Baby Steps in Data Journalism
Really great: A step-by-step walkthrough of “transforming a slew of data into a stunning chart.”
(via lifeandcode)
ScienceOnline Bay Area event: Data Visualization and Data Journalism in Science, 19 April 2012.
Click the image to get the links.
I would be remiss if I did not link to Nathan’s wonderful blog, which “explores how designers, statisticians, and computer scientists are using data to understand ourselves better — mainly through data visualization.”
At Forbes.com, Naomi Robbins has a blog called “Effective Graphs.” How cool is that?
Robbins is “a consultant and seminar leader who specializes in the graphical display of data. [She trains] employees of corporations and organizations on effective data visualization.”
I learned a lot from her post about misleading pie charts.
HT: @albertocairo
![Results from Data Scraping
Okay, this is even better than the first one. I modified Nathan’s script to scrape both the maximum and minimum temperatures for 365 days (meaning 365 Web pages!) and dumped them into one comma-delimited text file. Then I imported it into Excel to make this graph. I just used the Excel chart tools to make it (Excel for Mac 2011).
Python (partial):
# Get temperature from page
soup = BeautifulSoup(page)
# maxTemp = soup.body.nobr.b.string
maxTemp = soup.findAll(attrs={"class":"nobr"})[5].span.string
minTemp = soup.findAll(attrs={"class":"nobr"})[8].span.string
# Above I added a scrape for lowest temperature too](http://24.media.tumblr.com/tumblr_m2inmpbckE1rttnkbo1_500.png)
Results from Data Scraping
Okay, this is even better than the first one. I modified Nathan’s script to scrape both the maximum and minimum temperatures for 365 days (meaning 365 Web pages!) and dumped them into one comma-delimited text file. Then I imported it into Excel to make this graph. I just used the Excel chart tools to make it (Excel for Mac 2011).
Python (partial):
# Get temperature from page
soup = BeautifulSoup(page)
# maxTemp = soup.body.nobr.b.string
maxTemp = soup.findAll(attrs={"class":"nobr"})[5].span.string
minTemp = soup.findAll(attrs={"class":"nobr"})[8].span.string
# Above I added a scrape for lowest temperature too
Results from Data Scraping
So I’m pretty happy with today’s work: In a little less than 3 hours (including blogging about all this and looking up lots of related stuff), I was able to use Python to scrape 365 Web pages and export a comma-delimited file of the maximum recorded temperature for every day in 2011 for Gainesville, Florida.
I opened the file with Excel and used the built-in chart tools to create the graphic above, which is quite simple — but it’s showing all the data from that scrape! So cool!
You can view a Google Spreadsheets version > here.
