Handling Data Flashcards
1
Q
data()
A
- Function that reveals R’s built-in data sets.
- Most packages have their own built in data sets.
2
Q
save()
A
- Function that allows the selective saving of objects.
- save(junk, junk2, file=”junky.RData”) = will sepcifically save the object junk and junk2 to an external file present in the working directory named junky.RData.
- There does not need to be a relationship between the external name and its contents.
3
Q
load()
A
- Function that loads a saved R object.
- load(“junky.RData”) = reloads the objects present in junky.RData
4
Q
load(url(“website_url”))
A
- Functions (nested) that allow you to remote load an R Data set.
- Always check the results of your remote load by reviewing the environment tab
5
Q
Reading Excel Files
A
- Useful packages: XLconnect, xlsx, gdata, readXL, etc.
- Function to read data into excel: read_excel(“file_name”, sheet = number, col_names = TRUE, col_types = NULL, na = “”, skip = something or nothing)
- Can always learn more about this function using help(read_excel).
6
Q
Reading Text Files
A
- Extensions: .txt, .csv, .dat, .tab.
- In the Import Dataset tab in the Environment tab, if you have a Local Text File, R will automatically load it (?).
- If the file is a Web URL:
1) Enter the URL.
2) Choose heading “Yes” if variable names are present.
3) Strings as Factors unchecked.
4) Set encoding to automatic.
5) R will correctly identify the dataset as tab separated. - You can check your results using the View() function.
7
Q
How to Read Text Files (functions)
A
1) read.csv()
2) read.delim()
3) read.table()
8
Q
Reading Non-conforming Yet Formatted Data
A
1) readLines()
2) scan()
9
Q
read.csv(“url_name”)
A
- Function used for reading comma separated (typically have .csv extension) files.
10
Q
read.delim(“url_name”)
A
- Function
11
Q
read.table(“url_name”)
A
- Function used for most any type of text file as long as a separator exists + more general than either read.csv or read.delim.
12
Q
readLines(“url_name”)
A
- Function that will read all or part of a text file.
- Useful for data files that are irregular, have no delimiter (commas or a separator) or do not conform to a standard format.
- Will read virtually any file.
13
Q
scan(“url_name”)
A
- Function similar to readLines but will keep a record of the structure or patterning in the data if your need to keep that information.
- More restrictive than readLines().
14
Q
NA / Missing Values
A
- A place within a vector may be reserved for the missing element by assigning the special value NA.
- Usually any operation involving NA results in an NA.
- All types of vectors (character, logical, numeric) can use NA to represent missing values.
15
Q
Numeric Vectors and NA Entries
A
- Includes the symbols -Inf and Inf (positive and negative “infinity”) and NaN (not a number).
16
Q
na.omit() / complete.cases()
A
- Functions that will remove observations with missing values from a dataset.
17
Q
Package foreign
A
- Package that allows us to read data files by competitors of R (DBF, Stata, Epi Info, Minitab, Octave SPSS, SAS and Systat).
- SAS files must be in transport format (.xport file) for package foreign.
- SPSS files require a use of an option to be converted into data frames.
- Stata files can be read up to Stata 12.
18
Q
Package haven
A
- Package that will only read data files from Stata, SPSS and SAS.
- Can also be used to write Stata and SPSS files.
- SAS files can be read without conversion (.sas7bdat files).
- SPSS files are converted into data frames automatically.
- Stata files can be read up to Stata 13.
19
Q
Stata
A
- A competing statistical programming software.
- R can both read and write files to Stata.
20
Q
read.dta()
A
- Function in package foreign that can read local Stata files or remotely stored Stata files using a web address.
- Result in a data frame.
21
Q
read_dta() + read_stata()
A
Function in package haven that can read local Stata files or remotely stored Stata files using a web address.
- Result in a data frame.
22
Q
write.dta()
A
- Function in package foreign that will export R data to Stata.
23
Q
write_dta()
A
- Function in package haven that will export R data to Stata.
24
Q
SPSS
A
- A competing statistical programming software.
- R can both read and write files to SPSS.
- Package haven does a much better job of reading these files than package foreign.
25
read.spss()
- Function in package foreign that is used to convert SPSS data files into R objects.
- Can read local or remotely stored files.
- Needs option to.data.frame = to make the resulting R object a data frame, otherwise read.spss() returns a list.
26
read_spss() + read_sav
- Functions in package haven that read SPSS data files and convert them into data frames.
27
write_sav()
- Function in package haven that can write SPSS files.
| - PAckage foreign cannot write SPSS files.
28
Differences Between Packages Foreign and Haven (SPSS)
- Foreign preserves labels but haven converts variables into numbers and stored the labels.
- Can convert these numbers back into variables using the function as_factor().
29
SAS
- A competing statistical programming software.
- Package foreign can read SAS data files but those files must exist in a portable format created by SAS software or user must have a copy of SAS software on local computer.
30
read_sas()
- Function in package haven that imports standard SAS files directly to an R data frame.
- Does not require SAS.
31
write.table(where_to_store, file = "name_of_file, sep = "some separator, like tab (\t)", row.names = FALSE (will not add a row of numbering))
- Function that will coerce an R object to be a data frame (if it isn't already one) and then save it as an external text file = can be imported into different non-R applications.
- Data frame written will have columns space delimited (default) but can be change to tab, comma or virtually anything.
- Missing values default to NA which can also be changed.
32
write.csv(where_to_store, file = "name_of_file", row.names = FALSE)
- Function that is a special case of write.table().
- When used, the result will be a comma separated values file.
- .csv files are the common format for data that is to be exchanged between software.
33
Results of write.table() or write.csv()
- Tab separated (delimited) files will usually have character quoted values + "jagged" appearance with what appear to be spaces between variables (fields).
- Comma separated (delimited) files will also have character values quoted but commas separating fields (also appear to be "jagged") but easier to see the separation between the fields.
- Both will typically have a first row which has the names of the columns.
34
subset(x, subset, select, drop = FALSE, ...)
- Function that generates subsets of a data frame or matrix based upon certain conditions.
- x: the data frame / object.
- subset: a condition you want to impose.
- select =: which columns or rows to take.
- drop =: if you want to remove any rows or columns.
35
Substitutions
- Can just change the entries of the data frame or matrix to the desired entries.
36
is.na()
- Function which will force all NA's in an object to be replaced with something of your choice.
37
$
- Operator which can be used to grow data frame columns or take data from columns of the data frame with the desired column name.
- data_frame_name$column_name
38
Adding new columns + Combining vectors with cbind() + Adding new rows + Combining data frames with rbind()
- Can use cbind() and rowbind() to add new columns or rows to a data frame.
- junk$Name
39
Merging Data Frames
- Can merge data frames but must have same matching information.
40
List Extraction Methods
- Can use $, [] or [[]].
- [] and [[]] will extract component entries.
- $ will extract a vector.
41
Webscrapping
- Needs the XML library.
- Try to use the readHTMLTable() function first = parses an HTML page and retrieves the table elements.
- Utilize readHTMLTable("url_name", stringsAsFactors = FALSE).
42
unlist()
- Function that converts a list into a vector.
43
Package rvest
- Package that also contains many tools to scrape webpages.
