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,
})
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 - In this article, we’ll explore ... them in your code. ... The simplest way to remove decimal points in pandas is by using the round() function. This function rounds a given number to a specified number of decimal plac...
python - Deleting decimals from a pandas dataframe - Stack Overflow
I have numbers such as 24.00 2.00 3.00 I want to have 24 2 3 I have used .astype(int), round() but I keep getting the former. How do I get this to work? More on stackoverflow.com
how to remove decimal points from values ?
https://www.google.com/search?q=python+remove+decimal More on reddit.com
4
0
December 5, 2023pandas - Python - Remove decimal and zero from string - Stack Overflow
I'm reading several spreadsheets into a data frame and there is an ID field that is a string in some spreadsheets and a number in others. I've converted it into a string, which is the data type I n... More on stackoverflow.com
python - Remove Decimal in pandas - Stack Overflow
In my dataset at column 'Time Period', I have series which contains 2018 and 2019. When I plot it with 'countries and areas' column, I am getting results like this. enter image description here enter More on stackoverflow.com
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
GeeksforGeeks
geeksforgeeks.org › how-to-remove-all-decimals-from-a-number-using-python
How to remove all decimals from a number using Python? - GeeksforGeeks
March 27, 2025 - Removing elements from a list can ... :Make the fraction an incorrect fraction if it's a mixed number.Subtract the denominator from the numerator.Round the decimal off if the division does not come out evenly.A number System ...
Homedutech
homedutech.com › faq › python › how-to-remove-decimal-points-in-pandas.html
How to remove decimal points in pandas
In pandas, you can remove decimal points from a column containing float values by using the .astype() function to convert the column to an integer type. This effectively removes the decimal points and truncates the decimal values.
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
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.
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 - It strictly truncates (cuts off) the decimal part toward zero. For example, 5.9 becomes 5. If you need it to become 6, you must call .round().astype(int). 3. What is the difference between Int64 and int64 in Pandas? Int64 (capital I) is a nullable Pandas object that supports missing values, whereas int64 (lowercase i) is a raw NumPy data type that cannot store NaN and will crash if missing data is present. 4. How do I remove decimals but keep the column as a string/object?
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 - For bulk operations, use NumPy/Pandas instead of loops · Always round late, not early, to minimize accumulated error · Always initialize Decimal from strings, never floats · Test rounding behavior explicitly in financial systems before deploying · Removing decimals correctly is more subtle than it appears.
YouTube
youtube.com › hey delphi
PYTHON : How to remove decimal points in pandas - YouTube
PYTHON : How to remove decimal points in pandasTo Access My Live Chat Page, On Google, Search for "hows tech developer connect"As promised, I'm going to shar...
Published April 13, 2023 Views 88
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 ?
Top answer 1 of 2
45
Use astype with replace:
df = pd.DataFrame({'ID':[805096730.0,805096730.0]})
df['ID'] = df['ID'].astype(str).replace('\.0', '', regex=True)
print (df)
ID
0 805096730
1 805096730
Or add parameter dtype:
df = pd.read_excel(file, dtype={'ID':str})
2 of 2
2
Check type of your numbers before converting them to strings. It seems that they are floats, rather than integers. If this is the case, convert your numbers to integers:
df = pd.DataFrame([123.0, 456.0])
df = df.apply(int, axis=1)
0 123
1 456
Then, convert it into strings:
df = df.apply(str)
print(df.iloc[1])
'456'
Stack Overflow
stackoverflow.com › questions › 67722165 › remove-decimal-in-pandas
python - Remove Decimal in pandas - Stack Overflow
You probably have a nan value in this column. You must remove them first, then convert to int: df["Time Period"].astype(int).
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')
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.
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.
Reddit
reddit.com › r/learnpython › how to terminate or remove the .0 point from an int.
r/learnpython on Reddit: How to terminate or remove the .0 point from an int.
December 9, 2022 -
Hello everyone,
I am still new to python and learning.
So I practiced some exercises and made an app that calculates the percentage from the number the user enters.
My question use, how can I terminate the .0 part if the user enters an Int and keep the decimal part if they enter a float?
so for example, 5% of 100 is 5 ( Int)
and 5.1% of 100 is 5.1 (float)
Top answer 1 of 4
3
Try using the g flag when you print it. x = 5.0 y = 5.1 print("regular print:", x, y) print("with g flag:", f"{x:g} {y:g}")
2 of 4
3
x = input() if int(x) == x: y = int(x) else: y = x print(y) If the user inputs 5.1, int(5.1) will truncate it to 5, so 5 != 5.1, and y will be just 5.1. If the user inputs 5.0, int(5.0) is 5, and 5 == 5.0, so y will be just 5
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
7
Try the below:
m=(df.dtypes=='float')
df.loc[:,m]=df.loc[:,m].astype(int)
print(df)
query qstart qend name number strand
0 A 2 1064 None 0 +
1 B 2 1076 None 0 +
2 C 2 1064 None 0 +
3 D 0 741 None 0 +
2 of 2
0
df.qend = df.qend.apply(int) # round instead of int is you prefer to round
print (df)
query qstart qend name number strand
0 A 2.0 1064 None 0 +
1 B 2.0 1076 None 0 +
2 C 2.0 1064 None 0 +
3 D 0.0 741 None 0 +