Overview

Dataset statistics

Number of variables3
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory27.3 B

Variable types

Categorical1
Numeric2

Alerts

시설명 has constant value ""Constant
공급량 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:10:00.581443
Analysis finished2023-12-10 12:10:01.313335
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고령정수장 100
100.0%

Length

2023-12-10T21:10:01.374006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:10:01.471687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고령정수장 100
100.0%

공급날짜
Real number (ℝ)

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20201010
Minimum20201001
Maximum20201020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:10:01.570009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20201001
5-th percentile20201002
Q120201006
median20201010
Q320201015
95-th percentile20201019
Maximum20201020
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.7953308
Coefficient of variation (CV)2.8688321 × 10-7
Kurtosis-1.2060745
Mean20201010
Median Absolute Deviation (MAD)5
Skewness0
Sum2.020101 × 109
Variance33.585859
MonotonicityNot monotonic
2023-12-10T21:10:01.707613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20201019 5
 
5.0%
20201003 5
 
5.0%
20201006 5
 
5.0%
20201010 5
 
5.0%
20201002 5
 
5.0%
20201001 5
 
5.0%
20201004 5
 
5.0%
20201005 5
 
5.0%
20201007 5
 
5.0%
20201012 5
 
5.0%
Other values (10) 50
50.0%
ValueCountFrequency (%)
20201001 5
5.0%
20201002 5
5.0%
20201003 5
5.0%
20201004 5
5.0%
20201005 5
5.0%
20201006 5
5.0%
20201007 5
5.0%
20201008 5
5.0%
20201009 5
5.0%
20201010 5
5.0%
ValueCountFrequency (%)
20201020 5
5.0%
20201019 5
5.0%
20201018 5
5.0%
20201017 5
5.0%
20201016 5
5.0%
20201015 5
5.0%
20201014 5
5.0%
20201013 5
5.0%
20201012 5
5.0%
20201011 5
5.0%

공급량
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20091.59
Minimum683
Maximum37088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:10:01.862117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum683
5-th percentile5198.85
Q112792.25
median21763.5
Q324047
95-th percentile36229.2
Maximum37088
Range36405
Interquartile range (IQR)11254.75

Descriptive statistics

Standard deviation8842.5511
Coefficient of variation (CV)0.44011206
Kurtosis-0.51411161
Mean20091.59
Median Absolute Deviation (MAD)7639.5
Skewness0.12713478
Sum2009159
Variance78190710
MonotonicityNot monotonic
2023-12-10T21:10:02.044909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21792 1
 
1.0%
23356 1
 
1.0%
23059 1
 
1.0%
21696 1
 
1.0%
36220 1
 
1.0%
23891 1
 
1.0%
14007 1
 
1.0%
22940 1
 
1.0%
10804 1
 
1.0%
33032 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
683 1
1.0%
2344 1
1.0%
2934 1
1.0%
4024 1
1.0%
4265 1
1.0%
5248 1
1.0%
8121 1
1.0%
9128 1
1.0%
10706 1
1.0%
10804 1
1.0%
ValueCountFrequency (%)
37088 1
1.0%
36472 1
1.0%
36468 1
1.0%
36464 1
1.0%
36404 1
1.0%
36220 1
1.0%
36048 1
1.0%
35544 1
1.0%
34304 1
1.0%
34000 1
1.0%

Interactions

2023-12-10T21:10:00.910058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:10:00.667884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:10:01.038891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:10:00.793600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:10:02.179006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급날짜공급량
공급날짜1.0000.291
공급량0.2911.000
2023-12-10T21:10:02.313706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급날짜공급량
공급날짜1.0000.097
공급량0.0971.000

Missing values

2023-12-10T21:10:01.186443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:10:01.282402image/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

시설명공급날짜공급량
0고령정수장2020101921792
1고령정수장2020102023750
2고령정수장2020101723005
3고령정수장2020101832228
4고령정수장2020101934000
5고령정수장2020102021760
6고령정수장2020101611872
7고령정수장2020101610706
8고령정수장2020101712968
9고령정수장2020101822852
시설명공급날짜공급량
90고령정수장2020100420220
91고령정수장2020101323768
92고령정수장2020100511648
93고령정수장2020101810849
94고령정수장2020100124728
95고령정수장2020100220788
96고령정수장2020100512071
97고령정수장2020100614456
98고령정수장2020102037088
99고령정수장2020102014656