I have a load of csv files. I want to create a loop that allows me to do this;
df_20180731 = pd.read_csv('path/cust_20180731.csv')
for each of about 36 files.
My files are df_20160131, df_20160231 ...... df_20181231 etc. Basically dates by the end of the month.
Thanks
# include here all ids
files = ['20160131', '20160231']
_g = globals()
for f in files:
_g['df_{}'.format(f)] = pandas.read_csv('path/cust_{}.csv'.format(f))
print(df_20160131)
You could do something like:
import glob
import pandas as pd
datasets = {}
for file in glob.glob('path/df_*'):
datasets[file] = pd.read_csv(file)
import os
import pandas as pd
# get a list of all the files in the directory
files = os.listdir(<path of the directory containing all the files>)
#iterate over all the files and store it in a dictionary
dataframe = {file: pd.read_csv(file) for file in files}
#if the directory must contain other files,
#you can check the file paths with any logic(extension etc.), in that case
def logic(fname):
return '.csv' in fname
dataframe = {file: pd.read_csv(file) for file in files if logic(file) }
#this will create a dictionary of file : dataframe_objects
I hope it helps
os.listdir(path)to make the list, then iterate over for a list ofDataFrames