Pandas DataFrame stored list as string: How to convert back to list?
Question: I have an _n_ -by-_m_ Pandas DataFrame `df` defined as follows. (I know this
is not the best way to do it. It makes sense for what I'm trying to do in my
actual code, but that would be TMI for this post so just take my word that
this approach works in my particular scenario.)

    
    
    >>> df = DataFrame(columns=['col1'])
    >>> df.append(Series([None]), ignore_index=True)
    >>> df
    Empty DataFrame
    Columns: [col1]
    Index: []
    

I stored lists in the cells of this DataFrame as follows.

    
    
    >>> df['column1'][0] = [1.23, 2.34]
    >>> df
         col1
    0  [1, 2]
    

For some reason, the DataFrame stored this list as a string instead of a list.

    
    
    >>> df['column1'][0]
    '[1.23, 2.34]'
    

I have 2 questions for you.

  1. **Why does the DataFrame store a list as a string and is there a way around this behavior?**
  2. **If not, then is there a Pythonic way to convert this string into a list?**

* * *

**Update**

The DataFrame I was using had been saved and loaded from a CSV format. _This
format, rather than the DataFrame itself, converted the list from a string to
a literal._


Answer: As you pointed out, this can commonly happen when saving and loading pandas
DataFrames as `.csv` files, which is a text format.

In your case this happened because list objects have a string representation,
allowing them to be stored as `.csv` files. Loading the `.csv` will then yield
that string representation.

If you want to store the actual objects, you should you use
`DataFrame.to_pickle()` (note: objects must be picklable!).

To answer your second question, you can convert it back with
[`ast.literal_eval`](https://docs.python.org/3.4/library/ast.html#ast.literal_eval):

    
    
    >>> from ast import literal_eval
    >>> literal_eval('[1.23, 2.34]')
    [1.23, 2.34]
    

