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

공급량 is highly overall correlated with 시설명High correlation
시설명 is highly overall correlated with 공급량High correlation
공급량 has 4 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:20:41.491465
Analysis finished2023-12-10 10:20:42.611716
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
광동취수장
31 
다압취수장
31 
대청취수장
31 
덕소취수장
7 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광동취수장 31
31.0%
다압취수장 31
31.0%
대청취수장 31
31.0%
덕소취수장 7
 
7.0%

Length

2023-12-10T19:20:42.716527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:42.873615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광동취수장 31
31.0%
다압취수장 31
31.0%
대청취수장 31
31.0%
덕소취수장 7
 
7.0%

공급날짜
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20201015
Minimum20201001
Maximum20201031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:43.372535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20201001
5-th percentile20201002
Q120201008
median20201015
Q320201023
95-th percentile20201030
Maximum20201031
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.9493468
Coefficient of variation (CV)4.430147 × 10-7
Kurtosis-1.1858408
Mean20201015
Median Absolute Deviation (MAD)8
Skewness0.091423801
Sum2.0201015 × 109
Variance80.090808
MonotonicityNot monotonic
2023-12-10T19:20:43.560547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20201007 4
 
4.0%
20201002 4
 
4.0%
20201004 4
 
4.0%
20201013 4
 
4.0%
20201016 4
 
4.0%
20201009 4
 
4.0%
20201010 4
 
4.0%
20201026 3
 
3.0%
20201023 3
 
3.0%
20201022 3
 
3.0%
Other values (21) 63
63.0%
ValueCountFrequency (%)
20201001 3
3.0%
20201002 4
4.0%
20201003 3
3.0%
20201004 4
4.0%
20201005 3
3.0%
20201006 3
3.0%
20201007 4
4.0%
20201008 3
3.0%
20201009 4
4.0%
20201010 4
4.0%
ValueCountFrequency (%)
20201031 3
3.0%
20201030 3
3.0%
20201029 3
3.0%
20201028 3
3.0%
20201027 3
3.0%
20201026 3
3.0%
20201025 3
3.0%
20201024 3
3.0%
20201023 3
3.0%
20201022 3
3.0%

공급량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212984.32
Minimum0
Maximum391200
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:43.746586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9136
Q128383.5
median314157
Q3334624
95-th percentile358570
Maximum391200
Range391200
Interquartile range (IQR)306240.5

Descriptive statistics

Standard deviation148583.38
Coefficient of variation (CV)0.69762591
Kurtosis-1.7446657
Mean212984.32
Median Absolute Deviation (MAD)22067
Skewness-0.4791728
Sum21298432
Variance2.2077021 × 1010
MonotonicityNot monotonic
2023-12-10T19:20:43.965554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
4.0%
336512 3
 
3.0%
335680 2
 
2.0%
336256 2
 
2.0%
335104 2
 
2.0%
335232 2
 
2.0%
27120 1
 
1.0%
315584 1
 
1.0%
322764 1
 
1.0%
315464 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
0 4
4.0%
3968 1
 
1.0%
9408 1
 
1.0%
26174 1
 
1.0%
26196 1
 
1.0%
26896 1
 
1.0%
26944 1
 
1.0%
26948 1
 
1.0%
27120 1
 
1.0%
27152 1
 
1.0%
ValueCountFrequency (%)
391200 1
 
1.0%
386600 1
 
1.0%
372700 1
 
1.0%
369200 1
 
1.0%
363700 1
 
1.0%
358300 1
 
1.0%
336704 1
 
1.0%
336512 3
3.0%
336256 2
2.0%
336192 1
 
1.0%

Interactions

2023-12-10T19:20:41.989463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:41.676969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:42.159077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:41.817090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:20:44.136148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명공급날짜공급량
시설명1.0000.0000.792
공급날짜0.0001.0000.337
공급량0.7920.3371.000
2023-12-10T19:20:44.281890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급날짜공급량시설명
공급날짜1.0000.1210.000
공급량0.1211.0000.745
시설명0.0000.7451.000

Missing values

2023-12-10T19:20:42.356140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:20:42.564946image/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
0광동취수장2020102627120
1광동취수장2020100526948
2광동취수장2020101928592
3광동취수장2020100228386
4광동취수장2020102429032
5광동취수장2020102727594
6광동취수장2020103028528
7광동취수장2020102827834
8광동취수장2020101228658
9광동취수장2020101029236
시설명공급날짜공급량
90대청취수장20201018307628
91대청취수장20201011318944
92대청취수장20201026315208
93덕소취수장20201009391200
94덕소취수장20201004358300
95덕소취수장20201010363700
96덕소취수장20201007386600
97덕소취수장20201016369200
98덕소취수장20201002322000
99덕소취수장20201013372700