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Month: September 2019

How to use iloc and loc for Indexing and Slicing Pandas Dataframes

In this post, we are going to work with Pandas iloc, and loc. More specifically, we are going to learn slicing and indexing by iloc and loc examples.

Once we have a dataset loaded as a Pandas dataframe, we often want to start accessing specific parts of the data based on some criteria. For instance, if our dataset contains the result of an experiment comparing different experimental groups, we may want to calculate descriptive statistics for each experimental group separately.

How to Use Binder and R for Reproducible Research

In a previous post, we learned how to use Binder and Python for reproducible research. Now, we are going to learn how to create a Binder for our data analysis in R, so it can be fully reproduced by other researchers. More specifically, in this post, we will learn how to use Binder for reproducible research.

Many researchers upload their code for data analysis and visualization using git (e.g., GitHub, Gitlab).

No doubt, uploading your R scripts is great. However, we also need to make sure that we share the complete computational environment so that our code can be re-run and so that others can reproduce the results. That is, to make sure that other researchers really can reproduce our code, we need a way to capture the versions of the R packages we used when publishing our research.

How to Read & Write SPSS Files in Python using Pandas

In this post, we are going to learn 1) how to read SPSS (.sav) files in Python, and 2) how to write to SPSS (.sav) files using Python. 

Python is a great general-purpose language as well as for carrying out statistical analysis and data visualization. However, Python is not really user-friendly when it comes to data storage. Thus, often our data will be archived using Excel, SPSS or similar software.

For example, learn how to import data from other file types, such as Excel, SPSS, and Stata in the following two posts:

SPSS interface
Overview of the .sav file in SPSS

If we ever need to learn how to read a file in Python in other formats, such a text file, it is doable. To read a file in Python without any libraries we just use the open() method.