Python | Pandas Series.ravel()
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.ravel() function returns the flattened underlying data as an ndarray.
Syntax: Series.ravel(order=’C’)
Parameter : order
Returns : ndarray
Example #1: Use Series.ravel() function to return the elements of the given Series object as an ndarray.
# importing pandas as pdimport pandas as pd # Creating the Seriessr = pd.Series([10, 25, 3, 11, 24, 6]) # Create the Indexindex_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the indexsr.index = index_ # Print the seriesprint(sr) |
Output :
Now we will use Series.ravel() function to return the underlying data of the given Series object as an ndarray.
# return an ndarrayresult = sr.ravel() # Print the resultprint(result) |
Output :
As we can see in the output, the Series.ravel() function has returned the an ndarray containing the data of the given series object.
Example #2: Use Series.ravel() function to return the elements of the given Series object as an ndarray.
# importing pandas as pdimport pandas as pd # Creating the Seriessr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio']) # Create the Indexindex_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'] # set the indexsr.index = index_ # Print the seriesprint(sr) |
Output :
Now we will use Series.ravel() function to return the underlying data of the given Series object as an ndarray.
# return an ndarrayresult = sr.ravel() # Print the resultprint(result) |
Output :
As we can see in the output, the Series.ravel() function has returned the an ndarray containing the data of the given series object.
Last Updated on October 24, 2021 by admin