Method shown by Clinton c. Brownley in Foundations for Analytics with Python:
execute in shell indicating the path to the folder with excel files ( make sure the argument defining all_workbooks is correct) and then followed by the excel output file as follows:
python script.py <the /path/ to/ excel folder/> < your/ final/output.xlsx>
script.py:
import pandas as pd
import sys
import os
import glob
input_path = sys.argv[1]
output_file = sys.argv[2]
all_workbooks = glob.glob(os.path.join(input_file, '*.xlsx'))
all_df = []
for workbook in all_workbooks:
all_worksheets = pd.read_excel(workbook, sheetname='Output', index_col=None)
for worksheet, data in all_worksheets.items:
all_df.append(data)
data_concatenated = pd.concat(all_df, axis=0, ignore_index=True)
writer = pd.ExcelWriter(output_file)
data_concatenated.to_excel(writer, sheetname='concatenated_Output', index=False)
writer.save()
pd.concat(pd.read_excel(i, sheet_name='output') for i in os.listdir(".") if i.endswith('xlsx'))
– Anton vBR