Overview

Dataset statistics

Number of variables5
Number of observations451
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.1 KiB
Average record size in memory43.3 B

Variable types

DateTime1
Categorical1
Numeric3

Dataset

Description여주정수장의 일단위 수질검사 결과입니다. 수질검사 결과는 탁도(NTU), 잔류염소(mg/L), 수소이온농도(pH) 정보를 제공합니다.
Author경기도 여주시
URLhttps://www.data.go.kr/data/15109762/fileData.do

Alerts

정수장명 has constant value ""Constant
검사일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:26:21.786216
Analysis finished2023-12-12 14:26:23.253416
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

검사일자
Date

UNIQUE 

Distinct451
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2020-11-10 00:00:00
Maximum2022-11-23 00:00:00
2023-12-12T23:26:23.331619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:23.464898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정수장명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
여주정수장
451 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여주정수장 451
100.0%

Length

2023-12-12T23:26:23.610278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:26:23.719355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여주정수장 451
100.0%

탁도
Real number (ℝ)

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.033968958
Minimum0.02
Maximum0.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T23:26:23.801109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.03
Q10.03
median0.03
Q30.04
95-th percentile0.05
Maximum0.08
Range0.06
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.0082993394
Coefficient of variation (CV)0.24432128
Kurtosis4.8772847
Mean0.033968958
Median Absolute Deviation (MAD)0
Skewness2.029436
Sum15.32
Variance6.8879034 × 10-5
MonotonicityNot monotonic
2023-12-12T23:26:23.900940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.03 317
70.3%
0.04 80
 
17.7%
0.05 27
 
6.0%
0.06 14
 
3.1%
0.02 10
 
2.2%
0.07 2
 
0.4%
0.08 1
 
0.2%
ValueCountFrequency (%)
0.02 10
 
2.2%
0.03 317
70.3%
0.04 80
 
17.7%
0.05 27
 
6.0%
0.06 14
 
3.1%
0.07 2
 
0.4%
0.08 1
 
0.2%
ValueCountFrequency (%)
0.08 1
 
0.2%
0.07 2
 
0.4%
0.06 14
 
3.1%
0.05 27
 
6.0%
0.04 80
 
17.7%
0.03 317
70.3%
0.02 10
 
2.2%

잔류염소
Real number (ℝ)

Distinct46
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.71829268
Minimum0.39
Maximum1.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T23:26:24.022251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.39
5-th percentile0.56
Q10.64
median0.72
Q30.79
95-th percentile0.87
Maximum1.07
Range0.68
Interquartile range (IQR)0.15

Descriptive statistics

Standard deviation0.097056517
Coefficient of variation (CV)0.13512113
Kurtosis-0.28408342
Mean0.71829268
Median Absolute Deviation (MAD)0.07
Skewness0.066653669
Sum323.95
Variance0.0094199675
MonotonicityNot monotonic
2023-12-12T23:26:24.163685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.68 21
 
4.7%
0.79 20
 
4.4%
0.74 20
 
4.4%
0.7 20
 
4.4%
0.77 19
 
4.2%
0.6 18
 
4.0%
0.62 17
 
3.8%
0.82 16
 
3.5%
0.83 16
 
3.5%
0.8 16
 
3.5%
Other values (36) 268
59.4%
ValueCountFrequency (%)
0.39 1
 
0.2%
0.51 1
 
0.2%
0.52 2
 
0.4%
0.53 3
 
0.7%
0.54 3
 
0.7%
0.55 9
2.0%
0.56 5
1.1%
0.57 5
1.1%
0.58 5
1.1%
0.59 11
2.4%
ValueCountFrequency (%)
1.07 1
 
0.2%
0.97 1
 
0.2%
0.95 1
 
0.2%
0.92 2
 
0.4%
0.91 4
0.9%
0.9 5
1.1%
0.89 5
1.1%
0.88 3
 
0.7%
0.87 8
1.8%
0.86 2
 
0.4%

수소이온농도
Real number (ℝ)

Distinct11
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4971175
Minimum6.8
Maximum7.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T23:26:24.299979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.8
5-th percentile7.25
Q17.4
median7.5
Q37.6
95-th percentile7.7
Maximum7.9
Range1.1
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.13829319
Coefficient of variation (CV)0.018446181
Kurtosis1.9914963
Mean7.4971175
Median Absolute Deviation (MAD)0.1
Skewness-0.79885268
Sum3381.2
Variance0.019125006
MonotonicityNot monotonic
2023-12-12T23:26:24.422832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
7.5 166
36.8%
7.6 110
24.4%
7.4 71
15.7%
7.7 39
 
8.6%
7.3 35
 
7.8%
7.2 15
 
3.3%
7.8 6
 
1.3%
7.1 5
 
1.1%
7.0 2
 
0.4%
6.8 1
 
0.2%
ValueCountFrequency (%)
6.8 1
 
0.2%
7.0 2
 
0.4%
7.1 5
 
1.1%
7.2 15
 
3.3%
7.3 35
 
7.8%
7.4 71
15.7%
7.5 166
36.8%
7.6 110
24.4%
7.7 39
 
8.6%
7.8 6
 
1.3%
ValueCountFrequency (%)
7.9 1
 
0.2%
7.8 6
 
1.3%
7.7 39
 
8.6%
7.6 110
24.4%
7.5 166
36.8%
7.4 71
15.7%
7.3 35
 
7.8%
7.2 15
 
3.3%
7.1 5
 
1.1%
7.0 2
 
0.4%

Interactions

2023-12-12T23:26:22.840130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:21.895277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:22.173069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:22.932656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:21.989218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:22.641886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:23.022680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:22.085481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:26:22.744875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:26:24.515835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
탁도잔류염소수소이온농도
탁도1.0000.1530.000
잔류염소0.1531.0000.217
수소이온농도0.0000.2171.000
2023-12-12T23:26:24.608726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
탁도잔류염소수소이온농도
탁도1.0000.154-0.146
잔류염소0.1541.000-0.159
수소이온농도-0.146-0.1591.000

Missing values

2023-12-12T23:26:23.124044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:26:23.214849image/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

검사일자정수장명탁도잔류염소수소이온농도
02020-11-10여주정수장0.040.766.8
12020-11-11여주정수장0.030.837.0
22020-11-12여주정수장0.030.827.3
32020-11-13여주정수장0.030.777.2
42020-11-16여주정수장0.030.797.0
52020-11-18여주정수장0.030.797.3
62020-11-19여주정수장0.030.817.1
72020-11-20여주정수장0.030.97.1
82020-11-23여주정수장0.040.827.2
92020-11-24여주정수장0.040.87.2
검사일자정수장명탁도잔류염소수소이온농도
4412022-11-10여주정수장0.030.727.6
4422022-11-11여주정수장0.040.717.7
4432022-11-14여주정수장0.030.667.7
4442022-11-15여주정수장0.040.597.5
4452022-11-16여주정수장0.030.87.6
4462022-11-17여주정수장0.030.827.7
4472022-11-18여주정수장0.030.717.6
4482022-11-21여주정수장0.030.77.7
4492022-11-22여주정수장0.030.687.7
4502022-11-23여주정수장0.030.77.7