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Format and manipulate data across multiple Excel sheets in Python using openpyxl before converting to Dataframe

I need some help with editing the sheets within my Excel workbook in python, before I stack the data using pd.concat(). Each sheet (~100) within my Excel workbook is structured identically, with the unique identifier for each sheet being a 6-digit code that is found in line 1 of the worksheet.
I've already done the following steps to import the file, unmerge rows 1-4, and insert a new column 'C':
import openpyxl
import pandas as pd
wb = openpyxl.load_workbook('data_sheets.xlsx')
for sheet in wb.worksheets:
sheet.merged_cells
for merge in list(sheet.merged_cells):
sheet.unmerge_cells(range_string=str(merge))
sheet.insert_cols(3, 1)
print(sheet)
wb.save('workbook_test.xlsx')
#concat once worksheets have been edited
df= pd.concat(pd.read_excel('workbook_test.xlsx, sheet_name= None), ignore_index= True)
Before stacking the data however, I would like to make the following additonal (sequential) changes to every sheet:
Extract from row 1 the right 8 characters (in excel the equivalent of this would be =RIGHT(A1, 8) - this is to pull the unique code off of each sheet, which will look like '(000000)'.
Populate column C from rows 6-282 with the unique code.
Delete rows 1-5
The end result would make each sheet within the workbook look like this:
Is this possible to do with openpyxl, and if so, how? Any direction or assistance with this would be much appreciated - thank you!

Here is a 100% openpyxl approach to achieve what you're looking for :
from openpyxl import load_workbook
wb = load_workbook("workbook_test.xlsx")
for ws in wb:
ws.unmerge_cells("A1:O1") #unmerge first row till O
ws_uid = ws.cell(row=1, column=1).value[-8:] #get the sheet's UID
for num_row in range(6, 282):
ws.cell(row=num_row, column=3).value = '="{}"'.format(ws_uid) #write UID in Column C
ws.delete_rows(1, 5) #delete first 5 rows
wb.save("workbook_test.xlsx")
NB : This assume there is already an empty column (C).

How to read specif cell with pandas library?

I want to read from excel sheet a specific cell: h6. So I try it like this:
import pandas as pd
excel_file = './docs/fruit.xlsx'
df = pd.read_excel(excel_file,'Overzicht')
sheet = df.active
x1 = sheet['H6'].value
print(x1)
But then I get this error:
File "C:\Python310\lib\site-packages\pandas\core\generic.py", line 5575, in __getattr__
return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'active'
So my questiion is: How to read specif cell from sheet from excelsheet?
Thank you
Oke, I tried with openpyxl:
import openpyxl
path = "./docs/fruit.xlsx"
wb_obj = openpyxl.load_workbook(path)
sheet_obj = wb_obj.active
cell_obj = sheet_obj.cell(row = 6, column = 9)
print(cell_obj.value)
But then the formula is printed. Like this:
=(H6*1000)/F6/G6
and not the value: 93

You can do this using openpyxl directly or pandas (which internally uses openpyxl behind the scene)...
Using Openpyxl
You will need to use data_only=True when you open the file. Also, make sure you know the row and column number. To read the data in H6, row would be 6 and 8 would be H
import openpyxl
path = "./docs/Schoolfruit.xlsx"
wb_obj = openpyxl.load_workbook(path, data_only=True)
sheet_obj = wb_obj.active ## Or use sheet_obj = wb_obj['Sheet1'] if you know sheet name
val = sheet_obj.cell(row = 6, column = 8).value
print(val)
Using Pandas
The other option is to use pandas read_excel() which will read the whole sheet into a dataframe. You can use iloc() or at() to read the specific cell. Note that this is probably the less optimal solution if you need to read just one cell...
Another point to note here is that, once you have read the data into a dataframe, the row 1 will be considered as the header and the first row would now be 0. So the row number would be 4 instead of 6. Similarly, the first column would now be 0 and not 1, which would change the position to [4,7]
import pandas as pd
path = "./docs/Schoolfruit.xlsx"
df = pd.read_excel(path, 'Sheet1')
print(df.iloc[4,7])

I found a solution and hope, it works for you.
import pandas as pd
excel_file = './docs/Schoolfruit.xlsx'
df = pd.read_excel(excel_file, sheet_name='active' ,header=None, skiprows=1)
print(df[7][4])
7: Hth column
4: 6th row (skipped first row and index is began from 0)

How to extract a particular set of values from excel file using a numerical range in python?

What I intend to do :
I have an excel file with Voltage and Current data which I would like to extract from a specific sheet say 'IV_RAW'. The values are only from 4th row and are in columns D and E.
Lets say the values look like this:
V(voltage)
I(Current)
47
1
46
2
45
3
0
4
-0.1
5
-10
5
Now, I just want to take out only the values starting with a voltage (V) of 45 and shouldnt take negative voltages. The corresponding current (I) values are also needed to be taken out. This has to be done for multiple excel files. So starting from a particular row number cannot be done instead voltage values should be the criterion.
What I know:
I know only how to take out the entire set of values using openxyl:
loc = ("path")
wb = load_workbook("Data") #thefilename
ws = wb["IV_raw"] #theactiveworksheet
#to extract the voltage and current data:
for row in ws.iter_rows(min_row=1, max_col=3, max_row=2, values_only=True):
print(row)
I am a noon coder and new to python. So it will be really helpful if you guys could help. If there is a simplified versions with pandas it will be really great.
Thank you in advance

The following uses pandas which you should definitly take a look at. with sheet_name you set the sheet_name, header is the row index of the header (starting at 0, so Row 4 -> 3), usecols defines the columns using A1 notation.
The last line filters the dataframe. If I understand correctly, then you want Voltage between 0 and 45, thats what the example does and df is your resulting data_frame
import pandas as pd
file_loc = "path.xlsx"
df = pd.read_excel(file_loc,
sheet_name = 'IV_raw',
header = 3,
usecols = "D:E")
df = df[(df['V(voltage)'] > 0) & (df['V(voltage)'] < 45)]

Building on from your example, you can use the following example to get what you need
from openpyxl import load_workbook
wb = load_workbook(filepath,data_only=True) #load the file using its full path
ws = wb["Sheet1"] #theactiveworksheet
#to extract the voltage and current data:
data = ws.iter_rows(min_col=4, max_col=5, min_row=2, max_row=ws.max_row, values_only=True)
output = [row for row in data if row[0]>45]

you can try this,
import openpyxl
tWorkbook = openpyxl.load_workbook("YOUR_FILEPATH")
tDataBase = tWorkbook.active
voltageVal= "D4"
currentVal= "E4"
V = tDataBase[voltageVal].value
I = tDataBase[currentVal].value

How to iterate over a particular column in excel using pyxl(python)

I am new to python and need you help.I am trying to write code that iterates through a particular column in excel using pyxl
from io import StringIO
import pandas as pd
import pyodbc
from openpyxl import load_workbook
d=pd.read_excel('workbook.xlsx',header=None)
wb = load_workbook('workbook.xlsx')
SO here in the above example I have to go column J and display all the values in the column.
Please help me solve this.
Also,I have the same column name repeated in my excel sheet..For Example "Sample" column name is available in B2 and also in J2..But I want to get all the column information of J2.
Please let me know how to solve this...
Thankyou ..Please reply

Since you're new to python, you should learn to read the documentation. There are tons of modules available and it will be quicker for you and easier for the rest of us if you make the effort first.
import openpyxl
from openpyxl.utils import cell as cellutils
## My example book simply has "=Address(Row(),Column())" in A1:J20
## Because my example uses formulae, I am loading my workbook with
## "data_only = True" in order to get the values; if your cells do not
## contain formulae, you can omit data_only
workbook = openpyxl.load_workbook("workbook.xlsx", data_only = True)
worksheet = workbook.active
## Alterntively: worksheet = workbook["sheetname"]
## A container for gathering the cell values
output = []
## Current Row = 2 assumes that Cell 1 (in this case, J1) contains your column header
## Adjust as necessary
column = cellutils.column_index_from_string("J")
currentrow = 2
## Get the first cell
cell = worksheet.cell(column = column, row = currentrow)
## The purpose of "While cell.value" is that I'm assuming the column
## is complete when the cell does not contain a value
## If you know the exact range you need, you can either use a for-loop,
## or look at openpyxl.utils.cell.rows_from_range
while cell.value:
## Add Cell value to our list of values for this column
output.append(cell.value)
## Move to the next row
currentrow += 1
## Get that cell
cell = worksheet.cell(column = column, row = currentrow)
print(output)
""" output: ['$J$2', '$J$3', '$J$4', '$J$5', '$J$6', '$J$7',
'$J$8', '$J$9', '$J$10', '$J$11', '$J$12', '$J$13', '$J$14',
'$J$15', '$J$16', '$J$17', '$J$18', '$J$19', '$J$20']

Read a specific column of a certain cell range and store the values using Pandas

I am trying to figure out a way to read data from a specific column from a certain cell range and store it into a array using pandas.
For example my Excel sheet consists of :
test | p
Food| Price
Chicken| 8.54
Beef |6.73
Vegetables| 3.2
Total Price |18.47
Note: there is a an empty space on the first row for a reason.
Note: | indicates cell separation.
I am trying to get the price values which start from Row B3 to row B5 and store them into an array via [8.54,6.73,3.2].
So far the code I have is:
import pandas as pd
xl_workbook = pd.ExcelFile("readme.xlsx") # Load the excel workbook
df = xl_workbook.parse("Sheet1") # Parse the sheet into a dataframe
x1_list = df['p'].tolist() # Cast the desired column into a python list
print(x1_list)
Which then results to [nan, u'price',8.54,6.73,3.2]
If I just wanted to read the values 8.54, 6.73, and 3.2, to result in [8.54,6.73,3.2] how would I do this?
Is there a way to grab a certain column of a certain cell range?

As written, you could use read_excel in Pandas. This assumes you have consistent formatting.
import pandas as pd
# define the file name and "sheet name"
fn = 'Book1.xlsx'
sn = 'Sheet1'
data = pd.read_excel(fn, sheetname=sn, index_col=0, skiprows=1, header=0, skip_footer=1)