如何解压 Python 元组列表

Places = [('Ahmedabad', 'Gujarat'), ('Hyderabad', 'Telangana'), ('Silchar', 'Assam'), ('Agartala', 'Tripura'), ('Namchi', 'Sikkim')] # The input of tuples is given
City, States = zip(*Places) # The zip function of list comprehension separate the data into different cities and states
print(City)
print(States)

from itertools import zip_longest # Do not forget to import itertools or else error might occur
Places = [('Ahmedabad', 'Gujarat'), ('Hyderabad', 'Telangana'), ('Silchar', 'Assam'), ('Agartala', 'Tripura'), ('Namchi', 'Sikkim')] # The input of tuples is given
City, State = zip_longest(*Places) # We use zip_longest so that the tuples which are not same in length can also be unzipped
City = [City for City in City if City is not None] # The different lists formed might consist of `none` value for missing element
State = [State for State in State if State is not None] # The list comprehension to maintain the same length and remove the none values
print(City)
print(State)

Places = [('Ahmedabad', 'Gujarat'), ('Hyderabad', 'Telangana'), ('Silchar', 'Assam'), ('Agartala', 'Tripura'), ('Namchi', 'Sikkim')] # The input of tuples is given
Cities = []
States = []

for City, State in Places: # We check each value in the list and then extract the different city and state element
    Cities.append(City)
    States.append(State)
    
print(Cities)
print(States)

import numpy as np # DO not forget to import numpy or else error might occur

Places = [('Gujarat', 31), ('Punjab', 237), ('Assam', 33), ('Tripura', 14), ('Sikkim', 6)] # The input of tuples is given
States, number_of_cities = np.array(Places).T.tolist() # We will use array operation to unzip the data
#np.array will help us convert the tuple into array and .T will help us to unzip and separate the data and tolist will convert into list
print(States)
print(number_of_cities)  

import pandas as pd # Do not forget to import pandas data frame or else error might occur

Places = [('Ahmedabad', 'Gujarat'), ('Hyderabad', 'Telangana'), ('Silchar', 'Assam'), ('Agartala', 'Tripura'), ('Namchi', 'Sikkim')] # The input of tuples is given
df = pd.DataFrame(Places, columns=['City', 'State']) # The list is first converted into pandas data frame with the help of pd.dataframe which help us to have access to elements separately
Cities = df['City'].tolist() #tolist will help to convert these dataframes back into standard lists
States = df['State'].tolist()
print(Cities)
print(States)

from operator import itemgetter  # Do not forget to import operator module or else error might occur

Places = [('Ahmedabad', 21), ('Hyderabad', 32), ('Silchar', 43), ('Agartala', 24), ('Namchi', 21)] # The input of tuples is given
Cities, people = map(list, zip(*map(itemgetter(0), Places))), map(itemgetter(1), Places) 
people = list(people)# itemgetter 0 & 1 will used to get the city and state element respectively and the map function helps them to find the elements in the places list and with the help of zip we will unzip the list

print(people)