I am completely new to openpyxl
so, as you can imagine, I am having pretty hard times when I try to make use of it.
I have an Excel report that contains only one sheet (called Sheet1)
. I'd like to search all cells for those that contain specific string (product name ABC in this case).
Then I would like to copy contents of every cell in the rows that contain cell with ABC
product name. And assign every cell to a variable.
To give you better idea of what I am trying to achieve I'll give you an example:
So in this case I would only copy cells from rows: 2, 4, 6 (as only they contain ABC
product).
I have already looked up similar questions and answers to them but I don't understand them (never have used Excel before).
There's no need to use the pandas for this.
from openpyxl import Workbook
import openpyxl
file = "enter_path_to_file_here"
wb = openpyxl.load_workbook(file, read_only=True)
ws = wb.active
for row in ws.iter_rows("E"):
for cell in row:
if cell.value == "ABC":
print(ws.cell(row=cell.row, column=2).value) #change column number for any cell value you want
is it important for you to use openpyxl to do this? i would suggest using pandas if not.
import pandas as pd
df = pd.read_excel("path_to_excel_file")
df_abc = df[df["Products"] == "ABC"] # this will only contain 2,4,6 rows
then:
for row in df_abc.iterrows():
# do what you want with the row
from openpyxl import load_workbook
wb = load_workbook("report.xlsx")
ws = wb.active
for row in ws.rows:
if row[4].value == "ABC":
for cell in row:
print(cell.value, end=" ")
print()
wb = load_workbook("report.xlsx")
ws = wb.active
abc_rows=[]
for row in range(2,ws.max_row+1):
if(ws[row][4]=='ABC'):
abc_rows.append(row)
To access the selected rows separately, further add this code
i=1
abc_dict={}
for row in ws.values:
if(i in abc_rows):
(a,b,c,d,e,f,g,h,i,j,k,l)=row
abc_dict[i]=row
i=i+1
To access selected rows seperately, use
abc_dict[2] gives entire second row as tuples and abc_dict[2][0] gives first cell value. you can parse till abc_dict[2][11] to get each cell of selected rows seperately.
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