pandas convert to tuple & float to float64

[metalray]

Dear Pandas Experts,
I got two question on my Introduction to Python homework.

The jupiter auto-grader expects in case 1 a float64 and in case 2 a tuple, not a list.

case 1

    newfour_2['GDPDiff']=np.subtract(newfour['2015'],newfour['2006'])

    return newfour_2.iloc[0]

case 2

    purchase_1 = pd.Series({'Country': 'Brazil',
                        '% Renewable': '69.648030000000006'})
    df = pd.DataFrame([purchase_1])
    sixlist=df.to_records().tolist() 

When I used google to search for how to create tuples I only came accross tolist().
But the jupiter notebooks auto-grader expects data type "tuple"

Any help would make my weekend a great weekend! :)

[snippsat]

The jupiter auto-grader expects in case 1 a float64

Check types of dataframe with dtypes.
convert single value with astype
Eg:

In [27]: work_data.dtypes
Out[27]:
name         object
age           int64
weight        int64
seniority     int64
pay           int64
dtype: object

In [23]: work_data.age
Out[23]:
0    34
1    19
2    45
3    56
4    23
5    27
6    31
7    22
Name: age, dtype: int64

# To float64
In [24]:work_data.age.astype(np.float64)
Out[24]:
0    34.0
1    19.0
2    45.0
3    56.0
4    23.0
5    27.0
6    31.0
7    22.0
Name: age, dtype: float64

The jupiter auto-grader expects in case 1 a float64 and in case 2 a tuple, not a list.

Remember that you still can use Python and not only pandas.
So tuple() work.

In [26]: data = work_data.age.tolist()

print(data)
print(tuple(data))
[34, 19, 45, 56, 23, 27, 31, 22]
(34, 19, 45, 56, 23, 27, 31, 22)

[metalray]

Hi snippsat,
Thanks for your reply.

when I run:

    newfour_2['GDPDiff']=np.subtract(newfour['2015'],newfour['2006'])
    newfour_2['GDPDiff'].astype(np.float64)
    return type(newfour_2.iloc[0])

the output is:float not float64.


For case 2.
when I run:

    sixlist=df.to_records().tolist() 
    return type(sixlist) #newtwo["% Renewable"].max()
answer_six()

the output is:list and not tuple so tolist()does not seem to do the trick.

And to_tuple() or tuple() does not exist: AttributeError: recarray has no attribute to_tuple/tuple

---

Even tuple() has the type numpy.recarray

    purchase_1 = tuple({'Country': 'Brazil',
                        '% Renewable': '69.648030000000006'})

    df = pd.DataFrame([purchase_1])

                                       
    #only_gold = df.where(df['Gold']== 5)
    sixlist=df.to_records()
    return type(sixlist) #newtwo["% Renewable"].max()

[Ofnuts]

tuple() is a built-in function that creates a tuple from a list:

thetuple=tuple(thelist)

[zivoni]

1) astype(np.float64) does not change datatype in place, it returns modified dataframe/series. You need to assign it to a variable.

2) I am not entirely sure what are you trying to do, i guess that you want to get one row of dataframe as a tuple?

    purchase_1 = tuple({'Country': 'Brazil',      '% Renewable': '69.648030000000006'})
    df = pd.DataFrame([purchase_1])  

This looks rather strange, with tuple from dict you are keeping only 'Country' and '% Renewable', so your final dataframe contains only these two strings.

Perhaps you want something like this?

Output:
In [67]: purchase_1 = {'Country': ['Brazil'],'% Renewable': ['69.648030000000006']}

In [68]: df = pd.DataFrame(purchase_1)

In [69]: df
Out[69]: 
          % Renewable Country
0  69.648030000000006  Brazil

In [70]: sixlist = df.to_records()

In [71]: sixlist
Out[71]: 
rec.array([(0, '69.648030000000006', 'Brazil')], 
          dtype=[('index', '<i8'), ('% Renewable', 'O'), ('Country', 'O')])

In [72]: sixlist = tuple(sixlist[0])

In [73]: sixlist
Out[73]: (0, '69.648030000000006', 'Brazil')

In [74]: type(sixlist)
Out[74]: tuple

Or maybe this: (no index value there)

Output:
In [75]: sixlist = tuple(df.iloc[0])

In [76]: sixlist
Out[76]: ('69.648030000000006', 'Brazil')

In [77]: type(sixlist)
Out[77]: tuple

[snippsat]

the output is:float not float64.

You most store it in a variable.

four_64 = newfour_2['GDPDiff'].astype(np.float64)

As mention you convert with the build tuple() after you have used tolist().

    sixlist = df.to_records().tolist() 
    return tuple(sixlist) # Will return a tuple
answer_six()

[metalray]

Awesome. Thanks for you help! Both of you!