I wanted to connect my interests with photography & data by using a photography dataset to create a data visualization through Tableau.
The dataset I used was from Kaggle (cannot find the link), and was focused on Photographer's years of experience and pricing. It has the following info:
State - Where they are located
Specialties - What type(s) of photography they focus on
Experience - Years of experience
Price - How much they price their photoshoots
Step 1: Propose the Business Question
Ensures we manipulate the data for the right reasons, and not just because. In this dashboard, I chose to answer questions that are related to both customers and photographers.
As a customer, what is the best state to go to for affordable pricing, but high level of experience (9+ Years Experience)?
As a customer, where should I search for Wedding Photographers?
As a photographer, should I expect to raise price level related to years of experience (more experience = higher pricing)?
As a photographer, would it be more beneficial to have multiple specialities (i.e. weddings, graduations, portraits, etc.) or focus on a single specialty to have higher pricing?
As a photographer in Pennsylvania, what is the current scope like? Are most photographers highly experienced? Do they charge high or low? What are their main specialties?
Step 2: Prepare & Clean the Data
When looking into the data, we see that the data is a bit messy. For example, in the image below we can see that for photographers that have 9+ years of experience are listed as "1+ years 4+ years 9+ years in business." Photographers with 4-9 years experience are listed as "1+ years 4+ years in business," and so on.
To clean this, I did an IF CONTAINS statement in Tableau, using a calculated field.
With the written statement above, we now have more a clean and concise experience dimension.
Other areas where the data can be cleaned is in the Price column. All price levels start with "Investment: [Price Level]," and can be cleaned to just display the price level.
Like earlier, this also was cleaned with an IF CONTAINS statement in Tableau using a calculated field.
Lastly, I wanted to create another dimension that would capture whether a photographer specialized in a single field, or in multiple fields. Looking at the dataset, photographers who have more than one specialty separates them using a comma.
In the IF CONTAINS statement above, this will capture whether a photographer has a comma in their specialty section, and will categorize them as a photographer with "Multiple Specialties." Those without a comma have been labeled as "Single Specialty."
The dataset should now be clean and categorized enough to build insights for the business questions mentioned above.
Step 3: Creating Worksheets & the Dashboard
Creating clear visualizations that tell a story using the dataset to inform customers and photographers.
For the first question, "As a customer, what is the best state to go to for affordable pricing, but high level of experience (9+ Years Experience)?," I created a 100% stacked bar chart that shows the % of photographers who charge different price levels.
In the image above, you can see that Nebraska has 85% of photographers offering Moderate pricing, 10% Average pricing, and 4% Premium pricing. To answer the business question, we can use the filters to display top states with Moderate pricing and photographers with 9+ years of experience.
After adding in those filters, we can see that Nebraska offers the most amount (15 photographers) who have 9+ years of experience and offer Moderate pricing.
For the next business question, "As a customer, where should I search for Wedding Photographers?," I created a simple chart displaying top states by photographer count that specialize in X specialty. This is filtered by a wildcard filter, and will grab all photographers (whether they specialize singularly in or in tangent with other specialties) as long as their specialty contains "wedding".
Nebraska also has the most photographers with a specialty in weddings.
Moving on to our photographer-focused questions, "As a photographer, should I expect to raise price level related to years of experience (more experience = higher pricing)?," I created another 100% stacked bar chart that breaks out count of photographers by price level and experience level.
With the above image, we can see that Moderate pricing decreases as years of experience increases. We also see that Average, Premium, and Luxury pricing increases with years of experience. We can conclude that it is acceptable for photographers to increase pricing as their years of experience grow.
Fourth question: "As a photographer, would it be more beneficial to have multiple specialities (i.e. weddings, graduations, portraits, etc.) or focus on a single specialty to have higher pricing?," I created a chart displaying % of photographers by price level and whether they have a single specialty or multiple.
If you want to prioritize increasing pricing, it is better to have a single specialty than having multiple. We can also see that the pricing increases as years of experience increase too.
Lastly, since I am a photographer based in Pennsylvania, I wanted to answer "What is the current scope like? Are most photographers highly experienced? Do they charge high or low? What are their main specialties?" By creating a couple of charts and utilizing the wildcard filter for state, we have the following:
We can see that most photographers in PA do not specialize in only one type of photography, that they primarily have 9+ years of experience, and that they charge a Moderate & Average price level. Definitely not in the ranks of 9+ years of experience in photography, but I will get there soon!
Hope you enjoyed this analysis on photographers! Leave a comment if you have any suggestions on improving or other questions I could try to answer with this dataset.
