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 12:09:50.258731
Analysis finished2023-12-10 12:09:51.027093
Duration0.77 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

2023-12-10T21:09:51.133044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:09:51.364804image/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%
Mean20210310
Minimum20210301
Maximum20210320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:09:51.501757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210301
5-th percentile20210302
Q120210306
median20210310
Q320210315
95-th percentile20210319
Maximum20210320
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.7953308
Coefficient of variation (CV)2.867512 × 10-7
Kurtosis-1.2060745
Mean20210310
Median Absolute Deviation (MAD)5
Skewness0
Sum2.021031 × 109
Variance33.585859
MonotonicityNot monotonic
2023-12-10T21:09:51.711407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20210318 5
 
5.0%
20210313 5
 
5.0%
20210304 5
 
5.0%
20210302 5
 
5.0%
20210303 5
 
5.0%
20210301 5
 
5.0%
20210308 5
 
5.0%
20210310 5
 
5.0%
20210307 5
 
5.0%
20210309 5
 
5.0%
Other values (10) 50
50.0%
ValueCountFrequency (%)
20210301 5
5.0%
20210302 5
5.0%
20210303 5
5.0%
20210304 5
5.0%
20210305 5
5.0%
20210306 5
5.0%
20210307 5
5.0%
20210308 5
5.0%
20210309 5
5.0%
20210310 5
5.0%
ValueCountFrequency (%)
20210320 5
5.0%
20210319 5
5.0%
20210318 5
5.0%
20210317 5
5.0%
20210316 5
5.0%
20210315 5
5.0%
20210314 5
5.0%
20210313 5
5.0%
20210312 5
5.0%
20210311 5
5.0%

공급량
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20951.02
Minimum10593
Maximum36256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:09:51.930602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10593
5-th percentile11406.2
Q113514
median21088
Q325124.5
95-th percentile35344
Maximum36256
Range25663
Interquartile range (IQR)11610.5

Descriptive statistics

Standard deviation8014.422
Coefficient of variation (CV)0.38253135
Kurtosis-0.93392315
Mean20951.02
Median Absolute Deviation (MAD)7216.5
Skewness0.49143782
Sum2095102
Variance64230959
MonotonicityNot monotonic
2023-12-10T21:09:52.149448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13958 1
 
1.0%
24986 1
 
1.0%
31752 1
 
1.0%
12346 1
 
1.0%
12067 1
 
1.0%
23978 1
 
1.0%
23743 1
 
1.0%
33584 1
 
1.0%
22638 1
 
1.0%
33792 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
10593 1
1.0%
10792 1
1.0%
10872 1
1.0%
10884 1
1.0%
10973 1
1.0%
11429 1
1.0%
11476 1
1.0%
11615 1
1.0%
11680 1
1.0%
11936 1
1.0%
ValueCountFrequency (%)
36256 1
1.0%
36168 1
1.0%
35872 1
1.0%
35824 1
1.0%
35496 1
1.0%
35336 1
1.0%
35008 1
1.0%
34960 1
1.0%
34920 1
1.0%
34512 1
1.0%

Interactions

2023-12-10T21:09:50.628091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:09:50.336421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:09:50.751612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:09:50.484754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:09:52.307774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급날짜공급량
공급날짜1.0000.000
공급량0.0001.000
2023-12-10T21:09:52.423970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공급날짜공급량
공급날짜1.0000.047
공급량0.0471.000

Missing values

2023-12-10T21:09:50.888394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:09:50.984046image/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
0고령정수장2021031813958
1고령정수장2021032010973
2고령정수장2021031624043
3고령정수장2021031721776
4고령정수장2021031923531
5고령정수장2021032019496
6고령정수장2021031512344
7고령정수장2021031613878
8고령정수장2021031712625
9고령정수장2021031735872
시설명공급날짜공급량
90고령정수장2021030212528
91고령정수장2021030224294
92고령정수장2021030413274
93고령정수장2021030921160
94고령정수장2021030111429
95고령정수장2021030521432
96고령정수장2021030823392
97고령정수장2021030420952
98고령정수장2021032031504
99고령정수장2021032022891