python-intro/exercises/ex08_plotting.ipynb

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   "source": [
    "# Exercise 8: Plotting with `matplotlib`"
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   "source": [
    "## Aim: Use `pyplot` to create time series plots."
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    "### Issues covered:\n",
    "- Import `pyplot` from `matplotlib`\n",
    "- Create a basic time series plot from lists\n",
    "- Create a plot from a `pandas` DataFrame\n",
    "- Plot multiple series on one graph\n",
    "- Create different kinds of plots - including scatter and bar graphs"
   ]
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    "## 1. Create a simple time series from a list"
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    "Import `matplotlib.pyplot` as `plt`, then create two datasets - one for the time values `[0, 10, 20, 30]`, and one for the positions with the value `[0, 200, 400, 600]`."
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    "Plot the data using `plt.plot()` and add axis labels."
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    "## 2. Create a plot from a DataFrame"
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    "Create a dataframe that we will use to make a plot. Use the file `data/oceania_gdp` and index it by country. "
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    "Extract the year from the last 4 characters of the column names using:\n",
    "```\n",
    "data.columns.str.replace('gdpPercap_', '')\n",
    "```"
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    "Convert the years values to integers using `astype()`and save the results back to the dataframe."
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    "Plot the resulting data for 'Australia'. Set the x and y axis labels to `Year` and `GDP per capita` respectively."
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    "## 3. Plot multiple series"
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    "Plot multiple series using `.T.plot()` and set the axis labels to `Year` and `GDP per capita` again."
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    "## 4. Plot some different types of graphs"
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    "Plot the data in the form of a bar chart, including axis labels."
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    "Create a variable called `years`, setting the value as the columns from your dataframe. Create a variable called `gdp_australia` which uses `loc()` to get the data for Australia. Try making a plot by calling the `plt.plot(x,y)` function directly for `years` on the x axis and `gdp_australia` on the y axis. Plot the data using a blue dashed line."
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    "Plot multiple datasets on the same graph by following the steps above for both Australia and New Zealand. Include axis labels and a legend. Plot New Zealand with a green dashed line and Australia a red dashed line."
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    "Create a scatter plot using `plt.scatter()` to compare the GDP of Australia and New Zealand."
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    "## 5. Extension activity: Customise a plot and save it."
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    "1. Create an x axis using `x = np.arange(0, 5, 0.1)`. Print it out to see what this line of code does."
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    "_Hint: Remember to import `numpy` as `np`._"
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    "2. Create a y axis with values $sin(x)$ using a relevant function from `numpy` with the x values from the previous question."
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    "3. Use `pyplot` to plot these values. "
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    "4. Plot a cos graph on the same graph as the sin curve. Add a legend and axis labels. Customise the colours too if you like."
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    "5. Save your plot to a file in the `images` folder using `plt.savefig('filename')`."
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