MATLAB: Timetable Monthly Average over Many Years

MATLABmeanmonthlyretimetimetable

I have a daily precipitation data file with two columns.The first column is "date", with date format yyyy-mm-dd and the second column is "precip" with double format. My data ranges from 1980-01-01 to 2010-12-31, and I would like to determine the average precipitation values for each month over that interval.

Example of desired result:

Month avgPrecip

Jan 0.0056

Feb 0.0034

…

for each month.

I have attached my csv file with the data and my current progess. I can get the monthly average of the data within each year using a timetable and retime, but I am stuck trying to average the monthly average data for the entire data range. Thank you!

    precip = readtable('CR_precip.csv');
    precip = table2timetable(precip);
    monthlyAvg = retime(precip,'monthly','mean');

Best Answer

The easiest:

precip = table2timetable(readtable('CR_precip.csv'));
monthlyavg = groupsummary(precip, 'day', 'monthofyear', 'mean')

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MATLAB: How to calculate Daily mean and monthly mean from hourly data

I would recommend the following steps:

Import the data file
Arrange the data and create timetable variable
Apply retime funciton to obtain daily/monthly average

The following is an example:

% Read the data file
opts = detectImportOptions('test_pog.txt');
T = readtable('test_pog.txt',opts);
% Make a datetime vector
Time = datetime(T{:,1},'InputFormat','yyyy.MM.dd.');
Time.Hour = T{:,2};
% Add the datetime vector and remove the 1st&2nd columns
T.Time = Time;
T(:,1:2) = [];
% Convert to timetable
TT = table2timetable(T);
% Apply retime function to obtain daily/monthly mean
TTdailyMean = retime(TT,'daily','mean');
TTmonthlyMean = retime(TT,'monthly','mean');

MATLAB: Using panel data, how can I create a new table with weekly price data based on a table with daily price data, for every stock

John, I'll assume you have the Financial Toolbox. I think what you're looking to do is to calculate mean price, by ticker and week, with the exemplar date for each week being the last business day. There are several ways you could do that. Since you already have a table, varfun is one easy way.

First cook up some fake data.

>> Date = datetime(2016,3,[22;23;24;28;29;21;22;23;24;28;29],'Format','eee dd-MMM-yyyy');
>> Ticker = categorical({'A'; 'A'; 'A'; 'A'; 'A'; 'B'; 'B'; 'B'; 'B'; 'B'; 'B'});
>> Price = rand(size(Ticker));
>> TS = table(Date,Ticker,Price)
TS =
         Date          Ticker     Price  
    _______________    ______    ________
    Tue 22-Mar-2016    A          0.13197
    Wed 23-Mar-2016    A          0.94205
    Thu 24-Mar-2016    A          0.95613
    Mon 28-Mar-2016    A          0.57521
    Tue 29-Mar-2016    A          0.05978
    Mon 21-Mar-2016    B          0.23478
    Tue 22-Mar-2016    B          0.35316
    Wed 23-Mar-2016    B          0.82119
    Thu 24-Mar-2016    B         0.015403
    Mon 28-Mar-2016    B         0.043024
    Tue 29-Mar-2016    B          0.16899

Now find the last business day in each week, by first finding the end of the week and then stepping back.

>> hol = holidays(datetime(2016,1,1),datetime(2016,12,31))
>> EOWDate = dateshift(TS.Date,'end','week');
>> TS.BusDate = busdate(EOWDate,'previous',hol);
>> TS.BusDate.Format = ['eee ' TS.BusDate.Format]
TS =
         Date          Ticker     Price           BusDate      
    _______________    ______    _______    ___________________
    Tue 22-Mar-2016    A         0.64912    Thu Thu 24-Mar-2016
    Wed 23-Mar-2016    A         0.73172    Thu Thu 24-Mar-2016
    Thu 24-Mar-2016    A         0.64775    Thu Thu 24-Mar-2016
    Mon 28-Mar-2016    A         0.45092    Fri Fri 01-Apr-2016
    Tue 29-Mar-2016    A         0.54701    Fri Fri 01-Apr-2016
    Mon 21-Mar-2016    B         0.29632    Thu Thu 24-Mar-2016
    Tue 22-Mar-2016    B         0.74469    Thu Thu 24-Mar-2016
    Wed 23-Mar-2016    B         0.18896    Thu Thu 24-Mar-2016
    Thu 24-Mar-2016    B         0.68678    Thu Thu 24-Mar-2016
    Mon 28-Mar-2016    B         0.18351    Fri Fri 01-Apr-2016
    Tue 29-Mar-2016    B         0.36848    Fri Fri 01-Apr-2016

Finally, apply mean to the prices, grouping by ticker and week.

>> varfun(@mean,TS,'GroupingVariables',{'Ticker' 'BusDate'},'InputVariables','Price')
ans =
    Ticker      BusDate      GroupCount    mean_Price
    ______    ___________    __________    __________
    A         24-Mar-2016    3             0.67672   
    A         01-Apr-2016    2             0.31749   
    B         24-Mar-2016    4             0.35613   
    B         01-Apr-2016    2             0.10601

Best Answer

Related Solutions

MATLAB: How to calculate Daily mean and monthly mean from hourly data

MATLAB: Using panel data, how can I create a new table with weekly price data based on a table with daily price data, for every stock

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