How to extract the months from a datetime table?

Hi!

I have a series of dates like this -

I want to create 12 variables naming - January, February, March, April,.., December in a way that each of the month contains the index value from the DateStamp for that month.

For example,

1984-05-02 is index 1, and it be assigned under 'May'.

Similarly, 1984-06-03 is index 2, and it be assigned under 'June'. And so on.

I have attached the DateStamp.mat file. Any feedback will be much appreciated! Thank you so much.

Answer 1

[Stephen23]

S = load('DateStamp.mat')

S = struct with fields:
    DateStamp: [764×3 table]

T = S.DateStamp;
T.month = T.date;
T.month.Format = 'MMMM'

T = 764×4 table
       date       x_CloudCover       landsat         month  
    __________    ____________    _____________    _________

    1984-05-02        0.12        {'landsat_5'}          May
    1984-06-03       18.49        {'landsat_5'}         June
    1984-06-19           0        {'landsat_5'}         June
    1984-09-23        1.49        {'landsat_5'}    September
    1984-10-09        47.1        {'landsat_5'}      October
    1984-10-25        7.27        {'landsat_5'}      October
    1984-11-10       46.36        {'landsat_5'}     November
    1984-11-26        0.08        {'landsat_5'}     November
    1985-01-29        0.11        {'landsat_5'}      January
    1985-04-19       71.61        {'landsat_5'}        April
    1985-06-22        1.53        {'landsat_5'}         June
    1985-08-09           0        {'landsat_5'}       August
    1985-10-12           0        {'landsat_5'}      October
    1985-10-28           0        {'landsat_5'}      October
    1986-01-16       16.37        {'landsat_5'}      January
    1986-02-01       43.73        {'landsat_5'}     February

But I am guessing that your actual goal is to perform some kind on analysis on your data, e.g. the means:

M = categorical(datetime(1,1,1,"Format","MMM")+calmonths(0:11));
T.year  = T.date.Year;
T.month = M(T.date.Month).';
S = groupsummary(T,["year","month"],"mean","x_CloudCover");
U = unstack(S,"mean_x_CloudCover","month", "GroupingVariables","year")

U = 39×13 table
    year     Jan       Feb       Mar      Apr      May      Jun       Jul       Aug      Sep       Oct       Nov       Dec 
    ____    ______    ______    _____    _____    _____    ______    ______    _____    ______    ______    ______    _____

    1984       NaN       NaN      NaN      NaN     0.12     9.245       NaN      NaN      1.49    27.185     23.22      NaN
    1985      0.11       NaN      NaN    71.61      NaN      1.53       NaN        0       NaN         0       NaN      NaN
    1986     16.37     43.73      NaN      NaN    58.07     32.67     35.15     20.3         0         0       NaN      NaN
    1987     57.67     1.175     0.02      NaN      NaN       3.2       NaN      4.2      0.05      38.1         0     11.9
    1988     12.78       NaN      NaN     1.35     0.32      1.93     32.89     2.15         0         0     27.99      NaN
    1989      0.15     52.31        0    16.26      NaN       NaN    39.325    27.73     27.95         0     73.26     45.6
    1990       NaN       NaN      NaN      NaN    39.08       NaN      31.6    62.61      2.52      0.57     14.19     2.61
    1991     42.97       NaN      NaN     0.24    42.42      0.05     18.33    23.24     11.95     11.17      0.01     0.43
    1992      0.11     19.39    37.41    44.77     0.06       3.2      18.9      NaN       NaN     79.05      0.06    0.145
    1993    23.675      4.22      NaN     0.18    2.335     23.44     20.35        0       NaN      7.39       NaN      NaN
    1994      0.36      0.08      NaN     0.56     4.15       NaN    20.115     7.79      7.91       NaN         0     0.28
    1995      3.08    25.135    76.31    48.78      NaN      9.47     3.105     0.06         0     16.29      0.15      NaN
    1996      9.98         0        0    57.57      NaN       NaN       0.1    57.03       NaN       NaN     20.15      NaN
    1997     30.96       NaN      NaN     0.27    46.88      0.13     51.24        0      4.22       NaN       NaN     0.05
    1998     0.135         0        0        0      NaN    18.545     47.78     5.71     39.99         0       NaN      NaN
    1999    20.705    29.365    1.495     73.6     0.32     72.77    9.3875        0    47.315    10.918    11.733     0.21

[Ashfaq Ahmed]

Hi @Stephen23, thank you. This is very close to what I am looking for. I wanted twelve variables with the indicies assigned. Like this,

January = [1, 5, 11, 17, 18,.....];

February = [2, 19, 26, 28, ...];

Can you please give me an idea on how can I make it?

[Steven Lord]

Can you dynamically create variables with sequential names like January, February, March, etc.? Yes.

Should you do this? The general consensus is no. That Answers post explains why this is generally discouraged and offers several alternative approaches.

I'd probably use the approach @Stephen23 used and refer to U.Jan, U.Feb, etc. instead of January, February, etc. in my code.

[Ashfaq Ahmed]

Hi @Stephen23, That is actually something totally new I learned from your code today. Thank you so much!

I have another data set of 376x268x764 double size. This is essentially the latitude/longitude grid of the temperature list of 764 days. I will have to exract the days based on their months. That's why I was looking for the indices only.

I am only using the date stamps from this DateStamp.mat file.

[Ashfaq Ahmed]

I am using this code to find out the indices -

T = S.DateStamp;
T.month = T.date;
T.month.Format = 'MMMM';
LIST = string(T.month(1:end));
find(LIST=="May")