Python | Pandas Series.drop()

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.drop() function return Series with specified index labels removed. It remove elements of a Series based on specifying the index labels.

Syntax: Series.drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') Parameter : labels : Index labels to drop. axis : Redundant for application on Series. index, columns : Redundant for application on Series, but index can be used instead of labels. level : For MultiIndex, level for which the labels will be removed. inplace : If True, do operation inplace and return None. errors : If ‘ignore’, suppress error and only existing labels are dropped. Returns : dropped : pandas.Series

Example #1: Use Series.drop() function to drop the values corresponding to the passed index labels in the given series object. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([80, 25, 3, 25, 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.drop() function to drop the values corresponding to the passed index labels in the given series object. Python3 1==

# drop the passed labels
result = sr.drop(labels = ['Sprite', 'Dew']) 

# Print the result
print(result)

Output : As we can see in the output, the Series.drop() function has successfully dropped the entries corresponding to the passed index labels.   Example #2 : Use Series.drop() function to drop the values corresponding to the passed index labels in the given series object. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([11, 11, 8, 18, 65, 18, 32, 10, 5, 32, 32])

# 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.drop() function to drop the values corresponding to the passed index labels in the given series object. Python3 1==

# drop the passed labels
result = sr.drop(labels = [pd.Timestamp('2010-12-31'),
                           pd.Timestamp('2011-04-30'), pd.Timestamp('2011-08-31')])

# Print the result
print(result)

Output : As we can see in the output, the Series.drop() function has successfully dropped the entries corresponding to the passed index labels.