Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory44.3 B

Variable types

Categorical4
Numeric1

Alerts

댐명 has constant value ""Constant
관측소명 has constant value ""Constant
강우량(mm) has constant value ""Constant
누적 강우량(mm) has constant value ""Constant
계측시각 has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:21:00.432064
Analysis finished2023-12-10 11:21:01.006566
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

댐명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감포 100
100.0%

Length

2023-12-10T20:21:01.116363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:21:01.291062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감포 100
100.0%

관측소명
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경주시(감포댐)
2nd row경주시(감포댐)
3rd row경주시(감포댐)
4th row경주시(감포댐)
5th row경주시(감포댐)

Common Values

ValueCountFrequency (%)
경주시(감포댐) 100
100.0%

Length

2023-12-10T20:21:01.476831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:21:01.626438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경주시(감포댐 100
100.0%

계측시각
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190505 × 109
Minimum2.0190501 × 109
Maximum2.019051 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:21:01.894391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190501 × 109
5-th percentile2.0190501 × 109
Q12.0190503 × 109
median2.0190505 × 109
Q32.0190507 × 109
95-th percentile2.0190509 × 109
Maximum2.019051 × 109
Range903
Interquartile range (IQR)406

Descriptive statistics

Standard deviation253.03806
Coefficient of variation (CV)1.2532528 × 10-7
Kurtosis-1.0475167
Mean2.0190505 × 109
Median Absolute Deviation (MAD)203.5
Skewness0.10989532
Sum2.0190505 × 1011
Variance64028.261
MonotonicityNot monotonic
2023-12-10T20:21:02.152009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019050722 1
 
1.0%
2019050409 1
 
1.0%
2019050513 1
 
1.0%
2019050507 1
 
1.0%
2019050217 1
 
1.0%
2019050110 1
 
1.0%
2019050503 1
 
1.0%
2019050108 1
 
1.0%
2019050104 1
 
1.0%
2019050417 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019050102 1
1.0%
2019050104 1
1.0%
2019050106 1
1.0%
2019050108 1
1.0%
2019050110 1
1.0%
2019050112 1
1.0%
2019050114 1
1.0%
2019050116 1
1.0%
2019050118 1
1.0%
2019050120 1
1.0%
ValueCountFrequency (%)
2019051005 1
1.0%
2019051003 1
1.0%
2019051001 1
1.0%
2019050923 1
1.0%
2019050903 1
1.0%
2019050901 1
1.0%
2019050824 1
1.0%
2019050822 1
1.0%
2019050820 1
1.0%
2019050818 1
1.0%

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

2023-12-10T20:21:02.386845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:21:02.537885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

누적 강우량(mm)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
182.5
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row182.5
2nd row182.5
3rd row182.5
4th row182.5
5th row182.5

Common Values

ValueCountFrequency (%)
182.5 100
100.0%

Length

2023-12-10T20:21:02.700919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:21:02.832215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
182.5 100
100.0%

Interactions

2023-12-10T20:21:00.540489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-10T20:21:00.747626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:21:00.943792image/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

댐명관측소명계측시각강우량(mm)누적 강우량(mm)
0감포경주시(감포댐)20190507220182.5
1감포경주시(감포댐)20190510010182.5
2감포경주시(감포댐)20190505240182.5
3감포경주시(감포댐)20190507200182.5
4감포경주시(감포댐)20190508180182.5
5감포경주시(감포댐)20190509230182.5
6감포경주시(감포댐)20190505010182.5
7감포경주시(감포댐)20190505210182.5
8감포경주시(감포댐)20190506230182.5
9감포경주시(감포댐)20190507180182.5
댐명관측소명계측시각강우량(mm)누적 강우량(mm)
90감포경주시(감포댐)20190502210182.5
91감포경주시(감포댐)20190501160182.5
92감포경주시(감포댐)20190503070182.5
93감포경주시(감포댐)20190507120182.5
94감포경주시(감포댐)20190503110182.5
95감포경주시(감포댐)20190501180182.5
96감포경주시(감포댐)20190502150182.5
97감포경주시(감포댐)20190501020182.5
98감포경주시(감포댐)20190510050182.5
99감포경주시(감포댐)20190510030182.5