How to read a column of csv as dtype list using pandas?

I have a csv file with 3 columns, wherein each row of Column 3 has list of values in it. As you can see from the following table structure

Col1,Col2,Col3
1,a1,"['Proj1', 'Proj2']"
2,a2,"['Proj3', 'Proj2']"
3,a3,"['Proj4', 'Proj1']"
4,a4,"['Proj3', 'Proj4']"
5,a5,"['Proj5', 'Proj2']"

Whenever I try to read this csv, Col3 is getting read as str object and not as list. I tried to alter the dtype of that column to list but got "Attribute Error" as below

df = pd.read_csv("inputfile.csv")
df.Col3.dtype = list

AttributeError                            Traceback (most recent call last)
<ipython-input-19-6f9ec76b1b30> in <module>()
----> 1 df.Col3.dtype = list

C:\Python27\lib\site-packages\pandas\core\generic.pyc in __setattr__(self,         name, value)
   1953                     object.__setattr__(self, name, value)
   1954             except (AttributeError, TypeError):
-> 1955                 object.__setattr__(self, name, value)
   1956 
   1957     #----------------------------------------------------------------------

AttributeError: can't set attribute

It would be really great if you can guide me how to go about it.

Solution 1:

You could use the ast lib:

from ast import literal_eval


df.Col3 = df.Col3.apply(literal_eval)
print(df.Col3[0][0])
Proj1

You can also do it when you create the dataframe from the csv, using converters:

df = pd.read_csv("in.csv",converters={"Col3": literal_eval})

If you are sure the format is he same for all strings, stripping and splitting will be a lot faster:

 df = pd.read_csv("in.csv",converters={"Col3": lambda x: x.strip("[]").split(", ")})

But you will end up with the strings wrapped in quotes

Solution 2:

Adding a replace to Cunninghams answer:

df = pd.read_csv("in.csv",converters={"Col3": lambda x: x.strip("[]").replace("'","").split(", ")})

See also pandas - convert string into list of strings