Pandas DataFrame fillna() Examples
Example 1: Use Series.fillna() function to fill out the missing values in the given series object. Use a dictionary to pass the values to be filled corresponding to the different index labels in the series object.
Python3
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , None , 'Rio' ]) # Create the Index sr.index = [ 'City 1' , 'City 2' , 'City 3' , 'City 4' , 'City 5' ] # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.fillna() function to fill out the missing values in the given series object.
Python3
# fill the values using dictionary result = sr.fillna(value = { 'City 4' : 'Lisbon' , 'City 1' : 'Dublin' }) # Print the result print (result) |
Output :
As we can see in the output, the Series.fillna() function has successfully filled out the missing values in the given series object.
Example 2: Use Series.fillna() function to fill out the missing values in the given series object using forward fill (ffill) method.
Python3
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 100 , None , None , 18 , 65 , None , 32 , 10 , 5 , 24 , None ]) # Create the Index index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' ) # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.fillna() function to fill out the missing values in the given series object. We will use forward fill method to fill out the missing values.
Python3
# fill the values using forward fill method result = sr.fillna(method = 'ffill' ) # Print the result print (result) |
Output :
As we can see in the output, the Series.fillna() function has successfully filled out the missing values in the given series object.
Pandas Series.fillna() Method
Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.