python-intro/exercises/ex07_pandas_dataframes.ipynb

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   "source": [
    "# Exercise 7: More About Pandas DataFrames"
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   "source": [
    "## Aim: Learn how to select certain data from a `Pandas` DataFrame."
   ]
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    "### Issues covered:\n",
    "- Using `loc` and `iloc` to locate data in a dataframe\n",
    "- Slicing dataframes\n",
    "- Creating subsets and masks"
   ]
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   "source": [
    "## 1. Using `loc` and `iloc`"
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   "source": [
    "Create a dataframe called `data` from the CSV file `data/europe_gdp.csv` and index it by the `country` column."
   ]
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   "source": [
    "Print out the GDP per capita for Belgium in 1957 (2nd column, 3rd row) using `iloc`."
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   "source": [
    "_Hint: Remember that indexing starts from 0 in Python. You should get the value `9714.960623`._"
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   "source": [
    "Use `loc` to print out GDP per capita for Belgium in 1957. You should get the same result as above."
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   "source": [
    "Print GDP per capita for `Switzerland` for all years using `:`."
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   "source": [
    "Print out GDP per capita in 1987 for all countries."
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   "source": [
    "Print out a slice of the data frame which shows GDP for countries between Denmark to Iceland from 1982 to 1992. "
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   "source": [
    "Print out the last 3 columns for the last 3 rows of countries."
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   "source": [
    "What are the maximum GDP values between 1997-2007 for the last 3 countries alphabetically? "
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   "source": [
    "## 2. Creating subsets and masks"
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    "Create a variable called `subset` which contains only the data for Hungary to Netherlands between 1962 and 1972. Print out the subset."
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   "source": [
    "Return a dataframe of boolean (`True` or `False`) values showing where the GDP values are greater than 10000. "
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   "source": [
    "Create a boolean mask for the above and print the result of applying this to the subset."
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   "source": [
    "What is the mean and standard deviation of the mask applied to this subset?"
   ]
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   "source": [
    "## 3. Extension Questions"
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    "1. Find the index of the maximum for each column of the dataset. "
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    "_Hint: You will need to make use of `idxmax()`._"
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   "source": [
    "2. Similarly, find the index of the minimum for each column of the dataset."
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    "_Hint: You will need to make use of `idxmin()`._"
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   "source": [
    "3. Print out the median GDP per capita across all countries for each year."
   ]
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   "source": [
    "_Hint: Use `median()`._"
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