How to convert column with dtype as object to string in Pandas Dataframe

Question

When I read a csv file to pandas dataframe  each column is cast to its own datatypes  I have a column that was converted to an object  I want to perform string operations for this column such as splitting the values and creating a list  But no such operation is possible because its dtype is object  Can anyone please let me know the way to convert all the items of a column to strings instead of objects   I tried several ways but nothing worked  I used astype  str    to string etc   a lambda x  str x  split      df  column   apply a    or  df  column   astype str

User · Answer

since strings data types have variable length, it is by default stored as object dtype. If you want to store them as string type, you can do something like this.

df['column'] = df['column'].astype('|S80') #where the max length is set at 80 bytes,

or alternatively

df['column'] = df['column'].astype('|S') # which will by default set the length to the max len it encounters

User · Answer

Did you try assigning it back to the column   df  column     df  column   astype  str      Referring to this question  the pandas dataframe stores the pointers to the strings and hence it is of type   object   As per the docs  You could try      df  column new     df  column   str split

User · Answer

Not answering the question directly  but it might help someone else   I have a column called Volume  having both -  invalid NaN  and numbers formatted with    df  Volume     df  Volume   astype  str   df  Volume     df  Volume   str replace          df  Volume     pd to numeric df  Volume    errors  coerce     Casting to string is required for it to apply to str replace  pandas Series str replace pandas to numeric

User · Answer

You could try using df  column   str  and then use any string function  Pandas documentation includes those like split

[python] How to convert column with dtype as object to string in Pandas Dataframe

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