Overview

Dataset statistics

Number of variables8
Number of observations1057
Missing cells1396
Missing cells (%)16.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.4 KiB
Average record size in memory69.1 B

Variable types

Text2
Categorical2
Numeric4

Dataset

Description제주도 수문지질 통합정보시스템에서 통합·관리하는 제주도 관측소 기상 정보(누적강수량, 기온, 풍속 등) 입니다.
URLhttps://www.data.go.kr/data/15062331/fileData.do

Alerts

연도 has constant value ""Constant
표고 has 505 (47.8%) missing valuesMissing
누적강수량 has 12 (1.1%) missing valuesMissing
평균기온 has 438 (41.4%) missing valuesMissing
평균풍속 has 441 (41.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:25:02.986574
Analysis finished2023-12-12 09:25:05.650217
Duration2.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관측소명
Text

Distinct84
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
2023-12-12T18:25:05.895750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.3405866
Min length2

Characters and Unicode

Total characters3531
Distinct characters122
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row가파도
2nd row가파도
3rd row가파도
4th row가파도
5th row가파도
ValueCountFrequency (%)
고산 24
 
2.3%
서귀포 24
 
2.3%
대정 24
 
2.3%
송당 24
 
2.3%
제주 24
 
2.3%
어음 12
 
1.1%
용강(한라생태숲 12
 
1.1%
외도 12
 
1.1%
온평리 12
 
1.1%
오등동 12
 
1.1%
Other values (74) 877
83.0%
2023-12-12T18:25:06.444371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 192
 
5.4%
) 168
 
4.8%
( 168
 
4.8%
리 133
 
3.8%
1 120
 
3.4%
성 84
 
2.4%
라 84
 
2.4%
도 84
 
2.4%
대 84
 
2.4%
정 60
 
1.7%
Other values (112) 2354
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3039
86.1%
Close Punctuation 168
 
4.8%
Open Punctuation 168
 
4.8%
Decimal Number 156
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 192
 
6.3%
리 133
 
4.4%
성 84
 
2.8%
라 84
 
2.8%
도 84
 
2.8%
대 84
 
2.8%
정 60
 
2.0%
천 60
 
2.0%
오 60
 
2.0%
생 60
 
2.0%
Other values (108) 2138
70.4%
Decimal Number
ValueCountFrequency (%)
1 120
76.9%
2 36
 
23.1%
Close Punctuation
ValueCountFrequency (%)
) 168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3039
86.1%
Common 492
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 192
 
6.3%
리 133
 
4.4%
성 84
 
2.8%
라 84
 
2.8%
도 84
 
2.8%
대 84
 
2.8%
정 60
 
2.0%
천 60
 
2.0%
오 60
 
2.0%
생 60
 
2.0%
Other values (108) 2138
70.4%
Common
ValueCountFrequency (%)
) 168
34.1%
( 168
34.1%
1 120
24.4%
2 36
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3039
86.1%
ASCII 492
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 192
 
6.3%
리 133
 
4.4%
성 84
 
2.8%
라 84
 
2.8%
도 84
 
2.8%
대 84
 
2.8%
정 60
 
2.0%
천 60
 
2.0%
오 60
 
2.0%
생 60
 
2.0%
Other values (108) 2138
70.4%
ASCII
ValueCountFrequency (%)
) 168
34.1%
( 168
34.1%
1 120
24.4%
2 36
 
7.3%

수집구분
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
AWS
576 
재난본부
433 
기상청
 
48

Length

Max length4
Median length3
Mean length3.40965
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
AWS 576
54.5%
재난본부 433
41.0%
기상청 48
 
4.5%

Length

2023-12-12T18:25:06.645263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:25:06.763423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aws 576
54.5%
재난본부 433
41.0%
기상청 48
 
4.5%

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.4 KiB
2022
1057 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 1057
100.0%

Length

2023-12-12T18:25:06.886343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:25:06.995292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 1057
100.0%

월
Real number (ℝ)

Distinct12
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5052034
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-12T18:25:07.118458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4561952
Coefficient of variation (CV)0.53129703
Kurtosis-1.2176489
Mean6.5052034
Median Absolute Deviation (MAD)3
Skewness-0.00070173702
Sum6876
Variance11.945285
MonotonicityNot monotonic
2023-12-12T18:25:07.258309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
12 89
8.4%
1 88
8.3%
2 88
8.3%
3 88
8.3%
4 88
8.3%
5 88
8.3%
6 88
8.3%
7 88
8.3%
8 88
8.3%
9 88
8.3%
Other values (2) 176
16.7%
ValueCountFrequency (%)
1 88
8.3%
2 88
8.3%
3 88
8.3%
4 88
8.3%
5 88
8.3%
6 88
8.3%
7 88
8.3%
8 88
8.3%
9 88
8.3%
10 88
8.3%
ValueCountFrequency (%)
12 89
8.4%
11 88
8.3%
10 88
8.3%
9 88
8.3%
8 88
8.3%
7 88
8.3%
6 88
8.3%
5 88
8.3%
4 88
8.3%
3 88
8.3%

표고
Real number (ℝ)

MISSING 

Distinct82
Distinct (%)14.9%
Missing505
Missing (%)47.8%
Infinite0
Infinite (%)0.0%
Mean404.27717
Minimum3
Maximum2700.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-12T18:25:07.427522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile8
Q134
median173
Q3570.75
95-th percentile1503
Maximum2700.5
Range2697.5
Interquartile range (IQR)536.75

Descriptive statistics

Standard deviation542.06528
Coefficient of variation (CV)1.3408258
Kurtosis2.2210265
Mean404.27717
Median Absolute Deviation (MAD)153
Skewness1.6898511
Sum223161
Variance293834.77
MonotonicityNot monotonic
2023-12-12T18:25:07.601547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144.0 24
 
2.3%
588.0 24
 
2.3%
20.0 24
 
2.3%
52.0 24
 
2.3%
21.0 24
 
2.3%
377.0 24
 
2.3%
71.0 24
 
2.3%
8.0 12
 
1.1%
1489.0 12
 
1.1%
64.0 12
 
1.1%
Other values (72) 348
32.9%
(Missing) 505
47.8%
ValueCountFrequency (%)
3.0 12
1.1%
4.0 12
1.1%
8.0 12
1.1%
9.0 12
1.1%
12.0 12
1.1%
17.0 12
1.1%
20.0 24
2.3%
21.0 24
2.3%
26.0 12
1.1%
34.0 12
1.1%
ValueCountFrequency (%)
2700.5 1
 
0.1%
2680.0 1
 
0.1%
2628.0 2
 
0.2%
2125.0 1
 
0.1%
2110.0 1
 
0.1%
2057.0 1
 
0.1%
2036.0 1
 
0.1%
1930.0 1
 
0.1%
1676.0 12
1.1%
1650.0 1
 
0.1%

누적강수량
Real number (ℝ)

MISSING 

Distinct478
Distinct (%)45.7%
Missing12
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean140.26718
Minimum1
Maximum1307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.4 KiB
2023-12-12T18:25:07.742570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q132
median96.1
Q3201
95-th percentile404.5
Maximum1307
Range1306
Interquartile range (IQR)169

Descriptive statistics

Standard deviation156.69957
Coefficient of variation (CV)1.1171507
Kurtosis11.679045
Mean140.26718
Median Absolute Deviation (MAD)69.6
Skewness2.7390866
Sum146579.2
Variance24554.756
MonotonicityNot monotonic
2023-12-12T18:25:07.896073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.0 12
 
1.1%
31.0 12
 
1.1%
16.0 11
 
1.0%
36.0 11
 
1.0%
23.0 10
 
0.9%
10.0 10
 
0.9%
15.0 10
 
0.9%
22.0 9
 
0.9%
8.0 8
 
0.8%
33.0 8
 
0.8%
Other values (468) 944
89.3%
(Missing) 12
 
1.1%
ValueCountFrequency (%)
1.0 2
 
0.2%
2.0 3
 
0.3%
4.5 2
 
0.2%
4.6 1
 
0.1%
5.0 1
 
0.1%
5.5 1
 
0.1%
6.0 4
0.4%
7.0 2
 
0.2%
7.1 1
 
0.1%
8.0 8
0.8%
ValueCountFrequency (%)
1307.0 1
0.1%
1245.0 1
0.1%
1107.5 1
0.1%
1042.5 1
0.1%
1031.0 1
0.1%
978.0 2
0.2%
917.5 1
0.1%
882.5 1
0.1%
837.0 1
0.1%
779.0 1
0.1%

평균기온
Real number (ℝ)

MISSING 

Distinct237
Distinct (%)38.3%
Missing438
Missing (%)41.4%
Infinite0
Infinite (%)0.0%
Mean14.267528
Minimum-7.5
Maximum29.4
Zeros0
Zeros (%)0.0%
Negative25
Negative (%)2.4%
Memory size9.4 KiB
2023-12-12T18:25:08.111860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.5
5-th percentile0.9
Q17
median14.9
Q321.3
95-th percentile27.01
Maximum29.4
Range36.9
Interquartile range (IQR)14.3

Descriptive statistics

Standard deviation8.3975144
Coefficient of variation (CV)0.58857528
Kurtosis-0.78962709
Mean14.267528
Median Absolute Deviation (MAD)7.2
Skewness-0.19254138
Sum8831.6
Variance70.518248
MonotonicityNot monotonic
2023-12-12T18:25:08.306183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 10
 
0.9%
18.0 10
 
0.9%
5.0 9
 
0.9%
27.7 9
 
0.9%
14.7 8
 
0.8%
14.8 8
 
0.8%
15.0 8
 
0.8%
27.0 8
 
0.8%
6.0 7
 
0.7%
5.6 7
 
0.7%
Other values (227) 535
50.6%
(Missing) 438
41.4%
ValueCountFrequency (%)
-7.5 1
 
0.1%
-6.2 1
 
0.1%
-6.0 1
 
0.1%
-5.8 1
 
0.1%
-5.7 1
 
0.1%
-5.5 1
 
0.1%
-5.3 1
 
0.1%
-4.6 1
 
0.1%
-4.1 2
0.2%
-3.8 3
0.3%
ValueCountFrequency (%)
29.4 1
 
0.1%
29.2 1
 
0.1%
29.0 2
 
0.2%
28.4 1
 
0.1%
28.3 3
 
0.3%
28.1 2
 
0.2%
28.0 2
 
0.2%
27.9 2
 
0.2%
27.8 2
 
0.2%
27.7 9
0.9%

평균풍속
Text

MISSING 

Distinct70
Distinct (%)11.4%
Missing441
Missing (%)41.7%
Memory size8.4 KiB
2023-12-12T18:25:08.610699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.6753247
Min length1

Characters and Unicode

Total characters1648
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)2.4%

Sample

1st row8.2
2nd row7.8
3rd row6.2
4th row4.7
5th row4.2
ValueCountFrequency (%)
3 40
 
6.5%
2.5 29
 
4.7%
2.9 28
 
4.5%
3.4 27
 
4.4%
2.7 24
 
3.9%
4 23
 
3.7%
3.3 23
 
3.7%
3.1 21
 
3.4%
3.6 21
 
3.4%
2.6 20
 
3.2%
Other values (60) 360
58.4%
2023-12-12T18:25:08.995094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 515
31.2%
3 262
15.9%
2 219
13.3%
4 150
 
9.1%
1 105
 
6.4%
5 102
 
6.2%
6 85
 
5.2%
7 78
 
4.7%
9 67
 
4.1%
8 62
 
3.8%
Other values (2) 3
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1131
68.6%
Other Punctuation 515
31.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 262
23.2%
2 219
19.4%
4 150
13.3%
1 105
9.3%
5 102
 
9.0%
6 85
 
7.5%
7 78
 
6.9%
9 67
 
5.9%
8 62
 
5.5%
0 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 515
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 515
31.2%
3 262
15.9%
2 219
13.3%
4 150
 
9.1%
1 105
 
6.4%
5 102
 
6.2%
6 85
 
5.2%
7 78
 
4.7%
9 67
 
4.1%
8 62
 
3.8%
Other values (2) 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 515
31.2%
3 262
15.9%
2 219
13.3%
4 150
 
9.1%
1 105
 
6.4%
5 102
 
6.2%
6 85
 
5.2%
7 78
 
4.7%
9 67
 
4.1%
8 62
 
3.8%
Other values (2) 3
 
0.2%

Interactions

2023-12-12T18:25:04.852118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:03.524755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.039792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.443207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.952544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:03.651456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.141192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.542241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:05.066885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:03.782372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.235936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.641732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:05.174511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:03.928483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.339007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:25:04.746844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:25:09.120333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관측소명수집구분월표고누적강수량평균기온평균풍속
관측소명1.0000.9800.0000.9730.3240.1090.746
수집구분0.9801.0000.0000.6350.0850.0190.349
월0.0000.0001.0000.0000.6950.8770.529
표고0.9730.6350.0001.0000.3490.4730.531
누적강수량0.3240.0850.6950.3491.0000.5060.000
평균기온0.1090.0190.8770.4730.5061.0000.577
평균풍속0.7460.3490.5290.5310.0000.5771.000
2023-12-12T18:25:09.582460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월표고누적강수량평균기온수집구분
월1.0000.0540.1580.3040.000
표고0.0541.0000.270-0.2670.351
누적강수량0.1580.2701.0000.4180.050
평균기온0.304-0.2670.4181.0000.010
수집구분0.0000.3510.0500.0101.000

Missing values

2023-12-12T18:25:05.323801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:25:05.468170image/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.
2023-12-12T18:25:05.578329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관측소명수집구분연도월표고누적강수량평균기온평균풍속
0가파도AWS202214.038.07.68.2
1가파도AWS202224.011.06.67.8
2가파도AWS202234.091.011.96.2
3가파도AWS202244.0110.015.84.7
4가파도AWS202254.015.018.34.2
5가파도AWS202264.0223.022.44.2
6가파도AWS202274.0340.016.94.4
7가파도AWS202284.086.028.34.4
8가파도AWS202294.0370.024.56.3
9가파도AWS2022104.024.019.26.9
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