How to add data from a series to a list in python-CodePudding

I'm having a series in a DataFrame where it is in object format but I want to loop each row and add values to a single list without a list of lists.

df['Fruits']
    
 index  Fruits
  0    ['banana']
  1    ['apple','grapes(imported,us)','mango']
  2    ['apple']
  3    ['mango','grapes(imported,US)','pears(imported,NZ)']
  4    ['mango']
  dtype: object

fruits_list = []

for i in df['Fruits']:
    fruits_list.append(i)

 Expected Output:
    fruits_list = ['banana', 'apple','grapes(imported,us)','mango', 'apple', 'mango','grapes(imported,US)','pears(imported,NZ)', 'mango']

CodePudding user response：

Why was your data in this format to begin with? What you had were strings, not lists of strings:

In [2]: for item in df["Fruits"]:
   ...:     print(type(item), item)
   ...:
<class 'str'> ['banana']
<class 'str'> ['apple','grapes(imported,us)','mango']
<class 'str'> ['apple']
<class 'str'> ['mango','grapes(imported,US)','pears(imported,NZ)']
<class 'str'> ['mango']

So you can use ast.literal_eval() to convert these strings to lists of strings, and then use list.extend() to obtain a flattened list of all the items:

In [3]: import ast

In [4]: fruits = []
   ...: for item in df["Fruits"]:
   ...:     fruits.extend(ast.literal_eval(item))
   ...:

In [5]: fruits
Out[5]:
['banana',
 'apple',
 'grapes(imported,us)',
 'mango',
 'apple',
 'mango',
 'grapes(imported,US)',
 'pears(imported,NZ)',
 'mango']

CodePudding user response：

Using and summarizing the following answer: How to make a flat list of lists.

Setup:

df = pd.DataFrame({"Fruits": [['banana'], ['apple','grapes(imported,us)','mango'], ['apple'], ['mango','grapes(imported,US)','pears(imported,NZ)'], ['mango']]})

I suggest two options:

Option 1 for small data sets ~10 elements:

sum(df['Fruits'], [])

Option 2 for larger data sets > 10 elements:

from itertools import chain
chain.from_iterable(df['Fruits'])

Output:

 ['banana',
 'apple',
 'grapes(imported,us)',
 'mango',
 'apple',
 'mango',
 'grapes(imported,US)',
 'pears(imported,NZ)',
 'mango']