4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
4
1
7
42602
1
34.128
-109.31
"WGS84
⋮
Clean NO2 Table and Convert to Timetable
Next, prepare NO2data for analysis by cleaning the data. Data cleaning is the process of detecting
and correcting (or removing) parts of the data set that are either corrupt, inaccurate, or irrelevant.
You can also convert table variables so that they have data types that can be more convenient for
analysis, such as categorical or datetime arrays.
For example, the table variable SampleMeasurement has measurements of NO2 concentration.
Concentrations below the method detection limit (MDL) are unreliable. To exclude them from
analysis, find the rows where SampleMeasurement is below the MDL. Set those elements to NaN.
NO2data.SampleMeasurement(NO2data.SampleMeasurement < NO2data.MDL) = NaN;
Create a table that contains only the subset of variables that are relevant to this example. You can use
table subscripting to create a table that has all rows (specified by a colon) and only those variables
that you name.
NO2data = NO2data(:,["DateLocal","TimeLocal","SampleMeasurement","StateName","CountyName","SiteNu
NO2data=11294497×8 table
DateLocal
TimeLocal
SampleMeasurement
StateName
CountyName
SiteNum
Latitud
__________
_________
_________________
_________
__________
_______
_______
1985-01-02
01:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
02:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
03:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
04:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
05:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
06:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
08:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
09:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
10:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
16:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
17:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
18:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
19:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
20:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
21:00
NaN
"Arizona"
"Apache"
7
34.128
1985-01-02
22:00
NaN
"Arizona"
"Apache"
7
34.128
⋮
9 Tables
9-88