Troubleshooting

Watch this video on handling errors in Jupyter notebooks. Most errors are caused by something being typed wrong. Read the code again, and check for obvious mistakes.

• Did you spell all the words correctly?
• Do you have the punctuation correct? Punctuation such as brackets, periods, commas, and colons are all important. Make sure none are missing, and you are using the right type of punctuation.
• Are there capital letters where they need to be, or did you put some extra ones in? Python pays attention to capitalization;”Print” is a different command than “print”.
• Did you miss putting some “space” onto your code? Some code pieces need space in the right place. For instance, in a “For” loop, all the lines after the first one need space at the beginning. Python will show an error message if you don’t do this.

If all else fails, look at the error message that Python prints out to get a hint about what went wrong. (more on this below).

This is like a punctuation error, or an error in the format of your code. If a comma or period is missing, or a bracket is in the wrong place, Python will highlight this as a syntax error. Like most programming languages, Python is fairly rigid in the format it expects the code to be written in.

Python has three types of brackets:

• Round brackets (parentheses): used in math formulas like 2*(3+4), also used in calling a function like print(5), and finally in creating a tuple of objects like (1,2,3).
• Square brackets [brackets]: used to create lists, like ['one','two','three'] or to select an item in a list, like List[3].
• Curly brackets {braces}: used to define dictionaries, like {"a" : "Apple", "b" : "Banana"}.

Most importantly, brackets must always come in pairs: an opening bracket like “(” must be followed by a closing bracket like “)” at some point in the code. If you miss one of the pair, Python will report a syntax error.

There is no difference. You can use them interchangeably. However, in Python they must always appear in matching pairs.

• "Apple" and 'Apple' are both correct in Python. But "Apple' will cause a syntax error, as the quotes don’t match.
• Having two types of quotes is useful when you need to create a string that has a quotation mark or apostrophe in it. For example: "This isn't a long example" is a string that contains an apostrophe (a single quote) within the text.

When Python sees an error, it will print out an error messages underneath your code cell. Error messages in Python are long. A good approach is to read the first line and last line of the error message to see if it gives you a clue as to what is wrong. The error message will tell you exactly what line of code is causing the error. If you don’t see line numbers in your code, try selecting the menu item “View/Toggle Line Numbers.”

A syntax error usually means something is not typed correctly, or that there is a missing colon or other punctuation, etc. An error like "Name 'Print' is not defined" often means you typed in the name wrong or are trying to use a function from a library but got the details wrong. Check the capitalization as well.

A coding library refers to a collection of functions and data that someone has written for you to use. Coding libraries are also called coding modules.

There are many specialized libraries such as:

• Numpy (Numerical Python): developed for numerical problems
• Plotly: used to plot graphical information
• Pandas: used to transform data, such as creating a DataFrame.

To use a library, you must first import it into your code. For instance, to use the trig function “sine” in the numpy library, we first import numpy, then call the function.

import numpy
print(numpy.sin(.12))

Notice when we use a function from the library, we need to indicate both the library name and the function name, as in numpy.sin(). There are so many libraries available that we cannot list them here. Look here for more details: https://wiki.python.org/moin/UsefulModules

Yes. We can use an alias, like this:

import numpy as np
print(np.sin(.12))

Notice we only have to type “np” to refer to the numpy library.

Yes. Here is how we import the trig function “sin” and use it by itself:

from numpy import sin
print( sin(.12) )

Notice we do not type “numpy” or “np” when calling the sin() function.

To load a file into Python, usually you need to use a function from a library. For instance, here is how we read in a csv file called “Colours.csv” (a spreadsheet) into a pandas dataframe:

from pandas import read_csv
colours_df = read_csv('Colours.csv')

Notice we had to import the “read_csv” function before we could use it. We just include the name of the file to load in the function call.

The “Colours.csv” file must be in the same directory, or folder, as your Jupyter notebook that runs the code. If it is in a subfolder, such as “myFolder”, you can indicate that in the function call, like this:

from pandas import read_csv
colours_df = read_csv('myFolder/Colours.csv')