Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory62.3 B

Variable types

Numeric3
Categorical4

Alerts

지점 has constant value ""Constant
주소 has constant value ""Constant
강우량(mm) has constant value ""Constant
기본키 is highly overall correlated with 측정시간 and 2 other fieldsHigh correlation
측정시간 is highly overall correlated with 기본키 and 1 other fieldsHigh correlation
강수량(mm) is highly overall correlated with 기본키 and 2 other fieldsHigh correlation
측정일 is highly overall correlated with 기본키 and 1 other fieldsHigh correlation
측정일 is highly imbalanced (71.4%)Imbalance
기본키 has unique valuesUnique
강수량(mm) has 4 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:43:02.622442
Analysis finished2023-12-10 13:43:04.832486
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  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
2023-12-10T22:43:04.965158image/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
2023-12-10T22:43:05.318697image/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%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20201001
95 
20201002
 
5

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20201001
2nd row20201001
3rd row20201001
4th row20201001
5th row20201001

Common Values

ValueCountFrequency (%)
20201001 95
95.0%
20201002 5
 
5.0%

Length

2023-12-10T22:43:05.569931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:05.712750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20201001 95
95.0%
20201002 5
 
5.0%

측정시간
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1127.5
Minimum0
Maximum2345
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:43:05.912196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile44.25
Q1511.25
median1122.5
Q31733.75
95-th percentile2230.75
Maximum2345
Range2345
Interquartile range (IQR)1222.5

Descriptive statistics

Standard deviation716.97404
Coefficient of variation (CV)0.63589715
Kurtosis-1.2374242
Mean1127.5
Median Absolute Deviation (MAD)615
Skewness0.032728046
Sum112750
Variance514051.77
MonotonicityNot monotonic
2023-12-10T22:43:06.142375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
2.0%
45 2
 
2.0%
100 2
 
2.0%
30 2
 
2.0%
1545 1
 
1.0%
1800 1
 
1.0%
1745 1
 
1.0%
1730 1
 
1.0%
1715 1
 
1.0%
1700 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
0 1
1.0%
15 2
2.0%
30 2
2.0%
45 2
2.0%
100 2
2.0%
115 1
1.0%
130 1
1.0%
145 1
1.0%
200 1
1.0%
215 1
1.0%
ValueCountFrequency (%)
2345 1
1.0%
2330 1
1.0%
2315 1
1.0%
2300 1
1.0%
2245 1
1.0%
2230 1
1.0%
2215 1
1.0%
2200 1
1.0%
2145 1
1.0%
2130 1
1.0%

지점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-0500-1780S-4
100 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0500-1780S-4
2nd rowA-0500-1780S-4
3rd rowA-0500-1780S-4
4th rowA-0500-1780S-4
5th rowA-0500-1780S-4

Common Values

ValueCountFrequency (%)
A-0500-1780S-4 100
100.0%

Length

2023-12-10T22:43:06.379507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:06.587340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a-0500-1780s-4 100
100.0%

주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원 평창군 대관령면 유천리
100 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원 평창군 대관령면 유천리
2nd row강원 평창군 대관령면 유천리
3rd row강원 평창군 대관령면 유천리
4th row강원 평창군 대관령면 유천리
5th row강원 평창군 대관령면 유천리

Common Values

ValueCountFrequency (%)
강원 평창군 대관령면 유천리 100
100.0%

Length

2023-12-10T22:43:06.773966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:06.949498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원 100
25.0%
평창군 100
25.0%
대관령면 100
25.0%
유천리 100
25.0%

강수량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.512
Minimum0
Maximum0.6
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:43:07.105578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.5
median0.6
Q30.6
95-th percentile0.6
Maximum0.6
Range0.6
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.16470359
Coefficient of variation (CV)0.3216867
Kurtosis3.2659628
Mean0.512
Median Absolute Deviation (MAD)0
Skewness-2.0643432
Sum51.2
Variance0.027127273
MonotonicityNot monotonic
2023-12-10T22:43:07.285995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.6 67
67.0%
0.5 12
 
12.0%
0.4 10
 
10.0%
0.1 5
 
5.0%
0.0 4
 
4.0%
0.2 1
 
1.0%
0.3 1
 
1.0%
ValueCountFrequency (%)
0.0 4
 
4.0%
0.1 5
 
5.0%
0.2 1
 
1.0%
0.3 1
 
1.0%
0.4 10
 
10.0%
0.5 12
 
12.0%
0.6 67
67.0%
ValueCountFrequency (%)
0.6 67
67.0%
0.5 12
 
12.0%
0.4 10
 
10.0%
0.3 1
 
1.0%
0.2 1
 
1.0%
0.1 5
 
5.0%
0.0 4
 
4.0%

강우량(mm)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T22:43:07.488418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:43:07.641521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

Interactions

2023-12-10T22:43:03.940253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:02.905935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:03.434557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:04.098818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:03.087268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:03.594012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:04.230620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:03.208128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:43:03.794024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:43:07.741245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키측정일측정시간강수량(mm)
기본키1.0000.8160.9770.804
측정일0.8161.0000.6180.814
측정시간0.9770.6181.0000.771
강수량(mm)0.8040.8140.7711.000
2023-12-10T22:43:07.861201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키측정시간강수량(mm)측정일
기본키1.0000.7240.5580.622
측정시간0.7241.0000.8100.458
강수량(mm)0.5580.8101.0000.860
측정일0.6220.4580.8601.000

Missing values

2023-12-10T22:43:04.413316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:43:04.736124image/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

기본키측정일측정시간지점주소강수량(mm)강우량(mm)
012020100115A-0500-1780S-4강원 평창군 대관령면 유천리0.10
122020100130A-0500-1780S-4강원 평창군 대관령면 유천리0.10
232020100145A-0500-1780S-4강원 평창군 대관령면 유천리0.10
3420201001100A-0500-1780S-4강원 평창군 대관령면 유천리0.10
4520201001115A-0500-1780S-4강원 평창군 대관령면 유천리0.10
5620201001130A-0500-1780S-4강원 평창군 대관령면 유천리0.20
6720201001145A-0500-1780S-4강원 평창군 대관령면 유천리0.30
7820201001200A-0500-1780S-4강원 평창군 대관령면 유천리0.40
8920201001215A-0500-1780S-4강원 평창군 대관령면 유천리0.40
91020201001230A-0500-1780S-4강원 평창군 대관령면 유천리0.40
기본키측정일측정시간지점주소강수량(mm)강우량(mm)
9091202010012245A-0500-1780S-4강원 평창군 대관령면 유천리0.60
9192202010012300A-0500-1780S-4강원 평창군 대관령면 유천리0.60
9293202010012315A-0500-1780S-4강원 평창군 대관령면 유천리0.60
9394202010012330A-0500-1780S-4강원 평창군 대관령면 유천리0.60
9495202010012345A-0500-1780S-4강원 평창군 대관령면 유천리0.60
9596202010020A-0500-1780S-4강원 평창군 대관령면 유천리0.60
96972020100215A-0500-1780S-4강원 평창군 대관령면 유천리0.00
97982020100230A-0500-1780S-4강원 평창군 대관령면 유천리0.00
98992020100245A-0500-1780S-4강원 평창군 대관령면 유천리0.00
9910020201002100A-0500-1780S-4강원 평창군 대관령면 유천리0.00