Pandas data frame. Change float format. Keep type "float"

Question

I'm trying to change a format of pd data frame column without changing the type of data. Here is what I have: df = pd.DataFrame({'Age': [24.0, 32.0}])

I'd like to represent Age in 24 32 type or 24.00 32.00 and keep them as floats. Here is what I can do:

df['Age'].map('{:,.2f}'.format)

But this line changes the type of data to object. I was also trying to apply: `

df = df.style.format({'Age': '{:,.2f}'.format})`

but there is something wrong in it. Please help to figure out the right way.

Solution

Your dataFrame itself a type float.

Dataframe:

>>> df
    Age
0  24.0
1  32.0

Check DataFrame type:

>>> df.dtypes
Age    float64
dtype: object

check dtype for DataFrame column type:

>>> df.Age
0    24.0
1    32.0
Name: Age, dtype: float64

OR even check like:

>>> df['Age'].dtype.kind
'f'

The way you are using to round up double digit zeros that's correct but converting them again to float will get them remain in single zero as being float.

>>> df['Age'].map('{:,.2f}'.format)
0    24.00
1    32.00
Name: Age, dtype: object

---

As you are interested keeping either mimic like int values 24, 32 or 24.00 & 32.00, if you are only interested in the display of floats then you can do pd.set_option('display.float_format','{:.0f}'.format), which doesn't actually affect your data.

For Floating Format without leading zeros

>>> pd.set_option('display.float_format','{:.0f}'.format)
>>> df
   Age
0   24
1   32

>>> df.dtypes
Age    float64
dtype: object

For Floating Format

>>> pd.set_option('display.float_format','{:.2f}'.format)
>>> df
    Age
0 24.00
1 32.00
>>> df.dtypes
Age    float64
dtype: object

Alternative way

Set the display precision option:

>>> pd.set_option('precision', 0)
>>> df
   Age
0   24
1   32

>>> df.dtypes
Age    float64
dtype: object

Comments

[Jerry]

Thank you. So there is no way to keep these floats in .2f or .0f format as floats?

[Karn Kumar]

@Jerry, see the updated answer ,, hope that will help.

[Jerry]

thank you so much for your help! exactly what I was looking for.