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.

I'm asking for both ways: 0.00 and without decimals at all, but keeping float type. — Jerry
– Jerry, Commented Jan 26, 2019 at 12:33
if i'm not mistaken format is a string method. try to use round method with the number of digits after the dot. i.e round(age,2) or round(age,0) — Lior T
– Lior T, Commented Jan 26, 2019 at 12:38
@LiorT, thanks, I try df.Age.round(2), but there is again something wrong I do. — Jerry
– Jerry, Commented Jan 26, 2019 at 12:50

Karn Kumar · Accepted Answer · 2019-01-26 13:52:17Z

14

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

edited Jan 26, 2019 at 13:52

answered Jan 26, 2019 at 12:52

Karn Kumar

8,8343 gold badges32 silver badges61 bronze badges

Sign up to request clarification or add additional context in comments.

3 Comments

Jerry Over a year ago

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

Karn Kumar Over a year ago

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

Jerry Over a year ago

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

Gilad Wagner · Accepted Answer · 2020-07-25 18:29:55Z

1

I believe using df.round is the best way:

>>> df = pd.DataFrame({'Age': [24.0, 32.0]})
>>> df2 = df.round({'Ages': 2})
>>> print(df2.dtypes)
>>> df2
    Age
0   24.00
1   32.00

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.round.html

answered Jul 25, 2020 at 18:29

Gilad Wagner

511 silver badge2 bronze badges

Comments

Prarthan Ramesh · Accepted Answer · 2022-02-03 10:09:19Z

0

If you want to apply to specific column of the dataframe

df["col_name"] = df["col_name"].apply(lambda x: format(float(x),".2f"))

answered Feb 3, 2022 at 10:09

Prarthan Ramesh

3341 silver badge6 bronze badges

Collectives™ on Stack Overflow

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

3 Answers 3

For Floating Format without leading zeros

For Floating Format

Alternative way

3 Comments

Comments

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

For Floating Format without leading zeros

For Floating Format

Alternative way

3 Comments

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related