I know this is asking a lot, but I have researched quite a few ways on looking up a column or looking up a row using python within an excel document.
However, these solutions require you to import different packages, when I do not have access to them. My primary motive for this is to utilize a pre-made excel doc with shaders listed within the document and extract them based upon a brief search.
So, has anyone successfully used python to read an excel doc and, if so, have you been able to match named rows with named columns?
EDIT: Answer picked because it's the closest solution, though it doesn't necessarily answer my question. It's will, however, still provide a very reasonable solution given the context that the user, and his/her excel document, will utilize the same columns and rows to get a usable database.
TL;DR:
No easy way to compare columns to rows to get a data set without using an external package. It's easier to just extract data as an array and specify which "column" is which.
You can also read CSV documents using the built-in csv module to read CSV files, so don't need to install any external modules.
import csv
with open('names.csv') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
print(row['first_name'], row['last_name'])
If you just grab the whole contents of the reader and stuff them into a list, the lists will contain all the rows and each row will be a dictionary using the headers in the first row. Getting to a particular cell would be something like:
records = []
with open('names.csv') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
records.append(row)
# cel "A4" would be
records[0][3]