Change number format in Excel using names of headers - openpyxl [duplicate] - header

Question

I have an Excel (.xlsx) file that I'm trying to parse, row by row. I have a header (first row) that has a bunch of column titles like School, First Name, Last Name, Email, etc.
When I loop through each row, I want to be able to say something like:
row['School']
and get back the value of the cell in the current row and the column with 'School' as its title.
I've looked through the OpenPyXL docs but can't seem to find anything terribly helpful.
Any suggestions?

Answer 1

I'm not incredibly familiar with OpenPyXL, but as far as I can tell it doesn't have any kind of dict reader/iterator helper. However, it's fairly easy to iterate over the worksheet rows, as well as to create a dict from two lists of values.
def iter_worksheet(worksheet):
# It's necessary to get a reference to the generator, as
# `worksheet.rows` returns a new iterator on each access.
rows = worksheet.rows
# Get the header values as keys and move the iterator to the next item
keys = [c.value for c in next(rows)]
for row in rows:
values = [c.value for c in row]
yield dict(zip(keys, values))

Answer 2

Excel sheets are far more flexible than CSV files so it makes little sense to have something like DictReader.
Just create an auxiliary dictionary from the relevant column titles.
If you have columns like "School", "First Name", "Last Name", "EMail" you can create the dictionary like this.
keys = dict((value, idx) for (idx, value) in enumerate(values))
for row in ws.rows[1:]:
school = row[keys['School'].value

Answer 3

I wrote DictReader based on openpyxl. Save the second listing to file 'excel.py' and use it as csv.DictReader. See usage example in the first listing.
with open('example01.xlsx', 'rb') as source_data:
from excel import DictReader
for row in DictReader(source_data, sheet_index=0):
print(row)
excel.py:
__all__ = ['DictReader']
from openpyxl import load_workbook
from openpyxl.cell import Cell
Cell.__init__.__defaults__ = (None, None, '', None) # Change the default value for the Cell from None to `` the same way as in csv.DictReader
class DictReader(object):
def __init__(self, f, sheet_index,
fieldnames=None, restkey=None, restval=None):
self._fieldnames = fieldnames # list of keys for the dict
self.restkey = restkey # key to catch long rows
self.restval = restval # default value for short rows
self.reader = load_workbook(f, data_only=True).worksheets[sheet_index].iter_rows(values_only=True)
self.line_num = 0
def __iter__(self):
return self
#property
def fieldnames(self):
if self._fieldnames is None:
try:
self._fieldnames = next(self.reader)
self.line_num += 1
except StopIteration:
pass
return self._fieldnames
#fieldnames.setter
def fieldnames(self, value):
self._fieldnames = value
def __next__(self):
if self.line_num == 0:
# Used only for its side effect.
self.fieldnames
row = next(self.reader)
self.line_num += 1
# unlike the basic reader, we prefer not to return blanks,
# because we will typically wind up with a dict full of None
# values
while row == ():
row = next(self.reader)
d = dict(zip(self.fieldnames, row))
lf = len(self.fieldnames)
lr = len(row)
if lf < lr:
d[self.restkey] = row[lf:]
elif lf > lr:
for key in self.fieldnames[lr:]:
d[key] = self.restval
return d

Answer 4

The following seems to work for me.
header = True
headings = []
for row in ws.rows:
if header:
for cell in row:
headings.append(cell.value)
header = False
continue
rowData = dict(zip(headings, row))
wantedValue = rowData['myHeading'].value

Answer 5

I was running into the same issue as described above. Therefore I created a simple extension called openpyxl-dictreader that can be installed through pip. It is very similar to the suggestion made by #viktor earlier in this thread.
The package is largely based on source code of Python's native csv.DictReader class. It allows you to select items based on column names using openpyxl. For example:
import openpyxl_dictreader
reader = openpyxl_dictreader.DictReader("names.xlsx", "Sheet1")
for row in reader:
print(row["First Name"], row["Last Name"])
Putting this here for reference.