Category: How to
Exploring climate data using the Python libraries Matplotlib and Pandas
If you’ve just grabbed a new dataset and you want to look for interesting trends, making some exploratory graphs in Jupyter Notebook is a good way to start. I usually […]
Mapping toxic waste release sites using the Python library GeoPandas
Plotting positional information on maps can reveal geographic trends and makes for an effective visualization to accompany an article. In this tutorial, we’ll use Jupyter Notebook and a Python library […]
How journalists use the EPA’s Toxics Release Inventory to report on environmental justice
In 1984, a Union Carbide pesticide plant in Bhopal, India, leaked 45 tons of toxic methyl isocyanate gas, killing thousands of people and injuring hundreds of thousands. A few months […]
How to calculate a rolling average in R
Rolling or moving averages are a way to reduce noise and smooth time series data. During the Covid-19 pandemic, rolling averages have been used by researchers and journalists around the […]
Update: How to geocode a CSV of addresses in R
This post is an update from the previous post, “How to geocode a CSV of addresses in R”. We will be using the ggmap package again, and be sure to investigate the usage […]
How to shift Alaska and Hawaii below the lower 48 for your interactive choropleth map
Last month, the Harvard Global Health Institute collaborated with The New York Times and ProPublica to publish a model estimating the capacity of hospitals across the United States to cope […]
What I learned applying data science to U.S. redistricting
Deciding whether to reelect President Donald Trump isn’t the only choice Americans will have to make when they head to the voting booths this November. More than 5,000 state lawmakers […]
How to use hierarchical cluster analysis on time series data
Which cities have experienced similar patterns in violent crime rates over time? That kind of analysis, based on time series data, can be done using hierarchical cluster analysis, a statistical […]
Diagnosing the accuracy of your linear regression in R
In this post we’ll cover the assumptions of a linear regression model. There are a ton of books, blog posts, and lectures covering these topics in greater depth (and we’ll […]
How to collect tweets from the Twitter Streaming API using Python
Twitter provides a comprehensive streaming API that developers can use to download data about tweets in real-time, if they can figure out how to use it effectively. In this tutorial, […]
How to explore correlations in R
This post will cover how to measure the relationship between two numeric variables with the corrr package. We will look at how to assess a variable’s distribution using skewness, kurtosis, […]
How to make a multilayered Google My Map using news articles on invasive species
Wildfires, hurricanes, extreme heat waves, invasive species. These are the climate change news that I read most every morning I visit The Weather Channel’s homepage for the day’s weather forecast. […]
How I visualized “Trump” mentions in hip-hop songs using D3
Hip-hop is often brutally honest about controversial issues in society – money, guns, drugs, sex and, of course, politics. I found a dataset collected and cleaned by FiveThirtyEight containing the […]
How to download YouTube data in R using “tuber” and “purrr”
Accessing YouTube’s metadata such as views, likes, dislikes and comments is simple in R thanks to thetuber package by Gaurav Sood. Sood wrote an excellent, easy-to-use package for accessing the […]
How to do basic text mining using Google Sheets
While techniques for text mining, sentiment analysis and other natural language processing are ubiquitous on the Internet, they’re not always accessible to students. I recently ran this tutorial in my […]