Python Pandas dataframe reading exact specified range in an excel sheet

Question

I have a lot of different table (and other unstructured data in an excel sheet) .. I need to create a dataframe out of range \'A3:D20\' from \'Sheet2\' of Excel sheet \'data

Answer 1

my answer with pandas O.25 tested and worked well

pd.read_excel('resultat-elections-2012.xls', sheet_name = 'France entière T1T2', skiprows = 2,  nrows= 5, usecols = 'A:H')
pd.read_excel('resultat-elections-2012.xls', index_col = None, skiprows= 2, nrows= 5, sheet_name='France entière T1T2', usecols=range(0,8))

So : i need data after two first lines ; selected desired lines (5) and col A to H.
Be carefull @shane answer's need to be improved and updated with the new parameters of Pandas

Answer 2

One way to do this is to use the openpyxl module.

Here's an example:

from openpyxl import load_workbook

wb = load_workbook(filename='data.xlsx', 
                   read_only=True)

ws = wb['Sheet2']

# Read the cell values into a list of lists
data_rows = []
for row in ws['A3':'D20']:
    data_cols = []
    for cell in row:
        data_cols.append(cell.value)
    data_rows.append(data_cols)

# Transform into dataframe
import pandas as pd
df = pd.DataFrame(data_rows)

Answer 3

Use the following arguments from pandas read_excel documentation:

• skiprows : list-like
  • Rows to skip at the beginning (0-indexed)
• parse_cols : int or list, default None
  • If None then parse all columns,
  • If int then indicates last column to be parsed
  • If list of ints then indicates list of column numbers to be parsed
  • If string then indicates comma separated list of column names and column ranges (e.g. “A:E” or “A,C,E:F”)

I imagine the call will look like:

df = read_excel(filename, 'Sheet2', skiprows = 2, parse_cols = 'A:D')