R – How to save data file into .RData

rrdata

I want to save data into an .RData file.

For instance, I'd like to save into 1.RData with two csv files and some information.

Here, I have two csv files

1) file_1.csv contains object city[[1]]
2) file_2.csv contains object city[[2]]

and additionally save other values, country and population as follows.
So, I guess I need to make objects 'city' from two csv files first of all.

The structure of 1.RData may looks like this:

> data = load("1.RData")

> data
[1] "city"  "country"  "population"

> city
  [[1]]               
  NEW YORK         1.1
  SAN FRANCISCO    3.1

  [[2]]
  TEXAS            1.3
  SEATTLE          1.4

> class(city)
  [1] "list"

> country
  [1] "east"  "west"  "north"

> class(country)
  [1] "character"

> population
  [1] 10  11  13  14   

> class(population)
  [1] "integer"

file_1.csv and file_2.csv have bunch of rows and columns.

How can I create this type of RData with csv files and values?

Best Answer

Alternatively, when you want to save individual R objects, I recommend using saveRDS.

You can save R objects using saveRDS, then load them into R with a new variable name using readRDS.

Example:

# Save the city object
saveRDS(city, "city.rds")

# ...

# Load the city object as city
city <- readRDS("city.rds")

# Or with a different name
city2 <- readRDS("city.rds")

But when you want to save many/all your objects in your workspace, use Manetheran's answer.

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R> dd[with(dd, order(-z, b)), ]
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4 Low C 9 2
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Edit some 2+ years later: It was just asked how to do this by column index. The answer is to simply pass the desired sorting column(s) to the order() function:

R> dd[order(-dd[,4], dd[,1]), ]
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R>

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By using the merge function and its optional parameters:

Inner join: merge(df1, df2) will work for these examples because R automatically joins the frames by common variable names, but you would most likely want to specify merge(df1, df2, by = "CustomerId") to make sure that you were matching on only the fields you desired. You can also use the by.x and by.y parameters if the matching variables have different names in the different data frames.

Outer join: merge(x = df1, y = df2, by = "CustomerId", all = TRUE)

Left outer: merge(x = df1, y = df2, by = "CustomerId", all.x = TRUE)

Right outer: merge(x = df1, y = df2, by = "CustomerId", all.y = TRUE)

Cross join: merge(x = df1, y = df2, by = NULL)

~~Just as with the inner join, you would probably want to explicitly pass "CustomerId" to R as the matching variable.~~ I think it's almost always best to explicitly state the identifiers on which you want to merge; it's safer if the input data.frames change unexpectedly and easier to read later on.

You can merge on multiple columns by giving by a vector, e.g., by = c("CustomerId", "OrderId").

If the column names to merge on are not the same, you can specify, e.g., by.x = "CustomerId_in_df1", by.y = "CustomerId_in_df2" where CustomerId_in_df1 is the name of the column in the first data frame and CustomerId_in_df2 is the name of the column in the second data frame. (These can also be vectors if you need to merge on multiple columns.)

Best Answer

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