680.5580.2781.0000.1870.7770.658
최고기온(℃)0.4800.4800.4800.4800.4800.5030.4310.8670.5900.1871.0000.6370.000
최저기온(℃)0.6010.6010.6010.6010.6010.4340.5660.8540.4210.7770.6371.0000.405
일조량0.0960.0960.0960.0960.0960.3780.5950.0000.0000.6580.0000.4051.000
2023-12-10T22:22:59.753473image/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
2023-12-10T22:22:59.938061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량관측소코드관측소명위도경도주소
관측일자1.000-0.0770.467-0.0940.2890.5190.3080.2490.0000.0000.0000.0000.000
평균습도(%)-0.0771.000-0.330-0.2070.624-0.319-0.202-0.4250.2180.2180.2180.2180.218
평균온도(℃)0.467-0.3301.000-0.2090.4880.9120.861-0.0750.3430.3430.3430.3430.343
평균풍속(m/s)-0.094-0.207-0.2091.000-0.340-0.3890.0190.0770.2860.2860.2860.2860.286
평균이슬점온도(℃)0.2890.6240.488-0.3401.0000.4170.512-0.4710.1650.1650.1650.1650.165
최고기온(℃)0.519-0.3190.912-0.3890.4171.0000.6350.0510.3030.3030.3030.3030.303
최저기온(℃)0.308-0.2020.8610.0190.5120.6351.000-0.2450.3930.3930.3930.3930.393
일조량0.249-0.425-0.0750.077-0.4710.051-0.2451.0000.0470.0470.0470.0470.047
관측소코드0.0000.2180.3430.2860.1650.3030.3930.0471.0001.0001.0001.0001.000
관측소명0.0000.2180.3430.2860.1650.3030.3930.0471.0001.0001.0001.0001.000
위도0.0000.2180.3430.2860.1650.3030.3930.0471.0001.0001.0001.0001.000
경도0.0000.2180.3430.2860.1650.3030.3930.0471.0001.0001.0001.0001.000
주소0.0000.2180.3430.2860.1650.3030.3930.0471.0001.0001.0001.0001.000

Missing values

2023-12-10T22:22:52.789653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:22:53.176051image/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 봉포리2020031228.610.82.6-7.017.04.19.9
18000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020031935.011.64.6-3.517.16.97.9
28000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020031836.312.91.8-2.418.35.511.1
38000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020031086.37.62.25.310.15.00.0
48000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020032157.112.23.13.217.58.710.2
58000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020032351.88.51.9-1.212.93.910.1
68000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020032578.59.31.45.613.74.08.9
78000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020030178.56.81.93.212.12.15.6
88000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020030643.55.21.7-6.810.9-1.010.7
98000090속초(기)128.5647238.25085강원도 고성군 토성면 봉포리2020031135.06.32.6-8.910.52.210.9
관측소코드관측소명위도경도주소관측일자평균습도(%)평균온도(℃)평균풍속(m/s)평균이슬점온도(℃)최고기온(℃)최저기온(℃)일조량
908000101춘천(기)127.735737.90256강원도 춘천시 우두동2020031557.13.32.5-5.58.8-1.05.8
918000101춘천(기)127.735737.90256강원도 춘천시 우두동2020032156.111.81.22.719.54.05.4
928000101춘천(기)127.735737.90256강원도 춘천시 우두동2020032653.114.01.13.621.53.85.6
938000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020030172.48.02.03.113.42.44.6
948000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020031940.612.25.2-0.918.66.57.7
958000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020030636.16.12.3-8.211.40.910.6
968000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020031434.46.52.8-8.912.60.710.8
978000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020032569.110.91.45.117.72.79.3
988000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020032461.18.61.91.314.23.310.0
998000105강릉(기)128.8909837.75147강원도 강릉시 용강동2020032350.68.92.2-1.114.24.59.9