How to name multiple dataframes automatically in Python?

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I need help automating a dataframe naming process that I’m applying. I imported 3 csv files and applied the code below, which worked smoothly:

Loja_1, Loja_2, Loja_3 = (pd.read_csv(cont) for cont in base)

I can operate the different df (Loja_1, Loja_2 and Loja_3) perfectly, that is the part of the code (pd.read_csv(cont) for cont in files) is working. However, I wish to automate the generation of the names Loja_1 to Loja_n. As it is, I have to name them manually, but the amount of df can very large, so I wish to do it automatically.

Can someone help me with this part of the code?

Grateful

python pandas

  • Why don’t you use a dictionary? {Loja_1: df1, Loja_2: df2, ...}? basically would be anything like {'Loja_{}'.format(n): pd.read_csv(cont) for n, cont in enumerate(base, 1)

  • I ran the code - new={'Loja_{}'. format(n): pd.read_csv(cont) for n, cont in enumerate(base, 1)}. When I gave the type(new) command, it returned Dict (beauty). But when executing the command pd.DataFrame.from_dict(new), it returns: Valueerror: If using all scalar values, you must pass an index.

  • Why do you want to do that? You already have DF’s in DC, and to access each one of them is enough novo['Loja_1'] or novo['Loja_2'] or novo['Loja_3'] etc....

  • I needed to generate a dataframe where the name of the stores appeared in a column. So I could work with groupby. I solved the problem by reading with Glob and then running within a for read + append within a list. At the end, I made a Concat. files = Sorted(glob('Arquivos_client/*. csv')) df_intermediario = [] for file in files: df = pd.read_csv(file) df_intermediario.append(df) df_base = pd.Concat(df_intermediario, ignore_index=True)

1 answer

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for i in range(1, n): #sendo n o número de lojas+1
     loja ='Loja_'+str(i)
     print(loja)

I put it as print for you to test, but it’s this string + counter format that can do this task for you :)

  • Until this setting, I get enough. My problem is to link the variables generated with the respective dataframe

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