Reputation: 101
If I have an excel file that has no row/column labels that looks like this:
and I have a dictionary that looks like this:
dict = {a:1, b:2, c:3}
How can I combine them into a dictionary that combines the values and that looks like this:
dict_result = {a:2, b:3, c:4}
Upvotes: 2
Views: 709
Reputation: 1369
This solution works for csv file having columns A and B
import pandas as pd
actual_dict = {'a': 1, 'b': 1, 'c': 1}
cs = pd.read_csv(r'.\dict.csv')
keys = cs.A.tolist()
vals = cs.B.tolist()
csv_dict = {k:v for k,v in zip(keys,vals)}
for k in actual_dict.keys():
actual_dict[k] += csv_dict[k] #updating the actual dict
Upvotes: 0
Reputation: 26315
Solution 1
If your excel file is in .xlsx format, you can use openpyxl
:
import openpyxl
letter_map = {'a':1, 'b':2, 'c':3}
# open workbook
workbook = openpyxl.load_workbook('book1.xlsx')
# get worksheet by index
worksheet = workbook.worksheets[0]
result = {}
# loop over column pairs
for k, v in zip(worksheet['A'], worksheet['B']):
# assign new values to keys
result[k.internal_value] = v.internal_value + letter_map[k.internal_value]
print(result)
Output
{'a': 2, 'b': 3, 'c': 4}
Solution 2
If you have your excel file in .xls format, you can use xlrd
:
import xlrd
letter_map = {'a':1, 'b':2, 'c':3}
# open work book
workbook = xlrd.open_workbook('book1.xls', on_demand=True)
# get sheet by index
worksheet = workbook.sheet_by_index(0)
result = {}
# loop over row indices
for row in range(worksheet.nrows):
# assign new values to keys
k, v = worksheet.cell(row, 0).value, worksheet.cell(row, 1).value
result[k] = int(v) + letter_map[k]
print(result)
Output
{'a': 2, 'b': 3, 'c': 4}
Upvotes: 2