Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory419.9 KiB
Average record size in memory43.0 B

Variable types

Numeric3
Text1

Dataset

Description경상북도 구미시의 유수율제고블록시스템 월별시간대별유량평균값 테이블 데이터로 각 유량계에 대한 시간평균 유량 데이터를 제공합니다.
Author경상북도 구미시
URLhttps://www.data.go.kr/data/15049702/fileData.do

Alerts

시간 has 399 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-12 17:05:56.785375
Analysis finished2023-12-12 17:05:57.993622
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

유량계코드
Real number (ℝ)

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.8784
Minimum2
Maximum460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:05:58.077155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile28
Q1241
median307
Q3389
95-th percentile449
Maximum460
Range458
Interquartile range (IQR)148

Descriptive statistics

Standard deviation117.38308
Coefficient of variation (CV)0.40354692
Kurtosis0.022270156
Mean290.8784
Median Absolute Deviation (MAD)73
Skewness-0.85491256
Sum2908784
Variance13778.788
MonotonicityNot monotonic
2023-12-13T02:05:58.222897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
392 136
 
1.4%
380 136
 
1.4%
377 135
 
1.4%
413 133
 
1.3%
280 129
 
1.3%
108 127
 
1.3%
307 127
 
1.3%
141 127
 
1.3%
259 126
 
1.3%
417 125
 
1.2%
Other values (78) 8699
87.0%
ValueCountFrequency (%)
2 103
1.0%
5 103
1.0%
8 102
1.0%
11 113
1.1%
28 118
1.2%
38 113
1.1%
80 122
1.2%
89 115
1.1%
92 111
1.1%
100 115
1.1%
ValueCountFrequency (%)
460 78
0.8%
457 117
1.2%
454 112
1.1%
451 112
1.1%
449 112
1.1%
418 111
1.1%
417 125
1.2%
416 107
1.1%
415 107
1.1%
414 124
1.2%

월
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4988
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:05:58.377677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.449607
Coefficient of variation (CV)0.53080677
Kurtosis-1.2102165
Mean6.4988
Median Absolute Deviation (MAD)3
Skewness0.014056364
Sum64988
Variance11.899789
MonotonicityNot monotonic
2023-12-13T02:05:58.735970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
7 868
8.7%
5 862
8.6%
12 859
8.6%
2 842
8.4%
6 838
8.4%
3 835
8.3%
4 834
8.3%
11 832
8.3%
1 811
8.1%
9 810
8.1%
Other values (2) 1609
16.1%
ValueCountFrequency (%)
1 811
8.1%
2 842
8.4%
3 835
8.3%
4 834
8.3%
5 862
8.6%
6 838
8.4%
7 868
8.7%
8 801
8.0%
9 810
8.1%
10 808
8.1%
ValueCountFrequency (%)
12 859
8.6%
11 832
8.3%
10 808
8.1%
9 810
8.1%
8 801
8.0%
7 868
8.7%
6 838
8.4%
5 862
8.6%
4 834
8.3%
3 835
8.3%

시간
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.4488
Minimum0
Maximum23
Zeros399
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T02:05:58.862723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median11
Q317
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9127822
Coefficient of variation (CV)0.60379971
Kurtosis-1.2085263
Mean11.4488
Median Absolute Deviation (MAD)6
Skewness0.015786797
Sum114488
Variance47.786557
MonotonicityNot monotonic
2023-12-13T02:05:58.997799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 459
 
4.6%
6 458
 
4.6%
8 436
 
4.4%
15 427
 
4.3%
3 425
 
4.2%
13 423
 
4.2%
7 418
 
4.2%
4 416
 
4.2%
21 416
 
4.2%
16 415
 
4.2%
Other values (14) 5707
57.1%
ValueCountFrequency (%)
0 399
4.0%
1 400
4.0%
2 459
4.6%
3 425
4.2%
4 416
4.2%
5 403
4.0%
6 458
4.6%
7 418
4.2%
8 436
4.4%
9 401
4.0%
ValueCountFrequency (%)
23 411
4.1%
22 410
4.1%
21 416
4.2%
20 414
4.1%
19 415
4.2%
18 408
4.1%
17 411
4.1%
16 415
4.2%
15 427
4.3%
14 402
4.0%

시간평균 유량값
Text

Distinct1634
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T02:05:59.380223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.4873
Min length2

Characters and Unicode

Total characters34873
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique793 ?
Unique (%)7.9%

Sample

1st row0
2nd row33
3rd row23
4th row36
5th row92
ValueCountFrequency (%)
0 330
 
3.3%
12 95
 
0.9%
15 95
 
0.9%
3 93
 
0.9%
16 91
 
0.9%
17 91
 
0.9%
19 86
 
0.9%
20 85
 
0.9%
14 85
 
0.9%
5 84
 
0.8%
Other values (1624) 8865
88.6%
2023-12-13T02:05:59.881661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9990
28.6%
1 4061
11.6%
2 3183
 
9.1%
3 2588
 
7.4%
5 2392
 
6.9%
4 2329
 
6.7%
6 2300
 
6.6%
7 2096
 
6.0%
8 1992
 
5.7%
9 1962
 
5.6%
Other values (3) 1980
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24863
71.3%
Space Separator 9990
28.6%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4061
16.3%
2 3183
12.8%
3 2588
10.4%
5 2392
9.6%
4 2329
9.4%
6 2300
9.3%
7 2096
8.4%
8 1992
8.0%
9 1962
7.9%
0 1960
7.9%
Space Separator
ValueCountFrequency (%)
9990
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9990
28.6%
1 4061
11.6%
2 3183
 
9.1%
3 2588
 
7.4%
5 2392
 
6.9%
4 2329
 
6.7%
6 2300
 
6.6%
7 2096
 
6.0%
8 1992
 
5.7%
9 1962
 
5.6%
Other values (3) 1980
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9990
28.6%
1 4061
11.6%
2 3183
 
9.1%
3 2588
 
7.4%
5 2392
 
6.9%
4 2329
 
6.7%
6 2300
 
6.6%
7 2096
 
6.0%
8 1992
 
5.7%
9 1962
 
5.6%
Other values (3) 1980
 
5.7%

Interactions

2023-12-13T02:05:57.633627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.053293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.371202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.707719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.136413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.477366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.786942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.270396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:05:57.563640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:05:59.970982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유량계코드월시간
유량계코드1.0000.0000.000
월0.0001.0000.000
시간0.0000.0001.000
2023-12-13T02:06:00.066726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유량계코드월시간
유량계코드1.000-0.0090.015
월-0.0091.000-0.005
시간0.015-0.0051.000

Missing values

2023-12-13T02:05:57.882726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:05:57.960161image/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

유량계코드월시간시간평균 유량값
15557340150
93672747733
1628234671023
38671546336
1647634931292
3664141916213
4296198120453
20134398112238
5665235915
181433771223808
유량계코드월시간시간평균 유량값
19233389109421
124123072413
78572594967
2129940912111685
19255389117210
6211241719181
87372685137
168513657385
1800937779957
7028250520233