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Proof reading: intro to r load data
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individual_modules/introduction_to_r/data_types.ipynb

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"which can make them quite powerful for subsetting. \n",
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"\n",
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"It is very easy for character vectors to be inappropriately stored as factors and vice versa. In fact, R's default \n",
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"when loading data is to store a string as a factor. Conversely if we define a vector we have to explicit convert \n",
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"it to a vector\n",
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"when loading data is to store a string as a factor. Conversely if we define a vector, we have to explicitly convert \n",
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"it to a vector.\n",
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"For example, if we define a vector of months, the default is to class it as a vector of characters. We have to actively \n",
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"coerce it into a factor. "
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"## Activity: Data Exploration\n",
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"Use these functions to explore the mtcars dataset\n",
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"Use these functions to explore the mtcars dataset.\n",
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"* How large is the dataset?\n",
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"* What type is the object?\n",

individual_modules/introduction_to_r/load_data.ipynb

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"dataset in the file \"data/worms.csv\" which you can download from the course webpage. \n",
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"This is a comma-separated values (CSV) format which means that a comma is used to indicate the end of a column.\n",
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"We need to tell our computer where is the file that contains the values - if we forget this step we'll get an error message when trying to read the file. We can load the data into R using `read.csv`.\n",
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"We need to tell our computer where the file that contains the values is. If we forget this step we'll get an error message when trying to read the file. We can load the data into R using `read.csv`.\n",
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"Assuming you have downloaded the file into your current working directory, you can execute the following"
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"tags": []
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"Use some of the functions we have introduced earlier can be used to summarise the properties of the worms dataset"
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"Some of the functions we introduced earlier can be used to summarise the properties of the worms dataset."
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"## Loading Data With Header\n",
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"What happens if you forget to put `header = FALSE`? The default value is `header = TRUE`, which you can check with `?read.csv` or `help(read.csv)`. What do you expect will happen if you leave the default value? Before you run any code, think about what will happen to the first few rows of your data frame, and its overall size. Then run the following code and see if your expectations agree:"
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"What happens if you forget to put `header = FALSE`? The default value is `header = TRUE`, which you can check with `?read.csv` or `help(read.csv)`. What do you expect will happen if you leave the default value? Before you run any code, think about what will happen to the first few rows of your data frame, and its overall size."
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