Introduction to Python for Research - Dr. Jason Kiley

Compared to an integrated stats software environment like Stata, which of the following are advantages of Python for data work?

All of these.
A modern programming language, with a full range of general purpose and specialized tools.
Large, helpful communities that often answer questions and create tutori‑ als.
High quality data tools that can scale from your own computer to supercom‑ puting clusters.

For all of its strengths, Python asks a bit more of users in terms of basic programming skills and a working knowledge of how packages fit together in environments.

True
False

To follow best practices, we should have an Anaconda environment at which of the following levels?

Each research project (or similar).
Each computer we use.
Just use base/root for everything and update regularly.

What does the following code produce: 2 + ‘2’

TypeError
4
'4'
4.0

What do we do with a dictionary in Python?

Holds key‑value pairs, often used for lookups.
Stores lists of items in sequential order.
Converts data types between formats.
Allows us to manually manage how Python uses computer memory.

Functions allow us to give a name to a procedure that may take input and/or produce output.

True
False

In the following code sample, which term best describes “.lower()”: ‘Hello!’.lower()

method.
function.
Class.
package.

A list comprehension is a Python convenience syntax feature that makes it easy to do the equivalent of using a for loop on one list to produce another.

True
False

Which of the following are advantages of using pandas dataframes compared to the data prep tools in most stats software?

All of these are correct
Better tools for cleaning, aggregating, transforming, and inspecting data.
Support for reading and writing common formats like CSV, Stata, SPSS, SAS, Excel, and high‑performance formats like parquet.
Easy merging, even with different column names or indexes on each side.

Plotly Express makes nice visualizations as easy as one line of code, while providing the ability to make more complex figures (with a bit more work).

True
False

When planning a data‑intensive project, the top priority is to put together a pilot study (even with manual elements) to be sure that we will have what we need to accomplish our research goal and that the parts will fit together (e.g., with identifiers).

True
False

Which of the following size/source pairs is the best case for using web scraping to gather data?

Large amounts of data from one or a few sources.
Small amounts of data from one or a few sources.
Refine prior made codes
Draw on concrete data

If the end data is the same, which of the following sources will be the most efficient in terms of researcher effort?

Retrieving from an API.
Web scraping.
Manual collection.

It is an acceptable security practice to put an API key directly into the code in a notebook.

False
True

In built‑in Python objects, and those provided by several of the third party packages we have used, we can use syntax to access data inside the data structure (e.g., by index, key, column name, or the like). What syntax do we use?

Square brackets (e.g., dataframe['column_name']).
Parentheses (e.g., dataframe(column_name)).
Curly braces (e.g., dataframe{column_name}).

Which of the following are good reasons to use SQL to retrieve data?

All of these.
Customizing the form of data coming from the DBMS so that it requires lit‑ tle/no cleaning.
Providing reproducible (and reusable) documentation of the data gathering process, since we cannot share copyrighted data.
Having the database server aggregate or transform data to provide data at a different level than the underlying data source.

When using humans to code/gather data, a good way to minimize human time spent is to automate as close as possible to the human‑required task (on both sides).

True
False

If all goes well, final data assembly is a fairly anticlimactic adaptation of the data handling plan from our pilot study.

True
False

Which of the following is my (Jason’s) top data‑related regret?

If I had made some of my gathered more generally useful, I could have used them again instead of recollecting things like press releases for subsequent projects.
I should have just written theory papers instead of all of this data stuff.
Spending time preparing. As Rick Moranis put it in Space Balls, “Why are we always ‘preparing’? Just go.”

Which of the following accurately describe the polars package?

All of these.
It is an alternative to using pandas.
It is under very active development, which means that the names of meth‑ ods and the design of functionality may change relatively frequently.
(In Jason’s opinion) it is a good package for more experienced Python users, but learning pandas first is a better choice for most people.

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Introduction to Python for Research – Dr. Jason Kiley

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