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 NoneReturns : 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.
