I have a for loop
which produces a data frame after each iteration. I want to append all data frames together but finding it difficult. Following is what I am trying, please suggest how to fix it:
d = NULL for (i in 1:7) { # vector output model <- #some processing # add vector to a dataframe df <- data.frame(model) } df_total <- rbind(d,df)
It turns out Pandas does have an effective way to append to a dataframe: df. loc( len(df) ) = [new, row, of, data] will "append" to the end of a dataframe in-place.
Within the for-loop we have performed three steps: First, we have created a vector object containing the values that we wanted to add as column to our data frame. Second, we added the new column ad the end of our data frame. Third, we renamed our new column (this step is optional).
Pandas dataframe.append() function is used to append rows of other dataframe to the end of the given dataframe, returning a new dataframe object. Columns not in the original dataframes are added as new columns and the new cells are populated with NaN value.
Within the for-loop we have performed three steps: First, we have created a vector object containing the values that we wanted to add as column to our data frame. Second, we added the new column ad the end of our data frame. Third, we renamed our new column (this step is optional).
Pandas dataframe.append () function is used to append rows of other dataframe to the end of the given dataframe, returning a new dataframe object. Columns not in the original dataframes are added as new columns and the new cells are populated with NaN value. Attention geek!
This is inefficient as it involves copying data repeatedly. A much better idea is to create a list of dataframes and then concatenate them at the end in a final step outside your loop. Here's some pseudo-code:
Don't do it inside the loop. Make a list, then combine them outside the loop.
datalist = list() for (i in 1:5) { # ... make some data dat <- data.frame(x = rnorm(10), y = runif(10)) dat$i <- i # maybe you want to keep track of which iteration produced it? datalist[[i]] <- dat # add it to your list } big_data = do.call(rbind, datalist) # or big_data <- dplyr::bind_rows(datalist) # or big_data <- data.table::rbindlist(datalist)
This is a much more R-like way to do things. It can also be substantially faster, especially if you use dplyr::bind_rows
or data.table::rbindlist
for the final combining of data frames.
You should try this:
df_total = data.frame() for (i in 1:7){ # vector output model <- #some processing # add vector to a dataframe df <- data.frame(model) df_total <- rbind(df_total,df) }
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