1.5 Comparison operators

In Expressions [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] , you learned that Python has arithmetic operators: +, /, - and * and that expressions such as 5 + 2 evaluate to a value (in this case the number 7).

Figure 6

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An illustration of two girls holding up signs. One sign says, 'YES', the other says, 'NO'.

Figure 6

Python also has what are called comparison operators, these are:

Expressions involving these operators always evaluate to a Boolean value, that is True or False. Here are some examples:

The comparison operators can be used with other types of data, not just numbers. Used with strings they compare using alphabetical order. For example:

'aardvark' < 'zebra' evaluates to True

In Calculating over columns you saw that when applied to whole columns, the arithmetic operators did the calculations row by row. Similarly, an expression like df['Country'] >= 'K' will compare the country names, row by row, against the string 'K' and record whether the result is True or False in a series like this:

If such an expression is put within square brackets immediately after a dataframe’s name, a new dataframe is obtained with only those rows where the result is True. So:

df[df['Country'] >= 'K']

returns a new dataframe with all the columns of df but with only the rows corresponding to countries starting with K or a letter later in the alphabet.

As another example, to see the data for countries with over 80 million inhabitants, the following code will return and display a new dataframe with all the columns of df but with only the rows where it is True that the value in the 'Population (1000s)' column is greater than 80000:

In []:

df[df['Population (1000s)'] > 80000]

Out[]: