Overview

Dataset statistics

Number of variables21
Number of observations764
Missing cells342
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory137.4 KiB
Average record size in memory184.2 B

Variable types

Numeric14
Categorical4
Text2
DateTime1

Alerts

last_load_dttm has constant value ""Constant
water10 is highly imbalanced (54.5%)Imbalance
water11 has 332 (43.5%) missing valuesMissing
skey has unique valuesUnique
water04 has 20 (2.6%) zerosZeros
water05 has 10 (1.3%) zerosZeros
water11 has 276 (36.1%) zerosZeros

Reproduction

Analysis started2024-04-20 17:20:34.851530
Analysis finished2024-04-20 17:20:35.308471
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct764
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96738.5
Minimum96357
Maximum97120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:35.679121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum96357
5-th percentile96395.15
Q196547.75
median96738.5
Q396929.25
95-th percentile97081.85
Maximum97120
Range763
Interquartile range (IQR)381.5

Descriptive statistics

Standard deviation220.69209
Coefficient of variation (CV)0.0022813264
Kurtosis-1.2
Mean96738.5
Median Absolute Deviation (MAD)191
Skewness0
Sum73908214
Variance48705
MonotonicityNot monotonic
2024-04-21T02:20:35.938411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97022 1
 
0.1%
96648 1
 
0.1%
96639 1
 
0.1%
96640 1
 
0.1%
96641 1
 
0.1%
96642 1
 
0.1%
96643 1
 
0.1%
96644 1
 
0.1%
96645 1
 
0.1%
96646 1
 
0.1%
Other values (754) 754
98.7%
ValueCountFrequency (%)
96357 1
0.1%
96358 1
0.1%
96359 1
0.1%
96360 1
0.1%
96361 1
0.1%
96362 1
0.1%
96363 1
0.1%
96364 1
0.1%
96365 1
0.1%
96366 1
0.1%
ValueCountFrequency (%)
97120 1
0.1%
97119 1
0.1%
97118 1
0.1%
97117 1
0.1%
97116 1
0.1%
97115 1
0.1%
97114 1
0.1%
97113 1
0.1%
97112 1
0.1%
97111 1
0.1%

inspec_yy
Real number (ℝ)

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.1741
Minimum2005
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:36.159009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2013
Q12014
median2016
Q32018
95-th percentile2020
Maximum2020
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8948019
Coefficient of variation (CV)0.0014357896
Kurtosis2.2219711
Mean2016.1741
Median Absolute Deviation (MAD)2
Skewness-1.1593545
Sum1540357
Variance8.3798779
MonotonicityNot monotonic
2024-04-21T02:20:36.350561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2019 100
13.1%
2018 100
13.1%
2017 100
13.1%
2016 100
13.1%
2013 84
11.0%
2015 84
11.0%
2014 84
11.0%
2020 80
10.5%
2008 23
 
3.0%
2005 9
 
1.2%
ValueCountFrequency (%)
2005 9
 
1.2%
2008 23
 
3.0%
2013 84
11.0%
2014 84
11.0%
2015 84
11.0%
2016 100
13.1%
2017 100
13.1%
2018 100
13.1%
2019 100
13.1%
2020 80
10.5%
ValueCountFrequency (%)
2020 80
10.5%
2019 100
13.1%
2018 100
13.1%
2017 100
13.1%
2016 100
13.1%
2015 84
11.0%
2014 84
11.0%
2013 84
11.0%
2008 23
 
3.0%
2005 9
 
1.2%

inspec_qt
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
1
219 
3
213 
2
180 
4
152 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 219
28.7%
3 213
27.9%
2 180
23.6%
4 152
19.9%

Length

2024-04-21T02:20:36.558956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:20:36.740489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 219
28.7%
3 213
27.9%
2 180
23.6%
4 152
19.9%

site
Categorical

Distinct30
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
5부두
 
33
북내항
 
33
북외항
 
33
남항
 
33
동천하류
 
33
Other values (25)
599 

Length

Max length7
Median length6
Mean length3.434555
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5부두
2nd row감천항
3rd row남외항
4th row남천만
5th row민락동

Common Values

ValueCountFrequency (%)
5부두 33
 
4.3%
북내항 33
 
4.3%
북외항 33
 
4.3%
남항 33
 
4.3%
동천하류 33
 
4.3%
남외항 33
 
4.3%
다대포항 32
 
4.2%
감천항 32
 
4.2%
다대포어시장 32
 
4.2%
발전소앞 32
 
4.2%
Other values (20) 438
57.3%

Length

2024-04-21T02:20:36.947492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5부두 33
 
4.3%
북외항 33
 
4.3%
남항 33
 
4.3%
동천하류 33
 
4.3%
남외항 33
 
4.3%
북내항 33
 
4.3%
발전소앞 32
 
4.2%
다대포어시장 32
 
4.2%
감천항 32
 
4.2%
다대포항 32
 
4.2%
Other values (20) 438
57.3%

water01
Real number (ℝ)

Distinct54
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.794503
Minimum20
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:37.172417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q122
median31
Q342
95-th percentile63
Maximum88
Range68
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.311217
Coefficient of variation (CV)0.41130684
Kurtosis0.38969686
Mean34.794503
Median Absolute Deviation (MAD)11
Skewness0.99900448
Sum26583
Variance204.81093
MonotonicityNot monotonic
2024-04-21T02:20:37.433253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 186
24.3%
30 60
 
7.9%
32 43
 
5.6%
28 35
 
4.6%
36 32
 
4.2%
40 31
 
4.1%
26 29
 
3.8%
23 22
 
2.9%
29 19
 
2.5%
58 18
 
2.4%
Other values (44) 289
37.8%
ValueCountFrequency (%)
20 186
24.3%
22 14
 
1.8%
23 22
 
2.9%
24 13
 
1.7%
25 1
 
0.1%
26 29
 
3.8%
28 35
 
4.6%
29 19
 
2.5%
30 60
 
7.9%
31 5
 
0.7%
ValueCountFrequency (%)
88 2
 
0.3%
87 1
 
0.1%
79 1
 
0.1%
76 2
 
0.3%
75 2
 
0.3%
72 1
 
0.1%
71 4
 
0.5%
68 11
1.4%
67 4
 
0.5%
66 3
 
0.4%

water02
Categorical

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
I
223 
II
213 
III
177 
IV
89 
V
62 

Length

Max length3
Median length2
Mean length1.8586387
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowV
2nd rowV
3rd rowV
4th rowII
5th rowIV

Common Values

ValueCountFrequency (%)
I 223
29.2%
II 213
27.9%
III 177
23.2%
IV 89
 
11.6%
V 62
 
8.1%

Length

2024-04-21T02:20:37.698272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:20:37.908265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 223
29.2%
ii 213
27.9%
iii 177
23.2%
iv 89
 
11.6%
v 62
 
8.1%

water03
Text

Distinct679
Distinct (%)89.0%
Missing1
Missing (%)0.1%
Memory size6.1 KiB
2024-04-21T02:20:39.285544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9200524
Min length3

Characters and Unicode

Total characters3754
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique603 ?
Unique (%)79.0%

Sample

1st row335.1
2nd row284.3
3rd row182.5
4th row48.5
5th row1,219.3
ValueCountFrequency (%)
143.2 4
 
0.5%
108.1 3
 
0.4%
130.8 3
 
0.4%
113.1 3
 
0.4%
94.4 3
 
0.4%
34.3 3
 
0.4%
151.6 3
 
0.4%
129.2 2
 
0.3%
160.4 2
 
0.3%
105.2 2
 
0.3%
Other values (669) 735
96.3%
2024-04-21T02:20:40.939406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 763
20.3%
1 562
15.0%
2 377
10.0%
3 277
 
7.4%
4 267
 
7.1%
6 251
 
6.7%
7 251
 
6.7%
5 244
 
6.5%
8 243
 
6.5%
9 230
 
6.1%
Other values (2) 289
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2916
77.7%
Other Punctuation 838
 
22.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 562
19.3%
2 377
12.9%
3 277
9.5%
4 267
9.2%
6 251
8.6%
7 251
8.6%
5 244
8.4%
8 243
8.3%
9 230
7.9%
0 214
 
7.3%
Other Punctuation
ValueCountFrequency (%)
. 763
91.1%
, 75
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
Common 3754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 763
20.3%
1 562
15.0%
2 377
10.0%
3 277
 
7.4%
4 267
 
7.1%
6 251
 
6.7%
7 251
 
6.7%
5 244
 
6.5%
8 243
 
6.5%
9 230
 
6.1%
Other values (2) 289
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 763
20.3%
1 562
15.0%
2 377
10.0%
3 277
 
7.4%
4 267
 
7.1%
6 251
 
6.7%
7 251
 
6.7%
5 244
 
6.5%
8 243
 
6.5%
9 230
 
6.1%
Other values (2) 289
 
7.7%

water04
Real number (ℝ)

ZEROS 

Distinct354
Distinct (%)46.4%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean29.275229
Minimum0
Maximum327.3
Zeros20
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:41.198618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.11
Q19.3
median19.2
Q332
95-th percentile98.54
Maximum327.3
Range327.3
Interquartile range (IQR)22.7

Descriptive statistics

Standard deviation38.898846
Coefficient of variation (CV)1.328729
Kurtosis19.951482
Mean29.275229
Median Absolute Deviation (MAD)11.1
Skewness3.8875852
Sum22337
Variance1513.1202
MonotonicityNot monotonic
2024-04-21T02:20:41.457880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
2.6%
2.0 19
 
2.5%
1.0 12
 
1.6%
22.0 11
 
1.4%
21.0 10
 
1.3%
27.0 10
 
1.3%
8.0 9
 
1.2%
4.0 9
 
1.2%
6.0 8
 
1.0%
3.0 8
 
1.0%
Other values (344) 647
84.7%
ValueCountFrequency (%)
0.0 20
2.6%
0.3 1
 
0.1%
0.7 3
 
0.4%
0.8 1
 
0.1%
0.9 1
 
0.1%
1.0 12
1.6%
1.1 1
 
0.1%
1.2 2
 
0.3%
1.9 1
 
0.1%
2.0 19
2.5%
ValueCountFrequency (%)
327.3 2
0.3%
289.9 2
0.3%
275.4 1
0.1%
252.0 1
0.1%
211.6 1
0.1%
200.3 1
0.1%
195.0 1
0.1%
190.0 2
0.3%
179.9 1
0.1%
179.1 2
0.3%

water05
Real number (ℝ)

ZEROS 

Distinct426
Distinct (%)55.8%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.9490564
Minimum0
Maximum41.51
Zeros10
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:41.843157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.17
Q10.775
median1.96
Q34.645
95-th percentile14.576
Maximum41.51
Range41.51
Interquartile range (IQR)3.87

Descriptive statistics

Standard deviation5.6831008
Coefficient of variation (CV)1.4391035
Kurtosis13.623965
Mean3.9490564
Median Absolute Deviation (MAD)1.5
Skewness3.2809939
Sum3013.13
Variance32.297635
MonotonicityNot monotonic
2024-04-21T02:20:42.262017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 12
 
1.6%
0.0 10
 
1.3%
1.1 7
 
0.9%
1.0 7
 
0.9%
0.3 7
 
0.9%
0.38 7
 
0.9%
0.5 7
 
0.9%
1.03 6
 
0.8%
0.91 6
 
0.8%
0.36 6
 
0.8%
Other values (416) 688
90.1%
ValueCountFrequency (%)
0.0 10
1.3%
0.02 2
 
0.3%
0.03 1
 
0.1%
0.05 1
 
0.1%
0.06 2
 
0.3%
0.07 1
 
0.1%
0.08 2
 
0.3%
0.09 4
 
0.5%
0.1 3
 
0.4%
0.12 1
 
0.1%
ValueCountFrequency (%)
41.51 2
0.3%
39.63 1
0.1%
35.54 2
0.3%
34.9 1
0.1%
31.82 2
0.3%
31.26 1
0.1%
29.1 1
0.1%
26.4 1
0.1%
26.24 1
0.1%
24.24 2
0.3%

water06
Real number (ℝ)

Distinct357
Distinct (%)46.8%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean92.374967
Minimum43.9
Maximum143.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:42.608128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.9
5-th percentile68.71
Q185.6
median94.1
Q399.65
95-th percentile111.25
Maximum143.8
Range99.9
Interquartile range (IQR)14.05

Descriptive statistics

Standard deviation12.767352
Coefficient of variation (CV)0.13821224
Kurtosis1.3529742
Mean92.374967
Median Absolute Deviation (MAD)6.9
Skewness-0.44146102
Sum70482.1
Variance163.00526
MonotonicityNot monotonic
2024-04-21T02:20:42.867790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.7 8
 
1.0%
94.4 7
 
0.9%
96.4 7
 
0.9%
94.1 7
 
0.9%
96.7 7
 
0.9%
90.5 7
 
0.9%
93.3 6
 
0.8%
93.4 6
 
0.8%
98.7 6
 
0.8%
98.6 6
 
0.8%
Other values (347) 696
91.1%
ValueCountFrequency (%)
43.9 2
0.3%
52.2 1
0.1%
53.4 1
0.1%
55.2 1
0.1%
55.8 1
0.1%
56.0 1
0.1%
56.3 1
0.1%
57.4 2
0.3%
57.8 1
0.1%
58.7 1
0.1%
ValueCountFrequency (%)
143.8 1
0.1%
134.5 1
0.1%
128.7 1
0.1%
125.2 1
0.1%
124.6 1
0.1%
123.3 1
0.1%
123.2 1
0.1%
122.9 1
0.1%
122.7 1
0.1%
121.8 1
0.1%

water07
Real number (ℝ)

Distinct66
Distinct (%)8.7%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.0901704
Minimum0.4
Maximum8.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:43.119896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile1
Q12
median2.9
Q34
95-th percentile5.5
Maximum8.5
Range8.1
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4459629
Coefficient of variation (CV)0.46792336
Kurtosis0.81737187
Mean3.0901704
Median Absolute Deviation (MAD)0.9
Skewness0.7598
Sum2357.8
Variance2.0908088
MonotonicityNot monotonic
2024-04-21T02:20:43.389540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.5 56
 
7.3%
3.0 55
 
7.2%
3.5 50
 
6.5%
2.0 47
 
6.2%
4.0 34
 
4.5%
4.5 32
 
4.2%
5.0 30
 
3.9%
1.5 29
 
3.8%
2.8 26
 
3.4%
2.7 20
 
2.6%
Other values (56) 384
50.3%
ValueCountFrequency (%)
0.4 2
 
0.3%
0.5 10
1.3%
0.6 9
1.2%
0.7 3
 
0.4%
0.8 8
 
1.0%
0.9 5
 
0.7%
1.0 7
 
0.9%
1.1 1
 
0.1%
1.2 5
 
0.7%
1.3 20
2.6%
ValueCountFrequency (%)
8.5 5
0.7%
7.9 1
 
0.1%
7.5 1
 
0.1%
7.2 1
 
0.1%
7.1 1
 
0.1%
7.0 2
 
0.3%
6.8 3
0.4%
6.6 1
 
0.1%
6.5 6
0.8%
6.3 1
 
0.1%

water08
Real number (ℝ)

Distinct18
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1235602
Minimum7.1
Maximum8.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:43.616717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.1
5-th percentile7.815
Q18
median8.1
Q38.2
95-th percentile8.4
Maximum8.9
Range1.8
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.17815097
Coefficient of variation (CV)0.021930159
Kurtosis4.3315162
Mean8.1235602
Median Absolute Deviation (MAD)0.1
Skewness-0.97183046
Sum6206.4
Variance0.031737767
MonotonicityNot monotonic
2024-04-21T02:20:43.807506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8.1 208
27.2%
8.2 200
26.2%
8.0 124
16.2%
8.3 102
13.4%
7.9 43
 
5.6%
8.4 35
 
4.6%
7.8 12
 
1.6%
7.6 10
 
1.3%
7.7 9
 
1.2%
8.5 9
 
1.2%
Other values (8) 12
 
1.6%
ValueCountFrequency (%)
7.1 1
 
0.1%
7.2 1
 
0.1%
7.3 1
 
0.1%
7.4 1
 
0.1%
7.5 4
 
0.5%
7.6 10
 
1.3%
7.7 9
 
1.2%
7.8 12
 
1.6%
7.9 43
 
5.6%
8.0 124
16.2%
ValueCountFrequency (%)
8.9 1
 
0.1%
8.7 2
 
0.3%
8.6 1
 
0.1%
8.5 9
 
1.2%
8.4 35
 
4.6%
8.3 102
13.4%
8.2 200
26.2%
8.1 208
27.2%
8.0 124
16.2%
7.9 43
 
5.6%

water09
Text

Distinct93
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
2024-04-21T02:20:44.459780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.6727749
Min length1

Characters and Unicode

Total characters2042
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)3.0%

Sample

1st row9,200
2nd row16,000
3rd row350
4th row700
5th row2,800
ValueCountFrequency (%)
2 56
 
7.3%
0 39
 
5.1%
130 33
 
4.3%
5 28
 
3.7%
350 25
 
3.3%
170 25
 
3.3%
330 24
 
3.1%
8 22
 
2.9%
790 20
 
2.6%
33 19
 
2.5%
Other values (83) 473
61.9%
2024-04-21T02:20:45.554260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 622
30.5%
3 237
 
11.6%
1 226
 
11.1%
2 224
 
11.0%
4 160
 
7.8%
7 132
 
6.5%
, 126
 
6.2%
5 117
 
5.7%
9 99
 
4.8%
8 62
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1916
93.8%
Other Punctuation 126
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 622
32.5%
3 237
 
12.4%
1 226
 
11.8%
2 224
 
11.7%
4 160
 
8.4%
7 132
 
6.9%
5 117
 
6.1%
9 99
 
5.2%
8 62
 
3.2%
6 37
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2042
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 622
30.5%
3 237
 
11.6%
1 226
 
11.1%
2 224
 
11.0%
4 160
 
7.8%
7 132
 
6.5%
, 126
 
6.2%
5 117
 
5.7%
9 99
 
4.8%
8 62
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 622
30.5%
3 237
 
11.6%
1 226
 
11.1%
2 224
 
11.0%
4 160
 
7.8%
7 132
 
6.5%
, 126
 
6.2%
5 117
 
5.7%
9 99
 
4.8%
8 62
 
3.0%

water10
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
<NA>
512 
0.0
234 
0.1
 
15
0.2
 
2
1.4
 
1

Length

Max length4
Median length4
Mean length3.6701571
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 512
67.0%
0.0 234
30.6%
0.1 15
 
2.0%
0.2 2
 
0.3%
1.4 1
 
0.1%

Length

2024-04-21T02:20:45.960467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:20:46.291613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 512
67.0%
0.0 234
30.6%
0.1 15
 
2.0%
0.2 2
 
0.3%
1.4 1
 
0.1%

water11
Real number (ℝ)

MISSING  ZEROS 

Distinct61
Distinct (%)14.1%
Missing332
Missing (%)43.5%
Infinite0
Infinite (%)0.0%
Mean0.25550926
Minimum0
Maximum5.71
Zeros276
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:46.643964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2
95-th percentile1.354
Maximum5.71
Range5.71
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.66339017
Coefficient of variation (CV)2.5963449
Kurtosis27.929229
Mean0.25550926
Median Absolute Deviation (MAD)0
Skewness4.6883137
Sum110.38
Variance0.44008651
MonotonicityNot monotonic
2024-04-21T02:20:47.063473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 276
36.1%
0.1 34
 
4.5%
0.2 25
 
3.3%
0.3 11
 
1.4%
0.4 10
 
1.3%
0.5 6
 
0.8%
0.6 5
 
0.7%
1.0 3
 
0.4%
1.1 3
 
0.4%
1.9 3
 
0.4%
Other values (51) 56
 
7.3%
(Missing) 332
43.5%
ValueCountFrequency (%)
0.0 276
36.1%
0.1 34
 
4.5%
0.11 1
 
0.1%
0.13 1
 
0.1%
0.14 1
 
0.1%
0.18 1
 
0.1%
0.2 25
 
3.3%
0.24 1
 
0.1%
0.25 1
 
0.1%
0.26 1
 
0.1%
ValueCountFrequency (%)
5.71 1
0.1%
5.42 1
0.1%
4.87 1
0.1%
4.2 1
0.1%
2.9 1
0.1%
2.52 1
0.1%
2.5 1
0.1%
2.48 1
0.1%
2.34 1
0.1%
2.3 1
0.1%

water12
Real number (ℝ)

Distinct63
Distinct (%)8.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.6208388
Minimum0.1
Maximum10.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:47.641456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.7
median1.1
Q32.05
95-th percentile4.39
Maximum10.9
Range10.8
Interquartile range (IQR)1.35

Descriptive statistics

Standard deviation1.4386576
Coefficient of variation (CV)0.88760069
Kurtosis8.9233527
Mean1.6208388
Median Absolute Deviation (MAD)0.5
Skewness2.3904326
Sum1236.7
Variance2.0697358
MonotonicityNot monotonic
2024-04-21T02:20:47.893600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 59
 
7.7%
1.0 55
 
7.2%
0.9 45
 
5.9%
0.4 45
 
5.9%
0.6 45
 
5.9%
0.7 37
 
4.8%
1.2 36
 
4.7%
1.4 34
 
4.5%
1.1 31
 
4.1%
0.5 28
 
3.7%
Other values (53) 348
45.5%
ValueCountFrequency (%)
0.1 5
 
0.7%
0.2 24
3.1%
0.3 16
 
2.1%
0.4 45
5.9%
0.5 28
3.7%
0.6 45
5.9%
0.7 37
4.8%
0.8 59
7.7%
0.9 45
5.9%
1.0 55
7.2%
ValueCountFrequency (%)
10.9 1
0.1%
10.8 2
0.3%
10.6 1
0.1%
7.7 1
0.1%
6.8 1
0.1%
6.6 2
0.3%
6.4 2
0.3%
6.2 1
0.1%
5.9 1
0.1%
5.8 1
0.1%

water13
Real number (ℝ)

Distinct74
Distinct (%)9.7%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean7.9275229
Minimum0.1
Maximum12.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:48.139880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile5.81
Q17.1
median8.1
Q38.8
95-th percentile9.9
Maximum12.4
Range12.3
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation1.3608233
Coefficient of variation (CV)0.17165807
Kurtosis4.5374621
Mean7.9275229
Median Absolute Deviation (MAD)0.8
Skewness-0.78942649
Sum6048.7
Variance1.8518399
MonotonicityNot monotonic
2024-04-21T02:20:48.396828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.4 38
 
5.0%
7.6 33
 
4.3%
8.3 31
 
4.1%
8.1 29
 
3.8%
7.3 27
 
3.5%
6.9 25
 
3.3%
8.2 25
 
3.3%
8.5 25
 
3.3%
6.8 24
 
3.1%
8.0 24
 
3.1%
Other values (64) 482
63.1%
ValueCountFrequency (%)
0.1 2
0.3%
0.4 1
0.1%
1.2 1
0.1%
3.2 1
0.1%
3.5 1
0.1%
4.4 1
0.1%
4.6 1
0.1%
4.8 1
0.1%
4.9 1
0.1%
5.0 2
0.3%
ValueCountFrequency (%)
12.4 2
0.3%
12.1 2
0.3%
11.8 1
 
0.1%
11.6 1
 
0.1%
11.2 2
0.3%
11.1 3
0.4%
11.0 1
 
0.1%
10.9 1
 
0.1%
10.8 1
 
0.1%
10.7 1
 
0.1%

water14
Real number (ℝ)

Distinct202
Distinct (%)26.5%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean17.658847
Minimum5.9
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:48.646163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.9
5-th percentile9.41
Q112.9
median16.7
Q322.4
95-th percentile28.5
Maximum30
Range24.1
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.8682145
Coefficient of variation (CV)0.33231018
Kurtosis-0.80897747
Mean17.658847
Median Absolute Deviation (MAD)4.3
Skewness0.41844278
Sum13473.7
Variance34.435942
MonotonicityNot monotonic
2024-04-21T02:20:48.899364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.4 13
 
1.7%
16.8 13
 
1.7%
12.2 13
 
1.7%
16.9 12
 
1.6%
16.7 11
 
1.4%
16.6 10
 
1.3%
16.5 10
 
1.3%
12.3 9
 
1.2%
15.6 9
 
1.2%
23.3 8
 
1.0%
Other values (192) 655
85.7%
ValueCountFrequency (%)
5.9 1
 
0.1%
7.2 1
 
0.1%
7.3 1
 
0.1%
7.6 1
 
0.1%
7.7 2
 
0.3%
8.1 3
0.4%
8.2 1
 
0.1%
8.5 6
0.8%
8.6 2
 
0.3%
8.7 1
 
0.1%
ValueCountFrequency (%)
30.0 2
0.3%
29.9 1
 
0.1%
29.8 1
 
0.1%
29.6 1
 
0.1%
29.5 1
 
0.1%
29.4 1
 
0.1%
29.3 2
0.3%
29.2 1
 
0.1%
29.1 2
0.3%
29.0 3
0.4%

water15
Real number (ℝ)

Distinct38
Distinct (%)5.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean48.402359
Minimum0
Maximum62
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:49.128438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36
Q148
median51
Q352
95-th percentile53
Maximum62
Range62
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.045547
Coefficient of variation (CV)0.14556206
Kurtosis17.253369
Mean48.402359
Median Absolute Deviation (MAD)1
Skewness-3.7322846
Sum36931
Variance49.639732
MonotonicityNot monotonic
2024-04-21T02:20:49.358531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
52 168
22.0%
51 134
17.5%
50 109
14.3%
53 81
10.6%
49 67
 
8.8%
48 40
 
5.2%
47 27
 
3.5%
46 22
 
2.9%
45 13
 
1.7%
40 11
 
1.4%
Other values (28) 91
11.9%
ValueCountFrequency (%)
0 2
0.3%
6 3
0.4%
7 2
0.3%
9 1
 
0.1%
15 1
 
0.1%
16 1
 
0.1%
18 2
0.3%
19 2
0.3%
22 1
 
0.1%
23 1
 
0.1%
ValueCountFrequency (%)
62 1
 
0.1%
54 2
 
0.3%
53 81
10.6%
52 168
22.0%
51 134
17.5%
50 109
14.3%
49 67
 
8.8%
48 40
 
5.2%
47 27
 
3.5%
46 22
 
2.9%

water16
Real number (ℝ)

Distinct124
Distinct (%)16.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean31.570904
Minimum0.2
Maximum35.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-21T02:20:49.601263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile22.6
Q131.45
median33.1
Q334
95-th percentile34.7
Maximum35.3
Range35.1
Interquartile range (IQR)2.55

Descriptive statistics

Standard deviation4.8432644
Coefficient of variation (CV)0.15340911
Kurtosis15.060768
Mean31.570904
Median Absolute Deviation (MAD)1.1
Skewness-3.5142177
Sum24088.6
Variance23.45721
MonotonicityNot monotonic
2024-04-21T02:20:49.854383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.1 29
 
3.8%
33.1 27
 
3.5%
32.8 27
 
3.5%
34.6 27
 
3.5%
33.9 23
 
3.0%
34.2 23
 
3.0%
32.9 22
 
2.9%
33.3 22
 
2.9%
34.5 22
 
2.9%
33.6 21
 
2.7%
Other values (114) 520
68.1%
ValueCountFrequency (%)
0.2 2
0.3%
3.4 3
0.4%
3.6 2
0.3%
5.2 1
 
0.1%
8.9 1
 
0.1%
9.5 1
 
0.1%
10.8 2
0.3%
11.3 2
0.3%
14.0 1
 
0.1%
14.2 1
 
0.1%
ValueCountFrequency (%)
35.3 3
 
0.4%
35.2 6
 
0.8%
35.1 6
 
0.8%
35.0 5
 
0.7%
34.9 6
 
0.8%
34.8 9
 
1.2%
34.7 17
2.2%
34.6 27
3.5%
34.5 22
2.9%
34.4 21
2.7%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.1 KiB
Minimum2020-12-21 19:43:30
Maximum2020-12-21 19:43:30
2024-04-21T02:20:50.145841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:20:50.431031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

skeyinspec_yyinspec_qtsitewater01water02water03water04water05water06water07water08water09water10water11water12water13water14water15water16last_load_dttm
097022202035부두68V335.135.611.371.52.08.29,200<NA><NA>3.26.420.54730.22020-12-21 19:43:30
19702320203감천항62V284.340.814.3277.22.88.016,000<NA><NA>2.68.823.24227.02020-12-21 19:43:30
29702420203남외항61V182.532.435.5479.11.58.3350<NA><NA>4.212.124.03824.22020-12-21 19:43:30
39702520203남천만32II48.516.710.56117.12.57.7700<NA><NA>1.810.919.05032.82020-12-21 19:43:30
49702620203민락동51IV1,219.368.712.73124.62.48.12,800<NA><NA>3.49.620.24730.62020-12-21 19:43:30
59702720203북내항58IV285.312.811.2373.53.07.835,000<NA><NA>3.97.320.54427.52020-12-21 19:43:30
69702820203북외항52IV158.76.011.3372.23.08.01,400<NA><NA>2.38.120.54730.52020-12-21 19:43:30
79702920203수영만48IV2,494.8103.814.4596.72.98.016,000<NA><NA>3.88.120.84931.62020-12-21 19:43:30
89703020203신외항71V45.917.031.8262.21.68.29,200<NA><NA>4.711.224.34126.12020-12-21 19:43:30
99703120203이기대31II104.236.88.9998.33.17.9490<NA><NA>1.38.418.15133.02020-12-21 19:43:30
skeyinspec_yyinspec_qtsitewater01water02water03water04water05water06water07water08water09water10water11water12water13water14water15water16last_load_dttm
7549711120132수영만56IV3,020.5252.01.0113.82.87.33,5000.00.04.36.117.53723.42020-12-21 19:43:30
7559711220132신외항26II110.031.02.593.62.58.2490.00.00.88.317.95033.12020-12-21 19:43:30
7569711320132해운대22I111.373.07.3119.12.88.29200.00.00.99.615.45133.42020-12-21 19:43:30
7579711420132다대포항32II335.732.02.599.22.68.2110.00.00.98.417.95133.22020-12-21 19:43:30
7589711520132동천하류62V1,635.6169.00.185.62.07.53,5000.00.05.21.217.64528.92020-12-21 19:43:30
7599711620132발전소앞22I33.622.04.0118.83.08.3140.00.01.09.118.55133.72020-12-21 19:43:30
7609711720132다대포어시장33II124.227.02.498.61.88.25400.00.01.27.817.05133.32020-12-21 19:43:30
7619711820133고리20I148.52.03.781.63.28.220.00.01.09.021.75133.42020-12-21 19:43:30
7629711920133남항37III166.72.00.7105.75.48.0490.00.01.67.126.24931.92020-12-21 19:43:30
7639712020133녹산58IV150.627.02.087.71.58.11300.00.04.15.927.54226.72020-12-21 19:43:30