Last week I wrote a blog on completing the Preppin' Data 2021 WK01 challenge in SQL. This week I challenged myself to complete it in Python. I am uploading my solutions for each Preppin' Data challenge on Git Hub. Feel free to check it out here: https://github.com/Dan-Booth-Data/PreppinData/tree/main
Similarly to last week I am starting with this dataset:
I loaded in the data using the read_csv() function from the Pandas library.
Task 1:
To do this I used the str.split() function and split at any '-' with a trailing and leading space.
Task 2:
I decided the easiest way to achieve this was to correct the names based on their first value. To do this I made a dictionary which I could run across the first letter of each value.
Task 3:
To complete this task, I firstly needed to convert the date column to a date datatype. I could then use the built in functions from the dt library to extract the quarter and day of month.
Task 4:
To achieve this I filtered out the first 10 Order ID's.
Final Output:
Lastly I removed any columns that were no longer needed.
