Create lists of values reading data from csv pandas-CodePudding

I need your help. I have a .csv "orders.csv" made in this way:

name          | number_of_orders | eurosxp
fried chips        100               2  
fried chicken       25               5
salad one           20               5
salad two           10               5

( and so on)

I'm trying to create a script in python to read this data and to do calculations, so with pandas, I'm trying to create a tab/list of values that I can recall in a framework...so I wrote this that doesn't work. Someone can help?

import numpy as np

import os
import math

import pandas as pd



class MenuNfeedback:

    data = pd.read_csv("orders.csv", header=None)


    def __init__(self) -> None:
        



      def name_dishes(self):
          '''dishes name'''
          for j in range(0, (self.data.iloc[j][0])):
              nameDishes = list(str(j) )
        
          return nameDishes


    def numb_ord(self):
        '''How many times was orderes'''
        orderNumb_list=[]
        orderNumb=self.data.iloc[i][1]
        for i in range(0, len(self.data.iloc[i][1])):
            orderNumb=self.data.iloc[i][1]
            orderNumb_list.append(orderNumb)

        return carbon_list



    def eurosxp(self):
        '''List of prices'''
        prices_f=[]
        for i in range(0, len(self.data.iloc[i][1])):
           prices_f.append(self.data.iloc[i][2])
        
        return prices_f

I see many errors and I started from few time to use/call functions

Thank you

CodePudding user response：

Your orders.csv file

name          | number_of_orders | eurosxp
fried chips        100               2  
fried chicken       25               5
salad one           20               5
salad two           10               5

is not comma separated, so pd.read_csv("orders.csv", header=None) will not give expected DataFrame, you could get well-formed DataFrame following way

import pandas as pd
df = pd.read_csv('orders.csv', header=None, sep=' {2,}', names=["name","number_of_orders","eurosxp"], skiprows=1)
print(df.shape)
print(df)

gives output

(4, 3)
            name  number_of_orders  eurosxp
0    fried chips               100        2
1  fried chicken                25        5
2      salad one                20        5
3      salad two                10        5

Explanation: I ignore 1st line of file and provide names of columns directly, I set separator to regular expressions meaning 2 or more spaces. EDIT: code ameloriated as suggested in comment

CodePudding user response：

You can also read the file as fixed width formatted if the widths are consistent:

pd.read_fwf("orders.csv", colspecs=[(0,14),(16, 33),(35,42)])

Output:

            name  number_of_orders  eurosxp
0    fried chips               100        2
1  fried chicken                25        5
2      salad one                20        5
3      salad two                10        5