In my Line Graph, I show the population of people in Albany for the entire census. I used race as a filter but excluded Native Americans. I was surprised to find how there was little increase in the population of Black and Japanese and Chinses people, even in the later periods displayed on the chart. […]
A concept I found difficult? Keeping everything straight! The gender inference project had me flipping between all the projects for the past few weeks. I began with the intention of keeping everything exact and succinct but I think by the end I was just flailing words about- “This is the thing that makes it do […]
https://colab.research.google.com/drive/1CaKmqJ2Ng8lhOu0bQ4hfLuDIYNKUDfIO (API Request) https://colab.research.google.com/drive/11jyBNm5ZpqTtMkMqw_ZU6n9hp5aSK4jR (Webscraping) https://colab.research.google.com/drive/1vULOFOMO-K_my1_nF-L3kxXeH_HLK1qv (Geocoding) https://colab.research.google.com/drive/1-NI-qaxN7cbESXyBoXQFz1ZRqEG2fwCz (Gender Inference) This assignment was indeed the most difficult assignment I have done in this course so far. It reminded me of my old college sophomore days when I was struggling to code with C. Like I mentioned the week prior, I much prefer to use Observable […]
I chose Option A, and, as a second-generation Capital Region Italian (though my people are Schenectady, not Albany), I decided to create visualizations showing the number of Italian immigrants recorded in the Albany census from 1880-1940 (I excluded 1850, as Italy wasn’t yet a unified nation at that point..). The first slide shows the number […]
For the side-by-side bar chart I created a chart which tracks the population of Albany in each Census year, broken down by race. I included a filter for race. For the line graph I created a graph which charts the top 10 most popular occupations in Albany from 1850-1940 based on the census data. This […]
Above is my attempt to put all three visualizations in a story. I’m not sure if it is showing up. Below you will see the visualizations separately. I’m not a fan of how WordPress is rendering them. The details are really small and they seem blurry. This bar chart illustrates the occupations most common to […]
API Task Webscraping Task Georeferencing Task Python. I found Python difficult. The API and Webscraping assignments were really difficult for me. I was having flashbacks to AP calc when I was stumped on what formula to use for what function, and it wasn’t pleasant. By the time I got to the Georeferencing assignment, though, things […]
I chose to do the lessons in Observable, so here is the Tableau workbook from the first lesson: (I made the workbook into a story, but when I went to embed it into this post, it was static rather than interactive. I changed the block to a custom html and I could click through it […]
My stacked bar graph visualizes the occupations of Albany residents, as well as their race. I went with this type of graph because I thought it was very interesting that the majority of the black population held jobs in labor or domestic work, with very little attending school or holding public service jobs. I played […]
In my histogram, I visualized the distribution of ages for each birthplace group. I then highlighted two ages that stuck out to me, 26 and 39. Almost all my birthplace groups have one of these ages as their highest or their second highest age bin. Since these birthplace groups signify all Albany residents who were […]