Methods to Round Values in Pandas DataFrame - GeeksforGeeks

18 Aug, 2020
There are various ways to Round Values in Pandas DataFrame so let’s see each one by one:
Let’s create a Dataframe with ‘Data Entry’ Column only:
Code:
Python3
# import Dataframe class# from pandas libraryfrom pandas import DataFrame  # import numpy libraryimport numpy as np  # dictionaryMyvalue = {'DATA ENTRY': [4.834327, 5.334477,                          6.89, 7.6454, 8.9659]}   # create a Dataframedf = DataFrame(Myvalue,               columns = ['DATA ENTRY'])  # show the dataframedf
Output:
Method 1:  Using numpy.round().
Syntax: numpy.round_(arr, decimals = 0, out = None)
Return: An array with all array elements beingrounded off, having same type as input. 
This method can be  used to round value to specific decimal places for any particular column or can also be used to round the value of the entire data frame to the specific number of decimal places.
Example: Rounding off the value of  the “DATA ENTRY” column up to 2 decimal places.
Python3
# import Dataframe class# from pandas libraryfrom pandas import DataFrame  # import numpy libraryimport numpy as np  # dictionaryMyvalue = {'DATA ENTRY': [4.834327, 5.334477,                          6.89, 7.6454, 8.9659]}   # create a Dataframedf = DataFrame(Myvalue,               columns = ['DATA ENTRY'])  # Rounding value of 'DATA ENTRY' # column upto 2 decimal placesroundplaces = np.round(df['DATA ENTRY'],                       decimals = 2)   # show the rounded valueroundplaces
Output:
Method 2: Using Dataframe.apply() and numpy.ceil() together.
Syntax: Dataframe/Series.apply(func, convert_dtype=True, args=())
Return: Pandas Series after applied function/operation. 
Syntax: numpy.ceil(x[, out]) = ufunc ‘ceil’)
Return: An array with the ceil of each element of float data-type.
These methods are used to round values to ceiling value(smallest integer value greater than particular value). 
Example: Rounding off the value of a particular column. 
Python3
# import Dataframe from # pandas libraryfrom pandas import DataFrame  # import numpyimport numpy as np  # dictionaryMyvalue = {'DATA ENTRY': [4.834327, 5.334477,                          6.89, 7.6454, 8.9659]}   # create a Dataframedf = DataFrame(Myvalue,                columns = ['DATA ENTRY'])  # Here we are rounding the # value to its ceiling valuesroundUp = df['DATA ENTRY'].apply(np.ceil)   # show the rounded valueroundUp
Output: 
Method 3: Using Dataframe.apply() and numpy.floor() together.
Syntax: numpy.floor(x[, out]) = ufunc ‘floor’)
Return: An array with the floor of each element. 
These methods are used to round values to floor value(largest integer value smaller than particular value).
Example: Rounding off the value of the “DATA ENTRY” column to its corresponding Floor value.
Python3
# import Dataframe class # from pandas libraryfrom pandas import DataFrame  # import numpy libraryimport numpy as np  # dictionaryMyvalue = {'DATA ENTRY':[4.834327, 5.334477,                          6.89, 7.6454, 8.9659] } # create a Dataframedf = DataFrame(Myvalue,                columns = ['DATA ENTRY'])   # Rounding of Value to its Floor value rounddown = df['DATA ENTRY'].apply(np.floor)    # show the rounded valuerounddown
Output:
Python pandas-dataFrame
Python Pandas-exercise
Python-pandas
Python
Writing code in comment?
Please use ide.geeksforgeeks.org,
generate link and share the link here.
How to Install PIP on Windows ?
How to drop one or multiple columns in Pandas Dataframe
How To Convert Python Dictionary To JSON?
Check if element exists in list in Python
Selecting rows in pandas DataFrame based on conditions
Defaultdict in Python
Python | Get unique values from a list
Python | os.path.join() method
Create a directory in Python
Python | Split string into list of characters