在Python中从CSV创建一系列变量？

Question

I am trying to create a series of dictionaries from CSVs that I want to import but I am not sure the best way to do it.

I used RatingFactors = os.listdir(RatingDirectory) and

CSVLocations = [] for factor in RatingFactors: CSVLocations.append(RatingDirectory + factor)

to create a list of CSVs, these CSVs contain what is essentially a dictionary of FactorName | Factor Value, then 1 | 5, 2 | 3.5.

I want to create a dictionary for each CSV, ideally named based on the CSVs name. However I understand that when looping across variables it is considered bad to try and name my variables inside the loop.

I tried creating a generator function using df_from_each_file = (pd.read_csv(CSVs) for CSVs in CSVLocations)

and if I print the generator using for y in df_from_each_file: print(y) it gives me each of the dataframes but I don't know how to separate them out?

What is the Pythonic way to do this?

How the CSVs look post import

0         0  1.1
1         1  0.9
2         2  0.9
3         3  0.9
etc

Edit:

Attempt to rephrase my question.

I have a series of CSVs which look like they are formatted like dictionaries, they have two columns and they represent how one factor relates to another. I would like to make a dictionary for each CSV, named like the CSV so that I can interact with them from Python.

Edit 2:

I believe this question is different than the one referenced as that is creating a single dataframe which contains all of the dictionaries, I want all of the dictionaries to be separate rather than in a single unit. I tried using their answer before asking this and I could not separate them out.

Answer 1

I think need dict comprehension with basename for keys:

import glob, os

files = glob.glob('files/*.csv')
sers={os.path.basename(f).split('.')[0]:pd.read_csv(f,index_col=[0]).squeeze() for f in files}

If want one big Series :

d = pd.concat(sers, ignore_index=False)