# HIDDEN # Clear previously defined variables %reset -f # Set directory for data loading to work properly import os os.chdir(os.path.expanduser('~/notebooks/03'))
Working with Tabular Data¶
Tabular data, like the datasets we have worked with in Data 8, are one of the
most common and useful forms of data for analysis. We introduce tabular data
pandas, the standard Python library for working with
tabular data. Although
pandas's syntax is more challenging to use than the
datascience package used in Data 8,
pandas provides significant performance
improvements and is the current tool of choice in both industry and academia
for working with tabular data.
It is more important that you understand the types of useful operations on data
than the exact details of
pandas syntax. For example, knowing when to use a
group or a join is more useful than knowing how to call the
to group data. It is relatively easy to look up the function you need once you
know the right operation to use. All of the table manipulations in this chapter
will also appear again in a new syntax when we cover SQL, so it will help you
to understand them now.
Because we will cover only the most important
pandas functions in this
textbook, you should bookmark the
pandas documentation for reference
when you conduct your own data analyses.