This question already has answers here:
Calculating cumulative sum for each row
(6 answers)
Closed 7 years ago.
Probably my question is really dull but I couldn't find an easy solution for that. So we have a data.frame without (overall) column. Overall column must present a cumulative number of pies (in my case) eaten up to a certain time period. What is the easiest way to create it in R for an infinite number of rows? Thanks!
Year Pies eaten Pies eaten(overall)
1 1960 3 3
2 1961 2 5
3 1962 5 10
4 1963 1 11
5 1964 7 18
6 1965 4 22
We can use cumsum
df1$Pies_eaten_Overall <- cumsum(df1$Pies_eaten)
Related
This question already has answers here:
How to count the number of unique values by group? [duplicate]
(1 answer)
count number of rows in a data frame in R based on group [duplicate]
(8 answers)
Closed 2 years ago.
I have a dataframe that contains a column representing the 'Year' and another column that represents 'Type':
a Year Creams
1 2004 11
2 2004 12
3 2001 13
4 2004 14
5 2002 15
. .... ..
How do I count every year in column 'Year' so it appears as:
a Year TypeCount
1 2004 3
2 2002 1
3 2001 1
It can be output into another dataframe, I don't mind. I just need it to be suitable to make a graph out of it at the end.
This question already has answers here:
Count number of rows per group and add result to original data frame
(11 answers)
Calculate group mean, sum, or other summary stats. and assign column to original data
(4 answers)
Closed 4 years ago.
although I have found a lot of ways to calculate the sum of a variable by group, all the approaches end up creating a new data set which aggregates the double cases.
To be more precise, if I have a data frame:
id year
1 2010
1 2015
1 2017
2 2011
2 2017
3 2015
and I want to count the number of times I have the same ID by the different years, there are a lot of ways (using aggregate, tapply, dplyr, sqldf etc) which use a "group by" kind of functionality that in the end will give something like:
id count
1 3
2 2
3 1
I haven't managed to find a way to calculate the same thing but keep my original data frame, in order to obtain:
id year count
1 2010 3
1 2015 3
1 2017 3
2 2011 2
2 2017 2
3 2015 1
and therefore do not aggregate my double cases.
Has somebody already figured out?
Thank you in advance
This question already has answers here:
Split dataframe by levels of a factor and name dataframes by those levels
(3 answers)
Closed 5 years ago.
this is my first post.
I have this dataframe of the Nhl draft.
What I would like to do is to use some sort of recursive function to create 10 objects.
So, I want to create these 10 objects by subsetting the Nhl dataframe by Year.
Here are the first 6 rows of the data set (nhl_draft)
Year Overall Team
1 2000 1 New York Islanders
2 2000 2 Atlanta Thrashers
3 2000 3 Minnesota Wild
4 2000 4 Columbus Blue Jackets
5 2000 5 New York Islanders
6 2000 6 Nashville Predators
Player PS
1 Rick DiPietro 49.3
2 Dany Heatley 95.2
3 Marian Gaborik 103.6
4 Rostislav Klesla 34.5
5 Raffi Torres 28.4
6 Scott Hartnell 74.5
I want to create 10 objects by subsetting out the Years, 2000 ~ 2009.
I tried,
for (i in 2000:2009) {
nhl_draft.i <- subset(nhl_draft, Year == "i")
}
BUT this doesn't do anything. What's the problem with this for-loop? Can you suggest any other ways?
Please tell me if this is confusing after all, this is my first post......
The following code may fix your error.
# Create an empty list
nhl_list <- list()
for (i in 2000:2009) {
# Subset the data frame based on Year
nhl_draft_temp <- subset(nhl_draft, Year == i)
# Assign the subset to the list
nhl_list[[as.character(i)]] <- nhl_draft_temp
}
But you can consider split, which is more concise.
nhl_list <- split(nhl_draft, f = nhl_draft$Year)
This question already has answers here:
Numbering rows within groups in a data frame
(10 answers)
Add column with order counts
(2 answers)
Closed 6 years ago.
I have following data set
id year
2 20332 2005
3 6383 2005
14 20332 2006
15 6806 2006
16 23100 2006
I would like to have an additional column, which counts the number of years the id variable is already available:
id year Counter
2 20332 2005 1
3 6383 2005 1
14 20332 2006 2
15 6806 2006 1
16 23100 2006 1
The dataset is currently not sorted according to the year. I thought about mutate rather than a function.
Any ideas? Thanks!
We can use ave from base R
df1$Counter <- with(df1, ave(id, id, FUN = seq_along))
This seems like a very simple problem, but I can't seem to sort it out. I have sought help from this forum, with the below topics being close, but don't seem to do exactly what I need. I have count data over several years. I want to obtain frequencies of the count value by year. It seems I need a table function with a grouping option, but I haven't found the proper syntax.
Data:
count year
1 15 1957
2 6 1957
3 23 1957
4 23 1957
5 2 1957
6 28 1980
7 15 1980
8 32 1980
9 18 1981
thank you in advance!
Counting the number of elements with the values of x in a vector
grouping data splitted by frequencies
Aggregate data in R
You're looking for the table function. Something like:
with(yourdata, table(Year, Count))