Maheen Asghar

Data scientist and analyst. Turning complex data into actionable insights.

Welcome to my portfolio page

Visualization of data from the Opportunity Atlas.

<https://ai-income-vis.glitch.me/>

The Opportunity Atlas uses anonymous data following 20 million Americans from childhood to their mid-thirties. It gives data on how much kids who grew up in certain neighborhoods earn as adults.

Stanford University researchers found that almost half of parental income advantages in the United States are passed on to children. The research also found that a family's economic circumstances play an important role in determining a child's economic prospects. Children raised in families in the 90th percentile for household income can expect their own family income to be three times higher than children raised at the 10th percentile for household income.

According to the American Community Survey, 1 in 3 American Indians are living in poverty--with a median income of $23,000 a year. The findings at Stanford show that children raised in families that are "far apart on the income ladder can expect very different economic futures". Using the data from the Opportunity Atlas, we will be able to determine if the statement holds true with American Indians in the United States.

Click on the link above to read more.


Determined if CitiBike is an affordable system or a luxury service through data collection and visualization.

<https://github.com/miscalculation/citi-bike>

In this project, I analyzed data from CitiBike data from October 1st, 2019 to October 31st, 2019 (2,092,086 trips) to determine if CitiBike was an affordable system or if it was a luxury service. I found data to support the two opposing views.

![](/images/CitiBike_Map.png)


CitiBike Analysis

American Indian Household Income

Analyzed the sentiment of Trump and Obama's tweets during their time in office.

<https://github.com/miscalculation/sentiment-analysis-potus>

Using machine learning, we created a sentiment analyzer that determines if tweets carry positive, neutral, or negative sentiment. In addition, we evaluated time series and identify trends for local variations to more accurately assess Trump’s usual twitter sentiment vs Obama’s.

When looking at Trump versus Obama’s tweets, we found that Obama had a more even distribution of positive and neutral sentiment of tweets, while having very little negative sentiment tweets. Trump had a disproportionately higher number of positive sentiment tweets over the other categories.

![](/images/Obama_Trump.png)


Welcome to my portfolio page

American Indian Household Income

CitiBike Analysis

Sentiment Analysis of @POTUS

Blog posts coming soon...

Home

Welcome to my portfolio page

American Indian Household Income

CitiBike Analysis

Sentiment Analysis of @POTUS

Blog posts coming soon...