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I have the following data frame and I want to break it up into 10 different data frames. I want to break the initial 100 row data frame into 10 data frames of 10 rows. I could do the following and get the desired results.
df = data.frame(one=c(rnorm(100)), two=c(rnorm(100)), three=c(rnorm(100))) df1 = df[1:10,] df2 = df[11:20,] df3 = df[21:30,] df4 = df[31:40,] df5 = df[41:50,] ... Of course, this isn't an elegant way to perform this task when the initial data frames are larger or if there aren't an easy number of segments that it can be broken down into.
So given the above, let's say we have the following data frame.
df = data.frame(one=c(rnorm(1123)), two=c(rnorm(1123)), three=c(rnorm(1123))) Now I want to split it into new data frames comprised of 200 rows, and the final data frame with the remaining rows. What would be a more elegant (aka 'quick') way to perform this task.
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Use the split() function in R to split a vector or data frame. Use the unsplit() method to retrieve the split vector or data frame.
In the above example, the data frame 'df' is split into 2 parts 'df1' and 'df2' on the basis of values of column 'Weight'. Method 2: Using Dataframe. groupby(). This method is used to split the data into groups based on some criteria.
array_split(df, 3) splits the dataframe into 3 sub-dataframes, while the split_dataframe function defined in @elixir's answer, when called as split_dataframe(df, chunk_size=3) , splits the dataframe every chunk_size rows.
> str(split(df, (as.numeric(rownames(df))-1) %/% 200)) List of 6 $ 0:'data.frame': 200 obs. of 3 variables: ..$ one : num [1:200] -1.592 1.664 -1.231 0.269 0.912 ... ..$ two : num [1:200] 0.639 -0.525 0.642 1.347 1.142 ... ..$ three: num [1:200] -0.45 -0.877 0.588 1.188 -1.977 ... $ 1:'data.frame': 200 obs. of 3 variables: ..$ one : num [1:200] -0.0017 1.9534 0.0155 -0.7732 -1.1752 ... ..$ two : num [1:200] -0.422 0.869 0.45 -0.111 0.073 ... ..$ three: num [1:200] -0.2809 1.31908 0.26695 0.00594 -0.25583 ... $ 2:'data.frame': 200 obs. of 3 variables: ..$ one : num [1:200] -1.578 0.433 0.277 1.297 0.838 ... ..$ two : num [1:200] 0.913 0.378 0.35 -0.241 0.783 ... ..$ three: num [1:200] -0.8402 -0.2708 -0.0124 -0.4537 0.4651 ... $ 3:'data.frame': 200 obs. of 3 variables: ..$ one : num [1:200] 1.432 1.657 -0.72 -1.691 0.596 ... ..$ two : num [1:200] 0.243 -0.159 -2.163 -1.183 0.632 ... ..$ three: num [1:200] 0.359 0.476 1.485 0.39 -1.412 ... $ 4:'data.frame': 200 obs. of 3 variables: ..$ one : num [1:200] -1.43 -0.345 -1.206 -0.925 -0.551 ... ..$ two : num [1:200] -1.343 1.322 0.208 0.444 -0.861 ... ..$ three: num [1:200] 0.00807 -0.20209 -0.56865 1.06983 -0.29673 ... $ 5:'data.frame': 123 obs. of 3 variables: ..$ one : num [1:123] -1.269 1.555 -0.19 1.434 -0.889 ... ..$ two : num [1:123] 0.558 0.0445 -0.0639 -1.934 -0.8152 ... ..$ three: num [1:123] -0.0821 0.6745 0.6095 1.387 -0.382 ... If some code might have changed the rownames it would be safer to use:
split(df, (seq(nrow(df))-1) %/% 200) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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