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add cheatsheet #50

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add cheatsheet
caalo Jun 24, 2024
0cbddf4
Update 06-cheatsheet.Rmd
caalo Jun 24, 2024
c1d2928
Update 06-cheatsheet.Rmd
caalo Jun 24, 2024
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107 changes: 107 additions & 0 deletions 06-cheatsheet.Rmd
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@@ -0,0 +1,107 @@
# Cheatsheet

Here is a summary of expressions we learned in class.

Recall that we focused on English \<-\> Programming Code for R Interpreter in this class. Many of the functions we learned require the "Tidyverse" library to run.

## Basic Data Types

| English | R Language |
|-----------|------------------|
| Numeric | `2 + 3` |
| Character | `"hello", "123"` |
| Logical | `TRUE`, `FALSE` |

## Vectors

+--------------------------------------+---------------------------------------------+
| English | R Language |
+======================================+=============================================+
| Create a vector with some elements | `vec = c(1, -4, -9, 12)` |
| | |
| | `names = c("chris", "hannah", "chris", NA)` |
+--------------------------------------+---------------------------------------------+
| Compute length of a vector | `length(vector)` |
+--------------------------------------+---------------------------------------------+
| Access the second element of `names` | `names[2]` |
+--------------------------------------+---------------------------------------------+

## Conditional Operations

Often to create a logical indexing vector for subsetting

| English | R Language |
|-----------------------------------------|------------------------|
| `vec` is greater than 0 | `vec > 0` |
| `vec` is between 0 and 10 | `vec >= 0 & vec <= 10` |
| `vec` is between 0 and 10, exclusively | `vec > 0 & vec < 10` |
| `vec` is greater than 4 or less than -4 | `vec > 4 | vec < -4` |
| `names` is "chris" | `names == "chris"` |
| `names` is not "chris" | `names != "chris"` |
| The non-missing values of `names` | `!is.na(names)` |

## Subsetting vectors

+--------------------------------------+-----------------------------------+
| English | R Language |
+======================================+===================================+
| Subset `vec` to the first 3 elements | `vec[c(1, 2, 3)]` |
| | |
| | or |
| | |
| | `vec[1:3]` |
| | |
| | or |
| | |
| | `vec[c(TRUE, TRUE, TRUE, FALSE)]` |
+--------------------------------------+-----------------------------------+
| Subset `vec` to be greater than 0 | `vec[vec > 0]` |
+--------------------------------------+-----------------------------------+
| Subset `names` to have "chris" | `vec[vec == "chris"]` |
+--------------------------------------+-----------------------------------+

## Dataframes

+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| English | R Language |
+====================================================================================================+============================================================+
| Load a dataframe from CSV file "data.csv" | `dataframe = read_csv("data.csv")` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Load a dataframe from Excel file "data.xlsx" | `dataframe = read_excel("data.xlsx")` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Compute the dimension of `dataframe` | `dim(dataframe)` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Access a column "subtype" of dataframe as a vector | `dataframe$subtype` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Subset `dataframe` to columns "subtype", "diversity", "outcome" | `select(dataframe, subtype, diversity, outcome)` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Subset `dataframe` to rows such that the outcome is greater than zero, and the subtype is "lung". | `filter(dataframe, outcome > 0 & subtype == "lung"`) |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+
| Create a new column "log_outcome" so that it is the log transform of "outcome" column | `dataframe$log_outcome = log(dataframe$outcome)` |
| | |
| | or |
| | |
| | `dataframe = mutate(dataframe, log_outcome = log(outcome)` |
+----------------------------------------------------------------------------------------------------+------------------------------------------------------------+

## Summary Statistics of a Dataframe's column

| English | R Language |
|--------------------------------------------------------------|-----------------------------------------|
| Mean of `dataframe`'s "outcome" column | `mean(dataframe$outcome)` |
| Mean of `dataframe`'s "outcome" column, removing `NA` values | `mean(dataframe$outcome, na.rm = TRUE)` |
| Max of `dataframe`'s "outcome" column | `max(dataframe$outcome)` |
| Min of `dataframe`'s "outcome" column | `min(dataframe$outcome)` |
| Count of `dataframe`'s "subtype" column | `table(dataframe$subtype)` |

## Dataframe transformations

+---------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| English | R Language |
+===============================================================================================================================================================+==================================================================================================+
| Merge dataframe `df1` and `df2` by common column "id", using all common entities. | `full_join(df1, df2, "id")` |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
| Group `dataframe` by "subtype" column, and summarise the mean "outcome" value for each "subtype" value, and get the total elements for each "subtype" value. | `dataframe_grouped = group_by(dataframe, subtype)` |
| | |
| | `dataframe_summary = summarise(dataframe_grouped, mean_outcome = mean(outcome), n_sample = n())` |
+---------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------+
1 change: 1 addition & 0 deletions _bookdown.yml
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Expand Up @@ -7,6 +7,7 @@ rmd_files: ["index.Rmd",
"03-data-wrangling1.Rmd",
"04-data-wrangling2.Rmd",
"05-data-visualization.Rmd",
"06-cheatsheet.Rmd",
"About.Rmd",
"References.Rmd"]
new_session: yes
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