Overview

Dataset statistics

Number of variables21
Number of observations784
Missing cells362
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.0 KiB
Average record size in memory184.2 B

Variable types

Numeric14
Categorical5
Text2

Alerts

last_load_dttm has constant value ""Constant
water10 is highly imbalanced (55.1%)Imbalance
water11 has 352 (44.9%) missing valuesMissing
skey has unique valuesUnique
water04 has 20 (2.6%) zerosZeros
water05 has 10 (1.3%) zerosZeros
water11 has 276 (35.2%) zerosZeros

Reproduction

Analysis started2024-04-20 17:17:39.086926
Analysis finished2024-04-20 17:17:39.441008
Duration0.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

UNIQUE 

Distinct784
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143628.5
Minimum143237
Maximum144020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:39.574462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum143237
5-th percentile143276.15
Q1143432.75
median143628.5
Q3143824.25
95-th percentile143980.85
Maximum144020
Range783
Interquartile range (IQR)391.5

Descriptive statistics

Standard deviation226.4656
Coefficient of variation (CV)0.0015767455
Kurtosis-1.2
Mean143628.5
Median Absolute Deviation (MAD)196
Skewness0
Sum1.1260474 × 108
Variance51286.667
MonotonicityNot monotonic
2024-04-21T02:17:39.944675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143900 1
 
0.1%
143393 1
 
0.1%
143395 1
 
0.1%
143396 1
 
0.1%
143397 1
 
0.1%
143398 1
 
0.1%
143399 1
 
0.1%
143400 1
 
0.1%
143401 1
 
0.1%
143402 1
 
0.1%
Other values (774) 774
98.7%
ValueCountFrequency (%)
143237 1
0.1%
143238 1
0.1%
143239 1
0.1%
143240 1
0.1%
143241 1
0.1%
143242 1
0.1%
143243 1
0.1%
143244 1
0.1%
143245 1
0.1%
143246 1
0.1%
ValueCountFrequency (%)
144020 1
0.1%
144019 1
0.1%
144018 1
0.1%
144017 1
0.1%
144016 1
0.1%
144015 1
0.1%
144014 1
0.1%
144013 1
0.1%
144012 1
0.1%
144011 1
0.1%

inspec_yy
Real number (ℝ)

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.2717
Minimum2005
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:40.322961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2013
Q12014
median2017
Q32019
95-th percentile2020
Maximum2020
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9206473
Coefficient of variation (CV)0.0014485386
Kurtosis2.1320483
Mean2016.2717
Median Absolute Deviation (MAD)2
Skewness-1.1429225
Sum1580757
Variance8.5301806
MonotonicityNot monotonic
2024-04-21T02:17:40.543142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2017 100
12.8%
2018 100
12.8%
2016 100
12.8%
2020 100
12.8%
2019 100
12.8%
2015 84
10.7%
2014 84
10.7%
2013 84
10.7%
2008 23
 
2.9%
2005 9
 
1.1%
ValueCountFrequency (%)
2005 9
 
1.1%
2008 23
 
2.9%
2013 84
10.7%
2014 84
10.7%
2015 84
10.7%
2016 100
12.8%
2017 100
12.8%
2018 100
12.8%
2019 100
12.8%
2020 100
12.8%
ValueCountFrequency (%)
2020 100
12.8%
2019 100
12.8%
2018 100
12.8%
2017 100
12.8%
2016 100
12.8%
2015 84
10.7%
2014 84
10.7%
2013 84
10.7%
2008 23
 
2.9%
2005 9
 
1.1%

inspec_qt
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
1
219 
3
213 
2
180 
4
172 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 219
27.9%
3 213
27.2%
2 180
23.0%
4 172
21.9%

Length

2024-04-21T02:17:40.770090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:17:40.961520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 219
27.9%
3 213
27.2%
2 180
23.0%
4 172
21.9%

site
Categorical

Distinct30
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
북내항
 
34
남외항
 
34
5부두
 
34
북외항
 
34
남항
 
34
Other values (25)
614 

Length

Max length7
Median length6
Mean length3.4477041
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북내항
2nd row북외항
3rd row수영만
4th row이기대
5th row해운대

Common Values

ValueCountFrequency (%)
북내항 34
 
4.3%
남외항 34
 
4.3%
5부두 34
 
4.3%
북외항 34
 
4.3%
남항 34
 
4.3%
동천하류 34
 
4.3%
감천항 33
 
4.2%
다대포어시장 33
 
4.2%
발전소앞 33
 
4.2%
다대포항 33
 
4.2%
Other values (20) 448
57.1%

Length

2024-04-21T02:17:41.168341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
북내항 34
 
4.3%
5부두 34
 
4.3%
북외항 34
 
4.3%
남항 34
 
4.3%
동천하류 34
 
4.3%
남외항 34
 
4.3%
다대포항 33
 
4.2%
발전소앞 33
 
4.2%
다대포어시장 33
 
4.2%
감천항 33
 
4.2%
Other values (20) 448
57.1%

water01
Real number (ℝ)

Distinct54
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.692602
Minimum20
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:41.394283image/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 deviation14.309966
Coefficient of variation (CV)0.41247888
Kurtosis0.38309858
Mean34.692602
Median Absolute Deviation (MAD)11
Skewness1.0011816
Sum27199
Variance204.77512
MonotonicityNot monotonic
2024-04-21T02:17:41.849201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 195
24.9%
30 61
 
7.8%
32 44
 
5.6%
28 35
 
4.5%
36 34
 
4.3%
40 31
 
4.0%
26 29
 
3.7%
23 22
 
2.8%
29 19
 
2.4%
58 19
 
2.4%
Other values (44) 295
37.6%
ValueCountFrequency (%)
20 195
24.9%
22 14
 
1.8%
23 22
 
2.8%
24 15
 
1.9%
25 1
 
0.1%
26 29
 
3.7%
28 35
 
4.5%
29 19
 
2.4%
30 61
 
7.8%
31 5
 
0.6%
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 (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
I
232 
II
217 
III
181 
IV
91 
V
63 

Length

Max length3
Median length2
Mean length1.8545918
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIII
2nd rowI
3rd rowIII
4th rowII
5th rowII

Common Values

ValueCountFrequency (%)
I 232
29.6%
II 217
27.7%
III 181
23.1%
IV 91
 
11.6%
V 63
 
8.0%

Length

2024-04-21T02:17:42.106576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:17:42.320515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 232
29.6%
ii 217
27.7%
iii 181
23.1%
iv 91
 
11.6%
v 63
 
8.0%

water03
Text

Distinct698
Distinct (%)89.1%
Missing1
Missing (%)0.1%
Memory size6.2 KiB
2024-04-21T02:17:43.759109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.916986
Min length3

Characters and Unicode

Total characters3850
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

Unique621 ?
Unique (%)79.3%

Sample

1st row25.1
2nd row41.5
3rd row1,654.5
4th row310.7
5th row485.4
ValueCountFrequency (%)
143.2 4
 
0.5%
151.6 3
 
0.4%
113.1 3
 
0.4%
94.4 3
 
0.4%
108.1 3
 
0.4%
130.8 3
 
0.4%
34.3 3
 
0.4%
723.1 2
 
0.3%
444.0 2
 
0.3%
96.7 2
 
0.3%
Other values (688) 755
96.4%
2024-04-21T02:17:45.424551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 783
20.3%
1 574
14.9%
2 387
10.1%
3 287
 
7.5%
4 275
 
7.1%
6 257
 
6.7%
7 256
 
6.6%
5 251
 
6.5%
8 250
 
6.5%
9 235
 
6.1%
Other values (2) 295
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2992
77.7%
Other Punctuation 858
 
22.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 574
19.2%
2 387
12.9%
3 287
9.6%
4 275
9.2%
6 257
8.6%
7 256
8.6%
5 251
8.4%
8 250
8.4%
9 235
7.9%
0 220
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 783
91.3%
, 75
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
Common 3850
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 783
20.3%
1 574
14.9%
2 387
10.1%
3 287
 
7.5%
4 275
 
7.1%
6 257
 
6.7%
7 256
 
6.6%
5 251
 
6.5%
8 250
 
6.5%
9 235
 
6.1%
Other values (2) 295
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 783
20.3%
1 574
14.9%
2 387
10.1%
3 287
 
7.5%
4 275
 
7.1%
6 257
 
6.7%
7 256
 
6.6%
5 251
 
6.5%
8 250
 
6.5%
9 235
 
6.1%
Other values (2) 295
 
7.7%

water04
Real number (ℝ)

ZEROS 

Distinct366
Distinct (%)46.7%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean29.363985
Minimum0
Maximum327.3
Zeros20
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:45.669671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.2
Q19.3
median19.3
Q332.4
95-th percentile96.96
Maximum327.3
Range327.3
Interquartile range (IQR)23.1

Descriptive statistics

Standard deviation38.612253
Coefficient of variation (CV)1.3149528
Kurtosis20.0127
Mean29.363985
Median Absolute Deviation (MAD)11.3
Skewness3.8758227
Sum22992
Variance1490.9061
MonotonicityNot monotonic
2024-04-21T02:17:45.921435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
2.6%
2.0 19
 
2.4%
1.0 12
 
1.5%
22.0 11
 
1.4%
21.0 10
 
1.3%
27.0 10
 
1.3%
8.0 10
 
1.3%
4.0 9
 
1.1%
26.0 8
 
1.0%
20.0 8
 
1.0%
Other values (356) 666
84.9%
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
1.5%
1.1 1
 
0.1%
1.2 2
 
0.3%
1.9 1
 
0.1%
2.0 19
2.4%
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 

Distinct436
Distinct (%)55.7%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.9185824
Minimum0
Maximum41.51
Zeros10
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:46.181064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.171
Q10.795
median2
Q34.61
95-th percentile14.444
Maximum41.51
Range41.51
Interquartile range (IQR)3.815

Descriptive statistics

Standard deviation5.6181333
Coefficient of variation (CV)1.4337158
Kurtosis14.031298
Mean3.9185824
Median Absolute Deviation (MAD)1.51
Skewness3.3241329
Sum3068.25
Variance31.563422
MonotonicityNot monotonic
2024-04-21T02:17:46.420422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 12
 
1.5%
0.0 10
 
1.3%
0.5 7
 
0.9%
1.0 7
 
0.9%
1.1 7
 
0.9%
0.38 7
 
0.9%
0.3 7
 
0.9%
0.91 6
 
0.8%
1.03 6
 
0.8%
0.36 6
 
0.8%
Other values (426) 708
90.3%
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)

Distinct360
Distinct (%)46.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean92.354789
Minimum43.9
Maximum143.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:46.668309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.9
5-th percentile68.8
Q185.65
median94
Q399.5
95-th percentile110.79
Maximum143.8
Range99.9
Interquartile range (IQR)13.85

Descriptive statistics

Standard deviation12.658176
Coefficient of variation (CV)0.13706031
Kurtosis1.3958091
Mean92.354789
Median Absolute Deviation (MAD)6.8
Skewness-0.44005758
Sum72313.8
Variance160.22941
MonotonicityNot monotonic
2024-04-21T02:17:46.928627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95.7 8
 
1.0%
90.5 7
 
0.9%
96.4 7
 
0.9%
94.1 7
 
0.9%
94.4 7
 
0.9%
96.7 7
 
0.9%
96.3 6
 
0.8%
93.4 6
 
0.8%
98.7 6
 
0.8%
98.6 6
 
0.8%
Other values (350) 716
91.3%
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 (%)8.4%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3.1172414
Minimum0.4
Maximum8.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:47.225611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile1
Q12.1
median3
Q34
95-th percentile5.5
Maximum8.5
Range8.1
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.4524858
Coefficient of variation (CV)0.46595232
Kurtosis0.68275197
Mean3.1172414
Median Absolute Deviation (MAD)1
Skewness0.72286442
Sum2440.8
Variance2.1097151
MonotonicityNot monotonic
2024-04-21T02:17:47.580302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.5 57
 
7.3%
3.0 56
 
7.1%
3.5 51
 
6.5%
2.0 48
 
6.1%
4.0 36
 
4.6%
4.5 32
 
4.1%
5.0 31
 
4.0%
1.5 30
 
3.8%
2.8 26
 
3.3%
5.5 24
 
3.1%
Other values (56) 392
50.0%
ValueCountFrequency (%)
0.4 2
 
0.3%
0.5 10
1.3%
0.6 9
1.1%
0.7 3
 
0.4%
0.8 8
 
1.0%
0.9 5
 
0.6%
1.0 7
 
0.9%
1.1 1
 
0.1%
1.2 5
 
0.6%
1.3 20
2.6%
ValueCountFrequency (%)
8.5 5
0.6%
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 (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1197704
Minimum7.1
Maximum8.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:47.806668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.1784836
Coefficient of variation (CV)0.021981361
Kurtosis4.1394919
Mean8.1197704
Median Absolute Deviation (MAD)0.1
Skewness-0.93465664
Sum6365.9
Variance0.031856397
MonotonicityNot monotonic
2024-04-21T02:17:47.996397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8.1 213
27.2%
8.2 200
25.5%
8.0 134
17.1%
8.3 102
13.0%
7.9 45
 
5.7%
8.4 35
 
4.5%
7.8 14
 
1.8%
7.6 11
 
1.4%
7.7 9
 
1.1%
8.5 9
 
1.1%
Other values (8) 12
 
1.5%
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 11
 
1.4%
7.7 9
 
1.1%
7.8 14
 
1.8%
7.9 45
 
5.7%
8.0 134
17.1%
ValueCountFrequency (%)
8.9 1
 
0.1%
8.7 2
 
0.3%
8.6 1
 
0.1%
8.5 9
 
1.1%
8.4 35
 
4.5%
8.3 102
13.0%
8.2 200
25.5%
8.1 213
27.2%
8.0 134
17.1%
7.9 45
 
5.7%

water09
Text

Distinct94
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-21T02:17:48.685621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.6747449
Min length1

Characters and Unicode

Total characters2097
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

Unique24 ?
Unique (%)3.1%

Sample

1st row7
2nd row5
3rd row790
4th row45
5th row330
ValueCountFrequency (%)
2 57
 
7.3%
0 40
 
5.1%
130 34
 
4.3%
5 28
 
3.6%
170 26
 
3.3%
350 26
 
3.3%
330 24
 
3.1%
8 22
 
2.8%
49 21
 
2.7%
790 20
 
2.6%
Other values (84) 486
62.0%
2024-04-21T02:17:49.599918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 638
30.4%
3 243
 
11.6%
2 232
 
11.1%
1 231
 
11.0%
4 165
 
7.9%
7 136
 
6.5%
, 130
 
6.2%
5 119
 
5.7%
9 103
 
4.9%
8 62
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1967
93.8%
Other Punctuation 130
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 638
32.4%
3 243
 
12.4%
2 232
 
11.8%
1 231
 
11.7%
4 165
 
8.4%
7 136
 
6.9%
5 119
 
6.0%
9 103
 
5.2%
8 62
 
3.2%
6 38
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2097
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 638
30.4%
3 243
 
11.6%
2 232
 
11.1%
1 231
 
11.0%
4 165
 
7.9%
7 136
 
6.5%
, 130
 
6.2%
5 119
 
5.7%
9 103
 
4.9%
8 62
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 638
30.4%
3 243
 
11.6%
2 232
 
11.1%
1 231
 
11.0%
4 165
 
7.9%
7 136
 
6.5%
, 130
 
6.2%
5 119
 
5.7%
9 103
 
4.9%
8 62
 
3.0%

water10
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
<NA>
532 
0.0
234 
0.1
 
15
0.2
 
2
1.4
 
1

Length

Max length4
Median length4
Mean length3.6785714
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> 532
67.9%
0.0 234
29.8%
0.1 15
 
1.9%
0.2 2
 
0.3%
1.4 1
 
0.1%

Length

2024-04-21T02:17:49.823512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:17:50.014147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 532
67.9%
0.0 234
29.8%
0.1 15
 
1.9%
0.2 2
 
0.3%
1.4 1
 
0.1%

water11
Real number (ℝ)

MISSING  ZEROS 

Distinct61
Distinct (%)14.1%
Missing352
Missing (%)44.9%
Infinite0
Infinite (%)0.0%
Mean0.25550926
Minimum0
Maximum5.71
Zeros276
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:50.339546image/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
2024-04-21T02:17:50.762568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 276
35.2%
0.1 34
 
4.3%
0.2 25
 
3.2%
0.3 11
 
1.4%
0.4 10
 
1.3%
0.5 6
 
0.8%
0.6 5
 
0.6%
1.9 3
 
0.4%
1.0 3
 
0.4%
1.1 3
 
0.4%
Other values (51) 56
 
7.1%
(Missing) 352
44.9%
ValueCountFrequency (%)
0.0 276
35.2%
0.1 34
 
4.3%
0.11 1
 
0.1%
0.13 1
 
0.1%
0.14 1
 
0.1%
0.18 1
 
0.1%
0.2 25
 
3.2%
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 (%)8.0%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.5987229
Minimum0.1
Maximum10.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:51.187253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.7
median1.1
Q32
95-th percentile4.3
Maximum10.9
Range10.8
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.4269146
Coefficient of variation (CV)0.89253407
Kurtosis9.1575799
Mean1.5987229
Median Absolute Deviation (MAD)0.5
Skewness2.4274623
Sum1251.8
Variance2.0360853
MonotonicityNot monotonic
2024-04-21T02:17:51.625519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 66
 
8.4%
1.0 58
 
7.4%
0.6 47
 
6.0%
0.9 46
 
5.9%
0.4 46
 
5.9%
0.7 42
 
5.4%
1.2 36
 
4.6%
1.4 34
 
4.3%
1.1 31
 
4.0%
0.5 29
 
3.7%
Other values (53) 348
44.4%
ValueCountFrequency (%)
0.1 5
 
0.6%
0.2 24
 
3.1%
0.3 16
 
2.0%
0.4 46
5.9%
0.5 29
3.7%
0.6 47
6.0%
0.7 42
5.4%
0.8 66
8.4%
0.9 46
5.9%
1.0 58
7.4%
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 (%)9.5%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean7.9084291
Minimum0.1
Maximum12.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:52.037740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile5.9
Q17.1
median8
Q38.7
95-th percentile9.9
Maximum12.4
Range12.3
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.3521151
Coefficient of variation (CV)0.17097139
Kurtosis4.5079955
Mean7.9084291
Median Absolute Deviation (MAD)0.8
Skewness-0.75597728
Sum6192.3
Variance1.8282153
MonotonicityNot monotonic
2024-04-21T02:17:52.686125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.4 38
 
4.8%
7.6 33
 
4.2%
8.3 31
 
4.0%
8.1 30
 
3.8%
7.3 30
 
3.8%
6.9 26
 
3.3%
8.2 26
 
3.3%
8.0 25
 
3.2%
8.5 25
 
3.2%
6.8 24
 
3.1%
Other values (64) 495
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 (%)25.8%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean17.642912
Minimum5.9
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:53.099920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.9
5-th percentile9.5
Q113
median16.8
Q322.1
95-th percentile28.5
Maximum30
Range24.1
Interquartile range (IQR)9.1

Descriptive statistics

Standard deviation5.7943396
Coefficient of variation (CV)0.32842309
Kurtosis-0.74912463
Mean17.642912
Median Absolute Deviation (MAD)4.2
Skewness0.43164754
Sum13814.4
Variance33.574371
MonotonicityNot monotonic
2024-04-21T02:17:53.539025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.4 14
 
1.8%
16.8 13
 
1.7%
12.2 13
 
1.7%
16.5 12
 
1.5%
16.9 12
 
1.5%
16.7 12
 
1.5%
16.6 11
 
1.4%
17.3 10
 
1.3%
17.1 10
 
1.3%
15.6 10
 
1.3%
Other values (192) 666
84.9%
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 (%)4.9%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean48.439336
Minimum0
Maximum62
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:53.927374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36
Q148
median50
Q352
95-th percentile53
Maximum62
Range62
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.9601412
Coefficient of variation (CV)0.14368779
Kurtosis17.7993
Mean48.439336
Median Absolute Deviation (MAD)2
Skewness-3.7876315
Sum37928
Variance48.443566
MonotonicityNot monotonic
2024-04-21T02:17:54.336139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
52 168
21.4%
51 138
17.6%
50 121
15.4%
53 81
10.3%
49 68
8.7%
48 43
 
5.5%
47 27
 
3.4%
46 22
 
2.8%
45 13
 
1.7%
40 11
 
1.4%
Other values (28) 91
11.6%
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
10.3%
52 168
21.4%
51 138
17.6%
50 121
15.4%
49 68
8.7%
48 43
 
5.5%
47 27
 
3.4%
46 22
 
2.8%

water16
Real number (ℝ)

Distinct124
Distinct (%)15.8%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean31.59834
Minimum0.2
Maximum35.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-21T02:17:54.740154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile22.65
Q131.5
median33.1
Q334
95-th percentile34.7
Maximum35.3
Range35.1
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation4.784714
Coefficient of variation (CV)0.15142296
Kurtosis15.555283
Mean31.59834
Median Absolute Deviation (MAD)1.1
Skewness-3.5681316
Sum24741.5
Variance22.893488
MonotonicityNot monotonic
2024-04-21T02:17:55.180553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.1 29
 
3.7%
33.1 28
 
3.6%
34.6 27
 
3.4%
32.8 27
 
3.4%
32.9 25
 
3.2%
33.9 23
 
2.9%
33.3 23
 
2.9%
33.4 23
 
2.9%
34.2 23
 
2.9%
34.5 22
 
2.8%
Other values (114) 533
68.0%
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
 
0.6%
34.9 6
 
0.8%
34.8 9
 
1.1%
34.7 17
2.2%
34.6 27
3.4%
34.5 22
2.8%
34.4 21
2.7%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2021-03-01 06:13:03
784 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01 06:13:03
2nd row2021-03-01 06:13:03
3rd row2021-03-01 06:13:03
4th row2021-03-01 06:13:03
5th row2021-03-01 06:13:03

Common Values

ValueCountFrequency (%)
2021-03-01 06:13:03 784
100.0%

Length

2024-04-21T02:17:55.586255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:17:55.886181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 784
50.0%
06:13:03 784
50.0%

Sample

skeyinspec_yyinspec_qtsitewater01water02water03water04water05water06water07water08water09water10water11water12water13water14water15water16last_load_dttm
014390020172북내항39III25.16.28.3585.53.08.37<NA><NA>1.18.016.84932.22021-03-01 06:13:03
114390120172북외항23I41.59.25.7691.02.38.25<NA><NA>0.78.015.95234.22021-03-01 06:13:03
214390220172수영만39III1,654.587.66.3998.63.08.3790<NA><NA>2.29.015.65234.52021-03-01 06:13:03
314390320172이기대26II310.722.33.4593.72.68.245<NA><NA>0.98.014.95234.12021-03-01 06:13:03
414390420172해운대28II485.412.55.62100.63.58.2330<NA><NA>1.39.016.75233.92021-03-01 06:13:03
514390520172다대포항20I16.415.43.2393.43.28.133<NA><NA>2.59.217.15334.52021-03-01 06:13:03
614390620172동천하류50IV510.452.32.9182.02.28.21,300<NA><NA>1.16.916.35234.02021-03-01 06:13:03
714390720172발전소앞30II43.114.34.6382.02.67.52<NA><NA>1.79.118.95334.62021-03-01 06:13:03
814390820172부산대교30II64.711.54.9988.73.58.4330<NA><NA>0.97.616.55133.32021-03-01 06:13:03
914390920172자갈치시장23I46.85.43.48106.82.58.445<NA><NA>1.08.616.55133.52021-03-01 06:13:03
skeyinspec_yyinspec_qtsitewater01water02water03water04water05water06water07water08water09water10water11water12water13water14water15water16last_load_dttm
77414401120182송도해수욕장24II108.339.24.1498.03.08.513<NA><NA>7.79.417.65234.52021-03-01 06:13:03
77514401220182광안리해수욕장20I29.520.50.6390.53.58.478<NA><NA>0.88.916.55032.42021-03-01 06:13:03
77614401320182해운대해수욕장30II113.728.10.8290.03.58.3490<NA><NA>0.29.215.55133.52021-03-01 06:13:03
77714401420183고리30II13.60.00.1687.17.18.40<NA><NA>1.06.928.55335.12021-03-01 06:13:03
77814401520183남항30II70.60.03.9587.84.48.3460<NA><NA>1.46.428.14932.22021-03-01 06:13:03
77914401620183녹산28II447.32.51.693.72.58.245<NA><NA>3.97.229.03219.82021-03-01 06:13:03
78014401720183대변20I18.80.00.29101.57.98.40<NA><NA>1.06.628.15133.32021-03-01 06:13:03
78114401820183신항30II121.70.03.7286.24.18.10<NA><NA>1.46.426.34931.92021-03-01 06:13:03
78214401920183신호48IV574.022.61.3471.52.78.420<NA><NA>4.77.629.12515.52021-03-01 06:13:03
78314402020183일광20I14.20.00.3991.86.88.40<NA><NA>0.86.926.65234.22021-03-01 06:13:03