Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory58.3 B

Variable types

Numeric1
DateTime2
Categorical4

Dataset

DescriptionSample
Author경기대학교 빅데이터센터
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=KGUSPCNWSINFO

Alerts

권역명 is highly overall correlated with 상세지역명High correlation
상세지역명 is highly overall correlated with 권역명 and 1 other fieldsHigh correlation
내용 is highly overall correlated with 상세지역명High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:31:19.717871
Analysis finished2023-12-10 06:31:20.771544
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:31:20.914076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T15:31:21.151442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

발표시간
Date

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-01 01:00:00
Maximum2020-01-07 23:00:00
2023-12-10T15:31:21.328109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:21.484200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

권역명
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전국
42 
대구·경상북도
12 
강원도
11 
제주도
9 
부산·울산·경상남도
7 
Other values (5)
19 

Length

Max length10
Median length9
Mean length4.38
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row전국
2nd row부산·울산·경상남도
3rd row제주도
4th row대구·경상북도
5th row전국

Common Values

ValueCountFrequency (%)
전국 42
42.0%
대구·경상북도 12
 
12.0%
강원도 11
 
11.0%
제주도 9
 
9.0%
부산·울산·경상남도 7
 
7.0%
광주·전라남도 7
 
7.0%
서울·인천·경기도 5
 
5.0%
대전·세종·충청남도 3
 
3.0%
전라북도 3
 
3.0%
충청북도 1
 
1.0%

Length

2023-12-10T15:31:21.685511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:31:21.905768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전국 42
42.0%
대구·경상북도 12
 
12.0%
강원도 11
 
11.0%
제주도 9
 
9.0%
부산·울산·경상남도 7
 
7.0%
광주·전라남도 7
 
7.0%
서울·인천·경기도 5
 
5.0%
대전·세종·충청남도 3
 
3.0%
전라북도 3
 
3.0%
충청북도 1
 
1.0%

특보명
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
풍랑주의보 발표
36 
강풍주의보 발표
26 
풍랑주의보 해제
10 
한파주의보 해제
7 
건조주의보 해제
7 
Other values (6)
14 

Length

Max length10
Median length8
Mean length8
Min length7

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row풍랑주의보 해제
2nd row풍랑주의보 해제
3rd row풍랑주의보 해제
4th row풍랑주의보 해제
5th row풍랑주의보 해제

Common Values

ValueCountFrequency (%)
풍랑주의보 발표 36
36.0%
강풍주의보 발표 26
26.0%
풍랑주의보 해제 10
 
10.0%
한파주의보 해제 7
 
7.0%
건조주의보 해제 7
 
7.0%
건조주의보 발표 5
 
5.0%
강풍주의보 해제 2
 
2.0%
호우주의보 발표 2
 
2.0%
호우주의보 해제 2
 
2.0%
풍랑경보 변경 2
 
2.0%

Length

2023-12-10T15:31:22.138089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
발표 70
35.0%
풍랑주의보 46
23.0%
강풍주의보 28
 
14.0%
해제 28
 
14.0%
건조주의보 12
 
6.0%
한파주의보 7
 
3.5%
호우주의보 4
 
2.0%
풍랑경보 2
 
1.0%
변경 2
 
1.0%
폭풍해일주의보 1
 
0.5%

시행시간
Date

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2020-01-01 03:00:00
Maximum2020-01-08 01:00:00
2023-12-10T15:31:22.331934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:22.548153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

상세지역명
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주도(제주도산지)
10 
동해중부먼바다
8 
"경상북도(경북북동산지
 
6
"울산
 
6
울릉도.독도
 
6
Other values (34)
64 

Length

Max length19
Median length15
Mean length9.09
Min length3

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row"제주도남쪽먼바다
2nd row동해남부앞바다(울산앞바다)
3rd row제주도남쪽먼바다
4th row"동해남부북쪽먼바다
5th row"동해남부북쪽먼바다

Common Values

ValueCountFrequency (%)
제주도(제주도산지) 10
 
10.0%
동해중부먼바다 8
 
8.0%
"경상북도(경북북동산지 6
 
6.0%
"울산 6
 
6.0%
울릉도.독도 6
 
6.0%
"동해남부북쪽먼바다 4
 
4.0%
"강원도(강원북부산지 4
 
4.0%
동해중부앞바다 3
 
3.0%
동해남부북쪽먼바다 3
 
3.0%
"제주도남쪽먼바다 3
 
3.0%
Other values (29) 47
47.0%

Length

2023-12-10T15:31:22.783648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제주도(제주도산지 12
 
11.8%
동해중부먼바다 9
 
8.8%
동해남부북쪽먼바다 7
 
6.9%
경상북도(경북북동산지 6
 
5.9%
울산 6
 
5.9%
울릉도.독도 6
 
5.9%
제주도남쪽먼바다 4
 
3.9%
강원도(강원북부산지 4
 
3.9%
동해중부앞바다 3
 
2.9%
전라북도(김제 2
 
2.0%
Other values (26) 43
42.2%

내용
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
"(1) 강풍주의보 발표
27 
<NA>
17 
"(1) 풍랑주의보 발표
7 
동해남부남쪽먼바다"
 
4
울진평지
 
4
Other values (23)
41 

Length

Max length18
Median length16
Mean length8.77
Min length3

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row 동해남부앞바다(울산앞바다)"
2nd row<NA>
3rd row<NA>
4th row 동해남부남쪽먼바다"
5th row 동해남부남쪽먼바다"

Common Values

ValueCountFrequency (%)
"(1) 강풍주의보 발표 27
27.0%
<NA> 17
17.0%
"(1) 풍랑주의보 발표 7
 
7.0%
동해남부남쪽먼바다" 4
 
4.0%
울진평지 4
 
4.0%
부산 4
 
4.0%
강원중부산지 4
 
4.0%
동해남부앞바다(울산앞바다)" 3
 
3.0%
서천 2
 
2.0%
부산" 2
 
2.0%
Other values (18) 26
26.0%

Length

2023-12-10T15:31:23.048069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 34
20.2%
발표 34
20.2%
강풍주의보 27
16.1%
na 17
10.1%
풍랑주의보 7
 
4.2%
부산 6
 
3.6%
동해남부남쪽먼바다 4
 
2.4%
울진평지 4
 
2.4%
강원중부산지 4
 
2.4%
동해남부앞바다(울산앞바다 3
 
1.8%
Other values (18) 28
16.7%

Interactions

2023-12-10T15:31:20.351225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:31:23.292551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번발표시간권역명특보명시행시간상세지역명내용
순번1.0000.9560.6000.7800.9390.7510.680
발표시간0.9561.0000.0000.9650.9960.8800.877
권역명0.6000.0001.0000.0000.0000.9170.837
특보명0.7800.9650.0001.0000.9820.7040.852
시행시간0.9390.9960.0000.9821.0000.9480.906
상세지역명0.7510.8800.9170.7040.9481.0000.991
내용0.6800.8770.8370.8520.9060.9911.000
2023-12-10T15:31:23.556025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권역명상세지역명내용특보명
권역명1.0000.5140.3900.000
상세지역명0.5141.0000.7470.256
내용0.3900.7471.0000.476
특보명0.0000.2560.4761.000
2023-12-10T15:31:23.772282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번권역명특보명상세지역명내용
순번1.0000.2200.4730.2990.275
권역명0.2201.0000.0000.5140.390
특보명0.4730.0001.0000.2560.476
상세지역명0.2990.5140.2561.0000.747
내용0.2750.3900.4760.7471.000

Missing values

2023-12-10T15:31:20.531763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:31:20.698052image/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

순번발표시간권역명특보명시행시간상세지역명내용
012020-01-01 1:00전국풍랑주의보 해제2020-01-01 3:00"제주도남쪽먼바다동해남부앞바다(울산앞바다)"
122020-01-01 1:00부산·울산·경상남도풍랑주의보 해제2020-01-01 3:00동해남부앞바다(울산앞바다)<NA>
232020-01-01 1:00제주도풍랑주의보 해제2020-01-01 3:00제주도남쪽먼바다<NA>
342020-01-01 3:00대구·경상북도풍랑주의보 해제2020-01-01 6:00"동해남부북쪽먼바다동해남부남쪽먼바다"
452020-01-01 3:00전국풍랑주의보 해제2020-01-01 6:00"동해남부북쪽먼바다동해남부남쪽먼바다"
562020-01-01 8:00대구·경상북도건조주의보 발표2020-01-01 8:00"경상북도(경북북동산지울진평지
672020-01-01 8:00부산·울산·경상남도건조주의보 발표2020-01-01 8:00"울산부산"
782020-01-01 8:00전국건조주의보 발표2020-01-01 8:00"울산부산
892020-01-01 11:00강원도한파주의보 해제2020-01-01 11:00"강원도(강원북부산지강원중부산지
9102020-01-01 11:00강원도풍랑주의보 해제2020-01-01 13:00동해중부먼바다<NA>
순번발표시간권역명특보명시행시간상세지역명내용
90912020-01-07 22:00전국강풍주의보 발표2020-01-07 22:00"경상북도(경북북동산지울진평지
91922020-01-07 22:00전국강풍주의보 발표2020-01-07 22:00울릉도.독도"(1) 강풍주의보 발표
92932020-01-07 22:00전국풍랑주의보 발표2020-01-08 0:00"동해남부앞바다(경북북부앞바다경북남부앞바다)"
93942020-01-07 23:00서울·인천·경기도강풍주의보 발표2020-01-07 23:00"인천경기도(안산
94952020-01-07 23:00서울·인천·경기도풍랑주의보 발표2020-01-08 0:00"서해중부앞바다(인천·경기남부앞바다인천·경기북부앞바다)"
95962020-01-07 23:00강원도강풍주의보 발표2020-01-08 1:00"강원도(강원북부산지강원중부산지
96972020-01-07 23:00강원도풍랑경보 변경2020-01-08 1:00동해중부먼바다"(1) 강풍주의보 발표
97982020-01-07 23:00강원도풍랑경보 변경2020-01-08 1:00동해중부앞바다"(1) 강풍주의보 발표
98992020-01-07 23:00강원도폭풍해일주의보 발표2020-01-08 1:00"강원도(삼척평지동해평지
991002020-01-07 23:00전국강풍주의보 발표2020-01-07 23:00"인천경기도(안산