Press "Enter" to skip to content

Month: February 2020

How to Convert a Python Dictionary to a Pandas DataFrame

In this brief Python Pandas tutorial, we will go through the steps of creating a dataframe from a dictionary. Specifically, we will learn how to convert a dictionary to a Pandas dataframe in 3 simple steps. First, however, we will just look at the syntax. After we have had a quick look at the syntax on how to create a dataframe from a dictionary we will learn the easy steps and some extra things. In the end, there’s a YouTube Video and a link to the Jupyter Notebook containing all the example code from this post.

how to make a dataframe from python dictionary

How to Get the Column Names from a Pandas Dataframe – Print and List

In this short post, we will learn 6 methods to get the column names from Pandas dataframe. One of the nice things about Pandas dataframes is that each column will have a name (i.e., the variables in the dataset). Now, we can use these names to access specific columns by name without having to know which column number it is.

To access the names of a Pandas dataframe, we can the method columns(). For example, if our dataframe is called df we just type print(df.columns) to get all the columns of the pandas dataframe.

get pandas column names

How to Plot a Histogram with Pandas in 3 Simple Steps

In this post, we are going to learn how to plot histograms with Pandas in Python. Specifically, we are going to learn 3 simple steps to make a histogram with Pandas. Now, plotting a histogram is a good way to explore the distribution of our data.

Note, at the end of this post there’s a YouTube tutorial explaining the simple steps to plot a Histogram with Pandas.

Prerequisites

First of all, and quite obvious, we need to have Python 3.x and Pandas installed to be able to create a histogram with Pandas. Now, Python and Pandas will be installed if we have a scientific Python distribution, such as Anaconda or ActivePython, installed. On the other hand, Pandas can be installed, as many Python packages, using Pip: pip install pandas.

how to plot a histogram using Pandas

How to Read and Write Stata (.dta) Files in R with Haven

In this post, we are going to learn how to read Stata (.dta) files in R statistical environment. Specifically, we will learn 1) who to import .dta files in R using Haven, and 2) how to write dataframes to .dta file.

Data Import in R: Reading Stata Files

Now, R is, as we all know, a superb statistical programming environment. When it comes to importing and storing data, we can store our data in the native .rda format. However, if we have a collaborator that uses other statistical software (e.g., Stata) and/or that are storing their data in different formats (e.g., .dta files).

Now, this is when R shows us its brilliance; as an R user we can load data from a range of file formats; e.g., SAS (.7bdat), Stata (.dta), Excel (e.g., .xlsx), and CSV (.csv). On this site there are other tutorials on how to import data from (some) of these formats:

Before we go on and learn how to read SAS files in R, we will answer the questions: