Who checks the Weather?

The data set that I analyzed was about how different groups of people check the weather. The csv file that I will be analyzing came from a survey that was given to individuals in order to learn more about how people learn about weather. The file was full of data points that could lead to answering the questions of how/why certain individuals check the weather before they start their day. The data includes a number of different points that describe each of the participants in one way or another. The dataset asks questions about age, gender, annual income, as well as geographical region the participant lives in.

While studying the data set, one may ask “why is this data important?”. Well, there are many answers to that question. First, we learn about how many people actually check for the weather before they leave their house in the morning. From this, we can see how gender, income, age, etc. affect this action.

Who was surveryed?

One of the most important things to remember while analyzing a data set is to acknowledge what types of individuals where surveyed. Data sets such as the “weather-check.csv” would be worthless if we, as information scientists, didn’t gain an understanding about the group of participants. And after looking into the type of individuals that were surveyed, we can begin to make connections and conclusions.

In this data set, I examined the gender, US region, age, and annual income of all of those that participated. I took the values from the CSV file and created a plethora of graphics that showed the representation of each corresponding group in the dataset. From this data, I was able to determine that the survey mostly contained women, people 45–59 year olds, people from the Pacific region of the US, and individuals who made between 25,000–50,000 dollars last year. Lets take a look at who was surveyed:

Here, we can see that a majority of those that were surveyed are women, something important to keep in mind while we are analyzing the data set

Here we can see that a majority of the individuals that took the survey are from the South Atlantic and Pacific parts of the United States

Lastly, we look at the different ages of all our participants

Who checks the weather?

The most important piece of data from “weather-check.csv” came from the “Do you typically check a daily weather report?” column. From this column, we learn about all the people in the United States that check a weather report of some kind before they leave their house in the morning. It is so important to know this data because once we know who actually checks a weather report, then we can examine how various types of individuals check a weather report in the morning.

In order to properly examine the data set, I looked at all the data points and I asked myself “who checks a weather report?”. After hours of digging and sorting through the data, I found the data that I wanted to analyze. In the charts below, I determined who checks a daily weather report based on age, sex, US region, and annual income. It is very crucial to understand this data so we can make conclusions that correspond and create connections with actual people.

As you can see, it is much more common for women to check the weather as opposed to men

As you can see above, people between the age of 45–59 are most likely to check the weather. 18–29 years olds are the group that is least likely to check for the weather.

This infographic may be the most important in this entire post, here we are looking at the correlation between checking the weather and the geographical region in which the participant lives.

How do you check for the weather?

Lastly, I wanted to analyze HOW people check the weather report. Obviously, there are many ways a person can hear about a weather forecast. These methods can be different for all people. I was forced to go into “weather-check.csv” and examine all the different ways that different types of people hear about the weather forecast. By learning more about this data, we will learn more about ourselves and the most common way people check the weather report. And therefore, as information scientists, we could help do design/research work for weather applications using this data.

After sorting through the data from the CSV file, I was able to create the visualizations below. The charts demonstrate how/how likely individuals are to check a weather report. From this data, I learned that people are most likely to check weather on a smart device (i.e. smartphone, tablet, etc.), many people still learn about weather from the local news, and how the US region you live in determines if you check a weather report or not.

People are MOST LIKELY to check the weather report on their smart devices (i.e. phone, tablet, etc.)

Even though a majority of people check the weather on their smart device, people are still reluctant to try this with a “smart watch” (keep in mind this data is from a couple years back, AKA before smart watches became big).

This graph shows how our participants generally check the weather, a majority of our older participants said they receive their weather data through local TV News or the newspaper. While a majority of younger participants receive this data through applications on their phone.

Conclusions

There is so much that we can learn from the data provided above. First we learn how gender plays a role in checking a weather report. Females seemed to be more likely to check the weather than males. I learned that people that live in the Pacific region of the United States are most likely to check a weather report. Age also plays a huge role in this. Older people (those above 40) are much more likely to check a weather forecast than those younger than them, but they generally steer away from checking the weather on their phone or smart device. After that, I learned that people are more likely to check the weather report based on where they live. For example, people that lived in the Pacific region are much more likely to check a weather report as opposed to those who live in the Southern region of the United States. All of these factors that I have referenced above are all certainly factors that influence users to check the daily weather prediction.

Throughout the analyzation of this data set, we also learned a lot about how most people check the daily weather report. I was determined that most people check the weather forecast via their smartphone and the Local TV News. But after looking at this study, the numbers are more evenly distributed than I had originally thought. There is really so much we can learn from this data. This data could be extremely important for application developers because they will know who their target audience is, (ie young people, females, pacific part of the US) and they can create advertising/specific application uses that would benefit their largest audiences. Obviously, there is bad data in every data set and that was acknowledged by me while I was creating these graphs. I did this in order to make the graphs as accurate as possible. Data like this is great and can tell us so much about our everyday lives!