Import rows from Excel file in to Python as a list for each row

Question

My excel file looks like this:

             X_0          X_1  y
0    2917.211242  3289.522533  0
1    1888.937716   781.528356  0
2    4188.521414  1554.476261  0
3    8145.555339  9804.066728  0
4    9584.488981  6176.337189  0

I'm trying to read the data to look like this (ie each row in a list within a big list, don't mind the actual entries in the example):

[[3.393533211,2.331273381,0],
    [3.110073483,1.781539638,0],
    [1.343808831,3.368360954,0],
    [3.582294042,4.67917911,0],
    [2.280362439,2.866990263,0],
    [7.423436942,4.696522875,1],
    [5.745051997,3.533989803,1],
    [9.172168622,2.511101045,1],
    [7.792783481,3.424088941,1],
    [7.939820817,0.791637231,1]]

What I've tried so far is this:

import pandas as pd

df = pd.read_excel("nameOfMyDatabase.xlsx")
list1 = list(df['X_0'])
list2 = list(df['X_1'])
list3 = list(df['y'])

print(list1)
print(list2)
print(list3)

And this is the result I'm getting:

[2917.2112422149, 1888.93771568063, 4188.52141357231, 8145.55533888016, 9584.48898099062, 4039.63375666484, ....]

[3289.52253268053, 781.528355771809, 1554.47626074928, 9804.06672844197, 6176.33718886522, 167.607142550757, ....]

[0, 0, 0, 0, 0, 0, ....]

So not quite what i want yet but trial and error is not working for me. Any ideas?

Answer 1

If you just want to parse data from Excel and don't care about using the pandas DataFrame itself, you should be using openpyxl .

For example, for a spreadsheet like this:

and assuming that your desired spreadsheet is the first/only sheet in the workbook, you could do:

import openpyxl

wb = openpyxl.load_workbook("nameOfMyDatabase.xlsx")
ws = wb.active
cell_range = 'A2:C5'
data = [[cell.value for cell in row] for row in ws[cell_range]]
print(data)
# output: [[1, 5, 9], [2, 6, 10], [3, 7, 11], [4, 8, 12]]

Answer 2

You could try using

big_list = []
for a, b in zip(df["x_0"], df["x_0"]):
   list = []
   list.append(a)
   list.append(b)
   big_list = big_list.append(list)

Answer 3

You can try:

import pandas as pd

df = pd.read_excel("nameOfMyDatabase.xlsx")

data = df.values.tolist()

Answer 4

This is my suggestion using numpy and openpyxl:

import openpyxl
import numpy as np

wb = openpyxl.load_workbook('test.xlsx')
ws = wb['Sheet1']

lst = []
for v in ws.values:
    lst.append(v)
print(lst)

values =  = np.array(lst)