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Python | Pandas Series.ffill()

Last Updated : 13 Feb, 2019
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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.

Pandas Series.ffill() function is synonym for forward fill. This function is used t fill the missing values in the given series object using forward fill method.

Syntax: Series.ffill(axis=None, inplace=False, limit=None, downcast=None)

Parameter :
axis : {0 or ‘index’}
inplace : If True, fill in place.
limit : If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill
downcast : dict, default is None

Returns : filled : Series

Example #1: Use Series.ffill() function to fill out the missing values in the given series object.




# 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.ffill() function to fill out the missing values in the given series object.




# fill the missing values
result = sr.ffill()
  
# Print the result
print(result)


Output :

As we can see in the output, the Series.ffill() function has successfully filled out the missing values in the given series object.
 
Example #2 : Use Series.ffill() function to fill out the missing values in the given series object.




# 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.ffill() function to fill out the missing values in the given series object.




# fill the missing values
result = sr.ffill()
  
# Print the result
print(result)


Output :

As we can see in the output, the Series.ffill() function has successfully filled out the missing values in the given series object.



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