I have a list called testList that contains a couple of timeseries that I am trying to convert its values from string to float.  The list is very long and part of it looks like:
testList [date
2015-02-09    5083.628505
2015-02-10    5588.064283
2015-02-12    5716.556323
2015-02-13    5687.040303
2015-02-16    5746.323570
                 ...
2016-02-29    7460.167850
2016-03-01    7520.165439
2016-03-02    7710.032381
2016-03-03    7730.081164
2016-03-04    8040.123012
Name: adjusted_snap, Length: 263, dtype: float64, date
2015-02-09    5107.125395
2015-02-10    5579.177926
2015-02-12    5721.690076
2015-02-13    5690.344229
2015-02-16    5779.747352
                 ...
2016-02-29    7454.380019
2016-03-01    7505.175458
2016-03-02    7729.729257
2016-03-03    7764.529861
2016-03-04    8060.349081
Name: adjusted_vwap, Length: 263, dtype: float64]
For information the type is <class 'list'>.
All the values are numbers (except where there is a missing value and its null).
I am trying to convert the list values from string to float using:
for item in testList:
            for key, value in item.iteritems():
                try:
                    item[key] = float(value)
                except ValueError:
                    continue
However I get a SettingWithCopyWarning.  
     SettingWithCopyWarning:
    A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  item[key] = float(value)
I am very confused as I am using a list but the warning mentions a dataframe. I have had a good look for solution and there is a lot of information but I can't find a fix to my copy warning problem.
 
    