Ytukyg

This is my first post. I want to loop or iterate in a directory to import each of the files as a separate DataFrame with a name similar (at least with the numeration) to the name of its file.
After a lot of research I still do not know how to do it. Obviously I am a very beginner :-)

My code is:

Main_folder =  os.getcwd()

Folders = os.listdir('.')



for file in Folders:

    data= pd.read_csv(file, sep="t", header=0)

    data.columns=data.columns.str.strip()

where for instance Folders is a list of files names including the file extension. e.g.:

Folders=['01_load.TXT', '02_load.TXT', '03_load.TXT']

What I need is just to import all files to my work space such:

Load_01=pd.read_csv('01_load.TXT', sep="t", header=0)

Load_02=pd.read_csv('02_load.TXT', sep="t", header=0)

but in a loop since I have many files.

When create objects in a loop you can't give them explicit names. But, you can add them to a data structure that associates them with a relevant name. I would recommend a dictionary here. So, for example, you can do this:

Folders=['01_load.TXT', '02_load.TXT', '03_load.TXT'] # These should be called filenames not folders but anyway.



data_frames = {}    # Initialise a dictionary



for filename in Folders:

    df = pd.read_csv(filename, sep='t', header=False)

    data_frames[filename] = df



# Now you can access any of the dataframes by the filename by using the dictionary:

# Let's say you want the df associated with 02_load.TXT



df = data_frames['02_load.TXT']

print(df.head())

You can use a dictionary:

data = {}

for file in os.listdir('.'):

    data[file] = pd.read_csv(file, sep="t", header=0)

    data[file].columns = data[file].columns.str.strip()

Then you access each dataframe as a key of the dictionary, for example: data['01_load.TXT']

It is possible to set variable variable names and access them, but it's not adviced or a good practice.