├── Python_code
    ├── CombineFiles.py
    ├── Formulas.py
    ├── GetValue.py
    └── Search.py
├── README.md
├── datasets
    ├── SampleData.xlsx
    └── SampleData2.xlsx
└── images
    └── thumbnail.png


/Python_code/CombineFiles.py:
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 1 | #pip3 install pandas
 2 | import pandas as pd
 3 | 
 4 | #specify the files location (or path)
 5 | excel_files = ['files path here']
 6 | 
 7 | #create a blank dataframe
 8 | merge = pd.DataFrame()
 9 | 
10 | #loop through every file in the list
11 | for file in excel_files:
12 |   #read files into a dataframe and skip the first row (header)
13 |   df = pd.read_excel(file, skiprows = 1)
14 |   #append results to merge
15 |   merge = merge.append(df, ignore_index = True)
16 | 
17 | #create final workbook with merged results
18 | merge.to_excel('Merged_Files.xlsx')
19 | 


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/Python_code/Formulas.py:
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 1 | #pip3 install openpyxl
 2 | import openpyxl
 3 | 
 4 | #specify the files location (or path)
 5 | excel_files = ['files path here']
 6 | 
 7 | #loop through the files in the "excel_files" list
 8 | for file in excel_files:
 9 |     wb = openpyxl.load_workbook(file)
10 |     #locate worksheet
11 |     worksheet = wb["SalesOrders"]
12 |     #compute average in G46
13 |     worksheet['G46'] = '=AVERAGE(G3:G45)'
14 |     #save the file
15 |     wb.save(file)
16 | 
17 |     


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/Python_code/GetValue.py:
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 1 | #pip3 install openpyxl
 2 | import openpyxl
 3 | 
 4 | #specify the files location (or path)
 5 | excel_files = ['files path here']
 6 | 
 7 | #create an empty list to append values later on
 8 | values = []
 9 | 
10 | #loop through the files in the "excel_files" list
11 | for file in excel_files:
12 |     workbook = openpyxl.load_workbook(file)
13 |     #specify worksheet to select
14 |     worksheet = workbook['SalesOrders']
15 |     #locate cell and get its value
16 |     cell_value = worksheet['G11'].value
17 |     #append value to "values" list
18 |     values.append(cell_value)
19 | 
20 |     #print totals
21 |     print(cell_value)
22 | 


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/Python_code/Search.py:
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 1 | #pip3 install pandas
 2 | import pandas as pd
 3 | #pip3 install numpy
 4 | import numpy as np
 5 | 
 6 | #specify the files location (or path)
 7 | files = ['files path here']
 8 | 
 9 | #loop through the "files" list
10 | for file in files:
11 |     #read each file in a dataframe
12 |     df = pd.read_excel(file)
13 |     #locate the "Item" column and return the "Rep" where the condition matches "Pencil"
14 |     pencil = df['Rep'].where(df['Item'] == 'Pencil').dropna()
15 |     #print file name
16 |     print(file)
17 |     #print filtered results
18 |     print(pencil)


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/README.md:
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1 | # Automating Excel in Python
2 | This repository contains some code snippets to automate excel in Python
3 | ![image1](images/thumbnail.png)
4 | 


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/datasets/SampleData.xlsx:
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https://raw.githubusercontent.com/DavideMerlin/Excel_Automation/97bf130e18ee874c396a400d71ace0c84230dd36/datasets/SampleData.xlsx


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/datasets/SampleData2.xlsx:
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https://raw.githubusercontent.com/DavideMerlin/Excel_Automation/97bf130e18ee874c396a400d71ace0c84230dd36/datasets/SampleData2.xlsx


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/images/thumbnail.png:
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https://raw.githubusercontent.com/DavideMerlin/Excel_Automation/97bf130e18ee874c396a400d71ace0c84230dd36/images/thumbnail.png


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