The Pandas dataframe.round() function is used to round a DataFrame to a variable number of decimal places. This function provides flexibility to round different columns in different places.

Syntax: DataFrame.round (decimals = 0, * args, ** kwargs)
Parameters:
decimals: Number of decimal places to round each column to. If an int is given, round each column to the same number of places. Otherwise dict and Series round to variable numbers of places. Column names should be in the keys if decimals is a dict-like, or in the index if decimals is a Series. Any columns not included in decimals will be left as is. Elements of decimals which are not columns of the input will be ignored.

Returns: DataFrame object

Example # 1: Use the round () function to round all columns in the data frame to 3 decimal places

Note. We need to fill our data frame with decimal places values. Let`s use a random random function to achieve the goal.

# import pandas as pd import pandas as pd   # import numpy as np import numpy as np   # setting the seed to recreate the dataframe np.random.seed ( 25 )   # Create a 5 * 4 data frame df = pd.DataFrame (np.random.random ([ 5 , 4 ]), columns = [ " A " , "B" , "C" , "D" ])   # Print the data frame df

Let`s use the dataframe.round () function to round all decimal values ​​in a frame to 3 decimal places.

df. round ( 3 )

Output:

Example # 2: Use the round () function to round all columns in the data frame to different places.

# import pandas as pd import pandas as pd   # import numpy as np import numpy as np   # setting the seed to recreate the dataframe np.random.seed ( 25 )   # Create data frame 5 * 4 df = pd.DataFrame (np .random.random ([ 5 , 4 ]), columns = [ " A " , " B " , "C" , "D" ])   # Print the data frame df

Let`s round each column and in different places

# round the columns this way # "A" up to 1 character after the comma # & quot; B & quot; accurate to 2 decimal places # & quot; С & quot; up to 3 decimal places # & quot; D & quot; up to 4 decimal places   df. round ({ "A" : 1 , "B" : 2 , "C" : 3 , "D" : 4 })

Output: