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.select() function return data corresponding to axis labels matching criteria. We pass the name of the function as an argument to this function which is applied on all the index labels. The index labels satisfying the criteria are selected.
Syntax: Series.select(crit, axis=0)
Parameter :
crit : called on each index (label). Should return True or False
axis : int valueReturns : selection : same type as caller
Example #1: Use Series.select() function to select the names of all those cities from the given Series object for which it’s index labels has even ending.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow']) # Create the Datetime Index index_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5', 'City 6'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.select() function to select the names of all those cities, whose index label ends with even integer value.
# Define a function to Select those cities whose index # label's last character is an even integer def city_even(city): # if last character is even if int(city[-1]) % 2 == 0: return True else: return False # Call the function and select the values selected_cities = sr.select(city_even, axis = 0) # Print the returned Series object print(selected_cities) |
Output :
As we can see in the output, the Series.select() function has successfully returned all those cities which satisfies the given criteria.
Example #2: Use Series.select() function to select the sales of the ‘Coca Cola’ and ‘Sprite’ from the given Series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([100, 25, 32, 118, 24, 65]) # 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.select() function to select the sales of the listed beverages from the given Series object.
# Function to select the sales of # Coca Cola and Sprite def show_sales(x): if x == 'Sprite' or x == 'Coca Cola': return True else: return False # Call the function and select the values selected_cities = sr.select(show_sales, axis = 0) # Print the returned Series object print(selected_cities) |
Output :
As we can see in the output, the Series.select() function has successfully returned the sales data of the desired beverages from the given Series object.
