CODEWITHSUNDEEP
pythonpandasdataframeimport
Maks
Maks

Reputation: 55

Importing all .csv files within a specified directory into separate arrays

I am trying to import all .csv files within a directory. I would like to store them in array for each file (for example named as file_name). I tried following code as suggested in thread import all csv files in directory as pandas dfs and name them as csv filenames:

import pandas as pd
import glob
import os

path = "E:\\9sem\\INO\\Dane\\input\\"
all_files = glob.glob(os.path.join(path, "*.csv")) #make list of paths

for file in all_files:
    # Getting the file name without extension
    file_name = os.path.splitext(os.path.basename(file))[0]
    # Reading the file content to create a DataFrame
    dfn = pd.read_csv(file)
    # Setting the file name (without extension) as the index name
    dfn.index.name = file_name

And I am stuck. I imported the data into single DataFrame but I dont know how to convert it do separate numpy arrays.

Thank you for any suggestions.

Best regards, Maks

Upvotes: 0

Views: 613

Answers (1)

jottbe
jottbe

Reputation: 4521

Your code would always overwrite the dataframe by the data of the next csv, right?

So either you could use pandas.concat to make one big dataframe, or you could store the data in a dictionary. If you want to store it in a dictionary, you could change your code like this:

df_dict= dict()
for file in all_files:
    # Getting the file name without extension
    file_name = os.path.splitext(os.path.basename(file))[0]
    # Reading the file content to create a DataFrame
    df_dict[file_name]= pd.read_csv(file)
    # Setting the file name (without extension) as the index name
    df_dict[file_name].index.name = file_name

Then you can get the dataframe by df_dict[base_name]. Where base_name is the name of the source file of the dataframe.

Upvotes: 1

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