You have a few options...
1) convert everything to integers.
df.astype(int)
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
2) Use round:
>>> df.round()
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
but not always great...
>>> (df - .2).round()
<=35 >35
Cut-off
Calcium -0 1
Copper 1 -0
Helium -0 8
Hydrogen -0 1
3) Change your display precision option in Pandas.
pd.set_option('precision', 0)
>>> df
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
Top answer 1 of 3
64
You have a few options...
1) convert everything to integers.
df.astype(int)
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
2) Use round:
>>> df.round()
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
but not always great...
>>> (df - .2).round()
<=35 >35
Cut-off
Calcium -0 1
Copper 1 -0
Helium -0 8
Hydrogen -0 1
3) Change your display precision option in Pandas.
pd.set_option('precision', 0)
>>> df
<=35 >35
Cut-off
Calcium 0 1
Copper 1 0
Helium 0 8
Hydrogen 0 1
2 of 3
22
Since pandas 0.17.1 you can set the displayed numerical precision by modifying the style of the particular data frame rather than setting the global option:
import pandas as pd
import numpy as np
np.random.seed(24)
df = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
df
df.style.set_precision(2)
It is also possible to apply column specific styles
df.style.format({
'A': '{:,.1f}'.format,
'B': '{:,.3f}'.format,
})
Homedutech
homedutech.com › faq › python › how-to-remove-decimal-points-in-pandas.html
How to remove decimal points in pandas
import pandas as pd # Sample DataFrame ... Series" Description: This code snippet illustrates how to remove decimal places from a Pandas Series using the astype() function to convert the data type to integer....
Top answer 1 of 2
1
You need to re-assign dataframe
(which is, what I suppose your error is):
>>> import pandas as pd
>>> df = pd.DataFrame(data={"col": [24.00, 2.00, 3.00]})
>>> df.dtypes
col float64
dtype: object
>>> df
col
0 24.0
1 2.0
2 3.0
>>> df=df.astype(int)
>>> df
col
0 24
1 2
2 3
>>> df.dtypes
col int32
dtype: object
2 of 2
1
You can solve this by setting the pandas option, precision to 0.
import pandas as pd
df = pd.DataFrame(data={"col": [24.00, 2.00, 3.00]})
print(df)
col
0 24.0
1 2.0
2 3.0
pd.set_option('precision',0)
print(df)
col
0 24
1 2
2 3
Reddit
reddit.com › r/learnpython › how to remove decimals in float?
r/learnpython on Reddit: How to remove decimals in float?
April 15, 2023 -
I need to remove decimals from float to get 6 characters after the dot WITHOUT rounding For example I have 0.00655379 and I need to get 0.006553
Top answer 1 of 10
14
If this is just for printing... f'{my_float:.6f}. If you actually need that level of precision, you're likely to run into rounding issues, but you could try something like this: int(my_float * (10**6)) / (10**6)
2 of 10
7
This might be a case that you should consider using the decimal library vs float, floats are notorious bad for precision, just try print(0.1+0.2) Using Decimal: In []: from decimal import Decimal, ROUND_DOWN d = Decimal.from_float(0.00655379) # ideally you just start with a decimal print(d) Out[]: Decimal('0.0065537900000000003097877510072066797874867916107177734375') Wow, that looks worse - but this is one of the issues with floats. But you can easily convert to what ever decimal places you want with whatever rounding semantics you want, e.g.: In []: precision = Decimal('0.000001') d.quantize(precision, rounding=ROUND_DOWN) Out[]: Decimal('0.006553')
Reddit
reddit.com › r/learnpython › how to remove decimal points from values ?
r/learnpython on Reddit: how to remove decimal points from values ?
December 5, 2023 -
my boyfriend has moved his excel table to python but it has added .0 to his values (eg 160 becomes 160.0) is there anyway to fix this and remove decimals ?
CodeProject
codeproject.com › Questions › 5291723 › How-do-I-remove-decimals-from-a-pandas-data-frame
How do I remove decimals from a pandas data frame index
September 1, 2021 - Do not try and find the page. That’s impossible. Instead only try to realise the truth - For those who code; Updated: 1 Jul 2007
GitHub
github.com › beepscore › pandas_decimal
GitHub - beepscore/pandas_decimal: Using Pandas with Python Decimal for accurate currency arithmetic · GitHub
def int_by_removing_decimal(self, a_float): """ removes decimal separator. removing decimal from a_float with n decimal places multiplies by 10 ** n :a_float: a Python float e.g. 1.23 :return: an integer e.g.
Author beepscore
Javatpoint
javatpoint.com › how-to-remove-decimal-in-python
How to Remove Decimal in Python - Javatpoint
How to Remove Decimal in Python with python, tutorial, tkinter, button, overview, entry, checkbutton, canvas, frame, environment set-up, first python program, operators, etc.
Java2Blog
java2blog.com › home › python › how to remove decimals in python
How to Remove Decimals in Python - Java2Blog
October 2, 2023 - In the above example, we convert ... that can calculate complex mathematical calculations. We can remove decimal places in Python using the truncate() function from the math library....
Saturn Cloud
saturncloud.io › blog › how-to-remove-decimal-points-in-pandas-a-guide-for-data-scientists
How to Remove Decimal Points in Pandas A Guide for Data Scientists | Saturn Cloud Blog
December 23, 2023 - This function can be a built-in function, a user-defined function, or a lambda function. To remove decimal points using the apply() function, you can create a lambda function that rounds each value to 0 decimal places.
Top answer 1 of 3
4
Use a function and apply to whole column:
In [94]:
df = pd.DataFrame({'Movies':['Save the last dance', '2012.0']})
df
Out[94]:
Movies
0 Save the last dance
1 2012.0
[2 rows x 1 columns]
In [95]:
def trim_fraction(text):
if '.0' in text:
return text[:text.rfind('.0')]
return text
df.Movies = df.Movies.apply(trim_fraction)
In [96]:
df
Out[96]:
Movies
0 Save the last dance
1 2012
[2 rows x 1 columns]
2 of 3
0
Here is hint for you ,
In case of Valid number ,
a="2012.0"
try:
a=float(a)
a=int(a)
print a
except:
print a
Output:
2012
In case of String like "Dance with Me"
a="Dance with Me"
try:
a=float(a)
a=int(a)
print a
except:
print a
Output:
Dance with Me
Top answer 1 of 2
39
The DataFrame round method should work...
import numpy as np
import pandas as pd
some_numbers = np.random.ranf(5)
df = pd.DataFrame({'random_numbers':some_numbers})
rounded_df = df.round(decimals=2)
2 of 2
1
import numpy as np
import pandas as pd
#fileName
f=001.csv
#Load File to Df
Urbs_Data=pd.read_csv(f,header=None)
#Round of all the numeric values to the specified decimal value
Urbs_Data= Urbs_Data.round(decimals=3)
This rounding off will be applied on all the Numeric columns
Top answer 1 of 3
4
You can try using as df['col'] = (df['col']*100).astype(int)
as below:
df = pd.DataFrame({'col': [1.10, 2.20, 3.30, 4.40]})
df['col'] = (df['col']*100).astype(int)
print(df)
Output:
col
0 110
1 220
2 330
3 440
2 of 3
1
If - as your comment suggests - the data just all needs to be multiplied by 100...
df['columnName'] = df['columnName'].apply(lambda x: x*100)
CopyProgramming
copyprogramming.com › howto › python-remove-demical-on-a-certain-column-pandas
How to Remove Decimals from a Pandas Column - Remove decimals from a pandas column
December 20, 2025 - This guide covers the modern, safe, and performance-optimized methods to remove decimals from your DataFrame columns, updated for the latest Python ecosystem.
Top answer 1 of 9
73
You can call int() on the end result:
>>> int(2.0)
2
2 of 9
36
When a number as a decimal it is usually a float in Python.
If you want to remove the decimal and keep it an integer (int). You can call the int() method on it like so...
>>> int(2.0)
2
However, int rounds down so...
>>> int(2.9)
2
If you want to round to the nearest integer you can use round:
>>> round(2.9)
3.0
>>> round(2.4)
2.0
And then call int() on that:
>>> int(round(2.9))
3
>>> int(round(2.4))
2
YouTube
youtube.com › watch
How to Remove Decimal Places and Spaces from Data in Pandas DataFrame - YouTube
Learn how to effectively remove decimal places and unnecessary spaces from numeric data in a Pandas DataFrame. Follow our step-by-step guide to clean your da...
Published October 2, 2025 Views 0
Top answer 1 of 3
5
You can convert the type with .astype
In [312]: df.columns = df.columns.astype(int)
In [313]: df
Out[313]:
2006 2007 2008 2009
0 foo foo bar bar
1 foo foo bar bar
Or use .map and convert to string type.
In [338]: df.columns.map('{:g}'.format)
Out[338]: Index(['2006', '2007', '2008', '2009'], dtype='object')
In [319]: df.columns.map(int)
Out[319]: Int64Index([2006, 2007, 2008, 2009], dtype='int64')
2 of 3
1
You can convert to float before converting to int and then str:
df.columns = df.columns.values.astype(float).astype(int).astype(str)
print(df.columns)
Index(['2006', '2007', '2008', '2009'], dtype='object')
Seems long-winded, but at least we are working with the underlying NumPy array.
CopyProgramming
copyprogramming.com › howto › python-how-to-remove-decimal-number-using-python
How to Remove Decimal Numbers in Python: Complete Guide 2026 - Remove decimal numbers in python complete guide
December 30, 2025 - Python's built-in round() function removes or reduces decimal places while rounding to the nearest value.
Beepscore
beepscore.com › website › 2018 › 10 › 12 › using-pandas-with-python-decimal.html
Using Pandas with Python Decimal for accurate currency arithmetic
def int_by_removing_decimal(self, a_float): """ removes decimal separator. removing decimal from a_float with n decimal places multiplies by 10 ** n :a_float: a Python float e.g. 1.23 :return: an integer e.g.