Extracting time from datetime

Hi,

How would I extract time from a timestamp? Say for example, I have a table with some 10 rows and say 5 columns.

Column 1 is the datestamp, for ex : 12/01/2000 01:00:00 and Column 2 is say Windspeed 30

so row1 looks like 12/01/2000 01:00:00 30

Let row 2 look like

13/01/2000 01:15:00 45 where 45 is the windspeed.

If I use the hours function, I get back only 01. But when I plot the two data with hours on the x axis, at the same point i get 2 values, which is not what I want. I want to plot two lines (for 12th and 13th) with y axis having the windspeed, and x axis having the hours. So if were to plot for say 10 days, i'd have 10 different lines with the y axis being the windspeed and x axis being the hour. But because Im only getting the "hour", for any windspeed values between 01:00:00 - 02:00:00, it all comes under the hour value of "1". I want it to be continuous.

This is what im getting, if you see the x axis has 0 to 24 values, but if the time is say 00:30, it plots at 0 itself and thats why the ugly graph

I'd want a graph like this

where its in hours and not minutes.

Example of the dataset im working with

[Star Strider]

@Manas Pratap — Please see my Comment.

.

Answer 1

[Star Strider]

Try this —

C = {'12/01/2000 01:00:00'   30; '13/01/2000 01:15:00'  45}

C = 2×2 cell array
    {'12/01/2000 01:00:00'}    {[30]}
    {'13/01/2000 01:15:00'}    {[45]}

ct = datetime(C(:,1), 'InputFormat','dd/MM/yyyy HH:mm:ss')

ct = 2×1 datetime array
   12-Jan-2000 01:00:00
   13-Jan-2000 01:15:00

Time = timeofday(ct)

Time = 2×1 duration array
   01:00:00
   01:15:00

.

[Manas Pratap]

I tried converting my column containing the timestamp to a cell array to use your function above.

However, i get these square brackets, and the function doesnt work

[Star Strider]

It doesn’t work because they have to be read in as (or converted to) character arrays. They currently are not.

I’m not certain how they’re being read (imported) or the MATLAB version reading them. I would use readtablle or readmatrix to import them. That should automatically import them as datetime arrays, so the timeofday call would be the only call necessary to extract the times. If readtable or readmatrix get confused and have problems converting them, and so read them as character vector arrays, do something similar to what I did in the ‘ct’ assignment to convert them first.

Attaching/uploading the file (or a representative sample from it) to here, and listing the MATLAB version being used, would help.

.

[Manas Pratap]

I've attached a sample file below.

I imported the data using the import data option, I imported them as individual column vectors and plotted them. I've written the code below

x = humidity_site1;
y = timestamp;
hday1 = x(674:721);
hday2 = x(722:769);
hday3 = x(770:817);
hday4 = x(818:865);
hday5 = x(866:913);
tday1 = hour(y(675:722));
tday2 = hour(y(722:769));
tday3 = hour(y(770:817));
tday4 = hour(y(818:865));
tday5 = hour(y(866:913));
plot(tday1,hday1,tday2,hday2,tday3,hday3,tday4,hday4,tday5,hday5)
legend('Mar 15','Mar 16','Mar 17','Mar 18','Mar 19');
figure
plot(tday1,hday1)

x and y are the individual column vectors that I imported.

Matlab version : R2021a

Thank you for your replies and patience, its much appreciated!!

[Star Strider]

Try this —

T1 = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/791964/sample.csv', 'VariableNamingRule','preserve')

T1 = 40×6 table
    Var1         timestamp          temperature_site1    humidity_site1    temperature_site2    humidity_site2
    ____    ____________________    _________________    ______________    _________________    ______________

      0     {'01-03-2018 00:00'}           NaN                 NaN               23.1                61.6     
      1     {'01-03-2018 00:30'}            21                  68               22.9                61.1     
      2     {'01-03-2018 01:00'}            20                  73                 23                61.6     
      3     {'01-03-2018 01:30'}            20                  73               22.9                62.5     
      4     {'01-03-2018 02:00'}            20                  73               22.4                63.4     
      5     {'01-03-2018 02:30'}            20                  70                 22                63.8     
      6     {'01-03-2018 03:00'}            19                  78               21.7                64.3     
      7     {'01-03-2018 03:30'}            19                  78               21.5                64.7     
      8     {'01-03-2018 04:00'}            19                  78               21.5                65.2     
      9     {'01-03-2018 04:30'}            19                  78               21.1                66.5     
     10     {'01-03-2018 05:00'}            18                  83               20.9                67.4     
     11     {'01-03-2018 05:30'}            17                  81               20.7                68.2     
     12     {'01-03-2018 06:00'}            17                84.5               20.6                67.8     
     13     {'01-03-2018 06:30'}            17                  88               20.3                69.1     
     14     {'01-03-2018 07:00'}            17                  88               20.9                70.5     
     15     {'01-03-2018 07:30'}            17                  88               20.3                69.5     

T1.timestamp(end)

ans = 1×1 cell array
    {'01-03-2018 19:00'}

T1.timestamp = datetime(T1.timestamp, 'InputFormat','dd-MM-yyyy HH:mm', 'Format','dd-MM-yyyy HH:mm') 

T1 = 40×6 table
    Var1       timestamp        temperature_site1    humidity_site1    temperature_site2    humidity_site2
    ____    ________________    _________________    ______________    _________________    ______________

      0     01-03-2018 00:00           NaN                 NaN               23.1                61.6     
      1     01-03-2018 00:30            21                  68               22.9                61.1     
      2     01-03-2018 01:00            20                  73                 23                61.6     
      3     01-03-2018 01:30            20                  73               22.9                62.5     
      4     01-03-2018 02:00            20                  73               22.4                63.4     
      5     01-03-2018 02:30            20                  70                 22                63.8     
      6     01-03-2018 03:00            19                  78               21.7                64.3     
      7     01-03-2018 03:30            19                  78               21.5                64.7     
      8     01-03-2018 04:00            19                  78               21.5                65.2     
      9     01-03-2018 04:30            19                  78               21.1                66.5     
     10     01-03-2018 05:00            18                  83               20.9                67.4     
     11     01-03-2018 05:30            17                  81               20.7                68.2     
     12     01-03-2018 06:00            17                84.5               20.6                67.8     
     13     01-03-2018 06:30            17                  88               20.3                69.1     
     14     01-03-2018 07:00            17                  88               20.9                70.5     
     15     01-03-2018 07:30            17                  88               20.3                69.5     

T1.TimeOfDay = timeofday(T1.timestamp)

T1 = 40×7 table
    Var1       timestamp        temperature_site1    humidity_site1    temperature_site2    humidity_site2    TimeOfDay
    ____    ________________    _________________    ______________    _________________    ______________    _________

      0     01-03-2018 00:00           NaN                 NaN               23.1                61.6         00:00:00 
      1     01-03-2018 00:30            21                  68               22.9                61.1         00:30:00 
      2     01-03-2018 01:00            20                  73                 23                61.6         01:00:00 
      3     01-03-2018 01:30            20                  73               22.9                62.5         01:30:00 
      4     01-03-2018 02:00            20                  73               22.4                63.4         02:00:00 
      5     01-03-2018 02:30            20                  70                 22                63.8         02:30:00 
      6     01-03-2018 03:00            19                  78               21.7                64.3         03:00:00 
      7     01-03-2018 03:30            19                  78               21.5                64.7         03:30:00 
      8     01-03-2018 04:00            19                  78               21.5                65.2         04:00:00 
      9     01-03-2018 04:30            19                  78               21.1                66.5         04:30:00 
     10     01-03-2018 05:00            18                  83               20.9                67.4         05:00:00 
     11     01-03-2018 05:30            17                  81               20.7                68.2         05:30:00 
     12     01-03-2018 06:00            17                84.5               20.6                67.8         06:00:00 
     13     01-03-2018 06:30            17                  88               20.3                69.1         06:30:00 
     14     01-03-2018 07:00            17                  88               20.9                70.5         07:00:00 
     15     01-03-2018 07:30            17                  88               20.3                69.5         07:30:00 

vn = T1.Properties.VariableNames;
lgdvars = vn(3:6);
lgdvars = cellfun(@(x)strrep(x,'_','\_'), lgdvars, 'Unif',0);           % 'escape' The Underscores

figure
plot(T1.TimeOfDay, T1{:,3}, 'DisplayName',lgdvars{1})
hold on
plot(T1.TimeOfDay, T1{:,4}, 'DisplayName',lgdvars{2})
plot(T1.TimeOfDay, T1{:,5}, 'DisplayName',lgdvars{3})
plot(T1.TimeOfDay, T1{:,6}, 'DisplayName',lgdvars{4})
hold off
grid
legend('Location','best')

figure
yyaxis left
plot(T1.TimeOfDay, T1{:,3}, 'DisplayName',lgdvars{1})
hold on
plot(T1.TimeOfDay, T1{:,5}, 'DisplayName',lgdvars{3})
hold off
ylabel('Temperature (°C)')
yyaxis right
plot(T1.TimeOfDay, T1{:,4}, 'DisplayName',lgdvars{2})
hold on
plot(T1.TimeOfDay, T1{:,6}, 'DisplayName',lgdvars{4})
hold off
ylabel('Humidity (%)')
grid
legend('NumColumns',2, 'Location','northoutside')

There is only one file and it appears to cover only one day. Two plotting options are provided.

.

[Manas Pratap]

Hi!, thank you so much for the reply ^_^

I just have a couple of questions -

lgdvars = vn(3:6);
lgdvars = cellfun(@(x)strrep(x,'_','\_'), lgdvars, 'Unif',0);

plot(T1.TimeOfDay, T1{:,3}, 'DisplayName',lgdvars{1})

What do these above lines do? Im a little hazy on that and I want to understand it completely.

Thank you!!

[Manas Pratap]

Actually, I need to plot the data according to the time for various days, so the code snippet that you've sent doesnt actually achieve that... It should look something like this

[Star Strider]

With respect to this Comment —

Those assignments retrieve the column headings (variable names) from the table and then use them to create the legend entries as 'DisplayName' values (after ‘escaping’ the underscores so that they display as underscores).

With respect to this Comment —

I only have one file. See if the Signal Processing Toolbox strips plot function will do what you want when more files are added. (There are likely other ways to work with that as well.) See the documentations ection on Import or Export a Sequence of Files if that is a problem.

I imagine that the dewpoint remains relatively constant, so the humidity rises appropriately as the temperature decreases. It might be worthwhile to calculate the dewpoint from the available information, and plot that as well. Just a thought.

.

[Star Strider]

If my Answer helped you solve your problem, please Accept it!

.

[Stephen23]

Manas Pratap's incorectly posted "Answer" moved here:

The answer is actually one of the comments below. Thank you so much @Star Strider for your effort and advice, helped me a lot!

https://in.mathworks.com/matlabcentral/answers/1580244-extracting-time-from-datetime#comment_1819019

[Manas Pratap]

@Star Strider I have attached the complete dataset. If I had to plot the temperature site_1 data for 5 different days, say (March 14-18) without inputting the data manually like i did before, is there a way to select the data daywise and then plot them? The x axis should be hours and the y axis temperature...with 5 different lines for the different days

[Manas Pratap]

I tried the below. However only 1 value is returned...i need all the rows pertaining to the date so that I can plot it hourwise..

T1 = readtable('weather_data_2sites.csv')
T1.timestamp = datetime(T1.timestamp, 'InputFormat','dd-MM-yyyy HH:mm', 'Format','dd-MM-yyyy HH:mm') 
T1.date = datetime(T1.timestamp, 'InputFormat','dd-MM-yyyy HH:mm', 'Format','dd-MM-yyyy') 
T1.TimeOfDay = timeofday(T1.timestamp)
T1.Properties.VariableNames
T_Mar15 = T1(T1.date == '24-06-2018',:)

[Star Strider]

This turned out to be a much more difficult problem that I at first thought it would be. The reason is that the data do not have consistent sizes, so plotting them against ‘TimeOfDay’ was not possible. I ended up plotting them as best I could, and then grafting the ‘TimeOfDay’ vector onto the plots using a set call, because that’s the only way I could make it work. I’m not certain how robust the code is, however it appears to work reasonably well for these data.

With that, this is my best effort —

T1 = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/799489/weather_data_2sites1.csv', 'VariableNamingRule','preserve')

T1 = 5780×7 table
    Var1         timestamp          temperature_site1    humidity_site1    temperature_site2    humidity_site2            Var7        
    ____    ____________________    _________________    ______________    _________________    ______________    ____________________

      0     {'01-03-2018 00:00'}           NaN                 NaN               23.1                61.6         {'01-01-1970 11:59'}
      1     {'01-03-2018 00:30'}            21                  68               22.9                61.1         {0×0 char          }
      2     {'01-03-2018 01:00'}            20                  73                 23                61.6         {0×0 char          }
      3     {'01-03-2018 01:30'}            20                  73               22.9                62.5         {0×0 char          }
      4     {'01-03-2018 02:00'}            20                  73               22.4                63.4         {0×0 char          }
      5     {'01-03-2018 02:30'}            20                  70                 22                63.8         {0×0 char          }
      6     {'01-03-2018 03:00'}            19                  78               21.7                64.3         {0×0 char          }
      7     {'01-03-2018 03:30'}            19                  78               21.5                64.7         {0×0 char          }
      8     {'01-03-2018 04:00'}            19                  78               21.5                65.2         {0×0 char          }
      9     {'01-03-2018 04:30'}            19                  78               21.1                66.5         {0×0 char          }
     10     {'01-03-2018 05:00'}            18                  83               20.9                67.4         {0×0 char          }
     11     {'01-03-2018 05:30'}            17                  81               20.7                68.2         {0×0 char          }
     12     {'01-03-2018 06:00'}            17                84.5               20.6                67.8         {0×0 char          }
     13     {'01-03-2018 06:30'}            17                  88               20.3                69.1         {0×0 char          }
     14     {'01-03-2018 07:00'}            17                  88               20.9                70.5         {0×0 char          }
     15     {'01-03-2018 07:30'}            17                  88               20.3                69.5         {0×0 char          }

T1.timestamp = datetime(T1.timestamp, 'InputFormat','dd-MM-yyyy HH:mm', 'Format','dd-MM-yyyy HH:mm') 

T1 = 5780×7 table
    Var1       timestamp        temperature_site1    humidity_site1    temperature_site2    humidity_site2            Var7        
    ____    ________________    _________________    ______________    _________________    ______________    ____________________

      0     01-03-2018 00:00           NaN                 NaN               23.1                61.6         {'01-01-1970 11:59'}
      1     01-03-2018 00:30            21                  68               22.9                61.1         {0×0 char          }
      2     01-03-2018 01:00            20                  73                 23                61.6         {0×0 char          }
      3     01-03-2018 01:30            20                  73               22.9                62.5         {0×0 char          }
      4     01-03-2018 02:00            20                  73               22.4                63.4         {0×0 char          }
      5     01-03-2018 02:30            20                  70                 22                63.8         {0×0 char          }
      6     01-03-2018 03:00            19                  78               21.7                64.3         {0×0 char          }
      7     01-03-2018 03:30            19                  78               21.5                64.7         {0×0 char          }
      8     01-03-2018 04:00            19                  78               21.5                65.2         {0×0 char          }
      9     01-03-2018 04:30            19                  78               21.1                66.5         {0×0 char          }
     10     01-03-2018 05:00            18                  83               20.9                67.4         {0×0 char          }
     11     01-03-2018 05:30            17                  81               20.7                68.2         {0×0 char          }
     12     01-03-2018 06:00            17                84.5               20.6                67.8         {0×0 char          }
     13     01-03-2018 06:30            17                  88               20.3                69.1         {0×0 char          }
     14     01-03-2018 07:00            17                  88               20.9                70.5         {0×0 char          }
     15     01-03-2018 07:30            17                  88               20.3                69.5         {0×0 char          }

T1.TimeOfDay = timeofday(T1.timestamp);
T2 = T1(:,[8 3 4 5 6])                                      % Extract Variables Of Interest To New Table

T2 = 5780×5 table
    TimeOfDay    temperature_site1    humidity_site1    temperature_site2    humidity_site2
    _________    _________________    ______________    _________________    ______________

    00:00:00            NaN                 NaN               23.1                61.6     
    00:30:00             21                  68               22.9                61.1     
    01:00:00             20                  73                 23                61.6     
    01:30:00             20                  73               22.9                62.5     
    02:00:00             20                  73               22.4                63.4     
    02:30:00             20                  70                 22                63.8     
    03:00:00             19                  78               21.7                64.3     
    03:30:00             19                  78               21.5                64.7     
    04:00:00             19                  78               21.5                65.2     
    04:30:00             19                  78               21.1                66.5     
    05:00:00             18                  83               20.9                67.4     
    05:30:00             17                  81               20.7                68.2     
    06:00:00             17                84.5               20.6                67.8     
    06:30:00             17                  88               20.3                69.1     
    07:00:00             17                  88               20.9                70.5     
    07:30:00             17                  88               20.3                69.5     

T2 = fillmissing(T2,'nearest');
T2VN = T2.Properties.VariableNames(2:end)

T2VN = 1×4 cell array
    {'temperature_site1'}    {'humidity_site1'}    {'temperature_site2'}    {'humidity_site2'}

[TOD,ixs,ixv] = unique(T2.TimeOfDay);
for k = 1:numel(T2VN)
    aggvar{:,k} = accumarray(ixv,T2{:,k+1},[],@(x){x});
end


for k1 = 1:numel(aggvar)
    figure
    hold on
    for k2 = 1:numel(aggvar)
        plot(aggvar{k1}{k2})
    end
    hold off
    grid
    xt = linspace(0, numel(aggvar{1}{1}), numel(aggvar{1}));
    set(gca,'XTick',xt, 'XTickLabel',string(TOD))
    title(strrep(T2VN{k1},'_','\_'))
    legend(compose('Day %d',1:4), 'Location','best')
end

The plots here are constrained and resize themselves to fit the window. They will probably look better when the code is run offline (that I did not do).

Experiment to get the different results, if desired.

.

Answer 2

[Alessandro Livi]

Simple answer for getting time e.g. now but any array works

timeofday(datetime('now')));