Summing rows by month in R

group by month in r
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summarize in r
aggregate in r
monthly average in r
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group by month from date in r
r sum multiple columns by group

So I have a data frame that has a date column, an hour column and a series of other numerical columns. Each row in the data frame is 1 hour of 1 day for an entire year.

The data frame looks like this:

          Date  Hour  Melbourne  Southern  Flagstaff
1   2009-05-01     0          0         5         17
2   2009-05-01     2          0         2          1
3   2009-05-01     1          0        11          0
4   2009-05-01     3          0         3          8
5   2009-05-01     4          0         1          0
6   2009-05-01     5          0        49         79
7   2009-05-01     6          0       425        610

The hours are out of order because this is subsetted from another data frame.

I would like to sum the values in the numerical columns by month and possibly by day. Does anyone know how I can do this?


Group data by month in R, I often analyze time series data in R — things like daily expenses or webserver statistics. And just as often I want to aggregate the data by month to see longer-​term patterns. to the month boundary, so that dates in the same month are rounded down to Then you can summarize them by month like this:. Give Column Sums of a Matrix or Data Frame, Based on a Grouping Variable. Compute column sums across rows of a numeric matrix-like object for each level of a grouping variable. rowsum is generic, with a method for data frames and a default method for vectors and matrices.


This could be another way to do this using data.table

library(data.table)
# Edited as per Arun's comment
out = setDT(data)[, lapply(.SD, sum), by=Date] 

#>out
#         Date Hour Melbourne Southern Flagstaff
#1: 2009-05-01   21         0      496       715

or by using dplyr

library(dplyr)
out = data %>% group_by(Date) %>% summarise_each(funs(sum))

#>out
#Source: local data frame [1 x 5]
#        Date Hour Melbourne Southern Flagstaff
#1 2009-05-01   21         0      496       715

Summarize Time Series Data by Month or Year Using Tidyverse , 4 2006-09-13 72.43 5 2006-09-20 72.62 > is there a way to group the data by month (summing the values in each month), i.e.. Date Income Group data by month in R. Published on February 22, 2017. I often analyze time series data in R — things like daily expenses or webserver statistics. And just as often I want to aggregate the data by month to see longer-term patterns.


Another base R solution

# to sum by date
rowsum(dat[-1], dat$Date)
#           Hour Melbourne Southern Flagstaff
#2009-05-01   21         0      496       715

# or by month and year
rowsum(dat[-1], format(dat$Date, "%b-%y") )
#       Hour Melbourne Southern Flagstaff
#May-09   21         0      496       715

R help - How to sum and group data by DATE in data frame, This will aggregate with the sum everything on year, giving us aggregate(. ~year, data=df1, sum, na.rm=TRUE) year month x1 x2 1 2000 6 -493.4367 -994.7560  Learn how to summarize time series data by day, month or year with Tidyverse pipes in R. Data by Month or Year Using Tidyverse Pipes in R. a new month column


I'd use dplyr::summarize and group_by, with a sum for each of your numeric columns:

summarize(group_by(df, Date), m_count = sum(Melbourne), s_count = sum(Southern), f_count = sum(Flagstaff)

aggregate all data by Date and ID, For each employee over the 6 months (sum by column); For each month across all employees (sum by row). Step 2: Create the DataFrame. Next, you'll need to  To sum by month has nothing different than How to SUM values between two dates using SUMIFS formula.However, this article shows you a more dynamic and specialized approach combining EOMONTH and SUMIFS functions that you don’t need to guess how many days in a month to sum month.


How to Sum each Column and Row in Pandas DataFrame, Generic function for obtaining 12 monthly values of a zoo object, by applying the 12 months of the year (e.g., FUN can be some of mean , sum , max , min , sd ). Summary of a variable is important to have an idea about the data. Although, summarizing a variable by group gives better information on the distribution of the data.


Monthly Function, 3.1 Data preparation; 3.2 Group by Month; 3.3 Group by week day Now with summarize we define which function we use to group the values  I have a very large dataframe with rows as observations and columns as genetic markers. I would like to create a new column that contains the sum of a select number of columns for each observation using R. If I have 200 columns and 100 rows, I would like a to create a new column that has 100 rows with the sum of say columns 43 through 167.


Group by function, summarise(total_sales=sum(Offered_Calls,na.rm = T)). After the group_by, I created the Year and Month columns and after that used the  How to sum a variable by group. Ask Question Asked 10 years, 5 months ago. Sum column with a condition in R. 1. R: Combine rows in same data.frame. 2.