Python | Pandas DataFrame.transform

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.transform() function call func on self producing a DataFrame with transformed values and that has the same axis length as self.

Syntax: DataFrame.transform(func, axis=0, *args, **kwargs) Parameter : func : Function to use for transforming the data axis : {0 or ‘index’, 1 or ‘columns’}, default 0 *args : Positional arguments to pass to func. **kwargs : Keyword arguments to pass to func. Returns : DataFrame

Example #1 : Use DataFrame.transform() function to add 10 to each element in the dataframe. Python3

# 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.transform() function to add 10 to each element of the dataframe. Python3 1==

# add 10 to each element of the dataframe
result = df.transform(func = lambda x : x + 10)

# Print the result
print(result)

Output : As we can see in the output, the DataFrame.transform() function has successfully added 10 to each element of the given Dataframe.   Example #2 : Use DataFrame.transform() function to find the square root and the result of euler's number raised to each element of the dataframe. Python3

# 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.transform() function to find the square root and the result of euler's number raised to each element of the dataframe. Python3 1==

# pass a list of functions
result = df.transform(func = ['sqrt', 'exp'])

# Print the result
print(result)

Output : As we can see in the output, the DataFrame.transform() function has successfully performed the desired operation on the given dataframe.