Scale up Python Function Application to Create Similar Audience List using Pandas DataFrame Apply

We might have millions of data instances in a DataFrame, and one of those features might need functions to further generate a dataset with specific purposes using functions. The question is how to scale up the process instead of implementing one after one. In this article, I would walk through briefly to leverage pandas dataframe apply() to scale up the function application.

Table of Contents: Scale up Python Function Application to Create Similar Audience List using Pandas DataFrame Apply

• Email List and DataFrame
• Embeddings Function
• Data Series
• Apply()
• Full Python Script of Scale up Python Function Application to Create Similar Audience List using Pandas DataFrame Apply

Email List and DataFrame

We take email lists and embedding creation for instance. As you can see, we assume we have 144332 customer email contacts for this case, which is quite impossible to run a function one by one. Thus, apply() methods is super helpful for us to resolve this problem.

For data protection, we can’t show the customer data here, but please include other data features as well, such as name, phone number, address, transaction history etc. It’s better to create more concise embeddings.

In our case, we manage the data using Non-sql database, so we need to convert the JSON list into a DataFrame using Pandas 

df = pd.DataFrame(customerList)

Embeddings Function

For embeddings function, we would elaborate more details using Python libraries to create embeddings. Being said that, many AI platforms nowadays provide embedding API, such as OpenAI, Google Vertex, and so on. Please feel free to select and use your preference. Just keep in mind that to test the embedding performance, please use one to provide a solution for the whole dataset, instead of mixing different models for one dataset.

Data Series

Subsequently, we need to select a data series that is ready to run embedding function. In Pandas, A series basically means a column. Here is a sample code as follows to fetch a series. 

df['Customer Emails']

Apply()

Eventually things are ready and we can run the functions for the whole series of data to generate the embeddings.

Here is the sample code:

df['CustomerEmbeddings'] = df['Customer Emails'].apply(functionA)

Full Python Script of Scale up Python Function Application to Create Similar Audience List using Pandas DataFrame Apply

If you are interested in Scale up Python Function Application to Create Similar Audience List using Pandas DataFrame Apply, please subscribe to our newsletter by adding the message ‘Apply method + Full scripts. We would send you the script when the up-to-date app script is live.

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