Python | Pandas DataFrame.truediv

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.

Pandas DataFrame.truediv() function perform the floating division of dataframe and other, element-wise. It is equivalent to dataframe / other, but with support to substitute a fill_value for missing data in one of the inputs.

Syntax: DataFrame.truediv(other, axis=’columns’, level=None, fill_value=None)

Parameter :
other : scalar, sequence, Series, or DataFrame
axis : {0 or ‘index’, 1 or ‘columns’}
level : Broadcast across a level, matching Index values on the passed MultiIndex level.
fill_value : Fill existing missing (NaN) values, and any new element needed for successful DataFrame alignment.

Returns : Result of the arithmetic operation.

Example #1 : Use DataFrame.truediv() function to perform division of the given dataframe with a scalar element-wise. Also fill 100 at the place of all the missing values.

# importing pandas as pd
import pandas as pd

# Creating the DataFrame
df = pd.DataFrame({"A":[12, 4, 5, None, 1],
                   "B":[7, 2, 54, 3, None],
                   "C":[20, 16, 11, 3, 8],
                   "D":[14, 3, None, 2, 6]})

# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']

# Set the index
df.index = index_

# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.truediv() function to perform division of the given dataframe by 2, element-wise. We are going to fill 100 at the place of all the missing values in this dataframe.

# divide by 2 element-wise
# fill 100 at the place of missing values
result = df.truediv(other = 2, fill_value = 100)

# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.truediv() function has successfully performed the division of the given dataframe by a scalar.

Example #2 : Use DataFrame.truediv() function to perform the division of the given dataframe using a list.

# importing pandas as pd
import pandas as pd

# Creating the DataFrame
df = pd.DataFrame({"A":[12, 4, 5, None, 1],
                   "B":[7, 2, 54, 3, None],
                   "C":[20, 16, 11, 3, 8],
                   "D":[14, 3, None, 2, 6]})

# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']

# Set the index
df.index = index_

# Print the DataFrame
print(df)

Output :

Now we will use DataFrame.truediv() function to perform division of the given dataframe using a list.

# divide using a list
# across the column axis
result = df.truediv(other = [10, 4, 8, 3], axis = 1)

# Print the result
print(result)

Output :

As we can see in the output, the DataFrame.truediv() function has successfully performed the division of the given dataframe by a list.