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.reset_index() function generate a new DataFrame or Series with the index reset. This comes handy when index is need to be used as a column.
Syntax: Series.reset_index(level=None, drop=False, name=None, inplace=False)
Parameter :
level : For a Series with a MultiIndex
drop : Just reset the index, without inserting it as a column in the new DataFrame.
name : The name to use for the column containing the original Series values.
inplace : Modify the Series in placeReturns : result : Series
Example #1: Use Series.reset_index() function to reset the index of the given Series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([10, 25, 3, 11, 24, 6]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.reset_index() function to reset the index of the given series object.
# reset the index result = sr.reset_index() # Print the result print(result) |
Output :
As we can see in the output, the Series.reset_index() function has reset the index of the given Series object to default. It has preserved the index and it has converted it to a column.
Example #2: Use Series.reset_index() function to reset the index of the given Series object. Do not keep the original index labels of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([10, 25, 3, 11, 24, 6]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.reset_index() function to reset the index of the given series object and also we will be dropping the original index labels.
# reset the index result = sr.reset_index(drop = True) # Print the result print(result) |
Output :
As we can see in the output, the Series.reset_index() function has reset the index of the given Series object to default. It has dropped the original index.
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