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 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.ravel() function to return the underlying data of the given Series object as an ndarray.

# return an ndarray
result = sr.ravel()

# Print the result
print(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 pd
import pandas as pd

# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])

# Create the Index
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.ravel() function to return the underlying data of the given Series object as an ndarray.

# return an ndarray
result = sr.ravel()

# Print the result
print(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.