I have a list of file paths that I want to convert into data frames.
Here is what the files look like
To better help organize it I would like to have a dict where the key is the dates, and the values are a dict where their keys are the names and they have a dict where keys are results, sales, team, and the values are a dataframe of the file.
I hope I explained it well.
2022-03-23_John_result_data.csv
2022-03-23_John_sales_data.csv
2022-03-23_John_team_data.csv
2022-03-23_Lisa_result_data.csv
2022-03-23_Lisa_sales_data.csv
2022-03-23_Lisa_team_data.csv
2022-03-23_Troy_result_data.csv
2022-03-23_Troy_sales_data.csv
2022-03-23_Troy_team_data.csv
2022-03-25_Bart_result_data.csv
2022-03-25_Bart_sales_data.csv
2022-03-25_Bart_team_data.csv
EDIT
Sorry for the edit but assume the file name could be '2022-03-23_John love [23]_result_data.csv'] forgot to add this case where they could have a space between the names.
CodePudding user response:
You could probably iterate over the file names and do multiple dict.setdefault
s (or use a defaultdict), eg:
filenames = ['2022-03-23_John_result_data.csv']
dfs = {}
for filename in filenames:
date, name, category, _ = filename.split('_', 3)
dfs.setdefault(date, {}).setdefault(name, {})[category] = pd.read_csv(filename)
Or using a defaultdict
...
from collections import defaultdict
dfs = defaultdict(dict)
Then your dfs.setdefault(...)
line becomes:
dfs[date][name][category] = pd.read_csv(filename)