Converting a list of objects to a pandas dataframe

Question

How do I convert a list of objects to a pandas dataframe?

class Person(object):     def __init__(self):         self.name = ""         self.year = 0         self.salary = 0 

For example below works but I want to have a list of person classes instead

import pandas as pd import numpy as np  data = {'name': ['Alice', 'Bob', 'Charles', 'David', 'Eric'],     'year': [2017, 2017, 2017, 2017, 2017],     'salary': [40000, 24000, 31000, 20000, 30000]}  df = pd.DataFrame(data, index = ['Acme', 'Acme', 'Bilbao', 'Bilbao', 'Bilbao'])  print(df) 

Answer 1

Sort of a combination of ayhan's suggestion and what you seem to want -- you can add a method to your Person class that transforms it into something that fits the Pandas DataFrame constructor.

class Person(object):     def __init__(self, name='', year=0, salary=0):         self.name = name         self.year = year         self.salary = salary      def as_dict(self):         return {'name': self.name, 'year': self.year, 'salary': self.salary}  person1 = Person('john', 2017, 100) person2 = Person('smith', 2016, 200) person3 = Person('roger', 2016, 500)  person_list = [person1, person2, person3]  df = pd.DataFrame([x.as_dict() for x in person_list])  print(df)      name    salary  year 0   john    100     2017 1   smith   200     2016 2   roger   500     2016 

Answer 2

First of all, you should modify your __init__(), since your version just sets every attribute of any Person object to default values and does not allow for the user setting them.

You can then use the zip() function to create triples of the values in your data dictionary and then use those to create Person instances

import pandas as pd  class Person:     def __init__(self, name='', year=0, salary=0):          self.name = name          self.year = year          self.salary = salary  data = {'name': ['Alice', 'Bob', 'Charles', 'David', 'Eric'],         'year': [2017, 2017, 2017, 2017, 2017],         'salary': [40000, 24000, 31000, 20000, 30000]}  foo = [Person(name, year, salary) for name, year, salary in zip(data['name'], data['year'], data['salary'])] df = pd.DataFrame(foo, index=['Acme']*2 + ['Bilbao']*3, columns=['Person'])  first_person = df['Person'].iloc[0] print(first_person.name, first_person.year, first_person.salary) 

Output:

Alice 2017 40000