Overview

Dataset statistics

Number of variables3
Number of observations87
Missing cells0
Missing cells (%)0.0%
Duplicate rows8
Duplicate rows (%)9.2%
Total size in memory2.3 KiB
Average record size in memory26.5 B

Variable types

Categorical2
Numeric1

Dataset

Description경상북도 구미시 유수율제고블록시스템DB내의 수요예측블록별유량 테이블 정보입니다.
Author경상북도 구미시
URLhttps://www.data.go.kr/data/15049707/fileData.do

Alerts

수요예측일자 has constant value ""Constant
등록시간 has constant value ""Constant
Dataset has 8 (9.2%) duplicate rowsDuplicates
유량평균값 has 14 (16.1%) zerosZeros

Reproduction

Analysis started2023-12-12 13:31:44.607276
Analysis finished2023-12-12 13:31:44.863381
Duration0.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수요예측일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
2020-08-31
87 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-08-31
2nd row2020-08-31
3rd row2020-08-31
4th row2020-08-31
5th row2020-08-31

Common Values

ValueCountFrequency (%)
2020-08-31 87
100.0%

Length

2023-12-12T22:31:44.926618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:31:45.016693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-08-31 87
100.0%

유량평균값
Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3955.4846
Minimum0
Maximum86031.791
Zeros14
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size915.0 B
2023-12-12T22:31:45.121031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1230.4621
median1268.1301
Q33551.1678
95-th percentile13511.913
Maximum86031.791
Range86031.791
Interquartile range (IQR)3320.7057

Descriptive statistics

Standard deviation10219.774
Coefficient of variation (CV)2.583697
Kurtosis49.832138
Mean3955.4846
Median Absolute Deviation (MAD)1268.1301
Skewness6.5319441
Sum344127.16
Variance1.0444377 × 108
MonotonicityNot monotonic
2023-12-12T22:31:45.292747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 14
 
16.1%
11146.3359 2
 
2.3%
109.1921 2
 
2.3%
4191.3611 2
 
2.3%
2886.1146 2
 
2.3%
3824.7034 2
 
2.3%
2074.4086 2
 
2.3%
1268.1301 2
 
2.3%
221.7281 1
 
1.1%
3327.9969 1
 
1.1%
Other values (57) 57
65.5%
ValueCountFrequency (%)
0.0 14
16.1%
9.5806 1
 
1.1%
33.25 1
 
1.1%
109.1921 2
 
2.3%
182.9833 1
 
1.1%
221.7281 1
 
1.1%
222.2451 1
 
1.1%
230.2221 1
 
1.1%
230.7021 1
 
1.1%
386.8872 1
 
1.1%
ValueCountFrequency (%)
86031.7906 1
1.1%
34288.8332 1
1.1%
18394.435 1
1.1%
15129.184 1
1.1%
14203.0739 1
1.1%
11899.2046 1
1.1%
11146.3359 2
2.3%
10023.4164 1
1.1%
9309.2166 1
1.1%
8257.5884 1
1.1%

등록시간
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
2020-08-31 17:29
87 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-08-31 17:29
2nd row2020-08-31 17:29
3rd row2020-08-31 17:29
4th row2020-08-31 17:29
5th row2020-08-31 17:29

Common Values

ValueCountFrequency (%)
2020-08-31 17:29 87
100.0%

Length

2023-12-12T22:31:45.429309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:31:45.538994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-08-31 87
50.0%
17:29 87
50.0%

Interactions

2023-12-12T22:31:44.640588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T22:31:44.744455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:31:44.828783image/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

수요예측일자유량평균값등록시간
02020-08-3111146.33592020-08-31 17:29
12020-08-3111146.33592020-08-31 17:29
22020-08-319309.21662020-08-31 17:29
32020-08-311071.9682020-08-31 17:29
42020-08-31765.15132020-08-31 17:29
52020-08-310.02020-08-31 17:29
62020-08-310.02020-08-31 17:29
72020-08-3186031.79062020-08-31 17:29
82020-08-311268.13012020-08-31 17:29
92020-08-311268.13012020-08-31 17:29
수요예측일자유량평균값등록시간
772020-08-312906.56042020-08-31 17:29
782020-08-312074.40862020-08-31 17:29
792020-08-312074.40862020-08-31 17:29
802020-08-318257.58842020-08-31 17:29
812020-08-31399.61072020-08-31 17:29
822020-08-311715.66672020-08-31 17:29
832020-08-313218.00422020-08-31 17:29
842020-08-31541.05782020-08-31 17:29
852020-08-312383.2492020-08-31 17:29
862020-08-310.02020-08-31 17:29

Duplicate rows

Most frequently occurring

수요예측일자유량평균값등록시간# duplicates
02020-08-310.02020-08-31 17:2914
12020-08-31109.19212020-08-31 17:292
22020-08-311268.13012020-08-31 17:292
32020-08-312074.40862020-08-31 17:292
42020-08-312886.11462020-08-31 17:292
52020-08-313824.70342020-08-31 17:292
62020-08-314191.36112020-08-31 17:292
72020-08-3111146.33592020-08-31 17:292