This is an example, which bring the value of a cell (in your case it's an int), you need to convert it to a string using the str function
from openpyxl
import load_workbook
wb = load_workbook(filename = 'xls.xlsx', read_only = True)
ws = wb['Sheet1']
for row in ws.rows:
for cell in row:
cell_str = str(cell.value)The following table describes the types of cells and how their values are represented in Python.,Used in evaluating formulas. The following table describes the kinds and how their values are represented.,Description. This is displayed in the cell, and should be identical to the cell value. Unicode string, or None. It seems impossible NOT to have a description created by the Excel UI.,The default of False means all rows are padded out with empty cells so that all rows have the same size as found in ncols.
0 = ANSI Latin
1 = System
default
2 = Symbol,
77 = Apple Roman,
128 = ANSI Japanese Shift - JIS,
129 = ANSI Korean(Hangul),
130 = ANSI Korean(Johab),
134 = ANSI Chinese Simplified GBK,
136 = ANSI Chinese Traditional BIG5,
161 = ANSI Greek,
162 = ANSI Turkish,
163 = ANSI Vietnamese,
177 = ANSI Hebrew,
178 = ANSI Arabic,
186 = ANSI Baltic,
204 = ANSI Cyrillic,
222 = ANSI Thai,
238 = ANSI Latin II(Central European),
255 = OEM Latin I0 = None(unknown or don 't care)
1 = Roman(variable width, serifed) 2 = Swiss(variable width, sans - serifed) 3 = Modern(fixed width, serifed or sans - serifed) 4 = Script(cursive) 5 = Decorative(specialised,
for example Old English, Fraktur)0 = None 1 = Single; 0x21(33) = Single accounting 2 = Double; 0x22(34) = Double accounting
FUN = 0 # unknown FDT = 1 # date FNU = 2 # number FGE = 3 # general FTX = 4 # text
0 = No line, 1 = Thin, 2 = Medium, 3 = Dashed, 4 = Dotted, 5 = Thick, 6 = Double, 7 = Hair, 8 = Medium dashed, 9 = Thin dash - dotted, 10 = Medium dash - dotted, 11 = Thin dash - dot - dotted, 12 = Medium dash - dot - dotted, 13 = Slanted medium dash - dotted.
(shtxlo, shtxhi, rowxlo, rowxhi, colxlo, colxhi)
Thousands separator for parsing string columns to numeric. Note that this parameter is only necessary for columns stored as TEXT in Excel, any numeric columns will automatically be parsed, regardless of display format.,Read an Excel file into a pandas DataFrame.,Character to recognize as decimal point for parsing string columns to numeric. Note that this parameter is only necessary for columns stored as TEXT in Excel, any numeric columns will automatically be parsed, regardless of display format.(e.g. use ‘,’ for European data).,DataFrame from the passed in Excel file. See notes in sheet_name argument for more information on when a dict of DataFrames is returned.
>>> pd.read_excel('tmp.xlsx', index_col = 0)
Name Value
0 string1 1
1 string2 2
2 #Comment 3>>> pd.read_excel(open('tmp.xlsx', 'rb'),
...sheet_name = 'Sheet3')
Unnamed: 0 Name Value
0 0 string1 1
1 1 string2 2
2 2 #Comment 3>>> pd.read_excel('tmp.xlsx', index_col = None, header = None)
0 1 2
0 NaN Name Value
1 0.0 string1 1
2 1.0 string2 2
3 2.0 #Comment 3>>> pd.read_excel('tmp.xlsx', index_col = 0,
...dtype = {
'Name': str,
'Value': float
})
Name Value
0 string1 1.0
1 string2 2.0
2 #Comment 3.0>>> pd.read_excel('tmp.xlsx', index_col = 0,
...na_values = ['string1', 'string2'])
Name Value
0 NaN 1
1 NaN 2
2 #Comment 3>>> pd.read_excel('tmp.xlsx', index_col = 0, comment = '#')
Name Value
0 string1 1.0
1 string2 2.0
2 None NaNLast Updated : 14 Sep, 2021,GATE CS 2021 Syllabus
Output:
2020-01-01
<class 'str'>EDIT: To further answer your question, there could als be a type difference (int vs. str, for example).,You are using backslashes in string constants. Backslashes are escapes for special characters in python string constants, so you have to double them. Or you can usually get away forward slashes, even on Windows.,Also, be sure that the value of the tag you’re reading is also a string, or converted to one at some point. The data types will need to match when you compare them.,There could also be some extra whitespace. Using repr() can help find those.
I have excel table FEB2021 with two columns: Lot and Product Name.
I would like if the Lot is known (Tag " LOT"), automatically to draw the program name.
My code is:
pr = system.tag.readBlocking(["[default]GZPT_Room1/LOT"])[0].value
path = "C:\Applications\FEB2021.xlsx"
inputWorkbook = xlrd.open_workbook(path)
inputWorksheet = inputWorkbook.sheet_by_index(0)
for row in range(sheet.nrows):
if sheet.cell(row, 0) == pr:
prodVal1 = sheet.cell(row, 1)
system.tag.writeBlocking(["[default]GZPT_Room1/Name1"], [prodVal1])``
`
Though no error message pop up, the script does not work. Any idea why?There could also be some extra whitespace. Using repr() can help find those.
print repr(sheet.cell(row, 0))
If sheet.cell_value is used, I get properly the LOT numbers.
from xlrd
import open_workbook, cellname
pr = system.tag.readBlocking(["[default]GZPT_Room1/LOT"])[0].value
path = "C:\Applications\FEB2021.xlsx"
inputWorkbook = xlrd.open_workbook(path)
inputWorksheet = inputWorkbook.sheet_by_index(0)
sheet = inputWorkbook.sheet_by_index(0)
for row in range(1, sheet.nrows):
slicedVal = (sheet.cell_value(row, 0))
if slicedVal == pr:
prodVal1 = sheet.cell(row, 1)
system.tag.writeBlocking(["[default]GZPT_Room1/Name1"], [prodVal1])``
`
The problem is how to compare slicedVal, type "unicode", and pr, type "long".
Conversion with ord or str(integer).decode("utf-8") did not help. Any hints?Casting pr to unicode would only have to happen once.
pr = unicode(system.tag.readBlocking(["[default]GZPT_Room1/LOT"])[0].value)Casting slicedVal to long would need to happen on every iteration of the loop.
slicedVal = long(sheet.cell_value(row, 0))
Fixed.
The correct code is:
from xlrd
import open_workbook, cellname
pr = system.tag.readBlocking(["[default]GZPT_Room1/LOT"])[0].value
path = "C:\Applications\FEB2021_2.xlsx"
inputWorkbook = xlrd.open_workbook(path)
inputWorksheet = inputWorkbook.sheet_by_index(0)
sheet = inputWorkbook.sheet_by_index(0)
for row in range(1, sheet.nrows):
slicedVal = long(sheet.cell_value(row, 0))
if slicedVal == pr:
prodVal1 = sheet.cell_value(row, 1)
print pr, prodVal1
system.tag.writeBlocking(["[default]GZPT_Room1/Name1"], [prodVal1])``
`
Thank you, Jordan!The file I created in above step is sample.xls and I put it in the same folder. The below code will print the total number of rows and total number of columns:,We opened the excel sheet using the file location and put that value in work_book,Here, we are calculating the total number of rows and columns and using two for loops, we are printing the values in the excel sheet. It will print the below output:,nrows and ncols properties are used to get the number of rows and columns.
pip install xlrd
import xlrd
file_location = 'sample.xls'
work_book = xlrd.open_workbook(file_location)
sheet = work_book.sheet_by_index(0)
print('No or rows : {}, columns : {}'.format(sheet.nrows, sheet.ncols))No or rows: 5, columns: 3
import xlrd
file_location = 'sample.xls'
work_book = xlrd.open_workbook(file_location)
sheet = work_book.sheet_by_index(0)
total_rows = sheet.nrows
total_columns = sheet.ncols
for i in range(total_rows):
for j in range(total_columns):
print(sheet.cell_value(i, j), end = ' ')
print()Name Age Marks
Alex 20.0 40.0
Bob 21.0 50.0
Chandler 20.0 30.0
Daisy 19.0 45.0Reading an excel sheet:- Import xlrd module and open excel file using open_workbook() method., Read the excel data using xlrd module , Read the excel data using xlrd module ,Check number of sheets in the excel
Installation:-
pip install xlrd
Reading an excel sheet:- Import xlrd module and open excel file using open_workbook() method.
import xlrd
book = xlrd.open_workbook('sample.xlsx')Check number of sheets in the excel
print book.nsheets
Get the sheet based on index
sheet = book.sheet_by_index(1)
Read the contents of a cell
cell = sheet.cell(row, col) #where row = row number and col = column number print cell.value #to print the cell contents